commit faebadb2b6ef37bf298a08ec702c5ab724408339 parent e721db5f1957f645ffd31bb9eb97ac3023761745 Author: Brian Graham <brian@buildingbetterteams.de> Date: Sat, 4 Apr 2026 11:42:37 +0200 Progress. Diffstat:
154 files changed, 36516 insertions(+), 56 deletions(-)
diff --git a/.claude/settings.local.json b/.claude/settings.local.json @@ -8,7 +8,8 @@ "Bash(yq --help)", "Bash(yq -r '.items[]')", "Bash(/root/loop-benchmarking/harness/lib/get-oauth-token.sh)", - "Bash(pkill -f \"astro preview\")" + "Bash(pkill -f \"astro preview\")", + "Bash(xargs jq:*)" ] } } diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/package-lock.json b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/package-lock.json @@ -0,0 +1,2301 @@ +{ + "name": "loop-bench-oldyixfl", + "version": "1.0.0", + "lockfileVersion": 3, + 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place */ +export function mergePiece(board: number[][], piece: Piece): void { + const id = typeToId(piece.type); + for (let r = 0; r < piece.matrix.length; r++) { + for (let c = 0; c < piece.matrix[r].length; c++) { + if (!piece.matrix[r][c]) continue; + const boardY = piece.pos.y + r; + const boardX = piece.pos.x + c; + if (boardY >= 0 && boardY < ROWS && boardX >= 0 && boardX < COLS) { + board[boardY][boardX] = id; + } + } + } +} + +/** Clear completed lines and return count of cleared lines */ +export function clearLines(board: number[][]): number { + let cleared = 0; + for (let r = ROWS - 1; r >= 0; r--) { + if (board[r].every(cell => cell !== 0)) { + board.splice(r, 1); + board.unshift(Array(COLS).fill(0)); + cleared++; + r++; // re-check the same row index after shifting down + } + } + return cleared; +} + +/** Calculate score delta for cleared lines at a given level */ +export function calcScore(linesCleared: number, level: number): number { + return (LINE_SCORES[linesCleared] ?? 0) * level; +} + +/** Calculate new level given total lines cleared */ +export function calcLevel(totalLines: number): number { + return Math.floor(totalLines / LINES_PER_LEVEL) + 1; +} + +/** Compute the ghost piece: drop it as far as possible */ +export function getGhostPiece(piece: Piece, board: number[][]): Piece { + let ghost = { ...piece, pos: { ...piece.pos } }; + while (true) { + const nextPos = { x: ghost.pos.x, y: ghost.pos.y + 1 }; + if (hasCollision(ghost.matrix, nextPos, board)) break; + ghost = { ...ghost, pos: nextPos }; + } + return ghost; +} + +/** Check if any cell is above row 0 (block-out = game over) */ +export function isTopOut(board: number[][]): boolean { + return board[0].some(cell => cell !== 0); +} diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/constants.ts b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/constants.ts @@ -0,0 +1,66 @@ +export const COLS = 10; +export const ROWS = 20; +export const BLOCK_SIZE = 30; +export const PREVIEW_BLOCK_SIZE = 24; + +// Tetromino colors (index 0 = empty) +export const COLORS: readonly string[] = [ + 'transparent', // 0: empty + '#00F0F0', // 1: I — cyan + '#F0F000', // 2: O — yellow + '#A000F0', // 3: T — purple + '#00F000', // 4: S — green + '#F00000', // 5: Z — red + '#0000F0', // 6: J — blue + '#F0A000', // 7: L — orange +]; + +export const TYPE_TO_ID: Record<string, number> = { + I: 1, O: 2, T: 3, S: 4, Z: 5, J: 6, L: 7, +}; + +// Points awarded per line clear at level 1 (multiply by level) +export const LINE_SCORES: readonly number[] = [0, 100, 300, 500, 800]; + +// Lines needed per level +export const LINES_PER_LEVEL = 10; + +// Frames per gravity drop at each level (60 fps reference) +export const GRAVITY_FRAMES: readonly number[] = [ + 48, 43, 38, 33, 28, 23, 18, 13, 8, 6, // levels 1–10 + 5, 5, 5, 4, 4, 4, 3, 3, 3, 2, // levels 11–20 + 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, // levels 21–30 +]; + +export const LOCK_DELAY_MS = 500; +export const MAX_LOCK_MOVES = 15; + +// DAS (Delayed Auto Shift) settings +export const DAS_DELAY_MS = 167; // delay before auto-repeat +export const DAS_REPEAT_MS = 33; // repeat interval (~30 Hz) + +// SRS wall kick data for JLSTZ pieces +// Each entry: [dx, dy] in screen coords (y increases downward) +// Key format: "fromRotation->toRotation" +export const JLSTZ_KICKS: Record<string, [number, number][]> = { + '0->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]], + '1->0': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]], + '1->2': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]], + '2->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]], + '2->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]], + '3->2': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]], + '3->0': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]], + '0->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]], +}; + +// SRS wall kick data for I piece +export const I_KICKS: Record<string, [number, number][]> = { + '0->1': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]], + '1->0': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]], + '1->2': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]], + '2->1': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]], + '2->3': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]], + '3->2': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]], + '3->0': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]], + '0->3': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]], +}; diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/renderer.ts b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/renderer.ts @@ -0,0 +1,239 @@ +import { Piece, TetrominoType } from './types'; +import { + COLS, ROWS, BLOCK_SIZE, PREVIEW_BLOCK_SIZE, + COLORS, TYPE_TO_ID, +} from './constants'; +import { getGhostPiece } from './board'; + +const BORDER_RADIUS = 3; +const GRID_COLOR = 'rgba(255,255,255,0.04)'; +const EMPTY_CELL_COLOR = '#0d0d1a'; + +// ── helpers ────────────────────────────────────────────────────────────────── + +function drawBlock( + ctx: CanvasRenderingContext2D, + x: number, + y: number, + size: number, + color: string, + alpha = 1, +): void { + ctx.globalAlpha = alpha; + // Main fill + ctx.fillStyle = color; + ctx.beginPath(); + ctx.roundRect(x + 1, y + 1, size - 2, size - 2, BORDER_RADIUS); + ctx.fill(); + + // Highlight (top-left glint) + const grad = ctx.createLinearGradient(x, y, x + size, y + size); + grad.addColorStop(0, 'rgba(255,255,255,0.35)'); + grad.addColorStop(1, 'rgba(0,0,0,0.25)'); + ctx.fillStyle = grad; + ctx.beginPath(); + ctx.roundRect(x + 1, y + 1, size - 2, size - 2, BORDER_RADIUS); + ctx.fill(); + + ctx.globalAlpha = 1; +} + +function drawGhostBlock( + ctx: CanvasRenderingContext2D, + x: number, + y: number, + size: number, + color: string, +): void { + ctx.globalAlpha = 1; + ctx.strokeStyle = color; + ctx.lineWidth = 2; + ctx.beginPath(); + ctx.roundRect(x + 2, y + 2, size - 4, size - 4, BORDER_RADIUS); + ctx.stroke(); +} + +// ── main board renderer ─────────────────────────────────────────────────────── + +export class Renderer { + private ctx: CanvasRenderingContext2D; + private holdCtx: CanvasRenderingContext2D; + private nextCtx: CanvasRenderingContext2D; + + constructor( + canvas: HTMLCanvasElement, + holdCanvas: HTMLCanvasElement, + nextCanvas: HTMLCanvasElement, + ) { + this.ctx = canvas.getContext('2d')!; + this.holdCtx = holdCanvas.getContext('2d')!; + this.nextCtx = nextCanvas.getContext('2d')!; + } + + // ── board ──────────────────────────────────────────────────────────────── + + drawBoard( + board: number[][], + currentPiece: Piece | null, + heldPiece: Piece | null, + nextPiece: Piece | null, + canHold: boolean, + ): void { + const ctx = this.ctx; + ctx.clearRect(0, 0, COLS * BLOCK_SIZE, ROWS * BLOCK_SIZE); + + // Background + ctx.fillStyle = EMPTY_CELL_COLOR; + ctx.fillRect(0, 0, COLS * BLOCK_SIZE, ROWS * BLOCK_SIZE); + + // Grid lines + ctx.strokeStyle = GRID_COLOR; + ctx.lineWidth = 1; + for (let c = 0; c <= COLS; c++) { + ctx.beginPath(); + ctx.moveTo(c * BLOCK_SIZE, 0); + ctx.lineTo(c * BLOCK_SIZE, ROWS * BLOCK_SIZE); + ctx.stroke(); + } + for (let r = 0; r <= ROWS; r++) { + ctx.beginPath(); + ctx.moveTo(0, r * BLOCK_SIZE); + ctx.lineTo(COLS * BLOCK_SIZE, r * BLOCK_SIZE); + ctx.stroke(); + } + + // Placed cells + for (let r = 0; r < ROWS; r++) { + for (let c = 0; c < COLS; c++) { + const id = board[r][c]; + if (id) { + drawBlock(ctx, c * BLOCK_SIZE, r * BLOCK_SIZE, BLOCK_SIZE, COLORS[id]); + } + } + } + + // Ghost piece + if (currentPiece) { + const ghost = getGhostPiece(currentPiece, board); + if (ghost.pos.y !== currentPiece.pos.y) { + const color = COLORS[TYPE_TO_ID[currentPiece.type]]; + for (let r = 0; r < ghost.matrix.length; r++) { + for (let c = 0; c < ghost.matrix[r].length; c++) { + if (!ghost.matrix[r][c]) continue; + const px = (ghost.pos.x + c) * BLOCK_SIZE; + const py = (ghost.pos.y + r) * BLOCK_SIZE; + if (py >= 0) drawGhostBlock(ctx, px, py, BLOCK_SIZE, color); + } + } + } + } + + // Current (active) piece + if (currentPiece) { + const color = COLORS[TYPE_TO_ID[currentPiece.type]]; + for (let r = 0; r < currentPiece.matrix.length; r++) { + for (let c = 0; c < currentPiece.matrix[r].length; c++) { + if (!currentPiece.matrix[r][c]) continue; + const px = (currentPiece.pos.x + c) * BLOCK_SIZE; + const py = (currentPiece.pos.y + r) * BLOCK_SIZE; + if (py >= 0) drawBlock(ctx, px, py, BLOCK_SIZE, color); + } + } + } + + // Side panels + this.drawPreview(this.holdCtx, heldPiece, canHold); + this.drawPreview(this.nextCtx, nextPiece, true); + } + + // ── piece preview (hold / next) ─────────────────────────────────────────── + + private drawPreview( + ctx: CanvasRenderingContext2D, + piece: Piece | null, + active: boolean, + ): void { + const W = ctx.canvas.width; + const H = ctx.canvas.height; + ctx.clearRect(0, 0, W, H); + ctx.fillStyle = '#0d0d1a'; + ctx.fillRect(0, 0, W, H); + + if (!piece) return; + + const bs = PREVIEW_BLOCK_SIZE; + const mat = piece.matrix; + const cols = mat[0].length; + const rows = mat.length; + + // Find actual bounding box of filled cells + let minR = rows, maxR = -1, minC = cols, maxC = -1; + for (let r = 0; r < rows; r++) { + for (let c = 0; c < cols; c++) { + if (mat[r][c]) { + minR = Math.min(minR, r); + maxR = Math.max(maxR, r); + minC = Math.min(minC, c); + maxC = Math.max(maxC, c); + } + } + } + if (maxR < 0) return; + + const spanC = maxC - minC + 1; + const spanR = maxR - minR + 1; + const offsetX = Math.floor((W - spanC * bs) / 2); + const offsetY = Math.floor((H - spanR * bs) / 2); + + const color = COLORS[TYPE_TO_ID[piece.type]]; + ctx.globalAlpha = active ? 1 : 0.35; + + for (let r = minR; r <= maxR; r++) { + for (let c = minC; c <= maxC; c++) { + if (!mat[r][c]) continue; + const px = offsetX + (c - minC) * bs; + const py = offsetY + (r - minR) * bs; + drawBlock(ctx, px, py, bs, color); + } + } + ctx.globalAlpha = 1; + } + + // ── overlays ────────────────────────────────────────────────────────────── + + drawOverlay( + text: string, + subText: string, + color = '#00f0f0', + ): void { + const ctx = this.ctx; + const W = COLS * BLOCK_SIZE; + const H = ROWS * BLOCK_SIZE; + + ctx.fillStyle = 'rgba(0, 0, 0, 0.75)'; + ctx.fillRect(0, 0, W, H); + + ctx.textAlign = 'center'; + ctx.textBaseline = 'middle'; + + ctx.fillStyle = color; + ctx.font = `bold 36px 'Courier New', monospace`; + ctx.fillText(text, W / 2, H / 2 - 28); + + ctx.fillStyle = '#aaa'; + ctx.font = `16px 'Courier New', monospace`; + + const lines = subText.split('\n'); + lines.forEach((line, i) => { + ctx.fillText(line, W / 2, H / 2 + 18 + i * 22); + }); + } + + drawLineClearFlash(rows: number[]): void { + const ctx = this.ctx; + ctx.fillStyle = 'rgba(255, 255, 255, 0.6)'; + for (const r of rows) { + ctx.fillRect(0, r * BLOCK_SIZE, COLS * BLOCK_SIZE, BLOCK_SIZE); + } + } +} diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/tetromino.ts b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/tetromino.ts @@ -0,0 +1,152 @@ +import { Matrix, Piece, Position, TetrominoType } from './types'; +import { COLS, I_KICKS, JLSTZ_KICKS, TYPE_TO_ID } from './constants'; + +// Canonical rotation state 0 matrices for each piece type +const PIECE_MATRICES: Record<TetrominoType, Matrix> = { + I: [ + [0, 0, 0, 0], + [1, 1, 1, 1], + [0, 0, 0, 0], + [0, 0, 0, 0], + ], + O: [ + [0, 1, 1, 0], + [0, 1, 1, 0], + [0, 0, 0, 0], + ], + T: [ + [0, 1, 0], + [1, 1, 1], + [0, 0, 0], + ], + S: [ + [0, 1, 1], + [1, 1, 0], + [0, 0, 0], + ], + Z: [ + [1, 1, 0], + [0, 1, 1], + [0, 0, 0], + ], + J: [ + [1, 0, 0], + [1, 1, 1], + [0, 0, 0], + ], + L: [ + [0, 0, 1], + [1, 1, 1], + [0, 0, 0], + ], +}; + +/** Rotate a matrix 90° clockwise */ +export function rotateMatrixCW(matrix: Matrix): Matrix { + const N = matrix.length; + const M = matrix[0].length; + const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0)); + for (let r = 0; r < N; r++) { + for (let c = 0; c < M; c++) { + result[c][N - 1 - r] = matrix[r][c]; + } + } + return result; +} + +/** Rotate a matrix 90° counter-clockwise */ +export function rotateMatrixCCW(matrix: Matrix): Matrix { + const N = matrix.length; + const M = matrix[0].length; + const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0)); + for (let r = 0; r < N; r++) { + for (let c = 0; c < M; c++) { + result[M - 1 - c][r] = matrix[r][c]; + } + } + return result; +} + +/** Build the rotation-state matrix for a piece at a given rotation (0–3) */ +export function buildMatrix(type: TetrominoType, rotation: number): Matrix { + let mat = PIECE_MATRICES[type].map(row => [...row]); + for (let i = 0; i < (rotation % 4 + 4) % 4; i++) { + mat = rotateMatrixCW(mat); + } + return mat; +} + +/** Create a new piece at its spawn position */ +export function createPiece(type: TetrominoType): Piece { + const matrix = buildMatrix(type, 0); + const spawnX = Math.floor((COLS - matrix[0].length) / 2); + // Spawn above visible field (y = -1 for pieces that appear at top) + const spawnY = type === 'I' ? -1 : 0; + return { type, matrix, pos: { x: spawnX, y: spawnY }, rotation: 0 }; +} + +/** + * Try to rotate a piece clockwise or counter-clockwise. + * Returns the new Piece if a valid position is found, or null on failure. + */ +export function tryRotate( + piece: Piece, + direction: 'CW' | 'CCW', + board: number[][] +): Piece | null { + const newRotation = direction === 'CW' + ? (piece.rotation + 1) % 4 + : (piece.rotation + 3) % 4; + + const newMatrix = direction === 'CW' + ? rotateMatrixCW(piece.matrix) + : rotateMatrixCCW(piece.matrix); + + const kickKey = `${piece.rotation}->${newRotation}`; + const kickTable = piece.type === 'I' ? I_KICKS : JLSTZ_KICKS; + const kicks = piece.type === 'O' ? [[0, 0]] : (kickTable[kickKey] ?? [[0, 0]]); + + for (const [dx, dy] of kicks) { + const testPos: Position = { x: piece.pos.x + dx, y: piece.pos.y + dy }; + if (!hasCollision(newMatrix, testPos, board)) { + return { ...piece, matrix: newMatrix, pos: testPos, rotation: newRotation }; + } + } + return null; // rotation failed +} + +/** Check if a matrix at a given position collides with the board or walls */ +export function hasCollision(matrix: Matrix, pos: Position, board: number[][]): boolean { + for (let r = 0; r < matrix.length; r++) { + for (let c = 0; c < matrix[r].length; c++) { + if (!matrix[r][c]) continue; + const boardX = pos.x + c; + const boardY = pos.y + r; + if (boardX < 0 || boardX >= COLS) return true; + if (boardY >= board.length) return true; + if (boardY >= 0 && board[boardY][boardX]) return true; + } + } + return false; +} + +/** Get the filled cell value for a tetromino type */ +export function typeToId(type: TetrominoType): number { + return TYPE_TO_ID[type]; +} + +/** Return a randomly chosen tetromino type */ +export function randomType(): TetrominoType { + const types: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L']; + return types[Math.floor(Math.random() * types.length)]; +} + +/** 7-bag randomiser: returns a shuffled bag of all 7 pieces */ +export function newBag(): TetrominoType[] { + const bag: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L']; + for (let i = bag.length - 1; i > 0; i--) { + const j = Math.floor(Math.random() * (i + 1)); + [bag[i], bag[j]] = [bag[j], bag[i]]; + } + return bag; +} diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/types.ts b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/src/types.ts @@ -0,0 +1,25 @@ +export type TetrominoType = 'I' | 'O' | 'T' | 'S' | 'Z' | 'J' | 'L'; + +export type Cell = TetrominoType | null; + +export type Matrix = number[][]; + +export interface Position { + x: number; + y: number; +} + +export interface Piece { + type: TetrominoType; + matrix: Matrix; + pos: Position; + rotation: number; // 0 | 1 | 2 | 3 +} + +export interface GameStats { + score: number; + lines: number; + level: number; +} + +export type GamePhase = 'idle' | 'playing' | 'paused' | 'gameover'; diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/package-lock.json b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/package-lock.json @@ -1,11 +1,11 @@ { - "name": "loop-bench-_wezxzen", + "name": "loop-bench-3fkpubdq", "version": "1.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "loop-bench-_wezxzen", + "name": "loop-bench-3fkpubdq", "version": "1.0.0", "license": "ISC", "devDependencies": { diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/package.json b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/package.json @@ -1,5 +1,5 @@ { - "name": "loop-bench-_wezxzen", + "name": "loop-bench-3fkpubdq", "version": "1.0.0", "description": "", "main": "index.js", diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/report/jscpd-report.json b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/report/jscpd-report.json @@ -1,6 +1,6 @@ { "statistics": { - "detectionDate": "2026-04-04T08:59:54.291Z", + "detectionDate": "2026-04-04T09:22:24.081Z", "formats": { "json": { "sources": { diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/package-lock.json b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/package-lock.json @@ -1,11 +1,11 @@ { - "name": "loop-bench-fg3fgin8", + "name": "loop-bench-rapthkjt", "version": "1.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "loop-bench-fg3fgin8", + "name": "loop-bench-rapthkjt", "version": "1.0.0", "license": "ISC", "devDependencies": { diff --git a/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/package.json b/dashboard/public/artifacts/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/package.json @@ -1,5 +1,5 @@ { - "name": "loop-bench-fg3fgin8", + "name": "loop-bench-rapthkjt", "version": "1.0.0", "description": "", "main": "index.js", diff --git 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+ /* ── Right panel ────────────────────────────── */ + #right-panel { + display: flex; + flex-direction: column; + gap: 16px; + width: 140px; + } + + .panel-box { + background: #12122a; + border: 2px solid #2a2a5a; + border-radius: 10px; + padding: 14px 16px; + } + + .panel-box h3 { + font-size: 10px; + letter-spacing: 2px; + text-transform: uppercase; + color: #6666aa; + margin-bottom: 8px; + } + + .panel-value { + font-size: 26px; + font-weight: 700; + color: #c8c8ff; + letter-spacing: 1px; + } + + /* ── Canvas / game board ────────────────────── */ + #game-area { + position: relative; + } + + #board { + display: block; + border: 3px solid #2a2a5a; + border-radius: 4px; + box-shadow: 0 0 40px #3333aa55, inset 0 0 20px #00001888; + } + + /* ── Overlay (start / pause / game-over) ───── */ + #overlay { + position: absolute; + inset: 0; + display: flex; + flex-direction: column; + justify-content: center; + align-items: center; + gap: 14px; + background: rgba(5, 5, 20, 0.82); + border-radius: 2px; + backdrop-filter: blur(3px); + } + + #overlay h2 { + font-size: 30px; + letter-spacing: 4px; + text-transform: uppercase; + color: #fff; + text-shadow: 0 0 20px #8888ff; + } + + #overlay p { + font-size: 13px; + color: #9090cc; + letter-spacing: 1px; + text-align: center; + line-height: 1.7; + } + + #overlay button { + margin-top: 6px; + padding: 11px 32px; + font-size: 14px; + font-weight: 700; + letter-spacing: 2px; + text-transform: uppercase; + background: linear-gradient(135deg, #4444cc, #6644ff); + color: #fff; + border: none; + border-radius: 8px; + cursor: pointer; + transition: filter 0.15s, transform 0.12s; + box-shadow: 0 4px 18px #4444cc88; + } + + #overlay button:hover { filter: brightness(1.25); transform: translateY(-2px); } + #overlay button:active { transform: translateY(0); } + + /* ── Next-piece canvas ──────────────────────── */ + #next-canvas { + display: block; + margin: 6px auto 0; + } + + /* ── Hold canvas ────────────────────────────── */ + #hold-canvas { + display: block; + margin: 6px auto 0; + } + + /* ── Controls list ──────────────────────────── */ + .controls-list { + font-size: 11px; + line-height: 2; + color: #7777bb; + } + + .controls-list span { + display: inline-block; + background: #1e1e3e; + border: 1px solid #3333668a; + border-radius: 4px; + padding: 1px 6px; + font-size: 10px; + color: #aaaadd; + margin-right: 4px; + } + + /* ── Ghost / level colours ──────────────────── */ + #level-bar-wrap { + background: #1a1a35; + border-radius: 4px; + height: 6px; + overflow: hidden; + margin-top: 6px; + } + + #level-bar { + height: 100%; + width: 0%; + background: linear-gradient(90deg, #4466ff, #aa44ff); + border-radius: 4px; + transition: width 0.4s ease; + } + </style> +</head> +<body> + +<div id="wrapper"> + + <!-- LEFT PANEL --> + <div id="left-panel"> + <div class="panel-box"> + <h3>Score</h3> + <div class="panel-value" id="score-display">0</div> + </div> + <div class="panel-box"> + <h3>Level</h3> + <div class="panel-value" id="level-display">1</div> + <div id="level-bar-wrap"><div id="level-bar"></div></div> + </div> + <div class="panel-box"> + <h3>Lines</h3> + <div class="panel-value" id="lines-display">0</div> + </div> + <div class="panel-box"> + <h3>Hold <small style="font-size:9px;color:#555">(C)</small></h3> + <canvas id="hold-canvas" width="100" height="80"></canvas> + </div> + </div> + + <!-- GAME BOARD --> + <div id="game-area"> + <canvas id="board" width="300" height="600"></canvas> + <div id="overlay"> + <h2>Tetris</h2> + <p>Arrow keys to move & soft-drop<br> + ↑ / X rotate CW · Z rotate CCW<br> + Space hard-drop · C hold<br> + P pause</p> + <button id="start-btn">Start Game</button> + </div> + </div> + + <!-- RIGHT PANEL --> + <div id="right-panel"> + <div class="panel-box"> + <h3>Next</h3> + <canvas id="next-canvas" width="100" height="200"></canvas> + </div> + <div class="panel-box"> + <h3>Controls</h3> + <div class="controls-list"> + <span>←→</span> Move<br> + <span>↓</span> Soft Drop<br> + <span>Space</span> Hard Drop<br> + <span>↑</span><span>X</span> Rotate CW<br> + <span>Z</span> Rotate CCW<br> + <span>C</span> Hold<br> + <span>P</span> Pause + </div> + </div> + <div class="panel-box" id="combo-box" style="display:none"> + <h3>Combo</h3> + <div class="panel-value" id="combo-display">x0</div> + </div> + </div> + +</div> + +<script> +// ═══════════════════════════════════════════════════════════════ +// CONSTANTS +// ═══════════════════════════════════════════════════════════════ +const COLS = 10; +const ROWS = 20; +const BLOCK = 30; // px per cell + +// Colours per piece type (index 0 = empty) +const COLORS = [ + null, + '#00cfcf', // I – cyan + '#f0a000', // O – orange/yellow + '#a000f0', // T – purple + '#00a000', // S – green + '#f00000', // Z – red + '#0000f0', // J – blue + '#f07800', // L – orange +]; + +const GHOST_ALPHA = 0.22; + +// Tetromino definitions – each piece has 4 rotation states +// Stored as [row][col] offsets from the pivot +const PIECES = { + // 0 1 2 3 + I: [ + [[0,0],[0,1],[0,2],[0,3]], + [[0,2],[1,2],[2,2],[3,2]], + [[1,0],[1,1],[1,2],[1,3]], + [[0,1],[1,1],[2,1],[3,1]], + ], + O: [ + [[0,0],[0,1],[1,0],[1,1]], + [[0,0],[0,1],[1,0],[1,1]], + [[0,0],[0,1],[1,0],[1,1]], + [[0,0],[0,1],[1,0],[1,1]], + ], + T: [ + [[0,1],[1,0],[1,1],[1,2]], + [[0,1],[1,1],[1,2],[2,1]], + [[1,0],[1,1],[1,2],[2,1]], + [[0,1],[1,0],[1,1],[2,1]], + ], + S: [ + [[0,1],[0,2],[1,0],[1,1]], + [[0,1],[1,1],[1,2],[2,2]], + [[1,1],[1,2],[2,0],[2,1]], + [[0,0],[1,0],[1,1],[2,1]], + ], + Z: [ + [[0,0],[0,1],[1,1],[1,2]], + [[0,2],[1,1],[1,2],[2,1]], + [[1,0],[1,1],[2,1],[2,2]], + [[0,1],[1,0],[1,1],[2,0]], + ], + J: [ + [[0,0],[1,0],[1,1],[1,2]], + [[0,1],[0,2],[1,1],[2,1]], + [[1,0],[1,1],[1,2],[2,2]], + [[0,1],[1,1],[2,0],[2,1]], + ], + L: [ + [[0,2],[1,0],[1,1],[1,2]], + [[0,1],[1,1],[2,1],[2,2]], + [[1,0],[1,1],[1,2],[2,0]], + [[0,0],[0,1],[1,1],[2,1]], + ], +}; + +const PIECE_KEYS = Object.keys(PIECES); // ['I','O','T','S','Z','J','L'] +const PIECE_IDX = { I:1, O:2, T:3, S:4, Z:5, J:6, L:7 }; + +// Wall-kick offsets for standard rotation (SRS-lite) +// [from-rotation][to-rotation] = array of (dr,dc) attempts +const KICKS = {}; +(function buildKicks() { + // Non-I pieces + const standard = { + '01': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]], + '10': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]], + '12': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]], + '21': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2,-1]], + '23': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]], + '32': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]], + '30': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]], + '03': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2, 1]], + }; + // I piece + const iKicks = { + '01': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]], + '10': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]], + '12': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]], + '21': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]], + '23': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]], + '32': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]], + '30': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]], + '03': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]], + }; + KICKS['standard'] = standard; + KICKS['I'] = iKicks; +})(); + +// Level → fall interval (ms) +function levelSpeed(level) { + // Classic Tetris-style curve + const frames = [48,43,38,33,28,23,18,13,8,6,5,5,5,4,4,4,3,3,3,2,2,2,2,2,2,2,2,2,1]; + const idx = Math.min(level - 1, frames.length - 1); + return Math.round(frames[idx] * (1000 / 60)); +} + +// Points for line clears (single,double,triple,tetris) +const LINE_POINTS = [0, 100, 300, 500, 800]; +const SOFT_DROP_PTS = 1; +const HARD_DROP_PTS = 2; + +// ═══════════════════════════════════════════════════════════════ +// GAME STATE +// ═══════════════════════════════════════════════════════════════ +let board, current, ghost, nextQueue, held; +let score, level, lines, combo; +let canHold, gameOver, paused, started; +let dropTimer, lastTime, animId; +let lockTimer, lockMoved; +const LOCK_DELAY = 500; // ms before a grounded piece locks +const LOCK_MOVES = 15; // max moves before forced lock + +// 7-bag randomiser +let bag = []; +function nextBag() { + if (bag.length === 0) { + bag = [...PIECE_KEYS]; + for (let i = bag.length - 1; i > 0; i--) { + const j = Math.floor(Math.random() * (i + 1)); + [bag[i], bag[j]] = [bag[j], bag[i]]; + } + } + return bag.pop(); +} + +function createPiece(type) { + // spawn position: row 0, col 3 + return { type, rot: 0, row: 0, col: 3 }; +} + +function initGame() { + board = Array.from({ length: ROWS }, () => new Array(COLS).fill(0)); + bag = []; + nextQueue = [nextBag(), nextBag(), nextBag()]; + current = spawnPiece(); + held = null; + score = 0; level = 1; lines = 0; combo = -1; + canHold = true; + gameOver = false; paused = false; + dropTimer = 0; lastTime = null; + lockTimer = null; lockMoved = 0; + updateUI(); + updateGhost(); +} + +function spawnPiece() { + const type = nextQueue.shift(); + nextQueue.push(nextBag()); + const p = createPiece(type); + // I and O spawn slightly lower + if (type === 'I') p.row = -1; + return p; +} + +// ═══════════════════════════════════════════════════════════════ +// BOARD HELPERS +// ═══════════════════════════════════════════════════════════════ +function cells(piece) { + return PIECES[piece.type][piece.rot].map(([dr, dc]) => [piece.row + dr, piece.col + dc]); +} + +function valid(piece, dr = 0, dc = 0, rot = piece.rot) { + const test = { ...piece, row: piece.row + dr, col: piece.col + dc, rot }; + return cells(test).every(([r, c]) => + r < ROWS && c >= 0 && c < COLS && (r < 0 || board[r][c] === 0) + ); +} + +function lock(piece) { + let topped = false; + cells(piece).forEach(([r, c]) => { + if (r < 0) { topped = true; return; } + board[r][c] = PIECE_IDX[piece.type]; + }); + if (topped) { triggerGameOver(); return; } + + clearLines(); + + current = spawnPiece(); + canHold = true; + lockMoved = 0; + clearTimeout(lockTimer); lockTimer = null; + + if (!valid(current)) { + triggerGameOver(); + } else { + updateGhost(); + } +} + +function clearLines() { + const fullSet = new Set(); + for (let r = ROWS - 1; r >= 0; r--) { + if (board[r].every(v => v !== 0)) fullSet.add(r); + } + if (fullSet.size === 0) { + combo = -1; + return; + } + + const count = fullSet.size; + const flashRowArr = [...fullSet]; // original indices for flash effect + + // Remove all full rows atomically, prepend empty rows at top + const kept = board.filter((_, r) => !fullSet.has(r)); + const empties = Array.from({ length: count }, () => new Array(COLS).fill(0)); + board.splice(0, ROWS, ...empties, ...kept); + + combo++; + const pts = (LINE_POINTS[count] + (combo > 0 ? 50 * combo : 0)) * level; + score += pts; + lines += count; + level = Math.floor(lines / 10) + 1; + updateUI(); + + flashLines(flashRowArr); // purely visual +} + +function updateGhost() { + if (!current) return; + ghost = { ...current }; + while (valid(ghost, 1)) ghost.row++; +} + +// ═══════════════════════════════════════════════════════════════ +// CONTROLS +// ═══════════════════════════════════════════════════════════════ +function moveLeft() { tryMove(0, -1); } +function moveRight() { tryMove(0, 1); } +function softDrop() { + if (tryMove(1, 0)) { + score += SOFT_DROP_PTS; + updateUI(); + } +} + +function tryMove(dr, dc) { + if (!current || gameOver || paused) return false; + if (valid(current, dr, dc)) { + current.row += dr; + current.col += dc; + updateGhost(); + extendLock(); + return true; + } + return false; +} + +function rotateCW() { rotate( 1); } +function rotateCCW() { rotate(-1); } + +function rotate(dir) { + if (!current || gameOver || paused) return; + const newRot = ((current.rot + dir) + 4) % 4; + const kickTable = current.type === 'I' ? KICKS['I'] : KICKS['standard']; + const key = `${current.rot}${newRot}`; + const kicks = kickTable[key] || [[0, 0]]; + for (const [kr, kc] of kicks) { + if (valid(current, kr, kc, newRot)) { + current.row += kr; + current.col += kc; + current.rot = newRot; + updateGhost(); + extendLock(); + return; + } + } +} + +function hardDrop() { + if (!current || gameOver || paused) return; + let dropped = 0; + while (valid(current, 1)) { current.row++; dropped++; } + score += dropped * HARD_DROP_PTS; + updateUI(); + clearTimeout(lockTimer); lockTimer = null; + lock(current); +} + +function holdPiece() { + if (!current || !canHold || gameOver || paused) return; + if (held) { + const prev = held; + held = current.type; + current = createPiece(prev); + if (current.type === 'I') current.row = -1; + } else { + held = current.type; + current = spawnPiece(); + } + canHold = false; + updateGhost(); + drawHold(); +} + +function extendLock() { + // If the piece is grounded, reset lock timer (up to LOCK_MOVES times) + if (!valid(current, 1) && lockMoved < LOCK_MOVES) { + lockMoved++; + clearTimeout(lockTimer); + lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY); + } +} + +// ═══════════════════════════════════════════════════════════════ +// GAME LOOP +// ═══════════════════════════════════════════════════════════════ +function gameLoop(ts) { + if (gameOver) return; + animId = requestAnimationFrame(gameLoop); + + if (!lastTime) lastTime = ts; + const dt = ts - lastTime; + lastTime = ts; + + if (!paused) { + dropTimer += dt; + const interval = levelSpeed(level); + if (dropTimer >= interval) { + dropTimer -= interval; + // Attempt to fall + if (valid(current, 1)) { + current.row++; + updateGhost(); + } else { + // Start lock delay if not already running + if (!lockTimer) { + lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY); + } + } + } + } + + draw(); +} + +function triggerGameOver() { + gameOver = true; + clearTimeout(lockTimer); + cancelAnimationFrame(animId); + drawBoard(); // final frame + showOverlay('GAME OVER', `Score: ${score} | Level: ${level} | Lines: ${lines}`, 'Play Again'); +} + +// ═══════════════════════════════════════════════════════════════ +// RENDERING +// ═══════════════════════════════════════════════════════════════ +const canvas = document.getElementById('board'); +const ctx = canvas.getContext('2d'); +const nextCvs = document.getElementById('next-canvas'); +const nextCtx = nextCvs.getContext('2d'); +const holdCvs = document.getElementById('hold-canvas'); +const holdCtx = holdCvs.getContext('2d'); + +let flashRows = []; +let flashTimer = 0; +const FLASH_DUR = 320; + +function flashLines(rows) { + flashRows = rows; + flashTimer = FLASH_DUR; +} + +function draw() { + drawBoard(); + drawNext(); + drawHold(); +} + +function drawBoard() { + // Background + ctx.fillStyle = '#090918'; + ctx.fillRect(0, 0, canvas.width, canvas.height); + + // Grid lines (subtle) + ctx.strokeStyle = '#12122a'; + ctx.lineWidth = 0.5; + for (let c = 1; c < COLS; c++) { + ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke(); + } + for (let r = 1; r < ROWS; r++) { + ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke(); + } + + // Settled board cells + for (let r = 0; r < ROWS; r++) { + for (let c = 0; c < COLS; c++) { + if (board[r][c]) { + drawCell(ctx, r, c, COLORS[board[r][c]], 1, 0, 0); + } + } + } + + // Flash overlay + if (flashTimer > 0 && !paused) { + flashTimer -= 16; + const alpha = 0.7 * (flashTimer / FLASH_DUR); + ctx.fillStyle = `rgba(255,255,255,${alpha})`; + flashRows.forEach(r => { + ctx.fillRect(0, r * BLOCK, canvas.width, BLOCK); + }); + if (flashTimer <= 0) flashRows = []; + } + + if (paused) { + ctx.fillStyle = 'rgba(5,5,20,0.7)'; + ctx.fillRect(0, 0, canvas.width, canvas.height); + ctx.fillStyle = '#fff'; + ctx.font = 'bold 28px system-ui'; + ctx.textAlign = 'center'; + ctx.fillText('PAUSED', canvas.width / 2, canvas.height / 2); + ctx.font = '13px system-ui'; + ctx.fillStyle = '#8888cc'; + ctx.fillText('Press P to resume', canvas.width / 2, canvas.height / 2 + 32); + return; + } + + if (!current) return; + + // Ghost piece + if (ghost && (ghost.row !== current.row || ghost.col !== current.col)) { + cells(ghost).forEach(([r, c]) => { + if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], GHOST_ALPHA, 0, 0); + }); + } + + // Active piece + cells(current).forEach(([r, c]) => { + if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], 1, 0, 0); + }); +} + +function drawCell(context, row, col, color, alpha, offR, offC) { + const x = (col + offC) * BLOCK; + const y = (row + offR) * BLOCK; + const s = BLOCK - 1; + + context.save(); + context.globalAlpha = alpha; + + // Main fill with gradient + const grad = context.createLinearGradient(x, y, x + s, y + s); + grad.addColorStop(0, lighten(color, 40)); + grad.addColorStop(1, darken(color, 30)); + context.fillStyle = grad; + context.fillRect(x + 1, y + 1, s - 1, s - 1); + + // Highlight edge (top-left) + context.fillStyle = lighten(color, 60); + context.fillRect(x + 1, y + 1, s - 1, 2); + context.fillRect(x + 1, y + 1, 2, s - 1); + + // Shadow edge (bottom-right) + context.fillStyle = darken(color, 50); + context.fillRect(x + 1, y + s - 2, s - 1, 2); + context.fillRect(x + s - 2, y + 1, 2, s - 1); + + context.restore(); +} + +function drawMiniPiece(context, cvs, type) { + context.fillStyle = '#0d0d1f'; + context.fillRect(0, 0, cvs.width, cvs.height); + if (!type) return; + + const shape = PIECES[type][0]; + const minR = Math.min(...shape.map(([r]) => r)); + const maxR = Math.max(...shape.map(([r]) => r)); + const minC = Math.min(...shape.map(([, c]) => c)); + const maxC = Math.max(...shape.map(([, c]) => c)); + const h = maxR - minR + 1; + const w = maxC - minC + 1; + const bs = 20; + const startX = Math.floor((cvs.width - w * bs) / 2); + const startY = Math.floor((cvs.height - h * bs) / 2); + + shape.forEach(([r, c]) => { + const px = startX + (c - minC) * bs; + const py = startY + (r - minR) * bs; + const s = bs - 1; + + const color = COLORS[PIECE_IDX[type]]; + const grad = context.createLinearGradient(px, py, px + s, py + s); + grad.addColorStop(0, lighten(color, 40)); + grad.addColorStop(1, darken(color, 30)); + context.fillStyle = grad; + context.fillRect(px + 1, py + 1, s - 1, s - 1); + + context.fillStyle = lighten(color, 60); + context.fillRect(px + 1, py + 1, s - 1, 2); + context.fillRect(px + 1, py + 1, 2, s - 1); + + context.fillStyle = darken(color, 50); + context.fillRect(px + 1, py + s - 2, s - 1, 2); + context.fillRect(px + s - 2, py + 1, 2, s - 1); + }); +} + +function drawNext() { + const w = nextCvs.width; + const h = nextCvs.height; + nextCtx.fillStyle = '#0d0d1f'; + nextCtx.fillRect(0, 0, w, h); + + const slotH = h / 3; + nextQueue.forEach((type, i) => { + const shape = PIECES[type][0]; + const minR = Math.min(...shape.map(([r]) => r)); + const maxR = Math.max(...shape.map(([r]) => r)); + const minC = Math.min(...shape.map(([, c]) => c)); + const maxC = Math.max(...shape.map(([, c]) => c)); + const ph = maxR - minR + 1; + const pw = maxC - minC + 1; + const bs = i === 0 ? 20 : 16; + const startX = Math.floor((w - pw * bs) / 2); + const baseY = i * slotH + Math.floor((slotH - ph * bs) / 2); + + shape.forEach(([r, c]) => { + const px = startX + (c - minC) * bs; + const py = baseY + (r - minR) * bs; + const s = bs - 1; + const color = COLORS[PIECE_IDX[type]]; + const alpha = i === 0 ? 1 : 0.65 - i * 0.1; + + nextCtx.save(); + nextCtx.globalAlpha = alpha; + const grad = nextCtx.createLinearGradient(px, py, px + s, py + s); + grad.addColorStop(0, lighten(color, 40)); + grad.addColorStop(1, darken(color, 30)); + nextCtx.fillStyle = grad; + nextCtx.fillRect(px + 1, py + 1, s - 1, s - 1); + nextCtx.fillStyle = lighten(color, 60); + nextCtx.fillRect(px + 1, py + 1, s - 1, 2); + nextCtx.fillRect(px + 1, py + 1, 2, s - 1); + nextCtx.fillStyle = darken(color, 50); + nextCtx.fillRect(px + 1, py + s - 2, s - 1, 2); + nextCtx.fillRect(px + s - 2, py + 1, 2, s - 1); + nextCtx.restore(); + }); + }); +} + +function drawHold() { + drawMiniPiece(holdCtx, holdCvs, held); + if (!canHold && held) { + holdCtx.fillStyle = 'rgba(0,0,0,0.5)'; + holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height); + } +} + +// ═══════════════════════════════════════════════════════════════ +// UI +// ═══════════════════════════════════════════════════════════════ +const scoreEl = document.getElementById('score-display'); +const levelEl = document.getElementById('level-display'); +const linesEl = document.getElementById('lines-display'); +const levelBar = document.getElementById('level-bar'); +const comboBox = document.getElementById('combo-box'); +const comboDis = document.getElementById('combo-display'); + +function updateUI() { + scoreEl.textContent = score.toLocaleString(); + levelEl.textContent = level; + linesEl.textContent = lines; + const pct = ((lines % 10) / 10) * 100; + levelBar.style.width = pct + '%'; + + if (combo > 0) { + comboBox.style.display = 'block'; + comboDis.textContent = 'x' + (combo + 1); + } else { + comboBox.style.display = 'none'; + } +} + +// ═══════════════════════════════════════════════════════════════ +// OVERLAY +// ═══════════════════════════════════════════════════════════════ +const overlay = document.getElementById('overlay'); +const startBtn = document.getElementById('start-btn'); + +function showOverlay(title, msg, btnText) { + overlay.querySelector('h2').textContent = title; + overlay.querySelector('p').innerHTML = msg; + startBtn.textContent = btnText; + overlay.style.display = 'flex'; +} + +function hideOverlay() { + overlay.style.display = 'none'; +} + +startBtn.addEventListener('click', () => { + hideOverlay(); + initGame(); + lastTime = null; + started = true; + animId = requestAnimationFrame(gameLoop); +}); + +// ═══════════════════════════════════════════════════════════════ +// KEYBOARD +// ═══════════════════════════════════════════════════════════════ +const DAS_DELAY = 170; // ms before auto-repeat +const DAS_REPEAT = 50; // ms between repeats + +let dasKey = null, dasTimer = null, dasRepeat = null; + +function startDAS(key) { + if (dasKey === key) return; + stopDAS(); + dasKey = key; + applyKey(key); + dasTimer = setTimeout(() => { + dasRepeat = setInterval(() => applyKey(key), DAS_REPEAT); + }, DAS_DELAY); +} + +function stopDAS(key) { + if (key && dasKey !== key) return; + clearTimeout(dasTimer); + clearInterval(dasRepeat); + dasKey = null; +} + +function applyKey(key) { + if (key === 'ArrowLeft') moveLeft(); + if (key === 'ArrowRight') moveRight(); + if (key === 'ArrowDown') softDrop(); +} + +window.addEventListener('keydown', e => { + if (!started) return; + + // Pause toggle + if (e.code === 'KeyP') { + if (gameOver) return; + paused = !paused; + if (!paused) { lastTime = null; } + return; + } + + if (paused || gameOver) return; + + switch (e.code) { + case 'ArrowLeft': e.preventDefault(); startDAS('ArrowLeft'); break; + case 'ArrowRight': e.preventDefault(); startDAS('ArrowRight'); break; + case 'ArrowDown': e.preventDefault(); startDAS('ArrowDown'); break; + case 'ArrowUp': e.preventDefault(); rotateCW(); break; + case 'KeyX': e.preventDefault(); rotateCW(); break; + case 'KeyZ': e.preventDefault(); rotateCCW(); break; + case 'Space': e.preventDefault(); hardDrop(); break; + case 'KeyC': e.preventDefault(); holdPiece(); break; + } +}); + +window.addEventListener('keyup', e => { + if (['ArrowLeft','ArrowRight','ArrowDown'].includes(e.code)) { + stopDAS(e.code); + } +}); + +// ═══════════════════════════════════════════════════════════════ +// COLOUR HELPERS +// ═══════════════════════════════════════════════════════════════ +function parseHex(hex) { + const n = parseInt(hex.replace('#',''), 16); + return [(n >> 16) & 255, (n >> 8) & 255, n & 255]; +} +function toHex([r, g, b]) { + return '#' + [r, g, b].map(v => Math.min(255, Math.max(0, v)).toString(16).padStart(2,'0')).join(''); +} +function lighten(hex, amt) { return toHex(parseHex(hex).map(v => v + amt)); } +function darken(hex, amt) { return toHex(parseHex(hex).map(v => v - amt)); } + +// ═══════════════════════════════════════════════════════════════ +// INITIAL RENDER +// ═══════════════════════════════════════════════════════════════ +(function initialDraw() { + ctx.fillStyle = '#090918'; + ctx.fillRect(0, 0, canvas.width, canvas.height); + // subtle grid + ctx.strokeStyle = '#12122a'; + ctx.lineWidth = 0.5; + for (let c = 1; c < COLS; c++) { + ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke(); + } + for (let r = 1; r < ROWS; r++) { + ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke(); + } + holdCtx.fillStyle = '#0d0d1f'; holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height); + nextCtx.fillStyle = 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+ + /* ── Right panel ────────────────────────────── */ + #right-panel { + display: flex; + flex-direction: column; + gap: 16px; + width: 140px; + } + + .panel-box { + background: #12122a; + border: 2px solid #2a2a5a; + border-radius: 10px; + padding: 14px 16px; + } + + .panel-box h3 { + font-size: 10px; + letter-spacing: 2px; + text-transform: uppercase; + color: #6666aa; + margin-bottom: 8px; + } + + .panel-value { + font-size: 26px; + font-weight: 700; + color: #c8c8ff; + letter-spacing: 1px; + } + + /* ── Canvas / game board ────────────────────── */ + #game-area { + position: relative; + } + + #board { + display: block; + border: 3px solid #2a2a5a; + border-radius: 4px; + box-shadow: 0 0 40px #3333aa55, inset 0 0 20px #00001888; + } + + /* ── Overlay (start / pause / game-over) ───── */ + #overlay { + position: absolute; + inset: 0; + display: flex; + flex-direction: column; + justify-content: center; + align-items: center; + gap: 14px; + background: rgba(5, 5, 20, 0.82); + border-radius: 2px; + backdrop-filter: blur(3px); + } + + #overlay h2 { + font-size: 30px; + letter-spacing: 4px; + text-transform: uppercase; + color: #fff; + text-shadow: 0 0 20px #8888ff; + } + + #overlay p { + font-size: 13px; + color: #9090cc; + letter-spacing: 1px; + text-align: center; + line-height: 1.7; + } + + #overlay button { + margin-top: 6px; + padding: 11px 32px; + font-size: 14px; + font-weight: 700; + letter-spacing: 2px; + text-transform: uppercase; + background: linear-gradient(135deg, #4444cc, #6644ff); + color: #fff; + border: none; + border-radius: 8px; + cursor: pointer; + transition: filter 0.15s, transform 0.12s; + box-shadow: 0 4px 18px #4444cc88; + } + + #overlay button:hover { filter: brightness(1.25); transform: translateY(-2px); } + #overlay button:active { transform: translateY(0); } + + /* ── Next-piece canvas ──────────────────────── */ + #next-canvas { + display: block; + margin: 6px auto 0; + } + + /* ── Hold canvas ────────────────────────────── */ + #hold-canvas { + display: block; + margin: 6px auto 0; + } + + /* ── Controls list ──────────────────────────── */ + .controls-list { + font-size: 11px; + line-height: 2; + color: #7777bb; + } + + .controls-list span { + display: inline-block; + background: #1e1e3e; + border: 1px solid #3333668a; + border-radius: 4px; + padding: 1px 6px; + font-size: 10px; + color: #aaaadd; + margin-right: 4px; + } + + /* ── Ghost / level colours ──────────────────── */ + #level-bar-wrap { + background: #1a1a35; + border-radius: 4px; + height: 6px; + overflow: hidden; + margin-top: 6px; + } + + #level-bar { + height: 100%; + width: 0%; + background: linear-gradient(90deg, #4466ff, #aa44ff); + border-radius: 4px; + transition: width 0.4s ease; + } + </style> +</head> +<body> + +<div id="wrapper"> + + <!-- LEFT PANEL --> + <div id="left-panel"> + <div class="panel-box"> + <h3>Score</h3> + <div class="panel-value" id="score-display">0</div> + </div> + <div class="panel-box"> + <h3>Level</h3> + <div class="panel-value" id="level-display">1</div> + <div id="level-bar-wrap"><div id="level-bar"></div></div> + </div> + <div class="panel-box"> + <h3>Lines</h3> + <div class="panel-value" id="lines-display">0</div> + </div> + <div class="panel-box"> + <h3>Hold <small style="font-size:9px;color:#555">(C)</small></h3> + <canvas id="hold-canvas" width="100" height="80"></canvas> + </div> + </div> + + <!-- GAME BOARD --> + <div id="game-area"> + <canvas id="board" width="300" height="600"></canvas> + <div id="overlay"> + <h2>Tetris</h2> + <p>Arrow keys to move & soft-drop<br> + ↑ / X rotate CW · Z rotate CCW<br> + Space hard-drop · C hold<br> + P pause</p> + <button id="start-btn">Start Game</button> + </div> + </div> + + <!-- RIGHT PANEL --> + <div id="right-panel"> + <div class="panel-box"> + <h3>Next</h3> + <canvas id="next-canvas" width="100" height="200"></canvas> + </div> + <div class="panel-box"> + <h3>Controls</h3> + <div class="controls-list"> + <span>←→</span> Move<br> + <span>↓</span> Soft Drop<br> + <span>Space</span> Hard Drop<br> + <span>↑</span><span>X</span> Rotate CW<br> + <span>Z</span> Rotate CCW<br> + <span>C</span> Hold<br> + <span>P</span> Pause + </div> + </div> + <div class="panel-box" id="combo-box" style="display:none"> + <h3>Combo</h3> + <div class="panel-value" id="combo-display">x0</div> + </div> + </div> + +</div> + +<script> +// ═══════════════════════════════════════════════════════════════ +// CONSTANTS +// ═══════════════════════════════════════════════════════════════ +const COLS = 10; +const ROWS = 20; +const BLOCK = 30; // px per cell + +// Colours per piece type (index 0 = empty) +const COLORS = [ + null, + '#00cfcf', // I – cyan + '#f0a000', // O – orange/yellow + '#a000f0', // T – purple + '#00a000', // S – green + '#f00000', // Z – red + '#0000f0', // J – blue + '#f07800', // L – orange +]; + +const GHOST_ALPHA = 0.22; + +// Tetromino definitions – each piece has 4 rotation states +// Stored as [row][col] offsets from the pivot +const PIECES = { + // 0 1 2 3 + I: [ + [[0,0],[0,1],[0,2],[0,3]], + [[0,2],[1,2],[2,2],[3,2]], + [[1,0],[1,1],[1,2],[1,3]], + [[0,1],[1,1],[2,1],[3,1]], + ], + O: [ + [[0,0],[0,1],[1,0],[1,1]], + [[0,0],[0,1],[1,0],[1,1]], + [[0,0],[0,1],[1,0],[1,1]], + [[0,0],[0,1],[1,0],[1,1]], + ], + T: [ + [[0,1],[1,0],[1,1],[1,2]], + [[0,1],[1,1],[1,2],[2,1]], + [[1,0],[1,1],[1,2],[2,1]], + [[0,1],[1,0],[1,1],[2,1]], + ], + S: [ + [[0,1],[0,2],[1,0],[1,1]], + [[0,1],[1,1],[1,2],[2,2]], + [[1,1],[1,2],[2,0],[2,1]], + [[0,0],[1,0],[1,1],[2,1]], + ], + Z: [ + [[0,0],[0,1],[1,1],[1,2]], + [[0,2],[1,1],[1,2],[2,1]], + [[1,0],[1,1],[2,1],[2,2]], + [[0,1],[1,0],[1,1],[2,0]], + ], + J: [ + [[0,0],[1,0],[1,1],[1,2]], + [[0,1],[0,2],[1,1],[2,1]], + [[1,0],[1,1],[1,2],[2,2]], + [[0,1],[1,1],[2,0],[2,1]], + ], + L: [ + [[0,2],[1,0],[1,1],[1,2]], + [[0,1],[1,1],[2,1],[2,2]], + [[1,0],[1,1],[1,2],[2,0]], + [[0,0],[0,1],[1,1],[2,1]], + ], +}; + +const PIECE_KEYS = Object.keys(PIECES); // ['I','O','T','S','Z','J','L'] +const PIECE_IDX = { I:1, O:2, T:3, S:4, Z:5, J:6, L:7 }; + +// Wall-kick offsets for standard rotation (SRS-lite) +// [from-rotation][to-rotation] = array of (dr,dc) attempts +const KICKS = {}; +(function buildKicks() { + // Non-I pieces + const standard = { + '01': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]], + '10': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]], + '12': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]], + '21': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2,-1]], + '23': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]], + '32': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]], + '30': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]], + '03': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2, 1]], + }; + // I piece + const iKicks = { + '01': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]], + '10': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]], + '12': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]], + '21': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]], + '23': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]], + '32': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]], + '30': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]], + '03': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]], + }; + KICKS['standard'] = standard; + KICKS['I'] = iKicks; +})(); + +// Level → fall interval (ms) +function levelSpeed(level) { + // Classic Tetris-style curve + const frames = [48,43,38,33,28,23,18,13,8,6,5,5,5,4,4,4,3,3,3,2,2,2,2,2,2,2,2,2,1]; + const idx = Math.min(level - 1, frames.length - 1); + return Math.round(frames[idx] * (1000 / 60)); +} + +// Points for line clears (single,double,triple,tetris) +const LINE_POINTS = [0, 100, 300, 500, 800]; +const SOFT_DROP_PTS = 1; +const HARD_DROP_PTS = 2; + +// ═══════════════════════════════════════════════════════════════ +// GAME STATE +// ═══════════════════════════════════════════════════════════════ +let board, current, ghost, nextQueue, held; +let score, level, lines, combo; +let canHold, gameOver, paused, started; +let dropTimer, lastTime, animId; +let lockTimer, lockMoved; +const LOCK_DELAY = 500; // ms before a grounded piece locks +const LOCK_MOVES = 15; // max moves before forced lock + +// 7-bag randomiser +let bag = []; +function nextBag() { + if (bag.length === 0) { + bag = [...PIECE_KEYS]; + for (let i = bag.length - 1; i > 0; i--) { + const j = Math.floor(Math.random() * (i + 1)); + [bag[i], bag[j]] = [bag[j], bag[i]]; + } + } + return bag.pop(); +} + +function createPiece(type) { + // spawn position: row 0, col 3 + return { type, rot: 0, row: 0, col: 3 }; +} + +function initGame() { + board = Array.from({ length: ROWS }, () => new Array(COLS).fill(0)); + bag = []; + nextQueue = [nextBag(), nextBag(), nextBag()]; + current = spawnPiece(); + held = null; + score = 0; level = 1; lines = 0; combo = -1; + canHold = true; + gameOver = false; paused = false; + dropTimer = 0; lastTime = null; + lockTimer = null; lockMoved = 0; + updateUI(); + updateGhost(); +} + +function spawnPiece() { + const type = nextQueue.shift(); + nextQueue.push(nextBag()); + const p = createPiece(type); + // I and O spawn slightly lower + if (type === 'I') p.row = -1; + return p; +} + +// ═══════════════════════════════════════════════════════════════ +// BOARD HELPERS +// ═══════════════════════════════════════════════════════════════ +function cells(piece) { + return PIECES[piece.type][piece.rot].map(([dr, dc]) => [piece.row + dr, piece.col + dc]); +} + +function valid(piece, dr = 0, dc = 0, rot = piece.rot) { + const test = { ...piece, row: piece.row + dr, col: piece.col + dc, rot }; + return cells(test).every(([r, c]) => + r < ROWS && c >= 0 && c < COLS && (r < 0 || board[r][c] === 0) + ); +} + +function lock(piece) { + let topped = false; + cells(piece).forEach(([r, c]) => { + if (r < 0) { topped = true; return; } + board[r][c] = PIECE_IDX[piece.type]; + }); + if (topped) { triggerGameOver(); return; } + + clearLines(); + + current = spawnPiece(); + canHold = true; + lockMoved = 0; + clearTimeout(lockTimer); lockTimer = null; + + if (!valid(current)) { + triggerGameOver(); + } else { + updateGhost(); + } +} + +function clearLines() { + const fullSet = new Set(); + for (let r = ROWS - 1; r >= 0; r--) { + if (board[r].every(v => v !== 0)) fullSet.add(r); + } + if (fullSet.size === 0) { + combo = -1; + return; + } + + const count = fullSet.size; + const flashRowArr = [...fullSet]; // original indices for flash effect + + // Remove all full rows atomically, prepend empty rows at top + const kept = board.filter((_, r) => !fullSet.has(r)); + const empties = Array.from({ length: count }, () => new Array(COLS).fill(0)); + board.splice(0, ROWS, ...empties, ...kept); + + combo++; + const pts = (LINE_POINTS[count] + (combo > 0 ? 50 * combo : 0)) * level; + score += pts; + lines += count; + level = Math.floor(lines / 10) + 1; + updateUI(); + + flashLines(flashRowArr); // purely visual +} + +function updateGhost() { + if (!current) return; + ghost = { ...current }; + while (valid(ghost, 1)) ghost.row++; +} + +// ═══════════════════════════════════════════════════════════════ +// CONTROLS +// ═══════════════════════════════════════════════════════════════ +function moveLeft() { tryMove(0, -1); } +function moveRight() { tryMove(0, 1); } +function softDrop() { + if (tryMove(1, 0)) { + score += SOFT_DROP_PTS; + updateUI(); + } +} + +function tryMove(dr, dc) { + if (!current || gameOver || paused) return false; + if (valid(current, dr, dc)) { + current.row += dr; + current.col += dc; + updateGhost(); + extendLock(); + return true; + } + return false; +} + +function rotateCW() { rotate( 1); } +function rotateCCW() { rotate(-1); } + +function rotate(dir) { + if (!current || gameOver || paused) return; + const newRot = ((current.rot + dir) + 4) % 4; + const kickTable = current.type === 'I' ? KICKS['I'] : KICKS['standard']; + const key = `${current.rot}${newRot}`; + const kicks = kickTable[key] || [[0, 0]]; + for (const [kr, kc] of kicks) { + if (valid(current, kr, kc, newRot)) { + current.row += kr; + current.col += kc; + current.rot = newRot; + updateGhost(); + extendLock(); + return; + } + } +} + +function hardDrop() { + if (!current || gameOver || paused) return; + let dropped = 0; + while (valid(current, 1)) { current.row++; dropped++; } + score += dropped * HARD_DROP_PTS; + updateUI(); + clearTimeout(lockTimer); lockTimer = null; + lock(current); +} + +function holdPiece() { + if (!current || !canHold || gameOver || paused) return; + if (held) { + const prev = held; + held = current.type; + current = createPiece(prev); + if (current.type === 'I') current.row = -1; + } else { + held = current.type; + current = spawnPiece(); + } + canHold = false; + updateGhost(); + drawHold(); +} + +function extendLock() { + // If the piece is grounded, reset lock timer (up to LOCK_MOVES times) + if (!valid(current, 1) && lockMoved < LOCK_MOVES) { + lockMoved++; + clearTimeout(lockTimer); + lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY); + } +} + +// ═══════════════════════════════════════════════════════════════ +// GAME LOOP +// ═══════════════════════════════════════════════════════════════ +function gameLoop(ts) { + if (gameOver) return; + animId = requestAnimationFrame(gameLoop); + + if (!lastTime) lastTime = ts; + const dt = ts - lastTime; + lastTime = ts; + + if (!paused) { + dropTimer += dt; + const interval = levelSpeed(level); + if (dropTimer >= interval) { + dropTimer -= interval; + // Attempt to fall + if (valid(current, 1)) { + current.row++; + updateGhost(); + } else { + // Start lock delay if not already running + if (!lockTimer) { + lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY); + } + } + } + } + + draw(); +} + +function triggerGameOver() { + gameOver = true; + clearTimeout(lockTimer); + cancelAnimationFrame(animId); + drawBoard(); // final frame + showOverlay('GAME OVER', `Score: ${score} | Level: ${level} | Lines: ${lines}`, 'Play Again'); +} + +// ═══════════════════════════════════════════════════════════════ +// RENDERING +// ═══════════════════════════════════════════════════════════════ +const canvas = document.getElementById('board'); +const ctx = canvas.getContext('2d'); +const nextCvs = document.getElementById('next-canvas'); +const nextCtx = nextCvs.getContext('2d'); +const holdCvs = document.getElementById('hold-canvas'); +const holdCtx = holdCvs.getContext('2d'); + +let flashRows = []; +let flashTimer = 0; +const FLASH_DUR = 320; + +function flashLines(rows) { + flashRows = rows; + flashTimer = FLASH_DUR; +} + +function draw() { + drawBoard(); + drawNext(); + drawHold(); +} + +function drawBoard() { + // Background + ctx.fillStyle = '#090918'; + ctx.fillRect(0, 0, canvas.width, canvas.height); + + // Grid lines (subtle) + ctx.strokeStyle = '#12122a'; + ctx.lineWidth = 0.5; + for (let c = 1; c < COLS; c++) { + ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke(); + } + for (let r = 1; r < ROWS; r++) { + ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke(); + } + + // Settled board cells + for (let r = 0; r < ROWS; r++) { + for (let c = 0; c < COLS; c++) { + if (board[r][c]) { + drawCell(ctx, r, c, COLORS[board[r][c]], 1, 0, 0); + } + } + } + + // Flash overlay + if (flashTimer > 0 && !paused) { + flashTimer -= 16; + const alpha = 0.7 * (flashTimer / FLASH_DUR); + ctx.fillStyle = `rgba(255,255,255,${alpha})`; + flashRows.forEach(r => { + ctx.fillRect(0, r * BLOCK, canvas.width, BLOCK); + }); + if (flashTimer <= 0) flashRows = []; + } + + if (paused) { + ctx.fillStyle = 'rgba(5,5,20,0.7)'; + ctx.fillRect(0, 0, canvas.width, canvas.height); + ctx.fillStyle = '#fff'; + ctx.font = 'bold 28px system-ui'; + ctx.textAlign = 'center'; + ctx.fillText('PAUSED', canvas.width / 2, canvas.height / 2); + ctx.font = '13px system-ui'; + ctx.fillStyle = '#8888cc'; + ctx.fillText('Press P to resume', canvas.width / 2, canvas.height / 2 + 32); + return; + } + + if (!current) return; + + // Ghost piece + if (ghost && (ghost.row !== current.row || ghost.col !== current.col)) { + cells(ghost).forEach(([r, c]) => { + if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], GHOST_ALPHA, 0, 0); + }); + } + + // Active piece + cells(current).forEach(([r, c]) => { + if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], 1, 0, 0); + }); +} + +function drawCell(context, row, col, color, alpha, offR, offC) { + const x = (col + offC) * BLOCK; + const y = (row + offR) * BLOCK; + const s = BLOCK - 1; + + context.save(); + context.globalAlpha = alpha; + + // Main fill with gradient + const grad = context.createLinearGradient(x, y, x + s, y + s); + grad.addColorStop(0, lighten(color, 40)); + grad.addColorStop(1, darken(color, 30)); + context.fillStyle = grad; + context.fillRect(x + 1, y + 1, s - 1, s - 1); + + // Highlight edge (top-left) + context.fillStyle = lighten(color, 60); + context.fillRect(x + 1, y + 1, s - 1, 2); + context.fillRect(x + 1, y + 1, 2, s - 1); + + // Shadow edge (bottom-right) + context.fillStyle = darken(color, 50); + context.fillRect(x + 1, y + s - 2, s - 1, 2); + context.fillRect(x + s - 2, y + 1, 2, s - 1); + + context.restore(); +} + +function drawMiniPiece(context, cvs, type) { + context.fillStyle = '#0d0d1f'; + context.fillRect(0, 0, cvs.width, cvs.height); + if (!type) return; + + const shape = PIECES[type][0]; + const minR = Math.min(...shape.map(([r]) => r)); + const maxR = Math.max(...shape.map(([r]) => r)); + const minC = Math.min(...shape.map(([, c]) => c)); + const maxC = Math.max(...shape.map(([, c]) => c)); + const h = maxR - minR + 1; + const w = maxC - minC + 1; + const bs = 20; + const startX = Math.floor((cvs.width - w * bs) / 2); + const startY = Math.floor((cvs.height - h * bs) / 2); + + shape.forEach(([r, c]) => { + const px = startX + (c - minC) * bs; + const py = startY + (r - minR) * bs; + const s = bs - 1; + + const color = COLORS[PIECE_IDX[type]]; + const grad = context.createLinearGradient(px, py, px + s, py + s); + grad.addColorStop(0, lighten(color, 40)); + grad.addColorStop(1, darken(color, 30)); + context.fillStyle = grad; + context.fillRect(px + 1, py + 1, s - 1, s - 1); + + context.fillStyle = lighten(color, 60); + context.fillRect(px + 1, py + 1, s - 1, 2); + context.fillRect(px + 1, py + 1, 2, s - 1); + + context.fillStyle = darken(color, 50); + context.fillRect(px + 1, py + s - 2, s - 1, 2); + context.fillRect(px + s - 2, py + 1, 2, s - 1); + }); +} + +function drawNext() { + const w = nextCvs.width; + const h = nextCvs.height; + nextCtx.fillStyle = '#0d0d1f'; + nextCtx.fillRect(0, 0, w, h); + + const slotH = h / 3; + nextQueue.forEach((type, i) => { + const shape = PIECES[type][0]; + const minR = Math.min(...shape.map(([r]) => r)); + const maxR = Math.max(...shape.map(([r]) => r)); + const minC = Math.min(...shape.map(([, c]) => c)); + const maxC = Math.max(...shape.map(([, c]) => c)); + const ph = maxR - minR + 1; + const pw = maxC - minC + 1; + const bs = i === 0 ? 20 : 16; + const startX = Math.floor((w - pw * bs) / 2); + const baseY = i * slotH + Math.floor((slotH - ph * bs) / 2); + + shape.forEach(([r, c]) => { + const px = startX + (c - minC) * bs; + const py = baseY + (r - minR) * bs; + const s = bs - 1; + const color = COLORS[PIECE_IDX[type]]; + const alpha = i === 0 ? 1 : 0.65 - i * 0.1; + + nextCtx.save(); + nextCtx.globalAlpha = alpha; + const grad = nextCtx.createLinearGradient(px, py, px + s, py + s); + grad.addColorStop(0, lighten(color, 40)); + grad.addColorStop(1, darken(color, 30)); + nextCtx.fillStyle = grad; + nextCtx.fillRect(px + 1, py + 1, s - 1, s - 1); + nextCtx.fillStyle = lighten(color, 60); + nextCtx.fillRect(px + 1, py + 1, s - 1, 2); + nextCtx.fillRect(px + 1, py + 1, 2, s - 1); + nextCtx.fillStyle = darken(color, 50); + nextCtx.fillRect(px + 1, py + s - 2, s - 1, 2); + nextCtx.fillRect(px + s - 2, py + 1, 2, s - 1); + nextCtx.restore(); + }); + }); +} + +function drawHold() { + drawMiniPiece(holdCtx, holdCvs, held); + if (!canHold && held) { + holdCtx.fillStyle = 'rgba(0,0,0,0.5)'; + holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height); + } +} + +// ═══════════════════════════════════════════════════════════════ +// UI +// ═══════════════════════════════════════════════════════════════ +const scoreEl = document.getElementById('score-display'); +const levelEl = document.getElementById('level-display'); +const linesEl = document.getElementById('lines-display'); +const levelBar = document.getElementById('level-bar'); +const comboBox = document.getElementById('combo-box'); +const comboDis = document.getElementById('combo-display'); + +function updateUI() { + scoreEl.textContent = score.toLocaleString(); + levelEl.textContent = level; + linesEl.textContent = lines; + const pct = ((lines % 10) / 10) * 100; + levelBar.style.width = pct + '%'; + + if (combo > 0) { + comboBox.style.display = 'block'; + comboDis.textContent = 'x' + (combo + 1); + } else { + comboBox.style.display = 'none'; + } +} + +// ═══════════════════════════════════════════════════════════════ +// OVERLAY +// ═══════════════════════════════════════════════════════════════ +const overlay = document.getElementById('overlay'); +const startBtn = document.getElementById('start-btn'); + +function showOverlay(title, msg, btnText) { + overlay.querySelector('h2').textContent = title; + overlay.querySelector('p').innerHTML = msg; + startBtn.textContent = btnText; + overlay.style.display = 'flex'; +} + +function hideOverlay() { + overlay.style.display = 'none'; +} + +startBtn.addEventListener('click', () => { + hideOverlay(); + initGame(); + lastTime = null; + started = true; + animId = requestAnimationFrame(gameLoop); +}); + +// ═══════════════════════════════════════════════════════════════ +// KEYBOARD +// ═══════════════════════════════════════════════════════════════ +const DAS_DELAY = 170; // ms before auto-repeat +const DAS_REPEAT = 50; // ms between repeats + +let dasKey = null, dasTimer = null, dasRepeat = null; + +function startDAS(key) { + if (dasKey === key) return; + stopDAS(); + dasKey = key; + applyKey(key); + dasTimer = setTimeout(() => { + dasRepeat = setInterval(() => applyKey(key), DAS_REPEAT); + }, DAS_DELAY); +} + +function stopDAS(key) { + if (key && dasKey !== key) return; + clearTimeout(dasTimer); + clearInterval(dasRepeat); + dasKey = null; +} + +function applyKey(key) { + if (key === 'ArrowLeft') moveLeft(); + if (key === 'ArrowRight') moveRight(); + if (key === 'ArrowDown') softDrop(); +} + +window.addEventListener('keydown', e => { + if (!started) return; + + // Pause toggle + if (e.code === 'KeyP') { + if (gameOver) return; + paused = !paused; + if (!paused) { lastTime = null; } + return; + } + + if (paused || gameOver) return; + + switch (e.code) { + case 'ArrowLeft': e.preventDefault(); startDAS('ArrowLeft'); break; + case 'ArrowRight': e.preventDefault(); startDAS('ArrowRight'); break; + case 'ArrowDown': e.preventDefault(); startDAS('ArrowDown'); break; + case 'ArrowUp': e.preventDefault(); rotateCW(); break; + case 'KeyX': e.preventDefault(); rotateCW(); break; + case 'KeyZ': e.preventDefault(); rotateCCW(); break; + case 'Space': e.preventDefault(); hardDrop(); break; + case 'KeyC': e.preventDefault(); holdPiece(); break; + } +}); + +window.addEventListener('keyup', e => { + if (['ArrowLeft','ArrowRight','ArrowDown'].includes(e.code)) { + stopDAS(e.code); + } +}); + +// ═══════════════════════════════════════════════════════════════ +// COLOUR HELPERS +// ═══════════════════════════════════════════════════════════════ +function parseHex(hex) { + const n = parseInt(hex.replace('#',''), 16); + return [(n >> 16) & 255, (n >> 8) & 255, n & 255]; +} +function toHex([r, g, b]) { + return '#' + [r, g, b].map(v => Math.min(255, Math.max(0, v)).toString(16).padStart(2,'0')).join(''); +} +function lighten(hex, amt) { return toHex(parseHex(hex).map(v => v + amt)); } +function darken(hex, amt) { return toHex(parseHex(hex).map(v => v - amt)); } + +// ═══════════════════════════════════════════════════════════════ +// INITIAL RENDER +// ═══════════════════════════════════════════════════════════════ +(function initialDraw() { + ctx.fillStyle = '#090918'; + ctx.fillRect(0, 0, canvas.width, canvas.height); + // subtle grid + ctx.strokeStyle = '#12122a'; + ctx.lineWidth = 0.5; + for (let c = 1; c < COLS; c++) { + ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke(); + } + for (let r = 1; r < ROWS; r++) { + ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke(); + } + holdCtx.fillStyle = '#0d0d1f'; holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height); + nextCtx.fillStyle = 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/eval_results.json @@ -0,0 +1,249 @@ +{ + "structural": { + "pass": false, + "checks": [ + { + "name": "entry_point_exists", + "pass": false, + "detail": "no index.html found in workspace root, dist/, or public/" + }, + { + "name": "package_json_exists", + "pass": true, + "detail": "package.json found" + }, + { + "name": "build_succeeds", + "pass": true, + "detail": "no build script defined (static project)" + } + ], + "score": 0.67 + }, + "functional": { + "pass": false, + "error": "playwright eval not yet wired", + "score": 0 + }, + "quality": { + "lint": { + "pass": true, + "errors": 0, + "warnings": 0 + }, + "typecheck": { + "pass": true, + "note": "not applicable for javascript" + }, + "performance": { + "bundle_size_bytes": 0, + "size_under_512kb": true + }, + "score": 0.67 + }, + "code_analysis": { + "files": { + "total": 2, + "code": 0, + "docs": 0, + "unnecessary": 0, + "unnecessary_list": [] + }, + "lines_of_code": 0, + "dependencies": { + "production": 0, + "dev": 3, + "total": 3 + }, + "complexity": "minimal", + "console_logs": 0, + "magic_numbers": { + "count": 0, + "excessive": false + }, + "function_length": { + "count": 0, + "average": 0, + "max": 0, + "long_functions": 0 + }, + "max_nesting_depth": 0, + "global_declarations": 0, + "naming": { + "dominant_style": "unknown", + "consistency_pct": 100.0, + "camel_case": 0, + "snake_case": 0 + }, + "error_handling": { + "try_catch_blocks": 0, + "has_error_handling": false + }, + "comments": { + "comment_lines": 0, + "source_lines": 0, + "ratio_pct": 0.0 + }, + "separation_of_concerns": { + "verdict": "single-file", + "files_with_rendering": 0, + "files_with_logic": 0, + "files_with_both": 0 + }, + "html_validation": { + "valid": false, + "errors": 0 + }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 7, + "tool_calls": { + "total": 1, + "bash": 1, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 0, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 19 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.67 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/gameplay-bot-report.json diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "javascript", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1", + "run_number": 1, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:07:02.563152+00:00", + "wall_time_seconds": 857, + "exit_code": 1, + "completed_at": "2026-04-04T09:21:27.378605+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/transcript.jsonl @@ -0,0 +1,7 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "javascript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse JavaScript (no TypeScript)."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-oldyixfl","session_id":"aeab7f29-fa12-46aa-9566-03046f5a1eb0","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"0f3c1a2c-76c4-4bb1-a34f-e51fb09f4c55","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01DHZey2vA1B3V7VL2RxgA1X","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser using JavaScript (no TypeScript). Let me build a complete, well-designed Tetris game with:\n\n1. All standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls\n\nLet me create a single HTML file with embedded CSS and JavaScript for easy browser use.\n\nI'll design this with:\n- A canvas-based game\n- Nice visual styling\n- Ghost piece (shadow showing where piece will land)\n\n\n- Next piece preview\n- Score, level, and lines display\n- Keyboard controls: Arrow keys for movement, Up arrow or X for rotation, Space for hard drop, P for pause\n\nNow I'm building the complete HTML structure with embedded CSS and JavaScript...\n\nI'm defining the standard Tetris board as a 10x20 grid and setting up the seven tetrominoes with their distinct colors and rotation patterns...\n\nNow I'm outlining the control scheme and scoring system where clearing multiple lines gives exponentially higher points multiplied by the current level, with difficulty ramping up every 10 lines cleared.\n\nI'll build this as a single HTML file and structure the code around core game mechanics: managing the board state, handling piece movement and rotation, detecting line clears, and updating the score and level accordingly. Writing the HTML/CSS layout... Still writing styles... Writing the HTML structure and game logic... Defining the piece rotations... Defining the rotation states for the remaining Tetris pieces... I'm going back and forth on the best way to represent the piece rotations—I could use coordinate offsets, string encoding, or matrices. Let me just settle on a matrix approach and write out a clean implementation that actually works.\n\nDefining tetromino shapes...\n\nNow I need to think through the coordinate system—the board is 10 columns by 20 rows, and each piece occupies a 4×4 matrix where I map the filled cells onto the board using the piece's position plus the row and column offsets from the matrix. I'll structure this as a single HTML file with clean, organized code.\n\nSetting up the UI with a canvas for the main game board at 300×600 pixels (30-pixel cells), another canvas for previewing the next piece, and HTML elements to display the score, level, and line count. I'm going for a dark theme to keep it visually clean.\n\nFor rotation, I'll implement basic wall kick logic—if a rotation fails at the current position, I'll try shifting the piece left or right before rejecting the move entirely. This makes the rotation feel more natural without overcomplicating things.\n\nWriting the complete implementation... Defining the Tetris piece shapes... Defining the remaining Tetris piece configurations... Defining the game state variables... Setting up game initialization and piece spawning...\n\nNow I'm implementing the collision detection system to check if a piece can occupy a given position, validating against board boundaries and existing blocks.\n\nSetting up piece movement controls that check validity before shifting the piece left or right, and handling soft drops with score bonuses while locking pieces when they can't move down further.\n\nImplementing hard drop mechanics that instantly move pieces to their lowest position while awarding points based on distance dropped, then handling rotation with wall kick offsets to allow pieces to rotate even when partially blocked. Finishing the piece locking logic and implementing the line-clearing system that removes completed rows, updates the score based on how many lines were cleared and the current level, then spawns the next piece...\n\nNow I'm working on the ghost piece visualization to show where the current piece will land, and setting up the drawing functions to render blocks with color and transparency. Writing the render loop... Finishing the ghost piece rendering...","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4729,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":4729,"ephemeral_1h_input_tokens":0},"output_tokens":0,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"aeab7f29-fa12-46aa-9566-03046f5a1eb0","uuid":"f9efd4de-f970-455f-be0e-e3d3255bc0e4"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01CezgtXj1iYybgsNWREhifs","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using JavaScript. Let me build a complete, well-structured Tetris game with:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z/X for rotation)\n7. Game over detection\n8. Next piece preview\n9. Level display\n\nLet me create a single HTML file with embedded CSS and JavaScript.\n\n\nI'll structure this with a canvas for the game board, a side panel showing score, level, lines cleared, and the next piece preview, plus a game over overlay. For the styling, I'm going with a dark retro aesthetic with distinct colors for each piece type. The JavaScript will handle all the game logic—piece definitions with their rotation states, game state management, keyboard input, collision detection, line clearing, and a game loop using requestAnimationFrame.\n\nNow I'm defining the seven Tetromino pieces with their colors and setting up the scoring system where clearing multiple lines gives exponential bonuses multiplied by the current level. The game will start with pieces dropping every second and accelerate every 10 lines cleared. For controls, I'm mapping arrow keys for movement and rotation, space for hard drop, and P to pause.\n\nWriting the game code... Setting up the game constants and piece definitions... Now I'm thinking through the rotation mechanics—I'll transpose the matrix and reverse rows for clockwise rotation, with the opposite approach for counter-clockwise. I'm also planning to add wall kick functionality so pieces can nudge left or right if they hit the edge during rotation, plus a ghost piece that shows where the current piece will land. For the full game, I'm building out a complete HTML interface with a dark gradient background and polished UI.\n\nWriting the HTML and CSS... Still writing styles... Styling the start button with a pink accent color, hover effects, and monospace font, then adding control instructions below the game board...\n\nBuilding the HTML structure... Writing the game logic... Defining the tetromino pieces... Defining the piece rotations... Defining the game mechanics... Finishing up the wall kick data for the I-piece, then setting up the core game functions to initialize the board and spawn new pieces with proper positioning and rotation states.\n\nNow I'm reconsidering how to handle piece spawning more carefully. The key is centering pieces correctly on the 10-column board—most pieces fit in a 3x3 space while the I-piece needs 4 columns, so I can calculate the starting x position by centering the piece's width. I'll simplify the piece object to just track the shape matrix, rotation state, and position coordinates. I'm working through the spawn position for pieces — starting them at y = -1 (one row above the visible board) makes sense because it matches standard Tetris behavior where pieces like the I piece have their active cells positioned so they appear correctly when the board row calculation happens.\n\nActually, I could simplify this by just spawning at y = 0 and triggering game over when a newly placed piece immediately collides with existing pieces on the board. Let me set pieces to spawn from y = -2 to give them room to emerge from the top, then write out the complete implementation with the standard rotation matrices for each piece type.\n\nWriting piece rotation logic... Writing collision detection logic... Writing the collision detection logic... Writing game mechanics... Still writing rotation logic... Writing the render function... Writing the cell rendering... Writing the piece preview renderer... I'm ready to finalize the code and make sure everything works smoothly together. For line clearing, I'll keep it simple and just remove completed lines instantly without animation for now. I'm also implementing a standard 7-bag randomizer for piece selection, where each set of all 7 piece types gets shuffled and dealt out in order.\n\nImplementing the bag system...\n\nFor piece locking, I'll go with the straightforward approach where pieces lock immediately when they can't move down anymore, though players can still shift them sideways before the next gravity tick. Input handling will use key repeat for smooth left and right movement, though I might skip the full DAS implementation initially to keep things manageable.\n\nNow I'm thinking about the visual polish—adding cell gradients with highlights and shadows, grid lines, a ghost piece outline, a nice color palette, and maybe some effects like line clear flashes. I'll use 30px cells for the main 300×600 board and 24px cells for the next piece preview in a 4×4 area.\n\nWriting the complete implementation...\n\nI want to make sure the core mechanics work: piece rotation with wall kicks, ghost piece rendering, hard drop, line clearing with scoring, level progression, 7-bag randomizer, lock detection, and a game over screen with restart. I'm skipping sound to keep things simple and focusing on visual feedback instead.\n\nFor lock delay, I could implement a system where the piece waits before locking after hitting the ground, resetting if it moves or rotates—but that adds complexity I don't need right now, so I'll keep the simpler approach where pieces lock immediately when they can't fall further.\n\nThe game loop timing works well with gravity ticking at intervals based on level speed: slower at lower levels (800ms at level 1) and faster at higher levels (125ms at level 10), which naturally gives players less reaction time as difficulty increases. I'll add a score multiplier display for line clears and maybe a \"Tetris!\" message for clearing four lines at once.\n\nWriting the code now...\n\nAdding 3D cell rendering... Writing the cell rendering function...\n\nNow I'm moving on to write out the complete HTML file with all the final decisions locked in—a 10×20 game board with 30-pixel cells, using this 3D beveled effect for the visual polish. I'm deciding between the classic Nintendo scoring and the modern Tetris guideline system—I'll go with the guideline version since it's more standard. For the drop speed, I'm calculating a formula that starts at 1000ms for level 1 and decreases progressively, capping out at 50ms for the highest levels. Writing the complete Tetris implementation...\n\nNow I'm thinking through the next piece preview canvas—I need to handle the different tetromino shapes which have varying dimensions, so I'll normalize everything to a 4×4 grid and center each piece within it. I'm settling on a 120×100 canvas with 22px cells to give enough breathing room around the preview.\n\nWriting the preview rendering logic...\n\nNow I'm thinking through the complete implementation and realizing I should skip the hold piece feature to keep things simpler, but I do want to add proper keyboard handling with DAS (Delayed Auto Shift) so the game feels responsive when holding left or right—there'll be an initial delay before the piece starts auto-repeating, then it moves at a faster rate.\n\nSetting up the keyboard input system...\n\nI'm realizing the DAS (Delayed Auto Shift) implementation with separate timers is getting unwieldy, so I'm switching to a simpler approach where I track which keys are currently held in a Set and handle the repeat logic in the game loop instead. This way I can manage the timing more cleanly with just a couple of counters for left and right movement.\n\nSetting up event listeners... I'm realizing the DAS approach is getting too complicated, so I'll simplify by using the browser's native `keydown` event with the `repeat` property to handle continuous key presses automatically instead of manually tracking timers.\n\nSetting up the complete HTML file now...\n\nActually, I'm realizing the browser's native key repeat is too slow for a responsive Tetris game—it has that initial delay and then a sluggish repeat rate. I need to track which keys are currently held down and handle the repeat timing myself in the game loop, with a shorter initial delay and faster repeat rate for smooth movement.\n\nSetting up the key event handlers... Writing the input handler... Writing the complete implementation... I'm reconsidering the line clearing logic—the splice approach could mess with indices, so I'll rebuild the board by filtering out completed rows and padding with empty rows at the top instead. This is cleaner and avoids index shifting issues.\n\nNow I want to add a visual flash effect when lines clear. I'm tracking which rows are full and setting a flash timer so the cleared rows briefly highlight before disappearing, rather than vanishing instantly.\n\nAdding flash effect logic...\n\nActually, that's getting complicated. Let me just clear lines instantly for now and keep the implementation simple—if the game feels good without the animation, I don't need it.\n\nNow I'm finalizing everything. I'm storing the high score in localStorage so it persists between sessions, and I'm structuring the HTML with a title, game container with the canvas, and an overlay for UI elements.\n\nWriting the complete implementation... Still writing styles... Still writing styles... Building the game interface... Setting up the game controls and constants... Defining the tetromino piece shapes... Defining the Tetris piece rotations... Setting up the game state variables for board, pieces, score, and timing, then grabbing references to the canvas elements and their 2D contexts for rendering. Still writing initialization code... Setting up wall kick data for rotations...\n\nNow I'm implementing the rotation logic, checking if a piece can rotate by testing the new rotation state and applying wall kicks if the initial rotation fails. Implementing piece movement and soft drop mechanics... Continuing with the piece locking logic...\n\nNow I'm handling line clearing—iterating from the bottom up, removing any complete rows and shifting everything down, then calculating points based on how many lines were cleared and the current level. After that, I check if the piece locked above the play area, which means game over. Otherwise, I spawn the next piece.\n\nFor spawning, I'm creating a new piece from the queue, pulling the next type from the bag system, and resetting the lock delay and drop timer. If the new piece immediately collides with existing blocks, the game ends. Then I update the next piece preview.\n\nWriting ghost piece logic... Writing the rendering logic... Drawing the placed blocks and ghost piece...\n\nNow I'm rendering the current falling piece on top, then moving on to draw the next piece preview in its own canvas.\n\nFor the next piece display, I'm clearing the preview canvas and getting the shape data for whichever piece is coming up. I calculate the centered position so it displays nicely in the preview area, then loop through the shape and draw each filled cell with the appropriate color.\n\nAfter that, I'm updating the HUD to show the current score. Writing game initialization and end-game logic... Writing game loop logic... Setting up the input handlers for game controls—checking if the game is paused and routing keyboard inputs to the appropriate movement and rotation functions, with special handling to prevent repeated inputs on certain actions like rotation and hard drop.\n\nNow I'm realizing there's a logic issue with the lock delay system: when a piece lands on the ground, I'm decrementing the lock delay counter, but I also reset it whenever the piece moves successfully. I need to reconsider how these interact—specifically, what happens when the piece is grounded and the gravity timer fires simultaneously. piece. This is correct.\n\n3. But there's a conflict: I also have `dropTimer` for gravity. If the piece is on the ground, I shouldn't try to drop it via gravity. My current code handles this with the `if (onGround)` check - if on ground, we handle lock delay instead of gravity drop. If not on ground, handle gravity. This looks correct.\n\nWait, but there's another issue: if piece is NOT on ground, I handle gravity. But what if after the gravity drop, the piece is now on ground? I should start the lock delay timer then, but in the next frame, it will detect `onGround = true` and start counting down the lock delay. That's fine.\n\nActually wait, I need to re-examine. Let me trace through the sequence: piece falls via gravity until it hits the ground, then the lock delay countdown begins. If the player moves or rotates the piece while it's grounded, the lock delay resets, giving them another 500ms window. I'm initializing the lock delay in `spawnPiece` and resetting it in both `tryMove` and `tryRotate` when the piece is on ground. This should work correctly. Refining the lock delay logic...\n\nI'm realizing the lock delay should only count down when the piece is actually on the ground—when it's falling through empty space, the timer shouldn't be active. The reset behavior makes sense: when gravity moves the piece down and it's no longer touching ground, both the delay and reset counter should reset so the piece gets a fresh lock delay window once it lands again.\n\nThere's a timing issue though—the drop timer keeps accumulating every frame regardless of whether the piece is grounded, so when a new piece spawns after locking, that accumulated timer could cause it to drop immediately. I need to reset the drop timer the moment the piece first makes contact with the ground.\n\nActually, wait—I'm already resetting it in `spawnPiece`, so when the next piece spawns after locking, the timer starts fresh. The accumulated value from the previous piece doesn't carry over. This should be fine.\n\nBut there's another concern: when `onGround` is true and `lockDelay` is still counting down, both `lockDelay` and `dropTimer` are ticking. Once `lockDelay` expires and the piece locks, `spawnPiece` resets `dropTimer` to zero, so the new piece gets a clean slate. That works.\n\nNow I'm tracing through the game-over flow more carefully. When `lockPiece` is called, line clearing happens first, then `spawnPiece` is invoked. Inside `spawnPiece`, if the new piece immediately collides, `endGame` is called and sets `gameActive` to false. Back in `lockPiece`, after `spawnPiece` returns, `gameActive` is already false, so the function just returns. Then the main loop continues but should stop processing since the game is no longer active.\n\nI'm also verifying the scoring system—soft drops award 1 point per press and hard drops award 2 points per row, which aligns with standard Tetris rules.\n\nFor line clears, the point multiplier scales with level, so the scoring formula accounts for difficulty progression correctly.\n\nLevel advancement follows the standard 10-lines-per-level progression, which checks out.\n\nNow I'm reviewing the rotation kick logic for counterclockwise rotations to make sure the wall kick offsets are being applied properly. I'm realizing the O piece needs special handling since all its rotations are identical—I should just return early and skip the rotation logic entirely for that piece type. I'll return early for the O piece to avoid the undefined kicks issue, then move on to handling the I piece kick data for counter-clockwise rotations in the SRS system. I'm working through the SRS kick offset logic for counter-clockwise rotations. For CCW, I need to use the negated kicks from the next rotation state—so when rotating from state `rotation` to `newRot = (rotation + 3) % 4`, I apply the negative of `KICKS_I[newRot]`. Now I'm implementing this in the code by selecting the appropriate kick set based on rotation direction.\n\nLet me verify this matches the standard SRS spec with a concrete example: rotating CW from 0→1 uses the kicks for state 0, while rotating CCW from 1→0 uses the negated kicks for state 0, which gives me the correct offset values that match the official specification.\n\nNow I'm checking the JLSTZ piece kicks to make sure they follow the same pattern.\n\nI need to verify the coordinate system—whether Y increases downward in my implementation matches the SRS documentation, which typically uses Y positive upward. Let me trace through a concrete rotation example to see if the kicks are working correctly. I'm checking the coordinate system against the standard SRS documentation to make sure my kick offsets are correct—the wiki shows positive y values going up in their notation, but my board uses positive y going down, so I need to verify whether I should be negating the dy values when applying these kicks. I'm realizing the coordinate system conversion is tricky—different Tetris implementations handle the SRS kicks differently, and I'm getting confused about whether my y-axis negation is correct. Let me just stick with negating the y component like most implementations do and test it empirically to see if the rotations actually work as expected.\n\nUpdating the kick tables... Defining kick offset data for I-piece rotations...\n\nI need to step back and think about what the I piece actually looks like in each rotation state. When it's horizontal in the initial state, it occupies a single row, and I should verify these kick offsets make physical sense for how the piece moves through rotations. of the matrix has all 4 cells.\nThe I piece in state 1 is vertical: column 2 (0-indexed) of the matrix has all 4 cells.\n\nWhen you rotate from state 0 to state 1 (CW), the long piece goes from horizontal to vertical. \n\nIn the standard 4×4 grid, state 0 looks like:\n```\n....\nIIII\n....\n....\n```\n\nState 1 looks like:\n```\n..I.\n..I.\n..I.\n..I.\n```\n\nIf the piece is at position (px, py) = (3, 5) in state 0 (so the I bar is at row 6), after CW rotation it should become vertical. The natural rotation center is at column 4 (0-indexed), row 6.\n\nActually, the I piece rotation center in Tetris varies by implementation. In modern Tetris guidelines, it's at an offset center.\n\nThis is getting really complex. For a playable game, I'll use a simpler wall kick approach that works reasonably well even if it's not 100% SRS-compliant. I'm implementing a rotation function that tries the new rotation at the current position first, then attempts several wall kick offsets if that fails.\n\nImplementing wall kick logic... Defining wall kick offsets... I'm verifying the O piece positioning—it uses a 4-column matrix centered on the board, which places it at columns 4 and 5, keeping it properly centered. Let me finalize the implementation and stop second-guessing the details. Everything checks out. Now let me verify the S piece rotations I've defined—I'm looking at how each state represents the piece in different orientations, making sure the block positions match what I expect for an S tetromino. I'm applying the transpose-and-reverse method to rotate the S tetromino 90 degrees clockwise, which transforms the original 2×3 shape into a 3×2 vertical orientation. Let me verify this rotation is correct by checking that the four cells still form the proper S pattern in its rotated state. The classic S piece CW rotated looks like:\n```\nS.\nSS\n.S\n```\n\nIn a 3×3 matrix:\n```\nS..\nSS.\n.S.\n```\n\nThat would be:\n```\n4 0 0\n4 4 0\n0 4 0\n```\n\nBut my computed rotation gives:\n```\n0 4 0\n0 4 4\n0 0 4\n```\n\nThese are mirror images of each other. Hmm.\n\nThe issue is that the \"standard\" S piece states can be defined differently by different sources. The important thing is that the piece looks correct and the rotations are consistent.\n\nLet me use the \"official\" tetromino states from the Tetris Guideline. I'll map out all four rotation states for the S piece: the initial state, the clockwise rotation, the 180-degree rotation, and the counter-clockwise rotation. Each state has a specific matrix representation that I need to verify.\n\nNow I'm setting up the rotation tables based on the Tetris Guideline specifications... Defining the tetromino rotation states... Defining the remaining tetromino pieces... I'm verifying the rotation logic by manually applying a clockwise 90-degree rotation using transpose and row reversal, but I'm getting a different result than what I calculated before—the matrices don't match, so I need to figure out where the discrepancy is.\n\nLooking at the actual Tetris Guideline specifications for the S piece, I can see the spawn state and how it should appear in each rotation state, which clarifies the correct positioning within the 3×3 bounding box.\n\nThe issue is that my naive transpose-and-reverse approach produces a different result than what the Guideline specifies—it's rotating around the geometric center of the matrix rather than using the specific rotation center the Guideline defines for each piece.\n\nRather than trying to derive the rotation mathematically, using pre-defined rotation tables like I have in my PIECES definition sidesteps this complexity entirely by explicitly defining what each rotation state should look like.\n\nNow I'm looking up the standard Tetris Guideline rotation states for the S piece to get the exact configurations I need.\n\nFor the Z piece, I'm working through the clockwise rotations—starting with the horizontal orientation and rotating it 90 degrees to get the vertical form, then continuing through the full 360-degree cycle to establish all four states. I'm working through the Z-piece rotations more carefully now. Let me verify the clockwise rotation from state 0 by transposing and reversing rows, which gives me the correct state R configuration.\n\nLooking at how this positions the piece in the 3×3 bounding box, it ends up on the right side, which seems odd visually but aligns with the Tetris Guideline's rotation center definition. I'm realizing my computed rotation state should be mathematically correct according to the standard, though I'm second-guessing whether this positioning makes sense in practice.\n\nThe wall kick offsets from the guideline are specifically designed to work with this rotation center, so using the official rotation states alongside the SRS kicks should handle everything correctly together. I was wrong to doubt the transpose-and-reverse approach—that's exactly what the Guideline uses for J, L, S, T, and Z pieces. Let me recalculate all the rotation states properly by applying clockwise rotation repeatedly to each piece's starting position.\n\nFor the T piece, I'm working through the rotation states by transposing and reversing rows to get each successive clockwise rotation, then checking whether my computed state R matches what I'd expect from a standard T-spin configuration. CW 90°:\n```\nT..\nTT.\nT..\n```\n\nVisually: the stem of the T was pointing UP in state 0, after CW rotation it points LEFT. So the CW rotation should be:\n```\nT.\nTT\nT.\n```\n\nIn a 3×3 box, the leftmost column has all three T's and the middle-right has one T:\n```\nT..\nTT.\nT..\n```\n= `[[T,0,0],[T,T,0],[T,0,0]]` = `[[3,0,0],[3,3,0],[3,0,0]]`\n\nBut my computed result was `[[0,T,0],[0,T,T],[0,T,0]]` which is:\n```\n.T.\n.TT\n.T.\n```\n\nI see—this is the same rotated T shape, just offset to the right within the bounding box. The actual board position comes from the piece's coordinates, not the shape matrix itself, so both representations are valid as long as the relative cell positions match the rotation. The Tetris Guideline specifies rotation centers and SRS kick offsets relative to those centers, which determines the final placement. I'm working through the coordinate transformation for a 90° clockwise rotation in a 3×3 grid, mapping each cell's new position using the formula new_row = col and new_col = (N-1) - row.\n\nVerifying the result against my transpose-and-reverse approach, the filled cells at (1,2), (0,1), (1,1), and (2,1) produce the grid pattern `[[0,3,0],[0,3,3],[0,3,0]]`, which confirms the rotation is correct.\n\nNow I'm working through the rotation formulas for all tetromino pieces. For the I piece in a 4×4 grid, I need to apply the clockwise rotation transformation where a cell at (row, col) maps to (col, 3-row), which should place the horizontal line of four cells into a vertical column. I'm verifying the rotation transformations by checking each cell position. When rotating clockwise from state R, the cells at column 2 map to row 2 across all columns, giving me the horizontal line pattern I expected. The math checks out for state 2 as well.\n\nNow I'm doing the same verification for the left-facing state, where cells at row 2 should map to column 1 after applying the rotation formula, creating a vertical line. Both states match the expected patterns, so my I piece rotations are correct. Let me move on to checking the T piece.\n\nFor the T piece's second rotation state, I'm applying the clockwise rotation formula to the right-facing configuration, which transforms the cells into a downward-pointing T shape.\n\nThen rotating once more to get the left-facing state, I'm verifying that the cells align correctly to form a vertical T with the stem pointing left. I'm getting a discrepancy between my rotation formula and what the standard S piece should look like after a clockwise rotation. Let me reconsider whether I'm using the right transformation—the standard orientation shows the S piece rotated should be taller and narrower, which suggests my current result might be flipped or using the wrong rotation direction. Let me verify this rotation formula by working through the coordinates. For a clockwise rotation around the center point (1,1) in a 3×3 grid, the transformation should map (row, col) to (col, 2-row). Testing a few points confirms this is correct—the shape rotates as expected around the center rather than the corner.\n\nNow I'm visualizing what the S piece actually looks like after rotating 90 degrees clockwise from its initial state. The original S piece has a specific tetromino shape, and when I rotate it, the top-right portion moves to the right side while the bottom-left moves to the left side, creating the rotated configuration.\n\nI'm considering how this rotated piece fits within a 3×3 bounding box and realizing there are two valid representations depending on positioning—one shifted left and one shifted right. The key insight is that Tetris uses the center of the 3×3 box as the rotation point, which determines the final positioning of the piece.\n\nNow I'm computing all rotation states for each piece by applying the rotation transformation repeatedly, starting with the S piece and working through each state systematically. Now I'm applying the rotation transformation (row,col)→(col, 2-row) to each cell in state R, which maps the original positions to their new coordinates. After sorting these transformed cells by row and column, I get the grid representation for state 2: rows 1 and 2 contain the marked cells, with row 1 having columns 1 and 2, and row 2 having columns 0 and 1.\n\nContinuing this process, I'm rotating state 2 to get state L by applying the same transformation to its cells, which gives me a new configuration where the marked cells form a different pattern across all three rows. Continuing to work through the Z piece rotations by applying the transformation formula to track how cells shift between states. Continuing with the L piece rotation, I'm mapping out how the cells transform and building the grid representation. Now I'm working through all the Z piece rotations to establish the complete set of orientations.\n\nMoving on to the J piece, I'm applying the same rotation transformation to find its four states, starting with the initial configuration and rotating clockwise to determine each subsequent orientation. Now I'm tracking the state transitions through another rotation cycle, applying the left transformation to get the next configuration with cells positioned at (0,1), (1,1), (2,1), and (2,0). Continuing with the L piece rotations, I'm applying the same transformation to get the R state, which gives me cells at (2,2), (0,1), (1,1), and (2,1), forming the pattern where the vertical line shifts to the right with the bottom extending further. Continuing to apply the rotation transformations to get the L piece in its next orientation, mapping each cell through the rotation function and then visualizing the resulting grid pattern. I'm verifying my original rotation states against the computed ones to make sure they're all correct, and it looks like my S piece rotations were actually accurate from the start. I've verified all the rotation states for J and L pieces match my calculations—the original rotation matrices were correct all along.\n\nNow let me check the T piece rotations to make sure those are accurate too, and then I'll verify the O piece as well. I'm verifying the O piece spawns at the correct position—columns 4 and 5 on a 10-wide board, which matches standard Tetris. I'm also considering whether to use a simpler 2×2 matrix instead of the 4×3 approach, which would still center properly.\n\nWith a 2×2 matrix and y = -1 spawn position, the piece would start half above the board, which is typical for Tetris pieces. The 4×3 version with padding would also work, but the 2×2 is cleaner and achieves the same centering result. With y=-1, board rows are -1 and 0. Same issue.\n\nActually, wait. All pieces start at y=-1 in my spawn function. For pieces that have cells in row 0 of their matrix (like T with `.T.` at row 0), those cells would be at board row -1 (above board). Is that intentional?\n\nLet me reconsider the spawn position. Standard Tetris spawns pieces at row -1 (partially above the board) for the top of the piece, with the active cells starting at row 0. For example:\n- T piece (row 0 is `.T.`, row 1 is `TTT`): spawns at y=-1, so row 0 of piece is at board row -1 (invisible), row 1 is at board row 0 (visible top). So the T appears to have the bar at the top of the board.\n\nThat's correct Tetris behavior. For the I piece with y=-1, the empty row 0 stays invisible while the four cells in row 1 appear at the board's top. The O piece is trickier though—with its 3-row matrix starting at y=-1, the first row with cells ends up hidden above the board.\n\nI think I should use a 2×2 O piece instead, which would spawn at y=-1 with both rows visible starting at board row 0. That means calculating the spawn x-position as the center of the board minus half the piece width, which gives x=4 for a 10-column board. The O piece would occupy columns 4 and 5. over detection and wall kicks, having the piece be smaller (2×2 vs 3×4) might change behavior slightly. Let me think...\n\nFor the O piece with 2×2, when checking isValid, I check all 4 cells of the 2×2 matrix (all are filled). The boundaries are x=4 to x=5 (board columns), which is fine.\n\nFor wall kicks, I return early for O piece (it doesn't rotate), so wall kick data doesn't matter for O.\n\nOK, 2×2 O piece is fine. Let me update the spawn x calculation:\n\nActually, I realize I had it as `Math.floor((COLS - shape[0].length) / 2)`. For:\n- I (4-wide): 3\n- O (2-wide): 4\n- T, S, Z, J, L (3-wide): 3\n\nThese are all reasonable spawn positions.\n\nFor the O piece at x=4, columns 4,5 are used, which matches standard Tetris for a 10-wide board. ✓\n\nNow I need to finalize everything and write the complete file. I should use the SRS kicks since I've verified they're correctly defined, but I need to account for the y-direction convention—in SRS documentation y increases upward, while in my code it increases downward, so I'll need to negate the y component of each kick.\n\nDefining the SRS kick data... I need to verify my understanding of the SRS coordinate system—the x component is the column offset with rightward as positive, and y is the row offset with upward as positive. To convert to screen coordinates where down is positive, I simply negate the y values, so each offset pair [x, y] becomes [x, -y].\n\nLet me work through the conversion for the 0→R rotation state: the SRS offsets (-1, +1) and (0, -2) become (-1, -1) and (0, 2) in screen space, which makes physical sense for wall kicks—the first moves the piece up and left when kicked at the top-right, and the second handles floor kicks by moving down. Now I'll compile the complete kick offset tables for all pieces. Verifying the SRS to screen coordinate conversions for each rotation state—the y-axis negation is flipping the signs correctly, and I'm confirming that the offset values map properly across all four transitions. Verifying the coordinate transformations for the I-piece kicks by converting from SRS to screen coordinates, accounting for the y-axis flip where negative values represent upward movement.\n\nNow for the counter-clockwise rotations, I'm using the inverse of the clockwise kicks—negating the displacement values from the target rotation state to get the kicks needed for CCW movement.\n\nBut I'm noticing a discrepancy between my calculated kicks and what the standard SRS documentation shows for CCW R→0 transitions. Let me verify the correct kick sequence against the official Tetris wiki to make sure I have the right offsets. Verifying the formula works correctly for CCW rotations by negating the CW kick offsets. Now I'm confident the implementation is solid, so I'll write out the complete file, though I need to handle the O piece specially since it doesn't use rotation kicks.\n\nWriting the HTML file... I'm settling on a 300ms lock delay to give the game good feel, then writing out the complete HTML implementation with the canvas-based Tetris game, styling, and all the game logic.\n\nWriting the HTML and styles... Still writing styles... Writing the HTML markup... Setting up the game constants... Defining the tetromino shapes... Defining the remaining Tetris piece rotations... Defining the wall kick offsets for I-pieces and setting up the scoring system with points for cleared lines and soft/hard drops, then calculating the drop speed based on level.\n\nNow I'm setting up the DOM references for the game board canvas, next piece preview, and UI elements like score, level, and lines counters, plus the overlay for game over states.\n\nSetting up game state variables for the board, current piece, and game mechanics like score tracking, timers for piece locking, and localStorage for the best score. I'm also initializing the bag randomizer that shuffles through all piece types to ensure variety in spawning.\n\nImplementing collision detection to validate piece positions... Writing piece rotation logic... Writing the lock and spawn logic... Finishing the hard drop logic where I accumulate rows and award points accordingly, then I'm moving into the rendering functions to handle drawing individual blocks with support for ghost piece visualization using transparency and stroke effects.\n\nNow I'm adding the 3D bevel effect to solid blocks with highlight and shadow details...\n\nRendering the game board... Still writing the rendering logic... Now I'm setting up the HUD to display the current score, level, and line count, and checking if we've beaten the high score to update localStorage. Then I'm initializing the game board with an empty grid, filling the piece bag, and resetting the score and level to start fresh.\n\nI need to be careful with the piece spawning logic—I should draw one piece for the current active piece and another for the next preview, making sure the sequence is correct. I'm realizing the piece spawning logic needs to be clean: draw one piece for the current game piece, then draw another for the next preview. Now I'm thinking through the game loop timing and how the animation frame callback should handle the game state updates.\n\nWriting game loop logic... Still writing game logic... Refining the game loop logic...\n\nI need to handle the timing more carefully—checking whether the piece was grounded at the start of the frame versus after gravity applies, so I can properly initialize the lock timer when it first touches ground. Let me restructure the loop to track state changes more accurately. The logic here handles the lock timer correctly—when grounded, it counts down toward locking the piece, and when airborne, gravity takes over until the piece lands, at which point the lock timer resets. I'm thinking through an edge case where `drop()` might not actually move the piece even though `grounded()` initially returned false, but that shouldn't happen since both functions check the same validity conditions.\n\nNow I'm realizing that at very high levels, the gravity interval becomes so short that a piece might need to drop multiple cells in a single frame. I should use a loop that keeps dropping the piece as long as the accumulated drop timer exceeds the interval, breaking only if the drop fails—this ensures pieces fall at the correct speed even at extreme difficulty levels. At max level, the drop interval caps out at 50ms, which means the piece drops roughly every 3 frames at 60fps. The `while` loop handles multiple drops per frame if needed, though it's mostly a safety measure. The `Math.min(dt, 100)` cap prevents huge time jumps when the browser tab is inactive, which would otherwise cause the piece to skip multiple rows instantly. Now I need to finalize the HTML file and make sure the best score display is properly initialized.\n\nFor the pause feature, I'll toggle it with the P key and show an overlay with a \"PAUSED\" message and resume button. I should also render the initial board state so the empty grid displays behind the overlay when the game loads. Before writing the complete file, I'm double-checking the spawn positions for each piece type—the O piece uses a 2×2 matrix spawning at column 4, while the wider pieces spawn at column 3.\n\nWriting the complete HTML file... I'm verifying the S piece rotations by working through the clockwise and counterclockwise transformations manually—the state R rotation I have doesn't match what a proper 90° clockwise rotation should produce, so I need to recalculate which configuration actually corresponds to each rotation state. I'm confirming that the rotated state is correct—the grid `[[0,4,0],[0,4,4],[0,0,4]]` matches the visual representation with the piece rotated around the matrix center at (1,1). The SRS system uses this center point for rotation, so even though the piece appears shifted within the matrix, the positioning will be correct when placed on the board. That confirms the S piece rotation is correct—columns 5 and 6 with the right pattern. Now I'm ready to write out the complete Tetris game in a single HTML file.\n\nWriting the game code... me double-check the spawn orientation one more time to make sure players see the right thing:\n\nS piece state 0: `[[0,4,4],[4,4,0],[0,0,0]]`\nAt x=3, board columns:\n- Row 0: cols 3+1=4, 3+2=5 → .SS\n- Row 1: cols 3+0=3, 3+1=4 → SS.\n- Row 2: empty\n\nVisible pattern:\n```\n.SS (row 0 of piece, but starts at board row -1 since y=-1, so this is hidden initially)\nSS. (row 1 of piece, at board row 0 = visible top)\n```\n\nSo at spawn, player sees SS. at the top of the board, with .SS above it (hidden). On the next gravity tick, it drops to y=0 and both rows become visible. This matches standard Tetris behavior where only the bottom part shows initially. ✓\n\nZ piece state 0: `[[5,5,0],[0,5,5],[0,0,0]]`\nAt x=3:\n- Row 0: cols 3,4 → ZZ.\n- Row 1: cols 4,5 → .ZZ\n\nAt spawn (y=-1), row 0 is hidden, row 1 is at board row 0 (visible). Player sees `.ZZ` at top. ✓\n\nEverything checks out. Now I'm writing the final HTML file with the complete game implementation.\n\nWriting HTML 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0KmTkHuBs6ulPGrmyFTefs9KGPtvgWMsE2eleQC9FuSK4C/ceja/GqFCvoCbb9WyoLBwugpQrlnqqpK48r1vQKhUop/tncMiAIfoImmHadVxJzP6HTz4O5UNR6LNVbjPyvnriWWQcbiXQ7vEgPbjEgth/pTu1G2Y1/f51oah+hlH7WMrTW4tSwMzBB2xvi1aYO1i8QMB+IrXGYDIDvm+ViaKrnN9DgKv0fK1Ln9YofRBY5SwiiCkk6AGLGgH/Bcw4Do9Qynd2l24QwNOrLmrTnsR0r33bd1R4msIrvtzomZOlzP0HzdTFhCp5GwwEwEEshQurKJf+xWtOox01Qy3bq4RwoIQIcrrom9VMSXI/OoQ80+serX3/vfKBgkz3WzIiktBS1zlSFpqUz//OKCFzylurK5s9fa14OFOJU3EC8Piffyb3KcB3rj7+PvMQgg5oIY4nYliYyupak7pQBa6qj6OUNnLEmyiJDOYvGzxN6wtWseVWgPLLFKQRItwrimWkY50UMqH3jqrXbnVh0LdECSGxJ1ei4eK2TSOBbK7Day6YNM6bWaQODvtqaN+j76qtT3UgmAmKucJNXbmDOO4i+sXCU48kVd5c7zyWocqz2cFFqoyNWAMFOmqZakdEwck53NgpdxS2KXq4pCdTyfrNmR3w+rDg3gJCbBQnIrfGq0FO9okuwEwDorq/RmDeVbCgp+w3oaLDI5kcbqjlf4AsLFX3RR3LQ5PFRX4MSHSa6JMUqTaHuVYm5hNLBeXfl+bp7Oe8GcIFS1xRCpPOka4NmUdbWx2uFCkzJoCyGxFg5vL5apWgtWFKs3NbpB3zSgBH0cqNykz9K6Bpn+0D23lbDtY2GBQlSTJYlgM6WRb5yeIsSrw9TqWP6t7/UJb/qYXKfbbfufEo/AGXM9G09IPAXz0FAldrG8+7zZCupLUjdp+mttClOrDl0I7PQ5Y0j4Yv3uYsGv/sXFAvXmczKUwQCH4qKmR0dPDi8V23BcrMGQiYmn0tNsDCLy8qw5fCAFI6BaQjTkWH/66j9Iv/r9C/6ZBvFVrlD3aofTLH4HZ3Qop3SS+uefl68E5mHmh53kbA/EvVUhh6ZB5vCh9IafDg+GYP9Xk9uy9e0YZqWWI0gqRF2iKcZcYOfR6sc8uAtKitZUrHt6N3m17SsM0Li+i0v1PM0dDhJzEjOw45KkEDeM3jIdoBEMtYjePcrghwp75GyWoPlhLDymdF8D7CZ+WBnoOrn9OAcyxy8C/TgNDq78Bc2CM5OLlxzVahOKZ4KnhRC760JQehk3fw+4dWZDF9zmyXvwhNj91lLYSlQTRi7R1LOVLU2ice5ESzvkd5TpvTrj4enOak0OrhJmUqvOFA9+QljSrcRfNSH7VH7n0+XggEM8QB0ZsI5lEkouG/zwMdUriZhTTFz46YmKeFCSQzCXy9MwWxXy4Qe+nVqQdxQ3xNIw/82aLSyeHrfr914j+6cZ7ks9P0A9PA1XqQIlAQUF/QOT4Kn1cLoybTx5lPETh6+yuB4EcsBE8wm6FKDDwf3wwxzfzkJRC3QFOOhIEvpt4M14JBh7gOO/fTO+zTcjUPadvc2PpU7bfYzCWoHVbim4jprfv/SHVZq5H5TTpefhzxOJKdFOGfvR4YBe3HvkzopY3hN0tdeoIRtxq26W2W3uWZUa8gLnQkcR/aL3TCqfy1uLJovEtT3F7ZQPgSk3JfnXZNh44Oc4yNi6VVbaWccvXEuoMgYkhxFVpriP/SYwMl1Tz6xuR7tRepc3sw2CNDM+mXt1cukH6UdYysOzJtLLDOaXBRzc0fZvm+um8ynoQbiGH6TghuMY5H3Z+7N+oHwV+mHQ12ps+L2k2hbxyM5s156nv4UkLcoSw2SXwVYwF0ifu39r67GY2Ts8Ry8a9wElh3R38b46wOhUgbRwpHliBb9JmRu/mfINhOw3CJGpPhGektqSy3NFgMptyu8gvR1j1iVv/JE99p11+H5OaE1Zs7w//457C6iNmGdQWbDARzGk6B13O/x4t96vUvE7eQwipWdjLyYsea1S/dCg6ZMszB41dik9kFipB9wIUrtzl4LcHDfoA7vVA5WPHkvZKCBXWAXiPr2xZMSRIS4E7tgK2/pOaXH5kw1//381m78AUwQvnrmeptVArVWYpg+Gs+6G49/8okxQoudxMqzoAPRPgk4GCAcLSrGBfhq57hXrRs9qDTzyaN4Bf5tAHio24mWwQkZb2l1XfE0ts1DJivRNeyi7LWgg3ujlfh00QPl++c+wxCoiPd+N0qf5/G1U2tVpYhTHI2AHJ70Pl1FqkwunvkVz9a8x0FAYmtlxL1RxUh7NwUKkjUaTI7LKGn6z6CHMbqd4hmqmfHkIcMGt5KgMSltaQpb0HQXKIrJtbenbwc4+ymwPPvt3eQMqfrrjZK9145Srwyq3DmyV1IYAnTbCkLOitjxL1ih2uV05dWX4GHgnbPFbQKRp27weKgw5Z8fh4pIxS2xUoN1QWTF1n82W3zhFKdZfHd0GQ59fsEYisDKVqVIW0qFiGl72GXki9irOTbCmdC5kRJLktnfRLsj8Ah933HGH+mY2w57FFlWUpAPnHGeTLBWljPcrCvkfFOEa4Uq2u8lYCWxOS/wTOuHNHmlSn3rBGKwN31SGzpuFemyRHG+G2ix997Xm+3O343lZMKuzC36W7AWuKHbJpn6k/zfhnQDamsgivLrWKCztC1e+IYbiyd0KA9OG/C+4suwNfYUCOatL9wcVuhp+7lBTL+Ju8cvGRj4UWiO9F2sIg4HHpRZKHbKm2+po1/SEfArVJVlUc4VKQueYXfLXlgBVB6KXmKo/ulgCqVQlvR4GQaVOLzdn/80gNU1s/HmNL5vIfVK2r61FpvX7e/nsQzJgqAN1v8DP4SPPpm/TRfWpXQ9Nh/NKfZeg4D2vk5oQ06LNpGxyOHzyP4G2GgYxPRpAEsEaZF2fpWEM97s7m+XsLFhYXraJ/XM71F7oJirgconT5nbeQXWfjgT/heeVmplcvKbVzhiz4GYqtq+6+a6s29jb3t/EtDdHPg8HHMoSMb8iKHs6S+ikGTaxREz1Eo0xRhu/ULH2mD+K4Ht0gRQy7Ws4iOrUy0vknkaxvdaxZYo1GVr3aPHnZhiroksF25ZvCMH5acl7lG7weOCapOpCtHvsqwq/fhhyo9REk40viddIallzaNoQAC547pc08euQGa7VZiuFcJNSaIa6Ukp+kIdnr5+7wTyNbcwE8C0xZrLe18HDdzkOvOWM4PNweZrH9VCjox86miXfnRsprEA3EQtZbsyOsiaWV2A3KOiUEBijn1jGie6P2o71aA2RlykgRnm6XoZtgSCH0yFjkEPqt828tyFc4YxUgx8H4DFCasCVb5BPaHutGD15ocePy9xtS8vShtGBJjPgbxb6LUp8UtpcrBIk3nbsQZe2jCVQWKZuXT0DIQDY9fYjfjkn3rqdfhXdGx0aCk8UBpES4uc1O0I9C4/e4DxhL4+UOaJ4J/UrMWfGo+t9/hAr0ni+ttJzVpza6+qPL51cP+k2GdGt/IWhaJLD2sdaCP215xHosyxl1S/nH2vm5Vrs9wt0Jafq4inT+8lXoIAW3iciQkGR5UAkxw0AbVHXkmWOm/FTCpZaDw8pMHBdGjAyas2FJlRQ/bL19jSlFnenU8e3gqlMnYj0lvIuPtKFHiZyxnmx+sj6B02DbcWBvVYJqfnkOLWZ5jC7a4QYYxs6bSpsmE2Prn4y9Kcig1IoTsuYPubtBzr63G487PU3nl9D+Hfa2oj1U/7VK9MTBSO+Cde77HFUbnKhcyuTHoXWh+6Acj9DIprbGRupShOpZ/qfrPaLQ/yN3fudJrkU7UqKirdI0k3Ji935qhTuzXB7FSOFj7p7cH44CWhgNRLoa12J1DvHKMdjm5L/ijNNoKJgYqELeOBjenS3dkONkCmtdqj4yYSHB9Iku2Mtb1WRn93AssJ4YX0mUt8zUXLqGlKmMqonhIEPO85prYUwINcBicZpaLlVvyA/dATq0zob8BW+QoateIeX/JeBj5ifaARwKsxJwmeAO3/jOClVD4mUNtZDMwqC0y1yt+0YY82iawXPlgHbf7OjUG6pNOLOF4CdDF+xCDKi8L2xI9CcEMsAhbllOBxiQAfsZSU9Pg+ts2r/H0OLZ0gP5lBJNhM99Tz1b46oMrBLZQqwdck6YgnNGSlEuFlipbLQjTXzRQvuc3FzWXdul1IqubLhruDFI4pmICg/PZtwjkom0OIGUP6uyoolBypZBJLcii9bkfONDjsbLBC2uRAgGvA2a4bSyl7I0fdSQRh4+MjM/jV6On4yZ9GO1tNG57gBL02hckZM/alEQBRzhxkiX6qQ4WJWJcturRr4+dgibYmnIPqJhF/npaxIcPelDrDLxcHquSETBZJlOdnp1zLuAOq6qI8+Up+a0OjzQvKBf8i0HI1S8sFCKqRSqOZX1oOfogpF812KHzZ83iRRaZpTtAMeczeuYmAjKm15CtqA5ZXWMbZn7xAgu9QASe/DmYCJsFKIShG7UPCf1GL1Sin6E/RG3+Y8v3LsGhs3gUZyVLrUuFQgcdwzfzJCQW9Te8qY6NINlIgO43IubtifUytfDJZw9xLInzk5HgeIvQQba28nBFQR6Ce9rUpsOLd30HeikQ8YpIoQHhTz74LC714/uCy1wlHqH+ft40DBg3i9YdlidIN2cICVf7pPX7bcCC+F3iRa3JuJHuE4X5N9fEHMo4a8pHwkxEmDMuNWxIjlTtyRhxhaajFf8V6J7KoE8kxDNn7R611i4tYH/HTAJ1awfKH99WnQHN5NjEm/55L6vgAaBgI1ha9rsKz3qUTrgNwdQFBlRzQZ8fAPyzGOmy3Bf/SA2ToWaHaldyRCeAHmPs+1EwMZTvadVW0K0Kobp/7lUBFAjafPGXmdogjEM/XWEfGznvYDHonUa58JwgdvJpLMFNQsh2OTZ+cIBoRtTdKHvZDDpSQoq4Xwr2yBBrqvzgYIcge0+4LXCmkBNqHFDXZoQMIry6XDMMlvdZq6onI7CncoccJxmG2bGVnBNa0GLDMB0TdO6LNmrm7jPVGkdjLIfySBIpdfQxg7CNimyNCGmlHuqyJO3BkneQc7J3KiXY8mj6ET9AdAio68UA2a9DAz/EImEcBNZdBGJZ1LHkcNUZO/ev18qe4hw037Ed8exvbHk7idkSMoXupwx+8rqCdmYrLDVTf6aENfouEPMu2xMGL8eYDd8u1XJt0fvfVKbR/MboIkSsVAQ5mu8r41EUAWADQKOtCL8acTdu5W9GLy1JZ9xqJOgFVZnoDW4PEgxeuKJDHDHuPyMMjaPurdKZBmrJhN6kLpRM/PdVPrqQN2QIPinOsqskYuYa3TTQir+RxIMN85eAra5tyVCo/qZrEQZHdRDGPqO/MMHz7WI64+2yGDe+4e58lgvfvRYla+O0DUIs8UBI0EyvNZc4afBsma17n+cNyVdqYY03FZDn7Rq+B+Sr/x+0XUqgDv1rMkP/ssjOSjVq0yEY//5+8nN6yb0rBKVYGkbTxJowSEpa3zeN2X3LP1bYfQP/czkqgKgNACpFoIKv8u1DB1vpiyhAqTlS2Etij88g9av9rOBFehgZKMbKFm4GKmoWCUjCRobhA0rFKVeKj+xYfbXyRnf5acMwIqdB/tnzj0qfaWdFqShKOgVV+CayJKzVeb53UFU2mP02XGSpc6bxM7WfZ2PAmuQKCjVc/b4tmX6ISun3lZcUithRWK1Lyi/CPSjqFBUGed5wBKzp8mDFJEVhNrcQa0lPZUTs9D8irfpLwtLnZxV8hOltrcJzeAc40Bk72IuDUomfj10RptgSDJIjgs6wCPGf8KYzvB78AO/BwfehXxJjMVm1uHaDa+NnR4mlhBOed3s02Kxk04N0GZ4eYVZG159jt6QeF+Rm6J9PDbIxCKDrWXtQVdn1LvvrSJOvgzXg12I27GVjAAIn/qA8qX5v4coxlEBrHqOkNoogwNOYEazlmmi/zjJZkyqr1eMuPi6RMQdRh/vS9OniGJ9mOrYhT0pgeCVymKvr+pi7NHZgJ+nTsCf09KY+eUyTpNXXDaYFFdTqvNmo+Y2areakKJaQXpixHP7gS0SZmP8AxS3SqSpSb9Cu+Oz4Wj/P1jtAEAbPYJlrQ7qYQyucWINYrH6UEJ3Ui/ocnOLuPI0bbnu6i+IZsu1etB2jzY7rxblr/ackcHZyQbqd7lqGW7DElAuUEDKHWg7tlZs0TOzhTzhmfb/VpCFKTwFcgCWXlyIicLLgqfOErkKP9Fsq2JOl+pi5rlaRML3KYgHLc5X2/PZa1krj8HJtqTOR5jcoxB0mEtz+UFFufQnkJ13WS9NMzzT9sQs2aMu0MUW/C2jL/fzTrPO28WeF/mmTV91qo9+dK/++YdP1YqaaUTE7HIzqTNo05V8PYvzgCYrSPAMUV4ZpgsXBlW0Gl7H9p/KuIr/J9Sngbi9aLOF4ECfN9MsRdnUs3j9VbFdww9J3C4b8YnlBoUdoi8GgvQV+LUwX29g7GLevdPx4rhrRrGn0yTN66buKWi1Un0xPSxSsBQXnF9wrto8L9plx3Z3JHiC+WFJ3m7yk43BSLFbhK15n2t2eHAxTHr4+84mWx4T2HWf6mhC+2KiFnOz8WKV1AlGR7cg/f1Y/xLOAmci10c4yxyyz4MhVlQoQvOXU3mR3lnk5wpcd2taCGyDZo5fPp+GuFOEeFrtn1NZr1+h+jJqrXtORNxZGKJFWt1kqmi0lsEWDo0H9gklGMkDnyK1XSVei08/5HfOkGWCEBpKuMbLnzPIgIVdqUYAVgPTquZrXhc5XtrUrfnJNdixLxNokOcfTn6vDuRmy3E1oyi6+gBp1GRuLCCT6PF/20MAOlpt+hOIL52qBdX58iEF3VZQvhwd2+02lMo4u2mqXyRTwXBjuob/w2mpeUrA9SuyuvPcdvj/ks6MurWXOuVER0yN183UQZ3OM7rmPGMj0F/yADZu/0nsAxpA7E4edtHzA5Nno+P8mjOrgD70mKvbfGx84sivmjQhIilXLZB5d3TBx7Lo8sQl+VWQBK9hAyVX7+m69LxN4Q2hoBgMM5OjyN0c4/W2hjqyR7fp/a4Bc04XNVyftSe5Uyxlbidq4b5OuAAOBseuQBZ9TmSpKRm5vPlY1asTgDT0+auaXbJNaA/F45+D1ngEJGsMcKwm10cxwpvBEDsuNUgLWCwMCJVHRr5m+v0JzQj86XtgVU2lWyGK2cVdTo44JNFP7iGUzTkBYZ+f9qAGuR+F8T6ZCqEknvmSxh8I0UJqErX2zF+zecqtP71LEXr3ap8Zbl3aRM43UwLFyy++KLqXZyzPIt7CHFz0MCs7kOu4U9vqG5u5m8NzLWaXcPpJ7d1cGsZSKjFXHXiRJkID0eYT9Y0lAXpD4K2aHjT1jAihdjAA/Pt8tivcR5+ojTLqGFmqzEvY1Kz1GP94I3q7OwRoFxN8PYS+C9enbWhKqQi+KVMjwr5MxKVYkXi9h9/+t+XrY7duU4wqjs4DtQP2Es/4U/6sQaqfpAaw9i5X8aMQP85850WoZihouU3agg8ILYYSMHFkvo2QlH9l4PcoWUZdpO6f69oNOREjWrNdLn233f8Z9Tw98LQeWWozkJidtxm2Lwj5YALKOlLo54wnms2WrNdhbWW3gEa5EP+/YlYrZyC/cmRRbiYZBlAZZ/C3arZvWXtwm7lvJSIzxC+yoEKEKF/6kGy6Z7RXUUllkuWvxXo7scJZ78lFPfaW2gXlR4Tvj3THnTCXHdgcMhYi+2P63L8yD/Rhn9DpJYz9QhCjbe9H7gmUBh0ONSc8I6ygcntNcbg4sWDZO4PtmhJ7UoZ1xbqdsJxybGGNR2P5onPElFb0IR6ZRar+BXthUwj4ZLMwZZCzzEJoqSFGbNS1SRkXygUXMThG2ePX+mOVxxegRXrIFDyGL6vF5PidPgeIBgifhsIVqK2EWEFwg42OGKc9LwhF8oIICYPNS8cBx/VTQ6E+yFxTBN4uI9PUTNyXfnLnQ31uHpdDlt5ETTm5lIBjErZ+uqKeFRNmK/0eJQwI1MQfHFfpfBWji/EdYx+j+1aQxp1mNaQkE+nJmSXU1+qtRs9O/fDkwU1WkNXYNUoWSR2JKgF4vuF6cNvM1xn5/cUv5jIe6uEOrDLXxIrf25m+4C4f/NJ/HJ0J6PhQ5DKEvXZCaEGUWvyziJtDh397ExUyKyRRO0S1Wd10CVc0JKj/dnXfcu4/6MlWXXozQIjS6TBSS5JHlJ+wkLoCxRynFkm+0WCikpORjOeIwnlmb2JhKLlxtMzY2g93w2QqykbV8a3W3oNGYemIl3qjeRQNh9b2GXNI0HESnCksugX+UEeOUHiqSmF/eGRrvVGxjblLotE+AdR2pwUQn1E/91ykZ+T3939mSpUNfJndJ0TCQbbqXZ0N5Xg6x5dFtdo4hBowJx5FO3Q0+iP9+dnftOK2SNK5zpxR9LtAem8CxC9K3+BaDNrW5QEC8Kjl+oWn04410xsLdcKcQ91vED8uV9OdSTm0eN4niDRD+wRAPNu+NGsuLCT0U5XFvnl0ooe2Wm1zFv7MK51Tc1rRSHzO5IfYxAqYNU7xIn1iccuNNjFPHATiA4DzH/bzfkarLzPfpPuTzcATgPZ0U5xnfPSmm7Rb6wi1lGTqBfWp11tMWLG4xc9hpgHxB+ecHuaNZfVg1pvjI3sf65BfN+7T70XEaXNt/0ujibH0Z8MEVNduKiPx7J5NpdnSo2iS56aUKJtgXpesgxQP0L5gN8LNb7NrEoDtfGE/LB6TCbCf5Mptaaa+c2YdU1J7k7LEOZWUNYQXf7lNHN2WPMNzrPRpjaqqJaEUaUfWMxu7ckzrqIuzUt3Po+MGXzWf7AYFze04m0jzwTxw0eJA4jdqox3C86UNwG+w8mBHM+I7daDu+LdeKOaQruTRGS5KqB+4bmKqsEnqqq1j0zWvyKQjKgRVK90Jk6ogaRs9s2ZQiZaPy066/AHaTevRdGig/Tr7dPZuF99N+lfDBVmKbp5KEaZYHRzaOcy2QPHXzEJVUtKyud2jPuZna6zJ9Sig1UdGme34RU8X9dWKywgyZlBWRn070BldAyt7sTXWFKS3j3V7JZWjzefK4Ei0xyDla3oPrsyY3QS7c5hlgX0fal3AKyz0LSr87t8dmjJT6NaSdhKxX4OMDyNN+Zg1ZtrEywZe/fko8jhSJTZnyDozSoz42O+JJinejVyx82sRb+LEi+w2T5hGkyWmQAfKFdksslwhymDaUTUBVyt7JTs4IxpMKe+h5qcuo1Yq2Tx2qqkrJ6K29wN3EeS9THgnBXbBbjmYRCeCeWFJnwS2FQb+kQjH9v8drLYZjBAQEe5TlORml17NLIYMEaEArymo/tNM5NcQCntStAapnz7muW8JNxKzPLRE27XUVwsw47i9WM7AK4QGeZ2+2Tug00WFdNM/dP88HeWHm2bKcCGaXYMjNuRHeMDEIRB9KMTdX6N+J/TD9k6zn76KhbgO3PAtYp8mbM7whWhlolYknLj/O+nwdubc/484zu/HUOUPGGw1LciHnhoA79rvb9E72aeAXZ/5BBqnKnY8JAwTxAD51CQUsvM0F4ofSdpoznEq28j8Ci74nQ9m34ct2B8Y/E15JLtMx5e2W1iUvD5QLGHJrF3mfkOQabUs8hERvWppt87/C02ukfc5T0CRZCyqXJ/mAH8ZXqTAijF5cFXw9IWz5IQoWgzML4kAchioQ13WWC2kvKeQq+ps55+TKWzLrlwI6x6awkAEuickNPEm9VCb3JlqPOTCoJpR6Qh6GX1w38RRZm8J4EOiMTHmTYDRYUhR8VXL35GeFGF5ZKY1EYcd/+5BjI2BcgznHdzsouwlHCKR06d/OrkVgtlfthtLLjMtdIoO7ZAnSU/lr9zpfb89L28CJjJj6ewLPwm8edvhLY12IH8pcx7SP33zs9uIQ773lF6PEcySxRnDWPQNIFXsmy+NyrZ1yagXTX18fAyvSmzKKHzJF8RaQ1VgkMgFlslIDyJWoG0f8HzUtm/ExB+xFaISx1d7ybGxBYInPwTWK8c+R6cdpemAUGokRwIKlfv29M/bzYF8XsR4xY1/QV+q0mXPM0hB5TcDjSO9K9M8P3Z6EiGy2uFA8gb/yPN+DSpR/aCQbVkcV19L8DHvDGXc/UHpZH/l+8evmbQB4BTOWn0Q8tEP6Yo6zqCi06AxREIPF4suSEQ4EWDKWbST6mIlB2kIpYQ83G2lZka0f0APyhRQkZZd4N6oakO64IAJpwQ2nk9DyCnz3XiN7tDYMPo+A0v3IKFFq/DyQlpF0dHrwvn+hd85vXarlyLdz/z2YaEATv9yuC7V/sjqZWYKYQTnplj13Rby928iqDnOQ2ZNfmAqf3J14Y/TN9Ih2SS8h5XtxVAtmzM5E+xvFrDltfLSEomzcxq4XP67mRTbRNU3SRqi+lM1DEjZHSzfscMYM0sG+QwjP64NN5a8boquIsmwCesiF6gPxm+IeuimBl6b581ayBaHsI3kdCLdiwYfzLlBi1EZhzKEEFjBZF6ZkBzA3MzYlWK+qTXOCyksBeQbe6D8L71pu9+E9uo42vctV9hKUFFCNN+8Ehd6BSEvX8/+APw1rZ+QQkiScNTzy3iTB+LcatH0MDRTK4Aer8QAJLamf2VTqQqY2qp4V9boKzEPjOuTegui66XDpndMfNhyZBalRb42XBWIq4rvyQdAACkG2C9yixBW1vweRabGvp2YYhBAk75GP4luXJqnuqKkYhcqOP9F7kDKPLitVvAgO5VdV3ibmMB9xKWHdmJQM0bGwOxxZ3nr4KMaaljSLvlvo1Nf8nvLqIc1izEzKDY1WZujKxnrOqqmesOq250UHnd2u13hBD/Hph1RrDY3gCsIkmED0hnioLQ3eNfBm0HgVfP1aYRnZvcecptWhdXwgZohGNi0UJFHIT5mVZbBrAN6CrNZvoPNV/R7ne0pgXVN3jcqJuqbOG7nFwPEKXKmQh8u+rZ3fWvdOt0YOzVh1zzmO/3JJOJmbewYd/R55YgW5MVy+X22p6Xab9bKOsgXablfOFcDTqO68eYaR7eVOzgabQf2jEqU5QW+ihLf7e7/yevYEq4ZAqU7jT2PutlETnhIHdwYDu6NeW/EqZm1+iLrEqH8NZyTCB9GF36ArzUQhZDI9Yh+yBK8m+0dLEjtD8eDrvEUign5yWODe+T+zzGdo60WK8WT9T6f+cpgg2D/1SLMwvvk1OEsYcks9ZgtV5aPbHaYoHcRieNzL2UB8GtUBjru19ja8BD83Uc+fPNpTqn8yAYk/6AMpwhXJj9tEQ2RA4RCDOO5yp/eq1kcrdeB92NUrmWj9aSjuz+I8wWPr+TGmri4WACqmlZHhuQrL7GCDn05f2zI8xXhfnxkDNrQRbiye5pFotLhdldk2Yvas3rkZUGHd3IkR6odIZeBtRhkX2usoXcVTzNzEw9btSR0m9zavvga4Uf7mhmWY7d6nAcjBH4C62mMGF4fDGh32wVKTB0idS1K4ietp6boVCR1Q633WUlZjbZPq9Y8OM4aH1bA6YZKzVqd7lsy9WX+is63PeZEyxD77eqtQ8YIUeC5xsLUyp1UdZIn9kl+H0qApguP46EFhmwqwAtfOCbgBLzl2KaYUfeqs8Pum4BpJVOy9RnG6N/e1ovPqX4nH8Oh5VIKNPs/oSGzzqSqdT1Rgc8vbczRcvzSSEIxLTJeZjuke99WABnV8D+9lJ6Vk54n71wuWOO97xW7xPsUqMTZcELckCdbS1rvKF/w03Ay7qy6aQ1uXjHIpuDSjMEzWiKHAgX570vMZTkQSpWc+RV7yqhYtDi9z/dnOffEyXseRS5zQKPeXITDRF7FAF2CLRfLpEiSS3VkR7gxze7udRHtKszBo4821ESD7MvfnN664oLdinP7v1OGSzYz8kUAwYOUqWriD2hamenH+DxBOy+lrEpmBXR1CkifJUNk2lZnQ1pDIKqMQT5kTM+oy9hfjkeZ191svGkHAdkmokD5bbh+OJ0M5Ma5Jc5Z5fu6PKzYqQYEPHKmymfBqSDrMvIW2t62j1AH4kn/8fl6url+9v7V6yCWawAGgursACy+KsgaFlVGfaooMMsUDVdmiWgoiuB5toWXax3AaUy2YYehCXcW7XJHmd2WpPoNx+M3WNw9nto28rNiW3O4Tinpf7NpT1Ax9oKAdE8DJxr4DDcVnkrjdwF3BvbLrWK7bLfkpIzZse7OwLDy3YSHsbI6JhUDjNbEiv6gnm1bzIRQ11KwP/diz28KAdkUaQOrE7BnBrjbqT6dP9+lIoc+JCASiOixfpdx5+s3ZZjj/n/d4hTbW+kVEhBK7Oc5qendUcXmPCO+DxQem1ZlK7OneQTUXjRmTSA5prFfqNn75YP86F4Oze95uYPF1XsYoaoz+nrj40lDdfawmw9doFNyJRVn4gUrAj69+j2Ju4skubAh6Lxn1R0aq7+N40CynvwzsXJx8aXZoThvDzXSaJ16g9hrUCVi9MP3syMaRkz5tPjGjncp+LMJbT0rl1/9U8xGrS01A9ZSgNNpRlKv/jn0JdPB7tmwni9fSwfScHLWicqSU3CT69lMc3EbGd3NXH5wbjGQjhZuAb2r20JI8zSiyheGf5SN4RDueCYw/yimLxjSohbaSf3g5sWAQJSjxs25H6jXIy2Byy3N0bUgl51UGbKbkHJP09bVA3yp3knDj3ZDW8+ZIji1qvh/mv/Qtb/HnThAamd6IfdDYXF7nSvWgsfJk2A07zZPyfPZJAHxQisdJxeU9ePT6JVstDNxwUqdzh2aQF4Hx8Pw6acneTULTWRJ1lxRV3/r2S/PyqJDOd/HexxpSrnt56xfC1BYSvvQQR5hwCrcZQa82kXjAHfH3tTxm5alkJOThFstqxiRiFmSUSi2cbzjbxDcSllPUI/odfj7DBmldIBr2SosxQCQi7yITzsGa5PLl+nBfPPMJ8G0AGcPXIHV2nyRgOZdyov2bb5swYLR3ytmyFPUPQ8ul2dIQ7cfuEdCAORN5RMQUgGEw3mbkVHUAqDc26XhoN7wGYsBScnYpRHzAGxpV26koEy9edz/3cxYaMIxvh3Ljo0yci4sWWk69QXeBPaf1v4qjqjbozFzTZFmAtRVhWPIuQQI0wKLTEonqxHCPTS0KduTDiW0IIt91RyJyDXDalI2g5KnrjStSknBD3tEuS+KrJTqe8vWy0m2vo67P9Mc2pm+Dw1U2xAGIJcGczg+dFcq6p7ql3JhGTVKPWK3aG1IMEXmvJUUlfEMNxlveDS9uRtB4xFLU2hufCYdUNY8MC0G3nZwB3ThJ158MVu4D1XdHemNyBAkW1cDUjvsWxgzn/qhrdx+l6tUsNskVGt2ZOnCbsWD3Biwr83SlCxwTL4MOORty9FG/FxtS7t9t+mzyHR4QQ4KG8ffQfkfmx3H9dDsqyEYsybMQFdFla177GUd3dnji6lxjsV/+xB/jm6UhtrNcNnBnOOPE5U+s/WQbe7sUY30N85IhH7eWLV7Hl1pluWFZiRAHvQG7M5YT+B02Pz/1xcAQl2QbmWLbShN59FR7KZYQi3iqqLgT9ngbzC0vrGz1tZ39c5Y9RJiUEbgP5ZNqtxFUhKRue1ZYBrV6dOBjLBzr8cmNDMQjORFvfPIVkaYARaDzDCt6D+y8+3F+YKzH/xb2IuWcDLLZfccAm3LYnDGytk/4m1FiuyvPU6sV22435yci2UIhrlWDsKFny1AVtXpP3ZrBwR9sVgdMtogt5MoaXe+FMWv8FnyosUF+YFFdFztLvRV1SeiUrvsx8oFFzgQZdImNu6ISgR8CRHmJE18xcBbCx9x/4CSAd3/9AjXjXB6e3DqZtVuFHcTaR6mU/fLk4XCue4tYIFraPLtb/WbTnLhurmYGuM8IKyMhDIZf2ya9MzVeFei81wHnEOe52s974/y5GUm84stvvuWSAToxzVFvzeiZv2Ms+FoZtSOq584sOm0S12KX25NFnbuj0Jn47vm5z3ka5kZ8HXhGGhPLmgYSyaMgbfgaQsN0sAooj+B510YzBxpZ48+hdBSgzyQrVVrq3SAj/nMXd3evIRDd8hPSBcvQ0NJmlJvUdMQyu7dYQMGtxXO1RwHdE2ra1cIVMWaA1v42F/rM2YRomFhfoiEuKEBJpHwhBn9QAs1rBg59hbBXqllrODeoX1MHJaBNbuTJXUsC0PZ/Ihtgi2synZHrs/ijecCP5LcO9Iw/SHQknHar2JYrmyubp9j1BuAhAd45p4ypdmmjMUqphbgpiSROf4ZGR3kQ+ZMfLAl9pIJWwyBxTVScZEgEK4jR6CgnDk+rW6HFt5DS8lx3Cb2LurLM23pO9ykYwY8Z7DYGdLEtnln030WKCcDBLHQfqEke9nYKzVemm4ZDXOkKv5THtpOOQrSp2l6Kbmf/Tiz9uA4TKjYkglhrvg5FiMra8HQ/P2XglierTnfcT0/5ufZT2MSaOpGc34o9oy9EjRdxyAg/NU0f5xtavDdd7BIr7StAJRPoybioGsM6pahKmBE3Y/7ovhJ4eEsmR/1LKccCBBneAEthw/wm+COviUImNNacZ3IaxLPU9RdRhlymq/j3qjqCbdLSr5oTtSUyT/4rBEGdpT8pB6LGN4qnv48Rf/VQh/rpMnyiW8fKIWwcvrHPuq7mLUhpbmuz/JohfujOPWrTzOcq36n/6TdnxFe4kLdraZiFqsCyUD7IgXFkpEAFrwsmH/UQ2prSWgf4Cqo6Ro/8z3cRzkZngFNfsqsxRL4v40DkEp8fj6q+E6WbuzOrVZeNJsnNhM0d0tnpHOHU24364AVSeM2aPU02MUF2+oNpZfxgUmn/jyug1qoaLS+vDucmDPyyjOlWdEVYyJlmRYEzl0xrP/cVg5SKPnca6jyftrTLUzsRvLPBvUNyjIE2aawWMdADg08QF5fKJBjEKoq3nalHDfD0GlmpmytS0ltwo+KJ/KvRoJsxhcDtcBU8r01IhiYYjq1buoSKMC7v59eXDXiWHChcTCdohDdzTSrlcjfaOeKhpwiaGL6S5YFgK1ShfRuvqBlyhjNO7RNFoHFb4lpvjfeZqakU9N7FLKkDXMsCnDhAwe8gG4FPFxMMOMYPY4d4re9mqjVnJ6OweEfqeAhYeoVxngn/YaWOem+cx7nD4sLeLr4wWVSSckgyZtXqBeskjUNQPnYChzlamq1IYKx4xOjojBiAAg/Jhwa1Y/7YliNv8eDGANdyBxpmJONTlamSI9VhdJWJxsKnwGb4Jq9k+XyYI28ZZ5zukBLhvXBmds5UNGBf8oGjv1Z3CPQknXhOjZ0fVAryo45OnWyCnztgnKfDPwu/rASW8IBg0KaPtGkehMcM/mjsJ836mj1JOOChDh/CVJA5HvyTcofXi6rVer6K1s7cV/pyoxxu1klwm4QAJJmgYXuGZm8Uw5gLrVQLNeSPBIK5XmOu9Up+h0iuMd9C7V/wId9WHqosh3rxSEmmhuEpO6kwFXPnWiTt05RZ7pDSJd26LJL078fbdtAKklhWrg2Xo42870d5VBjPsQ+0NsUSAnYyUEmKLqkhVead69kr6hyyXNFG8LBsT8rVeyqJjOvpKhowUa442bnKmxhAMTnc6JHszL49v9vVa5LkPRV0+1CT0l8Om4398tE6d9NdVL5znB9JAykk9b/9L5vCtwD/47d0/EBp5RjUV+2Ih/LS2lwaG0zfpd3tkLK/GgsPi8UT+8ck1y6jDeJ0sL7irWKcrMwp+lPDKZh1y2QwPwbYh8kRMgkaU1KkSYAVqz0PWnYBOjgloV9CarWeSH5CNQHWwayFy0Aca4uZ7iBmbflmyS5hERFHjjSh/uilYjROspG4M7fem20Q3S+QaapnVy//0E7pjnrpS+aeMAwno4F/p/UM03AFlKapNNJ1TT9du0GDWZt72b5POQ8sHm4m0zcH/oy0nl0pk2GFjc8iDlvpBAL0A+oiMav7JU/9eqQYlhLsfMUoIIvOnU2vvJVZrn/0HwcyhliDJwegKfSa5t3ZyhdyLRn4WtHGsAgBWcMTuwRgMAf163xK+yzhyB6aI3ygYjFeCig59qMi8QLmltSApCpdr9Vk1W2AoCQgBWe8TOyFeH9+xq5n087CyPSD97ookii55ukKSphZHWPa9e8yNA6pxTJixP3w6A7ARhYxvdKqcNUs3VVnAs2nx+HKtM8w8iMngMOFNX2BVWKhd29p3tFDhkmRhZZfTQFJdCFTPhtQNj86ffxqhZ08yNhEg7mkxDTmpAywYMgshj/+g/qwlK9GemqyMHz81TVSa6f7zGezy1NtdDDeSJO2k0ApWxBNEYwSKAf8X0dFzVve35UZ3M6KwRAqk48Z3G2GdI66C5hdrrxB6LzY6NPXuMS2UcMcOv8w84dr/SFTu9bR21rq8m05On6jVrMPxZn8zcQ/rRi+YRib1uf6FL4GumbI/WR1ot3kpAzl8AEHeCkpnC3yOxsUhszIvd1IqLcZBW/Wqgy0/6FMrqo2OqrB5QCI5MrIeLGI4mPVjOF2JOAdCnLIGlTScJVdFsq1MZZ2mx0xIIe7meawxHyJ7dl/1rj5FBJvOs8h4ACgaKHmlibxG2+DJ8aisk7valBEqS4cemiePHe1MPC+u8feQGRBB9eAUDQvqe3dl58LlFzBtaaHEwwqjjxVUamcC2mHdZxFWEUsh1GMZvFp286G1fQHyAFf2Sfep8s7lDZqAUQirzoUPRY9i8EVRG1rTPjc4K9j7VDXfhtCc1xt/yY0SHNgt3pkHAgg2VMnqj5Mgqt2/q/fwmPrXpb5umTD23TaaPGewUrF5IWVvNQXXdnHc7u0jwXv8+cnpTE+8RX46W3uolImHT0tHPh88kgJlQCczDMdX2KsE0V7HcN9OHwH+vQeFoeNPQgnKC5CPakasnu6nnrwdxQfyn2Z+51/wl8Fl5exkejd6rJ4kk4uX6pgbjQH0nL1gBlShv/DAJwMq2LeqJiEJI1fIFPBcG0BQZVamL8t9Q69ieUKfJjlu7JHwHLuuY/PCMCHQQU3e7X2IXkCPaEpxC7T0oLB/Liiwk2N3GpoIqzN70J2c2Kee82gDkDaJiWtzfT6L8MxgnrC+iRPAmAGR07KZx2hBd14aWSSop8BHyp46DVcAjm4m0sb5Op2sKQf/sqBXDB7787Ri4o7DJADAKlD43R9kCXKj27y4PrNY1+MCofCYSHWaRPU8SpeU/f9PmnzmSE6U5M+KkzKcQCDFRVOCUvXHNFZCHubM5IkYN8Dg1/A4ElWT9sq9iQG5q0/gH2E8n7F8v5vIXAGQJdv2u7RW7K02VbMQ1EgS6jzSDxpMObCazQPZ0Y2MbSY5GvNtnrzM5sIQtSIBcnMWa39V4HVVSqjt02dg+JxRmVNGA/n34li1A/jFhrgWwNau6B2qUYjfJRTz9wa9Hz9W01xXChXRPcaSnZ9z0MB2Yy069/Ui4i6muOaP0p9x2K+oAEe7aGJDnc8Y9peZhOwm3K+H5s+kbWD1Rz5tlHvSl7L/iGQRmpRQcdpG4MOx4YUUlqcnFs7y2QF4LQfSSlcBkxQf2XAX4sR+z1gtp4HvbEtpgoep8TUsOnP1xIswq4H/7RDsZNXkM7XNTvwfwXlpC9j/QsptVER/yiTshj3QSt32ztO4Bf0QxLoi+RhaNdiAi/SoTCNxqu+p7aBz26Wl8bNpkpvV5JJMP2/KL+u1KHs1CNxY5VbJ1MSopGwFIapuP/3NI34VjKdkQ1QPspvqZGg/uVV1sViJn7hUOzXKBmwqhHdGlioFvaa35m1i9+RGroATlGOBkxcwkiPEROaTxYQba2xUW3Irl5PUKbJYDCUY9s27SYysoB0LgXVHtOY2qArgvWLXvB2GffP2PPFVr+wzOWZLGoBni18OVpFXVfPkL9YR2dEK3b9bG/PJwS/df2wwlrbe2WV0eQfwRRvzkbklDR3gfyPAN9x6D6FO87gpY8S+O4yEMh2cQuLwtO+pNfU5A09oCYFJfGa7iPgcQ34RZdELBZvYfIUxmHJbTGvGdl8y57SK4ERcissrHJsV3fwxIaW8b+Fx6ETdlU+vPflgeVi0jawIkKKrho1F67pIqAKROJarJwMtkKXNXLuLinZqOZe3dgn/pn0YX0pmv1rpntVps3ZFTm3mB/iICJcEjlxD/pqrMEYunzVZV9NwbMTxH/tg00E3pkvbNwXs48M+zP3sZ8oTQpdHiDY+zAThcZ61YpHsTNOPU+k1f2Jd1xa5/bY3uSu3Z3+zKBog8Yp0AbuhDOw10iHZlxjgiAQFeA58y7XpJ6RjWhhCvG2R6OP8XS/hT8fM97TSx/o/5eRY0Tvofov/9C2t9yj8MVfD8InSKPeoF+T37lLGul8LkVs2pMTALkRYqRmU81F00yyuARjm+gGugt9OatMNARAsweQlWA2Ze6Ue+chDi7rXtSvs18dF2+cyOYxtbVKHsZEUwWhCm8HfTJZmCfYlt9JsAN0bzbaJLvtHurwddg9j4DOMyxPhX26pd+aGs04sX+9il54Vdf5q75/FfktFXdDht0I4p1IHhgu980u0FxrhNZY3PbQfKTEGOClxUhbanMeBDd7CKgIqZVmGztsMp+C0IZUvJQKwiF/s8C9RAJm2iaypVBlKluj2opj6UmHh950OETzXFnkUKSc41qX1jLN+5wbv8pNTCJeLtltdUDlKota7rCxlz3Ml8dGYT+tWBsNSykOXet2MIwm6/z8N18cF51idD6ffmDyCT/hy4vPs/AfComec6e7Gxe2lULc/FhmtHyxLqNL3WYn69c4NC5xPH8W4q07qTU5thPJDi1vBnQuKegCCTqhULTmRwO6Oxcx9Ok92lPsdvD3rVxf53eQcieBbo3qsA+dLc65tooDdMMlWju2VToNl1jv36Th7vGLbsJcWWUYKuUV5rUKIcKxq83yxTQiYgsi8OiNdzwo30+86RCXC46KDvpWmE2w3fIqMV8szVg0e34t4grOmeBb7L3YsHlSBjUj22jY0E4UqrKT2ozji3SK+mA2Iwi3Fh1LXdHHZY4+/uhyUScnTkPDQMav5yuVfxOl02kiVB/teYgKi/2wKBc54Cgb54Er4rSzByg296adKG69vLwrmy/Z8Ev6kPgq+XQFBZzudVWhOE8yfYxHidudGEOAs11y31u6sOUK4Xn+YkEdDHasoi5Zh5AYNtebzMHv8eZAjUar6wSzaa416TBzs6sDaWLTqFHOI8PE6GvsJxeQk1p9MSEI0iEqHQq6TYkF/2QE/Z8LYuww+/2xinypFqvVjMU7jFsAHZI7QKO/cY09GG5mRIDE79QybmDptUuVXh4CYDVPNNp6223EEi3CmKtGM8YFlLeNcT4OYYrn6ZGnCjiHdiXAWonBson59a7Fo8fX9BLAu51VU9/QMZD3C0ZmuemJNB1Uf4s6NLvrM47TRx3XacLp1Ch8paWc9OwNcz4x2I+aBefoVWy8E4uhGGn1FaTyvGsnUMyS3196ZFhrQsKtgVuMlvloofm1CVjSP6nf+qo/TUAqQ2RMcSXpzIAf27NtC6njyJERFTI8F8d1+j1NRhsEM7s5Ni0wv6EZIYghY6ucv2l0uTd2FnKAfxypafJ1xt1aVH07wIgyYxf7PSNfoz4oVjrLzkDVZ9Bez02lCgdqi/jO15uPaPz2pd7tE81yQVo86GA54TgQDN9MKZbbYNSx/IvlZO79lUt9Whi1WiAtW0DbvtcOf244sVSCtxAUCuY/fr59MM0uGZSTW/7cPJw9WIhEaegOhWwXIc84GNrLPwCcZ4WBJApxtV9iwLfSKvpDZILqMZ5DPmzxB8uC43GlsE1Bg1bKlat5+Lje8UGub6/XsCbicXGLfY+zQJ1NWfjH/R1SYdDKUjRzbPfDDpsUrq+og6ABDEVGr3DsE4sVHgLwAYZETQltKwiGhlitO5rw3+LTisx/hq3Hu78yT4jLT3WsPiffwucWL/Tish8WUgFYmfJw5O1uRxi8VfV0ExZV3fS38uAN59dz3X4LOIpl79LQZELn7leamf/x01K3su8QoeYsE2l/m9rNMW/yGV4BPCbLxHgb5bm/E4OBFXkhfeNZX9bI3R4v8g4rdO24zNcnerTATNnW1F9xyB4A2xQS9Vg9eQ1SM1x2EzweVDvIBVHNU+QWoBPzkQXUWXZnctZMKPZnylthhun3uDzfOxkFLSuWFe+Si3oe/d5RbqomlcRHBXJFYPF6oZOHQZbZ8uRhdkf6eSQutK4PWHKQSlLSvxXkG7UIh/HhLfgtEsHJ0Lx/t5D1QaO0BkrWkxrrMyNSqqsbH99D6iBzLQyhPmsZocXOwZ1AUBRkRlFnWbXzK/6fs8LrQFZhrU7wXfBpxPCwv8jVPrgHB/+Duwzd0wvn/SB02b2Es9+PmufUFj4zRN6pryLqlTkZWsTVzBr024PMZS3MFSBSeCd/ZK9TTxN+F3cBkz3DOTLn/IF22BkX+NjaT/C+eQDimnAG13LfGxHamXGaYLKtuzsCXQKxikpXAMy3R8UhHnkPhFSB7rAmoN3VKmuQR3X6GUQauTnVCNwF9bTwSr4kJ1sgQo5L3E6EVmXSITi+opSVhwfu7OpX9Et16tRhdwn2Do+Fh5JkgaVc+pYwYBtvKXrcqlpD4TqE08F7aXiulpNwcha9cwS98iEpqz5XHAQpwyuo2YmMbi58L/h6tydfR+j2JQ4AU8Nt4XGU4oWWKyqKzBuwv/5PPKA1oQM3uqEOpuLmyIV5nMYBu/es7469LrPDzQTG9efD2LzU9OIZ/CiyF1hvkRkkyzNNZzVQilHl9gTgLY503xYmTKw4kLVOeGsCAJP7BIIapLGKod3zzC41LpeAmbj9d9QPc/pDwXsCfG5Le/MRyFX1yiEyrfcdWY6AHP1T6dL9EXxL+Jh/DTXoF1VLtI4HUqlRJ6SpeuML6X/QQ8ckAB4UWu9WZN2wfg5APt0roB9UFY8hkFMKsLq31MpNtQ6ZiYvHutLy7D6maeqDC2dkKB7NoYNLb1Q3AhodC+2QFuO3WUJMoY2YC2bR5lA1oKCOHPhMJdnVPsjsAuigGITsbpThlcKX6q2f+i0on4FRzzKCPVBpal9F4FtIZTy7tOIYun9T8KgtFuhUphxnj1wj8+8qP9UtQKzqvRu9dQru/Wt86ZaMd+wJd5TwgU0wB6CVrD0kqLwwIh7OUKcVWmrBwG5KUd2wpR0BAPjoM2UMxA1YdPfvbPDGftO8g9HgxT8pxs/kdrb11LVot6CHWqSo3Y77y7IB1nqgDQydrcxqI4MD2RGtMXk3yhiEvGSk04qtzw88R3oceG38qI99S1st0q7Ub8Fp1OjceWMtWSmkfJsWAHi6mHom4Js1LQACULAb+BheliGNYPC142FOl8cDObOiuvH4bE3BnD1RZCrK4Nn1Ilj6B21d6wG/aAeUUdTC5Th1KKcomWEq+JOJ/n9T26fKZoJJv8jqsYLmHj5+EpvqkwcW0KVocZIHsd2EW05cdagfbASaPOpNsVH6mmiO/JezMUAEMLZzRT3qu1KtCYbDZjlQKfY4d55v3IlKI82pWGSq7Zh+jg5RcxztfDrTt7y+UHRxAVutC7aIbg7vlA//d48MdIDoXBMmSe41kc8Tn7mU3Ml12qE2ci5x6S5+eaUQLbhM92R6GyCYXW+Z4+Gi/sBNV9X3droW74aqFGfPNHTmuLO82vXNSThTFEimAUe2uqsWW0waCLzJWWUVw29qZJygQgp7BbLNv7YpPWxDyEWuUzvBgj86W+KKesJ1H/vcdgS/A7LgM2l9fUtCUnaWQkMU8siEM8e9NLuheIBXi/MK3qY44veXQgIra/1JDskbrF6BcPAHfjGfetb8JtMsu2xd75OeMhy6DD841cfcS9ryM3UkNCLysak+ZjuMd/fWPOz8E8Gc3lZt1nRGml8eXvlXQkjYUEPUuR8CW2j5jKFGjNL0S+auHtclrDoOsqXcgWXdRx5VVnm7oJUtvuz4EAShespim6dlpbper1ZY710p4ootU2H9Kb2XI8ubrgdYxnVW014QxY15oHLYlMA9LQBcCOcvkpqYAzMVaGgdHf7bczbhA70s8CLWADB/8YX0GNiQNCn+yog3rV4rSl5QxizQFS+jsiXEKuZnHGVZZuV953s7sbIwPUuTrz3GoGDFCqGhNzibP45HcZBhfswOYbcdrVIVFnyX2qQECwNX+HZcPduDv1FOlIzM5XXVHpPoW/2klLmfuH9e5iHsJ/Xl+lGqBv56D3LIT34/wL/cYEVU4I9ZkbZANj6Id1lRuVF2yUQ8VxQr+huIsZyci+4WnreIKkigg6kL7PBLBlD/KT6zj+B788QQJmmcQf5/CyXZuaYccYTrTOG/aVwwPZPZUNt0eicYZozpeJLd49mKldBPtAtjUwWRRc4wG0TOP4/6vK9zpEzwJT/Mt556eBGErnl6P2YUKSHdJHaNvYaVl6wRlOJYJ1QVxFRYiuqoKUJGVv+7sPMpFEg/U3BeF6NjgjNEhYSIKiUvDL+lLqhKs7B183oHdXNevLQfZ4f2ev6JgBniJeM1Kz3q3c2VWHucjTu0tC273wDnOHTLQQTI72WmuIoaoDR4qN4h9HcndzOvyXHMgV7zZwyBm8Z+oi3OJ2A/hgcxZcIQquF+G8RdbdrMqO7X0oqqUxAEGumjWwbXTY96OJVjz7a0B9YNCdXauIhclkapS7ZZtoma1/Xo9tlSvo9/gG8GR38U2DE1VRs5gdEL3w/a9vL8cQQ6jsQwbED/Tngh2sosJbaAOMQW2tUF5SRWXIYNH+PgS/aWc4lyUumLM7hPGrTIMIQzT5I+Q7j16Sv5UK6oyr7aSMKpfFe3uKjcAJUTX1rCN9RRy0VMRwpoVTj7Ytz3fPycGNzLorSgvI5+GKpG7fGKWcGz2v0Nt+OiLkHApunOSzgq60ZD3CCe5dt9LnwBnl8XLY2F1Wygm63knzpkYrqiSQep5Twq0kY/ze8/huPn9HAivP6/J5/Am5BJfYXN0tvCon7ozYhuCbVNauxcJOlwwaTvn0QVTbwktnY09PQRbMJZPENQ+1t2DxDMKifDnbT5KVUo++B2JFZtU0z2CMSI0KbzxNZiUNrv+omhcMfVq3DVrRV+u37Z9GpWvvQ88kNhphizOS6tRvHS4oUHOSF39NlGMf/8MC9T5axJXW/HMOGtWtO9j7CKEcwZTKxkjFMmikh8TxbBt8HSexQZM9UWWnnT6ONv7jcpf8iOQYcNe1dj067BFU9upCpfdueyDA1Njw+HAnpXLeoe7693rpuUURvqhNPEjdr+WQXtrb9p7b4wLZFaG9kqyEyU3mYnZ708C3S9CGXl5z38bltFOWiRZAM6qOsSfjf4PicF8dP3/pSnLkN5oYQB6nsrHu0K0pQ1Jngw4dAJR/NaRzBNh4DCnmEDXZpRwsUDGiuIA9xI1yv8HuCdUO/GexUD75dPxlxE3wpihOMYM0AS78TUa7cWzxfzWek/WlOIMHHSN8TKT3r2utzb7vhQ6ucfOjxGtiN3Nzzim1/Wcy++efsk+5Anbg1gfBcapMPBwIr2x898nuKtKRJUsbY3JTPqpXOFbs5Z3IhQt5PJI4GkEYpRWvVc3tECxheqQvyPAiaDpt1eTEHV0j8DRhh+CSEHYHyyE3KEtuGPsf0/j68YLbo9U2qNZITZZgzRYVnWWyRmSDO91mRsaZwOkjVw9oAFxRCblqWsHv8rqMkVc6poHE/yrfqlgi4VbtzlDdnMQegPw4nsXuDoof4IJ9qQU+IsKVvnvN42/mgr8tKqma6kvQjZ6hRU3JBNMJMR5LMBcDaCR1hQAyFD5mSIZqZHuNQ5STwym1juwf1szUbWMWHOgJbygam9Nm5WDXTuIq3lccSzV6SQNHtAAtmCrfo3cf6tLx8AGlTbmYbwucVcybB/aDWesyY7GWD7t8WhMZFlrw3jW95sO+QGFU1Sb7w6hE6NHqSXrebwrR889Pq1IW4I085YVcbl7J7o5hZGBXUWH/W4U55BDYjs8Lssw6IrB2mHrEgwh5R/zDuniQFOknGQNliMERJH4zturvDmNpYbwPjc/VDqnNWkaSRFdl8p4irkEp2pEl1yggkogZElSiCK+BSkRFpgIo9uuuORxi4/N8l6gFWNvH5xaTpxVnhhFz2orO8/emR9NQmrSDrqmztEYw4/yhppO4zQe3STofYxgJWef2H5W6Ch3q3ub31aa8m1NDwJyi3E+ULkyr80qE2GaGjjKX8NKQPjw3LN6rKdsbFx6xJ6KBz77ezJSKogtiy/l9AbpkvbSyHvucFRvsXm8KzKeNWFruURaFqKrIHe9Sw0gZ6YuMFHbdEZmjZ8wDkXoZ4ggxownY9uPXMtGmyEDiqee3eHSk5zS9nC35O4BboOOFcG25rc4sI78bRqu+mADirUS1wLT39sMaYS4iEs4T90agwOGc13xSdYyiNz7cZoxK5awo5eY9jKPp30S/zQgKq0Zb1d0y0RvYNPHQ3IStsTJ8m/tWZPmEHOhkHC5pA10WCgb1afkaxRnPYFtaKWlymiuah74SwyHvLi5O6fZA2QEfAU6zTl5pa4kCGwyy3P3mhY8NsGVfeiHUFyxf1My/KmBUTMbEWEGuWSYXLt8e+J+/J/W4/q5Mjkkz+RmJVNo57K5CrfUDfTFJs4gkQ+KQ6ypGNy+xVMl6bcU4/P8hOTrlHxq84LU9W7EicaWQn9kCvDQMQnNQ5FL8HvgvyMdLXwjEniMeB0cDje/INQL8hesPCZ+9IV/RQIftZseIfTKBb0rQl7G9ouYoBZaLlSBkgom+WMw52ICTF8YwijIw6J3DLR7CsZ7x99Boog/3uQX540dTz8mNMjqx2+NP+YhhUlgErKX9QONfNt1wdICGEFniVjzsQIvOEGANz+DmlThDPA6NVFrqy0KLX4q1BpyAAbwYMBdYA+oPkWPcl7wAAtPttmo3+43p0su+C42771bEXWA+ZmM1TBXeqbts2XQNRiXNxS26YADPUyoXof3MfThf+aL6jyC/iPMGNbE9zBThWRMtxqR6oJ2Bs6s5+w1ccw0FPu4BzvDzU6QfFqEpHOS8rDMN6ej1fnGeLXo+g/vgD/ig+HUaRXr+bmlwb7+5bOke389LuiaAafN3P56Fygm+FGBOz8jQqNGkj7cnnUASdmf/R4PGpOMMCeQsoIOU+Pg8sZgIfp5skgfxU+7NP1gIuMt2OiqbO4LEnEkxEIgHNtR/WQ2M1N2umeGhy5LDG3pNOO8j1NwkK1liOlvcOPrLJ1VAg5TL1Hq631o2dpEURjK5Ky0ZRQ3nQJaRMdE/BXNOdVPpnmLTCIghDtT4+WXnVNUpgrII3dg0T+0EsiaZvbFqJI0+rWaoEy/FoIzCaRGNkxYBQ2pAWAuhbgS86KTTJYolsSF+hOx0NqaWnUURqKamaoTTLG71W+qtLgZzg9zkUHpmf1qoYC2RReKI9ZI8lCsP0k8oOGSY+Ld5WX1cV2tgKxGSudIQwEw/mopTf7VIMFtg04uT/LCJUrUYLxciHvzN+moSXJBd1KuTJMpRsiA2u9NvzwPw9nfK6mS/55ky/zN2aRCWKp8nTxCtYld6p2i/oZmG91bQ6YYYaOsc2awZ7tb/XgfKBMC+K2bcftcPkWK44NyJtMzyIQJLTbKxZpmPh/+aHp+lW7JR6d7rwONx7UPRgI021yx7SR6N3R6JpiksVluFoKZwY9S+vFmf5D5bzU67r/1waqcO6zo2cPHNl1StEC5laYJnLNA+p1YWFhhZSV7/JuA9KndYk8yahT9VOxY/aA7NV62fucmrZ/6Ll+uHekHnkg4IWhvaHUSW8LSnIFxbadxV6/AQGeDr4Tqc5T2mdAyFbj3hOQxtpbbzNYZzQKLS7gvJ0PtGmErO2eU7sDOUlISRFlXJDNIoLpLBA+k13HMm/mrOWcARd0qIUafJi7iR8rD3BHU4O+zjJuWpGw9mJSGjCqQm332Fh5RWRjsE1XWKRYwgGlgJ+jUzW6AW4aWt5H3yKW/mKDJ/h1aR4M7ZgwQ5zWOXl0wAzeOw/Tbui748E7Y5DNFfwakfu/Oscz2ObqnLlvRi5wB+ivGIKG5rWbvSCDdfLau8relfw5Mu8/F8i00PSBMPm0EdxHUNmqTqS0ncm3ly5lPxfq3Rp53MeVsexF9jkPQC6bb7mMZADcO+fW0q1rgo8M3Ckf4qzmZR02RCzFxoMRaUwhA8WHz6usuc5ucZWvpsDzW/utsSoaupY+ai41ASyZxFWMQSXw4xBXx1csE2/4alZC7lelzGvhPTYKyP5oPdMn4M6grBv4573ufBx9XhzIl1FhCr9C+PxNYeFAZA5+Cijy3JL9FRch2/vXSyj+DAjHxZQaiiA3ONAWA2vtx/thVoCeNdMnZhbuE7UST4ViPsjNjUGD0L6NQ3KmDy+0h/qfSvOIz8ePXlJ59XghmzGPRqero7cccRh7OBotyhMpk6th4wgyNmHmvBYQ09G40+a7JUesf+/qzl/AWm2ixtd0DOgfTeWp3SnSDGOC7o5zQWmcyH8YtTdxMahbTFJNjbp4g5JfBTfRqECmbHMDEXGJRq1MVO81tFY7oQaNu+ruwenF8X4KIZIEm4i+PMBCpLoXFcHSav6tChLtSEc0ubgoLdYZaYyXY7FtK4r03VOdVxDQ0BWqHPj2mWHjFmOWrlunLh59Uvzuin1Brvvsl4i4uBrVkUUSFxtp9Spt8Y1Vze8I517qqwiEyhktEa2Sx+RcnUFeTDA2zLsg2SadBhxJYp4NME2JB3W4HCYOSfqfckZ/ZCtoN3WyBGOlKoouh50xwvSjFdXN9WohKsze125NLYm3mkhAPDJZ8ul+UKEvX4y5T9oH4kewno5EA15WXARh+DK21UFl+8sbWaJEF59kLwN9RUFpSeaMgqe0m8CENNxG3R39d/UZgu0dYeHV8eKMyQFFtwpjO4SZSUDyIAwtb+0AbIymYwIjhomE1O/ih1kz2WswaMFKtn/v9sYDBHBL5Vns35uNXj5KAsquiYKgauRZ9PN8gGU8Mo5auxe5TuKRHIuvt9GPShNe17iSVZk385jZ6TmREiaBGELkvVY1Q38vkpml7tEN77XkjTgsZ9VQYHRM3ItzAza9TxZgLwVNpAObR10h6KeKDLim5PX6Du2d/FjlInJqUBblL1SLda3WTisfQf4Vr45hs3ogOiUUMjDrJePN2WrKj5TiqZpvI9dQjIUA1g0sudFY+SWcIKM5bQmOqKj9asoq+0Wk/U6rLpBip01MW3TIXFuNBeO1vVhE0FFIWJTrYWX2ZvaiKcwkuxRgleikTmvDFY1gW8H5PkldsnAk5A5tsi24FDp0Q8Ie6XaNCCHJt9l2yQRMjxD0Pi1hPNBCbw96NOnrgwyfFHgTx+RAns0hQofYX+7Ad2RfSardS13kAPQ4aOWzC25I+XvIVrwn3yki822Nxms7FSw5TGNhy/9DrRQPVR1peF7zRMpep4tUuRpsPmu2ZnEh7m+qd0cov6lgjHiyBGc1EUqX/9pyWpQ5f6IHc/pej+OFmnkXQ6x0cs+w3oWDCeootFXlc93G52XXN92totRdzsWoZLNPHfnKrjAYGBJRKYQqnLo+LU2ysmWNGeydME73g+RmAZ62LPo/Zj/VJWogtgI5Ex4sdw2+h7ENgWGtjC5n6E3eXAPr86shvE0YDOMebz2x1LiRRB4dnJWzVlK+uSAWtrqusAiG6jM0CLmXC57IxSc8B+QTjd0I1RjR3OFsVDDF2mMisknMVB4rm535tSZNVdulZj5I4aCaVC3r2Qim9faiyDUUci95YbdqvWnSjUbRuDTiCEjmc5YS6sf8UPy+c+X4589c8O13vEQLpkhemHJoR9t9d7LGVc+Af8OCu47XPmaE7bVBtwEcEx9W2ELmU92WufsdawgkT4Wi/VBR5ki7BcBOv8wj4LspW7ixMdlrZngsgVATf3L4ZNFZoGnjl4eXOJ9RA8smkpuwPNhR3VGXkwsnVmFWc8qeUMs0UEGTy0S3DI/wVHLxDMLOMZbmle1TipdCI8dOAYvVpU7LluyS70dMWDWI9e8UXEsRfXagNOqgw47u1oO3crG07SVxUVyIJeOp2jIA2bz9zzAJPXBu/calyJajUeYGH+l93VdqsnRbZJ2+GH246JFHHZvV+3AoAlcaZRPkjUNRHxhsWI/XN9NgctVgLPCK7OXqlMTVPZ0WkJq1mq3E0d17bsBHryBi9yU0TC7JY7wBC4nKIeddkrmOJ5brzalItsJAFyUAD3ARwWV4jAltXJBDSEFO0an6uH20fcNxlDONXLk/XdpIGXh//9VzdRnX+dDrFQkJqv6elfSLoBXTpqPJS77IqXychXlNce98KKyTfw91QAfxDvRN3lzkMfH4w+kQTkqlrYz9HsmdKyt89KZU+ULbBc3OaJxJBYw2f45plVzrA8f9MN5PVrYAI3R7qusK+Fuoj8JNEv/vZ6kXeYxXfqEbgTS1V4NXonPWEMGY4/yXZ9smZqsdGsRgA8qNaSUSgifWRMHVqcnP6UqjwerA5DZ23FGoSwuNMD3aJFUx0ObPNRJlrmm3IwqYx+c/La67VWDOmwn78G9qyRlobpGkfDUPQUNN6YB/gFPThUdcFboqW7zVpSSf1nHPkToWGRR3zfi1jY68pyXVe8qPaK7bOrz+RLoPbqD37csU1TYSWnhyPf46OS9PdnVSGn5Fl0ZyN46VP+86lrnDxWaYj+l8/vOCfTJEdHtd30QQ6eS4dkO/9DLs/ZdDyBi+acKq4vapVoLhrD4gV64SQqn+g8yX8y5SKIrRBJKmooywjo1x8A880jCcO7eJgX8+cqEvpw27KDmj8c6SnEL9G2Q/reiI5jUXUHSN7Mgs+eToewRHSwI0RViVaOZhs/8qb1DS3U4TvssYRz7j2Tl632ZXW/nWMSr0ZFhkrlQwLcaHTMZCgbGSydq/M1C7balDuUgORTDPNr+mp+XeWR/lECvzYaIGS7KD6vgX3Mfq4xldIl2Vr7zo6THW3HdFadGHVAIXPwz4zq1voJBcYlv2zjN7d+U6qdKt3QIha4UQsXSutaSLjdrNcMCd9ljg4KHkRaUmEBIrs04MWa3y/1UedVwK8F+BRz5lsHuMzqhSvp3c8+CRCiiZXoWYuQ1jRYHKdXA2wZw560haHB5sE2ZynoKJIBFQsdoMOTXXJMhk2jDY40NjYt4zlf43CXips/nWFSzYhr/nIFhKRp7AwuUUbv6pb+IDrfve3Ge+j80Co4eICEJHxczFNT2QM8NzQ0bBN7SvF0qagST3bd9Ekem1m58CT0hzu41kc8WdDdBlI7b7xblAM814DXquNyYIIvtcMy6W54nml5RYVmbxB+JonjatvXqpu6OHxHxVGAqLJ5JxE4K8Car3nXLNdRS7xiIpUP2/lIgaps5pOFb2fN74dv0tbWmnZJCcT4L/HzA5By+uH2HCNB38a6entemN8fvIVC9dblxWP2VAuiI7keC5lYlPQw4GuQfoVzjGw19o2NbviEYJdG1XvHMNsBfQx/nxogQCjEnYYGGpfNTQ5DCq8gwx5V5Wo1m0+Vwa7sI/KM8/apFBxKAvImqbi8Wx/+i30MrhSfBCOvhorXg1ePY1e0mP+EX05vMMlsEkxgpDD5p06bdJgsGI+jk8r+6iJU+zZn7ra0vtTgoEtPEl/UhqxHy0bXFmY7PlD8vxh3rMY7FzkPsJl0bP4gE8ZfurkgM8oA/oI+ZArLgwdInj9IZy9iX+CQF8j+cfzGU5VQynFpxgOot/MfVqP6grHr1X6Nc83aRIbvCXAA/hc6Op+Nkt4FP/untkWgCGGF+NxQ4nsibXAxI7OKqOxtU1CX9pHa4US2Hfdsj6tcfJ8z/z8La8hFk2qrntkhyTZNNhCPl0oLOYLJQpTAWrmD9jJn7/x8iLjYVji/Cb/rHjTpZaz6fDyKg5SDRD25RAXcQwpILAG+y11aaP4H0YpD3vTWAHI5s5UkvzP62onK4ZC3ZMfUmcNCq+jN+8UEBm0EL0/ugu7TOSpI31Sb8ZzJGwzuted9MfiUAEoGzOuJ51YevCChIz67MnV90r52Ht0s3CgndDAuqdyEmfPsEVKXZvKxEh4WHYbQ39AgF9ka90s2SkbptKLCzWtnLNcdBKvOntqKGyBbnXeIiFyhPt1G8RkX0WnlqhqkSjY3+8buOWVeJxOX2IWkv4UMc37Ul8vOjwkleAjjfeuanU7DiA4Zn67EjxgcAsZIxka823kCttMTSn/0n5kviGlHusS9OEV6F0YNdWeuweI+UL6e9rvb/1QFeb1rAn9pQIvBTseXgORfctx0/q2o3zNkyu75Xjd5CGfsov+TKliAAdo68O1Agt761VBwKa/yULQMLzL9IyDWH6c3ZKqA7mnuxeNOIUcCs+XTTwyuTxEbpxc/azo4q/kPoQNKiCCUZC6uTKIvD+6xA0r7OE4Y+/fUKgApvipG5B+pquFSjmPI7cmMVQTJZw2ceuxLn9dTSOvcl3wHG0yhCpu1OVkQY3yPJx6UU1XgwANoTBgGV/kBZPAn6HycFHI6t8wm/7YtBWVmpA5828XRWnI36JO0IuBHsxLs+adrMzygxx1OB57aVaeQkYSJ6KrEo9Q5Dv7ONk2KqZcIybp9BxR3yxlj/+nk8iQCGEheA3NNrXsENQEM4ZuggtVT6JBfdeGEoWec04dsz2W86eHgaAcKeZZb937JkdgGw306OLiWV05c3ys0pdRR009GibMdiflG9jpEtKfYg9nUjLWTxa1HcF5xaQHHqapT1SskQzO6ta1ZlCJe8gBZdOkTTxv1MZ8rnMAOiCrbozCbDfWZbBp2tqI0lCnsLGgV22J64iv9xrMzumUnkCBag3fbXjGqrY5pppGM6VNPQRh4QJoZ7QUatxX8tQsUM5tealZUdMbJUa/SbbeTQC7Tc4KK7uTLcesChzKpzdfDtp0c4YTVZdWgR0jCHI0+Rk1pjop+A/AEDM9Vcu4rmUsmOucImN4d+NcD0SffWQdFpOoHd/xrWvlmJ/2BsV6mQHuzMcDHJCmREnIJiWI6CTb0bl3xoLeD4bLGiSop/v76yjvKAJxr6yofALfkRGFN3Zxcdn1zK3LUvan5YDAlEvG8p0hFBW6RRlu7hqPbyvE0BxUEZcAxMwQqsklphLDYhO2/01bwL6Z0F67ugeTKmBNx4ySrIdXGf6W3+qBUS2OBMJYliYiRCxO/oLYBd0vERWfeaI7L+AWb4RWdzG2JzIZI5/bDJBOCvhwFEmwAijwxNDOBNzN+d+8j5q/k67h3CMhkjnFQh5U41KHjTLYG6WOPwUZ3NaxoH/VeP6826ENiwLsuRf68Uxpp9Swd5dqYGNOVJZqnYae8G0+MxbpC3cjE8+kzohXw313JxyHs2OEJqenr7hQxU1t6KFqewgtgmElxS3pZUvzzQr+Tj48e/D4dE9jdCMMIb4YpefCg2IoyV4sKcgzHTjnz2i8x2kx3jux+Rp69vDwqNoLIJChbgt//Dehk39hi1DMvo0KUruABf0i/ZLrws8AeQp8zOVw27CbPQKFGpX4wGE2hYBT4Slm4kPAmSZYWK9myVmv5KB1gPyTJjzWmD7ypcrhdfGhUk3fGSIxpnrTdR+IZ2P5qM0aGN7WpXMLFDpUMRooKpiGePg0JWLHT2rWq1RuhpoqfVl/aG5BVYHADoNK1kytGeyPoysRZCty7ZUihDPmN0CTPsrKfKJ/hvJH8GOB4nHTaHjXe/39Ip/r1V5/h+wnqG5/+/v8We9L2TYnqDLaJ/widjV4d1gk21/vTgRmQf7SEKjzD686XaZIOb0V4357W6VH/stLMDnwkGYC7LElNyGV/uTPfPa8Ue9teCzzIqltQJ3//9drTuXCFc0i28rNA+XqOw73hlOfYk+uHVGTazH2r8D/ZLhFGzcUa86xVDBdB54xKQGltqi/ZDIvPg82IE1oIP8stIk+f4CwJFeUx6CbqQr//RkeNW0erpJ5gn/dByX+zNDSCrwknQQQPLQeyFgRGb5qgeK4+PmZBh0zPiY6wH4qtOuNpmzFm7aXXINy2B+nidN4nbeb/jd021OfOlx0ff6QBKuX04d8N/WRyJPqDOVXQBFfTVTjk3vBQIKhY5UJcttIvCXRo1Wp2gIZ4fti/7c2ZAHlI+1gA+nEVwADIeTvIk+Z6X1NcTK9IiKTh9py/z2DmaKWm5R2FkpbiYZ2E5mH8mmcU6S3oB+X2D9lgSSNlIyxK/Zr3Or2knB+EsD9/znjK6vGtvWqXMikiSVn+szsSY9q8WtSk56fMfbkzRbrZQCD4EXDmq7+ELao5Yh1q9/i61DnpnGiLy7BSQMZtcwZOELgr6SDiyipDt3nEPHkba0OvTLNkJJ19DDowBmz0H9CzKvCQUcjVVyGhE78GtrejcxDO7evThalwHt2SBtrw7mKGbRldnXlY369PvIPVP1L+g08uHwI59w7scKX5KyHDTgrAjkU9HW49h9MwRIisU2js6n4/eAu7Qhy+XwWJhZP2Yb5Ou+igzzx+ArwwocFX86muT89dGjyPZqmgF8aQ50Kkf+aYc3K+TAj4DE4MPyLq8YEWv++QtKBIkEAqS3+ySK/Y30I/5UNBydgk0doGC6a7QGv094BzWMOkEjX82kwS3SNhlV3ja206hRlPrXCfiMQKvjdfPVmTVi4MQflYman2cdbNB+skkg0AJFb2UMRz4LiOlm7DSRjlUYwJagLIjAelCsimZLXBQds8AH+L9jLlZDpyb1JQuQAKWjTGdL9yGQnBYR6HW1O/GJDFUvT4j8yn2Q8rVqKK902C5KJ7SaKSoHDbqSVKLOZSLvXlFsoMfGswsAV6lwIApT5XGQHFnP6faVBG1RSdaLzfOR89/wtVeXAxu87dCxFpwvp/XOiGdgQvy3x70lZfyDH2LzKB722UFosCxWR5Y+gXeVQla6HpeN3UOZBzMMeZxIoeljals0p51GxhXVyrUVb/kets9zVjy248Kn2GLBG1xjSTF56Quamwvsz4uWjWlo0bbudAFhMefEQFZZJ+B7bbJ+URl7bi2+4zXjEssEfDQhY4x72V6E4BPQ2JG07yUTZN00z8hoO4GhAbD7919LdzJxKxyPd6Zylond93EesOuuWghsQbbRnh+G0GpVwtnlOZYkjpvsraxvmC9MtggbL6UdvnaYSv5WqFRen5Ew6ULTzdiuOl2UHO8iEAijGYSVxf3dhK7dBq1uTDmyriaSwkInO9k06UUfQl4ePZkD+RTNGkgmpD8BVKCQXks1fRjWxuYFo89s0FoZUsWyluXai3GnTMKytbSIK3wAmCEEs1UYUBSBvuCF94yjHXitV8RfzCNau3HqhGpcUByhtAiInnUDS7Ttr8zUpWOWYMbCIwxwVsi0VDQ/EwITEoM0UxCqgrxKb8jjtcd3b3hzXBgE9A3cASmnZ4je5gfCHjMOUNQo8KLw99JmWBH3Hej/GxmRjzKctCCENxRo7VZJbH14g7XZk76r/v6gOrd9+F0kPhYTHs0Cognfid6DsflZ0o+xAqyTGBOs+0dUPR2+Yac8W2oW9E01geVqCrAXNJr9nYjqC9bHbB9bRwNdvt3VbhtRfs4tPpseECAPkuHOEOlCAj6/iAPlC9CFNCAGqGMFJdkY8M82GVXAtHtu22IQBf3QS+h7r7sSLtyMkOZvzv198RaVu3FJQ67rVfcDHTkRljrmj26VQSCsW4tC0bKdA/irIt3dB9VV29L5u5DQd4tFDfZ9pVO3k/xmkqeAGfajYlPmQcXF2o9TY2gUpvGREMILw7DFN68jspUItYDD4NqUZfuqZCrtveI+vSgVIgldCu+ZdSJnRFDB8QDNOYqL9aHblFg546vNTumPe1Q0+cd8jNaW5NEwER0C8BbwfVABeSBvdFPFjfg3d23/RSSfVFPejTCtGgXu742TD80QTLvE7kHKk4wZlQuCnfXIE5lOFm/s/Zx2lquZ72s/Zu8/d543tFNNHBCRajb0TmC08Ek5Vmjk1c0scOLp5lh7KSbqRqL+0e8SKct9g1bEXGziyMI9n9ftjCi9RHpr2vtK190duGbS7xq5FWwnyPaJZHivS1tJ9HEwzqsNOxnnbJNJn37VRt+2nebj3+aquc+HWKY9o5jg8zq0rOBRuCnR6Wb14Lgz1uPC+lM1b97zT477RONO5R5XF3j9hYo+Sk4pYTsd0duLcZ0IgqGzWDIEbAyHv1N5MEtSd/l9Afrqq4ZF0mcDjxm3YVrjfAbWtIiBdI3XfFV1qgzuT/NAmWi4MEz0fH9tg08bpmt2WwFeIzD0R30SlSlqExQfMK5qFp5fkogSRlhzUJRGR7jBipqnM77kQWFhMB5Ame+QaYSKae/wzpbEmkeOTyZFFeBWw+mPdNqFSJ6a1G1M1mb+P68ZDpFENwnSS6G/V/2Xdmm+eq/Q8PjLxWyiS4Ix38guNMS5DoM5GSXIZkXh5maW+5QGLfV6JaCTLjUPUMKzpjyHovshqlsm2MW4C9WT6oGNWu0Bfx4iOXuIwKTR/KkhVg79jmYLXDpFyjGMdkKy0x9TFg5YAq67lf0ZPrJnl0FbV9h9n3qV97tIEG2xs9L7+dGWtwOHfOzCIwYOMxp6nDdG/f62eR+uPkjagXAZBlQWzQiVuy7haTuGRFu0i0DT8q9y0BL0LwNWTdA4RH7mndOhZd2xtrvPtAg+MhWqnkMcCek061lHEQOsxcyQm3YUsQpjAhBkOZMYIQHKWQxs8ViBDFAXPPUUrQ7q5xvS6z1bmx5gUWDYXBJvl54BrQFFyERVrxgBySf2+ABkyODNmUEccZidsca24oErBtYkZunh+XBecNpMLpZ4cHztjj8B7IlSCpY9StZm1GIjt0TYPayLWpvv92TrxnNphWHw3oQnVDU+UIkMUnuNHwyZuyX0uJpzms2d3Ni5T/IM4Rcp9ioUawcGzOYAMqPdVTP/UrG9apY3+6FCZ8Cj0XO7XbxBQi9aPxdNFg16e/Psd++IPcAoEos9OxKXR0ZMmViE5pqBLPe/5IDarb3/8I9p0dHVPNUZ9Lgk91yVsdq1JbEgaogXluiwwrajmIpn15jeVa9TKonJuLCnoeSlot+76Jh0Xr52Rzvh/ZHSbPfoirwJiXTS7fSJBi276s6J9x/rM/he3FAjaDFwXzOspCuF7BzIqXrhGRMCvfW2p9IN0TuhN9ooUimf1acIpAPDaAFJ2twwz4s0TJduAqBqvDGLIHGYCoBwhjoUkuhjDYxF6QE9eMHN1nzLgi5J+B0vJH4c2Sfu1ZCgO4bS4qZunV6twO2j5C88cfIbj/6yU4Fv4LShxKpc9KHO99hM69XJrQkoJDTEJJtLgmErlrK+bvMUq3LyLPvl2Qe0/D46mvX3Q3Wj6kXt9TdSDDORsBfd370FXEZrd+0cwwMlu01NClSqA4g/AKPAVZtOeWdLu6faSr5o+zZHRcrlohcPMZ+2thmAma9lCop9isuMopG32bHGiXdFlfCxQlGIqVZp7m6Vr194XZZlJRbXznpCCozKcPbhT6kmYMoEsd4h/asC/pO/UuTbAccmJmYtjtQZ+F4b6DQob87WoolwYaZ5AuGf0p8CLuh6kLE/SkFlxbcp8+Ki+vWZTIWSVHw/lnUkdu5IelmZ6B+csWkwfCrHKMBdLKwR4qW6B9fzvO3lhmzZIyHRym2hP9BYFS1E2cDL0Ya+8URssKxqdsq9IzPCMexv5/edeyzSgxzB/dQr8+l9crYO0YEqBHun1t4Xmqb5PNZqErt1XkKXjpms1aaTexGaszXZhYcnMZd3RJEP4euiFfADSNwubiL8PcHpZCGBvfXGtjplVbKZW3L+cCmSuoMUCvA/UNil5fWyq+EYIU+20sblxRizspi7q/RY3zHNKUgF1g1fLeeKz50N5Nb/a71idxebn3M9kaS3fQuZC3jycd1vXzQGlsEzGiE6o6eQAQZzhf80fhBCCaLwv6sCT2e/Zwpejr7FUQs1Zx95EpBegwdJO2kKUS5nqiPuGUASswVezJ3+BxdR4KxSRUCBBiq2wOIYHTKHmM015XVuunx6fsoDTaJ58wGfdT0ZM4J79Q2msiUJaacvS5KSOXbv6AmDwSW84pu+6SDdD/O1Q4F9P0Ghyay0xWlKovyTEPIpcA3CvHU4cyrq309g8xdhX+0h7xpcD9z7Eg3TAI7rgPjgm2qAh9eH1ZoGsdJ0dyLpvSAjoxDlNm/On9sAdXg6p1kZmeWU/LWGBOzwtNi1Auzj+UlI/J3l4XQ2wxIIhjmvF3k8iqDdOWwZYDNS3qaW1PZTSTN6yrS3HpsxBg3GhGvx3S8apfsHwQSLCq5OyXTHsVV7KyORdUfaiXKfbka+uSHzdEmLCxRbp8+vRLr6alrybsINCDBHrD6Kxfr9UCavwDqO9fgkfX3bzht77G4lcgqxhQayT6wsSAgSNQ/Q5xhaoNJKk1j5AD3QlnJhxWvcsH39GsFflRAqJ9LUKhG8K4UwfjaxacQq/TxVmoqNq0D3JSgHS7awlQqP4EyYYouh/3hLULfGVLgCUhSpHejIhmqefiRIZk8ScuFQdJBuRWoa4j/81ACSe8TaIDqTLthWArei6+y4Y8sc+Fsd03XnlQVn0D1wB4wekGJZYjm9X2TMU5fQHvQ64jud+yPPlyLPOn/49Rmlwl1rBop9/TfVrX9COueK+awbfY8qcgIeD46rKYT3aYf4j/xNDr7+ZPK4RbnaZF4p9sPAy9JrFgU458ux/srwaA35ILc9sc/8tps3OzktQ53bdKqjYOqpuEXX2mldqIQIpuHC2LjO4gZGioESmqdsNimdEdDSKsCKmYFEZ1T2hU2XwaZ9lzThUUuqDNqHqX2F4PJXpeavo/VpxfocrpzQXoEYMZ4kgTerSgWwtfH8kfH7CTke+z7+iP6YL4uVN/A1GE3YNMoIyvka/I8aHFhoVhnEaniUo76Eaet4v5p4WJ7esR50pznIR1YIL31RTCb+lbBrsy1Bi1JXhKR1OHMxG9IaUvcbU8KBZGCLVa5LnFnVan4xJywjLqBqUe4OzlybwZefpfRa8I65aJLxzH7GQoTDt7eLG53pqP+NJsuRm9LV7ulk9fZ9E9ph06vn7sl30i+5dgnlDYLeQ4eUeaB8xE4KMd6ZYNSHMPdyvZuCp1nt7C6VZspbWk5qRxT/bKtQtfrDHhr4pNdSeWu2QsheFp2gNaI/iDXRQzFN+rwNehGG0vDuzkbA6B6IQuco65mn60tkagvK9mTuxNSFMdzV8ngwIY5mmCzd0wCiZLg2I+SJSGEuvi0193uewKiujY3+Jv0ajqQZRqJvD+JdF/nUAA8pP0qxoxR4av2jrHVoPSUGXrVKck9Ej00LkJMuYWiOMWQEYyJpgm0su7I9wGN60X3yVCpUIS+QVbWorpt0/JdW7kYYciChcE4hlryPJ7UQh505Cr9MKeF//m2HQN9iuFNU1GDt8tWf78MiknsR49TyLvAK1zERdpNOsQQdYHd3eYWdAzB1q0/V1sQh5dU6Xe/4RE8ubR8QFLaUYWoYukuDl1eU+SwYE4rRpGnLFOPT36yURn2AMEiPhdlykJvvNxo62EbRj2nMQD0EaIwROkGsF0e1MHzFHSzu16iA1AZviitYOfQ86mEfJPy8eMqJNc344I4yfpLNSmdAJBvo8ThvH8gS9qDkxjiwQJlxECHe2ZWbIeTotUj8NjO1FJQ0X15r+e3Fiu4q3mqxfBXDDfQE+szM3OLe+7a4SpsdRzX+ZoRyMpzoYANw2gSH0q5S+MwGuxpquy6/5z7J4IdoOhk1nWsNt48d+wXcXBjny+irnioy0HkUdLvOTfi5oKoNXXv1MFeW3ZbN/zIdt/ukf6k/PEpceLkGeny81qUo7qS6r/ZW7anG9LMCcB8ercdE1WhVJpMltPsgYbn1yXICk9oVVgj7gdu7a3L5a8J4Ku0NzvDqbREYIzrObeWL3WW6Fo8V8ddfyIHI2Jw1sXD0tv65zVFSeEVa++ftPGiLyjGArN8tMeF/hAFcP9RiOlFtncFW3My8tM29HRgh1zI26UcvDZayG7i88pbaCwo5YSg5375+FGTYkba6g6rQFbSnVKflgOiNcZCCmaWXcWmofYmVtEv9Bw45Nwe8G3FYSZYxbRIlmf7VQI7W7PsJu2cxSDDmROFbxBOLybWKTEah+DDWE+QN49dWxO+M6vNoq1xbE1CNbD/AawE2Rnkj9joeyVn8Wry4z3a3DyAzJ+uIeVRafSW/FpjsIEGALq4XXs66TwdRkOjwN4ha1US7B1C2qrmYx4KsjZR5Tzu4nKy+NurQOG+7rzfV9VCcB8LHt454X+XXuWUClNCqMWvk1DUWXqbzXLV+7ac0+b7LYWp+G5pYidWrb5QdUOIR8OK9+CpDrkrSwKXTtUYTASumsdjx5bPgKV/vu1629T+0Bmp7RJud8BabPTHY9F4ofWTLztM44TRBlK8fyrYbffsdYMHSJTVmINb20aL2Rtsauynpko5MreaVvPQRNXxT8TrYXUIfGqZjaMr1Bz6JMWkDWoBJEtQvatU3hBZu8DoohSuUWW53P+IL1IaSvBp3Ph1apLY+t4baHs5D04BPHW5tflpmuCsGpAOz3Bjan8aw/UStZEfA3T7RuEZ3qGXc17whNrStfkZMn02aAJtwUmR31Xg8VbWp3OOuW1WC2mwnyj/TVJ/tjzPDTb+9rDjUtF2jIAzEoCl2j/vcIs5x0vsJtsfBQlx2ayb1JoichP8vNIrAbet/4Q101lraIojFv+WfhHMaxwV4jQ+ql03BujTIDl9U6jfrHbY6n8ypxBHbnXC8d+7Ai7UMv0r7iins0958AZ1HdWJXM+ABk6dsmXMWCyLJ9P7auvJHKQcjaUL5OWMFe29VMHyjHOYb7cPYAmyFtHwmUhJqt50YlaqUr14+BkzAq+rVILPvi3z0HqE2OAwiY0/bjTTGx1vHWhB9RgiAZCvQxbh/5He0SAy/h+pHL2jjXgoH+8xMCRe8ddXn6JwCkxexShS6y2l4N7y2rYPNH0rDi2c2zqPht92fRyfnz3IN+F7PzgKuosK9WvXkLMP1sd4Csg69x4q3AG2SgAeWqsNHU099tjXJDJ9cxmOlMPaflrE8fFC7KL0OWB+NLTwALgVFFN6lSB0oJbXCzSNruP3IPFFzuwLhUrXJjVpKRt6k+PthBiFb4OXJP0/Hp9sSXIN/24g7GgHns761ykXXALNFLVhvwxg0nuKK1KdongIyKlMH3DWxFCBzgD3h/CZiCTvVsSrqMAzv7vP5+6uTcZYOZh3qzv8eSLbymD0tnzoiacH2kloY6/MmyQZOWRmdV0CgxU90epjLwQzLABMNXMgANpRKxJM5V/T6bscMDUsQLFP7uwkBMitI1tgqBrXdOMwIa7DbsfvcuV36pdIltsKGiDn+8mRp96Roc/rcezcSIOsgefjQV98XssZrkk/vB5B50z1aEPgfoNlsgzdbbMG+eCto+sFt+qAMf6e+InkYPe+V4SlgrBLVs7n65oTCHjypalefRR6XG8qshXTO7HHsa2HB0+gXWX1U3nvPUsQbNEdMUsA6ge8AjPzXqfURWV3bwKFY4PszFS7JOh/qCqWbp75BoTsUSUD0YNvYaaFvbeckDK5IvxdVHIi3ssI8wgS40m3ekAPqLWSNmFuzgb30KMva0UGHHCyKp6Dfy9bOzlLn1qYn6PqROy1TMLiPL8PvlIZfHE1gzrBb+Mabeqfo2dKL2gP6kLoZ2aUC32B6Z8LUx1v3yIvn9yRD870NnUFymC0B/if4IsC9wMdK+PDrNzRLbSr+b4LZmvzUBcrtQMmGjkX7sHp3hDxsrqKmWsKYlviWyuUpgc7N8KygpKAqQN13mXnBneaeiDPyCeA1XXN+Gy/Ssraaymb+AqsQH2dg7eNjueYrhVffNgX7kaVYGwfV0XzmRO6iV23zHhziCXl/cdtwHXsrvttR6MCAtyQPJF4jiBHFjOaDaBmzzrRyCfS5ppEQ9ADZpXWC+oAQP5agAu86KirJmSBmAKCB97ogNc4Byza7SD1h8R2nly/NU1MieSFiJBR8Ufy8f/GUMwcDIkx+Ore+yaZB2IfPUS+4Q1Mafc/sc3oz6hGrLlc9a5dlr6LkhCY0QBqdPmYXqYhd9CbZ4BLNV8ivcQQZCk8dWCK7yc/kC48V9a9d8FPsSo+1hdEvJ6OuGHboaiokzF/ySamyIOUZ+QHvvpIn3iJzvV+BiyiRzjDDNHXk1/BCoSem38dEoFuHynzFfhB0QqfMK7XAXlu6azFCgCOEJNE2ieZ7BZ0GxJYMNKXqC3EtDJvew0ZaH8QkIncqqCcDQ6CLtc2/S06+lKWPgon76902JXXGhnVmaTT/HSWtiGs1c0Gu0Lci+gnCPsl6EIyKTS/qMth1aTYOLnDiW984r0MMefcJrrcJ/RE+EpSuI/ZyJB7z2ZDV7Ag4ErBzAFwJ+aTjpm321f1mVU2dwq78ix2vduLpVHAwkU0afeoo6tymA728iMgHasTWwo3eu6sX+Kq4ZISaKsibaJw6hB64Cj0dr9M8QDpqb/HaUdoIt0FrsLchUCnXpL7HJiIQnTbKsvyCHJ4B+9zrJSGKkWe0kHq0F2zQtr1+A2dYb4YyVBY5cVN4yb2lccDcwaK/tdQhiYPift7BiusX36GlW9m46MJhZ6+7RtQeCpuuhSgAARmAWhw0K2w9WJM5qJzvejLS0jIpcSGwKEj5mkusWZSqrlL3eYn86NvSLjLTXPRFWhBOkkILJGWVwF+MxSfiSLHnwaLXk1H4S20vQEyzF8A4tF6vj9Xo7zrgxdMIfvjmEkxyiSwqyQVG6z70d4Wqt0VhjJKd7ARgxLxSCd5HaQuAzz40wT4+LkBXmQlv7kqAg05oqwEeUA0Bp79hV8NlQxUX2OFZnh28hPJnP+3Aw8mok3Y2aRwA+HMaDjQW5lGTcc2MagHb2OenhuWiLJMHhPCvYyctilC0mX73vumEaiZYIJjCGWDc5mbUNS8oylVpzlg1rtrYdGDmssytiub8m6ffbdRy+tClJwiJY3jLS3NpWhyQ7brjp57yoCs8Lpnv66X+0IRk8sBZkfAHXm2rFzPyb41YJtgskwgTIgyFeHKwmhinbvdulsND0vfeoD/sVKbX8uNDc1cjLRjWtY3A+miOp0DcPD+Le7Vx2EoCJ1OEIH/rQ/R1hZfwWLX7HizGKjMnhKHRYanwp0G+19IYVqZlJnKbHiQqxmS/yJvJ9xiKKFrIs8wHYMRW753LOP925RhmjrjAYiXPIs+E7yp1vRmArzbQylsp5DjIZEizkPGabs9lCEPbWGSZPOMmg2YHuajG4YHYQaIfnsFNhy0luSe+tsnIWqrMOB4KqL5LtEkDbN/9gnEFL2AztWGSmihrfLU/fjl2CZeBWoHs8rHgoHEkeySU9yEgaveTzV2AQBJc32FNerSWZJr/Obl/jowAC0e0QKHzQZ/UtxqSDYBcOdEUXZbXsQby4aU9lfQxi5wRQOf3AGy2yicfGxRWI7eNSf6i23N/5dxr1pSAoGRxvV4O8V3Xfl/LXVK3X+5qj4yRiGzRWnjAz9R4KoBUpvc/Vo/8nKg5Fv7Y6y3g/p9zjvXkIIPH3fPh4tcw3FGDr6MVzvl3W7A/jA8DeUdYcZ6CypVaElgnQAuD6q9U4ChLKyOw1EyFHaPkdZjpvfy21fBMvsgs9wIrZYVLHIpWnWQhfkpqBlhF4WnqO80png/+kHLyYnIrav0B7rbPEN3Q7WPVW+JkbKG2TwtL/EkSF8OM34wsibVMYf6p0S4+LxanXzuiq5MgmqiB2wqAxbYF3eFA45jGjS4cvXHBYL1uMSViQdEL3aGtDr4qr8PGbehnqDp145iH1VPfnfV70GqNPS9mfZxS4orMBBwARiTaeDzvehqv8kkig2GHeZIOHXn2EBrcpXm2VgQtz5nXzMHwdD2plo2oDAgFGb/LJ4d99daUmaZRWEMCGiUTUaCA1gA67BSPJQ4qRTI7kQ+5+QeW8tuOY4rgr5PgH8PZQ+A4MG4Y3RBGqC8MmtEC26vMcW3AiJCDA8WvZQKUjsVeOCKQMgJ7JBQYGwCGcxtf9+mwWLHWCbEMNi4VOzFwKMt8gbfB+ZVkBxBOa3bdnL2+TPE11wZjZSzzBOD/RjABv0+3/jaFLaCoHj310CSd5oZnx84n3gz42wF7DP5CySpgQRtp0u8DOxPK6BhwsA7T9awRwZXOW6IHMsTjMxakY/YxTqq+TWIiL2QFoP+MEhmzCudQVsnpow+7fi1YSsCJWzinEznq0acjHitLYjsXHWoj4Td8iSqGeilgfxE+onfgdxh9ikxUaFQAMIWbe65OKhFTMpfRNNtsEKRtCNNBm2IcMBGOjVvsrXrbdMkHf/8EJj3RXQtA1osCgwzYCy7gI5m6BBuDuRzQ2+zlJzV+GDNubf1kYQxAD4qXkmdT2tfCfu0DlhzejV9kF4lG7q/1qpTRSx03cm1WlUHUpkzcNWbwlESz9KQGUiW3XvRWFMVLEcQvZMYTCU9qRvxA2+xSpFNJv8WKLR1kJ5IOKII7RSUg6BWimWpGh+VjTAqAkFh3ku0kt0Dw+QmFoMMxPR4z5iUlpd7aBIt1rcIuzT2/ZO5kupRAgWO97ooXsdXjC6Ykj+y0iIj9c5KIQX37BnDev++TUx+Ro3AB8k7pG0PI8gMV/iGCu4yfP/M4rEJZFtkJSIl4qSsBFsskCLVx3x+KdDgHOOUVtazswZRChdrc/4aoGCYxAYitASzwobKSd+mw1EmK4uUttzXk+kLYzhefRACsEuLWX1kWjQZ70ErdbCOiqoOHidlpZ2ER3AqQJxMBgHnW41zb+enKdK870SBAnsYYJ9JoHJI986j6Om83faGf093waR73J7ZBMk0N8qekc8KeFpRI5lfpfsPlWCj2iOJkjI7ltyz+YCL5Mjondj90za8kfxvlgz1RqLl+R7h/vLMo1cfvVxYBpsx86fZqrTlaP5VjYG05+eDE2YkVNxEvF5E9bsI/hAkqTOAIqQMXFwkDFkEY+nqn2lPSPSwhJhE6nhO4sbkf5LaVhgYGyBMZehSeEJpo0vm3e8yS4Cq5uveVvm9sPzWd4ZDAqQ/bXVsNlmOzcMb/wwBmID6jE+GtdoxQAXqYQZqthPnuntXWHnPcd4LT+muaVQ/yAiq6pWFT8WiVuZryqxfUL06IB1dRRm8oixhGUsXvnLMcv3T0+iOT0+Ff2MbOeP+UOce8dPUdX0mVzmv/qEiZN927hkfHM6ekgjVg+G3sR1NCvMPKe6vlbPfluZzV4+pXrxkZgEoXsMYZGYCHZWBrDLeG9l/h8tGEq/H4hP0QdZBBrMZp1DBCI8f29K7r3VFenq6orq1xDpviOwQ+zFVbp7IuYZNnbymeJfZigY3SQDQ9GoOPdPoJdRc5BU/IL0Jn7RyMGsFNlfmUG6ERvxAsaPg8+7vUXLStNoQJbsQYzFsCD9opsOZMa+jKM/CfYnm95HK0mnJrjzfQ2IAgyKdBR9FMUTN9t0KZ3DaCukWC23WsMjEYCQvrb4oJYgaSJ4xTxGiRf6f0sHjUusGu/EQfwUQNWRk+jJ/V76iCGX57xPJzBxOlrAaQO6X6Nyt0KyoEoVclWl6XZwjdUiL/zSjA46X1Ks9yqdIqe9xLdGb+JDw4cqqJQ2+MifNFJUk4kXhJN7NM/rbPAZ70f1CgcvBSFJ1IVQawxnowHpMWVVQMjamFjQzG0WHIZSxcpEVpSV0i1JSbVAxV4LyJN/woZ4qS1f73Yb7vTrKK1fDW0F/8bXtIBwehzqDoai5gHlpvM+pO/aIUDSgD37kfq8aT8I5XqNWB8mbeDepois9T1zTmnwOuXOfYh+ou9ZTeu5BpW5cKqtwD7vE+A22nG0ELQrwh6XLmid+ZxGdDAfII2+u/mzGFfWw/BofqvtWP1zLdoHn8Lc6Q1LAEa2q/Vwd+Se7R5nEpkogYHXN0HMsb0pGq2VwEQ374JAZkJdAdGZASRuRklEuJ+3uLIQUh5BpucDJpFlPX0fOuzp3BufaelV0w8hCWbtf+tpCvTuJ4EsfsyqYTHHzzRplf3N/yxLt5oS/Qa6Q1XB55JAXqLRV/XrxkJEa/9A5vgC46cyVa5jl+a7c8mUsfnq3x5FwuBDejDKAmiORLbu73R3CGeB66IPw3KMm+EuFMgmmx5Wcf25uMbd4/C6ZwRo93zQ6EGmtvrJHR986y4qJdsGrYON5pe+UF3U0vHW0iu5REV2YOSaCqSJEUEB/+6mBIQYhiV/WzMPRlkqA1eqCd5AZ1wj2N5eGDvLcZ2cgpG+0I5IdM0G6CMCSSqPUxULa3+TYmmoyUf0/EkGvz3WSPObrN8dWwVDa4SKgbeasPEznZ9UJngJ1ckSpdb3zfxsum5aCrM6fSpGCH2+ZX/xujWtCiWdO9qKFBdpwV9o0/Y+MDUlupZhPrcNrbzKYcVlxZeGogjkmj+3Qvon1WEd3b5vROZ+Nbun7FobX9qko+QemB6jWyT43LkXGwb8dRUKCyAUflge0btRQnT/NSg2ktqimI3CprvC4ssCuhuKSfrnDwcsfEfAOnTxwDRsrVS/HUCOSZ1Oc1hGLEVWtulje/m/1ONy9fY6yZ7TSiHfeW0njuKngWdFXAXYe1QaSP9xrA+YVXJO8WRdK9SBh5Md9GV33mRtfT64nd/8ztLg9kPfvd+DGHzW7UjLrvkXJgYnXKANLlEYm5pbZ56GXSxPmJLdwXfDjIXJDmCLytA2p42KOMjXoEX9y+uP7HA9FdMeE0eiNMuFRuz8OlSMWEQ901LCjJgsVXjHrLuWAZ6zNa2iOy+9LiD3HyIbrec4KGpuwyZepgZaQLHcawD8vF0BWxBcZbOC/oJWndA3ykRMwMQI0WHnfeNjs5+CFHIMAB8VdKuDsxBYpe3wz0YfMx6XLEl6Up5nmTPbE4HHfmcRGrkYFo4AfPDhGnKfYZdcmnkj82AYlK3E6h0yNh89ZDbtaULJL+KXiAYkmP65rzYbtxCO38jye3wn9/p3UE+e1HdDN3S1xeR1z3vmA/ac7iN4GDA8YGG9DEvkOV/1V+KxC0ubJwLHX0KM9kgOHPaazrQqlC6dP/sSM6rFcWv+p4tui64mvBOMMgwrWNk+FkHOiD+jCKiVmXyqC5aYoAf4hMA0PSggv1v1gYzrfhYFGZCDzOBgA/SC74TjwY4t8dHrHqpMnIaASKF4C7lxgzADGBv5p++5nIlGBy/YSrl/DffM1Xt+/H6SOpBK3FAmZKXrtqtFo8HoCpEKlpggkUiM9Pdmb4QVAL55ouXZc+zDLxXeCwb3s6ACVGYRRC+GSmTpPJ+UG6whpxDDzhXOeQv7rG3ixKrrpewtXNaQDt4jklgh3XDul3PgUdKyvCe2IQL7ZyGxl3CBKi4SJDIbmVjWfMzZB767ieHm0B9ahWxfvWG4Umn5BNbpwDsNXbTtYnldjLtBT/U2J94wSHKEDJxKrlj+fNhI0OsTyOsiRUsVmnn4ZKzF/TvW0k1A/w4iJ7pVlPOicTsmjkOuLuE9PYxgUp1nOmtCuyN6dqmurpr6J34JOLNxkaMgYmokZRUj7BHOQOeyWxhmfMipI9dVMTIfWy+SDLSwf7JOJIEJoJQYb3iyfM0vq/flM02QJtpr3wljgUFdzrm/0sIkSpRfsg/cQt1BFl8NT04+EgfXc9KjDDgAwc3/4L1VZ07lVtqDnBLl9zZJMUAmaKC+CxpP32CYo28rlkGfbGQ8hRymmQGadNPTIT3I/pgigYf6x2J9dxZ49MQTjW3rGMS/kRUf7YVjcNWwMULOATm++8JQ0ZCwJftMMbaF+vOb0/lYmJ1ckvdF0+9lUy4/7nCpLZ34avc76kkfAb0MHH/j7EViyUaSSsQg6SdqULISVz8YmHpjj35EF5r+SagtuuSB1Sg2jd+rdTO2ngPVTNPNRdZP8TPZZvsK2Xa8pfTGiDcda1eq7T9LilJEqaUznEIiHnD93Xw5OBp10cNPpSgzNlwFdxZuBpCAR7jiCR9r6HYT8wcHyCnDDpQSpAnNOz7tLsI7FtQoiYEIrB7T/8VNqBScR8rxds70WMa5jZ1pE9/Melzem/SWLYT0Dfyup3w22vE7LilwBU79HISXzXvJUvSC6V/Ogs3aiK1AgnZY251MD6MYDff8NVdbS3nztcTVNRBTXa1J/3WX2ZtAViuDImc47TykwSJxUwv16LUEHyt0YML/FulM6XsPtlT9/WbmPMJ+2iS2T3RLKlpWBo6KxfyDp8Cx+14/wldTOKKugxfD4CUAqPSpa7MILwnNA5ob58ns93GodW+rbjRSJeKPiClijyokFxy4vcZp3AT8RUB18n7mXHu1elQgiBfuje+L2CAPEIFQqtXZyo8K6R36wqcOmHsaBB6SEueM3ngIIwnGBHEMX3kWbetgkN8tyJ4r02UiwXebQIx/0K2EZ3hYAsMG278zBAWWGTQF9xe4OZCtVGG7xhoApseCqO7uGhj0LbSIlaLlu8QrVkS1EfICa3Z5elvzfUEuCsi4PYK9MEvHD6dVhFu9mttTnSLYIPkD1mcyRVB9t/t13XQ0mCmh1NUdCrz2dOePgbyV42ur1Wjlgm1Lbx1KeuFgZkqofWDx36J/9azdw3I4kSgbo35QIyR0ZwecjQD+JAvnS/wwQxZ3t2ozk/LPIgu8Bio3oGlcqE1J3RpbLrvkHufJKJcHWqtcS+pCfu9V/3Ro16+T0kKg8uEeOe4IbYglqJfNsCAoSsSZQEc1sQO7IY0TSWd/LX/30nBOjWSqJRCFVTzwmAkLhMsuyjzF29KWxRFGLY4FKwNfGkTnzqkBr+qCGmnyIIhqo6PkvZHl2yujihF3wTJHqmTaETUxf5VI+HzzBmgw08GOdnr2KD+oRtNle3hVrQvrsphhLqaIrDO7Iti/EVVJaXTtOwjGham07LnrtFmEgkNA7IgfRqAlSecBCvuL2YMJ/ZeO0zf3wcH9WtkZjtBWGCiNrRtBIUYME3r/LGOfjPovGUDMFwnYX5K5IMzMmCC+JbMBt0RoiwArWdCrN7RDv9VuRMuAwAfLrXYl+WMCEd4HmBAgPf92h/3T5GUZTjHKDLsVFo51Z1IHXLj9D/wZx88dmYujzU6oUL5XeOpVHrlwuV2FyrHfHeSlVU83nyZIvmqWONAoifdCV3jJJHAdU7PcgIWwV/38L4AuYU+yZkJyb/U/lmafWATSTNipxOV/95m+6BfKWcofQvFe5J+78CQ+yGOStVOFYDT5pxNhPn7ZSKTgNOOmU5kAfS1gIfbSpaGzg4LWiQLj8Jy1cIkyYn3+5RLZULSmPzCzducEJfx7LjQiWIz0vg5daiTmqzv4zy9hkCri3xo20MEk4PgbAwXEFFnkyM7VAIcYkyjHKPSS8Gh6L4aPCZaZ1YvcotQopMveAJ0FUDl0Sbil54r6lNXlY9totS0x8M/HeJnvgJUp2shhFC+gxXLxSOi7rURW7zl+kqm0sKonvgC1x4c66B6JSV0rbQ4GJbU5GuopC69qLvg43DKvuCTQXVxKtJihpPLDXrYGg2Q05ITgtqAKmcxNBf1tfeXDXKSaJBu58Mwdv+hRjZ7CA1KHScqViuwTj6hwf2vl9TQY9eRjVRMvbvfAbthWCPV6cBr3cgAHh2dGx5nPxyO3UDaBlHPpTEOjNIB73nN/STZr9swXCq3HBLAOCjggWxfpt4QA9JxRvln/Wk422s9RHMITRFCJ0JlJwuzKuM55bPSYs1cses98HJA4W9oVZTaCVf5y/RO1Pp5nwBH/pb6YMl2mb01vCARoAsXKcajSGyPP30EwEtrWwVAakwYZhksvSfjjnA6towzdf4wsePyBuDgBgS6RFiGtIISC8fbOHXlJx3MJQKUE0ZQkdmXLE3OLXfLFcsP7GZm7DBSS8sCugjdOnygACtlkS0MS+ha+uh4I/6aor/aUoZX/JwzGkwuj19w3HOvsGre5gL/J1TeiPeObX2b/49whA3fqwazox0V0AA9NyXo+72B88xyOHCRXdewggmJxbbk5cP9WgjGluvobWkmpWpbqZ4EGN0Js5ciUFwnIUccmPpBCr7D3Au5A81gBM6tSiJTkE0ACvcQG1Ns673uSrxEUrzcNGlQdtYS+NuPcZSpSUrmg6xNkqKRZRtKFr7riXXbmTfZFk8Fzix/+aBFmzw6xGjrHFa1oxemZ0hQJPli3PHb7YTvV+MAEqix/ToD1SAEblJReTAlSYGf8fftXMfSdOhZcuaKyQZ6JmjbAZZnGO24XsN9VxMUFF98oJlgvFc0ooXZDZoXh5/aC4vE2lB1LEnBh3labW3n8iCm1nawRUzqXLIt9njo/TUbrGmcoaFoR4HS1eOzzrqAgswl+Q1JoCIz8zjFRfgHZpjfybte9lHfqXJOLO7Bh2MbAqAFvmUOYJ5BrnDDebfFknucbvs+OGKFOh/lSxZou81IKHspY9P2F+GtlsEpuBVO0wprtkAy+OoCuGf6kuo61rVBWWqJU2kkPfo7AQkFTySHY1qu20t45T+9cCTwDV5IC9j/sbXlwOaRRWiiQrgfOm9wxyk3aLg/xqix51y/tv0LpElafnkBv2yyEq0G6z8rUIvhh3ScqZciZ2H13r8M946s+xqD7tVAKHGw3GUvPLYIt2VAJozYhtTjSM6XkWDUMfOEVDjwGA+5qzPauMKe7BgPKPtfjOty/KPBHzM5zd7DLtErwUSZKiIu37sYEX7l+9jXXlqmEbsI0N18faZg1mXwJuhlcl7voJWJTBHCxnoxFNmgNDjeTkL0FgNFilgf69yru9/dlmACRyrxuIglz/sx0r49HHIlyQ+MDC/nW8TzFVuyP/o+U+bOGX6FNx7Qe5DckOtCdJDNjA33XxaKfCmXwTlS7HStnS/YWNjR7+ZNn+YpPkd+Iz5FhXiSOWX9OywiDvXi7LN/kaq1AOndm2zj8pMIlDZHWrTUIId/3V/QIN4ACErthVAlImQfCn//2yCc07yx5eb1G6/7yq6Gk/VsjrSmFymFxj+iFbAeiScT6fJljl/+r9uJn+N5tKb/DizPT6Uil3tNTtIp0v+ENMjozalVxrhcvuxSpQCtUYJwHbkQ96QNebwbyUa6ksTsV2oGawp5X9B5ovt9xYcF6kM+8H3qZ3CH8qksA8LKPbb+vDfNsCHtUh1kDLktDtSveAh6u17CfDIuZcZE0d4CD4w7D1ycz5hGhLS4JtJRSp0lfagvkBGH9BB5tFtVcUdkkEgEPy0BBaD00scOt8CU2Uf9Xoe1EYZA8ncgqSSHtY2FP1QI1lgfWLIvhO7dRprCxZNHb6XZXwH7FIdr5pZPQw2M8zWMjNNimtUXAtH4lmTdmKaMuhUI82w9gYLfWr7n5U1oMyelhtmPI02XGhQZZmIQwcitMea6EEFTEMInXkEXxdTVum/98QUA+z1aenW8ub+kmqf3Jpg+qAGjYZMAoonHsSqqXzH3LwaCmpzf6fnvoLZ4lCE1ps1nQDQnagWjs/LM78OMOeqKy5pE7GVQxBiy7qWPW29cNk33dyvupZiOQRaFcY68JHimcVm/47znnEVihYhCZWvT6p4EJeSE4ihwXXnDoFloTVS7haL2YjNM7AHj2ehr1DAPvUt4NeOU6PQBGu1pJq1WjbyyOrSRMp/dfibOkqM7Ef885fmrFVYHtW5fQZowbY6ycNXtEqSeJCXKAouEly5HSx/RkkcrgU4Z+4JhGqmDBGguDZp4SfXsIlLE2TPOwdpKuvrh8F6KAVlf3HgzLtaQQDxYdqVqd4FvQMe0ZBff56lUHnTTmRQHnQcRx8vft/vp5D02CPrUH/5p0uHGkSsul5Wng24jCKkqaKag7gdl8nCS4//8eKA29ms9Twv7DD7VS0bDmDyrgpeCTeynuCHpVwsvkU8GpiTv+6GNg50F4zYlTGCPS4d0BX4FQwqGJHvWIimKhOClVIcb5MQayGkn2Ync8JAnDoI9UrxUnQa1Vysti1zcTEtdvJ8EYSCm5HUD1HxVTFFD9zNkV/sN+Y96qh8svYxi9KNp+h0Yzvag94i2zU5RMG/9rE/iYA3tVa+yA/GsnrOkqmn4wCReff1P19v2qM84lGBIMWqyRQvwdHvAsyUDumw2QYszMhkP0UGPahFX6WlOnB93YeGe+WyPunJd8X8VhIqxwzpYuF2bFFsnVQSADsJeTgDzJaFpArPjTshPxrJ0OzQIDAp1bwiBWoMn8fk9bMQtorvsW9X2DOHR5iXW1DVfVPyxXf8gCXQZ2Ql7NFrJawDElnKW7BQsMZ6FYUj5MUUjHYkvPdrDRs1CgJv0o0gX+mI03bGvVED5DkS0vvKPKMpwedpXf4PjCFB5UoQw2zC612EQKI1L8HrJvlgiHNqSA+ra6k3Ff8jcHyncnOEgRMgqoKkOmYrc4Vb2tI9p0D+0tKztWBXqTTNUxNJj46uNW8TD7TKe4OmCV8SMMjX36z7BZ2J0qgZPLIjs08O3j1g8Qhc+Elpcfcw2Ce/SYSbHotMpcHf7uztMflLF4WhjBeCIIR9I8AKw9dOiLjFm28iiCvlq6Rm7GWPtAyMhIXZWx3vmX4aI8LJs5mCtqd5ku+NjtXqdFgTpo2aRCiP8NfRc8ctf9o7LGaYKVz9bzpe9l/9bXnBAo3CpLfvXLI+pLMnp8mAe1ILlW1Pkf6IU4iFDnbSp5Nvnt9aH787OAxoB4JfGx7ec0awdEzEjVEjuM4vwHE6eSPExl5w16/n6SsnKsCL+nYylbJTV92QQA8AGjCvcBWOP+sXDnU1vyYZfgzKpdU2CtLyRi/FsMn+3qU797YRZNqbJw0CdmMnrlk7KlkCQhl0fUhq2RA+w3ZxvpUHsI6QaGXltnSiIV4V1yxSYui9lBJkDnPs3QEVgN4GWEHbo3s3qxV+JFi1SRXR5A3PDxOAEjwFPHRrExbf9dQoXF7kfG1iuDn9V+m8u5a9TY06lbOJ7WKCZMAZbIHkDwyuGzy8vq4PihOVDZIIt5KzqJH9z8jg+kAWP0y+M6EnTaPsf3D/QuFdunW/RSrijE5A7viIymSdleFWtLeJLGL2yp3uTEtgVKuZQjx8qym/UI9NUbjUbJU6ZPaAw+SAZp6sx+GS/XP9yP3jo9wu0fCeRURtMEPTz+EYxMtkQt2pn8pX0uDJliDsBDN8UbH781W/mc8FI83Q7T3CC0wUNIeB5Q0n1l8b5npYvWwpChrDcJWz528krXflWK6dgtRnJLUQRLO/UgaiAonc4UX1EvngEbXaFFzcX+ubKh5KYONikyIOMs4XgKPu8+lU0UfZnIRJuEFx0zgrYK5Dv1ufCo1947hJLgW0qp5ku4jz0y8EMEtgVZQn2v8ZMfadZYdUoq1So/OEsu5QD4F5ruoSqJme15K+GV7qYQ1gpJKjdFATSwLWg/Q6FNwgMoMqqvkxn5s1TO2sHgeA/7I4EIq+IPwIW/uneURe9kSuxET5h6n5IbyiByJNEaX137zau938h1jAVY2kwKR8xNj7QsKvGMNoBGS29GvxekFMNGlm6GFgWj+KfIAaycov3CRY/a5JrOy7pBimz3562VHqGzVXfsJrCaeL58tI+Lt3SAyohbQ9JTHCj8oyq0FEltk2LQSCc+X1GtpuHLlfadyUNsZPoNhFYf54ibd3S4gMzg7Gwn5N4oOlZiYqhfEyHaAVkyIEAqSZTbzJQrJcNxXOFafIvH4jvXV2UNJKeSHlp+nxwvKcdg/XtbRyDxos9BKXefP12l+vv/LjtK00XJ4h4FdmXRcIYX1sxCrBQ7Nqe63EUBVNEK1vs7TZQ+fm4jAjQ0q3JkCi3bsu/UTvcq/h9VhtluZkZpRuNKPEi8jyYhpkT9+73H6kIr8+wxmS5KLvgYk8XzRMjrr47Op+nvpFhw+x0lEg5LB4NGr0twvEDkTFxngTcIcw1qpkRWV9yPL+g8HIeWKotQBukoBXcirWJdAHa0hyZJIVq/S14Qvz6M2JA6HL+gr6PEbsJgnOW944+pQFQ0RHpeZVLqT1gL18Uq/hA8KfNdVUCTik46n+5O5ZvfDTLXqtRu4CLqAhQQLLB09t6/9G6YkDf2bneTKB0NhaV6JXQX7jfRDYZ96WUuuTgXQJ74pLpqoVD2sWtue154CgNgZAggIc4RloCd6ChFbt92EyKQonoyfa8kQ6TXdA1Wj5FqPnX3bPmvKRFFcOLd4PpFSZcvslSkeYkiMq/qnV9VZP/uJXyKb9JA3fmSPpTvU8PGvUyXdI2SZ1E+/yzuGkpG0Jdl35FgKnuPu8K4rSNGoxmzwPAXEn55iNi6lwJG3mEqMMPQSSmi4GGsHhKC4W2RJh8WRFJvEf0NH6WVThOQ9P6TfJgC3x+ugA+UBXqvMtyXBBSG8BwneCoZzjA0osPzLxiTPm4fIyLlQHYvALYTGrLw+OVK/OUNUJGG2bHf4cHlowT0kL4c4o6XtC/KxC0agFSiUQUMzOSN97//Cn4NdoYB5TAr3rYhbHTQiYYFEB8CUl9yqWKMhrhM65/BB6vdEq8oZtK9cb8s8QaKB+cE4PWAy4bKE9mDTntsrO0vgfm72FMspo0+w4RADDoQSSVPBECjgJfsODhoNvfFSxOxN3V5O6KdsV86uQtSk19/+e4uVCJ+oGznwo1xl/Bc9Swu+nYtZu5K/PGFuv6xLCP8TazNdHqsSawkfY6SbLOElW4U6/BTzsRthPugb6Hm+H1jfmAFk4gWE+zJElEr7sfbjUcP6L1E5OM4DCRYBGPr6Rc8I1deFF9CcUV/F70EaVDJUbTmds94MHEB8IGTvPhLDDutidvqOYyZ3o5igthgf6Fc6L9T7aEBM0F7o07L7VQgs+omoIx0HjevSZNK8uItDOYTl/PpqiMvclZWDUY8Y9cb4ZAFGFLuQUvJ7yZkutw8jLDRfnBAkBAI63rgGqyvwHj933gMSGIL9ZKipFjSHw+x3n2fuF+XXiMbu0GTSwxxAKP3a9CBAgrJe3BPk14M6GOxmzQvhYVM9HkYwuxwZVWARjlIJJfczh1DGd6HzUXp93+74t9yWj9iSfNMnD/tp60Z2Sh/XlZHNkGs0Cw5o1LaBVl7lsTyZ3y8J9O60W4HY9EQF69UxE/+zhtdAVJT58SK8zkSf5wb0RbOhnT6aH4vXgEo0mZ/bBGf0YMw62VFntYaUS6UYfyJglz7M0Z56DL+z1c8pzmqNc2GJ2vlSOcL4aaLZXmfAb++6dB+uCjPEJuD+eTIsgwJtZSm+7bpfqE8SNZ6BKjgrve5ejvrvVACkicF7SLgJJuh/+qGXjtP10zfDumjL+o6Y2lsnYDG2qVZMTQHomeTEKDwZd/1aRmiTdAWGGltW95dOGde6vgENylh61TDtVu+b8TT+k+1du9bAfIhp+vnMWrBMO/k3dqLsEaHpzOR8RwGGBuVoM/Q+OfXRkqXAWVLAk1LHyc8a/uVl3j5jWmWHAhTq3EvAUJ2Umae2moLveJOAg1nnBDZOvsbtvL857+HThdv8WGMHQGIWFsBr9UxRxCldDJPZjP9k6vg/4tbviRt0CyryD8BeDuep1t5Bf2eBM+nDHjvPDPcbUwbnjbC93TzCVvE/XPS1j6O0DeijRmyW1AVkCRZxNPOHPOAcLfXfOCo1hRisb3EogEHr2Wn4H/yjfRt0jS6PL/K+9dfyYATYtpZQUvkfoSEhl7wEcdjQwJmlqYsiHEx4C73Y7XePdEPVkIdgymjFRs2vJCzokPCuTzCmktFvGoG6QP3bgCcg4yydK3C7JT6r8+1EQL8/mOA6riuS0dOVUtr5PBcVDQJ/RXFo86Oeq+1qYU/QErbA4g9+SgzVLxI/IPCFN31dDDz8wFQpTOAPDDqyLMiywQ2ZXOVW1i9F/ediOb/JHTTpPTMnpZw+MRecjfXHFOfOYP0mz6HWAI6DSGxHUilcdUXfzL/WPRpPBFNjggGtDeOKx6abkZseZlxrW1qoy+Bxy9Helft+3UZAoPjhyzbERM7hv4vjcB8+ON0EAmCS5V+32TkLLr3o1zzSnS//baeXDzjZv7Fnw8Lvvv9MaLQx5+mYz2F1qDRfJnDZJebpaCDetpQrzVNi3jEYEQ7OL1nqp2q7e3DU6ZUL84VWq2Fk4gRaPub22zlqrv6/LA7zZLs0j5f5A930LlwRQXd707XVNJ2QE0NTOSfPg5rnpRuTPG092SKSI2izrjKGlfYJ7jo39oV6rXRRMsN2TttbZFDB2LScf7kvrYq2VNGahjiy9nlp18kWRoP5xE1St9zjPct2jutciLU/GJynAuJ1Eo0mPIQkvg8enb6QkD/q+eNZ0w85yybMRit1X28Qklj350QVn1CyTPf1b+yI8vC8TqGDvDIsc3ZAfJhKuvw2f56pF3QdOjBOkpmNx3bA5hbhSaAsjzBRIbmr9sA7I3MjGld3fd/um9Yw9Oe0rf5KgqNixQiK2iCGKAZ+z0IknpGN1Ghjl/1C4WqOCFaoLU0/BYxVuwAREdrksoz29F3MTisOhXIdnFP7NHLAHtcvJ6/x4U2zmPDFCK3EuoWiorjfolKEy7yTsa8XwebMVxpum9U0R89xRf4Ri5kGzhL5WRKzF5nqIoVsJ0uYqf4b5v287HTz5of0K5oo1XUIBXxZ8HBWDUxsKzfLG3HLTgALwsWbzs6ESlkW5fgEImypyocs5fulULIvivBQL6yks6d6nDbVFxpSwCbOmtI3fO1yuXh/8I0Nd7QsmlycL7222ULN3kJ3dAILWBsWJleMeFPJO/e+xz6mguP8dueFkLn6KS/8WRbF0Inqqxie41MF+zKkZZ/boRdnPT6sFSU+JJgoDX9QeaFbrR0pFYN9kqWaDjyxbgxu+FIpNUti/6lTPvY/CwUu70UTqL3nX/tqqENJEMPMaAHNnuOyRWTHj+IfQf6jqzMb5g9tp2598uUKwfpfbIP3+tvSlI7Q1aOzg3rxsecFmSaiP7pSeuCew1todxB+ahw3s/sEkoLE0JSxx4vYgFJP77JoDe8VGVbggGIwI5Tcri6/an8n1AxEcXp8vm682GyApC0pGewLWvNlnF1J5pfueSh4XuCngLg2T6H6ukWxCUmORYb9NP3/lshJKu6B/zrRyc1tKUi0+dJ77TuCzdVUkhwSp4j6FUhFr/apz0TzOCb+2uL0kKbgasYv1I0A0OI2GP9DgHZB/tCVZbnZlZ9eBt4ZBmxP5CV6usGxmhpJfuzApT4fXLeBqfnUEzflSDNBzQLeB8jMgmH+0gvgfCe8DFjqeJcbMKocW47bRLHRCpZZepE9Qvmp3YkJEDuno9HaehG/4XqVWmma1ZA65bL4TilNZjabTDY/G+X1GL/lA/WDExV6pgY0FbbPh4to2exFKKGzDykkeECpjpH4BzREVNlMx/Nxdi57vdho67n/Jdh3Y+KjoiYYS2bojxv2amSai9QFJwK8kwqBxVD+CIWLV6gUG+y6oe0//NbLJgxvubCxd4h47SlRk3f+02I0GfSxniYUp6RiP855KFt69jtkt+Vcb5rrhn7EZGSzcTnOP39V1FoywlSmvM/F3iDiRf6lfxnzFoPwTyb1Cutx2sQaLDyKB3R08QtRmTrJ+xpFo+F/UKiUiQgfIeAjg11VNiDSGE8X2APEyV9Wp5xphmkosgfDX1lcmtRKUi77fxD8sUqweMT1KCMarPSB2f13gaUqGcbD+5uK8Ey4+AxPaWu/bM5JCDgje6/qZjL4tfs4Or5NmRqBmqbHSjUdb2xmdzzJiJxjEwrnhU+jM7Bfx0ufm/irjYTp8Xo/8zAPEHE3jR7mvA5Xbok2O3qdRcnOH8UOf+hN0WhZV0UiqXtlTjMgBd40FTHRjcmyB8siOe2GnXdAqxEORWkj2MTqofCYyz3oFHvKgEInHr/Dece0Byl6HoFqGoVco3aQaNyGyHlRuGbRvkCJI5MfgFfmIzMiW2+kiCpjc8ljaU3U+lxi+P2WNqi9EAs+6grh743Yj2jjLWsnET9BpoUKDRMnUCD0+PBnB/j8EnbaEwFTVJliobqXng0v0II77JA2sSVJ21m1K70dYvfDuCZVuYsOfvLCnirmGllrPww72BXUgKqj+PGaTkaZYQ0oD2d8Bx/DpjSEeVoy0B15/XBXEBQVDrA+lGon+WHLvkfZ+3ggFMXeu32F75AuYKW3+wnuopybecBS4LNn9GgMiLLk2xrhWn4Q86YmX6sA3d/fzCTQzRf4zK26OmW1PFPEgziM6+Oj8yfl6juIdYp0BXV869Yvh7uKqp4B0sxYuMsK10idSihReVCdwmrPad6r4GO2cuwCggded0hQ/lZA5CERMFn4R+T7W1VqvpYpXRDndHXMSGALOo9/cZLaAgm6i9dIVVvMbCUSIJjOQxkOHKZnXmOm+IfsrlWURjxdpy4RW8gIGG6N7hAzCE+uhmtXCAKM/TupToE/4HRjDd0CKfRCg4CE2bC+Wo+yb4Cv+6jjZlRgDZ5jutYdhaitaIbVpEXeF16ccoLyWGF0qE5K+6mid0/DUM2OAn55qMObbekAZVoaEn3hTY+nU+FtlgwQY4Va2bHxYoOLtQ7Yb4Ph+kWpoqjcAVCyxaqfoVEoCGAs7Ts1gTRYSeED1vtOC0jc5I/lqPSeTIlO6BGrZCo/DINAnYK6UqbkS32GCLrs8+XiQNqAOGYT9BC6D/0Gn5ScAoU6djaIZ1pRqsDgIJJY/2g8UJrQjjaCb8zvJ+bPhYltX1l1ktOTqIfYFu1WsTitnazssku7rVnfLou2lXx9/JGEOcz99xhJTQ7wMA5jY40IP3AYx2JxOQljiBPbiMdMocioKce1Yn2GfHze86y3wn635cYiyn1aVzA1CLkQmbAtS5/x8UbMpg8vDVJaDy/CPLW6asl0MmEYedprJTxX7eLgtZ9gcYXvfmcKO3WG8/CRcLFQXt31V4Zb7BdwgH5Lls0Xjvz5gHkiE4+qBefVYhmO43TuGlkJE4tudJx4zE6Qve5lGN3VKZKKPL1d9fMnrdWZWIEs08TKtyh+vaJmq2iUCVAIj6AKnXUni2oG8Np/y/HoYzIqK5f9xpGSg5+VfuPGWNQNOnCTxMsabHGDnl2jo/ZeLPg7qHChGVy6M8BROJaOSL8H7Pp1jsfFkfwknTU/YcQ6Y8Ov3kH6QzKeVx0HtfYsDLkN2v8BiDPQY7q2XVwk47EMOgO+fN3KvwM2qxh+RpdD6R6Ee1NgbbIkaA9u1xiUlv8GtB6cyQ4hin+IOl8Ibpvfi2clh0QfDCj8o+c46OtF/Gfrv5muVo9HihSBYcHFiS66lw9zDfYSFEnnyKUEhVGei0MMb58DZ/MDioJPJOGCXdiLeTuk/XplG9HI2TdPWQU/gsrkCp1yqe3TCtc8qDDB7NltYoRA1FVGdWQOqlQDy+gXxrmyPDROmlN4dBJGzgTFfoaNqYFbfHd0luKaE+njEoAGAxWRRsQrM+2TxXdaAw5q+N0KJ8Z+Jw60kAve4Oe3AdKppi7iF/vP7mibk2bE7jor9po5XfWSp3EKId3kf4iwOPjBlXJ94014OMC4J/IYIyJFtfwOim+q8uz+LAxIISwrHv5AcYbZO+xmMW47lV59pSrcYzbUo2v3oxSgpDnow1PkQm3gz16N6yYHRWKvH49yJECZxAYFE3VmcY4emLKNa8d9z0m8NTCF9Ht7W6vQveR5NyidKl5OynkogCE+5wikiaOJ8VlsEnP4ZhVo2Nhg6E0vdE65CUe40YwRg0NTTmIoWQER0gEHjsvA9ghBf4xAHwVxCVBmV0rjQR4ssSbPic4LJFiBwGDbcz4ozvJ2wqmK9zA8eEIEtbhQEgV+oziar2lWA3SiAU+H4X1WwfNCt6Bbcsdz4ZvE2/mxdMmGFFPhgKLAJ/Z152VoDRpbFBjbKIKJzyAbGEVexHxSVz4i2WMd2rbaazEu1V/prDVh+46+FTr91TVaA6MolHuCUfqdjKE51pv/Z3gPHqtrvpUpAMYKBezhTlqTq087f8JHAkFzvzux1Vkx+EMhSsQeWl8xhRIbHD9dFNEhCk+RReiEQ6mB32RnmzI2TH0D4s9MCutP0RLT4xhPgiR1Fsz2pnWToq/otLYidJV4mXsg2wGe7gT0T6ZxKVuP9vux6zL8Gmm6LZPPM+44S/JMllBFcjrbN58J4z2blFXzR5tkAloL/sT7Kq8x0S+R8rqflJtUAODQD0meDDnDsl6PpWrq5gmfzL/MHAu1xyZ9IpMRG4plcj8XPsjnv37vesXkp2bb+Nz8QkKpoJBSZs1t4qwVOdCXN9AQQThytJWLBLzMdSKyYqYUX3X+ZwwmSJF/1l3aQuPASdp5EGz08UvXbiif5KQDBgSO3P2MrhItayboPTT4LcZmuO1JcjRxiMKrnALmoco9jfO0lDBwTHSwgzOctLnrHvRjr5Us9x6KTOk1wDDt3k68VcDHsFP3HmwqSVTZlOEg3k15xxTw2aFCh/gy2jMVUbbjjiVEM6kgsbtGpU/s7vZS3Dhol007nM0gA2gPHDQPHM7AN2x22w5Y3zD7yH+OWKLYbqXU4ed9zLMbeyc4blZuETq6vzvXbyvOUz0s2igO8uiE08A57+KboYUg6j+tcCAag6fd4qgnpGXxPw788QcWfN5xaKQLE0AHHK+wTseknzLExSuq9pWSmTwBMTaOVpxtNLjIQ8K6Ly+TTLqG3Ar38yyWTH8J07bmUIpuC1DGXGePBuu3VlOhZafYGBdd4oKL8XDfPAP4QvD3Yp5dLKsnhSfY3EGskvrbNXQUfRbk3gusJ5icYBrMoCNvPyix+3Pbqc1EgtsqStGiFmP+HqrcNIUU7XnOXIqDT8FWNPHkkZZYmmDLLo4YeH2aQqmm/jS4NjJW8ddVlQhoCvu1OQ/qJKiJNYd25ircMewgd9JEOReTs9o46Su309/7zDtVpFqQHim0DKr/YUz4B+AF5FekoUj0aYYn3V0l8jaGhciWQEsGKCe5i3MMHR/Gs6WqPZ9zXKXlZeDCzUqL0drMIpSuTek1SruoOtd5i0KTD6fr3y0exc2fXTtTXDukLwpNNkS7233zUU4WV0bvNyH81cJLfXXE2fczYItLp7wcwS0PRSOECr8wtxGzpYLPv2fSdsCrG6oIUiuqkpbLDTM0F7Ovfl1oMuEUSF3nEFmuy7V1NaaoSrMPNOWqon4DcSuRGJNbd6LvbV7KnlLpZikPLqN/XbRAPoR5Ewgl527WMsBzLdUDHycAc6a2stuhXuzA9KAf0zqu4aODuiGYSkfEMY88FWUs1JTZZBX9X/IaLhKMUgKwJrSlfoXiaxCOkLgPhM/cOC+7FMSVjbBK4j1v13J1aEkxuZH9Lta9Xenda/5RfNwDwxpjpi3U049jxpweYDCDUL4/j7FXFLp0tuavmdFKip9Rm0u0XSATutzxdcXeI/P7zF6bFgqQdEfBE6qW9ZmuwvkEv0emkCcqVrYMA1IXVSmHiAkp9lZvQGLk3ch1b0wcME665LQn63iNLzUvlZNvZW5rXIXKOOD1vJzHzg3aekrFcNQbxvNvfAMuf1Kg39/NJVXItz0jKejpltGj9AujpOOZ30UtlI4CSYr9h6SQ+JQ27P/A0NyykJZEahtyiCnwVHZGxAzSFLNEMKO6fT+6r6pKvKh9Rgh2yeMj8ypiRWIXaY8Gwv0fEwl/1jpbMpA7Mgy6P/lkP1e15NAW8/an+Ilz3cE0s7fgivYAyl5ZM1LZrXkcgFF9o3E/x5mg+iUft7mJ+Ut2MfkaDLYjx1hbWpP7wrVOBH1htnGo8ZQn8v2q6WnwryUTLIyyzHb7GRKt6jhnOtcKkMk0LkGJ3NygITGo1v+Orl4wXc3YsRii8UI6UUVt1ydfFaqTR3jGv+bfkRT0keYC427dtYMC0bALgdc/qfDNteycHlTYVrWKwbJ7lQzppgKYQyApujx1Uqjb0IKgmgBQxxda7gjSTcxT7Cgbr56yGOa/yG8CO3zlxyvpic9ybjt5/GB3/IOuwbt6A9sC+pwaCAo2QtvA6MR1h6Ur/FS2EQTWPNE397fpafWlRCtBgghW4gnRM9m6kIBgIemfLnxiVfLLR6c96LDre7TfibC8f7zIvh/n0ayiKaTx6GluZTOAm7cmT7n+Qq3izYb5pJLyw4ZgjinIf5hTVx6IBsnG/Qy3E17clk+RNwIiK25XV6MI536F4Ctd/PHZs6NjwoiNmvyoRVmsNwi5MADk6x26Y6tNsWxqG4gnQ7xAPcDV9GFuKtFtRX/sEmGw0cFdyj93SDvSG5jmLq+KwEUwkypDYcFjB7M2W3laYE7qJ7BCKx4O2brXRO33z33UFC6x6v7xjU1OsdpZeevHEq2uNzEQ7rmoT77dd1FLfp4mKlePKArkzd6Nhj0j7DwzfR2uVbzv5Gi+jCHX2w9i0pMQJDubmDVE9l/9+8sskhXXsOvVL35H6tAwbHe//XZk7wvJPUorM99JxuwuJYNkzSDdcGkwP6S41Uh7wKTmPCgNUfCNx09I3IHpu3+6JtGpcPQGSKqj/vHTm8yyngjvxnMhVYe1Dj3TRteubS8Q1ERzsEQIy3+YtbPmrpPjIvRHhr8nUgmP8cpZTLRHaMV+ynm+StHo2Z0RvNknaNpyXLvWHbq6WMMglrXm64k2fyrlgX0LbhOEV6YZU2xT15qpEHjsPXVTTDG19r0Ffv3GTfbyfW4Cp0S86YiyNpbkqQepEqgw/XlTMN2WcZThlmECETXlgzd+wbUP4y6l03qeml45f6rBoeqjNs+Hya5bUdzG3ZdNEeo7cnjphj70xNlGm+Y1/vNJG4xe3xSb2ZK0rhcZDiAWFaqfgIza3exZW9S+B7uxu+jHi+9DD+9e9gs+DlyuOFnSCqeTDqf3ilmtHaefmroxrEPR4lHYOExtPw6NQ02HFGnSg3VrUdDya3kDbMqMrGfwHEXQxWkGPp/vQUTvZxiUZ1qrRmVo5TVS6ZFKhrh40XiyZjDaCyPKkP39ixfD5dLmncejTHa7vvp+5OTNqgOyjLlrrTMlM7MPl0MXxXgDBTraFjuqqiafBObbmdyOZFcotYIlFiBCGmQG2OsVENnpYkwJ9Bq06sHG4ecS6Sunp5xHyTtZOTRaM1uCWq6Thhjod0Q2PyJ6NM2tztSqzPWameU0cHe13NWluh91qeV20/PrhpM76GyAtJMHOL9ZKK7RVyWpLm3972ftMozaWZub69PUGsKxZ6jKsA17d279fNBF+tb6pkLb5TGeKNJXaYjUPhX3yFwco/bUyHVs0Vm5xTPRUQkvg+SOHwVu0yYGYJ1gLwbaI2Ob5a8IKGjE52N/7FpxnlXJX/9+ewq+FC9cFZLcMu6tCsjN6xIXEa1UnQaP6yN/VP+Grz3Q/1zyYFkUEUhAS2BoFAAfEbATq2IOMJs8C7/N0V/nTYdjAIAeOC3+D/vwCA/ULuCcEKhWzL0q9z/MdY9OwcbNEPcDbwsC5WWbYxwDkAU29ErI9Bvd1uSCbpZxb9mxA7u/7eMbCuCK5C3ie4zgzvVfLc1CEY+oyd72/4fS4uu4xTHSF09TAc4R7HHadXuF5PWvapxHeKT370hQV0VtCNn4LJOMw5oj7OKJbJ76EFrUuaFufM+uyw0+Me49PoarMFp55nZxtP59c1err97VrWYSptVvXI8JxFoS+DO34RyUgXGPCJ84PesdnqhzgMv1TY1piAtF0W+GKK6N9epUe5lrEloIJrsxZoCYmioeyFC/cvtrnjm4/14c/LUwC71e+0b2JCgcSoLzR2Cz+NeXAJYa5jkrwN62PKKecHxxA0mVsXovpDjTAXf5k7vfgdrzQvVHg0NkwvzpCrh82vpKwAxxhnylY7g8aTPLS8v1HHyJ4eN0onGehjZB1r57wIveBrgXZYEt/HCgiuN1xEfyyXIlOSe/u4gDRLZG3p3FC0bAz5E8gFe9j5GLaNvCMkOMlxEYWUzjwrToCoBUi6r5Yp9oNUfZ2MqisPfrd7ZfoGnjfGoWYUlfmIHMa+bVpZZOLtF1jvUMU3mpkEMg/dUDJwlkqocc96G2oiRn2FDAAMgsrWU0vrWTl8lnFHWsS8KFzEddtgaPSPcL1kGQHKwhMDKGKRNxm2a8K78ACa3CIm265AWqkCaX8DzIIMRHlVyTILSCLblIypyKBFo9Br787QQ40JjJJd8oVKg+M4AlPerjwGC++1zxigVqwFB1STB6Git43a6xgJN24myrbAyYcWwe19Gt3qUsqS9B+vOfWDGIx5xGSTpH+Ak7giE4hssVD1eirX1H5sayI693u/LwlstS2N2mOJWZSPGJG2Dl4VeNMOCPaXqfYs0MMUGGEl7P2IccU+e4WnYavBnyv3EeOJ52uga7G4VIY8wWnc8s4UBChV83Ss2PtYiYfpY4yAO6wlP58OLFF3a/Ti+xCtKJRoeYns1pmD4R0FE7lJHXqXdgH9cKsILU1sJztXvgaHlGnJnU2IwnzTAhc7wrews5H/XqrAp+N2TbIhmkzb0fPYA3oZP8kcl54/K49BsYzUHcKcIyliV9r7Zx/TeyMXulUr9Ec8HR2NXSwFHxDCJpmPGlRC+Mbuw9YPqaaItHfUovNYKtFubOs3BWrLQw8PKR45ySdWbCqjT2/SsLtCxu0ZYPmR5dpX6ADXOKyDkaCZIe/ILBphelStHvCiyc28oiXOLPlx+MzZLSiKAIcTjlyjKvK1JsYblxZXv39uCrOdvtNpC5mpSb6BI3vEfeTrBKOidfrAFf0gcFjBPS/v4WetpUhuIE8ne2GdAZAIPaINzMsvpUwZCG8hjHgXTkl2E4FoCR2qhBJj5Q7O8ppBxtCpr/zcXR5Ozbh4TQP8RHdsVzSFTuvD66sO5BM1U57O0gnVMCVpt+DqvVvMWDrhGTNPdqBxTngYv5XmaUUpXL0q8e+z24IFqP6aNm89EEmPZyBjq7WHHz7YC8LTQLeaPqciV6siONQZhrt0xDhIrnmkQrFaPQavxWFZhh+2VI0migQqVaTBDkgF3xv1FeODIcqVEJcAER9B5NkrV0txRYspn3qE+pIfDBTWkf2ljxvKoSz2hzVNxbJDKDojJkJ0S4OB46Em5blpx6FSeg1h03FYrkA/orts0BdXM0mYPV+i8LyeJcyWU+Kns/hi/S2ULR69JRzG9aRW6p0/zQEErp8Xn7ULhV2mIvvhMfxFESMbgJU1Li5VXG5nqkyxf0DaCzyFEzWvXEYXCAGMGRG09HvNdXnafpeP4Fe3e0YuUQA+n+nXWQ+gR/ZKKaQgP6zC1gNvhb9HKhsBktvWhOCQoiVsK6iPt7rej6PSHe9yCQ8ivPMEmUTz6kxj0Wffw9+0qYlKQqgjWIjuFU5eCugZ2a3ab3wtMuhAtRxZ3Phq3s8Y1C+7uH+Y1Sgxvrcwd7xxkN2awQivx7uwsI3yWDDSeGhUxvaql8kWAa1be+xkvEWSpJOsab0DZCrbl/o79ojxy8yiOF+douXRZZTBRGtQLB3hPmJnmrMJ39471IQ0NeBvcy6RlKnmXS7pEcXls4mQ23dRIwF+1gIG0dBtcl6Iv8e4NHglBz3UCX4M4wECLv//8ndoqTpyJQvfRxNb/DKqkgz9VWMONZeHsNxgf4nnu5Zk1xedDs/ngSPpQoLNR4C4Jz4jFueM71OPCt07JxGGu79jbSk67zOmsM79s/PhNl7+s2bsKiYXCVXOx1AvdBdBNjpSKij7oci45qt/L/HQKmKeUaPgQ8qCaEWylm+1NJZ4rjiswbZXaKnTJlWywPIFJ91a/fvqb+4q+QGgCN5GNQmQe3ai3PQQ3y7Drt6HuOohdXBSjtuG0Fm4jS1HlA+fDbhhjOuedAblmJ4FSI25hgW99hb5t4yCKgSdz4aPtDndu8SOdTGHY7tJP4binlqgKPJ1xYMSRw35jdR13r7d/6Yg/9lMAhKjccmpBUdw8/3cKMUueQAQMUCVkeL7yB7mtN1kGFmLlCpCIR10Y9zb71Pw1mL2O0IEYhnVrCA5+lCvWBUvuYe1Xq79LhwHt63laZYeCNIXn/ErlmglIeDt1y3IRubx+6e8vNTdk6Uaio6/UmCQTxSIJtc8M0L4oWgr9fHeHLmOJ0CI+l3Z9dsVB23OnGzmzx2ZjPobfaOqknxD/9CRoqwVnK7ynVxup1IXkDRc6JXiDuVqQiD8cWFHFn6UD0D1vSQ9Uei+cMoVZjPhKv/qdum9QrGGBlK24QS9jiLyYGzIlXwcJWpunI7Vb695TvdxYLNAfElU1+6BoHPpjiRV5lxEo6s3oFa7B5yS/+KuBqmHVTpFVC2ChYldCDcpFcFy0FGIayZ2CrAavOAPD8wFAnTO5KvUc4gvqJ/S3mYGVeHz1BoabEvGGz/nSb4tE8BqRX2+b43xmzRMJ4jH/w+WkQo2fsulIYqXYWDN7vknr4dlhC1H9kY4JfXWP6Js9l3CQle0+lKdhM/3yf8zfnsCA7SavUQYZT3jL3U7acN0/V6qPr0R/lXroJNnzMBBNMj/24KzycT9qRYlIQPIW/xNlr/dIgAimcAzw0vhxNShmEGQn4Es4s4iI52XsbbynSSmuBMrC5EBMVM3ctn5IHJm/i/dv88d8JkWh3H3zFEItnCPHLBdJASSHLuax2CtDJPgBOKD6OEMbEYgoUfFH1+w192U+84h/cdgo7reOTqQznr5uSB2AOl4ZVDfbfEF87DU5yLuNW2b9m/Uwu+MWo6B7uCdDdYKfy5/tmkAh8Vx1aJ93Bkrabl/hXeTGN1so7fx8y37aC6khonO82z823+v5NhVZ5n0lhPl78jP7KKF29nNxmfgJ/wKmeskj4gFmKZV6lHMlDLOC0t+NtgcmfXx/bSnkGyL1A/rCnxlXsXHk4oAiTgUF6slCQJAaZ53DRvVsSeIY4xZytdgX0+FmDxF5zaqZDyqJlBRVZflavpctG5gTQ87X6f8RsNhFufmztr9+4gsRKrBtlVF3vU5+61RxM6TxyLzB71aHXemOvPpgv1LriAUgaoxNP2gi6yIRTCEdbnAzE7sMZREzYzUN/0sKUH3slZM5nUJxFqgFBTBrm1BpGq5fRPz+GgSIRzRv4IrIAzUS8JQMUcfjgXOB5qS8RhGPlSUZO44GguK7C0OxGfTCqNejZ3U0QsDanJGRlwIy6zAPTNxTscEcXsV80DX4916Z5TKazh4I5sPrWF0+OBcAMu6cV78eB3NIlPq//UzAdUYbDKEll+t5OszR02iqdkZFUM2bqbTEXsPOQGaB6eor44SxKCXE2YLBPnZnK4iGpAJxOnLBK0FDVbpc8Uh0jOHEaqPFVFXnqyXWd1nJSoIjvoYt1skXG1B57NhZzV/KqzKPiJThgLkKWDoEpQwPmVIPiAJNenGnoZmbYInJYW+qz2sb4aJ2v1Gcmw2ERx1rFG2foBl/UrVF1PsZU4q7v16Tkfz8wU50MJoyl6CXy8kEWN7RmPmafon1jHq8oyWPRiSARRmCpu8A2GlA+0vAbCCK7lbk4EqLVAq05Elqh74mYysrOzG8UYEXNLsS0LLbkORfqIkPI20oAQB2xPu7cXGyUH8ZpW3X17mrxHJ4TMQ67eNba9uyVU0Uxx395ZqaZ8iXXL8wbIblUnCwTTcfePVjJop7FHlMX5L7mzq1W8j+Fg+Kkmony2qYtGJacelTGUuRMx5D9Eq4dwEXhE6NFbhTgDp4I9FBbgaKhtwkOTFPviyfxYyA1H14pDFwzSNvCBO4Fq6KMCpTNH9K6EwQ0wTeLQgnQVSi67QEqQsbdioMh37xMh3TelgKuJvqE8T0OSiVTS/+r2+vQiBr9k6BxCmO7U/8r00c2CxEgPrm6pX57nNL+0E4x10EqG9e7W5JNSRxzEXmfnZQ5S6bNks3Fu4xim5mKkEIchAi89kX36EXnqRrmEXuQMXsY1iuqPZYrczjl/4ncPVif+aT/zIvrDHj1xqlHtxuqgDj1JsthsXb0+cgbY0gr/OYyJKBlR2ztpfc5e3x3L928PtUvYtsua9AI4N9qr22pKGdJrZMpQkY3C5ICjodAZsvdm9djHBvmbyKgXjs7u/jwBb7I4k+LWSEBUk3/4PdWbaJXeTIDM8zAhB3Ow+Ol691khqBwd30QOsAYmhvzgEWcu3MF3dosQ4Oi4xY7CpXpg9yIjOChMxS+t/oYm5hA6qNBoVI1SDAI7qyv5hnvRWTWxPp8NiBBKSYbWGESclIvSlfMJFWk5DyHb3uQZ/WrXVlG0gjIx1fGbw6SYriZ36O2d57CW1gWAsv58oKtXrMR6tU95OfGlvn3FYQyc4VjDaGFrlphE2D+gkJl9mKwjYUplQyeA1XTWT+EVCXLzGziP9f7wy0ZTSUR2/K3ch3G8Ao8+xwHt2agRdjrRP5WjB4qlvnQ0K+OsdFkdueivvWPls6UH3YnGUO6SSd8OF57DVuok3hIQbEG8hgyVCmgrSgAyYFwR6GGYRsS4ACQw1aKCkxnMg8j8FKGmXxAgZq9NUXy7pK/0To/UPs095bUj1BeR8YsFwHMA6oIHIeMoHkWN5UCS0pcWP35olgSCAphm5KdpIAcLorRj2XChYpLPwMjzMzwI5DfxaecHM6VqmQ1wlblLYnXbJCam/DPZxNZW7UyAjsvpBUcgHJOF9CMRHA92n5GYQFZRXz98cnBEzJLuJhscUoWSu28RKVUrbBIGvCOLELzwzo4cYxIecfyTRZkggOFYspC+gJibQ2IefT5edBfKcvyS36GUHZSdduOtiq8FwA1ZZZA5WX5S5pW9If1AEPNxAjhZeuuE5HNKyCggrD/NJmVRCXLlde1927O+ceI+Lqw1fEg+sqLmcGhASIZRTRt5KkyHDatfQ94ofpZluC8N3mqSWqfCi2aTIEVN1RNKhrJdWggk1r6p/bWFWbGGFxVU222fYz2YQL7JC21uMCDoenxiI+4626nFlUgQoZFCfWI3OB6danCXYTjKq2fMT0s67Dx1BNcuRoVkarn9rm5PyIU9uD5zmaeUj1YSEHtcOnof/U6nNrxaJ/WTMUq2h94lsB249QzwNThRtpcEwjgtpOW+Ni/GDRVuTLNzH9iTyx7i41GJ+DEXJ9LTY5JELPkfATGdWdmFO/Ottg2zgnwq7i7bK3W7ZGOYvPLO+lnrcUItgtjTRSLw4r0W8AVbmOsdsl4lummOYxNhgqxiRtOfKHfZ6Txw02RcAe6mdL0E6Rak4Yiqsym/FcuUDirSiJez6pEbO4IiSoKeb8PcKNlEzOF6hF7qGiIuncLG9LidUISoEp0GVOIjWXw2Q3UNtZNPOLDD7qaiIdp/Q9qZEFTO4mt8mpgbgp6QgNIlxb7TZoR9tpja4BWBJMe6Sux+mcaP2ysOwdOZtdXxkXwOa4wdmn56/sZiTiJ3qAZ1ZeF14treRwIvQ4MfcONaA215XqUIsZO3JMq3kf4GwqhCJFYEZhgHXnxGAw9auLd4C1xIUvukNWydqtWuHfBqTnq5MwOmtHvPT0ogsEtXtcIgspZlGx5KRbfSLzJFdBuONcOZlUSRT6kncmpi8wsQxiULqH5Q1+d8SanRoHxKQ+6MTWyZMd7rXwY/Zc2XcfIkUaqLQ8AKLslhhLecVchl0IP5rFEpSkYSjuCStMYV9ZYe0SDMeaZeqYUc55QGgSDe1oCwDA84bWhsSz0gBvORFnMav+QldoVSaPf108CpztV9Nr2rxYCxn2F426M9X7yrlbr0926n49biFBs6Bsp6Wkhbo0uvEkww1pQRDtzDHVO3c4eQQdNvBYWejwOamW+gDx2CQGhGSDtuBISI6Z85A4kHs3yYr3Tic13fRYbNPHuBrEXXXrN4vY+MEOQcKuEadt61ofwKw0Q+Cm8iIkj17uOyPptU7SRAMWWizVYr9PpSC2tg2EOzKm6u8typeR16cBh1GHoeRmjJrG0suHE09rT8fXTeN0lqE94zpbMGeThnsMwOHJrwvsHh4ZzeCQ2OFBKRMYIK1R2745BVmk9AwgQURn4KtKdzefJ/0tBn4LDnxDDAPECA4TPNvFlRUMpHnvnJC1aIQZhXoxCJIDH8nRavlxP2DCZpq98ird5GYL8SANVD4a+gORR8o3vexGzM8NR8Gf7Sx9zACs0skSdZHno8KDImb01+42RFPtiL9aahI/TFVORjPkaMzHdAGiGVT7TVFCGhyKiblpBShxEkHe/n4J1+44rwZtMe6RRgoug1fTQIapLcPU6siUONiXwiVwgq1+hzlHWi2YTVS2wfvKdiUyUzXxGqaz3PuiaSjwE7ZlQoddl4o3v7BaYEOOWdTdzU9SFzHGKaJA9VWVqCYiwGLGE855pNiM39/gBxngbHuCcU9lxJ2+WvR3WsDc74mFJnkNtuuLGQgvsZjtNOwLGn3a7l7JjI/rQD7Lt7dj/F63EvndmLldFzVZ+MU4/BByW2YCEF+oDehqst3XTBHLOAzt9a7ZC6jCjLCFsP8iObip2aetiIN2dy7KJBxSM3IEqCCHmdJMnYIPqaxKlAqfunLZxL5qeRMxsLzUgWVc+cbmyf4VR+ZkH2/yPtJSWwz5KVZtbk1iXpTDOoBpl+7qW1eE3WNSj1CRkBvHzxcqukIGim5/AiReRBhfYNcLGisvvckQp6yUYG1bxKIMIBoLEvWS6mDIEWexT7c6k14LHg/37dQ67X0lVg5H8AOE2pjs/JhSlvH2iWiNWVio7MCIsSfB/9Fl0+FIxWOT6bbi79Un9e6xTYCClDAoLJC+JAIfc5VMtq7asLS3GdtpxwaqNN2BQHHiWgQW9FS4RQ4E99i0iKSqaAeJWIVr3LiehhB+3vzO9Z8FXctRMr0LuIHuunynvVixBV414EtESg4nMqvlDWJTkBXGZJyYOcxgddBsF+E1w0pYZRFqsk96dls8zlvkprs4tEs63+/P9OIEuo60+gA/kFIcnHM6wSee88+xWyz4IPrFTv5OEExMk2baRT/iZ+GsgisTSyTSqPc1AMk9+cGLLpTTZL2/ald8wpr9LMbQRBdPq2ooB4/NKHX6rYULRAkjyueI6dtznjhp9SfTRm4aDzcujbTDn25HZOie6J7MSMB1C7N9+fyNwKxXBeFnDa6Dl/F6wO+hs6HcZ5kgy3QOnjBUd/mqAmokoVUlkIEf1zoiOLYEbB4Of9ZIIb/kc/XYgMp19aKoeBVNJ2DO48zyJO+vW2plK7cEkAMHH/PMrjNf6y2mHDum1jvRJdAJ5mbTaWPoApJYTx35J/qDA2qByY5fmbRDNDGm1Z4E1pF3YKEeNCzCoqJNN1B1QPbm08lIOwsP96pm9vmsMA5g/juFNe4DVfM13Bl3/7DuYPg2hnttX8FscMVRRdilLoXdD9VZBZYreggqef9Vh3LStyhO5miDYpAO9oEa1HpPo6M5lnov1NC0xfOc2v7z8ARlBzI6tkdRGZWYnX/jk5yfTxTrx4tsyLZctYtTckg6EOsymcb0SXROBvKYAsxNaJS88UUrJ1YKsiyMEl7Yu7ArSb7qgsK1AjW/AA4mSH9ZB0BtQzYOeW3I7R4d0aCyMwagRuwJtS0U6O3/gTcDli83BJ/WoArSxSoa1czucQGh6TWfgyACM5DU8+4fb08u1bROtjecFYC6bVBhLP7JMTZEjJiKyQQSZXY2LGmpX8dg4BUZS/+IlwXo5+RiuTEeRTVnozCCG+yaFGE83BGhItXyG9+NrosGf49E0nf18e3hDPbDmr0FC0xpd74E6iJ5e46p8ZPhoICpT/t+0Hi87WMXrwTqPvWm65E4ayKjGXFOc7ht4xuoFbPs4kEx+bp54Z3ZAQrmM65Xc7z+AnuO5fCLEf7aSchR0APu9wbeprldE6rk6cTvXtmxLzm/IpTX53w1HDpqAxtlbmzVUJ5e6OllyfdoaX53bq0xki8Z0zcnw23W6zdnUkzaZUADARkyij/K/3qMuFxREyTHwTAxx4r2CdTnD31gVLMVmgH/Q2alpiePE/YyOpyYmx6+0LotiI24hiVZVmrM68db7/eFnZ6pK9L7VQDPH2sDiWgPTXsElWzvI9GLooCFkat8DZBBRQlbP/iTW5h0bfS4Ug3X06g4ZY8q+ingI/kMBjUzqt3g/NX8meI1HtepoUdjOVybS9Ze0IAVCb3vSszmmVfGohv5U9Cb3JER5GXp8VoBVnmjvjfrcc6p/Lla674Qih2mcoDQKqOJK9HaRvPjKD4ToNs1ag1fyFV2BwBKhhDSe7eENvyKpNfX78LUQCAhyIP9qf4bs7So5MvHqwoEVAYvK2vgkmXh678H0kgDbsIHgCwFrpaNUXz1cq/rLiZDz7j0L9H7IaurTgpW3+nbK1ggd/xyanCZCs11ys9V9XNN1l4G1IUOLAX0OFzuo8lVhfedjhLKk1KJRNq9PKSJw1NXgZkE5zp1x/UonjZnyDjlYp9xSEkyQhVfg2vABLsfnjPYggxB5trlywSWkPIfeTpSoROagivQZXM1zvN9evW9biQkIAFc7k/Xtd1VFkfjRTVUxxkcS3HmAVzhqYUylXpevTUWYERFnY8tIYdpohtwtWCZmWBp9VeCNkQvawQOTksILgk+Cw2sPpcs4D2BfnuSWLbxJoHvB1zVDVNB3a5BpY05aaSMV/BW/yPVVjACtpyvWoFDXTZ/Ea4U2rcWTR3d2l3yy06rWSIcs/u8XiTl+RUn0L+qA9WQjlzEdIxPEdHNLNg883b5fL8GTRXK+r9QtXu1XwnK5Npr/qn9WhmNn2rKU40ouTR5iL4BuYzDeS8HhXJanXSYqMHDaZyjvPRjszZsOLF+rUxI8dLyaT8MZ7EKRXlXZ2HaLu5C6iC8siCwgDAHwMvT03qaouonXuRLmkyIdk3yWmtk/Z2NODZ+u0NL75F+a+uG/Wse2IjulBPvD+Mt+RMaOpVP6qCz5DY7gXONXm4D/FpYDUR9AWbVMhV0XjSlwZVPZiU4eOsMgeqJwCiJqJGzWWYRyWZZtrYS6SBK/RHoAvjq+YWXATAP/cg7QQX+c/cf1L+QrmrDLcYifENtV3KnLzymJXzR5yaU6359FPniEhTSqumyroc9VjUR6pjgX+VpirFNO9SBFVhHev/Fkt14W4jkJrkSpNdi188ELtITUDbO53p3RFWxZNVgR15g3DfzlqAfgt/U4dEx1D57hvE6OJMxThHqln9GeqebQOjceHsn3CQztkcQttftfDCc4cVi6Un6o03oQewP0VOx9dQq2EfXDj1RLS1fIowT9hPRY3fMUW+75PzDPj3BNdQhbHHimSCeADELtV2hRKKk5Hb9M+jxyw4YT3ygvZi/uJ/mbV1pzyYJu1Di3HbdPLaR5xCyAZjr3JE/RzmZP1scC0ewXjAdeAh0wCeKkB7rTAUpQ5pDFdgO4sPadhL5xHP5tIaSXJ55SG1ZtzeyXc9j+LGw9dBiH5QmHBC4+rP4U3nQ6QGpz+T36CtN4bib3LqEQdmfiAR74UwbHppyTs5bbpWhOcgwRgdo9qQTEyKEMVkHHw7HFUg4ALhDhEbqS9tZkiaEJE5R+CHKtnHR9B/xlLsC236jLkvpgTCw9tLacpV5y7AAb0EE7ANGmO3+otr+Y/iqiHyFHjjmhsG97DUktWwcgCajOCTznWgfuYbxTLOzusXEr+xciRKn7E8e2rYxEa3dK2Px4uT2E/1ivDUAnfsvvzpDrgw3qoRrKXxzOyDIZMw9Gp3rG4AMh7sk7Ou9/fB2wxipO1XBfn1sOtbyCquSynXBEJ5EXQtgeDm70mVW9zPEWk1dWcSAP30lMYELet5fSehV/1HZjY5Izf+v4lWv4t0oqeg+y1WKlihYEGNwgrA7nuW6Wq7Q8qkp/XdKGZ37kgpaUP8UnD0SwOAmUn6Z45CLM2PxM+IqzRV4/BREukgyERNMa5fT34973rPgAjzuSpMrQima3TS6ho1XxBZxFod6oR7sRYLO3ATXe8sjbhitKWP62uflnR3eMXuuzkX36RcdhVTA3lQmboqBwJdCFcpXx2Oz4Xc8wXhgPPEEDcG6b8vzSG4xUwg8JP/C1aN5UVr9ioyHFjSB4LvXRW+eHkTCWDQna0HGbj0NtsCg0n9xCvQklf5VQ3zEPOPsdc0obc1GEV4X1AvzZXrsNqDuy9Fkq/RwA7azfjx1+gqTK6gD60uzLzcBekEWJN05vSxnb7C4ciWMowP2hqVHYm4tcXfc1zb2L2Vg522FL3XDvmG0RuOuaZYorav/YRl+f4oPQRDBrorbAxUsQ+VSKUNgRMxOViszK32AhqJvf3I1LCA8IimKD9mfqRxmI/b9zNCUabv4ZooXUqBLBLbXdyGNtRZGT9ghw7Dlzgiea8J9sSoMgDl6E8hquEOzcBUbqv6hg0WZO3fmJzm4EPE9WguenBoSCoFjdOKrdULcEnU+Xrbo5H8vTrQvIlz933UYM/QhGi9xqK4o2vkjVFZjBkR37cwOg8PI3omzyR3EZDg8lpy533jd9cml6gFwLveLrqowDoxiFbWS83UOAuRbKpSonS3bG+svN+XsF49Sac8T+QFyQeiqBuqw9W+6enlpLs4wftoNR4rygV+c4p/c9axXMx6thJtnmZ211vyyk3BY+nRgXNvWnTUgOxzGW5cFl97wdIE8sqdIuGQYUC6duAJmXhGROI63SWkHndB6BK+Ha/zeHMyYWAT2GQRco8XaF178jPK5qaeWlPQarfbYDs9VL5bWhT5TngBq/LxLXyJt0mQ4ES620or9n4MJroY5R8187yPwctrKIkLYkZNACZlnj2tE1PNcG/QULh06cljI06tjEO/ZrbdVIns3uLpyQ/0iqV8yskrX8S6gQhVfRynbTG3xlHMb8GLjbZkbp0JLocEg2QLZ16L3On5wO35sCThQR9C4qdqkpevgq83Bzap9YeQWsYNbeRilH6XbtF9PPMhBObt5GyegSaL/MacA+y7Qs5kZnqk5kuVI1q/NzgzNP+b7z0ogffo/Hal9vwzQVixRjGBsH4GS99aIiegOTNGFcuBvNV4lanCwmb8svF6hPN8u88C1BFEKldxV1FnZs+vkBWAgpptmziTIc82NCsiX16CQPI13/dcgw+a/kkvGZlZoC+N5UcMsYjx9t8QzEFrsI7lhU9E9HfHOcUfvAX4YYD81v6Yog6uKWVrqWcvXzL52TTq+FYVJ7lFnkZoqEPN1jIkUXPlp6VpXApxNrUy/VSkJ3UP4ZesuGzX+Fox6xyWEQlsqlZ9wSQhqNSpkFu6XMO0o24AaMc7uTTsa4/wG4takO3U8RQCLH9mSYmCLY28kPlr647vBstoDBKeYLdgrHDYXOkcmhGQuP5BR4R8ulVNnHklnR0edsY7I2CI/7lo0dTyEGzwVTyTtv3TO8vjXTOKd7o5zEc/i2LW1GKUTmfo3rjJlZokrcMWIOAR3NmsI7xADon7rK6Bv0w53gPnKVBtvUj5Oye5nX0lOuGiQSL0n+Wh2LLuen8Ca1ow1l5jf1jNCkQpcKXQ85dvVQ0FAgqtQ/OPyrNtS2U+j3cxI9tye4jWmhV79Is/E4IGs63b0p4T3dUOg/659vJnLy1uatzVaXp7xkwd8zF+dCKk+CWtnR8nmsiOb4Gda76xscRzsCnTkwEIhUuVR9Ff5pwUorh+/ifO+KSOQAHDwb0VXgXDxEcFFhHmwm/yCQqqw0DU1sMjR6gEnEKad4R5fMIVtTL7t/Z7SCdqq54f0AKzMvOdIz0bbBoPDOkWZSY1MfkMxTvf5lNHBl1pMnSsQ7lRSSWEezFmCzyX9mxR5RZH6erf8hAONFxJyXaWKibhwPW2BcE8wOjremZFaw8w5qHgnOFUoRxzVebsW88mbiYZbDLBXnlhVIt8+i4H+fTOHjtsCoinbp1fZhNtaWszi2NgXrZCHGqhTRwF15yrlYTnzcNQCCNz/0fe2MYLCrF25UryRI5TzpKww0b0M4OMh5MLNLYmBfG/NhG9IX36felWhPeBxvQqgI6EFJMtLpMm6C4eMHFYLg81QA2d23/eCJPb7bfRtu/EzZFFB+dTnAgBB3Y0fTYbfytEaEpHP8V0I2AWWkI49Rali81TBut+MRBmINJ1vMBUtVOUGaFh99kJGEcqA3gc0EK0qBwR55vgaGRWxGS/TSf9Zl1HtvwghYay8OJWyZBaie9wEim1FwMn9eeAZdGJJFAXcIgJteo22CEb7LEIX98q9j5qb+1Scb34dRJ+YKq5lgbSqm4vjneKxlJJ+/ttJ+4y0/DLBHPzQ7ROYR/Rt3KIpOd2u+rG8n9XqBUpiGUfSiPypnZJISWn/LINFMHvv8T9cxyzt+Gq4TIZUX+qDiuL7L8eArFooYFSRwcFmb9EA/fbUldFIr1T0DjQLZ+kjBeYzgu4DehoW8VnDYcmKCqnz7/oG1bN4bT4Sle3EPQvDWNZtPWRtwlE5Bv1nAcOiG06SckEORvLCBoK+NFP+rDWXYiDomGuGgWFvvTQaTjpEeLm+HGkcF5BhgKItvLtpQxMKN5eSuw5dbkiUG6owP2ie34nyu8HtIRiBbZJMBwi3BAfV+MozEgGQX2WKNoVbQZv1Rj9lOW6DxytyUemwDLaZUqf0WP2+sRPc+dgWhn7yvOBL6SdsCarCRze8/a9RGOLjPlryFcHiFxMnWOw6WdzxublkXUMREvKCZGWFzVLO4zoXgRuHwo9txcgmKG+0ZZBtaLzL65Os1jXl8hKbRZxEa+t1uUrRsYeVD+OzXNUenvdZ+FUPNT3q5Cy5bNuzvqNLKHQJsgP/gx+NMZ4b0UeIHHH/8KPFk6xBfUHg5qJlxL3Ls2TaAtnfU9JfSZL/dk6u5c3kRIE5gp92pJQflC95X9Uv6k5kDwAAGb3b8SgxMuoZTodznvnGFMOIVBBbaHswF+ddrGMTiBU+mmJLMhf45iXX/r5Zj+PR3gDUAIhfAWqHOAdVOLk4FefKnHGdzSUwMZxcxfT7rW2u4NrFciHeL7UeVeNyUwOikj8uQb75UBwOwqgG9aK0doSk9sZXUK05pSI9C3WGxHne/AR504vCjNOZjYcqKnWVlbES8+z8iJj2xFul1dHJWLDnXOg10w8ao/2QQDFJrDdsqCwn10UGmT8ETyB7+ax88GI9KRN3MQtCFfozwN5WNO5VQ+r7U4H9eOYlWu8ab5I1OOw4z2l9DUbRAADFxlXfZ8NNK46wZVnANgNQkyN8Hn4zglamy9BaxwFqZOoJCFoZ9QlHS6P6S7X5vpSj6zbjuTRXQ7oJzBFKyzhJXQ0IcujrlFQxcL2xHKZ1LLhZ18PAXlqbdCLF+RdcftdzEFwJP0vOH8PTW9ufNFL9LJ7/IxD4ze1P1KnHi0W377GBgtnd4VjsXsRhZiAAO8uUy8hNG9Zw1ux1TSykFsO10KaH6TpEYdUar+k44+T7t2pHKi1jYKuL0yeKaJF1e0fk0OI0uAnfSGJDTamyogacgGh6qcqZ9IimztJb1wFVs0JtSgvMv0xxVSppIQrWXcS7MF6iSJ9R1d8t7cFxnszhp5AZAKk33BbndJ5+PB5ZexyPF+HtJB7Ltl+vqFKaEDckG6/JyQG6U6fI9trjHsIG++IVZIKW7AbCsADDOZArba4JiqIxnVAa14ugdVbbu8yPtk4zZMBVD+qhryIdp0spFKJu8TIAdcyZeEjGQ4MvCARU9IRjzDeh5u6ectp/zbfzm382H1WTe41Vl8qp4+49NGc7Mm+/SxZQ/nhSV8lYBFca9KTvT5gScKGM/XF2bc2ClzPxZmX+bAHGEH5JWr7JpKQy6qTF/whqGlDLVRr+FJuGIsv3Zx/LBSk8jPCfOZ1Qgc6NksvMN+ncVjtVe2s9wGfVVcQ92yT0whwOoIXdmfYJ7nEt7zwetvmFTm20e8V60/3lWgAcIGHKuuEYTWdh3eRHKYJ+NHh5OW+O23r+LvBq7aqQ1rv+gbIzrMRJqcyjPWIQM1ZxQsgj6PXQVyTmnSjNgtz4xivEe1dayj8OeVNO+aOn2oa61porRlK7BE10JfzG0Eba3+DdABnuhuflykJLzfAc3tw22aqlJ6HcJaMyShqZY+Zo+9QS7SVkM7JzDRleoJNotJO0gIqNwFpJE/6Arc8u0OyZyL6GvVHLyidGF329v/5hju1bI0f9/2l30TIAhSQ8ZaWaN0kCLpv0XVcU+luAmMsfu8hZEjxxPnFLqFLiQ8BGhnuAS8kc+EePOQLiZ/BRM24TO2CN+D8wllx5q41wTKEl3e/wXj5r0NlR2/mU6odc2vSjkydIKiqWsyULplOF38fhOJOfsuJHRVx3D93z6Ktc0JI4S840JGlCgQrl+tBCQN8Nf7w0iw/iqi4c9zBXxwrDQWM+p7C4oL8NWNJkytssXiI731BofuGmRRt3HQ5vGE23Oo8cPVTtCH5q6TUHSyvfMpX/J6sYyzM8B7Yi4Onvb5ZOH6YIJXLGWHkh6ad0+aMVt+E19XxhJe4wR9mSHL/I0IX1wFdfRTWuhc7ExA31H0M1Sx3ps5Kx25pw3g9XVC5aCWrwoCErS3E/ysovde43SKHrHYcYcnfQTE4p1GfktGV7IeflwOtCUi1/Hi2lcBKRffvp1qlRvQulTYOKFvzaCfeKAy79w/aPI00uamqBKrRownQyVcohNB9LnUN+uPFFu38qrGv48cEppv+jd8VW6b4u4MrwPWDFnxmzBg1LAxoD09fz1CCDEmuU/Il+1VuPUPRgdq3rs5hIIGZrsgjN/CjBycB9PoSPsQilR06/0Zjy91Hh97jjsFVY1ICZBcQjwpQcjBmNGI8A1gLw+MLhRCp1r+YFwRDGRmSgGXKyrDpRmYSLZz56Xy4ddMAx05WCizjGyx200ZKwTvD+ajghucNAlxSlOA/Q/IP64TbJ4mabtJljSyp5GwJ+w+CgiEa3yNflEDYVUp5etjIdhct1OyCs2LsctEsDC9xZG78ZmjujFPmO1frH2KJAO7D8yochsJd+p97Zy0/R9zroaXPULCI/q/57VswZeBTP605yZ+JcrgfHKRoc2qB0V/DDYABiRA/jXmO/R9oulcWniIcfEe2zfKW+tbHvv/egrts5v46NIOcEg7DG6B8d0gv7L1S1hA6yQsByhDurRdWN781WMmnCSjHrRXTxMfgGevE+iwJoYPKgUrXkEM8ucidoOaGUnQPivd2Hp+xvbbpq/LWBwcxGgC0I/9WO3oGu/PWpTAOHDzixGh7RVYArUIkFrsNpowXOq7KImCa/9hq8QCrvfuJel4X1ynUqDnNxOwpbk7Lj5Ce2OinwBMN3wp5GwOl2J2y+hfywBjv3o74bqDt+bWA0Hr+Y6SL4W+QIKQeM+aV6D83hxl9EfBF+/Ht/ZYSZA7x0IXqbOImBYiKqQb4ZTkN4Q1nRJgpgjsNpxaw7USTHgJiVNfq2CmNsUD+jCDjOZNEbHj5ulaCBDhH7YyndnLRBYtcAaJ8D6HW44rdK2+bHRkOe2ZqnpADIfMZcegNtUTy+Llto3uhst1OK4DVfYNRkXNsKo73yMdH+1GPVI2blJnvSZhRjjM56vh3elzSJYjKBQPqhBvjWY1+clD9I1mJjL9SLfP5iUppfvpaQEfESdwVe/POyupx2vCNUjtGV1b6I7r/WtZDlkm+mRwT/jpY40vgmCJBUFmyCWl9xfcyyPks6n3AooQS5lZXFJedg5YlQDg1NhJtnVOUFdY4muzjbEbIZU4xVlaDEqJjzjceHBnGH91QsrIOeKaqVsETutGj5kYhy4/5lW2w49AKH/jrHxl+hcY9HhSl56xRoiJ0tbXjFuMIVSR0H1p4WCarLuWrfcW9SWElafHOgVMS+JenbLyVJt65qCoyJzv9OkaBSHnNe+WdjzswxZosghWNMFDjw2CSDMao/zBw2Q6pHyXCCUE77o6ur/TQt/hKH7kursbbpkqnYxk0CnENeBu5HbLk6aparcaKz6YoxPgBE9TRWkQYYE+9lJNQW4SDKPS4a7btZLkT9+Fpy611jOdWTDCea4DLnGOofV4e8PfuU+UVUKdxjVOh+0T3rnQxrH4SpJWvK5a+08iMuUTuv2PFwbd1jUrQt0W9GkHnWpy0kYqpOwSuIp4WbZlA3GleK0T6nQFDFWtPZPOpkZ0s0YDyhXu0DW66lAjdJv/MExl5FE6hxkI0rIB6s5ElnrF+7Z2zmRPbQk8dYDNIjFhLgEtRT20KHGoJ4IfFWoUEhczrlyEuymaFsAPk2LWU2BurFSH7qcyt9GEJHU21ZW4qUOezHwtqMA8nC4Lv2W9QSvoxWcCx4u/dq1zZRWKd7yRH7rRbI8cA3kmGD4BeOdMrbSvDioFUoLz0O4YOjogqeMDAqZsPzPU+nLY2/HQMuQHT4pY1s+itRBRT+rtzC0e5bSrSq6MNWksFfGPm777MU+l1/C4j8loQRQyKPX9a66VGPlYS4x3mUhn7os8VNSWdC7LIj8gkNz8CH35x2hRq7Rbc8s+mj57BBtcJ/AnA3RzkqtTkUfUFNFvIJ/6awSSS1WfgpK/QWGqdq3/6Vq/oEoM9Flh+oojdZuMNuysVh+nx7uqD/MCAHSiY+PDXHvVkYEtks3JZgJQeCcDFzztpH3pWKoBbWJJHH1dvE5a5gjp0Oet/Qyq6fOBZQ/ehkWghc25tGDSYKIc0PaXOz2PM4FE8P7NJRL8PMyrTk0f1TqX+mm/YVDI7bxi+VlXJe15l2ckmTRitW3tAj9+vO/srXnnXCY4CRE4MFQlYldddxOgWaCVU3GhJib+6H+SpeZ6q1zlXtV7aE5W/m9ZlJcO8nlst/Ow9BmKh/QcR1u5Dkpl3GD2eVR0evOFGRCA35HVNSDRm5t9nbsITdzWe6RP9+uCEZv0XWDYZjIrDEgrqPOYbTblhatkm8suwb0kPEgrj2U6EEBIpDuCpcmEAkYtskgzQA3LzQKSOwYBnGEEKNh/Ww+U5OCSnWTjck4XL2V7vOvUrxbVqCgG2mx2wMp/SXdYhyddmnzHZ5ewVoamlx9rDF3ioG5ZaH0tH5Xq+Vpq9pmZepcOH35BGEUisKYkK7weWKq/SMxueAMsL6IDN6RSj6W0hiDkFD2Hm3U6d7k7QhiPUDrFjheud4orzWlsRqKQRfxx+UOnjV/5jesM1HIPTAQHAdy4OoQC6TpFsZVgq8r9UT3jXXs4yLBboYZAvShP2s6hsLIkjNJuzYpfE0y+A5MEIKGiPT09YcjMt+f0xiOoWL2udb+069eTJZRrGrIfxGawikZb2PdAJTtuotKjEi4Sgy/fO6ISetr7l8T8cN3kirq7c9A8eYAZSWWEUh9E0TCZGngTxwIgNj2MxbS6+QWBIzg5mwa/HsmDtyj0QhzJrTHnjyiF2aS4Tef7eR9YRwg31Ky5L8DxW944TzyCADksUD28Dizvxxgnq7iLB6CVWQoB54kz+agYOB+RkVYirEgWi1+voYxMIiSHLWdGsre8jpzLjDxhpRQaopDCFmn26UI+8PNX2ERm0uNVb60qc7T2wzPDaRVy0N2Mym4WVfIQf+MLOM120+2fqBbNuI/H+Gu4ng3cuO9ri8Z5zG0Xza/eAdJLMz74kBXvaYShz5Mnp/CfAi+fAfSGxZw70Lzl/h/ORqvZRAJpbrkhOLkVlUjIpfBc36xdcY1dg1FCVFtoDGT4eyqIrho3l58aMRjSXRaHsF3V+RGKVYBorluijoM+Oi9G6sdEu1Ry96iT/2FaBNaEbI4WRpfhg0crUYdW92fU19SBetOPgVwfraqEIRU7Fjmlzgw4AuRQop1QKfaTyYpnhcZ+zGeV9K3cwE3qephzf/rYks1f8CPPAZs64xHV7xpjhjuT3Uxm32+FgQ9XEsRzpBgAQHuMae06agjmgt1HguQAWLDFGlLXvKREAsDfXoZLyQ2yhiucW9gDjh8+7m3GudmwcfhjiYndFSEVlk0F8GtLCjqPgpqrGRa0y/UjprWJxHwMK7/J4TEMkys3FF9XdQbhJbVgDR1bjDhkA7RfLp+YvxqtbSk4HkIJksf0io+4rw+lKLXnur5uWrnRAjJ+LAv5OWt7v1pSmYi8chrH0cpZ/fNMKzNNQeOp2zPhaHh9R7/E2UfJD8S2NULValbher9cRQ+QxTmySF3Fg8zq9KUyKXb5qlkCj4O1hmDgBsgz269mW6naR0zYaH7QHDwdwTRoD9X8tMvng1TQPxq6JNcHDb9QjQVWOK09WdqwHTTBh+/F2FOOS1JvEM2cH1+A7acCQwnLM+0V7Xpdm90HWxOHypeSukK2Y3o/Ljy9mVhhuKEz6uQIeY+3U3LwkTwRb98HcJi4nbQwyvoMNRFQCFWEp3jvTqEqIwIiAc1un205QIx+2GzPOtKVsrx8lQep6N/G9FmjHOWHCSs0wUuepWeKc4es1s9BTJFNk9OrQQqHQxGgIbCRMTTCHjMUf3B0Z6AXXD+e4WC6IpERwDVVHBwyCa48cXxxmhfOgHAU0gPvSD7sdjQAPbdlO9uvaLNIn/jxhONWm7WZaakF003DAKj7FE0jCZaCT/TkgJgRh3wBjYVMjSYtAnQOR8WHyio3vWnEvv7SRXVTVSQo6eDuNai7xWx3jSwc7MKXmANZgwT52+MO+CaKbSGGmEoPligPfGVm8RS/nUv1JVeNtHsAKfuBDp2oU2xMPCILPveE++G9boMKxqBzgB7kAaUw3uBiyrZbKwS8P8q8W47+piyh8wfre5SNgFuuH3sfU/JzaFDA7wWhz8Mc62eMW6Wz+uMsYy1ywEpkNYJLFr0j3r7f9aGTxhM8Mlt8rTCuyIdEkROkvJEF5tpRBp1kJmaVuh5ylr2ZbpWAdmA7dGvhMGqw/nIY/I7svESSn8D4ZZ8UltN759wnDs7sI86xxV11FelPMafPXUGCigYZxv2HkCSHGM9bJcq4F9TXwm9NpdU02Xln8Q1WhVt8ap0tNC6/78I0Y4lcp9VTSekxoj+b+1Hip4alEebJrFPPeoVYYvO6TGXE44w94Nnq63Mbqe/FeWPzEZkoofI3J30gH+ea16RPd3CMj9m0k2MOalTWMx81OS5aYISIjFnQIHwR7jDkh3RUmo24wtV7EJpcAiTXA75L9wr7ssNyvc5s5ZKzQr01nJOjlj1A5JqoOBgUMptFW7Fs+whd6KjNrtWA/lnqMlKgdbQ1FU01yNJGiMRjtt2XGr8f1Cm/EWuNaETfD3aFpzoy8gd9C4EBVPORTVjI6Lsh4RsHBRGmUSwr5k9+DJCWmiT9LBUBHtl3F4nkRSVj6mD7BaRBSQ7cOkcrcDENiyHUf7FUdm8Qm49MKx/5YDccbg+jw6EFkfPC0IZHk6zYXj/lhWJJT3+HMMDi7PUSRxgauV444PyBbkYIiBhuemuAoPFf/Hk1IS++8WIVZKJOlacP4uEKIDgRRixlDai67/ZmbZAA9P0SUer3dac9xfAKkJvtJwhyt9BVBxoIWFeryCmdHOpGb7Vvvyuz76InON1zkCIaYaEQkqSCzasH9VLIBbE8Uvh7yaEg+9CciiSOGrSOje5hxHillE54jT9O4YeLP4WYW3d0jK2ICvU5k5Io7TZhsbMrVwDZtzMCSLggBayvjBI7hSc8HpPQhZR3eXAmmpYvKVstVF86hw4KLj02Ogf79IMDtYh4ec7/BF6bIa3QfdBII+Tk/wxDYWmMr8Be1ARoMEDYeoSiKAo+orKE1oY5TFOBJIwvaex/l17Kvi4irMsRAGMQqo0rKMK45mxTt0v/xfW++CuM1lR0Q30JDAw4nkZ/FviuX56j5kQ4W8wB4xhwHlGQuzoUitSyLtkqwS+vl4rMOzCk/gJh5RgZ4jDYyuU0CFhIAJskFj18vfqyJuh82HDQ3/UoHIDi/ogahE6WDoiNjl676kO1uyHqc4Z3WYW74ATr0FFaMpq/wFH+tNjPU005dX2CMYzUhZnxq5OHZoKt0nLPEZoYcd0gE9uyJnQbwt1iuWQhfoj/bRjAU32lCnf1vQMWF+y/1jITKBK3mjdBa8p74nYZq+i9VkmCLAntv7CLVhzN/8kFHAD83apfZ/IIIAA0SAJA++6P1O/M9CjQuTm12aoEDdVa2lTi0AwU0sArE/C0FEnPb4Fux80WIZ2DFOAbdHXkHuzo6wxk31MZG498CIGHJvxYYm6JUjVRrT0AFUnYfiYXdsvvT/VciWLhOtjGm5cYKuw+IlOxW4C+QEurnYzKUN1qYhi8WnB9oF5ZCdKZy0aUhSyDIPld1fD9yUmFUXAvZLxpZcJwDbwsiNzMGeNFAENnfUp2/EU2+H0fh4jvt2kl0OEs3t2U1/yt007UbjrHdYnPVSv7wVUNM+58L+HEgDQ6f3O1G0S/cG3fkQyZLiLcyHe73wlHaJr06BN4R88X5SmWWUf6NJd7O6JNjDTBvNQWYIgV/7FME9Q0EQn8g9w4bfWcEIPSxGyaXvGSPn54iOSfZhUH7pFd4SkJVOTaqE/+oadxg+TPbWAc9X9naRVsRzGOExo0UAEt4Dn1snF95r5T2mT3T40+azBn1S9+mRBvlQ6LQtJIlkKBOo7c8cxyqQpNkntgv+IqKmOAO51NsEM0TfYhu6qGZUc5+M6/Oyo16hPA6bWU0Hz+uI+xMNvqU1WYCKW7R+8uPknkwbIKPFZjB0ltCX79ZjsftSQNgMuT8tJM4Pwxe32SaaJsDWM2yINeyKF2s1gAEAHBeVCV0Mp9PXoPBKt7333NiawvMS+QopfrE8jqXxC+9b7mUa2ggpesNCpa9FRRFwUeIKBeLsyJzDkMrkxPL0irsw/KwFX5RAtRvlMI+9rpHvgt5nskUS82Bhv6+xujFcNQe9WXBiDe8wcHrdeZ8IRUYh+G7nhPSVV3gVMbZ8wLyyYgXUeY5K3++Axr4wniFq/FXJDM9mLx9wOLxZwK0/SH4+GTiKnMvd7mF6+5b18vxXYdaBkZ6YlBnl6M42+wMSvrOKsHCUHuvsqFr883MoCY+NE0ujF+Mn0HuX0tqI/rk3AgTeLT51jdDtVky2OFP0ir9PCCKxUemFwb1nOBVFMq9YoqYuwfd7PLK3TdjEQHpYr9Hlij+OrriPFHdc3IM+batmluUbHcKV7bfHm7Sy+4nlik60ZKX7ys2iC3O2p36XzswmJ7rxBo9zmM2gLTYke+wybBci4SYXGqXpDFid90/YuXQ/4rJDXcG7BwE9cgK4KEOj0pSjydPCMHHQ3+1dixWewFRyW8kapqTA0fATuAQKTTtRuFesQnP8KJaVrhXdJdCcgPRnJ4XeDEZlKfUebt1uu26tUPrjfTQ2dLHJvw2ZtO/sLgt67BTNyTJDyZGnDDmNDJ3oOkN519AIIslGqlncD+vUUvO5Aw2F2JRDALDEbhf/yaeoOI0NIhwLyBCJuhzbi13iiuOa+518YGGm/eO/SXBxm6nQKA55h8cxFDC+UJ88sg+J8Lz+WtB0aJwn8Fpc0FT3aoZ6xgPkmDFhfmopm1crwI8HUI0Jv+BWUETOEMkIq0ztnU86G97/gAoEc3D8++e7VaqjMbknEqPn9JsMYYge16/xnQbeatsnKraW7qcUOgJS+Xb4DkFh053fnSvfxsIsVlg5aZaca/PsZlM+V19SKGWuxmJEfpRkO2906NpTkPU3mgk1WRrR8/V1+UciYVl6+DQSk5+Bn9jHmvR+jat/j3ZWaOYKKKG4NARiobVgmEEcInDjHmZRdw1IRvRiRx9KbnP0BR6qnzJ9IlrspD7NdR31sXtn0oY4JgNjYYmXmzZAOG6MEi9yPCs5kl7mOoB0KgwuPbXo9aUTnHNKX9u3SJrVxMrnEc9Y9SI59dH79XZZMGWk+4vM1x0LtnoBGPHDwQiSzlonjIPaNgR96qW2gbvIVymXVhgsJZ79ySs2UYOjzCNKGt5MNg8ZkGo31LD83zTZ7oEflZDK2eCEhwLenJIgcE0DHIKiDdLa+6C3KEWJTneXCzmOM/rxBYwQC7ILWbT528ZQpMfTIv3E+jXxapPEOFyOSfdEI7oFl6RlSQ1EzqAN8QbxENC/ZlrphFaDuSG0oj89HGv4TAxgfm+z3cyjJ7UsEd5PGMjNVHDEmt87CdPe+9XQqowkTroFzefQXreuW+N6w4UU17S7hWadJahAxGNtTjIMsNPhLG2nZDikbItWgXDHKyHkG4Y+aSlYUiYrPACwbjig+/nkayxQv2YAPgHjESuz/ZWr6LX444rBn7Bx2Ph+a0twDL/2iC4LLhxxTa2sNyzzIpjaUKM1I8jvhMVtCyxSQAfuln/icdmcPKLWOjdzPWu4yB3AcnRg38RydiHQDWSrZAtc9edvl+CKIE6Rbxgd/M75QX6hG6iEdpyiK8fPBWXYeouMG0xc9swzD1fwdK8rDjH2ZAhYwh6jvaCCiodx/ZwTZiS8owBW9mtbrfUthqLwa4IzlTSp8b19DLCPtVvDh8re8TzgabLoSta2KWlumcwWM9SzHZqAILKLOGEEev7p2uHp8AbgDEU+o3BGjEbdvh68qi82bbdrCk7sjsKOrhq110QCweZmEGW6uM8nlfH3Pz+tcNPz6IpM7Iv62ih2B7EGyAoMVlLv+3pTI4Fnjuxm2T8G8wkY0NYslCYXyNRud7cLsBQjNzfKyynSkaorXE6z7YUomOo/xDTuJ4qjiA7+EnyTkMitnJ1c16k/UFYuDR9XgBOm99/UBnGYHI57m3i+SscIY0nXway3sz4tYQP+WBOobYDzx+EVrBOXf/iprnZMDpR0kSywVnS1ezNjRvgoQ12V1YLB1Fc4osJyQjO1a/E1m2iQSxTGwE2/YfO2sdyBT59QSpvjw+wS33+NSoIQaTzVm/ci4BxbXgZJMMbaX4WAL1R8pVsGrCoUTJRnOO4UcSAT457P++TSj00PmjSHYhpQXXRaKK/Yw/OwsqUozlmRk9LRWifTvoUck+cNruLQGtK7kWokxB9/weH+2SJ3ct2Z8QWocn5CoyEWyTEeLVKolN28Jbz1+O8CsrLogmdv49ghnwyvvaxZsmcmbY1mWILz3FYZIj1u/P4qSS4/DsYyfwtFVOaniA3eNzBX+J7hGalUtp/XLUIctIWtStmm3huGigV9VO05aas8GC6itC1CRXTN7ULqSk1qRbehFR0bX+4aMcBM+e7cI+M49pxh/u/PIuZkMl0Yhc1G271qo1AXoDiYYyRu4MsQ58O54CCtLjmZCvcfNTrpaFhflLeNshZvo8d8x9gw4kyEamgw6m4qhdQByggeC1dz2rg3EvH6ct9ssSN5IVYi1Ot9DzYFHGsXQ9H3tjaNbCeE3latPECcvdMzeEfRjx3z5xdpMhdajmqUP4afjaZViqIYM0K42nTf7TX6lZlP0drDw+yVJlXODhTt48kaRGHsRvz0P6xOKz6ogaHJy47KmCnI3RnanZzGrbsLmjOomhg816xUZAlhwluF/h26ZKl6lP2f0ipMweQaOejp+0Ow3hPkLEZSzB3jPGUpYiAGDB0cnoUvetI7kbz3r84SwIXr5l4YfbwtmZj5196H9gDkpBlC8kVP10UCJ9sunN8AWMQLDPmJNn5z7npgXTznGue5KY533H9VkOIw9ISJ7lJqTT7rcME/Fhsy24F9hEQbpJgg36JbkkPwRED39JMXLLWlzFUZNZaWB+x5FAWkp1StS57EqHOUipVRBNLopX9RBEwZH5OZ2Pvypz8Tj8wSaG0+U9cSzoFP1SZFfnzF2jqiMawJMF7mOwvi5ZlcuvnQxHVNhv0ZMJdxBOtdjPX9U+o7kvisaPWXsu8GVoNRUSL7TCPHHW9E+XMw14pcdrM9uWSj8Gqe14ot1UpX0s+zwHBajx4gbonmzAp49Ls9FA4+psgiGnHeQSv+VZpKDiffkCOn4re0VSINhineg3p2wZ21xbhhKCmjMuvCztIQAA2cpFYgyaRE3mXgBQKPd7NJHWiW+b12eTYcKpvQBwRfBdQsTomMelBU5MVpPJUE0552J1dKSMqn87lmG/HtdTI0Kp+m0MxXHBj/Px9um7weNxjtIH50ejp4Iw0MP2DN74FFjoyaoXareOgW66T4zaazg2EYPwWbIF1V0/WciCiBdcPZ+T0xGXUiNByJuV+1BuDZJAKAAL1Wn+raxnJf4JPcdi9ZTNwmUXsB+1cd3Pe9QNPjSvOnoJACo9hDas38PAPwbB1PE3XoT/ZGSdfQkxY2jqvjcTNvv7JuFiTN4rqsIrf3otF92GMByW5NcBKiMVeS7xYrP0MHdF1a3FFFTWxxTWka44/pYJCvlsSbgv2GLsJq0NjWF9blFw23UU6xfKYX7uGymU53Ph5R1Iv9TsxXlvowMhMrDaG8e0Gg+Z28XC+GL0n42hh6Fy1/uDJYUQLOqhcozHhjJ/uT21hg36DmBJTLiLl4oklkmB58aQ9uR0rxwzrmoDOCWvCjk0QojGGT5F3uVwteH2tMfW6TDqwSqrJfeNS+PEL0ZTJ8WfI8M4qxbZ/G6puxuxkxFhigG7JkGHfFrAfI67TA++IjzFClRwkxkC3jZnQLRqN4gjSxwDbwrAZSI/KWh7EVTbZU30Jvx/bg7Yxhi48WFbtuj2uSaxDmWhWEy7TqzAV07CilFDXDYl69/psim/wJxLdk9TLo+Rjuus0xe9uTo5VNdZ2pXxcn3o3q93V1JOPXRw/w03+h2M6BAI3QlLqy4lCVf5OjdKUPxpAzMAIxEFenWoD/WEomvx1+e9H40BIPd+Kso+Brh6AmVzLF7RfkfRmcsiSaR//RQpEe2+uhFEIGOwvLcRLso4MuE+vr2ZvGLtnpLCml9+cg2NTox6EXVcV8srUm2PRPEzv8rbv1FWkBppVE91ab3T4Q/0TwdEIjVc60llBVtAMwwlcH1bDoKZDO0sg4v6R8TKnGLrwTaISXH9Z6NGUDHVO10H3nqPIP2AOn3KSA8fri6ZRtt90RCdlWXfyuFNsvmqW/YmniUf9HPQ04qZeelatBG3BgRqodZYYOIj5R2egWcv5FAa5i96SJ/PuAM8g6H0b5LQ7hWHwPnmV6QUyyXRbuFL6KSGZx7yhhkFkF6LhH8Q7qydICaPzddwO8a4wzlB/MOP4leNqhfXyiXA2o/jhjg5lui7l6pO24mxstiqWPxfr7fQ3woT+f526z7gMBog8Y/XtF8QZgpRx+T+jiwvIRsM1r6r/ECUiufwrurIxPdpLSQtT24LNNfZ2juorwjaKJCtZ3Um57V+MDA+4V2nT5bvKCA0ZKXG/spQKs8Fb6dnH07Re2XF/abjoKF6wun2Q8fYyI/uYzR6cHEt/9E3+z+zClICqMSNcJExrowHv1bUrwjRnLXII//LPvkhzM9nfVtIxaYQUJvm/kA4bzgVYn6OJpSzDH2IweMTAa8MsmH1h9wRr53e9muCsgQZyxkMRRCQB9ieaz1IIYsHPyvT5tW5dkVaTuCHZNGcQRLE6l2nAKutZ9xjrdt/DtsgJeF50SVrrfIQPwzaUC3Pm0fUjix67IDqxcrxjVs5o77VuL58rcmh12RSdnush4zVtQC3mIWIB18okvOtEvGiS2y2r4w2py164BO646KMI4oFRB14qTiUHdSTSdGz+oG90+A2lL8gt94K6cX3IVQQWyRCQcYy1HeIqY5VZNYd/LdygD+h3D5q4V+TNCwNZFiEIyOefTOPMvhCdl6VLgMXx/A4BUyw/pQBeORgch05534eqZ4ry6izZ6jlMkzP6d/vwfLfKQWv6xoh5Oy0atTKk7/VXsXXcc8YQpcqySylxUg4Zv0wi/6er6CGj4TjusRFJoZHqRl/PlRpHDTLxp1nmnxUyw6Ct06cedkrERR/PwPNGNKTK7KY8gD4Bucu97FXIbkuQprZj8vj2Xl2qDG4XUwi/UFSB9AUyM1xD/pib0M/S9eFFCDXxRe/9mVo8JEnUrgtVenmDDYggmCigfFeIjuoE9NyGv7ZT8J8EX8jVbCRAqrM1r/CPqszW0QEUuhuVw9jhutjCchfLP6EqFu3XnLL5LEbtDjO29F5oMPe+Wn4OEwWPeUfQEo2rA6+6HDzqyiL10gPspcN94fxoEzi9+NzFjzv5wKw4MWbkL3+FuMPICYmA5pPr3C7V+HwEXfY3fegLL2m9Ne+/ZldgFb/Iw0myjen9l/1HF0TurBH/xXzqbIQgAv9yFeI/SuYotA+NGa5hud8Djczc7wpwyM4b8bMmTVFAchfuAtpbvTH0ZFjeGXXCcxmjIyfB3PbF6m/Afbwpmc7kRWKPNekXpEmQvas9gNS0kUUXgiI8InIzONgf2xxoTF+uaLtAUhlqf+jgiowNXbTlXOdprr4AZ3J2RCZpl0shPw6SGk0fox3Rv1bxUDrY+AmgMzFqG/+o0RDeZgG1F+tgYIjk3t6ncQKFIvIE1MMkY/NPC/01n/sB9CQJaQ5zk7a/nt5I0nr5NF2cD1hojNi0+ZutKWXkGuvsrCgXi3PTsfVt9whChmhPJqwt1Nf54AvVI/HPfO98ZWjF8mrBHdA1ueFiT/8Yril9ExzdoNx5fpRvsPSLh9ELwI5QU96sSD3RYjHE2qEYj/pen8anyfqlGb7kO/jjjuoh2fyhtu1SsTrBhHQ9rnq5XkdqcE9PWLCfuoirz77hFwmLslvTz+Z1fPcU2o7LwJq8szDqaC4Av4E3t0QgVlwUcCBV5Ue3XSvvRed6USlahv1ZrZ9WSypUrElgXtDhJ05A4FbPRQ5Id+DETsFR1litW7nzCEmz9DosrzYj+IImjjxxsn/bw30C2mKnl/KbRBIKhnPtb2GsLKLDwQkZF5pCjUaLXAhVjlnO+HwpU2bvfQDkCGFWvuDy3aixwInLpnhI1JVdcPxAjn55dgrRcuQK25n/bxa3sNUy0MtW4oQCCcYnba4SLZFjjmnx0D0xKQAWG0NPrhoamppNSCj9lHRyJXTkyQQrWwV8nMCjgd9hRPKGhr2Cq5WnR2dEAjSnrnmNS1D4nySyUINEvcleeiih8wz30gimWJUADZMuINE3ZWgIIJE08ncjDFm9NLtD0zwhJZtiXAuYoFcUEN8ziM9IkxeoZtrm4n1U+e+Q+HvN5EC/Y/u9G+Z8AW2hKHzk8YFNJ2T2dwtxSLhGLhQp4Z4JVlCh9Q6Q8wOO3bprt4zsmXaJCVpeuOpbfbO4s+BSOJ3caWRMQRqzGLyZL8WLRbUu1xayP/Xyc/4udO5nE/zcprpvs3mQWt7WMk1cy0OYFRgCZHZj/SDjakAYwSJ3x0JYSGSnanq5KcqC6uP4IhrG/J4kEcOhh719U7sH2r+q0nMoZtDqYVJQBj+2XgEdmcha0XYfOAvKmTF9u/q9DvOJFoPzbAF0aRyLZwfEOt5hkoGgwWSCnBUBOwqWjKx6z+G6VyCv6B2ChNtK20T0ZttrRek/AUOSmw2tsWJCXFVvcF/HW97IBJ9e+C4bOnNpuqy5WUG7Zywv9TlWuPXa45NpGbs2B1Vvd4BBzPXIOHvGucILjcW9nYQCI5HJEvlEkNyf/ZKqfERfwp/xrZ0HyJ/u+FTw93ouv+DfyCDWDYEPNg+plTVGUdQaQvae1MDMJLgM5cQtByUSXlb+j7NRZdsDGJMZHVkGCA76KBzHQ9ozALf44Jt5btjTrcl9h5bZYsanrTl1mXFxYrHUhLY3cCd4E+Yr5fIth21fDNta2mMOnxINsu7r18nypy/l7gDZGBp2ACMwI9UklFGDcEf1MOVPODRIMcEpXU54s6akBkASYhRASv0tyoSYBOvTy9AwJJWLpzt9E2XtJ3tS5gchFG77BNK8WrR0rBJ95mq5ellVuegZSz7AaI5s9dwqWniydrt/d8x+55Nh8RzYoYRJ/BBxEltWrJH1Ptr4KoncoRrfdHRUgFURWmvAMhNXnB+Lr+U9G+XB5Cdqes9f+g9PIVXQvFuloHDoAtjQpjnFIPAOxaGZcpsWhaDYTdpo3j+DFmjGMijyk1buH1z00pECpnpsW+uU35XSYMYiZqopP0x1+32cdoQxRDw12dSNx5A5W8ZmJZj394YDV8sIKsI3/5XAK0jO2gh+xXYtIbcm3p0x8D8wE5UdYLp90WnonhWG7ISpOUUoCzr3A5nB8mvAgEA9T0SbW4AyYLLSVDb7FqayRXS410beewlJYx4Wa9TAwy1WIrilL2+CieZkzp2CE6efc4g2V6VRYCru0u8f7Dx6wcAI+bLGqkjlLYLUVmgCbBHrqWlws4LLiMpNcRnlWOeUm0w2Iw4vZnPWDnDUaRwHtw7UqQxFDV0Lw20TPyUyrW0jQhyy+bpHPuY++0DhlUgZ2FdIwVxB6i9ilE9M/icAF48gsUs0Ni9MQuo9IKkzLQfzhPQ3Fxyh/IWFPbCsFbTZmFsG62fg0yjBQRZYqm/3eVryPaXODez65/yegQ+R8OYyl0BIGHiJM9h/8tMvzT5CFeLjtttCOu70RL4Cu8dJCIyBgTrpYHIP7LTntiUohMZ6zwgoiMknaW220sIRLQg+zjvmlGdjfleFHkZBbID4mdsWKjKD85ODeorAg6VNvPBOhhYKT7IMebI7UEYOq1YeLiJIuf6v78we1rU5msAva7H2tytJhjlCQ1Ai6vvPY755/HxtpF//OFofz0CNpZFKqi8OO0woEN8OpyQtmi69sfeyMiSxU0wF5DqXazXbcMO52cc/+DgMjMQQOUl57O6VLKVwwCL0WKt2xOxYfml81op28jzmcK6+D9FrEw9Yj66nebTGjr4H1f+TyJvnX+0sKmlYLXT8U18XDOzTr7S04I5KFbUPyVPMLplakZ84HKOyVkK1Nb8zw8LzyhKA3naUvsKJJ15RI8ub5pDerSql4CLx3cWwg6uswWQAb4UqSqlIoOuWBQKXliAxJwEQsOhPgj1cVycCgFVI5ks84Lp+5rmQSvAucZiiLAVMuUmWeD7IyX7l471Ro357GUnOjw0B1ULt/gqZaX1hyCKTTAjH5+DPt0cXQzuGuFaJpZpPcsGYRDVtHF1VlKEzy3ez0KGGzGtqtavSEFChrUA7l8OjyLR0k23AC27lZiLIJmwsOgSm/yliIU5hmJ41Y9PD5369T2CpMbZQv0n4WNmjbmfYwe4YF/A4jAmbYEvRAL2E5vPIYCCQ/h+n08sws/OIMO2Dp4BfcBxicOxpN8o2oUJmap/Gx9fx7v8S26lTtuCyNUJrI1Xa3JG4gtpyJF2/3aSUF+Mx+h3/+tfD9mjTN/3mx+IZttJVFH74ytbVD6XIr14ZdfMxAnJzXax62VNJmWGYznDyn1oTbXXHiiYHd75SiVXCye33vW/ZoVXAfulFTyUTt0K/VeoYsuOuvNs+5mRe7lkbRvHt0dLDmT+Ln1cVQnJcfHSQvHO62uVyUyi/tElNYUon8xA7nlEivYocq6IoHuJDihFkBQudQ1ZC/b2j9OSx+4T6iIwUgE3It2PPbS5ByHD6Omj3mEiFykpVjMS3bN5oqCwhJDN7QbUn0km2t7curkyYqaZysm9E6INx1zuEd7gNBDidnzWAIDlUlBc98YvaRJBHr4B54BdEPbrG5WBtKJLN4lLQ09K4lpiUmvVcXsJM49XlYCp/mJMg2n+5acIbQf8vDuWXAzPMv35xC73Ne/OpTVWT4B+/xiIMDHiFu0rluuxl1+b/w0aY4swe5B2azGpjuvy3aI7CAmWy2Gq2iA/mJAbET5gnwTZLZcIpOxe+xUm6Zqt3XpXBd0+Zh3gLCrTADKvtu8amtXiwDCxi2InnTgL14hEOG+v+asN09QxlYq+YVSRRTezqwN7sNEv1Sqp1/kOiE0UpZmfAglM6LpfP3eo5ZbBhbfY8D8oGtViQgdBkWoyMb/pSDCJkgmC2f1LlTEfs6CbTxYnV8AlQ+BQGmhQzI7OyGMYhJkpddZjzaoyyZcF7XYCiLygIQuYiqJMQhJxaAN7eqx93SPsmrgGJSNdPfq5TPO97bwrnO04A9IrZ8BcDkaOp8VBxUfxHiTBtjf0NrW3ha+YGnuX48m6rRsTp/iugvsCS62kG3Po3HLJZgB7DFj5eQVMR9+P2lwLtVuaCNyyGJ0LjGsMwBvjfCmiyK+4MFcVqVg13uz72xrlw4vuIbCEamJ9UWSpVf4tjckHXcLnJprxW3sbgawHLG7jGUouDOiyGCk9GmyfRnQ3ShH5bCxosWj06oha4yIngN6aY34DmKGzEk6V/qYesNSu6iNdgIu260Lz45oj0/pqJyQ3Q0oNQrqTOn20qGI3nm8QunWnihH/PvYYkUXA50qOUOK4BweDiiqFykVNBKf5svY0AGo9Hl+fAiWB/D+kBhmK30g6aFt4hTfP2dzPFNTzyOKHJGSoTU59fZYKnoKBcnwJvglXXrWZ5+rQF+xr7obr1U6k4sy5IsbVFk31qbk2EpmftjddWPfw+tuf/GRO6PlJ/JZXjNan4G9qwoPg3X2rsQiN0MOSccucJuIUULJ1KDYInoRpp+Dv8GtEF+sgv9dcYpAxkfjO9rFWhLE0pzga1P0fxWoPj7M8MJqK6DW+DAOMzm9gG6h76ZbSfaewwJF4SYBZGZOHzvWijTe/slv2R//nbFuZmPZxh4nFrFPcCiM5NZHPcTvsbP1eaXkrjw2Z4F3oZqupHqdVwyWhER3PKI9aB8J+RDaXL2r5JF+dOYdoxOwzT5Yrr3ewcOgI0sB0gUpJQunusfiYAOesJCk47p7kc8P7NRIjFVvJriNZh7iSrGcHi+BOXDADF0bfH986+bhQS6/ZEXYXNbfOzYKlOpgfSpj12KKi3wjRVOeDQyVcjRUFz4ETGTZAMyugUzuh5pyG8bowwIRzqdXhN37RyamFGm4JtPoMhj70M0mXHuH6bSp75L3wiOhThnLDQzqhDvMtW5usFrbwJMHw31jkWnPrNbw5cruI5AjlMSyeeKSeHu8m5tkHvi2q6kgCJ+drubmjmOUvFUCYyUMcZuj82PeIu9Euo2agrRbwRA83IIKuPE+fnbLMZ1ufzDozmlxQhaBWouc0NqQLMLku95afS+pTDrTROfanxg9T7w5MVo6neF+vbszqd9ELForTgX12F4Z6DhhjUHypZN7hJrVmL1m3SpciGAEQ8E0bmKeDVkIpsCoqp3H8OKbpenOS6OCf+fFZeIY+ZVCI41HT0wBLHA7elPx4B9O4Ssrw7r3qX+tARitd/4w/I3d4xanfrLrZi3BJqC0OcZgBdIADNyRNBozGPTt0prMByxooMC1UqwH1PNXgS8GbGG6Py/arrY1iMjt/0K6icDyEZ/Qei6r63snmcLulDMkE19nLKhqd5MZ4Wbv+A9eGSUYe4TPl2BmHffYe4zrdn65cm41I3tUJju6RXuc/GV9psTHrA4C8j0pf6dOez/w9tdwoklzlCz/S5HTCeXRP2MIZAaO7b/D+XvrpdBC3Xa314i48Z23xaxqgIzBk84ahozRI0lBbLp9NbI3O3u7o5c4Z30xt3SUawa188gmHzwjGJUDFVLdGiinOWi/h2GQnz/tEMldoszCFJXVF1wJ3+bcx8xMYgN78e6Igx27iE6JpuNIH5JS3g3tlsTk79rknpirbFDvinDJv3mKbq5QzZa56s2s6U+4kfRukBg8pVAFyW8ZxDZGhzRCX7BzQFviXm3OjsZ180HjWLHPvctgUiKHqhW/5a8E8a8kl0XiTdysA36F4rLiMXmUU8NKEhSCkTTZ3CaRaYMFQDot0Zo1gC70XFhvz+S119l04oEFOXHyT5u1y4kcUArJxs46KClpaDh0EEeCe2cjG0Rn7TyB/bXhnZupjUhIv3UepLuUNvCHsvLWLNbg/RPUu9AtVHHotC3UlxlPr3fMVbFsu3iqB4f2JlEtxUWajjSF5v0MGZyAmr5GhFYRWlpARFCxdJdjdUibzKgOwsYVq2Yf0iG9R7oVkOeQsGGOhRS1nV8OTMOPJxouwirrFRHLge8lusVRXff4MhdK2V5DCo5k3cYbev0vRG7rJqOmn2A5ZV7IdeI/q+D9PF/E6IuE6qEHUFjlvtqpdW1gkSROPQos8+dO6n3ZECZtH/o5Nym6ZOx+2baIiUM5hzfts/jvMpKWh6Dhe3RRFmFbQTJgvjA2rxirL8WYS3kdN9sAvlZpDSq4qBten16Kx19ovQotFK/yMfaBSyR7RTQmZD/TiKiopIFhKqs4JEX97mhm3R3ZYz7RjyTPshMCXu6knMRgZaIlt4JDsg3qbrsH+nFFCulA1Ljwd9MHUV+mMNZiCRQehfv9xTGKpOnuGBqsb68zm+7UTkeQy1uFinfOlMvNdC1CpjW8cYFCpfdfQw29GtGpOPusOyRsRtHPXtKJ3Mk9kyqfBNU/iUZqMwgozrsIPhSt8EpGopJXewsmsrrki91EdBgwsxtZkomZELk7Pk2fdaLaCULTBfS3SSE8xOnbshWXXWt1ixioeWxopV8QcuF5tFhce4u3uABCgtcfuTTPFAhJQ3bZYiZamwGYdkUm/e90AnbHN77bsnzoX3ESmGbFeJoRWBpiGFkPrKPTeYBLuAiDs/6Vjb8oIpbMudddpvX2wxVDvGjNUSlpwwFLJMVkFNHV+/ikw9S6neDiNos5kamL7X+g+vOFl8kKn5tujuuQuqYJOBNL3WjNhkyu7NKcRIqds0dwfMU0Gb8Io7RCfSpBKh0SPZGNziYFhzrgq862pnkJtU84qcC6y6zeSwB5v1b1Hkf9T2DyaB+Hh30lRqvcewNtbSRhuXpHp4DzcZ57k75NhsaY6RI1wmal+V9Jhj3gxMHt2my2SJUiPV+juFBq59X3R4rF2eviExeLFtxSMCeVFYXfkEdYHWtGvhXDBn3Dui8E5spkgDJz9hVUhORR6dHULaVPcUhx/XV2lLTpO/imf05WG5ikrJdCv3JUbysW+5CIo+sdiSrJoKOrvWoz6Mpu2lU6bEpeT37pEazFSEiwyJWYCqB0NqnzgP4FtWv3gwhX82Y7ERrqS9ZEf2foOdWqCigTfeopH2ADTAOQJ0dDDCZLYOgn5cIO12lVrkIDI2KRflNQbyPy3pWUk4YqSTOnaEFMvQNly+f49c039CYRNR2r5NlG0s8ib4vRYpUgHAYTyF33N1M5ertx2g4LYIba1TfyUk/5kxV0tGovpRau8CkYmz++no13uhDtWcm2PwzwH3oRXA7dCzPwSs2ISSG5UqZ8iENMHKYKMjEOYD/X4mRXWf617x1dilJLhRjEEt1qWl5D92qAtnAYhbAmETpO06BQqHFY4Nqt1uzFUqDkMhKHXVpk2D9FFVxVN6YyPnKaKFc+OOWJ4f1tl3Ig1IAUCOF9wgwI8g8GNCPfKai3SbBmAEgfyb6pKbD/I7qAE8UeJ9GWAqXljYD00yEdL4c0QED2dmSfQCcq5g5hCZ2iLWEtqNqcwxP8AF7/qmnb3lSaqR2pNquJr4Hil33ijdio12rV/QhsjPmPMeP7b9rGJI1dyXgrIKL18Y9Yi/QlOnTcL5RthkNzSQoSWTE7QrpWczUi/zdXclKRMtohpaXQF1eIcl6/hxkseObRFMhnQz4FnrgrYxcMOOQPNjtk4WoQcKux8Xkjz8KsMGwDQ0ujRjpFr/7I0KecAbICMspNPN0COu/DL5VWvpSDJyEKZN978iwb3t3W9fiUeF1NfTBdLv6qbQiky6Gm1WcLxOI1mcIiCABSYCrovjcZhlproKJeyG+aSV4JzEpsZy1JR3+7EiWIukHET+6u5MLpOUrDp9juJZY+u1eMeiKIdcUS5OzHyQPb9gegTPd5Y/Ucpon/JeN+rBdOZGAG0dHLyCtq+7xQnm7z3BefOAvROC0An+cmRBnL6mzGY4ZWV98n4mw4Frn8n7CovfyiB3MiehDQZesMVci2o0ZC0XNeGgLjTiIJDkdFDOVCvGIK+1NJBP0srAvTWfUxLvobSCwymePTZ1zzfT8bcVHNeHDxmdwRK2/YT5H5vZvnS+M5ET7Oi8tmN8lYFD7a6hG2UfSU9Q83PBm73Ic/wRG3yv4DHZHl6MH6+GdoilVWDoG+jD6JDG+HXsIIARUdwzi5UIm6c/h1rCN1WH/CpgN5fsyF6LOdVPE+AAXBhEm5A5GIhCBSjvBt4+ABpZd4zE9XCSsubI+Lc/ekWMtVjSXEVNv0jT9BEdto++yLNsPvNv+1M96PhWtawT6UfmoL8syWw6eN/5SJlY4MSkA90/dIlc99JDnl2jTRP3Ymlm+Eh2+essnY/RpAl/eSiEnVwcDTuATZxFXv5Wr8C/pii5hvpzPZK6bPAB3MZHFl8Iqnw4P9dWt+S1nHJ6W9QDanHNR2TDBNrtSRNbYRo+2GTxczRCMrhM9YqJkoJVFZfJqfdo1vhETSafQIbpAnyNo65kh2/2odUZcc5in6PZUUTOaNmGcpWA/ZCDOuwzQR4mcMmbsfPRBPU5YOn2IBo0dHlVScLLTRdjoSVc1J+Pg3kga/H5OoUiuqrfnVRHCU41cuE5IUmUkLlrrbX8X9eKcQ5OYB5YqRDI63szk/sjptb7zbVytPIwRMnPOG1nwp662UTEjkYc1+glxVvOch5kt2SeOCN5ZWrJv1yU67Bdj2JeCfpvstcNdIECKVbwsXMd0ipBSxCAfcDtxKOYYRlj/UA6jcj29JsYvXj/zsTRLSesT+GzYkPZpXZw3pZsSmKLL7cAQw2W3BP2IrVM+MLygSljzZSG1tg4i8dlW6jMPdgjMu5vMo/ffGei6D9VyNwnHNZSlapIU49Z3HVA+/Cs6WzRaMEx3eW8XBBlx7hYr8zsEuXFNbg2pv0M++HcYSJA4c7ICxHx0UZr3La3B2Qz+nF2BZH+Ddgg30xZvhHrNLFLUuUMptnr/M/D3oDjPRiiKKwRTQkfyeoIZOH8XOAuTZtovvT9oYJeE1yTkZ0LL6IfEzUv4sD8q97+7V74yNf6dl+RlXSOC6Z5+XSslfox8H/8hv5djbhhnfa+t4xF8KzlADvkbgZuG2pXP+HBiiv1xxiJFhGAJqxW3Uo1Y+AV4UBkgzeio2aaNkmA53FRqiHYURyz4CNG4LZMVKQXlEMnM42u1k3HBVEEDA57vX3J7NAPzyiwPIzDVdfIxwyXHQGmYPNGLS+YSto1978dCU7aoRCCuDFS5Yxrp1ALJIfXj9dLcZdlAQkAnMeGHIgHhDNVI3bh8WRblBlMsmBB9mliMepsYQHrKhXGPACikLYTpJCOu6LTHMcwsNRAUaWkZ2Ay83lfpI2onuQJDVfKLXJnXJBc01iLr8JdazlhrCz6reVDErkDibkBesPkh8sVQq7ct6/q1LcwvOq5NP9jOJnW/6ZCZGfgOsxCid2wp0sFiOjVDUUBN+CDEcaInGLppx0qVIeyFVK6jcEAuXpqM7m6M2jDJttmXHmEAHp1dxpZO1KktCyKdZazY6XeZCaScVO08PhDfUS7nSnrUmU2HxRc+k8mKS8Z1zz7HmnsIblLw9STcAe0y53AtDns7XPzY2AHAzXNCj4wX0MhrsOccJoCZ29Tbj0kyZJRUzKsfahglGxLX58vzW3XHyuqUU0uA0rnuy0+i6jNpeMY5Zm6dnk8p/dwqcs4JtQ7tS+/gY65QIIO0OIO6bSe6hnjGScoyFYkmO+XC/uLWcurE60dRvAcDY4cNuPn3OXlZPmpQllyZBmiesrOdp8n9BRIubhHENGC/PmVSAS7/qOmO2kbaSJ2O1opC03winznr8w7P4+z6QjP7mUwlIZ8ReQZyZXjvFdV20IdNODB5KHrL+45p0Dr3BFxw2iwLL7T8ZSB2928bJJuVxdlRvNneaEAQxN68AKsgWIyQ+Vkmoya0gUD3ohpDdHBHzjYo0g4gtqFukAPzoIlIG08UDOC3xAJUTMORDgNikwMoA+I0Jv315l3L67x38Wu4Qs39pgFtz3OIV4VJTrpWjCF4rVSSHIrUzktPYUZ211j0nFcJ7ubYQyiY+1JUctzhd4XDr5vkC5OQc4lL6XUTSA/itjDsjjebskPP+HFvunrNKL411UlV2+OWg+Eqnrp/wJ11+utDe1DXVbCUZKvnuKtgTI0cSXyuPfAr2CT5nWJywsmWe25Xo4/PIYIYN0Pl2aD746p4HYJ+HWvX+BKo9NEHJ8SxSD9A/lSu574+hvOOtl5I3ktAZXmUw6qWqDkdNb+sQ4mc44LF4yh55smlNKitEjx0FIkZ6FmOsqSa6od6RhGmz/IR5UQqymbEBrmnO6jrqML1lFdwCRcPHhQ2LZdu+M0q3ZkFa07rAMVWm+9Th4Tra5U6V3EQ5f175sdU2B1iGPLwdOJYR0hdwC6ZSe/Zf/pTrOuy1rOElQ591ieKv75BkDbUUgIDm5CyJmUDZZv+GG9NjAPhwPO7kk1j/I6peKQm5JgZ8KHLr36yF8U8FgLJSykNNv1ciQf4nOEGmZIlZfL9XvclQJltNNG2liN2uSVqI2TMCHVIFw9sSu/rO21Cse2MJTCalou+xXuhn/EfmooSeFRoEbIqgoGXo8Tzn5UmmUwgHZ5WW30wO4thsMDIxKb9U6kcXi1d1BhE3qKgpfyon+wZRXJPDx7FKmWQbHkrPqYHdl7tUqjIUWxB/MndkxKiud4DZgR1D6yX8KeYk29LpGKMF360Gk4OKL9KbNfKWkWqyGBtoRJAe4N+HnXGt38iC66Zw5LFEkHOLEGZ36eKFbkdqoPd/l9qv9Z5Boiid0rzAsM3mSDN+QksasrKCGrkuvqrXjNRUrXpEJz7o8qgT46mWxy4x2fMGlOlEAAi9phk1wWO+DmTnttnTZvQT8f2pIERhYN0UF9f/e09AarrVH6i6ATA4Blx+CVZBMb8GX/HHvKyfYnCXHlFlMWuQL+ROg87vDCVsRBMN5Ly+lGnUFcDnAcoBdEmnGtgoXysyr9tFMluCSnrrbqY7kp7tw4YWmJWDyAKXVvN4oEenmJ221I7jag48FfPfy9HdOklSN5UNGX9rHfNbp2Yc7uyghbs06pox6IbypfCTP4W40DTiGhaZ3eZVa6WF5/VfkNx7FP2lSwTlzBJ5NRJjOMjtcbFZFeE5RA5aPDDHvhvznIk1ktwSmIm+D6EgoFSqrjqI+beC+IYcPm5pjWzfW0ZHEBDLpLhr+1F3FAj+Im2Z0l4yoxpMNb5s31KTqLFSxrXrYeg0BHEjfgieERedt53X0WyI7EyOlqhnyZUCEkrbtSYpEiuDalz9h4NMHUL39ChWbYS9cAm0OxUhKjBHi2o9QfhDBWbnd6sIJEM/j+ueieqtMzyvG4Fp3yh+aILWLF0tLOm0oY3RKESz+LJ4ynPuMcaE2xFVRTTlUKOiPuGswDA72hoTJPKb8DBA0Q+8qHKvVgZ/pAyqCsJQAP1jp58Gguzp2OP+hgBDJVd3SMEh65RO+5SdqnY7FWKyAdxglLOIN/iWx0fUMmlNCQymFn58yGPIEExJe9S1MotNBlDc7YJmposhJBpsrCOi8p9o1XQfCltv1TunbVhjyZMdl39Zce6ya9f0UaUDqNWQFhDaP86xHTKQhcqPiPBh0cjf6U8GlVhI7s1MoFm47VnHlG+cldfK1hpXtM4tkF8zXwWDod6NoUmd0eRwIpvictGuV7pqUaOUTAT5QeF9KyDrLy/toKHojCexSElHEIfVqT8AEbtB9ERZfRoQEmWA482igH27tERrricaYGRNNYqMehm4MLOcR0vw91Yr8KOxUmhQUZK135iRk3YnIiDzp/XoLmqorIYEseh9V/67fdpzc2No6G1mMWWaiTAYLsm31OCiPNAKkEkvqgwLkmkH/mRrCaCOEC23RnCgpIXFQDVP/g+dzhiQygXm+ReuwjE75u4bOQAXle+QWp/iescsN/3flpFWdSJWK6ogjI5ctOLEyIA+s4O0iKiohEuoOVzf9H9ONahfibfi7RqjU0lN+5konl1b92gacYetJKFYOdTvRGe9ffDgY3HpOvqobOZhnoRipvcBqD8UZVOcdhbqieRcF/s7oVW0jF0gX1qooEsYn+Jr9C67tM16wa+IkE+go9U9810Y7nleTtXtRuKORt7faTYnIBqlj+Z+7HkC+ZiqaMYaEErSpH0WL62zCr3cDwePHUT18vdOzb+7LfOtoEYaXqpYZafeXpjQKy5dweMsAJu0T/GHa8XaKvu/DEZBqs2LMowrIFDSPYIv7c+PBQj3oWBufTxgMxUeE1onJ7V/Su4RAS5+Y8KBPu+ig195xWiqAbYMraGouGnS4iYTiDZ5/h5jQ086lXUlMbprVEDNlTmgluYgjkJgrxcveHphOudh7IBHELu+8lgh3t/xP2a/WN0SVkV/fZ2I72aqCq8pzfCMRkgvHv8CxQDAhK7QiIMk/Pn6CmBfYwPkcThHPPYU2x0Ob9+WtHTloBi2rdd1T6Abxmk4+42Xd2W97UwilTn6I4x+z6n1FZ7K8nkvQs0rfw6Ly8SR+OypZc4ubpPl9FrrTXNmtO2rohc5UdXhJ2HrqapOKyVBjFiz1JcYrajyTXR2r2fQA5RoOdqpSysBkxU0a+c2JCxLt0Dm852MJXdxF+BGhOhMRDuYcC7Mdk6RDrYM57QEQR1SS20U9KbE37Ba5CERoeXw9ZYxitsFzfCOZ57Oo2TeVFFs5mka1kgQmo5DYKBndbZtDyr1Pit8HzJz0XfXhW6z6XfM8QBA5k+VnYselDzSUJUhHjIEodtWjdbowQfYSC+gBtX6LWEA7d32HiZyJgfW5+sQxgQ5BrfagsmLxJsC0HbKLz5toEcqUYe2S80NqTjPy26o/kYwQ3161NgAVrRbrfy7t6nQvWsXrY85lnPlWKk4J/CEzVMV30Nu1nypQTlibG7mECi6XSxvducNVxJpCAwXlApfjAraFxqflGEKkLXzCom2IYcAv6LBXLabjUav8JKMSQ4+1odIEsxtxULK1yZEwN+tHSN5JZC/OjiJCZO9avmWb88uAs+oCDblWyrqtXM7S9UdbLT65R10jCpU9J0VchJ5OL3WMncPwn+YZFPVLBFkGg+hGRTOMhkvtsu7kc6mIbZB4ys1F5YThpyRV4Bbc88c8d8OADY7RifglLLSC9GhrbOCwjCNkp2cthUeSqZNXxbS59/iUICmQOmWy93dd4n6rht96NkhRMMDcxX9/nMdmMyFwvKgfQC+MP5GVPXMMa6lBHshZpVaZjPXqxwWrk+Ieg/38ymCqcyWYRCZjvP7VkkTVFq2+AmC09At16Bb8/uvOTvNnYvIiM5GA8uDqQuaPRO4pGyyiDqAoOM2Ppsz6O1is71aJ8jzyZXwkQsB4JVDDRVzBd8y/JjyGl0IFeaGt3qaTjszmip3kdITn9/8iFnV6TyzbVqPIoUi8Cp3nN/M3hQHRKhYhyxIteaP3NnuRf9MAAKo4X01UZWUdR9ZYhUJx8bu2SC+1SawrIdVfMlXJYtJ+lPYAMvWtx2MdS3O7TkgeCOO+dcom8M1K24T9roFEvCjqhKRrYI2Tkf+XFKQ4bq7P43Lqb7c7bZicbKyLbHrB8TWkyMB7te0LvrYOQrxcAVYOL3IqntyTIoyOQ+2JNtqCR39EQAa079YP0LRkUtUtCbxRZGPo7F11/eKXmYilm5UyKEBx0joJOpbA/NXQyOnKbjfxZjLfPbx58R2D7Igmp+b5ciXVep2JOoVS7O+nGkPwpaFDIxkauWQmCIMYyrT1NJvRDtjR3nFF+lOOV3WOoocIm9Igbc/fm8951Hu7J1oez1b35RBwVUUlwrp5ppO7f1St/aoTsvMFC6pt4J0KQgAcXY53nMVf5MJn58F4iYEp8DSlcg7QBuflSXBNwyAZLMaH0tEUx+IiHv+YlFWGgaztPhyZeexcMfC7HHlmMAp9Lq7zDUX7w8yq2KP+eh7x6cncA3ERoJGs6DWv2JjyG1LVFrE5OWhbJzGsWM0Ebp/3waKXz8LHrlRr5/yh2BsCC1Y2z75SrmxDvevrcjmYKCgNNaGxNhY51KTmcO6QvBAeJRcpufN0IFuW891X89zVgyc100S6sETVCgIZoOWGcuRo+8d3yqj3mgwpWVEWntV5AIMJLTLoI7evLSJkwCsqojnqt16M1FkH6nB1yvGAe1EFywL5CgamFA0c7VQWoupHsit8JjgMFzBvzXu+9yFZ2hIiI5GfLg+AeVB6gztNr2DT45JZ19FSzwivkF4N0WCpUeM2lRs6nyNdfOx4EysZZDSW8VOfzLxbKJM2NeqFEi/3lZugPMr3uI1hS6e3wXqDmCCAeh7yBc11s7qSVxf0KGSq5LrnOl/wwNq+C7cR9tAkfpNj+pnTEDMqfemt2A6bNjBj0ofeeZKI2hsNMYz+FSLqFNQbkgaTLWzNqjN/grPq3JbJxt3uR39+dp0kW1MjG88QuzpT2w3wIgF7RMdAhgRWAWxuftutK+xt4uif2xSEjhgcPlIY0olaSZS2kbbsKS2sVFdin/7pIb+pX3AKOYb9VAVLjPWuZmdrnQ6IDThXTi9fxx2z9A1ObX5pBUDf1JQ8dhBRMLBmF3jKvaDMHocCpGMF2Hyo1g+9Zl6bBFY2Uop5Metss8CmHsHs4TYrVEZkLTgpP/mmILa5rHF+Go5rKikqdjPdzrv+aWxieeZdyreNwBng9YDVBnjV4wdMBmipz4LL1RYowYXCKlChZjk8Rx5aHhK5Ud9E6LpWo4pmsPjxMK7DNlwvZmxwMQJg5WT8DrkuO3wMs/b8VbAoBm6dhEYpk4icRUgW8q+AgpkBTEN0Oj08B9Ol5uIipygCe9PMK64s280Y1c2UFYX6K9pmiR0ujERk+ZOSetfqNRC4TnDOJS/00HVH0mJv1rQcwgacm6PaG1bVqO2Z/Wvk7kp+SahAg8VTtyxGFYIvpVfdT/womfxBq6GixbRy1wXyF/B1uB3+GSkjmf1KHtezTyVaU5Y3w4L3nZ3QvmCvTv6eQ7mbvidhqp6n5+vcZmw0nx3RyN4DzpFUsOxRKYIYnc1wcSsVP7swqVC7DKLCMtkdc1a0zdsxc6PYfWe/Ph+molS0CE1y2XLfFJOGdlzUQOUVLFGn6idG/jAs8InfCYLRbPESCP+BsB84fJpV2ty+Xc4s+rkvwMePIc39aNju7uPg205SIof4bvfbj47/m9BGgKMQ+okomT1Z0p/lUp6PbcdsjLOWhad4ckMW0Icfzgvdbe7ANrCYNBuqFd9RqqVniUK5SabsR2NDRkqvxfwMULUC3IMZKF3Wd6QTexrtxDuLUu7Z5czt1UkvRXIzKDNt413jSSw0Q0z3PqnMk1etm/hzC7eu7LYm5dSFOdsEEiR8NC/Yk+G0QaKR3ysbg0li8s2PULdnBzirMhOWx/uzGH4WRPK6+ZyPsvKvkQ6NbbnHpG9uQ/xzvLgRQDzlLP/d3mzxDEhydXokrPefjV4hTb9KD6+6yi26NKkTP7bjnd5To8+0k3ZGdRDIAG+XBKx9I+MLmvg1pZ/zJyu3PFJDUFyd+JjgCrGPAVmFMcevFSmIJaGmZGs/5CDkKR3bWQhqRgnSUHXUOZak12bamnMI+GzN0sujE5Qe+Gbe9/hSoCmcI9PS7w1gn9LJkNBzjIIUTmL3eCav8lUna5Rji4q1zPhiLlEEEVACLfqplrVhMQWWGrvdTqr7MXzDWPvj/mYMCNOsetNC8YwTtX+CVWlf3lf89byplxjNTeJ8PNTmwNo032iARjq8bPFrcIqPQoqdNLTIkxcG6QnrW7YeXWg+B8L/R/u/yeSOsceeH71JdF/M8uuyMI/Us+vrBA3Pfl3ufZHERu7aHPSg7yJiV+pXFg/uRbkFYJ9hDu3eAK4qsqmxNQcIiBPGFkrZzeUJYmnCnWNBnjhWr3DNu8aQpEU77nly9iDwrWDvpskckAxxeiNNqGn5dMECMZ2a+0Y3QtUJVXWdh8b/GxvReVqjKwUpZDbwac+CWjKx5hAF7AytBY/Nt4vwEvg2auSGMifNN23TmlcjLbltHBSZ2yyVtBAVpm+77jCCk/CDUDmjy4y5WNEdLwrnEfF1Ytj/kuMq7RzM+qGTIUizTPIypEqhp6IuopO0SBPnsejBw9s/r1TJ1ArNs0dn++lio4YtuN92hWSMVwC5fPCNZiNZsDp1O7HTf/jyPbPJx75UfQ3DrP4c4Ne1ppxbnfc7QGK1L+5zRwtrPRk89UrnOczZ9cUluR2NeUxmNggqq7XNGpJNbfUoA0lzY6DJg9yE3XcZ1vUM8kGGLC0b8bxP1yP2pvMUQXEb5H9pw6jt3QEGsOExZf2v4/nJzBBZvkxKk0FFtIT3VKI0NGvhQp3iw30xcwgOaw7R1vj18XRBniue3/3Rep0ko+as80QuRgokjxIESFuQlN8PvVlSzaeUM29daVMX4HT6LhHKvsGzhEMw4PyeBQk12hXJ70lOvRjU+Czi28Tljbln5rJ8zEilt2l4gqAbfMGvgD3otqFH1PDxk1WFyl0UG6XiLYTjMsKkhZxKUGGWGZNxUw8TeOC8kz3XsSafVDKhpBbZoTGiKVuZ4bpS2hH4fp/Jux5a2y/RWLMTUpg4B7iPwffIavdY2gXQaKCgsVQ1qW58Jtt0YEwiZ9Bs462inlaZu20dDFr8+m4lZd9rH0+b/QKz6qavkrVtfRsnvkHreFTn3BIFf4Uf1RZ7RthMKKxvcd7jMRx7xpaY4kzS+tpiR1smh1Oih7toODSsGQGT+2keS5qplQ/YG5r1pUdJRRbRtJqBt1GcCBLy0kL9BOuijPjqkg+5lRIl3pUVQmlMex9I+DSbMFo3EnFWe1r4F2NPNZg4L1DHQWFeX6/76vlfbnEHg16hl7Op8HdoMRLFuTkGy9Ikh3AUBTBgmJzOlGXE0fzB0m/v0E3T9KDBG8T9fwhFgePWMhFdnjKpqYJfwxcHJOdy1cHvOFtZIrO6EtRJlM6Bsgqd2pD9kf6qcWUuu25So/5asT/fLZXOKds8swIZvl+2DSXBkmaPxbTw0D6lsOcfW6pnRsxZ8R252rzdc4OkIR5JxZH66KgIQyWYVRm2gItBXBNwl/VlpfLcCgMYBZGymQqXtDLI+yxkvasPWbti28ERcQixt6dhz6BRTU5QJrNWD9Omj0Nv5tGhliGOAOFv+EAF9mZyNvqnbRYKLJvdq1lztI1mt2kNXtV8Ru8kbKKtTJ4FBcc8LwR4VOcXe0ggyjSNbKMjx1treguP+W26XcwIenUyCjrkRAhLJz3bt3tudz94jxiNHrkit1LtpnlQiJFoFtleDLEQ6EtQaRT1AmYMwpUc0E48NRrap605WkENR/Sxqq6BXGL4g9h8xJJB3tC6SEXe2k6s8WHyjoLghN/nktkCm835Ejo2x8OSfTF0CBcoyZ1rqsTuBMoAA8vKsoDrWsRFmcLCP7cJsruS5r7L83UmHXOww9o0qp1iYlJXustFiMBY4g+KJmopvbS/reHHNatGVNat2vcKyuuu4Mm6uHm0KXGXN/dnRp3pLJdlcRqGeko4Psf2eo6tpxLlfr1Kaf1GHipMTd9H47wsb0SXw1fvgPeWBdnXzq8TOp9QY1CzCXIwbM5pxI4MakmYrIbO4V2yHc/2+nySjWaJuam0mzh/xsojOL+yHQ/TVKkjYxcy/QaT8BrpzW4XPhjZq8LKObtTh6TpQ1TwyRXaJE4P9RAGr424E5kpR6NjAfhoWbmWlAK7v/oxUprOZSPHCmxxEzHF8a3jFMxL6H21IYXYUlu3AfgStwjRcqK7uC6Om6TJfQoPtpfiWEcF9K4eQRcKH+plzhDDjl7CXO9/yGZhmiwmCzJiepYU3SGGMUEJWDnlEUxExJJaH13xxtT1DahUKeiAeJZUGpZpQJp6pUCwOF96LRq8DKgvQOhcNvmoVAREuIk7wpgk+cQsSHCTJ8PjinRqBgBLRR3+hqZMslJ+h7CNOvKFHNk6jM+QGc/iUVMN+/+XYtdEfwWdEZ8QY2wFL68Cavkkpnqf/2x+ReN7YP2EEgY0KUOdlEUvNaGuxQnTs8Y6nDUlCRqhbpcRYn7af1kWs3JXt0QeOOd71xcO+iDY0WbiM7rayb1/kgu5crUP0/sZ/p8t2ml9EkWdnxSwKfFZTD9Lx+TnMGM7/bKZgq4Ye1V1xFA0de0FdO7OuOR+EGO7u8cPoSL3OD4egvnCZWynVMZCpS9qy7jRg8PENlbze3knqMx8fwBGYJXnT0oTEP4Crbpl6C+35sqWusJXwBmbRRjRtgAtn+OgXXQ7U0ac+ZcQPkLppxp07qzzlF0iLbV+G2jVv5qRlHQLj/Y4imJfdKN4+Bo6eREuN2F0SjQ8yZgbMNFxdlfE3dXxwChUxFUgpQtZ7T7hRmLeZJ2M3izB4TrqTDwAePuTfFVQ6cIndbuosH0Mx//7Lz09unhEOkR8YSQYxtgxAMz3GjIBM6oiJQZDGJ3H2bOy7/ywq6Tjbq7mioSelyVA2YiL1WS9BNbvFexQppmA4drfplWEluHxMUBPJT5+iBGSdB3ivXldEsJ96KLkDFDGfstW9YN7FSm+0EOMa6ifBlsMNPB2X0HLIkAXjHu5aJcsfYh9GZANYB4vGD2RKdKuzct/2s6aGwsuCIRARZQcsSYR+ssJ7LriLgFTlxCd/GkHrIf65lZjQarbfdc7EHKE8rBj0+mGMHEi/7LyTIIGJi3SXPGpJ9afy92+Xn+QE6+fX/cvSCYkaL847eUW0xqpdfMWUIMpMzcfotWOegXBSvaDw4QglQct2BA+mjb29OnUhOGst64+KOBZC7o7TfvOXe1phdLo6LzxLg5yIQOGFfJpkaqhW2O1GkWliiipt/n3Q1bUF/cKXtnBFw/GFugx57DGErI1HzwEN+W0u3LIzslh795NlEzEGyAizrruIJ90D5BUBA288YiGwXq83XFEmJKQC/GUhbFm9V3G5c/eDduktwOWwIBY/dhVeAgu7VICjBIWwxUIp3DWYpaDvej0x+s/J00UPGNG2W3+tbz4I6CuV0Fby6qNbQHOJJNloDXn6r/ATAS66JW6IwJ00RYywdc5QbKWX0IvA+z+MDoov6dKRkDb5Sn2AlU/tV0NYyu5ImkQmb4y9nSZQBBfgW+2rO+Bfs6fZfGq7WNPrKzYaudUsL5xW+IrTel92yixZ4U5yWHLMZos+jnBK2GP28dN+F2QmJFtOaovDUrMd7Xig2abK3o9jvg4Gfy/lXQfDps2/jTufQYpvYXdrPBft7v1lPBgThVaERi09cUDIaYFrtnVehjoaLhG3QukF3OGaysaiK7hdLm9DIObfTSI2OssraVtMA7KXkCJ/LLQ9V/fPbFKT38Su7ZM3TRjnaVpFoE6EG5sAKMymsKVwhUUP2GKFUDJRHvzL1htoUJRXqOsA5RrJCjB22ttlUn5DloPx39DlQkl2yIhdGhCdtz2pI2irNkyUXaq9DzTppeLCTS9C9SH2WYZOCK2rekfXhDhKbFQXZUesqVWAGA1TPVTJSpUGxa1cWniJgJej4xi83SPA1aA8iqNyyVONz1njDGNO6U5vzasb9SY+CXIc965q/4HI1Nrb1PcUxlQBK6x6a7DU3qTwBvyCY2MuvwPjNhDsDZhey0ZQ0MlmAP7KeBafa9lA4J3Qv0Fc+ocPZ8fMEiAbWOal20+f8ohQR2CFyhT5ulxQo/oqx+IktwL3vyXgspbhboVxVLqqTVgJ7iaUgsOFClgy9Bk7evEZtUP+eMjXAnpMzfz5nhrcnh08VMlYkM7r9OD/2oZC56YBSKsWZQ+y9oizpclSYOwExyA7pWZTKTy0ZkpnIqC76ITMD8mUJ2F4Kv6r5ebjrKrS9YcBDTBPaT7nMxCsI9h9WaRhqo8SGRbbc+wMnXjQe04QmjhUufaO1YPzrxPaOjnQyDWqRF9lBX8WtUi2CNwTfGuMQoUrPW1Ih+Assw1nuvbRzJig2il6sh42x+oXCe+LAM5dEQZQ7zaPEOOhSC+oEkwnXv5hTVLveKWG1ewniyCUy8RrZ3OXXk3NowazmU35qaFaCofTIy999RDluSs86u9UvzjyHAkD99wGH79g0K75/w36+2tjBrC7jYQUNl+ljTHCFg7gPWh1m+fqYbp11qJeXW/d8DfpXK6i7nCS7OLYbFAlMpfMcQIgNdBG+2HqkifBjWsXqvUPf8z30mVZ5ecFC4p/r8l2srEeNMlSImSwOH4AAbJWZn8kbn1QXvn+JtP59jaQ/d3he5+zk0uItDWbzaGZIFL46ewqTIHETIDhZSBnJEVh74T4tJ86MsxUFlzm9sLr9AJTn+iVWya8KgDRGG+xPYMN/P/gTpdPiFcgXwBy076ipG6ETssxPyTu1TJnSGb6jgZB8Rah8XhWZ09+QglRasSVumeulh5Pil86bnXOKVobWtXLJAttEOIl7KgPZW0lr/XIUZCl7qOlsl/zIB6pCEZv3waUCh3vMhQu8h+oLeZKU1Oen8wTHTDG1wKhH2fE9XQ7fWPQIT5m3BEpse35WcCuAR2FkVRcM5rPLDXyVUpLXjTI59knbiq8Cgc6E8pVXmHA4/6wNQxTXuHDabzPHYa7x4c+rlvmffqQ2fhXR5OR9UB7Kk8x0BYoia6aCoEDZjhl/fmqiT/5a6T5KcbdDVYjqXtiz4wFziSRmXwTdBlFhnq1VhcK12XJP90j+onU5nDoUfgXgFYYkmON3yqZ+PutjAoskEyRXNxnJJyFfTKfPLGufq49UFPe6/IHrecENYOo2zPhdV4DajFX2lbGFbg4SVBZ6fX5E9udlSzcE3HEueb37bZCTVsfkIF0Bw0sOqSI9lnehMWmtpinr0sBsm84Z+6QUhZf3tDRgYkSNtgoysqfKuZjNEtEL/lYn/85/1ugtyTTt9AqlW4T6ot3UTm1CPRm4gpjAW/qSrLKecetdiUbj67aJE7LL+y/3sK6c89NPkWgjYTVTG9zktpsm5x6vgR4E71tgxCLNmGqKy5rD8vdW/aReb1gmd/05wFa3C1zpF75BMddahla/4yUhtJ8Lwvk77SFutMVF9aGc7TU7bHTCYLaMeP60Q8Vm8G3zXyFeOTei5YuG6MOweApmWfT4mPTEpS1CSIFR+Sc8FTQC6sl5N++891Cw/XlxUKrA22H8/EyuWRHxw8jye81Sc7KAkCqMWnOJqyzlwh0kaaGQB+pckzlEx1vDMCHTeceIZZsFJQBJMG5ilpHOnMHCiQgtYehzW2S3LMppNMIc3pa0I5ZJ2RgGNTwH4bGb8a+Vy/AC9nvMpnNC75x0cpDI4r991JNaJzeTKRcX2fevVkYTE1yIMd2G7kCp64RLJPN9yoaNMLHYhhnD0rchoSdg+YrrA7XIqDCbaTxZ96XzGsLxLvp8ybNlnTAwCNa+Yj0+r456KKpaWPaZmO3n6jLcs5cffnAex2usOuIrbRX03hlkKEcEBmH+a7U5bcO0v/LPA1ALfQulI2Tx90dYVhzOEU3Aw1jatN/Z7eFPAg8qCWbDdfj+kXWgMzyLubZYB6Ngv05yQcrstDd5p9JQBsfiWb6r81NIPqjRwbmvSFqgJm+7VWS6HK97QsjAPVlYLc3vlawSJ9s+XrvjnSzUXxf4NUZqPR2UK89vHTPlapQbuwTppFaiFQZV0/5QDQHhD9dBTabbjLwZe0FHe/76dO3H+nn3JzW2I9QalsHozJb1AxyG6rrt9XqXvGonKF8ncK9FkV3p4BnU61RGd6T4kxyXUh6ugccxbR86ly6ZOnFFXujAHCzlR2lc77cmxXDeOik9fjHR/stPuWfbNoZRkNTCI5YFFA391Cxj7WtSYi6Xyvk6FiVEzN0Owc/Y/FY+dayMTwuZX1KDptxW6oAzwXFXWb8LMEHNzPSdpgDAgeeksl7g0d+/tKI3eIPmv1OK93yWlYU4Pbjkwzpgy3ULmure19VWxzMmjaPCLfUr+xPFBlYCS7bIi7BSymBQ4cSh/trX+H4naYUYSFXdTRnkKaN99XPm8BSgiZn1HkiTX+Gz2ceMY3G7m+AyRQRDbUL+GZfHwwtDK/ZMygPkwt1BEjk99B51/rNcTf6qsQq8Q8hdEe+BwrcJjedAKXGvvaz2nIEjEBf3LLCmOLUzR9n4E/euT2Ap+VsfJC2PekxNf+63Ud00tQQAM2fqPOdz04+PEYk6e9i2KRy/XdUBZ3ZoPmhSMHD2g6NfXZ0EnkTaK6ug5n7DCk+7Z8gZgTq0plnzPU1ZkaIe7KGRRKX/Nsxn8nSM8Bh7K83ZNBfxY5FZ0/y+02B14K16rkjauG13NqpoiTOHreGRjIaPXDwvvx9X2qeynv5UZGhQnO6GAxsLObeRlwWt7Mm/rbtXMQa1oAOnQsRAy0Is3K+opmFRsZaza2Hlq0g2Ye7meR2q9Oj0bL8QfX+EAEEeUlMCL4S4FuvsVogigE8fy3GmbtcUisahvDrE0RhSfwmedsVPxZQnYhAW55UyDQtI705nK9WjT+09fdNNqGNW2+AP4PCLs9R2VrBkfxAJrRqWIeCdf9WKzCHYp2uEhiDkfw7yBdTuGSD5C+XjVgV/pP5nl5DLnPZPaZRaKDG89KbRB8nmROZJr4GAVp2ZVlYpjBg9fo/7Dyvs+bwPWiqUA5ywO6CnKda+gHfHTActlS6MHJojFV0A2mf+KS24KXS4IcaCfpNModJAapaRh08iyVCAfD+0P021zejkqJunXEmH5/yj/DbA6qsJZNHJcC55IZLnqBpj98XUA96NbBoXCzv7xetkvdGommuXZq9Toy7vS6JzBVoYQvyIYg7p0wcx/Pw9Seu2grIeQG88GfOo+RRg4nqNlzUKuuFxTaIx04Xw5+01xi+fpgx4Gy/j9Xcv0PbmOlBEP34hhyh5aUfwD3j7q5xxG8xcK6YcXTFGQmEjMu4e48xfP+EcV8GU6bF7QuKXnQlMzxbjVqN8j7kJkhhJsEP5bBGGZLD9FG7nUrWGWekvWNk1fiE43K7prngBfIW51JTxliUHrgrlcXQQd6CwOAn2raW83UF3SQfmPEAP8seNyy02enOKjaCpywQ5o+rNPpDODtRuZd7L4uEVKb7dCLxLILij3uJDjGS3iT8Ghu0gzwkW5Am+P9p1ywsbakiopJM54PSesK085QhR3oNcjCJHCpGVWltnnVLbdwy0OupJ3AO5uKyhYWRLL03dmrWvBwjizaZkz+tk6YKjZWTYUc1mHP/fTSa0y1FsUiiCMmlCuuOSPtEsHJCkq8fvXztixFXq/CnFz/xhTscI3PcgKa31MRApdXjmywVdOIDPzeND6VnG39qcb7Qe9Q5lO5CT3mPLyakVHnOpHf+F/+E6n6YgxkVwYPVv6vzV2RlgjPdtpByazSuuGMIFLBVKIwXVcUMSwVOSZ5nMOmDAAQVt1CenMMbABK4fpPkCggMdbiMsdK83Hh6aILbfOHZXm+vlH8DFs1jp1sKXzr2ayJd7eT3qzTF2vJOgzEkrSOOZOGp/vCeuug+xtEfrqY31CVZv5bSBeuOedd0Z9I4ialCPvsohDR81mWhBA5dd+yW2Wq6+RoeUwjzZ48lYAsoSG/PuOqaAHboadDSIvkbVGuxGV7PKSYcaKiFIWQ1wks9F3HB267qkRyxvx5aKbSyn6J2AUtwFmmampNMrDLcwzeZQD9UrTBU/JgLQHYjZtfWf7GU+wh8J/kpYDTh+UQKkI9J7yWY+b0vcvMUx0Ym319I40YEz/ApnAt6KRuYtpQCuX/8S5zT1JgSTWJLJCseFxy0cbJcVm8GsQyqxH7O01EsMDpD/qsniRnuUpwy7+0EarDbl51QOouPMf9OD3bwKiC6wxkJd59HPT46NfuCCJtlvtjgSjXQ7T33+VHVz223LFJaCbMJWg/UV/xg5FOWi/ie+j1a6XaYvb1zel4ArdaOVKlr+qeacdyMg0UxfE5v/FzjFi5dgiXu4UfdeZlhrtV/H3o2OacZ0hyP/373kzFsLpIsRXGlj7oObybTWACxBKuX6fA+qIpddSQJlB9sN4HBEq1awqz3p1I1Is9W3p5Sg30zz9ek/olM5SidQ/PrwXQWq8ILDXafeUV/lX5gVJyVNza8lBe4o17iyr9A2wqmxx2KOmpmlD83/Qg+vnH626d4xYbNZI/Kp9Yb8IeLzR/BjFZ/jE7hQ2Cas8PDnQZ8uC5E8vNZ+zKhapfCIiRz34zlouNe50HgZ22QtlgxJ+KEmAYFEInat9CkILuf6E1GLzcOtnv43pGYbm2+NpJGcGtlJ4iRdwnxW3EWB0EvZUObUwTjKLUb5e7mB3Bg4hgyqHfXztMcx7Vn5Bd+xbIHzYMTq4puQBltU+0x0MHMRwfWQBY8RAjw4ydRnHPWZZCoYjQ6fFIfGeny7Xz55aXpgCzdi/4xAfaSMoO1PKUVfhVtwvsef++a0z3h76IaUHQq5hK+qwrYKOzQFCpcT/qLmiRs/U8xkYKgArHIGcE7yi+cnZMFQCWqntA2lMKcY9ESAxaHd585ucA4TDlUrAEk3AaL0/G7uelF9T2GaYZqtOd17zmD0BpZ5ttsqFKgk2C4XF6XoehDHZF22NaMdJHrbivAFq1DPNWWMCzVOhTdWUDWODxs8LKiZywoitDosTq1KZsZL8Dwnxlu1USQpWOVebtEaS+bvBGAx4784mQYN73k3nlCVcOl8v3MKiLvso+dN/Ip54C4UwLa15JddpGPWpMCl3XPcU/ELKron9molxkYvYx/mWxkMj3rwAkJ1npm+nQLxlUzan/IClgUC4txyevH9iw+TDuBgPjH0qZwr6zeXemde/EwEsvphqVrk45IW8eiSEzh2B+Tp+yUZa9XBp1cuFVa1GQ7r6IjsUEVjM9WAgcLMzRNmRYbiT6kHMxlVvjVLAgVT4/rejyRLuCzczFd+oMrkwYBsFmYnpSN3kETxgFP0os2wQjy+b4xNCeDeyeKG/JaTMwPu692K5kVvczFnSpARHr14cm57zz/2gX1DMr1dvFgK+QjcwY7oRJzRVUyY6TFy/KIxoIAIHBrcWNdPD64YU+NloNctKCdpZZLFJ8jtwOaGLDkuFwFccAJQVxcV6VAcE6Hb9VUdrRDkLFaL9dIzL2TcqMIv8HA0sIK5d+qJXo74ku+/z2DwummOh6ErTcNro6O8kR4Q060xzVCG5wLS+RJ1WvMwvwHzF/qqeASxx0h36Kh06wJBfBD7wCjxauoJOzyqqJ4gUP4vasva2XjLBrEFtnJO6/JjAHv4uJGhSZd+yTyrVweW2s0sNsuLRd8vmiMHkLqUGpTO4IFU1icQjp2IgyKQ08suC1TYIVlJ/PWPtsMi6NavwY0pUX2zqCv4RurxlK02UTb0nbzPh6EelmsXsk5pjDlRpTbrhc1+4+wgQLhKbGzeFvu+FYGIeRcSTLDUBghWDGrMq9huq4gxIsDBkaRA8BGBtNGNkgc2uxbZ0+dw8CwNo8CRxdFYJr21L7svOW+2TTztIkUSloBgpA9NBoLkeMVq2PztoGibi2Crleq0PZOlWUzIRPjDG119++U2C5s1hYc2n21WKQgIBKYD2mWuXdpjD1hucf2eyydioI3dPUlH3Ck2/OHYaheA/J3rQIkhnmLJAs2YYH60LKeQyoVeLKBz4GsNjMzRc6NQhmpHXju8w/EhTWqiAx7junWQAiEtriSZTt3tN86FHqomhjSM1IsZL+FNotaBLnB/ALYWlRxogVtCWPRwDP8vcocUEZe5FpT7atVVhtWtU+9R7GuwFjQSoofSMl6yyDbGddDPAsBTDIon63PG0+DzWv7wABOr9cRMDsPeFCNF6D2bP8q1MMfOeEWGr37QwAqckFLyZhTyzjbpY6mNmwWThkwlR8KLybaIN1pnl3z1HkO9xOKVM6EYoiUX/KG2VBY0qMVDIc7Ibb2sCUNeIwvWmtFGwj66i1aD00g4/35ltpzwcMCgLZyjPSx1wsGY38/sCLd77EAssZv3nMf7+lgnLq9V1XayztVVeY8kCPsdoI79JM/yzrfTM7euujkcq9+9hWO36LgDBliFlBvQ/66gjHv4DK5IejPBiX8Mm3eWBNL09UUL74VunlFBOKkxhV3Wvr3BvBaiGHOvFkTyaDrIPN6wRbBvz1OTUP2gpUnm6sI/XZKgJLv/q2bN6aRlOSz/+Ol1qqM8mjVo2tFXjvFETdY8RN17G+2vcRUUvE6OBWigZmwRKvFI6udWm90MnQTx5F6LUb3kCh6qoarZbhsRrGaX/cfuippGXPUDvtlf5NTLlxIqFccr8YWTtzd2E6K9YE/61jJXZjLjf1/4ipr1ZODqWjwxdd9vLfYzvT+RCgLwnnBZxOm6V7Gb5N/5/zmQAyvlu9MslwAV5oaNLerlr8JrgiyuXdlPsOp/CQ2G+uwVLsVPDftGfU6WAAM+rBdp/kAk3EvLdwkMt57sdHV7cf0Z/jh67k1HLbSadyj6Lj/Kp+XKhhvMttFoaInSlTmnmIDRRQgroPObEHMhJ6ys171p0D/L+8jHzu0OZnE9pP+Yz/vXIvXZy2smTfEHl/7OS15pJz0fNGfN53D6p7IIVz/XeJlmfHErIjr/DTXkzd9VFwIg5bZ40Y+mZJiGs4VDW2ZOP+83uTBiUU3MgZaRaqtqMdH+9HMAQIl4KEuDL0q18JlQG03zSehMCgKSB7ozwDqoqDVK5hYhhdgveNob6eLp5aqxLaZPdWHYL5sjsG3V5x4WdRMP8cZPcXJ43ffR2K4VRte9k1jBiEKW/7N6d1NmS0gwL5iFKk+zn78CE+jJJWKBp/XJCLQtYDVEalTW3YXNUUmZ35hEPDecimjrrRG6+/kcG2K98n6UCp1xRMokJ2fmNFS7jw3FcxR6Hj3eCb3gvbWoXPy57XhLJ/JtBW4o62xP7OCU8mwcDHdFAy5JdJfU+jAfyAJrfBZusbSKGNiK5QNIdI0RrBk/DuRiR2dzVv+WSQqccDC1tlf+xF7giWjMZCfLNmvwZ/iQsf++FR0H7d46NAL8SwpiqXcYlWk+U98G6IAJI+L/QaKLjmcWoZHr/+1L2WyIPRNaWPM9EKKySF7++oOdF3TabMvgrRnG7Xj/TKmZsJVi92NFq9S54RtQTUEPx6qjnMEIWVWVbLXNm76ZzansDFPMOmuI/V74SuhYSr4WnTXTbY9jJCEkRfqSkeMxt9+iiQbp/pnuNV48QAbYnkYTgTfazCbf1v2rj1sXFJTObxeTSPjfAzz/+ejtYIYmBY6Oo1t65G3q0xxHz+k8ewmIEkFSlw9dzeM/UH837YcoDRegZovnY3Ef8x4+OeIAhMao9+D+e/UG9+3lPMbL7xTrTDOyqnOizyBw3fgSNRwyYUfNR7Hvv5WKdPlnGW6IEBZCTWtwZegc29inVaGZtqHpSdM8NgCJKiOuk8uHypUButsKyGX57CT40HjcgiLlbY7/c+LrqjKXKyNydaxVoHC0+8hqlF7MaVsq2Lm9pvCO4SVbc1DvHaT/xv2FwDMmlBeXB42K0n1J0IuCV8wA/tlcW52lqKMDTETl5qCqeM98EZfQGm5efJP3f4KKDCmWEP6FpkJ3AqZ/7buabIxx3GmxmZctQDh39wD/Bb5jeD8QBshWWV2bxqMn0+QIvJxcpN2b1lN11wPcXphLuP8TirCL7jscJqbTgVCNKCAoP2SyEjz+s9MNs+uKy9EVGiPgNDHgxY8ZQE/F3OozJfcBp0Y7H22vvAYiScERDxWZFikSbMNXDi4lt8ZTECm3+ndAJOV0sG+9t/BMEq8i0X4GB2GuruJXD2oZE18Au02fopLKoC8rKeCVE9rZ5B9fbEK1321yw1GOOV3AMj2WUmjkuTuud/YNUO/Z++KkD3Jw0LlfrHywHPljSOBbOswVrwhkV4XlMC2AKK0OLMqngKswK1QkBC9KD4QM3iLwiSS2pFgtprGhgOfy/39dfvRYjA/XfHv4KlfSOrjupuHwKvIOm759M+HeytSB2rIHSyOxq+yTTMUcFdKldKzc23eEkzdgHiaLWsFEMxf812KnywGfvvhtkq10Ro0MqXvLO8bFQZi69tOFqdMDUL7dPp8hDV9ZEe9aPTTMuBao2F4tRdnrN6eFFtwB3zdzVXxwRebmK6smYBk5H3edm2zPh1Q+zPUSyttU4283JUlYIzoj3HLG7IL4nz+W7HYx/TDkQJ3/Oi9NXW26w7Ga3swPaS4Vmwyc01eudMcokYkmCOm6/AlIOfC0WKUIfNjdds1fpjx0ETE9zSZgT2ZOgYF5BoFNQ8bbQ8fjCxb+9zeMTySEAHSEjAbldXGLYpH+odizJwbUkCcZbWjd2lEwetY6KW5rmWrG4hc5x5igfNmGy5EO3TxgBRZ87bNl9uHFHmruTMMrHuagqawBE5+dbqUA0ejCU5eaCNXtL9tvsiO8hin67t8xgmB1YKPuo/zze9tQRUd75Vt3zq+nwDGGuNeNB08e+mKfRpVLe2pRKtc58/00GO2zv7HzOcdEMSYdxB1r9B0qAjMOe1GXTZewqBDdoIrvzdeMbdIM2wHLGBbUqVY+vQ+tW/jysxEpt5m7QkKsIW6b0zBPrKAZLvT4TnPfFva659YGUGgfqY6hkZ7L1eDT+05xJKHGefMZhmtdGRDm76ayOaAqOFCe8871BT4cwP2H0ZpGCmwprd95d+1VCblcaDrdTLPoVqqxz8EnJ0kTKxTQZK7AH7qaZl89pYcUh67FZatoAD1hGumtub9yhoq/8KUPxbvWaDKLQETJWrEk6bdk0PC8KbEkE+3kX2X5RQW/iK5TZDwAxOnoDdp8jOvV/8JoQeS7DHKBM5e+MEvYU0M+/AC8n/1SoKNZ6cUaDWVhfKYLGVgikAmduuaSkjeqRR+Z6Z7qMo5pddf9T/FwzdUU8mMSWcPoKnUzLARNi1eb/MQaym9iGCy9YCp25eE5alLyuVbJ6fVYMGyz7hoFndjrG+4GY/57TWQJbRM9zFHXi/GreVMKe8Jqe8TVBrN52gofFU0Oc965/vcEhx4LOfomSptab0tFkQS+Wu4kxTe0nloExnSrFeQBFKdHt6iJsjuoHPL7+JGOkB71O47mzs2ga+67lw8DjcHkCsZIHU+PZODllKd1GVYOXFOXtUSrP+YyfZXkywsyH3DER3NyoBDREFI7VINRNyUG6Ep+JNQ9CaGbmRmFE+VQcsgkGyvzyW0JuU+VtfsK1mmT4VEUyGtcNHZ/Y/Qk6gwaE4KzH1te2z4BQw0mHXB3+KSgYdoSZr5EYujp3J77T6w+VVGimoY8YWz2jMUBG7zr4D68frw6XtWxjzGqbkQzQuVohK2/3AupiYGVkoVjwWfeQrKZi2ckVi17G4acWYMXuhtljb8hi6S3VWxCTaCxOsJi8CO8dOy8FcLbROsI37xyMkXMtuQDA6JOMBg+TgOKSSO4/YLwD7tWCY3qWETe0E5m3N7PY/XacSd4SNT0ir6boOkIgUKZdMmE6OuFKuRXWfqgYiogn9GzKcmBNhtUczcsQglY1qbpch2XHLonhJxu7Ptvz3Pnq29ns0rXfW++upsyu2hEORTAFjUQ5xk6ihevlW5ma7Vf8qlW6wLv6ZlX3GoZPbiozP8ehhh8BIJz+Asd3EORaeoRSlxpUGJjYi8TTrBgdp8faAHezv4OwVM8Y/tfEbVdhevy7Cknac3O40j+l5BiWSSkyx+aXWadyjNcOylIvymqyteQcsaJOemPPEzG2ssss7b2S/fcmkEPYZVm4YgcIJ5IoF4Rh0sb5ON/xSVN8GUtubtBNT64ygVp5b5icaPZfnMxdNwxLNb9cFuybNUlzMv5ByvgvV20oO1cvNnRaEQmNsQAh2HR6Xc/WSmvW9L873C5uOWrJlTqAaxegPb+ZKNrMxHl4Ok2TZ3Lvc9KyjzbEaWP1dTjhU9PjJtut94NNYnqP2AcXQFKwqxG0w4YDiQZIbV1PRPuTazrLOYI976QlbD0QIMdd57kG5U+TeMm8l0fccNzBYaDWhG2IsVu3q6jwIUtmYluQu/gP7RfR/jgxPhYFbRfCqDjvWEu2qP4SKul9dr49uGWZkZWQaYdz5AGXDFC8JFedwWUyzZkW25DOVKZjCUzd48JlNF8p+jbNxgSeU0PY6CVwesx3a0yBpI8dLDXS4Qb4ppFJUYKPvuXqpQAvHWoJcC+tNEDajP9FMUcaHuwgWzQ9LHQD+uG6uDS5OWntiT9/USJqBBshkmVxBRJYl9dJc0ry6e9v5P+cTBwtr7+2Ii39NMXDgxN+ie2ZJRB4dUY3aBG2F7MqVS5EL8rc5uObgzMeKAlSkgsjCEL5vUW9cCtmTD0M4SQr6ljhA4EeOOi1FWYYWncJevdHG/F7p4FWP8Ygn9pK/KsmmUhjqye93BjxBBH5rkqv5utNg+1LHy53jmqLCOsVEHNmUIZkVOcu/ZHOE3bpGfwT1K0uFGIgrThe/3rHgyumTwrv1187YZrhuhW3AV8aTK+L6D9KnOAlaTpVyd7pRX55GIgGgFDZbNlKybvnNMOeqe3rJCNtKpFqCzyFhatqbQuK6+fbSto4JXdb3snkOSCZXtd58Rg1rfniJpSgDBa6CKiNIAM2dpRrhaDHeunkgcCdpsILJ6yWV2G+f/lHXbGoZnMP2CuLTZreQTafC5W3BeFIGTGShN/GY5tkeUMl2NekXNw9yBSiJ1CbcTRmGjdQEdDzBYWkgBPpkZ6IZTBmlizY8iRsndTO5juM+mgcnRPnzJfqEaITnhycgcDhXYINgklLR19/qcdhTISKay8i63CMHAcQ3wxZ0fejWdZknlJamw5nAPU5CQN8MCSNKhGSDgNDyiz+bZTNmRwAyhfSXsQ5UBKSnZY92X6aT5caox8g5DCOppUXAQRAYi/PpMA45fAg7LpGF61CAPnAtHlunYTSZby/wICu/3HuIGcvRdWxgGoB3mmxJsNfK95801lrbaTJiKkN4tstP5xaJpy+BWnRkvSve+07wVt1Dye2yoWj3IbGJlpuHxJroNzHRK41Afjw1fatPnciQXgFiMZGXerIaQkKp1u0yDi8IR4ddy7B6+RA7qk2kGbbFG3op1rysp2ohgZzpA1eeR4nKaAuqbLcGFGVMfPkCWRJtkaz4P46yHzXUtp9R2q+38B5gIdj0FV/I7h6M/PxXJSWSuuC+Xp5SHXqkwXwa2iNWgZtc3isl5gR27zb3II+VRIn6JBXcFYeVncp6GA8TO0eLWJuLH63JrZmtRCP3foQQhJZavOcNeoZgusJ4E9ZDKqy5EdIPgL7BaelXWCcVqPesG4VRsWkrt5vFzuBDzeqE1CwWvZE8hzl5SVSmCdRGMxXdpC1UR6bB5aqCHAgloJJshQlh7lEwRpfbNAIQ/JZ4vCQLoee2ZwAdehI+O7hye/eyqV/zv4C2mkL2QOsHWzOiTFSk+djMicowraG7tLNgeWPsKLzafIgVpnxfu9fIDx2uHSd9pkn7WE7jHlzvsXAT46R95ljMe8kRVM7Ej6M7uTXGUZda/FGfvXTjASP0Ul6vM52JMWS5fz1/kxryj3E7vUdmiSI93Yeyzzn5uWse2OzLujljwB/2bTpCsWxFOebMyin1IDO8zCRH5w7c+9Z5TEEbNImY0rp0IgmVxTUCSpr60C/wyhERFWOtGWt1vHDunrsVtxP1GmRC7YPKwHy0tdVFY2Bk7L8XWth4j/6uDHnAtIhW+hayqleJGF0bZm+Zw082cPhR3wk/F2Yqoe5kP1bqTkvw6W0vzOF247+oVcU+bOmV4Fkd1lnvqGJ5DgUMiGL7r4N7DcXAhM9cjxzmUlpCi0u6UCZlbkUXgpTIIl4bDHuq5YaZ42Sq2cyqaZp5DAdS4iGh5ZtqA21ymZjmToxDkLLyBNV2S34gYgoMlnDJyq2FZwXMV2dotW6iayXyE+F/aZsWhhJIQfyfg5mekzCzRU+fW3Sc6Wc/QwC+P4CLa0zpgLcAskMvYM8V6be61ToQPAbdvY0tbdC2d8+gs6l0lcLUuvXFpidz2N77G/90d+KHdSLNU9knvQFS0u2JUlv9ZZixoCrb6NLBbXuqEbJwAzsgx0fujaueB1DqzsksTar1GRVrQgpN4b7tAP+orxvI1mCdpMQcEsh95P1vqzu9bBYEm5zQK4wp8Ygc8w046jhbbZ15sQuqb/kgbXLYglR2f8aOepu45kF33FWOXCel8AETfUp2YX4Qw+LULVshJWqRFAzK+FiHFQ9bwTHVomSeW+SKmeh9jVlHSg1Q2e0m22aQcExGizGbbJci8CIxNucSFD12j8a3N54QVZiuO57tbJ87BB2X83RsG87GY/RGj0VHuQzEoKSKhqfyCQLLo1JtxyiYQ1dslx82XDBwUhY/TIJSspY0lcPCXElCZX0c17tbWUFCm6veS+xufSJjkkS3iNgAOyblXedliAmNPhNVpi76rVIPSodwatg9dmTtbHp6C6ubo8GFwvU91p2ccFKqSAdE0Yf9E6I0Mt9KYIF1V66WyFQtq1naeKgtw7VrULwbSBjKvis9x+DhFM+LFV2afzq4mYcen790X2iZ68P19BbEVaTcnoXKYT/bRsFRYYTigEiYOj+faMfSEo9fqoJe7ly08L9G620hQKL6EQB94wt472u+f9kr7rakYV8j4ZoFdS+/DOB1ew3d4aLJEbd6jR8soXJ7TYVqaJYBJy5CPycQUBVcdH0cKvFspp5DwL1NGrR++Hz1H6S3nU3Ude1amEt2MKoxKPKmKydZE2CbQX8SElEUlmu8vCAnGF7hg2P4N6JehLCaIKIigNiUWCHzt5iYMR5sKu3/RV7XyFN77H7y/LJHPs3HfJ0Yw7SAOn5YJCQZ6f9Wih050B6TRBlywpIbgI6qycwyALmALUARqu5pPgwibOc4og81Yf3Hcez7UlHMU+/KfmrHyRm3QBlor2CzQSIwa0bi8FksAV9v4dhdsN71iteDkl46FtxHgQaoYe3Og0SqNRbIqQ7yvK08dpQ7pqmEA7cTwiu+l31nkwC6DKjn0kb3A7otxvSlKBuaM5g6YyV2/c3JgmYOqcsbJkGwi/22NIKRIuUv8H1XRA0QCyf5LVDGsEAssy4hW8SclNWFfkhpXmt+3xCdYdupo7FkajWpJ6ASKRPIy6w+9ptvYuT+LIHuSpzbtFEMm7txRO5ZYwvE9K159bZsLXVJUT4FPf66FOfsHAPwalQiZg8KxOEBPim6nIgtV0wsgMoSJ8I6+5BLeCRI6O774CnSCnO9ktRtLqulBxduY4mEsnCDDSKK7m6mDs2itrg4ROhrqChv55ETLgieYvK/q7zAGB2t4lCmqzAdki95DXH3zyZQMycTsTg/XJB/EEYdYIbAX6gJ1dmqAzSo+m2K3dMEv4F062OPo1Eg+0Ml0/U7/qLRybwOkvK8U4pth6YDWz/oJZxgzi6CFYQWr5b++uWQgI+irigD20pQpnMiViePFV1Eye5ZnZRcSD6Q8bohg6cnMbEc4zAhweHgYc7sUnTjseZbSlY9yYB9VSIbkWhmuRv2MSyejjOIAGTNlwlPwqKqKMrAio++Zc+XPWo2mVyHCjZ8OZQigb0dfKCjERFWJpqxuLwcaeMSLTgbdCQuQGogVszOddIs2X5/xZE1P0QooqD8WlVMbnKHGwztpsJ/tcjRFzOSvUMboLWP70WeRKCC5pbAncq0f0G2un/LIbTeZ5SKychHGj7fFw9pJyjhAX6Jojw79FO05zKbt2yBnhqqS2RVeiap8nVLJ8tOTzgMj9pToTbj4hmZJnLcW2KGL4Pv66ogNnxqIgOoJDli+t82E4NlJlNj7mRqysmk7yBJWYR7qtVuxxlo8qfoLfokpm1j5qkJhtFDU/lPbBxsl327xzU5V/UDuOUOlvFQHsvN+A/N1DoFBc6q1kPRlS2BwYOM5+X+9evk2VzEvqgmNhOx2zz2MAfXD+LraME2GCxjY0e7nu+IHZu025MbtG+6jYKu6iU2tPjVIXJtsYv5WJAQTAMSe/QxgSzJglC3leXJR2zm0nemW2WWZO6iM4eRPk1/PDhr8nJiWomz7zEHc9JI0k52z/EMGWdbH/sBd92aryHA8V5aAuJaKE4ImydU9GnQViW78XrMJNPR92WaRyJnk1ScKY6iBQqHMk7fJkJKAz2d/OTBqkbyo4p/yRglYHp2MFqvXydMqHOXJV2s/XKw3IbvKWcLj/q7FLxlgrBnF34jhcZs7ojahWd3gIXnEgOIlX7RfZR8HvZryCiCeTTSWjUVPn+Pgyb4YW8T7LPLZQJxdo8TA9DSBVcYisI9ZjRFjufLK1nWt9fWgZ1MveKLfTIUu3rwascZxZCcpkZYaomOIy1YrPavQtJ/gRERF4jt6HMquPr4o1q1dHgV8fx4AY3j/jxA0yW/GKLBY0wYZFK/1fCF3a3YyHy5ukOzHp5VG08o5tno91f3ef84pY60U7mnNq1caSUmx+Z3VWITV3WksV8M33QmGDp43PJeqj5V4J1JKvJ4tYbCEyl/QgGV1xhCECF0UFuO+PNT8tijxHidyhJrtXFviA5lhW2HXpfbuGK/7b1sFqSkhCwlXQPkZFvmsrqRmUBM+Tt1h5NbL3Bj4PYHRKFI4NZISxgHi17iVW/nXKAGJ3F9mlNUO7gqVqzGW8lyrqb6A7K9qd58wt+BRD93KSGct1g8WJAx2ltvv17shC7FyZTeFrIJ/gakrGR7o/zacoKJ1GK05MvY7XddvnGGwzHL2t05oI5nOreQ/oK6XetEaiaXlHpk/kiLimkpf9h2CaX5R9vLo82o8lN14nccCCnFfhrViNzH0SeNID1401ZjrPubjNhs8PLfld+WX1I2t9/NSFRjufEt5SkfP2h6NtnksxEIkCiDuj4puqb/MnUChQxzKRChkc/7T1qpTjp81LsdqdJRti424TYTNE2JIDNFwNJpUcnUDzKy/B1PardVCOmPgYCCcFZwwGylGWchJQLpGmhyFAMSJMUa2FFV5Ble6xC1Q0GVZlqjw1cAQ0UdAR83eniK1Fn8ffzgIlwrFT0Fpvb0hlDpKxxJ/v2rxwuu9OXVnWL4s5oNjaWvC2cGQsUJcXV6KUC32Lv/7w9ItW998wS3XX+gz85LghkZvfKO0Qymoy6In+GoMO9qqcCqgi8VhRjOtqgSMUxZIkIHyZGfpKcY8XyFb4uSOaexhbSmcGkCy+oNvJkf6YKi8LKQElhuxJl1sC1fO8AsPnN9E3nV1hARdu2SCLANpOij/1wzIPIrcvjFig4H2b+EAhnabvU2UVuhhmMSbeEzlYzhooTOSzFhMkgx4I/zuWW0Ward5qZti53E1NGC48xUdxlZcZIX+L+llIn3qt8+I3naJaAbB72PxHlOkENm6VGgb2H9uAM9RGb7sVSaJgvL8Jua6mp34OM1odOiYsSgUpWJtDRRN2IuRH407L6HYARmwViC9vs53tplx1Vi2hkx8OoO6ebz9JwW3T+88QyVAKY0xzDni9gnl0kLkyt3S51SKKpFoihpAgWBstdfKnzeb7RJra1LTCwz8hkCrq4FRgg9pioNmhoOa2R6Doku5idUPBb+DuqTWE/I7IMBYj6w88a6+JnB2ttYCfsjP/Dde83mmXD1sWTx6glU2uZGUQlfzwvpfXZufBwUaQfORttRRThHXNntdtyHinaIwgfizG88h8yMuqYCPDbmQjDpwpMtVtPXHs6k7418IHX1x8aHbHmsG5JK2bDHl0Sv+WJM6V8/Z+NgmdUN++ceNWjcZXBJGuqcO65U6uLCPofodEA66ph8EEbW0X1vuBL0ijjJcghzVxwrEuwB66Wa7fxJyrI1u5HSl25q9AXVbTsfaTo6gkCIb6ckVmFFDQLeX2XuP+cv0cY4S4HYRKFYiPQXUnGBj1eg4fRXkAYn9qMIm+17sxlAXmYcc1xnWqrwRdKsqtnIzPz71akUdWfmF3vWjsCgPUJB6hnyNci8XG/WmdGA+vQZecgO4dewvswL3MLp7WQ5OeHhpsvrhd6Zy2rBLNGMApo+6JqxZSVdivJmiMQ69dZwmZSoL8Pon8X9y4sWw0QcBCW641xdW89QZk/vdNyXA7TYYbUrx8IfiRZeku5+Z6gR+Oj5fSdjMS4+IX4Jm4ZDHRKNgwomrTKqg4IDPfeaiQafC8C0N2bD43FMCnUj+LEpUqsEjcMAtu1MWdfmd8prj1pJ5JQLbc90tRvuCQAQKxToLpUit4rT50qjE3sbRvI7/4S9uPx09N4SDtcUJ1FNCIuZE/llpybDYDbmst21zlBThBTkE7U+V7neky6p/28NcWxFCSvhMHXe/1dZ5I7lXuJvL3EObhlJ0+Yvb5C9QrE5LG+UfbXsQYEHwLvOviDtmnDJPWw2BT9XRIe37VlkpLpHNKNjQRq+ZDq6wPzYChsra0yju3cnkmh8gKoYDBMAUT5qvqyBV+ox+RznYjhpSJk3stm4p3bMb6jUEAMrFp2Yfpf64gguxzBfAU7O1gOh6SvaxZaUqotWQ45l+jZV2ezpHj5LxIxgYJMOsTUKtOWVjDMZEyWtKzQ6HfUQUbvIWvHBs+3nJD2Gmu4/6s8RaBgbAO1w3YAfhjycVhB+UxUdHkCHags67vmyHM7MOqnH0F/PMxhiWbExF3Vj/VVNYZDyED9BYRA7EclevZTaA595D2qcQnG4wIgumujpJeX0yE2p+QhXYFm3YCLjHoBrrZgYosSo+ouDynGmNCJedpmpC6uSeBrKZorV4gVSSslUFKm1+taAHaeaChlEJqQlDGBwaLSwTVoX6kP4UAUJsLt6aLOCKAhCqs5qQyw6nl02/5yigD7+WnVyXPKE0b27ajb9EnHCb2+3g6MtKhBi7tNJECp1kplyKzjWYv+lSd/w16HZ7X9t9GS2+73SZnhwrxUksQHDl6uWXF4Uy3DJ4/ifj7RIMJY5YJPUSfboK7/ydLZmLE6YQGqStblqmNTRV8Mc3jsDxtU5r4QOhwe6lhdyWwpGzCV00EVETtBLqtO+EUPLUSHrYV6NYkvXYGAgmMIduIxVNDS91//lnYKjOwjf7j69q8oEaRMCic8GnHrJA/rLKSFpl6I762SaT2Ou/kPihDcvCnXOMHETdu37Xy2bFzd0TtpuJW/K4J4WrNkbkD+obeI26dS3AAq+VoZvUOBajJKls34VJKFh/w2HsWqi4OKPrSMgfEjevM3aX9u57i/0IXaEmgqpQ0cfhZWDpns8PhwL/cVQdhzoygmR+OptyAhJlKjKQrBEX5d00FKBG1+rQSKTPsprFbNBQzsLifYUZJhzvRFWdPDi67975yytiWaA7Y4rC5j87mwjqPKVVucTZa49U/rzLFEcJ892A3LvCaPkg+NGCT8KZe6gAXrLJ9SdKgdj3EJns3tGKSwWwQDBbISO2PgR8K/e7sLbpO4ujAtKQXfOH4KS2js01CaSl0/fL6I9EkUHPjkfPwS7q/zLDAb6qH7ldlP+jwR0pj/2UyjcWdHbtQ5VWXUVs+jQ4ckBB9LO+OEQtKFu82ZYmDvwczadx8nvHYvqz+UlH37HqhNdH7zHpRSfPHNxhY57HGpmK/9LclpcL8aPK1auZUWhL6zyEhcAiv6Mh/Xqfs1SJPoVIQFOkV7os9rALVWm/SYbPu165PsOHAiUNHzD+gUe3CZPbI9puT9v5NCRIBx2mek7Uv8liR710cC5cLBAb97lkGqhk8VNlCW73mUwRJzUMFemxRCc1g1cZGjOzu9/XU9Vz0BWTRhZ6HYhHYD/VG3ZEPnlFfJC1fPgE849I3e+kXS22SDW56tSku1itnbPjjGTXDkFZ4pJoCSa+Wu17Z0NupDiiNF4I7xyVCQUA9BsRK6hGXFwXSD8j/uKkvLxU3X11VdEq0DSO196J2pCC+NUF+ej/kptXBdMLdLnGaR/grT3+juIt9WRfx5OyoyXIY7DkP82Sgo6QdQ9dgqw85WFkU9c7ztpc5Fchrhp7E+HVNFwwFcRwqQ5HnGAcpSUpvJFiXkTb1iZvCwHP13k2T3XXotDO0tf82Fn/22VW6hA4vFIsKIGl5LENtvpsq1X7lvEpLHkgJ6OJYYtmfUNtfyJrmkYEqX4tgjbfwr01/xawWc9uu5ag0sWlaW/se2LBsCHnRMd1nreYBs7jR3apPMjhsINFLIMhx9dZLIr3/Bv7a/14QVRAkIvagZacggpNUwSZd6JYExR3UboGNjwu97/bVDqnx+lqdr19VDjO43oh8nZdStBHsR+amvluQUfAwAg/IetQTNM4Exvz0akZIXsTsw5oQF8/CDGPz79ftVgrcE/7HuW/Bq5R9l2aUAwq/Z4ncwrECTt/p3VHU2MaDCd4VtEFaZ38GUThQaPbn9L0ifSbmvGN0WgGX+GB6RyUf6L8e1QYyqH09fL0RZvPOsgU7NA76V7AheZPUZ2oPaZQ9AGFNoDl8VA/2Nbi/poFNsyV97Nm6nVJMr2VFvtIQDbziSb3dzG9w3+efTBhAbK3ZCTbGfeZcH3X9wMLcbLYcwH/9Aweq1j2N59IpR+bkVYgfUiPezn2IDh9YTWIf7rxb6G3RoGY+Ylo78abZ5YTGK1dDwk2EcVsjKEp7iFdHQEFwZ3o70TUfEbRetOOcW9tTQ9p9IWrUXA4prIdgff3AyrPfEBda/cw84L+XHz2WwJdesr2NKCFC1wiplRHK3cP56xUumF303qu1uWwZakZ2+Ta0+2i88/OZG6h4536ZogfSAJBu1jqFW62hQ79Gl9z3FTwQA3/pjw4bdEhTimUblR/CGIe4ua8Fk3A3GXkNnzAYJ8OCQRmbwkwEiPc2xFXIeXD55g2XILww9XXQRM/su1TNatwKHWEM0cz5Ngq7Dx8WRm1Ujseb/fJDk31ReLImR9vpg9aGoNlAnGLUHJhLK7kryj1ICKPK+od8zAmvMV0IDkhEHJMfz/AiAPQ2XaOCfKAY/18J9is2vsHsTM89sPsxlU9BS+cRSa4xFHas0/CehnXOUct4NyY2VtdFhsYbx+AhHyKNKxixoKH8GWFgNtOju8On8Ykto8UKRmj7Xjd38zs9brDmgA8rf835yy3pijBmWIctVG/cfxiDyCOxFTb/k0hDxso3+BJKWX0gO5AFlJlVdPS9KZsFAis5ca1M37CNJj0EhYU0sxf/JSj2eKXU84uhfC4W7MiFXM/50YLnUXkwRzfb0Mc+LkJWpZGW2yzR7hfr+wbpCve3n7bc1JqBRXztZYA2d8VJze6eboPMW1gh90+UG+Wt3zQq4aCw4yob7bCssth2HAPX9J6lg+rvdaOS8pV6/5eO1w+VqAjZS6WkR3trqkE2JkSYpy3VwmARzGhKdCiDDvMoz2TQFOZcuZylwlLu3lcfGh8R3DLNJTKOBWg/hxpcDXWoyHqdq8V4vG9orqakQ/ngGgxwiajAmpTplDncsOvaF0TyLUXZCBQ6uoAiEIbGkBp0QmndNztGlPEmRWqYHr0i92aKW5HLdtYtb/lRQRmdjkgc3j+c7/te3+NnDsD04qyV6pHLEcZqnoIEkl1Rqk1fX/pWAsJOvZUoZ5+xcWQeCTCcVYqY5byEKdfPtwFPYzvb5w0NxqZ5hViLcvNd5A1JoY8FJ9n8dex0P/E+BgkrTJ5PbRBTBWWHPmr6sNBQyrTkn+osVeRBqH7zBFz7ChMa1nJ2QM52jsH4qq0RifLOeYw5ryFAJA2g02DSeMqRzgf9qDxljxq1JJP+cSSLo0NtYUhZN5rz+pnXREBPpuv0MsCVUgGgHTdrd3mlK+7nReUkrg+uOVGovgtaPyfuP2gD/LyffQnWt4ozhW4kGOOSFxv+Uhn3IhEmuTqx6RCzqkAsOSmQ1d5kqL+uIQTYAFzlD/j1oPiuwRDPIvGYTLWO3HTmJU9QIT3RpEp8ysqdMQDtU3aAX3wDXndKc7RoHNAxdVWWuNB9Kw61ClwROc3x359pVsuLZHVmcRw+M/vYx7iiqYkxBjUA93V1KvdX5AeufZ1PuvH+afyzmAOyp1RQXm72dqWL9F5I5TgFdwa2CgAXTlDc1xi2jpFIHJGuoV9Yk2qhMeZ59r6WQdSoKXZr/HF49LalTnwDE+Kt4zxDk4DsdozmVJpG8RZ4w6YHmTVKw3iOKX/aKHoKYq7OL7xVg6XEiIoy5ndrGHFgW7FjvC8/FLEfs3ULtTNk8HD/HWxF/rnr+xx+HVCIFL757PGv1hAflUAjtT8hJEiLUUjmoXb3XI6k4Az1+zY26+JzOGOaqNXGBwzoDY2h6h0VFccr/oBgClQ3ouj1/sq9ESehxUl+3jo9ggiNldOQX2erQnxyzZhunkhRfg9Hm6G0jL44XvPGSJffyhzxThqTBhzI7sRSQSyVQutVScqsmVPRMBnRe5XBCIx/6Fb38ozzxFB+KXsC4L3m/KCyzdwgd9LXhKqf07IcO3A8FVmwfGkJ96jX/GQ09Hq0GbKO6OpMf7jIDUWdQeyY8GTWHuWaI1+so9gQpiIBqd2crj8+gwxaZtkSLgdEkaI23xhXJry17/RFA/pSOd/No/VHQNF2YtV9SQpJBLOmf108DS7DuRCOcUWXWbZYjPY+0brBL2XyOGp2AgtkCFs3l87Lbc3quAqYLxptJyAj+XldknddHP/u/0eLuF8bV5hFFxblWBTJhJJPVHnVcoYjnlurW+1oMDR6IpdoZkkEgNaE7sX2uKlYVYqeiCCtFkjPhDsvyYoorELeac08AoojNbvCvZh94nHr9muXy/6MUEvypw+BPRaJ855u4wuK9DhZRM9LIyvo7KpRFQcuGQK4NGZxttBA8BiKUMQhyQxfwGnhCufKrF75LdMaBPBwaIWamUS29zRtif8ZSu53KPzqj2WxejsRH/CYTLBuZ4V1efFGcdxeEkgQ64dx3x1Lc5EjxvSw73u0ilBRioxF5eiIfpXffza0wk0C8HPeJqowK8YdFzP1rTzvSw1bfThFgMUavU+eh0yfHsqG21qP4Dz8+5w1SZx1MwqOOLtwL2NuaUE97PTI40U+UXQhdxCJHkxkJiq5C14S/xVjFZnOTKZL+P2KSRu8qlDKUyZ1RGGgVazmu8V0UIyt9DN8AJkzow/9wAHZxhqU2nwNz8fXqGZn5mHuU5fKRIkeih1wo35QuFb0oQuqmsx4vVVy+Fh7eCK9HQNNxGcpwmZ7+avhBxRT2/iUWUU3c6usAE2UPT2VfcozumTkegvrAfhQN44TNuaUP9gRRAm9WHXyglhR0bfWXKu3AVShM9ZhMR1J5OL2CO1ylLNm4xXNxc6GfGq/pMjHLUtxRujgR0tG27O67qvxC8xnBNxR24QYAWBahxEQencNO21jHdtDnqmt6kdh2siQTv0OirJKvRtxokJRw+rNSGUJTTTMM2PKcwd1rWC+yQfxQc4X/mDcnEEO1jQvrt1KV3P7ON9BxWJ/pc0i2qg0ir9xWB+EEfa5K9XQbxYWe8jO/0hEbjkSQ3qAxmC4oIUqSqk+MVntzw687gmzTzXgBKaCMWH6dXeKCHA1A5Xbs4J0gOxwuN8XQTjCTiwImqAWLYCMC6hc9hDsOiOKpjDqwBDxQizd5QDtGlb8MKy2hU0YO6n+FfE64vamhFG7cAz/PNBNysQVfktgGe3+J7UI7kLv4xSgKz1A5/0RrXTeFNT16LwFjza8mZUAqBDHLocIqFO/BOdsGkPD7u1dq39mztJ7iLR45V9wHyvBD8+nBwM+i9cz5au9KTsVNthEsNXoCtPhxKwPyxyofncNNOSsXEC0r3QL/XqAps0ezW0u1dtm5KLGAFroRXx7whXMjPdJ7+a+JsYJnQetEOj7d5xiiyMStk8XJFHWhGRar7p/dhcEMhbVFtZxHSYvRL2tmeWlVflDRzfpKsHJq81mVeTgdC8SFN8au+/7WIX7T9GCjb6aQxJAm/sBiMGK3bdHD0Qu4K3UFipKHyqA5F/HDaLEgETWRAYpq0oGkxTG79vGU/jkIU5AsxALEDL0mqXhUjtULZNs3gH68DCOKmWHeSCswBUMg1Kz0t7bfLjCobHsHqK8wsOjFVZ1Gls+7MoGr8lHDN2se+goaIZ5mYgVFBb9QDt6LZSL2NbFW4glMAq8GStBV7wfHCP+w8xl1APaRp0djHhnuogJpTVz25bScGv6fAwNLagxd/AV3CkQ43XStGmzZXWfHDu35+tVABoRhqy6ihkFAUJxXaK0zllPUPTc6i4lVU1hDtStQL0K0oQ2FBDfg7FzR+wcxC1WdWC3/1Nzvf8k0/TrLJkM2RZeTAvU38GCWBCeIDzrTqOonDf22sfrtEBcqb9vvt1TKZE9h1syAqtY/hnJK6/cqJIZXupo5RWphYrtO2iuC9AqDBEllMezdiNUJJfGvr0gEG7gld1dMGBVWl7aTKRrWv1HVuereRU9W2ZvzuccpPwdA6ktecH3mRqyRC3SgWVwKNhN+4LXoZxGH9g5KFPX7p2OJzVxE0o1U1Av6TSeFtluXUuhnjw7pN595tXAVh4hdXLo7Oc4/HCyN12+HyQLs0ZYw6HACjIg6ZvjWvIUIUhUhvsbper/lf5E8VqEIl5RuAVMGWwo0nY/EpZ9tnWxD3knbU+pETaKpppFz72CnLU/dVrdvZQj6AUVu9b1Xvn7f46OGlWy9xtyA+mzgtaL0oTpHuedw5hMITMunfF+jCfwJDiHOxSo25x/Y+5ePD9y++VnM9vstGX6Md8Byn9ChLAeUeZMO8oRg+o7V8fx9cL8dCgx0xU/q9KYkm5OnnMe07hMh60WOG7vSl6gMCTm/FaSfKOdec55DO9bfwBwl0uj0tSHDvs0zie0hNj6FicnjJLRUWS7xFulNSz+usFw747ZK+Rqu25Hj+mWtElq1Empv8Bt40x1SBNkNXQf+7XH3f/lHQpeI5QKQdFAL5al/VgYLufwUHq6CoIyhj8N/8CTHsEAgnZDBFPo2568AbHftXFi8tyhpwqgUYyzVJP/axtnetFJxqqKXEuUItua0e/h2+uh8hQnRlfRKwVA0tEvmnMjW5CXOrDncuov3et3G+fUYJu5W3/Xw6tC7qComVVovfiiDLav+BM66A4BGPj9DFjGw5FiJys1Vl+7WGEIWfkvxkmoDc2j7M+XWmp31Haed8mS+GOIsfFY7Hleqy9Vhr6mxTebndrlVufaebKnmnD0FH08e6N+seuvm7RZNtgl/cUrWveBcW1YAamuyXH4STzzg1x/7xYNNVKGh9UGKvwNKEk4e9TXhj/dzysf5xWjEaYpTnzkAJ8HJUu0Oi8RAEPE04prlENy/P7hP+zex9mXN5GPtxEWRVYbXvERMuFD7+CvNqLB7/Ec653lqTMeX2b3hIVlychf1FJiwMoULZE6c/sODQvNQkKOmcfK+F94JjwmSayLH+ZPJJ1WlvsmfnCWAaH0aORtAurI1aMb2VUO9Xj+spf4gIs77gGnpZdBfguCAklL13/ldatcMSyh8zrD+UWSQxpHZ4nrHU3ocntZNyMm/X2O7ufUi5N8vc34086l+JRyiNxawjnlwNiQ9whBdklfktNfj7o3l7+K79FrzJT9QFQpIvTJlt2ja8YOSCgKVogGiuySY0owDeD06UO5eAL0W4xUgUiIpr026XvED3QAwSorBefSmmEdgqmh2Lw502Oqrng05JJvz3IVa30VQGUQ1+cHHTQtkUUWjd35vyzopDZfGTM+o53FvM3k58qbSIN4gd0vIRVtLPAvf9qYhPifrBQHz58XDnrX7YRf71bim2WhCICYyS3SbP/HWs815CrrqwHllTblT7JlaVniZwk1ShmB9w3Iq7EPcRnI5cy8+sNNklYAqNeH54UISLtLl5hPiRVcyp/5vdSrVrAnSSJC9XDP39lP9Jl/BDiD0J+uUO3tKHPBb/wI8P5C/aTMXGNZEhPNYxEM3v0lUucG/g5FkBW/sqO0XBZOZYw5ValkI9qspgx18Px1N+2g63nc3ZOiRDUbiBIxO1a3PyRFSHtg4A1ib8swNmVywWb/JGcQ9PptgosIq2swmOe6Qn2uJdhSs5vyCJSOf/NtuOBnwKvotyUrLt4PMyLiQxMovhdCFhiL6U1Lf1GG3hOxIOKEmOUGMRpGrA/k5KHiqFrrt3ne5GvFU8ji4ByGTLQkTT5P1SJ5MlvJc0g6r7Jr3w036lzF03iQ0uMExil51U4YaRKWGQp3FwK3fojrxtqvN4dCvknBOuMIKsBGr8VdaH/gymy0YjJQh0YRgfbXERrzEkgJ2+9WEb6qMfc+1ClJLnvSoBp5eSg0XLxM1Brxln0q3T0qULFhnTDjGXD80x8BrdN1zYuphvJ6i8bbnmukQjF71rCyLNCvePL1wBJpnhY9wKb7KFVfgOv7hOwjBNJIGLq2vZVfArOynt0pm2Lx3cMgeQSBDO2hjhde9Di1oD5vEMFwXlOcgdfIn1VPQL2nv1izrqLpZUoOMGYuTwyLcYoQBgqUtLW4i4cn8WPgzCZB527naiF7XdCuaWRuAQs+Z4fZn7YEv0+0lPuRkYI3OWecI862PIqwOTQuDd1QXkC0KhyMMKl6sSVOT3D6jKzroWMVaqiEXQ2ozG5v8wMDD4bA+mrQoeR2wrnVnMDvHjaDyvStEdexgyuFQp9PfIHYctsVF+HQAey1iQ+qqw4iqoWpWXR6MdqX6X1J/Yz7LdUHdKv3ODc2502e4/jbyqlCMYHBVJbTE2MWAuDqk77vNZLrT9vX/PO2tvV1z1+o/ArESVFj67fShZ4nPBa4/3ek54mkOwmOCosGye564W0QKI2V9jAUmPl48M8QIzcxZ5s66dUKQl2fq5QiiZ4Hjs8zktyABNj23Dih7PpGrzyf3zmf+flUP4/ABXw1zR0BCDzZaR3jaJ5juDJLgehFu7za3scINO2mecGBlR8IvXbp2ao0zFI7EEiCzAGeTugYsSG/vsKlk7zEjIivyPH31DFdh+LoGhLl7Rd6JJSpccvjlfRqly2LNiUMkFS4jvxVLhwHrBXlwopR+9IY4oB5u92zeonsDgL/Z6RQP5txxEOvR7pRrwOLf0vJ1mFQ30LSyE4fYnReEf8dHe5KW1qmvmqgtkDgnoA+3vT5HcBpU2Vb03tr9nTM1sEgEwYHOFFiiDqTrQwKQW5ptETDQyMeRb4Q6JzAcF3UkDOgndhzpPlSXzBNhg5+ZjVgrdh60NDDmYwrfX3YrwU71r/X4lUWcT+CEx/2Kcjtb8kdTVdVeP4y1NIUogK3y6pJTp69IPvKl1G1SxMiNNikTgQNBAV6LrqlWlvImQgCip7XOak+nIIvwBEs3qywPKoprDClxWVMY7RnxWjX9uNZBW/Ul8V3WPJfKgO9nuzOv7c4XsVRh9V/Ml85VBjzIkaXHMZSFH3ezR8gPmejQU0j1YMBPlFo/PfbzSMwKBa/lFOzRyPHWYjHEF1RNwtiX0wrC2MGXFCs5weQud6M1MOlN+DcY3vQulKJR/90zcyYpwG8JE/PzKYW6hX59ByGcb2XZdrO8MRyY0RXJjMyHvcN00MMk+i6liAi48a3ncMiHXKeaGPkvfOVbq9mWJ6pZpAKZLUWncJFWYMvpUSKIoj7Ym66SNVvHjK9DUNqLRMUtLfL+pXhX2wImbmTuL3fpXSHgiBz0HC7wxoc4xCjbJ+vQFfB6jNPDymN6hin5rRYz0qJqkTZoKvvSj7Ss5wndYvcwWPb0EKW+IoJVN8zh5QhgVTy+kmeIH2MzEXBxMteq7bheCHNBG5I4rNhZSMeIH4K+V2MGlFgzWBKtHmCfk70tYSSiqW7FLxiZ72I9SecWGfHsD2Q8K3XNlDwsqTRm7xVU60uuwTj2Dm51QQmVSu7G8OeX3KqctQIiI7+fQDZQo+HkGvfggrVReXiJcxv2JvWOlGcNho12DUCN4jllUMO6AWSSacqVU8SBoX59DmJdXoTzzq4HqrzG5Vbjen23bbTJcvmGCWl5csHGX/9lzG8B3h12J6t9nCBuVJOK6jnFSNinJR2OQ0WGwcsoid/bksBTCZqPVk75NBONoCFKdEMOlmude563EHwdoPsw4LV7OBTY8KPSW5HoV/nr85S5+wxzTvasey8CAg+bqa+Tc+1XB1tCYxPx/8b0UEqUsQnVgfxRiTTAMyyr2qC/X9Y+PHEM29DD1Y+Ul3q228VwWnV9G2BPmGOCdfhrPNcwWKSAMseo106Gj0zii5DSBkERLnMweovbfluOXTfJ7kUXVIonmvKVmuAyRab9YaWFospRfiUktjgHeNKkmZuSoOO6NkFhiqjT59qH48up2gOVbDOv1H/3RUJwveIGXEdGPq04hfh1fqqbVFnIPr1fXJihQ//m/ffQneI20P1sIOctvdxZGIXBWhsb9rGprrZwf2Vz1flUtMD3ylLM+V+6xS8a0jKYA9WM6rsSXDTRP9WZisTsckwwR+xGA9I3dsei2peXi/fWOVlfUwytUqv9anRO0iYh1r4v3zox9lcd/VGR0w3Kj9QoJhZqq3Sy1SsA8FawBZO4zC73AxicKi5QtljTeBwedTgdSxM+SYC4TGIdrKWnJI97YbXmlDOKBvmIso2/2uQV0N/NxDchUOZer8+nt+gNDBiMRc3YNy91IwjV/2R/07I6739wED7lizvkKTevBoyCpeAWNC7RoQOsqfCFC8izPmA+Sdxe/soyeD0Qxb36O5mZbpVfTsx2qaYc3ZteJOQV4cTwCX40r7Oa1zJq4Ra5ijeHkw7E1BiOcpnwERyqBIUTMontYHyHv0SG9KNl0m+PTocaHImWfzwH0vKcrN3Wj7p71zyXsej4SsIK7XmPrgf6PIQsMEnmbEbhG7yiZtONnidgZEGLbhwbCcFUIIahJ0PjG8oOD/BtmerVFzQY8tZW9ZM3+XSXITb/F6yTtiyoVd49d00ay9odm6NBKz4Riz7pRiD9iMBRE8nbxA8mOCMU6tYK6jgZlRWi2nDwEfrMjhcFnUEPB2qK0pZ18Iahpu9+H0rdoXFe+lOofAriascPnkQCxWWRav3lsNHel+PAH+CGCrxm2A2sEJHOl0G0yjqtShhwB2hyfxKvUkA3TRjkZwo56hm1efAqtpPsrIa2vHZmKd3uO+IessZakqmeAOqHRchC6/UjhMPTDv7ZYizd8Mv/UTg9r3C2XBQsmUqEojtMpBZvz69q5XvnZ4MwCdVGDWbSsPlcoMROhv0OZLkK5aHVHcKIbPF+E5KyMz+IMitgR3q2uyqXt+2d1sjT35Rc8V2NauN1+euEa6bRx4aByXZ8Dmu/8CSVfGvSKBoUR6rCIVQquag1GVznDNTlqcDtN533DCQn5fHDSLEBef58J++YpHzJzaoWtRToF4rcAImRNta4+EGAUfs+YJeHK7bXySB8tS5IyyK1LpwhSEykWgDKs7tnN+9xmlmFFCe7Cb4uZuxF612bTJmxXBkeG57aN69HaWYhwyqwAtspYZiW7hLpwCoZddWb5kmpuKKPU+Iue+anHUdgdKlGAUZiD2bH18nWvHCs5cMpPdYjpwSHW5MqFdsuZFj2eJJ+RrE76AxH5jN6MnzC64+Ki5vqdo1wpHwy0kaJP34Ccoe9t1uLiTx98/CEQ9KALJkUUQ1U7wk35K4LAzJ4zrhcyDdTs2+TgbttxmFb6cZpgeMvZ06stQA7hlIDXyI8sK6FG8mVPVIo1ykCr7StQxkRF2j3HDPMUwKgmEdpMuqy1aD8B2rcW4SIX6IHljjwkCujpQbXw/+3ty49vM8bCNidFpI6LP87/Mvxmu+QzJMw7XKq/AovsNOoSE3a1tAgzy3TiB5JrX2aFpUXliSq5f8PUpxC0VfnRIiKNiAyCyTBH+pc9E5kR5Tr92yKgwySXRp0DFcPL0FWQRll763v4j0DT3gI7D71Ifl5Bu4T0FXE0tOX52Y6zJqd+qHsoFiRxkZ3ONHENtPX2l8lsCHtcJnw6Axhue3J65XBAVyyetYgwU+5MFaWNwHKelzp2OLwYKR8q2vlyOJh+jIiovPXOB2Es1PLLL0Rjhfh05ihH/2fC5t/IZOV2LxeX50eAuAhSXfjmF78giRb+vVIcXz+d/IWfEtnK94X0dwUwaK8yrynL7cOOACPqdzEmTD9tsR9ErwikFYx+deZcpEk7B7vZ+7vPQaLUpYVvwDy3XfJDNm8rqAnE+Mgf4VNYL2TWvLcev0Fal6PLtySU8jJrjf409Hf4HA2n033PMpi2+KAxJlBI0t9hVE+kCTxIQFQxUui21Ex1GpQXa18L7XsWCqg6ijQtKSdq29Pvv4fw634tXbZYgIXOmPER64WNssOgCPrWs2js4aPxYqCjU7TuU7lgUXC4omIQhnil0GL1O3jInyU7CWOOiUiw459F2oJutpquhqn1AtnByJ5fF1lt/N9FP/3H4ytPeBhUtZQdbsaaEbGMPT5F9uflSbdUXx0sh4DUigQP7kbUK2juajhGyJhigBB3PUGpaaGB3nThNpFWTGE3fCyjHvgi4Zs3WM8bfyDsYgIof//3Upt1SLVdOqY6A+OK9JK00wEkfXqZe5bapQYY9QvwJ/T9Gm0xzWJkmkD9SAP+1qL/kMwPNYYKLlxffanQjmwIt2Bka4lJ+v9h4dmUVd1kYxIq68T/v2O0ZLqJfr8kPk4JPwbvgcvndBeq8RfgRUj/6L8K8m2E7KVXsScvKXh62aeiXl1xhJOXhucGuKuhzm2twURjwJhHS8F3JQP2WleNYceoEBpTK/ee1XAgirV+VuaYVrvXydcHnOjloKxWeBo5oJa08jwfosesUssLEug511kekneQuF7sUP54u+qZ0rW8hPkgCoB5l6/GOyoppDiCRxgareD1PEAiedIipM6ZUTMXtcaCvYl9rn3XgvhjxDhs8uVRfcanWRiqkEciuW3X1AgfmGCGUlfFgyK8wPvr1U3yAeNYm3NSV437SJlBYvKxCD9kFbR1NU//fJyWJ2m1qbXE8+7H0GfVy2iPepzv6FOCxS1H2ZZpIz24uhh+Gtd8uvxj/lTNeVBKENa7XP/vurfLND1P3yZlctkWQSch9np5p5x+PI+asGqaiutpEyYwKnB3IpuEnF1Iu2jA/MpY+WyVuDsw0/dNDx2FOu0sKym9ZH7/IKPaNSHlitPAIRWm7/OBdLBs9UJUGTXgkVlg1W2JJ8jYmbuKuDQu0BgjtA3sTfoSYH9I6SSrFuUN4jGUxMOlZx91m7vLjbUeWKg0O8Csy+qKKxwkt548IO9vaRVR3dPnKIc+CRGZBZFKpuDhNdu/Wc1IzkztnGQYyH0K/L+4KqJjn1NnlSgBfm3CTPbOAtcfue6yyssRwd61WvziIxAAGyvUKw42p6RRUFvxNQ9bRhY8DRHN7jBYpD5yJIz2Fy7oJGRLRHFcRImbEsPB4CAIsW1LY2GLIrM4AcHxRuw0nZTTbvl0XHolHxqZfvdtTv1KKGK0NBdc/vOr90bRdyTxKHXV4aNovo1e0Lbs7LCILsKjd/+jSE889ILEborz1VnZaitYwJw6UAFcdN3lNmB5degw+a6Ye668sjpmKzjovF62uxh6Kw++j/6bu8TyCGzE8HzcUbPimtgRJrbSlEkUxSVz5v3Nmqw6YSMRHuJ7i9ry5Nxi91qNNjY0ekR9VQIPzAnMdZd43zM3pTEzg1u/TdYMOL6/K/BNkicz4+Uopy0DtG8ejDUqN/A41mE8Oc363DgSzupyY+jyp5VlYqlO0uVayryuM6yo5uKnKTEKNCKyImsx53mzICm9JzD+dgkpmJ72PQv4I6q7hS1FzRwAFyirHIF7wYnOtItLtiulYdVLbjHQZaK7BWu2HsynQB/bO9WoG0eyiYutKqQqEc0ZNQjS32+87IMHzCTziqGaMaZzGNO1h8vx9PqpxjZW2TYlTXXNPcG9H4z64Jm522aiW4EwZFhRPX3lW9sUCxBmFlcrGMApRFKpW/BcEGZaC0gXbs7/eOiNer63N5AHi0oeBpoCDTYGdSJEcD6wu/C/7gyOvcVZr46vRjR1cT9bRm31Gza28jGC2tu5HROrfsarm5mHZDV3B7qFvfUQbH4SpQoM41hV13sG2SH1qJR0StB2mdh31kzjiE7CG8oG2B+vDZcfE9SsOC+/jQeIcNfvA3i0PKQSkbkF0PLjKiQ5mnqNbXTDv9CsQL30Kg3sOFTMjaQDk/8NlbvRpllC0LloOmpCuq7BJVwlE5DT1vAaruWFmEkycV444Ociq5VhWOArfJpOKic/hv2nnD9n5AWdsVfGeNCN0MukMVzvfU6to5IAlFcZO3orbpN4g7CZZVORvj/KNdyJ5JCpBTBzZ8YbDzeDF6hMWKB388dAugGcoeCZJyT574mzYUzo6XLHuGZ/l0ytt4Y4KtiE2ydB0OdzcMvQ918YXiOtOCB8zXIiYQz5lj404LzncaDf/SBCcpUpXevedRIThrTDysvPD1AJAix4EKb0a0FQvRzWlALGr84alhRtHce6f6pZddnyCLSR+uPrkrlDZaLuuUf/baR/vwZtNUdi0Xbnoq/hgrm9cTW4NR2gJs89iY4WS3/clU531HpcFyNcX2mMrZ9ocBwytAinchB8MYawi+myeFysOrodAngx/eon4jiyZITrDiP2HCft+jjUITHRdXDm73sJHvlNGKVrYzKJEEvqSyIQgRinGjrIy3p7xaimR3ObpTPypLQu2Ik/VNHhlENb9KtUzQmw4rg1zMgmAgQBQYaHey2oS1TGbw8/BKwHenvFXIvqHPiyrlImh5nRv1J1Lj+to/LyU2xqAo5hSBcUMpbWA7mlj0GbmNrIVVwPb1cH+ugLiAr2K+ZpXDjsTygy/UXls3o90WwWsnKxM0ugLs3PypQRh/7tnMvbUD3jKV9AFN3BZdDU9DV3X8aHKFbOXH62/yKAJ9cssimvulPk3wm3V+77WowN+q16xgTj/CXjz6EJrlUiTnEKPkglQhrLlmieMy7ABNHLJT0sQx+zp82t0TY6n9ymQVqoYZsFlAuYecSUu49JQ0fuWklKo+qW14V5sEsgxDh0lpSHOiA0l/7pV2S7pxoH0bxZoEPUZdIllVpvUluK7qZQimVZW+wbGxw1du6+hM6UOvwkkVJJ2DZw5gwFJfj9xmTnAU5cGvaHgdKGY0JEjuNVycUPSdsHpvneS1asAvR7zlpgKNLAnT62xiL47nIruBSe2mwbi/A6ziGnDy4ESACU86GUrrqDGlCN4gOVKkRIv3HBSshxQt+qYRbJkQA6/0VE24d7APr8rfaIAfBzz4i/wdQoJ/uSpObQUUy7D2sE/TNUx1G1mDiGzaCisqku3HaWEF/t3HGxXmeL0Ca4DNwUhgwTGiHX9s9uKe/xfdwM4PAWS6fGZfdE5YeJy9VLVnCasigEHSUwddSOBpKlKvMUI1UinQvpPgDXqEgUXziEuG2D+Fpou8Oas3H5WvgmkHI7rGxAWZjVkdRmY9cIArvsRFFPkdaHViFCcOtY9N93UEWnRFXi4h/kgjjy5srnbgV98HsKTW7Q6is7iqcD8cSqFsSLvQBlIVYEFbl+fXZGbB+mLBHdn48Ub1XAmC702b8UuxwNd7wyG6QKPGlBnER/qlBtToAv2Lo+w8Krjh6UMh9qZZJnszY8DMM4lxLE/BWmeMU/LCxWHgEJ7MYSXABJ6FAMxnMxgMh+YvZIVyXS7K4J5nM9wRQqxRq8+eEOlkDddWT0c0T0nN0ZtncTGpQ78Sz5MY8r/tQYVRMFfAcLLHXWuTpc2pra5V1ZTME0Yyly72rIEKycBru69qghDoJZoUEl5p+80jZ6zVmq0ao3bxzHHVSnSJ7CEsbnLBcES92QecPyPjCxLiZb36359QdK2rZjsS0XZYZUkUdxuVgGEiqgdGUyiZ3IxGv1jsiAy3KHIL1+UgjLJHY08xDIcNq8OOsQ/O4G/+pfeijMNNKlCO7R9tw/O9lID/5pfRkRa+023w1omLNLcM/3KLVWHNOUOUPacONBbctPaSFGS6AvUZc2CLre0Dv2PCtzj800LcMXV+PQxwvTQFSx7GS5BCDldeeg3cFGiwMJM1c9RHQiQN74HXtPJBjuLVVSFXbuamb93ephze8H++2jZjFRRCONjbcskP2Z1SV/gQudWPNmBe8qnXDsKQVD72pn7mgE7p1lA0vpQ0DCnW4rOg0xhbwEqfAjGE1wUABE+aBHA0rnJ9rZudPGhC/cc6/N6DU+n5LOzaoChOF48mnXDxcPbPRDpa4HtYguYgq5wFMnR4VlmcbtAnBanR5KhTVfpbgG7GuDbojRJJdqDrfjfFhNdWuOpaA5vepE1jRcY1Sjxun/qUIoQ7aOJyqpGb3tQLwMFjjZNLb8n4fUFi5fOjsU5LgvgaDbvZJXDvBOs+863fEod8GgUxpdXc8W43kkISE8g73jswrIAbFQnDdvZIqPAwLbTVz62/SGVC7s/yNa2P31p0XuWyuaPJvgJdTjLfIEFBH9znoIfoB7Xh02XkGch7qsPuGoURh7GHI5AQnX9GUvLkDeK+1+XCfTMAFs8z23x4jlSeyOwuXYHnOoGTu36ctrtEjXAsUhzwRDL6ifXMpnlNpYdd5m7Wg1Xt0R/wfwmA8t7GxyJ7/ttbkR4jK/iE93jPU6QAlSeRCCaQ5roeisX3zxVNbxSkgc9lClTvltRUoNcpcqv/qGgGCNWsGeGjwTReyS5Hib/iZPXSboWTvwrqnNQckw/sdE2aS+VJDohRmi8AvvFYWHWbN2oXfDsTiTgaQcmhoxP6X4uuV82L7Wp4BuQUru4sHXAX8iCpdJo4XsG2vD2fj2NPTm748sNL2g0loTLywQJEe1IMO0qv997zRrHjy/Tx5WYZmndbqHwl0QZ1RqA3+yLrY3P2TmFDOgBS93UKI+Yq/oEyRl/c4WHotDNa/hce0Urq4fjF0i0h57+LfetQIyg3Hkx1cLRCCGqqkfFSQ0/ryy4FKWXpttlQDRZQuLgX8Mp5cA7CWxQMdBDxH0D1IooUuGL5yBSxotJFmrsvWJ6qcZiG+Km9q1sgkGYk1mpknGZLj9kmGQ6QknPomJKl6afkzZ3i8mmghvWI9YSR32Y2Jcu/wuWh64N08/8orXgLyyywNhKZHxIpPlIprqVO5wecgWaHBMQepuaTnzxKAu30Y1R25VpOX/Vy7tK0NQvRipRylgTiaRJuBf8XEi21a+oNsj+qaiAUwW51zaNqKWDbaYEvzA5G3l+QPFENmRern57b5H1XS3ZPwTGom52UOnmqahCZ44YuIVnc9KBouu+Fbk8b5Mok6xYMVMoqdi0b8zixINseu37tfrO4MDHl315Pj3qSxpc5G/sVmHVPosSe7EERnkpclYwZr6Kcn6rW7vVFS32bLlY2qla+8NwLyULdf1Cl7AbX839s2fBQ8AHb5+b9l6bHDPp9+7x2knMHiwJ6BXhYZjDWZmHF9mO2y0TGPTjQIm5Q5XDX+y7N1CEIWpjDzgX/NktgFqtS2mbfEqv5fGjQZsZDzz29euLKCT5rYkxZzk7fOjCGlYRgjbEZi7R47/0aOPMx7xkbdtB1DpRBJ8WoL5sU9PAzR63+y20FhxiWhyO2d64XTOdjkM5o5y+wXxtRxY7wgtCyV/38TZZ+SI2o7yuwl3IMl4F2gzAhqSP84dt1nz79Nms2o/4W/Al+AuUshMqfLiUoz4fqIMzgcUAYYnpSsRigFK0H4OzpOa0eqtznJvnCvC8bl4p1uTCOM5Lf8oHWst1nJcBH14p3cbtaajwEvQvx47tshri1YdQ2v70cZcb5y50c1EcwFNOZN/9E5XIo1FCQResTnXPG+SjQB4JtM1IuNveu9K23VDuvnxnhq6ZKWMztoXyb3nhaTHtsA0SeagANJFuJk3xfChHt3/t0U+6FimIyiai557Q0lQ7Meudbvvj4Tv30FWnSP/1l29HPGATnB4uSERnBDnOT08fktV3DDqz4GuNrKQM4xoPhjjB8xjE2lvP8HtStWNvFBK3fAxf2+pChBdZp1VP9CTVu+LdhQBbtQBftFzhqrEVCo8UhY1mdBOM9dfUMd/utJx2P8Hly6Mv0KXMEIDhJoK05eQ+ffixXQJ+AJaKxMdWa+ZHRfI5sjNnp4YaD8S687T0pxvVJNzduuDa1xL1EGPt7OrSAXP2l4QOfx9l9eqSakKrhFFLaZHveruRudmSxs+F6dawjlv3HjDXmvqrfEY5SCk+dzOmL+8aMX29BnTyqb+l+8I7EU+1eO4ByYJuXxFX+3Jjewim17ocERcbgx/OrNs+pBInn6KxTTvdcLiB9OQr7Pj1sb9FS6WA5OrmwoULHZF0e3nKGbHsQsYH/SBjg2hwtp4HaOdQtT31TGqZ76vX6cZZguhgQBEsOVCqVX3Vt4cSTo1ogLwziv41JqA6ENPdYko+0HUht0DnUHZ2U7B//cc/r5pjz6eOKxq8UyOCBCzfLyU3zpru/q1VH87seAdjbqPdz3j4k1WYYni/14ay+Pd6p3atMOt6EpqCZFfNvAKohzJliIHAjve58rfjHRiqpAvn8bohlWSXPjngKHY31PqcGH7DtlsN5oeprSypPx2RNp9w6WgLKFZP7x4gPXqoSdrXV60mhy66tcZVpSS6vZtt9B4bCCXZpRoQBA5lbKKeHyywSd0/7u+/bZr0a7+jkHeNOT8pGJcaU+ygWBHZO3RprJMl9b9mkLVPao7fbmWfVnhhk4ZuIHV1N11qWq0a794uP2GmBtzoM21Xr1kMsd/4hl6Nk7SfR+GZNVlnl6bZpaCHzqD30dAXRyqIjf7SnJvj8+HkuVcdqE1YW1VZ7rTf6sBm0oSnGRbvyv/CguquxlNCZwXFmf1UAnA1Zduh01e9YvHCu7FHM++f3falwfZY4s5KQRjC+Qz7FiaqK7J+5PLzSyCiWWwKeqzuH1CEYSXd039vhE0U7DBTBxCuRIsOLl9IYbp1r2rQjIDj1bkkgg8Vt6rddwFE0BQ2/kh5uqUinoH8LSk3FCgks20jVHLzzUAG7FkZFf+p0/7/G4WrOBc5nSER4KjZXCN+szH0+usrvrPidOtNgg9BhJbR/99Q7aWSBaIwgWpyuwaiCvzI94oUPQlrXdP4diaZXQ4hwR5FrjbYl40W5f6Labx/IATOdQEcEz+e07uINVW9K1i02IR7mgD68xyHHBlx1x5nCJdQj3YqCFBu8KGLsdPs+YEgDDOiW05qKmI51d+Vd4VEz90F0P5gGEIYAROV+ttFQVpmy7hRBeIfHP9rjFGsqVGMZauBiCmir49KyK/7EnQTfhgEzTCycW3nENSD96MvbXVqoiT6N6OBnaDM+ajcC6p8tRpD/bOFt/2wpzSqczG/n8agahYcrLj5AaZSM3WQU45tjeDkMfzMY7SAfzyWtoSlKsmd5HKsQPMei+VogLwsv7oK4tIKWEuq54CAA0d4arW81/kws6AYnE7TNsL2S+AQd8HLXcFtYLu/b7qRv7DTzQIOUultvhcm0w2a/H2xZCpoaS7lf33o22pZyaPyqurNR8h7i7a+cuXzyXZ8zvYs19ZTixHKNeqxwPw67mhkpzewDYPFC+98dfzECLpFDTQnDPQQHBLFa2QMr74AaykTZBdK+vW22ChFHh8TwW87l6ThhNo1YEjrTnIw+OfSTMcwOrcnTAgu/KVU5zsuENFs5768siaNaqQ1vOWJCpJJAXN6tcLRNbigtaMpqYnZmzNWcmQAWQ9DyJbjs4A5V2Oprd7n2EEKq1g82o/QDUVRsv9F6rYZ+PvU4eIlPqaOCMYqPqb5dmMp5rAzeny0WgUYYUg3GPYq5Ov17pDmxO1YppAHhmZntDwlppoCQhiXyNzZUsFAJw83gAvEGmAU1xsciZDhYaS8C1Xc1dbYOfT+3j2hhACJf0vLCnS/rMbD1DgxhfteqCc9U0X51D86P88a+fuqmg3JjTtPvwlg9QTOf0qdKP+wikcBiBrI3BJjMDo12Z5X2NS1dB5KwWEZfUhJNmuy3MEauR65ptL/R2NZjpyO17g0WmnxeLFhKBDtzKUhvCzq+99cYbDPhGHQnefr7Rf4L7y17IhXw9o9h6PkwWbW6/B7KtYe3ckhJfX3fyG7uBF4OiSmAw2KrlE3hBuGSw3yzBsjXlnLsizQreEHwrXX5MyTZgbeJ7su3n5sZIoXwla+mw2ujuomsAdgdt3T8u56LsshtmBhWOLbZSj1Z2nEbZ/k9PsEbFiHwRgg7dc5dN1whWCc6jYRlRe9D4Hz+uytSw5v1MaXwsnhshsN+jbJayVz56Lk/v5U+mUWAnbm1jzaFHHpJwNK/4lWTsartuyW3di5GyFolkdHDEkOgg5NWybRZUng/t4Wq5Jv1WpzvjHvo+gOUrl76Lty+mmv0ysUPXEUUQa/4312LjJtwqVlSDKZP+6kMOwXMz/Z6q0n4jJhIggfX8NO/+UiQA4j8RFWbTE8gOlYuo4KFOr8BAjt/i2Dx1rfvPybezmv2eJrgtiK6tGWT3C0jPLO6yFVZm0JTiOKOE3P+tXvobSwnh+Q/miUKBnLi6WPshAXw3Hk+MqBEEF0vZ3985Fndu8OzFqAA6wTEPVQgePpnykv2aMfb7x0olbV/X60oBbm3k2bzdWLZzkdhpgpRbbkt/Utj8emkxBPgbpLSCXdTDuQy+O6x34k61QykFuMGhPS7jaa3mkBZJ0MxsWFjGHnjbUlwy7jsBDDJCZPsk8hSgotERjUpXKPcmBXAOgQyZDxLRAo5vc9pd52qp0Og6yZWtCDa35c1JHXuXqcFwZFRths9gE8tZN3MZMIwWUhHDr3alohjX8G7th4T8JTamu80RU8RS95T+zpecs6i9y2o/edm8pchVIkklGc3bnSN7So0hygt7qf8uKdk7/j/pd5v8j8/Ojn+7K5n9wobNa9oA4hT8h6TzNSN9JECBXjN4w4T0b8srZAmAp+PJa47p2HUsXZcVRpUy12DaKezSzc/4D8Ih6+8jBHlEqEAkmJ1Aa+3o+gTiAxH8PUau1hMqRtx6oBCn83V7xFXp4WukSaVeB1XigHnTA3nE6Hi+Zo2BttYKSwO215vd+FJeLMAiuEH4Emv2l+HCPgg1AGyH/g8hoy16gXKuF7Uj3YcsxQIzIYFZ58NMY7F7s5a1EqY+5/EePcXDZQUGzUl5Eq00JROijabGArkeYVCnJBnDazKV9/HP9cB1vy9JOlgjhucxKrZLOmQDW3tLeRlhyCbXwi3K8hzUVA/xynhPT1OJpWDUNsvvYdPL5I/9dHYU1ZeQaQAuPsfVv3mQRWrKvcrpaFHXaaLos/AR3B6GsluLqnb9eiFWAMriiAO/SMO8yH+1XNkYHtDX2DjrZ4FPHlXiTrLVgdvgHF3YsfXPo2oi8ChlanKSESTtvgvFWHxVO66JrbkZEU0TH9S5lmeZZL2ZKCN1rTMJefC8Uv9BgHy4v1xbCtZGO5Sqfkb/kcFnk05Vrw8SfPCS2nHls2IDm9yrr+UQAjTtaqIX+HaxhW1ZiwDUeLvORr7f+SY4BbHMVpg707BkeN+ah5uQevS5BnXuj3aRWf86BCts7749pKjQV/UAa5nxBPDh30QYQGdNTlB9Fj1hRiLuTJNZ2gJGtpXBpd8cvucxQzIkmgmeWR69Njh1fHSrpGWtJYUQIKOzrZOmCgICEjuQ8h4+QOH9DA2rQ/zc88qUofTFMpL6J7QX1sYQ34gYTQAvR3e5vmFvl2ge3KIaS72B9Wo2OfUCHk7ZH8PizU9e2hF43FVTty5W+vW1sZQyxteh8P27cR8sOEnRQ90HLselq0GGZjLP0j3TSu8slTnpNi2oa3T4Jnfz3m3KhFG1K2+QoTHRi4EhmcPpbK1/ibYT9cyateoP2D6Arhq5oIPVOQcAtitpfnUpFcHb5zThQctrvThUezsWPyYRvFOfCRMZbxpbbTTm9cK+k8nG1mvL17MvqIdXvwnapwn6Wn8qegotlhvA1py6dSUtmh3cs9Td3KC+GY3089fVPLDtC8r5OqsKGXQ5dg5RcxRuO1B4JWgGMC030cDEdE3eD9c78gvzoq9B6f/NCjXJUUWAbQavEtLxqgqsHKWvv5YmyMsingsI+g/jR/8zYa2FiMJKhgf8I6j0YaDHVuLxrlhVSmQLAkIhSobU0k9PTr7i5JlGOFf0KRaoYSy0WpZ65esZziMG9CQ35e1W4rQXXrg5EvgfYI/NUIjHPfcblMTUOdPzG2wqQ8WF0z82PWdNyaoaR8msOIDFepbW3phCMDC/wqYj4Epcayzt8zhjfnu4zs4MfgjTjdbFZaqn3BbUfR1sd1Vu3FYlWTlpfdDLloivN1mnYHwJFVCJ4G0oTvOusQwVHEoOm8jhv09H5OvJP5aGF5rflDAHougNqW49x/kqjbZ4Me1XTcwsWhPZ0gJMsI6E/M8gau9Z3z/39afEAoRAO4IeO85A8/aTzyYp21K5RBMhrGntk77XCkaSWgE+AUinOo6szrHf+LypvNXkafGiwvKSai0zNsSq+bO4I9Fejl3eKMk4sJtWyqJdu0H+7tEeRyb2s/6LQeyN8A5HYPLCl9f6sL8BT1Lsrlwfn4KTMyi0e4ELEWrn9GnqDyX2uDbEpt9I8vT+Z8xR6ny8alybJc8drMNbZuoxGq+N+4BDVTLfVUJRGHDMr3JloOM8F+ZDKQjjtqs+CHipWPV4/cal58j3fL2APQSS4QaG15LEAhKktt8XDcLrIBt7+DJxxrNtg3mkQv9lzFJqBFMLmicZvUthacnR257S29hmO72djT22fAP1zUCjSx2j7VARJ1Z0DZMT33899SfJ8O6Ij3YlHN+cCz2+1sWK/Zhz0f0sx7/uYLZv5dsfYs4Faj3ktnWL6/rCDxmXA3PhNrjHlQsjVntaVeileLH4rix3q4IVpcXbfxJX9G6RxY0orzClyw5wx5mibsMsDTaesQqRXNyl6xTgIg0XAIWuATcTavYZM8aqM4/cTcl5COni7z/bXHVIz02AeZL9PC9X7KTVtnP8HR/OjTKoeoKOEcqpmqQdmra1YOlrvufERuy/j1T+wukmHnH+myOd4YGVvHnTIGAqsFa4bXrr2vqbSBZPzM6nN3PHp2/X9Rtxn8paz/9FzsXv74uu9aQYurAyKzEUd1vEckgGf3zaYKt6ammm8jT5QIoNfQjMALzCQk+DTPOPBk9aYFBGiGJF/NboKHfK1EUZ8olQfBioYkPiysxdTO5tihzZTZ9wfl26bs3OutggReQG89WOVqMUpZuy6mDKgiK8lCGlSsxJFL/cLSwkMX2HIWEWLy0y51n53UWERmuipquGfEjznjdY/c09mT/QnI4ZKBSS0FW/8i8+tI/I4NAvjchRERxS+pSGhEyYKWwIlalJJSMg9gapccBipCASJrDEQDOjC1RBq4Vchla3mc7Wx2qS4si1SBIYucAs8sXt/QQYJwnzQiUNi7dg2FU3LUXvTOv7n2s4SXEWKz/nHAPh6Dfx9TaciW7paEw1opJ4Jhgveq3vIcKZQayh98Dj6afjXSasg0/v4Wz2WpzRsYbmJchz2yj0lqO/TfKMGAOP0AZuuQ/YUbLthUCWbaRBsJuXDcPV/uqVYVZV+7xPu5pQ5ZCUKuxX0tVeqIZkJxb4Y7FGbiRuRAcWeL2N1/GW6QQwdzEG3YIZnGrZZQaxwPy+SXVtc99B2dHqT7f11NweqeKdn1rhfqfSf/P2AjCnjFbps8I/qQhgPp+gJIwIhKmOZajAomh8o3CJQaBo7blfCu4k8moiPxmYh/NvtiUcHOaVzyXYTn8W+ubyr2dARp0FPvK9dpBiVVyCjvsUcCVcej1gXsB7Z6GKmCeIV9w63hn+/r2HVzDRd/Bl1xhB/QNkcTpAsBK9JepVEzYq3DF47mww9Swg6hmQ4W6+JsEeL/OIRFz9uK64HR0rPzZAu0w7quHnDIvmKt97Oa9c3u8CfnERUAejitK2tGnBNeMFGIyiQkyVBGHEFyUag5gJRpQrtAW0XEJYQGZC7abvRei+6ZVq/sbbrENwRx5ONddQwXKeXRjd4BejvBal3ebLkxqbYJ7U80UwAy8bXiN8Afvx1hWiDmZh0nvIm6LJWs72HtnHbyzH7+DYYPOCu2qGst+sM3lqurb6i9bmVOKb3jVdtrHDWCChgu9X36efSBvo2WL0c8TlesRpaxqwKy0HREDVIE0g+SfCf+bn1YsC3A5EUD2weRu42WXVGkAoTDfeeYO/16NJaKjby1Vb68wHPoNf3Tg9jYs6q2jfz5lBedisqF/orDOFqNBX8wzFG+CHrANiGWP1/a+8KyQj8rqcB6gZrp0pre1WDC1YKX0/ghTOkmpifXcK2x+Cw4YN0AW8412q/3BaaP+ISo2iKpylQcrQkMduGYgdSQxJB9+RTw0Lmxjj0oyXDOKeTtx6Q3ckxZbe6jlJbyn7vR8JKvMJ0/p/dj0lGTI1iyQP8HfFiLDtzQXF1GaxBXdvGai4k8SewJq3ezszaCJz+lUy8Uay3583oiD74jCJWVFJhyXGLZFCdTiRXwfI0Oth46sxSmfLLqJQCAW0y7HwcZpz7qKdtxsPpAXNp8Ao9sL8B4nP6ip01VcPXt8s2rrTmaXGv+eUfb4sfCB0rVkm2/i0gX2z/24JojqqnDySIECnCNGt4LMTYmt7QDqM0jaFLw5Jjtl4lrS8Y4rI9bU/Up3ogpc1YVttl+58TGTwiyw3uzCGXYectPIxWO+Sbtd2KycUtnyhKAK2HKhNwltGIPSp7YLizyNemrr6vWk3QxpkUDhFbDPpYUa2s/XJmuGj428YhG6duK+LxYVxJSVtuVoCWshGHAAzWS1HRXK0tyPBFBTlJrvH07p7HulRGm+h4RI9M+ws+cqUCyUJKy9mHhK1W9d0IZP440Ii5935n1H8zukSuiXibHfi9PoTyObBwRRYsfN6kAhk2u9uOz/wOFuZnWMOAqu21gJ8iXP9DgoJkeEwbtBDSoJg0r8JaQ3I9psY1OACuf42naP9156RJgpeRm/PKFssNfJi3F5KihOpiuZsVI5sMp2cZfo14H8r1OlNsYtBRsHcQgnyzLsHnanj0TZ/IkQkYZNRWUmj9rM1WBARbokiiSgqVo5trHfwJ4rU3B8Y424j3UnQJ5OvZnnhRdmftB2ae1HB2VOl7Lh40oKTxDUvhwMbI8e0J8x76gyYPwZ+1SkOcfGA9pg9wXOgWNklF2g2+IVn+rP8WrFonONrc7jdYZqp5Wp9/GPCVo8WstqxVxOicd8ewNPNzmOqi4S+xkKGXX66VAS7xr9rmPrzxZPpP36Z7oScMGGZZEsKlNNnt9Bct3VBSIV1VI59g5L0qUR2/Tn+EtwvEePwx/tI42mj4TRGVbrtaCr5VN5etfIYpswl9oa6ScENM52HpTgsy0BKm4U+yq4XCGaRld1auWj92ej9t0BHrJcp3mc342vUuyZpQf9SFARJLshvIc4vVyMOJqSWBHpSVf7Di4Ft0+XrbH1PxihljowbzIWfthMsFT+vwFaLg1YzMpaIVeic8rdlGYsQRrCIbYQpVc9nnthAFCAw0zYagT9yTVdThoDaOifR3dvbCkdjivbIAXXz+RtlYbDvD5GytPGm270jO6KozeTUP17waAH2KmuOSb1W5VrrtkdZQvb1YL9NHiwE0njsB6gdrHhwNv7Bq7xenH7g4vkWYhVZpTHaEXSJzqkLPGhHdRh6fFcXwPI1PdtASDUH8UiYU5z6UI3+MeOMSp/DH0k1ELcIBzfOeZA2zd73Je24n/E9GRHTU70u0wVzBxXAw59VshyZy4ViBmc4LmB/ozJEPSH5obw0jXFr/AGv0W/5MMWmaYd7UpZZ8fY7RldejpB+1878XpLxFK5Z9thnhEL0rS7lZ9TeDGhaZ+2iUwtQKhPOZ3MBeLFVCqugHP3PxHdGAame8cmfYKjdg0RlB3bUhYD856hKD8dvRLt/UekhgmxwSx+FhhK78rEwglCT3B7LHxCd3XhLI8r5DZweeeDap87qH1vjzmR3694s9lys+eSzKpQjJHzp9dcXrnsoOGwgfJdB2N2zO77e6Ri30r8SCULAZxDS7bkkStVg1vm+MBeooizLxryT5Xq3beYEoHg1ncEv1Ips9xuwNe80/LuqmI26QzeWYA9A1S9WbkJhgy4kEdkSzsAGctlhp3wnUpIYUQdSMGV51g30ydPpET42r6ltThAmcm/ol8UrKxPCj/foZlDag+bnoCevEJmJkU00FyzJhRTO6f7zHyv43/XYIubrAj0juIGuH/2zMDWnMUmkDAiFlNCJX+pXKFgyjfBbylWM6LB5mI7UeXVcXTvqRO6q8hS5+7qaEn8m3Lu6ySWvI8b+fzHd0qyAdqtDP2Lm94XzcYBgS32kHZk3SRv7XL3WOztzikQ91Qttpdd3+b13vZETSkYs7CkEjbE2wsZa8zCwxhoyORNv3sR191wrbXNSPLZNRypcXPv2h0x9Fq5395+L1GykAujKkupjw4ekq4RbXB6CzuQfs+79+PL+81zsbOmRNO6vPM2yHstHGkXRnqlp1//69E8nhq6LjdLK+i2h2y/WP45bhBhteGDhFOnMrmEuf9K3mUhwy6VfirRVeffe8pbPfaHlrb7N/gxN5MNeoI4Zk5OIMcOh1thPioiDj1fYCiq2HJhwEywKbilvn4fxXl4uHpacfQ+LBfLpEp8NWalxnW/P4x9zLAXuMi3a5RydJrCrgifddygWJlO5/ZLZa6eHAb4Ji+748r8aD2Z2glwDwlu1O9AcwfTqMXHx/QQelxjwU/eCpy6RFSboTRY8aO1g/srYpa/7Cw3GCV4WgxQuGWffsTKllYiNVxeSD2Q0AFbANlGKGy+BA7Wz3/Pu50y4d3v945DHJmW07WoDiSVxMRC1VM+4euuk84ceN6bevQm/IQM7TLmEYJDIW3BDqH8U3LuGp3d0b+IpbvhsqBIGmYjAlLdK8MF27c8uvvNRWekDB0dzubRGX0Poi+zttrvlGfjyVWNWtMkR3wsWBczq3udyN4Va601zAdK224ddN0wOxqVktArko1xw8KganenWT3xC6stdk5BQxDSg5K9AyYTgBAoH61i0j3xYQ6aUWQWUjrpCP8qkJKxJJexYlJBMSjsQ+y3tuJ9ncSmcU/8k0kCk5RBXPpUrq7aEKnvRJoGp+kTFEZupkJEBq3qv5P7RWll9xSdNcHuxwycIzwRWIZQTn5JPA4SvxL5Xk+DR/XOCXCfxXgV21iBn3kCgmfZQiqIwxhCbHMMb2cH9XJAWL43DS+65Z1D8aDK0szdFVCdkE42DX4WvcqkBxc7h2usls45dSkhVjx2NZRDQU30hsj/x9oBsXpzIXV6NpbgC5erwm2lnE5ZdEoikBsZVUBXIA6zxtrIpqlZk42n2WgV5JVuE0PMrbzEmBU9+LmaHh+5qUYVNNRU1krWKHUV5jvmuh6ytHkDhHw7OMZGCQdM/I7jn7PcamqbAIujxebymfdbkyZiBpyq0hDS8ti48nFZk09SuGIAYELTxKsrauDtISegKSeUFcM0XagXNJYKHAuGFwamYBn7WdIIne7F+SaPzWJrVCgN8yNED0SfHRRvR5/6EUyQlUw33N75ST84uO9QFcua0GhLRRLoKjJHy/g1wVNVeTs7DIFCnnT4tduIgHvqmG3GWBN2P+TcG1OGZPhAsamTgOzfXQvCumAXpCXsPdYp9CZ/9XvW06ts849H8bpIYNb5ktznVujkEIN2rWyq+ajdzTDPtbt/+A4kkfmzYjatCnhVeRQalk6u1ffgNBM+whGzAaFoj37Ktw1gdI8/AEHTPV1mRdLzL82W0kve+P3hyXyay+g3B0fiaUA9j5kOd7gmuPfSsU7QuKCWOQFNkBkxuC0VpL7OJRgfCyFvSqm5eYRazKAbNJoC7f6jQ/evJIea+JDQVdtkjipfG53hmPMnRctDfefayDqj7WGsXpfx3x9I11+7ytr6gULogCWmF/V/Y78WdP4VNLAnA71yfztLCBQcijvIxJdFq8XHByDY/iTN7Xk+6mBOT+CqHZXr1IJFJnUj0+mHBY8rvs/fDRuuOJbRy3SJpoyMaZCWrMFFVeu+D4dgcJOMBzF/dhKj0De+CZrMTCkUMjNACS9smyzGz8U/luVtUfwZklHfGHjaosVq84j+hdKEfbWrFOMKFCbngk4/TK8hXkSKJ/9mqYXusvL3pdALdhwy8EDd43cBHQQqU8pk/HROeJj5c1qBQJXp4lrBDmznjHq7Yk8BGCrRMyAZvSbCejL/cksQOs+y5po1jQXSJF3ZTiFkhxmbcTRKems8Lxz8vmQOMqbMMC7wcTYU87VH3vaDI/xOMNhlTl/gHPQXTjgCrS3Kh6Qe/Ivz57O+qZ4m5Tjb3tZvE7c0jTxgd8XlTWC2MqWYufl7n8juiR5F4NZbUjNOF9RkKaIFvfvDTB7Q0ztxLYPHyT0wc9B8zIkr4j+siQJSyjXAsRI41jkMuMAXgALOPENhlQVjDx+h+PfX/D4HEm5jUpr82+1HtOxzss3Q50YwQZXM7KZEC/8T5uUxESvtoskDFh6eU7hJMRST/T5rA/Ret/+iKLtrjddCdbmsMAHm26cwhEX5Ej2JqEORrjvusom0NE7j1si3C/EOgDQI/etaymxC3iiJoP8AcQiZfjnEklF4nlSw7V7H6ER7FGQ+P6BFcNOURQeeEhKpVN0WzWBaZMnasTPlpY8Al8HqSNh0jTLnWV6z3o+1t7DcmkvJhxBuQo/EmXX3wTTHUx3MKTOiLhZpxvesrR9+d4dF9l6L4GI0vsZu1ey3Ji1Ahj1oaTcrHjrYiX1avWLsHPIaEdYvDL8eeJo+LrfVAJeh6pOXGnFVPdvN1fzSsK5iXfrCnjNjfs+hKmMDE1MK6/mHPw583gumKqkL3QvjMSehIjNsrIIQpeNt3DKt+HLZg9fUs97PCoZ7IQ+bFpnvMtLcDz19Jd6NXSV1k/UieDkIeerhPHjkEvNK3UJ7C9+5dNoBupP/ahoKMqMSGhlc4B4ESgblD/gwkv6p04xGOhLQpVbdOH0gq93VKhgBL36y5szllT6lotRLou4Z4amETQ7YTTApndvwrTKtyoX6zo/3Ki0EJqtYT7jB8R1q6O6slClPVNW7PWbn1Ac888Xd4OFN9RoELA0SxvjqJrvjEs5SO4HvA91zL3hS1rRFJD7e/RaALhMFfN4rpEsb5TNZQGkZgE+DGomfXtF1FridwFgMpeK28BS5fCE14oVJCSyMFsWT1LVAFjOKlD6SXB0Ve3Ry15whzV88zaCXbVeJ4yVU4CE46q7b9abwHsvTftSqHA29kTQfuVWHp8XSIBfwMviknzab153/z+S76yl6CEKUcD5gqi3iC++5oAl6ZQqMXpEyopdFRCHM767Mj34vWOY18XjXB98ow/VNQ625FkE4S6UEfL3fg8phMO1ucrAlGQae2y456EGVLQzo6ANtJgIWkMn5yCGl7Mfv/QUulgAESMLsmAwGG0+jnb40uWgsgqeSYv7jw0kYTR/1+Bt9hnF+qQ6jaNZIPWnRs+b1ydaFWo3PrAKN1q+g+73fDuYiW5Fz8ZNSEaucusZrvVz9fIrJSlkxMfpf/VDGxRibwKOH6ekoz4FFcUUZmif4EV1qIIRH//undY++HVKUgZymb2ADmJ+bGT+f59iWZaewSJ2uxZ1i6ZGYWOKSE/bqCBH83D044vEZ/ZLXOnsguGkINDgQuFoe7diwDw3gS//A8b2aLzQ7W8ntpgdbnxkMYNGn/ms+DQcMalwFMGQpyVvyMS5g287+Y4xRSpuP/frgUkHFZEXwUc09prvGFdDy3Pc3KJgyKQrEQ4W5hQd95R43EZkrya1eiWTs/7KgrRfWx/9+C8Q6WFiiDiz68jA5KNqsA7BJZOLx69oQj+kAkbJ8aQEQ/J4I44zD4XdA7IKNyqD7Fj4u2ppoa7iJM19Jk/Q8EQjvVXVcUBlIg3UYLZh92qYWgzr889OipiSbvNqaiIo+schzUKpiAL4rlLk3mqvgTBb6z4pv/PeQ05e6M+TV1Qvd18KfJXyJd+L5Mjx29mGww9jYf6pUlmOqULpt2axxUzj19/6/UahrIvg4EeRlOLgp49Nk6tNPHdxUwZ7pglVGh5fcO1tLfzONslv4N+oS7tixy/OfH/dH6YPr9fhbbXT+Gd3Ml1YEtZefRyuXxV5YM2OHWYz8CuVwrai9CMhSHMmpN5XbWhsEVQWVwfYueunthqMyNBVKQGDAqVrY8tMkh2j1LZKXV/Fn1tIOqDilgVGE/WCEbFwu0sSVP+mvyRqj4ivTLA7ew5w5rjx4x5oorF+twcHNNdVzFG4InrGMvqN8+mPxqRI+n+KsX6j7IIsYJYcJFbEFm6QIdW764vmZyLqCTIXdHcn4vGitJnfeE9okTvUGCRquGr6WthE7bLfq1bBnJUrNRpRF0Pl+/rvgWWkMfUZI0Uy1pYIb7/jMyKQbVVl7cM5PtALB3r0z/V8fHVGU1cpHOh33RX+mGze2CFb6kPJTWCIL2DkDpFFujWPzbtatrdTbqtSrqV29kBDuF84bhMMgKayPikZlbkeHmAq07s/gQyfpAJSioK7LcD8DSaATvbaFhZZnt5NE6j2iwPoY12PvDqHv3pA4C6x6T7X2gm2QJIMYUAsXnUR0LM63DBH4ffUXR1XOXwiBaDxC7TQUj158wu61Y10VRxC42SQZu1x5UIwVb3c6Fe3aqYzoPrM8N1QlqxYJEJjWyAvp0MEhzyvlN1UcJZZzwMpC2gAOkNECfEX6w47IlQtsVvfP9QkLGvu5Ig5U/R7hiCxvmGIA4x+YgPHWnmQb60ppK665jce+Er0+pyr+pndkpFhIc3ei4e1eixWhuaB+Qm3yNNWsM3DQVVrSCBzvE3joXdDxCyZDXNlWwfKjNGblGSWHYF8wdOHj2Pkq4vZydpBGuvGiJpe10ZCDbhNy1C9SRt+vAzVm1S8KEyqAaQXEYodkLJ13TtAZPdPKHta4C8SZTuvmGVb4iuAwUNfADbMYmmraAdEXnsuGmWmUZJmAiO7WdmCDMG5Fz1PIKCu3esipolbIhXXNhXgx+BYRQxxZpEfZe4lPb8Ixr1+ubLkJVny3VGO6zaXb1BU9MEuSpJ9IZh1OLx8qpCwgWumaoOg9NqEQHC56+8+N+XkYs4GVlbuTnCQjL+kYkSdVbg6HYl4HwyUjkzPzeFivlabOqRMIhVUdLKh3kfB/Al2+zb6rf/wf5QN24g7+yC130IS+K4+mZACSySiM68BNO6+rNzuIfLNrCHgfz1so+LJuPLCIJPlFDrDqVc3zQijbl5ClU+82r03R4NfFv41gOc9Hrq6+zLMQk6xT2c4JGKb7byosagUmrym1R2vfd7kw3UT/KqiI7dirf9DxWv+KbgaY9fLkH+OEDUYJklmNfh4srxX2I5g1J20Z+cNSZi9p0vIWt/sczJKdBSX8209WQSn0kPadWCh6XnMA8hwdZGlf2MkrkNoB2qYXHlLsaAfQ6XZQ+EUwZtEFwVfLQuckUWC773JXtb+VpH3kXN4ELe8H4Ze2S/B3w86YGxiNP4whuNP+S2LUqKIqStflhZ0wB4+nRepTD+iMUSuqWDmjnmz+06rJbXFI9Iny6DiD5N3BqVxOGvMd0SK11uuusWygtL6DDKLBIXHiXSeMxQ/Cl5u0o9RiEaDZhjtxr4M7zvfziutCxWNdFD5QL1/jJwV3nYkXYN5HwtByezKsM1TZKnoVv4xBvOp6wBc+4cZIguud/ZQyTmvNF3bi0LR2bhBMUPSg2kcDD5rGjrhYFKClKPmTtXuwoTpZbdw/hS5IdIJDCS5Jbh4AeTdi0ck3yARYNbizTOkDb5MzuC+YpSrf4zktGnSGHcpthyDJLJmc2liiYdNhGFWvddVYmDf5ZmtporVa3DCFgdq3HY0UyYIovszS1Bo20v0kd84uT1UDn+KRGEj5VUR/AftKe8Kc1PmUkfuucswuX/GFtnJnNhek+HTSnNcIx24CtwaDohS883h/0J2wc2SNkApsKKdEF5aRzGburbMRMGC6e9SoKk2Ohkd2HP/DUAVs3WS8PGNWKu5SO32r1BbL7buNLL2TDBKM2nWjJIUPLckfnk6urhcMTMmtZwpHXCB5jWmtaZpRpmArqBGqoT8UldU4T8/qhNYa7UxaiTJDrnO6T38u8Nn4SsWlcdRxFXNJ19jNygG04G6pXXbo+lUTE+6cdKneKgJNRJtw2nhv34aDUQHgHKHShJvS4+tY2iXjn/6GeahL3rqtxA7CgQva5UCKdlsUz1RIKmEWo0uA7JfgZclWSYu1b8YN4go9xYBXs8sehyD39oYc7g1gRuRc6RfsgV0nu1Y6JiZq0KS8NEw3xCN4Lb3kXtJ7fTzC6Ht2W8Q9Er/MwhThqA8ERkzBikmcKH5TGSXvPCyZJmhRx0wj57XBYs3kYSNxJlncJcA8E9nOp1O8Ri24Q16v8tFy4f07jH452JPgnjiCDKskq/+H6oZi2rhTCFKy4GGVB8tOIAJSpuMOBDBt2MjGOkc6VeSbKdLmkd00a4JbsQjLctJxwWI1UjW1vTZjn6do4byJbykPintEWS6dstn36MfsGFe0RXnOdkOOcgNdjGiU20ZJzG3GPZbr2OiWHGQIQ0Bfelg6NO0s1UjfeWhzMJb2oy1P7DEnq8nlzNkkQZPP6bV5/V/GV1IuxlNR8h3E7mRKCigNufxyzEFf72hV7TrLnVxlDYvfYaXBhkEuCdUQ8HiQhy2BN9IZLiygwvOTmGxy+Ag1e95CyCCbgGnO9lX8prdkiCh7DxcPxrgxlWwFx6NtkAlS9QDLiqr0HTFVw+v5QHOGifbZvZTvHbGxozmfuqF01tO+1tWFcrwY6OwzBhFbQcTvGAXzAucEZ44y9cGUpdBgwJKswl6VHnJttkWCkK/PKAX42Mu96DzxdKtEnhaA3yP7hcdj4CkG/UZSmcgqJXOZ0ypxbW1kDoxuv5YHBUR2jqmOzSJSp784qmmypl3XO7OdL8fr/HaxD+ko4wU86kBDdWB2ktgkXl1ldCa8bqPVZ6Or3YCJ6vCTL0D06DhK7qfaJswXx1p4VYHnijAcvlXNf/oafq4fdFRFahbgA3/YqUxcDosGbojP2WuK4XESD4g1APyvGgTphhbK4NiaqZVXdBFk0nCwe86RUoagTO1oH2nA/cz/cW3I9XQc8lyc3zp5W5iUSVfRxNJLprup19tjECuVGbN8mNJ7i4Pq8HyebLgJxk2/79cW/IV+39WZhSz/3jHJfyzosrGneiROmEofxW1yRwSAIULjK6iii52h7ehZCljB2vCqz5Pw283XA/kdgitAV96TfWZSOJL89WUfkIvc4iardeegEYB7cm1xjy2dyxc9Umochhc7fT110h3E9LZcAXQ408Hmi7p0OXCtE0wE1HZSTUTqBYpNDYjlMIqBctAn7X25ZYc/Is7bkn03ll4NaGM5OhB2Smi+JyT4LYeRs8tvFkVm06QEL8qC2KHLMr582HgVCg92SgqGAvYofjT29wCAzo3aF1s2DJEG42UFXg8yfYiy+Zkw6hbb969Lh/CrO4uCkbYBb9UtHZCoFEDbwdpaykRShB4YdaZoohuXsSn4oO+NKoiBXczeQwSo2w7gbSYxkHlDTJiwFdHDLwUqFE7z5cBGc4kSb0KnKMglUGnZG+M55hVtZP2LVffSI8UwwioXIV6u5wBardNd7MIm6KlJQI8fXXNa0SB3VLhV3XEZLUMpYSUFhzRvZLQOQlPztP7gp2i3ugI3xynyhOd31deA9PvPhp7QXJlFGaveqHaDxRxi/0IFK0pjijB9bhJeYqqVgvb9eqQYLGiuPEplQSms0Yhh3jAFQTPSWSgfgkHTo5FdIJfr+qKUZc7watq09QRWVSc8CVcbMZfONqRs7ROsFzB2axPBohyc3qBb9o3jR1M0/s/E4vJqKKDmS7NeR62wm2KhY4Bt3IbRJzUgjWv9O7G94WiuhzT5IeWxossVZikP6O3rQFKSKAPbNwn/cpuJP4NunmJcPF/WqPw13cmPbkK0Svz9rCvRCxdU8mTm/krtoafV2iZJaOrE1cw6ZkhbVJOk0722Xl/qvha+u9XfBrNd1xK/e1sAkJCv6tuGEwnFr0GpaP44M31oxolY1dPAXh0uj3vJUjggU8wrRiMhwwKoH153/Lm5gtpSR00KsKNgw5QwhTthotlcB6Pndn8ga3dJifQWkcOoS0BM9Tdr7VAQAmMPnnIBGnsGEFJ0gHMcsfDjO+pVwVAtv4YKQft1HEsrGqukQep88GeIPWmYVzwoTYPQuVMgr+zVQObR4kwQuvPi9tgnEOU1CTGelCIGIp/qlAJB/24MI7HaQEilDDc5TmTXJxfUZ+zm598rm1xODgDqr6tJD39vcMfr4z0fTTB/NGlF7Vqoc6L2oVjh0qxDVtb2SJBPcHTQivNkBPnd2Laf75agG/q8O25fV0an28yqRZE9G2nJUlvKZ84AGy4p4u16KdeMlqUAecPnDbHg75uYOkbSAw+lltkNGfEzNxOD+mjfMhlZprg5LggG4f6H7rp87/jSY5WVOOzMDatIDEdVLUqZ0oaPIf69+iT2ngzz9UMAMre77fYJrMuQvxrYNukMGQjHXTcxiOTDekt0AxhXskSbzBt6rllbkx7cp0T8mvkCdVGQWLUTDBva5CkO0wV9sron/Mw0fKjur8F8gy6Gsjyr2fFz+LIwNTuR6wlqP+8++UNm8HtaMZ/vx5WJIQ61/fCiPfGAXtDRRNbhcGR3mXfK6TlYUkI7hx3YDUSG56aR/CSGUOmVTHO7lbA/e1Sqbi/dfYUPnb5NwXBcG03JfsH7n3vbHXNTVroE0FXUZpoYz7iCFQSVzC0INli4OBJwyo4arexcYP8ofyvKYObda7JXjmN5uyQrdMlsfOTqyHN5lBlx+Qdu+rMsoEd6iBg55D+opIsnrCIUTbhNOzZXJK+Br7qan6pO9L7p9fOOxk4qM1hNwtDqPEq4lO2cXlPfvCXNhmhS4RfOApFVldAldP7TWcTv5fjNQxrt0KCcn4Flj0KbPyOcYFkjstGCxb9qyy1IaJhQFcAfLSd72u92bQLhcg4H8dMZ733MAUTd/6BBce4tX6xY6rYhR/IUIx3s7K6iC6xHPjL0Srnd6SqU818tLmvXdI94uRrI64DQG04Xb5QeCYJ7rO6NhzgxPdZMzHH6hrxi1qsizPaRDpnPPpeDmGjBl0Vksy9LDarNjb4YmDPjYbBkTd41d1bPHw/eUJRe2hcQKKijMJT/rGUOWCsziMQB8w4HUsrihuK0d8tnTeizSqIaRbiWl476vAqa+Q8f9PTIibP7N+RHvJXt4fojc3qupw8BzIaXanysYbGjVUeB/X0MmlO2X5VZqSRcHSkVjphQ1F8Hubh22pemTUloIpR1MCKuFQYf5MoOHWt5uZU8UgelhekEoCKAaIIXjXEVAH32kas/E8pvTjcMYvGoUBCZm8P+DxwqggGUACq9PRo/hgD9onEAeMS94A+pZcokrqCJM5yvTZ/BwftojVuQvgsfFkHvQ/a652pyECIu7dUByEHPem2zJ5+XcfDkYsNWqAW+7r4dWcfFZRPAVV0n31beh1sYXw9QzcTCFP7YicYvIopgdEBDdxCVwUppgABqrTZMzQ8EWxZFt32+YcAzc6SEhf9xRrCQo/lVrKUdcd72PHBC7zRmNngVX+3otOvG4ICjaJwzwTNHwmMn916elQ2fIz7OlbxCANN2j2Bx+yDngdcJmyZfzBdX5DieDs1KSN0oBTp6YcgeSTcBuzu35z3GhUl4b14HRS7yKmVCcAp0CKyxSqrNzNYYlYhKWhxxNkf2efZ43eibrucXHv5TnhC9XLS9ZzebzDz6NrQS28ZDv0H8NNTZp81/BUNJizGezkSklGF/9nGy1dW9Yr+4INrCCceUzWHCttV/1XY6teCQafQ3hsipjHuqJsnKUIhWVsRk2a4XnJiohqw4xtR6isJOTI8pm9JtkaTuuEPdfio7T75y5B6C2w3Slz3Wqk9CxFJbaEgntlFwuEdt7glLMXwCnDFnpTtDQEWnQdYFP/kUl+WuoVgHylPC1gIpJ+S2iWuCARuFRMPhjZImwJ6F1JH7Z+Rp4bPs2pZ9OiOh26ZAKXLNMS1riyHWOl5PKaG28go8eaOoKjkljXZuWtUq0ZbPIICuFD67ahY2XIBfYK+ubAetL3GgL/2dG9zWCPPvlwnMw/YJ2KtltsBK9Fu3Ul6ZOkp4h5LTYELzD+8g6++ggBxiPGC2QBIWlEnw9oDTQSEVdQ8qBKyW8wxYQ1Fi6uDaKE3hwiXsfK4BTrpfuUETteyYdNYwh0IIeZr3gnR3/i60S1c3dseaDQrNLpcigvRlFsaLTVKGeDlU+mCTMb7iLuByagyOc+CUNJfJIH4Hc3HcYjWcyPFQtxaQCnRKbQC5TDE+E+4d3kJdi9POkvR0vx6zVUg/EigeCXuXTYgHrz4gjKy6OC6r+6PbL/5uSxDhyaEsTQsCKAnnFID5pfcNvPojJ0MavottDFoJOO7gwf59ojCS35S9AF28JvWinUIOXZVMnT/vwwzomAqdEVBdyjk08PiJtPsi6lf+xj+eoh3Nm5sRzCQoi7AVAfdtmn4Hbgi9kamJc2JhIrN7JONROKRFM9KD513hrFYEpp7ykpBv9BdC3Bd1swbb+glrPYsqgQPESt7jKgjmWUBy+KSLKeadD8nLKWLTgM4Woo3NvXZKPZRltEUN9y6kaCqrcMxEf/A/7LH1t4Ycfljyt64FoGx3wiLNZpG6edWejxgMvWFHGG0S4JlnrEE72PqMx22BghbPWMvI3cfnAUHziXw0Vp+PBsyvKE+ygHDqlzm2JvGlNjmursxiyJ+rQkJqVwSqv0W6loefB5gVnmz0ngc7+Gc3DrBJ3cE3s/xjYVtSf6uzEqlBQDD8ekyO8Ar2QJXGGfMCyVZoW9qcvnGTuH1L2PzDQnf1PdUFe6YP+kddTIcYkQXEAPxFmzXR2x62bANDO/tEkTc1pwCxUXbK+1xRWDAmWGJjyauM7IMDGRh6wHbr0TjEaI3n/FXwRu8RmmBzLp4YUCMMxNRokYBe4Dn6kfi8vptVDNiRfiY560Um3s0Uqpu0ytIGuARY+Cs6UwK2mbzcE+To0M/w42TXdIXaQbjxq9DaSQVKoaVpAQ6rWJdxej8X2CkSdugplH67k2Nhlzc1+Bj2V5p0y2zPmCqsD5cnjOFg4zuf4W9i8/HZMb71q3bU3h4a0Wbw/WLDskxI57E1ALdFLLoNdB9HM2BQb3tSpPRDsiCrXOTC27CpUGnuN+tfNSDnUID2FOfnHwx5JTJ4dX7OI2jTrkPLn9Xf6M9bsFPwBwqPLpDlExyzweH7qp5yPXcrhSSP92DqaC8PTJnClaBMafmNvhOp4MSv/hmyaiCP5ZsAZ6lCx6KbdZo0i6MhhoEBZUj1CoHjXsXaBc3XI73amabRuoqKDR1ggvbXo+vtASF7lhz6TC9k127sOFRpK8RT+UQNKmPa1MuiGvznKhKGOBtaOT4J5jFUnp3u51w6PeNejSsfq9+cedfW6EoICQH0z6rFSgkaKDR2OKnIfwUJ/NSTQwX7AVrchruOni7HdXEkXE7AEM9h/ruNofcY9XsEA1dzAxXnW3RPUnILv8X7j3k56ETizYq+pfKhgNFJ5yydLFvhKs7AYGFsdhuowQCAmz3IiRt9omK+eWCSVqAcxNOmU97iv69qAiaSwYky8TCsil60UmOyrpaZ4USwBtLwaHIxYETnvPXTzdqSRkBSWiF7cjoBvCgomrlMCL7eXvvq2uE1Jq6BM6KCqvmNn06OxhhL4WFZS1RfKVPwR9XM+esjWKwfaPlcQtiQCYamFi8jj/PYrV+cICisGgtWxgy+8zaXlzz2IK6GRD+MwTEU4rwKtKTxVAet2zMI1TKSW4XOqhisYuh9XXk3VZdW1RbjvC/HRubyhdl20OxGY0qyIqpX6aeLdoA4Bz+N6MXybM2/8izrF8Ds6tX2UnQ1NjgMOHQkSz1FC7q1Vzu8eOEt7riaIzwaFavmJZ+n/YB2whHJ5fOn5HQpnhz9e+pCWgCoFcMgYMkvnDA0rREMLYFrUIa55Fkwet9lyz5TxUsaiOqrNrbyaWjSc+s2xMydyBo/tG9+6tvgHLa18A4K96IvnIZSrXhIJwj0INreZClTw65QMvmlylYWGUwEw1z8YMAQPHKp8vshzV57PnfpaD53FbfUvuZaFF8akSdt88ztwwhFq19kk4QROpBYNZpWXt41RYGmcxyMnbKJzaF8yHgpo/pdM+TVUpgSMC3TWvZUuBCSUQBV+Fzb2YXtsQgAx6Bf1jqxXsMtD5qyMjgSjRHGGY7BGSZ+VZAyNNGBJ4jnRKzcR3/qfDmzLwN9Wez3/BDeatSDE9ySvK9e33rLPljTQKrOwIYmINpKAygc46JnaDfS3zamnpkqQCtNd8/fvaZPUxggV6ZEdFYk+BGdEefeUZKA/3m0+eLg34MgKuqiKyelB2DPMEFmwcah3oCWxn+aQggn0yzWS4gwNG9BhpdKk7pzLJVPJSHvoyKqOGslFDTafdXz9bJfSk4l2T+Oi1ow9BU6CWXhSRgdY3K0QambVnFL86S9ZS1KaUrU3MOBTQQdJwFI8u42sXh0bCwZAToexSbHX36Rsz74lnKBMPRxbVI2W27e6N9kwG5mgn3obLsT8RYpHubNoF58ejON5h8gciIKl6Rj+qqlITCD9ON3YzCQwcnZ03JoIKgolUeiE6p5cpQGgHl/5NxwrfGX5idYYT/uv4sNpROfTB/Z4IBhIX2x6vK1/9omBXUE8371ckIFjrfRysh4SXwGQu4omCKNZKFbXY19hqV4ICwR+NLEQywusRuIscYAKonliCoEUq3tnunyfI+hjT4np59yRlTOERjb90ZNBUbsOpVby8F57vA4Ry3eQ1d1n7sK9rsrtNOBARixgwt+jWGEdg08P+z9zlzxNDxWXzeZLdXIs7WO9JNnVbs/jRsNShHbKARtlSD9OcFCbgmi+h7S4DVLkKPNT7jjl1xFu8NQqQ0Suh9/uTa1w24MQ6tNLAa41I68chqmvzhOhIC2Bgj4ceVHe14LT2JYSPkaAXsLL5zXCLBW2CqWDRPMiDCJeRzA56+fduSXBmcHfL12OnlVUzvv5mop0kg5Ex93Nw4UYbHvmYM4FjA8QvsmHtZrOMkRktX94XBsqOf6SrsiflpDMIetdiNOF3SOMPtnNyJ1OCziSHQwB/032hEPYrv/7VSbmKrAhDAaaiii/pjbG2io60f2ASQStavEd52K5iPXNemmVFn/ouBOZwEmfkDoOhHU8J50Cp7okYdWawqDZIX2pLsT5lcy/BCpciyeclaSeYrgkWVuvoru8bXOkJKPkW9HFCTvxC8NvAITSu5ddSAetGdOv7M3MyeNCRLTrjb2DzNIrZsohOqK6DmNcclzSJnDbRLPKMWGDvU2yQs7l5Lqf892DP/LAeZJS3Wa/YJP9D1leZ7VSzPYfXuLy6mALCnVFZMkD5qUZjay0uqNnXI6HbEUhJMeeXvQ/ekKdr0i9XHneJnkWgirkaBlLIvRHMcCG+mPr0Rvf47XLgNt60/ZtZncILN9g/urLXmiqU0rbwgG5oubxGioJgKgIG2AVVYm+fV5fneh2h4Pn13j0tqNKfmAPobfyHsokXZSQ9aBWCjiBTbgMGNLLHVK3oGHXgKxjTZh2ExGlbo104PwJUy5HzzTSeNbECoz9Pte2qzwie7IzHVuXU+xyFA4ZD5Gl5meUhj4ydqyWuxXt046qvj70D1wQbmC1vdfVhqvT8UkW9Jmu4WlLLF07Eg7wjELYX5GNPYPQWGx5guaULwyjgfO4LV+Dr9HdejfO+BzrwGmV1LC6u6P7JT6r956dpEETa20NpzPXWNEedeIKWLNoS/Y5gXr0l/cjjkbKHYFO1mabTF8IglZfge0X6q7h2MYhHq2FUcj0ubiuI45oE+vOowsjdwTe/HDOPiIacm1NlG0MiHgV0wWIwlglUiGnm3jfyifRXP5Nhz2Py4ilZmKZX/EkDPfz5kvChEfazSLXGKHE6K9NRpeUYRtWec7PQ3q8ZO/8AzAyaF+E+22QgRww5KsS8e0AKYkwJaq1cuY0x/WIFHYjX60eiEv3JBn3e5a7ogrcurJBbtwtjGpmegsUYSJBxu/gnFS1Ez6yWPuFObePOxMYwQ7I8mIeLMfXxMArL9YCgugUJiPvc7LmVW/LsWr0LmuncxxY9OT9jtL5f9C790FXrrGqlB2b8cuqHhl4HBNM82WJSQniNSuGEyVukK6iysHrJeETlyVTviF6ga3cGcDECtADV76kmO85k8LbQNNdwoa6YnLGD+KuraEH6OjAnLDOauNrFDREUC4lVmt/sWc6foZsMvfYiWk7T9+qe1SyxCca9mfcJ4YgifzBclZbyT0Nu9Tqjnyym8AAsMdnX5NRedPq36VJcCeDX10ShoKl0+vNmERJsnkDLsfD/Z6SHi0TNQXnJ9NyumulauLKfQjldoIV6TpvpXKDM3QEeXrnTdLTWzRbxYBlRfCkJiX7K1sgU4mbokkcpGiPt6+eK/KQKAWqX2+PVTlZgiDWdlSkpff+Nw9S6tuwe/Y25w/sKb+pZN6oKlJka5pKsXOkMEdE4V31U3KjwT8hMja+3U5GrtaPxzileqj8xB/nC8Y6c9+swNnYIiI9crB/88dhxHgjgdrqPobMcRaVwzUSj5Q43P282ek6b1Or/Re0EP/K5dyC7WOz5nnQgXOvIac8OjjMIG6f7sdwFKQEiTq/P3mt5FiVbDn+ujV190Phsd2C30xaKYQntjU5ruOP7CaYQj291vvuVumXg7Rj/FjBfUgma559LUoN8Rec/AfVcC6EEYQ2/84V8S6kTvCjhDTi7LWgAJE13O+cB8q402SNns+6mnNB63AOlR9ZwHgxMC5q3ejwJAaP045r1Im/wamUZKzkMarKAhPtSdp7q81N2Mq63V33rSfH2+lbCkwH+xQ1EHHzq1og+CLPjWfua9uGgBqVeckQcbEhQlXRdQ5KocP5pJfFrLfDhtjPagn09vQvxePw1FdBuBhEGhZaHr7quJ/5+/kpxluxpBe+UDSeMOg9Z9XQy/XEvjvZeGxr1spWr4Mq1OZxk4L3p7GdPPGaMYzt+0Zj84AiO8rvGDBtY/gWgzYpJw34HjM50Zi2b8N6AjQXY2N/OcmkLFM7+ZUzP0EEG5o5Dir3ClSKmLSuVAiDxo3zydUNibL4LQ3yceK374LWPhKel8EpESPSddfdIJy3ySotQd1TIjPcCX+v/QTbDWzB+8HMsfb07o1Nfxw6+6M2MqoQuVTU4YxvgQ1LI1rzml6pLtX2I2XXbXxBULaGelwAidKuQg+hydPqEsvFUrVivn2H45KMC/jOdeHPLRClQdxaYEsmIlOaYDME+X9Nz4RcC9m8fOpVsd/kH/HNWm5AyGv3SJjkQLsJVZX9Jn74oytfPAuCQPDUqqY7aYSo42FYJl63l8nGoTb5rmR5+dDpwJo4wP566gf30Psi5dBFwagHE0Ap+Z8WFVWW8eyLj921S4wvj/KBs0fDRZI3a0nxdvGQwmp+qgJJpF1oDqoEVkwtYd70WJ907LYLX9BxnjiutKcSng8em9ssstYJCL+ZQCKMmsWyFR+fQ5fyB/V00hj324Cff1IrGCXeS6nYqrBvjSsNNY98BO/iX8j4CzS/4rdXZtGuuuGGo313KeTxWpjQRq4p2vwZqzKNs043/WE2s85nLQfZYjGGC66lOCt3YctrcWT38BSf5ef7cQ98jfgoeiIpkhHirbi3Gn7aOVS+HXPWxy8G2tUQkhEN7g/Bg6F0dW0MYRRyF5v0EgQylMW70jAiEYXnvQCfeFnGpqJksEJftKHzAHWsxxQb23QoGofDlK1ei4awwtPy0Xmu9UjfdO6GVZMC260A3m5/byov0UaQAGMxdTc4eaVz7nOebQmUlVaxb3SFTiKUbgHqoRBa4j5ur+NI3jiMMdgRT9FMae2qPiavfq2bCRShVN9tw3+mcHeDRZFRrE/RhM+oyAqcwCwmB7C7ltrQWCXkj/6tOfsCTJTROBOy77Da9+DsJQqvY/q0zkSeCTi5DgLeTx0iUjoj1bzjKd04n3JStCjhEO6MoYF9CI84dODbpTWFXzXTQkaxRBviyw9VQossR16LuSxbjRW7ZkYGopLmQZ22VxWCIhRyY3cdO9y5yg+kP2cG9Ckr5/5rF8kSW2+aR7PMoI1BfqgLCrmNYQzt9Yg/I9VkWeehTu/J9t6YlFx/07tZGV2r+qsPV47sN6GdPZIpGHyq620+Z7FECFkNXHHAHOXjKfV2XLDmv6ZwSNz/44jVc2yCuMIPj6O1R7CLjFM42/ErmrDsIDaubFOoKkPndcaiyiyTayVYH7M1+uPoKQepQRHfFlNIEL6a3jU3sqvVm0huKuMvHfU8HryXJx9H0vZCaenC/yk3t/lEnB1tbiMUagGcy2TrTgO0D5ZEv4N7/t7BJ8Nb2U0JnD+FqG/iCoCrjFmlXYOVPPPi1l5n+K0SNWVz3S8uE91G8g6UJGpkn0zXHQH1APaiyy3k47a6BUM8A7K3uEm4IAt/RqrdhnbFoQBGAk70yG0kWh81NK9TqScHKRXtFjUlHo/QScvgwa5ZJNoEHs3tm9kydiYfFd1vA4srcUTjfSJ6ehF7i17Ou4kFL7dbLkhSn6S6uq9EjyaJqh7leyju85CUzqrn0kFxvcZ7S7jQznll/80QVmA45NoVY00zm+tgHRkWqqCudv4Ejg9lLg1c+Z9MkdqdIhgRyunB8KiEOcfHyuSRaN80LOK3Y4A2Uc9F5EatiHpzSIWFOvUFI1h3YMoqco3EgiI5OQKiPm/t1s11JQoPzjWjDgd3s+54pdD8kE/vWUZyNhGMOBnanfpJhzogTuYQjdcBQjymRjZv7OJInK9SDpgqSufDLBWhhJ5ktC+C20bB+HxULiv7bxfO55gMnfgwl3+UwRoLW94osdCmsHKiCo3qKWIqKTH0koi5MyqKlmfEz14hYgdSP83WY9hiR5tFWZmhqqgwR8tDVdCemHCzxL9+nqQiWf8XB4Jps+Slj3bddNxfOZsXLcPp/V/UAMB+29DGEQGl8JHCMTwVJBSQQuwWwepxJxdMCFCYfsMMyRFNkbVVX1FmQUURBehbolVSoUJQHnCWR25fr1EJSgrCuaqZEemMmjPIWS6jx13cq37egwhgJKFEAuT7jvGGEH3onRgoYPWGZkB+KAeL4wmq9vIvO7/dk1O0MpL49bzPIRmh9jQlgx91CZ61UPDIygtC+jEVkJ85T04AdUcZeVFcqttRyds3Ljiohpoj2xNLoE0RdcFIdwKm8ltYOAcdTHBUUw1CKYQJzisldtcIVV57q5TrWTFNiuuq2f8dkC+dcUoo6+L/iAhfRRy2yfN7rJQM4Ol/sZr5aIW1N5cSRRR4IoXhW3Lb45FVjyBap63emVQKNaXFegY76leFb/ATFLZ6is1+oWXA9kAEEc4YA9Vy0C8H6SHCaGJnZ9+sytGJVxblAE8uCAAE0ZueCtvmEmc6Jze5eYf7YF7aXlCR7WzTBiN4Pj/Q0tWZZiLBj/piZ8DZEff9XPWj/+CbHHMHJuKWDvt1/EXSjIySh2ZrnCi9dwNgtErj0Xx858Nt/VWfqCLaAGxh3nLqwPsHDxchb4MUniBB25OBaavMiEjceUWCl2sfcoPf3ZHYjeP2YJdNf6ntNiJCBLS3ifjzE9lMZucUnIpBZwcgL71iessdq8JJzi/yLmXWIv4mfOpphceY5wbo1xWP37FaA2DTB0ZIMWaDTz/L74scglkuFmWJ9a8gFlolUDvzjHK4biM86VDuX8dLJKr1avWsGezOXvR2AJBdoM0R2yqo19QGsjKdz7oXMyCyCPxpigDooZ2FxDuzByrDXIaNcXStyc0DdmYSixQ7xcrY3wb9yJKMlv9rYjEtXV/a5OCzuvLEfxQJwTSmPdncJM5LnnDTIlOimNfouwEWkVUsgZKRQ3+FKvp9iMjMYULin/DAYza87ZpCEgypHjRePv2IOGID6suCICRwTfmXL4ICeLrv29OJtdrLMorjd0qYgNupH2JSnq7kzkQ4johEr607084n9qf753KIj0FfpC1fdg1d0iplclC7pgP4uyzVrX43tkdYGOOPlEjmxOwtHP9ETY5e6Y/Zl18gl6YawQu4xxBt/Fw5N4PXBh6qNEZY//NK+mGH0tMVRnV0m33n8g7gmuubrhpddkGcasVk8WTUUao+RfIB3e2Q3Y7l/usXjvXp//1i2FyL01wUQTAz1HsPkJqL/llMEQYOn/xKu4XQUETb7NUnM8txNcdOF935Q+Lq9sTsT/J2WvXgPuAtvrydGduv0+x5r8tewVpDxBfjC963qRhy4h9ElWiNbu2WN14rZGu3Wcy3SuiVWZMBZ17ZLFXPWiKLhm06E0/fLhk70GI9B3ZoUVj/QQDhk73REM2RdvsB97iPkyP9pw9CM4vT9yFF0+QeQkTPEXT/WNTpqYuaQk9kNK4+USzsI0B9fbx1png6dV5EGKMi5Ik6t1KctC9VepOPbcMWOAwedRDfZBCu22nxOL2BH7ysoqiWvPOC0v/q8PbqbupKCK4WQpYlJFVySJdT36FtHvNtSyxc7X5LPQ8l3HGrR6SA9wbupBrrijk6juVawo/pf494niLmDaL4FuyWXzBhovhFlY5zoktBl9Hs90lanWVmX0QtrScKncUZWCOFZbkDwIrqN1wlhgb+pLwGMoo6NWCmDty+6r6iu0x6t87Wfr7SAnVXCfGws2Xq5MyfXjVuCpbWq4tjZEEKa31pAga1T9/pMiidRZmKET2kNI4tGPzFTOcktTElojzu+Tb+ccTsCbvLiaZmDWtJwt2f8or0cUH6sjK29PU4ztmPkQnECQHc7qkwBPYLCRmNR9bYRg2z0eICYiMfuajnfVKr/L3lJ8YW60pq0JqAQQGFtU/pHSK5AmSFRJJH/QBxT+wyn+Nz9TRd1pMN8Ci6tQTpOzJR9yWGm9g30y142sZTqRmUtmtLdlvdc1UJehJyP51Oc119qOQ1m3I4t05+uaLa/BXxBdXIgKQ+/ma4pOtX88wS5B0UDc2s/B/8s8W09MjAf+9BAgiTNYPBrm7EaXxyo5qISNsw0oKl0hnoC/eUbkY5yogvzw8ENUqL59mq0zSvyb+O63mEJI9fWSE44DFZSQ35DHFxS2/c5gnvc62CffxqswPwHzP/JdO7ajzqM+2y3yHXI7DgVpkFwQ2DyBfumv5qYHnE2njr044lr4+oPh/6kj9LEH0d8xWLGcYX1bXQUoEThWNmvVdXQEIzIPzmIrqZiE+Nyafz8m+mOB99oxSaTFdMjL+mHGU0telHXOFQgR09P7joukZUscOdVPvWfFuvzEBZBTyxOKWrRk8LdwxQcxar0nPyEU9VGDylGwlHgvMA176oWMvcY9UdqpAh7uz5yr4zh+CgBhv9GF+PRokwRfa6RBEoOVlJ867oXfFuDNzMp0MxGIjL5npPZBURWbXp6pk3bD7YdZ13d7oRGiQ811Nd7etYTJVSuwj88pUEo5mkKDFZwIIn+XxE/cdCrWjYxJjudaT1cd1GTBMzWGTNbX1HTJFi+0RIWBk2RtZje01KTzS3L8Vjp+RDaAFaLIp5xOXWhHkkY2NbQXU+PwPYb/LCWxeK/NCcwUueE6pumOTiQ1DWUJ1yL7GbvGTK/7nEd6z1GnqywZzbeJ90fSh2kaCLGu/PxCleuCruuXwDKUfk5mCHlJWV98hu/Qscp5stNajoelmL9gNfmGZ7vnH/4P10iDF/KFi2bsTrGx+WLAT9ZEPU0S/UNL4i66EreOKmbfMY6zoDI5QNkgppMP6AUNF/tg6Nin1ATC91G9UckC4Tj81Hz+xP9sb9Cje5PsmR825WCqT/AWG2dEw0hP5HIWVI1gQp2/beaHH0+lIPwSOdOoMsAyfuo8/WTnVkENX9gy5alRFqy9L4YH+5rYBon59pi9ur3zWs7Dy/98FzD8KzosljjuR5F0Skygft30WxewLkLL+mJbiJnWmIDqiblBZz/uzQb5ERmG+0JzsNvFUr1F95ZRyKx7ZHMybpHOAKPda10pZ7sjLYw1zU2O+4VrRZY8GREVL1N8wWhQLpc93g1q1x8G4U8eHYo8QL1RXk5iMUQDVq6vSCfqazti+a08FBpk8Uct+frtsemO2TTqs1TjCoHZGxopPjKr29CjbGDGVXnp56PanSRz646Xc1zXNnep68S2aW+cf8BfWHT/ezLVBTirICgcVUHIK6ig4yh0DY0ar6J93u6MLyAjNw9nEZWGZjHpGhzLqtpIqC47vgVxWthu1VTDZd6xv+IdP9PzlLRjiRzvvfz0n/lw/A1hwjTjhps98c6/chsHxK718NbCE/hxaquDCpkZWqCWrQ0sbdw3277n5pV1P5Tc8d/+Ym12BbPffNc18LmnFHQbpiUWt3idXwb4JZjDReQX2LDRt7SSBHfuClPnp6+iDrZ/bml3XkgcBmjJLTAlWchqixzgE8F2kgsNH3Yu+SsOeuMA2ucP9m9XHDuI4UrP0Ix2fBAOXBcferWI+kCsZjlO544LlE9EI47CB5rG+t9TcPW/yhCWnQgenvhZiNbYGy98wgZq+YLPoVl6OVDfkKGmRidffyecOZmF3LAghKk0xdZgsX0gjlhml+QS1IEp+P+pU2Mcz6igs8MeG+l3RAcx7rEmKHegy572uYJ1lpeeRYDxluziruuAI7KWdByxEeeMy8CLWXdBXPeYZ1xvJ9DwVjqYe+ak4umi45xMFZCSPGjOzBxXwYiMKXMge7aI09u3esgJNhyq+mOaad+5tCkRIhaqu+kD2BzHwjt15q0rO56XWeEnv6enDLLWUqyrdaeBOY9O9Yasn9VQX6gho0MH3n5BGvcFEWPZpTlbqsrlfu3FgvtPh3U9U0miQc5ucAJPN9ZQrSIjQ7899/SNHyAR6LH3cTmJEzcxwOJcMf4SYeK5N9vlXACvY7UmcpB9fFN1gWWST2wqDEAb+6N00Yfh8v6YJc+xynDLeP7LuESHlhWKgBfdYtcwtGf7IHOfAHRRXQ7RAl4sKX7GzAhyQl3CdfUsns6dENqGJdhLSt9ulusE0AlbnjpQ5F3hlrc385gymADnqZC3xdEm3UtIQNuO1Bcz/AROB/XuhAEfo8mn+8lpKrkOVXrmiPvhuA8bI3warkmvEZJt2ykve5aeynUcWzMNcIFODpGzo+oYkJ9n3CzNffpVGbBSM2OaAcEEUSqoKaCU3pbhb0WG8AOrzyj1s2/h//euXOw8RNWO7gts4AX5/u8rz7CXK05pcCgrNMN6v/FrkMCfacw3MxHZUyyQTpAbnC2bCQv0tBGu5J+xQ6IbK5JPVf3ocJFLMOidlEePjCl7Q8UiIvCM2IOcR6WYJOnxnRtHqGovhDdRIky1twlKi1D1t4QAARCNHAq0fvVjoVOHmJFC5GizB+C4kSHc6NA3sfxLqmPHq+FN4JnhLZ9RVS5RGuzCvJxUZJq9/yLbKU5iWVlKvzWPP+5TSahbpzIU8SniOhajdQppHfOUdQEC1uVTvjifUIr6lq2ZPd/D1vUDtcp+OAjdFuW84dvsAEqDtnGaaUSyA5abHDB4B1l1rY9l5HXWN/ERIZDIZNeisCWpsAff1PTs/5ac+jhjfiHKRz37nzpFXyBaaPYLVQvjFQfk60SrQvd4tNaa1mfMpBASE6pI7k9UGcQEldG2A9NlzvR31Z7EIRGT95DUFJLLVmiUHvC04gYImysiEPzkM/Pw+8pOD0/OhE/aBx8yHd4kl3jXzk17zQcbhuGFZUyF3VRECyY/WIkyUlBNn+TZYNFPH7fayHpMLuSw8T3+vYSKYfKjelRC99nMj1AaCT6faMjSPI/Y0jz5w7c72Na7JxlEEtoFstDGM+NhpLcV1xTIFy4elvAdbXf4zrYS4NnosSrnmqf5vB4OzH299YiMYKKcIXeSTo/KQ8b2ufztT2oABkwKP+t8VPexRHCePQYL55OTXuwMDjj3+WOdJ8MoIzLIDC5Y/y3pnRfl6WWcVFyfRCOuFcyQNi1Jq0xhQKotBjA8aDYBkAn7eq9U8eitdTWohwk+Ax6c+IwdwE/DFE49Pr1IECVYgnxwLlbY30hhbPfXKdJi6OaoG18AXVUV968gjXuPaK2NWbQ2T7lXD6t9MGEgUTWhJyLtgv325Su3hC7mDLPW58moSVzEUQXtzf5WvB/M1+XPz1wv4px6+YOHYOwXvWBjufUm56ItnTp7VR+GaHq8FSCUvdNK8tCm/xm1yn4Sue7rUqiYCTnxPnnJb4RL8Unuw1kUUE2NQ3pafP5Jpv4IBaJbYxSMIR9bSQ/QlZVntOx5wQ/x5ZT/tzw2sm2MVVBdi4pA0agyWmbfAC12ZPkdLPUFfCgV8ZABBc+KF3yRY87zfMXar2Ibt5OK2SOlfeftTWQTf2tk45LyaYmaSSpRTCTjrrEpAorD8WNfLt+QWBCTwmGAJE9vCdR+wi4noEUyypK/lFFBF1mPsozQC28q9mGfSVfNgSGviM+fULoO3TxhNXpSsC8A2y/18pjGwb2quFgOLAGHL3A4G8R1SXEFkb9MZ/DxWb5M8Zc4teLTqv4FNjd1OG4tjWfgbqSpo2W48XQ/Pe65Bfg8sL3vMxD0nVVALCif8rGlPfptOAwo8Vh4kRuUd+yI4KCs9N56KndwYTYuXhqeSq7zihnp2bJa1ZkH97CZoj4MuaZdRpWTSIQ5Y3+GSqFicJ26WWgWNLk8IcSOrJnwzgHzTXhNpMIjK3X2PSDgRLYI0iqt6LYnyJ1KC64wqL3cQZQxThmEFQ1YxSNPzAfoYI8Re7XsA6EuCyqCtg7LKv4K8TfbMnzk3jgkn7TGsGhWApQypIHUeN5J7PKm1OhujDnAGYPF9HZO0+0v3ubxoZOrby17/Ob0XVnXfHEN14E6jMx6LIOHzmhM3OGAYgnm2fh2DqlpvP1Ee0Qj7PlJhneU6K0B0rKegRbEkQmfnJBER9qFI46gxEOtyImEwOq8otbWLNvtjyre0wUavJW814HGoDczm1mU/rjVQZcx+ZDwfzvGRx4ekYO39itzceWOseVDGjAbKOEJRuMIPrS+XwX+p5/zTvuWzQzmKf1Kifke45/hVStxZoja+wpUQMe5snDA/88n7NUnbeVg9MVODgXSPBbxS/OaDrQeiZO3iPAL08Yl4d7SQDeIwE1S4vQWrEuLdiMMSbgIYs6piK1mMBmtRRVXBxEE4zqRxQ7xKQfZd7dZ7fAAk5AVkYfLwgBSnzU7ru7nGZQlOEB7qZ0IkzzpQ/H63IaD5emQqfJGAM6c3UUwlubqLcbgJI8IfB8mC4I79qykRHtdzDo6xS0Xp8McZTI3SA5vknhr2ejx75eXWDgU4whIGkYSVy6WFUWX0QyOUC99Qkhxag6DhR2MbFKGJ9s422Fncv5n0vBPK9LtCrQH5tN7g4yPdzwaEu9TYCcXxkYkZY4GX4UhsOlMGwFrqtm36n0TpEecPzsT2DQ3yaAEyrt4u+Pv46flhaWhGx++GmBsOfevL4KGJ85EdKp0AJV9Mj8nVI4/Mjc39EsEQ77R187vJq2NACTPbRDh8Ncd6mh2iy8Sxx4vn+eVkb/DLxFGiGaYYtvvD26bXxCtXQctuwoHve5iuvi1AXyWVctH6ehdHYk0cXLttgGyUaVb8GKxdPif0QnCgwZG437chpEVx9m4phAm1OZBJAGtMjsjmCl5gCllVCAjbhkvkkngsFwJd6io/kmBU/H0tTgeq/9WQLdxTE1KDOXGE4D3YuEmuefTEqXhxaVFFDGyWM439QhXl+b5Ie1CuYyZSZWT/dUn4G1ZG5ysyqWNXkg1Gl+GLxCydfqYevybW9WL5Z+BX/va7LWPrg5zwFvHvZ8VuqoYvUJ7psUqqnXkc+o7YGTOUg8GrBFI9UryjG1efiU3EE2pRBOnqvHMgosgPIhR4UUZFxIE6P6dADMGn+9S395UyNKk2/kKUdEsRRjpynkrOJ/v5BfP63iIFm1I4/xhlSBZHbm34IZxlfT153ctuAur8Ilp0sKPcFYL8B6ET7jVhRNZnT+lJ8GTrDFs4GTCdU76w2tPAULUYsYBvos9XzTMRmRfESrrpcoAz+Z8TkMA+G1petbH/KPRIYsu0uDatLn2RzfJA0ufQrMfrBKL/bdZQKnRaUdPr/xPY9GqLolMwmzcvtGvVz6W1M2cwQDUvhgMU74+ipqVJCuZ78u+V8E9g0MvHQEmbzFFL6uaj0l6kNkdBF6zMtlEYdxJsL4ISnvRJp0crl6Sx8irQeF+tCLcYkOwJT9kq4ATuJ4p0C9jjj3lSfv0cGC5/R2R3eq74pgqjK17TkYl/PRXe2Um5sdtqOU++a3egfG/Hs5h53AKj1KxhrE1NfjESWKk/S6goRl329j+GllsxMBkhpmpLUB9WEUZmiigEwQgVLxg6ky6vaX6rhndVQ50kzCDNT+6YUTOIfezcQmkR3BFKV5LLKF/w0lfOJW/m650EZcx57WfZmG+fac8kB45sIN84QFxgvKFFTbezSQAFpj5/H/m3UD3zsAssd+mEIw25Y/73rX2zp51sLmH3ki81fFrMdmvYgVZDSta9VXCTDYimmMIMd3ge6uAjr0S3OpneGQ1+6XAQlpwwVqDn+HgGnTAN6K4DMfR2HoV7qYWDqp2V9RHC2F6qasIPvTLGZ78brTzaBofYVGC+QocMAjLN4Unlf2QMCDhqvFv7CDjPWvPnohtkAABfCZOXmkNKh0mgIsDu1byBzthVncbsreS2K46k90wIt32v6il6dH9JjnJNCQGrhz51JaSwt95xkiiyDq35Ge9FQbj+FAb9hyqIJgPznC7mxQssLVoLzNSd/6otleN1KoXt95ubnXWVM/2FbP4WHRuxfC1qHiykNYkOaFo0CriU1egJ/1gbgKhDgaXeRgCqrPNLEH3qfpD/aSX/fYUTUO/izsWXWyBkG4izm6KvSC6KUwZ3GhZRydcv93H4z/58L/W70F6FCY4rQ6Mn5wJC21tI6qi7UsiuWmt7dxtQm29eTa8HtkuP6Oo0S4miwcGJ6Ntz1/UClP9qXUmcN+UcQ5weO8Ny3dZZXwC168gHYvx/nB133JGsPX8a14bV7Y//OPNu/aV5vuqX9bzFua/ItXm7OPE8XMymZP+Q6XMcgJVKZZ5aWDZ3k2WBKXuN0eFs/8bTWnRE+McPFUmef8nEpn9iXC6F0amCYbJe9hIGSK3FJ3m4uZk9wVRw9c6pexrQgfx3B7lAT7JI7wvdurHC3mD2Q9PGjn0sYchjafa0VsED6ngsWnfiq+UeH+6EO9r2vfohbHxG04izWdX8yzcgMHCLA1ZOruWGXN2bwOvG5aXmGq3CHPOv5JcdL1zLxgyt34Fd6ykNjxHmC6YEC9LRPPodJSH9+D+8E1HvIYDj3+bp3VBh2SYVHN1YJ1dBT9ft5MrbCA2m98LCN9MxRjgEwsAZRMbtgth/FnZvZEl2gWW+YWCqZyPVp5Ju5DPSoUPkW4oeNI5yqpUJxx93XdxrlRu2zukCvqyOQxh4AlyjVQA4ckFnJOYB8U6RrYtpj3AN7/P4ne4SdBo3FF7pdmz1XWglIwmHkZjJJchvc1ibhSFqgNdleKa85DJK27NAaAYTPrkrrgPJ2T3T9j6jW5CY8yJsFZyRs2vcfKDOCx02lLImkSbOSDDX4rDCUgLTSWGetTvceNk8BwuQmE2bjdQ9qBrx0SwLyio3AHzq5wFoRBgN9THwoyuJw0KJunUcofMjfX1QkcN3T9uv9uaYiC83BEsuwAImyh/mihGbDwDzBZ38b9BCzySd77mHkMXeuCL9CzNFX6od+9x4jDFAZtrhpIOgDrZ30UoyYcU105sJPOlOBO4rB0QVfNcw68+3pQqjLGh1dDZG2rv4XDocjZArZahLTS7XaO+fsyphdYrRJvSwwwgWI681W/UGkZ74h7RzG7aQI8XejGN/Jk4wE9uvgRKrFqaMaQsuvF06fEjhqwrSLef4mb/heB2LuA3kJHUqbSr4pirzDT29Q1SSR+x1mWhiTgP4YBVPAaM/e7YnTK/xMjGtEI+ZG4n1UK/OzGAhfefMNz19fWu7MZlb8CQvOcvxGsX72JzEMsCC10WayEciV+QML4IC9mh7fOjId+9WM50O6X7LsPjMSQNAi5cL167AIxbw0vJZG9PTTU+m3lNYDWO9alRdPqLc/HHaJT8NJFqIW0pJ2HzyDUQnHF21f3URlkXXRwpDOeiG0VF1tmsDs18Ywb2Zr9dc+ISkmgIw4vsFFHfi7RdbVqR2byJbGBatnoBkuExGnIfxVsMMsFK/iT8QzukWB7kEYjSR3mVf7uwD6yM3/fbOlVj3S9XZPTL76K8XHAhZWie5+bNg0A11Pc3mA8dFnKDudnmQ5EbREBBJ1WIrza5QiTD7EBXTb/DtTB2QXa7Ps9qZNtka5Q8yd257vFg3zrHrn8WBQzELWSNEoTtkdBzXGxmW/YL6QYyfnoyfhnuWZALDqLwOwye/zEbjAUWgJH3bzGhdArCbTerTStKRhFAjrgd/R10rK7/DNHCJCJCyCf70NaIn1Lzmd7sfZkI8X7tdi64Y9wYyj7SDCysifFae+iueMrg4L/IOK/79NSk4xYnEOj/VLZaadrQF/NxlvTPtWYPk5kxYbf5rtg7k/++aXVDF8xlep029Ljx6UCpUsaz5PRFFp8XhiYE+tb1N4+eh1GUHmf+5y5EVr1WlEx6rcXaY3bpRIQRAok8TfXkt5ggu1PDEptwVOCBAU/ra7kKWVaf82Cq868Ekyk+hprxM7oFwlfaVvo5xtI/NKe0dYsNLeL5UoQbfXE6+E8U/hVCdUWQGqFhQDhlbKJdktbF8f/5dufQ2EmUOdTRPKgQb+eU8+K5bxZ88wO7bi+uo5w+U/dP7S/0xSxUgV9DnK4LfOcqXv4bxCPLnPOGxNDUoOOhxAORaTWCROECfveQKtbKVSzgQZ2VXkcFUMfLp39hN1+lWEimXBqzcJTvaxG/nRPcCkCBUH+qXbkY5s0vVrn/ZyWAY7k8NYibLCNbW5tH5frW+VgQETIlayWBnvaU+x6k+9+S78YMFqSQeQTWUbtkNmAiSPgCdj7oEKP+HAgrXPI6RaPP1m8NT0FhpbcKINVOsrblV8W1w3Xj5PtxBuc0Nst6lajqBJOqLnVMwHHZs65yQaquX0EAKNRT/jGyWFn8ZZh1p4Ll1ags9hWjD6zDmNViMlwTHAMQVkQXKIYGVbzDFpcSm1AcUUyKauFsZH6jMrnxp/SfwJz52uQc+JgRTEvFZxqAuPJADgHkw3moZEYPU9D5jySrixSYK5pxd/saWbE6Fy+qJPOXb17r+T+2sJwC2wIyhVff58Ga8Anpgm9bAIN5iYOqy0wn22vP6M3l12NWhUTLvRuIfS1S99bQQ07OEnQ0qEO5V+YNtcjl5MYxwAXqajDLAIPPieRS+2j/8A/Spn28TmmnW9x8p06GWeGeiWA37UkOA1UgY6HjdeC+zUbKmkmIBG/w2u5oYteJob79fs3ujzymorN8A3HvRiyB7SDgCbCckWv0nvo25GmYhefO+LpS/truPlF1twPSVjZCACiF9tVdb3yVKaMqRsyLMhQEwKjuM8db3Mtc9cDvHtkgPVIRxSbgifcsZqwoUnlGd1qGd0xXI9E2D3ekq6iR4VvFaiLN47aP44TpHV2or8p+CyPTozxDQJlosBr3n6p6lyRhPDfaw0HonAdA2LxNJkSf+FvbLcQql7WEqe31mraMhKYCXtsPgVNc6oYLy6AL4EqUFhQEQCzjcOq0d9voAPp6Omyr8994tWB0IaI0sSplgSnwnWN55Z35g3ZGCkxJan+5gbHbSX59Rle8ULTH8UQnpE/8Vd8CXYTB1D2efgA36H/61H/i61QftkYWNu++YJkOoAfOePp98DFe5HWdZg/2L2Byv6r+phPZL0oJnO0mywSDR+diBhPdNkWStW+pfTGz0dLwKAbd+kxpPG/Tidto1giY5fh0AS6G7W+DygCC0S6HFaPtz0ikcoxEAsMcvVoFhN8EFADVFul4KS3i0XmViFKaXoeEe8JiA+pSmq7UFNKI8NysFy8rrO82hRXbSz/A33Q9OD0NbSiy7mZnA4ejCZSmcpdC7kAcdhEk8EL0YlsRsV7bJc+ao7PUJwDs2HCHwvj8BcgLT10sDGpY6RKYmSYw3/TvAeeFWtVAyWjI/WNazdr/nhwqVNYAJsSpEf8pEaoaq1dh/0W6S4X6CU3n8r8kn/d728PPyG8OnG/gYM3TIi5sdg2QNBbmUpgmN693/iM7xeNloWh+0Sd7iFmp9GWSah+FAy4cLvLB400Pbc8eYj42NNe7jIDXKybnAks4JnGQTOlFeqseDSxKSrdVINAYP9pCENfm1FOfob8j1x5BDEn+PxiPXp+YZ/BX7TnqB4FHXjfTgRvOGLjO0Q03VFgrAqaQxHCd0ztmkgfh5NCN2G7qNM4X+loY81hyHC8HomoGgo4Nn3j1BMEZ+xvPfBowJ1z7ZccqkIW1wvJjvLPtwNp4xfsLg+nQY5iEjZ0YNrV8vnGjBZYYI7abHvRXkgmaERNxlD5qE9o51UMGF6V5Sx+4tnRTzfoNxlv6+1I1lLtMhuHW8LJJXE37c5n2ZdM1Vw1NWuIJUbqVg2V7Co0nCx1i91Za35uHTsqx0pW100OPNZM+f4iNTw/fxQc43tQLKwhTGQ+UeVM/7KM/AiUyr8AvZvW2wkXaC/Ux6LCPtzCS8AUXi7t8udS+2z+nYyZtcYNQFtP77YXy666YaimHhYo5lsKbcJMvrP5Vez8FAn4oiglB5b871cRZHfSOAmT37pu9oe3UHfb8NnkfOwcvuaghar26+lnbhBSRso6kCQOKfyfHFnrCWHxGtONaBRVC2Kp0ivTtD871qb82/Mm7rx60NDM++LiPfFIkeOUL7PhGQ4/hFSLcXP4mUJpEuj/TBYNXmefRow8F/YCiK73DXOY3VO7M5T52sADGCVcj2Uh+Caert8vHutBPb5DyLO8Xyl0LGkNenqOXWWUns24CBTcZ294E0FcWSWDO1BpEgWkRXSHDMtmsTU8UxCVlfL+1jI5J0hdgAs+TNOOwP0yrRYKKPXZGAhpzPhV6Ft0XiUKtV+nmDlCDCWrbrasCYm9v7Pg1BujW2v4GFDjr1DpDqzFyHTXocO0h20myaFaNNWU5vhTg9CmxH1BqX4fVlNn3kPyp2Y9jOJHUBlJ3C8v3J+sBdEwPcGnIXFJQ7SAqq200YTbf/PtLaMXUXmfL+8f0NS1WpS/Y3scGgrWkQh3VNXA+BBIWZjl32uZpd2cMhw7D2LUtj7406Lsverbdt2hu+RRlOrpklt5CqYAq3AxBUzoMPZlG69rcCDUPw7Lsw2K6Ox2kLh+A+LpF97jlocIwKU0lM3JaNQnIZy2r7ccq4gftIFWWJ4sxm+e2YP9iRsF45J2wO+su1pTfUugh1bSfLEOntXi9tRLqI1TS7hJSmbX/+3NlkjNZpLrOjgXgrfP2EDcIrKNN8bSdVzoGMzBQfnq75iUzgyNtNOwCE6DapRVgPx5TTlRZ3LCClkqLP8F7Kz81zWEIywIYvtrdm0Ee5Fp63yIqFRfL4KbreIEpz6mMK4k2yCD9iDGZNcfLJsXg1gkuIStNuSsi1D2bcrUh6bhpjKSy4uH9Zkp3n7qOcixTmxulAV1jPS+8ZFNCCTBsxEtxOMDcRMlUPrmZ7wlczF0ba+bwFWeAuy67Gzb82/niZKjr/Pqy8SfkgsH0TwCbCen3CVVd2oe9AB6C6bv3KsZOAq/usx2JdCIt1svpPfGwcUo4AYuLne1k/8xDxQMqgNjMuhYfxiSP9ASfU/JSn6jcDLn4hejYDQ9LO8BmDaYwbwE+Rc2rZRmLinglq02hCR2snTjXuCaZ4TpQoh03MONKQIjBt+x/I6mq49Kpi202yPMM+Lg1X9jVseZM08u5OCCM8ofHOBWZrJ4x+jyRPqn2cX7rsJwnAo2UNCSXYsEPdQAfEMaIvOdJJc8/Xeb0q1hEahMsMHMPwTmgiW6ImXBgkD1CT3143n2w5JvJsKZdQ3fvAstTUwPkD5AEFzHPJeU9z7d4NdgEnLvqaxXR+J2fVL2bFbSx3jVxgtyny1WpsWilCR6BEuLD4F8bpesT03ZAgDrSOGxnofv3UA3nXnsWNHS7oRBSlzGYj5DV1XB3f+WEAC/Qhy2IraadyL5GmaHaZadCzISzvZ6/hPvrs2phnPeD/ZZGjrKi1OpIjVCySa7bUAuV/MV6PaaLUe7vxyd7dxRLLqgWzsCpBgsOsOhQZlXD0DuX7YhOkJes9ZEAjd+MZXjYGeDGYEae1k4H6w7yPJur0f5GKUGccOeBOQdt6jsXXhJAp9yt5SDkmjEBk5vZ3FZ7UafTed2Rfc7CjmiVkFO//RCbGbgWWvNnnW9KgfJDNZL9Ei3fN1TShZrvrSJexmaeihh5S4WZM8NdPjoKOkXxgDl2JvGR/iS3HR7ABeaLpfsYY56RUvTgP3z2AITfzL52FZmX77+533qMuCmjD/iOpJF/48rhrVp5G6+X+k+H3b+wlx173X6BcE7G3VJruQ4AqYHcKSlx6sEbm30pdpcUhcisOo7Oee1JbuQtChJ+h70dsZZPoq1iaJcOtObPxt/ki8RbYY920fTGXL0jbXaXws+W8rT8W+Fk0+uM5nDzT1TnnM1apdelO3NOBwFhcfjWlE5udVtOPjBmBH5KQ8szxfHErgrvMoWetChsYPEH8tyI/ZhswRNmZ4B09pvojRirzhu0rLd9wyXyhz6vaJ+qm6DqPXbF4LyMAd8C+EyXT38Poaisuo+Ki+pbQZbPD0BB4RSFZlk/CW7sz1JRqLpESD/RrAgAWXbFJZ19ZjiFD70CuAqwFQB8x0606fdQT4sxRW8YQZWtIjpH3T0lSyRhZVqP3D/qb5izADlO+A94Mjn/wN93U7wbpffmxej13c8RrgpGTC9zE7pIxtWsjnVSGuGoVqF4Xzr4Ho2+VoAzJLQZWKhiHOcVQCGAh/sI7OtLtllgqWD3v80z0187rdvBRRLAL4tLQmA1Al0CtrXZ7/nhKLaZaBcqMaHlQoZKlSqrbekvg9BZnx+dUZdk4M2DohbXrPZIg3OgRHXj7tNKCIjYznJI228LH3U3RvHNxp8UPWQ4KsXi9PUDcuKE+JDce0ywd2R9TytA3KugfD82u7uph5VHK5eGmNJ6jIYgNcggnD2bS44sHRTdVsNfjiFhYpBnBit3B8QBlNZkpE0Grm/EWgo7WQQ8NE2LFMNachLH2VYO7BfWWwMO/v6sIiM9gV6zYtVao939ilQ//Hpv/pLHVPZdo/Qre5s2y6WoBGei6Qr9N/Nm1Nf4AOwaGDKlmvuqDbDNryOGDTDBUiflyxs9hmOHg+tjTFJ0ss+Wi6jEgznnMPxDGu+/r/6j0xu3jWR0te0aKNs+I176Mas2vBnP0Xh1q0d3Oa4V3DSydy9S5ueXFpwpbJcrJIJyfu76omH3EaV7mYYqc4yCW3ZqIN9aeTlp84bLABrZA7wshgxxxvsSk/TOPvfWvEu7njHRIUU1Wwq2uQFxE2/EhWZjnC4oDDC953xCa/V4jREIm4aITwl5OxJBYNTppsqW22i5Y5guuOYRj8qIk7iKxlWMe8kOv0BRiUNa9s/xLRyVBK0y6mSYyr2lxP39cwf/1dPVCLVSvNerQ/AcfJv8WihqdSAnXYI2mcj1cS3lHKRJ+GjJ/ctIMnntqhq1uMkQCRjh4HwOeJuh8XZUizvsslUq0iWyneoIijVgnRQfJ0O15ntS1ppRW/UkX7xh7oYjaI/Yo4WX4WNdA1kJ9AvORuwlM9Kza6rJ2JDlpTZcNkwo4fM2uexbjrBJ6fPjKUOPIAsLt1Uu87hEk8/1zllOLacStemIxpESYhAXMxZ/m88x4ZQIVkqoxl7xFNkDXJ1KilLRPyvd+a5NPx7PH+bss7x4HMAF30ZyiyoAkTLIZ5Q+d23xsNN6p5AaDgrAgjIvJ6Yx4aDWJvTukrg8OQElhFV88Ly85/4jnsLMhc80yJIDdb1ih/DdCGh9cBLIWLce1aHTE3xSUbsDQkAdiiL5y3qg8ee9KUQqHLk3NEmz5aCLsjH7v951Sq+VqFHuPBEnAoSi+yInZZM59NZd7IOxTxMGt1WFGqNlXOk9QBhvwxnJpCIegEfp7F38OMGRb0yZrsBf0dLQ/pHpqD30VbvQEL/fgf6UJ+HD6pM+xt44C7lccn2Z9eyAraZ+EpsbIgJmcu1oEk6TYlzPAfsho0nzMr44nJ6t92SRjJe5FaIVZplrZszI7wHjerBEJhjPVpghqNO04dfiAgkoeDg/1vKwYsgK7qyjESbfNumaGbjjU6IdiI54nU/cIKvBvvzHySmq7yMZ2+d4K/6lI6JS/0ECHYHW38yvgqYCPL4jel89oFybJuxOtLhgTyJ/VA21yRrSqUHgGOAkoUWUxizRjyzuf5Vrg8FFP8deyCcDhIGkgyc3mJJr/zMe4niavu0CCdim+kzrdCRoanmHiDRGyMgE74tPJpD2z9WYiaPitt6RzcAM9Gcs0FLiosHwKB+MyHlRNhaie5Fd1J+3nSo7TE+xu5cRSNkmLy/gawwgoiE3obMYtULDgMaKWyBaEVh0TXQJUYvUTiCLLyy3KEuDcDv9EbauUGftjFDFtHQGv0iRkbhNHPGfQN5NQEWlZ4zrcmzXUHhN0X+dmVBzoZpyxBuYYnWHkIQwR19mt+4bK8zakvmMwwb37oUX7AvXKkXKiNMMpmg5xfM0FnmHTW3KAQp13yt/OiB0EhnZ6yKH0J7uZQykPS6jIq9tRTKGdfrCEW/Ifw4PuV/k2u1tksR/i2JiUeA50CFBQdCUhlG3nT/aab8QmSPC9urJP2yJSYlgcehmQIwsifU18SIBpq1Yn7tNbqIQVcTmOu/0TMgLbXOxqO08BTKUQ7rCOYr3umb++0grIB0dYlQ347EWoEkaTjLlpj5Wbwq/VcnxAhBkb0qHk3sXk4rvKacwxhHwd0A7kaIDYKdE4hI/yG7kd3WRSbC6b6JWUu+WWvCREbH9xZEsmfP4F7We4JnQWe0uSmBGGpkXW5nSln7oSe+pbVQYgE5BLEumHktGYEuq2+XL2u78+jxVeFtp0PUhzpF4AOW5bTJZo9sVLapftrpx4xaIN7wrPEeq0AHKGfj/rStV1SJmkGn8sfXBBhWi/2I3Jy+YBKtcsmB9gGcDyx5RqqknjFQk5vPkSvdddkR3lJp62rXf9YGpBu0urvsyrq9PtvDIy9gMyn4J7YoJkgS7m4g8U+BqiR6Osir309G88lYQlDwZDiDKOxN8QFS+ZWbSRA+ENlVXjsO86SAInb0687UHE11Z89m1mEdtecf3FCa4dQpDKCQ6tcUs6q3oqNqcUoonXc2njcvfkseDg6cdN6m5Sa+2d51OW1MkSn0zZU0GoUoZJ7qs7odTl1nWQ1W2HBNfQveeZBIiPxfx5lKOEPRAj+YYoMv3qEMhjJo/nSJHJxbEiSRHE54e7bq/meKTaJwVMj9EDoSq+wF2YHyVw47mgKiN5GR4yckXne8rt4UBcxK73RiI8s1Rx4bLN5QiGAsJ30a8QZVWfSZQreO1CwtKVeQzZzvzLADxZnmsHJMWoPGRTYaXRW0FrlC6DENt0f4d7iQi51s2eGh+a6VUfejvxhTli5f/MNEUeHQXfsJCgvb84Itc1UfAaZItb73wcvzqcc4cteBN5YnhWOxY7fEy2X4rgepkKgLgU3DY0NCBBpk7y3ZfvcYcJPG3d0V9YCdIFiX6QNHPmru7GvsNlbEDkl3Ks73fCQda0DZdXazAkO7P3KzluUSfRPKXQ1f3S7LwhZXyXxJBak9dU9cCbFSxEu/ovTHpsFU0b6kUGK0SEwRopUZhKGwBi8sgJHgrLGJJxgEZnvDeHLlRCn8TI4FhB7s+JryScbD2Q7uXyAL1nX9T39oSm5EabjMth/ZTZjs4covS4VOBJFP07bX79tBKMbNXdqH+1CyKzaeR9YMytHGBGbaHdbYaeHAixaEniKlWyx+V8gbBJZeQNstmLUzkbJBYEpeba095GfGUJEpuVa92cpgXwWFC75oZnYkVRLDp0E6J3SzzkDqO49qwOpyuxO43DCotMfrQ/Y2oZdvm0WlGT4rO21jfVFZnaX13Q+nZ4nVnVIoCwxxNg7tr9esfTWGEHArzxOZCBpcBIOjJtt25oMC8EnBSaoxwtgsPZf2kG0iLTeZvGHslTYqsFEIC/gJ+GMi6zAwYFCZ600Oh9RlPlE/XvEEQBhh1wR61soZgxqAkicYHdB+RUwTcr8YjUNiWkfRStQr4gkvhnNUc88YjS8dbRMVD5Bs+1JzMxQq23lBMIB1YZRyei4wH0PHOsRmLbuj1D5wmPPb+eHbuNbKClhO0ASRF8ZS4N1NEEOelwLIunoNjch6nMQweb8b2/eggG8NoLgBM92JsfDOCt8v861daw+laFfcJyU4OBwiVUpERAArmx0ixKAq2/PV9P5wADe1nxvmlPth8O8PwK1v7MZpLJbJXYYyy14SntaUkAN3CJOHnIpMpuzr/BurCYo28yRk0ch1Qg858jTIxgLCX1ISPH3AGTiEfcTbhYQTxnNU+i9w+IpBklb2S0m/15PSbV/WszqhzIDfs7/Nr+Ov+E2NFt7aCt8/QkVux4luVQgZYf4Cjth+KAvNdMsoL208nOC4goo8TlRnx07qvADkCbo+ZN83CHjHmnwxsYUE17uMehP0Iiuxh+l023DBnSMDwJrPWVsfkumFcJRMMPv22U6eJheiqBFkq5fvaGqBYDb1tpL3jJvCbqVUG//IoFBHqXaztZ38aCymciJrl+N/7wRF6K0PrxUJEGd34FarVf5zgt5G3DxTAiYAyGV7xvE6gMi+rMTnKdkyAy7ZSRNJGxNzD43+SmatPNPulqPfnG+Rmb6VfV7FLB4KPUz1XqBFnCwhAAwi3kGLGqOYLW98cpDRNrolXdYj1Sz23FtTmWIwfcu/9A+iDyn8i4Q6vmY5T5sMCnHZ9IFVHg0kk4BPlJvBg+2EDEPw0QPFoTxKOv/Wd7ZPsSdrb791HRpQ/i96BHlYoOF9gIwZuF979hO0EBon5Q/bS4QzizYRfsVFwo7ZVMqAQU8Kg9tjgMhfYH/s2mbbx7AeqT8Z+poJ+e2qvVFeuQiiLiwehlB7RZzAFgeK8v+bKo5uaq8aqwK+rFiFoiPv0vTBV9W5akKhOM7IB0O17BkFfg/EAIcZOz9Qsmz//nC1IbN6ci8C/ntL3JCPv/NSDV8njPz9yk7i60e4vZtF9oiaDtRvObs8hSUcfr27eOSEcf64xnIB+w6fIadzlR9pzI6oDaVqZXBRSXMM2vOGjv9Cuyyeih18DNK4ugQKBmjq1Fbn92CMLkem3PyGrakaAX2qbzRfxcijWRB7zXPdtDPTJz/jbkoMHarP1OAWCjx9hh4Jlvkrtzeio30w1C/5ykB5lNR+mB1uOhVlPqmGyE7Mm/Shy76ECw2c1UfNSFJJIIw3LPkilaMy011tV3D1qz1aMrtuO30B1zbEgxnFrBluWDzaZg55VWcku0LwFgQhYcs7N9UGk3VQymD+FW/q304yfMjwsMUEEbeEJMvb7fWub+T6aSEDyBjS39LKvijUFbdQ0ySdYOG5RksAy1c+E6XAYgcgOb/aZFvowFBjaGTU0E+o0UzFgaEmMu03CFJ75mBYIADPKCf0n9m6f4Ww19FlVqibYQHcTvyAfewFiPEe67L67v8rkYd82QvTfp89DRdI/b4d+Xo1QBF1zIgLC3D8WvaGPjfijCJ9c93zWGxMrHuzxMU7+uC+zko5j1lYFfBSY8YnukQkQ9d+Xw2Vlqr/7Z8fpVP4/nRglLD0+YvTcKmcEkwx1GuSTKTViL14i3EzLMJD/rJpDHzrGMlw+BSb8r+XxXJO28B5P7UnCpgYAZjoB6FCkFtAr3s3QC+0hffhTwYTSayO4SGPbank9S+1t4gomAKGsuLPsdhnf4ouRWYOntoY+bFXtvBOXzHwTH5bLagRsT5445BCGF2ddQsQFV5fvGXxJ0AErJ8987Rv0Gh0t3632V8+ULBDVbEkoSHvjBv1COzm3tms0qG7WBBxMMlrj76CTgIOT2Q9RxrNwq76tWY06tSDTaazoWXEO2I6p/5s+ypoWBj4xCq7DFcgX35ZL1pLiEK709gV2xgHXGxBif0DcQtjXU+Q1eRJxn2a+EXcDm5kRZKPGF62dQ2NiQIeU1W+UxRw9XYl2c4rc9+JlBxm8CEqI4eZXBD+kphEe/EdvRTwBcXQKX6ikHu0UYL3QEkKWGDLrvVoFxCtc5FhCDAp3zI7qUDh4L4ytleLmZjZXGsSswslxsEdxX8pb3cTDfkuCuVg5zcKHhOvE6F++WQ4pIteDmrcvAYU5YsZfwdJTn7f7c7AmnVRfHTqaTs9UJNeFuwJd+ucgz4TtqDoQgQgQOZF2uVFKLmkG/6FNizaBCUHmN0BJDGjo4/K25iV+TWn77iSmgMu8fW0Z5Z3OSMENA1MZaBBK7gf5BOMRzaaq+6nLDpHLlNBxQG+nxeUmUt/HWBDyjFT7rfwjIUnMAgsK2niSt1XZ89KaHVKDXCC7Eqt53Itj/RAqzj2no494B3XqjUI9eJHyC9dSCqbKlP6DGObe9Pq8hlvIkLNpJ87gTs8iujQmQVUItenoHFBRq/8WdQUy3rq/PwEmf7SVFC1SLIlhbGer1EgJYU3+Ovpg5TnMaapdHGdNfK46D/x/tki4FTAzzjGVY+XTP4cX07BPoEsivtBAKHMGn4IUl5BW+M/t5DazGtQDIQ5R8B1KGEjwanexyhfIsHwUgEVqhEb0oqde2IgX3s7swyEYBtx8kNfRVBPai8zDlMoclF5WhqLRaj2wvPCRfw0Cu7FGmL/l/f3PhIz1zKt5BuncZZysXyQGaz0g6q+9YJ0ChiOWZvchWwgh6qfJVmHmH5l4snPofJOj8t8kJde9e3bbT5bOkzoztuUPB0YZIQb68R8fhygftDOJ6xOl38MAs4LUrgokaQkXu8/Jy0oPoY7FJZlsix9y8CQcdntTOK//AYbskZM9FtJva0Nd9avG+rUEaKn0nGMN4SuoOfoYZhiQnBt1e96L0DovoF+Ae2ktsJvIsSpTzF42qjFu0p+tCa2sIm3cwICVyoGcL3P0KacTNfENCkMXV/MVBuIZOTTiml45ncMZsNGTTgu7cGKpMz+L++mfxdqa40OqL5AAJzIBvUrUosdapXOcHFQLhCBVL22gCn2VOKFZIDTo/bcbpgR5o6QLwjHpRv97qZGrAA3aBmoH7v+UBk2tZfG/MKXg+PMxw1kuX2aqg/9cqOgMrGNiPupnGD3C5LUCglhMQCZAv4OPs3NKZISttpVFqajySz4WeDEQerNuts0QpWnpaNX/+3wshqwRIc83dM1908dBaP9+4VTHffr4Wy3dRrT6zdlMFB2IucElje945o5KqE+Tsoif0sh0kbLSFsnQf01MF2sXcW2fzKTLaGxIUlKLm1nJe/JjL0c7/2XpJKIJ6P3I2EbRZbSHEKqU2KSrlAwI2eZSjfaPDX8Lk+5XUyhoS8gHuurdjCND1TKm3n4O2ypTqtPFPFJd1ba6qgR11Iuk4F5HIFAK4p4GGpweTZIUrN1zjEToL/b7YrsAsvXlBRa16e3yhprzZu6khTasDnYiKW+MO2gR1p55akRwnZwybN9txsDHZIKMComxKZxnqx6ux7bb/XLrjrmiwu3V0Fb+I25EiOYSQf2Wap6mO5XhnBb8ZFtNv0PMJBmnukmHWPvAx8daa5JHUreYWIdsASc1g9QyU83XHECx9bETi3JIEMRLluqOoDUiEWYtx3eScPuAY1/L3wGwOHEzevjM6kcvpOBLMNNodFvq/xpN0iSY6xabapGokxO3ASv5uDSCFDbxAxhMwnnkwTXkxAhU+rqWk89bSOe99hOTolfniQ8QAzhvJH8x0rrx+MNSt5aTVAf4NwrCGqlPc6y2AoBj9J1nl2+iZwetsTWqDxaRrJUz544kAZzFe1UWSc7J9qyQnSJmup1j6yKSMhEsq3iZtwqW6JEAp0y89PN8COVVSXzFpYSPlQyeADN1PT/IZsRHeUBe5ZhaFRnVbCzzzj96XqbMMzyYGwt7ooQm279fYw50JfrNRI2W+2ImOYqAr4ZPg7QqHhUFzqtnwMcx9MjaFvdmr/OW3HZlNc0MnRZqKh+StUUuuIEewLdL/vIdYNr4PJAWhizSHT4Ye4PIHxsondyF5hmI9jOEm3xpMRCa/HkBsk56oTEtOv8MAke4prwXBUgkwgimplhzjAFMBt9U12Zzexac59Yq0Y+lW6sRc+dNXXveq6kTQJdKRShELPdcIVuA4jFrWllZYx3RvFOUqUsb9yOnrUZDqNDz/oZZqMGKNnaxi+W68OfSFruWOJLLbvsRPMZKthAXEupywtf3IElOpKZsa8r3ji6YuweL2A4ksnI7hZd/xKLq1MNM3tiSluNSzlCGCuklhI5SLyehbPvF282MheJTrCZXjaZPTZJz8rztMtQHZe5kA9jElaZYmnopYqQENSEzWiYfACkuhNSt5gtzBDjVg1UYTrDPDFFw6KNfvzQJcZ6WHtcYMpEvgoCyhI7mNnTNwDVS0MacakL3Ttf8i4Ben4bnaz1q/HST/oivKXZZNdgBRSJ5rWZz+3aSDAaQhlP8aG6DjWQyao/2vxy5amZ8UlDVvfnGGm+CLP4nrsHVBjmYYk7lZe4Kky7Kx7t0coBsiOsgonVEmIr6YFp6kHXkFJLuC8NhL5SONmA95xDkZIeufeRv2zUlaAplrJBrrc95clcEbXrYpfw+mghdwTFgHwkMuIeb/y1+whO5KvRM3t+HPk48acQK93vc3/Hqdw1q750USJKJ1MdNGUDMy1gQPg0AQTg/yBg1t35SMe2JoIFOaxDo8rxiuVG+YK02gNunDPaF00hhwJRtn5Rho1m08ys1dct2tKO7GAx5QR5LkbkGj1WWol//GwHEClN7kqHO9eKs1EHdV64o2nnb6ZCO7SsLQ/rlowqK6pGgsYjCR3wjxMXdInlgVMjbiHOwaa24fIssLJ/3b06qKU9Bpi0YwmV8CMVNgg96d1e/zHD1TPhtHjG/WoS4s3r0QX7MTOeLRBJZqwJsjDTYND4rZSPfAwSgtTecZdZaoeWArk4PzQTG9FxgJlhcZKysPlSGc+M6kL7sX+zcXHpRSzqebL3SV6YKrg+a+N6lLaqck0RDkCjrHZoYffXfAyzIbXaVqfNRn700gKlQ32/3sXESNBoy61mmfeEtNKtmfmmD+UGQ9A0WcAhsMwx5Cu9o0up5qksAYM/GvS9QdpBLOn9KDiGaCvjgo0DetIXWHJByXQjUzW16BILd+BnusKpbeaXbqZcAeGn5H63MH6xSR1UA0ZE1PzJ9yg1XUjlH8/8Zwloi1P26eY7V2RQ7DpUXuieorwytzsVTHv7ErIl3WupNaSrUDcQcO11khxAD+ST1PbA4gyJVqsUaNa7V3kOVMpywbmerWCa+NLwc/CDYAoWNlKr/yAIoK6tp8nybMZdfmzi7IFZDN90wJbqVEfTujoP6AvYdouEc8aObs82cUtCQ5/JoHi10eWU9NnHzDNpUC9BYXrLIziuuzKoJFJgvblY+fmF7rGlX3rK2gI6fQph6gyDzeb6GvbkVPK1fV01IEmg6QCtw6vB4cLpwPqpBCC3DA3Q4+PjM927aaE+ZxhYygOl/qNBkXa3XzeBrD75qYt5RaZ3h4p1P9ysIJf4HjDNvDIt6wwQ2R5F0t+ne6k9UZCC6BYhwlAw1QH2wdvO2e8FbiE0CaMNVwv+GmAgmfymgv7qDpmefpDBwf5DRGrK+UveYW/5/Zrg0GnXrVsRlAukistfgZpd4fMM8mH9ELlhPa3Os3fVTppNy1+ET3iqoSc0b3Ax/PP7eCDIUv3+piq8+I5zXBJmW+uh8g1AT5BLn3ZXFv1CnOy7m4VylPaQqtKXpfebvjhJnPmRDwUVxdd0ZuEpFBpMlB4k1fa1L+tVTNLqjtkkav/WFRePPspaauWWgs+DEhcIz7T3O7rcrxOHcwxnmXkmQt0W2jLI9mrA8vBsHfLlua9E5pdO6EAxfQL8XDl5ynxkzsYqr9f1oJcQiDhMf9UK1EC6fFv6SPjUr8cw93NFiCdGxTdNWMtL7BHh7+uFC2x0C5qnYmUNqYxtcLHKWN51fadzuPy2jVxup7AM3HKWp+uvoNE0SMQp6GgO+POG+clAgRGLLn/FEKCEI9/dGNK5kpDmxGuXe8MrLLmCQjAFtFsAls0f+nTXGtQZghKO/hn7xwtQALU3W4SHcacJazoFbDe8NjIn968CCUwA+TuQhgkYSRtC+OBluk+hhBC6rRtcV7+6q7b2jZZklEsCajeJ1YHa+L4ulNIExrYanYiOXpLlgJ5NU7KG10nGIoRSxL88wq96WXow6U4pDf0kNf48ejIY9sY9ySgfnJP3smj/E0h5VtD8zm6GiBonZEwZ/4O6CxJ5xTZz0li3+r0XY3jFKQpMqzky00LOdvPkkuCa12If+gl1Osn9DGWRg/DmVHyeYx6eqpv+g88Vgq+4GgJny2GeSktjEbwxhD6xhNjTUM1abOG+Kr03t5LnTSc/Xw0dL8VyZEo5vHJTh+To70+r6s+yWc5iPa2RPKMcCHXAgpWigAO2NswGwrFG6NTKEf7nVetqFyESGhl+C7XdicGoUOyELNoQ9FnpObyEqYQ/q5jqQfilE5r6HwbulErYuxM7G5BGifOMfzotBCYo/Y9euTNu2Ohvyln3Idl9xES7srVhzn2GAWk2gg500hOxmD46T89JpSNFR5YJNTkdboXa2UZ4GvXinv+TdDAak19F+GqveNcZnRPEYEF/xmH2EVlMrysSjPxE2SSLkHw1uwmEGoRTAjK2VNX4/IeaHQNxTP5MymJ0aVkjiwJI9bute/7UF4l80tnTnlKxebMxyAxf5aHXFq5yjAKC+U4MLo7rVCKx3G+DsHZDzsTmv+s6Oslze/Utixz/AIwDNGm+84dbJItWUbUUO7tCFZoZVaN9tmevPbFJwtxAgO5npSliRyUaohxMVJkYw0AAZ+ISNaFP1GXsUF8kjc+NG2clpCHOMCsgKMRSAncyoH/AHN9rdyjddVD09K9N1kljkPQNr9JMFfyiUwhdiBeq13jCX6IEpm3mvKyhcToLvSbhx6VLnYoIAt08rFF/Vje1R+59ns++rpCAsb9dwiw+ZH54EeFQ82sMKb3QU1da7JBp6Bqtx83xKNLtgMdY5VWi6PKHnxOczZ3LJA3ZhZmtVJAOf/QBmKNQk5Tfp3mtwVtkfh5wgONo+IkJIrijUJj5sDh0WQTRJGRFfFfNt5ngGKowSSoY08cZeZyzR1VZR9s3DGGGnaf87TDIbulP1WE7YjqmL4NFHrFnY78NQInrT5mIW6Lo9YfJWzZ21ihvJovXblLUs/fNjOmTNW49c+dDA/dEQWqpZWBVXibyCzMDfFIELYbrexlZDm8mCHK+sFnF59n4+4DZtuh3owGLywmL/l6ASplHFpSwQj0RveRYMtWGDkifaWqqjj+60qceJmC6b6wMKqpso3829rncBIJdMV9zazdmemKsDlV+CEBHNb6DwUKTv23K+3IElfxlz6uNOBXKbhbXNunWF7S/NVkjqXTmnZ3zCppN8MGXO2yxToih/yml6w4wXX3/DKCrezBiowdbFRDqGATHzVjwE4cjfMF1Y6oXUfF/Z7wdKwuYXja55YjtkWqjSCTHxtghQACqzFwmGmXYq+NStX9adMivGD8QaUpYXsSB8VFPnOy2oB1VdFfTV7nXIxHmsEK0VpUtiGrBdND/aTLR8wv6SlfTOV2gfaHWoJb1EkqJzT2iT7oLAXdHL4pEjQFGhLRYIYGt0QUPPnK1HJnhcqeB2g3PyMdMrF/vvolIxsFzfl2Nu9aVGOu+iHJWMu2Jyr0nh6qc7tCRJdly0Ga8lSE9YI07VxwrCD0gIq1y5xcK2fmSp7kQlr2BQYTcNR5GUrSIL0VhXjikrsH+WFtCpfbATx0H66jw0OZ0nZCbOq4HCEJZqHLJlO23GYpLqv8c/jF6FWbnLk42u6oJpNo8LMbrMP4MjytclXrP0pfBNpTVmR05GczteDfes0LoIiNLbAQ4RsMUXC1ALU6IfgiUVKEn6IZZ9+EBM96XooQ+aREm1ADoZgHHhJN+zhRbR3mg8rhIt9eM/qvpqMYaFQEqUoG9pqgaWv1dQ10MTPgEkMgB44qn73FddDmmUWO6+LKTA9BTMsgmWRinA4KQ4HortGgIa66MKsYbOP7KlBDRdpY61yDLdHo3jC32La4sVOI1laIc3cYmsAnqOq3kNm6ckC53Hij0LoYRXPDrneLTuqRqftjA+qLuGf0HZPogkYKxIhR1vnHdVqQrwHBelMjW6Qg/Sl2+yGOCGEybywvLcdhSvB5XmQUfrpYsnUYJQKZps1CTlm+IJa86+UKPbTbl/mA/QBacNuNpPLXS9cbmpFozzJhw4CTMTo52xWxvYuI0tATpZ7+no9A3HmaNG6q0P1VuLVhe7mAV7TVfuYy2Q6FIdwPT+Se61ZuTED0bnEhaSUjbmjIlR0YRJ59S1/wXsRFlKsjbNvtUj8QXVumO2lcnzNa9zo4DZgbcc2XRWsV46dBmaZnbdAGi2S2IVu0WCgUCV9ybL7YwkeyKkDKhz0UwpnnavfjEyQ459ULwZZvOCiH3Vyj0RFWYdMjTt0bCLD/6l78nZMAJKhRXPFeDpvQ3fO+7kZ7y884kWbXOCfmrpFBXxTppZs76a7uWSZNt7qPvjFtLhK7qGhTTeNptzCXyM06hpwWeBhpmFRdXJ2a7gUXiOCO9siyVlHf4xbGSgA3hvyvXh5S0udjeG+M2BNfH4BQgDO2ZpMhxp3cCPhiEU3enm997aWSauF5Rgu/qYQYtbHVDqz8xQwGcieRlDrvu1kP5rEkG7L5PtC0Zlpnpdxi9F18Icqk2y6mgv7dQbtZfWKmfrKP3vO40qsKmUhX7lt+Fw7Qds9PtP8/MUqLh7SkMf8v9xnKRP0i0mlCdbK+tCzAQEBturqOTxYN8s61/Ga7inBVI8fUBjJtRhCitVDZtcos1hVu9DivpPPSM+Fp7wj5VcdUWOpXB3/8ShnhimCI4Kda+XuvhO+s5qHNsQZqxIbfPsk/r1MXGCkCU3cspiCD+qgEkTE7vFY2BGDUeOFDCNhlpK8OHTXKJ5ICUMalnhlwU1JK7++cMkDPozNM6mKj/i69KWEG2lAjrMyTFPswDDGtNPCgKjP0TPWnFpffUJ6PaduMEbE9+E4EQwLir1REWbA4nuaNHbZ5C2Kr6djWBinban2VBmyr7d0LmoQrqVWRXz4YWBGfPtSqAd7voZelH6+LcZ0Go9fM53yyMk8e9I9vVKUMa+K6gGwPHMhfvdZs1ZDZIFVtMOaxsLjSIMJ+SC137sq6AFPDszuXMjUgrSCVreNkaUphWh5pB8A7YdUcO9MWepDhftxtYyhl2ERuRwzgTxDuBFhtuXhdg2dujES+xan760LD7gDrixwTcc/BtkwYOkn3fGAnBu2HVsEym2ySV+Gl4KCLdxmYNYWW1ZdgIedkWViGzv4NkrnQKlFQopSsaPVqOB/BBGeZlTGZIPd1U7ywG3K0KrbDPnCQsP2QY2YPLAv4ZM+gOAW2npXistu+kY+JRKMJ2YI/I+eR2RvdKo7i/+tlamAurNr0P9U/krwEAxtzj4b97pMOWgDAKO0rZQpQzxi0exM7/D7s8UzvyaXu/QZ2/4apfvOOAvHGb2GI9JRiphwU/nKrBwi6p7KHE76w9Qjk6qF6juaeJM6ncFX9FthkuZm9k2aDdM0pwmQOD0Ccn0JQh2ggZbMIBTS4OCw8F5QHkSBQBXKe9V+IMmX1FFnbTQRJh0CxqhOQ6gnwwuttqZvt55ZW7mgYEzCbIiGYIfEmgN3dG106/OFmT6HF4r2pCoud/MEFenUGZ7dfl9DFDKN3yoOoUZebPxiBSalblZTSPe8Kd13UBIC5iCWQ1l6VOWFYTiUbTQZ0zljPXzp/MDXq5PrGC7quuKkzO1ofevqUEpnbbbXb3aV1B8ONQLXwZDCIKGYFco8qiIpDovc8Wkyto18WGQnzG4um5znkH2Wozmm8gfwwl3BLEu4sWNXyTH5CkFip9TzJHEnaZypo/wWjltNUux7sdScN2iktgc7Oz7m3jl1DS7AVbruPW9RwkBz+Ibyud7To8TyLCFhgH2w1a69VuxWeaqsvAzHUUTd/PUXB8WUvb1ZggnZonzxDxtaS4MmSRTjGJkpVr0CuZMDX8P1nMj9zYTTSDP+4LlAsZql4iHMqPDfDT75gKQPtvGrmOS3oVUMetpyKwroHDoOSlmaPlblvIc9BKoaKE/6F+6EdsqeG+LHDXIGxs9RgleF7Q/oiWG3KOwL61lOn2U+eS7QmfY4Abzn7+r3q3MmkeZwirCO85TqDupIdyHAqAcDbgEime/DtIxC1mKk192c4QyNu3Q8b8Y6zQKYS/MARFN2gujFtlCiX8a/tg69X6RvFFXTt8Uf9W7tXCQmUMqHd5V6suCPLshYUApDv4GaXzSJ8FgRxbjHfxXodd2vGe7YwQ0V7TXy/CLtI5bC/ah0jDBqeOetzjiF+k6r9GITObbBs5DAaUIrnIv32QHHcfc+n+5qRcq7/OxTEJETklwEw35EsKu5STGT5Ov1+2DbvmqWyMKTgiZdznalqHcx7Cgr2kXUMDtbuYKMbPrTMmWzKqcDulBWLREGScNdFETBQbflM3J7j5Pgsr6q9H2y8mhgGGpuIpVCHIhaNKfwNjlb2ppouA82gd1B3ZSQMnWY0SXT4N7ZsX+cb8YfOAwB+esqyCmD8dg0ByhYMAgzDekd2ZM4tHcjqfRkn75Tbl9UckdSEDZnjena2dqQkwKIJor8zl/JNxnPZ/oQkOAtjr+w/3zBx2ofE7M/bD5E3XLDNKdikp3fUnBeRnuyEPYLJjXTIzoHlJN7gcToIOvovhycUrWXSNzfVF8KEyOg+BWevZU09rKXbtqd+o852lZjpAB2mr+r+aiq4hCK1kCpdpki8h+/g4P9dZbWBuNmgCAMc+rI+kRGgYofXOlbsd1Xx8vGYJS72J9BfKSyNy7B6F3z8ZaekB7lsz7Ap66s7xEes+x9iYbZoepNdZH32LZF6a6BWfgLKYDh0rN34qztK3hEVk6n5AQUk0CSdJUMukbh6D+BZ3oiUibO4mXgSJrYFZ5/Aam7jhQhupr3h1wKo9y/mxljBnY0gbAuOt4jkx9HE5dyzjfozmNh2S6g4x8wta3mcpMvBmAGG3u4O4xa9VXlWZ+2UuuAJ8tHnJigeKH9+7ZXiV1DBrKjgVRw2xqho9QBa51sDmtpFIN+zhPEiuxKbB/ulu2OaeXrY+iiw3ET5mQJJHlAwGGrmH0nzoy4xaeUlt1cQHvLjvfp5KEj3KQ2OZcJrC9UaSX3uZf+13JkxT5fcN9NZQ6+V8BpG4OzW7YpnCKk3FFnwiVF6p69/Sfxkvs8x2afCi6WWgma8uKd88w9w2lcEAtnWuD+9OpEvchf6ZH5nKcvbonuDk2Bl+rsdSxOGQVG7Vr1CYiF5vGe8N5cJS6lzn7czF4Avzzdco46e4uLKXAE+F+CDhY4CfeLekb84TKYNc40cLCh4eAU35vuQhyzwTFVx4a8KPEif6vbdQCyCxpCWvuCG2fHK30kwe4xE0Q+Z8Y87876W3FMOVEyL/8veSFiwe2bZM4ov//LPqegjc4bxBHnoR6g0bMn40kCPN+jWnbqP5cfa9mD2S5xaL5HydlbQOX2jbosqw6DQ+brJ6v8UvIqe3xxoyB9hLhywMJS716LQ1OR9CVXlPD4ALSvaezGWLGT4BCOXT27NPcnhyG+LX7tTT4ZPtQFxCC9amWWk2JDwxrlzFXl8vObqRzNDv2yup/jGBIPc+j5ujSwQrOUrK8LSKBGxU3HiZoce0IMb5v3QiEERyPRs+9gtHF3mORC34N+n85Ocmz/A3SFN/rv5CU4Jx3dq2uAodJSfiOWDoFuYMuJAOqQJgT3SnhRJKLPKwZFhyfMEiXPkvfAmlTJwiMG3EJHIxYzRqFNuGUaEyicLp6LYwzCl7aRB0PJxVdfC22HDfgay9s2C9oFmffzs8rkP43eNeK7+FnXEqiC1lPtOdYwzQzI1aIhJUbH8FuwgZPQK3UfUEU/3ClSGq1TrJqLVAcoODaiMwuocfHExwV0+nanZ+Fp/IKXtLYHQxIlerfJjR2LopPNMr95nALms8pt3DU/S+i6+W1Hg+o0PNCLWmhMqI2JbgZPSyra8BFTtYXAKjHQTZB6ogEEGxdDdwuegVh+mqfrfXE1Wkw/uZCTkwXdwZ7LKqOGKX3FFIsPt1Wjpapo2bf8XsunyPLcGxueWVtFe7CZMzJLRVy3KQWpDiioWwZg5eMgnaI96xvT3keNuH8NN5igfR8MHN372trnlmR2Ki1kVrD/9OlrwRfkmYvsGDYy3rQYLDM3NKgN8hs1haFJJWM8mQGM2fbIk3ezPgnpoRqBDynDj6F4boJsm50TJEdZOFLzL/1COoYjvxPYYT9S32+rrrlG+MejQO5omF3F9Tw0hM8b1ey4PHuDmxjCehgZ7GPgmSA1XANU0Si5j5LT0vwxmkTtkYSoZwgTrd4Dpv4EwmyQkTVtizsanzoYj762Zu1aUEaV6cdpsGytpWjjiG29Sp/jaOYpd5lWxaa4eIVYiTYMdzUHuxC5KZZPg+IHdDKwvmMXlZOfUzncMWVsjrZGtDUkiwsL+9jX/rXS3aNDiR2tz/Xu98V39ZOPwPhIdJu4RyzMLjRfVRgHem9VecAecupNeIH85p+b+qBsASOroEUtRDQLypdgbTwsfaEUUhaE5V1ta4tW+7VLr4T5k9JuHfs9tc60xTUECZo5okdsQaGkX2XY7KWaPWzVtiOLu1i6pfETuMPD5Vr1ZyDXZQDJniFaQWxPJ8OSWxFf7spOLq0yKbBnaeCQqwW2Qn/fsym0Uc6viZdjhzK3sxKU2kLa4JBt0d95HsnfuuHKnNTGE3vc5ZNMf67NsdDZaGdiZpooabSqMSkPDYgcCtLMzYxd1JHbNrzRWYZ2A2g0VO3cPNQxWPizTFufhwu3V4yVsPT7UCdssPfwL0/Q3Awb530GcSs9m3R45dHVe8a5VQctNCP66KCRzLaqeobVfnm7zus5ob2eD2YeFLmIF990+OVtzKYZ4CqsuaF51R+tNb2yArxf2oFWWOzX7+LjbzbagNasN6cD++P/Y9Ak54biSmsnXTIB3E0/kVwji/w7Dc3pCcH5JRQNItYGKKVdn4RVFZhxGjyMpZeJXX+1YGc4bu3hagDvD5tWk28x2kaW7bCOhrKhGJY2do77W+MAOGfcq2eXTAeeQHJz4q1WTxJWR1nK+yt4LUDzYP9lGunYWbwuidP91KmA6vvUGn3h9Up+O3glb/8GHI7Qcel2h2kES4pB3VXZdVkbgYAu02mxM4OdHFA749rQhJrqq3SoLen/i3HZxIsSHihE3Cex4k5TYdo/W9ebR2JSogXZnb5mKsQNk//aG6x1WITZttjGvJtsxLITFUqBLTf8Ithc57OjsRK712e4hSRdAE5UhUAKKrzHz+6tpXIbTPykf28J8x1sOqeNNXQefzayNTrD80gkoKeZJYgJOQQfuMgvgdKUZryyC2ulD0Gb0B67jL5xJ13Yy3dut4KOROc5XB8koLehlWyqv+wXYR8grd/lczmdNdK+I5pCwvebVZzlji/QNLmLKsgKtJqu6zYQlSVzX4HRDg+ttHmmbyVsyWMFJuyAmnc7Llt1de9PqMpmYPtD1Lj4iqggUr7xfF0KuUwgLRyXr8c31q2E3KJm2krV180ZL+WW8uDIttU/Vi+6SBDicpEklApzv/euoO0bdYwhzbn453S0qhdOsxxQw/695LL7oE6FnNjcG2tV2ENfYqs24xb9I9SA8O6BFjTi1USGe+s6dc3/SNS1IcxAoY2lkpqd1lw7mUvTWXMVTDhyZpwVVnM6B3g0F6bKX70+Nw2+JixdzUBvWTM71+8CPcBGTv3ghWwKDtlFvJCYX6zsDaqV2ij3LFov35xriqu9+z803yV7+Gq0yaGfFV9YyLb89TiHKS3VEH06DGbKYrTs0+0vGKiVojPGUKK2KofQlyaHBRrBw+wHMiBuYsEAQs2U3rKOPba6Ey3eXyBR2mM/C2ifL9K9nSLWVyxlrGukO2yeHkLHRpcG4a3LviECyK54y8eYWyV0n2DUuf5mSVljHb8+7UEhh9OooekCTX2UADQsyUByyvSH1IqJDzKCKUq2IkRJovrAQIJUSkkZI1IL9EP2bqcieGgptUZlkzLQtQFV8RZ8uRVhcKGONxdMPQv/J1aypk3XfxWvtWLIGbbX1SA5urucH9agy1kZXrQPk3zAuvU5SpcRlwQa88rfZGS3PF3oDg3opfWpPTHgvSTxUZ9IXbW/S7stQEmFAJwz8b3DIGVDSu1cAbGe5gGPWDa/8Z0c9qxwQZULNyk3QRIqG/rAcWK1XShakMn3ghuRCCgtmUCfbo9blDe2rd2U9pEquToUjJR17IPuo/Q3eGheGQjgI1udNx0XtfmsOBnCR4tirhI6mgUjtciLZWSGcTf2Ix3qLedrcPKKA7ZVqN5+zCkM9iJHku1WXTmyQoAML23ArZ9bGu0/xgP3+CbV2MEqG3ktZsuK51p4JsNjyO4lyKgeLQvpvBnp8LKAz1xOPJjw90fxNxJoFjI0dDJDMVMvTnbDB8P5sFWcAciJPjM5yJ4uor3Vb5ja5lk0tD2TrdtshMuTR8w5hsXHA4aWQAZx3HbdH4rB0GybdGODmwKdScUFJS/TmDcWxCJiBWejXC/RAb1vhzSWC65XVukG8uTdATQeMulHf1SP0acz1vTF/RE2pvYTYMyGyAgX4pL+bs/NhHL8t8ui/NOjEQzDzGS7hhJh8r4XMk6YUmkSCoq6UFEhEgRslZ4xFx9o3kb2WtKLlg9rcIUfX7Fm9B4te1/83Ybo97dLM5QSERXNsl47bDP+T7lNd4uNpfOgx1/5WQC27F9I0iBdrDat8oR09tWDPLSrV17voHokup9EEav27TGkoLO1l6xDQazG+p6zT2eyAKc98QvF9RujxB+tqO5syrF0+8izeqTGT/mx0Ba6nzFI0rOvoFPReteWHbk0VgfppxdcLc7ae6NJ9RnYvq0dtl1P+cF8OslHaJdoyWcEfdwDqkkt9zCnANxBHxYuNSTz3i7HWmyN8KSUjwZEYbE1gwq3j7xCYAtz70Cl58Ol+3u5InoQivttIsOBdoLd1NtEWF5P8AK+aVr3AiGNLIrLXaywIJPptG/TBAzngNP7TYjgZFq2ULKKlK6gmTMXFEzRLY31giqa4tPVgh9rFPIzAeo0A18wux7ZcEAYjNcHLlst28IUXuMcwPJkJlpfjoMy8En4ocEVuGyDb8Vfc5io7a9tCc+FVVe5nJNgznrK7Au6NURQky8sc6v5IjhnGaGCr7ilC56U6RzrrpWzVu9tp1pTSLD57eW8UWHJI8K6eBKOvM05X9G+yUDBmpP54jqMvTDqivo1WzetaLvfRPPIAZC1QHa6zRt3NZF8ofMco9K1GnXIOHlKrHoph5osce6mgp0LE7emWBr2+/H8OIm8LBMzWqSp6FCClytSyeTDfX/uiIyloIPiUeGEtwb71LOYiaOMTRItPAJ/VnldvGCpJqf6tyW7WR+O5IRtLlAjiMB0u2J8elrarzVRwFtK7rYx7bHKZWWOFTj4dvDPgExBUwz7gIjBn46vatQfJhyb68q79DPxrvVu4yeBGIF2Xqo9JT1pbiz42puUx354f5remBC5wTp32Xs2P4gCYineK3ZTq4M5grSHfTwxtyODaq2loJ3ASQkOWm00cqtdgOIlCwGZ8rYmW9Pi5T/ukMAZ03eCIFp3CCfmn/3S8hgAGszxi2YvvuxAy5TuGQseJk40qjYKaUaA1N/u7GD4aGx9E9RzMIGLncMjLWC7HDFaCccr7V5B9YliSD+fPvTVWrXbQgjxcWMhGX+icfofg4RSWOTjceQUIT7oINAX367Ch2QmlLsqoTduXqRE51XYwFq4Q3ELNfzgCCFhOhCdmIfdlpIniHMSSR54zNI4aMgqZCSqUGzOxBztolnCa0HGPDGuUHpIuDQf3d3rzJcL8PsCt2NtOiSsYW/62XqXQhLnOJU7smibCkxg9NoR0AdHXY3juFB0rBZjp7fgI6XQUk2JbsJWk3uv3JTvgzbXrs3gQCVd6U2awODa6xjIqerOa0ujhBxPwvNnHRKjcPtqtFkAiuQViZ8R3f63ui5ANkd9fmC37ogwHUdPmPdY8KRDyqeLd6MgGR9TAp9a5Dof5yxpDSpUVuvA42NZ5qFmp9KEkoUha65ZIpmJDDTrzcD1LpTdXEbhBmZieam8tu5ssYDK+iqk60vC4RTp/HHEMfHXjosWkMKl2X7vFpIqW+2UVAlzuS0dUoKTMo8fIQ01h3j9YD+QJDfzyh71v5EjzXMQHqeMbdJpZBCo+G3K+Oc5g3uAkm3uPSBQ4y7d+QVFmCUWirPEbfALjNZ/B9c3yycXkV4H8df27J80viRhn0rzrrjxjASAoDgR6Tiu9MOTkqPZboBr7G7JeuClDYOLLZ/7LalRg3d87y8EMn8WT7yzmdel0CGJb7Ch5B1rdVtIdtas0dqTqS24YY1QmYBbwSnrZZIMiHRed+LSmJwWOKPocQyiyRdIOohg7OpS3wVbq7iY9mDRsUUL79f2q/iereoeDeVIglLE53hKaD2f8ZnPmruxNwAiWdaVZIMsr5+q7+F9Oh8FERkoM2/2bMKD65WJB/64W/OSL55wFafW4bXk1/xVMLM36aGjMViwm3TtpIfJJ7xt3IJRiEK+aUmIUR+y6MVANvC6T8XserMLpj+nC2qaxTqP0qytiYRATnu55sTT0uPknM+u5EplyPqns7IHvtvopOpHzDYMPKL4tUKcn4KpGBY2fTS0rbOhCsI4oZeUTrQhPnM+8Wu8XD7LtcKkbCkpqna2FR4XMcT//y1XmZIHZ08CvGbINV1XqZAqIZGd8rOaQq3ZUHdCokhvjubOwflDKOTYdI/EIN9r4G7b4mHqgI1oYOIAnj5axrumlGG81zH+uKrGI86p1TekB4zZXtKgUhMw+iXuDBlrGDLZAyFR4E34Qgel8UuqJQeQqkw8m7fAzWjXtZUT46yZB5wDSWu0vvPo7X9DAj9emVxnyZt0cnH86ouYRYr8tqOF7vwBLhm2MeIVOEQrV0gFaxFdTBhkD8l3RHzftP7hkKRw0nPtOQg9UApdGNoAtQoug7tuqCNBVdZi9YBSa+eOmzAuqSO8T3ICR/UFtcjj0KvWbKZrQQ+fXpabggx4FQbSX9LPHLnRvIYhn8S0lWaQt6kxBalz4hkjX1IM3NRDcczGhygTR883FZ5j3ELY5JHqiQPTBLgjiuxwZ+yF0maYwCQ1csbZM2pUKNJUQfxp7oiH3l2TH9FgZb3OOz5tIBzqNhnBZrTJoCaCGKPinK3Z/LRXVjHRbFRq9qvBl31r182c/LAlzY8UUp6UZODj7JVumvyHws0wXEW6aRUD0iCI76JupEc6ONOXF303kEiqyvf3plgCqchVLfHR9kBzHJ3ss7u+JhjMXitVkl9ZHbM1pWXYcW3orIwKOd/u+oCMvDr+1J4XLcnTAnsQCDw4h75F/wIfWhJu8QkNw2oYYSHo7N5D6IGCo2jCvC1WfDOiGg9SUZZKe0ajk8wAY/6R5Q0SKYaHtaX81PSIrPhhaF0OaekUV/KvWiQKs9svzHwBjG06PpE9TWFpFDeAolWHW0PKaEuHmlIly6gSLkLmmktG/qcWxoqU/PjUURNc9y8bDfs9YODMxVWxWhawCJx5NNeh4Krf873DxbNK/m+y/sflza+vooZAxKBOK0W2As705FHDTNLYx5brDIY60bk2zOj+BtcGfZZtpnktLOTJQBlpTHWrGfbmWeFmQEWfo85n1VX22TdmUSCWw9VsJy7x87bVej6D0uiNL16vCiM4nYFtTj27r+GJyurb2NioBuhmY10SBwMao+F2Rl23lXX3JkR8gf/8a898t497KhaWlPAaCvWH9z6JNNYyS6sxkYF7HES6m+BMZlV25fHaPA2ahJhHl+iww6rIfItZ89hNMdJrVEFyQzVon6B9aUgwr40CjZSDvBaFGfMxNHDZmyC+WlhG1NtQfoVUlLeZaPcc2etlIWqk5RgBZI0lNn7FEasLWePpVyKDpTWmSF3z4vLCYAfxaSkpAO4Ouko/KlgMbiA4awl8Pn3btyZjw7zQeuM8YsygA4PXjQDqVeQIFswSVsS2u92qPzICVX7IU9kaCGzeR4cyiFoFByshLobEUA6uylMCrdLcfI2KeCypuIAjwKKYuap6chCJDSdVb8qFfXDBM6JnKuMGzS6Iwt+t4sOv5ZmFQx8yqec/5DCToHBqCievCSSWGZw30q8hMCj0iHn5cq5TzgnDn+MxINJo8m0HgNarJkwagrwDw82+WCX2qajigFOYJZzVz4+DS3ST4GUTVM/BIpHXuU/fktHXfM2fHOVwe/Qu8qmjCPsx5oPsRZro7KHbYO+Wxdf3419yYk11DAv1yVwWux+zRudzcEGgR7c+aPMtsXh9pA9N7NVTDj19X/6f2VMnpvePbd9qprn22BJkgtsO6pEZ+51hqwAjude/FKpO0chhbBRPtbfBX1+TbXNckcX+HNlQrGiEawdYQ+H1N7ITVEm+55GA258qUDOrKRzONRKZZ9Ya5W8H/pFddO5+NG2D09oJIU+pQnw1xJVhfM914ZaWs9ZMkkbbeZsZpLI2YRnsZZkeTNBr81c6c3XWU0bpEKZrPiWR3Yy5aD79Of33yW1U+c4+ZZPkwd7GtXj0Dbdf3pj/DRqECDlBeeoLhySuAwvsWzYAaEaCnGP/l9r9s/wDtWiyrIl7Y9N52l9hNo48mH7uT4NF+6YgM1FlBoIGycVlQ4PzC3pboonxOIk4Zsby7k9MhuPn1Pumie7ttNvfFKeErJX0kMXKS8ZSuEULxqFKsFBfGxJ07nls7TcPSUIXldwMI0soUUHFAO8YCgIPftmUQ1QYA/HlYdyfAh/U2T7UYLrINoqnVTI+6Md7v6Dm7GYosDl+CQ1fqVyi9vITXChZsXK31ztNCdegpYHDfol3++Fqb9SCfeuI3i5kbSBdatEj5H2qUEjDbLDy6ZuWANFWj5UFlhqyywuoc6URALL2qgNib/pT2DqL6ZmxnM86GXGumTqf+Uvw8wR+lrDwwilQkT8FDrdyL+2O7ieSUyd6AzbZCgHQUcZyOirnhb00h66LyGyLEjtI30nS1ML0yKSCo8Bd5Y4KNtaamvP3cXURQIE5n9xI9407qm3k/AxHSoLtwnFgAl/eCl/ck7WogSPWcavQv429cfnz+Ssn05Gr8Tfl7ZNwg7dF+KEAok/nVpp0F8jZahGCO/roELW/TQs0aeHaQ+AZDhJO142OBpd+soPUvWKHKsXMfaJIMOEqYYsqN6Xy/HnHlzNxOmVd46IXPMH9RpHZgGIKqlilZERCfrWeWuQwdrCSi7AFvF4MGWcc3DiwQ/B/yLfAN/k90WNr/u3EL3gwV0GbTVSQt7xWr3JuiZOcRkhBNQfn3Rj87kfd6rJShV8r5Uo4oF94a6z+vp178jOWogaxy1rSZ35oiDLgCH9dpqEVZgR2sTlESWjem1Dd9/ZBmiGk7Dcle/VuxB3WesbDjlMgJPgSZGMUYpy5qc3SsnNs+pciHIokpr2efk5Ki+DEYiQkW7LCjt/N0K+dQZX+NZCYMKrIHakEU3g1Y2ZOgN1NoO+lHSUweyMMFwaM/zbhFDRXfKLWx3pdfEm5tggj3m5El17t9H+x+o/lXuYQ0R5oqnWZgAgUluDry4aMmv9exi1xOD9+UXLmHiYPRka6R6cXrwFsUJW4JUFpr7Wy6s2U5S+C6Mx0ppQpmEBtvnoGV5mj9FUrewsZseTiPOS1X0GWVkyb6Aplnz0N+VixgZ96rYWrDLuIqm0BVBazfp0Rbsm/t95m/ws0GUNqNST0AxnniJ3rXccnzY2OvkDeSgKSBJ8ebhZuXwzLz4NQ9ZOFEtK5BQ6IW/mFYhQSeSt7DGB+ZNhrhCXm5PpWyTefqnGtpa8lGlcO+uls+48Y34rl1+L7AUizWoTWeVX+2Dja4gOU02uVYu8tGSn0fpBuXZqm5LH93OokgFyUtJK9YVYyVT2uEkyHp29pfJPNjL6DYoHmMLhwP9XV62mDmEdNJ92D93VFtzr/mA0gNgunXvEjiDY0Y84m72oOR29JBt/UZElBvwug/sSqmEiGmm6Ifn0NgI0FKwHR86e7BbcUpEbnUXiD9qoeCM8o+wr0SPNDlfxKtGNtTXp2sshoM5u/mexZIax9yNMkgM2gFoKCG+s4Y4alNzjTkFU0CnBku6FpSO9btRUAo5JbxP6ND6XNqTjPPY/CCqj30+KS1iVYI6B3plM/IktKOmpEl4avT6uwcgTqpsC+JmMs29eBBkVDt8g+TrUlKbHLAia9SuV6QghPWSRblbC4l3Y0aG+1FYoB8GWUoAO8xJS+x7hUVEz+uBGR+G0vp+DX9v9ThCPCB50l83m0rEp0JgOhuegEaTCxAoBMZ3eVwq3bjrzi8LHRzN7Szj3U/ppJE7K8ajFQN7Bk/yY1p+XApKREoVDmKrItd790eMsJCR3hKaGgVIj1HcJC/+s/CWLJ+XWCI4QDGvbmWiS0dUYC2fp7unH0z9cp8lEcxNpjl5QxiJjkqJgOmcJJVC1J7sNACAHANXxkSU5iYz27+0DT1mDBtN9HvPBB/ndU3QhP12FLzlFGO8XT40mCtS869Uvf0j4VNG3AhxgGpB2IVm70122EcDhQsfMqUtDMUndWjRXZaYIebSnLTNsocuwbPY8IVl2+J1cye/A4UQEiMD2IBowo7We1wIFprvAQOoV2Jjs3fD2kCgVjelj6XhkE0BOfxPGybKYXWEh1PN7qMF2c5etnLQIf6qQuITxTvB+bprvSWeGfl1e7WttkZ6SB2XO817IO3xbQzcvF5IW8MMv2Fp4WdhlFBscl02CvV7nbGulYv3nooFWFDmWZyJZZWfkI8EVI6vJwfIrFUWwTolcffKmv0YILdjTSo/5Gnb4rerf+OXggj39krWjNEaqbrYqBXNzi1IMzlO2HQE3X3Sxo8iSmruMWdZkLecFjXxBYzbhMVbuixzhFhD8nQyt9tQKiRFjkZtVMwQxS0NlGkDQ6u5rC2WIuToMipgQQIFLw5GwkIo02Oyjlg8fSV8SS4KxBS2Q5dsJfT2qY4iiWE+7kJSbgELEGaUvs3wMlZY8DviAMO0WPHrqniEhVpIWBJPi68Fv9nTCfi+Yr/merrmfwuJmE0u1k8JpjV3RK4ye+t1gbIBsCusURFWjjQuTs2P/KgWN3oyLEgg1UtAAGOv6VL05JTkBiKOHwPCE5LM70jNl//C0FRtAV0tHwEUHsEx3Tbw9KP5QCucEWKyQJnXbPMMZq0jXmEeTgokKK0qoUWyowrBTWlbdvdxFg0UfC6pyPthJEskifBc8xFdDC/dVGGWS8yaDytd6xae73oT7q4XMU26skAYf0v5s6YfINtuvAncf6jPEhVYHAgEQlusmKVEM0U7mXAMx0ngveOTE6JD7Y5M5ZpBlazpmd1jna9RTpXQ8VYKnLkeEABDR7Dyb2wBsd/dnXSdrt2X+ae4wp4qVYMyJKQYpMKhxG/b43xlyeUa81hXuiECJLUSu4oxd3E5xgAj3n6i2p3YgkqU6AFpk6HVM1GQ/CtqMq25AOleLssLz1WyKwpXhyA4UXcl+fr0nm8RSWmG+qcmF/5ZevyU+Asu/ZJDPoQrdAXfZjLNtJyv1BneC1AqWFfSfSasI3HKZ+CWWOw4ZXrDS2JX9cpC5oE3Fj/Nt+f0HIYSCyQ+U2tcF9zI8YVUTB0+rFGM9fPIgaB3GY9v9+zgnFoLxm+IePVk6PK4enKk/xk3pNf8jHDe4zUZPiZY8i7zm38/+PxREN15gnLBDtZ9Jv/GjrK0NILv8nGYJv9gE476mxQ5Eqm+lK8S1rjcv6KnKXQqHnKH3vv+7EMAinXfAOod9SW2RNOYezciHVlmf91AkgeswMwXDw9AS4DbiC25fG1Hemv5msJ6SkO0sDHpN4ZC6wwqQqjpve0G4WUwdYerNP0RFFSiwkdBDhr8M0DVKc0PvaT1uA8aag5cqLieU5eXt1rzyQ0PVjz+y1evgimdgL1xy3mko/6MQaExM40UU3caStnT9qlpD96klW4IZFfzLkJVuU3t+WCJdgt2OscNU376hzlqfBdieg5PixjTUxDG3kfMPsd/BUJCjI2g5V80VtF/EnXBhtpui5AYvgn+XAqJDArNXTyZ1naGchNobezRjagf/vDGjFuLUD8yL7+jEonuhvuHb8ONr0uKA8d9T7UtG4uPzsPBHauCzfnB2RB58LAhL7nzOnerBdiHDjkivlRsVdqe9Oklyf1z1mMEx9/TdaZtwc9u4tpWeXsib4BALBrbAlw8ptbj5R2EnXqKp9JokACRSRsWaUjSvLcVIO/P7XeoRrZnclJekESytOOVy99avmq4BAFp+jmS5JWw54p/t7DulcB/s0ZlJVhyM4UmZw+587JKJHdV4yRK9/UDthLMcSYy4Y9reOuDETFIQ/CBdssESAQekZ1N8Jv6sUSi3Dem1kIUl4E0UJnttDoks2BX+JnUXvZYqPA19Vg4wKqF4R7hIT4iFpKdsDWxqFwLttvO0y+XgqTnSRn3Y3Hvm01DV0dpzp3/p+XdpkrOVjHfiFiUJfw3LiWfmpiO2LLifVKAZ0PJ2cLgruB51kx1Xt/+Nn3zbXcHz3WajVi6IZgkQJa4kkKP2WASpfos9dHZlyk0NMRbz4kn8dq3WbxOnIyAF6GvOC7s7RrMGVTlJdJlhHKADJoDPqEJLKRvkO322J7QYTw73AvO+Wx6x3Pic66kxJjtqLp9LdMKHRTCqoDAyblv3Jfe7wpthp8x/6UsXpH5GEg+FoTE4EsLiNJCEVYFsq/L9qKP6tIw4ZQymcCHCbmEglMPHa4M4vKjYXiuCqNwKL9vw5T5zd7YVNMi+LA4IVTQ4CgAVC+9nZEQsRVB0j+YLZDtoR54GGgQpR3zgk/n+wg0K6A0tR71J3L5QSLDhKTqP61rbs2o0mD3ff5PUy3uIl+Ca/FUnyWfhfaYL8AFTQABd9HVrI6Lmltb6exD8h3JffUV8ckVPqR9xEW8p3YqQDYSn1CsHzUtLf9Z//6kJOKNhYs7bXzN50rz/ai0DVlEkLdr5OzxFT60K4Cvc9Y4btRD6HlfNjH9E+FKUb98dX6eW6tAEL/nj7NKcX0SSMSw8t5iOeGb2PRBg53vD/ALmeQsASihdTGsyCi2Bd9pxQdOJGVO0ORbdlkJyhze61A1keQKa8qXAXTW9kWiZ3mfs1xO/HllaFqLSHj+SyRUVvFgVqGVBY0M5l0dZAw51wdOO/jynkS8oqKlGtNwqxL9yYlR9Oue5/pujfeJVIYk5J3RQvQGfnL9f9y2qRqXCZS5Z4p5kA6MtEMN95c+mbaGaGqkg58kV17KeZiKxdkIXxMErHaDpXVGkaxcxaOVDkuhi2/nL+lAQ2YKZQ5g2c8ZHn9FmAr9eYeGejEqsrnaky3JVmqrnKhGx0RBs4QaKx2xTBNDhSNfIFRMxf7xA+X7xEUvYomH0caQL8vphhw1DYP0XOf0FIFj2FADAK8KSCD1QSvTSzX9VCQR93yDg5S3KXhs6XI5NFUfBGPDyY2JGJskceH2iujKVxrO//Xf+0UwJ5g1TavKDySfNQ8IKwFUlOAUgfXbbP4nkLkg3a7wfWNZsWFF2jk5VuyI79ocGbWosUp9l6MHO5R5Df/hNVlNSugNOKufWVbU1rrP8ZKirPnEc/srWHtmz768EWspGNoQo5aLDqCreGqBU5V2+jNqrJRiwZ1pzROCjoLepAWNRjYLp/fzGKCFH/NGpOP1bfDYt6IT3pYihM3Te3OY008Iaq+aptxQ+3lo8pNNvdx8RJdh5yGKIZvMAlfrvpj82+nNFeneTpv/9hN7VIuHDHbiPHIVi9RF+X7jXhA02HGf7ovDRE8X8Jkou6eqNtHkemXzdw5ZzIq9jYpFbhsyjKFYGYKu9HP8/JJl4CltNOkqm+GL50fGLPUMWHbQsthYkff8QW6ORHP0JOyoDkAmC1oyw0/xzQNkm6TLre5HFeviIaBuxFKpbD823whrIv/aIfTvdeJNSa9HFqhQyjik9Ig/nJRHhqhYT320Rji+E+yrY6m5m4oPOFj/MYJeaB+n4PrbQkXhj9PPMHQal6a9r9ti9hhfJAiWWYeCgb6PiDFdDbpXPvlMisSnUjbGOfdA39V61aXb4FYe8e8Q8SDg85ip0PUPMMcfOakzZ7O1L+cdWoRqe6jfGbtE64qAmEE56gQ984iVtp1rkqLlMngUa/k7U2idlXjTx1Yz440RWtmuebXlP0tncPr0mv7Ai4YjQWO8bfYZKhEKwUPFcsciCk7D6Yb+rah82X1UYHLmn3hyO/R8e2CrxiMpAf6mwEcgbxZ06M1qG0LC2li7//3ax1fy87Q0/jUKn5Fv+Zgn+Wkuemmn02ter7n1ZhSPoy2ZeGSWq18yFH8sDvPXICxlXuy+i9KlP6XcYnUoMXwY3S0HN4s5nI1Yrkj56f9OJjQJZFHnEOkxqpuBSHTBo8kLnwtoM1Lm3v127vGYkconu11ROUXgxs+Z9py6Iiam8DdEgZX7h3ypd7WIT5rJ2rReca5wgTPFviHcDS5RhSBhYQi3Diy92e3ncPDHPwF3OXGiWNR10n2qkQ81T+cHv6fRA9VwTzoQm8Euu2guQmD7h6YX6PhZcIIWbb/st6ILqTgZbbp3GVcDdMtRIK1Oh7+qrOVWDZFoVw0CLEVXGUECGc7uoVLCY3+uciMtD7q5syGicmh3OHozRanTAk2wNeufasGyZ4vHBCEeQbxv0wuJtl1m+5IXLIKbmEZgq/o6im2szOzqdRC4/zfF8uWDXYSc1EZPN1QqrBpGAJSCV5zNWtgCRqzvDgycDGfd+89ynqv2+/JdNznFWVXETFgftMR+ox+aMwnTt96XK2fTw8aCe6iC3J2Kaga2ebWpL5M1L7DGsOhhW+hfn67tGnuncxF9TRWnKplv6+1w7fYwWFRHa499vjSxxNPCfVTDddlQErRkDwvAW7GHTyCSlS4a16HeavGwFCTTM+z3a6XTfgYNIBhRCFRhjlKAg2fVc1t2yISzvILA18u+/C+NoFDrp/NKJhBryNu9mlxntMqFnUreUBI78/VypHoSOX3g/fx8aJS1cWozvyL0RxF1qvhPdBJ3ZLNv27WTdQx8vBbHP978pdvv4vWprXjyUbOFpXS59lZfJIEqQSmP5S++d/Q779Qx/ZBChVaBzsw9E+Oj199ywfTjTyfi2hjTuRZvGGqdPmxC6eq+PHtvPdwmfnGdLxjX+iSjk7QYyF8vvCaCA1QnQIKhmD7Y5mbR+cR9aTWLO5IGMJdlhJJetEg+DermxVpHYuj5vAWm+MJS3RuZb5qXNV4Iy0qnyeoqFwRxcQug4J4fwxOV1s4tPj+mx7Kfu12OcT1osHoCYsNdI8nHGB2p9cNWuwaY94pu7ekHhm2OQgP5c8vx00LquE0/yHj/DpoMBfpC2An0nS7ppwNpiYdxRUBABVun7UBpFveGa6wAnDkGieVVjFLep4MHc42t1M1WtxjYArHPa+x0auuMiIdALOl3KAtDn/MbXI2owpK7Rw+Cqsh8kG5xEuMDOMOHc/eA+7F9iumoHDe25V8cFzgALhpJrEGEotQSakcISk9Nl1JPvEK1E9RpjUeRR5d1fxVnBPTkx8EeBsJqtLfSFxhKzyo9iJqlYf9tUnndCsBwoA/7qywtugx/6LBoqchPlGWSqQvgG5mAOjyPs3TmNH7vmYaZjyt0oTqdqiA1sgrzBKXh8bBbR8ihkG4+eSiBBfAfQb3W/vAVQhFEXSTLfujZQRUFa7V0dVjY41W5J55hlSJHWNWJdLEkpc6fEyamqgnWp9AfsMHFd5Q2qPDRDh7G+OkwUpGRObaHTYdLBfGYSvQOeLm/WlHrBH2gbi1jp4sHcvO5A7ENqKXXySA4sEg5LKiwJCrCZSRAOdj5q1Zyy9TwWVrx2gucKDfanM1lwSlebj0gEnPPT7obtbgR3Rxi51DKnbnjm0TmZB0k8xLdJWrKQv75WDThxPpExinXHvqKKC2hEQgD9EP5mN2dM9dwPj+wHtcU1irw3szlnHBTbTzhu2ZAYrNfO70wRdiLxlVrJb2LL35vsRC/s6ItD2/Tb9K/1DIISSAN0HwLj2S+1lh2q3ZvyVliaTG6S1oU9nYgFOCudjCa63HMGA3i3GV0+y/XvFCOjOXIKJMTRS/LUpNIxxYbUpz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+ }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 6, + "tool_calls": { + "total": 0, + "bash": 0, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 0, + "productivity_ratio": 0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 18 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.67 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 18 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "javascript", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl @@ -0,0 +1,6 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "javascript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse JavaScript (no TypeScript)."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-5vlxz4ta","session_id":"d309e78d-a326-413e-ae14-7e68f8beeb6b","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"61ff51a5-21c2-4e66-890b-9075efa2926a","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01LXbFDFEEMoVDEUsv8qPfSH","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me build a complete, playable Tetris game in JavaScript that runs in the browser. I'll create an HTML file with embedded CSS and JavaScript.\n\nThe game should include:\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys)\n7. Nice visuals\n\nLet me plan the implementation:\n\n**HTML Structure:**\n- Canvas for the game board\n- Score display\n- Level display\n\n\n- Lines cleared display\n- Next piece preview\n- Game over overlay\n- Start/pause button\n\n**CSS:**\n- Clean, modern dark theme\n- Responsive layout\n\n**JavaScript:**\n- Game board: 10x20 grid\n- Tetromino definitions with rotation states\n- Game loop with requestAnimationFrame\n- Collision detection\n- Line clearing logic\n- Scoring (based on Tetris guidelines)\n- Speed increase per level\n- Keyboard input handling\n- Next piece preview\n\nI'll define the seven Tetromino pieces with their colors (cyan for I, yellow for O, purple for T, green for S, red for Z, blue for J, orange for L) and implement the standard Tetris scoring system.\n\nWriting the game implementation... Defining the piece shapes and colors...\n\nNow I'm setting up the rotation logic using the standard clockwise transformation where the new row comes from the old column and the new column is calculated from the grid size minus one minus the old row.\n\nI want to build a polished Tetris implementation with ghost pieces showing where blocks will land, a hold mechanic, next piece preview, score tracking, pause functionality, and a game over screen. Let me write out the complete HTML file with all the game logic...\n\nBuilding the complete game implementation...\n\nI'm implementing the rotation logic using matrix transformations to handle clockwise and counterclockwise rotations cleanly... I've verified both rotation formulas with a simple 3x3 example and confirmed they work correctly. Now I'm setting up the full Tetris implementation with constants for the board dimensions and game state variables.\n\nWriting the game structure...\n\nNow I'm setting up input handling and thinking through the movement mechanics—I want to add DAS for smoother horizontal controls and implement SRS wall kicks to make rotations feel more polished, especially for the standard Tetris pieces.\n\nDefining wall kick offsets... I'm outlining the complete feature set for a full-featured Tetris implementation with a 10x20 board, all seven pieces, rotation with wall kicks, ghost and hold pieces, scoring with level progression, and various quality-of-life features like soft/hard drops and DAS. The controls map standard Tetris inputs across keyboard options, and I'm planning a polished dark-themed interface with animated line clears and a game over screen.\n\nNow I'm thinking through the technical architecture—I'll use a 2D array for the board state where each cell is either empty or contains a piece identifier for color lookup, represent active pieces as objects with their type, rotation matrix, position, and rotation state, run the game loop with requestAnimationFrame to handle timing for automatic drops that accelerate with level progression, and implement scoring that scales with the current level.\n\nBuilding the HTML and CSS... Still writing styles... Still writing styles... Building the right panel...\n\nNow I'm setting up the game constants and defining all the tetromino shapes with their rotation matrices, along with the color palette for each piece type.\n\nDefining game configuration... Setting up the canvas contexts and initializing the game board, then implementing the 7-bag randomizer to ensure fair piece distribution and a function to spawn new pieces with proper positioning.\n\nStill writing game logic... Now I'm implementing the ghost piece logic to show where the current piece will land, then handling the piece lock mechanism that places it on the board and checks for game over conditions.\n\nAfter locking, I need to clear any completed lines, update the score and level based on how many lines were cleared, re-enable the hold mechanic, and spawn the next piece.\n\nNow I'm setting up the piece spawning logic—pulling from the next piece queue or generating a fresh one from the bag, then checking if the new piece can actually be placed without immediately triggering a game over.\n\nFor movement and rotation, I'm checking that the game is actively running and not paused before allowing the player to shift the piece horizontally or rotate it.\n\nImplementing rotation with wall kick mechanics... Writing game logic... Writing game loop logic...","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4731,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":4731,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01LWWZYicMXiHBYNyv8MvzZE","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using JavaScript (no TypeScript). Let me build a complete Tetris game with:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z for rotation)\n\nI'll create a single HTML file with embedded CSS and JavaScript.\n\nLet me plan the game:\n- Canvas-based rendering\n- Standard 10x20 grid\n- All 7 tetrominoes with proper colors\n\n\n- Wall kick system for rotation\n- Line clear scoring (like standard Tetris)\n- Level progression with increasing speed\n- Next piece preview\n- Ghost piece (shows where piece will land)\n- Hold piece functionality\n\nI'll set up the board as 10x20, define all 7 tetrominoes with their colors, and implement controls for movement, rotation, and dropping. The scoring will follow standard Tetris rules with increasing points for multiple line clears, and the game will speed up as levels progress.\n\nWriting the game code... Defining the tetromino pieces with their rotation states... Defining the remaining tetromino pieces...\n\nNow I'm thinking through the overall architecture—I need to manage game state with the board, current and next pieces, hold functionality, score and level tracking. The rendering will use canvas to draw the board, active piece, ghost preview, and a sidebar for stats. I'll set up keyboard listeners for input and use requestAnimationFrame for a proper game loop with gravity timing.\n\nFor scoring, I'm using a level-based multiplier system where single lines give 100 points per level, doubles give 300, triples give 500, and a full Tetris gives 800, plus bonus points for soft and hard drops. The gravity will follow standard Tetris progression where pieces fall faster as the level increases.\n\nWriting the complete game implementation... Writing the HTML structure... Still writing styles... Writing game logic... Defining the remaining tetromino pieces... Defining the Tetris piece rotations...\n\nI need to reconsider the O piece—should it be 2x2 or 3x3? Looking at standard SRS, the I piece uses a 4x4 matrix while O typically uses 3x3 (or 4x4 with padding), and the rest use 3x3. Let me standardize my approach by defining each rotation state explicitly rather than mixing matrix sizes. For the I piece, I'll map out its four rotations as horizontal and vertical lines within a 4x4 grid, and for the 3x3 pieces like T, S, Z, J, and L, I'll use consistent 3x3 definitions for each rotation.\n\nDefining the piece data with rotation arrays... Defining the piece shapes...\n\nNow I'm ready to implement the full game logic. I'll add wall kick mechanics using the standard SRS system—for regular pieces like J, L, S, T, and Z, I'll test a sequence of offset positions when rotation fails, and I'll use a separate set of kick tests for the I piece since it behaves differently. Compiling the wall kick offsets for the I-piece across all rotation transitions, where the coordinate system treats rightward and upward as positive directions. Converting to screen coordinates where rows increase downward, I need to negate those row values. Now I'm laying out the SRS kick offsets for JLSTZ pieces across all rotation transitions—mapping out which positions to try when a rotation would normally collide. I'm working through the wall kick offsets for different rotation states, but this is getting unwieldy. I think I'll simplify and just implement a basic system that tries a few common kick positions like the origin, left, right, and down variations—it won't be fully SRS compliant but should work well enough for a browser-based game.\n\nActually, let me commit to doing proper SRS wall kicks properly. I'll organize the kick data as a lookup table keyed by rotation transitions, then define the offset sequences for each piece type.\n\nBuilding the SRS kick table... Now I'm mapping out the wall kick offsets for each rotation transition in screen coordinates, then I'll need to handle the I piece separately since it has different kick behavior. Writing rotation logic... Defining the piece shapes... Defining the remaining Tetris piece configurations...\n\nNow I'm verifying each piece's rotation states against the standard Tetris spawn orientations—checking that the I piece forms a horizontal line, the O piece is a 2x2 square, and the T piece has its stem pointing up in the default rotation. Continuing through the S and Z piece rotations, verifying each configuration maps correctly to its matrix representation. Verifying the remaining rotations for the J and L pieces...\n\nNow I'm thinking through the spawn positions for these Tetris pieces. Standard Tetris places the I-piece at column 3 spanning to column 6, while the other pieces spawn at column 3 spanning to column 5. I need to figure out the correct spawn row for the 3x3 pieces on a 20-row board.\n\nI'm considering whether to spawn pieces at row 0 (the visible top) or row -1 (a hidden row above), and I'm leaning toward allowing pieces to spawn at y=0 even if their top rows are empty, so they gradually enter the board naturally. For the I-piece specifically, this means the first row of its 4x4 bounding box would be empty, with the actual bar appearing in the second row. I'm working out the spawn positions for different tetromino shapes—the I piece needs to start at y=-1 so its horizontal bar aligns with the top visible row, while other 3x3 pieces should also spawn at y=-1 to keep their top rows just above the board.\n\nNow I'm thinking through the rendering logic: when drawing a piece, I need to map each cell in the shape matrix to its pixel position on the canvas by multiplying the board coordinates by the cell size, and skip any cells that would render above the visible board area.\n\nReady to implement the full solution.\n\nFor the game loop, I'll use `requestAnimationFrame` to handle rendering smoothly, track elapsed time to manage piece drops based on a decreasing interval tied to the level, and implement DAS for responsive left/right movement with an initial delay followed by a repeat rate. I'll also handle all the standard Tetris controls: arrow keys for movement and rotation, space for hard drop, and dedicated keys for hold and pause.\n\nWriting the implementation... Defining the piece shapes and rotations... Defining the tetromino rotation states... Defining the spawn positions for each tetromino piece and working through the positioning logic for the O piece to ensure it appears correctly at the top of the board. That's 4 cells in the middle. ✓\n\nFor the T piece with its 3x3 shape at y=-1, the hidden row contains just the stem, while the visible rows show the crossbar and empty bottom. With x=3, the stem ends up at column 4 above the board, and the three cells of the crossbar span columns 3 through 5. ✓\n\nNow I'm setting up the core game state with a board array to track piece placements, plus variables to manage the current and next pieces.\n\nSetting up game variables...\n\nNow I'm implementing the collision detection by checking if a piece's cells fall outside the board boundaries or overlap with existing blocks, and I'm also tracking the current piece's position and rotation state. For scoring, I'm using the standard Tetris formula where clears are worth more points at higher levels. I'm settling on a linear gravity formula that caps out at 50ms, which gives a nice progression from 800ms down to the minimum over about 10 levels. Now I'll build out the complete HTML file with a dark theme, subtle grid borders, and gradient-styled pieces.\n\nFor the visual polish, I'm adding a shine effect on pieces, a ghost preview of the falling block, and some animations for line clears and score popups. When rendering each cell on the canvas, I'll layer a main color fill with a lighter highlight on top and a darker shadow on the bottom to give it depth.\n\nStill writing canvas drawing code... Finishing the shadow effect, then moving on to write out the complete HTML structure with the game container, side panels for hold and next pieces, and the main canvas board. Writing the game logic... Defining the rotation states for each tetromino piece... Defining the game state variables...\n\nNow I'm setting up the canvas elements for the board, next piece preview, and hold piece display, then initializing the game with an empty board, a queue of upcoming pieces, and resetting all the game variables. I'm realizing I should use a 7-bag randomizer for better piece distribution instead of pure randomness. Let me implement that system where I shuffle all seven piece types and draw from them sequentially, then reshuffle when the bag empties.\n\nNow I'm working through the spawn positions for each piece type—the O piece appears cleanly at the top, the I piece's 4x4 shape positions its bar at the visible rows, and the 3x3 pieces like T will have their top row hidden initially with the middle and bottom rows visible on screen.\n\nFor the ghost piece, I need to calculate where the current piece will land by simulating downward movement until a collision occurs, then render it with reduced opacity to show the landing position.\n\nWriting collision detection... Writing the piece locking and line clearing logic... I'm setting up an animation state machine with a timer that pauses input during line clear animations, then moving on to implement DAS (Delayed Auto Shift) for smooth continuous movement when holding left or right. Now I'm ready to write out the complete implementation.\n\nLet me think through the game loop structure once more—it needs to handle delta time, check for pause/gameover states, manage line clear animations, apply DAS and gravity, then render everything in the right order from board background through placed cells, ghost piece, current piece, and the UI canvases. I'm also reconsidering the coordinate system for piece spawning and how the O piece's filled rows should align with the grid.\n\nWriting the full implementation... I'm realizing the O piece shape definition is taking up a full 4×4 grid when it only needs 2×2 cells in the middle, and I need to trace through exactly which board rows are visible when it spawns at y=-1 with the shape rows offset by the spawn position. I'm realizing the spawn position needs adjustment—for pieces with filled rows at indices 0 and 1, spawning at y=0 would show both rows, but for pieces like the I where the bar sits at row 1 of a 4-row shape, I need a different offset to keep the top rows hidden as intended. I'm settling on y=0 for all the standard 3x3 pieces, which places their top row at the visible board edge. For the O piece using a 4x4 grid, both visible rows appear at the top of the board, and for the I piece I'll need to handle the spawn position separately since it has a different shape.\n\nWriting spawn logic... I'm verifying the spawn logic—if a piece appears at y=0 and collides with existing blocks, that's an immediate game over. Now I need to finalize the complete game code, though I'm reconsidering the piece shapes to avoid wasteful grid sizes. The O piece could be a compact 2x2 instead of 4x4, but that creates inconsistency with the preview rendering, so I'll stick with uniform dimensions for simplicity. Adjusting the O piece coordinates to verify it spawns correctly at columns 4-5, which matches standard Tetris positioning for a 10-wide board.\n\nNow checking the I piece with the same logic—at x=3, the four-wide bar lands at columns 3-6, which is properly centered. Let me verify the spawn positions are consistent across different piece shapes. I'm working through the spawn positions for different Tetris pieces on a 10-wide board. For the O piece with its 3x3 shape, I need to figure out whether x=3 or x=4 gives the correct center columns—x=3 places it at columns 4-5, which matches the standard spawn position, while x=4 would shift it too far right to columns 5-6. For the I piece with the bar in row 1, all four columns get used across the board. The T piece's center lands at column 4, which is slightly left of the board's true center but matches standard Tetris spawn positioning—using x=3 for all pieces gives 3x3 shapes the correct columns 3-5 range with the piece centered at column 4.\n\nNow I'm finalizing the spawn coordinates and writing out the complete HTML file. I'm also thinking through how to render the cells with a 3D beveled effect using layered fills and highlights.\n\nWriting cell rendering code... Writing the game loop... Still writing styles... Still writing styles... Building the game layout... Now I'm setting up the core game constants and piece definitions for the Tetris implementation, establishing the board dimensions, cell size, and color mappings for each piece type, then defining the rotation states for how each piece can be oriented. Defining the rotation states for the remaining Tetris pieces... Setting up the game constants and state variables...\n\nNow I'm initializing the canvas elements for the main board, next piece preview, and hold piece display, along with grabbing references to the UI elements for score, level, and lines cleared. I'm also setting up input tracking for keyboard controls and the delayed auto-shift timers for piece movement.\n\nSetting up the bag randomizer...\n\nNow I'm working through the piece spawning logic, checking for collisions by iterating through the shape's cells and validating they're within bounds and not overlapping with existing blocks on the board. Writing game logic... Implementing the hard drop mechanics and the hold piece functionality...\n\nNow I'm handling the piece locking logic—placing it on the board, detecting completed rows, and triggering the line clear animation if needed. Then I'm removing the full rows and shifting everything down while calculating the score based on how many lines were cleared.\n\nSetting up the game loop timing... Implementing game loop logic... Writing the cell rendering... Writing the render function... Writing the rendering logic... Calculating cell size and positioning...\n\nNow I'm rendering each piece with a shadow effect and adding a subtle highlight to give them dimension, then moving on to update the UI elements like score and level display.\n\nWhen the game ends, I'm populating the overlay with the final score and resetting the start button text, then showing the game over screen to the player.\n\nSetting up keyboard event handling...\n\nNow I'm handling the pause mechanic—pressing P toggles between paused and playing states, updating the overlay accordingly. For active gameplay, I'm mapping arrow keys to movement and setting up the dash timer.\n\nStill writing input handlers...\n\nNow I'm setting up the game initialization function, resetting the board, piece bag, and all game variables to their starting state. I'm realizing my DAS implementation needs refinement—the current approach with modulo arithmetic is overcomplicated. I should track how long each direction key has been held and trigger repeats more cleanly: move immediately on keydown, then after the initial delay period, move again at regular intervals while the key stays pressed. I'm realizing the issue with my first approach—I need to track how many times we've actually moved based on elapsed time, not just reset the counter. Let me use a cleaner formula that counts how many DAS_RATE intervals have passed since the initial DAS_DELAY threshold, and only move when that count increases. Building the state machine...\n\nI'm realizing the single DAS state approach gets complicated when both directions are held simultaneously. Let me switch to tracking left and right inputs independently with separate timers, so whichever direction becomes ready first can move the piece.\n\nNow I'm working through the lock delay mechanism, which gives the player a window to adjust the piece after it lands. I need to make sure the animation state blocks input properly, and that after the animation completes, lines get cleared and a new piece spawns. For the timing, I'm already handling the first frame edge case where `lastTime` is 0 by setting `dt` to 0, and I'm capping the maximum delta time at 100ms to avoid issues if the game loses focus. For the board storage, I'm using piece type strings and looking them up in a color map during rendering.\n\nNow I'm ready to write out the complete implementation with all the core systems: constants and shape definitions, state management, canvas setup, the bag randomizer for piece selection, collision and piece manipulation functions, game actions like movement and rotation, the main game loop with delta time, rendering logic, input handling, and initialization. I want to make sure I get the details right on delayed auto-shift for smooth controls, lock delay so pieces don't snap instantly, the ghost piece preview, line clear animations, hold functionality, next piece display, scoring, and level progression.\n\nWriting the full implementation...\n\nI'm catching an issue: I need to initialize `nextPiece` before the first render call, otherwise I'll be trying to draw an undefined piece. Also, the overlay should only appear on the initial idle screen, not during gameplay. For the initial state before the game starts, I'll render the board as empty and keep the next and hold canvases blank too. I think showing just the empty board with the overlay is cleaner than previewing a piece upfront.\n\nBuilding the complete HTML file...\n\nFor the line clear flash effect, I'll draw the cleared rows in bright white to create that satisfying visual feedback.\n\nI'm keeping the scoring simple—just updating the text directly without animation. I'll skip the localStorage best score and consecutive tetris counter for now to focus on solid core mechanics.\n\nNow I'm working through the mini canvas sizing for the next and hold pieces. Since these are 4×4 cells max on a 100×80 pixel canvas, I need to calculate the right cell size and center the piece properly within the canvas.\n\nComputing the layout... Now I'm calculating the positioning for the T piece—with its 2-row, 3-column bounding box and a cell size of 24, it centers nicely at coordinates (14, 16) in the preview area.\n\nFor the hold mechanic, I need to handle three cases: storing the current piece if the hold slot is empty, swapping pieces when one's already held, and preventing multiple holds per piece until it locks. The held piece gets stored as just its type, so when it comes back into play it always spawns in the default rotation and position.\n\nI should add null checks when rendering to handle the initial state before any piece appears, and make sure the start button doesn't interfere with keyboard controls.\n\nNow I'm implementing the full code, including preventing default browser behavior for all game keys and ensuring the DAS timers work independently for each direction.\n\nI also need to fix a critical bug in the line-clearing logic where splicing rows shifts the indices of remaining rows—I should iterate through the rows in reverse order to avoid this problem.\n\nActually, the cleanest approach is to filter out the cleared rows and add empty rows back at the top to maintain the board height.\n\nUpdating level calculation...\n\nNow I'm thinking about edge cases in the hold function—specifically what happens when a held piece can't spawn because the board is nearly full. In standard Tetris, that's game over, but my current implementation doesn't check for this condition, so I should add that validation. I'm realizing the hold logic is getting messy trying to reuse `spawnPiece()`. Let me just directly set the current piece when swapping with the held piece, and only call `spawnPiece()` when there's no held piece yet. The `spawnPiece` function mirrors the hold logic—it pulls from the next piece queue, attempts to place it at the top of the board, and escalates to game over if both the initial and fallback positions collide. I'm noticing the spawn and hold mechanics are now consistent in how they handle collision detection and game-over conditions. , the standard Tetris game-over condition is when a newly spawned piece overlaps with existing blocks. The y=0 and y=-1 checks handle this.\n\nFor the I piece at y=0 with rotation 0, the horizontal bar sits at row 1, so if rows 0-1 are filled, it collides immediately. At y=-1, the bar moves to row 0, which would also be filled if the top rows are occupied. Same logic applies to the T piece—checking both spawn positions ensures we catch game-over conditions correctly.\n\nNow I'm thinking through the animation state flow. When lines clear, the game enters an \"animating\" state where input is blocked and the board displays the flash effect for a set duration. Once that timer expires, `clearLines()` runs and spawns the next piece, transitioning back to \"playing\" or ending the game if the spawn fails. I need to make sure the game loop properly handles this state transition and doesn't process input during the flash animation.\n\nHandling the state transition carefully...\n\nI need to trace through the sequence: after setting `gameState = 'playing'`, I call `clearLines()` which triggers `spawnPiece()`. If the piece spawns successfully, the state stays as 'playing', but if it fails, `spawnPiece()` sets it to 'gameover', which correctly overrides my initial assignment. The key is that `clearLines()` itself doesn't modify `gameState`, so the flow works as intended. Refining the input handler logic...\n\nI'm structuring the keydown listener to handle each game state separately—idle and gameover should start the game on any key, pause can be toggled with 'P' during play, and the animating state should block most input. Let me organize this so the state checks happen in the right order and the pause toggle works consistently across states.\n\nNow I'm ready to implement the complete input handler with proper DAS timers that count down from the initial delay and reset to the repeat rate, plus lock delay that resets whenever the piece moves or rotates. Defining the piece shapes and colors... Defining the rotation states for the remaining Tetris pieces... Setting up the canvas elements and DOM references for the game board, next piece preview, hold piece display, and UI elements like score, level, and lines counters...\n\nNow I'm implementing the bag randomizer system that shuffles through all available piece types and pulls them one at a time, refilling the bag when it's empty, along with helper functions to retrieve piece shapes based on their current rotation state.\n\nI'm writing the game logic functions... Writing rotation and collision logic... Still writing game logic... Writing the rendering code... Writing the ghost piece renderer... Writing the board rendering... Still writing rendering logic... Adding highlight and shadow effects...\n\nNow I'm setting up the UI functions to update the score display, level, and lines cleared counter, then handling the game over screen with final score display and a restart button, plus implementing pause toggle functionality.\n\nStill writing game loop... Continuing with the game loop logic...\n\nI'm handling the right movement with the same DAS system, then managing gravity and piece dropping with adjustable intervals based on whether soft drop is active. I'm also tracking lock delay to give the player time to move a piece after it lands, resetting the timer if the piece moves away from the ground. There's something I need to reconsider here about the implementation.\n\nI'm realizing I'm double-counting the lock delay in my current approach—accumulating it both when the piece fails to drop and when it's grounded. Let me restructure this so the gravity system handles dropping the piece each frame, and the lock delay only triggers when the piece is actually resting on the ground.\n\nRefactoring the gravity and lock delay logic... Writing game physics logic... the same speed, which defeats the purpose. I should set soft drop to 20ms instead so it's consistently faster than gravity at all levels, and the 1-point-per-row scoring still applies correctly.\n\nNow I'm working through the DAS (delayed auto shift) implementation—when an arrow key is pressed, the piece should move immediately, then after a delay start repeating the movement continuously in the game loop. I need to handle the browser's native key repeat properly—ignoring repeated keydown events for movement keys where I'm managing my own DAS timing, but potentially allowing them for other actions like rotation or hard drop that should trigger immediately each time. I'm working through the DAS timing logic—when a key is held, it should wait DAS_DELAY before repeating, then move every DAS_RATE milliseconds after that. The counter starts at DAS_DELAY on keydown, decrements each frame, and once it hits zero I move and reset it to DAS_RATE for the faster repeat cycle.\n\nThere's a small precision issue with my current approach: if I set `leftDas = DAS_RATE` after moving, the remainder from overshooting gets lost (like if leftDas goes to -14, I lose those 14ms). Using `leftDas += DAS_RATE` instead would preserve that overshoot and keep the timing more accurate across frames.\n\nHowever, there's a risk: if the game tab is backgrounded and dt becomes huge, leftDas could go very negative and trigger multiple moves in a single frame. I can handle this with a while loop that keeps moving and accumulating DAS_RATE until leftDas is back above zero, with a safety break to prevent infinite loops if something goes wrong. Since I'm already capping dt at 100ms and DAS_RATE is relatively small, this shouldn't be a practical issue. 50ms, the while loop would execute at most 2 times. That's fine.\n\nActually, this isn't quite right either. After the initial DAS_DELAY (170ms), we want to move once every DAS_RATE (50ms). But if dt = 100ms (cap), we'd move 100/50 = 2 times per frame. That's correct.\n\nI'm implementing a DAS system where the counter decreases each frame, triggering movement when it hits zero or below. Starting at 170ms, the counter ticks down until it reaches zero around the 170ms mark, then moves and resets to 50ms intervals. Each subsequent frame subtracts the delta time, and whenever the counter goes negative, we move and add back the rate value to continue the cycle. the DAS block doesn't execute. But if the player rapidly switches between left and right inputs, the leftDas timer might retain a low value from the previous press, triggering an unwanted auto-repeat. I should reset leftDas to DAS_DELAY whenever a new left keypress occurs, and using the e.repeat filter ensures only fresh key presses trigger this reset rather than held keys.\n\nSetting up keydown handler... Still writing styles...\n\nNow I'm verifying the piece rotation logic, particularly for the S and Z pieces since those have tricky rotation patterns. Completing the rotation mapping, I get the cells at (1,2), (2,2), (0,1), (1,1), which gives me the matrix [[0,1,0],[0,1,1],[0,0,1]] — that matches what I have. Now I'm verifying the 180° rotation produces [[0,0,0],[0,1,1],[1,1,0]], and checking the 270° rotation as well. Now I'm verifying the Z rotation by mapping each cell through the clockwise transformation and building out the resulting matrix. I'm finishing up the Z piece rotations and confirming they all match the expected shapes. Now I'm moving on to verify the J and L piece rotations work correctly too. Now I'm working through the 180-degree rotation by applying the transformation formula to flip both the row and column indices, which gives me the upside-down J shape. For the final 270-degree rotation, I'm applying the counterclockwise transformation to get back to a vertical orientation.\n\nMoving on to the L-piece, I'm setting up its default orientation and then working through the clockwise rotation by transforming each cell coordinate. I've verified all the L-piece rotations match their expected matrices, so now I'm ready to write out the complete solution code. Let me also handle the T-piece rotations...\n\nVerifying T-piece rotations... I'm verifying the T piece rotations are correct, and now moving on to the I piece. For the 4x4 I tetromino, I'm checking the default horizontal orientation and then working through the 90-degree clockwise rotation where the piece becomes vertical, mapping each cell position through the rotation formula.\n\nVerifying rotation matrices... I've verified all the I piece rotations are working correctly. Now I'm ready to write the implementation code, but first I need to clarify the spawn position—checking whether the I bar should appear at row 0 or row 1 based on standard Tetris guidelines, which typically spawn pieces in rows 20-21 of a 22-row field. So for the I piece, y=-1 is the correct spawn position. Looking at the 3x3 pieces like the T piece at y=0, the top row of the matrix sits at the visible board's top row, so the actual block appears immediately. But with the I piece's bar positioned at matrix row 1, spawning at y=0 leaves an empty row at the very top of the visible area, which is why I need y=-1 to match the standard spawn behavior.\n\nFor the O piece at y=0, the 2x2 block correctly occupies rows 0-1, so that's the right position. The standard approach is to spawn the I at y=-1 while keeping the other pieces at y=0. For T at y=0:\n- Top of T at (4,0), bar at (3,1),(4,1),(5,1)\n\nThis puts the T piece fully visible, with the stem pointing up at row 0.\n\nBut in standard Tetris, pieces spawn with some cells in the buffer zone:\n- T at standard: stem at row -1 (buffer), bar at row 0 (visible)\n\nFor my implementation, having the top at row 0 is fine for a browser game. It just means pieces don't \"slide in\" from the top - they appear at the top immediately. Let me just use y=0 for all pieces except I (which needs y=-1 or adjusting the shape).\n\nActually, you know what, let me just keep it consistent: spawn all pieces at y=0. For the I piece, the bar at row 1 means it appears slightly lower, but that's fine for a browser game. The game ends when a piece can't spawn in its standard position, which is standard behavior anyway. I'll initialize all pieces at y=0 and check for collisions at spawn time. I'm realizing there's a tricky edge case with piece spawning when the board is nearly full—specifically, whether pieces should be allowed to spawn partially in the buffer zone above the visible board. For the I piece in particular, if row 1 is completely filled but row 0 (the buffer) is empty, the piece could technically fit at y=-1 with its bar occupying that empty buffer space, even though it would collide at y=0. I need to decide whether to follow strict Tetris rules where spawning fails immediately if the spawn position collides, or allow this buffer-zone workaround for edge cases. the player. I think the fairest approach is to spawn the I piece at y=-1 so its bar sits at row 0, giving it the same buffer as other pieces. I'm setting up different spawn positions for each tetromino type, with I getting y=-1 and the rest at y=0. This way, if blocks occupy row 0 in the I piece's columns, the game correctly ends since the piece can't actually fit.\n\nFor the collision detection, I need to handle negative y values as part of the buffer zone where pieces can exist without triggering game over yet. I need to add a return statement after setting game over so the timers don't get reset, and since the calling functions check `gameState` anyway, they'll naturally stop processing once the game ends.\n\nActually, thinking through this more carefully—`spawnPiece()` doesn't return anything, it just sets `gameState`. The functions that call it will continue executing after it returns, but that's fine because the game loop checks `gameState` at the top of each frame and stops rendering. Even if `current` gets set to an overlapping piece, the game over overlay will display and nothing will render that overlapping state.\n\nLet me explore a different approach for the I piece spawn position instead.\n\nModifying the I piece shape to position the bar at row 0 of the spawn matrix would work, but that breaks the standard SRS rotation system where the bar sits at row 1. The rotation math is derived from that standard position, so changing it would require reworking the whole rotation logic. I'll stick with spawning at y=-1 and keeping the standard shapes.\n\nActually, I'm overthinking this. Let me just keep it simple—spawn everything at y=0 with no special cases and see if it makes for a fun game.\n\nThe I piece at y=0 means the bar occupies row 1 of the matrix, leaving an empty row at the top. It's slightly non-standard but works fine in practice. Now I'm ready to write the complete HTML file with all the styling and game logic in one go.\n\nWriting the complete game file...\n\nOne thing I need to be careful about: the `render` function calls `renderMini` with `nextPiece`, which might be undefined before the game actually starts. The `renderMini` function already handles this gracefully by checking if the piece type exists and returning early if not, so that's covered. I also need to make sure the board is initialized as an empty grid in the idle state before any rendering happens.\n\nThere's one more detail about the render cycle during line clearing animations—the board still contains the flashing rows while they're being cleared, and I need to make sure the rendering handles that state correctly.\n\nStill writing render logic... Writing the stylesheet... Still writing styles... Finishing the button styling and now setting up the HTML structure with the game container, left panel for the hold piece preview and control instructions, and the game board layout. Building the right panel... Defining the piece shapes... Defining the rotation states for the remaining Tetris pieces... Setting up canvas references and game state variables...\n\nNow I'm initializing the game state machine with modes like idle, playing, and paused, along with timing accumulators for drop and lock mechanics. I'm also loading the best score from local storage and setting up a bag randomizer that shuffles through the piece types using the Fisher-Yates algorithm.\n\nContinuing with helper functions...\n\nNow I'm checking collision detection by iterating through the piece's cells and testing if any fall outside the board boundaries or overlap with existing blocks. Then I'm setting up the game mechanics—calculating the drop speed based on the current level, and implementing the spawn function to place new pieces at the top of the board with a game-over check if they immediately collide.\n\nWriting game logic... Writing game logic... Writing game loop logic... Refining the gravity and soft drop logic...\n\nNow I'm checking the lock delay mechanics—when the piece successfully moves down, `tryMove` resets the lock accumulator, which prevents premature locking. Once the piece can't move anymore, the lock delay block takes over and counts up until the piece locks. The tricky part is making sure this doesn't trigger while the piece is still falling, but that's handled naturally since `hits()` only returns true when there's a collision below. would be false. So `lockAcc` isn't accumulated. But I also need to reset `lockAcc` when the piece is airborne. Currently, `tryMove(0, 1)` resets `lockAcc` when the piece falls. But if the piece is in the air between gravity ticks, `lockAcc` isn't being accumulated (since `grounded` is false).\n\nActually wait: the lock delay accumulation block only runs when `grounded` is true. When the piece is in the air, `grounded` is false, so `lockAcc` doesn't accumulate. When the piece lands, `grounded` becomes true, and `lockAcc` starts accumulating. When the player moves/rotates, `tryMove`/`tryRotate` resets `lockAcc = 0`. ✓\n\nBut I also need to make sure `lockAcc` is reset when the piece falls a row (because `tryMove(0,1)` already does this). The lock delay block checks `grounded` AFTER the gravity block, so if the piece just landed, `grounded` is now true and `lockAcc` would start accumulating from 0 since it was just reset. ✓\n\nI think the logic is correct. Now let me trace through the `tryMove` function to make sure the gravity call works as expected.\n\nContinuing with the movement logic...\n\nWriting the game loop... Writing game loop logic...\n\nI'm thinking through the initialization flow: the game starts in an idle state with an overlay prompting the player to begin, then once they interact, I'll initialize all the game state, hide the overlay, and kick off the main loop. For the JavaScript structure, I'll wrap everything in an IIFE to keep the global scope clean, but I need to expose `startGame` so the HTML can call it from an onclick handler.\n\nNow I'm working through the soft drop scoring logic—when soft drop is active and gravity causes the piece to drop, it should award 1 point per row, but only if the move actually succeeds. I'm also considering what happens at higher levels where the gravity interval might become faster than the soft drop interval.\n\nI'm finalizing the HTML implementation now with a focus on visual polish: a dark board with a subtle grid, neon-colored pieces with glow effects, a ghost piece preview, smooth line-clearing animations, and a clean sidebar showing the next piece, hold piece, score, level, and best score. I'm deciding whether to draw the board border directly on the canvas or use CSS, and accounting for how the canvas dimensions will interact with any border styling.\n\nWriting the complete file... Still writing styles... Still writing styles... Building the game layout... Building the right panel with game stats... Defining the piece shapes... Defining the rotation states for the remaining Tetris pieces... Setting up DOM references and game state...\n\nNow I'm implementing the bag randomizer to shuffle through piece types, and defining helper functions to pull the next piece and retrieve shape data based on piece rotation. Still writing game logic...","signature":"EqLMCgpbCAwYAipAQFFUIeb0+rvLbp/qv5kjLulps0CTW1H9SIyB3RVz0oxJL2cBxeNdXmaYfpHxL1gTFQg/JmG3g3BrpaoO9IfqtTIRY2xhdWRlLXNvbm5ldC00LTY4ABIMC0Oetqdg0OXyl9lMGgweS1fabn4G9FalPdgiMAzf24oPvTU+S91BGn4zvGuq6GrNHvncciRrISICVFcuN5d+OUwiCnaSrkZsMYLyqirzygpP6E1W10GrynE98p92I/ilItebvbycDJZWqcKeqXcjsN670ebHAjnaosMY0DeEo/TsHD++Xnnw+Ny75KuBVaKsWzGG14QJh/GPPu6mYTgcqH5xr0Jk6RURuVRUZwF/jGqJ8vYrlRRfrMQVmkE/GbzTK2miYFBPRL0hquo5l9h09TNhT7S5BF0MY3IKWbSH91S/NOmqnbzlrzUKl6f4PZzxBV/pBCX7ioWPhaDusM40OM3FgeqO5Vv7iYNlczbQhEugYY6QtGmg6+pv1//JgkRxKVd/ngvkHGglsRiPeQAOafNLCAS20N8hIMSkRG6ErYGFEN7mCKLOnBeCf0JKbF+u8191ON5XbrNy4dnrgjQ0GHTv+gItnPQ8r8B1iWbycX02WpWJ6as+anSFrEtDYvgscLPQVY7rOhQlhZXSm4pQXmAHtdhEDFn+KUHwW71U9lnSK8Q4zzPOX7gVJcJwtHxlsJwtuKj5h+Y3FsSml05r3019frxKRbvkU7nMn6kCDdiHUcE4J2ohxWdLf1qOlyDsVuUALX4FW5UdGOKj6GUzuK0QFPgbvPCW55KpGSexvwsHlSlbYstxpdSnRERhJ3g2f5w9RCdQgNZfoaEC83/px/7ZkiG7O/hEa/j9+t3qiupzC3XROOtxZinGqq+7DFKgkGY6HmocllMUG1ZuHjLEw4ITM0JH/wT/7no4Kd/Wcaz4xLxlLFeQZrsP0wMQQIStpUGAuIQBsQE0GJsKUk3Pd6MQV1mmui6PfId7BjtCqiAkpd+GihlwvyhdHfHsWPi5T24EDrQazHUSIzHLNYWk10vC6nYkwbfU6Ji1EKKS6ZIfnTvSfELLjrV8+l180ZuKzd02EQjgqrN1ntWFRmXFLisjZgsrUfm5Bg/jhqPVhYTry0pEngnN8sj+Snlp7LOOcH3IyHmWn2wC/fhV/GqbXHcvyxfoJXrmuwl6FiHYHT6r8AV2h4oYhCIAy3YleXtJsInhEDmj4UtmSCnqeyVcJBo7+QkTkV4CcgbCBTG2665BvTnfySUm2wuIE1QHdz92rrAeJkhKluKoasvn2fDy1LK7k6nkbdcyN5pBwes2XO4BISKqc3IT55Tsmk0qTtClGVhT0XMHHihH+ycq62A0M+1tnvy+MnHtcvRVh3tpxyMFddUdfTt8GFmPy5gRq2wpsBBAzRBS/SzXOx4DLqJQxCjg/27L5zmtBLImzrawbg9xjSypq8FyjO9zisYHm0EVPi8r7xATqmeMs8xOtyZ1Xkv9PmlqVnVN+DKzk7tT7XLhXOKr2Rs2vu5BkrEkNHprNTVqxV2ESJWVMHK6wB74Gztwyen5nQBVkx1Smlvexa+2x5LjeaROE0AKs6vzGrjTXeY5XaYEeL0Ho3e29WGvFQyV4U5ZrYmW1jDDWoWJ4FmBh+WsO/1x0c6il0p8wKLrYJVgOWLTtYxS2B5nsz9sQl1/XDsPM8nzCeDmYaZc+hmfYbM29zMJr4knNc5L5An/hyCC3z/kHz11KGqe9j4WP+0S9DhyVv5NB42hzfKo3tqVLxaWp1dK0QWXAWG7mX+xhC5io5M3nhkup4WSDcvObGSxlVuquJ7Huf/7tHu9lSCx5Eo9dGcZoFm8njDntNNZ3rTpSsEQ/1ea3w4neFCJp9iWuT3UMhleiZZk0oP/y1OS+6ir5RT8kWOv53GgZEhExuUGS/qiEJ/fsQU0SwfQfnwjG3cIMqN5SQFibEWnk/2hJrBvs+IdH3Ci231lYaPrg3LuRi63akbdWgssXEN2UWVPA13Q+4o/TcI9RIW6kI0JNO95fQNXDMSA3hQcarUk1sCDaRIkYCHN1CH9TvZIQMSmcqsqCY7M+S1IN/BIJyS2GoWYRDuvVz0QQCPdFrvAd8jwOzFTNoqzZ8Pm8gSZqlznl9H2cwmyHvSjf1WnEhOwL9h0W2u2urBqdHFUiQ+VI7HVJnJHp1i7VXggNwdp9E5BOE1V9ZH3+xgP/Kj36blmBCskkixwCUDQQW7YNNz21M/lYHllh6PAHP+DZ+iOeSLUdkVy99/a0/Wv8kWQQqUZ3CjjCgybuyW0iKmO4XBKCBYlYlznrZTbpdNn+Fh/fXX5EgZNEnCSHvXYbt4XCWLY3kgVjpqDNu31Pmw7zry8S2lLuaHI7kD8Yx75ZShhEwB4wrjkLh9xYKKvGT2NUb2z9lBgU4s8y0hfUnkBN2l0x1ItxXsnpU8mFJap1kMnkPHViroTHlR3DDPWVm9uANR/7z8jIk6tAno1bZhp5MT5h1UGFFEJFivQBwFzk5QrFRY+xFbfYNxME7RaB4Mnz14VHGYmZXM268L6FPEPfBmd3vrNbA4CCqa2zCHMAHJLRQaJKdS20ifmuVCX7wu4heZmon9A72eW5lNZgOwlNsK/YraAEKOqWX+hxIfC7AldPsTcgxfWc74DsE20x438NmHUngG8UOiisxe+9VGNHmTK7mOYFp0SGMWQpnkOGnC2ejpCd/D6WhjJo3pmcI9Pzf/eIV7LypWAnpTYONC7YvYBnwqjIejoGAyNVrv8V5UriXhF3FBY3UKQgAc3FC1kCaR4Joomerl4buNASbtGJaXt8pbFre3emHBAUnaDg/2zPTigZAosXOFWLllodd/jv4fUx9qeLuv1g1bSenePEBxYFyEaRUiT1hO03fIjv/zJtYrOy+ufd5cq/qjhM3621biWuRXDQmimnwvaOw3Ny/dtC/095kvCayusihgfgWaNB3KVMk0A1cC936D+ST2gBcr+ZGXdU/aTMqY99VhsYuZbNpd5ovc7CwBIRMh0EEVz1UEcsCJe3vASNBk+pDT7hT9SYNeUYK9Q0JMSXMc4YdwLPKg6Qakg50v6jqeYOfSql+/8VkINMyblHC3n7Ekgvc9VqXVRIorrBT6oVZ5E8mA/MU3fYV1Rv0APC1P3OEoyX6tVdfWbrsT0ybImpx569dgyU472l9DewZfnNowTwJrocPNMIA/ZSE3OrwNpjrGdSf+VleWoPGT1sKImt4uN5ZGJHJDgA9WIR51iWgu7QCQwujdXzmGDG0RvqBI7StUtk6DcT1kib3G9HRA091Sldgp5yaL7CBlJfZJiEMLfibNQzofOApMiFEHyNFAiCBz1I70Rx5dQoTk2447PJ3iTOpvmxP7ssIvIHubrjtHSstKO/Xs9ccZQeUsw3MtEXLjoaXjSf1nboX3RRqJnzY/FjogmltDPKUJQ7tAXnDCZqD3mYD/qYtJuAwwqCC7Tk2ipmUYxVjgUxp0yQZh/iFXK7lM+jluEg7hbjnDDi/VZWAy9/X11Mdn8l6j3RUHT8h07KmwA7pGvV2Q5zDCAkJVsIRIce0Tgw5AFgs093t77K0eLw/fiywsxIEvZ5bAqCRsqb+WcB6N3ZeEoZ4h25VlqFNUaQDFQh2fiYZx/pGnJooqPqcBtwXgKPMr16SwpJwaydiagvaJO0IPGcFBSDQtteWvqfMvp+N+BvYNyC5qhHymC3IoIEKTr11rxfSsdytSYPJmkcW9q63xzd8gfY0d23L/ECtM9cK1sPYBn5bUUDQ6seL30PcxwjIZQQZ6hOmwO8XGjPxxjy+Sfu3mug8tKk1ODFwfu4nw2JiiOTuEF+F1xp0Bh4ZaOwmQY0r2ojemhpk20LGdfPxYLWPoXBQo6FQXTKW1y0SN4U3upiWyJ64R/81ObPc5o4QbUXnYwHd516P5oGgeC7ObAn6ST+VOUGGU36fVSTtucCEkiXjS+zHABot+Kt0trIvAnMpmJcH291Z/FutPEy/87/cRyY0RN+a4SXCPBQzr72OmBVGnMImA8031dPkMNLhv01giOPF0EmvvMKW22gZw7IZt0RF/CziXwtFFBpRujR2K9nzlRQkW9hXRadGDsncIzsbJ8/BX53SLfDS1h3cwsUF2/Z9RxWA9/gl5+IzKtZ31YijhcsK/9F9vsJxNutcMoc8fsfeEQzeGDhYNT8Exy1MMWjvHGVEA6l6uzk6yuRbjuwE6Tq4mRFU4TOz4fXW+ZUDJNoSPulwC2r8dH0suebBThrQZphFx2UA7V18TrsmrTDwTWon86jA/9lIOnkfjCMxxvigJTbOrmBx/BsvV9lXJtD7nQRpOyaQM0WbNROI7mpWom97Acu+wzaPaOjN1gI03l2yMu5nZIRNSm4rOfZZplrpcfarsGKR9gguXb1CW2IIMIyyxyYBWZFDeKu/tAn+5Kc7r2jb7BxVBmE3cyIfq+sT9DbaLT3FaKPxYKcQOf9ulTlZa3exulQrH1UIO2ij2UU65vUTEoIbHUCRdh04A0rEFp3ubmCSRhqdygbDwBuh2Lrw/7k91DS4Rv3Ak1WB+ELHNeSu5DkDsUGkaEEQgbCJMllkMHL1BoEmgkDiQ6nQVBxwZL+wvRHyYfljUrPuiWzZMK6Pp5rvjM27hraRdA8XiTX4wZKZWdXEBMOhy8lqLaesqDKpeBPU0kadHTI4vvVQAxd8bibd6PfXLn7LM9yPRVQeUF3v8dOldzpwEcqTPsmXEPVE1hY6v23esDFGFjngg5Krdf9djPTmTSzIi3py8tG3scWSCBpnGAg/8vCORvnU5zpM+yGgWeK6VQqSBVsRuGdt8rZRN61xwq3DGcL4RTB9lPgQQ6mPnwbjYcWmMQsQNnrdc32KeW8RHmA3yMutUj5LQdN4QIAZpf70BI0UoMLWFWD5Khszi6SX/FMpCc8gF+EBff++7cl/7DxPU4FE94p6OJVNTWqx94Z8eQJ4q0JqN3+USInPtdy7wxciCb7/OERbPnWjSJwA/Pq/36YvkJQGz9fNMB39paNg0nDrYt/FTdpks/KXIW9Flvjp2ggRHDYlbfRaJxatWT4X1z60XKuseFl17CjG9csZ8pm/izWEnsR5ADBHeaHZ+yj4QUwl/WDJgk/44dPLIC5f2Z4C/NPoRUwqObHswBG1GUVmrMmXbnbfDTYWJbNBnisfnD3gD3v4uK8pr0p/CDuxQRT6rg4K/C3IOAtJszRcYOxSaP8msCz9iywGim00pcaXKo1yhf2h9wFoRL9YzGyfu1tSfXYroiyyV2N8e8sLgi6ZJ6Vewdv7s5LejwftzB/g+M3C61S7rI8tPXHB54XTkG1XRZiS021sp8tOGMPGYDOGyFYe/bi9AZyYZg4fl8wFNnc3bICVs59tpobh2txEVwM2UTdEqQU8zI8yGW7M5YgbmtGMVrexG6QME0lSa4CybUJ4Al1LxwLfI1RMXOmvX8JTk2+JkIP9BvCyxUHsStQLGvkv82reIxdA2t2MWtBNYu2/SulxV0WrpM99KOfnmHHM829wjXJxT9RzM3GLM0vzf+gTIOE3G+DuCmVNdHTkEkGAcBSQA2fwzEaHFTPGYnuY+7MvQ93nzzlZrB+CGCGjgxaLENKnZn913pY3qeAFiJldzQ2xChVfYPHObKVMzYgk3vCLJNgm9JafwEcF8A2/7u5kntzLu6f5uJwgk/WdYa0s3HHwVdMF60pR+hDzoY+7JKUNH71gahDFP4D8wXPSp8dxYqrVvYlxoJct2Jd6lLf1oxPw7lwoUUPt6J8cgMDWaEUoZUZfhXd2gbsYm128Urg7e+AO3a1SvDlRaCechSNiC1AsFsg0bme6JMkc/NC5HQBb4djUlAk9hL7brhRyD8DcxdYMg0ilf/h3VDeatol/w3TQfU0f2D4R+ca9CO+V0NtRRYgx6ZaHS4xmjhbvo8f9SQHS2UeP0+A50JeC5vn7cfi3CDfnfUCHU7eTBqh/UkEbUI6RjNk3hWuM9j+lOnbNxEPyrCkrQK5kLIMnWaXmDGkhgF73SpKWh3CT2KXrM6o/OqAVHNT+svydHV5fV2mN35YzBnx6f30+1zt23ZmeNa7Rq32eB9SzEgWtRTrHoTpxt6+xwTgZ+4bbghKhk/2jZ0j+o1asUUPsU/QamobDmEujq/gufPW9+zL9StdN8DYM5hrxQW0l//PVRsOs43fAenAfqsh3G6XZ3ouY5rUbNjRItJCV93/xSTk7OBKOMCmESKleSkiiF/IcIL5A3U4dfeCtrreWwUhRX1KPaYM+NBxG4SGACTp9pFAfqpFP0No1g0mOlavjhkMBvuH7ignp/3RnJ4n/VCZrEky+vFOJeLqqB/juCfnxKK/zXE9lI+va3qS0LsGJNwMVMQZ+fqBf7P3BNZgXG6fb7Bmq4H9jQnny9vkPiV1OVHGouZZjJxkuYnUSDLdq1ReH+cRn8ANcRXXSHLNSSHvRGd+TmbztMrwLbnnK7aRDe0NClQPZG8CZ9q579r13p7Hhob0P5CtLM9xdLtmfhVz5cx1nvvUQ21ueOo7W1noC+nNKXuOWUAfyeZg0Qrv0VXxSffwbrM6yX8c061VcPEJ7y3+RvGeYOo81GS3BETt6JOZA6QfAARtb8c8b130vSsMxZNzCrBSkvChpwJl9SMyGJA+yXXgI4z9wyz2y4tPPWydLwE32NUVn18e2tAiI5GccE1zczVUMIa2SwN7jUAG+srqc2v8kXfz/Rumpe9SsJ87I2lpt6M7CGbRElmB1y3mE6nVbnPIT2bzEoH4JviauqSRAg8V7t5OTYeiNUWTnqReMbfkOM6eNMtWYAHw/Q+cic/+VtXb2s7z2gPjLdz9FF0H4L/3SrTFSywEcb3xzdej+3FwNu0S0+V4DbfEtUBIznOXMJ3Ggcy6bSYqSxF3SrxmsLVqodrOYgx1osdP590VwVF4OlySH+bkkbeJ7sUuvF2qTNr2FbwmiUFDh7qr5ymi21004FKlhQTDljvHYEEnovnddRgyto7/0cBK5xoseaRl6L0K8couoin4qfy0uJYvuC5b3pAY63juPIXn9vMyHmxSdudUNkyQCxLqkwAcO5SkurQMM3oWIcyjKK0OLMsJQkIN9xDolV6nEB/tGtkrGPK3O/jG360KbaLoMwKLbBuzd87ZAB/3DAipuumVgt3mAcKf6LvPCs5szu6gyfr8bBgFIYYWoHXLs2Nu20KR16eKUB/mnr3DTV5bJlV9hCCv+aq/jm2ZvTmdGdFwHW3jqGh1UVUX893wyAD6oF9wNaR1kFVUpMbfKX1YMa39GbwKCvScJV1j24mo5Olk4piQkomUi/Wi0gWawhDQ1xFsUzongH3XSElEKLxKab9nF3RJNqFuZBqB+cfb9ukiTIC287msTulImls2tx0CHhvQXcBDkeAvMNHKByvIaaUviwphuwysZGnImxMN7qyekWEN/TybG6ZQ/Rg4lVVBVtNQ8f9ohdB9kKKhwTqJcO/zP7eh8G0mQXJ6EMBUE424iqyjmrkJxOvyyebYV0xn9akftEu7jh/71brFxXj4FYL1cG/Md7vcxD+yZuwVqt2i2G8knqany9gK+rZuIYHF3dRop5pQya80R2nAyFdwMQiWIBBCYHRek6jVSbfFC4RxD36QXw7RpuTfGk9nNajtOMBOZDiLk3iyBdn5yyMyR2CXpYyY5tvsDY5enk4a2AfsE2ykRybdfkWTeUZreg2l4F3iNysl4v0JkS+QuE5ngMH3+RH/hhILmWttxxmDh32yeJY8ug5ekravJvlQ4o6uFTd68C+penNy4H9bdDplM9yzVSrMHny5idClVFGJoFBRGZKIVptHJvosxI2Oek76Vde4uv1J+InNwDbTq+96WFGEH/AqHYOumPRbRv+zkGEuv9AXYkzTs01pjJKdIh4Es9IwyhULWTN0KysOcqpqSlxOrKCPZah+3Y3sGxMZitvp1qdrOjp5Eoq+Wjvu5JuwEanGzfwSAt0nR41x8H/gkeGgAnb0V9mLHJ4aVYVsyjDcGAg/Ne6biF67xtaA+o9Rk/lthgWx3/ozqlSbAYFbFUDdAVpl1vNSO9N0bMqVllJ/Y4VKZXwqd/R8A5NQ8d/3bv7akEJ/nCJwWcteNFXkIfJTOLjG/DvZn/n8JoRsVcD9ZaYOBKJgLius2jD3mEdooXum07Vr/4bpO4RwZ7WUash9YL8llxR0ymDg3Y3CMrIPUcivEiLYXo8TPmCDcpkUWrLxpiBYi+/v0h/GUV7I0sXP4Pqc7bU7P3rzaJS4Y7onbmcRnP9z84D6AfEkqZH/0ERc0V6JwNmDfbiDwOFPPheIuPmWQWR2DjvEbcCKlEPLCspFuXJAq8qgJ6vu7kEaTbetXYzvymGDHg3zoIfUUy0fECypCUNmS1uezsJQXkjFykExjJEKtkabmYu4lj6nvFEznDzaRIHktrsmhMut+hHBc+dg6avtiHNkpcGuculgD1pZCXbl7xOOaDx07BkTZWJeshrFpeb5ZsuzCYRbPEGTaDUoyyzISyxiXKh2Ok/X0z+Q8TNv40KEjus2M/GruoqYwhIpoPjwcBnUdvByqMNB4Sxho8+6keuXiAeYVqFchZhoFMhcMJ0KqzcH5mrGLs5uvNS4vlM1gakxleGzWCw9v344YeR7X2mewaC5UyfVo28wS1HawAwpYyhxGLksBO26Vxbi0DD43Yt/RkNhJozKN8Mm9U3C7vsGTPLfqcqrOqScdjLu8IyNy7U07qfbkR+3IOaAbyI+xwCB+nsfN0C2/Mp5iHv6QpaNGZHTwJVPcH2v0KD1Sk2Bd+pp0iadyXNXn2T/Iear/FM1/FEJO2jdfF8JbGc7nS5H22izAyTEdSGvZq9GDf/aYwyuiLjlj7ZrHGMJIH4lNU7bUml8WS+p9KoD5jLNYYXBniDUlwtHQ4te7hI/BLd+tM1FJfT4GEsrSCcMdmkt4849E0Sgzw0SXMQ8O054zYgR6cTgafLYha/ExIFgbQg2A3Ziz9hw+onZyIRIXWpQKWgIkxNFkz4S6THcq8AqTgTI+nvNPsW19AKaM95m7mtER2gmpotnuaUH77LLWx78tpfTAdVL+SBv0LKc4n/ldjhzQsAft8G6vy4LRaNcAe9IIk4h2WkRytkw28v5ZjhGpiuYg6zqd/8WP2neK49R25he3/gG6JkVP9c1Pt7GxMxX0OV20ZeDr/EG7NVc4DBPfuMCkGxOeoT11VMKVPNlBZnfAl5Zd4TsmOHI+rs48wyhRmXvTlFLhcNYT1WeL26I8SePkFJGbuYzkstMhEEzJJv1rjEd918eCmVZ7XROVWSMI0fNci03N8pnEBB6RKwdBzDY3Xx1A61t20sDZkQrAKuxBypLJVIPOp4tBw/Ph5WjDBPoNOnZYV/KsLRQ354wuTo3jiI+/QSLJ/2SSofYWDIY0M8+TXxZ5Z2AeSXTro9exKl6kHIBvg2il43RzQOAZKN/h6uO5okiLxqXGVeTOKGDg6rbzz7kazFJ3cUiI3NaRWbYSind+jAb99ai4TZYFz8X6yU212wjd+mdbgQMEiTZGX0O+zdMbu1Rjgz/HqzET8HOe/+BuPy3/2RdOn883/IvnEtYEwuyQyMpAnug/hAseBtOtRaPMX3HbU03d8BJojTWrh/1RHEZk/sWUrj7I0CTJmaZMJPxoMV7W0IzYrx4Bk5MINZIxGTLZjGXljNW76DLn19CDNYJ6w08hqRy9Q5bSu68LKM/S71eMJorm2P1fd3FZCM6mF10PCHWW2TiIpQ8fTs2wUOZ34gm2EpqbLmB452ZXmfpCCnpqRJlWzgUq1o/HXohArY1qYMR55WTTPFK4jy3fQDNFTARyUnjyZocEGCO70iPMPUP17HZg9gx4yoF3aPLzsrQ6rYRxHEVtTd4x1auHs8UIZvPp82dVM09isxShF4j9/BX8etXjuUz+Mr9gOKT5OCLDKzZBurQOQCLgrwJIesKw2HOIAyCfPvm4T071kLmLp6rLRXa+kTeCaDcOoz5FdbXupnoB221+eOEWlA5xy2iYe6GjEYpXCJmj5t4/UZhyJo2iFpQwOmcDfzNdciEOcvYtBg9od7H7O8306+O1hOrZNNUX+JA3Tx67TGNQFIrjt1oKd0+PL04xR87WHc02kjDd9f1IvIulMBdgsqaSG5sbKiIZzkdCjXqpONVFR9zCuhj9keJXXXkqJjoCGndzG8/rfeiyaZ/jxfJYZj0s23D5h+Jjw5F3qzmh7EcMMcVPq17drOKxknxBIikYl1MMdBf3jYmXxLhrBF33Naj+pz0/pWZkk/1dPy9FCRfarSZAPTfnziQ3J5NF8SGBZvrL8m+tjsEb2xppD9Uk9JPOh+N2Zl+l7dZ01ugeu4Wy9A2KoAXUHtxXLZfhld5XjSNUutmWhEtfTxbZoYyC427ZB+dAiL8R6KF4USv1eTalerCrs694nut9ew43bIf83sqOWljvII5joRxElmT+z7CnfME6dreKDSrUvbWPWzR83M0+9eKaYtMbQmsshOLkjEcfOjPpAgIi8hDwS/Og3RuuRSgyBr8wBXoUdQ+8VCXQbCnAgG4JI/0tLmsSXEpB6wlr8n41O33FRLkMmtx+ITp8H9eKSfcCSVuGFxz3UNdZdTSvHFvxE7D20XBsFsOm9yLO6sxKroCzn7qBJZsCLd/6Uc2pJG0tX1VpdzsBp5eUwE8aB2IIKvBkQ/WLjorTSv4F/LtiGjqX9sFz4RkjA2gHHniUAVshHPcqA630nImmahvMiJiNwVGbxVDmgGjeFMlbukeFkqo+Zs0fz2fef/cLaX6Uja5QH5Z95njbsi8lG/+56l03gCWouj3j8jQGPKvCRRzEUJPXwjaNUQWSgh+vrCRkHZey4LXk10WA1i09IMVwEeQiBikQhS16hwseu4AiXmaPecj1Q+avRLpWp47MVolLa0KlxAfQuEd+a0mGoJf0uNAm7Q4niA0KH6uuQRzkHVqR5vng1EElWLKpf/mdFpcaLrU/BqZH9I7lxtGkxapi6ErC9DwRQAmCAvNuIVULjlCsp0Pes2i/ErBFyfZzIQ6iOw85IGRzQhnMGZ1yrbal0hJOREgxwe3BMIu4PhZxwlUbOSt8br6Xoe1ervikqwJl34YcA8YqcN6CKgqXXdXpZe01AwaSBBfQ8ZyVDX94s/SdY5FqDtjn1B3iEgFvYOISHzcHaUAn/Tr5R+aUfSdUEtWLVe/rpK9Vob3BQsThm3lYXXNsBoZtxpbp6K7fDRWrUqNkFyeixCEX31CVjCLCCNF0q3u//9irar1SM3G1BJ0wc7lNZakWPGyyDzu7sMReZyYFwTWy8ML5Jkzfo9y0uzx1zZqw2fQ2GwXxpY1o08OsdvdEEo19ZJZDJIt8FL/NlzVtcy6ToplduDZiKfjz/6SwE+wHS98aMJ6ADaDycrv1z769EmdNjKSWi5PiiM0KKbeFe4ohFYnp2ld4l3hs6l9YWxcLkSeuXPqalpFOu9bL/CPZVhdH/Kr0oBPkifxA193vRv3ASpdSSZDCz0NNyOY+PPtd8Sk2cA9oAYMZiwuIFL9TRv8UkVYT7JYGWx1fqvfrcPxyy1LqdFBE40r+CeF71a1VbNgsm7kfGofVvFcptbwPUKYOpiVDWrrL/Ys64NtJlr3qw8PRfmEbD9S8eAgyxLXy8vS8/XvleD2Dfmzga5dY2/4nDBmyqDO0NkIVexnVbL7GuHZSe8QyNG/R7syQd1MAU5+tDlQ7rt/I9YjbQ9nWG1HH5EWKGCjxj0kxnxnYItZj+s0yTm+Xgpf9FHXY6OSMCFW6ag3tuSr3xyoQYNUAVK5+i4GHMsnWz2enRgIWBemPm9RjGsrpnZlxctfymIPzL86BzdaOOXmIClP9YF1T2bfQAoMYPL/gAycgpQbaIW+qViy/mmNH84lNjOV5jNtGvgi3UmTMvt8P6W2nTWE5Ix8aU78K+vx4KpXLVxOAg+b8twLTmp4sohGpwPriTjWxmMCjgMF/lz3CGesf9Nfph62ipX/a0QXTmNvUtXP7bVSvOXW/hzW+/hrR2Eh8ZW/C+eSo5lAbcMPxteLbpB5M6o85Zv/ntHh6pUsQVmk+zOygQ/jTtdeRq/CfoVnPHf5EuR3c4HLCyzfA5l2G8iaIg5y0c2jkg28ROFKQFBO8Ckaux1tAv2digVeWN+riwVih6nS6Xtzx6NrYF8bqYKIEbeKFr2msPMtjZczAWYC9QLctsnE+418g6AE8Nv0fXUnRNQesY4Nccya/LdSCorTctBIjGeyxF0+KEUipp0u36zCbtV9y6ZFlaQENq9V07BESkuFCCTaGMfs30GlqKFDYNK//B0uDAvFZ0ioyCTFRGvTcYu/EDciDmGaRXrJy9RExELHh2ipq7oCW4dn7rLbz+/fNoeG4vazNKOHxkNBjwoL+Ox6bFzbdM0Gne7+e2STXbedWbM6UBGUrl0K8OzG63zU4K9IGgh9rw8M1h480zlikFHopLmLJndARwGAydu47Lxk9R2pbt6U7xEwKIkMMHO9DuT/4aSaKYhxHCjN9uKNJ55Q3zgDkXQ7G+QvcPNhwZzxz2xDrnMxPr4Wc3NUtES4dd0UavSxLrhFC6PRNGH9HyAIvWdj0UI0iUa5Kg0tsEVW5+dA5lEmaKi93PhWusSkJUQd5WOe4t8uNhnBon717Zik9sjtUt7oRQR1u23Zph0MwG1SBfaT+ytcfV2oq74Bc0hU/wYjwNAe36XA1vM/VsK/Nio1j3HigvvYfbt9uA45jVovRwCbQXsCdpDSH+QFgeRq4Pd0tDjC0KrM1qaV2huHTqLeizWmhNRR1tD9jfuvixC0Cv6xSrbYp23BdBZHLrjf7Qv4g1vf8TR1X0Dh/FbO6TiCYFfmlz+hUoaFFYbGBe9QWtd3NReGssj33VreQqM+vToXyzQrycf9o593T0YrjrN1Y0m4uQSAKFjpfZbU5yzo0eycRmiTWif0WzhXmKURgHSH0A78zmAveEEYG8BC4NYOhwgNCVhF408AopcoVnzVv4xtBhX02q7zE/MDyQkYAuH8kgcrdmVfmkM4SiowwQLNEgNObt9o6uGRmxER1Ayzon0quGO7G8mBwZNRRBVQo+M14DZGhOyN2/LM17g+U8WfLN4lJ/UDe6uFdCKxYuFMfAV2XrHz5Sk8yd5Ib9MHEzjqnHxRavrOwEYCi2//ZITXkAJlzbP9f757J2T4v63qkhFCIytii+l6lr3/BT8ZrFlp6BcMjC/K1R2RvpiRWArX/6+biavrQ+18GnL5ZzkvQWzp01ApBOHj0GWWYe60wlfhBusxH43Hfl1b5mXJJn/+BWWlNB+xzktY+NheJDdsmqLcbeYdAW+x0JHGxFaaHlfEOF1ZPSghrYTostYTLADvkREC2vagQgu1nrCF6Ds7rVWE3pn7KwEgf2UAg5hmM1FtAx0uYXz3S6YIcrm6HzYC62SXev0ZmbIh6mxL6YPipUycHi60tRg3NlY+/qFqB94pJzD5HdFKK/35IgfLvIqmkz4CYRnYM+2P0kNOby2tI5DWUqGMuGicfka5x0bW8y8l9B2nAZig9CpGZmvnZHx9Zyj7eULe5dfmyphoTPAk1MdG6LphbOyTnefHDAfqUOtoKoZ/nHiKZBsqaDq66wEjx39rHMX8TEMaMkIQKq65HKdy3eFISz5Er8KTB7QD6IYxFEQmFm2AdXQoLBNirxse75FNsL7Tmlt5J10HwZ+NvdzbEufokH+ZQHMh8gqPHtgz5SRYq59Pwjj0JwNDR6LRp0OLHc7WYaI0qP3HCyq+7BeEXHv9wxoxkZXtcn6eoYhhMOiyAxeP2quKSjb9Q3Wk+/eT+gp7MvJKzlwNfsVIZecGQuIPSQxsadywThScRg/AE+OaT40+tt+WXh2xPTNiOiQBFXdriQNFidwL53B7tUW00yDkkNVBs8ZbKDDem4PTwUdIAmYFCh1ZBDrOoTlfeid7Jxrg8kEjYdmK23BLy8Qb0c8g1RnR6XMLZHNbHPzgf8mWxSMnXwZiM/Fbw5hu9qaPdljKZLIa3g9NDyfkBFnDzqSNgR3iYKMdg2udQaCQCFEWnXZJ5MZSmqOv3bl36eBdrlNsEBI9zxp+g/O33XrFJw6SLieF+r4VklP28+pt6UsQh4nlVUBa6TUV6EfzH15mPvv05H8XMfa4nblsh6gGRT/3V6lKkfkLZctTa799l+e4Bn2yTm+1UaAWwUSniBrNaT04grhO1BF2vGmGPYfCkXsNyVvMGyVnhWy2hFvLQyEKSJMYeCdgVDy5RAkMSOaqZUVhT6T9sxyFIh9qLl32Zid4S5KNSxPdHKE3KF6Mo0Q4lV85FPNF4dtk/bcglpWb7wKxFu5tD8aNGn3A/PkxRrbyqOC1I+RH2XV1KU4ew8qpCkxtd2+v3MRP9UQUcH1SYSuZESRM7pvrzvckOUrnA7OfXcTQG/5tEtuhNUcfVDr7Tksmk7zgZQwR2n5mSk97AlRPnwI7rXMZpC2Jy7uGg5IOyzkomvdfSS0cdT9GBqPLZNyth3TrMiTHfhQw0CfHpETL0sIWmcwAJ3wXqfYx4IeJSH+SBUG/559adnc/8Vks7Dbu/KFActEz5wcwqo3456wrVMK/fncBn3XE0IvAPzbhAjPjNv96DcQI5AIpwmOaARfZo9ke0ZLvg6ldwHGvKQ2VAikybSrAimIXN2pM8PftefCJaMDYPhTjdQJ/E5wBXvdKaZU1/OMV2O3Oo02Cft2KJdf78et4HqchTLBRTDmB2ZipBJhhfW+AwjOqU/vu7je2VDKnodEk/R2bE0DNQfIIX/5Ob+gpUcl0F3mz153IYxv7BdP8+U5AZX7d7pM6kW+GJMbvb9KUKcXgym8mlJ/yQlLIMRkgmT3ybImr6EzmUJmYUD/MsU7U6COfa2KbtfHIxjB+iGNJjEHG1UkzctYG9nYAPwnUYNEIxGEAu7oOIOAgrA36LwFFwHyvUA2OJ0jR2SrgCLIQFqZzMk4nONJjWB3qY7eB7tg3mA564X8lhoZAxSMIV3+w6V/sb3sL59bcBhc5OMK2AMGOZ21KUySyxwDdvOuHqsethXcUhB8GWNqEcMnclgzurnwlw8JF8zruDZzlgwF6cGkX0DrB6ps1zxdUt5qhpD/FgnMi1lAk4TKhtxGu2LXFeom7LLKwqp8blVmleAi89U2J5M5xwMxNC/4B4B2Z44bHElUggKLKDhcszm32d3YMPE4Zy6jHiW2T6b7RM3XBXS2zyTL5/PTpna2ItDN1m/L1DlGzrpDArcosG2dBzrmD2GTj7yVORbvumRzeNccjBQ6I2FSLcdmfa3iap6A8r1JlcRBMmDRIY4wfczdVCqcKVEMBjw8SAzMaoJP/j7GAVBS9XuwTtYjAZllobk2iny5GGOL4zwKgRMjVD1kbiOLkozYJWxlZ3TWWxTTv8sn1P/0vLyAQzDPyORiJUwo077aWzU64IquMz/e4RsThFh78EAVBqoKcbUz3grt3gXNYaIp7LjU1nQLQZOYIq2IHvnEyyp07AmLcynB83RUWJjwLu1PBkZ1P4KmpC3QGO5Ut8SXrNzy9T6hDp/Yedpd7OlaARGhPWM2OgHx5jOV2RpOfxxLUNFhkEjB6VHE2DuZDFPSpDiAyBkYImsYHyXsCaNOI+mvQuXzjT+1D/VEI1yinA1Kc/oq+H7oW6+TzgRVBf4We184QHSewTqcEZCQ/IEZ7pMCyAf0QWK02J+JROFzV7JGfQRRy9uml9ZbsL3Pzi6y4iI8C7E9s/Kq8JFuvJ3R2T+ZEStlSgAEjDbXi5QDJYgHeB5Z+AaiYKlYSeEYLmn6/1nISO8Js2W/M2uT4nJhw+Lv2mf8TuMd7z4yucRF4pIpfNDAnCaxx+q7VXjAVODA7N43oyeJXHDVjpOPHrOksBUosM0zBTyfJN+78Cv+MR846yZlnTogt/123Fan6sH2nW2Ed3ZmE/3pnOucsTPAr/JsDjEV1jv+i/WZuk05FiDdR3Xe6h+729iL/6rbxwIYsnhC4WwXjPUuBrLVeoSZMS/H7vV5ZZmMcPdlAcA/vB12millDpUTVJ7AgzL5BiSBj2Voq9ij9iGbGjrCMA2oCeqUBhke3SYFbzlbsd7JEvr6lxAZBH5og8ffXopy/uhjppYbRLvxuS11ee4yAUuXEl/JJovwBUvIiFkiQTDrZWXGDuekADu2omQFvWMjrrj8j2JRuDg85Tc/WaWqhe6fWNpfjWXioo95Rd/zhTEbLsp378n0hCDJAsq8r4VqgJqUQWAfnORMNl8U75awjgadwiq4Ysg6PW0DY7RxzZstXY+eMWSPko4aHLK5gQPL7qjZ/SqMwDZB1zwKmntEONCvdXW7IW8wsrzbymKoF0dtsVLfmay0rwhrH7CS5Nt6ITbH9BoTWLWhVeu2Xa0J0RDbyQW07hc9OTeUEilmgwdhJ2CDIu6tX7/P+9zdQ0BzbtVT6PdTgrJMxo4yXk3h+w1Zm5GEQEr8JClnlwZP9c+syi7vfJpPptYOk+dtres2iE+JjZ46LKyoDip+mrcZ3QH//yQXQTDMq8p8UJHgOrcrctDVUirAnx8sdLx1NO0TfQn3yqJhF1TtK3lUWffNQwDidURqj7Klj3I7lN7uCH2tp+rubRnCcu83GJNGKJmS3P9csQgK9nFZSQrkwKK+fDaiqgLP7zOSktb4zGs1i4VBAFa+ynDn9v7LhuGuc/6pohagPzPW/zjk1CESSKyMoAOZaHhpvqUCDNNjxYeKRxpu908cxjf9/e2G/E9m9+hhCPU9230flpXnjxcLUkZxn72uTvM88HZsAE7bJ6C0hykW+Jl72VeannDUfyCi/hUS6Y41F19ZhKi3A+rBeTJPSII9JD3xjSXizqDtIRcF6LXWBBMZ3AC50JTTMfKKvD1R4k66DYisy4SaBEfGJk1meeeIKpMbtEvG5QeEj1Bdjl36aKbRVScAU8wNgszpKPeyEuARsHOVK0RI7ErUkwdamZNPwFAsQN5/6JUieGVx4z+GXlkFn3t59HV9d5q9FFGJjc3LODsELqUfkFM0CJ1MpeN0LR5V13zIkN/qJR8ODckQar2aFxdYivwgbRUFk5Ipky5Ohmxou/3FCQRW8UuKQfZaBGSD6UMQ6j6UoLSd1QCgXWlvttbJ0/8U0S+6K6ziI68OoQ3SbxI0MDaKlF5lTDjLeOA2MhIRsgdqoVoUESQTmDowgJ5v3FwFVPwxGh1YDJfdLiJuHIbHX8my5r2kTtK5MaezMJlH89dfjwHgLElWOpF7bf7VWa7KP44Qj0hlb2r6XSOHD86pfjCGeYBr9nKsTsA3g5WpDb78coGU6e5xNtqmIMBljKZd30TM9l123tKvFWhL2UiKaQ/xIP1nbTUMeLx4xhHfJrlD3U9lDky2/YTdMTU9APU+UBsfpMWrExgbiNIQhj9sDhypGwYDL4tnszIy/0pQq1GGnZ7pbXMlp9GwksEbfOaghBNrNMsZ4rZPup9LAo8Bv+MQ32ZJlLMBhi3e4Sunk3kJuFa3lMeKf6DWhs0HYGhN4/jVcDKkGnc3E/DQWcwkJHMrw3Glt2+7KF8bFgNMLLsLRmVASA8hMBQPwhCAKmhGzENlxRwPSaYVY+z7G+D7o2yJmFZJmbjkvBCozpCjw7s/FOAudlzXyh+swWRW030olUvfg1TyS5eV4vN0doyOkDXTiG3IZvrAORCOL2RxUrdtq7ahgJduRBbKeFD7J9De1L/FCJXopybJzJ58j8uBLyflH8lEEFv6KQ+06hMbl/gVRUZwI8LHcuCw2lx+yRePC7zU+0mQxnhC+1TzXlgUiHPGnM5qVKncf21D5/uxKELXP4wJTF7y855SJA46lhBA9gZyB1qgP1VAsuhKE2IE01H7twYNVKUlN/vp/KfKU0N738q/NX5FL8PthFZ2qjGn0ieyzJYxl2/phiJzlZsAKOVVhVzcsnCgddECZ4SNHw4pOQGRklqbonfbyaezzZ2qYkxbruaZbuqcWq3BYw4uP+F3CNzIX6Umv+TKedrLB+/SvV3xe2CHEUI3gIXi/jksBFLac0WxCcgFCX34MUOV+i71qZXeJ+P6+/jiaY9AwxOq7Yg0mDvvUofqbt6Xs7fbMFkxJUjRkbqWhOyU8k4bqKgdSN8l6+wu4YZHLfSlJHESjXqyj4WloXoc+cyx//xOrHmyysWm4W6aUvvw1pDODe8NpG/MyRxkSlbosCv4/wWTWLmEtSegU0DGfcd0yTHHy7n0ouQu/nFsR2Ina+qMgqi8eSjpmJ6hTC3oHpI8Okr6C5Kn8lUmtbSLu1LeV5kv01jglDVtHMHisjbHI+Gf8fDBWge2ouLabOlESca9SeVudKh5677LNPTYmlF8890ZiQ9Z/YHcSm+LbsgOLBrQs30QhdBxWbRRvlQJJ0B+I4xIdu2gwX/xOqGcoeM/xfgDlG6kf5/qBr0uVo9J49jkMxKF8qReKNwxk59LqyigrF38/NjY2HkgbK8tfbIw5wj6g5PBiuhFkmTK5KtzkzSMwdad2EDG2FM5Kfrc91XQVtx4NtyHKUHtshAovPnFodcWCzr4vPpx6bgUmtiGQmTXukqQ5qKPRFYBFQw4QZ/kweYvHt9QWLJbhaIl+UEfEk+hYLH+GLvWR3UjvWMMY44JiLcDASX1RdlugBx3yw0emIAswJt45MGw/vCYpeksXFYjQGH3geVOZPn+M5ZCr4Bsr5YclECL/sIyPOLjrniH5Yh2+zoXroULYHSGgkKgopAsLLWbJC6QwHmWmdno7AAeNOORkuOexMq+WUqxzmSvxRkTu14h1VYFK5KqENPIetTJC0ILHwinJm22UJuYzaEJbC8igdkxaLVeeWYSBbT1FqidAJGcBIiwcaG7TgWQSPUccI6H2BRav9LcGDUWJNRkMT721f0wo6Ts86ArDdS+71GvjX53z4kkePTPzzqzY2PmvX5w4StQDqv/dnZ+ktEKE8Cf0ddrHi1ChnZMkXZzzI2ZuW8GShhbVjIs1CIC50vrSnThTtLZ3G/3ANjvFYSq2MTV+dJLFaCIQjwIsuYGNRterLA+fMgCo7XAyq35FbkXm6PNlha5WQrVn0qifI0SbckulJ7hjtgtNIdFsyFo/INCEOTM4UWGqTmZjKLTBC5rlo1Zst2jFBkkiHoyjJg3NZLWAPWLlEyUeO0qm2tdv/3dCmsCQ60DMeOgwiKyssaFJSgciQmY0vGWLCQCOGX5JcsyUb3SiXmR1b8DhtXoD2wNEaP/DOPl5TgLx9eJB1JMErO5WACs0xb9ev45LxIJfqOC/1lKGaK9nSD6MzMNlmRVxfIqExyCUh2X6XJbfM1CJOn+wwa/E4XiOeAHJUA8qt0BVw8rVgf21OWuGXXYIn0IKcRGSivNWMcvqVlHcEVjlrRgFkHV+DsPYnJp8+7jVmsfJWUIQ/jiZ5x29JXLpVODYhHawzaTIISK/gI2cbWW0zCcY/z1oyB32lFpo6px1jrB3x2XtiwlTqfGoiP2SkkuTj5StlvvF4SKWNx5IQICA6rPlc9KFKiodYyxy2kbwUyb7ouR2FrirC4rVb24Lj1w9N0dy4gWTqxoQfW58aN1p0eAYMVHPWwEbsJpYDSuqbVYH+8Kwl//qIVfLBtEeQGXUbSxbj6PEe7lfFuckYTgYIDQGp6x3kQGBm2cK6YxTPUDFaMyqElLzUwJnMudwsii1cI9fR47i+M1G/hL7iBE+1O/A01jD42w07cvYoqPFX5BxSyKQBE92OaIJLtYvPZkACQYC6DYdBPMPM/mkq4jgvAddSpcgvttymP5FI4soH8pvBw54KtKGe/YL5Sw3hkXPxSnpDTFdcEksg9Ioo0MVQDiJ9AQMaDdvPqzceIyqDOPStnRm+hVYHYTYGakGPo41RGH/Qi0wKSm6p+rDqaM3x2kezuFF8D5CJypij8owCNPLAfzQwEc6PK0C+Tzfzq/jU+IejfNIUOfhl1M5PexqzQQ0kkeMv5JtcgKQVfFodsbataaOAERs8uWUp+s8cq2SODkODIDl668j/QGwn/dmqsvPDMlrBU6mqy9uyAyHW63DnnrcqqKB8U4RAHd+ta+CbfVDPUOlEcyKrG7W6VWdf++FYCMivgplfmvjmbIapa7OKl1HgFFG+q2M/qZE+a6v7fgjWLfjHGnEPxnlkS3sEx7dMhpdokwOqI2bDoQGskfbT4PnfN5knSj6BTzaAzEkMyrBbkf4mhaezD7XQiaeNmXAc7l+Ezcum7iWpw4nG8g5h3QGGSOcRmvHIspxOY5tn/kj0Rrg+DtArSM22uVhz8jPup7B8yM062iv4KSnOBLoyLwf9WZJLNduXjxnNCtRnkhB7M6+HuW2WzBqzBgb2SWn4iSFaWhEioCVo2uVTUWAomJp11LNiPBL9cXFuegxxEg2A3fQUBuX4QJszXCBsaLgNgQbyGe2pOjIwXnIqqp3iuZJ8vdc4lUogKzkZrixBAS2lnlo6oWKRwVpRGRlFmrtrZLAAw06nWKap6qHpFPv94za7327uqojLYdfbma6m25jEycG6Po+d9/3JyqVF0HJOphGtGxUI4wXyAMLDT8/Oqeuaky8LHNFSV5JI2V8CwWyNq8EurQT5hr4BjEbjVExJavIAnTzsLOpFrgXMpDDlzGHwNXK4koMeHu9beEEFypn1oUNRt7qiDLzfIivqD2mOBRSqh6bK+P9nJWF0w5ZOQdxa3qkfroiCdRpC3OnvJom1TqJlWEwHSXzp4Uv8gpwbVxr4dBDXAEClRLfUNUhyxPRdKWGCq4mr42I3ptGabxo0jhXPTLk9hC5lRB3hxqwovdTjZXD3TsxaP55vIDa64c9jcVajMNc3n2oisGEPKken1C5ccLF2BxNGZfCepevLYjgMSi+xQ5TQ9mAJAJzCCYMRkmsRnzlT+A5R7RW5kTLfqR5YpeAHFnv6/h+sbh2YhISu2ofYdz+K4WbAmiNYxNkqA8juCsSDNyada9zmlRfjowihwUbEUOvd065HWIa0iIZZvr8hj9hQzUmg93Rb6Ld3XzsoUKZYOrMFnQ9VHM4UbEgt+BaGtr40E3JU9osugBq9Qw6vEXqKaWzqta3C0fCx5+EsGGvlmXv8OtkKtfs1LnW9h+lLHHBFmi/Grr3vcw6T4C9ycgFRwzpLVhBbpQb/sueJtFv+nYnZH8o8G8TmOXsPAoK8VKb51AI9UZaiMO89SDLfcvkfKuK4py5uS3o5Du6vBr0Ehbnvc2qCW2ACE1cOTb3AkkMGxi/mdUbIjNy/O1+J1J8TJJBiotTHRkgyHuBCuZiCVM1bMDDfaN4xQcrlQIFFneFiFTd+/0g9sa1rIBo2CnvLY5OyXT0teoM+Ms7qYigMrf7/OZNqkWcyXYUR+ZwmH5bgXQ1oHjA7wHjMoSFJefafRI9iy2+y/HzGMjj3FWMbWOrc7tGDu4WLcHz7+n0QiNoZeIxnBpnMBPytBKal5m41lVU4z7JSVANkCDRLy7y9xgUnuxycKoMCWFX/9/dulOGXyWG0o0Hp//KunJJDEl2dbdNyCDarQxXEjTYTRESSal7cHrJRS8djWDTtdlsNrLsl8z5NmXqSAl1aeA6qr7C7hDjyjJMOdeqlqihAYfZNhPVyAOlHONDwKLSDOmHKOp18QAKVOI+GLOdtiZMrzkOXpnaQphUfdheLkOivlzqIlUTkYTLEZOhWbJK2Etrlu/EYTy0smp1pd710xd4g248yApgttK+iymNmwaORo8X8ot2tSzPIOp0TIqDUplrVFYZTs7VpQfxXbTIEvEpVcommnSghT99VGpw4I5y647KsSBOw0Gekt4kl+ZhtmSKtNCJZYoC9mlj3htp48YEB/RSOKZgpWzIKWAAzaibIPfeHHQ3NChHcdZG6rUjdsDmxMERWDuKPhVK+jaVise63GbckzBc7E/rNea1fhjp5UAGFCnFV8csxG1hW46qNtuXI8bApxFNBJ5qCYONngHuYJrKrkScCYWhh/UMKhF7HRUxfdetvhj3DPpDTD+kf23+cL+yXSujeYMfB9J2AauooSTehJrjQX+pTZWRfekRVzTVKqtif7Sr1FRud+LC73lt/oqiLgG0zL2EHoNDoDKmYVA+R5s+R7flgb+UvkMH1vvYrmLp+G9q/YkMCSuKe30lbsKNw8I5JPv4cS3iF4GJwXmcF97lS0N4yfeI+Wk93fHYMHW59H/fJxTpWp/QUbBj6VQkcCBUggDr15EC6Kik7GkpVcD9MSwlWsKWWuimqdpt37OP+gQ1Bn+yHNaF6Dao+3M10U808htLDEGVWOp1eH40nRvE+wWNx4ufTkwmAV9/HHN5CyIwfA4izMupjlfTU4FXxAKwUJb3PHrLQ85EYSO0s6QTCFlPb6EQC06bTiHBFkvJ3bHAZ4l4s/9HMIAAqmXAR+mpk5NT7rVPSyRNuEg7+gWqE8tmBB5r496kXiHtUAg2Vf+eIq1lxxzMjIb5Z+TjtFYYa0gc2+utkyEDdqOPvkBAqLAAvpggsIwB/ee2i2iM1rcYt94Cu7rJ0GB8s9gPUFylOBcE2MXQuMSkaMG8IHGYF4dNhmnMgpqQVmpVzU5UdUEICvuVVxm+OgaIgjVshZ78JaiBpjPoieNzq3Yd/Gd8FGJOVf6q+0N8SyBaF1/xL7YDkdI1bxhP4qKr1Xkiqd7WuWuh2pxdAz8wLYVZX48Dr0wBqudozqXnF8CsnumTZmwQeQl+QxeEyjbJ01UnSTNcX8QNqOdEeT/P0QL8TFv9/MMo5QvTQfperPXvdJeUIcWlVfev+Y5Y5HZi3pyNUfFwoWDWSxWD/32SnSnK+9DoyTaSbs91pE1gjcj3V4hLlTBZZtjQDESnL8p6pZXbxMcIL7ekRGo2z7T/V0Zh2U9cv1k/rWrwdsydJSezyNIOM1HoKPumhG5rXOfBh6aUNW69CNKdLjxypQtIPJ3dEAEZ1ogjevk5vS+obSK+FhZE+Vj59/o3Xy4zECO79VSB+Yu5LEgcBMm/GXrx3vP2FEH4AZVFg6zQAhCsC98fxRtSYrW9bk5vzAKZ7yQh41NTpKthciojXBUOcBDSoLIJ66LD3F1m7IGwv/fnCP1QNR63S4GlF5tan/QRw1HkGmyO6xfCzF0L9QTGtsAto+soXAvvFQEsxyXQXKpMbgBqe4HWYW+HAhagQsklfxqPwpu2z9fAlh6mmsALifOBu7cq2w0Y50KXOXGw8BtORpOqHUOzyXj0iehcxW7ysWC8nAzSDQzhM4QacQcP0JlIfyK997YNTQ//U7P1+dXf/XqK/QcvhK9ZDI53+7hzCfwTSp71kmK7Z6PJC50hqbWf2La3L/ORy3OCPq2Wq7FKbWM1/AbwBoGmxN0RltH5j6yZ38BIkhFwcFTlT2vAL/7fQHC3O34Jfy3Z8IHKDg7DHnPq/tcuz2EAnSF5C4XX5NLb/xwu/00yxPBcNk58AuesPKPYpBZe8yne3+oerngPJppO+1XAc1DcGFv9YLvsQA8D1YXWDM15aWDAbXG0AVGPx1qZF3RAUuTPQKkpszd/owFPiy650+WV+7dsrJVHl+gTYuOAGhXxd25+RpztQGyZ0r5bMzz6hhbsdGh6OF+r70Ny4Qo/8njCgobh9reuqc+MLbHCUr1fYiCTGtE8PEDYcwv16BTjLuTIz7Rmwivv+51+mtsIFiaYF+zucKZRUQ0NMK8EJYVEkgVfZrhe7Q3Kgi5cPl7rpcCU3rWg8w1vuQBgb2t9LjPQQw6FKykzb1YnbEnfFmsb9kFgfQvb4VlvbyKh8WS1NFzYnu0SePASm1jI47eZ6zqnCoi5bHoumPm/Pn2uj/HLiXu1B1Sr+fRgIlr58mtjhq0L70MSbRN4HGBkPT/OBT4f8bjjbMKr4IzlB5/46Q4ktcfAOP28v1nkx9gzoy3FKdHfnbVnV0AafOswdFrSpnXQyfWHLLC/f3ELsTBZr0qcr9oSgnY/jo5+KlJltVZN7jrvtU0ygqihz87QVLl4wDPD+a1bxWg/X5Zga1RqlZdqJAYa+V0gz0S5IFjqM5Dc463iEcUOfYCWpzPYhkzHM/6A3l3ENYj00/eYhKK6l/ns0hgcwFkRRbii6VgyFZA8krjezqxCs8nRmSSqLO7AoxZvB9nwhpbuBsiHuKFj6yFRL9HwebFFG0ReKbfFEHHJBj9wfNZ7i574cZ+MnnCKd7KYxLM3EePbBkzjZfaRymAlqRuAmE4YhiTUgLApPJGu1wef6K1GYVzpZjoEMjE8Ra4hcA+rjlOJaSluBqBx4XCroxzvXqZl1+5OAwFHOTXXx7dlDb+od7WAkGAYI6L5TZs3XSv9ji7UROyYQBEh4cS7Kn5mH6QzALuaNSLMN2VkocxN+bRe7Ux29c3SqoWuv32EPReH/p6dMsWYD3V08UDXUwwrcZrkoAJJjoyVquLfEz1B5kq8bSDj4LhsmUUCw5uDQFTIOCUW/EAr/1qdtxI19Bn88sAFygoow5oiXbscSlCL/ZzgAScerVxCQuyPBmnaX3+8q/OmzIHkNdIqqFzkNI9iORdudDc7RCjv8zUrcsFNdHus2HAV6R3qQ/0idX2D6teXE67JnBiupGNrE5L7zS90iUHlo9HTNmoUaJLx8zeRoPRhIUHXHRVozvZAoUtVs8yg4KwjBrHwq8Lyg1tiO3e7z7De0IxcVA+SYGxBlIgHNVjzbIJbx8RH/SlwaSb0ZabOZiMVOi+zOv7IuHv3Hgu2QY4EwHMK4lX4ZU0ogqfgROMd1VghyaJd0xDVVEtE6rfBX+0xGkKkgtjJA+75NulrjHQs7oQfCFnaIHcvN1N0K3sp0ZNUaxDI218pEqNgsKpJITWxWiqkr60aHbeD3tbttwjwfSBMYDw1edGF2o77rJQqFn7VFiz9IeiCEFfIEzXD6dreDPpLJ/XuhspDHOZnmle6wPT8vLlY/5b62L+3eoJjzzE3EEZdE5gnWYUoyW3Wi+j4lYhK0pXbBHvF8JQu+wfoDpTH6wQbFdEZB7UjPDs8Lwp/6YqpXB9P25EhXBhD9FBKBGTz9MjE5aQGnCcqZJ5RpZCw3mhdEoYbXZq1X9qQYxTGBjRbogjjV0Nvh2avTkoGFha9L5N2AHkngyZd7ABPGxP2XNhvkDXja7PR5vUDMMXFVVi1sPDbNMLB58f6NfqYEXTACRx9pOHi8UQjzI2wDurXQpl+KKnJMrWuMbqq082EVSkbOB1xjNfnGs0v6Xv2vhb6Z4XJhgOf5pLWl/mWhoTDoPRl8thjnhnPOKVVV+C64jhJrbGzytjsOPAksmGPJm2enoVW9Sb/Y7oKAK8pT2rn29fLxjyZWRvW01ogCaLC+6mdb/1bPNTrcDPJ9C5LzvkciWbsxw/AqUPGXkUkRJ6q/bCKgpsa2+u5g0jYQhREh9VrDu9C3WcAUpepYPfMqj50JRYxooRi4NGWeEHGNSqnTnVGZHgCotG59KSlfPcAtn5OIs8HPqr5xY0FM7tcXtUPG/LHIJErW528Txqw71+Q3JB0UGWsNFC1xqwF+Gzta2yU8Ytz0Lo0awu5NXwhV4cBjBFSnaIZ9md0z8j9zJHzpUw8z4h/SB8MEWg5jB6M2Im3mqzZZdgtUmvMnUKb+YHeS6VylFWeni0Dmaun6+9M8he4KJlCGulaHad2GcewazvRW1YqwPUow4AP/UCvpDRSKV9DIW/Wj9+CxGkr7QIg8A/MAFI7FESN+V4az6n6EtzkrqT3D6LkiPo1x7pcb2SlhFotzvzTBg0ydGV9h6+GYQFD9Q08/aGv3uywh39iLqjRfKy8b6xRZ/t+qAInPAJNgMST87pNZMizPCzFf40RHumBZiS+hyqSgWFKopUmQrhU0BLmekI4BthAO5NXNRaqTvcs7HCDVxCcGKYu18XNKldGlcUIpFBGjrcv20gMAgQ3/hg/fLaWEs/YPGBwcCuW5DL+T8IhpF3RRNR97HCc1GOG52Lmj4LNx1V8CXwA73fkqdiwpbuWOed0/n7U68uDQHE1blVY+uJwzzW7y6xeSOjOu1SMU24eaTeXsr+hxaGXiZi0c7WUWtMdgsB3LddJBgt8r32S8qpKVotYEC356HOWH6CTEbomYyEdMIxljbhrgLsOj772F9Kbm5miHdghICeZfSdXNt5PCO/MWtah0TYh3l6Py6FRqn/eRfr2+MJu3ioPUFwaFUbsmIcHJBJ0mxUaYSAXCpoTk7KKMaPiOUbExi+tTyYH3c2q2nssgXXDVSiHQdxNdBmbBXTGGkPXXRsz0alW0kCyJ+xQPsZkr84U+EfcwALOCQ1tISuCJWSf35UySBdWlpDeOsIT9lLxbRYvdSvOEoVe+1AFACMZG5wx6Yz2PldveTPYgwnIjOZtNZH30p0dPfzyJh3jNT0TOltvb9EIa9lUphL0HS2v5vltQ+UE1unFReJKljjMWZLOOFPC+oRdFgEFFrqxfcAs7LIHQTzWFVPbZ1RwKJzSqKldl71tF3KCuZK2vWXMUFf44PeDF9Nmng0+gzAEZr6DcEzudXIuXGEus0Hcd4Pa5vxZu2ts3/zhauMkGpm3igp6WhWYNAKAFd0vMi9njodNWMWsJhzKE4QbNW0yVTZArzJExwUdqAGTuNgHzxotFtjK7SLLBvEmxjMT+rlWfu9ZDiGsmdo0yJaTYRKVRZc5WXuAIfxxbcHVbXF6viT0WN09GCRjnithR6FN6Iw8N7Tvf+gw/co2TVfm1Wsn4Q1jzTa081mbtUdEs6vvIjaKvhdciS7KmwsAGnWpJ2IB3o4G+N3dwSsEMccaBOxHuaIFC0/CNGNNR+H23R+vZQzi/8eMIYEcRaybRpOMyfzd0FZtnXQTZx1K+pDtFflLOycPEtx8YaQo+eaopkioJZamjR4bjrWVLspABVBqM6cTD4cOiS4taLNOxX02rreYV1iUGZT1dK5IKYtVRSHfEFzCtHLYiSCtP8emBuCsgYAyofv7GH8hBmBJKfsFE3Ds3b32O4msSr55DGl4YwHTUk4Gpg/jKuiNHuVKPAVunkpvahXmPTtDf2/CmzE/FNWd5wVQaG0r/YHBuHHzn5ZRxw+fYjtje+dXYuGe+IDxBtru6oSic5Dba/aCb4rAA/0EtPQX60WmYlCBeXiGyggJDKq+qsFfBlYv+jdbC/30otGiljh6FKFH9yXGZzWob7cw32sd5XuL9TO3PEx25gLrLbqopb/idhPxACAE+85W5/46oMMaFi8F+HQMx9Pz0BQgaWJkteWtfdv2Zxtg8ScZAWsfxHA23IN31Ji/KPSibA/3roVtDmxwleHrNPWinNMDYm92c3p/eCXCc3R3NnrziBkPVsdVdGXTbZkHml4B3qoW2s8vhL9W+behAfNvJ/4GJg+eqU0TAjVyjqDz8/C6FWfBJMwvlYkvm385THZxpQiJEohYv7Sl+pFxtZpm1EafjnW6Fsb4QBNF/KJv0tfUwQW/s07UHCM8Xf+WdatOSHDyoJe+vqb0lUSvW3OeTThBn9pYor0tJ5wAqRhu5HrK00LjjrFlakkWOYdiHp1iz8lT3sgyjVMa+dS88qgPbTMnts1yxaGqHXbiPrXKP6Q0KTXJsaftal1IDzzlO7LUZaz/8ZqWHpapVG7UDUo3wHd69Aks96jgDs3uk0+Eco113oPnDmM3HPhuJdYtFPuITPo01K/bcCrrfDtBKmawBws579QGQWqI72SMaR5qj2wrKqN3IZSUYT8I5/tr5G7r5Mo1yvRAurM+SlX+zHVFTL755cT+Y8IC9D/BTq7QpmjOm10V3fvRVKzD2PikysYEzPuqGCKLJph/hyQnaZQrcBZTBUXLuh3Vq+HnHmZuVFJ6POnwDKGyaLSR+5vM5AKCCQRhj5NZ7r3csNZEWCi0F/vQKqgqBBk3MaNwNnEr2RYm8S2zvWhVp4qdQ1rAmNcV7PTsBMZdjYJAugyIClTP3D0zk5E1A5Ipe8zZNcu312Ut35pDm/IKmvPHnsOt2qt2fJemQkvaP7Zs9WCl45KhpzvurX/CGbigALC5I630x533fpOkv4HD2JoU0NGBKFZA3XqPErRidE5VnsCrnQwOR2SHaNs3u9dt4Hb69d9ZjN+xnkM/iHBwmpAoqJGumAG4A1HEHwEWhit1ENWRqrHV7P9t6cxmIG2VgV9XG7S4stxHF0IpPBDcmA4jkpLK7P/fqiq614mI/qTEZOWchaZ09kScNW3O+jHESUgrWQN7CW3MX9g6L0OHUben6Bd4BgqUUHUDJo3HdgUJM4qFzWEbxXyAN2MmDvd4bi1eoZC+zLv0c7fBKwNko84cJT+m2Ne6s5CEINiXHxiKwGa9ejB4UOdZ9YKnb/Wfsk2H+lIpRG9lkQd/+o11XJ/uAhr6l96YP9lWoXaNbDgxdhxG9EYFUobDBMrO9Zg/uRJ5C0TNu/rXu5eOOCX+du5FqadL9RwyTH7Orux7mgmgLvbluakgUPa65ADh/zRDisTQgRwHTw5n53+6QYmzxaW5o4Qn+XmMP7/Wd/E3j9vVhV1XVVAdZVg9uj4aV9i2x4KwVNr0KkHbZLA8lOvZT7kxt7vCDT1yGZVAO/v9d+bfy4fZG0zYnEGHazfpJIMG4cKC56V6k2xgyjgCNHNC1zh7718LsMObd2P/oPLQdJECJnc/SGzhAXb2YASj1PCBad3FRo0mfGXP6a0Zrba1R1Rgmm0v97ZChL5eVU8pd/O2BH8aqmf/a71B/0KyNnqzrh7jKClQweGM9bUz/X8yrhjhtNc+2jWh+Jm+No1ZfxU4OGmFewNqCw3ygPz0HZ6UjxK+r0JQE2iCHpP0igSqHC7KisjPgfdR1QpaEUspVmSf34XCesp+nPExm8aQdgtUwVIYO3C4qeQDpeBhhkpXXr7SVgYK7odrOCf+ZevUP6F3c3fHAS5t5yZZldaIdyH9QY13KI1lBnU0tvPvWSll7tN9WZ8lEvaF5t5sz+0jIuVDUR0irJTPsAqYoTej0IMOHXTO4Ll9+dsJpZRelY162jqEbH2PiSTBdJCsnpsJf+yuiMTIkBF0H14cCRqBAGQBw1Rve/keyZyKeXLpme4/UgQP9OVXUp+X7/rW8Y6/eFLBT6xPLcEHDge/QBmfBqc6jhJHKhEesmZMc+pv0gud1JIyXmRwctYqzjb4+etKj8XuQ8q0b+EJfhxDcEsbAhQE6aggxNLpvZbwz+V9MuPmtlHLneUWQitjObznJ0yRYBabW79TZx4JP3fMahXh6QYTV6xwLdGTNqV5iJS3bH56i6XYytKlIfC/T5NdeNOdCn6Vky6Q8OxnZscbRT59wl0nGtGMZiBhGLDToQK19iiDykprYVdhJ6GnPlG7DBDHEzDkPj9w+uZN56C/3g58akOqyDei+gOzR8/v/bl0uP/yponKAynswi54OjzuUvxNrC7O+PQveISeOBz8RvNmOlEE49RhBWEhZ2YovfxZWoZ/vZUQn7R3XXar6UhLNU5Hillqc90rcXMw9lqJ+u2pHcDISw7MdWP1ea/ENeZ0/zkg9GvfjIDxj1xxfhs0zAYgmr0ViBczMuUxPymwLLcN0u8am4kYf1R5rYc24zVRU+5Lu36bFT5dQiAH+tEOyeM0UtQoJbBraq9Qvw2aBAFQaxqHT+3FGAqkjyUjpqASZem9Pkm8rIWD44zgRrZRJ/7MXF4Q2Q1c9Nmb42oWUKy3QZUI2YswBKcmjTjKkN7JaITHh/XDA7B1oEbQ0bvKHTilGaCdpY99tUmnOq6V8BfG/HE98zVFDFA7jRLauBNEHnMo9fsKTPUnis4yz2aBQFg9EeJzzBMdzQo3sRYuuLrvPgpO2EaE45iosPnz8vAbTk1WmYgrMvQqBUsVhC10QvL53CEvy5SsfTMSd5vi10HgfqIXLn8PMFbCr2Iu+2s3eEziqqJ76pxPRNGWDxGNT050fJSLGP7/I6oPBrVETWuf3RgWunRGp418tqczaRD1rvaEZhRoAMEYC0M7qSFE0FpSXPKEE8QB0cvZJJAWM+T7HsIrnTp2AZP5JjSRJhrAIHyGGq/ZMM0jV/Qavhr5mB9u7B8F/gxVUUP2dTn+pvXi24kAcTDTE8j0ppGGzpVp0RJoa8wRFOhtKqb0Y0GKAuxLgl6GFSQGC5dWbA2mzgAUtXv6rB5Hr2pAdFde+SGCz5CDPLatjocS8uJSZ3I4DFBqYOPz/d96ZogmMOgVLgoFdeYE8Tpp2Lo/+hiDvDkd4iNkWIv6i0EmoupdaERjqc+kNlOweA3Npv8H60L6rekfVexVdkKi6sMU7oQKiOskRvoubXqFQXNayIWKKVMrlwCY6IcJ1hl4nunl2jsRFEwL98ILEU1GEfANaxmruBAore2xrEzUBkMEnOZyvUedUCWXkOfIXdi2Re5ndeACl3DGmTPYhqvax3gXGqhIZi2QZlYwPZCHruWDL7wCVWKQuZh2LqhhinuA0u2dc4XxY+AqBlS/mmluUwZB9YiYtkRTBS5OQLCQ+ee6t9kq5wpHRiRLGE/ur8dw8I54yETm4sBNVshh6Z4yoYueWjqBqgCoJlcy7/N2RDkYhDidWjVYQy7qKerpRkCj30KYXkf4prBDK836OntlIdhzBf9BDhGhv5+P0THw29zv0DWmm4RJTsEPgrDqXQrgbB4qfkF6ILsgO91NH+Z6F1L0oa8h4po3+Qz6I9APJ20eHGMGYCoyT22pWo6G3NyJJFNWLqf0ZcBiizAKZmzCZcztl3Ur2TthdWWfcOHC1q3wkRjMOmb3bMVjleh9Ka1ZBsGbmo+1H0AoUpDJSoUZCd0w9uGL0o4jmiNdMkg3fvcaSsg337XaruETzcEzMmiXiFq3SG28csmcV5V/Z0ptzi9t3iVp1+MuMmIhbNIi5jQE/m9HwPKT6v4XjpJ8iWGQ4QhN5mGtB5Fs1w8Xy+Y1+dNeh/cjG8nl0I+eGh4KBth+vgiCZHjVS4Pv78pYjd7h9CUyYy9XpQMi9EQkxScB2k7d53vE2t9Dwbk5COd6db+r484onAKQCJcbJrs7yHugvd4k/7a6g9HoJ6mlB1sJ7wOGs6rWWRJjBPbBzmOzWftPXcsWXeawZNdk9E5qldxYfS4CJJyf0mAnIzvl+qEAu4GC3uDeTGd9LdKYKyXo9PVdxUTXG60WywMGYidI4DA2sBfO8IyyEgRGA/v1WOn1D33/11yf+sV59FEN9x3poq71B1JMHt9ac12FBn7ecRTM1Y1PgB9jKKYfcG8HwYIx6y1+JKmEgUDMx5fBLV1LXxoQGbLn9Jf7d4qN4dBxY3pThb3QOf4XKZN1Qn1UulnFxIls6oqpXsPZkVjvBfgUXb07T4dnV2RylQz6klQLOTeWmTzAlyqquIFdJo9UwoFAszY1JpaaZUYIKRlUrKN5PVK94F79tQJQn7yso3halhrsiqmeVRYCLpHLtMxff6kYdd855tfElizlfEBwEzFHL392ROO2zXNVIcJf4W4ch+ozhaxMtBIayLvWXCGKiloNlHtWi2GErC7+VfEVMOUPhxoT9tntrRGT91OsyNRLcZghRQXwflxeb92Ca8nawTLkIwbbOm4wmJIcvu23AoP/zYu4vlb6Ajzxu0gsNBAQrbYhpfJk+extupTADBetgjIvTm4HTmzw5oFuvUOL7MckoZ5HSQ9i9gLihgYEG1NmFpROgJws14F6fzbzYqcol24JeJero0293GEIGDZIYffHJXBU7Dz4Sanm6GmKCpb3fve/xqK8Pk+KnQhr64lsr/RK/GcTXBu3G6scEyb5pkQbbGUt28KsFqpG7Fe1osLGMLhLhVxmFkoKdZa9zuwH9vWd91WdqmNta+iSD4Ssr9XdrXiRtoAovlr2XsBTXQSsAjbaykaFqh5tBNEE6tr6mi+Z6thFf8gsPsnDSz5vrt3pSkBMKrK5ip0RVtpj4NYiKTR9mmr5gefLYO9gJ3cc7HTTAZgP5jXW+6blI5DfvmatlbgkAM/POhHx1torsRfw+Bch+F+1/sg4qkbJuMXsV7nKDx98kkLHTqZb9VEJRdar3KDbP9/gr33zYjuCHGV4l+n3P2eQPaf1cjnUTrl3P8licVcuAVC1uZfkL3FmBdAwa+6LsF/TBkQlKva/KqLdMclOdpO2sVfwQWzw4Q40ahzcZZpJSBaIsElz8SQj+UMJZvA1J8kZQZG/KX2oBqwrgLQYNUwik+nCIWi5F50WBIS9GohROa+VModraGeTjV1PwHd9CBALh8Xcn1d2StQzUdvsNHY617Kkgg/lbKFqa8+SoEvvHZ9WkAzFdQU8w4tqtKZN8NS2k3TFzX1M+gDIFDpnWne99FauX42QBMuzYP408ezGZS0uradC8/NdAWLqeQdQAHWChaTP1aOhiqqCkIEXPktfrbxea/SVrrK9buh4cV1PcywbqFr0Ef3P9WZl6z/Bw0bfSuvGS/1DnoZLuk52ImRYBuyVhURzCkKNZJqX8+mmRgP33wa/34/YtxW74MVK0SprHhSluNjGlsUfXZDpiZ3b90ETHBvjy3fbOMeG7qLFzW0CtpUEKPLHgdUWdRSHgaAFqq/95y3NtNqrlApxZVOJ5xkRuNefxRgJ/r6x9VQwUzedByPOd0PPWFrMlz8v7puF+eG0XCBkF5e0XufPL7FkIAkpgiMPvSgiTmZInvcT8d3NWv3f4NHSanTOAV+qeJafP69aA2f9569xD5o3Ubv/I+BZ93AVys6PX3/nhp4fDDj9DYzMDZgiyEOgYr/njeGdVpSc7brU+2ooQ0gHGrPLcOYE1bIimr1awbI3Y3ioqeRrhxod91zfoBp3kz0P9KeBPp/ZURgy72DYbAA3JgSDTyM7mTyxAR50x60nc9QE+ayOadZminOzSeEh27qMfh5g1a5+Ao/S/xN0V1O0dJ27YyqJnAncwmqRb1oJEeygGLRwBf7rDnQJXv7VbSJJTc+XfA8bBlxyzKtKgjzYXCu3visfQI+mgR7cdeyNBqlG42oqcHfc3e2YV3y+jpxr1QtU1AwHLob2XxDU2BITQqeURDkxpd5bM2UKHlxpgQrRqIyqdd2x/JL3KWSJNrWgOF2eLBlmNSz4IHmCbkHmrb6rD0xo1iif83IV5ZcJnnOoKyQeQLcrEMwTldxdj4RCQYy5ARjdk7i7QR27a1b7ZS3HKvy286YVeL4cV40M67a261UhepW9tZ9rt3vOlHEZelPWG8hDza04rRBltIVksqHq/URORC1Mtp8Kceb31wGL2hmdz14Dv+buAUl2VU4cVur0ZgnuHp/rBX+F9UGy1Rje3Txnihc4mu1VaI26OshwFiJZyED/cQPnUThvCPGHK6ez8ehtpjM3VFdljSlPrYJ73ZbH7jtGWQUzQzilw1Vxqv1mox3lsNoBqaAM0hwO3USeORoqfeWLyGGEzQvgAwmo6+No7IZSwGHh/ihuOXlhPRjDDZK14PIuBZ2kt3KddVA0btB9GfL/SIo3HaLhK+vcxUkds+i5B6YsrZWMUy4Qj0guS6mwwVfhBLixJSujjOCAPqZ1l7T/I5kzQI6ycU2wm3GtFtRy0+cspFmqS/3/SWGqgMn5+KTnyGJSFD8/rfGZIPdBHxlE+/edQr2g/ZxyW1eWYTltEZaFpjQ+zVExtryIHrv09AinPaZeJ1BkKVbvZvFpihYvi51w4mnu43APLNGKCh4HSdT60MOdWkQ8ELxsbJQr2Cc2cRZQ+9Wdpfs+foYsdUTlGjRvQt2VBbM5HQScvkatk5NjZnAc7WrPJt7zRGtzyWS9q2kzgqXxGGNgYHxNKI0evJnV1PgHtpnWmfQmfOEhtqAGDfIyqZSQjukKhLEIu/8dnuyy9myos66QWyf9Cu+ez9beFq9wA54FGOj/gavk7xK16eDsL+ruAt2Lmf0KQ6U5sgWRtH4um8Tt8xwWm08OG9Shqa8EGHnWKMZGWKU33Gc3j2Z8HwQoVAsZFOoKP2zaBelfvyDxI/vor6qFXRfmWyvzp4XjCD5+PTvbgwVZVVtnACGp1dE2ElLQyIjuTu+Z1F5DWLcpwqTtZfO2URGEaC1fUA4JOnXCvlqXKliFr0WrQ62gi/ZWbWD27cboToO95UXHTnkE7YsOjhVLazypAMUfwzVK2zvpUMqB087aXfXSKWSnfQqe/1f+qwbs9ZlR7jOSY1QPIFBLHI8aQp0pK9vbxiJA8mUvrK02TNGCb0DQthRMdXsgjaUyXXxiOfkf3DjGtPdi8gzb3/Oxtb5lIt+JtUBjNRhyqalgAGCyKOEmttvgseClq0DFxhfmr6EUAMx5SXGv2bdz/SU5KSMTsk48r/+sxRTm2rys6P4zupDVm6mS+WcU7aFusV5SHnHrrqnmfw1ECx5sBh/c9e0P6gX6ZZMxAHO9VLwkpANJVyFJo7/Ec/vctsakH6G4LvyGORJQuc37S1WoNMlujFaEmEj3MLvRqnsmT6AzzRwU5R8ni5lxhiGEarLCQR7/+TyFRzIvNVtKstNvHBJrokTYoFZ7MUuAFGVfpaER9LYqeY8Rvi5FxS4l2p79KlAOYzo8E0TwgcvdRy1uMeRLqC0SN+gQ63Cujw+SUpsaIdXNUYEf0x98xQmW1UwgnfjgnfbtoOuszFKYhl8G5Iwe6Cw5zUDk8K9I4ce55R/0rFstHqiyAkld3uNwiFcCcdDWmMN+XmIDM4AM7swiQGgJyeKtf2r9KSQT8DT8ttkjkBIgnVxgaVjnnG06/XN9tD8jX085ULBHl4ZMlJL4crki2CzgTjJZUHGv2/BFqDMhxLODHN5olkf9KdJTd+lDf1HiD+zsWx/mlKykYUICf1kPQFwtzRzpGqlm9LkYBNQOMroRjseEeTR7KE1heYlT/fFYosGHLWAf9FjTC96eiAcLsm8oui9OE72LZPLoHe0yk+kaDJP6FjAXL6siYk9b5GXGoJPw1IqaJXtezyn2s4CXbJqlsGfpUHqquYJq/cbg5m1adMyjs904RTq1cMphOJGxqiDQmZY4Yfjlkc9fuBvQKvmJD+xyzrS/w02xPufPSMVdXWuQ1JM8lQrloJ8NpvW1mFr0DMRh3bwVNcBmoWWl9TTtA/FQAR1bpqFdEuWsp226akhWSHcMA/ZegcpH6/Ic8xIxmV9BTSTjFpQLCOPIBOnKw38D9VnO+YjVET+1VqAPsxNw9An0K/Qtwt1E2gPsd0/khriehwZCphBmh+XWyUDWpvBq/mCkzDm6GMDjRxWQFBTfLtOMZIgQLCTuXZv4vLxXJid1CrcOPSi7cAxu9bjG8QLLCWy3gFRvrSHlrjwedO6z0FdwKJOVVyXx0ZZ1yP+1gj+dYQdS1+tPlNBU2tbrtygRXflSmHV8/0Shmci4fOCcSegUpucWOmk+Oe8rxUrBYNvITq51bDr1MdGxCgxxl26LgbV+DyRpjlY2lFHQaFCC498u7bagCMxbA4jwLwT6XkQozvuwx1ZANd2RSY6Q8EeiE1s85ALE9HQCHBXl3N2s44G5nM5bzTK8Zkqj+L1PqwfVy/L7HxUMrqcORqbn5124kl3qFjdCOqG4/MpE/cQPgQLPgx+aOT9lfUzT4Yu+eOglslhF1w3AQguzDDtCXJsukWhU2XIysn4S01wBSUqjI9Aznb3GntnTw9Q5kSMDbUTzCSV35IyVczXOZdOBz/EiPxwNzr+yUrY1vCKhp19/UqCJWQf0WHCjpkQq7wAd/5T1me1U8A0b0jzxS/wv8Vy8WJxHC1o/+FwZeoQ4NQBqex/+t92pnPaICzXRrvXXjg1bWZDk37BETfj9hCPGe2tFEqm2UKUxA+X/9G37N2VgXRVBnkSmUwK6RSSu68VHyuRtcA5icFzM33Fn6IDjOANlTygiDnI4yON+qfmZ4c2qgT/uqdWJNZbUFiLAb6lzQlpchQeCIfSwI914+tBMh6CYeu0xlYxiehiMhc9MHLvXVYqQESRxntDOTDzYlHGyTfFLsrzhirfAWqMpwnJsZkEqZfQ94RBstbKeG+7e1wAdrUVbHyIJy2CVnWCe6dce2lrjIAKSnEDgRTR0fAq8Jt2/oF0/UAuN02yt/LFjIgDK7sX5GO5vrOm+sGAkU1pduSE9kJS8vehR7+MbeehuT47UfZqz/w5q5HuIE+J14eBjsww1tl6HZf5hlvFkU+A7rfjNzEVrvFx2i1Z0JuDmBUjevqO97oebdvMq6M3w3iz7w/0ssGrsC5ncvwdXfIOh9DT36tNlaEldiRCi1nrYVxyJxZmtOcCJlWCJL0SJzfAeclC8LDl8a2i97K3KVEhkJY3bX4zNFMl5qlFBiLAcmjjyGHnA8A0dqHs0df2eppuer+HwGFs1n8CSVET5Xp0URB4vyxvmxk5hCpBelhfDWe9/9iSYiF73biIzHSTp8eECY9pF9HdS4hWrAuFsP3Qk8J7Zb6A6mw2vEYCeH850RQaDykxBzviCRug/dah1QcGTRnPyFP8aRU1MzuTT/pVf8Jcp5riSPyji4bRpo1rH8ruzc8+D9zSypr5NykI0srnjoxmH5SVXMrv3TM54jtyKQCIJ+gZc5jlMw8LEPa6K5wuyq5jG97/LVk1jQelDBg4ZFBw1R7vxI+i60V9mtkGzlrf2bMD+9Fd+9vAttcHPmF4Q9dyyIsAwVlMfTrD+wQWaj8o4zefBzZvfnMLb24gAd4Bl4+tpjVmo4XMjGhSHwnld0u3luRrEtvsWd3NHKwKFkK1NLMJ2xV35mxjIRsx8NSiwwrd/uOokRDxlb+fgSa8QCKDnAAIhC4NWveNYDMWG1x5UgiWp+pbbI4mEO6l9cS/Q/AkdCGu6Lo+zJ3b6dkYKy1ABf0pv9Qpex66IO/Se0af+bPnMrvhtaMEcUmiwdOqfNgTnLU/92QtB9B1MINonFCUXxqMGP8+0T1v+/+m7OVRC1BRcqE0xmCaxRkrWeMoruwDnZqkRHGJxfM48ZurzvgLV1BaGNL4nIv/C7N5T1UNUpDzYxDqSiA989GP6cfxDqEhbKGLzhCTMnd6Ug3IQEUNwlw6sdHSoKXUgpQm7Rq34DfT8hAcyIswgO6qjsSSG7O0QGSVX2ZuPUeeRb03lgLU3v7HzKZWcMp5i7iIl+QF29qXlJlsorMxRQovGywYxmHU/gjTiZ0b7kx/HYvPuTZJ6xs1MvEtHygJAwvL46Ea4EpoLPL8HmC3r7lbxMn/vMnAlHLcwQlJN7PoSUbUkWfTFY+DFLKMBr6ayC/z9lz24tFqjusCmYhpM2ywG14xGhoxbJXHqDIU1QgIm+bOBUuCecbJByqcga6nXK79PIjZJw1iNWi6OEKvuQh4x23EVltSNmue7N+r07L7thU7IpoqTuIo0WtZwxw8U7NOGi6jiTVQoe0jq9s+8KnMzPSN6oKEkSlPPtzHP+wjH3WmHgb4o9cEy4vA+cvpDz9o1t4IWixYFh30tCkfYlHR2k2phjAV3HRSKMfp73tzrWcq4ewxnHAnNZ/6sT33yhLf7cunN/JJAHMZxPBpvwSOsPMFdQl7N/946vK11iWIADy09kou/WG+dvXiD4/eruCRqZnJuLDjx9CuRnBuUN1Ac8agv/WbK5r52SOLZ/9/07XYp606UgjHDPyA7oScYhpMQkB+o89sf3U5pKthdu55wnR0j4BEW48ALXxQ7yiKwnuJhB0RIFE8UGE06YykX8+lkgd/De0P7ylVmi+Dq+pFWvZQ112l58jLziKumRMu3t8CSosANW6aP3CG4cOZMvnrE/irSsTYeuIrF0JxA4ka1C/ZSbbfBSL1oAwE3q/sPurpAo6Jxw+tKEf7u/z5IOiCUWuRBKv1WID0ta0iIJ5eMVGmMVHrHH8KRYnChCRLShCNKhA8P6EUNiOYCmx1KNcHO5pMLhci6vRWvqI8e9IOmn+WZoiIfUW1t74ramF9SXFcLPluwNMn5NbMKME8lABpIEk73hVwn45owRV05L8g8BbiJEn16lCnAMC9U/F+NEuvpXr637rXcdfQkF5Dukpk8+S8w93FDcJq6o4hfKcW0BibNO/vO98uQJVrtxG1YA8dHnzv7sAugoPOyjp8TLmrLkiUuMPQ0oB5pTHloXzUAPxLdsdhnFETM2JsqDQ8/WGAJ7J4a7wV3TQNRvbegzy8NuyNyAspgAaCTYfvjARJeJv9xHD53jOGKlqaJmdtTLdKnK2YEn5McLPL5ZkT2nNP68N2E6ycDe36J+qLV4eWXf1fk39XpwGKHvwupmA4ulU92su4gryHqaHVFAChEW+GPLdPK2moE1VuupKSARv28SJ5EgeAKY7V/7uaallHWMvDQ6hCXAQ6AIA35qISX7rRg8EKOZ3LfxhP7RxcDsdIsxlWqhCH2SQziCq42t/fKkmCzvn0fcVjsXFEK5CGFJDWbp1OjlWEUKFUvofuH0iVnTSi++2KK59SCWT+YrLex36TsLNXidg2cR88CvaP2AHRdXDmKNchi6T9W4ghodXsBvhgkXZl+kOPontZ4v/tRKprU8qF8zJsP13iL4m15Xe5FSZTil44FnOY98HpNW2LYcr59QSzOwgaWcdtEN7JrnS/v704aMrhyVPIORAJOS0qdXz8AXo2YN9xi9kNS2Q25mF7lnqlADb8/JLizxZiV0ss0q6mIz3J8X4+0QI1VlEXVBjvbNO+tVz2m9PvpJopNP2NSEtOoYYMCtffttmmmkMsvKcu8B3GykJcOronJV8p3R58k469e8Ch4jM8Jev2Aj12yqY9x86qP99nC6MNpfAej2/2ze88TLDZdk3M9mClZybuKOP6Hbqtg4tu0QixxDTourxkzFE2sP/5f51hYcSxnC7en+cftLtb5m3PkbZbYuWV/Alow4rza/FVVnyVVoubbVCekc0eRzROzm44h8QcvcBNZXDCyj7xXMMQFRHRjsWPCch5UBtRdM2l8u43tIiSv2Y4AjVOy8SzwIGyvJ+5Gs6UdJZ5nUvbp+SOcXVzpDvHNn4qL6URcv0xbmbbZ+sc1wLJ0W1ZLwPE9WoqfQ9k/6Ve8SIO2AmUf0/V2Tyygz+GAsC8Vyh8u22lIhe8aVfVVGDPKhCdH7odYMY92xdQZy715wjNzKf2C6Hcw2Ws4JIskDWSZKR9fzq1TJlU+4biuG+JX8tCfKg5q8xvCGw9Z92C6FW8jjwkVnHCZuvEhAtJDCzM1U5dIN5X331l96DkmQSjTJXJcJk4LZp29/K3mfvCOUY9EmmE1kKFhUqOF+5cEcSSVfcjHXxDH7/Ge/pLNgdbNunm3eJAObHSG7r32BfOkwj872J6nSx/9oGTw7H7MJbQBgmaBPCC/0egiKLtkNGQDiTxSJNXcTfZ3naxVhO8YFlFQ0ApgYckSgww6K9ruvg/zSm1sQOEIKu3FE3/EjIqItcXmCYYqUSjsFO+TeHOW6rJ4Wgew0Nty47hR9IzRY4bKsScTOo2UqzZQl/sLDLt5o65End5mDFaOYNPf+K1fNZ0u/Of5jdLMJhQRGaVpW4eZ1Hi5uUSVM+3oAOKyGpf4fBKxi7jJXkzRleErbyYnYd6OAmLIET+qgzJdr2Pfr01+CeaTLd4wN/bycOUpkj6Xa1/X3HZ+tieSRm9zG/agpz5CGK3aKdYoD/bkhdzDNfGiuZIOJPutNsmPVNDOXrTTkMZNFYQjIkaqvk2NAZnoMsy6cc/CkNSUMrKRU1N6xzsOalIkHoEUMhGPvrwXSVcxNxUgmjiG80vRtJfFGD650QfgUw5k0iQAym/Q9GWmAffOr9vrprdRwCRtv4vLRWDIXGgF+U/fjrAR8ohsiMRJj4T6excDM61ulSyBEPJ1nnOPT/aMt2uI7uwJqDGmRVHGeqciMuM+PugZla3wn+chPfBi/1lSFFLsnb/ESg600Q+fPOTuyg8sM3frUotc7aoQ/uUItuWB3KS1R+cmpQqa+RHxeyNHA3xzYDzXeKci+M4eF5MkFmea0ezAvSU41sokelZ620QGAJAJgguO5oYiF9fzhZc22y5DQTF1T0QakKKbqbhe8UadHXkmQBkwI958ymeDEO+gSGZPW3Ilj9V8YhY9jFe21I9w8KWuzpN25tkUgq7Febx8MneCuQpVHFc7L0h2tDNSYKEtYeZgeXwLMmDgZQ3u615iPkKnaMni5kEvoVBMI9352v7IpojCgTnkIbyT1ljtrUjhXB6/QjgqXFTjWwoef5AKWWSQGEGSXJqqDjjvFUkH1T5jntQzfz1iyfikdf9l/ijHxF3OOxqyAV3CRTRPagWvesLkUS3hLKR03MaHtoq2SIlrwk/jtbqPxSVTvE0gQ5EK+bNwF+GIOKcbLsGtpocXOaG3QnpQ/a0XXnEO/XOhQzYTKjxWcse9D0ebKdXW5vqRDEdhCxPkq45Yu0+TeA89B3d9thMESmkiT3GKwZzvkTxrvQD/jD6kJzW5pcgx2vqPNTxdmxeJH3Ss6YrbAnfVXuBV4wEf0mHk/o9ouTGqpVqdAV1W2oLqhAJ5l0bi3S1M7bDBdfZrr8GbEC8qbcDItp1bhNGx7aLnQh05Q8HeelWe9YP2AwA5Q/09W/xsoQN+enTEjMBLXTn7iGbEdrNdhXt+++8kHGxZDBc1nk2up+DjrcnzXRQKDPolOTsgrG6F6ogJB+lTVTC55WGiiB+Tvgr2pbgcadOPAUyxy8874+Iy6SogVjNFw2Aci8OBSEEYlcATSeePlCjXtW0x82Ii85ZNNXLMVxGwK1rK0/hBhMSAJnHnTkaSx6JTjBA8r7/WBDaEkKOqVXAuwQJMtZydGH7k7N7n4hyTT/9CllefkWun2cv15lyKjjVmUJIWF/Xk2TXgFFyPof7i26p1BpiCinKgJo/EYUIwJcHnZEeIplcW7ZyUUFT5NjYPo981N1J/o/MrY6KG/I7fHm9Ro1zTKHoCyXAaRjh30p9slJ128WwDFYC6SSPfKNzirJL/GvABdcP9x01oYnR0erCLV4eLFGpuyK1PICJi6VYwcmy19xC3TIUfBaXd2OpKen+SG5x5LGp1ZwXQzE+djxAS6Bp6cdaRqRD+V3SJUjWMYeGt8cpQka4ShPdl8/VHx8Gl21GjYLf170SRZQSCv/cVhthPv+w84rhXu/IWMm4f/3V+DBWTUGVFsFFA2lnjnp/4t0lcFMq9aoZbZV8zvL+JsUW+XWwNxbVqNVhIlCcZKFOYwrBm9BZo1UJQs677We1assTBhoaIcQLKQ/y872OSsKpTGfyjXuz5wnS45k/9/1zXAyGvcwHTnjBYOoJM9AeEzsdxKtFlTNIVNfw8MJgFmSJi3rM1Ki3aMhLLBXEDXvSuFCoRTVNK8f4n9XsqNw2dkNvOCxRWSYHb3cN5++Sz1IWDSCqd1Rk9zSZpZK0Yo7qCXL5ucOb2PnYc2vBU7ztnJoqNkr9Qa91GvUb7aCHzSHkOM9vFjGXvA/Whu8W8yGVWtJRqFFj5STGak8ACzTpfs6zXOGu/PnPuhYWTqWwBrulhm1TPNNkuQop9CIi6umHbUDWEsHvwQI7xwfcZFaSbkv3GUId8FXmNo+b9ubw6xy0r+dfRc8NdqRVTG6do5y8BEsFoHzBtwSCW13jk3AV8Nh5DgU+34fhP+SRxC1IfM2ydYIYMiq3AEfJOCU+u6en7PtoyTevSqSv3k/GBmGYRGFsEx4Ho8SDn2XsPUdydS9fyHimD+SMZHYiMf2qu58jE6N9cd5kUGHKNacupRN4/sw1iIe4A+PNmrU9dl7yMSlvY3Nr31yyIKBUCeBv4bCImyefSF6hr9IM6efapN839RixnM2XyJ/5yPadspiNnZxmZen+JMBPOhQPH1Lv4aIcV2MGUrQcStmjAJxfVYShgnapN2WVv6VXqnWAkViHVRCjEYzMC5oGCaEkRJstD/cN0nZc3zj2JkDTCDJwNaLAANSi8ThFZxf7DX3BMZSr4j+9VdnSnmpvt6nlKfjO2LoR+KaxR39BOVPEkoT04FyXzKQpV+GcGB4KKEf1sKF5CtfwPB0t82IgnJOxs5MpwIPrM50HB4Xez8bh4Gpe1gJzG+esEapusZHB0TfyTJ2nuOpskYe8sXyMmUwv34Uvslv+6z6GLn1ovUSGKpBHOzzTPjlQc94HQeetzPPCMedPVjjX19YPjB8z7aikZlmLX/vRqcPd/obrsXqagzN9ri3BYgLzguUnoJshIuYuS9R6KLPp92lD7YAb4n+f8QXiZe2wbxCWeH0jwy1vHmu5CYy9IH0nEqIpIoE0Bx9pLEzPla188Vi5riLho9/XR6rrL5xp0ExQN7UxHd9FZOZuALbRYTgMeE1+kKKHrveSijxz7UcmWqeF4rwbC7xshkrR35LiN+OW9xOL0aBsuzv+lhK16o0ryFJkK6jlKjazkMP4uR/J8rywempBWczlFR9a3FI5WNCklEJNgD5FjzQuNUxijAhAroIUKx8AJPqH+ggLh0hWW+2JIi4WYgzazV+pDK3mIGzFW14Q3h/YIxleymiWBzQJC+LGWnqoNVshNT6BtDk3pN7jFJ35cqzcinSBbYwGlXqof7jknQxwsxRzwYMRWy+Vq5DJCt5m8NzW2rgnD0qHO3paEFoL8UZTjIngi9OO0roweSuwjRNdurgd+bqSTMziOeZGgkd8pwt72d4k0n7JLIStQ+3/+Ql4R9eHfe9XQkB5bxvBvRNVOBvVh5hWld2sfwdPmUenv099/YawJN0pwI9sKnypxnbkPIdgxE5veYOSVlzvKbJ0qU6RtpU7gCW9tblNCsd0ohIdk47fZ6/2XUKV4lQX/T7GpRf0KQjAmFOBHsw7hGCYLuO90bafxZIxILAM1/hN8q9yna+j4kcQ4RYZKShRUSS++gElOqY+LDyuHhqqoqldAdJgwmqfV9Lf91lxic/VXOPjOKrz+JPVPQkoeu3bPQg+Xn9UWlNots+9Vc8clhwOMfEFgLrmUj9ENJ+6OMHKDGwjEoGybQvQQ3DqxdO0Xu3L4FUSW16m+jHQVkoMmahFAJWSZQnPScaykw/tGFeNcH9Zxq1bp549oN5qKQiN7MnTdHVMCV3/ceGfWwWj4wZwjTNTygbMFU4BK3ctFTzFmM8Hjr9IkImFxWVMwC4HpoWEwbYrW4xQZl9UeNSJFwnp6A0dyI1wQJERjcc+7oyGSpoO6RQdjBWlB7XlM1RqN6nAzT9YBqX4mlBnvlXPIdEHi6dGDKMSPhfsU/M8n6/1uk+rNQP/a66vHKx4g0cgK/cuwfL1wIPQaSHkllLichzmYSHTMjDxJdNZkbHGDd0l/p+VDRZ1PrBiIo8w08tyVSpwCS2sJWez+AMTuUQ/KYm+c17C47R0+ZoEFFYc6U4g2zksKdhx9RLaExnNERwSLI8JCwiyud8HbZYGIsLZivTet8w3kmoO8JPAexIuVHovqqUpUobpBXNLAfeWcxOYMEkuWdki0IXrFqMJtR2FqF7S5c7BipWNhVs8oGoezJ68kCNlo6O+yctUoZHGogqhx459x4uYlpmRB9G/xmI741DZ9PFULHr8I8WK1U5ydUSvAQx9GwwAFUnpSWKh+Miyp7iaGgm4pTPbP5GC0rGxsmMZ/zb/nR60bHROKZzfw/oXnooFIVAx/OD4D47H1UdHmJkXdH/gXgpNPUEz3A64/CSfpdDqknGifvkcxuRCeCYEkLjdpMLkaJvnDowTSYbm7Tx8Uri4l6rtyphnjhXXkfttvsDwWtgfsunGnbWkKKfhe+RIiSf6ioR71oL+XRTOI4cXnI0jFVGYuTEVYqybXimGIczBICBpSbAeVrrHD4SnT60LSK8RNxxQj3alBPgCd4CFYqklm9Izwed4mgJnf+8rFZIIEFuTOSBFbhjWk5mTAyCS87V2B/VUKl+RJLgswxHL0B8ChRDGSie0o4T1GmaXt70qErf7+hmxwI5QLqY76YE9GY6xxBvDcT16Gh8nfhlnEUj90eSKTBTK0vrL03kF4uT+e9rds71mfnGlgp8g1EQnr4e8aepbSEwlM6GcvhIhZbbe6l8HUo89VvuD5MS/SGkucJsd8EnfCrLKvR+L86LpdU6cAB65rVX67JbjyTYwP197+DDeps6Z3sx5jSqH3LY5VgCqq8yRInzO7q4tLgL1E3gnAqgCxANyb8+NTFhgI100taABlhjT32sTKcxqlImXI4pwybH2PXaSfUgRMIPoG9+WYw8VTLyhpa30zmpiLOd+hORqzriQJMcfy0tezEcrS1g3a5XkBCsVtUVs0z2ORuR1t5ZCVBkRN0xwRPsXbxqUk6Wiq614hdKuDbU0ESeaMaYkAqjC/9/LG3Va+PyQH+BgpZakKwzctsO6QeZMGr6jqS9g29CYWsUxvDy+//Q0/n24jPbjbz3dh4dZShHMJkf3YdzfQG4S/SzwEnFsRulYVei3F0Io2moaaUh/2xGtbK9Qhki+g3DK73LhsqRW2yTSh03wO13NYf4lodgic0Nqs2qr3bRzz6WtsrL5IDugt1oYY6GK8iH7/AiCl/IHKKYNKKDqJTXz8P7fvYRZSkznMbXdLvoss/nwBC2TlQm6S0gpsdkEXHqNKRq1dY7Yvl4jODqnWNmhi2YNnAu+4zBzhH28oz/hy0JJNK7fUqtphqESpd3dNL/E2IJV25oPhw7aF1xuyhaWX9HKIMUIthu+Li5MLF6kDiYMoKF9NXN7x5L8tXxLUqQohzRDkpvYi5UJTlN34iYaUmmFOAS/u5VHdA63F4BEVnxS/NGzsj7dAte0xGSs9DsflIh++uYjxyZNGh7GA1jM/TtKwhTJdwrrKZk3MqNmVNnGU2sewRExKL9Q35/0DZYILOcogsGZNFspnGDHQQ6y5AzZWqEfNPLU7QxfyRMXDKpJTrG7gUrfYhMy55MjdhYEFVeNWgvxdmi2yIAa3f3FNSyLnoTKeT/baZcGBOuw0imR53muAwLFIjm5IQx66qCZLIKDPESkgBfBedTSIfv26U4qWjbEdi8OmFstw7KSTm7MBY4rrKga2r+Q4QePuM02PEaaBkyf9mZEq7sqdU+Lqt94hUnVY7ExMcYJkzbg2EhvlumSHxPtm9ofIZohFF5a4oFHe/b7gIvufcNniUBcJ1XBiuJsWrY69GshB4jKB7zCkLWTCStNwNU4QwxAbJ0iGA+FhPQZEreg9SzYPOFI5raReUS8Sep4/ESA43flG8gENXLl7RovJQlpPpNfydxx/8WxOiIIyVhnvgN4+mUT0LBXbVskE+xQZYexfI5/hNS20OCIfOfikGUVYQxTM5+Z1Ip5yl9lB4YyvOrTqXh4P1kQ7FcAX7y8teTEijakyUpyVgb3kDfJeMBistvyBZOp3kZsAqJ/jf+9+B0AAYKEHU/AbxPjcm+TjLCswsRuewHZ1IXESMswrIMxQeAMu6RXUv9avntkerqBpq2W7G/+mVnM0koeSeQixtkJKH4Sr5Sj22wQZv71HQrFV8ek6vMdnZkYOW3ZIlYpm0T2ws5zp0iQkmsQzIrEbcfsiQ2f1q4M9ZNIstpdst1wS2Z65GDYAouNcNlf1+2EAHkOlY+kdJiDTNg8qvkD0q+TOl4a8ck4Pu2RFl79oz01pnIyiBxjmt+XFbXSaeq+zTIY917BKwxAInwjIKHl0xf267coFlujPlrsrGzvdJCU/VC105olEEmKSVzb48RxxOcQ6IQsQCnVjZfTSZaFO74S9fNSLbBKK7UR5iSs4pBiRLKCPPoQXmox9iada/EYt91QRIp9XIzMwJwvJbSHk/LXNkvUwwD6TIZ0XKtFkw+R94dFlhYBFOJd1C8M2Qijaiz5EjEv5o3YhOGNEHn1EyJYiDlJ3Xt5UEuvIiSH5g1bZ1e3QEb6jugBkzWhadjrqGVZVVO8lk4CCcyhc9QxmplglKhhqaVcT0p75oGnOQEU34l4vliFxMGCK4DZ1ir7sI3C87z8cLmYqfUGOuTRDbJV98rPsqPpfTXI13Jpsth8x9t9U94J87CtT0No2F17wbaKnuXhPUb8WFm9AXLFMTAMdesHC2TBAJX4MaLG1G2R4eI/hgaMQAshX+RebKLqR2RxKwQtBz5/KVnnbiXhTebLQurRrKB9YGkc4imGPD0WwuO/uDMqJQKrihU0qwNmQ+5Le277j4NJnfcLO1bVbjdG0awc48iVJ/SCdZa9laMrn6UDpNJAp0jpX9j33Z2mMSJctaVvAGZt7ru90Zqko+l9RVtkSd4y0DPQrOwo+dsWdeCmgq/0v/YoRw3CIWyfW+4KBd1YHnZ+qqE1HL6wtfeQri18sQ/165l2jp9/QNQh+U6VW9ZsMVQvuCZDZV6ZjAd4GG6KXAjujlhXgviDGrTulzKf3/xD1qSpYyZV6E3bGpCVjjk8i1tdCK8yqzEjyXE/tvlRGFkSXkhOKQ4srfrQE7GgoKYaVZWbiOHLGZtP081iyOHyvre98qpLJICUohW1ylqiCY7SgIZU4oGi/thsPAa0qMhcU/QguNKkADCfWvG4IhA6tW2yPJodoD/CyPQ9ybFHntt1JsPMcYfDctqynuHIaobYjM3FiX35Ob5/EBgvAbwAfNyY5mwvflyA465lnrCA7JR6ROYf0eTTLt6uQHowmS67kxIzFI6MlsuIj/NiKSy3SiEha7EcCMotKI5lTCDBDbYzH0TJRCxa+KkwDlZYKRPGJEkfuft4nc1SaVCMaxNJvWcpOOA0eq9ckVrLtVkMwdf5YPv95PhX4q3WQLOBXCm2KFXNB0tL4/7Ym1G4rD4BJn6ji128ICEiFzmOjV5aqvLRm/cy5XWVixFyk5ka2Eg/swR8S/fMNMgn9E48xL6bFH66cee1LSzx7d95wGFn89DkkXjzdeHnIurfK4/diIidkkfxhQnByGOyyYJhtnTbJ4COF5Rch04zouLyYtCZxfCsaU0uk7ReNV9BH55MnXW1E0GElz3MGh92HBH9QpTBiezMPFIKJI8JPSD+sYSPPiIRorsEVDxsYeU8iR4urtpexAcqKVcxzhHQZC1CUFQJxV5hrk1U29RPmZ3uIlh4PUYkSF29nAyb7y3jlw8t7OTcNJAkNQnQFIj0bNy+P8keNAMv5Okn0KbMxuTdxjqxgVxyk20ovv7kTK7ECHIkZ4EPL9HkE1GPtVKZ35El4nkk2rdU9jtA7R5R0ZNWSpXZwVCBYWZFzVqySl2BglDvveuFgaHKEOMM/xUd79tZ0g6TCG8PgJzm6PV7R73l9jRZXr2f4WbtCZ7pRJ8a4nyXeHs9929utkJbHVfj41S9jJa7ySVWkk1Ygaa7NKKfL3MJj2XJVp+8cXLGHctne9+yGrHR/ArxozEnyQOUJ1xCbwEY1QFifjHsVLKNLtc4egQWAAJDuBEL/Su/zHxdCJRzuJWN53VXNnizsgHsiUHY77eWNJ7sAcoFrnBBDVk7R3Qd9eG+G1LXcFcYoWHCIp5Snp1lsnpFM2tWV9urtwcck1TJn2VulQ2wquDvj+LDuykNjl3cgO1M6fL5LSo9DlqMw68zq4fllVGjfhQHGomMFILEyl7VuiTU0h+F/R6lvofz2xabvhyKvZ2bTqIH8nqlHAY9/a/twLxQZ+jludhSUTtqCKt7Sr+YdUqGO44p3qnrAzW6ms+c9GkNK2rMM4hQvG9/nRSQ9r7AhZYF43Fj0GteIN0pLGrRfQbsU0BdHzJd+yD0+sJLRnKGMFN/2+jfvcpaV5fHeS4I0R58a64wzQg3DCWeYq2reTaupE/jeljHHDZQns4Vtwj79oqh9JP3Zu3mMUeENpjBzNLAuapVMr4QPo6mDyE/+j1Rn/iicdJLYewwTR0EKfN1RC/xbr9Jq0CDW1/7WMgQkK7N/obsQwJOsPXKGthU8Ydy+YbSrL+19+Q+7hVvpwSWP57OsIYXrbjGEZtXTv31f8Mmk/EjJRwivQuaoDi78zew3CPkCEKyK2Cj7EPzfwX7+S+/SbNy8r2dilRC+RkkCtZzUGgJegGl+5j6eBVnqRyPF7tIDampRJIWQ2ULvEs9ASTBfCE1knnPhrV5hJhBSbz/iDMMx2u0fWgqUxWsXaF2lg/n+js210L73jIBffuHTJrBjnrQqVIxeyykdRSocJXkBYbfWTQzLWqYO14cVxbabst1puGRGmOFd80jKmSrDVFr+1PkOhnBmRpCrpWXCPB/5jO165sxO5fts5XA2WwEYui/MEYeOQuOAq7K83ZZdJVUy3yjxeDmY6l/H2GrCOQuvoZ+XesAjmoHeOqXLzzEmKsCUNIen6NeWK01K4bzNfnpanpXscpeB/Nhn86nfiWL+4tW3YLix5Tf/+ZiP+YtQsWeolnVNZwwe5eqcGRSc0zVQ3OSScmmcVGIydfmYiQ01EbsLbdm7HbgO41ak92H5vVB5bGdlwpnstfuJRf5fnEWh37xZXr4HtxTPKHiU0OVG/QOfJJVXbamoozLoXo1ECH4VEQJdE98wJxZuBzl+MvJip68RSy+qqi3hZd4H01xJx9HL5B6lNH2Y+x1hr8Tp+h34Y5UwCazePtdbqskJMlKFn+wF9iu7WXLDjp9ZMsqU3uHX/bR1juTXQcTdKmLLmC3vV7IId3YAsXUnuFpcJOxC7IQpMbr9NUNhrOxog47geGGkT/XNHV+URLSKaO2zCupijgNmsr7zWOCbzuWWeVpFoVDXZrvuKyv5Kig4dDMzTGQ4nGZvHlaenVca+/gsx+H4WsMwPpZJfVnz6Nws1awlSChQVWj474QkUGEkWEKdoAMA9g4+twTfRqdkcpRuXv464zmnZvJKIGdCGqpnk5wqkzuJiB9QMBe6s3aNbewwpF8GLR7yliUzQuQmowppnfzK/vy0guL+S2G4ku66RpJ11n0XEm3qHJ6dIb2o8GD3eddaW02HhB43qGXN+dUL+oNeipodbirWqDTABJ+h3qFSiFeDh70rCkprMCTd6Pd4qjCqYOJA2LDOgM6Qp2zgnQmz/CI+JKxiA25R5ohVYBvOEd3WgzWyuJclVqn6cqcG2ojJhFu2eWmTd67Pj1i/nGILggLTvGq7/IQ0BrwcczaauetvvSlsTGYbOO6TZhK95HZSRBaj/PmOiu+s9cptB21PZvgFRfSGe8MaVak+jX23ALD40jH1sedg6PJ7xvnrJb6tHvq62dH85o7aVtWW9nHmYVwRyeOQvBZfaOkmPw/Cq8TyAZa6NKqwqkLY13dgaCte+nWcj+If6I3Egdb62vr2SDkkgpPEkEnswANQc8nEYdTTJWEWxR7Dyo7m2UlQI3s6bj0soRf4w3mlf/DTIzMLcCICjKgfS9HLWzkIZqW1YTUIXmoYAjeE/w0eejlzKe4B8LQjGCKv44MJT3qtVBpGwkLsbyuK1fdfqnzwStDHAlO40DZO4a0M9rjcmNCXvD8aqT75QvNz5iomVJ2V7RMXCHX+xUMD6srb3pgHl//8VelTJHFg8vvUxujU8N9AmctdBKJ+F6y+VbTTePGh+sVkhZ7C639G2RHqy/rBHwyTk/ud6kIPDzQyjJ8YZTfdDvIxN4ovxFUEbdjpHGXBqNiEmq/DaQwM0zKnsZkD9ZvILqdo/VOxvGbaByRQ/N4H3GFkSCZHvCYqIHLOGcShpwliwPWAshiBzutz2PBuyLwoYtMBQNcYMqmjY4Nn1NErD5kQgk243QZn34YyX2Hax+UTa7+fWdWp2P+WgnqV8Au5OJaf3YPz6A+6C/kb9E7aQ+gYhXDaJ0uugt7XenD6ngcEHiiTJpr38Dc5SsY6LCOE2lRAvJomJgEFYoYAfk6phx64/aedeffBco5XlM8LQmmvJ3GNNys7SaWxD9bK866N94Gv4ZivcAI/KiNKBxkNIevWSY9wdstecNxPl9/B4vMnPkPcYOwDrfaDWegQcTmxydBGc4v3IO2dQM73+XP1+tT9M0VDwzOBbtj8768rkeDmD0fBVVPNgGdu+2mbo2Ds/7swPopchCUg/7qvWRwxKAMYqUwq3Wa2P6Ox0/BMzTrDM9CuiDqTQMVCYrl6KfTvCrFtBgJmguVvti3kEX5gp4doRKfgUFLmnKOK9ZabxC9rL60KMC5An27ClpO6YEtKCT3Rj/fqlvfoTuUytduqfuBMeBidqQK3Q5i/UMPw8Psdtezii0/Bn0xXCmeT2rn3vCnuctVLUZD7tkYzSwhSavAagXhqtgk9m7JnspHza6FlmwfuGCQdzPyhNzKTQZaXTZCJih2/xO0SRT/EDY3n0TboWP33lxVxcTOfh8k8ZmghF9vTDnuvvC9QJskY+FPn0gH6/L5H3QquLn6zbIbyktqiLw6TilrLH7OpG7Krq09OQu9Zm3sbPv/ye/b+UseoG4PeYUZnxq9aWWSKuElBkCz3w/1h5Znu+GJnAFqJioVxwKzToq/CZXcIGveo+dLmOVDpJalwjchcmJdzeFog5oz/n5xQKzUf0nYjyZ3eYXv7OJ0a2utepJmo4nK8gMUx+JmsX5AWBiSy1oQFwnENdkB3C/xlEg1KebcFbPdXTL4PhGGElw46TjDQPJWn8W7MqxPmwo3GIxw6N/DZsOJBQfFeloig6pCwlAZYPTdQXQKFeOIPgSQHF56bcEeOBEDqnp+6e3mDHd+LfwXUAqqO5Bu7DIAfqxrXbzuG3oaaLjuANqNfs0JqJrYwHQwUEAEPbaDFJwAtTEkexoh72dJZkLBeQypnP51EbIaXOf0LloV4qIZnyustuAqPwQ4gLwXnZcGgO8ASO9iziu5E3VfkgXx/4dmMiMzef8O+zfmov2EFqEtBIPhnwNlcQaZw962CXQCalD9HSLsJseAd2CzGilwV+IHDGKFUTo9J7QV891p0TxnaFOgY7aAyxHTPl4K5xS4vZEsa4vrbhk7s5GbWMVcPHRSvwlOXCMvijfp/DuN85Rfydp9Hi6W1B81z3NFachetT3wvRfWFkbvSFYKeYwgIV30bFAJQxKWgwu6gLO81jbFtU9Qr5ae8UZRKspl5iZXzvs8uiVOZFoQdxXBbl6OgeVgp2OxDIt475aBg2tkaVeUkusGkio/BBBNLEBVaRizc/HkDvD/h7GHdM8Kz6bs5D+BFsa6dVTis1EIdQGS57nP14ohBey87nvD98Op/p2ZQZm7NG2JN1Ir3lcIcX3ne7dqNQ7Vf4YsZ7CMl1q9iTSAMBPunxi156UGaePadQ7q9w/bKcYEK+Ptt6Xwo5TwGSZXXt59/cCEDfChfvHZOb37Gbkg06VF8eIdgufIY3Sa85dTrt2R7KEH52pd5iRm299n5QsjXcrTWg20TEf+VwR8SSyCEXyqSDCjRfLKTyoe7FMDw1bufaqpGs3Wusjnk17kIIk+XFXnPC7tp4UrgSvYSwYH62FJK9kR7mkHoCE8a+aHYQSpIxvoMR+nwYYZJiiMXD5rub/mB5753YBPHXVzDiIce7A4xOZR0nUJ2i1uyGhIUyjPc0nF3Py2bXhsmt10SVyMeD3IZyb523GlMfb1HiIF64m2gD4kvMcKt04vhMeGnqQhJP5nbIwzPXAhMJId8QnqhJEtUZb9xBHo2SPTZC/ARnNYutKptbaGvGGmyoqEgtVTbuCYZ8V7MzCCMhdBgN8cEn4IGfa1Shczx+CuarFxF+oPgXyEUSrNwTDSl60LJyBr2K23FTc3YV1d/DLP41QghTVzjCd/+gHHYvOQ4RVdDfpy7uaz25n5VlGAAPSFcKLiaGb5KQIDxZh7R8wO0CHbcaRctxWlEP11Uosg9qzX8ntMHHXjLiywzOyq/fHqULzM7rftjuO5x7lbzeppsLu6xPoboWOEqwuVOETfhyabsEQYhB3eipu28Ee0re5nUjIbSkQ01znPkDo0pL6Ht8EpGO1oQXSZozpgYYCg9Q5dwv5PuRhmus9MsBy3eSkpQI0KXmMBYjhLQHj4iOJdvsDAlOnLz47JruboC7v3KkPSgOgA7/JQYD5uGZal1plpG5HH0BfPLHAiBpe1io9sB2gVCJDLjtsOHrRVjSt+JBk3rIgQYx4OARvdIgJMA+pcG2GsZbwgtf9Y99q++ecPLWrn6X20jS1EPDze3dycs2pCfU3VmBj4DoMLJux3fVhFdtQ7qcPTMBrVmFU94yp7a9PrC59kNDgdrDm9J+6dpKndpEJP5pcujU+3txit6c4MlZ65e2+jZCWx+GZc9G8V7TFS7d+31vlJi+xijsuhMgr6qsfpEkZ1iGte0DbgnC5Jqow9d7OKmjXoNaZJtURvIGbRqNU5KSPq6ta8wSS1x7SWN+DV1STV562GKNDdrv0YS4Vn0kDiVEdroE0PKTLnSvcS7MAj9myLfa0k40QpiEXHah2+LfkioVoOPUUnyi1nP0LH/YPYujroLZVJrzEwNPKpWkp8KlIcz4wDuvavjMUXbyCfxyZ1pcT19MAg86eLoStOcDcH94F5bI7QUgGbUNoeqZ4qDyrHpoCELfwvK4dL3cHmIkmAiXQk9oXJ2DxUr/iwzDV8PnpxGQ9kA4Q161IYytCmVnkaC7eVJNebo93gh0ddr00SvsnWr+gthlM0BxWK+QwkKxnatVYy5NOXo6wQwvURva/kO7loNtEk80XyJQxN7wGTOHLoGG4IERCEffUpSdI+NNPMWL6NvJJK7gG/TFG07Kgi60/O1cPltQpggGIFMTt289d3alcePnZymEG8bzIk6H1IaHE2a9gHdBh6AOU4tq64WLjtq6Oanv7NVp4r3P68765K/fm4cwcoSCKVE+baAIpsdqiCInn8AQpUDh5x8a7170bxhs5F7NMSwBEZjHRTm5FjiJsoPhVZ2IjzgLHm2KJov4bAjrgki4maCrzCq9u2IBOwSNMvgJiqga76dbvT9Ro69uxOwC3F+5Y/OdGtQt5Shpi5nStQc2K3GhlGmaXtDNwNOZOt+qPlqfNuPEczB8TgRKxwd/fxId7FPmaRR7f+AiOChYhGis+6vUJxXaAnVpHQ9w1GqIpbCPz52WD8rOr0nq19ia7DzOSckG4Ij6+UgX6B7xhrkkQvLincEqJf9rEv3PDiSNumNLXLr8lgybSmH8OKpYTNzJGrEJZ2ie5a9aYSKj98DqWYwEpguAW3fPD85KIW6Aza8bAzODKFMMtFEoqF4qVqVY1w0jcX+Ti9ug6cH9vrCJjJCHz9MHXDP3wBAREHJaAViLQt1XoFZ0RgCGBAIbNpK3PAcvez58I1y1K8yGijvcddj4UAC/q+IgGldSKdEF8Bhx0Slpk2eGBikyGZNUNtRbiB3b5R0tOrxEgt/nzyrH6KB8wK7i4DcETe6R+NI/Kib11m21JhmtGUlc9r1TFADFbDaZQNT6TsC4y2MiBujNZgSIJp5S4lWfAXhL/1HQrY69s3ILh2/Bb8fDRYDbfrQykUQngofF2j+crIaC9TacUerIFiJ1CbCbbGrTZF3ipsvvnP9Wr4jVd8YUOk5084ARjBP6AkrkRnhZeImBKqvN/S3Vm/iuSTSLVxSaG4qOVCUbSbUsTQQykYKojFLaaEW+L/mjj6rMY1cDhQd+5fwbaYGcqaVBiPbs21+wXErt6/R16BYEB8iOiw0wX6chMeCVBD25kc6KjPWYBfRKEl49JqZJW7LdSpCPdyIRkgYRVOSMVwqaXPCOq5xm4ksM+ekXTlqAEqIACX6MSS0VuSMe6G3Z2KDDYFT+ukiSikGaU7lMqdVQlMxl0VDhYJ49LCfDDVu8WMX1FtvJIu3tiYEaB8VCAoeSjirqlib0xnO3JS8kHj9+ScWR4xPmOVA+TAAHVXNu4IcjWDjs/AVi7I22aByHt5vxfhNCUTprIuAYVYg7irLajW4Fwct7LrmcgCseuwo7hn8A6A1Zqw5cAODR/Szz6idYXTG1nrdApFuRZgLzkFZjkdTa5BfbLLWcjnX6Xeqjlrmcx6c/Zo2s7OdI2BC9rqvSHjJ/F8B5BJAiydsCkA1zMq27ulcl4Hu3PghIJ1d4gyn72Xu8PZxbb3VMnM307E641Jm8fQWlR7BzzaxVC4gjh7/AeSeCJsf+nPdzd2dmOoLqaUoN5weMlqridVaLzTdKVYpt7UklFjtiWDgwtPhUPIO4Mu6Th7u1VFumKYe71hzAfHRCBXqKJxeP1PulLXra/8Mhu39+Y1ZVR/hP+A/iu+XzjZERkL7f33eyBJ8j270hcIWI7oO1WOqQR5jILLmWB5okk5rdfp6r8VZIXyGg87VCOe4v/8cLvnHCW+0Y2Qq17upapCuj0ePFCSK7tLFQMKRPGP+/Vne5IhzxRD4G7ocuGykUFYfvp34D4fQvEZ63NYolD9mYts6VRzj8OE50cq92pAfQmLAKalorBwN6BrFk7YcdmI9FStrm/DhgLXmU9fJOV/lBKTevZ+WeXaRFuHegKHS6Z5WlXCjDJLC8uBkL6p4BHT0fo3tbmDCSpm1pCGxJ+5p7QeWoWdlFiNg4yDGVET5Lc+yTNNaOrUgLFm8pV5a0HEeOHtqvU0qB38qxt3QNFrSRkC/MAfhaLk/GJrt33I85Ssg3qAuv9nDcdm1MS1CCXLvgUZAfttGw6RrnXPRv6Iz8b+0O4msyjU7YiAS9TfIy6/dbVHFsLR71MbQTuJM59TG7G+xIw4Pp7luXC49rWDivhH9Iq8ZgJufD+h2pE4qb0BuCMdLcqVLcjVmcmX90Lz7q9vnaG8yQKY+0QU6Ff/E7LqcKoD54vyuDHQxSzVJXg+bXeH9FtlEZmb+bsqcE1baGnJKzXQ0r4JBq8t6JuVDifYcioH+cWoOJRWqbFQo4H3JHbZVIbRyOQKVMz+JA9cRad8gCu2PQ+BXGK2Ss1nxag4xqpXrznKg5w5/cKTjFfQGvleuoR7+lYFuKtSWx6Xhk474JE75nGz65is2KS466Gr0+u4Mc8HVNsU2yNC1Mb3FScRX4kgqmYUS1CBe28VUio3f3RPzqJVHEXRUCpb7nq81EeXK8U4jZy83Ul06T42+WS3FoZKoYUl8H/MMDpAYneWs9oY6zOUZ9WIWc0FZASGe46fmfEcSv6AXrxIfazdMCm+p1BpjgUDboRVVjoeoMlxrINUytjw9THDX5DjduzOwdWnyFWBi07Uq1QjWfMFhWU3j3D+5JaLwHxBXDafrps8X8tyzLx6CGTlJQFwWqlfB2lidTbuva0/FshwdjZuclaRnbGp5ZhVUcl0Y5WGmVtlODQ3w/vG7K10bc6QIGLyC085WNSH9t5Y74J1j9SGdkcPWNfY8TTZNG8Vc098+z9kgFZzX7VW3ONMGR3FV+nTihhRDyv/LX10svh856agZkLNWvs84uMTkiu0skJmx/L2Jdgu0dWVbD5d4G7TNuyEJ8YAioWVC3jc6I/X3Xprur55IvAu65dnPDfdFQEwia+NrgOIaoMZz4SNdeFu7JKFUcvd1va2Fv8ER2QV1WBK9XrzkgB/KkQHQ+bNomt8X+U5hCctVX0b0ejvAnwgOJ3gg435nqZHWDC4cgfA5TKmMQQ8AXT+7GoqmNb9NoSatqCypHp/r8T3/g8jjUG7SP8FsxtRSWFhVUZMeyw6K1Rabxll5kLFOTv4/Y82dhSPEQLjQ/CSsX02fE4iHgTOIjvkgJpJS+A64hYLHsgVq/2MzDyYB59XXK0JWBaASb52625ET0ZJFayASXJSIhDMOa6R4CEdNYa8aIacatym0xqHj1FzO5AVqRcAfC8k6y+2NcsvcFW63QZkl+K//BGCAMQbSc6y2a4ajzlVAqo50917kfSr9f5CdEEqCkmN3e5j4kQIesVEwwFjf/eHNlZPpWfgUVmij4NR/jTXe5nt22km8DvXphr4O9xZtc6BKRwuws7AtHVqSvj2x7hd82u1Mm8eTZojinCCk/ljLNzMROAijB2/T2QSg3WTmeIzgwxK2BNATeA7ep1uJv5BKiRDrJMl3g2EqZ33S0aj7e/3xaNMcq5GLxTL6hJolPXZr1ZuTZ1bT4dgiqBEg5iExuh+Rw6YHLVLz6Snp4oD4Za3FQwYLi6LXV7tr17td/kmol9BvijH+mRccUhGJzCtF9ICKcRqG64HJfKA0Ggqv/HzzcKMnLVmupH4gHa9ni4ICqaJcxvp/dDHbxtPokizYhBzH+Yzvx/FoyyMWqQTXYtNB+xbCbgCsb0zR45aK/qQqQifzDmSKxFyHLgHem5p9XeNcBIjln5lZjkMuHIUYYIkUxKyjfmcRDk6dR1WO8zB3o7oFh/rtsUyqyRHpm+xoK3dOkAptQvF3KUnLigAV8c3OW3jU4wtQTGRss00aSfudPAzjmsI6KXBxlJZdWbqQCGXCl1pxLG8YIK6BlyiZuJbYt8Caq3dTFx0cE0QmFoQUCtebcHIZ5ciCaFLdX0qI7U9t/nVgcCJBEQIWo6/6aKHNcD/GrQCcCGFrNtE777jcPLyL8fnkyyDmJuw0I7IzZNUIBMgz0XYfArUuZdCopYXoqPGywWg7aJgMadVXMnjxZrv03SQQIvRe2Xyqyixg8dISZwd8pfIlo3HDPF2Q4rIDUAnV8/6UxIw7iIuMQmcJVasZsajxM76xxEKILsHELtOYOCnTGE72cZQ7ckBX4yrfvGPwuFwmyYaUcvUr2kIPboX7HIwWmRsJoWCY8xJ0CGKCCDJY/co6kG3mBM+WDH1fkFkQm+kU1AxPP7dL4pTN3FQkY5fiuSvD3zVuOp5YdHQ7I1XOxMQJJANQ4QkmpiLTC1UA2DD5OcroUy91jDWz3T2rWHexlTsX/yRvYy4zbu21WeWGpOHOJAYJSIklkh5kA9N9WvehGi5naJNZTPsCCQU89fQSDH5Fy/Ez7yzBeU69u3I/Y/eN+ao1O7kLM5afxqjpveD3M24EAymsG96megHGP6q2ze6RjAMAPVJNfSNBxUKZ/1CzoLB2Wb4cX+CW57O1ABYYEpN1KewSSaRf+yBS4LDOEH/E4MdJGL/vMw3RoN3qnZkQNxPuz4rTPHzy4ZxEdM9GIvIzdCnDvHgvBaEZUsBZ0754hEHXEqMUbRPB1aSwmvFDqvX8xQ/Q47X2hpLhEQyZZZ99IzWU2sL1aTgjRfokM/qhbGad2ouAhq3sBAUwztevFL6iZDvinxj3hs0kiojuyDfyVkUrbp7V3nn1fZtvgJj9V/4Y/tv4MS3Mz7/3COGLs3MasOEjH/KIWcX6JCYaPcM6Qy3Nu/V0THdWXq5oSw4jsy8aCv4KHIGYY90qH6wqAPn+7Sv6K1VmDgzXxTC3q6z0OSCP91IEYWJHTZgWKOI5XYFblZlLQIPH3nWxGx0i/srScuCmSciGvOkETAA0NCno2jJxKfyTI+SqrzW6g77DhvKzi0cdnlBGcYld+MXM2hJrIvy7OoGBOt74CeMYnkoLvxd5LImsot6Oe/birSjI237uODfUalAofgyjUpJDtDwfQUy4Ie0BISHO5rDSeLCxt+GF3eqBPX2zFEauLU9+wSLEE/fmNrnq8zIMns7SXEvU7Md3MIePN9vVMDpoGEu4g0IhGIOwQbh2O8wp0jYZKNVKcPtrnIp3U8NDCKRDOwGFJjHZpj9HcSXuDOCOvzsUVFp/KckAiWtJggP8LLRlU9l/BI3k6H0+Ix2/TLNHpQgQ3QW5F8X6zDg8UICk+HDDM+tH638ne0Nuh13UkQQJq3AnSuQKqebF0wod9rd7uxKk7z+mWO3GmCrd0GsEATn0S+rv7SF9q+23cSdqejIHVJsrJ0FjXzjbnPpc4gJeCrZIVp05MSdet12EQzATxCTlnDoczeRu5t8X+Y12cYJ6n1+dKq/Bbksy2k7Og0cD5NB/iyVxON0/7p3/8TgrMK1fag+1D9UQHJrZ4b2r2UEz3ukGSw2qOXfLhl+7VSiycYj5DUY+X84ERzfOBXbmrwVut1L/YGQTcin2JtO4kMAjSFHJuep+tn1KkcNpcTJKcHSIh/oWJwkejr8EE6G6y/xTq3GobtYupx8OdHDCg+3hhePOf3RMG1Qn3o6T+dRYyRzFSVXxf159FzWCDfpUugtesA3Bmtow9nJ/tCmLdydYtL8kYswruvWpvGTEINzOmNzqKzZAQa9Bxtx/8v3FZtgza4rYKkSdbDR0JLJRk+b9KKL78XU6ZUHXpys7SCt0sZmtUSfzy6EH86aN7hjyXWhWx/B1GA+Z5r0XGW/jKrIIlAk4NByLYL61DInO15MN8U5hTufw5+SqHBwUr1YZsD0YD4zf9ZOnp8TjyhnHX1oGVPJ7NYv44JlA35TwW3dYvP/foi2T0A18D+p7rocPq4mRQ8e4boJXNcncRWJ6zf+04+sR+FIJRNHePWTAGlSWnLIRJh3U4kRSCgTmVXDBR9pPuJq/810DSqj8ldRal/lCmugJk9+j8eVVtKScAeyBuUJMwFLlyweIIPjRtR8s6MjYUT9hyJD/CG8mCSb0Ak2Byg0MLrbUnIBm5GNvvqb7txIlCFiJWaC6ql9wcRQg0Y3mFk9AeYUbxR87ZwpiaHWBpF2NGGrVpEu5xhmL1kndK3sTu/qvEYvsM8uKG5QZOLxzeExu6t97jl9r0QlHx4bd3YrHm73wodpyZrtpxr7ktbTq9Rgk31ly2/7i/OnNxDhe6erMFVq6SZJyH6PNSyWC10VfKIBBD17C5r/V4O8R7t01hiVdrFkfXHUm18TdD5a1ff+sNoWieJ0EwGpLZ02xj5AUsIEcu164VECgz/1d2TYVqXRMzeWVvqi7Uu9VlUwPEjybGmzm56nlH1g+otZtizn45XPMrAhdvrJE4LayME8C5SJBElCp9OZcJhFFgnGtq2lHunx3yIVY7orCL+VR7wbEdV5x3ub1xCk9o+i0c1jpk3h+EM73HTdaAb4U3e05ShmubP2vfK5kiH0hkXa0j/LPgpEcBMKdCWeqH/hySn15FZx6j4xkPFlErBLC8OayuB9YgpbxGOiNuiyLxeI6mbqS87z4Y36b8gfE41X26R4kz4UZKM5A3ykPu3l4G+mdLHLMsdqrsLQ5cqq5YZSvM/WL3PgO76XHAXhx8lTByLo9GWFCNTp9Ff4dsz9SSJhnReFf9wj2dnzCgnf7eeB6C4C5NsQD6FDYJ4td2sFCSgbHq4PmcasAyWXNhBokzTAGstZBNEFQQ9ZyfcJY9gXA1H3rSqY+swRBVAb367MgRlSoFFKthvAe4gDrcfUVUdbaWP8LOguo/+MQs+6M5CiS0v8HOv5zthl3TnWSB5Y2913ueSikMrN4a0JHqfBTLm8Wmp1hTbfwD8a7AxWp4QDfzUEGi4yXgcAwgtfeNCwp4iequg8IjrvbKwgj7/ipkNgM/PETn38PtjGfmNd/+Vv1vWGekq2j7s2bhLh1GDIB3bhT1Goj7Z1vgQJCvUKNlddNps6ooLXSuhN8bCW6Tu3IxIU78Xa0khZr+melngrCaExOSv5sOYmOaN69eimhcGUtJnWjkhOSYi9UmCApVe6SaSuKK2woTa9kqSEEyRNs24bkmr9n3uIuQ+2KkW5MW/nSGmnMJv3oWi3kd+RJEYvIc03sNOfTazL227NR0V6wg2SUTF2csdMfj1ObOlzJiYAAFAIJsPLb70IvQBdUGwc8dypR5yrFCepJL8tvWgjm5UiXoZUGZoNvTsU8PBZg+w08YhD3EQY/AFOXNTcUMaak29FVG90Y65CvFgRSIvk1YlETVVhQC7aibii7bWZZsjVQRVhZC/kIqsL0nz4LCOQBPADvVrjjNL73xULhy0banHSswJEsBC2HYD6K5/+ZEvC0vK215m5rhlBk66RjzjcmqHYZe4yDOOAe6f9TIRgxLGv76ZUkWygi/CwFTdNv7oBwqk4JCoaOyMDG600Uu79czg+vI9ne/YhfslCCFCQxL1oaHbbl/J//H9vmjM3X3YMDgibxKctLrMSNdJJ30d9KkHwJhfTPzj60JPEuKmM71ZjzBV+OCI08CCf+czU2ltMaw7uNFkTv8dqVtzDt0F7EN3xsAFWR2HCmOGjEzLtS5u5u4+gdzvaLLsjHpLz9Wcxq4r9LBSPLpsnIQXT3qd2GFHTw5Fe9sWD7Tk+jKrmo1Tq40LKpLbDcJAmaoGWxCKWI4DRgYzjoDdVLoxBgDSsdCVUhDO/3o3ZgEYcscEh4YJMVkK7fcgrjhefkUDxEjXZE/0x2lSAeGBrxNeQUVabjBKcn/KOR+L31rdsc+fhaqJRy9uDoEiAFqeA/hYdMn8ubuUaB1DAoAJFnBrNNwfxlQgq/aFM2rOIgEJIL2Uw7yGefdwMCxLD0MR4Ndg5c8JDza+IfUo8hhZ1Uk8W2bB5mHGYIOU1quqFOpVTOBB21rPV0451QXbNbWIGEu/SOfBPpBkVDH/zmwG1Zeoj+BepZoxnsntxj/pH3cp7bovgZ1dW8KHh5BNSw8vneEgbRfMZIDhk/5Qa+SgBNNvPEYBMy4MINfaO8AVXGE7to4AG2syH62pqfa8SzKcHvvXyZyfwRa5Nz+xesqzyDlsawW/AEosj57157DZy8wayR9y0vimhyxFRTUzpUeFEAxYgQdrGMMcoHSNt9DINdEOAHBrTQAVrDfhBDGYqeS4ZI3SvDyrBRCbcgRe8bGEZVi50KjKc/kYSxZTkUqZtn9PMAFy88xa5eg/5CwtiuevqHMmdqDyT1A4bo0WQDwhx5AI6aTXgc1mrF9FONJCIrjM8s+KWkyy55OLQvdtDknIYnuJSiBc8vkzfIOtlxWIyEVGZjIxO2BQmDcMIiVxmcwLNUEgvdhd83lyU5Mm+klmbZ13Oe2IrVYvzqkunnGemfJdPhZm07lHi1aidUqnKj2z9vlkaTBnHLx7edEOZj68WSej6xxEuhySxCxmBKQ3VgW/oWW37kaAPZ2fIkKZHt0XuV934doNmzaEinatR1xGSgo55wlLtZKh/WIGGiYrhjQjC+N1eimGIopZbhAhVBYrPW+rp2ZsDHu7N3kNOK3DIcp5Ghl5VMnuH+CMIBNoHpAUMWVxUdOkaio83vKK/6k7yS5/qEejL0Nk2wE8FWGmPskTSdOkRnb64gFXJBGaZd/sMfaezQztQE/g1dwrv0kVn053lo0c0HGLjpumRRbXFDp34mnkzn6vSKyrV/p3bhwvWL/FD5Msk2UWE2HgVQJyn4PXvifXaETSwr+rQ+C3KXzQTT3f9H6IIBp6V4awx3vbsiHjz97T/epYBNFz8xrgs4KLrzYFlP21gv/z+BIG9aeqqDDXxYImnOv3bdnnhB97RH+AAFKZioe13ZWGnStCedCIs9YFww8pp2PnhBxlua9viX6p34NiP/6/u885tWpp/riO9dGegVm0/APKCrivnRylEptRL9DjKYm22AVZcZvWeq4KRVvsdXPbFGyZbIiZS8ysdnJhyawz2EO4iJLFBQjkutYGTBRMCg6cnLX7KODDpma3q1LaDbetoF4VNloS+ljRRVjy/TzHXGMrpkVGm6qpi2EScOcQozy5GHwxaXycQvW/rsvCq/AgiwmqS4xuTlnHfE2VHV40AVOCIoNzEjx1LHAxKoM7ibEVvvkiQ1wxz1gIekDtgGdvMtGCNhTONKtGIaUvtnK0NS1vBzelX3EiVTKuH4USLIqUPWTW1U8wjRn8w5To6Sy+AIKOFEDqvnC9yyJFd2jKlfslkfDeyZrhgcqbj7zH1SVX3Qs+GXmPpdwXXuSb0FsYfqeJhOo3kZ2FwjuuLUihDrEv1p9dyGNh0f7PYXVUq+gp+aNrQAOqJcthrjMEW7cy27b2ZRaU1Sjbqynjvb+aTtIXqsAFKq5Y+T3rkyyFGaXkl4q/dHIXh1eXokwWdzLidLmang2udp9LBHsClD/IrWbUpP9TZRPRIO7j+i3zgmI77Leu5iwLS+6EDfnOjLfeAXcZQuWCiRYseKpmOBIqK+myUYBOIrpaPiLY3pgxQZaNHrrykDSdW2y5yBvQo4ymjiZ/WiVgJ0Rk17PJcX8tIKCJsINnfbODy7DXQgjh8CIIM954hdibdDiFk7xjuNn3rQiew5+c/TF1h/F0cccAZPoNoPlCXYe2jiUP0FykcEJJMFoLJRiFXsVu7EGuiQiQO7w1Q2yeE/S7xz0r9t1ya/nBiQO2SbhLpCgPRcTLcZgo4HALkGs1OTUXTX5uL+AouhVna017Gnkq2VaSLC2ZfzjdS668EwLeEwqxnPmYSYZVbjzIAF3X25I4kci3Ei36fGYc0l9CKks3ZJPLBU/q0keGYE3KXyOtdcUvNaXwqrm2Abht8Oc7FU5/ClWGfYqpfIzIEPpTIt+2cqqxJF2BkvGF7Kp2tj7PkVtQG2zg+Qn2/E0deu8EGqLmBU0noTjtZ99d16U4gBS7R0SMZYEgPzIl3QfeNewT6aOyan7jAWVJLQrzIH5qpLgGWJEOny3/VwYx5CFuhejkLu4X7hqvkBheZJ8gvu5PHvoFoA3qsdPpPTSbFy9oUCFBGx3iOIyWa7MTndgkqSCccvY9v4dZWntned4SvXD0EFuDRGkL51lXjvAh185VGnOnl/prj35YkqteG47vUL20dfPBQXtqnqGd92LALgqKg7yP4VS5HFJpqebr/w931P60QnKjpQwsrcI87P+bKMdKl589Elak6RnLBOPrXNvqFu7PMk/JTHRRhsjD27xP3Ib5tfwSCymlCGcM91BWzX+f8FLaV+pmElh2ZZhs+vt2TUBmv1roiSGviv9d9j00RO7CpF5cKkto9WHbQdorOBhZZEp61XA9meIzNW5t3m7AD6CXsozUbgNhp5HcQN8lVSziTBCRMEOZqNE0FmoxiDklTYKQvA4FTcjAVmQWJq0YIEYleTJLAB38ZL5DABvg12lY1fkIKk88mORRm911ffEmzYOSfRek3s4WHOMpraaXuNChO12Qwbqfoh1C6vvwleFWP7JlcD+JhHMAQFw9UyUyd2zorL/zdDLJ09p5VR06WWZskbOD+W35w97gYJ1YGVVQ/QAIr0csaPvgUpzARt0fR7182FjRXGLXWW3MnyJGfdQgp7TiosvtKsQWx4QXmaaTlB7TABCJd3sOuhXUjShGRY7TRqJWxpZN6K2YacthJKRPDEOLYNqvYG/aic84FVFlPNtDEo3WIPZvTebTytYpOosWEyhoLr97UTjTXFeBxyOcXrQpBO/w0rmmlRL4jW0DgBT4vRkHP9s3u+j292h7laLwZtljp12tDiDFlOm3mHRCnpo0sWW8omyE4Yv+3jho0OnlX9LLaESvMJA86rIsoQvDBiW8+nK34TaK0pWgsBrncVgjh0YsA/dW6xQK5+MVdHn3LPdT6HEY71NZ/gXOSwfnsnUCONiZZBSnB1PCgvAFOuTu7zDocp692/juCwxmMemCqxNvww2LHIGoI8oUQdrEKP9MkknxxD5vJC/4F86AnlVQddbPulGqPx5eWqCe9otQ5zHxTzXxJKpakuwt9QyyBLGXgKlad8thwjb8dwdr7s3LlnYEzrlKSCKZp8xeHxq2fU7JW1icgwJ2v5c72gIE7ozUW+KHMfErGKl13duIq8elHD0m0/GS1O7fFCd/daDPYvrN2wrh7qAgB5QRkBCOhEzFHLpEry2RbJqqkMPU/acb9xmLDuTkeR1HCSvzBuvtKP9HChCoGb7GfdXtxUTHfsw2o59Vca7Mifpr6mzkgCMC8hWZls811yNgMMuUuqu79GlGSX+oLaMATSnanXgkJQcVY5evg5aq3yQMNy4lBvrD6PWL3U+7hTt5wuDkn3jMkZOOiTJIQ172lOU3AW6MtCeLjbY4S7+wXBgsp0ez9UILPAzktTQRzHtibU142c1E4jLb/5Kv8PPZNg6j6kGNYdR0+tb3pEtsdGMJ7ppp6uAv+d22TXLCAS5JwRg5aCwg6ABCp/1ncY615iwvvInuoJHBI6YEMuQF/stI9PqY412WXrWHG1C+6kqg7BsncQWU6M8SNETgXdPOfHSq0fk79TwyFIcCAldwDWplFIaoHWx7Rp0mMFMcetfl27bazz/Tr6MFlYf5GLOcbe4DegVm6FcRVHMebHyFEMZf7klSOYQlUoZbsTxtiq46Wjot3hhRsymgBVuJauVJxr+n1xY5SVHqZMnFbWq0QTSEMicm4pI9mSfHAogskyipeLC6bBMW8l/2n6bbPbIFDP3fb0u8z3YAHywJuj+yMlNndt0lknAyCoje/JHuLMzaRS9kGoHzpXrCmROuot8pM5kd7+DTo6aG0sdPQ24RI3F3v/3noYN6kAOAUVhLuRuCrB5C1W1s57EnJFDg0IygsHxoIlwBXNsrBl58Y8UInTzOIqP0uHScBVWMx9uXC2ftQgaPN9qWSgB0D2Y9iH5hQxQqDzaQSTCgHRmTJg2yVU4Q54kP9iLu8LVuWW07HLB1pmtRhEg28yY2LQMx7jHSzmgBwfDCsdftVKE77cp9aswSREwBlA6fdIGWDVxheRL39eGkwB45TwBFus8p95Qd7W8zUs47rSpXUExl4bWUc71cbVPn51foeFDNSR5haGizHtSxechY27VM8he7PdvYDhQ0lZRugCwAa0K1vBoMNEcwp6YFBeqP2FQRtejhe4oZWljzN1p16aPIylN3vqrdsUH4ARlq4aTWSbKFoHtBc640qsEZH5XhfHTtWCy0Xv8JoaQ1Zwwfe8c22S8mtRn+uXq2Uo3RSMPwIYcIKi5sJVVAqRRmuF9C7QbmHe4QXqV9MUMV4+U6XSyCAEFZ8qjDxQgbJCDrcuPEnW3Mpnlh7vZr5GGEZJQDSxBz8re9S6pkZu5I3ka3k9/9SnrQBWSvF4NNfyojYCbHBmA4znn0mifGWPXIl9eMfreC9mXHoSW6zKRQr5Gb2/DkUJS+DmU6QnzAxMVwlk395Uu9kVTnPNaq+k1UBK2aWJZt0oaMSYG05iykB60tHx6EtMXF2+roqh2CrsKLGxg9b/1E0rWapdUDYNSgSK0tadMQBvDWIp8TyWQutrM+yTirTOZ2Z4P1sZoq/01XLsZL18mb2edaadMpYvagit+gYX7MvdNhAQ+da60oPosoHRrNzgC9Ly4VIbnEy9hs3i0ApkjGP8C7KVmFdS5QRH08J7Tu+QGBmDBl0TobJ3EvQdveTe5HCzx3+Kgf4ri6E3MJRBLWhHKJZHy8Gdl3QUZgv0dDuTJOrHJ+j5HVf8mAg5TONS+2RIUo44Q94M1V6CxW8fkoooFmmiSE+ZqtBwS40j0IVf2mTejovwo4ymQbepHoU2LF8BJr34+JS5rHF84Jtq54C3j0NT4+54nBGcRDlXal50el4nhs7df2++r8IcgiupFTJvlNX4Ysk6wb0h2jIjycIIhwgHeRLD2cG6CwB1hxVWI4GsxdK/7t9dPtfMmsc97i5nlDB07crs6BAVtuVAVOPriXA4KCZTcMjZW/cSm+Rxhs7hE9pXV9PQv88/QkAmeKkOfXfZt26q+CC4jY930pRUVgufiTKOOKMnu9CS4G8qmJ2eREPQTLpqeeSEFhy3XDpz/v9oZNnzS7rCBHjt7hIHgEIQVW+/oC/SQDc43c4HkOnohcMWWivCZulHlNslmfRLu6Wd5ZB2KeA/H71aRQIJMeVH+WuwYHnHGtJEaflV+qjoiblhQ4HB5K9CQH61lRZn/oDTbVRN24Wa/82hpOgIHD7JVfJ6kcXZRLsCELV06Wu+oQDfXwtB/DVzn23XnjRG/7y3U7u4KxDoEzZiSymhB07hqLpbibNTHxEXd1Vv9q/ysYbL0K5j3K8SXNGmGzb2dijFdgX2Vitf7vixdae4SC4HTXRh5YTKvcit7CVKh7rNJgFUn/TjhNONNMTxAU/HlUJnAyQ2wdsD1AopOrbsI2iL9GnD/cFZlJPb0DRIh+SDfUCr5ZBhpBbBmn1dF5t1nNe/yBGgHQosSZbWqGnT9UOGK/id0tdR9cULETLVHPY5rTk86d4YnBvJdR8rTsi8XEoO6LehQK9LYHzhV+Rqc/Rylov2nPIuGVGXAJvGTgYF3oK5eW+Cn/6RwBZGGjAtOlj0w/C0NolTYLtbwKMgpoFoQgEZaUOGbe257/q5zeQKDo3CRoCX2Rm/091uor4Ynq/Hgu29gld2MmZf37gIjBVG6+L1CI0GqHLF3f3LLnaODE7VNZNrUhW4a5VJAFUBI6AGBMBVVx0BWdBUp3NHmQCmrbhA0+koCVTMoY+ceL2y82gWeI3Rye9REQQlaWZjWWdkKXkrOrfchkQjIFvFGeN9dB4cADYWB9t8Tx2b6CPOp6miY1KyRfth4veaypgNQVegiTS9eO/Cx+Ze7GrMSYYR0W9CpDJxxjgbfgmKLIXhqiYhleNaF9BgeT/l4hcnQE3NNOY+S1/OYvBM8bklvBV57zdnpxba4sY3z15pm6VsX9MxOjXHxHbWOxyxrmFb+Iv5ZK65MQ2QToIseCLM+nCK+kFXtFN27IDzikBtNVwCc74qYhV6LdbK3TlufXs1IwQfDEQTGnvaPYA8IGukttQs8bovhNkqKuRjjflj+V3XjZBeXjrHMn/UKuUIqBICpiOc7f6Pe9ZZN/YTWwk/Zs/lsuSjhud8/4bLehx0slCbwWN4JBhrzTGwlYOLLFA377pfpsjoxRbjQ1pNl/whJYF00//rTGruuUf7Dpn83wThXWF0N8Lt6LXDF3bTKq7LrugtDwvpGykMm1qNmzo8hjcZBb7E/q4uTPB37A37ceF1D4DzGRTJrgITcIcrEf8QayNJiA0fKAEC9dK1d3O3JW/KUhQcwq1Z6MWHKRvVfBFl4JtkGAoO1MOHQ+Ea8f/5fmM7CH6rboOXEt1McIfuSqWXR16hXUPakeigBRpliAc7QTq0gj9Cc9UiQaUes/n5HF1kGho7gsNW++cq6Y/pI1TxDJkhLnht+iRbE+Ounq0Xm0D9wjXZwwell2Ii+ZFYu9odNsWnhRaLkbYJA6yfXzr5FWuAsb5Gz/3V5rhZ5tReiAzyh85Y2P96i4ER7XiL0T7nylUuW+Nxsfmw2Ce8Ex5c8IV3K+WiIEmzeo8F2ottOsf5t/iwl3DE6H3OfvmnJNYy3N3WXQMd4e1rinUeasojKc38Kj/mo9wnsjE5zaVXPiitNditRsLjlXVoMkdsYqpdCi+YXsTh+4V0kL8mvZ193V50wz9RonAoPQqPQqtiw6uS8oiwmziQR9he3z9kQWNWpga5hQdctasbI7styG6WqzwOEsW2u9TWdVjsNJgZkVxt7eUMYT8f5gU+3cA6PnuPHxyEPIeWPJhABKZ3P1EgkOhLFLXDLtU/Fxeqm5FM4xoXXwemNTFJURg7MFRnIMcSl4T95zv4Xh9lbQ+KshradwGB/ey+KQV6Jy9Bu54d8gehuLDMjoPTiTKrhgIjpdzgMvv/qU9T/3lwFiWYXNsZZY21mpqRHQ55Rq9VfIAznuqAJ2Fuv1Qv9WzK3SLHHrdN2LC5u090xeLNx8In/4xmKfFDGNrlD5Fynaf2LHCxEGmlhdZ+ztcUjta7rJ3fqQ9zftyzF4mCpC6XVewFHV+it4TJsBWA5/UrWIgQS7zFErQb5kIJj2YAmpzyJo6UOabeZYtw7euHyov/KiLN7HXC5LzXHOwfFKERTMhSoNXuLxxwy3K2ms/aRnCoy1yd9HksSl8nbaRaDUzyW8ptRFlvTJR6UOoCOIICMFztA/x1TCUW74izosb4J0scuZCSjFJpRb6xXFPWbPesJQVSIVCfnOd5K748XUYr8wd4KSPuAvjrhHOspHQRFjXuhZw70CSHeflbJjnppZm45Q7LPxbjQSZKURlNTF4HMV+3YyTI9Shcs0ZHGnaGThL9MpkfAuipze3umbt9Blged6tWzuJGAZQnOGGkqub9ZKFdpMq1UcFvH1BHZPeCli9OMkEQMzXriaER7UQbY/4XG6k+1D0pStLEKiOmjg8BNR1lL62vk/dKo7k1LSULkb5ROYLHVASDM4yeao2NcY9i9HD1Ue3GLgvm/5HaEc73xdsPEpZWU44KfAJ5gLWqxlcP1lJ+bF0EwucgiFOLI1k/Bd7fvXDYSWAFM5po2Y2mkkU1co6PkgmdpjwY9Sr/SZZuabvI4eDTJtE7rMcBsTjyjnczGgC8RWpNNgZkF3UjuUYMRWKiyP1XkndugXTdAyWH46q28AuiTxPIPKTCig5dpwKaCqq4kZ8/vCprWVqNO7+DJM3ZKaEEYmKxq5hIb7dH5R6flX9EOlsKWHKYp+Lbs5dFrk+CzVxnX+ynhVFDLNZkxgrYH5+ORa4WxOAK/zcGmuiUecTmoKvRNECAQGCZvSi1eXiIi2FsUNSxepvHF7J/+tfzYqBGzhM1uzqI9N8XI81+COsrG3MwcE9jRSdRoTVr5pgzD1Iw42TV3G5NkbLWRKPpGBvX2u9UFfsdf3A4gnnFvHhU+52dRpJpuPwOjIBMdHzCbHL+6aWH2OrZrtl8+M0nqxgz0PPNpwGeku9hD5C3xsQn0tOYxMcuhVoXpcA1MxklNa1791wY3FADfG7qZKcEMUcqx0FHRAcKIFEa7AuY6bodmIxXKtrzVkXzBogSBIpbKX0hJkXGlKff1ZDx/C+/KMQa/xhAsAp3EC+C9mjKieHlXlnSh1kFM1iIp2/MoqqxtY+t8MgUnL1xEWKNni7vH58HfcG75y129Wvrlcd+4aImUJZuWqk+sbgkobme6r5Sl5IFWpKmi8GyRK1+F7FYZ0cwKfHSzSx6kuXJFrmGNIf+xWDLdeLoJhxc9fBjTQ+2iSAprHartMo2YF/K39N3DYRtAXylVNtNCKY96uYZGMSjeQRlIV2xG2g9lDqMd83wBTBycCH5xM3Hhh52FANN8mFZlrSbakkJclrRNeT8oDtqvODV56TuplcCV/v1rOZvZs0fr9FEUpdMgNm3cjvZlrTAicLI/JTL+9nphzHXrWxNhGBy1k+8ieepTuBP2jyKsDuRXqD1bhteCRWVHRrAUcNQcuQ2WHKi/sJ3JAL8cLt1jTKSSeelYmpRwvQxpaHw5jeicojrCwrAkEAGNezDCRDkunP03ilQc3B3CB5PkRQNgMHNpUu9GYvsNa52BTpWKzuK/tubBB/IQsLOiZMBwiQTn0fR7cFyIE+qwMpISb3/bGP/+nGDYF7Zi0bJr6+JDMscCU8ueEyXNnOLp1cbbujdCYxHAuoxOelTSJloswn+JtC1BRXVDXFjlEbHUPANTCEjk38n7VwcYZsOUXGOM7N0eKGTK/M/ymYgg0UE0Kq+PlsrJQOxQRSmNSvlXrrKH9DcIDRoBaVSd1HGRqOC/Lz/mUhHHKwARNsBpwyzt3wVT/a6q3tBTiemEzS0nUnC1wRy+LfzA7gWZ8168eTWImS48pnhTeQA1fVK4TQQ1oBazHg2pO7ydbm3N6BJ0sBDfWOeYSQRYKJKv04bvwUgYmMebBDax+ObxbIgp+g02Pq1JVdh3YIbWirl4vqAbmNgxFu2ixoZANzk6qgj0ny7/k8iB5xfUaShxmkgkftujyguhNok0cGLUZ8T3nb1dy7SNhONuiD4aZwsAs9igAHPMPxAglW2ot3B3+bgVzn14BzvzngbL1pAwHBtg+3CeC0z+D9TDYl8sWJ58oBhoQ+FbmfZRc7o6A3ggVqOi+wFfhFBMbLQYDh53CaENgs1CRC+sD/Yr0ib+rlo1k3kzOrq8x0qsXpimAoCxVL/UzrlpzZ6+6IIlQSpVTu20TKkHnhJujySnfgzaBzSS79EVFenbzSBjmPzVvKg+iXV0pwDpqCBhGJSKkq2l6dk9uHNdoYUZlwf3lydicRj07qEgK7qhAfcP1nH07EafmnqnDLhrkenfSHDRG8+qfPqg7GIa8d4sxUVmp80WDgufj2zZ0CioLpesRRC2dc8mHHMeW6atGBzZ7FPG6mRmizmYQKwJs/sojXigtoCCIH2MsGLJ2fnaciKaZTO2zaoKAw3SDuDAlnY1b1TPPv/UKzqfeYtVGnzEu6wrs29jE4oMkJtNmZMPSypbzPK1XG5iqhnizrmqf0JSd5KZCU2pqvPoDGHYyp1aCHnK1kxSZ2WzFlZBtq3fhQwZ1Zm0+OGxneFdgdwGsmBR2AdzstKEb+9p+nYZaSITqsNnCl965J3kO+dJlj+N7PAS5A77Kz06L1khfQWmw8i6nsba+KU82hImOR0vMzVlHS37stFrlGvMjBA2zAj7DOd3DkfZp6MoqGWIWiayMjU182OShu9nXeYdLcWzAdXiiN3/kIBgrH6qqabC30iDH5VmFj1UxRJxWuKufwzzZp8WzwTTDY8xrshDeEfHcSeZGVShbrobFhu23Gj0yqAR0ztRhGwcmko8hS8m4xY7PpH5msmQpn0zA3hMfkC+HwjXruH8GwwYqHez5N3n1+Ba+UjINO+Gebg9iXYYIEoVJlAh73JHMn33sObrzNhGMw42csAiyS1pwD93znIYOFB0mw1xmtjrWNHGOZmoo1WOSvqKhK26YJZqlBR8wQI/DlcjtpLSZBps6RgzTPiZPSdDtBDQG/BXmHZm3UrwfVNhGR7wVpo6YRFLqViX4stmFWxt+fJNBsEsArlX44km9sP3hJ6oYf1UjlRNbHDxOlBMpSDM1oWTTKzK53bK76dsDqcOnyBIPSk0DnbF6eGGYeEjgFBWbp7FdFx2i/8gib85aXLgcr2RlXR24aQFhpL1xNmAfw8peJ2fQMiG4FzX4qvHrZyMa406wRrrKlqkf8yRyNCqDiL0atixAlVbdBROCUOdL4Ap/SbFoPQSfePH+EHNtSVLmpeRgkvc+7Il7xdblCKyW5m5P42SGYsK86QAduVjQkvXf/BLiqrftZ0CC4X6WH+DgYFEfDxkCkeZYYG3LJutymO/eOzmeUJq3+Gpc+XOOj8aY+WdvKF0M8Yaz8VVgfhTXkRAnLcaYuDIzNoJOJ6qLeJkeDXQB4nnxWeeKcRNvAzcr8z1KCJkXtCIlmTfA1lpcc8VjKYevbO5WJ61OdkhiIsX7WOKlUXHxLnrjC3uLRVdqlDe5/TPi2L3jaqFND6+MwqjTuAeIbOo5ZKJwOI968RoYn1sMhyydFNWBOBBchmGi7CZptqxfgOJryUAaKoajfRjmflseRCUaHUNnfZv5Mop3wC5jNInwi9Fm6YBgxetM7nALO47JOrXanGBVJiDUaA6l3IupzHgMu42O4kgTlpSlpgCQH5S7kKLpIOmEtiQbjZB9jOJyCdkAfsL5RLX/wShLDAFTXXUGBwkhs8FcukIirSnfSsbQ2ck0rhaEA6ClZl2JZCDhnNgOCtXBH8/IHDDMOowyVeZ3ytZ7Mc6ZCSyX1qLubsUXEQkvy/1/NANkuAMsM6LkawCvjZ0Z7mRZ4IfFpVU4RrWtbMTYJmwaYkcNHNOVK/Lj8vIBnCXzYN7jzgvbgJeWm8xhg7BBCkeQxKIM1Ge1CzM5svdQj/g/TOA08sXQ/bn6j5wgYEbjuV7k8mhWOwERJjAQJ2v53LugfYepMIHbu/VV1BySJCbjD7oUM2eNocDBFXprgy5LQ0TZrrXi9ZLsm8iOaI8dZhwUOfCjJAbN7U/U6ES6/zV7ReH8xU3SMUkwOwTnAxdGFllQR8lcgUbtSZkgbRMdmS17vPzAfjiZtREKf19hSHc6UWvboi0/yxlGX/yERDIx0ZQEjHgYAG86IGmPcfrD9P7FBCJB2xtSEvORUxnZWjU0vwX2v9QAPN0QXVoNSsGo913Skis6shalXCazZMpMWjAjvLyVOCQaP+NHcYQq7gRNMXlXfMg20hM7pbYHFfA3+ACkKapk7yzIcTUihFPcUXWCAV57aax9CyOyLsdt33rC2Ez6nri9FAtfXJDPTf78Asnob8lVIk7RIX/35CO0Ar+FKpFjMpGXHUZ3rgiHMm88p9JVR7WY5GKeTFy8lTsaO+kUORrqgnrqYHQycy6rY+G3zsWsd7UFkpV1rAQZk7X/5yAWQDcYLLduxjHbwrb+CymXgEds2wyiNZ/eRVdKVLSpGeV3fOFlpsWEyfQd7f4/Mf7g0JcOip8v1kMWliTXwTpniDD5xeSa545qxy/ikjVho2bpjVx8AGWFXoc8ENh6naVxdPSA1zMyWdc1cn4TYXh2+9ZLW4mLfYukaTkhy/T18c1n2KRKWFcagnhvdT9t7IZFeteIUZqBOoZAgGDbp0PsM0tCMOVRTTVFJot/vOO45XO2PM/2uqbcA4A9x16IN1cXxJDfNyn6bzA/37JgzBv6YouS4WgOnrseEzEexv946fZvqbRg4RP1k0uhlLM2SvXQFTz68Eq4YVRoSKdU3kJ8gTeWohdXUiFSJ8vhmyKeUbLjdxKto0Vy6ASbiXQ/uRsIzYLzoPUfEeC+fUrqMpSEVt85D001TxHLpSEu9McPUZk2fMfdS3advZvHUzghDEvxqwq8VYjOu+xWQxEuPQsdygkZ0lki+d9uklRnxjSxMB57i4ZZTbOOJ0etUFw1WOj2zarufGBvs4sEk5U+uwO8k51uXpX7F9cWLG6jjbFrXVNYxl8sTWc4qbBYd+O9rs1ACYzQEf0kMiSfCn+UEngTmCdQU+PK7o5QURIhpxW9VSwENzkwD29EySZZxNYV8wNUyRPzwcmfjM8pLATYjYYTxW+IG/IWLGp7y/gUSw+pMDwdQSoJMOxFrU6E4APRUlIOTlkXe7y/NBi/Zqq0O6v2n5CKcIjKqtT4qY2651oCuVMc4InMASrxZchy7sOOSJD5KB+2sxGs+OZKbdEsxWYsnKde6MF9eVODzxJoFNQtOAy1Lrfo9wfUMt5IX0HWj7h/+pWh9EwXvyXh4HzvGL1sjjVJJfi09zq+hn9FNk1/21HNwl3IC+7NC7qi+AL7xcgkcsVwFJZzKvKo4/7/oB6mcZFvMqQQrYscyox/SqEoO0e/qHfUEJGk4ERiMyw/lQubFpE7E1uxxFaONvXAOgQwV2VrIDyK62kasudFhecj3IocmWljBx38ga2lIL+on31lkr5GD8T4Vf5LPYq4pXV4eNA/da9xA58ZI9ii0VAa0Am6/NeNM85UUVcdJZVoBmypX8OBCsOegyTbQf2dIuMnOXIbrme034bEoYIURfvvqCzcSHbW3hNGjfh8WFimOW+461St/CuVs0a1XGXvWYJkKYtrj1QxGZTwYaMBgvSS8Fz610o4QmkMa8hIDKxfoJCsfXO801fupxJ8PMjy/+76P7mOFFyDXbyXqnEdT/x6ln001EsDoHELcYfQyIZY6EHQSF1iKlObLeKSLotQoby8A2JzE6L6xoE//JaI+YmYaHQOX7nTWsXUyX1q8mIfh2S7lS/EwS7upvj9FxEumMgPLImJ3JJ4+95xz86zyQXQsG2JgXq6k1UXVkETvlISE4Naq6yKdfhReRmIZOkYE+C5b0EUs3jE9AqQQx47idXXTiMHx04vjTOWYxq3meQnALqz1zM4N2/XOsPh6ozgJSNGlfvLMHcinFEAkozM1bn2TYASZD5kGIbvRCYKmhBOs4gQ1E+nil+1OMzw5xbsySPi1XOi8N5EfVcNkqIhTFsz4nUYMAuZ1G/cAozwMlJCTJ0t1ialN2QmgaFCEHkDu7bw+Q/nxfVaR77FQSt3O7ksxkah5lJrsDfHj+nZmU87EGj/Y0bBCglZUzMPQE/3ntZ5aoorwBou5x8TVrULNyHGv/d5AFPOlg07LUOYwlPgE1P0fE4iM1lEQG699Bi2LbRlb/oP4iLDc0D6WLbgNQ7zN46qLb5lENvsr9YfRAiYqRBgcJvbiYpxPiW4GRzWGqVy1iK8+TwLZY4Jsqel5GwT3l6Ij0kyzeyqcFrHhJuvfqNMz4KqLRA42MhS2jw5D7xjgYBBjtEEJFU2mzTG/O/qYzGSP7Hi2r1eAavBdgVw8Jt5K3gWbGiLvaXeeuAXYoKZq5K8mA1amn1GqdxPWPYKuW6X3NB/PXGEReIcEU9E8D0s8uEzC3aTAQlTfEGDMUuNI9z+1fK+g8ANn6KQteTIssBMltA4t7xn1i7Zny/HGvZdPQLjcHfX6iHbdjJh9cW0DYnXRIRChoUh5j5hLedz7WO3DrG+MoRv7Y6MvzdnEvCi6tORLYrUtNgb22MAI1RhxMAeL1FccjScVTDnHRsMu11PFh1p0Fo14w+Kq0exbTtVFJZyDhpjKE1qvdGlq2eXCKp6IJ26+/bT8fprrc6P5l8MKbZZOh/yOQ3bi+LLK/Yq3sG8px3C+phjtZqm54tcuLJrFFDvAA1MHMcSz0UdoOHfnI3hJ3ic6ISWmYXwy+Ci3nST3zZtWIfwkobFLl5gTeh92GjHLN1meX4XhIR7iajnNj0yoIwR791oe4dKdfulpuZQy7JkQh2oYd6vsY7YtotYWd9X5ZldBNI9YlagiNMU1ibUJw6uwXXV6excxz0ysbE8sNwBAFiG7EvmMhTMHHLRJ3zm9duLAQ7QN/qSzLY7xmvwv4Jj1Hd1ZoPF7AneiC43zKBxPASCCcf8wTWN0qFNBJgLWOWR6lTrF51rTNI6miP2BcS3gpKFGvr5ksC7+X92U967nYvpC8pVUb+K/8bLkm2wDyAQAjYyMMyop2brSxonl6HtWX4Txz16JZ0g4panAppiH7vqQKZJe4+C8YIebHEROwwZqGaRyvqGOIAwK6ny8DI3UAqlAlA/kHL/10QqNTAe+qSqUYkJpMcnqSgDl6m/YlH2aXKOUvc9eG4XOtKntXrcAKLNR4Mes3XnsIc4z6F8R3lp/nNvpbLnB5ZAZ/RNFg9/RiIs+O3+Qx0zjRFfzpJ4fuxEzcjqBXekRGW+w2sMGT4QQxqVBhyR6HfNEfkUzYzYnZfIxUxFjOKNBvKmPEWHiFyN65NJW2TAVHpvzG/yItnCAQLoHdNTpLU+EUu3OjwL+wfE6Q+Ha0y0hsEwre/gqGEdxCyxxiSAZqHNmhG+5k0H4tpG43KfZQtD+yzr0W2Oo1ImsqfsrJ8vm73ngK/Fy9t1sN0/8ZdnRCRQ3aib7OB5JnFw/q5LnQDj+/DI7k6WNiZddGq+B8Nql6nbo3U4C3cdbMhOPIk/xF3LJV/odmxCMwFy95tcScU396829idv212uV//r81gqexaiWiy3nLhavbJ5a+wm0LjvVK9bT8gPW32mIerNJfE5iCSGvygDDHm6j0sSePDydYIPvQgEn12m21U2BMO+FRp41XEmmRYJ2a7Z5mkiFhDGNIazGE40RUujFqFR5syHxeW4LdoZ+LXBie+H/Sl49SvZJh4a6zGqKVR+JY28b6YPgkgCUkSd5/y2u8EDpOn9ThyCZcI9WlSfYywp6DRqrzEEDvjehRrlh8GFY3LIaaP5KNbZV/CRa7109Hlv2L1tSnKxyzKIAogWPDyv9/2EY9FnyY/EERA3Jnn8GZEoH1m8BvY9nawXc6BW48i5sdgHazYLvqzaMRmBVW7PQYbZvo7GSKmOe78ohpEBUvlqC6CQV3kVXJmfPXsMAWaLCoGgRXYrfS4xKrhZbbADZk2Q6WcxRhMKUj9wAzM8H39mcIRWW+W0j0ydaJ+B+o5bJcoXr4F1nfQFLELFwVw9/XteEZgGzNwy47ESuOCBNKe0EqhFr3VXB7viV7kf2b4mxOPr/T6gvPY01m5ao6r/jq2GuDIQpkdGpPh/VPEkreWhrwDG7WzATmTeuAYGz+qIRrdE6P5YySLz2BziMHmp2Z6GM9dYrzMMzBKSFTjJ1y9sg5V5GOaIhOpGfyFtOWP/jia4YD7/Qa4YBYOFgpU1YsHDLloCcMGokITjAt+M92epPh/qxNaMgLFWT1B5zz407qdpLH+CfbiAY/Lq5w92ZixxC5NadDk0oaGiux7I7UtEealqXfpS5YJyNrfQdiwXvSHERYIIdjaxbpDghF75HhX2rm+L1JmrYTeIwoFzcmfr8bJ7HnAi/VTgNyZZMByP1FA/6z4ktVKpLLpRRgGhHemFFyfm3XjBo0fC6HyunwfLRZCB467NGPKCq6MB8FBi2ZApW4ZcxxFWVnpeQKnGi/JsEGc1bCHnt82HA6YUsZrzjDtwHZv3rsH+hulYnaM8D8hAwWaanSWCrbzLDAllp2sdTlo81/feDlwFEVJ+fA6N4A/Msf3R2/sqgk5ZNREB1GR87yeoxXcAbODAX0vsjAoihhsoQ7HbJvVPn9PL6S502uCMUZZEPAC62ALDLdXI4ZqJYPjR2aFXJa060l6R6VfwWWvqx6vbX6e0CzDYXYPatMLbv7P4iKpxvRPDAJOMffOOzmCojwsfoo5EFfaQSbgQgol3WJ+LKvkVlmQ3/fzqY7yqhaAd5cEeG4Py+4OgLHo4hzi9gyT8bItcbYOc2AHWfb6qC8WzrmHeMoHFG/Lx9aIQy66fxQGjT9cWlo2I4vMt94Me3KWd6Y/+2VF3/E5TrAG9lVt7Vd/6B3ziax/pXh8RgmHuoM1yxv4l7qVT1NLhwza0Orm7KjQ9alZtNv28c9BLjcgUvQcxHl6q/ZPxoJlPFvoHv7Ga4rfQWWsDaj8j87UB0Yf4Wu6hT9B4gVX2yoSaLWRVD5eMw2wGn90PwCPMbLEtcO03isnPO+fjza2XpKOXj2z55bk0M+1hnBF5UG+uPQAxP0xrY8ERi96e397tfdgAWGKqF2DE/KJrjOhwBVoJgOMTEondtAjCmx+INr+Bjxn8PnP1Lk88BDq2iOir5i3GeVl4IJfUwC+wtCXgiAYaTRUUeezSDq2CmbYmF5f5ofkg26Pn0BVFUDPhgvtPeKbuZ7KgsuK24A0wIKaWwfL5ceQ8LbkAchk5T1VSD2Loo/KgFMqVoi2sS7UtEIBgebggjbkyEpFiVpVbOqmluBdpLdzVzKWBOkM6GFRXooKnG03WJ2ytxOD1zkCb5v34lL6TV3hNj0wQUvKqTukNuwNDpWNE+E1kNj5qhxlnkNcm8v9NRvFA7d6YGSDyaY5u9aiBnmYR/THhpwSn+nleHN7ZQ8alqtnWKpu9bngKDZkSBsheXomseaxMYuR9b+S+VPvD/RN59pe/yDWXMRkpbl50JQoKj70Hby1s4i/JSa7u8IJYw32q3ulWfVjrKNnKc3f4ukFu2vOj8y7RI4/tI6/gs9ioJkrVwYPugGNBPfsP4fRDhlgNSvbfzTmUN8dg7LNLSs24Di/rClQ2poHzoGf82uY9aPPgMxn11v8euBQk86HIq05PliK9wcMgx2ttpsK/y73WIL86bEVmY7IkcRmQzT0MNhinX2Sh6pibF0cwGOxST5VmiGw2WpSkCUVAdXEXw+i28+TdeBW3KJHvhFHZAku6axi4eq/N3JGsQxlg/TP5OPD62GmyvYhsL8Qk3gl7i1TtNXeVFLYx19nedD6pZ3saue7GGgi0gleSWxRobfdOpbm6hJ7ZyLsrwVjbkLjLGZjAr165tiutRGCVBcCKqmtrPiUoTDKRnsUBiBjDE/E/TF/kpoSuJKJVAaT5YgFSuF05dRytXrZm69zkTFrvifHW/1zMeX2Rp0hLzDnNn9brXjfqO8sr3sjmUbGq+Ask+uL5ICkmS9CZU+vA1tUXpIG+SysrJDBE4ptl5f8uDKjbr18K0OwdexEynps803W7UTXqEd7X0+kv9Rs9vQqu7FmnqItNtfYiDp2cP93hzb0IbkCzx3W+HWq7p8PObHvQ/5oBw93lmuqUJ+4TZ7hWdtWFgmQ6lCVK4mOQDTN+yY/c5EJTRlbFo/RSQLpvqfqvPeYZnc08Sv1sWw5/vUDzTGpkAeE+F1bpFSgEWlDghU99BMldf3tRTifPQmx1Z6tnROBySuSboKWdjePpr/avXjEdRcOLshi4XF6YWkmlvURbm093SCjXUVeo24Li804fsvWqs3E4uofzy+yDqcil1Qc8i1jyEgTjld9IRKo1MyyJzrsgC2IZZVEaP15ko7H2qB6WvEou5NvtE4cipgnGmywGlxnn2hVXIx3Iaw3KzsxtYVS4spePT0I63vtrMsZzfHqkFeyaVMsaG+J3K7Gh7uLp9iJFY6Pja9IdadvmSw0uU5bwgFU315oKOJPGdzNaKU/vCNoBSR/d/sg2W+Em7zWmSfPppQd4bXAPqm5L3spJ0l9dtI8SFcg4zBtckb7prFdh5KejzIzuhxy/pRkAS85E4dJfN/H3YOsH5Y4IOFGhl850RyLq2BjdiWY25p30rcLnKO8oYT3yaY77lLGa44K1tPUfNukHTF/UjyABl6mS0EZwsbwbsLhUG/Eg/e5lXl6/edKD0AMCRn2cL2SpcPb+ME1RGa3TnO63Hh5VMR099o4IIYe2QmFJQNDqFGVHkyabBjHsf5m9U51J+WwGmZ83KutkC6s+j8Q014oKWHXbtAA9Y8tgLTdg7NXXJbqsb6RySO26cRDVDZTZq1bjfMebs6HLSlLJsMmiSdeZ5wPoFcX1DY/geJIlYguRSXvtpYeGPUyTXjIvMGlvN2b/RIWqi5yJsu+nDo0nmgPBU63xjp7tB2HVBK/X1rFEALJ7h697eijEQPGog2gmSK5GD2mhdod6u6jZXGyR4NB0VhLcHMwNhwHd84EMeU8pwIAsBUEYQ5kxmzNl5cRfKVy7Am8BbuJ3MNO7/DnYHuSRqCI07QZhivlgGkimaHlH4CdEX9eOUpUzIA04OM4WuNoVQhw7+OVhetgWTXvVrB08+Xc5iGCs3CWxlJdSrAIYkt40Ytj0cjK+3cjtOrHTBPkOqQHWYrD0UCdCs2HguYAT33pKQsujptmrWD2qPM9U6bTjcOKOz/6xdZku8PDPGgT0ixtV5SO4/F9XRqHOFGvTGWGM5ukwpXcoP+yxTyum6hbnMV8V+uoTGmjSSy6rc5pB3r36l84SrUGhEUj8tvf3MpXJTL4gOP3uAyQTCPE3XMNspvBIol9GTIV9mFyXu6hQ/mKD+lCmANtxZeeJ8SjACV//DMmk9kr4bDuLu5fhpUFzNy+P4zDrEh6KFP+izyQPM3capbJorKFrm5hHGM9KEloiGuAqCul6cVlCFT0NX0smZ8RHkvPDJsWD8tQKldgAZ3rGMpMGwhLoY6NuPYwwwkWXk2Q6EKz33fElef9w09sp055pBovt/5OOk+hcqF6zXFxgvPnh8ZiexWqdtUknHeTMYI7PucYfKu10bZ/RjGn7WdJDpB45MNzSE8LNmZuQ+ONd/yZSOAf7YNOLcY9qdpMiMyZG1sAm+ywy9ZMvzKyL7qKvgr49pv08nUDcbcJZSH0BI3fAqvJUHN9TsnzDwqq+4EeORv3+jqnfgPMwPMkH9GxqHnkWC50hwIEaQNrISeGzMLSHE4ojkluBLignCkk+Hl13HOL93ZcKFE4SzcjqSsL0nPnk4bKgMkT2Y7iZ3XjIeIu/TXHM0NEhZan4w3Iv2NVzfTLtRypnZEl+EDkXklEIJUNcCxi3KkdMpUKc2MW/Z4pRnNRWMVE8tykifel4X3XbQfTOdTf4P96oSAJUX19XKp0EoJKFMhdoK/28XiYVM+dJYmXqvV3wr4BLwDAgxgUKS28c3LVmOQFGVKDdtEAOM75w+ML5B3gFlZFGmNq7oRvuMhvfb953iyuPutFGxZ8uJSGJF4KUW4kmIqPqgpkrR4jWBoHEPiYuyH7SHIN1wxeDUb9sxYBiQdi7oSlu7Qe2VO6I8CP6LD6dZAdq6GaTyHjtWbZgtsIss96J3sqo5k1lJDhWWnBDwllzEq1BjapmtDli/PHVVYxCHiAmCn2sLdUTM22rF0C3VPsnCunQFmm+Ty4zEzCZ4simf4hRTl2tc3WjKcZzI3QlPqBmLpGp+nv5FuNuEsBoAiuo3TzF6Z8relW7bNGneDr+byKbXGc3Pxj5TGxPTh1fKHf/y1ryxNRbFOlQmFEvTRu9IP/EWKL044Asv5yrfUjrOMT2YWWnnlPWf3XYRC4HPbZymaFDJMGJZGRhg3b9Z+SE9CI2JV/Wq7BG3kZt9eU3r4mh64OdflV9mL/mcfjFQvS0Iz/337J52Vm6DnO5CKS21Py9kxyUilUFZPa/xdsbD3nrMHOHESgnY7cxVvVbx3MyOQhqODWRtfJ+9R3I9y8BehLcZUFnOSJ/pYBb49cnzUVRybS86OD0iTFLnyR2sJhGP/aPQ2GNFeKrYijJFOuITvj7UKDhq82VStK6b78mgMh76DowmlBmiEw9blOSnFbiJ0NakyLGu/gz4OFAb+T0KucBzp2RtldY13oFyKZbAChzz1OVcgT2ty2tiINvoyLYtJZQLjZZOtQPk/7RuhrlZrtNJ1C02QQ5DIqL3WeM2ewNYpXNQKX5xXohy/coDqxeE+so7/KteLgGzOphXkQBUcWf9OVGt5Ntpv/kGHpdjxQpu0HwQgNPRwWzYXsnhbZpF7EyohW1hiEEPGJqiAnrbZOx1ipYIeSX65ZWkbLUI8RnlEUtQyIOhmjAW4WbS//oRA/Z2xMf04BbjqyrEJ6VMA777ng/FpmEQt585gCwO9eKZ3IOw47rMHKXWFpRzbtmBixrwMZ8F6PRxv1+uPeVZmJe6G8ZO4VZAdxW7Pfp5St2l+dQaZDgrAIQR4UW+r0+6cBLyA2TzTI+R2l07E4Ib/8TwY4bpOZfS9GCi9AWDo4fKdlIj2qXr8jQlh85dl+3CpJMVtLmdu1OMkspJIFWDo2NLvkIKN0Rm2v8O9Y/fBYEdHCQ9taSUJbRQjfZy6u/9YLgN4X62tPuL6PKUBlNELFN6bFgOoUISQKwcxMYSM/Si17wrA6KUmBnwMFvWFxfc40kI0Gef1Fwo7tKwKC1BWUkkN6GDuHIWW9LvGDQLoZERauJHnuIKkL9rxH6s6KMNUnWTkagQHm/nhGb7oqY3Kw8v667tvYrAelPPOkj0tKLYLB39HchV1gXstvHTVb12Bccn6SshboFqDPfNmCNN5NtW7QQymwqxVQZqHNMOkfU/2fgm5NUpqhPfVfACumRugCt17oArfB/KYdvDZFE6paB/WJyEzqZeVgQqfi9s6l9X7EXXXQQwGKnEodM24T3OmVIFnV+HZFneHO/2i/LfxE+nfRS5Oui0r5ZjmKG6XOz0ghvumYlowPa4ez8aRWAaVIE0mLKqXdvGOqfrQEHRL4NeCp9ZRdJgj4LOtVAamvLSmcPckQy/zs0ljsgSchzJBcsonfx46GgUWwrcxgI/+TPR0JDL85zDcbiKcE7ijHqEogSuAKO5nvjYWqtjsWUCT1c3/ektNxoVbbvnyNIltKJj2dL2MU5mYgDq+boU9uLhsdsWLMVQpdqWVMKf8M/hQIgyZ+6teVt9OCayv6eeqUH3dDuKC4eFGmcA3NZcPJi+/2TUFbhsvMckEm+oukMmm+UeNHEPjLnocVAzPH+nMA6O+NWvZEuWSDhhfkzYTefqqsVWclsN3oBW/F4oSocVKxCXEhJ+ms/X1VhBeamb5qGtQ7ddP8PJp2a77uXDZ+wWdMz0lqsIVxt216Kkzlr2SbeY8tlEgnUxGETen7qHdLQF1B1A/eVK65dAJLv54tf5TzWslL+jKJfX+RrPWfVod/RS09RjewLBRYYfN0lGx+SEhsnFGniAqPZ8lKkRL9VXJNx7EEJrJrsU5F/inq9bzO4YkmVZ8ZaVYrokaF7oPtukSdU9MRPk0NxkctgHS9eiVXv7K6OseORjAAxtnMYqMGV4bUYFOChKWHqZSjz2gLv5A/iLTUsQAD5R8jwxcpZoGKP5ozwMxpxJphizyzuPCjKJGGJD9k0Yxea9jQpjlb79o0EuswoPOTVsuPzIaMzpFx+vJL6dn5GDsgoHg2vwkuLACkAfSYwmVhjgvoQdmd4Xpp+P+LQ7FZZmMuszqaBr/GQzPWiNsFAB20M+BxqjRhARBI8I8C/2SOm7QT+6/xFltio87dTVSPQCmjyrd/h5Sp3/yRMfTzAARBDorHAewokhdQ7EKwt8+P7pgtvluZYGMDgKlBxUTsa9o1Rnr6DNKOHP2FGm1oKOKF3jgaq9CmAfF7pa17ax2RAoYPyPSnwGxtxBzH4gKBNVTI1SF0JqdkP5Re5BzGkMtlJL6NO67JSumMZzVly3iJYFNnMY34iPlGRKUzwau9yNCKDxkNQPmFBUKPWt1zLiYCyr+LJI5UAU384zVASG+RCwI9C/6EG2zN+bSFJ6eh+N2S1x2YxRNpouk3gtu/e2Sdij0IDHuQbnDSTwEQWSbtcNkUzJ/BEow9P1r37413JcUgCH9amFXeIX3IlU7ilHY//CBtf7vrcYtJ0R4IQq+XKdqVuR2D9r8fWYbS7CUwSloj0CAvKAybEsRufQOnG5wpPsQYyVGrAbsUFZih/5nlMQFrMxmg0b+ajGUVoBSuJgOgyYm9ycyjY2lIh+gC8O23PsN/GdqruHZTaPjuLu3AwaRSamuueQ1wkTunZo/yaIFFgOPTG0kmpSoLXg5gRZL85kQY2TvPBMccr2QZmwhOfXC4t4/Q474vz5UbK0eCHG/pjR8Trd5gFFkTnHTJYTuvHyjl2fCeFY3YxHulf5FAZHF48i38xS6mLYGGsSwDkAZa5dmzB7VeW+vDFNPZr3DF+ppG58LskdaiDlIanTl8Z730FazdnmxeQwzEJb5EVjn1UcJ8HGknn6AeamHHbRPA8hrv0Y9ZJbwZiect/L26tZ9fGcrA44rCEv5EALFS0JQCCw6ur7yhFWGZRX11V5JrwiR8q1re0AlsN2BTII8pLEOwc65niOtLI8My25YF+0U7TwnK1qu8/+M9R8pffyIOy/CHRYFtTw/GhHy9P3hh5RWI+F4LV7daVgBOBuGBRzFgG/PDYH52lxlCAnqGg1+Gj10gt2bPoxPPvI7NS95XzU1yyXx+Ual+crO5GknTmbLtist2yueOOevQHYAC57Dy8AgKAhyXAr2iojBcJyRHpMCz1xOJZ1/dfI/uDEr47hLKQbza5BghnSNXSXmMNqOIqVdH9j+XgHlC0jRaHWw2fVa+mL1b1T3EyuvlR32YQtHI44AlGYxwm5+U7o6vkql/wlA1Qas4Mzz/3oda2Q5PIZNanQ2Cl2Cadtk+CxsZidr+rZxlA2kBzTXZFHuyduvPzAKwG660bk6oPeXXvGfFy//qUlx9ILnq1pzapA/1wbu9luYebQ2VbiOM9lbE54PQRo6oE7UeG17Ic8E03cozkdo9m7XZeDRD6PYDh3eb+WfT2y23RoHBgbtedyzv3+b7z1LdSbnE+9+nkEe0BNIa5saKpyCXzmCu9xVT66uNUFrfOGQW5KuIer1HJtVsv8JASHE86Rtphjg/Gn9ZRilUGeB7C78Mf2oT4EL9+t8ME89RLX6KzNb4d0Qf6iwmeIoqXjHYTKqrhuGq0IKKsON7cREb0LBmnRdrn8bbvRvvYsAvEKD2PrL407GBpT81pauQ3a5PzEv13o7fTGKlpU8mfsHKk29WBmDjR4gocpHb/+VUjxpa/3Ia2/cE5UbrMlSVa4Sea7xBUNBbToXNixj9M9gp5d0WZwgyEz4bX3ZArCMtemBT77q0wf9O6Y1kF0ZgVn049XZwKEQlkgqDJmr2BuTcA5TZcqtVW8Ytql0Szo4gMystbT1Gk4WlSSB/tO63OdVnBnXFHMGw/9CdHdhyyDojFi6iflkDn0bpzVnkHpEqS7mmi8aRcH+9PmoxvdAEGeSYBlvpOcrDgO3qWpMkQlsXHGxyNPkCIPdhcJDJc3PATHZ1Sgz78Bp39o9bfpuE08097f9UEVqxpIjA5EAXLWPm2fefpxrmoms2bGcpvZ/eqYWB5/JE2SHP6dYwjp47i3EXCtu7CkZKo9mszdITAKUYNYObDxVNfHzdu4umvMbB88BEy/JSdiElTF7WrbpuJGUNGewcULK0XyLdEwQ2Mbh6b7+BTtOVjVj60JjxWryvnvCtAEBGnz/v3q2FizOyau232hinJxnh+s+tnRJbiJKgOVweW6EVNFUe0xBXaHc35xD1HGkMpJozNXUrIICqnepvqqqG9wgPrE2Ik7vk0zy6RL7tiINl7ZJu86wLbeMTIcS6AOrKy2D8nHJV9WkxYIWhVTz6LklddPuXMGdsC5xNv+mOpSd0cQkY3OyC/dqNk92KQ+ANd5kb1yP+lRTqlHcN4GNL0AO/KCBNEGF8DU15fkFgVxhHfyNhAAxvhvB+FDDNK0yDtAmyDjFsv/Dg6lvc23FACBz/ZjHuQz3821daqO10qSCjF6ePCaN7GtYigxAqjUnkkam+Xhgh2zQbbqR1M2RqcQb/R/0NajmJq+7YQx9dEyEgwbvr7SvPX8WJY7EazVeYuwJKuWJKPXTKuLKSUUNQfXGalhUgZ1GF58Ga5pFENi7O9cBkTUGnH4K/4XDh3fNSPbl373peaU8NH7qkXQVVIYBiFXdWu7BYj48ivfQlj+frVkoPzATodoa+kqeihV5LBLHMoAXuBNAWJiBV1QRgfO2TTrLkrsWNLM2dD7un/6gGGYJ64Smo9oXzlB9qWUIIU3tb3WfquyR5u2zS2Ga5ebRG6H8fb1Cr0mUtw/yQeowVNUNSOvn5JM33o5oiS2wmS7Vo7uZ+ql30qQwWI7zHAd20kAKaudk7R1uV3BYIKqoSVS9bfApLlv1Gn7QJWZpRQB6nkrPC/cmfs13sgbrM+PotMbiXh2f0o/IUwh7lwJIQKL+dwjpkiLHF0eEDmrUvxLOxtO7/8CtGvsT7OKDyVUBfj0UqNhzThlb+/VauLu8eTHEaX7jfwOv73AVm0c1u2rqdZNdUrx4Ay4t5tEP6G2ByDoudTaJjCiAslFoyg7YjP8/n1XHDhfAMGlVfLF+/v71TIJRHM4nqUcyhp6JTk7XRYfGS7jU2rsBsxFBLXFM3Pk58ZSy3/YMhyVBCFaMnmVycSiMZWR0Pzy6ltPFTrAPWorMEu/aepaulZveG1n3wX9zD3qVTMb872KeNEd5TgpZLmJF3WQZ2IT+q78ItVaJjzZD3hMGmnLSlxwYDOjkps4XXwOgR870w3R6NCdqBqFzP40phqg72l7R3jQneOJxTRbH4JZn1/yCQBqSqoyAbxPW2/ivq8XW1SLV9ODmQZ3/2V9AEsHQ4jHXiNQwZeRw7ZJPRdJuVk9Njb5PYERRY6oy3ZSDZEXrBaTz0zbysc6hCKmVbmFqxgmUBbDGzGmbYTaz6FMwc/MayA6trx4aQ0TNbQMNZTmWTEB8SlYv54yxc577UKwB5b64ZxglyoL3/g3GoZh1UpcCKF/lJkawuEyORHoJFh7vx8bkgD0/qXaFt8bzlDfsPSG7iDNarNh04OVqhKDHpulJYAws+tqrPbEfv312DNeH90LrLzdianGQfh/6h+hHOvc/CMBr4sbZCsMKoLaj8d/tUK3I1707F/lU2DNKRk58jmJQzUHVbD5rIqDJO6e38eWowAr01v8v4Q9DBgaTYjdsue2DRoAXKxdbMIhQo/B6PK9n6ftAsiKSPe/LnWFNgej5hgoF/yYZAxc/stILF0ZM2y/zGnMH8oITljN8A8FtAP+o8Eu5ZdgTdBE5knINa0fUhNXnPtgC0RLzdrMb/qkcU6jPr3nhLRbko8jcjqQukhElYkc/Gjj55Odm2TGAEV+NMtoE9UKVjY8Z47hqYQzt5srBxrHy9wSazXeqDYaLkKhIiRr9laUY1TwVEnKQ0quiADUvwYW16Z7bv540fGuNzIyi/yLy7bS/H+hkmmH3MPFz4eHuFf4N7IEG1mz96J1Rxfp2PWVfk2NUCtJgHtmAvo9550rPsQnESkiwsxuoK7o6maHylu9bvGrFdkvjsk3kjs8zjRokX+Ww8Vu+zhWFD6gouaZ9iIv5gw55ZUXBZm+2tuyKGJWJvrD2qzkApFEXqT9JnEDqNKjqjFTRDxz9MIkV5RBt/HG7FW+SUerprrpEcOOKeWD95E6Vmw6HtlAJLF/CmN5L6NPXHfilze52Nr7y6j/jqlgQOd776SZi5eVdUEL5cnc+DRtCTiPdb6Clia0L4j+TL3vzujM/tAe0MU9jHS4KzdcjzxgTD5CMer7bIDsN3T+ZmHREDM8LNsx/4TucUkvO9nyHkjC8BZ3uWXUfhZOwdbJV8MYiNFVo3pJozAVJS+L/UKmvoZ7HubDQkjLnU7YXX7F4uNX9VXdImdNHJCf9nvQ4crWNUPqY7n/6vWqP/TGzeRpcf3rwRuXXslaBNmNsUbOmwIRbJ33g94gyJIgfAWYKwdZLMTFH0wWzaK+dNxJNwvrN5/S+qcyzH/tJ+4/Iy5Y/vmrXMpaeVcy9BWuC9pAyxa7bx+GN9TLlxJkUrKhwLfX9i1HusQP000GtVYbBRQE8c3DXbWyfq2fIcjFTqzNFnwMiWRVute55qdJ0xX5CJSuGHy4wFgX3k8YXhyAkHqUO2Ofm2sHfeX+GCLbKzPPMQrCebiUk4di/zRdylkyYR/jlSHuFYGLdCISVDSgtiIs7+LqB9qf+YHxZLOuLb8HQEOHZqP4JfUfM7u0RS26f3y67aatGE2YqRw2nnsn+QMvxfNdIkZzEFh3Xp81viVsjJWeXafNB7tRObJOCLBwrK/aSXi1I5iD99swDn0xwbzqvXwDa1qaBJZol+EvIvptARGxyGKq3cGK6go+yG1ny7Y8SeUdGfVct/mH/vH9tPk+wBMIr3+PZPBlcTHlszVCBrM9OB+w7aH4TJz/Kot3NQHZW2FqU1uAJD91vrFCWaEOIcWs9ZMc4kDmqESveTOcaQEuLzMYopsR7Kc7zEBKuaOXIHw3CCJ9xBbr2DR+FZRvt1qXC92m0CHerpC7zzjZgq61QtE95fDg5s40ox2+zElbjrW9BP2msCklihyENHs/3ExuldW0dPKz9KTKDnfBv8iTFEv5TerSjnAVgRJWOwMhNoKyFCrul5uAGzd1oQfw4l3syI3LXwkQZrJ9LQvjpYEhxPPlKjB05JpA8cRgm6X4b2xoy3wqdyl8qsi2zUpgP+1EKZDpb2WwPaiZW5ppTUu5OyYGEENDnQsC0DOoxnTqGLjMfHtLPe/QboAITYNyRfatlf1IfjI41g/WdsxeOdnbeaJOrPHAZ/FLGG0vbBSb85gNQoSAqDgd9cY8ZqTseOgii6v80df/0pqez/ziDAMRutE0wxUr2IGCNGAALnHbdoLHI8lrAGK7V/rFFw3Z3hKvasBK5Fbh/ajWJDmdqaXBIaya5Xg6OugZyso25ZJJeD5IG1SBlwiegq5z2OVveiEOvIi3s3aqPeNUqcvzZLmdlSLqZeUcTAKuTbW5OLv3x42RA4HidWE/Oy0DnOAVfRsNC1E1IzDYKNtoW/J3hIgW9DVNIsn+pEkBBCZinCoef3p4r2lAsaPHGC3qqeUmbo8pMkUgca6iy1DLzAcGxpP9imQsEgmxpb3OZYhyeidwOr7AjPZ5GqqHb/3LmosWiJNSO80IzTdM3qzzjrq6ayAuMOXPSSHzlatoa3qo00ZcfYMd6WdfAyJl04+oCh8tFQnAiJqOl2z/12q/SSl+DzWeAjrw0BwHgn7Y7PHMlL1Lulljm2h71tzeVKtHEvaCmvX9pkkEnZjzMRWu4VvaPph2twBrvaHAi4TOmQXoPnAGr8LlMg47ECC1JHKAGrn2DqJHt8L3YwnEGNlYDRbJHdIBXuCr0HOP5pWVG7bRhm6K0nalu78zis/k/oXUxPfSBzkQi8A4/VjGo7YMfNxHPGG3VH1tzWc1kxZKRDgNBQKpsTGR0Td7CIVJxKVxtG6qm4zMOz+mwJEJG3bnJFfk4hlO5ASReyiOERh/806IVfT9F83m1saWyEgEa1VeQgvMPEsUjUFCXRSA32GYP73shjaXEWK8ytOixU53zPwhQs+3AQYxStn07p7fdWFK85aiFS9NxXiuSgtU4s/TbZZkROb5/DHYmwN5dF8a4TbPzNH0gVhpTgSOW/PL40IqOIJTNCNc06qkrdGp2IFOW3bOXKM0ZsPt7CpFyQAVC81HI33Vc4+eizp8+uG6E10FvR3PNQx9eMrQkiVXVqEv57LSPNXAtA0fwF7XZF0au3Jcuq9sFxL0GVZvdeKDJ3t0SQgep5KpS5J2r92eprKmXcoBsMba0gn4cnsRB+sr9jZi17mKDW6WhjK7GOQjJwe7kpYKRMSswdVUxIOJMRGc8vpFg9j/heKr/9P4T6Mxmgq10uGrfmKYGR7ldJ5RYBw8gEIVfxDGiqSnoeMTp3CtESzNyxKbhVLDrnujqW7ylyK0Nd/BHu2dCU9N9U7cJb5g6vFiIexOpbeHWZKz3UhJcTaq2ktBY0Bpwv18DBjk9oPDurCVDF3z1atQx6417qT+XEimQd9OcvFvwfpPMXJD2taAGRCLv41zMb73RJ4yb4tKgzWmG29/1jAjXvlJLFdbPaLKh8tWLvuGN5AyclCIzhqP34G4PJo04p/ROGsZO3EFUX7zGOUN7148LImdZc3k+Ynqt/7aQlqmkm1iVyO+IystinQXN0AYiJ113XTMsW3IGhwE56AyFohIfZ/yWKrqNrdtUQXlnU9/LQtYXqcA6rMuMWFFvOA7h0FIIT58BCG+Xc6EvZ2WWulOwFqr5NB6NFx6c3mV6+7E5erR5EdCwOMHpT0h046k/OnpSIF8H1krrytee+v/KN+uixUE795BSf8cjemq98IEs6aVzk+stiYC3lkMsGxJ13y9ZowS1N0LlqclWkUj2MIqnsyAhBNWuRRuTrY8kjmTUPeRROZV6D+F/Bq5KQNKCrLc4VfLcpQh70Non5dvjW+o96Cj909PUKRc9+f9oXWvfdakue9MuSeeyzRQqYp3JH8IgxUAUPBBrFCPECsmhq8gWQtMkX2TqQQXOO0nYZLB+Z181IeFfOJs/IQ0fib8peGPij1iRGLB8UpeZdA2o4bLLaZ4eKrGl2Nh5+3hYFLJGWx94tiECmuO4Wp01isFTRM5UgY/G6Ajn/TP7SNvzVqWIX+5dnW2wRxIWH2JtiBEPVaIE5YRkuns+tA/tOnaJAM4rw5I4p0qYqSYQsIVe0BFd5CCOR2DK+A/j/l/NRaFACCIziQSe6911TY+MvPCI6sQqep2Vegh+23QVLMEc8lZ9YOS49pNbEUE7dSV4Ukkzs09q17gRfZcOmr7T53Vfwm7iNNLe6vo1N18PnMV2Zf3G71twQY4hrqe636TXeX/ylWLeJg3IkNv3/gVJqwki7nzouTDwo8sy4WSBy+Z0eBFkF02XaHhipd8ARuC/anXipWQgCpQ6iCXLqf1hclV5J/DHiahZtJChz/xDrSfydpPn0rs1TMXkCEJ5wgOw2eY8iIajVSOFzJ5YD/C2TjuXxLjCIb7d3DgOuoK1pU3ZWM9HvGMpFsXHEzIVpkCBMa+gGCBeDoHEY+7aMX/OO50TexSCEgVZ5l+4wVroc0ANfurncyGhbNGaJKdlASxz/o7R7DOKMYiBUVpgH1wk3f5OwSLB2Ml+CqJJppV0EsoUbFfzNC9t8OCAUVqhDwLN/oLOXmQD07EacVo1f3S66mVnBoW1bUHlt/nTX6jbrnEZHD4yRUsdO/vCvteYaodrUTKH1L3whz8OafhxzjSIVnLrtsdXCTMB6JuXpgpWsxS1QJmpuaDPQkgcuSGDFEds2ZJMUjl/yxlzOeuJIUTd9k9QnlUv37fmGyP8Jbf6bJAe+YhGSmktaToGLdTWXhTac5Rxrqr0nAvEsKOOgDXydGP1psbNgsmhyZI6KovC8DtXYhKJicl7pMeT2fU+naaorzIE+3N/stGzY39HaOWl81VdgGcZrNXFsm3P1SSwoL6HAMrwBOocmVkfZC4TaWjOSY0/LmQbPiQQ85qJE0ioAClgKb0OuuGatoBp96qaSxt3rouuGkk9Adg8K/t4SSm07F6lUj1vy/2NK98lH0hce5W/tgQ72zcr+BJbaaA+nSTUHJRZ6ePfwvChEDGr3eZ1toey9GooewAJYJ+RoFb32lJxrnTFp001blqdU6uZWnQTBfn2ztXPfEJ9yVCQil4DfCX2OUhRorVC1jkwOvpeMsRgkzJ+X18+P+AYbdwqobfO0Ylyd5NwdFXFg+zZYUxdyUeXfVb3i86+KdGhaZGYSvZpmf6hP4jaDSQ9+AYAzLs/eimA8UywdnEWG+ekqnuFG18QEZPEOt/h2mRSmh+yu0chtt5oBA1kMyQX8kqknT8+0sm3vRovGI6dAoAXtCH41N8AIZ8Gnv7jhbZHf3YkL6ZeBLUb/XJrT9azCEkL2FXFvaEm7xt5iEjjlDiqhzKwlT63HSEVrHdHNZR+STu04kL2do3BzVtirj9uHGlF7okbeoucQCCqBHQeKdT8/KwLCnqIN/4wwz1XAAvIPvd+RLuvGhOy81PQudr3v2TeieGa0vCx1W5kn3mAMX/p46rf2Om1n8JENaplQyFq2R+D6mFD2uCQ8SlWmqEScGF8ONFJU6OG+n1kpy99esgQZvrwA3WIfGbjLITFznZkN669JKAKnO/Xfgqx/7Nw8aascEAB87F5qAeAr5iyp+keTr7+3rdHESTuKHaeT5U1XJLJj/wr9vRo3UQ0jbNZEcpnUPQ3tEuJL9GJPYKetyGdhPw2G2f8jA7/hbS5B6ss9F7tSfF4iHCDWOBXjj9MBp5GkZ0tpYYCxXZgLo+Y9kilq0JfSpl5WiOWXnFSxVHvP2kzDUhaf87sqqS7kqYZMdyhqD2C0ApoeqiQ3qypPFOQJrae0Oee8dfOxu56fP6tlHMtyi2m8JSFuDs4ERMxk3ulLUhc7m+mF/KwlQSRfL+6GkuPsWLTgszgsWcxZytWof2xAz013TqfPApn5ds5PS410OAN4rQSK6d4nbt4D0tjOMv2+60gORoTDHIBpxyt5lsLc44SjBBvZyQIBlzYA7BAPmVyEZX+ioIcidljPzJZwvP7nQVIKtSzxYsVHrTxssBQbawWdbgya+2vvna2fB29vXdWVywN5JIQqwo0XI+uMgX5v2NoEhNRYfy5vLip6nnlrpkomIIa4kaIJp69nzT76h/bSYRr3Ey8bRFWB+dTcUmho/R3S0ZM0Ehhp2AdNdaTa9KCxO4FpTK0TGvH5JFAMwx1YNwVT6Itw2aZ/XxxyQ8G5M2xnQlsfyZ1hvxVCWTGCdUT9/7kjR8sFZoFkbu8a/iof4K4exJUvYblAMZX4vEeR5TYf1xYKYNUptRgBuCYatzDnUlxyviUSl21aA951GROlIzU3mQgvYE8R2tQtP3GUBl+2+tCMFtxT0dIa9zk01fSAunwPZ3mhfl3fRjP6j+eL6ocraOHc9neYf41XT6CcqpX/RjXJ11UKarF8lPaZoB1dqDr7fWqhhT/J0joDkF8JdQB0Z2lAkf786UAGgWueXNCHRsWXTnQj7yGji+Es5G5MyMCJpTMX7wMvHa1rVps9pvW3WS+UjLhrqVCGJ6w1ByVnNicFLvGPH4VYzQcRzSr4gdsMD9jRbZxoaPyS0TCEjMs53iMBf1fr9OSzveErmYZexQYWi7gxFrBNJqua3VWNyjbcahOh38cFk82ftID+rRFMJ6kr7MBBZs/rgMFl4jmXFwMxs0LRTo1lFAT7I8LBR5/HqZs6X1MbVkIWTIodQyFHRw7bNaC+LIT76pFw5jBckAGikWEdnflVPHurbtN/TeGGaZdBr6uDnZFO8ubyWOfjzwV9fOZ5BgkmdeALgzlvRpgwELR6FaoLw1maUWvKPGJBxwupw6RWwMBBP1h/d+Gd0nPi4ykSaBTJnTJCdTVse+OeXzQksKETr8e+l1mWsz5L+uOnNAle7gw9jBERGNPMgJ6fD7Z5/QoJAA7P3z6CS3upUBwFX2YFLQKIsgixEAQ5X8rAJXXZDFd5wMCNnInXHVCcQHC3qDkjAe2KeICj2WSR+5v1f2SgJtf4rK/MWbgm/3GNohEzP7gqcbNBrpcEeKwfYKaOQhrTLkzxUdLhEYAHTBO/+sMJu2TdqlhdD56zjO68hQjNoz1bGa1DVhYMHBR1Qzr7arf6kE+dfsX6NGbC8e9ZLsh6zizdx/YQCEVRzJ63UCT6eBkGwQdXPNFsPpfIPIvj3UChm6T5lQ6rDfmntl+xZJ9ejAPAQsldxxCDJbkCCJIGjdVAz8+oX21/5crk/z99ft9W9DIsmeRqiPTSfHyYnrS4tbldTI1WXx7oGinaK+oMopvfLXDauOnOnL5EvhgBo6wmmiLa8jE+4IlAgfcap/IFgnP0iCfRwXKEKQg86kS+saprYCxyN8o4R4AIn42Q5SWqqdKaj7gyfMWs21DWvSrMGwSNM+LquSppidnxch6dHItVXBF+LNcYLISqJXt7y0WHzJVE8Den9sdVf8IXtp82gLEY+gJByUTeCZQrnaUZps7t93G+Yce9bscO1Iv2mXWRB5grqnsZ6kQppbwxpAAeEPV9iGnhdJG3IcvjvgtP/chB4oAJ+uttePjSWwPGTQC/lYa8lcqZGJIQZsVZMMNjmQAgyrZt0bK7yi3Ydfp8BJmQnax1YH0nJFt/niN5lSEF+rT89pJYixVfcw9ZtpERpgSSB9uQkiH0RQOC+Qv8uOJCDvbEigxBpMQU+qgfNDij+J2iN3tvz6PVuc6+no0FdLVrVmIjf+2GMsPBgppBk6KIsQYweRjq7Q+X64QsIPu2aQBC2BSe+j+7RNR7gSxPSgv2T5Dz3m46t2FnOH+hcfnjM3WqeBII7szpugECIBLPJX0mk3cGKhVuac/+nTIPOERbNBL88kVKW6lZEAR/DtkWOh8H9kXg6nl4by7KyAMvVCl6QjWCKGbcgKCBOYljTgUoPujR9ifZsBBNyC6clM9XqP1LU1aBG/OjePuR6HIEA0E7eLX680wslPaKE1L4hcIUVIbqlpg0CR1vSGTb6Ca5XdKTASmKru6bSzha417IqhOsF2cWvcGRlge10iPgn72kecHj3YGocjkSLS0rnovHvJ7KqyGlJAU1SVEfVcHFCENATUbDMP8Xa0vRUVtN80eXSJ4vJPUW9PJ7eqOLHCHMIUyj0wWaGHdJh+72jdyl+hsJrHxxs1LW8g9e8F5k45RuQTrM3/+8vbmcyUwKXeiBdgA6FZXLW+9Qbd3cMWUsf3/JIlNRUlGr+//eJVsQ6z3FVJDv9aASaO/8Ej7s2TFTBLlYnw1lMy/Lo+atLAr989bSRt1zTOXRxD0xtFacTghFr2lCgGKLBsGWu4mVOHE4vgaElNK+hZbT/RkZdQleByNCrLE67UtSW3ImqufLA8cdR3296DB9Zlw7SVGollIgBgCdV/SykYFD+LfiXTgLR4G/fvGb47Lso1JSnjLpERTu26s36WSipbZqGixc+7QJVs7p43V22cr9XdddrrZw2DjkfENiW/NdRDUNhSNKcmzY3qo0Il9BPIxE8WFrpTSD5g9qM/gVCfj7cMLk3PIFsQdseclRAVk/l53/5GrsHxzh84hpIdsJlCMUtuVXnuSC2hg0Io6F+f2HZhRDMXuk1Ho8txKJvSilgfUk3iZS9tVWjDr3UwUHpHDM6rB3zfRDUI/dhZay73Vw4ayOhtqs70YnJfhDCDTPv8yUVwUF46aw02axrRLuRJNsC9/cIv5a5xT570DcWmqmsvMF0Y26ijmixBajOU3/7aLDDNgf0Zm4P2HcHi2PGgGlsP5eXmQ+cs87XhlIFYZ5JbzasDI4Rml9giFOPd8R/mWyP4hsQbQQR87EpEQlC3k5pH7UO+Xr73Q5G/JnTDK5YWg99iq1RQYw+OTv7T0sZMlcn3SlJ5qY0l7HpU5QkhtWfleTisRB1eTBGIhKnTk3Bvh25JYlzde7NEpgUrt/HI/GTt+Wz1RG3QwapCJv7qn86kK1moiNg5ZlPZ8zukkV8H419J6yvVWau5v9uBaZBrOA1esGlzhpPoPzJMtjqw9+sihfroZYJ0RonGQZdpF+ZjzKsBhB+rCn2WQbN8wU9QWKh63xcjGLXQ9tPcecW+Wzehc3CRJxLESPcsN5Zkzq59mLtA7J2zJfDFK1lZxYateaJbq9s7C9/9NQfzs0etNarstF6YB5nqpuZbnWbwpWKLJJOCnHlPNgiAhEcGrgPDWIlqIJxxrMs2VM9G8zVsF5DCQKR0iEeONot/fqydrS5qOrFmRi5lFNWZTNCTEZDZxvORr0nPWyta8+pSlXYV0FUuqqgKW7cyUIkNhdC9/Z240PX+dEpRqori/mqIPsoP4GXuBHbDA5jyMehsdiAgD0aIPDlnqxr7kIctyvN4hWh2NfNEafLDDR3IjiAeBMvAFs7xCb5bm8iLTNbzhRQBQ/6Xmbfyxt6RAnnmkQsgGHYJ9s1xR5973Q/hBLVNU49muXxfV6zbISNcoxiY8W9a8Qigc5KSc4ZdvdMlwv6PDb7NHr8pftYdha2+Rm+64UlzaFwgFlFYyLR9ldZBfEmXrqF1ZaokW4ygEVzL43pvycSquay0xCa5hGZ+nFC3o7cpIO4NpS8fRwB4ftBGJQCLfztsGFP4YJy6NeijKrCvabR/1/+RrjGzLf/7Xb9ou3y9EV/W3exagWrbbLA0KpIIHGTOFUOrHuXXd3U4r8p+EX1sCP4mgT0dwbLnI3zKZ/aXh1GGvdnCDFAnLJ/mQzqBeYXJAUCCvuG63iJkLQxS/aZ82jUSHxh2sBUoxL/KttEqV5t9w5CZGcc8ggFmuVxrwrv6M7qSFQKNcwxNqdryQ7NPoaMjB3f7m7fsl6xpmwaGQcdHIA3nBs2o4ZF7vza6sIJhfl4JGWITRcM3gk588uy5OIUNQVGimhnFBFvOvjgKixFoozhaWxdugJpkBlLGUpA/ICRr8AtQY479azJZR7XrSXgje3mlAijGFqFV/BGkzBsgwrF+GjbiR7Oui16L5TDzc2zAwsNQdJsEfHP6aVlQeLYWIVnN1yesBS5/F+MnYQp4ty/M/xuzhymwxWZfbIIfzeRwGzclVc623QjQUrJYJOBlwqwuG/RJERVgghwj+F3MGBmVCTpa2xASCZsnch2r2sFRh11VSooKhR/RRoxXIU65ODVku6LXDqT/wvj5Hs7pChwFFqUqlOeDYIUPRpihihhfEdqMdowQQgN3if9IhK80MuBCptNVfGhRo8ZtMqD/BGF2yGaAkf8XWCun5PO3kKHjEeS3HvANdz6tkQ9lzhcOw2QmDPhKtk9+UK12j/zskfPA5Y0GPpappJhClrrSvDYk14+1KOb97oYEp845rAZRsmaGi9g9Mn+MPNmv3MM7u+0jX0SDkMUeJaBF2VXMo3yckwNMbkNUfQkUVs8fdScPtNLin3+PwsHvruXkg2gd99SzgKB7Gsnc102tG4jHeURG4SXfpdG+bFENiNxG6L0WGUcDBxTn1c1cxR1QsBl+asRsYmBzAf9WKLB5Pq8waupyU4kfY3hcf1B03fW9wEixiY15CHKnHJX4BovlmCzkkz8ssnjXWfIFtpPh8ExBc7+xkRVhbwZYCNNQU/1S87P2lYlc4c7pclluglVzTCaP8YCyZzjpE67o892WAGCy7WUfRubZU14pvf30QggMckr4HVH5H/UtkooMiQpvyTUin1jJW/N9ovz3IedK+20H+bWiU3a6VkY+WQzFjfMMO1pT2Ff2iG1Pq80S1JBEzhgZXWLUXlD+LfBKnqglFgzrpJeo/Z0DMjJPM3QhhS4qqAtGozdwEnENfHO7eNP+pA/8iajmviQqws3MDq+r8ugT4/qt4FBD5ILShURx85FXlFO3V9m9dYKdRQvHidkm+JIAhf3zRNG77kpt1PgOn53GYsiShBVrl8eSVo8F01Qyeh8Itfgapb6DdjyUEzKsidcshckWgG1BGCvBCo8mIvpcP4fsJNDfRYb0vxudDjv6i0E8cv9Er83aEOAXeZe2EkpzRFe/T3Zcu5e+Le8TSiBzkzukv0GWB6yCoLZPcLJTv9Mv9zP96Px/RRrCYW24wA6pWxYk32pdIuDie3opLnw5K9HCuk88OJTGYnANVjZEdwuQcy+sc6wLmndqocE5T9nmd298g/GrRDPNWIxesR5swm2wXOmFtraSLNsD39kdYitwsSJQl2iKJ6RK3jHKbIgk0ASf+coJl8fd+u6e9Ur6LERG3InNkdWBPtPmE1ZUwgEw8s8TODMFaXrZptTGO0P8aCQrZHy4L4SblaJeX28IxOtS9cqPyd6LUX7C+JqPfmCB/Wavvq8tH2ssJCSYmqN/FVX7tcNU7EndWOkaBj3OXENHu3/KfZxp3XY3kHKIBR5BkX0kWohm+sCKPpDtzEgyhqxAmD+FA1YowlEqhX0bAqKGxNvAwR6YdtekyJYIJNElKI/+cFTy0rFsppyfZqQxxwVSTd2vYp3uObAnoFOWyLbX933GgUq2lapt0BbQT8iJq48bnuzJIxNGfb1LPUEgYDkvY8ZQtGOhGt3Ivro9vXi2RIMADS98ORAD8wqcbjzh38211R0osYxQwT/olDVvcZDVD4OKkCZYzpaimUTMI0Qzq/S7gETNEQGIS/+SpJ8N9wZ8W8DQctbxJrruUS0rC4tHAlfXKpLc5qS/CqznpYaf5XR5zTFMf2KNaA8WLUfDZ/BNgHy8XfHMiR4MIX5qvMwyJdB0ocz3Z6tNcZsE0na8j9A9kF/BagHN+GDrUAnDvPYsjyHXL8UB3kbaOHj99Vr4/p7WeR2lUotf3N5FFx82Mo95QCNhoCewcIwG+6DwsGc65d3vzOIS+4s049ycaj5L65qTtdnTzDigr3hqMWqoJ61M31ejfUEfsLimn5cxxKN79G9I9SdlQeNpcy1QYq3yYvTCqMJZmecV6EHCQB8ACLfbwVV5IKTrA/KWF8ftkUf0IEqFlJ+YivCoWvdR5w2dCiwW9ZCH1Oya6NLpwvNerjUYYKgY+L4pYjZ5B4fnn152OsG6jNaM9ll9QCdpWy9EukLpq7e7RswgRiWdYrw1BJgyrQoRh8wPPiUQarOvi8kWATdtDx6pbpPBcf19BuNRR318eyp0pI51Vd5uJ1tX26nZz+k1y4RLh5sJt5mafLCgD6y31nkXJMxXB13TL+LDAqGLNKpMYPV2/q8UN7jcsURlzPQW6nw8kXx5jyAvmzrFogV5BXIinRdM66H63vGj2hvQ5YnjnaRmFiv8oy3RzOgjNAlekCdmOxl/4mtRPGRM+PbfRfIDEAKfcgZGXG8x/Awg5LCAz0RqMnpxPU1rQIMkFP4cUVQjqic9rswTlrxNt4bEYw0IGfbkKB6dojglvPAXTJPshTmfNQPbkABJ611rmZdDilSkgxbE/XfOcjkwXjyMeuVg4H/P0M0SDsaaVSDJeKfnjn5RtXYr69q1AGMCeF+Hm2cP8sdpM29KJN9Z7jRgHjeMMmdsM4Lo3m1qwycdDqFsTaFQQmF60j1JjR1wp+1MHBfF595UCx31R4/zoZRrck7lNBf0Lg/19wj2/8t7y8KFiTvaWk8BZR25WrkZXBVsHPBX9OKxnA3HdXF8SlBQ7rK2ZuU8zGjMnfj/+PFTQyT9O2emxGXWej37SuAqBB8Bc8/m4pb32PyfTnGCBmfe76jTTM/fN0ZO59IXaHulnEzB0AJ4IW5i9y2Lu1rUENTsM8gODMyar56fblbW2XpDCZqwT3nhaERz0aS19o6wm9U5CjR83n8+TBQMhtkXxTMuE11qIZdytOOOByQ8T/y2Qjp+6qt5IuXuR55YMhCAzKOUnjcJ7zqUHSx3JX6aMzWh83MirpcbWTdiTx+DQXhif8KYhBPvTcSHURsdTTIbnioVSKTzAN71UgEKU/EBGoELVtt50DZjjIWsB33MuxdT7CoEI0EyWH85Kce2krpoqvXcGBunvaAbzlvjdpNcl9JyRxc8SlN4Y7UaJXkXxgqikqowjVH6Oxdv1t6BT0qqwiqL1JgpVMwKBIJNkNkjRrFdbDPnt8zBUQ7H/q7WdzP5l5gyMX3Dt97WfmQcN3j4b4STfs3lFx1ul/r4vdZfiXhcQljRokTBUMJtUgIf3HpEI3yVWy1iZHipkQnQBLKdKgz21an0ItFnwrVXYLs26df0TZ4VPBP31JdG0Qv5Zy7HkEPrSB0IcqbGczbK5pjpN2RBO2kOvLzNXI0CFHY2Ecf6od0X84g0POhoeRMcWf3wUD1a+pAAMYYq5+nCYuS/VJhMl0MtpCO2kJ99emUP1DZFUqAUp/Xd5ftn2xp/SYhn8BfE1ZYp4xslsV6O0X4y0Y6lsnVjYqTPFke2V21EfWT+t3/gNQwpnYgIGraOUd967+S6SkIRaA77vdadg92xvMH/OKH1j1Kq0yXufIwMiTXpPrT1cY3nmKGqGQRhKYxCOghqB7OmRHO/XlIjm+NN43F3hNx3HNQBpEBt/XKE4tc21M3ssXSM/1+yt00jS6ADMS49Jdf8mCHYL5RQkjo32r1AY9UDqYWvWeGeZvfZecK0/uTh4NO1/YJ6Yq7wi0M6kgapZSnLHTdfT1wZK++1QBn4BVS2XNAGtbFDQG+h03OjHP0jU4uPNPAMKretYdmzEHSj3U9Q5jdyB6YyuOUeK41DoTEvFdpbE+EOX6DivCu/on/oDfyFrbt++eoQPTZ9Y4RPAEUfn9xsiI0GnBGCdeiK9WZC3yVLqs0VmWPkEGcphbrXg8sSVcVsULhS9VwVc2J+kR7Z/pa0gwrK4acp/W3GQskTnA3c92Sij44x1O2W3oYCVxh8KwmiRN4zRfXsnExxj1p7PlYm5Zon0KhEUvpburlKr0htUttv9fSDCEd3SUJ8pYhIqXQWxnF/4xEPLPoeRlo7cBhYHck95wT49iyNzBRWm/xWBi5ibLTZOq+Gfo1aiDc8f37x0KMATUoKtKAB6uHHPlHxcaHqthe1DoYSyPZq627cEYYTRChLkMilJPJvOXo5m0gaxpZml3dd26+YVLaSrXIa/Vnkoam5VplE2TOoi90EiF9P2M77W9q/QeGxEYcuhTxMMhe1BDTSjq4osRuoKh+M2oaQVftwGwcIR4UxsmhRG5hSN1XHnDvuxdrvGHMzrI90iLPTL7hEwIYdyX0XB0cApipx8jPQaJ8LtuXvxB0LFXQpvzoPAteskkvxp0ImWvnJ2VZISwC/u4gSPeKn+5RkR71+LZB0dqWzFILx2HASOERdfnANRtitZIaXUNLXZmb9CMV6CMKiqKpzERagYhThy0po9Ru7twitBF+S4wNf16R2wM5dAE68ZuHE5OkrbwwRl99IiUNZynnhkLwlkVLfEhA6rkBWWVTxDbTjog3YSEOtfqvHMBRPrL+xWwrYLm2nUc6n1ubPC4B9C3Sh4tuDR3c4iU58uwBarKyKR/gPpfTzfZHu5uxXqin4jalJhCGz54mDXzMrSWBUaM1xTZnaN5fVc5aSqxcFlyvOTDdMsd27Gi8trxJEUDqqHVgPZ+e+2HG3iIw4YAmAHXkVgdUlbCBqLzsWfI9Gc9y7ZV+TBJQk8HjjDGer2ZYHLul+ZA+pkKfENScOAbktbyivQTgQ4cWwKPGkxG51+LqkekqS5DjPRCI3LN8CBBlS7gPkHlAzsX7lPQVsJOF5Jx113JDNMKzant86aa3LkCiJtvRQMgVBtrBeurixTCYO+e2hQqjr2pgeeqsIeOM21co1Y+xoMgYlnaJD9UfLcd29w0U+2VeSyyySnA7X5Ee0aiB4C+uomt6VUvNT8mH2GBIi1/VEiwSx8ebYN91QDyCwSlBRAnPePaxX4MZtctBEIrXvUTr+8YIL9LfMdPzzyyVppovhQrazH8qCIy+rSA7Lag/5sdzFiclcii24d376iqfZ/HqTQq24ZsMV7DbOxG7RJKlm0BYZhsZJuULDJ2XgqV8Lcr3MEcpT2vJJ5rYKrgSjXhkZ8Ax7ZG1DVGO1yaIy++b0TpgAbqgkPvT5hhyB/wm1NxO8K2nmR9QwbBv7KKzihcVjmV2CgcOHNrzMpSO+QVY90gijBWW0b6+QIQsEqLlVPmhztJTBUfxxFrjqK8eAUX4dgJlUqeQR9p/2AXlwXwKnERTWs7ISzHcY2tDWyoAK6aNbjrn0pzfLW5PPHBcpaARbIpNdVp/dwpRYZmfjfKHkWKc/bYVnz7s2UMVOA8c59UnMShSXjiHCdHn6hBYfNJnQv1uuIY65HSdbN4yuHJGjHd1WnRknExywHw8o9ZIEqLTA5DY8bXPPH7AmhdNFmMkXiVMCRVMWdJz4mAfcaVcDLu2lvInxMlGfS6BAzS73lCyPYc5QM0cg7bGCpnfLjdEgjYviAo9aLhb54cxtMTf0XwE8VuEVz6dATQZYiv4NdkFcSsQTxl7PEXNGHs6sIGhGNkShXHIvgpvZeFfkM1nqvKV9GIws1U4AugDLSDjRb+HhxIiRPd42sJ6ax13OiqC3LaH7TxElNmpaxi5QFbuhgZXwi+f6BsyiwSAzi7P7SHCOKzTsVzWTxbb/n6/1UW8kpI1fR05EflGEbfsHLVO3p5itvhhHnlNyUk/domIqYz7igTdEwmEJeeZiNAEZpA+a9B66uAz1hF1Ql1/nn593nDFRDbKaCeHebEMHMlfMVvlxivMBlYvXvo4sYvzcijZ+siexgiSG5TRti2GO2UBxzNZmk3tgrQ3Ke6M771qn5wI7Zto0kVFqZ29yoghqxhEUeZQkQXT/o5eWJLd1IOOnllL4tbPHR3H9T+2vsj9QkKG0ImCEg7XISkzKb7144x8ZdwPshtOkF7CPa8dh8t5CBtDAHE/fUNhfFHPPNHqGfa5HpAg6l1YPSrlp6mN7Z1JEHCQwHTqBAEhgzBQXwwyueavKOK0c1D30g8tsMcLgkHuRjeOt1cxZecHptrdvGFzPSzoSIlUsnjobT0VfZeb8RMbUPgm/Z8lJheeEjET/LngCjWu1CKdcdC0ygM8MpCD1ZqiA/sRrhELteH77TW5RLnrrmSXT69SuxrpJwTmvGnjh2cWA+vri+WRpVLBjShtCd2c+jlb9rRETh88fqrGKr31vUKz70toOQQDLWfjhEH+nK9NFsGMRd8EfUQczmxUtAvyDpxodYrKXaE4s4ARc81OnFiDyGR65/l77oMJh1ywVfrMBHy2wuzOms0AWNmysCJThfRRsd6ixToVzjSG809EDSpN6XQARxdlDkPC055AIw+jdeWe/PGwIiGc8hTrpzeGl8u/wiFEheVEyB8IjhAsegD8GlTBAQqqBpL/LOio+fFbLbZTR0YkjbNKdgnb1S54mRkJ3Rrdp6b0Tc/z2S6ref8Pd7I3uPWrlRv1wPDS0NTzpJZfundH7ewQROs89EN0bccNcdQuQDdCcJR0+mv0Ap4X15F865vmiMo8L+LfLAFivK1H80BTLvPQtGI/WIHrtTm+uOPBXLaDam/BDFFLcbVkR5/mJD1Xv7duE3gXrWrb32pK9m97HDYhRtF+Zkgj7mQwGNJjHXGGm1TKvfT2x5yzYQ4Tdrky/Cqfuobm7kNN5ZxIG7dgs17KFmdDLRuIwXjYzZCKet1g8UiEMa2X1TQ6uWHg+eWAp4UnoK6o6nS/R0J8Yw6Wbmh2zp4RZ9L5hyh17GhpyApXOUndLrVZdb5iLtWfrbo8e6BbcqpM2QmU7eGpMEjH+HwqsUabRrspbgAE4NDaP5HhlDVPs9u3iURdUfdXsC8FcShF7AOxradccZEcBbGU3dsZ8O5pGtL3o9yGmvZ4zLJI4cdUBCqkow8/j8qSJFaQfXsBwMRDQ1FVwpThLyuNlsWwF2C88bnlqLnDRIH02RwJQi+rLMh1LvIb0vbhs59wGuIV2PdEDWfglUM5P0YR4lv90y1aVF1qMLkao1Cyb6vOmXq9lybVlDt0Ur6aXnCTW85sA/eNGz+igdejljW2RA//ZCJjBdzusuyxax3OJozy8ajt552oCMWDKMdNXrZ7HCi0NYKHf6TP5ypeuRDh9I4ogFLfau0qeRFhNI/+xNgbDl7HVa+3eEoujR8A+sOYKAcyEYF5OMn2vNbl+dLFoWJKog8upr02DI6WQt/+vd4/DkVCHAKXyDpTN7nuudLSTO5nl/AXLB5rG+Ru34HVBEQGErTMS4l0hI8k5hmwOCL/jbWEOwNwgzph/8q3bp2bo+2O3opYXrH7yAVrct5vv0Yu2nD/14NaTFV9FkUBCS3WL00m2lnoU62pFJRJe3WWMrAT4QKezPNcKka7joaqdleMdwZuG2a3X9TAeFFAGSqZVZXta7EMcdmBAb66f2829KEPRweMy6mhikJN27OIgBBjStjWWAVoGdQbaeqRNodl0263Vuh3H50404bWduqhXCYrpYsj7ZYLm5+Pag4Q8pCwb/x2hi756IWvu2z/bHK5bchXAnZMxgK7tUikweBBEQ+w4hZ4mAo0dpfneQ+as3SghegC26YlWFMOPM4t3WA4CtgdzsRxo66hQSBySdvizu7r/dfRLbGl89C3pu4JZDfrlFPUOzNN8jAyhcn6QbvEWBW8FTAaIWt7HVoc9kE7vwguOCoEnUw9UcSv/7UiCKv6CkiozeDIH7MG2mkKH/rtrwKOphHfDyjBhAmQTSSzlbN/tEfRmQAMyQ3FGl47uzFD2TfYbF3ORfoLW9VqzvgYaoD8Wb7TLMSQNwv+lcY0zcGbcqmH5wv5XTWdBwnI18INjugli/c5DvF/P0r2DLOm/DzxkhZbVsneqkK0gzWL1Lq3/jFaCVc2mlhcJGRiS2VXy2BN/MT6CopJUcvGuupKjXi8YaYEftSoHNY/uMzoVcm5nT/rwomzxqwtA9oJlOmMSbItg0vhqxmnP4zGmLLoHQNYA4NpZd0JncBaRnlme6DZkyYO1SE0Mg5/KtwymTO9YgU4FzWxzcImEeclVjMQyvDZt3l/2z+vDHa8Bj6fiuicUoy275QDO51Sks1cwd+kjY4uwb8SDBsElB3P7JPQHByMYadVrUjWUZ4LqzoKF0xhduYRWZiA6QGcqarXUjENDYbnq2mPuOUPViB9lRxn20O3fKAv8ma0JOFln92YPKfhbeOAFEDcuuYyT9z7PMGJOMlJxBQWmu61t13YOgEORmGGAhpQaiqESHvH/Mxb6EvacKDkVbwHNmth5o9SO+5LWDln4G31yn7tZ7zM1zM47XkIbJMeQEiChYF2ICvFi0awvDmCSTlomw4095Dp8Qyzrg5B0PTTCTaHsGO8wNvFY3573fPqIEHbO+0lOkPMytKBrVOoJbDrwVn2bm9OjKjJGi8O7D6ol/688yihxCbeoQiM5kWt4pAgxugS336Z5bC0dd8i801CJ+kCpj/SUjkuLRDFSsGhnCSMqN5RLuc4bHlYHnvu+RCedEfWbNBQYiLst1ryYVU8Za+bVsoPqYof+iWWHtfDydI+9oFg1zxkJx/yNr8Q5JlfTKfUF5uVJMTNB9VzFUvkqTlGL2C2la/exSE+D7PltqgCtrRc3s8JOMUtFVkPek88KdUtHEqGNc4s13lYpPmUJ+mHQc08rbnFrybMakWtV5xZt9uEwHO5HC9FWsYfY+D5s9YuBNtbgM33yHOqkW4eyr0rHQIkkpkTad6FBASgRljsI9dwm+E98jzdtel+Nws/7SVKFRnCbaKWroR9LgiLM8cLSrgLEuJICUGkchSUokuBuTvvH/L03e1OcL+i7nhoYopXqNoL3SfKfL+gei2yXHz7bpKRh0hCVL3LjOJ+7yu+2EMwHUu6nhd4Ozvc00eTkntWWCYLyX3PbqmOUGqi5Dpp7R/0HYqhPUQ9NiC/wUBaftG9LCRoD7KhvvQMNfajBN28vYguHoUEZspJgCWTNw9iyYSEjwRZF38pPZm4f1jkc18VsyWaX53VZ4h4CQUF+ukb5DO/52HEh5WgFoClSDmioGX+Ze8oObAYkdJa1Dz9aJfvEivocMM+opm6jHgX0zztOIq8yVox7tMknVVhEyWRGVOpN4KmWyleO5/ltUvzlUrz/RQP/9QnDIVt3UEYll+TN18Xp/UYor98Si+mtmN/uA7nVCJPP0H95bneVd6BJPdj5TRfm1XTh1io+I4zTEQKb21FPwL8uDVxQq6hv4WgPyLr4Eb1cdQjflR4gclM86Y+dJFmvLMKq/Qn4SuHl0ptuH4ZVFuQJx0HFG/eXhFAjIyNgOjOKJxw2xzAUynunNbAJcO+k5XIfh9QKmcm/piu6PbeNMHOfw6qvhhlbPw0z1qyYaWmeMNmUK4lXNcSN9cN1oS8FBFx1UD8sMVQOqDn3U9mLtf/t14frxMEKlHlNgaLE86qij+ihia+JsIJIwIry4Mxd39cB8b3KXB9E6VgFW8Aj8Nx9loS0Gu3/GtEcU1wF9BPPHk7lEG79DMPNKPbd/nG/4U2L0UStKsATW2X9Bk8peS62i/PCkONlOk7fQG0DCCFxNwW7JRm58gU/f1v+zFrwwrjyiq1j86BRP6oM+QfPAJwb9rFpeH8Ixx4faaC45jjhNBRox4PMgL1KNz/s3vyOG9yZI+MTRS/x+3leTrmeXSwzr8PLsb7/vZaSd0wU0++aD42pYvdYbzV+ROSE48mnl5q2UlFbp7NUFTyKRY1+HspfyPh4ob2MYoyVAPhA983HhO1wDbRkk21pVZnVQtE557h06M9laaZQyk9CmfpCikUEbkG1b8tQSEuhVKbcbYdeaysa/lVCe1ZHA1dg2k9JkZW8KDIK3XUrDF1FOIxx1MH3VNMxCGyi8nf4KBo/1Ojfo1SsvEHs7is0gB1bX1kMRGLCxf3VoHPqMuU0iWySSP6mTB4LPRl8fMsSohzXEE8z5ZyCXP7aO0lfeFjUI3ty6q/ScXVUWxqVZa3ldOWrQiq/0EVnnEFk64tF/8AF27JG6yE8Iyc3ylktvGIcvzX90ZRFhnL7sbSYIgILCicJ0CGc8XXmi3jXkrrsquSDbKc4avZ+5Hd10iltVnNiOihKbCFnp+CRoBkRn2xu2dworoxVD77SwvbuGeaSKRYtmhb9QxeO37EiigcfaiIVu+v4mV0vIUWYW21B4NA1Mr0Oqa8raU7M0RwCJkU5cIv4/KnE2eo5tdLCcSRoEZ9DWEae/fPn7pKkUz2MUopP7kCYDW94nwazHDLIP7RKPa5G3EeKp05JGuUYuwfWtR1evTwFsulSMcHXuOw/LPGOmEmJmwKBYPKbjW0z87Z0ntlg60D00RMYeEUhrwb52uGzNtJEsBIiD4U/PTkLv+3TPqbCAa9Avy8rH/kMobiNT1MmIaqawtJHLkTohNhQK660CvJ6/CGRQJ9ve/2CY2LjEhDSQf55rJaA4wnmQn8whU2KDppNX8X6Lm9TqLVDp1XpL4H/5mCTK6L1aclTxWZMrCIBQWucNCbahuti8/lxDA4j0OtyoS/Ni9TTofdeSzS+cGko0Rnwc4BMSyhjTTIIOtJbU9pbMSIlczXV+7qZR1xaIld4qtIHAxfIxchaFMMPoXOYIV8ex+s4fjp6zdzPOBgxxkHlH5ObQPTNMSdQf+5885CrMozp8ieGdfnJj0bsZ8iF6thXCIDPUzmB/HU5745ofYvXlah1Wpzwz3zqkWAoPfVFITkkkrWV4jvPI2pqaibzmU5NP1/enT1qhFtIDnvrDF07+dYPu6KbcgWFUngQuEzMmgDMH7pZyEohBB+QinZA/bea/mXw1nEF9jj/2PtdqBskBJO0aA/6pFCFmg9fJdQkPKGd6hF/bbp55rrpL6m0pxB13d1udkNqo0s1Tp/LcHlUCLAp0cERvRONjKYALkN2arTp+TpPXTYys8hLPeE0ovaM8g2QImRvHeWLxjwlnqA8+Ol7v3yv0LT0zGfp5zljewzrbVj9IJLvnrZxaRGMQBzIyRtaRCYo4A8pbEmHIai2+iHur917IIhH9xl5KbCz0LTQtm2W9S/bBG+nDd0g2QoGx5/FItHC8/avgmem6xMPK32aW7N7ChDTzOkhnZdWa5fbCi2T+tDE7BXdw84P2i+kKVefmFjmlXpsP1kL3hJ8o/5TEKVvdrh48dk6YmO2KIYNCoP0uxxDuu8GUkS3aRJJRaEoAaKfDGZ4SIpWzDGWsxTLbE+RlTpaNLYhDA3ZJ/sPBmd8ilPIf2c4L2t/yOynCdZnX2gZ0XoKdG25j/fk+0V2M3MM6KL++lxcwUwXjLnrpqa/gHCWC3EkgnGsoGrxy2gNoVxLzHTtZNxidcJ+KtSaZNiYkkms1BPaAeHsV5MvZll/cYNajwZwfklYk+M6fmAo+fTdYpcK+SqcyEvIkARnUVayAVq9ow1Qy2jaAx1njNrUkbOy3SlpysiFM+urfDP6FvufPM2MX+174iQ8NK9ofRYbCSLurNECsSfNbZ+/M0n0kS+OHbVgMvtntA9x5E9BJlWzyoFUfFhOf4zE7Grou4qG4bU9bAGtBqujYTpGQkbXkEAm+hm4e1tDRxu5umAMZIjZSMF+3sl3B9wfdeZeSvpSuIgvI0ywtU2EU+vHkZHY5LQKeW0xLMKkb/T815sKasCqLUNEXdz9QG2lr87MYZHAFvutU2cs52gDdwc/zkgrZOcCvr+Ri/lsh1LF4Z2fxG4FJ8M2qBpg/xCKGt6s/FiuibxsE52ry6KJ+jb8bJRzfw2G8l0mtafRZrP9PkW7MTLfDM+NN6dD9Mr6X5dDHc0ZKSfAaYbE2vQYIjRk4tdqWr+jpfLtj9yx9b7e436WwCC4mRmMCz/D26PuD3Vu6MORKXQJEM6uMlYtwmxJfUzSLUHZ2xw1dToRnFeB8lFJ6Iv6Ro1pROYyzw/spMkG1UQItovKAo6y5P2dAGHkj8+dq0gXD8TVeqBAjqGfcO0YUXpJmlmSHehyfJutTBwYqAgV1/UF7ItWggjWOFwYhwKda1/xQGSmDHcfi7Y2rJwGnLA9DhNPMfxczOTHmbafGFPI7Ks0gDByZxf8MbFyAIh4JWvY76fimERODG5lFWqBcESggHg0rZhDWcRTYcBGkfbB5Sf5DT+koQqmS/MXmiOAv9hfwS6syf1eO9YG3bKBk5yZMGLqC8UfhVA8SorH3LfPiNz8ahH97smdDInV3YLaUYRoZW+/f+zgYI5gp22ojU6fsfOk0t21z8/mUQGEUNBcGG5HExmR9L9z5fas/sXcqSlA6IdMDeiuO6O++GTsQTj6+FhgNwmftswEkyu4dXthl222A3Q152nHhmDF1fCBvHBLRut9bNr2N9qInbhrbTogGVZWPt5C1cI1dIXkkY2VWUV1K2cPZyGPCdPm+J3ykhVs0Za/4BNHmQH+QxHtPVnNlNp1xeTfjkpHq7niYFd+cS+qGJXA0GG5xxvvxDoyP9x6WJMHEEJB3l9kvr02OlQR92RYCNZ96U2i3KxG1Ldhs8kBQ4+DbD7TYhpp1kZcsKxyAsHJLw6Cx9d3ostQIuewyitxtEVt+Tujlz5kDK8HzTHuq+OnpdDNBeTf8Idsn7qIXb5v49eRMIhJxV+LKVqFhaYmyylezy8/lQgMdc6MKId76KBW/SCmaxnq/W+emXFSwyWYPdqnCMPGKa78MjCQcwJBMsLEJIKa5fihgkL+hFIL/nQSuFm4FkXU4sj9lFye0fP7d96gLDK8zKyoPkx0xO0PVXi6TYsZNUNqjUwFGv4E2MCrKl452rim+F2cWOnUV7AqwNiTY0WyzMOGr8vI9skTxlND6xzhDdd4lfDNavvv1ZaEA9uWyLjCyWYyOCMNrYR2z4/e5VvdJRztCV1oGC0Fk/TemXnbA2/G1JaqKhSF6alsP8Y3GZvY5jwyMOIW22fBoTG/b27bIDUnQYVkyS5Ezbh61/9FPBQv5cx8ppeSYM+CRM/vFJuSPIcnJGFBE2EnFso1Um7AY3iJ70fbhLlJYPw6oS99NUfXK2gH1iylZG9a0a/cOV6fQwaV/bSl+QHfRh7dcDwY7FXBFB/X0ncjqYqiWWmVSoegFg9czMOAKnVf5oznC0vLGXSktBu6U7oHYj8Aon+xqutM9xqGp9n8BGfHZwlxi2FrrTXGJbhVRrGByIjZzCgBUDOfbERVi+VzdJzvS22667741dAr3H/zlJnVimDFj+jFm9tMKitdkMUu7d5t0YMWZ/th+DK7qA0EZoeoPSzTby9AX+wFZKxRQiQlR5HFTjV0V4+M3K1ThtcGYIWFBQLvr7bIFL8RdFI7XQSIoy6T28F3xzW3gUluqOeDIU6vslzPEEBrLODDOaYJMxUXn5KQsr3VL1F15CreuJahmUuNnIlYXjuLwFWuIl7dJNyMggjSEe1oBO+oaqaMp7KkOUWvSiOrjWBL4VAvsIMDzP5WrhLene1TTETgCHajiuVg5g+abCwAumUxmLoiJ84q6W0KKY4psniWXH2gisSQHTiVL3lkVGnrsAMK1cwPwwKv8B+lm4EseXVkklII23j2eiHfThCtDsUKF6fC9/3IfwBm23qJ608zDijIWJG1JmgZBSeiVkR5jvcWhVPAa9eiD4+AS1Z3B2hHwOH818e0eLNL5IOi1ck5uJSnrow6wFmLdFBv+B5kfGr8Ka0s4INR07XxTgG70XnR2QcFl/QqD73yVQuKjajApD9/HEO67oR/89oT6G4raNQBmONsOFBg77dgzF1GjhDdwfwugwshv94C2D0rn/ovcTCrrEmjJ9FK/UiiL2D9mEtSwqIPHBF4mVwcXwFxh8cTqdKYsaLH0FBY6OGQew6YpyLARCL86YF8Ba3VXiz6dYU8HYVf0GFSxfEu0T29r9Wi3QTv+d1WwOVQ6uALMQW/hEs7qak+7gkLqkUtYIaQWeqRpY1EQiq+kedWgwcCdr21a1zVe3qTHmFFL7pQ5yHU9EAGXF/doif04fjFY78edWhWGrQBo5oo2Eg5qAJZHd6RHCwcAHXMkhGvjmDyAfAjf7bicrzTNTlBNy+guzLiEQzexnN/PlY+bXw2ze/MJfOgf2TQGpiGFusG2qn/2vssnEqYhfqZErxeYm1t2evMC/vtvvTELU3iQhnl8pqmzq3F6y89us9w+fGZXqFUs7fzryxQXwz1J7pBVubFVX00sLLgN2rRHlGzj9Jld41WHxbloZqJZD6mss1riRjYM1xRfmifC1HKv28hdq/WJWwf5TWl9lBTv9mz59DPvIosugp9i+GSum5DzS/0MGntohAShXIEHRXO2Ts9czn2su69z/2RLgwA1LEP6HsjvjSHytrV7f2wqktzTUEuycBWx8VR9GDWJ/VPX48aHGYxYFeiwJ1sjpbrTI4GUX2n1FQVqYDEFfd5+OEkPPKuRJBd2SCcmNkbVvf+6fXRTIVZx7iXYXlbxpolnhXiYl6PwCRPRMhaRFSV38M6bRET4jewpIP44cO8vdBk+0+97i5Z3sLY+Prsh8j9j6IwNoIHxuBN5yggW1541rYnmhsEcwY/Zk87IZeyod1u2cixzQ+ivm+/jQalp4w2uVCGscZzNGFXtK8oi5TneT3tyZS52olz7bCF1j0tBm2r+rzYdpdzXiNQwqdt+7hyxXv4deBrXSoLur1FScAOVoxATdEwKuszOZtDgZ6LA4c82fVtTeUbH1pf6m/YCXZkWAwd42eU/cr0hQKti5YVfuulbDUjMn2gJsY67DI4xu9csgUnITNrRHCcNN/8kWDzaaYcM3MIdrirPTEaV4iKL/QlKSkQejwdMyBZRP2mPOWsYYqzXZF1kU/QOKYYinNPPxrSF4FJsrCYvgJRtoy1hLf/hZ7yITs0CZLtGUpROY/aa9xA8MHr1LGKsoy9YCTZsloSdzramd4SASvticld2EGEDaFnmPmwUrdxjATtWkRLZ6qHbUgvhnUPXB8lugHCF4VPvntpCtqxaDn99Ebxd2qVnn/Ka/VBKtygKscaurcA3ZIEzWq1j3Xt+oIor6KaNX00r2ohasd1YRK05d03v59MyWFXNrAtTd86NYIxZ25F6K0wySKIbrLkVd5w87FAjflyrwIzJN6+XHDXGs9FcE4T29UorL82m04ZFovDC+m0fDvowj7BjfPjt6YQMJjS308SzDoLFGksI6wHVoG3P3Mq7kAG7DPcb6i77Xruy9UVcl38wRrdjsYIc6aKsj8juuuCdAAdZU2Fssxmbrz/Ra22wdlWIBBiwnUbgvYNl96+3GELMk5Jz3EUyY7PkQrctUb6GHD75EOV3qD+K7E4vzMl6vqtGH9BXn2ZMV9nMrnOct334pCjrkHid1DUmyH286C+sFQtaG7aScVpMj4Pf5bwMdPr1TFT0OsnshYz4TCV3hu8bq+mJPGosjQfCJN+s2XtgMAkrQ8DWXDAd3Jyamy+cZWKmdpvpHQKw4cz+p83SGnEwyq+fk8wXtApxEFGQKE/96eHvuPUv8trYHkT0z67eInSqdN9V96n0/G+XLVAdZjGnE5Ggoh2lRvgtt5g5ifMg51PNoE0qMkuwdkSBNVQvGuYMmcKA689De50GRLjPvBphe5a0QecSho8bca7OGfpCPOXs7ai1VObacQ5CvntMXhAty2GcxS8lYu0qhBCpflhDdvUpPc0s0oPYO3puQJ1yqE1d0uHZygm/FpLNfJUnqtqUktrcxRFdMQXUV58JjwmA2gxe9jaMXH6PylBe6uovbQ9/neWAAhakKxNpGkmguBZHUfS4/htxW5ZhIsSoc+5TtsIkWUk28Hjh8yeo4DgH6RqBgq0gKLOic5tfyD/VI3n3mYOCQlqUYQMNAnlWJQAZUSMLbtkkA2lzfn5mBFKb6V9Yp+vTUkSHjpGJxX2Cs1fI72PceMY63GFgbgkYiGTuU1HrsHOk2iQROetfwrRsGuJN/ylatS78SxTLZ0EAAW0TknXDuDJoqniapDxSHEQU4SkL78NCDXZFWV4VIj5+S0KSjt+AYoTRLZU3hWy/oeailwEWJGawiFJJiGanxst61NTGceFaL5ySKB8AGskoTTn5Ev/38l/M2P9TiRR2unYKPp+37jUqAyyrM1M42ZPC2JPtbPAVOENLf2VLCHWDX0vHQ0Klin7+10hyW/kdqYM7OfpAorZJq/dYbLKtkEhqEmhL17ITcVevY9XnxpTANh8x6TpHUa47rXzzgntGRlmhtc+xmIS6tuKxUXF4Sc8Yq7319foXdOM9W764cqFtLCSz5s0HvyMvN82vnR6kuxBlwgpR2XVUwJhQYX0Fl4GEnhKgjFJx16uedO1CNMxZHaebjNaXZ5PcvAUJc/ZuxbMqSl1cm+/h1+sIVM44YlGVGkdkjBpiWAVaSulWNSpmk8R7yqdZXSEUu5sG23PsCobXLYAWhjof2ATOMETzSdCIQqIbNJmmgjAJgtl2VeaSiQUc/NL0WIphzW5/qcj50CrHjUujvy7RNVac3Xbs8tj593KaeSSgRDajpOkJJUwdH+GRqshtiGW/0ulbFZmAnMZ1ezrP+Mw10oKdoAaevJlbEVfO5Hpx+wJmGUWaA8BgOk0ITQgUvmqMnHnUFsE2dVs++70WBQCIAvxW3aIlyZqOe81yRqk52hbY0jZqEmg/gP8YKwU089OITI4cXOmdZ4lknNf6PPco8Hj2FajQvpje7UxuNeLEWPTGb1BiGeSziBhAorpVPMM274leZ7i5bq99UIsrZr+kg6/2Dj7YvARIOG9CEknf6QF5FcFFIKKuJm0ufXeF3MfynPo99jRwz96jtWFVfThq9yqzpw8KZZAW3lHRNyaQEWgpnqszPnM1MIZhmVR/U19ypQnmHWYuQ62WPg7tETY8lMwX6ST27MrI8oz/L6OCHEmTsfPSGtbdo2KpcgXpG2R2U0IqGAuu6+P8C/bQIf28Iynl8V2XDegwkz4I75n0OYaRnGVdWxEnMHGQ5tZTmOdFFz0oQRAsQk+Uo7FJkfG9yJX9jbb9x0uGjRRg5mkzOWQzqO3aJRqcO/jZRqnNzqben4QU0ey69ohhkebQvo2Nb+mvtxOPKzaPGwcgqX5lrJmYfqjWMXGdjm54uNjF0IBiXaTRnAxBQ0nCwQU9u6+Faj2cTGgyinByMjJ10HVvl0nz7Gug6Mn0sPC9C21VZnwm4Oo4etQAjBAHzYqDfs1gKYBCiJFA0/7KvjwPLOgIYTobkdCUGnZ14tlhIcoqFMaJp/CfpPzNvM6FsH88MGSsn7PbynLjrcUVH/srikpBxPfC+GyoQ7etF2AxB6CFqdp+6oJSbHRzwORv5b5idgQ5+3xmN0zMvc01BxiucXQIu8LPbjjHOufmtGi8RyTneSKRT38vo4IEH/FsjkKMOf36OLoEQDurHfbUhoZFpvTz/eD3y088gUpPm+DjxwDkzMNHJz6b604uuK/DqWeF4M+P1ZvE6JChdQYbA2XbdNURjtI08V0hj5fR4Z9Gpb2w6R1KhGLbL2VTIRipXaupvAdlkpy3EEqEe3Zaz14xR3du2fRkF4wBtIv29nw/d1gLwPKAhJgN+sqN3l4va1k+/DWGpDDyORt/fP7oLN/Ks0OKHxVCXa4KR33EI1qSn6dZ4Jd+JizmoB5ERBq09e/LqwBenKTd6rezhBiwVCaGxOJgEidwuNAlHELEkP8ki9+cwY0l3c5aGy6fYma40DnX+LSjlRVf5+fghSr3oUG469i2cScFDCMm5nZ3Tm38SicKVKBXKuYu5FM0YMf7Eti8XVKEcBCvGcLKz2PRBOAbyw3+tJ4DoZOZywa1S6MzAEGVpeubWrmXDJhG34c08Wce89wCMfpK/wYBgt8GBTuJRugmPBGyfEXTS4BbfQ5kN7t7nvLHYIHMCvgqgcZq/QOVdalQP9pcKcQvzgdcwxzJtmhN+ACTwxIguhUzEQqsjIP+ZoxYJk1TcC6ilwK/DEqBzypy5bPjMTTqkjXwiT4w5Jf9Gfy4ivTef1Jm5iCeyJb+Rs49Wv/6QuZ+gGq4kEhPq9ydYTAtbnQIk+DecBuV0WUCHqIL94na/ro34Z5+k4PtqLAHb8LiVtiZIyX3O2ikuxn7i/ruUwQnCVuX2eIAIBQs3Uc7Bq+aIoXT/K3H0Tn0G2ChrASKwazl82n8+6HJoukJbhRO72pc5CTGz1LpskAdytvzjDBv6bZ7d9Q1DqaR+gRkmvaa4EGHI2/uwYiN8MkqcyAKiwJ5Jf9HyfhkFj2aim1ERgz47iNmlaGTTM6jl1jYy1hw9doNAg5abvx43p/kEt5E34XM/McjFjk2uGArBwjDRUKLqM7cY0lY3+eeztMF6335JU8VbQVwnxUd/uq1fzKNAXR6sNJ/b8ByP4Wk2nC13xu/RC5exOyoUK/JHP95jyy6jHnwml5yUa+EE8vjhTteJVfv1YSNTFSc3PDFhVyWUAQFTVAqajHBF4zVEi29LxqXiOR72gHer/TEJnHs5NZ9WtgN+JwxIwVxN2epB/bZvUBm30NgIo9fC/zeFgLSRuSsuh0g31AinVDLZMYJY7Y2SNkHV3hYj40nT8wx++VUsha8r5hh7j4Klw4VKrDQABQ0EyUQAPcN+7i21iNts7wAHafnt5AXT416S5dAkMX/MN+5nK/gxJcEQiHtG6xjl4UnSrJ+EvjOyJQrerLjNgdGsZayn3nEKiUDKhjOULILZnuOn2lSg4YYrcLS5LCW5H4/bPOR0LWmmr8pVY+iM5ej7slTLA3cAL3RFJdJ9GAKr4yzBkV5qzZsLCwL4rG2IQO6PJgupzZSnlGboyka6uo1HPcmBQiIgxYLeJVSfl6l1FHAbk1hBTyTwhWHjV66lx5JJqwg/dPOY2CY4Hd3Sy58x9tFJSbCGwp2YL1IYVyn43nQPkrpkPAfN7l965eD1WbqGhRG0fDZtrWLqOywN0yhmy9ZM+n+qMbhlnqIjReMw3hzGC12E+wF4yaf9B8tIPsxM14YUMvQdTvtQ88jjIjdic6aCGGTuDjgw3LXMwIYZB2zhZEec+s7dQ2fRvo1M2BRbj2mqDwurOjF26RfnseP0SHylnPbjW+DVTwwjvxdHR7An657yjLD1tmwSytmjY7VOYTS9y3i2IamO8uEwowEug1Va3sOiMbCoogMGnWr/mmHIn5R0HwWTRIDiF/Njq+VU6Ua7Tcu6Jh7109kne3cH4pnLn4zAJjpRYIpYo5os0e9N5Z1GV9NeD6AiHqiK2XQ3hUbQgYjx+HNG2OrVx/likvI8h/6H+UUn0mcmSKSoMXawKfew1m7Lz78IDvaO23Q8XnLnU/Jr1fm1lMFsJD8/zevv4cKkOrp6zctKHp3/Xyju/TrjOwwYeQkwdvOQi9DsejKM9Or3MhYhhO5brrRqS+aOvtTIs1EZ2I451m6DZ5RR3IwXjskRs++p5wVktZ0DO4FyKwZa+ekJ5ekOV5Bfba8N6qXunmL9zE7Vf0oMyig0nrDcF8aA+4lskPLyuyzFCNSM3fobeZCM1j3O6j++fQFP0vuqcGpn+p/1Ovas0Rvl6oYEdfC0qLWEXytHa038LITpi9gsfJXYCDGL26b40ZUL4TzW47pFLhcYL8Nyu/ILDg6S7mWyOtespjMl6h4lB1EpQqlI1aRKlWd6rPjiGRxpzqYmL466vISB98AEuET6I8uuk3VlVDIWNp/rf4Wh8h1UUzih4k9K1+O4ESO0o1oa2GOkntVaYoPvoqW71UPNL5IAPa2oVoXnqONJ9UOugO6OcfDoH4mH0B1yEeJ9HFvRI5wV/UDYUkNogb9LPJnQjehdvgorfxmEmAXhmCdgxZRQn/1tP6jQEzSbQN2etWGXX9XhVur7xXMS8eBN8qbg86DB14yJwhst6VEDXcyW+xIYfKQxi13fCsPkkQqMLhf/aKKZ6upgT+AGBocV23mTyhrJqZKWt9LdW3CRPPdIChE4yTKcdOER/yaomYWe9ifWlOmuili5G/HAILkH2gp1W9lBcOF8QEUrcvarjAbkxqChsIDiOFggWlfjlmWygmZeiX8xKPgNGzTkEJWNn44YrnokK57d/VdQYpwZ2DUclYSOOyKlBLZ+HzvxaLKFCGxjmX/TXFgOLDbs4Usg2/SKmij1Hf3IVnD6cN67NFORMpdIlLpL3/ImRA9qGo5ITKu8N6E6/8og6fFUQgDMgFpPzfCyzGNFwmY+3BeGm3RZo8kuzw1UI3BjOhfKtynIjn9I0ElhqmNUg9b5M0QkzOLHKIaJRTO1Iwft1OuBHHuNI4qIU4cu+/pT+KK3vSRLEJwSiogWSfkI4UzWZN0iQDa1rHchARpDWaDnfCqpocc61jxamvp83ky+hhRJG0GwQCIqr7ru801Q4fopBJzc9EuB2HqJxkOMTbZm/dGcHjx95u/+i56VM2od4KW8lSVly1EUuY236ZhODhaGvRS3kEs55qsA34VX2X+g42bXaoa+MNQfgeawvpQyiKxe7tr+EKOweDrlfZaVYz76l7k9G8oN94nIud1zgsvLPKNQNcDC1juut0MtuwOqx+JopUEhrem8gfXzb/N8Tuw3UCJ6UYPS0HZs7SuXsw7R0kH6bnVhkzm9In2j7DwMWtR8FJVtgiV3v7XT8/kKr5QIWSxbQurFzlKwgAF1b1hYc2BBQxAzfilDb+1o0Zilufc5M/fhmFFdLly84quKLCSTrv+gQEA/wrMtq6qeLUl3nO9SteIsVys3L5mB19Iq68QbcHbnVOQU/ZGhSMv5G1yMgX1tu/SMkLK+7KHhyMG9hDiT9QCUcOJxZTU9Ya3xaj/kMqWmUnnZsOVWaY5DC0ngIPY7rv+VtYMertsSg+p3qRIygahViaes2YAPpm6bOLeAGeLHLNcoAPADXEBLxqN87Zl8wfEX0UKBxnMxyfAEpgAdmltUFYkrAmVUArrB3kfDxXW39keCDOvQBOtNnIMBbIIMqt8QsbWj60DnjzZLBpKFjBetGU/4/S/DnzCJ7zGqxp24CUDdc34xZ6JLkLq+8aeNH7wcMFzyHx91zAWy2UlNENNMxEfJsyuoOfG8b8cNuLug22LDGM/AwtLdJKmzA9hky0aEiuesPXxw7+ExHRxoOaATLGTqDk+T/gQp1T4DLddV57RjBAX1KYL3UeWV8YEBIl3MQRkKLUHYya3SCF1vvlE+0ZhdN5Jg5PHFUo+s5rc6JkICcB/vc8J+UI9B9DMwkA2SZzH9ZAM85xaty4u81HM6OMRq7YI53g6UZ5x5FCkwmwkofJl62BNtxLNOqYyM2wYKRHU9M75+b2kqgL/sL97yRgCDp8wuHAdHXE3KKXPXmp86hnw+JdCMiuvnXxJd83Vo2unWHuV48HNRq/aX64agzp+yNZnj9mnU0NMAfrsz3NP+wMzJa4gYNlaa9nbZH7zNZu6z9x3fasKZ3nrM4uHgWutOftML4F0k0L5Qu+dsJqAI001GIGkPBHzL18p2GwkHLqqpWt1Z/TknIrw/GML4/SpYVvoCuQTkm7c2joseI5hiOQfIRS9f/reCVoFd0XQjBipKePoNyF8WLETNo4+5Eu+sTpnPKL3elEE3nBpttilCpBDYd+rmjbrSAhUP78ORfW+GpKF9sIHxdkDR4LBV8AhfjSZhPTWDfc85lWTb8n5GY32Sm4V+HgVProXExVzqJEDy+U+ldH/nM5U/fZmKcWD3nS3w5IEno+f/nkGhfKrzhhhe9q4Pp+fpYQZAop4qa5aUFm0aQ6+MxUwX5iTxIT1NU7hZ27AjjZFR7KZTZWU5kOw7jot/lVS3n3ksDl48r/M5VUFYBwDPFwZ9eYnNNjjJBEOwqrj/IQAMA+GcUOpyUAhhylt7Nim2tZOf4dDq06c0fqaNY8h6JG4DoOdK1Dr0uLCTVuGL4jZbD98YLV5lpve04+dNlD/CQaMooUU1Q0t5LgS45jpkwkl0wI6UqLNa7iAbN+VGOsanm9f2Z8tM3DPcHSYfudw+KVqnulDbMPJqfo/IycEiWn0jlwim6zXT2s7CbdUguBux0Ho6EfjH2c0s4hhf2hmr4o4U6YTGQVAANIWalhZhPzCtaprYgnvnpTKoQWAaD7YbkeX7RkoRj/Un0dnFs2q3rBUkAVWZQ46+zHWiihH5S7Nfewcdh7kNsNUeIH6Bb2Vh3mdWqfE8h/edbIhetbA2cr/sWhIBnH9dTRpw7FhEk/9y0dU6UmsYPRdSf5sFIDGygH3Y4DxCMh9aOuKkoNc/tFbscwQd2NY5ZFYlAr+e8ZUtOyHdSdgV5aL7PNBoPR7DhYSCkZNSnWTJWgIjQx2PEuskkKcfzIKRh9YomKa7E+7LmMAMG2G1ezocUkY6E3xYApZ0O6Or2wadICAFckh/QNiCgdSUTPPXgxOiD1ceGCQkOaEK3XBZU2AsB6S7P3quHEMV38W8yQwghvM/rRH9s0U5eD+v6YaTX2iabbyTeXSYhoyezcvBUZVI35G8lFOZl0m/eH+2uSwq+8ZEnB7zj4wRXP8q6SmKBF7u/rC+TROc0UIsl51mKZuMlQ68CRuDoCU12U8JidSTiooZVDyTKIk0PL3RGrOCCDkkHemeKCjH5uGWaQKybhIxpKMqpuLRw/V1hmCcNG7U/1jP5iJKGZ8bj8f/NF/heeXeN95FCf8noEofSLI2gruGpAXqt2sLMDKcJA+6ZsbtrVT3ytbbJsWLEPwgO1mkOvk9ly79ZxDqscUV4cUdns7N83zzUzUfFJ8d9JezQroqWp/ii7wQGkV1+7MJSVxka58PeqLAKSPPrxIcJGYIkPGBiUE9Pe/PQFsqo/96qbQjWV5FqYXeLWTNsGzRGHB+Q3FdCq8iHE4VToihEtT+e42gXvWnO1bivsLnZTcc1HDaAlyAlBXs6ebSVzJ6CMrdCg1fOWV8Yo/JUfhsSC/jvk1/8Io242uvDWl50WkDDD1oxdOU7AiD5b+zeiIZCIXANBBfWkXcoU5083EcA6JHOV1M4cdnEaIDAAu8Z3X+Vx/MdI7LoICd6H8spJD/yzJLcCRonlQzMXSz+YxoAeWbDIp4qeV7AOgRdGVOXj41BmGfBFTQzy7RKkkXyLnynskpBkADEWkjazVPtM1fj58HJUi/i8EdPgYW9xNJKPLWOW78ZnFLs7KI5uGwXusjXQ+PocREn0xaqJCSd2RX/kAX891XP+9LXvALpN/4412CjqtKV6DcM93I6ZouWBHJruhziySfsVlOf70FTdVoot0KO1RSA130+ioKJFib6OcDrLayQzyZmKVW58f3LnES5S7PES6LFwPRmKXH6O4ETdaZOwQZamNNEXTunAU/CihAY3PvYhcHBj1MqjqHv0EgCr6J7Qzm2HUx5LZtPiv8K62hsAlXwzWBrJ3T16c2FmXRBVgHsKrGdWonlW5ZnXcL58OTOGfgdIDjh+xyvLjwP0ICIvyeOXPToPZ4FwZou+3bCwyBY/yCwPTf7VwxPps8Lo2AW3BDDexUkPMCMUWruz1q8D1KJdR2ynlEvNtJTyfhamX4juAUDdTVbYNXB4JnkkqEKhJsdKF1rMksVSi6ft4rdzvOll8qL7UDwnm0wuBh8wPCAcXnh+p03+oehwLalDzuF7iOykiT5p04HKGwkf9eR4NHrF93iQrxwBG3rkMyQC0MqyDHgQjl/MbFthyRK0C7MKezEFui95verTmEGH8hMlLnFuqJyFmTCTYk50t8w8YTDMgr2NP3TA7tTBGz06cIcak6gGbA5EiTvBOX9/oSZM/ZW6pPsak64MQ1APnc327kjRPwmhHuygxGMt4G2dIGnKuCZH0im0jdsTKNdIiI0ELpOCWR1V/X5/ZMOpgqkhLLx/SrfPt9SGnY/XbIx6tYe78w/xFZ6i+MlGBWg7BcZNOuSmNDLR5PrZD06eX1RV7R3sZ/F3GMaRZtC8JlD/p86y8gyHnoqZM7h/psPSSKAZpFPyeHEOEQzg7NdClytdrUCXnNKch5t8INRsKM2rAB68ifUkf/XdukINpHgC1pmtUiTtYfV6MYAfB5VeaJgTBoCEVizcFsXgUoLtl9BUQcguDDmQBOtM076+xqAU4/6vH5uq2GIzQba2fhMdlooc9GpDgGNk9i3q8RhgQBzUbJVZ5T2XJ25JtfYNMJTZhEpJThTFeYBFxfviBk6HMvLufkaS2/pI/4jALLMXQMwQj/NVq686JfUvE9pRlC0IQJZvAjGrRdt6YLL369LxVjor7oDJ8zpc/MZlbB9IoCp1FSAmADZhFSHiXBKzLOWVvwUCgH5OE7lmQqrxsUVkRQcQzuRFP8tbgi7hDMsLXZoA/9vhFwFBGAIjiUtsCVXbF0FAyDegyPV9Vuo7GcdX9D/nHVM2E+h/XlLYnD1OKBloxA/+qCrSyYFRK5ND7b+npJ8KnUUs0ebi/bY/JbRPY8rjoei1CKL09uDZzFMyEI2LL8MZWw0ok9f6DQpZ/a5msZxkQEE4/unl+ZPiO+99qbLk5vsIpW+oohH3000/m+cgHaiC/F2XSryw+Fc/+HBh0TuwMmF4pwjyXCZWz7bswqcq/qYUenbVZo2+pJo9zjYRiU95Bcrzb7nUt2vCP6tUc1rii+rxrMHtq+V8PztxlJ4KS3AUWqBI4WyFVuhGDrOpawt7SQAdWvTWE0QAxfnSGqOm4ZBBNQ8v+iMB6T44535yd981vn20Rkl3vpaXt50nQyJg7PnuhMb+ioxBIlvfyVtWudKhA2hEWW2JezpnPdQ4lsQ6U3rSXajGK+wq7jjMWKdq8MVNgo6kVXLQhMXNgRGhvjLNHU6K8HY68QI96Jd9wcsNAoCUA1Yz8ub82skZxsVMsVGJ3J7wZ5AoXNMw9c9LcNBTIy+LHIE15MgkC2UUtcdO+YR+D5+qgi6rtFMoSIVkk5j49XtkIjCv3M4nBrNqTKd531tgL6jkdUIY59BxtvfbUPnBkm36fESh6ylirEszbCRqmGOxH0Tk8fY+nPZKvKUmX4s8ieUy+OxPdSfGoY1jlEWZ7SdTILtVDcFgedGOehGa3PamNC7mNZcbYXD4EPJyQVCVNxBzFEm10hrppvzCHCLx7Kedk3lwaWwTZzJpYoNTSNCMwYtXphZ0rnZ/EH4piExtPZY3SOyc7d2mPL/c9/b3ESIRiiaPRx2CWvtVGNUDG5iVyOuBmCYjp2rF8m8pwcwaiZwpR0MdEjVsg+21uWD45L/3nJ5xtKnZpkO3mZhJxCUeUmyE5TG5LXrmF1SyprDlFElmpZHMxbA6mZ4zVFOC3lgfgKHYLaddqGsPfbGxmDP54mvkDWx+yiehizX+dXTi+MCpEt4Qy8MnkFZ4vKoH8EnkY59Xe/5vIdEupTTZIkAV7cOSg1fbWzR1O/YXHRQNNaC/i8b1cZIRbRnV+RCFZWpwpceffFT+LwrFnwz587zhuOYzC/2urh7BBMcT7QlvoH1C4qz5DPDNGap/yUoQcmIYuoqPAgyJNsNWitpnntmCLRX6zs/Q5UfMaYHI5tkXf5c8pYXySWe5Wp9VqQBEbO7eJaojoUd8MV1ZrsIBkKJQhdFQ3Lt6RZNqSzyL6nhlyUuuHlj22O6JgSILxzM+JJqoNYRwYLN1WyOmF/rG/zqqI7/vhiUQbnr65SJwkqyVv9+9tZA2DzvMZAOcZeXtkKQq0zQqge5MdNdh7rYO4W0LNQ27+g5sRCdd9pFYfhbX+BdpOJra/JIbwv/DfL5njnY2OaXusfDIJHHmr0rifG99aVs3+w7w0BYLyF61zcEbiskl5hwT4tYa17Ql32KP43dyBPE4eFd2jyWVcUnmD7giea/zAmqOTBO19Ko+hf7jGb1g1/MdorHAlIqpuibfW+zOqR7Mao+I7kPPgmwA+eRwBITtgqoj5b2uo0wfjRirMmIMvZMRBrUd8S6rR7owH1aepU4roAQ63YTN7lol043QRMEQxKTuu93C6WpuNwAsXjQvXX5u0J0kf5aSMN5rmknj6P0pOCYrTpJ5bxjnGhwn39KHJcswKnB7ojZanlRVpo72nj3tzaoW6qWAJnPymh2EPSWqz+Ze8UJr+auRkSyVn1qNdwwkcMeVAqlJTToNJYpUEfEHbhmnOWN06SBlqfxCgS6HoRBtcJwE+1ZQNLz42U9vSpc1ckPxg6Gwrw1P8tjCy4hrMBIRdVWEaOCFvniQINmn+5xheryDAXF3KVR4O4yUHAd170bLbOrPctu4hqQYnCg5VQepuAmwZbW1kAXxHxROxsPxHpwGFKZ2rTIBJQ19uNKRsMWO4+zs0dRl+Eg3IWmd/J9dVRcgN8xZ+jsQZy+cCxUMn/Y9Ha9COB+Pjkr98UNguSTYRKwX1de9ULlRdRkASkDERFA2icnepEondYER64SJumZwYDTO9z//BjFRCaorlradz1LfJlsfxOIo/Za7muxNxuXZd3+XVfu2TU/WoL3uc4k6LjVdADCTnhy8xGu+N6okX/yfySpCyw0+1OM5XAVsDqMTlTHRajecbzrwa2VuE25mzO55+hXH4vc4Y/kf1t0oNr/XIdSgR6bmc4BSNjN0E6vhs38oYG1DuGcI5I4O8dLeAFa0k1uBGA/sY0skDrWWK8uLgzV1RcOL4+OKDmbgaZj0h5AO1BE7o/T8z6CKFsAMOFCcVy8VuUD4z59hZBirAK6tIxBERXyJccWkbvJwSLbAcJpreagVGCdrsWyvmOT9dy3CDQEWQ263gUkIqyW0/kbosimTJDwTDuSG69E5uhcbz3ClfLVsc12165eF4eFuii0ULnBRfpEUg64CyurG1OY+uxOidwyuMnsj+vlH0i6fMYZIkoea36Zc5iag7PMlFTQFW/jCCCkDLcBrGb1BKEXxX4OjbH+O6Y3L/PXQ3gJY8jV4aQ8em1B9f2u+Ib+su9mr98kM2yKDG7kM01PVCAKLGIJSnJ9T7RZiNtuDI4eX4/L66xOKNDNTBY/8h5JAk7d/V+KaI/zyz1axU7Qe6EwDCJOtkUz5QKbbvwE5LsID9hhd1krhzMg34IEB2wgSakBBl1SY2aYUnPGrktF8AErIOVe+e5okF24l1c4gvZiLpXtMSqJGX1TOhTcXu/sdeXTOc8VshxGLUv9TTYb7GABo9NFxCjKI2nkwtc4HiXFSBQz0+Q9TRpIQQJS5STKgMz0ios4Cn1aWb6ZWRvNj+guXW9dKKKYuO2jowAN7mbR0ySHC8SQx9SNoEnAgBw1gFpZeXarzRM8Ewm/j7Pe1QetO06RZSOLco1A2hROKSmHE6SqiIDZ1F7fVo3G1M5qvnDcUQEcrizyRA3gUXhHlQF16aMw8DJi/xUN8yqRJzWIyI7vngu8tC+oU9rhQ6yefZQ81BgwwLQApA7ChB5jDojYdvqcZ8zE+05oL9SsAHkW+kdhC/GOZs5Ti7NTZaqP4svr2kmfNvENCtASyAX5hMH8sRQbypbWul525K1Q9zmXj3bryWCPkouTU8JBLhp/W/QBWNwoESq7PopLvEFpNoO8V2o3tAJXay3SI+CTv4M7px1ukqMyNGauHY5GJfmE9tksEqsUcNqkCLiwpAWqZBpnIPvb22xWrDJPSStBKk/i2D30ydMHwWXIL9gW6D490gi8Sj14jKjaG8mu1lQ53VfY+jA5obic/PM1D7Qq583jBc/hi1VAcS4uXt18KUIPEeH8Z7NApxuAM3P8lX/sTCX2ozohF2bS3xQ+JI6zCPbvulgsiNNmGX4+SgLcjdqR/+W7ocU2MEENwqoBEd6crb0fjBZYaCZ7HX41CkSX1eF47Lo42KA6l2KTgm9A/YstnrSXIiWrED+gtnL9+D+VYoLgLPRaKKKqm0kGSocqpnjNQ/+yZ+Pe/yNGa6oniqjmp6fKV5lX1RNK717Uy0hZcLQRYfpG0ZjQd9ptFNBqQ3N/tsC9hREe6k2AEB7mbFFQR5zR9qoWMyWbb4XT7sp868Ej9CPjb3hisOFWj6bpuXGnL9hXKJejmgSzkbCVUv2eh6fIz7jxlF24Oz3QQWUKvSrO4YNvsJGQ3sNJcJTKg2/NVM85LbNJzpxvOtXQCw45jgxSIM5FOViBlqTS23wINLiKUGAZuVZsNf0OzxlVXncffCvEf+h/XU7l72TBE3lS4BwEfaT0lBeIFyHgjUOctJEdpFuMpmcxnazgWC6m1BvvhVOBDwDOH3L+rgKclRGkknt//lZQrhRhRu1t1H1LygEz6nR/V+60GgS/VvG3ZSfCkJ+Y5xMi+Id6Fc1QsBIkvivyw/HmpKF6wJnNjQX0u97yj6ZHN7gRzfyUxkBWiWNppXiURr6rC8CqtVozpUzbD5v8yACSwJlOs66jh6mZykF5lvZfEbWLKsB2tcEm3TXkU77IQlPwiBYYfGwlkouErDpYA6PVUlz0sIkip2z+LesPYRTX/bjpTx3aGIXsP6MIVumKZeVoOWXNVcl50Ou6uie5tMAGwQxWeCyKtHK2MMxJkVx74LaOD1mv95vamGT7XyaceuHVmyRytV21/ixvh2EE0kG8yjEpaNQJdL7eIxNrvXyR5fMzvKYzo+NbQ3URoccsiMcPTRb/AmL+hObs+C4YwlG8bJ7Lyvg+9r9PTmr9GrhM/NB66nM+Hgs5MLZE9tmUASk0UVBKyTwgivS/CN0DHsTFIsl7oHvbajm4vpW6nTFDt00yIpagXPPF3dQp5+auGEcJD1mUN6W5mn8mC5A8TIkVz/mZRX1j2BnRGSryvgktf2BHCro0F1x8dsxEdf5qx9D6051d2bA9svmZUBixESpDpvM3gvjj1l5tSL60TNR0T/8zClltEoOaN9EQLXeJ3Bh7XgRav8ABP7trqa14Tvyw3+nGILiQqOGCaWL1efTSA7ECjMJmKgPEOcw67xiv2ijnkPQydxZUpKeYjcyTssjjVNeZlpN5fvx9JYsNpOgegXDpPA08LTNbqZRbV3Jgo9wVPF8iegGvplY/QCrny1jZSPHjmRjgPClkgI9M6+Yb25NjS3w4QOq5GM2Hi+zYfuhrA0UeIVjwV9Cnb636g0wJjifJevdPNe6Slq6bsjw1TB6LcYqXIqp4e+OlxpX8K4nuvPdPMM+YfKqnImmUJNRCi9lGU6p7b64/jCNpKsgRoFbyYZEdE7tqeL4T4WVXgwt7rx85tJ1k/RMYn/bsgKY6krLH+g4PIIRW9AUhVT5gixUsRMXCk9Dm87gKSFPkEMo/QDzcTU4PMPgsqS8AWrOGrc5cRebhoUUV5Wnqqf1IYJ4BE/Xurt9TG2IoxagasBMYZDAbhDWsp1vU17idIn+X3/a0pCW/ktCenyR9yaVWL1xTxD8Lgp+QkYUkHbcxc9SvHt9GW1bgWVoy6XI0ESQ1BnSV/mzwffCJz6BNJzsHbulv0qg1UBFwbdHC74bmZFlggn3PkbDjs4DvErV05hO2BKpvHovJxJQVvRuv55oiFJDbbTbGqtdUMbZWhNhDACYmfG2ZBEZLKyBXFO6lJ9fR9MIFdrtwSAXDqJTX+LrwwxBul8htZhsHAs4TmMvTllnJYnqBAVdLEEFm3sXG/kMXWbMd/CKTH/NSfQgHiWuVtEuNc2rqeX8SqELgHuLQbk+xOEZChGagMOULqVgiWrhwbX7evEfj+DvZq0E2Z/mXDG/A1KrkIUFpaaW8rYMIQcWGxhQgbvK1O0330SGDJt1y6VG89LZ+Hp8IHrzBjTbHVB5Czn//aPlr7KMIX8Y3cwfmcVQvED0/HHB+EKHUL/QCQf3ZURFXCeWTHBfdi0VhOcSpsfcZUe94EK0EYZU22QR+CQgTIglhgtm/YyzutU4ArP9s8DkcPHCQ1wONErtBe3/2Ihotm0XT/XLxcf4IMH9DpxsRrtAqrgBBon2E/5A7y+q3YecqrLNMNvRCvBGMeUE09zT9N7QKEi65ci6MTmskawZo0a0EPSbA60j+Oxb+BSpVQF3R60XqAFWlvw3+iEmrPnKmfarlV99Tvnvt8lm6Q8lN9BGt9jNga9rUTpfdPDD14NLco85tp+Q9PzNPr7mtVj7/Jiyru5rrK2jtyCs0nqlElW24ysKRuglZh53NQnWF8EMYD9IcozzYk2M7XM541qV/vZxjW0SyAAUpFqU2IXsDZ1V8rIV2g/ufX1bvKG543IFkCknnmr1UsbGAjEn8zzgF/vuyl5/Am+AFPJ3xPLy7FUJneakxDJiqpFuydC6OEenYi1aayQ4YwDpNlGitgK6x3A9h7o2c2psWHtKtgcAmRCSjH6nMPrARgQhTuKh0+NVJWdO5qScJ0uXprUa6CpVNJAhOHC8wIjyX1HcPJ4elWl9z/xqwAnhaoxUOZVPjvsOCPvNek5QjAi+JVw5ALot8c0fi+/Eek+u2NXHklhvyaOlpwuBsynnkoUYiREjlbP8OJKU5XaDPmCxgUZvgBrijfUYF38SR9V5Szq0I3sUlcZkEg/8bxF0AJkM46by0gznLeugK4tfbEz8t72KMPLnnNJMpiWdq1R2Z+287qXGU9SaE3a04fC2NDMaIb7OOqWyrzPsZpZ7Il47GBYjJ4Lqa67bBWszTuOUAUVJLxy415qnIhwqnz/2YsunrHLbMmnmeN4C6w1DJSSlnonOzLSRGwex3ZikV+4ut9NKDD1h8UMv1vC08iQCfAR6S2EVsunVGjyePjd8CyvmH4b23Fn8HVYvhUQYNND4q8elNrWzaZjXssk9zaYoyyxlWJwZ5NDOgHCQZcId8EYZJjm7Ed8aVqCcgxwK5RzfjKMmBKNO9qi4PluiTPN5/5vEEDawgxLOSZCH41hDC/HnfDDvEwvSnrqzky6eXr2KjNFkqgJM+vn5TQ03KZtbpTkJryR05Vo+ac58QKI2uFJ7P0/LkwutwXxbUonj1uk9woNLKAu2V1Rxsbddkl/ehdZzKd5YMSCQiT/VBCYnFAgEyOTEhIgbXITRsfDHKl+ztf/o1tJj+DRAN2e1nIUCij/3B9LuPDwuKcOYP5ARiQidInPkEvYV6VDvMjiz4k9Pd2eSrgqIKqDI+xhDD/x9+DYu/b2Ya+fyEbjsSAcn1icY4InMZnTp7JMT6F8jTZkcVgSY2xuFuVTG1QzzEPp9zT1vnQONJyGm+OsVTKC/Z/V99pV2H0FY8SUjznVf5FczkWdOgUjHZcamn7hiKVb7M93Anc3RzsYXQN8jX7t5fPcFnh0BSdWeX3m08+cisQ0eG818NYSA/kEAyi76aXJEOolKMRNBaIiwQBURUwMSR3/m6vzhIFc3q1B1Wj8J72zKJkb3rHroAo0pGShx6BYsvrFBe76RMmK+JLHFMrODnbQL4QjUTNl8MRmIi3yaCtYaooKobFVfK+/wbWGiaYII1n4lZKL/fY5S/B16gYoqg+Hek+sB63qhr0iky8nbik7esGbNxG6mQ562MyoF9YM5rfsOfXZGycGLZ4l5xZjDhnfhTgyY9jyO6PNnH4vOru7sHzZJG/cc/BnHs8fVVcIMKCfUsmDERu99R8jgnyiJ9k4Z0dYlsJTekJMRU2tdBr0BtmyFX9d6Iwb8EJtsQtNQBqBpRVmVlBt0j9XlR+YIUdKNTYEgBlqbchBgjDWyynNe0ZPbYMi1Ss4GY41Egy15gEE6aaKzEb54lAZ45CVHaS4oTKW73HonJkk82xnfscVGnH9cdmj3rvKifInmccz1qoV31o7Liyh3DBIj6/QdwK1b20XAwSWRDUXIdzKgL4FQlbn/fJAxUjO8Ol99n7LUE5fmrjZn0l9qd0BzsLcxz9x92IpBORhfgUY7hRNfrcXEoh1Xc7ufEwguIHsno8Oxj7gRF86VE5aEaY1wT8BbzcMDNuM5gnTxYMGV3lRK4ESRr9G+R8wdfZ6enzWhKF2gSaHTB5+WDaxiSBM3JJ7KniMfMvbqkczEtN5mm+mDHKAzcWkf1G8Rs9rYhbYc6n6Tw8vEFRCOBh+j4Tk4SN5zUvWNNf8JTKF0bbAcmVqJ4BXu7zVhss5Oo1f/sRktyjpimrquzMpIxmlIOG2tsixgIaf8o8PygLYEJWryB0p/UGhixqnResBsI1mXuxVJh/+KKbNMAN48zR5JD+NRmtgLrFd2ZNG3se34fW2Sor+RMAcIfambuJm38Ffi3Xl5MFBEEBFRT7VKEv8vCEFrLSUJOVpLZaXjUmf0XjTHU47MITuAvqWKPX0SSxP7rSNRNapOQh/G39GEVU7pOn3+j8OB89iMBeMTf9A49iIaOOgaOW2xv2geZs34Q7SQE6yCWJM4wJeSlqJkHjWV5wuHuts2aOumyGoo0DcrRfqnVrMPIt+CLU1egCj08+tqDO6DohnYmMTjIQSPCUCcavS4UjgB7palaJ8IrrBzI5OFsuaZHUTlIl4gxUaWTMYwKM9Tm1yNw5PSDikkBV3R+iPq0YxouTisyyvlJQl98DN8WpD1Crb0fkPEYr5GNCQo/RRX7f4TN540tKr5jVKILGKq1T1E/oo5f/q/fVZTtE+ujO1vbsosd52gMKmHj2gELKd7N11KZ0/Lq7JeKhK1RndR0vCaxpY1t9V/q49e+XiiknceMoYLfCwBC2Uyl3bkpEj6VYtHRakpOR3LF/pAM15HToF3Abe/tuniJPBWme+86qKITuODOc6TQVjoHtnA2w7wj3ut9tFdMCVThNn1lz8HqZJgvWB+n2Ry87krv8tPrh+hPzSmr5gPL5AgVG+YuKKZ9X92DNqwACmsLaIk2goGA50OyS+fZDLGp8ulXmNjTfaI58r8h0ifTj8ANFEFTBRQthQQFS2Y57SvGrkYH8tUHnOwKGALrhj+45+Fmi8gqmUGG5gV32ZmoLERoeOpv28lvhOtulrd+LHwyokK8jqo0NfT54NaLaHuJd/sUL4O1md/Pe9xdmyObImxhe66yQlRDEJflrPNb1rAscJPCfdTmhyLe3OfrGhAIpzUzkrTHKnwSH/7uU5atv1qri5wSnIrDj62ijuiwbZVp2bNWyRxWFJ2Zq5gw52mu0RObVNVY/eMxJufmfVM6qYDebmn899nBzo2x+mn5LETcTV1nSaM8WZn8sWCaNHvUdc5KYxVoFCzXZC/Z03U5R80RlsqxBse8HVBhmLy8+oeGNccAC1pCZjC0kDNo0xshNnyK4LGJpHrnuJK+eFYsPU6Dat8QmoZB/sOYN/eb32eapFZMK38spg51DE8LlCpUO1yd54bvVWoPXUwnnIMkqQokmddAEXrjxcqfn7p2lp+4Fu+LHabR+jTnP/8hjSJh/xWS9eTCi1gApsGdGqv5dhoFvl4DNn9roCKHWNEzpW7MGbh/2JEoSqzw8/p+qvbIBVM176vbJToMVconHlIPMQIY9cMoK++RAB/6UzgkFUUeFqvnFC2OOfk503mFJvNCMjthzww4gNF7am3TSQEeS7wjsajWvfPn6iGk2oCHjcTtiO2/9yBGMamGDHsVqE6dBKC+YBPp/6lDP5I7+Eumo0lepIviWzLg5IXOpWY1VM5hZJErXR0C0FA13OyNDBC0iNOuY1z4en4jaQKMZTeJQYRLpQNyYaT58LoNZmhrgoCIryvvLvAN+k/7KLcGTcVVX1xSDS3bfhXkdiexGmLCLziUz1W92N8FXVGFKTfDfLI802REBChP84mmn0apvJ+lgOOypiiPOhspQGGcwGOQHzfc1cwn3fFqdVIx/hKtqMTgDHSwBe87Tg98LqVuiT7J+bCDTXPrvICg/srHyZCM3+dbRCWhAqKWV1OBS6wTxX15iGhiBAkUuT3evjAOLwqy4Z+hojzxXXdkoVdSaErjpz7mjwBIearlYFaGHVhnQIxUzrEUDBJgV0uRsLHWFQyJUHpwjxVwY+iSvzEtareXDUhyviy7MfAVg32RSOxxQKbTC831fYNWR0RAwsDHfcO5ooAnGjA7g0UD+vy6IqeBrs4qbv+ZRKZY8+JtBgJWlXknDXB2Q9XsWmFUffUrnCGp9rTJNDxgDmzJCmLolECT2bO/LZn22fZi8owioek6QlfqwhTv2cV3rEUojsEmCaBo3EnUdAwQvJpdE9vBXXStmHB3ZuIGHgJXFPZzYLIfYyETYhs0RnISsCuil9aI9bkiW3yvH0/uSb2t9tVzgGhVAkctvuyrKl6R6SdLIwRIzmSwiYIeLc9bBGhX5f1z3FggkEVVWjymlgWyNIFLTX7ahNMZ0m7R4qK3jW2RDX1urep5h1z2yYccIQdr1cdIZCuUSZByDEugr0El4Q1MWyGJ3bPb7x0rae1pP2S4g22ExEbzBP5yrztonxIQ/Yc8C19uHgxlJEns1Q/eExuq/ohs6vTacWIuB3wg2M9zbWoo197fUxqBLT40DNn29NrAIDPb5pPXPset+RKJl4ol1jk1T3Sbv97jQ6jy+OXp08Ug/8kUW1UUDuVZYkrkNmIHPQVS4jLRTP4YZNo9TrLqG31dZI/NIJWpIEXr7h6hBsXWefVgmaaE6QhvxK77JwRE8+FhraiWdEYRzWPKZsL9FmGqirO1QF2KqT1LI6+yz4UDwE0lacxiZg9cxFWDL4VnI7CQFodzPlL5E74OEYtao7/ZPVwZI8t+QGBBl+ACTEOjXaFsH4DchMRAXhgX3quH+nQHgRPM3NCGq5q2C567tijk50F6akq4p/Gx02cdnFSrbSSzUaBJXDbyfNY7fxDsD7y3Vhm34IOnGMvpfQ9Bd1AAtwDn5IAVetBk3XNZ+o4xbGTZDu5jNzCSfWJcPwEaWZVgP0T9WmKr9pSHYSfedWlFlW0PxqUQH/KJfl41szl1f/8JGUCiimRRGffy81EgP25a+95PuCeRKld+IG2zdJ/hhbQDRefMBRurzlqJr8oOrFk2MhGuFxU+ZFRSmwfW1FLVthsrZ2uA0dlOx/nm8tuMw3tFwuBmC57qRA7ZxZ4atB9Qz5RVklqVNNXAQIHdL3B2+tLgkbF53RgbaMAcMb+T/ub8SLo7MypgmwKRSzR+oEOLYWoxRO5AGhDH4POgbAuDStTZYUB9fNls9RYD/hx1EbELmPbxB05v7eQVk6KYJc681s9w4LWOQ+/EYW91+5PaVCou9Xe/cdrYJhPPsKxpk5B3cf9j24NkWFjtZKnvNhvZihnzI0eiEOIUDI5CR5LWeDY0qstkORz2uRimTkFD3TyRpP4jMPDofZ93eaqHYvVwPYrmBcPuH2rRC2RObx8uv+KK5z1q4/tucCXVQWRaQcO8sRlZXuhZAYWQdG06yYrzhNb+jluKrucrU30lC8Y7K6tPxENZIPzvImuozdHJrvCOKvdyt9Z7EuTg4lOzuUonPCQgHBZQDEXtIbvZtQUIyCw0zlacyEU/Ws82PwQO+3r4wiK8yatuxQV/m3Cf1R8BPi1cydiSDr1XdYm3vX8yZ5dZRvUiEgwUX6RnOTaDuLQwKS3TlpWTnc7pdayBufQE0DG/1QeiFr8KduyvSItqcMy8J00AOAkc1aG+FKl4d+TtcT0QYqXFHYfk2kLpJ8fcvskyl0vkaMrIAVVjOFcSLqKUCsMw46ThpqwCD66lkZ7lnS5tqKfpt8Qr9qBVey6wVuFT3EXtOJjIX+pkXQALzd/rS4YSLRs9/wMkPOEzKi5MNE8Ltpa6BbnT6pe0OWcUGcqP5cFHZRHATZIbU9ouolvjmKMGnv3iwdzDCnAg/fEcwRb3DCelGfflFoVad+2WwQ9omeVZlEBJjxynLusF99Z0D/QW8YV5gpjG93NjNDKPmQf5dUr3ov6Em5Pkc/4aqXxEQd1SdIXML9Jzyu/Kt8hThuKU37RGHsj8IFnNNmqebdjYWZaEWwPB5tNAbjUuiPx0JnzXwy65CR3qm2TtRlM4PRrOyaxfYBsK6JvwSi7ZuBBMqJgGPPRelm3ptM1SLhbNnHvqLdajWGpwu9jFWoPfwMyXyTGQntdV8Q9jIJ/ke8NjjnayZYhFriEChnb9nJ/1sTl6v0Mgx4UgN8Ro446ThiKRVeyR2lFLl1U8LKfJQGgg9NUO9YINgCSo3bQfIV0Pvy2QG9Dp6GrkXBYiTyBvbft4cBkLnau5ZFb3S5dRq7qQCXt30yDdV562GeyeLg+gRuJqjVJo233a+vQCuNwj4Qjy/r8zu2KrwcoOZ22TXicaHQOX4W2GEdmgzrVcWc3NSpX4Oh8P/TqSxqOc+Ps+CMAMuzukpdpiuXW4LYGKJGNbLCg1yBVsgCGV9rlVeFKrJdt8U76321StlIxv4+Ml207lWhQMSJXvsQYNsmsVLVA/44LS/HjS/aQNCIVWvTGmIculenY64xJFu0N7ecp/QUpw5yLtbhqowODWz8Xxg9vAeGwizn2B9V6WGWWB6q2yMLwtQ3d2rOOyb8J5j0x7SR80YRHMpkFtmlQBPIY5Dnm0UcLt4eZy8HwpSNoDvsA5vahS8nrs6V3IdgcOlzI/k2kGxmjU9s6gWUH2+0hKVquqsg7gwaMwPUetwlYjlAQWHxl6/n4fx22lZ0QItVc/MIRLYVenjIyWj20njrREpR54pHrkBPfu1aXzMNeMP/FU7iPBLt31vS46TCZidlpUSe4G5ccbY9Mw/oz8nVvrrWChlGAf3NeziFeufHG1lO0Q8GV49wD5uAN4WPA8BWxpU6jBHZbnUZfNeCBvr0EqYwZFq9G3LRGnXNoHzLlnbA9VYQSDv6qtdlrratj1rXry08VRu5Oqj3/y6K7OizOKF815A789DpM9N6SlJLN8w8GR94sFnIcdNUd8LEQhQ0FtyBe6DfQXaQfDatuyWHmqvZeeKbt2bTkaLplsXPkGob9G9meO3CqmBJzCH6qAF46yN+BnKOg/PDcbWZBmFZfU7w8ZbYKtU28CbbJ7mdPmsRHJz1MoUC3ATd6HuCWNuc49YLXfJV9m6K0KvrUDnfg827KojdcqhDOATYp4nO8Jix5h17pldXwZpJ8MH3APavnKER+pGVMCclcELv+69VUGVC7SpmK3QMRHTVQqbyq3UumGHUffpiycbHitXxFoUNXKbHqqXv3CVqmCoiqFLmIxNX7sWlao/A7FzRfihCPqXYJJMVziQ3g6/S95TpaaqkKeVEWy4XcMwCXzXhDvjo7TqqNrUj+nTJDu8x76iJ5ixOVmc4FrTMaoClHgFYcuvrD4/K66pAjrjgLiUhr968N/4+2eoju9BLI1bka/68HJCrzWaUxyz0tHhyIbZMhRlEEcUTU4MpYa530ETd1Epfdxu1urG3ITIpkyjnpPGVbNtmSfbdmGmdOPiQehlwmW55Y0VROw+66oy5P0Klrp4A3KkKuJECIjDGXVEWzORhsGS+y0jdogF9I3Dk33VidGEjKPe3vAHnREJVHwFDdvqgv9+KzBL3RN9WLCx6yV5v9xurlscaeNgYPiUMozjh0yEASsfatOkf+NItdwXHq0Da6U4OufNCqKJptZ5W8ShWkNgO05p96vyTyZ5hERRfeTQ/40vTE3Gc+xAYJIOCTs6qGNmSoTbkfmhPRjEj6Emic1ANfNxTl3z+d9pLu6txTS+kX8fqCNrsp1bYVE6wosJ9nYz5evrnxItKaRcscUB6rZLmaAsxKsoQppysMR9J/rYmJzmWXUVxD0LOVUM51KNjvLzHUxpQEDqkNn7ruXJk9NzjgjTIrmLwi6GWalGHIng5Sas2Wm2NEOuPjcHJhe/fT41v3cxqo4I5ElZwpa+ZUJ4r9zXmywjgIU1iwZUO/hxZQikMrfyRtj/PfUGgYQSA7oQck6+i9PZ361rSsHPp0dMfDVClq88rtsmhAPkUJcAkF486aAnGgu3dRLdNTk3b9PesqtLDpBwNdiXQUrx2RqbYMOl6slsMLA4iCqBtkdZX9l+Z6F99CP3hEDi6MJNdMfdKh7CFt5uy9SkwfwnAS//VuG6Ob0rGOwhLA1iUfdoIytSxMUmAJEnX98NCAP8r6dKT2IJvJDXJqZT/wCnRQ1fHoqCJDWMsGTQOWWCqnASTWyXIQmkdqgHOmxQ+R6Arbp6pOnq5V9APaFUR/6TgOUsUo6WmURzgQZ47bZKoGQKsHn5aH0fI2HXh6gC1O7fEekcJPRCI/27hbusEJico/0NVDFLVtnWjbZzaMaYfGuO3zPWSvxcOQ5kaN78yHRRu0bhSXvqI5AtgyV+ncK2CuRwdc6Os5Sh6k+bEBODNGpfW6AA2mK/bI4ihiEB1YZlbsb6JhmkGm+jSSZ4j7b/LQ4l/rB0SJC+J0hct3PgeyxQnfThFsqm5PBNmnM8zOAOoElta77gkO1bAJgjrja/Ame5PuTkfeLVBRJwp0SVy4B9gx/5nA/isKNyE8UZ8TcDEmmw0PGdzAvGm87SB8svRxohc+cmVAPxy5zGTpYnROcuY3mPtJY1kx/uZ9mYUfWbNszUfpM/FedWfSNM7PmQ+rVy9ADrsBTL4pGimOjwU7gwQzlg5Il6Q4vQHkxM8sMZ2X4DFsN03SLBTc9vVaHpn78lRnTexZxTJxzcMalVjUhzJS4mowBlb8eK/N2A48OT+uhfttSOiX1gM9K50RSCMoDSpUdzAt6NWmSMgnt3Mee5UQbs+syWIGyAYpymn+VCp11uRxQV6YGuAvKd2Ic14jJdSP1QuY+g2Ox70ZBZ0RXYXvKHO/11bglZKigEyg1mHoj2kESPEJXataQ0xycOHMLVS+PM6hcTZxoYffxx5sA2WSrrcowpcgWxZpWKBlR77iTYIP+XoOECyMfyj5JSZCIrQcTOAbirJSM9eq2iPX3QCtXY/C32rEUUV/G2SzCN7bIZaKLTGRkQRCaQfLF1CE6CyTJFbcPakr822CAG5vZe6iz2eKsCKlAnWGteJM74LxWwzwuw9DcwjTIz4B4hGIXIKhP9ODM7FqMjdMTRJvsKlJmkQK8nBdIkU3PJhYqDw+7goZ42SlNm4G93kVBZ1K8vYMp108LCkk1he/7LG77VVvEUbNmzERAsRvVwcnUGYQmpNiCJY0IwONrarLpodGTh/X+jvjDxGmP8sCnmksc6b2uc2s4ldC5Lks3GYZeTVQubvYckEigWb17rerucPvyhS0Fy8R7JJuabH2VbV69WFkxehofYc7/daLJiug0myNnzw+KUmGnKieWqwaPjMJVWs5FB+l5azoLjKkycGIpnyE8YOOCW2c7zWqIVgJ2G7cpfhODBXRfqslD/AgzknS0witCXWRv+r4STDHyoqYUoeEcfP8I2QRXMAZzPESSqQ6PjtLMRBDcGeJxpOq6hklMQI+pYTNYX2NRuA9zh+jQtP9VQnpEvSn6RYRyfGgTpYg2nTw0hzaEi21PdeOpGVTXXWTYegecSa8wIjcz9JuaecHuBsnIDmP7ZDLB+9tRTYBZgsmUtCb/FEroCQ/v0I0YSPcxzVLgaopbDFwoH+P8tO/eSfSxbP4XblCT54RBEQ80lusVy69pOEz0l5R5w17GobtJDx8OAhi6ipB5oCmCZcr4fITC8UoXq+EPifgCfVFA2mqbjHOYdZ6se8GslLLtONw3BBUMp7qr9MB4igmrRoMiPgRx+0/mUl9R+bft3/81hBESd9gLwejKHDSOnb4yOEaWjN2qQgq8OpIH7uK1U3QxdPv367zBngYhDKSXobT4IoDTL3eiCI8l1TxabQN616z/otmOuVaqxyqfan/k9C0pNq/rqiesFSAH1tbJVzT4MkYnOVzJnaWwuJ+HCxrbu0HRORF8mF1EAtuq+vqOd6GAmmTbx7ppjFe71M94pq4S1cqklQ4BiBH45gZ1ZPYXQe6Sdno0eXJTBmiNeJnKtZKdrHkJCNTbYycNxh5y7UzdvvOoDvC02vyxog1Q6e0bdZ+cGEV2PXuBOZnwfCIvNB2bA4mM/Nr8GrEogNXiT6oebnev0lelT5AnsSVJPO3hgh1UFEXHBi+w9A/NCA7U+6djTL8qPoQV7j6d8tnCnfldUFvVGB0pa/GgsOOIfE1lSLk63CESt8rcn5sBBXiAyKOBFERPOBKNHmpRF2guXylah0gDDIyWUcPg0NEDN1L8Ra7P0N0BAsibUXANt5nxbVkLuECfD8QtrdLDghS+UgEoFHQXUPkOQcp+ET6oFWB5JR9wxt1+dvHYUGKRaFUdBhi0oqtKIfLWCNW3iYeOszrlVMwQNTkvBGRD9Kh+ridNkpvegi1E1vBhVI/IeCBvc1WP7zzabBOSMKIdg7IMh1fDQ3d0xZrZkeepmBj5d3rGGm88GLjL34g3CMLiEoD4RKt5h/Jdmec6wEehUnziiausNKdUKHfwY60VzJfARJa4B+tSA0VcuT4sjtvgZsSh2lPSKoRC3ISMkomRW3JNqLxqLs7/l4cH+8JikjcjkcDs0XKMzO5SUajo4iuU3IV4Jry77tfy42PbG55p7IfK0bdbWHPeWgXMnX2Gt1XT01nysUDQFo0VH652YjcxX/GU8bsUhgK8siIDo/S7t80AkHefkKJUrFxfIGbs9LmPwFZ7YirBP6mb4CQyekEugc+0n83BKhIHtN+4lWMBF9vqsrW2fBe09LOvqQVzWjsYZiCO3fNaYJ64m3eYN0RYLUhYGsCsQ88uv6VHQm/5nysrFtFwGykE+6P75AxJrdL6ISX48fZRAH/QKDD0ZVGvmI3gTeBNCUnljYoVY8rk3nlWI3CpfIOnkn2eA40TyN8ApzJuLvhUHcQjRhVmHQ2QAEpPshCr0dP0h1k0vHGOek6TnXXn1b8yDJ6GbifU7NAu782NbfAn4IZPoHDhBCq0rNn7wc/Q3cPSkEOGtxgfwZENGUCa5hH0R9vROQtJqQGbmxN55VyOBsPLx0g3/sRILzsuR/vvAkkXFgz8+LmhUmZCXLwFqnIVYY2/X33qtER0xtVzC8HeqYHpHBbSPOlL/7fmi9VELkrZZhmJJlGBFZpxNmLATU9jt6i0z4W2EtXek36OOiu96DzLApptKHNpqCuJNmDHYBu9Z1p23XXiBGcCiKUseB8p8+QUxpcfvRHLRQe1MOT1JorXREjig6m2XkY+k5mc9x3A44mki51hMiODjvMJPHiyMHUqpAysDQKxqkFUqZMfONF3E3fMdE3PUTn0NhjIR00opsAyaG5iFmG7Ab64khMWR7eiB2eSJ5aEkvZ/JZe8q7U1EW6OmvfDORjTu0m6rHcxVySgJxl1+prkRv3nkohYncRt8gg9uGRDfmlSaSa0FbB10MKjVUnMUTcZyC964/C8Vl5Y9JDLtERNhksicf2y5euqfyim9EEZYTL1jMcyDZ6c7R40+VEganl5RFSTDCtdyf76+RBCEaXQCYW9dd/GlpZrSdoN5tBzzDM/DG2VPQWqPpJLCJ/xP7P4etNCptXL6p0bw/moZiho4AvOVHvpHx5GGcsNZl1kJ+tQ8GavPCj1rcDO2eJqKDV499UdpygIZYjVeIIZp4osoaP3/kA0r2FOPsoikwrVWOJe54mhAM57eDaNPTidfhUKQEi+g9cBdgFQLl7GVodDys/kEtCKPeWtvnGY38C5SbN74CY175BVecxp3TQXX+fxNRxSIkUyEaIqKBs76KxlbfF7/RtuwQOeDPCPa24EzD1GN1CEhQltAwk/63ft6oCyKVKbEbRXZdow6MEpLXHbDL1kNqhVXdRO36w0jIsLd4nxlmGTMHe7thkw1AOFRXQKWol38cBD/iIeQJOMvKozI+i1etbRlZZ1otLwyraIRu3qEOtBDcKpiggqQk5GMB1o6CKG8XAXjgj5BYVoyd/Ie5Kx6Q4VIp0PGsnoKsnlOz+FFt0dtiGloa+rQ41E/dO28VEqrEZE62C1cq0qruW70UEMwEBhbdTYEZLiFRZ+Rx58yyLVnwF8mY3ylJtDrZhIAySlaoll4Wf+WEv1WzbnDyAg83fz8h6hPkoHc1sC6h2ExQhpMRZWbrpHxTEUaEvECB0yQyb1VishYd0InBUXc19Fdaf/7A0R2QxlbT+6oLLz/+FJFo0LvGV9G6UQWH3JHBKcOyCe+tjxp93sBOZVj6WO2I38kqEFiKuJLSv6pMGDlsZub9dK4PVV7jFTilOepjFulFFVlu98l61YarlxkA3QxhpCI+Zv6YXGIf025otfNlFZwVIp+e97smrrjet1I6NW/6ElvOBKhn/xNuR5kTuoPpQ/buKv037R3haeoyFegqF8iMh0RnViYuqZ7y/8TvjuvYZtd+psEX5ZMcs5mYKqTceNrIbG2QP+z/l9pIaxEE10AZao/lyAy0JvPt/U4loGQ+QOmj4fCsNnLwU3qgN1MaM8P1mbHAp4mPFzFvaR4uiXAs8duY9ZMxUo/qmfCkaDU3Y7zBbchfGe6nKDughJ6pPIHKPZHORhDjc69s1tpB+znhfU9O3ICy3UgHzoNsr3ULygdm2rotpl6o11Z4Tr64BwV11M0BGk8KeiN64HHi9J+8yHuhify8GTtyfUyNUSlZdmdJs8fg7Ksf7qVsEGlzqUy5qhIAeiYOdzecEKD3mz6E3ZZ284RNswwnKUX9f8s+YxiBKDhe32wdgU/4//4AtE90GdCpmOPb4yLVH4uqi5fDvRAn89yrXux3pjx9k/zadSLgynTBDNZ+ifwKuIjaVc6h+4hO43AKqJlB2Y84rTZZfSxquAn05wyvodAKArDFehtHaNQePnEwNUyO64KuI5BebDhiiXb9OaPc3+fb4cow3Fqmm6ysjVyDAYV90b2bzvjOYHPLmZlqVTK/QeKyqkp2MwvicqMtFmSS6FSHYSuUVSnFRMnKxO0W8WVTicKAnNOjf5Ntlz/M6EjmlZWmK2lQjOsQkY29CcSNBUdrIBUag2VrH2tGwDggb3p40i9oq2s8fHylOyjUoo/q9jrzHjtGbhCykninXj8lUulivZmwisxkJUkNcDQex0YHsxCHtvu4qhYV2e9QP/iaA0XWmymF+0YB8O9l3LrzNx9wJuX4MvEU8Sw6wNRadn+4rDXnqy9DSlyQmhvlavm90/EPTOkxuWtDNq8O8BMPQ/JlEKl06mYvFi8yLLirOV6eWafMoP2lviO0O/pqKCdPPNtbJ1Wo2lYfG18t4WQDcbSWMfy/lKkp+BZVr0X1oD802jwtJZesMXKIvtmeR0ojaOr/mTu3KvVuVhbklPTM4A/u5scDkRGK2lGfqczw3N2zhL7HI5Jhel0hn8lDtEf7tywrdtmPwn6MvcaJ9eaQJm4A6EbrqT/LmEQfK3WxboMk/2Yf92Y03iq19zomCvBMD5bCVY5EPs01/UqydvMqkfV6o1f8/Ex4/4/UCy7R/EizcHMjYCQZ2LjBz8mlKSLhhng0XxcW9kKYqwwDat0LRqb0ck4mbFvvFJVbAOejwsgelrGOEjfMn3qGgdlHudaeJaxWV2I6xRTb1MvqO2j5ilv8XzSIvDP11Iv3y//Q5bXOOJejDPXA1NV8OOwmXRCyzSJx2RExTwvTV/B5SGViN4H114YSuT6UyOMJyLJEOs83ZCGu8RPoL5u13qEW341ad1RkJpPELQXM71z+i1MW8ATorPaU+V42qgkwU/0inQevy7XS1wmvM72IvB6hJzYJxGVBoDgXwrGfb0wpnY3RwNpPIcW001zClPBmNUda3X43Wgnzen9zS01e2F+7LJestXvmfboXpMrU64Jm4DbKEh3IWD/Dy/kr0H82SX0PXxsGEZQCsImiArW90nBfCFbuhGFGmyDAat4gcy7R0axjRaFxLceI7ogsyURzBxnzIRCJ+U4SuwCdUE9ErX0LpoT7lzEw6rOkKgesAnuld+PCnSm0JNO1YJTOWiLUrm1RzrXLHsmtlSYa4SvMOb94LJCxPReMaDL1D8s7wV5cOKC2Z0AIOnZuu8XPBdGuRSbKa3+n2Mtb3x1lUvt43juCpmQ21UmpjshmfEVlA8fx4ruzxxgmrYeeU4JhzUK1cSvk8Io28HU46G/+//Sa/TvMZ2qwfxCDulmYElbbay4zZ04JcTskg/2eXmWFdvbD9d8u8R8VOUUDY8e4QZKEgJxvf1RzdBpK18tMuN5AzfBAoySKHdG00i1bWtlVfUtZe7cl9PlM6YzLHFECa6N5Q9rzyfRwj5H5k1U3T55LqVeHw8EmniYIf8ozgsbT1HNY4+Ij8P1zyyFnj2iOqkicRlv9miM44asPwjTT85bxiHmHhCZM0zlXQn67c2CN6E5o68kkGPK91c0mya9fgjcw6d0d/cMWLOspAv3lYC8rrhUE+txpuv1zVS+bo4kNYofts2VXCuLtAsSL3EjeSbaym8D0y9xLFogEKsM9G9LUMEEnRyzmnl1bYIEbW0KWJWZegsrRv1al87he+xIPguTycoA1ts3wX8qDZdBXTnxkjMJLeh70EYzzhgvLuNJw5u3DHvzrZQBLAgRQ4LQsWK97b85D7YoC/2yO/qPZXQxIciwa6uDztGyTMVM5m6R8EoA1ZCHE5AFDlZiZg44AK9BLyEZCcZuhtOcKdbRZnKMv1OjJ1c0Ek/IUd32rKW/3D5DNesvRzdnPJZJcmgOlj+koEPSmbjECQi3oELTOrdnaACCrDQLw+WQgmtg5R3oowN1KDQ1A2gFHriyp4zAcFYzBEolCw29iJUkrYKl3h7Cg4/updS5MbIyhuO/9ONqkCRVRcL1jWQHi7K95iRaQbKowMRTyB7qlqzkX3CLlVSY8MNe/jAOr0PNbFYBGRTeVasjF5L2G8cntXEzlziNOBTYif0RQ+NgSHGk61G4u/RAruBYKjia+vZ/K7cbmzJinQIlayUG7Y9oYho8VaENQuNShxW+7PrJbl6ErO+XKgJygVE+QyXbum+FiR8xWUpmHoNBqLrpthNu3MVZKf7uxtJj2jPgZTWbGGlBIuBeiZYI7laGv1xY6qHr1tR6h/7kGRVi0jprR2zRQ9ztBNSkIvYlueOl74do0ul+ai8FFcxAdtIOJkl3CT3aK4h8JhHopadHZzDC7q47Y9zVaS4MXWmQ0q/xprmFqH7BpwV3mqnYSxP4YGVdsCrPHs3lMNi7E1TsLg8QKOAaVKRpUfv2J3qSt+b17/b17EC9sh3hg3OMXGwi6K64SinGEsLqx0Uvoyh3Bu7xF5RUv4+1Oz4Z6i1JAbjCP0kv6eaACQudyM9BIALnxTMkVrobpf3I9rb2Vl8ro4GW1nzRhsvVdAL+xdiJKRDK3sB6CuUM4mvcqVT+KdOMRPR3sx8Ol4yYntysWmTmZ30JsNhrntWrRQ1qyA3YVjhrznsZ/21tCnCYLoIZEpNphD2KIev938OpIBA8Eo9H7P8N1FIVRTQTq7O9kq4aZmia5O0y09kRaY+H0krMZdPqeaglduRWCSPPysWvUoQ89kjr6FvnXVxF+ExXwduUVIDTFgJmILwV4zUuFMzITh2ZitoyiwEMm3uRRQGZF6Y5NdP/Clb/D8Fn18ZBpUhXqjcDnickPNBGIqGg30pnw3thoQRiWjVhSZGPy6vN3Wq5jqF2KevveK3ULkUvG51oqgiDRAPz8HkwsNsfLHIhLJ2DJXYxxw0eqvZh1Ug55qx1v/G8m3T0arykuAVphglp3wFrrVZs3TwK85o0dUqmJzuRg1zB/etofSOXgdxx4QAOtF2VzGj6a6LVPNH8AzhbcIt8fnR4++HohxOEgT5ih1rhtjcYlH0DLUQnbuBeCPI8Y0DwvRx0bSkOdgM2bUw2CaB9XO6IMSSavUHINphTS6e48XMenYjWjODp/Vp/m02KqzzOfI9Lus59fRqXLR8zXGydeqUHCCV0gDY0SacXAnLSQyzFZ1RsbqSEKaAd9ypbFpJYccdmLL0qpf2oUX0HJDrRYFLGPA9i0B6Tw8oyhVFdcMqkrOXgYYOgCxW+KXftMiqemsoM2krQ7QWRJzkC3fSySGmwy7Ct10UlJX6vjMX4ugXkZIS8HWMd9T8mFbNX6Iw0jU0Hv+gxya+yaBMyOFe6rUE7GinPKMhnvGQhKrmIFsVzF76yU0S15bJd1O7CAoLA/mFs6g/KXP0XE83X8guiwYTPXoj+bbCuuYDusd011CqHTdxwAMS0FX9fci7i9zmOJwVaQncvOv9foIPHpP6SZPrCobp1UqHywH5cVMzmIpCixkrqpn4Zo24KkF7YLAxASStTJHZifbt5HkuhvTpg71mGAHkQEhFVv+7kAMTks3AbgWdCq98/S3r8Ha6SdEW8+J9DCWvJn18Qjs7TP05jcld0tAtWMY3smuL/2MAHQRWoHRG3QbtRrAf+RRYdL4C6hY9mb4QwjnXuOtTzHucR6UpwREA6LmNsKN9fAwu9ptVjYuVEowyxeTgTueIw6h1Ooo7RbCzh4Nzv6rCCML6IgcvRJcWgpuA2ZSrDGImdGX6uSYNfpIAFKMb3TS9KKjkMk/d89cMz0vO5rq6SWiVS0srKx4VCXAcA1qSFJBOn91/ua7bm5wj+XRiW8gl8c+ffkztIKRD/CaiABfxzDQB3RCi5qtHE3yWh9wJOR6/Gqid1BRxHQK5+meEZdtBNu0qGZOit9yVbZ8SaLAwfBhP4KVvrbf/pdjRIuDkv17F+8a9U9FUvmFHmFke3jeQEuhMqXTjTC1RLmBCFs19y0MoGdKo4A9XKUV9b0bpNhRO8EZg0wO8v+DVHKIaks5wNDnRc7rXzoqbUU0YP0X9deOmipye1rRKaRbnr+UO6zyuZdAy5McwzLIuibsBh0O8zLQxq2Pm8gX/UE0WCgT0oD/C7cTPxOJrETjob1ubNARVew4XJIR3ElpGoQbGD+oR2TCJej18IqgAAdxoycOPyOX6IA+j48T6+xoYKjHUioYWguQko2cxYGjcXIcF8nG5LPOaFZV5ATMa1HQLzNdnGyGTX7Q175sikhsV8eM5xgpQtl/ERTSySLSJqsibJA3wq3VFGqTIY9bC9Wz2gxJXA39Kb2mIvCikRdf/+PnFjexHg632iz5YlNWenDxsIhj8w1LbMySnG3c9kvIAUF+xjgr5T6bUtw13/gXGNU2g0zj70Jce+RYOJh29l4yU1ro3cc7qVnDlkukEONTuZNv6H5wb2JrZ6otqxM+fS+7FZyuxA8dlxkjRrdgfqWZWtS0hmoWAjmCDeI6wTWqtYjE3DEM6vPZhphl66cWXFEKkq17M5hUjUtJI8J76KWoecjRi8idFydDrVGM4WMpAdk2MRVgRyaZT5P5n6Q7BHGxS652BFP/Xi7sFQh6bsyUlo7jTRV6SDDBciDR3k/D1FRjib5BwCoFks8CaIbVbswOv8XA2YRf1J38Dth9gjHdHs9ec3S58EtLbm197Ni7mDQih+Ym1bDtB4hStkDNkDg6MUnBSdIEbHL9ztCzw0I46hvbzNqUYFrIsyN55Zo03RbERhdfeD6yAvi+rcg15VSzJ1qt//lDmIIaNu5SxLfgtyAD7Nejd5aCv/nB2LoHfJ9oJyuwFZvRuHoD2Sqv1Ba6P+Wg6L5kVqu9quJKzEWJ/IYqXoXQrwF78nwykM5NADywthgl2P2BY6IUjFzgFJhb3s9ARr18n6lxVDHwhTRlEH0MmeoB6QQzjuTKDPTP4G0x7URKODT7j6n9TEhgtQColpO0EEhdQpon4x1MGOlhE3JQzCCclXnnl9xey43sYRpGaRgFwudJxX/zUFBxMv+TTMSdSa21UESrtOcKOrpAgu+2aBsNlkaGMQgSsnLAZ45mnKcwdZb6ykVcEPIS12mc/uyaeJSW+Tv1379Lmd50R8taw9HI4QdlvMTf6O5XbvfQReEZR9gU+sSRLAKpr1U4r6m1Yf0STAxm1iPQf7Z60M4AJKR2mI62odGP+xq+WiMQyVi6GvDZghsb0GVp5Ks5QKdjw7j34sIK4bVbPKT/+62O3lxjg3HbPxSsT9go+0XJGqlWMs++1S8nSxkDiIMiqxJ5Hgz0rFbuC7I2ZsCjkMgX9mDoQHdPHF7BkRspfY5FUi6bTU3sktP4PEhyUHQVt6FOBALHHEPpsY/20/wBJiyeqR7r/+cPW2ebD7P3rPSaZoMuKj4hZxXpAKx8igmgQE8ipB+0HBHV4aykYL4OrPGIu+rVD164D5ZcJ3fuRMo20sxHd3ctBYL6i/qnJZgd5S2xjOfDWuBcPsUd9Shdf2VcUv/WApgfLQdMMhCLyYIjjS8O5M8b8aF9LJEwkPqCXZ4gmUZQOmh1WP6Vis4zdNsfDFLFItbXLSQA+MUJstgKtPBFNV+TyfTugUGBe6qsEK9ZoFn+S5HbNVHl52iZB/8eLGAL+NMz5xdbVChqXF3tz8ka867z1QqUjHvN2NETmirsWMCD8+eHteeZwzomYG9KcGPbBdIf9inWmbMff3Kz5Gii3S6jx+0z5/dLdpPXJA/Q2XkMzyYnT+17bq1wQz/TC9ZvBpgvcqPWxipM1AD0gmdOpbf4tw+wWLuRmYRr9IZDlqy4lNamiubZCVTNWPYvgt3smodvHhIOIibv6NJZdQbAb3ru/CThpr4yPQDANFn2dVOhsR7gRkVTSTGduW1DYDunhy+pPU8OBzBevRirFSSZPKPgsH6ZPmgiYlwG2rCDCLtkA0h1QlzsVvbFhPW/fdl0N9iZmnq3SoW3wwmQnsI0Al0Pn6zbeSbM0tlXcTzjxSYT6UIAd0i+ShETzvLPvNmiYyFI1kDwTNa8GfP299nbxtvNgfsEf0RTeW9J272bdJenAXUkO9gxPHif1OtkS/lgFdZxpJD+a8EJlt0BT1xtYhptO6jpAB2huwaewjDKueuhXX7NPa2TmlfhOJNvFwXLqGE07ifMm5aoPJjSCSzdkWBO1LEe7DaJrbwaxnKU9/lVAWHq1Blavt93Kw8oCpgZofxs9ufX4AlMS03nmnx8srK9RvwEG4vXakKXH9uEo7tjDqtTbJaJirqqBJWgqJBtUcT6eLoD0FMhLyi5F50YmYn+RAaHX9ht1XhNYOlzUhDoFwUZUqJq5i6fi9cUp7V4h1UH0Ol7t3kSlCSgjYdoA1UH9HQvN3fB+sGUW/mRVDzU08ry9sbn8Dr102px/w0DLJBVA9N+wUp28nOTPY+1pEHXP4/9H4SCRnBLcTwL6qE5eTn/v9v8P2urxOyAU3c2nirlzWaf5IHOg7T3SBxObwZIbiuC+Dq6TSxCMTC5N1KwEp48nBMhCtXISGh5v9ZMzKjQ7gltJhD2rE0rR3N0gz65sOL4vocT+9zr9AsQ97vZ4xzc5AedEUPf0YEN5R4VTrzE/OsiEsQczjQj7bNNPvqmNpfLnt95ezyHMax05QIMq6Gb9qNthKzKKgLJ6qVGL+dJhUxhE/Cqg7PGZQtfRwnPNGqVBTlOl9QWzypcH9K98/RHtGYNYs+SaQVKu8JYCLnuPW7I2Bblfgs80HPrqgBChozLGR2Tjijd/McaPHZfODc+qft3CX14ReBLZl3y2bucI//TLqeduoj1YqLXZZCudOkix+MhxJK28SnzTb64zqX77wDMviA7YSTUaZKPF7gw9MIVtynN0DHgr1D90R2S3/BCb1QLjPitaOaaoU/E0UK1kbpn4EZmw6hVq4YJaaw67/C+/5SWGdMp0sygWvXnqARNJxQtmdJ2CJR1VxXAQvEyhsNLxo0W3bboOf2mIIhAUi7F0TUE2IhElVXM+qph740QB8eY2HpH9/6DXYs3Et/eW+yFLvSjGkMNQhH80X7JmVKR1O6I2r7izsz4ygzektAO3rRZO52KakRc+qV9X4xR1rBPLfJcElU48NysuWRYY9+fRZlrlwKgbvKosoncgSw53+mRd1cLswCLObrXF/79iWVVfDIQmy+m1vbhykgOTTDfAMbnfpna2JmCnZ1ZJ2MDNHg2KF2mi5kPudWOSkgUQn2eSUfXXpSK4A4QDzkUmzFVqdRKiIu31uPpbU1fyeYxlz3auzKcmB8anV0zE+Sn7xiSsABBmWeDXjxbj87uwqQ/9sb87N787eUpXeDjEXZ9TioQCm6Bv55VLcOaiOQ7HwhAB8SpTlykddx46XxVtanlPcQ5acJr1vqnj7lDVhdzDAUP2tJ4QV1ExuEoMZAqKmXD0AmtiABGZH/kMMz/J6NelHY7njrfK5aeTCxSPMfsKEhUhReibn+iQs+zQ3S0z8a7rBd6eWVyUPO7XMhw+qg58yIYK3NiKHPytenIrRStjV9HhQ0BGXX3+Q1dc25v8s4JF1Tnm4oAugkO4i3IQBotljsGXaTNnf/iyygPcTvu27HDgofdDkdwXljbsE9fscSZ6uBxmqhvrFRheg4ZBi5BqmwvTMIWoWZ7bCz0TsKdoAOzbeYFfWfH4GrweB09h9c6zkmQtrBQbq3VKyevh+pXAJRsi2wNdZov5YolDKHQ0Ko64Rvn5YTHvdkC+lwkcTvaqnKWgO4qSTP5gNn6dIcPOvy2ES1P35cDrhIYg1lF9Ccv9S3S0SgpO6KJGEVULBWfQX3gp8bAO/01VU2DAXBQreIqCQg4y4pwwJuBq8GtuE4daJK86Z/3bvoPFw4fUNKLIG1R1FShk+U/Ci4fuvzHFQwtkLvOP//zuitRZAbdhdHrlIfVTxNOLwRgxoOlJpXeThyE7sGdgyZXX1SO+CnEr+byWRZhh7Et95rP5w2nAv9WFwZY1R2ZKrAKmlk8Uj33Hvq5PUayu4R/7X++85NGeIMcu9M74VIjvBEt7VF3MRs3VE4f4JLj5YBxn0Azr43w5YG7FfVeI7FKxRWciN0iox99jvDQz4x75w8iN3zYF/j2/cgWGiJCZqCQRNeyHeCGWF8t+2+bAueLN+vJ/ami8RXzWxwx4ESZCEf9H0hu7gHTinx2OoCm8OdFIQ5ZtrZiAIVHCczeACOnM4V2AfjWOVZUEJ4x4QbG3e0HZQdtH9dt8Lxibl7dzNlZ42t1HDNyl8Sa8me7CVyBbQiMsXz6GL6amkiovEw6k3emt3vAL9MckdqBBfekjJ9y1zPETz1FoCHv6RPxX7SaKJm0cHMBWG7Rr+IHqJIGkgOzYvZpc/NZtn+RTvZvEQ6kcCgjfx/lUpGG8wl8KbTvF1spGozjK0Ur+O6StpbrwyywT/F4aMumfm7Aiv8wlfdgH1jJhzP4Q+cG/x17T5j5/opXTaDzbqWIWwBfdXGUf6TjpbWfhkSj8WG1HO7/7JsE3tzO6eyRHIcDwpFjKZR+wqFDqQtNdC2/mxjc7TEw91CF+PnWreiiQzkes2m7PpEMIas8r/c6LO+3niZkMfS/ugNxciw3xJBonzUTtvIx5vZb5PkNd0KM9ZcRhtxobvWu97bqhhMc7AGE+/YVY4kON9aZUSpCngo2V4lRD1Mb1TpXUWTu0eEwORxQ2kLSG+oqlmOi/S8JE7gcB+pFqrSXtuLlK/lxvmQ2ee5DCUV/cT1UXpse+dVCbk6vAb/1oiMpZ/03aan64aW56CligOrXI2xoQRXB6bT0XvPN2GzCW/yIxe/PppJRbakNeqtDlOygRrFOCAaWHYT8V5nKQ0WU3TjPHjWhgymlWbzVKf6sw38bh3is/oXflkz/LSdynZhuwBiPjMXCT+Gkbn91WkjBizDmLEkwUb/049F359JWZyV94qxaM9VPYe7Jh/7Q1szVWZQuaH23gZJ2VlNtmxw5nbrOkBofsYF7oeTWOTYX798c2uLncvArBXUV30wiCmLpHjkX120RjpiZCtslBYenahQrRnFssXnAp9dMkGVdFAyEwHHjDjkiuaNc8JWh7Vt23XEyR5kYatIIleZc2cwpDYXrnLUhwY9s8eaWpKFCQygAy+fcCzZSOcN6fgtXP0a7xuX3dW5UUubZCvzWASUvqGqmQ17g5PntxMp4Wm5s2s3LM7//LQsbtSEvx27828lGHCiJBoFfjKuRsObbsSA4BDBZ4HbwuP3LzQ5cxh4D16uw+mQ7PN4bWSf97Nxp0QTXQaqAnh5AOlzV0zKYXuKgvBu1XrspGw1mxjTJyCyZM0YeHBeJfxGaywkeAGsuxzFvbWBkoGsUZWzuvhFHPduRaseUaYsluzLm3U1spt6uxyRXtAfnzGTVgko40xKDLtLaDhqdfCvH9CSSD6QwtRVL1QMQLmCKQ9C+H8TOY2HFx2l12X4/XjsL0fCVX3hsz7OTFtWOjEZeexHhOEux9urQIc+q+OBgiTI5IwRHcSj1YkekF1ChCFACwG3wAaegV4n7H5Qu2fK/d9uiMAFm0sGrZOtGWo1BDSOvHa1+wa9xOqv5X99cS+rKD39l12rkqNAJR3ZIcSLJdrl0oQcTonW2hzLC+mEonU5MnxwtuJzSrkj6M4O3vqKe1jtlZ0h8c4m+jSTgAiOd0/+xkabdhTL6h2036D01v/8TPb5lN3MjxT6vUsW06vjNx6wY+1uM8juOryp9PH5dru4FK1KVduUNIXA/IE/E7V4hImgRbJeAHvxnRFJp21Iu+4y6bKeUex5CDHdCKG/rLN1JRDnKLgLAzsORRu9zbmdpvuWND6ZaPpDbnvMpGWhVFTWt6wfA4Ocwn8wy7PYGksOEmGHr65VbOMs6LxNmdrz0ohJXhzNUMD9jqB3MazewEK37sQgE8U0JaUUZdGJgFZPd4q27z3cfNGw/blez6Wm7geozwjCCeBj7ekwu8NEP/9XT/YunhLq1P9KzjhfnPuob7dj9dbxVRUzIcidw1FKmmcgGi2JRc3z3eOtjSCh72JpMhgNGiQ80VGAUFUu53I+Ro/i1jgVRjooGbXIaUnuRWPUQ8dV+QsvWoYju6Q7/sJdRnqQnEeiyyrOKT+ZTUjaZu+bWzskLPuoRh21P25jabIol374Ysftlje0I4e1X7Cgw/728o8IsS1ALYYCESNrlQnTnYlFiCiPG7Ve8U/fBlJV72l/fTblvGqkfdrlFxDWDnCMEfo4Ac4nKVEkSu4DPnLIyhm29VQY+4G7L0xvwjM42jX/5yqWRDkGtub3cXq6T0WwjEuQUX3yGm/F7VUzSvqDXohZ2fWRFQJYMeAUGhGpy2vdfx6V7ds9b8jcYjZvkjK4UcWnzZynJGEB3q3VXyai9Oz0NK3iVcGAkVFoATEeQAVaovF1sirij2kI4SeP1tVe7JLJ9rOAD6cDdTbHqUNKUnjvt2CFqpGgUXlifzzdVHLH7xMEezfHvHukJDoDJHDb5NYUNWiPma6yugRqSpmSmQFe+JZCWY9JKINnuCAKz8IZmeaYr4kEsJezlf6mAsOidu9YXrz4Zuw/M6oC82FCILYfdu4ilXKZyNuEFwUy19iMT4b1enm8qIhfeiOFQFwlDuFNT4SFbgnA336I6zN7jRddl48U7ki1lYa1auz4flGl0FiI9krZ0RD6P0vsVvzURDfup2B3k+o8FFHp7egfucnPJulmRzd9LguKhEVXItE0Z6yuy8DtwcL39yLrJph5lfcWs+96jlsYb0uOJFNDSGFA2tOg/8N3v/NsnYIaMiTfJ+H2Qo53eIry/VsXbZvJ3ARxWoGIYFgFePqMViydEV5X3Vs5+W5QUwOWLbdAE7KHdZrGINTnuIGuvYq068RtzrHXk+oxS13wioVtulEJeabW2AFVWzhdt8dJXUKGBjjkKtilhlSqbrGDCQoRL4pRtd23ofgj23AnD6KftA+3OuiZKQ/DMWZtO+02l9dYoYH5QIMt6wGYYU53CpJJfpxDyBUnL2dJAIfmq1Y7rFr/BZTJWXGBTolnmk3T7ouqXTssalrAS/C4MyhFsWlp5ABBH4v4RIoaqX5IQ6CqfP2XwR+N//1Vk7YsVE6qlfzqyra+OOU02UGS/sSwSnIkuxOnppugas8tGLJ1QdcWDYfua7LmLBkYnzClu1zW3/TRGLHjj2h7PHoy83Hm2Zj111pXVa9x2THKvyNry+K0fGzYCqiFHJ6NibLu/QV1AHStf1J4+C0hRiKYJaK4kBO2y2U73Z+ZvvcSxH3F/WkmSiveVXWrf6xW8zlkQZHQMtol9ccpv6mEShAe1rVhEJ+IhNcgzrLvAWxGrpEhXB2bMHWDFF7zkdceEvmRZGcm6Mxx72fxockEOw7RKMPd57LWbWVhFve1MKXbvoNdaDdHuYNStqwa9MFKkWM0FQm+x7HYEE7q1dQ45sgDe6dMVVjOsJiRLe3LWYsOD5f9Mwhibr2KZOYxPbkePTIzm8cQdinfSZ0snts8ahQgWEvhk7rUo/qPhITxWoM3Ad3NHJtwb1NBDq0cluIVquXX+qBlRFxXV0TrFeRnGHh26CaZayCukc4IsOojEu/ItyuLfiY3Mt/UqBTekyJ95TKwAW6VcKRebF5ba3QMy8mzUQBt20SbLfwGida6McJoCuYKt7VTiw7Jpr3303KDYhIxM8bpENqmdr//otAybYaeF0osXH7mcVGide8s+eLCzo0mu+IAYp/pVkyLVFQo4Fbsi0WoxR3h/nrEamtwl0IUei2xINVt1tLLRe+1iYnUWffBK5blqe1NeCUOhnHMYZPv1hcfSLbkYgK7nEnlgDTEU/8lAyWlx9q6KiQD3eYt5xtaFCydjXKsDzf6faA3pKZDzWUt1fhayROThQbCZ7TNb/M8r/oyveB6TXXuBC3NZzEWCxViNNBFJ/CTDVTsWqFs1zGiabBPk3n+LONsxq6u0ERVDDb0FA/V+n7eWvBO/hlGmtcZyt3MomlpznO14ZnBe80ELNeAylJNDdhtENW9Gd1qQmXhK06Ybbfcam5bToed//ifRxbNk8g/F/F+jV2xJMhURxORT9Dg/wKzI+E4bXxIYl3mtOwjY/ibTR3HlI51dbD7ty54YvK/To/h45p4mSmLm7g2j3upMIA5nrq2QogLj/iDVFR43p6EAceb3Oxvp/JShremvd189GvLHKiTQSQuZBfNSZ0xMJaq7Zs8+K0WNHWp0hT9PRJvEsqaY1sDl0x8Y770PQ1uiDH3HJclkfNzvx6qAJWevLhr4ZoeQ7mgmscOkexzU7ZeohNVpY1PlYhPGBCSLNc2DA5lyi5Tot2hqVbH+eg87SVn4G830ZnmN0XAE2R1jX4saYRI08SDAf6dkaa6zLIjXlRq2hieR7Z7ScdtDkh/y1yG/QojdAJFQj8ycGJVUX0G2eRrjUlAwHMoYidu0qp9axI7UREszrrWmCMDrtdVmiH9Bcx/07qb2pl6/p2CJNduSjd9+Qclyy/fIHYxPfMQYjoyD5F6vvr4m7oE3FFNtIiPdansh6U7qlFUxCGSAgcxK+Fm/YKVhC4d8Cppiu+l8mRVeTMLlRU1b+PWgxP5nSetUn3ijqNGaMmDmJG2h5hMIeZEwLAAcqLFWlvawHUdz1vmc5Lvwz2nIzyFG6K9DZFwG2ZfrL9kUDVosozAKpRPPg4CJXTsmve3rG9hszvnNZqY4+TtmXD8BO7xi97a8szf0Na6P7kG7IyZR+zYDVT2MEvX6NoDzxOSJAsMOhX8n2phjUNgn/wATC/f4mBQ2mgoNSBdbp4EnuPCxl0LHoPJNBAL8ce2I9TpLVand+yU4oeheDWD1nkX4gq2ggl18c/ehGb/1SP72qoqxcIrUctEgEqBy+1P3pLb0As7/7ABdcsBmonWz6aQikMcBcwuQ8kyJuMFxxrjIxWu9MEQPbLNa3vI3zJhCA2CZX4jY+hzs4qX2mmmKnBFfnaq9EOujEDw+HKCn8/La9lPT2FpFsIrFtq4nPVjVj9JBS9aSgp6F8j3her3TqKZv9ogfJgj+vpZPJZ8C22Cy9MiKadMUacMxmYgdDdKJ6XAYoVXu5oYUrwcCscJwfLX/Quv7tp4+5jl6iBRsapqYHfqhpYP3QTOWOe0apYWNZko10y4rDwChymeUwauqQjaErWWxeVL5wwibatw3v2Ohx0Ei63SOKAww9yb7Vn1/mLAeqHuT/9uKX9AKOomAqrnA4Go9LR44c0HQ40zKjR4HTL29P0NcNcleaLP1rZSKSNOQz58iDrKKI4KTLgmSclg7jhrnjSdELRmSc4u0uJKFe1iEfSixs3h1/sDsAzv7+fzucva0AvHOw/ytvIW6B58CvuyvXHCZnvMnBGtGYOwM6PAutkKRqt3Mz0VJhQjo+JXzMJAy5NYqZ8QZlbwPdnpPwGECWm1KubIdBxSpi7k7brW+3mBNu1uZLX41PWxOWnSvyB5Fgc8I7BdZkrbU97AZvm8OeWclV5S52NbH5QoM7+gRc4EOjRGVIH4UyhwqJyA+IVygEn7nv+YjYN6y0nPxKPkN95qmA2CcXOUjt7MWTLcIYx/YXcmi0RJtrox78gR+kYE6Y59okqYE125qhTbFs9yus1HEilbYOmGwo6eXFWH1SLkg7vIpZjJCjuXATzU0GuiVyZJF0F+bg3g6/j/FJfinM/JslmB2AX/rg1oExluBp0nICYIATORmT/d5Pww5vyzYq9QzR3bEV6vYOJ6dshmCgwLeIHfJtqT4OimsNMXF5U446xVZIo4a00I1C0ryWiDxBpuuPb7X483Bx8REfuPCzeApLXfVKek7/lIGtiREM9uQFZrpEQUE1eB3OaP2KhuNciEXF6SyV4fXkCfTwsn72e++43ubW6qGWWULcTuSQvoydp5iHu+zBYhqZHV60Y1cHf3Ll1heDiif2jildtgfj44Suq/A2cvgi9tklbVBK+0pX7tHwCVfg0xVdUbLJ5diSSYFMVDBrbsyH901WKeDveg7/e6iviI+4C6032KegEncr+kXxjF/dI/ftwm2LK30ZAv6Yd9Tv6Xm8pLwbY6+yjfLPj12GVkPNNEZ0z5kK0dZjwXjWKOjx3JMkygpha/nLdXkBeT1t3JOGYiUvfSpdXOVcyoPah/G5vEa9ssOG6uCw6NztKXF/eQaKejKkPvFg0x5RCAskqSTtRj1kqQ5P7H+ozTlgKZbyc0TkCkLy4tdKdb1dZHWzRAhbKMe7SHmLxaF2qGj0NI8xR119QKd/PsXb+iPwCZiPQs82fUum6ZRghJ1DWyRHR4fHzVKUAVtJ+crtXCo/oHns0LQFEp4a9NGHIG4LfNgqr+obK5ge0hLtheGoIKggfJa81W11Dcheo/dDHC9Pi9snc4e3ZgyQME3S9T8Mc6uCLo4Oqa5fMKOp1CZoENihKzIC6+oRKSbtjOAcYeSbPEJSorGt8+NNwXkifRIRreRgFGEMyU8lfMSVicB5e2Aq3p4my1kQUYH9vZtbpYvX7Whpmnh2JHNoUWzqlmwE/h8ULTYJH0nk62RrJXo37kCeW/tgDr0fl42YPDnO5wtNG57KsQ+Ea8ZHGcVL4KliRRFWdF0ypELQ8pQLMCYvCvojBthQizGMLKpfjCWRze0vfN4LFabRItg1LYGkf5YLpctRSNCsbYXNcnL1sHodraMUYpeYNNnWxKUi7pj6U5CJC5g1/K6Sx4pppE/3OCs5/tpw3lk9e2+514GsIVum0WVDaMUZps0uXwhaz0c4tenRzjaVv2eQdJ1C/yIYjQLsrG2bYCHq74zNGLldoDJ6XlnNW/iPuAv9tdvDEZ7RVrSZ5GGNRFRnAcwYmGqIsP1WDPaQUYCL9MxZaHsEj9XqDYkb7o/TdTJvgwllFU9aTHewaLw0HMBdr4jsRcKj4FM2vQm/Ffgh4t45gCR4gfWKS9/JNKH8+kAR/kOCrcV3BExt/gy7n8g0WcuHQP9YvFkgfoKxmx8J8bgHQub0KI+g+nPRTV5Qw/5KuZfs8Szd4xRi4gW8nfiFuJUhFQ8BlGeUuZKNa23yJKhlrK5fMAXsKmsLRlnKR2wPVYZXKMkEdIzRbYgh/nNDMpYkXWwybJX1m2Ur0pb1+jz7tUaT9PAWqsqNTrtI7PtE1yp0SFLT2dp6qKlZ0u8+3EK+skkg18qTVlJp2e+v2rLVjTau87Eq/mrhkqlz+mYx8ExAQE0L1JF6WihH15t6XEH/M6z40SmWUw01SKpvaN6z+HHCfVpW0u828uLz6Vxcc8oQRcJ994MZfHcehgZ1Pg+Ar8NMutqWwO6MMSg4Q0VlAQ9a2b/tw5yrIOuosLUkzYgBVJFsbEyQFFFW1/5j3rTPBOAZbhFOgKjsBk0c8RzNRwIPEEJGLyMYfI4ybACDdXhSnjE5cs+UCuOT5Jri17ZVzQwYSYs/1glOKRT4pdbcJUvpTEf9spc9iiRqOE49K/vqlxh5JZykZmXMOahhDlKX1dO3DvyNoYLkwOlbZXHMrKKQbRN7AxXeEE6dap0akQuR53dyactmafYJAnufjUBZFav/IGem4gcwJzLiXENGb64snF4Ke0XGR2rSAHRTm9nztoPXY7DxvRG/rzIa+mUMHNs+Wi8MDQJbFPAAWlOoHdb2KEU8TRYfTnjlNSKvPHmNq7WU/WielnUVrci5yPkyinbUxME5xeCqr3g05axsjeyJUMYCbEYbDawu+KpEh6zat/qReol/+GI0MHYVamM5yWwkiUA59i2uVnECsg/nuQBY2NW1n4cTFzpJy1GoLtLDC/kAWKxuPLmkXNpwqocif+WbEjRT0mn237daImlfpmYNOPHq9lZ/mBMrS15cyBUCRX52m043mwwXGdIL0WO+zCfwekHTTpJQ03XUCJSIT8ITuWaKy+xry4Uj1IHIbti/oYTKEl51J6n6fEbRFgDjw8CebnCOq38XZ6dIoJ0xeLE6yfPIZ41aRZhsXh8doAMHU64ZVYopBJ56PiDpWi1FuAN2xkmundTcfrP1aqW5arqX9nhRoLXat2PSGObmOEpPD4ppOEUQbnkwdfDfF7t0eV0t8SbcsFddLiJ3vpzuQXayZZuJ97CrKckxCccHShrB4lXTrT65CIBGR/3ycLxU+tvX5vnvL/75Tvfa1AVHgmSTlKNSBjUGFcVxo4WMaPuBztZAKMY6/pe3cSctscdHLB/+l2DBGFwzxkiIYSGy5bedr1jI2Zs7ZqS9Y67uVsPUC3pD9ZV/jGIBePLpm420sjak+ukR1nlBJMSMx0EuwIvKkS4Y4ACW19WJ7Ar90T5aZAkrnxPjnk70/zP29yoyM4usXE/mbQ2ypjeR4PBwa+QQRQ0r+wQyWJ0u7eqTvq1Ig8qUPapTimaqbrtgJeAP29n0cbP8Ao2iz3Y7ZMNKENnT9UwH1zxucxZa17MgzVF2XRZOm47PaI9kxhq7e0xYrR2XReOo4NanYYDVTQrddoPV09QKRWK79vjfxJQX0+rTjAHdl4QRUzeBUYUwmfc3PYwy/9d27cLScfW6EEJ2RMmZZRTTNvVMdpGEkkCchX8MnH6GJCggNMgLteatAl+uMsInBflf+BD008FhyaNFSJ4iYh0/LNeV9TLM/g+AAu01HbF6uvz7DSxgOZtJjWHIpE/1vXjjbNDrYwOfb70jwz/2ZwjMSO3F7QHv+cFZNzlSZuJ1X/rvjdf397tSV2RSeiV8Pzn3SGUNsOpxNoBL7FVm/SrpfdYBtbQefMtmDGRVqVNIkCfkUJ0f5dcMPjX6JX/+uN3C9AGNXatRIAaKBhCPvYdvwuUmt2coHQdZUBRRionGCDfqjz0fnhnYoiyrIA0KnxOTKYg7QriSFe2gF9OzPUbDtNeTesg9EpEs11weWKu7Rb6Txy8lrV+Fdv3ydcMvxCUz0QJhSkYrkeF1oE+xKNn/OZMMDrmByo7xiZxMlixmiIMbIxdyVP8h5uz2bhrEj15v8ryoeezE0fWpd/6yYm3GgNDKJcUKyg9baAEd0Q2OzhLlT44lP2EgoV8ieDtc7c9B/O5YEinP+rv3BbnIDkuQugjWLzuA8kdyUSu30bJzMfHtN6mR5GS4gHr6Y3yqSOnNWYPGrpQ40sunxlkrXYTBkoFVIyt7x5szXsj1GdFtuQI7/QQQcYFVzsyu/w2tFNeMdgGZoFG6VQpPBIkAJpjN04jd28cCB6BZp3V9RC5Y5p1hIvF89uekxiJWrqgpaphegcceqFdHT286BcmdXWAtGIUQwkaeYo1RIeV3ju/0w9qKozBPYwdqcqC63lA5Qv+NFIZ7leQCC+L1Zzx675RhzoQtg676rXQYWhiSuwNVUSbgydPco7vsTzjMAxxgUy5jB3ckWO6VfGE533UjBxHoCDM0z9RqsVgfSAa95mXu8x22hov81ki2gqb4ZGOM5j1/CkgggIa8FUnQ02B57hJeKHMLBUUusHG6vH6Zd1zYWPwSZVGb7rWIdD5FO9DjlCrBH+Kf15u3azqn2HNCDRF9wzRXN9s8/K2Y/Kct3+EcC/VlR5jQuHFZulITQiIcLWZfOSNUplzep4NzCe+XtnIcv7CP0Q4Vj7u1kIl6ySUuT2AaZmG5EmgpDe1rJfyh8H9MGwGpJPtMyGUUaDxnaadODAM7phh/cwZmmw72FoiDlqLSnT05s1dZlbyJaYYC2PryNHAKTm91xkL5uxwb5/qyzT80hzQexvUdmV8wsbzsCIOXLIgzcxBmrlUb/vbEi+L73kBGfE3MKT/vFbAvkSYHkGYp3mG0FdQP+3TX7YJ0iGDuHISNFhn7FHSeD2PszDZAPUU7UYQ+qebtFDWVxlNMKF061QkTDieRmPWg1sVh4o4DZ/2QOB190+NB3ZJbelHOJ9f6loyjSmUl18yG1glZQJQ43NAzfKak2Cx7qxmkusubdMrVYcvjpcw+qbvXWEN0RBT0LMx6z4mccwTBaKc/uUyt0QGCzzOia8d1nU/Ddn4BgqGptxnhg4PejwBXxTuEs7lyHvQLndYzdkigODp/S3DEHz0zTI7px9l9oG7rk2v07VVs69sDxrLRT1SV2LBVMk5+VvMjiXuJjkDmzhH7zUy2rrjPbq3K6X0eDN72PUn6jerQknixRFs1R7HGN+bhn/9M7/61sB0reXa0sJe5zWAz+tAWoOcIXlOgtbsSOqtrqCom80Zmp3b4YUD3iU1zhRwr7mQdLRlIsnVr6RY3QE9CjaQEz3zKe0Yr8ztgmj7hQTPmzCar6nMUWJwS5CFZ3rc7cQa7g6L7/OJnlxsBiiUoY45XM68rf3UjdaCacpgM/qkTLE4mr8hSyZpsjrkjOKgM1V4UFWbak/isZrinjNGbs+YkEs+SGpeF9pDl/EKPM/74fKij2R4EOsb1FToath2ca7QIUuuAb7sUbySAjPeSfrxYwNBKOpTT6lYXN6TTeL9BHgpdYyRmgQZb/ovPYlm1NxTpsllJU7ofmLTulwDjN06T6JC/2RkBdM2l/LGdJEM0M6ydZSg+7H9P6b2m9iSzF05swT1puENok9/xc51bsrIoeKfGC85VFS3rZH2FqgPepkDEsDOQQM54PWPwV4/vpSJBTWEGcRSp9WiP/MkZjaKlGyVWBPKQdoWmi2yUChqKVEoLsU7ySXFzOc+yfdgF3nddHNZkGtAXOIwd5GA8igIj4g1ISTdHvJ1bk6nD5gMNN8dAhvhSqCfEnzbX2aJ6i0xskSlezM2qzuNAjsFGhjleYc4y1d2dFrqxTnnGNA+ut8P6YNhFu/7f0uRKqt3+Z4+nIfYUQQ2LfuSJlJnWMMCWNWpJklKsneEvphSGvYX45pLvPJaQvfxqs/JxanIdqSPwf2Parxe+gxjjXqvw/Wo0lmi0CoXqSjmHjqW3T0CEqv0bTjfQKovMU0C4T4qMiwsOB/lixp7QLpBawh5LoTOxtAIRSdwn2yc68wL1OnOdTQvl9KXEZVnknBHgM1Bb9bQT1eMmcVkmjAOOiU6G9rYMmTeD8YXXeu9rTh7C35ctQYj2Wih4W/sFO4R1OUiQMs2UoX42fXpO9EWnDOddJk/9gchggL/SlmKnNw0g8jszDiaYBXQd8mLoacFBVl3Ri+Xybfun2SMc4q795DRKaJQMyzI3ogJq1HxNei+T+QCqPUP/BmBF3T99BEEwJrvnsZw+eXebNkTzr1a56P1YAWJORtKjqzJz7CD84mxcTZJq4EZ4eo0wKRd3CqRjsadEfoVSP5RLEDUJc2WxJv/CA5IYZu5/G/Dl1TKjxySWjCAM5HgsN0S2NoI/NgKj+mGGufd+ZdqAERIWLlZYeRGoTo1MwhFXmw826IKzKkX4DB1nTKIr+/R4rWSB9VEN/tmc5TNFNd4KBkHsxcl4egNTx6oj4TL8pRu9cv2qnMfGjnIBxcOwyk2GyAzH6sAoK6GmWpZTJ0a/Hh3LrwVrrBUbmiDlBBwYzwRHVsRiWJqkPL69GuQZsXxC1jfmsRUfO/XbxylSbVtI52LhWjW2iGVuWvtoru0yag6pMyskGGFhNPgPOmqyC5QeP0TN+FYMngv6hvmS07IeorhZcFUWqo9ep+fDvzzQslPDq2c8uMPIpEhrdM2c2IeFi9cSRc6zYViG+bMH0ML3fRrWWMJr4W44O8LfcL0Yy4NQIw40RcXAfO5RSfjsEt2jrb82YVwzGauNMgh3t3ZSs/ifK4Iwqdu+/kS72Y9R5929ChmN3/TzZx61M6RHDeSX85/0P3O86uyht2X6+SIZ5LiIzTyJVXBHWg2+5cnka9vT/uLSa+18spy7z+XDfX1BUX4l2lQHS1sUzacH2RsAv//mKXeH9h0blH32eIlckLpgaF9oUQx648WVWRuTWop4q3QVM3yNzcvnRFDQLQmOre5tYN5XPWUof9PxtwypFDVZCrfp71bY8dwYeTLXExPRr7ysJddUWk4vamrN9j/7m7dd7Rv9e/KIa3KVsXrpS6itxvHOOzKIBW+ZIyBGh3/s3C2QietaUh98WcwgVy9/udRJyN5qWYWzHpuuC3rCL0I3faXlno+s2PHfE5AhGRhkO24t/9c57FR01HdHDCsCGB/zsLTng5urdGo4sF6p+sYhmoNgG+vmdEtEma6++DdckX46ZEq0IT1VA8rsp+Uz7k6/c0kVldOCBmIeHe9c0DhP93MSNP+Eesnh+l9mlRnUzHOFRPEpOBZZ9ttISE5uW6ZUTcBXIgvSduacJ389MziHqy1JyqNSniiCsb4JPGH6FMhpmKsbzRhdt2BG2gJGS8z+HQ79290LlVf7Jf4MkPkcpVuNNv8PwRVTrKwrVLz7i7bJorHbe1iBzX9CqbLjgoLEfEMYZaOPUhZEEBh6IYeS07bF8dfz1T3OrQo4tTc72jpyKoE/TwtIJUt8w8dRh/Knv0T+6/N7E0/orVeD9y0dZZIP9jNsqzi9PlLIf32VDmatCPZPjW/HB/qQstbf9etwaJVQ3bSyWMeQSr1W7QF+ISXFXw6jHRJpt1EJyAe762pFBwz5gGNI583RBKJdwvmU4rmybHYg4EnDJJVVHfoZwvIr0DaLfcDRXhgPGw3caJS0goB+NS6JemRBhp6fbGj3z2ws7tQN7Rju6RlkgSlOGl8+auQpyY+IOXClciHjya3vm6RI1+mG8yJmVzqsLWAM1UZib8q/r/y6JBA+1PSb5Lexu0YL+LKgedme/jKvHu4K1a3Lbo5fomgvKZoVwHg3uytDYA6lx+HMxfK4oB9cxt6PcV1Z9GoM6IjIwqCN2S9rbnB8EzEa0VU3E5NjtTUrDksFsf0yF/SNUsxQBXupWm/NNKvLTgA+B7udYuqvSqmKhnJTgwGE1CpbBdGA90WXZsnQiXB/WKByHFaakqWeJTuw3DUPDcJQGWLLjAfUVxQBwS56A36f0cdN6/2c4heqJv3CoiZ9qrdiNJC9RbwjP9DyOSYkE87fhRKqFq9OSsf+qsb0f8CkMQjyy0s2tCJAPJR4v5Gq/pxWVwi3NuGVju2Mln9PRW4f9BzttWYaJNeeg5aGRaKfHI0YFKQFloreQ0hDF4IVzXSpFicjuSY8CznHQ049xX2TzZBkUjEI90G+IFOmTjYcf4bw4q+k/46WJ/EKkeJ7ayG8eCmXEhb52RfA3X2upeowC9wk6BQVhwvYe9x1Dd02CY8JdMV4yxQ+vzkFxu7ZHbz7RLevtLhhlulXj3jjFYIBntK+XVjagO8suWWvi2eDSFVQHF+QaMNVCviiiQPDSCH5QPawQT00uGm4chKz3g6H0d8IYv3ZGr9P3RjrLbKUbq5Kmj4c7DhpazUdQW/LUBHJ+hqMkqy3Zmfl6jyjtQwMqJgFv41ZjW2V4ozaJB1rcUSf5kckCAxzekB+hhx6w2RpqEGs/w7fuQXIYqK179IOJetyfx24dG0LKPBveJKqvd88P6jB19JWiCuypZ48hTj61ozo7mAKUcpO1xcS6ub+XvW3P4dEJJWPkinyfqT4jEZRLCU7avlFlJHkqj1nl9h+zoJTiEa9vbbHAxL1/3/uzgffQVIuMLpNM8a8fhrwsYOle7GJLfulHvkBy3JHFs0DX9d4zff94oc4Mrf+npzprNHrwB4fCdiuLgpzq8yoDEez/b6Bn4y5KnVmN+zW7U/zMeTg1Q+hT428aQQJF+cM9DHQwk6b+0Uoca+fSdk9m8DxPK2twSYrkiHtLL5BjRmyHBsB6xCR3ihFMNM/195LGsKnZo/VtMS6Kksv/08xf2+SKN9uinjqmlrKAvaS2KbKMYszWXxIcRX/RRt8gB+XlxvGGhB6euruxUTCgz8PMC+tn3CldMM4xeFy3rZSrVXGEBox6uhyxtsey1JOAO90Rb9fBhUbMYWJ8s7ihEaNPb2ZYdT1gKezPmed+wZMqjZIpwfX20CgFfJDSHWvWk1l7Ff3egLiDHp+1PDPPUoQ+K5q01S36Sw9LGcDL5mdwgIHVq3ERUzvYssIdBktzjYlVXDWt029uOEjuAXOeqL6Nq+DnijRtdyICBSbj+fCRNPly9Dwo1si4Z2/B5SlpT0bxt4CGv2ZjcurWLyi+G1hqw43IZsQYPfabK9CvuD+mDEVJ1jPj5UwE6szECkqfVVy+lljGiYBeeK6GZLeVuLXtSRNdi2bBllPJYxA/nNiLT5n4/7njc89XVwFscs5mfDPZrlZAJZ9rRraanXVTi6Gl9mJsDkwnthHJYq7ragrDjAmQ6jcrnzgT/AZ+E/vKtcJJaGIKTEHOxSBC4Ho/4/ui1mpw1HfYYAzbf513L9YMMKahFjZ2IqZjpST7eDRuQaJ49SbNE7gTOaBlyIww6mP9LJC5cgNULItjXkP2+liL+QgXAB6hI9ubLQdclobgtFKDrXtNfxktHX+cXt8cd4GCEN/lPq8dqBHWfcJ+i2XvIh7XPmEKvrzxbdosOzodoYhNTD+FBZqmLdz7OY2gBPkdcg4Wz5d9FkfLzt6qUfiNZsUByZ3fJ88wSO99NvM16Y7o2PW4iCZRto4bMMna8e6zgJzVLZCv6i7adIY1PH7P1KEymWDVbVJfepAMIG/LY+H76iLjUjaE2x2N30Jg+YAxDESQdgXH5EILVpV1fZ1K4bMxF5OBi6l926wYQ5iF8AMwsYD0gZyf9SlHuuTXlJczf+tqsxPQoasXfQX1gtF/mE1ramzgm0h0BQnYz8OUi7op70L2aZxNjc9wq5HB8MrJbb3wwW3pC6o8DEdGuq4+F0RMOP/p8VmNj5QgILupJ89E7CDk0VNt+l8kY7fY/EXnx9AQnmIQ96ESyIhb6SmjDVQCEzgDRNtNRF9Ufv8cB7WNMq7NFTNAVq3IaHCww2861unV6BXa4VQAOqWha0X0IQPHQBL7eCquDo85YEs7lnIPfq6QZPcS+Qg54qd50jlHoQlEmgPJhedtUbf5E6hoYbpcFOxO4vFe6vNU0/spSMfBlZ7V6oclFGELurbRfa7BT1ZtnTLa4VwLnQGr22I0BVnf/71bY3wpMLqBQ+HJCF3UuanTgGJTIaRia4oBm4CoIYCUicGQDYspx6msMKT8IuBxvtwlR47RUXMjkuJzuROqoPO6kCicLTbXUFz+FX+OgX8dFvBYBhZlQstjmiLfOulqcIKep6KYsHrwTmXxv2lP37Iz7NZ/vIcoruO0Mg05DweOYED02rtrIaXxd6wPirhvdH/dDZYB26MpvxWnj6irjC0KC40qbB6w31ZxvemvrNIo5bgY9LlFEYgE7jkNbWqdRnyv7ebv2FVJASjgw9MtXF4yIjbEXzaNEbocb3ipRN+K5O5aGw8iYw6xs2pNYzlWd7TB1qMSWBPQ2btLJW8HZieLBPN/qhudUiSftdpThOboCgIAs5mEh8ljy4ixeeAnt3B2WBp0Gsa6FOYMKhgEu05WLjYLXy8MO1jV8sHmvwe1zdyI2ZQvSN8XxYWh3j7ow/UIDbbOyz+M1XFtkwGaPNTbqiAM0en4BdERuhB4Htyd+kFAkEoVsD5pXcYyDeYpdrPaMSpYM/fmDmP34ah+rm2aTk4QMKjfa7N/Me00KNtH1GdntPdl45itd1ng0+PK1JjLWzDkKM66X0F55f743Mms+U07Hr2Wn7GRlq+P4JO7s9++/ygp0XZ6JRvjy1WVU2wEDVfgE4EDLDjL98ggRUUBN86VxNcVN7ZpyGN3qhJyYWwZvgMX31BVqeMusib70uCTofGXLamne4qcT5JPe3XTGSYlegj11t/6Rl0bv3hRkfcQuzTYMWDqT/dvSoRfX1ok8TEAo3dDCQeLGjV+YRD/HZ9GaZHRhmzTtgvjibVwT+vIwsOTQQzE3e4beBc2LZ8XuDLha4K27NzjUvtV6mzXuRVhSOJ1SOvA1B10yhtbzU7SeC/NxR/lhTHUje36a7FbbKoywCyr9s/v4WT7zUgrQXEjuWaW+UY8rCRbF6sksmIqmJpuSISvWs9QS6UZJ/UP0FWU4yIRX2kfAQijz8rfCAWVmtU7wmmh8Exttwoa0swXNxsq/rccv2a9+QGtt1e34H4b1mZcwt8ypXiPbx8K/h1qXVMKgreSYJsPdVggwaiOMNHPFSivEShN9pO5tcCN+O0jt75vyNeWZHoThGJF5fj46QwqlGnTOb+2MhtCuYyU8EaLpXuJh7o6zREpv9KYwVOnt5wkALa8ZyQJtWv1sKIqD8A5wVGU0gzdXlMFmh5N3xo/oli7KkoiLmXKuOV1T2qkTRrFozHvvDabtF28jPlXIXKOK0iIifr/uNsFkFcfCLg4ktS4XsTxKi/iM25EneDCVnq0apR48/BKcnAluakEGr9Nz6n51ohbjBT0sL++IpNcl5Gof3jgWjbVLMgoQ6sTxb4U4jJ/UgpbZsgIohWxehsEFZMeaKQ+Py4BOKu+20NwZm1L3zysnmCde7m2bofICign0zJWCtaXL+kTJs207N9t8QNFRQT7+k87YFXyKSF24NOaaKmhllI49h1pWQMk8/rhS6eU+bi2ftgeuX23kicLWxOgKHTm25cAt9KBVDS77QKASYn2KVR6ctDnTDe7PvxvrNNcRlhuJK7YC/T+/XaRYO2v8MEL/i7pHIrF8byq/KX9s8VmcJ/Dsu+a1oNGXjmOHm3eFhX5EqcNWPIbb10bEk2ZCYgxrSmbHd2cuvBWsXROmy+XCtBEniBm/+Q2ZLru2mYIzyzx9uqgDZOFtXtOHUMghHE0LyX1IQyXXz0MIPxILaonkSf2wiVjot+Pc4GMM1taggr1/7vNfb/osNwsBQuBast78Enr3wm8VgarZdvCLHdBoucvdVnsoWfYBH/yOa/HvkAbhDt6ybGfQPOnXKpQCQUe0OzKU9iuOm56va/mQJ3m473Uv1k4TUQUo5fRotrsVAh6JSMqP25h+VuM/AukYi7hCVUx3juPIu4m+k7TCIhyi+UF2eQH5Nq+7nTfmO+xqINIMRAQH9W0104PeC6Ee+NpztX+6nfBHRs5B1Iqd4qUxht/Fy7FQxZpNAeiyZuaNLJxTmTzVTm1BR+5RX4dKyc3fwmQtrklZeQHdK5fkWrAKC3w2w+iBRwoEtJFGhS3qTBrDLGnL0se+7JeSG2H3mmXr3yqoFJGd0kmSnzkw5hS65ZqmQleneH0FokdjeoF1ufOLPqX0UValdbdwwd63F5e/nK38hRbw1joQKN4MMkbcwlrO/7H0oTJxmtDWg+vYdfFn1ScodqeEPrDGDZ0dKQ49+IEIWVwrErs0ufTJC0TRe6YAhGNyzr8kokfv38ZpApS/eOPrm1fYDh20cBULxfa+e321HOKMu1BTkMjmb4MfmsktF015DKE9j2qsKLZ3IwxE7My/Lc2KMRSrNKesg8nd+jD1hSV4oktU+gOWTAPVBUVGjK8cjUE6XOeZsgVDbiQpiHP6pDY9xVpR6M778dVg1x8qomFDhjiRJfub2F8BaD+iKvgPbqdzrjqEMrZDVx9ufSAva33BUlQgP8TsEJ/wPsfQ2VKS14Rwy1FfTF8sG42aO1Afh/2jEL56l81Ks52isHG7s5m4heaqCHCkNObLJditpIDLIDno8biqKViUnYb4tlD3gaRY0nMR/45I/PLFjXdTkCfjir8+uRrk/hU8JYpbdV2y7LhdBBhCmXSZfxUJ4VCBHIW6xvNA6qd/6Cy9uhfw2CXI367VOXoH08GMWExIh5DMv+YBRMLWybuTG4X2HlYacbSetd7arOECqFE0/0jyIi2Fuvy2E3YZyXoO5wvonJ84QJz1HluxTlwDJSjIBZrKerZQKp73MmyTZcjljtYn95EXjRgqvGC6q7og2p0QdcWD5/G1CsxRtyrCLV+jRDWhxWiayQj3W96Pg4DWJ/1+TanfTjzCZtpfEZVV+kEsFNyKJwHhYsBueGatRFOC/oOIMLjTOQKyTryanz23EuSpz0mv0arbZJfMETXl8PPOa1g1DJ3KxHr+2g+ntSF2Sh8PtLzXbuB4e+euEL5qd5rbJZ9L3Bmp0bx10DRfHKat4qHnOOrUh3W/fqMtR8Uak4Z0CIdyygm4yBKvbO6QCEFWQ89NYUs6aEE0AZfFWdwuoXxNG/VADwtyi0tLdclfqEZA/L9yMv2IFQsGVhbdjMbMJULB5/N1IuejqCz0F7aSlvo+Vr5qzwgqBojivxrUUloaE4tPGEk2XD5ZgtJfuOtvvEjXBmSqfy857d7p/zuf53QLPANkq6aQlR0ASDqEBhPCGgLsvK3yWAm/ruQ+e4vBYFZsFZNR/OJfxf1oq1O8WP3YpQjy4BA5jba0/SoJi5Abril/6ssSUQBe5LLBNBOZvlccQDECMmyBUzDJ02OYDThzUZnYcWe1WF+bd0cNmNbBxDFC4Caq4ATtSWDOXnVswiuFxT3x/f1WAElPmYZ5NXlphH288scP9jyEHFMItty44y5dBt9rrCzjcmK+pwgPGpfHzHX+sgAKMbIuCdRpEkvt3nDaFv2NtyIl/ihbf9qS0s7xPh4CvjjDdZsr9T+NXUhv7mQBXxwkcz7VcIY6SiL3G0QouC7NxRDQQQTBY8/ouJavjKXErDXCShRsWlmJjWVUJqKeRcM3Vje+qkiu8KkM4hxtqjHTHhDWYiLgTW2Qyx+vHmeEFyr+KPs/JIelhU95zGGx/NJ8iUJhkdDojQEO/hjC7pmNM8VxgHiqVX1WohK4AyMFbn/79JiHUSgI40IlpOxmFJjdgUC2h7nQI08EPFS6xyTjBjZU4Q2fPK/C52kZ48jamB4hspHAGdyEVquSS3f4aZ7MVU+XAqkOCE9GVkIWRg1SlgqpMvSFm23GlpDwdWjhY4kO1P/P5HUvO+Qye8ynm6pOStzk6StGo12uLzXw40Hk7C7IEQZ4H2VIxSitGSGXRUvYcYSMG6jtiUzt+jWkGpblS2Fx12k8xgIV/SjRWf6PvaM5ONy+UM8l5BM5DX1eyc4VMblEV8HFfWpnXeiklLsa43xciVWqrHNnugBNIvVG2LuNO/qK2Ys6B/y7V8W/CmXlpHyxOuKSgZrXUPDAho6GQ+fKIHOxOu4kMD7x1ItsdZV2fSJDjeGA0M8dzNuzrqIG9OB42aYQa1JDz1tuJcEXGsoNaJYv+qJPQmRhS5fJvzc6KV/EYBIFeC3I0eASOhGDYFbxw5bPqyeUDgjMTHSJF6CKPqnQ8PSMkpyhRJ+OXUlw2D/MZdR9yV6yffKXvwrfkJeb/8Zrhfc49na6oivWCWHYXGz1R3zvh5g6GikggfZ6pctXYCg6fEA0leZI3Dsqo6bbw64tIMnULj5ESjWWWzoiRq0MK4eVQezzZSbmmmABk3/XVz426k/n4pQ2CpKcQOQpWCa5ENtZBnQpU1GY5qHN2p7WSlCaa3tR0yZ7AA3ToZk3PqXCgagmodrv0QsjrO9IfOb0yRpjq9wuhDqKWr6XoDJHdECG0vvSuZFv97kDqWld+9YLp3D0Sv3rYyWXXGePmZq2/T3f5IL6FRzIbWzZnZju5heU/kQZtK/LH/lUIpFkAnM/t3GtSvd8R0w/XkiKMCESjpNU3w52FPugfnAdCyrCmE32YeUHZqHviwoMkjSY56oyF9mb/8SBPBUxB3fvFyYIM28vcbmLdlNKpW+2Upw0iFUGs5o3kLf5+St8vxBD0x+cMFKgkT4WpqRbNMfu4uj2/natcc/r9zN/evhcPHxdVTCot+E+agBpRjKjY9OxIdzSQnGuqGWuCtG8RfxPvQtHI0gNYtOT5s/aJ7XR0xfC39GeLl3cx1hIhASHEyIk6Z8vu+kBcXojFPHmMXnLfytvekIa04pnXvCg4C5y+hAf4LgA/Nbg2BcS8QdQUnELqJ1TD1RRpjTgmpvbqXgzgRXSKToAyKvr3yoEHziAPXHXUEuYMQW1jygzlW8xtkpfymYDuZKbffzb2vfvbdU0p6yxWAt4jfcqtxzCuvlxvR1GZQZgtsHOSRb7626GipEm3vLCbRJROl0q7XBBi1R1dvn01sRxd8e0mU+DD2JaWRxUe3WePE0PpZwmTYrcf6VxT/L9ccw4AeM3o/sUxlFCNpbUn7dLZ0vdEO0Yj4COdUH7CVL+FoHzZM3a6eHbtIMM7Lr3w8cH/xdlqXrvOsnuma7DSDAjMU+jtzcTeHYGy0/QEETGAUYknAvE2IhBHAZ+H9Gcex/bsuT0r8EUENd+u9Gv3Q/IaA/MAa00o1IKdtZTE/ZA7VD9Qa90KemdrZSrqFQGyrm4DegsHV+nROXQwuxGVLz2D6Dr1u/7k3xpRNXjuz9iMFPNnh351UQh2gTKj+qp4NidV+DtPwitwsuyM6AUj6JS4TNZoA7ZNQ60ZhBgSYvziqHXuqmEQWUuSqfh0fkEh5MUFeS2BPiDB/3l5LBQ7ImG1jR6oPuPGD77KbwH9HyhwnX+Ai8zaHo2ZMx/OQaCHKBvHrU+bdtih8cHsi+MH1IyIxielvVGWr7N2svo8pluMiUmEFhG9udJ+ogo3USJw3Z+I7vSBwBPpZYgS68XPKuwydorqWSyl8P92uJgCwdmclPy9hqQBNQoKF1H13/T4kN8AUcJDYMIojK3b6KT/lOUL9aZIIh4o277dFsBjsVGeUcFKgDYLPUskm91vmfAxAt9N8J0O+7KkyybpbRFm5HMq5q4TgpEkcrqbEiaPLCDY3G8+gn6qm+syNH6h9+i4xSAjfuZ8usXFctpS/LYW7tPFoWV45txxUBcF8slh7LEVAaMGEgRQEYcJ6uc18fTXtHG98FMy3tRW+nqI4vDxRFr75Py6cflmlFoVfaamVgFWzxX+2W+9D1kA7NztwdFXZ5UkrCuRMS6YPKDX7ID3eOtXTNvYXnmmyzfJj5ot+k0yZv9XHt39uiwT9QzygmZ3iPcN9FFPWvZl80hbSwBK80WihDNrPVwHJzdwo9iCWqp/XASi0Us4cJZ+kcxkyvR9iE3inGwrcWqtUDXVp9Kho21gVc3j9kdTLqSqoqYsQSnZOjjUicF/NTCTOLIH9hskm7LrdDMFmLXe/o4KeVha+xuvZg6GVxCJladJfvxJp8CMmpuZnIX8Rob0XCWRngtp3CxDhaPeSacz0fnC5LHj1OkUEC/JUBfPBbF3LUz9idoXvJM5X3FwLmOt7fwxSsbXqAnAwQlyk3H0QSPoaBiRj7swPV+jA54/dUVmg07hxKE0hqjsmeDuGWl9zaQz8dOJLx3LyI5Wx8zcTco4BGOX8dtUvsh9f/Dkf6wwRqGKdA+yBrb6gNG4zToC7NYZf2SSR2KPZ2vgR7E9yEsmdPu91KSyTFVrcIxH07w5eDo7OMnfCt3wKPB2ZIwYgK1BeGXryNJHiHbeMP8/QMD3/SaPkgq/NxvZeDhe/I7wekmhUsoAcoGh3Y8v4Z9OJGwXVA5BTfw3dLwfBD7N260CIWg1JN2cs8XxJ2MMwAGqpnBWgNKzvCjsyW2GPm2ujvm8myYC02P9ubuxWowwP8+mJmnI/BMd/c0Gxpe5cjJ0gN6SurywgQevgjwTi1ye8K72JmYNgnAaIVPQgWlTafw2QAxAc58cvyEg8m6Di+3OGu7jqjiqL3I0aALfgQKEn7drRABV//GtNwDlgm/uchhSpqUlRxV/ZvuqfFKgWTER7NWZr8Li0TP+sJVUltonHKgu5V+3bTtjRnEiiQTvAaO4b+mYLt9v5CfvvJ5KEAyVJefvYEUAWOonExGwdHg6DBJM9lRR6IjjG9n2gWQ7z1sSv6QJSFiPuSF63jkh7SWYiUKySSTEE7L52Ud2SXamk5+gvE9HtnJ5srXz125oBX1krdFirGKs4q4ma+xH9FaNqphANSkBXN3pXPcg3CHWM1UhzpNlWex8NPHcHmfZy8dgp+/zt0+TlwbFGYFcVZCPSQlQ1bEs39o9JHHhNJAAMMtJLoyZAj2f3j9EvdsRTJCIhQVCCHg8BDefWPBBSXtTLwIR4e5OOaGuhhmwljWCzzfafybyLdTtjuo9/ti2tD4Ix1NF+YnwusjoRpH84ShMTweeOUjPfR7Doe8hm00bwxdHl+E7/2NZBXNZoOs4hoCLl7/9u7gOwULTrUSad01RkwzMrxWk4BofxVGP+s1Yvf1l1iY07Djq4OY2e48dXqExys5HnSrq1e7Glc0F9+2ywGP81eQirXjD/SzGmRBxVCcnVFFeEecCKrHjfibFnebkvczYlP/g98SU5meuZLnxLKHmGnUUz9+zILV9co/pafbOJ3KI/12pl6dt4BQFdgrcpVaZDPzg6OMvJzLtpXduTFwGEtjfyn9m8TGG/WGb9sC8SNgJCe+lqAapNHP5YmsqKTHWanPVR3Zto2wJUEmZ7I6LdvR59jwAYH868bTfqOvULxHXg4/GHQ/GSxbdD+28SloRc286b3YAJuphQMvZnzqB7J74K7dLL4zfCPGluITY+kFuRrjzZCN1ALcicmTaDrKJjX4US9FS1tupTYnvE9lNEamUyhddqMx2jux3+03fXb7giTBi2eRan/LJTRAT+K9Iw33eI1OdeAqvQbqIYQohqcgWubLLB5Tw2oGC/YtPtwC9ME9VFVarT8HfmZL+Dp8aP8FgzXHSQkTx3NPVN5Q33/Sn1GoxhSMZn7FQmKaeoktGLrs5JQ4pSCR1gqlQ1/Wq1RQj70II1ZmI9N2vd6XHA1z5xbqfXrgcuDk9przaFfGOfYpzoA8u07GXtzFsNf1WRkGTAuLa69spNlTPiVX9jF9zKWorbcLY5SZnlAoATaG5ZnZOthKJ/YyMvCiP76N7EyAHy82PrN9bQSp8x392wtb/XmWbwKJfMtgkGSFtCd7LhR2SmLr0ikU7L9H5DAvxtXs0lzlNsxxYIXFuVqzkAecsX24mNybcOzKHNhRJBZSpD67CRzMMzfKnFO6xR+iga1CqEAuOpIY3TJJ9e6FF8bvjrg/uEUJfVWvbr4t50V3xMHxuk222HXnfyuDUkYQk014tqYZkfja8I6qDdFPdWwdTdjfkbJ3QYnko44kOcI7P2BgJoz3qlPP7LnhsCfBYJd3bf6w84QrBhLN3lrLRWqlS90UgpEoMKf+l0+UZ+vZeit2DxnfPnf4wr669hGoOf41ArnQ+YxTMmcAIVN60KmM/DFlYiFoMU/K2Xs2gcNUhRug0Uk1TTJiYd6LiSqf42WOME+IQ7p6+Xg5yy6P9lOhpirL3S/hiag2+9NCVt1Fh/nOnC60/XFksXUSlAfvNyTN72nJVptjXpMPa6//VDKB8wtB3PwV3i0Bdz/kq2Uv2HBznfCVDfYkMeB10rUt5J+J8XHtwcXw05sxfmst1pNb4yZOT+oubjg5/YBHF+dHO8py3QmGeo+VLSCzQzo6ok4UYZ7P6UCrLfgZjIN90ow5dPjWaZj3RZmcMZ6Wx2EJhsGZ+N8VwxGeJdCzHG1qfi1V8fDof5YbSb1oyQfHqev8Gd0dJf0GNQADtPqDUyfRF+cZSWgOxzGBl7kvZcKmwyRCVwt9suIKTBZJqnCrumRvt9nH9mu58g6w9DAnN7IPADclQ6U69NBWLi/dmahUvB8m00dla4DaBgCyJ3U9n9pSzm3W0VLe6vKxteNNun3Znfv8A1TVfN5Wv/3LfWRJr8+jRCMlzMsUJUCnzh0+lvHownaBzulAJ925iUcWMjhwKzOVF1VNL3Wp9wl8KQwJtfL3vIsURggHRm1gT3rmiKk3NC55UIiChS781Ulx8QuZkBAOJxQSOnvNZPoQEmrV+bcPDmfn3nthqGokfCnpIjZCToxdd1fqVthQhV3a5YrGUBl9JHsvm4DGZOrEAwRao3whmEOukmCvBvNn+6KXP5CzKgxRLe5hdTUbiasZ2f8Jy8gaMqZWiWP5NUj5jRUqwFTLr96G+hzzTO1vp86THg50S8Tz2PhuVdWtxlo+BsidHcbPndP1k8h541fv3oSKww/nAzCUkBfIS+RNkI1uNajUYjSBL/GgZ0cii5kxBs+0RxEbJbesec3NsJIA3fVzSNoUOuKC7dF65F8n7lOQIpeyvtLBiIJiob+NDT6nSaxeBlwOOOytp82GV+r7me+yUhromFAF5wa891pkDPJwYHtkABbqzOUDsVgrPGJibaJF2hNPRs46QmkS23XWxHSs/g16eSlm3l23fiVXW4L/UeNnJjBCMVRiC5DBghENUOcmhHEsVooBHPsPP0glqkTXTWA1ashPfY73Ha+CEjgmbG6oF7A/MrsPfGpOsh5MJBpIAAeGUA8oa4W66P7dMW/RyWLZBUccf4HX6rZvhP2vf2+zQdhCCvur5/RCb+cEXlqKoIHoYSQz/RRL5avvo/8jyA6BPLZTYudPsvJ9GGvT6v4/QH27sT0j1frvy8OIVv9Z5Jiz2Q4Z1sV2o4D89DE79rBMOtONskLcVaYT68GiiX9cQg7roUZtVnLPFrKOKZjs5gZVCeLTtx9/FKgePDnyU+E8Yf8D+JaRi/rHJdVwGOfp/Um0HsqJR8qUFDqDR1V7STjAwq+5c1TuHx+aX7l47rFaE9gInIKBk+d48cHST2oRxdxiN5hn1Fj3XMZV43bhvjUVWyy8+XQZh4z/jagmxcHV4Reeh5tWemB+wf6EO2h0a1otDINAXSBdb3/8HKbNuJ2UdxtSKBLlVsZjqi1Mj3Rut4yuovJj0BIZ0jDwt5ajw0lpzoiBoE5uFKGXoj/+B5BpScuSN/jZKWbtcJlIy+ItivmIy885H0BWkRZeYcnImxhHp3gR/iV9uc3Oc3f+/C1imRv5oD2sQ4iXW2BXV4R+I6ladqrONKymGy6n3etmPDgy/4ywen7bPd4w5Zw/tmEgq3K+UjUlWjc5mCrRIqxsE3jscxGaXN1GMR3ERV97n2/H8y1azmlHp+ndQK6IAW/1FkwUfg+CAV7Yc4C9dUr9qfUVf3hp7sjSn+/X/q3UkEcSE/Z15xdSHgKPhkWQQit3wDsgdwmxAeU0YB6LpiujXrNqa/eez1toGpapXo1qPHWXQQKPKwilx4/zJyasrdGp/IqhRnjzzbxLgxRUdZa6TORMyQFxRKY7lMpDaapdNZGvbOQO5HY2SEMrjLCfX8uH1ZPm/hpErylT3LAAV8IokilpocZh7SD6es3EGla2dKieL8Ny/AlC4U6H53zyqSDqohjeVxY7aqskJ70b4a0snNI/sYTHEDFB1mlePPel0TkC7ulKqBquzyrVpUa/kPEwrB83OuzUCQCSeGauSxI3CatTBRYKxN1uhyXSnePyiLDuBKSLoejv5nFS8+KXt1kmv6/R7Wjya7+saIBbtJGkXOjIclxnAfUMNqNPOPGUVOOw4/KFf0eklg/GyjR4r1nXiNYYi/HHrd+cPiTYm/MLjLp/7fYJKX167doxvxERAVkQceahliy2Agnt8E9uqA/lfniYPCNvdM7RAc/9LegahH57lkq7G6ZKzdHkkR24P0gT1UW+WVzSNShmFYk5hmjgjeeJeG+FJRgqWptff4mTUma3fbW3+eyTCFIVKULXWsNMcKI27yLlcXeUT0CNAuwdyLbuQNaCzjn6ItiWWzKM0Ds6iJXDlUWps1W9PNIK+X7iI1+fByOn2OKhAc+7hQ4FXRnKDc/B+cWwDyXGJJ7bltKXhLJM+3wBfxhD5ow2v8MS/ucWj0mqCyqEarbU8I0amQzvl9c/+duQLgploL70F63bUKkIGpzE4htmRRS7mfkjK0Bp/dFowrH1u85OiH3X26tf7wPQCW03TdUnovrz3HfP/Kxls3BsvVP2hhV22H6Cb9Ml4rV+Bpaoc5HwsYS/dfYjVCThu9yYriiT/DgDXcdEl4BqfkKgJ4NRsOChWQTumlElAh/U3KeJoVLgzrII/1q1JdjB8cSlL7AfUWFcCg0cBzWe6W/kwf1+yJ/HzP1zC3bDRTjOKD+c4dBI4zesM93J4LlUD7AEVqrynJcx5sYsQMytgh2nDb2mTBrsUrPty4hW4dkI5wSO9ipRJYc9051nbjF4QvuRKmSkqxZWJxc6whW2kepCuHfjOBYC7qN1rfZxFH06hoGb/48JAJhJV9X0XgAs/S8vOoK3gyGCkDa9uzsja9HKAstg7X9DuBTAMps/YgaiejSHWG/gfNp+iLS5rbT7y00rr+nYKRhOkjbxqse0c+h2A6LDIBmffNbBA7oqG5dzw4TlYjaSyTu0AfqBfAJqvFuNhiZywjW9Kl1cDm+nPhAV3MUQKUtPmHljFWgSA+PN0YqmsVpafDWKT3yETpEN6SqL88LFjycu9fkhy09dgqOdUgufL9iwkmZ2V8Kse/po6JhzdwxqRsrHYjL3gIJTcKCLMS4Y1oy5ps/UBhOUJ5mtGsiTDdnFF63Jx5Bpvf2Zu6AWAXwKqk3vofT0E7QI6/RZ/TAvvRdvTbwOdJnJ7cXLKOFXyRs9vbcfVnK1j7e1PuxZRxPCozJpq0Uh8FsSGqXe4vT3R9ZZFXfe4lXrToreh1CJ2k420Jsr/0mo70CMAtFcZFEWEzMbZhWGXAvHXGIV82+DbMjxWBTGjrnXlVAzEp2b9Prwjc9MXHZ7uWOQ+5Ur7Fp67v8xSOncNOimzqS5Z0yGk96xxaFVJqjLWgLXJVDxAhHsebQVBuObMq9cgV0sCaLiKaeakvRj/YwLjN1YQ2h/y0R31XNOsqjVdf1cULCLTJxa2n+vAyU+m/bkw/zG6VyVKH2CE3N8GRRelYdTwleYAPiuySJKn2jSAlx+GySB5jdlfFfvJCr/Ch4EGCZsmYAwdmNxVRfryI8C2MuK0Yb+zaDCo1whbiySo7KSvx1vy/tC0gGogd91d2va5rH7Zsnp2bEtiEeoqPha0dGpahW/jtR7pErSr1ksgwJSPpJSJ0pi2267CBG1cuVN4W9ORxJi1pLaAX2Sk8NeK+0bgYPLNFJICA65tcNxDmyuYk71vCnntT5nClDBhoN3cdkg2Nobh+kRPHXZWdhiRN4WbOrCHJNKUXtkWpx2v2mF6rNBeMjGyOx/ULgtMu0iI9uU3VgPPBoumMKgP/VhaMX/DYxOv0pCFkSl2NdwBmEvHYKuoNT2gjCnryNbqqHIP9+FPUGXCa2Uw8wizhOhYnDGgWU3tYwXC4B2vItdIjQZKGxm2otLQxWph6hNJVgbR2g80cBf75itdJfLgwQGV/850B8sqQGNJDQwG+WdFbmIx8nvY+n6toqauIWz7ue6euOKwtoyCruRw+nVQgFqXzr1sihEpCvOb5e7o6s6ZTebJc3cMT+ub0JHP+/W/7+371jCkMwAuBQuqfXUe/br4ccGXx9AAOPgPqcmg/HUT/7bUYZVmSMwTg9PJNcR2KwHoJeMU/EIgSZbZ8ewIz+cbhVFZxUxRZ07e7AABUTy6b9yUetaCWtrTX9IEUL4fhmUJzCOZ9QK5MyDUghjhTsYAQivjTpqUu8i774G1urOruc8p6IWlrd0Z6ZT1cqT1Hqd2lpcmHBktrIStPwqHpcSpzhl97Gkd/xhB54W/4IjFs5R5nQWRdA89qPzEsUO2dMGRKrxkHVMow+vir3HRTiydkJd9ilaruF2xEnJ6hL331HadTPHTxsAARbRMuW9krrSrtc1Q2DvELprcXv8/Ip9qnJwL4j62JM5YW8up8qf/wdIyw5TrWlcQAIi1jHKj7ebg+cVF7FxXXoH7AnAaOe/CCAejQHY9qvJm0XVf4er3LCWdTKTpTfzXoboMmDl/yQsQQq3+ZETvHyl8bDaibCYXo7IEVgsqa0dkPlPSW99jJRNUlhxfdD3KMemLCrqHSPaVuiEPoXay4DleLIm/PTKSassuQyw6VcXgHJvLC9VA3nlHiKNiyzO9enTKsklnv5JZfqz9yaDjviw3mUQf2mB5+R+DRhZsj6I5KAjEW6p4A8o/QrDGWRO8LCjpttQ/9hn0/fowODGkWwL3g8YMTM16Fk2xJEir3A2kibprSCNE5mhLscef+CR6gr3swgeTOk3sGlMBydJO2tp0tsFVBiAYrTJM94CdilE7wFxSNOtgwCIEZMQarosM6N/LLDEQJE2/tXhbnx8iAYfH6EUeNOjbzqn2qpf/5U8Eid2JHz+IJGRLcXSzpmdutX1syB1kbhBl5XaYLIFjPB2WryPApPKJsLBMkGNQ5ebaNmI2NnbihQcJ4nKAAV6zem0dJHhI52lrFFb63ovnr0godhX5bM76faKM1kzCab72nrATXC+/9dsavFRbeCECSj5yqQXtbS/WBo6KiPhEnQRcW7ctuC2uNJissXtKh629GcFRPSRnLArvD68pJqxF1AxrYWenuUYMpkgS3zOhgIiPjERO8XNIYCOP2wjsL7YmB3vm8sqx4arANVn8Sk8Hv2ejrqlmwnwrHTsWEgCMDNI1Cvcvh3UwzEXffwwI+MNZMxEud5N3Fb4KZTMNOYmdjlKpoxThYNEpFPVmbR1ZyinLP2cvMelKmdSApaZBOPf8F1C5uHu0KFw9aZPW2vlBKgdN2RNCUv2IAjvQFKzNJBFWm1avCxc8+36sPNLJkbtMKJnVVyVJuaeUwzF0uVj0hverrhDQuXBy+8sEyRq//HrLsL93U0SM3+1T9K5TNodDR6V5yM35IvQWdqmjYwxdHaaLDF6wwrSHFaueFg3ES1ZmgKMUytvh+SpzaOpvsK5yRryE+aU4CddnMPnt+uc+x4gML4r/voD0RpAhguuANHwrC0BYd5RNg54TQmjPFpZYBhxQ46RfDriHWDdzPVAAP7CN2NSRjFfdbjjbatMliCNReQpD8onaLcVMoIY+ZnW8inEapmRjkyP/YZ0a0TM4fwj3azBuEMATqkWib9PrhHFFEOyBi6O7qTzddRszo591qlD2opwlr85T+69f2dqFfQSnYO3jdmAhmuUjSn+Q+M0QzRZCAO8IYfm5TXzUWdNXer0uocAgTxS/rlgqU9bUib3H4Iku/FmIevamUZ+XdnBV2i2b6LdJi3Woh3iGQhm4FJGtOPR+hB92VKQVBbow3+Y+kSo10S733k6wNEMKYaRFFSeAP4uioRYGZwOld/U76JTVbeVeAiSzdYM6UHABYnwC66iMCqZDWPNEM0P644TmvBrSnq876vlivst6sDZ/27SK86jvao4/BaLrEtEjORNvuSRpNmt6vFs2vAoyLb2vIzl0eR9yAkvV+gleOSp9paVMHl+fMHvOEwfL67d+qNCLO1Tgo04OpOjdY8bmYTd/4OVMjUfF466yqy8XMcZGZaAe+aCOLl+r7vnseFQUniFk2EmjUA96/X099JRaIVcRFVQOQ5y/26KZboOj02Jg5AzP5NEgXRMqoSfMZ3pAvD1tptvtIyH3n5J/zpRJrcpEMRTjZ2rTO+DAcrEfzNFQX6mCVbe9nRVnwMcGSN68M5O9g6Pka2g8OKBrEyM5Ib9KZSSNTX+rJEysK3fOpPmpfCw8jHfDRoAE5Kq8BqeIh5faNkechdojlFrk7ewBsfEzUjHC9lH2LuYC4750U76M01La7SmDJSUjPSlSbwxOsqc2650vpvHXKHI3Rrje1aHe+lcsLkF0Ov53HtK3+NhCXCUMi2Cb09w9eqv3QPG0E16/dt9OyrTus7KPLVXZ9TQqFuOXanW/kdRetPX+BXSv1/C4ERtJFsnOhPO/eFy46AIGkpLrn2gBpxRF4gbxNMzEr3M1T11p7uCRg93DxZQcg6mUrHpeQTda/pViP7WlOto/U099eGYYtcsMT0FGoB3AUf5ik6mI2oOZrF9Z8VYXwJneUlesu1hbnb5itgV3zZ1HTt+0O/HWw8TAklVuKIgk6siwet42IgW2vLCBMoU01MqaXMz8F0s7vEvnu/FpuuiX1qxsGuZDROMKvtGOsgeA0H6hdokchFYkJyuhwsCcymmeRGiWoQf2DzJVxXxP/FPc4j6neoTpj1qiGLE/wEicd7GPSuwf3kqMtHL+JCKYRtSrm0W+Yv/EAvd9I23jw98+lRmih48nsQAezRssoIT8mumu6gh/I/+29DkhF5ZnraAVTu1oVRe2tMhgYUEZrpKaV0JNDdZfjqMunfflBMUgc7gPLv+I6n1gmOPvMFp/Vkd1lK7DC/cJ/LWmTzrgk/swR2kHqAff9R9UvH57F9EbkeViJlXELoeYinhcURCFwXolH0UXZKPDAzIf6YiKogD5nCdv/re1komanFG9ruQItu1NHSV+CtO4e899HW4CoUW9FNsFdmz/v+7MZhuD7/Dd9kkaifC7QRMGRvtMe+x6kvq3654633zTOVmfCNt1mTh1dDPVh7h2O1ohgNedy977qSZvFtxOE9fM+C77Y4oObao2Rpl9PaGqbqdVv7f+xcbJAarcn/9Cdw91TSxF56EF941VZZ/5oPgBMzrX/TWGU6qpP9manzxa1dWNVntrs6AKS1tkqByEg4vTqI0PKoy37Eanf0RBxH8rvw2j+EAxLkl+qdt77/YBxD+iuJ+whEP+z5SfTFSyFwvW84kCGCSWLvRx9JNr2NLfBOFWftAlIlXijLy0pGihB1TED0nZMT4J23FV8NLZq7+KkioLiXZ8iIFH1PWpCStbii88gl0qWqye8rggR9HVII+rKuYc9hjIAB8NX2+P/oT7B+gmgJ9INuGR4sTyWQD7ySMC6S1jB/8+ZlIp0CgXhsKyQf12BRdw7i7a6Jua4tSlISy8t9XVq2WyKSCryUkY2BaNbE7/E/rfcqm4vek6+zhwva/gLQIeeyUKMrBw1ZPCDeRBH7w/5rqlNuPGf3/Mm+W/OoDx/KHeyeTFzgpb5deV1QSTgM3cTOGs5GC5hxXaL1/9LiRQNwbIwlyPomLLIGy3t8HUG9Z7VqjUkfLqtgU22xm16aM6p9ub51pfzo6zZOmdU1D0afbE5udwWKHdGcB8c50fXFQoY0IhKe9oMcvyARgEoSCxZSS5/BF0O3P2gzX4yp/outAhTD+OH5V/PX1qKnUL6xBm5EguQbnkasF12tBgK/tjZEf1PsPh2UyMrVlh4QleRH4Zu1URY8zv/qmUZDmn/8GaabfRXnQ9f9eExti7gJOYLd6Qn2t9MDQDm1US+pRu/qe5pkO9qA0LT99NzJXp+BKGZToIYekvip+1ytLEqK9DCCZoI7jmlkDE8mVkkJqy8fuSoO1DMgfDfIEEGesa/T1z1QCqLCMhX43smafOJtbmmtfnUXMGWYgElqvnDveMA8WcId5GaTmzrJ8wj+2Tp6T8o1wNH+Du81uzGeoCWOqbkxTomDI0qRiFqeSY28HNRoXpr9ymmRbcRYkWu0rqEgquSFSd39IuB+Q2EV9IcyopZenB0ugtsakuaFh9uK5nM+n0VTIiD4urmZPDXZ38NbyMkvpX502VIGC2NWJp1SjSlfOoL2Dqw0h+hyIznMTfkh2xRCMxNhvD3NCrddNfQqrZDcupVb3R2saokG4YxJNHTU65Avk8zQn5XjDPAn6etfWJLWdx8g98orJ8Scd31YFtWX6qF+dHiMRXchB6mW/jnfHeVJ0ZOfQFLo6YklcWgcpK0iSsjXca3kUbr2QZewyxGE9vKlZKTjVYVF/4ntZUlxYmmEyG+X7lod9yL579tZJ9lzbzwkg/OcfQWsKjB89u9Uhp+weJx4YQ6I8m+0xDt4x7BPRe3OTzOpQRtOoNNejP1UU+NpaLstQPVYjEfYfLfWfhxmx6zpzuETfhLQ/mR252RpoTviXjBIW9ibPVpMwZ215X5vuuBWPy+2tlUkZiMzJ+54Sk+PnWiNZufQ9Iv5SNrTtSdmPYQp/xIsVujr1/PNdQr8ZncD5jvnFtWaSXaOQBktc1jU1zFr56qz2o9w3F3DOdmmDRNaFcd+VXgC+gNTNyG8GHx4fqVbW0lAyt5/tBh7gbwLd9AoSG1JaTQg3g39jw8DBqZP+Eu9zVMp8lM5h9Owa8ZkLrm8tGnlJZx+XlFUxjyYNpih3hxIyaHrgO/oQsYvT6io50vnHkAO84k8t2mI77CDdJzRuCfmqIb28l5g5b4RCSHGtF4eB1kC6OpfYFeuXK0k7+HJdjTdAsAeFVi20BnZ8kUIhOFsF0QRzC1/e+sLvjaQUl3vzXkFg3pR438gqjDD/h8eCT4JHqLW9QAHA2Ucr562cZTNCjhoWGwTOxK1RZpxMfrk4ipQOweJIL7nf+eEDC06xQyacbMm9VFCciSYQZGMmnfoCnstMRZs3YDGZEORBBe7jA/eDn+bbXnWhF1RqBREn0bKkpJczLdISNXwkBpfxO4QLdmmcNT6m7XdIcvC4ajBK1Nf6CutRkrb2ZzSCXzAptX0S5JxpfBdnMHHVE2bMPH/w9716++oidgzbjLZ6vVWeLvfdbG+RDLA8pMe3kjwmY4vmbYuAaCoW5LNQ9SBycoF6H0X8q8hRqx7DQpMC4pgDxBpAv+5OJmCPjQCffoh0G+EYDb8ssHgybr+NekmKPpULH096mIBzCAZChYmvZ1DykSupMHCYbLuHaItA73B3FgYU4AUpTXTKBS+Qrm6LE32tvea1brZAhwYbJWioKh9mFKgBATVaECS49qkMFnTT0g/l0Ej/+BH10kb3gUf5AsP2pjP7NxfJfv85vDGxV7FV1PWI6WGMxLIAUABMBjXyEFFQdAySLK2QaQ8RdOhWZ6oqfyCCqq89lUNtmOkSLk9//hxVsPC1r6aE2fEgNNNCafN3p4z+Tk0PDzEMLZMTmEOlFfcn0IR6A1eHpY2X2Q5WHWDpbDX69mxQvavMbhX4nzEXjfUMP74ql58UlofX4YVtsHUDUx0nwj3qKGrPc6b/BdkWpJfH4QTnCGijIo+XvGO4/A0W9vEqaf1z9TctHdTOcp6z4bVFJ9i36bBX11XV6KBIbmDS581VC9mJWoGBUD4cZ+n0m3bSDeOvt3eoZQvzglH4pJPkmRvyr5CJtZ/ZCS5sE/NwbeRQY7hJ47ZbNQbyf/ZCHLJG8cTtPPYwIbWDCiVgZ+w69bekn3PFeUFxNv8gjSFfieya6jdjw/wX/DZa3JlPKOehgQoTo6RQVgb+c7IJ9swI9SiBgqKtwPbYA23N4NHcDmAZVCJhFivF3Jddc0ZzHQUsZrxPMu33YUFXEgnS4XmBfvHezbvAudj165QXawkyyUs3b5ZFuyvomb0nd+r39cDumiWdMkO5P1YA7QoEL0psOSZlKz5ZzLXtWP3uXaFB3o8TeKVcw+koxzlNUSG7mSOlbbFSfxxh9tpvXK7Wt0bkoxS2H8mXTsXLQqM8dVlexDiUnls6z9sHbJpj2IuhZm+k0Njq7EtzuUZJOj2G3nWOmCStRjqKkNwzzra7XPY0a9IzFXeWbdRXrTXu3jXANOGVnHLNszZrJxhNPJaQ5YBGeg9ah74RctU6mxS3oJ49Q89HwOPnIGQ/03ookx90leS2Jir+mTwVNsKQDAAXSKU3NAd8iMTwKUaj02fKJKuZh7KmdH2tT50J4VkP7uam5SpPiqT+9cRpaln4MKtucRj9EWqZ1JIOb8vfzV7vn9QzzQPMZRPeJ57hNwAz1gCbjQ8SjNb0xHADW6epZCpx1RGqSynN5jL5urgomFCNzdgoxHQNRnEHtkbnzy/30fJZ8Ppqa0HiH1PS0pBmFfeLD9WPTVmysKOeq947b+dNcCneWU2Jqx8sonvZF30r4z1PJlNkvyDAp+ZQsn1WpoBzqp6yZvU4BJ86BEDY3DTmoEJOmFAm2Xd2hpdIHBKE5CPJRtOBTtc2S/JdoamlhT3cTbA3SsrbSSK7gKLn9g+TNNUxfG5sRniU4XeDbZVoB/75ZOchX8oFU5u7+Rjz0T4anhmtuLfxClyC8SR47vG5HmU1sGcifwr17W0cQTDaZ7L16o7LD5zGLaG2uARD0EIVT31Hh7qKBN/14nv/zk17nJShLUTAcmHLRxr5scAAdyZvoSoSyhdvgC1zbPWk2/gf9ZVDFEvvYd+uqeDzAvSzgbHbgedJWnwkvLBWqbaJ2mbiwzouunlIE58ho9iY3AGffLJ2AjJTKIZegQ45WoViU+vq1/KOnAFzg617GdvXt6QWbpFN08Nadrt0iw9RlvodnREAMZWBjBgGNQkEE4vOG5fNTMl42px4Gf8ju/jigETzDlWEEghLkU6Fyvruqbo6rwJt87PztLPG+7yK97OszpT7iA/Drm3beNmqziwXWURNr5Dzk1i9eZ6OOEzH7IvOnXeEKKyCSQX+Xmev1jAur79a8rhbWMyQanj8YPzXF7hZXluHLDgZbaItHUYJYLee8GcP5+bJBjs+x2eD09VE75oxwKtkIB3+F/mX5hstbEPPlaj4BQmGvZCEa58AX22+IWy08HQbgRigvk/RsAWu/2mobpkijecMuJCjv8ve5LFlXkNEBOFgaKiX4jv1QPdr5TcHaoHWLLupjVSNxyCOMUn+2NJhZQs0wOi272bRhR/Df3FIruDhkP6Z894+RcO9yOc4iXX/R02Fp2ZJBKA+A1E7iaIdW/A/7vIFtMgMfMw0SVDGfhDElWk7DvH6RuI+EJ3pCdHQqc2WrhtPKiWFrr6KgIlQymlkTELqupqK/08ofsPe6S+TenQOPcY2VDUrfYfLqPz3VhG7wvYeibOdoJOYwxcTGUhlbKS0hHOS3FltQNOPX9esZG/PT4MlyIHQsiaF9foNIUPERTT5wyaAJZyGyGZ8inUQdVdDipQWT45uzm5DyIo3dWhu3zEKrYsa2XxrimehxVXgI+dttjsO2RtcT8t+VdmyCG5LJQv+yDIE5aoXp33aVZjL2NA+XwVlpKNnhFf4q4eP8JZ1g+WFV+0vgyIOlV1FlTZVrdJig31Aw0L0Mw0TFlUrzWTcpAOehCFYFL82JWijZem4Q5ff8bgDFs3YvN8e5FiphW8yxOVWY9GqtM5HCQu/gSUSFpw4GN5TpK0yBZSgyp7d68945uwp64zR38Abps/a6D7slX5gIR6xBNvj7X24EOcGNECzjLUmJ7M5SKH+tU0/eaQqhIqairrvqqOMMQWSd/DonUeF0RJLNT0r/hVT5ahHUy9HNBdegPnYWLTBzEvv65UfXA3s0jMd4jUs5JtcX/ur7Ut0xaQO/ozNOfQRyQicdQqtuKkEQIv8M+bNuHn2h8egYpd7SqBOPwGwLxolsOP/6BHHPN8c+kI0lzAo8ygWosvU0H1bjI54ECwlhjx9dRc2UTq8lTwEAeJBkqlvu+nTebw80IIUgpMnaAnz0WEP9YniELj9RW/BaTMtd+/2vKSy4ikzRwu986fJSpqnNUkht31IYE8OtIwcWXpUxGyXZw3eapWQh+ZQhWd8H1H5UKHPqp16HVIXJ8wpEdWEfRl6LTIjUN1LbqI62HQHTXMIc47pVNwfDWAOsS/LPxg+72OIvr/No9MO+zXt4B5E7MIeXQk7jq2tNKRuL899UYdmFqAKislhZaGpJCyPXN3SVIJSqEJkWGz79iIQOKlORfuAF0pKS+JTrdtrkTZ8AAgdvudB6iN4fIip8dvF8hy7m9PZQs8QTPwuoXTdLzVzjM2TGZLPIdZrSeR80ZOZElbE/Z5N6J5FHVNwswY9Pl35DHDZXMXjQuKUywxApdTjablb9ZoNlxHlU1HEc+tedqGMs/MZlhz8FfERjG6Qv3NUfiSeRLrin/B1e6LHH/4dLH6YhVN7GU4myBaMAugpw02zmcESZdH4xk5MHR+6R5zc5MFAoTpFYFPlRpl+dZvWdyQAitO2b4XHGbwRwL+RJrrjomiPQ1rIeDxc2o6CqUDWt9UwVXLlIpwPdlnvTrjyuL/A43lVtsbpHX53nM2iyX/B/0uVB+x7iSzELzN4ZSI9h9z6YCmOv/zDQcQjirUDxyyR2g3AJDrZMCKKw5UTm8w0MHOOX0Ckm3/r8zMAT50Gd4VX1ECgtacCMI/5LqxSHXZjVOfcTghPboswiQwLgeU6LeDF8kZkNc5KV7rCfVWU9j7JqsCtznoXHKwI83l3dhME2gAKt6uF7e+HCHExN6hLlPSFO0SIaqKnBQxhqwUNMjFtrRtKiz/5P1Wgx1zQQTOxFnEbzcEO723A1yvsnO+Cmjl9OEggpul+Ru8O6lvaBsVAO2+aNvFSSXp5zAESIoatkXd0El4mBwjjCVALTfBc2WKUcbbb/o1GIMEyHLU6EXcVgGrzbOSAk2vzrTvDduP81vlm3IVGA9smp1r4yOThfFxbfcyYKruRWd8wcjRcOOGNG1HD4/CWe2t2KGhg/jO+ia56iA3Q87KPc9MP0wyc+0twlTncibKOHbSyOfpVTbjXeX9ropSzJIFpc92zxhH+D71FQANJk804NzhuxEe9Y1uC/vx+j+BoUviDWNpxgoKv8uqRqxu7ZKoxX1vslNtIUUQkdO62KYRFUZ+cG2PcTjFmMPcyWnYTlSxgKO/uhYDCfQHiQz8xTVateLMmeagreWinnMCVcUr5Q+a2qXwlznlKHvS2/oYsadWPwxl330+nONuAH0d3zmB7XUdIE2u45CqWzR95UQQ+kx+X75wWxjMQW3FVoRKsMVgbiyBWPtWqq6x9RHSm3WGIgiEEiYKoJ2mPwwlCaxTfMDuF9c9b+6OpVoYn0VjTnZAIJ74l4X7fvyKM3QCi1P4ZGvVFIq8FQMrc+cGA/T0p5JXGjELnzDku4gcP1CD/ZffvbSQctaqffNsl5HUIsYcYqXhjbpRNMkZ//3u8FjSAU2BbVH/UsWeswDNUeHeN1WiXhfMNwnE1EEaL3h/dHXwBafcnrzL9coRTpf8hwcMo+nyhPwSotsHVkEfgUstuyIWWFHoh1uZKx/9sWFY77vdFxWgR2ZvOz/JZxW3TeDtNm74MdyYzznI2d8YXAfUd39K6KDdyEV2N8Pd8BqF4eZPurvIXnfHQ8ZZ8thauKQryONLCNTdMzRJcyLUhKbsqqcz8f1j3/OQtx9is4JqnxhtnAIU9+gy4Joa4bB33+eZFv0Q5iBsAVK4O3iTNhleI5EXPbEa/grtXNEOoDNiLAGLVHBjkJN5IlDNaNIkM9IXQyWqvVHImWiClk+kq88WFllVgZvdJ+VFENUbS/6BzWnP6v/FWlLbKJgSUyjV2yQ3YJ2ov4JGerZZpo5S67N6J3R8a8esCeXBzbkqMaXQyDG/LaTSsFHIcxZBhjnyk5rNzTRlYmYf0JhtRFBZBzWPaPGgYnMY7PELrNl/ldDHiUDCXcnsUeOmptdlniLh4xwvF3496GJa8zRffAyPci5g5k+1XfxOkBLyIPdIBt1eYslOuvUZer5ZrARLn6MM1xIp15OngD5xsAyMf93lEk/8Jf+tRCwfkg+8yZDT/TSV4Af3H+dl4CU6EGqFQTtrUh9GhJ+dv44RQZwSPEq8oLdpg5dwn6lNCFmD9/Zs5tCDaHwwHK1e1+BuSxYk3AY+AqMvpwc9L7yZdTohzHhT6tf1C+yIhn5Lf2swjV+ANPdjsF+hH3hMo7YieWtTzDxm7rEAIqXG4KdVc0nplzJy9JqGLltXSfzRj1OUXeca20NTxiwNSA8PmRAQBLVB5vEvQC2J+O/JImj3mcZncZJrX1cdykeyWrUw23P+HcDztmMsnWc4wr+h4nQe9vaw33yUawvgtGZ4yo7ncJa0xEnoMnbw4kRUTHZQptye+VohzK7MVuy7p8Il4e0NlLUS29aIx+YkGVIn8r9h28VcAYuW3WAp+ToZqOaEUlxL1X+sy7vls1/jESJxh5qzFTlXOqELqz3+74b+xaSSNcsAEMdgb0CiGZt4lsvIgESPj7RFS6shxP/VBTMfdu635hQTADn7bcOeS06gywwNXznHXel8ht11EcLNZsBGW5IjtjX8kkQpXaC63x91WAscYswhfNbAA5ksGs+Yxdovu24RhRwfg8+BpucOyu0tEsoEQmqAT1/3/mGewqwP+WJ+fH2uvIwnlZYHlzXP+Hnul02dJRZAxLtkoREprBnPhNMrg4GMt6fh+u3LS69Q5vjmzhzoxPs8aeSczwIOpZUcg7vPq/U096pLUCVXOuHFfP/LTN9t8PZL5+Wc4D9rvDkvCRIjnFOuOVbH21eYYPS6tCtUUx6E+q9EUNps36W4U22N2wnGbcwYa1bjZibh7FFM671sZ30Hht7WU8ArmXhhs17WeyfWyaoncKtbJYe5vBrVfqwywQ8uwa3vrzQBvaSgVS80OU3l6HeU/QqNlEcLea39cUtzI/8mKLovRII2FjtbZY7wVG3CyeYY+hPjfsmOrbbPcmjv5ty6GP2lnKcTduDaZ+W5on2/b15HkI2B2dKMbuvJXEu3UCFyPTIMYqv3n/WW9eVAkLIe5WqCr2VM91oHbAkjd7EjwmmfOh/NMAkPL+4J4ZRX4zu1lrxQQh/hlZl39a6fPvNbWvzzd9/AJwi+0bHcLXUUAW3phWJmpK2HI5XaNPUSFebn9iuvf6ZEz1DJr2u139/1sWgYZ5H9ErEWf/EB9EoULCs5ez7WyKdSkPxFMqfzICIBi/+j8z1b1bHBCNIoykxBhFSiq9/CcZaAHPHNb9GHt6Ufahxe9ClRtJQ19WBLudxECIt+/2TwAxkKbACu7ihTZgcUElguqgoONdT6Ez6dRLWhBqIcBqZ9P0XULtqZQW+ChVf+Qu5ykCGrRLu4BsfiLIAjyy+O3YnPduEg9CUUSlQ0lQkEjvpCWFSXaQudYNHL2tkIAikOSwKRPPF1BeQK8+G4DueeyII+rrJGQua14Y2mMfF3hmQyc9B/EykNbJJ2U3FLW7SR6sy5/r81kKNJR/vmh8R4Wut7AfS253Mo9O55apQnfCiDhPPzK7IVQlG8/30iDDFnkH8hdN/eYeYIKmSHnxi8nft/Dk8fkHNGhj1Si5hd+KsHIDpRcFgREv1alM+yimfUV7RbUC8ChqbicVts5n+9fjWXwWgFS5VCcvArtDGfh4rJMr0ADIrbZQr0fpEw/dfANVvclCcag82uYAEJV00Ri2cnNfNgJVb887ngMb29BVCJrnazcZIa+UsTyi+vbj5uLpiQcP4RbO0yDOdnHLW3VhlbCgMBlL9GxLWagiCB65cwJt7zzot3h/+lYzsKuE/Ju7OQpqCSYqYalKmIsmMy2ZunY67vktvkKqsQEogcs+ssKgnLReA91rcm/HvsZfepD/B3DVPOb4nbC4/IjDFgqaOSvj78qmYOLOCaF+zr4pSuWRZhyoc7/xyF5G8BzXUq+HYaZj4JolkE2SofUNHOhs30OoA0Fbz72GQ1p0pjNynQi16ofyXDgU41SkUPFE9VzR4AgUOi6btNkUl18qS5j72O2Q9GGCr2QRSpDmIxRAYNWqrZLh1T66gAeThYpEd8XkyG2pjI9jSRypRRV9uiQ6xfoZaL7Q1hI4du4T4NJv3x99zCpuM5Lu3TL0GWyYjJEfgbdesHqq4DMHqXTlqKnLh8Xf0qMnPvwYnqudY/ZE510Lp7/opI275IV0WjdENMOl1YejkpS9huXkiheUW0hLf2ulimnpxzEpcuDRDQZMWWvs2Ql+utETeJGDNpE+r8OAwXymfkYLAg2Ij8V8f1wUWsz26JjRxEDMLQKXQF+yIUA3eHhKswUrTZJQYGXBAb1+7nicwWA0cx/Fgi1ADQ+VQ3QdULq++J8bodi0sGSbw18lQgWE/2Yt3qGVjmCUCm5Sz//0t0pZPUxAsGYJxmcVr9LYfgXFxkFKcDdrd8odQtk/naiHrE86cHr5xW18zqa+CJfQSw4zXIC4kndtpIguXwe+aqqnqPORhT/3OQ8VC6X2omVnWIJbrD1olWTKVZEKjTQcxK/zvQ8VRSYw8v1Jf4Cnf7rQ4vYonM4/Ve7o03LyRB7GfjJluieAShsyEToxV7AaljzQ9XkhepWs9qhDuMJSUuBlWSdFIHvuTTAsw3RvS6wHaykK9bRzw6vcmpyN655iJ/kkmKw/D8MiuBLh44hsiP4Hxzgu857YuWFwtl7KMDBnyzYBVxP92DuCTVxinyU6R2DsL1KAY2bIRWp6h0aVxIIs9MYyP44sJO3z8s7NatQb2V2VWThjb1YshcEIlciFgIiy1VLGjQ1GjlSisixAa+hKCimn5ECb8i2zWgIrC75Qwg26v43Rzwzw8EzPip2IKPjOueeReJSaHwXqcrJF4LZ4x5/kI8zBKmHZD9UkYAa1U1rHqfF6QcA3Qt4eRVmOVgoOmro8H57GhzLOWxP5Cx0BNHUg+RhOzJz4iWDl9pOHEUG9yC7+AFz3aisHI6h4TJDCIAhOamxqmdiG6x1uaHZrIf7FsrcX9LRaLnlvtCuClKfD6kUIDI6JjRHgrvTuLG9aApmylJ+GonL7vL155DyFtOzUQeUNQNczfth6Q5pOf+Mjq5GCI2OZvAw1v39tmSebrKuKUJT03CaT58ReAfObLWfTIV+L/DhJN0Kjf8scDozOAmG0oLKeZ44/wbLEeCo/O9/mn1bt3VbE0H16vf7Qg6cggC/JnXcRznV8jcWaP/WZcJl/mgps6FOTp1opri8dxcuLi81WifSbP0cbxxgg46WMrL9qKyStxiHr9ilNgTkCjd+fvqtPkXmyP9SYTp0ua2qYjj4GtZveu+g2khMsH3MPdA5mvPwA2Zq7v8E1vrz9U3lfJhoJ6H4uFkQpUiSLVnq33ELXuHB7PbbbqdyBTTohkXfo2NT8yLSLb79t1NFWOJqZveQ+QaZOzzOyySk0Tkf5OTcsLtYUlmWHk7GBotigAJU9vftLkYYF2/VEWDs1/6wWIZXtyODm5fTjgv+WKO/J81a3sNGeUV/rkNbEmgcpQQN7tJtzdEk42K0dwxq2USEchsQZ3qkKHz4ll7QyWP3pWY+e00GjU6E0PISyubN2u6XKjnTF38UC3nGEEhjmuqM6wJiYb+mv0motN9DGV6oEx1E6AlVkEUSOd6oC3qjo3pdi4dM2UXZeJmP+H8X1/arE5z7UZW4bhn5vTKHTNVG7SIgmRmyvxwMVQWtBJtUP3AAk+QYokJ0/dAH176Lf17hMj1KUSab+D0dNpm4SVMv1guH/nvFrXHm/e9W70UuWqjvQQrLAcMQ8FO8PoM+23tMc5CNXpSpDlw/SnW5/7K7iYG13qVdj8oYkbT6VG4pd3oZI28EpKZvPk5/rGCNhQcUwl2/c57hTIr/IaXvaAwppG5AkQrmF972rTswfiWOtRIXSY5tH6hoQbh9HFEMfRoJI9kT+xISuarq/j57trSC8t10qvuH5iXGBVw+nPHsHvyPp/ASsiSr8xaktRA8Vn5AymC//sZK7VAWp0X8aZDczK/t8ODFUnGJx6RjfqlRJ/hQcsknjogiVmkO5pTCBjhOdtLWzhIaUjInSpZYL3qtkQsMmN9WRtFbO4YrvRA0A/O3c/BAJKxWBh6CFqv4lJ9gOUh+lD0pR/N6FPI9qhqJAhsqzPVyDtgXVY794XOa3gEZPpKo1CX9NUibpejStnIL8PrJkhjhbmYjfi6FdxzLRZDsfRDRfZ2SL5mlEkgmlrr23r166dCJUPpPFMO+15Ab5RincRMb4N7k1nB++FumCuuy+bA6O4o/XPN9UNFEJceMSvSxj3JHa3+V8PapiHhzvu/jzXy4KDaVTHrrG7sabtacBugJkjMASqys4r4z/rr0raVSchskPymwLdpwPRfY2F8s7IYS/V9BcP6tn7vjgbeYw0RdiP8Fz+WBH5x5ZI8fzQ9XRV0ip04/T4OEO2nOgjkLe0PlXq+pqMUwBzXS4UkSpvP/idY6PUJR8QmhWHEA8Tw6fV9nZ5melLwepkIatcsrvecu5/O7K8fjcqEMd43f9jt9XHCbQBtQYMfonKOMKnczA+kCerfta2Lx5UTQ6bK3vZH4gJda9yk2WaaWeBOFA0sfrYhaDVPlNt7uEjq8NHyuGfhSxj4d7MtDrHta9+WCURinpigRjXpO/LbTwZ/zcujEX/C/uHUzjEo8lEjAtt2WneKUJe1m5+YDtkuXjf/EnINMX5jDP7pO7Og4SfF1wD58o1Ae6tYEpQS/cehqAB63pnWtBz0Uic427W0173wpZe74kDvB36WbxxCJFczRA299cKk7hAFKfe1eWg06dYegIDoJ34zsDz6CYtCPjhKbbCSBrcxANeGzRS3OHJbqOevKeuhP2BcHHzrcWg4l5ws9NRpd7AISsGu4dGn5AchC2MD6fzOz8x0WSHe0VSZsf9Qz+D1LLqFkJIZpYpaKG1NLtKrPMluRFUT8wfuVnVBN1MuVNSmuOIbbFAKT0Ct/gx/pkv8gCLbMEaQ16a5pdGJGxp0vxz8VFt5DllqR+yra3gjAkZmQy2XCnRAS9frR12/AnMJcfvMkJQaa3kDe42Z5qki6kYGRM28AZmo2StfTrIumbmh1rOzjfpb47iFgwJWAwjz3LRylKclrLcRvhMr6H6cJq3ASZff8sne1Ilo6n3egl6YALMA07TafNyMYVXCJYR/GIEA1nQ1PY2Fzgr2UdVU6/2KobKAqAY6tRnOPPJcIcWwN65kbJJ8fg+ChcQb5UCj68rUvfrfSELj6IFlumgajr9erXtkQzw6g6OR3Q0s5cT+wCfS0bH5FzmGnrRF01lnHDP204yDM+xyHA1aCXtAKwo9ugbuFTxidyXVtmjIcFhPT3A3piBcmSYP+HJZSOrnBS/RVGIgEJU45Xh+0Ya/Z82t7wJlXPVsMNkQGb4tly3KCXHHpZ9JjewmBExFj2ajnkjSaltNpknAsK+qi6/CYHN5T37HPJR1TOOwynOvlGW0bxI/hxtKsR32KH0v3gxcM8Lhc9O3492/l7htQloM/ueGmLUFHwdRaxuXXAXFXeXrDVNTNXv+2CbmRE0ENZiYDXH167u35cSmns499SekNhjoqm3cM7vF2BZGQ2Vbh5/RNFZg0XIdU9Q7BFrTBo/CQ8sk7vKOe7eclPFMSdGL+fNfJrusENLlYJj6gqiLPCQRApFeLIAzbJ9TimPiAR/KLDiiVIwV81uFVl11/8bUNAb9eAaM7/e9Fec240bdoGyvA5H2wRb3lyKYmNCEEPFqih49KRBepMSY/VgWviN47OdmgSQjKeF8k3lfMWlVkXBt7y6ods4umxmrwNFJjXB5jNOftWE46PkZbFwNZXQUeNte2Td9mHMRx2FsUHjPnYMVItqxZ9XsFbbIF/phSz48c+rD6py67eWGeGrOffibVre5tWx6VO5kaWUMbhIQlexrgBcD5ajtMlR/3KZtfIFxOZBwEqQ9/foHXnLoQXc4PG5Z8uKnr3XerQpYtTLyPuQpLloJOHD7c4p25MThXko1loOCPuIXJx4Y2IYjo0p9lVaY51Sa9mdZddOmjcjSYdOPNnyd89fTshymJO2z80ymnpewN2czhU4S4Ey/UJ1bkHX/+Ab5kl7PW55oHFfr/waaSMGA+/gSMgzNCK4Vb75uGt878+BmFBFo6CWUufWa1cCLrubg+9Y9UcNulx6jDP+9vk5jCOqGCUn+fdKRbv5H9zuYCVH/2BPa2JiexWe23wkthjFNSk/wi+M6enQnplJcRt3cE7aQHuoRB76GPp8ysd/hDV/wJfj3shQ0PZ6cBNERpBCEH/Cn6a32Ngl2MkOzkatYQpY4MFqghBY4lcVMNBF6d1jHHBP/aCT7SFyuip/Z4RqbS6qIPAHLqnOsqKpye5SogaqGOs2AHfnszk6wYNn1gsKoCpQZARPvhEXYbPBmLY2PAq3gBT/DNk+TjDE8xhoqFZcCMhAASMeNRk1JABjrj9GMItNhguP9z6Cg085UbSA2pYlo/h44bQP330toN47hwYKaRKFbBWVVbBWvYvBaY5EYA6usBl2mx6ZAvtf4em7p6GDR2ihqT8Yq+L6ON4r9Xq1huKQRj7H+hEii56UR2wdYovOFGBnarhkkLiHItpP1iKOzJHx6ULQpeJy2zjznGszgpd1BVTjSkIDlsCz67Nn8ejhw0/6XG+n+Nghs9KFaxgtZ9EargU+JFUpOheO9npNrmd/Ymn5idxV4nLJ88UGCyevefjyo9pFaIO3CLl7nwY/tTfvO8TR2Ah0pr34uWXFQAl3y1a+Gg9yF23eFBpF428GIYCMoaRTC40nYx2bbE52MTvTIwtg1pj5hA5n7tEzTyLs1hK/BDzCeHkrJiwAzzoNJ+TbcHMZICMbcQoW8diPIIa+xLgw3QAPFRE8TiKxAjqiPjwEZu5xHu2Im9ZOPEzwWlKCHF+IkDLpMFn1Tv4hMcx+SZlm+5I6u2kQj9eArvsFr7z5jvhFQs8N7AiW68GdR14r5tx2oSspT91Re/EQ99xvKYPqLH/PfyQeQHB1mnXff2JVHsV5fjgeQ9EymTv4o6a8Fl2CKc4AxroADgbX5DqzK/w9JBmgKbvK+7VKBjbCMATPY2Kmvvfeys3rSZ+m17/o+3EO2s0bNnoBBsp+FgWiaptAmWFSbl/UoS2iK4vD0UVhrem0c79PR4aAaAYZXhRoJW3NY8z5xZf6sawADtc0fEBUbSMoLaucKnDHZ/6ELQzor3re+2+jUmXawkP3FhHOyTXrHHRxLwUYObPJ2NyzCt0KF5Vwfv8gIXx3i66wZQinX9t8Gpf9HsVQh9QdtNwt32sSYDcv0JKu+MSn2LIooJYtp+HU5nY3jq/PClVn/5pCptqmyB6ojk7ky1/2G9/YL8kctly0jzlN7dBkZQkibclW7N7dtm+/6P/69u0alKtOZQgoLCYxapN3xtOmyoHtWQWk96yRq6t/mb0EzOIUzFZ5+XJm0zf5YVacZodnTT7E9cWa3RtDLgoLd1xQ7ZBAJuNG1P5Wi+4yj2IJfzEF/pYbknTGbbxVgNhTkyXOZs2vo04M1UFe/Dm0Fi19DNraPhCe3c/AzTTZWw6dRgW48AcYT36w+sdnkdr78B7RLwr84ZxOHmua61lduJk2lffq2SrZJCAARUIqCop6Lydw4sMR3rAB1glGXR/zr/vgNp3iUsr2lzoJRy3u/S3A66WTxYq0gee4H29Sxx+8dhqAaoApJIA4nR44Q37ka21sS6q38LWD9KCIWIYPSW265r3II8/g1kpe8VT8jBUpmjiTSCw+Pk86WGSv3uxiJpIOpXJvA+2tZ++LkYuO1n42fxpDVpcvMIbojIl3dei/PhRPauXW7Z8LsFh+6soWA/PQMe5NS+V2r4gwrOpHxSu7IgKwDU0wxqZeQYN4z897hl7AHUhTHFZdCHn7M06yqhxsgv2Jv1XvpjvzrA0MZsMVDdksHqEkPZgDFnVWzicNkGIW1S370DJGC/EP/vP3jufl9+NkhQOWh8rZzY0YKnINS0t4KvwpkE0NGwqj6g11CziTzwVlBTen/xqg7uf9ZByBtPSSfE01HWIOZMKQNX36KvxexCKaEsPg+ajEKzc3AHANfDyuJqiXNuOpOs+gIOU5ua8YLJyTXZQr+YEJB8ys0GXDohAZCEQ7LozsGoGZmkrsR81+fPjquIYb6Bgd44YdSu6TcG7PG8VMDEQhPMVmba1qXB0oVPDm9SbC1xfmUoaOAPS4c8uWhWwX4Vh+XLiZEX4fjHxWbVOs1AfRTKkc6+GLCdEQ7ziPk7nYFHsgqtBioCylWqXR7aJ1tdc6rHHTH/TBb6uG9Yl0GQiccncwKBmlxeG4SnRkDSjQT76sSaqb33aKZ/wGcSoMKBnPTorUN5zSCtO537Kld6xu0Pm+/O7338IVHdq97bFVXymWFZa0HGg5ftetncadWKpHRVYeQkVAGh2gvMtcCIy6ygCB8iuZUfZUdxqM6HzQ/CCiAFiJsaJd5A9aYURC8yMXWv5FBNDorLC5oymUz8NNalHyQnOVy5X/P7EhYhAL/aMkUVMiurzMPmR14s7+dXjleZBqgS/YKRdOzHHkzBYRi7c4Qpnokvc1RmZmxOzxvf8S8nBlk8D7DuZmxmlv9Dp6LTEqEcohA2AYYM6m4p7+Em3u9atPGzcdTw9SAR4M3ZtHpctZ+RaV7p4OtDIXmxV4+RpnNEicq5KcbZczvruaf3Ueb4ADLHP4YAiaLPNsZZK7uoWS4gTNVEwGIfU/CbUAqwjlrNoaW66kgi3oVCn0/m8gMGxwb24fUP4/o9ymcLJbctDQNdZOnKRzyP5SJQ7gXsrdJ1Uu9Hrjh2Gd+A+TMjFpTN76j49O0uO8uSuIpzxnDawTYJcy1bXMmO0OH7HYco8/7l8vCDTg0NBWOl9b14j6w0Fx6rB9daQRre+MLia10RerNYPVPRDZwRjJGfA4wEXs/gS3hwsOrji5kJzvMtPPqCbhVOTR89Z9sirAIdBjQErCoTG+Yrk89cFo9H2yvoHiK5aTcPjMVujKuBVrSY9FQ9Z/KxcdR/heB3xanYhWH6BNGJ00dDKlPAV30PajKCYSOzVaJoQ5Sd0TrKlQfLchyCPNn6FXzq4akZIwb9PsbSGU7JYTIPLuGPsQtMQRbGWS2DFlurN3MIPnjJpxoAenWssfl4OKbqNsQtDrhAXzNujDAAk/kZdlqw6Q6g02PKqWkEQfbCVoun0soGV5FnkBugqBAgmjfPE061Rb6dTCQOC2OWWXyDFUCoqEmV9JxMEaG65lYBfdaArXqP8WEbCUbDDaDZXwRcEUx0KL5fUK4udGYhCCnKImj6Ca4x0nd9bdxt7KxA8epK8OgIAEks8PSzQMUEibTRraS9AUzYUne1V8d0MzoN5ya1UGID7C8VHp6yiI6Xc2aQRRQhr+eo4fCoWo9zF7Nj2ZggZnC/hQRJWVLtzk53XIM2OHvAny7Wyh/ckpzvstqk1eFXpEXEznNDUbuxs5lCBwvRtZDSaNxNsm5zD3nXGka4wnFGtPzURRJUu9KrxtcTFF3fkcnkjSkxFgW/Qj0Y0AjvFjXy/MDb6LgSRc+4Gtzbd+Uo4TO6KzGN1IteXMUXads9+oSs7hphH6Am4o5J1CWeylLeHXkryjWb2ICXoFQCobqjSK2+DAN/o981+t47PHtMvD657XpkKYQdJ6z7xkpdxk9TUvRNBG4exJyyGevY1vbo3fcaIiT2FxBuLHc3vuM7oEs4u2MtPS3TCk8vLw50MpKH3xyNcXvmKO6DqCXMp5H5yLLMnl/2/mK3AHiQIylI4C5Uexf1ltSdGNKCQ1rUz/nuL28YmRDE3Ab9x3M+NTMSVyhLPXEVHzunV5jxkM0e4Sq9mOicRCEyKfK26pUCpitikWQcU4+qGwI/i5k76zTr6oP/s8b2TIjlBsZjIAD/ak82cLkmG7/oIrO/vSMWig6tnjeFV665S7334YTegsr5FJjEKhkjT06yxL2FjG9A9ngFmktsCqkFR0SM3eCJN0TATnQam//M/xWQwxcdNXZQqe0hJi/tUHaolVpD9WfmlvuRDtMqOqe5rz28+FL7qvteo8dldxV9pduM9CPTFmbS2HRyT6Bm59ldyVmGOhPkYqSTRgm/mCkYeGkeyEBB4LvvroY5OR2fazgAji8feWBIgrAKl3pjdVTgAFXtq+HJ3PQmYpwmFNdZagkhOdnjga9h+E1tduKxQ5s92RqfsxYwGmbNgMxF/MOthRoKpCRiVwbOm9pbv8nIPZ4mXKEc2e5xxTmVcUHZ9xFox/i2buuIjRpO5QYV/3x4sM2TeH1GtVrB36JtwvdGd0E9wnIly2Jn6cnMSwA7JjtTA3z2HGoG0W7FFl4mCfzYPvB09QU8qazXZNljsU0GuO2mfByeMNzGHcBfHbSmuo7YHF6HpXIqm2KeQcuiuJb0iMK5MTBshzCVzZtxffoY6dkqwaHKInLJI+Yz9f5akx52yR4SObpX4Cgs12V7u/rBfo3bj71J3qJbCs1S1nHp1BdCT3EG55cOMmrB4tKI3fhxW7SuZvxkYGNCoRiWIFmgTdlcjBQY46hY5Q39/kREZ0IbVRyFIkWB8oBDn4MP0+F/1Wp5625KerVONZKO8CIi8xYoGkxFjbqrq2yr5PoGjKbF216d4bc3rIQoZD0jLiiBP4NAswwf82NVhvOXzXl/ChPklu0L+mEb9uRQ+rIAZKbKS9k2roamXB+3zBQTmSyvYJjF179vZ8d5XTo1zHt4mMpdy2znODuCt0jPFG7qx0QfoPzpnq/mfLTj3vTRnLl4uy2qcUC8yb00h6xq0czjp7M6iRE/BTXakh6Vz/XTZTRsrs+OoT4dQqpFxZtA5YqABXQ9a70YYdwwT9ikoa5dg9eCIpX889J9P7gK1MrZX2l6JIZZh+p4edYULgc2dtk1CbSQ1H8qk8zpQxLsgfv+0jfcQHuO3d4qvWy66TfcDfZfqin9lvRZU07K1waGANhX2opwxx3zaDlq/rSMkbMQ0RKn0l73nrNA89ZBi8o0fkYoMMlLJ5u51yYhW43DONixUJQLuMRm4D5QIzvCpsaoHz8GGEcSnG/uoM/QR1fUw8rAnp54pN+ClgByXirBc2iPxV5KebQ89n/g/5T70o5Fi92EnIqZBC3ode7dWQ4Omuf6yo3oM23OmWcvqT5T3XoWE9HMLHE8wsDa4dKEW42rZKMn66T5iSaL30lfkU4cGKovXSNBxDcRjYKtexFfS1/ufz0189MWeL4yXPJiUubPyRNM7YU6ToIAdu2R63SmpJK94KEN2wNyIRfKi4+Jm/S4QIpe2U0EaC+SXpsuvF/lfxg/3v5SfutJhWgGbpK6w/HJ66dZ2K4VpOswz8cBY4uHjPx3wXUc8tjjGyo9W1uzvJgI3BIdlT7MsTliTsZFYyja5ydz8PTmlAkAdLWNmB2DK0Hy3cttDs/TGr/KHs7xdQJ7WW9BNiEm/SwVZc5IhR3paHyDixjlaMx71Tbu1CyPs0BsyYeMhUteDNTeA4JiJtza88XSI09gQHptqtiABgE4WXckLZ7rNcUiEuWXKTeLPa9GmdRv1/GSPX4EXnBw8fjZGzACp+PNClH4IMMEMVpTWQjZmny548tzqQvp/xyM2Zk5PIu84jumYSy70d6lYqGLX4uC3H8NYCArwbNggnMFtSj01PFhSsc7NHXvKueaiK5BSYW0CAC4YE3otOJAEBxZBqHC0lfNBuyD4GFMoEL/engswO2SNkQQqDHJ9Qz4e7RhOAZADHncejw+xKG6RYKocdq5Tc/l5L0VdR3AuOxF4qD0wGjb/rCbsfnsW9f6z9N21jCuJPxqqk2l4Juas9C+7qJX9MBEN5WDnrh4JsiNkxAXGKwGztFsO/7fjm25fs9XtHkdfPiMCn98L4b5UIoMG6CySpjzQaAMkHSIF8F8QNiyif10CDriOOE5wtz8ICqsZ7xKsDAYLWwBjW0uk64kbWXVVzw+o/qbcHgaCObkSovxbCG7vZdV/0kamUyY2iZTo1mbTzan4SOHYXNGrHJhgb+e3YeIZoEUkxIEz2ALFOAZUdMGeE7ZPgMHWanhCFIvEcgtlSt5fAww2AWl4LMtThdY+A2AKFdUbeubY9vVJnK6bEObCRwy6jnU6tfMYor1YJMLxlGHwmJte6SlLuv9tKTbuaBCYUb9EkPn+4nBdv05X97+8sf7A2rMiVzGL2BGioGcczKUP7Pqvx0x9RK3BEyiTI61Co6SZLpDlYHY23vXtb/3pVxGictz0gVfVRyvPbUMd83IAIO9+abTmNVDhCYP9UKPiUXn/rMaExrocfxlKtdO2cZxT4C4XssWOfoAGJ+XEFfA5ahhNqSkzMfBq1oSYPOxUDg2xgMxl3w1wDmn871SnYpy2ooRhdfDxV2eWrGYhvKJN7EaqanAAXTsksbRvO/nnH/uNUk4xAidpSFUD2t71QdFXjfpFuDQ/7PEBI+AGyvZ9Hg3Xh3KvWTCTNvo9Z62Fcpxv8AAAbIWE3PG2tv3xNhd2pw3aDO0jADKU5IEi6ii5rszLbSTnX17n931kuKQs9zBCRZ/imQwhVZOKJmzo9K0s+PWiRR2gvKagVvMwf1T47RGYj5UPThT1fOIulIZU8j5WJM4mBhHPgtDRZaKoQTQqhBHUPrmRsyRJAnAkyohNUaFIFUNv6QARUwXZKdsFCgJ9rMtKLPSCccSgLbfuRYSfCNtDxFhe1yVQPb1OjWmiDv4m9+uKbJ3dKOIArHfUocMxfKf3PmUXq/iWvGgZLFb2QkWXRVu19ochj3PHDKbeR0CmXTB8yaEiwTTMRjNthI/uwpsRfn3ImHq2PENbjGZR86onbdgU3KBdsohKX7a2MRoIzvXsAyLIk3O30De7eJS6X05Kj9YWqXzsz3UxyEr5TL3kyyB21ENOT6a388ef7kkpt2uHlU0Dab6GSPAepJpGTDA9cBVaFZx1PtfChimy75CmUMK/x+fYCt8+I/EPGcPMP4d07vPxkSUVYUIzSb91/RjxucXz/k1tWOKbF0pAMgJSAvCC08Xp+HrREvW+gFCo9ErygFo/9jmJHT+CgFEgpAPHM6LpH8SLal89PiQcbqIW7xmmQSq1dd3pzZJ2AAC6v+P+WHu4wgwxWt+dBXDPin2Ccw1wFN487bBz8n0Lta7WOCBadO9OLvCtme7CsPBSLmXJHHD7E6l6JnlbFbbA7Std0m72in9AuoX7lghwI/RRCnC4+vYIO3kE6yozOaI6B8xCDH5cgKXPxvVCvFujlnZ282fOTp29ngGgk4yIOv9TW1w74CmJEmNJAN7Ngx6Wf56egYWru10cAQ4f3ecZgCNIpw2l1KR7mfOn8i78PJ4gUmqPovczqOXN/g4rVqB4Qb/HIakL2lVxstiKd5bZENu1/dkgE1zNZPh3BQ5LOwr5kfONzuqetzZxvhaCrbMocFwkquHK69/XOIcPTjZ7tymtbnvvI7a63dFs2/cycXQ/9qchR8e/BvxwbLDPwYC5Dxxf/9t4OV+uzNPIxel7tLUAos4OUuaHv9OyicGeo+oR0hEdJl75zF+zC/OA+Cln3WSP3kzEPVyObxNI0I3OGN15AH3YK/hpWliA1T2siyT1mZo93ESRF82gAGlZtZTeUG7LP5b2SJsO9VYkyTYZfKxRmEoWsFVket4hA8J6xC1I3GUXwD9cvctBN9ltnpUbO5gRAlU+3w/zHICj3fR2HGsvKyk4QWL/IRz5tZrSAh9jSgtv1X70JaY54RuY8fOPYq2Qt5DpfsRuo/8S03fMCdEc/sW0vzKVtdhEHD1z7OKNCGeDD+pLBOqHArwnRf96drp85RLrLut1oL+DEEkkrPixB6s17OKAvtDrTd8REnTyUq8Wk6JoQfL2KRr7vYxuSZkXAinizf2HPDJp+XujmNvS9ZXWstyKP2S1EL6ZvHx8k9yBGknNg+FHpSJllMFfs0s4/ZHvR57T4vOHxO+ACjaijcAtBbCzHXPmsGaKjuGGokJYfFk+KFXLvYEZuXy3JaXjZAd81aICowdKF5jWqmyKZDBXQs55jMLuY2tGETYB65RAXojVC48DKwGMx9LPGVEdE+OuaBDRkbDjrmOsqex2toqR6FliNcF26OCGRz3/lMs3RBzi7atDVQ90BGIAa3DruwUlJD9HdP8KnRzLy2Uz7MFunEv9Rgp/h8ea6rIrA5l6zBZAgkXZqWEcdIcvUlSATXUg/Ty2P9lXZsZAdoYA0zJU7hFV5QZB9+MWYp1gJlJar6Kq5JqkfmbcWaG7sqkFTSuC/uthAF/Cz4rYEMhtGDxwB/Oq1Mq7kO5oz1QoJj0aWk35EP7tuA0g9cXd8J6EqNxOrj7j2UiFbDGwFQfUbMFxoe8aYFkmS8+5bvCpHKHywwLe1ojZMwj5v/M9D3wcrArBbjdNZURGzDuhQBr9s6rBckP2Sgu1/qvwxduTIlivr8UqBJqbhAeOyi8OFmMswuhS0wMXzwGYEHN4p4JqK/Xm6n7pH+SyFICM44i9QdLowfRmkDf6CaRxA/Cqrz/RkwRh/Tc0DAWDSbLTRedkEt6QVyjBGO5THdQ4YvP61h1IdlmPT/w8tikz4whkYBICztUtz0Ly3xjLXamPFnVElwB7y8P9ViGGsWuFtJt6W8V9oldhBCeENQLXx5kdL9psxt0VWrwTnABUZyPcUym13IAyFAVPeGsfXQp+Q4OPDBOXOMSz2VKSyi5aOT5JRTicIga8bt4GuXqUNeL9PXqBfXAhdc0i2hRlDBTSVlqgKLuLFXNGvGbQgdUf1cE2LAcNg1jwN5Vkwqt2/k5HRDBSSsZqUC9doxTkOHscb0k5KCWhr4ga6ULMDYw8IUJW6XSmuO+ilYvcaRrdtXRdqSznqyzgebrvdKQJV3dKQLNanlFaCjtzOu6/DzhjI8iLuupN6DaCRCQy0W6A76s9SQuLeMd4TQpTdfMpvH3IytWFUIoLnzTGwHaGwRT8bQSvlWFQgNG2P9g5TkA6rWS0gDnHWgXvKRUBk3Hd4jazFqTPXZMdNAKGBEKHo8caQWnSSy3YuW7ND9kTScfnXmiB13jDtxqOrqz4tVsUEQcbPsQqV8jIM5MJ1vdW6mpy4hDKT4czEBNQFuMas+KBhCCM0YpqaIFfH5bV6kn4AOtJqnN87mntjmoYZ4Ygw65nj0eFFhtLcvkokKskb8SbCMwhEMOb6ws/naplvPrh8Q7U1z90qs+aAr0eR2kiPHZbNEbCvXq2fuLKvI8L3rvVTEZsnDmyScaI+ePwAgri+ajpimW5tOQaPl6/a3dv8yKpmO+Rce71UBso+TXS7NVgp5YAOnQeGZtb6C2mXFOGc7itBZPzq7K++mwsHKOjVcTKMUqUejLDIL6gFGJqucxIp9hA7YRK5/885EhFc52z52z3nv5wvz4CEj8ozyqtxYDxEJPL7NZKG9hdAtKmI+DDpqqISb76t4Cqcyn6qwGKhRq+YXpRdd3pUb+EAi91gcNOXmid6y/dy6uwhx1EQ/VAHXaDDtVNO+4CWrACD7zjtHhkCJvUmKbf6UNU3FwA+OXnFj8uuYKAbl4xD2lRQVZGu+UdGAkjPQPR7JCw57PnUyfjrSxKO12Vh4gXnjF1zv5TjLxzXlC6Jg3oujhcazPQNx2+9buAiQ3Fb6vVADqUbJJb7YWjRqoX1dRB0foXnxX2Dpo5eCGbcrN3gGZSmVCGE9/N8rWud0pem+cSxv96nVTVDeiigk44ao1R/4ds8BarygvtQbqgpINmI87+SfP51NfIWjdGXABZxvIKcJnyeHSvq1YmK3Np7X9xEYaRDXJi5bUKLJ068Br64hJ1/Ph3q16i9aKAdVqsHSNRJ04mdpMpNIGWg5Jw2CKrdk45P32CjU5AS4MFF61wRoHONZzhLjHTUJFN1s9G/fwTRC+6sXBclk4ps+6tCvK+J5jXBLJirw1TX0kTBML4lFdae0lYghDjz6vAHV1MR2+1JC60QCVvcduJuKPEhtkipUoPN0c+EzRI9x71+UkdYvs0pFq947uiodOwovyEMBRtk5MenIiUtXivWTtdCF7Q0Aw8D1eykvW0AJEw6PIPomd6cPz9MfevF0LKmcJw5tg210Vk1oh1rpIrCeP53l89N5aMbHFZf0+wEZ/v/+O8dmbPF/uAQ3PONJCWJMXtwRrqkJCqW2vrvMnJQJQYxVMrvlvH7wy0wsKwgYpezWbddG1V3H8NRcR5V/kGVltAkgKDoWlyGvR90IhhljMbPXYse8oVHN/mN0KviLk0DF2IIKEYpIOT1TLE7ZuKU6/fuaBG+uxGmmYcOyhstZd9xaUbtCXKCEAuWjyb1m6q2Rhj0Tfo/PzHfwmMtoz9KdI6fSsAlywa6nztoBO9AaQYP8hfRHEaDTp5CPmyxz+wLp3OM8Yz22Im4kCqxmqXSfEQ8URCRG2o0NCchYW43d0FXk1GwuymjAbSl4ceOr75FSslJvLD5U+/vpEiw07u3k5ZmqSHrxrmBOb0J3sTR8zU/+wQSr1VpYWtV3bZh/h8td+usVfZhp4TE0Bj+XvIXjNhADTrc8oxLZ/fK8yDyd+3dVdQn0UULq9O6C3aRkW9l68w5Niu8Ph8QJIq2G0XCh5F2A7zLTBB2eZ5q+69/5wjYZQs5FVtFzWhCfAKuT2LgAOy8KHCFxyVWNAecFFiXVqlv/5yfI2Vy91NFT7S02Pnrc3gLzZy2xKsv7K28QKZhKj7o/e5QE1yTplyDDf4OVg6J09ETa0Ml345TXsRTGFkj7VW1jar7CZXRNZg3Ba887fQ3pwk92ccsmQrgZYVFjYZ9CstfZc8UL87r0KrZeFCXCZES4SszLgCz5nRTFq2caQ+3tqVTK56VfIltbhm3/lurV4rWAi5s7IK7hLKlyoETy4XO15G9EFrZADc85PuOpPoNgo4YXFzShQ/jRYLAMkkJrF4XLkuiPYG9qnX2ukcg/rC7pAc9btLkie5N5OQakIFdXHfEPCQSuMGN+RoYHvaUahs6uxX5L/5n1a+CPdCb6aIld/lIMRJP0KFvV3kk0grK/rWf1ZREBO0MNbB5YiPbjxG+tPw1KUHJGR+qoj5QqaExgoenYXYdPvCqsGNbCEevD2boSj/u3qAcMAV6gPR2zQXCIs+aJQTWdjZ4IUPsZ3RM8kqcmjwCRy3E7r6g/L5E5qcBeeId+sFrzxfIM99iycLXImCHK0hqaqziv4y+0h5MdWo2jjEcn5jh7pnPA05LT6pcIAIB++G6tpSiVfWOYJI9Z/pud904SiyAVSUyiqHcyQGLYzJmeiTlhI2JDOLBGYzG3u7eHpkfOVi7r3d2152ZgrrbcBnEGOR0FzxDJ8vMLL8Yri6rXc8Jhe52CrkXtJX2Ba8g64uuqrlr2Zc8PvJ6E459e8cx9PtHtkxbTlcCXYak/dojYyX0eV58mMPydo4PAkbu8xbBvR0Lq8OUuzb408RR6XeXFZwAVlpNHUZiELUVqEO2jMZPLegnhmOt/Uu5uUc0iRlVX2YrIXI0VTS7CrGPXK+aW41e5imLjzhSlPq8PqQpXmqnzfF/to0KXmxWk8lA6V9OXpCZbXB18Svpca9CuzL8hxoyu7gp0uZuq2R58vYq5Btb1M01JkPsJ3rtP6nMTLtnxuyA5kTvxv6XDolf36im5Ysf8tWzGStExdoCYgTy1VC3nqr6C/f2SCgwttThoCGF89GiwJ1YDuSczTW3igHr31vRBhWC+MxuLoKsZ/kuYtl7MTvXnx6SLeZclizDx39OP6OVZu6VqyRbZr2PCPFW+vxDF3ksKrBQzA7c8Jz81VM5+lvT1eN5vt7hbrg368cIKa2Yt5gZccWdwoJoJxH1FmiTniyrSbiYSyfc9S6Kj7p5dFgJfUq69PTVDkNt5TGr0tWbTgfR7huYhVo4PDmPe9EDNvan1jBOkOeGX98KheM/XJRbNXuHpecpsS1my2hsp/NXoE2F4N1jVgUvCszg1Hmn+JKO7Yjfr/0aB4UlhkTkfsowf9CpG0B5ZVDrwIga6DTLXq2zTE7QczDxKUYhd4crzlGMOKI9hwpXaaPWFO0wdzd0aZ/224L6kXENAkL0XZLEDJth9hkKNeNwpaIYMuHkcJjadVpC6pjyzpODhXw/+eKKt7EXCbeok3J6N8NnNqCdyrmy34xE3COtm7hO9lZqcubq5JOqWaI9u4daRS28Uc5OewnLyHnrOf7Hw5K+/QAxWTIfa9qK28+fbyYyVHZN2cbx/omCBIvhvZFDb5CDeUsN70Sf4W5BNjHOmiJn0wxdh95eKsoAzW2OaT9vVklwDLw4Xnu7YWmZPjruBucJN063MDUjjBWnlHSV1wmu8FZenpE7FAPwfZc5vLBEapB5lNhUV0EPzYuMJanLrxCUoP0Hrc2pftkG0XK7VuMETh7t0lli9rSQJS73SpQId660FT0nKMmoDUbNf1Et1wUrrbdATTQ3zZLCr507MSpEBOZEcxoSV74l09XvVQI0BllLiPOdJ+NsGRL/1p/OlHxQmS3dS8L7O9ZxrA7QvrYKWtC8CzmK56vJsxW5zLssbk+LGnjHiRYujwvQt1EzH6+yagjXB9QLt+xLQH/hUEYdpP13AMr2CYulyUhoFQ/sb04mi0LesqnkcZLTMP+Z9xL1F8NEHJu9+d1OmXu2EggU1LXnBgCrDHVXa98lxHE9zld82g+Hl+XkMQE+3Waynpg3PxYXuB+S2EgwEXFn9Vxq4RH8pExMTtbTS75aY7i9NJvcX1pZFAeSCvytrOHC1H1CT3RmgarrCCzZvuNmJDwmPWeI2CVc51IvSwlzwh1mNqZCpCwZ2uzu3KIwb5ALX1zmW6fJYeYovi2YjQrYtZCFWIJ+Yfs1sm8d+XloKZJilMXuzDrya5t3JKysVBjggGqLUVVWWW1J29c0adfXXPhhwusxom5IjlcBeiKYscEdBh1jbNXRtxivc/3Sv5uIbJnppkbulPmWRbSvw+TozFQLlOFQ1vDpNLjvN3sn+p4tApzIdN1e7TVWt36M0zTTQVuWfr/N2mvGbU29yzhf97ubhrjnEJfTOMkQoSzjEZjk4JwZBts5+avoalnQdRbdcC8zcYNH4aaz6qamBhU+wVMBB/5ZRjX6cLsCKTexyKWjCBLcYCt3DtZJQ92fZ9u3lD0VeBTGiuh4YUeh+rjHY7dUHLH6hJKTYY0dsCB2GXsIJvOJ7uUyAJodYbpg3+ulyhXPngVIaEJvFyky9aLuLhvlLmWrYBVSusayaBZEIuJF2IMst+Br0zdxsJ2709+zYGjSfR499v+DiqM+YPuKpUSi3Kv6s1oTjaT2yB5ycxwWCu2LTErEPpXisyZ4uiAbHg0TIFgE631evK4LtnRXXrJ5fzGeofK18wz1j7yY1OVwXSqDyW+8bt/Qc8BcbgAQqdw3XfzvbmhokHoYBD7PzkWBY817WM44FhgBZMVrMMMXDdAm/S4TqZE/nFFG7rV0bJuYGG8wER55YEMWzOjD1uOmEbmQKKMe7t7pKUxJLETm6Q4Jhn2gGEsVyF1BzHDMb6+oYt5jdJ96lois6ZdU2+B5G4pRud7jfstqvJei4Q84kYgnhfJPrKAti5U2w23dbIW4E8fu/VSkqFLP63IEycfHEIHa2/eNDOLmQ0cgzAagR/pX9qAVBG3qkEMULNoWrG1eMT+avGvVg/IO9jXyW2JGxnn0hfFRy7JuiGN1l6peqYxhgXSX1N0k0AF4nRxDhF1fw1OFNJN9d2J6nEGPkIbFKlvAqUe6xAq+BOBOuBHTQEDJvVZYMev/QRSHTuZsPLyse2yr/JOW4/+qosRBeSuwiWaLp/lufumMeJU3jYA/WaTR2YkfReelqSiL1HRKplxEOo6r1qtEpNX5vcVpDjaiV5KB8tPO2WWxDMaPTZl96IGACSpheySyzAhSxr0FGt4/RSHd56Jo9P9whsscgP1/Cmb/N0jQhi3m3wBMmkA8WS1jAX2vH4CXc7ykMhj8TkvzlZLYR0gHBYt/ND0gBcdSqt4Xgxd+KtsIfPF3SlR3BS3QWQwaXr7U6M9f88zlqNHrum2R1edgfFHaLzTd+5cxhAhtrQDbdA3Oh+atAQtoWBXeXu71xi8hvWlRp529V6T28WO5nAG5XlZnM1lWa9QYNKN83J5AOgiJqhnQ9bM21Sgv8m8+GuOMEqf0sFqNSloP4rh+BYSfbogTzeJdVuTPoPqU+pRmkiBulym8kIWaEPrlCoYnnDsy68OBOF12Mn3aNVb2QFIWTedFKjefOPAO77YuIKNLXD+75yJYv9gnBQYGQnoa10lVI5nQRgG/2ZDedyxRuDPDoJOFhpD7nl4pVmlizzqxZG2GfcslnDtwGqQh2+eyiqvGTYzXVnfnOtLn022XpxHdGg6kfMNB9Vt8w+VWdM9fEVsYtd5bG1x+lbsklLFVkkfdkuu9+Jo7Ae70O3jOfguN5tUK5EaklEaDfgs7uGXJmKcMlfHFmWpVH9I1514Lp7K1uJwipPMY2fAv2sXBRnpzkdhbg1j+vhsX4dG6i+6HbCFOczyqxKYTHUn/vJK5aLweUFc/XFWMJ+jhd86oqd0ZRlULIjY0nIHZloU7R0CAozjgM7V4PUcezMDwjocG6HCMFDnCrawumyrUiLAHLrIux4XV7rZTAhq+ICw2dimbk6ZMV+TupAUBqEfI5NxmtcpZXxik0BomuKVi8M4CWNjL38feeiNN7iRvgPScVB8IJ8F2pTyc86iEI+s45T0N4jW84ZGf+1jhjgEkXPiXgkD9Bww6ehXJZWuQvdAFD8FdWFu7sK4H3PyOuYSHc1Xq3rIYETEXG+rOLpxT79LZ/Esw7ANPJdOul//ViqUPndsJaRYGVaffOzCySn08sQHyZ9NiKk5RxnB2lCbDvVLySdJOJ0kHC5PSTBtnr3MNhF+0vXq6TwVz8V4FHFVMSLSSI6XrBv1dJZdN5jHnE1G8Fiut3Jj77FNhI+/pmgNQSqDjWNh5JnVH1ZQ51maEww465QTJcub95BBJTluX0o9N6DjRisXxnSb6Enc5eT95CZUgdr24w7w18p53j8ZIYbsYOIjF6iYVVwsr6f0zZ9oqvowr+jJhebwB8SYSJgSx8hyFbtAPprYTxR18gH5Yh6rMwQQFnzgLb/iM9oKc1UsqcddmxMn+FU1kkIvL20XvAZ1GRVDqRJeh7GOonLaYrwlObZgDfoPmTeCRrRpO3P7dbSQ01GatcJN1ncj90psAIFv96OK0FqKes8ucW9fHTW06C7hjvngE1PTxUeTMl5rvEh7xYudZJgBG8scX6WLAt6unZAVd4JmMyM9BobXvA38H13DStBD10rWkoIKYMajVCjo+SY6vOB4uTPTIg9I40oHCUClOWv2c588mfgn+rjhCKAYiJevRAM3iimsC56fMc/sv4GXWDd7QSts3whJQceGjUCt9JNgmZMD/yfqXdFka8r/euSKzCV/u9DzWCr3i3wQ0q5UtJGkCHY69HQX1z0PpEl3qjhtHN+CUpQGLit/xYJ3QLXYGEfOVZppy98kwwhcx/OkklwRkVmqY9lKLC/5yBX1IX62QID7azxi5svF+4nP0/DMLQjjoUgdliPgCdopp/7HqATUnxqAyVSWkNV//yKHhb9Y8dT0+yFZRo8WGEJpqJ3auRTH+IJJTrAhLAyVRpK6ObBY2oTcaitGYRd6ScvTjX7NvhK+xTZRrVQWD1BfWPVnpSPUXB1BiqEsJbavyk3ymfeNAK69u26mjzppVXbQmTnK647NjRGZhjASc97f+XxMuyxFpkEa34edCucJP3VGLRZcciZwbTIF04pdBNb+EQikcb8/8IiqL54+r2oIAKQeRQh8GVERnUIg2xuQ+RRpGgX5DmGQEb+CpG/g2IvZNePU73+uoL9tAUCdKNuzhEXUH1cHErkvDcCt1zK5yzTPBwo7yRX0dMeq2OAqGTQWMFvda0csXs7TGfUQblQcs3PyDW0opu4rydPmJZOapajdld/uC1x4e3ouQhVGjz115zERXIwPtYbePVkfl5M45XdE7mS1r0TLRJAAp76ZbYoheVuLlKb5vDtMxxpz265sH6ArJ0sArXAs3ajsOB1nPUlWJvZB80o2wnFTocmbqzpgxGjQGSlhmRpsHv6jfObmxWgiS5Q2ZtB7gTrZEoCU5zOXep8HjXBaRzXi1KO2pg4DnDAsU119CiEcIM4WfvyGigbrj//fBwa/OxsrxN+iU/mcLrd+jj6X078cpRC9CEFzq+dyMME5tk2Dk72891plNnkZxFpSlwkhC+JTiES6JKpvVmPD9X3fdKLw9N1tdIUlv0hDyXToZj2YvFfEAXMHgXDGsdHhtPtL2MSXpIEhIzDrs/ZkOrS5VqLYfstQFUJJVeVsPHzXzxOOush4Hw4d6d6bxbpG/cruE4gqNchQtQoWkmiVAEbEQTeeDWz4+hsaI/S8PI8Z+UGNkFfrXO2FUA5UPW4XjWZXyT5FvCpmZ42mUxB7deL7+xoBfzsubjvdHIgwAWEOprXlXcCcPPa1s/p1hOhXidiz6mEEKl3L/V4Nm7ruPDw/FHjGe5l9NJKjv3Cm+XpQ56jj5cGhwRGMqgfZVRx4rB0jVOSTYmAoKGN5UzCTFll5y/DukDMYjkAXbmMy9QnKT6O6z7XiOLDjBFZw00EqdH/8Khd1kkyXrGtkS6OBjOgtn1lprvO08AuoFmjpxPAFQ40469mIBbT/bxfvbwLo3BQKOw72Uhb5Y83MA0mDYAZXV3dCCTQIVuEuEFPAoD1rFlByKPTAFhMvln3LfN3/mYD60sTHmucXCcaZ7YWBwz3cRHwEfxbiELmvw+Ek9RbrJLUQG9K/+7NRXsQzjJ/FZ7Ctg03k9CofxBmIREORxM6aBSl0F1FZnkjf9toDAXQMhkqwplMDIlIBmXshhHijmH3NaY9EMG3Ycaj3EfMrHSc7juLfzAgG7oWdk441JFTMYnp5w+HcPNGd3COQM9ZfGW5cArzUO7u0yIkx+gKUf0CUtEwp7q35orUqm1N6RLB3aMZi2Z4spKTRAf1TPjHeSwHPN8B+wUqdcp6B8GCaUiCmSSTlNsBNUVYfIutLyumWYCFz0fDrVF8WkvUhZkS0YLuMEVQ8I0J0529/9dItQyWPx5UDjeuSkU30dFPqrJ6+RJxs4sO0cl5eSZDWCx5hcrQFDGLP5uDQtxL3slJdiXDQnFVbS/g2YpN14lQuoIEKvz0HS5hd7ND8drTK7r889KcQBLfei644UrVfLg5TKwzktoBPwID9x3OKztzhgUckbuH2PJC0XHF4x5/VLIQXnD7kvJtyHxLN0pBySpSfSlguccm8Gsm5agdNXvi9cYAZsUt3fJ/ZxjejPt6jF2UkTyozIuuN5kQ+Y7UleuMkJIYcqtO8EvIdhx1B9vbltczx/RRofgLX6mnkgKvbU6ktii11scEPBEulNG1U2vpYMNRPhTR02MsCutmqM1tMU7AapXi794TB7yxkD+HImG6y7FDqthKw/iVps3ChunO1AZB1EZMMWArFJ9SrbtJM8mHb1nm1GrhhuPgyPvbyrW+fgtKAakFqUvGJ7mjOiYmUooP7m6Ku67KTY+NQ8UQwPbBgrAZ80BtzsUFLEn8NuIf4sq6KX7zQxQD8BfQkYs3Zw00sgvdqGmZeNbNugFvjamzvbW3OeA1hzJo2s7s94tt9CPvhqPCAzu61+qenbE2TYGcAcYY4e3O0d3Yxx+FGITv4fc5HClSqtnVfV5kFBfvsfcuZG2TVZkx+6JmeNqlXZki26hrxXAxy5uCYgSoPYJQFC3cfTys5poMShS4UAeGKVk8v52M2JJb40ABtdsFwl8yo4ADTo/FUkIxAHvazDvVINfwUyinTejI8n2Tl25/KtvW5Qjvz1/30vvGp/OJme79vzLo6annx2Nmoj5Pdpz6HFW3mZ8RTwIoQywFQd+aHeVVpdouRPOKLklI8JRM9fNSebLIfuZIa/KzkNW+PCA034nbI/bUrWyzS1YxJ2VCRG66UUm3w0zBPLAsvrKfSUMoYkk6Apc0axCUAAm4/pwy2eSsX6KROVZOsDbtzoCW7wKF9aYY8ZvIDB/P/rfbX8gA8+uQ/JQjlOqjKzXcsE7jCDWq2SZMOHa67VycMVZZ5W1jUIh+MSX3gmNwkWQMdgAZv8lnkv5455f0ya45R0pzzCkTps02gO1ITHXgIa4X04gPapp67Jfc73y/VZZp53a/FizN9j0svQ5WnVTLxWj5Kl1zQ0nfwaBPF9MUkABnSX0STp3tj1nsi1rbTtFIiMdb7l/OA8bWR2sc+fGA7bgP5vjAqNITaUOKpygPIWr+uqYCfBMZEGo5Pi1SAiZXO1EC6yhf223ejjIkznqKBbnLZTUAIebLJvDzctAV9Hy4hyRPIAyB8t44h0uzG2SMvhJv0y2MToCyYf/I5AEXZFoUGU1x2VRCPvMIwOk1NYpEbjb9IsLIdcClTFrozY9famHfA2ncS57KuDIPJisGglOm8XPqeWQwBB0szomXLvi9aZgZ01gxGsKmfLbS2icbo+oadGKS7VXMUD1kDr3p4HSzqpT28C1zUxubu3CbSO1ahu2uUWmchZWiVC04koM2CP/89ayl0HwcvBsr2RDs9WMY+Obayaq+RkEEtnQ1uE9Rq3ZQC1F7vZjcihXulndGfCm3xPrSJ5o34EZ0GyG/1WYzCv9hzzDwcHwGBh7fGugLSi/XjhYKa3R0wqdOi9iXF0dODeoIu31TDlo5Hao6a8CchSzT16lq0RnUihUDL7n8iutfYfVofa1y0AHKNH1QF2mZv74Usv5QqS94mJ0/yrUJneIfZn+Z0XjFo+1Wc2+oxXNtyIKiX3p3cli7Ow3AKZBeN4VhqbFPY9aUH95v0whzmkVhoAiIDjsu/MIm1tTduVmBQlRg3WDynmns6ylYWb/DtUpnPickuYxAkoXS4KOQq7/BQopX45b+3eJu0LDkH67V7HWBaB29BTOZ7OCkbGqHTBGiJsIa+IuME1FJhy6zaiWTLICJSJs0HAW8qqo0V478AGfr6UtqyXDq706Fj94+bb17hs4RI5SLbup1jOSk6+So76DDAzdHE/9RytGQNtLLLSWoIjCMvxgxdtZppA1sS2n3ybGzO5yQOLNcPGEPr8voiFLCaf6Jn0M29XvvLD9W5LowwM5X/nyEbs+AhGMI+05gjyT67CxXxFtP+iXlT2JXNxicvguKP9IOFpwryMe3gw1k2Kj5vEtougrGSFuAeNm/fhzXaYBIvGeO/pw4hqPR1Sz7JosKT9rj9VNoraa/S4zML7DAudTZmWzZQdp0zm0ozWPm66fpix3VHZzzLO/zdvqFSJkuTz2oOZR1kAJcVMHWYxUiqbhKqwxc1wCuhvm96EtryN2QZ7TnlFHkIKUm+bMDe5qNyiRuIuZKNTxCh4ZeJCOdaAGqy5QKjn2sjvhtP1xAq+8BSGF+pAPOf0SwHHLAiz8L4/F+f+gCS1qMmqNYoDANrzXwfPRjFccE3IK3dXFvABMjtQ6O7pS4ZkAU64geEQn5CbzqXNplnNHDabXRfEBv3tcQ8fKBwmal0NN9dCoCUWF6Gj2i/Ouuqvvg1N+7xv4uAfZei+3vEhzcKcHga86DbmOeL6ZYFWUFm5YwDaTuDzTYMFEEcj8zHzFWrZT4ZCoQ4s0ZECxzVTYp/FjA52qvlDC0RzcbCin5NCHSsrOy1vCYeJkj1FWU7lU4VVhmB9InlBPmS1iBi2jFmY/RKTUIijtK1kW1vYbqTmjRt5k6gbC9MFmmvOqu7gzMPE9F0dxoUQi8Ml/qbhq/9hs52O3d6pNYJ9dnP0MWDL4TNk8tTgGD4r6UUtBQEiaMQozEZR1p/FESXXNaDSZOLbGKBQ7j0Pa96PbymjQAZ8eG/BYJTtsbphtN07i1Mp4mF5q215S6fCz0VOUjRSNvvjrXxTop9QpANE6Hg9/CWNBJv+Rp/RRqNV2k7Y3KDK0eAj7gztMSC8n2UZnmqMF4uCUJCzCc7Om+lI+T9RcrJ6OZlJJv3DND/+QThApbQbNOkICjv1eRNTVypDHfWkIjwiirEbph4mE89WfLMtnoUSwAC+AZCGsaGyf63xMfI270eavapOAFj+g6RReCSvSmR3kXBK00DGwjgymHYSfkPgdxR9Prqzy9vmmDVrz15ycSty6X3jYVUkGwaY0sUL400m47dTUHf0bNaSaFWs/eM3FDTBwP0ommjPWmZRFaXfenEvylnnHy5Bn3Jp5cN4zrRCzyewtpejIBrQ7376RmtzpJ67//s4XdDrxiwXe37VwfqFBaxekGs8RlwYSqcR39xKoGpqM9UFXZIP284erzQDGSr3EaUdZSXKY63dLMK3ybjIQNLt8SEvGGd+09fPV+kgsyqfjF/SElTXmznJ+1rZSKYTI8gi9I676fhOMRremN6TUFXrwc1zOpxJ+8g1GUx+9F9xDvHb4UQAFE3HXB8DLof/caUK+i48i8BvdC2htMdhTcwZwJd9XEgfoB8QaTD9ThUf/byxR2OJaK3zIXNIlB0bCDaZ0Q6MQxHAJPgLztxrt7Gfa+aVyh/u/zXVXFjKfCfjDY6OTmsUFF26yGXfOJ9QNJ4N4gfRcLCHbNIe/ri8SMRIHNzNw0GQeBCspn2A4upBX/Duhjjzbxdqjr7ew1WW4hUpUvz+mEFYnuOU9+W2i5fq1KZecZXxoyOuxHov/qJcfXP2xWwGdkqzI7Xrxk/+SK+4743kk/4lOX3f45f0GEsDAeNCCAc3rHMJQq9S59MJ6akeAAJru6vwFN1fxVYO0/QDXw5lfAEgnz2o730DZHuE68JK8YTsIkz+twfI988jciJTNNVG0qHIaxvpX8HMtBF1+LWDoz2kuCtT/zqV7Peenl176svLRmOT/VS3KvXgOk3citJ6MCGjHikqmuU0tW6IkmFCTh6t/NiFyg5jwpM1qTp8/roNvQ2JwvfgQpZ1QzS1WQybzdhsF2Dxbf78tnjuvqx3p/eeTAvODx5vGFXw1/0JSZx+dYZh7ktbczMXkYC6diHXmbG0NpQvcJk6mZxYkxAFXsaVZOGCHa0vstj7XQQspMhtm7KwXNkoivrDvCtgeH5Ppp1hAM6vFuaFBBPfeW4dYPaFiegM9h2kthy78ZtrmlbzXliOGwXqYKl9pOLxjAwJX5ZlYO+QzJ/3wPPWRZLhbCioiLBOlOEpTTB7dUitfZ4BhLI7qHdUSLM8BxERrhH4ZNhxQBzf8b+ghn7coHxUoD/5AYWY2rvxWCRgKZg/SOG9cQigijcbEVhymKTP6NDx66xLMvUTq6q2dtgQzUypW/N7DyQf5XVVNEmILknk4oHMqeeP40AVXIWRR0Ebln2Qy5jXpudbqlnN4bpLQIrNHSXGd7VVigym+oNtBTA4mzjDimkyNVnLqLBgPhfKhs9I/7jWxUi7emGkQ6ZPSdG8Pd0LKyY0DnrWQeO5GbF5x6OqJRJ+gIlK5A4lBc5OECrfkjBP2iS9bNUKltNFRqb4pKFuaGocx1fCOVUkPP0vpIuRIiUqcGuLztJcJbblPL1Pd6QojJ+7wLxZ9hszeoGpomPWzxAtEib/NgqVZYIVY2A53TYG3skb6BTzlXliLbuKQ8ymSGvsHi/G8f0MXC+lt2FNNL6i7gQVLejY2I4TOAg4ipRFVCwJDMiChkbaF6xofvEDZdY8RVaNKp7zZ85BNk0Nyo7LwcPKyT+QmQLAnXCAZcAhOzQVblX7wQvUEPPOYVX83qjqJrR2NSeH9ziyWiFrTl2ojJM1Ri+oY/y2JMkIr8n2YGhxUM4a6+Ftqa29BxXwFxyj0xTgRffu+4AXKPhBugfV0PjVsbkuBn8TO5eBPUoW4eeCkRs7IpRKt0gFgtrnJjvTkBHDwvXGH+C67viCDA5XLapHMx0dFLbn0iquIwGngqHUVd6JvN8OQa3s5rAoHXabpWamheFchiuTdptO+rxNYEob8G8NbBkoboqvQImaC5C5WfcK+vzU5+t8cy0SD0/PM8698cblp0SdIFXYj8tNJiZDNM/wA5Qj1OmcsiejqNvrnoF+Ml/aKgv9NvripEvZf9r4gNhy4xTyjun6294F1i6lt4rR4g4bBNXMcoBUtAVR+KwQVFQZ1YwtEqyJt7x9OERb38j7uOm0thHIrof/XVat2kT2w2hNYZ7i6uBpKRNC7vvxNhaAHNsX6Jo8zlIRAg5nzMniVcYL4ca2/hSQINX+eEUHEgyk0H0OvjwFP0PU/G8xL0YbyRHMRtazNzbWSMK5nX01aaI5ZceNqbPCiTfE49U74ogyZLM6SMYgwzCS7XBh0FaKrIE5iRPLOG8IoU2kwnPUl3LdaWC6q8UaLtZW7mh8ing4HZxJEoK58GPtYpWpybHI95bxoQSX7EpzDnCdqYgYCoc7lm9YxPJKs1bhuIQwV67EpJ/gIJCv5S14d8ZDhN4gIQC2Tj6IXYf5wDNR/70jIP4EBkJkY1FlSHW2v8oZ4x107VimfLzu9InjNJMlsGwQOJwJkDwAQLMVeaKbFSaOdkJjHNe9qsW1R9kTx8MUm2+XUQeguIgtiHjrj5SrzFG+A4F2093BxNf4QzOKhZpmBbJvMauSA7IdZzPUVpJNdmitTISAboItlfPgWEru283uMxXcIUe5rocQ5xIJ//bQGaqAJ4LXXxJBh2RSKpjqpsjqlxvGycSOjPGdHmTXOqBz2x2xgEbKYgq2NfiBr47Mz6PpOz0QIXXif5pusmHWGBUTBL9NMNwGlN07BhigSLdroD/Bk7EbPc2g6OrW3pJHCGvhiEn7NG9cna9WVvkH042DMhjP2nH8vUdN8joEMMQXw8Dkr8+/uUzYRe0/zxBPjX2y3PoxqGDZVQGFIiDjs1O6kBe27VNvM9upWGoky5jyG/zSt2Ypb4OvYxjsu6BfpvFMdUsL6W9XVZudkwEmkDLCrpAwoc9A6lnZa5qrXMb+vqQcnxPwHzFR2rn+0p+CeIhN7DIEVzUSXBW36Wrl2vkkTYbc5ZPO8PnjxIwB5hxmHGJwom2n7e0h81KcSTYp3UUAECT9fuPKwE8uV+vo3Mwzi/QqOnvW2/XW84G3oPbhZCCvtqK2HL9prIIqJDNaqaHwan2Q9AAaKQ8GG004IWEuYj8owDrryf0iiDPNvSJEvf1wMRsjzNnboIYVWK6jdfViNbByl5vEAhfD3eb8qPYt+h+g8ndBz5H9bSnq3E+lmFrmMnHySmWoibIbJj6qPx69wABFxad2pIMomMA0I/6jfdOs1qxjU+uT4Mf73n84hsHd5F3rCV3wfBbr8OuUzx+49AbZ51kl7WNjXB4ZOGWyR8+R9/SaCsGHzqiQWi5koILAheUVpSD5EOftK5ENMSPggEnH436HTMjtST+nh2CqgG1lNxCq8nR/mybS011OQIHRGubyeFs55vhTrkZ03CZzzuPXGDjm6lz+Yf9Ttu4jsfCVXxcWV9mX6yOZ8LgPbTDwZZE84Nt2dafmPPythhKjMHYxqs6YC3DTJYLZjNsFK6cN9iCy1V1lxCG8OlUbaMlQWUZAltZNRlm+H+mHF1GAP10L0kC4oWR6Lt4XA4oFvCwn/jZ3K+aFSH43+S6rK27D0aeQS44AkganIKj+WsrxBPYQO+9MU4bZDBPhcZXQkNQZJHJfieR+ZtwH8lxnWBEQwMMUsTEmfRsT3rDeNbUcA8TknxVV1v3q9V+2MOPvkpq0obKaB3+xOxPIh5Z1huWcZTV+BIfutG6JKxZt+i8tit6Sb/ajQbnmkPhQxZDhhE+dk9m2N9H/j7xtq/d2Tbw+npjikcUfVzba7gZguSo6vrBR3lpnZJScAW9U9QldAj+27RJQ99PV3X3FcguPwb5pXY+VahXNJQi2dVDF4juHAxtY8Ul7jhjljYUV0WMnrTBS9w36fy47J37lZSp+mAOENoJegfftUjvjlQ2f0HN++QK8yYLej8rApAMvL69DmLufR/ypoZ59RECTiZE6rLNdriLHz2Vw6x8/ElshSK7SrCBBaxHBTMOANJ792bBq5YAR1E2eoHhV9+iumKcF2xAo/fhArpdb/cd4me+HiDSr6FeTZ6kqDduZD5WPSRqjiAisG5oq3FOUY0Z3/iJiaM1d2lpVFLukjHFVGB7L7GxNkUSH7MkflMk8hpgQhhahie4XTrxUY/BeSLzJqp3uONksooQ8IWx4ai0QirZEiezhgEf+rSMpZTll3WNvUzrC4qyZySwEB8T4nWBLpt2lOFFqEoX4YpXU0CUezw8Tv+MogE9mRMQyHkazwP6RoTAcBzAskR94gt2Zrc/TMl38P5F3hLSwMAoZGZVbgOfnOQUil3wrcX6pxgdAkVy49qKP+aTh5kDPhFPK/NsyQ9P2vsW7Hxve4Fj4oic7uLIH6nwAZ96EckJ5oTra48m8OSBZkqfilxOUogyUtjXCsoqPDPTX8dSvzkYCC9NM3CMc8JpqhJTakWGn2+xRML+PczSv7bQjo4AkwOjo/ppT5Rl1e6+cY1TJW8VFxvAVOXryL5Y288sflbb461ZcBIH4ffW+AuXj6Znqr8V0nv8pnx3JG1fuyT8EayuedXRQ/+3kO/YBCHzqlpZvOPc1CRPiYssUL7qNdGibrnkj3Ko1PVKX27N46/C19YTaclmhNIvzPBXN+hdhj9Xmv0lKhAVlctu2rb51vzx+aLYkrC4eoFEaYPUgYZsiqOEYaZXcd3oIwQ/d7zqRpCGachsmrh0ArvIi/aptjARNLvQF85Em1b+12F7Q4uWTCl1jmuxVBaZWXveUhqaz6gETWUnu7Gm3kxkIlGu0UdfvZw8ns3E3vpDi0DIDaoRBgc4a5OZGHasG5+S18URQdJ7EqLNYQqYDMEG6HrxZwyI4noWU1nnaOS+b40+RP2dR6aQWuZewjDTIC3Y7yCZzRtX716mUACd540Mwuoh69Z1dqZkjxkvh69zgLXzsivBJ5yTT9B/psjcRYYqtJatgYf1qkn8c4TLoI8PpKVDpBptj6wUTZLfUW63FPcM0SDQq8Aw8MAUnVbJa8Z7FS07Z4MDC093uri8iXqLlJL8RoZldq5AnnBQQHTRBjMyTpCltNP8KJkEF36Sg40l3hU8r58mpKOiTvob8zaKFzr9waLXrJEnnSmZghimiVh5gzdYhk/ivH5+5iCPc6vYub36o6Mt+pSvPfeVpDL9kE2JBvI3gZeFSYrGdEos9wqD6NB/PG53uYUOuHFbzJRzq59grJYTW/cQqlBEKaYCnm5PosqUnDgG3RnJcMiNpsnXN0//iDyM2Xifsha9azjTgZRNlVDUfg5bwiNIw/N5OzLHTFPiUrClCgOvBIO1m/Nhz0vapvQMrbZfn4+JCbCk2Bk7ngFzJLYL9DNE2F8BZdBeuCitmGiBj+poTfcl039/ryv5VhZyIhP2E2IIxfgnhfghLAXj9UOAYeLxqyHoCcc8iaKqaSIhmUZ3tRN/7CNpOJ8Y4WzQ4LtwA72npB+O+weIiUUfoWc+tUffUUjWJ5uDYdqFyTAvIvEyhbn5SxAsiMTjpDog7uyTE9pIuKfy6J4PcsSwoNQ4gRzWfHbyOqXbd4YDhXJhEPQBUStX0VRQbtkLcP9LdS+A2s46TfYaYE0GIPIW7UDeSqmbbiNU/1sTacc7lZIy8tue2Pd7xTUwpQJuqyRPkBA5y/gsUlZzWrhs/PcS/iemdjAFCHY6+d7l3Cnncw1SZFa+IXM5L+Y0m5wkLgZ/EDoAHl2ZoApJOosOnXHKjLvo3ddHozETZxG6XC7GNIOiXEIIbghM3hDp7x5cw1hqSQjFRPVV7JHUs2ymuvhUl4oTuPoFIjOw7S9PXSvE4TbmSX6Fu4jeQO4Wc17yEnHp8JJKeyxplRmQWBzI38qJ21rHCExLzW+cRsQiv3thLAZNIJMi6tQm+pCxqltL9+GMH3y/7M+TWssXVLUd3d9ICgp1qpfvbGpXQHRO/e6LBfqCd9JzKUAVnC/G/xcQG81m0GUOFxsjOlGNZwU6cUSaiVT/cPrhRr/n17erSqLa3uNo/xUXbaXBPZtAZjagioOhbO0aDc9NANGSp7t7pq6rYvjuNRg/TXHX3vgq+9R0sIyp12MRutQwxvdFWykLmwntxZXwGcnQHOyj9h5tQR9VF8b6t7c1dCoO/KYApxf2qG95PZnqfqybZ9SRPjWp1vQNyWSI1q41feo00jGe+NWgEQWvPgH625rzXOMO4oW00B87dGh8KsxiB3xki7ft/AuAGVdTB7UApvxEUm3LBQb8DzTMSYwGhpAkvMbWlX4H1Y6LdQsmt5NjFWVGWA0IQVH0ojtvPVjuXzECmKlg2pI5/k4q9v2p8MyhcwWTCiFNZz4BPOOhD+SP5L0mJgxxm3Trpo90yvPKjDxF96tQ1VKFUYVDgIJYXxVjZarswD8N6l1TTSg15un2Vi2N2OQduIwsb/U54hzApMXUxzpml1k86cOAgfH6uyvF+2w/hKmVWNFqPG1p9lohse0rR8Da1YUSO500w70gQ+6cLgvJptaIwKmNpvxg3gAeuPxjVWJ+ABNX+ajWv9zeGTK5PBKxDMnsHe4rNKAlyAGTMhjf+lk3jAHjNMm/J9nJgwvTxkRYjGbZ46zMMldGcpPGKKLAj1ofdBdwcP1Khwv+gK15NQuqluormn4n970c8iHkgiNJIBlA5py9nWKSlH7ofmf3UL2ZEEJRxmGlEgXGSjlLLfp6IYZiDJ1K7jUbzyWG3Nd3Hnr3ZME2vZErgz67ZmryBqEkFLFc9VT6nSKn0GCpekdX9jZgLwCoi9tC6buh+qtzRolwgvJSlE4/E1RfoHKBgUL1UN0IhKNzN3QHM6mDOQfvqoFfd1GVMbKktCyCfCAE1Bg/X1dKZCiLmLiXdTCZOow1ER9X+pFULD3O51PCgyzg12wGFkeamNVTaj5dngS3q1OtLXS98KQ2WRFB7HJ0HW8/6p3eyXWFP1vWsa+j4yicruanDMbmehkL4PhHxdaZcTNxz5JLIf3RqZu6bCfCmjysIHbh4Joeelm8+wXJbYBl9/bG3+ZI45EbduZOjLZazgsQctSDi4IXw9eRG6RACHJKaFXa8ps1rzHSRsRoNyU/MBhrUqAg5Jd07TLRKJTyC2y1WYh4RQlApGYryX5rRG/V29m9eh9/IBfCqNOpr422GqYZohhu5JO5QBLtDzXCzoE6KCUfww/JUwWl4PCHzhhwVbzTh3yN40HD7IZVnhf96yodcMMeK7jiLzFAgtCVN2GvO0hRffQYunPDpo5RMqgnYslgD2ilDDW4pZlbN7ybbGJ+ihM2uC1tTTCjcKpUH6puqy5XmTZJf+MvEnOy214tb91zcEW6+N4SV8FD3fE9ioM0vU3lBoY2pe8hlql0PdUl2LNaEfafurOasEBcM4PnQ+5cXmUJo15GC6iGMAhcQxDbBo+mycUw5xze2i3ukGxuvqXgtPSI+l6kZqDwSmvNFBQaaqjqbHbql9nlbcnqT0ZguElFhQWMavlHO1lvYf98ZZMdDwpk6tloRfB/I5dkeQ72nLqml3xl7NI1Yew1GoPc3othE9GZHzB7Sy5eNQg7t8gcI51Hv0GzXhfw7FpzdQmFXaC4ADbiPbOujvVdHz/Dy6+bdyNPaUG6vINojtYLLJRRPP1XLIOK0YW3tEIzh2T1efC9vLJhxatGyZ06Dwlm5Pgp7AobtOw+6emK2wzA8nftuzV3BsfLQahX4Bu3bpcUqwnZ5amqA9DYvimZTHe+HKyK0GAuOxtF0y2vNj99qwhxBkpKF58FWH9PPzrYR6CJrhF4Z5NNUcp0bXfVhZc+QybSQ0isdMGQiMYV5ThYo/IbfGlP44l1o1qRfsn193snc011DbjvShxHFf0O75Oly2uDdfMCrRfga17HrDgyrLj68kcT8jpMRzuEp4hvyFAENjlQ80/y3hJbHd5T01Lp+EIXDdILgliEKZtF8t0Ueog18h5Q6Hv+PT3BMJav8T+6DH1md7fXmrDUMT/JfNc78JVZCctonzoijNcftaJgOVjCe2okYE9tBHzYMY9S9obhracw/b5YpREXlsh1BbxcBahYa47XD2Xd5q4gLiOYhLXBqfpCtVdh1mS1N9o9NMDnnkEUw16VZY1rVXS3Qb/k4XUHcfmpvGigq6e/bk01aoc/SAf+ywUVwa+76HrZ3RQ8J/ZCeBJpbzK0077iGpU912rWgeJXh8rTaWjm5mqVzrsSiwNNJj4jm1kdIf/i1MLqXIlGn2oZwuqUAy9iwY+IWPYGlGNwSN3WOuRe3TfP0HsTF0yIUuR2A+RWH/9GibXcbo7WOb2DnZY4NVna0rNrphlGqlnEkf9m+vNLNPUFp/ljlsuZKiel14yousVODa5XgKIvI+Chi/fm0ITyOmhSKzZeZuBthz5RYc/OuKCCEmx4i2hp37X0+lbf54gN4uZD1CPm7pTHvwUSVGDpXHx7ST/8txrY85hHhYBfCzsJvRe0lTQf93ZI8gP+q/y/uRT8lzDBpAxgWZ5+AKai4xFMGYiwxwqlu6WNpTdALDdsLoQZ+1FDs+PRX7AXNkDb7ALUWAXlah2Cu9xYa+2MQ/H+WDc+ApBGvHZgRPpw1dTRk2RglVt1QI7onMlGLoHC04A/HdCRuf2K9WMWjBeIfOHJUMozFNdEF7lSDvlct91idoGCtGD8Uddqrp8/eSaRyqKfLUDu0TH/xElEwOQme1PmFxPl5UOc6hjfDg9oKYUggXeQq0ahIX9wCGHjEX8KE+1CPotAOi01p7yvcBQBB8VuHbBYnG5vWb2YYnFNI/qXkGACYWz0borKMkhMQnTCqhOaQ9MTGvZz9r8wBHMWAhl0bmu7O8mFxXv9kIc1vEZTq8hM3/zw/8lRcSB3FeGsFVbMrnjnE5qy27VdHC2FOY3A+g44XIIhd+xjg2IzFAlwdFqUqk6zW0zA3Yl3vtbE+GnLySKJhf5xCsXwaTRjy4vYu1i2GaVxxcuB1C+axKGK0E5DD7Eg5jN2IQHCQPJGvhfXVnyclpy499A6KUi6DxI9nXHDjXwVpdiRl7QXh1TItpMqY30CAvx7kqPeUVJFBxgQA/V6SL2AxxZ9/BBfdQ/MkqLPZIxid9wacMRw58LeNC6dQDiqEKRycq5DOFnlWiJkmSWFWFxX6/eJ/vu9jczWmVdOBWYLtJj74uVPXSYmQQFNXY1a0SZ8U+nRVYmjMhIC6RPnVzhiwqRp8SiVxFgk0bcScUauAEXoyuLURiY+WjIqK8vYncRuIYM1AkfhNMApdWiHsYWW2EHxmnP+FGrTqP6/stTVcln2rzxrTZnFWw+lfEiYOTslMT6ru07x5wtRrTLp/PWzRzV7VQrS8ibAJSEpgRsh9BUm4YvXKAO+fLsvv/rWS09t6qvt3NrOU9BCZD8iltxo8EKnmP/HPsVcMMdDeWVCInqjYbIzI1wVjQFiuMgC9WlHUl4f5DoZb+Lh+JfmA16/T5S7zD+X822iBmp0RNqaaPIjr4c6s0vjfe0gMd/Cw0u+NABwLFIGV3XlZn5q/O9Bw9ktD+E8tUonP1qwGtGPlJdpd99Rmol3lJ4wE0X3TdqNXUFHFBWcw8M361ZbyPfUIHAdWTrDBnMWsgyV5R2+1fuqK6saJinsOUBPeitkYw/KJYsUCqGw4dyFVGRLawIUxo//SZP0jMUcdTT8UusYhiznzz3KjwCMdwCnrIpgMbWzrW6o5MR/CvOwB6b8MiRSqzCEEbiKcheW69Dpd50x/8JO3g7ntv6spSMgRjWhTEL4YOuoj8sxG2NzUSlB1hn28haHrAep0uReMk6BS6DTh92dexq6/GYOLVaiSkGEc/1X0Ybvs4Nc/2EbQoiTRpAosI44DdODuatreZkjLHD9QAXLaTi6gP+qWLswAfYHpQNh5H42syfwqTkBPBlyt+wMLr6Kv2Iz37kMVOexF1yzX1kuUakwmAlL4zvFfbbm2WIP0LmXw418lYEqzEf1UAGyqhAhfaCW3DlG3uHbw9kRkkbc6AFqX15AGop/RRdBe2nCUB5F6d2GspbZddqKy4X6ip0iPbu7dpWLzbD2+FILDDRXSoJbGVav2eA5DXj/Bt8171XF5vxhxRZqBZmbZjpfk0xqgQ4+QzfzRFh0viOHMR6blfHTInxLCLW0HIeHwsFM97wQkoqHNf8jOHjRQL4CBzP6jJw4oy56uQklmmMI31T51AqaGBXKfLN/yg9l10IuLoPJyxdiez4lUpit73qJosCK4BJt5G4bHDAw7PU+zQ0U/+lsYf1bbjDtK/bEUrq+9xraraSRlrfcI7IYeOpRKYGxETBGwzO8QzwZB2mNJNcF1Oc988scmA4doh96RAnuXHhhgcIAgJxFgHJagOZu4CqqjoUgSCAT3MHpGsYZy5KyMR0u28xGVHF8uE4rwPkuDDmZYMnMQIRknWAu4t3WKGDrd6xQBQQ4PoBWODhGAiUCPQK3m3FIUbpGVl4eaMY8BVUlNtF3kCu7L4QR4E6oI+b3Wh8CQ4/NqkVc3FAjIfTSpSUHAqdFPM1gqVj09SikEOtFTbfxOSGF8skYq334Ryb51NUHUHyKmFguN3G8K4DuA8x5ylneMl3cOOleC4pk+OTEJO+0A+/U6VLrzjSa4AhzWjYFqVve6H55FH0atwJPE6satnuUu/rKPJcnDr+CzQ0Sf22ISBBItNE4sZOR5RlfccCMuBW5BdBWVEfPQEAIKpPIb9+MkbcxFWBBdmRf4fvl93ty8Rl1//kf40KzQA6CMBs/SscKbSD97SasjrGwbPB9mXvQcMvLm94Tjfssb1UUCXdwZbxGVFwZ0s8nlOyic9/QU3xpU7Ifc6XVK6crVsy9jkYU3I5HTwMCfpEAHMhR2z4wVtJSmVvzoE7KXicC1vaX8AOhv4/Y5l3Am4ItEGLeNF2H/3QY/mWXLcVbSkxisUpEQ44buPpGmCWfOSML01T5QrVJXe+AgYPB90m/Ly4BTzWvCn78Yoz0sBZTLWTldlnw9DAj5sXtn4CxHyCkutaD51/5QWBWoWqMqX/VlqMXRvfuBIZzgWuioiSa551u36jT7fFN+bdUkMkGl/RvmqgKJG+351mAKEkZJGKtdcshnD8toiXFVapniIXfLSW0peJRdTGjHYMfu/t3QphlYvMFmaPgdFFJVTJpE7pZLmVEfQNKg5n5XjKVpYQnjsKwL6coLn7vj/fRD4pA56dw1au26RnDGPOj2yh5Vnf1g5EaxsLnKB3gvkQ8ZYsBKF43MGlZ/AxOOfbg13X/K4qJe3VZDyoSwF0DxCYNs0Jem0jZE9SJpdaJ4bVKoSpH16H0ENT4gIlP1LZM6XFs9AcpYD7uVJnWZWL21PTnUdHvGkDCWFEoz3NNyq/tfujOURb07GlYusx/hvP1n7inELo0DPWc0hCSseMiy2doAGmzV/og0MLE+N4/TXXo71lNbYTGd0eV6oO2jBNamelCtU5jiM8jOYmVTxVoV7peQqQyLgOSHIoFQfIoQCXYFNgBuQfUSL7BOZk+ox64P6t8cFd0+d4Kh2LZwNMY1hwbSdU2+bZ+x9uDW/ZevyayBEsALAWzSowBRRE4WxY61AYhQ/q8JruHMfzme8soRi9semIDr7hHV3rTkJB5EKe/c2a9vNbAzquoT1R7wMshKTh+s1fUTpv+suf00zGknfhK6dKH2d+nr6dq4thvPLhGCUpNpgDQHrFy/S9SXk9UuGs5ohbCCwJKHCU3JFnvomlr1Umbna1S1Zv/mQQD0p7d1f9FCuJZdlIYFMl6ruFkUqD0Qb0Fyjxa5ySTSgzYntRbkMB0if2wja3ubn0OcQSZYBxNNOsGQxDSElTOGF5DpD0D7IqDyalQFaZPLJmAXq0UQ98eLG/YDnzt3LVXFU9cgN8gzm80uQxQMmim5wGi3BsDRNEW9BOwzAyXvLP/6aM9lGTFrJmwNy0nvf0NWp2EqisbK+6q8hHOmefX3c7o+wsRBZrGxWfMplRreWbvWrxavcboaiXqQK67P0fH5mim2puqdCBVrZXEP9UaaxRqxXXfNgwcOseQtTUQ0yZnTb0A8IQd7/CDSsh0xzmpAZHN0rfdxwEUas+UV6wZX/fCEPzckpeblX6DukcSdT6R7ojgS+r9KqcML2q10sosBWsuqnbnZkTiHAi4ygS9ifMMl9M/ObZmsGYEwAajUJ7wlDR8pu6pUrtyBW10l5IAitieZdw5fKuzAFAehuZ1OQJTo1b52rH2AIM5HSW1Zk5/Zt6qtfwFSKvnNbCHUpVkcISOVEzNqooL/iKw0Q1wVBkJF57uYNt7dY6O0pLavaEXaYTIA15VB+kpcLIuhdbTpKvtktfkIqhtiT05NGTL8IogCqa5yhWJdHeKZmb47Zi2ORhLI3kpmMFc2/7IISm9GOyX7h9u40YJZeYzIcGYZjkjMS5x87qCRsF4pYime13a0Z+VGNDMBJ4uHn3U+JizPClzDiNwYCZKy6EpdYGsy7RGcV0QZDthcyGqxv3q62cRN1z5f/XHq8RQuweSyJ2B9/XkQ2f3acqT+Ro5UOjegcWJpzo+rvZ5JeNEL1BjtsMNP/K8lanJDovccIRgKoWGNqkoOEipAcorUWLdVGE2XYhybVqk2n2Z+NFinqdaMYbzZmiKo1wLtYoa3WkPLCUKtSuGF8ulq0kqD25vJNRa4FM/8QR9fOFbNiWxWU923rl1shBBOCBTS30+AtDYdfynbjn6ydqaaqYRMhmqHWa23l4XFkvpVtiNqhOWQB7KRKycuMJhBqDbMgT9E6ZY3In40A8AX86YGvxbFD7tEvKFIwUEsuemlpvYlsy9AClGou5V9vqlo1p2U15tqUmYmjp2TV7vW5BnOyY6yP+zpHqfo1n3ofsVSBMuCWML7x53mqdRcKXuzRV7TwL1I9mOJiuNuOUNvymJle3tElyG0DBRhLn/wYsN1czFRLyBv+ecUZ4M4dN/3jN6DV9WkvJcLw3cxy/0PoHIp0jT0BqhWpKLlMsCOHEJilaFaflkmIHCkKvWUljgSJDsHIcVtANnhAZHedYoHsEhaWIQu3zj/Mp+TgK/TC15jTkxOK7VSmJDXRsDVvIb6DB5205anAXDyBAUNHDK2Al+xO6OZ9FFcWdI1eOcvdlVZsRB4k0zPp2Yj9yzroBGOgB9hijymyMkIN09xxGQLn81xyQZ2caCPKAKH5VjWdA2xrGjzdDPR8D4TwUJUp9al7n0PPJj51ya/0llmDkEdcgId3XetbFVVGHXeIzFGc2560+4tdJnC8tqUM08uDlIwXeIcrqV/LUKbmgxCBbDblvnXOGbbk72DRegJW68GtoBy/7TFTP77A5KHl0XNnSHkTbjamA5rCzmw8yWLWoxv+1o3TMAlaa8GBfFPN4siYWV6+QjzQihsIa8DqtmbgAPPjDlE1M2787GykxFFmzXSipQZE6+iqF8fLQY0i/nTLK6BOnOjkSeuOv7cLWDd0iK1LDyZU+KLSafqZVloFy8PwwL7O6wQxeIxDb6+yNgyJY6wpIOwBnXqYlHAVzxi100GQOxTt3a22eVLrPO0rT+9GoXzwGrUd2/SCQ51rf5j2bBtIVgcqeWuOmCnsRczqKb+ggnl3oWtDUgDpXUUhWzcV2t5prftQSpJUndoil+k7jIyKiHU2DyaPR5cQM/lNizhB06UhjjLjvtCqUiV4m6R1bdCj/ZdzDHjZ62757FhPDyFavdmUDaib7AjkjjzOP6eCMNGv/3MUSelLQsqJTigYBzO7tP7p/1q6B22VT/WLqMS/CUECSDnL5vY9YVy6c9UKRUdc7xBZ6z4bEEWZz2NR4ESXyCr2qBvFQMDGHGlQAGRTmhbs9BOkp6QQ8FnWBvs7fB98U4xVxOsLDSLpqwJ/74pI41t2Sgu9XiB95BwsA7Tdg4Zw1WOrqGCQ8Ivat5T9lUu8DdtSHyyKMnnd8FEBHj7hkjYR6e7FSUS3CJm8xS50Y7jOex0fbgs+2k0Kp5TvsMe+pZ0yqn3fyIoywQLiw9njLVtCIqwSz2wEugbVCgYyzXxgPifKdFnIeM2hmHcU8kgEENU2RJ6UspC8yi5i+sOKpeCAogGaLiKyAqcftzH8AcMZTbYuHG0EdZTiRnECySCTDc+IQJh4zZZw93DrV0QIxOmmr57z9C5pjNaGlKdL7JwNKDTdQDKRs4GW/dqQkelghZsKK8JkMGsVXRMsLVffwAM/lFSvnuq3vgXjyy9yqUfvHKH1j9xOsEX5XqUVa9b6B5/tnmzcEas8oStKayyWWysvWl7UDlPcpHbbib+pjWeTwtbVIGwVr1FGw38kZYWtZRObw7Eder86A2kRWdI0mRxJyXy98gOlsVoq4AlJTGIAxai62XFSSfSnZYNgYeRB5r8tojNiQ3d49OXL2qzmA2a4tuepd57+VUYlRMB6m779psbIjtasQvFSmk9ev9j2WsLILCIW8gdnh7H6U6wjPDvRySH3H2z8tL94qFoG4yaHXy8iAZl2/0iXaa/u4nk5tV/Et5u36ypCXnXmiLGycB/6djK8zWKItNhuVkv6TJY9noU/0/2SeE1mv1DwXd/IYCoZiJwJtp9+hal1CqJLDzp8hES7rZEKhd9MZbnO4CPOm0pg5Iwh419/EkDkuhWYegI5i+z7Ny1oqgrncqmhGsdiwfUBO8UwiDR89dncIoG0OrQb4UnUdUyX/HvJXlhBijmLCI7N6j7rlVoK9eeHUkHoBCbab1R6wOTKPyoVsfi877YCSHsmZ0ER595IHyzCBLhdk+tfpU8HAutqA1NhCik0bfulJvL2T4bayYmoVYLE2SSp5j/MPF3rMf3a5Ly5+UW3ZeGMmCy6ddXSriGtjelEcLnCsTBiWV7WOpe1lAULZEihKWCi4fWbVAmZN2OUFs8KLI2wSqLNMMOZ7ISCRBzxDNT/35OBWiOjbNVgaWDvLYwxJZaatPx9k18wSw8Q6RcdlmkqUzqJYIRjX3i/yDXummqaSe9JZRTOYBsHR6aVZLXL6zd4T8KTVXkQiXkkEPlR5l9jg9e18f/bcalus1fX8HKzMtinheVkHt+mNP3I6okJFvAw8ICNhDdCLBTxPHjCFpiD0r39h30bu35CRMY6IqgRLiVw1OWSycohCehKZNcV3fHy4fpsoXT25tCAeh6s0lbjP7b6V7wDpERY6sYtCpsYR4l60fmC+n8VJO3QQwT7zrZNb7pu9lIJ9S9NJyDWqtAwkxIcj59VMgkE8Us2vcRHLobDJXK/fZMxsi+CIrsqehnJD9Ytgvtj5vuX8cmWvJpNFEfmGJixLhUhwb20tr4U7dHwvKuX1EKcngsowaZnvvE6FcxDb5VKfxGct4+sWb90Ckby3DuEHT05F/PhL/IiM4XimLDjyrjekobpFXApOOlljtQFKu7KylyfSKey6HJppF3gOBxuOe0PKxDox4F2L95ZBe63i+QTwYLSJGWTfeJU/0FswNtKHZwyC+C1CsjXiI5hgA5VNapNXOKVsYXn1hUbMhgkXDzQj1NzuFwID/33JLvEPzdjX8wwwUY1/3DJH/tUZ0Uao9yDTZvqpYIVICqG1HRAjnGBtVhxmEl8KTD3uZ9wpVgRgwRN/xhGQprMyvaGYsYMIQLAndqbCvoqAuFiHmmfDgXHmT6D98Si29BH42x+RsWNsEtgC0kAKlq93ryiUVsvFoMZ+NyIsbUfLKZ4I7EoGQASwpJJlrx2IwYI+3nRHk1/4Vx3AXqA+6bYjxkEyRXrvEttXShuRrnnLW5Wo4TtsYOu00ad60V1JqmwTEriFYqUhWnI2+C1HSykEaQJHI3WluWJA0ywpNfTnKfWMpf6eAtUH0OJOg5KFRkJMxKxlEe6tBEEkF5S7VHOfjEwWuQMga8QUqseyhS6HNr9CVZD1JK9hBmDEyyjT2daRXs9AOCLlOeuLBfE8J4cyiSF25nVS102hQVCduKGhDFQJyLWoeuPV29dJoSr6n2Aj6JPjZuOZnG/69qHWcQOdYB5I6MGrR5lVSRjGjV/TUqPSFblk4P9dj8jWNPMQimfOOPxxHLDXZ7fBP9fa1YKiMxE8fHGs2a+TcRqIu2lhGVOAITbHG9Je+i7n68RMrCUH+suxCdy7lPDZ03ACOpJ7bgxfqdlw8q/hFoB21eOYYmsffhHDCpv7iHLqFIdriiBGtkGCln6ROMjBMDcZjLpWdtTE5tCAINuGC+jUAcr+92LzOw0zBw0Nrv8rAskzjFDly9BX7BaSBNxPDuGtdjXrPv7dWf443yVyE9SiL7HDNmNdXXWf9uVFjX7dWHJ8gp/hP9sftMp4JoECqxfLhlHOWGYZOkquBcQjqPP2KrZbELUSRFWgVxJK1CRLWkiqZURDxwGqOkK+LvEG2ZITH0FnSukJn+F2lCiYuDI5RJPnlTDUkRDhZb86d5CmwszbiXHHQb5uVe7OxrR/SJT8rk/+kmncb2nMUCTSwCZ2Gxdd3jfcUIlBvCQ5KPNChHkluqvKSboV3NtiTW24OA2OlY1IpSIA5PFmztaQptbOszPzh/5ha6UHh/DDK66KD43y9IWPNVpc6AHaYsWJ31VWsObm4Q1sDe0qYnJ2ysYKaiFzJzO56PxaXs3zXwHdQCrAmz8ag2di+HTVOq02m6pFRKV6PFsDXwszB+yGWTFjwFmMQqG2GgFulFIOWPOPJwbOf4tJo6ux9tbhifHLwy/rCabGSvpQNmI/Mhpb4zTLSCSmyUKzJ3j/hlRiQJBO8mWCsPvLVvxwbuuyEvtJuF9tBIc+fsaFmyYObDOQzcACjRiA+qFJaZy5j2iQGuAV3etlgz/8DY6orCbYl4koqETfh0zen4zhDUKG8guHXIugBVwe4ZbMwZ41INHzPhkBBjxHkWGuVGFvnMmBdkcFUWDDzKlJ3FI3CSskZGOSmFxSe6Vseh3dyucRpOBr7uNvUIEuPrGtVUTtMlixv3OYr9t33hNlxPw6lf1LUVvtwyLP6ubdKt3smtwF+Cp6v1QSk4T+rlpUM+F7YFOGspcZvKOe5xQteZ0dKjZ5OF4mhFJ6eX/U0p5vDFl769ut10tZeRwTmSKiH1AHj0fPX5FABwAT/GqVqFWZANQ5mMu3YrHQePn8tJ6FO1SIRpEupr3T+ieqpFVC4/eLZ9wR5KFUllbyn2LtRxuvGh8B1RR7p3gdLBllQKTSm0gFJNopkEChz7iyMGCxT+8NvSAKP4uQdxItQdBfiomKlkBo3s2LdqlK0xF2apOynqq5WLLFuB58Dc6ClCmvyZ9+EWP4A4kHCq+ap/jEMFWL33A69Qn8sIEYO4/XzRnu1okAcwSa+ZdoiXhmaCIYcWW7UN+Gl6PJI+Q8FNvdQ3tOlXQMmUKnjsub1CNkeS+XJlxAHWTeuH2a65tiapjoCe8ixTEyjr+To9RoWGHgKduuK7KNZJukp+vsqL5hwa8Pp20fJWlt9BXajpVjWd/lquaOhKYaA65gkYOOVdlpmmgdnp+AiVr4gQ0/DjkJxMtQ6j5HPnhedjguzcgpYyCD7GhBrhX9CxP+NA1xJ8WK5Cbq/dyBAXB3zoB/lshL/1jWS0gAPVb/xTLt1aOYArXp8c2k5fBhLcBooojfrkIwyOa7lT7eVcDrp8Uph2Z60T2tYKOqwsSXaY+a8gBoZAGAuqsXFjERwU3gd02tJEQlgyWqQEC/0mEoR0jR11kXBPvsjoyFHzBkAqqPMAFCDAPxi5nNIOoDcTYpkuSouaRKLF2Z/+AWWn2wxTAaW9Zeskm7qjub8E1xfds0jRq8Rz4/VSeblN85HKOQTy58Mi98E+nNYRlAG7cQ8mSK5caq8jh0Dw4PcFYIzj+t2OYSCzpjQsJ5G8QWeqKDz8WUDoG7KW+KuiPzxFPKzJjec+m5umt5mn6uMRB/BLsTBKqa+tWn285170YgmKQLYVRUwPjg/ZTrWPYu/hcm7nz4gvSVHJJeBx6mP47T5fjfFxJcGI3v2rinb+FFhNvAFStU3lhJkjVKs/vUdav9iRUCmdc2Qr9AceuRqr1qIRooj61pYf4uw39SKaUQ841dWQuRpe9Y/eqjz4Yhz+FH+5f29LBkbzP20xf+xYhFZZCmoxHeV2mCB0gpJueyyE3Jrxm03NrhoEAzOiMclzPfOeFy2CKH7osKhGCOhztnUl5uoiMKJi1R9YORI9kNJHEKUuFW/eqsgxpFqxOwLHqDAdUKnZzkX8f1WZsSLgd7atlQA7+TLpWBZdcxch8O04w91tMrpOBMZvJs7nfR+eNWgEzq5WinSDz2p4HDQWRFhHPiApyGIbDCxsnK4J4txraEzBxISufTg4nl+ezmITBn4TpHqvNSzwM5/OX4D/gd21J3s2bpEhKMnAc8Wi0wUjGoRUdGFcqHpOJhPrhPaVp2s3dK+1EC0CMj41XQPsHEujug+eZN3rcaoyHfjFn7YuCVtSYGxRj68gC5hMllRYueeoF4OvNTH7ea8zMATelz+wFb51B/aK12DaMK5LD1IhU6UAspxvP/it6ltwdu1xMdDW1/uZBgrzYaz2eTFbvz45xXwf4ucVzxCeLWX5hfVWLqFFFpIRzvXBQX5yBAKxAkPJY59DJv0FNSsbjQce7KAEIb3fn9MytLpd2F/3p+KQtUyhfkwbnXrq4p/xgZnWTbDBFFDt9my6PHTmieSPPiwsGp3Ap+u38r+JVAT1kSJIO7w/gnYppEpb15kdVNJql//PBOay7MR8h+SRL16yeQCN+5GG/c+4xzIr4EREymqmnuIw312xv4++H2ux75qgld9ZNm+m7a6HjSrIdKkrHpf5LIzWAq+OoeqegoeBobL3ofKYMUuBGoaW4mo/87a5bTnBV0fOrV2d+9U9zpz3Hi+HA6oG4JoFp5GopiJlxVJYiPzwmyyOqVkpo3yxsQZleI8DmB09kDS7NsbqJMqVLuUq0aarM2FSueiwGmAm9GVMk7ezCuelrmDl4BtrqKrcEEFu9x1eul/3qkArm7GBJ3cKMIEO69M1UFvSGAiMPfT+4hQL4OBEtdU6puOAkrlrVJcclEuvVkAL/K0WC7hHPNr1+Z1xGx1wRtPDAPMa88gVBVHz/HXg4BqLVomaqe5ECnGpVm3uEZDAkF2ff8zouzk4vZHLu0WR34fiVEh2agT9dzsFj6JnM6fEsh5cAZ7HLRc1hRzxL5fqRgALILgAtPQjf/rRGYVU0EHOWlrcyp9dZ2930pRN9UHzfYAY6iMypZLcH6ije72ynZAYlFbRUUbNWvpDfphFxlSgxjTiOtTkRjjnsjA/Ofdayy95EzF/iAPZAK7eIoXncaVZ5O0n80PMkC2gPw544pbAjQruDM/E29x/6v5mmhF+m8ttZA5vP5Xwo7OvFDygyNJJltwTt4+T7uCVIKWy0HqqC32daep9zlOXlFxFkzbVuGfG2+QK3ZuUSIE0PWrJOHunyoKb4xYSUcKfbmMpZHhS+XhCQ+GALQMcbMwj46OJmkXWEkZgmlvGvzlTxYw5PsEoki60ijG23W3NO+i81712KNDL/KSTq0xBioMn9yG1scYrpZjMzgP6s1ZhDbj3DEHa0lJQUTKxloqkQ39B7nwD88Ixrn5uKg19SQEiplNEHr/LsGUESjsiIKPjeswCWN3qggcqdtlulLMKoQwUxBE++fqx0tSVHqeIUgo7GJx/5emIVvSZsOl94s50XYQI58Zh9POFooi8UN3Y5kQASg+1C5QNI3+fwyxA/ydg4MbhN6HA+mcWk1NLKDG1ZVgXnukRCpKRLn3BAx0oSOJrH/PQg15sLxeRiijD6QmLZlQYTdF2yash8EifOABbzNSYEBOHVvfKCtlmyBB17G495C0fuPuZ2Rz9BWy2Be4drqcnqoD8VAFuzoEGcTIFioNJofDGhvUPjkOx2emgu2zgLuNc1hYTv0qlof4+VsmxIKF/Lt0xcVTQBJy7h4277EnTHlpuGK+87lbNNDqLhx1w4S/FUjdy9VMv2Wp0gSRUfPEQmZs7zJ0Ax4ZOIVKrxaHjZVhId7htIUY69TqCWuaE6sttnxXQF0dQkrh3v5QKkAspA8CUFkVbgRDCZTgiacKoowQ8vW4g2WCFGpHE95paKX9sBV4TL/qfPmajvKjLVlVRFIWrJvrNlNJTk55bWUVExIWeEnsbKyidK6VUNF/2eFzqnLrHnQ5I+DVW8c8HZrG+lmzWStFtAD+iXk11Dv6W83MmrsGOoWcxD1w0UXXVmh4UAIJBfGK4Rll/q7FavTszt/ekfLyPOZ8abYdpb6VS5KX1KchB3zOJAyLK3Jrwh2MO2rWofT8C1V2hiu7SAYwne4niKQmDJk52Pnce7cy9OftEvVpB8cNlwRGrulmjQE2oTtqKmDyyD9szOw2CiobtLCRxh5rlfhFb/ozi1IqidvFfTgtCr+1mTv8kLg7m4oWBlWuUWD9Vvo/XA+U5cJbFpTo9LhMjzaZXUBXUWCbUQWlal2IMA77hTfycqLUAMQEhko0RUdxDF9gQVc2S+WNPtVHBQZA2sfPjKesDoXCazjpcr/a0FM+UKmu8U1EcbXkRwyh+nK7XbC+QPf45K71BfuuD+0F5tJXEGwiMGueQssqu6nqGv/SkQgB3BDHZBukVYVEWBgjhMubaL4iIR1/YMC2DOlo654d9zp/gA1h3FFdcSRKwo/iWpgHjCeYkc+DQe493NxHgnYLNrsNqQwMwvYgmwnWvYcBefhJGydSSuPHJMaakJSFF8GPTgjG7sdR1MCZ9jcXr4+2sAtksztowEfmyh5vDdSWRN+bR2EVgQjW7Zl2Gs+9m+4qNj5POzKE3Y5J1DHT6q89uln2doc6xW+wL27XwXS9Sb85XdQZeQYuLjN6BPj6nhfCAr/5O7YNEWloRWDKabIwkyf0gXfX05uYDQ/YYMCqxVOwWmLObXIuzeYOkMCcs7TaC4tqtf7XhJ4MQJETF8j8ohyjGlVZjS/QdRVjS9K2ScT6uOReGG08IcjFo/i4utBi4o1Ys97Gmi9Rxw+NM9tSye/KzTzCaHhjLGaQNpPwfPH4b7UcudNsrTVut31UmhXuBka4sqyzyOkaRK0UQzuNjxinscq7XupYMn8hRs3I586IDZ2oELHF0ntcw5o9mB5Fo1Cwj8fdU1u159EtxmsPIGr3KtS+k6B7URFi9ThvIEXh3n+tCx8OJ8IWPAM2+ugoV+WdHop8Bn963Gt65QjcEPpQnCdB5uvXq8QXx3NNKG2s0HR38BQEAE1zy4ayqwdKVEkpNzXl2fDGHE7TFLZmmV30VYxCqEjG90BKhhC8GZ9W2GdIfcNQUIlOeP93F1YYxPXwwdFdhPuhd4tDpCS4+JkwMzmc/VsJOSeEIuXM1XfZeeGHGY79h4AKZrwMv259g/VVe7+H+5CQ6kHxkTvrZ0wWHCJReg/Oq2z5OzhSH0J8V3o9qdIjn7MiL7uvhV0Y0dxc6ZjcxYSNGVnDEGdzq6fAb8BfZErBtb4IJFuAtEZAzjEzq5khqDXg/YZtAupHioge1qEDdn7bW16eiZRDDoQJmZtYqDM71e9BPfyLMSdJDBwO2vh9DNfL0+eV/rCtr33L0cH7AJX9+TIj+yZmWNZ8NSocjjKs9bPIdwaKsegu5Ujq99srGVJr0XeUJs3VdYx8c5AM1rqVKMvRkZMDAocLjAilHhntfTUrrSuXHqSzZZ90+WGNdKqMMjH7pNkLDL/JgHCyoAEVvlAhXEZYoDD4FU/E8l/gRjhuxfhp06PVdQbCJ6697YMYkXunOO5jHHdRGNhdbhwL4SXftd8d+jRTAkLA1wpI/MvGHZlRZIw19eLzX9wHoXMA7YRu4vLT9gAXMt0SsBFy6yDmiVMPCIOpDuKAY/0ege8gNmKaQbhOXb7zC4Dve5iMpVJW95SjtfVrwMTmPvUvoc4hZ/3w6BpsO1Ngx1mea305ejoo6JMH/w68T6PuDk1+U22eWslU9fjC0GneOdFgS6PGyv52Yl3U6+7LWeVzAf+9oXWGs4qc9eWLEEJ55E/acgt8GgPf8zyuwpjMInC9vBE5+n9L6WB4tqX9BclSvvnK17ixBmKnxkzoVbnc86QAOjsn8ZdnNnVRjL4eSg8HjWauIVRPjZkBcPMTxW2MPR0u+p6YcLo1A9StnMpMKbzvhD4LWKKsIl6j9VoX6cfmgELHtwsrxdcnBSlitszijsB3uy2bhB4WL3G6S1IdcoydUGDZeIP8dhgJZ2AgS0CgnJ0+lgUxrDONuiuBlmBCoGfFZUjPaikwCKZwFt8SbQer+gyjmHMcAzY1+vhYt+yCNlioC+6CIWetbaivY3uddnNCoBv/XfxLnYdddOPm5HfuS7eYgKtUstu2paPTwiGZ63gSwF10s4nc9d5B+WfltjBqFkxi6yXExFQCO+714pZ13uR57ovW611KO5lRekw/MD/YLxjvyLFAlpzPp55vrasQ/fDrRIYZo/IsWr0ymDXni/R2dTHn0vi7bsgq+IgpA2cYT8K2m+UlCak27ai3d7hKIDUyI07ESDC7YgWOR38zfDFlV8YLyLb1xak/TZ2aWMOcpiFqL+uNnMnezO9ufWW3ADfDvASIcpTIOjBIAbNjwuDaXgrLhqxbQpAYybje7dtfILKcXLs9C8ozGG62gKVKKL+KojPk17x22Qa/Rb07GZCHTMDpl9XoQP/QjFvZZrzAXyBoW2mVOC9RYVjA4+vofDdKk1zjHQpugEoXQOvxdrnEbso8IJK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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_output.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_output.json @@ -0,0 +1 @@ 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/eval_results.json @@ -0,0 +1,249 @@ +{ + "structural": { + "pass": false, + "checks": [ + { + "name": "entry_point_exists", + "pass": false, + "detail": "no index.html found in workspace root, dist/, or public/" + }, + { + "name": "package_json_exists", + "pass": true, + "detail": "package.json found" + }, + { + "name": "build_succeeds", + "pass": true, + "detail": "no build script defined (static project)" + } + ], + "score": 0.67 + }, + "functional": { + "pass": false, + "error": "playwright eval not yet wired", + "score": 0 + }, + "quality": { + "lint": { + "pass": true, + "errors": 0, + "warnings": 0 + }, + "typecheck": { + "pass": true, + "note": "not applicable for javascript" + }, + "performance": { + "bundle_size_bytes": 0, + "size_under_512kb": true + }, + "score": 0.67 + }, + "code_analysis": { + "files": { + "total": 2, + "code": 0, + "docs": 0, + "unnecessary": 0, + "unnecessary_list": [] + }, + "lines_of_code": 0, + "dependencies": { + "production": 0, + "dev": 3, + "total": 3 + }, + "complexity": "minimal", + "console_logs": 0, + "magic_numbers": { + "count": 0, + "excessive": false + }, + "function_length": { + "count": 0, + "average": 0, + "max": 0, + "long_functions": 0 + }, + "max_nesting_depth": 0, + "global_declarations": 0, + "naming": { + "dominant_style": "unknown", + "consistency_pct": 100.0, + "camel_case": 0, + "snake_case": 0 + }, + "error_handling": { + "try_catch_blocks": 0, + "has_error_handling": false + }, + "comments": { + "comment_lines": 0, + "source_lines": 0, + "ratio_pct": 0.0 + }, + "separation_of_concerns": { + "verdict": "single-file", + "files_with_rendering": 0, + "files_with_logic": 0, + "files_with_both": 0 + }, + "html_validation": { + "valid": false, + "errors": 0 + }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 7, + "tool_calls": { + "total": 1, + "bash": 1, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 0, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 19 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.67 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "javascript", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3", + "run_number": 3, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:20:49.574840+00:00", + "wall_time_seconds": 770, + "exit_code": 1, + "completed_at": "2026-04-04T09:33:44.883116+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=javascript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl @@ -0,0 +1,7 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "javascript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse JavaScript (no TypeScript)."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-xwmz17oo","session_id":"1bb8e69e-dfa8-45ee-a9ae-dc59bd0707dc","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"6edc664b-aa4f-4698-b6fb-2c8cba38dfe9","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01SEwHtGk1JKnArToJKWJjL7","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser using JavaScript (no TypeScript). Let me build a complete, well-designed Tetris game with all the standard mechanics.\n\nLet me plan what I need:\n1. HTML file with canvas for rendering\n2. CSS for styling\n3. JavaScript for game logic\n\nFeatures to implement:\n- All 7 tetromino pieces (I, O, T, S, Z, J, L)\n- Piece rotation\n- Line clearing\n- Scoring (standard Tetris scoring)\n- Increasing speed (levels)\n\n\n- Keyboard controls (arrow keys for movement, up for rotation, space for hard drop)\n- Next piece preview\n- Level and lines cleared display\n\nI'll create a single HTML file with embedded CSS and JavaScript, using the Canvas API for rendering. For the pieces, I'll use the standard Tetris color scheme: cyan for I, yellow for O, purple for T, green for S, red for Z, blue for J, and orange for L. The controls will be arrow keys for movement, down for soft drop, up for rotation, space for hard drop, and P to pause. I'll implement standard Tetris scoring where single lines earn 100 points times the level, doubles earn 300, and so on.\n\nWriting the complete game...\n\nThe board will be 10 columns by 20 rows with 30-pixel cells, giving a 300×600 pixel canvas. I'm also adding a side panel for the next piece preview and game stats.\n\nDefining the piece colors and rotations... Defining the rotation states for the remaining Tetris pieces...\n\nNow I'm stepping back to plan out the implementation more carefully. I'll structure this as a single HTML file with the game canvas on the left side and a control panel on the right showing the next piece, current score, level, and line count.\n\nI'm going to use two canvases—one for the main gameplay and another for previewing the next piece. Let me build this out with a dark theme to make it visually appealing.\n\nSetting up the HTML structure and styling... Still writing styles... Building the game interface... Defining the tetromino pieces... Defining the remaining Tetris piece rotations... Setting up the next piece preview canvas with scaled-down dimensions, then initializing the game state variables and the init function that resets the board, score, and level before spawning the first piece and selecting the next one randomly.\n\nContinuing with the piece spawning logic...\n\nI'm defining helper functions to manage the tetromino pieces—getting the current rotation shape and validating whether a piece can move to a new position by checking collision boundaries and checking if it would overlap with already-placed blocks.\n\nWriting game logic... Writing game logic... Writing the game rendering logic... Writing the rendering logic... Writing the game loop... Writing game controls... Writing game mechanics...\n\nActually, I'm spotting a bug in the `clearLines` function—when I splice rows out of the grid and unshift new ones while iterating, incrementing the row counter causes me to skip checking some lines. So after splicing out the cleared row at index r, the rows below it shift up to fill the gap, and then unshifting a new empty row at the top pushes everything down. This means the row that was at r+1 is now at r, so I need to check that same index again—the `r++` inside the if block counteracts the loop's `r--` to keep us at the same index for the next iteration.","signature":"EpvFAQpbCAwYAipAAh+FHdTm+0FA+1IktJ8iyaPFJba/Vi8sxPdtjj29umirrznaM9ViPVd3NFwnVA9hvY3qb5nDW91G6psq2kHNfTIRY2xhdWRlLXNvbm5ldC00LTY4ABIMv9a9U3Onh2bQbNN4Ggw6iGqyty6Dpyv18tAiMC8WVV5b2jJiHTteKtl1tijyv9jU5+kS/rHJqp0uh7aPvCiQJBWpGkNAicQkJdZtLCrswwEQubXGQRNkr1Qd42Ngy7Id2hCs4e3qYHfjZ+A3bCrNl7+aIZvXyY3uOduf5PrtGpaA2+UDRWwDQY8+MIAdBm6HtIiNsh25u6ienAz1ExMnxaD1hzbMLZZlgON8Lktdyy1P4tD6h64Ayd/Ers9TUjn6b4w7L9l+WHnxoGkTYGfDRo7qhIXM1LesxKtlvntelqMpqsSrSWuCRal0czby7trkYqUjC1w94tpY0IrsYfMAqn/jVlTbFNsXuL3fy0RWw+Ykk1FwxNLLtZhNpjgXaD+2pLkEgiPJcwGkes78UU1ECRGayizijZJb1JLvSEoZ6cg2cFqMtEpLaGHEMSIvXVcEhnWJAuWwFyhTLAbFgdYTnPBAPjl34Ny2gymTsugySkK96IU+WyPdKTJf4CblHWfZGBdoSl5mBUlDZSsNgBLl9iPqcMIQyrXy9JrXJSM6LR9etJvj+4ZsDL1i7tS5imVaSX5LjzxSPSsJrVDQ1mYe1SAptndYv3pvdItekPT7CTBD3m83vIW3LFPLYNfNGX5FUMMig7vZ9Sf1HFjHm5kiMRvsFfcb97ULA+sdR5/aqhhlhseRHPoznZ9P4jXS55QlckkuPw4k3cG3114JHatgmQUgykZGdUL1Aw3Pgj4w8OJc4IrchO05HcIIk3+p24nFVzP8WGkoB3pkb4flho+ZXlqvd8++50dFNxJjB9a/CQBsGigE3h9P0fo+B4me/vsOO5GTVGV4uS7oyV5S7NMI0S0mQOBUrZnjuuywj1TfnQKcnP5sSDIpOMsf9MDg0gz4zIxhqVVbB415pY/+uyQEaqwKj81Z6O8v9XiFu2GRFxagWci7KNZTOFR+o4Pk/vrKCPQrexG7F7AtFJ2zMvAGuDZ1/L/f8Qp5VJLegONky9pwXx+mQTKYmPyeEnW2VclCmSBNmnGTKmEan5PYVeSfm04h24ZOw3Z+wbZKUd0YcbHmCK+m7wtlvB7x/RzIaQb3dNoYZbCD0CAGjr3dedOWeZr1m5XV0BsrIRQFP4OikqrXAJAQ8lJu+axCfgdXJ6ih/rkgZOOeBzkZmXjmWWHyt9zuxNFli5ala3oJDSBE/zS3oNhiF5JOHndzA3YWphqjSY8dvfNFg6cHhfJZtJRHCF1KMFnIaK452ZoQGI3WiPSb36Vd5wX5VhTKzzwZXQ2EnIrLdJ3hDu1RLayOwumRo5precPX9fefUMIazLcNyHHtCVAjvKIydXNeafIRXc/Ckey74XUKkfXCDkpMVrUVJy18cQ1aFkDm54698W/Cl33w/Y+Ui9HEh+TGOkdSTv8tMFIOauf6wM5py6pkMSvyrKun/zAeP1zVXHUOqAD7CNdalTAmh62pyVGNUdpYZbPso2Tsq1vBnFpRvVUSxuoOHO1KQBH45i87I8WmWOnO1uZdqYfgbFMkpJuhkqjD2E32Iln4ebpZ5A/wn210LlmpnYupeDj1rxJZSHcfyMB44RadUUS4ZV5jiWQqSqgEyYVjLZNcVkognCIro1DmHD2f/qnVACsIln95Q2ksLxTWckvAHyRFUjuzQa9MsYFL3mFXhbu7tSFDU5FvMt55wdKAu42GnyBwE5W2sfM0SIO30Qm4p6BmbcFuiKrkAfWsi79Sk/LXI/DGmnCWnOMqmEr/707UJoDy9PN4RWEI4JRMbAoNGFBGZHwEa2jlscXcxAHcCVKUODKvSY3XyucbWMTFypoyJD6vmpmz58tQmAH8sIUaeWyFBtCmpZcmyw+zqXCT7kpcODKCpQDciMKpWvOA7K39+k+66izgzjcR3+abKR4ZYqcNpAxTJso3tRMy0w6CvsOAtyl3qDosTfWINu4f5Uqu3mpnl2zBjhs/KFswXq1sSNpivjM/YAgJ/OG8i0Ew8/DFc0za3M1YijA+6Ik78XLfdcxb4o1S6YVm/GTn327+wGyUJGXsDfoFh54zWzHUQUI0XOIK5fOaMEjLUAswOILzXjk2f9kFBg8V8fZIz2LOiXsRSrHriqwg/0NhSXoP/XHk/ndkEnU1kyL1hP3+71c+raFmSIGgf9B3jIXxR2LDsWG2dpaUHFlYfOQGnU0h1eu7DqHr1M+tWFFjNombUc4WJOIj9saDk0LMsm3hfp0tsnqQQtUcyKjsb+FL3nS8IjUosszWl42gHFclRpd919Rw52y1Q3x243Cww14JA4ZrZxl/wvx1iyxlS8YERDUu0nCJxBWCCzLDqGlFcf8BXDU90G1/11DHbsLrr/PG+qkIQ0T5ZIx/J7dxhNdGPgLhFPr/P5Y+HH9kiCpzbFddyIkYev4t8oYtlQasvapn7GvHiz1gBifZnNBN2R8icc6E1pKtDEST4oLn3HqRqvlQxJtxwSMS22mmk+PcC4BRox5R4fhETFbI1zDOcjdzD2SnpnKhZgG0tpI3KdUuP37iUxTuoEqfjmD7PaHXj+MbT74sL3XaIvqD/xIMStOpxoMuT+3xyUszG+z+VX3WUMkCCOiwH8vk2QEVY0aDbWxeR6aJ0xbrmVL3zETkwaQxN7puEvIiw49NyfToPf/EJsovLVA+vuXmHjhjJm5OJqGxHEBXFMEVgWN6Y5t8vZuAslB3mc9GrKDqAx51hNGT5Vm90TiT4GzTpKO/+SV4OlHSKUt1O8p/CCBkBqlJiC3kw0ft79jWuudbWabWBFPdh+0cuUVyHqyN9x+vB4J1UkZvveAItD8DWm39EIVEFBHsSKFMgd9+pE4KQ6I5h/gXp/Nz9ByDUS/Ig7Yt9KAPau9ODhPURimwmBzpXTDgP3X32uuqGiTMlYg0FuddLoTrLn23250u+eIIupjGUeJfZkiS92tjK8WjYWQB3jeVcbHUH8Do4jxY7wev5HkVmvqRMcw54LYsosQ5TVzBBQq9IcHzDMRPzRCKgATz7QrvNRA9zA7zG8JHZeu/MA484xJ/X3h/8BGjw9wPoJNSL0hTsPttKa+vpPdUbZNw86gb/MBIUWXD9LRc9LzM6Lp3ocuWhai/tnU0wbnu7ioyVifiTQ+DqTe65fWMF7+5Ws6raU/yOYXHrCc1oa/2MfvChdTn036ujL3TNLG3/oQ1n8J3SIOujFeAj0wgj4nRQeYGrhi8UahU6HF5YaIToyDglY4WeD3VgRyrLmyuGVWfKUxTjvdcXzbMb7ZpFdw/p+3IZxx885+9DmhhdatFcsA2yWs7hH4StF5DGaZBRcTNctrqXZKj3HTNf26Ievuj+7hVwCvEm+s+EFeLk06vll/XMuKyS4aIMG4IvjtsRnW0pGw79xRUJnqigyDD7kYSD07y2WmsCLfm1qAe0EY3AjeOHZfqEx3msa8Jk3+PN28gu9lgK0a9c7n49A34tqAbTr2ny4gHSOcd4tKZ16BYlr7oSZDlNMNOUUFY6SSXfDYJUPEdGBbacG0fR67O3b1JhBkEph3n1kxXkI0xYZb+6NRWfRS7iHCBs9s1bwp4ph+wEEFEGRcncyidxodCRtAga5ebYMLNvuTK5cLKmerm4JjHlVaJB1plbdR3v2/DuDzaIYKE4kHnDqSZJabiYxpo0KoGaavZCx4mQgZ1z+my6taZ1JHio0BbGajftWiRWHxQawXplj532ieY5dJiu7Cbv0y8sHabeMGREnQpabz6kL8zNDt6bkI60NdjbkRbPt0T78K6kz1EDb0vL2nBoQu3I69JQaf8cGPwC9OX1ou6AYNRZNTaOyEWqJ1Qi98/cuoh8tFxFur0qEMwB9lxbIyYnlRhTtGTcNpxHPWzW2ddVbi2jvasgTmh+4++WI3O/U6UCdeAtRzA59pBXLdVOQGXuq7QgSI5W/anQtGOX37ay1SKHf6cCyI8/9d8/hQJoMEafr4kOnyGKopuW4LJwCO4xlZgup0gjPof2CnKFGaA82lOfH2cVV4wXape556tBO+dEo2W2XD73c515Am9JAH7gud3CzldmLGCv7+vTCw15J9oute2ziO0ub/t2wSPxt91/FxExRCd2c0u4I2AfUZk6x7ib6rcL6vu8hczX0oIgDUHn8+dRaM6arKKHsepedrI/y0UFF5TQ9Vh7Df60sRoVTubJJ7HRQfDHmzwWE6AxIgZ051tqOWfc9jU2t0htW24KaIhN3IsJ+fgQnzS36933xk0EysoE28Uo5vHUUMH4I0S0ZkF1ZNuX/YGnBd8i9ZONvxLBMbkBDfwcHxtJfWW+cChSuRSGOl7YL8nWNV5oQkA2caJ+wFPGEOqqkQ3n5Uho/3yDg506rx9PMc8w3EzYOwwBE4mZucpJVa//rj7xL0AIzpV+xbJyCqIcDDjILjAyPju7kSfLNqbUuKuFfhGuuRxN6naHMtib8SGJA+K/yfU/M/v249JA97ID7DlD2/Xg6P+lr/dUlUnQQyP32UukPZkHqb2FlhHRxBDBUOrgGxF8aMjyt9QJ2XfIkEevt7oFzJqtV/K13vW2HzLRd+5wwiWHn4QXugUxgXWUylLTfv44kvDSvb+masD0D+tM9fDaunSfwY04bIyTkrZH2DpM0YxpKTrE/tOWofUl3t9G2bv6oXQkEbrVHjX/L6JJMoES6Mvu3fIX30tijhF8WvMc7z2GxYo7PLURi/ADcQCMYD/L9IUK51FesJwT2GnIyKv5bW3tMnhvQIB8/pai6ZR6NhFcGvcddOl3NcVaKObMQj3rON3a6yBL66En4xxBRCDWpgcm8mT84Rxk+5YxPlm/N2kGDoQhKvx76DPUANEMq/3wM3WOWshv6Sd/SShcpe5vsDWeCoQTsk80j2icv4BhnGWyVhQxN0hXzLAn3bcwcsvX1H7Gx/EQP2qOaNob7lRqmLHnVonkDGVhfO6vpzpeUD2N93M7rHdcGYIGLZc3zs1DawzdpdlpT6eO3ifwXsjuj9dyeImcjxPDTF4pgUUkU8lUa9+07AhaanbJyuidrJAhF/QTES72hR0NKtagysyIYrBzmvRXvjAu014RrMbVF7QbrSAqfkvzr7HVdpo6rsVs/J+Tl7wmAd3DTZ5yTUDKN/hmDORjWTSQf/vXxKGqBFpi9eRh5Cg079A/6XRp4EEVWH9KG6YZceQ97y0uWrxxtldKgOO0mZKM629HiMfabp/guzNkyTvH86Tpmkpc7KP7LFXNrUzUogK6iSXNsaWxcPYKS4v9XJ7e1UM7b7cmrAVTSWkxgm6nJEUNZU6okSYU6CNYgCW4Vf6nxx7n9b6qOt/cs678vzlAprJEQDDDXjA4kPzglFSU3W1eYaMKeNDo2LV7Un6/VnzZiURWjHQ+4TwcqQWFUq2bOifXL6TPPNf2KBN0rvi9L9LLCbd4Fk8G67AHuH0HicQOKV4CkzYnMNmYSqAeZ/TnWwpeGgUX+kV1Kbf6kqwa0xEAv/ejxokQ9M5OSxjziITMXDLt9BMZQ4Bfrxw7sToN+mqOYOjJxAMRo9UlM3CnUv4OAPsU8J7y0YNVGe7FxfFtH3XxiH5031JZT6tYpwBj0XThSxGLmv/RFy5lTN8kGSQTitlBYqrV+LXHJBkl8zEhck+niMKDnQSBEPBuh/eNMA+tFnFkG7TXsVigU363FkGisZ/FZ8T1p2/GcbAiJCtMlSDYQjhtk24u/R7ySehP9HLzJTefP/EqnQq/Rq6eHam5zLFHs99u1aKtGEQLiHE03XJ4QMr0jaTbV3GjbCtINSDgdvCB7l2gPOVUg7JRjE960AaFGi1TwA/FqC8uDOOFXx2JxgKycGqbm/JDy2oa5xYuZQP8KnGmM8vSt7i7jjHqsJBrfe9RBA1Vguc+JOwaAib+NqafMeMZORRCzoeRo5Ul8ySN6uFmstjmudgebjlPGpckdr0itz4++74O2Qpyuu7zpbOSjy06wuN2haisGFS+Ufsm/Tl83/mfygLZJoF9RPbqJBGBZL5xoi1BS4GaEFC2+yosoabnWy1grYnMOQhUpBmAxGBM7wEdllCU1PqWWuGLrv9Mxqif/DKYSWsE2JnXMWeCo1EQKGgwCOawJxvqmjXvhghUj9H2jZdzN+YqHhNI2c8ioa/33pgbi9au4+UmU/aQ+DOtZ19EgUDtuZsuF8oGrHfSrxD4qZ4FfCRZDSijO8lYsPUuaaWbcpcTMsUPa8geGhakME7dg49GHVf82agSYZkr/HMzlkLF4dwScXDyifNx1fNfauOfiFp+FQlKLXg+auWkwKI2dxEMKclINx9XRnpijuOTNcGuwPvhv22IsuMlWqbmn74bJjbFe20N7jlKx6KRduOqXoMw5NagGIyZwk6G1PdtwuhsUsAxa5N5BzETLQWEuPBI70EV1rAYydrSKEkpg9dmMZivv0S36LqvccX42L/YExz/pAgZk7MDYwlNwNQov8kv455yvVPNjWKQnk+icRMKNyG8bUfR00vF5NgCPHB7+Fna1fOL9aN3LJ6oTH2AyQfOp/8egEnXJEMqeyr9PnIpRnSuJErEiPrD62LhwkdOXoVoO0XoTHAVB/9HSWYI0HubG5deOXi3xBxN1TOd5eI+7JkAaixU0EtMeyPNfjfUCDZO+zHmHs8MHIQoHZn5wuocdc77JvcEwKq/PvLYFVE9wunRzqLWpwd+VzcUbcDhXX8RfoX+iEqanG9LZDeMmtLIfQIZd/jGjN4ftsbzDLI3nRlicwn+lUM9jW7wUJQwmVnqr0EOzI/+OuKjTAujgk7Wp6cGqNOHUTubNIEcI0+G2JYftnvQs3tRsAUZZcjWmXhHrE1aeFx6Usdl+QHxk90k5QoT6rd2x5msounKjvvfyJxrjba8uQZglMnvjHtVwbtBnHMy1NtuB2KmL7v8J9q4+6Q/Prh7+kAp3r2auE8ztHS6j0J9hmuv+To9+m+HUWgyI4K1vDyFktyhkNXgrW+WI6aoGkX3e1QZqSu+Fxll+fL9n2Gjbbgza+0UANnLJRXJq39xrYB7CjX1gwlq32duRlb8UvDLYLOEVli/EWiQ2shhGAn+bRQpUy0GZdeIJzhimlLbBoYuxV0wNgBErw9CrWdVvLYsQxgPklSqzaS4usGyPIsY7UCFUTf6WX/ZuZd3nJVs1P0Dx4Rnjgrmh1hzc/14rdiiN7+1lx+bPwMsjqQwZSw31I5BF0PbkdOsR0qXizNI/W4PUrnJKdLkXDVQEWt651oob4JcJ10he+I/35YHjhKQophmkdB4GNKI9ryOsJMtACtlLV4BIwDjG2iHivWIlPTFYD+xH0ZQz+QKlZ2OgQ9qpUMDXUph/GwFbrubADkD5F/vt4BXaUtGy85EXan755NekaT6hF5maxULsBq6UkxfuvCyri50nybBR0PYvOWhURospKYWZwclfAti7pmjAhybzgUU0HZQYp3tj1DVN83ZEB/RK1dUXkghoMg8PgF0fKuyUDBzrKwEISkaU+kgsdGJcdbvndOJl6Mmq2Hq4O6piskQ8i5vA3pJVi2z4ubxusplmCu8Chh0+ePjAYyHMA+4Rc29HQvNwdY4Hf7p74PIiOi7QsNqqT63LQta7teUu52Q9/6f7zIZ7rQjAKI+66wWr99xPDXINQdrW8moLUlCCuFZNsTHdCVLJ8lRlF3j62JFXVpwqqDF3G/Cl7S9OcnfoZrsXnK/pSYxNUcA8VSyvP7oNa8de7MSMgSNT0o2TestENgcO20FvBDF2tbqTD3pbbCRqfTsW3CW8/ze29uGclbehqRKlCQWCobILVBJF3GvHbf0L23EUTJ0F2AH0y51dNqbBok5ucpUdBUTCQr3D94pU73RPBEp5SsgW9IwTOQldS++RdN7MCk936JoEX6Xzc35gBjhQlxjbWKObZtwmubVl+1mc7to6PSU5ja6ehf84lhIvti09EDSuGtZ8VcfMvuzhU4zH3BS2tX/uawCFwSI5OJ0KYrKfzSsNXidpUcAJ1El2VUfHkXar5s3oHPn5cT4Ln5ZZjnVr3m1jSObKC0N/KrJcNdmutQmgTK1JSQSg7IXrLNB/LUvdDMHArmcloTf30lnQ9Ppug7tp/VsqcpfycZ5rqXt1wngHrycuvWrICcEOeekfWo0CxO+F4zSkGFChYcb/4y+VrLgBbfhzocvc1orTYRCBo066UUWLnV8hoyX/2HvN1LEd+G/ByenL9GSYMC/H8AlAN8S/onLN7fPn4z6G0z9/pkNrRL95JvBUtB5yDTpu7734DuZ3a4n9nITLV5smLnLdNL8U/l/7cdJuFloXGGqJ2B4AAE88iWiySAWCU3IKpEXmpw4jZFj6zRtl2Ztc4KH5IftzAvRCMHpLv1VxfB5DXkOpWdJs9akVi06VARFow4Nedf0VhDNXTY++t8HQtFWvrW4KIZGl+mG4kGVti8iylutJPzW03X9GqsmYv/fwzIJNV/bdBUloeUxB0D79r1LkHz6+4QtG36RnwUd9yjZCdD2Z6R8L2YuA4j/9NwvE2IpyFy8exZfB7OLrXbxw3rI1iMQ6EWy/8kB1/SCtkfMPSex5VLEVuy8cJssOyMQHoapsfOv35Uje1RFpCUgD+AH+JYzEQsPb6DMc4+VDaCZZrv7LSCmD0CYPPfFYvubUBthCyBz+R/rjl8IOOYpYACv669R7nZrwbvhJ13Q0wyNp79eojE83DCxZ42pfeSflY8GtQyHjJZ1yoXZwikMkGVAUQZcrtZ39t+rLkYpz/+fbTQ+w+4vYoJTmFSyh2BztrveqwyMR2sYWfhhlTgfYxSAky+HlVPgamQOFwRdNlB1f0i02l/eljEOSrPQnfJavtUQqLXUqxgBYSlQZmBgL42R8t+z0HibcThDCCek2fy9HVJVKhDs0iJO0yWWpybdoK3bOBjhUiT8HpiCHW5l9g860rUgkYUTSvHlD1+fxjgpLQOSHbWFIIMgiSYBoOmLhmTU/K5tn/MF95BQ1YUYH69E1A0jHDNT2bAwaQOSBlUs556arRIjTXXScFJUuYzVQBdSXbKTfMjTiuF8ktdMEoohXnuZgwPPwxX3WU/IF9dcqBHHFcdl6hFm1cxRpdiEU2I/jDSaLehritA6QiDN8xRYxIs+VpqekH6h3JK4qm2SQZGjcxPa8GDZu4MNcFh7e+Tu0vAagaSJRC0Bvo0eM0D6QiXZqi+bxgjKze0cSJp2m5PbzOc04is1mSARmbRv6OGHUJUT7UwKcemVl7LAyPkBM0voOQEzrVaaCMPg6V0jtcxb1c6ONApW/QS6xVz4K+NZVOWQMpVvLAg03CcxoCf68r5LcCmHvvYFB/QVbQrp5585Vne+dqXHyYdohrLljE6c3caf3gWrTYhxL0adOHbN0/VbjuSS9Sooy4fL6FDIVUWqUpxW+X4UBU8Ul5LSj0H5dq6ZBwK561jkIhKFuoufNJvNHLhIShWWd8UpuMVDz4j8b3VFo9fA0yZWcg2ZFUA5OsAbWI30zKtP3Sx+b3hQp2EqUxdCCylIWf+W8+XN04N7dIWI2FCBjjsSZ9ZIuSdgK/7Ng8Vbe8eJBW/BKw00ZQag0OEVRDa4Jf2/VPC/+Qc0ZvXjKTCHr98NQNseCct3hQWP33f8A6TthyIP8XzdrtlZo8PijWOK01CHv8wX8Q7fKr7HgV+dnHNBC1GU/cmjKzC/Lrp98x0Pt8+yD987Z/OmIiF04Ys+wFzPk3eXEI7kOV4gxqBEfoLw6oiw+JekSXN2um5Wy/ARz92kkrl6GOcBepRCZg+UkLJssaW5ibGTbKUc0gtsykwCry9446Wdfjr1TB2PwDrNKPVnN0oGgMOnY86h1SuFhiQQNRZKYzo1tZtSgKxA0L5nacasFTM0WOcMnqbYyh+CAdc9prmm7VgzGPQEujC6CDgd9ZzkZe+Rri8Vj+yjal6KMWyu+tE2iAJwE5LLpOTiwzILib98G7QYKNsGSuMVS4OIH10o9ca1XGelP97Azcc/EVctPeUUB7/twIrJihCqzfncZg/Z1rmFMm9JZmF1GCcNwl3522O3lz4LJnmO5winwaXOH9xNa+MvtkTapMzrsrLVoJbok0YBokbq51GxY2fCt7i7edQvlyI832b3wnt8HcTXxF10aSnk+/D9tH+Jb2uGfrT/qrTj6oNnA3/vAcu+/dSgZnQTK7YvmhboFPvGXBu9d+pnxwIvcdSJCWp/i3IS1uo9zPT53K3wugbd0MYwVOd8t2x1utiGPZwgnwK8IuhzqqKaAlIGMUDh+O9E01QXGMXHZUUmhKOosZ4Zfs91siXBrNb7mmQQzIAVndl6uZPGe1VeyUqZYKXhJdkkA7zX0cLY82Uk07++RWBc9CivKiSfUcK/LTzM8Hk3lsARlCnv/7G5AyEh30YLO2aEd1LeVQE4v5Fwjp1cqgJQ60LVpzOqi3VOH5w4HKPguRNbwS2Abh1+4YuxhlNzP1Dsb9TjDY1Z8N7TVx4vGW9RGUJnpSTWQUuGNSKwY6BcPeBDE1gJ2o1IVZtR2Y8ezWEikL496AEyfm/Ofri+2MsA553i0ElHaT8B91Fot1hJDSlcO4SzHgcDQTPbEalg5r3b75yVz464duJ0JVpo8hWk6q0XmT526GLM8N2NgloL9WdwfP1nUYKav1oDEnlTC1Lc/yAtBXZxQIy8dv7YNuIVrxyhJcTNkoBdebkEntye/XuTK4ZyUDwJSsb40s6OPhm3NJJNJ4Ya/f+PnvGUxAniafX2zCc2YdcWet+yp8ccmYtzwDV7qTM8dLM8DIuMOHyVRuPTt/C2a4w/lzDTR2JEP4jRhlYeSw5VwdUux7Wq7X19KhclYTX3Dku/pXczgzNfCBtSkUOU26sCg/KX4ih4xK46edhM733Z5y4TX9/yDfre+qZFxvus6Ov1YlO4PfoqQqXQull0aBlbeClxO2i03b2JEw3rQy6Be2SMZGnP3b/HkTjws8UukJVSucNbVxzdFuHOzWIXDPWIZQW5BpFkUcwVhOVPoMiOWt8EK/L1Q4IwUD9y86i/MKXmUjVP7CuP+zKZLFpgIa/1Ycjkjin7L4Dp8c5gD673ZvJJqKroFpYmQmE8/7RLxqJ2A6AJsbqCicFdB40Girz1CZTR4A8n00sEtNm/G/nz435NswFXLK9j21JfB9d7gzj70IFMT3+spyQ5y58Aswqs8dC9ORX6fibClOQrLzVhmqYVq3Q6cGrzZgmAHodGflSNhL42Do8FJH+/KuvPysTARkI9zLf4dmxhdljYRmR5pMtyXD/YM5B1BdXrpFvONRXkE/Lh53jtgD3r0jF8g00ZYKO3WWpI3qiyDnrZleF/AxOSnNOVbW/RZcbqP2+PnW+GytVerEv8AYq83b3izQCwFKIsajp8C/dxCKnrkNS0bjQfveN9crjI9VTjhFbzE18OyIe0aykCq473PNLWVy68pv6459TpX1XYbqXqtSzG37KnAJL9LksJPINmGuqXreXTkeLUOVvSLjWp8nRYED9UJ9mVTJaW9QXfZ+nphBf17cQLGRMqRPbBvwKzuKOgV2cFC3PMl4fUV8D9HCWKXMRNdnXkNiEexqeQucRvxM+ENGCqwWcYulrrc9C2miXnmhVf3xn9qLtErocsAqN/zOHhyt+oEgS2jDwjok2SSHN7BZlHCJeSG2rHU5OePqSAsUZgYKeyX/xs3wajA5MOdjAfuXUsjcPLEorIqbobwylxO8JsSWvUD+LrdKX5F9YiTVDkgEU+AMu3rZpvNiZoN7L/I1AX1S1U3N4F6QJxuHiZ5asp6jZWJJEB8LVy5mZYxYtuw87HEJdWPGJYc3y1BAD2Y34aSrKgxEk+644s4J+mc5xhGv6I3ykEZFi/JwgDlrcWJymejmUpebbLZoQH8KlIAV2Ge5IaPS8yQuMl3P8Gh/bsi3EzgcMbvwef130I4+25yWQ6qh+BEhb1gPHLkC2vX8shPQ4xhPQMG9XQjgWWZipMBODe+1tTSr8+SGRjZYXW7zq0tjPLwW5yvrYZ1oZeM14JUCAJHcQ3m7lMhxqs1hkXCpu5HjCUDbS41mBDOBLEQikTvCTOx8K3BZhc/Ldih+r1nFXCbq6wtUi0F2pukM1bUAuHESnSOFCKo+WeVtO2xR1j+IYtE+YJwN47MXKxya56bnQ/p4SlUifp2IoqtQbbtndtsxkpdf3JD6mlY7xD7cQj/oLQPiA0WbdnIKMfNDUggWvuBc8ISwwZrf/dj3lFjj1URLjt6yafC3C1g0G0FEu8kY/U3cQJvjPJwZXjsW+yV4U0KqefdKugo6+bGwQMVAjiIPVlv+XhqS17Jku/lR8ZGRl52taYQT07HJKCUlG++QoF7vbAjvuoQmCzW1e2mIbaDXTPn6EpZKHW8i849U2bPJHwRwQWi8gEv4pAOYEHwdzV0CoP5YLq10PiYy8xKK21F7/WhIpvVZHDAal1rVcVTKjhFuy/hLip0ct5qv8ReJG09N1CJY/2q+gmk4/IJH3u91ggvOQAD0VLe1MnVRevCfwK1Km3j3ifRnOgEl2LlaSVXpSGX2hh+b4Tky94O0ZBGxYVmhZ0e0DoMvmGE78kyoau+yHIMQLpA0i31NG4So2DR/Q3aG5YVN9AJUiSSXegznHFyA2+cctyeUb9/ZpnfiEOUcrskEEOwSbbd2KT9RxXsKc5vczf9GRJbBl2A/x7Kd/Vxx9pwrUwVcfnG4CDp2RhC7xy4PI/Uj+gYkt9ku80cy+LPw3WKBvt58sunfX25wie1TB7Ln7nxu1hChDigLWEWRAyD5ghVZfdLREt9Amg0+VqpzfhOYvoqRiMgtnDDl70lvXuivAAGTZfsEb4MCMx1el57ZrL7J8wHw1mh3LrixdVXqgM/SiVOAfI0nAxO3n7+ebPbBwGrqiiQA2+7OScta091usuXaBXqjEbvKqeRiWYR05f3k5LkmtV94BI2vVMg2qQSxlS8j5q8mTgOeGUsPm9BDW4cETwKNUcomK7UK6L8mnRaUaj35KZHvJMWIPMuOAWTZ5j4D3GukkwUEzG06Fs964ZsX9rN70sxmXb3vOB1P4Tmf4hPUJJyPojKRQ6JICR+NXj/BHPiT8zsfqiEBpcTwABqKmU5x3K4Xwox5V9/KuKgvvsq6Kbn6rbhU1xiljn0L2txCx/TvCHQqE89dGZx/hovW0q3BO4POBPlHHQjPba47nxGX9s7+9yT1MLdYwuAv7j+/VkzfNuv3wF4QRQie+Nj4y/TmpnKxvmYqmq/HqenqmPi3+Ga11hSOUCzIZyBkNk+sx6MJFivY/BjteKryUTXf+2nZg0I7Pm8qrG90YfOYtqSteVfg7C3tQC1gU9k3dQQ9x99Zqnjde5g3zHIGZDT3G8byt9CY+6vayqKVbEWbd1Tk0J51fb0kKrLDbT0rUMyNaoZMV9Ty+LmfcWaZybFbVzSYurLEEUqsJfzao+HZSXSdnYVWUKVuycJzBG++1lDVFgvvje89mBXpPsSHAHfYcL3xsxMwGOqoHrEIRNFdmu9si/93VZjsM3rXZjOgbOhf1l1HDmpKSM5GH0CHo1ZmZ00N14FMSw07WqFmKTfsDtCYOhRr01RpEYQsF6VCC7lsO3k8zXD5XMe//XmsZyx05AYd3r7joWLJLaCTbRgBq5iiHXbg/9x/ottBBtAAE68GyqS6M3ZOedpFp6V0g2BPrad44VnX2NAIzM17CGXagCHhE9AWShROXtheqcUe9FYn/+GN6B1HWVrXfMWqjLct1VyDpeG6a5jaIXMfHsS2EMgMMm9mRZT75CvYz2tGvAAHi4iCGwUuQ3nW86mdjJTkpDufGFscZMVDSNWw+0ONx77XIfl9hoD1ptWWICtAhaVQA4vIUTG4ICoBMUPuL/Udckn8yRW31il7H5UyarxM8j9u/pLwgUi1EsB0JNB5IkthcmUdoh/zsURDc4FOjQA4FHdwHCIi7ZUd6DW2K8A1o4DvzlFmjzedc+dNAeLQA3C8/IiZM9eusuUYl5RBvqJgdr43NnDOc8LEDZQEO/3NzDQujFlsjqS9rje2jIkdKTlhlZtFghtdE9mev5C8vAD9k5XMKk3J9oO7UsgUHZXD8+ff5V/ZHwjUNLpRGSmYnE1V9sHY3y98i8rdH7vR30nDSGy/IUM1Zd6kB5JPpxyKCeWQ4PkmSs2ieKtw57xgOSBJ4rXmKjaKehjTeM2JnBo6cmIpw6QwQIVsNlK8GvT88iiQEXOfJDPYZA+yw18TjBHoh7wxjWLaB90EQQgnkClMgs9p4Kz4a5tVvdHvA3+9tEuaIbUZduKAXYfRhjKxGxEkzgr2XHiCiJbx9owyqfTmP3OlbNc/UK+t5/HODJUJE2A/eDLj//A+eq1+N/9QHymVojZiz3rUcOLSMsVwE6C+w0/p0DU8ST6qgFqwF1Ac/w3CEk0Ni8sHTTW1/3jFVgSKeEm7RYZbMEfLI4mk1hxUDau3vzYvG3lwg+oPJrdUvbDol01Ggk+VLVi+2/xttrw5i5fo8fGtxnGyBfWXCoqrBiaiFunhFWgudchBeUcQyS/MJQfVt2Kf2C5ywOnK3Q6z3UH9zXHuaaI2KtNtXvdEkzfRg3xdATt0yOpClKKd2qFLcDGpHtvLzZhLC7ukTnV/MSyiA3F/zLoTumf1c4SfBHrftwmew1DBVO0mNcnSYerW2iizD+TsAoxi0qqGH4BfyINcveJswEiUchPu/K9k089/Py/dfuSPMEqErDmUkvnp76oa8r885GrAtagM/I4le0KAXMyc2wglBwUPMn5J8QcpsucsysS3emb832BFLBQhi6VMDqahU839zsulTTyv3hxXSQbvb1xprx9T9GMbUtD9uo+d+Ysfuh13/6f9JmomrKdAU+lrOPMAGN4VqgwHoeILT8o49UP08SQ0Abf12JepQjEh+OtfxEL1RKLerHGOAHfdH/CL1TcRkoRUBXA76PwnoQb6r6mq/GgamLCR5GjEJg5VKhisni3rgpIYFizHHBxwyYylt6p2mcAARZoMDwWgA26ZONWT09DQV0xQnUIm/EznPgx8JB3cb8ogYX/yoJ10gcGwUMYG5tjAtZ5YD0Zvphbv5bcXqtKqC3r5+V7tmtZnWci7m8NXKxSPYJb2TsEhc8Xfty/iChdo3nvX4e7ybxlKGOoZcUYbedx0qd/OoYB/ZS5qSxU25xVRXvIpfgclofmV/lDXC+kse8PGWC3N/EpobYc+6rtxQKUP5VUf2HCMWjQdiRorIBGjlwpopAiTAjbKL+bsgsvloFqVLOYbbpuLuhmAldD4KNyF7Cudp5jUHXzc0zgTF48a/S9as6iI/GswNI1yhESBN4QlUuBbJzEFdBWGv58nFzTBSmsju4YkR1o8Dkv1oSkH9TkMiTlYB81TpwhQN5YTUBFF0bH7TAMu1y1oLKZcWwa8vfYovAZvGNn8PrQJjIveWbTMZPuoi5iYQFBw+I3iOR+IrJFY0Yo8EwDdMncxZJdXuFKmzpFcu1ALTNrGG8l6pg3D1u6nCRZiCwTqYcwjaB73bQxq/aFR8M65bNPwSo+G8nLYXAVF8PF339GvdDs+piJQmfON8aTyuObjjG/h3a7ZF7MqX+60H+JlJoRJQPP1HuHc1gEgM782LZA9c9NGBBp3rI10SEpIOK0Sed7C/3WZNsUhKthNJ/7zRxVNSIkQGeFfz42TBzUxp+LGERrIrV7FQbKWToGizUOJVGMlHHSKM5sc/kXwHV3NGEDTvkDEo/Rd+eGtTxMq+lMnVcnGfwgUGq/DTQgNmhWbwZ7f2yaTe3t5lpYlBGMJKqvooZ2miGOAWxr2Gh0IKQXOCuYAqKXYPxfprpfFJMNzQ40jJuaS4KK349OdExgT/nNFp3wWWbx0PZlKJp9PKD9KFnNPtOKo89ySdAAYr+RpKVLZamM41yDHxhkiYqzNH+0qNJb7s3xUscMtsGS7iWcC4mvEVA+2Rw813NVxzIqMmO3cDoUgBm+ecSvQ9PDN1uO31UUrT9HAlSvyGc9lJVLey8e8lKHE3cNJUAbp2159aCB2UfdWpBjQ/Swz0OcvIRVxdEnetFqk0RnCn8Wm2MgsNsIliO3aJ77V2815Ssbs6hfOyqLc7TtUkjVUTHO8mzN8VD3fMczGZUzCgX8V3C1XGwbHZwYY+L7YxGTypWN6mFDaoqFT8zq6+cq/MB3TMSPRODWKM251lQ+MbEl0QCslLuhJZd5Z0//sNc/FveabujkhQjIMhpBs08lyMfzzFMz/UxojDOuVZ4n9wZTR40+XuXtSBfp8DSqu9Xk0c+/eiuO+yKbt1yv4OEXaVvaAVhvV6xS837pIdVuLDhvaaXYh/YQiPN9dVLqcplM0B0RTS35SmgGwy047Zk2WK7uHDPuU7T2mOc3njfTlpbcs1l/1XC8c0xfcXdz+PYARDs2Q2kGwo5esvaucC6Q37IgFJWFrUMCkQD7NtzA0LM5dS5hX86Z3OrgItStVrQ3fy0ikn8+/tAQcEvFKjpj6cJwv+k/+270F1MkHZtmw+f2MEFXp8/rYJE0GepGC5d1CWx8wqRPwVthLJ8ivcd2MBnklmuMyPQpN96bJzMyqywPEyH0RkC63Hr4liAc8cPkwTZU0mkFJ/s88LNmDeB3qwQGyYAkxYa+RASIa8fjNNRndNtNkWEVR5GvsiZQU5A2y93MfDUGENotLDBqWKRaMXtsgNqSFzIqXWBXdZyz8iSQHhiersClzHsgJbtgliH9w4RhgtifBb1xsFOJHAoAdppFZHfqeIGg7/3MxbWVTQmgeCB5MKjiIF2qk3KZ15lhq7qnCYV2osZnuGvlQcnMyglCGbu22II5QN814OYjXuJhuU4XJR5sfSokiB8fG/ZcxX29n8toxxtO5Zw4rTj6n1IBPJspNUelO94LIXy5v5kBGiP7rqU7DkVOYqMfQ7zqMLrWkQ8OtfHwmJjlIPk5gj0L2M/zKZfuhDzhH4zGfDpU7/jiKHTCGLWK9esz6L/zD2kI0RU0S/tKj6EM+pxinxVrtSKnqapVadovp+R48MIgw4St5kJySfjAxywjjSeOmC4oOEaVL6N8uhvoVwslxlHhdGFmsCwI1T+riwsKUe5bOalmBh86aOa3W1k1lluimIHphVC14ghEZjMOxOGYhUIn3APNNcaRt+YjtmNc5VxZ9gPcuoLwGgMDpGE2atJIDd2Id14MTmUgvbF0GqKtIMXmwzOUSlAadHek49pKw3WiiPyIsU/AzEenWIwxlUW5EPHBEM0Y3HquhuF0PZsNEpXZLpVSa/ywcxPtbcDKyiw7P0VR0lDi4pkGNyQUdOPvUwUU+pkrWAltH1usBeQjyT5ZvYH//dCUxRZjB+VjX1CoxSCB5RQyl6XALSc47uDkOwTtpsYvYs+9lMNrC7fExJmklyNE/zm3szD7Fp0zH3ZgrXrIGBuyyEiJGF6+/mCx2t+eyTA7ZE2rGWK3UNuS6YGLxkG9ylLIdwpBeaSxP7DOUXLKgbR5C/npmTi0KLuy+nvdtmomwGhjFk2lOduFPsooSlMqR7qU/hEdx3RTKUuKda5jvHktCWuZ89+58PTJZJS42An5EfbIi8xAmmnLH7coqCcTmwY4NEqrys/hMe0YRckK8Y0C7L1O9NR1MMY46uQ4kf/lLf9J+s+JFY9f4mOZGwc70NP0DGZ6gRUF/NhsuWvFZjC1OYVwIqA2uFcUvyHHtrUvO69BvhiJm2DEfzKozRadCgu0GIfOOp4iocnreSQAxIGLQkJrsMesXS/ZhdkacXwGfQAE5zHWOor6tGKO+DoaE954/aEzhOXHzW0kTQfX8a4VY6+/Q4H18sfSJDQa40RB0ar2qiR1NffyXtsIC4OMbOYUbqFlni4pwqP40U54oYL/cbWWzWinrbdhQzvvi93lSZg7zcqqRmyydG8mxiDGIC2dUO0l4nX423/aR6iFCIfvUs9FyEOKqfaEDSoGezq59+RVwshDCPJ7a7EkF8wqGzb1XoC8E/wnvBiK7sxxueCx539hL2sH5jdqZljohdBwXQ+kl6RLDBFcFSRuikhAOOjhL9gtN7M6WTxK/JgMxb8s43F9q5XSzamQqpWVOrdLTFs/4uillHqJkLT+Qo6dr64MEv3pORkST4Sie2QtYJn6CtAMmlWky0ODzz6whTSPhgvi75kVtAH5ihn3+09tDNKo25XsupPSn8brH+J2s8jlkJEG+V7yhbkDhiXGrWV3dXHpMHOVls+RDJ09DDcINyxLEQ7+wIZJ/BLBwiDAoMVgFgCzQO0gcgF4kY9LIQ5LprftBijWavIqBDJ8OSa1V5IhrkQF1H48LpIcG5LA/wSepninYBPCsLHBc8JAo4orsTsXfxQWyOuVi3oAe15B/DWoa8jWRvcljKv6bZwd1f2UzP+/r7XwPxQOrfzRmA5qdeVqEfOwmgIgN6jPUhVk8zEVwMM2bsDquwi65BDNVjVknBrxtw+qyiaaCtmM5GzRjdogLQ7PSQXW7hw5c+kIQePW2OUmbJ0QmfoOG4B53vVwdgjBDrVK99zsgYEPwFLmGuVwF4BqWD78lX7hKxPDcPp/AGUlPAARSvLezMeUoXWyBIQC0YLSQkxJ4wuKNcqPOTbZ+UyJPJkyoHfzDigUS4pPCg7Z8tBYPQQqLdBrpcKEep14BdQCd5Gxm5dHIDRogX0PXfuN5hFNyd9wAoqunEPpUKeB9wgqiS+rHG/q3fg7Kau8ss+8xf91iExw8zQY+iSRVgBqwx+ati+/phQ1IWQ1sAIYKYWyEMS5zyagAg8NSaWs7U0gLnzCbV31KFAC/8Sy0f2OqqEucZ5EKIVj1psh/414mefxiHAdFvooTlnPLMxb/8ytoV/MY2bDn8+t/48BYoBdHD3ifU/e52p/15v8sNjSVQOvhCNJv7YCVGuzOEQjlhEnhRiJVv4VqKwQ/2TwSiOvcR6MfLi43IjwLGjpWRh36GASHasTVUInUaopmgANsCtC34mweuDc3oxzlne1xgE6vZbblHPGs6sCv7Qb+tvTcH+sbt9NGUTpstIU88+v4WhOzbkTZhi0IQ91+viuW1z5DLBR+Pt7SOaF5mBVh7KNGymoVe8/19qMDXfEqt5H8zAbWCLlrS+VrCBbk2uv1+F97MSJvKzG1warpXhwNTiK+7IBK5w5aj4GWVTbpVAqzvQX4zQzPvliFSOOBC6ZV65T3fuHJxr7wuikqaMH2ii8EsoUT+z/XDjqu/UFVZvxfklU9Qrn9uw5Tdw8xHdPXtBw/e072++SvJFBfGGAmFSRK12ltTllX7pKgzYd8VU5w+V+FNVW4EtvSNWabeVEEGJvXJYAQA4BK4NaTU7HiBbyDx7aIrMo3c0prNt5RqgrAoh4vR6S37PSp1lo5CDzSFy+8exJfGyneGb08qFvpcJSi+lOzVrEqHH3wd7ZWmmxGO1kRm6qzF8kewVCvNB9D/TmBJI25xCm677LUdqsOUw3LQzq5JETrEg5rzW8fvhpsjQMM0fNA1/4e35UqJicf5PKIUcrqR251VJdAKSWYo/L638B0TuyOlMMInSFRpzPEeI4t4wR6Et96Ziwyiujllzzdq5bGsadiUoLgCQ3S8XlG/1CF7K4YMYaUEnmGaDdKMufvBV6EoLPzQGZhe+uJ9c1YaDUT1BYz6UzNvKrdyVtCAwtJqn542iyOrrWBIZp7CKDeCrGdxYVHc0Hw1gnbx1wP8dcDZhRlM+cMpXaPbrYi1XrW5hh6veGUuNpZq6XmkCtgNGctdUMLJgR2D7IwdV2KrudbsOjN2E7ryyBcXXQMcomO1FFDQwBAIlvl9AnqjKKfjxWmTXayxKBEFf171FEUM6GxDlYsst9TlE+YIWyzZ6/MYYuUjzhqLOJtaLltVXbd1eQ+86pZsrhdN9loak1a4vlxLLP4wU0NcNOHg7b2TPWd+oWEFe9zuqyz4nZ5R5HtyTDdZkyjxaozVW2QETMQjKw5vFA3BZedUq/RNl/bk57lco3inDbgxKVJxp2JA0qolj6ebfTLd4OjbNuqxqi/UeCypDp7v/QzU0y2c25jgznNhhvlhDw9V6BhGKLewDpBLKaOqbg4/izPVl6oB06teSXh2l5yS6VXldVBb6dpMtwE2bOKAJSLqgepr/22TR1xZMfnBWb/y3VCIjuV46GkV84H7hZp1dsoo9709C/WzB1d4OwxpoJc3ZHx3H/QmbhVbTDL2QxSYkqDIDGML2aQbGZcPZ4K3iOdTwUlKdND+jT9F5H+4nId38NEQ0gxFe0EBepqC2c3oxc9fNzIY9UYAJTPT4lo8iHHQdNgORkY4Pp/V1mlsuMzAlKjxNJT9h9nu2nqs1gygRtYGVzCF89AdEtYUYZNdoe3z01AwLSKe5c/IqRCZd90qyTB7R3zBLs+kgs4Mq22Yoorx9D6MpGxqw9BbkXfNudQBNh5r2e9LDWjQmfgb0AaTtgXl1htZN65UZ+G28mCd/yD+8ZfqpotthBepjfr4uGVeiY1i86b78zVGNaSCSSbzzhfCikoNxBRjCN4eKxAGF2MlkpS4yEzulqZp1x3TXd1YA0M7G+7N/lwr57baE0g6EWK+vX4/I511NbNjMF8qEI6sfahOHgr2dV0OOrfxDk8h47x0S0IiryT1/SsR9dJVUCaNXlCcqAEaRl4L8bzdQl6j+u3Wy+WKw6v57n6NcsQ4OwBBNFVhjA5U/jlFPCetLXvC61ZstqRV31nwJwMHVkbnW9GQUBzp5jsFrl/WjhfhGExBA+i8/8/UHENZIzouAhtb8mXKQlFHoq5Pto7quEZPaRLaO8EdD/tsgPgrRDTUDoERj0jko6L+adVXcgiiEVxRMw3WuDWXpmEIstgA5RW+1W28WeBjSO7cYhFNxcSjmd1FDiApbYNE+CQg6uXMz8JbCKuEEUltSASKPwfnI4tqHEUe1zXAlsDJ1uWSiQAhW59k9kJf5mn/TT+62acTxHIOQSqQSH+fpPzuwCiW2uEqubcMSrNACvPZVuggmGT/UfYc3mq4TA0KWGMLJV47JiZzYh1X1iyfKrorHMl8OEcKYbds0WHY8j4/IKWaLwWwFEUQShpOYxti8cqDFX7cARpE54ejbjL+YjuDLPwRHCNS2gefkgE1fLn5NfeNAiNxeM39x70O/xfdeTKeSV1ZUwtdvKU9uinFz6Wyb+p7vpRQJ5lEHmegATj7pHuAbGeLRvnt1CRJMTZb8dmDRNOzPYcOvjfO+ogRiavv/teCtSHA/BlMMHSKCGHBfbnnXCsqjXPBECR/wDPM2ZI/WGqGnwyKI0+zn7Y4wKPRyReHUVZdBXebrnYYglQNJHO3VGhBwzFXPt5yklS5UH+FecS1lgjcsYNT67tk+88CoMQ1hDS+l/hzzePwGKjysHb+3X5OLVEFv55z4MuxZlGRV7qfRvxGRinwB5oEj3EiSPeUVg0UkDebgIzbug4LUg9ba36bwn1nEF9KOv86n56nX90U3M1CMwMHuX13qqsC5Jp9eOD2CLT87sBHkXDPKvVDSuPVJc9LNGp9zSd0DXuuXFZ3Qm8DBlbeboTyd2tS3Jk4Fo8ijixFDWqSWzO4Vy8y4PhSlA58wFxjKUnAjP6HYSre8K3hkbta4nsv/Kk0Fr+x/G9ZfKEsRgz8V35G+6xmRJmDpuguAup3IsK+lkzPnVDB3d1yh9+9BuGJd8X4xNLFra9Y5NzpS6VmkG/Kn4vDa0iK54PsrHVAhBL3IcuUhL5B49QuTCB7Vh2VaFvaETq5j7E1F5A7m3owjCezbwT2ORllmDSM1YNUv7CW9hdCg7/Z6Qfv3SvIZgnmOQFEXAQ5v2biqBLjvDtA8Y4DsQVwNKrnd2Di3kOiwg+vnjgwo2UoxD2+ZfBtfSWYjKp3Ypn3GOshCtdUPmhOvhjyrPcOPqCzP5zukxM+O6D86y47RRjsMwZ+5sFWs0kq757R/Tu+TKjon9VDSrEFpRnRrkScULa4r5yfzoN66kE2UaO4QtKi54tL7/wfWuYHFLqynO8fJ/zJ8e7MdDr9vLUUG/w8aXgkyIUnwSO6/6WXD/mCV7vNPyNmrtnVhYPAux8tKXaJKpUBPSAQR+2BMQD6gsZrcznQ0aHU8lHofK3DjdwxV5fk7n5cPst4wxy67OgJag4ouIORospjjaKcWJ0E1ta8kabWYRGR8Oghomn7ahugV2ArqQZQl6AEHTSZsKibijVqG+25wClo4/6np/fQzfTEq8iv9JTXnbBJSHL1pxhI8OYn0QAnsrryNqRlFxGjKQe5XaF9Nj05K3iOSw4lRuOzOrNaIZYn61iaZ89Ve4OGu7pP8Rlkc5Rt9Y8dndV5kIA+euPZyGAQyfdew27Y8KlIhy569xqR0CqweVhrVFYxXt+xXD0xaYSo3a+qFIVznvEiaA3HDy11EuEBdf8aUFAhZM0Km8M6d3Fi13ek56k456vaSlCR6j3IOjtLbCN1u4fOC8md+88x64GbyKhXPPaN1QG5eKEyprw61E5IF0WDk7icmYOk0rlaeaNA2pyi9jXwc4PFyrjOZgGyCEETnJulBjTNbFaG3h//nfvOF9yuyE0syXf0nfxPX0dptLQM5eSPyCvXVc+/asT8nHB1fFmCSPe3mpla1it57O4TI/Ifmznys/HrZ5n2nN3WkOvXE06adiT+sclBYgiesvsZeYJewB94gOcXftXRONLPzuHEfpBstr+xPHeQCP66Kf5O6C2AuT8Dri5ngwXt4XBF215+BYuYQIkoToFUel17kIMPXmLmQW/0ezM2q/z+YuqZr3SZFRNh4g0ZRmyARq9hF9JHUlojJTnNenvtd/EaJNGPLw5kZRdPRKQqwhTyhXnjQklSuoeEtcGugG5vAlzzrd9gOlLPIbbzNSbBDWgB/mKy5c+S6a25TsU890z++bxA8IT12A4znh/x8wryuO1TpKBdbgRXPb8bvZlsZflZcwjG77ofofRA9nIiUZg46r4FHgFjbOlbvwJ2KHCOUPAZF7mUfZYxJjccBo+ZEPJ0ZCyxKngBDoQv0AQ23Yc6xxI6hmjaX18YDmJBAu7YLTu/n8bCYdfq6R6iQSIrlHDPMqyCJwFyw1pub4rVqbt0Uy/qE2jhrKxQAerNpwq5kiYfq5sH9Am8q29+tv4eF9VYcVH0+jREjawpc635lyIbjm7x5Xh0Zj00rtwk+/fjlNulf+h5nb1lS00lazgHczFpoeOdwsote9QxJehoM6kV4mSVAP+a+t8+HbYUzI5Spv/tLGqsARYEs9909udqHHVnJMsF0lRtSwa8FuhaGY9GVrIsleCu/jJc37NPoJJQ3TKfqM/sD7RZSBCh1oThE6zoHlaWBxE5RmcZY5x6pELHzpqDm7Fbw16HEpxh37mVbjilgHJF60yCFZxVOSUnRCFYF/nOAeBm2tOcvxvbopAqA65h3MU0OjM4lI99L/5DzhEoXpE5y1P5bLv6IO78cMzHLghxAsPsm7Gx+3sDdTCyHmqcv1prXnZ5dNIPrjWb8PVsJwckf2b87Uv8c9VvVF9z08G+kNruxbDXtBRoyxE74RwTK3Wf3Nd/ReEfLELqka5aJ16dsFSTFP+okuEDgK2EGQ3LkDAB/bbO7ysSFQFyXZWGBHPDcEhXL36hGN/dmREEruqyjiWBCEcs6DVHhQLlr/NvG6RAsTk/4VRFKLoU/Qa6/1qnjh3t6BzPxmtXkNbwTcL1IYAbQ5hc2e+4J5jeol/aERlCWdD+BOlG/EdxyIOy2xYFr59BVmAV5rT5xnD3vr61N9V9VEIMpy7whvl4zlPRKv7AOjGyOFt/sJsgI2ps+fK+9v6maI2I6ADFb2EqqPhtsPbX0KjILTA3v3DPqmvKI9T9XvHCGSdcWEnngMtSnNfAjfMp8RxFUm8oKwjvHpDqyRDDB0XX0Mdd5hhsAxrr6jVwUSHCpBdLSKAI6mDn0TxibLGcHTbEfqkutQj1//KvCMDWOB2y5tKbD01T0kp7TyUmnf3O6gluZCmv0XfoFDeUqBJjIi+yVHNr7DsjsVlgPZKOZlKaPKNYAOFP856O0MWZQxyMVIckTtABVYpeyKtYgd+mNxA5AL0h/WUSXUn+m3VZfGH8qBSYUC4VBLtpgXRfomWRcOZx7XVHck7AwL0LwHDvQJ9adqyh3GkeaCdC7G916QBFqEOwDdSetGaQMkg0N2Lt+l2GFvaknTf/w2DIkZvyehg0sFYq+kIbKcEIs5qSZlUdTG6ksWt67rNPQoeCYOycDqsIFsLMmpTi2yGRk5048qJ+nSSvXKd1E4YXDjOc96CELLBy3J0OO95GmANSb0kbvOMiLkHoWpvfcH63C5rOwifJq/1hp3rhyuT+z5hyBz8XXQUPbfElXf9VMrWfpBZnTkhg1pigM1nwJhfcYEpIeh7cPfeWdT2RwUrIswmLhCGqwSfJ8/nM/WqBBGzL9PlE+KEiwJygqp139OeZ4f5ZIkLXuBvKtZVhKyTz/3a5rnks9y+PSzdh/uBUXmnNZ/lVdM5N81fe/h4AuP7faBT7rDLXC1fKrH29RkGAmDKtBEY3VOkztgGiBbA6sL785fDmo61cokAJOd5fsSSFkd4pUHuxZyRiIMtBjC5e08wF6tySgUFv+06zx0y9hRl4ODnXZ0sT+T97ckrHR/pZpYXwJaXinaXPn3owotMSuKLNErYFfycuyY0O+xSxZWdD2ZvkEyRH6cNSTHcaiGu/5oek7WwEgnKYiXvCDYg1yNIBQbHcX/72l8l6LbGxoY0jDY7bjIED31a6WRZp7G0MoIPFCzcc30AhAhWcHfWp9/CrqxcL+yHL9CrvqCTVliTvFtNidHqw36FD6aPUv8YJJJ9BMOLtXzoEVvpLi9McbTUv5fqoQN+Qw3pD1X0I+aE+oqDqC+xg0G4TsrgEA1uY80JwMtnBvhpTE3PnPtWhD3dO4q4otnq5ua++6U2eW03yOSczRGe+qon1zdY+3N4nYMvCs3mS5spnrzct8ylN6pUSDyjy8YMWq08X96HFolgLU0aqY96/6CXbs3NcZJ/T71HX0+jyhK8/86estmuNO8FUeZlMXHyJTvWpkaCLZAbCXcO4PoZcEh3kjgJUsFsoBb68//X2b3+4scjUrkllG68lnvKXJNs2sQnzGGI+IkIspvIyfEXdqFXXXO57g0Y29u/oqV59bYh2w67oW0gJ2rDsmkFDZeWBsjgsdbXzu83r6tgNcQR4Bo39DwlxRiJt/g1KaLjUlqwdhkZdlrJPsnpwZ8ov9yWMfycmp9kGTv5LKnK93LHf0OwTcfcNvxGka7ybUOTBmfUkw8bCpy79XftOU8pnoTHrwbdc6yEDRLPsCsvVOuDw4iPdob8xVyiqadKiyLAOlPYGjBVvnIG5wOzrxCCUfit5KLwyM2y5aE7sy3G3gc0mK/befNzab4+aArAa1GoUgRON7N9+o64R/kPutjdHu3+NjxzypEZD+dp2vxZc6o5SEO2IgsAE/IP3qnpLtXG9LFPgwzJ6rhwiD6Fd/ck++MHdV8gqFmPMqoXKupTbB42ts83+R5vGjRtJsQt0t+DUZyPulBnclyXmkD8pGpIxibmbIvX5kGgSzFiLv8tNgI7YxgUXlB49VIQ/8h3nrnreNKEUnaGWw+JRyWnXY0yq9+FJIukxqMJncRDGZ07nwOWqcoqqV64bQZor22DEWXDj6/rKpkZ5o10ixlEZrrHQaCVTwpODsY1qpg2GlUmXAeXast4rYTIk/7vNoB5YHS3/PpGLxApj+e1bKtx0TMsCO6R4IaclUQ73FH/CKqilnp4ewN5mulhfjilEjGZdDLWeGBxDaJDT5zVylzUoquCDkyYQuE0d5nWkI1RDdnwgOWiDWKpungBAGSU7OL45ct7pD4+cwxlTSZJ6zmB7+1VFY+70tXZmBTbkzpXZOlC4btvqVRF3hKbpbPGyL44HrwRiYzlipx2QHJZS3Ma+IqtNvvmSzqk7R8s2dyL0aOtwwYKkzLHQVyom7EV4Tv89fQdRF6Zks5hjU0T1yFQLAQHDP4vcIxCTMiXxiIUUkQ6kPpo6CkuptbpFNzKJTzeriNp15+e3t9ByVch5CvrRIKlJZWdK+wO+0zkG8ffyZUAop9gJFMsi91csH6S1n1qo98Giv+7Luyk7LeVAmkUWFwSc9NAeEFfVjEYbyM3Z75JRkQl3qfQgDNBxzBIKJ6/ZfUFqTwAyS/X9CRf9O624qkyqAYAz9kasmI0CuoLqD/ofNkS2pAqNqiooPVxNJ+wBFOC3J4m9PZQGbXPfWAWEKN3FF7g4C+qLK60fwH7Q++m/EFRynlo+E6N+pZkNah2p4gNvnCVc684d6bm1H9u9GDWwM8ove+os1gvIodmolTdF9bL8uaF1TUuo1kVpNR1ZuL9l99MvczFYTEJo6pdzCQQjsqk6/WO0hPu//9cT9r7ZHZqRJ8uWv4rZwU81cGGfrdkB08Lk7A3x2uRb4mQoAtQUIKTFe1OQWRfj+C7S0b6mvfTImoa4OMMLXfKq/Od1C2RZXTXACUpudLy1+gOADbIQmjZAvPgOhYDpXTINnMU/MOO31aT0IYOHZUo3okUhn2xRn2hjfzxjO5OtZFF0SuNA7X15VF8gX0r5a9UocDkYzvj5S9VeYm8wdzrWvIHp1evjuT5kHM9IDQfzLhcF76slzAz1mXIxJNJCCVPODfXVhElD8OSE2p4hbvl/QpQVhulzVzQlfnXVwXMsDwYlVr26g7mqIHE0K0wHaFKTI+vdn5jGnGU9sMG+76MxsIYBjqyvPxBcy0/GhZBpVNwIBnje6UX4/jdM1EV7rAjutajbuzKXQdnIB2UkQys7tJa2XB9NaHW4XORjwy9PLBbPhfRkfwybk2eUIcGacoAZOUvw7VSHACrghWNGYp7TERioxDA1SN0gL4Ab9i1g6DiiNbN32/xriV7qVfoyEsL+6pVupdwlNo9t39e6dV81ZC/5iuCoSYxx8g7nsQt+SWtvmhj9VWGGOJptia6P/eTNHBEUpdXncrncmxA8AGXgszqZ3Txrlv4EJ+u2rkst4X7Xk3RunZhzxX64kp1fAa5SyKZwHUSHMbT7SE9XQNjFRVeSyQ5V6J0rlCq7yUSbUnMdfPpT9EZkCwHMxHZO+o9uhoduOMaWP36PzHFPLLi3x0OQzRmOGtfwlZ9XyT6AFM46Tth4hm5iAFEIhcJEjX18/q4YCeOg0aYVu8hBBowgJCsitVeAXjBJWpWvrZ1T+dP4I9onZWClER/Pkmu1CrOlbqQGmQYq1JTJRCRbE0j6V34WmsHMQe9fcqyywr/888BWQuinDsf/cazAgYnvJMvVAygBaAVOUtqy/MEiq07rp1d/vvlLk+BSldQwzaaGZc4SZuyxZ5KdOWmfvOrjSG+Gq0nUzwPKy08fUfm19WZ5l48Rb569fWrK3038lMyKgCGxHLq/YnX5aEFsz0q87aTYwaW+7LQAz/3Rwj0sO6H7vxwJ2eBuKiOfn2TICcyCUxM1p/0e/2kMPv/VuQ8eMlxXFYnxBMWO4vsao3sjMfn9+h2baukvmRBsytGf9ZKauERqwTOVTiE3F7In8mofgB3fGWNAhbST9FURiFJ+6Pt4wknuF0APjMMndhen9VrbWbZan1ywVrAcqJiRxegfbFNLr8AIMxAP22+soYpTQDZkqxp0RgC3xVL8T9XBtL41F3/KTlE89XYT1O8uackfFVscFTfB4Dpb69D4J+RCNMTUydGLQsHOsKqvrJzjC+2/l3lvD3hc+ZgrW5zEWoUYxiFv7KsN44kSKUn4BAUNhkgmuINCC/RxRxclhcCsyY7Pqf5rRIk0WILpsChCbz6wDwjZY8F6lJBdbOVfHPf3oIIR0qBOALvoQ18rYTWjWLd2V4OOiyoNeqKUIU/58gX6bUNRKRFSsWcMPRYjgeMCX01CYNycj7nF+Q75lEMRhNv/UmvIEO9uMVCm5AtumiiUZ+NDwQ2dK+fdVVsOz+ETAtN4JYMkT6dgFryesxjf9eijZx1yXLaisAq/yub/I1b0msz/V2XBtFYf0Fzd2sn+pDVw5eALxHBZaGsrTODuJjb200a6FQP6ZR5ttAXY8k4+v4BYHmX8brVje4Ywu9FLWue86+ORIDYODp2tnyp8m9jjjYw46OXCNV4uUAWDmPnRSmg4JQRxZz+4q8rZeBW0m4IsmqMZoh4bdvasbU4brjjzn13wzoheIml6krbJ8yFmKkgUuvXUppCjaDn8Uqn6PCz2xQLYOfMx/QFLYiaa5hoItxvjjv0n6VGvCQhzpvEeZeuhHWBPwV+lxJ9ynAz2BOuvmy+ZDD3ZxqLB6+qJOFn3ORyjnwXxX/cU5CZG/UzQ00E5/D8M4U4OcZLqntOXzJPZvvcfqQ2qI7wzAozr8Y+bG36B3EQRicVAyqPGJqDH0ym9hVADundAVc/mGuLMlX8A2GO1/wKgmM31LcKDT4T1lE5B+UW4wW84l999OWwcmfhowu1zh9vFxBQkju4ImdOLjzWHJ6CqGK7t+5UWPMkhI8ld3mdOEjSXhddM30RJ/BerQIw/Op9lJxXqmFvnsq28NT8O4zYwGBx6I0ApFZDreFormaVUVnbntK/uS1pMR5ZUvziDgOqsWucN4XEvgH8e1I5UEAxol1Yi3E5KcQZchnnAojIpEJct+LmJ1OgjmAdJvupaU9M3Q72zLibP5ZdURMeUu6spwkRRhb/GHISM2n0RONqHBWMxmguLIjqBOEHcegXEH5BUbLoUaxz3/Hv380RC5hwmSlWuDX8b1CKgZs0y7anSyGcBVpy4d0wyKwAEDr9metjrmXP7zEsv3luBKLCdTmOmkW6+CK6Vmu+VhaF7TRSrjQCTOYeqP7t1ufL5HI5rVn/PC2p0L1ea3MNBs2bRHa4pmwnHbW0dsUwTBjKGL8+Ifs/BHdxgvFjcMovOR7VrhdY93f0omRmoAHbj3PcFpt/5zRCObARwAxA9L0KHBfo+ajnXixWNwnvaINgynvilKT4pBJYAmyb7iOeBAywV6wZlB1HN1mQnSO+8WjwlZddMUFPL98BBszcvccYAx74QU1K6GiDsqK9BBfjCwYjdBsWMe8Km8k9ADjIMDfXswXXQn28ak0xR8qbXZgEIhOWyrs9mdMNwA3JoMCZfq3jmqiakReeXteBX35sRH3/4AejK1Mike73mtnj9Da/W1+cO4uwBoHQElInErqEMKtcC44A8GJYwdh5EoTLL5h91dL2SQd2i+AyBE1SaDmjHq8FOQuNEXpa+0euGIODORM/RDnWqcLuRvJE01JJvhD+CZq0K348lav1gCa5Z5NbvakaEA4hjsNferGoJATZ0LWql3ChcyYgxPap+Fj3sJDWvlU3zsAz6YYUu2d4XHL35iQftBWB4cLNRFQ4I3KShvFJyaTfywd6Ggr5kE+TVtCz7yIlh7QVo6ZiPm8HknEO4pvLU0Cq0LvKhqPRuZl6EPUrjqiEVYbPs+mpNrMPTsDA7WFlV8XiSTJ10wVrYtdKPIKuHkcfjmgOFgaEjYCAxOZU3HIucBJPuvJ7WQgXC2+RM8NLqA4DKEyF38viINN7D5Q6e5Yb6ltKb2a5kH4j5/N2VYDe9XZ4U3p5/7y4AQT/wcbwo89Y2MJR5T3/oz/+DcRwA7iU36apklKFPc8PZx0n7CNNyawLhB2hk3Lr2ARA0Zd1CmjmpPcY+3SmRk1umVEemcJzaxgHHdiNX4YwQt4eHdtGR97pNzyhIJfSWJCdBu9PG7QiTI5FmbW97Wg+5fpoFTVPeeNr9y51Uy/cu4Fi4AcOxKTMq76jSxR4LQ1Nn5kWvlo1D+YRbcV+p9B7Gfj/zRg4OZ4jLgCOuySOcJ8FS3eO6pWrRyM5R6xwV0p1FBL/s/ze4Y4Fsp+cPDFjrObcly2QvpCrm2Q8xf3e5HpoFLzgOa+hGxLLz4oNCRh5abP6eHJSV4GefIWpdF2moTEL7PGXiXbF/obRt0L1NTbR6n2810TSmZGkwV+w1mH9AvSBxVnqmI6w1NJ6bhVFGuJ5ByIduxQCNOGreAW0rgzSRlkeDAz73JLyRRSl9kEE2X4Wcacu0PQYf3JAl46dXrF76EyRFE+0JGlRdZ0AQJwjcOdBoSeyxSzp2B0Q7rDLXKbnx1/k7br2eOKppcIh79G8PYRZ1/Z8k33EPDZvGl4j2qAUQimNvatqvUMmSV/Nu5cBNNjywCCKwpbkvPEdit3MtrTa6I2wf8oDH91qo3QDpH+Sq72uxuTP5j330PExNE9ZQkaXOCK02kqW/37+aq0PBkU4ONg8v0sX4hqs2ZcAO2ur6nn5PEIbh5H5mX4OacrUwHZ/0ZTFrfYbZwM9O7D8c3fHtr3aHgbVb3iCVyNWveMPsJzVl/aF8pv/fAUUAwc9crNIVepnTgOIp2iNldy5qQbogCIdtc+ihuoQ98wQBVOEv86ASTMr3dcjURx7RcGo4/H+BL+KQswTxLgOU4s4NWZqRk4cxnwxgjw5Hk0h7BOpks+cysKZ1PKntTZKVMZk/yjfg0wH+VQzbMcR5q6ZlOJGW2iqoxXCzR8xAsOiJ5kZ7D693F3vWgqbQ38k629hBmuRqoNIH1teHrWew9Z07W+xlMir+fOTG5oZmjAYhhw9J1wJzxmNagnflck3FZecIUHBwEQuzKredIVYC3EU5rVgWpE5LTURQt5yYqlVaxo/Usffn2WNHmdqs4XaO3joJCKoNqnBHauz3wql+rXGBS3XUFe4hwcmdiasA0Nkfy6ccOjCS3CNIUA1n52xAn3C0RBh0A6rGgmiNLDtPHwiNyaeIZLPJm7p842PQChUqhY/1oQtEjCkZFL7yf6a64X0cuCuNPa97/zBRGBUpccNNrw5lNKFpdqeCf36PkFYKt0DcbaSFXKG/+O80A5goZiwinxpaaIqwxnPr2mNSLO78SnFCS0QbYZYhO3avmIGv2/XelNUYnaPQntjZuVSepJbAMoh/l8GVV1ljPrMsvsgYWiTl12or3D0iYC0j4l3U98vsfv3pIm/q8YfIZaNci2Z9xNYzzMYK0QecAIYXISgxgHd0tCZ1/hDOze3ogvcz8stJE3/RfRlu1trWvH9K1b+bcdjvyyfJNtGvBem1q3gaYLuULXjT6EmBdfIuYL+4i/4Jui7MObm3AMjGizMIrLWZIwb6H7tGEdZ6R6bZQQAQHZUUbE8ZjQ3VYiedkOFDjIExXG3G5/oxBvGskcArw1CsZnMkt3H2E1E6gV94nt2dXkxXLSnCEvezJlk7mfKBzVFKiH7j3q5ByeP4LR6dAT82KgPGc6h9lNfbxzcr5R/uDteasnvyC7YcRsTcsh1MnVfpR0Rqfe+CXBpztMe7YgqQgrhAiz9oxvc0bwPcUTLhdlBX/kB9UCxHN71+dxEDp7NCrqpQkFhXdIiU3ramgKFscLCUBZT2hWN6Aehjc8QY9bYwCOgEQXnHFWeTj7va5PTwvOcYMjIwmgBwKwXL9RwkLwDwYlb1NilYZMgoHmsc4LN8cAKCsGsJDDI8FpG/zVNC7cKJZxndaNilplTC2I4y8Vh0S/D57TjijiQwX9cknaU5/2KoFeWjASSdP5fqaFAdlVOr+uiVZNW9bZ9K9/9P6IeZgrxZRMpLg4gpk3nhro0i/1WPUvi9D7uXDeH9UtWrEpjOa+Y5mGLaEZJYvWAFhUgw613t6GWc3DJ7XWNVaUfKwlyCgoz/Ow1r8XYSnJDm29foXfTxeVVcwA0cySxvgwVParCXj8g+PB/sqpLQdHMGc9DskCvIJhTFNho1BvhMJQuZrrfyunWneS/jcRJaNtItX78K3rtGSs+yKLYsRjKdCpl6slT9FwHrwf9UmrpBbKoVUQM4fNKA9oTQeX4NvkDzi5V/xcMgg/yb6o69JoW70AjjJkWeR6qarPV0tQyHCJjVezKZOnhaSSTDbSfIMxelCX66lG/sgmhJJEECfUVJU6q7bmeE6o3H8OfbXOHe9QG5UKgPt0DVU4XU05ToDYlZlvTg70gxem9+FwcMHeE5cDR4knzGwxwhj7udvnEUJFsLBsbMeTyquZbdIQzgNUaPicArzRFWpnlTf9Qi2BcyUFs6IY5TKSF3IN3Gopwe4nu1Hw+DpLRGMlG986qIrGPZ9FcyKZERnd49eXp+AXsGiAtUEvaCWHpcoBBGU+Ki+r8WlOhCT9ACWuMuv9dUCOtsCmC/wDEnbZBQ+Z5SWf810L5jd3Xm5pmcK3Naqv2+ZlLtFw470mEeeh4VLjwfEmkrOWoRlHkGJ0W1cj0d9VQnw8l14yiOBCln+PQjjGxx2Z8CyLZkCQcWQxg1kyRY9U5Uf21bQ9AajHFqg3WyICEibl27mD/oiZuvZW2llO7iI5CchhyZJCgo7xldvGF7FWKJ/pZ3DGt2u6x3FdLmdklGERRs4R7K8MjWor+P+AmUemSL1yEGQubgyeYgRK+nzjzPdmPRyJlarbUCesbeCRoSYHhbqePDQ5OxkWhrq2MHu6Y2YahMkAhPEpq4MSVRdJSmproL3okgqfVtnc3w/Bx3zfuNWdEsLk5g0VXtBFAFcC6xEX44auL1LrtAw/DKVezG7ciRp5bqTVLDWORKhffIC+UsDlbs1HGsMoic/Mg5rh7C09CaOvKOugVuDGsL+D9KtbZyZP4ILf92WMXwHZEYIOxtdat9QxPHaQumL90uvoJAEsLY2jxNLDT/jCY++NLGY/hCM2R6FqKdP4jUHW3rOZ6+Fq1/uCLqJqNM8QijvACdc4aQ6si9iFQKQrfqtb5jbgT0g5CuIyT/qesTc2FyJO1spMUSY1oln5MX2QnLz2zMnP3UMsfRGT5bxd1uTAK9Nf0hWUvrKfGXeYrw6ZZsixNJmQ7bzzqPgVSOAGwhEzhDvTPu4/uUyuJJtl65H5nUq3H1e5IfIwfjdmVUISpasjDc6mtc3YDFnGFWEMADmR513w8PvwuhePjcwFYNJVqqD5AjM9AiDhihPsxKcCrQvhQHp6M/lriNqLesAeCbnEP66mm8lknytNX5AIY67cfC2ITPVMrBMC2hwdnr5fkiv9RsQH0Iz6C5T96Kv4Il5oh8X64SofyIlERxhn6xAMlobne9/eehmzI3P0vlpLQUTMlJA/MtWxvBNFH8paNGGxpB9HcRGfMGJysQ+sgKUidUlfjTHs4fcHNe8YcXY/yRKQUx7hOc7j6f630pYxMPlwRP974zQqeNWGf8e2IpgYGcJREUN7YMWu/MFS8LXRSBFD9dXfC/OrSzUAGrXg/SQxjbWc5ojtxgnVUmv72/06vFUJg/yXT+8fzEQG+5RtzMaRrOnpNQH2VZNbwL00ekdPK5Zy721XU/6+9FCHXDI/+szbmlxZKaPOtbexN3W3FwXa+VyBa05hFmx0DEB2VvlVcep+zY5Z094wPIUqGCz4+H8n5oYMVjCcnAbCuidzU395w+zuuUA5YRjKsDtbUljGVLwKpscYnzWw7XySriLqAQUA0wFSZDCkVRcqr4QvTy3McaqfOKD4djMu/6R7Nz1lqxGQZM/5JvpjlmYrTH6KyQ9KD4p1z1N8ufvmlHUp43HloazbQQ8i52nBo586LwYqnQWfyt2id1rxi5OOQ32wihv4KtIJfa+k+vGW5Xj5YCBVGIKj/AmZS+eWhXNCUwdmp3I/wr/kOfy4fwtviMsfe0W/+kLIEOsEUYAQ=="}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4732,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":4732,"ephemeral_1h_input_tokens":0},"output_tokens":0,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"1bb8e69e-dfa8-45ee-a9ae-dc59bd0707dc","uuid":"20812162-aaff-4419-b034-1fed62c8360e"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_012tdh4vLbMCnVLPLXtieJ3B","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me build a complete Tetris game that runs in a browser using HTML, CSS, and JavaScript. I'll create a single HTML file with all the necessary code.\n\nHere's what I need to implement:\n1. Standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece movement (left, right, down)\n3. Piece rotation\n4. Line clearing\n5. Scoring system\n6. Increasing speed levels\n7. Keyboard controls\n8. Game over detection\n9. Next piece preview\n\nLet me design this carefully:\n\n**Game Board**: 10 wide × 20 tall (standard Tetris)\n\n\n**Pieces**: I (cyan), O (yellow), T (purple), S (green), Z (red), J (blue), L (orange)\n**Controls**: Arrow keys for movement and rotation, Space for hard drop, P or Escape to pause\n**Scoring**: 100-800 points per line cleared depending on how many lines (scaled by level), with speed increasing every 10 lines\n\nNow I'm setting up the HTML structure with a canvas for the game board and a sidebar for displaying score, level, and the next piece preview. I'll use standard constants like a 10×20 grid with 30-pixel blocks, and implement the tetrominoes using the Super Rotation System.\n\nDefining the piece shapes... Defining the game pieces and constants... I'm setting the drop speed to decrease with each level using a formula that keeps it reasonable—starting at 800ms and dropping by 70ms per level until it bottoms out at 100ms. Now I need to implement the ghost piece to show where the current tetromino will land, which means copying the piece, dropping it until collision, then rendering it semi-transparently. I'm also planning to add wall kick logic so pieces can rotate near walls using the standard SRS offsets.\n\nWriting the HTML file... Still writing styles... Finishing the button styling with hover effects and setting up the HTML structure for the game container with the canvas and overlay elements. Writing the game logic... Setting up wall kick offsets for rotations, then defining the scoring system and drop speed calculation based on game level. Now initializing the canvas elements and game state variables. Setting up the game loop and piece spawning... Writing collision and rotation logic... Writing game logic... Writing the game logic... Writing the game rendering... Finishing the ghost piece rendering, then drawing the actual falling piece by iterating through its shape and rendering each block. After that, I'm setting up the next piece preview canvas with a dark background.\n\nNow I'm centering the next piece in its preview window by calculating offsets based on the canvas dimensions and piece size, then drawing each block of the upcoming piece with proper spacing and color.\n\nAdding highlight and shadow effects...\n\nThen updating the HUD to display the current score and level.\n\nNow I'm setting up the overlay system for displaying messages, and implementing the main game loop that handles the drop timer and piece movement based on the current level's speed.\n\nSetting up keyboard controls... Finishing the game loop setup and handling the overlay button click to either resume or restart the game. Now I'm reconsidering the piece locking logic—since `hardDrop` already calls `lockPiece`, which spawns a new piece, I need to make sure the game loop doesn't try to lock the same piece again.\n\nThe key insight is that after `hardDrop` locks the piece and spawns a new one, the game loop will check collision with that new piece, so there shouldn't be a double-lock issue. However, I'm realizing the `dropTimer` needs to be reset after locking to prevent timing issues, so I should either reset it inside `lockPiece` or restructure how the timer works. Writing the lockPiece function...\n\nThe key insight is that `hardDrop` calls `lockPiece`, which resets the drop timer and spawns the next piece, so when the game loop resumes on the next frame, everything's already in place and ready to go.\n\nI should also make sure the game loop properly handles the case where `lockPiece` triggers a game over—it needs to stop requesting animation frames at that point rather than continuing to loop. Still writing game loop logic... I'm realizing the game loop needs to check `gameOver` at the start to prevent it from continuing to process game logic after the game ends. I'm adding that guard condition so the loop only updates the drop timer and calls lock piece when the game is actually still active. I need to make sure `dropTimer` is properly initialized in the `init` function and reset correctly when pieces lock, so the accumulation works smoothly across frames. Now I'm thinking about the visual presentation—I want to add a dark theme with colored blocks that have highlights and a visible grid to make the game feel polished.\n\nI also need to handle the initial game state with an overlay showing the title and a start button, plus a high score display. Let me reconsider how `nextPiece` should be initialized: I'll create the next piece first in `init`, then spawn the current piece which will automatically generate a fresh next piece. For `createPiece`, I'm building a function that randomly selects a piece type and constructs the piece object...\n\nStill writing piece generation... I need to figure out the spawn position for the I piece since its visible blocks are offset from the top of its shape matrix. The standard approach is to spawn it with a negative y-coordinate so that only the actual piece blocks appear in the visible game area, with the empty rows above the board. The I piece spawning at y=0 puts its blocks in the second row, which is standard Tetris behavior, while other pieces appear at the top row. For the game over condition, I need to check if a piece collides immediately upon spawning, which happens when the board fills up to the top. I'm also planning to add localStorage for the high score and implement a lock delay feature to give players time to adjust pieces before they lock in place.\n\nI'll skip the lock delay for simplicity and use module-level variables to manage the drop timer through JavaScript closures. I need to handle edge cases like hard dropping when a piece is already at the bottom and ensure pieces automatically drop based on the timer during gameplay. Now I'm writing the final clean version with pure JavaScript, proper game state management, and standard Tetris mechanics.\n\nFor the visual design, I'm going with a dark space theme featuring a subtle grid on the board, 3D block effects with highlights and shadows, a glowing current piece, and a faint ghost piece outline. The sidebar will display score, level, and lines panels along with a next piece preview, while the overlay shows the title, game over message, and a start button.\n\nWriting the complete implementation... Defining the piece shapes... All the Tetris pieces fit into square matrices, so the clockwise rotation logic should work consistently. I'm verifying the transformation formula where position (r, c) maps to (c, n-1-r), which correctly rotates the shape 90 degrees clockwise. Let me test this with the T-piece to make sure the math checks out. The rotation checks out perfectly—all the coordinates map correctly to produce the rotated T shape. Now I'm ready to build out the complete HTML file with all the interactive features.\n\nI'm implementing a 7-bag random generator for fairer piece distribution, which shuffles one of each piece type and draws from that pool before generating a fresh bag. With that in place, I can now assemble the full game implementation and think through how to visually animate cleared lines.\n\nFor the line clear effect, I'm tracking which rows get cleared and flashing them briefly before removing them from the board.\n\nStill writing game loop code... Still writing game logic...\n\nI'm realizing the animation timing creates a dependency issue—I can't spawn the next piece immediately after locking because the clear animation needs to finish first. So I need to track whether lines are being cleared and hold off on spawning until that animation completes. Writing the line clear animation...\n\nActually, I'm going to simplify this and skip the animation entirely. I'll just clear the lines immediately when they're complete—the visual feedback from rows disappearing and pieces falling will be enough. Let me refactor the clearing logic to be more straightforward.\n\nRefining the line clear function... I've decided to skip the lock delay feature to keep things simpler, and I'm going with `const` for constants and `let` for mutable state. Now I'm writing out the complete HTML/CSS/JavaScript implementation for the Tetris game.\n\nWriting the stylesheet... Still writing styles... Still writing button styles... Building the game interface... Defining the game constants and piece configurations... Setting up the canvas elements for the main board and next piece preview, then initializing all the game state variables like score, level, and piece queue. I'm also loading the saved high score from local storage and setting up the piece randomization system.\n\nStill writing game logic... Still writing collision and rotation logic... Writing game logic... Finishing the level calculation based on lines cleared, then moving into the spawning logic where I set up the next piece, check for collisions to detect game over, and handle the end-game state by saving the high score to local storage and displaying the game over screen.\n\nNow handling the block drawing function... Adding the 3D block effect... Finishing the grid rendering, then drawing all the placed blocks on the board, and finally rendering the ghost piece to show where the current tetromino will land.\n\nStill writing rendering logic... Drawing the next piece blocks... Still writing canvas rendering...\n\nNow I'm setting up the HUD to display the current score, level, and lines cleared, then implementing the main game loop that handles timing and drop mechanics based on the current level.\n\nInitializing the game state...\n\nNow I'm setting up the keyboard controls to handle player input—arrow keys for movement and rotation, with checks to prevent actions when the game hasn't started or is paused. Finishing up the pause toggle logic and event listeners for the game controls. Now I'm checking the rotation logic for the tetromino pieces—specifically verifying that the clockwise rotation formula correctly maps each position to its new location. Verifying the rotation formula works correctly by checking each cell position maps properly from the original T piece to its rotated form.\n\nNow I'm testing the I piece, which is a 4x4 grid, and I notice the rotation formula produces a different result than expected—the vertical line should appear in column 2, but my calculation is showing it in column 1 instead. The rotation is working correctly—the I piece rotates into a vertical line as expected, and the O piece stays the same since it's symmetrical. Now I'm thinking through the spawn positions: the I piece starts at y=-1 so its blocks appear at the top of the board, while other pieces spawn at y=0. I'm realizing the spawn position needs to match standard Tetris guidelines where pieces appear above the visible playfield, but for this implementation I should keep it simple since I don't have upward movement controls anyway.\n\nThe real concern is game over detection—when a new piece spawns, I need to check if it collides with existing blocks at its spawn position, and the I piece's offset means it occupies row 1 while other pieces occupy row 0, which could affect when the game actually ends. I'm realizing the I piece at `y: -1` actually makes more sense for standard Tetris behavior, placing it at the top row when spawned. My collision detection already handles negative rows correctly, so this approach should work without complications. I'm reconsidering the spawn positions for different piece types. In standard Tetris, the I piece spawns higher (with one row in the visible area) while other pieces spawn lower (with two rows visible). Since I'm treating y=0 as the topmost visible row, the I piece should start at y=-1 so its blocks appear at row 0, while other pieces also start at y=-1 but their shapes extend differently into the visible area. I'm realizing that using y=-1 for all pieces would work consistently—the first row of each shape sits off-screen, and the visible blocks start at board row 0. For the I piece, this means the four blocks appear at row 0; for other pieces like T and J, the visible blocks span rows 0 and 1 depending on their shape structure.\n\nFor game over detection, I need to check if the spawned piece collides immediately at its starting position—specifically whether `collides(currentPiece, 0, 0)` returns true, which would indicate that blocks already occupy the space where the new piece appears.\n\nWriting collision detection logic... Finishing the collision detection logic...\n\nThe collision function correctly handles negative rows by only checking the board when `row >= 0`, while still catching out-of-bounds collisions on the left, right, and bottom edges. The logic properly distinguishes between rows above the board (which shouldn't trigger collisions) and actual wall/block collisions.\n\nWith pieces spawning at y=-1, the game over detection works correctly—when a new piece collides at position (0, 0), it checks rows 0 and below, finding any blocks that have accumulated at the top of the board. However, there's a rendering issue: the initial display would cut off the top row of pieces since they're positioned above the visible board.\n\nMy draw function already handles this with a row bounds check that skips rendering any blocks above row 0, so pieces at y=-1 would have their top row invisible while the rest displays normally. This is the intended behavior for the spawn animation.\n\nNow I'm realizing I need to adjust my spawn logic—I was setting y=0 in spawnPiece, but I should initialize pieces at y=-1 instead to match the hidden-top-row design. Let me refactor createPiece to handle the initial positioning...\n\nDefining the piece creation function...\n\nI'm working through the math for how different piece shapes map to board rows when spawned at y=-1 versus y=0. The I piece's active blocks start at row 1 of its shape, while the T piece's active blocks are at row 1, so I need to figure out the right y offset to keep them consistent visually. I'm going back and forth on whether to use `y: 0` for all pieces or keep the special case for I. Using `y: 0` universally would simplify things and the visual difference is negligible, but I need to think through what happens when the I piece spawns at that position before committing to it. spawn it, the top row of the shape (all zeros) is at board row 0, and the actual blocks (1,1,1,1) are at board row 1. So the I piece appears at the second row from the top. When you move it right or left, it's at row 1. When it drops one step, it's at row 2. This seems fine visually.\n\nBut there's a subtle issue: when the board fills up to row 0, can an I piece still spawn? With y=0, the blocks are at row 1. So the game over check would need rows 1 to be blocked. With y=-1, the blocks are at row 0, so row 0 needs to be blocked for game over.\n\nStandard Tetris game over is when blocks reach the top of the visible field. So if the board has blocks in rows 0-1 and an I piece (y=0) spawns with blocks at row 1, collides returns true → game over. This is correct. If I use y=-1 for I, same thing: blocks at row 0, if row 0 has blocks → game over. Both approaches work for game over detection, though y=-1 is slightly more standard since pieces spawn partially above the board.\n\nI'm going to stop overthinking this and just use y=0 for all pieces—the game will work correctly either way.\n\nNow I want to add DAS (Delayed Auto Shift) for smooth horizontal movement when holding a key: initial delay of 170ms before auto-repeat starts, then 50ms between repeats. Implementing DAS handling...\n\nNow I'm thinking through the full structure I need: the core constants and canvases, game state variables to track everything, timing mechanisms including the DAS system, a 7-bag randomizer for piece selection, and all the essential game functions like collision detection, piece rotation and movement, line clearing, and rendering with that 3D block effect.\n\nWriting the complete HTML/CSS/JavaScript implementation... Still writing styles... Still writing styles... Building the sidebar panels... Setting up the game constants and piece definitions... Now I'm setting up the DOM references for the game board, next piece preview, and UI elements like score and level displays, then initializing the game state variables.\n\nI'm also setting up the delayed auto-shift system for smooth horizontal movement controls, loading the best score from local storage, and starting to build the bag randomizer for piece selection. Writing the collision detection...\n\nNow I'm implementing the rotation logic with wall kick offsets to handle edge cases when pieces rotate near boundaries, then defining the movement and rotation handlers for player input.\n\nImplementing drop mechanics... Now I'm handling the piece spawning and game over logic—pulling the next piece into play, generating a new one for the queue, and checking if the new piece immediately collides, which would end the game. If it does end, I'm updating the high score in local storage and displaying the game over screen with the final score.\n\nI'm writing drawing helper functions... Writing the game rendering... Writing the next piece display... Finishing the rendering with 3D-style beveled edges on each block, then updating the HUD to display the current score, level, and lines cleared. Now I'm setting up the main game loop...\n\nHandling the game state and timing—checking if we're actively playing, calculating delta time, then processing horizontal movement with delayed auto-repeat (DAS) to let the piece slide smoothly when held, and managing the drop timer to move pieces down at a level-dependent speed until they lock in place.\n\nSetting up the game loop and control functions—initializing the board, score, and game state when starting, then managing pause transitions and animation frame scheduling to keep everything running smoothly. Setting up keyboard controls for the game mechanics...\n\nI'm handling pause functionality through both the P key and Escape, then resetting the directional input state when arrow keys are released. The overlay button toggles between paused and playing states, and I'm about to draw the initial game board.\n\nActually, I'm noticing an issue with how pieces spawn. When `initGame` creates the next piece with `makePiece`, it already has the correct starting position. Then `spawn` assigns that piece to `cur` and generates a fresh next piece. Let me trace through this flow to make sure the positioning is working correctly—the piece should already be positioned properly when it becomes the active piece. I'm realizing that since `spawn` does a reference assignment with `cur = nxt` and then creates a fresh object for the next `nxt`, the two pieces stay independent. Now I'm checking the spawn positions for different piece types—the I piece starts at y=-1 to account for its shape offset, while other pieces start at y=0, and I need to verify these positions map correctly to the board. I'm checking the collision detection logic for the ghost piece placement. The `ghostY()` function increments down until it would hit something, giving the final resting position—let me trace through an example where the current piece is at y=0 to verify the math works correctly. Let me trace through the logic more carefully with the actual formula to make sure I'm understanding the collision detection correctly. , `dy = g - cur.y + 1` means we check if the piece can be at `y = cur.y + (g - cur.y + 1) = g + 1`. If it can't be at `g + 1`, then `g` is the lowest it can go.\n\nLet me re-trace:\n- We want the ghost to be at the lowest valid position\n- We check if the piece can move to `y = g + 1` (by checking `hits(cur, 0, g - cur.y + 1)`)\n- If it can, increment g\n- If it can't, g is the ghost y\n\nFor `cur.y = 5`, `g = 5`:\n- Can piece move to y=6? Check `hits(cur, 0, 1)` → probably false → g=6\n- Can piece move to y=7? Check `hits(cur, 0, 2)` → probably false → g=7\n- ...\n- Can piece move to y=19? Check `hits(cur, 0, 14)` → false → g=19\n- Can piece move to y=20? Check `hits(cur, 0, 15)` → true (floor) → stop\n- Return g=19 ✓\n\nThis is correct. The ghost appears at y=19 (or wherever the piece would land).\n\nNow I'm realizing that for taller pieces like the T-piece with 3 rows, the collision detection needs to account for the entire shape's height. When checking if a piece at y=18 is valid, I need to verify all three rows of the shape fit on the board, so row 2 would be at board row 20, which is out of bounds. That means the lowest valid position for a 3-row piece is actually y=17. The ghost function is working correctly—it finds the lowest position where the piece would collide by checking if placement at g+1 causes a hit, and stops when it does. Now I'm thinking through the drawing logic to make sure the ghost piece and current piece are both rendered properly.\n\nWriting the drawing code... Initializing the game state with a fresh board, resetting the score and level, and setting up the piece queue and animation loop. The `spawn()` call at startup creates the current piece from the next piece in the bag and generates a new next piece, then checks if the game is already over—which shouldn't happen on a fresh start, but the check is there for safety. the initial board state (empty + overlay). Let me make sure `draw()` works when `cur` is null (initial state):\n\nWhen `state = 'idle'`, the piece drawing is skipped, but I need to check if `board` is initialized before the loop tries to access it. If `board` is null or undefined at startup, the rendering will crash. I should initialize `board` as an empty grid during setup...\n\nInitializing board array...\n\nActually, I could also add a null check inside `draw()` itself to be safe. I'll go with initializing it upfront since that's cleaner. Now let me think about visual polish—I could add line clear animations, level announcements, or score popups, but those add complexity. I'll stick with solid mechanics for now and skip the extra animations.\n\nOne thing I want to consider: making locked pieces look visually distinct from the active piece by darkening them slightly. I could modify the block rendering to apply a darker overlay when drawing settled pieces, but that might overcomplicate things. Let me keep it simple for now.\n\nActually, I'll skip the darkening approach entirely—the ghost piece already provides enough visual contrast, and keeping everything consistent will make the code cleaner.\n\nNow I'm ready to write the final version without overthinking it further. For controls, I'll stick with keyboard since that's what was requested. Looking at the layout, I want the board at 300×600 pixels with a 148-pixel sidebar, totaling about 468 pixels wide. That should work on most screens. I could add responsive scaling for smaller devices, but I'll keep that simple for now.\n\nLet me finalize the game state logic before I start coding—I have `idle`, `playing`, `paused`, and `over` states, and the keyboard handler correctly blocks input when the game hasn't started or is finished.\n\nWriting the code now... Writing the game loop and overlay logic... I'm checking the while loop logic that handles multiple drops in a single frame—each iteration drops the piece one row, and if locking triggers a game over, the state check stops the loop. Then on the next frame, the loop returns early since the game is no longer in the playing state, so no new animation frame gets scheduled. ✓\n\nI should refactor this to only schedule the next frame when the game is still active, making it cleaner. After `endGame()` is called, the final board state gets drawn before the overlay appears, which is the correct sequence. The while loop stops once the game ends, `draw()` renders the final board state, and then the animation frame request is skipped since the game is no longer playing—so the overlay displays cleanly without any extra frames. Now I'm ready to write out the complete HTML file with all the styling and game logic.\n\nWriting the HTML structure... Still writing styles... Still writing overlay styles... Building the sidebar UI... Defining the game constants and piece data...\n\nNow I'm setting up the scoring system where clearing lines gives exponentially more points, and the drop speed increases with each level. Then I'm grabbing references to the canvas elements and score displays so I can render the game and update the UI.\n\nSetting up game state variables... Writing game logic... Writing game mechanics... I'm checking if the current score beats the high score and updating the stored best if needed, then displaying the game over screen with the final score and a retry button. Now I'm setting up the block drawing function with positioning calculations and handling ghost piece rendering...\n\nStill writing drawing logic... Writing the game rendering... Writing the next piece preview... Finishing the block rendering with highlight and shadow effects, then updating the HUD to display the current score, level, and lines cleared before moving into the game loop.\n\nNow I'm handling the core game mechanics—calculating delta time between frames, managing the delayed auto-shift system with its acceleration, and implementing the auto-drop timer that moves pieces down at a speed determined by the current level.\n\nFinishing the game loop and then setting up the initialization functions—resetting the board and game state when starting a new game, and toggling the pause state with appropriate UI updates.\n\nNow I'm wiring up the keyboard controls to handle starting the game from idle or game over states, and processing directional inputs... Setting up keyboard event listeners for game controls and initializing the game board with the game loop starting.\n\nNow I'm reconsidering the DAS (Delayed Auto Shift) implementation—when a key is pressed, it sets the direction and immediately shifts once, then accumulates time until the DAS threshold is reached, after which it auto-repeats at the ARR interval. Still working through the DAS logic...\n\nI see the issue now—after DAS expires, the remainder gets set back to the original DAS value, so it stays >= DAS on every subsequent frame, causing a shift every single frame instead of respecting the ARR interval. I need to reset dasTick to 0 after the auto-repeat kicks in, not back to DAS. I'm realizing the calculation is getting messy, so let me simplify with a cleaner DAS system using separate timers—one tracking how long the key's been held and another for the auto-repeat interval, so I can trigger movement immediately on press and then at regular ARR intervals afterward.\n\nImplementing the timer logic... I'm refining the input handling to track when DAS is first triggered, then use a flag to manage the auto-repeat timing cleanly. Once DAS is reached, I reset the repeat timer and start firing moves at the ARR interval. On key release, I clear everything and wait for the next input. I'm realizing the standard DAS behavior is simpler than I'm making it: press the key to move once, hold it for the DAS delay, then auto-repeat at the ARR rate. So I need to track how many ARR intervals have elapsed since the DAS threshold was crossed to determine how many additional moves to apply.\n\nActually, I can simplify this dramatically by starting the DAS timer in the negative—when a key is pressed, I immediately shift once and set the timer to negative DAS, so the first auto-repeat fires naturally after the DAS delay passes. Then in the game loop, I accumulate time and shift whenever the timer crosses zero, subtracting ARR each time to handle the repeating interval.\n\nImplementing the DAS/ARR system... I'm verifying the timing works correctly with typical frame rates—at 16ms per frame, the initial delay before the first shift happens, then subsequent shifts occur at regular intervals matching the ARR rate, which produces the expected rapid-fire behavior.\n\nSetting up the keyboard handler...\n\nNow I'm thinking through the edge case where the player switches directions mid-hold. If they press left, then right while still holding left, the DAS resets to the new direction. When they release left afterward, it won't clear the right direction since the keyup check only resets if the released key matches the current direction. This handles the priority correctly.\n\nFor the rendering, I need to make sure the ghost piece doesn't obscure the actual piece. Since I'm drawing the ghost first with transparency and then the current piece on top, the opaque piece will naturally overwrite it. I should probably skip drawing the ghost entirely if it's at the same position as the current piece to avoid unnecessary rendering. I'll skip the optional chaining check since most Tetris implementations just draw the ghost everywhere anyway. The key thing is drawing the ghost before the current piece so the opaque piece renders on top and stays visible. Now I'm ready to write the final implementation with the board dimensions, piece system, and spawn logic all locked in. so the current piece completely covers the ghost when they overlap, which is the correct behavior. I don't need to add extra logic to skip drawing the ghost in that case since the opaque blocks will just overwrite it anyway. Now I'm refining the drawing loop...\n\nRefactoring the ghost and current piece drawing... I'm going to rename `ghostRow()` to `ghostY()` since it actually returns the y coordinate, not just a row number, and then I'll finalize the code with the standard Tetris Guideline colors for each piece.\n\nWriting the HTML and CSS... Still writing styles... Building the game interface... Writing the Tetris game logic... Setting up canvas contexts and DOM references for the game display, HUD elements like score and level, overlay controls, and initializing the core game state variables including the board, current piece, next piece, and game phase tracking.\n\nNow I'm loading the best score from local storage and setting up the piece bag system with a Fisher-Yates shuffle to randomize the tetromino sequence, then defining the piece creation function that generates pieces with their shape, color, and starting position.\n\nSetting up collision detection...\n\nI'm implementing the core game mechanics—rotation with wall kick offsets to handle tight spaces, movement validation, and both soft and hard drop functions to control piece placement speed and scoring.\n\nNow I'm handling the lock phase where pieces solidify on the board, then scanning for and clearing completed rows while maintaining the board dimensions. Writing the rendering functions... Writing the game rendering logic... Writing the next piece preview... Finishing the rendering logic with highlight effects on each cell, then moving on to update the HUD display with current score, level, and line count. Now I'm setting up the input timing constants for the Tetris game mechanics.\n\nSetting up the main game loop that processes input timing for piece movement, handles gravity and piece dropping based on the current level's speed, and triggers collision detection to lock pieces in place when they hit the bottom.\n\nNow I'm initializing the game board and resetting all state variables when starting a fresh game, then implementing pause functionality that toggles between playing and paused states while managing the overlay display.\n\nSetting up keyboard event listeners... I should prioritize readability over minification since the user just wants a working game. Let me rewrite this with cleaner class names and variable names that are actually understandable. I'm also double-checking the ghost Y calculation—tracing through the logic where it checks if the piece can move down one row at a time until it hits something, which determines where the ghost piece should land. = 17 is valid because the piece's bottom row lands at 19, which is within bounds, whereas g = 18 would push it to row 20, exceeding the grid limit.\n\nNow I'm ready to write out the final clean version with proper structure and styling. I'll create an HTML file with a dark space theme, a 300×600 canvas for the game board, and a sidebar displaying score, best score, level, lines cleared, and the next piece preview.\n\nWriting the complete HTML structure... Writing the complete implementation...","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":0,"cache_read_input_tokens":4732,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"1bb8e69e-dfa8-45ee-a9ae-dc59bd0707dc","uuid":"829079aa-5d7f-44d9-a0bc-5f88a502d710"} 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It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=off_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=off_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json @@ -0,0 +1,27 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "off", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=off_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=off_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl @@ -0,0 +1,6 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/claude_output.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/claude_output.json @@ -0,0 +1 @@ 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console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 27 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.585 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 27 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "off", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run1/transcript.jsonl @@ -0,0 +1,19 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-nlkj6_tk","session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"17ad4ae5-af8e-4adb-951b-7a8560ef9219","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01AQuLYLg8ChwFynSwNGq6LU","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"I'll build a complete Tetris game in TypeScript that runs in the browser. Let me plan out the structure:\n\n1. **index.html** - The main HTML file\n2. **src/tetris.ts** - The TypeScript game logic\n3. **tsconfig.json** - TypeScript configuration\n4. **package.json** - Package configuration\n\nLet me think about what I need:\n\n### Game Components:\n- **Canvas-based rendering** - Use HTML5 Canvas\n- **Tetromino pieces** (I, O, T, S, Z, J, L)\n- **Game board** (10x20 grid)\n\n\n- **Piece rotation** using rotation matrices or predefined states\n- **Line clearing** with scoring\n- **Increasing speed** based on level\n- **Keyboard controls** (Arrow keys + Z/X or up for rotation)\n- **Score display**, level, lines cleared\n- **Game over detection**\n- **Pause functionality**\n- **Next piece preview**\n\n### Tetromino Definitions:\nEach piece has 4 rotation states. I'll use the standard SRS (Super Rotation System) or a simpler approach. I'll define each piece with its color and shape—the I piece as cyan in a line, the O piece as yellow in a 2x2 square, the T piece as purple, and so on.\n\n### Scoring:\n- Standard Tetris scoring:\n - 1 line: 100 × level\n - 2 lines: 300 × level\n - 3 lines: 500 × level\n - 4 lines (Tetris): 800 × level\n\n### Speed:\n- Start at level 1\n- Every 10 lines cleared, level increases\n- Speed increases with level (drop interval decreases)\n\n### Controls:\n- ← → : Move left/right\n- ↓ : Soft drop\n- ↑ or X : Rotate clockwise\n- Z : Rotate counter-clockwise\n- Space : Hard drop\n- P : Pause\n\nNow I'm ready to start building the game.\n\nI need to decide on the best approach for making this immediately playable in a browser. I could set up a full TypeScript project with a build tool, but that requires a build step. Instead, I'll create a single HTML file with embedded JavaScript that handles all the game logic, rendering, and controls.\n\nDefining the Tetris game structure... Defining the Tetris piece rotations... Defining the piece rotations and color palette...\n\nNow I'm thinking through the full architecture—I need a comprehensive TypeScript implementation with canvas rendering, a standard 10×20 board, all seven tetrominoes, rotation mechanics with wall kick support, scoring and level progression, next piece preview, hold functionality, and ghost piece visualization to show landing positions. Defining the tetromino pieces as 2D matrices following the standard Tetris Guideline format...\n\nWriting the game implementation... Defining the piece shapes... Defining the piece shapes as 2D arrays and implementing a rotation function that transforms them 90 degrees algorithmically seems cleaner than hardcoding all rotations. Now I'm setting up the overall game structure with interfaces and types.\n\nWriting the complete implementation... Defining piece rotations... Writing the HTML structure... Still writing styles... Building the game layout... I'm laying out the control instructions panel with all the keyboard mappings for the game, then moving into the TypeScript implementation where I need to define the core game logic functions like board initialization and piece shape generation.\n\nWriting the game engine... Defining game constants and piece configurations...\n\nI'm realizing I need to double-check the T piece orientation—the standard form should have the stem pointing down with the crossbar on top, so that's [0,1,0] in the first row and [1,1,1] in the second, not the other way around. Defining the Tetris piece shapes with their standard orientations, where each row represents the piece from top to bottom as it appears when spawned.\n\nNow I'm implementing a 90-degree clockwise rotation function that transforms the matrix by mapping each element to its new position based on the rotation formula. That confirms the rotation is correct—the T piece rotated 90° clockwise matches what I expected. Now I need to figure out the wall kick 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":487,"cache_read_input_tokens":4241,"cache_creation":{"ephemeral_5m_input_tokens":487,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"e3d29b59-078f-482d-b8b6-9b5722fefa20"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_015S3QbVBcBzyK78v3FsABaD","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me build a complete Tetris game in TypeScript that runs in the browser. I'll create a self-contained HTML file with embedded TypeScript (compiled to JavaScript) or separate files.\n\nLet me plan the structure:\n1. `index.html` - Main HTML file\n2. `src/tetris.ts` - TypeScript game logic\n3. `package.json` - Build configuration\n4. `tsconfig.json` - TypeScript config\n\nActually, since this needs to run in a browser, I should either:\n1. Compile TypeScript to JavaScript and serve the files\n2. Create a single HTML file with inline JavaScript (compiled from TS)\n\n\nI'll set up a proper project structure with TypeScript and a build system. For the game itself, I need to define the seven Tetris pieces with their rotation states, implement a 10x20 game board, handle piece spawning and gravity, detect and clear completed lines with scoring, and manage difficulty progression. The controls will be arrow keys for movement and rotation, with the down arrow for faster drops.\n\nNow I'm defining the core game types and starting to build out the Tetromino piece definitions...\n\nActually, I think a canvas-based approach will work better for rendering the game.\n\nLet me set up the full implementation with the board dimensions, piece interface, and tetromino definitions...\n\nDefining the game structure... Defining the remaining Tetris piece configurations... Defining the remaining Tetris piece rotations and colors, then planning out the canvas layout with a 10x20 game board and sidebar for displaying the score and next piece preview.\n\nFor the game loop, I'll use `requestAnimationFrame` with timestamp-based updates to handle smooth gameplay. I'm also thinking through the key features to implement: a ghost piece to show where the current piece will land, the next piece preview, a hold piece mechanic, and proper SRS wall kick rotation offsets so pieces can rotate near walls realistically.\n\nImplementing rotation system... I'm simplifying the wall kick system to use a more practical set of offsets that work well across different piece types and rotations, then I'll write out the complete TypeScript implementation as a single clean file.\n\nWriting the game implementation... Defining the tetromino shapes... I'm defining the rotation states for each Tetris piece using 2D arrays of 0s and 1s, then moving on to implement the scoring system based on official Tetris guidelines.\n\nFor the game mechanics, I want to build something polished with wall kicks, a ghost piece preview, a hold system, lock delay so pieces can be repositioned briefly after landing, proper level progression that increases every 10 lines, and a display showing the next few pieces in the queue.\n\nI'm going to structure this as a TypeScript project with an HTML file, a game logic file, and the necessary configuration. Let me start writing the implementation...\n\nWriting game logic... Defining the remaining tetromino pieces... Defining the wall kick data for piece rotations... Defining wall kick data for the I piece...\n\nActually, let me verify these offsets are correct. The SRS wall kicks use (x, y) coordinates where x is horizontal and y is vertical, but I need to be careful about the coordinate system—in our game, y increases downward with row 0 at the top, whereas SRS documentation typically has y increasing upward. So I need to convert those offsets to match our coordinate system where positive dy means moving down. I'm converting the SRS wall kick offsets to match our coordinate system where y increases downward instead of upward, so I negate each y value. Now I'm mapping out all the rotation transitions for JLSTZ pieces—the clockwise and counter-clockwise kicks from each state. I'm working through the rotation transformations for the L-piece and I-piece in the coordinate system, mapping out how each orientation shifts the block positions when rotating clockwise and counter-clockwise. Continuing to map out the rotation transformations for each orientation state, tracking how the piece coordinates shift between left, right, and spawn positions in the coordinate system. Defining wall kick offsets for each rotation transition... I'm going to implement the proper SRS wall kick system using a lookup table that maps rotation transitions to their allowed offset attempts, accounting for the coordinate system difference where y increases downward instead of upward like in the official spec. I need to convert the SRS kick offset coordinates from the standard Tetris coordinate system where (0,0) is at the bottom-left with y increasing upward, to our game's coordinate system where (0,0) is at the top-left with y increasing downward. The conversion is straightforward: for each offset (x, y) in SRS coordinates, I transform it to (x, -y) in our system. I'm working through the JLSTZ piece rotations systematically, converting each set of five kick offsets for the transitions between rotation states. Continuing through the rotation offsets for the L and I pieces, mapping out how their wall kick data transforms between different orientations. I'm working through the rotation offsets for the I piece in Tetris, and I notice the L→2 transition doesn't look right. Let me pull up the standard rotation system from the Tetris wiki to verify the correct offset values for each rotation state. I'll implement a straightforward kick system that covers the most common cases without getting bogged down in the full SRS specification—trying offsets in order from no kick, to single-tile shifts, to larger adjustments and diagonal kicks. This should handle the practical rotation scenarios well enough for a solid Tetris experience, so let me stop overthinking and start building the game.\n\nI'm structuring this with a Game class to manage state, canvas rendering for the visuals, keyboard handlers for input, and a requestAnimationFrame loop to drive the game forward. The layout will have the hold piece on the left, the main board in the center, and score/level/next pieces on the right, with the board itself being 10 blocks wide by 20 tall at 30 pixels per block.\n\nWriting the game code... Setting up the canvas dimensions and layout with the board positioned at x=100, y=20, and defining the game constants like a 10×20 grid with 30px blocks, then establishing the color palette for each piece type.\n\nDefining the tetrominoes... Defining the rotation states for the remaining Tetris pieces... Finishing up the piece rotation definitions for the remaining Tetris blocks, then I'll move on to implementing the full game logic. For spawning, I need to position pieces at the top center of the board—around column 3 for the standard 3 and 4-wide pieces on a 10-column grid. Working out the spawn column formula using the matrix width, which gives column 3 for both 3×3 and 4×4 pieces on a 10-column board. For the Y position, pieces spawn at row 0 with their top blocks visible, though the I piece might need special handling since it starts partially off-screen. I'm going back and forth on the spawn position—standard Tetris has pieces appear with their top row off-screen, but for simplicity I'll just spawn them at y=0 so they're fully visible from the start. This keeps the implementation straightforward without losing playability. Writing the complete game implementation...\n\nI'm setting up the official Tetris guideline drop speeds for each level, starting with 1 second per row at level 1 and accelerating significantly as the level increases. Writing the complete game file... Soft drop gives points per cell, and I've got the full control scheme mapped out—rotations, hard drop, hold piece, and pause. Now I'm implementing a 7-bag randomizer to ensure balanced piece distribution, which is the standard Tetris approach.\n\nImplementing the piece bag... I'm planning out the visual design with a dark theme, piece preview and hold displays, and a ghost piece indicator. Now I need to structure the implementation—I'll create the HTML file with a centered canvas and instructions, then build out the game logic with collision detection, line clearing, scoring, and the main game loop with rendering and input 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\"\",\n5\t \"main\": \"index.js\",\n6\t \"scripts\": {\n7\t \"test\": \"echo \\\"Error: no test specified\\\" && exit 1\"\n8\t },\n9\t \"keywords\": [],\n10\t \"author\": \"\",\n11\t \"license\": \"ISC\",\n12\t \"type\": \"commonjs\",\n13\t \"devDependencies\": {\n14\t \"@eslint/js\": \"^10.0.1\",\n15\t \"@playwright/test\": \"^1.59.1\",\n16\t \"@types/node\": \"^25.5.2\",\n17\t \"eslint\": \"^10.2.0\",\n18\t \"typescript\": \"^6.0.2\"\n19\t }\n20\t}\n21\t"}]},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"1689f5e9-b827-4fa6-a8b5-397d31f22d1e","timestamp":"2026-04-04T09:30:54.321Z","tool_use_result":{"type":"text","file":{"filePath":"/tmp/loop-bench-nlkj6_tk/package.json","content":"{\n \"name\": \"loop-bench-nlkj6_tk\",\n \"version\": \"1.0.0\",\n \"description\": \"\",\n \"main\": \"index.js\",\n \"scripts\": {\n \"test\": \"echo \\\"Error: no test specified\\\" && exit 1\"\n },\n \"keywords\": [],\n \"author\": \"\",\n \"license\": \"ISC\",\n \"type\": \"commonjs\",\n \"devDependencies\": {\n \"@eslint/js\": \"^10.0.1\",\n \"@playwright/test\": \"^1.59.1\",\n \"@types/node\": \"^25.5.2\",\n \"eslint\": \"^10.2.0\",\n \"typescript\": \"^6.0.2\"\n }\n}\n","numLines":21,"startLine":1,"totalLines":21}}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01PrYMRh5F3KKre6aoK7d36W","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Good. TypeScript is already installed. Let me check if there's a `tsc` binary available.\n\nNow let me set up the project. I'll:\n1. Create `tsconfig.json`\n2. Create `src/game.ts`\n3. Create `index.html`\n4. Update `package.json` with build scripts\n\nLet me write everything out.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14462,"cache_read_input_tokens":4728,"cache_creation":{"ephemeral_5m_input_tokens":14462,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"5cac29c0-2816-4853-a3c1-472fd7f12f3d"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01PrYMRh5F3KKre6aoK7d36W","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MAfVWpt2FtrmSPNrawxWbU","name":"Bash","input":{"command":"ls /tmp/loop-bench-nlkj6_tk/node_modules/.bin/ | grep -E \"tsc|typescript\"","description":"Check for TypeScript compiler"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":14462,"cache_read_input_tokens":4728,"cache_creation":{"ephemeral_5m_input_tokens":14462,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"fef5b136-aaa2-4d3c-be7b-1ff77c1904aa"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MAfVWpt2FtrmSPNrawxWbU","type":"tool_result","content":"tsc","is_error":false}]},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"c427b7a7-2458-45b0-a4a7-204ca3eebd4f","timestamp":"2026-04-04T09:30:58.185Z","tool_use_result":{"stdout":"tsc","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01DZcLWYzJyWL62iRpV38KD6","type":"message","role":"assistant","content":[{"type":"text","text":"Good. Now let me build the full Tetris game. I'll create the TypeScript source, HTML, config, and compile it."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":214,"cache_read_input_tokens":19190,"cache_creation":{"ephemeral_5m_input_tokens":214,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"824fcfd2-66b7-4fb9-af4f-574fb221ecba"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01DZcLWYzJyWL62iRpV38KD6","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_018fF8srmh21QPwhY14J8qNX","name":"Bash","input":{"command":"mkdir -p /tmp/loop-bench-nlkj6_tk/src /tmp/loop-bench-nlkj6_tk/dist","description":"Create src and dist 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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_019ekYwTvheEZ2vbX5eqBGqj","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me write the full Tetris game TypeScript source:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":251,"cache_read_input_tokens":19557,"cache_creation":{"ephemeral_5m_input_tokens":251,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"e3a77d3f-3512-4e83-9be1-854b8a426427","uuid":"d8cf9969-ce53-45f5-a30c-8fcdb51f0b68"} 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/claude_output.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/claude_output.json @@ -0,0 +1 @@ +{"type":"result","subtype":"error_during_execution","duration_ms":479011,"duration_api_ms":92819,"is_error":true,"num_turns":2,"stop_reason":"max_tokens","session_id":"4e1490e6-de9b-476d-9d84-99445435fed6","total_cost_usd":0.1231038,"usage":{"input_tokens":3,"cache_creation_input_tokens":486,"cache_read_input_tokens":4241,"output_tokens":8000,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":486},"inference_geo":"","iterations":[],"speed":"standard"},"modelUsage":{"claude-sonnet-4-6":{"inputTokens":3,"outputTokens":8000,"cacheReadInputTokens":4241,"cacheCreationInputTokens":486,"webSearchRequests":0,"costUSD":0.1231038,"contextWindow":200000,"maxOutputTokens":32000}},"permission_denials":[],"terminal_reason":"aborted_streaming","fast_mode_state":"off","uuid":"dbc32059-14c6-4b22-b547-7eba9cd41479","errors":["[ede_diagnostic] result_type=user last_content_type=n/a stop_reason=max_tokens","Error: Request was aborted.\n at OE$ (/$bunfs/root/src/entrypoints/cli.js:1237:11929)\n at next (native:1:11)\n at vI7 (/$bunfs/root/src/entrypoints/cli.js:7634:9034)\n at next (native:1:11)\n at VI7 (/$bunfs/root/src/entrypoints/cli.js:7639:11078)\n at processTicksAndRejections (native:7:39)"]} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/eval_results.json @@ -0,0 +1,128 @@ +{ + "structural": { + "pass": false, + "checks": [ + { + "name": "entry_point_exists", + "pass": false, + "detail": "no index.html found in workspace root, dist/, or public/" + }, + { + "name": "package_json_exists", + "pass": true, + "detail": "package.json found" + }, + { + "name": "build_succeeds", + "pass": true, + "detail": "no build script defined (static project)" + } + ], + "score": 0.67 + }, + "functional": { + "pass": false, + "error": "playwright eval not yet wired", + "score": 0 + }, + "quality": { + "lint": { + "pass": true, + "errors": 0, + "warnings": 0 + }, + "typecheck": { + "pass": false, + "error": "no tsconfig.json" + }, + "performance": { + "bundle_size_bytes": 0, + "size_under_512kb": true + }, + "score": 0.33 + }, + "code_analysis": { + "files": { + "total": 2, + "code": 0, + "docs": 0, + "unnecessary": 0, + "unnecessary_list": [] + }, + "lines_of_code": 0, + "dependencies": { + "production": 0, + "dev": 5, + "total": 5 + }, + "complexity": "minimal", + "console_logs": 0, + "magic_numbers": { + "count": 0, + "excessive": false + }, + "function_length": { + "count": 0, + "average": 0, + "max": 0, + "long_functions": 0 + }, + "max_nesting_depth": 0, + "global_declarations": 0, + "naming": { + "dominant_style": "unknown", + "consistency_pct": 100.0, + "camel_case": 0, + "snake_case": 0 + }, + "error_handling": { + "try_catch_blocks": 0, + "has_error_handling": false + }, + "comments": { + "comment_lines": 0, + "source_lines": 0, + "ratio_pct": 0.0 + }, + "separation_of_concerns": { + "verdict": "single-file", + "files_with_rendering": 0, + "files_with_logic": 0, + "files_with_both": 0 + }, + "html_validation": { + "valid": false, + "errors": 0 + }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 6, + "tool_calls": { + "total": 0, + "bash": 0, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 1, + "text_blocks": 0, + "productivity_ratio": 0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0, + "error": "Report file not created. Exit code: -2. stderr: " + }, + "score": 0.583 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "off", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2", + "run_number": 2, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:33:39.496740+00:00", + "wall_time_seconds": 479, + "exit_code": 0, + "completed_at": "2026-04-04T09:41:44.388070+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run2/transcript.jsonl @@ -0,0 +1,6 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-usm085rl","session_id":"4e1490e6-de9b-476d-9d84-99445435fed6","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"c5b36cea-a921-4090-8106-40a9380ae868","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_014podt7GjgtPUnaDfDY6Wrz","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me build a complete Tetris game using TypeScript that runs in the browser. I'll create the following files:\n1. `index.html` - The main HTML file\n2. `src/tetris.ts` - The TypeScript source file\n3. `package.json` - For TypeScript compilation\n4. `tsconfig.json` - TypeScript configuration\n\nActually, since this needs to run in a browser, I can compile TypeScript to JavaScript. But let me think about the best approach - I could either:\n1. Use a build system like webpack/vite\n\n\n2. Use tsc directly and reference the compiled JS\n3. Use a CDN for TypeScript compilation in the browser\n\nI'll go with a straightforward setup: write TypeScript, compile it with tsc, and create a simple HTML file that references the compiled JavaScript. For the game itself, I'll implement standard Tetris pieces, rotation with wall kicks using the Super Rotation System, line clearing with scoring, progressive difficulty increases, and a hold piece feature.\n\nNow I'm mapping out the architecture. The game state will track the 10x20 board, current piece with its position and rotation, a queue of next pieces, the held piece, score and level metrics, and whether the game is playing, paused, or over. I'll define all the Tetris pieces with their SRS rotation states, then set up keyboard controls for movement, rotation in both directions, hard and soft drops, holding pieces, and pausing.\n\nWriting the TypeScript implementation... Defining the piece rotations... Defining the remaining Tetris piece rotations... Defining wall kick data... I'm getting caught up in the coordinate system details for wall kicks. Let me step back and implement the standard Tetris Guideline SRS offsets properly, being careful about how the coordinate system maps between math conventions and screen coordinates where y increases downward. I'll start with a cleaner, simpler approach using basic wall kick logic rather than trying to get every edge case perfect.\n\nSetting up the TypeScript implementation... Writing the game implementation... Defining the piece shapes... Defining the rotation states for the remaining Tetris pieces... Defining the wall kick offsets... I need to verify the wall kick offsets for the SRS system, since the coordinate system in my implementation has y increasing downward, but the standard Tetris reference uses y increasing upward. Let me check the Tetris Wiki to get the correct kick values and adjust them accordingly. I need to convert these rotation offsets to screen coordinates where y increases downward, so I'm flipping the y-values by multiplying by -1. For the I piece specifically, I'm working through the state transitions and their corresponding offset values. Rather than manually converting each one, I'll just implement this carefully using a grid coordinate system where row increases downward and column increases rightward, which naturally aligns with screen coordinates. I'm now converting all these rotation state transitions to screen coordinates by negating the y values, so I can properly apply them in the game's coordinate system. I'm verifying the rotation offsets for the I piece against the wiki reference, checking how the kick table values transform when rotating between states. Continuing to convert the rotation states to screen coordinates by negating the y-values for each transition state.\n\nActually, let me just implement this properly rather than manually working through all the rotation states. I'll write out a complete Tetris game with proper wall kick handling and all the UI elements I need—the game board, next piece preview, hold piece display, score tracking, and game over screen.\n\nWriting the implementation... Still writing styles... Still writing 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":486,"cache_read_input_tokens":4241,"cache_creation":{"ephemeral_5m_input_tokens":486,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"4e1490e6-de9b-476d-9d84-99445435fed6","uuid":"70470f25-782a-4a1a-932f-195983d2c5d3"} 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--git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/eval_results.json @@ -0,0 +1,254 @@ +{ + "structural": { + "pass": false, + "checks": [ + { + "name": "entry_point_exists", + "pass": false, + "detail": "no index.html found in workspace root, dist/, or public/" + }, + { + "name": "package_json_exists", + "pass": true, + "detail": "package.json found" + }, + { + "name": "build_succeeds", + "pass": true, + "detail": "no build script defined (static project)" + }, + { + "name": "typescript_compiles", + "pass": false, + "detail": "TypeScript files found but no tsconfig.json" + } + ], + "score": 0.5 + }, + "functional": { + "pass": false, + "error": "playwright eval not yet wired", + "score": 0 + }, + "quality": { + "lint": { + "pass": true, + "errors": 0, + "warnings": 0 + }, + "typecheck": { + "pass": false, + "error": "no tsconfig.json" + }, + "performance": { + "bundle_size_bytes": 0, + "size_under_512kb": true + }, + "score": 0.33 + }, + "code_analysis": { + "files": { + "total": 7, + "code": 5, + "docs": 0, + "unnecessary": 0, + "unnecessary_list": [] + }, + "lines_of_code": 545, + "dependencies": { + "production": 0, + "dev": 6, + "total": 6 + }, + "complexity": "moderate", + "console_logs": 0, + "magic_numbers": { + "count": 27, + "excessive": true + }, + "function_length": { + "count": 24, + "average": 4.8, + "max": 8, + "long_functions": 0 + }, + "max_nesting_depth": 6, + "global_declarations": 4, + "naming": { + "dominant_style": "camelCase", + "consistency_pct": 100.0, + "camel_case": 188, + "snake_case": 0 + }, + "error_handling": { + "try_catch_blocks": 0, + "has_error_handling": false + }, + "comments": { + "comment_lines": 44, + "source_lines": 433, + "ratio_pct": 10.2 + }, + "separation_of_concerns": { + "verdict": "separated", + "files_with_rendering": 1, + "files_with_logic": 4, + "files_with_both": 0 + }, + "html_validation": { + "valid": false, + "errors": 0 + }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 34, + "tool_calls": { + "total": 12, + "bash": 4, + "write": 0, + "edit": 7, + "read": 1 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 4, + "text_blocks": 3, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.06, + "total": 16, + "passed": 1, + "failed": 15, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "exception: page.waitForTimeout: Test ended." + }, + { + "name": "hard_drop", + "pass": false, + "detail": "exception: page.screenshot: Target page, context or browser has been closed" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "line_clear", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "score_changes", + "pass": false, + "detail": "exception: page.evaluate: Target page, context or browser has been closed" + }, + { + "name": "game_over", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "playable_30s", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + } + ], + "summary": { + "total": 16, + "passed": 1, + "failed": 15, + "score": 0.06 + }, + "gameplay": { + "pieces_placed": 10, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 0, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 20 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.572 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "exception: page.waitForTimeout: Test ended." + }, + { + "name": "hard_drop", + "pass": false, + "detail": "exception: page.screenshot: Target page, context or browser has been closed" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "line_clear", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "score_changes", + "pass": false, + "detail": "exception: page.evaluate: Target page, context or browser has been closed" + }, + { + "name": "game_over", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + }, + { + "name": "playable_30s", + "pass": false, + "detail": "exception: keyboard.press: Target page, context or browser has been closed" + } + ], + "summary": { + "total": 16, + "passed": 1, + "failed": 15, + "score": 0.06 + }, + "gameplay": { + "pieces_placed": 10, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 0, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 20 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/meta.json 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"max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3", + "run_number": 3, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:35:39.213608+00:00", + "wall_time_seconds": 331, + "exit_code": 1, + "completed_at": "2026-04-04T09:41:14.143593+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=off_tool_write=on_web_search=on_run3/transcript.jsonl @@ -0,0 +1,34 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-732u9ti4","session_id":"59856856-0d28-4626-b264-1712ed2b2c42","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"9ae098e5-5bc5-4c40-9497-cd62951a4df1","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01FR72bo6DEV945dm8jBTXiJ","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser, built with TypeScript. Let me create a complete Tetris game with all standard mechanics.\n\nI'll create:\n1. `index.html` - The main HTML file\n2. `src/tetris.ts` - The TypeScript source file\n3. `package.json` - Package configuration\n4. `tsconfig.json` - TypeScript configuration\n\nLet me plan the game:\n\n**Game mechanics:**\n- 7 standard Tetromino pieces (I, O, T, S, Z, J, L)\n- Piece rotation (with wall kicks)\n\n\n- Line clearing\n- Scoring (based on lines cleared at once)\n- Increasing speed (level progression)\n- Keyboard controls: Arrow keys for movement, Up arrow or Z for rotation\n\n**Architecture:**\n- Game board: 10x20 grid\n- Pieces with rotation states\n- Collision detection\n- Line clearing logic\n- Score/level system\n- Rendering with Canvas\n\nI need to decide on the best approach for getting this running in a browser. I could compile TypeScript with tsc and bundle it, or use a simpler self-contained approach that doesn't require a build step.\n\nI'll go with a proper TypeScript setup using package.json, tsconfig.json, and a source file, then build it for the browser. I'm planning a fully-featured Tetris implementation with Canvas rendering, ghost pieces to show landing positions, hold piece functionality, next piece preview, Nintendo-style scoring, level progression, and wall kick mechanics for rotation.\n\nWriting the Tetris game code... Defining the tetromino shapes...\n\nNow I'm planning out the full implementation with a Board class to manage the grid and collision detection, a Piece class for handling rotations and movements, and a Game class to orchestrate the game loop, handle input, and track scoring.\n\nWriting the TypeScript implementation... Defining the tetromino shapes and wall kick data for rotation mechanics... Defining the Piece class with shape, color, rotation, and initial position properties... I'm thinking through the project structure needed to run this in a browser—I'll need TypeScript compilation, so I'm setting up a `package.json`, `tsconfig.json`, and organizing the source files with an `index.html` entry point. For the actual game, I want to build something polished with canvas rendering, a ghost piece preview, hold and next piece queues showing the upcoming three pieces, proper SRS rotation with wall kicks, and a clean UI displaying score, level, and lines cleared. The layout will have the game canvas centered with a side panel for game info and instructions below.\n\nWriting the Tetris implementation... Defining the piece shapes... Setting up the game constants for a 10x20 grid with 30-pixel cells, and defining the color palette for each tetromino piece.\n\nDefining the tetromino shapes in their initial orientations as 2D grids where each number corresponds to a color index.\n\nNow I'm setting up the wall-kick tables for the SRS rotation system, which define how pieces adjust their position when they can't rotate in place. I'm realizing the wall kick data I had doesn't match the actual SRS specification, so let me pull up the correct rotation system offsets for JLSTZ pieces and verify each state transition. I'm continuing through the wall kick data for each rotation state, mapping out all the offset attempts for J, L, S, T, and Z pieces as they rotate through their four orientations. I'm mapping out the complete wall kick offsets for counter-clockwise rotations now, finishing the pattern for the remaining state transitions and confirming how the test sequences mirror the clockwise behavior with adjusted coordinates. Continuing with the I-piece counter-clockwise rotations, mapping out the wall kick offsets for each state transition through L and back to the origin. I need to account for the coordinate system difference between the wiki's convention where y increases upward and canvas where y increases downward. So I'll keep x the same but negate all the y values when converting the SRS rotation kick data to my implementation. I'm going to organize the wall kick data more cleanly by storing separate kick tables for each rotation state and direction, using standard SRS offset pairs where the column and row values represent the test positions to try during rotation attempts.\n\nDefining the kick tables... I'm referencing the SRS wiki data to get the correct wall kick offsets, converting from the standard coordinate system where y increases upward to canvas coordinates where y increases downward. I'll create a clean implementation using a map indexed by state transitions like '0>1' for clockwise and '1>0' for counterclockwise rotations.\n\nDefining the kick tables...","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":486,"cache_read_input_tokens":4241,"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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01LWp5Tvc6yptMAkzMHEuZWD","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me build a complete Tetris game in TypeScript that runs in the browser. I'll create a well-structured implementation with all the standard mechanics.\n\nLet me plan the structure:\n1. `index.html` - Main HTML file\n2. `src/tetris.ts` - Main TypeScript file with all game logic\n3. `package.json` - Package configuration\n4. `tsconfig.json` - TypeScript configuration\n\nActually, since this needs to run in a browser without a build step complexity, let me think about the best approach. I could:\n1. Use a simple approach with a single HTML file that includes TypeScript compiled inline\n\n\n2. Use a proper build setup with webpack or esbuild\n\nLet me go with a clean approach - I'll use esbuild for bundling or just compile with tsc and have a simple setup. For practicality, I'll create a modular structure with separate files for game logic and type definitions, then set up a canvas-based rendering system. I'm planning a standard 10×20 board with the classic Tetris pieces.\n\nThe game will include rotation with wall kicks, line clearing with progressive difficulty, a hold mechanic, ghost piece preview, and next piece display. Scoring scales with level - single lines worth 100 points per level, up to 800 for a Tetris. Controls map to arrow keys for movement and rotation, space for hard drop, and C for holding pieces.\n\nNow I'm writing out the TypeScript implementation...\n\nSetting up the file structure... Defining the tetromino shapes and rotation system... Defining the remaining tetromino shapes...\n\nActually, I think I should restructure this more cleanly. Instead of keeping everything in one file, I'll split it into separate modules for constants, types, game logic, rendering, and the main entry point. This will make the code more maintainable and easier to test. Let me sketch out a file structure with TypeScript configuration and then write out the complete implementation. I'm settling on npm with esbuild for the build system, and I'll set up a package.json with a build script so everything compiles properly. Now I'm writing out all the files—the HTML structure, TypeScript configuration, game constants, type definitions, tetromino logic, board management, canvas rendering, core game loop, and the entry point.\n\nWriting the HTML and configuration files...\n\nFor the visual design, I'm using the classic Tetris color palette for each piece type, and the board will render with dark backgrounds for empty cells, colored blocks for filled cells, a translucent ghost piece preview, and subtle grid lines. The side panels will display the next piece and score information.\n\nNow I'm mapping out the controls—arrow keys for movement, space for hard drop, C for hold, and various rotation options. I'm going to implement the core mechanics cleanly: wall kicks for rotation, ghost piece rendering, hold functionality with proper state management, level progression, and lock delay so pieces don't instantly lock when they hit the ground.\n\nWriting the game logic... I'm organizing the implementation into separate modules for types, constants, tetrominoes, board logic, rendering, and the main game class. For the renderer, I'll set up a main canvas for the 10×20 board, plus separate canvases for the hold piece and next pieces queue.\n\nWriting HTML and styles... Still writing styles...\n\nNow I'm setting up the game board with a 10×20 grid and 30-pixel blocks, which gives me a 300×600 canvas. I'll use separate canvases for the hold and next piece previews on the side panels, and I need to be careful about piece spawning positions and rotation mechanics.\n\nDefining the TypeScript types...\n\nI'm switching the board representation to use numeric values instead of null—0 for empty cells and 1-7 to represent each tetromino type, which makes color mapping more efficient. I'll set up a colors array indexed by these values to handle rendering.\n\nDefining the rotation states for each tetromino using standard SRS notation...\n\nNow I'm working through the wall kick offsets—for most pieces I'll try the standard sequence of column shifts, but for the I piece I need to account for its larger rotation radius by testing additional offsets. I'm laying out the I-piece kick offsets for each rotation state, but I realize I should just implement the standard SRS kick table directly rather than deriving it myself. Let me use the proper Tetris Guideline specification with my coordinate system where x goes right and y goes down. I'm completing the rotation test cases and now working through the counter-clockwise logic, which reverses the clockwise offsets for each state transition.\n\nDefining the wall kick data... I'm laying out the complete SRS rotation offset tables for the JLSTZ pieces, mapping each state transition with their corresponding kick offsets, and I need to account for the coordinate system difference where y increases upward in the standard documentation. Now I'm converting the SRS rotation offsets to my coordinate system where y increases downward, so I negate all the y values. I'm working through each rotation state and its transitions, mapping out the kick test offsets for 0→1, 1→0, 1→2, 2→1, and 2→3 rotations.\n\nActually, let me step back and use a more practical approach: for standard pieces I'll test offsets starting with no movement, then try horizontal shifts in both directions, vertical adjustments, and diagonal kicks. For the I piece I'll extend the search range to include ±2 offsets since it needs more space to rotate. I'm working through the rotation state transitions for JLSTZ pieces, converting between coordinate systems to make sure the kick offsets are correct in screen space with y-down orientation. I'm pulling the standard SRS rotation offsets directly from Tetris Wiki—these are the test positions for JLSTZ pieces across all four rotation states, with the coordinate system where positive x goes right and positive y goes down on screen. I'm laying out the rotation offset data for the Tetris pieces and now I'm ready to implement this in code.\n\nWriting the game implementation...","signature":"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TypeScript is already available. I need to set up the build with esbuild or just use tsc. Let me check if esbuild is available or if I should add it.\n\nActually, since `typescript` is already installed, I can use `tsc`. But `tsc` compiles individual files and doesn't bundle them. For a browser app, I need a bundler. Let me add esbuild.\n\nOr I could use the `--outfile` option with `tsc` but that still doesn't bundle multiple files. I'd need a bundler.\n\nLet me add esbuild as a dependency. \n\nI could simplify this by writing everything in a single TypeScript file and compiling it directly with tsc, avoiding bundler complexity altogether. But esbuild is cleaner and faster for this kind of project. 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for details\n\nfound 0 vulnerabilities","is_error":false}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"f5412ffb-f1d1-43be-a409-c064e983f25f","timestamp":"2026-04-04T09:39:23.857Z","tool_use_result":{"stdout":"17 packages are looking for funding\n run `npm fund` for details\n\nfound 0 vulnerabilities","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01EeBSVZnFWeQ6KELcJhiU7k","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me build the full Tetris game. I'll create a well-structured multi-file TypeScript project:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":126,"cache_read_input_tokens":13971,"cache_creation":{"ephemeral_5m_input_tokens":126,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"25ac167e-78a7-445a-b328-99e4fd80039c"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01EeBSVZnFWeQ6KELcJhiU7k","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01J33jhhoobPK3JTvPkFyZVk","name":"Bash","input":{"command":"mkdir -p /tmp/loop-bench-732u9ti4/src","description":"Create src directory"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":126,"cache_read_input_tokens":13971,"cache_creation":{"ephemeral_5m_input_tokens":126,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"28d8e858-4c7b-45c3-9b7f-156da9255171"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01J33jhhoobPK3JTvPkFyZVk","type":"tool_result","content":"(Bash completed with no output)","is_error":false}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"bf48ff9d-9fec-4c79-b1bf-abf2350c64b9","timestamp":"2026-04-04T09:39:27.878Z","tool_use_result":{"stdout":"","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":true}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01UAp9bQdGTLLxxaZhYd7JUo","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01X1oFDTdBUfFYoR8xk48ULn","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/types.ts","old_string":"","new_string":"export type TetrominoType = 'I' | 'O' | 'T' | 'S' | 'Z' | 'J' | 'L';\n\nexport type Cell = TetrominoType | null;\n\nexport type Matrix = number[][];\n\nexport interface Position {\n x: number;\n y: number;\n}\n\nexport interface Piece {\n type: TetrominoType;\n matrix: Matrix;\n pos: Position;\n rotation: number; // 0 | 1 | 2 | 3\n}\n\nexport interface GameStats {\n score: number;\n lines: number;\n level: number;\n}\n\nexport type GamePhase = 'idle' | 'playing' | 'paused' | 'gameover';\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":131,"cache_read_input_tokens":14097,"cache_creation":{"ephemeral_5m_input_tokens":131,"ephemeral_1h_input_tokens":0},"output_tokens":53,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"8c86e036-68a8-4aa0-bdf7-d7d3bd3d7348"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01X1oFDTdBUfFYoR8xk48ULn","type":"tool_result","content":"The file /tmp/loop-bench-732u9ti4/src/types.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"94e7b4a9-677c-4b57-be51-6fbd57845e9c","timestamp":"2026-04-04T09:39:37.944Z","tool_use_result":{"filePath":"/tmp/loop-bench-732u9ti4/src/types.ts","oldString":"","newString":"export type TetrominoType = 'I' | 'O' | 'T' | 'S' | 'Z' | 'J' | 'L';\n\nexport type Cell = TetrominoType | null;\n\nexport type Matrix = number[][];\n\nexport interface Position {\n x: number;\n y: number;\n}\n\nexport interface Piece {\n type: TetrominoType;\n matrix: Matrix;\n pos: Position;\n rotation: number; // 0 | 1 | 2 | 3\n}\n\nexport interface GameStats {\n score: number;\n lines: number;\n level: number;\n}\n\nexport type GamePhase = 'idle' | 'playing' | 'paused' | 'gameover';\n","originalFile":"","structuredPatch":[{"oldStart":1,"oldLines":0,"newStart":1,"newLines":25,"lines":["+export type TetrominoType = 'I' | 'O' | 'T' | 'S' | 'Z' | 'J' | 'L';","+","+export type Cell = TetrominoType | null;","+","+export type Matrix = number[][];","+","+export interface Position {","+ x: number;","+ y: number;","+}","+","+export interface Piece {","+ type: TetrominoType;","+ matrix: Matrix;","+ pos: Position;","+ rotation: number; // 0 | 1 | 2 | 3","+}","+","+export interface GameStats {","+ score: number;","+ lines: number;","+ level: number;","+}","+","+export type GamePhase = 'idle' | 'playing' | 'paused' | 'gameover';"]}],"userModified":false,"replaceAll":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01JyWibU7K3v7THgnzcgQnDN","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_017BY85n83BGk7U6RqjK7DkM","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/constants.ts","old_string":"","new_string":"export const COLS = 10;\nexport const ROWS = 20;\nexport const BLOCK_SIZE = 30;\nexport const PREVIEW_BLOCK_SIZE = 24;\n\n// Tetromino colors (index 0 = empty)\nexport const COLORS: readonly string[] = [\n 'transparent', // 0: empty\n '#00F0F0', // 1: I — cyan\n '#F0F000', // 2: O — yellow\n '#A000F0', // 3: T — purple\n '#00F000', // 4: S — green\n '#F00000', // 5: Z — red\n '#0000F0', // 6: J — blue\n '#F0A000', // 7: L — orange\n];\n\nexport const TYPE_TO_ID: Record<string, number> = {\n I: 1, O: 2, T: 3, S: 4, Z: 5, J: 6, L: 7,\n};\n\n// Points awarded per line clear at level 1 (multiply by level)\nexport const LINE_SCORES: readonly number[] = [0, 100, 300, 500, 800];\n\n// Lines needed per level\nexport const LINES_PER_LEVEL = 10;\n\n// Frames per gravity drop at each level (60 fps reference)\nexport const GRAVITY_FRAMES: readonly number[] = [\n 48, 43, 38, 33, 28, 23, 18, 13, 8, 6, // levels 1–10\n 5, 5, 5, 4, 4, 4, 3, 3, 3, 2, // levels 11–20\n 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, // levels 21–30\n];\n\nexport const LOCK_DELAY_MS = 500;\nexport const MAX_LOCK_MOVES = 15;\n\n// DAS (Delayed Auto Shift) settings\nexport const DAS_DELAY_MS = 167; // delay before auto-repeat\nexport const DAS_REPEAT_MS = 33; // repeat interval (~30 Hz)\n\n// SRS wall kick data for JLSTZ pieces\n// Each entry: [dx, dy] in screen coords (y increases downward)\n// Key format: \"fromRotation->toRotation\"\nexport const JLSTZ_KICKS: Record<string, [number, number][]> = {\n '0->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]],\n '1->0': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]],\n '1->2': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]],\n '2->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]],\n '2->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]],\n '3->2': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]],\n '3->0': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]],\n '0->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]],\n};\n\n// SRS wall kick data for I piece\nexport const I_KICKS: Record<string, [number, number][]> = {\n '0->1': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]],\n '1->0': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]],\n '1->2': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]],\n '2->1': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]],\n '2->3': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]],\n '3->2': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]],\n '3->0': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]],\n '0->3': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]],\n};\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":348,"cache_read_input_tokens":14228,"cache_creation":{"ephemeral_5m_input_tokens":348,"ephemeral_1h_input_tokens":0},"output_tokens":62,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"b8fa0596-a2b8-4f01-a6e5-1a4a6dabcc96"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_017BY85n83BGk7U6RqjK7DkM","type":"tool_result","content":"The file /tmp/loop-bench-732u9ti4/src/constants.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"e91da6fb-6412-4dec-b23e-b6dbd5fe9bbe","timestamp":"2026-04-04T09:39:57.115Z","tool_use_result":{"filePath":"/tmp/loop-bench-732u9ti4/src/constants.ts","oldString":"","newString":"export const COLS = 10;\nexport const ROWS = 20;\nexport const BLOCK_SIZE = 30;\nexport const PREVIEW_BLOCK_SIZE = 24;\n\n// Tetromino colors (index 0 = empty)\nexport const COLORS: readonly string[] = [\n 'transparent', // 0: empty\n '#00F0F0', // 1: I — cyan\n '#F0F000', // 2: O — yellow\n '#A000F0', // 3: T — purple\n '#00F000', // 4: S — green\n '#F00000', // 5: Z — red\n '#0000F0', // 6: J — blue\n '#F0A000', // 7: L — orange\n];\n\nexport const TYPE_TO_ID: Record<string, number> = {\n I: 1, O: 2, T: 3, S: 4, Z: 5, J: 6, L: 7,\n};\n\n// Points awarded per line clear at level 1 (multiply by level)\nexport const LINE_SCORES: readonly number[] = [0, 100, 300, 500, 800];\n\n// Lines needed per level\nexport const LINES_PER_LEVEL = 10;\n\n// Frames per gravity drop at each level (60 fps reference)\nexport const GRAVITY_FRAMES: readonly number[] = [\n 48, 43, 38, 33, 28, 23, 18, 13, 8, 6, // levels 1–10\n 5, 5, 5, 4, 4, 4, 3, 3, 3, 2, // levels 11–20\n 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, // levels 21–30\n];\n\nexport const LOCK_DELAY_MS = 500;\nexport const MAX_LOCK_MOVES = 15;\n\n// DAS (Delayed Auto Shift) settings\nexport const DAS_DELAY_MS = 167; // delay before auto-repeat\nexport const DAS_REPEAT_MS = 33; // repeat interval (~30 Hz)\n\n// SRS wall kick data for JLSTZ pieces\n// Each entry: [dx, dy] in screen coords (y increases downward)\n// Key format: \"fromRotation->toRotation\"\nexport const JLSTZ_KICKS: Record<string, [number, number][]> = {\n '0->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]],\n '1->0': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]],\n '1->2': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]],\n '2->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]],\n '2->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]],\n '3->2': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]],\n '3->0': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]],\n '0->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]],\n};\n\n// SRS wall kick data for I piece\nexport const I_KICKS: Record<string, [number, number][]> = {\n '0->1': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]],\n '1->0': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]],\n '1->2': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]],\n '2->1': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]],\n '2->3': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]],\n '3->2': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]],\n '3->0': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]],\n '0->3': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]],\n};\n","originalFile":"","structuredPatch":[{"oldStart":1,"oldLines":0,"newStart":1,"newLines":66,"lines":["+export const COLS = 10;","+export const ROWS = 20;","+export const BLOCK_SIZE = 30;","+export const PREVIEW_BLOCK_SIZE = 24;","+","+// Tetromino colors (index 0 = empty)","+export const COLORS: readonly string[] = [","+ 'transparent', // 0: empty","+ '#00F0F0', // 1: I — cyan","+ '#F0F000', // 2: O — yellow","+ '#A000F0', // 3: T — purple","+ '#00F000', // 4: S — green","+ '#F00000', // 5: Z — red","+ '#0000F0', // 6: J — blue","+ '#F0A000', // 7: L — orange","+];","+","+export const TYPE_TO_ID: Record<string, number> = {","+ I: 1, O: 2, T: 3, S: 4, Z: 5, J: 6, L: 7,","+};","+","+// Points awarded per line clear at level 1 (multiply by level)","+export const LINE_SCORES: readonly number[] = [0, 100, 300, 500, 800];","+","+// Lines needed per level","+export const LINES_PER_LEVEL = 10;","+","+// Frames per gravity drop at each level (60 fps reference)","+export const GRAVITY_FRAMES: readonly number[] = [","+ 48, 43, 38, 33, 28, 23, 18, 13, 8, 6, // levels 1–10","+ 5, 5, 5, 4, 4, 4, 3, 3, 3, 2, // levels 11–20","+ 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, // levels 21–30","+];","+","+export const LOCK_DELAY_MS = 500;","+export const MAX_LOCK_MOVES = 15;","+","+// DAS (Delayed Auto Shift) settings","+export const DAS_DELAY_MS = 167; // delay before auto-repeat","+export const DAS_REPEAT_MS = 33; // repeat interval (~30 Hz)","+","+// SRS wall kick data for JLSTZ pieces","+// Each entry: [dx, dy] in screen coords (y increases downward)","+// Key format: \"fromRotation->toRotation\"","+export const JLSTZ_KICKS: Record<string, [number, number][]> = {","+ '0->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]],","+ '1->0': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]],","+ '1->2': [[ 0, 0], [ 1, 0], [ 1,-1], [ 0, 2], [ 1, 2]],","+ '2->1': [[ 0, 0], [-1, 0], [-1, 1], [ 0,-2], [-1,-2]],","+ '2->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]],","+ '3->2': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]],","+ '3->0': [[ 0, 0], [-1, 0], [-1,-1], [ 0, 2], [-1, 2]],","+ '0->3': [[ 0, 0], [ 1, 0], [ 1, 1], [ 0,-2], [ 1,-2]],","+};","+","+// SRS wall kick data for I piece","+export const I_KICKS: Record<string, [number, number][]> = {","+ '0->1': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]],","+ '1->0': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]],","+ '1->2': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]],","+ '2->1': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]],","+ '2->3': [[ 0, 0], [ 2, 0], [-1, 0], [ 2, 1], [-1,-2]],","+ '3->2': [[ 0, 0], [-2, 0], [ 1, 0], [-2,-1], [ 1, 2]],","+ '3->0': [[ 0, 0], [ 1, 0], [-2, 0], [ 1,-2], [-2, 1]],","+ '0->3': [[ 0, 0], [-1, 0], [ 2, 0], [-1, 2], [ 2,-1]],","+};"]}],"userModified":false,"replaceAll":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_013htLLiVCRgCkiacYG2LFKG","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Nu9d3B1hTJLrjqMBKjcEQa","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/tetromino.ts","old_string":"","new_string":"import { Matrix, Piece, Position, TetrominoType } from './types';\nimport { COLS, I_KICKS, JLSTZ_KICKS, TYPE_TO_ID } from './constants';\n\n// Canonical rotation state 0 matrices for each piece type\nconst PIECE_MATRICES: Record<TetrominoType, Matrix> = {\n I: [\n [0, 0, 0, 0],\n [1, 1, 1, 1],\n [0, 0, 0, 0],\n [0, 0, 0, 0],\n ],\n O: [\n [0, 1, 1, 0],\n [0, 1, 1, 0],\n [0, 0, 0, 0],\n ],\n T: [\n [0, 1, 0],\n [1, 1, 1],\n [0, 0, 0],\n ],\n S: [\n [0, 1, 1],\n [1, 1, 0],\n [0, 0, 0],\n ],\n Z: [\n [1, 1, 0],\n [0, 1, 1],\n [0, 0, 0],\n ],\n J: [\n [1, 0, 0],\n [1, 1, 1],\n [0, 0, 0],\n ],\n L: [\n [0, 0, 1],\n [1, 1, 1],\n [0, 0, 0],\n ],\n};\n\n/** Rotate a matrix 90° clockwise */\nexport function rotateMatrixCW(matrix: Matrix): Matrix {\n const N = matrix.length;\n const M = matrix[0].length;\n const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0));\n for (let r = 0; r < N; r++) {\n for (let c = 0; c < M; c++) {\n result[c][N - 1 - r] = matrix[r][c];\n }\n }\n return result;\n}\n\n/** Rotate a matrix 90° counter-clockwise */\nexport function rotateMatrixCCW(matrix: Matrix): Matrix {\n const N = matrix.length;\n const M = matrix[0].length;\n const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0));\n for (let r = 0; r < N; r++) {\n for (let c = 0; c < M; c++) {\n result[M - 1 - c][r] = matrix[r][c];\n }\n }\n return result;\n}\n\n/** Build the rotation-state matrix for a piece at a given rotation (0–3) */\nexport function buildMatrix(type: TetrominoType, rotation: number): Matrix {\n let mat = PIECE_MATRICES[type].map(row => [...row]);\n for (let i = 0; i < (rotation % 4 + 4) % 4; i++) {\n mat = rotateMatrixCW(mat);\n }\n return mat;\n}\n\n/** Create a new piece at its spawn position */\nexport function createPiece(type: TetrominoType): Piece {\n const matrix = buildMatrix(type, 0);\n const spawnX = Math.floor((COLS - matrix[0].length) / 2);\n // Spawn above visible field (y = -1 for pieces that appear at top)\n const spawnY = type === 'I' ? -1 : 0;\n return { type, matrix, pos: { x: spawnX, y: spawnY }, rotation: 0 };\n}\n\n/**\n * Try to rotate a piece clockwise or counter-clockwise.\n * Returns the new Piece if a valid position is found, or null on failure.\n */\nexport function tryRotate(\n piece: Piece,\n direction: 'CW' | 'CCW',\n board: number[][]\n): Piece | null {\n const newRotation = direction === 'CW'\n ? (piece.rotation + 1) % 4\n : (piece.rotation + 3) % 4;\n\n const newMatrix = direction === 'CW'\n ? rotateMatrixCW(piece.matrix)\n : rotateMatrixCCW(piece.matrix);\n\n const kickKey = `${piece.rotation}->${newRotation}`;\n const kickTable = piece.type === 'I' ? I_KICKS : JLSTZ_KICKS;\n const kicks = piece.type === 'O' ? [[0, 0]] : (kickTable[kickKey] ?? [[0, 0]]);\n\n for (const [dx, dy] of kicks) {\n const testPos: Position = { x: piece.pos.x + dx, y: piece.pos.y + dy };\n if (!hasCollision(newMatrix, testPos, board)) {\n return { ...piece, matrix: newMatrix, pos: testPos, rotation: newRotation };\n }\n }\n return null; // rotation failed\n}\n\n/** Check if a matrix at a given position collides with the board or walls */\nexport function hasCollision(matrix: Matrix, pos: Position, board: number[][]): boolean {\n for (let r = 0; r < matrix.length; r++) {\n for (let c = 0; c < matrix[r].length; c++) {\n if (!matrix[r][c]) continue;\n const boardX = pos.x + c;\n const boardY = pos.y + r;\n if (boardX < 0 || boardX >= COLS) return true;\n if (boardY >= board.length) return true;\n if (boardY >= 0 && board[boardY][boardX]) return true;\n }\n }\n return false;\n}\n\n/** Get the filled cell value for a tetromino type */\nexport function typeToId(type: TetrominoType): number {\n return TYPE_TO_ID[type];\n}\n\n/** Return a randomly chosen tetromino type */\nexport function randomType(): TetrominoType {\n const types: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L'];\n return types[Math.floor(Math.random() * types.length)];\n}\n\n/** 7-bag randomiser: returns a shuffled bag of all 7 pieces */\nexport function newBag(): TetrominoType[] {\n const bag: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L'];\n for (let i = bag.length - 1; i > 0; i--) {\n const j = Math.floor(Math.random() * (i + 1));\n [bag[i], bag[j]] = [bag[j], bag[i]];\n }\n return bag;\n}\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1466,"cache_read_input_tokens":14576,"cache_creation":{"ephemeral_5m_input_tokens":1466,"ephemeral_1h_input_tokens":0},"output_tokens":65,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"92f2bdf0-1ef1-48e0-a6c2-c0330de79c5d"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Nu9d3B1hTJLrjqMBKjcEQa","type":"tool_result","content":"The file /tmp/loop-bench-732u9ti4/src/tetromino.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"5574c45e-b685-436f-bc1e-a8bfd2962fbf","timestamp":"2026-04-04T09:40:18.067Z","tool_use_result":{"filePath":"/tmp/loop-bench-732u9ti4/src/tetromino.ts","oldString":"","newString":"import { Matrix, Piece, Position, TetrominoType } from './types';\nimport { COLS, I_KICKS, JLSTZ_KICKS, TYPE_TO_ID } from './constants';\n\n// Canonical rotation state 0 matrices for each piece type\nconst PIECE_MATRICES: Record<TetrominoType, Matrix> = {\n I: [\n [0, 0, 0, 0],\n [1, 1, 1, 1],\n [0, 0, 0, 0],\n [0, 0, 0, 0],\n ],\n O: [\n [0, 1, 1, 0],\n [0, 1, 1, 0],\n [0, 0, 0, 0],\n ],\n T: [\n [0, 1, 0],\n [1, 1, 1],\n [0, 0, 0],\n ],\n S: [\n [0, 1, 1],\n [1, 1, 0],\n [0, 0, 0],\n ],\n Z: [\n [1, 1, 0],\n [0, 1, 1],\n [0, 0, 0],\n ],\n J: [\n [1, 0, 0],\n [1, 1, 1],\n [0, 0, 0],\n ],\n L: [\n [0, 0, 1],\n [1, 1, 1],\n [0, 0, 0],\n ],\n};\n\n/** Rotate a matrix 90° clockwise */\nexport function rotateMatrixCW(matrix: Matrix): Matrix {\n const N = matrix.length;\n const M = matrix[0].length;\n const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0));\n for (let r = 0; r < N; r++) {\n for (let c = 0; c < M; c++) {\n result[c][N - 1 - r] = matrix[r][c];\n }\n }\n return result;\n}\n\n/** Rotate a matrix 90° counter-clockwise */\nexport function rotateMatrixCCW(matrix: Matrix): Matrix {\n const N = matrix.length;\n const M = matrix[0].length;\n const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0));\n for (let r = 0; r < N; r++) {\n for (let c = 0; c < M; c++) {\n result[M - 1 - c][r] = matrix[r][c];\n }\n }\n return result;\n}\n\n/** Build the rotation-state matrix for a piece at a given rotation (0–3) */\nexport function buildMatrix(type: TetrominoType, rotation: number): Matrix {\n let mat = PIECE_MATRICES[type].map(row => [...row]);\n for (let i = 0; i < (rotation % 4 + 4) % 4; i++) {\n mat = rotateMatrixCW(mat);\n }\n return mat;\n}\n\n/** Create a new piece at its spawn position */\nexport function createPiece(type: TetrominoType): Piece {\n const matrix = buildMatrix(type, 0);\n const spawnX = Math.floor((COLS - matrix[0].length) / 2);\n // Spawn above visible field (y = -1 for pieces that appear at top)\n const spawnY = type === 'I' ? -1 : 0;\n return { type, matrix, pos: { x: spawnX, y: spawnY }, rotation: 0 };\n}\n\n/**\n * Try to rotate a piece clockwise or counter-clockwise.\n * Returns the new Piece if a valid position is found, or null on failure.\n */\nexport function tryRotate(\n piece: Piece,\n direction: 'CW' | 'CCW',\n board: number[][]\n): Piece | null {\n const newRotation = direction === 'CW'\n ? (piece.rotation + 1) % 4\n : (piece.rotation + 3) % 4;\n\n const newMatrix = direction === 'CW'\n ? rotateMatrixCW(piece.matrix)\n : rotateMatrixCCW(piece.matrix);\n\n const kickKey = `${piece.rotation}->${newRotation}`;\n const kickTable = piece.type === 'I' ? I_KICKS : JLSTZ_KICKS;\n const kicks = piece.type === 'O' ? [[0, 0]] : (kickTable[kickKey] ?? [[0, 0]]);\n\n for (const [dx, dy] of kicks) {\n const testPos: Position = { x: piece.pos.x + dx, y: piece.pos.y + dy };\n if (!hasCollision(newMatrix, testPos, board)) {\n return { ...piece, matrix: newMatrix, pos: testPos, rotation: newRotation };\n }\n }\n return null; // rotation failed\n}\n\n/** Check if a matrix at a given position collides with the board or walls */\nexport function hasCollision(matrix: Matrix, pos: Position, board: number[][]): boolean {\n for (let r = 0; r < matrix.length; r++) {\n for (let c = 0; c < matrix[r].length; c++) {\n if (!matrix[r][c]) continue;\n const boardX = pos.x + c;\n const boardY = pos.y + r;\n if (boardX < 0 || boardX >= COLS) return true;\n if (boardY >= board.length) return true;\n if (boardY >= 0 && board[boardY][boardX]) return true;\n }\n }\n return false;\n}\n\n/** Get the filled cell value for a tetromino type */\nexport function typeToId(type: TetrominoType): number {\n return TYPE_TO_ID[type];\n}\n\n/** Return a randomly chosen tetromino type */\nexport function randomType(): TetrominoType {\n const types: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L'];\n return types[Math.floor(Math.random() * types.length)];\n}\n\n/** 7-bag randomiser: returns a shuffled bag of all 7 pieces */\nexport function newBag(): TetrominoType[] {\n const bag: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L'];\n for (let i = bag.length - 1; i > 0; i--) {\n const j = Math.floor(Math.random() * (i + 1));\n [bag[i], bag[j]] = [bag[j], bag[i]];\n }\n return bag;\n}\n","originalFile":"","structuredPatch":[{"oldStart":1,"oldLines":0,"newStart":1,"newLines":152,"lines":["+import { Matrix, Piece, Position, TetrominoType } from './types';","+import { COLS, I_KICKS, JLSTZ_KICKS, TYPE_TO_ID } from './constants';","+","+// Canonical rotation state 0 matrices for each piece type","+const PIECE_MATRICES: Record<TetrominoType, Matrix> = {","+ I: [","+ [0, 0, 0, 0],","+ [1, 1, 1, 1],","+ [0, 0, 0, 0],","+ [0, 0, 0, 0],","+ ],","+ O: [","+ [0, 1, 1, 0],","+ [0, 1, 1, 0],","+ [0, 0, 0, 0],","+ ],","+ T: [","+ [0, 1, 0],","+ [1, 1, 1],","+ [0, 0, 0],","+ ],","+ S: [","+ [0, 1, 1],","+ [1, 1, 0],","+ [0, 0, 0],","+ ],","+ Z: [","+ [1, 1, 0],","+ [0, 1, 1],","+ [0, 0, 0],","+ ],","+ J: [","+ [1, 0, 0],","+ [1, 1, 1],","+ [0, 0, 0],","+ ],","+ L: [","+ [0, 0, 1],","+ [1, 1, 1],","+ [0, 0, 0],","+ ],","+};","+","+/** Rotate a matrix 90° clockwise */","+export function rotateMatrixCW(matrix: Matrix): Matrix {","+ const N = matrix.length;","+ const M = matrix[0].length;","+ const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0));","+ for (let r = 0; r < N; r++) {","+ for (let c = 0; c < M; c++) {","+ result[c][N - 1 - r] = matrix[r][c];","+ }","+ }","+ return result;","+}","+","+/** Rotate a matrix 90° counter-clockwise */","+export function rotateMatrixCCW(matrix: Matrix): Matrix {","+ const N = matrix.length;","+ const M = matrix[0].length;","+ const result: Matrix = Array.from({ length: M }, () => Array(N).fill(0));","+ for (let r = 0; r < N; r++) {","+ for (let c = 0; c < M; c++) {","+ result[M - 1 - c][r] = matrix[r][c];","+ }","+ }","+ return result;","+}","+","+/** Build the rotation-state matrix for a piece at a given rotation (0–3) */","+export function buildMatrix(type: TetrominoType, rotation: number): Matrix {","+ let mat = PIECE_MATRICES[type].map(row => [...row]);","+ for (let i = 0; i < (rotation % 4 + 4) % 4; i++) {","+ mat = rotateMatrixCW(mat);","+ }","+ return mat;","+}","+","+/** Create a new piece at its spawn position */","+export function createPiece(type: TetrominoType): Piece {","+ const matrix = buildMatrix(type, 0);","+ const spawnX = Math.floor((COLS - matrix[0].length) / 2);","+ // Spawn above visible field (y = -1 for pieces that appear at top)","+ const spawnY = type === 'I' ? -1 : 0;","+ return { type, matrix, pos: { x: spawnX, y: spawnY }, rotation: 0 };","+}","+","+/**","+ * Try to rotate a piece clockwise or counter-clockwise.","+ * Returns the new Piece if a valid position is found, or null on failure.","+ */","+export function tryRotate(","+ piece: Piece,","+ direction: 'CW' | 'CCW',","+ board: number[][]","+): Piece | null {","+ const newRotation = direction === 'CW'","+ ? (piece.rotation + 1) % 4","+ : (piece.rotation + 3) % 4;","+","+ const newMatrix = direction === 'CW'","+ ? rotateMatrixCW(piece.matrix)","+ : rotateMatrixCCW(piece.matrix);","+","+ const kickKey = `${piece.rotation}->${newRotation}`;","+ const kickTable = piece.type === 'I' ? I_KICKS : JLSTZ_KICKS;","+ const kicks = piece.type === 'O' ? [[0, 0]] : (kickTable[kickKey] ?? [[0, 0]]);","+","+ for (const [dx, dy] of kicks) {","+ const testPos: Position = { x: piece.pos.x + dx, y: piece.pos.y + dy };","+ if (!hasCollision(newMatrix, testPos, board)) {","+ return { ...piece, matrix: newMatrix, pos: testPos, rotation: newRotation };","+ }","+ }","+ return null; // rotation failed","+}","+","+/** Check if a matrix at a given position collides with the board or walls */","+export function hasCollision(matrix: Matrix, pos: Position, board: number[][]): boolean {","+ for (let r = 0; r < matrix.length; r++) {","+ for (let c = 0; c < matrix[r].length; c++) {","+ if (!matrix[r][c]) continue;","+ const boardX = pos.x + c;","+ const boardY = pos.y + r;","+ if (boardX < 0 || boardX >= COLS) return true;","+ if (boardY >= board.length) return true;","+ if (boardY >= 0 && board[boardY][boardX]) return true;","+ }","+ }","+ return false;","+}","+","+/** Get the filled cell value for a tetromino type */","+export function typeToId(type: TetrominoType): number {","+ return TYPE_TO_ID[type];","+}","+","+/** Return a randomly chosen tetromino type */","+export function randomType(): TetrominoType {","+ const types: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L'];","+ return types[Math.floor(Math.random() * types.length)];","+}","+","+/** 7-bag randomiser: returns a shuffled bag of all 7 pieces */","+export function newBag(): TetrominoType[] {","+ const bag: TetrominoType[] = ['I', 'O', 'T', 'S', 'Z', 'J', 'L'];","+ for (let i = bag.length - 1; i > 0; i--) {","+ const j = Math.floor(Math.random() * (i + 1));","+ [bag[i], bag[j]] = [bag[j], bag[i]];","+ }","+ return bag;","+}"]}],"userModified":false,"replaceAll":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01T9DpTCfabyuLAdZR5PV3wD","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_013Rs9f1GUxDKdEkQJjtJBV7","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/board.ts","old_string":"","new_string":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId } from './tetromino';\n\n/** Create an empty board (ROWS × COLS filled with 0) */\nexport function createBoard(): number[][] {\n return Array.from({ length: ROWS }, () => Array(COLS).fill(0));\n}\n\n/** Merge (lock) a piece into the board, mutating it in place */\nexport function mergePiece(board: number[][], piece: Piece): void {\n const id = typeToId(piece.type);\n for (let r = 0; r < piece.matrix.length; r++) {\n for (let c = 0; c < piece.matrix[r].length; c++) {\n if (!piece.matrix[r][c]) continue;\n const boardY = piece.pos.y + r;\n const boardX = piece.pos.x + c;\n if (boardY >= 0 && boardY < ROWS && boardX >= 0 && boardX < COLS) {\n board[boardY][boardX] = id;\n }\n }\n }\n}\n\n/** Clear completed lines and return count of cleared lines */\nexport function clearLines(board: number[][]): number {\n let cleared = 0;\n for (let r = ROWS - 1; r >= 0; r--) {\n if (board[r].every(cell => cell !== 0)) {\n board.splice(r, 1);\n board.unshift(Array(COLS).fill(0));\n cleared++;\n r++; // re-check the same row index after shifting down\n }\n }\n return cleared;\n}\n\n/** Calculate score delta for cleared lines at a given level */\nexport function calcScore(linesCleared: number, level: number): number {\n return (LINE_SCORES[linesCleared] ?? 0) * level;\n}\n\n/** Calculate new level given total lines cleared */\nexport function calcLevel(totalLines: number): number {\n return Math.floor(totalLines / LINES_PER_LEVEL) + 1;\n}\n\n/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };\n const { hasCollision } = require('./tetromino') as typeof import('./tetromino');\n if (hasCollision(ghost.matrix, next.pos, board)) break;\n ghost = next;\n }\n return ghost;\n}\n\n/** Check if any cell is above row 0 (block-out = game over) */\nexport function isTopOut(board: number[][]): boolean {\n return board[0].some(cell => cell !== 0);\n}\n"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1920,"cache_read_input_tokens":16042,"cache_creation":{"ephemeral_5m_input_tokens":1920,"ephemeral_1h_input_tokens":0},"output_tokens":65,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"6903f524-3a7f-4233-88c6-b1f55144738e"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013Rs9f1GUxDKdEkQJjtJBV7","type":"tool_result","content":"The file /tmp/loop-bench-732u9ti4/src/board.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"c3a2cd2f-77c6-4322-a5aa-8ab73cb9158b","timestamp":"2026-04-04T09:40:29.631Z","tool_use_result":{"filePath":"/tmp/loop-bench-732u9ti4/src/board.ts","oldString":"","newString":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId } from './tetromino';\n\n/** Create an empty board (ROWS × COLS filled with 0) */\nexport function createBoard(): number[][] {\n return Array.from({ length: ROWS }, () => Array(COLS).fill(0));\n}\n\n/** Merge (lock) a piece into the board, mutating it in place */\nexport function mergePiece(board: number[][], piece: Piece): void {\n const id = typeToId(piece.type);\n for (let r = 0; r < piece.matrix.length; r++) {\n for (let c = 0; c < piece.matrix[r].length; c++) {\n if (!piece.matrix[r][c]) continue;\n const boardY = piece.pos.y + r;\n const boardX = piece.pos.x + c;\n if (boardY >= 0 && boardY < ROWS && boardX >= 0 && boardX < COLS) {\n board[boardY][boardX] = id;\n }\n }\n }\n}\n\n/** Clear completed lines and return count of cleared lines */\nexport function clearLines(board: number[][]): number {\n let cleared = 0;\n for (let r = ROWS - 1; r >= 0; r--) {\n if (board[r].every(cell => cell !== 0)) {\n board.splice(r, 1);\n board.unshift(Array(COLS).fill(0));\n cleared++;\n r++; // re-check the same row index after shifting down\n }\n }\n return cleared;\n}\n\n/** Calculate score delta for cleared lines at a given level */\nexport function calcScore(linesCleared: number, level: number): number {\n return (LINE_SCORES[linesCleared] ?? 0) * level;\n}\n\n/** Calculate new level given total lines cleared */\nexport function calcLevel(totalLines: number): number {\n return Math.floor(totalLines / LINES_PER_LEVEL) + 1;\n}\n\n/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };\n const { hasCollision } = require('./tetromino') as typeof import('./tetromino');\n if (hasCollision(ghost.matrix, next.pos, board)) break;\n ghost = next;\n }\n return ghost;\n}\n\n/** Check if any cell is above row 0 (block-out = game over) */\nexport function isTopOut(board: number[][]): boolean {\n return board[0].some(cell => cell !== 0);\n}\n","originalFile":"","structuredPatch":[{"oldStart":1,"oldLines":0,"newStart":1,"newLines":64,"lines":["+import { Matrix, Piece } from './types';","+import { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';","+import { typeToId } from './tetromino';","+","+/** Create an empty board (ROWS × COLS filled with 0) */","+export function createBoard(): number[][] {","+ return Array.from({ length: ROWS }, () => Array(COLS).fill(0));","+}","+","+/** Merge (lock) a piece into the board, mutating it in place */","+export function mergePiece(board: number[][], piece: Piece): void {","+ const id = typeToId(piece.type);","+ for (let r = 0; r < piece.matrix.length; r++) {","+ for (let c = 0; c < piece.matrix[r].length; c++) {","+ if (!piece.matrix[r][c]) continue;","+ const boardY = piece.pos.y + r;","+ const boardX = piece.pos.x + c;","+ if (boardY >= 0 && boardY < ROWS && boardX >= 0 && boardX < COLS) {","+ board[boardY][boardX] = id;","+ }","+ }","+ }","+}","+","+/** Clear completed lines and return count of cleared lines */","+export function clearLines(board: number[][]): number {","+ let cleared = 0;","+ for (let r = ROWS - 1; r >= 0; r--) {","+ if (board[r].every(cell => cell !== 0)) {","+ board.splice(r, 1);","+ board.unshift(Array(COLS).fill(0));","+ cleared++;","+ r++; // re-check the same row index after shifting down","+ }","+ }","+ return cleared;","+}","+","+/** Calculate score delta for cleared lines at a given level */","+export function calcScore(linesCleared: number, level: number): number {","+ return (LINE_SCORES[linesCleared] ?? 0) * level;","+}","+","+/** Calculate new level given total lines cleared */","+export function calcLevel(totalLines: number): number {","+ return Math.floor(totalLines / LINES_PER_LEVEL) + 1;","+}","+","+/** Compute the ghost piece: drop it as far as possible */","+export function getGhostPiece(piece: Piece, board: number[][]): Piece {","+ let ghost = { ...piece, pos: { ...piece.pos } };","+ while (true) {","+ const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };","+ const { hasCollision } = require('./tetromino') as typeof import('./tetromino');","+ if (hasCollision(ghost.matrix, next.pos, board)) break;","+ ghost = next;","+ }","+ return ghost;","+}","+","+/** Check if any cell is above row 0 (block-out = game over) */","+export function isTopOut(board: number[][]): boolean {","+ return board[0].some(cell => cell !== 0);","+}"]}],"userModified":false,"replaceAll":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_015q7cc7XQfg2SeFbKegApcu","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Wait, I used `require` in `board.ts` for `hasCollision`. That's a circular dependency situation. Let me restructure. I should move `hasCollision` to `board.ts` or make it available in a separate utility file.\n\nActually, `hasCollision` doesn't depend on board (it takes board as a parameter), and it's already defined in `tetromino.ts`. Let me just import it directly instead of using require().\n\nActually wait - the circular dependency issue: `board.ts` imports from `tetromino.ts`, and `tetromino.ts` already imports from `constants.ts`. \n\nSince `tetromino.ts` doesn't import from `board.ts` and just takes it as a parameter, I can safely import `hasCollision` from `tetromino.ts` in `board.ts`. Now I need to update the `getGhostPiece` function to use the proper import.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":905,"cache_read_input_tokens":17962,"cache_creation":{"ephemeral_5m_input_tokens":905,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"43e33574-f703-421e-9025-ef95bc4d61c1"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_015q7cc7XQfg2SeFbKegApcu","type":"message","role":"assistant","content":[{"type":"text","text":"I need to fix the circular dependency in `board.ts` — I'll import `hasCollision` directly instead of using `require`:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":905,"cache_read_input_tokens":17962,"cache_creation":{"ephemeral_5m_input_tokens":905,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"cd445c35-c1cb-4ee2-87d3-c55c22dff3ad"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_015q7cc7XQfg2SeFbKegApcu","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Sj4TuojqweM5dGyfZ7hejL","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/board.ts","old_string":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId } from './tetromino';","new_string":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId, hasCollision } from './tetromino';"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":905,"cache_read_input_tokens":17962,"cache_creation":{"ephemeral_5m_input_tokens":905,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"54d79d02-7600-4142-8031-ef9f61c8d33d"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Sj4TuojqweM5dGyfZ7hejL","type":"tool_result","content":"The file /tmp/loop-bench-732u9ti4/src/board.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"2602bd37-ac2a-4620-8365-50c72ef6413d","timestamp":"2026-04-04T09:40:37.090Z","tool_use_result":{"filePath":"/tmp/loop-bench-732u9ti4/src/board.ts","oldString":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId } from './tetromino';","newString":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId, hasCollision } from './tetromino';","originalFile":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId } from './tetromino';\n\n/** Create an empty board (ROWS × COLS filled with 0) */\nexport function createBoard(): number[][] {\n return Array.from({ length: ROWS }, () => Array(COLS).fill(0));\n}\n\n/** Merge (lock) a piece into the board, mutating it in place */\nexport function mergePiece(board: number[][], piece: Piece): void {\n const id = typeToId(piece.type);\n for (let r = 0; r < piece.matrix.length; r++) {\n for (let c = 0; c < piece.matrix[r].length; c++) {\n if (!piece.matrix[r][c]) continue;\n const boardY = piece.pos.y + r;\n const boardX = piece.pos.x + c;\n if (boardY >= 0 && boardY < ROWS && boardX >= 0 && boardX < COLS) {\n board[boardY][boardX] = id;\n }\n }\n }\n}\n\n/** Clear completed lines and return count of cleared lines */\nexport function clearLines(board: number[][]): number {\n let cleared = 0;\n for (let r = ROWS - 1; r >= 0; r--) {\n if (board[r].every(cell => cell !== 0)) {\n board.splice(r, 1);\n board.unshift(Array(COLS).fill(0));\n cleared++;\n r++; // re-check the same row index after shifting down\n }\n }\n return cleared;\n}\n\n/** Calculate score delta for cleared lines at a given level */\nexport function calcScore(linesCleared: number, level: number): number {\n return (LINE_SCORES[linesCleared] ?? 0) * level;\n}\n\n/** Calculate new level given total lines cleared */\nexport function calcLevel(totalLines: number): number {\n return Math.floor(totalLines / LINES_PER_LEVEL) + 1;\n}\n\n/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };\n const { hasCollision } = require('./tetromino') as typeof import('./tetromino');\n if (hasCollision(ghost.matrix, next.pos, board)) break;\n ghost = next;\n }\n return ghost;\n}\n\n/** Check if any cell is above row 0 (block-out = game over) */\nexport function isTopOut(board: number[][]): boolean {\n return board[0].some(cell => cell !== 0);\n}\n","structuredPatch":[{"oldStart":1,"oldLines":6,"newStart":1,"newLines":6,"lines":[" import { Matrix, Piece } from './types';"," import { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';","-import { typeToId } from './tetromino';","+import { typeToId, hasCollision } from './tetromino';"," "," /** Create an empty board (ROWS × COLS filled with 0) */"," export function createBoard(): number[][] {"]}],"userModified":false,"replaceAll":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01RmFsRiS6vLMhKVFCSKeyz7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Fxt9gPHQNwkBhWPSwo8kY9","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/board.ts","old_string":"/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };\n const { hasCollision } = require('./tetromino') as typeof import('./tetromino');\n if (hasCollision(ghost.matrix, next.pos, board)) break;\n ghost = next;\n }\n return ghost;\n}","new_string":"/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const nextPos = { x: ghost.pos.x, y: ghost.pos.y + 1 };\n if (hasCollision(ghost.matrix, nextPos, board)) break;\n ghost = { ...ghost, pos: nextPos };\n }\n return ghost;\n}"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":524,"cache_read_input_tokens":18867,"cache_creation":{"ephemeral_5m_input_tokens":524,"ephemeral_1h_input_tokens":0},"output_tokens":73,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"8502168c-1b53-4177-aae0-0b0a1f3b2707"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Fxt9gPHQNwkBhWPSwo8kY9","type":"tool_result","content":"The file /tmp/loop-bench-732u9ti4/src/board.ts has been updated successfully."}]},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"4541140d-24a8-44b7-b7c1-4b51c0585bfe","timestamp":"2026-04-04T09:40:43.817Z","tool_use_result":{"filePath":"/tmp/loop-bench-732u9ti4/src/board.ts","oldString":"/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };\n const { hasCollision } = require('./tetromino') as typeof import('./tetromino');\n if (hasCollision(ghost.matrix, next.pos, board)) break;\n ghost = next;\n }\n return ghost;\n}","newString":"/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const nextPos = { x: ghost.pos.x, y: ghost.pos.y + 1 };\n if (hasCollision(ghost.matrix, nextPos, board)) break;\n ghost = { ...ghost, pos: nextPos };\n }\n return ghost;\n}","originalFile":"import { Matrix, Piece } from './types';\nimport { COLS, ROWS, LINE_SCORES, LINES_PER_LEVEL } from './constants';\nimport { typeToId, hasCollision } from './tetromino';\n\n/** Create an empty board (ROWS × COLS filled with 0) */\nexport function createBoard(): number[][] {\n return Array.from({ length: ROWS }, () => Array(COLS).fill(0));\n}\n\n/** Merge (lock) a piece into the board, mutating it in place */\nexport function mergePiece(board: number[][], piece: Piece): void {\n const id = typeToId(piece.type);\n for (let r = 0; r < piece.matrix.length; r++) {\n for (let c = 0; c < piece.matrix[r].length; c++) {\n if (!piece.matrix[r][c]) continue;\n const boardY = piece.pos.y + r;\n const boardX = piece.pos.x + c;\n if (boardY >= 0 && boardY < ROWS && boardX >= 0 && boardX < COLS) {\n board[boardY][boardX] = id;\n }\n }\n }\n}\n\n/** Clear completed lines and return count of cleared lines */\nexport function clearLines(board: number[][]): number {\n let cleared = 0;\n for (let r = ROWS - 1; r >= 0; r--) {\n if (board[r].every(cell => cell !== 0)) {\n board.splice(r, 1);\n board.unshift(Array(COLS).fill(0));\n cleared++;\n r++; // re-check the same row index after shifting down\n }\n }\n return cleared;\n}\n\n/** Calculate score delta for cleared lines at a given level */\nexport function calcScore(linesCleared: number, level: number): number {\n return (LINE_SCORES[linesCleared] ?? 0) * level;\n}\n\n/** Calculate new level given total lines cleared */\nexport function calcLevel(totalLines: number): number {\n return Math.floor(totalLines / LINES_PER_LEVEL) + 1;\n}\n\n/** Compute the ghost piece: drop it as far as possible */\nexport function getGhostPiece(piece: Piece, board: number[][]): Piece {\n let ghost = { ...piece, pos: { ...piece.pos } };\n while (true) {\n const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };\n const { hasCollision } = require('./tetromino') as typeof import('./tetromino');\n if (hasCollision(ghost.matrix, next.pos, board)) break;\n ghost = next;\n }\n return ghost;\n}\n\n/** Check if any cell is above row 0 (block-out = game over) */\nexport function isTopOut(board: number[][]): boolean {\n return board[0].some(cell => cell !== 0);\n}\n","structuredPatch":[{"oldStart":50,"oldLines":10,"newStart":50,"newLines":9,"lines":[" export function getGhostPiece(piece: Piece, board: number[][]): Piece {"," let ghost = { ...piece, pos: { ...piece.pos } };"," while (true) {","- const next = { ...ghost, pos: { x: ghost.pos.x, y: ghost.pos.y + 1 } };","- const { hasCollision } = require('./tetromino') as typeof import('./tetromino');","- if (hasCollision(ghost.matrix, next.pos, board)) break;","- ghost = next;","+ const nextPos = { x: ghost.pos.x, y: ghost.pos.y + 1 };","+ if (hasCollision(ghost.matrix, nextPos, board)) break;","+ ghost = { ...ghost, pos: nextPos };"," }"," return ghost;"," }"]}],"userModified":false,"replaceAll":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01KNbyTDeH3CyjqTGmkVqoDr","type":"message","role":"assistant","content":[{"type":"text","text":"Now the renderer:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":448,"cache_read_input_tokens":19391,"cache_creation":{"ephemeral_5m_input_tokens":448,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"59856856-0d28-4626-b264-1712ed2b2c42","uuid":"2dbf4e10-7386-4fe8-8160-a47fa84d8ed4"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01KNbyTDeH3CyjqTGmkVqoDr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RP2Va1R47TnXiJBg6iMbRC","name":"Edit","input":{"replace_all":false,"file_path":"/tmp/loop-bench-732u9ti4/src/renderer.ts","old_string":"","new_string":"import { Piece, TetrominoType } from './types';\nimport {\n COLS, ROWS, BLOCK_SIZE, PREVIEW_BLOCK_SIZE,\n COLORS, TYPE_TO_ID,\n} from './constants';\nimport { getGhostPiece } from './board';\n\nconst BORDER_RADIUS = 3;\nconst GRID_COLOR = 'rgba(255,255,255,0.04)';\nconst EMPTY_CELL_COLOR = '#0d0d1a';\n\n// ── helpers ──────────────────────────────────────────────────────────────────\n\nfunction drawBlock(\n ctx: CanvasRenderingContext2D,\n x: number,\n y: number,\n size: number,\n color: string,\n alpha = 1,\n): void {\n ctx.globalAlpha = alpha;\n // Main fill\n ctx.fillStyle = color;\n ctx.beginPath();\n ctx.roundRect(x + 1, y + 1, size - 2, size - 2, BORDER_RADIUS);\n ctx.fill();\n\n // Highlight (top-left glint)\n const grad = ctx.createLinearGradient(x, y, x + size, y + size);\n grad.addColorStop(0, 'rgba(255,255,255,0.35)');\n grad.addColorStop(1, 'rgba(0,0,0,0.25)');\n ctx.fillStyle = grad;\n ctx.beginPath();\n ctx.roundRect(x + 1, y + 1, size - 2, size - 2, BORDER_RADIUS);\n ctx.fill();\n\n ctx.globalAlpha = 1;\n}\n\nfunction drawGhostBlock(\n ctx: CanvasRenderingContext2D,\n x: number,\n y: number,\n size: number,\n color: string,\n): void {\n ctx.globalAlpha = 1;\n ctx.strokeStyle = color;\n ctx.lineWidth = 2;\n ctx.beginPath();\n ctx.roundRect(x + 2, y + 2, size - 4, size - 4, BORDER_RADIUS);\n ctx.stroke();\n}\n\n// ── main board renderer ───────────────────────────────────────────────────────\n\nexport class Renderer {\n private ctx: CanvasRenderingContext2D;\n private holdCtx: CanvasRenderingContext2D;\n private nextCtx: CanvasRenderingContext2D;\n\n constructor(\n canvas: HTMLCanvasElement,\n holdCanvas: HTMLCanvasElement,\n nextCanvas: HTMLCanvasElement,\n ) {\n this.ctx = canvas.getContext('2d')!;\n this.holdCtx = holdCanvas.getContext('2d')!;\n this.nextCtx = nextCanvas.getContext('2d')!;\n }\n\n // ── board ────────────────────────────────────────────────────────────────\n\n drawBoard(\n board: number[][],\n currentPiece: Piece | null,\n heldPiece: Piece | null,\n nextPiece: Piece | null,\n canHold: boolean,\n ): void {\n const ctx = this.ctx;\n ctx.clearRect(0, 0, COLS * BLOCK_SIZE, ROWS * BLOCK_SIZE);\n\n // Background\n ctx.fillStyle = EMPTY_CELL_COLOR;\n ctx.fillRect(0, 0, COLS * BLOCK_SIZE, ROWS * BLOCK_SIZE);\n\n // Grid lines\n ctx.strokeStyle = GRID_COLOR;\n ctx.lineWidth = 1;\n for (let c = 0; c <= COLS; c++) {\n ctx.beginPath();\n ctx.moveTo(c * BLOCK_SIZE, 0);\n ctx.lineTo(c * BLOCK_SIZE, ROWS * BLOCK_SIZE);\n ctx.stroke();\n }\n for (let r = 0; r <= ROWS; r++) {\n ctx.beginPath();\n ctx.moveTo(0, r * BLOCK_SIZE);\n ctx.lineTo(COLS * BLOCK_SIZE, r * BLOCK_SIZE);\n ctx.stroke();\n }\n\n // Placed cells\n for (let r = 0; r < ROWS; r++) {\n for (let c = 0; c < COLS; c++) {\n const id = board[r][c];\n if (id) {\n drawBlock(ctx, c * BLOCK_SIZE, r * BLOCK_SIZE, BLOCK_SIZE, COLORS[id]);\n }\n }\n }\n\n // Ghost piece\n if (currentPiece) {\n const ghost = getGhostPiece(currentPiece, board);\n if (ghost.pos.y !== currentPiece.pos.y) {\n const color = COLORS[TYPE_TO_ID[currentPiece.type]];\n for (let r = 0; r < ghost.matrix.length; r++) {\n for (let c = 0; c < ghost.matrix[r].length; c++) {\n if (!ghost.matrix[r][c]) continue;\n const px = (ghost.pos.x + c) * BLOCK_SIZE;\n const py = (ghost.pos.y + r) * BLOCK_SIZE;\n if (py >= 0) drawGhostBlock(ctx, px, py, BLOCK_SIZE, color);\n }\n }\n }\n }\n\n // Current (active) piece\n if (currentPiece) {\n const color = COLORS[TYPE_TO_ID[currentPiece.type]];\n for (let r = 0; r < currentPiece.matrix.length; r++) {\n for (let c = 0; c < currentPiece.matrix[r].length; c++) {\n if (!currentPiece.matrix[r][c]) continue;\n const px = (currentPiece.pos.x + c) * BLOCK_SIZE;\n const py = (currentPiece.pos.y + r) * BLOCK_SIZE;\n if (py >= 0) drawBlock(ctx, px, py, BLOCK_SIZE, color);\n }\n }\n }\n\n // Side panels\n this.drawPreview(this.holdCtx, heldPiece, canHold);\n this.drawPreview(this.nextCtx, nextPiece, true);\n }\n\n // ── piece preview (hold / next) ───────────────────────────────────────────\n\n private drawPreview(\n ctx: CanvasRenderingContext2D,\n piece: Piece | null,\n active: boolean,\n ): void {\n const W = ctx.canvas.width;\n const H = ctx.canvas.height;\n ctx.clearRect(0, 0, W, H);\n ctx.fillStyle = '#0d0d1a';\n ctx.fillRect(0, 0, W, H);\n\n if (!piece) return;\n\n const bs = PREVIEW_BLOCK_SIZE;\n const mat = piece.matrix;\n const cols = mat[0].length;\n const rows = mat.length;\n\n // Find actual bounding box of filled cells\n let minR = rows, maxR = -1, minC = cols, maxC = -1;\n for (let r = 0; r < rows; r++) {\n for (let c = 0; c < cols; c++) {\n if (mat[r][c]) {\n minR = Math.min(minR, r);\n maxR = Math.max(maxR, r);\n minC = Math.min(minC, c);\n maxC = Math.max(maxC, c);\n }\n }\n }\n if (maxR < 0) return;\n\n const spanC = maxC - minC + 1;\n const spanR = maxR - minR + 1;\n const offsetX = Math.floor((W - spanC * bs) / 2);\n const offsetY = Math.floor((H - spanR * bs) / 2);\n\n const color = COLORS[TYPE_TO_ID[piece.type]];\n ctx.globalAlpha = active ? 1 : 0.35;\n\n for (let r = minR; r <= maxR; r++) {\n for (let c = minC; c <= maxC; c++) {\n if (!mat[r][c]) continue;\n const px = offsetX + (c - minC) * bs;\n const py = offsetY + (r - minR) * bs;\n drawBlock(ctx, px, py, bs, color);\n }\n }\n ctx.globalAlpha = 1;\n }\n\n // ── overlays ──────────────────────────────────────────────────────────────\n\n drawOverlay(\n text: string,\n subText: string,\n color = '#00f0f0',\n ): void {\n const ctx = this.ctx;\n const W = COLS * BLOCK_SIZE;\n const H = ROWS * BLOCK_SIZE;\n\n ctx.fillStyle = 'rgba(0, 0, 0, 0.75)';\n ctx.fillRect(0, 0, W, H);\n\n ctx.textAlign = 'center';\n ctx.textBaseline = 'middle';\n\n ctx.fillStyle = color;\n ctx.font = `bold 36px 'Courier New', monospace`;\n ctx.fillText(text, W / 2, H / 2 - 28);\n\n ctx.fillStyle = '#aaa';\n ctx.font = `16px 'Courier New', monospace`;\n\n const lines = subText.split('\\n');\n lines.forEach((line, i) => {\n ctx.fillText(line, W / 2, H / 2 + 18 + i * 22);\n });\n }\n\n drawLineClearFlash(rows: number[]): void {\n const ctx = this.ctx;\n ctx.fillStyle = 'rgba(255, 255, 255, 0.6)';\n for (const r of rows) {\n ctx.fillRect(0, r * BLOCK_SIZE, COLS * BLOCK_SIZE, BLOCK_SIZE);\n }\n 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last_content_type=n/a stop_reason=max_tokens","Error: Request was aborted.\n at OE$ (/$bunfs/root/src/entrypoints/cli.js:1237:11929)\n at next (native:1:11)\n at vI7 (/$bunfs/root/src/entrypoints/cli.js:7634:9034)\n at next (native:1:11)\n at VI7 (/$bunfs/root/src/entrypoints/cli.js:7639:11078)\n at processTicksAndRejections (native:7:39)"]} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "on", + "tool_write": "off", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1", + "run_number": 1, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:36:43.519354+00:00", + "wall_time_seconds": 297, + "exit_code": 0, + "completed_at": "2026-04-04T09:41:44.845265+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run1/transcript.jsonl @@ -0,0 +1,6 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-m1wtnj3e","session_id":"81007775-798d-4063-893a-bb945f999713","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"f7c70c31-aa03-4aaa-a83e-dc2b24ba1eff","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01G8azpiak9C2tAGqx6XQow2","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me plan the structure:\n\n1. `index.html` - The main HTML file\n2. `src/tetris.ts` - The main TypeScript file with all game logic\n3. `package.json` - For TypeScript compilation\n4. `tsconfig.json` - TypeScript configuration\n\nLet me think about the game structure:\n\n**Game Components:**\n- Board (10x20 grid)\n- Tetromino pieces (I, O, T, S, Z, J, L)\n- Piece rotation\n\n\n- Line clearing and scoring with multipliers based on level\n- Progressive difficulty where the level increases every 10 lines cleared\n- Keyboard controls for movement, rotation, and hard drops, plus pause functionality\n\nI'll build a self-contained implementation with all the game logic in TypeScript.\n\nSetting up the project structure with an HTML entry point, a main TypeScript game file, and configuration files for compilation. I'll keep it simple so it compiles to JavaScript and runs directly in the browser without needing a build step during gameplay.\n\nDesigning the full game implementation... I'm setting up the core game structure with a wall-kick rotation system, then building out the full implementation with canvas rendering, ghost pieces, next piece preview, hold functionality, and score tracking across multiple files.\n\nDefining tetromino shapes using matrix representation so I can apply a mathematical rotation formula—rotating clockwise by transforming each element's position based on the matrix dimensions.\n\nWriting the game code... Defining the tetromino shapes...\n\nNow I'm organizing the game logic into a proper TypeScript class structure with all the core methods and state management.\n\nI need to set up the HTML layout with a dark theme, centering the canvas with a side panel showing score, level, lines cleared, and previews of the next and held pieces, plus some basic instructions.\n\nFor the rotation logic, I'm implementing a matrix rotation algorithm that transforms pieces when the player rotates them.\n\nWriting rotation and collision detection... Building the HTML structure... Writing the complete Tetris game in TypeScript... Setting up the Tetris class with canvas contexts for the main board, next piece preview, and hold piece display, along with game state variables like the current piece, score, level, and line count, plus a bag system for piece randomization and a drop interval timer.\n\nNow I'm implementing the game loop with DAS (Delayed Auto Shift) for smooth piece movement when keys are held down, along with pause and game over states.\n\nBuilding the complete implementation... Writing the complete implementation...\n\nFor the ghost piece, I need to calculate where the current piece would land if dropped straight down, then render it as a semi-transparent outline. When drawing individual blocks, I'll add a 3D effect with a lighter highlight on the top-left edge and a darker shadow on the bottom-right to give them depth.\n\nFor wall kicks during rotation, I'm implementing the standard SRS system where most pieces try a sequence of offset positions like no offset, left shift, left-up diagonal, and larger shifts, while the I-piece uses its own distinct kick table.\n\nNow I'm setting up the scoring system using Guideline rules where line clears award points based on how many lines cleared and the current level, soft drops give 1 point per cell dropped, and hard drops give 2 points per cell. The level increases every 10 lines cleared, and the drop speed accelerates using the classic formula that gets progressively faster as the level increases.\n\nWriting the Tetris implementation... Defining the piece shapes... Defining the game class and canvas setup... Setting up the input handling system with DAS (Delayed Auto Shift) for smooth piece movement, along with soft drop and lock delay mechanics to control how pieces fall and lock into place. Now initializing the canvas elements and their rendering contexts.\n\nInitializing the game board and piece queue... Writing the game logic... Still writing rotation logic... Still writing rotation and movement logic... Still writing game 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":488,"cache_read_input_tokens":4241,"cache_creation":{"ephemeral_5m_input_tokens":488,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"81007775-798d-4063-893a-bb945f999713","uuid":"b4be2973-13e9-4367-b110-542284c699a0"} +{"type":"user","message":{"role":"user","content":[{"type":"text","text":"[Request interrupted by user]"}]},"parent_tool_use_id":null,"session_id":"81007775-798d-4063-893a-bb945f999713","uuid":"5391bbc6-7293-4950-842b-4f3ba11db44d","timestamp":"2026-04-04T09:41:44.200Z"} 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last_content_type=n/a stop_reason=max_tokens","Error: Request was aborted.\n at OE$ (/$bunfs/root/src/entrypoints/cli.js:1237:11929)\n at next (native:1:11)\n at vI7 (/$bunfs/root/src/entrypoints/cli.js:7634:9034)\n at next (native:1:11)\n at VI7 (/$bunfs/root/src/entrypoints/cli.js:7639:11078)\n at processTicksAndRejections (native:7:39)"]} diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/claude_output.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/claude_output.json @@ -0,0 +1 @@ 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last_content_type=n/a stop_reason=max_tokens","Error: Request was aborted.\n at OE$ (/$bunfs/root/src/entrypoints/cli.js:1237:11929)\n at next (native:1:11)\n at vI7 (/$bunfs/root/src/entrypoints/cli.js:7634:9034)\n at next (native:1:11)\n at VI7 (/$bunfs/root/src/entrypoints/cli.js:7639:11078)\n at processTicksAndRejections (native:7:39)"]} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "on", + "tool_write": "off", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2", + "run_number": 2, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:37:04.829673+00:00", + "wall_time_seconds": 276, + "exit_code": 0, + "completed_at": "2026-04-04T09:41:44.761145+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run2/transcript.jsonl @@ -0,0 +1,6 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-k1kq0ddn","session_id":"5c797ab2-dec1-4779-924b-c58d10fb45fc","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"db399de9-85e2-4284-9f3d-c327b0f5d3c8","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01PKtcrrtHdt6x5EFUcmgFCk","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser, built with TypeScript. Let me create a complete Tetris game with all standard mechanics.\n\nI'll create:\n1. `index.html` - The HTML file\n2. `src/tetris.ts` - The TypeScript source file\n3. `tsconfig.json` - TypeScript configuration\n4. `package.json` - Package configuration\n\nLet me plan the game:\n\n**Features:**\n- All 7 Tetromino pieces (I, O, T, S, Z, J, L)\n\n\n- Piece rotation with wall kicks\n- Line clearing\n- Scoring system (based on lines cleared)\n- Increasing speed (level system)\n- Keyboard controls (arrow keys + Z/X for rotation)\n- Game over detection\n- Next piece preview\n- Score, level, and lines display\n\n**Controls:**\n- Left/Right arrows: Move piece\n- Down arrow: Soft drop\n- Up arrow or X: Rotate clockwise\n- Z: Rotate counter-clockwise\n- Space: Hard drop\n- P: Pause\n\nNow I'll build the TypeScript implementation with the game logic, piece management, collision detection, and rendering system.\n\nWriting the game code... Defining the tetromino pieces with their shapes and colors, then planning a streamlined implementation that compiles TypeScript to JavaScript for a standalone browser experience. I'll use TypeScript with `tsc` to compile everything into a single JavaScript file in the dist folder. Now I'm writing out the complete game implementation with all the piece definitions, board logic, and game mechanics in TypeScript.\n\nDefining piece shapes and rotation data... Defining the SRS wall kick offsets... Defining the piece shapes... Defining the wall kick offsets for each rotation transition... Defining wall kick tables for the I-piece...\n\nActually, I need to reconsider how the SRS kick system works with our coordinate system. The standard SRS uses y-positive pointing upward, but our board has y increasing downward, so I'll need to flip the y-values of all the kick offsets to match our grid orientation. Looking up the standard SRS rotation system for the I piece to verify the kick offsets for each rotation state. I'm pulling the official SRS wall kick data from the Tetris wiki for the JLSTZ pieces, mapping out all the rotation state transitions and their corresponding offset values to ensure accurate collision detection during rotations. I'm working through the coordinate system conversion—in SRS, y increases upward, but in my rendering system y increases downward, so I need to negate the y values of the kick offsets. The piece position uses the top-left corner of the bounding box, and the rotation algorithm itself works the same way in both systems since the matrices already account for the coordinate direction. - y increases UPWARD in the kick tables\n\nBut in practice, for collision checking, we just need to try the offsets. If we're doing \"row increases downward\" (which is typical for grid implementations), then we need to negate the y component.\n\nLet me just implement it with y increasing downward and negate y in the kicks.\n\nActually, you know what, let me just write a solid Tetris implementation without getting too bogged down in exact SRS wall kicks. I'll implement a good rotation system with basic wall kicks (shift left/right if rotation would go out of bounds).\n\nWait, no. Let me do SRS properly. It makes the game much better.\n\nLet me just use the standard approach: for my coordinate system where y increases downward and row 0 is at the top, I need to figure out the correct rotation formula. I'm verifying the clockwise rotation transformation by checking that it correctly maps old positions to new positions in the rotated matrix.\n\nNow I'm working through the wall kick offsets from the SRS specification, which are defined with y pointing upward. Since my coordinate system has y pointing downward, I'll need to flip the sign of those y values when applying them.\n\nWith that conversion handled, I'm ready to build out the full implementation. The key thing I'm realizing is that piece position tracks the top-left corner of the bounding box, and when rotation happens, the SRS kick system tries different offsets to keep the piece in valid positions.\n\nDefining the TypeScript structure... Defining the class properties for timing mechanics like drop speed and lock delay, input handling with key tracking and DAS/ARR timers, and then laying out the scoring system where clears multiply by level—singles worth 100, doubles 300, triples 500, and a full Tetris 800, plus 1 point per soft drop.\n\nThe game will run at increasing speeds using the standard Tetris formula, leveling up every 10 lines cleared, and I'm implementing all the modern features: canvas rendering, ghost and hold pieces, a preview queue, SRS rotation with wall kicks, proper DAS/ARR input handling, and lock delay mechanics.\n\nNow I'm building the HTML structure with a dark theme and starting to write the stylesheet...\n\nWriting the TypeScript implementation... Defining the I piece shape...\n\nFor spawning, I'll keep it straightforward: all pieces start at y = -1 so they appear at the top of the board on the first frame, and I'll center them horizontally using the formula Math.floor((BOARD_COLS - shape[0].length) / 2). me simplify: I'll spawn at y=0 and allow pieces to briefly be at negative y (off the top of the board). The board will only be visible rows 0-19.\n\nActually no - standard is y=0 (top of 20-row board), and if a piece can't spawn there (blocked), game over. The piece bounding box starts at row 0, but for I piece, the actual blocks are at row 1 of the bounding box, so the visual blocks start at row 1. This is fine.\n\nFor most pieces spawning at y=0 with a 3x3 bounding box, the blocks appear at rows 0-1 of the board. The I piece is trickier since it's 4x4 with blocks only in the middle rows. Let me just keep it simple and spawn everything at y=0, letting the I piece's empty top row sit there naturally.\n\nNow I'm ready to write the full implementation. I'll create a comprehensive TypeScript solution with all the core Tetris mechanics.\n\nWriting Tetris implementation... Defining the piece types and their 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EnES/WzY8WgMHlTYApWPpaid7fXqL/6KKllp+HqNA48klSqFfiQc/fJ4kVMN5ijPecBmrlG0Md1UIFC6xfjCMYHTsA0TP73bnMpOhIwhm0EA2BOCBLDVuQlPBJrSQm4qrsnlN/OLqOtipDeiqj/1N9Sl1TLpcVCMde5WbOvgQLVVYMTm2tL+z48q5bT8I8+3mxXsuXYviS3Cs1SFTaaI6o5wEn5LAv8olcsblqOY1XWy2R/SmnRUfAbfGH0upZYHiXTaSZjqoTwrJkhxg7+fizTLEKV0Ya4rRA2DEgxVvbc5YUMwFWTzb+BYYbXL0iIZi60A2eXkbcHcE/kgbhURMskOF2fvmdVt+kEbCOFhu9v3zXcwpTyGhDr5ZUhlDKT1wLTSVj5D9KgQ09Z7rhQ8eEOcl901CWDxKxSNUqcnW8OVQ5d9FDOslpfwYI3JJQHId2cIwpZncvdOmQJKjEqJHTmmf7C1J5qzv8tWv7Ck9+7Xq7uN5bIZS+/6WCCmTcHdFVFOWlhdxC4mwzxxEIzPAssjtzBwo/3pljnfajp3niJ1B0KOdoeWi2li5ZtNzawMNTi+SWrKlFWvcXV6B8zaGO9jCKwv3kBZArQ+kg0eyow8u99jwADW3gaWO62b/j4vKJNd+r6zQfImDZPa7xZP+Hq6qoNWnjaBWBZMtANdnNopg61VFAFCbxWQ0YwXKVrzZYHEL1qMETpW4HuTVwDFryKo4Jy44Vnu/jl/TigB53KWjRDJBlxu94pG437CkWlchH3youIGJ83vAIzzSDLBeobq56RSz+L87tC8F+ByKBJ6hQE/v4YMyVQuHwAVni3ielakvVnCBtJdcqFPCOTxNRbnf5+TmrUCeZeBpbMakuNPms3WY23VXHkOFp5QsIKTjjZyrbexS3bofCDrW1X64pxdzYmHm9Gyvb1xla1iszKdVCLXh1hFUuMlNoCG+VaUavQFC0u+jfP6bWEMmGf4aicDk64L7ymhMLSInfmSh9Mg+2cOsfzclgMVLxHRnDgOyEp4XeSkiw4WD/PIv/bzMY7Y39sVocFMZjIYVwSubmucM6LNUXSLPltYblFfqr5ErHNcrDY/W1f5VZgPMaRSd9s6gUqEZ6tRc9z4Vou2JJof81T5SB4L+sJyvqa1Nsl9p6TiyJI5Wfpo252qkfeKXHGnFhHAdFO1TttJ/+shHTVLW+ZS3f61TGQOWVlM/5KacB8uI4ppHf2Clrn9x6Q16YiOzBLkknzWJ9wyQjrTiTko+CNrdqzsWC6u8ylRUI/xbwc7gqgyQEzhCJoHL4fg3SRaHnte5+3H+SZxE3YjzubkFNwTx0fcrOj4TW3xI6o7cYU6Ac+2YCBum7JJNhBK/ttneyFKZbyHaWj2/baNVjG5SIETlD197rxpuRJFfK1SWecmBsjZkOxMWeY1u/m3/cDYkKas5XsGdEJyWY/wlyFNQ+4MgLaIiThQkGeiqFouKmYWOZT0NIsKaXcVrJ4rx2BB98P27qXSeOiIHXVJQamF9A7iT7wAQhwlMo+5OjJCDW5P2dpvt52Nvi8ZEkWIbQe9msCdU0wAaLE4wtSj0Mq5xvqbK6GQbnNgARVYAuiBPSC73JwgRUDOnCQFYZpcvzOwKGwHj0Uwo26+pACHQ/3IjN3CxDJz8h2ztxxiiCg7cBOnFj2gv7/D34e0imiXb34kdEahDk/db47ZA5azKciRv7wdVUa7Ya55wvpavos8u4gC2joZBot2eGwv2U4D7W+T1gufdWgKBeKMFk9T0alC0h9B7oZHywhr0LCiOuCGX1a5HYVLZ+5Kr9tiqb1kSyj8pJ5/e8uMCLI2fQQSLdYC2VCXLjOKEAZXUuSARBaJi5R723D5BM1ztyoXIGC6SddWZiUcPQoywWsqY+OC0gD2mOpKM7FOr9vXfOb8LI6vBbY2jwV/q3yC97M5u4s1EdbcGCqV4wYuGfbvTqZfaWXK3Z/UM7a8n6yOqN/t44lOjFsjyTIBATqqcrQ/sInjMMbrAthyxs/yY7JdlCegq4hc5dAaObrOStneFIrqgDVRXRy1GFOEf7CBWIGsydwxzxXjsUfCCh5UyLbI3Yqzke04h/JXhpjRnxGu5YUNwYJId/M5IMmP4kVTvM/wECVUJ+aK5ExfEuagR9mz5eb70ZMA46Y1u3DxhzDyfrq0OLsa3JniOakeuwcOj3OnG8sIxGs/P2zoJ/2JHFsb1esJ0wPT278kgfEhaZGfSRbSsDDmYmGf889LcfrLs99950elRZrPOKGfv1z5977THrsVGjBJzB/JkAVxeubP1sDRoqVFCtIb8aRxwJ72pX63jS4cpc4QpQQJosPDF+SJdpKtkHrtBVgFo0I6KWwhZDmlfTsdzFndA3kMMrJbX1/yW3Ucq0gR0q1zsnB7XXoixOdXocZhM+QnzQHjAAIllJfxl69K/WM6KLaHAXfDmf70mTPedp4RXbvpeAumoJahjGTv1LFoqmGyejZSGk39cUcPxEcG9LCf4UWuJERwww7kM8Z+lE9d28mQ24EojTUvHRoVge53LlJdenw7Bb3Dr1NMejPSb2dMQoC3BYBTdCq/PVsPPovRAIdmr4Ck2+arcxj9bLJBDxtg+Po7V1uPhpAC07Lkh8o0nZS7wA+m70JEnwiPEvyjka2yddmx2rnM2ZDQpBg4YbvwOYlzG8OWRfp8G2TPk1Hty1mV+fe9HQnqbR9BwZ0S12bT+unicEH4SXhAgYVs+8QP89UVXHrxcAAKOdC/cZUVgkwcNV+ybTMjOIao3QyhN0A8gaNu37e/L3sPsWN//6AnCWs/19cXP0hJa10UQo/M9OzpYUV86u+uMJm68c88J3dZQzLz++jWxTwVQM2uNky0S/wO3XfuqQxtjN00akdVFwZoi76sWKvdr0xKooyMOHzYBVqSK4X9h/b4fGH64GgAz7YYBD5kmmAcelmC2i4ky704dTwjktcdwWVnGgv8MvT2+QqQEON2MVtnqwi16oh1MwD6Ahj6clpjVszMJevHjlgyVxHaSZrpgP6v9uputdlAnBofP/0FZx/vftYiVcdhNnGBF6aSiDjwL+9/hZzQZs6KKLbVNCZTbEgsA2Vj9/KrwLNj1UXVdk2nPj0RBBvjOaZJmnfEJcyJZL0r2AuJQubP1qT0W2pYTm5SY5Td0+p8WM1kli7J7cmANcTKCrTCETeJSRXLTDqMp9aBPNV7onmil5K07W4HfPaiUTZqbSWPy3gK6/ArrHNSZqrP51B4btD0M6hBzyM/mRQRKFkGicBQtb3xqjbxlyPffVP7Qh5HRlwXaThOopNftDqjrY7MwkamloZHuyHW8W47LK2l+z/S8LyUAHDHx2CiGTyFNHW0GQHBIOWkxq3KfHfdI8wGa9dcDpLjx/CU0YK+dS5jNNflXMEsbLEiNVb5Vzx3FZjNU9uh3dzypmEX+YVTQ0ScozC5UBEucjZQYU7wwGOVKnFnIzG3SCCOvqqs7XdCfWYR5y65W+C9LlJsQHP/mhOsD50F6ITJ3Nuk0kf47VoDuJ2q+qJVn/rBiRtGmmeFmwniNb74kIQaYcVTRPdIUSmMFEEAYIFDOJTNhoqd7r3cbQNmlynfJG7dngaYrBuLajw5/8lT1SAv0tlhFY68Ylsa+Qnh0IXfddEEQRpk5Rluh325hjT5Ul6RAuYBhyTV5VdcPFEKumC6Fi3r1XfkzfrQB3thQioYe95TnpF+1IfEEH6LL2JfceWHbRIN4xd6EBFNGSR9mmv364URxDeBn1Gi1gNkpgv6M2PKZW/Z9VVL/0HNGF0ElZNdCS8SgTZZt42CZ5tJct9c9QAc3B+1bdRJY2YFA5/JFF7m+dQsFpyj9nQ46sOfd2f+s7V/a0aWlIl8cry9dxIX7oKu12DPFJ16WB6IMbCQPlh3iPzrfVDhOrp2FQ8GO/bdDls5loUQ9sAzFePL/5DyGLKHg651x/v81osPHyTVKyTz5trQvlLC6FtZnAN6QhPr9kUYfI5E87jPsUIPvjQOO6vzrJDJsF3KXRSyWuiPuyTKO9oHFIwXyHzB2ov9h1iHxsdurDPpfBgMmFpqcT+rK3X1zBKn6qxK1TcjX1oUmK9hA9qaNpac/+A7so6IvTnbrQqXxyXgICULT1ZnHrs9wCn/92747D1qzb46TqRGUsFhB2XXn5LDmCOo93ynhzsOiXEjuiWBpnZ/VfHVNnz96FJvwrsm4QzbH7Mux7r8uFmZg576XmWp8BjECOfFOwJCVfkni2NuFX/IaQHR6/UPipeXz7veXlX+wK1FBacW4cNiQcvcgnTaT4siyC7uyalnezV3PhFDdj+2FXDixpqz9MLkdsApnjE+txJ3kPnTEZHW8kq571mLyubXfUFqnum9jD3fiKr9xrHwPU9OaBF7kgIg5mwTHeReuMjC7+pMCIf6Uoxt9shFwgyMqO1+fl4atZQ6SePEZiWfo3IHJ9QQQNsfW/jMe8HMDioTRdy30NRP0IQYibvY5O+rxEDgQ4/m2wdK/hcpijqhkVN7zfXoE6eLGNw0QhGEpFT8OkAtsX0FU+H6RQ2iaUq+Tloayvt16CeK+/3sxUKPgaduc8NYhby4gz8OkWJGN6Z2pRYbCXxduUey0ZjmvxFyNcNwGh5WgZtIfZube8snWihc+Jq3rPecgq2Qb9JhHL1MzJMx+HnAH5IPkL4IwEuVw2vNoVysEVLswxOP0M5FK/8Kua/aYVGWeo8tQtN0eHEmkyPY7YLN+tGKuUW9udTz9ZFjgF9XauzaFgHZWHz68MRWBoGmDGsSlIprm3Giam7ZCo7JpbLm1iCGjn9Uzi1RCJEb0/sszvpdtkLn93lGXAfo0MbChCs0tNEeYJX2y9rOgsXDY8tXlyj2l47XOSOsnUd8KhU+zsFZraYPd8D4XCIzqjgsrqcjX5uM0WMKXTE/mjrQnpN5kpkHx44UZiWn/Y+rxngrZT4Z8zhrwiLM+WYSxwEQt4Q8jAZkj//ajMK2oJDDTUXO3LD+y83Cll7p53HKMtCQzkysZs2/WcY63yW8H1X66mD6zKHB76SAXOktCGtpVpMoAOHSzlKr7cawmxuaG6LHgaMJrTFmb+KaPuT4gkURdXwgA5ywr0Z2UsfcD+Wjehnrz1WSTd8eYGF/HfMJsWljdUGKV3j2d/TDisS86pEKJAmds1284AZp35hRoXD5ixsm4/bjJl3uspqe4o/H83RIar2hbhxfvD3Yi1m0k0Zr/be41/4NmCZ/USf/tPw0ta9Llm1I1pEkH2gJofcgHKlV7G34J2hEK/yGgulz+lLct9qgh1nh1gc9IDDzkAWsL37hZEKGdkcRjHs3JfeEke/x+d9bRFrF5Yl3D7q4Ujfev6q9DFMN2WoBJ6qW+fxTKz/DX6kxsC3DyPNytE/syQ41YsAV2JnrQvXsvDVYWm7z2jCtUJD1fvSFnk2LBXqwE4AkIQjuvDG8Za62WXmyvXH1dMNUEAmF8x5jE9dFGth85arIx8WtENpfQsLj7DFj26qGHdOQeQ8PYzSB1UlfrIlQ9MFQCHxn1xVui0ghjeoKGvt7a5x5DxRiAxsRIB68F3MJWB+untAuAyaMDMD+r/0CZcuVoDEcTirmk+/4ylJaRyS3KjQmARmvEtXR3XpMvbHvO1r100Z77SHI6lDLOvqoJUcAqxVpVH7nxBy1tyT6PeHU6SeRtn7P0s0wKMo/xCiKcpiGUg8ZK98tw7VWLojcuRux32kiC2qRb7ZvgaIUYhbpTMEmf/GbWZ/9bUlmxpZnfLrdWrWVzY8+7D4WfbF4MavZXAlebCTH2NpbK4OWopoTDI5MgVuIK77vrbHVHYIFzcjMzHr8+Ams5Ktz8R6B7MvS+xW8IUDkltjq9SGSfpTbVtc9G6j1HWLJp95d7xpF1q6i1q12IaTmd8pSmHyloZuOyK6sk/dEP8/szLbHsYovxoBHPZiQhhpHEtaZjI+vKWBQEItas3uciq4a93OfmGzdujMzIrOXUDGNd4BKCbp4egIL+hmXjerUGFjfP+mfM0KHfUdXO8NrPgWI4iJhQGIInRyjtmCSPmMjwl8XoaV9kLTPelkQLKD8muSJD91AaM9vxyWlhBoSe/wawMzL3H/6/8gEjlT5ZDGekHunhBnDLrKyog4X73sUsL2i0QM3TP0rTjVZYvS3Ds3JmB55DlOgRHjyMC6/HoVoOusdZ88WpAzsiPiT6O02tUrkrbx/Jy7DApKSgSV3yIy3l9PkC1RFwvfMlO6+EZ5scNXk9M+YVQDbfMYj3eqh1J2ISvbv/V5/+Iqz+cToGAmIcD/Ke3T/K2i4nDS5Ylg6dL0/1bclhOOr4LPpP5qHn4SokWaV0wCigbluX+VYcdIVGKh8FM3MYRgWX0FS1WI9zirDctz6vbJ1pxAdy2H4vMe1df2ObC/0a3FBE6Sb+K0QDfNlXEe/Viekg2LiBTmhsisRAZOEVszQ8AS6CN/hMsKo/omIrHmrWX91U1Soq6wCXfVYktrTzFa9T9ppg6cwkDsEVBlNLS56glzj/+VWuxoh+pDTFMPZmemlQUIhzmZZMVMVZ1Qkftx591viJFjqfcL4cO/Ym11lz5My4n9hhNTnOTBcqy1ztqrFr4EgZ0V9WLUGyrLJWtY561hiqLT+JjERtLG4w8T4Gm//ku/CFyT32vmc8CBqkW4rwPzdi2K51E/Enu5fECUE1DkhP8GwiaCGAQHRERg+teP31wh7TIfvT6dZfUxLuEZNClzGhd7CQ/5welZoiQeOLiJFigf5EpLrty2lODqB6EWwfZEM/LEdM3FDvpW3g04QPsK/2EW+WX/jx0dC9MC3PqSENExeUyLTAiEHrU3FJ8oGNLyYior0EBDGW8C36RvYayFS34z7eD+E7b0+fwD8YPOwCraIL6ParfYKOC/bhAEIq67xLvXlC7sn7QWNaatK/lwQxRSjxkjCRd+KS4TXmkMMLB7gopTd+SY+4PChQtIJyHFpVFInN1HZ1rcTgO+kPo7vNFvqLClkRIXvxptJUMsxaK53e6r70ixNK1gTqqMBNnZ0vRVRBlDoyyQAVmGyEKtVEF/UksKnCeyMnAc01by6uVxmEmscRKoJV8vJtXWJSL4eDopIchMmAkONDrfFiMiw1GU7AfIf/ql+ztWg+xYD/Ap+B3ASwJUyVA3BgZh9tvGn8gz3+GanHwkbiDq9FsLesfSR1tpoYe6yej+MvpUx80cfN96tVGwekNdQC3pQwoCZuSxeQA5199IfoRjzFQVW8C8bgCuUZcTpjgoeQ9GzIuVOEQ9lArXXK5GtLSBH3gq3r6oagNWVGlG9Kxh8F6z/lftXW7A6Ea9z7wuSfbn1u4jIkLbuCigJBmrIFKWc4cag8Hmsfy5ewFXiw0Ysx6A7EKvuShV0QaRVRZWTZjQV9W+MljmjONgeM4FkUWBteHpH5Xieggb4anmPjtRQddAw4jpaN0+XHsv+FgpFAZADQcO7icGT7OpL2IP2k+hyI7KUJ5F+4htcYNVJ8GLHzj6cLZYuoBRE3LZEAueGKhJGezCSsHbJPtRax8KF6+k2/b6JyXCRCM2IymalklYZ/vgwLwj0LQH8vuHRGqOMDL4e9eJH9xinBLwhhipWO9FM7En/HXOE91DgqR9ucCefqAK1o9m2XGmkkpYmR3ORZson+yNYBL77zOpEpIK3k1pBaevsBhmMAlVo5tbdwaYBTwWAZI+fSBFwX8ogH6ZEnLwXZChEX+Y9HuEcZ5BhW/XxwXfJG2iLl6setEXHJGMalh2hCWG/x3I6wOGDi8oe1bJ+oBObLbjsfbqZuhMjFruFJbUtblVyP/BZEhm3OMnE/Q0cEca2XsuoqPY2Wcv9RejFxSskiIBGp+gdQdGEpMrxE20GM1NcwACCHUL9Vp9uq7mEs8lzZi3uV6qsWG/390TJYJr07pYDyEIxOHiNmBuCAHyP07ZvsZYzCzIB+Ylq+zVhjKM7tAY/M0d8xv8iwmuaGZ1KYpmgoaRDbV5EnLULF+DHB6SOLJNYMby8mf1lq7+BqiLUPWZyR8Gnocs27RdY/GUiwLI9xVjDMKK8zvQXB75KUxsS54o921FPlhf+RaNgb/tAXY6naSaYF29p6tNLiXspMhXUqQrRwQAOIbIUQMgPUidfwdRmQjPD/fPLqz3ebF7wsQfyh3w046elX8pJdp7qPPm+D6UHVd6MAvMNOSlpKjf4NpVqPuVmmJ9kHcCvrsL5qs/mnN2+RnM+WU/Jpm3ZZBMGrYG/KrNw5qZIl/CoZfCn9PQOF10DtaUwVqvmfKKlC2+gKR/6F8YMkHzXxVvxkFRXlxi7+QBzuVf+mi4Rdh0cBTecGM8wtzGyifwChUeIPmEgeBO6wJXoyyFUyxD7XK7KvJ16Kcua8YwSZMMeh1PdC8JwCOKEUTlzoTvHKEfjUTwVt9hSqu8dUr9j20eythurLEuKlIn8EiCcZhuqmIKPYcUUcVMF+QDnY7qzyDiOwgyRgagqmIu+UiXwAjtyTngXZtoWyzJnew8GXkgTqJx8B6M+sklJ1ZI8wQCB5tm1zkKURGvFomAjKZ6ljfWKUo6M1pR19SjN1xcRv6PXovDkYRTcOcP4KJuR1f+AqH4L23iZKnoyNGG+ReIU/uT7IWH6UFBtii9kVr/ro7Q9ysPM9L1rZcePuoDZ2I9tIRflBBx+kUE+EKAytVqX+ppZvjTQpuJpDr/8R/UFYuC5SVY2j5apoYGvdJ8+mRa266uIfwxeHSzdWLo+akVt18DSSchPQ9CngB3E6flvrkH4Ux9IicKUIJJcJbF9HqFOu5rBZli/vhESb2QX/r4lCcJ+IFP1x5cf0eV2KRs/WKRBr3WH+XOcWBIdvZGWHEbYninKqyAEoP2401wtBNsLQZsCDnirTbdIYef69Mxrx+ZK6lMWN+6rAxJoZrOaCur8QDmNLU1WEDjiE0dzZXyCvT2+Lyq2zO/b04EI101wC3IF5soLfbxeXQjcQYonLAbEOVnz011xM9EL8esW1pDiEFaDZtsDSrUX2YdcO4ATsLOxFdGeXdcUPus3Q5FIa90JcrUQr7+hcs91B1Nyi360V2lFIrcmnptmjksV9HJJ+xGVCIyyLYMuXE0UNQVdryzNVaY0WVZvMoMDpMcCBxz57hm6xxA0TYBNfuDsoBmBPYCIl5M2JLZtY8A+e/7VXmtRpNK+Ry3UmFjHWATL3PAqQYftDgkWO5m9OypxByoQZmFJzlaEjNo6VMV5tRMsZ9J/9do6sIXdcBGekAixcpsBthDslvFDteAp34c1y/LRENid+7j6KWeTYPCo1GTTJOkvagB0DDmbPTwj4x2XrTNJe62SjMHXcJZQgHpy2TUUHMAmbeLrZwovk95koP9zbwOjb8DmCYNv993I8/0rk88j0frGrIFduspJ4Bco3VYTB6W17ETUOYJAfzeFNiq/gsFw7u/KR+m7yfXfR1gU26msiVIc9j6QJ44b/HtjkBculsGHNoWRQOR3xmh0X3fUOf+AOHGaDQewb11RHzcNHKvYAUnZgEVBt6YN70A8xgljNGSAMvCzW1zigOcAx1/r/0So4u8InO398mxdJ/HrYpj4wwiJj3rg477TVO53Hh/YX3T4aNWvT6Beu9QRkCWs09U5jVUr2xcR/S2SI42mcBR6ZT9XOycERLyzz2T9saUEWMqF5vLpBMIv2oVwH61iFrGsYb7ka9JRgJCyCkL3aqmdIkQ8qg/kwpAKo8F9OppxxuUX4gvSdH+tqGMDiukKr2tJqRi7HoY4ws4hchIgTXaPzBxDFJsr9ZExx0D84POn8cR37ewgIcq3UNVPGj4jrzId4kfcHYttRNOtUJE6oxj38qyMHiME7ceC1Eg7Uy/XUzPK5pIMaO11vE4jI+GyMmhB7XSE8RR2L5EIt/4Ibs3r41MXuRdoN+8gPwDaKdDO6Qzvar+QErlYaOeO1AulOXGs4sYh3U9IFcq6FDfFAwhMalqKezsAzYbGe4LrtCdAyopI1D6NKYPIeHwnSCFWm30mtG1DaCqYFaJ4pZOyxei5C+jtCsJOhUaBD3PZHg8jea2YFVWvo+8C5XLkJSeWCM7JB4v7+X+5eZOTaA7Axv0KCUW2ThViGnP1MbrgN3lpIUChHpzW3xztY5tHwvUtFNWSzgbPqgsvFsbGk2/Gafsv+YJeiCpcgbc+D9kqLg1661xgnSRALEcFqj17giTLP3gBG+Xp53fEI0fk6M5SK1h4sZNSILcmRG4AwgCzXrEzDnD6epbHN/Ik6HU3GRWuviUAQkldINzUwi0J2exj+Ma51bq3hCZ+8qTrPUvICh7gpHc322uNrQC9GxTffswGgpo6ixbuEWe+6CfwdfooiNw2Y8ZTd8aG8h6mZ6ThePUJfCqbiwoHR13EtfYaJBMljLgPPr83mTJtggPR2H5qDYHpYG8bKz18sy3f958nK8Yr0AwSKLK37R1xVyG7o7DKl+dn4214s4Hs2SiEaU8KbJBDrSC2+P3bDsOluoUmFaA05E7KTbrokare/d34LFZc6IS4NiNHdSDL4EPHFhOqGHHFbwYDzvhV/BnMunYioeo5PCPjsIVUrsJy/izqW30U6XSqRyYXFfKTrmXUALkubYxbKNJAdRn7YHKN128bShAooxg/6GSNcZJQWdAAepDxP2mP+q2mxuKN2iTiu/pmw2zQ+sxPPSd7JzLEc+aTMyc5n3r7xJ3ggy9ZVnRfhK9Xk+txK0MVlrU4wugH4nOpY7yJhRVEC/vFyofhCwK68uoYAgEb/4jGc1d8179qakmqLjFtStE4PlxDqkzROp7tnLC33DRtFRZLaV+mrzGQmen118tqE7WIeEiaOGI2NQEzt4+ibd5Wuv1oDf8ZvvPKY2Kz1QM9VxUZm/tOxf6L59lYh7MIoZR24KDbj+xk1VYSye2xxh8NTqoqcd/llz1xg+2KhrV5pbdZUAbtrnOVmi0Q5aa/llKknxd6Mgbvm638OPyzZ6kdYbY2y7W++7my12CqIbMnmIBVbzFWjWdftszfRyQDzQH7GUGKwKVJk5qKq6Ljh0hyTM7lfZfVw/Gy/eziKmBGhzJAQYuEJl8FbT/7Hze0TJ2GUUHIkVQ8D+pDiLh7LbvGXvZSj0wicQHkNVyCxDzgiK/eZ5k5irKBPShVfrlz76zegeB34tyRd+FnhwjxoPcwbfhsmCD5cVWKqYAK+rPK7oOq/Eu+84/7+Amr+M2fClI2fegJ6EmVKSNGmP0bZVrpUlDR7xcaaDfgHDhMfDViNCtr/M/Rez9YHDFkGmpp5K0wrmy434VghYD5sVVIwS37RMVZx7Rq6Ww8YZNYJbomfi5xPZPypBMjxtO+o1kILa8YzrnT8JEDYiVk5YkQdnPBYELZHVZ05NT5dZ3O5XXyP4Clrjlo36nHMac/1+8413Yu9kN2/VpiFOPwc9gsqw32sIUmF2DLG01zjED9ZRQu3ry9ZQ/EWtaapu5fwylqw4kVm/hUspPAw/9Wk+pNb4C5CkSY07bWI8Y8RRzJQWPT1wY6Ithk2jwnl5M3mEu2OcRnxD/vOtnduP8yR/Ltg5TjJ4T6EOzQeDeZJKRJPB/c4Z6zDfHPoAiVrFZKp8BAUmrh20fBWVYGmONWLdNqJI9JfNx5c+rlSzOePtnoAbkfULdjjfQ669IqiRxGpKVBMfzR2IuB23T5aiNqUzP2eZyz3C+DnDEkCG7Vast8zXu1C3AIGKHQWWVSE9512xpHjzyLEMnAdb3JlKqXkTocjsiE+6Vpx/v4EFESudMbey4FDann8A25rJxbGk7Gz5G/y4nMVynr9CZZMnIO5urpzY6WOghHDZGAY8FUbdCEQQ6yE3xVKaopIZB9HzGHJdhNFr9kJ9myHb5lwXvniLBTTQWr2RDEWEiYzsnuWfvskPi8DuBiN9Y5tEaYBi7pAjnlwBiP4hER/tD51HvAauabEV7+gFIEnPWhiSLO/9cq5gmFGobnQPAJdOSFabvOn/OhB5XMHAhWt0UC3Zw9AhSH/veAUsu/9Ad6V5G2y/kMX29r2QH/oJRKB99QSpljAflVg6ApDBKI6yOItFXB1rKLBcc6oW/i0fhAiTrEOByiGJCTUM3QKKAZK4g6MwsrsQftyW1Qv6uNovbMkEgIMbytxxAPU6I7spkMQwXgeqm1jlCzTuGjIo+n7P2kWupL2yHK6SF2s9zSwqRzkMERswYPJKESkaOIX99wwBPi/i0lDWcK48L+t8NnnOJG3JZg/UL9mnlr8ffgNyVD0sUoG3vWP0maaUv2hyVRJOAFLSujoFICl8XixIROGNnLM6B7Bt+8AdRbYtxZQn29VcIaZn9dUqRaUkliNlazbAtqG8ozeOtFHbQQZ4cbA2zMKsCbmZLHOxrZBw9JXUQNh8WOrMT8IwYoI/NcruDFNKwN2W38vYjIZ8Gmq5CcW+rPt7/RPyjIniVvHZDDgRbV24zp6U4t66rzi2Dxy0zeQk5J2zEUgvPZIepnGK7fyl8+wo0QZX2ULAWhsM2urtukiozqpcnL9KDw88Cz07P0F1Vp91hW7ECqxr1uQxxyeSdCS2qkgzlxJdxzqfN1PpgejiVNJ8RWk3/UQCPwLem7roTxTbd4FOY1+XScuQLWZtD0FZoIZQNlwXWm2BsQzUpqej2apQfK1uxzyxV32uDKYCVn0BQOMs0K/WovcmO+jfXgSo7MxWvD5+Aht3+FrepDjdrxE4uR8FteMvx8sgfs6JR0LKEfaMYcQFUPbYY1QFZ2veEEL4CDsRdSqcoTdwCfrltoOznc9zg8aq62553fiAZlezD7LYlL+HeltxNEtFELuXOM9bmlumjDUNiv0CFFnaRCZEZ8qqYB+CCEUSKBdODz3wf3HIT199VvrjcAih59QL3gbEQiTj6lvxeCvPr7LPAANSDdQsYjy8/0fnkkUAFkKcn8tskX84KBMHT2nhLBmRH+U5BlxcmM9hCeVLA0diZzNaukp/B8Z0+vwwZMIfwvGeUYZ8T4BP1gcfQPvvJ+6uTYYMyGAC9oePgDgkFazst0uSEIzKCtzmpt0KqpYqExO6YrNvCSoIV/Im+tdvv7DQ9xmrxOshagmnZMTyJi23DEsGm6CO+i8ZyYkvAztCjZBq8euWE3SjzUm8yti80U3jmnQAC+jhbxHorfjHU1nSkMyma0H9HVzXQecqe2pN9vlyGx6hy0ZPAK3AycUbA1fcnH8hA727Un8oDS47Mgd4+Se8u4blAhpzMNyZPpQkRR9t4XAtkuSOhWgVFcaYqpxV6o+z0fqSwg17Wdc/qu6Cj2dknsEiLJy3QMQqkbVdyFvEhFNJ3Nm/0Df3EPs4zfLVW43SBpiriBsn3N1V3PqgeXGCrPHGIQoOw77fOzanv7dxFGoEOoi12CpS2Wa5exEgD+i6jwZQkAiV9SAFGNqTGp+LmoU0xeYCMRCATTqlqeQjjkd7s34HlR9281fIJonSmE1xg5vzipFG4f2IjeLOFc33I2U8z4/jJg3yuqUodWN5+4z0gzdXZt4PxRLtuKOxOeeDV+IVLdmPTCtqw/7DpyyMSRoEPV0k3PBWB5w7Wn2WpJMWRIPZHw6b8tfpEGEJ0hgoUXiKua0BtKGlt2lpC6j2PlO5tO8AewT9MaY8PABAjqbQzMxcDxloxXMsbVv0yZXnx4NnM+Pz/za6ApY4kF4rBnbp7HuZ6Z6HnwTetHYkgmQZI/i/MPutkt0TChEB3LtMv5doQSt8M+z+enEHR/dhlLrlBQ5WIUbMjNFNiUd4rHMFNfrhV6Zfm+1DK36fEQX9hwX2jMHArXZKGUrgeCm+GmyRDaVHVUA6EkaxC34MU+JOSYX2xEguMwuEpkbtxQ2wvf5MxPOGOrW8lydVFqUPTpziwzsD1Vmm2KXLbR/H2499LIQnU3GsY8c5/IrfyrnyQlCRkPOrM43YSCQezUkR4oKxeOhcjgwTl22YkkyAD6xa6oyBEkAigDEpHtYIJAjzkhaSKnj9GdIWQJtlMbwDPzlKuSg/n5RSt05g26Jyy6nXNaHxTuvIO2x0v39GfTDDH45sauIseK8GfbH9LSUzcloqyrzgvoovWhdCv9RBEyyDWlcnXikkeyJuhOC91F1lSrSzDg3oz0Ki/Vw0m47nAeC3IDY3kgVNtdwYje5wsACGwtdjxKmHc2Um4G+MKyEuXoZ6thoPZaXDk/VRuWgPvLbfrKdPNCrQN2cMjEZ5DWgpDZNsNivk5AgA8jpoaGbosCrjSJakHgaHDXD4GsOz52ywoS/n2LiJASDjV2DurZiedybDSy//75AHH6lkICzonPj1pSRt+qDhobsOG4uW4PB0ONZaK13f7w09lWLLh15mERfQ5Q+VkcXrdKAFynq5F+V36bbO4gY95kQ7Hht9mGE+HKdhQfWHeh6/5iAYejdf6z7Vf9b1EdpygMlMWPMDlDedvC5munesHFyWv/+Fk6kkxBElBRzPn1K3cWToGfqf7cA21qHUQiGhHUr/P2YUFLiXmyQrNWB5hb28N2Hy4NBVktJLv/1Rp0qYMvU/aOQM5utMF26G4PSAuwIZamP7MjlFUYLMKc5Fdph5a+OjG1pBrqlaavb25WsDDcffFTSbqUCa0tth3xqQrgfHsQwjhRvvLrQysG1CQUO5lyyy0bHnrn52Lnx9u3dXwq/It+0VxrIxyH0azawsGqQmaLg238W1W0fnV0jw2e4m43HbJxyo+GRRlFsEBLQ3L+3mCxRQLaXH9ZR+mkqkuASaXZCjJMU3WFtRiVZjODu/dZFaJged+Eq99I7m8y6F7yzBMjCimhi+dOeUeR7gLSe+L9+fOmBWUPyo4sxdorYRvZzCZoCF5drVeIkabYF/V0pXBxmp1Bb73Q76JAFeDIV9uuY//2aC3fOwVDnrD1jTUAgwg4LjGksl9YuesgmI7ymSLVAjOG+Rnp7EfFKcybSh5CcyxLG9UX9+v9Z1hrJI4CFYlIfnfHKvMdCklEtQdngfpCNV2srwmm8moVLZoHJ8xC5ovtUrvE/TAzZt8oa5gt2sUz9aPz3Bu5WFOuFCLBgfTC1P8i4ZDomNxv0Qb3un1jpbBtleTCDvP4aOxGhvOCYrgT1KFQnM9DFiZ/840QHlYnua2FIJ5PMC277usmLDtpFvcP3Nq66ZghzvY7+68wQTq40TmKMoWPxtkthdJXPDDL/28Nx/DGpo8UcWUwvUu8WsN5JRSOiCjH1gAiL2r0tRly7MizrBpVhWaU9J9uAVH8mSYIVTlzTqUpazQrp6mDZTSgHNdcGfPm/AWDqsp4gfG/r04lEDQaCURPhcQlAC6zKOKU4W3hnd+pcsiNCKFufjrEph8rQV/mHx5dLYmREakWp5dL3+ijQjRFpHrLCQwkK7JgGOmD7DlkV12icGWENxvdr9e4dbvZL3HJVyAVd5qWrkmLFOMSrLjUNjVFQ/bB5N2jSIY5B2wcpO4piQ6aFxb+1l+Za7lkYx93ZnOwFxtUm3OrWIHSBrW3YmvEOG7OMaLqC9eOQLiNk4tBcZiijA4HMhHQuQry2QMRi0twkHW7xoQgSBKbynAEZsonQeit9rDnK4IzMj7UrNqSHSO/LW2OcpTlRMOCmPI25bwkZ8/OXab90BXb5JAnESkZFHMxwHpJJELnCMxe8P+l8vNfiJvZ7ZzOXlcCYf9SReMLvLmclTh3WnafolhSgJIgaQ8YhhnuKSVYwFjvEw0JNhiM6CyYHV0Yu/0W65sKt8ejBpl1To/XNbFgm7ZtB8SiGTPy4Ya2y69vPXoeMF2Obx9p6Q0lmIKL3dHOdAJ3R1SZINfLM4h859wbynfud76HaFMEvPKyuSnZfhTX0XTyIkc5wWW8J1aV3SCstYkyGsC7BoOHwgjZDsUjBfFochQ2NMlrtUc+kju7zjL/52w7iDsoEt0HFkDmNBSX/B4W15vurjssUT1VkPmXZ6k7VjfaQwc+4e4I9XCdA1WUvvUnTWtVQ7DAaJnH9A+Xw7KdhTnWFiXmPpImosxeyEUF7jSBm8MpBQfldLC/t3yCFkIIhYD45fS0C6bVG4HC7Q6qp8iGYz9ZwH2mq1eHOcoABisq1j923wsVGuI5vFXL28axwNC5cD/IbITeOS5kBI/VywcyDlsbj42Db/FypR4opfiocinCPeOkfId/fGTkm7LsYHUUjqL6ILPpk8p5F7tDLgz8XvXbIlp8ubOgJHLoaNaUywjYeDnvEy+LQucR8DAdHjJidzU9XPeogN31rQO45o39TN84JRuUYY+sUk7YXIBQQFMTIRWv3oVyWqsKNV6aXFl2mP52leyEA2Yg2csf0qimzBRYN2EI+JZnO2X/hT2ZAOCW+jdFOzo28ytUjcAUXR3GXuQa0VcoghihrGvBNWNrMAb7RI0+qe/cEtNyuND7Xr1E8G38t+wVKgS69ljNzU+jrcNHZPoD4D/bLp4JS6sEDjgHDU8YYN9c9J+yW9z2eqtpT7sR531AGpGn0+WdBCt3uPVoEfi8ipPxBznBCBlTNjjFRhZ2awolL7QubwRMpjrlnBVjaUcLqr2pS2X9y2tDlsn+gtuld9+DybQ+EkyWNAly9ca6RqffJe9NHwD0SSr8996u/LZheONNxcu6l8KAKdVZ10OKy3GuL2CLPjw8kvY/5b2rMk5uwfoO5pJR1TsNbd+mk3lPv8SUJ3oUh8uCvKmM0WX0f956TbGRBWr8EHgAqQw90PVq065p4bSZkCVXRh2hOZ/d/lRzd+6/tAswAXO1F7YORIcGVScXtgxzGkLIoe6hWBRO5mlfZmyDuB+SLE9M5ObLW0FCW56pPp5EQDZFx3dn/mvp3VYDZXA+dBDzAM1ZYOFw9BOWQ59yLk+eLWeWlWcVldBAy2NDV2ByPvuuiKDvx6UpnAo1ZBK6x6DMopc5w2ffK8thZkg82BP+Wqb438rFlwr9hCqJHSvfpsZpMpZwX+BkCvNXxn6Y7sIJEbLyOC5kadHHjleZvUwNu9NY4BOs08gpwE81Zm1i00pZ40RPNUCKkbORDI5tKVUl/kQbYaq9EARFGvfm7ff0kkzltBR+5YY8lAmQsHUmMhUAjBsOZjhgbB5IDrsqmUo6rVvgb31+b2MhA5oji2Zbu5CC9dPFoRaPyEOc5S8LIuJl1qnXPzHkOYh/2ApwsJO4/fpxskN61SyLQlxb+cR0qA9dUzpkR3BEvOjEKxejIb5INkAKllLW6wUKa0hWWqqqUZZxxbXcbMjMV42EVELXLvRLvgzeFvZQdhpQxc8tO0jVL/Y2sC1rshawfg59NNfQTE+BrKjvkEWJBY3ynORdEXtxY1s236Tm8du6scy7+ZhRGUMoNxCG4APdSgohs9gY64JLmdkWQFyJCLABlf3sYzxo4IQk5bQjpcimtlCM/05G4B2nvPH6wm8q5K3WgihzmMf8vQFPVKCAuZpH9AEfO+6aSGv6vuAQs1S17uVFbS1u6sFYOgh2hDGyb+1/Bf35hWycBOMYZBeEJIcL3qbdwFdLbR9CKjRYqTw4ZOziUWn8NTAm2VyKg78dNGrK4TsDdUoQAy/ndikoDQsFzgyh00bDy9mBd5ACwZecaIolKzE4LJhqKFSj0MbKZiZUrtUnrI+n1LzKuI94mAXPZG58ZdLCWD/Jos1CHX69iXLrmHbgTXa68tnu5mMYQ2gHBtEgNBcr9Z5f7G3K1ya0aKH88b82mXmfp30FiOMv9v7j7GaPmsKSLbUEIx6euDcc/UgMFGIEvJmfPHSTdTrJihHrRInitPHI8PDQzFVKHvPrpT51hrdDP81vUDXox1NV8M8MZzXurj8WCgR43d9Ukrkg+hB3BF5p6z/FAU4lp1oMUxaE7XItXhowtfwI5Nqg8jx7cZ3pe3mSuIdaRbceyjvH2gkFXmxrbu4hxupTBLaMqQMoTwvbgJacIfYn3cvlps3hNfCvql9ZKJcCufcNN48UxuYIT9BnCEdEpG5m5wF6jPfqVOhUbjQIlB0k3Wqld3uu2rDK8rptinf+DcYRddOx06HjO2wrxZfSK7vkTNhz5TYVZsvHNQkby1COYXRcs3tGwP98MpViufvUBLNIRMYEr57sPjxThjUMZIxUs80BXoCqjtn5ycN3sQmHKiMP6jhgPr6eGEKeL33eOGogKUpiKt0fu9yOW3KWrXUWaiDpRBbW4gbdsjgNeA2twmBNFSvu5Pe+Zx2XOU5LxnU4iEX/Il7j2ELCRDqiulUwV4qs3SkUaoXmPPn3TXx8YBYmqpqyTfpTzXYNUUe7MUxwWb7HX6Dj/uvdOnNyuTmX8BiwvZ9fJM5Q7yELErsb2nOoPWxl9g0YJBq8OhXOfhXha8D0mG79twwsTrM5XIDaHquBzPM93Qp42VH0PIXGREiyVNSgvUf7ZWzmZsdgz6rDaYB39Z5BsvAEEUpQ0ItGPHjtjRtNzcKsi6mr52LhCzXin1Fp8tqHqkOcpH5AtTHeR2Gqj7CYkqRkwGjHAbDybm6EPSMduxcDnh3QV+sPvNR7ugwBhizfXGIuCrRPuMnR4bCZhBBLa9MqeBSZi3+BgQhSx17ooEPG+155cRspAGtpOOaDd0Ym7F3F1Zuu2eP35BYYfQnMbUST8Vox72h2+wMYUpj9WfeT47PTd+cpb1n9IoEE03hD6f1cITI7xn700G2qr6EyTl0b7LxHgzRQCVSAYETCyZHhgZp6vCpZ8qx3LgYP+WDCxbVGKLvSKMdV9BozgtvtY2HBATOCimeK6rhI1Ql5ty7AaXr2POW7Yu48eUWAwdbZZ2xm8NKlocbmJI1861fPz1wnwcxnSUukHWl6SakAF2GJjBMaIY/KKAulywEBCyrDWXUpjiDxvHsSQOL2OnUDWI859zkhUVpLO1+Hw5eGlLRlvzAFbDMNjEAZKmg95Xt3zMGs7jAaEIj3sIvClRug/8X8+OdrBGkhWz7h+PHuyQQni/iSYGUa8wHMf140oeGkTUGpYQUIS+gGduGKkiKXcFIA/Uqa+q9RVfvH3xum2MFCMgFOty/N0RpglVPwti6R5TRJqJn/X66I02jqc1X+Yx60ziurkgiGU6JbvkEDbZ3Cffjf3RHWjhTRIr365dxLOVQGGilIUUSwjIrLFSTAFuOecGtErnLQFOJGZY02Hr0kr2oVQwkmde1NjcmSdXI8Qs4ndeqD7MC2huBSkAUsTQuyeVhT8aQnfFvBiU3b20pj8YUV6mC/wQwBdf1xEBk3jSOi1Xmql1uT9v2H6o/7oGyRKdXJjdYcxT8wo+/cdl3dXv/5Hb5Y7vdF0FbEtYG1XtEhb0f4F4PZgE48h/SDmxq7WwWQJXsjueEr4OTkkDs7tyEg5/hIePl1JVX8gVHjWFemEeeULTIusHF03Z4eXSfFa+cNL3sPus4LWV5n1LfAtI7PK73phfpdL7/78uMJyuA5nGhcQOjYmL+PXg3QufiM2qtVLE/0J3KGE3youQZpl4NMA4hqHLKoM9LPwM7zLH6ChxqTI1cMmkF2pWEdajs4zsU7a1AJwqsEgnvxxV+O6kzNHvPaKo6pyZU7GMdbT5Ap+iXPBgvgSroWYMfWNv/xlqkDgfLLSwZiR3vVMqxE6vGue/Mnt/Qb/HCh6lnrvRbzHEIptqLM/lNcRFEneASgK5fB9AVnGw5Jo7apnDuxGr91Zytu0Oh9EeoB7j7iuknoiieI8o/poWC++LTlMOMXZsho/GGly/SnOnh5vSitsKFvYOjvrgrqJsEGyLx1EHEynLnHUEMQS8agS0KJKRXoUcVMi0CLnV9Suu+kBC+/hB472CP6M1nh/glkNIoTjK0DWlHQvz/2IoAYEmPCFVvkSgAjV3XB6VTMLSQ2O8ZbTo7K9CXsqHgwl9O/fYqmIYRchYTclSQohn9HwnlwQQu3bqlZ/+anj78rQcMPBvujRjN9wYWDpEim2kNxLcyBCGWHIp4soS77N5uGWbatTTgelr+9iURF0+rf4nWvRttorrzc2P9jJDq4ljH2TZiwGtLV49XO0AHiqVLMria0R1Fv8LcWvvzksCq7iZZebVcaTKGS9tRNSc3PuV2LsgQAmtZ0wA9NefmALHd3mJAp8mGLU6LJG9VaIcZPI/T9LQ8fqUt76ljE+dnjZEefX1nSGIJd3nDqUJE7CSWCyWuVxdVuPvlDMqIq4c/8qgdrr7/TG6zolMHq7osYn/kaJHKX5U6oES8BGFcKb+ciOCepU9cAsihEJO1CgIN2LP4IqCCoOvSlDrbpdA5iDG4oPuFCg+TeK+nTV+rjHT9bA8zp4AOW22V1CJ6FkG8TbXCYrZNuDn61zQTtgj5ye+XKw7CQEvlb16Uqgy6uCg70Jzftn2dwdNTWNx6yoY3IAHINq3cJTAihvLkimnFeggV1Pk3BTPfE/aQEhQIEk/9cPWH7R0wpykuDujc91dIamoroPNVP0zl+iMtj4CBCyiO3GUHnttf7xlzchdvmunpjnIjbZzZQMmbt0nVG14uLY/QHNV1nGOW6bmUHovygR2eUXvBpR2N+B1YPnKcbZo+/vZZ/75tx3NtnVWagKs2/W7CLrkj9U9vWYTl7K0brPqJP9hFNiUEBXdi08n3PeWh4L6FA0SiwewOqyC2SHpyaKPH39e1283R2GdOQDFy1gsEt9X7x7KQiWa0QoYPC53Nzp5H/Z2xnuYDA0ALsFuSQsJ95gouUpkGmhLZdu2YLFgKPptyMhD/vhVGOvSfljVDEow9hoPG9RuY58wGK3YWVHJkJ31yjzvm9Hl5KnnNimgSdxdwkhTo/UTeYucjZqBYkdxrXc1xHbW8pnapokYFUvAsn+meBvx1QkP4UFPyutOonR0khR3W31TdjTbJxXmHKodPqV3pFKxrj/2SKPY4FQw4FGIf45gssWAB4Sy1zzvzE6oN4MfQPN8zoXBrFOP8uZiSk+Vp8M47FRjx9aADdq1SE2QhFJGCaDStxjaPdDw7QuUynh4I/qew8zFnq5V3/2VVOOYhwfilxaY7cs6fg3fYUWYl5zQaB+RqzzjSed/fW8MZ/cs129WK20ZDNhPWFrf2XLc9wQkNuesSoLv4dzcSL0cjAV9L2uijZ5lTH0W4A1hSNSsuC7fSAmuK8cvI0t69zzGdfplR3+1mIDXLhyrlMJ4BAcoC0FDQN5F0i5ukCQtLequJKZkq6DM6+eun58pHR+6s6VuI6il9R2yR2IPPyUHhMBZcwSchj38OHmfkIc4KoilOqiBaEyUjK/StPDVVzDKDOsElqj2yDF3UMzmrIZnDxJ02p7ZygVll9StdeODG+3y2RIltQcwKovFg3DzM2OWLqgC+S7nrop6mLN/8omJx2vHPkOCQbf1Rz53S+mKAAr9KqXgeoxejjyPc8HLNuh8ziC5OK2wux5TdfNfuz6FSpiuiQmmRULaR+NvbrMabG+8YwTR8wFs5sBQsTfEv+deUfLOTYaB5f+/B1BF7jSXTwoEbuPOPdSXP+9j/yCHQSgw4Aaj0lvAi4h3JIj2AiLC7oYPLY5f07a59/ojee89NSdpLWWfZxPaWNBZo/veibJvTwsqGo+CMTlW9VK1VJrBmK8xgm2w/1C2isYt4sB3z+AZpLGMqu1iUP0ryJgltmtrdlR9VA4KauD4vR/UJ/jda74dm6oxAwQe/oCYubEKg0scfxh3TIyC7bAMKDxN6KDljHPUGiy02xl0FvL0eBgdtMDhO3z65/GAE="}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":488,"cache_read_input_tokens":4241,"cache_creation":{"ephemeral_5m_input_tokens":488,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"5c797ab2-dec1-4779-924b-c58d10fb45fc","uuid":"5f942b32-5ff8-4a7c-98c3-b07c80448cc0"} +{"type":"user","message":{"role":"user","content":[{"type":"text","text":"[Request interrupted by user]"}]},"parent_tool_use_id":null,"session_id":"5c797ab2-dec1-4779-924b-c58d10fb45fc","uuid":"6dcaae6f-8cfe-4fb9-abef-934903ae97b4","timestamp":"2026-04-04T09:41:44.199Z"} +{"type":"result","subtype":"error_during_execution","duration_ms":275483,"duration_api_ms":95050,"is_error":true,"num_turns":2,"stop_reason":"max_tokens","session_id":"5c797ab2-dec1-4779-924b-c58d10fb45fc","total_cost_usd":0.12311129999999999,"usage":{"input_tokens":3,"cache_creation_input_tokens":488,"cache_read_input_tokens":4241,"output_tokens":8000,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":488},"inference_geo":"","iterations":[],"speed":"standard"},"modelUsage":{"claude-sonnet-4-6":{"inputTokens":3,"outputTokens":8000,"cacheReadInputTokens":4241,"cacheCreationInputTokens":488,"webSearchRequests":0,"costUSD":0.12311129999999999,"contextWindow":200000,"maxOutputTokens":32000}},"permission_denials":[],"terminal_reason":"aborted_streaming","fast_mode_state":"off","uuid":"f5239565-1af3-47d4-9f68-8419f3b28f05","errors":["[ede_diagnostic] result_type=user last_content_type=n/a stop_reason=max_tokens","Error: Request was aborted.\n at OE$ (/$bunfs/root/src/entrypoints/cli.js:1237:11929)\n at next (native:1:11)\n at vI7 (/$bunfs/root/src/entrypoints/cli.js:7634:9034)\n at next (native:1:11)\n at VI7 (/$bunfs/root/src/entrypoints/cli.js:7639:11078)\n at processTicksAndRejections (native:7:39)"]} diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/claude_output.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/claude_output.json @@ -0,0 +1 @@ +{"type":"result","subtype":"error_during_execution","duration_ms":185642,"duration_api_ms":120864,"is_error":true,"num_turns":4,"stop_reason":"tool_use","session_id":"cd8c0c5f-5035-427c-853e-978967587625","total_cost_usd":0.1524876,"usage":{"input_tokens":7,"cache_creation_input_tokens":1870,"cache_read_input_tokens":13697,"output_tokens":9423,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1870},"inference_geo":"","iterations":[],"speed":"standard"},"modelUsage":{"claude-sonnet-4-6":{"inputTokens":7,"outputTokens":9423,"cacheReadInputTokens":13697,"cacheCreationInputTokens":1870,"webSearchRequests":0,"costUSD":0.1524876,"contextWindow":200000,"maxOutputTokens":32000}},"permission_denials":[],"terminal_reason":"aborted_streaming","fast_mode_state":"off","uuid":"48966043-b51a-4719-88ca-42bb95711295","errors":["[ede_diagnostic] result_type=user last_content_type=n/a stop_reason=tool_use","Error: Request was aborted.\n at Ux8 (/$bunfs/root/src/entrypoints/cli.js:1237:17403)\n at A (/$bunfs/root/src/entrypoints/cli.js:401:17832)\n at abort (unknown)\n at k (/$bunfs/root/src/entrypoints/cli.js:16449:610)"]} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "on", + "tool_write": "off", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3", + "run_number": 3, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:38:34.895807+00:00", + "wall_time_seconds": 186, + "exit_code": 0, + "completed_at": "2026-04-04T09:41:44.592189+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=off_web_search=on_run3/transcript.jsonl @@ -0,0 +1,12 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-lkcio3_w","session_id":"cd8c0c5f-5035-427c-853e-978967587625","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"049ce108-3a54-4837-8073-99a7698de516","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01TLSRYgykQqAcU2QXwVamUD","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me build a complete Tetris implementation with:\n\n1. All standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z/X for rotation)\n\nI'll create:\n- `index.html` - The main HTML file\n- `src/tetris.ts` - The TypeScript source\n- `dist/tetris.js` - The compiled JavaScript (or I can use a build setup)\n\n\n- `package.json` and `tsconfig.json` for the build setup\n\nI'm planning the game architecture with a standard 10×20 board, all seven tetrominoes with their colors, and controls mapped to arrow keys for movement and rotation with Z/X as alternatives.\n\nFor scoring, I'll use the classic NES formula where clearing lines multiplies by the current level, and the level increases every 10 lines cleared, which also speeds up the game.\n\nNow I'm writing the TypeScript implementation... Defining the tetromino shapes... Defining the remaining Tetris piece rotations...\n\nActually, I should step back and think through the overall structure more carefully. I'll use HTML5 Canvas for rendering and set up the core game mechanics with a 10×20 grid. My approach will include a main game canvas, a preview window for the next piece, and displays for score, level, and lines cleared. For rotation, I'll implement the Super Rotation System with basic wall kick attempts to handle pieces near the edges.\n\nWriting the complete implementation... Writing the complete Tetris implementation... Defining the tetromino shapes... Defining the tetromino rotations...\n\nNow I'm thinking through the full game implementation. I want to build a polished version with a canvas-based board, preview panels for the next and held pieces, and a side panel showing score, level, and line count. I'll structure this with TypeScript and create a complete, well-organized codebase that handles all the game mechanics.\n\nWriting the game logic... Defining wall kick data structures...\n\nI'm realizing wall kicks add significant complexity to the rotation system, so I should plan this implementation more carefully. Let me outline the full structure: I'll need a package.json for dependencies and TypeScript configuration, then build out the core game logic with proper separation of concerns.\n\nWriting the Tetris implementation... Defining the tetromino shapes... Defining the rotation states for the remaining Tetris pieces... Defining wall kick offset tables... Defining the drop speed calculation based on Tetris guidelines, then setting up the Piece interface with its type, rotation, and position, along with helper functions to create pieces and retrieve their current shape...\n\nNow I'm writing functions to get the filled cells of a piece at its current board position, create an empty board, and validate whether a piece can move to a new position. Writing the game logic... I'm setting up the complete game interface now. I'll use a single canvas for the main board and HTML elements for the side panels showing the next pieces, hold box, and score information. The layout will have a dark background with the game board centered and controls organized on the side.\n\nFor the rendering, I need to handle the ghost piece—projecting where the current piece will land by simulating its downward movement until it hits an obstacle. Then I'll write the canvas drawing functions to render individual blocks with proper spacing and colors, followed by the complete game loop that handles input and updates the game state.\n\nWriting canvas rendering code... Writing the complete game structure...\n\nNow I'm working through the piece spawning logic—I need to figure out the right y-position so pieces appear at the top of the board correctly, accounting for the different heights of different tetromino shapes and making sure they don't clip through the visible play area.","signature":"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Let me build a complete Tetris game with:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up/Z/X for rotation)\n\nI'll create:\n- `index.html` - The main HTML file\n\n\n- `src/tetris.ts` - The TypeScript source\n- A compiled JavaScript version for the browser\n\nI need to decide on the best approach for running TypeScript in the browser. I could use a bundler like Vite, but for simplicity I'll compile TypeScript to JavaScript and serve it directly with a basic HTML file that loads the compiled code.\n\nLet me start by setting up the project structure with separate modules for game logic, rendering, and piece definitions, then I'll build out a full Tetris implementation with all seven tetrominoes, rotation mechanics, a ghost piece preview, hold functionality, and line clearing with scoring. 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I'm ready to start building the implementation with Vite, using the standard Tetris gravity formula where level 1 starts at 1000ms.\n\nWriting the game 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/eval_results.json @@ -98,7 +98,7 @@ "score": 1.0 }, "transcript_analysis": { - "total_events": 7, + "total_events": 8, "tool_calls": { "total": 1, "bash": 1, @@ -114,7 +114,7 @@ }, "errors_encountered": 0, "thinking_blocks": 2, - "text_blocks": 0, + "text_blocks": 1, "productivity_ratio": 1.0, "self_tested": false, "score": 1.0 diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json @@ -23,8 +23,8 @@ "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2", "run_number": 2, "claude_version": "2.1.92 (Claude Code)", - "started_at": "2026-04-04T08:48:02.455889+00:00", - "wall_time_seconds": 700, + "started_at": "2026-04-04T09:07:02.558799+00:00", + "wall_time_seconds": 913, "exit_code": 1, - "completed_at": "2026-04-04T08:59:49.595714+00:00" + "completed_at": "2026-04-04T09:22:22.253160+00:00" } \ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl @@ -1,7 +1,8 @@ {"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} {"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} -{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-_wezxzen","session_id":"c11ab9e1-e3fd-4a04-b658-f2a1347d3a59","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"e0ebe218-e1bc-47c2-876a-1de27d1d1215","fast_mode_state":"off"} -{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01DVQNYx2KUJC43G9tyWBvym","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me build a complete Tetris game in TypeScript that runs in a browser. I'll create a well-structured implementation with all the standard mechanics.\n\nLet me plan the structure:\n1. `index.html` - Main HTML file\n2. `src/tetris.ts` - Main TypeScript game file\n3. `package.json` - Package configuration\n4. `tsconfig.json` - TypeScript configuration\n\nOr alternatively, I can create a single self-contained HTML file with inline TypeScript compiled to JavaScript, or use a build system.\n\nLet me go with a clean approach:\n- `index.html` - Main HTML file\n\n\n- `src/tetris.ts` - All game code in one file\n- `tsconfig.json`\n- `package.json`\n\nNow I'm thinking through the core game design. I need to define the seven Tetromino pieces with their rotation states, then build out the game board logic, collision detection, and rendering system.\n\nFor the game state, I'm tracking the 20x10 grid, the current and next pieces with their positions and rotations, plus score, level, and lines cleared. The mechanics involve spawning pieces at the top, applying gravity for auto-drop, handling left/right/down movement, hard drops with Space, rotation with wall kick support, line clearing with proper scoring, and level progression every 10 lines with increasing speed.\n\nThe controls map to arrow keys for movement, Up/Z for rotation, Space for hard drop, and P for pause.\n\nWriting the TypeScript implementation...\n\nDefining piece shapes and colors...\n\nNow I'm thinking through the project structure—I'll need TypeScript configuration, a package.json for dependencies, the main source file, and an HTML entry point. For the build process, I'll keep it simple with just the TypeScript compiler rather than adding a bundler.\n\nI'm planning out the complete Tetris implementation with a 10x20 board, all seven tetrominoes with proper colors, the SRS rotation system including wall kicks, a ghost piece preview, hold functionality, a next-piece queue showing three upcoming pieces, and Nintendo's classic scoring system where line clears multiply by the current level.\n\nDefining the game types and constants... Defining the wall kick data for rotations...\n\nActually, I need to reconsider the coordinate system here. In standard Tetris, Y increases downward, so I should make sure the wall kick offsets align with that convention. I need to flip the y-coordinates for canvas since it uses a downward-increasing y-axis, so I'll negate all the y values from the standard SRS kick table to get the correct offsets for screen coordinates. Defining rotation kick data for the I piece...\n\nActually, I should step back and implement a simpler rotation system first without wall kicks, since that's what matters most for a playable browser game. I'm planning to structure this as a TypeScript project with an HTML canvas for rendering and a game logic file handling all the mechanics.\n\nWriting the game implementation... Defining the rotation states for the remaining pieces... I'm realizing the coordinate approach is getting unwieldy, so I'll switch to a matrix-based rotation system instead—it's cleaner and more standard for Tetris implementations. I'll store each piece as a 2D matrix and rotate it 90 degrees when needed, then layer in SRS wall kick logic.\n\nWriting rotation logic...\n\nNow I'm mapping out the full game architecture: a standard 10x20 board with all seven tetrominoes in proper Tetris Guideline colors, SRS rotation with wall kicks, ghost piece preview, hold functionality, a next-three queue, Tetris-standard scoring, level progression every ten lines with increasing speed, lock delay mechanics, pause functionality, and a polished visual design with gradients and shadows. The controls will be intuitive—arrow keys for movement, up arrow or X for clockwise rotation, Z for counter-clockwise, space for hard drop, C or Shift for hold, and P or Escape to pause.\n\nFor the build setup, I'm using TypeScript with a simple configuration that compiles to a dist folder, then serving everything through a basic HTML file that loads the compiled game. The canvas layout divides the space between the main 10x20 game board on the left and a sidebar on the right containing the hold piece at the top, score and level stats in the middle, and the next three pieces preview at the bottom.\n\nSetting up the canvas dimensions now...\n\nWriting the game code... Defining the piece shapes... Defining the rotation states for each Tetris piece... Writing the game implementation...\n\nI'm working through the wall kick offsets for SRS rotation—need to nail down the exact coordinate system and test positions for each piece type to handle rotations near walls correctly. Defining the I-piece rotation kicks...\n\nNow I need to convert these to screen coordinates where the y-axis points downward, so I'll negate all the row offsets to flip the vertical direction. I'm finishing the conversion for the I-piece and realizing the wiki's SRS is getting too complex to replicate exactly. Instead, I'll implement a simpler wall kick system that tries the rotation at the current position, then shifts the piece left, right, or up if there's a collision—this is what most browser Tetris games use anyway and will work fine for the game.\n\nActually, I should just go ahead and implement the full SRS properly since I'm building a proper Tetris game. Let me write out the complete implementation now rather than keep deliberating.\n\nWriting the game code...","signature":"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-{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_0175h5gacirs4ArzXA1tu7yb","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in TypeScript that runs in a browser. Let me build a complete Tetris implementation with:\n\n1. Standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls\n\nI'll create:\n- `index.html` - The HTML structure\n- `style.css` - Styling\n- `src/tetris.ts` - TypeScript game logic\n- `package.json` - For TypeScript compilation\n\n\n- `tsconfig.json` - TypeScript configuration\n\nI'll keep this simple by compiling TypeScript directly with tsc rather than using a bundler. The game will use a standard 10x20 grid with all seven tetrominoes and wall kick mechanics for rotation.\n\nI'm planning the core features: ghost piece preview, next piece display, a scoring system that multiplies points by level (100 for single lines up to 800 for Tetris), and speed that increases every 10 lines cleared. I'll also add hold piece functionality, pause, and game over detection.\n\nDefining the TypeScript types and tetromino data with their colors and rotation states using the Super Rotation System...\n\nBuilding the HTML structure... I'm adding the hold panel and controls section to the sidebar, then moving into the TypeScript implementation to define the tetromino pieces and their rotations.\n\nDefining the tetromino shapes... Defining the piece rotations and wall kick data... Defining wall kick data for I-pieces...\n\nNow I'm thinking through the project structure—I'll organize it with TypeScript source files, compiled JavaScript output, and configuration files for the build process. Let me put together the complete implementation with a polished dark theme, a proper game board with grid styling, and ghost piece visualization.\n\nI'm planning to include the next piece preview, hold piece functionality, smooth animations, level progression that increases speed, proper Tetris scoring, and simple sound effects using the Web Audio API. For rotation mechanics, I'll implement standard 90-degree clockwise rotation by transforming matrix coordinates, and I can handle counterclockwise by rotating three times or with a direct implementation.\n\nNow I'm working through the game loop...\n\nWriting TypeScript code... Writing the Tetris implementation... Defining the piece shapes...\n\nNow I'm thinking about how to handle rotation state—I could either store the current rotated matrix directly or compute rotations on the fly from a rotation index. Storing the matrix directly seems simpler. For wall kicks, I need to implement the standard SRS kick tables with their offset sequences for different rotation transitions.\n\nDefining kick tables... I need to account for the coordinate system difference—in SRS notation, positive y points upward, but in our grid implementation, y increases downward, so I'll need to flip the y values when applying the wall kick offsets. Let me reference the standard Tetris Wiki data for the JLSTZ pieces across their rotation states.\n\nCompiling the wall kick table for the I piece...\n\nActually, I need to reconsider the coordinate system here. The Tetris Wiki uses (column_delta, row_delta) where positive row means upward, but in my implementation y increases downward, so I'll need to flip the sign on those row values. Let me redefine the kicks as (dx, dy) in screen coordinates and work through this more carefully rather than trying to match the standard SRS exactly—I'll implement something functional for wall kicks and move forward. Setting up the kick tables...\n\nNow I'm laying out the SRS kick data for the I-piece, which has different offset rules than the standard pieces. I'm looking at the complete wall kick data table for the I piece across all rotation transitions, mapping out the offset coordinates for each possible rotation state change. I've got all the kick offset data compiled now. Let me think about the visual presentation—I want a dark theme with a subtle grid on the board, and the pieces should have some visual polish, maybe with gradients or bright solid colors to make them pop against the background.\n\nFor the layout, I'm picturing the game board centered with sidebars on either side showing the score, level, lines cleared, and previews of the next and held pieces. I'll add some nice touches like line clear animations, a game over screen, and localStorage for tracking high scores.\n\nI'm going to use canvas for the main board and piece previews since that'll give me smooth rendering, while keeping the UI elements like score and controls as HTML. Now I'll start building out the full implementation with HTML, CSS, and TypeScript files.\n\nWriting the TypeScript implementation... Writing the Tetris implementation... Defining the piece matrices...\n\nI need to think through the spawn positions more carefully. In standard Tetris, pieces spawn at the top of the playfield with specific column alignments—the I piece centers across columns 3-6, the O piece at columns 4-5, and other pieces starting around column 3. The spawn row is typically at the top, though some pieces may start partially above the visible grid.\n\nFor my implementation with a 10-column board, I should use a formula that centers each piece based on its matrix width: spawn_x = (COLS - matrix_width) / 2, floored. This way, the O piece with its 4-wide matrix (including the padding zeros) will naturally center, and I can set spawn_y to position pieces at the top of the board. _y = -1 for most pieces so they appear at the top, with the I piece's blocks landing at row 0 since they're positioned in matrix row 1. For the other pieces, blocks start at row 0, so spawning at y=0 puts them immediately visible. I'm going to keep it simple and just spawn everything at y=0—the pieces appearing one row down from the absolute top is fine and matches standard Tetris behavior.\n\nI'll set up a hidden buffer of 2 rows above the visible 20-row board, spawn pieces at y=-1 so they start in that hidden area, and check for game over if they collide with existing blocks right after spawning. Now let me just write the implementation.\n\nWriting the TypeScript implementation... Defining the piece colors and shapes... Defining the wall kick data for I-pieces... Defining kick data for O-pieces and a helper function to retrieve the appropriate kick offsets based on piece type and rotation...\n\nNow I'm setting up the scoring system and calculating level speed with an exponential decay formula, then defining the timing constants for delayed auto-shift and repeat rate. Still writing utility functions... I'm working through the rotation formula for a 2D matrix—specifically how to rotate it clockwise by mapping old coordinates to new ones. The key insight is that for square matrices, I can use the formula `result[j][n-1-i] = matrix[i][j]`, which swaps and reverses dimensions appropriately. Since all my Tetris piece shapes need to support rotation, I'm standardizing them to square grids: 4×4 for the I and O pieces, and 3×3 for T, S, Z, J, and L pieces, padding as needed. I'm realizing that using uniform square matrices for all pieces will simplify rotation logic—I'll make I and O pieces 4×4 while keeping others at 3×3, since the O piece rotates to itself anyway and the I piece needs the extra space for its horizontal and vertical orientations.\n\nThe real solution here is implementing the SRS kick system: after rotating the piece's matrix, I'll try placing it at the current position first, then systematically test kick offsets if that fails, stopping as soon as one works or abandoning the rotation if none do.\n\nWriting the rotation implementation... Finishing the rotation functions...\n\nNow I need to decide on the matrix dimensions for the Tetris pieces. The O piece should use a 2×2 matrix since it's rotationally symmetric, while the I piece needs a 4×4 to accommodate its horizontal and vertical orientations.\n\nFor spawn positions, I'm setting the I piece to start at x=3, y=-1 so the blocks appear at the top, the O piece at x=4, y=0, and the other 3×3 pieces at x=3, y=-1 to align properly with the playfield. I'm checking the spawn positions for different piece types and noticing some inconsistency in my approach. The I and O pieces seem to have different spawn row conventions than the T piece, so I need to look at what the actual Tetris Guideline specifies for spawn positions to make sure I'm implementing this correctly. For the I piece spawning at y=0, the blocks occupy rows 0-3 with actual filled blocks only in row 1, which works fine. For the T piece, spawning at y=0 places the top block at row 0, which is also acceptable since the piece fits within the grid bounds.\n\nI'm settling on a simpler spawn strategy: place all pieces at y=0, and if there's an immediate collision with existing blocks, the game ends. This avoids the complexity of handling negative y-coordinates and hidden rows—the I piece's empty row 0 sits at screen row 0 while its actual blocks start at row 1, which keeps everything straightforward. I see the issue—the J piece loses its top block when spawned at y=-1, so that approach won't work. I'm going to simplify this: all pieces spawn at y=0 with their matrix top at screen row 0, and I'll detect game over when a new piece overlaps existing blocks at spawn instead of trying to manage a hidden buffer zone.\n\nFor each piece type, I'll precompute which row contains the topmost blocks in their spawn orientation, then use that to calculate the correct spawn y-position so the topmost block row always appears at screen row 0—this means the I piece spawns at y=-1 since its top row is empty, while all other pieces spawn at y=0.\n\nActually, I'm realizing the I piece at y=-1 creates a problem with game-over detection since it would check row -1, which is outside the board. Let me simplify: I'll add 2 hidden rows at the top of the board, spawn all pieces at y=0, and only display the bottom 20 rows to the player—this way the I piece's bar sits at row 1 instead of row 0, which is slightly non-standard but much cleaner to implement.\n\nWait, that's overcomplicating it. I'll just spawn pieces at y=-1 and not render any cells with screen_y < 0. For game-over detection, I'll check if any piece cells overlap with existing blocks after spawning.\n\nActually, the standard approach is simpler: spawn at y=-1, check for collisions including cells at negative y positions, and if there's a collision, that's game over. Let me stop overthinking this and just write the code.\n\nWriting Tetris spawn logic... I need to nail down the spawn position logic and then actually start implementing. For the I piece, I'll spawn it at y=-1 so the visible cells start at y=0, while other pieces spawn at y=0. Now I'm double-checking the SRS kick offset convention—the wiki uses (column, row) where positive row means up, but since I'm working in screen coordinates where down is positive, I'll need to flip the sign on those row values. Now I'm verifying the I piece kick data by converting the wiki coordinates to screen space with negated y-values, and I need to make sure I'm using the correct negated values instead of the raw wiki data. I'm converting the wiki's rotation kick offsets to screen coordinates where row increases downward instead of upward, so positive row values in the wiki become negative in screen space and vice versa. Now I need to work through the complete I-piece kick table for all rotation transitions, starting with the reverse direction from R back to 0. I'm working through the rotation state transitions for the Tetris piece, mapping how each orientation transforms when rotating clockwise and counterclockwise, with the wiki coordinates converting to screen space by flipping the y-axis. I'm working through the rotation state transitions for the J piece, converting between wiki coordinates and screen coordinates. Let me verify the R→2 and 2→R transitions are actually identical, then check the 2→L rotation to make sure I have the offset calculations right. , let me check the wiki values again. Actually I need to double-check each entry.\n\nFrom https://tetris.wiki/SRS wall kick table for JLSTZ:\n\nTest 1 = (0,0) always (no offset attempt)\nTest 2:\n- 0->R: (-1,0)\n- R->0: (+1,0)\n- R->2: (+1,0)\n- 2->R: (-1,0)\n- 2->L: (+1,0)\n- L->2: (-1,0)\n- L->0: (-1,0)\n- 0->L: (+1,0)\n\nTest 3:\n- 0->R: (-1,+1) → screen: (-1,-1)\n- R->0: (+1,-1) → screen: (+1,+1)\n- R->2: (+1,-1) → screen: (+1,+1)\n- 2->R: (-1,+1) → screen: (-1,-1)\n- 2->L: (+1,+1) → screen: (+1,-1)\n- L->2: (-1,-1) → screen: (-1,+1)\n- L->0: (-1,-1) → screen: (-1,+1)\n- 0->L: (+1,+1) → screen: (+1,-1)\n\nTest 4:\n- 0->R: (0,-2) → screen: (0,+2)\n- R->0: (0,+2) → screen: (0,-2)\n- R->2: (0,+2) → screen: (0,-2)\n- 2->R: (0,-2) → screen: (0,+2)\n- 2->L: (0,-2) → screen: (0,+2)\n- L->2: (0,+2) → screen: (0,-2)\n- L->0: (0,+2) → screen: (0,-2)\n- 0->L: (0,-2) → screen: (0,+2)\n\nTest 5:\n- 0->R: (-1,-2) → screen: (-1,+2)\n- R->0: (+1,+2) → screen: (+1,-2)\n- R->2: (+1,+2) → screen: (+1,-2)\n- 2->R: (-1,-2) → screen: (-1,+2)\n- 2->L: (+1,-2) → screen: (+1,+2)\n- L->2: (-1,+2) → screen: (-1,-2)\n- L->0: (-1,+2) → screen: (-1,-2)\n- 0->L: (+1,-2) → screen: (+1,+2)\n\nNow I'm compiling the complete JLSTZ kick table in screen coordinates, converting all the wiki values to match the screen coordinate system where Y increases downward. I'm verifying the rotation mappings for the Tetris pieces by testing the coordinate transformations against the wiki reference values, and they're all checking out correctly for the JLSTZ pieces. Now I'm verifying the rotation offset data for Test 3 and Test 4, checking how the I piece translates across different rotation states and confirming the screen coordinates match the expected offsets. I'm compiling the kick table in screen coordinates and noticing a discrepancy in test 5 for the 1>2 transition—it should be (2,-1) not (2,1)—so let me recalculate those offsets correctly. I'm working through the rotation transformations for each direction pair, verifying how the coordinates map to screen positions and collecting the resulting point arrays for R->2, 2->R, 2->L, and L->2 rotations. Completing the kick table for all rotation transitions in screen coordinates...\n\nNow I have the full dataset, so I can move forward with the implementation. I'll create a canvas-based Tetris game with HTML, CSS, and TypeScript, keeping the setup minimal with just a config file and package dependencies. For audio feedback, I'm planning to use the Web Audio API to generate distinct sounds for different actions—clicks for movement, chirps for rotation, a thud when pieces lock, a chime for line clears, a fanfare for level ups, and a descending tone for game over.\n\nWriting the TypeScript implementation... Defining the piece shapes and wall kick data... Defining kick data for the I-piece... I'm verifying the rotation logic by working through a concrete example—checking whether my clockwise rotation formula correctly transforms the matrix positions, but I'm catching an error in my verification that suggests the implementation might not be right. Verifying the formula works across all positions in the matrix, and it checks out perfectly. Now I'm writing a function that applies this clockwise rotation by creating a new matrix where each element at position [i][j] comes from [n-1-j][i] of the original.\n\nFor the counterclockwise rotation, I'm deriving the formula new[i][j] = old[j][n-1-i] and verifying it produces the correct result when rotating the test matrix. Writing the CCW rotation function...\n\nNow I'm thinking through the I piece spawn positioning again—when it spawns at x=3, y=0, the empty row at the top means the actual tetromino starts rendering from screen row 0.\n\nTo get the horizontal bar to appear at row 0, I need to spawn at y=-1 instead. For the collision detection during spawn, checking against screen rows that might be -1 is fine since nothing can be placed there. So my approach is: I piece spawns at y=-1 to position the bar at screen row 0, the O piece (2×2) spawns at y=0 for rows 0-1, and the other 3×3 pieces spawn at y=-1 so their top row sits off-screen while the actual blocks start at row 0. But I need to reconsider the T piece...\n\nActually, looking at standard Tetris implementations, having the I piece drop from row 1 instead of row 0 might be acceptable, but it does look odd to the player. I'm going to use a spawn function that returns -1 for the I piece and 0 for everything else, then handle collision detection so that cells with negative y-coordinates are treated as valid (non-colliding) during the spawn check.\n\nFor simplicity, I'll make cells with y < 0 invisible and not checked against the board floor, while left/right collision still applies to all y values. Game over triggers only if any visible cell (y >= 0) is already occupied when the piece spawns.\n\nI've been overthinking this—time to just implement the full code.\n\nWriting complete Tetris implementation... Defining the piece shapes and SRS rotation kick tables... Defining the kick system data... I'm deciding on the simplest structure—putting the TypeScript file at the root level so it compiles directly to `tetris.js` in the same directory, which the HTML can then load straightforwardly. I'd name the output to `tetris.js` which the HTML loads. With `outDir` set to `.` and `rootDir` set to `src`, compiling `src/tetris.ts` would output `tetris.js` at the root level, avoiding any file conflicts. I'm configuring the TypeScript compiler with ES2020 target, DOM library support, and strict mode enabled.\n\nNow I'm ready to write out the complete implementation. I've got all the core features planned: the seven tetrominoes with their colors, SRS rotation system with wall kicks, ghost piece display, next piece preview, hold functionality, a scoring system based on lines cleared and level multipliers, and level progression that increases every ten lines.\n\nI'm also including keyboard controls for movement and rotation, delayed auto shift for smooth piece movement, pause and game over screens, plus the optional polish features like sound effects through the Web Audio API, a start screen, and localStorage for tracking high scores. The visual design will use a dark blue-purple background with subtle glowing borders around the play area, solid colored pieces with highlights and shadows for depth, and a very transparent ghost piece to show where pieces will land.\n\nFor typography, I'm considering a retro pixel font like \"Press Start 2P\" from Google Fonts to match the classic Tetris aesthetic, with a fallback to system monospace fonts for the numbers. The canvas will be sized at 300px wide by 600px tall to accommodate the standard 10-column by 20-row play field.\n\nWriting the game code... Writing the block rendering function... I'm finishing up the ghost piece drawing function that just outlines the block with a stroke, then moving on to handle the line clear animation. I want to add a nice visual effect where cleared rows flash white briefly before collapsing down, which means I'll need to track animation state and progress. Now I'm ready to write out the full implementation, organizing it into logical sections starting with constants like grid dimensions and block size.\n\nWriting TypeScript implementation... Defining the game piece data... Defining kick offset data... Defining game constants and interfaces...\n\nNow I'm setting up the rotation logic for pieces—functions to rotate the tetromino matrices clockwise and counterclockwise by transforming the indices. Then I'm initializing the audio context and starting to build out sound effects for different game actions like moves and rotations.\n\nWriting audio effects... Still writing sound effects... Writing sound synthesis code... Still writing sound effects...\n\nNow I'm setting up the game state structure with types for the board, pieces, and game data, then starting to define a bag generator class for randomizing piece selection.\n\nImplementing the piece randomization...\n\nNow I'm setting up the piece creation logic, calculating the spawn position based on the piece width and centering it on the board, with the I-piece spawning slightly higher since it has an empty top row. Then I'm building the validation function to check if a piece can occupy a given position by testing each block against the board boundaries and existing pieces.\n\nI'm also implementing the ghost piece calculation to show where the piece would land, and starting the rotation logic that will handle both clockwise and counterclockwise rotations with wall kick offsets. Writing game mechanics... Now I'm checking which rows are completely filled and triggering the appropriate clear animation and sound effects—if all four rows clear at once, that's a Tetris and gets a special sound, otherwise just a regular clear sound. Then I reset the lock timer and hold state to prepare for the next piece.\n\nFor the line clearing function, I'm removing the completed rows in descending order so the indices don't shift, adding empty rows to the top, updating the score based on how many lines cleared and the current level, and checking if we've leveled up.\n\nNow I'm handling the high score persistence by saving it to localStorage if the current score exceeds it, then moving on to spawn the next piece by swapping in the queued piece and checking if the game is over, and finally implementing the hold mechanic where you can swap your current piece with a previously held one. Writing the block rendering function... Writing the board rendering... Now I'm rendering the ghost piece to show where the current tetromino will land, then drawing the active piece itself on top of it. Writing the preview canvas... Writing the stats display... Writing input handling logic... Handling the remaining rotation and action keys...\n\nNow I'm setting up the key release handlers to reset the directional input states, then implementing the delayed auto-shift system that accelerates piece movement when a direction is held down, calculating how many repeat movements should trigger based on elapsed time versus the configured delays. Still writing input handling... Still writing game logic... Setting up the canvas contexts for the main game board and the next/hold piece displays, then initializing the game state with an empty board, retrieving the high score from local storage, and setting up all the game properties like timers and piece management...\n\nNow I'm attaching event listeners for keyboard input and the restart button, then kicking off the game loop with a requestAnimationFrame call.\n\nWait, I'm noticing an issue with the hold piece logic—when swapping a held piece, I need to make sure I'm properly spawning the next piece if the current one becomes null after the swap.\n\nRefining the hold function...\n\nI'm noticing some inconsistencies in how pieces spawn after holding. When there's already a held piece, I create a new one directly from the held type, but when there's no held piece, I call `spawnNext` which handles the delay logic for cleared lines. The issue is that `lockPiece` sets `game.current = null` before calling `spawnNext`, but if line clearing is animated, the timing gets complicated—I need to make sure the next piece doesn't spawn until the animation finishes. I'm checking the `lockPiece` function to verify the order of operations—specifically when `game.current` gets set to null relative to calling `spawnNext` or setting up the clear animation. Let me trace through the actual implementation to make sure the state transitions are correct. I'm realizing I should reconsider the sound design here—when lines clear, I probably shouldn't play the lock sound separately since most Tetris games just use the clear sound effect. Let me adjust the logic to only play the lock sound when no lines are cleared, then handle the clear or tetris sound for successful clears.\n\nNow I'm thinking through the game over condition when a piece locks with cells above the board. I should check if any blocks end up at y < 0 when locking, which would trigger game over. For spawning new pieces, I need to detect if the piece overlaps with existing board cells at spawn position—that's also a game over state. Updating collision detection...\n\nI need to think through the game-over condition more carefully. The standard approach is to check if the piece locks with any cells above the visible board—but for pieces like the I-piece that spawn partially off-screen, I need to distinguish between cells that are legitimately hidden during spawn versus a true game-over state. Let me trace through what happens when the I-piece drops from its spawn position at y=-1: the top rows are off-screen, but the visible portion should still be able to lock normally. I'll use a stricter rule where game over only triggers if the piece can't move down at all from its spawn position, rather than checking cell positions after locking. I'm realizing the `isValidPosition` function doesn't actually validate cells at y < 0—it only checks collisions for cells within the board bounds. This means pieces can have cells floating above the board, and after a hard drop, `getGhostY` could position a piece so some cells end up at negative y values if the board is mostly empty.\n\nLet me trace through what happens with the I piece specifically: it spawns at y=-1, so its rows are positioned at -1, 0, 1, and 2. As it falls, the piece moves down until the lowest valid position is reached—which for the I piece would be around y=18, where the bottom row hits the boundary. So after a hard drop, all the I piece's cells end up between rows 0 and 19, staying within valid screen bounds. I'm working through the collision detection for the I piece at different y positions—when the piece is at y=18, the bar sits at screen row 19 (the bottom), which is valid, but at y=19 it would extend beyond the grid. So the hard drop stops at y=18, and when locking the piece there, I need to verify that all cells in the occupied rows map correctly to the grid without going out of bounds. the piece could end up locked with cells at negative y values, which would then be invisible on screen but still occupy board state. That seems like an edge case that probably doesn't matter in practice since those cells would never interact with falling pieces anyway.\n\nI think the safer approach is to only trigger game over when a piece spawns and immediately collides—not when it gets locked at negative y values from some weird rotation kick. So I'm removing that `by < 0` check from the lock function and instead just skipping placement of any cells that are above the visible board.\n\nUpdating the lock piece function...\n\nActually, this is getting unnecessarily complicated for edge cases that probably won't happen in normal gameplay, so I should just keep it simple.\n\nI'm noticing that `lockDelay` is defined in the GameData interface but I'm using a constant instead, so I can remove that redundancy. Let me clean up the code and stop overthinking this.\n\nNow I need to be careful with TypeScript strict mode—things like `document.getElementById()` and `canvas.getContext('2d')` can return null, so I need proper type guards. I should also make sure all my variables are properly typed so the code compiles cleanly.\n\nSetting up the project structure with HTML, CSS, TypeScript, and config files... Building the game layout... I'm working through the canvas dimensions for the game preview areas—the main board needs to be 300×600 pixels to fit the 10×20 grid at 30px per block, and I'm settling on 120×120 for both the next piece and hold piece previews so they can properly display the piece matrices at 24px scale.\n\nFor rendering the previews, I'll draw each piece centered in its canvas by computing the minimal bounding box and centering that within the fixed 120×120 area.\n\nWriting preview rendering function... I'm verifying the vertical centering for each piece type—the I piece lands around y=36 which looks reasonable, the O piece sits nicely centered at y=36-84, and the T piece with its empty bottom row positions the actual blocks in the upper portion of the canvas, which should display correctly.\n\nNow I'm realizing the I piece might not be perfectly centered since the matrix has that empty first row, so I need a function that finds the actual bounding box of the blocks rather than relying on the full matrix dimensions.\n\nWriting bounding box function...\n\nI've got my implementation plan locked in: build the HTML structure, add the CSS styling, write the TypeScript game logic, configure the build setup, then compile and run it. The main canvas will be 300×600 pixels with 24-pixel blocks, the preview windows are 120×120, and I'll add a 300ms flash animation when lines clear.\n\nFor the input handling, I'm using a 500ms lock delay with 167ms DAS and 33ms repeat rate for smooth piece movement, plus Web Audio API for sound effects. I need to be careful with TypeScript's strict mode when accessing DOM elements, so I'll use non-null assertions and ensure DOMContentLoaded fires before initializing anything.\n\nConfiguring tsconfig.json... I'm second-guessing the module setting—TypeScript is case-insensitive for this, but I'll use lowercase \"none\" to be safe. The output path looks right: with `rootDir` set to \"src\" and `outDir` as \".\", the compiled `tetris.js` will end up at the project root where the HTML can load it directly. Now I'm ready to write out the full configuration and implementation.\n\nWriting the CSS styles... Still writing styles... Still writing styles...\n\nThe font size might be too cramped for displaying the stat values clearly, so I should reconsider the typography choices.\n\nPress Start 2P is the classic Tetris font and at 16px it captures that authentic retro feel perfectly. I'll use it for the labels at 8px (the minimum readable size) and bump the values up to 16px for better legibility. The left panel will show stats with this hierarchy, while the right panel keeps the canvas centered with minimal text.\n\nFor the actual dimensions, \"SCORE: 999999\" at 16px takes up about 96 pixels for just the numbers, so I need roughly 130-140px for the left panel with padding. The right panel needs similar width to accommodate the 120px canvas for the next/hold pieces plus some breathing room. I'm checking if the total layout will fit properly on screen.\n\nAdding up the widths—left panel at 130px, a 16px gap, the main board at 300px, another gap, and the right panel at 150px—comes to around 612px, which with page padding should land somewhere between 650-700px total. That's reasonable for most desktop screens, though I should note this works best on desktop rather than mobile.\n\nNow I'm ready to start writing the actual implementation systematically, beginning with the project structure and configuration files, then moving into the HTML, styles, and TypeScript game logic. I need to be careful about handling null checks for the game state during animations.\n\nFixing the hold piece logic...\n\nThe key insight is that swapping with a held piece doesn't consume from the next queue—we just use the stashed piece directly. Only when there's no held piece do we call `spawnNext` to pull from the bag and generate a new next piece.\n\nNow I'm adding a visual indicator for when hold is unavailable by drawing a semi-transparent overlay on the hold canvas when `canHold` is false. I realize that checking `!game.canHold` alone is sufficient since `canHold` being false guarantees `held` is non-null, but I still need to handle the initial state where `canHold` is true and `held` is null—the preview drawing function already handles null types gracefully by filling with black. Now I'm ready to write out the actual implementation files.\n\nI'm setting up the project structure with TypeScript and planning the key animations: using `requestAnimationFrame` with `performance.now()` for smooth timing, a 300ms line clear effect that flashes rows between white and their original colors before collapsing, and HTML overlays for UI states like pause and game over while keeping the canvas focused on active gameplay. The start screen will display \"TETRIS\" and \"Press Enter to Start\" over an empty board.\n\nNow I'm working through the line clear animation logic—when lines are cleared, I'll set a `clearAnim` object to track the animation state, flash the rows using a sine wave pattern to create the white flashing effect, and after 300ms complete the collapse and spawn the next piece. Writing the clear animation... Writing the Tetris implementation... LSTZ, KICKS_I (wall kick data)\n- LINE_SCORES, getLevelSpeed(), DAS constants, LOCK_DELAY, CLEAR_ANIM_DURATION\n\nTypes:\n- Cell = string | null\n- Board = Cell[][]\n- Piece { type, matrix, x, y, rotation }\n- GameData { board, current, next, held, canHold, score, level, lines, state, dropTimer, lockTimer, lockMoveCount, clearAnim, highScore }\n- GameState = 'start' | 'playing' | 'paused' | 'gameover'\n\nFunctions:\n- getKicks(type, from, to): [number, number][]\n- rotateCW(matrix): number[][]\n- rotateCCW(matrix): number[][]\n- playSound(type): void\n- createBoard(): Board\n- createPiece(type): Piece\n\nNow I'm mapping out the core game mechanics—position validation, ghost piece calculation, rotation with wall kick support, and piece movement. I'm also handling the rendering pipeline with separate functions for blocks, the board state, and preview windows, plus the input handling and game state updates. Writing the TypeScript implementation...","signature":"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Let me build a complete Tetris game with all standard mechanics:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrows for movement, up/Z for rotation)\n\nLet me create a well-structured TypeScript project. I'll create:\n\n\n- `index.html` - The main HTML file\n- `src/tetris.ts` - The main game logic\n- `package.json` - For TypeScript compilation\n- `tsconfig.json` - TypeScript configuration\n\nI'm planning the game structure with a standard 10×20 board, all seven tetrominoes with their colors, and keyboard controls for movement and rotation.\n\nFor scoring, I'm using the classic Tetris formula where clearing multiple lines gives exponentially higher points multiplied by the current level, and the game speeds up every 10 lines cleared.\n\nI'm going to set up a proper TypeScript project structure with compilation, then write the game logic directly in TypeScript.\n\nDefining the tetromino shapes...\n\nNow I'm laying out the core game state structure with the board, current and next pieces, and tracking score, lines, and level. I'll need to implement collision detection, rotation with wall kicks, line clearing, and a ghost piece preview. Let me start writing the TypeScript implementation...\n\nWriting the game logic... Writing the Tetris implementation... Defining the tetromino pieces and their colors...\n\nActually, I need to reconsider how to handle the O piece—whether to use a 2x2 grid or pad it to 4x4 for consistency with the rotation system. Let me go with the standard SRS definitions where the I piece uses a 4x4 grid and the O piece stays as 2x2 since it doesn't rotate.\n\nFor wall kicks, I'll implement basic offset logic rather than the full SRS tables to keep things simpler but still functional. Now I'm writing out the TypeScript implementation with the core constants, types, and tetromino definitions.\n\nWriting Tetris game code... Finishing up the tetromino definitions, then setting up the game constants for scoring and drop speed mechanics.\n\nNow I'm writing utility functions to handle piece rotation by transposing the matrix, creating a fresh game board, and cloning boards for state management.\n\nSetting up the main game class with canvas contexts for the main board, next piece preview, and hold piece display, along with tracking the current piece, score, level, and game state variables. Setting up the canvas dimensions and initializing the game state with a fresh board, score tracking, and spawning the first piece before starting the game loop.\n\nNow I'm implementing the piece spawning logic, randomly selecting from available Tetromino types and positioning them at the top center of the board, with special handling for the I-piece which needs to start slightly higher.\n\nContinuing with collision detection...\n\nNow I'm implementing the lock mechanism that places the current piece on the board once it can't move anymore. I iterate through the piece's shape, mark each occupied cell with the piece's color, then check if the piece spawned above the visible area to trigger game over. After locking, I clear any completed lines, reset the hold ability, and spawn the next piece.\n\nNow I'm handling line clearing by checking each row from bottom to top, removing complete rows and adding empty ones at the top while tracking how many lines were cleared. I'm then updating the score based on the number of cleared lines multiplied by the current level, recalculating the level based on total lines cleared, and adjusting the drop speed accordingly.\n\nWriting game mechanics... Writing game mechanics... Writing the drawing functions... Still writing the rendering logic... Drawing the active piece and pause overlay... Writing the preview rendering... Finishing the game over display with the score and restart prompt, then moving into the game loop where I'm handling the timing delta and managing the piece drop mechanics with a counter that triggers locking when the piece can't move down anymore.\n\nNow I'm handling the delayed auto-shift for horizontal movement, where holding left or right builds up a timer that triggers repeated moves after an initial delay, then continues at a faster interval. Still writing input 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4729,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":4729,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"9160c245-c9ca-4da0-a64f-1ee14b0a2b83","uuid":"7b318f21-96a4-40d6-a39a-eed80f99a0af"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01E7raw3DA8tdG67buyvGwqJ","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me build a complete Tetris game with all standard mechanics:\n\n1. All 7 standard Tetris pieces (tetrominoes): I, O, T, S, Z, J, L\n2. Piece movement: left, right, down\n3. Piece rotation\n4. Line clearing\n5. Scoring system\n6. Increasing speed\n7. Keyboard controls\n\nLet me plan the structure:\n- `index.html` - Main HTML file\n- `src/tetris.ts` - TypeScript source\n- We'll compile to JS or use a simple setup\n\n\n- I'll keep it simple with TypeScript that compiles to JavaScript, then reference the compiled output in the HTML file.\n\nNow I'm laying out the core game structure: a standard 10×20 board with the seven tetromino pieces, each with their own color, plus tracking the current piece position and rotation, next piece preview, score metrics, and game state. The mechanics involve gravity pulling pieces down automatically with speed ramping up as the level increases.\n\nFor controls, I'm mapping arrow keys for movement and rotation, space for instant drops, and P to pause. The scoring follows classic Tetris rules where clearing multiple lines at once gives exponential bonuses, and the level advances every 10 lines cleared.\n\nWriting the TypeScript implementation... Defining the tetromino shapes... Defining the remaining Tetris pieces...\n\nI'm noticing the piece definitions are inconsistent—the I piece uses 4x4 matrices while the others are 3x3. I should normalize everything to a uniform grid size to keep the rotation logic clean. Let me redesign this with all pieces fitting in a 4x4 grid for consistency.\n\nDefining the Tetris pieces... Defining the tetromino pieces with their rotation states and colors... Defining the Tetris piece rotations... Defining the piece rotations... Defining the rotation states for the remaining Tetris pieces... Defining the rotation states for the remaining Tetris pieces... Defining the Tetris game constants and piece definitions...\n\nNow I'm thinking through the scoring system—single lines give 100 points per level, doubles are worth 300, triples 500, and a full Tetris clears four lines for 800 points, with soft drops adding a point each.\n\nI need to handle the game loop with `requestAnimationFrame` to track time and manage gravity, where each level increases the drop speed, starting at roughly one second per drop at level one.\n\nWriting the Tetris implementation... Defining the tetromino shapes... Defining the rotation states for the S and Z tetromino pieces... Defining the game class... Setting up the canvas contexts and DOM elements, then initializing the game board with an empty grid, spawning the first piece, and wiring up the input handlers to start the game loop.\n\nNow I'm handling keyboard input for game controls—checking if the game is over to allow restart, toggling pause with P, and then mapping arrow keys to piece movement and rotation, with Space for hard drop.\n\nContinuing with game logic... Writing rotation and wall kick logic... Writing the game logic... Writing the rendering logic... Writing the render loop... Writing overlay text... Writing the game loop and reset logic...\n\nNow I'm setting up the HTML structure with styling for the game board and UI elements. Still writing styles... Building the game interface... I'm setting up the TypeScript configuration with ES2017 as the target and DOM libraries, then defining the build scripts to compile and watch for changes. Now I need to think through the DAS mechanic—how holding left or right will make the piece move repeatedly after an initial delay.\n\nI'll track key states with keyboard events and implement a 150ms delay before the piece starts shifting every 50ms. Rather than overcomplicating things with too many features, I'm going to focus on getting the core mechanics right: all seven pieces with proper rotations, a ghost piece preview, smooth movement with DAS, wall kicks for rotation, and a brief lock delay so players can adjust at the last moment. I'll skip the line clear animation for now and keep the implementation clean and bug-free.\n\nMy file structure will be straightforward with an HTML entry point, a TypeScript implementation file, and the necessary config files. Now I need to verify my rotation matrices are correct, particularly for the T piece and other shapes.\n\nVerifying rotation matrices... Verifying the rotation matrices for the I, O, and S pieces—the I piece cycles through vertical and horizontal orientations, the O piece stays identical in all rotations, and I'm working through the S piece's four rotation states to confirm the grid representations are correct. Defining the remaining tetromino rotations... I'm verifying the rotation matrices for each tetromino piece, particularly the I piece since its rotations can be tricky with the standard Tetris rotation system. The I piece rotations look correct. For spawning, pieces appear at x=3 (centered) and y=0, though the actual visible cells depend on the shape—the O piece's empty first row means it starts showing at y=1, which is fine. I'm double-checking my O piece definition to make sure it's consistent. Defining the O piece shape...\n\nI'm thinking through how to handle piece spawning and the buffer zone at the top of the board. The standard approach is to spawn pieces with y=-1 so they enter from above, only rendering cells that fall within the visible play area. This way pieces appear to smoothly enter from the top rather than starting with gaps. of their 4x4 grid, they'll appear inside the board. Don't draw cells with y < 0 since the top row is hidden. Looking at the spawn positions for each piece, the I piece has its bar at row 1, the O piece occupies rows 1-2, and the T piece starts with its top at row 1 and stem at row 2 — so they all have that same 1-row gap at the top of the grid. I'm going to redefine the piece shapes so the 3x3 pieces (T, S, Z, J, L) sit at the top of the 4x4 grid without that extra empty row, and I'll do the same for the I piece to keep everything consistent. I'm settling on a straightforward approach: all pieces are 4x4 matrices that spawn at y = -1 (just above the visible board), and I'll simply skip rendering any cells with negative y-coordinates. This way, the game logic stays clean and the spawn position naturally handles the different piece shapes without needing special cases. Looking at my earlier implementation, the collision detection already handles cells above the board correctly by allowing negative y values, and the drawing logic only renders cells that are actually visible on screen. This approach keeps things simple and avoids the game over detection issue.\n\nNow I'm thinking about adding lock delay to make the game more playable—when a piece touches the ground, instead of locking immediately, I'll give the player a brief window (around 500ms) to move or rotate before it locks. This is a standard Tetris mechanic that significantly improves the feel.\n\nWriting the complete implementation... Defining the piece shapes... Defining the rotation states for the remaining Tetris pieces... Defining the piece rotations...\n\nI'm realizing I need to reconsider the O piece positioning for consistency with how the I piece spawns. The I piece in its standard rotation has an empty row at the top when it appears, which matches the SRS standard. I should verify the O piece follows the same convention.\n\nLooking at the spawn positions: when pieces spawn at y=0, the I piece's blocks appear at board row 1 (leaving the top empty), while the other standard pieces like T, S, Z, J, L have their blocks starting at row 0. The O piece should match this pattern too, appearing with its top at the board's top row when spawned. Verifying the S, Z, J pieces and their rotations - S has the right cells stacked on top with left cells below, Z mirrors that pattern, and J has its corner piece positioned at the top-left with the body extending right.\n\nNow I'm thinking through the complete implementation, particularly how `lockPiece` should handle pieces that extend above the board at y < 0, which would typically signal a game over condition since those cells can't be placed on the board.\n\nFor spawn detection, I need to check if the newly spawned piece immediately collides with existing blocks—if it does, that's game over. My `isValidPosition` function already handles this by checking if any cell at y >= 0 is occupied on the board, so the collision detection should work correctly for the spawn condition.\n\nNow I'm thinking about DAS (Delayed Auto Shift) to make the controls feel responsive. I want to track held keys and implement a delay before auto-repeat kicks in, then repeat at a faster rate. I'll manage this with timeouts and intervals tied to each key press.\n\nSetting up DAS handlers... I'm thinking through the visual polish—adding block highlights for depth, translucent ghost pieces, and maybe a line clear flash, though that animation might be overkill for now. But I'm realizing my DAS implementation has a flaw: it won't respect pause states, so I need to add pause checks in the action callbacks. Also, soft drop scoring should happen in the game loop itself rather than in keydown handlers to keep concerns separated. Actually, I think a cleaner approach is to track key states directly in the game loop instead of using setInterval callbacks.\n\nWriting the implementation... Defining the piece shapes and rotations... Defining the rotation states for the remaining Tetris pieces... Defining the piece rotations and types... Setting up the game class... Setting up the piece spawn logic and validation...\n\nNow I'm implementing the collision detection to check if a piece fits within bounds and doesn't overlap with placed blocks. The move function handles shifting pieces left, right, or down while validating each position, and resets the lock timer when pieces successfully move downward. For rotation, I'm attempting the standard rotation first, then trying wall kicks if that fails.\n\nWriting game logic... Now I'm handling the line-clearing logic by removing completed rows and shifting the board down, then updating the score based on how many lines were cleared and the current level. I also have a ghost piece function that calculates where the current piece would land if dropped straight down.\n\nSetting up the game loop to handle timing and piece movement, where I track elapsed time between frames and apply gravity at a speed that increases with the level, plus implementing lock delay so pieces don't snap into place instantly when they hit the bottom.\n\nNow I'm wiring up keyboard input to handle game controls like movement, rotation, and pause, with special handling for game-over and paused states, plus implementing delayed auto-shift for smoother left and right movement. Setting up the DAS (Delayed Auto Shift) system with timers that handle the initial delay before rapid-fire key repeats, then clearing those timers when keys are released.\n\nNow I'm updating the UI to display the current score, level, and lines, then drawing individual blocks on the canvas with shading and highlights to create a 3D effect. Writing the rendering logic... Writing the game rendering... Writing the game over screen... Refining the keyboard event handling to prevent default scrolling behavior for game controls regardless of pause state, then selectively applying preventDefault only to the relevant arrow and space keys.\n\nNow I'm thinking through the HTML structure—I want a dark-themed layout with the game board on the left and a sidebar on the right displaying score, level, lines cleared, and a preview of the next piece. I should also add a title and some visual polish to make it feel polished.\n\nBefore I start writing everything out, I need to decide whether to include build instructions or make this directly runnable in the browser—since the user wants a playable game that works immediately, I'm leaning toward including pre-compiled JavaScript so it just works without any setup.\n\nLet me structure the project with TypeScript source files, a tsconfig for compilation, and a package.json with build scripts, then I'll also add some visual enhancements like a gradient background and animated elements to make the game feel more impressive.\n\nI'm noticing a potential issue in the game loop where the lock timer logic might not properly handle game-over states when a new piece spawns. Refactoring the lock method to place valid pieces on the board first, then flag if any cells ended up above the board boundary to trigger game over. Finishing the lock method...\n\nI'm completing the `lock()` method to place the piece's blocks on the board, skipping any cells above y=0, then clearing completed lines and spawning the next piece. For `spawn()`, I'm setting up the new piece with the queued type, randomizing the next one, and checking if placement is valid—if not, the game ends. Now I'm looking at the game loop's drop and lock timer logic to make sure the piece locks correctly when it can't move down anymore. I see the issue now—the lock timer increments every frame regardless of gravity ticks, so I need to reset it whenever the player successfully moves or rotates the piece while it's grounded, not just on downward movement. This matches standard Tetris behavior where any action resets the lock delay timer. I need to think through the lock timer logic more carefully. The key insight is that gravity moves should reset the timer (keeping it null), but horizontal moves should restart the countdown by setting it to 0, giving the player more time to position the piece before it locks. I'm also considering tracking whether the piece is on the ground as a separate state to make this cleaner.\n\nImplementing the lock timer logic... Finishing the lock timer logic...\n\nThe key insight is that when a soft drop successfully moves the piece down and it lands on the ground, the lock timer should restart from zero at that position, giving the player a fresh window to make adjustments before it locks. My main loop handles this naturally by checking `isOnGround()` after each move and initializing the timer accordingly.\n\nBut I'm realizing the timing gets messy when gravity and player input both trigger movement in the same frame—I could end up dropping twice. Rather than overcomplicating this, I'll go with a straightforward approach: use a simple 500ms lock delay where the timer cancels whenever the piece successfully moves down, whether from gravity or player input, and locks once the timer expires after the piece gets stuck. I'm going to simplify this and just implement a basic lock delay where the piece locks a fixed time after touching the ground, resetting only when the piece actually moves to a new position. Writing the Tetris implementation... Defining the piece shapes... Defining the S and Z piece rotations... Defining the piece rotations... Setting up the game state variables...\n\nNow I'm initializing the canvas dimensions, creating the game board, spawning the first piece, and setting up the game loop with event listeners.\n\nI'm resetting the drop and lock accumulators, then defining helper methods to get the shape cells for a piece and validate whether a piece can be placed at a given position by checking bounds and collisions.\n\nStill writing game logic... Writing game logic... Writing game loop logic... Writing event handlers... Setting up the DAS (delayed auto-shift) system to manage key repeat timing, storing timeout and interval IDs in a map so I can cancel them when keys are released. Then I'm updating the UI elements to display the current score, level, and line count, and starting to implement the block drawing logic.\n\nDrawing individual blocks... Writing the rendering logic... Writing overlay UI... Writing the game restart logic...\n\nNow I'm setting up the HTML structure and CSS styling for the game board and sidebar, planning dimensions around 470px wide and 600px tall to fit nicely on most screens. I'm also realizing the DAS timeout handling in `startDas` is actually fine since the timeout fires before the interval overwrites it. logic checks out. Now I'm ready to write the final implementation to files. I'm skipping the high score feature to keep things focused, and I'll set the initial UI values directly in the HTML rather than calling refresh functions unnecessarily. Let me also verify the drop speed progression—it starts at 1000ms and accelerates as levels increase, bottoming out around 65ms at higher levels.\n\nFinalizing the speed formula...\n\nI'm defining a lookup table with drop speeds that decrease gradually from 800ms at level 1 down to 50ms at level 13 and beyond, giving a smooth difficulty curve without needing a complex mathematical formula.\n\nActually, I think an exponential decay formula would be cleaner—using a base of 0.85 means each level multiplies the speed by 0.85, so level 1 starts at 1000ms, level 2 drops to 850ms, and it bottoms out at 50ms around level 16. This feels like a better approach than the arbitrary lookup table.\n\nNow I'm ready to actually write the code. I'll set up the project structure with an HTML file, TypeScript source, and config files, then handle keyboard input properly by preventing default scrolling behavior on game keys. I'm keeping the feature set minimal and classic—no hold piece, just straightforward Tetris—and I want to display the high score prominently in the UI.\n\nFor the visual polish, I considered adding a flash effect when pieces are about to lock, but the ghost piece already provides enough feedback, so I'll skip that and keep things clean. Let me start writing the actual implementation now.\n\nWait, I need to think through the line-clearing logic...\n\nwhen I splice out a full row and unshift a new empty one at the top, the indices shift. After removing row r and adding the empty row, what was at r-1 moves to r, so I need to recheck that same index. My loop structure handles this correctly—the r++ after clearing cancels out the loop's r--, so I stay at the same index to check what just shifted down.\n\nAlright, the sweep logic is solid. Now I'm ready to write out all the files. I'll use a two-canvas approach with the main game board on the left and a sidebar on the right showing score, level, lines cleared, and the next piece preview. Dark theme with cyan accents to match the I-piece color.\n\nWriting the TypeScript implementation and HTML layout now... Score, level, lines displays - Controls reference. Let me write everything now.\n\nI'm realizing the keydown handler will fire repeatedly when a key is held down, and each time it calls `startDas`, which cancels the existing timeout and creates a new one. This prevents DAS from ever actually activating since the delay keeps getting reset. I need to add a check in `startDas` to skip if that key is already in the DAS map, so the initial timeout can complete without interruption.\n\nWriting the game loop and rendering... the timeout fires and `stopDas` is called simultaneously—there's a potential race where the interval gets created after `stopDas` checks the map but before it deletes the entry, leaving a dangling interval. I need to ensure the cleanup is atomic or that the timeout callback checks if the entry still exists before creating the interval. the same moment as the timeout fires? There could be a race condition in JavaScript? No - JavaScript is single-threaded. The timeout callback and the stopDas call can't execute simultaneously. ✓\n\nWhat if stopDas is called right before the timeout fires?\n1. `d = this.dasMap.get(key)` → `{ t: <timeout>, i: null }`\n2. `clearTimeout(<timeout>)` → cancels the timeout ✓\n3. `clearInterval(null)` → no-op\n4. Delete map entry\n\nBut what if the timeout was about to fire and our `clearTimeout` runs right before it? `clearTimeout` will cancel the pending timeout callback. ✓\n\nThe event loop guarantees that setTimeout callbacks and synchronous code can't interleave, so the DAS logic is sound. Now I'm ready to write out the full implementation. I'll also add high score persistence using localStorage to track the best score across sessions, displaying it in the sidebar alongside the current score.\n\nWriting the event listener... I'm handling keyboard input with DAS (delayed auto-shift) for left/right movement, using `e.repeat` to skip auto-repeat events and manage the timing manually instead. For rotation and hard drop, I'm preventing auto-repeat entirely since those should only trigger once per keypress. Now I'm thinking through the visual style and color scheme for the game. I'm settling on a clean dark theme with a simple terminal aesthetic using a monospace font, then considering a gradient background approach for something more modern before deciding on the final styling direction.\n\nBuilding the HTML structure... Writing the stylesheet... Still writing styles...\n\nI'm settling on a 140px sidebar width to give the labels and values more breathing room, and the 300x600px board dimensions should fit well on most screens with the title and controls taking up additional space. Let me finalize the implementation now.\n\nActually, I need to verify the next piece preview canvas—it's 4×30px blocks, so 120px total. The tetromino shapes fit in the top-left area, but centering them in that space would look better. I'm calculating the bounding box of each piece and offsetting it to center within the 4×4 grid, though the pieces have different offset patterns depending on their orientation.\n\nWriting the render function... I'm finishing up the loop that draws each block at its centered position, then moving on to set up the actual project files—I'll need package.json, tsconfig.json, index.html, and the main tetris.ts file to get this working.\n\nWriting the TypeScript implementation... Defining the piece shapes... Defining the rotation states for the S and Z pieces... Defining the piece rotation states... Setting up the Tetris class with canvas contexts for the main board and next piece preview, initializing game state variables like score, level, and lines cleared, and setting up input handling with a debounce system for directional controls. Setting up the piece spawn logic with initial position and rotation, then checking if the piece is valid on the board—if not, the game ends and I save the best score. I'm also defining helper methods to get the shape of a piece and validate whether a piece can occupy certain cells without colliding with walls or existing blocks.\n\nNow I'm implementing the movement logic, where I calculate which cells a piece occupies by iterating through its shape matrix, then attempting to move the piece by checking if the new position is valid before updating it.\n\nWriting game mechanics... Writing game logic... Writing input handler... Writing the input handler logic...\n\nNow I'm handling the cleanup for repeated key presses, clearing any existing timeouts and intervals before setting up new ones. Then I'm checking if the current score beats the best score and saving it to localStorage if it does, along with refreshing the UI to display the updated score, best score, level, and lines cleared.\n\nDrawing block elements... Continuing the render method... Writing the overlay UI... Writing the next piece preview... Finishing the restart method and initializing the game...\n\nNow I'm tracing through the locking mechanism to verify the flow works correctly—when the piece can't move down anymore, `isLocking` gets set to true, then the lock happens and `spawn()` resets the flag, which should handle all the cases properly. ), so I'd just use `%=` to keep only the remainder after dividing by the interval—that way we don't accumulate excess gravity across frames and the logic stays simple. Simplifying the gravity check...\n\nI'm realizing that using a simple `if` statement means the piece only drops once per frame, even if the accumulator has built up multiple intervals worth of time. This could cause the piece to fall slower than intended during frame drops, but at normal framerates it should be fine since the accumulator won't accumulate much between frames. exactly 1 interval → 1 drop. Fine.\n\nAt Level 13+ (50ms interval), if the game lags for 1 second: `dropAcc` = 1000ms = 20 intervals. We'd process 1 interval per frame, taking 20 frames to catch up. At 60fps, that's ~330ms. During this time the piece seems to fall at 2x speed (since each frame processes 1 drop but occurs every 16.7ms instead of every 50ms). Actually it would fall at 60 drops/sec instead of 20 drops/sec - 3x faster. This is acceptable behavior.\n\nOK, using `if` is fine. Let me use it.\n\nBut wait, there's a subtlety: if I use `dropAcc -= interval`, then the leftover accumulates. Next frame, `dropAcc = leftover`. If leftover > interval because the lag was so severe, we might still be behind. Using `if` instead of `while` could cause permanent lag buildup.\n\nI'll use the modulo operator to clamp the accumulator, so if `dropAcc` exceeds the interval, I process one drop and reset the remainder to zero, preventing any deficit from carrying over. I also want to reset `dropAcc` whenever the piece locks to give the player a fresh start.\n\nWhen the player soft drops, I reset `dropAcc` to prevent double-dropping. The logic feels solid now, so I'm ready to write the final implementation.\n\nI'm thinking through the `isLocking` state check in the game loop—specifically how it handles the case where gravity tries to move the piece after it's already locked. I'm accepting the infinite reset behavior for now since it mirrors standard Tetris mechanics, even if it's more lenient. Now I need to set up the event listeners, making sure to prevent default scrolling for game keys regardless of game state, so I'll move the preventDefault outside the pause and game-over checks.\n\nSetting up keyboard handler...\n\nI'm setting the canvas dimensions programmatically to avoid layout shifts, with the board at 300×600 pixels and the next piece preview at 120×120 pixels.\n\nBefore writing the final code, let me verify there won't be any TypeScript issues—checking that my array type syntax is consistent, localStorage parsing is safe, and canvas element IDs match between HTML and JavaScript.\n\nNow I'm considering whether to implement a 7-bag random piece generator instead of purely random selection...\n\nImplementing 7-bag randomization... Defining the piece shapes and colors... Defining the rotation states for Tetris pieces... Defining the rotation states for the remaining tetromino pieces... Setting up the Tetris class with private fields for the current piece, next piece queue, score tracking, game state flags, and input handling with a debounce system for key repeats, then initializing the canvas contexts and DOM elements in the constructor.\n\nNow I'm setting up the canvas dimensions, loading the best score from local storage, initializing the game grid and piece queue, and kicking off the game loop with input handlers.\n\nI'm defining a helper to create a fresh grid and implementing the piece bag system for randomized Tetris piece selection.\n\nSetting up piece spawning logic... Writing game logic... Writing game logic... Still writing game logic... Writing the input handler... Writing the rendering logic... Drawing the board background and grid...\n\nNow I'm rendering the active tetromino piece and its ghost preview, checking each cell in the piece's shape matrix and drawing blocks at the appropriate positions with reduced opacity for the ghost. Writing the overlay UI... Writing the next piece preview... Resetting the game state with a fresh grid, clearing the score and level counters, initializing the piece bag system, and then spawning the first piece. Now I'm setting up the HTML structure with a dark theme for the interface.\n\nWriting the styles... Still writing styles... Still writing styles... Setting up the TypeScript configuration and package.json to compile the game code from the src directory into a bundled output file.\n\nNow I'm creating the actual files and checking the directory structure, then examining the offset calculations for the O piece to make sure the positioning logic handles non-integer values correctly. 0 = 1\n\nSo the O piece is positioned at grid coordinates (1,1), (2,1), (1,2), (2,2) in the next preview—that's nicely centered. Now I need to verify the I piece placement in R0.\n\nThe I piece spans a single row with four blocks, giving it dimensions of 4 wide by 1 tall. When I calculate the offset, I get ox = 0 and oy = 0.5, which means the blocks would render at y = 1.5. That's a fractional coordinate, so they'll appear slightly blurry on the canvas, but I should probably round this to keep things clean.\n\nNow I'm working through the T piece in its initial rotation. It has a width of 3 and height of 2, with the stem pointing down from the center of the top row.\n\nThe offset calculation gives me ox = 0.5 and oy = 1, which means the piece would render at fractional pixel positions. To keep everything aligned to the grid, I should round these offsets instead, which gives ox = 1 and oy = 1, positioning the T piece cleanly at column 1, row 0.\n\nActually, I'm reconsidering—sub-pixel rendering on canvas should handle fractional coordinates fine, so the exact values might give better visual centering. But wait, there's a real issue: when ox = 0.5 and a block column is 1, the pixel position becomes 1.5 * 30 + 1, which could cause rendering artifacts.\n\nFor pixel-perfect rendering, I should round the offset values to integers using Math.floor to keep everything aligned to the grid.\n\nCalculating centering with Math.floor...\n\nActually, Math.round gives better centering results—it places the T piece at column 1 and handles the I piece positioning at row 2, which aligns properly with the preview grid. For I piece: c0=0, c1=3, r0=1, r1=1, pw=4, ph=1\n`Math.round((4-4)/2) = 0` → ox = 0\n`Math.round((4-1)/2) = 2` → oy = 1\n\nI block ends up at row 2, columns 0-3 in the 4x4 next canvas, centered vertically. ✓\n\nFor T piece (R0): c0=0, c1=2, r0=0, r1=1, pw=3, ph=2\n`Math.round((4-3)/2) = 1` → ox = 1\n`Math.round((4-2)/2) = 1` → oy = 1\n\nT piece positions the stem at (2, 1) and the base across (1,2), (2,2), (3,2), centering it nicely. ✓\n\nS piece (R0) uses the same offsets as T: ox=1, oy=1. ✓\n\nFor O piece: c0=1, c1=2, r0=0, r1=1, pw=2, ph=2\n`Math.round((4-2)/2) = 1` → ox = 1\n`Math.round((4-2)/2) = 1` → oy = 1\n\nO piece lands at (1,1), (2,1), (1,2), (2,2), perfectly centered. ✓\n\nUsing `Math.round` ensures all offsets are integers, preventing blurry rendering from anti-aliasing when blocks are drawn at non-integer canvas positions.\n\nNow I'm verifying the TypeScript null-safety: the 2D context assertion is safe since it's always available, the bag pop is safe because I check the length first, and I'm casting DOM elements appropriately. Everything checks out, so I can start writing the implementation. `parseInt` returns `number` in TypeScript, and `NaN || 0` evaluates to `0`, so that handles the edge case. Now I'm ready to write out the actual code files—I'll skip adding a UI button for restarting since keyboard controls are sufficient. For keyboard event handling, I should make sure the game captures input properly by either setting focus on the body or listening at the window level, though `document.addEventListener` should work fine regardless of focus state.\n\nI'm also going to prevent spacebar scrolling by calling `preventDefault()` early in the keydown handler, which I've already got covered. For responsiveness, the board and sidebar together take up around 444px, so on smaller screens I might need to add some CSS scaling to keep everything visible.\n\nActually, let me just keep this as a desktop-focused game for now and skip the responsive scaling—it gets complicated to get right. Time to write out the actual 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/eval_results.json @@ -236,7 +236,7 @@ "errors_during_play": 0 }, "performance": { - "load_time_ms": 19 + "load_time_ms": 21 }, "accessibility": { "issues": [], diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json @@ -109,7 +109,7 @@ "errors_during_play": 0 }, "performance": { - "load_time_ms": 19 + "load_time_ms": 21 }, "accessibility": { "issues": [], diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/meta.json @@ -23,8 +23,8 @@ "run_id": "tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3", "run_number": 3, "claude_version": "2.1.92 (Claude Code)", - "started_at": "2026-04-04T08:48:02.458212+00:00", - "wall_time_seconds": 954, + "started_at": "2026-04-04T09:07:02.557729+00:00", + "wall_time_seconds": 854, "exit_code": 1, - "completed_at": "2026-04-04T09:04:03.169981+00:00" + "completed_at": "2026-04-04T09:21:23.215891+00:00" } \ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl @@ -1,6 +1,6 @@ {"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} {"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} -{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-fg3fgin8","session_id":"df637926-9d56-4e49-86b1-6bb2127c25e1","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"58b597c2-b88f-46c0-81c7-e9eb73d79af6","fast_mode_state":"off"} -{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01S5xXY65YrF9oyXBTZi5chG","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me build a complete Tetris game with all standard mechanics:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls\n\nI'll create a well-structured TypeScript project. Let me think about the structure:\n\n- `index.html` - Main HTML file\n- `src/tetris.ts` - Main game logic\n\n\n- `tsconfig.json` - TypeScript configuration\n- `package.json` - Package configuration\n\nFor the build setup, I'll go with esbuild since it's simple and fast for a project like this. I'll create a proper TypeScript project that compiles down to JavaScript for browser execution.\n\nNow I'm sketching out the project structure with separate files for the game logic, rendering, input handling, and type definitions. Actually, I could consolidate this into a single well-organized TypeScript file to keep things simpler.\n\nFor the game itself, I'm thinking through the core mechanics: a 10x20 board with standard Tetris pieces in their classic colors, game state tracking for the board and falling pieces, and the essential gameplay loop. Let me map out the piece definitions and what data structures I'll need to manage the game state.\n\nI'm also planning the control scheme with standard arrow keys for movement and rotation, space for hard drop, and pause functionality. The scoring system scales with level—clearing multiple lines at once gives bigger bonuses—and the difficulty ramps up as players clear more lines, increasing the drop speed progressively.\n\nNow I'm organizing this into a modular TypeScript structure with separate files for type definitions, game constants, piece logic, board management, rendering, input handling, and the main entry point, along with the necessary build and configuration files.\n\nSetting up the build with esbuild...\n\nDefining the core type system for the game, including tetromino types, colors, board positions, piece structures, and the overall game state...\n\nLaying out the tetromino rotation matrices... Defining the rotation states for the J and L pieces...\n\nNow I'm deciding between using pre-defined rotation matrices for accuracy or implementing a rotation algorithm with wall kick logic. Pre-defined states seem clearer, especially for the I piece which has unique rotation behavior. Let me set up the constants and piece definitions with their rotation states, colors, and board dimensions.\n\nWriting TypeScript constants... Now I'm structuring the HTML with a dark theme, placing the game canvas in the center and adding a side panel to display the next piece, score, level, and line count.\n\nBuilding the layout... Defining the tetromino pieces with their rotation states and colors... I'm looking at the wall kick offsets for different piece types in SRS, but I think for a first pass I'll just implement basic collision detection with a few simple kick attempts rather than the full lookup table. Actually, no—full SRS will make the game feel much more polished, so let me commit to that. I'm planning out the core game loop using `requestAnimationFrame` with a time accumulator for piece drops, then handling piece spawning at the top center with collision checks, and I'll work through the rest of the implementation systematically.\n\nNow I'm thinking through the additional features that really make Tetris enjoyable—hold piece functionality, a ghost piece preview, and lock delay so pieces don't snap down instantly. I'll implement the standard scoring system where clears are worth more points at higher levels, and levels increase every 10 lines cleared with corresponding speed increases. Let me write out all the files now with these features included.\n\nI'm setting up the project structure with TypeScript, organizing types, constants, and game logic into separate modules. The main canvas will be 300x600 pixels for the 10x20 grid, with a separate preview area for the next piece and hold piece display.\n\nSetting up the renderer... Writing type definitions and game state...\n\nNow I'm laying out the standard SRS wall kick data for different tetromino rotations to handle collision detection properly. Defining I-piece wall kick offsets... I need to implement the proper SRS wall kick system with the correct offset values for each rotation state, keeping in mind that I'll need to flip the y-coordinates since canvas uses downward-increasing y while SRS specifies upward as positive. I'm laying out the wall kick data for counter-clockwise rotations, checking each transition against the clockwise pattern to make sure I have the symmetry right. The kicks mirror the clockwise ones but in reverse order, so I need to verify that 1→0 (R→0 counter-clockwise) matches what I'd expect from the opposite direction. I'm looking at the SRS wall kick data from the Tetris wiki for the standard pieces. The CW rotation tests show the offset sequences for each state transition, and I need to also map out the CCW rotation tests to have the complete picture for all rotation directions. I'm cross-referencing the wall kick data against the official Tetris guideline specification to make sure I have the rotation offsets correct for each piece orientation transition. I'm realizing the wall kick data is getting complex, so let me simplify this with a basic but effective approach that covers the most common cases without needing the full SRS specification. Defining rotation kick offsets...\n\nI'm second-guessing the wall kick data for a couple of these rotations. Let me cross-reference against the official Tetris rotation system to make sure I have the right offsets for each piece orientation transition. Looking at the rest of the coordinate data, I'm noticing that R->0 and R->2 produce identical kick values, which suggests they might be redundant transitions that could be consolidated. I'm clarifying how SRS coordinates map to canvas coordinates—the (x, y) offset represents where to test placing the piece, with x being column offset and y being row offset in the upward direction, so I need to negate y when converting to canvas coordinates where y increases downward.","signature":"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-{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01UaAhDLR6B23Ecf54HVu3xa","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me create a complete Tetris game with:\n\n1. All standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z for rotation)\n\nI'll create this as a single HTML file with TypeScript compiled inline, or better yet, I'll create separate TypeScript and HTML files. Let me think about the best approach.\n\nSince this needs to run in a browser, I'll create:\n\n\n- `index.html` - the main HTML file\n- `src/game.ts` - the TypeScript game code\n- `tsconfig.json` - TypeScript configuration\n- `package.json` - project configuration\n\nFor the game itself, I'll implement canvas-based rendering with a 10x20 grid, piece spawning and movement logic, collision detection, line clearing mechanics, and a scoring system that increases difficulty as the player progresses.\n\nI'm setting up the core game mechanics: all seven standard tetrominos with their proper colors, a rotation system, scoring that rewards clearing multiple lines at once, level progression every 10 lines cleared, and increasing speed. I'll also add quality-of-life features like a hold piece system, next piece preview, ghost piece visualization, and pause functionality.\n\nDefining the control scheme and piece data structures... Writing the Tetris game code... Writing the TypeScript game logic... Defining the Piece class to represent individual tetromino blocks with their type, shape, color, and position on the grid...\n\nNow I'm setting up the main TetrisGame class with canvases for the main board, next piece preview, and hold piece display, along with the game state tracking. Setting up the game canvases and initializing the board...\n\nNow I'm thinking through how to get this running in a browser—I could use a build tool like Vite or just compile TypeScript with a simple npm setup, but I need to figure out the best approach for easy browser play.\n\nLet me go with Vite since it handles both development and production builds cleanly. I'll structure this as a proper project with `package.json`, `tsconfig.json`, `index.html`, and the game source in `src/tetris.ts`.\n\nBuilding out the complete game now with all the polish—ghost piece, hold functionality, next piece preview, level progression, and proper Tetris scoring...\n\nWriting the game logic... Defining wall kick data for standard Tetris pieces... Defining wall kick data for the I piece...\n\nActually, I need to double-check the SRS specification here—the coordinate system matters, where positive x moves right and positive y moves up. I'm working through the wall kick test positions for rotation, but the coordinate system conversion between standard Tetris (y-up) and canvas (y-down) is getting confusing. I think I'll simplify this by skipping the full SRS implementation and instead use basic rotation with simpler wall kick logic—just trying a few offset positions along the x-axis and one on the y-axis, which should handle most cases without the complexity.\n\nSetting up the game structure now... Writing the rotation logic...\n\nFor the O piece, I don't need to do anything since it's symmetric. Now I'm planning out the UI with a dark background, semi-transparent game board with grid lines, and colorful pieces with shading effects, plus a side panel showing hold, next, score, level, and lines. The canvas will be 300px wide for the 10-column board and 600px tall for the 20 rows, with about 120px for the side panels.\n\nI'm going to use separate canvases for the main game board and the hold and next piece displays. Now I'm structuring the HTML with a game container that has left and right side panels, where the left panel shows the hold piece and game info like score, level, and lines.\n\nBuilding the HTML structure... Setting up the project configuration with Vite, TypeScript, and the necessary build tools...\n\nDefining the core game constants like board dimensions, cell size, and scoring rules...\n\nWriting the main game logic... Defining the tetromino types and their properties... Defining wall kick offsets for the SRS rotation system, which specifies the exact pixel adjustments needed when rotating each tetromino piece to prevent clipping through walls or other blocks. Defining wall kick data for the I-piece... I'm finishing the wall kick data for the remaining rotation transitions, then converting everything to canvas coordinates by negating the y-values since Tetris uses an inverted y-axis compared to standard screen rendering. I'm getting tangled up in the coordinate system conventions. The Tetris wiki uses standard Tetris coordinates where row 0 is at the top and negative row offsets go downward, but I need to figure out how that maps to canvas coordinates where y increases downward. Let me carefully work through what the wiki actually specifies for the wall kick tests and how to apply them correctly to my implementation. Completing the coordinate transformation for the remaining kick rotations in canvas space. Compiling the I-piece rotation offsets for canvas coordinate space...\n\nNow I'm thinking I should just implement a simpler rotation system with basic wall kick offsets instead of the full SRS spec—checking left and right by 1-2 positions should handle most cases fine.\n\nActually, let me commit to implementing the full Tetris Guideline rotation system properly since that's what modern games use and it'll make the gameplay feel much better.\n\nI'm going to write out the complete game now across multiple files: package.json, tsconfig.json, index.html, and the main tetris.ts file.\n\nWriting the TypeScript game code... Defining the tetromino types and setting up color mappings for each piece, along with the shape data that defines how each tetromino rotates.\n\nStill writing game constants... Defining wall kick offset tables... Defining the Piece class with properties for type, matrix, color, and position, then setting up the constructor to initialize a tetromino with its spawn position centered horizontally near the top of the board.\n\nNow I'm implementing a clone method to duplicate a piece with all its current state, and starting a RandomBag class that shuffles through all tetromino types to ensure fair piece distribution.\n\nBuilding the game class... Setting up input handling for piece movement with DAS and ARR timers to control the repeat rate of left and right shifts, then initializing the line clear animation system and score display, and finally getting references to the game and next piece canvases in the constructor. Setting up the game controls...\n\nI'm handling keyboard input for different game states—when the menu or game over screen is active, space or enter starts a new game, while P or escape toggles pause. During active gameplay, I'm tracking arrow key presses to move the piece left or right, initializing the delayed auto-shift and auto-repeat timers for smooth piece movement.\n\nNow I'm mapping the remaining controls: down arrow for soft drop, up arrow or X for clockwise rotation, Z or control for counter-clockwise rotation, space for hard drop, and C or shift for holding a piece. I'm also handling the key release events to stop movement and manage the directional state when switching between left and right inputs.\n\nInitializing the game state... Writing game logic... Still writing piece rotation logic... Implementing the lock delay mechanics and drop functions... Writing the piece locking logic... Still writing game logic... Writing game loop logic... Writing the rendering pipeline... Writing the board rendering... Writing the rendering logic... Writing the preview box rendering... Still writing rendering code... Writing overlay rendering...\n\nNow I'm thinking through the DAS timer logic—it should reset whenever a new direction gets pressed, but I need to make sure I'm handling that correctly in the current implementation.\n\nActually, I'm spotting a potential issue with how I'm accumulating time across both the DAS timer and the ARR timer. The ARR timer should only start counting after the initial DAS delay passes, and it needs to reset properly each time it triggers a move. Let me refactor the update logic...\n\nFixing the timer accumulation... Refining the DAS/ARR timing logic...\n\nI'm tracking when DAS first activates by comparing the previous and current dasTimer values, then immediately setting arrTimer to trigger the first repeat movement right away. Once DAS is active, arrTimer accumulates each frame and fires movements at the ARR_RATE interval, subtracting the rate instead of resetting to maintain consistent timing.\n\nActually, I can simplify this further—just use modular arithmetic after the DAS delay kicks in to determine when ARR should trigger, avoiding the need to track state changes. The cleaner approach is to let arrTimer start at zero and rely on the DAS_DELAY guard to prevent early triggering, then use the modulo operator to keep ARR firing at regular intervals without manual resets.\n\nWait, I'm seeing the real issue now—arrTimer keeps accumulating during the DAS_DELAY period, so when DAS finally activates, it could have built up enough to fire multiple moves immediately. With typical values like DAS_DELAY = 170ms and ARR_RATE = 50ms, that's potentially 3 extra moves right away, which breaks the feel. I need to reset arrTimer to zero the moment DAS actually triggers, and also make sure to fire an immediate move when the key is first pressed.\n\nRefactoring the key handler...\n\nImplementing the DAS update logic... I've got the lock delay mechanics working correctly with the standard Tetris timing and reset logic. Now I'm thinking through the visual layout—I want a clean design with the game canvas at 300x600 pixels (30 pixels per cell), flanked by side panels for the hold piece on the left and next queue plus controls on the right, with the title at the top.\n\nThe hold and next preview canvases will be 120x90 pixels to fit a 4x3 grid at the same cell size. I'll use HTML elements for the score, level, and lines display, styled with CSS, and add a dark gradient background for a polished look.\n\nBefore I start writing the full code, I'm mentally checking for potential issues—making sure `lastTime` initializes correctly on the first frame, the drop timer resets when a piece locks, and the game over detection works when a new piece spawns overlapping existing blocks. The `isValid` function already handles pieces starting above the visible area, so that should be fine.\n\nWriting the complete implementation now... Checking the spawn positions for different piece types — the I piece starts at y=-1 so its filled row appears at the top of the visible board, while other pieces like the T spawn at y=0. I need to figure out the correct spawn position for Tetris pieces. The I piece has an empty row at the top of its 4x4 matrix, so if I spawn it at y = -1, its actual cells (in matrix row 1) would appear at board row 0. For other pieces spawning at y = 0, their cells would also start at board row 0, which matches standard Tetris behavior where pieces appear one row below the top with some cells potentially visible at the very top.\n\nThe game over condition triggers when a new piece spawns and immediately overlaps with existing board cells. I also need to handle the `gameLoop` timing properly by initializing `lastTime` when the game starts rather than leaving it at 0, though the first frame should be fine since no dropping happens until after `startGame()` is called.\n\nWriting the implementation... Since the menu state doesn't run game logic anyway, and I reset `lastTime` when the game actually starts, the initial large delta on the first frame won't cause issues. I'm ready to write the complete implementation now, starting with the visual design for the game.\n\nWriting the HTML and CSS...\n\nNow I'm setting up the TypeScript structure with proper type safety—making sure to use optional chaining and null checks where needed, and being careful with type assertions. I need to verify my wall kick data for the rotation system, particularly the coordinate conversions for the JLSTZ pieces.\n\nMapping wall kick offsets to canvas space... I'm checking the official Tetris wiki to verify the wall kick offsets for these piece rotations, since my initial calculations might not match the standard implementation. I'm looking at the wall kick offset data for different piece rotations in Tetris, and I need to clarify the coordinate system—specifically whether positive row values mean moving up or down visually. The wiki indicates row 0 is at the top of the playfield, which would mean row numbers decrease as you move upward, so positive row offsets in the kick data should represent upward movement. I'm going to stop overthinking the coordinate system and just use a standard SRS implementation as reference—the exact offsets matter less than having a consistent, playable rotation system. I'll apply the wiki's kick data with the assumption that positive values mean right and down, and if the kicks aren't perfect, the game will still work fine. Now I'm converting the Tetris wiki kick data to canvas coordinates by negating the row offsets, since positive y points down in canvas but up in the game. I'm mapping out the specific kick offsets for JLSTZ pieces across all rotation states.\n\nContinuing with the I piece kick data... I'm working through the rotation state transitions and their canvas coordinate mappings for what looks like a Tetris piece system. I've got the transformations documented and I'm verifying they're correct before committing to using these values, though I'm having second thoughts about whether I've got them right.\n\nActually, I'm going to simplify this—I'll implement a basic wall kick system that tries offsets in order of likelihood rather than getting bogged down in the full SRS specification. For a browser game, handling the common cases with left/right/up kicks is plenty, and if there are edge cases they won't break the experience. I've got the coordinate mappings I need, so let me just code this up and test it rather than overthinking it further.\n\nSetting up the game constants and mechanics... Defining the tetromino shapes and colors... Defining kick rotation data... Writing Tetris game logic... Setting up game state variables... Setting up the hold canvas context, initializing the game board, and wiring up keyboard input handling with event listeners to track which keys are currently pressed. Writing game input handlers... Still writing DAS logic... Writing game logic... Implementing wall kick logic for rotations...\n\nNow I'm handling the soft drop mechanic where the piece moves down one row and awards points, then the hard drop which instantly places the piece at the bottom and scores based on distance traveled. For the hold function, I'm swapping the current piece with a held piece if one exists, or storing the current piece and spawning the next one if the hold slot is empty.\n\nContinuing with the lock function...\n\nNow I'm checking for completed rows across the board and collecting them, then either triggering a clear animation if any rows are full or spawning the next piece. After that, I'm clearing the matched rows by removing them and adding new empty rows at the top, then updating the score based on how many lines were cleared.\n\nWriting game loop logic... Writing the render pipeline... Writing the ghost piece rendering... Writing the rendering pipeline... Writing cell rendering logic... Still writing the rendering logic... Writing the menu overlay... Writing game over screen...\n\nNow I'm putting together the full HTML structure with the game canvas, hold box, next piece preview, and info panel laid out side by side, then I'll add the styling and configuration files to complete the package.\n\nI'm noticing an issue with how I'm rendering the mini pieces—I need to make sure the hold canvas doesn't get cleared twice when I call `renderMiniPiece`, so I'm refactoring `drawSidePanels` to handle the context clearing properly and apply the faded effect when the hold piece has already been used.\n\nFor the directional input handling, I realize my current DAS logic should already switch directions when a new key is pressed, but I need to be more careful about what happens when one key is released while the other is still held—I should track both left and right key states separately so I can resume the previous direction if needed.\n\nTracking key states... I'm realizing the repeat handling is actually working correctly—checking if the key is already in the set is equivalent to checking `e.repeat`, since a key only enters the set on first press. The sequence is that I add to the set and then call the movement logic, so the timing works out properly.\n\nNow I need to prevent default behavior on arrow keys and space to stop the page from scrolling...\n\nSetting up the project structure with HTML, TypeScript, and configuration files, then styling it with a dark retro aesthetic using monospace fonts and cool accent colors.\n\nWriting the HTML and CSS... Still writing styles... Still writing styles... Building the right panel layout... I'm refining the `ghostY()` method to calculate how far down the current piece can drop by incrementally checking valid positions, starting from a displacement of zero and increasing until it hits an obstacle.\n\nNow I'm implementing the `drawGhost()` function to render the ghost piece at its calculated position with reduced opacity, checking each cell in the piece's matrix and drawing outlines for the visible blocks.\n\nWriting ghost rendering code...\n\nFor the score display, I'm updating it every frame through `textContent` assignment, which is slightly inefficient but totally fine for a Tetris game. The high score updates automatically since it's checked in the same `updateScoreboard()` method that runs each frame. I'm also making sure the `valid()` function can accept an optional matrix parameter to test different piece configurations.\n\nChecking the rotation logic... Verifying the rotation logic for the I piece—when I apply the clockwise rotation function to a 4x4 matrix, the new element at position [c][r] comes from the old matrix at [R-1-r][c], which should correctly transform the horizontal line into a vertical one. Verifying the rotation formula by working through each cell of the I piece after a clockwise rotation, mapping the old positions to new positions to confirm the transformation is correct. The I piece rotation looks correct—it forms a vertical line in the right position after a clockwise rotation, which matches standard Tetris behavior. The spawn position and kick data should handle the placement properly.\n\nI'm confident the rotation logic is working as intended. Now I need to write everything to disk and make sure the high score display updates correctly—since `updateScoreboard()` runs every frame in the render loop, it'll always show the current high score. I should also ensure the game properly captures keyboard input by making sure the canvas has focus when needed.\n\nFor the keyboard handler, I'm being selective about which keys trigger `preventDefault()` to avoid blocking browser shortcuts—only arrow keys and space will be prevented from their default behavior, which keeps the implementation clean and user-friendly.\n\nSince I'm listening on `window`, the canvas doesn't need to be focused, but I should prevent page scrolling by adding `overflow: hidden` to the html and body elements. The game container is roughly 700px tall, which fits on most desktop screens, though mobile users would need keyboard support anyway.\n\nNow I'm ready to write out the complete implementation with the package configuration and all the necessary files. I need to think through how soft drop should work in Tetris—when the down arrow is held, the piece should fall faster rather than just moving once on the initial press. I'm considering whether to let ArrowDown repeat naturally or use a separate flag to track the soft drop state and adjust the fall speed accordingly, which is the more standard approach.\n\nSetting up a `softDropping` flag that toggles on key down and key up, then using that to reduce the gravity interval to something like 50ms for a much faster drop rate. I also need to handle scoring—awarding points when the piece actually drops during soft drop, which means I need to distinguish between gravity-driven drops and soft drop movement. Still writing gravity logic... I'm refining the keydown handler to let ArrowDown repeat events through without blocking them, since setting `softDropping = true` multiple times is harmless—the flag just stays true. A cleaner approach would be to exclude ArrowDown from the repeat-prevention logic entirely. Setting up the keyup handler to toggle `softDropping` off when ArrowDown is released, and the gravity will handle the actual dropping motion. I'm realizing the `keysDown` set won't track ArrowDown since I'm skipping it in the keydown listener, but that's fine since `Set.delete` won't error on a missing key anyway.\n\nNow I'm ready to write out the actual implementation cleanly.\n\nWriting Tetris game code... Defining the tetromino types and their properties... Defining wall kick data... Defining kick rotation data... I'm defining the Piece interface with rotation states, then creating a factory function that initializes a new piece with its shape, color, and starting position—centering it horizontally and placing I-pieces one row higher. After that, I'm building a Bag class that manages random piece selection using a shuffled pool that refills when empty.\n\nNow I'm setting up the main Tetris game class with canvas contexts for the game board, next piece preview, and hold piece display, along with state tracking for the current piece, next piece, held piece, and score.\n\nSetting up game state management with level and line counters, pulling the best score from local storage, and initializing timers for piece dropping and locking mechanics along with constants for lock delay and soft drop speed. I'm also tracking directional input state for the delayed auto-shift system that handles continuous left and right movement.\n\nNow I'm getting the canvas elements for the game board, next piece preview, and hold piece display, then setting up their 2D contexts. I'm initializing the game board and input handlers, then starting the animation loop.\n\nSetting up input handling... Handling the rest of the arrow key inputs and other controls—right arrow triggers rightward movement and delayed auto-shift, down arrow enables soft drop, up arrow and X rotate clockwise, Z and control keys rotate counter-clockwise, space performs a hard drop, and C or shift keys activate the hold function. Then I'm setting up the key release handler to track when the left arrow is no longer pressed.\n\nStill writing input handler logic... Setting up the game state with a fresh piece bag, initializing the hold mechanic and lock delay counters, then spawning the first piece and transitioning to the playing state.\n\nNow I'm finishing the spawn logic by resetting the hold flag and lock timer, then checking if the new piece can be placed—if not, the game ends. I'm also implementing the game over handler that saves the high score to local storage, and starting to build out the collision detection system that validates piece positions against the board boundaries and existing blocks.\n\nValidating piece placement... Still writing rotation logic... Writing game logic... Writing the game loop... Writing the rendering logic... Writing the ghost piece rendering... Writing the rendering pipeline... Writing the mini preview canvas... Adding highlight and shadow effects... Writing the menu and pause screens... Finishing up the game code with the HTML and CSS setup, but I'm noticing a potential naming conflict with `softDrop` being used as both a property and possibly a method name that I need to verify isn't causing issues.\n\nLet me trace through the `hold()` method to make sure the piece swapping logic works correctly when there's already a held piece versus when the hold slot is empty. Looking at the hold logic more carefully: when there's no held piece, I call `spawn()` which sets `holdUsed = false`, but then I immediately override it to `true` on the next line, so the final state is correct. When there's already a held piece, I swap without calling `spawn()`, so `this.nxt` correctly stays unchanged and `holdUsed` gets set to `true` directly.\n\nI'm also noticing that when swapping a held piece for the current one, I need to make sure the timers reset properly—I'm resetting `lockT`, `lockMoves`, and `grounded` to handle the new piece correctly.\n\nNow I'm checking the game over condition in `spawn()`. The logic looks right: I assign the next piece to current, generate a new next piece, then verify the current piece doesn't overlap with existing blocks. If it does, the game ends. Let me trace through the spawn sequence to make sure everything's in the right order.\n\nI realize that after calling `gameOver()`, the function might continue executing since it just changes state without throwing an error. I should add an early return to prevent any further logic from running once the game is over.\n\nNow I'm ready to write out all the files and double-checking that the rendering methods are drawing to the correct canvas contexts. I'm verifying that `drawPiece` correctly uses the passed canvas context—in this case `this.gx` for the main game board—while `drawMini` handles its own smaller cell size for preview canvases. The `drawGhost` function is hardcoded to draw on the main canvas, which is fine since ghosts only appear there. I also notice the `_ts` parameter in `drawClearAnim` isn't used since I'm referencing `this.clearT` directly instead.\n\nNow I need to write out all four project files and verify the `Bag` class logic for shuffling pieces. I need to verify the SRS kick coordinate system works correctly with canvas coordinates where positive y points downward. Let me trace through a concrete example with an S-piece rotation to make sure my clockwise rotation logic produces the expected state transitions. I'm verifying the rotation logic by comparing my 3x3 matrix output against the expected 2x2 S-piece rotation—the shapes match, just with different bounding box sizes, which is standard in Tetris since pieces use 3x3 or 4x4 boxes depending on their type. Looking at the rotation logic more carefully, since all Tetris pieces use square bounding boxes—I is 4x4, the others are 3x3, and O is 2x2—my implementation should handle them correctly without size changes. Let me trace through what the S piece should look like after a clockwise rotation to verify the shape is right. Both representations are valid zigzag rotations of the S piece—mine is just shifted one column to the right compared to the reference. The real question is whether my rotation output aligns with what the SRS kick system expects, so I need to check how the standard Tetris rotation matrices are actually defined.\n\nLooking at actual implementations, I see the S piece has four distinct rotation states, each with specific cell positions within a 3x3 bounding box. Let me map out what those states should be according to the Tetris wiki to make sure my rotation logic produces the right positions.\n\nComparing my rotation output to the standard, the shape is correct but positioned differently in the bounding box—mine ends up on the right side while the standard places it on the left. This mismatch means my SRS wall kicks won't work properly since they're calibrated for the standard positions.\n\nThe cleanest solution is to precompute all four rotation states for each piece type rather than calculating them dynamically.\n\nDefining the shape matrices... Defining all the piece rotations explicitly...\n\nI need to work through the T piece rotations more carefully. Starting from the spawn state and rotating clockwise, I should get the correct orientations for each of the four rotation states. I'm working through the rotation formula for the T piece—applying the standard clockwise transformation where each position maps to a new location based on the matrix dimensions. I see the issue now—my rotation is producing the correct T-piece shape, but it's positioned differently within the bounding box than the standard Tetris orientation. The standard has the piece aligned to the left, while mine is centered. I need to adjust how I'm handling the rotation to match the expected cell positions.\n\nLooking at the standard Tetris rotation system, pieces rotate around a pivot point at the center of their bounding box. For a 3x3 grid, that's position (1,1), and the transformation for clockwise rotation is mapping each cell (r, c) to (c, 2-r). Let me verify this works correctly with the T-piece coordinates. Let me verify these rotation mappings are correct by checking each cell position after the clockwise rotation, making sure the T-shaped piece ends up in the right configuration.\n\nNow I'm looking at the actual Tetris wiki specifications for the T piece, particularly the wall kick data that defines how pieces should move during state transitions.\n\nI realize that if my rotation consistently shifts pieces by one column compared to the standard, the wall kick sequences won't align properly—some kicks that should fail might succeed and vice versa. While the game would still be playable, it wouldn't match official Tetris behavior exactly.\n\nRather than relying on kicks to compensate, I should just precompute the exact orientations for each piece and rotation state.\n\nDefining piece orientations... I'm defining the rotation states for the T-piece in Tetris, and I need to verify I have them right. Let me trace through the spawn state and its first rotation to make sure the coordinates match the visual representation. I'm verifying the rotation logic by working through the transformation formula—applying the clockwise rotation to convert the initial T-piece state and checking that each successive rotation produces the expected configuration. I need to work through the coordinate system more carefully. In a standard mathematical rotation where (x, y) → (y, -x) for clockwise rotation, I should map the grid coordinates properly. Let me trace through a concrete example with the T piece to figure out the correct transformation formula instead of getting lost in the algebra. I'm tracing through the rotation logic to verify the transformation—mapping each position in the new matrix back to the old one to see what values end up where. I see the issue now—my rotation is placing the T piece on the right side of the 3×3 box while the standard Tetris positions have it on the left. Let me try the proper CW rotation formula where `new[c][R-1-r] = old[r][c]` to see if that gives me the correct alignment.\n\nTesting this formula on the T piece, I'm mapping each cell from the original 3×3 grid to its new position, but I'm getting the same result—the T is still appearing on the right side instead of the left where it should be. Both formulas give the same result for 3x3 matrices. Let me explore different rotation definitions since various textbooks handle clockwise and counterclockwise differently. I'm testing a CCW approach by transposing then reversing rows, but the output doesn't match what I'd expect. Now I'm trying the opposite—reversing rows first then transposing—to see if that gives the correct clockwise rotation. I'm testing another rotation formula—reversing each row first, then transposing—and getting the same intermediate results, which suggests I might be going in circles with these transformations.\n\nThe T piece seems to have a symmetry that makes different rotation approaches yield identical outputs, so I'm switching to the J piece to test my rotation logic with a non-symmetric shape and verify what the clockwise result should actually be. Finishing the rotation check, I see my result is a mirror image of the standard J orientation—my function is rotating counterclockwise instead of clockwise. I need to fix the rotation formula to get the correct behavior. I'm working through the transpose operation step by step, converting each element from the reversed matrix to its new position where row and column indices swap. I'm testing different rotation approaches for the J tetromino. The transpose method isn't giving me a clockwise rotation—I'm getting the same result as before. Let me try flipping vertically first, then transposing to see if that produces the correct clockwise orientation. I'm tracking the position mappings between the input and output matrices to find the transformation pattern. Looking at where each 1 moves: (0,0) stays put, (1,0) goes to (0,1), (1,1) stays at (1,1), and (1,2) moves to (2,1). I need to figure out the general formula for how old row and column indices map to new positions. I'm testing different rotation formulas to see which one maps the old filled cells to the new ones. The transformation (r,c)→(c, R-1-r) maps (1,0) to (0,1) and (1,1) to (1,1), which both appear in the new matrix, so this might be the right rotation.\n\nLet me verify by applying the standard clockwise rotation formula new[c][R-1-r] = old[r][c] across all positions to build out the complete rotated matrix. I'm testing different rotation formulas to figure out which one correctly maps the old matrix positions to the new rotated positions. The clockwise formula gives me the wrong result, so I'm checking the counter-clockwise approach, but that's also not producing the expected value at position [0][0].\n\nLet me systematically work through all possible row and column permutations to find the right mapping. I need to verify what the J piece actually looks like after a 90° clockwise rotation—visually, the piece in state 0 has the corner block in the top-left with three blocks extending right and down, so rotating it clockwise should move that corner block and reshape the piece accordingly. answer for the J piece rotated clockwise. Let me verify this is correct by checking the transformation: the original top row becomes the right column, the middle row stays as the middle column, and the bottom row becomes the left column, giving me [0,1,1],[0,1,0],[0,1,0].\n\nNow I'm double-checking against the actual Tetris wiki standard for the J piece in its rotated state. I need to verify my rotation logic is correct by working through the coordinate transformation for a 90° clockwise rotation, where each position (row, col) maps to a new location in the grid. I'm verifying the rotated J piece matches my implementation—the cells at (0,2), (0,1), (1,1), and (2,1) form the pattern `.##`, `.#.`, `.#.`, which confirms my `rotateCW` function is working correctly. I realize different Tetris versions define piece orientations differently, so I'll accept my current rotation logic as valid.\n\nRather than trying to match the guideline's exact positioning, I should precompute all four orientations for each piece type to ensure consistency with standard Tetris behavior and make the kick data easier to verify.\n\nLooking at the standard definitions, the I-piece cycles through horizontal and vertical states, while the T-piece rotates through four distinct orientations within its 3x3 bounding box. Let me verify these against actual Tetris implementations to make sure I'm getting the rotations right.\n\nChecking my rotation logic...","signature":"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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01H3hjYiqW5qBbEXdsQTCzby","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser, built with TypeScript. Let me create a complete Tetris game with:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z/X for rotation)\n\nI'll create:\n- `index.html` - The HTML structure\n\n\n- `style.css` - Styling for the game\n- `tetris.ts` - The TypeScript game logic\n- `package.json` - For TypeScript compilation\n- `tsconfig.json` - TypeScript configuration\n\nFor the setup, I think the simplest approach is to create a self-contained solution where I compile the TypeScript and serve it directly, or use an HTML file with inline TypeScript that gets compiled to JavaScript.\n\nLet me go with a clean structure: I'll set up an `index.html` file, write the game logic in `game.ts`, configure TypeScript with `tsconfig.json`, and add a build script to `package.json` that compiles everything to `game.js`.\n\nFor the actual game, I'm planning to implement the core Tetris mechanics: a 10x20 grid with all seven tetrominoes in their standard colors, collision detection with wall kicks, lock delay, and a ghost piece preview. I'll add features like next piece preview, hold functionality, and a scoring system that rewards singles through tetrises with increasing points. The game will speed up as levels increase, and I'll track lines cleared and display the current level. I'm also including pause functionality and proper game over detection, with controls using arrow keys for movement and rotation.\n\nWriting the TypeScript game code... Setting up the game board and piece definitions... Finishing up the tetromino definitions with the Z piece, then moving on to build out the full game structure. I'm planning the file organization with separate TypeScript source, HTML entry point, and configuration files, then I'll write the complete implementation with proper compilation setup.\n\nWriting the game code... Defining the tetromino shapes... Defining wall kick offsets... Finishing the wall kick offset tables...\n\nI'm defining the core game piece class with its type, rotation matrix, and spawn position, handling the special case where the I-piece starts higher up on the board. The clone method is being set up to create independent copies of pieces for game state management.\n\nNow I'm building out the Board class to manage the game grid and validation logic, checking whether a piece can occupy a given position by testing each block against the board boundaries and existing pieces. Writing rotation logic...\n\nNow I'm setting up the main game class with properties for tracking the current piece, next pieces in the queue, and the held piece for swapping. I'm also initializing game state variables like score, level, and lines cleared, along with timing properties for the drop and lock mechanics that control how pieces fall and lock into place.\n\nContinuing with the constructor and helper methods...\n\nWhen spawning a new piece, I'm checking if the bag needs refilling, then pulling the next piece type and creating a new Piece instance. I also need to validate that the spawned piece doesn't immediately collide with existing blocks—if it does, the game is over. The hold mechanic resets so the player can use it again.\n\nFor the start method, I'm resetting all game state including the board, clearing the next pieces queue, and initializing score, level, and line counters back to their defaults.\n\nSetting up the game loop now... Writing movement and drop logic... Still writing rotation logic... Writing game logic... Writing the Renderer class... Writing the block rendering... Finishing the grid rendering and then drawing the active board cells, checking each position to see if it's occupied. For the ghost piece preview, I'm calculating where the current piece would land and rendering it with a semi-transparent appearance to show the player where it'll drop. Writing the preview 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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_013PUpY1D2wgsWV8uuMgt4M5","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me plan the implementation:\n\n1. **HTML file** - The main entry point with canvas element and UI elements\n2. **TypeScript file** - Game logic with all Tetris mechanics\n\nKey features to implement:\n- All 7 tetromino pieces (I, O, T, S, Z, J, L)\n- Piece rotation with wall kicks\n- Line clearing\n- Scoring system (standard Tetris scoring)\n- Increasing speed as levels progress\n- Keyboard controls (Arrow keys + rotation)\n- Next piece preview\n\n\n- Game over detection\n\nI'll keep this simple with a single TypeScript file compiled to JavaScript, using an HTML file with a canvas element and a basic setup that doesn't require a bundler.\n\nFor the game mechanics, I'm planning seven tetromino pieces with distinct colors, and I'll handle player input through keyboard controls—arrow keys for movement and rotation, space for hard drop, and a few other keys for additional actions like holding pieces or pausing.\n\nNow I'm laying out the scoring system where clearing multiple lines gives exponentially higher points multiplied by the current level, and the difficulty ramps up every ten lines cleared. The playfield will be a standard 10-by-20 grid with blocks sized at 30 pixels each.\n\nWriting the TypeScript implementation... Defining the Tetris piece configurations... Finishing up the piece definitions with the L-shaped tetromino, then I'm moving on to build out the complete game structure. I need to handle canvas rendering, game state management, collision detection, line clearing, and tie it all together with a game loop using requestAnimationFrame. I'm setting up the complete Tetris game with a canvas-based board, a sidebar displaying score and next piece preview, and implementing ghost piece visualization along with smooth keyboard controls using delayed auto shift for better gameplay feel. I'm settling on a straightforward structure with separate HTML, TypeScript, and config files that I'll compile with tsc. I'll build out the complete game code now, starting with the HTML markup for the board canvas and sidebar UI, then move into the TypeScript implementation with basic wall kick logic for piece rotation.\n\nDefining game constants... Defining the rotation states for the remaining Tetris pieces... I'm verifying each tetromino's rotation states carefully—working through the S, Z, J, and L pieces to make sure I have all four rotations mapped out correctly for the game logic.\n\nNow I'm thinking about the game loop structure and how to handle piece dropping. I'll use `requestAnimationFrame` to keep things smooth, then implement a drop interval system based on standard Tetris timing where level 1 starts with a specific drop speed in milliseconds. I'm settling on a simpler speed formula using `Math.max(50, 800 - (level - 1) * 70)` milliseconds, then I'll write out the full TypeScript implementation with proper types and a game class to manage the board state, active pieces, and game logic.\n\nWriting the complete implementation... Defining the tetromino shapes and their rotations... Defining the rotation states for the remaining Tetris pieces... Defining wall kick data...\n\nActually, I should verify these offsets match the standard SRS specifications for the I-piece rotations. Defining wall kick data for I-pieces... I need to clarify how the SRS wall kick offsets work in screen coordinates where Y increases downward. When I apply a test offset (dx, dy) from the data, I'm adding dx to the X position and subtracting dy from the Y position to account for the coordinate system flip. Let me establish the standard SRS data but remember that the Y values need to be negated when working in screen coordinates.\n\nNow I'm mapping out the wall kick sequences for the J, L, S, T, Z pieces across all rotation states, checking each offset pair as the piece attempts to rotate and shift position.\n\nActually, I'm going to simplify this—I don't need the full SRS specification. A basic wall kick system that tries a few simple offsets in sequence should be sufficient for the game to feel responsive and work correctly. Completing the SRS rotation data table... Defining rotation kick offsets for the I piece... I'm looking at the wall kick offset data for different piece rotations, and I need to clarify how the piece position is defined in screen coordinates. The piece's x and y represent the left and top edges of its bounding box respectively, with positive x pointing right and positive y pointing down. So the wall kick offsets are horizontal and vertical adjustments in those same screen coordinates. Let me recalculate the converted offsets for the JLSTZ pieces to make sure I have the right transformations. RS Y-up data for JLSTZ `0->R`:\n`[ (0,0), (-1,0), (-1,1), (0,-2), (-1,-2) ]`\n\nThese are `(x_offset, y_offset)` where positive y is UP.\n\nConverting to Y-down (flip y sign):\n`[ (0,0), (-1,0), (-1,-1), (0,2), (-1,2) ]`\n\nSo for `0->1` in screen coords (Y-down):\n`[ (0,0), (-1,0), (-1,-1), (0,2), (-1,2) ]`\n\nThat means:\n- Test 1: No offset (0,0)\n- Test 2: Move piece 1 left (-1,0)\n- Test 3: Move piece 1 left and 1 up (-1,-1) [up = negative Y in screen]\n- Test 4: Move piece 2 down (0,2)\n- Test 5: Move piece 1 left and 2 down (-1,2)\n\nThis matches what I expect for wall kicks. Now I should just implement the game instead of getting stuck on wall kick details. But first, let me double-check my S rotation in screen coordinates to make sure I have the shape right. Defining the S piece rotations...\n\nNow I'm verifying rotation 2 and 3 look correct—the 180° and 270° orientations match what I'd expect. The O piece having identical rotations is fine since it's a square. For spawning, I need to figure out the standard Tetris spawn position, which is typically at the top-center of the board.\n\nI'm calculating the spawn X coordinate using the formula `Math.floor(COLS / 2) - Math.floor(shapeWidth / 2)`. For a 10-column board, this gives me x = 3 for 4-wide pieces, x = 3 for 3-wide pieces, and x = 4 for 2-wide pieces—which centers each piece type correctly.\n\nFor the Y spawn position, I'll just start all pieces at y = 0 at the top of the board. I'm settling on spawning pieces at y=0 at the top of the visible area for simplicity. When a piece locks (can't move down anymore), I'll add a 500ms delay before it actually locks to give the game better feel. If a piece can't be placed at spawn, that triggers game over. Now let me start writing the code.\n\nSetting up the game constants...\n\nNow I'm defining the wall kick offsets for different piece rotations using the Super Rotation System, mapping each rotation transition to a series of kick coordinates that let pieces slide into valid positions when they'd otherwise collide. I need to double-check my wall kick offset data against the standard Tetris rotation system, converting from the typical Y-up coordinates to Y-down screen coordinates. Let me verify the test offsets for the 0→1 rotation state are correct with the sign flips applied. I'm realizing the wiki organizes the kick tests by source state rather than transition direction—so from state R, both the R→0 and R→2 transitions use the same test offsets since they're in the same column of the reference table.\n\nNow I'm converting these test coordinates from the wiki's Y-up convention to Y-down by negating the Y values, working through each transition systematically. Continuing to verify the L→0 and 0→L rotation offsets by converting from Y-up to Y-down coordinates, making sure the final offset arrays match the expected format. Defining rotation kick offsets for the I piece... Now I'm adding the remaining rotation offsets for the 3→0 and 0→3 transitions, then compiling all the kick data into a lookup table with the origin point included as the first test position for each rotation pair.\n\nI'm confident in the wall kick system, so now I'm planning out the scoring mechanics—singles through tetrises with multipliers based on level, plus bonuses for soft and hard drops—and defining how levels progress based on cleared lines with a cap around level 15, along with the drop speed formula. I'm working through the actual Tetris Guideline formula, which uses an exponential decay calculation to determine drop speeds for each level, starting at 1000ms and decreasing significantly in the early levels before leveling off around 30ms by level 13.\n\nSetting up the TypeScript implementation... Defining the piece shapes... Defining the remaining tetromino pieces... Defining wall kick data... Setting up the game state variables now, including the board, current and next pieces, scoring system, and input handling mechanics like DAS (delayed auto shift) for smooth piece movement and lock delay for placement timing.\n\nNow I'm initializing the canvas elements for the main board display, the next piece preview, and the hold piece display, then sizing them according to the grid dimensions.\n\nSetting up utility functions... Writing game logic... Writing game logic... Writing game mechanics... Setting up input handling... Finishing up the hard drop, then handling the hold piece mechanic with C or Shift keys. I'm also setting up the keyup listeners to track when arrow keys are released and reset the DAS state accordingly, plus I'm starting to define the movePiece function.\n\nNow I'm implementing the core movement logic—checking if a piece can move horizontally, updating its position, and managing the lock delay system so pieces don't lock immediately when they land. I'm also writing the rotatePiece function with similar lock delay handling, then moving into the main game loop.\n\nSetting up the game loop with delta time tracking and DAS (Delayed Auto Shift) to handle continuous horizontal movement when keys are held down, plus soft drop handling when the down arrow is pressed.\n\nNow I'm checking if the current piece is resting on a surface, and if so, starting a lock delay timer that will lock the piece in place after a certain duration. If it's still falling, I'm applying gravity to move it down at an interval based on the current level.\n\nI see an issue with how soft drop is being handled—calling `softDrop()` every frame while holding down the arrow key adds points too rapidly. I need to track soft drop separately with its own timer that runs at 20× the normal gravity speed, rather than resetting the main drop timer each frame.\n\nThe cleaner approach is to check if ArrowDown is held and use a much faster drop interval (around 50ms) instead of the normal gravity interval. I'm rewriting the game loop to use delta time and apply the appropriate gravity interval based on whether soft drop is active.\n\nRefining the timing logic... Writing the render function... Writing the rendering functions... I'm going to write out the full implementation now. For the layout, I'm thinking about how to arrange the hold piece, game board, and next piece along with the score information—I want the info panel on the right side showing next piece, score, level, and lines rather than below the board.\n\nBuilding the HTML structure... Writing the game implementation... The I piece spawns correctly with its first visible row appearing at board row 1, which works fine for gameplay. For game over detection, I'll check if the piece can't be placed immediately after spawning. Now I'm thinking through the O piece positioning—it's 2×2, so spawning at x=4 centers it properly on the 10-column board.\n\nLooking at the spawn positions for all pieces: the T piece (3-wide) centers at x=3, and the I piece (4-wide) also centers at x=3, which matches the Tetris Guideline. Now I need to handle the drop interval at high levels—at level 15+, the interval gets very small (10ms or less), which could cause issues at 60fps. I'll add a minimum threshold to prevent infinite loops when the drop interval becomes sub-millisecond.\n\nWriting the drop interval function... Finishing the drop interval calculation with a level cap at 20 to prevent the base from becoming negative. Now I'm ready to write out the full implementation, but first let me verify my S-piece rotations are correct—checking that the different rotation states represent the same tetromino shape in different orientations. I'm working through the rotation transformation step by step, mapping each row of the original matrix to the corresponding column in the rotated result to verify the 90° clockwise rotation is correct. I'm verifying the third rotation by applying the same transformation formula to the result from rotation 2, checking each position systematically to ensure the matrix is rotating correctly. Finishing the rotation calculation and confirming it matches the expected result of [[0,1,1],[1,1,0],[0,0,0]]. Now I'm moving on to verify the Z piece rotations, starting with rotation 1 where I apply the same 90° clockwise transformation. I've verified the Z piece rotation is correct, and now I'm checking the T piece by applying the same 90° clockwise rotation formula to see if it produces the expected result. Continuing with rotation 2, I'm finishing the calculation to get `[[0,0,0],[1,1,1],[0,1,0]]`. Now moving into rotation 3, applying the same transformation formula to get the next orientation of the T piece. Continuing to verify the J piece rotations by applying the transformation formula and checking the results against the expected grid layouts. Completing the J rotation 3 calculation and verifying the result matches `[[0,1,0],[0,1,0],[1,1,0]]`. Now moving on to the L piece rotations.\n\nFor L rotation 0, I have the base configuration `[[0,0,1],[1,1,1],[0,0,0]]`. Applying the clockwise rotation transformation where each new position maps from `old[2-j][i]`, I'm computing all nine positions to get the rotated matrix, which gives me `[[0,1,0],[0,1,1],[0,1,1]]`.\n\nNow I'm verifying this matches the expected pattern and moving on to rotation 2 by applying the same transformation to the result from rotation 1. Finishing the L rotation 3 calculation and confirming it matches my expected output. Now I'm moving on to verify the I piece rotations, starting with the 4×4 grid and applying the same clockwise rotation formula. I've verified the rotation matrix for the I piece is correct, and now I'm moving on to implement the final code. I need to make sure soft drops properly update the score and that the DAS (delayed auto shift) timing works as expected—first move on key press, then after a delay it should auto-repeat at regular intervals.\n\nI'm also capping the delta time to 50ms to prevent the piece from jumping multiple cells if the game loop falls behind, and I need to handle pause state by skipping the game loop and showing an overlay, plus add a game over screen with a restart option. I'm still deciding whether to show a preview of multiple upcoming pieces or just the next one.\n\nWriting the complete TypeScript implementation... Defining the piece shapes... Defining the remaining Tetris piece rotations... Defining wall kick offset tables... Setting up the game state variables...\n\nNow I'm initializing the DAS (delayed auto shift) system to track directional input timing, along with a key state tracker for handling player controls. I'm also grabbing all the DOM elements I need—the canvases for rendering the board, next piece preview, and hold piece display, plus the text elements for showing score, level, and lines.\n\nSetting up the canvas dimensions based on the grid size and block dimensions, then defining utility functions to create the game board, retrieve piece shapes with rotation handling, get piece colors, and pull the next piece from the randomization bag.\n\nContinuing with the piece spawning logic...\n\nNow I'm implementing the collision detection system that checks whether a piece can occupy a given position, accounting for rotations and boundary constraints. The function iterates through the piece's shape matrix, validates that each occupied cell stays within the playfield bounds, and ensures no collisions with existing blocks on the board.\n\nImplementing rotation logic with wall kicks...\n\nNow I'm finishing the ghost piece calculation to show where the piece will land, then locking placed pieces into the board grid, and finally handling line clearing logic.\n\nSetting up the game initialization...\n\nNow I'm loading the high score from storage, spawning the next piece, and starting the game loop with proper timing. When a new piece spawns, I check if it's a valid position—if not, the game ends and I save the score if it beats the high score.\n\nThe hold piece function lets me swap the current piece with a held one, resetting timers and spawning the next piece if there's nothing held yet. For moving pieces, I'm validating the horizontal movement...\n\nImplementing game mechanics... Writing game logic... Still writing canvas rendering... Finishing the canvas drawing logic...\n\nNow I'm setting up the render function to draw the game board with a dark background and grid lines, then continuing to draw the falling pieces and other game elements on top. Writing the game rendering logic... Writing the game loop... Writing game loop logic... Writing input handlers... I'm setting up the keyboard event listeners to handle piece movement and rotation, then initializing the game state by creating the board and resetting key variables before the render loop starts. I'm setting up the initial game state with `gameOver = true` so the game loop renders without updating, and the keydown handler will trigger `startGame()` when the player presses Space or Enter. For the display logic, I can use the same `gameOver` flag to show either the welcome message initially or the game over message after play ends, depending on whether `currentPiece` exists.\n\nNow I'm thinking through the visual style for the blocks—I want a 3D effect with highlights and shadows, so I'll add a lighter border on the top-left and a darker border on the bottom-right, with a slightly darker fill in the center to create depth.\n\nWriting the block rendering... I'm going to stop second-guessing the dimensions and just start building—I can tweak the sizing later if needed. I've settled on a block size of 30 pixels, which gives me a 10×20 board at 300×600 pixels, with the preview areas for next and hold pieces at 125×125 pixels using 25-pixel preview blocks. Now I'm writing out the HTML structure with styling for the dark background.\n\nWriting HTML and styles... Still writing styles... Writing the HTML structure... Building the game board and UI panels... I'm realizing I need to be consistent with the canvas sizes—I should set them in JavaScript rather than HTML to keep everything in one place. For the next piece preview, I need to account for different piece widths: the I piece is 4 blocks wide, most others are 3 blocks wide, and the O piece is 2 blocks wide. With a block size of 25 pixels, a 4×4 grid would be 100×100, so I'll use 120×100 for the preview canvases to give some padding around the pieces.\n\nNow I'm thinking through the game logic more carefully. I'll skip the line clear animation for now to keep things simple. There's a subtle issue with piece spawning though—when pieces spawn partially above the board (y < 0), my current code doesn't draw those blocks, which is correct, but I need to make sure the game over detection works properly when a new piece can't be placed. I need to verify the I piece spawn logic more carefully. The shape has 4 rows with the actual blocks on row 1, so when spawning at y=0, those blocks land on board row 1, which is correct. Now I'm ready to implement the code. The collision check only validates cells with actual blocks (the `1` values in the shape), so empty cells in the shape array don't cause issues. When the I piece spawns at y=0, only its actual blocks at board row 1 are checked, which is fine. As the piece drops and y increases, the blocks move down the board until reaching the bottom boundary around y=16, where the piece locks in place. So the piece locks when it reaches y=18, with blocks occupying the final row 19. Any attempt to move to y=19 would place blocks out of bounds, making that position invalid. The empty rows in the shape don't cause issues since they're just padding in the bounding box.\n\nNow I'm realizing the I piece can only reach rows 1-19 since its first visible block is at y+1, meaning it never actually occupies row 0. But that's acceptable for gameplay—other pieces like the T piece have visible blocks in their first row, so they can spawn at y=0 and occupy row 0 immediately. I see the standard Tetris guideline uses a buffer zone, so pieces should spawn with their topmost visible blocks at row 0. I'm adjusting the spawn logic to calculate the first visible row of each piece's shape and offset the Y position accordingly.\n\nWriting spawn logic... Writing the spawn function...\n\nThe approach works because empty rows above the board aren't collision-checked, so I can spawn pieces with negative y-coordinates to hide the empty rows in their shapes. Now I need to make sure the rendering handles this correctly when drawing the active piece on screen. I'm verifying the I piece renders correctly at spawn—the shape's filled row appears at board row 0 since the empty rows get skipped by my render check. Now I need to think through the game over detection logic.\n\nWhen a new piece spawns at y=-1, it's invalid if any cells at board row 0 are already occupied, which correctly triggers game over. I'm also considering the \"block out\" rule where pieces locked above the visible area end the game, but in this implementation pieces can only lock when they hit the surface, so blocks should always be at row 0 or below. Checks if the spawn position is valid by testing whether the top rows are clear, triggering game over if the stack has reached the spawn point. Now I'm ready to start implementing—I'll begin with the rendering functions to draw individual blocks and the game board.\n\nWriting the block rendering... Still writing grid code...\n\nActually, I think alternating squares would make the board feel too busy, so I'll stick with just the grid lines. Now I need to set up the project structure and write out all the files—I'll create the HTML entry point, the TypeScript game logic, and the config file, then compile everything. One thing I should be careful about: when pieces lock in place, I need to handle blocks that spawn above the board properly, since we only want to place blocks within valid row bounds, though the game over detection should catch most edge cases before that becomes an issue.\n\nI also need to make sure the game loop respects the game over state and stops processing updates once the game ends.\n\nI'm going to skip some of the polish features like line clear animations and level up messages for now to keep things simple, but I can add those later. Now I'm ready to write out the complete implementation, though I should double-check how the I piece rotation works since it has a different rotation center than other pieces.\n\nThe I piece uses a 4×4 bounding box with an off-center rotation point, so I need to make sure my wall kick logic accounts for that. Let me trace through a specific example to verify the rotation and wall kick behavior are working correctly.\n\nStarting with an I piece at position (3, -1) in horizontal orientation, the blocks occupy columns 3-6 at row 0. When I rotate it clockwise to vertical, the shape shifts to column 2 within the bounding box, which places the blocks at column 5 on the board. The top block sits above the board at y=-1, which is valid, and the rest occupy rows 0-2. The validation check would confirm those board positions are empty, so the rotation succeeds without needing wall kicks.\n\nNow testing edge cases: at x=0, the vertical bar lands at column 2, well within bounds, so the first wall kick test passes. But at x=8, the rotation would push the piece to column 10, which exceeds the board width. The wall kick sequence tries offsetting by -2 to move it to column 8, which is valid and within bounds.\n\nAt the right edge (x=9), the first test fails but the -2 offset brings it to column 9, which works. The left edge at x=0 is fine since the piece fits naturally. The I piece can't spawn at x=-1 since it needs columns 0-3 minimum.\n\nLooking at the actual rotation mechanics: in the initial horizontal state, the blocks occupy row 1 of the 4×4 shape at columns 0-3, so with piece.x=3 the board columns are 3-6, and the valid x range is 0-6 to keep blocks within bounds 0-9. When rotating clockwise to vertical at x=6, the bar moves to column 8 of the board, which is valid. Testing x=7 next.\n\nNow I'm verifying the wall kick offsets are correct before implementing. Let me double-check the I piece rotation data from the official Tetris Wiki to make sure I have the Y values right, especially for the 0→1 rotation transition. I'm verifying the wall kick offsets match the Tetris wiki format—the I piece rotation from R→0 follows the same Y-down coordinate system, with test 4 moving right and up, and test 5 moving left and down.\n\nNow I'm double-checking the R→2 rotation state, but I'm noticing some inconsistency in my test values and want to carefully cross-reference against the official wiki table to make sure I have the offsets right. Defining the kick offset data...\n\nI'm second-guessing myself on the coordinate system—need to verify whether the Tetris wiki uses Y-down or Y-up conventions, since I'm seeing conflicting information about the axis orientation. I see the discrepancy now—the Tetris Wiki defines positive row values as moving UP, which is the standard math convention. Since my implementation uses Y-down coordinates where piece.y increases downward, I need to flip the sign: when the wiki says move up (+1), that translates to (-1) in my system. Let me verify this interpretation against the actual SRS specification to make sure I'm converting the offset table correctly. I'm catching an error in my I-piece kick table—I had the signs flipped for the screen coordinate system. Let me recalculate: the wiki values need to be converted properly, where positive Y in the original means moving up (negative dy in screen coords). I'm rebuilding the corrected kick offsets with the right signs. Verifying the rotation kick data against the wiki specifications...\n\nNow I'm compiling the complete kick offset table for all rotation transitions in screen coordinates with Y-down orientation. I'm noticing that R→0 and R→2 produce identical kick test values, which seems odd. Let me double-check the Tetris wiki to make sure I'm reading the rotation kick tables correctly for the J, L, S, T, and Z pieces. Now I'm converting these rotation offsets to screen coordinates where Y increases downward, flipping the signs accordingly for each transition state. Completing the kick data structure... I'm completing the wall kick offset table with the correct Y-down coordinate system, and now I need to verify one of these cases to ensure the data is accurate.\n\nLet me trace through a specific rotation: when an I-piece at position (3, -1) rotates clockwise from rotation 0 to 1, it transforms from a horizontal line into a vertical column. With the default offset of (0, 0), the new blocks would occupy column 5 at rows 0 through 2 on the board, assuming that space is clear. This confirms the piece successfully rotates and settles at the new rotation state.\n\nNow I'm testing an edge case where rotation would push the piece off the right boundary. If I try an I-piece at x=8 with rotation 0, those blocks would already exceed the board width at spawn, so that position fails validation. The maximum valid x-position for a horizontal I-piece is x=6, which places blocks at columns 6 through 9. When rotating from 0 to 1 at that position, the vertical form would occupy column 8.\n\nFor x=7 at y=5, the rotation succeeds since the resulting column 9 stays within bounds. But at x=8, the rotated form would need column 10, which is out of bounds, so the default offset test fails and I need to check the wall-kick offset of (-2,0) to shift the piece left.\n\nAt x=9, the piece is already invalid for rotation 0 since it would span columns 9-12, exceeding the board width—the I-piece can only exist at x positions 0 through 6 in that rotation. The wall-kick logic seems solid, so I'm ready to implement the actual code now, though I should handle one more edge case involving negative y values.\n\nFor the I-piece in rotation 1 at x=3, y=-1, the shape extends from rows -1 to 2 with blocks at column 5. Since isValidPosition ignores y<0 and the render loop only draws visible blocks, the piece appears as a 3-cell column at the board's top and drops normally as it falls. Let me verify the rotation 1 shape...\n\nActually, the I-piece in rotation 1 is a vertical line occupying column 2 of the 4×4 bounding box. At position (3, -1), this places blocks at (5, -1), (5, 0), (5, 1), and (5, 2)—with only the bottom three visible initially. Once it drops to y=0, all four cells align vertically at column 5 from rows 0 to 3.\n\nI've verified the spawn positions for all pieces: the O-piece starts at y=0, the I-piece at y=-1 to account for its empty top row, and the T, S, Z, J, L pieces at y=0. Now I'm ready to implement the code.\n\nBuilding the project structure and styling...\n\nFor the line clear animation, I'll add a flash effect where cleared rows turn white briefly before disappearing, which requires tracking which rows are clearing and managing a timer in the game loop.\n\nImplementing the state management... I'm settling on a simpler approach with a flash timer and state tracking. I'll add a `flashRows` array and `flashTimer` to track when rows are clearing, then during the flash duration the rows will animate visually before the actual clear happens and the next piece spawns. This keeps the state management cleaner with just a few variables instead of a complex timing system. Continuing the game loop logic...\n\nWhen the flash duration expires, I clear the matched rows from the board and shift new empty rows to the top, then calculate the score based on how many lines were cleared and the current level, updating both the score and level accordingly before transitioning back to the playing phase. Writing the game loop refactor... Still writing pause logic...\n\nActually, a simpler approach is to just track a `paused` boolean separately from the phase state, so I can pause at any point without losing where I was. During the game loop, I'll check `!paused` before updating any phase-specific logic. Now I'm laying out the complete file structure with constants, types, piece definitions, wall kick data, and all the game state variables. I'm sketching out the visual layout with the hold box on the left, the main game board in the center, and the next piece preview, score, best score, and level display stacked on the right, along with control instructions at the bottom left.\n\nNow I'm working through the dimensions—the board needs to be 300 pixels wide to accommodate the 10-column grid, with 150-pixel panels on each side and some spacing between them, bringing the total width to around 632 pixels and height to 600 pixels.\n\nFor the implementation, I'm planning to use a monospace font for the numeric values so they don't shift around as the score updates, and I'll position the message overlay absolutely over the board.\n\nWriting the HTML structure... I'm working through the canvas dimensions for the preview boxes—checking that each piece type (I, T, O) centers properly within the 120×90 pixel canvas with a 24-pixel block size, and they all fit comfortably. The J piece dimensions check out with offsetX at 24 and offsetY at 21. Now I'm ready to implement the full code. For the line clear animation, I want to enhance the flash effect by using multiple sine wave pulses instead of a single flash—this will create a more dynamic visual feedback when lines are cleared.\n\nWriting animation logic... Writing the implementation...\n\nNow I'm settling on canvas dimensions: the main board at 300×600, and both the next and hold preview canvases at 120×90 to keep things simple and consistent. I should also think about how this scales across different screen sizes, though for now I'm focusing on making it work well on desktop. Configuring TypeScript settings...\n\nI'm realizing that `outFile` requires a module format like AMD or System, which complicates things for a simple browser game. The cleanest approach is to skip `outFile` entirely and just compile the single TypeScript file directly with `tsc game.ts`, letting it output `game.js` naturally. I'll set up a minimal tsconfig with ES2020 as the target, DOM library support, and strict mode enabled.\n\nWith `files: [\"game.ts\"]` specified and no `outDir` set, the compiler will place `game.js` right alongside the source file, which is exactly what I need for the HTML to reference it. Now I'm ready to start building out the actual game code in a single TypeScript file.\n\nFor the piece colors, I'm going with the classic Tetris palette—cyan for the I-piece, yellow for O, purple for T, green for S, red for Z, and blue and orange for J and L respectively.\n\nWriting the game logic... Defining the piece colors... Writing the Tetris piece code... Writing the complete game implementation... Writing the Tetris game code... Writing the complete Tetris implementation... Defining the Tetris piece configurations... Defining the Tetris piece configurations with their rotation states and colors, then setting up the wall kick offsets for the SRS rotation system... Defining the kick offset data...\n\nNow I'm setting up the game state variables—the board grid, current piece with its rotation and position, next piece preview, hold mechanic, score tracking, level, and lines cleared counter.\n\nInitializing game phase, pause state, and the piece randomization bag, along with timers for piece dropping and locking, surface detection, and row flash animations for line clears.\n\nSetting up input handling with DAS (delayed auto shift) state for smooth horizontal movement and key tracking, then grabbing canvas references for the board display, next piece preview, hold piece display, and score elements.\n\nConfiguring canvas dimensions based on the grid size and preview block dimensions, then starting to define utility functions... Writing game logic... Still writing game logic... Clearing the key states and loading the high score from storage, then spawning the first piece and transitioning into the playing phase. When a new piece spawns, I'm checking if it's valid—if not, the game ends and I save the high score if needed.\n\nNow I'm handling the piece lock logic, checking for complete rows and either flashing them or spawning the next piece.\n\nContinuing with the row clearing function...\n\nI'm implementing the movement and rotation mechanics for the tetromino pieces. The move function checks if a horizontal shift is valid, and if the piece is on a surface, it resets the lock timer and tracks how many times the piece has been repositioned before locking. The rotate function applies the same logic when the player rotates a piece. Now I'm working on the hard drop functionality...\n\nCompleting the hard drop by calculating where the piece would land, awarding points based on the distance, and immediately locking it in place. The hold piece function lets the player swap their current piece with a previously held one, resetting all the movement timers and checking if the new piece can actually be placed—if not, the game ends.\n\nNow I'm setting up the drop speed calculation that gets faster as the level increases, capping out at level 20, then defining the UI update functions to refresh the score, high score, level, and line count displays, plus a helper to show overlay messages like game over screens.\n\nWriting the rendering code... Finishing the ghost drawing function...","signature":"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+ "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 7, + "tool_calls": { + "total": 1, + "bash": 1, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 0, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 25 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.602 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 25 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "unspecified", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1", + "run_number": 1, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:24:20.612599+00:00", + "wall_time_seconds": 782, + "exit_code": 1, + "completed_at": "2026-04-04T09:37:26.539475+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/transcript.jsonl @@ -0,0 +1,7 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "unspecified", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n"}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-eh4etafl","session_id":"d8c245f9-210b-42b3-a308-05ce1dc83420","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"4c922366-e357-4590-a90f-3b6b29f90a3d","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01Rmat9H1AyAoNGoYyAhKM6v","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser. I'll create a complete HTML/CSS/JavaScript implementation with all standard Tetris mechanics:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls\n\nLet me build this as a single HTML file with embedded CSS and JavaScript.\n\nKey features to implement:\n- Canvas-based rendering\n- All 7 tetrominoes with their colors\n\n\n- Rotation with wall kicks to handle edge cases\n- Line clearing with visual feedback\n- Scoring that rewards clearing multiple lines at once\n- Progressive difficulty through increasing speeds\n- Next piece preview and hold piece functionality\n- Game over detection\n- Full keyboard controls including arrow keys for movement, rotation with Z/X or up arrow, space for hard drop, and C for hold\n\nI'm setting up the scoring tiers where single lines are worth 100 points per level, doubles are 300, triples are 500, and a full Tetris is 800, all multiplied by the current level.\n\nBuilding the game engine... Defining the tetromino pieces...\n\nNow I'm thinking about rotation mechanics—I'll use a matrix transformation that transposes and reverses rows to handle clockwise rotation. For wall kicks, I'll add simple collision detection that tries shifting the piece left or right if rotation fails at the current position. The game board will be a standard 10×20 grid.\n\nSetting up the game constants and piece definitions...\n\nNow I'm thinking through the full architecture—I need to handle the canvas setup with a preview area, manage the game state including the board and current pieces, implement movement and rotation with proper collision detection, add a ghost piece preview, handle line clearing with animations, and set up the scoring system.\n\nI'll use a 7-bag randomizer for fair piece distribution and implement basic wall kick logic to make rotation feel natural. Let me write out the complete HTML implementation with styling and game logic...\n\nWriting the HTML structure and styles... Still writing styles... Still writing styles... I'm building out the main game interface with the canvas for gameplay, an overlay with instructions and a start button, and a right panel to display the next upcoming pieces.\n\nSetting up the game constants and piece definitions... I'm realizing I need to step back and architect this properly. Let me organize the core structure with a Game class to manage state, individual Piece objects that track type, position and rotation, and a Board represented as a 2D array. I'll need helper functions for piece creation and rotation, collision detection, line clearing, and rendering both the board and falling pieces to the canvas.\n\nWriting the implementation... Defining the scoring system and game speed mechanics...\n\nNow I'm planning out the complete HTML structure for the full game implementation.\n\nBuilding the complete Tetris game... Setting up the game constants...\n\nI'm defining the speed progression for each level following the classic NES Tetris formula, along with the scoring multiplier for clearing different numbers of lines. Then I'm mapping out the wall kick offsets that let pieces rotate and shift position when they'd otherwise collide with walls or other blocks. I'm mapping out the full feature set for a complete Tetris implementation—a 10x20 board with all seven standard pieces, wall kick rotation mechanics, ghost and hold pieces, a preview of the next three pieces, and a 7-bag randomizer for fair piece distribution. The scoring system will multiply points by level (100/300/500/800 for clearing 1/2/3/4 lines), with levels advancing every 10 lines and speed increasing accordingly. I'll add hard drop with Space, soft drop with the down arrow, lock delay so pieces don't snap instantly, line clear animations, and full UI screens for start, game over, and pause states. For wall kicks, I'm going with a simplified but effective approach rather than overcomplicating it.\n\nNow I'm thinking through the rendering details—each block will be 30x30 pixels on a 300x600 pixel board, with a subtle 3D effect using lighter edges on top and left, darker edges on bottom and right. The ghost piece will be just an outline at low opacity to show where the piece will land.\n\nWriting the implementation... Defining the tetromino shapes... Setting up the game state variables for score, level, lines, and piece management, then initializing the board with empty cells, generating the piece bag, and resetting all game parameters... Setting up the piece bag system with a Fisher-Yates shuffle to randomize tetromino types, then implementing piece creation with proper positioning and rotation logic for clockwise turns.\n\nNow I'm writing the validation and collision detection... Writing movement functions... Implementing the hard drop and soft drop mechanics, where hard drop repeatedly moves the piece down and awards points based on distance, while soft drop gives a single point per manual descent. Then I'm setting up the piece locking system that places the piece blocks onto the board...\n\nStill writing game logic...","signature":"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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01Cdc2qgZk9nZ3yBLS8tVNP8","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser. I'll create a complete HTML/CSS/JavaScript implementation with all standard Tetris mechanics. Let me plan out the features:\n\n1. **Pieces (Tetrominoes)**: All 7 standard pieces (I, O, T, S, Z, J, L)\n2. **Controls**: Arrow keys for movement, Up arrow or Z for rotation\n3. **Mechanics**:\n - Piece rotation (with wall kicks)\n - Line clearing\n - Scoring (based on lines cleared)\n - Increasing speed over time/levels\n4. **Display**:\n - Game board (10x20)\n - Score display\n - Level display\n - Lines cleared\n - Next piece preview\n - Game over screen\n\nI'll build this with a canvas-based approach for smooth rendering, implementing all the standard features like the 7 tetrominoes with proper colors, rotation with wall kicks, a ghost piece preview, hold functionality, Tetris-standard scoring, level progression with increasing speed, line clear animations, and pause controls.\n\nWriting the complete implementation... Writing the game implementation... Defining the piece shapes and colors...\n\nNow I'm implementing the full game with a dark theme and proper styling. I need to set up the standard SRS wall kick system for rotation, which has specific offset tables depending on the piece type and rotation direction. Defining the I-piece rotation kicks... I'm laying out the wall kick offsets for each rotation transition—these define the positions to try when a rotation would normally collide with a wall or obstacle, attempting them in order until one succeeds. I'm finishing up the SRS wall kick data for the I piece rotations, then I need to adjust the coordinate system since my grid has rows increasing downward. Rather than manually implementing all these rotation states, I'll simplify the approach and write out a complete Tetris game in HTML with wall kick logic built in.\n\nWriting the HTML file... Still writing styles... Still writing styles... Building the left sidebar layout... Writing the game engine... Defining the piece shapes...\n\nI'm debating whether to use a matrix representation or offset arrays for the pieces—the matrix approach is more intuitive for handling rotations, so I'll stick with that. Now I need to figure out the scoring system.\n\nStandard Tetris uses multipliers based on how many lines you clear at once, with single lines worth 100 points per level, doubles at 300, triples at 500, and a full Tetris at 800. Soft and hard drops also contribute points. For progression, I'll advance the level every 10 lines cleared, and the gravity speed decreases as the level increases, starting at 800ms per row at level 1 and getting progressively faster.\n\nI'm creating a lookup function that maps each level to its corresponding gravity speed, with a fallback to 17ms for very high levels. Now I need to structure the actual game code with a Board class to track fixed blocks, a Piece class for the active falling piece, and a Game class to manage the overall state and logic.\n\nFor rotation, I'll implement the SRS wall kick system with specific offset tables for different piece types and rotation transitions...\n\nActually, I need to be careful about coordinate conventions here. I'm using x for columns (positive right) and y for rows (positive down), so I need to convert the standard SRS values which use y-positive-up by negating the y offsets.\n\nLet me work through the rotation state transitions for the J, L, S, T, and Z pieces, mapping out all the wall kick offsets for each rotation direction. Adjusting the kick offsets for a canvas coordinate system where y increases downward... Defining the I-piece rotation kicks... I need to double-check my coordinate conversion here—when I negate the y-values from the original SRS system, I should be getting (+1,-1) for that 2→3 rotation, not (+1,+1). Let me verify this more carefully by working through the original 3→2 data and applying the same negation. Compiling the kick offset tables for all rotation transitions... I'm finishing up the kick offset data for the piece rotations, then moving on to actually implementing this in code. I'll structure the full game with constants for the board dimensions and piece definitions, then handle the board management, rotation logic with those kick offsets, input handling, the main game loop, and rendering all in one clean HTML file.\n\nDefining piece colors and shapes... Writing rotation functions...\n\nI'm deciding whether to precompute all rotations for each piece or calculate them on the fly—computing them dynamically is cleaner. Now I need to figure out the spawn position: pieces should start centered horizontally and near the top of the board. For a 10-column board, that means x = Math.floor((10 - pieceWidth) / 2), which gives different values depending on the piece size. For the y position, pieces spawn with their bottom at the visible top row. I'm settling on a simpler approach: the board stays at 20 rows, and pieces can spawn with negative y positions that get clipped during rendering. For the I piece, I'll spawn it at y = -1 so its active row appears at the visible top, and I'll apply the same logic to other pieces based on their matrix structure. For collision detection, I need to validate three things: that the piece stays within the left and right boundaries, doesn't go below the board, and doesn't overlap with existing blocks (checking the board only when the piece is visible). Now I'm ready to write out the complete game—I'll implement a lock delay system where pieces have 500ms after landing to be shifted or rotated before they're permanently placed, which is the standard approach for Tetris.\n\nWriting the complete HTML file... Still writing styles... Still writing styles... Still writing styles... Building the game layout... Setting up the game constants now — defining the grid dimensions, piece types, color palette for each tetromino, and the scoring multipliers for clearing lines.\n\nDefining drop speeds... Building the rotation system... Defining rotation kick data... Setting up the game state variables for the board, current piece, held piece, next queue, and scoring system, along with timers for piece dropping and line clearing animations, then grabbing references to the canvas elements for rendering.\n\nNow I'm setting up the bag randomizer system that uses a 7-bag algorithm to ensure fair piece distribution, and initializing the next queue to show upcoming pieces.\n\nBuilding the board and validation logic... Still writing game logic... Writing piece spawning and rotation logic... Writing game mechanics... Writing input handling... Setting up the keyboard release handler to reset the DAS state when arrow keys are released, then implementing the DAS logic that builds up a delay before rapid-fire movement kicks in, and finally starting to initialize the game board and score. Writing game logic... Writing game loop logic... Still writing rendering code... Still writing the rendering logic... Now I'm drawing the active piece using the same matrix iteration approach, then adding a semi-transparent dark overlay when the game is paused with centered text.\n\nBuilding the preview renderer... Writing the next queue renderer... Writing piece rendering code... Finishing the piece rendering with shading effects...\n\nWait, I found a bug in the rotation kick logic. Let me verify the CCW direction mappings against my SRS tables—checking that \"0>3\", \"1>0\", \"2>1\", and \"3>2\" are all properly defined as reverse kicks from the clockwise rotations. They all check out, so the tables are correctly symmetric.\n\nNow I'm verifying the spawn positions for each piece type. The I piece's visible row appears at y=0 with spawn_y=-1, the T piece's top row is visible at y=0, and the O piece starts with its top row hidden at y=-1. All the spawn positions look correct. I'm checking the Tetris Guideline specification—pieces spawn in the hidden rows above the visible play field, so using spawn_y = -1 for all pieces makes sense. For the O piece specifically, this means the top row stays hidden while the bottom row appears at the top of the visible area, which matches standard Tetris behavior. I'm realizing the simplest approach is to just spawn all pieces at y=0 and clip the rendering to only display rows 0-19, letting any parts above that stay invisible without affecting the game logic. This way the T piece shows its top row at y=0 as expected, and I don't have to worry about different spawn positions for different piece shapes. I think the cleanest approach is to precompute the spawn Y position for each piece type based on where its first occupied row appears in the rotation matrix, so pieces spawn with their topmost blocks at y=0. For the I piece that means spawn_y = -1 since its blocks start at row 1, while the T piece would spawn at y=0 since it has blocks in row 0. I need to reconsider the spawn positions more carefully. In the standard Tetris guideline, pieces spawn in a buffer area above the visible field, with the I piece starting two rows higher than other pieces. For my coordinate system where y=0 is the top of the visible field, I should spawn most pieces at y=-1 so their first visible blocks appear at y=0, but the T piece is tricky since it has blocks in its top row of the matrix. Let me think through exactly which pieces have blocks in their first matrix row and adjust spawn positions accordingly. So with spawn_y = 0, the T piece displays its full shape immediately at the top of the board, and the game over check works correctly—if the top row is filled, the spawn fails. I'll set spawn_y = -1 for the I piece since its active row needs to align differently, and spawn_y = 0 for everything else.\n\nSetting up spawn positions... I'm verifying the spawn positions for each tetromino piece—the I piece needs to start one row above the visible grid at y = -1 so its blocks appear correctly at the top, while all other pieces spawn at y = 0. Now I'm thinking through the spawn x-coordinate positioning. Writing spawn position logic...\n\nNow I'm working through the SRS rotation kick tables—I need to map the correct offsets for clockwise and counterclockwise rotations based on the current rotation state.\n\nI've got all 8 rotation transitions covered with their corresponding kick table keys. Now I'm thinking through the lock delay mechanics, which should give pieces about 500ms before they lock, with the move counter resetting on each placement action.\n\nThe tricky part is handling when a piece rotates off the ground—I need to make sure `isOnGround` flips back to false if the rotation creates space underneath, so the lock timer doesn't trigger prematurely. My current approach checks if the piece can fall, and if not, I start the lock sequence with a timer that increments each frame and resets on player input, locking after 500ms of inactivity.\n\nFor the soft drop, I'm resetting the gravity timer to prevent double-dropping, and hard drop just moves the piece all the way down and locks immediately. Now I'm thinking through the DAS logic for left and right movement—immediate response on first press, then a delay before auto-repeat kicks in at regular intervals.\n\nI'm spotting a potential issue with overlapping key presses: if the player holds Right then presses Left while still holding Right, the last pressed direction wins, but when they release Left, I'm resetting the direction state without checking if Right is still being held. I need to check the keys state when releasing to see if the opposite direction is still active.\n\nFixing key release handling...\n\nFor the soft drop, I'll leverage the browser's built-in key repeat instead of managing it manually.\n\nThe issue is that my early return guard prevents repeated keydown events, which blocks the natural repeat behavior I need. I should remove that guard and let keydown fire naturally for each repeat, while still tracking held keys separately for the DAS mechanism on left and right arrows.\n\nSetting up the key event handler...\n\nI see the issue though—ArrowDown is firing on every keydown event including browser key repeats, which means soft drop speed depends on the user's OS settings. I should move soft drop into the game loop instead so it drops at a consistent rate I control, just faster than the normal gravity.\n\nI'm settling on the final implementation now. The key spawn positions are y=-1 for the I-piece and y=0 for everything else, with x-coordinates at 3 for most pieces and 4 for the O-piece.\n\nI'm also locking in the game mechanics: 500ms lock delay that resets on moves and rotations (capped at 15 resets), standard DAS timing of 167ms delay with 33ms repeats, 150ms flash animation for line clears, and a speed curve that starts at 800ms per drop at level 1 and accelerates to 17ms at level 20 and beyond, with level progression every 10 lines.\n\nNow I need to handle keyboard input properly—preventing default scrolling behavior for arrow keys and space, and making sure the pause key works even when there's no active piece during animations.\n\nWriting the complete implementation... Setting up the piece definitions and rotation matrices... Defining the kick tables... I'm defining the kick offset data for different rotation states, then setting up a function to retrieve the appropriate kick table based on piece type and rotation direction. Now I'm adding the scoring system and calculating drop speed based on the current level.\n\nSetting up the game state variables... I'm implementing the piece shuffling logic using a Fisher-Yates shuffle to randomize the bag of Tetris pieces, then I realize my spawn function is getting convoluted so I'm going to scrap the complicated logic and just write out the complete, clean HTML file from scratch.\n\nWriting the HTML structure... Still writing styles... Writing the HTML structure... Building the game interface... Setting up the game constants and piece definitions... Setting up rotation data structures...\n\nNow I'm defining the wall kick offsets for the SRS rotation system, mapping each rotation transition to a series of potential kick positions that let pieces slide into place when they'd otherwise collide. Defining kick offset data for different rotation states and a function to retrieve the appropriate kicks based on the piece type and rotation direction, then setting up scoring constants and a speed calculation function...\n\nNow I'm setting up the canvas elements and 2D contexts for the game board, next piece preview, and hold piece display, along with references to the UI elements for score and level.\n\nI'm initializing the core game state variables for the board, current piece, held piece, and piece queue, plus tracking score, level, and lines cleared. I'm also setting up flags for game status like whether the player can hold, if the game is over or paused, and various timing variables for piece locking, line clearing animations, and input handling like delayed auto-shift and soft drop mechanics.\n\nNow I'm setting up the bag randomizer system that shuffles through all seven tetromino types and refills when empty, along with functions to manage the piece queue that always keeps three pieces ahead for preview.\n\nWriting piece helper functions... Writing game logic... Writing game logic... Writing the input handler...\n\nNow I'm setting up the game initialization function that resets the board, clears the score and level, and prepares all the game state variables before spawning the first piece and updating the display.\n\nHandling the animation loop and pause functionality... Writing game loop logic... Writing cell rendering... Writing the game rendering logic... Writing the active piece rendering...\n\nNow I'm finishing the pause overlay with the resume prompt, then moving on to render the next piece queue by setting up the preview canvas and calculating positions for each upcoming tetromino in the queue.\n\nRendering the preview blocks... Rendering the held piece in the hold box with proper shading and opacity based on whether it can be held.\n\nNow I'm setting up the start button click handler and doing the initial render. I notice there's a bug in the `hold()` function—I need to save the current piece type before calling `spawn()`, and I also need to fix how `spawn()` handles the next piece type to avoid calling it twice.\n\nLet me trace through the logic: when holding with no previously held piece, the current piece goes into hold and a new one spawns from the queue. When there is a held piece, I swap the current piece with the held one without consuming the queue. That's the correct behavior, so I just need to make sure `spawn()` isn't being called redundantly. Looking at the spawn and nextType functions, I can see that spawn pulls the first item from the queue and pushes a new one from the bag, so after initialization with three items and the first spawn call, the queue should have those three items minus the one that was consumed. The \"next\" display showing three items makes sense since we're displaying what comes after the current piece. The queue logic checks out. Now I'm noticing the `hold()` function doesn't reset the movement state variables when swapping pieces—I need to add resets for `grounded`, `lockT`, `lockMoves`, and `dropT` so the newly held piece starts fresh.\n\nI'm also reconsidering the spawn collision detection. The current approach tries moving the piece up by one cell if it can't spawn, then checks again before ending the game, but that's not how standard Tetris handles it.\n\nThe proper lockout condition is when a piece can't be placed at its default spawn position—for most pieces that's y=0, and for the I piece it's y=-1. I should just check if the spawn position is valid, and if not, end the game immediately. The valid() function needs to properly account for the board boundaries to make this work correctly. I'm checking the lock condition—if any block lands above the visible field (y < 0), that's game over. The spawn check catches when a piece can't fit at all, and the lock check catches when blocks end up placed in the lockout zone, which handles both the block out and lock out conditions.\n\nRestructuring the lock function...\n\nI need to check for lock-out before placing any blocks on the board. The key insight is that when a piece spawns at y=-1, its blocks are initially at row 0 of the playfield, so the check `piece.y+r < 0` correctly identifies when blocks extend above the visible area. Even in edge cases like an immediate hard-drop on a full board, this would properly trigger game over.\n\nNow I'm ready to finalize the code and move on to the row-clearing animation, where I'll make the cleared cells flash between white and their original color before they disappear. Writing the flash overlay... Writing the flash effect...\n\nNow I'm thinking through the edge cases—specifically what happens when the player presses a key (like pause) while the flash animation is running, since the game loop returns early during the flash and doesn't process normal physics. I also need to figure out what happens after the flash completes and the rows are cleared.\n\nLet me trace through the piece spawning and hold mechanics to make sure they're working correctly. After initialization, the queue should dequeue and enqueue properly, and when I hold a piece, it should swap correctly with the next spawned piece.\n\nI also need to make sure that when I create a new piece during a hold swap, it gets the proper initial rotation and position, and the drop/lock timers reset. One more thing to check: the `draw()` function gets called before the game starts, so I need to handle the case where the queue hasn't been initialized yet.\n\nI'll add guards to check if the game has started before trying to draw the queue and held piece, or I could just initialize those variables as empty defaults from the start. Let me go with initializing them upfront so the draw function doesn't need extra checks.\n\nNow I'm ready to write out the complete HTML file. Before I do, let me verify the SRS kick table offsets...\n\nReviewing kick offsets... Verifying the y-axis negation conversions for the remaining rotation states, and they all check out correctly. Defining rotation kick data... I'm realizing I need to be more careful with the coordinate transformations when converting from y-up to y-down orientation. Let me recalculate these rotation kick offsets systematically to make sure I'm negating the y-coordinates correctly at each step. Updating the kick offset tables... Defining rotation data for JLSTZ pieces...\n\nNow I'm ready to write out the complete HTML file and get this working. I need to reconsider how the clockwise rotation actually works for the T piece. Let me trace through the transformation more carefully—when I rotate a 3×3 matrix 90 degrees clockwise, each element at position (r, c) should move to (c, rows-1-r), which means the leftmost column becomes the top row. Working through the T piece specifically, I'm verifying that my rotation function produces the correct orientations. Verifying the rotation function works correctly for the T piece by tracing through the logic with the 3x3 matrix dimensions. I'm verifying the rotation logic visually with the T piece, and it matches what my function produces. Now let me test this with a non-square matrix like the I piece to make sure the algorithm works correctly for different dimensions. Looking at the rotation sequence for the I piece, I need to verify that rotating clockwise cycles through the standard four orientations correctly—starting with the horizontal spawn position, then vertical, then horizontal again, and back to vertical. Verifying the rotation logic by checking that rotation 3 equals the clockwise rotation of rotation 2, working through the column transformations to confirm the vertical line becomes horizontal. Verifying the spawn positions for each piece type—the I piece appears at row 0 with its cells spread across columns 3-6, the O piece sits at rows 0-1 in columns 4-5, and the T piece occupies row 0-1 starting at column 3, all matching the expected Tetris spawn behavior.\n\nNow I'm writing out the complete implementation file. One thing I need to handle carefully is the DAS (Delayed Auto Shift) timing—when the delay threshold is reached, I'm setting the repeat timer to trigger immediately so the first auto-shift happens right away without waiting for another interval. I'm realizing there's a one-frame delay (around 16ms) between when DAS activates and when the first ARR move happens, which is acceptable. But I could also trigger that first ARR move immediately when DAS activates instead of waiting for the next frame.\n\nThe classic Tetris behavior would be: initial keypress triggers a move, then after DAS_MS another move happens, then ARR_MS intervals after that. I'll go with the immediate approach for the most responsive feel.\n\nNow I'm going back to verify the SRS kick tables one more time with a concrete example before finalizing the code. I'm realizing my rotation calculation is producing a different result than the standard Tetris T-piece rotation—my function is centering the piece in the matrix while the expected rotation should align it differently. Let me trace through what the correct rotation should actually be by visualizing the piece step by step. I'm working through the rotation logic step by step—calculating what each position in the rotated matrix should contain by pulling values from the original T piece, and I'm seeing that my result gives a vertical line of T's down the middle rather than the expected horizontal orientation when rotated clockwise. I'm looking at the standard SRS rotation states for the T-piece to verify how each rotation maps to the next when applying clockwise rotation, checking whether my rotation logic produces the correct sequence. my rotCW function is definitely correct—the matrix representation matches the SRS spec perfectly. Now I'm ready to write out the final HTML file with the rotation logic and kick tables all verified.\n\nWriting the HTML file... Still writing styles... Still writing styles... Building the game interface... Setting up the game constants and piece definitions... Defining rotation matrices for each piece... Defining the kick rotation data... Setting up the game constants and DOM references...\n\nNow I'm initializing the game state variables for the board, pieces, scoring, and input handling, along with timing constants for lock delays, flash effects, and movement controls.\n\nSetting up the bag randomizer to shuffle through the seven tetromino types, then implementing queue management to always have the next three pieces ready.\n\nNow I'm writing helper functions for piece creation and validation—setting up each new piece with its type, rotation state, and spawn position, then checking whether a piece can legally occupy a given position on the board by testing collision against boundaries and existing blocks.\n\nWriting game mechanics... Finishing the hard drop and now handling piece locking—checking for lock-out conditions where blocks exceed the visible field, then writing the placed piece to the board and preparing to scan for completed lines. Writing game logic... I'm tracing through the hold logic to verify it works correctly—when I hold a piece, the current piece goes into the hold slot, a new piece spawns from the queue, and the hold flag resets to prevent immediate re-holding. Refactoring the hold logic...\n\nThe key insight is that `holdPiece()` needs to spawn a new piece from the queue without re-enabling the hold ability, while `spawnPiece()` is the only place that sets `canHold = true` to allow holding again. This way, after holding a piece, the player can't hold again until they naturally spawn the next piece.\n\nNow for the flash animation during line clears—`flashRows` tracks which rows need to be cleared, and the game loop enters a special animation-only mode that skips physics updates. Once the flash duration expires, `clearLines()` removes those rows and calls `spawnPiece()` to bring in the next piece. The pause mechanic works correctly here since `flashT` freezes when paused and resumes when unpaused. I also need to make sure the current piece doesn't render during the flash animation since it's already been locked into place.\n\nSetting `piece = null` after locking...\n\nContinuing with the lock piece logic...\n\nNow I'm working on the rendering side—during the flash animation, I want the completed rows to pulse with a bright white overlay that fades in and out using a sine wave, creating that satisfying visual feedback before the rows clear. Writing the blink logic... I'm verifying the timing works out—at each 40ms interval the phase alternates between white and the original color, ending on white right before the rows clear. But honestly, just keeping them solid white for the full 120ms duration is simpler and probably looks fine, though it might feel a bit static.\n\nActually, a fade effect would be better—I'll draw the base cell color first, then layer a white overlay that starts subtle and intensifies as the flash progresses, creating a smooth brightening effect that peaks just before the rows disappear.\n\nNow I'm ready to write out the complete game implementation with all the mechanics figured out. I need to handle the case where input is processed during the flash animation but the piece is null, so I'll add null checks to the movement handlers to prevent errors. The cleanest approach is to disable input entirely during the flash sequence, which keeps the logic simple and prevents any edge cases with piece state. I'm confident the piece state is always valid since lockPiece() flows synchronously into either game over, a flash animation, or spawning the next piece. Now I'm writing out the complete implementation with all the core Tetris mechanics—the seven tetrominoes with proper rotation, wall kick offsets, ghost and hold pieces, a visible next queue, line clear animations with flashing, standard scoring scaled by level, level progression every ten lines, accelerating gravity, input handling with DAS and ARR for smooth movement, soft drop acceleration, hard drop, and lock delay that resets on movement.\n\nI'm reconsidering the soft drop speed—standard Tetris uses 20G when held, but for simplicity I'll stick with a fixed interval around 50ms per row.\n\nNow I'm looking at the scoring system: single lines give 100 points per level, doubles are 300, triples are 500, and a full Tetris is 800, all multiplied by the current level. Soft and hard drops add bonus points per cell dropped. I'll implement this exactly as specified.","signature":"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not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 19 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.5895 +} +\ No newline at end of file diff --git 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"max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2", + "run_number": 2, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:24:22.034962+00:00", + "wall_time_seconds": 370, + "exit_code": 1, + "completed_at": "2026-04-04T09:30:35.563317+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl 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It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n"}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-st5faakp","session_id":"51362cea-83a9-4448-b173-97c33c3a433b","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"afba112f-79b3-4c7e-ba2c-886b5ba2497e","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01XAABJtxDKteD17aBgYQhWi","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser. 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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01MXGpCCD9dUTb9nw8CU6rWU","type":"message","role":"assistant","content":[{"type":"text","text":"Now I'll build the complete Tetris game as a single, polished HTML file:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":188,"cache_read_input_tokens":5417,"cache_creation":{"ephemeral_5m_input_tokens":188,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"01181a27-a2bb-49a9-b782-e4bba637dd38"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01WcVMzGio9JerqEQ8VTbTbS","type":"message","role":"assistant","content":[{"type":"text","text":"Now I'll build the complete Tetris game as a single self-contained HTML file:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":0,"cache_read_input_tokens":5605,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"498025af-eb6a-49f4-ac0d-63679f9a7bdb"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01WcVMzGio9JerqEQ8VTbTbS","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01NGXmT1123ZWPq32Q3HRMdq","name":"Bash","input":{"command":"cat > /tmp/loop-bench-st5faakp/tetris.html << 'HTMLEOF'\n<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Tetris</title>\n <style>\n *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }\n\n body {\n background: #0d0d1a;\n display: flex;\n justify-content: center;\n align-items: center;\n min-height: 100vh;\n font-family: 'Segoe UI', system-ui, sans-serif;\n color: #e0e0ff;\n user-select: none;\n }\n\n #wrapper {\n display: flex;\n gap: 24px;\n align-items: flex-start;\n }\n\n /* ── Left panel ─────────────────────────────── */\n #left-panel {\n display: flex;\n flex-direction: column;\n gap: 16px;\n width: 140px;\n }\n\n /* ── Right panel ────────────────────────────── */\n #right-panel {\n display: flex;\n flex-direction: column;\n gap: 16px;\n width: 140px;\n }\n\n .panel-box {\n background: #12122a;\n border: 2px solid #2a2a5a;\n border-radius: 10px;\n padding: 14px 16px;\n }\n\n .panel-box h3 {\n font-size: 10px;\n letter-spacing: 2px;\n text-transform: uppercase;\n color: #6666aa;\n margin-bottom: 8px;\n }\n\n .panel-value {\n font-size: 26px;\n font-weight: 700;\n color: #c8c8ff;\n letter-spacing: 1px;\n }\n\n /* ── Canvas / game board ────────────────────── */\n #game-area {\n position: relative;\n }\n\n #board {\n display: block;\n border: 3px solid #2a2a5a;\n border-radius: 4px;\n box-shadow: 0 0 40px #3333aa55, inset 0 0 20px #00001888;\n }\n\n /* ── Overlay (start / pause / game-over) ───── */\n #overlay {\n position: absolute;\n inset: 0;\n display: flex;\n flex-direction: column;\n justify-content: center;\n align-items: center;\n gap: 14px;\n background: rgba(5, 5, 20, 0.82);\n border-radius: 2px;\n backdrop-filter: blur(3px);\n }\n\n #overlay h2 {\n font-size: 30px;\n letter-spacing: 4px;\n text-transform: uppercase;\n color: #fff;\n text-shadow: 0 0 20px #8888ff;\n }\n\n #overlay p {\n font-size: 13px;\n color: #9090cc;\n letter-spacing: 1px;\n text-align: center;\n line-height: 1.7;\n }\n\n #overlay button {\n margin-top: 6px;\n padding: 11px 32px;\n font-size: 14px;\n font-weight: 700;\n letter-spacing: 2px;\n text-transform: uppercase;\n background: linear-gradient(135deg, #4444cc, #6644ff);\n color: #fff;\n border: none;\n border-radius: 8px;\n cursor: pointer;\n transition: filter 0.15s, transform 0.12s;\n box-shadow: 0 4px 18px #4444cc88;\n }\n\n #overlay button:hover { filter: brightness(1.25); transform: translateY(-2px); }\n #overlay button:active { transform: translateY(0); }\n\n /* ── Next-piece canvas ──────────────────────── */\n #next-canvas {\n display: block;\n margin: 6px auto 0;\n }\n\n /* ── Hold canvas ────────────────────────────── */\n #hold-canvas {\n display: block;\n margin: 6px auto 0;\n }\n\n /* ── Controls list ──────────────────────────── */\n .controls-list {\n font-size: 11px;\n line-height: 2;\n color: #7777bb;\n }\n\n .controls-list span {\n display: inline-block;\n background: #1e1e3e;\n border: 1px solid #3333668a;\n border-radius: 4px;\n padding: 1px 6px;\n font-size: 10px;\n color: #aaaadd;\n margin-right: 4px;\n }\n\n /* ── Ghost / level colours ──────────────────── */\n #level-bar-wrap {\n background: #1a1a35;\n border-radius: 4px;\n height: 6px;\n overflow: hidden;\n margin-top: 6px;\n }\n\n #level-bar {\n height: 100%;\n width: 0%;\n background: linear-gradient(90deg, #4466ff, #aa44ff);\n border-radius: 4px;\n transition: width 0.4s ease;\n }\n </style>\n</head>\n<body>\n\n<div id=\"wrapper\">\n\n <!-- LEFT PANEL -->\n <div id=\"left-panel\">\n <div class=\"panel-box\">\n <h3>Score</h3>\n <div class=\"panel-value\" id=\"score-display\">0</div>\n </div>\n <div class=\"panel-box\">\n <h3>Level</h3>\n <div class=\"panel-value\" id=\"level-display\">1</div>\n <div id=\"level-bar-wrap\"><div id=\"level-bar\"></div></div>\n </div>\n <div class=\"panel-box\">\n <h3>Lines</h3>\n <div class=\"panel-value\" id=\"lines-display\">0</div>\n </div>\n <div class=\"panel-box\">\n <h3>Hold <small style=\"font-size:9px;color:#555\">(C)</small></h3>\n <canvas id=\"hold-canvas\" width=\"100\" height=\"80\"></canvas>\n </div>\n </div>\n\n <!-- GAME BOARD -->\n <div id=\"game-area\">\n <canvas id=\"board\" width=\"300\" height=\"600\"></canvas>\n <div id=\"overlay\">\n <h2>Tetris</h2>\n <p>Arrow keys to move & soft-drop<br>\n ↑ / X rotate CW · Z rotate CCW<br>\n Space hard-drop · C hold<br>\n P pause</p>\n <button id=\"start-btn\">Start Game</button>\n </div>\n </div>\n\n <!-- RIGHT PANEL -->\n <div id=\"right-panel\">\n <div class=\"panel-box\">\n <h3>Next</h3>\n <canvas id=\"next-canvas\" width=\"100\" height=\"200\"></canvas>\n </div>\n <div class=\"panel-box\">\n <h3>Controls</h3>\n <div class=\"controls-list\">\n <span>←→</span> Move<br>\n <span>↓</span> Soft Drop<br>\n <span>Space</span> Hard Drop<br>\n <span>↑</span><span>X</span> Rotate CW<br>\n <span>Z</span> Rotate CCW<br>\n <span>C</span> Hold<br>\n <span>P</span> Pause\n </div>\n </div>\n <div class=\"panel-box\" id=\"combo-box\" style=\"display:none\">\n <h3>Combo</h3>\n <div class=\"panel-value\" id=\"combo-display\">x0</div>\n </div>\n </div>\n\n</div>\n\n<script>\n// ═══════════════════════════════════════════════════════════════\n// CONSTANTS\n// ═══════════════════════════════════════════════════════════════\nconst COLS = 10;\nconst ROWS = 20;\nconst BLOCK = 30; // px per cell\n\n// Colours per piece type (index 0 = empty)\nconst COLORS = [\n null,\n '#00cfcf', // I – cyan\n '#f0a000', // O – orange/yellow\n '#a000f0', // T – purple\n '#00a000', // S – green\n '#f00000', // Z – red\n '#0000f0', // J – blue\n '#f07800', // L – orange\n];\n\nconst GHOST_ALPHA = 0.22;\n\n// Tetromino definitions – each piece has 4 rotation states\n// Stored as [row][col] offsets from the pivot\nconst PIECES = {\n // 0 1 2 3\n I: [\n [[0,0],[0,1],[0,2],[0,3]],\n [[0,2],[1,2],[2,2],[3,2]],\n [[1,0],[1,1],[1,2],[1,3]],\n [[0,1],[1,1],[2,1],[3,1]],\n ],\n O: [\n [[0,0],[0,1],[1,0],[1,1]],\n [[0,0],[0,1],[1,0],[1,1]],\n [[0,0],[0,1],[1,0],[1,1]],\n [[0,0],[0,1],[1,0],[1,1]],\n ],\n T: [\n [[0,1],[1,0],[1,1],[1,2]],\n [[0,1],[1,1],[1,2],[2,1]],\n [[1,0],[1,1],[1,2],[2,1]],\n [[0,1],[1,0],[1,1],[2,1]],\n ],\n S: [\n [[0,1],[0,2],[1,0],[1,1]],\n [[0,1],[1,1],[1,2],[2,2]],\n [[1,1],[1,2],[2,0],[2,1]],\n [[0,0],[1,0],[1,1],[2,1]],\n ],\n Z: [\n [[0,0],[0,1],[1,1],[1,2]],\n [[0,2],[1,1],[1,2],[2,1]],\n [[1,0],[1,1],[2,1],[2,2]],\n [[0,1],[1,0],[1,1],[2,0]],\n ],\n J: [\n [[0,0],[1,0],[1,1],[1,2]],\n [[0,1],[0,2],[1,1],[2,1]],\n [[1,0],[1,1],[1,2],[2,2]],\n [[0,1],[1,1],[2,0],[2,1]],\n ],\n L: [\n [[0,2],[1,0],[1,1],[1,2]],\n [[0,1],[1,1],[2,1],[2,2]],\n [[1,0],[1,1],[1,2],[2,0]],\n [[0,0],[0,1],[1,1],[2,1]],\n ],\n};\n\nconst PIECE_KEYS = Object.keys(PIECES); // ['I','O','T','S','Z','J','L']\nconst PIECE_IDX = { I:1, O:2, T:3, S:4, Z:5, J:6, L:7 };\n\n// Wall-kick offsets for standard rotation (SRS-lite)\n// [from-rotation][to-rotation] = array of (dr,dc) attempts\nconst KICKS = {};\n(function buildKicks() {\n // Non-I pieces\n const standard = {\n '01': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]],\n '10': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]],\n '12': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]],\n '21': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2,-1]],\n '23': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]],\n '32': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]],\n '30': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]],\n '03': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2, 1]],\n };\n // I piece\n const iKicks = {\n '01': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]],\n '10': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]],\n '12': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]],\n '21': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]],\n '23': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]],\n '32': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]],\n '30': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]],\n '03': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]],\n };\n KICKS['standard'] = standard;\n KICKS['I'] = iKicks;\n})();\n\n// Level → fall interval (ms)\nfunction levelSpeed(level) {\n // Classic Tetris-style curve\n const frames = [48,43,38,33,28,23,18,13,8,6,5,5,5,4,4,4,3,3,3,2,2,2,2,2,2,2,2,2,1];\n const idx = Math.min(level - 1, frames.length - 1);\n return Math.round(frames[idx] * (1000 / 60));\n}\n\n// Points for line clears (single,double,triple,tetris)\nconst LINE_POINTS = [0, 100, 300, 500, 800];\nconst SOFT_DROP_PTS = 1;\nconst HARD_DROP_PTS = 2;\n\n// ═══════════════════════════════════════════════════════════════\n// GAME STATE\n// ═══════════════════════════════════════════════════════════════\nlet board, current, ghost, nextQueue, held;\nlet score, level, lines, combo;\nlet canHold, gameOver, paused, started;\nlet dropTimer, lastTime, animId;\nlet lockTimer, lockMoved;\nconst LOCK_DELAY = 500; // ms before a grounded piece locks\nconst LOCK_MOVES = 15; // max moves before forced lock\n\n// 7-bag randomiser\nlet bag = [];\nfunction nextBag() {\n if (bag.length === 0) {\n bag = [...PIECE_KEYS];\n for (let i = bag.length - 1; i > 0; i--) {\n const j = Math.floor(Math.random() * (i + 1));\n [bag[i], bag[j]] = [bag[j], bag[i]];\n }\n }\n return bag.pop();\n}\n\nfunction createPiece(type) {\n // spawn position: row 0, col 3\n return { type, rot: 0, row: 0, col: 3 };\n}\n\nfunction initGame() {\n board = Array.from({ length: ROWS }, () => new Array(COLS).fill(0));\n bag = [];\n nextQueue = [nextBag(), nextBag(), nextBag()];\n current = spawnPiece();\n held = null;\n score = 0; level = 1; lines = 0; combo = -1;\n canHold = true;\n gameOver = false; paused = false;\n dropTimer = 0; lastTime = null;\n lockTimer = null; lockMoved = 0;\n updateUI();\n updateGhost();\n}\n\nfunction spawnPiece() {\n const type = nextQueue.shift();\n nextQueue.push(nextBag());\n const p = createPiece(type);\n // I and O spawn slightly lower\n if (type === 'I') p.row = -1;\n return p;\n}\n\n// ═══════════════════════════════════════════════════════════════\n// BOARD HELPERS\n// ═══════════════════════════════════════════════════════════════\nfunction cells(piece) {\n return PIECES[piece.type][piece.rot].map(([dr, dc]) => [piece.row + dr, piece.col + dc]);\n}\n\nfunction valid(piece, dr = 0, dc = 0, rot = piece.rot) {\n const test = { ...piece, row: piece.row + dr, col: piece.col + dc, rot };\n return cells(test).every(([r, c]) =>\n r < ROWS && c >= 0 && c < COLS && (r < 0 || board[r][c] === 0)\n );\n}\n\nfunction lock(piece) {\n let topped = false;\n cells(piece).forEach(([r, c]) => {\n if (r < 0) { topped = true; return; }\n board[r][c] = PIECE_IDX[piece.type];\n });\n if (topped) { triggerGameOver(); return; }\n\n clearLines();\n\n current = spawnPiece();\n canHold = true;\n lockMoved = 0;\n clearTimeout(lockTimer); lockTimer = null;\n\n if (!valid(current)) {\n triggerGameOver();\n } else {\n updateGhost();\n }\n}\n\nfunction clearLines() {\n const full = [];\n for (let r = ROWS - 1; r >= 0; r--) {\n if (board[r].every(v => v !== 0)) full.push(r);\n }\n if (full.length === 0) {\n combo = -1;\n return;\n }\n\n // Remove full rows (animate via flash handled in draw)\n full.forEach(r => {\n board.splice(r, 1);\n board.unshift(new Array(COLS).fill(0));\n });\n\n combo++;\n const pts = (LINE_POINTS[full.length] + (combo > 0 ? 50 * combo : 0)) * level;\n score += pts;\n lines += full.length;\n level = Math.floor(lines / 10) + 1;\n updateUI();\n\n flashLines(full); // purely visual\n}\n\nfunction updateGhost() {\n if (!current) return;\n ghost = { ...current };\n while (valid(ghost, 1)) ghost.row++;\n}\n\n// ═══════════════════════════════════════════════════════════════\n// CONTROLS\n// ═══════════════════════════════════════════════════════════════\nfunction moveLeft() { tryMove(0, -1); }\nfunction moveRight() { tryMove(0, 1); }\nfunction softDrop() {\n if (tryMove(1, 0)) {\n score += SOFT_DROP_PTS;\n updateUI();\n }\n}\n\nfunction tryMove(dr, dc) {\n if (!current || gameOver || paused) return false;\n if (valid(current, dr, dc)) {\n current.row += dr;\n current.col += dc;\n updateGhost();\n extendLock();\n return true;\n }\n return false;\n}\n\nfunction rotateCW() { rotate( 1); }\nfunction rotateCCW() { rotate(-1); }\n\nfunction rotate(dir) {\n if (!current || gameOver || paused) return;\n const newRot = ((current.rot + dir) + 4) % 4;\n const kickTable = current.type === 'I' ? KICKS['I'] : KICKS['standard'];\n const key = `${current.rot}${newRot}`;\n const kicks = kickTable[key] || [[0, 0]];\n for (const [kr, kc] of kicks) {\n if (valid(current, kr, kc, newRot)) {\n current.row += kr;\n current.col += kc;\n current.rot = newRot;\n updateGhost();\n extendLock();\n return;\n }\n }\n}\n\nfunction hardDrop() {\n if (!current || gameOver || paused) return;\n let dropped = 0;\n while (valid(current, 1)) { current.row++; dropped++; }\n score += dropped * HARD_DROP_PTS;\n updateUI();\n clearTimeout(lockTimer); lockTimer = null;\n lock(current);\n}\n\nfunction holdPiece() {\n if (!current || !canHold || gameOver || paused) return;\n if (held) {\n const prev = held;\n held = current.type;\n current = createPiece(prev);\n if (current.type === 'I') current.row = -1;\n } else {\n held = current.type;\n current = spawnPiece();\n }\n canHold = false;\n updateGhost();\n drawHold();\n}\n\nfunction extendLock() {\n // If the piece is grounded, reset lock timer (up to LOCK_MOVES times)\n if (!valid(current, 1) && lockMoved < LOCK_MOVES) {\n lockMoved++;\n clearTimeout(lockTimer);\n lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY);\n }\n}\n\n// ═══════════════════════════════════════════════════════════════\n// GAME LOOP\n// ═══════════════════════════════════════════════════════════════\nfunction gameLoop(ts) {\n if (gameOver) return;\n animId = requestAnimationFrame(gameLoop);\n\n if (!lastTime) lastTime = ts;\n const dt = ts - lastTime;\n lastTime = ts;\n\n if (!paused) {\n dropTimer += dt;\n const interval = levelSpeed(level);\n if (dropTimer >= interval) {\n dropTimer -= interval;\n // Attempt to fall\n if (valid(current, 1)) {\n current.row++;\n updateGhost();\n } else {\n // Start lock delay if not already running\n if (!lockTimer) {\n lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY);\n }\n }\n }\n }\n\n draw();\n}\n\nfunction triggerGameOver() {\n gameOver = true;\n clearTimeout(lockTimer);\n cancelAnimationFrame(animId);\n drawBoard(); // final frame\n showOverlay('GAME OVER', `Score: ${score} | Level: ${level} | Lines: ${lines}`, 'Play Again');\n}\n\n// ═══════════════════════════════════════════════════════════════\n// RENDERING\n// ═══════════════════════════════════════════════════════════════\nconst canvas = document.getElementById('board');\nconst ctx = canvas.getContext('2d');\nconst nextCvs = document.getElementById('next-canvas');\nconst nextCtx = nextCvs.getContext('2d');\nconst holdCvs = document.getElementById('hold-canvas');\nconst holdCtx = holdCvs.getContext('2d');\n\nlet flashRows = [];\nlet flashTimer = 0;\nconst FLASH_DUR = 320;\n\nfunction flashLines(rows) {\n flashRows = rows;\n flashTimer = FLASH_DUR;\n}\n\nfunction draw() {\n drawBoard();\n drawNext();\n drawHold();\n}\n\nfunction drawBoard() {\n // Background\n ctx.fillStyle = '#090918';\n ctx.fillRect(0, 0, canvas.width, canvas.height);\n\n // Grid lines (subtle)\n ctx.strokeStyle = '#12122a';\n ctx.lineWidth = 0.5;\n for (let c = 1; c < COLS; c++) {\n ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke();\n }\n for (let r = 1; r < ROWS; r++) {\n ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke();\n }\n\n // Settled board cells\n for (let r = 0; r < ROWS; r++) {\n for (let c = 0; c < COLS; c++) {\n if (board[r][c]) {\n drawCell(ctx, r, c, COLORS[board[r][c]], 1, 0, 0);\n }\n }\n }\n\n // Flash overlay\n if (flashTimer > 0 && !paused) {\n flashTimer -= 16;\n const alpha = 0.7 * (flashTimer / FLASH_DUR);\n ctx.fillStyle = `rgba(255,255,255,${alpha})`;\n flashRows.forEach(r => {\n ctx.fillRect(0, r * BLOCK, canvas.width, BLOCK);\n });\n if (flashTimer <= 0) flashRows = [];\n }\n\n if (paused) {\n ctx.fillStyle = 'rgba(5,5,20,0.7)';\n ctx.fillRect(0, 0, canvas.width, canvas.height);\n ctx.fillStyle = '#fff';\n ctx.font = 'bold 28px system-ui';\n ctx.textAlign = 'center';\n ctx.fillText('PAUSED', canvas.width / 2, canvas.height / 2);\n ctx.font = '13px system-ui';\n ctx.fillStyle = '#8888cc';\n ctx.fillText('Press P to resume', canvas.width / 2, canvas.height / 2 + 32);\n return;\n }\n\n if (!current) return;\n\n // Ghost piece\n if (ghost && (ghost.row !== current.row || ghost.col !== current.col)) {\n cells(ghost).forEach(([r, c]) => {\n if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], GHOST_ALPHA, 0, 0);\n });\n }\n\n // Active piece\n cells(current).forEach(([r, c]) => {\n if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], 1, 0, 0);\n });\n}\n\nfunction drawCell(context, row, col, color, alpha, offR, offC) {\n const x = (col + offC) * BLOCK;\n const y = (row + offR) * BLOCK;\n const s = BLOCK - 1;\n\n context.save();\n context.globalAlpha = alpha;\n\n // Main fill with gradient\n const grad = context.createLinearGradient(x, y, x + s, y + s);\n grad.addColorStop(0, lighten(color, 40));\n grad.addColorStop(1, darken(color, 30));\n context.fillStyle = grad;\n context.fillRect(x + 1, y + 1, s - 1, s - 1);\n\n // Highlight edge (top-left)\n context.fillStyle = lighten(color, 60);\n context.fillRect(x + 1, y + 1, s - 1, 2);\n context.fillRect(x + 1, y + 1, 2, s - 1);\n\n // Shadow edge (bottom-right)\n context.fillStyle = darken(color, 50);\n context.fillRect(x + 1, y + s - 2, s - 1, 2);\n context.fillRect(x + s - 2, y + 1, 2, s - 1);\n\n context.restore();\n}\n\nfunction drawMiniPiece(context, cvs, type) {\n context.fillStyle = '#0d0d1f';\n context.fillRect(0, 0, cvs.width, cvs.height);\n if (!type) return;\n\n const shape = PIECES[type][0];\n const minR = Math.min(...shape.map(([r]) => r));\n const maxR = Math.max(...shape.map(([r]) => r));\n const minC = Math.min(...shape.map(([, c]) => c));\n const maxC = Math.max(...shape.map(([, c]) => c));\n const h = maxR - minR + 1;\n const w = maxC - minC + 1;\n const bs = 20;\n const startX = Math.floor((cvs.width - w * bs) / 2);\n const startY = Math.floor((cvs.height - h * bs) / 2);\n\n shape.forEach(([r, c]) => {\n const px = startX + (c - minC) * bs;\n const py = startY + (r - minR) * bs;\n const s = bs - 1;\n\n const color = COLORS[PIECE_IDX[type]];\n const grad = context.createLinearGradient(px, py, px + s, py + s);\n grad.addColorStop(0, lighten(color, 40));\n grad.addColorStop(1, darken(color, 30));\n context.fillStyle = grad;\n context.fillRect(px + 1, py + 1, s - 1, s - 1);\n\n context.fillStyle = lighten(color, 60);\n context.fillRect(px + 1, py + 1, s - 1, 2);\n context.fillRect(px + 1, py + 1, 2, s - 1);\n\n context.fillStyle = darken(color, 50);\n context.fillRect(px + 1, py + s - 2, s - 1, 2);\n context.fillRect(px + s - 2, py + 1, 2, s - 1);\n });\n}\n\nfunction drawNext() {\n const w = nextCvs.width;\n const h = nextCvs.height;\n nextCtx.fillStyle = '#0d0d1f';\n nextCtx.fillRect(0, 0, w, h);\n\n const slotH = h / 3;\n nextQueue.forEach((type, i) => {\n const shape = PIECES[type][0];\n const minR = Math.min(...shape.map(([r]) => r));\n const maxR = Math.max(...shape.map(([r]) => r));\n const minC = Math.min(...shape.map(([, c]) => c));\n const maxC = Math.max(...shape.map(([, c]) => c));\n const ph = maxR - minR + 1;\n const pw = maxC - minC + 1;\n const bs = i === 0 ? 20 : 16;\n const startX = Math.floor((w - pw * bs) / 2);\n const baseY = i * slotH + Math.floor((slotH - ph * bs) / 2);\n\n shape.forEach(([r, c]) => {\n const px = startX + (c - minC) * bs;\n const py = baseY + (r - minR) * bs;\n const s = bs - 1;\n const color = COLORS[PIECE_IDX[type]];\n const alpha = i === 0 ? 1 : 0.65 - i * 0.1;\n\n nextCtx.save();\n nextCtx.globalAlpha = alpha;\n const grad = nextCtx.createLinearGradient(px, py, px + s, py + s);\n grad.addColorStop(0, lighten(color, 40));\n grad.addColorStop(1, darken(color, 30));\n nextCtx.fillStyle = grad;\n nextCtx.fillRect(px + 1, py + 1, s - 1, s - 1);\n nextCtx.fillStyle = lighten(color, 60);\n nextCtx.fillRect(px + 1, py + 1, s - 1, 2);\n nextCtx.fillRect(px + 1, py + 1, 2, s - 1);\n nextCtx.fillStyle = darken(color, 50);\n nextCtx.fillRect(px + 1, py + s - 2, s - 1, 2);\n nextCtx.fillRect(px + s - 2, py + 1, 2, s - 1);\n nextCtx.restore();\n });\n });\n}\n\nfunction drawHold() {\n drawMiniPiece(holdCtx, holdCvs, held);\n if (!canHold && held) {\n holdCtx.fillStyle = 'rgba(0,0,0,0.5)';\n holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height);\n }\n}\n\n// ═══════════════════════════════════════════════════════════════\n// UI\n// ═══════════════════════════════════════════════════════════════\nconst scoreEl = document.getElementById('score-display');\nconst levelEl = document.getElementById('level-display');\nconst linesEl = document.getElementById('lines-display');\nconst levelBar = document.getElementById('level-bar');\nconst comboBox = document.getElementById('combo-box');\nconst comboDis = document.getElementById('combo-display');\n\nfunction updateUI() {\n scoreEl.textContent = score.toLocaleString();\n levelEl.textContent = level;\n linesEl.textContent = lines;\n const pct = ((lines % 10) / 10) * 100;\n levelBar.style.width = pct + '%';\n\n if (combo > 0) {\n comboBox.style.display = 'block';\n comboDis.textContent = 'x' + (combo + 1);\n } else {\n comboBox.style.display = 'none';\n }\n}\n\n// ═══════════════════════════════════════════════════════════════\n// OVERLAY\n// ═══════════════════════════════════════════════════════════════\nconst overlay = document.getElementById('overlay');\nconst startBtn = document.getElementById('start-btn');\n\nfunction showOverlay(title, msg, btnText) {\n overlay.querySelector('h2').textContent = title;\n overlay.querySelector('p').innerHTML = msg;\n startBtn.textContent = btnText;\n overlay.style.display = 'flex';\n}\n\nfunction hideOverlay() {\n overlay.style.display = 'none';\n}\n\nstartBtn.addEventListener('click', () => {\n hideOverlay();\n initGame();\n lastTime = null;\n started = true;\n animId = requestAnimationFrame(gameLoop);\n});\n\n// ═══════════════════════════════════════════════════════════════\n// KEYBOARD\n// ═══════════════════════════════════════════════════════════════\nconst DAS_DELAY = 170; // ms before auto-repeat\nconst DAS_REPEAT = 50; // ms between repeats\n\nlet dasKey = null, dasTimer = null, dasRepeat = null;\n\nfunction startDAS(key) {\n if (dasKey === key) return;\n stopDAS();\n dasKey = key;\n applyKey(key);\n dasTimer = setTimeout(() => {\n dasRepeat = setInterval(() => applyKey(key), DAS_REPEAT);\n }, DAS_DELAY);\n}\n\nfunction stopDAS(key) {\n if (key && dasKey !== key) return;\n clearTimeout(dasTimer);\n clearInterval(dasRepeat);\n dasKey = null;\n}\n\nfunction applyKey(key) {\n if (key === 'ArrowLeft') moveLeft();\n if (key === 'ArrowRight') moveRight();\n if (key === 'ArrowDown') softDrop();\n}\n\nwindow.addEventListener('keydown', e => {\n if (!started) return;\n\n // Pause toggle\n if (e.code === 'KeyP') {\n if (gameOver) return;\n paused = !paused;\n if (!paused) { lastTime = null; }\n return;\n }\n\n if (paused || gameOver) return;\n\n switch (e.code) {\n case 'ArrowLeft': e.preventDefault(); startDAS('ArrowLeft'); break;\n case 'ArrowRight': e.preventDefault(); startDAS('ArrowRight'); break;\n case 'ArrowDown': e.preventDefault(); startDAS('ArrowDown'); break;\n case 'ArrowUp': e.preventDefault(); rotateCW(); break;\n case 'KeyX': e.preventDefault(); rotateCW(); break;\n case 'KeyZ': e.preventDefault(); rotateCCW(); break;\n case 'Space': e.preventDefault(); hardDrop(); break;\n case 'KeyC': e.preventDefault(); holdPiece(); break;\n }\n});\n\nwindow.addEventListener('keyup', e => {\n if (['ArrowLeft','ArrowRight','ArrowDown'].includes(e.code)) {\n stopDAS(e.code);\n }\n});\n\n// ═══════════════════════════════════════════════════════════════\n// COLOUR HELPERS\n// ═══════════════════════════════════════════════════════════════\nfunction parseHex(hex) {\n const n = parseInt(hex.replace('#',''), 16);\n return [(n >> 16) & 255, (n >> 8) & 255, n & 255];\n}\nfunction toHex([r, g, b]) {\n return '#' + [r, g, b].map(v => Math.min(255, Math.max(0, v)).toString(16).padStart(2,'0')).join('');\n}\nfunction lighten(hex, amt) { return toHex(parseHex(hex).map(v => v + amt)); }\nfunction darken(hex, amt) { return toHex(parseHex(hex).map(v => v - amt)); }\n\n// ═══════════════════════════════════════════════════════════════\n// INITIAL RENDER\n// ═══════════════════════════════════════════════════════════════\n(function initialDraw() {\n ctx.fillStyle = '#090918';\n ctx.fillRect(0, 0, canvas.width, canvas.height);\n // subtle grid\n ctx.strokeStyle = '#12122a';\n ctx.lineWidth = 0.5;\n for (let c = 1; c < COLS; c++) {\n ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke();\n }\n for (let r = 1; r < ROWS; r++) {\n ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke();\n }\n holdCtx.fillStyle = '#0d0d1f'; holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height);\n nextCtx.fillStyle = '#0d0d1f'; nextCtx.fillRect(0, 0, nextCvs.width, nextCvs.height);\n})();\n</script>\n</body>\n</html>\nHTMLEOF\necho \"File written successfully\"","description":"Write the complete Tetris HTML game file"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":0,"cache_read_input_tokens":5605,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"40096783-6d7a-4d94-95bf-43a849283ce4"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NGXmT1123ZWPq32Q3HRMdq","type":"tool_result","content":"File written successfully","is_error":false}]},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"a3aebb86-9a04-4f0a-8c23-7c7cf18d29db","timestamp":"2026-04-04T09:29:40.466Z","tool_use_result":{"stdout":"File written successfully","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_011nRrgYJ4e6VJ5u3WmFc8Jr","type":"message","role":"assistant","content":[{"type":"text","text":"Now let me verify the file looks correct and complete:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":10659,"cache_read_input_tokens":5605,"cache_creation":{"ephemeral_5m_input_tokens":10659,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"4b5cc9b5-85ca-4c2d-9fce-ca9c9a7191f6"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_011nRrgYJ4e6VJ5u3WmFc8Jr","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01QYr6X6gShcSXMFFf7mNMKx","name":"Read","input":{"file_path":"/tmp/loop-bench-st5faakp/tetris.html"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":10659,"cache_read_input_tokens":5605,"cache_creation":{"ephemeral_5m_input_tokens":10659,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"b7cef9f4-ea36-41c6-8b24-3e64799c564b"} +{"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QYr6X6gShcSXMFFf7mNMKx","type":"tool_result","content":"1\t<!DOCTYPE html>\n2\t<html lang=\"en\">\n3\t<head>\n4\t <meta charset=\"UTF-8\" />\n5\t <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n6\t <title>Tetris</title>\n7\t <style>\n8\t *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }\n9\t\n10\t body {\n11\t background: #0d0d1a;\n12\t display: flex;\n13\t justify-content: center;\n14\t align-items: center;\n15\t min-height: 100vh;\n16\t font-family: 'Segoe UI', system-ui, sans-serif;\n17\t color: #e0e0ff;\n18\t user-select: none;\n19\t }\n20\t\n21\t #wrapper {\n22\t display: flex;\n23\t gap: 24px;\n24\t align-items: flex-start;\n25\t }\n26\t\n27\t /* ── Left panel ─────────────────────────────── */\n28\t #left-panel {\n29\t display: flex;\n30\t flex-direction: column;\n31\t gap: 16px;\n32\t width: 140px;\n33\t }\n34\t\n35\t /* ── Right panel ────────────────────────────── */\n36\t #right-panel {\n37\t display: flex;\n38\t flex-direction: column;\n39\t gap: 16px;\n40\t width: 140px;\n41\t }\n42\t\n43\t .panel-box {\n44\t background: #12122a;\n45\t border: 2px solid #2a2a5a;\n46\t border-radius: 10px;\n47\t padding: 14px 16px;\n48\t }\n49\t\n50\t .panel-box h3 {\n51\t font-size: 10px;\n52\t letter-spacing: 2px;\n53\t text-transform: uppercase;\n54\t color: #6666aa;\n55\t margin-bottom: 8px;\n56\t }\n57\t\n58\t .panel-value {\n59\t font-size: 26px;\n60\t font-weight: 700;\n61\t color: #c8c8ff;\n62\t letter-spacing: 1px;\n63\t }\n64\t\n65\t /* ── Canvas / game board ────────────────────── */\n66\t #game-area {\n67\t position: relative;\n68\t }\n69\t\n70\t #board {\n71\t display: block;\n72\t border: 3px solid #2a2a5a;\n73\t border-radius: 4px;\n74\t box-shadow: 0 0 40px #3333aa55, inset 0 0 20px #00001888;\n75\t }\n76\t\n77\t /* ── Overlay (start / pause / game-over) ───── */\n78\t #overlay {\n79\t position: absolute;\n80\t inset: 0;\n81\t display: flex;\n82\t flex-direction: column;\n83\t justify-content: center;\n84\t align-items: center;\n85\t gap: 14px;\n86\t background: rgba(5, 5, 20, 0.82);\n87\t border-radius: 2px;\n88\t backdrop-filter: blur(3px);\n89\t }\n90\t\n91\t #overlay h2 {\n92\t font-size: 30px;\n93\t letter-spacing: 4px;\n94\t text-transform: uppercase;\n95\t color: #fff;\n96\t text-shadow: 0 0 20px #8888ff;\n97\t }\n98\t\n99\t #overlay p {\n100\t font-size: 13px;\n101\t color: #9090cc;\n102\t letter-spacing: 1px;\n103\t text-align: center;\n104\t line-height: 1.7;\n105\t }\n106\t\n107\t #overlay button {\n108\t margin-top: 6px;\n109\t padding: 11px 32px;\n110\t font-size: 14px;\n111\t font-weight: 700;\n112\t letter-spacing: 2px;\n113\t text-transform: uppercase;\n114\t background: linear-gradient(135deg, #4444cc, #6644ff);\n115\t color: #fff;\n116\t border: none;\n117\t border-radius: 8px;\n118\t cursor: pointer;\n119\t transition: filter 0.15s, transform 0.12s;\n120\t box-shadow: 0 4px 18px #4444cc88;\n121\t }\n122\t\n123\t #overlay button:hover { filter: brightness(1.25); transform: translateY(-2px); }\n124\t #overlay button:active { transform: translateY(0); }\n125\t\n126\t /* ── Next-piece canvas ──────────────────────── */\n127\t #next-canvas {\n128\t display: block;\n129\t margin: 6px auto 0;\n130\t }\n131\t\n132\t /* ── Hold canvas ────────────────────────────── */\n133\t #hold-canvas {\n134\t display: block;\n135\t margin: 6px auto 0;\n136\t }\n137\t\n138\t /* ── Controls list ──────────────────────────── */\n139\t .controls-list {\n140\t font-size: 11px;\n141\t line-height: 2;\n142\t color: #7777bb;\n143\t }\n144\t\n145\t .controls-list span {\n146\t display: inline-block;\n147\t background: #1e1e3e;\n148\t border: 1px solid #3333668a;\n149\t border-radius: 4px;\n150\t padding: 1px 6px;\n151\t font-size: 10px;\n152\t color: #aaaadd;\n153\t margin-right: 4px;\n154\t }\n155\t\n156\t /* ── Ghost / level colours ──────────────────── */\n157\t #level-bar-wrap {\n158\t background: #1a1a35;\n159\t border-radius: 4px;\n160\t height: 6px;\n161\t overflow: hidden;\n162\t margin-top: 6px;\n163\t }\n164\t\n165\t #level-bar {\n166\t height: 100%;\n167\t width: 0%;\n168\t background: linear-gradient(90deg, #4466ff, #aa44ff);\n169\t border-radius: 4px;\n170\t transition: width 0.4s ease;\n171\t }\n172\t </style>\n173\t</head>\n174\t<body>\n175\t\n176\t<div id=\"wrapper\">\n177\t\n178\t <!-- LEFT PANEL -->\n179\t <div id=\"left-panel\">\n180\t <div class=\"panel-box\">\n181\t <h3>Score</h3>\n182\t <div class=\"panel-value\" id=\"score-display\">0</div>\n183\t </div>\n184\t <div class=\"panel-box\">\n185\t <h3>Level</h3>\n186\t <div class=\"panel-value\" id=\"level-display\">1</div>\n187\t <div id=\"level-bar-wrap\"><div id=\"level-bar\"></div></div>\n188\t </div>\n189\t <div class=\"panel-box\">\n190\t <h3>Lines</h3>\n191\t <div class=\"panel-value\" id=\"lines-display\">0</div>\n192\t </div>\n193\t <div class=\"panel-box\">\n194\t <h3>Hold <small style=\"font-size:9px;color:#555\">(C)</small></h3>\n195\t <canvas id=\"hold-canvas\" width=\"100\" height=\"80\"></canvas>\n196\t </div>\n197\t </div>\n198\t\n199\t <!-- GAME BOARD -->\n200\t <div id=\"game-area\">\n201\t <canvas id=\"board\" width=\"300\" height=\"600\"></canvas>\n202\t <div id=\"overlay\">\n203\t <h2>Tetris</h2>\n204\t <p>Arrow keys to move & soft-drop<br>\n205\t ↑ / X rotate CW · Z rotate CCW<br>\n206\t Space hard-drop · C hold<br>\n207\t P pause</p>\n208\t <button id=\"start-btn\">Start Game</button>\n209\t </div>\n210\t </div>\n211\t\n212\t <!-- RIGHT PANEL -->\n213\t <div id=\"right-panel\">\n214\t <div class=\"panel-box\">\n215\t <h3>Next</h3>\n216\t <canvas id=\"next-canvas\" width=\"100\" height=\"200\"></canvas>\n217\t </div>\n218\t <div class=\"panel-box\">\n219\t <h3>Controls</h3>\n220\t <div class=\"controls-list\">\n221\t <span>←→</span> Move<br>\n222\t <span>↓</span> Soft Drop<br>\n223\t <span>Space</span> Hard Drop<br>\n224\t <span>↑</span><span>X</span> Rotate CW<br>\n225\t <span>Z</span> Rotate CCW<br>\n226\t <span>C</span> Hold<br>\n227\t <span>P</span> Pause\n228\t </div>\n229\t </div>\n230\t <div class=\"panel-box\" id=\"combo-box\" style=\"display:none\">\n231\t <h3>Combo</h3>\n232\t <div class=\"panel-value\" id=\"combo-display\">x0</div>\n233\t </div>\n234\t </div>\n235\t\n236\t</div>\n237\t\n238\t<script>\n239\t// ═══════════════════════════════════════════════════════════════\n240\t// CONSTANTS\n241\t// ═══════════════════════════════════════════════════════════════\n242\tconst COLS = 10;\n243\tconst ROWS = 20;\n244\tconst BLOCK = 30; // px per cell\n245\t\n246\t// Colours per piece type (index 0 = empty)\n247\tconst COLORS = [\n248\t null,\n249\t '#00cfcf', // I – cyan\n250\t '#f0a000', // O – orange/yellow\n251\t '#a000f0', // T – purple\n252\t '#00a000', // S – green\n253\t '#f00000', // Z – red\n254\t '#0000f0', // J – blue\n255\t '#f07800', // L – orange\n256\t];\n257\t\n258\tconst GHOST_ALPHA = 0.22;\n259\t\n260\t// Tetromino definitions – each piece has 4 rotation states\n261\t// Stored as [row][col] offsets from the pivot\n262\tconst PIECES = {\n263\t // 0 1 2 3\n264\t I: [\n265\t [[0,0],[0,1],[0,2],[0,3]],\n266\t [[0,2],[1,2],[2,2],[3,2]],\n267\t [[1,0],[1,1],[1,2],[1,3]],\n268\t [[0,1],[1,1],[2,1],[3,1]],\n269\t ],\n270\t O: [\n271\t [[0,0],[0,1],[1,0],[1,1]],\n272\t [[0,0],[0,1],[1,0],[1,1]],\n273\t [[0,0],[0,1],[1,0],[1,1]],\n274\t [[0,0],[0,1],[1,0],[1,1]],\n275\t ],\n276\t T: [\n277\t [[0,1],[1,0],[1,1],[1,2]],\n278\t [[0,1],[1,1],[1,2],[2,1]],\n279\t [[1,0],[1,1],[1,2],[2,1]],\n280\t [[0,1],[1,0],[1,1],[2,1]],\n281\t ],\n282\t S: [\n283\t [[0,1],[0,2],[1,0],[1,1]],\n284\t [[0,1],[1,1],[1,2],[2,2]],\n285\t [[1,1],[1,2],[2,0],[2,1]],\n286\t [[0,0],[1,0],[1,1],[2,1]],\n287\t ],\n288\t Z: [\n289\t [[0,0],[0,1],[1,1],[1,2]],\n290\t [[0,2],[1,1],[1,2],[2,1]],\n291\t [[1,0],[1,1],[2,1],[2,2]],\n292\t [[0,1],[1,0],[1,1],[2,0]],\n293\t ],\n294\t J: [\n295\t [[0,0],[1,0],[1,1],[1,2]],\n296\t [[0,1],[0,2],[1,1],[2,1]],\n297\t [[1,0],[1,1],[1,2],[2,2]],\n298\t [[0,1],[1,1],[2,0],[2,1]],\n299\t ],\n300\t L: [\n301\t [[0,2],[1,0],[1,1],[1,2]],\n302\t [[0,1],[1,1],[2,1],[2,2]],\n303\t [[1,0],[1,1],[1,2],[2,0]],\n304\t [[0,0],[0,1],[1,1],[2,1]],\n305\t ],\n306\t};\n307\t\n308\tconst PIECE_KEYS = Object.keys(PIECES); // ['I','O','T','S','Z','J','L']\n309\tconst PIECE_IDX = { I:1, O:2, T:3, S:4, Z:5, J:6, L:7 };\n310\t\n311\t// Wall-kick offsets for standard rotation (SRS-lite)\n312\t// [from-rotation][to-rotation] = array of (dr,dc) attempts\n313\tconst KICKS = {};\n314\t(function buildKicks() {\n315\t // Non-I pieces\n316\t const standard = {\n317\t '01': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]],\n318\t '10': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]],\n319\t '12': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]],\n320\t '21': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2,-1]],\n321\t '23': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]],\n322\t '32': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]],\n323\t '30': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]],\n324\t '03': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2, 1]],\n325\t };\n326\t // I piece\n327\t const iKicks = {\n328\t '01': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]],\n329\t '10': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]],\n330\t '12': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]],\n331\t '21': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]],\n332\t '23': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]],\n333\t '32': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]],\n334\t '30': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]],\n335\t '03': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]],\n336\t };\n337\t KICKS['standard'] = standard;\n338\t KICKS['I'] = iKicks;\n339\t})();\n340\t\n341\t// Level → fall interval (ms)\n342\tfunction levelSpeed(level) {\n343\t // Classic Tetris-style curve\n344\t const frames = [48,43,38,33,28,23,18,13,8,6,5,5,5,4,4,4,3,3,3,2,2,2,2,2,2,2,2,2,1];\n345\t const idx = Math.min(level - 1, frames.length - 1);\n346\t return Math.round(frames[idx] * (1000 / 60));\n347\t}\n348\t\n349\t// Points for line clears (single,double,triple,tetris)\n350\tconst LINE_POINTS = [0, 100, 300, 500, 800];\n351\tconst SOFT_DROP_PTS = 1;\n352\tconst HARD_DROP_PTS = 2;\n353\t\n354\t// ═══════════════════════════════════════════════════════════════\n355\t// GAME STATE\n356\t// ═══════════════════════════════════════════════════════════════\n357\tlet board, current, ghost, nextQueue, held;\n358\tlet score, level, lines, combo;\n359\tlet canHold, gameOver, paused, started;\n360\tlet dropTimer, lastTime, animId;\n361\tlet lockTimer, lockMoved;\n362\tconst LOCK_DELAY = 500; // ms before a grounded piece locks\n363\tconst LOCK_MOVES = 15; // max moves before forced lock\n364\t\n365\t// 7-bag randomiser\n366\tlet bag = [];\n367\tfunction nextBag() {\n368\t if (bag.length === 0) {\n369\t bag = [...PIECE_KEYS];\n370\t for (let i = bag.length - 1; i > 0; i--) {\n371\t const j = Math.floor(Math.random() * (i + 1));\n372\t [bag[i], bag[j]] = [bag[j], bag[i]];\n373\t }\n374\t }\n375\t return bag.pop();\n376\t}\n377\t\n378\tfunction createPiece(type) {\n379\t // spawn position: row 0, col 3\n380\t return { type, rot: 0, row: 0, col: 3 };\n381\t}\n382\t\n383\tfunction initGame() {\n384\t board = Array.from({ length: ROWS }, () => new Array(COLS).fill(0));\n385\t bag = [];\n386\t nextQueue = [nextBag(), nextBag(), nextBag()];\n387\t current = spawnPiece();\n388\t held = null;\n389\t score = 0; level = 1; lines = 0; combo = -1;\n390\t canHold = true;\n391\t gameOver = false; paused = false;\n392\t dropTimer = 0; lastTime = null;\n393\t lockTimer = null; lockMoved = 0;\n394\t updateUI();\n395\t updateGhost();\n396\t}\n397\t\n398\tfunction spawnPiece() {\n399\t const type = nextQueue.shift();\n400\t nextQueue.push(nextBag());\n401\t const p = createPiece(type);\n402\t // I and O spawn slightly lower\n403\t if (type === 'I') p.row = -1;\n404\t return p;\n405\t}\n406\t\n407\t// ═══════════════════════════════════════════════════════════════\n408\t// BOARD HELPERS\n409\t// ═══════════════════════════════════════════════════════════════\n410\tfunction cells(piece) {\n411\t return PIECES[piece.type][piece.rot].map(([dr, dc]) => [piece.row + dr, piece.col + dc]);\n412\t}\n413\t\n414\tfunction valid(piece, dr = 0, dc = 0, rot = piece.rot) {\n415\t const test = { ...piece, row: piece.row + dr, col: piece.col + dc, rot };\n416\t return cells(test).every(([r, c]) =>\n417\t r < ROWS && c >= 0 && c < COLS && (r < 0 || board[r][c] === 0)\n418\t );\n419\t}\n420\t\n421\tfunction lock(piece) {\n422\t let topped = false;\n423\t cells(piece).forEach(([r, c]) => {\n424\t if (r < 0) { topped = true; return; }\n425\t board[r][c] = PIECE_IDX[piece.type];\n426\t });\n427\t if (topped) { triggerGameOver(); return; }\n428\t\n429\t clearLines();\n430\t\n431\t current = spawnPiece();\n432\t canHold = true;\n433\t lockMoved = 0;\n434\t clearTimeout(lockTimer); lockTimer = null;\n435\t\n436\t if (!valid(current)) {\n437\t triggerGameOver();\n438\t } else {\n439\t updateGhost();\n440\t }\n441\t}\n442\t\n443\tfunction clearLines() {\n444\t const full = [];\n445\t for (let r = ROWS - 1; r >= 0; r--) {\n446\t if (board[r].every(v => v !== 0)) full.push(r);\n447\t }\n448\t if (full.length === 0) {\n449\t combo = -1;\n450\t return;\n451\t }\n452\t\n453\t // Remove full rows (animate via flash handled in draw)\n454\t full.forEach(r => {\n455\t board.splice(r, 1);\n456\t board.unshift(new Array(COLS).fill(0));\n457\t });\n458\t\n459\t combo++;\n460\t const pts = (LINE_POINTS[full.length] + (combo > 0 ? 50 * combo : 0)) * level;\n461\t score += pts;\n462\t lines += full.length;\n463\t level = Math.floor(lines / 10) + 1;\n464\t updateUI();\n465\t\n466\t flashLines(full); // purely visual\n467\t}\n468\t\n469\tfunction updateGhost() {\n470\t if (!current) return;\n471\t ghost = { ...current };\n472\t while (valid(ghost, 1)) ghost.row++;\n473\t}\n474\t\n475\t// ═══════════════════════════════════════════════════════════════\n476\t// CONTROLS\n477\t// ═══════════════════════════════════════════════════════════════\n478\tfunction moveLeft() { tryMove(0, -1); }\n479\tfunction moveRight() { tryMove(0, 1); }\n480\tfunction softDrop() {\n481\t if (tryMove(1, 0)) {\n482\t score += SOFT_DROP_PTS;\n483\t updateUI();\n484\t }\n485\t}\n486\t\n487\tfunction tryMove(dr, dc) {\n488\t if (!current || gameOver || paused) return false;\n489\t if (valid(current, dr, dc)) {\n490\t current.row += dr;\n491\t current.col += dc;\n492\t updateGhost();\n493\t extendLock();\n494\t return true;\n495\t }\n496\t return false;\n497\t}\n498\t\n499\tfunction rotateCW() { rotate( 1); }\n500\tfunction rotateCCW() { rotate(-1); }\n501\t\n502\tfunction rotate(dir) {\n503\t if (!current || gameOver || paused) return;\n504\t const newRot = ((current.rot + dir) + 4) % 4;\n505\t const kickTable = current.type === 'I' ? KICKS['I'] : KICKS['standard'];\n506\t const key = `${current.rot}${newRot}`;\n507\t const kicks = kickTable[key] || [[0, 0]];\n508\t for (const [kr, kc] of kicks) {\n509\t if (valid(current, kr, kc, newRot)) {\n510\t current.row += kr;\n511\t current.col += kc;\n512\t current.rot = newRot;\n513\t updateGhost();\n514\t extendLock();\n515\t return;\n516\t }\n517\t }\n518\t}\n519\t\n520\tfunction hardDrop() {\n521\t if (!current || gameOver || paused) return;\n522\t let dropped = 0;\n523\t while (valid(current, 1)) { current.row++; dropped++; }\n524\t score += dropped * HARD_DROP_PTS;\n525\t updateUI();\n526\t clearTimeout(lockTimer); lockTimer = null;\n527\t lock(current);\n528\t}\n529\t\n530\tfunction holdPiece() {\n531\t if (!current || !canHold || gameOver || paused) return;\n532\t if (held) {\n533\t const prev = held;\n534\t held = current.type;\n535\t current = createPiece(prev);\n536\t if (current.type === 'I') current.row = -1;\n537\t } else {\n538\t held = current.type;\n539\t current = spawnPiece();\n540\t }\n541\t canHold = false;\n542\t updateGhost();\n543\t drawHold();\n544\t}\n545\t\n546\tfunction extendLock() {\n547\t // If the piece is grounded, reset lock timer (up to LOCK_MOVES times)\n548\t if (!valid(current, 1) && lockMoved < LOCK_MOVES) {\n549\t lockMoved++;\n550\t clearTimeout(lockTimer);\n551\t lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY);\n552\t }\n553\t}\n554\t\n555\t// ═══════════════════════════════════════════════════════════════\n556\t// GAME LOOP\n557\t// ═══════════════════════════════════════════════════════════════\n558\tfunction gameLoop(ts) {\n559\t if (gameOver) return;\n560\t animId = requestAnimationFrame(gameLoop);\n561\t\n562\t if (!lastTime) lastTime = ts;\n563\t const dt = ts - lastTime;\n564\t lastTime = ts;\n565\t\n566\t if (!paused) {\n567\t dropTimer += dt;\n568\t const interval = levelSpeed(level);\n569\t if (dropTimer >= interval) {\n570\t dropTimer -= interval;\n571\t // Attempt to fall\n572\t if (valid(current, 1)) {\n573\t current.row++;\n574\t updateGhost();\n575\t } else {\n576\t // Start lock delay if not already running\n577\t if (!lockTimer) {\n578\t lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY);\n579\t }\n580\t }\n581\t }\n582\t }\n583\t\n584\t draw();\n585\t}\n586\t\n587\tfunction triggerGameOver() {\n588\t gameOver = true;\n589\t clearTimeout(lockTimer);\n590\t cancelAnimationFrame(animId);\n591\t drawBoard(); // final frame\n592\t showOverlay('GAME OVER', `Score: ${score} | Level: ${level} | Lines: ${lines}`, 'Play Again');\n593\t}\n594\t\n595\t// ═══════════════════════════════════════════════════════════════\n596\t// RENDERING\n597\t// ═══════════════════════════════════════════════════════════════\n598\tconst canvas = document.getElementById('board');\n599\tconst ctx = canvas.getContext('2d');\n600\tconst nextCvs = document.getElementById('next-canvas');\n601\tconst nextCtx = nextCvs.getContext('2d');\n602\tconst holdCvs = document.getElementById('hold-canvas');\n603\tconst holdCtx = holdCvs.getContext('2d');\n604\t\n605\tlet flashRows = [];\n606\tlet flashTimer = 0;\n607\tconst FLASH_DUR = 320;\n608\t\n609\tfunction flashLines(rows) {\n610\t flashRows = rows;\n611\t flashTimer = FLASH_DUR;\n612\t}\n613\t\n614\tfunction draw() {\n615\t drawBoard();\n616\t drawNext();\n617\t drawHold();\n618\t}\n619\t\n620\tfunction drawBoard() {\n621\t // Background\n622\t ctx.fillStyle = '#090918';\n623\t ctx.fillRect(0, 0, canvas.width, canvas.height);\n624\t\n625\t // Grid lines (subtle)\n626\t ctx.strokeStyle = '#12122a';\n627\t ctx.lineWidth = 0.5;\n628\t for (let c = 1; c < COLS; c++) {\n629\t ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke();\n630\t }\n631\t for (let r = 1; r < ROWS; r++) {\n632\t ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke();\n633\t }\n634\t\n635\t // Settled board cells\n636\t for (let r = 0; r < ROWS; r++) {\n637\t for (let c = 0; c < COLS; c++) {\n638\t if (board[r][c]) {\n639\t drawCell(ctx, r, c, COLORS[board[r][c]], 1, 0, 0);\n640\t }\n641\t }\n642\t }\n643\t\n644\t // Flash overlay\n645\t if (flashTimer > 0 && !paused) {\n646\t flashTimer -= 16;\n647\t const alpha = 0.7 * (flashTimer / FLASH_DUR);\n648\t ctx.fillStyle = `rgba(255,255,255,${alpha})`;\n649\t flashRows.forEach(r => {\n650\t ctx.fillRect(0, r * BLOCK, canvas.width, BLOCK);\n651\t });\n652\t if (flashTimer <= 0) flashRows = [];\n653\t }\n654\t\n655\t if (paused) {\n656\t ctx.fillStyle = 'rgba(5,5,20,0.7)';\n657\t ctx.fillRect(0, 0, canvas.width, canvas.height);\n658\t ctx.fillStyle = '#fff';\n659\t ctx.font = 'bold 28px system-ui';\n660\t ctx.textAlign = 'center';\n661\t ctx.fillText('PAUSED', canvas.width / 2, canvas.height / 2);\n662\t ctx.font = '13px system-ui';\n663\t ctx.fillStyle = '#8888cc';\n664\t ctx.fillText('Press P to resume', canvas.width / 2, canvas.height / 2 + 32);\n665\t return;\n666\t }\n667\t\n668\t if (!current) return;\n669\t\n670\t // Ghost piece\n671\t if (ghost && (ghost.row !== current.row || ghost.col !== current.col)) {\n672\t cells(ghost).forEach(([r, c]) => {\n673\t if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], GHOST_ALPHA, 0, 0);\n674\t });\n675\t }\n676\t\n677\t // Active piece\n678\t cells(current).forEach(([r, c]) => {\n679\t if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], 1, 0, 0);\n680\t });\n681\t}\n682\t\n683\tfunction drawCell(context, row, col, color, alpha, offR, offC) {\n684\t const x = (col + offC) * BLOCK;\n685\t const y = (row + offR) * BLOCK;\n686\t const s = BLOCK - 1;\n687\t\n688\t context.save();\n689\t context.globalAlpha = alpha;\n690\t\n691\t // Main fill with gradient\n692\t const grad = context.createLinearGradient(x, y, x + s, y + s);\n693\t grad.addColorStop(0, lighten(color, 40));\n694\t grad.addColorStop(1, darken(color, 30));\n695\t context.fillStyle = grad;\n696\t context.fillRect(x + 1, y + 1, s - 1, s - 1);\n697\t\n698\t // Highlight edge (top-left)\n699\t context.fillStyle = lighten(color, 60);\n700\t context.fillRect(x + 1, y + 1, s - 1, 2);\n701\t context.fillRect(x + 1, y + 1, 2, s - 1);\n702\t\n703\t // Shadow edge (bottom-right)\n704\t context.fillStyle = darken(color, 50);\n705\t context.fillRect(x + 1, y + s - 2, s - 1, 2);\n706\t context.fillRect(x + s - 2, y + 1, 2, s - 1);\n707\t\n708\t context.restore();\n709\t}\n710\t\n711\tfunction drawMiniPiece(context, cvs, type) {\n712\t context.fillStyle = '#0d0d1f';\n713\t context.fillRect(0, 0, cvs.width, cvs.height);\n714\t if (!type) return;\n715\t\n716\t const shape = PIECES[type][0];\n717\t const minR = Math.min(...shape.map(([r]) => r));\n718\t const maxR = Math.max(...shape.map(([r]) => r));\n719\t const minC = Math.min(...shape.map(([, c]) => c));\n720\t const maxC = Math.max(...shape.map(([, c]) => c));\n721\t const h = maxR - minR + 1;\n722\t const w = maxC - minC + 1;\n723\t const bs = 20;\n724\t const startX = Math.floor((cvs.width - w * bs) / 2);\n725\t const startY = Math.floor((cvs.height - h * bs) / 2);\n726\t\n727\t shape.forEach(([r, c]) => {\n728\t const px = startX + (c - minC) * bs;\n729\t const py = startY + (r - minR) * bs;\n730\t const s = bs - 1;\n731\t\n732\t const color = COLORS[PIECE_IDX[type]];\n733\t const grad = context.createLinearGradient(px, py, px + s, py + s);\n734\t grad.addColorStop(0, lighten(color, 40));\n735\t grad.addColorStop(1, darken(color, 30));\n736\t context.fillStyle = grad;\n737\t context.fillRect(px + 1, py + 1, s - 1, s - 1);\n738\t\n739\t context.fillStyle = lighten(color, 60);\n740\t context.fillRect(px + 1, py + 1, s - 1, 2);\n741\t context.fillRect(px + 1, py + 1, 2, s - 1);\n742\t\n743\t context.fillStyle = darken(color, 50);\n744\t context.fillRect(px + 1, py + s - 2, s - 1, 2);\n745\t context.fillRect(px + s - 2, py + 1, 2, s - 1);\n746\t });\n747\t}\n748\t\n749\tfunction drawNext() {\n750\t const w = nextCvs.width;\n751\t const h = nextCvs.height;\n752\t nextCtx.fillStyle = '#0d0d1f';\n753\t nextCtx.fillRect(0, 0, w, h);\n754\t\n755\t const slotH = h / 3;\n756\t nextQueue.forEach((type, i) => {\n757\t const shape = PIECES[type][0];\n758\t const minR = Math.min(...shape.map(([r]) => r));\n759\t const maxR = Math.max(...shape.map(([r]) => r));\n760\t const minC = Math.min(...shape.map(([, c]) => c));\n761\t const maxC = Math.max(...shape.map(([, c]) => c));\n762\t const ph = maxR - minR + 1;\n763\t const pw = maxC - minC + 1;\n764\t const bs = i === 0 ? 20 : 16;\n765\t const startX = Math.floor((w - pw * bs) / 2);\n766\t const baseY = i * slotH + Math.floor((slotH - ph * bs) / 2);\n767\t\n768\t shape.forEach(([r, c]) => {\n769\t const px = startX + (c - minC) * bs;\n770\t const py = baseY + (r - minR) * bs;\n771\t const s = bs - 1;\n772\t const color = COLORS[PIECE_IDX[type]];\n773\t const alpha = i === 0 ? 1 : 0.65 - i * 0.1;\n774\t\n775\t nextCtx.save();\n776\t nextCtx.globalAlpha = alpha;\n777\t const grad = nextCtx.createLinearGradient(px, py, px + s, py + s);\n778\t grad.addColorStop(0, lighten(color, 40));\n779\t grad.addColorStop(1, darken(color, 30));\n780\t nextCtx.fillStyle = grad;\n781\t nextCtx.fillRect(px + 1, py + 1, s - 1, s - 1);\n782\t nextCtx.fillStyle = lighten(color, 60);\n783\t nextCtx.fillRect(px + 1, py + 1, s - 1, 2);\n784\t nextCtx.fillRect(px + 1, py + 1, 2, s - 1);\n785\t nextCtx.fillStyle = darken(color, 50);\n786\t nextCtx.fillRect(px + 1, py + s - 2, s - 1, 2);\n787\t nextCtx.fillRect(px + s - 2, py + 1, 2, s - 1);\n788\t nextCtx.restore();\n789\t });\n790\t });\n791\t}\n792\t\n793\tfunction drawHold() {\n794\t drawMiniPiece(holdCtx, holdCvs, held);\n795\t if (!canHold && held) {\n796\t holdCtx.fillStyle = 'rgba(0,0,0,0.5)';\n797\t holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height);\n798\t }\n799\t}\n800\t\n801\t// ═══════════════════════════════════════════════════════════════\n802\t// UI\n803\t// ═══════════════════════════════════════════════════════════════\n804\tconst scoreEl = document.getElementById('score-display');\n805\tconst levelEl = document.getElementById('level-display');\n806\tconst linesEl = document.getElementById('lines-display');\n807\tconst levelBar = document.getElementById('level-bar');\n808\tconst comboBox = document.getElementById('combo-box');\n809\tconst comboDis = document.getElementById('combo-display');\n810\t\n811\tfunction updateUI() {\n812\t scoreEl.textContent = score.toLocaleString();\n813\t levelEl.textContent = level;\n814\t linesEl.textContent = lines;\n815\t const pct = ((lines % 10) / 10) * 100;\n816\t levelBar.style.width = pct + '%';\n817\t\n818\t if (combo > 0) {\n819\t comboBox.style.display = 'block';\n820\t comboDis.textContent = 'x' + (combo + 1);\n821\t } else {\n822\t comboBox.style.display = 'none';\n823\t }\n824\t}\n825\t\n826\t// ═══════════════════════════════════════════════════════════════\n827\t// OVERLAY\n828\t// ═══════════════════════════════════════════════════════════════\n829\tconst overlay = document.getElementById('overlay');\n830\tconst startBtn = document.getElementById('start-btn');\n831\t\n832\tfunction showOverlay(title, msg, btnText) {\n833\t overlay.querySelector('h2').textContent = title;\n834\t overlay.querySelector('p').innerHTML = msg;\n835\t startBtn.textContent = btnText;\n836\t overlay.style.display = 'flex';\n837\t}\n838\t\n839\tfunction hideOverlay() {\n840\t overlay.style.display = 'none';\n841\t}\n842\t\n843\tstartBtn.addEventListener('click', () => {\n844\t hideOverlay();\n845\t initGame();\n846\t lastTime = null;\n847\t started = true;\n848\t animId = requestAnimationFrame(gameLoop);\n849\t});\n850\t\n851\t// ═══════════════════════════════════════════════════════════════\n852\t// KEYBOARD\n853\t// ═══════════════════════════════════════════════════════════════\n854\tconst DAS_DELAY = 170; // ms before auto-repeat\n855\tconst DAS_REPEAT = 50; // ms between repeats\n856\t\n857\tlet dasKey = null, dasTimer = null, dasRepeat = null;\n858\t\n859\tfunction startDAS(key) {\n860\t if (dasKey === key) return;\n861\t stopDAS();\n862\t dasKey = key;\n863\t applyKey(key);\n864\t dasTimer = setTimeout(() => {\n865\t dasRepeat = setInterval(() => applyKey(key), DAS_REPEAT);\n866\t }, DAS_DELAY);\n867\t}\n868\t\n869\tfunction stopDAS(key) {\n870\t if (key && dasKey !== key) return;\n871\t clearTimeout(dasTimer);\n872\t clearInterval(dasRepeat);\n873\t dasKey = null;\n874\t}\n875\t\n876\tfunction applyKey(key) {\n877\t if (key === 'ArrowLeft') moveLeft();\n878\t if (key === 'ArrowRight') moveRight();\n879\t if (key === 'ArrowDown') softDrop();\n880\t}\n881\t\n882\twindow.addEventListener('keydown', e => {\n883\t if (!started) return;\n884\t\n885\t // Pause toggle\n886\t if (e.code === 'KeyP') {\n887\t if (gameOver) return;\n888\t paused = !paused;\n889\t if (!paused) { lastTime = null; }\n890\t return;\n891\t }\n892\t\n893\t if (paused || gameOver) return;\n894\t\n895\t switch (e.code) {\n896\t case 'ArrowLeft': e.preventDefault(); startDAS('ArrowLeft'); break;\n897\t case 'ArrowRight': e.preventDefault(); startDAS('ArrowRight'); break;\n898\t case 'ArrowDown': e.preventDefault(); startDAS('ArrowDown'); break;\n899\t case 'ArrowUp': e.preventDefault(); rotateCW(); break;\n900\t case 'KeyX': e.preventDefault(); rotateCW(); break;\n901\t case 'KeyZ': e.preventDefault(); rotateCCW(); break;\n902\t case 'Space': e.preventDefault(); hardDrop(); break;\n903\t case 'KeyC': e.preventDefault(); holdPiece(); break;\n904\t }\n905\t});\n906\t\n907\twindow.addEventListener('keyup', e => {\n908\t if (['ArrowLeft','ArrowRight','ArrowDown'].includes(e.code)) {\n909\t stopDAS(e.code);\n910\t }\n911\t});\n912\t\n913\t// ═══════════════════════════════════════════════════════════════\n914\t// COLOUR HELPERS\n915\t// ═══════════════════════════════════════════════════════════════\n916\tfunction parseHex(hex) {\n917\t const n = parseInt(hex.replace('#',''), 16);\n918\t return [(n >> 16) & 255, (n >> 8) & 255, n & 255];\n919\t}\n920\tfunction toHex([r, g, b]) {\n921\t return '#' + [r, g, b].map(v => Math.min(255, Math.max(0, v)).toString(16).padStart(2,'0')).join('');\n922\t}\n923\tfunction lighten(hex, amt) { return toHex(parseHex(hex).map(v => v + amt)); }\n924\tfunction darken(hex, amt) { return toHex(parseHex(hex).map(v => v - amt)); }\n925\t\n926\t// ═══════════════════════════════════════════════════════════════\n927\t// INITIAL RENDER\n928\t// ═══════════════════════════════════════════════════════════════\n929\t(function initialDraw() {\n930\t ctx.fillStyle = '#090918';\n931\t ctx.fillRect(0, 0, canvas.width, canvas.height);\n932\t // subtle grid\n933\t ctx.strokeStyle = '#12122a';\n934\t ctx.lineWidth = 0.5;\n935\t for (let c = 1; c < COLS; c++) {\n936\t ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke();\n937\t }\n938\t for (let r = 1; r < ROWS; r++) {\n939\t ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke();\n940\t }\n941\t holdCtx.fillStyle = '#0d0d1f'; holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height);\n942\t nextCtx.fillStyle = '#0d0d1f'; nextCtx.fillRect(0, 0, nextCvs.width, nextCvs.height);\n943\t})();\n944\t</script>\n945\t</body>\n946\t</html>\n947\t"}]},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"b70358d3-4998-4897-ba6e-2563a49f8780","timestamp":"2026-04-04T09:29:46.272Z","tool_use_result":{"type":"text","file":{"filePath":"/tmp/loop-bench-st5faakp/tetris.html","content":"<!DOCTYPE html>\n<html lang=\"en\">\n<head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Tetris</title>\n <style>\n *, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }\n\n body {\n background: #0d0d1a;\n display: flex;\n justify-content: center;\n align-items: center;\n min-height: 100vh;\n font-family: 'Segoe UI', system-ui, sans-serif;\n color: #e0e0ff;\n user-select: none;\n }\n\n #wrapper {\n display: flex;\n gap: 24px;\n align-items: flex-start;\n }\n\n /* ── Left panel ─────────────────────────────── */\n #left-panel {\n display: flex;\n flex-direction: column;\n gap: 16px;\n width: 140px;\n }\n\n /* ── Right panel ────────────────────────────── */\n #right-panel {\n display: flex;\n flex-direction: column;\n gap: 16px;\n width: 140px;\n }\n\n .panel-box {\n background: #12122a;\n border: 2px solid #2a2a5a;\n border-radius: 10px;\n padding: 14px 16px;\n }\n\n .panel-box h3 {\n font-size: 10px;\n letter-spacing: 2px;\n text-transform: uppercase;\n color: #6666aa;\n margin-bottom: 8px;\n }\n\n .panel-value {\n font-size: 26px;\n font-weight: 700;\n color: #c8c8ff;\n letter-spacing: 1px;\n }\n\n /* ── Canvas / game board ────────────────────── */\n #game-area {\n position: relative;\n }\n\n #board {\n display: block;\n border: 3px solid #2a2a5a;\n border-radius: 4px;\n box-shadow: 0 0 40px #3333aa55, inset 0 0 20px #00001888;\n }\n\n /* ── Overlay (start / pause / game-over) ───── */\n #overlay {\n position: absolute;\n inset: 0;\n display: flex;\n flex-direction: column;\n justify-content: center;\n align-items: center;\n gap: 14px;\n background: rgba(5, 5, 20, 0.82);\n border-radius: 2px;\n backdrop-filter: blur(3px);\n }\n\n #overlay h2 {\n font-size: 30px;\n letter-spacing: 4px;\n text-transform: uppercase;\n color: #fff;\n text-shadow: 0 0 20px #8888ff;\n }\n\n #overlay p {\n font-size: 13px;\n color: #9090cc;\n letter-spacing: 1px;\n text-align: center;\n line-height: 1.7;\n }\n\n #overlay button {\n margin-top: 6px;\n padding: 11px 32px;\n font-size: 14px;\n font-weight: 700;\n letter-spacing: 2px;\n text-transform: uppercase;\n background: linear-gradient(135deg, #4444cc, #6644ff);\n color: #fff;\n border: none;\n border-radius: 8px;\n cursor: pointer;\n transition: filter 0.15s, transform 0.12s;\n box-shadow: 0 4px 18px #4444cc88;\n }\n\n #overlay button:hover { filter: brightness(1.25); transform: translateY(-2px); }\n #overlay button:active { transform: translateY(0); }\n\n /* ── Next-piece canvas ──────────────────────── */\n #next-canvas {\n display: block;\n margin: 6px auto 0;\n }\n\n /* ── Hold canvas ────────────────────────────── */\n #hold-canvas {\n display: block;\n margin: 6px auto 0;\n }\n\n /* ── Controls list ──────────────────────────── */\n .controls-list {\n font-size: 11px;\n line-height: 2;\n color: #7777bb;\n }\n\n .controls-list span {\n display: inline-block;\n background: #1e1e3e;\n border: 1px solid #3333668a;\n border-radius: 4px;\n padding: 1px 6px;\n font-size: 10px;\n color: #aaaadd;\n margin-right: 4px;\n }\n\n /* ── Ghost / level colours ──────────────────── */\n #level-bar-wrap {\n background: #1a1a35;\n border-radius: 4px;\n height: 6px;\n overflow: hidden;\n margin-top: 6px;\n }\n\n #level-bar {\n height: 100%;\n width: 0%;\n background: linear-gradient(90deg, #4466ff, #aa44ff);\n border-radius: 4px;\n transition: width 0.4s ease;\n }\n </style>\n</head>\n<body>\n\n<div id=\"wrapper\">\n\n <!-- LEFT PANEL -->\n <div id=\"left-panel\">\n <div class=\"panel-box\">\n <h3>Score</h3>\n <div class=\"panel-value\" id=\"score-display\">0</div>\n </div>\n <div class=\"panel-box\">\n <h3>Level</h3>\n <div class=\"panel-value\" id=\"level-display\">1</div>\n <div id=\"level-bar-wrap\"><div id=\"level-bar\"></div></div>\n </div>\n <div class=\"panel-box\">\n <h3>Lines</h3>\n <div class=\"panel-value\" id=\"lines-display\">0</div>\n </div>\n <div class=\"panel-box\">\n <h3>Hold <small style=\"font-size:9px;color:#555\">(C)</small></h3>\n <canvas id=\"hold-canvas\" width=\"100\" height=\"80\"></canvas>\n </div>\n </div>\n\n <!-- GAME BOARD -->\n <div id=\"game-area\">\n <canvas id=\"board\" width=\"300\" height=\"600\"></canvas>\n <div id=\"overlay\">\n <h2>Tetris</h2>\n <p>Arrow keys to move & soft-drop<br>\n ↑ / X rotate CW · Z rotate CCW<br>\n Space hard-drop · C hold<br>\n P pause</p>\n <button id=\"start-btn\">Start Game</button>\n </div>\n </div>\n\n <!-- RIGHT PANEL -->\n <div id=\"right-panel\">\n <div class=\"panel-box\">\n <h3>Next</h3>\n <canvas id=\"next-canvas\" width=\"100\" height=\"200\"></canvas>\n </div>\n <div class=\"panel-box\">\n <h3>Controls</h3>\n <div class=\"controls-list\">\n <span>←→</span> Move<br>\n <span>↓</span> Soft Drop<br>\n <span>Space</span> Hard Drop<br>\n <span>↑</span><span>X</span> Rotate CW<br>\n <span>Z</span> Rotate CCW<br>\n <span>C</span> Hold<br>\n <span>P</span> Pause\n </div>\n </div>\n <div class=\"panel-box\" id=\"combo-box\" style=\"display:none\">\n <h3>Combo</h3>\n <div class=\"panel-value\" id=\"combo-display\">x0</div>\n </div>\n </div>\n\n</div>\n\n<script>\n// ═══════════════════════════════════════════════════════════════\n// CONSTANTS\n// ═══════════════════════════════════════════════════════════════\nconst COLS = 10;\nconst ROWS = 20;\nconst BLOCK = 30; // px per cell\n\n// Colours per piece type (index 0 = empty)\nconst COLORS = [\n null,\n '#00cfcf', // I – cyan\n '#f0a000', // O – orange/yellow\n '#a000f0', // T – purple\n '#00a000', // S – green\n '#f00000', // Z – red\n '#0000f0', // J – blue\n '#f07800', // L – orange\n];\n\nconst GHOST_ALPHA = 0.22;\n\n// Tetromino definitions – each piece has 4 rotation states\n// Stored as [row][col] offsets from the pivot\nconst PIECES = {\n // 0 1 2 3\n I: [\n [[0,0],[0,1],[0,2],[0,3]],\n [[0,2],[1,2],[2,2],[3,2]],\n [[1,0],[1,1],[1,2],[1,3]],\n [[0,1],[1,1],[2,1],[3,1]],\n ],\n O: [\n [[0,0],[0,1],[1,0],[1,1]],\n [[0,0],[0,1],[1,0],[1,1]],\n [[0,0],[0,1],[1,0],[1,1]],\n [[0,0],[0,1],[1,0],[1,1]],\n ],\n T: [\n [[0,1],[1,0],[1,1],[1,2]],\n [[0,1],[1,1],[1,2],[2,1]],\n [[1,0],[1,1],[1,2],[2,1]],\n [[0,1],[1,0],[1,1],[2,1]],\n ],\n S: [\n [[0,1],[0,2],[1,0],[1,1]],\n [[0,1],[1,1],[1,2],[2,2]],\n [[1,1],[1,2],[2,0],[2,1]],\n [[0,0],[1,0],[1,1],[2,1]],\n ],\n Z: [\n [[0,0],[0,1],[1,1],[1,2]],\n [[0,2],[1,1],[1,2],[2,1]],\n [[1,0],[1,1],[2,1],[2,2]],\n [[0,1],[1,0],[1,1],[2,0]],\n ],\n J: [\n [[0,0],[1,0],[1,1],[1,2]],\n [[0,1],[0,2],[1,1],[2,1]],\n [[1,0],[1,1],[1,2],[2,2]],\n [[0,1],[1,1],[2,0],[2,1]],\n ],\n L: [\n [[0,2],[1,0],[1,1],[1,2]],\n [[0,1],[1,1],[2,1],[2,2]],\n [[1,0],[1,1],[1,2],[2,0]],\n [[0,0],[0,1],[1,1],[2,1]],\n ],\n};\n\nconst PIECE_KEYS = Object.keys(PIECES); // ['I','O','T','S','Z','J','L']\nconst PIECE_IDX = { I:1, O:2, T:3, S:4, Z:5, J:6, L:7 };\n\n// Wall-kick offsets for standard rotation (SRS-lite)\n// [from-rotation][to-rotation] = array of (dr,dc) attempts\nconst KICKS = {};\n(function buildKicks() {\n // Non-I pieces\n const standard = {\n '01': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]],\n '10': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]],\n '12': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]],\n '21': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2,-1]],\n '23': [[ 0, 0],[ 0,-1],[-1,-1],[ 2, 0],[ 2,-1]],\n '32': [[ 0, 0],[ 0, 1],[ 1, 1],[-2, 0],[-2, 1]],\n '30': [[ 0, 0],[ 0, 1],[-1, 1],[ 2, 0],[ 2, 1]],\n '03': [[ 0, 0],[ 0,-1],[ 1,-1],[-2, 0],[-2, 1]],\n };\n // I piece\n const iKicks = {\n '01': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]],\n '10': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]],\n '12': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]],\n '21': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]],\n '23': [[ 0, 0],[ 0, 2],[ 0,-1],[ 1, 2],[-2,-1]],\n '32': [[ 0, 0],[ 0,-2],[ 0, 1],[-1,-2],[ 2, 1]],\n '30': [[ 0, 0],[ 0, 1],[ 0,-2],[-2, 1],[ 1,-2]],\n '03': [[ 0, 0],[ 0,-1],[ 0, 2],[ 2,-1],[-1, 2]],\n };\n KICKS['standard'] = standard;\n KICKS['I'] = iKicks;\n})();\n\n// Level → fall interval (ms)\nfunction levelSpeed(level) {\n // Classic Tetris-style curve\n const frames = [48,43,38,33,28,23,18,13,8,6,5,5,5,4,4,4,3,3,3,2,2,2,2,2,2,2,2,2,1];\n const idx = Math.min(level - 1, frames.length - 1);\n return Math.round(frames[idx] * (1000 / 60));\n}\n\n// Points for line clears (single,double,triple,tetris)\nconst LINE_POINTS = [0, 100, 300, 500, 800];\nconst SOFT_DROP_PTS = 1;\nconst HARD_DROP_PTS = 2;\n\n// ═══════════════════════════════════════════════════════════════\n// GAME STATE\n// ═══════════════════════════════════════════════════════════════\nlet board, current, ghost, nextQueue, held;\nlet score, level, lines, combo;\nlet canHold, gameOver, paused, started;\nlet dropTimer, lastTime, animId;\nlet lockTimer, lockMoved;\nconst LOCK_DELAY = 500; // ms before a grounded piece locks\nconst LOCK_MOVES = 15; // max moves before forced lock\n\n// 7-bag randomiser\nlet bag = [];\nfunction nextBag() {\n if (bag.length === 0) {\n bag = [...PIECE_KEYS];\n for (let i = bag.length - 1; i > 0; i--) {\n const j = Math.floor(Math.random() * (i + 1));\n [bag[i], bag[j]] = [bag[j], bag[i]];\n }\n }\n return bag.pop();\n}\n\nfunction createPiece(type) {\n // spawn position: row 0, col 3\n return { type, rot: 0, row: 0, col: 3 };\n}\n\nfunction initGame() {\n board = Array.from({ length: ROWS }, () => new Array(COLS).fill(0));\n bag = [];\n nextQueue = [nextBag(), nextBag(), nextBag()];\n current = spawnPiece();\n held = null;\n score = 0; level = 1; lines = 0; combo = -1;\n canHold = true;\n gameOver = false; paused = false;\n dropTimer = 0; lastTime = null;\n lockTimer = null; lockMoved = 0;\n updateUI();\n updateGhost();\n}\n\nfunction spawnPiece() {\n const type = nextQueue.shift();\n nextQueue.push(nextBag());\n const p = createPiece(type);\n // I and O spawn slightly lower\n if (type === 'I') p.row = -1;\n return p;\n}\n\n// ═══════════════════════════════════════════════════════════════\n// BOARD HELPERS\n// ═══════════════════════════════════════════════════════════════\nfunction cells(piece) {\n return PIECES[piece.type][piece.rot].map(([dr, dc]) => [piece.row + dr, piece.col + dc]);\n}\n\nfunction valid(piece, dr = 0, dc = 0, rot = piece.rot) {\n const test = { ...piece, row: piece.row + dr, col: piece.col + dc, rot };\n return cells(test).every(([r, c]) =>\n r < ROWS && c >= 0 && c < COLS && (r < 0 || board[r][c] === 0)\n );\n}\n\nfunction lock(piece) {\n let topped = false;\n cells(piece).forEach(([r, c]) => {\n if (r < 0) { topped = true; return; }\n board[r][c] = PIECE_IDX[piece.type];\n });\n if (topped) { triggerGameOver(); return; }\n\n clearLines();\n\n current = spawnPiece();\n canHold = true;\n lockMoved = 0;\n clearTimeout(lockTimer); lockTimer = null;\n\n if (!valid(current)) {\n triggerGameOver();\n } else {\n updateGhost();\n }\n}\n\nfunction clearLines() {\n const full = [];\n for (let r = ROWS - 1; r >= 0; r--) {\n if (board[r].every(v => v !== 0)) full.push(r);\n }\n if (full.length === 0) {\n combo = -1;\n return;\n }\n\n // Remove full rows (animate via flash handled in draw)\n full.forEach(r => {\n board.splice(r, 1);\n board.unshift(new Array(COLS).fill(0));\n });\n\n combo++;\n const pts = (LINE_POINTS[full.length] + (combo > 0 ? 50 * combo : 0)) * level;\n score += pts;\n lines += full.length;\n level = Math.floor(lines / 10) + 1;\n updateUI();\n\n flashLines(full); // purely visual\n}\n\nfunction updateGhost() {\n if (!current) return;\n ghost = { ...current };\n while (valid(ghost, 1)) ghost.row++;\n}\n\n// ═══════════════════════════════════════════════════════════════\n// CONTROLS\n// ═══════════════════════════════════════════════════════════════\nfunction moveLeft() { tryMove(0, -1); }\nfunction moveRight() { tryMove(0, 1); }\nfunction softDrop() {\n if (tryMove(1, 0)) {\n score += SOFT_DROP_PTS;\n updateUI();\n }\n}\n\nfunction tryMove(dr, dc) {\n if (!current || gameOver || paused) return false;\n if (valid(current, dr, dc)) {\n current.row += dr;\n current.col += dc;\n updateGhost();\n extendLock();\n return true;\n }\n return false;\n}\n\nfunction rotateCW() { rotate( 1); }\nfunction rotateCCW() { rotate(-1); }\n\nfunction rotate(dir) {\n if (!current || gameOver || paused) return;\n const newRot = ((current.rot + dir) + 4) % 4;\n const kickTable = current.type === 'I' ? KICKS['I'] : KICKS['standard'];\n const key = `${current.rot}${newRot}`;\n const kicks = kickTable[key] || [[0, 0]];\n for (const [kr, kc] of kicks) {\n if (valid(current, kr, kc, newRot)) {\n current.row += kr;\n current.col += kc;\n current.rot = newRot;\n updateGhost();\n extendLock();\n return;\n }\n }\n}\n\nfunction hardDrop() {\n if (!current || gameOver || paused) return;\n let dropped = 0;\n while (valid(current, 1)) { current.row++; dropped++; }\n score += dropped * HARD_DROP_PTS;\n updateUI();\n clearTimeout(lockTimer); lockTimer = null;\n lock(current);\n}\n\nfunction holdPiece() {\n if (!current || !canHold || gameOver || paused) return;\n if (held) {\n const prev = held;\n held = current.type;\n current = createPiece(prev);\n if (current.type === 'I') current.row = -1;\n } else {\n held = current.type;\n current = spawnPiece();\n }\n canHold = false;\n updateGhost();\n drawHold();\n}\n\nfunction extendLock() {\n // If the piece is grounded, reset lock timer (up to LOCK_MOVES times)\n if (!valid(current, 1) && lockMoved < LOCK_MOVES) {\n lockMoved++;\n clearTimeout(lockTimer);\n lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY);\n }\n}\n\n// ═══════════════════════════════════════════════════════════════\n// GAME LOOP\n// ═══════════════════════════════════════════════════════════════\nfunction gameLoop(ts) {\n if (gameOver) return;\n animId = requestAnimationFrame(gameLoop);\n\n if (!lastTime) lastTime = ts;\n const dt = ts - lastTime;\n lastTime = ts;\n\n if (!paused) {\n dropTimer += dt;\n const interval = levelSpeed(level);\n if (dropTimer >= interval) {\n dropTimer -= interval;\n // Attempt to fall\n if (valid(current, 1)) {\n current.row++;\n updateGhost();\n } else {\n // Start lock delay if not already running\n if (!lockTimer) {\n lockTimer = setTimeout(() => { lock(current); }, LOCK_DELAY);\n }\n }\n }\n }\n\n draw();\n}\n\nfunction triggerGameOver() {\n gameOver = true;\n clearTimeout(lockTimer);\n cancelAnimationFrame(animId);\n drawBoard(); // final frame\n showOverlay('GAME OVER', `Score: ${score} | Level: ${level} | Lines: ${lines}`, 'Play Again');\n}\n\n// ═══════════════════════════════════════════════════════════════\n// RENDERING\n// ═══════════════════════════════════════════════════════════════\nconst canvas = document.getElementById('board');\nconst ctx = canvas.getContext('2d');\nconst nextCvs = document.getElementById('next-canvas');\nconst nextCtx = nextCvs.getContext('2d');\nconst holdCvs = document.getElementById('hold-canvas');\nconst holdCtx = holdCvs.getContext('2d');\n\nlet flashRows = [];\nlet flashTimer = 0;\nconst FLASH_DUR = 320;\n\nfunction flashLines(rows) {\n flashRows = rows;\n flashTimer = FLASH_DUR;\n}\n\nfunction draw() {\n drawBoard();\n drawNext();\n drawHold();\n}\n\nfunction drawBoard() {\n // Background\n ctx.fillStyle = '#090918';\n ctx.fillRect(0, 0, canvas.width, canvas.height);\n\n // Grid lines (subtle)\n ctx.strokeStyle = '#12122a';\n ctx.lineWidth = 0.5;\n for (let c = 1; c < COLS; c++) {\n ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke();\n }\n for (let r = 1; r < ROWS; r++) {\n ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke();\n }\n\n // Settled board cells\n for (let r = 0; r < ROWS; r++) {\n for (let c = 0; c < COLS; c++) {\n if (board[r][c]) {\n drawCell(ctx, r, c, COLORS[board[r][c]], 1, 0, 0);\n }\n }\n }\n\n // Flash overlay\n if (flashTimer > 0 && !paused) {\n flashTimer -= 16;\n const alpha = 0.7 * (flashTimer / FLASH_DUR);\n ctx.fillStyle = `rgba(255,255,255,${alpha})`;\n flashRows.forEach(r => {\n ctx.fillRect(0, r * BLOCK, canvas.width, BLOCK);\n });\n if (flashTimer <= 0) flashRows = [];\n }\n\n if (paused) {\n ctx.fillStyle = 'rgba(5,5,20,0.7)';\n ctx.fillRect(0, 0, canvas.width, canvas.height);\n ctx.fillStyle = '#fff';\n ctx.font = 'bold 28px system-ui';\n ctx.textAlign = 'center';\n ctx.fillText('PAUSED', canvas.width / 2, canvas.height / 2);\n ctx.font = '13px system-ui';\n ctx.fillStyle = '#8888cc';\n ctx.fillText('Press P to resume', canvas.width / 2, canvas.height / 2 + 32);\n return;\n }\n\n if (!current) return;\n\n // Ghost piece\n if (ghost && (ghost.row !== current.row || ghost.col !== current.col)) {\n cells(ghost).forEach(([r, c]) => {\n if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], GHOST_ALPHA, 0, 0);\n });\n }\n\n // Active piece\n cells(current).forEach(([r, c]) => {\n if (r >= 0) drawCell(ctx, r, c, COLORS[PIECE_IDX[current.type]], 1, 0, 0);\n });\n}\n\nfunction drawCell(context, row, col, color, alpha, offR, offC) {\n const x = (col + offC) * BLOCK;\n const y = (row + offR) * BLOCK;\n const s = BLOCK - 1;\n\n context.save();\n context.globalAlpha = alpha;\n\n // Main fill with gradient\n const grad = context.createLinearGradient(x, y, x + s, y + s);\n grad.addColorStop(0, lighten(color, 40));\n grad.addColorStop(1, darken(color, 30));\n context.fillStyle = grad;\n context.fillRect(x + 1, y + 1, s - 1, s - 1);\n\n // Highlight edge (top-left)\n context.fillStyle = lighten(color, 60);\n context.fillRect(x + 1, y + 1, s - 1, 2);\n context.fillRect(x + 1, y + 1, 2, s - 1);\n\n // Shadow edge (bottom-right)\n context.fillStyle = darken(color, 50);\n context.fillRect(x + 1, y + s - 2, s - 1, 2);\n context.fillRect(x + s - 2, y + 1, 2, s - 1);\n\n context.restore();\n}\n\nfunction drawMiniPiece(context, cvs, type) {\n context.fillStyle = '#0d0d1f';\n context.fillRect(0, 0, cvs.width, cvs.height);\n if (!type) return;\n\n const shape = PIECES[type][0];\n const minR = Math.min(...shape.map(([r]) => r));\n const maxR = Math.max(...shape.map(([r]) => r));\n const minC = Math.min(...shape.map(([, c]) => c));\n const maxC = Math.max(...shape.map(([, c]) => c));\n const h = maxR - minR + 1;\n const w = maxC - minC + 1;\n const bs = 20;\n const startX = Math.floor((cvs.width - w * bs) / 2);\n const startY = Math.floor((cvs.height - h * bs) / 2);\n\n shape.forEach(([r, c]) => {\n const px = startX + (c - minC) * bs;\n const py = startY + (r - minR) * bs;\n const s = bs - 1;\n\n const color = COLORS[PIECE_IDX[type]];\n const grad = context.createLinearGradient(px, py, px + s, py + s);\n grad.addColorStop(0, lighten(color, 40));\n grad.addColorStop(1, darken(color, 30));\n context.fillStyle = grad;\n context.fillRect(px + 1, py + 1, s - 1, s - 1);\n\n context.fillStyle = lighten(color, 60);\n context.fillRect(px + 1, py + 1, s - 1, 2);\n context.fillRect(px + 1, py + 1, 2, s - 1);\n\n context.fillStyle = darken(color, 50);\n context.fillRect(px + 1, py + s - 2, s - 1, 2);\n context.fillRect(px + s - 2, py + 1, 2, s - 1);\n });\n}\n\nfunction drawNext() {\n const w = nextCvs.width;\n const h = nextCvs.height;\n nextCtx.fillStyle = '#0d0d1f';\n nextCtx.fillRect(0, 0, w, h);\n\n const slotH = h / 3;\n nextQueue.forEach((type, i) => {\n const shape = PIECES[type][0];\n const minR = Math.min(...shape.map(([r]) => r));\n const maxR = Math.max(...shape.map(([r]) => r));\n const minC = Math.min(...shape.map(([, c]) => c));\n const maxC = Math.max(...shape.map(([, c]) => c));\n const ph = maxR - minR + 1;\n const pw = maxC - minC + 1;\n const bs = i === 0 ? 20 : 16;\n const startX = Math.floor((w - pw * bs) / 2);\n const baseY = i * slotH + Math.floor((slotH - ph * bs) / 2);\n\n shape.forEach(([r, c]) => {\n const px = startX + (c - minC) * bs;\n const py = baseY + (r - minR) * bs;\n const s = bs - 1;\n const color = COLORS[PIECE_IDX[type]];\n const alpha = i === 0 ? 1 : 0.65 - i * 0.1;\n\n nextCtx.save();\n nextCtx.globalAlpha = alpha;\n const grad = nextCtx.createLinearGradient(px, py, px + s, py + s);\n grad.addColorStop(0, lighten(color, 40));\n grad.addColorStop(1, darken(color, 30));\n nextCtx.fillStyle = grad;\n nextCtx.fillRect(px + 1, py + 1, s - 1, s - 1);\n nextCtx.fillStyle = lighten(color, 60);\n nextCtx.fillRect(px + 1, py + 1, s - 1, 2);\n nextCtx.fillRect(px + 1, py + 1, 2, s - 1);\n nextCtx.fillStyle = darken(color, 50);\n nextCtx.fillRect(px + 1, py + s - 2, s - 1, 2);\n nextCtx.fillRect(px + s - 2, py + 1, 2, s - 1);\n nextCtx.restore();\n });\n });\n}\n\nfunction drawHold() {\n drawMiniPiece(holdCtx, holdCvs, held);\n if (!canHold && held) {\n holdCtx.fillStyle = 'rgba(0,0,0,0.5)';\n holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height);\n }\n}\n\n// ═══════════════════════════════════════════════════════════════\n// UI\n// ═══════════════════════════════════════════════════════════════\nconst scoreEl = document.getElementById('score-display');\nconst levelEl = document.getElementById('level-display');\nconst linesEl = document.getElementById('lines-display');\nconst levelBar = document.getElementById('level-bar');\nconst comboBox = document.getElementById('combo-box');\nconst comboDis = document.getElementById('combo-display');\n\nfunction updateUI() {\n scoreEl.textContent = score.toLocaleString();\n levelEl.textContent = level;\n linesEl.textContent = lines;\n const pct = ((lines % 10) / 10) * 100;\n levelBar.style.width = pct + '%';\n\n if (combo > 0) {\n comboBox.style.display = 'block';\n comboDis.textContent = 'x' + (combo + 1);\n } else {\n comboBox.style.display = 'none';\n }\n}\n\n// ═══════════════════════════════════════════════════════════════\n// OVERLAY\n// ═══════════════════════════════════════════════════════════════\nconst overlay = document.getElementById('overlay');\nconst startBtn = document.getElementById('start-btn');\n\nfunction showOverlay(title, msg, btnText) {\n overlay.querySelector('h2').textContent = title;\n overlay.querySelector('p').innerHTML = msg;\n startBtn.textContent = btnText;\n overlay.style.display = 'flex';\n}\n\nfunction hideOverlay() {\n overlay.style.display = 'none';\n}\n\nstartBtn.addEventListener('click', () => {\n hideOverlay();\n initGame();\n lastTime = null;\n started = true;\n animId = requestAnimationFrame(gameLoop);\n});\n\n// ═══════════════════════════════════════════════════════════════\n// KEYBOARD\n// ═══════════════════════════════════════════════════════════════\nconst DAS_DELAY = 170; // ms before auto-repeat\nconst DAS_REPEAT = 50; // ms between repeats\n\nlet dasKey = null, dasTimer = null, dasRepeat = null;\n\nfunction startDAS(key) {\n if (dasKey === key) return;\n stopDAS();\n dasKey = key;\n applyKey(key);\n dasTimer = setTimeout(() => {\n dasRepeat = setInterval(() => applyKey(key), DAS_REPEAT);\n }, DAS_DELAY);\n}\n\nfunction stopDAS(key) {\n if (key && dasKey !== key) return;\n clearTimeout(dasTimer);\n clearInterval(dasRepeat);\n dasKey = null;\n}\n\nfunction applyKey(key) {\n if (key === 'ArrowLeft') moveLeft();\n if (key === 'ArrowRight') moveRight();\n if (key === 'ArrowDown') softDrop();\n}\n\nwindow.addEventListener('keydown', e => {\n if (!started) return;\n\n // Pause toggle\n if (e.code === 'KeyP') {\n if (gameOver) return;\n paused = !paused;\n if (!paused) { lastTime = null; }\n return;\n }\n\n if (paused || gameOver) return;\n\n switch (e.code) {\n case 'ArrowLeft': e.preventDefault(); startDAS('ArrowLeft'); break;\n case 'ArrowRight': e.preventDefault(); startDAS('ArrowRight'); break;\n case 'ArrowDown': e.preventDefault(); startDAS('ArrowDown'); break;\n case 'ArrowUp': e.preventDefault(); rotateCW(); break;\n case 'KeyX': e.preventDefault(); rotateCW(); break;\n case 'KeyZ': e.preventDefault(); rotateCCW(); break;\n case 'Space': e.preventDefault(); hardDrop(); break;\n case 'KeyC': e.preventDefault(); holdPiece(); break;\n }\n});\n\nwindow.addEventListener('keyup', e => {\n if (['ArrowLeft','ArrowRight','ArrowDown'].includes(e.code)) {\n stopDAS(e.code);\n }\n});\n\n// ═══════════════════════════════════════════════════════════════\n// COLOUR HELPERS\n// ═══════════════════════════════════════════════════════════════\nfunction parseHex(hex) {\n const n = parseInt(hex.replace('#',''), 16);\n return [(n >> 16) & 255, (n >> 8) & 255, n & 255];\n}\nfunction toHex([r, g, b]) {\n return '#' + [r, g, b].map(v => Math.min(255, Math.max(0, v)).toString(16).padStart(2,'0')).join('');\n}\nfunction lighten(hex, amt) { return toHex(parseHex(hex).map(v => v + amt)); }\nfunction darken(hex, amt) { return toHex(parseHex(hex).map(v => v - amt)); }\n\n// ═══════════════════════════════════════════════════════════════\n// INITIAL RENDER\n// ═══════════════════════════════════════════════════════════════\n(function initialDraw() {\n ctx.fillStyle = '#090918';\n ctx.fillRect(0, 0, canvas.width, canvas.height);\n // subtle grid\n ctx.strokeStyle = '#12122a';\n ctx.lineWidth = 0.5;\n for (let c = 1; c < COLS; c++) {\n ctx.beginPath(); ctx.moveTo(c * BLOCK, 0); ctx.lineTo(c * BLOCK, canvas.height); ctx.stroke();\n }\n for (let r = 1; r < ROWS; r++) {\n ctx.beginPath(); ctx.moveTo(0, r * BLOCK); ctx.lineTo(canvas.width, r * BLOCK); ctx.stroke();\n }\n holdCtx.fillStyle = '#0d0d1f'; holdCtx.fillRect(0, 0, holdCvs.width, holdCvs.height);\n nextCtx.fillStyle = '#0d0d1f'; nextCtx.fillRect(0, 0, nextCvs.width, nextCvs.height);\n})();\n</script>\n</body>\n</html>\n","numLines":947,"startLine":1,"totalLines":947}}} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01EWMKR36UUCpREudhxgS23g","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The file looks complete and correct. Let me verify the line-clearing bug - when I splice rows from the board, I need to be careful about the ordering. Since `full` is built by iterating from `ROWS-1` to 0, the indices are in descending order. When I splice the first (highest-index) row, the remaining rows shift down in the array, which means the subsequent indices are now off by 1.\n\nWait, let me think about this more carefully. The `full` array has rows collected from bottom to top (highest row index first). When we splice a row at index `r` and unshift a new empty row at the top, the rows below `r` remain at the same indices, but rows above `r` shift down by 1.\n \nActually, I'm processing from the highest row index down to the lowest, so each splice removes a row and unshift adds one at the top. Since I'm always moving to lower indices next, the shifting from the unshift shouldn't affect the remaining indices I need to process. rows [r1, r2] where r1 > r2 (since we iterate from bottom to top), and we splice(r1) then unshift an empty row at top. This shifts all indices above r1 down by 1, so the row that was at r2 is now at r2 + 1 — meaning when we try to splice(r2) next, we're actually removing the wrong row.\n\nI see the bug now. Since we're iterating through full rows in descending order, I need to either splice them all at once or adjust for the index shifts as we go. When we remove a row and add one at the top, every row above it shifts down, so I should splice from the highest index first and work downward to avoid these index conflicts. still (since we unshifted at index 0, and `r2 < r1`, the unshift moved everything up by 1, so old `r2` is now at `r2 + 1`)\n\nHmm, so after each splice+unshift pair:\n- rows above the spliced row shift up by 1 index (due to unshift)\n- we want to splice the next one at `r2`, but it's now at `r2 + 1`\n\nThis is indeed a bug. The standard fix is to process from lowest to highest (or handle index compensation).\n\nActually, wait. Let me re-examine. `full` is computed bottom-to-top, so `full[0]` is the highest row index, `full[1]` is lower, etc.\n\nAfter splice(full[0]) + unshift:\n- The row that was at `full[0]` is removed\n- An empty row is added at index 0\n- Old `full[1]` row was at index `full[1]` (where `full[1] < full[0]`)\n- After removing index `full[0]` (higher), old `full[1]` stays at `full[1]`\n- After unshifting a new row at index 0, old `full[1]` is now at `full[1] + 1`\n\nSo when I try to splice at `full[1]`, I'm actually hitting the wrong row since the indices have shifted. The simplest approach is to collect all the full rows first, then rebuild the board by filtering out the full ones and adding empty rows back in.\n\nImplementing the bulk removal... I'm tracing through what happens when we remove full rows in descending order to see if there's actually a bug. Starting with board rows 0-19 where rows 18 and 15 are full, when I splice row 18 first and add an empty row at the top, the indices shift and row 15 moves to a different position, which could cause us to remove the wrong row on the next iteration. I see the real issue now—the flash effect is trying to highlight the original row indices (15 and 18), but after the board gets modified with the splice and unshift operations, those indices now contain different pieces, so the visual feedback is misleading. The core gameplay bug is that the splice operation is hitting the wrong row because the indices shift as I modify the array.\n\nLet me rewrite the line clearing logic to properly identify full rows, collect them, remove them from the board, and add empty rows at the top while keeping track of which rows to flash.\n\nWriting the cleaner clearing function...\n\nNow I'm calculating the points earned based on how many lines were cleared and the current combo multiplier, updating the score and level accordingly, then triggering the flash animation for the cleared rows.","signature":"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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":12607,"cache_read_input_tokens":16264,"cache_creation":{"ephemeral_5m_input_tokens":12607,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"80f71dc0-10aa-4f1a-a096-2082299a6fa2"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01EWMKR36UUCpREudhxgS23g","type":"message","role":"assistant","content":[{"type":"text","text":"Let me check for and fix a subtle bug in the line-clearing logic — when splicing multiple rows in a loop, each splice+unshift shifts the remaining indices:"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":12607,"cache_read_input_tokens":16264,"cache_creation":{"ephemeral_5m_input_tokens":12607,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"bf92b2c9-b9ad-4e08-a3fa-04c1eabc1b74"} 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(board[r].every(v => v !== 0)) fullSet.add(r);\n }\n if (fullSet.size === 0) {\n combo = -1;\n return;\n }\n\n const count = fullSet.size;\n const flashRowArr = [...fullSet]; // original indices for flash effect\n\n // Remove all full rows atomically, prepend empty rows at top\n const kept = board.filter((_, r) => !fullSet.has(r));\n const empties = Array.from({ length: count }, () => new Array(COLS).fill(0));\n board.splice(0, ROWS, ...empties, ...kept);\n\n combo++;\n const pts = (LINE_POINTS[count] + (combo > 0 ? 50 * combo : 0)) * level;\n score += pts;\n lines += count;\n level = Math.floor(lines / 10) + 1;\n updateUI();\n\n flashLines(flashRowArr); // purely visual\n}"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":12607,"cache_read_input_tokens":16264,"cache_creation":{"ephemeral_5m_input_tokens":12607,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"51362cea-83a9-4448-b173-97c33c3a433b","uuid":"eea422c0-68c6-403f-bff8-d06f86d2c3fd"} 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_output.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_output.json @@ -0,0 +1 @@ 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a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_stderr.log b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/claude_stderr.log diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/eval_results.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/eval_results.json @@ -0,0 +1,249 @@ +{ + "structural": { + "pass": false, + "checks": [ + { + "name": "entry_point_exists", + "pass": false, + "detail": "no index.html found in workspace root, dist/, or public/" + }, + { + "name": "package_json_exists", + "pass": true, + "detail": "package.json found" + }, + { + "name": "build_succeeds", + "pass": true, + "detail": "no build script defined (static project)" + } + ], + "score": 0.67 + }, + "functional": { + "pass": false, + "error": "playwright eval not yet wired", + "score": 0 + }, + "quality": { + "lint": { + "pass": true, + "errors": 0, + "warnings": 0 + }, + "typecheck": { + "pass": false, + "error": "no tsconfig.json" + }, + "performance": { + "bundle_size_bytes": 0, + "size_under_512kb": true + }, + "score": 0.33 + }, + "code_analysis": { + "files": { + "total": 2, + "code": 0, + "docs": 0, + "unnecessary": 0, + "unnecessary_list": [] + }, + "lines_of_code": 0, + "dependencies": { + "production": 0, + "dev": 3, + "total": 3 + }, + "complexity": "minimal", + "console_logs": 0, + "magic_numbers": { + "count": 0, + "excessive": false + }, + "function_length": { + "count": 0, + "average": 0, + "max": 0, + "long_functions": 0 + }, + "max_nesting_depth": 0, + "global_declarations": 0, + "naming": { + "dominant_style": "unknown", + "consistency_pct": 100.0, + "camel_case": 0, + "snake_case": 0 + }, + "error_handling": { + "try_catch_blocks": 0, + "has_error_handling": false + }, + "comments": { + "comment_lines": 0, + "source_lines": 0, + "ratio_pct": 0.0 + }, + "separation_of_concerns": { + "verdict": "single-file", + "files_with_rendering": 0, + "files_with_logic": 0, + "files_with_both": 0 + }, + "html_validation": { + "valid": false, + "errors": 0 + }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 7, + "tool_calls": { + "total": 1, + "bash": 1, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 0, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 20 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.602 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 20 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/meta.json b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "high", + "prompt_style": "simple", + "language": "unspecified", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": "tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on", + "runs_per_cell": 3, + "timeout_seconds": 1200, + "max_budget_usd": 0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3", + "run_number": 3, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:24:26.132580+00:00", + "wall_time_seconds": 666, + "exit_code": 1, + "completed_at": "2026-04-04T09:35:35.999585+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=en_language=unspecified_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl @@ -0,0 +1,7 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "unspecified", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n"}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-u5h42hq_","session_id":"48aa13fb-e7ca-45a3-b6c4-240f42676d8e","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"b0555a95-43d6-4ed0-86ca-9add86f2ebee","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01SD1rV1EPkCusNZk9LVwVBc","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser. I'll create a complete HTML/CSS/JavaScript implementation with all the standard Tetris mechanics:\n\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z/X for rotation)\n\nLet me build this as a single HTML file with embedded CSS and JavaScript.\n\nKey features to implement:\n- Game board (10x20 grid)\n\n\n- 7 tetromino pieces with colors\n- Movement: left, right, down\n- Rotation (clockwise and counter-clockwise)\n- Wall kicks for rotation\n- Hard drop (space bar)\n- Soft drop (down arrow)\n- Line clearing with scoring\n- Level progression (speed increases)\n- Next piece preview\n- Score/level/lines display\n- Game over detection\n- Ghost piece (shows where piece will land)\n- Pause functionality\n\nWriting the complete Tetris implementation...\n\nBuilding the HTML structure and styling...\n\nNow I'm planning out the core mechanics: the seven tetromino shapes with their respective colors, NES-style scoring where clearing four lines gives 800 points multiplied by the current level, and level progression that increases speed every 10 lines cleared. The controls will use arrow keys for movement and rotation, with space for hard drop and the down arrow for soft drop.\n\nI'm setting up the canvas-based rendering system with the game state variables I'll need to track, then implementing the core game loop with piece movement, collision detection, wall kick rotation, and line clearing logic.\n\nStill writing implementation... Writing the HTML and CSS... Writing the HTML structure... Writing the HTML structure... Defining the tetromino shapes... Defining the rotation states for the remaining Tetris pieces... Setting up the game canvas and next piece preview canvas with their dimensions, then initializing the overlay styling and starting to define the core game state variables like the board and current piece. I'm finishing the random piece selection, then setting up the spawn logic to pick the next piece type, position it in the center of the board, and check if the game should end if that position is already occupied.\n\nNow I need to handle the game loop timing—I'm using a speed table that increases difficulty with each level, similar to classic Tetris, then implementing the main game loop that tracks elapsed time and triggers piece drops at the appropriate intervals.\n\nAdding collision detection and movement logic... Writing game mechanics... Defining wall kick data... Implementing the piece locking logic... Writing the rendering functions... Writing the rendering functions... Still writing the rendering functions... Writing game state functions...\n\nNow I'm setting up keyboard event listeners to handle player input—Enter restarts the game, arrow keys control piece movement and rotation, and the down arrow also increases the score when pressed.\n\nI'm thinking through some edge cases around piece spawning positions to make sure they align with standard Tetris 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":484,"cache_read_input_tokens":4241,"cache_creation":{"ephemeral_5m_input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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_011jYezqLUNJQovzDgDHJ3cq","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser. I'll create a complete HTML/CSS/JavaScript Tetris game with all standard mechanics. Let me build this as a single HTML file with embedded CSS and JavaScript.\n\nKey features to implement:\n1. All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or space for rotation)\n\n\n7. Next piece preview\n8. Level display\n9. Game over screen\n\nI'm designing the board as a standard 10×20 grid with all seven tetrominoes in their classic colors, and I'll implement controls for movement, rotation, and hard drops along with a pause feature. For scoring, I'm using the classic NES Tetris formula where clearing multiple lines gives exponentially higher points multiplied by the current level.\n\nBuilding the complete HTML file with styling and game logic... Defining the tetromino pieces... Finishing up the piece definitions with the J and L pieces, then I'm setting up a rotation function that transposes the matrix and flips it to handle piece rotations. Now I'm planning out the core game state with the board and other variables I'll need.\n\nFor the game loop, I'm using requestAnimationFrame to track time between frames and accumulate a drop counter that triggers piece drops at regular intervals, then redraws the board.\n\nNow I'm working out the drop speed curve based on the level. I'll use the NES Tetris speed progression, which gives a nice difficulty ramp—starting around 800ms at level 1 and accelerating significantly as levels increase, eventually capping at a minimum of 50ms to keep the game playable.\n\nI'll build out the complete game with a dark theme and clean layout. The board will be centered with stats on the left and a next piece preview on the right.\n\nBuilding the HTML structure and styling... Still writing styles... I'm setting up the canvas dimensions and planning out the full game implementation with piece definitions, rotation mechanics, collision detection, line clearing with animations, scoring and level progression, plus quality-of-life features like the ghost piece preview, hard and soft drops, and a start screen.\n\nWriting the game code... Setting up the canvas elements and initializing the game state variables like board, current piece, score, and level, then defining a function to create new tetromino pieces with their shape and color properties.\n\nNow I'm implementing piece generation using a bag system instead of pure randomization, which ensures each tetromino type appears exactly once per cycle before reshuffling, and starting to set up the game initialization.\n\nImplementing rotation logic... Still writing game logic... Writing game logic... Writing the game rendering... Finishing the grid rendering, then iterating through the board to draw any placed cells, and handling the ghost piece preview that shows where the current falling piece would land if dropped immediately. Drawing the current piece onto the canvas by iterating through its shape matrix and rendering each block in the appropriate color, then layering on the game state overlays—start screen, game over, or pause message depending on what's happening.\n\nNow I'm setting up the overlay rendering function that darkens the screen and displays centered text in different sizes and colors, then moving on to draw the next piece preview in its own canvas.\n\nStill writing drawing logic... Writing the game loop and input handling... Setting up key repeat timers for right and down arrow movement...\n\nNow I'm handling the up arrow for rotation and the Z key for counter-clockwise rotation, then setting up the spacebar for what looks like hard drop functionality.\n\nI'm also setting up a keyup listener to clean up the key state and clear any active timers when keys are released. Then I'm initializing the game board and starting the animation loop.\n\nActually, I'm realizing the key repeat logic is getting complicated with all these timers. Let me think about simplifying this with a polling approach instead.\n\nI'll implement a cleaner DAS system where movement keys trigger an initial action, then after a short delay they start repeating at regular intervals. This way I can handle left, right, and down movements more smoothly without so much timer management overhead.\n\nSetting up DAS timers... Still writing game controls...\n\nNow I'm thinking about the visual polish—adding a modern dark theme with blue-to-purple gradients, classic Tetris piece colors but more vibrant, and some nice animations like line clear flashes and score popups. I should also track the high score and keep the implementation clean without over-engineering it.\n\nI'm structuring this with a proper game state machine to handle IDLE, PLAYING, PAUSED, and GAME_OVER states, plus features like a hold piece mechanic and smooth animations. Let me write out the complete self-contained HTML file with all the styling and logic built in.\n\nBuilding the complete game file... Still writing styles... Building the game UI panels... Defining the game constants and tetromino shapes... Setting up the game constants and canvas elements...\n\nNow I'm initializing the game state variables—the board grid, current and next pieces, hold functionality, and score tracking.\n\nSetting up the piece randomization system... Writing game logic... Writing game logic... Writing game logic... I'm setting up the game initialization by resetting the board, clearing the score and level counters, and pulling the saved best score from storage before spawning the first piece.\n\nNow I'm handling the UI updates—displaying the current score, best score, level, and lines cleared to the player, plus saving the best score to local storage if it's beaten.\n\nWriting the rendering code... Finishing the shadow rectangles for the 3D effect on the cells. Now I'm realizing the per-cell glow is overcomplicating things—I'll focus the visual polish on just the active piece instead. Let me step back and write out a complete, streamlined Tetris implementation in a single HTML file with canvas rendering, including hold and next piece previews, smooth movement with delayed auto-shift, lock delay mechanics, and back-to-back bonus scoring.\n\nWriting the complete implementation... I'm settling on simple 2D arrays for each piece shape, spawning them at row 0 for straightforward positioning. The I-piece rotation will need special handling since it transforms between 1×4 and 4×1 dimensions, but for now I'll keep the implementation basic and functional. rotation and it'll work fine.\n\nHere's the issue: if I-piece starts as [[1,1,1,1]], after rotation it becomes [[1],[1],[1],[1]] (4×1). The width changes, so the x position needs to be adjusted. Let me handle this by adjusting x to keep the piece centered.\n\nMy `rotateCW` function transforms a 1×4 matrix into a 4×1 matrix correctly by swapping rows and columns. The wall kick logic should handle any positioning issues that arise from the dimension change.\n\nNow I'm writing out the complete file with a nice visual design—dark blue and purple gradient background, a dark board with subtle grid lines, and colored pieces.\n\nWriting the HTML and CSS... Still writing styles... Building the left panel layout... Setting up the game constants and piece definitions... Setting up the next and hold piece canvases with their own 2D contexts, then initializing the game state object with idle, playing, paused, and gameover states, along with variables to track the current piece, ghost position, and next piece in the queue.\n\nNow I'm defining variables for the held piece, score tracking, and line-clearing animations with a flash effect, plus a lock delay mechanism to prevent pieces from locking too quickly when they touch the bottom. I'm also implementing a 7-bag randomizer system that shuffles through all piece types to ensure fair distribution.\n\nSetting up the bag refill and draw functions... Writing game logic... Still writing rotation logic... Still writing game logic... I'm realizing I need to step back and rewrite this whole thing cleanly from scratch, being careful about variable naming and structure consistency. Let me build out the complete HTML file with all the game logic, focusing on getting the implementation right before worrying about styling. Setting up the Tetris game constants and initializing the board state... Setting up the canvas elements for the next piece preview and hold piece display, then defining a helper function to grab DOM elements and implementing a bag randomizer that shuffles through all available piece types. Still writing game logic... Continuing with the lock function to place the piece on the board and check for completed lines, then either flash them or spawn the next piece.\n\nNow I'm handling the line clear animation—removing full rows, shifting everything down, updating the score and level based on how many lines were cleared, then spawning the next piece.\n\nFor spawning, I'm pulling the next piece into play, generating a new preview piece, and checking if the new piece can actually fit—if not, the game ends.\n\nWhen the game ends, I'm saving the high score to local storage if it's beaten, then initializing a fresh game state with reset counters and retrieving the saved best score.\n\nNow I'm setting up the pause toggle to switch between playing and paused states, calculating the drop speed based on the current level, and updating the UI to display the score, best, level, and lines cleared.\n\nWriting block rendering code... Writing the board rendering... Still writing rendering logic... Writing overlay rendering... Writing the rendering logic... Writing the mini piece renderer... I'm thinking through the canvas dimensions for the next/hold pieces—the I-piece is 1×4 when horizontal and 4×1 when rotated, while other shapes like T, S, and Z are 2×3, and O is 2×2, so I need to account for the maximum dimensions of 2 rows by 4 columns to properly size the mini canvas with padding. for the preview, I'll always show the default orientation, so 1×4 or 2×4 (some have 3 rows).\n\nWait:\n- I: 1 row × 4 cols\n- O: 2 rows × 2 cols\n- T: 2 rows × 3 cols\n- S: 2 rows × 3 cols\n- Z: 2 rows × 3 cols\n- J: 2 rows × 3 cols\n- L: 2 rows × 3 cols\n\nOK so max dimensions are 2 rows × 4 cols. For MINI_SIZE = 24, that gives me a preview canvas of 104 × 58 pixels with some padding. I'll center each piece in that space. Alright, I'm going to stop overthinking and just write the complete file with all the mechanics: CELL_SIZE of 30 for the main 10×20 board, MINI_SIZE of 24 for previews, DAS timing at 150ms delay with 50ms repeat, lock delay of 400ms, and a flash animation on line clears.\n\nWriting the complete Tetris implementation... Now I'm thinking through the remaining mechanics: lock delay gives players a moment to adjust after a piece stops falling, and game over triggers when a new piece can't spawn or blocks reach above the board. Soft and hard drops both award points based on distance, while the hold feature lets players swap pieces once per turn. For scoring, I'm mapping out the point values for line clears at different levels, plus bonuses for soft drops and hard drops.\n\nNow I'm planning the visual design—I want a polished, modern Tetris aesthetic with a dark board, colorful solid pieces with highlights, ghost pieces shown as outlines, and semi-transparent UI panels. I'll use a deep gradient background and glowing text for the title, with a bright flash effect when lines clear. I'm skipping shadow blur effects to keep performance smooth, and I'm setting up the canvas dimensions at 30 pixels per cell for a 10×20 board.\n\nSetting up the HTML structure... I'm skipping the drop line animation since it's too complex, and instead focusing on a simple flash effect for cleared lines—three quick blinks over 300ms alternating between white and the board background, then clearing the lines and spawning the next piece. Now I'm writing out the complete HTML and CSS...\n\nBuilding the layout with styles... Still writing styles... Setting up the game board structure with canvases for the main play area and preview windows, then defining the core constants like board dimensions, cell sizes, and animation timings for the Tetris mechanics.\n\nNow I'm defining the tetromino shapes and their corresponding colors, along with the drop speed progression for each level.\n\nSetting up the canvas elements... Setting up game state variables for tracking drop acceleration, lock delay, and flash effects, then implementing a 7-bag randomizer to cycle through piece types fairly.\n\nNow I'm defining helper functions to create new pieces with their initial position and rotation, plus board utilities to check if pieces fit within bounds and don't collide with existing blocks. Writing game logic... Writing game logic... Writing game logic... Writing the rendering code... Finishing the ghost tile rendering, then moving into the main game loop where I'm handling delta time calculations and the core game physics—checking piece collisions, managing lock delay when pieces hit the floor, and triggering line clears when rows flash. Writing the rendering logic... Writing the rendering pipeline... Still writing the drawing logic...\n\nNow I'm setting up the keyboard input handler to track which keys are being held down and implementing the delayed auto-repeat system for directional controls, with special handling for game state transitions like starting a new game or toggling pause.\n\nHandling arrow key movements and rotations...\n\nNow I'm setting up the key release handler and implementing the delayed auto-repeat system for continuous movement when keys are held down, then attaching the event listeners to the document.\n\nI notice I made an error in the initialization block—I used `localStorage.getContext` when it should be `localStorage.getItem` to retrieve the best score. Let me correct that and make sure the canvas context variable is used consistently throughout, then kick off the animation loop.\n\nNow I'm reviewing the hold piece logic to make sure it properly swaps the current piece with the held piece, and handles the case where nothing was previously held by pulling from the next queue instead. The flash animation logic looks solid—when a row is flashing, we alternate between white and light blue regardless of grid content, and since full rows are guaranteed to have all cells filled, there's no issue there. During the flash animation itself, `cur` is null so the ghost piece and current piece don't draw, which is the right behavior. Now I'm checking the game over condition in `spawnNext()` to see if it properly detects when a new piece can't fit. when it locks, I should trigger game over immediately rather than placing partial cells above the board.\n\nFor casual play, my current approach of placing visible cells and skipping hidden ones works fine, though competitive Tetris would end the game right away. Now I'm realizing the DAS logic for the Shift key is problematic since it's a modifier rather than a regular key.\n\nI'll stick with 'c'/'C' for the hold action since Shift can interfere with other inputs. The `held_keys` check prevents browser autorepeat, but I need to think through how this interacts with continuous key presses like holding ArrowDown.\n\nActually, the DAS system handles the continuous input properly—keys like ArrowUp, 'z', and Space shouldn't repeat, and the `held_keys` check prevents that. Both ShiftLeft and ShiftRight report as 'Shift' in `e.key`, so that works fine.\n\nNow I'm thinking through the visual design, starting with the canvas dimensions.\n\nThe main board is 300×600 pixels at 30px per cell. For the sidebar elements, the next piece preview needs 4×2 cells and the hold piece needs the same, so I'm calculating those dimensions. The sidebar itself is 120px wide, but with padding that leaves only about 96-100px of usable space. I need to adjust the mini canvas size from 24px down to 22px per cell so a 4-cell-wide preview fits comfortably within the available width. I'm settling on a sidebar width of 130px with a module size of 24px, which gives me a canvas of 104×48px with 13px padding on each side. Now I'm setting up the flexible CSS styling... Setting the mini canvas to 104×60 pixels with a sidebar width of 130px gives me enough space with the 12px padding. Since all standard Tetris pieces fit within 2 rows maximum, this height should work well for displaying them. I'm checking whether the controls panel will fit vertically—7 keys at roughly 20px each plus padding comes to about 152px, which leaves plenty of room in the 600px board height. The entire sidebar content totals around 474px, so everything should fit comfortably.\n\nNow I need to handle a few details: showing \"NONE\" when there's no held piece, dimming the hold display when it can't be used, and making sure my key repeat logic is correct. For rotation keys like ArrowUp, holding them down won't trigger repeated rotations since I only start DAS for movement keys—that's the intended behavior.\n\nAs for the hold key itself, I'm going to stick with just 'C' to keep things simple and avoid any potential conflicts with shift key combinations.\n\nNow I'm mapping out the final control scheme: arrow keys for movement and soft drop with DAS, up arrow or X for clockwise rotation, Z for counter-clockwise, space for hard drop, C for hold, P to pause, and Enter to start or restart the game.\n\nBefore I write the complete implementation, I want to handle a few visual polish touches—showing the final score prominently when the game ends and darkening the board during pause. I'm skipping the level-up animation for now to keep scope manageable, though I do want to add a visual indicator showing progress toward the next level.\n\nWriting the complete Tetris implementation... Still writing styles... Building the HTML structure... Setting up the game constants and canvas context...\n\nNow I'm initializing the canvas dimensions for the main board, next piece preview, and hold piece display, then declaring all the game state variables like the grid, current piece, score, and game phase.\n\nSetting up the 7-bag randomizer system... Still writing game logic... Writing game mechanics... Writing game logic... Writing game initialization and UI logic... Writing the rendering functions... Writing the rendering functions... Still writing game loop... Drawing the ghost piece and current piece...\n\nNow I'm handling the game state overlays—showing the start prompt when idle, pause message when paused, and the game over screen with the final score. Then I'm rendering the preview windows for the next piece and the held piece, before requesting the next animation frame to keep the game loop running.\n\nSetting up input handling with delayed auto-repeat (DAS) mechanics so that holding a key triggers an immediate action, then waits before repeating at a faster rate...\n\nNow I'm wiring up the keyboard event listeners to prevent default browser behavior for game controls, track which keys are pressed, and handle special keys like Enter to start the game and P to toggle pause.\n\nSetting up game input handling...\n\nNow I'm initializing the game state by loading the high score from local storage, resetting the score and level counters, and kicking off the main game loop. I'm also thinking through the DAS behavior—the action fires immediately when a key is pressed, then again after the initial delay, then repeats at the faster rate, which is the standard Tetris feel. The soft drop and hard drop functions return booleans but I'm not using those values, which is fine for what I need.\n\nLooking at the rendering pipeline, I'm drawing in the right order: grid, placed blocks with their flash animation, ghost piece, current piece, then overlays on top. The flash timing works out to about five color alternations over 300ms, which should look smooth. I'm realizing there might be an issue with how the current piece is hidden when rows are flashing—I need to make sure the condition properly prevents it from rendering during that state.\n\nThe pause reset logic looks solid too: setting `prevTs = 0` when unpausing ensures the next frame doesn't jump by the pause duration. Now I'm checking the overlay positioning...\n\nCalculating overlay positioning... Verifying the math for centering multiple lines around the midpoint—with 3 lines, the spacing works out so they're evenly distributed vertically. The game over overlay is being called with the right number of arguments. Now I'm checking edge cases, like what happens when a new piece spawns at the top and immediately collides with existing blocks—the collision detection should catch that and end the game.\n\nFor rotation mechanics, the I-piece has enough wall kick offsets to rotate near boundaries, while the O-piece doesn't need kicks since it's rotationally symmetric. The DAS system handles left/right movement independently from hard drop, so they won't conflict with each other.\n\nLooking at the `commitPiece` function, it places the current piece onto the grid, marks any blocks that spawn above the top as a topped condition, clears the current piece, and ends the game if blocks reached the top—otherwise it continues to spawn the next piece.\n\nNow I'm thinking through a potential edge case: what if a piece is committed with some cells at y=0 and others below, and then a new piece spawns at y=0? The `fits` check in `spawnPiece` should catch any overlap and trigger game over. That seems right.\n\nBut there's another concern—during the lock delay, the player can still move or rotate the piece horizontally. If those actions push the piece into already-occupied cells, that would be a problem. Let me trace through `doMove` to verify it's checking collisions properly.\n\nChecking movement validation... I'm verifying the `fits` function handles bounds checking correctly—it allows negative y values for pieces partially off the top, and only checks grid collisions for cells within the visible board. Before writing the final file, I need to make sure `drawMini` handles the case where `nxt` is null on the first call before the game starts.\n\nInitializing `nxt` and `heldType` to null at the top would be cleaner, though the current undefined values work fine since they're falsy in the conditional checks. The hold preview will be dimmed initially since `holdEnabled` is undefined, but that's fine since there's nothing to display anyway.\n\nNow I'm realizing `score` needs proper initialization—declaring `let score;` leaves it undefined, so calling `score.toLocaleString()` would crash. I need to initialize the game state variables properly: `score = 0`, `lines = 0`, `level = 1`, `best = 0`, `phase = 'idle'`, and `prevTs = 0` so they have sensible defaults before `startGame()` runs. I'm handling the Shift key as an alternative for the hold mechanic since it won't conflict with arrow keys—when Shift is pressed with an arrow, they're separate events. Now I'll finalize the complete HTML file with all the logic I've worked through.","signature":"EvaWCApbCAwYAipAvWZpHGJp2auWJ/4jEvO/znLBOvlhnMgw+rZlEWaiG6+B7RH5ZYRMT12WZECKkHV7N0td+c2roE5srrPJXQWApTIRY2xhdWRlLXNvbm5ldC00LTY4ABIM/XDhx1VQdPKue4r7Ggyh3endKvnZHG2OUnoiMPmpk4OdNmAD6bAke4TVU+wADqM5LSpSOEIPJUHz3pu+pxONKQuOY/VPCLWQvTx43CrHlQi1nlnzqK5T/13Kb1Gzz+wttPgDWzy6H3otvrkxVkw/VpykYAgaKhZlEUFRzz1+VFY/nSrC498AQLVU3PJI9lRTg5zZk92V2NtWlpBLi4erJWqjiKAgTMxGDP+4hUfwwVnSIQ+ZglD1SQLBDVwvIE7xUSETdU0Sy0vKgElgLSZcp3kUcJzXy4RF3YD3vDg6tjVHj7ICUnujmYr19DYUa1FO+V8iyIddTqLA3LmYQ95HLGh8pSNAIwFZQa4VCuma919guLLRqze6tjPD13mligr4Vt2agiTwxKfQ+zfUpECWPlpseu4lHzdG8XUYvTGkArcRlAmESJZaqVV78IpUjo782V5AAsSCEY//TL1xFU8SKmDacX/OCWH7ZAYcZCqt6WuF9vXm3fWlKCeaDHDDgDx48xbkjzjKU73u5C7Zy7/pqu/HcUGMfZ3ZBMFgzAPsPSFL5XUM/nFzhFRrDeQVKl7RQOMIS0GRzrrhjF+03yP3H/8eK+jBbJbMsgA/sAVhei2b/afZl0Fmacm4I2JH0AzEOMpYaknrsMBUqrOmKe7h8h1KeVIt9aLIE8FLxxuvFfXxyQB2gatJnJJMg+DsVXfVacF9GfB+0S7xGGAkLmQwZaFFibToFeVWVqlpFsRYoA5gMBjm1qYfPZu3m4wVgNOL5nauDx33D4u6ge3d8Z1XfXq9KbNSFPml/Y/YwRhvwonYO4Yw/2kTMEgebTOkX80rLAlXBusigxGivwgP27v10W/cQDnVLslho1CeBkVw1nWsYwGkngoidcAPJSlSNmpaLjbnYayPJ+TjbuJftytVEO2Sr8R1CMKTg4pOBbaKzjpG0j16KcqQREqxO/viHk6AqTBljx3sGlMmpkj4JqvrBRGA5brRsFa7StObEuU0uJ7Xv2pCHnknqM/El86Oh9/4viJqr9yrzaOdTKASlULaZIR8EH/8qf1+B+iGhw1MUtwJtAzCveqjCEPNNyjIbJRi09J+iPihEZx5KKfc59tSWIv2yyM5mnIJe9DrkSrxOaxx7iCh4IJMgyOgESnNbol3FEcIaQOVuparFk8Zp8rARmzgyON/qxW3Duyi84hgAPxVwMNl0qab/ZSa1xnoCW9LAJdrp3jpdf3qgW9ANaruSb0tLUMgCGLIAe4HweVoFSrn0LFsses/C7GpOX7PU20m73RmiXWtObVjiKYkyvywYywB9kHQWLPO15uIXMFVrU3xzSHFZGHXsTOcnJWdEA1lOjeChAzhfnFzKpOng4ArAFBVP/oVWUJPZjUbxvzl/nVXaehGL0m/gzoO2LDwKxG1rSQ/L5Uglk4eI2mahaAvEE6b4VXoFj3a+AIVa60YPbxxMJ+SPTI/yq+iVCyzAmUyn6Ip9mx5wN8qGrRCI8ou7h1/qGi0WslcRubnwOxHA16CEC+o5kSUE2oH8I4xYLGVOqyS10BRL3YLsrkxJ56rHjiDVnLx8bHCsFM/KIT8DwRyNVB1pGshnTiARLVBjTXspbGwlQGnsz5hJ/1yJuk6JyhWnM22X7tqvU2EdmcDpazYB/6GfHnGhs94FQgndnBbY1STWri9p+ME9YpL7d8/PctngN4w8R1MU12PwDCMPMDrbiSqbVTr7zGd/s5eyK6jmO1ub5UAnbX+hAnmgzQqdqQW7qaRWqAGA1XAfyte46UPeTQ6nCqPMh5Mp9PQVeDU7GUhnwkqP1IXvoQSR+kQG42fhQQY7uoLB3iMLILnSBQw4oXY29tnvOYmXyVqaLgEJjXN9uUeGoWAOLuno2WK8JwcHb+evWY7rBlLFrMqTbhtKUoNmvTmLpqmzzg9aysMxPksYNh02mSXMJMX8Uxwu8OuNysO4X92NxZP6s/F3O9fDfOFA7CbbnGJN4MTcZZghQcQEV9TbepxLddGu/44QEqSFzHzdK0UyerZJOAH/yTTUQnCO8+UvRyrcomw6j2kxf4EqTl0TNmDOVpaEkKmkEL8g7ywa8b5PB37jgK/0TFOXbYBXeMXNuK5cMu2G1RYd5zCCod8tE80I1QBqS+sjNN5dhR+2yuGF1dngmybmBdlyqLzU1GS/Wye+Pr2H5sea5VuFkfeX2925kG8VwI4teMcD1/Ixoh2dTOgqPXjGr3YxY7YwQBJTOLaPQec77YAgrsfU1QFv3EVXd0QOl0GMemkJnaItDjesS78sgi8v/5D4ot9JWlelyUBCiiktVnNQ6kebCOrSnp8/DrjEaKRgPRIO0SIzLROlvykS6nBZB5hkUDojatC5jVZYyipXZP825vKHt/XiClutXwvWK18jg0Hfsf2o44aOdMvG0UWV42aeUvc4TpUBzst3CvgKUXvdFuYPXYSd4SLmhZDAlq3qUw3SIluXnpkoa9cbmTVQcL55YryOLsvgExgcX1LQXkrV2jYak+O5DFSG3lyDayFMEGdfU9CHGXRytLTymNcn3mtI8luodJXSyMpUJpqFJlWoJ1dkHP0gK8Bk4NEwWTTTOeKqJAG7LZjg1qB5nh9BoAvAft2jRYZNjcBEZGBbQABa1LQA607tSU1Jhzfz59HRknQF4y9bYc0zfKjC/Cqr7p2sNhPBgLi8tAFDLHwOI5N4eZKfYvBSmT9RfE1juxuSNd8QWrECnKuo4NAK7QtQFlnMr3ahTjVQVzAydRW4UZcsoUBpznR+Z0dX3G/LME97wWy2RPxYBcEJOrzpq0Z0AA9DFpnTwY7eXwnMk9HOtVusm2Nn0zwtZAM7S+WYS86T6g/z4VjdAh78OmDk/O9DFeKotgOUW3vddWRPiC7AJZFgAeUl/woCSM1Vx5MEgRFlDofXNAzyxn07uswm+EgxBy7SctQSbJ4T8f2qyISvrg3MvaoVQ0uUELDxWQtoyuRxfoS30jipSFQ/3j4xatrDxrFjdv6L9CfpIRpiLBcIkdIL8hYjKzzslmSiUR9jdPaqfQhaLnLhNRFTIWtRzV0iJwEiNPioWcxxvZPLz8B45LG+5vMfMPqEy3j9bYXe2h+PpVDgxc6qMkVMiGDrr+VLa99Pls87PbX215ZrZXfv4KhCWCEr5kizurKJhbe92zl8PoTvhcLI+d4adj9TDy6L4AaZNsZOL6GnoV2u9Yjl6glLP0LIDywBxlyOs56Ds3CX8CXiR23fxRd8WEWOktxmxVQfC0Pv+Lt06l+g+ifhfxAKOjnQnQNwXsObN0tDxEPDbySVMLe/+DfwtiwZPbcPMtbqgvrTRFC0Qr73phGuj90K8qT0CQNZkTuh+fsih+Xqe8gal0Y2HThbtCsMVBmZ3AYfcFxEDZTrTbEV/lYhEve5rTWLGwFr8kla9uPu2yvrqc0ykdvYfCN+db/cX1r0LKGEPYyiglnXX7v5yIB0nL22qHqy46wCl13XYHgCi8SWbGFK5ekntxdcQxNix3B3c6+4u6YcVcVXdBGAhzJ8D27p4Dg00wQP7B9FtubE9ETpkrGGCnuQWZxJvZs9wY6r3pkQCKsaFtbJy/kyn/wRN61m38qIJyxSX+bAqqeFjKrQDfN3Zw/ocMSryQiKSIFXgJISHIQmHT9Gs4FQKOax24Dfp7EsmdeYi2LFZRDywX9RjpBs3s78trbMPkMidG7UDN1UAe3ofF3IsU/r5dtZEIuY7l+pTA2H/x7BCyjgQ+ji2vHaSOpg0ld4k6UcabRPBRL8bJQTAynTyAlLjYgLYajd+n7TkEva5x3jzhCsn76dJ8TGnz2hWZqzFWCYWni4OIc9i6fRhNEUtDGH9XQGtO2gUZaK+9rbuf/AoGyhcEHFbHi5lMl8UVUrOgY199IS37Y87ahkWIp9PoRwsvplg9hSICqPK6UrrkuCUt9VI9tOwAf6sLXjvqvg8MAdQVduOxwi/nQchGU9p2icG0jhC0O/eYVIUCccj1MxTn463BbTjalTc+A97q5TGsBB4NAOb9GcTKyqz5glU28eqFcimYC3XFtKJsXQtEZtrbUUI8SPuvuxeDyr9otFOWaI8A697afuKrGoRZDb6TxzAYrofrbsLBvbBkGsmp28jcSmPiqsIfvIxsBADcQp0rzI6B0qDmKcQceuwgcoDH6aYVsbVe3hGxPb6aS10PMn+TOJwQKxUwAk1A4mk23O/Aq0FeFTfKI9LPt4Mu8gNbMPK5W4hocWLyTBTNP+MzERJvTw5hXOBsN8ju5lGnGc2/CzVtnv29s+I0RNc+FfwoclwY5676s4EdHmcmp4l9SE/oUx3vfdXACQr516Pf7hAlUisM0kS8eJjIKLpkCFxB/neSUHBKXhC03IVcbg1gqBoxGMe8SVfv+BH1n2H/viXTQjxcH9JoS3iOBH+kylBx7Cndi37OgL3UDD/1iB4G7U/Ngwf77jS8FlTA82YhXwzELdFoYmcD+ePyW3csbKQzYA38fOF1F53YlrJmB8yTFnYt8PqLdEkESrA+zP047ttRCWqH3hbu2ga6qMmuu9GFBmu3ISaGrZ+CojXxmkd+M9QakCm409QXy39gJ60B8PoYklMvDfK/CidpL8Tag+yWmHRsJm44GhGo1UsqNvp/YvYJy3dnPz8oQXZ/QoTBVN3p+6gHuzZiEmT18wvWKxXwYCFTICKvGRtChFy7J2aOhr6S+XIYekrKabhUPiZ1IjtqT5rcGm6hw1JjM+tbfqpDAbllOszMOekE7xYRPKPoGcJCsvEFGNHiiYcf7OYL1Rn6S7yYnZ43sYt90G4IrIIXwcPFh8Kc6GXvyYrr625doDtaTo50OQdE8mrAeZkd38UtVyGd6Ur0oP7Dhzm7QkM7gbEeD2apuFChl1E56cyRivOdIs/o2qE/6Se+F7q21xQiYNoxxmiuLZ5F3c/1H7Rh/Y/gFAazEscdFBFAQOzQT8PBfBYkKMSLzSwWXNPACrEWWVReArJPKxb6/JFWNG06ZC/C/PHS2wARotBERnYMmM8fWRPVcidLwFzPmvExr8k+yj7UF0hswZeIWQdd4d2xmVYdqnEF+D21jJV9AIHLWmiC9Ould6AiVAC7toio9pnJZ2FwVsuUUf3sIIabB8F5D5ciXRF4lnwLQldBwExsh/CLRmZ+nbFGk9ldJy63MxRDIVee6LI67D+lKOHp7gPF14vUPOE/VyttZ41q7L3kzXsSlfS1h/EgxD+Sdh+tvwhdeOUSbOutbcN8tp1hKytrZQ+bHR9GZNnlNMcfVAa6ecu5CEV/INezT2jharK/V++m2YFXrD8e421JmouqJnH6eDXkvi3DREDU3zJsSxPEtKBIQRrWYdIw+n1O14P59Yn9CXmFsxzxIcNANVusiiPr2/EOygHy/zyPvnaGZI+xl3ryaRqXVRAfx/n3hoTg5mny8abtjdu0x8vZPpt5GGCGs9iC/R9fEbeGwKvxa3K3Z/FG7sGm3DCLiX/uf+sCLVvuBzO1lVg3xLAUE7bKNMD8NVYXkrSuaA6GfBFAsXDM8ir5swcD/v9fhv8mgDyoLjOfQcfYXAgsyy3+K36lgX5xNvk6WXRWWcRMUPtg0a6ED+xbe6ayQXhfgLGfPZu53HR1ODPIpGfdXzYI6cgcvPOL1+fM/IN5kiDZhdqrv+4O8P+RKsyj1E+0OLeYMDuVBUS5G4BQNHK6GM+Bnns/sj7o9FmoHnr2YLDVfus6Uv5J0ZDcUU7LoC33o/XjVtmeLF5xO/g0Uzt8VcZzJShyLe+FP033k4xuMI4KOYKPckjrX9X6yMs6Fw0fO4zaga9D728O1Y0BFe0jVEpWHOSKxuVDa5Hd3cpw0ROAFJhSu8D1xItnt9ff36damV/2YwS7MNzM4/pZJgu8lkFXKtLFMVwe2Whm9ti9XZvqNZMSZS0hlibQ+jq/9q9nZxqI/ilScSvAlzSqO6LLjwWoe2m9bXgsSfo+B41GEA7++e1jX1gAw0hNHS6aEBPnU3pjL0rMdJb8MGgjK3cMqc7yMrSLZTf1xEO2gTUJEUfvZ1KfEEEGvnx35LrWGSwGf04GOu+wT0qCakzQhK+vR0sQwQRvENc8xPsW3rvV9z3o2/VSTFw87DX1Wo9/eXxCx+ogob+Ik/ne6HHPbef+fVlg//DMXg0xN4NLKD5xUr9ljEjAA0oo6YKeUIwnIaQKvoym/mmU13uzgqTiM7L3g6F8B2Ih5iQwv6ALcxNrvxsGEXsMeXEjjHxg3h9TZIEAKj5xjUkuxj7kqtkbxRgxz/jzacXOHNdnOFEGcpr7dCxqlg+oLMpFLo7IR7QSi2AdneRzQneiUYfRyLcyEE2sZA4b2qZQ4vwu9iMHrNreCY8XkvPrB0on8cUYf1+vdJMqBg1UQisPfJJtEe4Mp3xnUY17HqK39CD2+TVNcJUnptEasib03IamxuQw7V4vgDaEvsdUeLU6Kgk/QIZzaGZzQAeRHP5BeZmX8x480r9oXi+/ASafmU2a5Be0hthbqW/mU0bUI1V/dDG5kCr3Uw8CSulN9BllvPHbXaK5JR9+WUQaZT4salMPjZt9ToLqKebkPk/MLv6vWAmFx19BYgkFQZdAje+1sbnnaqdUm+6NCklCj4D7qAHnIIVGBLtSeZ/HqgrmYX1CThZUHst0RIEm0v8+LEmg+fQfA4Wm2AAYLQlIE3FugXGx5xMic8kKEBhYpBeE8ezIegU2CmHv/qS3BO5pBiYH1RmOIQzqVidZvEcZjrU5OnGgwvVQUVBVOVgvTcKk4ctlHrKw23japxj0j7TIZxxNTThiSVrWy+hZRNyd5fuMHcpekS4qcdTIjTIP8kB2ruVN7zLsjKNH0Gclj3LBou9enweNoH+R0oz1VfQ7mT9KBssKveGqb6SKMYFWrPGWOhJA/Hk86pUrwb51MnSubvwVxe0Cd75Xwl7s1AVgOFd/aww+/69FGTZOfy8eA2ejR/9A7PA/2lQKxbCvg4XArjMlpyrdqvNlj2HajRL/92FzBdprKDtW0yL+PcEiuEGfJt1n6ALV1OAU15x0iJaZw6S6XUEARULOqI++SWF6PBWGvNCnslbfgOP3dFVU4BlcuxAZW6X+mNFKKcauR0gF+Okr1h5Pvrqc4N67rCXnJKKOJFZnB2Pkp7/TMPbKfpiFcff3gY8+btTK1gA4ifAbZJHcaYqtUV8OZtTZvVWax8RGuebNJo3p/jBcnRpV044ci0XqlGqchVMwJzxuKTZlUMbCW2mo73sPW0KkYZsSiMEl1ruJr9MF/dXjri9TTUKy+m3+NvHYTTug6R8Hy62Nhx5MYzCyQu/52pJLur4EWLdPhkHeRKYzo1DbuyIbKSSghyJ/b0TdncOgb6cKv/AgSbu+H0xKodqWJNFztIjhIZREkHor28vuHiScBaUhILKM59BZdkCTfRLYcj6YsS6DkGUknaOSkHOe5TeEEe2hKqdvGpB5Zu1AnqsOmDINg7yUZ3D6+9LZH5wYTGZSGMV9wEtIFP+m7WC3Z0oWm4TmYSNvROUQb0IJeGM1ZNZ0r5PWVGjXc91wCwl3Ld2X858UWIjF9KkRJW6TD12zDawazzs+OXfOd9wI3YQ5wcCPmpMmxhwtlCXr8zAdmmlgEGLEqEYPyhI69lVRDbiQ3cnqfZMzz8xqHfYWqETjHOtOZsFrSSyAonIQk7AH1XbgOL7b9O5K9UYe8NQ5u6c+YwsbpMBxmTPNSAEi0gqK5FjsowPo1nbQv1RjVApwHGgMjkBDhdTIPSHmqriiw07xyqn7aJZSxPdXz+4qgpj1Oh0VbdQiM24q98cxaQj7tiAtoA3A50OmaEcc5qWBaSGHZuPPKGej0khTqy/4+BwIAfVwRrCyNpj5F8pafWQedCcNjB7QaKnVFlluXJNdJmP0art427+i4AAN8nulzgaZi1gd+EUQHvDliASvdsy4QS+YAFS6qO9XcoHZpP50CQoE2pLkdI99/I4ULjxRRgJUFPrHNZa1NoZfP+Wyfm/fXTj0YzeyPz6a+QMOUu77PSQqYH6UwpvOkhuaepKTQ7CRTMNKIsC9NVHikY+gGAWVKYO0470P2JovsgOnOqqEcizPMO4OcVAVz8TW51WZJ90YpbXXGaWkOTGHSl8M7Y6l3aWeprKMHaLSolU17lKjByetGYnYd9ujINLYVgx99pA52visYjMP1sjXNiKhzaOhCqBS/pH/SKyOXHEs/Q2lAuvUMwXxoJ/gImAFiPdo7HEG8pHHtaH/BsleJ8HSxziHBS9Q4VksnA4Ivn8G/8khJFChKMMmTuYXBCuy4DTodCWyJ3NJe8/TYVKpMc2RUcLfNwXGCzYiGr9oa30LHFtBqdzzCyS5mpV0EHWl48AgNhfl9rjfpGWYSevrYh3aa/DKlah2CMUHQrrNcTPP8ARnIWkOueREpntIsO0YVJ0uvZ+VfWUdaizUKsR/3UfG+rmK7uTzjSMj1HfLcu498NU1aIwX/xWIMCe1Q3IqrqWR9zeSEwUruLhhqLEXxIYpsRg13LnJHdDY5kroJfQ6y8njBYQeKXl5ss2E6yOw6s9Gf5b0Il3Kwfeu1bTvgXtsmCr5sxTardJY2tYWuEx9EB/VCKQwNdKcxQITm1k6PgwDTICQRYHXKls/VjC5IGmd6oCJV35yjhJzgd3Jjh7TBIrR/Mz+8c/SJwm4KQD67gBTo2uPHh6b62K+pcxdQu4oLWD/OIeFeubf+gqJ1Yl+xPOk0Qrg5rmcXHfMEV/lGCHFfPahtJjspG3Z3xU9HZzSJXb+BoYjAPcgY5+LBgzegX+xZp3VCzkGUCBqdswxpFSZvz17kWIFBL5PSsx4mqKpRgddQvPsy+N6T8xb+I+a2SAcLp6TRL7WqKYwWBiv/H9KSJNo5Pi4JABOqfIXRPbR/Q7xlu5G0Y/CPtOk2q8EFxSyGo+yxfY6XBqGq4KQoQVDjCjPwiomzDCjUvXRS2eRfTRL84Pa4kUqDhmjQ6dBdczCZDw/BsODYN9rUky1FT0tVCZNru0IOQRYyKVAFAiNkpRQabbNOVnJjLf1P67GLSKhmQ+fW1h4dgZ2uikhdCP4CiGODca0JIr5oGx13H3cE2nnxpDP21vS/20VMhmxl793Bk3fqy/RQhm/WEc8SZA7rg4pDNtDPH/Lz/tBo+MsTmzz+UOlSbiu9AK+B390Qy8FyoLwePaQBsv2+4e9MrBg2HcL6dv2O9IGcGTgoFWQVTlT4nJssollTk2cz6VNUlx5M1h+WZphobqP6qSMEgAf14XkVhM4NRggpgoMj7p/zgfh8lOW+lRqyaw3Psv0f2wGkRDK3aJQa3aHbUr0GXjNCCsIZ9tOi4hzzvUwVdatOe2r+q7kzJJ9PfN2Cv/q2yLBGU7YypgkK787sPIbR+Dma7tHdX2ZReDUQ26xXmgT7rPTE8PVkj8HsQE+9/6E8VCSn9MqJtCMxfNhZwLUhwcTulmP6azN0F3+/qhMmInS0/KIqcwmLVaLW6Z+frc/+Tyiut6qIRnqlNPhtbr7pEGdXRVw53MUZJ9D2gSc0gslg65bqJjuKqFlUxvvl2QbpgKxgnGgZkoQlqkYE7Nd+hBKMaPpn8tNeJ1/3p8qj4uBZNdSGgF8ht0n967KmStobGBwD2kfRLps6FsI1ZQfNQsUsTE8IdYYJ5L58apsYutBjBDSajPpg1NMNV52qPgZiroyR/xxy4P7pMQRalAEkGumuy6Tt87gO2gU8/c7Q7YlRoi3IdcCZm67wOCyreKtH+HRF8DHRHlM+9VMZFbgnEjIGWasEShD0J9vFBoCXILn/nEsPN+5GZql7T6X6NmllcGxMHoJY5jr59vyv9lKzvi2UZxo7SM5hbDkzIQf4sqjPtJHTYfeKLfE3b3Iq3ImTR4b0Kk2wbgyGGTBhQ7P72L9uizsKZxM55iER7FNeDQ9oq8ODWyMcl5iJjsdRzbYhSGDmfnJioEFe6PTAlrmgpqlOCCPq9JDUUA/N8Ly4+Z/XvSyKNgkshPPnheNkZ0jw+rAUTTtIfD3+a7zkez0xTqRXhpF1FeHg0U8k/iVZj6/lynCy/ofukBjvPnRMEHuF0lgRF9eazl4+2vXiewbVWh96lK+7xPyKcbAgrDnOMGEvzsMz0mbInnvKMbIRsttnU4Hji6C7ePYzYJ3H5m3g20HwYJtXf2GJ7PrXF4u3spdtskIC21Dezt3tJwzkbaRoF+N9J1VyJxo/FzqolTt/PnuCKgeIFZZWnVw1esGdjRUjKAxSKbc4cVOfyAy45m1morpitm946ZtKpa/+cDszmau+PVg5vtU8blHcZuytbwuCB2eqBxrQFvE3Un4ghspBI87waIxMJslza0RP3TnoX2xdJnS4pfx6cwohVKHcV1ax+aTIOorIfgISCAaabFnHcP3ap4Mgcqy2MapwFWfWDxrvoWe6G1nlqbJYx9NstfHfpCOQXPL/oq5Ck0+6UDFEto+v+TASvAx1oia28VgLUGD3Dbjb0WxM9ip+176qZtEaE5afkqHxwroNoWdhRN6ISSSGiJ7d9C/Hx9ZGCU2lNLexNYCmDqzeuAew31wv8QjPq/Z9c0u8kujbOb1AROSEYGNGazLWfrupOpyZg68h2utOybJ9NIe9SWKTLzpUR+hkjfTuDrZAlSPTQI3Ca0rTjXYSmn92a66N4bZNKIFfKKTvYEjsHVBR+rSpJXZsK12QL6BsKu5QINIVdDA+p0cxFwr+a2FkPvVcwHysf09N87TvKF1FGUfmB72y1DE3zr3gzlgOr19ReuKSFi+PbnhHtDfUlT4PYojuCxSCxepmzPxLM/7PTCV1S6eVArQVi0pjq9u6VgBeeA19b+/8xTU4mhB7f1d4J/aPEfckX6I1ULFjrIofw2txz2MsADyHYuknM12tqQQaZ7gE/no2aDEWQe/pzqBxIg/jXVoJD9ZU7dghD7zUrq82IyJMbdc0f+FyW4n8E8SJB7jUTm1VZN5nA2Fd4V2yFukcehN1XA7WrJiW7pCmtQWPEntmo9Kb8ukLyNrhOOs/BsoklJ0m4CFoZptkrsP/6hipTPY83Le5AfKcppyb2+/Nx5/ni83p/GwX3SbjOO+vgEXsWrpwOKMj2dcqTDjb8gkN/XPybS3zVV+L6PUyiHN7GFP7gqGOoBrocPepdUHbpn9Frtpg7gicovqRRLiN9uASVBNMwIMAR4wSGfsJTM3VW9NkVjup64n6D8BphrHT0roLvG5YQ0TTn4VRitSjO9UuaE+p3/g3pdJOJBvTIvhTZXgFsuSXoLPBNwtc5mNcVuF6Kwg8CHitbTt1FCb8VNjhuzTKMDIviyg05vqAWdACL52qEQVK8MIfCCcWa7dRDemCNk1DsPxDGbEGE0bSVijNMys242jHvWwSQ2Z5hQVG4g61zvWnm6DhwssCEd+YtUSrtj89HHYZeWG65B6GB/+sxKNjOGUJIBGFE4Qx9QAaIsM3eR0xwmEDJDK6ECPk0m8EDmKrKSz005O0Scl4aT8/y3sdHUN1GX2v+6KuJw72YPLWxQcWeD7EQB1NwVdsnbpknkgdIpNdvaLUacuI7vpwaNMQYK05SA6BWxt0c5CBltT9YUnLHXiOoAbcy81sFoGXt1yiHhFE/cpVL2uFC2oDW4f06YWT5PbcATJ7vkp/Acy0lb2IQ3cqH4T3e7e/Xkij2cZmFxdtGTJ8/Uqrxcqkbvi+1TRHvylGhCPVD1FMEMC51flTFxxnqT4VENuuyk9DODvHHmeNA8B0ncOQNiiJw4Qw6TiP7+6Pzvpwgyz3XbnbZwYdN8szOz8E3y0JBb3mBhbkCmQ4CLdIY4T0GizCNdPZ2jUUjS0eiomrSnu2h97Zzs2KArXNu3WNlTW2AfG2JLgiE9XtwPoMiFNshnFXkjc27QGO9ipoxf6IpyYExVViL6fxvlFbWY8YHXFUZwJFmGOYgcy37rqHnjDYo403uuntYjzIjrLGIB/NGycVoYpV3fEzModspekJJvHtL+xYXeeJ7n/CX52bUdmyikbWDB4s7urTpZvMSE9/BC5GRvklU1TnkKnej6ePGpWlo+ZHzS7lsjLDGFsAyJYYJoXhhDUOcDDvtgmaefl6r6GEvB9Yw7xa1/0ml9ujc78zpwcR9Tf4zcyhQ0twdtXwc3xGVM58B2azKrZ9DjJgb2Q7tQRFapRrRWflUcsJpzHnsLMH/XJX0gVWT8EUCmRww+mXv4EY+kkinlpjQ5Ok0wJ5Tmvy6buyzXWcpR2f12c5dYtgji8QWsMI4OdanHWw34wJdCkKTOZyN9uyB8XxUQKp7HEqYsS3fp9zBJrUKQeqxKjNmLkIlRf7ORrmfS32q+Ll1JPqs8DRaR3iOrb8vbZHLJohOC9/oXtNkQA4L9lXt9QrnD2lWIpIUt8rxOqGEn1tBHPMtkt6EPpq2hRJCX4nSFFs20fyMXKgxQR9TnVzvj7Xv87RqNwL14ONfYmc+N4w1SJg7oMMmYWXgEURTqEQjH9YqxGQhea59G9R8/edwovs33J34LSR0YolFBGLOuPIWHh9a7almSAUFc/zhl9YBJ4KcRl5+SoSFdIHyYAW6xbNvm9f087Oow8l8WldQNVSPDc0+sXELAD73+Yz+0o5WoctCTEKStw5ugqRgVeWZrBkCCYkBfg0HmGHPG/LrxuYQfBT9A7eiT77ltAp3u4sOoZrtk+RLnL3Qmsdbi39VycnONN/E8W+siPKYEQ/rfEOKHMOdBs7Fonpp1nqTYQZRMzOaolR/u8QEHFWTy5TE26Wx25Lr6KmrQRaBFLBJs3PVZs9qkqD0hm13qZoad6rypBwUJvthESlLrTMIkzlnfdursBmCeBgrhkBDhTACSJFMJphWhKTpPFBw7Xig0JBWPRmzW4Ge8c/FylmZULgqraVsM8/PZfAbOkHOKF7+rgkC2VbRbP2ZriI1smhYgiK6Q4k8Tla0pOfSknx1qNZxwuGV8l+uZNCUkSvMLsetk9uN0lZz+1z90Za+5vXOESGJl7jwirKfjjI9Ar5/GjbD95GxsnVlNmcTuNcns8Vi/FVD0jHwQKc45HTd4gA5vGnw63eF93ODHQBEQ+aDEstogHfTMfS4iZhlPeU5wLWtMJ+WhUJ0pJHuF+8BGGWfnGSm7pmGbilw3mVVEjDYHOx2qcUy/DPMxN6YDKOsOjW5R/wP3KAssh169s7pYxttsl48/YCLl2s+lskVR3b3SlyjHHLaERvRNkeLlTHTMx5dKXkMzChTa+DozRVjyu+7VgFn+gdAGNtudJMYUli1i2sANFgRpVUg04pCZeI4tgLglE+dcFX95Wp8fRYJxq8qBngDHKLVLw4ZRAH2Uu3XsTo+jxv1OM3a1zDLC/cSVKpvqlVAGmDc4xqH+zMM1olVaVqXF6RgZuUYh324qsWqeitlJG1rboom3MbsmO3lR9kWlequAwBgSJVENwMQ0oL8YbsmXvugZFbFGgFPI1GxX41nfoiv5h93ERsWMiWRSB+jHrObkFCAOP8dYGc02+NNTNOzCvP8gIgxv9utTLaNS2uiF3PagC9vH4ogpK7znAoBVRFuvxWlwQOYBmP2QHvqr2zRviZqkdpXFLtyDD3BX3hSBD4D8pDXjmKIxy6KRaFeljsnT20syMKeliCLyO3W6Mk2ARcwE5zQT/jYtMZEWipjbmqvmn1mNpNts1HmbgZluR5jS2VBpY+VgKQRVqskqosWul0SoNUDDI6pxkJo2Cs7WebT9+fbfow8HPBCfSNlq9o213UtB+Zg+sPfl9b5MvMgFp6dslxepo0/wLOfC2b94SQDXSNzX/ZxJZaXazF337qZLaz5pIvft3MLhsMdyAdoKmSiadkVCfH0oOdZZJD7zjNIXv5dXgBbqB73zybK0K6+L4AEnfAe9/SE/s9qtetdiQTfEHw+aoeRhJBmKCXOO7FjLiEYOFQTFbKoqGbIS7kpufFwnRS3bIghYzDEoSZ3hif+5DPzLgLoe1my0cLHjMZrNp9AE42c1WWozGnEMBFuxnY175rGudfCK4bJ+N2u1S3eKxnxFM4tk1X4V0E8n598iFQUtvO80gEkxliXNGXCfaEBJ9vLZnRsGbd8Wk9x9W3kMMpSEe1QqmVIGldvUk3717DNPdpqp+3jCeQh5cImqgeUtGIJfMWlbI4eW6FhUrAFeBLBZ06wp7AOCyLFqyfYg8PkFxhqqPTgAcjEE4p64N6uiNUGQ5zKcw69t6k91WgXAmDHuqQaI5/pDFeiGfFYdKbCz0KCPqXwX6oVyTxfP4lnsZuhUm2gl2Zx/j65kyOXhuYL0ZiHAYZK9MIOSWiOQEzl6jZbtHe1kZcZic6BD9hPFWBt9IlCDyfFXIyqyXxDQds+wZgreOV7EPoHnBrWv1NTVyt5Z1S0WvjFTj2S2zq5GoD3Lbyw9Lx9oYXmUtMD8i0D4f+aj83eNdF4Accs5+LXZwlDKeFFp5ye3KtW04S04pwsrUCIJ006mZHw9bNeL8dKS8eN2Gl2jq1fAUSn6DohdMtsd8SKYGbp5HacrH5jiBr23YPCeFXWhu5cZjfU9bUhXj/9wNjpmFMeU3VRH8VEonx+Nyd708KCSnTR3OEJwhCeMBdC0BisUkDdGjtscgn/gPunWcgrUFcZvl6kPhqLdp0d3V3tvpidPqKrNWw9SuxlDmPpx5CPtO0W3/Cjofmh+9RXXVpACTLNzBB1bbKhf87EDFzwmJGxztVM1R+x0s6ayqYbIW+iUeozAEHK5OyEYm8VwDU7RlHmN8nSxZyC3xRZEmg67yEpP1PQEEYQf3B0/cv6QBcODPNyFYdg4tVbql2XLFNgDpOIA5QAj0tmBtq9y8S1Km4gWu5roOftcDHrJjP/cufozJNuQUOD/nUMr/AGPhg0NWmjHhQAAIUANavMb5CgCPmCOb0O+UdP/76sfQYnr1VuRewvV3n1GBNPhro6RKn2nF1mxoE2rZFaNt8t5wX4fpbQJ8oVFqTZh4/cm+BWhrW6yAAJ+0SPAb3B+fNODgXNRPIfebTXjxRTkSqT+wEobZFKSJWkbG5x2NiMHRkhGFJTrbhzW+X3G3eiB6raz1RFXtwboDjuT5at6ohCzXi4eSuRqVL3JRqbYx+G4SfRc0aso7orzKDQSvC9+ru+182t2WDpA08HH5bDN5GbiWCrLSXcRfO3G/YuqlwGx9fHJ5azee2UGb4gkK+xCzRpzVgSqBjNvCp3DDCCwui+Y4YnpxQGHhXs5XedQTiNXe49p8LzhhEWpBJHzvwnYb+FXAy8WmZ17JjGj5afqoehCy66uaXd9SfZdDXAmyBAbnjedOnEcy3Zl+4EW32wqGcKn59A+gBGONLMe7KRc1uWpw1nhz4VW1LAWXtpn5HO1LHCpBPFjd9CuD+oO0cHAO1accBfGqPbAwBNrSVzqgelqlCZFpPFr77/jhygnnR8q1EijnSsY+rTRwYoQnaIx+88HLu4yy04MZIBGTR9WhVbbrktYn+z39zwN/isHSVsATek5y1urFrcH6icEWyMj4zPEm+xxOSt0yr9TjqizLeNUb8kMes/KTSie4kP8PvFHg9nJcj6RIhRzUHHo0zY3yDTkF2/WQoUEDMXFlsaiVyUYOmbBgyy54PRz5TGjpAZP9fvrOVDCjVuhX36ObXJ7gyaLGhu0cTIR1gM2YHbzgSPogsMJih9x2tYv1BM5PXnQcLGjDc3vmsXGEr5Pji2CjWAqsxj//LKQ4BJZSLKulqMNdwJy3SswLVKGW6h1neb3DCLgaKJImPlKHc1I5W0ESDcaa9uKOP5kuoLOH81UbqZplDrYKxp0GJ7ybe8YlKmcAcvnW3CObCWSI3TeixHJiHEQsVETegL8oX8NgSJBpcwB7vstkKp4YPtnK7yAlmLlsswyFuD3VkJeui1boWsGQUwu44euTRpiH3nknu1euQBH65ecF8hULmDv6rHHOmE6NIFPxCkqq03iYEbiMFkXvdrsO4T3xh0tiSQHOHZ+r83pMhusZYMaamKACMeBLdW2Pzz4J1fDa/ms716dr/XVLvxF7zLS/7m23/p4sctlpyRqgn8KvckSj2dFvAldlbp5Bfo0LfCB9FtsmwMbj/rpPOHBzY7SrhUd4Pqt31Km4Zj/9r4pe138SZujB4O7Ykr5gCuy0DzlBSVrWepVCM3cOmmV8SCnlTi8Njt1BUNv0aLCqR0F9GsYfPG+q88ZH1cZ8X6/LozJOrOK3a2jCVMIFua7rLW0T4bK769SvKHQGmj+EuyCen4H3mgM8Eph0NZ1kFo+yYOCUaOmVT4kO+65mngGmN1Fy/y6s4ecdCGENsDwHDCfiTlVfWuWhNzLmecSxr0JBiK44dXULPm4houtUW627lmu/MmiQKt4YPZjRCJU8wrVTYQOxrtQjkFANzlLy1hiYsyI6HESWxKJ3EngI08CZCE6wJ5wKiKFC2lj8EBv/etGm49pzCC9u6xBGbZZxmZytC3rYeRW7cKCbty+h4J4HdJc6vjiFJaAWyRpyMqgG3fC99oSROdwoDt5EZ6tuVFYhkUvpHhR+wcLAEO8wZYMnTrjZmv3T2nV++SC4i7b7T7dV1tSx1vLsXpcoT7eQsHw4UKjkUkwgC4W/E2X1QhKQZulE/J4AcdnATsmVD7ehSE+PA5+wtkcG2QEXhrFJR5mGcKJgp6QYCee50Q69xhfKLHIUXz0DtE3pdbLzmkKanJpgLKVhDL5no5kGXDju9+Y5mBkfnV1gOWgDXcV+dKEdDuImcjedcBLEsJ/8BOJteMrMaZ4x1A+IFP/I6614s8lJ5ygvlDI29fJa7Rz5dqjG9C1PqUK6bGbRpuf1SY3woz9HdM8LAPhLg7kATwL/bWuQqYR6hHK88AaK7tvBELttJUATDs+VuMe75ssWIPpXPQp9Yv6hF44BmDWAGe3FCkm0ktyL4V3+I1qXSNTj/Te2s1avpiB5wGk0Y/917a1IDb5N2CeUJHHitOEGXfmW1BrTQbzFvVhufHWhUIIXucBCnSrkQu4GUMGv9ZEPZc0t7KXHTRnA0wP3th1lP55jxeh7JsSyuQnsLVHLQoA79GxxdIsqSJk1c4KxkSojlfOCgNQdUPybJqY9qdoOh7B/vK1qLZDo0yPLoP6Bw05GbovxSUye0NL0e4BTUxHqvVsHMy4/ZKZNNWt3jRn6IzS1hENzL6RMxTtoD1DtabMUTeJGgPJZCVSGOr7f+1QCTIDQl7fwvVWir6TDtUjHA3+m4VeUP/Yky17gzvUqiSe7/GosCXEx9/RkP9hsaQ5eAAG34huSAO9zq5m0BmOSBKmE+voGS4UBN1xxfCgPIpA8RvEoOBUYDFsmeXgSEp+FzSvrVm+kSTYO4oquLhQvKGXfYJtOB2YxbN7ymGNXMZLDG1uKAzX0yZA+JGgFYgq6rBWIdK2fanqnj9oiUSXbXaa0VBhtuM38mKuuI/CLC9l3vYRQNf4mHbjpyPkNiI7bCgIDeI3SgbExrCO8zafNHUleSXFG6g3EHRB/9rbJ6IqYEF8zLHyQM6dWuOKVJG7COwJzkbuE9qazFXuZCIjSvnbintyag48l3UoIxUY2xLMXyE1/blWY7JOoE1G2MnTD7UjJdJ0mK+UNoKjGiQIS3LOw1LU4PAi5vucpvPmDPoAAXjrE2OKU36RTJ0v7u/IvY96kw7tHrUU8ffOAiD4246wkWEVY06fMJoqrEchQwmGF+R5j1xtJ/Qla52UehQMc08JlkktcEwYzVXHkevRXJyWH7NLLbVfloNsbP5Bc/GaOZwgnK5BAdAGNwxx5N9fzd1qVGLVlO6xrpBQTZEyh5P9uUD1xgBf7ofD3P8C3H7cW/AyMomv/0fNzUezu3rr96p1h8rha7l+SCiMBl01AONm0PUIrWeqnQTArnXbkOuM8xnMUfoYNGBzaxt6FNGH+C1nyFTqRSsODddxvkmHlM1rmJ90W2W03GjTn2PiNkxqWRfTBqi0Ls90vVUNR233H1Iut7eJz1lVN0+45DYT8Qywxemcc91fCNrswE85QNbEVEu0pPC2C/I3DCnELzQAn7axHq7oVjNLc2gHLoJJAn1/agtZqqR7nooszFl9016uigR//mt09lz7mv2g9JBMI+qeR7V+rsjIOND+pXMxWx512Ww0JsYX8tcsYHwAIM10pxrzGlt2LzKGkTK07inZsurTUjfRbEGQ491XbIENK10iNFM+/DmSQk+jraxaKX4Ugcg9xcUr5mEEsYjpL8IR3jC1+Ls/RSZJIH+PuW3O/1Vpa01YXnB7ywn1aajY7yJ48mluhboipeIhK5U/Du6+d2HGf1++na+UHNlyjJX4dEK7uv8sYXfN/uAKGRBPEkKN6BWWocLVgMD8t7JjrdAMxJCdw7VjDEUwUkeEUX9E39lDSFzkuYSJCewROLKoc4JezUAjXtx928mRBQiDwkh6XihpvBKIAqqJBNy6ZtDUWD+mWEH8e+0BsGmUyvzgVItDHew8Fco+SPbSirS6JZVKYIujhZ+Y42jQ4M3+ldHIwXBlM2zTHh8vF3nW7HB1NhH2/jsger5yh3+U7n87XUQWMEIqXZIOMdj4FvfbwUIYYHG/4qdAo17/D0KDZkWH8FLMO4irwUuu4OMf05O3OsnnYzpO0HrMVMLv897NiRyzFbCl0m9ly7klcZ+PvrKYhFF5lQ6PBi5TXFTfcjxoGtLORVHijWvgVayHBAQZM9eg7dbF4IX9nj853HIqxfDqsBJqnKmjzMNmfLb4Vv7+s0Q4B+OTEEzZ+3HGvKaSsyEvy85h6+pJmw7l+/PwR1h6Xj7DoGvPe0ob/VH/8ohQb32JcIzgHVl5H6KH1BJ9nwQ9AJdUkgPLjPPNtZrNanFUhb9CP/YjCQ8WX0OJvUV1NGLFw6nNcVdnfLazB8E01Fd107tIYZ5u5mIzn9GcQ9Z/wHnGUDHsK7V3vBeuGMRDJ7fk+17/piacr74HHPlg5l+8CnKJ+hhn0sE/X4rNWS30EtUVU38WkVt7IjdZ9UvtkxaKqRKTKZKmk4/vKSzx+QGVtl2/EpK3EzEBYTZoeSVrsiXp2Yu+68k+zbrLi/J6VEUFDH9pIfuq1Tl1xAl4+/eHcVcWzlsIboJV54aKhNjXedCaesxSlCS6ImYDrabq6dlGj3MPhe8KZffDYsdqH3J/yQl0hiANQaB6eCrvFUnqV5W1WYHXRFMVPAjNhMbYst85qO6UlgDSehcNMBh3UQVsgQ1Xc6SHmL5VGm9qMrltfAyBGb6dl5MRmkfPCBRgLL7mUCUZQZpJE/fuilPuKNtRkA9tkUS6ragrbfdOGOehPNYIWu/YUKzqLhaGLGfvn8iVQ72Ws+uEoiNpwlKiGnbVPFYwqKZ+yYRZs/dn+3foG72v1P8CN+Q1Zsn2UbJXDAzTb6OmNuDkvUO08bZFBTUQX/4zBwOHLmVZfpUjkn/OyzfbNWC7NmVzO2aTQJJMfs4MOL+/HJbUCUzJeZO2UPmk7Yd/bNbOjCCRQIScDKSt7HyPKnBEHE6gdxU6oCFNyFNyT9niERaSsn23TcaU7GvDLdL+eu767VMViP95kx73CA2seTMPme99+L2Kv7nwudcJJhyt31lv+TqueqkXJ1GPbpJUf3ckrC/45ptqjNDLdPykPMZht6WQYAm7H+VcXl58TU0jYQGBY3TJdL5sxNwsBGB2EfP9tRM/oTAsFd7YjR4xeZRI14xi7K0oUjSzoVbVgkQsVp4Ti7VOK1tvXbGjsKS0yatMjnozGMAxpRHpqp6CRA35DxM+xqI+dDzGZJj48n2VVPA+BSswTR6gLGQlNH0KneykH36HWFeJQke5OnrnKpbgUoZS5fecp5GmUQSKfWSV6umX/qhhYgaaBVnK90/33SfuopSPnuv4ZslF9nrgZu7ZTPQjeSXd4kAeWs09YswOFeXawftv156irkGMmE1HmT3oZohRBZk5hsglX4zplnQxMlPCB6FMOQupx1yudAvs7a3uHLoxtElizBxpMXDoZbx54Vv7MjKh+IqQ4Ibz18NeeWFn9HRvNrWKZjizUFnkvWti6BY3r66GK8Jw4Q630AfNc8fVeJiHWeDzOv2NqZBIxQEMmwMWTSH1eSh+zQPS0D7cf5d2JQymdiP1uqG+Gvg9KCTLqZvh7bQFbQDO4KOwZxwauq69RlWAsDOMwxGrjno79cUclKAy5ZV7O4XFuY53BTQte/PNp+q6C4GzwL3vQQAj0gW40lHZILpK0onoiJpUKJR7K9vjSaRyeLZVocoRcCPC3hGTb14MkYAgwFBWWD7nokuBn2iao4KW3d9XbnBwZovwtT9hGP5MlIDgOYbycuWMctaGnAM33sVPyebDcNaFlc2tpc2Sv9Azj8HMBcAtCPqg/qrBgLDrjyuFlzte9/2rAR1dTawaN3MN2X4SAr1uTU7CqCqC4MHJpsm2tVucAdKhGrf9emvPr9httwclLycOwTBhUNsRUIMU+MNKLFXR76tyuJLf+s8FDWn0KmhlvPQqcwlXqbTaJcoRejT7QN3//wOgqPDfJ3uk+eOgJHkaaf0Atec5rIzZLE47LZem8RdV6Ari6H6ej/0ZIatzl9RCLMHMLsaBm7Rid+NRz/Q9ARnQV0DlF9ylBZxtTSSqGoSds7gnBdRtC2BG6xmqvUGLdolzfzcYMowQ1TLsXmoTTOvCzqN5mdxF9QdXXcOXpK+CZGblyu6XP16+Zy+GxAldq8ovF8C/cCG+KpvWTHFBao7tJ4SBgsrmeguNKzNBcawABcT3qOgQYLoRIdpBZiXnYcdH4FQSO/tYIwyPbfkc+6/DBftUQ1TAYCBRiaDWUCqvt3ZSjTBHM7+5PBwrsZdpo4Or4tJ1hgWsH58fq20q51CR0aQvwegpsfX2xh9g49Nc0stzGhT6XD/9SZ8RjYsYMdYe/JIO5iRqekx0p3WUmY6eaClrzI6iV5J8kREJWiAi3RzLGfZwM1yF2v6bQThaBLXxkShSF+gFFhI78mV068pLXT/C1NuR3pCQCbZl48KVc4TMKJPA7QjrAzVE0rQZ8BYncSyhQAEPxV4m5On6Fyjmyn7WmP4BB/C66yguPcsOtRYBETwdJ9ImYIy0fExTD/YTtRltmrkD98KnH16idMeDCd3pKfb6qlRW9sKGacK1fekQT6b6KbqFHHBiMJ7bM1KQ4QfJ9sRoA4fPsQhUkD/rmnE6cw1uWcJKDOE0PFTfsEnsKoa3IFvwbblBHtd/eiKBAkAxYhkNLlAMEsKYL3FDbP/1yCs42epnevxdEk1RGAdPnEGeulBgEyaZ6zG0HSCm9jEyJF6H2PrTJ7P3Xm0j99EH9iJg3W1wHVsrx0pqgyHO1NBr2xpCbHUCIx/rVYE3ID7IifXEGU4pBMwLfW/ofEWktByJQZkR3pLJtbkK4vT4qBAOxSWMKIE31C5nm5F5s6oSNlT0O1a7TAZuRoHGAGvSNUyzwVt70pY5jwb905hv3MbwTN0PS3i3ReRFSpTCW9DTGPoDfXZZSS8MVDH5t5JaLSlqGDhexpT4Yt+csAcTJbK4ksgyrRw53k630LVVQkm7ZWqaieqop/pS1IFyQ7AkL7T9scmwRxm5Hhf3CdnJnSeMtO6YRejk3dPdV5vJti6Mxi21Avm4SYCQTZBx71Du3nJcwVow5EqvyhfWqL4cKmyxV5EqF1fnvxUtHBpCgBtBPG2znmMJrpREiqRorZflOpeIkCvJx/j0QJoSQB29ifCwrSH0i8gR+68L03x9HzrtLQfCp2H/3eLE8S6cRqWaJIzBI1kDEQzF5J2wP1GGEVUpAt7/Hm2svkVD6LUzALIbIB3IiiuSomWOM7lEkR2DA/oaC1SfTIrN2yb6gX5bJZ1vqqLnqWddC1fVZoHNwVIR0M30MqvlqtzLGuG0c1JVk0Jnnr1F3KiXkEREfjsq1aiMB+DsNmWP/9QAklIJdeZijtbsFou7m0dmBFshw6TZyYI7VeMSRfR/SY+sm3uz7Q+yk6oQ2p9KH7g193F3k24bbIc95GBx3H0xMFqauCqh5y8CWKJW+i5+S1SUTjAgBapLHYwEnNE5pGREd+kW0nwLd87EdYpofuVSG9VQ8wXqKjxGn8ebnTps3vsOM9ahF4LOTWISM4ILg3gqSC8lLGLAYYS6lbxlb8FrI8JmT59SGgn012gRtT/RHaofGpYuFx73nvFZulF+S3lJJ5b3G03Ny1XZ9GTU6nDeIBkuAwfqfimPS+lkqy0pkzxso5HpbnUvffP/MM1FiZ3CgiW7RfrlNIegYpCEiJDKd9nS6XIzlLflgK2Aq+Gi5ZnTdIXsE7QhLv9dEK1v9zGQtG5rfth7bxI38jhqXvp0Cc8A3X6uFAftTPd8hDrZ5DBKWFSKzy8lSDTDnxmsfms5yDSReMSVvVFKe2hjf/UdcGpjvV/6u7tLf11fKoZM7vbPwDRj61qXmuofdBOx3ubucBawsUWC+WuooPfzxSK4bx9mCsOxeYPdfH1luGWDQ2S761tWfjx0E20WpFcQf6rT5WGaOUrqjXPK/TsXSGnAucfZq49xRlG2t10/snDhjtoi+1m6GVfjGLK3NdWMRG/baePl7820gcdOXXNJ5CaQeH8UJOQSMU7DEZTAZ6JPqguedJeJp2qTcb/NK/u3ItsgCYAVMklVXGlzd8zdrAf2jhbNTxFnEzOWVtyxOkO4EJ4YmeiF8bH5jsKzT+aOH4kEYw8LLaLwpN7RzMWfVLZ4uaiWCfDbh+cpoZ9QpmlDu3dAs/QoujgIMkHSfOFHia6X5+lL3TeA7zu0V41qA/i/eTV/Z5dt23WrKcfOqG0YpyqdYWwWg52muRvyS/rc9soxzBGEzgHuzh3LqB1rkOYYGGulLheNwdlVY0cOEWSI0r0HVqK3ZAH1B/LC34tbeEGU3e3sZu6c9F0vbgXgGNyv3IzNKV0NmaTJ9cKnsgCV+vup0tz/2wg5p3hLB9VRM915S++Yac4KOV4OId4gLRbwm/PxLWPJlDHwJi1mFLLZMk6wDBUcVfuU7DG2FV/aqhcgymNeKCoIKkXCQMq/KaC2w7flKfWlsg1huxsKG+JkRJ02I7JA0iGodeRxRRpFNa2eoWRLpFy9ecpkf+qsOLGGzqPfhXKnoY+ytZGCG7210Frrl7JDxjpdroXHdmSeRBCKPE4H3oMYRkPuaOurRjq+vO2WFYkHgGUtQrFLaKjTy/9Nqodixx0niGK92lvnBZ2RNjGW185Uy8X8Fr1W3jK8qfI1GNaznkPRerK8eccj1ijnoL2/fRfO/IO/1VvpuSwvs49Il255dqU2+96sg79dpB/fjOemf2mj8JJnxbxjj+l1mOez7rVpkQaA+AkPuzDob9thgjhpzvmV9tVc/tGMchP05Pg+geuvtmJjj1SFgtKY1YVhR7TTclOC7oLhJy3s6e1N8AtyDEDCmuvLFd/2K1aqkOmwA3QjTWmD8nLQnl556ZJDxX9PvUzKE21Zn1ZBqE0JOnUIc5LIuP1NHiUDrW9YOWBTxihc9Ep84YF0axgpco4AR0kT0bUDqpSi6IHGWtbsidN97GKuEDBNpEPRty5ydVu9ZQsrIWl51gSPUZNTYZGYOsreHCFTh4KeoXX7EqKRmMHExnGdPd2yjyE8Q9Ol2HrnA2ZzTavm8qqftprdPJcBdomocPzvGNXsumyHoWy2oUzb8gj9ie9JcS3b5agZZsOB+X3ChyeFzwiZu4JFc+cskZkhRiG1oBbdva0PApWT5aTdU5kFnX1sSKP4A5z7LRw8FpEqmQZ+r1nWXvJ2J+43BcKLV8MwigIYbK0lPmVvTliVNoB1WoEyaqkwMpNz4MU3B81091m4Wyl69/EhmhoaKqKhiBCpOYNFQ5ue4OpuL06m5xMr4vHZa9Z/zwQgmO9grXnivvyd6johXEo/zGnRuSzevHvR1um1t7lrXCIaVHTGZj0zgv/+uxOemsSgyLRAevZy1gAaSydq0h2SmeRkZT8wSdN+jBgSIahIDH1Wl5tV3ex/lpumB+mku5H7rvGkL3NdeNA9QTxCRLvkxTHYucL+vKCLTM5mAYrIkGKHkbbrmvwcUyFNu5XUSPlAjnh6YKQGAoNeKp/fJm1hzenhZET2WXi4dKQwQXyq50ryavkBFR4vt180zczEHW45XZQdr79q5r7W3SivwIcgJY/rwmqqgq6of090JqGIic1q3+E9RvQJwGZ9Jd1r0/g8mAhMfyFiQWBk2WY6YdKbK8owVEn0vuLknIwnyKpHE4UXqwiZTnEqGYp+lXbSVzNLuXPo+lx6PqOfNEG99TkkvUU6mw0dGuYg3a8F+VjWE9EJgo0O31aK0Nk/meRJk5qe0lUzeRRInL6xord5iausB+ut/PBiWxQILAzATWwh1rcjgKYfkUFAc9oZdibDkZxtThZzoimu4zWsbMTXSeL7o/Xm99kzg/mZHV8QojDDVJ+1WkuHWGZZX92pD3LMTDgdclbamsrr6DYf3UitKnknSD+sQOR5tGczWIgnwDTa4tmHvnIzVcc7RITwOhIXjz+q2Ny5v7vOqSdriOWZTE3xc1cEFWMlrCwmhgGE4XqJIRLkfOm1l61iWM5wu6zLPlxhogJQyUmkPdd5KWCCCuy/IVCJKaV0gOtFJ64PI/Afap7gJnpjMp/B28I6uDODgwfdgiB58P8LZGQiRkWgTEQFLcaP6lG/B5fBVLdbpxXO/ni2DoLjL3THGfV5FtNjmWCJWqa9DbKeuBGantH5ahU+//qxQInvXVDD7QwqJWnSnAnGCL5jBP+lJ0DMWRYv3bcVeTt/guJAC3GSZlZoE81Hp4O6FT3XirITgV3wS5qGzckAMHs/DX3EU00Ar+X/xFsXCHGPtvqcqvO0V67K4gGU1rXyJ26qKBT6Hsz+xS0ez1FMU0YgTfvzvDLQJcFFqWq+36wBZTfKhmxldaH7/GDwXW6H0wiSdrlmXgU+JbLlPohBPnWb2ORL1by+B4xdPC1nXizHYOFdQADhGUPRNP3pEVx/aB9d0K/Svi+bnFLqWhY5p80v8EeoKO+3DoQw0eemVxb/649f1DjEUb/37wtai18eRoFHBymQtRm08L7r41xT4Fs49DIaj9ImFZNVpVPZqUGtLi//GPpP7gR+w8HkcA10IIidwaOpDVLs7aYfra08Wft4qxil3mkVUp+VW2Y2up+GHI4KVIkkg2Ep2nTJdSQkYlxKGgDOgvefFkhQQVRs5G2w3XPskro+i/Lhmanta+lIyF70jfo+bgNvicT74d6IT7rUXpG8iY2uALXBXHCu9baaJJ1aCFuK4pHgwYB01PbzQTce7ZEfMcvRIJTu5sEo38tJKwL+DGR47huRqMsJv+UthQAu4J0Jss0F4UEGOf5HausEmYoMjNLfd38Wji0xPR/eaX50gwIVpqo4jP0bNxT76JpD9jXkSTSayC1HI36wsOBjBa4lpkSPZQPRo36lBFcJr2GNAvPtO5eCD0GPtC7BUZ4gj0lz2y+3C2ggkR+CiiVrVpqi/rfHHAdHZs20uDDtSGVF8baF1DLSeJ9Wale6KnB1em5AxyKUNhGLpWfGHTB1K3c1DCuRn9XiOyGqjGHKrLLD8pYWCGBqzkwQIompR23qXGgZaSOfWrf1B++0pT0xNHacIdlUCK5zCvImla321DUiCQ23fOvv83FM9IzOyl5rQzHhHX02D0BNPEdxr0+7e6pgq3EHMmqXRxOyOcSe8IrOPhaubL8joOeqjYYXUEZaoeK3TaduhC04M04kixUQqhd8nGVS4wb9xVnbZdaNCV+RRw3VUfyEXQSVvhw3hMfCaRaoZ1APOqb+1IQHDGz4CGpBBxc3CxANPBRk5mRbG+7QJLVn5TsN5JskdITf/55IavtyTvO32ZKSKc8NaWC3r89pbVkq5zJyddk5c90PUfgs9ZuHi35jQx6UaUBvoI//chu/BqTp0UwWEPjZj9Pb3azFByIlDCq8gLEap0bZrS6kxQ9gzN6WdvxhHFE7fMOBhT+N8fyh9TfQ8vtoUpBHerOjYqYD5Bi7ntoMoMqdajv0ldUWgcZKrLXJ8+osCGVtZiG5zJ4zNvlRmSGq4kSADkphn+7gx8bKBCrmAPcUGuIqqYzWn76nS7ZWrt5LyZ1DxkJyk7p5TWZ0FZ1yXU9GUvb7KmqBFmUjJwiGXeS/anp7AuvU7eJqj4pQPrkmaSu9BYK3D6SwKvC6njchDMMpOw/Ynb6SV8/D12/btPJbVd4BYTJfbs6DU/F42rf1rGdhzXrVQdRPTD0mecsg5zvVzjmQKswOpEkAfgIPGvOsP7VoSoQMtxuWUyQnLvg48oI/21IQgIcmPH0bt0ZhFJjgZsE3lCkvT7LSMh+HtD6sh+gcjh3iH4cmWJg8E9masHtS95kgWSa8PCI4P62JVoFYTtHpx41UXswLqGk6ErRAkv5D50U11KFrM2dpvBd74KXKK8gDndzJFmZES1YTuEuJvnrJ92SCoX95QQrWQwbTko9qKjYCB8MjUvqj8prFdxWLUT9rno/lOYpLNL0usCnG02rkQjzNgvt9AfUT0WrlZ1BE/lSnnrRLW7trV1Efh71YOqwVDuSIjwtaiL/C1sOKTmnqmnTo6ETA38tFN/9KWxIN4vwZ+7ZjYhdtWlBX3p9wh5bJKEffYmfiC2eLwqJljbmb2BrMm44xhpserin/DrxWh/veC39TOS0FBUnfG7LNP10v78lFakpRjjhpn/4JCObG8WRuB1dB9ouRSG9Nt+2EhMG+AE3zT9uVx449yeSB6YcmB0EOOb6VsaLrK7E4GCm350UbSISQrF9Yk64i98+FKwlMVPJt1SNmyD3RF69Pw5aFdzwREKjqTL9zlCdCQm+NAYrn03S51wH2jBqSsQekfYQFGhtlNuaR09T6xavAgMHZGbcuYWDI8knm0UMTCISunMGRZyS7a0BLWdUCV2/Yuxoxp5/dJTpo2z7od/6JvDDsNYrnyLYm2UQql6es1XDR8g6mcUrgehkgeS6ePSntDUOUsOVE6dy+E5PYjV8x4yRg8m8dEB0rEoLlAMNg99QYMBe3hrykgWVNaYlfdsGJ4q/b3a/cUXXoBeoiC5YnGwW3Y+j/bq7ltE+fvBw5c2znjx6abwGYLJiTFClLqicxHYgwcVBqFTpgl6DeLsVB6xWafEZZf3TCXulJtJ9QF4RZAdPjlbCD+tDdpj4q+FIxQZuj6kIaYW0Ny7BmG53dogeaWM5etoydeGiA29oLRuB42FJZYnFAUxRQvbscJt8HJM/rjuJl4DHPzeq4qARW8G7lPCi1AM/A5wNJLuguKJGo+SJYcEFafhqTo+br4RaILe42bRTWp5AviNs9v2INO0w2JIjwHYqrTyVBy+N4DNOTNKBPFr1ZFLurzvGWF2Ep8+PmipeQ0bF97NKc30sN2tbZIxlj9+4UKmLXsnmAecJVSvsUMdlXQcebjNFV+2vv6MLJ14olES1ukp6OfBRaY4dVP+StVtgAIdEi+pFoaFJgcKoDotewrsxTPX3w9HDziAwIAnWBPpEVL+Ni0NXjuhsd5TqmpMbnNr+Hcti81GWYaKJBVUqeUGy+fIRLIINW3VUcBriAeOGxmsZ7bCFkqo6ZkLyBnJpazQI6ov6mn1kSmNhV64moJVr7TSe4D1BoqQMlEvIo9jKZw35XO6tNR7q1QPq43DZxcNQgJmeaZFh63Elu7OSdzGkbVRhibHNER1Qay3p/ov+BPG4P1rlRoVCU6NRJ2JNAbZ623Z1v3HWopApbBlwK/vgihNzcV8uAwVtqf59i7QUCshCbzybRQO3Cd9NlbFn1K6VM8AvFwgvRm2HcZZJ25dTQ3XLntzCpKcB86UUKgps37bGMAmw5Ctg4fRUOuk6oPeU9y76EnETVTZLcjZKA9Pe9LCCrwbG070yLUeFTFF7Oyl1BAaE9SzizKhdLRPbOmtkOLKLl1EIDnO2gcdv9LkySWQD65zJVg52MFACJ6pm2CZdJUcgM4RkQXz+Qliho77l4iJLpYXBV7w3BdYrqCo1DWPeDTHXknT1kwV9E2+BUFC1ZbP1A57D3FHuWLWF6qlpUG2MowjTtsDdrlt+zBwNm1dJExrLLclrLVbX3TRlmevN4ekDTul4kL54OMSyB58PIPdPgLS78HImpS67tsPBkmHiTjq8iw3W//0P4ygaKLiaRWqGH/NA0rnyR+VrWpv+0CzuUQoLne3FfWA+b8HzEN3E89ZZIzO9DB8Sv5TTBzSZwQwJH3lVuwhwyfxutYIA67TRwjx6RAs7nZSmY2fJ6+0YuHHY2/SulunFCzFpvTfjfvMxgNAP3O8u33b3bVn/Bq+A1eR4nmQAjFVqAiE3K6jQ14WrBeKpNKpSdetOys85DLofVuGNldbGic46uo+/q1xSCUQJsHFVgNd+Dy4V9uPLob6zhMzs7sfREHjBQ/MuGcjwuheiNgXntFsNkP4tXEMsl2dgbGQy//hXf13dxYhUcq2Rd4RooExrurP4HS+NAT/GTp4xs1q0T/usihykIRHLthxDUu5/5Ng/5Z5v7xvJJsrwH6+dF/Vk80DR1iIrL9D/HWD8K9SwD97JZeC5hLlvjufusGARO6IzrfxWfRfSFJw1/UILii9dnuUQTenIJ0MHFuoYeqzOaiFhbzvsO2Ra0rniGw+IHy8jiqNlLH2jVfmEwGcF+wJ5kj7PkqkXuOAhVIpc+uA4lIyyz/2gCzYUueFqDRCgRe2R/vAAnjY8kfXXGFmQe2gSNw1c8O6eP9+u2WTy0ARiUtpMXneR8GsQDyJrs/fa69DGdoUoF2cob9gHVzfuIp0vjMhzyj4LNiZUlSJtfzYpjs7+nRj5PDa0Lls2DYc0v7A2tyLBS0STJaXAbb/yb3ROXI5i4B9MYuhK9kI6ZUvYDH8gDNhUdYaH3cRJj02wNsE4x0VXWCS4KdiOLAWgmYxXD4cYmqO5T1rAE/mCO8abqS32wOG9FB07CLLK5HqMysdvhgGhODCGIEgvLcu01D6oFEuW/qx7y3gCACKmcAxa2MYvzkpcHmmq/HM5EUkPcf9KB824hcybwWBfAaY4dfrYToKe60xVY2t3tLRkfB1G8czLpW8hl9zNabc9HSzonyySKFDKKL39RjQmc5RrR2Pl3woKd0kl8fpwf2JnoaeqXpmd8M5EWJY2Pk1+wfS9byVU5jm8RtOy3FE5ak0f95TpM9ki+9x8OgE9YTDPgRwnVKjTsrGG/+NwdMeHlZ10IAPYnfgILowFOqqm4bsTvQXttCOse0R51WudrIDFIJXZVpQXb3nq08pSPTHYd2+ZZkEFImBBCgyMar/lKqdGVHTkiXw+MsT+4IRPtYD6x+RMbTmz3HnhUckHKlDGlZFV86UMgDHpFk/CL39D4Baf1wsNR1PrIxYCwi6luHdYicXjYYuUhCgAks5+DLuCuCwoxa8EF33D5AK1dJ4fFawxSjzz7oTwgIx5OiU9qgEn+gNoWRoQ5IIWVNdkUNQpoFpfyuIoVDbhwnN7OmnPUHX8xWj2rLwi8BjsPW/oDkkcdQsSXMBbSm2d+TKKJM+FznIBnMSeHWK9f2QBARqkMomvD1RjaOkjeBslc+8zo31wqe/E+wCYU8dAQzhngD1i4v8IRVlM/1QGoEunUrgDWfbMu9dUBAzWzpHH8ZmLJEwzRxL94YWQjG/KwNzKsmMEWZrqzWmsq2LfsmcCAg5Pj0JyOAGIlsAYb6yCEAo40n7euzNEb8vefl9KTfkgBApLQkfIE3sGwAo1mxQMmb4HdyP06QZ04WUt6c0wXKdIj1L083VPOq72OMplBxba4XXb7In11B91KBzWb4bWm+lc4KEVkJ4FvLyqq3JzMlIcuL1vj42uRtvShy9Ww913TshIG8O9J+YzQRYUUFQrlEap/9WaoaJTO/P5L/LE+tvwY4Krr7QdQor1FNkZg06gmrxJemo2DDTWkdVBNwsLka1n51SXYQOgQxzyTOS+XHtBBEx3dqWEKhs5Km8EzgJ4yoSkZGhSqwFOGI7AxKRS26MzBXAwVsjCAivm7zxCwr8JtsxJ6B9NkHDfDeZUp1ODp6TYd4P3xULRgfZtGJUfEWwsRwvK8nqWl/BAguHDK1o9L/A9ds+9LtASKfYU6zzW/xK5SfDDZ/kpRDWxSort6hxtGgn8XYOyESp3C5LRUIiU4tXtBkHsnlzW3d2mpAAwc+aLkx7FHTu1zsqggPzQPiWWMvPikQCmWk52Scrw5fJVnCXZR90sdRe/EocwYFb24N/myCxHckkoF4zOdfDbx0qQ9nNro1OgLVUZL6Iu/f1uTU2/MrQ76A1s5n1kWJzP5MbIh2g8jvhNAqpdsPnj/ip1ss2A/UN5RG44wVuHvkLGGiiH7AisoRXTOMZc+F56i55HlPjoVBZTH+kQp+MOYOjl7ZFz/8y/nMExj6bVLIx5kZdatL+8sxU1TouioYfjNk7XuaHcihu11jXlxF0wO9q79qnQEmdL9y4XGsngXnmsz2MwgqQ2J0YINCll0RHaXAcXwoJcCKMttMVWrynyqQ1zprF8HrJKkWV4myzu7rCJJOOkNb0NMrDuGCTvhVb/LpkMx1BEbnhqG/pdgRBz7qXhvgy9k8Y1+lv3YUgM5U2/V4IcmZcFV99C7uTn895giHkcPVE1y97bqXLHxXQlLUGGsPAsvkd4jh6Tq/A5nINKr/WaCo1bFazlWdJkygzWUdq4O6YTdKiEui7HfHVTuueTyQFO3R3PUuyp6FhFluXc92iPOZpEKaNJIkC67e3ZEFmLfou+znC2SbJ+zOmWH4xzifZd9TxkEIodDHNhpGbJ6CN26V8KCkg/hjqZmDcnT+ayaZBs/qPIE6DaauCV2knlI1tcEOZl61cPcBM99R3UwTo+ZlqdTzws0fYiGlTY39YzIpIWFB4ZHjThGJ+f/UmOtSQmrw/VqpSk/bJJkbDn9RZuAHfh4ROQbR8KxjQ+0w8uURQSNhoNpwTsttI+zVN4ZzbkDwCTTXYL72+PSlFGeJEeOPRL2GDO5++rmNVzSp/tbaRdW156LCzBXK0BhUJe0DJOI1RnY+zXFOK+dVZBhqRgayHxEtgn9oukqxviuPKdHXtqFpa6t4AhW5xTCDmrRtnNe04knlM/9+vT3X04Y5Uh3BIM2v/f1Hu9tLs4hN62UeoXvvt80ACnbbG37jmPUE5jFRmVYEE5IvJtbd+0qHT/a9xlGoWFnjIeTDQEjFPRGRBALqvZTnFQJ2HckpGTJAiPBTL6vBH5VRgwoc7PaQeLdFftVnNiuyzaJtPf8kaKcF5Zhd+RU3HI3sSBAF2ousiqmGcjHmHXlHXXVtMquAEUOX/D24JPm99gS1eK92Bi51tJJXWCZclUMc/+9WfeQwS80Dg7nvOJ75sNeUv3X1/3nSXmd2ycMaWNNhC/aICXOHlZfXZ6BTT01xUMi0OXGf769g7dl/FZVjg3PWIacVTX/IeG/1vECpKskWej7Wd5B6DQ1n9WyHs7OdCv3SfB1JE2W+SfssPLHsCSL1ZNwLOc3DXN3pLyauqbNrvzqSs/NNziy331jKnNrxlNHUEICVfchmEffzgy1jAQySgRkxnzXdrbmQ2uXOWJWMhemidVz3MVxErcySiMXnp95xhe8SlOSTU9RDweLY1Lp74iC0EDL/gkBGlEsRMpgQ2pUsdelcBtItH9QNpO30KvTsKs4IWmC7CSpq7yip673u/816CgUD4mMDBsimUcgv0IIFY0Bi5Ao7ete93iUPIqsE6FbPXAr3bK+Ab/aFN7oNlnBBHfMdQKfQe4d5RoY4IdaNJtSoZNGLFnoETC4BeIFRbBFXzApUtDZlVyRYAXK/SQkhj8OAXyPicCXaeXyRKmv2u/v9hcUyTDU7pSQIgfvEz3KaJDMdAHLu12/yqPgZgrIBBI0HadPQIQ08VqNIGnXO7u+YzWd7ldzJLBNlgelXRSE+LaDZW36p0fIsQVNKyX1AlnNo9l7RBorCY4dx2MWoZW7Nm6qJXKq8eRow3s8+k+v3C+pXHbVhoLUMWM55b9k7zoUBhoeoJHwhCrrULJKLEYC4bi3yl8QtyQF9cTJebAnmlpVYfAhgYeJj5NK8kf9gwHDu8BOBMeRBIqOiYHORqWkH742vhvgLgpmyNzVxPb/JiUVbIVjO0bf0GFXZ05v8jt0hG9qNsawg85CK3e4IAzbepet9luh8mtTPK/8fgoj/K+XqZZ5+a9WpDtmzxeFQzBySpCLFyN/qjycOR6a1am7ZDfkgd69adHPip7dDOOv6sJ+edEkvHW54CUU8a0vZ6PL8r4QtWRamQdgJoZD/xHRSLPkjt0C8u1FUTiWv0IhDfFDcT0rQ2KOWp5G4zQIm7tBJSFYhYPlzr1MRdaS+i/YrDqMw1GFuflYX/V69wZ2tk1o9xlcUMRyo+qCsL5e9iB6Rw33xKbiZjzaViz83V6GU/nZeIvuPQ49XKevUXlpBtdq2ZLMKpOV23mMpGIubD1H8TeE848ogSApLYaB3VNeTynMmU5uMmX4MAA1di7jTw2UjjfmUfMQz7ZXWg4D9AkGsCtB44yQKc/nNEOm83zqlNc36eNHdkk9L7lMhAacGvnLy3f9+RdfNQjzoTATPp31Notb3QqMbbls/3wJdrf6uwK8sM9/uerUC96RcqELZksYdxsVBK+R7h+8DaBaEplWP3MEZIQ9ZV/l5YIJv9nx2CwSfW98R5aV732rkPfMEKwHvoKT3ajMKXO5X4/CjjAhsq2RAjmLy4PuvQk5HK7hlYNVYWjUyKC3+Yo9eskKqT0EhdJhaCgmNnubVWLlfPt3vpe0KjN4O4wwuaNjJagN1yh5fVdmPCSjI1hyrcYPxy7pkbDePMP6/TaKxzbU6Y0U183sNj4RA9j9+Iqe87Vd4+Cg9tvuFj8rCm4gjOsh8rm2pLy6a/at7mqw5U4YeK9CoEI3hkNsyJABPoOOmuN8yOKcCx0sBOZA5YL/CdHM6Gaf7dZIuptg0je0pwqsAwugig652BD3MYRfH7+vVzV4TXc+BC+zwZJybcJmn/mqH+3wimOwkS6kyiRyjUTqsW9Ys3g5mtWoqWM8s8dDj3tN8m/DjE/2PNR08ZSvVJqNK62x61VLqHDRZbIFDT1iPQNAaL2OYWzS0xu81VvhsYoKN/r9Gau/0IimVNph/+3Gz3Ux6mee83sa3KH0RenYHp75QrksNqdy10OcOJHWZ7cIA5QlqWLNJkV3B2UkQmSbaZ2U7t7VVsc7K8Nh0cfORRau2N3pLFvriXsg3DTQylgW8lwFat9GDYIxQtO3jrTCvxT6GCVgQV48Pz5zU8MSBgrbDfgfdfIoQ4zutvvnyah+FQeAbmHtyJ1H4EWqj9Lr0gyHy981l2HLyorHRHBwvyeddt0GFvzoSdC6w6qMgRnrvsZ3KZrg6lYlYxTO8Ist7I+DXa0jYajt4PBYn+uXYEF/wLMFCm2Qsf7+S91arDNBH0kXlFXOGkRJmRyL2/hlv7erIoNamUtXXvmq1Z/9trw3TDxct93dq+9sMA/era/Eh888eQSU0ZGyLSfe5Eae7Jzj2jSs6MovBROs8Jd939e4fHuCcBG/os63DqL80j8+OOvjOeDuIgxrNvsAYHB5lzJEg+At79E+pz3scYNWeuj3ego51CMAASZ4gLxBnuOjBuPM8xVpKUi/+l9qulCm3UYrIIUrCJtORu0f4LkJrYCjxitjCRuPiDCpjx3cCNsxhgizXK68cSjAugNZn05M2B4fiznX+aq/o66QM3JnOD3OSYn++WyOyiE0PvyOOvR4KbZe3rS2BQVEs7hCOzSgx3ELBCcV3BlnUCdyML4ohUQ/O14ENjmn0JDF52mdfhtIm4SiAUES3cAhTqzZBLcovFsqT4nYS2xoOSmdrXiNPD5+zH4xUsp5poNFKOYN3M/og3zmyvArLI4cSwjwUgWTWBL+aOmxBVL2ctD2ftyBrmG7lkhLR02V7pN3WZ0pBEf/50zLyLf9+zwbMxe/g2V76X41ocRykt0pbMKmsBeHhXKn3zWW7rf71HIMQ9w01/OJig/zHT6B1YH3tb2YBgx6ZRHYZwfj/GPtrQBJf1Nl6M6zSJSAmcQ34Jzt8kZyqMI7g9ZP0Ym5yftLUqUqVwV0T2cY0RaG/M0hR7KGzBMv3zFnIPr4gTIyE1O9JqbHyOTQwi50NxfSi8biNB7Xu0l3ORw4bh59dichHv0y50Sj6qPMcbL1+4HhvIeNdR/lpyP/8fMIkbJaOSCt96Vi6EYC19nFpPiaMcb6VbjlAR/M70pcSJsFjwuo43eXk6hgdjNGqNtaP/aIW7/J0GHo1czAPCAQwJ8l1eFPtoHkeSlBaftEU7HhgZ2RiJ9FpEqDR0vMPRrJkRtjEKRFQFCfKRU6zrWHjCXeUvbDcLY+BEM6GgEZRyfHJchZ7Y72O65UnrQyDXASsD0GVlpYZq8o5Orp+SPamqeNnDhFzsiEXBMGO/YPbN5hgl3gACj+sJzSZscpXSIPqbYVsi9VsbVywkxrsbBVKiBHLhgx6fXK0WMtFu9qYLwh7/MzD2AXm6Q5XtaaEYva24xz44IASFrifer3Ive0aMy4RnBAx0zpVQzWCwk6D9keif5n2RxRbY8iU243UX06foeVQNZNNOVv1hBM+4OLV0UfSFCMz1B4sOYcQWBnRw64Y+77dPG6PeU4SP4prHC2431TPdZt0kuwWPAv3I8qomPARUqJ8kaxMi/rPNeyzfojjIfGxiC1gC6bmasm1bMGqrDg4BeeKMtakqP0nHiA8Hr9qp0vT+X9qn+pRPhHfjEJxMOfCx8UzA9Kuu/lXWljVAPmMzxBGQwkppTTAhylPwVQcts3Bg2iqobCL1KhhfZmHNcWpLL/BI8TGkfdvnfFwBmeNIlk/dDfUMAoByY0Ne85o/P3GcG7Ny7HHyWyT22lLekMzghHxmRUckGVg4rlPiI9yRckQMLG8IJIkC9ubCiBv2SUc5y214NzgeEi/NtypYoErJD4XeVPwQsot9KBcT6dboYIxVDPkHQv/qNESb2KTVNrlGSLNe59e31O7p3CLetJK5hRQCBThJofNSh62nd5IhoOcD25QmD2Hyn4qyDqPJmiGG/Xe2Bqo7lMoB/8+54kUc0pYruaQMnUb3vZ3KGxh56kFoagKHU0WD1rmWENwldNfSapNj2ef0HGecSRPIChYnhFXedgj5KmMOJIcy+5/AGbT9CAFiyUSOHC0qnntxEx1sfPXE+MFLalNkHcpgdbvyr4z0hkQaz+lXrahGsTa3LH4l7KN2sWA5F+Dr4NWu/TeE6yd/cmfx7XyovHiykWfXOER5N5lKp4eqogr6o9WV1rVOQsoTNEGW8kzwlmbGSGAWFB3mn+xXKS/jaE3jlUcbtJbtD+2n5Go1QgIarOAkgoU5vHusbZIJVBEbqWQFYDeqFVNPHFkaQPFkdI1SgoD1/L/WAduilEJU6O3WQPFApfU+HyBFS6yf6Q5ALrwML8nEMV6I29ovrMxmkukrWkQD2HxZ/ku+JNqGV0H3/goLI8nzqyR8WffTmTTLspcRQsLNFK13aZACVlfcncBh8oy6Ul/dxkPQjsdjCe26HEN5uXkTH75Q6aMad8iJ6te8guO1t6lL4XIzlQ8cHmFtGgEzae8cyn2WZL377bVj3PkX4DNeh48LfOL+IDDRUppXIaYCShw87oyl16Ciwe7hGEIjkC23LFFCeamJkyC/NtTCTm9Dqgiid4UN/2M7jk2tzAn1zl8NVMcOGhPrnWnT2ep1i8p6/DgeKRP4NExu4H4lca3O3PzecymlTP0Oy0Slp3g81smQyElLwebNDS/8chCTXjgHd9ryCbSzhDIxNWWSU8Paeg1KeHVV7MXmyeGsck/aFB1nkjA+PLE306N9RbOenmaIQu/9aNiOJlM5cJPNWsSV15HvSyslUx0PV61QSTUz6B+v4IbiVzMffB45pK2mz2XTGHDg41SIzDIkn48JELfOF7QiovJMF6ujfYXUT+HChI86nFjGwv4NZOZD33DhywpIkCOuRIOw8raN+4tk85GxdXrTz0W6SnbBeajwxlfAVHYFihCfyhgHqMWZlBGlCywcThnpnd2UL/B7i5ld7bOjPPY/uYW5Fs3yD0yQ6QlM+kvvNhDCE9ufIgwv7FgASsNBlWGXUf3/3ohHpQG36rMWmHIl5NjzbPXyOsz39upI8qb9ksO3mVmHcxzqYGtpRCz0P9IFPdh2y/7qQwRbzszoKqZgQ0lCpCidOWsvL2lgBvdapRsuxkrAQh0KW0euDG6Jd/+cd2xlQj3miUegt1FE9plZz/avpL/Xkupf7Jkz6nlSk3HDOjfvSNlt6/KOZPc1HEkNCdKVTJZrrya+twET7O4nusy9iwwoe8v7YyLk8/21yA2k3J/CR9SKt4xB3jGQ5+LtqMtXkrgw9wCH9Ov349dHksbioAbfJ27d9vAf1VdWp1niBMi/r/a1pIQdrDbmM3WiVLOgHE1jUCXcyKhaJ9vF0IMA3S2rLtpKLqaWFTcSH47jefvmEC2YauV6i/NOX+8x+LLjgrGyYNQLfc5sQ30lICy4WiNiBP+UqE0G/tuEEc9LF2bRVLlW+PRYqHq2d0meUVONszruVsjYKxrkWEA7/2L3duwxGedjEiyBe6tpSKpvhoRAgtoeEzXqeSF6N9c8AI2JyduEGxpNr2JpqtnKADmhQft8SLjk5FDJ03pMTsNrMnwnoE9DvLfs3xDExxNf6theMmakcL8Vh8RRxHwfOdDpisV0LEYnLdjBHrP7pBKmZ2Hfe1y94ZeAKSJfPerZEYYDHzXGVcz/LGIWprxCOynyns0KCo9OGi8z25GMIX2jR82bk33a5MLFKLa4vS6NdliTn+ZUU91EYHkS7iTXjjy3ZPhymTOYqXIpWZWldeBP6huz2QUCx/W1+x3mT0ZHtTjnL6mWXVYTqcfOgNzX+0+5KH2qRvj7xfffkOtIuaNS70KEd/LeEvDMv72OjFDhdxxjsxZkkS7BN/t2kGfOz3BPihgWBBnINAizsfvTf9dISnA70SQhqhecxOe1UOYpprWKoIyxKZ04kYRdh7Meewy74OC3Kmjv5ccVfRkSXcF0ZeZprgPOLVcRNAsCTEw50bKi8KXE8EBuZNQ7BQ2nGA56gfwIoV25dkQUpp8n6KaDfDwWwF1lhtnbDDpXnj/mQOpGkf/zcvc//OzWQ0MEs7BEDdQTHtm1b0EvGHMnRFjgGi23dufP50+g4VL2bUeK1QVzXMCQ3B8FnCWZVRGRohuUi8R/5R0RvoOQBvmdkK15GFq9b32SeEgVExqeTDHLzMxa/hQArm9xTFHev/NSWZ0CgXOM0EwqkBddBx9RmKoA2ohHLs5oUVKuVRfrop2WRSeNPprXBhyS3QRtevDBunPBVv0TONhEt+HTEeSiXUBCu5dC6z7R4cybUVKzDFr+mMgYZ9020AxW/VJ/Nv9XOIXFW1b6cTssL667waHfRlKkjhe9yPNqOaNqoVlzKvnAeBrUintivPk7GJiwX6UsqXkUJlNZXxStejCUrXGBqYXde/yHADgoU/WboiTaGROT1jSUumLtga3l0ShIuGdbEFYqnUrXcWOyQHkId0N0hX79jWg6Wljxz2uIz41N4RcKXJMW+BZmnJ11UNHiXB8jKrMP/uNJqmMrOQ+jA53kDIGRRtpO3tncdFjZvOwJB5YCIJ0iBoS5EDpP2v5BUuj1FNKNkMWImhYV/Zk4Sq/IhcDDUYgk8i9mCGGUJ4lX1lfGgavxNWrXonoBizKImLEBlpqkhCXCmWmrP8ayhCReNr/k15qOeuIE9oqnYweIjPeN3RXLkbpdXTQ84KQ2uKX41u9wkudhU11rPctJCzI7K/wfvmhswT9ldSaXRFH7+ZOIXlymZ2XVhKoTDcD7pm/de43CpgEkUH0sLHHyEJKzUWAdIYjf1OkRuzzOEcCVSkv89mz4bM5KRAo3ozaBFy2grQUHaymUmcfBmt9wFEYeOrIwKgOsOCG31NY5U3bsWg1Ct/31oQVz+nDJ2Csse1yz348lZQUh1tfgHm7CfJz0YhNGOSRvuh7dDxu/SaYH7ad9mVrAXMyy0irqjwh+VTNZrZngTNYvfvEq1Izr/gyaOtDaOFOwzowAL8WkOlOvQZ6h2rd3iioAU+el5XEpGwij3AQytg12C3SvWxZZNrZzWyeb6DyjpoFlLSGk51hrvocMOXQ9PU0hSd6oRXk7flasLAu6h9gH1d7WOFfyIJDkIk2xzAqPrpHUCP6K9yo5yrsmrRRbUlbJa3MSDKi4ASTvDQ3EooW9lNpdilcU1Ay2SVe8tmKsh47ugnHz9hsxEZBw2kp+yTkCTbx67s3RCaqz5O9+bXeoxHCkpjNZdgcKl2kwkOC+EoWQvum4Bia31NcgZ6KEeAPlsfSbOyHopi/u4quaoj3l7/xO4LKzDcxEYcKRtDPEH+jrPuK5jiOXFQNBpGEXpEDP+mxSX0nlFgd/ssP01Ms93oVPfnZa5L1M0IgRgTg2Kxybt7Fq0QV2Z7VhQVa2XGPNCg6VS/k58mmtUC7bcUWIX/jOSEG1R0wxDleljvsW6xPve4y9YrW395Iod9DJX4ELM2hI9IVH55su0IkMx7Z89U/9tEJMB3FFuxDAiw8agFQCQZOz2QpS8PZ/6HQy2WWCMErBwXrzlfDPvrF7EcB1hA7tV31EH8ZML227fueVQQHsiYoELYcCOzOo6BTxycDxPaGhoi96cO+JrZs9PdfLg2E2eMCX1eUt/F6MB3xjDb4FjI4NaXiObw1kgacuIOzPDvOCM+JA30J/c6JVWg/eo1mC32k/d6qJJhfLr+z2dvvwIUvMZLEw9J+C2Pz0KtmSpHKWdgLm0P/8B7N7vXdwqPgVHG5vQydPH2J1iT1+o3ZKy493SFE8I268hqSgwIG0frxd2UGIjeXrA4ct2zmUYNct+HEGbQbfy023UYz6vs/Hl5Z3N5KuWhnfY45ElCumHmehpm1GOlxsQ+6omgMhVuTs+IWLbPWuipLxgn0BY0QkgvyhMdlD+auIjX/PY4OaOXWwSa311pxUfHT8v5T8t1o1zYWIxsZ8JjnNF/6E0/iMZM0sJQ7shWfcqFO/5a7OsHCtEFH6eNtgvGv6AuV3qX0cUxsljn2UreBki70ovYEaaSVtEYqacNDa6qt5+/Dxg7XFGNVmN5Ej6ianyeoD3B4hZFYj4pQPr7fiO6K4EA81dMnJTdbNQH1f4/2/yFw3dd0hl2LbD3Ctst72SsXKEcHjA/twYPAlhqSvuh6mbClUwoHhzwv+baJkvUnzugUwJulYSIDL5Wzd+KZXHYMIU2YVaYcVBxOViijeH2PiI3qpYkQ4V4bmfJ93y/g6m1sdzBhdte6OoraGyLL9L2cg6Uarl3f75hg9Sa5Oty64mXKmbSxivh5UFBhu+Tj9T2+nxkS73DbZ0/KEYCk5+y5C5Z5Tpvn4gibicDhNy/v+sYe4t1WDA+GPdNEnmCPyST1oW/hMNTKgcCi/hpFnmZiADIL+j049kCYy4fhL8VkkItYbs/C+Cb2iocC4ebjJOgkwJKkZ+Fo7Y5roifGKVOEB+/bsAzByKXqsFSZNlfmHDDKlMKb+ObAWOD+kfgUSWy91mn21QzsKFLLBfxpRXyevUJJqdtOs4c9ffVzKuY3PD3A9y+eSYos24vMg/NFCkheDPIuNByKsaLwiZf+hsks/43lDUD+KkvTLyIKuUhKJYs2dhgRpoHEYFEoKiVl3LwQ4u1vKeNIgRZtGVwZfxgZG+4zcCAt6MC3JE5RWv2bKCrdRoQC6GS8T2A6rUuTfqd1aQXn5vvQt/r0OTjwf/mhfmyKwVuApxRvQZITFpbMYFZXn4SJaZ9eaLKIfE5K9zz8l97OWN/t/Hf6ImEQJr7oAKKODe2Im+AL3f2bx1k9qxUnDudcaQsCeyl3c1zw/Su6VO7tp6rnxkDQd7FseGxAciVdYs025rm//JHu8+dHHce7oHtBr0FmjX3/JjOphafwGYGg3b+O3qzqUhXZcMPlJCUz9nKb359RgsU9JsqnaPY/XLmYJ7Qyij5t+szeu5bYUzz5dnzaWeePaiDaC5AlykKMAgnqdiWkFVS9RDKDqukPaCNITxKFIGQm0QmTPo0AJUxx3Ifih8kpkBGMV1Gghb5nkVPFoHHCuQsMuaT7BTw/WbBWY034OTSDajzZhR3DuAppFA0QnSPQ/+bj6/GPkHAjt4AKvcLSc0U3kEv0mFJ+rRCHEt1+32vE+22PFN+4SsZ/NlM8CUy44P9T1xS4/grmmPnU4rAvrnPW7knyBbXGw8mpGElahOH54AXcGanvcGOBgoQ1DJOsEW5RRfWu07qA63DYbOPHWePJ0eNqMwumfQs7ywlmq0WdRsxy7r9YMmGHbxP0teSi2z+GNeIXrhTnDxCSiw68miLtKkMpxjKi6r1TyCtqmYAobcpS9dUGr1rRSYNHFea8X5nb/WoIaqy8mfvKIwGQ70U2cDeNiwabioi6mm1ST2MGzPLcbqBDhmAoSdZwxwp6W7m7IwjokxP6bcGF/g1Mk/WlUfJrB5ulyFBCwUOizy0mxZdSjViIXk85FlvqPnTa8IuaLAXn3iFQ6KJfWfxtVN5zL7JrZLbGl5kNm5pZ3zBW0LKtV9EM3VzKOjtjXlXwGlnm+UnqwOrAYgU8ucmMx4TiCoSVKTnz0ySc1XhXxaNQBuq/BDCAhzRnbq2wUJ3V/aDRUQyZw5MXhLgHpXL/Ty39ui0+bRmokrrwEVOOMTE1ukU896YquiXTHbI2UGpLSZBox2hPts2teNZPfBA900jZ5q6FnuVX9duehSmqJKrHIXGs6pyhCWzWPM/Hs31l+uqLe3qGNSlWmoZ9XlcPWqPb5R/UqBygzxjKR7Lk5GcsQwpmkTFAPZCQnmvKBKiDuxTCY6pR1Z4NJ2WzwDZlBJN98v5BObCWkXxZSFmjoA2a6CuE40+gViExlV+GZ/t8SwC8ulLzwGzgBz7un0zdR/S4P/3903ppXngb1D0MPjyy7jElUYGno8KKRyLKQ/7E0oolnTvRTMsitVssINLb5/U2LgeqExXIVhL6u8s//V8zAxUd0isTce4A2dPXZykGH2sVhXV1m7N5YO777mv+tU6vYBiCUSP9vewiylHzqd+qd+z7wHq4dmQjLT3nvayORjdRdGcJqcpoQNt3RGWN8OpNYt3FHJayE7rtkS7kxJgC8oykcpIQlZB/w/ASejkni7jPMEexe5rE4nhJrpKkfixsvBEAQ5UcqV9m0gD2MwLEURu+2WNhi7dunloZA38Ul/I6oGZjb3OguyygqTR24koHHIP5D5Ta06MjnCcJwg9p5BmOH5K0zljQqbXz7FPZ7T53L8XGzt1Il5OXT3LqpACB0gO8t+9/ZGRsAh4KswGIUA8j2qtImsTx0VVO6piO/oKVNf8rR94uBBvocl7ePMLiTHM0PxjVM+SsVZaODiIehrZRdSYHxvS+85whFMqeDPM8/q4acQ+TLNOAofKyc95ycQYL1tyIs7LhLHnAkCiC6tqAnCqy4ajWc41HBeaBO/oryWPfDochvOX7ISbBpTcgQBw+M+QYYsn8frMZ0/Y6IO7JHCVOlsPSMvQantwZb7bmddsCTyH5oXi8faaFVGOP1JurwOjcWJPFUMX3dbK4MrVqxzyOY+akdufyv5tDzFDkCK1ViJbKdj5EQtwkCqEuWmRXsSWy375xpen5q6xIPv12ODFQSCLfg7sN13OvmFO8pdfKGtrkcHyEPS9cL7beVrazhKUxj/b/lNnskQuV+ihf0DrhrnL7hmX4vY2ClBhF/X+S9hdlO1fPHHB/uUKIevWRcQ4HShkSefHKLHGsc5zfhFFWEk6w2J+nJaLZrsXNDWrPisURrrzI2s9L14e1F59V9+IE/kevEeabuu+g/8ekjm5AH+fAtKPC5KRj3wYZ3uy7Wcq7Pt5CIxFtj1goYaLWbEOAqAgKom8sEUt+rt0EoF1/VrPc06v+2UdguBucXOVJnIoHDup4fr177jTyxxTTgC7xDYXuBFMOgPbvF3miz3KRm3aa57ju1U6dxoX2FqS/j3DO8kRX/ZWB+tMyBBICVfUa0jt2S2KQaITfIL3G1iUi1MwBiMd3dHAjDTdoovErGlmvVPUX5sIGQ4+TWtQ3P/lNPOMqKYt19auHK135P7qdRSU2/Oq0Ii1Warg8Jw0NxqIl9CIBu/d6YcO8Q5xWj6RW/m7iIqNtWd5Waf8pIz8oO6mXsEQifNatdeiQsMF1UFBPAK66hMQ6V1sfVQcKKgmL8StifB0baeppMegdc9JMUkx+sqfj1a7lYNOdVHX0n3srBk5jaqsRj93RPfV7/8UGt+PWKFqSit5irB67HPfstwN1moPh/+N9xeeTyhne7xxAohiF+pa/TzdEX0+pvvohDVJ3lLeO2IVvfFI+3jRqmmjW8emOdC/szTmuEE+fDhwJ6BeH2CjlgozEKvDj2+f1de+ZWInnoq1aGbEjS8AmoPPFBBwgEWAVDIrkvYmKL1cchyQEPn6kCxJ/COHj5PzimTHnWf/PUJ8lmSD/GnKX4wd6h02Fpw2pRYEOmTAQp6lKanNIe015as/vWBj2wAfWg5Em+g9vaM48KkZqUUQOKxRTVxOBONScHu8pE8a65pM5et5Ppvaw+ytU58uJXZOuan6q0FR5IRCZbfGF1RZPZo7ZgvBsB9WVa5vzakMvMmp/RJqBFvboI7U50AqkrStOz+z14F4d6S9GlGI8SqBC+POXOQqPa65znI58ImHnvU7Hehqo+C8uGstnGXVoOZV3WyjmA84chUihszPU36URoeNZ25djOspbZnNdbs9DrVo7jLsbPTDlq7SEaDFGwD/dMUOr1w3oaRaeX7I7rO8KElisLBL+68n692MtJctuwyi7NbF//ofM5HI/RsuD8D1D5pcCkSnxtc5ZzuHfUMjyZlkcWSk3SUbce4gDA07CTkAHeVw29SswCaWlxB7Q4BcG/jHOWenn5/cR3j0q1UC9FB0/nt6sB7iYxk6mhfRfGdhpRhmjXgkRsVDNJzuF8rK+nzfUYd+qgUG+nHj91ntiXUW/YJE7aO9CJJ17orsidOs4fJmBzuzlsfDMJ7htNUrpsRfMsrwiBieCFHoAlNxg2nQPsdR/ETHp2Hnyca9fOkcIiTqNU4aGarhoYHHmQkOpvVfbdRFH3RvfnfnJ6omNEAJHFAwr6IibglIZirfk2stHFtAzSdCXZLcQJDiFlvnzyg/34B5pFjdVoCYRnB+OE6for41oAFpbCrljQCD5JS1hX597wHb8PMIu8CxozGCtEtb+Dsr6KNHr4Ahzt5DKyoPyEKHP29c+VI0nm9e4Q7RgwYBlC4LIbCumL0w1etYWRVvjniIw63Enfm4UclUktJf5Rdyo4OU9Sse0h2sLJ+rB5RQn71Q04JygLcl0TLtVUewpEgK2qwsV/Lu7EebM5ZJ9skDBE7jFpNiJ9htkuBM5rvqihcQNpZHcMhi+lQHqMWx6dhxdFRbsiVm5q+GRI8VtRGFyEUoTSsXagf+/iFcV2bwfcaamU9WsaGi0TUla3cwFILdc93myty7fdN+fi3DG45JwlXBn3yiAwg4Bbl48pp2YeoVBIGb4d+R7lvA59KjkWyNVcHsJUZgYUB/HSKi3dhk43+0+rTnWM05OmqzFzZtxLqWvJEvLfl6xTuNltHp/QToZw100fzwMYflPtgS4KSvaHn1AU55jCFw2CU+3jNqa/MODxsLq7FKnQ/FZieyzpMu/TNpP1BUctUDtUoiN3zJv8itb/OWVC3j239jTeWEMlbQa95XniG8YpT/p63cOiyAdEjNd1hKNg89eP6owq+hL3NoUspsLpmB8XauIbe10RTXw/1YDGfVCekfJm2C905m3B1rnj8FgHytvZlvYD5oOlIai9aX4dC1zn81Dq79LexDIzwID3l9DSDnF33HePaD7QP5FXpqTCzgFoE93RKoHtTN5Sp1a4Ljls/ucwMB4VLykZtl0PuibdPJfaKd7UskGIdyQjf8t23JFpBpt3UcPE+FmMRzja8mTz9svgrcVfFuYHUlN516NtDtkuwxzuf7ydKBtq6swI+OwOqpcu0D/HJSjvjivwtqI+tnGmQaTzCWpQwps5fY6hzokcegoUuDswtpSviJO+RbZU7cjz8I896e5uEKRfYBgNN1pR7QVWQv9w+j/5tEz3DMehbhkfRBTqNRzSGMBPNzP3qSuerJOuP9VDOYHGxpWT2+TEUgDtISDRoA36hbZ87L88T6VEwcwDpHf0plCk4XkT8sVTfvNEXD2Ui/x4Mkr+3ayzzPMLagD7Fxc1mHXa5j7gx3iwsHXGlU8pfKRoDwWbRHfDsDIfuLww3DoZ5ps9NjuBx+TR2Gwj7FIIWZL3nRFKvg2JR8J6KMyXg6fScjAVVW1dJJZ+ImMcq/twOFtj/t/y8RDMItgzAi8ZP3+Vl0Mr2ee4OsVinVf18fBvlZM9g+06n6mK0ft4DJh0PSQB/duL3Q05CAsBTRa4FDiz61ZPxE+Cpibq0e0kIWYay9TOtIJApaRhZzCxiwWTSn0Y9zVWuO93h0Z+Mw+vya+YMyeGfwyOiw6LChA8kb2DPw0HD2pCBtAVh+QwD2yWWCSPWhwsJ48erISfQkQ4x9pn7WiyLjwvdLy93rmqRSxRg5NMRyaUi/TBzMNQjDWtRcF7u9qaQiMON+qh5yCxtgvOLSF4oRBtBbDvSSfAxyrvuhhRszklsi1SEP3bxMMNSlv+4yvytjAogA1LcDGaDBE6oIg6FbtmjNXwtci7UY66F3C/GojpgDUWECAjRRRugiW80pq1IrT2oy7RiF5i95x9AfKmp/GzVKsfydKjAqSSs/nsIFfBi+e2NiQS/FjEwjE03AaaDqLxhMOgOI5M3KZIJgB8DNkTQfvgDBxf7yROKEYFnS2PBOcXkDdf7pFCJKO0pR/ZRnnro5NTLQoMUsG4hs/IvNYIaeGhvDc4QyyYzyFLfiY98erBeQByWGCAdLWqy7S2C3CtCPWDL+ZziSD5+6IJwfsjl3t8N9cBCFK9H1hxyl9iVNK9azc39u01GCnOXCMMvutiWBRcJjThs0WpsFlSDGSjHj7LjxmGIc/1//EuCO5Xi2OCtTAKbrsyYT+q5C7Yf1eZ8v5iM9ttQ4qJOiY1ZnLbLge7/zcbp8Vwl3TO0dAmcAuxoHtoyl6Vr9jxZK6ZeFGI4bQ59/k3HQzp0k4YkicmSmZrJ0YMBCtSfp4dHItm3KeMisGe+RlSCwgEKGre6HVsjsMQ99RAdJEVHQ3dol3LJRJmu1G5oeulyfaZqbDple+aR/XUcHRG14oEWRZcetf3KaXaATy7Qrs4D0f0jpQHmdHdMGca1llMg1p2c3qL/7Xn4X8QcZ41xJ+4RE/F0JUVGlmXfAIhHTdiLjP7/0zeenyBAf2II7zC8DeJW9fYni3J1t8AdGSV+0ZNNwHJ+VP2Q158hbh7gyujXeyjddAUiI3dHV6h1r8YOLNhrpIdFInvgOjKPwq3UDSl8ra521L/eXdlwu7wRCdp14+17XDE2cEzfa4xxJ6SsyCwbQ2mJPF5eLs06lzamNO3/c9xKmW2ay4XOr7c3nQIIeU3pDwqg486YX7+pAN5wiZN3vEPBzcNBSfgrvPT4dFlGHWpYiePgvEmXSUCvDXcWcNtQJcN1rTZ1dkhxzvIT1d8ps+Tz3mNPCia3wtmDkaVTrSgn7OnjPataxTmzIyexc4xSYof7FZd2XgISmGtFkDs8F4ShqoTtaJqbtrva5o4tUIrwbRCIiDy9XKXvuCKo5Hro5bWZchoOm89bzXM6YRLM2NiQs+fyoozqywFnGyB12Waqr5ucV85iMJqNAd4m/AieQPdI3gaeMe1sDHdJubaegZwrLTg0Y8jIliH4j+i3zxRr2Z1JHvX8BIWU7C/1iHDlcVomBclEigS8jLnZkkEwa9hOLsdQtJe9Cme77CjZA1I1glnGmpYkQy6lolImpN4hA0F6+Vuvv4ATAyBN0kFn4kTCIvfEQx8WkH6pXcS041AyfDpJ5fTvUWX2rY43vZqVXPeHnduSBCkeX3Y/l8dFFOExL/p/hmMrb7QZKcYLrUeLMv2CMTE8StloXzd33KCRT74r31FcnRm7Fx0IfrAutV+uTzxxNeky27UahvU2QU4Eh6J41eEKN/65lUpXhhDsfIenPztArSotyazGJDwxO1/P7uSYXkQvKMr9+DfWjdoihhhaJNU5yWQjuyQkFf1R+YDG5rA9JL3fvP3cQr7URIlOJUZGMZq6wdiShscdpDllDXGktdS+MAxnAFkYyXN9F4CtQrRN+4fdheY6FiDhQVIul1b7Qkh1hwdOeLVxfIlj/BpknretAXDrG1Nyj6fbr6kD2/2OBc/spFycLYUhuOPAQ3tHmWJL2mHKhMeh8BaHIPFWYBo8v+a6KC6zJBP1gNMfobMirBejfuGT/9yF0wFc3MGaFQ9JKcAtAUUmzePKN/rYzzrBmg5tTgkYAGzRHpR6/UmC2KjvjzaAxKQNzqmFkkGVRZa/orRbeioX8vvT90gn9pYS+2WpI4lzaoAnRucmAzORjTfhx89NRrEIgaW9D/RYP3emRAQ50GAnJkSfiS1RTjykWIocpYWKkYyuJOeha58XAdLJ0rZjIwz69cjX8eCSdLFsGF1ICaXwCrDn6JNyfb44oAUNE2WmMxQSJq7CJ+UuDxmmZvMAUleP0TdP8q2IDcohIPdGLeweNwY7HwGvjvNaOLl0kDZQawKaDsOkIpHJ7kKxBBLFwe9x7lR0btlWXwJXt1LOiln/JiRUD2reBEl87VLD8tyiKbBaICPzNWDLvpufiOoZ5HhqQGh9hV6Rf5E9eWtfhGsZ42+AEN47K2OLgxlHTjHXFbQgfxwgYt8Xxwbs9qJzFn2+E71ypyteh5k7ue5xebhU7vVlfS2SYlbvo9EwJkw52e8onR6mF2MaLyOK3pzSu2FULgRRYaWYrWcqouxstqTB6vC14iSf0bohrwWg9bmE2MvXrjJp2Xoq6ZWbbLLjaiqL3P0oVSSau+403b4R5dneEIrFKwm3enx3KRlYn20CHiEBJ2M5HUEzYW8+k8ZajSubCGQX5ZKICTwpZObiR5ubeWU5nEhOO1bWKvNM1PT4ECWiiNVf5aa2WSpExvbuKhZ9heKjvPql/Fkk3oU947A+U1q1X2yD6e2PSWIKqXY1Dud5qOpCk2OijKBM4AfEahKKwzamOwe+oXnb4Mu+TEvYY34ua/dkbHV8Ew/6qaqh2/XmyukO9hijCBtJCD4u0ZToPMBFao6Y164dL0jZFl1DVXzBUHwJsgNCeDSv/xUqt7xrAnP7A4814zrDmTqKMS9T0gqNgNvJCDQy8gIKUEluRl2GpSNowsbFt40Gr6fFhdbVzz8/wBYSuEcUsiH418tl/BjBYM1gA/SwwYzsCy0RCwuVk2AqEMjPCwXLvBpVKr1q2UuGzCxz/f3HBnvZktsqUTFqqYV6Nfw7QyTPqILdA1fXCCrByrDOwKGPl6W2s3lt+hetBmIpQPJfqzw1480hecehELa6bItXwimzuWNU+JgB5/G+W3f5S9/m0T6GqeuWyGCCpdrJgEnm8K0wF669wWWgOAYuk8kh8vdnLFtackyscrpxTGJYSVX2vkTN14oqM0diQWl93+ZbBNQhwMlLSWXoTf9W9CoxDqUv013F2z0Hur9q0YF6ejUdZO6mxlh/R0FCSf+5pT5TpbCAnvKH6dNOlHyOs/rI+eiLID19rfcg3HZqw64DSMOXYP1OHKfROwlWuBjLM7VABf2/hkFKnIi+PTJD29pAGtb3rB80zK+7O3t0zBZYtGc0i3mBVnn3UANkAdgp57S6iVg8zwiRJbaBvDXf2EW93J2LFMlEpPkfwrTuFOOj/WV4h95QT+a0wSAmz5kX/FQIKsklf8r8OcQkeIVpLArk5FNsFaijX1vxLrksjws/eN6HURAJp7YHr8VKxlFB728FbgIbDSg69535ZImFyrtG98RRiXwPJGG6g7+FU4gXmzyKM94FF8lJitWxEyoYEC6hXxpD/naf/isr7BL6iXQH6aX7BjNLbPaOH/tfGHKxnKbSkmb2WqvRlo0/tiqV3iM+8ILCfiB4lGhrRoIpPzbcaoAd6odyX5Qg1IssgrpE+sAgiAMB9ogEMM5Q8WVXl62PIMKwVEjyyaXyw1V5MsD3A1L80YLawwC2rYkNZk6scDdYMSg0SWrx+9JK5uQqUaF3S0KIdP9bWdR1L0A2FW/d6X5vbPEXfzT5Hyq1iyysY/3dTtjcA7TOmcOAqhiZQBGJdJ3InD7qUALVf7VwRSBNJkT3zZekyDg9dib8Hx6C0pW3Sc0N23j8ytdm9t/0dnRXemd+JGPjBQHVSWiWaEEYTtnIbD4ngtyjj+D2+sk+8ZXCUpLtNaIo7GO8llvUrU0Y7t/VGkYZ35g/FZmBTHX5sMRnVtOf176kOKlSt+iqxTdn8b4XvOaoVGZn5qqXj/sBbxXYEdXUiNW8nmYzE4JL1AO8DQQ1OGkbaHypm3Zfo93HyI/urmvAd3yn3Civ7ohQx14cDyTOOegh4FT65WVXtWtPkw7U1HMDcOb7c1nLBx/vgj0FRUlGh2Dky21M838QOvC+e/fIG1AoU8Inwvn830C6ztrsbxcNVYBmbeuEKU/5OW24fFWW081GHjBW8QgRM8r6c90FMTGsxdzz9EajBEWGq1PoaGLZvvlZW3xogyn5ztNr1Beee7y0y4zbDN3DwOQTygICIDGvkNkkeYt55gTomyJtjA7H6qLbEHj2xerI/9nN0qhGARGZWjsdjWFSzRH0n+luRgRzMXWhtZuQDgJnmPq/vzBuEOAbZvBx7K+ud1rm8cSbF/yiC1qYozK/AC9sUO11b13McrfgYNU9wrFq3GP4IK/WdzWEwHhRZ0F8H9E0MGm8oO6J3fOaI52Pn21fq2N0lZPqx0btGl10Mr7YMRf2thNT7l0LOVYmJ95brxEOrG5jk1nUOIPtWuwFIbYUxMe1l1ATqblaLXDvBMntRrX+ERoiyM75iJAHTQ3BQvwbW0sc8dYe+zayA9TKG1AbNVvipJ90ZuEIaWgpxQ2S5hnZrW8Djmegdva1v5WuVfCXIOBflO8kYLf9t0IssU+DrP1spt2kUwhG+tQQVzbhgHZkGg5F2YAXGyS+zgJMETA2Yk1IWtmtgWQS8gumSqnB/L9ewfWErs/lsZlIoakCNSzYmmII+4/BxtWC5xQfDVRvyzsFok66Bi+e1pT+ShWeBm/nvBSVPgKw9gu1riGet4Xvpa0WVraJJNo1bEEgYQ/9sPmp68gEBcoF2k7mnZg2iQjipUTvz13Lo08BAeWFYkv2kWcypD01BhbM/wUjf4G/nyzptJEAH6HQgf55FCY79rS79w/NkDJ35kgNWshP2BRwG08Cnjr0DW5qyd/rcgPpxGv6GjJKJ0+UTGsKiohfdqtsTfa/4O5p/Glq7FaHhWTA2kCUIpdDejlK6e2SP2KabopjGE5aywvFbfONHL/gWxtxMwzD/w/hptP/Ki2YbaudqrL3IyVGtmfrthedDNZpVGRJWCmZo296Jh7EBvoG3QprgS9Qem5ma0fMiSWwl5wzah8j0iBFzmD5zyKgfHhOmdw7kLCYjEHkxdxhS4aDzW61QLSbO2ju+CItjNTI5x+9eZjgBcIe7zLLRvhqNjoA3ZrKEDLNspBLxdbVhkRC5GmKIjM15VcqdOrik/wAE4Lq53APD00Rl8Igprr+GH4K0WNw2/lZGg+r3e1QpC2hnyxD8rDi+XGeJ0V9jLuSthXG7ev5CEYEnaUhD7GHvFHF9ZjFokrcH2bhISUK5FJ5rm6VMSFIEAw00l3YoRk2TpJozzEY02RN0NoZv5u5QsAdzWZTk7HwtX6pIp1YAnvmi/W86cmaus0v+lwwJN04rsunsk36mjjftvIX9dwK8zoWPRGYdyy4H0E+UF1wLmHdNgnMJr0FJyhSsyslXeu8tmmjbRyFYhJ0GMwXWGYKM5g6NRIfh0fze3nhffG7tnobfJnwOvW+cyCcKJU46adtXCj5BQyCBnfyj9nHQOW1WSc6uHcbpKrPWC6l4mYR7hhRUBb0MEW5tbmoZPpI4BQJ+WY6Kw1Qo/gWnfcc2qBRiOPC2rzN4b/xbeEFwcttP/wnPiUVh3q0xgDppThCRPvWBifyevrBa5YrQynJhbqBYIYD+whZVQz0WBxjM8rFAEmrjGWS3bRkmqy9JwX7jXOWbolL8wCIsFcJ4qL1bqy7QUAUIHyCu5cdV5fqxKfoMGP45rfECLMCptBBgvvB3AKgPTrYxCX4AG9m0wqDf2nlwDBBlUW6JbZCbwIpmPMNj5f3mqae/l5WJT9bRXL5iwQ9EhtjR130EJx+ktklW/IBYrlY/LeiMUpfK/mOM2cuvyXWXQUoXAXmYcWEqL/NjUBSPlzuoXRYD3Tm12HFYqahL9/A6hSSlWznHPqZzBf4uK+HKei+C3gJKMT0/S4Sl4SbpNnYVj9Q7zh37NmgN/TZ0D5qzyHvNg4eYXTxLLbWO54umQX4ATiNhyXTOBr1/we8NjaEC4jrb0x+8h0Zm/wqA7XgktoMf4lVepQfaVXXJMbUs2uh0NJH13rPyK2rap50TugANFUG8Lynzq0SOIR/WIBzdP/h9n+SRI2kvEEnc8guPsF+04rqWKDs+dQ3QNu2w22h2pfR50PE516SD0WJB0YMn1oZG3mOopsNIWGtr0GBS45px0XYLAd/vjTVIUwbWTKXJdV48FxPMigDmWMRuTJN3UiFtZIHUCQ29u7c/durMBhk4RdUc8yK60T2BR/G2hixT/j0674S+qYnvCmExB8GcLufIAf3FYL1UPJNPUNRNM4BJ3VqdU8ytW3cd+FPW1MLPwYsaw36Hp5CrJdp/6bfvd7PZq5U/XPk/bpn9+WNDkMIH3HIgueOAg6UvFRi0oUEgn42mhCTfr+owPnKjT30q72/c5zlQ1t4J3HSMwacH+ffUpBQJqtMcrjjUkq5cPoB+UN9Deo1JlJlvgxVKRAX9GAA3gS6D/S61WfknHwfQSGdaf0als0/k6NTiupOXCK+IRS3CVqKB0205IstVf/LIm6g88Yxf/r1E3Ca8ctLPY+hWMA5mH7SZiZh76d1k4cPkRyNRI6w5Cn1OCRfOEecasTfNVwCQL6JhdqQoE8ZYu7jWtIHxgXSJGM749Dz+j612h44wL1nLnYe3RoPNe/2r7x33/NYA6j74pvDC4XFWQQ9Lxoj9WkWR3cVKmWIsFwdvtCSUxHsRltlQpVZHWVog1o0qinFvyvKh7XcSKnDqr7xCw+imJzksdeA4VCbsf6MBuSJPM3QbUy5CK4oECNmSTvbLkC2cftANt4t+EFqaUBxUKf9Xls3vAxCtx8ER4w4tN9NfbI/JqETtt0cnNB5fe4Gi6/BssiBG8LGSfx045vDGEmb2oWRWlnZPesCpPNlup53qTvsp1b1bNKI7EFBRpSN75FXB9bbLSUaz0DtLR02aU+dmtugC6Hr8AL6TXfX59Ou/7AnHqzZkRIUcPw5W59wf5m1hqBwro7Z4amyQZ/bkkD88dFxG8YpOn8fcFYySoZcDEqCPrHpL4Ub7C9Khlm5BqeAQ5jsS8rbUJNFKnnR4pVqDVp105vfkI+ltCc5nZP7xqUESgQIQj/QHXq5aFJiNdSbmr+atEuuK4JiestbwwJi6tE7WYWVW9QBcvwRkbyw8riYMdL1YNQvfMmpiOi67hzsVehMHrgVJc0lpBNIyNx0h5JKuip3OLxOu8dEpVrCppufqXvh5JvNfFLRoRFyHVm+Mg+6H8KG6+hJ7Tr+R3mFaGvh7md0t58xupLvpu+0c1EpD1MrmpGlDz+unYOm7mgMBC2LUpAZZkP+Kx7H+mysK9o2YSWUZidVyJo+Y3UdK3FYzeUNuE5hhvA57ARLIFZRyCPKn2PzbLHAR/XRANBZvrvbsyS7ta2QnFecvhVu61MUGOrqK15J8ZewGX3kR+xaTpm3kapgyzvDREkAIsrAZQuwnyFk6stDQBTh5TVzkTF4AJYvKtRmb8FoYQZ9qAooV8qRX8b87hHpGCK/7I++Po2woqU3JZdwpjmjpV16L1C6777IL2Kmua0xgWknVKuQqaNho72oaf0cfwBOIMS2uIB17Us5mHPDOxPV5H7VDAxTlzInh73vodxV1L+ehqEv47RSD2LO5QZTQv4Sj/O7D7warYfH7VZZsK7ILcVw4RQ1mlp8+InR/ABBEZbrR11MvPzracw+lJonxZq+IBIMJJtabc3aDMiTRYWfhJxTcgd+yfsGGzppDZEMyjfKzmyOfl1tVdhOQJMxMSx+0TQD3OXDEfQni8NGbx36dFHLlildF5iYPjfps/EBzH6D0fZPiAiXYlKtqfyBBt2kULhWKrK5AddGIAMzWri6vhcDHXZclhHRBdTd1wleJqksMmCALBUXFyDphp15dlx8Zbf/V1psG4f40XvESohpkraEqTacZC3T38NNjmj5KSnBU8sM7RF+flyse1e9yLHUf6uI7Vt8jfcYNITwxEw5mNMxzY77NOI/hq1D8sla8OKEM2k5RrqfnMdA/qsG9gg3J44RxDXaTihwHsBYuSA+nPAVksbtyru2pH+7Ev71wJ7AGEJTMrgxUQWSMPYKxrKAJ3/aoct8RPTRmX/UvxrLHXShefN7LyuoaDO3HjbJjDEGrtW43+nbTV4zdqM7xN6kbwZms/eFX8p/eoYPIUm4LJg2YARtuGXs1vpKFV1InSzpUnkevfvX1W1x4VaOcurkxtzJGndldiM8K6i8Fu7GLyig6k1CPnbaBoUaaURz9vL8mFUPu0PK01GNaUTOpPTRP96msVCvDa5PciY0vG26bg+tjtw/nz3/TzSXtGNEWQFTNahiNN3p2cTq1c8cqp+TUY/Et5C995DKgqfvNB6fkxfcrM+zRK0skTaf9XKxuDB1cWRyxWkVk8WVE1IX2h/B5voEwwrK+uTw9HcjU4smRFEiGlJiiq4dSvwY9ohf8jJGB+liAc+skUlHTne12xMWQCroQE2fTeu5XZlFGTjkq0B4tCyU59WGNuPaufZCpuY7LzJkLrzAWHFjBjJYY/fZNHmXLd4tKywoF8HwUJ1NEPao/wJb3NHYxEJczT4DE2NZP3UTnmQnj0oE33PJEuqV8IbfSUiiqK5GnmWE/73rO3foCZlVnmQgfxnXlq8+bxUIpvUzfXiDZFmIB3t1YKqF75McA8S96xYjwGFeV54uQgm30LMOouvFfjX2b7MTvlVFdEBw8QxCjmKB2Dfl7UhTg3mbCTuCF93X0j+T1RJTtynaz16btH1Q/+gO8U6Rf4VXqEN+lycCY98Ykxyk2KYExuDLjQUemwxd8kbUI1BZrFJ+lJCorDjWATW7dhCDWCPUfMqDrI4jbN5rQImKWpOKxwwFN0l0IIt74L9+oL1JTTcCp6+jC9PVP0ifhUaTegi4r4b4YAJlKJJRviFWsK7HJUye+24SxM6Fj0Z9f8gfiL54eyaR2lgbjg3vHsgcschFWLYZkWaNVQI8bNe+rW6A3nNQqJa9peZ1lBFTjEmS4bzJJYASU22FEz94cjqPatmZ3au2OXrpSxq6Wi7MCd0vF4vaaiYQLE2ViJts+6q2MkTPVM8IuyYGDrxKathQiZ6ts2fMpqgQH2btFXuBmE+GuhWnFaUq9JCYGTKPYsBN4Omdz6NJq+XiRy+XxF28dPtDyfcSdAQn7NJHuQN3N4ovKreEeDHTtZSS9rsA/Sc2XJsZCB77mBUsIpVWO4mlD1pIZClLR/c6K0+0SnChEEHU0txbdGiHwu5YMTVQzTAq/w6/HjU6AG9NVwezYsaVlOzi7mr9icjb5zkkPclGNiB+ikMLPj9sMXmGljalsaW9l0/7IfvVLEDGa2vyJoIhecN5mAg6Wcl1PiMdqfwS6pqiXGYB4Lj0V+q8OL6SobKE3xeGfpyln9jSdK+//PowbWPPSw08Y00nGEj93ZfEn7ANA+MIHpwSFbV6JUfXov6poVXyG5nitWiAUCaJa1wcJjUwhUkKbQQqen3CHmFToDEHgko6aroR0PuZVfVyMMF1CuaaRk63MX0FG3HTcDxpsSlhTywv9kR5ZyxNAY73Edm0aGPYG/gPjBA/hUwZaWrosudfXlb0vG6Z6/a3Y2BpqkdR7cb+7KA//rKdV+KGhb65RN7w/h/Wqq3eCsD0eQeNKu3WsZAl4VGjQaNj3dfIsczGbUBgcGhwTelnRwVaQCG3+6YPhk32THDGsfLRy1hy/arhLNavP6aI7kJQHZzVhz43qAszQ6EL0LHhZ8FMxHEicycW+1mI92gPLgVkUyvavi3JhW5EEyPkM1xtJSVZqJ5cx363pf3voLZqbD73ByVW23HFgg/uCqdZ3Fx9vULA9qebsXsNMN8Ej/TfkjkgPkSPTAep8KiP2VTUYjo99vQWNf4ppSTKc8sc/IXmSL11q1cvh/pjHI3nntiu7Rkvq4gHEwbc/WBNQaWu6yYUG8bwKS3hq2d4LzXMNyHgphajZjm5WT4oN4D6jGngLzgHxGFhpUYfViqaEkpA4JvBy+9DhhUCEwCgb6i4ly1TVdcxZWT04EwGFHU76BVwUzkBgfx24YttMtupN6UCI4Y53whvq1eQwRVGwGQVzoxDBm8nIEakZPFEjZHILd1BQLqSKGslXy0CEzBYKgmfsU+wmTgyPqJaBdYo1qIyEwHgMPOZQAvKR0cc5I75Zr5gJG8X7ersJRMfc+/Tu1QGyBHFtcke++uwMNOQGbkp5h+HDbsYPm2/KdGuyLhF+Fcmz6clwhhC455Bj7J04v4TvoHysqwu6NAOPSrSHHyY4mhYSasmWa46kcrpBRfIcMAp3ZvHsfiONutVOO4DKtdqJ525Nxum9b4ksGgilyKbw0NMKko8ug9zPkkck9FnJ5FbCZNM7Kc2Qm890AKYpzVV7MNKT7nCvGvreXp8xXmNmF7OmiDmVs02cJe9gGftuv9fr4KbUF2ZqVnCR3JIulTM4YrSMSEpp3DE6sYvbgv6XRET9Z1GbfKUfe+eyNEjeJIdcylAoOhV6HSprlxI/PVv+p5ZsJechU/ikRUK+dm52QbIocKL5vnKWrX52vYVYOoRPgXLUY7F4MU1VlW4CFGXm+KgnTu1NxPED0WWHoMIis99vZXtG6AeGPVFHQzjdVamGXYtcN19DZKyCyrO/xtIGuFsjygIBEMlCrppGgREeTAhcRhzXkIVjs8eh9fLAsfNNaQUndx0D+BYMUsvFF3ZCBj5u7kilJUPQn/A5Zei2JoueT5B+jpxFPrvtf/zL7GUepqsqS3mbrP9AfTBX6X2XM/sr4vFGK6QbL6iIDAf9BS8aO2En/qdN2Kssx7lH0FYYFyjhbWXwqomsV6i9rgRNBftRee/3y+oG5crglNsoHDhe9yKbMefo5CGgfH7fFFU9dq/Ck/I65OYzRyDbH57WZfYMhoWOY5gQDrSsrRyMnbx+VzCTCvNZoHhtvCZqhGTpIRfmc/Q1se3CifDfHaUjgIrernB3S5mKOl9KOb2MGRQz0el49VAvX3hkpouDGDsGuosdqL7OQCW56HSaFEC74TK6lGDMjKDGKBHU9Xp3zXya+lzd8IvEWQuDEEvR3gAdn9At75lmexQWk9e/n+hIeFN2oqcnLR1sY3gzBrkah75VecFvTaV38J38dfYWU+fFhmLJJqMtU6ywIGvwyOndjO2lC1/+sshqpYSDvO4gb/momno43N0GMhiei7ydb3I+PC2gwL3RxWIoHNX53SkwzfcfqKdJJ0UUyqOE37Lk1AZPpyH3V9+xFNQAzNDyYVBPM23Z/SKe7eQcxur1eKNvasnsoY2vnJFyMcn1OxBWuJQYnWAwZhySmM5hVQXY7DYM3IQ/3tFupKpxuxe8HHYp0kZlYJeF4jWITqflecy76p4FGdEChxC4v1JX1PzXtR7hXaXHrBphhL3MX1O8minFcHZ9wy/4JlB6FMRTgk8wVCs5mpc7q+vF0usxawLMG8U0xGv1B0Lxr6Y8oXm1LPKebli5ycbS5fNOBE84gsBeVYlnUCo8Ns070Bp5sSCbEfUd2C2eql27prwVtPRvt3Qqv+k+Z1anqDWsglXAQXeO/jcUb61HfNEq044NaH7YhgR82G38NYynUyFLMEMUIOgPhjI3sembuW83yDycGfhhaM58no8Mr19MsY3O4SONJcQnd6tcgkkHyMi0x+Camn7iYrQspaVxUCzAIQwI/vE0DpVm9gLqCeYJRZ1lng5ZdDD0BhWEMhpGYblorrV5TlspzaarR+Bb8dkcqYFlhuS0zTKeurGymJFMGum+Gy2kr40nV49IFJ+P7LTubSJzqo1eye/Dxj+qxbm7E2+hBpNCxuQQt/Tpo2WvJQD2awexWkBfN/qKXXQ1NZ7TVh8alaezkLa5KVc4UZdhog4B8XeWKI+PUTMfRX4hDw0I75yhATXJoAaeXcrTOIDAh/zX9b8ndalpg16CC7Av+SDWlVOh9GLyCCfvdidrqV3eaH6ohMaZ5vEmCQYhxYfvqWmyF0YXMCwg2BmD1IaRspv0N8KimZR3e2C4DfP+ZPEZOnerjFmiHyxaOxc1UK615wVfVbEXpl/ml1gveRS6RozvPv8JKvYMSPt6cfyJyalA/0dWAoVltXdH9INS1XAXHYI7u1cUGKwlrFt19G2ys1g3Ly1JKIkcMJpEEQ5jQoVJQheUJZV8ve6w2LRCjHM1MeG2HnzMq+o0OGikFgXvwVyANdxPZJmOJrYQkyKsFxLDe/S67Ru4TA/1wk4jh6Vfe+tIqNPRhCZzA2E/XQlhUEbtOqP+18Nk0RW/hw4TTX3cyAgSqDkxoAvwSazzMzMenA/choZL30REb16v+gnQuAURyMdjxL3TTh/Su8Re6+xxIqoKytEdA3xCkcUv0+786n6fRFWqpobFItA91ll4idMIeZSoGvVD7EFJLJ/sS6he/5dnIzZis5qECjsm6yQn2zPso84s4s2h+45R58J+qFbVNTpUkqhMNJrxfzc4j4BnRGoJI/q5wrE27UbB6dtzbdLeq3lBebljVORnlJe2cxdZTT3Usm5a6pNmPjmz9OsxlQbjCtlbBx83UozNbj2uzLahKBdYM2il1QaCFKOEHSW+2g0oKXBeTlKbVlqP//NAI/PxbtWFYG9w3ggOu1X/2HGD5GlQ7W1xM1y4Crx0XBLG3pRdQrmpBZ3nVaagwy49hvRwPLwggsXwO33Rj/zSX0Y2z5gIs4+9fp+oJbyECjl9TP9KdoP0/TX7cFqgAQWmbZVkul4DH6fUR/SzmEYWWfZ3rnLqUGcoHvU+3RsgPe3eXwKZVdEa5IC1KsLdho0paHY4imhK3prWQNjAbCwSFpWIL4rjQAxPIgfwWvI1AU/1W5AYCUy4X3usSbGfFHWHaDCVKHqIq9KWItBuuLHD7BJOrqWZJmsilzVHA7s1xImeQ3VKfxlUo0Gx54QZ9Kf7jkP7MDTHsQxkB52wt88oy2b7mnOT4Xlj1EZSRweThAxK3De9FRsjUknHKgP/wJJ1f1iL86KJyV1oRT4KfWSfqV30GDV5MtBlQ4fche3FhqUJhAIZs92+MXlduaaLfW/jmYYj38HwUPIi/SZUNl0kn58lUqIgusXwXM3J6isS0u4sDQZewaxGy8tTERFeA58iz69TogypEEBCb+PyPb5ZNHsUtQduHYU1BsEC/q3X0KkJ66cdTvRyRmlAy7ALJvYv7XK0uFsM9tWPJH4/2/vfW5g+97fkbuZQaU739w5po67iDgsSV6KhHiNbSB3g7PeeLFTWYqw98emdy4tOPHQPEBKBW9KABGfJkQHzmc/akmh3SS9YSvJtthnV16vFcAcnHMN/k8KlpR2u3XYkTWzAhqVcvJm/pAlw3+vVOequR9KJcsfd7rS7Wpj1P7YdKCy8QKIGRKfE1O6t44nSha77Xlf+qlY/6nTydyFVSjdjOaQs003hU0oA82+5SQVH/ATmokKEhppej1CpW++gW6WEuYd+2L06M9J/Zhb8fabltzaSDNuJ6XYbFJa5jAgKDs0iTotlnFGBCKNTq0UPgcgS12LO8NtfZfxE7ZJGTNoTAuQjPrp0ZyzvJfBKxQcJDSspMCBzX6ye7fb2SR62083b9vkaL4eD45sJkx6W7aXmLe4rLhkDQqEjVx+Q9oVl6jYoBZ7W7XG0yzvWYRaaSDcwN3uVIfU+srWnHiAYOac9LVH/UOVoMkEbYVh6BrtDa+w6dtA7avJNxAR0qLqqGEd5F1o+ck3ZOKdoM4JTKNT1ATY1KTgTCdX6hyxd36TWRkDmF8o5I4EGb05OgaOeXYacDi8xz15DKj2hL92BzXlMEeyOTmxv1JG7pFuh2kS/i58p4r9gDz3r/IQgFDbz0Sq9n6amrBHbs1igrKxdpTU6gLuqwV/b1t9VPNszzhJO0oLWl56G5tS47PVr7XqLjIs/+3u3gvWplud4+dIhv0r3xPKjgvMxEcoIcJ2z0svWHnQggEVAHDtT+u+FoJcp7BVS+V39aGjPtmdrP1WTDshQktP9qPl/AgWoII1lyjyn8CGpEBJZhifFuCja5TmFv/gAvYN0vwVY3R8NjHp9TuHNWygsLvpQ0MxspRcpwBie5RBXDa4Nn+Uhe5HMRHKLiv2wbN61BdjTo0S9n6yIC1k2sFi87oGWeHHGWl6lANVJ9RVibXfGyBzrD5uI07nVJ+PixQHJZg2sJHkk9xgpjIgoaFm1oBnFHoZy1b1XtfHmkTi5fhPFWgrW2z5SiUST7cSvwbzly7qz6p4tEfb7pVggTnP6takUZgrPJtz39tvKt3gLrxOg+cffqYArnEkY8xaBWK++sbT6E+5VGLEGhKIoXCrjLLrjJtmZQqFMRO+iFgkZMzakUPnFgGyLcd78BuvNunN2lqgb7lLZ+KP/myp4VmaK2w/ZUCwdsu79ZNTQqn9DA3QMSHijgXViLi0JVzyuYdcGzi5xYNwyUzgrjCnikvah6AzYoiHdEG6oYxjQi5hT5F61TkUEgvyJR6RQWCD2E94qOyps5lm/xsMs/k/RivcEC3BDiANVK059PCQgEmAgEISnBtE+peb/+YQKBNwSTBjHLCiY5EuCCtijLDYO73LLu3YV1q744ISdH9WytQNgaXQmUpm4/quCNuds7WKRT+bIeFJDiBkryT9eIgBl9Rp5ypMa0BhnRPfmqR1O4Qr1ttU/nzDFvUGg3zC5qPU8kgJ+z/6v+1biMESNo182aPlzwUGrZzPOsxhDbGkavPz7BO1x+fkiCSXTnJcHeG0XnUA19+40yWSeKfhnOX1XfwWqWzm6J3uPRABrIsRxgmHiGLmk5TMEH6nNS0vBWlz3z51wbC52INc9A/+zjdYrewJKS/M3RLErbg62w4V7iEYM4MIXUWGzpCKuqguFt5pbrbrAekjlDHAaHioQmIWRla5UWh66Xc9L1DXrNd9D8ZlBGcSwUS9KdUqBWZaU/9pX8wISO1+rh5k/nCJJTfb9ZpSvINtM7voPrKq800ZAo+n4gBrjKyCw/UCya+LC7K3H76PLpC+BFcpEjFYzxqYagPatPplFp8Lei+Mx4IyPQ4UF/yMAUzUQPCzp64FZc5TPHHvUSfEL2Ca3NROQLP1GuUuy7LlBqRGjxwkaJqnfMEZNCrtAEO4RsT5OarDa9RsnhL4IpXOvtolAXyOq48Cs0ADGI7p939rbfzzunh2HkmEd3iYJnOU25vOV7Dq+jPv2MRmvUdltuS3WT0/man6qQXflv4tzXyOepWPqD4CQljc1X0X3eWdHe/isqxhC2bITnLVg+hzoTcyomnetjhewaeNOrTbgIlWImNA1bO+P6YGghCJ1Leqz3frLnDy6cKyTWrgkXpYnzT+4bOFVyg8luKq7DXQenMaYdwpUeNNeIKmJ2oL8m8sjuzmxWXp9E5gDqV2VjtCdFfFacJnQzS69UKKWUIjR5XafUBm4MW+Zhm7q7R1OPdUyxOXQ45s9Vh5Sv05aox7R26s/EWSHuzx/e3aExYrVpkkn9QmtZpNacSkGPUVOwTH2GCyWvDXH3jEpDuXfgr6g+Ca/z52x32+jrsGGkKbM9F2DmAFYdGLpvGhiwmd3go6tQ1VBud0hLiW0hwHt4O8WTdZME5mf2nmaUkRmZMwVFhdYLg0edRNegj18K6506tg89jTGvfzNMy6DQiFNLstvFVUUzO3Xl0hvK7NGxqcHjWBv+IMEgYeCyBweUG/o7E6ddfPw3LBKQCmPq7tvl9H/FHXTXdVQJjdqISArZo0dR3QUdsZHDhpCrmffYCybQRoTEQPLmj/QGjIP87Ko50srWe9N7Iy5R6wibMpX0rHH0TsdpuK1ahuqdXdlqikyky1W+6kZvTBOC7oWlvN0HYYHK8TmbSXA8s2h1e6hlFOS+mIOIcY76Lf7cZ+11tJgtabZ+paftynRMwTdfjAiqXh4EPbEtlM2yJLpZwXE6ZU8U9axJRxH/dg6Vpi9+lgsLikh+AuPCRLA0jkRjrHgJcmGkjzkugDusK6D/Og/nYDhGYEPnMkuFMhJJH+V1nRwfwzs/eq3c6VpbDFAxtb5MMdmKuvcXGsBx56Mgyqwkg40hlxTHkjz2jsfcJnte4EdVTiLBrgAPXq3oGcKf7aXvGbxphxTectl+LlC/vFUdK2ssnlTYFQNAVkcyI6dK1unoUhg+FqtluiNX0gMEdfpMv1/vlTRnBssTxSo1vFEbZfqAbbKHcJQOZGQzpjadrXLktExoESqz19tfdKuWe/BN19rkvRTFn+pZmGyj+94S5uAjvEugEJx1i9npa/+KpdV6bFM+KH7V9EKwCrVPZRBfzSNJFCK/v/vBK+kgJ8gRviiZiZBrEK7OCUXK7QNBozF/nbcfD9ghdQVS34cMrvaiN7t1nm4KBx27TpypyEjwKAOGIlG1huGd1nVmBsB1dOacNYSCz7BeIdjW/dZefzb8ongWi9ImeRQ1Qcd0ljBwj31qidl7XAAK91s2cwQ/BB9mymlUqAURpis4mMsUOBvFRQFuixagqelWZqztz7DYcwGbjp8ddlDaJfqr54ZGoYGbpZlNzdYeAgqiWsUeMBiFyjD5lfq45bzUE8FYlO9LSUSJut8GMozlk206d39C+mC/BVWirV4RyC5BRJcq7jIBC20MlhNjabCVznEjKqGsy7s5gEj/UpNqnmm8N1zZ86sZbUIOaI6IRjF/7V5xXpMN99Wj26VOf1P9GdWVdCoAfZuL9elNWxJp9gcmKYXdu7A8EX3uw493W3U+oGaKZtNBJt1ak8+ZgIxURrjmjEkBrCb6jrY9cnc3rVvJ3UlZQwKJdZKrG0doKRKI1yadISgY3LCJujorUlq+BxXntMMSJpIW/aky5FWf/DBTXz77xnfThBtRsXPugffUSRIYmF2H3niPaAJzeL2ssqTEsC4UnsRuk/K0r+qGpu7wRXNuDm84b5JKTXrFq+jazBILZbEWORl9fmUTuSQwbgeo9osPJY0C8UCCACmIn9EYs4P+uQY7LDVk0C9MMK0UYS8fhIqEYTCCbhTKjTdUxklAddKbbC4cv1Ckwj9+D1XMObBrnnRviq9BwJY+Bjk4q8Thtm88VRsteAagWHddzlnx2E3d/kpY6nij39jrvlP/e4sYY2pJryuiRcudpgGV8v5DQdYyLqdsU8MoJUyEnQ0Fq9YencsbQo70cwIE0teI+77YZhPQvwDFCMmd+yEWcmwdabCaBN1s4jou5Z7k7X9bMZwNUxPSJtyJh56dMl/HMZv7+0EMuvSFlFbLohTDofm6LgJOqtZ4sYAfRcl1DAWPBICswY2g91V3vHCSYXTil5PwLCiOHlk4C7UotoBSSsWrO7RQ4mcy9bHvGX2K6QQH/b22aDGMGKxXt3lQNz/Y6rkR19XQzDsVFJqKj/dznXQNvL5EEJGOvC3CO4UuWTVXyZeD5ZcnoMg6IWpcve95UYNi2t3baJhbd0kDJrr5SwFcmVWS+4ZtaUhMeQIBmYtn0xHzwQhLL6CYXtZngY0e5gNAa4y7s6rWNVdrbC4XN+6BpMOXGgEiAhz7fkD8qrhYnyne+n/CRcjfI5pP4LHXZNUVVo3PNF9/X5DNW28JX32Aev0zqHE51rgr1U+9xdW6GMGY2j1HNg5yejXUwV/Nshhbe66KcdhMNbaAvjK0GupE7Mfu0qJ5xVdK9Hvc7TwEw7yZux4IxLGgRtNyl0b2sA6ZJfbT7LlwAWA9z5iD0a7GEXLH5XddaP4UF524OwGr0lym/rnGeVomf1sz7tiVmw0C1yl0j26d/bLjLE2lHOV1naAYIECTWw20RipfzP0DGuJTVlgyR/oZwXaK26IG7Lo7BRlyK9o186mQf3TBTxEOkzBU/FerBzxc9nJkyYE5fmpJn2Qs/gShZk/fEUUHz4wzzsxPez3SIS8WNoN5JbWR0y0bakRQclwmCebjXlP0YGaakFQIoYcEpUz/JSIjFM7NWTPIpH85kcJrTUNiPIV6J7xGft8TUQ6ZG2IrM2KjDXCfeQS9iMJfT9GooPRlB7jonBQ5atCFuP8xja8/2Ggw+DaLFq84gNUIoP9mGj31uI4momfBvGakxkBaPuZsRukJBB2GHo5qABNgInuvxQUc64jrr3kDRCLkZOLN3Z0WJyO1CtLUT0g4w0qp1kPtRptpP2kD76YFq0mvGmKvCYyXGb6I+afCN5OzaSXbHFg7JVRfTfMKolSzcXR9EHyhX2eLLeI/J6TT+0R+0b3f48cIG1M5HS+MeBaeaIUeMocBDs7CgSNFI47U2DYU6HvT0M1UYD9W5JZsqqJIhOrz/OviCLR1+Pl41bW6VIwGEvpCNBPno2lg8p2WV6ImEpoAamyYKmJDAZ3JXBKhserGyStxs4SdK64LKohxouAz9MeHj7TmmKnYyqdV0NjvXca0z0VHtUtRGqOOWDQ3ayizRrNz2jECo1YxYnn1lTWIpK3AyqSf1bpUocN/qfvkiiqDrTc58b+FSF2+36p7prKaWgVokcuKDlClmsl0/EZgCwmGM7UbB02I3CvtmtbcKlnUF52IEleSIBbN1QusumqDQmYPjGQpHphsxKPOc5TbqyKTmeX2SUcsC8ToCmvBAZtm9ulnZOhaMUsKhvK06l1prC6c75hQOfQl2h0AOHtTcWkkUV5gIG5c0LNuYPbm1dAjXQbiyUaUKqWVsJpej7kKLipI8ukXURAgDii2DW5uqimBHv8F7PrPUY1plBhvMmX1waY64LmvzEPYVikYTqR2Xda1GI+tKhFZfQBVb/++bO+yWF0EXMThJk3lCS80rEXlwLubc1cTKYXNAz1sTeVEeIJ7x+Vwd+OhvbcRTuE369peNZ6vzhYS8bwYWAwwB+sGrX+4tCCYf7+437SV9mEb7tCzJaFOpYfmzS0C8NMJcDmm6/DHe0nmsQjf9rNWmDCUnr2x9EgH2MMJRohSjPcs93iFusx/X8QaUok5/0vv9QSMn1QTvqJY+Sic+mzfdAIMcM5VPaXAq8htcdLwwK1DWrRelTj0hKtuqEdKthMrW3Ubj/QSqnq8X875Qbzifo/WObM/41inK4bZY3YJhUZa6K4tzgYS92bwN8jT01y/CIWTi51tEfr/DN55nIDSxVO0XcOXkPNhf20DOVoRZVQ9qpHbOFuqdwdHMo7MG3zZYNrgllModlBQPWZqpxH9Chnl/Ywo9Cjvm9l3Js79d2olrc9v0HtItmVl4xSw3H6D7YwndmUbSJQcs7AjD19uy4WCjGxtiZwNdQr02V5GaYpOcnihYtkbaccqIOaEgMud+kFD9lkKKtFUszcx7c4kzKxgn/KnPciLP5oYxwcjijQ3g8v7siqZT0cmaurvkugRjlDC2dZWY2v8HzeCeVGUmKDEqERCDJoWVpv52MTy92np2qI49IyiPZvCDiXOuVQ/ZVe34kiKL9nr85vt8Fjpfh23F8xG3w7XHRkrh6mdJR2JBdYwJ21YxTOKjHTabLaMv5fKSuwZiHztx+MgdP8auF0hzRBh28w2wC4uFTvJyL+UUZIZU/Csp4RESFiHStV/5OL7Ww2CKnw9yaqz1+GWRRThM+Az8ehpwRLJ0w5T58FYiRJdbQ161SHEETl96v25sp9LagXWag7Z3bhqFcjaTc+b99vtkuxJBXq6kTP4w/8k9ffAFzAccWrRkTynxJf6k9UnHWBi6pAhkuoP/fcGMhHis0r9w6T0Mtz9JunMzGAcIVjlwvftj1yM1TRIuBVW97i5PtI7lj74s6d8/J0sqatkUVZEMZPKhtt+2t7HvT+6zXBMWckzsA4Brdv88bjdprLkCnUJ7xUBDlszk+vDUqyJUMfBldE3rIjw7gkUQ952NCxk9Xu2BcooUFSGyHzjZmf5wKvK1fIU8v5TZDhNhjR5i0eRNATefUdrHTYb0Due/PNEbyRWC9+hUwBPOuHry/8mfRXSrXNscnzsBG1Ct0Hi+Bu4YXSJqDgPDNjrwOaW84Swk9ooA3tedpmqUlkxNbXUg2OFV+KPjZRpcDxEPf+Bm9PpMHUeMDtgel8zmGjUFjmVi/BHXY1cVJf7Qd1sKnzf1dEwehdMh4M3tOkYPzdS+XGKjRg6Y6VsDrpUBNwy2837cBZEwEh/6fEnBQhb5S2qzPmvauOc25QoyThye/PwSo3Cxl2QdKSsb6KScQb0EmMp5DAHl/fJpcp3WsoWRFpDvj0HqyU06zi2kAtd9hnlY0gbh6rKgNKwsQwXn6KudmVnwmX1iYYSGBLhyS4/KByCkxL0ai6K1myMFcHiLcaEIUnbKxaGdAmCCOkHU/Zo0P13Kt3n/IJCx9rhXFOft48TZ0u3BPigF+jq9wz33ioAywfOZvm3GoR8ZEg3Z51ZBGvk62l3taKyB2WkSQ5S5Kcgpt3WOhqQC6dcIVXVpHK+JenCU8owE+1IYN1NewDk9fu6njAGbRa/VoKKOghVkH7VhbdREkqtvu5U1OZXNw7Z5LKALzyv4ztww+gFW54IgIJTrSnRy49M4lwoqXiTjP+GobkvDRCkcaiTkK1cyo7VMJdzqME+tJe2pQLdvWB7ApGlLiOHoOlnnXFsxcU8nUYF0I4FWyAyx9myB+qIy2xF9FIaB1KSrgoPd2j9jj1BCE0YvY5CucnY3YxdLnIvqNg72pz/eBI6QZrvJm3qIFpJzohJom6vInGbqbdliS4vR9oekEb1O0ssMTWtfCo6wNuvNTOWfO7BhsT1YbKTAMaq1EpbisZR7h6MTKhe/2tGOl6NQkrut+eIHB8W86dOyD6vhaPTdvWASOXgenf2I6cdbgPg2xvtfCPeMtOp72IKlTug3OjwRN65TUQAQT6TKD9rY9s162ybGNad5Ol0PMA9ZO9TaVwrEVHB5EBLy/L6PHsWr3o0smCJmGh7pjRrZjsWaMLQTVuNg1ARbwBFuyy7k6aEJ2LcS3uHUIrMku87vWEXql+Zr5FX1XLeY0DL3Fbt6dbRjpYVANmEAUmZMMMrcPVlAQ/7KyUzTlU8HAhoTp4ini9pDO8Kzy7tvM3Xps12ZkEDL+BcJR6ezg+pnRKyk49NyFnSqRvtgTfK57mBuvSWduAHGriI449ahdZqeXysqQdySUG7vwQqL3Befk+RDrSlJUGy4o9y3Szr064bkBtEZLobuStUl0YeDZn0EgACtT3CNOc5XMiz7sWpuedsyDpQ205IkuUxiS16ozljbYnrhkZXES1hySiVPVyKzeOPDjM/OtkL1ZbMj3muYitfNAF0eWaRihHyNykkxIEs7yO4hPcm8UT0tycnSIqiLRe6RTJDnb/JwzEgDD4Cnah1mlR2ZEgDRli7mCpSTKA4sA0No8HqIwnuurV1fDSJpW/htR/s26aoD5U19bKSwgaVjoAFLFSjYRVzaxOCOpfjAnjaxO1+tKqHo807AnpLyXFOZWJoHLc/tCwgJdV8g6ykWP6FaNwK1X2WaL6G2ALp4szG4jh83gVf/v+rgl6nbljmGhT+YuSodtlz503EB69O9NDmVCCfPlYgTVBk3LLSByMUQcLV06lExC3Z/Yp1V2XIb68l6vpDxRrrW261qBju7Luuf+Cv//vd+/ndvcrvaijdk5fTCmp6o1GSzQ9RLYVachuuh4U0YDkeK5CnUtixedKWRwl/PnRcXdzTF7BOQosr/MxgxB+sejq37t9KUBy/Lti1zaaLSwgNEBZhh0U63KkMep0xFt+p4gA6V7D9gY0gKF7sXLeKMzaYTvcV/5TOY/t1bbCStIkqo3B1QnbO23BC3Xgpdflg5ZnSu0sC/n98ToJ70DaYQireokKzQxezT+P4BU+D9WaNzfiPD8c44b9gacXRCv3Xl1V/LqYHG4+MEdgVLyExKt0cqNhWAP8uWsHwLUkQBDqCNUjx6erJHlWdZXa+4g1G51hgg2kRIE3wdQd9Shik6HfnTeNX/LMAMKM+RjAQOKc828KeE887RJw/VQ/JVVIHXrON+q8xdct0nbZGzr1Z/m/Zog2MIwBzR2XjNCR5sN0NS2M7a+fRKGIo4EX2HCIoGxiwc6wklPVEQ84i0aZqvlv4tFkuCUIg4hcF2lJS3Q9ex1E4woTdr9p8SNugVo2wfxBE8SKBuNHbTgva5mHmwBNdt+qZSaf5hoopziF9mVeG6OQA0aUO+vSc400EWPCElzj3GHJquZCeb1SAaTMqeDv2N5nfI1Gdch2ukLRddqpoiSrYEn5Gz5C/oiSNR095oUN6mD1EZ2ck5qGkI/hJFS+Pq3W4qE9luTSqdg28teQ2FaCMEH5AG002XvjFvxbOiucJZjCZRQJDut+bCd23lYLbK4s0fdUtKD0lbowQgX559+WWeU+q3r5w1qSSrSKiCPf1sdfrUf/3PINBM7M0c4dV/h+zfcEUkT+jYceT1WmwroxiDv8COa0UZ8PEVhvGBGADg2gHFdAA9R1yTLlVBnOxANTrG2wlg7XvIsF1LKOpFX9SZvfCQiweyTRKUAbtXhhG1Eb9PKaysMrfcuK1yQCY2gpynWpMr6WWCMXBdvyEtOcrrz1C1bKxQEjWz6in0TThVr53B3RFQBWsamLvCraYuRnp9aDfk9Px/Le5d3k8PdaR1jsGSmXXUa6HReQSItsODle8G+Uf19eK70Rf9ajR7UTOdcOQA9vhfPHY2eWIzkzieWgYxUx51tqCDSaa85I+taCbt32YZ6aYY+iH17AxE0NoPD/kpU3knRFE3/FzxZJqVPAQj9Yo7MQnM0OPd0ctG/50ulMePuvwTg19+uc7FgBPDQGpxZTephzqGoCO6mdX8I/trCPmTqCBtbl8Wl4vvmPs6DrNJQhwU4M8NqXfPspYyUZ5tabGptMJNPdFL7np5UrQZwtkxUmz628vQiHgqh6c8N/AUh1MMQ/lFncveXOLw6urbid9+A5S8RiYTJxZBscUgzI9xi+UqcsLHlHC00gHu9D5YlJZd050DZn+op2n62SlTpuyoNQDpFrzQWYFphnn2KfOoMQTRtHg71Iciv+V9tfRxE0H/Ky5SrVTCS44i5sFyvpE6Ftc0ChgxP0fDBrbCmheIuqTyhOycCQnV2Aq32TWU1oZxqKjbSkfkbPucmpyaiypXz/UEgO2yxgraAHhNMaKHuMJJE2CZKOqzuaaxelnRFc8rE7eS7j0KXnCTGbcmit7OHhRpaCJMG7eD8+1bC7yOHcqGWCPiQYBj480FKVBxD726lN2EsT8xqhAI3eL9nDlSXRyRmzUrWLEeA5IPrJwnrDQljJqxHr/hoyj7hJfnrS8cKgC5xtE1Y3EZMPPDoGImlZRmcDkahDDFHhhwZxmcCrxBNRDLtilj3ksDik1hOTODdijQwPrTQckhZbQLhIFPfWhDEzg0u0o2nk5tIg1bCBDlGiDrlHnEAkjc+wRydFaM1UdSAWv27jG+VTJB9QJMTOeNvTFJsMj8cw/iRIu+XvPR77eW16OI2iF6uz+mLeeSKw0yEcK4Z+f3ulDYpagyUvwtsd3N15SD1eN4WB4ACMcZmcdINSeI0tQu/EIrJ6OtQgEJwlRZDEeGBPq8/tQ7h+wL1ITXJTFreUd4DEKcqTEFOfB7rgEkYVOkQRG2qGHr98nCUDfSNwJ6KrcJpuyLvUbXAhL5JupkR7tFmEl3WMwCHz0a1koJYiSNjwEXZJ6Uvp6ZvjylsvcMvJanPKPfjtwW/3Su0hNrnKAJ1RtnCU3QYdFHfeziNf2wExzWYRjLBQMTtS/DqUlCmfYZOrgtW/ITLPdJF9GPzGMLL9L4ddiG/8HfukukY2kkq4OK2pE8M/j/9RPVkLe6jMtrqcxGdslcESVS5g8Fp56VgCi5esq2Cuo/ERsqDQz15hmTmwzNTQKmshzpPny6gohU1XklWqB/wjEx6i5t/i2iDYm7rR9ZK78NJpiNTshRjKkom43NGyDI/+66W8SFQqP6kNKzdYl62yH7G/5PA5ezZgYbZBx78T5vYstvbIusIDnppvf3d162EbBHLonVLQSU1zcKJVQqBDpiUCIbjmH568LPunHwW0UuMvGF6+K5Is8JPb5IFFJroDF9xHYDiWDn2s671E5nIBPIlMqSDEyyZWrVnPUz+jFrot5Ph4TYND55FO5NQjVC7az+g9Sp+rcIeys2yYJR/u1XgX5zCDujKH9g1BQVQmilP/U+mIUl9Ft3Ks8B11iP3oLsMb10/aZrmtuPMbCfFY4Pb34nhjGB8ZkW4ZSfukEeDo6c36F/OBDuNhiYdNoVp8iGob2F8M8dgA1TqNuKz9vASKmXpbF+wB4E3B1Bd0hvUmRQlvGl9px5auYS/VZuxRm+QLM1GxaN/+VoN1Sq2lJ4Pq+im/j10A7ITV7FP9hrZiBEsdTxgcMeh5xR/hIEg7YIY5dhgRNLTu8DduTDV+pwSMUtH+kqcCqhXcjcFPZov/okFLW2vHhM9z6jHzG0/ZbKs+suykrxMRtyR8yMq0ZPZeWCIbCXJZJIUdSEvG3+Th7OXyzYoIeJlJss9vpSgraHY7k1kwi+cfUuVCMIWikPsS8QR1rqZyaatTaInpXLlXERFTKZrt6moAhOfE1n4/DvdV7T7XDsMiemBR0eLIXFUzbBhJCqDqadvPOxCX9mzEhFf5fmb86lnemAlEfbZjhXayDNjqc5JiyH99W07BZwneAE9QRCu2LcyeSCYKkNjyB81ouoMJgNqwPQ2kNd5KtPH4aBavsLD60YqCbzRPGYGsUjEu1Dow2ucyrBpsTmvis1YyoOOfyCgkFnalrjQxzz/wMXnWYEiSIB7XsRBhDMfMLGa2eQs6knhndoBm0kHUKjfCeRMoB/xZnj0HA48UTdVMAaWmWMUlPtqMAzaYoDnZ/HkpunIr6Evg1f8vBrDYKvqQEazsLUwCT3cLApDxE9XNgPgXhzH4AUaCkhmH17WxHlfrZCEQG9oM5GCyoToU492cHY/zFIp6fy0LG1mfwOCwSJ3PPuYwhOQxrdmwu5N5Fj9Gurs1yuFwJ2TjusuFrZwXhDy1UCe7DzgxslH+S0vm6amiRKYD4PbV2E6saSlgiL2NoN3VfaVwVniI6W6jwE2BsgZUGKhOURglsCOO5sT68JO+EsjZtFPIvlvf7eRz/tKvL4Zd09Y8gsaNl8Z9fEqKR65ZAY0cyAU5kfCiwK23AesZawwBuBhcOuTdXWWSiUAKx2+pY2j2EYp8I+QO9U8suklHjuKOfBAUuIHhCq7dhlUarqf2JHvR18zyEgm/ZqgMxYp2XJAcs1mPSyJnAAADwtAOvp+QGEaPCTPDPEhnPEzNEoUlNbDmZ9mnOggGf1kJpFqW8R+J4ZLhIJwmOL0WW87Mf15Q8mCKxsV7SynrhLXz5iQmD1IC3FeqIA/hObxiljj0vtefVbL8pBPHlAHMUdbgN8Wbkx3JhawjM+dcd7iLiJ5B/RMf4Hc4BPVy0oxRO9e7MvNDoIEWvnOTS9jBZ1stqCHwVKKqlAclWS/VScRYKP5RO1ssWquxjY7I69WP4qPc4JSJsCUJW1V1/N2VRlxUGQy0qZnMb0gGBtVkeyGiVt6IdceaWnWGcz+fg/JFQkyG3EDrzTfJ6TNmx5SkJyHrCsm6nA37XODHFGF23rkdw2Xm9UKOl0HL/+k2MP751uKT1pO5G2pIi6hDma51MSyRTk8W4KF2AjVm6iP2OH+SCJs1v0KJ6SJ7jbI0CabQ7DiDT1Q/rJ0loqUtec+nF+zMi9IKfZov8sc8YywDEiVwJw5T4fOFFYBG/3U+EJsiNBmj25GQ0csWmY7S3Jlqo8+BLmpaZlHrsb8pkeXGWlKSPKeDmZfT0X3/UcrpOBTHsTjzxBqn3tS4AGD5xOr6rTdSxdh8TC27Fq7I6ShkqccjM3M2t66Kp+21j3bMjzKQ01qSxk5/V1elxZMkrKGEXFpdPQPdnlUFzOTvBVfP5h8xsEdkccjFqCodHZJNAthjBRn1XZMLYu64Wz7vla9tzIcNMA9E4ZvSHgpWnNNRwn4vST7VSVu53czH1dfwfxhCUcAVyG1dS0D84P0nZs+pwB8yPrI2UlXJWcVsCxfReW6lLyGI81ZnMM1iJS2+HlcBW2xbqKrrdyB7XCEW9O/xZjRp+jFnwDgxStFvGw9n3j9/7q8nzIunb30D30uVvCQwPkvv+vVR+VElO62wkbUP6OcevCU+WfaEiZIL9SuIxQTqlYAg4hJezMXU1ZLViw6p2K8tIw4/WpwPBJU9NWpDeKRjix/CQFwDScUQNiyy7ONZWkQ4uuTBYJjhwuQZ15kiOf2G0I0eFq7+3R2CfuV5AgjCbYmY7oq935B1I8/QDd76pYZIfNs5eVOF+JYRFx2ZypxraYThd5btMxzHo2jYe8qJUo+HkvphNmmTR00p9vrfd19B6okt46eGWSKtiYiFP+0feIXSNA7sFzlb5efY0AT70+3ihBkcW829ijI4oKHFj55Us1itcXAZkLfRyNd8m9B/1nylRzlHBaowrhYMqM+IB9f7nzcnkFJwBZ24DlBairiYdjf6RIxYkQuHGw0O7q8pNyTb+9bmLWqM1AVbZZyochTYzYZc6feJdkN6Z/Apf4FRWqZj6HqR+NTqXO0tU/ysEZNxiYJcxKO9d9folvHwhc9mqDUYp+X6qf/0yDmx216WnDO3aCGgjZzCPL9dxZPTtJ8OlBPQGAIEshHY1JwMryXVuQTIhbTEz0M70jYbDLIy7jLn7R6gq2E6oZxg1NC6gJlXnK9OmkEUDG8LWAZbAmM9SxkeksC6jFOVX9teOAe/ud+HNVEBo3fRMDHlfb9gPZzBZ5zVxtWJzgkB9OE0TLxTrm7k1YjgmT1q+Mg4mYlYo81EVQof2iANH8mczEmeHIg1OfDjvkNvC46RZhnHUW3+KNLSjikbvIeLUArVmimmXYNAm8pBMJYo08XZYOsLZm6bw05Ykzf34fZq+lNvSR0J6Ep4JFx9nF6176bNAjp79ssOogJnJuqpz3OvTp34Pi+wFn4MCx0Fe/DxlmQiX45Ez09lpugXiXI2U803IKWSRcFBdy9d7rFxbUxcK0OylV5LM6+MEqOmDnqBDNWHalHjNX8+1m9jGZ5K1BCevfVSIXLS3crkOttD6zwGiYEZHASaBUUaVldIxTcY5J1yeezbBu0cWpvHL4u2U6C58/EDlBvFn3e1RBO5OlrcUYhil1d2VbanS56eRp6o0uDQfQgjjFf0+KLhqEghYMaz/5wV83I/dHru+O3sidrXJcNB9IiUfCihZd54gX1/8y10l7LNsZo+dGz/m1zd5xgEtXxK+rlRYftuzH2r30jyOyWPa5zTAqTTW6cf3u9yKDAaas+veMMJ46bFx4P1wx6Rrp5DpV2K1l2NZ54NUne3MNZWXXBkU6sODzbLxUw/C5VXBu9KtKMp1+oBflwfZE5Ufal1SyTtQ/VUNro9UY4HNci2iiKMboCdckGVB0goGoSVbxWxlZ3oe2LHcTVdgi9VN7wdoKYF59wskZbgs4Kp463vX5aSCiga3Vn9a7K3jF/IkiXpnL1eAQRqvZBQo3Y5FZf9I/m+v2BC2TqxLZqWLASXvqUXjFNsR1uOPdhklSJLw3mu9y8xfXcMpGNohq9cTGCO3Ge2Olmaphqnw6swa+pI+w9V92TO9JqZcGXZf8FoSZINbILpQOqZOQbjIodH9CztbnNaXSroJUpUFf6QkL+WfdXBs5vGOXTOsy4LeYLIBH7RDCf4BxcClEtLqw8NtjYOgSYZkJfEy9JwK2qMFkTviEQonwhWKCSRHDROTOnDQMhzJrTCoN3YJt3Ztah9LXSOxc5c9MzFmrZ1qvO+OyUsW5lWCHAm0VSZq5Dl5hCxspLTQ8/kXm9ziOif5kSilOmLGIH69CsnY/OioBbLp1zZ7VHFE+/N69q/hQ6QK35+AVvZR+fKRvc29Sc0lzMo0xdPGnJDy/dWCpxF44K34khZNZxMKlY5j3HKoo0mntF889o2DM5Qc7Z1YvarjWGJuUfu7Cho4gr5MJlxoB1UcXal/dmFQepazp7ulpK0Qz9EwRd63zQ6Yyk0z5u2cLuj1qqSr7R/nRj0KcEyx1puXwTDq2pega4jTML8L3xh+eHqkZ9KDtJeHQVZGFUqoQDwAtbQQ/xeQipAQr1ZgDabaYNSMqoAZq3YZ5M+QV5Dam0ubwNSyBGI3sjO5x12VLIIqaahqjTJfEpdQT/ZpkA/CT4yYWybfWZ7fEVhJjCZnxU/pte51Wezi0pamZslfCHG/bOHf/k7HBR8QBdA/YwkR+qa7J2aQFitYsT96RVNC01cl8JjGXN0ttTSzgQg/VIPQUtF6MitH31HFO1HSdjxg7+cJyQ/I1mwP+PUj8y4481clDFBWLvteiVVh7mXgJ1Mv9Eny7nKgytOKxEqjtdb8pTMJ7pH9hCQh6tWkZ3pZI5MVZoqCgLXktqqCdRZvo7SMwJ72Uvmk66eheaIV7IN3mLqXOvmTxxX3ypfzTRofh4plm2CM57CU+cNNGbe/NmYVSp3YhrZhhbyLpzP6UiWHovl9onvIXxnTh6ye77WF5KxsoZJH/jeTnvpcpgXDRgwaKQbnOj2/WgbOJXaPP+Aw3yGlMmk6FbvcytC+UMv3CTuPLhhGy16wfx4TxMXqLQ+VtW/ngLmnUDXFCsG4gDZJxVetJbtjOuruaAjZEM/nxmvYfFfhsF7Um+ABkQOOa9Ok8EaE3SKjitChu7r6fvW81j9Q1itG0xOtesWC0mEoiLEdu4JURMKZ6ig0F3d/j1394RR+O3hx9sNqDQYJljzI+nTDTIU35EsHa1uS0GCL8iIjkm80SpQ/B6Jl1/yig7wc/XYQ728GdUnr3Pw0or0OyuN6DaZrgdMJasExBbpb1vuhsVuut+rwS7ceurupaS14C1b8F7yrT6yxkrqu1ogxsyo0Ad+4i4D3Z5esNtIrIZzR84RnnFN/RGrbjPKf02prnW/W1axrhUABfFoegP2HAhAbwaIFi4S5MaJMrrtQoWHDfwUGGRbaI1+SZzNMfsbseyvApXFjHLIaqPJtcx2+6JhbQ3QAszH4HGJ8xeHLIUX+AyxxPZ1ftRCousMMzIe9BPiuk6J0w0pV7Tv8u4aajResUBMzeOKbGksR7DwCx0fppRfeOuoembwKpzC4YqnJKLzhVtmADsJ+BgdwOoW5mDjPgRj7a2j8jUr1V/iglfAPmw6MU5wMMNykpoJs2xElqp8HOo1xcClT6nEblkq2mrEUXZyTlmSPDjqJGVBHjsL1a1QNrEvKqF/2FLggv4fKfI/L8SUgclUPYL6ys8TupUd9EzfiudOCZRwdsXIg6OLN/zI9ROZqvFgPShTXwtfVb48c3e0yztyHsoQMJa2rI2ICGXRzM7zuriiUcDIL7pEupRt2TQb8tRaY8yrqnOMblPBWo6iN+raObnRaIQCyFyKW5J54c8XOVX9Z6vbLM81JtVp1VtjekkGOsUjUGB7ESaMTSJ+0OxbDcF37mjO3KRHHP6GpHKXD0E0PXgKZ7fKc7r139pnkUg5r9Qyls5owvXQFJKZkj81T3W4FBfexzDKxkqlhRV1eDH0OMu9QGM+NGnbEXt7yXnVvh5GcOwt7xtcPVL0Ku6ktYe2ZIGqS4Xhbb1PKhf77XIylXxtvP0lEEu9RgOSBOVcxpJhuoALgVWw2tANYiIYpHVVIjkIWxi2h/HkTwVzOvfx8lJN+ifGX/4ryBaX6L/FJsOLT4qTuo7kbWRc1xbNrq8n7oeYO5Ch2MGx/Zoygb71ZpKNWo8b/kFrsyh2+2clWQ2kWCTp1GhNTp1OYrDTY1pL8yXCB92lZhP9uvnrr6yyhW1PB0S1gdhsPQt5CRb5sksmLPPJ9VLKEA5AQCSEWOi7Sqk/xNrzkREDLoxxSmnmaNy9dpi/1TRZP26G17uVV35q6MzmBgYanLFwhZJJd6GdAcWl/sWr29LEJ/mkbPGeRw8L9c4YY+GV72HMsLz9sLHhAJMSnIWWyHcVo2BbiMgKxpwh3PwduFN2HXlJ8vW9VtAJVd5tiu9SoEhEs5T/6MWJ6FnEmDTElzgfG0kkUGgrnfXwQMDQrXHD1ftnrb6CQ/F1GTZdVkWRiUkeqEdJwKoF+mfsWZm1jCaVJmTCYzzM9ZYeczQkmVeZ5W6kboGnRemTrCHVw5P00M3aNRiwOeDXjieFnU6g7N4igW5asAKCL1AGVyZ5uvhthJ6MA1BFtVwrxjriuZ3g2jCoPDp0jQRk/Dcchn5VR/QyBkqDE/lb5iJFlaZtfjLbIEY46XFptGDpBxC8BMPMhmlSy360gcG9p140PR8bjwtQHOi5K0hdlVpBcnokR8yD0wlki7H1cGgR+c9qNE7oTI+UNUQ9Xm9oDKov0hiBkmUQr/d3Lo0vTUNK9ijhes2NOuLXxHBIXGLEujeqgFMXI4SN7MEbXC+Rsxq26kvkk+U6duRlHj0/o8JkjOuUn2AXJ1l4r91SGC1wI6Ui9cw9H9gWNRQA8SxRLoVsW5V3HXqfZrN85iGVt6geZOawhTtX46IcOCtbkkoU/o8Z1VgwZt6tU1VVxYtmg9wldScUut4CA9ZaodhiTmhYuxissCqfm0fEH7rhmkKxhibShG4S0YRrlWl6TeGsAVsbMqXvtGBXK4BO9R9eh8rcrgU2udPGf1Sc/cAsiZFgYNMMyuSRZ27QtKgXLCj5s/JRp2ypb6xsHGcVKPwenl+kor0PVNu82VTo4aSXXx9HghMZtS+OCYaDPUipsfGXXJSnH0BeXjYPTuUdrenaaF07Dc7BGopJa/WYYp4pXNPHc8CSlHdnxiGBeubJWlCKG6loCbX9TVMkkTFUfoRHetgvQHTFiVzWy8EpkLX4CypktwhHO6U9QpmUFuzAghY0RZb0HaUhXaB9col6c5wmI3XItYrq6tag+gSCTd2813/EbonZR++QosOn6tP1LE+iyJeUvnz9BKIdIheCN2/g3MCI57ekXCIuyGFk/AfURxArbNhoJA8sDY9ggWNc7TqB0DNIXnMk2lGYAq8h+k7yNNlIh/qUyDoVx82GN5BhrxWCtZljQZy1v1irsj/9LeUiNz21Oq8AIcAxzO2lFcBcKo2FqDsqRcRJJJUqrworTNJk7BAsbkqAcHE/s/xIhDYvDXZ/TGzNXnokYPZOuIdHXYj/QPLku8/3KAnfaC8h/3ClIjk9P4DNdFqb4lJ6OhpVF1up2Yde/QYu6yQSsCBfU0w2zn6tWd7ba9lg16xZS72N4ht+lpwzvfJ+0zjiAKSUkZ3aQZM8oYEsNhPafxBnfq7Z/ayIPYxiZxcPr3cTtmvc2XJ94K+OugTAT4WZdH3aTCiZ4GEbFaG4cMYf4TYxzBnvL6/j5DYs9sV5Vpla3utECXlJANipSAbw9ipz11f3ifavjuuaeLTkhkpT3fmZy51qGu+BectY7dxUAnAQkAdtmSCcDaFaaYYf3q4ELGMhjKTCRpzTI0KZgVv96mDZ4tyZyeY1FuAf+/WBgFlRTL6Ob0MiJIoQLjXVcgVLg9Ona7eUilKpz0BP1EjU1Er7eU9mPIqsSKGCPmrftDQPUL/6isb36cXRKtMjmSm7Um/ZkU51iLSlTUwpLlSXTqudabFdWarzzsqz4rZOoZgGskmE2nJk38YG7ndW3DX1waxO7rPCl/mInSJiR590RgbC1whms9xWYrAijTfaV5LfTAHeC6vDE/FHo9S+AL8FP35XGh9u1zp76mnD0r7SHofjVQcU7te5EdDNdYrNv6ef8FCH5JZzuQJPLZCU39cKAEYWUAk98dMNpOmrMHIeStiM4ykX9PXql1fkhs2ozE417+dHMlVMibm0OTpyhEB/DXI7FBbug1SQQ6INAnB7v17DgsVbvIb/oWo6Ra1wChH1ReLPWpyC/sMsnEAOxlB6Vy/b/6o7Lv/ztGZ8fX+ehrm5HBFSpwdiyntgVZYGgrlBeiI6zFDfZAylmvRoJhYxV1VvVdtLnHVVS4tpw889aNA0pAvQZL4vXKyMWDDd+GS/+R/3bskWylQeHf7r+elWm4UuhZ3ZHuoXlUqzmSYbay1cUYTh0lpd9m6tyoCOi1t9XpQPYFuO2Z6gYMLeLFA1XdF61N3sTyNlN4578VaYLgUl9QmdMu1hEMw9v1FyUymFz31yu7X7eNem1oa7Ug9/g7lIC41dSz/vCmfNpztyz7YfrEMOeikH/B4WEhgPcNFoUKLv8PfqPkt449q1QVGoNAeJUPsO6KWmU40hxzVsKevH2E++e8ZdFxkoWKMXr8c4KSLYB23VW6AAmYekuVSM3LJ+4ix7jd64aLupjgW8XbJjGHMrieg/oZ7qvZ7E8RMrXdwFqWlAssbS5k+BUSvhN1Dkp2YIBnVflGgcLIc9zRYkWE/WkD2HD+mToTY524NC2S9/XQSfXv5Yae4Uazh/KHxY9rsXI9YIilKr/n+zjijjqB2uA9fJ+quVk/gYMNX6M95wJTkvi9OBZMyxmQ5wVqzE38VW9cv2RAnTtjPyvMyzEJGmE4/mWyuCuxfKvDhnY0iL67WjAj131nfMZX8KUoK4ObPvAYU6FF6VUvorjlfFBaHM50Z8mScYnTvMepDD/8EGZ2DYGef32GycQDA0S5GUcc65LkboCXZiofs3V833Pb4fI9IzZbp9pZDcoOQD97v6d9GvtwCrqW8MkVoFpDnisAnPiqePAZaaJfd3GrbCVP2VlhDrKAFRr+xB+P0ExPKCLN/tXx7dH6w2GVUUMVGpc6R+VGZcyVfj3p6WcRsNcpF9iPDrFjuKlcqg3CINbqu87aad7hBvkrAF895npRh+hClPh0BxHJgotgS+qv8+5vQZCP/GHaSqTRon2ESqDCjRgrUvPwnHoByPHhCsFSS1QlihRnxvY21m7SYOBXQ80IQlv1m47FGX19o7vqDyozo0F8PYu3lnM3Jg9VT4+2cJq2a1xwMX6VbRLMy2x/3FTSCfyK6Kl//y+Vcwjy2vxtJZAdHxH+EanhbhvlmDevmDOKOrbgia0KAHpdgeIGFsKN//gWhZlcT/Dv+zbkvq/zMoZmMf7pe0//i/CCRYP5ehaZXwaCfdt0/TF0THGSkcpJC+1Od5hqOPGTFOPwRHPA6XjURbeaIGJm47Tes+B3Sr8b5KTW6cBVVWMvY3ABg22XeZKj8MtY9Z4merNPKQMMa25UoG5BZLkzh0fyi0x48886Qj8G2FIzwXusxi6ndB7B9G0uzli+to/i7987biqgugBtrp09CHDNRgWRrKU98seWPNuulYs4tLKr5B+FfUWbSs7+rPtuV0d4sSFFySU2M/jXNmSvHhrFSJqB2SWLRkmZgCrY+/AojFSzBll1/4RauNW9sUw6bbIeaZrm2Y4BuNZzYg0key3/n5RVwrlGbSmyvXrC6R7XRfqYf+Q/Mv/DODOVZ4gSZoI+henRgNRh7nqRUxtYQhwQWwOjeQnqEPUCq2FGvrLLYZlfb0ojf80wNSzRwskKmWC2cXy96jU5zj2XF8gWK/yaqt//0h0YnG0mz25PW4qCG5MwvE0nhBOi1c58QHGpT/CNunsY/SlTmGap0zCwqj52MHxwLYU+jrkQRW1udvxGrWQqaglqycNyJzhBBS/KynhuzkUAPJmGqM5kc96IbD3EHfuH7t0nMDqTX2TsxaIC4+RedBvKHI4GQSWInSrqjyzQEJvOHyJCPLJ3f7IhzsMSlwMN/GFR17+yVfduWsXFjJm1YSIc7AejNdOxT9bKPy/fBzqgpKZuUT+LSzGgOeAhLPQVFKgGlraoekbylf5Rp9a4WQ7HkoDqWM5E1enH1LHjs146WNuMsHnPCrlI9GU5CCB5oo9M0e79tHej9mayV6/pLuME/veQpJfC9rwUATUtrqibk8Zet/cOeaTUPxEl/VQWqn9mYJqUWyFa+Dy+x/rzJYbBacOVKrZ30FzBxlnMVzfKPRSB9952L0fhPjYaLhyOfl7HToDGFNRlG6Tx4A0NyrSWEpmJSeIrFn/qxSRlVFNOViCt9PHpMPalvXXOkQL/Y0L25ZTWbSiVfgXqhZ7OZ4+V6NiUDfvTUCxMDphJJ/hwbKsPeqAMysWaSmzhXzIc5lXOI5YbF8buede9FudJPGYyqIl7aF/G8mYmDNZJPpXXBrEbgo1sEepzHrohIbg+wBLDIuQxk0XOEGbrD5/BuLB43PuKq04vpqDfV8Yttfinhd0r7/pKz6mkjr/6+qmW9Uc6fgZAAAVsPJkClM7+3u8OKjbHUp+3tMnhypHkJPmq6UkXnKgU3jh1mm/LBSZk5XpIiylg31NEB53XW7NhqeTEb3zN2O9JoLcNtpqq9ElZ5PjspksfiDBUws8ZtJqsKNoMQ9RujRPkvs2FM6Wy/7Cqq5Pni78Hq6BgBc9YyKHetXZ9NNhMZ6BHWKiB07HVBdV9LUrtRfjQn51evTg44cGyEf7zVfzgSmq+DnoejFPazdWEq2DEZnbahiY01YBYDZRDttTm0pxc/k5ykr3OuHBJ89s6gVHB+7Z6OWiwdRr/Y1UluQ3su3KnKHtC130+eUTAHgkJHy2tkCjzKL5ehPQCn0vloSoI6729tFIywKowxE+5aD3aNlZ1sBzIzrXIYgG6ISGZulB5b1C2ApABzPR7rZmnw2JgA9ZjXD6q9jPCusnLbfZpLqP/yr5Hj2JNnk6XLnvSsdbijETcGsrp19I8DS50C/amt8c69sg8i45PHVTTUSU7ZCx2+gX+wvyZ+hr8dsw/ISV/mhe3Ciz/V0mU0aM6Wu/fkYj4sVrbwOa5kbzymJcp30Kfz+8Smlt7dMUgQFwQ6tyQZMPhOxyIzxJHdrcO2HwjbQqN1WQzwmhy9+UBdtzK7/vgq0bNftIFD0OVH8ABANgxOktfUJIkSDCdPgf83YeQzuAA1eIbEZfOtynDudttaCI/tHxT/ntMOdrrzKNFr0TH5lh10A0XWb5sYKBGoVcSY39YF5zLCUiaSSY50G4kJbLKSBiqZe+p81v9/RDwV98L+AgcYUTu4apaq7EkhgyLfjqbdLSpZwyC6ovGjpLN65p0OMqdYdI6Xi6UdAGprFpZ9kj+EsZGh4d1dQifgC1/VwL6QxZrC2Qe6mY6zCj89g9igYR3PU4dHRByL5rm92Dz+Uq1zsCt99cDWVT54iPtJnT1aoKwUN+Hj53vJ2hL3bBzbRt0ahkNlwyo3mtPDznPqaQbftE9dRGEmX0Jsk7aC8EWYVCeXkDMyQxBG5e9H8LjTYbZYgHxGDUkNwfUl+8MuGDe7Q8bE0QKZFxPH+hC3Mazw0bnw3i8zJ9wYvoWts2iHLd0R/+MRIKx3U7FLd13o64j5OOFjDjNPAENgyDLim9hXXC0v76a/qcuSzTSi1g+hwxMuDy9OtxNKhrwLOAtQfZbTajPUDUZRbAj7RALK0weYICbDKZvCQfStY+DNevv9dPyzS7dL53tTWipygl2JjECPGUGJU/M74Dkv5UIQtXkAvujgU+eO3frdKREGaq44M3tvgi+2JrxT2/UTqLXZdIUnbLyVE3BHcnc59nG2jpXcPVKdYYoCmAz8685P7TMvPliwuY/xZgd1u1N8s2YdstiLhhI3ojQJf/qO3GF6oP5jzedrEBLETSw0f45g4lxKQt4cDGQa2cI+OqVDbD9fp6J5HHcCwu3aRb1z9KRoSMV/kzT/pw1KZ0kdJ0X685uKvN6jlAYKtCWhcKUt7IlHc/Pzd2mrLaWU00EKyhLst4jWqVJXFCOxbF/eqSqGFePrvjtFhPKFdTG2/d7TIV13QW06Sup4XiRxwi0lJmOj1soYTfe6f1Den25QnznSWvJx5zWt11L3gnuHAPrpJjgB928SCNlJ2NxXB7W2TPg7S8uEUqhX2gxxxJ9qMyJ4jfKstoWyXvV6ji88x/JtCH8lXNKAQ4KfU2eaPPxiki50NWS+v06M9nvQnfzJm8tqyhtURippV1/JVXJ4rMu7Mjx2RA9ISNSZpFUzEOWQNi4OioZoq0WJKfRuauVRX+tkt7Xa9XkR83dYHZq+h3u2Kyd5QlxgBLv1++1RE7AUvZRfWYknB0BjwxNXn+gA/avRePiE3QvGq2OyxdSuxeN8kc0sHVLxMGl+VCxOZUzMA3Kb1v54dn4jq9IDLEz86tkNMsdf8gFLA9vhN/L3Z/ECQyadzMaga8o/yVVjvrFDd2tuvzsb8JZXk4DOXqLx1gaL995D044mohBVyQ1qhGvFInHTLZ2r0kPssVDbH9Bk4E0SDUqukFhHlq5O6Dj7WsTBelhAUak44Mutgfbt4TuFcXoJstF3955nlfwES3VqKi40QBvz9ESiePGpVErVCM8GQwgBxrh/yPfMvqqF+QSHsgyi/5dBVLt7GOKTWjMLOWTj4NSe1nSqlBBF2oUcYPU/Rg9HGw2jS5rQ/j7I1VknlH1/rDBEeBhgs8RoKv362EDU0kWj8NzrdKTu+SDozAkcWaB0HO9PiTN5EdAPHCjkUbsNOI9vNip7s7L29+lDcEtpFJYI0sYLnX9JiyGXf15ZVJZxBFGcUSiyrZtP2FEwTdwFrbU0+bwJ7184v/n/ZERE1R2nw+KGPovdPxLJmiI2LzLMCfKBfRlteemcdMzBqkJaRxjgBqwJlPHt10K5IHxYgZxVjTZLLfF8sFe8e2frhXTlbs3rFGIKUS3zLI6+4soV/c802ZHBZbM5XelU3BfYqRY1575/tQg4SlensANU9z2kiZAPDrFXfd+Sc7KoE7A6LwgPT635ByoDqGcrQHuD9/DZBpcefWgKO3+3LbZKazvzgmpBSjDWO+5geZUxNqxt5GZTCeXzw8irTw2x77LOzUsiJZxP8QXtu+cbVbjBad5Rnj1eychOnufLuO5KNz2fv6I7qp0oNVJGdE759O56k3KswfQG0GdyDjo//t5CL0w6VUBWV59+XxtVsRl7V+Z6ZlDu4M10hWt9P+K7Gp4tHaDO1MPSI5prk697JX5Rqfq5zLd+OLxggumIJRnZ4Nqmmdc+GEdwnieUyqiZPjeu5WmM/0iRdknrsVr7GNEGRugUh+ctE5wfDVNKA9ymKgUUQcF62E0iMBt4eLewThv4V5EmXx/6NaE0U85U702KGmPIf8nQ/8341Oi0DObLfUum1tA+JK3alwvDWBcZvX1EgztHZJBa76McTPvybQyeBBbMj2NU5g1MZ8BgXdQz+fkE84azhMTxkIsQuvUe3Uk239m3hXhzjMWGgjXWMmym0GGO020UPX/QjMPHb5L7EUxCrVDN8dWwibYR67cD1hqiaaOMVAg8R8HuoZVl877G50SAPeRE0yrnsY8aSGuQ8Qh6Q9Lwfg33H4PFErJ9pTfVEHCwxamcdicL7xivYARHqsSWAjlGqH/9VVHDXWHShqDmqXNFAuRgMC0jeRIql2n+Qz+t+ZezJwlEKVDSnkT2fz/wcB75eL1y6r1Mb+C2Or5Rs5pkFwtTpkSkXnp4hNYXL+DzUATSZJR/pCjgKe72w7TI0s1RuD7/WwXrSwiBYhqh39O+yCT4Z3GjnecpQSQr2KX1RoxoqrXjXcdoF9CmVmxohzfarx6e7O7uPlmHjl5MANaGhyS2ypXeSkcYUO7dd0uco8y74R3GOVmGncxnIqccmZ/vjhUit/z2dCjwWim0iLsqHsUK7/hI5MAMdxFQ8cf3CJgoXWkYTvKr7hqf4KRMuy/V2Aht9+khcPSNxFaugm+gqWahicP/akLbo7u6IsXLQ2eL1HWZ1rHzYhzK1+is7GOCn2pe2z31ouLdrHXIpaahqrTE0b6YW4MPYExRiZw6xP2zwO5sdP/GA2qRy6cxIDdRBUBqFU1lNMSGn6ep4KB+dVsgZDBv/Y+WqwCsu7eGUswvASVWItfRqQq73/vFcbeSGAW83J1H2tLWLlBkWqeBXX0EVgCElJZrNJ2m7XDVuyRzuoVEtAHyKwTcydMTeno/8xYqcjLd2xSFAlX4ZlK+i5Y1LL5wS6wvxhYfC0jG0lK591q305a7VAX+ER019uXTsMswAWu/Tws2xyqA8oY71hzS3g/Hr3uqjlVQP5BzdqPrm/VOLiKGxbMfQgL8yF5RmcHdiCCUgCItjRdcXZYBqTAxajo6YikMTcvvGMwgGGW0tH486DPqygp037QNuMXnY2TKhWKJvyXKOPzONbkTWa+5NXF45Qqthi5STkQhvK6vIEplEbafnFLkd2MFxArztfCH3ZuGoB8kasoYL0E2CcX1HmYdbu+tKDcWiwJnifqLAWkFERist0PYoAQSQBGPAvr16Ud6K22fHL9N8OgAha7eCjeEA6AZ+8aC61UMyf+a9ggnLjLrXaruKRu+DcohB3Gn8QModQ3AuWWLHj0ykN/fmJQ2W09SqxF+FobQQD8Hf+FumVIsXwPttIMssUZv1pr7JKcgk6KYX/zyFayt4gcwum5PinM1v2eUHUZrbxk31jgsZBMs9ocL58Y35Zc7zX1R/EwCXps9JaSOzCzVYMMUZJp8mp9Dq6lMtHxPfNmOvsFmjUbKP5YN5sMurFLOLoaJqcBm7SkRd38auTltyoMdDlYfurryPrMWvLBbYV0zUxwv50gL/XthzJlM1aiHqlElMLMx4oGrS4Xsi0o9UCYdF8K5wW6nUGyBsK573GRPBJuPlDJgr+X42lkbXVLNAM8MajI8r7KV9jZWPoKAabqlx8n6O9YFieHhbvIUV/YZUl73roYkrEEa8wIiRTXAh2gkZAi/qQoKH6Xl0Eb9GHPssChN5nVNfKXNxXeP15xhuKce6tQ5NDmGlEoaSxXzuFoVmk5Blb9mpVMp4xZBcNDMPEtumuIPQuSuShVYignBKsxy9H/s3A4+u2wEfU9sBkyOMEB67MlGtPNVCiip/klRGCcn9GenDqZyXqXm3Jta1z27f51uAHTlZiZyI04dge75erAA90rmTGFWBlC6ns+z3gI5EHbZ6PuXbTjznPXHi0EB2FYV0Bp8b1ErP6Kx2R+rDrxlZpyJcPBIFbcrjRnGu1HL5qyGLrzZcHtCdlXCEK+IaY+S6QvNIr8YfMkzTJr9DhMlLnPzTPsptwcqC6K1ks+e+9XHeJ04jYZHtEdwx+msXGoftmZfAxVzH7eCel8ReUC9HURz7mVT9G1KKtDx8sPXim4seRnvL/tNJOffGq5mUw2OizlzsB0zFUaQoYCX2nOV1ukMVERYLkQcY1k826m8TJpuse7+0itMestVrN4F04YTY92WVJ3Szm4li7GqitRDiQj19fG1fdIxsjYJgzjA1sibqWqbShkpqLPCN83cAxhG85ym4lRvCjWP0BFxdDx419sRW3peu6oX/MvTgOqzP7PAqFtOr2VpSF7KV9FLfBlu3Sko7Mzb3D59yPzJjc+GfxpXPeWAONovyOubGBaeynSrOLSH5YcBGtD410qcUIKr6dGwGpafIqr503iP/ugYdW38YvPOEhGilHizeqONuyiVFr0qrbvLr6xGTyXBHitlZ0dLOzrwkf/GYb0Ae8OG+uZTSGde0rFw4tPMurUiSwHzwwyK7d5w6R6PA4eEvjkITD4r8Q5T/7xs46jkuiibxB46WYAJK4j5PvetnIB7E6ysD3Hbl8UFAarFgco8bDya7SuMucK/HXslx8YQs/h03KCASq4eU7iQHcCpGE7t5WEr3CRrxsDHFhE2LPeYTeb7pJMCr2IRGto2XZedncTNLYOHKzwOag/VMCFQAdApTOBtQgyMYYRzDN+7MYf9LRfYsHP1bYLJAqJV9rlb0kGZHRNWrojM8blcN8CKUMW7SqJ/AMf9GdqbRF2kmMvEXGX5GZxTqUiZalfyuHhdHWjhRKIZ2sCR0142R/2+G3uaYedMjbHjcDMSI5tFKGyJnDxYskt4sHYB1dqu7mhlXeh2GSzb6+gu9kg3pmv2L4WsIZmVxNPTmfCIIIH/aN2xjl21Ju0oZgMJCCsAEHTbUtkBL/HCDZGNSsYz/GTaz9Oc4DQHS8K9774bOjSzlxOqQZBruqTXAFmtr1Kojj86DN6DjVV/dU7HNDbE12pTh+NCXOj2z+4g4cZtERLIg335X65CWS/kvlVGSX86xbHjBLxHLv7qNQStxjpTMXQhgv2syT9WJE5SrExPX27nXkboe3944YJ9uKBK5tAdebZPNYHawVCF6xial18oEk05SVM0docWQQO2gDT8oeClCjDF55YeFhfvnw00dCQdqWB8+C8gh7hEf67Co+dfiE/GC6aF4s6GFdhXo02BZIhlFQlI8i0J/W2juhb1wnY624cbRHPVGQToGrx6+VaQu14kbS+N+4cv0Bw4XCgrjnnX96BTp3KCFFKXQRxv+RKy7iEHTT6k/jX8fID0qMbVX2+dJGx7HaVJIpNc/Hwm3e/3THS3LGWwQbX/xkFqcuxl8V/PTpB3VZTBVIjwx3vNjKwae1sx353PY9cOAgMF/TRfroHj8POHHTAFLEqG9Qn+YAbhQ+48jpeIjdfTfeNnWpw0yhCKyCC2jdbyJtAGLXiMQ3RhKEax23ITLluKAiAeT0doVAYxAVcyoTEJaZospidvH6unWij+gBnpl7Jj6UV4bHqnDku+jatfb2xRsLVlxeVqI0ersqX6uqcAlhbScsOCOGO+0E+OnJJejOVGzf508uI9wyjQp5ggrpTK0z/WcLjsX6jh4En4FA3jAjMr3R+6+878KB+lHeAV8LY/V74V1eKB1Xihh0VN2ysL02bTNVIDG8iCmOVpDg0FOmzM9Y6Ek4wjLh9UxY1FbsfkEOUOLDvbEc/U8wKSaaYTc+EmqiwNWjYoQdvYD5lnP5iKVynt9wNhW38aMc4IuD7t4LNgQd5wlCYv0J9eiIZi+Gl2sg4mitZWIu44jUzeZZ3cMyW4bxwlu1CW00CC2WI3uf8QTk3fNrmpqZJBj6pVmTHSc45P/zV5DtV0UaT1CsSINKGvHs1Dbo4ELr8hbhVi9K4SOTyHtyltw2/7nW+78B2o/sNTVvhQHE544v8BED4+KBSFWT9GcUd4MIquMEVoejBmkU5a/MKLZDWxeWTFwqyJE289/zt3Hv4RNyRJ12muf5GA8Ih7VaaoO0QmPQ+jR2OP9fmcsZboE5ryHdeGfkh2npvdTg5nFP7MCAewZTiB4TEg2ii5FQWqBnBoFaHqFkjoIkxuj3OGJq3bBYRp2k8gcY8yEgSkPkANkl/tLzmLumvlp4tasiYq8xY6jiZ/Gc1TjB9aTQR0/JJaBdL4ps5kvceDDmFi5mWoYaVkie2+gr9HjK4Gia3hh+b4B61Jn3JDp9BsEL6IhPGD4BOjXY1uuyC67LePFa4VGyBs9Gd76kfGNqXgRH3v/FF2DltCDOaWgJQ8YxN8rbHSr2ZFV4PnLDTn2E/TzicxW3qTF084d7kzDgK3Cs4/rtnnYfogFbM7hCzKpst+J5h7GtJ2fLH6yvo/sGGcvGUdzyMOubsEGFnQo7rUGVW5gBmV58vKgNR//NgNXICyrJsLGNi/ZxKo782Tm5ZXeYUzyxmEv+578fg86+B1Ixg6pSLzPpYc2s6Y4L7ytfN0vPRxmXkqtLbVuq5jbT8dAkbbGTNKAFI3yVF/9NZgCDhDNxOodfNwgtbW98hREp3wVvJTpwLwhKQqc3wv914x/wLkxXOqj4uibYPlIIpWee1pP2AL5f0kMJlQt4BYyWaehM0+jnScyMb88veFTG+RMRC03n9nibp9aeUf9tvazag7Zxc3WOLTcDD+zEgfNLPEqrLfE8B4khbgfIJPpM8TQd7dndEG1ElBFfY8kKi7XJ9VJgSkKXgJ7zI1hHsYKT4vQ0DqdkeM0OErFlQDJZH39JmHrBE5h0yA4FlKXzLCXgH5BELZCt5g8Oi0Iu/4r1cw++Zz9nd2R7QFel0gcAA16eqfH6n+fLstxfHJRxt9IslwiFzwVpVQK4bS4FkiKwFGtF6AKDoo+I/slU3YIg2fks9EleDD7QVGtwiZO9jIDvlWcUxoLG/1RtVPTngZ6ICl5PEBfVvojwU9qRiXjQfGBjU8alWtwBwozaP/w+msSH9BhTvB1Sdf4o0u3U1O3N1oswzpDwD99cbLUAH3J1CTQd5artRmmV8UwSIxTRfK21pJH1zvH5PiXTe6/1ytsrzwVQAvZZAKjwq+SghyAKb2V7qskepbItKeEXD1tVqg3q92MWA0BkUjneM1uCVNsqTwvUdqHnk9VsIip8kQXdHIv7kjjaBPRnFbVEiEHbo1Uydtld9EEZAxGkSaaONYC+4dvbAmU2OaSuqFS5REwkqDChW3uXpocROuOaPY8ohWxRA5VDdAxuAdUVYPFXYw24bKScw7FQ0y4M+mQk+7fZcDB1VkHUd5F20tjMBK8wcLIKSxHKDkPENxdqowpGoEIhX24BbeglPxBBIEBPWF/DBa8iYVy/lnp5qpQJx3dU0Z3IkHjLbJDr18Qh13/E051yi62UFRIfXY51PMIdnac2jZQ8iIv2LdfBzMMQdNTplCBKv1D7Un0JsIsPrT/JK5HIkTB2vcOAXVGm6/XfWZygvcEJjeKfzTShxULB9UHxo8IOsDiiQzP7tOfp/bpFcSzzKz7jivDBiWRYMX4pjEUdGFbCU/N4weCVU7dzu/IhAXxn8NHNIDBkY52BkM0YidctkZq9FzTwAkq2s/NURqX5sVi+Wr2ZE2+foxsfbSZiarVk6mqQTIlwhMTWyobi7lvBb4El5Kj+llBDZZ8RZkzF6D4FZyGzirk/1w4SCsLWpne62AnyOtlOo2msu2dV6ZSXHUcxnZBBy2Z31I2/olKWQpgTBbaHSstI47ktM3AUzhlmqGO8FoMGWd6Lj+cQxZwyN35PNOMdTF51r+cSN85oQ7X9iPyDouMWiBiP1XbUiy9Nt5ST950mstBS7b/PJuI2ENxcaOw3aMgetKYKXNMdJiOVny6VlW2/ynGEhz8ZaP2AjrRuhHKr19tg89t1iDYgbcUG1GjoPkgQUSoNpkjto4VrGFOmIKi16OnsgXHNF4pSsa6vLUBV52M1JuEaSEqHFdx2J5fyBanE8ejFN+JVwI4LPSsJJNURR0RkAiWz7ja0c8SJxqBsaf4CPHYucQz62AN1EBJeIjRp9Uq5repmUe4RcuRZl6wDgsX6L4CEmiBVlcrdNB+AcDrkAwoLHW5NBMWgFwm0DxYtRdmGzMU81INFxgeBmyGg6pS3Wmm/MtvAXYVjHUtVSGNHKrBkUB31yvZIPIAB4br7azFJSWr7fxrRTJP+feGasdShqAxNqlnpBPOtD/rXEpnShE4w2SOItYHNrwjpvVQ5Uia5ZFh2CvmCoZByCrrARXoRYhZf7DJ4xZFjidlJ/9/X7wD59etna81P0wdnHxy9SmgRfKsln55VgU4Q+Lwe6K3IcjosSoejlh+785zyElTnXoGO2iJlgMFyGXZ6DzCNlFL3S+tUyOAfwqsTy38AwM5Z1vb/WbgmLj8j/wBYgYuozXeQJwaHPPHrYqhM6f1wlzY39EV5Mu3Z57zOU/tNZ0rNM9aOiH3TLgXKxllfOs78YfL4W76s5UykckUtS732ZXL5QHCA2NtQIwp4cs3OywEQKwqxdX6FOiN+QvUu0/7rIjbSNTEawfnmxMfFGYlIS6EPDW8qVSp0bODosHoqWASR25Qu67UCjqfBM/ARX0ePcSuqzhMNhveLr/8rLjmGFrTHJUKL37DUyRj/Zb+MqDcmXFBzvNnyEZJ1Gr+Apx26Edgoju4fGMiFOySzielk1gWoy0tiYJv963/EkKhJQ7RUKxj2yVg9lme++c+Wu5I114LoJ8EVhCrsEHnwIPP08HbnaIZ5Mhc72GKqgQdsho6S1jzyS6cQ/N4PMxW1f8DjzmTcKEaw8ucGma/ejGHhNl/bCWdSVjyVHsHx3KNWgKVvvbtGgX36L51c6oNhCwTrKc5QbbGxi9u2Th+le/d/pzQlrg5kp1ph9YhRzVs/wQojjAYJjVjda8CJYkT3cXNxOL+/OSadsFSboTxHqgfnDV4oDt6npGAWG7PZLzjc7hU87Ge3KJR6VHr3wZCEr97tqFTNwcEJ1z3TT+m0PTw2Rg4DvDP8QyIoZIjcravgci5fyk9er/IAT/kWF7Tj5Kl69yoYqvhEDLM7NZx8lSmkD1qp6bHsZpFeRRkVI64Y3bMn0F8adaCAMgXFAEktM0Xe/R264m/qPhh0EAFSjXWB70hVGYRNUYRNzu5NZy36Z+RCo1dFgfQOOXZppi4qyaStRxi3D/hkQ/HZ1cZZObVKfiDO2tRHI+V4jIUCMvFVkfqa/cumQrA7p3W5P+CpkfjUKwDnmhgVoIyLremDFDGJjBk2WoLexnnhR1TTbRTsTLSXhKTZHwxUrPqX+Gc6Dzv3XUgbK8pFeBnQJAfcjRn+GXdRIV2VPAB5jEe3GTSaRzci6iswShnAA8EmbKGpeU7DXcpGYuBpP7eB1tyqAG/uiG+GCxszQ5BgNHED+X3oRp1cocqFzAosa4HTTy4p/D9jVKKvgWE8yxbic1IrkcBB0JJDSqq6edUVC8A5gs555WA7tXa31rWf2fyT/GC11ToLAws8yF34azTA+m/34gZiruoO78n/mDRaqYLbR8a3dxz2vB532UseeBSgse1RQcEdlscsvFJ/u2szZASVEh+FsMYeut+F6/B7RTbjHtSCezVpgKj+W8qq1rUSEyglEC7TxbADeMQY77Jtq9Fqk7YgsYkkdMMr383FHnlfGMG8xzCq5kdDN+LzU4mXtYkly51vRDxWEwzjCfvkMea/8ruKj5NCT0e3xIu5/ljhzD5gF0rTGrlDip7BhQRRqatPq6hOLfX6jYY4QRioA+vavEyzXi8mwi45vyipLfvAEx/eZVYc9h1j9aqwYbnMxiyKh9oSspC9OU60jIPIBs1x2ProUuXgxJ7aodGJvXKzgJ8O5lO+aY9Mk49LhwwcqwbLwhPdpsg7z9tGIVvHHuqeBsZ0Y119MRUfJUZsqpVlqgaQBoYqyPLWwwIV+1ve66yXtRW9lOMm/ejXeodOcWAjkjwcpy97zGZ0Z1SxYnes/qGwGYpddeF1zLfIyE1MQuyRLvzBiD4IGGCzhG9Ig1n1ANDtISIpqYCPuT+7fs+EtDs3jQeLai9x8E3uWXCxuilVVsYqoUQPpM1cdgvUCz42s0ZYzIpjZSCFtvtqjADkPSCA5znxRsAWE5u7DMk3Fp4dfdKtRfDGeBi10VW/NUijPMGblygDaGH4PaeYgrxHnDsK5guR+i4Nv9rLEB0KZe20SVHVLwZklnaJ4y/+PxXt8s0PDeX9kgyaxNPlbNeW4J9zMeMuXcGzdvh2fo6XTFwDcBuCcwUWza2C7XaqJSAzVr4T9gk+DVbSRu8yke5Q85dFAmkvk+aRadTvldhB9UZdW/ilHa8AsIzhjP3HHFQ7454DUnjfzLtP//N5Xd/OTZ8cTFwx3lX361MUrNOsD0ESSd1GtNPAAUIwS6Ayccmsb+MYkwuw6m3QPapFVjB6Ei5ZzWMdPJMR4Wl/OYmErvdikFfXpu0xmHEEYH1uym+3an4YboQxCY7gwKfdGOINPw2IqH74etygR9FNuD71F8Qfd8HeEtoTmPA1QKyPcxDzF4YvCVpdQYF9L3w1CBXv6zhbsZZHRzjvSOZnK2izy32+bcqpQ7dFTx0V/VOYe5GFQivaf1EfC/FFcsWimrvLNozbChkQBAHsptcXjhgud6+RZd2+M4jx6/lKc/HUvkNh/LGsTjSdZ4NLJump4SYxlvVcBd4mBmu1iKzAT62BTqaOBUQ9rfXEUZ/EmQLbmZYQt+kaEIA7jdPcFhfkF1T5yM6H8BX/YbdfM8s7nxYP4g8kSp3mfY+rUq58TqB4mR2uWxf+JEs30jUrlY/ULm78Fv1nZuzy9rlmk+bCMqFaShhPSEMSirkxo8PA2YrvIiy/36mpbu4DZv3SkEeHwPrZs0/UjXruIvz8wdMK9ynydfJL1pabG9e/k8In4lLI1c8nSGzFGpRX77cFOYG1E8+ymHxz5AFNFcIIoOTkJg2QNyHrtaKFyH3tCLh/mvRzmkSO1ZiuvbM3R56iEw5vLWeEC9a9XbYWhIOqQT3MUybSl8mwLY101hBUAnSgv/iNz1XxZrm7LlyAUz7+y8UWSDrmJxcogqnaqJQxe5eqhI0DjPIbCn+btQEZdg2J78b1qyP0vay5wTtkML/i6xmkwQRHstNKZA5bU9nFALDnXbZGHNobZUn9Zgo0y9y1mQt+mH2IWb/cB8eCmM5yVWQC3fCKKifNHcp426JvcLrti/NTCDAv51PuDZxqWHqabX57gCEF2YHX+1S9QAhrfxkZEcr44Cr7+yRjsKJ0Mo4pCLnk5RjEKb9L3OyCiZnVt7qsd93GFmZ7c3tVsmn9KS+NxCD9Lkve+UAEZf8tf7BGZOeIdO2/oLMPvdlD7+TG2fygYOr6hA435XORukm3KD303vZSv7Uk0C8YCfB2mDF3Zw/eZtM05IYYXlnZXIMea0nCFbsSWdd5fUkFX8cR1LBGR+8K4mJ11cTD+oTGXCqmt7CDw2d5jc7yOb/5Nic/B9FWtQFzFSOansexeTwE9Bt2VjrK3QXz/k8O0lPMEqc3DZLU3Sa2KN9v6uSgFpJC7ukHoGrQQGUA27NOO8JaMqslUvjtOgH1iworwANlNKc9jjviD+uIm+DLGgIRY7sMqKo+OuReUpDpjrzAh2OY41H6WYHTroDRbil7CnPu3wiUR8pIrWMwTyGi6aEpsWeuAmTg3C4daDsm+d+Pi3qWlqh1kzIULvaiK6RfXw+0OAfWcvvN4XqGZSwGrvjhPLMLMpb6eNbeNwd7PodR63gZ5KAwInM16yGpzt25iPEE6ZyGeioIDm6S+Wqq8FLHw4sYUheAdM0L3ANMGC1bK7V9BL3AXihDp7nP6zOUWueZCYWCfkOVUP6NmnYpZ/4Na1Rz72oKuWpIaM8NE/EriNvHj3qZZwPa8egqEXN+Ep9lOHVo9JJvo8d252ztaWR0qmh5H8hixlzN/wIS/Os/LgUokvElbGgi+Jp0vkrr7Oil/UN7DgP+NmuNRTg2WmOQTq1bGBGawe5eWs+NJQpXAyuefrqkbvHi6f4ylgLGw2WHkMGArLHRmkaQFUcKQsXP6Mo/taH4EdphsWvj0Syv0Fg6ujyFaOtD9+fVVo30AYzPP5ouG2BVxHWGDBrvuR3Ku/KxFNoe1AYl4AXrTRrhv+zG5FpoFt8WKp2Cr5QaKKydHWi3FdRrGG9e9VsWcZrMj+Xk3sfZrQeKygYx35x2CIaMZn5xcSOzYsp+MNV4IydF/J/0oWKvdNLcxdcGSSJWBlQ0v3UogarP9RPLnW5B4e6UlqZW1OvyW7GWCwRfZ2u+BKDg2bUS409mnXcqK5qgyCkRKPCwDw9EJtcC0g0Nglou9y3HpjWzhcP4BOw2keTnQfQvciryB1+9gGgzoj59XjWZEOUWtzxaJbDJPcuSKWWBU7BHYLiQzaBowW/HCOulyryQ/9uPGaLxbBXVysR2JkfBL5W8cg28yQ1J8KVN1g0GAhbIIhJEEeJBOzLsEmxYhadD/Ba0Gm82Q89lz1UZu5x1FHnhQj8PLlE4Fu2TsvINzscfQ1kvULqjMkXQEGy1Vo5rFojhoDZ2iMPmdzeAeMYrsvRWqKz8xMG9v3+shAx8rkvEsmUQ/FSJ0S3twBN37x7FeqC40PO+i71KAV2sNsfa7je27R2p7sFJeYl5Zm7dkaVBUVjFi64qX87X3wC4jG9Io76lTvpMT0mdFu+BrFoe0KVioBInxeKnm7/7x9No26qj4hOp/lQbue7+N0HwNFtpdV1r3M7tzpyLEOqYI0lX4jKNCHBoUo6lgYj9MstR7y/ofyiGSchtQuI0z4YaSahZZ7L3Sn5XD4odqCWYlkpHJvEzvGkDkePJAwBd+KUlxJDCIh57Pr5jfs2Le9PrVQ6VMzNJXqgw4n11akAGlWY5e+NtPTNWVlofwZMHhAH7HR3V4N/SBdBZe2n4nxPHVnh88Wk/QYs5ldSRGoJh3DAMO+YLTsngAUEQ+bFK4cbJpJ/o8ik04AL8s5yRHSpmf7fOc/pu8eyYIppwPhEBQet2Vzy+PTF1dRVzNs4dOYuHVy8CztjupzSr+EWEZyR3g1uR+3zbk548dnCMBnGIM4hGC2RC7YXTaviJtsk5KgL0jwqIl09IUsvnbsWWwNSqRsjRdF0tS6sonYXJvgk/Kh45Xq5+611DwBgixKS6sNyHo6NajWKxHPgcQcj1731a/8KfwLuyRHTVUqsm7Z5s4x7EiMPh7djCIDBWz+335AQyGnxWq7ReVSkiEtKO6NuTRNCrzuNL6LRYWbrgbXDgBazLxHhcMBVaaUKMYgAD4Rgmi3DDs04AnhUgN7duRXgViOKhEsJHRKZKrxGb8zJiah+48CumEC0btUyeud+H4PDoZrnNRz6oHnAX9XSxAcPC8JP3eTV8hJGuw0k0OnJ7bM3Cv22PdARUbZ3chvHXNMJ6GAHIX9QREZGHJeHLlXuFOFc4gpu6hR+8zU8wnZ6NCwKY51GmnIyEtRuJIonbBkkB3WYRfjmM6TFB7XN0yL65LJspVVSF4Vype2/p81KZ4zC91aPWEj8RUWgKy5bivf9a+DlZfORWSnTGCsU2TpAA8Mr2AXxQ1DylCtAFw2dVQzzkD03aodZS2WfRhR1PM3e6IRuBxgukQafR7EtI1vJEjME95vYuDdArD0OdS+GGS2drx7mhesyrhmh7VYj+ytUvX4NgNw+eGpNaqHHfTkf1wEjbOMb7yancgZxj/Bre0Yxv8KTPnMGALdHp1uvhfcbllSWVLCfB72Y1Q+mqpXsS682XIxZk9UBocQ/GUzBD+rg9xyBZQKzkHkTErHm9mDiyxtq8Ft4pC7qv2fjviu6hzVisL1qPnAmyuRD5h3TbrPVkptcWj4UIVjCsm5IqU19vOfz8vyAF8SArHQ43UjfBZO2plkmPAw+nwtGtUvdA4lFeioFvUNFnNU1aRIO11WzDyEfiPWqZ1cyPlIjfMxMKIR+pBX1Lqcs7ACD42KmDj18XOqH7CtIWirTmXoIamD/rhcTTUCxwaX1OuLbcIy+g7ACPUirbQrJBGDw1an7fH0C4NYgU4khzP99iLEFVotwhg0yhookgdlcFszKrI+d1GdcXoC2zDbxWR6GLcZVhr4QYlLjew3eUmwZ4InyYiP1H10sZbT13stodiIaq9aLZuoUcxYPHBU03LEkcZ5TLs1DnEjreH/9f+SL2PpZqgi3b83oiGHV+zk24aLJCesSKvVivUlucCiadIVLrObYXnz6v0VplUSijcvU5XRKGEkIlWV083EJhimHQIwT1iHfV4A+BOL0KhpfS5iz3auhCuFao86k2KyZ7nfre4B2lTTWz2s4o8iTdW2VXiz6jWZQ/DGGY6HTLtJNhv4hTeVyrJytTqz8Ki+zXFAf4yboeCBcfOI43v90Ve/LO3CqnULfUlAjREl51+a++ofBJxcrl+Y9ghZfknnxGumY32o9/piRLMOU4KPZ1gaF9nkfPw9OzIkdpi3ZNMVDIAuNa+nsdKIbJ02UfcaLpW2OiZrr+fW4IBLZX5glfNU9AYS9SMz2M5vOBdQwewGeWCS12TQyV3sShS6FkwTx8WKH8RBlFY8HnjfdOdjkFuNqEaOvT413GNBTviWRokicBrwW7AVyhqlM5zBg/rTAdVVTA4S9anzhVMQ8tseJjn6k0tylffKAupy72LitEJQ3RvCxRxF8/CTHD18YMQYZniQWFKhAbaIFTN0EJnLrix/PAuKizi0VBO/FS3d5uFspR+lUt3Lf77N4xccwpKhTbxRPR0FX6vB12dCtBENzoGoU/mnu/XcUWj7Zn5Cbzt0uXZr9mlVbk2ZXjp+yTPQ+TJ2fD4HDsoYpE1WS27YLC4TWewPNE1vXkJ0xXSkVzF4C0Lz7jEYDmUpcqR0I5P/w8f5IR/stNYotAkoAoX3ZxQbfH/b7Ewq+NVkzcbrFG0QOA2SFNHyREkSVuEUIyEZORkceeF8JY8Tdspl0//cwSZw65ZMiymdGJBQWKdSICOPxZAz+xKVN1Ph37Ag50MoWk8XQU6HiBxr529fM3bGn6deowaw0l7H+4j5CxBoImgWu9QKbs/6tti8YXNZ4Tfv5O5y6q5fm3wjjWEpJC9JLFwcwn2DEMDY2BEqUfWao9dX/vGYcp1WgVT4Tfv3n7x3dqPmsfUuWhBWFvlsaJM3r+bS6gk6Mw8th1n8nA3B+yIOhO6Za95LW9bXwmxVbJIfpqnKPIJ3r0Lb1BCE3HT84Wnv2u0mp5xl1NSGXuE6vonMagchk/j0ubg8wlDj8J/KgHik0ejDP/9W5gPCu+28KFQXLL5KGtOQfN/KOP/beZSxyxaApFcL1XLRh/sTyxkdE1CJ9FEAmO8SMtYwTN4/54BV0ayKCXyYGZ3cV1WDp0pq5uk/aCItUwWYHu6yNbEHbpKbYw4ENnl9q3gMPS01iDLreUVwyFnTjsm/0zIBEmBtqgYWLDiuBQVTzUcvE+UxAHP0JdbCa4Er4YeX/DXtIvbcbltDhOwLIfkwAcL22xjXjk+4I9ABRmgvuz9Jo3ls8Ku8+XNR3jvNGkTEvwjrP9YxZvVrLuozbeVmNz+PVrIIR1hUwxKUtLJBR0neA66hYDFZFXBc8ILsirA/iXVooxYgS/SdbEewwmJpT94rwrafT1tMlaLwjXRobs/RFLqtr0lMBjVMHvTOTc6dbE7vTQ6DkrcTVuIjH/UrQteJ/TXM8KT3bCpfe9cmFeY/nhXkiiljKJ4DAlLmTT8E+njBHZ5KGhg0neDNXQ31xUTalbPMdTW4eIKeSjGPt32l1sTEAFaS7a8608xICGe34o2F+Sl325LtwT1EeRB2tWiTv2ZdZfDVEAdkLGol2zDijH6bev9648SaYXKbZlSmvfH97nAUmQs031Vw+leaIdTUVjkNZOMZ2rR5mGznJ2XMQ2EuTqkpoP9NhrbfFagR+FbYPtkHeJ2VbpBR5n6kh0ECx+MsSMCBf4BfijNJYb/Az1JrQDRGniyC4fv77V3GsL9SbEDa8mviQvhWccFGAp9TwaStBGp3xzeedOPN2epr02q9TTwwVDgovNu3Ouxk/CO4s6EWcXzDr73BMlivfyLa8TPIUHJFGhUpYrfKzC3TfhDP9hINIW8rJ56KjxVemxQ/2JTiFNpqZ91MhG7zfYZbjMVMD3seOAlUV/DAFyQw+rwQIQ/oFs/y8IDScVVXyf4JcJ4a7gwgYtSqjXAgy1aqXgVKI4ACyiPOXkOxFEx4DZigA1iQS/PmrAjVA0aXPdc0Q/L0SuXEs2e31YOvRcIWrCFhbetDUFTQDmHEBt169dqRpRXHqEKtjfumEc+pXuu+bH/Y2QFBM+kI10/Cw3eoUi1TGXFhQwOnMovzKp62Mzn8jUgUiqYWvAUU/nCO9gOo3l6zLmXY1H8Lur02D8TfmHQ/zOBvk3X4MY4yZM0GeVw4wsbGG8zEZ7MdPE29uJDXND3+vHjAdo5JlLACN6HojpmwjPgiZw7464LH8cousttr6wRN2omCvX/MAYCR/cPQM46BJ8FuoX1sCUR6Fvr8puTneeDiniwBWbsTx+nu+mhSM5S391d/WVaMD65ImMFojtnAgGq42WclkmCzbNYh2tKGRMjCE8maySaHJ013xjG61mrUGYpKQym4otG3PzICssL7AO7S353cbqofazqFuM6DvZIrCmFmIPAMRsr3FlozP5bOsD1VDLcind77oMTtLNUBvS7EtGknUv7/w9eoR5sZlhodKbHiUZ35RkmrAzdrc1quU9VEcXtg6bG7xT3aAM+cGTvoQyYWCJX1Na2jBjxv2PzgkBd4YTzkHPA+GSPEuQFEPei9yw1d6H4G6RnFZGdLoP/ZjKfb3oTCKF0aB/tsRsD03RFLIhu3ABETnURs//nCSlm2Xu40eUyFZP9U/XQeUCbaSNJJw95j9g8oZxr+JhvQw9WEtZe4suVgJjxx/W9gzCxFjP/s04J1fiQbOQTUb5QG5iAGR2P8ye84sMY0I6lDzIYF2BQtQ3xXapAiprUA5XDq4vxOyuykx+i5WgpiZ6dIhpYu1fpV/mx57BR88VlkgX67eh/IOqUMsWm8oZJr8I1tpRbccWOl2SrKMODC/RxwtXP1HEfE/GMrVAwN/aEsWG+4Ba2w/Ya12aEGlIJQ/Wkvlr3lISWz/IuVz0ibxbbmpjc5oCdD+oWydt80OvhLgumFXNM3BJfQaGaucrZk7sjYa72e54tge4PabWg5c7jFnNif6JxsoIFOYbOnHuPi83VGMJkgwBqk9OXltg+FMo/sSoG0JJqW/11hBktsD1/h+TSGaV3IrwCCu9JENmsxR94oxCtxwMob4brtJy4z3Ddxk+l+a4aaqKo2h6PWWu6vxsi0mIvrTs6NhdkkLpuYblxwDfgxE77LRSbox9e3xrGA9uoYCfpBTgoqqB9iB6jWigZewpIVOzm9VFPU6ExwS1vd39jFDsQtMwvbIlQny2ET5gzHl0yWVG/pfUBkDOTY/1y775+OpsbGEftW6YnJrMYf+BYmJmQnFOYuTQ30lWxBhI9Jd2mn4lM8K6Irn4yyNVzXkp6Y1YRZLlEo3rJm7qol4/gtY+VQNTrr4tz/Pr5nz6+f0E4kiP8bFqNKWPqF1PEr8zZ0ayGCfH5neRIfQrLhx3x+axYjCwA0l1CPQG3WCXJ62djYOKOM+nf3JX5p+p8UdB0G4mS8lgQlT4YErKqzBUkQun9v1IPDbYthhA6g1ckHnyXJTliN9ZdIQJr+eiW2/Cork5ilubgn166DeUlj6yR6ix6b/eWWw/TGCHx1P6lP4PAhJc2ca8qwogy/4XsJl7Q68YUoL99D0388Zi2KxcBX7BKPHVjrNfWfA8+Jdn+PJdT2sz8djQNPSJJ6FtcDgiUi8/Jnk4wVu/w0b/eC82YeXJ14lq0RK65qdO08I1qJ8QCmKbEWxBDgpiV81Ecq48monz91vFggKsXZD288k8ZPs13s686a/GxBp+e133mGEl4lBu1RqTBTRGXH2KIpsQcHmy1oxIkLYVPZyAFryf7gHR1gEDD8hRyY9/Jl7KXHW0SombVEy50PjsEf75A1UUrvhLx1ZV0qmbL24gmliAC69cpOFnDrD+cP+p4Sr15zEsJ9kBQL2kfawQvocLkWffbwBxoc9pmDc9zTVQ6+tmAHKuQyGSHKUi0+cjZzNhHFix0//uFWZOVlCjaeKc5lREuYntw8mXpW0kNndrI+6ln7DX7xJ5+ZXdNXwWc76U5pR6dxWI1pL/7kzekLrvT/yOiBXuV0VTIdzaFMawA00qOg6jLmeBENsN3vAD7tC+viujOzArl9tBg9Mas0pgbZzo6fzOCWMJ5vFLFxRQ2rcnqfVYtasJN5L59kMJPT4B7cEJEr40q3HCGkExe7V+xOP+pCXzA5nmR81HpmZX8GanPDHpCk+HNEFXZIiY38tzWmoYEXmoeYokE1IT1rPZ6NM4cPuNeIwgb/2c2siswfMdpW5VT5jTjf3NiEjPU7Hfxp2sCRRZKFWrsN+I+zp6Uvyl3a7CJmmr/3yGh7VO8nl/v09CT+4m5mQkowBopipeuzY8yWR4KEf0QV/emhy4z2DbChYCDpMOS+ppv28ZGoImXGx78hCFnWHf4cv8ujLw33Fzqu2mSB596WEMYYPOFZCEkG5EoOKOlhvsAht8QgJFG4WHAJXxkHuTqbSMJuFmI/tDRmwcB04u3+wXHpSAzG8BQqhfXqUk6RvIj9ABAFZVoE2rZ9anlpk7Qrpf88PbTI7Sl8RWQFP1XAJcRxN/8nTH4PDgIV6bnW6+AaIpbeDgVse5dp9HHfOL2AcNyit8kTbICgbOaEfHzLtpeoRaXsXWIZUEhErMbD1/pcRCRTU61GXlHBZQ4vR1Dn+6yVguggVEQ40cu4Lw2GIz8IxiJ3IDMqmh7N5nTuVIKXj/D+ToKCss2EDj6ktx+ZASOO7YO7xmUEfriWB7w0xK6lLhlhMvBTzbjsvpOfccx2ho4Q7HC5R8kXQ7cEB0cvtCBVQ09NgG+bGEFMyYpfieI0XEvHo6rP/qfb3GBYngmHgBRCcbMrZHM0CVzk0wi78XU5w6TGbHXtT9nMhrA6w5ONLjirGuj7xBfpsA2HyYXH24K9Gia0mCOaXuehLxkMDWJybwxtm/8ACCjaKh1PCX+OzRz9yKxvSdIr5XKakQQVqQwKuaaowmh5JpzYNAO+w+ZcJ9q10o03Sw5c3hbJWpKLHToaFvGwdajhBCu6985xhw100fCdhiqBMfiy7mXn80W161agll/lNc1XV5ag5C/+F4LbMVRU9CPBYZCVf+75rzj8x8+65o8qP+iFNG1K9sCWJNhvU/0ib5x3sllTgE297nFiKbd9zo5mU94VQKBfSKtvNPNG10Ezqk1EDRW4uBC8yppqG8UyntEuriMSFgT1lGdOREi8UiBNWT6+95Rz0UCQFfD9+D5zgo4xu6BV0qO680CJX5cyEooVryFad3zGYZPlOOJUYJCeSppPvwOxXHC2QFJqj4q4VLaViVYIJVK9YRpBEQHvFfn/Qt3ZXXVypEkk5UK60B0/v7zPSRUXb73p1x+BhyzjUH1k9K0uw//XzJXrz1+b7xzhMPsiDyzi+/TyKVijuiCQVQUnWCNR0eeFX7/gDVlAl1lKNZaMTd3GgyzfMXMUmgNHsSemE/d/hjys7LOkVrbHaycC0ZMEl2cqihdpEC37Jm8br11aDtu/6PmZNZq3GwbVRPYB+WXwS2sg8mY3liw0FxLkqTBUzG6OM2pZW5toQ0fp17r00LRPRZvePTeMTmPZMlHzpJl32NJm31OU5giGZoLhVuAOisfxADeZME9m3hRjcdOQX543JBZjLKsN3c5t3Lso6kH8yYoyJ8cKkZZ8TwR9suuf6msWJG+s8v1tegXlMZUFKGCkRFSvoyzSF2Xgb4FKaK+XvyTOcLO13iBbuU0k9iHxDdD07vTbQKtTQM1XZ6uGKYt+QOh06Xp2Ny1BHYXXj6ZqnhnGYXgp+SOUx659qjMrgfWxIXIFqtwlTKlQ0YMDndWOnQDS84o875AkZVA3L6LyWo+wKWlqeMt0P2SiRutjEOcJ80wBVj++FO+sCz2F/zlIRusOC54ekAOaUtS0I/8p3guwVeO10Y4t+Rg1fi6zQEqYKr5unIe+GJIDUh/E0K80NHmdZe3QNP1lOOvTV2O7/IG690Ubk6FeWT5snM3wuYwH+NZx4kMN4O3muaIfS6QLAL1ukmiGRGbM7On0bWINWKLd5lRM8e73uKOHHeyPRCBr8ZwqqFNudl6f9YtggzkZRjFSZEWixNV78sqf1dyOeXofoOhYunT5hRyr4CehKiUwKNOHbGuR1zHyVhIVgAI7ph6dAeaKvQrNydCX0dE7wGa4DrB8Zy1b5U4BC0UqEv3iCsjdARAZrUaGmYra25UtZng3u49ywAfMoqsve672f+b+AJJgRDQredEfi1RimeJzyY4Ra7/drS0fM5Grwd0zo0coo/SNOAtBtLwt3JtODGUmjiEg6M0kQx4RpAreIDTYWtAF0hs8pX59TK1ay8F+aylcJ7rhcUN6F3sOmSSt19FWf1FNO/t8UQzIQ0gphBaw9Cl6pXi6XyGfF6pyfxHdPNe9MecNtNNSz2n07WjbFHy7k97qI+lhrSWKbvC6aV3gBXr21Jb4qb4PrDUq5Q7SGvQLp9I64pnIfQVs4MTeZGDP4t6oYR+nDrZLHdy5UA37V/rfL0UUqtGeVUQ0WP10fSf4rgNmgF6sy6JJtKaV3OlKgs2zdeO6N5T7r0S1jeR7inKYprrqoISqaFOLH4a9xdlXaHo1Sh8ok5fBJUOV6iIGIt9nfbDazHYb+Cfe2u4q/Ip2kfiuyVazquS5cVk6VRd7Os1MVSoOwn5Cq1mzYsc99E64KdBL7z99MdNOg4kO46epLhL8xX4/nGA8sDiT1UNZqpMNBC7KDGdi0kLpbMjakscZZiqwSr6HxerpqJFOZwLJazVLJoYvGAOL9Tq0bFtpSZ6rP1N5VcEs122koy0RnZOuNU1DWutBNfn+BJG9Ob2cChu/rerJhs1OWoPrTVu5gZMGY6eqnndRQDfFaqsbn1rnq740HI0XLjVFOxfdQJWt0pvh9DgLvLbo6qz38ppoumVguK5dJ3FbC3kqIuYDEu0dqc+88FhyVcYztgFTXiiLvKhMXMN41HDsltfzL3T9Up+aMOjUZpCjRg/+1JCmZVeunL8xO5UHrSE3cHy9Sqd/ycPDIkp2t7nZGCY+/BQbp4glbhVletgjUbHPlzWStGjcD8oz+qqUKyUiGSeuIUWr6GdJReUH5uUDE7th5mBkHM0gDuZkvemYsJGS7TvY6wkuthfcJGtr+RXp3dkj83eWl3eg5QMW5+kAiL2Jsz+FlD7U5/u7kjconF56jXoqkvv2ZI5VR67c4utGoIyuri2+ciOdIDf887V1j22uIga7KGGkqoyRP5CVwVUNG7uhZK2w3sDsipKKTgivYnrWftjX6BVPKt2OFQwjV90p8MWiwOnOwHPeFjQe04iDQzP3IFN/qJ1xvr58ZgFRYIg6cTRxOMD1M6BfR6rEKxK/HqL05Nt/1tjlPALqWtejvcVDUVvoA4rRs/GK9jXqK/h0XawqgciUDVyYh2r5UhiOIr4j7UfuCNpY9MYFN5W95h5qfOhJ/oJUk+XeG4wk0c0UISOSE9c04/S6Ko/aA6Hq9/slwurUxUzRAK0alVxIDdJf7kVxfD21migqxn0BIJgU8F90HBs0JPOq6va0gd5pn1iA53HzBMsP/t0x1xwFFeY7/GWdfe/2kho705zx3QF0YExtaC9Bmn7xGf3JS4nqmdEvzG5XEWopEbvLcaruAc2IQ6JIUw+LlYIYTdIcUSo0eqMFLRWf2jtwZFNVbtIFMo6K2yg7grVJ+B5Sj+7FdjWO6UGCmUPJymO7KDF0+w9u2u8pZhAgsbjh3zWy153CuTAX+KeSPCzyJ4+VNtOGXBa7aViTr4RK6l0wSxFyjgDb9dtAAAh41cFFHyGXHa8lSkTzBz82REUI+xJ5s0YwPYG8ikYEw+pmvApjFtwrTXYZkDlZ6e2erQGKyfyzB0eyT1K5k4NYLvhR5vZcsLFkqQ7BxHQ/Xa0EXZwXOKV6vF7C4kuZthlducalXQ+8AWWVsNbcdXjbUhOeuaOH494jP1+lr8E5/XZTSupAs198z52eK1ChWERV/NkcQJ0z8cX6tbek3zgZ1aFf/wkMuVl9pZfu22hkTCHkzjmF9oOhyzX1g86NlLn+7U3X0WAnH+Ojn0dZErXOYg34FtGPo+jzZXU6j0eBN8OKBX4PXGVTVuQIzTO3ZUTckJRZPU/pGHgR3JD3cubwAXEk/PQ8G57ZsU5nmBR9LI6NHVjQsSTVYwmNWEvruTOCs7oxg3Xkfvl4rOTpk93H0FBtLSXOYHESaqM+BoybSiToLtGpM3ebHnQ6lOXTxpDW6K9SmfirxA+Mljri51deqKVvOYGya0CuqG9Pd7ydCeIx9Ej7p3xORxwVlrjuli/4o4N7w+Ybs7/P98yG5WNfy6C/lQDGbapjroG7bCb1Cz4+GEKHLZA+nOTeeW0BAMaHVnMQASrbR2xL0Shk9Zs17YxKMY5W0wZEr2i7kmJNW2QpCSdz8xQdqDbQgqfo/KMuXDzNlcvkrBZutL4tUlpo/4GGJegsMrDlbxWhaoqI6hwHkrXxGjplczq44dFVTIhJq56uSR9gCxjJXS3CR4KdncX3Ot2GYtBgdMLYXm9XhrrRujK+mrK6kWZKBYX2s5eEu9wdnpHBggKErn1r/3y/6mOfkmERqm5T1VH+yZ7ac92uu3I/hOPTnftcfXLi5URrCcoevO+AZJwVdEvkjc2DknCAljEGlbHXyndH2NPNb2M6X/XcT7R2L24inVqyhjBgj4syfILXjcMKFJ/R9Z+zyc4AkKGnGFufULshtFet6Bj7PO8Dm1B+Tft+zn3/ikGv+TPawXmHl+6JNIVt1+Br7fC3iaHrHEdSYxaTnsIFaQ1OvOV0ZToBzQ5OmpUykmK5HGpAiBARHBJM9bMW8/K2QSTjYUWbvTbOCwC9chyRZhwbk+q+AHjvgjAngP0Ipi+pURYODwl5z35yGexEX6WFVRdxeRW2BbMocCR3uAYRwvhPDo/AArbcr9v0Gu7KOkIuHgpcKmxidfI8G7GHfqzjqVJF6mUyvKGfHdxztFp2qTIZx3o+xydtfLqxgo233nMzwEVAdSPkOYhUapHaPcrs+TN9ogfNcvlJhT0thWlhpKxP32OuMSjDwfB7Pb6z3Lxv3AIXNNQJZ84TtvM6CSf6HfPM+/7b1o7ExLFbwh4CYUTlJs0IYFz0zQY9XhakQhZVAvOiJwe+Qm48Z0vHi5wgfTuhY2dnif98djk/pIcDoUNciQbEas0z/DwsDrgV9GqYLBbJy23IKxQeJs2SRJ2tOj2zINzsphvWBQb7JLzzNH6mYExIcuPSk4aCOmmSVFh8RiAIr7tMkarlRf7aKKpnDwp2h7GDkTV8mqdIVGlStfrRZdRoMfxhYODkDi72wcZqVmS8JkmFTtcgOhAeXIi7tk7Ew4NsXgEASty1ELPI5Dp86dv7V/S/bx5jXy9z/LWSfAQkl0syhB9zNkfR2WwllAzYkyzrZ4YMMut8AL3KPJ9duXGF2d0NR3CxcJ133smBCaOLki2InBL4rsYiX1h6T8hJjG6xbz7ZQVt42GAEA09fM36zdZA6DhY/InMuarCLZlk/oxhTYZMQT4yVIAnPYY2/Q2Pn81/VBu8xzEV+RJapFNNDsBwh7xtA6fa3pWYe6VpV8wtvEueg132pMeRiMW3Lq+1WpVOXQMhi7WYgaXKC20+icLShMAwzMFYUe6zpEdrjdeAWCwmEmr66zK6jJxwuJD1YI2+ELSpwsogTGE7WXxBAoRsRXwS0rLe9RMomPL1Ou2eYyrN4XsRQNdFdYWlSuuPaF161+XgTP2lXALfk/iFmGsT7/MJOtRNMUrDurXgvZhJWV/LGTA22OxSP+1LIM3sN3hAK1LfSKgyF0F1vcNJLAbi+fREomb6AlisG4t3uYW45tLSNgukLoMYdosvOimpwAwwcuT1q+ylAW04aPkq7+IrbIBNYyG/kfVUdmiGnPs595uXigCqc3qCVWYGrHJe1kdy93+N75OcSN8ToyhhPCRpoKmU9O3Tm85Md3nJhSrKOY+ioGIA6u8YY5b8ydrxdqTzA9Rz9H0P8M4mKlAJ9w9qrSRku/R+h2wZ7nGn2c9hO8aYotkKChnh/DHBYgpLu3vGsG7j+dwJox2C16TxwCUd+IAWhG8LXqcCjqCe/PLpgLi2d/DM2xvMQXwfYhQsCmbuRbEIXSZRbjo1z5JCTgGXlSHCgbENpFzygmcDGVwV3AKb4q78cewXWYCQndCxHs4OMSi9xaYCaJ8a9z5LgZtPQRfnZnyImVVS/a0PfhZOpzRGtJ8jaSgC4K4Zn7rLmnxfwEAfQwm6vUn5w8JQQi0IYYjVdPsJFkkoKBrsAIFLIbiVkkbhlk8xdS36zY6vuSefF02w7l7Qz+vtWm2yHflLUcu0l2W8P0pDDfSzazTG5gfWTslqZQv9BPcfp98gaY1xQJKMMs7OxH5D05F9IP2M8rkSdzYoi2R44VLyTHE9fSSzs03bS1CKh9IjldJsMioPhxBAj9z7yzI6Wpg8qEm5GN7/4M+dA2wi0GM3I7TGYmgO/4P2+SXNPLc1J0APXGY9mKkqkUyX1Ms3upUAzdRCUKJ4rby97IsF3eExCLxlc0kM5RFk2Ato2e3JkDJYUTJXvJFSONQaJcMJvdgp9Upkryvm9C0wL7PQ8HOBhk+3IIcCy6VtL33G3VqNQOEkEQ44l5kHdCdNnEQlZUvBL3Oroio3neRsJcK4HcCfxXvv9zpL70K/793vZZ9fIj15Jsvf4Vlalnp9mDl/pmqvqf/1dwzHcKl14MPuatrJKe7s3rLcOq7MgrNLDX8ur5TUmfZAS34rpTo+EhYLj5xEhdGOzgIE4dDJV1yOAl0reLatqE1fC9UdeyGvbZ4KVa7Q/L9ThvYTDgMvhN3HDAqBBOItTHPsqpXDhy3TRP2I68+20TQ0hHa8kwVktQIeO9eMDuWRaQ65kocEt9KXVlRECRPxgf5mmz2Z2un+Phs0tCi5RUIhCSIdKUXu0C7wzAStxbCmy65NhdAefuicnieezTUhxtPSye1M55m9RKyzyUW8+HRXuAoUK7o/G6S7Rfn9zCSVQKt4qXAhy5v36B0Lbanskr3oS6GjEjfDiTcXJWIW+469b1bgXNUcAnY6YEmcnIsNJR6tnyuihbBAjxDEMO2pqfV8XJ+fp9tTkwU/3sUGuKgrgpgvLsVuR+qkRKSK4ktqYwZsl9LJScq1vrxnHSB65EaqvPN7ayS53Zz+m8Lp5Zdl3sdtkjnXU0Z8wXVAAe/0/SDAmGvkKZ0hVLQXr8svlvXdGzoFH12buaSXkAngHB/uUPoEwMoV1DDnxRAsyQ/+5Clse1zl2boLhNWFYYjE1YkJeQC/iAENqmZGHeQKTqbTaTXPNTOFO13kLiGwRLipR+H/p7LR6QB3DRDGLOcOKtWJ+zlh0ndmSpDZtGnRMFkdvjINqSmk69VqExZ0KtoXUxC3M/3XTXWn7ejWDst5VhrvNI3l2wlScjL/H8iaDIm0C8T7r2mzj0AmWIQyLSPh46ifa2CgH7cdU4elk/EhC7SOcJqZjMy/Fx+PnASmLidNGCeNp+9OPSW4vTLB7UbU1+UUWB7LQeb31Modlk90dkKD3BUebCPjkBb8nVysx4DStBZP8H/UQCJi2pHKw0zgO4duq8Ne1GbicHfGFIUmX1eNehihZ7Nl0vSvji3At5MQNbq5Nv/z5eYCPkDf8R0jd5JMUIsiD5CeC3pf3vTAJ5UKwaMTF9c20mTGVqMOiHUNTQWm2xLxA9d+AFl71wVApCveOU9i06ltTr/CnmbMN16XjYZKD4Xu1GxtDpW9+KcM2xr2yYOCUKMILFk2SeQzvHHhuz5qI3CZaUBWmYvBRgjTYgdAtDARRLuKk0Y6IID9MJWj/pNHgaH2RZTnRaLYjdEXR1jRIGQAHSuM9YrcmcmZ1BHCSq54nT880y1/BFckzR5gg5ImNtqC02d+9jYsnqhGGDnFe8eBSOKTHdR9e0DQ/NZ7jAEN59yBoyvYv+gxQ3drBzwSrAA04hOrHhXVdYPTxNRN5jv1t18sJcxNvbOh+ZCB28x/J61VK5GgwScg0kDCHkg03JUzNd4lIy+4wPVQ6koG3A7jlPiYDZH0NTWPhMtb4cV9IGEJ/jGYyyapAWGBkby9LiILdfEDA/O/msVDx2hRFBVf0rXewGiepO8JL+YjFCvF3lfUlOJh5W4Fdtj1S/2nU2U+jtH/mpENK4UA8TQJutiR53Ac9zplGhSxTcrJjiy7+4WrdPFTxiVb8Ta2AlwxX/uBlRNMNKjHi2sxPSbfWWGAkjJUJlSlYBYDbaHeVzTk8bzvEu81HVgfXdQG6mG7KRUNMD0HEnspQSIjXKw+wgZmYXt+hUczYrChnB0pUf3lLQvFcqUyIyJ0MVoioxrll8HKWy9JlgQld4VXNF8Hge9IH2Zyi8EBJ0NWt33DkFbmSidst/5j1F8oRCorkFezCcXTvzeCSiBw60jVvSTBUFHImIPkbIITuv9Gz/NX7tIT1mHPmijI79WhY9trTY+g2sR9Kco3FRC6TfhBe2MIbNcGyLJ/nR0XT9Xj+UNeo67qznFDU8JkWN6yin8TCGzGLk5n0MI7UMu4Cu+Kjd5qWpgFUCtPHpikFPPyasRLIBX01MpMYxYeDaC90ygXWEeuRAfYfdpYT8Bb7YQnOtljCusTatRd8ZQqRajAhyXjp0ZRpGlq+phkb45iODEPZGNdq3+v3tw06uV7o1wEg4lFTsFeybM8hBmGKhlZH75qzqbTwPhRLUtTpIpZp9LCLq0Nb1v5IVByYXqknNdhLieYpA6vZuL/C+jyxSdW6DVxe6fnidcpj8kPz/giandUD8C5GWTr9BCW7/rJd/rHLYbt8Et2vWDYHUnc9ibyvv2gqAYNtknIWH++4nMujDq1cT0SfPFXQnsV5CoxD2GsHTrdy/yeP45GQSbnTeRBba4dh3H7r4oUaeQ03amGNJvOQTbIBP/xA+Jt2egvro8XDGZ49HNK+H+dx9xk0yWjmgUeL0yhzF5g830sx1A1fmxUCgtcztUhw57inkGBZxm9tDdyIrDOLfNTnrF2g93PCz+O+7ecFp+ZrkZyK95rhdLznMr54zo6bcu+vYYBlGAexwGgZVujK+YBZx+OoI653KWoVAnEHTW1kTMDXQ+Hy45fGAdsBg2JUj+aFTpvahAIrXu5WnkS1b5TMoPeCZAJMBSBdpgfWXSNGIzvVbXTfinPM7oDUQTXNWC0nlqnBprL1tgSDgXLBotbbuY2VNOyFT87yjovCWNf3vUt1nOA22PwnGC18EsJGo9pIsirWx7dyhp/KpezGSEfqkN4s9qz4ZHP3//IYGI9J7weiZ1RS8/T5x/QBVafstREJ+x61KqWYVU43Dx6i2WN9H7v99eJmBy/jPRqLX7GjjOgzw4JifIOMnn+2JMDCutCvuCrngrHaXcF1wlX2GCRDhiPqCGZ8o5nq9sJ85PvCrOzcc750A2Ag8pyxWXaekGgEX7ICfwwrLzgn50hpS3lgy/brBGJtI9Z5sYMJ7uj+PTnqOrsMjcV7fss4Pd1lJy6X6JkHke1P/yThT7xRZ00k1z5x7ZQ564qUcqgjBbng5geFob9fBA8XG6mW6mum7wxqo9OxsYiNgMN7cHGeGMXV+AuvHxK5CbYAVuevavn0kiW1kcXYZCX7PN4nGY/n6rkX68ZqCVWwIecSZYMVnwdsmXvR1rknRNoekemxqn2mJE71X9H7FUoSz2tJ7DezO7ZYj5eXON/j8CmbEccg5zZ7Abz28sjTVh3KEqlQSDaqquGKOBtGZGxe2qKcSsS+O3G/acCWF3/Y8picgMzWZW2V9MxqM+OVT0bhJW5GGclx+N2Lzo/bTiAdPOUBTItsM0awjiJq0Z6wh0TaYa6y4ILrfq7CW1Z6QBKP3ww0fLXml2+ZHn13FM8d6oh80ZFC97q1aEmw+RxzvvWnUFvzmdDjdWzLn51vQxvj0FgbfnYUUVKf7LEBgetwM3gevtTUcuVB8c+a/64Kmbn2R8Y+CyQiWHMn1IZYLup9MdRlgZN8O+kALMCgy0US+U+UHjBD5X+TVpJQug8ClLagZgHd99BiI1QkkwH2DVzPXDQRHIHXP9wuo6SUy2kGcTW5DfFB99flnKuIeoWB3HwzaUsGH2lgguK3Qs5Jyl3sc1T8bW66FQvlpluSQUtFQGGix86aNjIU4igItsxjv7pMjLMXkCpfQiVA+mDteVfD2rcNTX0JVwhXttjy63IP8KdQqiwARXBQ+P8VXIRCPuOXHnwT8lqKBrOQoN0O2T5mkqEWmAfoRc1Eg6SoWx4gnFhRSQSaKhTOMseqRVJAatp+UkgbkAs2b4JpEa7aBw+eic1v+m27buQOnQlUbko7gdaIXNNLdyahvT/oLovjCRJHnO4FZtp3ZN08xuu/WUzluqPwS3o1e2Y1bfH04BZy8hwvsBoyDbjiCB2e+onlzsfWXyOhFSi7itpM9zRqD3AiIERk8N4evSQTIz7AFN7D9nDZbp0Y0U47aRJssv6RuOfA1oMOvqvg4Yi+7nH/zsljvu4n3R9SePJYRcd3a3BxRgthKVOXyST362WleFPZVYVE68uPRtOlkuq0N0NqRgloW9dup8Hc+fM1cO8Fpfvfmr1Gxy5RQXnWqm58te2A0bqKwlwNxzQuwRB8l48QJhtNk7Y41m9rUoPfjACnNhlaLQrGUI+vrDgehLkkYkikEJFZi3CQmk4TRB5fnrRs7uKDXRPiTPaddFMOLQpUV1QivWZGE7sRUs/IXG7RuwluJluZmzyQ3mQhIAZ51GN/FkSSLMTZEiQr165g0aTU0JEUIo25f8JsQ7lks4PbYz7LXeaV9h6Xe49C7BJLUVB3hTZyg19gaI2KPttJhN7/8sTj0X/VRRBCbhZPuzaxsHvUCfl/suynX6Cmna8TYY1u1P/EfbxPsEMHo8WvSdWl8Gnnw4LeYt4Gp878EIrvuYWgNyPUeKVjD9NnN5JJYo1qU1ZOXmwDDXAo91qTwdLTd1SNqrD7M47YhCULa15M5LLxy3tyxHv9plexntqf9vDvsVWAgC7+k3PI/+DpsOVrH+fUu1Wfo3HjK5FHypMJmNnJo4AJk/I/egl0RJZ2EXtsg6UeXHzc8ApFRVzmHWwYIUaGp552t40XE6+QB7FrSgA0QmBat4E3dzJY78d5spBHoN+TTTmOs9S9TlL4QjDM/jjEouq+IgPvSrqrwuGuqyoDh3vV/962wrxhpu74b2t1hHcZhpExVw+ay8FniCEeMdp+C0ymKXUzrNdqmKkeNh6OXNvH4zjLtycNvwi7sJaZNiQP9aqE90j0383bZD1KfpVn6o2/u36p5122q2bX/dbRJTef5s4whIdGpN+TDE37n9vG3VXMer8tIqwJIfdvYvuIx5AZYt/XIUhuiUkShEMbL93fnukcvGwQkLnx1vNCh2nt+mdb0WPP+LyOpcP8/utyTAT0C5pEYOrW5DUntNJ7qwPgcxIeUqhumFFeoTtUj6MT+UIHiqfQuTvDTNnT8cd2QAnH8OoMFfhCiAzGuRRZDP6UuChtsl/pjiL52i9QwzhEulU6yITe/VI8KJ5jRnKRrv46vr0BkPFmGF5a/sTep+VOGzT8oCqYRUYGF2WBJ7cXgMu4qisJxu9y/CB7w8HTlHmuJpNtChOrpBsZzP8J93J3Xy24+AHKRiIPgpSIIPNasjXHNQTow+URRg6akW3+casMJLFnhdwCDtEdXklU869EihGNUgyffr0OrV0t1iWtGQAcGfsQPy2FaZkG2GeXUsdCk4mDVtwrHeCGOd6oydg4tYa/KmJZ8GHNTZe+dyx8wbN0M57HQgKuScP9iBfFCa3pxKTuWxb76LrOQ8PkAotXAos5JQ4yghASIf/hsuhWyj2lmt9AqVLgFQkkmVFxV5MBgMI4CZoVDrHZXcrYn/opM8FKi2xNQGPuZ+CBvA5Iq/dBkk9eMyl8pbtKzgH9urnsKbAfvPD7/PrKpmIVd4DjBWtE5G/noqi48IAykfl3dBmtd/VjaW2VaEIkP1oKkoDG6FHr20gD5sHngeD2V8fVQZ+GMuwgPskn0nNVetXvi/Zf71amvdNKpD2nmA35CH2ABXILpjVyWkIRLkfkbcdqgpTMgb/7WbRlZ7OtGyPpeVhx9opQGgXQcigrM+wjiVA//SHd+6UzfVBtAAcOTTXrajnJXwhvWzpXegkMKJrlQFubxR6tVL0/SFhHWCQrvJhBeswIWZ09WQreacRrwIfaa8WzGaVsMv8cOdHvrSn4o+bhVRduAVNudqEObVYT42ClOwyLAgh38sB6RlsIaOGPDyjV6OD1Uw3UqhAYMROj5fZId2wdl8GYenDLqQEbkyXsTysMpNKsQd/T7HEssVrBXLB3Q2xooDjLrDi/Foknqg1wywHQ3rAPsQRZfyD7fynvKtLhEP2zaIg2krS7bYU5EWfoA2JoqQMBrB4ECB45NhSmVSBhJz4XssznWtLws1s8aKWHgqq5CWhs7F/2Rv3MMO+xIiTZgReNe/7dwcehGhJLsQHJ0opO3LlXjryRJBQffJWnyjIwkshJclmCrSanzoKeHT7GMhE3e0Ijixdg+sPVdKDMlu3bN/eBjF439NiAUBXyJC/KzbbO+wuKL2QVkRdCktao3RmRKOLbUuM6yUmHR0GvAkhQm9C+t32HU1NOOWdtOJSOqb/VmMxWAlyNnh6oI1B0f4YObuNd9eakMnmJjqecmEQEOTxdj726fjJpeiGklwb7LJGos2P/wfzfbAkVvVhtLhqySgohkNclk3mwielR21PtnZa/Y3LUxGJKsJIZQaG5j6rdu8L+B2EFPddaWFO1x5NdOhXQ6aPXyF6yT5aqlBa+ihCeH7oz3TyAIa9pqXgXsXXEuCjgXoIyrfZreEzvpMkIwdRfjT/dMt3IMNADls1VfBE08ZRQ6u16k3zIGUjxfKdd/++N+4oTAYOrPRcKAdtxyUzVyP8wXHWPArfkUwc+DY3V9iJd+CBD6wdIuGD39kWTW6dSI8C260FP2RvR9zX1ZO/hpQasdnSif5ktIswfVgqcxFemHRzpcvK/2qGwIp2jdffW24Mu/oH0jr2wZ6SN0eYVcuOt4oi7/fN19GiCatFJ/Qgp6DRfr/c9eM8E4SGV+0P3zCELVcU5iLcgdlfbdWuNGrcMIBbR/hFFw2OS5zIajfp5RAubSEPOPCBioCGvHPJSljrt2bB5FDeoJOT3WepaiS0JvtnOZ2LDxoWmUCAzDPDkuFg8EdBGQ+BnJPnJDFYgm8pQawTZnRUDfHSdiS/u/vCmYNDbXtNZSW8ljKyw3Q5eXAAl+rwz20gEOIFSH8f1n5wiNBlFHLV2x5cKogplsW+hZcZZllpfZIL9u3R33D4toKPde9QqEsZGDREOijv6mEVDMUPSR246zxpsbC0dx/q22/9cyAgTx8Vir+Ljt+ZzLC89fiEEq4HX/GFim1DgWDw/NG/IpMlEgfxMYhgbnBovoM+WnJv2U3/+4pCIQQ3EN+Nim5FzDSp++nX+hvu/X1vSI2Y7khiKCer1LGE/mRtvY3g5slK9hfUNIJRvT4OorsJK0IxkdhzdqdfC2XmMKlFWqCSmigX2DoSpr4D5bJ0PhL2dr/ZEzLzu27bHF3DHP9HByPpeKa7a/ka24IDTq7+UrETf6NYlOv+611t2NXbd0kNQnb8O5C8tyDE7IsTaCqerlYbyvWU9jnZKvoKcIqrrb4TKGsrUvgyrywh6hK/KpenPmrOh5lzvhRdUMGjm4MmsjjrGgShRKBSTI1wRmK5o1Z4mX/l0rkEkL2Xvdk9GWV8xKY7MqLUuBUm0Cf+OjE+ReV6TrYe900ZNrghHP4fd4MFXINDtmLf8/syNHrQMaa1kuxT88UVpbahfSwZgiPeMQCmnIHy7AhFChQ+keVG0jiPZ4Pa14CoYBK6gGMpQmfLCkaOrvJR0V0RVzkvpIGhQHEBTAyjzKx8V8X0wztYSdFfNdwOCTmIZgjI/1O1yET5/ksh9gAXlrweYUmHn7cLfb4My2N8mYuvvon85A++tKNqmT6dgjg9a7s0GBbv4F575LtvXWaAihzPaE7ZsmjvXdPT9Q6tb5UfCBqog6br1uar6wi88r/VFdh9ZNQI2zzDm6+VXAHEQg1QTFKuE6eO7GUGr3fh9SFF2Ag6aWY6Bw29xap+sTcS6MIjAdibq1e6zBQ5wOnWHnVFPV/tu5y7bNF30XzBGM+r6OJD1B4lvynRChSsdcHWHhJg1x0k/HzBXxRXrjDUntpsTKUl1eThOHv75QAdN66pAsGPNJcrK/vHiMduOQg90lpQICLCPUhxhdcRzk0gh0OpBF1shIPKNuLKj8IagYbmHB2D02FkaDKvsVCcDOpBthsVUB9nF+jdrUegUuY7Stq1ANIqF+v42KFFCEoQueP9Eaei79H61Pj8oieALL0QCy5PiqRFgESFRIV5mohqkgjqbSgV4RoLEMC097fZGolBS52tse5VHMPFOyj8CEM3PZb5XEj4VCRNU3QNoIijr0Y2ytQA74Sp1Gp1SFtQtBG3MXaS1Aearl4TwjES08qcyGNuMpA4U+34SWgg37P0NY1dkLw2jIf2cAXwx7Ul3Kr+ZqYhV8lLKmg7WPzSD1UF1/ABJA/JHA35sEQnPmB7ROJILfXpeplPIshKJlv1C7gUsgmqfDA/1ENTwZWccyChJaZz6gMHBKxgJ97/53bxu4TOCP/3dy9WryRx23bNPnDTD7mqy2RP15uN53/tT5NJ3buJoqfDpVkPvFDAM7vji8/Bjh0j6r5Ffp0WTzxI8WUp0hEx3WVEItdNhiLZu+YJnw0bRfnlMx3Ry3ndW/FnzI6vWr78z+dipg6oOz2pUp60BmwcmU+VsRc8J3lCHu4UtSVFjj800nIHOWZF8ev3q24DICAQ/flBvIcvYpIlbQB53FqlCAvATk543Or9BkmyDP+BYFnWwxAepkuigW5CwNvWHr7IgbofS6u0L+slDEMelw/i90WueThZnTP5JXXqiEnUyVKzLMOynb3Mk5SgzA6RmFpr9bthwJ5yvGnKtsjN4JQ5d1wA8kzHZvcZ0a8e6OygAUW2M6Ab+9OjiphI8zmgBT/ZikHXyjFfqsYfOmKIzPudp+1yneBD5J8vzd4i6iTxDVOKWNCKLgFr5K+lecEJqqmq/Kl+0L6JUgBeqim5oqxNkE3cIWK7qEMEJjWRbTIHEZq9Sg9SePPEXbicgNEj1LcqU7R6crzxeG7l9I3mlWrjj5dIGJMbOG+ferP0q5nu5igl9GJh1a62ZgU7kSF797CjwkQD5ubd4yUb5BYZW4I25kqMsH1nEKElj9wN5m/H3cKD6l7p4TJQ3xOVblrCUxRl5KjwpozLIYWqfJXvIr3PjY5pI91SPbZolRpjQCclEKtsx8tTHVphH6T3SgLBFYhiOXtOWXwIfXYrG/LwJ6bN0ziY1cJ4UGBhOcvzDRZeW77GKF/l4UZdXHq2SsBe/ClMPiEZBY3Aw0Zj9t10jnHz+jh/dXmZBo5rFjHvk5hy3VnYbJ0MqFMo0SbcCOnJXlA01WyQH4nuVlwVqFM93Ban6Uzhl8b2ZEB46ffRwFPecCajU5Wbc9ZLiAnlL9CtpOg/Q1GmY+kpfnL9/XD9z5xbOKnnurqCSMSnE4uLWyVkYWzqFB51ROcIls67/aH251RPF8ci+lMvkLR2MBGMlUL1NAGl1Iyn24X7tedXmkv8q9bFjXnOS7JepkXEj8FFxzblMRJwOPjWGyJFEM+V+Zp/ZZeq/tyJL+uy36c81fxzUedqu8fHIpb94GakBkPzuOj8W7SRu/clUS7mhTqqW/p2+0I9vlLf1uYNa9zEwzJcmt5Z0zJbQzU9M1FV7beu63axQbNZJl7oPJOvF6JLNITEHt9b5W7/1muA2e1Aj4tuY6vWEp0lGnE39vqt5u5C7HFYkZR1Uc6WH1xyzfuKyW2QLeGzGw8kv8JAO1U4Y5WyvvpUKefDe0JA+7gIrrKviXwV6l2tVSTaVUOugk6bC6OwMJ7M6sPxaTW5fJLKECsGfVydbssBFioon1haN/v0Yz1ZCNbfFKWxxRmwJP0Y8qWgEqY8LQVgxNXp93e5YjSF/N/+l+34YGdUbA19odO0ZzNu0ySyEhqbEFPDraA6JFGf98/E2mQfJ29xPOkcNsBDu0+UgzCSx6T0SVftIfl8yDKxstzRsGvs+FvbeIdp8SIftf2un/L6LtZpo04j/BIy52jeCGJbm0TfJwstMIHGRjiTAKat/j3SZsceM0SmfmqLYXGAxsH/ljKRhPgMLkL3i8wLOWItIHHt65SYAI0Tm4p6AqlPdYIy1PVuhPu+Jn//sYIA+xS6LuQhpJdQs1pPi4mUpDRvdgP6fkitk3+6oJ1hQXQ5KnTkJVIkUS/zTlozKyyUD6JenqcqxCN8gnSWWFaxZysOrKpnasRzU8weuscDEh6G4utITm7RPypZ6qaO7YcbbKI+Wwwm3V/cvyLNIr0dq7d05cooUhZtQsuAc4tN+PPv6hZP8WgW7Fe1O9Tg2k1jq/Jv+e7yeM9Mi2Q8CxYtTx8fQBWgkBybyzuiNI3412r7GKBNRu3uIXVQ3BA2/fu2hbJGIYtFbOQfY69mbMBW+Mb7wQO0JKgRuC8kIwbjdUERosDOPVoRohmbBISCeQkZToOTsea8o2tZrHntwiS2VSG6dZVeGLJPYoH7OwJ44JTjc+PN9FNWRptwiF+h8VsHumNTweU+lYLh09/UO1FkKIqvtvRGfq6wtzbU9/+j2ThJYIjmvHGLeZm/+/Ozb1AXO9XSOrI5+1Xr+xRDpfy2jikpwJIu4n+Cx1lL3Ka2cQv2gSsJG9JO7B/VoWsFtDIaMc/vhWHTi9VxEn/g0WNFqUUEzl3zUyx4NjlOosYrc2BVI+TFGT/7PA5kjedFsQ1ef17BqBS2p+Gng3TP1KcDWHpYlYgW8TrR/kK8elsYWEysrDsZ3AO2ONDXgLLvkiUzDM8ZIKqY9ZElNIZZaWBOW+X0xSFVsepbDCEfIFe/mRlewOjH3B9LIw8o9QwdmQwkryRfoCrgVSY5veD41BB9TjAnn7/EfTRZdpIAZa+k/NMlHHqFx72xBJhv5AsJFwD++fWQ2BfgY9M3HM+w8hs7iytqlh/GlZWONdPe4UZrGkhcXZTguOaRiMdNpEClsSn9mCABpo9G/N9ferGA2Gy+coKAGQ1ZvkasbYLY8phm7HDpR2UmOPTcaGqsgus+jU4hEPSF3/nUjILV88ZiQRUcNnHCLSqLKaJzUfVfdvoBx+x+7aWCuIk6mxfzfOx1jh2mbkfCa4E0m/VDFU9SzKHtRRMZ+rqwvrWueaeXV5GLuWmBRFctwwVq3SN/On02J2/cMN1LLZzY7H/Xi5nurtlZ5D5mLwqpKJx3U8mWMPzhkiDvEX5ztAOq2KU+T0tC3FITSqF2qKa7N8jrfmbinG/s+eh5Louds9VB4E91F66UMN98uHugZaOHIvTcyEcscPXl8WGNso6DWU6a5EtiT3kGWJaGpcRH1SSr+yKRVbF/SJBYAdZfBlhAPtbU7WXDTIaiZ3hwCEtjrDkRMUADr3D+8NBjziIl6FqEmBH4h/R2tjqVosQVgZ7nOfdDGWcJ+V6fhENm8OKdTNBriVdFXVVUvXcvCrev5dLPP6kfPkewTdAdAXIn0w9Rq/PJuqVJbX8r7OGXn9CL8o+mUJeJDhJSYHxd5sejEiVDMxyoXh8CVzm0RoTxgE3OgzrsMi55Fj01D6JpoYg3Em7TOp1joDR0+/xDNzfF422nxacvCp4Nkw4gxvNsegJAJLG0cS5tzyjLkw7FF5yx5WT7lpBl8DvTvmX4El4MWHNMqOKaOIdFEDv7k9jRprVV+6o4E5BksuBoYHex9c4vSrC/7rd3Xb+wDXCk2pCBfJGsaYRgo7viUuNeTGk1kVI/2SjM2f/DGrr4tHJMyodC5ALgSrd0o7s+vU9ctw8/chM0pp6x6fIODB+oGVYuykNohfkzom2k7kdm6RwoTjubUtrGSyh1QHwvhV0/qT3329yDxITPPzaHiVGEzNiD2zyZim19Mv/qeCdaLXCRPUdjlhHKwzI4h3l1ui0DgH0mBznNuA388tPetThr42BckGHDuYkTyYZYsyO/eOnyMj0s3pLjQpQmWkpdNYRiHS1KFR3ShZf1u0MYYu6HoUsWtQTzDYBqqf02uJmiAzGsoaVdjBRU/tjAWWnc5fbGBssHgriZnTOU/iuX8gRa7+usAN1S1wwEyX2l0fX/HRCcZ3QLDO1ynm3l3mJd6xHzuTIEXWbal9eZmFs9L5QSeYDUBvzS1nq7fGZC4ckmkp/mkLcS7HIZdewsjbyC91aoeWK5aVCyn6igzHZlPqYecnhGRiIL+FY3ynoyhXr8MD6XhScppRet/PZrM79PtsdhkVmKaUKVkmo2lyvq+hB+7FTT6UyMNDVM3Hrjq/FeGrhzzM8EFGHe7JLfy0ET92GpcYpOirAuftBDK3qp7aMtaffwds+T5RW9yH8O2/Lci6HOY28GGWfsUIR39eVSqmfzmF51NMoOgAszSsPJofSVq8xfJV0EHgYdHE6LEvWhTgMaqwFfJ0/EBSso7xR70fiquVPI8rH8ovfjvr5Z3wZS8uA0sjLChSSegfwBDapsSj5W/bQi0J1SV07e/UbWgHVmk+XYHEd/gg4l1xJCggLvooacFJAKQlw23fXxImbpihBTKTLsYwWULIzMHm56TGgz/iOCQ6foZh9OZxoUN45tJnMaO4gFU+VWTAw65EJRYaC9eWqmd1L1KglclC0lLaerd2vIhlFLm2RyNCr50UBce580RjzGis8g/z0aHclIjvu6YwCVjl8WIVyGioTN6GV+CUQqneNGpJacpHM0zwMzFOCua90Z1rBcwYGkk0zXbCPSokIkGioBlkA8j6qCFjyU/TJSwlxnnVsrhpuaI1OA3kt5GE0LSVumEOk15AY6+fZvxWLwR3Xxxe1PJBZFalZQ7qdcFlEU+5e7AIWn+0JxlgxLtw9bCbUGOQkRRXWFOoNLUQqZ81D3kGd8oXQY72wfQe6tfZEEEen1+URoKhHmrH3GqRBZnaycWPwddbXh9sYINTsFIgx+AZfSJjTyt7mpsB1hDrkldyn9waAZ0mD2frTc3Ufsrk0M8l7MS4cGkFjHnroInWODyqI0ei4pW9K+h2gMRM1fUb/Hcj2sELzdGPPhP8nWrC/ezr/h3hUtTpkMk8UJhF00X9a+TVet4M4VqSYV/i58YDFMyMWiizL43+pJ+0D2y9TdrC5inbs6+YVvyh4egg8tTuBi6YMjqbqMrKY4MYYJiL76d2igubyVAZQPqzlXO5TGXlTQua/tqbt0n7maR9EpFKxkKxW3Cvvavq60iSSJ1QQP9X/iQNdiYiQ5LF8Br4DRrMwN8CzLN+ESrlm+7Jo12d3WjQMmWvMGsu47ZpIklJUwA6SoAK06wqz7U1XN0VaTtgly7yh6ZvFddWD6djxbwXsMSSiCF3+HYd3+2Mf7zOzV74GN2pRwzsGqTvFwEZagaE0u5kq1o6RnniIu/WAT4w8LgZAGAuFbUeC58dy/k2XCGjIsqxJ3CCc5RP/DmGQR128yFYxfA8PjdNbn1Ew/sa5XMIJ9wnNManPrCp+a/2zlagDLIZ5Wu7c34kPWzvRoivj4FGfyhA2v7m2wlMrjEntk5ecWzSgRKfV4FIed7qHhRu5aclRd5M8l+6180WXJ5HTYT2plZ6KLluhUC4xu3pUuvrMw1rN/lHqwsFrtwTmikdgIBIpgYTiGtuLkgz23aWn3y+ODt7LLp1KjCGk1urOpV/1jWvK5LQ3U4nHTEj1MYPvU0Yp1ExQ1xbisgy6x4mkKU1wmGOkllewvtwtjO5sYVg4nNXbAIubqHRIiijy8toTg7K4EkJkDJcZkWuMpbkbk8fI5RTJ4maB73tkoMcUSjzDErvTXxF/BU5+dJABeUu0BdWac6mn1OJudmjegbqE7PkbVu6kvkmIWsVVWadv83tiWWRoEvF+zI9SGzJHrQix9sgirIfzljNzjAgVpGQk4X1sUCivp/bKrqTNFQ4TMoMRn+wpZs/3ORgK4DvfcYgLXMuLLlOpcyEXAuDoPbzajcf5vk+CZ+g75sdDXdXrbNN/Ad+fr07ldJZTX8vrsYhEuTK+XeWqkAFYDihwP7D2GICVNMenY/LPL7RTCFi4JQbNI6ibMnyTAXJY7v+j8yLRlSgZ+XGvFwa8F2pr/rCQuUoZktA/VtRYH5Sk+mi8iv/8zqfq1HABDUB3giakne9gfyAn+XZUheNGXUNMEKYWIMilpyjjEIfMAxC2pErlP7t00mk4/ykMUriI/y+8XwoyXXhrfk4fUE83dJQdGTGfOCon4vySsKkr5zTMgoLvRqXRy8e1PotMJOPadJCIL89iVfMgU1+HisiydbSuYDXz4Rdd1MNk3eymTmRQpEH1ZScovOGD9MvQ4VDmHvuHIo87sbAIq+UUAq3P4n9w+0+EXbhr+N1zx9LAy7wR8D+lwTTp5Ncuo3N9RzBnDB7CcmDf6dvSFwnWVShVj9hG/DO8nmxQAftKwB8AQ94cUhNapF+OB7RGcIPRto4ayhPiYKJjkFLplUIdwkUzJoMdYkIEi4ev3wtYUlskZWWu72kT9E3CofCUhVpJpnbvueRjyeZtw17CRCDE2CGSh02KgIO3cTNQ+BFOlbkZSXzny3LZhDNJLIaFQNhOUsl5pfE78bcp/g0EHhLB5gPT9U9O6S9eAfEiZ/JHWvAt1wOnSy3DeFuG/Ny0JDQdZs5rayw3m0xH2p2mHojbJsHGFEECssQVFSJ42iA7e1s4kHcXrK8nyd9+CpZ3oJnIaN3Iw3uGTYof2SWSWeKprvepBwUMrMFGvOJF216Dh5NXfXl66SJKk+9AD9R3gw2hIwma3beCDcab2+Y3YRR+Yp2l0D9t1GjTo3eAd+Df+bbiX1Vt/q2l0AKX5vCg9Y5eKC7S8YVMFc+Be1BxPhlwT/znezNfAqWfOcqqzOgJPTpV3yqlYGzp7+rGUSnxJ315pphjb3oJWzUZAUOX2l972iD0NeoRonXUoWN6CjxnYk0DhJ3JZgWa1qadI2Emc719+fctBmllT7IrqcHrmb96xKoGDMxSQRh6g2FPD8B2BZzRy7lu8shPPk3iRjsFLMrBHc03BEEqZJYSaHT03TSdO5k44d1SnisKHWoA2gjbyF6Sl3f8PHCk5joeSHs5Nwlsu/h63Qv4oqrjjacLOTbNgc1i5ZA9+9/Dh25m+10MEdvlSfe0Bw1muv6ccfIbMHjMRzeOeQK+w7PITaqyBFDW/qFIiOQAT7i+5QGeX9XjVm2cxjJBv/Bg66Fapn0TORvxxe+Ezg+qUGgKGm+r36nxYEFg/5BNbOeaS+epaV/YXJzvNhM1G1JviTf+eCo/htNFe1TEXv5t8zVnIVckZKrQSs7+XNZZUgLQM70atTyc/6or1HmHaELudcAmJFrfc28Xbmom+bU/+AaKyQQZhsg9E3ja2DBC5RqQF50INT5gSc3LQ7Poq7BIPRlkN9U3qjIw6JhBTfTLFCscVgKoXKfgUnfH/uc2pi6bC6AStvkqao1/+5+rTtw1zaDjytXtJGoGeoj47zWrI2AU/CIMU8X4HZgD7VFJ6E6EPXfr41m7iKpxC1wczp9ae1/n9KvBmDOI3ROT0rKrjWgsfhEOz6OzatccC0DEGNlmYsJsEDzBbYvJiJ68AwVc5YI5iUlu7oM09x2OIgEYCVW2MmtGHeC1nT4850ZTkUh9qLslf2w/Vnn7C7AwlPNNrVFAzpdk382/3YGsX6Kpvl5NK45qF+BQrg4eIBT6rkIvTiLsbkedfABD1xLXZjae7uljoWvE8xsrhcm02rVhvempoZKjK6Wlq2HMKCXWGWhUN7nGEqHvtJEwY4Yf5zK3/+ASbqzc7/4h0Gj9UvM/000g5eIZSf+iV6NuI0yx7JC7D3xNTJvk4vgUjQqQNiGBY2qJd990H2QU2bxbvVE75nREVimmYwRq0lszI0gPLaR1JY2If9NJhqHy6sz+QdB96WMi8L6OvtaP2zZyK8krZZqkFYE8KOPMiYTFG3y+EuyN/NHpi1NqYnV8ySVKY/APRvEEbATQqE2g69ywwSbBS2bDPvUYY2q9/9pJnz4Pvr8843PUjejvFVNe3v0T9GhF/Ze1EYnWWSMewW1y6lopj2tap+UG0J2dAClHw0HJo+a+BDgvU1r16ATYV2LfpGuAcR48xXZtlVZR+61908S7iIApePaH4BtmG5fnbRXb/cny7j9VVue5/GSh7ZG5szvt2P4SpYoBXdtD1xaD2eCjZVlBCFZNLwBS9T3snMvaVmZj3qfIUmCvlpRcAzpMQyrAvoN5bqI7A6AGAkd94ronl9PcShPYrd0eCufgIz0wA4SPLKktiNMUzTTi1jGW4CXgXlFNj5XdaVJFUcw6aqKGNGwhH2brT7X+Tabof0Yz+4sMaZyaFIZc1wvp2lRe3IE16x53GeSSsuZx82/8s47dVTLGklRqtVkF+xLVNs8B8sVy/6T7CZvXwgn0gWgkQmGPqu6ZgLaRISefRiQ+gMOqTvcpYhCvOpIjhV2G6p+5KMteuCe2jcCBSWucTKVL7OYu2R3y+6sqsnf7NVRUHfQH6hRuFvWm/Z+OhIlyXjlRQP0dquCu634LE4GdfcQkB0o3zJS9R7ngJ74xnS8+fAe2+1gWraswCuGKPDT97r0dzqG8DKQdPwCkrEEJySuXW4TmhF+/ufJT0DDBSeXy103rroIuSYXtrr83+8WIvqVkqZKOa4R61Fi+xGinklhChOXzzJeriGV3KAVN3s5NAI5igEeKeTBcol0v3NF3LbYJ6qeOH4wEPmir0WUSwLGWPSZPaukw2bm3ox/OOOHLvqgLDsEmljBZ0K2SGck0qWld0ALKjKTsIV/d57uy6gzmRcd/ut6IJa8pEWcx71wdx/z/mF9ndjZJnEAwcvlbC5CWWYQ/aNDiRvJcwXg0MO+TdrFz4pGtxvP9JciRlD9+qbuqz9X8varn3Zq/rgRKl7iUWYrxHRwrgekEtyOLqBxw7hlHT2arccV+nnyjnwWYh9FkAEFoL2BwCYYJwvOJYllqiuPDL703QJz7hpox34EFNLZblmjbva2bfxwFer7gVVwtDBFgP9yqBPgSPTdIIVKYB+rMSbb9wTwpegH0wu6zBl71io3szajPjAg6QssBbD/9kkrmY0Uf2pQKU6L4kPWrY2GPvfdE4cGO2y9K7o2s0FLiinpyOdYIkBWdPUZwkHeo1tp+0DjrYu8fqm/GhVA0BnygX0nZzleoRaXI6/xkCEfo15dNuYpIEx6nydUkQZCcBr7iK58shZin/4msQpjqRZGw1psgZKuuD9dbfnVmRb35CbyJm4DVNJFqvThz30vwKXCD+NyyzxusMPOhRip33yxioqbySddpURP9c2uSQrcEhm84Qrczim4HtIpTa4SGnjEkJH1aGfUiJ1Ge6M6DG79vlouW8cUr0D2iu+9ODq7Nr36aDyuKWsQ9kO6gteJRC6qdy0jurO2z39HK2ev5zR9cO6N1bK1xjTS47gbMYgwCeAxsGikutfOUMWryCo0CfikGH4qmpHkwmKUb31TidIYOJeP9iQfZo1J+cxtFLXSlKCKUdDVVOuAHPUKf6rHKmHkfuardPybn1RXRcSzl5tES08z0NeTxz+5tgOmRSbmtmvlpsds7vIQF7zoRSUiMStnzrGNMLdTwk4CCS+5dRWsVHH7f5N4vX7Tmy9J98yrxDTYguZe+uGVAwumzhnvIdapZmvSnbE1gXOr5OyA1bQkjMZTTSER/WMKQeoSuoc25yz1dZkckxoFH1wWt3oU+Z4Z75w9hGdGJJBu9qMJqgE4S97R7/PiIf2JiEBGp4OtR7At8dc5cVIcsc9puFPV+5zg7UAR/5UAmHqymfEaYbACunzQDaJ0heOG2Nh1ndbFU0dkU8NxnVM7Jo+hHfHraef72PRn/suPw14RenwP5mVidJFX+jcroVoNrfGbriJddfZRHaWlH1hlm4YnVpB2vpBOBKj4tosQ5M8uSOGW33KL7WCYWiZlrcEyvlTlFlymGwj9pMEKHZDSABmcGhYlGY25sZQxW1vE+JFwbRI20WP9uSH478BCN2LEWCZhknIKf8PYJtrdjkPCigHdFYthiN9W7UiPvAnmwERGp7PVn/jQ9xsoHov9+Xa8H7QeiGD0qicIRx5O0A32iG4/UWOal80FB3Zn+FJrnMy/0cljc2YVwrs7j4R1O+BGOJLCOVcTnVu6JZ4V1072deOkRjkjvw2F1d4txBapqr/fJ3tcrK10obUGu1hTKK44eyzREUXK9jE2/HumpgueZJpmCYIpu8ihObvSZ10zBhMgPbDkugpQcYb77rBcFoUbOINutTDf2gXhcaVMZB1pFkb8E0b1kGYJuIVJzgbHp+ZIG/eeipNk8sOcjC4W43Lip41eMS0iQLCHNxOmlvUXFPhV9CpoAS0RE8+X4a372HN2mqV7srIyb/9pRcNRGPGhBeHeqa0rt+FSPmqiYe23lKPXYiuTHHqcCtkbco+pZ7/ByadDLYUO9tcAJZKmPmFuccN6jr10ADWVNOhJ+XcIdkTaamLruEerE6PG1nUbxI7POBvLHwKFA3a2MDwX0t3gJqCTJ89/wJ8sJGUHou0pMd9bZs3IbXxKK7g8RBvb5OIJy56jKcoCEli7KqQVprMOmfvOn9NvUCb0veK5nv1rQkiIC8plrJSquSEcjC5BGTTr/C3ns0H3ZONxLaqWvCxRf0nfH8oQ0w/2aQHoZg6SiQMkNp5tKRnxr41eaMrnTeHBlNBFgwjnUlSt3LVCQzjrsGUHTt4TfqOeI6a4SWK/aSu74RwpQLGKXaNtWtEWYiwVh8xzGnOw6TL711+iTwvy8RXcG31pdutVl04/1qygFMfnWm8g+zmWwSGCKffKVEwDa4SDuKqNi/Dp4qx6/XfoOPRqT8K8F2wTsSpjKLQaSoJzrlMbkP1/kJoAaSaL+xD1cdMvnOsNgkDcoWbLd8yT6GC8ceFEPLuZFBbMTHVtEvsYVlhsN/xK5PiDEviFiO7FnKF3u3oMTrdCJEUjKwNi0oLMEPMW6/FYE0qtoDRPWNyb4ZgkxuFVXbxlGAXg1rwQEjuNJyd7jm9oufR0FJQnJW3olkiyrDLtddQyEZjh+SeaZ9GFOCLnfi0smMIg8mGNdJP6Vx13G7hiljqXFeI2ARbbv9DCCWiSdHCih7yzDyXZJv5S9CK/zPojDOhqUJJA9xIsDLeknBZWYXIsxCJvZNqFExQvQpBZs+qt/r2Tu0zIX4RpSP2pp01IwNT7O8J9ShyVSBXwO3wAUm2AuLsd6hhrP06cPGOyEQD64qYMp0jHi4PmuqObqGzJieY68w+gqL9TDOk2v9mSiyX86c3qjMwJPBcpG9AEiyxr/aJmiAfIYF77OOmBrn8kTTLG6yA1fMCk1rtSt9DBjHlkbUNunWsjerhyyw0tAaIMDT0JaPqgzpILKKRwad43JpYLn1yDvak9ag38+2RzRlKK5iuyoYkftJpEnHrl3ZUuSFzl/Uzo3wKUJYC86PLqXnvYLJhMOCZjNV2ITk6BA+b3BOMhE4WCTC7pS/TcJCVyPtA1EjKr4oMT2hwYR7904XXOJifoVsm1XEXV4gyTxO1r9mpXx+mzZt91SQ0JhSECPOKdRBrAoJyCOWwsrHyIcrnFdtTB1dItSHboGvnnyMWiyb7kJeZ2HQnu29byGuTEKwbso9Lw8mzuAA3SDMlYGRzilq/A6deHNRPffc8F2aWIkBWwm9esJhHrvNNJmeTt4mLpURjJheSBHuDiwFo+h8esHfH0oJVyGnAfiCFGuYub4KadMGfw8vdM7JS6igAugXCEkFtzk1wMQ5as/uvkq0hNjvAItHE8OJqYwOoQJ43etG5YVpznHuU3IbUtukZufFCuBNgyiBvcp9fSkPRBCm42XxnNNpvaTqzW9AsDUEgSu1VkjILB6MjlCD4Ol0FO/U62P6pvmFb6zm8V9fBfDV6J9/R6YuxP7OwS0t+nFSVMfU6YEszOKnDcDkYMimHglRahn2RTFvgibRCXEK6q3n13rOkWx1BkDpA/IJDRFph/yq11JOyvPI08Lcyvp418qAd4SC7QwRIJWijpR0vie1Gu9RBmorGGIrsRy9QTrxC7Ov7PRpl3PDjUcO7VdSsX/F16bMnvYhqC632yYedzBvS5eUN/4uMEGYZdeSVXBiK0TWA00XO+nQlzUVYDBn8k3pS3kFAjhYgw4LYjvU48vrIrHPeEad8xiBQAiX0V48PKMm54q8tHXEFvUsQHnvvTUks0FU/5AIObfr2JNSqfs63DYDZOFLnxkgSH8hvyknswJlZOQy7cihFy4KqvijlUvfbYYitSyZt098LlMNnXJ3YQUG4XgSue7XXXjgzBxndSbuj3RiIch7mml2I7UhQvaDD83z63yDaIFxIynVr+5O8SbSIO9lRGHLAighp9k0QrwLhki7+D5LcktG94bC7V7ZWPmveCOUuGWxBafSGWlBrn+kEYLdRvkNBoYdcWAaToT6B6VSsFBfZpu+udGsevdIIc2OlkozZaacNNQ/LRkda2I6Qv3iT+xrnZVFZYtaunV75Nx/WRjef9g7hkZmFlg185dYDV1m5WyP9fzyJh5ftsX6geyOVEZhJzcFCsSbZoyrdEk2ZFlnwmTB9uKIqEILLrrHX0+x2Q6X7ZklpmlsxAb8JsvAotP7k9HGiIYyrTGtEVLqqhu0WAOQKy5B9kAvXQ2rs2Am6ndNhYKH7vCUuEX4z08CK4ErNgS0JV+Q7KltOjGT3FOi77rsIjgStW4XwBrFawenBvZVCpGcaI+yNHv67kgQuXQPBZEKf1PcD/IN8N02D4DgHrzfWKMHE7vhNlVtTJvWz+/gcQZxTesoDRFmAv495gFktustMzO3B8gd6m9BZX8rNmsMiqeM0mUKZaCgw3teQinP2z8Etb3TASRlm07qv0tN/d+u/vEB/+dqIaiJtE/xsZdMhTs3xTnhZMD/Cf0t0kwnMBHDwRtcGQ46sb1cHW8NbVi0MM8tx8EHTS3yCFN+JaWn+uArm/Gb7eCFU4TwIWOTy7E7PG3JixH2FuMPH6E7hHmop4RHuaWZh3SWCZSjV3luHpKqX446jgAfSlESOEojIpdDOdB0DzLiLJWbZdbSuv3UgFUxMseF4x8qQLFdVnADufgmQzuKp6SLkKNyUnLxHJy6fapB1wIHDIketI9WmYxTGyC2LDU1ubaiPrWNB/aHPe22xJNL0bErpWRFnsiZ5z+ObCI3h4/EZlHZSz5kT0ljY9qYBqT9kiimQkx+vBcnMezyD8jH1gWIgX6xnNcydhtKQUe34IK6LVDxSAT0ePclhS1mvYK9/nAkM3BiKLB1Buj2zcAosfUCKAxKaLdNM0Qq7mcLZEL6RpLKXYIULp2l4olReFNxqBHw5qpkBE1jM2QERMsH5oBNoHhEbqYy97XmwTe7qSdEBgoiSsqOgDO9LuDnQx2Ol2MPvldCcwsXlUX/tkLYln80NbhA8E4fpI5DItGQEzcqfWJwi8+pUw8509mfPu3uJzg9u6KdOvb+6SOHP2GeFPh5jr4r/fV3eihVOfKA7BZxMDYkch7M4+ZHPrXc0ys0/9AjVFgCG8bh/m/jwBanq4UzkhIzAaE8m2KQ5YUHvcdeX/Dcm89v/tKknKZRdJ+i5lNZm8Enn4wsKtkHVSVZqbTvJxPQwyAAz/dGw4WuOa2nDIeVx+Gni5SlB4JHNqKcOSbH/y5hRBoIh7IX6JXALfpdpO5yotIkjcFh7jWh30yOXCPBC1lfQ+OIxzgrosWmpRsIHbBVD6zU4gpHGmmfsEb9vtSCPznrQZCHZBN4HT+Mo3pJVMzN/iTPkUfcw0wUh0M/wr+CJrlqmVOu0YSyNhPQzf4Yf1QL+vSZAG5xOV5hPRQV9aDwcM26yEc+Z1SfUzF381PnvP82tfa7WwgrvK8tEW+Ep2wbZ/BKZ6hgAEbdTDjsXG8QXqZl4Gz79CGw6TyL9gOSG+IsblRtqygHcfYJ50RHMKJdGjAy49P05jRPDqk8IZLXi4r83pCSTKGx2y7G2KIBKpeTxwY2BPLstfimoXXNe4rn19Z+Sqiw6+anfMHryoqHvmUq/b5Aq+Ie0Fje6E4u10LX26eEjsv2eUbajp/RV3t5H1fCqSAEI2oLQyrb+9TEScNvm2LuAP90C6WaW4rGcJksqv9Hj38jeD2ljJ3DtGIRhPMjQb1VNImVFR3DQRntpjJnpaRS6aJ0S7T815cKTXj/xLj0uNtZb2cMdB61dj0FW+rVp+hkm5p9TRq9SrfGmwTpa3J1msHYvzSyV+ZJuQIr0Sk+OaUlWP+2NyADAE+0SUioQxua8dQSrcTviKMnkT2gMYQVsnHaWAgARSy+6bXleXeuFLGlGo/C5FqIommSfQXvNNioxdtn9i1zRzfuYUIxwM0iXrw/l6M/xAakMCAIWXsMpRsl+QKOW4lKfCMhkTHekLZlEJeMoMziMnSpqaOAp20UzjFTxeGIa/TyYIhZIruDz/hY57wGc7o73VSR5YEpIoeCmCMS/5Q2cWJut2l9F6C982KpgRK2HerQh4auZ5B3Fspq7XmkdiyuUIGYYH8cmR0l2+tlkolxIixjCRb7YeJH7phkCMMMxbzOu9C9sCXY6Pz1a4Nn117qAtXZHGTb+JMYla4rK24EMiiA7cC4Y5qGR5Uv5jCiLXe++ntC6sAOsTh6OLoGuEJAzEcFAgWfDgoW0QG3Az/RDjE0DFHy19okNuWgSUAkVW7lBnNCK8lbMDekez3pbXG7La7zrNrN8C4/voF0qO+2o8H06Fps2snmoqW/dw1Z4HCCbYCC/FKwFMdnn2/AXeKZ7RZ+wWktiUczvS8c9ZHqLS8LjZHQAN7QW3+oeiYTwceW6WpOPoWhFmx+ad1sSU7+Ol5aRkflj+1/Yk4lBeWfAuxOLzJiun0qnIHzc8AxcUDptcRyaU/uguPprBX/XeoTSoiAf3weIQ5zHqVzeNzmw8DruafIn2yUdMCQhZ2F9tdwUMsMnq7vkCxx7zOZrbBb1PdKvBjAglXezYUx4LWjt4bGTbJZY9FUi2DrMGDTUDDC/nmqD65ghhDUyF2piL4zwupbS2fSKoOYmy/HIPRl+Hd2DVW8qkkgRtdKsirKU8ySp+yPVXENxHWTArsAjsoz4yt/L+3VxhAIngQuYEgwrY8GGeTz6R5Bvk7O9arvSUIzm1nQb9hEJD1eso0ZthirpxtKaUBZadcPabjaiqEskRCubYUfSDA04WeE9k4KG46LVxa+fDh/AdJKfQH9/WKOrLM2VJGt8ZkeOW2WUylxCFAFuaMTdk9y3KafV/91xystukVcE4cfF3Wo7r1cnrLCfaKt4I/lI+UcpSZle9bcKgeH6MzDPGlTsaSKNJMolHXJIYWYoL114+4ciln1e4DkYO+3yq2ycTBAMt9hianhnpDBevnqb0gmk5N36cOSa+EL/AehlFBCMfMVLu1HB3LYKTmnQ8o2fzKukC1dFzDTCYyhJF3aYGBx7itJ69Rqwtipw2RJjKK29VljbqvgK1YRlnXkXcjXadMCFnqtx41Ie/5/xVLISFWJqiy0PlJedTxnRHI4QhDDlT2+TXvTXu8izfFyJegY/CYhSAzMg31j4vuSMMQp5HlDM/m33+chEgjKj2ipn+yDyjnfFoT6BFHsDWGTY1lGffwY8sPoEvVTWH82sBm+5vaWrD/nLstfo+IPo9l5XrLKySkEltZdC2bJp8yexY11SeYDESatiP+hHh71GP626x71RGH4m50BLJW8fC0vGnhILhi9ZaS3IajveQ6KS+Pr9StPvyhDSs2VC66USh/nheqwLdzf/bH5wj1d2fHiqD4WWEChzvbUSzxNbXQismBr4cqq7SlJn3+ueXm8jJITvAz9BPIf0oMSnyPYECi41sEfGFPlYRTrNkBQYKb0k8412ZH6YIGBLw4KyZ5JVDBpR4re/p9UBxTjUs5DhILAXOmnLHu1lMxBoOMnQlEKlhrKAMqy5hGkldnrv3mNjndlRmTp9wDRjrK2+XQSElvOSQVcSF8qNgFQYOW0iQ7QfGKm6Iycxb3Rr3DMZTfw6N4gU3aXiWA1q+T8RJ3NjlLtuTrONA+UwugkPSbxJJogxZQGNW1ZrmIhOgbJpNKySXy/ydgVh60vf/Yt6Y30sajG0gCzfOELddFZNMRqxtUrJpwVJ/ztAAU85XlpkAE1dsU/Fb/0+vx12EAaNryZqhfEV6v2Nlr7nugYmyI6EklZHWmx6CFQcXYqDBZ6POhddLnU5BqEVEEY6RxO0tz0Kf2qD2FcexmEDzuy0wtKEcJKG7AlvzFuP6OtfCwceamdj2oyEpSlL+n+4uxpA4TS8rJIc1ncke0TD7inxB6dpPpseCOCQG9AP7+Sk8Iv2ZWzU/WR8yKqutJBOozhL9vhjs+AzCL70X7hUgHAqOAqM6zLM0lbvkh6if2AJHq+tvprLe94nG2mUbmvn/g69Mqr7js4UvmqoMqP01NwQR7TEbKyY6yU6/HQm+d4ZlSfulGwvDZg8Ww6jS/lu+SqeyM31hpFcEnYnGwQp8/UHZaA1iPMnGr4svaVAwVWz1fOB1yOFypOEp8NBodYZlC3vmBGD/HCJkw7yWBDk1Un1Q7j6lfdfEQBSn6ZrGeVMw31+xtKZeeJQ0NPD0IzFPMHnnIjeDCbCLDUgI8DgATn8bhBKs7LYaRRzBvXv1sxwhIWNkeLGdePI70DWF9PLoxvf/Zfxzkish75YBhVjHOtUkD7D51lwHQBBLz0fQfINd+8Vbln8bjiJLVDGmqIorUAqft/elnN8B8jC1YuXghiUqVzIp6bjqV3EZCtPFa/oQMX4I6tLaRlTr3zsqr3F1CuZ2NnbL21GYjTfa1j22orB1rnhfLkCIdg/5JJ359/XYE+YNrGmJUn7sg5f87jDHwMdtnj4kYqU1Rx39Uf+W/7mZwpqWvOMCAieBWnmUpdDu9Tc/mF8cwi3e12Msra9mGPwugWy++R/mYMTEnSWg3tNqYhs8phgEdC5oZ62of/hH97y8Ga2J57CTi7gzCxbHZHcof1Fex8ecXX8h/aKOIm/LHvyvwU8+QVBapTI+C21Z25w9Aq1YsCtowbNzQUtR2UV+ExG4AvzsBhJQo3eYdAIqmOEFoNshk9Ybkf2Ni/slBX7e197gMBhIAOovgErZjaQuJU7C9do0M/kBwkw5tGMbJ9x1ZjgRwZfK9EZi/XGAKOkg9SnyC2vh+0TOF2R49395wBrZ8SPwCaMmi9SSXP9G3PsmcKwJxjtBz0YUv14RUjpb7jqc7P0Li9hGiGNDpp4W4m0a7p09ySwoppvDC0jznnWbHgkqYb7jwA2PSGF5sDYVj2DuFcPVknpweQZWlf7josBcPGco+2YV2S8/y6Qcg8CVyeaqMpM9auzOWAa4neHDaqJC8X/5DoZOGMx+Bf4tQtHEXi9wNbMs76YINOC4mraZcZrwrBGIsfyohiEvvOrhUK9TawQuq/BV/fZWiwYnS0JpJYw4ylNju9q7nhwHfz1MKR+PHxPjmvfwsVuNx3afJZhQDxGAOeMyn1uh/W6NdOYaEZcun5fmq0xKkUR4fGWBOieQSST3XULw4ToxMUncij8Fun1tjbAPw1CIV0xA3da2ekuDWjjCKxzrPzDHR8/g7WXycNN+FOUornJo67qtbLk9P0X5+e/SV8JceKWOHcT8yy/ZSAs8MlpuQhsqajeeTY1GdMLfwpBoYKijhMlsIC8+YZmFJLkKKXWcfpW/00O9jUBjuz8o+bBizmPwCwjAOnIHnMvYttkZMFSDTR1XuZ/gOzApsrDfXrgUyCkXccBGilH0UbN0FsLbGZ43+wpBXyClpbDEMIs5RvhleiiMMaQj7utfO+eDRBAI2v/7yehm8TrXpgpbcuvHpe6NTY1HxYerBDFI4JdlUIGk1zClQOZfihnJTudXuMjFZlxqeROqj/P1vopZLAUalZA86NDdl9XhANTmAN6+xWlITnYvKVfpUSgYL05chKraqCjKLTE5jFvG88M6/enI7a6gqyMjn8UPIuYQB/hGrFXh+bsBqlDCVnTtl9xp+9DQKn2hW9OGNRrScqFMQzsNMOzNBHJ3pXOh2BQQ2Ol84CLBcigpT8hGy6E95H+2eNcUzSNh0nTsX6DItKZvPSkTSSUr/aBSbnxNr8cifXmta9ANOy3YhyJmSc3R70F3l7aR2TT6fc79Ev84fT3mo0Y4uzQsWb96RpvvgYLNHwAzsvOY21cMIyq7M/wn6rObLunt8pgcCVy0vGpHlJdiAiRXQFijFP2jksXzPnqugh7QYWaHHOsIPe4kapwqLaBPSkzJ2AFF3eqxl1EdCeKc/CNGcNkkKJqLpZs/xI1mK3CYZLmx12ykklxC+2PeH8NORTMDDiPcSlwLJusGLDaSxzAZSlkSmkJI6+XmHsUA9F5VhlVPP8i9CEH+nOMTluAbcsArQFFolTnV5bEZMS1AkFD9XC7jnW8iYUsS6OKb91pePsP2wnkE4fj4+hq+5Jl1iYXSkAqZ01KO04ERdQhd6uhonRjY7D3A5aJtfUV/ZnOPNiKkTzWQq2uGWKzifjSYhzUKuTF5IK18NX+pi/NsVFpHqN4LUpEgSpHOnUAHnhYmqWkwavGKhaCqSnNGlIKZzjEb6d9Ae6qfh4k3VA9sE4Y38mXgiL62MLn/bLjttUh7aBL9vddvkE+ySA84SQVq1wMoIt/fCb6ekGeiPnVMRzOUxwUdwkiDViNlTxe8szmG4m2ommFz3ZRO6BFckCxBigb+avBig7kNr19yBGaopu3X2y6cgeFQ3aWXYbjfz3tnpgGE9ifvjxvuoDf+szRQ3711Pz0XlE19wgnXoEg0ogrtRoax/hjr8jzndMb6zs0b0aYl+npgENayPxAWCw34KCkNt+J/LSZpotlZuDh8Ng941/jmNMHRQrLDYElo858B0gfswk8hg6hTmQbuxOFS7kAA+nZZGFh1lbGyt/ri6bNsRscSOVJswx/iQVxf6cLRM5NLqmaw2hVkdEVVb+GlXE4p2ywoTBl3g3LQG3CdG0oWQM97kaf19Z+MyxbfAuaRvuhJzFuQ5G3mZWHDlAppNc9a7tOtXQ4dECHaAB3+D8tnI0vCV1xnNQmBlLqqiHdNH7zWnNwmkHG8s0l04XUfLK0CgUo1CmIPBKltq3VHeDXyvzI6fnaW8jmDOLnoJkWzMJcaGOpKC4skAEBaVD0hur+cuPNdMqI5qC7GFVWp7cPR18RQtWJDIe48r4jGyQoxgWbj3+oyUJqd+v7WIMOlnM0bC9NQGzZ8960v79X1GK9a/NdnY850cVwnK9vXmf/JBKT9yzANVw+ZWsMJZEaNjqgNigAb5BYdZu8k5uV/1d8xKMZaq26maPG3GguP5Y5QVPx1jFZocUAO/ycwFCcA+Cg51nFY/bD8N9W0etzfHwDuKRZyrUeB6l4652gMgoXFEf0HvWDqDWsJZRT1yoLi54q6IlqxJpV+FiERzWslJRmhQ2NIELEPD5g6xpl6hZVum7N5Zu3jgDYklYkELu0BjcFmWx7l8nXRAcq6Rc2CFJrmXapH+Xf9ZvCoNwuQrjBOvmx2YSsYckCJYnZqecVkJQXMw9JAqH4TRNPSYuQ6RnLui6uMFpsOJdzCUPQNRaXRo20qFWzpu9QSJ9nrtHv8FDHEF3eLafTR2psacW+8jpuYkw6eIAMtmybK5GvHpQebhaFN7YakmC/m7Dg0tlNeHRlJcn0xKSXpgRc8Dy8exoyd5BYyrZgR/QJbOTa8NWpe1aLT+LZuhtoYKFf5JAgYbgXsNZqFyNv1+oBLrh52ALEHhKjuDJe4bEG26vnAl4YwaPY30zdF34/fzsncJOZ1JgOJy9DxH0l8wrkXF6/iNNDjr6wla89ZbPehckDHUuE2h/pzhHUomnv4jHHti2xf4xFKq/emAGjxrm+X6invg7pXTkDzzDMh6cpG1J08hV9JGs18J/wfDtm1efuqxpNl0WGleZ8VZmLaOBv8k2cKucbUvxvmB6LWsXCp7v39o6syyDxzOBWuvVLk3GiPuQ+6+N3UgTr/wk6gvVmXGftVkns5QN3ylEYSuHKB3a5dfV0pszjs7Kzluj4VkdATfvy+A6FMWzQVqiEh6uJ6lkjpQ1Flm50RjGxbxvjE6y86pmnKEoNGTrFRgdRrSOh4fjiUEQyt1bz1a6PIkMEJuHMndi43/VmEMzm9yOymDNsmG01Dg21yXhnyL8ssFmUGYG/VWZ3mCesgYfSXhdWcWem975sNEEvlq/fwFZJz3bmw5FRN2k2gIERoe+hjCY6kKlG0xSWW+o/TKypE1OBxzFWsyOmrTFT+Zwd5wodJ6O94EhdxOHUGO9e43Kr9VKvYP5Tzyu8PYSQ0l5ZHrgu44OQC9htVJCs5gFt/FuK5YMd2dHMSI14SIGA/1PwEQ1zXwnriOqxxolXg95A+So4KcokPK/AlX4WsIgaVyp+apPYjmfY+qkKVy0nzi2db7JrXJj255A6/B3UI3iWnvr2OW0ZXCJKVSDdQvJkJNeBkxGC7Aa8eGJ4sZbxlZrmo/SpL3mqx/54+7GQe1eBElUV5jmHxQRvtLDdy4deKXqHS/+UlGinKFObiGZLI8Qp86Vc79amkH9wR35Gvn+HS6PzTiohzno6xxc35PE+fm+cOxWxvbktyT+Ev3oHMOCqgioUyZwrNK+z0TggkZ2u0WzZTMn+a1zrcNnLIT6HmdjL+EQHn9qp4KxPKsHyjl76xu+V3pzrScSPaNn8I7wzz1iFi9ow3Eyprvr/ROEUC1mAB/GBfi/HoDqrEalibO8UZq1EV6Rr7uGw1czllqcTkd0Z7qp1dYkGMTA8kqO3HE3RFyWyN2Aden1QFpe2gKxjwWxyCjj5cQhTazf2nXAMOefDcipEu+d49nzzd9IMfdWtqoKeLcz0yRXBYXLwDOPWePbY5I9/MxuZqpzp0kjVbiD2JRYvSIQnWQVkmxgec2nfJqe4L/FHlXJm9JEvRFMhZcgOdu5CaJDggAtl+XQZVQX9iXOsCP5HBdU6VSnbBvq/cGduJEX0DBWOLpxMJhuN3apaD+tzvUj7OzfuXG6CZjvtXiFdXCbw4M0/tM4wqPpPi6vxwabaX+7Jt0gqyzvlDVhVQHY02221HrRAX0quIH7F35qKdgW0448eIXCcN4ZkV7Lpr6K6MEpbaUKWYTrByZCGNjy5uVKZP2fsA3D06gWC7eVRm9SA+uAbsv/b0XxUjvps2Qempz8hlrnPCDkr3LCBJkITrG3kzRj6rvk3mALy1sfP2WRXh9t2TEU97FOltuJ2EELG/OpmUIGjDRGLDBzY0OlyH5zjpiAfZGYbQ+LNkHexMz5J//UbMm0wme8w8V8iCbQoXX0SjjyskJDv3To9Sz6l6y5OLbEAcCoX68J0fh5xuo19TuqY77JJSeJOT9gt2esuqxNKveNnXwRto1Ah975MsvTvTw4KLUi6wt0mQYBcl58KtyzdRFJGRofQYzduEok+3FkNXjsE2aSd4uVegZh60/zV0iztmm5ZBQ/ETkzF/ssxbqkeOw9+lRyIluL1VaQxCIQTKIq5y8+fE48josyqacB8obyMqPRwJ/laHceHBNIJxwd4l8IqmFXgCMReh1QxhXn7y6CNT3xBVwLFtoq/fPBlGFnbSSqZz97aHTYjd1A63PnNzVLbTuow+m29EzCxEQtguTy3S1ivUyzuTvgvN5vDqejNDTOBVzrn0Tfw4IK0IBFAkZkoaH70McvEiD8UKAIgYt9V87h03+WTo4iYjAien2/tAQ4+1HlgXCZcNtNMgl8sJFECek9if1YGHRp+lu3UrqE2j0U5M6GlAFDwKe+zc8r9AZQzTNhxrNtXuU3Vt2lr+JNtjScpzaTDdXWUs/0zXVvyIjm1sT/b0tyhpy9puuprGOpvJ9d1WEzWcIYkAjOG772PgLweWbJOgFjrsyctut44nAC6VbLPtraEUvJia6RKQH6NSiVyvIbmfprrNVvKDZVa9kUg9AhZhEHX1LPTmk1b30dcGzTMfpeQos4WvB4CK0KFMiUrlKT7QY339dQE3KckFMzZaVl/JSjMcAUrz7g6Oi90X/Ax6iJiiiWMvR3e4qF3tRZz9AVHo+sk9uP7xxHP2Q6yqfycibKRJkiUZYlE8aBD8sHBZYXFtsY9Vs7bSPk9XBlbxXMsHNrICO19i0Z40svy8f+TgP8A2LW51+0iPl+FMutYPiy8pW8Ody5xdSpRY7Az7IysX1ifG9yJj7TF7QDcSnKk0L00EunbuG4wUfsr+ZvFs78+WgLzTj2wmyD2btaAbhUGX5/Ijx94Jn5YHDIE8dXCWRQGPKyycpKwf4KcgOjOz3SX4nJpbht7d1oTGewft5uDuqk+tm7jpwW9zL6W8ZbSGhebmRAy67/hP9phh0LxQ6TKDSYtwOPTvFPDtENeOMORbaEt5TfMlifNu+ZBpDWXwDvupsM4g0zbecw5rMaCho3h7/+uvIeyS+GPp7RXhiQTa9qFUJ2xx/aVh3eIGuM+gCnhm3feQiRe/Eru/UXRqkkluaahfeSFgOIyAoD1Fb8N6Ca3hguAwxW/rVncVYzz/hTDt2b4ZuX0tq6JCYOrPKArK1l4Stm9TsUavpvbS08J7mfhX+ZD/D0eeequj74yWhJzk4HR5WxefxtDoXuljiM37D/CaZZVnO8nlz+Ki7/zMlA0Y1alx1+yD8mMDSPyTT78G/KyeF0l+rGmPf9BqQ0LNlb4iDzFQSlcLxifXitz1QMyUmWBR0bjV9MAOoabTr266HjnZqVmtaXJCV9yzDIAMFjNj5QDS90YIr3lCl/fGKxg7/e0T9OydDYaJu+xX7iX51AetbeVcZp4++Rd9lesfGVh6e1w2P6g0eSZTQEbikli5B/XGtFxp7QuCMIXtxmsGjcT5XMdXWibkFaA65r8SYifN5aABf+BS1FS9MXO+cN85Iw82iq860G7wrAsm9rimjox7KbUvm3tIfw0wR/lWv6/qeQQD/3RSuqT/32ewYEbiCKzlkA21PIz/jIUiBhSqBEX9v2aiYGBDFBvqzvqxdnDjGaD4oKHruqD4Dh0LgeoTqvm+k+BqpPaDFA3EtxZRDi5+QxYB8NZN14dx4alXQGj3EUGmoxm6FkLZqPXAs0y3UOqriLKpxocl7gvgjCEKc3DEQf7OvhROfncTPNn8gSqSkTQfQwJ2Cw10JrWhYx+6xjgLOW2eN3OFMIGCChs1ioqG1Xd6Ubq7/ID6AUbEPVoDQHlTVbXlg2HoQYgm6nY2aTev7Witv3CPewZhjqiBwePle+SUG9fsaR5tTBq+km2duuAiIAtYRCYN5qtAog2v2l7Q5jkbSSgb9W8KT9EHjYy87h9KU4y9ThUempjq5prw7s/P3qUDsWXd7J5gsk1EoG+PN9YE1BJV2uab3yhNMpOBKdNYuef3M5RhqTe/DgwE6Jtq0tvYEgfpVQkQGbJmpqy95xK6JDssDj9mhfywbaFfulislLDcaLpPY5hjzg1Wu700j/Y3sZxiB99XCDAgFkirAjHs5z2KCB9Zgh/NWZ+aMS6/VFqZVtezzsH2mCmREo8FqraMHGK44+ybMxFXTT6H2E4nmfcYg/0agKB2G2TkOJXOEfCalVLTikk36Z/d9oR9dDXipYeujrkRSLNxm3uxeEClsHJ+8FpEXW+QdfhWzOIhczYSfTgpPEpIQhGVj4Bp16Q4VzcUCEAA/G/SA5UeM7MIiMDwm7uSSR+LzsOnPCdfgedkLn6JqYAj2dorGJ/oynrQSc0VHuJ48r6MGVegleue1FMMTq/P+KowBVk4SG7VLmlbJMWHRllcTx0+1nr1s4xTGxl6YAKhsquySwaDN5TSbZkunpaettoA4uY/jfAifYJ+ko5kcnS2VbtdWojhVAx7smDimIrQ7G0G+AsGCMhcVtcVzKZAE8fL5poksIaTLfBSOF9ZRIDUBASu5ub+/v7v7Idew/YsUc+WB/VchOK5VzAtKMPYeQyAnvGdE2ijVsaKfVgi39yvgTPj+rNTBIeZIfyjtWOD3K9DmrH6o4/npW7UEgz2EOgQPcQTJ8JeWti59T0dXsrbegzUDrWcwqf+lPZj9PWXe8Xkk8HewTCY4rXdxf9gGHpLLr6FzekbO1Db1Ws+va8NSnVGOjw8hYAeGF1WYrAa8GFCVGWiH1oYw1zi8pnYBcHuReJMAaMaIwbNq9Z++dPV+WKe3X5bxfut3/bXQWuBD2G5UJeUXGgISxwGt8vGskkwSKf64kQpDMRVALsHpQPCiWuPoexdxXBePanru2Kv3pLBJWP4mnjeYxhMdYCDGQnznRw2ESqI+1G68/1xhg8RHLDtfY1gZ7996hEHcGzFBAJ/7CENnP3UTug21Y3Jiy5Seoe4ZMpuXU/D5fVw9PSWqK5Ly3QUwqN/t2w4eUBJy5ilAqWitw/sxvtxH2Ru7NkpFNP1yA9C+3Q0atHBuQfAyYSiZfIazeabRBLm6XHmnDtaCQW7BYLtTfXnspsaJ0nq5L+FsVy5cEyedsBX4V+PXwXPUNr1TTzc9hcSDyz6VM/IZIvn/BOMK54lzNZUNMBf4Ruo/8iHyE7b97bWLa3tYgoY14wn7xONCUEAjrUcgzNLW4X6Eo07AiiKZNAVdWF7dQkBxF9DyPXuvQjSehP58mMPfUVuwBlyUZK9B8WglzkYp2LA+JHJUe+KeaTdDotNCjx/7t/xbgYWEn+7fIR3nQwrs/jqM27todqZ27BNNjUHVm4tngFPwym2OmZR/dcDIP7O6FeNtHUARlAz7uctcc63lUP1ZyiaULhvldvJfzyBNeHGQeThQn+3h1y+zxvxY5ZvFPH9GFxqqy318gT8o24A8rWnXJyevjfUAn1hezo6r1BM4E/N4SGKfIDrk2Dh7CwFb3SpqgheQF1BF9J5yOME5DzlpjcVCnTKIVtT0ip8BrzD3laqTQW934oGQUA5nDTlotfy4DVtXj9+AT2C0J4oR8gf4RNPdx2pIP0cxsCrFYjKWdT2LzlinsU6WTob5HyZ2/NKqqiPCVEu9RJV18+jCjnol/05EcM3TxeDS8vag3bWI2LrAXvCX5kV8b+yhmivk4zpvtbE7XnMLSD22+A+buPeJnz7OK5UrtuWgFypcD4d/WZtUwdRl6jRFSvACO4syCJ9kcVwUwThoti96tRxYrq1IQ/CAYemqr7ZvSJSgeANGwyjiyQvx8yR4VVmxmiSpYlijY0VGhJjFNL5oSlevcpbd1m6x+3fNclvTNSms5wV2N3R3qEQ9uau7rCqrJSgfpcj3QOHlqpoz6tnmOA4Ly9504/gD3Ye3An2GYSag/GzfbNOImfGlkaEFsuiL0A47IdaUao+KUzYKvSr5UMmeZNCYb42a2S5t0skmgqFNuoNfzBpHeh6lz7pNGLAAEBjdYlmiSgWhrry0OLfMmRvT5vkvbl2MwDvbCsMCMtyqCOfChn5EA6ekaHTfT0a7r+KqHHRQsICe1Utj6rTLksEnskpFE+1ZE1PZp9vLuQAzWEpkQAxKqTRU3I50hjIlFjjsFGIQ4DOArxnwZWA0BIaCiYyUvoKs7VifG4OEvRVFY75AJxm8iiXVIZkU/OrZusx5AbWdxIG7fQx6YiPVXBBc4i0Au9pcU93OT1+b7tEgXlpAUn1ujGStH7U3yve37584qa8+r2L7J9j2TqLNTeUtQ2fJ6Ix+0EUY5eqq97+zGM5/GIJQtIx6wxY7d87FFUCeFsXFDFUBbNlQM22d0RT33Qf77UY5aFqd3RsqedGxLxE09wT4IKnRxIm8EhJXek+D9coPYoRgvrKneY4zTxiThSzawcR/UWzywoArspxeLYUaEws7dHUZP2tq6nq+sVa4iY28WYbMHPMvuKTSjHddIft1iT7x85a7X6WmOmxKx0zR9SAKUDAwpHBMoPI4MKIZKRsc07l7hsJX6OE2dYWJu0koQtq1p6Q/UFUbBQ++qgK/1s1KsuAgzLdWUP53L5atDkDKlZ6pTfJFy4Hej5cx4bF4rxC0jx14MOaiToWGnIN7kH2YUCsp1KW1rPKfTQFb4lhQSNYRbaWOaNzSVCnX332QSji1kn/UsAJEo7AojJJJUqo38rHip7HzWHs2q5zQg/HkH9NO9inTcGtQvJnEI6iP+pG8pCUdxxnsKa948vcRq5RahDGtQpNlrdVYPl/Hdk995wsS4oQCmyvESeBQt2JA0GYDfGEHHVrXy2gXQfs7pELlHigGBOgVw1iWRjyqNeUtNmCeeTUJBeQ5t4YXsJG4P29vxx6uk9zWusdlGR8c0j0fN3c4c/a1MavpGnzp+WTbngxdKW7+Nt/k3R8IeXo3VtB1B8ipiCTWZuRF6wEXFXjRDj9UyOiSYk/eGlt1QHaypYt6SMam+3fOpmIjH2qyUWGfHDUGV1eBvt4pwBqidsJ/O5LvO3ErhUvIwR1wnB2N06yb1DzE0i44TLSVuF3zs4kDPL75C7+8BVojpjY/Tjnm7baoipbNw9o21H3FiDkqEW1k8T0dtEsZaQ8b7Pr+YxuCX9Ieur7k47qjJZGWBA3Oya2tOT/tWZp8I78ukG12GEYzeZ+oGRBMV8BO4gR8u/Ubfd38biK/FpYI/KVypplKnsffCsUSl3oQTebabUQsC9wvT/Ltc/vptStwpQPoioWRlzwp6p9CXccEee1xdxLXQtE2Y+FbGHI0xEhGp2bmNkAU8V7wglLiTGcg5FxvJ4zUIe3UA1d/dg/BBLEuDIv5pKwg4PlUVvsMZuFM9lbAbCE/2hQlkSAgE9RnUIrJM388paPo+yLviaP1Dq1UQ7oc28JkOj9WwNL//kymGJ0YESRZV/9xZcsqrnj1wy1/raQcH7zFJ4QpdBHUS8dskA2EZM+7lJmfbQ8ohYnJ/fNz2KNNdWRlR4aB3q/VfuXTWIBjSL9E0vFTO9kpo4zflRz7NZrMt6CxNZHBL+YzXl6w7YKEpJ4/BxodWPyoG8V8fn8PIKNR8B2MyAyqRl8rVr1jORCf7I4rlRHK232CI7Jas//f0093aZrtV4HS8xao9yf886C5WmN4Ya0eEUA3PnA0gGzHf1Blt73DIuRWavwD+OxZK3IO4UKsrjYI0v2HGlqxwLITfuR4jnLAg1UC6g/XnEKgBioyLRdmj+BaAsninKjPk7uGLmCn69Sq2zll+ZcdtWAcrAcmn0Y1wF9fwIBGLHNHvpN9RF8fAMF8xVvc/dpN37j4NqxjfhZQ15laCzZYFwVg2HqvFfgYOS0nJ7owX/NkiVBmEo6pf+EP/1kf7LPmTi2LUvxCRY2txtrGeL6oflqm6yrX96gzT6qgm97fxaSq/u8j2osAWzxCm3fM11ghhXUmbp6VdZVFKJOmT1GXVjfGr0kF8o4+DZUhqlCoSUMyRGWh4bMBmX0+Ev8zSQ0hBi4ZBL4Drg1qw4O2kI7cAjFqr6ZGwPXaUW1eA3Sua/SmQujayJ3LtAL+HQN01g+ZhOHoNjeciqxNpUNyCUEBKbFntHtJQxcoXQz0XpUh3v2gwKGsCpQpoYO2LRmgwDbrQY0YStorkE+GIST+P0VFQEpXiMxzAzCg2kI4kXLLB5bdyTXqJ36SYmET8Ezo8iMWdy7X3gxWFPPQ82zHW8KMrF0li5aIlq1Sqy2NcCpPoGLbLcJ817xKiKMeTQYxF45JIKQauYXruEf9LlkZ/unmm8tJ3Mqr3Q7G6lylOYn4GSAQQoiVPLAGiSwizD98kLf/MtQCVzwzwFcVaArXPg4oLvaSq32ooozmJoO2V2Q9uQx7aidD+p3DfKRLyTzP9dihC0b9RRUi9AQlPf+/ZMQifmpAtcA98kKnBkSeUsuVE/Vs3pAJ8LkMw5UG6lZfCCUQPuRLVsW55df3A/zlw5O8h+OanDw3WK6ItpCSCQBsMYub3m2uFsXFw4QMU3JYA3x3BpclsruTeFec7f3Xupj7eIUibDiCZ8/3nUvMT6XWvsdZPZI2MwSQGYdSjqkJ7QoBygNlug4W7jUsNz4q8CXZC7JX8rvbARvv1cQpn0y5laWEwNlDqegexj+Vxv9XE6IiSAIBVWybnmE7HVl0r589FBLcPF/ZJ6drf7eS5L01n5TmQOuGm92on13GLQt7JXwUNpJvj86p6stJjN8RxqJcdunCdZlTRBtE82JGcrDHGY05/6i7nqs4vKo4A7SWsOoTNE64qZo9MkhQU3DH4dRiPW2rUybALGh6Gvo7wYpwnDtH2elqOUm97ofQU04MCbScgOJgBnWA/t2zR3g9glOVPVHlJtByUf6COQPUxYJwIyYIE9HeO1h2bvocEREqYzFBcQxfJ+ISnHlJEzCjV1FWSj/mdkHVSOX6UBs1S3DVKX8CcNpkFeKTnv8zzmRwfPM0zFtfnB3BsIrUEn52+xTcky67aaPOyVUwdF7x/02H/FMipwXaRU4u9+aweb+41v9xTRqyWLNCSHCW5wBK4wGc/HHjwaY/xSxi05H4TxotQhaZOlg5SwzuHXqz/104sJGciyrlJzWL8RZ7Gg3Ams6E3l5Lc5ILsbfGdU4F5Tb6Hjdt7ENnYPEigWjRk3EELovfKntNb0hNuq5riFhpVtSSSCmZ03/naG1UAId0PI/ItD/DDG0TaYTPVlUGucOS26tnTVX8SnolKjptCJlr8RA90jH0Bizcg1istJ2do7eQIeQSOEaufgbt9cJ8UofbWVcbGmHRllM61+RQDIMdw0bHdsScgJ9/Ey2U5/giVczmIBNIRnGr5JB+cH5aSUR3u+gWl+Z45vsWFGTWZ5MjRefbsdED2pEbwYz9MbaUtqdCnKdN3sumMUCYKP3bIb7hHVsDbp+ekor+7nC59LDeo39iu4d+ga39N4tqOLNq445UY0oe7KSLHEWUCynLyfJSj2AGp7I27MLAJO2fZ6hp6CjkJGGSc1dlSym3iO4ADC48YFhmfY32AuAr6rpiczPBI/Qi0bphHipdTDR8C4SPvPqJO8wSbvv97XgfSgw18WxayA1dhkkQwc2dtL11q6TxMRxCW+/9iTsTrxb5VJzOlol4B1cwq7GyspRSMoS8STOw4KbgpJexWlVwbCp3PM4E4bxVkM2a4U6r4YNHi9vJGSHDqwaRMtJe6lPXJqND70V4I92BQGvYkbd78YBknfL38mSdVAqf3bebDgoLL3g8Aknrm8Q+o+DSCjKOXovPMIIHtdOZybpSdyjL7Cg4G9yAZ4SMdMukQ8EOvwEBL7Jt0YsYUYBsDSXaybVgLriFKc2I1nL1Q6z6Bha1y1EnyQOK6JrmJObY3o3o0/Q6g8E/OAhpLIKO7pWZP/8Nr0vDipw2/+a+h63toHB72hIja59mkaOPlvmWiXiwUbgd29VKQEIM3b8orbmWf+wfJSYIar59R9OUF4lMC4n0KtFziLAR6G59STgLhfoi7VfYYpyINnNaLbuJzsTgwkIJpWZ0LwSPwtJ9GfWeBH2S1ThCpANfdnjMh9Ax3WW8n/bfz4FTKPyxVQQrzjzFvcXDZgQ5bEUByVKcKBrbUavnxG9yEwnSnXqdam9GrfgJFsVxMWMjrtrEFs23rGCZcVBHKidQ4hng25xrb2hkAaDAluoBXJ1K9TyP3mK5fP5cmY4RLNyHnxb7qWYv6vcNJ14ZZZyaKnNzewx5wjhkIrEX8rwudkW90eI7paAlADgxzR01t0BjJPScX7hiwdI8CpbLIDAAYNh2UtwNuRsilyEt2JoYbmFY7+BPsiLZJAEqMDYsEpLMs7IghuYuloCzIzX5xkGL6Od/jPxjW4kX0y2b8Vqy5XH9eAZwUA/5EvRiYcK5+KJ5xRCD2ibtwdqC8wtcL7OfKMcryjpCeqv7Ar1HwbnbKe1g/jKNHRJgIDkE4hZRgZ1Lz/UOwSia4XJ06BbPJoESjDX+MiCs2qKdrMNbfUKnti6EW6niRqnCN+xTtvhGck/cQuQNqtEjw7wxO8AVzldFQX3s7Uby83oq5O4mJ5BuC+1PEp8OAMpQHJgYAtWOvaOvxJFuFlsiBEv8GQH5osZmRe/bWHnSVe64pByiYQWSdKk7xW4IHwFK0KXhwLaq674iLflhskMSBLr+0A/T8vyyxxDGujuoTMbMiSZ1C7AW99Y5RhWX12KmxU/iNrX1sA2PSlppK4wiiWIUqpaFwLxUHs6y35GhxMUfBszio0uSFkhcLnB6KaK3/17VQoQQ7DUrNhRJGPIeaOrLBDEKg765ssjrBjUw+bEMmv3F0V5q1NninJ2GWUGspjwQLOqeT2zbKvGGs/sRmWUtAicfYnr5uGE++RCddq9tr5hMutR6lmnI3PfMZ/CbLA4Gh7ukKrA2irIXvEv6AZ2Q/eBEmmi0oakJEQuJkp/drISZOl7nSK8sQoJ6P4C6iMvftf3jJJ/iihM08nemxiBEgVR5XeGvYeWG3jD/m9ucdpVfjmhBxC6t8ktWINXrR8xFSOb3/VLdH/H6OZR1NPYYVzaSq1z9i8E9LLcM6gSKY5gonswDEZrCoG9LDXWShyzvznM2JgpDAqRMbqL41t4q6QjuhZ57UVLhCFVlydR8UCCGesd/+b7BGmYH46w3DBKR1N+l9YCv4A+PttTj24OHkyPngrS9nl4aFVl7SM6iIpetDmcSqV0lMCJSaLf+Qqe4uMSV5sAaTZSTIaSWZ6jNy9P9nru1N5s13wrDNar86KwlkHSYSWC3SK2jfub/y3aLiNOQmHgk64K8oiExu5R1c/cxUm+W+5wXL1182BWB5OtJ+Hfa2fMgxGHxaSIVbzB2BfBQ4+wxFJMSpX/IDXnm9T20vL4ufZ23iYp3Q7NVGsI7CKtyqZCSUL6M+BYMYx/yYvE++Yo3P/fGyG2US1mAiOH37UFZ2foFFuia1+rbgE2w2wfxWlCG2Qb0Iyqu+nQnyc5qmfQtnSNcow3ah1OeBH4ORHKdGpKN3X0o1mxHfhkNz2WNBx17vDKWBdVM63tljoTqG9DldKp/9ohDXH7gDrHiRCk1nQeJi1W2Wq7fr9IAgbBSAs6Cus2mwlV8cHehGPbr4xNZS6aqTiP7FvC5w+SMmnFuqG82Zi+AisWq141vOqvP98tmNn8X8vMPzyBjd0MYuvn8AcVMg8zJawjcZb1CHX38ulCHUX/0ZOfkR1Lard6kk4iapEAdze2cYxVQiaBq7sRfrHdpH6HuRz71vOMIMGcpoFXakwo9NP+lLD1JQEAlqApPXI/t5lcYfcYeyLR4qP/wJpRCUldWvF6cd/BR93xPj5ePQTOKCGL0ch0Q51MSKNesknM16SUaIWeZClUSGdbhtnA9fzJpD1PMagdPh4RuTx4v6yaCCUHH2dCi1F6+J0aBMADQU2fUrEUPmJSMrer+ZORDpNyNmMrO3d8xJ+YLL548p/TwxTDKUoa+5POB2M5ZVle5whe80Wn4rMd+EQx5VZ3/8ktqvSSBSLYJb4H4QzCoRVkTqkMmIW5xABO3ySqVClv/hAAGiwZ40JLOStuhMxygTaW5gsWSgkqsJ2XPUXvxn5lEUgP3TsrEDufSmJh8HzpZnRZcnUP51KDViEqY2UbIM9iprQ2wE/fz2F4Y5f7Ofk3TjvoJL3nsX0BhwtE1ASLi26m6Mu7lHaqa4HxmM32VLaaoglUdVH5dUCB7iSytAWYEpPaHzrkOU5kVPVZuzCH6LDPmdg45kZHUb8ZaSFsC22EwxUNJpr60pqJayX0IKOMRQ5EIVJJ7X+66r7jBj0ZXbEOkpScSzrz+KKLIR66L7G95PZsTjdI8xtjmBJvb2JEoffnUk8PhjRv8vvStihkZbylCq2nZarjQicsBx5E9wU36SQj4/ISAHSKb3XYtjUejQDSXI4Zkau+PL1zGVTGkVaF9qhQVCJXN9IxzsjB6u5GyCB3WMI+aFNbEprbNfZICvyV+VephbkU0Cf370E6iAd2485QP9jH+9kzKGlNnExsmW3uaJF6SJY0u80+jh1bbeBizvmQrE6mavnYO8lEWtdNHLDZFiY/tIF+qFFTfjLk4KrlpXEZyA/Pa9LcY4E710zN6+ipl75v7XuHX4fzPNTbH5MOvYNJq7rCHY81uLfaZmInwwuDUNvBAEraSjmFQsjlOxDARiGfXMpsgPveiMVPKxlCcWDpUyc2CoSQJ+5mbbwUe7DNOnXsWo+zV7as5u6B0cAaqsz7eFveFb5inNGmw+kGprs4ztdB1pLPDMUPq209/7Anwsl0dJ9XUj5h4mpYX8EPDUNRArfan1oXXZjOP7gvN+fJoWhDymMKaiV9ztP44FFAeTk2wZyiDhmajFh4YfCvTDINVafjargUbofHwAf6dcluAa4vWGhLRdx8IbQ4/f1iVotxfoC2ou2IFf/pMnl+uyiVWVANU2If3/YvFCRKq86hGWnc/kVCnyHC2/iA7NbNvkS3p5J2KpRE6DXMN1jcZoc+ReSImWiD46G0fjQK+jZpFPdYh8rT6/BMWd2aoJpWaPNk4yt2Xu+lpg4K+Fa7xUiEYJZZnG3YBZplvicWm07pq3aQ97BmRfUXpTkgi/OdboSdy8W9Z/Cu4KboYiNYPa04c4tu2gaxkfh4O/VjmkAXXtNVl/IOnjcPIAWOGatz4WLy/RqEJ3aRymrjDdRkZ/fpChYKz6jlFmAc7c7MQCmgtOueBLB6A1DapsGG/Ohx9hCVsvVaZ6vS/w9LUxWMSws38grYLsRWXX1u3Yvs33YAchx6xWGiYov7VRNT3cbqJOIgBZ5ElKFOMYlUMqEpF4wiGo7GeP0fIUsnZ3ue1cGOZllyOLFF+9z1qgBVuxrFqtcAjBtS7DXPM2aMnN9Jow51cLgi5l1rYQHkzHGy8A/wbZG+U+mKedb1PZUj6RIrcrGKNhuYWkKCq17heIZoWGa2riDcV8ZMwH4ZVOBhfwYZf+hZGBIGOHSXb7zsdb+2wHiS3XC8gxdqmyAxy0ChCdUWOO9CsdBJxkR3SnzqqvUDZV82Ej3pFiyHKMXcOUodnuQMVs2R68pXeSu2DNsY/kWPatk1cpgvr+BmRTbE8r+3ThyNpq6vau1Z9VI+kYseiRaRHq5GlHASGGvptlSHyINGyPXV+8lh+CPUJYWoTA5satn86uU+GVHiLvOXgbTvBNMbAj3BZG+Zb7m583OuBrQwaI0F7z0Jn99rMLgHNuS4Bv5CpY2z6Bkjwvv+PeQU5hOT0mAuTyt9phv9+at8sfcrVfSXp+GKGy4VldseU8IX3vN4DrT6s3lCaFS84z2kmJfL8T+GmMJiMI8wYJ52xF9WWj1pClCdsYWCLzVnOhvikcjTEUdCtpb3E1PATIM34mVAVelO4PtkFio/8LWH55Rf6x2D5+6zGQIrsv2g8aKigH1jzg+6yrD34uD3dzCdIlnwMnfaGL5rIfo28Ml4Ma/Px3l7WEkObeuw70RrC/zig2NvQS/YAQnn2BrvNjMhsT7CTnf1D7CDWP0ZUpfJXhc3l76oqe1dXdcAszYQJGa6JbSAOxo2sg9rVkQZ5rHYKTJb9RofBBU3nhR5qC9tK63zfkDx2OoEsS1VvmxPOMGFCZqAMqxTmhP2eahuCupN/iNXSsxo2TOT3Q+mg6zHYYEN71CHSX3i5ETQF5cklshpiVYW/YbH1tkqPNSYB3Isup93yjBOXhavYXJuQbiHw342jbt9urNw2BvoZvHBypUXUU7iZaIbiyP8PpYz64xmZ6uLiN844blk/iE1p9P6f+J58tV1DHtvtJYns0x8KSW9spfbgBSF6dALqmOzQ2b1rNLyH5r7LmwYn40/DUODdBiYjfn+eRPfxsT5Dt6P5wh3QECa7fsLu5YFgr6QZdlKe1XbziQ259wZ9RDQt2q0rqzygBEwaiYqmF+obaPrbU07suWLbn6bm4cbaURWyfK5oUTgbaQaIkkeY/4Zsp10fg25q0QRXmgPbz+4fspyC6VtK1GJbKSwSZH/nNlMXG3i74DDVDsksGDQV6XfzaWCa4/N4mHGJhGSQFC928W5GAZY5hgBLyz/gBU4bvha3JgaSVuyAjj+l3h/ZBC8CEj4DGAiUcsbi0SFHZ/weHqvD/fKF/h95A7UnAMRFaRJvWlQkuTfVgyh792NJ9mTDxcNEJzN28cESac6YfIVSHVEm39pxexXiomg50Kx1bb3ybJNKUKGZr1/kFoVMuAjmPjbzecuWIDkgZMXonVvkyS7dAg7le2oMSEZdR5CK7dNoTQZ2jBexYA2yRVymzxdwqsSSZW5jMs7UBZzyGBgEB/v+viOSsPS8melwe0fNyWduEMLqALiIpSNENxoo50GXLWp7lM2AS3oyyIIG4hu0s+sxRTRFKcA3zQrM4D/MWviW1CsmlcdcttY7mA8hHndaRp5tlAfhAF7ysycQ1a5bLqQmzCao2BkcfQplTS0GhQn2Bd7ChQJHapJ6zZ3IiaeRgfFihYsB2w/tfdBQilih4WVJoCrVDUk+4rqxwuz1o5bei4iIwQcXon19u+nBvqoWYW2zPdmPBmxFQZ9tyNRXVZ2wNSrvK/4XuioLt/0xalZREFwAMRtZzm7/jhhl3Xa6pUonp/7tHouVRspQkhmuMtI53i5OZ/CZQXFY2kLQ/pOD5BvrwRDyrLc1NF52nmxb9rtc17tVzhdncQVuNRfXaZtOky2ar+BxdXIALQj/upsGhAuhAjG/K6tUU8JZKuVBN0V+SLFBCfEXvDD2okVJZNEyAGtcLVJlYROmie2dKPiCvs2JHg5iETmIH40LIgcG1P01DPyhYHLNY7z3T4K05Qkm4sxOrptpKaV5UeDnTf1yX8fBUGWXNPNT4IYKDM/xwb5FPj14F2dSG0JJvVTgM5Ttp2vZMRQsgwb+J/rxGPgrjfEkVCUsc5dq7hN6KRlaCyoacDXF+o8jqMpXG2ouETsEzllot0Ux/NKAXrmzKHHzVP6aEK4C1uggY/wOb5ENAxJOGIPU5U4Sjm/PD0cdL1yXlNsAZobRE20hWDHvMc2affw3B+Y2FGwaSZCUQ5vLSDsannuxi6XstnUHJlIR68wbRogeh53rZ3QbFNt52eBtpi581Z+U+BB1U0zcXTwrIRBu9tcNgvyvoDiYlCx8DgpyuKrJfMxshvu0Dq+qOHBabNu2J3/NLu2ZSG0hVaazATyFV4UWwh98l1ELFezXbL8sLcr3GuxB9xzVhvjvHrrVJfafeIYCZp2Wwm7eiVlzhUOS2cqwo/tKQaMC+WJ68EJ3bluNaWSYnubH0brFctuRg/8YCIBB+nn0R49ldbDzXL75iQgsd6ZInvRElY4hJSab9dpV4iophjYDyC/axoZ2RIm5Ln0fcVLU+3dPBpESELWgkKcVOHugSNiIUEB1gh7LDVCl4no9XtRDqIqDwcNfBZkQU+1/6Be5MIm9M7meR1iqqF3ZVQUQ+/2tF4+RXvpHLr7QL9J5M8KnDX1tC4vlqtkSKwgeBrV89LrL++65/8JMkIo5cogw4DzXtAX2WfM8BRqBJX+abXlH5L3hivCYMkZmiyCGbP2zR0XU7SOr5xVKaK9/xSE6n2VESfGDHqSuFLMamBpbYUs0h42j7VemesIOE/er3LExXXPwj7Rc8wa1LTZHN4SduP3R4NG1x4YGZCvBKPCKgNhK0X/jBXrY3rtUQXJD/UIS89u9lX54QHWYJdJjnW8f2+YyzrV92UeVAcCWj6l6c8F9lwmNML7vakW66Lx46fhmGXxvWCB4oXZ1aTHL0ChIARce2DxUQ8a9aONOwKyGX5xYKxtxHgfWD7xzFw4L/ruNEeqPbbmQv8H4AzqVKPP1gMx1OS+SfOO/Zpid22y4nIpSxyK3Fi+islQtx/Hh4GWmEO1nm5uCCov8HMDhPieWzQX8GWBBiPHKOrMZmznRDXyDQFeSUfyfm4WdNH4fpQEQV6MHK/bDIMA3/9skaF89eIdMakVS2UMccZ+YI8HO0AK3k2a6g8ztYN2oOs/tC67OtUwJCyVtU5IMfrpSEvy1ASgglr21ObshSLiBBhcBvzSe1zD7qhfWp5QpRx2L2daOtaSt40tlF+ia03zRJLvfZNcQpB3w66nvn8p9XNzUZeII1mtSzr7t/bg/hm8UIfWbpe0AktfPtieqDOa4nNDpDyi2jjBqq0X7nqyiQJK0ELaBg1M2oAQ2HopJhkHnjyn5+Wq8AGv2rroDCgdwXrbAbq0unZayTVjBVq0P3AnzF2z2bueKmlqeLqx3ecGw0fuMEBAQ+Efmf3IU9fOaitPZ7Tg16PiWBNowTR5L3svlx/yqL1dNu2Bgpr8xj6qv0RI503Nrs4Cub4nMlwRirNwEedoBuwAzNW/B69j64BKhFxjPLuXNvcMz67/sVyODQxckKQd6q2O+33inb8eJzhlGsFIjw96l0KQ60PbkmBNQP0MM5KT/XNW+viYmyJlg7bUKvLYrXuYE+ajmBHH/Tys4G8Ff4Lad9Qfo7R4L0sIxskveGBc1BCAV9mE2mgOgmkwO307SEytsXWEmdIiNJIPttzrP+czX3XcwNjShgrB79+hdtbgNRE3FzZjky38tWyCLvrftJ6+vRwyFaMdtzAljCmd9jrkKz47Fzay8jeSvZP5mqZP9UMI4hq0ls5k+zO1/JJ+RKXY/MsXuFhDHk/m0hrQlMMPX1v5WNYdRjVDggBSxiqNCvmAjaSruaKhyayfDowLjqxEpjNiNyKeUBFQavlFS2zWZ2e0Sc5KedBf5bUJSGTXCgpcEZPKcXuscxeWlBD+Pqn4mecq2s/mC7FQ8ZU/TUjJnSbrkP9QmQ5V3RdhqxRwBAg2lNDblAOd3YGdWvGFSK7o/woxdfxmgE/k7sA+dlvKt1R/We0FMy8zTB75nZY4G3yU9FF5RJKvgn6g7JJwzsXBYt/quRec1i2bnBenW5kazX5ddvWRGPXpl+TTyp9eevelSh8bPpHysXNA0HVUTEYBeFKhMbSgs6Rc7L3730F4D2LELFFIYD64H/5b7F5Wdsr797jFfXUBnP+UTim8ZC6YeuTPrdfc3LFh72oTdF3A81zOirdSiPO5pc9KVnncJXbfs6T45Tza71RzQJU9Va9ng9PzhCqtkh7S7GoW1UTjyRFf5viI0YGkLbQncOIXquLZXgStFFc+SKsZcFRgjXrQXM7KdE2xVlbJ6xASy92EKXHjvGcus7G0LzDr3iA5v679xMnukf0pW0zEg1Z2AgJtBKEHe/USDp8265Q8oIFfdtMqJ4liiErM6b3ZiWzxytVIHJnuDQ2WF+sg008yVSirFSuxs6NYB+G1gizi4XEElWaEY5OY/B6JCd/02YqKg8ItjfPXPw+XmjVSxwa0QmkuVYtV1fv60ks9CUzneayHc28owIfAOu4tBUnHTUJndScwUqnnwU2qeWX6Q/b7MU0CrUCBPRvAb5gB85Ul5k/uopwD6mq5S60dkhdAginLyRh+04fEZWzbw4OFEEqF8uDeihYEV6fa3xNsNlW6HG1bDlNEglrL7ombuvIlOrIEL7brG5eT6gtmg/tUxB2QfVcceKu0gXXeH5V6cAIiAjRbSFJXwN1hI4BLqJ8NirjyDPv5mdxaMpBwx9W8Y4AqkFpHg/9qE705qA4M8jGfAErK9savv7yxJUFYZwBfqsF8gOmRqHfcNEIPifdh7okVuezW6rXVpfT4Sxk4kgohlCApTdg+QK+bnPxTJ1fPZq2ghEkBqLE1fFlKkk7mDP4/5ESPgBNvBUZXJ0t8zCbdZlKc3p0e12x7qzy3zBSE9L60Cy/D2TibwTytFwPTrHd6kwQM0tdq6Sc5mAdMzkRMHTSjwaFTcEgXcxQeSl7Vr9XcmJu31YJQLKrqddo3cGxzIcBucKBaTVBv9wO59LiVBoEzQQHOzYOKKHawKgnpS+bMpXZ4Bqw6wdctQjcButWbRxNC8uMS3Cy63Ay0qAaFf/CbFocr/2jT2P1LSb6dIOl8BSuc4qraWbfvHKTsm0/ba0ZACphIXcjwK3gVnZU1eeFjnW/QWu3Op/qlHrO0YYvndk2LREKkSqHOJ4iMHIghla8pyY9dsqW2A46nRGKZRyVTEmIJBB/5eCnmLTlX7tCHZfwy6+mK7sQLynmGlkypMwH2nI5KysmEBNCdprxhOjHH+rhmVO2y8rhNgxDQiYBoPXMBzr9yIrAxjXuBqMfrfYk6HnR2Yc0UooRziW1w0Y5g4MBM4v+Mlr+d4wmt5wrI46LVWfWEK24nhnjLStr66DMsNTw/42tOvwIGDBJeHhQoyHWlz3FLHE7kMlxKpSSdlaWvMaFHDtm6tUg/KrkcX0pZXGkTANdbakGRrtDHKF5XJ+/Cb+LY4mLlX059vJtMeJLLoo3Q9KGKPkbjdcrz3fkgy4hb4YJ2QAqSAJR0wnbkZSV/K6ERFbRSQEXjgTAbVdCaIwGhiiqHShObqBaM+WBOpVKNNuwW2ePYImcE5PGgruDEi6JmhFIzV/J7jtOwZAuieAZWOg3mPYt/2gffZ9QZE6qXyBAGTIOyIDzay0yVTw1L7ceTSTlMZ+2d6xvbzIX2sVFY7LhcfeKdQI1wDUYeMRVIipzMQMsd0r5+emYckthxttEygY+JLIXdTlOgI/+6/cRQdKmRI1xgzvNtz/pFJfZmphpIN7j4jxje318xMkyuGq4mKXojTjfQBx8CnAWFvdSCocsv0ea6yguenTtzfObFZ4fxOFiXGWzzErcSY8WbFr2gpC0hUHUiAKf5vpXP4MGQK79XhRJvLhubDRZ6ebczTaZAPNk2mNb4081WtRUziPRhe3yzAke1pl8sL55Dm0jKCeEDUF0zHjQxUuDsNUiFsUDOTHZAe5wq7AKKuT+EdBGjB88f5nXjTJ9ieCPXFSwZ8/p2oDgZ/V2Ipe6cPEo5dVWam55fHAcDQnr1aAUjOaH1Bxn6iofdCbVDDhzXkve8hUdhXXngkIXaDeyCTJki2t8lxxyL4IpfIxZhJNckzzORFpYCEi5odX4s6YqI/wsWqtFuCCfJJvhncVVq13o4rsg3TmXX0mJV7PotyyLUQsMeVpuPPCov68sORAMs0AVuzdxQlUQC5LNnfY7gcg9sPTRkPRSv2wObBb+XvWCSWfhyfVcmDmoi9pUtU5T5S4NqA8U58tohcY6l4lENIKTOMjeS+/0hNkm4JJmdwXbVqyAf2jLfJLq+8YNd1lhwgqzSJuabWPw5tAtzVK+svGHVzrTsj7dHiijtvUiWjs++XVPs4P6cmSbYUK5oi7tmODmf43gRWdLZqUWNhuUYWkoX6MxCQD0sYoVHQ/pN+PqRExvB5SVeXIn1CCWIZ1rEiRx/AqIJyl8pZWJQ/YISkVMLZ35ASvLOEaV8NaQdd+lNe2F5u3suj8G4HXz1onhzBGFUAVgDqUPJb4Lt5Xx0da5HqWwFOcCAm90+3U+NuTxE6PIbiStXJiARPUreEXrlSncozi6qlaqBMGmmIzCfr9xli+8TjpEeqsOWF2rffKo6cgo5HTZU5PxGx5KKvTQSwL8ZFg4eKsoSJE4rIg5RgOebBPa8htGCLyrBAtuqJFMcwOF6Qw7T5cW5UdwApES3pkO/1M1XR8Qpfq7Umkp0ZmgCAuZPqsAxRAGU21exYy57YxM0NSLHwhDidwlxc2/8pK1DXdvDLxXCSOYXAm3Sy6qQHxLUWldQ0JRwsVSgp0n1dllTQEKLMOstFu6yKTjm30MtYl+6DjcyfEuyg2+nypKSwirAa5lwsOLQ29phMGyE3Gi0ojXjsaxTtcH73GddUOW0qUxrvVdZxacrsc9WzdWu+gj+dkCtg4lrLWDpv1tv0fP2xURvbzUcJTcK08wYZSChewPVtb94123zD/K8U509qnnVY9ZehZBWNdF5kt2rm4iwJvR9tVBHjngNS2v7Em5VYs8M++QeFJa+2VRIfINIAE0w8nutQ0R7EfDYZgUNj9le8w4/XL0cO+Y2mLJeEXUoFyz6dpXh9t/eOkDDfZ47ppt/O78jfdeEHCNLCk+NWDPqMmOtBL2+d1JVElZQ0Zh9vSRlR3ZYaahrdBeub/zgGJ0lpX1fkR60Ls8kIbzvds+O2p/zopIQ/XnOBdZC3ZDa5lKjo01wAbc7oJP7pXv2R4t6pQkvGX/CrHuMBziCj9M4C6z+bhPo73lzUfbHHe0yFooVHh7a6ZPNe1N17HlM90QQaDJEuHQPyJoNkfaZ7QlUxQkn13hdIF1GoXPGGHaKMdP+YXe3igibNEcbV0wvE0RPK/cNvjXaOLDSDfzfG3SxCy0Qk5cv94FQuLAOmS0+TIXfoTff76QuIedUFDTALDe5seiCiCyIdCDORaed6Xb0XiFzfUKUGyJBa3+gtN6yKQwOoQooJEzuyc0S2dBZHMauQY8sEJIwRaOfJV/6Eu17LVdKSb3YKte/wYETF/DDq4mlYsAqRHzUv8wdSekhFMeJZNfpWZhHVfuHdzgC0mx6CoMYkbaocCWWFtXtiHyIUcyswQSvaqBO7bqfxFPRb2pipLUIiw4J1QU2phZjBLGz6ZMvdP3TzgDLwMxyjD0G3ckeg/jLZwTmaEeM3EtYSQEIO+keLEn+nATfw+XB922czZL2eiJz7PBeN5677GLHHj8QnooU4Z5HP3aAms0jtkG5hxPy+miRCDLq/bodAkrYC7rf6qNyA1HjImJvKbGocR07yPKwe60U9tYSIPUDMMMXk+/3682ryY5YLd10CDLHB06j5UTLdu076NyORbYGwVAGK3mJ2AJDFpIDIFaDA/zaG4wBc/oE7WkvqG79vz/rEzJVQQCqoiGksZQjEgj7udyjrT6bkwRn1nCB/YTG7vEH3reIWWJX45Cjipp5u6vVOHQIBFBr40MNXCdCYhetP0mMJfOJ0YA6g6SzXWJsqZaMUH+++HUwAvNtLVjLEXOjqCgOYU8SgaqwWfhflB9LMf21VatJYVKueStonOY9PVWk6X4+FenXe0p0QnYLHzs/OEmabgOcy0CBdl2m7GEHY9XwEj+2weGRwgmHcSUVaMLhvKtUM8Buf/5TohwF5bH/cIdS1dWnQ2F1T/P4mZuXVSJSBIFtHHhV+wR41FmNpcZSHiUm/ObYVHqQYj0971S7udifb9qTSSUnMeRlsE9TICg4maXeYvt4k0F3kC4m8DlxwAxoecy/HkQ9TtIrtQ/B7EMRPWk/U6RUdU9oJBl+0p569KWhjJ2L8+qez/znL30JOyzkLozb5tIgieSv+hUmhjlwaYmt2NFqt4BYwl78uautZfms752+DaADL0IcY8AbfoB5yldl57AMXoASxOQVN7Eu9AuBh477iNhgRWOGXUWXWvEg+q0LB4A+gzGrKSuuBkcwXOHgPXxdWrrBgiBKnUOWriqhk3LNN0LgVE1MPaHCjqlx1Z5am6UAKA5FIdii/EqfgYfVLa89CLFP2heQ8pWOoCKr+SMIi+eZqdhcoPTIvmCnctgnJ88WGpsOaElJ6Taxrnt0raOnZXTJzXlYmwIPYY3wX4jYR7JvJhz/VWRcRm1UgK0A4KbpbDhwkGF3X1Isdq61HQ3Q4rGj1Rwbp25RxPRYGvb4t0xxZnVWkHZji7HuLzl21omhBOPnkixKLVgdqywWrRJ7uM6RD1LJyQ4zDP/adF0Nc0HL373r2DNlhygzGAgzLlaGbBU9H+hQl9OPT9RUVBtt5SdWYIMvNs4v/ix1aCSN1LbhD0D/vCvnTiTR/LiCdjeIQHsgX8/YEjYMtsgR5nGZ1Lbb/6KbMyulPRmg79Jj9HygzGw5Tq3PljMrYw1XXwTZgmEHuM08smTwepAEEvPUchaACbCST5DYQlnGOovLt5nGuJURKK1UPz1zn3d0ZzIlDMS4HPIkePBM8tl42idMfkTRKf74r4zuEHTtz7sYt8N3JFMNjVHvqK1UwkpUuB+lODyrJJTgN2yJYwAx7Tn1MpH97MJYmGLXySM81orSmi1q7QDbApMpQNXnML7tGDW/lavsRxCnBU+RyiEM5CnAsYcay0P7gxstHDnL4dABoHQyMNOhr1RhYwcRLAVz8wdBdIz+lgaOTBUaAaOlX9BZFSPhhXaPDSH1ucJMfVhugSjrAQt85lvpO5RSHgDWSC7F3e3YCmZ8M8+rJRmb4/WW2NGIhKXUenUMungqXarMAsO2pHfccbD1//kW4tH45vkJ3cFKkIARXofZ8d1P5dwbsVRDIC1ePOWsoz0rWYpPuRUfGYd8mgPOrkNdq+ayj8a1GGdi2U3B/86uAoIuqctraFbVKigo1Ilh4reAhQ4SngH5UlDDjoPA2RsO7qy/STw83spz/JuecERwPgHRufN0UARmWIuJqpkkJDs6QyllgAWBilK06Xnjsv9K7qX6dajeI+GVwPATtOqfFxMOSoJzZ4xBVarX4bILm7rB7R/J70TJEHCnferWuEnbwLcWGaw5IeFfWUhIfrpFijL/hRxMguPnVXL1CgFoeo+/YEfc62S24Ymo0sxcDo2yFatJZVVi+/zTtX7NjkynbCIiftIBB7Bqjw//CLzuOvkZqeRIzXSPO0Rss2nYWF1eiVmenQoRLFl651uS0sRKonBVGVLfI9OapDy77LFqfJyHpRROLvI8FA/eG0UTGr1V2nVEFYa4GWazdjxD1GYTA/NA0sNzOcjy/b0a2JO+ZRH1EnEVN7ofaUAGu5sQDtqWfZ8GG1HN2jyvDRD5t+76AYTF2sHcBGh23tbAiERl1K7zwfwA/dROOqxWxvZnprUmZdaWX0tWEDcBIhShk5+neRTD/2/f6aQCqLJjXwc8wY3s+FW9qze2IoL48chKyWAJu1UNFkOHjHnabEJsKOV054a40omYD+q9wrYCiQyX9TJAoonnObVgvQglwcqv7L4ccSKOIqZpqCULglKLj9jOduRNZgCBcVPxU1xVbXjjJh9ybVREQn9OJvVoMK5fM47hA+alW2LAdYyfJuDdtIxqBlGnpdUsUdNHPw9qLvXjcbE5/BhOXKyE9dkvFChDMuEpdkeIaXqU9ZNl73xichDteV9Rsf52qTZ++NIIuiOVJb7SUNb2aS51BgXFyFPkHw9UCWN+xBSifg7XkDEq0cDx0Ao2HwXd+al4Y1iikP+dJmh4GUh9ob+hImnflsRlqmAl0CQ763wk+xJwkt8XtY2a+mAH0xUv8xg/rGfWlqhgaRd+buiZ0KVHAOlLntZSs2aV2fh7rNUQ1zwErxivZC8oiIQbu6fMNdYa7u5s2ZUP46F1HcQ5lQY1dWrFE3od1o7NIu2s4JDKS8uVGThamgqlT3BsBoRYps3eQqhfTgCkUl380Xxv6QHQSvwjvAtga3OpMiNPEMmZtw/E9cz6crx8UrdFG1X4i1F34eifaZJ4xcpii4pVtZXrAoXKp7cf2SnoAsNKFd9ss2VJ3Lj3EpX8EdBQHVWWu+I5jvNlJIQvtpK002HlbSSu0tH2uaxdQpA0J6lFSP2qP6gBPvEh95wyb/8x5IDfNIIiZM91LT6QAYY2OriFZ45KL6BWNx2dnTYHXTnSXERLC42s46ckww1aQ/jAAx+feElH6gnxkxXo5199m6KH069aj94WRuYKpIhsEBwKeiESiytioRcYoS8rLApAdy+rdWzNOlBTFEUNYfe84PSKYC4tOknG2NtHz3OpZ4iK614MMCB+/UfT9gAr/UiNUfLATxIDv3Lp6R0xHyCoG32ot7KMf2ie8yUjF7CoQPcC7a5HGzXWk7f3AM1+In/C4dtMOs+LlmeY8yBDVPj7eK8FNCAREmXFNnNAtbbtxGU5QFl15EvFnYh070yMZTGTBPl1QpkHzh2VmzWvGcyUFYWK+afTqnYZiQDDqMFm25C2V/zNiPjcxjV8/km0MfFDPAujZGNt5EBqsJ7m17aXEzJo305MBOFhnKxZxfNk5xfyvEwCBVu9GdMAAsgjEsjbGydxtcYBvfFNfVONdqPHEekrsUQhp1nyrnpjJBbRG2+4zS3qKejN6XsvwYIG/edjQ9ZLFq6uED+3RXbJpkJBtCs6anw/6BdDXpwB6yJz6A0haXrV0crQrcWFTirltLk7ycoZwBcnuS03qhN5RlgTHRL8R4EMa9m8aghelemZcFF342rCglkOofAv19CqiLcpv/yxU99DD189JLTIwPrpKabmdphJ/NoU0Z3YpTT+jfbvWouYE0X84WjG7PWnxvqvzA6hq6qcFxEkHG15DvM/DpBaoMqob/wz9leG7jg6L2A+Wu7HR0/ZceI1wKdL8RTqpzrgBQWfMtRtPbD/MasQ9u0lfUg4Sq84zhAaJS+VaKXqK3K0X3Q1/hFM64ijf6WFcyX8pdhXtMgtyyyka3rySHdG98CeFCBNAWLrOwoABqY2cZ1BSVWZzgMh6UtPhhkq7vWUw9u4/9ynJ522cqhBZ7vjVTRZLEQXi27/57QlbVLamKASC5tdB6lQBQKiPdO42KCFb0hN7uxGsAoXYsE5nD+fzQYg51/XJ6i0p80mdP2R4R+9AxD+Ecg4EwR0aDWXSwV9Ri4V6WXdq6XXkjU4XKhgrNwaiga8g+supMeteaO4EvMW5pqOvZ1dgn6CmZeGLAJCgpGqMr7rB/lXbf/Y8dxHWZEJ6clP3EwVhzKadv06UXbLFtYH+UIT7UgACr6TbfirTcYIopsC6PXS233Z0pHitoWF/IT5o2L5F65nISWX1YpMOiE2Eb2fJr03pIi9H+dSGEG8Hm5SLLVVTzEErHMk8y4rv8P/F67zLCU6n+f+4cUzCgKCoBAb9BOp5jc7kaz5FkFdgxcuLPJZ/UDwamlC6pnctsjzJQABwooIVc+C/SdbRTnerVgKojDyY5fnqVgbQGktDoPj2vkfHyli8HfqECwlC/8ad8vQo+vpNyoaW2pnb5+Dj5TGoDSU4YMewOOCbYmPYABbtEP5bO8EwkG5Hw3CTYrvlKedIH0aFauRowp40n1WtB7Ju38bm0zkPjaGWA4Ts23yo2S1jEMTObFtwF7+CoRucQ2srsT82jcbaE2Om2ARs0zqJWiWQJcJQNJwYy4xP11bLHZYIWsmm8pbmGkAe42LFN4M060wcGhNlFy5YuZkMyLLUO8jI7PBOuPvr6NBkiCtTEkwanVExuZAOmZp2QU+9YFQU0TcO0LC8lnogKxQA7Fvqj8ufcijIb8eZeDFxL+kVH+Tlfcz5ume3qgJF5/qoj5x07tlY7zMhNvdjNb8maILAwKjN3sFIX3s84n5d10rS2166S/1rZuDbt5OE0o+iXZpREU/h/wcFenXTU+K3xAssItrPzHibdkLAcpD8FrjgSGJdSW1oqVZ4RZJXja+gCy9bff2YUPN2EGEw+qXLjxTqwhOBgUpkqBg5wRABNCwKvHOMiQnG+nkVXWv3KCPz3fUUajrnSW5G1V2m6ZkRtxVMLpM5HPmu0YrBGKmKEMQeN41t1DgMn5ZUPYaivLYgmK4FIQz4mfeU3bqX8mrjTB2Qmp7W+QJbtS0BCtZWDX5THrWn1c3GSA58OEWxtG1keHEGaIphOk5Q3LOizbxLc6/hFsbr+No0wqN9mqQwzdunNlfwj0m6BpsXLk+CMbNnqE5w/MYeDqkt+eFZPniLII+u3AiF6ZvqEpb2jt2RX4GE7Ung9p9Q/OgzbZUrZqJm2fS9Fl513XknoODI6Q7rhO/wQvKbCVjKR7l9rVU3GWofKoLJ53yuRznrJdE+j2BB6ZtRbyqeGWBeHNK9ZyXIfzjbUrE4ZGkWj+A+gcSMzP+5AEu9jmQHhkbdrflhFDcpdPeoxWsbDyouCquql3JW6daFfBcxWBSDThHrNIHZRMZtGpJROgf2QoxpIMktZwBnXDmg4JMzCL+ZvuSqsblh4pN1yElMFxEnRaQPTyLZ671CaPV6adUxoQenthZDZc6PNw2Q2005D0m3gPbbw9XTjThFm2pYm3x6Sw7v/ERMxb8Do5LCrPL3WiIg1wU9Vw95U4Tpe9PWdfAfF0v1sFErJQdQBxcCrLTA8nVXbTP1EvZLrL9QJVQ3m0H/FYw3E98ev+k+vKK7Lh7phV/d773TMSIzxWqxer325ppQcsnkjkbiDIbBtUHGmcj3b5YH+0644+GuCrqnDcRhrWceEehgphbzL37MDa21gJvPhDbpyciTr1RmnIEltwC2ueHQan/WPM7Dxk4BLik9V7NcpV8DQHgK+wS6d94VFGt5+rfhk81Seo56XZSBu2niSpeQx6v6jI9WsPGWgUWGdKca/pzuEbbt59eU+UxXMfUfBEjYX8A97tf/2ov5+otX1EWd3jkmosxpzzQItkp2W1FQ7a5tQdGxgRuSjWZKpA1sZrVr6CjkojEWw7O9cr0ojifbwXLw9mHmmlb8mq17vYiLoc24n3K51+PXFBdCkCwalTTYnMcfBiPd7Vbt9987UztG9L6N9YZft0VHxiyg86/UhNsKMyETwMB0OCjElZKyPK6ili4Yg522jV3znVfb/DlJlRoLHYtdz7+YjSKKfouHV+FGwvrL8KEK7+ETnrlhjpgvVe0jzuL661R/v6IWckS6/ztvGwR/rO2lA1TCWEizSqQF04y/276TF3iL/qMNcWSoKT3jZswcraxbMJkWnzkNE2aboWQF9u5NS8CzZxLfWDZ8iBg8i27o5wz02XNHGzKwpgq5ju/V9Fm2R/55GELC5KwpuqQmnAj3tZMXBQ3YOx79wV3v/ofPoCa7UDRdbAFcOBec18ovicNM0Q4jDZxwwSZW1X9wwWMM1gR4+pCzDee/RbkVzUlS4TuwbJX1h9Kfrc4cK2MGuRZexozHb1gPW0l0JyqxTflxsbuHaMGJceZYa0cvtA7BEV6GyxqU3+2fM65YmQjLXxRqxqMLOaCvOjmK4y+Bs85ZZHsIYFOtVFRWdfi0c6wi7cbsQ5VByprcSjDddMj40pF+HHU0Waj2JV40aB9GqXZKb5r6RvnOeZw9Z3LP2/Nl/PEVo0GQ2ptJsaOQnM97aAih4CfWBXJUNfAD6PMmVlGqHBO0yQYTjnXwHmOBYyTg9Ar/LG1ww/VtWRoUDQ7sby3gojfcX8FXXVjuX2Pt7qQrg5gQRxiwuX86/D6FR7KHiRTnDCs3Nj3pjO/jAmsNjy8XN7DaXcZ+iX6B8jTOfU7MMxP/kcafT5fOxouUURW2J/9WfuqT819ypRqpAzfqELyZAHtvC3cCrvzDh1Yc+tEjt0YQougz+t2QblPomVCrikSRfJnMgCi1Nbdentgh+41rbSAcwfeuAKok4PG1Mx1DF3v510efoTLhKzfioacBNibM9D5VmJpSDBVyUbcYXM/5yv4q3AWimzr71jPWVWa4WC/M84kROU/QgSxfJhj7k2giNfh1WTNZnmTMeJ5NXDsuHf+aTDH72rBayc/ctSmJje7+c8HI8FqGC1Rlzhvnjv1GLcQyvmgEThrspL6lojpNsakASmeLOm0vj679WT+1O/8i7TZEsZDdnxpDYsaNUQjABghrw16IU3eJXmU0WFEB4Ngw0TSP0wD0XySGO6rKnteRscoZHmvz/GwmQaeW4ApSAzCMOuKj1YkVka9BGLmV4Fj+RHBoIYidUqzbBL+T7YUX8K+gYgIGj4iD9E3mO8hBD+h0Gbv3mmYxex/cNgEJvQtCngf4oLSW25rk+vwQ6LbqEgJwBhMuUiP3Ye+m7A32sDTJ6MY0uv+P6AZ8lg4yhXnIfUUtqgx9dn3IaOUch5JFS6jpbUNExJZczHZxLai6OWREEAsOYPqcyYqaD1WJ5lLlr3VsDDvkJZhfJwNETyVRVHzpvuZ/lJpFU0zrcFZcGfR3f1wcZ9vNqxc8fyBO1JyUYBJ2XOadHS7+CvaylI0eXChKr3+htubKjc1Jfx9az4KVas0LSP2NtFywHHuWK1AY/vji21ANAH1eyQ42xFI1t3gAxg8a516Z8O5bHpF8uY/GoGAPpvCcTV5WpZ9z1jeULdSc7PGDa4zec/iEFgIVphmODaDkslUP2RsFXpFSW5nNOjVfLXD0z9Tq6AYs4im0g9ibEm7d1yUUGtNfNvf7kPkOj9Naupx1ehGuedBn3zkThmlCSUk+wWnXS223wHcUbAbjc0XSGfIGxM0ow1HB3NEqSM1JDh0hVwYdBYwTFK5QryarwM1lviuvQhhsjLePVFr4J+/tNq9c+sXJKB8Q1KExzZW6fSjxFhRSqegWO2VXE76KAfVvQxg9shB/kAYSd4yGyhRz9GvoZq+qC2Y/147Wf7ELFmOhQVgoQ5Oe5AicFlCqRc47R1Z0prcgPoDmctx32c/WeoQ2hx+1Iwm0BPM9xK9G3jBqnKK6ez96ODDrSBQ15itzOvH0JzBZrZufKEcCOFmiNmkWhle8956Un/Z0ibntAdlIrbIuEimJJST4tdVbE0QwErKnrcdhIsDda3SNZK82ni/s6yAsz/zxnuQz/NV36/LcPbWIytLqNwCUTOqT1iT28gGQkt1wvsYPdm9Ib6Ah7rb2TAhybL1YQPOkT5MqUKpRFMH/jwex/K4jTIYPizZKEqmkjIpHgixp+q1yZoZPdezxzM2FfVmwFHPQOqWUspslJyB0HAbhtq0wsT17i7t2N8e/LF/kEIgWxfC6VjLMGTUHTjUsS03HpKvGT5Zvf69w8D2/0m0xL1RFMjUja55relNQv08rlHgohVcYDhRWbuahAXWwt5MZmnySCTNMLvQThvihusoNeyDcHnGOvHzheSTbOGdq5EwvKt2v64rTjYac6JR2nbT23UzAluX2wqNuJff8gL/egYYe1jy7AVtZuawZRtLjQrQb9vuzRFJ37xlKPnzNYaC0bZ0RQY9DotjQ0so/2EfRZ72qPQP033+R/55ZE2cO8jwyV7uC+wkTfrds/T0laRpomqlUs+FEM4gmamjrg3IEUTqHvjZajdeXYjmdldzWwLMcQQHtcWiDU2FtvxMgFl1M97l/F94NOi8O1x0A3KcVRlTLpE92Y/Ri0QyOnKIy1xC4viP7ZYyaD2DcJOZ0pXW7wLHrcQ+fYGq27Q3TTC41C9ExhU66lP4PCg1942i0rEXRIlk9nZrJKS2ky0MSv51Hy99Pix1Fq/XoGBPOTP284YEVEEYzWjr38RpTcggLRYEoz1Hn4/B0u8dekvwsIXfa51yZF5PpdlOJ0kuOzrGXSP3GNwf7ov1WU1DgwOQv1iqORK2JjQIcRr6tWThFQSwf6F2Dphe8sVIWQ/VHNZOeYlDyN9wRNkto3q4WOuEbikYko2slF/ZI4prIetsI0jj03iVzrBwUmoHquuyxXVtC6cTo+2Zi0wFPllobjzHFmGFTTkLXy9UNBJ2ZnORFcmZT/Of878OIKkOXIzUonUSFpSk7/1l/r7tvB/Xl3GmZA/ksyN05zhH6Me0o+EzH4pfLojkT/HvXitZIMvqYYhJBJAHALtIGqbdvyX/956ZUB/elEFfdVbNlbdMT6QQbXW/ch4Yho+pmPjqxGg4Aa1JduzyFNVO8DH2rkdZt8vGBNOugeFmoO0JoczSboOQW9InZ4/QN6KvGTVtwjRfcjL4/9/K2ztMDQvpITVWYjn/rfzDLahgHkf1B7bLK0izKNhlGdYhD+1HooNeug2n+rSswv5cJNb5qrEklk+V4yAUXrR4N+W4w1vLahOshyE/2zjuCTQZD9UWShYPcV6rF7YyGGd5CYsX1VKGRH0/lHvDyHjO+23WffCAIcYPto2WjlEs6wCf1v9FNQeqFtFPkIFpzCZRChG3gI1bCrATbGCtvcujJeH+qXnVwuKPVCa1ksfcTWjL2VSJZLbn480kH6gZv4zyIN73nAdpPVj7RwpEn2tJFOkn75W2uyEVeDE5DPJ/IJqdbfYRSNwE5lVlX/PzxtFt4i8zyn2KMG59/I43V3WltD0ZAeLGSicPnmPII4WdkVRLg8R5xmKbhufxXZFg7z4DSWRWU6GK/A/HYmkLPI74QFKdQ1M0b6jemTGQXraivr9PITp8WsuG/wkfsGAE5mlWPEWIcax3aTsM5c1T+7mAjvUxmxyV0hYzHS6sovkHKolz191MPfAd1zjXKMXnvYHXwSbjdkYCU5mzQnIRRt3gIxtQglkMug2F32YivkwG4q0Cy5ulwiSBFPpIXYM1uvZvSc0jyuXmSsxWygXHRiiXTlsFlsHTbAN3v7vQS/mLgzkokFFPMVCy4PKXSuSZMJ42QWm/NtqzDr/gD6Y5S9dMI8QBXcDJxJBCDkxwJ99I+0hCB+2F4o7AQ7YH8lWkHAVQS4cOOn5s+DLQOm9rgJylqlKgR9m+eflzMj1ROlwPI+3UOJ5QETx2UeryfqIUX70n33a23qUgPVvP+KieKH3g09h0v6ag0IOa0XyWM2Ijd062LIswYncSjXkeCCSHufNpTvgc56I4Y4AbZ2VQWiXlMVHjRNv1iYXH7wqikkijw6yDgu6olLVPwZgI4muqnL4buExS25XaK+IRUH52etz8SC01uFMmEYhORycKwYVX4VZ+AthE0Sk71K4IBIgW5dIZG6JHOMoz2kUyQgpjiDQVI2TVB9Cp+ClKXmQ4RgYHIcFhqp7AYWGHX5rfk8dvq2QM9i9in6kRqULPiCEMG+o7Eqr6svcXMSSwTlTC3E+13tn0qvXHLGKAC3gY05DT0UCxo4N58rdJTiJTs6jr1mtpsc8bxXrDfEltdvEP3o2mLJhwMXLCnSz1YG05W3EfaS4uhOVdm2cLVeYLT4h4tyc4ATGwL38X3tWm5+dK5ah/wIr6QaxGSnlWLNUQVS0eF5lYPGIoCmmnch8cOQD1UzDJxy4tMPuWZzQ2u3VnZd4hthNBIfdTIPXj5ehBqpyVVYltVV7mGhfAE8RVMmN0aQqIlcdXD9/U48e/uXDEwA5yu03sVqc4XOGKtVp7hqd13lp4G32B60np7i5pZUSznDkdQeu1K0lXQFRgyBkooGiOERppQwaXjFHlHSKTawFKyFw6ErB9ouwm9OtyGvsoa/6snUgnRCYv+gBhkJLa3Z4SjHR6b0e1z66dls3zMUbKHDEFbMuT/+/qr3WgyYS33c7aYXFOGtKx8/weBp11npaDEkZ4oepUumenfE0aV+HCj2pnoLfdETB97goUhITm6WpGfwq3UgeFu6EvJF6lwh5xOYa4tHpt3puPU3R/NAToWPXqbNeVdcvUDOmO1ci0lw/DhLXMzW8DYvI1Fw4KBY+i2sBTWobVSMA9ODyqLz8huPLgeszpTZ3WvdiobTKTQU5vKdH01QQxRE09h72dxzGNxTyu1QpyYc2/FxTJxIQC32sp0odO2HXQpXqplD2wzKMGnEmKVWgO3IZep5AoP+hB9Qck0vGeWH6h3UGFEdCAzm3MIxw2bkQdH3t5RBTNM0dLQbCI+SnqfAUPzs146u1Wmz8C35YmI+deVyNIxa0Acdg1If1snP6Z1uDZeI2jwTHIdRm25e8Ave3WRPXIP3TMuiaHkeow6a5wwiE6M/W86ct7mp743SpdsbkjWIInUbzM6rqNwVUOP1FkNDB41EJPyrNh6DEHG4o3C5qAyxYRvZFdcGrh9sgbbzMBxKDJWNUoD7sejMkddDo3pixBTpR7en/9QOiOUWeTzRy6SPD53E7u4Hn9I9ni2BJ+mGVLBL+DWwXkvDJ49AkKeAd+N1dahRDFEcA32KBvhcP9GkmBbFQUZ85G6TyMctRELunCdlZZOGmR6Gmca/W/E8gM1RQseqeVDJ2gVAv1EaZJrImiI4/owPCDW29W/Is2rPrMhjH1Q3cQkK3MGfegzFzhUDf8Wu7QzGAqJrkUDHSQK3ZXpHASgrgcfBHfTLxY430dKl4NqLPDuNba64OJmqcWS81lXzjhgEq0qSpnVBp/YFl9qJu6h0hYW5fv/5Az/1g7WkHP+l1fUTjXf9ZeNYxLjsfQIea0acDDcyG1EwGA5/KEUkeJnh2oshbmz87UzxSw9MDaKFCnd/oTsnIozG1jztK/ZXTKvDgb1yS/5xK/ynM0yK8bPbFrp0662hATQZtdo+iu2uP+sK0i28SKTRdsQYENJO86tvNOoRV9FljrPqJSPTJDU0Abv0sdDkQl1EAITCPIejgmVPtqRIUnWmYvnrZUb64dMDUFusuLqpYreAZXg8MHhq3OpLdXiTNF0HXqsxZN2pISZHcHGkGX7GWBJHbI6GKZ2VIwdzBRcgMPGhv31PhyxOlA2imMCp9od1emhO9lCowZTtH6S4SRCQ5caAmMp7kpOnzjh/e8RIOvqLtlRReg4p93MZVIzESju5CRxTRSGNtw2R3pIo3t+u/22DqxK34QzILZkY1FiPNnI4BGbkf7wZzmm/L53jxKbBCe2BS8fNVkjhGuKeL2wWosFwT9PkmK7DHlNKiHVNrMzcYcr89j+Hc5II2s/MkMsbgpVxsa5YTKBUz2BmcjJHdRjguyei5TqBQBKVqgAHcXOca4WMkaV6hoINpCNPpQoQVNUGG6iuxNb2o6U9Gtp481Z5a0HGxWQtPLtuHHQtV51zSjn9wRen2x0PyfiAkqnw+gZD74qE/hwpzglD+98gPIxwBxuKSWBR6odIomIkJ3pTCLMrgexH0Z1dj2boUlZa3igh0DdSsEl5gi8EKSQAmjFE1eHVsyR+Trdv/ewGS4S41bFOzWt1PXpGSL7MQ0e5Yu8bKazQAug210VtO++LLoHplPXx80pb3k1hRwyWnR8p+GKNeqjhMM/b9EPE8+0UMWEdqZN4MNITa9t81mguTycNJEPiEC8ja6/UX4azpYdI3KuPKOiv8YfVK4Gq/LZuw7KJnKVYUDD8uLCGAEkPEIAT8+j78YinIq8K9kRWu43g7QG48zywZhNmS79j4drC2kUYba0k36ShXs63uHCsZc6oKfGCtELAM1Aj+VAQjO+j9OTz6fM7HWgcQ2ice77E0pG7pMikj2hJJjXOxMFcQ6sL+6ZrKrcgjB6leFJ/Q4f1/UlApR8y/QcB3XXkd9LYzR7eDP6LV0lGCrvvcWD2bny5PxedMitWxHoqqRH/+Hv7UJzRrfMm3HZYaAYWRv85b8AVLRNs3PlDhrQMWVRUAYs0B2U3wBL7B8AtAN9d7f04JNmhlIxinFGAKBiDsEpd3LZ0EIJ/+bnANv3eMRC3n54pYcuV4n2HK5f3ppCWcjkRHVoooYE8979OxBS61ISB80O7fTX5S5Jpq4Mnv74uZ2gLDL/NoRDmQU5kYhUMtnuKXtzNZgfOoG2FzYhU7zYShOeN+ub87ufiXRtrkchRq2o6OuNLaXFi5FiYfs5o4RH2jS7s+fA4UX78uSMRlnC6boCEwZI565a+meI+p6qdSHjAfF37tQO2aUqDihQ9aCLZVf5n6WpYpVySPjKiyM74D2Iu3hmFCHhyUqUfPAa8sAXBNoxf9mGUVMunGtpGkMKzB51TGDdSAocJoo84dZ7wv7y2eYO3ECDZqnJG4WTEx0IfUPLf2iZUR8HONVXmI9VZcd7swUAP1w3/urAqCw2xzCn1m9UEmeFF3tzsel3/+je0/dH+oPTt+aA18g4zqMCdc/A5NfZinzzY0n9BIFlqPyUALsit2ZVZPAErpt577CgOt19nfnENEAsKnY4W6gNtPuey8TnIZcnmxCcvv0o9waabS7QKUJT/CZlnljPHjrOKLj46CParpHDwL6ezsrV83PNqcHVy7+mNp4YGxyRH8IIXiKCYuIvSJmEC/actX7+UGweBRZON+0HVGIMQMcuwJoV4hHl8snz4grzJzA/WNL/oJva9BAFEBpCc6FIP4um5HZVGEuy55ww+obQzsZ8/CSjrq8PzQmTDb4nVIcABwCpRQj03MOexdERFDNXKXXULP1cb7IYyvR/DLWFfVrIcvmVCd8PDg8msVx3EV3oJGCpMPYiAUIWYNSdgSKj1dRvUGbhSvf1QEKLi5dHaHfsFdpmihRfgDkKAvR7qLU8iUT09PQDiBJ5gUgPUnCLS2CLu7h4DoWM2LcicvTCKEI4Rb/g9L+eOqLerMHJu4gCpoLrIZD9M9u3DqS7mDpsy9ccGaOj4YewN/jRNgtCZ4E7Z/WKy/s1GqcgwCeOayKSfUBis3vOmM0+lYriO2xRPT3Tav7LJ7+81JlnMm7yI+C51www1Y3zYpgMoblIYgzpDQifmSJ4hR07AHd26NlFJp+Rcee9GXk6/LANGYEmWuJ80v2NVToSlJULiENK/EDR8c5ZGtqBTXAQAT2uNFtZpXYuriuo6FAOfZv6rvxul4GHmxXndRv+HEEnT4wbxSuzpt2ox/T0o7zauZUKBA8W3mXuj4bbI69p3Gxn21MoqI3yNpfNrJ14+hCGRZF2+PDt+GhvacWrAE1JJ1QcfN8h/5BUz/mM6Ri7WCaJqaODHpOoRSuoJlJdrWKllo4a1Or80z5Vg0qDkki7W8hIW2diulAfrzLbln+wvU9dpxo0Xr6+i7LJ+HCGAoEP39YgKam+VTJMyU86J+rLtxPR7IG8yAIkvFGOIpTUEWEUvjDvINNKdzFashgXuYsfvC+j8BjvXX2Eoc19nZaexlooz4qF9B5BRb/kkSnDEWXs6lKNP5Ld8tky6bj2r7KIzuPFs5zb8OBH3UkmZYSgQl2BoT1rB3BEIXwyEgRojE20jFtzyyZjbj7OXluil48SlcFE7mxxl95y+tXCBEYTyWhCoxWtqmFnfy3hJj78YAFciqlPJlo6kVCB0YP/KR6zl6XIMEuyHZCdxROs0cq6OeEllsDB6q/Aup9q2fSaKzjYXBns+zFulKOg6VfkCMr5HBUXfU1THsHvEMrMsCTDaW1xXObW1Dq1qgqFLSzBJCpXk9Iu6IrrKS+4SA4NTRrDTa29gBsqjF0TGxC+XqQZXnmyi3Hl/OnbBSJ3HeslDioQ2dJTHoEOSVm1nUa4rcM8pcAKC7FjsncptLqryNTe0B9mQ+DP2467UNhnS4dyg8MzGzjBipPRy0PWFMevN+dpNoXfCU5RbwyOQmJEG5g5SnEHKvyII0/8nv8BmUV+msAlgZE1j6GPbCk2UE2K77jGu6kk+uh0ksQjxqALgV7XMo/WSgsNB6LDITDS0v93QDN1EyjwoT7o4Fx+iF4s/QYKT5DQmjToauO4TCqFoepDuZ0NAaJne5YQpHR9Ma3qww49C2tHBYrOGaRW94R26RsOwHHWFXtBUGnH71ZHEG8ipMJQpAr08t1cYkYFgtd204QLRhFNA0Uk2G/rKb4/0aCmtg1IUqVYifNATo+3QJqkSOaT9phAsqPMiC+71p+ziJNXTYnxW56g08NiPhqmhTV1QjvmIf2pKod5Q1HWifzGLV+p2TKwJSqH1+gyf0ctBjuiNeuKsHoMWiy14IzCMbsbArfWiRhD8QdT7OW7jNAlpuAQOVsKk9TCJVnT1fGy9nGgGGubAMtB6/plgK7CJA9VsUSPozt9b9gg0ggzWr95qK2AAKcP5Ii26M3ZngXKzhGa0S61VSizPGOPuIcG4vxfyNbjQ5+6QjQAaM5h/hvzJr/QWOJUFUuLdIzTKO9cViT1h/Ryu0JAp7IB3qLuGcgs1YVkcIh09cjDN/s+0s9LgHaspX5ZNeIOLw3MZ38iZcl+f8Kwg6vxjI7ApOEavA6GGvwq4FQDhHhn6gt5cnIpQiS+jpan9lux8RjmSxyCmXTT2KNkRv46QE5upSQAK25RHFd8PREJxbKcQG6Ozzgws1rFoRww3LWQyNL1nzVAeadaDB8IYDE3Y9WpHA7mIzsh1GNN8faJoiOA5TPFuGbWh9LvqwIUKMvuG4cd8U73HFkRu/V9URJ1s5kKb6rg/ybfCJGBZfjhTPk8qmvXAxvpxHeQX6/fafIxIw4P2VNCPnzzqJTZiRCa/9r9jH3x8JQQ5AqmXiPhutiITuzo39McLAQGKbiMz+Wgb+cNsCmmPSTLG16j0FLd+NOrlFzMH5JRJbx1e6OFYCKwo7No20o+Gvf8sPm1o2d1F0s5cILodQSCpHy+tOb+siQD6MwojpPqGAEDpcUDBzi0qgjFvryDeqzHMOU2Uig2mU5+VhntS7IFion7L6eXYme8w9LWI2Y2R5/0jYGLWEN+Cfhvw5POKE4zORTOdxzbqxGiILpmvGrgJn5mxOF6xMBkrLYNjLXi6L7DRPj5niSs6wzhxmF8oX5lsHhOWhBy/TSdFwsR9GyE+91rIKptcwNCNWxNZ8+q4sHFRv+xPMN4pBVQUT4B7fwXpDWc59MZLlu+VQRDyhM/MJTX2xJe5tYijiOPwBMO6WdtDf/gAgnYmFhkbBJTqXC9X2JDgGncdNxevaGbR3/Ur6Q0pVCEeYdxb3LrfFewJ7hrZBcko0Qo4OZsyZjxoNa5N5pbJPJedqRuFt8HueA4vZkeP6sCQbdYh8nsPj/QVau5rz6c5Z+n8UUXUswIIqA0pWAQAQAXh820l2Iphv1eXbxLttQiXXjuHYNJHWWHb2CUtCmfNg37TrnGlU6UfhWNl54xAT5vl6pIsPJW3LflUr+nyWY8nX5fJeuxv+6DDIth7CuyrAa7U0lmF3PS2IZx9FdHpZecY9IvqQ0qOoeF4QSn18oVezgZ7Uy+e/ckhJWUKqlinR38ljfE5kdjUGc5ra784JMCutCitl6ZpMBL27U3MpMB3qx0R0ISHQ/+ZbAZ962zMlU+VDOnuJ6BDgr3r1AzJQV8I0VpIXjlZnUEcUVAtJAr9QyWU6zjKLEXMtgXftPgDvaMiUGAUjfF6QVP0a57Fh+XUZlWvPbkEs1D+YXQoS8rceSDc20lezLfDT89A6ITOhhuJnyJouJkEiMw65HD5YpVMkO1IfXQ+9PhKxSJyDytUKMnq3Qtwl4SpdIXOTJ+Lhgzh8cpzrFQ3TwauaOsEcmfBdbcG4xrhRoF+FQJW/5VGzOBGXilcfv5y/nR02l4/JAv/cAtFMn2r7XrpyGCHWU4IbUrSB2sed4ZkSzu2dNPlqtabIkn97JVWlSc+YFqyDJO06hxIihEBxzYBP0zs/uxAhUfm/kEqhHbTf8jSI+Rw82VcbxrM3F6IizBYv8ChvtF+wIS3pFgHTppdDziMesb4EStZt3T+X/4GuNuk5vs3BucN8keAPWNy/KV3Q2xi9RsoYUSScPzNLGY1A8zkTSHUCaXGJb+uP2a3koxE9nYT0r927xXudPvjUANz29dRthE/kCWMUWWctz0zXlx8mgMabldW1vWwcuDPiRo9wpBD5KTvEGKTzUQvKXU6rQawx11UG3N4g1YX3keAm17aOCH7nymnZPafxoIOMz9buzLgvjom7I8ZCwsgVMnyqI++2Gzyipgo75l7l1V5XsdQvnm65/0TFd3+bqPyaWumxbN33ZOVnSAodDMuU8RKfDY8C67z9LdPSTZHvkZ6NNdYCYds8XGsJJh3/pSst3gB9WjBKILjWggTmVPrOFwvmseshvXKeJAx4Lf9QI9+qHV6VL6KivYLiawfNQPlVR8K/cAiopQSafj9LLLZDMZ3/1zIblNBnJxrgLzHP/KrCHhM8tR0rFZAFLhhTgfxugN7Dqk8lv5xAEdoeZozJCFqh9Vkgiga5kUoGQVSttBOULvoZ98/hmUmpJRjVN3cGlq9ZryTnc6a7XpA7TP4I2FuUwmyjUwMtcH79VS7xMOZQMOjf5CxF1Qxmh+5nfZKToJ00TdzSllHeRuOYqyJ0+0x+AVUOk8U3mbyVZv59cjzP2xYwpPxp6Fao+cuR0r8tPow4Hbh1Q+g/bSBuLgo15xD/U7SH4SecJIwuLidCC8T5Mz4zteByVWrhrUedbbDCIxLQTaTSgVqE0dbfiext6eADQ+lIST2bpEs6fTEy2feUMwcVaQxP8eIATVDR6VygrG4yLGGarzEgrKJ0xIrUMCXUaBjowc36YfIhrgWOs+wh3ldnBoWrRiL4GQKiExKCZJ9hQuYIuvuKfVOpKxSC3AaUYnc/y7sZBgq0jS4Lr14h96QqVhYvdoz0S6yOWXCBiNyzz1rcrp9GM2+p5rH27DFtmyKRlS6emkyw+Cyx7TA5OPmSGda1PPEuOueoF4CNbGfWuF1xr+kJ4EVsi2Lwf1ubFlCgmDByuPvD3wQhp9FBJKQbmgQYzXnvj/mkPldnxJYKzDSCM6R22T4Wb3Q6rdQVb/jwDMFDNTkRcYDiqsMmP+r/ViWzoPrtGhF7ZVs0NHm2aLYw2i2DW6ItOQ8WpcDqRxJAn52U+lX1HeMYDThit27nI5HapR8x3TGLgH2LiaLJamSzSH94At/7pmY4ZbjYkCSmerU2DhLGYz6g3u3iD3E0GcMZZL5zOcFX9ZXON+rPXpt7pa+D8XFZS7nSulNqLvdf84H5EQYd7glByfW8JTPR/7bQl0dLaAP0b+zmV2LWA99e6PLYK2TWnOPHz83G/mmjLLbD8UT0bAch4weTj4Kecxi+WPiALFviukQ7801cGg36NaP9HBISB94cfKalwe8D6bOesqO2zzZQa2cuk0X5CmC6P7f4Y4Xfd+iGINMnk+nZJzeSgE4TJDCUT9I+JxL23dkxas5ZbVVWyPet/Fb+QPl5VpJiJniXs8GZqm4qs+tJBgB/O4X010qsUhw5g6AI8WYf9U1HTOfO0esYb7/tvtNoSs2ifwZaT+tyIzzRk/5P12XtZHbCXI4tYShrWKqL+fzB9Knykdg0lfULuI1zmf/wFI3Q4WV6cT9Uqo8Ygj+hm8QzYd6bbQOzBQvgR23pv/kTUS7rNpmTVZVmzbGBSEWFHCzj2TALL9mseXNuEmzWz1t2ERF3dSf+lQQ1ycb7tA89zGavncoJU0nHzlBC43PU7UuwipDoDjD0Ttc8bIs1JEBASAJAP19A8KI+aXYwnfLfFy8a33ebO/EpSSmKyEaTqPhwWG3YBnf3X8mBUBVOHRCFe/64Fl0Zwgw/4yLaUN2fvRQ8HqOUsNeSEYAY2RS9MHBqKbroTmawbBJ+42AhJ30J2G98Bq2jNqoaSptJGiCePYOcMGjYM1wV6QkqsD6Dkd2bo9f6fTlivFFh1wICelWvFOL7uKunUiBOf53xSBdEOIc15EOGfmfZ9WFQ7UjZrPeqfTSVZaJ1/I+zE9CB88fed9IS/9IowxVB5luHbstqffQHm6JCkDz5XJ5P8dBKgrJbdzSWSn99XCEWGueB870SiF8bxBeqsRr9/mGi7XWCbfHOQnTtAY7mylqWIF6ElZ/tN/f5zstZSklkbkvWxRmHUgZJa2ca3IW2To0wv3qjnbz8fW8rl130vQQ8tgdnkJB6ZbWlb85eUT31OUuCjsNtQ8AmR2M8dFj328fdG78h2zmqJzcAOZYOemIngFPGJWSCTLKbslpZoHP1E9Fs8Y1pJnLOpjd9Py2rtbDWyxLnYFv9SZJv8mJ5omUTilxbcsi1KSeQqqZxqJBZRzuA56q5qHAyJtzFL8UZL0diY2rhzZvgmn0q9Uqcabv4sCkIx7v40cm7Wpv7NG6JjQpuHhk34SQ9AghproqP1vKWIdD0laSkCJXNUPmg3IdWwrjTE9LGqBrIWFZDU8Su9q3FUTcBhzNWgowRxVfEywvzWxuRe4xbLoA4669YDtJ5s01PoCvyePJspggMhbi+gUHGfzcoCpDToZzvFyJbnIhE+2Uq8TbQ2y+B3ZyNEWcdviOwsXtmOET+R+sAV4H7vJrGFoH852RsPxxpAVBKSeCqtdFoX7iEBqsESrZl4//YDIJaP73P8X9w2u3aZX3qHzoW5rngh4+VZlh4+NmdBSdM2dr4inMgRNcoVXxDXflME+HFVPJIKHquepvX4j1xCoSalGfVhsLKz/8ESWNt9cBCwMJUWCCjf7IffjRf0jxw8tifMKIHuoK8KylpXtA3rYRuKx9aTzagLblyR/YgSl1gQ/o/JKdj3avEJ8VCl8Fg3JmOFKomFXyAAZyeMiuH8YS9eki47t+Iz2s6Rj+EuZKzy0rjZrM44SHyiDD1ftkzPqnayFO2LeQcO6eN8jltyh1ivJ9nlNXwyDAdCvXopKFbc54D7qHy/5aiQw0LVFwn7nxQHSxUykFctOJFylLcwj7TOjZFO4COyjT2NDZkXtbGLsCMssyuB1b9Rz00Af+ZH9ocyrupenj5ME/D4ty5Z7KIBlKANBUZsHKhWk3/0sxVB+JKD/8a/2Pd3UQeTy6Uq9P9Dih8yyUvWb0MhKumMrCUxQ2BS/i/n0NZw0+0c//HKnrqDP7f6MpiIjAzlKTZ4EOP9By+x/v21lfAnhZWOoXAnsW7knwTKS1sgNd65z3x7ohRZKyLKaNlLaB7LhTz054z9HTqUAbtrhKjscFaXmF31LSlOFvyMksl+XJTTz2p62Xfnp0iHBUOx+DGBuooRa8QdnbO2QX0PoH8CRxHJeUNJmDPFaySAhhaAPhDlHd4aeifQbdQqTtidu9DiuiXiEm1Y/AoJCEgSH2QpHzbJgMdJcmWCXrB6g254Jjsmui+ndBvdRezaOCo6vVdBeKdZk1e57Zu4Ez9VYRTKH4x+SD6AIxjsHEdakK4tFDrZoiNhZWdS5zV4Pqiebs9fiio5wWJlojomX9DCt27l1QkF6IGglH0aYQk8eBfK2FvLbd5Sdsm+97D4RfiF/VnO8hkd3jynXehRHvx7N53AENsS4p78dxLeTBptfLqR8UoxYCy5b3OVXxpuPpTsGSO1T26pwwTZkdOmEGROO0BrBQVxEA9zLsbkR/hBxzWNUoDEjtJ3JgI5R0wevmp0pFuRYc0uUE+7r520b8o0PVdqwHyWFAVqqR5xG0do+NUsuVYONJEfQyIrYR3XmPlUyzJLjuWQGv++8J40hM7jvuW0H/G/yTFV2IScUPAwne1FyG+7EkQpDDEoXVpDF+GFzLglxE20iFDf4fRVy/YwuKMTil+ncOWVmmhjjkN/ekvAzQLX+jv1V0tTV/gHMSTVY43A+z93o3ehScUGPlnGnwULrv3xHxI61kk6+rrZotQOHpsx3rCSPHLTwEQouAqKSevRzDyOvJrhJFxP/KZDtco4CJr9/k8QWJ5GANA+w6VQ7QWhhb6nyE0AzQGuJl/4KHCVe8ifNUsY91T8wWXKDbd6hxT/99B+HB3JXFYga4gb8S6YqnOHeQGcKHjZvEV5XJynKqEVQ7jqfhxO8c33KUtMnMty919MiMNV7atwHprC2jRaNKh+Sq7QVZcgZq60pZ7X0kbyXEmeb5cN35ZNITyGPDXq1Rojs+d7mUJXt/SmmS8iFxLZ8tcl/AnsXRNBSGFQ8xUJKoYjgspX6Ol+zTsPznFUUZfxVBUYZHqrieOP06fuQtORwPx8UzZc9bPyEp3mX9G+620dpIcRaABspB2bKBQ/whE0C6LNwlorTNdk0x4B41VKectfz+Xdk3+PLB25iZ3MEFtAWGx+uaIcKye+tW0JLCtSNhJCD0ZdZy5OaRaVyGs2dnGfnXKngBgC86b1YgDto9Lmo+qSXsVOndMkZVQ3mJwRW2WQJC02RxZYCqkCeqFLsUQE2Pc0w0NGt5XL9fNst2VQnqqaJw1PMTm7vrrZK868vXBbZMYtVpKJa5f5VigL0yaoAD8XdHnx/7CISC7dP5xrH9QqavDiRpDiEX6DRUbDtT5MwyhT8S367nKsIh3WRxlJbf795W4/cDV96RUwdwTvHt4xU4IwCveSAAQHlS6L7XWOqecVaxo7WvNwGGv0kQdmYS1oCXQnsdx6OZG1+YUKC9Hwa+/Ro4+0caXqvrkaYEtpwKAMacSDd+txEONLaFGcK9suwTwj+GQuitqo6B32RdDhJ9236Tz89SxCi8bQoiJ8J5C1/aAgsmABTm8ZXdLhd8RlPKJ1IpWgqdGv93o9AnYYiiZlorS+G3H/EY87t6EpT+S1iZ/VJA0A8yKQcOeZUQ5z15j5iCe6WOZ9gsFE0L0mOXZ7pw3o4SxvnosGRnZIi8kUD7sOTZWc8x5j3PteGbPViWy/t9bbzxy05qBFz+UCuWrbJEIlT5cgsJZlHGvgo86y02Hkyy5H0IopzkhFPqmBQtXx9FRkyYQLggfmG8ltyY9Ma3oJQs0/UDCH2UGrh+aV2fi9DVTrkR7HztkSQea/fclMIa/I8vFF/PJZ5KYUB/bwu0zrO+xpRo3tMXBPqwF3j5jsU8GwVC25VUjXR/FDpICdEPsQIYs6GNgWwxe+gIiL+y4qlhAyTGzO6OqA2mXTw3PxfbKqQYXwXzxI5zt90emMbAaIWB242/KVSKfgcpXPc/Sf9XpN6NFzRpddM7S8u4xLUsqQNz8D0qtgjVbtuYw28wdJLRUSuH14uBsQ/jHDaiqCKMgrc4ziJW72sXpFlJrYOPqrX17be6QnCHkt8BdCC9QaMP06gRfcNpV24jgQ++kIX8jW1PTr1NKWr9S+FCOwen7Bve1h3DcefUdsveC00UBGC/rRqYT9DynpM0woYuTpPcELX63ZTHYffO1f7qySQLpjtVtxwx8jQEjuGNJQT2e3Pty/rQEkeCZ5eGh5IxBiv6W0JPlaxl4qbTbft60wuALm8cmxAdfHWfUwQ3iylCL7fyuyjUHqn+oUTdR0CN/6QyPHkc79ZPzCp2TpkFslIwj8lj9o6WXnoReU40FSYfzKJ1vSXI7MRa4tD0sZL3j9rx8IAhmxMdyhWgzC+vDyGR06oXpdtxOoUzo5j6UNMoCm15W9Qo369JLhUD1bBhwz9wmXolg6uKM2xntEp4EV/S3dZpVGCQCcH078fPY4W7ce+5wlXr7VAdvX2c+VVsbL0Z/76Pd2soYNGuOydD7Q8fvu0tydfa8WXb+6fTDcaD22FvJGXG8e+4RGe4EIp/+Oc6ZZ2ikl21nM2YsF0hvqYkftX7RTOb0T6rzn1x+eMNyHhVEHmjpc2z704B2IsQrRQbUJmX9HS93x3VCxfmQdzDpSChXv2yFgnyIUWY/bcKH+KM+lN/ElQstFA/Os48Lw6uIXSkL6MfR8MuCDgfhawdhVGtwNEZXRhIZmEd10N9XDpXtwtL/UtEkawj7xVrxi8XyeBWN8uPIaPmUPpfP42BbXGKN+t9DRhiBfxzIOuOYDuxan4Zxurz7/DjvRze18aVLTsYWMOCdTuqfIt+GZq1kjjxBrrFY60wqw6T7c7QTYWTJCMrYvbyXkv+lsq/4yQP7e7ouhYxhUHzsIj5gTVHwuLBVGBYVevUmulNqtpEVB3oNsmeiXEoWObKpd9g5DlTc0VSABwG/0sYi9ZXykiR98mOUIITDEyG4QOb9A1eCa+w0Eu/B1VHrwCcGCM+DEF9XHJdc/C/YpPOFj1rwc1xGweekW/uSgy9SUKadhxNb1ZMFokMyzdI3SuPZdfmGQyptK/0K3zBbXNZCptQdSefyMGIrQTYayKop05JddH9ZiOnxEu+C40imqvjkoNqNdZ5/Rw+Y9v8hkvBUdK5i1z9UvmanbRbOir+Oy6BjmPvKXLXA1xdeDpaDYYX33/qoGzuG2CQQLMk1UNBDhD4v1hYQUcjBD39fewcpo+f9spUUPKf3MKrGO9k2TQ4bQzQ6WAqzcPAYBnZthDCLiivJOYqoRNhPXzIDJLo6NKANv8FQZ+ehQegPAQ31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"size_under_512kb": true + }, + "score": 0.33 + }, + "code_analysis": { + "files": { + "total": 2, + "code": 0, + "docs": 0, + "unnecessary": 0, + "unnecessary_list": [] + }, + "lines_of_code": 0, + "dependencies": { + "production": 0, + "dev": 5, + "total": 5 + }, + "complexity": "minimal", + "console_logs": 0, + "magic_numbers": { + "count": 0, + "excessive": false + }, + "function_length": { + "count": 0, + "average": 0, + "max": 0, + "long_functions": 0 + }, + "max_nesting_depth": 0, + "global_declarations": 0, + "naming": { + "dominant_style": "unknown", + "consistency_pct": 100.0, + "camel_case": 0, + "snake_case": 0 + }, + "error_handling": { + "try_catch_blocks": 0, + "has_error_handling": false + }, + "comments": { + "comment_lines": 0, + "source_lines": 0, + "ratio_pct": 0.0 + }, + "separation_of_concerns": { + "verdict": "single-file", + "files_with_rendering": 0, + "files_with_logic": 0, + "files_with_both": 0 + }, + "html_validation": { + "valid": false, + "errors": 0 + }, + "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 8, + "tool_calls": { + "total": 1, + "bash": 1, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 1, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 19 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.602 +} +\ No newline at end of file diff --git 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0.5, + "run_id": "tetris_context_file=none_effort=high_human_language=es_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3", + "run_number": 3, + "claude_version": "2.1.92 (Claude Code)", + "started_at": "2026-04-04T09:25:20.983132+00:00", + "wall_time_seconds": 521, + "exit_code": 1, + "completed_at": "2026-04-04T09:34:06.164569+00:00" +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=high_human_language=es_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl b/results/runs/tetris_context_file=none_effort=high_human_language=es_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run3/transcript.jsonl @@ -0,0 +1,8 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "high", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Construye un juego de Tetris jugable que funcione en un navegador web. Debe tener todas las mecanicas estandar: rotacion de piezas, eliminacion de lineas, puntuacion y velocidad creciente. Usa controles de teclado para el movimiento y la rotacion.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-8xq7n6a5","session_id":"90bceb9f-5727-45fa-8261-4b5151e69f48","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"c39036e2-6e98-4d17-a3ee-d3419c8bcc75","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01SHSxEa8UXZUYmwthhodgtA","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to build a playable Tetris game that works in a web browser using TypeScript. Let me create a complete Tetris implementation with:\n\n1. All standard mechanics:\n - Piece rotation\n - Line clearing\n - Scoring\n - Increasing speed\n2. Keyboard controls for movement and rotation\n\nI'll create the project structure with:\n- `index.html` - The HTML file\n- `src/tetris.ts` - The TypeScript source\n- `package.json` - For TypeScript compilation\n- `tsconfig.json` - TypeScript configuration\n\nLet me plan the Tetris game:\n\n**Pieces (Tetrominoes):**\n\n\nI, O, T, S, Z, J, L pieces\n\n**Controls:**\n- Arrow Left/Right: Move piece\n- Arrow Down: Soft drop\n- Arrow Up or X: Rotate clockwise\n- Z: Rotate counter-clockwise\n- Space: Hard drop\n- P: Pause\n\n**Scoring:**\n- 1 line: 100 * level\n- 2 lines: 300 * level\n- 3 lines: 500 * level\n- 4 lines (Tetris): 800 * level\n\n**Level/Speed:**\n- Level increases every 10 lines\n- Speed increases with level\n\nNow I'm writing the TypeScript code...\n\nDefining the game constants and piece definitions...\n\nActually, I should step back and think about the overall structure more carefully. Rather than just defining constants and arrays, I need to plan out a complete TypeScript implementation with proper project setup. Let me create a well-organized project with a package.json, TypeScript configuration, and separate source files that can be compiled and run properly. I'm mapping out the complete Tetris implementation with all the core mechanics—piece movement, rotation with wall kicks, line clearing with proper scoring, level progression, and the hold/preview system. I'll structure this across a few files: the main game logic handling the board state and physics, an HTML file with the canvas and UI elements, and the necessary config files.\n\nWriting the game logic... Defining the tetromino shapes and wall kick offsets... Finishing up the wall kick data for the I piece, then moving into the scoring system with point values for different line clears and drop types, followed by the level progression speeds that determine how quickly pieces fall.\n\nNow I'm setting up the core data structures and utility functions for the game—defining the piece interface with its matrix, position, type, and rotation state, creating a helper to initialize the play field, and writing the rotation logic that handles both clockwise and counterclockwise turns.\n\nBuilding the TetrisGame class... Setting up the canvas contexts...\n\nNow I'm loading the saved high score from storage and initializing the overlay to show the start screen, then setting up the keyboard controls to detect when the player presses Enter or Space to begin the game.\n\nSetting up game controls... Setting up the game state by resetting the board, score, and level, then initializing the piece queue and starting the main game loop.\n\nNow I'm handling the pause toggle—when paused, I show an overlay prompting the player to resume, and when unpaused, I hide it and restart the game loop from the current time.\n\nContinuing with game mechanics... Writing collision detection and movement logic... Writing rotation logic...\n\nNow I'm implementing the soft drop and hard drop mechanics—soft drop moves the piece down one cell and awards points if successful, while hard drop continuously moves it down until it hits something, then locks it in place and awards points based on distance fallen. I'm also starting the hold piece functionality to let players swap their current piece with a stored one.\n\nSwapping pieces and resetting positions... Writing game logic... Writing game logic... Writing the block rendering... Writing the render loop... Writing the rendering 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":521,"cache_read_input_tokens":4241,"cache_creation":{"ephemeral_5m_input_tokens":521,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"90bceb9f-5727-45fa-8261-4b5151e69f48","uuid":"8b48b990-6a55-492d-bc3e-3b156c467926"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_015hB2qcUUGwXPb1GCbVga9a","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to build a playable Tetris game that works in a browser using TypeScript. Let me create a complete Tetris game with all the standard mechanics:\n\n1. All 7 Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or space for rotation)\n\nI'll create a TypeScript-based Tetris game. Let me think about the structure:\n\n- `index.html` - Main HTML file\n\n\n- `src/game.ts` - The main game logic in TypeScript\n- `tsconfig.json` - TypeScript configuration\n- `package.json` - For build tools\n\nI'll use a simple TypeScript setup with `tsc` to compile to JavaScript. Now I'm designing the core game mechanics, starting with the board structure and piece definitions.\n\nI'm planning out all seven tetrominoes with their colors, then implementing the core gameplay features like gravity, movement controls, rotation with wall kicks, line clearing with scoring, and visual elements like the ghost piece and next piece preview. The scoring system will reward clearing multiple lines at once, and I'll add a hold piece mechanic and progressive difficulty as the level increases.\n\nWriting TypeScript code... Defining the piece shapes and colors... Writing the TypeScript implementation... I'm switching to a simpler approach using 4x4 bit matrices to represent each tetromino's rotation states, storing them as flattened arrays for easier manipulation. Writing the complete Tetris implementation... Setting up piece definitions... Defining the piece rotations... Defining piece rotations... I'm getting confused with the coordinate systems here. Let me step back and think about the standard Tetris piece definitions more carefully, starting with how the pieces are actually oriented in the official guidelines. I'm defining all seven Tetris pieces and their cell positions, then realizing I need to handle rotations systematically—rather than trying to calculate them with a formula, I'll just hardcode each rotation state for accuracy. I'm working through the J piece rotations in a 3x3 bounding box, trying to figure out the correct coordinates for each state as it rotates clockwise. I'm working through the remaining rotations to verify the pattern. After the third 90° rotation, I get the configuration at (1,0), (1,1), (1,2), and (2,2), which forms an inverted J shape. One more rotation should cycle back to the original state.\n\nNow I'm mapping out the L piece's rotation states in the same way, starting with its initial configuration and calculating each 90° clockwise rotation to establish all four possible orientations. Completing the rotation for the third state, I get (0,0)(0,1)(1,1)(2,1). Now I'm mapping out all four rotation states for the L-piece and moving on to the O-piece, which is simpler since it's a 2x2 square that looks the same in every rotation—just (0,0)(0,1)(1,0)(1,1) in a 3x3 grid.\n\nI'm realizing the grid sizing is getting messy with different pieces needing different dimensions, so I'm going to standardize everything to 4x4 bounding boxes. The I-piece will use all four rows, while J, L, S, T, and Z will use mostly the top three rows, and O will sit in the center. This way I can handle spawning and rotation consistently without special cases for each piece type.\n\nDefining piece rotations as matrix operations...\n\nI'm implementing a rotation function that transforms shapes 90 degrees clockwise by transposing and reversing, then applying it dynamically when the player rotates. Now I'm realizing there might be edge cases with certain pieces like the S-piece that need special handling.\n\nFor proper rotation mechanics, I need to implement the Super Rotation System with wall kick offsets—these are the fallback positions the piece tries when a direct rotation would collide with walls or other blocks. I'm working through the standard SRS wall kick tables for non-I pieces, which define a sequence of (column, row) offset positions to test in order during rotation attempts.\n\nNow I'm laying out the wall kick sequences for the I piece, which has different offset patterns since it's longer and rotates around a different pivot point.\n\nFor the rotation logic, I need to handle both clockwise and counterclockwise rotations—the CCW kicks will mirror the CW ones but with reversed state transitions and negated offsets.\n\nRather than getting bogged down in the wall kick complexity, I'll implement a complete Tetris game with all the core features: the seven pieces with proper rotation matrices, a simplified wall kick system, ghost and hold pieces, a next queue, line clearing with scoring, level progression, and game over detection.\n\nWriting the complete implementation... I'm going to write out the complete implementation now across multiple files. For the HTML, I'm setting up a clean layout with the game canvas in the center, flanked by panels for the held piece on the left and score, level, lines, and next pieces preview on the right.\n\nWriting the TypeScript code... Defining the piece data...\n\nNow I'm thinking through the wall kick system for rotations. I need to implement the standard SRS offsets that determine where pieces can shift when they rotate near walls or obstacles. For regular pieces, there are five possible offset positions to try in sequence when rotating clockwise, and the I piece has its own separate offset table since it rotates differently.\n\nFor counterclockwise rotations, I need to figure out the correct offset logic—it's not simply the reverse of the clockwise table, so I'm reconsidering how to properly handle CCW rotations. The tests check out—negating the CW wall kicks gives me the correct CCW offsets. Rather than deriving them each time, I'll just define the standard SRS wall kick tables directly in code, with separate entries for CW and CCW rotations across all state transitions.\n\nDefining wall kick tables... Defining wall kick offset tables for the I piece...\n\nActually, I need to reconsider the coordinate system here. In the SRS standard, offsets are given as (x, y) where x represents horizontal movement (positive rightward) and y represents vertical movement. I should make sure I'm using the correct convention for how y-axis direction works in my implementation. I need to convert the Tetris wiki wall kick data to my screen coordinate system where row increases downward instead of upward, so I'll negate all the y offsets from the wiki values. Defining wall kick offsets... Defining wall kick offsets for the I piece... Converting the coordinate system from the wiki format... I'm working through the rotation transformations for each state transition, mapping out how the column and row offsets change as the piece rotates between different orientations. Defining rotation kick offsets for the I piece... Writing the complete game... Defining the Tetris piece data... Defining wall kick tables... Defining the Piece class with spawn logic... pieces spawn in the top 2 rows (rows 0 and 1 in a 0-indexed 20-row board), but these rows are usually hidden. The visible board starts at row 2. \n\nActually, for simplicity, let me not have hidden rows. I'll spawn pieces at row 0 (top of visible board). For the I piece with the 4x4 grid where the piece occupies row 1, I'll offset the spawn row by -1 so the piece visually appears at the top.\n\nSo the I piece spawns at row -1, placing its actual blocks at row 0 where they're visible. For the 3x3 pieces like T, J, L, S, Z, spawning at row 0 puts the top row of the shape at the board's top edge, which works well since their blocks are mostly in rows 1 and 2 of the shape grid. I'm working out the spawn positions for each piece type—the I piece needs to start one row above the visible board so its occupied row aligns properly at the top, while the other standard pieces can spawn at row 0. I'll handle negative row indices by just clamping or offsetting them during rendering.\n\nNow I'm mapping out the scoring system with multipliers based on lines cleared and level, plus bonuses for soft and hard drops, with level progression every 10 lines. For the canvas layout, I'm planning a single render surface with the main 10x20 board in the center, a hold piece display on the left, and score/level/lines info plus a preview of the next three pieces on the right—I'll calculate the exact pixel dimensions based on a 30-pixel cell size. Writing the HTML and CSS...\n\nNow I'm thinking through the architecture more carefully—I need a proper game loop with `requestAnimationFrame`, separate update and draw functions, and a state machine to handle different phases like the menu, active gameplay, pausing, game over, and the line clear animation where I flash the rows before removing them.\n\nWriting the complete TypeScript implementation... Defining the spawn shapes for each tetromino piece at their initial rotation state, with each shape represented as a grid pattern showing where the blocks are positioned. Defining wall kick data... Writing rotation helper functions... Defining the piece interface and game state...\n\nNow I'm setting up the core game structure with the board, current piece, held piece, queue system, and tracking score, lines, level, and game state. I'll also need to manage the drop accumulator, lock delay mechanics, line clearing animations, and combo tracking. Then I'm initializing the canvas and getting the 2D rendering context ready to start building out the game loop.\n\nI'm planning the layout with a dark background, the hold piece display on the left, the main game board in the center with grid lines, and the stats panel on the right showing score, level, lines cleared, and the next three pieces. For the lock delay, I'll use a 0.5 second delay that resets whenever the piece moves or rotates. Game over triggers when a new piece spawns and immediately collides with existing blocks. I'm also implementing the standard 7-bag randomization system so each piece type appears exactly once before the bag resets.\n\nWriting the complete game code... Writing the Tetris implementation... Defining the game constants and piece data... Defining the wall-kick offset tables... Defining the wall kick offsets... Still writing helper functions... Setting up game state variables...\n\nNow I'm defining helper functions to validate piece positions and check collisions against the board boundaries and existing blocks.\n\nSetting up the piece queue system with a bag-based randomizer that refills when empty, then implementing the spawn logic that pulls from the queue, initializes game state flags, and checks for immediate game-over conditions.\n\nNow I'm implementing the rotation system using Super Rotation System (SRS) kicks, cloning the piece and trying different wall-kick offsets to find a valid rotated position.\n\nContinuing with movement logic...\n\nNow I'm handling the horizontal movement case—when the piece shifts left or right while on the ground, I reset the lock accumulator and increment the move counter to give the player more time before the piece locks. Then I move into the hard drop function, which instantly drops the piece to the bottom and awards points based on how far it fell. After that, I'm calculating the ghost piece position by simulating a drop to find where the piece would land, and finally implementing the lock function that places the piece permanently on the board.\n\nWriting lock logic... Writing game initialization... Setting up pause toggle and movement controls...\n\nNow I'm handling the game update loop, tracking elapsed time and processing line clears with their animation duration, then continuing with the active piece logic.\n\nImplementing delayed auto shift... Finishing the ground detection logic, then handling the lock delay timer that triggers when the piece sits on the ground. I'm reconsidering the overall structure though—this functional approach is getting unwieldy with all the state tracking for DAS and soft drop mechanics. A cleaner implementation would simplify the delayed auto-shift logic by tracking how long each direction has been held and moving once per frame when the timing thresholds are met.\n\nFor soft drop, I'll just scale the fall speed down when the down arrow is pressed. Now I'm planning the visual layout: a dark background with the main 300x600 game board in the center, flanked by sidebars showing the held piece on the left and score on the right, with grid lines and a ghost piece preview on the board itself.\n\nI'm also thinking through the line clear animation—flashing completed lines before they disappear—and sketching out the overall code structure with constants, game state, logic functions, input handling, and rendering. Now I'm ready to implement the full TypeScript solution, starting with the background and board rendering, then the ghost piece and locked pieces.\n\nFor spawning, I need to account for the buffer zone above the visible board where pieces initially appear, though I'll keep it simple by spawning at row 0 or -1 depending on the piece shape to avoid empty rows at the top.\n\nWhen checking for game over, I'll verify if any filled cells of the spawning piece collide with existing board cells, focusing on the visible rows where the piece actually appears.\n\nNow I'll start writing the implementation and handle edge cases as they come up.\n\nSetting up a clean TypeScript structure...\n\nActually, I'm going to skip the class approach and keep it simpler with module-level variables and functional code instead. I've been overthinking this—let me just write the actual implementation now. I'll use a straightforward setup: game state stored at the module level, pure functions for logic, canvas rendering, requestAnimationFrame for the loop, and event listeners for input. For the DAS system, I'm going to track when keys are pressed and trigger auto-repeat after a delay threshold rather than accumulating time per direction.\n\nImplementing DAS tracking... I'm settling on this approach with separate tracking for held keys and timers. Now I need to implement the full code with proper grid rendering—dark cells with subtle highlights for filled blocks, and a semi-transparent ghost piece to show where the piece will land. For soft drop, I'll use the keys Set to detect continuous down presses and apply the same timer-based logic I'm using for left and right movement.\n\nWriting the complete implementation... Defining the piece shapes and gravity speeds... Defining the wall-kick offset tables... Defining rotation helper functions... Continuing with the piece initialization and game state setup...\n\nI'm defining how pieces spawn on the board—the I-piece starts one row higher since its shape has a blank row at the top. Then I'm setting up the core game state variables: the board grid, the current falling piece, the held piece for swapping, the randomized bag of piece types, the preview queue, and score tracking.\n\nI'm also initializing timers for gravity-based dropping, lock delay (how long a piece can sit before locking), soft-drop speed, and line-clear animations. There's a game state machine to track whether we're in the menu, actively playing, paused, clearing lines, or game over. Finally, I'm establishing the timing constants—lock delay of 500ms with a max of 15 resets before the piece locks, line clear animation lasting 350ms, and soft-drop moving at 50ms per row.\n\nNow I'm setting up input handling with key tracking and auto-repeat timers for left and right movement, using DAS (delayed auto-shift) and ARR (auto-repeat rate) constants to control how quickly pieces move across the board. I'm registering keyboard listeners and preventing default browser behavior for game-relevant keys.\n\nHandling key presses by checking if we're in menu, paused, or playing states, then routing movement commands to the appropriate handlers while resetting movement timers when arrow keys are pressed. Writing game logic... Writing game mechanics... Finishing the hard drop and now implementing the ghost piece preview and piece locking logic. I'm calculating where the piece would land if dropped, then placing the piece on the board and checking for completed rows to clear. Still writing game logic... Handling input for left and right movement with delayed auto-repeat, then checking for soft drop input...\n\nStill writing game logic... Writing cell rendering logic... Writing the cell rendering function... Writing the color utility functions... Writing the ghost piece rendering...\n\nNow I'm putting together the complete rendering pipeline and main game loop, starting with the layout structure where the left sidebar holds the next piece preview and stats.\n\nSetting up the preview drawing function... Writing the complete implementation... Setting up the project configuration files...\n\nI need to fix the TypeScript configuration since `\"module\": \"None\"` doesn't work properly with `outFile`. For a straightforward single-file game, I'll configure it to bundle everything into one output file with ES2020 as the target, and let TypeScript handle the module system appropriately. Configuring TypeScript with `\"module\": \"None\"` and `\"outDir\": \"dist\"` will compile the single source file to `dist/tetris.js`.\n\nI need to verify the correct casing—it should be lowercase `\"none\"` according to the TypeScript handbook. With this setting, I won't be able to use import statements, but that's acceptable for a single-file game. I should also consider whether the strict compiler options might cause any issues with the implementation.\n\nNow I'm thinking through the type safety concerns—things like `ctx.getContext('2d')` returning a nullable type means I'll need to handle that properly, either with a type assertion or null checking. Let me start writing out the complete game structure, organizing it into sections for type definitions, constants, wall kick tables, helper functions, the piece factory, game state management, core logic, input handling, rendering, and the game loop. I'll make sure to handle all the edge cases as I go.\n\nWriting the Tetris game code...\n\nFor the scoring system, I want to keep it straightforward: base points for cleared lines scaled by level, plus bonuses for soft and hard drops. I'll add a simple combo multiplier that rewards consecutive line clears without overcomplicating things like T-spin detection.\n\nWriting the scoring implementation... I'm settling on the visual design now—dark blue-gray background for the main canvas, a slightly lighter board with a subtle grid, and bright cell colors with a 3D effect. I'll use a monospace font like Courier New for that retro feel, and keep the text white with colored accents. For responsiveness, I'll stick with a fixed canvas size to keep things simple. Let me write out the complete implementation with clear setup instructions.\n\nWriting the Tetris implementation...","signature":"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start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 22 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.602 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 22 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git 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a/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/transcript.jsonl b/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run1/transcript.jsonl @@ -0,0 +1,6 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "max", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-o9xeiz1m","session_id":"87d5e701-3460-4b41-bfc5-b8f784767ea2","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"702b8b6b-07fb-4dec-b380-882c609f17d3","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01WoVjPAi45BQtMqS5k9Gg4G","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game that runs in a browser, built with TypeScript. Let me plan this out:\n\n1. I'll create a TypeScript-based Tetris game\n2. It should include:\n - All 7 standard Tetris pieces (I, O, T, S, Z, J, L)\n - Piece movement (left, right, down)\n - Piece rotation\n - Line clearing\n - Scoring system\n - Increasing speed\n - Keyboard controls\n\nLet me structure this as a single HTML file with embedded TypeScript (compiled to JS), or better yet, create proper files.\n\n\nI'll set up a project structure with an HTML file, TypeScript source, and a config file, then compile everything to JavaScript so it runs directly in the browser without needing a build step. Now I'm thinking through the core game architecture—I'll need a TetrisGame class to manage the canvas, game state, and piece logic.\n\nFor the board, I'm going with the standard 10×20 grid. I'll define all seven tetrominoes with their colors (cyan I-piece, yellow O, purple T, and so on), handle rotation mechanics, and implement a scoring system that rewards clearing multiple lines at once, with bonuses scaling by level.\n\nNow I'm setting up the game mechanics: speed increases with each level by reducing the frame count between drops, and I'm mapping out the controls—arrow keys for movement and rotation, space for instant drops, and P to pause.\n\nDefining the game constants and piece data structures... Defining the rotation states for the remaining Tetris pieces... Finishing up the tetromino rotation states for J and L pieces, then pivoting to think through the full game architecture—I need a canvas-based board, a sidebar showing score and next piece, and a complete TypeScript implementation to make this polished.\n\nFor the project structure, I'm deciding between pre-compiling TypeScript or using a bundler, but the simplest approach is to set up a proper build process with package.json and tsconfig.json so everything compiles cleanly and runs immediately in the browser.\n\nNow I'm thinking through the game architecture—I'll define the core constants like grid dimensions and block size, then set up a color palette for the different tetromino pieces.\n\nDefining game constants and colors... Writing the Tetris class... Defining the tetromino shapes... Writing the Tetris game implementation... Defining the tetromino shapes for each piece type with their initial rotation states, then setting up the drop speed configuration. Continuing with the game class...\n\nI'm setting up the game state properties like score, level, and lines cleared, along with game status flags for whether it's paused or over. I'm also initializing timing variables to handle the piece drop speed and lock delay mechanics, plus references to the UI elements that display the score and game information.\n\nNow I'm initializing the canvas elements for the main game board and the next piece preview, grabbing references to all the DOM elements I need to update, and setting up the canvas dimensions based on the grid size.\n\nSetting up constructor... Continuing the game initialization...\n\nNow I'm setting up the game state by resetting the score and level, initializing the piece queue and hold mechanic, then kicking off the game loop with a timestamp to track the drop timing.\n\nSpawning the first piece and checking if it's a valid placement—if the piece can't fit at the starting position, the game ends immediately. I'm also implementing the collision detection system that validates whether a piece can move to a given position by checking board boundaries and existing blocks.\n\nBuilding the ghost piece logic... Writing game loop logic... Implementing wall kick logic to handle piece rotation near boundaries...\n\nNow I'm finishing the soft drop scoring and moving into the lock mechanism, which places the current piece on the board by iterating through its shape and marking occupied cells, then checking for game over if the piece extends above the board.\n\nAfter locking the piece, I'm resetting the game state flags and attempting to spawn the next piece. Then I'm implementing the line-clearing logic that scans from the bottom up, removes complete rows, and shifts everything down while recalculating the score based on how many lines were cleared at once.\n\nNow I'm adding the hold piece functionality, which lets the player swap their current falling piece with a previously held one, repositioning both to their spawn locations. Writing game logic... Drawing the grid and board 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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":4729,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":4729,"ephemeral_1h_input_tokens":0},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"},"context_management":null},"parent_tool_use_id":null,"session_id":"87d5e701-3460-4b41-bfc5-b8f784767ea2","uuid":"fb1c9b14-d485-4e22-954e-073c0de41914"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01VBJHc2a2bnCZRwPNXfjwSo","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me build a complete Tetris implementation with:\n\n1. All 7 standard tetrominoes (I, O, T, S, Z, J, L)\n2. Piece movement (left, right, down)\n3. Piece rotation\n4. Line clearing\n5. Scoring system\n6. Increasing speed\n7. Keyboard controls\n\nI'll create:\n- `index.html` - the main HTML file\n- `src/tetris.ts` - the TypeScript game logic\n\n\n- `tsconfig.json` - TypeScript configuration\n- `package.json` - project dependencies\n\nI need to decide on the build approach. Since this needs to run in a browser, I'll go with a straightforward setup where TypeScript compiles to JavaScript. I could use a bundler, but a simple compilation approach will work fine for this project.\n\nNow I'm designing the full Tetris game structure, starting with the game board...\n\nThe board will be the standard 10×20 grid. I'm mapping out all seven tetrominoes with their colors, then defining the control scheme with arrow keys for movement and rotation, space for hard drop, and P or Escape to pause. For scoring, I'm using the classic Nintendo system where clearing multiple lines gives exponentially higher points multiplied by the current level, and the level increases every 10 lines cleared, which also speeds up the gameplay.\n\nNow I'm setting up the TypeScript implementation with the full game logic...\n\nWriting the game engine... Defining the tetromino shapes... Defining the remaining Tetris pieces... Defining the tetromino shapes and game structure...\n\nI'll represent each piece as a list of rotations, where each rotation contains the relative [row, col] coordinates of the filled cells, then build out the complete game logic with the board state, piece movement, and collision detection. I'm defining the standard Tetris pieces with their rotation states using coordinate notation. I'll represent each piece as a set of [row, col] positions within a bounding box, then convert them to a clean data structure for the game logic. Defining the rotation states for each Tetris piece using standard SRS coordinates within their bounding boxes — the I piece uses a 4x4 space while others fit in 3x3, and I'm specifying each rotation state as a set of cell positions. I've verified all the T piece rotations are correct, so now I'm ready to implement the complete game logic.\n\nWriting the game engine... Defining the tetromino pieces...\n\nI need to reconsider how spawn offsets work. When a piece appears, it starts at the top of the board centered horizontally, with its position representing the top-left corner of its bounding box. For something like the I piece with a 4-cell width on a 10-wide board, that means positioning it at column 3 to center it, and starting above the visible area so the actual cells appear at the top row. The absolute position of each cell is calculated by adding the cell's offset within the piece to the piece's current position.\n\nLooking at standard Tetris spawn positions, most pieces start at row -1 and column 3, except the O piece which starts at row 0 and column 4 since it's only 2 cells wide and needs to be centered differently.\n\nRather than overthinking the bounding box math, I'll just hardcode the spawn position for each piece type and represent each tetromino as a set of rotation states, where each state contains the four cell offsets relative to the piece's origin point.\n\nDefining the piece data... I'm realizing I'm overcomplicating the data structure. Let me step back and use a straightforward approach: the board is a 2D array with rows 0-19 and columns 0-9, pieces have a position at their top-left corner, and each piece's cells are defined as offsets from that position. I'll pre-define all rotation states for each tetromino and handle spawning by placing pieces at row 0, centered horizontally based on their bounding box.\n\nDefining piece rotations... Continuing with the remaining rotations for the J and L pieces, mapping out their coordinate positions for each orientation. Looking at the T piece rotations, they all check out correctly—each 90° rotation produces the expected orientation. Now I'm working through the spawn positions for the I piece, and I realize my current definition has the piece starting off-screen, which isn't right. I need to reconsider how the piece coordinates map to the actual board when it spawns.\n\nFor the I piece spawning at row 0, I should set pieceRow=0 and pieceCol=3 to center it horizontally on the 10-column board. The standard Tetris spawn positions are roughly centered, so I'll use row 0 for all pieces and calculate the column offset based on each piece's width—4 columns for the I piece gives column 3, while the 3-wide pieces (T, S, Z, J, L) also center around column 3, and the 2-wide O piece goes to column 4. Writing the Tetris implementation... Defining the tetromino rotation states...\n\nI'm noticing an issue with the S piece rotations—one of them seems to duplicate the T piece's pattern. Let me reconsider the S piece more carefully, starting with its actual shape and how it should rotate.\n\nFor the S piece in its base orientation, I have the cells mapped out correctly. Now I need to verify the 90-degree clockwise rotation is accurate by thinking through the transformation properly rather than just applying a formula that might be giving me wrong coordinates. I'm verifying the rotation logic by checking what each orientation should look like visually. The T-piece pointing up becomes a horizontal line when rotated clockwise, but I'm getting confused about which direction it's actually pointing after the transformation—the visual representation suggests it might be pointing left rather than right, so I need to reconsider the orientation naming. I need to work through the rotation math more carefully. For a 2×3 grid, I'll apply the standard CW rotation formula where new[i][j] = old[n-1-j][i], transposing and then flipping to get the correct orientation of the T piece after rotating 90 degrees clockwise. that's XXX in row 0 and X in row 1 at column 1 — so the T is now pointing up with the open side facing down. I'm visualizing the T-piece at 270° rotation—it forms an L shape pointing left with the stem on the right side. Now I'm comparing this against my earlier rotation calculations to verify the coordinate mappings are consistent across all four orientations. I'm mapping out the cell coordinates for that rotated T piece and visualizing it in the grid—the bump is indeed pointing right, which matches what I calculated. I need to think through the rotation more carefully. When I rotate the original T-piece clockwise—where the bump points up and the three cells form the base—the bump should end up pointing left, not right. Let me visualize this: rotating the paper 90° clockwise means what was at the top moves to the right side, so the upward bump becomes a leftward bump. Rather than trying to work out the rotation math, I'll just define all four rotations of the T piece directly by their coordinates, then verify which direction is clockwise versus counterclockwise based on how the piece actually moves on screen. Defining the rotation states for each piece based on visual appearance rather than worrying about orientation labels. The I piece has two unique rotations that alternate between horizontal and vertical, while the O piece only has one rotation since it's a square. Defining rotation states for remaining pieces... I've verified all four L-piece rotations and their cell coordinates match up correctly. Now I'm moving on to implement the full game using canvas for rendering.\n\nSetting up the project structure with an HTML file, TypeScript game code, and configuration, then writing out the game implementation with constants for the board dimensions, block size, and color mappings for each piece type.\n\nWriting game code... Defining the Tetris piece shapes... I'm realizing there's a mismatch in my T-piece rotations—I need to reconsider what clockwise rotation actually means in screen coordinates where y increases downward. Let me recalculate the transformation formula and verify that my rotation 1 state matches what I'd get by rotating rotation 0 clockwise. I'm verifying the rotation result by visualizing the grid—the vertical line of cells at column 0 forms the long side of the T, while the cell at [1,1] creates the bump pointing right, confirming this is the \"bump RIGHT\" orientation. I'm verifying the rotation formula by working through each coordinate transformation, and the results match up—so my earlier calculation was definitely off. I'm continuing to verify the T piece rotations by working through the coordinate transformations. The second rotation gives me the bump-down configuration, and now I'm checking the third rotation to confirm it produces the correct shape. Continuing the rotation transformation, I'm applying the same clockwise formula to the remaining coordinates and verifying that rotating again brings me back to the original rotation 0 state. The T piece's rotation cycle is now confirmed.\n\nNow I'm checking the S and Z piece rotations to ensure they follow the same pattern, starting with the S piece in its initial orientation and then rotating it to verify the shape is preserved.\n\nVerifying J and L piece rotations...\n\nNow I'm setting up the scoring system using standard Tetris rules: 100 points per line for a single line clear, with the multiplier increasing for multiple simultaneous clears.\n\nFor the drop speed, I'll use a time-based interval that starts at 800ms and decreases by 75ms per level, bottoming out at 50ms to keep the game playable at higher levels.\n\nThe controls map arrow keys for movement and rotation, space for instant drops, and Z for counter-clockwise rotation, plus pause functionality. I'm also adding visual features like a ghost piece preview, a queue showing the next three pieces, and a hold mechanic.\n\nFor rotation, I'll implement wall kicks with basic offset attempts rather than the full SRS specification—just trying shifts of 0, ±1 columns to handle edge cases smoothly.\n\nNow I'm building out the complete implementation with a dark-themed UI that has a clean side panel displaying the score, level, lines cleared, and upcoming pieces.\n\nWriting the HTML and TypeScript... Building the HTML structure...\n\nNow I'm deciding on the project setup—I'll create a TypeScript source file, configure it to compile to a dist folder, and set up the build tooling with a package.json so I can properly compile everything.\n\nI'm also working through the piece spawn positions to make sure they're centered correctly on the 10-wide board, accounting for the different bounding box sizes of each tetromino shape and whether the top row should be hidden above the visible play area. I'm going back and forth on the spawn position—starting pieces above the board at pieceRow = -1 is more authentic to standard Tetris, but it creates an immediate game over condition if row 0 is blocked. For this implementation, I'll keep it simple and spawn pieces fully visible at pieceRow = 0.\n\nNow I'm working out the spawn columns for each piece type based on their bounding boxes, making sure they're centered on the board. For the T piece specifically, with pieceRow = 0 and pieceCol = 3, the cells map correctly to create that centered appearance.\n\nThe I piece follows the same logic—starting at column 3 with rotation 0 places all four blocks across columns 3-6, which centers it nicely on the board.\n\nNow I'm ready to write the full TypeScript game implementation, using requestAnimationFrame for the game loop and incorporating soft lock delay and DAS for smoother controls.\n\nDefining the game class structure... Defining the game constants and piece types... Defining the piece shapes... Defining the spawn positions and rotation offsets...\n\nI need to implement the proper Standard Rotation System wall kicks for the JLSTZ pieces. The wall kick offsets vary depending on which rotation transition is happening—clockwise rotations have specific offset sequences, and I'll need to handle the counterclockwise transitions as well. I'm realizing these wall kick tables are getting unwieldy, so I'll simplify the approach—just try a basic sequence of horizontal offsets like no movement, then one space left or right, then two spaces in each direction. This should handle most rotation cases without needing the full SRS specification.\n\nWriting the rotation logic...\n\nNow I'm planning the full implementation with a single canvas approach—drawing the board in the center and the UI panels (hold and next pieces) on the sides. I'm settling on a 550×650 canvas with the main board taking up 300×600 pixels positioned at coordinates 125, 25, and the left panel starting at x=5.\n\nActually, I think it makes more sense to use HTML elements for the score, level, and lines display since they render text better, while keeping the canvas just for the game board and piece previews.\n\nSetting up the structure... Building the HTML structure...\n\nNow I'm thinking about the piece randomization system—I should implement a 7-bag system like standard Tetris, where each piece type appears exactly once per bag before reshuffling. I'm starting to write the Fisher-Yates shuffle algorithm to handle this fairly.\n\nThen I need a queue system that maintains the next pieces, refilling the bag whenever it drops below 7 items. Once I have the core logic planned, I'll write out the actual implementation files.\n\nFor the visual polish, I'm adding a ghost piece that shows where the current tetromino will land, and implementing lock delay so pieces stay briefly after landing—giving players a chance to adjust position or rotation before they lock in permanently.\n\nWriting the TypeScript code... Defining the wall kick data for SRS rotation... Defining kick data for I-pieces... I'm going to simplify the wall kick system for now with a basic set of offsets that should feel responsive without implementing the full SRS specification. Once that's working, I can always refine it with the proper Tetris wiki data for more authentic rotation behavior. I'm realizing the rotation kick offsets are getting tangled up with my coordinate system conventions. Let me simplify this by implementing a straightforward set of wall kick attempts that prioritize horizontal movement first, then vertical adjustments, which should handle most rotation scenarios in practice without needing to perfectly match the official Tetris guideline.\n\nDefining wall kick offsets... I'm going to implement the standard SRS wall kick system properly by looking up the exact rotation offsets from the Tetris Guideline specification. I'm mapping out the wall kick offsets for each rotation transition in screen coordinates, where positive row values move downward. The pattern shows how the piece attempts to shift position when rotating, trying different offset combinations to find valid placements. the offsets are [col_offset, row_offset] and I want [row_offset, col_offset] for my code.\n\nSo converting to [row, col]:\n0→R (CW, 0→1): [0,0], [0,-1], [-1,-1], [+2,0], [+2,-1]\nR→0 (CCW): [0,0], [0,+1], [+1,+1], [-2,0], [-2,+1]\nR→2 (CW, 1→2): [0,0], [0,+1], [+1,+1], [-2,0], [-2,+1]\n2→R (CCW): [0,0], [0,-1], [-1,-1], [+2,0], [+2,-1]\n2→L (CW, 2→3): [0,0], [0,+1], [-1,+1], [+2,0], [+2,+1]\nL→2 (CCW): [0,0], [0,-1], [+1,-1], [-2,0], [-2,-1]\nL→0 (CW, 3→0): [0,0], [0,-1], [+1,-1], [-2,0], [-2,-1]\n0→L (CCW): [0,0], [0,+1], [-1,+1], [+2,0], [+2,+1]\n\nI'm noticing that some of these rotation transitions share the same offset patterns—R→2 and R→0 both have identical values, which seems off. Let me verify this against the wiki definitions where R is rotation state 1, L is state 3, 0 is spawn, and 2 is 180°.\n\nActually, I'm overcomplicating this. The full SRS wall kick system is intricate, and I'm spending too much time parsing the exact specifications. I'm going to implement a simpler wall kick system that covers the most common cases—checking offsets horizontally and vertically when a rotation fails. This should handle the practical scenarios well enough for the game.\n\nNow I need to actually start writing the code instead of continuing to plan.\n\nSetting up the Tetris game implementation... Defining the rotation states for the remaining Tetris pieces... Defining the game structure... I'm setting up the canvas elements for the hold piece and next queue displays, then initializing the game by queuing pieces and starting the render loop. Writing game logic... Writing the game logic... Writing game mechanics... Writing game mechanics... Writing game logic... Setting up the movement controls...\n\nFor the arrow keys, I'm initializing the delayed auto-shift timers so the piece can smoothly slide across the board when held down. The rotation keys map to clockwise and counterclockwise turns, space triggers the hard drop, and the hold piece function lets players swap their current piece with a stored one.\n\nNow I'm handling the key release events to clear the movement state and reset those DAS timers. Then I'm adding a pause toggle that switches between playing and paused states with corresponding UI updates. The game initialization resets the board, score, level, and line count to start fresh.\n\nSetting up the game loop with requestAnimationFrame to handle the delta time calculations and only update when actively playing.\n\nNow I'm implementing the input handling for piece movement, using a delayed auto-shift system for left and right arrow keys to make the controls feel responsive, and setting up soft drop acceleration when the down arrow is held.\n\nImplementing drop mechanics and lock delay... I'm implementing the hold piece logic where swapping pieces resets their rotation state and position, then disables holding until the next piece locks, while also clearing any lock delay progress to prevent immediate locking. Now moving on to the rendering code...\n\nWriting the draw methods... Still writing the render method... Still writing rendering functions... Writing canvas rendering logic... Finishing the block rendering with darker shades for depth, then updating the UI to display the current score, level, and lines cleared with proper formatting.\n\nNow I'm setting up the game over and pause screens by toggling an overlay element and updating its text content to show the appropriate message.\n\nI'm also implementing helper methods to hide the overlay when needed, and starting to build out the initial start screen which fills the canvas with a dark background and displays instructions through the same overlay system.\n\nNow I'm realizing there's a bug in my hold piece logic—when I swap pieces, I need to validate that the swapped piece can actually spawn at the current position, not just assume it will work. Let me refactor the hold method to handle this properly. Resetting the drop accumulator and lock state. Now I'm implementing the DAS (Delayed Auto Shift) system properly—when the left arrow is first pressed, it moves immediately, then waits 167ms before repeating every 33ms. I'm tracking this with a das accumulator that starts negative to enforce the initial delay, then triggers repeated moves once it reaches zero. I'm realizing the logic is sound—after the initial delay, repeats trigger every DAS_REPEAT milliseconds. Though I should double-check the edge case where the update loop might not run immediately after keydown, or runs multiple times in quick succession, to ensure the first move always fires and the timing stays consistent. Now I'm ready to implement the complete game with proper scoring mechanics—soft drops worth 1 point per row, hard drops worth 2, and line clears scaled by level—plus localStorage for tracking high scores. I'm also thinking through the visual design with a dark color scheme to make the game feel polished.\n\nI'll keep the special effects minimal and focus on solid core gameplay, using a clean dark background with vibrant block colors and 3D shading. For the preview areas, I'm using 4x4 grids at 24px blocks, and I've mapped out the drop speeds across difficulty levels starting at 800ms and decreasing as the level increases.\n\nWriting the complete implementation...\n\nNow I'm thinking through the lock delay mechanics—when a piece lands, it should have a 500ms window before locking, but that timer resets if the player moves or rotates it while it's still grounded, up to a maximum of 15 resets to prevent infinite stalling. I need to make sure that if the piece gets lifted off the ground, the lock delay cancels entirely.\n\nRefining the approach: each frame I'll check if the piece is on the ground, and if so, increment the lock delay timer; if it's not on the ground, I reset the timer and clear the grounded state. When the player moves or rotates, I check whether the piece is still touching the ground afterward—if it is, I reset the delay counter (assuming resets remain), but if it's now floating, I clear the grounded flag.\n\nImplementing the logic... Finishing the UI update call, then reconsidering the lock reset logic—I think the standard approach of resetting the counter when a new piece spawns rather than when it temporarily leaves the ground makes more sense, and I'll cap it at 15 resets per placement with a 500ms lock delay.\n\nImplementing the ground detection and lock timing...\n\nNow I need to actually start writing the code. Let me think through the layout first—I want a clean Tetris interface with the game board in the center, hold piece on the left, next pieces on the right, and score display below. I'll keep everything in HTML and TypeScript to minimize file complexity.\n\nBuilding the game structure... Defining the piece shapes and colors... Defining the rotation states for the remaining Tetris pieces... Setting up game constants and the core Tetris game class with piece management, scoring rules, and game state tracking... I'm setting up the canvas contexts for the main board, hold piece display, and next queue previews, then initializing the game board and retrieving the high score from local storage before wiring up the keyboard event listeners.\n\nNow I'm finishing the event setup and triggering the initial render with the start overlay, then kicking off the game loop with requestAnimationFrame. I'm also defining the board creation method that generates a 2D grid filled with nulls, and implementing the piece queue system using a 7-bag randomization algorithm to ensure balanced piece distribution.\n\nContinuing with the piece spawning logic...\n\nNow I'm checking if a piece is valid by iterating through its cells and ensuring they're within bounds and not colliding with existing blocks on the board. I also have a method to detect when a piece hits the ground by testing if moving it down one row would be invalid. For input handling, I'm tracking which keys are currently pressed and ignoring system keys like F5 and F12 to avoid interfering with browser functions.\n\nWriting input handlers... I'm implementing the movement mechanics for the tetromino pieces—checking if left and right shifts are valid before updating the position, and handling the drop logic that moves pieces downward while validating each step.\n\nNow I'm adding the soft drop and hard drop functions, where soft drop gives bonus points for manually accelerating the piece, and hard drop instantly places it at the bottom while multiplying the score. I'm also setting up the rotation methods that will handle clockwise and counterclockwise turns...\n\nImplementing rotation with wall kick offsets...\n\nNow I'm handling the hold piece mechanic, which swaps the current piece with a previously held one or spawns a new piece if nothing was held before, then prevents immediate re-holding.\n\nContinuing with game logic... Continuing with the line clearing logic...\n\nNow I'm removing the cleared rows from the board and adding fresh empty rows at the top, then updating the score based on how many lines were cleared and the current level. I'm also calculating the new level based on total lines cleared, displaying an appropriate flash message for single, double, triple, or Tetris clears, and refreshing the UI to reflect all these changes.\n\nFor the ghost piece, I'm calculating where the current piece would land if dropped straight down by simulating the fall until it hits an obstacle. Then I'm setting up the game initialization by resetting the board, score, level, and all the piece management variables like the hold queue and drop timers.\n\nNow I'm finishing the startup sequence by clearing the UI overlay and spawning the first piece, then handling what happens when the game ends—checking if we've beaten the high score and saving it to local storage before showing the game over screen. The pause toggle is being implemented next...\n\nStill writing game logic... Still writing game logic... Writing the rendering logic... Writing the rendering logic... Writing the mini piece renderer... Writing the flash message display...\n\nNow I'm handling the UI updates—refreshing the score, level, lines cleared, and high score displays, then managing the overlay for game over and pause states.\n\nI need to initialize the game when the DOM loads, but I'm realizing there's a bug in how I'm handling the soft drop mechanic. The issue is that `ArrowDown` presses trigger both `onKeyDown` repeatedly and the update loop, causing double drops. I should consolidate this by only handling continuous soft drop in the update loop when the key is held, rather than in the key press handler. Still writing gravity logic... the browser's key repeat won't interfere since I'm checking `wasHeld` to prevent duplicate drops. For the immediate response on first press, I'll call `softDrop()` in `onKeyDown`, then let the gravity multiplier handle the continuous drop when the key is held. This way I get instant feedback without waiting for the gravity timer. I realize I should check the `repeat` property on the keyboard event instead—that's the cleaner way to distinguish between the initial keypress and browser-generated repeats. I'll use that to let the first ArrowDown press trigger softDrop immediately, while the update loop handles the continuous acceleration via gravity multiplier.\n\nI still need the `keys` set to track which keys are currently held for DAS timing and the soft drop multiplier during the update cycle. Now I'm refining the keydown handler to manage game state transitions like pausing and starting, while keeping the repeat logic separate.\n\nRefining the input handler... Finishing up the key handler with space for hard drop and shift/C for the hold mechanic. Now I'm thinking through how soft drop should work—I want to avoid conflicts between the initial key press triggering a drop and the gravity system handling sustained pressure, so I'll consolidate soft drop logic into the update loop where I can properly manage the timing. the immediate press for better feel. I'll handle the ArrowDown key in `onKeyDown` for the instant response on first press, then use the update loop to apply a 20x gravity multiplier when the key is held down—this way the accumulator gets boosted by the additional gravity while normal gravity still applies.\n\nNow I'm implementing the scoring logic for hard and soft drops. Hard drop awards 2 points per row, which I'll calculate by counting successful drops in a loop. For soft drop, I need to track rows dropped during the gravity update when ArrowDown is held, incrementing the score by 1 point per row.\n\nI'm also deciding on canvas dimensions for the preview areas—I want them compact but readable, so I'm settling on 96×96 pixel canvases for the hold and next piece displays, using 24-pixel blocks. The preview areas look good with those dimensions. Now I'm setting up the project structure with TypeScript and npm, then building out the HTML layout with sections for the hold piece, main game board, next queue, and score display.\n\nWriting HTML and styles... Still writing styles... Still writing styles... Building the game interface... Setting up the type definitions and constants for the game...\n\nNow I'm mapping out the color palette for each piece type and defining the rotation shapes for all seven Tetris pieces. Defining the rotation states for the remaining tetromino pieces...\n\nNow I'm setting up the spawn positions and game constants—the drop speeds increase through levels, line clears award points based on how many lines you complete at once, and there are mechanics for lock delay and input handling.\n\nSetting up the game class... Setting up the canvas contexts for the next pieces display, loading the high score from local storage, and wiring up keyboard event listeners before starting the game loop with the initial draw call.\n\nNow I'm defining utility methods for the board and pieces — creating the grid structure, calculating cell positions for rotated pieces, validating moves by checking boundaries and collisions, and detecting when a piece has landed.\n\nNow I'm implementing the piece queue system with a bag randomization approach, refilling it with shuffled piece types when it runs low and providing methods to peek ahead or draw the next piece.\n\nStill writing game logic... Writing the game logic... Writing the hold and lock logic... Still writing game logic... Writing game state logic... Implementing the DAS (Delayed Auto Shift) system for left and right movement, where holding a direction key triggers repeated moves after an initial delay, while also checking if the piece is currently on the ground.\n\nNow I'm handling the ground state — if the piece is resting, I increment a lock timer that triggers piece placement after a delay, but if it's falling, I reset the timer and apply gravity based on the current level, with soft drop acceleration if the down arrow is pressed. Writing the rendering logic... Writing the render logic... Still writing the drawing logic... Writing the preview rendering... Writing UI helper methods...\n\nNow I'm setting up the input handler to capture keyboard events, preventing default behavior for game-specific keys, and managing game state transitions like starting a new game or toggling pause.\n\nHandling active gameplay input...\n\nI'm setting up the key release handler to clear pressed keys and reset the delayed auto-shift timers for left and right movement, then wrapping up with utility functions and the game initialization on page load. But I'm noticing an issue with how `dasLeft` is being managed—it looks like it's being set to the same negative delay value both on key down and key up, which might not be the intended behavior for the delayed auto-shift system. When `ArrowLeft` is pressed, the first move fires immediately and `dasLeft` resets to `-DAS_DELAY_MS` to enforce the delay before repeating. The real problem is in my update logic—I'm clamping `dasLeft` to 0 when the key isn't held, which means it never goes negative enough to properly reset for the next press. I'm realizing the issue: when the player taps left multiple times quickly without holding, the `dasLeft` timer could accumulate and cause unexpected extra moves. The cleanest solution is to reset `dasLeft` to a large negative value in the key-up handler so it doesn't trigger immediately, then set it to `-DAS_DELAY_MS` fresh on each key-down press.\n\nSetting up the input handlers... I'm realizing the soft drop multiplier in the update loop might not feel responsive enough for a quick tap—it could take a few frames before anything happens. I should handle ArrowDown directly in keydown to trigger an immediate drop, then let the update loop handle the repeated drops if the key stays held.\n\nActually, I'm overcomplicating this. Let me just implement the straightforward approach: trigger a drop on the first keydown press and let the continuous logic handle the rest.\n\nI'm also noticing a couple of cleanup issues—the lockResets reset in clearLines() is redundant since I'm already resetting it in spawn(), and I need to double-check what happens when hard drop calls lockPiece() during the update cycle.\n\nNow I'm thinking through the color handling. My COLORS map uses standard hex codes, so I need to make sure my color shifting function correctly parses and adjusts the RGB values while keeping them clamped to valid ranges.\n\nHandling color shifts...\n\nNow I'm verifying the S and Z piece rotations to ensure they spawn correctly on the board. Let me trace through the S piece in its initial rotation—it should occupy two rows and three columns, with the pattern showing the characteristic S shape across the grid.\n\nFor the Z piece, I'm confirming it has the same rotation behavior as S, with only two unique states that cycle back on themselves, so rotations 2 and 3 just repeat rotations 0 and 1.\n\nNow I'm ready to write the complete TypeScript implementation, making sure to handle piece shapes correctly, manage the game loop properly from spawning through locking and clearing lines, implement accurate scoring, render everything visually, and respond to input smoothly. Before diving in, I want to think through the ghost piece mechanic—it should display where the current piece would land if dropped straight down, matching the current piece's type and rotation but positioned at the lowest valid row.\n\nWriting the ghost piece logic... I need to compile the TypeScript with `npm run build` to generate the final JavaScript. But first, let me double-check the T-piece rotation logic—I'm visualizing the second rotation state and want to make sure the coordinates map correctly to the intended shape before I write out all the files. The T rotations all check out correctly with the bump pointing in the right directions. Now I'm verifying the L piece rotations across all four orientations, and they're all matching up as expected.\n\nMoving on to the J piece, I'm confirming each of its four rotational states—the cells line up correctly for all 90-degree rotations. Everything looks solid with the piece definitions, so I'm ready to start implementing the actual code now. Let me think through the structure one more time before diving in.\n\nWriting the game logic... I'm realizing the issue with rapid taps: if I call `drop()` directly on keydown, combined with the 20x multiplier in the update loop, the piece might drop too aggressively. Instead, I should let the update loop handle all drops—when ArrowDown is first pressed, `dropAccum` jumps by `dt * 20` in that frame, causing an immediate drop, and then subsequent frames continue accelerating until the key is released. Implementing the drop handler... Writing the Tetris implementation... Defining piece shapes... Defining the rotation states for the remaining tetromino pieces...\n\nNow I'm setting up the spawn positions for each piece type and the drop speed progression across difficulty levels. Defining the type system and helper functions...","signature":"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+ "duplication_percentage": 0.0, + "score": 1.0 + }, + "transcript_analysis": { + "total_events": 8, + "tool_calls": { + "total": 1, + "bash": 1, + "write": 0, + "edit": 0, + "read": 0 + }, + "wasted_turns": { + "total": 0, + "docs": 0, + "ascii_art": 0, + "server_starts": 0 + }, + "errors_encountered": 0, + "thinking_blocks": 2, + "text_blocks": 1, + "productivity_ratio": 1.0, + "self_tested": false, + "score": 1.0 + }, + "gameplay_bot": { + "pass": false, + "score": 0.19, + "total": 16, + "passed": 3, + "failed": 13, + "report": { + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 20 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } + } + }, + "score": 0.602 +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/gameplay-bot-report.json b/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/gameplay-bot-report.json @@ -0,0 +1,119 @@ +{ + "implementation": { + "renderer": "unknown", + "grid_detected": false, + "grid_bounds": null, + "controls": { + "left": "ArrowLeft", + "right": "ArrowRight", + "down": "ArrowDown", + "rotate": "ArrowUp", + "drop": "Space" + }, + "start_mechanism": "unknown", + "score_element_found": false + }, + "tests": [ + { + "name": "game_loads", + "pass": true, + "detail": "no console errors" + }, + { + "name": "game_starts", + "pass": false, + "detail": "could not start game with any mechanism" + }, + { + "name": "auto_drop", + "pass": false, + "detail": "piece did not move in 5 seconds" + }, + { + "name": "move_left", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_right", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "move_down", + "pass": false, + "detail": "no change detected after key press" + }, + { + "name": "rotate", + "pass": false, + "detail": "no change detected after rotate key" + }, + { + "name": "all_pieces_rotate", + "pass": false, + "detail": "could not detect any piece rotations" + }, + { + "name": "hard_drop", + "pass": false, + "detail": "no change detected after hard drop key" + }, + { + "name": "piece_locks", + "pass": false, + "detail": "could not verify piece locking at bottom" + }, + { + "name": "new_piece_spawns", + "pass": false, + "detail": "could not detect new piece at top" + }, + { + "name": "multiple_pieces", + "pass": false, + "detail": "grid did not accumulate filled cells" + }, + { + "name": "line_clear", + "pass": false, + "detail": "could not trigger or detect a line clear" + }, + { + "name": "score_changes", + "pass": false, + "detail": "no score element found and no number changed" + }, + { + "name": "game_over", + "pass": true, + "detail": "game stopped after stacking to top" + }, + { + "name": "playable_30s", + "pass": true, + "detail": "played for 30s, placed 11 pieces, no crashes" + } + ], + "summary": { + "total": 16, + "passed": 3, + "failed": 13, + "score": 0.19 + }, + "gameplay": { + "pieces_placed": 102, + "lines_cleared": 0, + "max_score_observed": 0, + "play_duration_seconds": 30, + "errors_during_play": 0 + }, + "performance": { + "load_time_ms": 20 + }, + "accessibility": { + "issues": [], + "issue_count": 0, + "pass": true + } +} +\ No newline at end of file diff --git a/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json b/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/meta.json @@ -0,0 +1,30 @@ +{ + "model": "sonnet", + "effort": "max", + "prompt_style": "simple", + "language": "typescript", + "human_language": "en", + "tool_read": "on", + "tool_write": "on", + "tool_edit": "on", + "tool_glob": "on", + "tool_grep": "on", + "linter": "on", + "playwright": "on", + "context_file": "none", + "sub_agents": "on", + "web_search": "on", + "max_budget": "low", + "task": "tetris", + "cell_id": 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a/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl b/results/runs/tetris_context_file=none_effort=max_human_language=en_language=typescript_linter=on_max_budget=low_model=sonnet_playwright=on_prompt_style=simple_sub_agents=on_tool_edit=on_tool_glob=on_tool_grep=on_tool_read=on_tool_write=on_web_search=on_run2/transcript.jsonl @@ -0,0 +1,8 @@ +{"type": "harness", "subtype": "config", "model": "sonnet", "effort": "max", "tools": ["Bash", "Read", "Write", "Edit", "Glob", "Grep", "Agent", "WebSearch", "WebFetch"], "max_budget_usd": 0.5, "timeout_seconds": 1200, "task": "tetris", "language": "typescript", "prompt_style": "simple"} +{"type": "user", "subtype": "prompt", "message": {"role": "user", "content": "Build a playable Tetris game that runs in a browser. It should have all the standard mechanics: piece rotation, line clearing, scoring, and increasing speed. Use keyboard controls for movement and rotation.\n\n\nUse TypeScript."}} +{"type":"system","subtype":"init","cwd":"/tmp/loop-bench-c4n513d1","session_id":"e9ebd7e9-6fac-4e46-8689-fdcdeb0e8c7d","tools":["Bash","Edit","Read"],"mcp_servers":[],"model":"claude-sonnet-4-6","permissionMode":"dontAsk","slash_commands":["update-config","debug","simplify","batch","loop","schedule","claude-api","compact","context","cost","heapdump","init","review","security-review","insights"],"apiKeySource":"apiKeyHelper","claude_code_version":"2.1.92","output_style":"default","agents":["general-purpose","statusline-setup","Explore","Plan"],"skills":["update-config","debug","simplify","batch","loop","schedule","claude-api"],"plugins":[{"name":"claude-hud","path":"/root/.claude/plugins/marketplaces/claude-hud/","source":"claude-hud@claude-hud"},{"name":"rust-analyzer-lsp","path":"/root/.claude/plugins/marketplaces/claude-plugins-official/plugins/rust-analyzer-lsp","source":"rust-analyzer-lsp@claude-plugins-official"}],"uuid":"1e132289-35a1-4ef2-af08-e14f389660c6","fast_mode_state":"off"} +{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01LBS9k3MjxqGKbVV8v9e3Nd","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants a playable Tetris game in the browser using TypeScript. Let me build a complete Tetris game with:\n\n1. All standard Tetris pieces (I, O, T, S, Z, J, L)\n2. Piece rotation\n3. Line clearing\n4. Scoring system\n5. Increasing speed\n6. Keyboard controls (arrow keys for movement, up arrow or Z for rotation)\n\nI'll create a self-contained HTML file with TypeScript compiled inline, or better yet, create separate files. Let me think about the structure:\n\n- `index.html` - Main HTML file\n\n\n- `game.ts` - TypeScript source\n- `style.css` - Styles (or inline in HTML)\n\nFor a browser game, I could either set up a build process with TypeScript compiler or use a single HTML file with TypeScript transpiled inline. Let me go with a proper project setup using TypeScript and compile it to JavaScript.\n\nSetting up the project structure...\n\nI'll need to define the core game mechanics: a 10×20 board with the standard seven Tetris pieces, collision detection, line clearing with scoring, and a ghost piece preview. The game will speed up every 10 lines cleared. For controls, I'm mapping arrow keys for movement and rotation, space for hard drop, C for hold, and P/Escape for pause.\n\nDefining the game types and structure... Defining the tetromino shapes and rotation states... Defining the tetromino rotation states... Defining piece rotations...\n\nNow I'm thinking about whether to implement the full Super Rotation System with its wall kick offset tables, or keep it simpler. The SRS is the standard for modern Tetris, but for a basic version I could just try shifting pieces left or right when they hit a wall during rotation.\n\nI'm going to build out the complete game with a proper structure: an HTML file for the canvas and UI, a TypeScript file for all the game logic, and the necessary config files. I want to make it polished with dark styling, colored pieces, a ghost piece preview, score tracking, level progression, line counters, a next piece preview, hold functionality, game over detection, and pause controls.\n\nDefining the game constants and piece color mappings... Defining the rotation states for the remaining Tetris pieces... Defining the wall kick data for standard Tetris pieces, which specifies the offset positions to try when rotating near walls or obstacles. Defining wall kick data for I-pieces... standard SRS uses x/y coordinates but the convention can be confusing. Let me use a well-known implementation.\n\nIn SRS:\n- x = column (positive = right)\n- y = row (positive = down)\n\nThe kick data from the Tetris wiki shows the offset adjustments for each rotation transition. Since the wiki uses screen coordinates with y positive downward (opposite of typical math convention), I need to negate those y values for my implementation. Actually, I think a simpler wall kick approach would work better—try rotating at the current position first, then test adjacent positions if that fails.\n\nBut proper SRS is worth implementing since it makes the game feel much more polished. Let me set up the coordinate system clearly: `board[row][col]` with row 0 at the top, and `piece.x` and `piece.y` as column and row offsets respectively. Then I'll implement the full SRS kick data for each piece type and rotation transition.\n\nDefining the wall kick offsets... I'm seeing the complete wall kick offset data for all rotation transitions—the pattern shows that opposite rotations have mirrored offsets, which makes sense for the symmetry of the piece rotations. I'm working through the coordinate system conversion more carefully now. The wiki uses column and row offsets where positive row points up, but my screen coordinates have positive row pointing down, so I need to negate those row values when converting. Let me map out each rotation state transition with the corrected offsets. I'm realizing the wall kick offset tables are getting messy, so let me simplify this approach instead of trying to perfectly match SRS specifications. I'll use a basic set of offsets that handles the common cases—no kick, single-tile shifts left and right, double-tile shifts, and vertical adjustments—which should work well enough for the game even if it's not tournament-standard. For a more polished implementation down the line, I can always circle back to proper SRS, but for now I want to focus on getting the core mechanic working.\n\nNow I'm carefully mapping out the coordinate system conversion: my columns increase rightward and rows increase downward, while the Tetris wiki uses x rightward but y upward, so I need to negate the y values when translating their offset data. I'm working through the JLSTZ piece rotations and their corresponding wall kick offsets, converting each one from wiki format to my system. I'm looking at the official Super Rotation System documentation from the Tetris Wiki to verify the exact rotation offsets for J, L, S, T, and Z pieces across all rotation states.\n\nSince my coordinate system has y increasing downward while the wiki uses y increasing upward, I need to flip the sign on all the y-values when I convert them over. Working through the 0->R rotation state as an example, I'm converting each test offset by negating the y-component to match my grid orientation. I'm comparing my rotation kick offsets against the wiki reference and finding discrepancies—my 2->L and 3->2 transitions have the wrong signs, and I need to verify the remaining cases to get the pattern right. I'm verifying each rotation transformation by comparing my coordinate system against the wiki reference, accounting for the y-axis flip between them. The pattern holds consistently across all four rotations—when I negate the y-coordinates from the wiki data, they match my system's offsets perfectly. I'm comparing my L-tetromino rotation offsets against the wiki reference, and I'm noticing a consistent pattern where my coordinates differ—specifically, I'm getting inverted y-values in several rotations. Let me trace through the remaining rotation states to identify where the discrepancy lies.","signature":"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+{"type":"assistant","message":{"model":"claude-sonnet-4-6","id":"msg_01LWoWqYKUCFuyQTjiD7ng4U","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to build a playable Tetris game that runs in a browser using TypeScript. Let me plan the structure:\n\n1. `index.html` - The main HTML file with the game canvas\n2. `src/tetris.ts` - The TypeScript game logic\n3. `package.json` - Package configuration\n4. `tsconfig.json` - TypeScript configuration\n\nLet me design the game with all standard Tetris mechanics:\n- 7 Tetromino pieces (I, O, T, S, Z, J, L)\n- Piece rotation\n- Line clearing\n- Scoring (based on lines cleared)\n\n\n- Increasing speed as the level goes up\n- Keyboard controls (arrow keys + WASD for movement and rotation)\n- Next piece preview\n- Score and level display\n\nI'll use a canvas-based rendering with a 10x20 grid, supporting standard Tetris controls: arrow keys or WASD for movement, up arrow or W for rotation, down arrow or S for soft drop, space for hard drop, and P to pause. The scoring system will award points based on how many lines are cleared at once, with multipliers based on the current level.\n\nWriting the implementation... Defining the Tetris game types and piece shapes... Defining the tetromino shapes and their rotation states... Defining the rotation states for the remaining Tetris pieces...\n\nActually, I should reconsider the rotation system more carefully. The standard approach is to use SRS (Super Rotation System) with pre-computed rotations for each piece. Let me structure this as a complete TypeScript implementation with constants for piece definitions, game state management, collision detection, and line clearing logic all organized together.\n\nI'm planning to build this across multiple files: an HTML entry point, the main TypeScript source file, and configuration files for TypeScript and npm. The game will compile down to a single JavaScript file in the dist folder. I want to keep the implementation focused on core mechanics—the board, piece movement, rotation, and line clearing—without getting sidetracked by fancy visual effects. Now I'm ready to start writing out all the files.\n\nWriting the implementation... Building the game class... Writing the Tetris game implementation... Defining tetromino rotation patterns... Defining the rotation states for the remaining Tetris pieces... Setting up the game state... Writing the game logic... Writing the piece placement logic... Updating the score based on lines cleared, applying the level multiplier, and checking if the player has advanced to a new level by tracking total lines—if so, I'll adjust the drop speed accordingly. Then I'm refreshing the UI elements to display the current score, level, and line count.\n\nNow I'm calculating the ghost piece position by dropping it down until it hits a collision, and then I'm setting up a function to draw individual blocks on the canvas with customizable color, size, and transparency.\n\nDrawing the block with 3D effect... Writing the rendering logic... Writing the pause overlay and next piece preview... Writing the game UI... Writing game loop logic... Writing game mechanics... Implementing the hard drop and input handling... Setting up key repeat logic... Finishing the pause logic and game initialization...\n\nI'm realizing the game loop needs to keep rendering even when paused so the pause overlay displays correctly, and I need to reconsider how the piece placement works when `placePiece` is called—it should properly cycle the current and next pieces. Let me reconsider the input handling—I should implement a proper DAS (Delayed Auto Shift) system for smoother movement rather than simple key repeat. For the ghost piece, I need to calculate where the current piece will land by simulating downward movement until it hits an obstacle, then return that final position. I'm refining the ghost piece logic to use a cleaner approach with a `dy` offset that increments until it hits an invalid position, then returning the final y-coordinate. Now I'm thinking through the scoring system—standard Tetris awards points based on lines cleared (100 for single, 300 for double, 500 for triple, 800 for Tetris) multiplied by level, plus bonus points for hard and soft drops.\n\nNow I'm planning the HTML and CSS layout with a dark theme, centering the game canvas with a right panel for stats, and sizing the canvases appropriately—300×600 for the main board and around 120×90 for the next piece preview. I'm considering whether to write this as separate files or combine everything into a single HTML file with inline JavaScript.\n\nI'll go with the proper TypeScript project structure: separate HTML, TypeScript source, and config files. Before I start writing, I need to check the current directory and also clarify how the `isValidPosition` function should work—it needs to handle the piece's current position plus the offset deltas to determine if a move is valid.\n\nThe coordinate system has y=0 at the top with increasing y moving downward, which is standard. For piece spawning, I need to be careful about where blocks actually appear on the board relative to their rotation matrix, especially for the I piece which has a different shape than the other tetrominoes. Writing the spawn logic...\n\nFor the T piece, centering gives x=4 with blocks appearing at rows 0 and 1, but the I piece is trickier—it starts at y=0 but the actual blocks don't appear until row 1, which means part of the piece spawns invisibly. I need to reconsider how to handle the game-over detection when pieces can start partially off-screen. I'm realizing the I piece spawning one row lower is actually fine and matches how many Tetris games work. For game over detection, I need to check when a new piece spawns and immediately collides with existing blocks, which my `placePiece` method handles by validating the piece's position right after spawning it.\n\nChecking collision logic...\n\nI'm verifying that `boardY < 0` would only occur if a piece's y-coordinate goes negative, which shouldn't happen since pieces spawn at y=0 and the shape matrices keep blocks at non-negative positions relative to the spawn point. Let me trace through the piece definitions to confirm blocks stay within bounds. I'm verifying that all standard Tetris pieces spawn with blocks in the upper rows, so the `boardY < 0` check isn't needed. The real concern is when the board fills up to row 0—if a piece can't move down on its first attempt, it places immediately, and if that row is already occupied, the game ends. The placement logic seems solid, so I'm confident the collision detection will handle game-over scenarios correctly.\n\nNow I need to implement the actual code, but first I should make sure `isValidPosition` handles rotation parameters correctly...\n\nDefining the validation method... I'm sizing the next piece preview canvas—since all tetrominoes fit within a 4×4 grid, I'll make it 6×5 blocks at 25 pixels each for some breathing room, giving me 150×125 pixels total.\n\nActually, let me just go with 150×120 to keep things simple. Now I need to be careful with the ghost piece rendering—it should only appear when it's at a different vertical position than the current piece, otherwise I'm just drawing the same thing twice. I'll add a check to skip the ghost if it's at the same y coordinate.\n\nWriting the complete implementation...\n\nFor the O piece specifically, I need to verify the centering math works out correctly—with my current shape definition, the blocks should land in the center columns when spawned. Defining simpler shape matrices where possible, though the I piece is tricky—a 1×4 matrix for one rotation would require a 4×1 for the perpendicular rotation, which gets messy with jagged arrays, so I'll stick with the consistent 4×4 approach. One thing to note: with the 4×4 matrix, the I piece's blocks actually sit at row 1 when spawned at y=0, meaning it visually starts one row down rather than at the very top—that's fine for this implementation. I'm realizing the I piece spawn position follows the Tetris Guideline standard where pieces start above the visible field, so having the I piece's top row invisible at y=0 is actually correct. I'll stick with this approach and move forward with writing the final code. above the visible area (for some orientations/pieces), and as long as the visible part doesn't collide, it's fine.\n\nNow I'm finalizing the implementation. For scoring, I'll handle soft drop and hard drop separately—soft drop gives 1 point per row, hard drop gives 2 points per row, without level multipliers to keep it simple. For the game loop, I need to use `requestAnimationFrame` and track the last drop time to manage the falling speed properly.\n\nSetting up the game loop timing... Refining the game loop to handle the paused state more efficiently—when paused, we still request the next animation frame but skip all the game logic and rendering, which keeps the loop running without unnecessary computation.\n\nFor the pause toggle, I need to ensure we draw the pause overlay immediately when pausing, and reset the drop timer when resuming so the piece doesn't suddenly accelerate.\n\nNow I'm ready to start implementing the actual TypeScript files with clean, precise code. For the O piece, I'll use a simple 2x2 square shape and position it at spawn x = 5 - 1.\n\nSetting up the project structure with index.html, the main tetris.ts file, tsconfig.json, and package.json, then I'll define the core constants and tetromino types.\n\nWriting TypeScript implementation... Defining the tetromino rotation states... Defining the rotation states for the remaining Tetris pieces... Setting up the game class with canvas rendering for both the main board and next piece preview, along with tracking game state like score, level, and lines cleared, plus timing variables for piece drops and input handling. Setting up the board initialization and piece creation logic...\n\nNow I'm checking if a piece can move to a new position by validating that all its blocks stay within bounds and don't collide with existing pieces on the board. Then I'm placing the current piece onto the board by marking those cells as occupied. Writing game logic... Writing the rendering logic... Writing the render method... Writing the rendering logic... Writing the next piece preview... Writing the game over screen... Initializing the game state by resetting the board, score, and level, then setting up the first pieces and kicking off the main game loop with requestAnimationFrame.\n\nNow I'm handling the core game loop—checking if the game is paused, calculating the effective drop speed based on whether soft drop is active, and triggering piece drops at the appropriate intervals while also rendering each frame. When a piece can't move down anymore, I place it and check for completed lines, otherwise I just increment its y position.\n\nFor input handling, I'm implementing horizontal movement by validating the new position before shifting the piece left or right, and I'm starting the rotation logic by cycling through the available rotations for the current piece type with wall kick attempts to handle edge cases.\n\nStill writing game mechanics... Setting up input handlers...\n\nI'm wiring up keyboard controls for the game—space to start or hard drop, arrow keys and WASD for movement with delayed auto-shift, arrow down or S for soft drop, rotation with up arrow or Z, and pause with P or Escape. On key release, I'm clearing the movement state when the player lets go of left or right.\n\nNow I'm implementing the pause toggle, which stops the game loop and shows an overlay when paused, then resumes by resetting the drop timer. I'm also noticing there's a potential issue with the soft drop timing—when soft dropping is active, the effective drop interval becomes much faster, but I need to verify the math is working correctly for different levels. So for soft drop timing, I'm reconsidering whether to use a fixed rate or scale it with difficulty. Standard Tetris uses 20G acceleration, which would give roughly 40ms per cell at normal speed, but many modern games handle soft drop differently. I'm leaning toward a simpler approach with a consistent fast drop rate rather than scaling it with the level. The soft drop speed formula looks good across all difficulty levels. Now I'm implementing the actual game files, and I'm going to stick with the core mechanics the user requested rather than adding extra features like line clear animations or a hold piece system. For piece randomization, I'm using a 7-bag system where each tetromino appears once before repeating, which prevents long droughts of specific pieces.\n\nImplementing the bag system...\n\nI need to verify the rotation logic for the O piece since it only has one rotation state.\n\nNow I'm thinking through the input handling—I should make sure the rotation key doesn't auto-repeat on hold, and I want to add Z for counter-clockwise rotation using modulo arithmetic to cycle backwards through the rotation states.\n\nI've settled on the control scheme: arrow keys and WASD for movement, Up/W for clockwise rotation, Z for counter-clockwise, Space for hard drop, Down/S for soft drop, and P/Escape to pause. Time to stop overthinking and start building the actual game.\n\nWriting the HTML and styling... Still writing styles...\n\nNow I'm thinking through the overall layout—the game canvas needs to be 300×600 pixels for a 10×20 grid, with the side panel at 160 pixels wide, which gives me a comfortable total width around 484 pixels. I want to make sure the height works well on screen too.\n\nFor the next piece preview, I'm calculating the right canvas size—a 4×4 grid at 28 pixels per cell gives me 112×112 pixels, though I'll pad it out to 140×110 to have some breathing room. The tricky part is centering pieces of different widths, like the O piece which is only 2 blocks wide, so I need to account for that offset when rendering. I'm verifying the vertical centering calculations work the same way—the I piece sits at row 0, while the O and other pieces get centered properly. Now I'll set the canvas dimensions directly in HTML at 140x112 pixels with a block size of 28, then calculate the positioning dynamically based on those dimensions.\n\nSetting up the canvas...\n\nActually, I'm realizing there's a potential issue with the bag array—when I initialize the game, I call `createPiece()` twice to set up both the next piece and current piece, which means I'm popping from the bag twice right away.\n\nI need to reset the bag at the start of each game before creating those pieces. Let me make sure that's in the `startGame()` method.\n\nNow for the drop speed, I'm going to implement a formula that maps game levels to drop intervals. I'll use a simpler approach than the official Nintendo formula—something that feels responsive and scales well across difficulty levels.\n\nWriting the complete implementation... I'm testing an exponential decay formula that smoothly decreases the drop interval as levels increase, capping at 50ms to prevent the game from becoming unplayably fast. The curve feels natural—comfortable early on but ramping up significantly by the mid-teens. I'm settling on an exponential decay formula for the drop speed that caps at a minimum interval, keeping it simple and responsive. Now I'm verifying the T-piece rotation states to make sure they match the standard Tetris behavior across all four orientations. I'm verifying the rotation states for the S and Z pieces now, checking that each 90-degree rotation matches the expected grid patterns. Let me verify the clockwise rotation formula by working through the S piece systematically. Using the transformation where each new position pulls from the old matrix, I'm calculating all nine cells to confirm the rotated shape is correct.\n\nNow I'm checking the J piece rotations using the same method to make sure those definitions are accurate too. Verifying the 180° rotation produces the correct matrix, then moving on to calculate the 270° rotation by applying the same transformation logic to map old coordinates to new positions. Continuing with the L-piece rotation calculations, I'm verifying the second rotation by applying the clockwise transformation again to get the 180-degree state. I'm finishing the rotation calculation for the L piece and verifying the result matches my expected output. Now I need to move on to the I piece rotations, which use 4×4 matrices instead, so I'm starting to verify those as well. Continuing to work through the rotation transformations, I'm verifying that the 90-degree clockwise rotation produces the expected vertical line pattern. Now I need to apply the same transformation again to get the 180-degree rotation. Finishing the rotation calculation, I'm getting the expected output matrix with the 1s shifted to the third row, which matches my definition. Now I'm moving on to apply the same transformation for a 270-degree rotation. Finishing the rotation verification and confirming the tetromino definitions match the expected output. Now I'm ready to write out the actual files with these validated rotation patterns.\n\nSetting up the project structure with HTML, TypeScript game logic, and configuration files. I want to make sure TypeScript compiles properly so the game runs without any build issues.\n\nWriting the HTML file...\n\nConfiguring TypeScript settings...\n\nI'm realizing that using CommonJS would require a bundler for browser compatibility, so ES2020 modules with `<script type=\"module\">` would be cleaner. Actually, the simplest solution for a single TypeScript file is to compile without a module system entirely, letting TypeScript output everything in a way that works directly in the browser.\n\nConfiguring TypeScript...\n\nI'm realizing that since I'm not using any import/export statements in my TypeScript file, the compiled output will just be regular JavaScript without module syntax, even if I specify `\"module\": \"ES2020\"`. The `type=\"module\"` attribute in the HTML script tag won't cause issues in this case, and TypeScript will treat the file as a script rather than a module.\n\nFor the tsconfig, I should skip the `module` option entirely and let TypeScript default to CommonJS, but since my single-file game doesn't have any imports or exports, the output will just be plain JavaScript that works fine in the browser without needing a bundler. Checking the TypeScript module options to confirm `\"module\": \"none\"` is valid and case-insensitive—it is, and it's the right choice for a single-file browser script since it outputs plain JavaScript without any module wrapping. `nodenext`.\n\nYes, `none` is a valid option! Perfect. With `\"module\": \"none\"`, the TypeScript code compiles to plain JavaScript without any module wrapper. This is exactly what I need for a browser script tag.\n\nSo my tsconfig.json will have `target` set to ES2017, `module` set to none, and strict mode enabled. The HTML will just load the compiled script directly.\n\nNow I'm checking my TypeScript code for strict mode compatibility. I'm using non-null assertions on the canvas context, casting DOM elements to HTMLElement, and handling null values in the board type explicitly. There's one spot in the line-clearing logic where I'm splicing the board array and adding a new row that I should verify works correctly with strict checks.\n\nLooking at the loop structure, when a full row is found, I remove it and add an empty row at the top, then the loop counter adjusts so we re-check that same index since rows have shifted up. The logic handles this correctly. I need to trace through the array manipulation more carefully. When I remove a row from the middle and add an empty one at the top, the indices shift in a way that affects my loop logic—specifically, after removing row 5 and unshifting, what was at row 4 is now at row 5, so I shouldn't decrement the row counter; I should check the same index again to account for the shift. I need to trace through what happens to the array indices when I splice out a row and then unshift a new one. When I remove row at index `row`, everything below it shifts up by one index, so the row that was at `row+1` moves to `row`. Then when I unshift an empty row at the top, all existing rows shift down by one, which means that row that just moved to `row` is now at `row+1`. So the net effect is the row originally at `row+1` ends up at `row+1` again, while everything else shifts accordingly. Let me trace through a concrete example to verify this logic. Starting with a 5-row board where row 2 is complete, after removing it with splice and then unshifting an empty row, the rows shift up as expected—what was at index 3 moves to index 2, and what was at index 4 moves to index 3. Then incrementing `row` to 3 means the loop will check the next row down.\n\nActually, wait—the loop is going backwards from `ROWS - 1` down to 0, so when we find a complete row at index 2, incrementing `row` to 3 then immediately decrementing it back to 2 in the next iteration means we're re-checking the row that just shifted up from below the cleared line, which is exactly what we need to do. After clearing row 3, the board shifts and row 2 becomes the old row 3's data, so I need to increment row back to 3 and then decrement it to re-check the new row 2—which is fine since it wasn't complete anyway. Now I'm thinking through what happens when two consecutive rows are both complete: row 4 gets skipped, row 3 clears and shifts everything up, then I need to re-check row 3 since it now contains what was row 2. After the splice and unshift operations, board[3] ends up holding what was originally board[4], which isn't complete, so row 3 gets skipped. Then row 2 checks the old board[1], also incomplete. The algorithm correctly clears two lines total, and the key insight is that the `row++` followed by the loop's `row--` keeps us at the same index to re-examine it with the newly shifted rows.\n\nI'm also considering edge cases—like whether all rows could theoretically be complete at once, but that's impossible in standard Tetris since pieces are placed one at a time.\n\nNow I'm thinking about the soft drop mechanic and how `lastDropTime` interacts with it. When the player holds the soft drop key, the effective drop interval becomes much faster (around 40ms for level 1), so I need to make sure the timing logic handles this correctly.\n\nThe key insight is that when the player releases the soft drop key, `lastDropTime` was just updated from the last soft drop, so the next normal drop will happen 1000ms after that—giving the player a nice grace period to position the piece, which is actually good for gameplay. And when they first press soft drop, if `lastDropTime` is already in the past relative to the new 40ms interval, the piece drops immediately and the timer resets. This all works out naturally with the existing logic.\n\nThe one thing I'm reconsidering is the initial state: when the game starts with `lastDropTime = 0`, the first animation frame will have a huge timestamp value, so the piece drops immediately on frame one. I'm thinking it might be better to initialize `lastDropTime` to the current timestamp on the first frame instead, so the piece doesn't drop until the normal interval has actually elapsed. I can handle this by checking if `lastDropTime` is still 0 at the start of the loop and setting it to the current timestamp if so.\n\nActually, a cleaner approach is to set `lastDropTime` to `performance.now()` right in `startGame()` before the animation loop begins. Since `requestAnimationFrame` uses the same high-resolution timer as `performance.now()`, the first frame's timestamp will be approximately equal to what I set, meaning the elapsed time will be near zero and the piece won't drop immediately. This should work well.\n\nNow I'm thinking about the overall structure—I could use a state machine with 'start', 'playing', 'paused', and 'gameover' states, but that's probably overkill. I'll stick with the boolean flags I already have for `started`, `paused`, and `gameOver` to keep things simple.\n\nTime to write the actual implementation. I'm also considering the visual design for the side panel to make sure it looks polished.\n\nDesigning the arcade-style interface with a dark background, lighter panels, and neon accents. The layout will have the TETRIS logo at the top, followed by score, level, lines, and next piece displays arranged vertically alongside the main game canvas.\n\nBuilding the HTML and CSS structure... I'm testing different canvas dimensions to see how the pieces center properly—a 5×3 grid (125×75 pixels) might give the I piece better vertical spacing since it would have more room around it.\n\nActually, I think the cleanest approach is to just compute the bounding box of the actual filled cells in each piece and center that directly on the canvas, rather than trying to work with the full shape matrix dimensions.\n\nWriting canvas rendering code... Finishing the piece dimensions calculation and then drawing each filled cell at the centered position within the preview box, which properly handles pieces like the I-tetromino that have offset filled cells. With startY=0 and the I piece's block at shape row 1, it draws at canvas row 1, which is slightly above the vertical center of the 4-row canvas—that works fine. Now checking the T piece positioning.\n\nFor the T piece with height 2, the blocks span canvas rows 1 and 2, which centers perfectly between those rows, matching the canvas center. This approach is solid.\n\nI'll go with a 5×3 canvas at NEXT_BLOCK_SIZE (28 pixels), giving me 140×84 dimensions for the preview area.\n\nNow checking the positioning for specific pieces: the I piece (4 wide, 1 tall) centers horizontally at column 0 and vertically at row 1, while the O piece (2×2) positions at column 1, row 0, placing its four blocks in the top-left quadrant of the canvas.\n\nIncreasing the canvas height to 4 rows helps center the O piece vertically at rows 1-2, which aligns better with the middle of the available space. I'm settling on a 5×4 grid for the next block preview area.\n\nNow I'm working through the positioning math for different piece shapes—the I piece lands at row 1 with columns 0-3, and I'm calculating where the T piece should sit to keep it centered as well.\n\nI've settled on the design: a 300px canvas with a 160px side panel and 20px gap between them, giving me 480px total width and 600px height. Time to start writing the actual code 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b/test-results/.last-run.json @@ -1,6 +0,0 @@ -{ - "status": "failed", - "failedTests": [ - "a123abce010ea7d96fa7-488977003e1cf02fbef6" - ] -} -\ No newline at end of file diff --git a/test-results/index.ts-Tetris-Gameplay-Bot-run-gameplay-bot/error-context.md b/test-results/index.ts-Tetris-Gameplay-Bot-run-gameplay-bot/error-context.md @@ -1,16 +0,0 @@ -# Instructions - -- Following Playwright test failed. -- Explain why, be concise, respect Playwright best practices. -- Provide a snippet of code with the fix, if possible. - -# Test info - -- Name: index.ts >> Tetris Gameplay Bot >> run gameplay bot -- Location: tasks/tetris/eval/gameplay-bot/index.ts:94:7 - -# Error details - -``` -Test timeout of 120000ms exceeded. -``` -\ No newline at end of file