grid)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.IOException;\\nimport java.io.OutputStreamWriter;\\nimport java.util.Arrays;\\nimport java.io.BufferedWriter;\\nimport java.util.InputMismatchException;\\nimport java.io.OutputStream;\\nimport java.io.PrintWriter;\\nimport java.io.Writer;\\nimport java.math.BigInteger;\\nimport java.io.InputStream;\\n\\n/**\\n * Built using CHelper plug-in\\n * Actual solution is at the top\\n */\\npublic class Main {\\n\\tpublic static void main(String[] args) {\\n\\t\\tInputStream inputStream = System.in;\\n\\t\\tOutputStream outputStream = System.out;\\n\\t\\tInputReader in = new InputReader(inputStream);\\n\\t\\tOutputWriter out = new OutputWriter(outputStream);\\n\\t\\tGridChallenge solver = new GridChallenge();\\n\\t\\tint testCount = Integer.parseInt(in.next());\\n\\t\\tfor (int i = 1; i <= testCount; i++)\\n\\t\\t\\tsolver.solve(i, in, out);\\n\\t\\tout.close();\\n\\t}\\n}\\n\\nclass GridChallenge {\\n public void solve(int testNumber, InputReader in, OutputWriter out) {\\n int n = in.readInt();\\n char[][] g = new char[n][n];\\n for (int i = 0; i < n; i++) {\\n g[i] = in.readString().toCharArray();\\n Arrays.sort(g[i]);\\n }\\n boolean ok = true;\\n for (int j = 0; j < n && ok; j++) {\\n for (int i = 0; i < n - 1; i++) {\\n if (g[i + 1][j] < g[i][j]) {\\n ok = false;\\n break;\\n }\\n }\\n }\\n if (ok) {\\n out.printLine(\\\"YES\\\");\\n }\\n else {\\n out.printLine(\\\"NO\\\");\\n }\\n }\\n}\\n\\nclass InputReader {\\n\\n private InputStream stream;\\n private byte[] buf = new byte[1024];\\n private int curChar;\\n private int numChars;\\n private SpaceCharFilter filter;\\n\\n public InputReader(InputStream stream) {\\n this.stream = stream;\\n }\\n\\n public int read() {\\n if (numChars == -1)\\n throw new InputMismatchException();\\n if (curChar >= numChars) {\\n curChar = 0;\\n try {\\n numChars = stream.read(buf);\\n } catch (IOException e) {\\n throw new InputMismatchException();\\n }\\n if (numChars <= 0)\\n return -1;\\n }\\n return buf[curChar++];\\n }\\n\\n public int readInt() {\\n int c = read();\\n while (isSpaceChar(c))\\n c = read();\\n int sgn = 1;\\n if (c == '-') {\\n sgn = -1;\\n c = read();\\n }\\n int res = 0;\\n do {\\n if (c < '0' || c > '9')\\n throw new InputMismatchException();\\n res *= 10;\\n res += c - '0';\\n c = read();\\n } while (!isSpaceChar(c));\\n return res * sgn;\\n }\\n\\n public String readString() {\\n int c = read();\\n while (isSpaceChar(c))\\n c = read();\\n StringBuilder res = new StringBuilder();\\n do {\\n res.appendCodePoint(c);\\n c = read();\\n } while (!isSpaceChar(c));\\n return res.toString();\\n }\\n\\n public boolean isSpaceChar(int c) {\\n if (filter != null)\\n return filter.isSpaceChar(c);\\n return isWhitespace(c);\\n }\\n\\n public static boolean isWhitespace(int c) {\\n return c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n }\\n\\n public String next() {\\n return readString();\\n }\\n\\n public interface SpaceCharFilter {\\n public boolean isSpaceChar(int ch);\\n }\\n}\\n\\nclass OutputWriter {\\n private final PrintWriter writer;\\n\\n public OutputWriter(OutputStream outputStream) {\\n writer = new PrintWriter(new BufferedWriter(new OutputStreamWriter(outputStream)));\\n }\\n\\n public void print(Object...objects) {\\n for (int i = 0; i < objects.length; i++) {\\n if (i != 0)\\n writer.print(' ');\\n writer.print(objects[i]);\\n }\\n }\\n\\n public void printLine(Object...objects) {\\n print(objects);\\n writer.println();\\n }\\n\\n public void close() {\\n writer.close();\\n }\\n\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'gridChallenge' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static String gridChallenge(List<String> grid) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<String> grid = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String gridItem = bufferedReader.readLine();\\n grid.add(gridItem);\\n }\\n\\n String result = Result.gridChallenge(grid);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'gridChallenge' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static String gridChallenge(List<String> grid) {\\n for (int i = 0; i < grid.size(); i++) {\\n char[] asChars = grid.get(i).toCharArray();\\n Arrays.sort(asChars);\\n StringBuilder sb = new StringBuilder();\\n for (int j = 0; j < asChars.length; j++) {\\n sb.append(asChars[j]);\\n }\\n grid.set(i, sb.toString());\\n }\\n \\n for (int i = 0; i < grid.size() - 1; i++) {\\n for (int j = 0; j < grid.get(i).length(); j++) {\\n if (grid.get(i).charAt(j) > grid.get(i + 1).charAt(j)) {\\n return \\\"NO\\\";\\n } \\n }\\n }\\n \\n return \\\"YES\\\";\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<String> grid = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n String result = Result.gridChallenge(grid);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'gridChallenge' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static String gridChallenge(List<String> grid) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<String> grid = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n String result = Result.gridChallenge(grid);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.BufferedReader;\\nimport java.io.IOException;\\nimport java.io.InputStreamReader;\\nimport java.io.PrintWriter;\\nimport java.util.*;\\n\\n\\npublic class Solution {\\t\\n\\tBufferedReader reader;\\n StringTokenizer tokenizer;\\n PrintWriter out;\\n \\n\\tpublic void solve() throws IOException {\\t\\t\\t\\t\\n\\t\\tint T = nextInt();\\n\\t\\tfor (int t = 0; t < T; t++) {\\n int N = nextInt();\\n char[][] map = new char[N][];\\n for (int i = 0; i < N; i++) {\\n map[i] = reader.readLine().toCharArray();\\n Arrays.sort(map[i]);\\n }\\n\\n boolean OK = true;\\n for (int j = 0; j < N; j++) {\\n for (int i = 1; i < N; i++) {\\n if (map[i][j] < map[i-1][j]) OK = false;\\n }\\n }\\n\\n out.println(OK? \\\"YES\\\": \\\"NO\\\");\\n }\\n\\t}\\n\\t\\n\\t/**\\n\\t * @param args\\n\\t */\\n\\tpublic static void main(String[] args) {\\n\\t\\tnew Solution().run();\\n\\t}\\n\\t\\n\\tpublic void run() {\\n try {\\n reader = new BufferedReader(new InputStreamReader(System.in));\\n tokenizer = null;\\n out = new PrintWriter(System.out);\\n solve();\\n reader.close();\\n out.close();\\n } catch (Exception e) {\\n e.printStackTrace();\\n System.exit(1);\\n }\\n }\\n\\n int nextInt() throws IOException {\\n return Integer.parseInt(nextToken());\\n }\\n\\n long nextLong() throws IOException {\\n return Long.parseLong(nextToken());\\n }\\n\\n double nextDouble() throws IOException {\\n return Double.parseDouble(nextToken());\\n }\\n\\n String nextToken() throws IOException {\\n while (tokenizer == null || !tokenizer.hasMoreTokens()) {\\n tokenizer = new StringTokenizer(reader.readLine());\\n }\\n return tokenizer.nextToken();\\n }\\n\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'gridChallenge' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static String gridChallenge(List<String> grid) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<String> grid = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n String result = Result.gridChallenge(grid);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"gridChallenge(grid)\"\n ],\n \"solution\": \"def solve():\\n\\tn = int(input())\\n\\ta = [sorted(list(input())) for _ in range(n)]\\n\\tfor i in range(n - 1):\\n\\t\\tfor j in range(n):\\n\\t\\t\\tif a[i][j] > a[i + 1][j]:\\n\\t\\t\\t\\tprint(\\\"NO\\\")\\n\\t\\t\\t\\treturn\\n\\tprint(\\\"YES\\\")\\n\\nt = int(input())\\nfor _ in range(t):\\n\\tsolve()\\n\\t\",\n \"template\": \"#\\n# Complete the 'gridChallenge' function below.\\n#\\n# The function is expected to return a STRING.\\n# The function accepts STRING_ARRAY grid as parameter.\\n#\\n\\ndef gridChallenge(grid):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n n = int(input().strip())\\n\\n grid = []\\n\\n for _ in range(n):\\n grid_item = input()\\n grid.append(grid_item)\\n\\n result = gridChallenge(grid)\\n\\n fptr.write(result + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":270,"cells":{"question_id":{"kind":"number","value":21401,"string":"21,401"},"question_title":{"kind":"string","value":"Maximum Perimeter Triangle"},"question_content":{"kind":"string","value":"Given an array of stick lengths, use $3$ of them to construct a [non-degenerate triangle](https://en.wikipedia.org/wiki/Degeneracy_(mathematics)#Triangle) with the maximum possible perimeter. Return an array of the lengths of its sides as $3$ integers in non-decreasing order.\n\nIf there are several valid triangles having the maximum perimeter: \n\n1. Choose the one with the *longest maximum side*. \n2. If more than one has that maximum, choose from them the one with the *longest minimum side*. \n3. If more than one has that maximum as well, print any one them.\n\nIf no non-degenerate triangle exists, return $[-1]$.\n\n**Example** \n$sticks = [1, 2, 3, 4, 5, 10]$ \n\nThe triplet $(1,2,3)$ will not form a triangle. Neither will $(4,5,10)$ or $(2,3,5)$, so the problem is reduced to $(2,3,4)$ and $(3,4,5)$. The longer perimeter is $3+4+5=12$. \n\n**Function Description** \n\nComplete the *maximumPerimeterTriangle* function in the editor below. \n\nmaximumPerimeterTriangle has the following parameter(s): \n\n- *int sticks[n]:* the lengths of sticks available \n\n**Returns** \n\n- *int[3] or int[1]:* the side lengths of the chosen triangle in non-decreasing order or -1 "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Easy"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static List<Integer> maximumPerimeterTriangle(List<Integer> sticks)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner sc = new Scanner(System.in);\\n \\n int n = sc.nextInt();\\n int[] a = new int[n];\\n for (int i = 0; i < n; i++) {\\n a[i] = sc.nextInt();\\n }\\n Arrays.sort(a);\\n \\n int ans = -1;\\n for (int i = 2; i < n; i++) {\\n if (a[i-2]+a[i-1]>a[i])\\n ans = i;\\n }\\n if (ans == -1)\\n System.out.println(-1);\\n else\\n System.out.println(a[ans-2]+\\\" \\\"+a[ans-1]+\\\" \\\"+a[ans]);\\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'maximumPerimeterTriangle' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts INTEGER_ARRAY sticks as parameter.\\n */\\n\\n public static List<Integer> maximumPerimeterTriangle(List<Integer> sticks) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] sticksTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> sticks = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int sticksItem = Integer.parseInt(sticksTemp[i]);\\n sticks.add(sticksItem);\\n }\\n\\n List<Integer> result = Result.maximumPerimeterTriangle(sticks);\\n\\n for (int i = 0; i < result.size(); i++) {\\n bufferedWriter.write(String.valueOf(result.get(i)));\\n\\n if (i != result.size() - 1) {\\n bufferedWriter.write(\\\" \\\");\\n }\\n }\\n\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"//Greedy approach\\n//Constraint = sum of two sides is greater than third side\\n//Perimeter maximization\\nimport java.util.*;\\npublic class MaxPerimeter {\\n\\n public static void main(String[] args) {\\nScanner sc = new Scanner(System.in);\\nint n = sc.nextInt();\\nint[] a = new int[n];\\nfor (int i = 0; i < n; i++) {\\na[i] = sc.nextInt();\\n}\\nArrays.sort(a);\\nint ans = -1;\\nfor (int i = 2; i < n; i++) {\\nif (a[i-2]+a[i-1]>a[i])\\nans = i;\\n}\\nif (ans == -1)\\nSystem.out.println(-1);\\nelse\\nSystem.out.println(a[ans-2]+\\\" \\\"+a[ans-1]+\\\" \\\"+a[ans]);\\n}\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'maximumPerimeterTriangle' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts INTEGER_ARRAY sticks as parameter.\\n */\\n\\n public static List<Integer> maximumPerimeterTriangle(List<Integer> sticks) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> sticks = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> result = Result.maximumPerimeterTriangle(sticks);\\n\\n bufferedWriter.write(\\n result.stream()\\n .map(Object::toString)\\n .collect(joining(\\\" \\\"))\\n + \\\"\\\\n\\\"\\n );\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class B {\\n\\tInputStream is;\\n\\tPrintWriter out;\\n\\tString INPUT = \\\"\\\";\\n\\t\\n\\tvoid solve()\\n\\t{\\n\\t\\tint n = ni();\\n\\t\\tint[] a = na(n);\\n\\t\\tArrays.sort(a);\\n\\t\\tfor(int i = n-3;i >= 0;i--){\\n\\t\\t\\tif(a[i]+a[i+1] > a[i+2]){\\n\\t\\t\\t\\tout.println(a[i] + \\\" \\\" + a[i+1] + \\\" \\\" + a[i+2]);\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tout.println(-1);\\n\\t}\\n\\t\\n\\tvoid run() throws Exception\\n\\t{\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tlong s = System.currentTimeMillis();\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tif(!INPUT.isEmpty())tr(System.currentTimeMillis()-s+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception { new B().run(); }\\n\\t\\n\\tprivate byte[] inbuf = new byte[1024];\\n\\tprivate int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate double nd() { return Double.parseDouble(ns()); }\\n\\tprivate char nc() { return (char)skip(); }\\n\\t\\n\\tprivate String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'maximumPerimeterTriangle' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts INTEGER_ARRAY sticks as parameter.\\n */\\n\\n public static List<Integer> maximumPerimeterTriangle(List<Integer> sticks) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> sticks = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> result = Result.maximumPerimeterTriangle(sticks);\\n\\n bufferedWriter.write(\\n result.stream()\\n .map(Object::toString)\\n .collect(joining(\\\" \\\"))\\n + \\\"\\\\n\\\"\\n );\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"maximumPerimeterTriangle(sticks)\"\n ],\n \"solution\": \"from itertools import *\\nn = int(input())\\nl = sorted(map(int, input().split()))\\nans = (-1, -1, -1)\\nfor i, j, k in product(*repeat(range(n), 3)):\\n if i < j < k and l[i] + l[j] > l[k]:\\n ans = max(ans, (l[k], l[i], l[j]))\\nif ans[0] == -1:\\n print(-1)\\nelse: \\n print(ans[1], ans[2], ans[0])\",\n \"template\": \"#\\n# Complete the 'maximumPerimeterTriangle' function below.\\n#\\n# The function is expected to return an INTEGER_ARRAY.\\n# The function accepts INTEGER_ARRAY sticks as parameter.\\n#\\n\\ndef maximumPerimeterTriangle(sticks):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n n = int(input().strip())\\n\\n sticks = list(map(int, input().rstrip().split()))\\n\\n result = maximumPerimeterTriangle(sticks)\\n\\n fptr.write(' '.join(map(str, result)))\\n fptr.write('\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"eJztmM+Oo0kRxDnwCtxLfV5Q5d+q4kmQaMQB5gCHZlealZDQSjwEvC+/+Ja2F297EAdua2s0lv1VVWZkZGRU//3n//zmFz+7Xr/5Mx9++7eXP719/e3nl1+Pl9ivb3vvOfe00Sdyzd5n7HP8RK8YZb69Vuew3bNjZo/qHXayz8g949SIszvW8hg5IypWsZnZ8mmrhucxqz422Dx6W420eSzP5BM7Rhyfw2bu0zXnyK7cbj3MVwZx+Ngem+eD3XxZRebUWe6l72x28+ReI9NWnFw+yok3Vo6uVXsHZzlZkeAcdbIOCfBUrs1evseylbttjx0dlpPjT/debMPKudljccD2znBS5LuIeSbZOD92Hx+rZxb/gpxzsceuoe3T3ZONTyZI2evby1fj5dNfv/70h8+f/vj7v3z7+d/V+MGztwLcgnj57qvxg8plvL6lgyrl83H2cbAmrDzp0UUFYs+2OYGgas/aVWucRQy+KF04CwugmgqeFdTVbB+grTPIJ1kxz3BqYJaVAB9guiOGkfeaIDi8QSqrApQpn7n3gEOLMzbVA+GAGWDgMan8GpZtBS5GDYIibw7j/HnSDtH52ZNSjfYD8Y670qmdQcAwokgpnDpuTygIBVZlAj0wLyfeaURiYBeQFsaeCRVUUzYV0aDgJnEwXcQJ5wP+wGfOo6zJfmDRdMOoNYGqag6Ke63Vp2KfNCMqlh5AGCRaAggCpaCiEGMt/o9lA0BIneeeV/wW2L0yt1o+VLzm6xvkog/3pM4dlL+UEjusY1pZrC0HcRoVVOiZAfGL7WCugR4l9hGlbiwaEvYkHUdGXeoguDBITTyG/94kFNB2gH+XTbGeh1TxBUdyLmAyYQVVLy7RhGREKyADk1YLWLV8iVf0k8EavlJQ4uNReKWGSZgWRARwVJBG7qa0tL3NZZtjeXZv2IQMIUacC/nQgUV5k8fYfy0SgBo9zedCpNSUyMPmOxgJJ2o0WNAadFXvYjeOo7+omanQJkoif1C4nT4eQTUgCxJGfzhb0+vwZ5swG9Du2JkbrtCB7CqZWiZ2bXUVX026CHTUZ3ElkQea0mltQfVg7jBwtbWNX1E6aldqZtgNQvGUNveg75HdVj3QxpcknmOaZiU1pIrCFKLAHokiUucswSpRgEIm2UIDQ4FPfqWgMAytRMmLEo+rWfrCEdBUwI2QAw3CGWNJeOjFVnGBNA3tmKgxmPMJeaNESKRdU4NTScBy9VUCuqq0tBdxOnjSk03oU1IIjddEWnWsSKjSO7QE6wOSiAyMI+LFAIqLBCzeLt1Gmkirzxc68R2i+zG3PB8gZReoRcwJg3lgrxUadBP5EofIg0OJ2dAgIqWj6CumYfKGQyEoaJXhsJBnU7wqHkK5nwZ4X3V79r7nY82hDhHkCZMehU+16oYtSDIsTAlxad6ei9FbYgHmTEB6aaONjAGIPseioTiNswJh4DOVMwpCwugHur6tVaWjwYcgkhMSz1SQinNQXENMhKBlDwYB1UAoJyOu4Gosp3JoH6VujUikiqhVOJkO9TvkDIMsgLWZidRYs3qrgf15NW+b3wO7Jf8IFuWMEDlIX3JfPmUEFj4Hu8NKSolf0SSjRYUqwk8jq3cxLqgfwwClUtPggkRV9ApXc4iV4s7YHCuXQm8pJLqNn/EV0re9kEq0BneDHtE+DALUDsaggigHs4TQJ5ul5lIxi+kXjXd2YAgwyY54C+z8CkPmKZ4zBrTagVoCPF1Kn+sMC6UmP9YydXgkhpmzSUB51osQ+pmYh4Yr2Fk+F6IbHvekbsE+4ByUi56GdbBjMNbJGxVDSImO2oIfqkka7JEMZxJH5dEQ+ixpYX2aKgrN3MzKd7NG0/n35KVv2cWbmZ9XJ2NZFpHQKIvHW76jUV14tJU7maHdEgx2EUNZUYQQsqNQrtWbnMvGIA4DU2ZgI2jrSHSgIK0OXzAjiA2m2Gl85AlziSFpURtOYGkSNk0Np7yElxGCgSZmh6LKcmFwL25gjDUhoBpLD2OCTvHNAo3x52W4J3pL4JbyI93r9Q0eoIyYceiO8m/ND1WBQn4/xZUuHWNXRdB0FAIzpW3R1nmwT4fSQSUGNy4hinNLxjBlLTAbfdkIByk8OEGYRiKNBXXlTk6DTspYcJAuCLInujwweoBRcxVjwWyHzC53jpEKkmyBwS1ia4jiazDUre94HTwfEqweYzAz4cVwjCXjmXmOTD1H74bGPeFbeo+2O2W7tzqFsHAsWxQqgUDfMsiZB8TE9AGqho/4KuCAH9RHVyVmJXZEo5NehAfAjIVkM8G2NNORdPxT4k25uLgcOHaXJUPGgmFIKzhjn96Bugxw+hVwIBMzTvKp51ZKw2RzgteRSGmQufwIfGVVS0DoRAAekjIqwzQV3FMXLujUsnqiemPhNvlsIOHWRI5UVppITKqjrAwwIzYBHi1rD//BUfKiOl/umFxJGWRl6fWmJegJF9ebDRnkdl3lUJ3QzOAOpCuiYodgcOSIhjKM7EL/IJEyI6ihIDD5NeTLZANTICeDg2tgyZh/oXVu4dzhvQH4qGBM1cGJTze7fv3xIpg8npu5Xz4eI6OPc/h/v58GdP36UUzz/TV++vjTx48/PmfVf1n4YRNcDTWQ14GIDo3HgfVhmDBFTJfBoT8TYe8xBcxnRrkuG0PXC+YmysZwQC51CUR6GS1ccbA6yCtjfcjV4ivwu2foD0oytEOSgoLgQZq7x9DVBif0PK/3Bz6Iv6TP1w7r2q2uneM6xXSirtb7iqGvePKKza84p2JW5OvKoq6M4srOlCn5Kut1IVAXGnEhY0IJrQQytBj4WPSFbn8Svyv+8eN3397rev9vJHjy/MPZ9h8C6O/vL8gu7w9k937UeX99cZf7U89pyfgXnIBaT3e6OPvy3e/+8at/Ac6VkR8="},"max_retries":{"kind":"null"}}},{"rowIdx":271,"cells":{"question_id":{"kind":"number","value":16828,"string":"16,828"},"question_title":{"kind":"string","value":"Beautiful Pairs"},"question_content":{"kind":"string","value":"You are given two arrays, $A$ and $B$, both containing $N$ integers.\n\nA pair of indices $(i, j)$ is *beautiful* if the $i^{th}$ element of array $A$ is equal to the $j^{th}$ element of array $B$. In other words, pair $(i, j)$ is *beautiful* if and only if $A[i] = B[j]$. A set containing beautiful pairs is called a *beautiful set*.\n\nA beautiful set is called *pairwise disjoint* if for every pair $(l[i],r[i])$ belonging to the set there is no repetition of either $l[i]$ or $r[i]$ values. For instance, if $A = [10, 11, 12, 5, 14]$ and $B = [8, 9, 11, 11, 5]$ the beautiful set $[(1,2),(1,3),(3,4)]$ is not pairwise disjoint as there is a repetition of $1$, that is $l[0][0]=l[1][0]$. \n\nYour task is to change **exactly $1$** element in $B$ so that the size of the pairwise disjoint beautiful set is maximum.\n\n**Function Description** \n\nComplete the *beautifulPairs* function in the editor below. It should return an integer that represents the maximum number of pairwise disjoint beautiful pairs that can be formed. \n\nbeautifulPairs has the following parameters: \n\n- *A*: an array of integers \n- *B*: an array of integers "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Easy"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int beautifulPairs(List<Integer> A, List<Integer> B)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner s=new Scanner(System.in);\\n int len=s.nextInt();\\n HashMap<Integer,Integer> hmap=new HashMap<Integer,Integer>();\\n for(int i=0;i<len;i++)\\n {\\n int current=s.nextInt();\\n if(!hmap.containsKey(current))\\n {\\n \\n hmap.put(current,1);\\n }\\n else\\n {\\n int temp=hmap.get(current);\\n hmap.put(current,++temp);\\n }\\n }\\n int counter=0;\\n for(int i=0;i<len;i++)\\n {\\n int current=s.nextInt();\\n if(hmap.containsKey(current))\\n {\\n int temp=hmap.get(current);\\n if(temp>0)\\n {\\n hmap.put(current,--temp);\\n counter++;\\n }\\n else\\n {\\n hmap.remove(current);\\n }\\n \\n }\\n }\\n if(counter==len)\\n System.out.println(counter-1);\\n else if(counter<len)\\n System.out.println(counter+1);\\n else\\n System.out.println(counter);\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'beautifulPairs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY A\\n * 2. INTEGER_ARRAY B\\n */\\n\\n public static int beautifulPairs(List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] ATemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> A = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int AItem = Integer.parseInt(ATemp[i]);\\n A.add(AItem);\\n }\\n\\n String[] BTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> B = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int BItem = Integer.parseInt(BTemp[i]);\\n B.add(BItem);\\n }\\n\\n int result = Result.beautifulPairs(A, B);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'beautifulPairs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY A\\n * 2. INTEGER_ARRAY B\\n */\\n\\n public static int beautifulPairs(List<Integer> A, List<Integer> B) {\\n // Write your code here\\n int L = A.size();\\n int matches = 0;\\n for (int i = 0; i < L; i++) {\\n int index = B.indexOf(A.get(i));\\n if (index >= 0) {\\n B.remove(index);\\n // A.remove(i);\\n // L--;\\n matches++;\\n }\\n }\\n System.out.println(\\\"\\\" + B.size() + \\\" matches: \\\" + matches);\\n return matches + ((B.size() > 0) ? 1 : -1);\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> B = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.beautifulPairs(A, B);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'beautifulPairs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY A\\n * 2. INTEGER_ARRAY B\\n */\\n\\n public static int beautifulPairs(List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> B = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.beautifulPairs(A, B);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n private static InputReader in;\\n private static PrintWriter out;\\n\\n public static void main(String[] args) throws IOException {\\n in = new InputReader(System.in);\\n out = new PrintWriter(System.out, true);\\n\\n int n = in.nextInt();\\n int[] arr = new int[n];\\n int[] brr = new int[n];\\n int[] fa = new int[1001];\\n int[] fb = new int[1001];\\n for (int i = 0; i < n; i++) {\\n arr[i] = in.nextInt();\\n fa[arr[i]]++;\\n }\\n for (int i = 0; i < n; i++) {\\n brr[i] = in.nextInt();\\n fb[brr[i]]++;\\n }\\n int curans = 0;\\n for (int i = 0; i <= 1000; i++) {\\n curans += Math.min(fa[i], fb[i]);\\n }\\n out.println(curans == n ? n-1 : (curans + 1));\\n out.close();\\n System.exit(0);\\n }\\n\\n static class InputReader {\\n public BufferedReader reader;\\n public StringTokenizer tokenizer;\\n\\n public InputReader(InputStream stream) {\\n reader = new BufferedReader(new InputStreamReader(stream), 32768);\\n tokenizer = null;\\n }\\n\\n public String next() {\\n while (tokenizer == null || !tokenizer.hasMoreTokens()) {\\n try {\\n tokenizer = new StringTokenizer(reader.readLine());\\n } catch (IOException e) {\\n throw new RuntimeException(e);\\n }\\n }\\n return tokenizer.nextToken();\\n }\\n\\n public int nextInt() {\\n return Integer.parseInt(next());\\n }\\n }\\n\\n\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'beautifulPairs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY A\\n * 2. INTEGER_ARRAY B\\n */\\n\\n public static int beautifulPairs(List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> B = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.beautifulPairs(A, B);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"beautifulPairs(A, B)\"\n ],\n \"solution\": \"input()\\na = [x for x in input().split()]\\nb = [x for x in input().split()]\\naDict = dict()\\nbDict = dict()\\nfor val in a:\\n if val in aDict:\\n aDict[val] += 1\\n else:\\n aDict[val] = 1\\nfor val in b:\\n if val in bDict:\\n bDict[val] += 1\\n else:\\n bDict[val] = 1\\n\\ntotal = 0\\nfor val in aDict:\\n while aDict[val] > 0 and val in bDict and bDict[val] > 0:\\n total += 1\\n aDict[val] -= 1\\n bDict[val] -= 1\\n\\nif total == len(a):\\n print(total - 1)\\nelse:\\n print(total + 1)\",\n \"template\": \"#\\n# Complete the 'beautifulPairs' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. INTEGER_ARRAY A\\n# 2. INTEGER_ARRAY B\\n#\\n\\ndef beautifulPairs(A, B):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n n = int(input().strip())\\n\\n A = list(map(int, input().rstrip().split()))\\n\\n B = list(map(int, input().rstrip().split()))\\n\\n result = beautifulPairs(A, B)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":272,"cells":{"question_id":{"kind":"number","value":2149,"string":"2,149"},"question_title":{"kind":"string","value":"Priyanka and Toys"},"question_content":{"kind":"string","value":"\nPriyanka works for an international toy company that ships by container. Her task is to the determine the lowest cost way to combine her orders for shipping. She has a list of item weights. The shipping company has a requirement that all items loaded in a container must weigh less than or equal to 4 units plus the weight of the minimum weight item. All items meeting that requirement will be shipped in one container.\n\nWhat is the smallest number of containers that can be contracted to ship the items based on the given list of weights?\n\nFor example, there are items with weights $w = [1,2,3,4,5,10,11,12,13]$. This can be broken into two containers: $[1,2,3,4,5]$ and $[10,11,12,13]$. Each container will contain items weighing within $4$ units of the minimum weight item. \n\n**Function Description** \n\nComplete the *toys* function in the editor below. It should return the minimum number of containers required to ship. \n\ntoys has the following parameter(s): \n\n- *w*: an array of integers that represent the weights of each order to ship "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Easy"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int toys(List<Integer> w)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n private static Reader in;\\n private static PrintWriter out;\\n\\n public static void main(String[] args) throws IOException {\\n in = new Reader();\\n out = new PrintWriter(System.out, true);\\n int N = in.nextInt();\\n int[] arr = new int[N];\\n for (int i = 0; i < N; i++)arr[i] = in.nextInt();\\n Arrays.sort(arr);\\n int last = -10000;\\n int count = 0;\\n for (int i = 0; i < N; i++) {\\n if (last+4 < arr[i]) {\\n last = arr[i];\\n count++;\\n }\\n }\\n out.println(count);\\n out.close();\\n System.exit(0);\\n }\\n\\n static class Reader {\\n final private int BUFFER_SIZE = 1 << 16;\\n private DataInputStream din;\\n private byte[] buffer;\\n private int bufferPointer, bytesRead;\\n\\n public Reader() {\\n din = new DataInputStream(System.in);\\n buffer = new byte[BUFFER_SIZE];\\n bufferPointer = bytesRead = 0;\\n }\\n\\n public Reader(String file_name) throws IOException {\\n din = new DataInputStream(new FileInputStream(file_name));\\n buffer = new byte[BUFFER_SIZE];\\n bufferPointer = bytesRead = 0;\\n }\\n\\n public String readLine() throws IOException {\\n byte[] buf = new byte[1024];\\n int cnt = 0;\\n byte c = read();\\n while (c <= ' ')\\n c = read();\\n do {\\n buf[cnt++] = c;\\n } while ((c = read()) != '\\\\n');\\n return new String(buf, 0, cnt);\\n }\\n\\n public String next() throws IOException {\\n byte[] buf = new byte[1024];\\n int cnt = 0;\\n byte c = read();\\n while (c <= ' ')\\n c = read();\\n do {\\n buf[cnt++] = c;\\n } while ((c = read()) > ' ');\\n return new String(buf, 0, cnt);\\n }\\n\\n public int nextInt() throws IOException {\\n int ret = 0;\\n byte c = read();\\n while (c <= ' ')\\n c = read();\\n boolean neg = (c == '-');\\n if (neg)\\n c = read();\\n do {\\n ret = ret * 10 + c - '0';\\n } while ((c = read()) >= '0' && c <= '9');\\n if (neg)\\n return -ret;\\n return ret;\\n }\\n\\n public long nextLong() throws IOException {\\n long ret = 0;\\n byte c = read();\\n while (c <= ' ')\\n c = read();\\n boolean neg = (c == '-');\\n if (neg)\\n c = read();\\n do {\\n ret = ret * 10 + c - '0';\\n } while ((c = read()) >= '0' && c <= '9');\\n if (neg)\\n return -ret;\\n return ret;\\n }\\n\\n public double nextDouble() throws IOException {\\n double ret = 0, div = 1;\\n byte c = read();\\n while (c <= ' ')\\n c = read();\\n boolean neg = (c == '-');\\n if (neg)\\n c = read();\\n do {\\n ret = ret * 10 + c - '0';\\n } while ((c = read()) >= '0' && c <= '9');\\n if (c == '.')\\n while ((c = read()) >= '0' && c <= '9')\\n ret += (c - '0') / (div *= 10);\\n if (neg)\\n return -ret;\\n return ret;\\n }\\n\\n private void fillBuffer() throws IOException {\\n bytesRead = din.read(buffer, bufferPointer = 0, BUFFER_SIZE);\\n if (bytesRead == -1)\\n buffer[0] = -1;\\n }\\n\\n private byte read() throws IOException {\\n if (bufferPointer == bytesRead)\\n fillBuffer();\\n return buffer[bufferPointer++];\\n }\\n\\n public void close() throws IOException {\\n if (din == null)\\n return;\\n din.close();\\n }\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'toys' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY w as parameter.\\n */\\n\\n public static int toys(List<Integer> w) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] wTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> w = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int wItem = Integer.parseInt(wTemp[i]);\\n w.add(wItem);\\n }\\n\\n int result = Result.toys(w);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.util.*;\\npublic class PriyankaAndToys {\\n\\n public static void main(String[] args) {\\n Scanner sc = new Scanner(System.in);\\n int n = sc.nextInt();\\n List<Integer> arr = new ArrayList<Integer>();\\n for(int i=0;i<n;i++) {\\n arr.add(sc.nextInt());\\n }\\n Collections.sort(arr);\\n int result = solve(arr,n);\\n System.out.println(result);\\n }\\n public static int solve(List<Integer> arr,int n) {\\n int cost = 1,base = arr.get(0);\\n for(int i=0;i<n;i++) {\\n if(arr.get(i) > base+4) {\\n cost++;\\n base = arr.get(i);\\n }\\n }\\n return cost;\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'toys' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY w as parameter.\\n */\\n\\n public static int toys(List<Integer> w) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> w = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.toys(w);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.BufferedReader;\\nimport java.io.IOException;\\nimport java.io.InputStreamReader;\\nimport java.util.Arrays;\\nimport java.util.StringTokenizer;\\n\\n\\npublic class Solution {\\n\\n\\tpublic static void main(String[] args) throws NumberFormatException, IOException {\\n\\t\\tBufferedReader bfr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tfinal int N = Integer.parseInt(bfr.readLine());\\n\\t\\t\\n\\t\\tString line = bfr.readLine();\\n\\t\\tStringTokenizer st = new StringTokenizer(line);\\n\\t\\t\\n\\t\\tint[] array = new int[N];\\n\\t\\tfor(int i = 0; i < N; ++i)\\n\\t\\t{\\n\\t\\t\\tarray[i] = Integer.parseInt(st.nextToken());\\n\\t\\t}\\n\\t\\tSystem.out.println(solve(array));\\n\\t}\\n\\n\\tprivate static int solve(int[] array) {\\n\\t\\tArrays.sort(array);\\n\\t\\tint selectedWeight = array[0];\\n\\t\\tint cost = 1;\\n\\t\\tfor(int i = 1; i < array.length; ++i){\\n\\t\\t\\tif(array[i] > selectedWeight + 4)\\n\\t\\t\\t{\\n\\t\\t\\t\\tcost++;\\n\\t\\t\\t\\tselectedWeight = array[i];\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn cost;\\n\\t}\\n\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'toys' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY w as parameter.\\n */\\n\\n public static int toys(List<Integer> w) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> w = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.toys(w);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"toys(w)\"\n ],\n \"solution\": \"#!/usr/bin/env python\\n\\nimport sys\\n\\n\\nif __name__ == '__main__':\\n N = int(sys.stdin.readline())\\n W = sorted(map(int, sys.stdin.readline().split()))\\n\\n cost = 0\\n last_chosen = -5\\n\\n for w in W:\\n if w > last_chosen + 4:\\n cost += 1\\n last_chosen = w\\n\\n print(cost)\",\n \"template\": \"#\\n# Complete the 'toys' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY w as parameter.\\n#\\n\\ndef toys(w):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n n = int(input().strip())\\n\\n w = list(map(int, input().rstrip().split()))\\n\\n result = toys(w)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":273,"cells":{"question_id":{"kind":"number","value":3583,"string":"3,583"},"question_title":{"kind":"string","value":"Jim and the Orders"},"question_content":{"kind":"string","value":"Jim's Burgers has a line of hungry customers. Orders vary in the time it takes to prepare them. Determine the order the customers receive their orders. Start by numbering each of the customers from $1$ to $n$, front of the line to the back. You will then be given an *order number* and a *preparation time* for each customer. \n\nThe time of delivery is calculated as the sum of the order number and the preparation time. If two orders are delivered at the same time, assume they are delivered in ascending customer number order.\n\nFor example, there are $n=5$ customers in line. They each receive an order number $order[i]$ and a preparation time $prep[i]$.:\n```\nCustomer\t1\t2\t3\t4\t5\nOrder #\t\t8\t5\t6\t2\t4\nPrep time\t3\t6\t2\t3\t3\nCalculate:\nServe time\t11\t11\t8\t5\t7\n```\n\nWe see that the orders are delivered to customers in the following order:\n\n```\nOrder by:\nServe time\t5\t7\t8\t11\t11\nCustomer\t4\t5\t3\t1\t2\n```\n**Function Description** \n\nComplete the *jimOrders* function in the editor below. It should return an array of integers that represent the order that customers' orders are delivered. \n\njimOrders has the following parameter(s): \n\n- *orders*: a 2D integer array where each $orders[i]$ is in the form $[order[i], prep[i]]$. \n\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Easy"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static List<Integer> jimOrders(List<List<Integer>> orders)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.Comparator;\\nimport java.util.InputMismatchException;\\n\\npublic class A {\\n\\tstatic InputStream is;\\n\\tstatic PrintWriter out;\\n\\tstatic String INPUT = \\\"\\\";\\n\\t\\n\\tstatic void solve()\\n\\t{\\n\\t\\tint n = ni();\\n\\t\\tint[][] a = new int[n][];\\n\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\ta[i] = new int[]{ni() + ni(), i};\\n\\t\\t}\\n\\t\\tArrays.sort(a, new Comparator<int[]>() {\\n\\t\\t\\tpublic int compare(int[] a, int[] b) {\\n\\t\\t\\t\\tif(a[0] != b[0])return a[0] - b[0];\\n\\t\\t\\t\\treturn a[1] - b[1];\\n\\t\\t\\t}\\n\\t\\t});\\n\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\tif(i > 0)out.print(\\\" \\\");\\n\\t\\t\\tout.print(a[i][1]+1);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception\\n\\t{\\n\\t\\tlong S = System.currentTimeMillis();\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tlong G = System.currentTimeMillis();\\n\\t\\ttr(G-S+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tprivate static boolean eof()\\n\\t{\\n\\t\\tif(lenbuf == -1)return true;\\n\\t\\tint lptr = ptrbuf;\\n\\t\\twhile(lptr < lenbuf)if(!isSpaceChar(inbuf[lptr++]))return false;\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tis.mark(1000);\\n\\t\\t\\twhile(true){\\n\\t\\t\\t\\tint b = is.read();\\n\\t\\t\\t\\tif(b == -1){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn true;\\n\\t\\t\\t\\t}else if(!isSpaceChar(b)){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn false;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static byte[] inbuf = new byte[1024];\\n\\tstatic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate static int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate static boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate static int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate static double nd() { return Double.parseDouble(ns()); }\\n\\tprivate static char nc() { return (char)skip(); }\\n\\t\\n\\tprivate static String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate static char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate static char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate static int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate static int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { if(INPUT.length() != 0)System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'jimOrders' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts 2D_INTEGER_ARRAY orders as parameter.\\n */\\n\\n public static List<Integer> jimOrders(List<List<Integer>> orders) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> orders = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String[] ordersRowTempItems = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> ordersRowItems = new ArrayList<>();\\n\\n for (int j = 0; j < 2; j++) {\\n int ordersItem = Integer.parseInt(ordersRowTempItems[j]);\\n ordersRowItems.add(ordersItem);\\n }\\n\\n orders.add(ordersRowItems);\\n }\\n\\n List<Integer> result = Result.jimOrders(orders);\\n\\n for (int i = 0; i < result.size(); i++) {\\n bufferedWriter.write(String.valueOf(result.get(i)));\\n\\n if (i != result.size() - 1) {\\n bufferedWriter.write(\\\" \\\");\\n }\\n }\\n\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'jimOrders' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts 2D_INTEGER_ARRAY orders as parameter.\\n */\\n\\n public static List<Integer> jimOrders(List<List<Integer>> o) {\\n // Write your code here\\n int cust=1;\\n List<Integer> al=new ArrayList<>();\\n for(List<Integer> ol:o){\\n int a=0;\\n for(Integer il:ol){\\n a+=il;\\n }\\n al.add(a);\\n al.add(cust++);\\n }\\n for(int i=0;i<al.size();i+=2){\\n for(int j=al.size()-2;j>=0+i;j-=2){\\n int temp;\\n if(al.get(j)<al.get(i)){\\n temp=al.get(j);\\n al.set(j,al.get(i));\\n al.set(i,temp);\\n temp=al.get(j+1);\\n al.set(j+1,al.get(i+1));\\n al.set(i+1,temp);\\n }\\n }\\n }\\n List<Integer> al2=new ArrayList<>();\\n for(int i=1;i<al.size();i+=2){\\n al2.add(al.get(i));\\n }\\n return al2;\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> orders = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n orders.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n List<Integer> result = Result.jimOrders(orders);\\n\\n bufferedWriter.write(\\n result.stream()\\n .map(Object::toString)\\n .collect(joining(\\\" \\\"))\\n + \\\"\\\\n\\\"\\n );\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'jimOrders' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts 2D_INTEGER_ARRAY orders as parameter.\\n */\\n\\n public static List<Integer> jimOrders(List<List<Integer>> orders) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> orders = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n orders.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n List<Integer> result = Result.jimOrders(orders);\\n\\n bufferedWriter.write(\\n result.stream()\\n .map(Object::toString)\\n .collect(joining(\\\" \\\"))\\n + \\\"\\\\n\\\"\\n );\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.InputStreamReader;\\nimport java.io.IOException;\\nimport java.util.Arrays;\\nimport java.io.BufferedReader;\\nimport java.io.OutputStream;\\nimport java.io.PrintWriter;\\nimport java.util.StringTokenizer;\\nimport java.math.BigInteger;\\nimport java.io.InputStream;\\n\\n/**\\n * Built using CHelper plug-in\\n * Actual solution is at the top\\n * @author AlexFetisov\\n */\\npublic class Solutio {\\n\\tpublic static void main(String[] args) {\\n\\t\\tInputStream inputStream = System.in;\\n\\t\\tOutputStream outputStream = System.out;\\n\\t\\tInputReader in = new InputReader(inputStream);\\n\\t\\tPrintWriter out = new PrintWriter(outputStream);\\n\\t\\tHRA solver = new HRA();\\n\\t\\tsolver.solve(1, in, out);\\n\\t\\tout.close();\\n\\t}\\n}\\n\\nclass HRA {\\n public void solve(int testNumber, InputReader in, PrintWriter out) {\\n int n = in.nextInt();\\n Guy[] guys = new Guy[n];\\n for (int i = 0; i < n; ++i) {\\n guys[i] = new Guy(i, in.nextInt(), in.nextInt());\\n }\\n Arrays.sort(guys);\\n for (int i = 0; i < n; ++i) {\\n out.print(guys[i].id + 1);\\n out.print(' ');\\n }\\n out.println();\\n }\\n\\n class Guy implements Comparable<Guy> {\\n int timeGet;\\n int id;\\n\\n Guy(int id, int timeOrder, int timeDeliver) {\\n this.id = id;\\n this.timeGet = timeOrder + timeDeliver;\\n }\\n\\n public int compareTo(Guy o) {\\n if (timeGet != o.timeGet) return timeGet - o.timeGet;\\n return id - o.id;\\n }\\n }\\n}\\n\\nclass InputReader {\\n private BufferedReader reader;\\n private StringTokenizer stt;\\n\\n public InputReader(InputStream stream) {\\n reader = new BufferedReader(new InputStreamReader(stream));\\n }\\n\\n public String nextLine() {\\n try {\\n return reader.readLine().trim();\\n } catch (IOException e) {\\n return null;\\n }\\n }\\n\\n public String nextString() {\\n while (stt == null || !stt.hasMoreTokens()) {\\n stt = new StringTokenizer(nextLine());\\n }\\n return stt.nextToken();\\n }\\n\\n public int nextInt() {\\n return Integer.parseInt(nextString());\\n }\\n\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'jimOrders' function below.\\n *\\n * The function is expected to return an INTEGER_ARRAY.\\n * The function accepts 2D_INTEGER_ARRAY orders as parameter.\\n */\\n\\n public static List<Integer> jimOrders(List<List<Integer>> orders) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> orders = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n orders.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n List<Integer> result = Result.jimOrders(orders);\\n\\n bufferedWriter.write(\\n result.stream()\\n .map(Object::toString)\\n .collect(joining(\\\" \\\"))\\n + \\\"\\\\n\\\"\\n );\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"jimOrders(orders)\"\n ],\n \"solution\": \"tuples = []\\na = int(input())\\nfor i in range(a):\\n x, y = map(int, input().split(' '))\\n tuples.append((x+y, i+1))\\n\\ntuples.sort(key = lambda x:x[0])\\nprint(' '.join([str(x[1]) for x in tuples]))\\n\",\n \"template\": \"#\\n# Complete the 'jimOrders' function below.\\n#\\n# The function is expected to return an INTEGER_ARRAY.\\n# The function accepts 2D_INTEGER_ARRAY orders as parameter.\\n#\\n\\ndef jimOrders(orders):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n n = int(input().strip())\\n\\n orders = []\\n\\n for _ in range(n):\\n orders.append(list(map(int, input().rstrip().split())))\\n\\n result = jimOrders(orders)\\n\\n fptr.write(' '.join(map(str, result)))\\n fptr.write('\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":274,"cells":{"question_id":{"kind":"number","value":833,"string":"833"},"question_title":{"kind":"string","value":"Permuting Two Arrays"},"question_content":{"kind":"string","value":"There are two $n$-element arrays of integers, $A$ and $B$. Permute them into some $A'$ and $B'$ such that the relation $A'[i] + B'[i] \\ge k$ holds for all $i$ where $0 \\le i \\lt n$. \n\nThere will be $q$ queries consisting of $A$, $B$, and $k$. For each query, return `YES` if some permutation $A'$, $B'$ satisfying the relation exists. Otherwise, return `NO`. \n\n**Example** \n$A = [0, 1]$ \n$B = [0, 2]$ \n$k = 1$ \n\nA valid $A', B'$ is $A' = [1, 0]$ and $B' = [0, 2]$: $1 + 0 \\ge 1$ and $0 + 2 \\ge 1$. Return `YES`.\n\n**Function Description** \n\nComplete the *twoArrays* function in the editor below. It should return a string, either `YES` or `NO`. \n\ntwoArrays has the following parameter(s): \n\n- *int k:* an integer \n- *int A[n]:* an array of integers \n- *int B[n]:* an array of integers \n\n**Returns** \n- *string:* either `YES` or `NO` \n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Easy"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static String twoArrays(int k, List<Integer> A, List<Integer> B)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"/* HackerRank Template */\\n\\nimport java.io.*;\\nimport java.util.*;\\n\\nimport static java.lang.Math.*;\\nimport static java.util.Arrays.fill;\\nimport static java.util.Arrays.binarySearch;\\nimport static java.util.Arrays.sort;\\n\\npublic class Solution {\\n\\t\\n\\tstatic long initTime;\\n\\tstatic final Random rnd = new Random(7777L);\\n\\tstatic boolean writeLog = false;\\n\\t\\n\\tpublic static void main(String[] args) throws IOException {\\n\\t\\tinitTime = System.currentTimeMillis();\\n\\t\\ttry {\\n\\t\\t\\twriteLog = \\\"true\\\".equals(System.getProperty(\\\"LOCAL_RUN_7777\\\"));\\n\\t\\t} catch (SecurityException e) {}\\n\\t\\tnew Thread(null, new Runnable() {\\n\\t\\t\\tpublic void run() {\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\t\\tif (new File(\\\"input.txt\\\").exists())\\n\\t\\t\\t\\t\\t\\t\\tSystem.setIn(new FileInputStream(\\\"input.txt\\\"));\\n\\t\\t\\t\\t\\t} catch (SecurityException e) {}\\n\\t\\t\\t\\t\\tlong prevTime = System.currentTimeMillis();\\n\\t\\t\\t\\t\\tnew Solution().run();\\n\\t\\t\\t\\t\\twriteLog(\\\"Total time: \\\" + (System.currentTimeMillis() - prevTime) + \\\" ms\\\");\\n\\t\\t\\t\\t\\twriteLog(\\\"Memory status: \\\" + memoryStatus());\\n\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}, \\\"1\\\", 1L << 24).start(); \\n\\t}\\n\\n\\tvoid run() throws IOException {\\n\\t\\tin = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\tsolve();\\n\\t\\tout.close();\\n\\t\\tin.close();\\n\\t}\\n\\t\\n\\t/*************************************************************** \\n\\t * Solution\\n\\t **************************************************************/\\n\\n\\tvoid solve() throws IOException {\\n\\t\\t\\n\\t\\tfor (int T = nextInt(); T --> 0; ) {\\n\\t\\t\\tint n = nextInt();\\n\\t\\t\\tint k = nextInt();\\n\\t\\t\\tint[] a = nextIntArray(n);\\n\\t\\t\\tint[] b = nextIntArray(n);\\n\\t\\t\\tsort(a);\\n\\t\\t\\tsort(b);\\n\\t\\t\\tboolean ok = true;\\n\\t\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\t\\tif (a[i] + b[n - 1 - i] < k) {\\n\\t\\t\\t\\t\\tok = false;\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tout.println(ok ? \\\"YES\\\" : \\\"NO\\\");\\n\\t\\t}\\n\\t\\t\\n\\t\\n\\t}\\n\\t\\n\\t/*************************************************************** \\n\\t * Input \\n\\t **************************************************************/\\n\\tBufferedReader in;\\n\\tPrintWriter out;\\n\\tStringTokenizer st = new StringTokenizer(\\\"\\\");\\n\\t\\n\\tString nextToken() throws IOException {\\n\\t\\twhile (!st.hasMoreTokens())\\n\\t\\t\\tst = new StringTokenizer(in.readLine());\\n\\t\\treturn st.nextToken();\\n\\t}\\n\\t\\n\\tint nextInt() throws IOException {\\n\\t\\treturn Integer.parseInt(nextToken());\\n\\t}\\n\\t\\n\\tlong nextLong() throws IOException {\\n\\t\\treturn Long.parseLong(nextToken());\\n\\t}\\n\\t\\n\\tdouble nextDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(nextToken());\\n\\t}\\n\\t\\n\\tint[] nextIntArray(int size) throws IOException {\\n\\t\\tint[] ret = new int [size];\\n\\t\\tfor (int i = 0; i < size; i++)\\n\\t\\t\\tret[i] = nextInt();\\n\\t\\treturn ret;\\n\\t}\\n\\t\\n\\tlong[] nextLongArray(int size) throws IOException {\\n\\t\\tlong[] ret = new long [size];\\n\\t\\tfor (int i = 0; i < size; i++)\\n\\t\\t\\tret[i] = nextLong();\\n\\t\\treturn ret;\\n\\t}\\n\\t\\n\\tdouble[] nextDoubleArray(int size) throws IOException {\\n\\t\\tdouble[] ret = new double [size];\\n\\t\\tfor (int i = 0; i < size; i++)\\n\\t\\t\\tret[i] = nextDouble();\\n\\t\\treturn ret;\\n\\t}\\n\\t\\n\\tString nextLine() throws IOException {\\n\\t\\tst = new StringTokenizer(\\\"\\\");\\n\\t\\treturn in.readLine();\\n\\t}\\n\\t\\n\\tboolean EOF() throws IOException {\\n\\t\\twhile (!st.hasMoreTokens()) {\\n\\t\\t\\tString s = in.readLine();\\n\\t\\t\\tif (s == null)\\n\\t\\t\\t\\treturn true;\\n\\t\\t\\tst = new StringTokenizer(s);\\n\\t\\t}\\n\\t\\treturn false;\\n\\t}\\n\\t\\n\\t/*************************************************************** \\n\\t * Output \\n\\t **************************************************************/\\n\\tvoid printRepeat(String s, int count) {\\n\\t\\tfor (int i = 0; i < count; i++)\\n\\t\\t\\tout.print(s);\\n\\t}\\n\\t\\n\\tvoid printArray(int[] array) {\\n\\t\\tif (array == null || array.length == 0)\\n\\t\\t\\treturn;\\n\\t\\tfor (int i = 0; i < array.length; i++) {\\n\\t\\t\\tif (i > 0) out.print(' ');\\n\\t\\t\\tout.print(array[i]);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\tvoid printArray(long[] array) {\\n\\t\\tif (array == null || array.length == 0)\\n\\t\\t\\treturn;\\n\\t\\tfor (int i = 0; i < array.length; i++) {\\n\\t\\t\\tif (i > 0) out.print(' ');\\n\\t\\t\\tout.print(array[i]);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\tvoid printArray(double[] array) {\\n\\t\\tif (array == null || array.length == 0)\\n\\t\\t\\treturn;\\n\\t\\tfor (int i = 0; i < array.length; i++) {\\n\\t\\t\\tif (i > 0) out.print(' ');\\n\\t\\t\\tout.print(array[i]);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\tvoid printArray(double[] array, String spec) {\\n\\t\\tif (array == null || array.length == 0)\\n\\t\\t\\treturn;\\n\\t\\tfor (int i = 0; i < array.length; i++) {\\n\\t\\t\\tif (i > 0) out.print(' ');\\n\\t\\t\\tout.printf(Locale.US, spec, array[i]);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\tvoid printArray(Object[] array) {\\n\\t\\tif (array == null || array.length == 0)\\n\\t\\t\\treturn;\\n\\t\\tboolean blank = false;\\n\\t\\tfor (Object x : array) {\\n\\t\\t\\tif (blank) out.print(' '); else blank = true;\\n\\t\\t\\tout.print(x);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\t@SuppressWarnings(\\\"rawtypes\\\")\\n\\tvoid printCollection(Collection collection) {\\n\\t\\tif (collection == null || collection.isEmpty())\\n\\t\\t\\treturn;\\n\\t\\tboolean blank = false;\\n\\t\\tfor (Object x : collection) {\\n\\t\\t\\tif (blank) out.print(' '); else blank = true;\\n\\t\\t\\tout.print(x);\\n\\t\\t}\\n\\t\\tout.println();\\n\\t}\\n\\t\\n\\t/*************************************************************** \\n\\t * Utility\\n\\t **************************************************************/\\n\\tstatic String memoryStatus() {\\n\\t\\treturn (Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory() >> 20) + \\\"/\\\" + (Runtime.getRuntime().totalMemory() >> 20) + \\\" MB\\\";\\n\\t}\\n\\t\\n\\tstatic void checkMemory() {\\n\\t\\tSystem.err.println(memoryStatus());\\n\\t}\\n\\t\\n\\tstatic long prevTimeStamp = Long.MIN_VALUE;\\n\\t\\n\\tstatic void updateTimer() {\\n\\t\\tprevTimeStamp = System.currentTimeMillis();\\n\\t}\\n\\t\\n\\tstatic long elapsedTime() {\\n\\t\\treturn (System.currentTimeMillis() - prevTimeStamp);\\n\\t}\\n\\t\\n\\tstatic void checkTimer() {\\n\\t\\tSystem.err.println(elapsedTime() + \\\" ms\\\");\\n\\t}\\n\\t\\n\\tstatic void chk(boolean f) {\\n\\t\\tif (!f) throw new RuntimeException(\\\"Assert failed\\\");\\n\\t}\\n\\t\\n\\tstatic void chk(boolean f, String format, Object ... args) {\\n\\t\\tif (!f) throw new RuntimeException(String.format(format, args));\\n\\t}\\n\\t\\n\\tstatic void writeLog(String format, Object ... args) {\\n\\t\\tif (writeLog) System.err.println(String.format(Locale.US, format, args));\\n\\t}\\n\\t\\n\\tstatic void swap(int[] a, int i, int j) {\\n\\t\\tint tmp = a[i];\\n\\t\\ta[i] = a[j];\\n\\t\\ta[j] = tmp;\\n\\t}\\n\\t\\n\\tstatic void swap(long[] a, int i, int j) {\\n\\t\\tlong tmp = a[i];\\n\\t\\ta[i] = a[j];\\n\\t\\ta[j] = tmp;\\n\\t}\\n\\t\\n\\tstatic void swap(double[] a, int i, int j) {\\n\\t\\tdouble tmp = a[i];\\n\\t\\ta[i] = a[j];\\n\\t\\ta[j] = tmp;\\n\\t}\\n\\t\\n\\tstatic void shuffle(int[] a, int from, int to) {\\n\\t\\tfor (int i = from; i < to; i++)\\n\\t\\t\\tswap(a, i, rnd.nextInt(a.length));\\n\\t}\\n\\t\\n\\tstatic void shuffle(long[] a, int from, int to) {\\n\\t\\tfor (int i = from; i < to; i++)\\n\\t\\t\\tswap(a, i, rnd.nextInt(a.length));\\n\\t}\\n\\t\\n\\tstatic void shuffle(double[] a, int from, int to) {\\n\\t\\tfor (int i = from; i < to; i++)\\n\\t\\t\\tswap(a, i, rnd.nextInt(a.length));\\n\\t}\\n\\t\\n\\tstatic void shuffle(int[] a) {\\n\\t\\tif (a == null) return;\\n\\t\\tshuffle(a, 0, a.length);\\n\\t}\\n\\t\\n\\tstatic void shuffle(long[] a) {\\n\\t\\tif (a == null) return;\\n\\t\\tshuffle(a, 0, a.length);\\n\\t}\\n\\t\\n\\tstatic void shuffle(double[] a) {\\n\\t\\tif (a == null) return;\\n\\t\\tshuffle(a, 0, a.length);\\n\\t}\\n\\t\\n\\tstatic long[] getPartialSums(int[] a) {\\n\\t\\tfinal long[] sums = new long [a.length + 1];\\n\\t\\tfor (int i = 0; i < a.length; i++)\\n\\t\\t\\tsums[i + 1] = sums[i] + a[i];\\n\\t\\treturn sums;\\n\\t}\\n\\t\\n\\tstatic long[] getPartialSums(long[] a) {\\n\\t\\tfinal long[] sums = new long [a.length + 1];\\n\\t\\tfor (int i = 0; i < a.length; i++)\\n\\t\\t\\tsums[i + 1] = sums[i] + a[i];\\n\\t\\treturn sums;\\n\\t}\\n\\t\\n\\tstatic int[] getOrderedSet(int[] a) {\\n\\t\\tfinal int[] set = Arrays.copyOf(a, a.length);\\n\\t\\tif (a.length == 0) return set;\\n\\t\\tshuffle(set);\\n\\t\\tsort(set);\\n\\t\\tint k = 1;\\n\\t\\tint prev = set[0];\\n\\t\\tfor (int i = 1; i < a.length; i++) {\\n\\t\\t\\tif (prev != set[i]) {\\n\\t\\t\\t\\tset[k++] = prev = set[i];\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn Arrays.copyOf(set, k);\\n\\t}\\n\\t\\n\\tstatic long[] getOrderedSet(long[] a) {\\n\\t\\tfinal long[] set = Arrays.copyOf(a, a.length);\\n\\t\\tif (a.length == 0) return set;\\n\\t\\tshuffle(set);\\n\\t\\tsort(set);\\n\\t\\tint k = 1;\\n\\t\\tlong prev = set[0];\\n\\t\\tfor (int i = 1; i < a.length; i++) {\\n\\t\\t\\tif (prev != set[i]) {\\n\\t\\t\\t\\tset[k++] = prev = set[i];\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn Arrays.copyOf(set, k);\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoArrays' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts following parameters:\\n * 1. INTEGER k\\n * 2. INTEGER_ARRAY A\\n * 3. INTEGER_ARRAY B\\n */\\n\\n public static String twoArrays(int k, List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int qItr = 0; qItr < q; qItr++) {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int k = Integer.parseInt(firstMultipleInput[1]);\\n\\n String[] ATemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> A = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int AItem = Integer.parseInt(ATemp[i]);\\n A.add(AItem);\\n }\\n\\n String[] BTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> B = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int BItem = Integer.parseInt(BTemp[i]);\\n B.add(BItem);\\n }\\n\\n String result = Result.twoArrays(k, A, B);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'twoArrays' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts following parameters:\\n * 1. INTEGER k\\n * 2. INTEGER_ARRAY A\\n * 3. INTEGER_ARRAY B\\n */\\n\\n public static String twoArrays(int k, List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n boolean isYes = true;\\n Collections.sort(A);\\n Collections.sort(B, Collections.reverseOrder());\\n \\n for(int i = 0; i < A.size();i++) {\\n if((A.get(i) + B.get(i)) < k) {\\n isYes = false;\\n break;\\n }\\n }\\n \\n System.out.println(\\\"K - \\\" + k + \\\"\\\\n | A | \\\" + A + \\\"\\\\n | B | \\\" + B ); \\n return isYes ? \\\"YES\\\" : \\\"NO\\\";\\n\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int k = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> B = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n String result = Result.twoArrays(k, A, B);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoArrays' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts following parameters:\\n * 1. INTEGER k\\n * 2. INTEGER_ARRAY A\\n * 3. INTEGER_ARRAY B\\n */\\n\\n public static String twoArrays(int k, List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int k = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> B = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n String result = Result.twoArrays(k, A, B);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.BufferedReader;\\nimport java.io.InputStreamReader;\\nimport java.util.Arrays;\\n\\npublic class Solution {\\n\\t\\n//\\tInput Format\\n//\\tThe first line contains an integer, T, the number of test-cases. T test cases follow. \\n//\\tEach test case has the following format:\\n//\\n//\\tThe first line contains two integers, N and K. The second line contains N space separated integers, \\n//\\tdenoting A array. The third line describes B array in a same format.\\n//\\n//\\tOutput Format\\n//\\tFor each test case, if such an arrangement exists output \\\"YES\\\", otherwise \\\"NO\\\" (without quotes).\\n\\n\\tpublic static void main(String[] args) throws Exception {\\n\\t\\t\\n\\t\\ttry(BufferedReader reader = new BufferedReader(new InputStreamReader(System.in))){\\n\\n\\t\\t\\tint T = Integer.parseInt(reader.readLine());\\n\\t\\t\\tTestCaseLoop:\\n\\t\\t\\tfor(int t = 0; t < T; ++t) \\n\\t\\t\\t{\\n\\t\\t\\t\\tString[] dimensions = reader.readLine().split(\\\"\\\\\\\\s\\\");\\n\\t\\t\\t\\tint N = Integer.parseInt(dimensions[0]);\\n\\t\\t\\t\\tint K = Integer.parseInt(dimensions[1]);\\n\\t\\t\\t\\tString[] A_s = reader.readLine().split(\\\"\\\\\\\\s\\\");\\n\\t\\t\\t\\tString[] B_s = reader.readLine().split(\\\"\\\\\\\\s\\\");\\n\\t\\t\\t\\tint[] A = new int[N];\\n\\t\\t\\t\\tint[] B = new int[N];\\n\\t\\t\\t\\tfor(int i = 0 ; i < N; ++i) {\\n\\t\\t\\t\\t\\tA[i] = Integer.parseInt(A_s[i]);\\n\\t\\t\\t\\t\\tB[i] = Integer.parseInt(B_s[i]);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tArrays.parallelSort(A);\\n\\t\\t\\t\\tArrays.parallelSort(B);\\n\\t\\t\\t\\t//System.out.println(Arrays.toString(A));\\n\\t\\t\\t\\t//System.out.println(Arrays.toString(B));\\n\\t\\t\\t\\tfor(int i = 0; i < N; ++i) {\\n\\t\\t\\t\\t\\tif(A[i] + B[N-i-1] < K) {\\n\\t\\t\\t\\t\\t\\tSystem.out.print(\\\"NO\\\\n\\\");\\n\\t\\t\\t\\t\\t\\tcontinue TestCaseLoop;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tSystem.out.print(\\\"YES\\\\n\\\");\\n\\t\\t\\t}\\n\\t\\t\\tSystem.out.flush();\\n\\t\\t}\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoArrays' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts following parameters:\\n * 1. INTEGER k\\n * 2. INTEGER_ARRAY A\\n * 3. INTEGER_ARRAY B\\n */\\n\\n public static String twoArrays(int k, List<Integer> A, List<Integer> B) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int k = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n List<Integer> B = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n String result = Result.twoArrays(k, A, B);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"twoArrays(k, A, B)\"\n ],\n \"solution\": \"def isGood(listA, listB, k):\\n n = len(listA)\\n listA.sort()\\n listB.sort(reverse=True)\\n for i in range(n):\\n if listA[i]+listB[i] < k:\\n return False\\n return True\\n\\nT = int(input().strip())\\nfor i in range(T):\\n [n, k] = [int(x) for x in input().strip().split()]\\n listA = [int(x) for x in input().strip().split()]\\n listB = [int(x) for x in input().strip().split()]\\n if isGood(listA, listB, k):\\n print(\\\"YES\\\")\\n else:\\n print(\\\"NO\\\")\\n \",\n \"template\": \"#\\n# Complete the 'twoArrays' function below.\\n#\\n# The function is expected to return a STRING.\\n# The function accepts following parameters:\\n# 1. INTEGER k\\n# 2. INTEGER_ARRAY A\\n# 3. INTEGER_ARRAY B\\n#\\n\\ndef twoArrays(k, A, B):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n q = int(input().strip())\\n\\n for q_itr in range(q):\\n first_multiple_input = input().rstrip().split()\\n\\n n = int(first_multiple_input[0])\\n\\n k = int(first_multiple_input[1])\\n\\n A = list(map(int, input().rstrip().split()))\\n\\n B = list(map(int, input().rstrip().split()))\\n\\n result = twoArrays(k, A, B)\\n\\n fptr.write(result + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":275,"cells":{"question_id":{"kind":"number","value":24761,"string":"24,761"},"question_title":{"kind":"string","value":"Cloudy Day "},"question_content":{"kind":"string","value":"Quibdó in Colombia is one among the cities that receive maximum rainfall in the world.\n____________________________________________________________________________________\n\nAll year round, the city is covered in clouds. The city has many towns, located on a one-dimensional line. The positions and populations of each town on the number line are known to you. \nEvery cloud covers all towns located at a certain distance from it. A town is said to be in *darkness* if there exists *at least* one cloud such that the town is within the cloud's range. Otherwise, it is said to be *sunny*.\n\n\n\nThe city council has determined that they have enough money to remove *exactly one* cloud using their latest technology. Thus they want to remove the cloud such that the fewest number of people are left in darkness after the cloud is removed. What is the maximum number of people that will be in a sunny town after removing exactly one cloud?\n\n*Note:* If a town is not covered by any clouds, then it is already considered to be sunny, and the population of this town must also be included in the final answer.\n\nComplete the function `maximumPeople` which takes four arrays representing the populations of each town, locations of the towns, locations of the clouds, and the extents of coverage of the clouds respectively, and returns the maximum number of people that will be in a sunny town after removing exactly one cloud.\n\n\n\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static long maximumPeople(List<Long> p, List<Long> x, List<Long> y, List<Long> r)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n static long maximumPeople(long[] p, long[] x, long[] y, long[] r) {\\n // Return the maximum number of people that will be in a sunny town after removing exactly one cloud.\\n long sum1=0;\\n for(int i=0;i<y.length;i++)\\n {\\n long sum=0;\\n for(int j=0;j<x.length;j++)\\n {\\n int flag=1;\\n for(int k=0;k<y.length;k++)\\n {\\n if(i==k)\\n continue;\\n else\\n {\\n if(x[j]>=y[k]-r[k] && x[j]<=y[k]+r[k])\\n {\\n flag=0;\\n break;\\n }\\n }\\n }\\n if(flag==1)\\n {\\n sum=sum+p[j];\\n //break;\\n }\\n \\n }\\n if(sum>sum1)\\n sum1=sum;\\n }\\n return sum1;\\n }\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int n = in.nextInt();\\n long[] p = new long[n];\\n for(int p_i = 0; p_i < n; p_i++){\\n p[p_i] = in.nextLong();\\n }\\n long[] x = new long[n];\\n for(int x_i = 0; x_i < n; x_i++){\\n x[x_i] = in.nextLong();\\n }\\n int m = in.nextInt();\\n long[] y = new long[m];\\n for(int y_i = 0; y_i < m; y_i++){\\n y[y_i] = in.nextLong();\\n }\\n long[] r = new long[m];\\n for(int r_i = 0; r_i < m; r_i++){\\n r[r_i] = in.nextLong();\\n }\\n long result = maximumPeople(p, x, y, r);\\n System.out.println(result);\\n in.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'maximumPeople' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts following parameters:\\n * 1. LONG_INTEGER_ARRAY p\\n * 2. LONG_INTEGER_ARRAY x\\n * 3. LONG_INTEGER_ARRAY y\\n * 4. LONG_INTEGER_ARRAY r\\n */\\n\\n public static long maximumPeople(List<Long> p, List<Long> x, List<Long> y, List<Long> r) {\\n // Return the maximum number of people that will be in a sunny town after removing exactly one cloud.\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] pTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Long> p = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n long pItem = Long.parseLong(pTemp[i]);\\n p.add(pItem);\\n }\\n\\n String[] xTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Long> x = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n long xItem = Long.parseLong(xTemp[i]);\\n x.add(xItem);\\n }\\n\\n int m = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] yTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Long> y = new ArrayList<>();\\n\\n for (int i = 0; i < m; i++) {\\n long yItem = Long.parseLong(yTemp[i]);\\n y.add(yItem);\\n }\\n\\n String[] rTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Long> r = new ArrayList<>();\\n\\n for (int i = 0; i < m; i++) {\\n long rItem = Long.parseLong(rTemp[i]);\\n r.add(rItem);\\n }\\n\\n long result = Result.maximumPeople(p, x, y, r);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"DNE\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'maximumPeople' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts following parameters:\\n * 1. LONG_INTEGER_ARRAY p\\n * 2. LONG_INTEGER_ARRAY x\\n * 3. LONG_INTEGER_ARRAY y\\n * 4. LONG_INTEGER_ARRAY r\\n */\\n\\n public static long maximumPeople(List<Long> p, List<Long> x, List<Long> y, List<Long> r) {\\n // Return the maximum number of people that will be in a sunny town after removing exactly one cloud.\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Long> p = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n List<Long> x = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n int m = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Long> y = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n List<Long> r = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n long result = Result.maximumPeople(p, x, y, r);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.OutputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.OutputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.Iterator;\\nimport java.io.BufferedWriter;\\nimport java.util.InputMismatchException;\\nimport java.io.IOException;\\nimport java.io.Writer;\\nimport java.io.OutputStreamWriter;\\nimport java.util.NoSuchElementException;\\nimport java.io.InputStream;\\n\\n/**\\n * Built using CHelper plug-in\\n * Actual solution is at the top\\n *\\n * @author Egor Kulikov (egor@egork.net)\\n */\\npublic class Solution {\\n public static void main(String[] args) {\\n InputStream inputStream = System.in;\\n OutputStream outputStream = System.out;\\n InputReader in = new InputReader(inputStream);\\n OutputWriter out = new OutputWriter(outputStream);\\n CloudyDay solver = new CloudyDay();\\n solver.solve(1, in, out);\\n out.close();\\n }\\n\\n static class CloudyDay {\\n public void solve(int testNumber, InputReader in, OutputWriter out) {\\n int n = in.readInt();\\n int[] p = in.readIntArray(n);\\n int[] x = in.readIntArray(n);\\n int m = in.readInt();\\n int[] y = in.readIntArray(m);\\n int[] r = in.readIntArray(m);\\n ArrayUtils.orderBy(x, p);\\n int[] left = new int[m];\\n int[] right = new int[m];\\n long[] delta = new long[n + 1];\\n for (int i = 0; i < m; i++) {\\n int from = y[i] - r[i];\\n int start = Arrays.binarySearch(x, from);\\n if (start < 0) {\\n start = -start - 1;\\n }\\n left[i] = start;\\n int to = y[i] + r[i];\\n int end = Arrays.binarySearch(x, to);\\n if (end < 0) {\\n end = -end - 2;\\n }\\n right[i] = end;\\n delta[start]++;\\n delta[end + 1]--;\\n }\\n FenwickTree tree = new FenwickTree(n);\\n long sunny = 0;\\n long clouds = 0;\\n for (int i = 0; i < n; i++) {\\n clouds += delta[i];\\n if (clouds == 0) {\\n sunny += p[i];\\n } else if (clouds == 1) {\\n tree.add(i, p[i]);\\n }\\n }\\n long maxAdd = 0;\\n for (int i = 0; i < m; i++) {\\n if (right[i] >= left[i]) {\\n maxAdd = Math.max(maxAdd, tree.get(left[i], right[i]));\\n }\\n }\\n out.printLine(sunny + maxAdd);\\n }\\n\\n }\\n\\n static interface IntIterator {\\n public int value() throws NoSuchElementException;\\n\\n public boolean advance();\\n\\n public boolean isValid();\\n\\n }\\n\\n static class FenwickTree {\\n private final long[] value;\\n\\n public FenwickTree(int size) {\\n value = new long[size];\\n }\\n\\n public long get(int from, int to) {\\n if (from > to) {\\n return 0;\\n }\\n return get(to) - get(from - 1);\\n }\\n\\n private long get(int to) {\\n to = Math.min(to, value.length - 1);\\n long result = 0;\\n while (to >= 0) {\\n result += value[to];\\n to = (to & (to + 1)) - 1;\\n }\\n return result;\\n }\\n\\n public void add(int at, long value) {\\n while (at < this.value.length) {\\n this.value[at] += value;\\n at = at | (at + 1);\\n }\\n }\\n\\n }\\n\\n static class InputReader {\\n private InputStream stream;\\n private byte[] buf = new byte[1024];\\n private int curChar;\\n private int numChars;\\n private InputReader.SpaceCharFilter filter;\\n\\n public InputReader(InputStream stream) {\\n this.stream = stream;\\n }\\n\\n public int[] readIntArray(int size) {\\n int[] array = new int[size];\\n for (int i = 0; i < size; i++) {\\n array[i] = readInt();\\n }\\n return array;\\n }\\n\\n public int read() {\\n if (numChars == -1) {\\n throw new InputMismatchException();\\n }\\n if (curChar >= numChars) {\\n curChar = 0;\\n try {\\n numChars = stream.read(buf);\\n } catch (IOException e) {\\n throw new InputMismatchException();\\n }\\n if (numChars <= 0) {\\n return -1;\\n }\\n }\\n return buf[curChar++];\\n }\\n\\n public int readInt() {\\n int c = read();\\n while (isSpaceChar(c)) {\\n c = read();\\n }\\n int sgn = 1;\\n if (c == '-') {\\n sgn = -1;\\n c = read();\\n }\\n int res = 0;\\n do {\\n if (c < '0' || c > '9') {\\n throw new InputMismatchException();\\n }\\n res *= 10;\\n res += c - '0';\\n c = read();\\n } while (!isSpaceChar(c));\\n return res * sgn;\\n }\\n\\n public boolean isSpaceChar(int c) {\\n if (filter != null) {\\n return filter.isSpaceChar(c);\\n }\\n return isWhitespace(c);\\n }\\n\\n public static boolean isWhitespace(int c) {\\n return c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n }\\n\\n public interface SpaceCharFilter {\\n public boolean isSpaceChar(int ch);\\n\\n }\\n\\n }\\n\\n static class Range {\\n public static IntList range(int from, int to) {\\n int[] result = new int[Math.abs(from - to)];\\n int current = from;\\n if (from <= to) {\\n for (int i = 0; i < result.length; i++) {\\n result[i] = current++;\\n }\\n } else {\\n for (int i = 0; i < result.length; i++) {\\n result[i] = current--;\\n }\\n }\\n return new IntArray(result);\\n }\\n\\n }\\n\\n static class IntArray extends IntAbstractStream implements IntList {\\n private int[] data;\\n\\n public IntArray(int[] arr) {\\n data = arr;\\n }\\n\\n public int size() {\\n return data.length;\\n }\\n\\n public int get(int at) {\\n return data[at];\\n }\\n\\n public void addAt(int index, int value) {\\n throw new UnsupportedOperationException();\\n }\\n\\n public void removeAt(int index) {\\n throw new UnsupportedOperationException();\\n }\\n\\n public void set(int index, int value) {\\n data[index] = value;\\n }\\n\\n }\\n\\n static interface IntComparator {\\n public int compare(int first, int second);\\n\\n }\\n\\n static class ArrayUtils {\\n public static int[] range(int from, int to) {\\n return Range.range(from, to).toArray();\\n }\\n\\n public static int[] createOrder(int size) {\\n return range(0, size);\\n }\\n\\n public static int[] sort(int[] array, IntComparator comparator) {\\n return sort(array, 0, array.length, comparator);\\n }\\n\\n public static int[] sort(int[] array, int from, int to, IntComparator comparator) {\\n if (from == 0 && to == array.length) {\\n new IntArray(array).sort(comparator);\\n } else {\\n new IntArray(array).subList(from, to).sort(comparator);\\n }\\n return array;\\n }\\n\\n public static int[] order(final int[] array) {\\n return sort(createOrder(array.length), new IntComparator() {\\n public int compare(int first, int second) {\\n if (array[first] < array[second]) {\\n return -1;\\n }\\n if (array[first] > array[second]) {\\n return 1;\\n }\\n return 0;\\n }\\n });\\n }\\n\\n public static void orderBy(int[] base, int[]... arrays) {\\n int[] order = ArrayUtils.order(base);\\n order(order, base);\\n for (int[] array : arrays) {\\n order(order, array);\\n }\\n }\\n\\n public static void order(int[] order, int[] array) {\\n int[] tempInt = new int[order.length];\\n for (int i = 0; i < order.length; i++) {\\n tempInt[i] = array[order[i]];\\n }\\n System.arraycopy(tempInt, 0, array, 0, array.length);\\n }\\n\\n }\\n\\n static interface IntCollection extends IntStream {\\n public int size();\\n\\n default public void add(int value) {\\n throw new UnsupportedOperationException();\\n }\\n\\n default public int[] toArray() {\\n int size = size();\\n int[] array = new int[size];\\n int i = 0;\\n for (IntIterator it = intIterator(); it.isValid(); it.advance()) {\\n array[i++] = it.value();\\n }\\n return array;\\n }\\n\\n default public IntCollection addAll(IntStream values) {\\n for (IntIterator it = values.intIterator(); it.isValid(); it.advance()) {\\n add(it.value());\\n }\\n return this;\\n }\\n\\n }\\n\\n static class Sorter {\\n private static final int INSERTION_THRESHOLD = 16;\\n\\n private Sorter() {\\n }\\n\\n public static void sort(IntList list, IntComparator comparator) {\\n quickSort(list, 0, list.size() - 1, (Integer.bitCount(Integer.highestOneBit(list.size()) - 1) * 5) >> 1,\\n comparator);\\n }\\n\\n private static void quickSort(IntList list, int from, int to, int remaining, IntComparator comparator) {\\n if (to - from < INSERTION_THRESHOLD) {\\n insertionSort(list, from, to, comparator);\\n return;\\n }\\n if (remaining == 0) {\\n heapSort(list, from, to, comparator);\\n return;\\n }\\n remaining--;\\n int pivotIndex = (from + to) >> 1;\\n int pivot = list.get(pivotIndex);\\n list.swap(pivotIndex, to);\\n int storeIndex = from;\\n int equalIndex = to;\\n for (int i = from; i < equalIndex; i++) {\\n int value = comparator.compare(list.get(i), pivot);\\n if (value < 0) {\\n list.swap(storeIndex++, i);\\n } else if (value == 0) {\\n list.swap(--equalIndex, i--);\\n }\\n }\\n quickSort(list, from, storeIndex - 1, remaining, comparator);\\n for (int i = equalIndex; i <= to; i++) {\\n list.swap(storeIndex++, i);\\n }\\n quickSort(list, storeIndex, to, remaining, comparator);\\n }\\n\\n private static void heapSort(IntList list, int from, int to, IntComparator comparator) {\\n for (int i = (to + from - 1) >> 1; i >= from; i--) {\\n siftDown(list, i, to, comparator, from);\\n }\\n for (int i = to; i > from; i--) {\\n list.swap(from, i);\\n siftDown(list, from, i - 1, comparator, from);\\n }\\n }\\n\\n private static void siftDown(IntList list, int start, int end, IntComparator comparator, int delta) {\\n int value = list.get(start);\\n while (true) {\\n int child = ((start - delta) << 1) + 1 + delta;\\n if (child > end) {\\n return;\\n }\\n int childValue = list.get(child);\\n if (child + 1 <= end) {\\n int otherValue = list.get(child + 1);\\n if (comparator.compare(otherValue, childValue) > 0) {\\n child++;\\n childValue = otherValue;\\n }\\n }\\n if (comparator.compare(value, childValue) >= 0) {\\n return;\\n }\\n list.swap(start, child);\\n start = child;\\n }\\n }\\n\\n private static void insertionSort(IntList list, int from, int to, IntComparator comparator) {\\n for (int i = from + 1; i <= to; i++) {\\n int value = list.get(i);\\n for (int j = i - 1; j >= from; j--) {\\n if (comparator.compare(list.get(j), value) <= 0) {\\n break;\\n }\\n list.swap(j, j + 1);\\n }\\n }\\n }\\n\\n }\\n\\n static class IntArrayList extends IntAbstractStream implements IntList {\\n private int size;\\n private int[] data;\\n\\n public IntArrayList() {\\n this(3);\\n }\\n\\n public IntArrayList(int capacity) {\\n data = new int[capacity];\\n }\\n\\n public IntArrayList(IntCollection c) {\\n this(c.size());\\n addAll(c);\\n }\\n\\n public IntArrayList(IntStream c) {\\n this();\\n if (c instanceof IntCollection) {\\n ensureCapacity(((IntCollection) c).size());\\n }\\n addAll(c);\\n }\\n\\n public IntArrayList(IntArrayList c) {\\n size = c.size();\\n data = c.data.clone();\\n }\\n\\n public IntArrayList(int[] arr) {\\n size = arr.length;\\n data = arr.clone();\\n }\\n\\n public int size() {\\n return size;\\n }\\n\\n public int get(int at) {\\n if (at >= size) {\\n throw new IndexOutOfBoundsException(\\\"at = \\\" + at + \\\", size = \\\" + size);\\n }\\n return data[at];\\n }\\n\\n private void ensureCapacity(int capacity) {\\n if (data.length >= capacity) {\\n return;\\n }\\n capacity = Math.max(2 * data.length, capacity);\\n data = Arrays.copyOf(data, capacity);\\n }\\n\\n public void addAt(int index, int value) {\\n ensureCapacity(size + 1);\\n if (index > size || index < 0) {\\n throw new IndexOutOfBoundsException(\\\"at = \\\" + index + \\\", size = \\\" + size);\\n }\\n if (index != size) {\\n System.arraycopy(data, index, data, index + 1, size - index);\\n }\\n data[index] = value;\\n size++;\\n }\\n\\n public void removeAt(int index) {\\n if (index >= size || index < 0) {\\n throw new IndexOutOfBoundsException(\\\"at = \\\" + index + \\\", size = \\\" + size);\\n }\\n if (index != size - 1) {\\n System.arraycopy(data, index + 1, data, index, size - index - 1);\\n }\\n size--;\\n }\\n\\n public void set(int index, int value) {\\n if (index >= size) {\\n throw new IndexOutOfBoundsException(\\\"at = \\\" + index + \\\", size = \\\" + size);\\n }\\n data[index] = value;\\n }\\n\\n\\n public int[] toArray() {\\n return Arrays.copyOf(data, size);\\n }\\n\\n }\\n\\n static interface IntReversableCollection extends IntCollection {\\n }\\n\\n static interface IntList extends IntReversableCollection {\\n public abstract int get(int index);\\n\\n public abstract void set(int index, int value);\\n\\n public abstract void addAt(int index, int value);\\n\\n public abstract void removeAt(int index);\\n\\n default public void swap(int first, int second) {\\n if (first == second) {\\n return;\\n }\\n int temp = get(first);\\n set(first, get(second));\\n set(second, temp);\\n }\\n\\n default public IntIterator intIterator() {\\n return new IntIterator() {\\n private int at;\\n private boolean removed;\\n\\n public int value() {\\n if (removed) {\\n throw new IllegalStateException();\\n }\\n return get(at);\\n }\\n\\n public boolean advance() {\\n at++;\\n removed = false;\\n return isValid();\\n }\\n\\n public boolean isValid() {\\n return !removed && at < size();\\n }\\n\\n public void remove() {\\n removeAt(at);\\n at--;\\n removed = true;\\n }\\n };\\n }\\n\\n\\n default public void add(int value) {\\n addAt(size(), value);\\n }\\n\\n default public IntList sort(IntComparator comparator) {\\n Sorter.sort(this, comparator);\\n return this;\\n }\\n\\n default public IntList subList(final int from, final int to) {\\n return new IntList() {\\n private final int shift;\\n private final int size;\\n\\n {\\n if (from < 0 || from > to || to > IntList.this.size()) {\\n throw new IndexOutOfBoundsException(\\\"from = \\\" + from + \\\", to = \\\" + to + \\\", size = \\\" + size());\\n }\\n shift = from;\\n size = to - from;\\n }\\n\\n public int size() {\\n return size;\\n }\\n\\n public int get(int at) {\\n if (at < 0 || at >= size) {\\n throw new IndexOutOfBoundsException(\\\"at = \\\" + at + \\\", size = \\\" + size());\\n }\\n return IntList.this.get(at + shift);\\n }\\n\\n public void addAt(int index, int value) {\\n throw new UnsupportedOperationException();\\n }\\n\\n public void removeAt(int index) {\\n throw new UnsupportedOperationException();\\n }\\n\\n public void set(int at, int value) {\\n if (at < 0 || at >= size) {\\n throw new IndexOutOfBoundsException(\\\"at = \\\" + at + \\\", size = \\\" + size());\\n }\\n IntList.this.set(at + shift, value);\\n }\\n\\n public IntList compute() {\\n return new IntArrayList(this);\\n }\\n };\\n }\\n\\n }\\n\\n static interface IntStream extends Iterable<Integer>, Comparable<IntStream> {\\n public IntIterator intIterator();\\n\\n default public Iterator<Integer> iterator() {\\n return new Iterator<Integer>() {\\n private IntIterator it = intIterator();\\n\\n public boolean hasNext() {\\n return it.isValid();\\n }\\n\\n public Integer next() {\\n int result = it.value();\\n it.advance();\\n return result;\\n }\\n };\\n }\\n\\n default public int compareTo(IntStream c) {\\n IntIterator it = intIterator();\\n IntIterator jt = c.intIterator();\\n while (it.isValid() && jt.isValid()) {\\n int i = it.value();\\n int j = jt.value();\\n if (i < j) {\\n return -1;\\n } else if (i > j) {\\n return 1;\\n }\\n it.advance();\\n jt.advance();\\n }\\n if (it.isValid()) {\\n return 1;\\n }\\n if (jt.isValid()) {\\n return -1;\\n }\\n return 0;\\n }\\n\\n }\\n\\n static abstract class IntAbstractStream implements IntStream {\\n\\n public String toString() {\\n StringBuilder builder = new StringBuilder();\\n boolean first = true;\\n for (IntIterator it = intIterator(); it.isValid(); it.advance()) {\\n if (first) {\\n first = false;\\n } else {\\n builder.append(' ');\\n }\\n builder.append(it.value());\\n }\\n return builder.toString();\\n }\\n\\n\\n public boolean equals(Object o) {\\n if (!(o instanceof IntStream)) {\\n return false;\\n }\\n IntStream c = (IntStream) o;\\n IntIterator it = intIterator();\\n IntIterator jt = c.intIterator();\\n while (it.isValid() && jt.isValid()) {\\n if (it.value() != jt.value()) {\\n return false;\\n }\\n it.advance();\\n jt.advance();\\n }\\n return !it.isValid() && !jt.isValid();\\n }\\n\\n\\n public int hashCode() {\\n int result = 0;\\n for (IntIterator it = intIterator(); it.isValid(); it.advance()) {\\n result *= 31;\\n result += it.value();\\n }\\n return result;\\n }\\n\\n }\\n\\n static class OutputWriter {\\n private final PrintWriter writer;\\n\\n public OutputWriter(OutputStream outputStream) {\\n writer = new PrintWriter(new BufferedWriter(new OutputStreamWriter(outputStream)));\\n }\\n\\n public OutputWriter(Writer writer) {\\n this.writer = new PrintWriter(writer);\\n }\\n\\n public void close() {\\n writer.close();\\n }\\n\\n public void printLine(long i) {\\n writer.println(i);\\n }\\n\\n }\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'maximumPeople' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts following parameters:\\n * 1. LONG_INTEGER_ARRAY p\\n * 2. LONG_INTEGER_ARRAY x\\n * 3. LONG_INTEGER_ARRAY y\\n * 4. LONG_INTEGER_ARRAY r\\n */\\n\\n public static long maximumPeople(List<Long> p, List<Long> x, List<Long> y, List<Long> r) {\\n // Return the maximum number of people that will be in a sunny town after removing exactly one cloud.\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Long> p = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n List<Long> x = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n int m = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Long> y = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n List<Long> r = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Long::parseLong)\\n .collect(toList());\\n\\n long result = Result.maximumPeople(p, x, y, r);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"maximumPeople(p, x, y, r)\"\n ],\n \"solution\": \"from collections import defaultdict\\n\\n\\ndef maximumPeople(towns, cloud_start, cloud_end):\\n towns = sorted(towns)\\n cloud_start = sorted(cloud_start)\\n cloud_end = sorted(cloud_end)\\n\\n cloud_start_i = 0\\n cloud_end_i = 0\\n clouds = set()\\n\\n d = defaultdict(int)\\n free = 0\\n for town_i in range(len(towns)):\\n town_x = towns[town_i][0]\\n while cloud_start_i < len(cloud_start) and cloud_start[cloud_start_i][0] <= town_x:\\n clouds.add(cloud_start[cloud_start_i][1])\\n cloud_start_i += 1\\n while cloud_end_i < len(cloud_end) and cloud_end[cloud_end_i][0] < town_x:\\n clouds.remove(cloud_end[cloud_end_i][1])\\n cloud_end_i += 1\\n if len(clouds) == 1:\\n towns[town_i][2] = list(clouds)[0]\\n d[list(clouds)[0]] += towns[town_i][1]\\n elif len(clouds) == 0:\\n free += towns[town_i][1]\\n\\n return max(d.values(), default=0) + free\\n\\n\\ndef main():\\n n = int(input().strip())\\n p = [int(x) for x in input().strip().split()]\\n x = [int(x) for x in input().strip().split()]\\n towns = [[xi, pi, -1] for xi, pi in zip(x, p)]\\n m = int(input().strip())\\n y = [int(x) for x in input().strip().split()]\\n r = [int(x) for x in input().strip().split()]\\n cloud_start = [[y[i]-r[i], i] for i in range(m)]\\n cloud_end = [[y[i]+r[i], i] for i in range(m)]\\n result = maximumPeople(towns, cloud_start, cloud_end)\\n print(result)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\\n\\\"\\\"\\\"\\n2\\n10 100\\n5 100\\n1\\n20\\n1\\n\\\"\\\"\\\"\",\n \"template\": \"#\\n# Complete the 'maximumPeople' function below.\\n#\\n# The function is expected to return a LONG_INTEGER.\\n# The function accepts following parameters:\\n# 1. LONG_INTEGER_ARRAY p\\n# 2. LONG_INTEGER_ARRAY x\\n# 3. LONG_INTEGER_ARRAY y\\n# 4. LONG_INTEGER_ARRAY r\\n#\\n\\ndef maximumPeople(p, x, y, r):\\n # Return the maximum number of people that will be in a sunny town after removing exactly one cloud.\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n n = int(input().strip())\\n\\n p = list(map(int, input().rstrip().split()))\\n\\n x = list(map(int, input().rstrip().split()))\\n\\n m = int(input().strip())\\n\\n y = list(map(int, input().rstrip().split()))\\n\\n r = list(map(int, input().rstrip().split()))\\n\\n result = maximumPeople(p, x, y, r)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":276,"cells":{"question_id":{"kind":"number","value":22923,"string":"22,923"},"question_title":{"kind":"string","value":"Flipping the Matrix"},"question_content":{"kind":"string","value":"Sean invented a game involving a $2n \\times 2n$ matrix where each cell of the matrix contains an integer. He can reverse any of its rows or columns any number of times. The goal of the game is to maximize the sum of the elements in the $n \\times n$ submatrix located in the upper-left quadrant of the matrix.\n\nGiven the initial configurations for $q$ matrices, help Sean reverse the rows and columns of each matrix in the best possible way so that the sum of the elements in the matrix's upper-left quadrant is maximal. \n\n**Example** \n$matrix = [[1, 2], [3, 4]]$ \n\n```\n1 2\n3 4\n```\nIt is $2 \\times 2$ and we want to maximize the top left quadrant, a $1 \\times 1$ matrix. Reverse row $1$:\n```\n1 2\n4 3\n```\nAnd now reverse column $0$:\n```\n4 2\n1 3\n```\nThe maximal sum is $4$.\n\n**Function Description** \n\nComplete the *flippingMatrix* function in the editor below. \n\nflippingMatrix has the following parameters: \n- *int matrix[2n][2n]:* a 2-dimensional array of integers \n\n**Returns** \n- *int:* the maximum sum possible. "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int flippingMatrix(List<List<Integer>> matrix)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args)throws IOException {\\n BufferedReader in=new BufferedReader(new InputStreamReader(System.in));\\n int t=Integer.parseInt(in.readLine());\\n for(int t1=0;t1<t;t1++){\\n int n=Integer.parseInt(in.readLine());\\n String[][] s=new String[2*n][2*n];\\n for(int i=0;i<2*n;i++)\\n s[i]=in.readLine().split(\\\" \\\");\\n long sum=0;\\n for(int i=0;i<n;i++){\\n for(int j=0;j<n;j++){\\n sum+=Math.max(Math.max(Integer.parseInt(s[i][j]),Integer.parseInt(s[2*n-1-i][j])),\\n Math.max(Integer.parseInt(s[i][2*n-1-j]),Integer.parseInt(s[2*n-1-i][2*n-1-j])));\\n }\\n }\\n System.out.println(sum);\\n }\\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'flippingMatrix' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY matrix as parameter.\\n */\\n\\n public static int flippingMatrix(List<List<Integer>> matrix) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int qItr = 0; qItr < q; qItr++) {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> matrix = new ArrayList<>();\\n\\n for (int i = 0; i < 2 * n; i++) {\\n String[] matrixRowTempItems = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> matrixRowItems = new ArrayList<>();\\n\\n for (int j = 0; j < 2 * n; j++) {\\n int matrixItem = Integer.parseInt(matrixRowTempItems[j]);\\n matrixRowItems.add(matrixItem);\\n }\\n\\n matrix.add(matrixRowItems);\\n }\\n\\n int result = Result.flippingMatrix(matrix);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner sc=new Scanner(System.in);\\n int t=sc.nextInt();\\n while(t--!=0){\\n int n=sc.nextInt();\\n int a[][]=new int[2*n][2*n];\\n int b[][]=new int[2*n][2*n];\\n for(int i=0;i<2*n;i++){\\n for(int j=0;j<2*n;j++){\\n a[i][j]=sc.nextInt();\\n b[i][j]=a[i][j];\\n }\\n }\\n int sum=0,t1;\\n for(int i=0;i<n;i++){\\n for(int j=0;j<n;j++){\\n t1=Math.max(Math.max(a[i][j],a[2*n-1-i][j]),Math.max(a[i][2*n-1-j],a[2*n-1-i][2*n-1-j]));\\n //System.out.println(t1);\\n sum+=t1;\\n }\\n }\\n System.out.println(sum);\\n }\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'flippingMatrix' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY matrix as parameter.\\n */\\n\\n public static int flippingMatrix(List<List<Integer>> matrix) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> matrix = new ArrayList<>();\\n\\n IntStream.range(0, 2 * n).forEach(i -> {\\n try {\\n matrix.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.flippingMatrix(matrix);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class C {\\n\\tInputStream is;\\n\\tPrintWriter out;\\n\\tString INPUT = \\\"\\\";\\n\\t\\n\\tvoid solve()\\n\\t{\\n\\t\\tfor(int T = ni();T > 0;T--){\\n\\t\\t\\tint n = ni();\\n\\t\\t\\tint[][] a = new int[2*n][];\\n\\t\\t\\tfor(int i = 0;i < 2*n;i++){\\n\\t\\t\\t\\ta[i] = na(2*n);\\n\\t\\t\\t}\\n\\t\\t\\tlong ret = 0;\\n\\t\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\t\\tfor(int j = 0;j < n;j++){\\n\\t\\t\\t\\t\\tlong max = 0;\\n\\t\\t\\t\\t\\tmax = Math.max(max, a[i][j]);\\n\\t\\t\\t\\t\\tmax = Math.max(max, a[2*n-1-i][j]);\\n\\t\\t\\t\\t\\tmax = Math.max(max, a[2*n-1-i][2*n-1-j]);\\n\\t\\t\\t\\t\\tmax = Math.max(max, a[i][2*n-1-j]);\\n\\t\\t\\t\\t\\tret += max;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tout.println(ret);\\n\\t\\t}\\n\\t}\\n\\t\\n\\tvoid run() throws Exception\\n\\t{\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tlong s = System.currentTimeMillis();\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tif(!INPUT.isEmpty())tr(System.currentTimeMillis()-s+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception { new C().run(); }\\n\\t\\n\\tprivate byte[] inbuf = new byte[1024];\\n\\tprivate int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate double nd() { return Double.parseDouble(ns()); }\\n\\tprivate char nc() { return (char)skip(); }\\n\\t\\n\\tprivate String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'flippingMatrix' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY matrix as parameter.\\n */\\n\\n public static int flippingMatrix(List<List<Integer>> matrix) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> matrix = new ArrayList<>();\\n\\n IntStream.range(0, 2 * n).forEach(i -> {\\n try {\\n matrix.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.flippingMatrix(matrix);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"flippingMatrix(matrix)\"\n ],\n \"solution\": \"q = int(input())\\nwhile q > 0:\\n q -= 1\\n \\n n = int(input())\\n A = []\\n for i in range(2 * n):\\n A += [list(map(int, input().split()))]\\n \\n ans = 0\\n for i in range(n):\\n for j in range(n):\\n ans += max(A[i][j], A[2 * n - 1 - i][j], A[i][2 * n - 1 - j], A[2 * n - 1 - i][2 * n - 1 - j])\\n \\n print(ans)\",\n \"template\": \"#\\n# Complete the 'flippingMatrix' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts 2D_INTEGER_ARRAY matrix as parameter.\\n#\\n\\ndef flippingMatrix(matrix):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n q = int(input().strip())\\n\\n for q_itr in range(q):\\n n = int(input().strip())\\n\\n matrix = []\\n\\n for _ in range(2 * n):\\n matrix.append(list(map(int, input().rstrip().split())))\\n\\n result = flippingMatrix(matrix)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":277,"cells":{"question_id":{"kind":"number","value":28615,"string":"28,615"},"question_title":{"kind":"string","value":"Gaming Array"},"question_content":{"kind":"string","value":"Andy wants to play a game with his little brother, Bob. The game starts with an array of distinct integers and the rules are as follows:\n\n- Bob always plays first. \n- In a single move, a player chooses the maximum element in the array. He removes it and all elements to its right. For example, if the starting array $arr = [2, 3, 5, 4, 1]$, then it becomes $arr' = [2, 3]$ after removing $[5, 4, 1]$. \n- The two players alternate turns. \n- The last player who can make a move wins. \n\nAndy and Bob play $g$ games. Given the initial array for each game, find and print the name of the winner on a new line. If Andy wins, print `ANDY`; if Bob wins, print `BOB`.\n\nTo continue the example above, in the next move Andy will remove $3$. Bob will then remove $2$ and win because there are no more integers to remove. \n\n**Function Description** \n\nComplete the *gamingArray* function in the editor below. \n\ngamingArray has the following parameter(s): \n\n- *int arr[n]:* an array of integers \n\n**Returns** \n- *string:* either `ANDY` or `BOB` "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static String gamingArray(List<Integer> arr)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.math.BigInteger;\\nimport java.util.*;\\n\\n\\n\\npublic class B\\n{\\n String line;\\n StringTokenizer inputParser;\\n BufferedReader is;\\n FileInputStream fstream;\\n DataInputStream in;\\n String FInput=\\\"\\\";\\n \\n void openInput(String file)\\n {\\n\\n if(file==null)is = new BufferedReader(new InputStreamReader(System.in));//stdin\\n else\\n {\\n try{\\n \\n \\n fstream = new FileInputStream(file);\\n in = new DataInputStream(fstream);\\n is = new BufferedReader(new InputStreamReader(in));\\n }catch(Exception e)\\n {\\n System.err.println(e);\\n }\\n }\\n\\n }\\n \\n void readNextLine()\\n\\t{\\n\\t\\ttry {\\n\\t\\t\\tline = is.readLine();\\n\\t\\t\\tinputParser = new StringTokenizer(line, \\\" ,\\\\t\\\");\\n\\t\\t\\t//System.err.println(\\\"Input: \\\" + line);\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\tSystem.err.println(\\\"Unexpected IO ERROR: \\\" + e);\\n\\t\\t}\\t\\n\\t\\tcatch (NullPointerException e)\\n\\t\\t{\\n\\t\\t\\tline=null;\\n\\t\\t\\t\\n\\t\\t}\\n\\t\\t\\n\\t}\\n \\n long NextLong()\\n {\\n String n = inputParser.nextToken();\\n \\n long val = Long.parseLong(n);\\n \\n return val;\\n }\\n \\n int NextInt()\\n {\\n String n = inputParser.nextToken();\\n int val = Integer.parseInt(n);\\n \\n //System.out.println(\\\"I read this number: \\\" + val);\\n return val;\\n }\\n \\n double NextDouble()\\n {\\n String n = inputParser.nextToken();\\n double val = Double.parseDouble(n);\\n \\n //System.out.println(\\\"I read this number: \\\" + val);\\n return val;\\n }\\n \\n String NextString()\\n {\\n String n = inputParser.nextToken();\\n return n;\\n }\\n \\n void closeInput()\\n {\\n try {\\n is.close();\\n } catch (IOException e) {\\n System.err.println(\\\"Unexpected IO ERROR: \\\" + e);\\n }\\n \\n }\\n \\n public static void main(String [] argv)\\n {\\n //String filePath=\\\"circles.in\\\";\\n String filePath=null;\\n if(argv.length>0)filePath=argv[0];\\n new B(filePath);\\n \\n }\\n \\n public B(String inputFile)\\n {\\n \\topenInput(inputFile);\\n\\t\\treadNextLine();\\n\\t\\tint T=NextInt();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\tfor(int t=1; t<=T; t++)\\n\\t\\t{\\n\\t\\t\\treadNextLine();\\n\\t\\t\\tint N=NextInt();\\n\\t\\t\\treadNextLine();\\n\\t\\t\\tInteger [] a = new Integer[N];\\n\\t\\t\\tfor(int i=0; i<N; i++)\\n\\t\\t\\t{\\n\\t\\t\\t\\ta[i] = NextInt();\\n\\t\\t\\t}\\n\\t\\t\\tint max = -1;\\n\\t\\t\\tint c = 0;\\n\\t\\t\\tfor(int i=0; i<N; i++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tif(a[i]>max)\\n\\t\\t\\t\\t{\\n\\t\\t\\t\\t\\tmax = a[i];\\n\\t\\t\\t\\t\\tc++;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tsb.append(c%2==0?\\\"ANDY\\\\n\\\":\\\"BOB\\\\n\\\");\\n\\t\\t}\\n\\t\\tSystem.out.print(sb);\\n\\t\\t\\n\\t\\tcloseInput();\\t\\t\\n\\t}\\n\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'gamingArray' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static String gamingArray(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int g = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int gItr = 0; gItr < g; gItr++) {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] arrTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> arr = new ArrayList<>();\\n\\n for (int i = 0; i < arrCount; i++) {\\n int arrItem = Integer.parseInt(arrTemp[i]);\\n arr.add(arrItem);\\n }\\n\\n String result = Result.gamingArray(arr);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.util.*;\\npublic class GamingArray {\\n public static void main(String[] args) {\\n Scanner sc = new Scanner(System.in);\\n int g = sc.nextInt();\\n for(int tst=0;tst<g;tst++) {\\n int n = sc.nextInt();\\n int count = 0;\\n int max = 0;\\n for (int i = 0; i < n; i++) {\\n int number = sc.nextInt();\\n if (max < number) {\\n max = number;\\n count++;\\n }\\n }\\n System.out.println(count % 2 == 0 ? \\\"ANDY\\\" : \\\"BOB\\\");\\n }\\n sc.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'gamingArray' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static String gamingArray(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int g = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, g).forEach(gItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n String result = Result.gamingArray(arr);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"\\nimport java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class A {\\n\\tInputStream is;\\n\\tPrintWriter out;\\n\\tString INPUT = \\\"\\\";\\n\\t\\n\\tvoid solve()\\n\\t{\\n\\t\\tfor(int T= ni();T > 0;T--){\\n\\t\\t\\tint n = ni();\\n\\t\\t\\tint[] a = na(n);\\n\\t\\t\\tint pre = -1;\\n\\t\\t\\tint ct = 0;\\n\\t\\t\\tfor(int v : a){\\n\\t\\t\\t\\tif(pre < v){\\n\\t\\t\\t\\t\\tct++;\\n\\t\\t\\t\\t\\tpre = v;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tout.println(ct % 2 == 0 ? \\\"ANDY\\\" : \\\"BOB\\\");\\n\\t\\t}\\n\\t}\\n\\t\\n\\tvoid run() throws Exception\\n\\t{\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tlong s = System.currentTimeMillis();\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tif(!INPUT.isEmpty())tr(System.currentTimeMillis()-s+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception { new A().run(); }\\n\\t\\n\\tprivate byte[] inbuf = new byte[1024];\\n\\tpublic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate double nd() { return Double.parseDouble(ns()); }\\n\\tprivate char nc() { return (char)skip(); }\\n\\t\\n\\tprivate String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'gamingArray' function below.\\n *\\n * The function is expected to return a STRING.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static String gamingArray(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int g = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, g).forEach(gItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n String result = Result.gamingArray(arr);\\n\\n bufferedWriter.write(result);\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"gamingArray(arr)\"\n ],\n \"solution\": \"#!/bin/python3\\n\\nimport sys\\n\\n\\ng = int(input().strip())\\nfor a0 in range(g):\\n n = int(input().strip())\\n a = list(map(int, input().split()))\\n \\n idx_sorted = [x for x,y in sorted(enumerate(a), key = lambda x: -x[1])]\\n #print(a, idx_sorted)\\n \\n max_idx = n\\n bob_wins = False\\n for i in range(n):\\n idx = idx_sorted[i]\\n if idx < max_idx:\\n #print(idx)\\n max_idx = idx\\n bob_wins = not bob_wins\\n \\n if bob_wins:\\n print('BOB')\\n else:\\n print('ANDY')\\n \\n \",\n \"template\": \"#\\n# Complete the 'gamingArray' function below.\\n#\\n# The function is expected to return a STRING.\\n# The function accepts INTEGER_ARRAY arr as parameter.\\n#\\n\\ndef gamingArray(arr):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n g = int(input().strip())\\n\\n for g_itr in range(g):\\n arr_count = int(input().strip())\\n\\n arr = list(map(int, input().rstrip().split()))\\n\\n result = gamingArray(arr)\\n\\n fptr.write(result + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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9f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r29e3r29e3r29f376+fX37+vb17evb17evb1/fvr59ffv69vXt69vXt69vX9++vn19+/r28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vHt49vHt49vH98+vn18+/j28e3j28e3j28f3z6+fXz7+Pbx7ePbx7ePbx/fPr59fPv49vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/b27e3b27e3b2/f3r69fXv79vbt7dvbt7dvb9/evr19e/v29u3t29u3t29v396+vX17+/by7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n28u3l28u3l28v316+vXx7+fby7eXby7eXby/fXr69fHv59vLt5dvLt5dvL99evr18e/n29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vTt6dvTt6dvT9+evj19e/r29O3p29O3p29P356+PX17+vb07enb07enb0/fnr49fXv69vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+Pbw7eHbw7eHbw/fHr49fHv49vDt4dvDt4dvD98evj18e/j28O3h28O3h28P3x6+PXx7+PbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98++fbP9/++fbPt3++/fPtn2//fPvn2z/f/vn2z7d/vv3z7Z9v/3z759s/3/759s+3f7798+2fb/98+8+BfdAADMMAAKNULacJf2KTaxg+79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79vO+/bxvP+/bz/v28779vG8/79vP+/bzvv28bz/v28/79uPbV7evbV/Zvq59Vfua9hXt69lXs69lX8m+jn0V+xr2Fezr11evr11fub5ufdX6mvUV6+vVV6uvVV+pvk59lfoa9RXq69NXp69NX5m+Ln1V+pr0Fenr0Vejr0Vfib4OfRX6GvQV6OvPV5+vPV95vu581fma8xXn681Xm681X2m+znyV+RrzFebry1eXry1fWb6ufFX5mvIV5evJV5OvJV9Jvo58Ffka8hXk68dXj68dXzm+bnzV+JrxFePrxVeLrxVfKb5OfJX4GvEV4uvDV4evDV8Zvi58Vfia8BXh68FXg68FXwm+DnwV+BrwFeDrv1d/r/1e+b3ue9X3mu8V3+u9V3uv9V7pvc57lfca7xXe67tXd6/tXtm9rntV95ruFd3ruVdzr+Veyb2OexX3Gu4V3Ou3V2+v3V65vW571faa7RXb67VXa6/VXqm9TnuV9hrtFdrrs1dnr81emb0ue1X2muwV2euxV2OvxV6JvQ57FfYa7BXY669XX6+9Xnm97nrV9ZrrFdfrrVdbr7Veab3OepX1GusV1uurV1evrV5Zva56VfWa6hXV66lXU6+lXkm9jnoV9RrqFdTrp1dPr51eOb1uetX0mukV0+ulV0uvlV4pvU56lfQa6RXS66NXR6+NXhm9LnpV9JroFdHroVdDr4VeCb0OehX0GugV0OufVz+vfV75vO551fOa5xXP651XO691Xum8znmV8xrnFc7rm1c3r21e2byueVXzmuYVzeuZVzOvZV7JvI55FfMa5hXM65dXL69dXrm8bnnV8prlFcvrlVcrr1VeqbxOeZXyGuUVyuuTVyevTV6ZvC55VfKa5BXJ65FXI69FXom8DnkV8hrkFcjrj1cfrz1eebzueNXxmuMVx+uNVxuvNV5pvM54lfEa4xXG64tXF68tXlm8rnhV8ZriFcXriVcTryVeSbyOeBXxGuIVxOuHVw+vHV45vG541fCa4RXD64VXC68VXim8TniV8BrhFcLrg1cHrw1eGbwueFXwmuAVweuBVwOvBV4JvA54FfAa4BXA639X/679Xfm77nfV75rfFb/rfVf7rvVd6bvOd5XvGt8Vvut7V/eu7V3Zu653Ve+a3hW963lX867lXcm7jncV7xreFbzrd1fvrt1dubtud9Xumt0Vu+t1V+uu1V2pu053le4a3RW663NX567NXZm7LndV7prcFbnrcVfjrsVdibsOdxXuGtwVuOtvV9+uvV15u+521e2a2xW3621X2661XWm7znaV7RrbFbbra1fXrq1dWbuudlXtmtoVtetpV9OupV1Ju452Fe0a2hW062dXz66dXTm7bnbV7JrZFbPrZVfLrpVdKbtOdpXsGtkVsutjV8eujV0Zuy52Veya2BWx62FXw66FXQm7DnYV7BrYFbDrX1e/rn1d+bruddXrmtcVr+tdV7uudV3pus51lesa1xWu61tXt65tXdm6rnVV65rWFa3rWVezrmVdybqOdRXrGtYVrOtXV6+uXV25um511eqa1RWr61VXq65VXam6TnWV6hrVFarrU1enrk1dmboudVXqmtQVqetRV6OuRV2Jug51Feoa1BWo609Xn649XXm67nTV6ZrTFafrTVebrjVdabrOdJXpGtMVputLV5euLV1Zuq50Vema0hWl60lXk64lXUm6jnQV6RrSFaTrR1ePrh1dObpudNXomtEVo+tFV4uuFV0puk50lega0RWi60NXh64NXRm6LnRV6JrQFaHrQVeDrgVdCboOdBXoGtAVoOs/V3+u/Vz5ue5z1eeazxWf6z1Xe671XOm5znOV5xrPFZ7rO1d3ru1c2bmuc1Xnms4Vnes5V3Ou5VzJuY5zFecazhWc6zdXb67dXLm5bnPV5prNFZvrNVdrrtVcqblOc5XmGs0VmuszV2euzVyZuS5zVeaazBWZ6zFXY67FXIm5DnMV5hrMFZjrL1dfrr1cebnuctXlmssVl+stV1uutVxpuc5yleUayxWW6ytXV66tXFm5rnJV5ZrKFZXrKVdTrqVcSbmOchXlGsoVlOsnV0+unVw5uW5y1eSayRWT6yVXS66VXCm5TnKV5BrJFZLrI1dHro1cGbkuclXkmsgVkeshV0OuhVwJuQ5yFeQayBWQ6x9XP659XPm47nHV45rHFY/rHVc7rnVc6bjOcZXjGscVjusbVzeubVzZuK5xVeOaxhWN6xlXM65lXMm4jnEV4xrGFYzrF1cvrl1cubhucdXimsUVi+sVVyuuVVypuE5xleIaxRWK6xNXJ65NXJm4LnFV4prEFYnrEVcjrkVcibgOcRXiGsQViOsPVx+uPVx5uO5w1eGawxWH6w1XG641XGm4znCV4RrDFYbrC1cXri1cWbiucFXhmsIVhesJVxOuJVxJuI5wFeEawhWE6wdXD64dXDm4bnDV4JrBFYPrBVcLrhVcKbhOcJXgGsEVgusDVweuDVwZuC5wVeCawBWB6wFXA64FXAm4DnAV4BrAFYDr/1b/rf1b+bfub9Xfmr8Vf+v9Vvut9Vvpt85vld8avxV+6/tW963tW9m3rm9V35q+FX3r+VbzreVbybeObxXfGr4VfOv3Vu+t3Vu5t25v1d6avRV76/VW663VW6m3Tm+V3hq9FXrr81bnrc1bmbcub1XemrwVeevxVuOtxVuJtw5vFd4avBV46+9W3629W3m37m7V3Zq7FXfr7VbbrbVbabfObpXdGrsVduvrVtetrVtZt65uVd2auhV16+lW062lW0m3jm4V3Rq6FXTr51bPrZ1bObdubtXcmrkVc+vlVsutlVspt05uldwauRVy6+NWx62NWxm3Lm5V3Jq4FXHr4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+HGw42HGw83Hm483Hi48XDj4cbDjYcbDzcebjzceLjxcOPhxsONhxsPNx5uPNx4uPFw4+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Guh7se7nq46+Haw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3h2sO1h2sP1x6uPVx7uPZw7eHaw7WHaw/XHq49XHu49nDt4drDtYdrD9cerj1ce7j2cO3hysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4crDlYcrD1cerjxcebjycOXhysOVhysPVx6uPFx5uPJw5eHKw5WHKw9XHq48XHm48nDl4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHSw6WHSw+XHi49XHq49HDp4dLDpYdLD5ceLj1cerj0cOnh0sOlh0sPlx4uPVx6uPRw6eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhwsOFhwsPFx4uPFx4uPBw4eHCw4WHCw8XHi48XHi48HDh4cLDhYcLDxceLjxceLjwcOHhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u83Cfh/s83OfhPg/3ebjPw30e7vNwn4f7PNzn4T4P93m4z8N9Hu7zcJ+H+zzc5+E+D/d5uM/DfR7u+4k7e977lSWtfhXrxhO4ynZ3mYwRMcRIRyKACUgOEwwSEuK7s9d6fAViZniJuLra+p3997bb/VJdvbr6KThcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4hsM1HK7hcA2Hazhcw+EaDtdwuIbDNRyu4XANh2s4XMPhGg7XcLiGwzUcruFwDYdrOFzD4RoO13C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcLiCwxUcruBwBYcrOFzB4QoOV3C4gsMVHK7gcAWHKzhcweEKDldwuILDFRyu4HAFhys4XMHhCg5XcDgwHBQOCAeDA8FB4ABw8DfwG/QN+AZ7A71B3gBvcDewG9QN6AZzA7lB3ABu8DZwG7QN2AZrA7VB2gBtcDYwG5QNyAZjA7FB2ABs8DXwGnQNuAZbA61B1gBrcDWwGlQNqAZTA6lB1ABq8DRwGjQNmAZLA6VB0gBpcDQwGhQNiAZDA6FB0ABo8DPwGfQMeAY7A51BzgBncDOwGdQMaAYzA5lBzABm8DJwGbQMWAYrA5VBygBlcDIwGZQMSAYjA5FByABk8DHwGHQMOAYbA41BxgBjcDGwGFQMKAYTA4lBxABi8DBwGDQMGAYLA4VBwgBhcDAwGBQMCAYDA4FBwABg8C/wF/QL+AX7An1BvgBfcC+wF9QL6AXzAnlBvABe8C5wF7QL2AXrAnVBugBdcC4wF5QLyAXjAnFBuABc8C3wFnQLuAXbAm1BtgBbcC2wFlQLqAXTAmlBtABa8CxwFjQLmAXLAmVBsgBZcCwwFhQLiAXDAmFBsABY8CvwFfQKeAW7Al1BrgBXcCuwFdQKaAWzAllBrABW8CpwFbQKWAWrAlVBqgBVcCowFZQKSAWjAlFBqABU8CnwFHQKOAWbAk1BpgBTcCmwFFQKKAWTAklBpABS8ChwFDQKGAWLAkVBogBRcCgwFBQKCAWDAkFBoABQ8CfwE/QJ+AR7Aj1ts7yTgN3s9iSjJ708CeNJAU9Sd9K0k3idVOokRyfdOQnMSUlOknHShpMInNTeJOsm/TYJtUmRTdJr0liTmJpU0ySPJh30sZPf+TADqMmdzYl8mP3TxM7mET7M/JkEv4dpP83ua1Lcw5SfZvY1kexhus9keD3M9Wl6V7OiHub5NLWruUeP5Pg0xeeRBJ9m0jyS3dOElYepPc3yaFrIw7SeZng0leJhSk8z/Zmw8DCdp1n+TPJ3mMrTDH8mxjtM42mmN9PPHabwTJa3w/ydpngzl9ph7k5TfZl/7DBvZ9J8HSbtNN+TybQOE3aa68kEVIfJOpPn6TBTpwl/zKZ0mKXTZD9mIDrM0JlEP4dpAczyYzqdw5QAZvgxBc1hOgAzvZjo5TAVgFleTI5ymAbADC8mFDlMAZBMH4f6/6b5MDvGofa/KT7MQXGo+59UD4ei/+Z5MD3CoeC/ev8mITgi9q/W/xGlfyX1j8j8q3V/qPGv3Lv68If6/kq9q6l+qO2v5LfK5Ye6/sp9q/Z9qOmv1Lea2od6/ko+q0N9qOUfuedDIX91fxVVPhTxV/NXIeJDAf/o/R6q9yv8qqruoXK/oq8q0R6q9kfw9VAqTLVXZVUPZcJUelWK9FAiTMVPBT8P5cFU+1Qk81AaTKVPhSUPZcGi+HioCabcoyqJh3pgSj2qRXioBRbJv0MhMPX+lMk7FAFT900xukMBsGi+Hap/KfimTtoR5S8FzI7IfqkTdkTzSzmuI4Jf6mQdqn0p/KS21HFH9elQ50vJJ7WVDjW+lP5Rj+hQ3yuyP4fiXuq/KK5zKOyl9ouCNIeiXtF9OVT0UgBEdZVDNS/FP1QkOVTyivDH4fFBVT+U1zg8Oqjih5IUh8cGVX5Q+OHwyKCqD4olHB4XVPFBgYHDo4I5+X94TtBj/56WPzwj6JF/z6Qfng/M0e/Dw4Ge+/a49OHBQM//eij58FBgzv4engj04K/nZQ9PA3oA1FOphycBc/jz8BigJz89MHnkCKAnGY+c//PA4JHDf57LOzz55yEwT78dnvrzAJgnxg5P/Hn4y3NZh6f9PATkWabDk34eAPL8z+EpPw+CeMrm8ISfh0A8mXJ4ui8HQA5Dijz94TGLw3AiT354NOEwlMgTAB4AOAwjMvrfoPnDECIj/w00PwwfSgT4YeyQ4d9GTR/GDRn6bWzyYcxQQoAPA4aM/zVs9jBYyDhQg1MPA4USA3oYJWQAqHGThxFCBgIanXgYHZQgwMPQICMADZw7DAsyEszwtMOQoESBHcYDGQJmrNWRWCBDmo4EAhk5dCQKyACdwxAgo0EMgzkM/zESxNCRw9AfIwIM0DgM+zEawKCGw5AfIwEMBDjEDEYBuN1+iBiMAHCL+hAvuBPsRvAhWnAX2M3TQ6zgDrAbjodIITuBhzzBbUB3zw5ZgluA7lEdcoRsBR1CBPeB3D45BAjuB7hJcQgPshdwSA7cCJCfH1IDgbCU+pAYBAYf4gJJsAD1EBVIBMWUh5ggNPCQEYgCZW6HfEAkJKc6ZAPBQYdgQC4gdDkCBWQbR4iACOEIDnBtf8gCXBa6Hj7kAC4JXUOyIDxYDrJ6O1gLsoQ6WAiyjjlYdbDoOFhy4PkfrDdwvw8WG/jKh57tgV+Le3ng1OLjHXhQOGSH7tNh1uTDTKqH2RUPM64dZmE6zMxymK3hUMH9UNX5UOn1cCI4VIQ7VIk6VI45VJM4PGF+eOr08CTa4emUw4j1wyjWwy59GO1yuAN+uCt2SMoP6dnhivr4ve7xK/Dxe+Tx+9HhkTAPDf7+95e/Of7yd//l7//u3//D3/2Hf/ef/vM//P1//oe//IvjL3/7b/72jz//8t/+5vivf/mPf37f1R9/Pucff/7/KrT6qNbdth5xJf6Z0v/Lf/2v/u0/Kv7+48/fGP7jz62cw1adYSuxsD33vlVQ2J7/3p4q30oYbPUUthoJWzWG7an8rZjBVnNgKw2wPUS/PZq/1YbYSi5sj8pvj7VvT5pvj+BvRRC2h9y32gpbpYjtCfWt6MNW3GF7iH6rtbA9Lb89jb89Tb89HL8927/VhtjKEmzlJbYn+Ldn3bfSE9sD8Vs1gq1GxFYLYqt8sBWM2J7Y356k38pKbKUJtsoAW2WErf7AVplgq0qwlTTYnsTfClRstQK2AgdbCYetWMRWIGCrfrBVttiqRmwFM7aiBttj+Nsj/dsT/1s9jq3gwPYI/1aZYStFsZV+2KpobLUCtuoPWzWNrcDAVrhjq+ax1QTY6gts9Ti22hRbQYitVsdWi2GrMbGVvthqZGw1H7YyG1tJh600x1ZqYqv5sJWn2MoebKVDtsIRW4GNrWjBVgVhK5uxlaTYyjhsJUS2IgZbSZCt8sRWF2ErzbCVatgKO2xlNLaCE1utja3+w1atZCuosVWJ2GpobGUUtiInW8WGrZ7FVnVjq8OwFdrYapts5UG2khpbmYet4MVWuWMr3bFVMtnKfWw1VLZyEVsRiq2Ux1bzYyt3stX12ApsbKUttooRW7mJrUjJVn1kq1qyVcjYyjRsFUi2+iJbrY2tTMZWwmOr9bFVp9iKPmw1P7Z6EFv5ia3CyVYHYyu2sRWj2CpobMUltnoeW5WVrYbKVu5lq/KyVTzZSo9sBVK2Ii9bRY2teMpWFGYrJ7IVW9kqZWwlOrYqJls1kK0CyVY8ZKvYsRUN2UqWbJVKtuooW8mKrcYJV95/tWwjqJhgG8DA7/Pxb0bBiCCGRS//6vfcf8QUIxQZMAF/X97Hf339nlaeJRgCNXHl7d34Rsgz4pkRKI1IZQKVxE8jFBrQA3fI/S0hfWnAD/ztU3ivATBQksfr/Xv73Mfr/VuANaKtARJQQkslrFoirP090fcty3Ba2lfI9fjEtn58IgDi9/mm/NbA8jN1WP52+ffl995TDDUColmWaqVU5d8rdWUZLt8ibbFyjfUf8ObbBcCJpkagNCAVrk8NWMNpkTul9b3af7381eUd8qsr988dUlpLcqZdvJu9YucO2ys7JfTvyrPSFl5/e/8rrZbyeM/t9ztvYaleWyH1nGssiXBvRH4DJKKc6Q95l7S41/hGK1da55M+/Fjnabv8VoApBhwB3ez0z20NPJbEO4O5+N57ptUq9ZA+bznvlMTfVq73/j4XwMU7+k37mbr67uCz7rS1nxkRacH0/50RmlZLL/XOGTXpFZ1v8ukTyztfGen+9s3bpc9nJGaM5A4Z3V7pCF2Ox5WePGk7f1u5JiW3DPaBHRtiD1/Ww7Jul60v+B2R6ezUyZmRmNqznI7flT5jPS+tzU4rZIxc+cz1+fwZtd967I8/lxr5yywKy3QGSyn+pVj+MivBUnl/mZZhmU1gmeRgmcthKZy/zA+w1Pxfpk9YZk1YpiVYphVYZpBYJjlYivsvU1YsMyMs00gsk2css04sk1cstfaXsvvLnBHLdADLvAvLnAbLjAXL/BXLXATLlAvLlA7L/BfLvADLNATL3AnLxAHLfAZL0f9lSoRl4otlyo5lto1lXopl6ollSoNl+otlQoRlDo9lApBlAo9lJoNl1pBl8ox1B90+3gcEukz6sUyFscx2scw+sExmsUx4sczTsMyosczTscw1ssyJscymsMyKscxmsExssMxmscyNsExQsswGsUxnsMzzsMxksUxHse7g5O03YNJlhoVlHpJl5pFlPpNl5o9ldpBlioVl3o9lJpJlOpFl5oRl+ohl3o9l4oplxodl0o5lKpVlEpNlrodlOod1B3g/lkc4bdqNZcaMZdqVZYaTZZaMZYaRZXaMZdKTZWaQZUaMZUKKZQKXZdqLZeqOZb6RZW6VZY6NZRKVZT6LZUqSZaKTZU6RZeKSZa6TZVaQZVKOZQ6VZUKXZR6NZRqQZVaPZdaLZXKPZXaKZWqLZQqLZQKNZUaJZd6QdQf8P2J/IbspW5Z5YZapVZbZSZbZXpa5OZaZZJaZZZYJZZYJV5Y5LZbZR5YZLJbJaJaJXpaJVZaJYJYpMJYpRZZ5MpYpM5aZN5b5RpaJZ5YJTZbpO5bpaZZpXpYZbpbpMJYZcNb9bV5c6XU+K3bmyljIuEuLWwN54viUfL5+n974poTpvX7utKnvHjsTe5X61EY9X+3l6Rm5sT9Yv/45dyR6MkGU+aMEwGNejTF/wYiQx5wgI94eMyaMeUomoFycPILtMdXIXElOZUYoYfiY4mOEyGP6kBGCz53sUjtPTEm8wyT1lPdPLqqdZ1kGk3OZBGSE2CN+HzOWjBlHRog9IvQR8E/QvZlJJkhf2D+mFRkh+Yjzx9wSY36HEa6P6U3GdCdjkpJxI2HE2nMnM5Z5w9xYGNM4jOkfxhQRY56HccthTP8yTxJouclgEpZ5cuXOU0y5tVKfKaflN4GZeH2E+HPnzm5YmItlzFsxbjnMnXRenRrLPb3SlFmmgZk7KcR8iydvZMawO+0+eaK1lCRiZ1o/icJ8X7dDzOEybkuMuS7mTl6yOz3H5155ut+bnMwtgrmStyzvsvO+Xpm/k2Is7XXn0/45aTU/0y5X/tXfmj3NLYe58/dKPftN+smd/uz3JiN70pPT33wvN0fmSv9JL12ph/wqrebfTxKlJf1aRoH1/I0C69AsayYsmTu9/cn36UWpc6/3yid1vlM/vl1G4pO3TtK35HBLOfOv/jZvl8Rwlbv5uVMbvl2lfpL7Lc/1zl5p5pMx0cq4qTXmWxnz/4zbRGNSn7lTe/Y3c57MlXGXNzqTiC7PTUs5xlOSTov4FHumSV7GzEjzpCfv9DdrLK1jW2Q7zo2yudLfcje37tygGtMsjZtbY/aXMZPR3HmvL0leepTlcSybyGWu3D99O+Nx0l6sjq/3jz+vyLn9VTBxRUpRlUYFG5W0i8ZgxNai3hbZwkgRRigvQm1RD4x2YVT+IoX3KTCqPBiFt0glRuEvqnjRy4t2XIQAIw0XabcoGUZN8K/KjnmuW1Nq1EXV75N8VLou2onRXIy2YnQQI5QX7bqIw0XeMCqEkXeLuGHEEyOcGDHEaMFFNzBahVFAjFJfxBGjjxf9uCgRRuAvcoXRgYtgYbQkI+EXicDI/kWjLtp20b+LTF0EFCMDGLG9KM1F+TBCgREYjKZehPsiYBmdxIgxRn8wOpIRVox6Y2QtI0IY5cSILUb/MMKQUdeLpmCUGSMFGNXM6DJGzjIKhNE1jOxmtC4jPxmpvugGRh8wCoMR7ouqXvT7ohMZackIH0ZCM0qXEduM4GAkGqM7GIHHyG5G7TCagpG8jN5jVD2j6hcJv+j/RYAyEpuRkYyuZ8QMI5sYBc/I/UXFMTqQEQmN2GGkOSO4GLnHSHlG2jMKkhH8jMBhBAojqBjdzQhMRgYzqofRcIycY5RFI2YYTdOoOUYnM3qJ0eqMFGUULSNpGT3MaBFGqzSyh1HqjAJk9E8jcxj11AgiRmQzsqlRxIxeaFQRIz8Z5cNoSkZfMdqU0WmM0Go0IKOQGQXTSJhGrTFSj5GDjCZmhBQjGRpJ18hGRsIzspJRZY0kaYQ6o3QafdcIgEb1NSKkkWmM6mcUTiOFGhXTiMRGxjXyoFHijHZkhEWj/hrB2AhuRhQ2uqoRjowyaHQ6I/0YHc8ItUbJM9Kb6LxCL3/2+bfGhsac2IffZ/k35OfEXvEN37ehVfTt39+whZMx9ftcXgOJOtswrPZv+g9XEpzVhmjRyr81WD6hfCfWlad4N4jTif3heu8GrTrpmZTHQK7Lp1tC2pG//e3tNZOSl3d7/N47tE/Jv77+fedN/ZUlYTbhG0sOnzmxPNzH+y/vk7JBfk7mlN83hpmd3z19bufd/Uzw2fJvf3X6Rqd/Y5f4O0/J37mb/9oGrL2WalnaZTnbvy9Lvnyu9c/MRf2nLWyvtOZYqu8+XpM6+Uple925s299pR4s+bbMr9enjcY7V+6cWvXTXoG1p41sl8frL9vxsYTpDzutmTL7lMkbeWdrm/mXOrx9ut8Y2oed5G9L7q5w+8Tye0YKT0lfSn+2PlPm5XNTP96h7/Q0v7m9c1ue3OdKz8kbWTP51ye9KOXPHSytJSzHSOddJiPF0vqrPnNPS3LnTVMea+D7O70otZFx57++fmZ82U/aPnC+ucZfpSS390l/cBRgJbgyLZ72TbunbOnhaR1LaLvglfG3b7rTvhkvGV8+xXt2euaTv/PW6XVpu5TKb3KNI7rTqydlyPi1hiujyaen79lGnb6UMZie7whi/qL/pA/7t/2nHbN9p/zDil6oGamSCLkoBmJYf1f0Sc5Ilaj7oZBrRanjzZWGq6h+UREmUdDkfKMxsqNmkjt4zY5uSZRK1DVRpEa1DuPz2wMObZx/V9RmFPTwlER73ANtE5+lhE0kMd7vStVVlHWJ+ExUW9RLORWY9fAKZVN9RaGYqJWoKFtRv4kSTCRtPl0VZWuiYKN0iccq2vMc7eGDrujMfMotqnqocOtRgq6oiqiD6+mJ9rxEe3qhKyI8EcdRBqUixqOESUUgR7ETzxq0BxrakwrtaYb2hEJXRGEiWBPVGTVqzve7s++etlC9ROleD0C0JzS6os0TJR+VfU7leCvyP9HDiSRPBHyiRqL6r+c02kMt7cmU9uAPT/cb1XLO3D/lzz1V+YlAT0R8FGnx6ExXlH8iIBRpIeVaPL3SFT2dM09PmdM3UvOTek7/SU361untafEnb2rJd9rR2ui0lDXgb1W/qQj6RNsnMjDqDldEkSJHFF0btZErSkNRN4pEzJu3UHIokkFRZFJ2x0MmXZ8c0Jvfpt39tMdGgSiiMW9GQWfU+C536jNXWqqMWVvkjORQBIX8jOTRJ0p0RqTI+1/pObEG6QOp+Yw4/1Z5SWGcivZSfd+kHVOrqZPUp+2SmklgW0acwk/nN77SN1LzsS2p25Q8LZhR4P0nJc+z0tb+nevV/3kzlqO0dOV7n5uRmBZ31KjH4ymf9sRVexipPbTVFTWm6ENF6elMX5r9vw0ByqfBTP/MF/84xqn/+PP3kv8vkUVFZNQff75uLb5uwr9unb1uTvLNz/BfhE+Ban+fxF///v797vd/8oH+8edvVmD7wDzb5ig3weUyueUyu+Xv83eb+/egxzNFHDACvfw+ytujO6PmjLIob7dX70V78elhC+b932f+bfTnRt9unH35JJTA3zFnLiw9n9vP5af3w9f4fbbPJmuXAb3mz9r3TkXqHzBM3v/bdvofH/+nL/+XVnBuPX/vpLLrqNE6KsmOeqij4O2oxDrKmo6Cu6Pw7yi6OurSjvKnowDyqIo8StqOEqijQOyoyjrKso5iqqMy7qj+OgrLjgKtozjrKNo76ruOQqujWu+o8jtK646iu6Mo8igqO6rAjnrMo2LyKJo7SvaOAsSjXu+oPztK4I66x6M+7ygvPCq4jjLKo6LtqOg7SgSPOrWjhu4owDsqLI/SsKNM9Ch3O0oyjyrEo+LyKAQ9ahCPCrSjIvIoZzsKKI9SzaMk86jyO6oDjzrEoxz0KIQ7itaO2rKj3u6ouTxKzo5q1KMw8KiiPCpQjxq4o0jvKCU8SkKPosijsvEoVDzKTI/yyqOU7yhfPaoQj2LQoz7uKK08Ku6OisOjgPUo4TzqNY+a2KPC8qiVPOpMjyLLo8jvKP48KhWP2tOjGvGohD3KE49yxaMO8aj1PApKjxLSowjwKNs9KvaOUtCjNPSonj1qXo/avaPY8yjbPGovj2LEo5L2qAw9Kl6P6s+jvPKo0T2KZY9i16MW9iipPcqCj/rNo1TyKOM86h+PWtSjnvYoPz3qBI+K3aPY9ii6PGpQj3rHo474qNI8imqPWuSjxPeopj1Kj4+ixqPK9CgkPSo1j3Lko+T2qB0+Co+Pcuajuvao+DyqQo8qx6Nm+CgzPqpyj7LXo0D0KFg+ijaPguajfPIoMz1qIo8yyqNS96gTPqqej4rOo+b3qFw96i+P6uijQPaoij7KV49C46NI9qg4PQpIj+rOo8j2KPc86mqPSuSjNvqo4D5Kmo/C0qM49qjzPOqTj1rTo9T4qEk+qmjzrBNr+Zu02ADnsMr2OAuHOdmw5ZvXgyzUP6EHHGzBg+JKDr9w1JRwBr7hWCbBAu1vvd5DMkR/EVKxvLNXsnvycKyTa3xi+ysP0OAtE0qQZ/l9+8TXf81v86/LAzjsXzwchOQOPnH7rzme42EcjokS/uAd/CRih3L6FuxyPkSXsTF+eQff/c7dXq/3KVeeXt4z/+oBIP/m0Cdv5JXWIf2Bkvj0lMewb47g8pkS+q/lN09KYs2wI/Nw0JanWyfen2O13NnavnwXW2Q8hsTBXuok1/sWO6W1Hsr6/OrcMt/e7Ws7r8nnpIb9NOh6cv3kHVMn1pXfcFCYp7R/pzV9l0kNe8/La+wPr2UYa3jyjm/qJ8/yX615jhTzFL95U/6UKq2Zkmz7pG9R/urO3dKjUjN+Tp5oO66UJ/Xjp78lLpG28LO88/K5b2rJ2p70Ims4ffsrbWretivL7G85qM03qau0r7/Nsxx90+nJuTK1nZGSmkwfTg1YEsv/2ocno+PrjX6/vP+VEeRTrrx7en6uTy/16Sv1lmdlFHt9eumVnmnrT1okvTpWIiPdt3vSFqkTn3umXXw77cmkt+RZ25LkjZ7UgDWcntyW7c0YsTZef6XFeM88PfXp91qk/abOU0uxXf5257f5O6PJN0oZvpL4LrbppGa0aW9KkpGYt9MuvY733xyBLcUHHvdQxiRG08m6aypj92XGXbyR/I+7P+NO3LjzNe7fjfsg4w7ImCppZPXjXsyYMmnc35nK9aY2dg9oZOxT+ZXZmCuH7kys7A7duAc67miMOwjjXsbI5Mc9x3GvcNyrGveYxv21cS9p3M8ad9PG3b1xd2/cWZtKTmIzCburMpXaMDezu0LTSVlsZmb3WMddtnE3atxdHfebxj3Kcddp3OsZd2zHXarp5Dp+k87YUllL7t5OJVmyRw/dT5z+0iz7zcodvNKydcqWUqVdduo272u9+fTzexff3SzL5rMa94PGPcdx12zO3CHv69Pd9Rh3tcZ9tHEfedwfHHd1x93GcXd13IWcM63zpBel3f1Xc0t3Eknnzubodl9y3C8ed5nHvcVxp3XcxZ5KrSYZdN7a3Nvub86Zo5om3XZvcTq9Lt98uaXzdK9MyW3HSp9MH3tSM5b5q0n/1b7kHtlUslL7dpUr8xRHkHuC407TnKmxldZJHeaefjqO3EEb99DHXbkxn9i42zju0o774+Pe97j3Op0RNGl9+17ayPHrvtu4kzXucE1njDy5W0ZB6j9v6p1Nmt5pTUfumbH8jbjUbWopvTHvGCuRPpDem9+mvfzXjM3cMyP9zRi3Hiotnjqx/NaPu6hzxhpY8kqPvVMeW9ke6+751Hc3r4nduNP6qSvLsFNjuT7Ww/t8FsC/k7vcnmB0wXRqtVNyfVEYCsfmORbO8XWzHz85usx/czScI+vnX4/Hl8epiTYyzoej5B59v3Js23T2r0eiTcurJzA52sysih/JzH99R+g5Ks/xfI62cyyeOREJgPUdN+dYe39Hzk37fed4NTM3sw1H5Lkfx905Gr9ztN5IFe/x5Di76ajnSORSeZw+UXCdY+f4VMy1/9PRe+KzjCaiBrFkSBIwZjIuPVb/12PqxABFaqA9Kv5kvvL4PTFNHse/IgtgtE+SqB/EjykRwIlFpADOHJE3BomZkpkQz8Ej4eMxdSP55D1vjpcntb3H6I3PQjKBd/Xe6/jih5QxMKZwfUf3TV59eVTeY+H0I4/+m3RbeQBjieihZiRfkRRYOYKu1IAJ3elPK7IFTyQYjFvDt+C655M/wEOkzB6p70gvJDv7YUyd47AieUD/QyKC/6a+kqP8MMauPjmA6440gNZv5/g9khBKMpSSBx6bdwSPx92Jw1LugX5I3eBlIQ3BAVLa1P5WOfpvLveORAFelEnaWxkDJRnAifbFW2kITq+Z6pl65x3NWx4JBCMWlUBg9L6f57IUzV7qNS/Fxpei00sd8qXs+VJ3eikAvZTHXmpmL2Wnl/LmS73vpdDzUt56qey9lMRe6m4vNdCXYuRLleelXvNSz32pE77UWF/qTC8FpJdyzkuF6qUE9FKse6mkvRRSX8qVL8Wvl8rPSwnrpQD5UqZ6qbK91HpfSsEvVdeXOtdLUfCljPVS93ypdL5UcF9KqS/VuZcy7Uv59KUO/FKhe6kxvxSFX0rIL4XVl4LsS+HwpcL4UmN7KXa9lP1eKoUvtcuXguFLjfGlPvtS9X0pKb5Us15Kji8FrJcq8ktJ+6XG9lKge6kfv9TQXoqkL7Xgl7rZS4Htpab5Ui98KSy+FBpfCukvxdOXuuJLAe2lXvdSunsp271UzF9qgC+1tJfa6Utl9KVq+1Krfqk6v1R+X6qlL/Xql1rcS0Hypbz/Ur59qdS/VJlfivgvxeuX4vNLVf6lpPpSMH2pUr6UM18q/y/lv5fa8EvV/aWg/1JbfSlEv9TvX4qlL7MJLOXSl5riS9H4pbL/UsJ+Kf+/1KBfio8vZdiXmvVLIfullv4yLcEya8Ey18BSlX+p17/UlV+Kmy9l/JcC/0ud9qW++1LUfymZvtTYXyroL4Xzl6kLlnLmS8n9pbz7MvHAUk99qce/FMtfCvQv5dmXAurLNANLbfqlJvtSan+Z+2CpLL9MNrBUcV9mAVjmEVgmA1gK8i91+Jda/csECMu0AMu0CMvMDEt59qWO+1JOfymgv1TLX0rPL3X6lyrty/QOS5X5ZYqEZfKEZVqApXr/MjXBMt/DUst+qW2/zCSwzJqwFPFfau0vxfaXiR6W0v9LNfllvoalev0ya8AyEcIyE8IyJcEyocRST5+n4LkUZ+LnC5nFV8C4tuIyqM0YLWugbcRnmOKZH0Rkk1h+Qle17xhv16s7gcREsMYB8S64JInk5vaK1jAluIoXqskyBCM70jbcz6hs4ISsRLgkqXJB6yrbBbecaBusrlSORRu9AC4xxtegZSNzDek2othQXz0jQ3CNI/7C6HmkN0X8wNB0RXfuhMIbLcwlelX8Z+LuKWlmQ6pT38haw5sTPkq6RAIyOAHRNqL8SrgzF+teUUOGHxsNbaCztbFtKEpqWLUx7IYLl9WJusB3ZoDiJlb68ATNLbyRXomPds5GUHq9m2358DdwkuRSwiZZoghHosoGzb19fRsAL2Un5NwP/tXIblsw9cJ1mb11XW1kHUfrxe7DKwBAttHuuLo7tZYDGfxlNfkeOU7AL6wDa5Lu4515QTmhWEuuB1K+pVNi330nmv3wrNc96bvc2eMlp73TLk9lGy4+9nt0nGyZKDD5Cn4kEpwK8+G+gv0U1ScaSugjNxMqy4UFPjuR+Lqc1qTta1+jLduGsvW5QXsrf8YNfG6OXtip+UvPlGEF3b/FXtKqbZi/g86Xef3XHBLgX20eW9o6WH/8+bNXv5XNSxd5Xmrv9zcyYi9N8fubtc1LuX6f+G8vJgI85/WnomRIjr2T65UZmTP38UrERl6a7veNwmWMWu7A3bA6PMW/8UlfejFXXn4qfLa8P6JcLy0NvEtpy/t4B2XR6O3c01Lhob6jZBodkZKfXuMdHsvg06l63s7rkfl6Gbx8ev/vzl7/eOflleWzlF6j2rmb5WyvfPONNdm+y+19LA8jmitTS94hT6+8tffJmz6WZ1szqZ/Kv1qSx/KnXe7cIbVqGaxnDBufPvG7m89lJfW+ed+0oO/F0OJ7S/Kk/vNGXmnt0Zu4j2165e3SQ7z+zp3zdtaD3++d+k9PSP1Y2uUdxrfYvvWbMvtGk7bzzld6Y+6Zd8x9LM9t2VLy5X3aZ1lLk2f5Ftsr98r16cMpYeo5bZRekf6Zp6ce8u7+9rHMqYFOT/Dv9DdLPit381+tyXkyXrybb/Tat3d61Hjn9JmMnc448lmOi50acwzuCANmpJT3v3xu+31aaqWlfMcrrezfb9oi4zr1kPGVUZzf+q+5805/SF+y5ldaKn3Y36ZX2HY748jxtdOXKq2Z69OTvc/Xf9q7xT6kLWyFW09GIQkzFxqHS9KtpMpS7srUZuZONKK2jZNtI2Tb6OY2arKNem4jP9qIyz4T9WYck1HPbVxzGyXaxj6T6ss0X/neOD5lx4ydbGOE+0wUobJkxrf2GZkuY6DOyHElalIpsdNUjOf1lcr73HkXc4h9OcV8F6W+zAdpxGuf/f02ucN8o0q+MUtimrUrGcjMIKYQmfGzbVR4G3/KHXyied2uJBwz3ZmxV0ZPt9HcbQxyGzfdRka3sahtFHCfifE0gaXx3W1Mdxvp3Ea4t/HybQx4GyPcRjG3McttRHkbWdzGhrfRtW1UbxvN2sZWtzHRbWxsGx3cRuW3se1tRG0bgdtn4hyNYzXutY3dbqOz2/jxNtK2jQJuo+zbCPo2rraN3m2jhvuMsJpRgef15WrzvXI3owKNATT2uY1fbqN321jdNoa3z8QbdkqbGlhJCWcNrNSk71jpyX5vGj8F6oxwb6On2+hy+pLXXKnV9KI8K2/np1GxnZ6WNzUDYKe0PreSl86x0+ldTz7zK59oW3fqZ9LrUjbr7cn3XpO+tNPTUqtJl5d6zvv6xCv9yu9tzSsp8VJCx0UiFhO7p5ifUfPUVXpIxlT6Rloq756MfH6e6S22XRL3ZaSceaOk6PMOd8Zd6jatn55jCc/YgdRMWiT9xL9tZWUMjbluY+25j8kFMxbsDyZyPa/crdMnvSYtlR6VN9XCXOc/F6n2j6II/8n4tH8qMu3548/rmfrjz/GY6M9JQ3/7NERDwY6fM4Zqtzkufv9KWJITyM9RJFRokKn6OUL8q0cofxM34nYeYvlNLqdq24R9vGDT1yDg378S5jLA19cENL+pGT1zQ89/v0IH/TQESifuNWRzPFw6HpweD5b/HD+/ATK+JtH4OY1o6Z3bT8D372/Uy8049Jq35DVDz+thktdsEL+n+y4YldEV/ZWB4C23P7kbWuME2v7+TR1xhtFr4Okom/Ka2OFXHhXHAfyjDNBrCOx4APjnhhGO9hok9BJQ9RpmPR5yfs2t83sWuummW/nVKtrsJxh5PAT7Gvj+awXr/FThnGH3eyJq7ycQnbemJOqMe+j3dx9q7wWhcyVa5jgFr8H640bgrzW5p9uQ47H2ceNzdOdHN/9XEupKoZlfPaNB75GJURTm176+I/B8dEjHjbrf06/ck2tAxr96uHwXVdXZ+noNXx4KROss29dygpbHTcRfG9kKbCC8pl2hDtV839aPtc3EOzpEPGvb907fQiV39OzN5vFzM7hS4afxmPfvjfweiP+rH9T2zUtCT1BF/rbnW9tMNVxPGQxdeqMgbzidC5qhQ1A//paAsNfA7nFrbZRMep1CZ9IfcDpeDwC8BiKPEj/0AUfEbVsT2uUWPm/Hr04V7Nl6fD208GryGVmvPcr37YwLn758etqFEeQG2+8OtqZhjnRr7nOqcf86Cspxirq+6ZNGaaeZ9GFDCZU8+L1v/rYkj22admELfNy8/F1DhoLTsEtDBH5/b2vM9sLZ5Lcq+2MfToT2XoPUR7f31TUbN1yxP9Rwa3/S68xyYLYfas8aWLb+tsXJg6DJpx/yWxXqPRI/OqGvB1p+d6aGlf7BOj2+3eVbWELa8W3b/dFamiXBgxY0yGlLnZYtvYh60HbRLXhr+/+kV2iFwLcUX/t5aW+1AKd5D9ry00O4A2/0mo/AJ1ZalpDB14xrv2sc3YQ8vuaoec2FNAZAjOIO2CItOWGsyg1gCU9/9WqBHV+OCBbxv7c2kwKYHFvn3cjhcBJwjEG6rOfLp1vDYx+zbDjmv5q3xdnYHjd6GWuW0/5/e43jyIP6v6fb31jojNvhVDN3eJxBDBEflmJcSZ83qPFdKRX5LM77s8Bl37D8p/Xj7IBc3Vvp4U/qgUwW5t36Xe4oYxP0d5/SEhKc+qK6PG5C/763fgjjfk1HRh1afnuCUfYn23mvWeV+5dTSmn/DfGWvafywEs6zT3q1s5t5LnAlXh3PUfptFN56zQb36kT83qi04Vf+dsx6z5Qwb2GAuNJso7zIa8IyLHnmX/uDFqx8C8K+Xw9ZzaSfODed2xk89uTe6XXOks5Bp/bZoE9MPHduR5MzOKISrxn3RskPRoG16t0MIFb+7DUz4RjsQvl9O8eRgfJKTozicbSmNelM145ZRgrjWptmK399zHmZZfrrEZ3XRQnWzzHuSLyT60OLxKb968GkXy3l7WLJHftj2U7f4tTPyXg0hHdsBXEI8+Z2LLS9yx7oPMty/DVfFn5XOy+f+hKU59I/uSsWqZ0FtnbAmSj5SpKhRAu/Yy2tbbYcf/9qmV/v/NgiKz6GY/Ayy8mjnQF70HY+17aY+BWxVM4+d8adWsU+97WN3sueNvbSNfmVc6gZW9LKtx5I2/OxvTSms8m2Pu1j8TBb26K3durtGMgyNK216p1tETOjvBk7z4onkNH32HvNCUPdMmxo6/Sx8s56XB4bMKDtNfvaa+K516N31JsjYmJ19QC/ER17/uiH+PSMUz2NWwnnKz3/zpvqbdritsXLxvgomfeas3OU22O82F54wuej30tpx/Ad3nrrA+gdaZ8fLYBZZpgUnTetK60l27+0UXwn+2Ra1j5JAMdrfk3qJx6FtWr+m9txcU1mjYwg55ptn9TyE77/60U7tivjy9K6gih9g9aveFO36Q+5s9c8+swEwL1mg/s9t8zE49hs/Vvzy4g8KbNzR2ul46s71+stnI+WFlz3+9TSegjEgEJ6lLl77DmXY0Hv6Hw/e+s4dY4+nUPvJ/WpF5patU8+Wh4zGJ2XsxhIgzk6NscRra/76PNcWTG5JiLghDvoO2Xt0PGCbPdkJzK/0aU90QOnq9lvHV/01RPf/nVhPQpUvWfmr8wR4N5R2HQUghzD6Zjv7MPWpP1trs6cbk8bLbbz6dbfuLQhtz2/nBkJ1nk9tkob2ScnfVLPLWPNGeqx74H6fmVO3drPL71Zj8SMGaWEYfPGc/CJyniNqPI9M3Z2ZV2gH+64K22jVtcgvBlzGylrxQj1fW/9wMxfb9ZE9rpHf6mdJZ3NXWkaSPcKrl6T974mWKXdHeNba8/cZ3JNymzfm/je2mE9BA+ZiNJZItsnXS9cjoJ4L7d9I9b71mNpx+OZetOX0Ef1gOgrCBllyF5RAaPblR2fho3+7v9k7ak/Y1+1L507pbXdkyXrtu+BSV4TSY7QegyhY3zFIkkAfCPWCK/5amfi697acI8VTb9ZX+sta+Uq13/z/rj6uJ2ttEK+76v1vrQS5ZW28plVAICKCm69YmcErTHBnTOpgTur6YwL29cjau/V6fPxhC3V63rcVdIdO6wP8GRNesdX1IO9wweci/UY2eJ4TRvKmzrva4UyHz2OBY9dvW1dXZP1misF23rsObfzESj3NXslNtmnXJmznGvujH2tpZ72tu/dWWtYEg4JvyKo12Sr+KiOi52yuQJdto5WYjvKyr9vR1lrLbOOiLdTGZuZEeQPp76Bvt/r4cP3csa5MzPG66usGeMNuqJ845dqmS+9aO1G7PkZ3yaWpOOd+qkFyPri3fGxbeuwC/tbiMfjPWOB66sZfRKt/fnNXN6tJAB37JVPdxx5eOm97Ff6lubcZY7mvVp/8nJFjFXEK5Z7aEtrxdPTB3MEeSDzvSZrivg8oUzWsCU3X9ob76udJR894VPvuvVIs569svY8w0P0YVh7Gsj+VlbN42q3KvPj7dtRwrTjaU9bmeNCtBxHHrMExmkxHGXe0/H4fj3zijcYC+mvMjpWRrTzi2vn23mk9crO2DrXxWb0O2ONPab4niEYyaAnH1hP/BZrVevnGJwrGf1ciz0r7Zh1tLWnZ541pmWo9IdX/6HjaTsjlO/is0z2ShH0EiczgrkBV77R5lxhOLEM0rYnNM/Z80qvcFUl2fNN3zvte8bztAXNOng9GcuOxMdr9JBbC7ycO547FDFtEf/N9Zf2Z3lnj2K+38ox1EU7+WSku/rrN3RivIPjyD6ZuaklMO9H8GK39Rbsby2hyhrKo9pmU4Y56DnYgnfW72/mF+tNL8LclBX7n5nrSfZFSYurIQU7mDFtC1fK/YT0ZqXmjKAHtdOCIbo7VvrSI3U21wfW1zU/8+t2yqsQCdOy9Ry/K7bX9ULrLbQcbO34547Z1nqE1OkhPFoP1p6v6apHMcG3Ug+nfz9vZiIZiJbBI51KClLP+oFyktTDqYfTzkquUzzmAbcMOdT+OLdOiJO95X0yr9nz5Zz3zmrUOc5V2IRjaHM8cmnwOj0n3EC/utJLfUfr/IoN1DqdjqCVuS/ziKPPw59KNDLjSNTNkPlKwj28PVkzlvY5v330kaSRHj/Aw5T22K/2E7/FvqEHyJbyW/VZeN9LD2RZbytrSbnN1md7nK1YqU1UBdy8xW7kbpYz63rHchiv379PZqusoOOdrnh9rilstWQRxdt53bwdt9NpC9npLSWOJ6aXe39eZVtae449wQyvlZZN35aC0nH1xh01Z5iq1kYCk3V0iKKH7d8wZzn/aVbUkkSd1+c/6J/49xtKkxGqVxBCHhLeeQsZcubBWE5HlgE12FvbNL1dP/k5s/rW/z9TNtdNK3sZzuZasNJCPvpvoS4eeFZyFFp4egdXbdbhJY0pKfezQ4p8bscT0OLpd93aFogu6wit8ceIpBP6utnfueIVxM6n/9umd+rHminXC85c5zbbqztNSuUyy+uN7NDs9Gctf3z1Ox6pnmTI1ecPOCN8+wXOcZZtxTP0btnvUIbAcBX6ie+VNWnGnd7yDj909YF87UzmrG+eyryT3TTHVGet55qlP4riiFjxxOLRuVp33Xdbkyu7ch8Jce6zffOrNxzDupIwmMP+rfTzJ2tP/YczezHOg50RbdKqiXftnHV9Pqc8J6Q99nDHK9ZqxcudrFAcd3dGljRYmpfdFtfI70e8rQff6H1tTTMNn99eQ3ZArlB05z7JRttv6w3tdNUzYY8yk9O++mY9oq2zd81XzrBf16oyz+xUJrtwZvnLd9+u1JQbeN3Fq8uRO3rUre8xoY4TvirNsyafb/80+4OuprMach58OiWRDDjWpCjn7egLD2/t0pW8xHc8K+d9/Rn7iQknsJnan2RDvrOG0qOT7Zg1WiGbVykrZnbnrJ3R5Ao6Xq619/nqWh7nlNKqvNm9uuKlhxXrRSujMO4hvt++3hNSrTdrXdXOvlJYUPb+svaPbdffdhbu8HzfboXgOSc+EkIzXxvI856h0Mt+nppM3ufTt44PfDpmFUN5nXfeZ2Jd489rvd+su93V1W/8bH5s+BOSY9+QyzkXzJX+kz0FZ5zsz75Za79pWSmEY1kCNhmtSw8wd77DafVzKh74zuzsejze+0eqnTWyCtb+d3Z87M+X9bbSE0Ij3dFWSgO3hvKnp53hn/o8WqfUm2S4YrXeFTbr6La0/dFaVzpv9qnDJF1Nh2nEXr3ZHdBeZb87vEU/odPH9Cje9EBH6619gGdSDZmLnT2f+FTjSNQb/9Z37tzdiUDQSod0OR99e3z2/HjF0lSF0Rlrzp6h9KFD6SfOWctxtO4wYfe8JjtcrnScixVGMRkMd7DPyDlfvfSMjnh9IeffXnCFlthLszMezpzZ8AyB0W6kZlxrKCo0Ye+ViIL08AqXc3zFm9UTeMMMv91wWyScU0viqn9kkjSbPMf7XLHVrjJsqSeeubNhetGO9ZAMfCsU+0Psp3zptR1PRV7eSr51/YT4qJfeDoGxkBDn7o8thEjoX+WN/NWWjH015gyb9derhxMOc7q/EGodhlm+kesaEwywb2W/1UvMnnV8PzPeKzZHn7H+s4fS+oqVHcnEpaTv2T/Tk+Pta0nqyewZXyiMPX5mGE76W3aB9VU6fmn2ATPLaDfsn84mHlmnrcPJ9RJDNVdGUOJnsiuq5XdeWJ1VbXwYayltd2bFHdaqxbtTb+74SC1c3Ss9z9/ZqZfeTMhA9pKyQ+2crtXNPss5sXWhrNmfcp7Vd1Ju6b212FlNv/aN+JxnVot3SFf2uaQfmSkmTNJVsHW7UpP2hMnOcqxx9gJW+EPGl+NX3vJkVMaHTNtlr1n7f/tcLfAZO7O/Pf30UntL9s07e/dhjNa8/WGldbRs58qarp0Xsk+X8Zv9zcQ86I9Zwsed1tJyZtfpSqxLZ60kUbTkZyfKQibc2QOSJMTPyUpKa5ldeEW1XmWqTCzBuNOfTGsmKiajw7X56wqowi3DmdOaEx/VPvmE3Oqrn/GyUgY9YT039joZd9ZepZc66sNA7MPX59HFVocmaSezn+4MtbKyiH/1hFnZW7InJQ/frjc/FndlnGaFnlkyDDZ+rCPXPYhxLCTGpuPV22qJ7Lqy36HlH/tVpV99fkWiUFwfaRNOV9lnViv6xnXHt3e0OuNkNszO9ast6sQyXbGi2a3Lvkx6uHY40ReZW7Nb7Yg+9X4r3n6iib7dEH0GPUbXayZgwzPXAsc7DdFaIRWJPtLy651mbTIfucos40xq27k3pNwk83IsQBipvvHnC0n5YoVCrVNa16ePfmN/u722RaxfeLv19uTdM9JXdkC0Oa68JnzbXebbWSPrrDt7r4kcCEmerLWzIsg+qX0168cJNdXqZmcncYCJ5bgS9+iVH5XSVusV7Hx/xrvOilWS/3mk+ucfm3L9lbWhnMp95AknbK3TmyivMyxRDz/0KW9hVNuVSJVEMen5zBV+bv1nxrSWvl2/xCLu7P25rp9QMld/j3ew54zMx/3KWonWcwZ0F4+ll1aXpzuPKxoLaXe9rA9QFa8puxuJNHDGcRae1N6316BPqFWPB3LZu+5EDWUsVOLiQv/k85Pak8wYD5A9rDNs3/vfYeBauVNfNxS0s8pLdJ976HXGL7WfJFp1hf7ZM73/JfPvrEkdNXMnctVW0FPKbrKWzXD7MSkdw0WvODEDjj73U5RG5c723jt0TuuXSIzssDifan/eL5ZD65d5xH29yYhTrm4yn67wpezZpW7tM539uG+WT3SoPqRvV5KcV6IVP+eUpcRjvxOVOhnXIcMSA3vR89FpV8ppwTClTkRKaI82MD5Mdu2/SABrxpaNh5D1RaJc4l9dT9aP+p/xN87sj2eHwvrvcHLbNJGK9tIQ8sxEt5Y58Sed+Kg7c7o24UqcraWKL3dm10mr6Eh8Lbk8f+J5GvcyGe9S3zfrQWvVQP4xgSiev/5k4huz+zzZ/ck6Qv+kU296j9q3UJEzK460YMbXmehQR3HFcsbTSBRK5m49hI6X6FO0aW9iVp2Xn6wOOm+kpxef1nqQcZmUiKnA9ab3tzd6SG4UPHrPRGCOvzrfrDcdj4koC0PQJlxvdjCdZb4oRPtqbOxOvKvk585uiGVO3IW1emevNjFprdV9HeOhBJN5IbEWWht3H07HRetpZ//rCb8K3Up0VtaPiSc3fulKTLKW7UpcxLfP5XzteM86+rK97pXZP8xfS7KzOxBfUX8skVHZqVm5s/bNHYHX1eKV8RjekpjkzAUygZT8ncw1ei/ZS7UHjjbnWy06b6bdx/WstXTetkt/0WjZL06EpF76lb0D1wXOXFqP+bxHYxFHnzyRz1fI8IoFkBhnVe7stu74e664EynqqjZRMantcp5NPFjW/ol4j/XLrnSFlssBjL6YrOayQs+6Wz+wElevXKzp67DM1kNssq32xWloDV7Zi7EZc1ly38KUvbAFr0yccOKrv/by+8Qn6LO1exDnRxq1Mzs+ti2buPFQHdfO48wev6jjI92Jo5aEOAN+cfh3omJcd+/E0rsXnBiqMB+9iNf2Oq1PLZ4i72PyLWyXc01idF1bhaka8fXuM+Miu/+yxzxXH+Bbc+XMyJuoCdf4enSnFsx9tLeyq97xga0Zo8SfxFe79k/sfWzUZ7GlGdm7T+yrK1PTuGIbjeKQobn7Vok4rdhw/er3ylyglU6Uu+Px0otOu/+V7BkZlYivlrWeiW2OV6C/JHNY4YE75xqckbV4krH3kRWEvylq/L53YnJCrhL/rKf9hqHFXuntOCPUndrQpuktd2IXz8RxOddnV8LomsS2hUAaB1vPN48klj7t6Dx7ZlbSnlcskuu+eCOJSEwfDr3JSRmJkOdTTMZMH4h/pb3qkNWMxFjI+F2Jn0zsnO+SyDFtwiR+1XFd9vY3fsUX3eGKXruh7O/7pH70jnZOtbhC/yKrM/uHxt9ZaWpRJzY8PNCZcWd3O16fvn3K8IbMZC9bj8t9MU+7eEyW8etbfwQvkZZhpIl3DfXV+/IdwzSy3pe8nWNPe3JaJ7stT/h/Ygbc07QOW0/sTD2EklXikbw++1Ba+Pvbwde3D8HIOlSLJ7dnKrKf2HYV1uG/3onMDHW0P+QUySTSPiQnsQp6xVqSShTHkzMUmcf1TxxTp8wqjCV8dd3Zq3J0h6t/s4ke2pVYeve/tOHbMZg5KztN2Vd1v0OJAjyK7Kok7i4rMj3hyorMvdQzsT32okTMJv7T9p3wTGeTzGWJqQhvWY70eMWd/cesyxJB8SRSPaPMlY5RfK7vzuyJJ8Y1+7BG1r2x9tlTrpzXsMUz40x2b/0+/Pb5qLtzeuKvwsbPxHQlfs8o0yfW2/2vzBHZh7oTFZOZV8scO9nppVnp563j37qajqcUXyi9yxW9MVfViamrnKmJT24Pye5AmO3H6OzDK9xGW5H9pqwiK5RSX1r/x1jfSgSgnkk9YZ7OvCHzOYlW8RNWWs0xlXNtmW1tU3dGZmcn0bjBRF5lrXe55v080on9TMxk7Jgrsi8Gz19d6f+xulnlhVOlfhJtbn/IurXC6xK/lz01a7gSd5c52rfTGnw7ZblzVpqJT8ueXU6pxOaHtIS0JyLClf66EiHmLJYYEt9uf5EeznE7eyjuJ350NNEpOZ1n66fvZZ2S0zdPZjRtrOTn3tnRkAV19p1DLxN9l8jn7Pskri+0U5b+hPzkLEMIW7x6+4DeTj+JMrV1KvYksUmWUBuetrgtW6I+LtdN2eWUCs77nZ3MekTLOWEsof1p8UQKJYZB71S/0XNVp1S8Vnpm4nP0jhJ/0jkFlj3TiTXL+QWtVmxUojoTv30lvjdsM5FRie/VL71zKiEzlG2XCNUnMSqOpuyIJR7mij+jDZQ0fuvErBQSqfVmx9Oe47ioRMskHi8xVJ2oLec4WzBWLivK++OElvOLA89MquWUdGVnNruumYsTl5u1W+KsOueVnKESPWuSgNkTTpVZRo/ljP3MnJ45Rev6ZGWUcwS+o7W3EqP15qyN75KoqsTGJG5hEnupf5vdh0Tl2Q/PzImOlERzeVLv9WzI6Y7km7jB17GW2AyJpQI5vEVYSs46hZV5fei9LZ6S5/xIzg2FM4f/72+fMdHm7iC8iV3Rz0y8xIo3qF3Keer4ivGscob6Y86+e1ZVOaP62ZNwHq1cIqgne1WO8exyJsIqESxpi3DdkED3azxXe16JzUu8ovPd6fp958Rxoow6vS6xOhL47GNO4v/1QLJ3H8/Wmnm++NJEb6aevX9OaSU+/ztD5Lhw3r8T5btyh5C0zNeJaYl3aj24t7u++CXZu7TWXZXXXSpTiLE6drZKdHdOCObErrbodd3nPDWJK86Yeu+coXOM5y20SPpOGCNJkUQ3ZxPimZ+J7IqflvNo+mCfl5hTCa7oXW11Tmo/OcFkP19pkZzLzkkESnJ++z7W/MqVjqNEZjqnZ6/wjpfojLlzFsO/3c99sxJxD/0NJXgSmeAMuN6sXGI/47WGsWhPdmaHrFitbe1h5fyd4y7jcRLteWWHRR84EXqW/81OojNUovtCjXLa9M1OscwnpxUSYZJTSLEbk5PUOTP45kxf9nyjVJB9ZFcl2YWseMKJYctJmTBta/7zXWOx08dy+ibroDB//ZmMYqnUnTPFO7GI2Qk1NiY+pKuGMyciE030jZTM/raLJfx85jdxMs6POT29cxbJmTGrYFvc59aTs6Xe/56UzedmZrHFzyt7EO42JjrFHZxKXFbG+53TkVKjTn1mxeGsHX7y5BSMY7xDluwDX3xI/Iesr3M+QhuYfZM7NSNBCrtzTbSyl5eTznKAxBQ5ZkuiqOz1Wzmzc9uvdna9v9gq3y5zqxEOl2W4vxO1WZE5ImyjKCR88ZA7p6SzqgqzSvmduzN2skOhrds5/+6cfmd3JvFRIdufd53Zwb5hvIcjtOo7E62f485+9uZC+Z5vvZ/9MvlYTuplL6OyNtGHzOo+sSv6gdlT+2hGZklnT88Anm94miMiOyCdaP83kauJIbEGvrM5OcPl0+OPPTntGILnfGrJn48kOB4zyuQzOd32xH/7zl2GcSXe3hXQnTWda+qccPn2FrOSTXyv64JEuccHcH6/okGhj3cZK3hnbzdaBNq9ij+s1/pFD4buJtIg8dVZj3v/O7vMzuySB9PgzSTeJufgsoJTaWGMIi73MZmE7M/OwonbrMwImaGsmZzx/M56+KbfmRTnnexA5bxnLF7lDIgWKTFIiU6R/ySW8tyJRkuL2+s+lpXdWLlHGHV2Z9KXsg+S08Fa9ZwxXDlxEE4eG+K8c12Jewkdjceo/5wTlBMfOBHFznSJgtBvTET6JLbEURDVi5zSzaok+907Z5DdBZjsLbrLeX/xeN4nGgjhWs7C1858mlWkdjI6EjnFEIUK51+VXs6Py+lRTHa0c2os+8VZHcQTdhV5XYkAzzmL7FBYbyNty1nXCmXSGieuPvsU3zn07JjE/iduKhHI2mG9qSgbTHR7nDUmJ1WfrAVcbyZaz/4QwjZPVp2x59qZDt+w1Sbemns0OZWTGOmU9k0/T5yPnCEqHJ5LykneFcL85F/jn2f3wbXMm73CRF9LR+Uhb05CWSoj0l/95zHK94z3FU/yI3tZab5ZvWqFErnkLPPGN8hcn13vO3OZc712Mj2wsz/raM2+58o5tZxlyHyXfZzMej4rER1X9pS/9k0Mhm3ne3l+H2hOTd4hA47uFR/MGdb+kxMQ0ZYxhvn99qlzjs/SRvsoNPLOePyYQ1Z2zqTZk4pXphWaJydi4tdl1yx7T67Fsi7Tho9eXPaA4qU8OYkcpprzpImZ/HhXvNnQyJQ5J7m8j/8a7zQsYnbO0Ol3ZXc+69BEIGSdnlh9f5Vo5yunKip7B1kXS3KcEVbiMZ6sDbPHKt/IDpR06E5tf+sIfVdt753YDPeAslJOjMHO+aPY1TtxR+5fvBkpmVX13hOLqE/1Jj4qliojIkpQX1yls6E9vCS9Rsu/2e1NxONfV3kZubHwWRvGp0rco3dOlHsi0zKuEw2bvfXEtyQmPyz3TFyBby0NC2E28mpyxjO6Xone3N+ZZdvr01EJkfb6J7v88VXcdcrbJX7sU2WJJ+8qLPFFiYZ6EmeV80f2/6wic7Yuq5v4Odl7ujNH6A3ajiaqnPc7ay/Zs55DUC3hm1nMvaSZnIPIHJG1WE4thZiFcybyMOuyO2t2bVfiaa3trINCuVciuHICKFo02r0z8QM5m6MvNNkZzEkK/zXnejyvN893ciSqFIkIysyrd5GS7JyW8soKI5KnfVoWjjKjbb93z5quc45DL9RRYDzzmZM42bWJHXsTe/ydWNGKXllVuTq7Y5MTQ6IvEf6Zde6Te+oz5+xkor6fEE69gu/stvtiac34tOFFOUW70p/TP7Oe1RNzBtcKvdkfSQklOeeT6ET5qqd+6tYuRYOuQorCvvRDzm9XLntk7nQ4s5tIlU0UbUU8amnDmTM7zgIZU4lx0uboXVRi1YyuqUS87MQtWIYzeimZhZ/sXGSMuzfxxeHb98I6cnrdHZaouuUs8NZ/y3nJsCZXW+f6dksTnxbyljgi1y8ZcWeizhI3HpKsvQ0Zzt5Bzqg+ievL+ZGcI3C2lYtesWbR24mHbEvpLcyVyPwo+XTohH5dGHso7p3elXge17P6GFE1OVfoR1ZnrmHdbwqTTMzYd+7JPnB/PFAvKOdenTtyHiQRJp2x79jMeipnjsKgQh7iDyfm4cxekmcxcmrgzYomZ2BzWs1dnugDPLEzOVP/WXhtVE7trew/WquhNO4UXGE10VGJlY6W1xfPKbNd0TFwBnQVll2z7GXk3OvszG62r/zWeNSKbkB2b7WZuBT2upyajP8pc4jiwacW5TwSHtthBZY2OjaVKDVtlzFp0SYyQe947uzNyjfr2YydnNZ3J1QxYPqMT7Q33lnzZpctK5eQz6jEyCtOPZwoonRKpf9gfzujIhglhyiQRInLlLFvIkjv2KJPAdI+EyWZ6L/JNPbnJ+tLhKVHHcLZsOMtJ5JKi+2O/xlm0lnnOkbunKHLzoheX6LyEitY2c/6WEFiZnLyIhGzrg6unL9w9H1RtRk77ljZixLjlP7zJGoxSi/hTtFHurKejWUOzzn/+PP6rcL++LMUiEfBbx/ovdwHMW/vwarz9/ciCBJVNK4BUnM28+XvX8Mwj9dR5jQoBenx9/gkEIeVPndjAxg9Ou6Dmw7h/P124Y7/3N7fKxFhyLPADUR4ck8MNNf8/t4cXUYZ4Pe5cBTQB+B6HFPO3PEsQk/K/Jn0gd/9H8IdoGoP1/8GMPtBlIdNR+JMXq7km2ssFaEkv/d6KBXu5q8849s9lIRwIqIWvfLXVJxe5L1Y4qL5Zg0033Te+qE84E6u5A4cTkanqK3h5ZtyTwY2agbUKos6PEmuAU2iF8dvmWbgDNs691e/aR6Fot+bmmSAVaRvSguaFZ2IaJ9CvvVFqAf39+lti/+69e99ub95MdiBpWZYopcZVn9vXWk7ynZ5BzoxJw6Kf+UdL0Dn7++TOvFuz21NMlTgotbwQxsREMD6l9YZW7wsSaUmeeunLQkhPkSh2Jeo20VAdpmRFZvGv/r53NY2TjPxYI/l541AeL8e0umf3oc6N18uZw0u+6o1SdlunGx29Kg30A8+8+NTqD0WSOy8W35+daW0O/Wfkl/ckyAVlARotbbPIDRQ5gL53ccRxKKd0pbvPvRw+89jn8SF/dX2a03yrLW9/rbFMQR4v9zttE7YNuOcOD0HA8pamH9tx/XrW4+t+VozGUFM+b9ekXeMBfDpLImp1dd64/vH+4N+6IH2K0bH9Tqy2tap9JDtaLVNt70IF5aZy7ud9hzuf4P8qFXH/plRzMhyBK3b6zluxE5rrrfMfHMTZooCDN8D5sqULbSa1gMrdLFM/b2db/31QPvA7VhmemCU3dYt3zzaCuv5WdYkyBtLkl7B30wV6BbSagT3/N6Xe5r7o0zaQhTEaS+9HBfWjP/KsXZWwe3T+dWVnundlteP9QBmpf61KtrVyzF12Qc4kM+4s04cC+AA1Am4g2PwKe0MwUAoTlhjjNDHdry0Zg8OENY+Npa2OFNC34LlDRGwzgXaK+3/88QSap1wN2mjpbXXtjh32KaLrQui7y7fxbE8lqG1z5sytDaqtJBs7RDHrk2mnq9H+8nSmif6dq/zjr9lScYcRC3hdlCetv9okVbGNZ+39u11VAKwOJFh29lSTIdlvmUssyPrcW5idDync4Ez1yKgucyWzN2cxaw3P6/Rhj/2FtxWRuuyFy3bRUtb9tjxb8bRtRxfpX24HEGvT+dwY5mRmx572edTz9vemNrbWoy842hdtWO02oXTyezDs5xr1jhGtrYal4J+Yg95LMkTm+PY0ZY+jmtb5Dm9xjZd1thigwpdEa4h6JzeiKVq54vTctYTa39qWyynfY/gP7wIe5qjT5/BpENoX9gKjNBrOe9vLdLpLP95CGOpqPN1xYZvx7V/O/fdj32eAxi09a2F5LlAEHqO11jydh687APanPu2vQiXwdLy/XZsLn819rfTJ576D4/zzpO6shc9GS+5Q/kulpZg6J+FvPxM/3fWSH9bzoOdX52ZlWj91q8A8aOxpi11PgLs/t7lyqc9hNq+tmWL/VyxV5c9xDHCkUIs3nLescfqueEoszu/tSp5u3bG1x/Tu0Dwgv7vONJbcM56tHKkIrOetYfOdMvxe2V21qcibIve9Tgz2pqvNVCOQfvqo5VzJlqErPF0fSr/Hm3IZYukh4NUqCvrzT7MNhh9oJ3R/FdryR57n46pb9Rrx5xDb2fMm8BQYpPKtnDUOL+fvh14gtbRt3RmPJ0FQOG/+2t5blvKHnJfelylVV/WAwi4zD+GhtJrLV3OjG0vcuw4IpxPn9airozWiQ2hV4OM8clbP0ebmRnwipdizWhDpmOpfEpntnJEa6kIDcG6budNvR3H76O3s629zjel9+to+qxE5ix7CDiVMjjPOu87P16T9nWuAdbgjeuRxm7YT7ae9v1kJOoL+Svkk1DtuLT5l33Sp2jHrHMTylFLWjxbquL52CLaLlPN4QNs39oWLL24rGKcDb3mARyjA6b3olcGasFXz/zoGse26EldZe5blooytCsm55GH8H3sqnNcnr7s+c50j+PosmyEOzCm9GztY2zQMvfRCuO4az1efeZLH2k51zxLD3bsPwBNTqNknaLNzJV4jJcj4rodTaMvx3YFdWLP19/Wt7k+f9JVm7PPpUd3Oe8/5WySldGtJ+l7rfdNb3n1bJ39z/jJ9kBnpct3ARkzxh0vpT2Jz7/1ys74Ua5KnCMcoWviX2mpONxObcfaWB5nYX3R69ZDLq3B6MPseCz8vSzD0lbfW2tz26v3ZAWa623TeICX93GO41jm7130LvQ2nzuW4U576T06y9tb7vSH/abn6Ifnekturd63c5D9cJ2uKU7XdI8+T/xb8DGrYO+p5Vlfb9H+M+Pcrb83tqmzz305urOSvWwRYCsz/tbu6fM767X2QV939RXPoWy1eM7ec+Lt5P7artM1JrWxbv2iS7tHUBqWwRXlcoy7+q47now+v2OBMA5KpS11vNy2LIHR9B9nNOeXN2/qTDEpjy3uam65MrpLLyjrtTOs4NWbXZkFtDzasbZFWs8n493nLj2i54onllWGa0B9kvtyvRkL1s6/evX36xoBBMPf9kB7zpqsgq3DM2TAp4SWlG+d1VxWRllztbPSzvrF1ZZ3/lpf79ce/izHOKCqzPfH/SnVKV2xVNfW2utXPxKb54wfbs/U87l9+pKHPI6Fde6swlzL6F24Il5Px4fU8mtn9OWe0zH1an/ivz36LZe+rs+6nnh0Hc9HnyT3dx7nuHLd8eJs8fu19tjaZ2XtiDvja8UzdBU/sWmXvT32RPts7/rsv3OEs+EVQqWlJYGrvlxGsSXXik68zcd5Xw9KH+9OD3d9sRwL9w5p0RPutHLGjqvdJ+sjf1V3ymOPzX20wG2vu6+MNW3sR6ts5cwyjspQL4SeKdXl/Mtn2YJ7hUHpV9j61vxzShJCgS4pExtO+H56yJm5JismVxaMnZ23tsdesXhauWv51qfX7yfzuzNp1k2utmKX3tSSFKtCk0Le7KvW9uX4uly13Zd9aWk/tQNPaiCEbcUr2PFX9SS1twS5Mu5sNXt7KNDtSvCO/0CZt77i07EwY73R27cexfPKzaQ61xu7HUvoemqHV5zhAJJG7Ub5/W09fKvCJ+3omto3Jdzh903WYvbSUy8rnKRT5/JV19EPgV+0l2zEHv5m5c64eEqbbF+6vlkpa0zvrx1Ymf0d9aaVZb1pbcS7zsrOdUS88XCAtOb2Djv06YkvpwXbWf9KPF7nC9si9Cb9/9Zeva6enjv+sz1Q2xKLenqfS1tXvmPrFUxawdn/Du+VsSztpPPgo6d6t/32TItkzeta0pp5pDT3X70mZ8PR947Ha8uGIWiB7/Sl21ksz9rOL5Kcy3X6o49KakavcV1juzzyvbE1S0uiVXzsM8++0k+yftfD+Va12jq9yhUa4CywpMSPnsDnz0gYwtIfx7h3eFw9XfeOF+QM4sy49beXfuOqrAh8uj6/PfzhkDxzlv0zb+e8fH22pRkRd1a7Em/nCPv8Kt/lie/kqJfMLFvz2pV1YtZE0myt0ONcyZGzMp0wd3aGysjVZsaCZfQ98Vf912UNOIfecrnnOmMb9Zp81uV8KgFbzqe3a8m7UmZ9tlce9YTpffXmiKDvXa5WzMhLi8iH48NLG9jWrTtz0441k62dvsXl3VyNXisr+nBFV0zuXKzYrqxHKjTA2Vwa9sSrPLOH4ht1Sq7vRHgEvqLveMdL0VuwBZetqTd+y/Qe14yXVvfWYt+XM1o7h7brU1cr63I2P+3ntst923/Sb9OLLvtqZU0qDxwJj/PFurTbrW+ZVdWET/qNvH3JEtfruvXVz7kq1DezvzWsDZQG3HfIraP4td46Po8zjmV+0p+dxa6lP3Zr5erMXoY1rFf5cXK/T5/x6etyfVEh+XeYjJ6A1KhDrr79BUex/k/bw6/4vR3ekjk63Fuvz7pdPjEjt7Nj4qyxYuu0JFsrKo+6XBEs7/y0ez3xo0KrMqZe77OzApqszpzpshq1zxP6VuaCZg0VGxtP2/lOS37rx+rPXN5zuZq+szqWrl96Glsv4toft0z/0Tppb7WWd/Zo/O3z6i/F53myF6Cv4n7Eo+1a+oHrzuojfuybGUGPNJZ8/XeazuBKkhQGoq6sCZkJiMCXtWH9P27pf/oyb15PT1UmCCkUCgl9pvVHUCWZy5Hnp4pENjRf/F5pw0R2cON68QmT3Nz1L/zD/mTj5bHN9EEg/C/O4NiwAbBJtY+IFzsEqZIxlWwnEX+CBpdVG2MQ+fviFBSMxNAD8KZT/g2+YrRgunNJESNoHM6BCuN8jA5YvpnytmJChkVFZnFyF/xY8eTrvQwMts1pPawD/ECZs8N6LdjjOlZeOLnwfqPMjx7zC+yZPBTUOgenI/AJk/OyrYbARHEualhfkM+/9VbQIIilrMjg/YjUlcvqWzEhcrHjn9aLBziifRG1GJhKimcNfDup9cx3mmHhnV4xsLUkTiU8FZWXeZkEMr7I7IGQn8foSW1uiEastuAN8PPaNhFqwZtN9zpWrDZeQoTwmOW5wocIxRq6s0Q06gVDRhdbGnqetfWo+EYjC16XPZrUHMeUObf6XOabslW9YviBQZ5VU1T/aRXERL6R+nWJrs2dsYr5cvpemZalvfm+sFXUBagUT3jmQZ2rqGXM1/o7Fm5NlhVe0zP7gKYeMz6eHNQxWNW8MjmcC3zdsHYgH4WvfvXD4hB2h9r9hIUuqwN47GG9jNpBgWaLta2l/8GjPiIusPeLf7B6JRKDA6ywSo8RDU8O4pqfvAr+B/6hRG6wx4NK9LSGteTzZSbLahGxieyDquuarywx0VwuFz5fbwkvtBbeXpYG/LaGvt0qGIiUKsmY1lZcPSy/5F622AA+RCUAcfmRf1tmkTAe2AkeYGID85nmAkQQ8d7rqsrUcRbwD5Fzg2f+zC+2eb1sHrWYYZ3RXZBt4OS6eubyj+iL/At0LXrkrNXDqr74W9Up3WjRnInYEg/jCfUUW4vhfH0y5KAvYmuV9oNPM68kGyrYlTXlLUEdB8s0W7cu4w6KA4dsMDkO6oUCU81lvCOCDOyTrGGDJ6d5gbm2FcbId3HGsef9mLXxJKDHKeuoBmZcLh1bwsvhS2veejreTA8vPnk9mz6nbCen0sr+0K/2OvS45+YkrTBit6zwgkvfvJcxN5wCMqYJgh1wmIPPL877NL/4rk+DG8fDBG9891TspLqGzw/2P2TJ8K6g5YEGppZqn8esn28npgyeGfXRPLLN+snh+YXn2Z4+cmrWanmOiJtbFgj0jjpooi6Yemn+dWr55KqDKu3mXCyxxIv9HFD0K59PDnvXRI0Ha6XVvdsqJO/Ft5O7zYezc7a1Nqx0WfvgJPL78LETCx/syBqusBkHPn+L9D4zWWte5IN4p89zzU/EgZygQR66rgpoydziD4nyVLVqmnezSq8Y3uybyAVTXXi2ujU4UYHYXqUHlgxaW1TiShYrKgGmUYYoQLTF3hbcQn2grI/VQzO2XvfU+oUKKOIvvMpUvcC7T1jouVR5EbWnzPn1ruA6mR8rv8Oagrw3ZwTLocJYgZO/fJeaMZhVUP1cYjBi/VXBYauHfJmzMPat7Oi18FRmTPhb6lMLznZSX55k6Gu98k7kpHhyvOKUgdTzbPGJ3gy/97jv4NjSW+KrjVCy4oVXnHLO4mcz9Knv4pnBpcOcnWgyfN8iz1IVA55BQTfAbzWJ+z6/p6COOgS5Ytla2Ab8JBY7NvkLPnzKh5/L/5hf61dhY/DDKuJKfYI+xErNtUk4RhDv1Leo3pE/wRvIXcsDWz/9ZFCt1VotevkJPnarrCNrEIePG0nB0mToqKqmvMfVjcj8WDchUj8yb+44nvBGYZlwTgo57zR2L3kJeMIikm6jjzZW4j1sg2d7rw7EnJrcYeg/tSs82JAJwcfCfoDQpqgJ3eZAITng5ZbVAXOckksfcrN4PM6IMZ2IOf18IybVtDnwda9IBhuz0l0yk0QoeTOq/GNbbTxoG8xutlGeE4QHwwOXOPZVCaY2kjNyLR8eXn0p+zjMRnnTqZJqq4fc7i9WSj4yXT2s13rlVcvAFWBFgzrUsnJ9ribt4eTK58v78Zxw4N/VtpGNDusv6mfwePzk1fawQy1K9aAcBbrKUscFqzkjGzPNrPG9y0ou1iX7QdXVpzWz/rCZj1WCSaioy8Lnk1cWPEO9xjK8It81QYyLKLnQ401jfS7e1kJYZ2Of2eVVg8jBGtdkrsjjRINUdnjaOVTpWM1Rx2j9iLgvTgAhFFzN4F9LlhgWq3wqGPIlV/yKzK8OltNKhqUejChZ+grsfMhfxfzxlUsn7hgTsT3rgK+aRtVT1kGsVJohqgY0M1IPsOV5yC/UfYEu/pCGNXTrWeJA63rYDx5GJSTZd50bf3l+/MxnPg6avbGszBdAQWqBiLxFVgJPXiioy9z5k/+JK0OOAJPwybGjZPPU3LMGDwbmr89d0EOClFCbzMj1UUUif5zk8iVv81d1BR2Z0U85ZFcPnhkW9DEyDtkzoxt5tzFOxY5qARh7tZ0wsaXi9Ltc+gNyNgexCsm3yD0OsJ+7ebMtqrFbNGVlH76RUw8DUGDpMa9GXVTA06rMBLl9al2s3FkT4cRRyyttEnZlyQF+RHw88yKbK7RewxjnqZ/m7yCNrf5TbMPO4mEmHPswgyA3r09+ibMvo0UVdV6NENZC7aA43UO0DwqdVvR4kkmVv6zU00EwQd3LrFxdOvrkEbOA17oPntlMgdgNlzV8WpmfYc1R5hlv86gnWSolOJW3d8C6FeuP9ZLL1DQ+Rs8JfhNpPGJacgHZJDyhCjSy4EWeu8xHyOVrmS3C6KLpHZtVPVrjCzp6fVq4aywh8sasHrn2QKM+5dmWFguHWbIKEZNYOyBXYk1U7BwiAgzzQhU5h7GDLJiYssAGa8mLgp/V4sp8WjHZdhZs6siP3pUTDcIxzxpa8sWN8LH6T9lg7c31V5lJrFHxgsJwLTn5YdRjPe2JiLUePlM+H8UFLNnCUw2VY3pL8o6C5avLRmIV1F5niFB2MYBIS4Y8ZoueOzQeMu2yYdQd1pBJU/db1nCtMpBZkFH6LiotRfWci2FNB351qCmFkatXtQYWqIpM5D+wTPj2oULjs4/D/FcrImdZIkAwjMwDvHqJDZanFRu+ajGwljVilCcFl77mrYKZzfEJVhys73tS7J4w9xTtgGkfvDGarrrZk0+uRqtkyWAz5NJ9/i1qMooRK9VGUnn5VMKDHj9VUmq0rJ/ChQafA/4ZMJlrqrckYxqsdqnd+vRRnjUsFmVdWdVS4cMOXktQtyMjFzG8vkLEgu+lrgQbuSYWu1XiTbNUfLXZHPmRcYe8dcAllojdyiaYvG6Fq0/xfswgUFagbxnzVnXhVIlWVh7tfIGBqSEnxg6eW5XYICh2X5wvS0ZewKouGNopS7CNIHKtqvjA5Opw1KCW/Iz7wn6p7Y+8pSqvqxPAM+D58TOF5x/UAua8Kn09s7VU1tkOrNspRoxTaUy+QNWpHrNsdXTH3wHHwv2aExGdhz5WJpDsZr2qLHhyNY2PZ9MM1Fgg5pfNk5/kLeBI13zM8mAM8ORqPGA1t/ka7zLRUaxptLIybmWBrAHOrdQY4H+mzOFUCUN01i9xygqt3fwuJyZmIDpjOa+ZC785OK2q8dEvraUHeOVAjJLuL3mlu0/uEOuV1k2M/vgZo5idHe/lG+E2zd9lNsQD6mRuvxh8uMpetWeLmGLujC29VrSJ7ODqkskseYnXSOT6wFeDWI55HD6cWF+364Q8lJrR8FSqqIGnqo/YhKpkapNblSwnZaiso9a2fEdYHap4davP4Ao1TjznEF2/ZrJ4cs/OZ861ZK2pBk6rw2agnmVrXuy76lxObozyVnjL+Ii3YSXVWquTlKvZ4sPpynPWyOjt7JuqdongW92Xip2Lw9l97P9zX+zVkrPF/qOSH6Ziqg0AyQ/zi48M6NMnsD5wBZGTUdGqQoldsMNIPO95J/eZ9oC8xms6nuDoitxwLldGZZGqLT6ZiLaI7zXscrLf55XR0nv374Bdq8yYzPt4QrQf41wcBcuKD7EWTISt6EPg1WGny95PNbd8fi07rXjThxiqkhwFVKkplRNDS1P0cpb9X1OcpspUHYsMsBwCqjbUAlNlOFWJodIeFnSi4yorvFSWF35pLJWlYFc7L6xLLvU5t7OVmIiXoG9lav/2y/guuX1/Igq8sWr/bfzipKj+BUuDVOet/aFGPuZB4Ac7DqZ6Jyop9iD7m2pcXzUJsuJEn8/ah8o3Nd5iD+uAxoshj2f2REUsIvaJ9+CU6Y0vqvTvnGIxlQoHkOcn0r6RFNRHnFL5/Kq6sQaBpQ07WNkvMYAVT3KuAXKe6/bigU8WUeOeJjNlVlKV8pFpge9a1v2xHJWHQw7WSjE2rxZU/KkSmLXddpcY08FXtwvP+pfYGEQHH7XsMoaJmufqt8l2r8bPCiB2DnNS1ltBlcbc+EasNns00WhN1YNUZIpem5pGCnfE6hK7r7aQOsKAiZ1UgtYyy4OFhm+py0LjV2Xn9ISqrF0Ne+KoUKzbmaiqx37e6Vrh5WChYTDKivC5bCT5kei3T9mms2A/j7UhPLBVOfZ3q1hTVfKaUfJsyyyAp5V1NEIZJa0JEv319udm4mQi9lOru75aBeoddgxRAQG3L1mRT/xm78MrdgId2f+iokYdOKfJ/jvrtvIPekv9qnFk3VzbmA6fTHQou8ke2QC+RbXeQ9QmjpMjDyoaQ65D5grUVKqSiAgFF7GG1UzQHdF5qe57zBqwf3sAxfy3cgRDQqY2j7rQV9sgktqzjHbFjkJWrMS0ehWQ+Zy3T5OzTKxBXTNl2NRq0sFdeoz39j3hXe2sEeuSa9iHMvQAKCXUKqNanzBF2+5stXmyUnZGy8OcqxSi6mH/gno/rBq10jQ2UeGqDfZQu3gVL+AflJNVl/lkx8lKHhWMaoG2aMqcy+ckGtphjc2TG47LAVpf443W1cnjQ9TAcxYea2cqxFACUJ8qIsvYniY7BMF1z+XDRbCgMvJNuSyiybSCP40O6lTdHRjIoccD+VBTKHFCZMu1TE7WA480rFyIPbB8UNwQn1CFX7cXho6225Fnh+BdbU73EdtYTaa6dDspeFN1pKAR1DIl00ify1gyUWVGDz9ppLM3zeekvonuaMGqDfnJV6UfHqOs5j+iOJ7kokf2TrZN/2wfinMw9LTDvAbe6WqkiVas/LJ/FhxOt3KpQJsiDfsQ5edR26KKX3Boq2SlrPGBN6b8jxVb4qncJhXDpR1uuw6J4J/9dH7mliWDXRdDPtZG5b3FvWBp+U8VI/hetfrfjV/8vv1o5DVbJtneW2cdyB/erhn8s9wm1qt+nvp4rVungytWL72tUBjTQbBXRwrPMDj7oFw79WJ0u9NCZEHN9MXw8pCcfWLWMJuzDm5dBi8h3jP2jdv1g21cJQyInZjCtIepNk9lbMw3VVmgrLCrLsYm0aanT9RxvTpVeGsN1FCoeq/X3MoISIywf3aoKCBKOhvhdhzAtk17rG59DcbJk6sKS5/GaT32DhMpljMoyOOGndes+e0ysF/JahS7PNQ4XcUj+JkTva3Fq83A6ubtNRNh4uvA7a+TT2SDQR3UH9erVnDLN7KDR9smXohG7LvBF4nK1KuodLWLRN6Djs6yj+y1G84uAHlF8iM6NeZ0tgxZp51x9kS/avipW8FBTRVi+gQ7lGWziThL/SSs+HxVSW2RBjmdmYhnmW+3T2EZrThZZgfyoqD9oeehDjKt0dNJuvTDqtbtzZHH+FSM8EZbVY9PiP2oNjfiO8Vlq7KTd+Is2806VN4e2QxPhHwUnhk2qVSkOL/FuhKekErWRPFb2iS6oKHKRX0aNaM1/DtYBctcKmbtL7DXVYbH3MF83553JjPMZd/NnSoDi2V1Wz9jX49sgHpRrGKYyR4rI6y/6sSrjCXDsu45RHfsL7EehdKwtxGNxLLy+15FPZ7TlWE1tjUm+2dVt+qLrvae57/zjtgd+5XQgt7cyo4DkRJ/0t+3bn8KHI5TQci81meO4NQCPhNNbDmxYaltcKKLejy5NeKjdXaZNBVix15sO8vuFB2qpdQdqLrOV7WAHYtkT+ShI2r1yZ3RUE1Yx0HOsphmMJbqbr2xSnj8CZWIep0Tot++Z988Wl8HuiPvRgs9UMVP9V327D/q1qgkEh/XUsNpt4UTh+6EGU7onUThE2JRKpeIa/Y/qqi0V+vcGQ6yHNTTYWbwSBOPPUSM9kgO9ckxJ9KXthfCi5b6yWE2N0W22LDVqNeqB/FdJZ68yqcXwh+CN5z/gOefTvYgLxhOifnMU7Bb1TJ1a1IyvS9+m1zSaTlgBjXn6qNQDU0y6+VcI/xPEZGXepjvTpYwduuxrT7oedhHKz5yEVZVzODKujO2J/Jx/UUvZpFWReMeEYM+0Z2/gz9HeQVvU9a7na+y1WRehtaqATkgNY5X7n2YQeOXPlEcXkidlXiA07TllKwu2csvo8U6wITPT0X6NDaRIV61PygRfnKITq/6Gp8gxsYvHSd03Uk7ZuI84e3Cxh/av6kq8ljx59tvDz6/ow3wvqoapnpLJ7qw/mbuf3k95+LWUPBFQ5xp9Y3/JWLnLJf5Drtgv8N752XxPHYzWXEGaasstbY7rOATZaxNn9shghXJAOs/sYe63Rmc7jvTjJqF87iOuFcexrqP3B2+2tOk7sLJG3CYU05PXHE7oYjswyqbHCbxusynrAPKdfhsoF9QB7qC9d4ZKXiPR+aQfTFruCoy4v6Rb4G9hNmmcrHsvyj/1BOK9jnXRLH5OrHhqvTJWYxu2+we2ytrTBubl61lT8EMn7kS+HCq4raOoA6QN/rE1ar6bzeQyAovoSL6VojE+eQUKg9dPScR2Z+lStmeUz0elcTX3it80b6+15WfnHHyJtU78hjEROpZ9frk+j3OvtnxvNOK5EvBeOYU+MDLhYph8O1RRUw9VP2w7LfnXQ7K6pj6YXTga9zpaiBwGQ81sU53vB2aoAv0POhRl/oWZ7zgdcuKEtzRwA4Xp2mhvRn25jtJD05mkrWtJdbCw8T6b5kjcO6MnlRs5T+XKriru8C3THkYc3PenW4OeOY68rpLzh+85BNexo/dJGO603tE9VNmAw4Nizq345IVVj/mvuCvIqctzldhdTvIQFNq8LAZ632lUrTMRFgfGAO5axlLdQj2Bd+JHDEzAgl8onTZJ2Lcnahp7QNrJ1+TLXlUaaoT5vQ9MiRYrzq9cScFETdl5GTq7lQZ0IKcJzsrzreLHwZ+bTukrp7KeG3VDHRhRdhuNbWsMjZW4i7vxLeo91ZVYl3eCWZlNo0XdXoS5xomfKqKISNb+Oppz4s50XcWI1Pr3//CqNAwPCJAgSC/CDKL4JLCeKAghQ+gOQwIC2KX0BwbJNcBWoVxbEFMHBK20BYejDIIIMJw1TAILKQWYXxYGGcQyLLQ9hlK+KE1IhhBSIFCsSqkjqEgEWQxYXxnkLyHokggW4PQNgyPC2WPMAggjLwMpZFAvYUxQIEODgK70AQbEvgw3DNsZJDxBVonlDSCgwsFvyC5DtKxIBoIaVtoCAn0aDjSgQoMw1zCYL4QYELDVWgYC62VYfxokG+GpvQwti+0XoQCQBgJF5q9QwNwGFcRRkmGNs7Q7h4GugUpQ0hZg5gyNOqHAa8BBAQJcgDNoSEnUIpBEBOKVUGsHNLRAPvCGMQw5iMMZgqDU8MIiTDuMzTkB2FrGFwS5LOhmSeM8gnC4gBJQ+k6hL0giAwNnKGpIKU1cgcFBEEgZ0Nbe5BShZGpgRAMxaSQ3gQKNcgOgugtJNVhDFw4hKFxNAw+CKPEgkg9DHcIcp/QchBG1QShZEicQtNgGD8aYGiQTmZqb9xajAQ289pbTxmnrToIX0K7ZigLBSAekuQwci4Mcwnti6E4Fxq3wrjGIOEKwzQDKRPK7WGQQUjqQntJEJiGVvYg5QmEeBiuFMYghtQryHRCKh7aLYL8NAgKQ3tMGF0UBlOGgYZh7EIYxxmI4DDyMgDBn6Xxmw1YQ5IZ2v8CpRWkDCFRDDLcAOuDjC80j4W2tzAMNATjIOUMwz3D8JrQPhFE0mGgbYAsIe0Mrb9hPFAIcqEwEESxgeIMlGig6sJIvjDiJ4zsDBL8AAdDMTjLvW6AFaT2QaIXylFBaB6o3iDxD41qYXRLaN8KQ9BCo0sQKQY6KYTw0GoeRiYFkiWMWg5CtNDEHtquQqkylJpCq2QYvRQAWaZenQnrjP0KQrTQEBuKcyEUhabZMFgkNDyHFutAL4YBalnaLX4DaiwMIA4NJGHEW5AKBVF4kMkGsU6QLYbBqWFwSZDUBBgdRMkh/IehNmGoREhfw+Ch0MYZpDxhfGFoLPz936MPKVav33HiQ7iJDulMSv/TUoYwJCiQ/mEYa0gwQkkptEyElt1AMYTkPMtd455nUoUwji1IPENBMQy7DMMRwijhMGQ2kJ6hiBgGoQYpZCB0gpA6DARJGYm4O4WxyKExNVCBYShwaGEKUpVMvR83BzJUJQzhDeMFg1A+DEQIw2pDIhRGBYWRoyEtCaAqDOsJbaVhuFgA/aE9IAw/CqNDQqNXGMQZ4FQQUYVxaWFoexC+hzEZYWRGhme/AXRoAgyNoGGgYWinD9AqFAPCIM7QnBxSzSBKDg3tWVoUM/WRAofyZ2hlD8ORQ7N3GOcaxHmhaTPTP5e+hVPPHXE0OgbJaSgFhcG+YexXGE0eGu3CMPQwYiOMvQ5DlMIAwSDQD0OvUmInbpYmRQmNMWHcUoafjI9FvB6KDYHIC7Kh0MbQl/6C3B5RBO8yiKF8QqfZoc0+kIlBIhwGa4akOrQlBKIzpGShMBNGyoYWiwwx3oev4GatZWxqIUUQeIUBr6HgFEbhhJJbGEQYhrOHARahiTo0RQdhXEiKsvS3L7GJu7KReIbmq8wbp7AB4i/Dv8KQ9EyRErfj0lISyr1hsE4o0YVGvtA+HQjHTD1eU0thhGiQaoUBZynjPrGYxsJMkc8Wz1wvhD/Zxl/Ptefo5WSB5Q5xhJNIXEbKkNKqRQ6H7+U+W0iWML4h0MGZnveprfJ3bian3T0MZQ5jjgONGMY0hHJCoKEDER8aXcI4rdD8FhKV0PwfRrsGgi8k8EF0GyQCgSYOY4/CyMXQ9hZahsLY/dBkHqQ2YcxWkAMGeUHbauHV++1AI7TMhQsPwpD3kMaEIWthGG5oBQzCkTBwJIzWCuMjw9CBLK3u07fo2/FXLxYoCm35XRhSHIT+QYQRBKahQTQMSA0jqoNwOTTMhxbBbH2dMZFbRhmKEaRXYbhMGH+ZqQdjTxkoENo5QuIdZGFBohFGgoYx8WGEekg+Q2NeIGXCqP0sz+zBll6Qaguaw8ibMDY3FKHDSNzQhBOGaIdRy427QJWcpgw9jIiCM/jgT14zl0mM4F04OyVu54QSgyjmhWE3mWaR3BvPSO4wgCYMSA0tCkG0F+StYSRKaEUOrYOBXA5trpkiB27hXsZczgUUdhhqHyRooT0yyC/C0LEgjwty+UCXh6bQ0GwWhvaG0Y1hYFwYCB4k40G8EkqqYWRGGKCTaXZQ/H1jh0QfiIMwpiqMPAjNTmGcYmjkCONpgng3DLMIA7nC0PAs1xA7p0EuNDeGQdKhNBgkL5meUHDUNEN/9EX4On2+yERMiB9A2BeKo2EQYaCAQ3kjXKGRZS7GKeDikNS1IiyEm4IYthIGfoVBtKEtMIz4D8PNwwiYDPO4FsyFNuOsu+bEcfAMhaswmCmMZQwD0ULDUhCQhUJIkL+H5vAwMjtcWRFo5UzZAHJtik9Bphko0TAgPojSggAxNFOFInqm3yLe5g46RCGBSgvD08OQ1gxPE7c300gT2pBC4TA0mYdW9gyzg5D9LbLFpsPCgIYwRjNcOBFasgNNHFq2Up6F0pLB0jAtlGnDpS+h+TkMuw9D5MNogzBkJLSPBnFbGKMWWtfCIJjQnpphjrbJd7i7bIqvjInbrGeIKg8/5xvBWuvGFPze9XXwA9P8i1MG9vvM12BCuJuO623C6JYgLgnC1tBmHMaWZel5HjgNMfMBf7aovWMH+Q6ZLPc30jaW0hPKHflGh0/jxl3k+2EseEqPXZ7fyTuCyblvjaaI0MATGvxCG3MYDBFaZEPzZyixhCE7oRU8jBEJjYWBdgyjJ0PbZ7jWJYwoCpeRZOiduNGUokWWmcvlf8DDL3t9c8ZJFuO3g6t5L4ZdhgEoQRQShg2FZpsgj8gQ578iKHZ/uuP4an0saAoaN7Toh1HOoY02XMIRRi4GkWVoPQ0SqyB7zTKf4mYqhhenzN2OOJAc8KJinpD7nCm0ZIk5ydoY4xvkSlmyK5N4cTxNen7iC5ifsZWh7SdL3GXmLvKBaxpG4QnmfMHJeGNEmZl3BfTMWLW2DcuHgCNc9xIk42GQTZD7hDbUUMhJmb9wzxWFhyCJDuLpUGBrGyYH+cxWiImDdSPXA5HSuPL7TeIyUYmB3UEwHcZ3Zomuj1nnax4N6hv8X/CALBkReYmBjzwnSPXIAGCTi/NOjsD413AFSKYMJKiDxpUwojS0PIXx00FSHwYaZsoNEqE2mJkxu7+/sw7cD8k1RVnmAtzJTFk9JWv0PdqYNgzWJXf47jvyLpxicbhntlvIwgjUIM9KXdZ68iRk/d0GEIYIhyFioREuCL8CfR9GwoUh0WHsUZaYk32hvBfGL4aLUsIY0DBMMIjbwiVGGaIL8gUGEIchj0HWHEZLh8GaYcRzaHcJYyzCcPAM+b1BpMDjIUwJ42N6beUTWCs8DPdkbr0WPoGRIkFCGgpXWXJ0YJghfy7qW+IrGA//fmOlGS7ruYzyn4j96+8CXTxYLLf1cjVXGJ0frv4K1ywFuUzm9bebfyVacccyF42Ea136vUCe5XkHq0T+QW7BKMk7ig3IZUosSkyHIaccGEazBcF6GNMQBmKGMY6h9S5cLpUlD7+MC65tkTXIx5q5H3kw82jiGutTvPsiNnGDMZLKMKQ4NDOnzG2XeS7ZH1G15GOfKcuBtyzZAKsJrCdZ3meNAH9bcuOy3KAp4/uUfZXNwxsE7MQd2sgmwiUWYWRDaNQJQsPQgBeG+4ehpUESEcQNQfQQJAVBUB5GyIXrWIJgLgw9Dy2CoZU9JR5eVF66ZBXGaGYaHepGFr5dFMQbbTiK9zEW95Pgk5fcSEAgYEKujckSJ28zptfMkWhCPeUlOgwwwLJSYBTzrE39GzYA6rAaRT0COWAQLgfBbhhTEgaHhSJ9GIcUmgbDaMvQlBVGqYbrZELRN4yPD6K9II4J16WE4fLhAo8w2jgMnc80B+ROeC64CnKoIOgM4vJwLV8YaxKu+wrNBmGQSoZIQGbVChq3LjNMITQVh8GCYcxlENyEy7fChQFZ8nvEMi5LCMXFlLl5yWoSZQ6M2SeXjl+FqdiPLDGefJVMC3YOo9uy4I6J2CReEY9X4rpt3m0WOWRIOAtYMhbIBQxh8E0YVhsuJwgXkwSRXBg1Gy6jCmN8Q/txkOiFwQqheSOM3ArDTcIIhnApSIZI+4MFes1eic56/twz0u8efAv2gFg8DC/uLJ4YYXw52ow2D+6N9gxmIJfhTl2G3IXBkVnybDBdNDWFts+UCF+MTabAgIkwHD+M4Axi1gztUEzYcslQ3g4X14WR4qFhIIjOU0ZtTyJ3YtMIlGmEJeKX9SPrieUZx7ZZtymigAFgYHqQqIbL6sLFEuHyqqw/1p2ILM8DroBJYJhjaKsOg9jCYOtMowm1URpuw3j0MOY+lPlDE1RoPG4cggfDEh4wczzjxr4QQ4loQyacN2LfkahmWW+N1aVhHsGnsc7w1Ujowlif0MAcxrtnyRLjH2jtDu0W4Zql0OyUYQ7ouSvr1LAc3KbLlaVBTJN13/GV8fAnxILSc8IibpkQmRYQJvUv8uihLcEGMGwotJuGi/rChZ2hZT0MDgsjaFMi58uKsKdH7ISdyGR+PP/ZZmR4LRBIWc+SS7SeyHkBmSPFCNcvhUtWwpCdcL1HhrX7iSWXOOGzLgNWhHmAyVla6UPm3mOqet9f9o5sTp4Zy4SdQJAXLosKw0Ey9cPYzzIXeETa1pfF+UtunCiD96ZighA5tEyHgRfh+oos8fY0O17iPWuUPKd+HuZ/idPECXCwkZkEFcuZT/N6eJuXPcUaaZ4Pl6KFkcRZ942I6a7tp+WTcZxHftiIicXGKoZ5nP6W2AQzubVqGT9xLBGEygKXx4SmwTC2O8tTxs3Sw6jtGb+Wf/x26zvsL9mBvuhWWt1ZK7z6H6ziA8GW2RkYG1yN7D6Mwg9jHcLY+jBmMTTBhuumQjN2GLoUGu8zrZt/VhLlFeWxraSIJ7erQXwUl5qzWA3RP8fqgKePM2tlUD4z5uNEugPSWOIQGV38MNnuXdWLrMy5RBFgFc4+bPBWbQI+4WKAlCoRuRT5mR7yEoZWhJaqLJU2Vois08H8jFtb0R9etMNTDU7olH/DP5TxV5snhvLJ4GGGaYaLbcKldBniJRg5rngJDWxZVjZLdATvaqyHR2UMXEp7piaLtDc0wWapUnhlDo0+k7M8jdeiyv7Ji7eXmQHPcPlouAwjc1/2T1ykByOSirGPfDg2gCeP6iNzNDDYFBHJ98LFvVg77CujQFKqUMhzGamcEodwHrk+KgyZDUOWs66SB2QV62W8L55t3FrqMivEY6heAEUs8Y94iSze2Co+pLa75DTMzWVuzWHlJ9FOMJQnNAqG0XLhOtsgawuNspkXl37WmIy25OO8y9LO1QXx/ETS0geC9BjRmKFGCB5jmPvon1ExTatX+NgpP7PM9VQZwW+QJyKQDSMywwi2DGt51q8/tBkFwpGF9nRbfZtWi3hOq2xEKy4nC1cwhmGd4ZqfTBU71P2nzDYMDI2gWZc3FtuzIzB4XL+XuqtEvi9bqCYtVu4uRw3vqu0RMbdMqcw8zJ6Kmgcb/tOzkSthV0stCv7nUwsHwrfGgTKHC+eyVCgNPImRlGyaa9HDUP6Ub33w8Pvui/ER38t5Z+W5hCMMlw9X2GbKAFOZqqvJuayR0Qpcqu25j7fiybMR7/Y9O1ZA/E1yJRVT4DGr8+aq2CojA1Ly/LDuW/7hgGqG1RCjm7Eej2c1sLbRxM8Hw5OjiVFjHs2Jg89hzHHK9RyeRD7Z51+yylbzb10MRkU9CfaPJ+Ra0zCkKetPq6PFwihetpC3AA1+rDNV1OXny+Trw61ciE4/sZx8Aqv3mGXjT9RjiGB5Hka5hbbtcPFhaBHMEicva7t4+yl6NMt4OMXitG29hqqQGj/QmtzUwNeh02BkYXtv83E+ASSJ9oBLwoIgO1xhGBpTw9DeMNwhDBkPY8jC0JMwKj1L7k4t5ePavnhOkQB4vswo5V5cE95UvRy50pRTPap3zNbl0ERZ8pycRHE7+cUyO56caLD0Ui1gvWDKs8EeDFcAf/u8Vls89Z4Cnln9HqtNlYqxgFlWpmAFh7rfIRJTqyDn4E9YTyv1V6tg5ci9E0Mu490gy+B3sBzydwbihBaRMEo1Q80ScZPRD1lWl17ZA/+0LnOrgeBkVsMMzs985cBVELH76Cu40L3jODt1lWBEoocTpOKXyH7RGrXFo/5HDlA8j2+Rb7y5wJQbJ19QiecpUxuGtQQfMq/l+y1WFTmb+MbH+unyPBLdttUl94XMS4SgBVppfURZnnp3TSaNtSWyyGGOKYcpopNhA0mCBpfKlmN+wV7DCevlfKMhA89TWSmDv12wMaXSib1e8iqP0Qp0uollj2uFCgs1Ixf7hatnw4i6MPI1XGeYkp0boi/O7JFBUidjPdH4SPZhlDSmr7uDcmWgVnWM1NpeNR6qbVW9fvp5n5894uyoIkADxmDlLGMKOtJ12SQxuegFTz5k8j8jF2uOnxGrX3aUdx/DXeAEUdHjLbi2Nkv7r2VehmcjC35V1snVEHllHa3wPuY+hW2LhaZVcs7OEsuBk/k09Y1bXT1c0xDnxIwVD+xqiAdUDsMGLDlSka1KObNp0TIKbaIVrcutNhGv8i1WJR65EdhCMxc1q0QTIiYX8YZhhW1jZpGeO3gbVR+ixJj1wAqKwMsaK7HMnVIXcbAluNwe0pp9GXWr3qA+qwDzIigsR42HnPDli9gdzuySl8B+1OQQ3aZs8wRFU0PhSshwfVdomA+XyIaxkr1KnK9jHkceqjeTk8Qv6bHRuJY14mlGqYKXZ3vuystxccqwGXnIoZ5ZVhCPcVwZn1wW2hwcq5bdVSdP9jqNzvDAG5XCsqJHFOY68DBiLFwZ0rGJ3Mccx32BzzHjPuq1xJMXscOawiZ9MiGfPJu8N1Uw3v3uF8qTFxtTH7KsgVJ5RA/JtUBZF8NcZRT8CRWiR7TPmqN5YAhacwjypfilIW5kj6wrWWs7IiXyXDtB1C1cFQeZ15E5h5+5EYQMgpzRWAZ/wgXe4QqQcBl5aF7NsgZBTBzygSVye2W0QOCvFi5j43nn9z8/Ta+CT3jg24kR0bM9ctdmKDCxV9MCOgWlsNcMfc5QuWcdf+ONjz0anFw5UmOoWPG1h4hzStWeZu8sub5pTmdPwZbThs1TvSmTT0xXfUqGy1WgXbmwbos9kFNYTxQP4DG4ZDQM8W88wE7Zx6QC/JUFslrNyeV8fdZ3pqwmjAcYDNTKVaDhUszWYJA1TCvFxIhBrmStE+ZZvZBKexGUqAkNz7h1YSLykUMGd2H5NN+m7Gswg4CXKDEbGSjXfodLj1L2Z4VqC9a1rN1/6kOMX2rpqVfuW9EzW4el1IeDwEECjMZOWcv+4HZujwNvihp2RWUs5xGV11LpSi5TMh5kVYMTytDhRjv6AddEJplzHTwMOQ61Ay5iybLevawqPvL8YC0VUNZGrUeINvGc5vvlGhJN0AeWKvRb5WEdLqonoqEZYzhOpt1PVJ0YVhKuEsxU+/qqL1K9xupZ1SVnL+t05BqMP860D+Kvy4AorO9aYmyifOE/1RjgJ19RtGwSHp4aCpfmhjE04SKBLFWX0wzU/4VVU4vnwrOUDBIRcD/yMzdnweeX+MHTrZcmy8P+8VclslXpp4rVOuxV/WGNj997PC/8/rGOQAREoWHHAVXasS9DDjZQh/mIk9nxjzUxazhWQ/CiaCGOKgtihErC1wo+fuwxFi/XXKxFhLWLAYt9LyNtDo6V4j/rcm5gQvvjrE3L/HDi6IeadhpafyHKlJ7W6EBvF1c2dpyCr4ONf+RDrEPBFRsHx9Xfkq0MK4/s+CtbaL2bXV7WKGFi6XCE3Z1Xywo60oM99qrEHAcfCz6/NQU7zvgcuSYV+NQHl71jy2iu14K3N8Zp81FXI3q5WEVODGw2xGnU74ocCm4WbznW7c1hN8no1ZPLm4GISl2Wqip2k4sZUuYU6rHVnnFyxxLh6wfIKOV+XYEhZkYthqZuWaOPOhNw+DGyqMvd5oPsvr2Z5FByNXa8PmbEYki+XV230fy9OiVsA59/e8fUb9tR+4ilxQCcBXCjOE1OD33LMLqVCiLezkpEGelUb8K3L/lb8jJY30HliLEI4TqlLLXlquhRynEZTLhuMKUvPUSBY0eV+g3rkjASxmi0BPNqdfiE22VGfgqjy5Cd0NodBoSFSxrC0J/GwJxBe3Wv8t9aG8hKlZHaIXtSeEe1f6/sxLUfvOUyWhm7rZMSZaxY4YvmVWv394LSGW/d+2v9jj/Ny8QwsjRGnNezwKm8FusnEFWtq4qcLx42m4Pl4HzZDTRUGRlByMrtyBvmbjCW9BoweLGzZs616nrWJPauTpltMjU1RaJ3VRN2FssB8nPy043KZQ31bK+ZAhkumKHkW+w9IROMNRpigV3YaMbKHq5p1xI1R099xBUynOC6ZdfDsu6Jncgq04uh7+L0zbq9UXAavJ21MFQKDLMOV9dkWAuW9cIPM6AqDBoIQ6LDZVGZVw1rR6eZIFEAXLdUosK/DbFoLjcOl/IaDclozJuIwlNrseKgn8cXWQk9nl85N/Wleh68gftVcvvWjoc4h9zklXdlx9U7cWbRSCw1b58sN+9lZmolhd7zhe6dixzCmKFwgXQY0tH+Abx6+zc5EfbwctI/+1LtxzxidZ5frEVe8xoFrroSn6n+kziIGp9hrI0W8PCcC/Dwuv3mrDlRfsr0rovDYZvtvICLoDeZYUDhSrkwGrWxBJbAedlXmca5cEdUt2pdZHYXkxgdwGCqGdXsPXJQZp3y/PZ23R2RddEPE3dudsmZhQmngrDsBN9XI0p202+0VZ6zX4whDsP12m6t022iFQgBFZCxeJkJWjeJXLecD7mq+bjdbZGZJ28Ck5iHfipa7VJnd676ArbhU+em3tgzhU8bInajs8oTMn21ZNjSkPMBxTFCq/E53g9fN7AZnpmx9eEa4JS5p336W2UCSjB3ljjFJY7hMtGOWeYRVHb4ZBn7EtvA3N6uH/yqnOGxO0NlqX3ZVAzVnQ7xs/pbu+oeOTF4YH4Cn7Ds8pO38e2oDJY629x5DsZrnpNc6XV+gho59sWuNOPgutVP61zEl2nlRcwGrgA5P+6mijsnXRzZKquQ7D6o5nUiRKwlkeHCAjlXYZs7XLzKe/Gc247+Zd2N3X+seBKh7KZxQsWSwcN67ZW+bB4ebMqUEhnlQ+zoVz1y1X0b+7R6Ao+h/mFYtfTz8VTiKCsp5MXkbus1f1wyoliy+bgsKB6A2LFiR7+qAPy8a7vs2ubclTsrN86+ON+Dzs0JWl6vEUrtn4yE2ANdhJ2M6FsGlYVRMi1yO+QaYDPGvodLB8OVM51LymCTifB3VZFWGLXPmxt+vgW1J3sDb8846PRaIx5AXtfOIE+ujLrsXFlV4d3tSkaLyMmdPmFEjE5KsXpubs7aXmzAjnxmHH7C7Z7WEvB4PD/TXeZnT0TkAcjujYlXk0zuY8wiKn12fzhxhbMcO0adeCDDbCcyno1O1bXN2sSQsAfGuL+8hiwJn2zHK3bOdWjh8pUMuWvr41v241adZE6Id9tdNn7xVDLG2HBUCTpvwUg6RZKgLN4LVMZlJI0z4frwh+JJ+4lee/xlI8nHt3VhuWXrxeqCsI3Yr4TCU8WgKz/dEawdfMIVm40f8FFWGez0p9viyAvFDEIsLUKDLWQfX/tG8ZznatJ4Wn3jkuuwYiLbIObRD/i0YCf5KBAR+HnGKqRoTU2m6gKVIVYtjdfRr5Kbw9tY61cDb+8PGdB+VNviae+EB7ABUWnZa49afm3xCR5SlsmKiV0wqhrIwtZ7+S78jz0CsB/zzu4g1jgJB3brqADnfe0pe64+UAYDzykPT05Udt/L+6n/BHUT6Rg4GwZGh4voumoAbsfeVFeqMWb9l33cIiunvlhNdgrQkXW8uh1yEFVJ5BdUUhYavElFr+yjZM2LyFUoixi+n7IDwu5XpyXY8/telCKTzJNQ0ZsqNMSut8cTFGcW6RQINVSTyq8Kt22djnzNjFjUF7NdM3rQCF4OLLrUacjVH/kipxAQxeytWGaO5Zvq2cjaVMurZBOF+lRgD1m+dWekyG+zSnfCBjbD362t20N9ZNvwRZyI8hTf6G9n0+VUycJE/vDtdkyLr9BpDPOFRyUhPRFTHfXVSfLucBS53ZfaAx7Jb7db1uqPno1s9HahyuGXCIpvsZ9LRSLI0ElEryqX7bdgaWSCWxZCbbz5uBpUkarq6Dt/iRNnxVC2n7M5nRniCVK345wi+PBbU7Or0Y5aVSuXKeJ86SGtc+Grp9MJ1JZj22XPFHmH3SJG3tdpaZxNqhhTvpc6Y9kzrtYFJckSPzNhoMy1ZaHtVZRVszqshlMGiS7dJVvOOSrVMnCPQ+3QVAWBN7MzkUrfQgfChQGN0v1Gd032Bm8A34LHGM6YUgkMi7Vu//VV9OFbjN3kI/Z+qtuXdbSD9b1TdEBT6hKpFWKxpRbd6RBWiO6kBXPMLauMJbvXaiwj5wxOwBLsAqaOvFSGy5VZwREvGS+s+C/zKfw5TM524pwoxX7JrZpUdkIFjgoNe4WcS6BmHo831S2oyXnFUWIhdlzP7OQQu5/kaa1ZO23D3Tw+CWfQOKIi0ZzrFZuBW2AXY9fwnUxFrJ/GCPNTPacxQuRpNdM9tb5mRQ+PpP7W2QWPbB5nGQUgZ2RRZ6zbl0R0oOayxDlDbAOSN9+xc2TdSQXkRPKf2J76TPSiC5zA0M8wej7LeW7v5aA4ufaPc9LR4g4n/qm2JdZM3/HqE2QXOZWvfKznwrM85Pz5djlqtYL2sVoRAxWA08o4RQVkisFUjPAMQ+uVZ3YSyLY3Bx9orfC1giPPv2SD2+o+dUR0c8stOIPl9qTbQ6eOxTkkZuX4jauztYboVCWjuZVcq8OPqIwcWXbXd9/mUGb3G2QCsiL7W3dmCP/LKht5JXqh9dz5NjynDBtc4rKWwZn9VB+phRYFbTNQPJJTpOgApVrHqNZ+fvk3bEOFhvv4ytyC2O0QMSu/HZ3UDZ2MZK5kPqWHcdKg7Lo25oRGfKNKDFjZcsqfU9dg9pbzYewsiJEL1IfljGP32ZTxBpWpydGfyGvZwaruiMxiqQ2zrxC1lV0e6pC3+Q45F70b24lzU2uXE+DtqIPUsDLraVIDpvbbCpSTZ6YYlbVS0YqdwNQN/cC2u4fdtLJ57hOS4RpH7mQwcmrexdqN8xnsupqXT2Nl2FM4h+1UBzua7b50ZhrdcIyjDReUNmsBWr49RJ4FuXq4YmcjGDWufybW49XtdqRKteDVS03s4xywW2UDwRoHZZDMrexxc/aRinfWhN7kpS7ob4IEHkkd12Z86vr+/e87LVD7dpPdX7rl7DttZD9n/3uUb3fbwHh6WX9A4GccvwT36Z90UvGlw8x4m979GpH9ft4NRb/P7J8/nbr8oPfP3H8JYn/+Kf518JN2HL/ffPqTO+H5/ebPpf4+/+eGfpD/95PxdCni9wz986fFHL9w9HvV3yf05zTO7c/kk1++vbfh913V/9rl3u+0MOv3dr+F+z3P6G9vkvH3dj839PU69bf3389xHR6fuZ+hwcfvSfonp13hDyL9DsZ4H5623ejXu/H7SRNPv8/8mcvv//Zbn244+T3P4Vv6fz0tJvj9392/2eDp9y7P5H377TrV7N/vP5v8/RpZ9NOul9XY/fNesXysYRd4vj7HvQunf7OB4O8d+6nOYP2bIv/9HivW7ub388FqsFZNhfw+f/b/6lLW79n6M09TM783etsSuqQ6elh37zLP1mWt73Tx5rfX/fcd7eRjHdoqTofJ3++MgT1oV1hL29L7aA9Pf36XNH7WxW9iG2nR2O8N32KXWbfX/e2n+tjxltz9nr/3N12U/X3X7r/34fw9ycKu2PGWBfz2pffr9KH6/V9Wr/h5C1i/aKVNmvz+dMdnf+OH1S32q5u9v0a1WMjCVvt5umDze5fZT45Nnk4yf3vBd03WsxOz/jPsZq/G4PdfdqRB2G/dHr6x2nKwvVP8udxTTl9LDX6/81uB33ulV6yB+9eIuNe5/34a9P+e7d2sIae4+LTqdZ78Tofk37e0rTbX+Pt5h+qftWAz7EvzPTwP3/LyZ/z2XtV9d3+wepNdYx/5nYdz/bEj3Uz1W4cUu8b6838/7Pawm5Nv39oYn9klit/n/1z/b2UO3gbv9LIa3XDVpwlf1CflDHahpdi/HenT2hx8f9fgN19Whs9/eNqWKfz+J96gk662Gc7Ug+fB6jpd/zqeYGkPvqI/58GeP1aVc7o7XP0+YbIXPO3Hnjax2P6HM9Ie6TTc733H/2BRXcb4fW/4tP6c00Ki9pzhdAz2AsvpdzybFRh8WgP3fvLF6g1ObvuTloj9bPLjxGmls/c0+JyJBb5YexfM+jn7Gwd+ZuGF8IGnw1g/z8AvBQspbHVhw0YBPrn6z+daIBEEf9hn8LcCo+0hU5/MXuMnsZ/TJa5e7cXOPnh79uLjcw7eJnqwl33nVC682YvH7k/eG2/ZCUnbYf9m+V74gc2KdWj/fSZR7P20pX6LBhO91/20heUsfn/w1lMrxcJ9koOXazHrb/U+PGrhM4k+TV21vR18I351cVL6Ww57l8MuTJ6tWJ8uwLf9c4K2p5U36m95sJPwjc/Q0pbr444XPs1IfYgmwUtw3gsLJ1p1C1Dv9YdvJNbo//Gxk6i3sJaPGNQFg9/zB6vb2AxRgxjUOKjfus94Dud9YKvBwxfnKKztwNt3ua4jIHGBU9yUze/nL5/GmjQo/P2813B36bRPXz9tl+Tbx/YTvvxEe2iBYO91r1vTeV9zBuwdtoo/Z2XeJjLahsUb7BGf+eCxP85jsebBu3ZC3t4Af0VE22AD1+oDpfTgvPZp/ZvY7cYHBo9xXJPF2xGLWzPIehJx+nztg6V1Ka5PH5720xvjHwb75f/9WGcQhZF6gdbiiSsQAmviDjbZ17YnjppEhEE0BNuwp/7fw05hnzHiPyIQYtbkzC6eqhPp9jabvZvsC9bF6e6EoaPJwVYL1KeXCGvy8a/aG55ZtMCbLj5NbPbyVN2w1NGq7eHgCSdW9BKRH6Jtk2WNW/jkcEawny5XtO2BHMB4LzvS3qA9Bmcq2jP45MOS+fYudHVkweY9d5zf51ojuIVo8oqgiKEgwPPiYxdx552uzwciOiA9UM2HB2aPpnEZf9XUXp9iop7oFHxyQDh/70hcI1q97Lj4cBG1JxHn5X99xK8WgPZq4B+MWUtL4PcjdurPacls7zs20PZ5HhDvZhce/MCL18WunhjXjLMBHXGOfEdi4vk4ff20vUd8Ozb2YvOcwWZksWTOGm/6sTuLmNLSk/ZpfC++ummXRmiuHn7mY4/AxovV6FStESyogxO0iS+Nsn6f/II9WBmQwPNon/qQ/t5tPJrEr0XU6DJDYwZOFmdqGDvw/9jn3kTMg9ctT3phafjnRWwaxOuA3j92fOEl9AOb328hXcd33rF3ofNO0Cm5wLWoyU6RiYAkm0bps8aeYoHseDrZbn/eO/iBFY9eGlQ2idRLf7v7CT0Fr+gCv9Sl6/bb/b1kJdsIuPF7h+c0rvW5a0xCRoNHbVzUFr6J11iRqKD/jPitI2B7OT4ZlDWIBS007HPHuzzs4+MbgeKw84AeJ9G825b6mflX0Mjangj26wOrvJxKVv67qAmbPx8IkPgr9jZDIbftXWtrF4eAZ/BgNcXhWDte0YiAHe7wLhNsv7DVJvLaD+BtzAu2eSJ2Dp4X67bf61wSpMGzvXhs87JJ3t1lmEYdE4vlvUDOnKa9tcze330+bRVc13ae17UVR3Gmmgz9fTte9AOVffiEzrzaHgoUwU8muAiE1oLmtv+PdXA3zcTJU7RwMRsnsZFhnwhzWDyhZ5DY0avaMZQoT6wZxMoWXfVJZKfIIJ5pfkEG/eBXea+PaDXB4YvTOsB1B7zET3a3KTZ6x877FOTTh/PWz2vOpU/gXxeWScbxmsVzOroY8Htmn2STn3LGN+vZBaqO2vr8h7fmvPj3SSwjwn6cxM1Z+D7PO39/xfZYGrtDhtjV4LaWI44F/eITQnQoUEFTY41OyU3AjQ9WlCPj4ecT11iBo9/mG5fnYoKuj7ZUeFEsB3w+sFvOV1e98LpaOxxIzO6xpcUOEmsu+8FpHcRfmIFjbqJ3WkSTh08jE8/LSeyI1qgMPABHMW6eAt6TWzig7iJPL63O9wLFcVr5rgPa3xu01lRpMwDsF5ajT4Oxec4U/eJXiaQLq5j6QzBkDeMaXgLf9bFH/oSMYIdTQ+x4u9mmvxf0iJ0XZ1NW6iGaBF+3QPVFTBzY7YBpecjWDxb4+I4g6hZWtm2AovmEp2SK8JADeyD2meNPsolHS1h4s4fIQgZxpnyCfpIsGK9ldtzUc1sR51rMKb9B3BETvsavmGuQ/eG3ewhOrwzPfHNnPH+MU/h2IuPHc76eMj6nHrGo55G1AidsPNUG56T0DP1Ui9yQNT9EotYlsc74MdaN8/KYdXa5q3E+seAjcg1yDTyJEWe/5gjYGDFigRkG9km2dVqU0Lax8Az8L7yK+f5gZWSHhtH8lVMyC/MziQt8jh6Dp31fbRX/jK9+X1mCxemTT5vEmuFTcb5gb2KmLLLa5ob9bCHGwQafgZ9hbdN5SqMpfAsRf5hpYnWNPRot83ZgwsOaf/hzbftlTfCiRy53kKUa0YiPe8viEjVkOAs0uLR5PEzbc+fIkxgEVoe7AxWcifeecn2gjpDtwijmAw9crmOTxZjLRzSFN8PyJ/kaMfoxH5yfsViumz0CA4hFu1TQEYFcgAj1XXzF7gwjmp8G6gDjfcfYCtPlk2OTxOKzPYNyudPcU+6FddvsFPGibbjRvt5D7hR72zIDPI9nnzzILKbAZjAA7yCye9KjFyKSPpzNI89DLmz2d3jCCWY+IKIi7/jw+S8WfpGGvIT8OQhhmYkQp0ALXU3tdyejmWDsB6zSwuXOWYgRZjfiQ9BOeK/CPidovAt7vUdaI+d0U02A0+im1v5fIPxjRgk3W3p4ctVpHASNYKUlH/tisazhNKYTiyeIYui1WI0pjjWbxnssPNLkXWQSwCHZMDybHHmAZ0CbWz5wkKN9rj9xdmPVnPF8ZGSDldTjgXxOPfoumToqHdjAaz1i671ldKliHM4dnr8bQZu9Fx0RTYwLk1jDv15OQ3R6cxyex2+UmcSr7yn6AifLMPO+Pfal16GfnzwlLXvqT4N5EzMMkTwYA9sm1mw5xg+PYZa6PF+PZ5xnMO6UPweFskpWrIy2VGciN948ZHtmvLQ2D/q1ZtGtIP05IDo4wM9cCSbkgOfnEO1rXUQcmQ3rOJz0l8zUPDo8LW995me8hlUGocEAb6o5wZKfEv98skz8HT+5iIPE4q4lcoLgh1nbybfMR5YJZgbUDaPSylDs2RwEBkkvQe5Q/DkvLpWLENXARJFvHnydzPNHhLo2XJ4jIhenfoDl4KWfqc+0kkVOOv32qYX0nwP00mi2PYBsIdbOSVniN7zrx4nesqDk7IEfG6WvBvOwRxs8j5W+D7yEfqyb9JpXAb8FTwiyDehO3uwQRz6rnFYWqAU8nNAyJ5LL/WTXiQ6wHBvfTjQ5D++1jL9kXvWK4c06rQtwNsESj/iK6PMQqYdnhBghetzYwNbyQWhUr/bN7y5TAYLaMn7iNOzwc3dAs9hngYqNce8rm8fvYwl+yycrzqc9ZEOPOf6RoSXvCKjPswOGXDytPEzJvbDXxUrWqz9x9VjtzfmFPZORID8KlcpXhg1uauv9Hvht0e+WNwOtlQwqO3j4lgWvu0T+JZcoZ4UlhM/0XBN54wnFU/mmD6fjhREa+K7jM/D8LS5sH2gt2CqJVTaqSJHtZB20w4sGwWxkKDfLNu8QkxO/yJdT2vDy3c3yWA1WVZ9AXe8sfv+8cl98OyfuNbPmaQf7dUQRen6ecBPdFizQrXfIfuAJbwWcqP3BbNzajf9annQ5Uvl54hQ7vl6rIYvTLW8GKpM/J3emBnde+bElUjI7lr81P4U9gDkcVvkje8nKixXxSGgDWqkHMhQhyA7BaL1+spkpCAR2pds+m18tPDMoFM8pmzeJMi+fwN6dxyrzkSEhM6Xuo0fdeIBo7Xza98oH8i2c6MkbHeuk4FXzOHKiRI+K33uJhuQRh0r0wZbybVkmMm5s4IUzOUSrz6oHfuw1+5CZWa4AZ9D6Bev2iu1lAIikj3GTiGxmTVW3dTT4N9DdZzxirT4rxUR8crq39Hh4gCEfYl2Mej3euOC0u62xWTKi7Ws9Sw4frgNvOdivR6aa9fnwbBvNQ9RjwMJ1hb2jqpyztUii8JSfgT2DvaHuEJQSWdd/wvBYMQe9D3UIeLPFyhRvIfv3iVXAbPq0Q+Z+yHmpR7/vki+CMSYrlF3nFJxl3GclycQPu/ZYheFNj4gCHvsMT9D2man68Y4T6/1Ej+b18BXrfi9Wva3CUPHBf8qo1DJHww+/Khz0HlgvDAbqhQxr6/yOmcL3yOPJyuKXHiMFvAfY+PtU/pgbau18vpVEPNWQ0VraJH6AbOUD88jbDLkUvusjJx3Y/DYrYV+2FTp32Xqu2h4yvuBjG5N0jqYuSNbU/fIn1tSMU9YZYQ4X63ZrKETqITfF/33UShE94f1KLoL1oVpxhhgYf7guW84pZpWoIDxYeGu7+nMG2Q16Hp8NT5Vtdj+0NHZZ26ZSv8iah+sgJrc6DM4E171WIp6jd1W7YraIn8Q/o2EImPb9iDvbd/HdrYbwf6m2Z1tNEMGCME+Z8cGNowyBKzhx38m/GqN2fCE7hslZVio/OMyhqgGPZG7Omnx8l3H8UGlSP7a1Zzk98bBMi1zitTEi5vLvrLOMGWsb9UiftXXWR62InA8sq/UCVjhhhWWkSwbSeBo1JPAA5KEprZd1O3KknP3IipNTLLgXosBFQVqLtQCsPa+5qlo19w4fLjfCvz6goCFmM9PHtxwZGFgsWMfTeVOfL54Nv6GPWmhLrMKjocphT1G4nUekd1QJ9gpbyZoRr8rv8TuPVU75KJkWVo8Ma8mY6eHxqMS4WF94VSVZHSNHAGWdFz5zWbsfVkasNBErP+ORe8puasmb3zRbVz9Gbh49fPRIRHCzHlRYj5hNG7Yi6XdxvtQuUkt9aqqDwhtb7/BzHpkE46lVIbCuDIDVIj/NSjdYa8gFHbG3Ch9yOlYP/JCAAT7wxpL9GOoAtQRzJd7dLGzKIJk9kROxqh+nHpSbD4bEaLuwarjinVvpNgexcmEVT0+lD7dqgGe2moYnJzqf6fqIqCeYdss84I05R4/Y6XJZ5ghgBrV84GrrfWCP81gdI1PDS5+Br35EpOTF1gumDAB1jbL2YW10uXcqu4gOfPsjcy5XBjZeVNYi3xjrd8RW1VagXzioZz8iMeLXVNGKZ+YE8a+tfAdDqqHi9Mney7uSry1jKP52w2mg5jqvHAV5a0Asanpbi9iREe6CNYn6DTV7Mo1GT2xM7Rkn5RxVWEdO0vq7uJpvnHI+xMfXOAs+4dkCeoH5eUWzcv6qStR+XO6oPHHqWKxyGknJd4gRZIhnqExwTdQEqgQWLb+uJ96ePMhKnLH1HSrxrI9bqccS+L/DKgD2KXa6emBWQ+6RmBKi6lFlUep/1GTKMEyzHuMdnAC51bHWc1UZ/B37L/kKGT+jrTpAq436CqxoWRnkLK9jdqxuFltSO3FrqeZWeKHI8+uv8HWxsq96TXaUmqkoelgjA1uiqbPKo1eXxzucI9QLO5z3y0ureZM1VXP4qaOTyyUiEItVQ1EZz0sd3CxSPdLz+QnkiZwCM75hjFafY4VLHQ5R0p1FQfdYtdmyVcQRqpYH1LSDT5BBjZpzMIzV+X3zd3QpfIIqhWW+hrUcsyR50VKHYFVIDQCnWPWLbC0MgBqDyYlT2zNVeJLnsu9BX5dGaM1ykF1ay8af1EWYrBjehrr8KTJHlL15xPy8hXHcrO1RLXDU8Jhxg688oSp1tRbzLBGUKm41/5/VXrE3Vmc9Gix9NahXPSXDL8+mCkttJ+eIXIOq7t6l/kpGSGQo84CaVL6IqPeBqxeWSY0p6voecMWyCo8P/y7foqrH0wHLwVtPvQHIB9V6vqWSjbqDEW0bd/g06hRkjvtiZuOsijWypFeec8q3c/pkv/EVj3VbdjmqJdVDWi210kGmKX5eenKxmT4ZtImi75CL7YjNOO/q5YafbK1QrgPkoBr/TBVNolN8ILG+SkU0GNI8QkU3bzeMVvwvNeqqcQK2XMYgMG2J/LVPVmNjjdQcz5QpwlYHfPuDZuzDx5pBrFeNDWefFVCL+11cp8YYVGYly/ovrJcIE3yV71YDsVtVymToau+3yl7qoce4T0Vs42PLnhFiilhxqKa21n+VBtad0U0RKa5HJXs6oLJFLKhH3QI8uTyh/srqmx5YxgMGaU6Vk/irpabC6CnjiiXLrVnVfY34oHo95AuKuwoTPCG55HztLiG6vWY0cvXkaHCnsTIY/byaN+vdqvetA5o7mEeDE7Z1K9DCxl/JJPgJL7nq1dtjReahMEsyzO82vzCmgPZ5kq+slcis+q96b3DFra6Kb1kT8ybxqvorGQmizHPr1PC9+JZxlXVy2j6nyiKzFU46lTJqmluljegdRn3LsqLNO+Poq2Wl8Akq+YnjuSwBecdW9UHNix35lpytGnt7bVQ84g34nWknAj9Xz//dbA4PoLYHnkfODU5120MBR32WHUY8eW4fgb1anmLrAiJY9loGVTSlrlv2Y5pxq6sE6fF/RS9yiWXuScz9yCameT2VOHOK2HewzBPVr5IpECPsmpEDfK8SQx5Mto2IuUXpas7F/PItREzOvmrMcd+CiAC7qGoXxuC1T2FZdWJfXrufONfw/+9zESBcGfyqOn8V+3a7PHaBidbYF5Uk1MejYuFZVmPNE4l3Rx4JGxaxqPZRecueogja6kUfPQYn7rVXwkzzVo7YETUY4kkzKStZS3aFc6f6vTjLclyq9WAA4ACzb1eItVq+RQU+yo1DLFC/cdjx2zP4aqW8++X9yMLsHcCDxYq/6l8s5LIoN6NRb8PZNIvk1JAXZ6mDNdZg7TK6+hB636LfGCqXiCnPkEFSJwx7yZMvOfzPuI9eS4+kF416QjIpa69miPKTcuawylMltlkn2TSVl/fFM+hJDjmyfTQfbIYqvouXLnpRHSoXLSLlLNxOQLxxWcMVd5lnybPhsUHOL/H9fe2/MHJ54vAYkfuytohnEG+YuaMKkMGQu9Yzqyoc5ZklrwFhwkHtyJaUdS7yCHaw5A2wAVGZfLWq4Ish8fD6wGeKD2Uazeyoc/G0r0qnWwmCzWBny+qMVrHNy/D5ZX0Kj6Q21dq9ijKYHzoiQ8/Ujuy9HSgwUc9VgFs5Isr7/PIq1LtlWmQq6COL6uhp3dA6zrLKIOKCeXisVhAR9OSflV9itN2I6kaGvQbWQ63wqtjhe+V4fUe163gSfyLWMk8xk8U/JFZ/prFJfT4IFj3tq1qDs7PtvgHV5CJM9XhEjddsSMvHw6uhwsY2vkI8SfQ80+5g3uuPOVc3C3ZiN8VL1sgetYVGJfXzYieYgX3UmuJzRIb4ulL/TKSo61uozR11dDBal5tVWyJmE4GoVFSxifeWHVKNKfuNxbYit5GYKi9yW6PJ0tr5lqs6UC8nfrB2z4pRAbTH8LNPB9w+/fzPOi+aB/hwGb/vcgJECjIINWOwIu/t2IKjs85u/0iIEbl5PSfInqwj4tVXyxIQC9CsbnsEVAXgtUrOP+pqrCPjdUFQr33i+p9YDaG2dXkV4pGehIzskSUjd94qMewSmvbequW2FiALh4YErixiVDC5FQT1sdNcQz7K7BJV8CHfIW5mLxVxvAVn0Cx78vO6PapmIva4qX8zv5b7VYtl5iW2tC6Az2c3c7tm7Fclm1BHt6xBmwuwy4+ac07QVPGoTpvzMtRm8JsqwfDV63L+KsFUtcEqLG1SvAeyuj31KKBu9xDsllWnbUzBuqjK1VU7W3H2qeTHtD3txH+1tksctyMD3whmy2P/8jEHVPsNdpo+A0gGS9igvtcq6lKLRZQxEpG1Ge9ULNvpZqfPZwecPJU1bljredTSgzQ+mTowgN9oViIGA18Nu4+3aAFr1Kr9lsuC4hOMZTLAeC16yU+Jw0v9CSyQegw52NgBZxWPWCmjYvXhavhBhrBn0X/y9/cqBuGg2J0HraOI5dw6rEiV+OVJBLWqT9jqAbZqLrvpsefLflvRw5asLxtVHxWM9K+pErQjpsROIIQyLshUENNLJkRtlRjDSMe+26Egr2XXAAp86wiqAshW4kwA1TsqQFB7vuPmaNZVeTtOxFHpBGKZW202Plae+VEVxkknhuYqE1gT+3/xLaL6KScjz/Zok6osjMhEGTzSN2We4ZZVb8rVq/ZUz+MZfM3WVRIS77B2UXdrZTta4Ru1HDML1aeR/cZaVFLZVX27YlE66fGWVVSyGLsn8NvbblZs+6hVPqIv7MHs5u4pu/BZs0bZyKlRY/mC/eSW7dBB5dLTWXrd9AB29Ex1ffy+zGFUeZk12PVPrPxEPs7KIHfmd6bZ06deXYUMPJ4nlDzF2hBZQOzPfWQSwF30Ix90Ds/tu1yqComJelryNau3j0qebQ2d3SRTVj1b973ssKZeecQDREbV4695AWfWzm4VuaprLj5hhW//r2cTpZ+/r1cZ8lTmQWRkvNc0yrP+204i9cbX2sXY+Bz7rMXVfE6ZTTwqOvDhy1jAWuFDYn7Kjp/b9WxFzw4a6194Xaz6Bck8tx8cNsPJDK+1JP0bpwwsao+YKkTY5n3cNU+QjNPt6aaSwnOWKg68fYGH7aRQ27ZEuXG1OdfsplWkt1S/4DOdQiPasZP3ql5BnqpAr56Q6MlP5uWvQAjHbwQ/wyVS1zjv7bLE3jyVngj7wuyqvopx69pq3mQtiK1wpMMasR0oeKer4iPDvSdLhG+38rCblZyCKoD9O0yQOFczf6e1iM2cGaKCyyo5TyKSt5JSxhFQza31O3uBCGidRX21WELvdHkDe0asc3FCL9MIg6r+E6uoYXzEu6o8v12EqpqtNYAriJV0SWz6Vs6+HBortoxWol/ivjWOq24iY3LyhnUE5+ccuzbIuG98F0fB+hLpzDXGJ2tk74kVGSvOfBqqLdULDztld8+6tUu8nPuizjZqyPmum6+pkLRioo6Fcy2Dbc+sHeL2sOPV7S6Uw6+r87GD2IzMLIZ3uVyQehh2ZJmF4QEus23V0g4mohKdxZ/1NVH91d9yIlgHPR6dUO+d/yAzIGfOm46rTBYDqEUnEj3yhyoZzMSxATLuWA00Vz32NNk1YB3TWqpMtfybXpRcachLYJkofo82KV8xVPIYI+SszIvlSeS1+Pzp2oKLPi3HqGcdHM7NqtlrziL3a/VE3IvHm6rfsQGno1D3UbVyT/qtaqG5mmp78L1q3fkcVSjDuo9d7a/KMSsd1rXxpXZGkKHnagA4TeousOeyG93pQ1sNpyoFOq1gFOUnH6u04jqj5+tsCjkNYgGWBtJ4xRtwjEfNrfndKzMvb+Y8CicjqeZ9nMqinoT4axSQpdGLYmn2FVoTDPo9ujmeutyaOAREASPhNJ6tpg7Lt0a/7DTEG0z+rh9+zB0ecwQzaKrAxDhUB2eIFW8tw85EOEx3Vl8qepfRcpqHzKE7i449quxUiVuL+fQhoDJ5Tp4B9vXV99Z0wgBr9aiFkH2ypq8NcPpkGu2yVEdKNqRif+o97PJTx05eHKer2V+mQgk9yVNyMkRPslq5tWNGttXYGPvwD9qz3U/DKr85C9y+lUo732/cxO/ZJ+7ME6fJ2Qe99dIqfNS6iHBkC7HA18yaeES+OcnOpjUFcN2+HWoyBuo9VFlbs4MDV6NYsgFyO2oMyJHNmPAbZT2XM5KreVAhY8cl76Xqxrlkqou3nsSM0mzayTz2TspgqCjDelWfUuE61pHVDHPKthwOcwPulAO7LI0vsqmf875UlcvnkIv5RvrSYWeE9QJxCHmEKg41aWBIePvHWrY6OnzvE/tJOZuqFOg5DfnIcWKba3KcHAKKWzdTwObleOXefTbnILEXub3h+FXPXawPqpcDA8u0gBNe+xOHujKnnBET8Yr21T6y/XJ36Fg27Lc1mmMvgPq35T6il7BD5+q+eJelllV2SzUOliwDr9Jyu5vgCjkHZ0eAJO9cC5VXqij1XfJ+nxUKMZ7sNPuoFstuAjE263Oc1sgzy2jd/mi7WdV4EEHwiltuVsX4UAsNJ2xn3FYzBk91hpM01IGAmVUPqo33rFmjlzOx78l+ECcbOFdE5H8nZfkM5GLW41i925k49YfWE9kFczq7POwtVdl+JyYREeQwb7eOsym0GasbKpP5fbzozUCvfobTYZUWfsaqt5ViqgmvGZbxFA3MuXNjPNfutZ2/F/eS75QKQ57KWUNyFCr/ZUIesxVitzV3a53E96Pfk3+73DunbKpH5RNYfzutjr1FYBiV1dZrVInQi7r1SKX+08keak4+NX74WyLva8bh5JDyjIt58NJ4jFFWdfXJ1A35uz+5E/ymzJK9ZtiSOJDP2TdC4U+GU5LgCsh867WbwNNkjwCrOkW25h3mFHgYPDDd8e+wR9JOZH8iJ+ZcI3sZVNo4PeB2khrNxQZEhNsRaccH6yxr5/Qtsx6nUoCNj75oOcvImEsGFJXeMMNn//vfL335/dmXup1/ihuWivtb+vKw3092F3j6urLxT18Qtf8pbuXqa5P6X7ukUdxY1VdN//4v96MW95IV9+cUQpnifuOf8+ifrCYI+uqg75/i1uvfp/ktP5da3EdX3E9YDDjrq7/67w30C7De13s8/ZmrP6chVCE8+n3y7wgVrry48aO4ZaIY2/f7/fTfuxTUFyD1U3VhvhigU9UG0YP7Vz/n7KftEt3vSfpfd5MCxZ0DxT0txZC7ouW+uOOoB0P3yrR8pK/devt//Ta7gNq//8vvT969HUdxf1dfN97f2I6puI2tuDu6rxtf/Tv9PNyQU9yO9ft59Vt08txXtLIXvWvV5cDf6vW/rm4Hrf2ySh8/b/KruJ+2gLDFDQlFK/LvadnNbq0pbjjpXe7P70BY3IheNPMUN4j+fvBuvqWfvJsEipuQ+8LjfsLBN3aZp7hHoq8i6/V3Dbsg93vOt//ewppi2ndxB0Jxi3Uxfrevfe3dD6vaYKW/t3+nodvvJ4P1713e7l0D/eLu6+K+6x6T/fsJY4b6aoFi5fvPhpt9tVI/cychfQHe5LtY1X5rxksVt1IUJb1+Hnan163K3eH3Ow0u7uX+/b36SRrY9YV/7gKWNvnM3gXuqfg9/8beet8Z8dM7zh71n7thdHGbceEm+rrBgZ3MfqNezzWwE6xrtXMpbpn4LXOftRqci2DPA3toSq6Yud4rwGnq/1VNmvzWoU9Ndajr3+e9WEmfrRPyvtSzn7BhcXHLx8+e/RzO8uK9piu23KO2nMWpb+fbu9Bv/bKDLcrp9+2fHHYZW6J4WdxI/FvJ/hbuSSvogAJ0Fvfr9hBt7KHfi/ExRUtzcbtdf0K/adOjxc2KBaFc3Fn0WzFOsefONWyZctswHqYtinaF4maevpihP60Ji+K+lPYkg9/HnvtfVxdHi7vo+0Tg94KFt9/YHSCLcSd9DeHhd1zVfndWvhqkFpPd2/e6Sm1pGz82+fYHG2sYUcxKL+bH91XKrueH1+1101YbgrcP6f/bKetvtdvnrC6o9/P3k3RgqMJ6uSG5f8AZ14ezj/rqiZdoUFI0ArUH6Lfo0RI9Qh0/zApjaasLJL8nN770mnAnTzHvv58Qa//0WuzUZDV808m3vHgVd7bfrl8Py+wVOK8n68H7Pfz+y3vhMXofuWHp95x4fj6/DutfrHkPgilu12wfhRUVVr2wmdXf7v42sCjaFIub2QqA/jPS9lor7NfytB5Omd6VZ9v4WE7E6uJuPzmRpf/XxKp3Yatdzvn9pn8+WD4rMznRRuEWsf1WlTXBbzCJvy2EaLI38ejj+fsnNwrgJVp8VtwZXm3EPAknhU+4Z/M1Sr6sHn6Gf225QHGTc3ETaT85T8I5Kp6wCf3f729Wj9PKjm/O7OoBAf3kREwi/oeFsHe7yxLFLeK/J+GMd9GiuNW2L9juz3xYkyY7+veL3+y9eD5xyMNu4rG1IqLn5pwOvCtnak9OMciE+wSKoavtq/v3m6QoWgqr9K4PK9ZA+fe9fdJ3y14L6WdfUb+JKe4p375ZK/b05WRhk9yK0BczsO/Y2+vzHHa5352bKPq6DnzO9RisVdth9NWHN/U3B6dg8ZPw7V3ULASCHWQ+/Lm7Q/Th+ZvC7lNJNOHtpqgs4BM+M9q8nvxl/YkXxfvyCdNT3/RZR3bsFky1OVkvmO3Dn7Tw/ff5hQ2D3/BdNNL3wkzOcr9Rl4vaU/Fne60JmlpdiivkjO1VfB5Wtc/UnvzfjdfqQmNbLxbIp/WIhOIOhN+fRGQsuR8azNnPX/z54LsevLEelTiyF28RIlFT/4VMs6+XIBJhwws8/IGawEsLb7/0BpOI9rLvXezvSPryLXx7IwoI5fbbnFYss4sBxR2PxcUDjZb5HNBXpsgQv/TxJOzIn7cUofHJfBcYu0KcFZ8X79UpU/sf7AHPBqKgENK7w7s8xLjtE4IwfXdi0OZ0tGSkT7EIFsz5cKKJsAsUBFLltpaOtpMV4wxinx+o+Bw9Nn+yLx9xqvi0rQ3g33pkW6OXiTd+WB+fk93h1Dzg5yaLi9utG5OzbjxnkwLFbcB9RTqnxlh2iE3syCSaGC8mz8+5mAckwzPsBWZugrvxCdkBseAVbT7s8scp4ASJLZveLUZsFK1WxXjizpiMaxMfjifk1LzsHZkUN6m2B+g3akKwPw0v17bNiIR+BpEeHvsTU4kKyB0+z2MRGfuZ+Ql3vlVDWz5TRIc3+LRk8Bio44BhNn6m091eZ6LAwz72yd1dkCjuTyvkg50J9kqCirn7qGh6LO6o7HShV+Dx04aZF3H5xkQytYhC+xOIyJN/3U14FSKD31sM7Qc82XbO+Ne+LrHX5Ll+m0yNGPGyVk3w/TYZe06JYfBj+Opv+Mk8OZ/AM2/yl/1x0q9P/vRy5HHY6hD1sdddlijKnMUg2kJs3UZKHiQq4ySCSQo/WZuY9RC718WWfCbY+wVpB5xTWOwh+3aPtNtj9rrFutihiJfsfnMSm17pHJCTu/U/nIKFHZoF9P5C6hXDs9qfFLEAL81JOSCWMjsmT8f3LlDlagq+cZ08wOa7yCBE++w42IMbpRp14IvYTTLc1WXdxnKgUPLllkI29hNDksvjjXtwUmf6nN9GQZMsuw2of8KKDbDTgh8IyLYLYMW4zCq//eBnyDG5qa+Q/TXL4S4Qv/gTdoI76Irb//rb9YE8FRY4lzsIui5jEFEGdoWox415xb2Xv08A+eOT18d5ecxcjjmdHokd8WmJC4Msm/M1j6txxFE8ZxE3weFDzE+U5EkYUFuM3CpuWuvfmeBAbMOT67kboC8QxZIL0m+/vCkZ60dsZZe5MalPFv7ZHJNz/Zm3yva8/D4cAj5/GusHzzywPXPwT8TuXuBpyeMa+vBp+ByRKqvxwaI894xrya4qGRZ44+E5L8shzvlAAmRSnDJusKyIFkA4q6Jv6e/6WIdtbojl43+WzA8ndOMV18DHdrtCMTS2uNexPSEYkl3DS6yF/+924jZ8oi2rQQaxW2zdyaVRD6TqqWevl9m9kQiPMWQMXmP9x9nEwsk7ltzCi808oFNy81d7g+VY903NVfGNMC0te2p8yOn2bPJe3f7aT8XPS/4Nz49dEaMRZxdX5vzeCL804Kz0D7AT3ArbkWiCCohcPGcXLTrSmWWb0XDuHnkzVhtcDdLby88ncx9YtRkHf+cG2l5/vM0C1bDaso7ZImHy6OGJBrfHeMGnca5jXF4gCvPf9rQMhu6YBWbmOclltiwN/pObdfvtyNkjHtucIHDUZwQho8HzXB4DLLd4L7z0mvjJ7aqKwIkR5AWMY+v8kZPLjnRZtLiruT+Z3Qe9i1GHHA55ll5xmJuAtURcy5UBd71iMHlOkGGXDItyfp8XrIUcs8iPDmfh4Wl7WGFtEcsLgiVjmgd/jqfaPRqpv0WuGPQLemx55e/5ibMvn1aybUS0LtvXlPk8MlT4igfc8hC5JpYDczuDNxvaPOg6rBgIh6F1zSqAWMyP8KvyD8cIbs7O2SlyMRnObHl4cIWYEDsPyB+ksUt2EfxP3J+bOHXjSz/n5jn3Z9Z22RusyLcYxNzLx/IMrOqCPT6RHxDnECXBQmebkeHzwS0g7QJdrAVb/vcu7LtIkjUc7Ah5aD1HFtezj70FpM1pbZl+ezN8/mFfRPWPKIi3+1xDUHFkPsGxrwiTXYNPLvMmMFLwaaLTaf7+gFJg1ImP26gBq1Bw5pucgnJXZ2pEc95I7h0cwh3gxYDg4sqx9hVmsqC7AaOOV/z4ZDGtefScVkn6+ec2VsqUwkKYHVyWmwhLVjj0LXjmlhoXxbZmbMBOWODQu4JtWuDY8ZoICHaaRBAYZu4GLNrd++2wKP5ecqRk9Ju4/MJiwUIUPrCwMe5SbsRojYDKEXn3Ix4wL45nn4ymTwethm3CWGD8HFDfkP2W78JmrHdsPnl4FsCWrIzejEytDwxnbXBqQFbYoXWZj3N9ZMb0LWZtnCb8+S6yTph27uVudggcdeQhqYDIpJHfUZdZYEXGqXfkJUMnRny+kTkasZvcc4qrXSt5fjPWkpfD/uE8S4/nU5F/IQLofbQKZpYkOwEGJt7NafbBM7xWedgRedpp1UlkLj+Gt5FZJZ7i2SZscGFRC6tgRFEh0+wfY59YAu+7rQ6UTN0nn8azmd3g3471LGxShC/b9mCfz/RbRDusiXz+kWmEpcSLUpuYZeVIdCSv+MpxaT9wvMSd45pvuX2shROND5zyaaDBSTaxSzQug1oyYPjnrbeUfWWFxduXf9MO8WBTjtR3lCPC9kDUnzwVqKDEA0Q9YtZ6sHDt5DtWGaxWYJ/4Uli10v8cOTQqX8SyZbXCGsqR98ATklduOE9uCi1Ek42QwTyfjKucLT6NsyMWfUHjG5v/QMhDv8GawzZs+GquFekTR/6CVcNyFDs+ZUHLWo//F1QWIxcIkPhbYsvBNxbnbnqWt4wN7+67fHpsnupogSDAJS/RO/g9ZlJwAmBFeLCNN5hUD/crWy6DJI7Ck5BnLeuJLYipyACQ05W839JOSsaD80gNCJ5kzyli59u32YcsIijx8/SR6X94b3Pwx1PgacL2QCBU5xkM0Rwpn08shjmkWaK4Pb4YTd4rqTcjsjwwHvC0k6xnTfk0PCfeRu7LSgHIak+rGHpCYpAZNB5jHbNIMvrIS1s1k30iz3plQvBvrsB7RPhySiBJ4521uRdvCSIiRhS1Bsa9dUYjBibWH/DbtGrGWTPWuOOgqZefoyiocTGq8dqKBu/+We+zmmCmjAdecjt4MFEfu3/YkdJr4fmpuO0PD0MFp6hWFAw8I9Uai2Lbcq1Y1MWNi2iOtcttgsfmETu9cuy8qTUsP1M+jVg8PDswokT2efxf4Ie1ZcitoLG/WgJRknUrWGJu+W7g7O9rt2AnfiKDR9yZ2PMs1tBKrmw/THuxDnuyStYTI2/PaZpxHUB0rL88A1ximasWSGl7Ooa4LqAmPIN1IrLR19htJD3El8v58O5yBZfRIo7o00Keu4kCPifZEJkUbfmdc7GGkUn7n6+z57VsR87zX2l0PMEiq0guOvPAsRUbaECBdAMlrQnuAAIE/Xfvep463QMbNnBx0Dh3n7W5yGLVW299Ic/IHp/ZeKZnGN/BpxviBzQzNn0dbtPU9jVrpD8uO0EUCUQBY7MWnz8wBt73h7jb05kPSKw8XnLKem1XRhTNX2+RL74hSJLkyE376dol3xffBE8/9MTRNvjItSnoJawhb4cnnrIl6j2ev8YrkgG9oE/0m7BxC1y6YCr2Nr5z1QPIHkyIbKGs4G6O3Ril/jLYyYwL8Sf2ccAtzC0/Dy+KtBA5YhZ6PQBP7VXnYwflOV/9CHQUJ/KCCYlPHbODHj1K+e3099p03jrcMezdMY4mEsDWGEXFd4btWeC6wwqZmF1bBSuCPwgHu40abHUssoffkbd9H6xV52JxvkbowA8wtDSGqJPltnKjQxtn9BBP5zV6BZab4mc4Z72PV2aMd0F77EdWp3ly/ItXqZNJlsPHAhopIK608NCrzLVkgFsvAwxKNOb74o/AhS5w5oEVySpIKN9TLK3vzP2S5V7wBiDbIVOHp09kPK/WGQzGe21ZxMtfPeZH8Y5m3bAb20gi+Vdr6COLG81F0WqAkbDpa3oW5qhwE0fn7WysJD/V3rLW7AmIaJEjtMy/Mn4nKtveTfkBeQzQyBhyU4t/8y3ovWV2E+gCtmRr3YzxEdE7q3kJ7DuaE8yQu30Z7teQX8LPJWad3kR5P72bjgjDRsrJ65MuNT9rE2OgeY6a0yiYNwif3fhO3wjtrDhQloZ8Nn3eyw01H0CsGOIlo7ftO7Of5teBNGQviWOeBJ9M2Anu+OLcj7kNxrlCj17JfLhZvBcSuPX08Q7WY3TeWMYWORtl8x2RIuydPL/Zelt+Hnz46HdjceDGN7zKK5s6U8zMZ/QpXlcihw/SfkSMMB5KuHwv+IdIa16xIgwPlmhj/SnjL/QLeuxdBb2go65MBdYqU/+Cs1De1Gz4JhdscH1rGKpjzFqLjO6dZvKYpQDORBsvOXaiq8dIx8JGP2J4dtv4qXkji5vL9zK8s1bI+rcoC/uLfQEPb5DPgldPfJZFhsbKZXQVLXSMcqINRMgh2ud28+7csnXV4XiI+ozkvZzO+ST2NOXYX5G/6JRTQBO+bXPRsa11kWrjHXji+kdyO2Y34d0wnrCwMZ83a1TJXMYOuO+vegkZEPGiJ5f+MtrmNkNiNAF8gscnp53biBXWHK14jEBNbTHv5d9yU453E72Ej/M2UyeWUOrAwMTUzm72mHdHEsLMTDASPsWqcriKwcG/dUSY9as/iRzB+awrGmx0CtoJJQd9e+Ah9dyv+wAuwq7B3u/kOURdU64MhH+qTKVuN96HvvnScrHnxkTkGYgBGem4bRGMCsleYkPNIAK1XuPO8N5kjZ6lFpJ9aoTJ08wvkj0zJotf9shwbjko7g6RiFe/b+npy3Vw4y6/ARcZ64HFpRVpoQJkAE1lZPMVuYl+5aUf40faF5BGyMnwjoMn4MEhD5tY/E7Zad4OvmW/nfECvzfkRjg7dpV8nmP2BRH2Pc1CXNopZKPzdtC34LFl5hhWTw2D9lusfMPaZXvB7IBRYKNd+JvrhNhY28ENNYN0iJGMArBvWuojosNepHKibidiZWaOGYDmxvsEOC7j5jLwR74LDazMv30LXLORaPk3maIBzmGdRpObsfQu4xFrtYcxKc8diTVvBwvOdx1jedrlBI3DSBx5jxvysciDOVpmsxhtQX5gBZf5PK8S4kmZ/2w2O8wMUcVlPJHIyDYbcBpTRibVTiC6ffRbOR3+b77GRuExOBFakZY25pObE+R9zcbnjFK9FGBUWN9Fbh7jw8s7ALnJ47HzZFPs2ZFEIhEpM2MER42EBUcy0RULL2DL2V4zY/UE23dWY/AZGKT2rSa2xkz15ldByI3iZG9ABcj51cYZSXn10WTb9G64BWgYs/21lVr8jiNvdTIWzXoHGAAlTU92dd67XpWxM85I5IaMsWOpHpPBxls/Igq0ygmzsOQzyRN4/WmEQi+YJyzPC7tPVGKHWQrWdKi1WGGjX7Jk1TNEjrb4hHxyBnHVeSFj+ozoCri1fTvf0ggIlg4sNLRlRPTwsveVT5PhXEaXsAuyiEiUvDqSvMyKx/c8rPaIynbnb4tskbGUpZGX4H1lMIifLrG3GaHmyLF+4qr7NW9Z36fjEXAyet9WT3COYWRBTmnrm2iP9DexpMh8mKsgf27k7qh1fVP2AZkhnpvmCT9aUqQFHL6ezo81yoDFB2ObWYEtSLP4zH3aRhLNmTQPhwjmNQMc/GBG4jGmr3+HXE2jUSKNEOkpUaBW44PGSWUUzebipI6xS28un3xhyIc5SKCU16xs7NdcMgZ4snICWBkqmA5VG5usmDXMiiGn0QzPVw5HX6AzkfRWRCbcIFE0e6jEEs1Z25gv2QvHHBt0IDlLR47XCLUIQe43jN2DVYi9rkVmOBzdloFhhzcZs0e+0fwHMwOxF3m8QWbweseJYMKxpAhhmuONNSTKn+bes56Fxt5Xy4IVMFbe+X7TuAnYnnWm58iJWGuDN8HwiRJDdJTRc2PcSx8KmyXDbyaeOW9qe3SC/LnsB8zhTrEHntE1Fm9GGTeoqxjkbax7kgkBH+L3MXS25Bbflvt+jf/ihYVeElqR2q5ttjP83sa3OmRUMgKt8BjvAqaacPLLfFcz07DUXTWmz2teornK5jBfbzo2gvtu3NP4oChFZkNfeJqh8SgJnCm/ISaYRNOW3h/5gQtO8lAVuJf8jFH1If/JLTM/xJwxPJ00Goi38rhOa7KM8xrxT7GfyAoplc83nmV0hlssfjavDM99k1G88MjWtq7wGFeCQ2tW09sKkk+9MNCa+TnIJz7+2uJzcmyMFZrPJp9gZuDpXAt8KCxIe3nWkcn9ml+BTvDzVnDI/i2iAKFXfoz3GXM0IsnumeHP3W+euVeC/rxGh2WWRCMg1Wa60LrwgVvOUB8B/dn5WpzIbQYANqyzytFX5hIgz7BMR+9Mvx5ed5HfuG5X8x0+zxnBqMtvn1c+AbuTYjyYE7PozfSQFZHNAFHLs1GBlcZ5yWg6ZAwessJe6zeXebx4XnjWG0+QcbB1i9H/PMd8VzK79tX2oQdO14+A7Tl3bvRWO5Hxsvo5VmyZEzLl02pnrH+Ec0v4k7WaZ4Ox7Ai4dwQbN7RWgdYVx8qosyr052MuvXbKnM+OXONnvZwyFgqJPbttt+gUVtbq2iujAjawZufqy7DmoYYnZme9AzKpv09N1qEeLWXbWOfaRuLQAzLk5HOug88Lq7NT22Q8lL295jKZB8vK5aa6eiuNJLI262rNiQVvg/OXUemtlWwPTt2OTyFK6Tyc2hPqhXd0rj53zQgsnmaa8UiVjVHLrrUMNaRcGXLO/hP5Sismll6nsSfXwF7BJFC4XrYDfWL2KdVnesTmB4pmp6ysXAF+jbXG2Z4p6LczftWTl+ewt+oZsgc9a2N/RlSnVQxTT5DbZN0ieNtqWSImeTqTAbnCnprTixzSdr98KHyWI6+IVYWXSCPsIFiyHWiEUZicW6xs83a3q8y4uea0I5OP8T79IxDs7dwbdD4WeZqlBsvqXTA2J79BxsUme3l19ikcXfMk6h/RGozQ6PwfbsTQEhHhSrwSbgTZpLSA36/5A/m6w0jLErPxfOz17exWOQS/ETx51DbIv5WGaOZo9KL1R8dyg2S2H/P5zUbT9+Tur66r5a07B1JOEg4HZoac5HeYi3610fxbfti4WKMs7L6VFNyCY0xExgbkZpWuVTldH2pkfCp76nOe6TmKMa5RA2QenC+OwlLnkWGgUnWbgcO+aXPBS4ssjg0Plmb+k4fzGiUfYiGxnPV9+BHH3F3jiaz8mqfnfe+KJPgl9NIy4qPFwbvf1sgcYz3eevg02F2w4qJK96g/l/fdTgX4hmGOGc80+m8VAzzeTuuzrDbi5updvtbhWp+IpwC6O0NW2RqoxHcId8CoFjEma7WsRoGTsRaGSrT9iA3AgVPN3HVY6CV9bVCBdaZpNU17K/z+Uc71erjpsB+3sQ2WQguLPBylYrFaayXwu8npPY9v+ohvL4iFu9C5hey8nIPfhbQY0ei44VAnsz8i9lrDK8P8iEVFZWh+su/W9ny5iZ3vxEnB6R07WpijlaIdbkqwD+jzs+y3IDtqpXmzrHLmoAu8A7B67taK3D6zamVLzJ7quwYCMW+E3Dlle3U+Bogr1IHqar8dr7ORGLKBJbJyzXjZa9+G/hb0G0waXQgW8vPKWg95MzMJsYDTmgu15RW3GxmBJzRL5xXn4GWD9puHZz2b9XQ2OwhqW0+hVwJrMa00l//E/42u5+KvOMfOg+2INvcCtGCE7lo1YIaMeQXmFVv71vljcOnc1lSXYtOXPLZ4El13ZIT65ib7BuZXHhIZAyNpNW5n1GAxsSZ+XjYb5urIRZBXwCDb/T5dx6FlHNxBOXxjTDBIxiWND3ZmJnbKPFhjEOY5gxPIpnjNuOioh9FYq1+XlhR9ZQ5k1zbKFsqCbvZcfY5lf42/YKPZz2lfFOvfu5pPb1EbgRxSY0vN17F+E1T5Km9915BJV0hd/LlGQMyClnHyW+Q6rBm3D4xo3KpqtZy4DnxoFj2I5eh3n67P1SJo+9CZdpKxXh4tp7QMMaRxIiukeK+w/lEbbaUJPKrRBzsPGHfYZjsknIA8MCjrWmdNl4BpFYnVCn4X+jnNhHyMIXKPZIPh+qgcWSJkaz2+ovz8284z+iZiMCopjCzAa53s2gdZ68n94h2NbRG19JRhopLaTwZCFOaUDTDKA0ay6r/xMN9ozio6HBuxUkva7Bm8TeC5WC9A5sBjphA+1DSGhVU1CrytWGE3iCwsq8jN710dVeFdDjbR2iWzJc01NSfZ/g9hvBgLCCqgRoaBT/VMGVfshTXF1rCDoKwHtHZPD6UrTYh+6qvqs8CP7e6Hg72mDnTv9rKNuWAFkCUtO9bnyB7ocZuBDMO/b2erohmmvDRxJfs/IJlme55m/o0uqdnUZmgbqzLhJI+5l0Mspy2D5WYl6LS8ZlwPLT4+u5z2FudzZ7XmagPrBTr/lggCnJJ8shVex8hRd7bhbi49Ar4XjvQao9STsqrXSknfaxoHAV/xTKt626fr+gXuBXtufe4UR4l+zaw4ciboWPl5tIG56y0VnQmGBuDuwOTva+Z5Zy+jnYhT26VKDzqWFgFdCr9nbRp84JET8Oc177pRKNaf+JF5BbJz113iFMwxi46nw7zBOTxmIFiJjC0gnnLwMXd0vhyMnD7OUe+h4e0sAbYPPR0R+5QL5R7JJin5V4YBO2VFISeF9jt2hnnkRuyiQGy0/R32XNu0zOUwT+BRd8HDUEFj7xS0wStTccy+MH9enGyfK7Mfr/4CT9aL32pjEIURMbGoNWJaIvs7iVSN6lpbCtLA+95WwcDVb9Bp7n5rJPx6C8AJYYSRfZCN5HSulQtWV6FpzRs0okq22DpdH5HYNdYMV6YsmW1iHfE2QzuN7cqigM3USOgEMgYXzHYiA0tpsSqKbNhFbdpefeuxqvYls2OJ9UGvMU1QrlEV+7qYG6YVxjqblaFdXsYLjFcaecd22K/j2JPEflneFxmGqc2V86+dUc5BJm97gq/IBDZJ74xYsxEH7zu698g7TaOfvCm8/c7WV+ABMLyZBsuqajxiK0Qe8/+NPyJ11tcPrZvRUqNO4I2pN+GZmkPITm57MRkNabTGCRoxl/W9ejFya3LLImQYYOQB1LoeLRT3iNzvM+SxjVBz4kbbzZ0z72ialaFONhbQN4K3a84Q3tIdOPIY7DB3YXYNLxpVfwdtv2S/H306bBDySRz/UKm0O7ecE99W3YLDicscs1XTk5oiQP1r8JX5RUip9ZhHbCBm7j4GrNbaCm5K6DfZCwtLd/R9eLvp7bAuUpbSqli9ZmIr5vbTqypfdYI13fJCcJL6ZddsAdBOWIWBDTrmRKm1zOVImaVaZ8ji2tsNu9A1qjIzeC5YgUOG7XqMLXZGpXyCyFOsgqWwJ489KOxQJ9OoLwyTeWSq8ROJ961lLPKIEIyucr5mmGhJfWtrncgrIHa8zGk0TmQWjR0trPmSgWm/yc5mRnxgIYhRHrqNnWE2O7gar3xvsxeMDlutLL6VKcU3+epdxn03C0utaJ6JuWqvSBKEYGWZTKwyYAQTmZE90yMzeqUXfM3NE3/Kb6u7iEd0XQPPP2bZ+Xsk344Z014Bcul6ynZHtM+PCMH6KaOQ+lOwEESC1rW71NBz5NTMirlGk2W6QAJHO2LcwZjCS7a2/BvaMl2Vv5eBNC7JZ9IYx/z+l2/f//iPv/3xL3/+8a///O9///Nvf//z+3/79v2//8//8b9+/PzrP/31x0//+Y8/v//XX7795/d/+9mfHT9+ftzLHz+TKFaCWxN+LukXmPQjSfLRkhqLpJdA0kckqStKmPWkQ2dSB590f0kwTtI3MelplOQCJ7nqSVeVJKqWSGjiHSbx2yS3JanNTbzVpOtJwm8lvV6SWrqkxiLpSZPopIR/TTJokghbkkeQdGxKKsmSHqVJz6SkBi6pRE/q55LupEnuZOLJJZWOSS/VpGNHwhUl0eykG1bCkSSSnqDLpKI0ySlI8naT+uakI2li95LuKcmZJ2xuom+SPO4kuzaxPwlOSbppJr1Uk8rUJJ6T3M6En0uyD5LOJUl3q6QDUJKDk/QQTfKmk8h5kgOY9CBJ/P6kG1Bit5P7l9S/JtWTCUZIujkmdQxJ1kPSiSrJlE86YiadyZJq1CRqlNRYJIgmyS9IMi6T+pik51BS2ZB0+0gyDpIM60RXJVxOUsmRVPkkdUVJfWTSiy7BF0lnzaSDZmKNkxqIpMdnUgeTVIMleaBJbl2SNZx0lk2wWOL9JNUYSWVqwsklfVyS/IIkizzp1pP0pEzY5SQTP/HSkrhNknWYdIdNYhSJn510ME16uCa1KUneeuKPJj0VEqyR9B1JsiyT3JCE50t806TPVlKRlnR8SWq1E72YRICT7jiJN5n03UnyBJP+DUnOSJLXn3g/SYePJPsm6UyW1OYmvdmSGqmECU56fyZaM+kNltRGJP2cksz0xBtIok9JLklSX5LUAyXdTZL4Q1KFlnR5TOp+ki4+Sa590o8wyeVJGJGktjuJwiXYKqkIT6IBSQVqkqub8JRJNUbSh6mef/4fOhVt+n/ozo/avJ//6HhXs1hv/fzolku0+RJjqZ8PPw8/Nz8/Wvd8FO9dDHdctim/jviiib+jxRw0dT+f3p8/uIV962fy8+Hn4mfw06cOOtQOMhEGFaKDXoMD32jQsbh+vqw+J/pockMmN6c65fPz5efi94N/X37u/98e/YPx+f3j/zY61b70x88A88dkfAj9W4K+EFGTkT7/Lo4i6HITgwEDwXBoKkM//65W6VGZKjHLsgfdU4Pz+HhZNSQmKl8riAhElC/28V6q+f5kKC895YIetkH0NvD3IwsDRNDsPvxNMTkxK4/r812MJah7HsE3zsqICzrTBpH9oAPtZ83V6DwZjBFlvT5IqNrQT0Z009snxmEHGGmzHUJMY3r4us/n6zl0vo2gwX0wuIJOgJ8dqHcnF+WzhhoQQpTq8y41tmcW+o1RcfnPc2rHpkNnGd1B7Uytp/bhslfl+wf9VQIpqQbuL8986htr5Bh9p4Mc9aD3y+ddxuiBRkGeT+B9fPa51ka/l9rt2pPKRw26bwWxic+p13qC0Qhkzn9WWzsTNNlPxnERA41kCH14CozkCQawjcqKLPmpvWUg62Qg32TI1qRp/mT8TE04qXepJ9PbPGAjY/KmUTcu6N7w8Wk5qc2AgdLFUS9TT+YzDAIPGscHw5OyMog+zxqcOKNQGI25+0RqDAaVHUHO8Ocz9Y6zKl8+K9/IbY3lgF+tQ6gnMHggFyfOkMjJsDciEUHWZe3V5Szq54NcFS6J5fiEstZBxcRn36q5/yxPIehk/tn5ampfL8kTarfL3nxWVTIcjDcD2X7ktt50MjoiGGVKt66gKjNgZaMmKdWu1rgdqv6DHmiB7/95wus9YmcWZ13vS7XI5x159/AdD79Jv7fkv5BB3Vma8iO37HNWfk7Qd+hzIWrQ1yxuMKgr//zfupv0Uvs8p/ZwVtyz5L9uiqfPAKHjfWG4TjK2ZzLKYpYGrxPnM4y6LLQa8OSBh1VSkV9DtnLS4l+pYywBEbTPahlQxDicOdkTpGJWFLLet1ZYnlpMxy7yjdQgBD3DA2Y4qDL7PDnQErWeydCCmXwG3RWMM6Fvz2dPXjRD7Qz8f9DvLui9+dEMC730OB6vzqi4iFpP7apjg10DQ/LgxGKiJfATg7ryz/7WeIlA+1FhXQLFOSa7VDoZ/+5zpoPnvDyfwWkM1ZsMXKTWr/QV+18yEIwZo+f85/d1f+nU/dkf9KFnhFTTobf2rZ48ONlCMAEfW8/XXiz052Yna1VoBjrtB7kH9T85hVo5NUq1hnpTdGkwPofqoSBHPYjkfr63TjzQb3Mr7ZsbtLjdfOPmphSn/fmM1qfeNPnbGfy+mKigYjqoYq4vR9prnXQR/7zd4gRrtfE6lGtxspwL304P9s8O136WyayfJT90LPysCunF9hGhC7rI1ufrrxj2RhX/Z1X1ZKqq6+2wp3XriakFfb+DXKbS0rUq9ORMrV6NpYmBTWR8SDCmi8h7nSCSObGG6DfG+cyNdmKUFHVYJaWTtc2Szxd7gZ6vyFHAL/V4tmCQEpzY565NbQeyUesfFSMLOg8HVWBB7l/AYgVoKeDxPoccrKp2ic7hpatBCOiWQL9VLPJzl9EwL5qc4c35YDFTKX3Rky/WDStQaDiImMR8fTI4h++aB7vAQLJAw8zinGMyRIfs9IAnDyp3glqkoDNAUENRNgjZu1iu+rm8iZWdVVap9taRVwfpqvz/IP5SyIS7CWo66FJGGo+NtFR+70casSDFyddAuMvz61yU6vL96jkTLFTvosXf7JL2iMG3cNclmAvcwsmWBBJfDrJbgzzkstd1jgNbM7zjagZ2g2HwUfHoqElBaGPkrfZk7CN6YYXoroobfqSa/WF4EjknZTX4RiSB8TlRvEPpq/rGysn5nAj7Vn5vYQzu5mUNC33IeL9X64M+cZ0VLQpq7esUNmihpHSANyqyE3TqCzqEBx0yg/yBwjB197FNMbUXDANONAC2ks4/QWw6mIMQwbjNmmta8sMKAy3HLZ4L+1XsegSj/gbDyWKjARxJVWxIEEsK6j3r7otskTeGymNPg9GDZKgWbsQiL/QYe87Q9LlB7wsskWiP0/gc7FFnSifGzw6jGSY6Vsmvbki18w8nVbuBlqYv2edd+FksVdAFPbafTCwF48ALLILKkMmBfuPWV+5E4RxQrlqCoVYvaCem8s8tDiQk1eTorvr80AIyFmtWrmnQyae0HFqXdVbFX5Sir29BRzFUj+rmz7c8oq+6X8e7ubHUYNSBfgPnMKkniBRE6hOJABdeSeVvFF5FS+M98dZbnFn5vZ//y50N1rlTfVW/eUHOeAFEfqNcCLwt/QgQArYADZapVerTRGawPg/4anm/8NHQS1SplFbHp0t9EL4Xu/aCXhjsl6t9MXDsy1kftQfn6AhJEM7DTzQ2UaHPCh00BQa+eC54DfUIfKLavYOl0OMrxjvo6R3B2PWtVj/Y69Pvy+0rPBMVm/usEFtfleNBF8HPytFsDGKnrv/zdngZxYEG9aRBxW4wiaZ0Bd+y1eEg3oNux+MohqUwqmsQx+IpgJAvEgLCJ2u6bHqdGlr3KBsVjQqqaUq3s8P6AqBxhknTAySYMeR47/pG8M/gZuEFsG8xlWfsO7greD61XQUowBXomdneGaeMDBe3G3Rk/ewS+nBgFza3gxGwdPkIOtcVZiiL4P8FeU5G7s3KEindzokPbAf7DAaexaoEfaVKnhOMCn5O7Cl+HyPHmNRTtqyekN4XbBaYgZq7oJL3I5lIQuXAlz+oh4UfDZ6ZjaxAfezJCxKo6HkQTylTg6widYPbrb56H5+ANmYkW1W4B3mYhQNBIHwLQ0OJAdWa+b8TPQlaTpAkw6onZ53c6+SUk2GlQ+3H4D3ymYM+3uWhyAYstBDWBM7hoIEZ5DmHbIm3FUT9KKv6HYFln75jfaOy+uIjVJ1RUJMY9B8I4qGxtJ6ihcQ6M6qTXPHCDHXuIIREu87EPoJ+BzzPPGhvvACqt4Lu9x9EMdS06MMJkoFtYBzdTHAL47TJRK3hbS9IA2uOJkeHJ+dCpVjQUf+zq/gvrJ+eeEGPvjIpL94xP+V/sIDcpqEHN8U5nH4o7fhfU+spM5Pqc1DBy/6jLfHaqKcucdOzgEUBF3EvyEUPOpbXX/F8bBZ4mIqtoJdyvSO4fXgufG89jRr20ufcNWwNXjZZMaVz8OLBXRVrC3q+xVajXrzCytn+7NEVsdSax9WnA3sHXiEsCqzFwNMflxPELtDD9rP/npr3HbvDSNqoKEJxXwPrxg3CIuBf0Hc6iNoHtR5Bx9SoqcggeTx3GLYvD2ixb+BD8JWD4fEXiFzXSgaeLP5InV3NCawTv8g23A62LCvD4fNTP3fi18OJDb0Vz0gGb2oRwIr4aHhPAyRPpXChJqw2XFnA1TD6d8BMzsMeiutAJuVMsht8V8JO8I0P/h23IJ+UFeH+snL3rbKkarW1P8gMdZ2lw/kNNwtLOrAgTMor1oV9frCqjca5lfAMyhuYc2gFGP3ITKLPKbTF5z7CpQw9QbREZcKUpyzbgF+T+nSgFCSKQYwTyx5bXMdq1WPYKaYnBF27P/9zyXugZ5CEF24q4QZBvykKqr6IQVfSoDNevYv/F5uiNt5iP04NXwO8QdZ96XBsOjsGtpkTLQeWjlckBtKAczvt6YADYdLmbJkRIcCR1nvNp71p0GZyjzhZPHHy/INIeulhmKKjXmLH0PZ4joOzpg609AOMAacceLvwTkxVCPq2FR7AO3C0au8bZ6o3BFONxt4yNqwtsHcpz6PtAxnG6RuH/lTnoK+W/Jg4kPU0kywTwi5xy2KJiJrnVD/rycKio3Xh1QeyUVNPQeyc1KvUBThQvaq9xlKjWwJscJBt+LRBpCBhLZLzDRhjZrgUt4NXwt+CAcYVkcIIYafGO/Up4HZCDaCuWPgp2ne+nZN1aCseKL2Uy5PFanvX8EBf7CBSR41w0Le/MBhYZehD4ZWjDeQhGZJNpW1pV9gtWIKK3tVbs3L2UFs5sKcpZwK6UMbgN7bsK3o7+Jn81YBLoZtfMPEhyCEsazvBUbDQ6IQrtoSBZOcTW0On2eKFkBlsa2Vr19uVfTnwqBVvDvo2lBXG30n5YVaLhTp4pviYdActD0guhefgz6Lrlp/kFiQjsRMrST+Q+vVgn2EFL94Tnhf3lO6pwWSKoC647JqcP/7+I+LVvuNv1j0KkczC7jOelrrIkl48lw0DY6SGVeHhjoprxvIctZJibCM7HR3jBjHemDz2KOMEpsW/IMIypiidWM8jx8tZXPwUdM7ijYhejcsnxZAibXjpHEZquO/JwGZ2ewbofRJdIi6w5UgX0gVPSC/NzxciFTAYA2wQYABqf4KZlaUB8CzEKthlvKFZPaDKBl1uJVx6aw+w0GOEZaC3WclFrgZeGLsxZFQSZgMWCD+dPngVxcC3De+1iAtu3/sIjlIL4f8yu7PeGkngRsO0M3OhMKGIFEmTwQjuFBiSezoXEo7GG0Qn4+CXNXLjZsEaBR7o1Nav5qv1sPDZ0bGMGZ6JnYIVCXwo6haDSYJBB5igCv6j5YgdLPxKLF3qOYL6BpEUOgnEEWfKKhNxoH42yE8OMkiDDq5lp4x2IWkh04sfDRPOztBLrXAF8ow/fsRg6Bn8lCD2MeGUUpwW4EZQytKygM8nd5Cen/XWsLLEEUBoW31+XCf4B05ygO6YNBFk8pfvs/lGbjrxUDg9uhAEsx4qBsQ5vnJx9UyiJxObHrAuzEEoza8WhWdG/39x1/BLyb0maoBPQZ+uYIpZ6RMQkTHKI8MDjkpjedgjMBhINaqTT9CfOcghjN2cCVoO9M4cqPKmuQVD2cNeY02IxQQ2KLhNY4Po8P2Zn1vRDXwrNA/x0Kyc6ljqfPwLeu+UTjt4lDz5gJfQCWiPOUFWxnNhZeOZ+pjcfTxrdpUe7MEchNJ18CrBfcFq4P0ttRBcbgEytLrSZUyWv8Jrxp7S/zmoGAq6JQeTdoN6zGBOTd0C7IVIW4+Dm165u3HkB+AcgojnNgNhg4sWMfTqGRXMdAiyxIO+qcWnyRtjyyY4U35JPIAXr08ky8FKgp0PmKsJCl1aan1VbjSdH4r1hfPh9mEFmDpXb/Fw1vByS/4HnGYsaYoDYS/RxrKC5gwc4zIw6moA8wFAmOQnB3N+S7cbJdGqom0ShlxNDhLYaFHs+yQ2vYxQaGvQ88Eo9Lh66FgK7nu4Y+SHBBzdfIhiwDkwFb08O/xo8xbQFfBLE36PLrKx3YetLeYWP6CvZZwIK6yfknrWU24W/dyxYKwzuB0OcJKlMI3pgEZGan30ao20EnEAAyfvOzlxpvXVE8B14hD0kl7PKzOGftughePzzQmBd5rsJx7o1ApP/RrWgAWhi2Ys4zgP5y5XD1+Rw1gzmEeuDxkIvIDZmgQPC92Yenwyq6IaGSS+l15qhRLRycTrOZfw7Dj3DPQPPP9AtpcZOAP9tmUv4VcTTQie3/pZZEpQSxX084/V9w6OBb0xiM8yqzqYthNU7tTbGaFD55gVAHIGGTILNegAH0wMr/WDRcEYB//RqEHggcrswaOmWpE4LBVbdYvhQ4ga6+0+YsXj+jd+tIjXvwU7GUE43h2iq+hAeLkBrzsfcxjMlADdmUuAFzb524l/l0/HXPACjFfC2GMLMrU7ahU8Dk95pHiGuzaNV8pmXzgW+Dc8VjRGgAGYxVMeIvumTQRtVr+aoLt70DurJAcdcowjg0Kn3Dte0qO0oFeREDTJXGps7QX2Di50wDlH9W8J6u4L++E9mVcjL43X9jaTz4nIsBFb3LAcILRJXtC4SKkRdqzSksvCvtPVv3xGd9UIuxYNDcY9hZ+hx2PdVnbpGI0SFyFj3DhjN7Kp5GwsbdBC3vy8cVskOYnP0hUt6CoQxxwzER0MQODV5kI3+leggrhkpGB/6f9TmXL8BKEFJ6VPBCPHNI0SB2SDb8FTGIt4AdgphvkJRNjhYegEVT4RmJx9ntwy9p95CuVwo2PD+FRJaXJbOdl4vKdpROMBIw00PNKrt+h5IdvEFAa5fPQeDCZnBb2DyvfhXeA24XCoLy6PDP4TthYUtMy22n2PLneHHeCWXTlbMhKJQI2Uywo0m7qOHZOrITNtYOWDzISQ4SFySg+K2HLp+FBUbVcMXbSgN4r+x0MM8CRILx8x5NZSgxBSZpK9CvhepP0YczQOWOthxkrxS1he4wVYJfgfsj2L6YXrMKKNV0ge5rxEvR8jQUoR7wJ+2MbRyCvIB78PdDGI6DGtvrhZ9R7+lzsDi7KNXMMzG3nBy8hGAuoQORBjVWhaMhDoA/M5ZeNNdS70aS+/Y3HrQVkht8nNxVbiHdM/tvQ8+gEmEAs10a70qw/6TMY2wxNfb8Jo0TGy1uZZE2+FMxSdkjM2yNALfPzgOXSTKCsGAoGt2kT2QREBEqB7diy9RXT7fOTrjkwLGsDoJ17zNMfAmC988qt3410zj9EM0lAnE2PlzhIxoddTubMBygJBHaMMRBivfgrs7iY+pb7SY5Ijxf6qG2Ueprl/WIqLPIMW1nzl87GqRJ+NV4KI4sg9wukhV+OAnR7zKsGlILRBXlPGa6QSXXFFXHIySj5nJ04zSkU20eG+o4uY+V5XRLklWkecHSu/zRmGK6AnfNl0btmUwSMGBHo5qa+NLMGHb+NE7PmUPyHrmHyGgCGf3NwJuzU2zDm2b8u4HvOjkIR36w2hN0Bc5FEs2DC6/Vekjx0ws45olBFAIqTMVCp9giXCTsHbTxm/KccyjF6BoPC5YDCCGBZ9HSsCS4QIOTHOPtW3xF7TjCzQskjP/E9yQefV1wMzvCIZIkovrCl6dZmJAb80rnkCWkxjmkgCvMfkpJZZNKOxPUz7EtvI+MFEecuIek+wEJnek5hLkBG64RkGmUJM9a39f0GJMrqBPFwQ6cv6iSKJnab4CsnXPxq+O9IFUgXzBOxK6HGQd5fi8DBbAGtyYKsG8knuN7OzY8ucECWkA0lQvRh0ZSwfDTzD7snhRNsIduaRhYORCz0146poVLLURkczuX1mRxsZxxcQuyLzdGAogC8n8MA44dOZ7Slm8NYbscKLlIfH4jCPr7ZKRg4vlUx+5J8O1YUNlGr055CVxSqBAV75atHLozbGL0af6x8Ns/oX9xcNCfOwzR4h2jsf86OwX/gRQZbmNkcClmBe8BLoK4kLzNT/ekCV6Hx0aazOScbjwwZhoyf6JPXKybQcxzgdNsKcf9Ds1LsnyyJgDMbyhhqlmpwFnCfZoUsUd/BwsTtzmBVA3OdV3ohoyJaQSbLQrkwPDyZxB/P+4nQ00xwzosnY4kneUZBXmXou2Rw4zBVomfyiwN+coOWlv3nESK9RM/AVGbzmVpEzFnDFYY40kkmnr3oOGhUumuhSLjH/1dfz5r74+MQmtisJfGTQBRqSLC+mMBQzrM9lDBEsDbavDlTBDNPyYWHjQS9YGbqIB72vS9JA72hXLQ6RqYSHobNl0dV4DaAF4xfy9mRxp+wccYqBpo1hJQJ35Kqf9QGNPoAEyAYJbkpOkTOo0gxec5KnXjAcC1zHNJNhy1eDrnmjQV3DBH0xiawsHe+IVwhTxLzjWjNxB28KFpDYXJL/QJ+N8uhhKfFksU1BtgAzdkvm+Svu8iN/IjsHYpnmzL9aB24ZORvL/G1O6m69VFhHNPaQ07BCxzx8LI5MgtlET6No2Ak8CM6O/qgfWYXHI94a8HtJlmBo+/DvEk079ebgXRPcPuB26BcUdOAvnTDRvYd7h69EjgoYlc5mtfOcO2+xzEfiW2SBjFaEWhrkfxqPoTnJUsPrX+YR4bstORm4tSGTQCUFU7cqN16bjiRoT9sf5IyG3yKfrO8Mq4xNMVeTO8s0+WL+5ath+bBBRKmSmMjAUiefpzdmIU9QirwiEo6lC2zleNWcMGxkbAY5tMzvjqOvJIdMjscU7XPWUyYNT4pZrnUfwULLO3hhw9BRMgZkvZI1FGnVABF5GJKhT9ERNKwt0Z9JHtQEH04wzGju1OotGAZsXLA/Qx4GzyVhVA4Sy3yf0t5oGDMlkGcZEtbA7O+Kx4Hi2AH0f+pHv8SSsEp7tL1ASuFdU34j2PlH243tU+dzc2HX6XAe9Mkv5LnRh2AtEGNnxbDbqxlO7viRbcbuhDy2ss174RFfGO9s7ISnTC4lUa1c6lUraEDaMMMxzGoGWYURKyQB1JHkn8zmbM326WiacR8kxDwusEpgWzsvfciGIYGdy0EEZxvT1I4j4QlDGMYv5CIG/tfF+6jfk1ezYEXotBbMyQ1mZZbkGwWYIFJsIvhHzGAMesh1102fu/UwaIS8oNeoqJEFsGUiq2eLrESGMJ9mI1vREDIP7pIWSmsum4q3TqwtzSx6ReZ44rJhYGkqfVKOF2w/YeemuT1E6Ma2dsDc7CuuRnrRhMN4WRB9k/1Qnl0buJpMJKa8lV8p58+tF5thy16jBrCvxO8Cviutt2Jv46r/jQWbR819NMsFqaMDbe2blh20aWVBGEcAmbPDaq0BZr7iikfsbdSPvdJfNnODO4jVm2QmL/1fdPW0enTKxpjr+BqjYWfgM7XmMORh7BjWbnq/yIdPPCm6PAX97oqbElOhCYl/BfnYw/xtfW10cue5geKMk5LhRueN+unJIvMwq2GNnvmWZviYKcEtJtMvzAEWdcDR0fE1tlmsMPaTDE8qn8v3NyrKKU9v4gRpoK/qPjLfszxutLc5yZ1DWO8LtxzEdMbS1yNSvzuHU6kO7qkeBzJv/eNrNKe+y5g7t2mSdTOtXdLCXmNzZjzq74M/rdSAXZxKHf5LLDOUtClkT41hpAbvmKgijC4TNgsDEPfEs2DldBovJpO9IoIDdl3gpWHe72tFIdmhR9RKxAEJOY/VuAOta0R+wgx4W5ExcquW+QCwuLG1s7JzsBlENplSXXoY/KY1CSNr/O1rFIwnWNdGPHeZ64sMLzEkHg1adKlL8adyWoMGJwDCLzqj5IF9RtKSE48tq2bVJxhGRs4KOGvl4GFChtzozNInhY+C+xpwLPNh50EsafaR2RTkX221eljn6L7Bw+A7TKrnJvpw6pn2zuPFL/3TeoulFr1dH4HN6sxYPDsZGPhATjPIExvWkut5oXuXdRnmQA7rR4wjG8HhBpFbO/F8k8j+3rJV6K63a6gHXkydCBmJdMis+w6ThlSAk7exD+MOei7HSJw+iPnA/l4LYsUH2Qt+Y3ZcYIEH0Fr4WcQ71jUCoj9LZgL1xTnVk+B/clrm6TztARJgbeRakNU5ec6E2WAKVfFgL14wXJC5kQf8QN6sMSN8RvpJxjYj1NgfuHchb/TTLn4JVAM+fIwKWT+O/0Il4LjWwW3wlbiR2BD+ZpgzL3dHFk0ZKu4d3jc5yU/n88C6EMfhhqZ17vhHgQ3a+H3RVXj4hkj+JAs30QND7Cevu6z7ExvLK5rvBHrXEyHGOq8ZpOBJqhuYXFx5CEapYJbM2bYaC8TVVdJUnPFzwBvM2xbZWDPYyUoE/UfujrVX5H4vK093M+RGRdWxtTNWUlwzM2GuaqpLoTLe7qi18LnkebAycrPLygikMc0iW8Z62H8yP4mb0B20zi7xcS5o83AKsFL4p/jRg4yvSPsGgNjNeU6jYFt8iJfd8Vx4+6sV0DrA53T+A3Gx9t9rZ8D2IZPGGc1l34Zj3BAEJU4zj32AlrFut3tfgH/QAF2JYL4KfijxhZS/tefAq7/8iIJAZaA1sozCG0T23cQv255XdmYOHAV6WN0OWzLIvGX2bvksnPX0ZoFXO2sLT8o6dGz3tA5ocivNCcQ6WDkIn5/Wo1nvNs3+xTuwgp5467jqbbQu3jpzkIOZWZVKU6fQmUXw/FRCjeP6sTWNmfFx9B3QlnGUXnl+vUKr/rE+cuxo8ok3t6gtYrpixYD4LvsGyGyTgxTWYpD/KZthHZCenVbVypTHOD4aw+ygR6RtFgrr3Ob0YtMfo5/6C1YdGp81j9d4NH4Z2aTneWUAiA6Tx/XI6HbdoggflFt3f5jdB7rYw6y2rhjlFEAFcNcJtzbs6kCu2la3UEnBRLlg/mYhUiymeeNY2CPnQE4ImDaGGH7Kkul9o/nZSfM5ycM55vBbPWGl2zEXGqS6rDCl2gg8uamrpfNqicbEQ6lnmmunRwZDO9TMnSGPLQZpDJkTay2PPWfg2I3zUql0jLmQO8fEkEKDD1yK+7BhOYiLGYciIrkb7SNRPG137pNRSHnaB7QP6mYljWSs+m++BZtLPcWxIpL8jY6FKZPWlfPWy8pN7L5dd8SxSG/AZR28J3o/lnEDr+JNG1N4rMuwijO871olbD2+82kGHtsBh2O3AXzJJO+d3sufNacRTFhu7lSzjtog4tT2TiHffg8sL1hiWvNi5pgYiThaWvspIz2t4wMdkbNRwWBkAO9SaXlkJNDDZA5bizrtkKA/a1aGPtTVJ8WaqNWtOpdzk7OC9aWmb9opaBN/gS/aVo6bDeiazQXyu4i8j9d6FvAwfNqyctaacbLUEgY48T1TiwNLPx87sciW+C2hXcCC+47gEBjsbbU79drMDAp6PxaakofHr7FmubP+sJIw8NQFj9ndGAJvEQ3Z9gv9rO9M/BFGd1P3Hex/6C1as4/9ZTJmKTbsIGwG3x7kroT1EVbwPcajsbmPtY3h+4LbQwYSRuXRH0RKj/y80VJQHPYIbE+X2roK8qXG3eQ65BjhQNRyaAMwDHNI654in3ZRYH+w7MGtpHNpITFiK6ILvCrzfpUZ2J6N9maOc2ketNxVY3NqcJX8HHjZG6SXeIJpDbiRKaM24PMAQS1ic/PR2yWORn+nEVpYs7JfY2fIDHyasSFY3GEFPbk9YV4fGJKZPmWzjOmgpWXS2FWqyIN4ynz19ex3JA8DmqIqcIoczPzp7PdmkhMvjxgiHjS5ScOs8qEl5R3hVSa55ZOdnOSEbN40kNsFa7e16d1pKuTi+PkY/QRd43GQ97XlnMnumGrXzh5Eh8NKjel9BxcNI6rgWyKMAZMW1+pgdMXUGtqnwigDPUBud04De2Bh1cOeNehx2ZvI3hrmR03ri+WNkbpjnaDskN3VuEHmVXZFP1W3IudXP86oIp6XsRKys5gGEssarpQXAmESNwz1M7Y4yJtKmTqQeS7r4sm0Jz44zfPfMlHg8yvLgSSTQXT0K8G3CV5aWOHdcQTZpPYc4Sv05rpj1YX5wUKZ98gKH6u35MNBa6CdHR3hgmM0y11+QO6OKDOIgpm5patZJxhj2SWA+4XfMY1TL6PVdjdC54g5wXKb3Lk0b99o/uoM84Ncwa7DLVgVC0MYvDWdroM5lYUx2HnkxP30NIn0jc5B6vzVic1CyxGpMcps5T5aa9q9Tb/gETHaHYUIUesH/TiqJvEv0nzm1i12uVl6Q9y1q0dMPAJ2wk4j3WOtc32JQ7EP2OKp1kJLjNmcJPYIFkJGxZ5CVFiEeh68uuzbQPR2EgnaZkfwmflYvahlty+K+UX2JOQElX+0SuLx0Ru5dAWeBVIa5irgmR7RrBIFN7v7XnDiaAD9F+tD8S/2Vy1M/d9hbh7YLzo3kkgBubtEYKfdh6zgcOeXvL294LBKcJLTXkxY22WchZq+fIynd+UsPgvSZRT7EZO8cp7c4u6oJqNlFI8bZ58BvoU4/sBbH9tbT8TkNROj8/fU5Owkt7W5VtYPSglzRJc9Fbnvj7FdnvaIBvHuxaLZOQkLJINvCz/5yBvYT8b6dPPT7KG34HnMS+SNiMEdJHwSe91HtAaet2uW2bAiCiX2NVtei0bERwaYCovAlxlGnEXd2fEsfTFwi31a7GbgOdprRcbJOjuQGLkEe9rhB1y0zOHHdyB3nZnghcewFHwShLmsoFmyYeb8wNRR/bes7DBjcHaviZIKGM6EmWTGVtkd4gXwXdn50uBkcinxAZmhEHS5L3tN9GEaswZB2dcCHAUHvq0UnupJuQL7PIj/uS/k8UZYcwQzv+yvYvY430Jdz6AqbcMBbuICo3sE4UF05R17fu0CZPTTODV8xWkJRJ/AEA65C2ITWNttX46uZNRnMX+Y+yjzTy7HNubyGFtU26DN0Cd5ZeNrnw/9f5I8tGW2PDt/uoMcuQF4T9v6FDOCXvPSiSwQsYrdkRq9KjDJ1X9HnonvmINnRVhaR2k27zLiDBoRQ7blqneEh0zyfidIbAcZYvDzW90CctvWpB8zB/BQln1p1H7DCAjSRe6uGfK+o1mO9uGx5k5ctGU/OJ1pbSm+iXkgrHY+djKxT4J9NR8ZG60GuAXmfHSMEm0Pe2aWl/k57GeauWHGFNlN2yd3Dy7YbOzX6Fp4fFgzCqg0X9yjtDb8NYuA+wJ6DPn2rojHbzIi2VES63rYSSzChB8br93k5C3J+Vl2LuW9dveVxRPpjrUvJ8i9s58nNgt+e4CC0jw3vMiBRO1hB8JXBgNdd/Vf+GmHQL0G68jMh7F3hHH2svsHxjvN2yHDc67uJWW0C+TD3RFTWVuNR7zM5UbGFrprEMubMAOb3L+QHdXzpV5vvFbK25vR/o3oW27c0Euana3tt6AbuXHYmqTTSKg3jvFu8DC5FtOoqHU6xx4CVrFxysa+X7tHcmvoULGNHajN8LVTHsn+Xdldp4ia4a2/ejdE8ch72URdxzWzFA892qvVoiG95M8Pc6hgEqZdYsj8OUpR5xDq58KzmVPqXcBm2WeM6Oe+ZpjbeUP9DGNm7hnZgAlC3qmEgMmJuYzmu8BpYIaJnEz7c2LjRqjD7Q9jzI4sGm99tFzx5CNOVm5BMpwdliufzmXizsLzWI3+dnaW/oicnpFB7BQYAx0S9hc1SxmZOep59jnMZyPfmKnB5VLjc5HBRQYRU8+KOXFn3HlsB5I5zeqhQnPI6mBx7IRDHdmwvt58HjUA/dP2V//GiaWDrzCPyzhR89LEH4kQrfaIsZhwyPitwc7vzuJD9si5HcTKk4yyAUKY3m46EuxlZJzuxPrmVn2afaGvZK/ORpKD3Xhls9mN7vZTp0OUZxtzJ69s2bfWmnHkJ7edJMEb2MS0Gxi8zV7ene45QCSrmeSNNsb3eeQD0VTIttnvy4pR/r0bdSgJ+KTE5tL6FOOGXQ8rey+zCisirntFOERswdiP/eu6p02d5mNvLmNSxiXRutiabU4LdVvTrK1t3zy0nyjxymCHbIPnRZzRmlPQkR1ZH5kBoj/Dbs/ky6U2Am1gNxWYja2vB/JnVlRJuP4mjBYcFN79VGM/HRVC/lM0vpFS4pjIg32k8cLm2x4crKz1ffiA2Rn18MnormFvOjB22rsYOxX2YbuiL/wI4pWPfQvxjIxKp90dfd/u0YouJXtNnxr/OtSHzfnYx5jPD5GqnJsdeJAEdOniM8sO1ds+h3ZolAXtXGt0IwwPdb4rO9LNN+qV4G9u+8ri58qN23Ucmz7s6doeutnm5nWAOa81+8Snujuleknbofa2Vov4Dhh1whIM8tyOtd5k8WX3nsWuDaNgnAKVL3Nb6WC2mNmJ3Ds7p6EJT/cD5PT5v0y7jtUZUGqVa1wVLsguOrAKoaepH60dOehe/EqiA9veLNwOpsgFc72LnzQ6CXIw4oN23eZiwRHt9uXBGGSh24cZ1npdO0PqrcPgvY0iiKd0V3lkuLuTsQ9wYrCOu1GiHSTI9nHN7PYki2O+XbciAsejkcOUAyTLdFpjbi6u+Fx+WxaFiD86MztXXG1MXMNaAzufLPtLEF++1i+A66xfhtHdr7h6GnHDr7yiI/S2tUL2Z9BntHOyPrgdILX7dgwg0wxWZF6ZYT07T9YuteyblTXeCPsuwtoteYbHDiqvFg2UblWO9admRINp7fuXyhj+LxHMuds2YTuMZds7CB1lNSLVrEFWTNp9nZhImuNkL30zdsSuxlLlCUE7w55dw0yYnqdQuyTn81oL472eIkwZlQevHzRuxiy1IcfOujDV9ra63bkIWeVeXLsxoyHtH4Kl3t0F+jF+8bJC+Dfwf7hj2OVl9w/kDaZuH7v6ID9E8ca06p/OD2aB6stTx5eysmm1KehCP6ijQt2PGg4BbDOt1NaLsYN3sw3sFT5C2HGl6/uQKBkkd96c8PBMYZ/sF4eu85S3yAGuAA9xw42kOFn0e9XbbQUe9JWRJqwk2ZV6GfZPTvsOkc+P7VvT/icgfHy9fZ3+YJcJoxveI27csUccf7vUpWY92Xfa+jhw+zHH3oqwnp0BApzGj2Br8exA+NuuKXqdohQ7CdtVwP0nKjeNRKsVe0aJUXJjx+Zl4VO85tLzdlSBMVG6jtfYcYD94IfxuL3LViI89tzDL6MKI5ezP+wPzwl2L/rmwdhtfAf8nWWtNFkNSX7CuMaGzJ1uhlxOj0iEmSd2TmvEq+wRW+EtrLNuy/XIir9IO0ysGURgGyIjie+fZoaAe+d2ZoeVCOnzuWXKDJpkdf4AK/dOXblf3gs2MoxAycxgm4zMEvFP+9KHXSCsezV/G26qawrgczyR3Uw1nAneU/dfMtedeEHXcfNer343dXD2gujaZPhqskzTHOOjVrEXq926rCM2v9f8anvtomHMeLfv8dAX4I2sk7XuwB5ZVoM+1o3qS5q7qIR3P1s4pdB7wjc0Nsp9n3bgoUuANXSjY7tInT0bhxHPxdthNeSukVKYw7nsp6FPDcYjorfs858iXruYiqCQSW7K4GfY2yG6pgNu0NyYoz6Xdcd3aJZSncw5WrcFK2UtibXeYedJbr29HczJhKFd9uILq974DJh52m+5M8fMy8Jqi7rtfYSvmlZqr47MYm3BOdYUpLXD2nS7ystBwdWb1WCPVjTANG4OGp9o1ElG+qQPxu4aPaKZMociBLv0m7+6rfizQ4IRRnJIUm2Q2j68GOthiRaBc7IzwYwENVKFY3f2ECyff2Ut3rXbs52u4Ra21crmRsIlvk6VktXv+ly9YPQJ+ESGk36tAaJLMPl+rOlGDh9jf0Qi7GoOTktqu5Z9ibfVr6yKes8tF21vWys9rZN6W18RbUEDv+Yxss9Oj7LjAbGk5VwGbvqy1zcZaMNKTzuN26/Aer2eTtWd0tklPDU7rqAJ05is1UZGFlIc3rVsWEy7GZCjTmb7tMfObS2BHbRyBHxileJwGoI1R9bgkKVm/aN96rpzmty+EbGlP4jfZz4MmNP4CEzLxGpn1xL2PAh2GN9nyhh3Jgbyhndv52cnYvS0KTtQ2cvLHCc56qMGw4PDU7CvtXUfYLPpVIXXake8gM6dQNLInQ67i3C/dtfa8zQ4nLQG3xyY12os4wXgBPmHbZdmkM+1jx8eYndI4x51fxjzH/pEDnYEJtCc6u3e8nmnPj16zaww9XCxs93VEyTJ580zOVpY8lfthwPGOPiAzDiud0RK7UehDwh62XacdjZHVwGLRuBCyVuY+oPmxpAFYS7cawUHZz2MT5E5Oa0aYD2yedZWE22cx54neLvki27Q6bZXj9M97F3THQ9AZfbQnvZ7NJPT3oNm35HX9Jg9SA4znnsa10NLT3t3UHmxjYKZ89z9VJ06Yc2pM2jw/YfcC9KSdmrSIneuS6352K/ArNdlhAWv0Ao++8nY+dD+vdYOk0f6Gn/RXyDTyVlRR44I/LPtPMa9OPaF85PELLCDmyzWAfu6YU7Ga/dRJMfu2frIqXZlJ+2zhKd2wOG7+fNHTwRGxZw98waJZDlBwJwE/JS97QWhRbZKGoznjaZfx7TGLX1T/bgrByLnjG2yozLYw3zs7P4D2FzuZudj69Xap8XeCPJvnIV5+3Z6sTsNEZ+VTo7AjpjvZEcpKwiOdQd2GkGr2y3wdt9g0As4XLvGN86v2Ub11jL2j3E6K4udMWQnbSIsTlx6O+MIbnN4UrwpHDjRw6PW6nwqvC1OYdkNyeyOr4khoBFwhbzu8jlwU+ah2RE9Ozcef9a4DN4fZzFBs7n1bsxSts8AXAc9G4e+hjxkWPFhZQfPDOtMX/8WebCrc7onnIv9w+1G+BqHAs/b7RapJgM/7C1D961lLfyWgbdHlp23w5sLsjryrvCKx4iGTzvoQzmfF2vIZ5wq6CQaK1vNS7dLkr4PVn7IS9unyL76Zksi22YOWGl77JbmxDHr8nqKh9w7Z0fVKt/F1O/C2Fg97qnaA7+G+eClw7n7WHw4unzUD2StWHubyp48v11qO48FDenkDtiV6E4L8JBtBTaSyROcL6ZHLBYVU8k09owhtD0eMXnsaVXLNBufbgZfnfrgZs0Iwu5P/VNu97JHAd76tZbfCWL2ze5pR5y4ncPN9equp/VvI4wwlvE0atL7Bjfa6RGvxDxVe81ts8HtENu7gbTYa9Feu07b5Lbqj2x5KqKKYl1rMZxp0p/EDpp3SoXLpN/LBu2EXSPInQ7iznt0Hql6CT1pNp0VZNaDJ6wg2tL8T2R1prmX8uFoYCfRwBIc61gfs4/4jN1aZJPMyTdPfls9JwduBHDL72Hd7IfTkRcYDzMMscivOwDS8N7Zlcg8sa95B5P3RV9h/Y0/mp3YjIH+IDU7VgSQuT2N91FZPEWVYW4GzIM5iuZ1P9an4Dvbm8tORDJs9qAbdjzuLBGje6VV4JPPEL1j3eRMyG7ar/icXBG5VqrIgyrgQD8n6PeoAaiJ2K/RqDCehXWwxwX+o7M1T9e3gvG68waWVKlAerURszuD1RrkS6n03FbyarnMTGgPyM6x6GqqadKqNJirfI0jExc2nwcGOx55dXagu+TBr3pPyaObZjZyQ+PaI9FMMzsq2I+C291+sdwm/gus+3DanVE252k6W+E6l0cO/JWhAjNQz0LG/qSDx7RXmBVw5EssIiDDqXlkZg6r9ugUET4/rAM1ci26Zve666CdPZDMtKOpXW3NS796eWgPEAjs6wizYeFpnbDsfJDRPfPxWEOdhvdhD3OrafQTjWzCNtjFBY0xTk+XQGupScxykZU1f2xoI5A3K9FkIYx52U8DVKaPH92DDpk0L/1VKvQ4eKZsD7cDnL/09cwm0ksSRS95S7J3TucSwxM68w6rnWbsqCWc9YOOktthxxbxuG0N1+1e5TwNxq9ru5wZYTfO16gNdkd/EC0Hk7BTTgx7ZGdLc05gFJN+mOtaQyTqkynCU+6JzOYN4gN25w1zd2XhHjkB/TgiAsbfe+ocvFxjSP7WHGCyZLte0rla3G64oCS7Y+oFGNvFFxvUuYxpB9fOvTFGia1E9ujrGLs70sB4gKOW3bReuQi0mbYDxAsfOK37sPp4OxHYmK/9AYzdW3fMT7tIzY5+smP2wT5iftCItY3LHUbj6a3gKdsfQ84hjXE4edBMDD0IGFQzb+1v5jQHOfynu0+gu/CmvePdJ4QcrXRmtPbdfvjYoGunLDBhOotcOXGKhHXcRgzRb05LjJ4XfNBXxKntFOTUY2tCebvhNCU71VgF/4oZuF/GeeVg7ccoM0A9vnUHdl90btTTfCz6E26fjIvVsVokn0jZ2E7+ErNNtSUIlnw8UOLCF8uwE7K1claf4Qnin045fGOU6IHhDlzjEUNmBn/H6NjQYzUmC09o3TG+pL1ZdnfpcVcvPj46XB6GtwuRg/X4j0yRNw7caH6y+TCdnYs9cr4D34U0ruzpBnw71sr5O3aBUNK0GsSO12sX09YhyLa9R7hH4K71iEXt/2nmJ/bL3AkqqQMWYppr7UyNcH6fWfdHq6FuIcJlZ1Q4ZN5uy0mqUd/eGZgZ8liG/eGdbYp2daak2uzYFRBvAq01qAnaxgjAToNoVzizSXmQLXnsz2PnTCMa9n609ykrDGcVIbFfs6W4TcYf7Wbg1BVWC+YZ1j6TwzOseuB90yjM29WRPI2ajsdcnTACiNZCl6JXY1oVbg9DWW41pL2bnEqP/BvBh+Ve17ktzqLFN0Q3DjvwT3UyFtCujPJ715mh+mvhk+VL0Z9wZXY02j33AdbImThOT7YflNn+9qDwLfAvQuvgZKhtzAj9YH6jVeFksMjg4YOPcDKpkXp1vjVKzULUE+xRgwcxegYxuIjIVBrje43mqx9e8VXA0SHtZCxHz//l90apOgpZp2klkT24rEacXTGHpiVX0w7ncLAjeh4l+s0pOXg0ci/d2Y/zsg5a5tP5He658Qt7WcBdj7bdTpXFzwVjLCMaTh+w4+vqfhFYKFi71d0bsHfHO2jMFE3Idzn5zulpzSHj1WbPWAdTmQ9p9ZD1y+ZC9PQZdAvodJnVj5/iPneWoIgXy+7/XVZWwg0ua/fkbEWz+JVb9qw7oLLD6FWsz7DuwMnyxA4mN2XbeUMGWFatey8cfR+iUXgH25ggVpK42w4nWGGvr92WnJxrnpUTIuxcBBLgHg37q19jzeHJggCd8eeEIydrEP1MZ09o3cjdsrpNy4Uezq8Zl/gsMF12CxEV7O4JE9wF7CPcL3o407mH1rTyGbMpqB4aypJds5xqARuwthHDrpGBSXbCi3lK9rqHle3uFnLXTjgiv5HuKCmus2+GeVmv3fy2rHviP+JR4j9m614sOB79cFLSld3C9sHeGIv0yfiPO0VE1jX3XGNw+9LH0Vv3LGq3iZxu9TOZsXG7Fxb+HWhk+b6umZqCtNZb1kUpNctOPjZ4I3EdfvFr3yH0Nic1p9jAOwi3ebVBKcYDn5B10H1BzdiXFbS60DhRc6p1Una6MLPXqhxysVJsZp0giHQR2RzOjzYL2l491vrZA/bYn1AJ4RzN9OO2LvtEGVfq2XZWOpCF2FNlQfu357thK62GsxbDqVvXuBseVncd5D52XjHewZBbBpfal9gbxM6IV7mPG/YgnJVpjsrTPFjAS7BCGXurj+29Y3WGudbgcHfAfrNGkdJ8fiflhZq8np9ONNjmhHATsRqjJyfC1ZDle5wP5YxF0Ljelr039b6NC2SzeXJ33COydq36t6bPjivyim/nU2Gje1IkSNIui1RSwA4dGM7zyFK2/sRT05LCXdhvKjoTkveCjTRW+HaVIrEqO3+CQl8r48yUBlW++tHO56KuDfSeVpN1Lih+h9NYtv3TzHXU/7UfXc/5FTnwGzUDnIa1MHgW+3a1CHwO0m7t7dP9bZAfOHO4i2F2wTEiQIxy2FvMTuBiTrtbm6Nu5yK7htLJJ5y7Yd8b744zo52crv4Bwe7uXCQnAFakyoPqwjOMboDJwzgyTNQ1l9hsfLv/yVo7A9cnW9vrLFHRXffWkMHABrF+c8DezifBRqdWUvuLDVIeep419468yu68Pc73v3z7/sd//O2Pf/nzj3/953//+59/+/uf3//bt+9//ae//vj5/b/+8u0/v//bz/7d+vHzcw3yx89unWGzIEd7W6yhSZKWd2SV19OkNYt9TCyRoO4RtBoLn2OBqqOfCYs7fMpG6I60CFLRHKtkmZsBFAn57MJw226QnG9g1KbQ6YBIiNPp2PQea4jKMgEPIG0TP1M+bDC4bJOrA6tCNjTjuECA2dE5dZSbYxFsfeYgAxOEIFuuFLTNRmx9hqkN94dygGl5YKdtaPTfL5Bvgy9TIBwF8tU61WZfDjAN95OVsJOOHjDR8Yumnr8ElWQ/qTzHgcXyfY+nwIkcKQW+3cZlOAW4Yw5FNRHOVr2GGLoFtMXI3Q7O5BZS5pZjGZ/xy+jsJqCQGcsGbcfKKQiDj0+Q0AuhJmsDnnWh3DQ8jeQY1JbKMKnVEBtJX+EABcLujy6hrbN5993hKnYG43JNyOxBwLhsfLtpYA69tRFxdpjG82X9KIenR/eyP5ohabFuSI6sXikvaE+LQFm5Q2GGhVp9Upy7JcPdsE6ajrNw0IZpEsh/t/81BOnOdDLG+DL3tozLHiijg8m323zAYitHQ05pMVuj8Lc0TrHEPt4uzVNuAWwUzFKY0+03v8wocjjcbU7ZBvgmZphcyjcOyY3lCSJ1lhDqcNlwA5nRIXp6zD3fgrPmYDIpZelB0/McVdkDBQwLKueCFtSvbaJtdE/7jnxMX3l/EWIOoJHgMmnWNikS/o5Bt62Wo+Rtj2mrf5sVd+rXsFEkRuGYlOJ4I4OPnpTNYDscyYk4Rs223pJs6rrXG4H8OMjAYlLfaLgb3B1TbTnx0YOVkRY1ElJq+a0DfWyfQjpKt/u26e7TxTLKzy/XyQHxAgPheg6HwuvmqJMt2VO2eY6jCl4HKyuZNkWxDOfRRXKF3hS/kT13f2y7bRP411vDKWu/LD41/UYqht/blMzW6I/uki6/d9bmDA5Ncx+69B6JXb9gpKN1LZEzsdmi3R5nbwNnBxxbamfQynKwHhPmyHj1cLeaZ82eggmKSmYXJCJRvOMwMc9hso4z8BtZswOmj7KK84XDZcs7E+O/xpGraW1LaAI5usVRtjgX0aGKllVlAytsc+al7VOfY6dsQqXewxLhwuiMdzGXRDrN+gzkOcI+LBlOtffRyqN/PClPwQQ/b4f75m6gi9LkW4Elu2FR81JvKNXeSu0F99Gm1o/je/h2282ZAmqLKstOhYs2GjKUv0QXNou22L/1DDtvcYdtBxwTj8UhRcSBmxkNGpEuy0Bsl8otjk7ljW/dos3kum5f4+ChHgpmgo1hKRM1RVaPd1BXnecbggfD6IKZXG16v60DTFR24MtrioU6barH1JC8kSUwypVNSLZhKSxpWwrtOPpH6gMJMXRrmbDtELvdnA3tvYO6HkvEKML0RNCivLvt7h+b8Pi+6EYbYkBe2QYnXjEqz3y0d03hclLsm8PlHf8NseDQsW5hYWvf/o2llLobtjhQZrhrFkR36jgSODp50tuNrgBDmqpq8bgSBSlkAwcHLvcQDcesWP6jJNve2RCSA17Fb48t0HVdTaWWENvuGJ9X14kkLUywTKDxP9bK4ju0uq3VbAcR3UbAb8QWhAQ4Z6FsYNcclg2l3MWY11FESldoN7XFehNIhQFESSpJfmnkLVLi3dFjBqDTIVy2CnEIi09bOoOclLcbFPf0X6m12E8RbA+245Z5yj1wjd+ob1va1fnaFzRhlxjPb18B91cU5Llvb4G60WCrjrm6nbvpOAOe32Nf1Kjt0fC+3laRJOjUAQqEZbvR3LUcWD3pm0rXp56U2JgTl/a3cNiwqeUzIlgRu42qlrpLnKwFRFos/VbbO15tGQZFZ4pLf6f1WrDjmGyHSTliwxQmCRwbExkidECPY9ZtlW/wqMcEQOY7tFcqQ1LaQumQ/CE0Y2NVx6Fm+L5oCYdUPk2GcLIgbUo44+rf2b5j+kk1mFYMBCjyb+IL+RRTgb5M7jJQ2EhejCoeMByGXp2NfPR00P+vfgqawSHR+sVqb1tYdGMZTtbW0+gT20yZALO18lNsgP7RpotdbZMS+gXIsN665JUeq7rOMU8iTDGG1txBACK6oVQjLQ4gE4d4R2xe7d0xEV2W4IrV/Xa+S68feYi2COzh1m/1XqAfthIlqmH/lStZCPW/RUCOqvd9G3+KmQ24IL0dctUDdf+50UveA9k2yCKOFff2UA9kTC/SgKBhJrWo5S02oEAzOIzPdOIeVus69X9N7RtqZu6g7yUmb+Qgj/Er4GgrUclMyXmHsjlOy+Gz2Q36uhUhMiknYxODKxeEpNlUSp32asHZc8PKttkUUXNSo/0LnqPWSu2I3iJSZ9m4utfkBzV5uH51hafMv9v7U3uLtcRyImQ1gzhEOfEd+UaeYMvQLpqw8ZEp3A4cQSMNPQv1v7q6BzfriYjl0Gn6FOpDNZJPsCFzJyroQfh2oLj9i6YOg/Wvp9/FQfpx8mNIlDdRr0Qyn/0xhGQRYijDejFovGMxo36H8tk4U0SKRIn8pd/FVP7UL/a+W04rEjbFzjvoIBL1A7rI1gEWKd9ObsG+y7mxZpOROsiIlrap+/7d9i1IxbFla7dFMg3JpEHHR6bSGFoNEZQ4XB+Z9ehB+L5dqqmWlkPjXIboUR/Ku8BNmXqI3Hpsx9SflWvSF5MN0EuybFNUrOWyhX6fCHiyWVPfQg9RmyJ61JJy7nKq6J+Q0xDDyIj6LTZgaaYF66YtU1N519TSIkkbECl1agY9IMtAmuvQumn7xMzcAnkkebnU+xMPe8r6DhLjrNM97NFC/F9Q2ZLpmiIQPSk1g/IAepRNVQf2+HhujVo3PVP1LbfMxEvD06m0eFPYveuN461l2zp5QL6F3VYbdzNqw3NaAVkdvS3vLLIqhpfF8hY0guXfpujLh3eKo+jas5CB9L7wtL412hTlCn2FHvaebpvQmsDZ/Izegd6r2JITsWWc91q/oPUJey7DbAMumXPbW+kThZyMngvvYqsB2R7ttbj39RazS+y8w4NOezfiHK2h2I+30D+9h/DD8+PnL2rJ6cuoaYkJlZGqWdLN7E/IESMo9g6zE5/5+tbM91xnqShdXIgGJxxb9ZfddYvM4KddwfcrV8NJutL3aQ+yISCj2sE+jKpFa5AUrNPKhXfx8HS8/auethLfOu9ZEy4Nkd0FyRpFVRibKAXgtEVcaLtVttG1IqhnNvNMnWej5k46b6fI2fAabKJQwxkk9g0nc2u2A8z72r39Clnq+VAJ9j4zfzGXtWq+13CfiWYJMvYvesie7z3HEWi+nCkrrens5KenZvJGEiV2JzFfv5UFMUifZh9kdxJFCaWbneVwBXbBZ4jLLt802SWeM35TdUbuO8xjF1dkUnF3XpG9ijofVOhAbjEumZ2120WHckqvHDA9oS/XdJ6iGYTUtDxW3SCNbwcYWI/dDXhm11X2FAHPon5KF+LuprSmhhAKzG4O1iJK06dkmRFigyIqC0nwpVo0Y9jeB9xBaT7JEXuDTj+Psypg2kJYww92mLXGrIMuRDRRFlLSkGg9pVhlfTqaznn5GfPRMQnOq9YlsMeudXSSQXZvt9ekdfJphFUakSx5Jx8b8glvtDk67Jtmr/tvzl/mIV/rHH7PezDk41SM1DGTdrntUrIbfXN/B7qsFrO/cFerIgk6bM5KNH9F2sUuUYZa7eyv0re2f3aXZzSeswA7KIi0cC4Gh5xSIJUsNIc66ZoT+8QNewrbRd0qaDs3Eb/3TDW6dpvSjV92wePzR6dL6tx+IlbZOWfObi/mSZgr6RS0PgV+DvUw69RRVw+T8WNIxmBed14z79aQKrvhZClDbmlgsjuX8e3W/xjoQkK6uz2Quis30CcGcq50j/Km+9o9YYXF7JJy7kqopxUKm3tkEMsOLOYsEjrtDnS79fxvMsXJT4YGj2SKGV1XG4fNkvhwigb2xR5YkqG631ZDGVA0bGDHOum/7iXhZ9xVe98PtQf7Lz3nrjo/mGqE2cBXWUICdY87WMWJt/5kN7a3lZXwyav1sfbe2QN2cCD7cFgzY6fptu+sHHjtxCyDSdGZFtoaT0ptpkZC5tWx53eQ4/S7xLfun9IEdPft8kx1IJ2Th8brALNZGmp47KDBjCaLWS2A2ykC9iVMc5oNjNkTQbAl6eAc7qtcqUtDd44dtq/9URLY2yVBI8GUv7JbdOYNz5ye8IeN7qoqnUP0IRNKrEg85tKRTQi9aHddkyqEj3b9s/LHrCaziJzWlk4T75xLe++KtdCNW2fJSZxoexNKbgdXsPJOeuj6Ikkc4b54DxuN3YSE6r5RnnV0FiPrNNcZdNE9ETqNQLmVEuKtkU9n6aXaWJpGoN/djcVyEsrIuX1z7NSj1JlvLQpitbcpUfaT35zuF+mJa+kk8ZFzZ64rFazhVXPyXrv1HndEu9ZWiVMgz/gfQoxraCXPb1rNkI+BCh2k1bbMv9K9VBujb+1ApzxwF7pnFhJogNlgyfa77KbknACf3C69uhcJlACaaiFuuvMPtncWXWSeVk9e/x0SO90Hwf30BnFH+IydPX27q7Nq/QA9R6wWHl2jq+aXrnLNyJ5zaBqriza5HZ7Oq/X0FqBp0z1X96JPtGvWPXYyhDpQROr9Es2qM1mhiNT1OJlbSQOfWEXw+u5aNPJN7cK5zahWK1pbpRbFqnp3jn6QoS9nqLgPdt7h3bEOXz19eMLTKIInOKu169vFt2o21qadaqpFGftNZHSykbUNdnNoDc+bii2v9kj8wHrEe0oa5wIBuuw+5oQeg1VX1I31ub/DNmkNz+gbJ8LEvtsp3notEWDPM9bf9Ez5Ls7i+F5YNAPzUOQmfjkv0OmtHXIwFcAZEuq00RMceRc7yD+/SLFOT+lp1p6snoseosHpq1ZB9ryPyuQ/TDqXHiIwZpWpvTlM17OGeZkSl65Zwl3/yCx2CXRW+/ZEOnZDL9Kaf/uA67F2zwgk3/xaQw5NQUor82RD71aLiUvVqKKL+SsEtXoujjhf22QvAKfa3F8k1DIw44xVA0u7O/h74/Sh+E3jNHfVkKeelPqcu6x/7W9YrVO17BpjIO1rChrfO8WEvJGYGZnvWizvHdoS/9oJnauJJG/Q70QoK+3ToF30rHfPxfVrVdF4frKDx8owd5B+keagT+8g8mAQ1Cx5CJdlspe0i4Go7NsNBnMKIJ64iWjWMDxqby1yoybJdxE+32JHOe+43QPFxqIObyV6QwLU5J5UU/VdQG4fdQ6flAewS07LA3siPdc9QL2D2CZPUO+DnTRJFLoq7z90f5MKlCC2p0/367ca0yoIk1dSu+Pe+i18o3suClV6Jcp9R3Os3RnteKqleVp7x7I93Ig+fe6gt8k34pOrcRHP925e9YlyJW7/RawbLHEC7nr0Ja01ctbjK4nJHeT5zs0yQW3LxtjlzZvFd5lWK4F7xL2gjiHa6Tsl0tP7kCFhr6yO8N3R0lY7SDiGtt5ZRPIVphQPNTCn4821I/ZSG+ifqpd4r9Dqab/EG567SFWEYEgMHaJVwsLu7lGuzRLfquvEftgd03+9I+6z3GNPlzesJcciX6dHKfI0IGEARtmTaxKxoFvEllo69PDtdFLO+siicK/dw8bD/O3QfxczaMf1RkWAegSiKRknfTdxuOwW9oV3J2FrPXYZs/vJ+h0E2sqt91GPXp9CnMOJ2wU1eqq0Xjarar2tf+19QX70R5QZ/TV1qVxc+zhiCaVCVkp54xzBgaFFgJcg2cJe2wmRnYaLVvPA3FDZgPCu6bmg+U2Lkd9A9uzmYzDeMI8JW4Y3DEKb8GSKhmkWdngxsHHV5/bi1+5bjYPeMBi841cY1e7/9mbNoy+svtKT5ZOm8HZI1S5IBhhkEa2F6BkqnKkh52aP5STRY1316g3SOmNfZCeub8qJy7coh9qmI9bSCovbOYX9OwCWjau5U36LwUvZaf+tv6w2XiI9LbJ8rP4sN9SKPvcWPWyaS6gJDTGaXGJo0C6B9/nxc3z28MfP6q/9ftu0hto0ldmMAN00s9w0FavK8FGf2fWzTP6mIdymcPljcE49oQDE5/9m/W192ab5ZXUWqN8Uybhpsr5pO7QZ7V718/WEzfPLadw0TfkASb6rAFl1DK+/LbpkM3KnJv/V74uu3ZQibcbbbobTbooX65P1sxTHpqXl599Z3xWsv8jBz9/ymeBpZaRrQmHUEz7XbNOo8vNXgxV+1NmmjHLTXq6mNU+eNnkLVnJqbel+7pe3nrzLYTfYW763lEt9e62tXPFNAehm5ELNWWTNH9X8+cZTf1sEweczh/W/rJB9KDq1doBvucEOcF7J/mR9VxGsmwbkm+HMm6Zum2Ham3KiTYPDevf69+JkywR+Pn9Z8z3IBt+yfA67wScLVG1KVzeDieq9WOfl8+xqkYA1JRcpehfnMlgt386JlEmuacp8OysZnrjPYZcu51sAvX7DLnl2h+fzFuV+bJo9bwoEa231mQqGbRrMb0ajV19+5PZlN5Sflvz6fLLmZP2h5Lzuz4Ms8Vd+htN5keTLGV33/NlICDfF3yPPwV8tbwR7tba/Z/1IyOJdClRtRtSWBLLy3kPOjn277E8B5ZIKblateU7WXKqkTmqzk94FJYT95+wGEj5Z1fZMOfEiKUqG2ZnDfpYUUYBbeoBd5W6W8t20PKxTY/3cwclOrsfdZv38u0KPdRcCPcBnuDtFyNbaOBeetl5vEPs82Wdu1utbxGC1aA+kOtRX7vNR/7zcLySEPVnohOQzm7f2fhV19fk3clVEee3b5L4MdpInc0+DnSljv2kSX7txkXDvPjqBPVzTW8CdVb8tntMyz1tzd17+6mVtFTrdtCjbjBDclN6WdHFPtzed97r+hpVz6wMdkkjI4da8aPWJHKantjx37vXhadfbhxQNdfXk3NGc/G2B0c1I29pzJA1NWO532Qj1IWc0+cbBT6T38PvJ3Sz3ddM+eTMCsT7DmnmLi/4sCr52iU+ytu2NY1XHzyCrLzdiI0XBCZ5UM3COyHyiT4psrf4d9ZvLTa8gUz0fiUIGCkDXuSPn2rWBrKoB0Jn9f5HSlz2vsG7tA+t5tWjoyYU8I8OTswj+6gz1JHccK/ay5xVE3wwcrv3kvPi/FTDYtGqoc99IFxZB3cvtONiLB3lINGSFvmoP2VX3uW0QbzTU594Lzk4pQvYO2uZpvcrO8xYrtM6cAnpjoW0Gkr+4Kfvx9NUnai13e/J8duAoY7z7UX+6A+gKdGB4FuHt8Jbxe3TF4nZs9uHF9gUyM6Yakp/IxkkRCytUYhf67WFPlIG5kEPkcyonaDZwyOGmvHzjBAk83NPlE/pkL0/DMroe/uoiM412fDIyMHjCRJaU/3m1fWCeqRZlB7C5E2vysj8HKz+8L2iGF6v6ag29a6zhHa6NnQcPXFBZ0VWbIUWbEvDNmLKy8vwbrV50Yb0R2u9q9ZAr1u89SpBMin/4rkQPbBGC+lzN4x4+yHBqDdXYYifOC4s8lBl2Xpm/PFNLkZz+VrtquR7OLkRZnM5GztntwU7OdDe8LyDAtq1+kv3xG7lfK9UMfHIiyf1v7aZnpAWvNe/h/os5WSHfeEUgaGNvRKCLXt9I3aWe1yIHJ6tlfzx3fq9OUKqRkLjeDjE5ducq56I1NJX3iLt2H28NNvqKfLB9jYo5WVY4em3qfG4ozxnsmKjpcju2pwNOu9jrSuyoz/C9aKFKgCjdJQLHeqKHK5Cwaf66GcC+aRuzp+hxisrESKxqacu29pF/X98OqWg0yHuBmR9RN2+Rr1hCm8XtSHEF2pt3rDSRuhHKhphNGRMtuAOcnfLAnT2pTtA68LepD8XzH70q1i9uf9T8PAfbFCEu5SYqG6C4wZ5MbRNWO/jbl91OkRt3+RUdodVBcfPhyYdVTXaDOzI29/poT5HbwU5utR+yneiQVC+xt++jZdf6o+WWZ4ruPSJY5Yd1bk9HjMdOinlebz0yrB1BK+bUyogVxVfKD5Ic7qen6R3x+ciPWkgNme4ez1zeGvZcnKbWFQ+I4bf2XbsvkueWqQGOFhMtwd2Z2gJ28opklIrUo3F/0F3e6K1W4TSHsoccsoZxxAn8X3TF8W+vlkj9zL1erIG7M/qOi1rZ4VcEhRblN0NPQeTGKR/eaHPfpz5U8kx3cng7eA564OVWXvdTTX5FwpwL+nawezvdGZ5/tJ6iMs5L9IIkj7652I6rp+w94vTDN1Wi9IU5Bf3NzVlzi0/oi3H7FtpehH+xNcjDUW+AMJc2Drm6akvRFD+nNhoNc8U5j0yC94hvacuLVjzaQW039xr5WaGX6v9ln492Vjuit85OenNbPvkNd2EhLYvv2ks7i0T1LqFJjqes1tIKi2q0QdyXR52MbIv91DZyC+xPHJGqGlU7y+dTXaH/61uzn8p2ajvUPHp/eIV6N2p+OYSpF6kvzDpbB6LhRZ54UkdkHvprvIV2gXdcar+UDeDm9o3Qp9BSqz24TerDKSpDhh/ZLZ6jxvYWpHZTr9b1qAeQFtkesGXql4kS3UPtu7j0yv9oBXhTTvzBdqSSFvoyWltRB2tjJSnHkqIpvQNxlAiff4vP9XGOeF4kwK3E91w+Wd/qFcPrsaoHRFlyO+hkMapWQ5wJNn6w14+27Oj76I2qV8UqeKNKJs+coiP1PBK1WWeIu9TSYPg4olO0wdVCIVfgltWaUFsJwn9dlZKpxVQzuPP65mpX/jbEGOpY1+N3sZPyJCL2rT8lIuW7hp4p76W3wlu8WjQYgCmGYc+juU0ZOeQB2dDXvukdEbX6SWT7cOKvCIpT1rI3auI3jcDZyfaztHrYIKRiif89/aNH4L/Rn82nycrK37L/KVvCjeaOjLbCYlckVs4h9ItZMzo2kfZKjNg03Sm9ql8j9uN95WdetRArZA8P9/1d3k2fgx5D3y4lWYsscyt65/8e74J44HHlehl6EJ6mN1e/yTsu6pbx4IbqVemJpBibM5W92cqPT0ADYHlHiri0ZfzVEhuLZGSrxE7IYchbImne36tnwYl4guo69xNkdcPzUpbk1fVf5KzEk2oJEZc8lXwIt0M9P91b7SPvggRePb7Qt1KGOUG0yvHt0GBHvkvcq6XTX0MqHn0NzvcFlaHTxhEZqv1khIZsBhoAXR2sJ6cenLpXDYmGh2MUoQUyP8SZMhvs89WTal3Kmj3ltpviEy0s65e9H/qn3HE+ebw1zdK7q95fdR0658jyiRXVyTJR4nN2YCvVRgr0NEUUnFdbf36DTzq0TXJf/XbeTRAL0nVePRrO4lFjeIJodRGyfMsjotM3FBnKCYvo1O08jTUc7aDWXOupjyPekDnE+3iGSNK38y7zU5SlVT365vKrYk5xjjzD+fHznvzxs4BPfBs05y6Y+dS/Z/2s9dRvsn7ym/r2wWiaUsbn22AMablui8/Xz+Ik6wn1sxBjGbTg8/ztUz+DvyrfZzBsc9AMsp7z+b8MoKvn1P8tm1LGc9Xvo37/8u0Pvy8ObdC0dZBgUYq2nl+WqxzWeq/g94WjBul6RcqykhN8I5/J+vbF84N3DN6ibP0gYXEwKLj2gW859fvBzhzetNjXCvjU7w/fEvxt+SwFfNjVy2cGv1nsD5+sGFD9Vf0sBmkQJq+/4jfuZ1x+X2soVrlCebz1ZeWspGR10MZ10CK3/u3pHP6K73r9XvacvSqmfTB4tlbI7nnuu/5dftOgofIg7anCevX54l0HqR6ljHnCcW9ZIesM1lD3segcT//lG9kNv1Hpejwj1vbRV4PWtuUceNa8VyJL63IK/F9+FrNRz6+VFOIdjH0btNgsOWSXXAPSmHy+sPpgwEtJi1LNDrNjZaNrnXyeXd087SJRL3teaHwwGLmeOThZvlEJn6wcuSo9WXLI3wYyw5kOdjg805N8pv5dfkqBcdac7CrvnrxdeSW158gnt2A97nwgsRfJRFbrBu0HuZ18fiKrEyl9kajLzhTSrlPj+chGxY/q9Bc34uXdB6tVkrmtdTqrmLpB6thgWFM5cMohUpf8rD2nSeqgMKOkAl0xuafe7jVZOTvPnpxwb7lr/l/+vZG0VDb4TdnB2nm1DWurb9kPpxZoku3tYJ8PknbDm+vd5zPchfJ56wlIyEJ3IdXFYdaJs/PuLTITSFTxrrXywa6yz4H24OwqcjRI1Rq0Sh0MER0U5JReRXKQk8IJtR722bfjLQ5SnUcd5fdyC9jtYglKAnmav3ff1ANI0fEWbHZGPfaoFdEzEx2idPm9l91r+VFXT1au7HHXlHBOZCHbQ52vNuBGvK7W92VvU+liJxc7M/h9eS6D8qrSBqx5+e28C5J2kajBmYa7wT4HUj29uazweuKcbKArXvYh2M9imQbtqEuW+ORVL3GCPC3cN555kY2Dvrq8y+XUphLljUtWy04mu53c0KuuRv6Lqywtym/8K++dt0D5YVWTb5+c0X28BWhIZTu8obwpNqu4oNLVnI52AZmpmEhpDKT09W+VWG43GqPwT90XrS23lZVs18ydrfhU/RWf8RbwmTmUN77xcbfRh8fd4zOc40LqkvVcNX+656zk9Y6wJ/+7vXNXuSUJz/OtLCYWps7V5UxCsRwLtnFgK3CyrUACg9Fd+ILd7/PUzGyEJZwIY7yCWexZf6/uqu9c3+Ft/TuUTEYl60Hrr02DwtoHqDSQsYPXWEVfiUbr09G7c+MWZVLLz+7YV0NTOiupeLT66Ft5StFraxPw8lXrgayixRv5n/j3yj3ro51hzQvdOUYs3O1Ro40KtKjYYaR6SKsOv9CLjvwPNKVJ26VVRIPQl6Fv4splFHGM4uBC08Ib3eE7pjEV8ib3bwTCSpCZqQU78rQgmdDwKDnGfvARajSk60FihzTh3/NGR0ha0S5h97T2D/dXx7EPE2+1tK5QZvPEhV1qQ42A8tN7wrWJjk99olZai8HutE5GQdo0PNo82hNpC+X1lfq4q4NaBq5Hi6s0hPKPusz3R2uPbg52+qgdw8iWuIUVLuMlLPBG6hr2uUq9piRobbjSOLkZI7EeqWEsZ2SrtPPbrn5NtVJfDFX1F0X6s2v5a9SBhAx2sZRb94t/n6z5GN2hdwupmPICO9mm0aMxLXuZ7AtrM6sWHqkzeuk8Hfk8yM88Uk8ewTu1G1v0wJ3KU+rxhGLUDW2vhYTL3LNP9ZH1FCNPbBq/2k0u6BG4/8Aab22FJxT0Gq08WhWt6DG6Q86HMYkWmKcYAxxtl3EF1J7QH1+WvESexfc8t2oN9KHI1TQm0aapm0qpGiFPka4B3bpXsutJ7N0e4xNtLzZh+CtsqTE2v13Q+XiaMzKEksedDi0tNkf/W7RO0PxoP/VuyhuSb3x4PTVP1Ba5hq0lQXKG1tvTHN9sYxJkWOvXPYP4XNfvOYX1KLfHUxVUulGEdkMPAm2NivULxu16Gfb+GD12JdnIB0lQioYWA/26ts4zEdqqzjb9mh5fmfG3yDPadJCxyY6q50ptbDGC9XxqTA7N7+nDkyB6dM8L6LISi2xPTlvTOJCdVr4f1UhMGy4lsbfDM7UxA9E+u0i/QTirRHFPI1hPizyxITNNDdqeJpR5nlLVbvSC1XZ9btdbedLRO3haRAfvqtiXkqnt1UveqAaLZ6SqVBcjIqT3Uga+YJcq8rBvVG+MAZ21Lfj0of1BHpI1Ct+Ryet9sOeeF4yi9SNyBPvZzKVw5cZ/LSmgl/SkhrUc3mfIL3XEK9m7+zV2bVoSLbznUHeKtzXWVbbxO8/xZKS9gp7Gq49RvV5PX6MuoIPYsXQOZNfYeSVEa4lsV6kBfUb3Pkq7voBfyV/9nefWG6exciMoub/0mzyxaw/1NeYi+JXxjx6kGHkat8gFYwn0qxozQD2eMrHeXWuJDWmuwbP2MjZT94lvjfHUPleuDHifYf7ET3Nl3G3ANW3d4ynY+Fx/aiyhJYdi+kRjS603FmAXPb4WQ49s7KqEQGcpw05TR668vr4CbxE6G/eai+B67dU9RxMpebrU4z9acqI4JCG9JZEiZckciGdesxNIqWeN48nU6Fcb5fnUuBQ5nFxPHFK3lh+aGAMjA62YnZB6XI+ednXwnmWwJHKQO9RH7fOUZ3RnrOtekC75qEcwgvJc1s1ZeVLj/mbbkKtj3s8TvTlDI6jjqrjzNP9p5kE/on+E/qxzaj/567PlvrvA8nD9U4yQuQ8a1DwNmd+QX+x0VnehheQbab71qtjkqQ+SYmYIjQONvowcWNvUoqrLeDdk5mgh9Vn3fGfWbhD/YH+knrGT3qS7U+NeT1Ks01MqFqPfWF1Lqy1C16DVwM7Mrc9iX/Jda4wdOHoQz5hdLvt05MFYdNSgNPX142fj/TUNN5wXtz6fvP66v58JZxtv8X5N2iuyDZfTSI/mJfC5PonCvKA1/06aqRHSvd/sXJPgpuFuG2/YbBxi33u+jGm8P66RUmkkthqJvMa7hBqhQ+MY0yD0e4eeK5Nwee/AE0OO9/usgYPH+/1rxLPa7ChimmflM2Fu40DVONLnDv6K+78q9H5TfUr+nQRl4+D6rnNnj4s1D9ewcs8IRyMIbrj5vNySNT/sFKomQdxwY6Fz7hMRef/Nmh/uliC+YVLzb9YmNXhu3GHjuJ47wIviNfCib9YvlfJ91L4R1DZUrqUeC1VzzweaJxTLKwoX+3X9uXPMR2iYK5P4biQ7GgLdeN9oQz2yfnga3hE6NMKF3JP1RIow6I2kfMPBN4L+RrjQOJy8q6rKCf/u7G7xLPZb4VocSUvFnus3K4HykUbUvpFsaoQF4fjmWa6Wp3doNaQze2fXCZEbiYb33xOqLrimDLSOLihpuXOMXb5h1zv3fFhniii5A9cgk12KFXRhSSWkHSlNGiI60qEGa47u8A7cRkq6YWLCZSkpF1h5yW8n8rmU4eadoRLSEuVvFBIaoVsjJG0clt57cmXKRY2QseEMGofVyAmSxson/I35DmeV56yqsPcEqY3kUSSfZ/HviVSv6t59FpKAJlYsw+C5C31JyBVtmtAcvuyKniKfR1uBTiEbE2k/3G0hRVWtQc4T2DUKIY0keOOtoA23kX8jLXyTdE+0SX2ZUFjuYA3Q4o21SYNpw4i/17Pm46quJGBn1Eos1VxSJvdJWjDrhIZDfcS2PFo87AD2aiM5lZWMrnXlblDjwW4U6FN5Vo5DjbRa4/CQNfjEBwvmSuDp8s7ovpYZnV1K+4BTaN/qWjls5sYeTinPc+F+imGNIkGkBQpoY+8a5A4y4CcSW/2eNTxwdnCH4tOheeMOhdUmmG6UQxrvwm68bbZRGGik7RoHzsb7DWMZkKIOf6FhU36gf0Pmy9RPsffoNcmC3Bn6I4dJkDWO7o1EVawuv+Vus2gB0Knir/wG/m7or0fAIuUw2Uj7Nsp4WSdWAk1f6juyNJoWGw+1lUw0ESudYlXoA7UnPN3Iz+Oq2IsyzAonFmlqJ6seFi2oWl0kcGn/pS331NpgIYv3VMYO9kFbijVb+IuqtmLzD9Sr26foBbCuFe9ZWduGqkX6sBI8Wu1S3p0q23gZ7Rg8Gvi7g8bNY2yA9F6frjbh4/QF3gcaJlHbKDA0Cp+hP79ayqHWXpmHGtj8qfyjg/1KJvaHqGbrMfG223vGgxN0Nkp3eTrrgfubva8qBdQgnjWUJdcG7/Q1R1+Jn91qB9aMdfaqlnE3VjKgfNLrjYJ0dqSV5j5GTfoOtKlPbRqSpjfXt964i30ZOegHlxKIbUSv59ae6zGNIrBaWIyNfp3j9UoyuzZ2GsZISAiRz2BtA743teYgIfIRH7fgbA78jeaG2BZtAtb4yg/3wSqmINQo+TRKzo0jVp5iPMOqpvxC3vQdRCOFNTzGn9B8cP8y9U34L/3Oo2eEtnCqYA3alM56Z6wrkckkqpn6X32QcQs7mluZhFbEJ1PJ13egmynGRAag0oBTULKz9zb0L+5Oz9jRGuNAVit/sUhzKHtEfUZlRi9aaaT3YHuXMoDdrsbMRhdSVb5oH7YegRUi1V3PhV4Mvl/aH+LG2ZVqno5X2kX5Ydc36mMvaEHhmqMP7VJVvUZP2WlDlmbXw6K5xrTY7aVN8CkDv8+dR/VE4ynAeBgZwNMdrtGKFix/QzKPz3JVRjueGowP5SbWo0x55FmGVSEVbeuveSIcXNqZZnyoR+P+WzlHrz3L4C/SgNJITOdKNR2LpDXjnkfd15JzyniMuuFguxE1u8OmzUt5+GV84plLb0JcffAaeHmSYo3DauwAfMSvbaKOohZjMx9oPrRCaEHXgmEzl6ceNKhgUY+nku65A35BczzmGkY70PnBnhTjT30op6SnSG3tvFYFuzGwz0dJhhdGLMNPfrWN3JA3vOHSMxr9Gskffb3RC9x5jNCQGX+rRzCiwLN37FvV2hPlJn3TppHw8Ayo3+evW8upleM00TxTe1Ylmpqc0Qr7eoi7llFclZLaarhWjTb11NCw6AW0ikiLlnAbG3C26sbS8LF6woXXaq4nfeNSvM8+xgnKPFzjWb1p36A5ktwez7xYM6XXvRwpQMxfjVo9vytRnqd8CnLiWQyLNJfrgdrIRn2MGJEBucY3DWpPvQM0acRFfRntaBuNS9H36ilDm6PF0xLCC9bQb05DjwZ/qzTRayAJSHW98bM6Dk0e43YjcCiPraj3TOHu1FPiT3fN/U83xuA+TcuJrJrJ8WSBnDdXpZdBimozx2KEA2U8Zeu5Jjq1tf+e0PVx+im8Cesk2ln9MfIn4nq8BmpMcyBG2sbzWkhkAEsyq2cZYz+kayMVj96T++BJN+ssxyjCuIi/euY9Zof0Puq1ZwfoeTxbwVlzL+Zt8BEPdn4p53pwNUK5xYdWua8fQStn9TTN06Hb0C4hURUPVZdZC32NuoNOmTHzLNNdCfvCHtauDHhCVK6QhKn/Uv6N3+A7fryaFZE7j9yBDsa3nrCmuSb4VfQXSqBZMmXe+NyzobGKpw9lW56is5eb3E2P1j31s05jxaKvNBIgGtH6Lf+tf2ElZmm0SNeP4y/Q8e73WDwzddUIxPyA+/IkBa0aPJ3Gkz73aNnMZRmreHYwxsD+mMlxL2qW1hVOLWVA7igVRJ7k92hFioVRuqChGiFH1HFPec08obrD9deSGI3w9GoU7Z2NB7An2sCljYVravrQtiC3nhnJbzyeLJpxL/c0Q6VFLZ5cPA+a/TAa5G5QfpiDqmYvpRLfPHp5PIsR4z2zsP4be6vpRuz6FM9lZpixYFp4tR4v3G/OijXDnc1pfU1P+siMsWXzTOSZFOoR23SyH4+nUblzT9zmDM19mSeEqsauxGOP1t4sotapq9fGjdDqnnfMg5mnNYuo9YAOZquqe8HjoFnFSNhY8eZzjJSg5PUach+baW5Hv7PMRZgZUGfxCNifZiZWS+uJz5MpNr80rZC2lKfjBYaZAS2Y+XwzFTe34H7bv/B+6r/8m7/+2x8/f/3kjdX+83/33upSfvyMCCbBGdFKojBkS9gQk5H0f9L+SQklKZsQOqqSgCvLS9ooR8ak2ZOoyvLjjnM4STCV5FiOyknLxXAlCZXDVtIpIXSSASlqhJRJv8XA5giUI3LSaEn954CSNHUOukmZJCWY9ESUIwFtWBVTnQA4Rj8p1RQ1kuxIIJAEURJncQ5Jy+dIlgA8biuETiI8B+EkAVNwSHiWlFyOiTm6RlWSUs0hN+FIUrlJH+WgnkJNyh85wuUokwR7kuY5ciXgSZosDjBuIqmopIKSaIohThCdQ24KDDli5kgelUiYCYhywMcC0RXAyMDKBborsGEBEgxAW6C/Ai8W4LyAewX+K/BkASELmFvARgMXF/CxAKgFbCygXgFNCxBaIOMCNxYgt8D6BSwsUHCBIwt8WODiAqcWuMOAlgX0LwBkAScD6DXgZYEQC+xYINICFRawMiAgP12Yu48QawDHfYTKA9bv030NxcfXA/BWlA/w4r6e/gOEHO8kyvtO8h6VvLelfHiFRsD5AgYYcMlAuwUqLfCdAbcLjF6g6AJKFwDDQN0FOi5QZgEcDNAar5Z/rwsIYoD4AtYW4LfArAXoLQBvAaYLlFuA/WIaYnpjvmJWYnjiUmN04rTjjGIs4u5immL4or4x/gmeYh5iCqLeMecxQTGIMbFxbTH6cSYx3QmhYlRiiHAYMV0xCIQRH8yIB9dPs+zyIaFrSPC5h8UPJRbCgZigGKkYs/e6ONq4srjCBCtx43F2MXBx7HFecboxYDFEMehxejGqccxxrTGbMWQxxjG/cWkx/zHjMd8xWnFqCX8TIMTEJViJAc5hJIYsBjhuIoFRnEAC8hjWuJeEHwk44l5iJOMO45riMmJkU4VPd0j6TdLrkq6I1GZT/U/VNhXmVMbTl5B6cvpwUj9Oz0hq2akcp36bbodUslP1TUU+td7UolO/Tv9BqvHpeUv9OH0HdOCnzyCV8HQjpIad7oBUolPtpgvy4xwFXTAf+0Gpcn/odaALg26ED92CqUSnrp8qfWriqf2nwygdFOkgSR9HOgRSdU4FPh0p6Z5JtTk17tSz08eRynuqzqnYpyqd7oF06KSHIVX/1MbTC5E6fWrmqd2njp6afKrw6UlKDTw9Tuk5SKU9vUOpoKdfIDXu9C6k1yA17nRmpEqfnpCXHy87Xm68zHh58bLi5cTLiJcPLxteLrxMeHnwsuDlwMuAl/4v+V/qv8R/af+S/qX8S/iX7i/ZX6q/RH9p/pI8E27nk4m1/clM3fxkLi6Dgp+MUJbPS+aXyi+RXxq/JH4p/BL4pe+MW/vEGcQHfeIJ4gg+cQOxxp/YnJjOTwxO7NcHa/OJrYnKfyLY0c8PabdPZDoi/YlAR/4+oV6E4BPShRMf6PaS4/Nu9/Mu+PM+8vP+6JPFvGt6aZaCWkoISaDm+J8iRxLnSZfliJujTAoKKQ8n/E96IYmhHM5y8EwSPKmUpFaSqE3ZMOnNhFBJbqWpIMfIHKxToEmyL8WrFAqTtkuyPweKJEaTrkuqKgFrkhkJchKmJ0mTVHmSlQl7k0DOcSWH7ATSOfwkkE8ZcUL397pwIcwIT17WpBiWEmuSbDk253iR40bKJEkSJHmbYlsS20klpbyXUkBSsikGJAmUZoAkoFMyStEkQWoCurRD5FiY4kAKVQmvk35LMj8J9zQ7JDxOgT8phxw3cjAASSPzkJnizQRxZoMz/Zm5yMx5ZhIxs4rMzTIt+nGum5nIj6g9zD5+xI5hsvkjRl4mGiOYmdvMNGQmHzPXmmnL97pM+WZSNhO1mbHM/G7mjjNbnnnWzG9mijjTopm5zpRsJsIzS5uJ+sytZlY0yAuZss3cZSaxM3OcedLMAGemPLOZmWvNVHQmMTPhGVWJxkRxoj9Ro2gTSvVeFxWLpmW2NNOzmfjM7GqmWzOjmanPzG1mgjMznpntz6R4Jk+DT5HJ0czAZpo6M6OZ/cyEf2aXM7Ocmd7M7mcGPBOhmS4NVsPLj7SDJHBOKjLHj7RXJB2dA3BK6yms58iRw3oKKDmE5ICeAnFKQUkbpGiVxHeSYQmnk8ZNGSFFsaREk7RIaT4JhbRLJH2RgnqC8ZTRk/pPMSdH+LQv5BCTUk5KMkn5p8CdolcS/0lNp6klBfMcJ1OcSJowLSVJzCXRm/aMFDhztE0LRFpSUrpMEiaJ6aTuUppJ+jIlvpQsUx7L8THHsTRwJPWS0mQKV0mrpAScMk8OiEk0bSxmDOd73cuPHChz3EiZIc0pSf6klScFliTckrZIGiwtQyl+p9ieVGFSsSmvpQCUlFkSt2mcSKkvpbOkNFNETMIphZW0PqQRI6nIFMLT+JN2ixQ+05ySQ0oKvUm8JUGRYkBK7ilbJzmbFqQc8dJQknJ6WlNSNEobSFqAkuRNITTtOil0Jb2RtHmSm0lfJSGQdHYK6TnwpgCZtqCUudPGlHRv0pVJTKdUlQJuythpfEjRNqm3JJOSaEoaJU1DabTIMS9lpaQdUkRMwTbJ4SQNc8jO4T3H0TQgpLUjaaMkANKakiaSpGxzyM3xMs0OaTlIoi2tBGn5SCIgJe4cpVMuevCK73UvP9IolOJXSr9JpKXImKNyktBJDaXdKsnsJGDTRJVCSsptaa1IqiYF9CQF0t6S0lIKJylmpvyalG6agFLuTFE5KYGUTdPSkWaWNA+kHS3tZkkkpqCSUmdSYUlQphSQ9GaSMklmp/iSIlDSkzlWJ9mUkk7KwWkpS3NQCiVJOyY9mVJaGi+SWEpqJanJNCakhJ3WgRTAk+hOYSOJmSQD046TBpkct3N4TgonSYYkUtPolBadpC+TpExbQkqwKVan+JKCTRK6SV+kqSupkaRQUr5KiSBH9SQ0U8xPai7FtjTdpHiaRpMUbZKISxE3xYcUGlLMTnGMjmROzb+fnePTv+fn7/n5e37+np+/5+fv+fl7fv63Oz9/z87fs/P37Pw9O3/Pzt+z8/fs/P/u2bn98fkBeY5XOPAOEeDiwAkFDJZ31PDCEt7ZwUskwJUDrha0SAD+QEblxTK8MQWgeHCjgRrnnT7AzoEsCdw6uJW8fAUcZgDjeccMr8wAmxy4Z97FA5gf7xQBlA8UcF5pwFuHeMkM74cAPBn0XED8eVcC0I+8BQe4YBCsAVcFE5jXLICbDFQ+SMC8dggsUF4aA3IrQOi8wQZ4XN4XwytuwFUHChI0TeDUQS0GWhisT4AcwebndSmgAvKCDhAzAWkENxTwQXCqeQkP6IS8LAC0Y15rxHtJgCoE/RZIXjAmgc2tYJsACwTqDQPXYIABwQZWCUB3oLQwKg7aDWPhIJgBksf8P4Pq4LsAhfZ4BskvOIVwDOEcwkGEkwhHEc4i4TnoVgDVgTkG+BY4F4ADgGPB+CtT6gBrMQEL4BsTvQwng5EC6ALYT8CDgNsHFB0oUoD/MfXNCDmzxYy1g6kFjA1oHcD7gLIAyAVYDcCQgOsByB5YUAA2MbsNEBGYaMCaMd8PHA/4YMC2gfHH2DioP8AugLkEGAkYQAzpg04HnBaYJIC1gBsIiCJIXQxvg+YB+BMIBQA4gHnAEDKYCYDAgYUErAFIfgDrgLjI6DAIhkCagKIHhCI4OYB5gE0ARAmIUAAlgDMDPAmz08BegQYE4COTv8BEgecI4BWYLkBcgdID2A/Yi9sjaH7BIZRTKMdQzqEcRDmJhucgIQC9BtYhAGWgRgEJBGoigEZgdgAEASYfcJOgJTAwzfwwgD+gOAAQBgYag/ugUwHFBhYCgGLgXAE1BA4aQAGgCQKIxuQ4QIMghQE0BDIBcE5MOgNEx3w74BXg6wD7CMYdABJgEQJXBTYDgDKgLwLHCCofgFHMygMrCZ4bw9OgnABoAJ4WEJYg+wGXyLQzYGtMtDPwzJw+UAEguAGqCS4gMBkgnwC6AE4fcEliTwLfxtR/eM7sN4CQIJoAiAMSF6CMYOEB0ggiGtAb4LQA8Ak6J1A8oBkBOwIuH/APYO0BCgR6E/A0ywxEfkEOgiQEWQjSEOQhgA8BGQdIlvAcUDwQ+QCzAVWBQX5QBhmGF60C6B3wLxh1B0cnPAd3AmicBUZDeA6apoA+YHMBsgWuQSc1kl+E5+BZASLCZD6gpiBKAosjYhsQho1sSn4B8ll4LsKSYGD5RWUAH3QfBulBICEBk18IAQSmAmP/olIw0A96AuP5HyDUeRNHXRcaAQyCTxW/SvhL0HsY5XdmHkADEBc+VdQUgVJEhfiARFuFEGXK/oLSgU0AwAJ4AJ8qbgBgA6JFAP4gfhJAAMzjf8A+rhdmSiwEYAuYzf9U0bIEjxJhjlF/ZvwBAGD+H4CCTxUuYYoGBqQBWAnABYBJ8KkiTF6IqU8VLkasEaA0wK8A3gMMAoA7wA8QUgRsBOAEQDQA9AAkg0+dF40BSINPFSSzidIE6MCnCncBFoOQFGBpCMzxqQJqij4DcAoINCTT8gugYkBMACACVAOAhMCXANgAPA4gQcBnKiTgkoELz0GABRQU1DfgGkFRAP4NdCGgdcDbA4gW7EGgXEA4AtIB/FeASMA7BZwV5C9AP8DbA/4P9CrgfECsA4gSbFSgVEFVBcgEjBVAO8GhBLwSDA2AXkBKBXoRxD4AO0DSAB4MbDvAMMGJAbYJxDaAh0H5BNoR7FVAYYb5x/yCDCQpSHKQ4TlIPgCFgrMDmB4oTcDSgQECiCD4j0DZgH0I9BsYLIBUgT4MCBu4lYCygc4HkAmIWsAhglsDKBXouMAsgawEnCnIoEB9gQkJoCDoZkCUgG0GECFIVoDGgckFpBvYjUC+glkH1BaoTIBfgb8LOCD4JEAigaUIIBLoU4Bjgm0I+BZYIUD+gsQMVAeoWcAeg5cKyCR4eICkgO4L3CZIOsBegXsKFA7YXICGgkkKwCbYxkAAgzYMWA64pcDJggUCoA+IXsCzgdkHdAy40QAxgzYG6A64KsCYgNYMnCj4nAAGg5AF2B2obICngLUFOChYId30c35BApoMdHgOOiSAvSDkARgHXijwV6CcAIIKqiXASWBmAjUEzhpQzyDPASEEhhiwvuCnAJkLMgpAMCB/ApkGjgxAWGAqAxAG5g+wN6BNAdsL9ioQqKA9A2MGohzQLuD2AQsFzicwbyCvAfMLlgyQT6BoAjgKthfQKyCrAVMIFjfQvCD5AmoKxiRgLiAiAq0KRiRAQ6DGAlYI2hXQUOBrA6QJZjZwYCDdAbEGsi0gOaDAAkAGFhPgoKC+AhsIAhzgO2C1AfQILh6wk6CiAiwFsi7QziBOAtUIRi/Au2CLAUsDWhzgS2CEAxYDEi9wyCDwAowJ/hDgrc3qQ35B/SE8B/0aKByQRQHIBPkUuCQQu4HnBrkOOEawy4E2AvkVQDdw0gBSBfcQ4B0QXikSUSWiTESdiEIRlSJKRdSKKBZRLaJcRL2IghEVI0pG1IwoGlE1omxE3YjCEZUjSkfUjigeUT2ifET9iAISFSRKSNSQKCJRRaKMRB2JQhKVJEpJ1JIoJlFNopxEPYmCEhUlSkrUlCgqUVWirERdicISlSVKS9SWKC5RXaK8RH2JAhMVJkpM1JgoMlFlosxEnYlCE5UmSk3Umig2UW2i3ES9iYITFSdKTtScLDpRdaLsRN2JwhOVJ0pP1J4sPuUX4Tn1JwpQVKAoQVGDoghFFYoyFHUoIAdBhAWkFYQ9IMdAUQRcC2x+QFHB1gZyD8QuYH5B5QR0HixZYNpBjgMIEdQoIOfAvwIWDlQvAPrAmwTgEpxeQPdB+wLiFSRggCxBZwJmG3QzILVBJQTQFpwu4NPAwgbWHrxVQHJBowLCChxtIL7BUQNIF1Q9wKTBwQTkFsR0oLHBNAOCDtRFAMTALQbWE6Q44CRBEAO6CkRkXhIAhh4gZ+CUATwImj4Ao+CNAyEMCiQA6eBhA9MP3hog/aBpAwcKOi/w7rxTANBokJqBS+VdBED68iYCoOPAEwReFVRa4G6LtcdCcs4k3b5Ju3mTeP0m9apJviT7SPrtmwScNynYb5KwmjRM8pAk4r5JxXmTjP0mHatJyCQjSUrum6ScN2nZbxKzmtRMcpMk575Jz3mToP0mRatJ0iRLSZrum0SdN6nab5K1mnRN8pUk7L5J2XmTtP0mbatJ3CRzSerum+SdN+nbbxK4mhROcpgk8b5J43mTyP0mlatJ5iSbSTrvm4SeNyndb5K6krROiswk9r5J7XmT3P0mvatJcOrCz02Or5ssHzd53m4yvZhcJ8m+b9J93iR8v0n5apI+yXqS9vsm8edN6veb5K8m/ZP8pwiwb1Fg3iJBv0WDahEhxQSKCvsWGeYtOvRbhKgWJVKcoEixb9Fi3iJGv0WNapEjxQ6KHvsWQeYtivRbJKkWTVI8oYiyb1Fl3iJLv0WXahEmxRiKMvsWaeYt2vRbxKkUdZK+ssizb9Fn3iJQv0WhapEoxSKKRvsWkeYtKvVbZKoWnVJ8ogi1b1Fq3iJVv0WrahErxSyKWvsWueYtevVbBKsWxVIco0i2b9Fs3iJav0W1apEtxTaKbvsW4eYtyvVbpKsW7VK8o4i3b1Fv3iJfv0W/ahEwxUCKgvsWCectGvZbRKwWFVNcpMi4b9Fx3iJkv0XJapEyxUqKlvsWMectavZb5KwUPXkRHkXQfYui8xZJ+y2aVouoKaZSVN23yDpv0bXfImy1KJviLEXafYu28xZx+y3qVou8KfZS9N23CDxvUbjfInG1aJziMUXkfYvK8xaZ+y06V4vQKUZTlN63SD1v0brfIna1qJ3iNkXufYve8xbB+y2KV4vkvHzxucXzdYvp4xbX2y22F4vvFOH3LcrPW6Tvt2hfLeKnmE9Rf98i/7xF/36bACpNAUn72CSwb9PAvE0E/TYVVJsM0mxA08G+TQjzNiX026RQbVpI8wJNDPs2Nczb5NBv00O1CSLNEDRF7NskMW/TRL9NFNWmijRX0GSxb9PFvE0Y/TZlVJs00qxB08a+TRzzNnX02+RRbfpI8wdNIPs2hczbJNJv00i1iSTNJDSV7NtkMm/TSb9NKNWmlDSn0KSyb9PKvE0s/Ta1VJtc0uxC08u+TTDzNsX0z7cZ9duM+m1G/TajfptRv82o32bUf9Nm1N97WL7tK9/2lW/7yrd95du+8m1f+bavfNtXvu0r3/aVb/vKt33l277ybV/5tq9821e+7Svf9pVv+8q3feXbvvJtX/m2r3zbV77tK9/2lW/7yrd95du+8m1f+bavfNtXvu0r3/aV/xtYau2il/rxqTjchsvtOl3c7sTxLlzvxvk+uN+DA47/IGOGG45XITv+sSaCP47bof6JV44zQtDxzXFRD6vnVYYVJx0fFjvUcdXxbLz8FYcdf4dNwm3HC8YyHZx3fGP8RcWFx2PGa3QcefzogqYD94FHj6ONE3nw63G/Cy7g3asOvunju25+XE+vs1/6+63Lf/T6B8cfTicWq7j/fJ+IrBME5DcD2UgokPslOtsEBHlWYrRDWJB1JHKuBAeJPYifCRESkXTkL4FC4pTE0ptwIdFLIupD0JCYJuecSuiQSCennU4AkfinIeMJIxIV5eSzCSYSK+X8cwgpEkFxKiWwSFyVs2knvEi0VdGjBBmJwXJO3YQaicxyWj0EHInXwFki7EgUl0xCJ/hIbFfQ1YQgifiSVdgEIokDk1s4hCNRb0o4cYVk+hqhSUwAtZy4y6NpoKITN0ribxOuxHx003+ELTErFHjigsn9NkKYmB4qPXHTjyaJek/cN6ngTVgTs0XhJy7+0ZxR/onrpxrQCHVi8qgDJTzYmkKqQQkbLA4Q/sRcUhZKaLE1oxaH6sf6UPtYIuofq0TjY6Fofm6t6GO5aH+sGD0fi0aHcCnmm9JRQh0qho3QKSaeGlLCIUuHhFFxAxSTEjJRQ3wIqeIq+nUbFJYSYlFDboRYcS3dSjKhVlwOdaaEZ5SUN2FX3BIFp4RwQ3dF2SmhHV0FjVAsLo36U5S36+qoQkW1aTLYhGcVxactgzAtbpKiVKyEfSaEbHGlVKcSdjZdLDWqhKO0nWzCuLhhilUJWZvuudt2RFgXt03hKiEu/UeDEC+unQpWwmAakTbhXtw/payEytWwgIJWQmh60RohYEIHKlsJs4shBfWthN+0pm3CwoQdFLoSot9whBAx/45VT5iSUDEhS8LFhC/nhjIJGxPWJHRMiJPwMeFOQsiEPueGQQklExIlnEx4lJAyoVLCyoRNzw2hEl4mnEqImdAqYWbCrISaCbmeG37F4MdzYfGboWf8WWx+XNu+oVusfhxezH58X+w+brAZ6u0b9iU05b1ax3AwISpvgNuGieuGjAlXeX/bMJRM2Orbugwx1w03E8L69lfD0ISyvP9rG57OG6omrOXtisMQNuEt7ypuhraGuf/q27p4Q9cvr+nin//sXV31x89zTj6+KexvCvubwv6msL8p7G8K+5vC/qawvynsbwr7m8L+prC/KexvCvv/rxT2/wHc+L967v5nR+z3dP2een787JHZ9pAEKb5zPuYq9rH4AvNYxJi12I84vV6wbJqf6H82lhNdL9zq8I5vDEMIgNkb5FJiSHjfeue16uQjYniikTnGtMTvPULbciJqvtret7XHIGOhQmfeFp8DW8upp2X7LbF7ywGu5XTRCy8oj53LAbDxVvHBCuKnSGqmsbGTniTHxuvWE/m37SvjwzVeJz/5Q35mHiQGDmuXPxx8RIxoTt8tx+uWs0TLwbaTxYw6tuQWetotG29cz1GoJX7vUd6WU2RLCqKTX4zCtsG73UO/nJ1bDrk9nZG96bKy0hi0B6sbQay8vz2CGavcMauH98ST3MIrxF1Fj1sOyO3RC4Qu2Pw4/YLXeXBREeTQ9GD1SUEdyI4jiufCpWxybchBlovY585J1rREji2hX+MN7wfHmcgjPaG9kMfjYjwPPGL1EYtE4L3yovpITgK5Xth5HpnYtS1WWuAMbjsPJwnHmuE+/pJEG149PztUWCIqFc8Wl5xzdKMQkxNNSzjX03zaHigEk0mPxZ9NnH/FE4eNBz8c2odgk3RrJCKH75bTXUu43ZIHag9Vnijdw//im3HwZD9D3cSz7SA54UzSMi0xfEsCpeVU2BLa9/iTlkRVW8hGh+eIbXiJ956IQC7O9gsa2iAO8QoamkioIyXkQSMbkSZKVhSscshvmypVwrtCHjRatuAqz81ND9uKd15sP34+yZNO5rkghINFsoLYF1KIAwGOjCc6Sy9vSz6vV4IQLAi3j/YkMdbTvNtx6Q8xUjg4iPAG4VBsGMnN7HeYhianTAIbOcgfyCcPmJfbx14/5DzZAtI5UM5sK0FyepJ73GtLLq7lsN2JcJL6a4/51lwXGSdcmcSDud+GBlGInLnaYBmdjHs2uDGHqH0iM8JFlJjVRz+SpmnJGXUCqMmakbDst6Izk4gvIW1i0jjxlsxhOzxyoi5RpoMJR1jz1waTE/1ycfaRA09LhrANTXhWtUl0Y/Xyi0h2EqgtGZmWY1ovSDFaUYg0Q5fEaIfgN1FkUmy9kJNOYJ226k5pg1guB75eoFUl/KRWgMkNU7iOmy74m5s20t7hTLQn2du2MYzErgSz+cPC1DdUiIR5aI/LLlg4bp/1JTTOubY9mIxErQ9iG5eVxGbLKb0lTdiJaQ+Ggh3liJU4sSXx1JIdbkmT9YLrQCtyCipYfkSUYg0ZfyxmGDohSU5dBZpq6rPm3DRppXawAgtLiFnKwzHD4eWgMkDwQc0AhS34gFgG6JzDwMad8F0ItnFK+GkMaEeU4T4Gj3IRtYfY8fjQgtvuBA58h18Ie/DsFauMxGaDjboDhw5oDwezVcxIKJ5jfUu80xbcx3VkH8m79vS/d6p+FR55hkLuI5jZZc7nvXKwopqDHY/xTcKlJZPWKxaYc88D1fKHGKNCqBYTVKn8RCw2RouCF8SGQjGMSVi2ZEh7wSZCZ/wq5uvBZXEey2Y2YU8eCXEmmpKf4ZMXtZVYLgzPpByE9uSDtVCi4bwZ71Lxv5SNIsAcvhZmOBvMFEdLUqgl29kWR9DowiE+ULhQF2xxxBsLRwQLjziE4t7j+JJDawv7TPjWiFqQxAg1wc7AGHHejfFAaDYmiHNjOFgQYAwjkRGOj1VBpmwfT0z8HNo/yBXq0gld+Be2GLOZn012hGyEGtiDB7kntiBWCVMmOyL6Qv2yS7wBQSWuLYY7x8GWXGPPwaVNGIBqsLdD4IpwESeGFRyCYx1TQmnJDzZ7N+LFk17uFbMOOUO/pPFb8sctibaWzHt7sM8LL0loGn+O2yaPsNDGsKJzTI9GVYqIROH5RSV6wGNTFcz2CVKz6Qf/AUk6RgYFCxErJUpsBAFadk6YTD6ARAUeLLSvBF4kTKIuOUa35CDbwJsSRIcGyav1SvBJtBTOJKfckhRsqYa0QfTQyJ/kGVRUK5YrIgCtklHJkbUdLPCGFagG0XAupkiJtBOCVZQO9xkZQlN4LizDgaMV0KDg0Ki4RtYwD4NYigeF3cSERsM8l7ROJKcjL1CI+IBIMNviyJdnHBzLg0WKlYKrBS4Q6aO6pJY4B+RpOGHOYAdnCHuQYkQlxCbyoLqL64DOmDTipoobi21/EGo0Ks9dBEAUaXEEIQTuhGiESMvSLj4g/MUOEVHgmSgOY8Mo/RIpFAwoD8rOzUcR0sWMUHontCLWiyClRNgLp0rOnIS6tDdxKlrcgAAyZK9EmxT2Y+EwI8TAmtyohk4uvFyoOFXyrCUUOsTtVNxDq0dvhXkglERxEPQsl5UiXMRXNAqEeQcGJG5asgJVI/3HCnC4nHrz8M4y8twH2pMKpFciy5h0IYSDemLolxsQGiRXW036Rf7yXeoqbZqAw0SSkoyUYJY4yaHnulRiZWx7+FthMs4mW41sHIwbvOQZ2FNomv2mitZoTDsGEyQj81etBQcnjtxkOSEE0RI0IHgfP36+J/A02sU9vAf+5FNKDprvv1NQKTmRv5/JuZSkb99/p4BTErNOBt/ebygv5GT6Bs8pkZQo7GR68P0mV5bD/XMeeq2Lv02BpCT9nV/l+yQDciUFDEsYKYgUSimlc83zuKr89fDbp/qsrG1RBMkR8v1rCjJl8duEerln1pag+v2ev+Z4n9Xmm8PeI4rZO6tKeank0DEZWpyMM2adSTnFduevPPew/so9k5kqOU1Pxgbf9bOXHNtCPa6/lGmsCjpA7Q59BtTOEef97YLymzUsPie/hdoJp3N97kNxqCSAzdM3v+Vulc/NW2ktCm3W1rk/n9HbyWxkeDS4M3uEswkD30/lAQpH7d9r4H6OCFkt17OqHDPeNfP0KRf4d5xGpItfNVa7fHru0KHM45tzG5KwlMnCnQ+7gxpQj2Ifk53hAnLCHTpPfODj9n28UHjB3xwJwgXW2ZUZuKBsQ70Hqk6v922+HdmrlNc2O0UvhjQ8SB1PT+Se9cg71tncNc9FYg9/PXD2YW0Jvifzr1k53CzuXV5wH2V7KNvSucHrB2pASXfKHpfyEz6WFJdyDVLd4SNasLnno1xRUCxyhB3lGB1qHO4JrZCrgeQnaosuI+FNa8DTm9z0/tANve7sYmMfBpI2KEcmIfB+D0cWVFpo5XBfrGFrc9QRvqEMWg56TUm4jKtxUFU95W4UbJl9Dq/hWlMrkU8pX5UWnl6lALT1V6SY40omA9fvlerg8IlwcyIb8styLIXXtbSQcoE7Y20eeNSxMAsqUeAtlKNLEpChJJKANC7kjeJ2SS5zMuYd7cZWdNYGTyl0l63uL/WXe0qxom1nzchDnPlkrDnXsy9KzAWZP0jvcBeT/TafyO60bOhmRwe7dJvaH3at3VvyS8pjAbAhKR1O5q4nc915FpSk1F2g2+JuBz1dPOVwh+mqHuST8nh5fCL2Ci4fOHKO9EQq+PeGXxbHFxI49V+uc2snpQZSLcXuHtkdmrikOTY/57HJtHu4pnQhmdDnQXLOkf6s4ZEC3BmtH1ozqLq1dfzq2do9r+HpWhhlT52SPl1bzU7VSu78DLnJCi/X9F9Il7yGeks/on3wG7TsQfc33rnjbfdU19Bc7k9jR1nyFI9PC0N5kHnaFMrWz0L5o6+cWmC1VdsLX6DG0t52bbs7whpw/6TSoi9IKRI19UdXtqEMXnXpy6Dkc+QslvDxDnp2rC72JOWFCahBeIRUV32xURCSplV35dB5a+Wm2spe0OJE6ROYgwk0wARWIdYAuhm98DnQxHWkM/xFAvd0bVgqKcmODrI01TL1At93jrZI+VeqvRvUUNf05sYSeMApTaq2XUvImvnr0Q/qp46WQdlY3I31Q40Hv7Dk8kGX0alz1+OV+kfk6npPfYH2QQ0yStGnsFr1kbUdONWNxCYURt468tCJFafeU++w9CPsorEqr7kaikZjc0ZXVtFf/b5eQC3j+6Wn1hpfH4TuGDdOV4XtLf6WSM+ISMtPvDGks/4Ia7Dh/roxlRKoNdAuwQs9xWOUxa8eIz2jEehmnICfncax2JBnaaX9RouqzUF+aCkqyvmVRnUKO88e16N/N6ZVVrXwaBMR4G5+co2210gDG/JwzeIOyTNMkEAiG0YR6LL2X8s5jEDYi7KKXRo3cjPa0eYYsxlNwQUjT9azjF2NgZF/2qnK0uYgzxtuPvJOTXHNennkfCEzaxphGkehC2qKrVhKCzbtgTJbX9ONheB+18bqR/CDUubRy/MreWSLl9aVZ41lZHuwVJ6SpC1c8FzTtF3QQUuuF9Aqon3jxif6CCxA855qrh6TXW81DtpeW8EukKipHSDeoGmuHKSoK2nG5Hr2bRShhdF2Gbco4cYMyIw6pZfnDo9RZVOb3LVcQLtv1GqcTFykRuglpydQbQj7Uoo8s9xPeeEKuduQkmiBugDdlvKGjD3T8yz8vZqoJdFqQc8Bf/EmSwlBEg4aOra2DhoiacNoU+4YffH98jSn77t+Sm/CN1VrYGTuedATk7KkXhtp8KyhzLOeyzu5qWcx1uWJPnfBwabMs6/qWUk/xa+6PsUogk+jpmVs5klTj2YkpsS6cuN8ZHXLR88XnomgIV6ms/JhpOEaDhzvrPCeNTzteh8k8GYSPMdhZzzNmTcgBj7db9y1e3EN0OfuHflnzUsbq2303IqMPWrfY+Tpua//+PkamB8/gzcr+C2Is0DiAtW9GRraQAduBsn2I4IvaLagF29wRzcAw1uUWzF2ARDeQC9uhpk2uNF72PDEb8H/3EMQXnCUQS/a4Ak/ABttsD834z0b1OoN/OIGi3mD2brBhtuAY26gVzeQ1RuY4n1cJ3sEqHSPC7XLfQTRfcQoBkEX2F8xiEH03uNCBwO8Cx0AD91Ac29QbzcAuBtw1C2Q7pSq21+B+gvYr9DFYIBvMYCBvd2MhG1w+LbYu+BEbiCb98Um9hr2K7YvuJF7CkvMcBVIURt4583Y0xbnF1TqDVT1BvZ6C3oMDvseYj2D/gvA9AZ2dAOtvoHF3QDIbiGLgaDc01Y2nwLlwVvdjo2BQf4AbrWBRd9CQz+iIcM74Dc343cbuNQtIvQQTnoKG408XOBjVkv73CM6NLDKgkSLfAz07Ab1dIvBLJ4zoOAbzOt9pMlSToRt5hqgqIEV3qDrbsCG93JHj+jNcBaegvS+wUnfIk6Lct3EtYZroIFuAOQ3SMa7yU24AJT6Bp90Mwa5p5jTtP8xkLjBZNxLWOvh3ZDbLYq1usCu0Vkw1Td4x/vxiYBtL/GlGd4DYHYz0PiUK3VoN62HDBRugEG38Ncgnm4gHTfg9Xsp/0q7zYtQAPjeDcLsBo14g1+/AZDcgABvMP/3HTMEQBvY+i389lDeuJLRwC3cNlj2mynqzcjqBnR5L9fJLsBI348w41O95j7wDrTHva/1wKpoZx7tktaGX7G2Ja8ByeYtAZtRxM0g5gbieoPyvgEF3oC4bwCH9xCuHDocwcnRyin9oRsvLNggt+9Hq7ulEs+CAlOU8e0TWSdyC6LxvnDh8oIrGcZ8itI7xEjn/uhvd9fe58qD1GDNIrhjc5a2jjsDs7mnerelhjLG2pC0i8fur9AmcD53v7LKc6+cQLcj7+B7968+HXpeXiP/gPgXh079d1WzsAbip1f1SzvJHYq6oyXkudwB1PEt/PxyR1CA4eM9r03gDkop3AePeg9pqK+xgRdpWdqQewcoM3wW8oxF7foRrB+g5/uo6ex3KdWPWozN5zUAAAbueWHkWS36woj05mUKmzHY3bWHQMCDfLybT2QvjDLv5nO1D8LQQ5+pfiHDgs0zQr4Z7N5gru4LLn+0TnCQ1TKkvfvVhQ53lF6oxHsWir5D64HVAnN5Myi+RacXp5/R5D2E/398FvtSfpRnrgGjfDPSvAFC3o86q8eB+4+6g63jDQiblyZssK73FI3fdwEoUY+6qc3ne72ktp31ADK9m57ClfsU6MxLKHbTBrJOX2oAEPt+bhyChRlaTteAH/FFCNc3abvY0bWKPB1pBGZ6Dy3kMZpi1/rHZoyE5GAPj4PdS/sjtY1zfDoS2LSH+kFjNj0asQGyxytKNri8G6zszRsmti8KAB97H/WRV38U4xN4NOW7dNbWyU1flgC/fDUC6NWb971sRucfAC83sPt7KTmsc+rNtcZaRZ54jO70YnhMgM038NfbFxws/2psxl8ZP9+P+xpqn3rK9cYq3RjAnbLmLa2UFqjXjR/gNWveN5JRJrF4eqhtpAffsQC8mmYPXxbhWP2StqxNndUXKF2+C4JfOb7/yB25rLc1OtL/ujt/a4TcpbAW3khSLkOT+5oO+YI+QjewlDfoznsYIykt6lf3FADF+NXQo6GDvH9hd6MIPMvjCz18gUZVN/VZShe0KkZWUL5ph5F8LZUybyy99YBKl1pmRKHlYUfuBT4243y9s1Sq6qMxKvfXwhBJ3rduGBexkqNWGpPo8bU5+pcb7XNP/aN0k/L81teN8H6LvdxvNdZl10c/iDT6shK/V660lp5cWOdR2tU4dgSA/T7aRuXHU5hx+JFH0BDLwNtftm8V8R0uvjPFF4bMq7P6R+lg1O35wkgAjg9jBj013qF4JdTmifedLmiQL40Z9z0paO5xX9DNuEUdVyYZtymeWdCaxxMN79kBVXeDWr6XkS28bsqDFPavQ++sfTaqx2dt76/GQUlovuS1/pq/+lKV5UrkhXGguumveDdQ8bnuVwgN4y4jEyS560GqZ1t9t55dD+jJ2uhdXeMMxSfvD9nL88X0zIiGdk+jnkO1J2jTYzQO9YwJjz6Xu3muRJcfT7vN0w0yiTYBOLKn0ZGnkuMZU+nlntUVIhXYMV48tXlHzB6+Rkf53+qX/pQr9aGe1rUeRneeZ6XhfZOPkQ/fK43XX2CHjT+lqr5gKuFqotKonBjlyi/jOngN/Yf+7nJBTdTveNrSx7k2du0aPIcWbYWRmBpn1kV7haQZ9amJai67O3pSPdHj2Vm68RQzM907q4lG4J74PBlBh6WMGdVwZ2NgfZCva2JVoPHvY7SA3D5aiRuTKPnlx8+Xaz9+vqfijHY/iVves1NGvE8yM+/3GVs/aTl7/z0Ye8/w+Yl3eD8z+H6KY/KDgfjFeHyGxk/Og+/3GYA/aRZ+r29cWf13RrbSg57ncp8890kM816f0faTE/f714yNP8kbZA3cn2uS83+fwqB+pomyqtwzLZjvbytrzjj6SYP8e2VG8k9ONFlzvok0Zhe5JpFGVs6IP0+MVLyfWcMp7GtAk5yM1mGA/URa3rUBCPAIE3BYw8PeK6vNENqJ7XrvxhqSic39+Xz8nlVBmcJKcjZ/fxUIgTOmfOlc6b7kSD7FxYqU5p7sqLNCqJ1W5uxIrslN9tjZS+FXGe4/hSG6xkoiw++d+RXj/WcAfsDo/onW57dQINR4EkflnlAYGIUJlSac6sjP5OnJY4TXwCps/o3UNb7PqS00h9eBBDgFyWnsJbFHJIEVCsQQ+IIDKMFzmmvgk+dOuJD8bVbOE+FIskzvPSdPz6zg6cA2HHeEhDT2m/gt9GRHhZ3yxIaOJAIJ/V0VlAcmokKfoRQtaNuQH9ZQWXlTwuFXY1XpTsxqkQRXjrxV5KoUpR2q8pkRsvdzIxuss0KxzMXkt0g1cBbJTry/LawnlH8ef8VOB88dyF6aI6PLPAvtKNCqsNOcOPI9FIvWP7FUuUZeQ9vufpGl8Pc57C7ntUgXd15yhP3Kd2XPOw8/kUzW2dl7lzKVfy/kBMCN09ULfqWWQeE5lB8ojx0DoOKkJhV+QSu0rC9tHf9mVbWpp3AWSUhmL3Ll9do05BZdG3zToWQDPqSgjw/fT2W+SHM0SFnVNkLDWqUAu9MWadPQhUQIkTqul6fIWFEf1fSOfm33q1Srjz6Xe8ZuP2fKd9bW5RF3cxcHGhblAdoqh9iZ5BxyT1aCtJThqrAtPKuxwqIsXZ3iblMdgRpXkuFL0cKgZcPVIi1L+ww9sepdSatoInRuVVnVXqmV7FROqXfcs6ib6i8W+MFzJXuW/SrDaKXXIEVV3cRKVO6T/EO0XvlBOwCDOchJgZvAmJzB3ufyPlBeS8LKlyvX/ujp0OJxqad9hrNFq8iu8YNV63TgTlUrtbRQ+8qzu4AL159CB+RkuAv4NadXyiM9Dk/xntioyl871mB26QwFsO196lWhgPA4W2uPVDzSnJXA5d71dEoydkw7oC50dGd7vVIHr41Ari9GI/QpyE/FajUtyYYyHU3Xyzz8FguQrGy0wKgACsCF2bT8rBDuTLmsRTpKnZ6Fp0CHsoyF0NaO7vDb6u5YZ8eOTeRtFa0fa9BWs4b66GG1YHo04yVjGDjOfcaQC1gz+NWlLZIABM/pXdvip3ERHFRruE9BTubSj3MNNhZgn+cYEyohQBod9ct4bBv5GAWxX7TykZ547YkmTu7QiQ06Wlah3uz6HVaof0ebJppbWPPEWx3WmSpS/i1NWL82TX+6iB6NW/T+SvtUhuFs8+nqI083Tuv4Mr0GXq/C8br9BjoP9BdZmnpPPOA5WkJ2h31bN3qEGtoW7RV3Hl07z52NftWspbdid/p67jmhSVe2qx6Q/WJ1lx6/G/Gykqs1Rg5Imrax60+NSJVhtExeKFENO6Yn6npAdmSUCM2HUTp3qEv68M3Wng/+qkWCp3iNpgU23jA2QDdTX84a9JJQld+27TfaCs8mejfkTZ81eC5+pGEfptZSOenoF3bg8W5KuNHplsJYp2k0pR2DDsYqSDXAtGdqK1hhU8IrT9nGhOx9a+GNZzzFwClPVfA9k9n5FRbeeGygTZ4R9BpTCVQT9cJaMKzcxDLou41g1R3jYSVKOylVt/ZBX8OqjhZP+y9NoK3WW1+DpSpo6DQ+V6Ox56m6xj7oW3n6NOLVDqh98NHTjXHyo8QqIdjnoyfVv+ivlWd1llU9ajTaoTXuegElUNn2zkqXK9EfGXepBciq0ZRWtyq32gG0TGrrrZRh9c7V8qz2qMtqjdZeK6Q2sWa0qaLLQ/2VwmoQdy7ysSnV0goqSVW0shjpTf2pp2+sLv9+tlQ1VtRDcf1SqpEEn96VZNdj1Kel9SwjL7hD0fsjyfo4dWoi7dPTjZKsx0G61AI93aMuyDWjTX0un54aPNMp81jj5a6l8LVRSo42X8tDpG1srP+SqmYMjJA9YTUjeSUBTnkKvudifbo+FNm7uQgtnvxVK7lSC1M9O3g9NByuWZuPjuBJG/Iwid9a9/Qq73i6caDnTSzGY0bi2jQk/576PSOwL3MsWjNseyHimsZp0/O7sqrfUU+16qxZHukL9G6r/fi5d/3x842508s0Ez2+n+m/GnRXzujv+9d0YA76qdIOle/TdTmZfRj0NM5EYu+vgLZjrmTSBTqZvhn0mU96Agdd3INZsMkkwqDvazDpMOgUnVntTMNTvklP1GCKZNBNOnNqy79zPf3bk/myQb/3pJ92PPcaVnK4J3djwmIwJTHoWp+JPd57Lj7T2zZjh3MHdwRw3wa6b7Pmzn5dJ1B/9KsPujQHveiDaaNZpEk6uGayJXn6gaqV3+ZKJgtmJOT9VTq+ZnIy790erm/SHOqlt23QNTroux703c1YzlwDp9gRsw+DbvyZWDqcZYXplB50UU7mHQZzbYPes5ksX755oAb0r3KTPS7uD8o7s1ozEeb7KzhbuYYe+0mP/Yx+ZSUPa4bLl5vsVBlgzUzbDXo4B733g3mTQSf5YApmMGk1Htc5ubLIX6AU0x84c1YKJaFSOkvTcsdKHp4y2Avc9z7dHUG9dNLOBohjzn3vNwsKI+3Jq+QbZKPz7819pnxnLwvOIgN086a1kW+gT2OnFSrBd3rCZzKWoWHuwHxZGg2hLXtXAh//isR2V8UeDxKCnDOZMuj7Hcz+DHpfBzNls6HXTeldcDxPGUyfDWYTBrMYs2gH4AgzU4OpmcG822T6IM2L0JO7oSl0XM8mN/kV/eSzoWtL+gCM2dD66r6QPTqrZx3+CvlkhfTzDyYOZoPXTF6MJagmWsBMyljKJxSePrfDNZ5L5+14lMOhnPBXuYztqlJeWzfll7RV0/lVYw2TFaI79GpOOksHHeCDebTZ0SMm1wZ9xYPJx8HM42DSc9CtOphCnXUoRfCosnfXr/Vgj4+yCn+ZrZtNbZVH3e/hzmKFQ2mEv8pJg0rAn1V2sbTMHVmVtshehWJ0L88K/cujX9B6qFPaf6h3fBYrrMinVnopvfwWb1KxGxUIVHplZ3GdC1uB5aTrddCxP5mdGXTID6Z1Br3xY1/LgEZD26O1L+q4/OXpG/vvr5rr0QqhHVo5pU7QVmUY3WfebdARPaa2CwuT7HosjBLIbw88Yv1b67RYA89iJnrQrT2YkB3MbI7nehNo9bhC7HzRQnolOsJ9lj5u6B1cM3Lb9HFIxcYyS0Ptod5EDUKi6LUeW53lKUe/oPRqweBghXdMecxkNXOlXluLjfa5d2wU/eGzNS0J3yhdRcuj19D68fRrddUjuYNvYj1Mc8yKPT/SFlvE9Ogs2qul7rBTVsLE2Vja3mvfuNvAMiB7W/psr4f+2BMm8mbTN0Ftpg5nsr6RAVa7tGzyV7llhXIT/1706dIfqhath7qJhSlaftdPNMI8xXiULteGb2r+ahuJqTXw0XtqA406iHy2f0XHH33r9M74BfSuItXM0E2m42fFzzIXPLvUg0rMeA7mWWaTzvjWTozxGJ/IC6jEHNBgwmi2ux4sNtRjnmK2e3+5hv2v2hPvLK20BsiqtnEon3gKJQS/XLTYxifQvxpJujZtrx4NijHTNLsUQO8eowvtmJKsjMHTDjcrcRGT74OJ9dmM6AB4bkNbiu4gUV3rjUZU4rqq7j/aK9apVWR3Xb2Wd8MYD3uu3y/oETLJXNLMWTKU4Q7L+/PN1CajrTfe1l7phfHdRbmFU/ClC1O9tCfyAo8Aj+qVImIJr+z6MlbS/J7fdq0K3nYZnfI9v61wsCgPehMiruI9sdhMcMym9umV9Hd+GocsdqdFxeZPfwWvmS6cHcuTClT0VG9ibKDH9HvPKXBcL7yNLjyDQCsi0m28p/wbXSsDQ1vHX7FUoE/MYpR+5KkeUL3Qosovfmt0AZeZURpgEcymJg5tCD7F1aqJj7yGDq5tG1fIF6T6GEXA66kXgD6PFDOONQJR7/T7xiqepFihd9CWHiNwYw8/1VZsID6lKzn6X6Ospp9Vg4xIocZUrz1lSB/jZGirv15afrxzc21GEawH7oNCMKtnSfRoeuLjt9PnGhtIba23Z4TpU5CWqd1A5h/9gnEgHHQ9xuoNLm/tM7IE/ZdRn/EDGvq4Kv2ycbuUr/x28JSqj5D+aN82Doc7epOltfH8W9kjWqblJGJkdmky0TaWZ1s42OUgFoCJ6XE8e0734hkK+hsvebKe0geaHD2OMaonOyVc++mpWY/GOo06PH0jG9tI8ijhPPeorfAamXnkiJpuVI/+NvbSWMPjed+cgz5Fb760pZ7m0Jf7b54O15a6acRS9VZYVDi7lXlzEUYLR2tvZGUsAZW01fpofERTF7QAxMbVp6gvRcsgr6G2p3s9snLSXLPnOH2fHEcyjTP5njnKAV7N7MRazTP1pao+necSOYCfMEE2GNvTFicd5v0H06NjeqbzfDdW+oLqj58BKwVrC/y2DU4RaG0bwNEFaOUC4XMBC7lAnFw5jTZ61INgKpSjsGMdnLoOpB4YeAEdWqCeLjHuwINl+iBP5BMYLgBV6VoPih+Io8AjVe8DpBeobOvwROHwHpG/RB8ENRgcp11AV93gyHUBl/geLKslQBhoagtowSVMIfC4O7FTAHbBtAvI1gKHdoH3tMBW28K2AxdKp3f2In0AIcse1wNgFSDnGxzUBVzaLr7iqbAqsHgBbtoFpDTQR9fu3p9nASYmMC1QX7v4K5CjAGZdD5/bZ4EiC6zvBgCSDuTgu0oH9uKvwBoEBXht4UZBhwU6eAOVtesFC2UlwOABO7wLaL5bvD8gqDZIeQB67gKMfVeKJpxagNnzDXDFu0glcNoA3lpbaosmCFxzhztAwO0q3ttGGtlL4c4CLYrwWABDBTt0Awy4i7IN1OUWWQ64NFBomdcIcpxS4d2QBGkI1jCQ+VsINlBYN+i3a4tO15RwVgWS4FHekCIQoDeYmPvC+VfWhi4IBQtMfooT8BFdAJQSyPu1kMxHuUUjmnrhlVVNZBdCJhflGV1QBsQz469dKM8BJYUGA+W5gNZY5YvfINvN+ytp7KWrC6Ihi7m5pZUyzI6QJWCYlwiY4HTSadno9s86eSEa1F5Xd5Qi5OfqIFCvD3dWQ9VKQFmHnCreE53acBlINtBvV2x1dAS+gFN4tqtiPchJxeaAL06Xe1YO3RZ0U0+Rrg543JLXD7IBrPlSGgEfBRN6AxGbQgh/leaHfyMVQEdWMcalz+EOYpdjacUkrVuNg9doK/CPSzTqR84W78n1wokvuQ+PiqDZSAX2oSldrhn6AHm+jnfWyk1llftsgdOxydBffD+A3DcglHQXx6JCVSh/0JqmHiF1IHgymxDa8let4pV2OAuVABleAtmDX7oepU57LuTehP7SRMkU2hT7LKB3R+sfZYknglC5nusLvAZKTmXMfQk9Dm403CneGap29G7du8l39QiZAdR3s+sztJ/aEC2PFob1IKuPuqPd5tWCVSkSVx7czaVdrWIz+yyuL9Kc5x51nOsfpEWaK1dN2wv9r+3lVSJLG4VlQL8E0H30cRcWFvnBwoCNvIEoZHa1MesRew4YJq8kAYFzAfO5FnZ147+KgJl3PcjJUpJZA5HA0aIOowjsAxYGFOJdQd9dSz2V40q7cuhTtNKsBFRpUewBZV7L64fyLwWMEACTLe5RbGH+iv3v0IcXvmwgounxbsy/R4v1R8Yh7EL516JOLa1emFUdAaWVMa2EMs/3F+cejvA9OLpryWU8xdYWob/9gkhrRVmt1kO/ZpSCN/flMp2IbmPbh1qmP4W258YbeDQit613XnoEOWXMo0XCwhgVSFulwr0g4cfY40BzONWMFY+Y30aD/LV7pbKB1GkPuVu7GPXGKtpetABbWpQQcZfRi7XEwZT+RnpwB4l61Cm1GC/ZjeX0+EfLYNyCXBE1LdB+lzZ56/2VGZ51PTV/FTDYFxvg/bsWG33ZrBm8/AUgPRPQoSd8b1KDpz/SivtjozpRAYj9zBdnDcJz6x2UDW0p0rKMD3nK0Ib4BgUoI2dZFVjkGyT+xRsfFji4GyTi5Qs89o2chUc3Jof+WLAO9GofIj+rNUoy1FieKXzZA89qch875ltCeM3R1j4fpcXIUOhzYxK4I3/Rbt/5MdTEK1dcr6W6kTB69MCvrbVB3ppRKNegp7wCaflmjweLCsrzFli2G78ZO+kjjM+Nl/Q4nlkujrvwwFIb+RHUWZvASUe864pl6F2d4ulFi2oURGzjHa69NcpVSo06oICe9AJk+5YJYzb1BW4qk0YmSqxx+41nsB7Gio9nK3hq3KIMQ09eacJMUGTDb/jVMtYCitcI5NGeQzEjfO2nOqLGIaVdP3X0Nf6bKHQrw0TFPpcIX4DjxxVWdc2zFfTUoi7jauNA41U5CDWwscKgr+W5Eu54Jrq7gD7EmQ906EPaygWlzu89d7gXNAW94/VhzJc1UBcauA3ROFYlknjVGms/lQ2lhacjS74irBfvbOwE/ZXtYjyj3Bp7QPMbQWkl1HToqRQZhxTtgPxVf8Wl14MY0WEftIpap2mUYkyrH+FZvuFEGhqRXvB5vTa/Naug3N7IB/lBCxaRmO8WeNSLLhA7vzLSlkrGV3qB+8YPZcaX5eA70F9fLDPYXSkC5BsX+ZYTbZHc5FdQYHimkDJEU93r5b5eo7oGI20sp9YSP748vxv/S/NjbMl9HummrVBWhX433+LpA5qrKZ4ubwxGTPUoe8FtPj24zeIAJ3ZNWU/cMFCwxIC6eJJ5neO5+Et55aNIgFQDSxNfDrQisfVEIhXjq4h4KUobV4rbLBZfuYh5oCSJFArangicYkB1P5dIerkysVzWw9NBcKLuU2JLs7bG2sTRAm1JPDRRlYp3ECnxT9xF8SfFd62i9okFCoqXKI7kJy+mbhPXTpxDEPm6CGxgT9GdUop7ETUL/DoxhOkzKdVdiGcFAlgTq1aEMdCo2sXiyys2jzw6YoKBpMdzqysXIQrMtIttJYYt+yU7/Tui78XBg3rblYgjB+9ESnzENWXvYJSJzSvOoYjH4muJkEzfVGnibg24AB5jdV8iGW7pCd+hhghgc/2CQCiW2kUbA13N5xZlTwQ58bKgHgirImk3cZiRFjqpSruyLaZf4/p8Tw2uNNE+wU8TO1rkMTLtpYknzB1EGKM/RJTIi3Ipzl58a+4MleS7uJ1IF3XtQjW5FLFS8zLSI3ozHSalist6MS3VQVYlUqUY3eDgUfsr9IaBlxg6I28gg4meTd2tNH9V1Y5f8AmRjSauqViXrKGJ1MqV4pmLqf47Bi+0Qooupm71/uJYsq/+C/oc9KFacZFIy92j+sVKut8jRaALVqmExtEVcHGGL46c2M7oBbW/Qk28iMkp3rI4fiI8k/8Xa/1ivYqzB87zxeAVJY/OKHGeC5X6IhaiuNz1YkgiG1JJpE3RwsV3VfaQbfr6Cn07JZFANFesuYGcsOsq78SC47kivmrNpID4paJhF2RMPcUyk/O/uMFDxEtf0IuuNV/cqxyKPnfUC+7DHqlNFDorLs4n/WmF+n4RbVV0XFEWJ5akuk44KwI8letC/a409ddroG31vQAPHoSV+BYAMfTEshY3vnqNWKZolqib1OBKVeuheabPcjcpzDpF4+fp1NzB9szdoOdQT9EU8SGVEG31Re/UE7F+7S06te8atKLQ/FJV3RHLUdsF97E/ooWLmS+Oq3jjImQ2bSwyXy6+OhRurh/+irMtriO2uopBLU7s0LqCAsp+m3oqCrTagTyI/ykeu/iNokCLoS3CYdXKacmbnlqp08aK/KntRU7UuyLftYr+CmqzcpGom16MHZWLDeu/9Ybc4eLWalFZD6ulR6hU/T5ok/RbFvHDRUdvopIWeQ1NQLwUO7qJ6nwRNdkvNpn64EU2rnePaj00NObZf+J8Uq0rTURZfttcieiRIp9fFEroc/H/4ebFW4YOj3KFJHiHI+anzzIK4pqlriHzSi+aUsWXLsZOWB6sqO9HmNcOQLGLpwovxLGE+/T3XpRa0WvpuhRftPg+DjFR2y+IuL5hQSzuKiWxePViIyOxRlwiZEKTKuUvajf3efSqYoSy960OIttiGjfXI9+R4YubrXShdzdaQ7P0EXre7t1Ex5Vr+no9lCtH0qa2yNgAqor5rPdUMu+7M+AputzE/1dO9OwiwPvmAvFmi9rN/UVw1cI/2gf4jrWpRil6fGmLpFXt5JYOUEZveLQDPoW1sRKxScuVMWWGHfmWBG3L9bx8o5bJ8WlcgfW7CL3GckahcNkIVp+lRD28BJ57Ukm/OPAiEu9rhYy6iVovDrxIsMZm8K4bq7CSqq5pA9EyKbm0mfhN3x8hdvE9a8BZaCUGLH0pRXTiKjKtb4oxxuAaMe19r8H2BfdIhaj4ImBXUZpFpL+2SJrwjTjGvmVGyyyCazFW0Uvim+67WvRTSIuyrXy6a+S5XO+JbmpvfX+N3oTf+rYI38rhuyTu20yK1yOH2iKxdrUeyrNewNMNskF/fqGbvVT166JnK/lEqvLXswbroR+4MElRqicUzwVDLVCqkVLR/sXe980gesmL3AtnleR7inRtyMN9A4U+VG31NIS0L2Mz9Zd1XvupHHqC8+yGHvl2Br0bd65Kl3z0rT3uyLdmqNei63si80Tg6cZI+L63Qkqy9xvbGBdxvVGo95Tvj5bfaJ8VEofQk1Z851G/7zAilvOsp61mVb49RCx331ghbvDWr4mdjrQwuVOYZSjNk6Pvj1AT0RTxzNt9K5M0V/LZxfAUL+WVQO6mx1Tm9ZhdDdKzoL96QE9Gnsvgmnja1TwAMl99V4v311rKWWNL42pPXmL+b++j10CvzTPcd0ng0z3D+gafpsVGrrSQ+kexpn1/gTGG8aencqMsNNT3BPk2gXLPYqzfSEM7fIzc3IU65VnJfAi8UE+3dps1e9400vBdTmJHazewVEX7oHX1DUHQ07eo/P7WHnhx8e2159D2csrTOvyFnv2+wwLpvV5Yy2xUY/yP9BLPM1tUQCAv9b7nBZ4aPwwlTRn2FIbWi25trGJ8qKxiJ9uNQDx/+cTMo52debR5e+brH92b7fZs0z9pr+P8pX/bOSb7r+zNo1cKLzams0VOUY39Z+eVfaR8b0+jfYy3k9+ue/t+W/ujS5C8lp17g7yEkyx38mjfbjrWTC/lsK/1/NKVbT+8XX90vu3+Sx+gXWp2af4yN+dUglNpdDw6eWSf5J1gsoO3OT1n9+b8pVfW7ncnd+w85J7EroP8z509cTrs2NNrd+Xt3bVnmBXSief0GXrh/MjtSLSD9/dpF7sr7f+kO5H+z3knBejYpCPRCTii9zHtvD1/TNDYYe7E2e3oO3ZR2ivuNIpddsuObq532kX6/9mfade6HYB3QpAT3O0XdQrgKAN3KoGOSnqheUPBncay5/Ox69IuPifs6D9vduQ62+KM3tx/9Cg61WXvn33CztzZM1+knhNGSL6d87df2v4990ifvLMwdpByxr/99ndO4U5StN87Ce80xLgTXk5SwF96s+1Un3ZQ2/fodAwzI+QBnGEZwy5fepKHPf92n9qt+ue8iZ3tt4e8qh1ODdjPzL8f9cWZJicBj3257Nepq223KvR3vgla7SvJ+/e+x9ttW5TMOyVRWbO8Zqe361s6QFspqb4Xd8dKmJiwu3vKRy3Pkfv0rNrbSecwXmaM589OaTuHq7NF7oV1OsnlbKzTo7cb2Z58Z9nYBR289rHfyb6qNVAX7KyWqkq+/FKv6fGet9PVnmHuhv7u21FMd7GSeW2OXbJqN7tz3sEJIORz2g/sRKT8VWLV3NtzixX1r8jSvv2rTjHAL3X5Tlz6XOnAqrAtTqg5E+QMC7kOO5mdKb6TTcTGztjeSTpnKued2FIj/pzCqHfyDu22S9b+djvVm/RxnWof9FRb7Q8vdjhjo5xRvfYTj2AHOJpLjHr7iu+cl/35WkJtoD3YdAiTj3XyxanS2wF+rpQqY1gnp0HtEnfGbd3O3j+6f52/dpZh3KlYJdDOdvZ4/pxr4HwxyAOM6ZSKEyVOtdiZv/VH+hd0yvkv7fx2MkK+sNo7jYXk0EddnRRWxrQ/zik7dXjn0JFzJ2ShlTPjRatrv7fzMk5fOgnrLtAvYqRB3ubOIVZnFqocQYudibsWxhjgz3748+ssnjbWOQI45QTuvFPh6JETMa7KuS3tvFOQ/gpKOq/qPAun+zG1S04BO8fqnIv8urNIf3aVMwfqHK4Tmnfepzmbc+dSoRtzH81/80RniKjCODF3+8Od6HcCy0mQR5l3+lt/4UyxFPYa/Y5SYcR118lfnWGf+hF21/+cu1nOUerr8UrOVVWvdI7VCfelNhnjqYn6Zf21MplvhjMsTvU6PwU9nYY+ziAw+XXnYbWo9ynsDh9ETWpQUxjT3n69rbPVThNwByc9nc7+HW1AHmldkRMnWJG3O9MKCsGdaFPjoMmUJlUZRvfvnfXU2gG00tjYqXN8k3gC4DDc6R4n3Mf5Y25iEIeLKuCUzZ0dnmrBtUXyCPo484L83wnHbqSkbcH6ORepJt4pDOw/uu+U5ZQjV/LVC+0wcoIlPM4cIUVOeRc1V5vms7qRg/EzFCOKmL9MAc+LVqGGor9O/OlZqpEAv3UWyVl1p3IuYgP7dfIIfVn6ICXN3w7jWyQWa+Ns8jTKKvJdn6g8yylljzvciMtI3jVzpRbeeWcnp24MoBRBN08r3HMaG7gqPalxBXZguHcnju9EsBGguzCGl5LynStvFMG/bzzAc531M9r3lGEs50S/Plq5dapL33enbIwMtSdS2xhYy4B0yWvln1khUSmcW3EWz3lhMTdEPKieL5RVJ82dMHWqVKyGIXeMYdR67NKlCRz0dKD93EZc7MWZ1q5P1Ety/3ty1OLxFLTVuenhrp2LNMZw/veu3F1rdT036btZ4aWza+A+zoN7CnNKy5Os5yxnyd2p0Ysz8n6v70NinVB2Zr+KZ6LcOnvlVPgvGCnHldzTOis0knS/8sX5KeMK/Eg1BtYiOZPuOp211yMsfTT2TRl2vkkv8OgLlHAtrf4d/orQ4syv52jPv5d67tSne56S1/gRfcFFVjFSZQ3GkGqoPDXqIK6rTt97T22CEluNPdRfo31P1tz/V5QMZxKN+vzV9rSu5CNX3sGIix0dfaW4H+q+s6We0JVVLaq6Xzz7GCVipZ3lh9dUun9HiRGlxMjnxg9y07Mh3x/jUqzQtUhaDHahvb3ndHhxvZUeSkuOfXPS2bj0xnJqB1S904VaEiigD3VtWDYRMNY9zyJjaJ9TmU4pbs81yNVypl4UDueURddZRvtGYtoTd6QmKhVYPOeXW7mzcn3kdNDJ/PSRCkjnZNRHzm7vX3v+nQxPH8lovd+/+tiJWHoPTd7Pd++djNN7h5rP+JqOp+hYlT7SPdXJj3WyQ3lu7ha//P773e97jffhWYnl3u8Pv62Va/KZCtG7hsFTClduntv57autWdXhDq48/07V7P2m5Omxz+/n4XOz31zfD3tv3Kez/sUacmro2L3QpHIlu5gPa+abyZUr3zSoFPpnJYUnciUrSf9GJ6uTZ+X7wo5yyuvEGO/3k9X23HPw13Sjdc4p718X94cvxV/x78htRzKzHvgFpyqUT64p18uXfJ/qRieO6sQJuYa9h4bobFburrkbdEg8GRmQqnxfuT/UTuzaybGEhlAjlO9H7sO1xJ/hPvfn6Ynicg38hUd1ShPuA48qO0qeJFd2JApqyJ0Nr5GfiZwMpLdD/8lTGlwY0CFZgsjtRmaQBCV5+quHVRXoD2cfuPDalvwK7sCLjqwWntiWd4MX0K0iY7Mp8+wRWc25LCvMXwfrX0hdRd4KspFcUKQF+qBBi+fmLBYqsUekbqE7yVt2coAd79M5i3XybOFR/l25cg21DHlQ3pDtxjWDpy9onrgxf2Ul7DSxSuccGhnoXC/XWMMuyBX/RveLzxrKOStH9mJ7O5FJJAdqz9wn/v29kmd1NeVhJQ9SBM0HTxlYmwKVGhJbXfOQYujFkBesR25i2Srrr0j45Fdd7UBa4kk7+aJwRImVX3CQ9VSktyulcKGx8qqGqtGsrUPbCU2ma2CnA90Z0KHAqX5pxS7QsiZ/uUNlDRMud+UH65dKQSce7kT+4Rd7RE4qdyhI11QaC3vX/rhf6YAkdHQzudPO+agTAXbO3Z28UPR6IznsbqjjrET7WdVEtGOwL+R2wuuy1GX46EquXiCfXXoidXwud8ezhjTEPkxt49QTPWguNNnSWU3Bqivb7G7C2YGVnuh1ZT2T9TQ0IifEcJk9Xm4i1di33rROcARdLli21GfzK+4M3Zp7r6ztaE+UUu8sr1kDayvqLN5zY8nL0hdAVbVDzkpP5L81+YgsSTckampDtB7Le/KUogWDqshDQyNSAYxGuH4429RQPRfc9MpH24v9RGLHUAKRjaKOwEf4VYs6y9PlmhSGd/0xcvDpckEZNpZQL1gzsl2IBFbTF7BT1jn0ufpZODv0vHA/3Sx5Ir+dek/+zbNWlUryV/3iGj2jnnR4fyQBmWxQb7Dmer0e9/TO3KE0bRHr6fKdT+ME7fmVJZ6rriGlsxkXGWOoKVCyykHjCqSOu60hf/VNSDX3T0441yAbek+eNblbwW5v9csnas+XFMYKFW2IntQYCUnWAuPlO3am6kP1tmh078Zy7JGooHV9HL9FDqvxntER9B9Ktb+V8t1Ikp1qM28M42qNXtRWPRTXbLyGUWvzKVpmaHi9rT5I+4PdU6KgTMGSVG3+lSXub4Rs/LOMnH0KO0Uv6o1U9WhIDnZmuUeosZZeRs+IxcOerKKtI5qF5qsq29pY/j2klZGqnl27qmXTzvP0o0zybzXluHd4BB+XNt/Ykl0UbWDXwis/6riRCRzU2mAb641qeC62felVlT3vZnRXjDSUZ+8GJaU5Gjr1XNWYVu+sF0OXtY1Qo25jLb2/dMaO6R8L1kYJgUpNfVnGjdxTScO29KvLUpU9QufGrlMrjyUxniQ6NT7B1pWq39Ruu1M1kSuvXqDjyMZAuvrQshl5EmciyXWpodDB2F7rVIxL9ar4OKN0aFjk0dVTrYrrN5bGE1WjWaMjdAHLVo0Tmh4fWVVitfZKy41YlEkjcJ6OlVt48H6MPfgkQqjaQ57Y9c6PllYLoydSDo3h4bKxWUcLphRDGo27sFHJjWdtcA1/2jw1GP0+2gpPE1pdNQgZ89OoUh+tNdM/IrEDGg6phxUaPH16zVJr+JVypV54CtZzGVGr42jZhFMDj1yRnKWdVybVcexARebb8gyoJBsV81cj6htPwin949b7K1dqqKcDT/TuV9oaHSFR/Kqxo+m5Zmj51Ur+7RnQWKh70tevKVf6U09MyiR/VaeGXOOvx/jc+E3vpr/AMmC92z0fsUI9yD2FIXvobNGWGndhCQsULnzT4Vobno9crVkFozXzA+q7/gvrMfSq0K2aGeC5yvbWXkFJrahxsuf0e0I3ZsCPSENke2rZjpZfy6yPgwLqoyc1YxtjS1ber101WmCdyPlAZqb+wgi2ld/+4vPb3/33v/+7//wPf/df/tN/+8d/+Pt//Iff/v3nt7/8m7/+2x8//6XPv/oPf/Xrh1/+9k9/8fkfv/3Xn/cO9cfPOvPfZ3zy0sr3833wJ2+++7TP81mf/Zmf1yycf2EJ3Pq3f/qP//Pf/S8WgkRk"},"max_retries":{"kind":"null"}}},{"rowIdx":278,"cells":{"question_id":{"kind":"number","value":15305,"string":"15,305"},"question_title":{"kind":"string","value":"New Year Chaos"},"question_content":{"kind":"string","value":"It is New Year's Day and people are in line for the Wonderland rollercoaster ride. Each person wears a sticker indicating their *initial* position in the queue from $1$ to $n$. Any person can bribe the person *directly in front* of them to swap positions, but they still wear their original sticker. One person can bribe *at most two others*. \n\nDetermine the minimum number of bribes that took place to get to a given queue order. Print the number of bribes, or, if anyone has bribed more than two people, print `Too chaotic`.\n\n**Example** \n\n$q = [1, 2, 3, 5, 4, 6, 7, 8]$ \n\nIf person $5$ bribes person $4$, the queue will look like this: $1, 2, 3, 5, 4, 6, 7, 8$. Only $1$ bribe is required. Print `1`.\n\n$q = [4, 1, 2, 3]$ \n\nPerson $4$ had to bribe $3$ people to get to the current position. Print `Too chaotic`. \n\n**Function Description**\n\nComplete the function *minimumBribes* in the editor below. \n\nminimumBribes has the following parameter(s):\n\n- *int q[n]*: the positions of the people after all bribes \n\n**Returns** \n\n- No value is returned. Print the minimum number of bribes necessary or `Too chaotic` if someone has bribed more than $2$ people. "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static void minimumBribes(List<Integer> q)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.awt.*;\\nimport java.awt.event.*;\\nimport java.awt.geom.*;\\nimport java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*; \\nimport java.util.*;\\nimport java.util.regex.*;\\n/*\\n\\t br = new BufferedReader(new FileReader(\\\"input.txt\\\"));\\n\\t pw = new PrintWriter(new BufferedWriter(new FileWriter(\\\"output.txt\\\")));\\n\\t br = new BufferedReader(new InputStreamReader(System.in));\\n\\t pw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(System.out)));\\n */\\n\\n\\npublic class Solution {\\n\\tprivate static BufferedReader br;\\n\\tprivate static StringTokenizer st;\\n\\tprivate static PrintWriter pw;\\n\\n\\tpublic static void main(String[] args) throws Exception {\\n\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tpw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(System.out)));\\n\\t\\t//int qq = 1;\\n\\t\\t//int qq = Integer.MAX_VALUE;\\n\\t\\tint qq = readInt();\\n\\t\\tfor(int casenum = 1; casenum <= qq; casenum++)\\t{\\n\\t\\t\\tint n = readInt();\\n\\t\\t\\tArrayList<Integer> list = new ArrayList<Integer>();\\n\\t\\t\\tfor(int i = n; i >= 1; i--) {\\n\\t\\t\\t\\tlist.add(i);\\n\\t\\t\\t}\\n\\t\\t\\tint[] want = new int[n];\\n\\t\\t\\tfor(int i = 0; i < n; i++) {\\n\\t\\t\\t\\twant[i] = readInt();\\n\\t\\t\\t}\\n\\t\\t\\tint ret = 0;\\n\\t\\t\\tfor(int curr: want) {\\n\\t\\t\\t\\tif(list.get(list.size()-1) == curr) {\\n\\t\\t\\t\\t\\tlist.remove(list.size()-1);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse if(list.get(list.size()-2) == curr) {\\n\\t\\t\\t\\t\\tret++;\\n\\t\\t\\t\\t\\tlist.remove(list.size()-2);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse if(list.get(list.size()-3) == curr) {\\n\\t\\t\\t\\t\\tret+=2;\\n\\t\\t\\t\\t\\tlist.remove(list.size()-3);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\telse {\\n\\t\\t\\t\\t\\tret = -1000000000;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tif(ret < 0) {\\n\\t\\t\\t\\tpw.println(\\\"Too chaotic\\\");\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\tpw.println(ret);\\n\\t\\t}\\n\\t\\texitImmediately();\\n\\t}\\n\\n\\tprivate static void exitImmediately() {\\n\\t\\tpw.close();\\n\\t\\tSystem.exit(0);\\n\\t}\\n\\n\\tprivate static long readLong() throws IOException {\\n\\t\\treturn Long.parseLong(nextToken());\\n\\t}\\n\\n\\tprivate static double readDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(nextToken());\\n\\t}\\n\\n\\tprivate static int readInt() throws IOException {\\n\\t\\treturn Integer.parseInt(nextToken());\\n\\t}\\n\\n\\tprivate static String nextLine() throws IOException {\\n\\t\\tif(!br.ready()) {\\n\\t\\t\\texitImmediately();\\n\\t\\t}\\n\\t\\tst = null;\\n\\t\\treturn br.readLine();\\n\\t}\\n\\n\\tprivate static String nextToken() throws IOException {\\n\\t\\twhile(st == null || !st.hasMoreTokens()) {\\n\\t\\t\\tif(!br.ready()) {\\n\\t\\t\\t\\texitImmediately();\\n\\t\\t\\t}\\n\\t\\t\\tst = new StringTokenizer(br.readLine().trim());\\n\\t\\t}\\n\\t\\treturn st.nextToken();\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'minimumBribes' function below.\\n *\\n * The function accepts INTEGER_ARRAY q as parameter.\\n */\\n\\n public static void minimumBribes(List<Integer> q) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] qTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> q = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int qItem = Integer.parseInt(qTemp[i]);\\n q.add(qItem);\\n }\\n\\n Result.minimumBribes(q);\\n }\\n\\n bufferedReader.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'minimumBribes' function below.\\n *\\n * The function accepts INTEGER_ARRAY q as parameter.\\n */\\n\\n public static void minimumBribes(List<Integer> q) {\\n // Write your code here\\n int[] from = new int[q.size()];\\n for (int i = 0; i < from.length; i ++)\\n from[i] = i+1;\\n \\n int count = 0;\\n int temp; \\n for (int i = 0; i < from.length; i++) {\\n // left of i match\\n if (q.get(i) == from[i])\\n continue;\\n \\n // ok\\n if (i < from.length-1 && q.get(i) == from[i+1]) {\\n temp = from[i];\\n from[i] = from[i+1];\\n from[i+1] = temp;\\n count++;\\n } else if (i < from.length-2 && q.get(i) == from[i+2]) {\\n temp = from[i];\\n from[i] = from[i+2];\\n from[i+2] = from[i+1];\\n from[i+1] = temp;\\n count += 2;\\n } else {\\n System.out.println(\\\"Too chaotic\\\");\\n return;\\n }\\n \\n } \\n System.out.println(count);\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> q = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n Result.minimumBribes(q);\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'minimumBribes' function below.\\n *\\n * The function accepts INTEGER_ARRAY q as parameter.\\n */\\n\\n public static void minimumBribes(List<Integer> q) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> q = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n Result.minimumBribes(q);\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\n\\npublic class HourRank4qB {\\n\\n\\tstatic int pos[], arr[];\\n\\t\\n\\tpublic static void main(String args[]) {\\n\\t\\tInputReader in = new InputReader(System.in);\\n\\t\\tPrintWriter w = new PrintWriter(System.out);\\n\\n\\t\\tint t = in.nextInt();\\n\\t\\t\\n\\t\\twhile(t-- > 0 ){\\n\\t\\t\\n\\t\\t\\tint n = in.nextInt();\\n\\t\\n\\t\\t\\tint a[] = new int[n];\\n\\t\\t\\tfor (int i = 0; i < n; i++)\\n\\t\\t\\t\\ta[i] = in.nextInt() - 1;\\n\\t\\t\\t\\n\\t\\t\\tint op = 0;\\n\\t\\t\\tboolean yes = true;\\n\\t\\t\\t\\n\\t\\t\\tpos = new int[n];\\n\\t\\t\\tarr = new int[n];\\n\\t\\t\\tfor(int i = 0; i < n; i++)\\n\\t\\t\\t\\tarr[i] = pos[i] = i;\\n\\t\\t\\t\\n\\t\\t\\tfor(int i = 0; i < n; i++){\\n\\t\\t\\t\\tif(pos[a[i]] - i > 2){\\n\\t\\t\\t\\t\\tyes = false;\\n\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\twhile(pos[a[i]] > i){\\n\\t\\t\\t\\t\\tswap(pos[a[i]], pos[a[i]] - 1);\\n\\t\\t\\t\\t\\top++;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tw.println(yes ? op : \\\"Too chaotic\\\");\\n\\t\\t}\\n\\t\\tw.close();\\n\\t}\\n\\t\\n\\tstatic void swap(int i,int j){\\n\\t\\t//swap ith and jth position\\n\\t\\tpos[arr[i]] = j;\\n\\t\\tpos[arr[j]] = i;\\n\\t\\tint t = arr[i];\\n\\t\\tarr[i] = arr[j];\\n\\t\\tarr[j] = t;\\n\\t}\\n\\n\\tstatic class InputReader {\\n\\n\\t\\tprivate InputStream stream;\\n\\t\\tprivate byte[] buf = new byte[8192];\\n\\t\\tprivate int curChar, snumChars;\\n\\t\\tprivate SpaceCharFilter filter;\\n\\n\\t\\tpublic InputReader(InputStream stream) {\\n\\t\\t\\tthis.stream = stream;\\n\\t\\t}\\n\\n\\t\\tpublic int snext() {\\n\\t\\t\\tif (snumChars == -1)\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\tif (curChar >= snumChars) {\\n\\t\\t\\t\\tcurChar = 0;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tsnumChars = stream.read(buf);\\n\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (snumChars <= 0)\\n\\t\\t\\t\\t\\treturn -1;\\n\\t\\t\\t}\\n\\t\\t\\treturn buf[curChar++];\\n\\t\\t}\\n\\n\\t\\tpublic int nextInt() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t}\\n\\t\\t\\tint res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic long nextLong() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t}\\n\\t\\t\\tlong res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic String readString() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tStringBuilder res = new StringBuilder();\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tres.appendCodePoint(c);\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res.toString();\\n\\t\\t}\\n\\n\\t\\tpublic boolean isSpaceChar(int c) {\\n\\t\\t\\tif (filter != null)\\n\\t\\t\\t\\treturn filter.isSpaceChar(c);\\n\\t\\t\\treturn c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n\\t\\t}\\n\\n\\t\\tpublic interface SpaceCharFilter {\\n\\t\\t\\tpublic boolean isSpaceChar(int ch);\\n\\t\\t}\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'minimumBribes' function below.\\n *\\n * The function accepts INTEGER_ARRAY q as parameter.\\n */\\n\\n public static void minimumBribes(List<Integer> q) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> q = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n Result.minimumBribes(q);\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"minimumBribes(q)\"\n ],\n \"solution\": \"\\ndef count_inversion(lst):\\n return merge_count_inversion(lst)[1]\\n\\ndef merge_count_inversion(lst):\\n if len(lst) <= 1:\\n return lst, 0\\n middle = int( len(lst) / 2 )\\n left, a = merge_count_inversion(lst[:middle])\\n right, b = merge_count_inversion(lst[middle:])\\n result, c = merge_count_split_inversion(left, right)\\n return result, (a + b + c)\\n\\ndef merge_count_split_inversion(left, right):\\n result = []\\n count = 0\\n i, j = 0, 0\\n left_len = len(left)\\n while i < left_len and j < len(right):\\n if left[i] <= right[j]:\\n result.append(left[i])\\n i += 1\\n else:\\n result.append(right[j])\\n count += left_len - i\\n j += 1\\n result += left[i:]\\n result += right[j:]\\n return result, count\\nfor _ in range(int(input())):\\n N=int(input())\\n a=list(map(int,input().split()))\\n if any(a[i]-(i+1)>2 for i in range(N)):\\n print(\\\"Too chaotic\\\")\\n else:\\n print(count_inversion(a))\\n\",\n \"template\": \"#\\n# Complete the 'minimumBribes' function below.\\n#\\n# The function accepts INTEGER_ARRAY q as parameter.\\n#\\n\\ndef minimumBribes(q):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n n = int(input().strip())\\n\\n q = list(map(int, input().rstrip().split()))\\n\\n minimumBribes(q)\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":279,"cells":{"question_id":{"kind":"number","value":15577,"string":"15,577"},"question_title":{"kind":"string","value":"Prime XOR"},"question_content":{"kind":"string","value":"Penny has an array of $n$ integers, $[ a_0, a_1, \\ldots, a_{n-1} ]$. She wants to find the number of unique [multisets](https://en.wikipedia.org/wiki/Multiset) she can form using elements from the array such that the [bitwise XOR](https://en.wikipedia.org/wiki/Bitwise_operation#XOR) of all the elements of the multiset is a [prime number](https://en.wikipedia.org/wiki/Prime_number). Recall that a *multiset* is a set which can contain duplicate elements.\n\nGiven $q$ queries where each query consists of an array of integers, can you help Penny find and print the number of valid multisets for each array? As these values can be quite large, modulo each answer by $10^9+7$ before printing it on a new line."},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int primeXor(List<Integer> a)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\npublic class c {\\npublic static void main(String[] args) throws IOException {\\n\\tinput.init(System.in);\\n\\tPrintWriter out = new PrintWriter(System.out);\\n\\tint T = input.nextInt();\\n\\tboolean[] ps = new boolean[10000];\\n\\tArrays.fill(ps, true);\\n\\tps[0] = ps[1] = false;\\n\\tfor(int i = 0; i<ps.length; i++)\\n\\t\\tif(ps[i])\\n\\t\\t\\tfor(int j = i*i; j<ps.length; j+=i)\\n\\t\\t\\t\\tps[j] = false;\\n\\tfor(int t = 0; t<T; t++)\\n\\t{\\n\\t\\tint n = input.nextInt();\\n\\t\\tint[] fs = new int[4501];\\n\\t\\tfor(int i = 0; i<n; i++) fs[input.nextInt()]++;\\n\\t\\tlong mod = (long)1e9+7;\\n\\t\\tlong[] ways = new long[8197];\\n\\t\\tways[0] = 1L;\\n\\t\\tfor(int i = 3500; i<=4500;i++)\\n\\t\\t{\\n\\t\\t\\tint same = fs[i]/2 + 1;\\n\\t\\t\\tint diff = (fs[i]+1)/2;\\n\\t\\t\\tlong[] nways = new long[ways.length];\\n\\t\\t\\tfor(int j = 0; j<ways.length; j++)\\n\\t\\t\\t{\\n\\t\\t\\t\\tif(ways[j] == 0) continue;\\n\\t\\t\\t\\tnways[j] = (nways[j] + (ways[j] * same)%mod)%mod;\\n\\t\\t\\t\\tnways[j^i] = (nways[j^i] + (ways[j] * diff)%mod)%mod;\\n\\t\\t\\t}\\n\\t\\t\\tways = nways;\\n\\t\\t}\\n\\t\\tlong res = 0;\\n\\t\\tfor(int i = 0; i<ways.length; i++)\\n\\t\\t{\\n\\t\\t\\tif(ps[i])\\n\\t\\t\\t\\tres = (res + ways[i])%mod;\\n\\t\\t}\\n\\t\\tout.println(res);\\n\\t}\\n\\t\\n\\tout.close();\\n}\\n\\npublic static class input {\\n\\tstatic BufferedReader reader;\\n\\tstatic StringTokenizer tokenizer;\\n\\n\\tstatic void init(InputStream input) {\\n\\t\\treader = new BufferedReader(new InputStreamReader(input));\\n\\t\\ttokenizer = new StringTokenizer(\\\"\\\");\\n\\t}\\n\\n\\tstatic String next() throws IOException {\\n\\t\\twhile (!tokenizer.hasMoreTokens())\\n\\t\\t\\ttokenizer = new StringTokenizer(reader.readLine());\\n\\t\\treturn tokenizer.nextToken();\\n\\t}\\n\\n\\tstatic int nextInt() throws IOException {\\n\\t\\treturn Integer.parseInt(next());\\n\\t}\\n\\n\\tstatic double nextDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(next());\\n\\t}\\n\\n\\tstatic long nextLong() throws IOException {\\n\\t\\treturn Long.parseLong(next());\\n\\t}\\n}\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'primeXor' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY a as parameter.\\n */\\n\\n public static int primeXor(List<Integer> a) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int qItr = 0; qItr < q; qItr++) {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] aTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> a = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int aItem = Integer.parseInt(aTemp[i]);\\n a.add(aItem);\\n }\\n\\n int result = Result.primeXor(a);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'primeXor' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY a as parameter.\\n */\\n\\n public static int primeXor(List<Integer> a) {\\n\\n HashMap<Integer,Integer> count_map = new HashMap<>();\\n\\n for(int i = 0; i < a.size(); i++){\\n if(count_map.containsKey(a.get(i))){\\n count_map.put(a.get(i), count_map.get(a.get(i)) + 1);\\n }\\n else{\\n count_map.put(a.get(i), 1);\\n }\\n }\\n\\n int n = 8192;\\n\\n ArrayList<Integer> prime_list = new ArrayList<>();\\n\\n prime_list.add(2);\\n\\n for(int i = 3; i < n; i++){\\n\\n int root = (int)Math.sqrt(i);\\n\\n boolean isPrime = true;\\n\\n for(int j = 2; j <= root; j++){\\n\\n if(i % j == 0){\\n isPrime = false;\\n break;\\n }\\n }\\n\\n if(isPrime){\\n prime_list.add(i);\\n //System.out.println(i);\\n }\\n\\n }\\n\\n long[] occurence = new long[n];\\n long[] temp = new long[n];\\n\\n occurence[a.get(0)] = (count_map.get(a.get(0)) / 2) + count_map.get(a.get(0)) % 2;\\n occurence[0] = (count_map.get(a.get(0)) / 2) + 1;\\n\\n count_map.remove(a.get(0));\\n\\n for(Integer e : count_map.keySet()){\\n\\n for(int r = 0; r < n; r++){\\n\\n temp[r] += (occurence[r] * ((count_map.get(e) / 2) + 1));\\n \\n temp[r] %= 1000000007;\\n \\n temp[r ^ e] += (occurence[r] * ((count_map.get(e) / 2)\\n + (count_map.get(e) % 2)));\\n \\n \\n temp[r ^ e] %= 1000000007;\\n\\n }\\n\\n occurence = temp;\\n temp = new long[n];\\n }\\n\\n\\n\\n long count = 0;\\n\\n for(int i : prime_list){\\n count += occurence[i];\\n\\n }\\n\\n\\n return (int)(count % 1000000007);\\n\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> a = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.primeXor(a);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'primeXor' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY a as parameter.\\n */\\n\\n public static int primeXor(List<Integer> a) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> a = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.primeXor(a);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import javafx.beans.property.IntegerProperty;\\n\\nimport java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n static Scanner in;\\n static PrintWriter out;\\n\\n static int N = 4501;\\n static int M = 8192;\\n static int md = (int)1e9 + 7;\\n\\n public static boolean prime(int x){\\n if(x == 1 || x == 0){\\n return false;\\n }\\n for(int i = 2; i * i <= x; i++){\\n if(x % i == 0){\\n return false;\\n }\\n }\\n return true;\\n }\\n\\n public static void main(String[] args) {\\n in = new Scanner(System.in);\\n out = new PrintWriter(System.out);\\n\\n int q = in.nextInt();\\n while(q-->0){\\n int n = in.nextInt();\\n int a[] = new int[N];\\n for(int i = 0; i < n; i++){\\n a[in.nextInt()]++;\\n }\\n\\n long dp[][] = new long[2][8192];\\n dp[0][0] = 1;\\n\\n for(int i = 3500; i <= 4500; i++){\\n if(a[i] > 0) {\\n\\n for (int j = 0; j < M; j++) {\\n if (dp[0][j] > 0 && ((i ^ j) < M)) {\\n long q0 = a[i] / 2 + 1;\\n long q1 = (a[i] + 1) / 2;\\n dp[1][j] = (q0 * dp[0][j] + dp[1][j]) % md;\\n dp[1][j ^ i] = (q1 * dp[0][j] + dp[1][j ^ i]) % md;\\n }\\n }\\n\\n for(int j = 0; j < M; j++){\\n dp[0][j] = dp[1][j];\\n dp[1][j] = 0;\\n }\\n }\\n }\\n\\n int ans = 0;\\n for(int j = 0; j < M; j++){\\n if(prime(j)) {\\n ans = (int)(ans + dp[0][j]);\\n if (ans >= md) {\\n ans -= md;\\n }\\n }\\n }\\n out.println(ans);\\n }\\n\\n out.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'primeXor' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY a as parameter.\\n */\\n\\n public static int primeXor(List<Integer> a) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int q = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, q).forEach(qItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> a = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.primeXor(a);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"primeXor(a)\"\n ],\n \"solution\": \"from collections import Counter\\nfrom math import sqrt\\n\\n\\ndef primes(n):\\n x = [True]*((n-1)//2) # Representing all odd numbers >= 3 and <= n.\\n for i in range(int((sqrt(n)-3)//2)+1):\\n if x[i]: # Number represented by i (call it p) is prime\\n # starting with p**2, set all odd multiples of p to false.\\n x[2*i*i+6*i+3::2*i+3] = [False] * int((n-(2*i+3)**2)//(4*i+6)+1)\\n return [2] + [2*i+3 for i,v in enumerate(x) if v]\\n\\n\\ndef middle_out(counts):\\n divisor = 10**9 + 7\\n count = [0]*4501\\n for i,n in counts:\\n count[i] = n\\n \\n # Numbers closer to 4096 are added first because they have a smaller \\n # set of numbers closed under XOR.\\n # Order to include numbers, can be further subdivided and the path\\n # optimized for sparse data sets.\\n path = ((4096, 4351), (4352, 4500), (3584, 4095), (3500, 3583))\\n span = ((256, 0), (512, 0), (512, 4096), (1024, 4096))\\n\\n # Array of number of multisets that XOR to j using only the first i numbers.\\n totals = [[0]*8192 for _ in range(2)] # current and next i values.\\n static, update = 0, 1 # tracks which part of the array is being updated\\n totals[static][0] = 1 # set the xor of the empty multiset to start.\\n\\n for i,p in enumerate(path): # step through path sections \\n for j,n in enumerate(count[p[0]:p[1]+1]): # Loop through input numbers\\n if n: # Find number with at least one in 'user' input.\\n # The numbers of ways to not change the xor (0, 2, 4,...).\\n same = 1 + n//2 \\n # The number of ways to change the xor value (1, 3, 5, ...).\\n change = (n+1)//2 \\n o = span[i][1] # offset, used when numbers are > AND < 4096.\\n for x in range(span[i][0]): \\n \\\"\\\"\\\"\\n A = [0, span[i][0]). B = {a XOR j+p[0] for all a in A}. \\n Then A Union B (if there is an offset, then union A+offset \\n and B+offset as well) is closed under XOR and includes all \\n previous inputs.\\n \\\"\\\"\\\"\\n y = x^(j+p[0]) # j+p[0] is just the user input number\\n totals[update][x] = (totals[static][y]*change + \\n totals[static][x]*same)\\n totals[update][y] = (totals[static][x]*change + \\n totals[static][y]*same)\\n if o:\\n totals[update][x+o] = (totals[static][y+o]*change + \\n totals[static][x+o]*same)\\n totals[update][y+o] = (totals[static][x+o]*change + \\n totals[static][y+o]*same)\\n \\n # Don't want to % too often, or let the numbers get too big.\\n if totals[update][0] > 100000*divisor: \\n for x in range(len(totals[update])):\\n totals[update][x] %= divisor\\n static, update = update, static\\n \\n p = primes(8191)\\n total = 0\\n for prime in p:\\n total += totals[static][prime]\\n\\n return total % divisor\\n\\n\\nq = int(input())\\nfor _ in range(q):\\n n = int(input())\\n numbers = Counter(int(x) for x in input().split()).items()\\n print(middle_out(numbers))\\n\",\n \"template\": \"#\\n# Complete the 'primeXor' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY a as parameter.\\n#\\n\\ndef primeXor(a):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n q = int(input().strip())\\n\\n for q_itr in range(q):\\n n = int(input().strip())\\n\\n a = list(map(int, input().rstrip().split()))\\n\\n result = primeXor(a)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":280,"cells":{"question_id":{"kind":"number","value":15974,"string":"15,974"},"question_title":{"kind":"string","value":"HackerRank City"},"question_content":{"kind":"string","value":"HackerRank-city is an acyclic connected graph (or [tree](https://en.wikipedia.org/wiki/Tree_(graph_theory))). Its not an ordinary place, the construction of the whole tree takes place in $N$ steps. The process is described below:\n\n*\tIt initially has $1$ node.\n*\tAt each step, you must create $3$ duplicates of the current tree, and create $2$ new nodes to connect all $4$ copies in the following **`H`** shape:\n\t\t\n<img src=\"https://s3.amazonaws.com/hr-challenge-images/15974/1453287425-a21e2a7db5-nik2.png\" title=\"nik2.png\" />\n\t\nAt each $i^{th}$ step, the tree becomes $4$ times bigger plus $2$ new nodes, as well as $5$ new edges connecting everything together. The length of the new edges being added at step $i$ is denoted by input $A_{i}$.\n \nCalculate the sum of distances between each pair of nodes; as these answers may run large, print your answer modulo $1000000007$.\n\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int hackerrankCity(List<Integer> A)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class C {\\n\\tInputStream is;\\n\\tPrintWriter out;\\n\\tString INPUT = \\\"\\\";\\n\\t\\n\\tvoid solve()\\n\\t{\\n\\t\\tint n = ni();\\n\\t\\tint[] a = na(n);\\n\\t\\tlong A = 0, D = 0, N = 1, L = 0;\\n\\t\\tint mod = 1000000007;\\n\\t\\tfor(int v : a){\\n\\t\\t\\tlong B = 0, E = 0, M = 1;\\n//\\t\\t\\tlong ND = D + D + (L+2*v)*N + D + (L+3*v)*N + (L+3*v)*N + (L+v) + (L+2*v);\\n\\t\\t\\tlong ND = (4*D + (3*L+8*v)%mod*N +2*L+3*v) % mod;\\n\\t\\t\\tlong NL = (2*L+3*v) % mod;\\n\\t\\t\\tB = (B + A + D*M + E * N + v * N % mod * M)% mod ;\\n\\t\\t\\tE = (E + D + N*v) % mod;\\n\\t\\t\\tM = (M+N)%mod;\\n\\t\\t\\t\\n\\t\\t\\tB = (B + A + D*M + E * N + v * N % mod * M)% mod ;\\n\\t\\t\\tE = (E + D + N*v) % mod;\\n\\t\\t\\tM = (M+N)%mod;\\n\\t\\t\\t\\n\\t\\t\\tlong C = (B + B + E*M + E*M + v*M%mod*M)%mod;\\n\\t\\t\\tM = 2*M % mod;\\n\\t\\t\\t\\n\\t\\t\\tA = C;\\n\\t\\t\\tD = ND;\\n\\t\\t\\tN = M;\\n\\t\\t\\tL = NL;\\n\\t\\t}\\n\\t\\tout.println(A);\\n\\t}\\n\\t\\n\\tvoid run() throws Exception\\n\\t{\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tlong s = System.currentTimeMillis();\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tif(!INPUT.isEmpty())tr(System.currentTimeMillis()-s+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception { new C().run(); }\\n\\t\\n\\tprivate byte[] inbuf = new byte[1024];\\n\\tprivate int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate double nd() { return Double.parseDouble(ns()); }\\n\\tprivate char nc() { return (char)skip(); }\\n\\t\\n\\tprivate String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'hackerrankCity' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY A as parameter.\\n */\\n\\n public static int hackerrankCity(List<Integer> A) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int ACount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] ATemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> A = new ArrayList<>();\\n\\n for (int i = 0; i < ACount; i++) {\\n int AItem = Integer.parseInt(ATemp[i]);\\n A.add(AItem);\\n }\\n\\n int result = Result.hackerrankCity(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n /*\\n * Complete the hackerrankCity function below.\\n */\\n static int hackerrankCity(int[] A) {\\n int n = A.length;\\n long[] cluster_size = new long[n + 1];\\n long[] total = new long[n + 1];\\n long[] p = new long[n + 1];\\n long[] line = new long[n + 1];\\n\\n long m = (long)1e9 + 7;\\n\\n cluster_size[0] = 1;\\n p[0] = 0;\\n total[0] = 0;\\n line[0] = 0;\\n\\n for (int i = 1; i <= n; i++) {\\n long a = A[i - 1];\\n long k = cluster_size[i - 1];\\n cluster_size[i] = (k * 4 + 2) % m;\\n line[i] = (line[i - 1] * 2 + 3 * a) % m;\\n\\n p[i] = (p[i - 1]\\n + p[i - 1] + k * (2 * a + line[i - 1]) % m\\n + 2 * (k * (line[i - 1] + 3 * a) % m + p[ i - 1]) % m\\n + line[i - 1] * 2 + 3 * a % m\\n ) % m;\\n \\n total[i] = (4 * total[i - 1] % m\\n + 4 * (p[i - 1] + k * a) % m\\n + 4 * (p[i - 1] + k * a * 2) % m\\n + 2 * ((p[i - 1] * k) % m * 2 + ((k * k) % m) * a * 2) % m\\n + 4 * ((p[i - 1] * k) % m * 2 + ((k * k) % m) * a * 3) % m\\n + a) % m;\\n\\n }\\n\\n return (int)(total[n] % m);\\n }\\n\\n private static final Scanner scanner = new Scanner(System.in);\\n\\n public static void main(String[] args) throws IOException {\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int ACount = Integer.parseInt(scanner.nextLine().trim());\\n\\n int[] A = new int[ACount];\\n\\n String[] AItems = scanner.nextLine().split(\\\" \\\");\\n\\n for (int AItr = 0; AItr < ACount; AItr++) {\\n int AItem = Integer.parseInt(AItems[AItr].trim());\\n A[AItr] = AItem;\\n }\\n\\n int result = hackerrankCity(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'hackerrankCity' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY A as parameter.\\n */\\n\\n public static int hackerrankCity(List<Integer> A) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int ACount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.hackerrankCity(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.OutputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.OutputStream;\\nimport java.io.PrintWriter;\\nimport java.io.BufferedWriter;\\nimport java.io.Writer;\\nimport java.io.OutputStreamWriter;\\nimport java.util.InputMismatchException;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\n\\n/**\\n * Built using CHelper plug-in\\n * Actual solution is at the top\\n *\\n * @author Egor Kulikov (egor@egork.net)\\n */\\npublic class Solution {\\n\\tpublic static void main(String[] args) {\\n\\t\\tInputStream inputStream = System.in;\\n\\t\\tOutputStream outputStream = System.out;\\n\\t\\tInputReader in = new InputReader(inputStream);\\n\\t\\tOutputWriter out = new OutputWriter(outputStream);\\n\\t\\tHackerrankCity solver = new HackerrankCity();\\n\\t\\tsolver.solve(1, in, out);\\n\\t\\tout.close();\\n\\t}\\n\\n\\tstatic class HackerrankCity {\\n\\t\\tprivate static final long MOD = 1000000007;\\n\\n\\t\\tpublic void solve(int testNumber, InputReader in, OutputWriter out) {\\n\\t\\t\\tint n = in.readInt();\\n\\t\\t\\tint[] a = IOUtils.readIntArray(in, n);\\n\\t\\t\\tlong nv = 1;\\n\\t\\t\\tlong sd = 0;\\n\\t\\t\\tlong dtc = 0;\\n\\t\\t\\tlong diam = 0;\\n\\t\\t\\tfor (int ne : a) {\\n\\t\\t\\t\\tlong nnv = nv * 4 + 2;\\n\\t\\t\\t\\tlong nsd = 4 * sd + 4 * dtc * (2 + 3 * nv % MOD) % MOD + 4 * ne * nv % MOD * (nv * 3 + 2) % MOD +\\n\\t\\t\\t\\t\\t\\tne * (2 * nv + 1) % MOD * (2 * nv + 1) % MOD;\\n\\t\\t\\t\\tlong ndtc = 4 * dtc + 8 * ne * nv % MOD + 3 * ne + (3 * nv + 2) * diam % MOD;\\n\\t\\t\\t\\tlong ndiam = 2 * diam + 3 * ne;\\n\\t\\t\\t\\tnv = nnv % MOD;\\n\\t\\t\\t\\tsd = nsd % MOD;\\n\\t\\t\\t\\tdtc = ndtc % MOD;\\n\\t\\t\\t\\tdiam = ndiam % MOD;\\n\\t\\t\\t}\\n\\t\\t\\tout.printLine(sd);\\n\\t\\t}\\n\\t}\\n\\n\\tstatic class OutputWriter {\\n\\t\\tprivate final PrintWriter writer;\\n\\n\\t\\tpublic OutputWriter(OutputStream outputStream) {\\n\\t\\t\\twriter = new PrintWriter(new BufferedWriter(new OutputStreamWriter(outputStream)));\\n\\t\\t}\\n\\n\\t\\tpublic OutputWriter(Writer writer) {\\n\\t\\t\\tthis.writer = new PrintWriter(writer);\\n\\t\\t}\\n\\n\\t\\tpublic void close() {\\n\\t\\t\\twriter.close();\\n\\t\\t}\\n\\n\\t\\tpublic void printLine(long i) {\\n\\t\\t\\twriter.println(i);\\n\\t\\t}\\n\\t}\\n\\n\\tstatic class InputReader {\\n\\t\\tprivate InputStream stream;\\n\\t\\tprivate byte[] buf = new byte[1024];\\n\\t\\tprivate int curChar;\\n\\t\\tprivate int numChars;\\n\\t\\tprivate SpaceCharFilter filter;\\n\\n\\t\\tpublic InputReader(InputStream stream) {\\n\\t\\t\\tthis.stream = stream;\\n\\t\\t}\\n\\n\\t\\tpublic int read() {\\n\\t\\t\\tif (numChars == -1) {\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t}\\n\\t\\t\\tif (curChar >= numChars) {\\n\\t\\t\\t\\tcurChar = 0;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tnumChars = stream.read(buf);\\n\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (numChars <= 0) {\\n\\t\\t\\t\\t\\treturn -1;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\treturn buf[curChar++];\\n\\t\\t}\\n\\n\\t\\tpublic int readInt() {\\n\\t\\t\\tint c = read();\\n\\t\\t\\twhile (isSpaceChar(c)) {\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t}\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t}\\n\\t\\t\\tint res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9') {\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic boolean isSpaceChar(int c) {\\n\\t\\t\\tif (filter != null) {\\n\\t\\t\\t\\treturn filter.isSpaceChar(c);\\n\\t\\t\\t}\\n\\t\\t\\treturn isWhitespace(c);\\n\\t\\t}\\n\\n\\t\\tpublic static boolean isWhitespace(int c) {\\n\\t\\t\\treturn c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n\\t\\t}\\n\\n\\t\\tpublic interface SpaceCharFilter {\\n\\t\\t\\tpublic boolean isSpaceChar(int ch);\\n\\t\\t}\\n\\t}\\n\\n\\tstatic class IOUtils {\\n\\t\\tpublic static int[] readIntArray(InputReader in, int size) {\\n\\t\\t\\tint[] array = new int[size];\\n\\t\\t\\tfor (int i = 0; i < size; i++) {\\n\\t\\t\\t\\tarray[i] = in.readInt();\\n\\t\\t\\t}\\n\\t\\t\\treturn array;\\n\\t\\t}\\n\\t}\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'hackerrankCity' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY A as parameter.\\n */\\n\\n public static int hackerrankCity(List<Integer> A) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int ACount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> A = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.hackerrankCity(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"hackerrankCity(A)\"\n ],\n \"solution\": \"import sys\\n\\ninp = sys.stdin\\nn = int(inp.readline().strip())\\nlengths = list(map(int, inp.readline().strip().split(' ')))\\n\\nf = 0\\ng = 0\\nh = 0\\nm = 1\\nfor a in lengths:\\n f = (4*g*(3*m+2) + 4*f + 16*a*m*m + 12*a*m + a) % 1000000007\\n g = (4*g + m*(3*h+8*a) + 2*h + 3*a) % 1000000007\\n h = (2*h + 3*a) % 1000000007\\n m = (4*m + 2) % 1000000007\\n #print(f, g, h, m)\\n \\nprint(f)\",\n \"template\": \"#\\n# Complete the 'hackerrankCity' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY A as parameter.\\n#\\n\\ndef hackerrankCity(A):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n A_count = int(input().strip())\\n\\n A = list(map(int, input().rstrip().split()))\\n\\n result = hackerrankCity(A)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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Pieces"},"question_content":{"kind":"string","value":"Consider an array, $A$, of length $n$. We can split $A$ into contiguous segments called *pieces* and store them as another array, $B$. For example, if $A = [1, 2, 3]$, we have the following arrays of pieces:\n\n- $B = [(1), (2), (3)]$ contains three $1$-element pieces.\n- $B = [(1, 2), (3)]$ contains two pieces, one having $2$ elements and the other having $1$ element.\n- $B = [(1), (2, 3)]$ contains two pieces, one having $1$ element and the other having $2$ elements.\n- $B = [(1, 2, 3)]$ contains one $3$-element piece.\n\nWe consider the *value* of a piece in some array $B$ to be $\\textit{(sum of all numbers in the piece)} \\times \\textit{(length of piece)}$, and we consider the *total value* of some array $B$ to be the sum of the values for all pieces in that $B$. For example, the total value of $B = [(1,2,4), (5, 1), (2)]$ is $(1+2+4) \\times 3 + (5 + 1) \\times 2 + (2) \\times 1= 35$.\n\nGiven $A$, find the total values for all possible $B$'s, sum them together, and print this sum modulo $(10^9 + 7)$ on a new line.\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int summingPieces(List<Integer> arr)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n public static final long MOD = 1000000007L;\\n \\n static int modInverse(int a, int m)\\n {\\n int m0 = m, t, q;\\n int x0 = 0, x1 = 1;\\n\\n if (m == 1)\\n return 0;\\n\\n while (a > 1)\\n {\\n q = a / m;\\n t = m;\\n m = a % m;\\n a = t;\\n t = x0;\\n x0 = x1 - q * x0;\\n x1 = t;\\n }\\n\\n if (x1 < 0)\\n x1 += m0;\\n\\n return x1;\\n }\\n \\n public static long getResult(int[] array, int lastIndex) {\\n long sum = 0;\\n for (int i = lastIndex; i >= 0; --i) {\\n sum = (sum + array[i]) % MOD;\\n }\\n return 0;\\n }\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int n = in.nextInt();\\n int[] array = new int[n];\\n for (int i = 0; i < n; ++i) {\\n array[i] = in.nextInt();\\n }\\n \\n long suffixSum = 0;\\n long subSum = 0;\\n long resultSum = 0;\\n long powerFactor = 1;\\n long result = 0;\\n for (int i = 0; i < n; ++i) {\\n long twoPower = (2 * powerFactor - 1) % MOD;\\n suffixSum = suffixSum + ((subSum + ((twoPower) * array[i]) % MOD) % MOD) % MOD;\\n result = (resultSum + suffixSum) % MOD;\\n resultSum = (resultSum + result) % MOD;\\n subSum = (subSum + (powerFactor * array[i]) % MOD) % MOD;\\n powerFactor = (powerFactor * 2) % MOD;\\n //resultSum += (powerFactor - 1) * array[i];\\n \\n //resultSum += suffixSum;\\n //long newResult = (powerFactor) * array[i];\\n //resultSum += suffixSum;\\n //suffixSum += powerFactor * array[i];\\n //resultSum += (2 * powerFactor - 1) * array[i];\\n //powerFactor *= 2;\\n //System.out.println(\\\"powerFactor \\\" + (powerFactor) + \\\" resultsum \\\" + resultSum + \\\" suffixSum \\\" + suffixSum +\\n // \\\" subSum \\\" + subSum + \\\" array[i] \\\" + array[i] + \\\" result \\\" + result);\\n }\\n \\n System.out.println(result);\\n \\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'summingPieces' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int summingPieces(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] arrTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> arr = new ArrayList<>();\\n\\n for (int i = 0; i < arrCount; i++) {\\n int arrItem = Integer.parseInt(arrTemp[i]);\\n arr.add(arrItem);\\n }\\n\\n int result = Result.summingPieces(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"\\nimport java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n \\n int n = in.nextInt();\\n long sum = 0;\\n long[] powers2 = new long[n+1];\\n powers2[0] = 1;\\n for(int i=1; i<=n; i++)\\n powers2[i] = (powers2[i-1] << 1) % 1000000007;\\n \\n for(int i=1; i<=n; i++){\\n long left = ((powers2[i] - 1) * powers2[n-i]) % 1000000007;\\n long right = ((powers2[1+n-i]-1) * powers2[i-1]) % 1000000007;\\n long v = left + right - powers2[n-1];\\n sum = (sum + (v * in.nextLong())) % 1000000007;\\n }\\n \\n System.out.println(sum);\\n \\n }\\n}\\n\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'summingPieces' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int summingPieces(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.summingPieces(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"\\nimport java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class D2 {\\n\\tInputStream is;\\n\\tPrintWriter out;\\n\\tString INPUT = \\\"\\\";\\n\\t// 6+9+11+18\\n\\tfinal int o = 2500000;\\n\\tlong[] ps = new long[5000000];\\n\\t\\n\\tvoid solve()\\n\\t{\\n\\t\\tint mod = 1000000007;\\n\\t\\tint n = ni();\\n\\t\\tint[] a = na(n);\\n\\t\\tlong ret = 0;\\n\\t\\tps[o] = 1;\\n\\t\\tlong i2 = invl(2, mod);\\n\\t\\tfor(int i = o+1;i < ps.length;i++)ps[i] =ps[i-1] * 2 % mod;\\n\\t\\tfor(int i = o-1;i >= 0;i--)ps[i] =ps[i+1] * i2 % mod;\\n\\t\\t\\n\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\tlong lret = 0L;\\n\\t\\t\\tif(i > 0 && n-1-i > 0){\\n\\t\\t\\t\\tlret += pow(2, n-3, mod)*s2(i-1, mod)%mod*s1(n-2-i, mod)%mod;\\n\\t\\t\\t\\tlret += pow(2, n-3, mod)*s1(i-1, mod)%mod*s2(n-2-i, mod)%mod;\\n\\t\\t\\t\\tlret += pow(2, n-3, mod)*s1(i-1, mod)%mod*s1(n-2-i, mod)%mod;\\n\\t\\t\\t}\\n\\t\\t\\tif(i > 0){\\n\\t\\t\\t\\tlret += pow(2,i-1,mod)*(n-i)%mod*s1(i-1,mod)%mod;\\n\\t\\t\\t\\tlret += pow(2,i-1,mod)*s2(i-1,mod)%mod;\\n\\t\\t\\t}\\n\\t\\t\\t// 2^(1-R)*(1+R)\\n\\t\\t\\tif(n-1-i > 0){\\n\\t\\t\\t\\tlret += pow(2,n-2-i,mod)*(i+1)%mod*s1(n-2-i,mod)%mod;\\n\\t\\t\\t\\tlret += pow(2,n-2-i,mod)*s2(n-2-i,mod)%mod;\\n\\t\\t\\t}\\n\\t\\t\\tlret += n;\\n\\t\\t\\tlret %= mod;\\n\\t\\t\\tret += lret * a[i]%mod;\\n\\t\\t}\\n\\t\\tret %= mod;\\n\\t\\tout.println(ret);\\n\\t}\\n\\t\\n\\tlong s2(int n, int mod)\\n\\t{\\n\\t\\tlong ret = 2L-pow(2, -n+1, mod) - n*pow(2, -n, mod);\\n\\t\\tret %= mod;\\n\\t\\tif(ret < 0)ret += mod;\\n\\t\\treturn ret;\\n\\t}\\n\\t\\n\\tlong s1(int n, int mod)\\n\\t{\\n\\t\\tlong ret = 2L-pow(2, -n, mod);\\n\\t\\tif(ret < 0)ret += mod;\\n\\t\\treturn ret;\\n\\t}\\n\\t\\n\\tpublic long pow(long a, long n, long mod) {\\n\\t\\treturn ps[(int)(o+n)];\\n//\\t\\tif(n < 0)return invl(pow(a, -n, mod), mod);\\n//\\t\\t//\\t\\ta %= mod;\\n//\\t\\tlong ret = 1;\\n//\\t\\tint x = 63 - Long.numberOfLeadingZeros(n);\\n//\\t\\tfor (; x >= 0; x--) {\\n//\\t\\t\\tret = ret * ret % mod;\\n//\\t\\t\\tif (n << 63 - x < 0)\\n//\\t\\t\\t\\tret = ret * a % mod;\\n//\\t\\t}\\n//\\t\\treturn ret;\\n\\t}\\n\\n\\tpublic static long invl(long a, long mod) {\\n\\t\\tlong b = mod;\\n\\t\\tlong p = 1, q = 0;\\n\\t\\twhile (b > 0) {\\n\\t\\t\\tlong c = a / b;\\n\\t\\t\\tlong d;\\n\\t\\t\\td = a;\\n\\t\\t\\ta = b;\\n\\t\\t\\tb = d % b;\\n\\t\\t\\td = p;\\n\\t\\t\\tp = q;\\n\\t\\t\\tq = d - c * q;\\n\\t\\t}\\n\\t\\treturn p < 0 ? p + mod : p;\\n\\t}\\n\\n\\t\\n\\tvoid run() throws Exception\\n\\t{\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tlong s = System.currentTimeMillis();\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tif(!INPUT.isEmpty())tr(System.currentTimeMillis()-s+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception { new D2().run(); }\\n\\t\\n\\tprivate byte[] inbuf = new byte[1024];\\n\\tpublic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate double nd() { return Double.parseDouble(ns()); }\\n\\tprivate char nc() { return (char)skip(); }\\n\\t\\n\\tprivate String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'summingPieces' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int summingPieces(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.summingPieces(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"summingPieces(arr)\"\n ],\n \"solution\": \"def coeff(n):\\n a = pow(2, n, 1000000007)\\n res = [a - 1]\\n for i in range((n - 1) // 2):\\n a = a * 250000002 % 1000000007\\n res.append((res[-1] + (a - 1) * pow(2, i, 1000000007)) % 1000000007)\\n if n & 1:\\n return res + res[-2::-1]\\n return res + res[::-1]\\n\\nprint(sum(map(lambda x, y: x * y % 1000000007, coeff(int(input())), map(int, input().split()))) % 1000000007)\\n\",\n \"template\": \"#\\n# Complete the 'summingPieces' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY arr as parameter.\\n#\\n\\ndef summingPieces(arr):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n arr_count = int(input().strip())\\n\\n arr = list(map(int, input().rstrip().split()))\\n\\n result = summingPieces(arr)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":282,"cells":{"question_id":{"kind":"number","value":61,"string":"61"},"question_title":{"kind":"string","value":"Lego Blocks"},"question_content":{"kind":"string","value":"You have an infinite number of 4 types of lego blocks of sizes given as (depth x height x width):\n\n```\nd\th\tw\n1\t1\t1\n1\t1\t2\n1\t1\t3\n1\t1\t4\n```\n\nUsing these blocks, you want to make a wall of height $n$ and width $m$. Features of the wall are: \n<br>\n- The wall should not have any holes in it. \n- The wall you build should be one solid structure, so there should not be a straight vertical break across all rows of bricks. \n- The bricks must be laid horizontally. \n\nHow many ways can the wall be built?\n\n**Example** \n\n$n = 2$ \n$m = 3$ \n\nThe height is $2$ and the width is $3$. Here are some configurations: \n\n \n\nThese are not all of the valid permutations. There are $9$ valid permutations in all. \n\n**Function Description** \n\nComplete the *legoBlocks* function in the editor below. \n\nlegoBlocks has the following parameter(s):\n\n- *int n:* the height of the wall \n- *int m:* the width of the wall \n\n**Returns** \n- *int:* the number of valid wall formations modulo $(10^9+7)$ "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int legoBlocks(int n, int m)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.util.*;\\n\\npublic class Solution {\\n\\tint md=1000000007;\\n\\tint[][] ways = new int[1001][1001];\\n\\tint[][] waysRestrict = new int[1001][1001];\\n\\tpublic Solution(){\\n\\t\\tfor(int[] w : ways) Arrays.fill(w, -1);\\n\\t\\tfor(int[] w : waysRestrict) Arrays.fill(w, -1);\\n\\t}\\n\\tpublic int solve(int n, int m)\\n\\t{\\n\\t\\tif (ways[n][m] != -1) return ways[n][m];\\n\\t\\tlong ans;\\n\\t\\tif (m==1) ans = 1;\\n\\t\\telse if (n==1){\\n\\t\\t\\tif (m<=4) {\\n\\t\\t\\t\\tans = 2*solve(1,m-1);\\n\\t\\t\\t}\\n\\t\\t\\telse {\\n\\t\\t\\t\\tans = solve(1,m-1);\\n\\t\\t\\t\\tans = (ans + solve(1,m-2))%md;\\n\\t\\t\\t\\tans = (ans + solve(1,m-3))%md;\\n\\t\\t\\t\\tans = (ans + solve(1,m-4))%md;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\telse{\\n\\t\\t\\tans = 1; int one = solve(1,m);\\n\\t\\t\\tfor (int i=0; i<n; i++) ans = (ans * one)%md;\\n\\t\\t}\\n\\t\\tways[n][m] = (int)ans;\\n\\t\\treturn ways[n][m];\\n\\t}\\n\\tpublic int solveRestrict(int n, int m)\\n\\t{\\n\\t\\tif (waysRestrict[n][m] != -1) return waysRestrict[n][m];\\n\\t\\tlong ans;\\n\\t\\tif (m==1) ans = 1;\\n//\\t\\telse if (n==1) ans = solve(n,m);\\n\\t\\telse {\\n\\t\\t\\tans = solve(n,m);\\n\\t\\t\\tfor (int i=1; i<m; i++) {\\n\\t\\t\\t\\tlong a = solve(n,i);\\n\\t\\t\\t\\ta = (a*solveRestrict(n,m-i))%md;\\n\\t\\t\\t\\tans -= a;\\n\\t\\t\\t\\tif (ans<0) ans+=md;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\twaysRestrict[n][m] = (int)ans;\\n\\t\\treturn waysRestrict[n][m];\\n\\t}\\n\\tpublic static void main (String[] args) {\\n\\t\\tSolution o = new Solution();\\n\\t\\tScanner sc = new Scanner(System.in);\\n\\t\\tint n = sc.nextInt();\\n\\t\\tfor (int i=0; i<n; i++) {\\n\\t\\t\\tint a, b;\\n\\t\\t\\ta = sc.nextInt(); b = sc.nextInt();\\n\\t\\t\\tSystem.out.println(o.solveRestrict(a,b));\\n\\t\\t}\\n\\t\\tsc.close();\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'legoBlocks' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER n\\n * 2. INTEGER m\\n */\\n\\n public static int legoBlocks(int n, int m) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n int result = Result.legoBlocks(n, m);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.util.Scanner;\\n\\nclass Solution{\\n static final int mod=1000000007;\\n static int[] f;\\n static int mult(int x, int y){\\n long z=x;\\n z*=y;\\n return (int) (z%mod);\\n }\\n static int pow(int x, int n){\\n int r=1;\\n while(n!=1){\\n if((n&1)==1) r=mult(r,x);\\n x=mult(x,x);\\n n>>=1;\\n }\\n return mult(x,r);\\n }\\n static int add(int x, int y){\\n return (x+y)%mod;\\n }\\n static void computeF(int highM){\\n if(highM<4) highM=4;\\n f=new int[highM+1];\\n f[0]=1;\\n f[1]=1;\\n f[2]=2;\\n f[3]=4;\\n for(int i=4;i<=highM;++i){\\n int x=0;\\n for(int j=1;j<=4;++j){\\n x=add(x,f[i-j]);\\n }\\n f[i]=x;\\n }\\n }\\n static long solve(int n, int m){\\n int[] g=new int[m+1], h=new int[m+1];\\n g[1]=1;\\n h[1]=0;\\n for(int i=2;i<=m;++i){\\n int x=0;\\n for(int j=1;j<i;++j){\\n x=add(x,mult(g[j],g[i-j]));\\n x=add(x,mult(g[j],h[i-j]));\\n }\\n h[i]=x;\\n g[i]=add(pow(f[i],n),mod-h[i]);\\n }\\n return g[m];\\n }\\n static void input(){\\n Scanner sc=new Scanner(System.in);\\n int t=sc.nextInt();\\n int[] an=new int[t], am=new int[t];\\n for(int i=0;i<t;++i){\\n an[i]=sc.nextInt();\\n am[i]=sc.nextInt();\\n }\\n sc.close(); \\n int highM=0;\\n for(int m: am){\\n if(m>highM) highM=m;\\n }\\n computeF(highM);\\n for(int i=0;i<t;++i){\\n System.out.println(solve(an[i],am[i])); \\n }\\n }\\n public static void main(String[] args){\\n input();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'legoBlocks' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER n\\n * 2. INTEGER m\\n */\\n\\n public static int legoBlocks(int n, int m) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n int result = Result.legoBlocks(n, m);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.util.Scanner;\\n\\npublic class LegoBlocks {\\n\\n\\tprivate static long[] f = new long[1001];\\n\\tprivate static long[] g = new long[1001];\\n\\tprivate static long[] h = new long[1001];\\n\\n\\tpublic static void main(String[] args) {\\n\\n\\t\\tScanner in = new Scanner(System.in);\\n\\t\\tint T = in.nextInt();\\n\\n\\t\\tf[0] = 1;\\n\\t\\tfor (int i = 1; i <= 1000; i++)\\n\\t\\t\\tfor (int j = 1; j <= 4; j++)\\n\\t\\t\\t\\tif (i - j >= 0)\\n\\t\\t\\t\\t\\tf[i] = (f[i] + f[i - j]) % 1000000007;\\n\\t\\t\\n\\t\\th[1] = 1;\\n\\n\\t\\twhile (T-- > 0) {\\n\\n\\t\\t\\tint N = in.nextInt();\\n\\t\\t\\tint M = in.nextInt();\\n\\n\\t\\t\\tfor (int i = 1; i <= M; i++)\\n\\t\\t\\t\\tg[i] = pow(f[i], N);\\t\\t\\t\\n\\n\\t\\t\\tfor (int i = 2; i <= M; i++) {\\n\\t\\t\\t\\tlong sum = 0;\\n\\t\\t\\t\\tfor (int j = 1; j <= i - 1; j++)\\n\\t\\t\\t\\t\\tsum = (sum + h[j] * g[i - j]) % 1000000007;\\n\\t\\t\\t\\th[i] = (g[i] - sum + 1000000007) % 1000000007;\\n\\t\\t\\t}\\n\\n\\t\\t\\tSystem.out.println(h[M]);\\n\\t\\t}\\n\\n\\t\\tin.close();\\n\\t}\\n\\t\\n\\tprivate static long pow(long base, long power) {\\n\\t\\tif (power == 0)\\n\\t\\t\\treturn 1;\\t\\n\\t\\t\\n\\t\\tlong answer = base;\\n\\t\\t\\n\\t\\tfor (int i = 2; i <= power; i++)\\n\\t\\t\\tanswer = (answer * base) % 1000000007;\\n\\t\\t\\n\\t\\treturn answer;\\n\\t}\\n\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'legoBlocks' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER n\\n * 2. INTEGER m\\n */\\n\\n public static int legoBlocks(int n, int m) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n int result = Result.legoBlocks(n, m);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"legoBlocks(n, m)\"\n ],\n \"solution\": \"MAX = 1000000007\\n\\ndef calcLevels(levels):\\n\\tN = len(levels)\\n\\tM = len(levels[1])\\n\\n\\tlevels[1][0] = 1\\n\\tp = 1\\n\\twhile p<M:\\n\\t\\ti = 1\\n\\t\\twhile i<=4 and p-i>=0:\\n\\t\\t\\tlevels[1][p] = (levels[1][p] + levels[1][p-i]) % MAX\\n\\t\\t\\t#print(p, i, levels[1][p])\\n\\t\\t\\ti += 1\\n\\t\\tp += 1\\n\\tn = 2\\n\\twhile n<N:\\n\\t\\tp = 1\\n\\t\\twhile p<M:\\n\\t\\t\\tlevels[n][p] = (levels[n-1][p]*levels[1][p]) % MAX\\n\\t\\t\\tp += 1\\n\\t\\tn += 1\\n\\ndef getDP(dp, levels, N, M):\\n\\tif dp[N][M] != 0:\\n\\t\\treturn dp[N][M]\\n\\n\\tcurTmp = levels[N][M]\\n\\tp = 1\\n\\twhile p < M:\\n\\t\\tif dp[N][p] == 0:\\n\\t\\t\\tcurTmpLow = levels[N][p]\\n\\t\\t\\tq = 1\\n\\t\\t\\twhile q<p:\\n\\t\\t\\t\\tcurTmpLow = (curTmpLow - dp[N][q]*levels[N][p-q]) % MAX\\n\\t\\t\\t\\tq += 1\\n\\t\\t\\tdp[N][p] = curTmpLow\\n\\t\\tcurTmp = (curTmp - dp[N][p]*levels[N][M-p]) % MAX\\n\\t\\tp += 1\\n\\n\\tdp[N][M] = curTmp\\n\\t#print(N, M, dp[N])\\n\\treturn dp[N][M]\\n\\nif __name__ == '__main__':\\n\\tT = int(input())\\n\\tinputs = [[0, 0] for i in range(T)]\\n\\tmaxN, maxM = 0, 0\\n\\tp = 0\\n\\twhile p<T:\\n\\t\\tN, M = [int(i) for i in input().split(' ')]\\n\\t\\tif N>maxN:\\n\\t\\t\\tmaxN = N\\n\\t\\tif M>maxM:\\n\\t\\t\\tmaxM = M\\n\\t\\tinputs[p][:] = N, M\\n\\t\\tp += 1\\n\\n\\tlevels = [[0 for i in range(maxM+1)] for j in range(maxN+1)]\\n\\tdp = [[0 for i in range(maxM+1)] for j in range(maxN+1)]\\n\\n\\tcalcLevels(levels)\\n\\n\\tp = 0\\n\\twhile p<=maxN:\\n\\t\\tdp[p][1] = 1\\n\\t\\tp += 1\\n\\tp = 1\\n\\twhile p<=maxM:\\n\\t\\tdp[1][p] = levels[1][p]\\n\\t\\tp += 1\\n\\n\\tp = 0\\n\\twhile p<T:\\n\\t\\tN, M = inputs[p]\\n\\t\\tif N == 1 and M>=1 and M<=4:\\n\\t\\t\\tprint(1)\\n\\t\\telif N == 1:\\n\\t\\t\\tprint(0)\\n\\t\\telse:\\n\\t\\t\\tprint(getDP(dp, levels, N, M))\\n\\t\\tp += 1\\n\",\n \"template\": \"#\\n# Complete the 'legoBlocks' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. INTEGER n\\n# 2. INTEGER m\\n#\\n\\ndef legoBlocks(n, m):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n first_multiple_input = input().rstrip().split()\\n\\n n = int(first_multiple_input[0])\\n\\n m = int(first_multiple_input[1])\\n\\n result = legoBlocks(n, m)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":283,"cells":{"question_id":{"kind":"number","value":85,"string":"85"},"question_title":{"kind":"string","value":"Brick Tiling"},"question_content":{"kind":"string","value":"You are given a grid having N rows and M columns. A grid square can either be blocked or empty. Blocked squares are represented by a '#' and empty squares are represented by '.'. Find the number of ways to tile the grid using L shaped bricks. A L brick has one side of length three units while other of length 2 units. All empty squares in the grid should be covered by exactly one of the L shaped tiles, and blocked squares should not be covered by any tile. The bricks can be used in any orientation (they can be rotated or flipped).\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int brickTiling(List<String> grid)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class Solution {\\n\\tstatic InputStream is;\\n\\tstatic PrintWriter out;\\n//\\tstatic String INPUT = \\\"1 2 2 ## ##\\\";\\n\\tstatic String INPUT = \\\"\\\";\\n\\t\\n\\tstatic int[] makeMaskArray(int mask, int h, int amask)\\n\\t{\\n\\t\\tint[] ret = new int[h];\\n\\t\\tint p = 0;\\n\\t\\tfor(int i = 0;i < h;i++){\\n\\t\\t\\tif((i&mask) == 0 && (amask == -1 || (i&amask) != 0)){\\n\\t\\t\\t\\tret[p++] = i;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn Arrays.copyOf(ret, p);\\n\\t}\\n\\t\\n\\tstatic void solve()\\n\\t{\\n\\t\\tfor(int T = ni();T >= 1;T--){\\n\\t\\t\\tint n = ni(), m = ni();\\n\\t\\t\\tchar[][] map = nm(n,m);\\n\\t\\t\\tint[] pre = new int[1<<m*2+1];\\n\\t\\t\\tpre[(1<<m*2+1)-1] = 1;\\n\\t\\t\\tint[] cur = new int[1<<m*2+1];\\n\\t\\t\\tint mod = 1000000007;\\n\\t\\t\\tint omask = (1<<m*2+1)-1;\\n\\t\\t\\tint hmask = 1<<m*2;\\n\\t\\t\\tint mask1 = 1<<m-1|1<<2*m-1|1<<2*m;\\n\\t\\t\\tint mask2 = 1<<m-1|1<<2*m-1|1<<2*m-2;\\n\\t\\t\\tint mask3 = 1<<m-1|1<<m|1<<m+1;\\n\\t\\t\\tint mask4 = 1<<m-1|1<<m-2|1<<m-3;\\n\\t\\t\\tint mask5 = 1<<0|1<<m|1<<2*m;\\n\\t\\t\\tint mask6 = 1<<0|1<<m-1|1<<2*m-1;\\n\\t\\t\\tint mask7 = 1<<0|1<<1|1<<m+1;\\n\\t\\t\\tint mask8 = 1<<0|1<<1|1<<m-1;\\n\\t\\t\\tint[] val1 = makeMaskArray(mask1, 1<<2*m+1, -1);\\n\\t\\t\\tint[] val2 = makeMaskArray(mask2, 1<<2*m+1, hmask);\\n\\t\\t\\tint[] val3 = makeMaskArray(mask3, 1<<2*m+1, hmask);\\n\\t\\t\\tint[] val4 = makeMaskArray(mask4, 1<<2*m+1, hmask);\\n\\t\\t\\tint[] val5 = makeMaskArray(mask5, 1<<2*m+1, -1);\\n\\t\\t\\tint[] val6 = makeMaskArray(mask6, 1<<2*m+1, hmask);\\n\\t\\t\\tint[] val7 = makeMaskArray(mask7, 1<<2*m+1, hmask);\\n\\t\\t\\tint[] val8 = makeMaskArray(mask8, 1<<2*m+1, hmask);\\n\\t\\t\\tint[] valn = makeMaskArray(0, 1<<2*m+1, hmask);\\n\\t\\t\\t\\n\\t\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\t\\tfor(int j = 0;j < m;j++){\\n\\t\\t\\t\\t\\tArrays.fill(cur, 0);\\n\\t\\t\\t\\t\\tif(map[i][j] == '.'){\\n\\t\\t\\t\\t\\t\\t// xx\\n\\t\\t\\t\\t\\t\\t// .x\\n\\t\\t\\t\\t\\t\\t// .x\\n\\t\\t\\t\\t\\t\\tif(i >= 2 && j >= 1){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val1){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask1)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// x.\\n\\t\\t\\t\\t\\t\\t// x.\\n\\t\\t\\t\\t\\t\\t// xx\\n\\t\\t\\t\\t\\t\\tif(i >= 2 && j >= 1){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val5){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask5)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// xx\\n\\t\\t\\t\\t\\t\\t// x.\\n\\t\\t\\t\\t\\t\\t// x.\\n\\t\\t\\t\\t\\t\\tif(i >= 2 && j+1 < m){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val2){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask2)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// .x\\n\\t\\t\\t\\t\\t\\t// .x\\n\\t\\t\\t\\t\\t\\t// xx\\n\\t\\t\\t\\t\\t\\tif(i >= 2 && j >= 1){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val6){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask6)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// xxx\\n\\t\\t\\t\\t\\t\\t// ..x\\n\\t\\t\\t\\t\\t\\tif(i >= 1 && j >= 2){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val3){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask3)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// x..\\n\\t\\t\\t\\t\\t\\t// xxx\\n\\t\\t\\t\\t\\t\\tif(i >= 1 && j >= 2){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val7){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask7)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// xxx\\n\\t\\t\\t\\t\\t\\t// x..\\n\\t\\t\\t\\t\\t\\tif(i >= 1 && j+2 < m){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val4){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask4)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// ..x\\n\\t\\t\\t\\t\\t\\t// xxx\\n\\t\\t\\t\\t\\t\\tif(i >= 1 && j >= 2){\\n\\t\\t\\t\\t\\t\\t\\tfor(int k : val8){\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = ((k|mask8)<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t// none\\n\\t\\t\\t\\t\\t\\tfor(int k : valn){\\n\\t\\t\\t\\t\\t\\t\\tint nk = (k<<1)&omask;\\n\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}else{\\n\\t\\t\\t\\t\\t\\tfor(int k : valn){\\n\\t\\t\\t\\t\\t\\t\\tint nk = (k<<1|1)&omask;\\n\\t\\t\\t\\t\\t\\t\\tcur[nk] += pre[k];\\n\\t\\t\\t\\t\\t\\t\\tif(cur[nk] >= mod)cur[nk] -= mod;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tint[] dum = cur; cur = pre; pre = dum;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tout.println(pre[(1<<m*2+1)-1]);\\n\\t\\t}\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception\\n\\t{\\n\\t\\tlong S = System.currentTimeMillis();\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tlong G = System.currentTimeMillis();\\n\\t\\ttr(G-S+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tprivate static boolean eof()\\n\\t{\\n\\t\\tif(lenbuf == -1)return true;\\n\\t\\tint lptr = ptrbuf;\\n\\t\\twhile(lptr < lenbuf)if(!isSpaceChar(inbuf[lptr++]))return false;\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tis.mark(1000);\\n\\t\\t\\twhile(true){\\n\\t\\t\\t\\tint b = is.read();\\n\\t\\t\\t\\tif(b == -1){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn true;\\n\\t\\t\\t\\t}else if(!isSpaceChar(b)){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn false;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static byte[] inbuf = new byte[1024];\\n\\tstatic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate static int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate static boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate static int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate static double nd() { return Double.parseDouble(ns()); }\\n\\tprivate static char nc() { return (char)skip(); }\\n\\t\\n\\tprivate static String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate static char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate static char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate static int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate static int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { if(INPUT.length() != 0)System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'brickTiling' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static int brickTiling(List<String> grid) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<String> grid = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String gridItem = bufferedReader.readLine();\\n grid.add(gridItem);\\n }\\n\\n int result = Result.brickTiling(grid);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n private static final int MOD = 1000000007;\\n private static final int[][] pieceMasks = new int[][] { {0,7,1,4}, {-2,2,-1,2,0,3}, \\n {0,1,1,7}, {0,3,1,1,2,1},\\n {-1,4,0,7}, {0,1,1,1,2,3}, \\n {0,7,1,1}, {0,3,1,2,2,2}};\\n private int numCols, numRows;\\n private int[] startState;\\n private HashMap<String, Long> dp; \\n \\n Solution(String[] grid, int numRows, int numCols) {\\n this.numRows = numRows;\\n this.numCols = numCols;\\n dp = new HashMap<String, Long>();\\n int[] start = new int[numCols];\\n for (int i = 0; i < numCols; i++) {\\n start[i] = Integer.MAX_VALUE;\\n }\\n for (int i = 0; i < grid.length; i++) {\\n String row = grid[i];\\n for (int j = 0; j < row.length(); j++) {\\n if (row.charAt(j) == '.') {\\n start[j] = start[j] ^ (1 << i);\\n }\\n }\\n }\\n startState = start;\\n }\\n \\n private boolean isFilled(int[] state) {\\n for (int i: state) {\\n if (i < Integer.MAX_VALUE) { return false; }\\n }\\n return true;\\n }\\n \\n private int[] addShape(int[] shape, int[] state, int col, int row) {\\n int[] output = state.clone();\\n for (int i = 0; i < shape.length; i+=2) {\\n output[col+shape[i]] = output[col+shape[i]] | (shape[i+1] << row);\\n }\\n return output;\\n }\\n \\n private boolean willShapeFit(int[] shape, int[] state, int col, int row) {\\n for (int i = 0; i < shape.length; i+=2) {\\n int colIdx = col + shape[i];\\n if (colIdx < 0 || colIdx >= numCols) { return false; }\\n if ((state[colIdx] & (shape[i + 1] << row)) != 0) {\\n return false;\\n }\\n }\\n return true;\\n }\\n \\n private int[] nextEmpty(int[] state, int row, int col) {\\n int[] output = null;\\n while (row < numRows) {\\n if ((state[col] & (1 << row)) == 0) {\\n return new int[] {row, col};\\n }\\n row = (col + 1 == numCols) ? row + 1 : row;\\n col = (col + 1) % numCols;\\n } \\n return output;\\n }\\n \\n \\n private long helper(int[] state, int row, int col) {\\n String stateString = Arrays.toString(state);\\n if (dp.get(stateString) != null) { return dp.get(stateString); } \\n long output = 0;\\n for (int[] shape : pieceMasks) {\\n if (willShapeFit(shape, state, col, row)) {\\n int[] nextState = addShape(shape, state, col, row);\\n int[] nextIdx = nextEmpty(nextState, row, col);\\n if (nextIdx == null) { \\n output += 1; \\n }\\n else {\\n output += helper(nextState, nextIdx[0], nextIdx[1]);\\n }\\n }\\n }\\n dp.put(Arrays.toString(state), output);\\n return output % MOD;\\n }\\n \\n public long solve() {\\n int[] empty = nextEmpty(startState, 0, 0);\\n return (empty == null) ? 1 : helper(startState, empty[0], empty[1]);\\n }\\n \\n \\n public static void main(String args[] ) throws Exception {\\n Scanner scanner = new Scanner(System.in);\\n int t = scanner.nextInt();\\n while (t > 0) {\\n int numRows = scanner.nextInt();\\n int numCols = scanner.nextInt();\\n String[] grid = new String[numRows];\\n Pattern p = Pattern.compile(\\\"[.#]+\\\");\\n for (int i = 0; i < numRows; i++) {\\n grid[i] = scanner.next(p);\\n }\\n Solution solution = new Solution(grid, numRows, numCols);\\n System.out.println(solution.solve());\\n t--;\\n }\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'brickTiling' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static int brickTiling(List<String> grid) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<String> grid = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n int result = Result.brickTiling(grid);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int T = in.nextInt();\\n for (int t = 0; t < T; t++) {\\n int N = in.nextInt();\\n int M = in.nextInt();\\n in.nextLine();\\n int[] field = new int[N];\\n for (int i = 0; i < N; i++) {\\n char[] c = in.nextLine().toCharArray();\\n int x = 0;\\n for (int j = 0; j < M; j++) {\\n if (c[j] == '#') {\\n x |= (1 << j);\\n }\\n }\\n field[i] = x;\\n }\\n int PLEN = 1<<(M*2);\\n int[][] transitions = new int[PLEN][];\\n for (int i = 0; i < PLEN; i++) {\\n transitions[i] = getTransitions(i, M);\\n //System.out.println(i + \\\" \\\" + Arrays.toString(transitions[i]));\\n }\\n\\n long[] profile = new long[PLEN];\\n long[] next_profile = new long[PLEN];\\n profile[0] = 1;\\n for (int i = 0; i < N-1; i++) {\\n Arrays.fill(next_profile, 0);\\n for (int p = 0; p < PLEN; p++) {\\n int fieldP = i == 0 ? field[i] : 0;\\n if ((p & fieldP) == 0) {\\n long ways = profile[p];\\n if (ways > 0) {\\n int actualP = p | fieldP;\\n int[] to_all = transitions[actualP];\\n for (int j = 0; j < to_all.length; j++) {\\n int to = to_all[j];\\n if ((to & field[i+1]) == 0) {\\n int actualTo = to | field[i+1];\\n next_profile[actualTo] = (next_profile[actualTo] + ways) % 1000000007;\\n }\\n }\\n }\\n }\\n }\\n //System.out.println(Arrays.toString(next_profile));\\n long[] profile_c = profile;\\n profile = next_profile;\\n next_profile = profile_c;\\n }\\n\\n long result = profile[(1 << M) - 1];\\n System.out.println(result);\\n }\\n }\\n\\n private static int[] getTransitions(int p, int M) {\\n List<Integer> result = new ArrayList<>();\\n int next = p >> M;\\n p &= ((1<<M)-1);\\n findTransitions(p, next, M, result);\\n int[] resultArray = new int[result.size()];\\n for (int i = 0; i < result.size(); i++) {\\n resultArray[i] = result.get(i);\\n }\\n return resultArray;\\n }\\n\\n private static void findTransitions(int p, int next, int M, List<Integer> result) {\\n int idx = 0;\\n for (; ((p & (1<<idx)) > 0) && idx < M; idx++);\\n\\n if (idx == M) {\\n result.add(next);\\n return;\\n }\\n\\n // *\\n // *\\n // **\\n if (idx > 0) {\\n int maskP = 1<<(idx);\\n int maskN = 1<<(idx) | 1<<(M+idx-1) | 1<<(M+idx);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // *\\n // *\\n // **\\n if (idx < M-1) {\\n int maskP = 1<<(idx);\\n int maskN = 1<<(idx) | 1<<(M+idx) | 1<<(M+idx+1);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // *\\n // ***\\n if (idx > 1) {\\n int maskP = 1<<(idx);\\n int maskN = 1<<(idx) | 1<<(idx-1) | 1<<(idx-2);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // *\\n // ***\\n if (idx < M-2) {\\n int maskP = 1<<(idx);\\n int maskN = 1<<(idx) | 1<<(idx+1) | 1<<(idx+2);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // **\\n // *\\n // *\\n if (idx < M-1) {\\n int maskP = 1<<(idx) | 1<<(idx+1);\\n int maskN = 1<<(idx) | 1<<(M+idx);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // **\\n // *\\n // *\\n if (idx < M-1) {\\n int maskP = 1<<(idx) | 1<<(idx+1);\\n int maskN = 1<<(idx+1) | 1<<(M+idx+1);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // ***\\n // *\\n if (idx < M-2) {\\n int maskP = 1<<(idx) | 1<<(idx+1) | 1<<(idx+2);\\n int maskN = 1<<(idx);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n\\n // ***\\n // *\\n if (idx < M-2) {\\n int maskP = 1<<(idx) | 1<<(idx+1) | 1<<(idx+2);\\n int maskN = 1<<(idx+2);\\n tryFindTransitions(p, next, maskP, maskN, M, result);\\n }\\n }\\n\\n private static void tryFindTransitions(int p, int next, int maskP, int maskN, int M, List<Integer> result) {\\n if (((p & maskP) == 0) && ((next & maskN) == 0)) {\\n findTransitions(p | maskP, next | maskN, M, result);\\n }\\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'brickTiling' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING_ARRAY grid as parameter.\\n */\\n\\n public static int brickTiling(List<String> grid) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<String> grid = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n int result = Result.brickTiling(grid);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"brickTiling(grid)\"\n ],\n \"solution\": \"def memoize(func):\\n pool = {}\\n def wrapper(*arg):\\n if arg not in pool:\\n pool[arg] = func(*arg)\\n return pool[arg]\\n return wrapper\\n\\nmod = 1000000007\\nshapes = (\\\\\\n ((1,0),(2,0),(2,1)),\\\\\\n ((0,1),(0,2),(-1,2)),\\\\\\n ((0,1),(1,1),(2,1)),\\\\\\n ((1,0),(0,1),(0,2)),\\\\\\n ((0,1),(-1,1),(-2,1)),\\\\\\n ((0,1),(0,2),(1,2)),\\\\\\n ((1,0),(2,0),(0,1)),\\\\\\n ((1,0),(1,1),(1,2)))\\n\\nfor case in range(int(input())):\\n Y,X = map(int,input().split())\\n mx = [int(''.join('0' if c =='.' else '1' for c in input().rstrip()), 2) for i in range(Y)]\\n mx = mx + 3*[0]\\n full = (1<<X)-1\\n\\n @memoize\\n def rec(y,first,second,third):\\n if y==Y:\\n return 1 if first == second and second == third and third == 0 else 0\\n if first == full:\\n return rec(y+1,second,third,mx[y+3])\\n\\n def can_fit(rows,shape,x_offset):\\n res = rows[:]\\n for x,y in shape:\\n x += x_offset\\n if x < 0 or x >= X or y < 0 or y >= Y:\\n return None\\n if res[y] & (1<<x) != 0:\\n return None\\n res[y] |= (1<<x)\\n return res\\n\\n free = 0\\n while (first & (1<<free)) != 0:\\n free += 1\\n rows = [first | (1<<free),second,third]\\n ans = 0\\n for shape in shapes:\\n nrows = can_fit(rows,shape,free)\\n if nrows != None:\\n ans = (ans + rec(y, *nrows)) % mod\\n return ans\\n\\n print(rec(0,mx[0],mx[1],mx[2]))\\n\",\n \"template\": \"#\\n# Complete the 'brickTiling' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts STRING_ARRAY grid as parameter.\\n#\\n\\ndef brickTiling(grid):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n first_multiple_input = input().rstrip().split()\\n\\n n = int(first_multiple_input[0])\\n\\n m = int(first_multiple_input[1])\\n\\n grid = []\\n\\n for _ in range(n):\\n grid_item = input()\\n grid.append(grid_item)\\n\\n result = brickTiling(grid)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":284,"cells":{"question_id":{"kind":"number","value":330,"string":"330"},"question_title":{"kind":"string","value":"Stock Maximize"},"question_content":{"kind":"string","value":"Your algorithms have become so good at predicting the market that you now know what the share price of Wooden Orange Toothpicks Inc. (WOT) will be for the next number of days.\n\nEach day, you can either buy one share of WOT, sell any number of shares of WOT that you own, or not make any transaction at all. What is the maximum profit you can obtain with an optimum trading strategy?\n\n**Example** \n$prices=[1,2]$ \n\nBuy one share day one, and sell it day two for a profit of $1$. Return $1$. \n\n$prices=[2, 1]$ \n\nNo profit can be made so you do not buy or sell stock those days. Return $0$.\n\n**Function Description** \n\nComplete the *stockmax* function in the editor below. \n\nstockmax has the following parameter(s): \n\n- *prices*: an array of integers that represent predicted daily stock prices \n\n**Returns** \n\n- *int:* the maximum profit achievable"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static long stockmax(List<Integer> prices)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"\\nimport java.io.BufferedReader;\\nimport java.io.IOException;\\nimport java.util.StringTokenizer;\\nimport java.io.InputStreamReader;\\npublic class Solution {\\n public static void main(String arg[]) throws IOException {\\n try {\\n BufferedReader br = new BufferedReader(new InputStreamReader(System.in));\\n int t=Integer.parseInt(br.readLine());\\n while(t!=0){\\n int n=Integer.parseInt(br.readLine());\\n int arr[]=new int[n];\\n StringTokenizer st = new StringTokenizer(br.readLine());\\n for(int i=0;i<n;i++){\\n arr[i]=Integer.parseInt(st.nextToken());\\n }\\n int p=0;\\n long pp=0;\\n while(p<n){\\n int max=0,k=p;\\n for(int i=p;i<n;i++){\\n \\n if(arr[i]>max){\\n max=arr[i];\\n //System.out.println(max);\\n p=i+1;\\n }\\n }\\n for(int i=k;i<n&&arr[i]<max;i++){\\n pp=pp+(max-arr[i]);\\n }\\n }\\n System.out.println(pp);\\n t--;\\n }\\n } catch (Exception e) {\\n }\\n } \\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'stockmax' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts INTEGER_ARRAY prices as parameter.\\n */\\n\\n public static long stockmax(List<Integer> prices) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] pricesTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> prices = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int pricesItem = Integer.parseInt(pricesTemp[i]);\\n prices.add(pricesItem);\\n }\\n\\n long result = Result.stockmax(prices);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'stockmax' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts INTEGER_ARRAY prices as parameter.\\n */\\n\\n public static long stockmax(List<Integer> prices) {\\n int rightMax = Integer.MIN_VALUE;\\n long maxProfit = 0;\\n for (int i = prices.size() - 1; i >= 0; --i) {\\n rightMax = Math.max(rightMax, prices.get(i));\\n maxProfit += rightMax - prices.get(i);\\n }\\n return maxProfit;\\n }\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> prices = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n long result = Result.stockmax(prices);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'stockmax' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts INTEGER_ARRAY prices as parameter.\\n */\\n\\n public static long stockmax(List<Integer> prices) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> prices = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n long result = Result.stockmax(prices);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nclass Solution {\\n\\tprivate static long[] getElements(String elements, int size) {\\n\\n\\tString[] elementsArray = elements.trim().split(\\\" \\\");\\n\\n\\t\\tif (elementsArray.length != size)\\n\\t\\t\\tthrow new IllegalArgumentException(\\\"Number of elements in the list does not match the size provided\\\");\\n\\t\\tlong[] numbers = new long[size];\\n\\t\\tint index = 0;\\n\\n\\t\\t// extract integers\\n\\t\\tfor (String ele : elementsArray) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tnumbers[index++] = Long.parseLong(ele);\\n\\t\\t\\t} catch (NumberFormatException nfe) {\\n\\t\\t\\t\\tSystem.out.println(\\\"Caught NumberFormatException: Unable to parse to long\\\");\\n\\t\\t\\t\\tnfe.getStackTrace();\\n}\\n\\n\\t\\t}\\n\\t\\treturn numbers;\\n\\t}\\n\\n\\tprivate static boolean[] findSellingDays(long[] stockPrices, int days) {\\n\\n\\tboolean[] sellOn = new boolean[days]; // an array to keep track on days on which we can sell\\n\\t\\tArrays.fill(sellOn, false); // fill with false\\n\\n\\t\\tlong localMax = Long.MIN_VALUE; // initialize the local max with minimum value possible\\n\\n\\t\\t// traverse the array from back and if there mark selling days for local maximum\\n\\t\\tfor (int i = days - 1; i >= 0; i--) {\\n\\t\\t\\tif (localMax < stockPrices[i]) { // found better local maximum\\n\\t\\t\\t\\tlocalMax = stockPrices[i]; // update local maximum\\n\\t\\t\\t\\tsellOn[i] = true; // sell all existing shares on this day\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn sellOn;\\n\\t}\\n\\tprivate static long calcMaxProfit(long[] stockPrices, int days) {\\n\\n\\t\\t// pre-process the stock price array and find the days on which we should \\n\\t\\t// sell the shares for maximum profit\\n\\t\\tboolean[] sellOn = findSellingDays(stockPrices, days);\\n\\n\\t\\tlong totalCost = 0, totalProfit = 0;\\n\\t\\tint numShares = 0;\\n\\n\\t\\t// go through all the array containing stock prices and do the transaction\\n\\t\\t// if this is a buying day i.e. sellOn[i] is false buy that share else if sellOn[i]\\n\\t\\t// if true and we have something to sell then sell it else just stay put\\n\\tfor (int i = 0; i < days; i++) {\\n\\t\\t\\tif (sellOn[i] == false) { // buy shares\\n\\t\\t\\t\\ttotalCost += stockPrices[i];\\n\\t\\t\\t\\tnumShares++;\\n\\t\\t\\t} else if (totalCost != 0) { // not a buying day and if we have something to sell then sell it\\n\\t\\t\\t\\ttotalProfit += numShares * stockPrices[i] - totalCost; // calculate the profit\\n\\t\\t\\t\\t// we sold everything so reset these variables\\n\\t\\t\\t\\ttotalCost = 0;\\n\\t\\t\\t\\tnumShares = 0;\\n\\t\\t}\\n\\t\\t}\\n\\t\\treturn totalProfit;\\n\\t}\\n\\n\\tpublic static void main(String[] args) {\\n\\t\\tBufferedReader input = new BufferedReader(new InputStreamReader(System.in));\\n\\n\\ttry {\\n\\t\\t\\tint testCases = Integer.parseInt(input.readLine().trim());\\n\\n\\t\\t\\tif (testCases <= 0) {\\n\\t\\t\\tthrow new IllegalArgumentException(\\\"The number of test cases must be greater than 0\\\");\\n\\t\\t\\t}\\n\\n\\t\\t\\twhile (testCases > 0) {\\n\\t\\t\\t\\tint days = Integer.parseInt(input.readLine().trim());\\n\\t\\t\\t\\tif (days <= 0) {\\n\\t\\t\\t\\t\\tthrow new IllegalArgumentException(\\\"The number of test cases must be greater than 0\\\");\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tlong[] stockPrices = getElements(input.readLine(), days);\\n\\n\\t\\t\\t\\tlong maxProfit = calcMaxProfit(stockPrices, days);\\n\\t\\t\\t\\tSystem.out.println(maxProfit);\\n\\t\\t\\t\\ttestCases--;\\n\\t\\t\\t}\\n\\t\\t\\tinput.close();\\n\\t\\t} catch (NumberFormatException nfe) {\\n\\t\\t\\tSystem.out.println(\\\"Caught NumberFormatException: Unable to parse inputs from stdin\\\");\\n\\t\\t\\tnfe.getStackTrace();\\n\\t\\t} catch (IOException ioe) {\\n\\t\\t\\tSystem.out.println(\\\"Caught IOException: Unable to read inputs from stdin\\\");\\n\\t\\t\\tioe.getStackTrace();\\n\\t\\t}\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'stockmax' function below.\\n *\\n * The function is expected to return a LONG_INTEGER.\\n * The function accepts INTEGER_ARRAY prices as parameter.\\n */\\n\\n public static long stockmax(List<Integer> prices) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> prices = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n long result = Result.stockmax(prices);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"stockmax(prices)\"\n ],\n \"solution\": \"test=int(input())\\nfor i in range(test):\\n n=int(input())\\n a=list(map(int,input().split()))\\n c=0\\n i=len(a)-1\\n while(i>=0):\\n d=a[i]\\n l=i\\n p=0\\n while(a[i]<=d and i>=0):\\n p+=a[i]\\n i-=1\\n c+=(l-i)*a[l]-p\\n continue\\n print (c)\",\n \"template\": \"#\\n# Complete the 'stockmax' function below.\\n#\\n# The function is expected to return a LONG_INTEGER.\\n# The function accepts INTEGER_ARRAY prices as parameter.\\n#\\n\\ndef stockmax(prices):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n n = int(input().strip())\\n\\n prices = list(map(int, input().rstrip().split()))\\n\\n result = stockmax(prices)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":285,"cells":{"question_id":{"kind":"number","value":9200,"string":"9,200"},"question_title":{"kind":"string","value":"Two Robots"},"question_content":{"kind":"string","value":"You have a warehouse with $M$ containers filled with an infinite number of candies. The containers are arranged in a single row, equally spaced to be $1$ meter apart. You also have $2$ robots that can pick up $1$ piece of candy and transport it between any two containers.\n\nThe robots take instructions in the form of *queries* consisting of two integers, $M_a$ and $M_b$, respectively. To execute a query, a robot travels to container $M_a$, picks up $1$ candy, transports it to container $M_b$, and then stops at $M_b$ until it receives another query.\t \n \nCalculate the *minimum total distance* the robots must travel to execute $N$ queries *in order*. \n\n**Note:** You choose which robot executes each query.\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int twoRobots(int m, List<List<Integer>> queries)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.Arrays;\\n\\npublic class HR_two_robots {\\n\\n public static void solve(Input in, PrintWriter out) throws IOException {\\n int tests = in.nextInt();\\n for (int test = 0; test < tests; ++test) {\\n int m = in.nextInt();\\n int n = in.nextInt();\\n int[] a = new int[n];\\n int[] b = new int[n];\\n for (int i = 0; i < n; ++i) {\\n a[i] = in.nextInt() - 1;\\n b[i] = in.nextInt() - 1;\\n }\\n if (n == 1) {\\n out.println(Math.abs(a[0] - b[0]));\\n continue;\\n }\\n int[][] d = new int[n][n];\\n for (int[] ar : d) {\\n Arrays.fill(ar, 1000000000);\\n }\\n int sum = Math.abs(a[0] - b[0]);\\n for (int i = 1; i < n; ++i) {\\n sum += Math.abs(a[i] - b[i]);\\n d[i][i - 1] = sum;\\n sum += Math.abs(b[i - 1] - a[i]);\\n }\\n for (int i = 1; i < n - 1; ++i) {\\n for (int j = 0; j < i; ++j) {\\n d[i + 1][j] = Math.min(d[i + 1][j], d[i][j] + Math.abs(b[i] - a[i + 1]) + Math.abs(a[i + 1] - b[i + 1]));\\n d[i + 1][i] = Math.min(d[i + 1][i], d[i][j] + Math.abs(b[j] - a[i + 1]) + Math.abs(a[i + 1] - b[i + 1]));\\n }\\n }\\n int ans = 1000000000;\\n for (int i = 0; i < n; ++i) {\\n ans = Math.min(ans, d[n - 1][i]);\\n }\\n out.println(ans);\\n }\\n }\\n\\n public static void main(String[] args) throws IOException {\\n PrintWriter out = new PrintWriter(System.out);\\n solve(new Input(new BufferedReader(new InputStreamReader(System.in))), out);\\n out.close();\\n }\\n\\n static class Input {\\n BufferedReader in;\\n StringBuilder sb = new StringBuilder();\\n\\n public Input(BufferedReader in) {\\n this.in = in;\\n }\\n\\n public Input(String s) {\\n this.in = new BufferedReader(new StringReader(s));\\n }\\n\\n public String next() throws IOException {\\n sb.setLength(0);\\n while (true) {\\n int c = in.read();\\n if (c == -1) {\\n return null;\\n }\\n if (\\\" \\\\n\\\\r\\\\t\\\".indexOf(c) == -1) {\\n sb.append((char)c);\\n break;\\n }\\n }\\n while (true) {\\n int c = in.read();\\n if (c == -1 || \\\" \\\\n\\\\r\\\\t\\\".indexOf(c) != -1) {\\n break;\\n }\\n sb.append((char)c);\\n }\\n return sb.toString();\\n }\\n\\n public int nextInt() throws IOException {\\n return Integer.parseInt(next());\\n }\\n\\n public long nextLong() throws IOException {\\n return Long.parseLong(next());\\n }\\n\\n public double nextDouble() throws IOException {\\n return Double.parseDouble(next());\\n }\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoRobots' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER m\\n * 2. 2D_INTEGER_ARRAY queries\\n */\\n\\n public static int twoRobots(int m, List<List<Integer>> queries) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int n = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> queries = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String[] queriesRowTempItems = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> queriesRowItems = new ArrayList<>();\\n\\n for (int j = 0; j < 2; j++) {\\n int queriesItem = Integer.parseInt(queriesRowTempItems[j]);\\n queriesRowItems.add(queriesItem);\\n }\\n\\n queries.add(queriesRowItems);\\n }\\n\\n int result = Result.twoRobots(m, queries);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'twoRobots' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER m\\n * 2. 2D_INTEGER_ARRAY queries\\n */\\n\\n public static int twoRobots(int m, List<List<Integer>> queries) {\\n Iterator<List<Integer>> qIterator = queries.iterator();\\n int totalLength = 0;\\n final int n = queries.size();\\n\\n int[] from = new int[n];\\n int[] to = new int[n];\\n int i = 0;\\n\\n while (qIterator.hasNext()) {\\n List<Integer> move = qIterator.next();\\n from[i] = move.get(0);\\n to[i] = move.get(1);\\n int length = Math.abs(to[i] - from[i]);\\n totalLength += length;\\n i++;\\n }\\n\\n if (n <= 2) {\\n return totalLength;\\n }\\n\\n int[] agg = new int[n];\\n\\n int right1 = Math.abs(from[n - 1] - to[n - 2]);\\n int right2 = Math.abs(from[n - 1] - to[n - 3]);\\n int corner = Math.abs(from[n - 2] - to[n - 3]);\\n\\n int rowMin2 = Math.min(right1, right2);\\n int rowMin = Math.min(rowMin2, corner);\\n agg[0] = right1;\\n agg[1] = 0;\\n for(int r = 3; r < n; r++) {\\n agg[0] += corner;\\n int thisRowMin2 = agg[0];\\n for (int c = 0; c < r - 1; c++) {\\n int thisDistance = Math.abs(from[n - c - 1] - to[n - r - 1]);\\n agg[c + 1] = c == r - 2 ? rowMin2 : agg[c + 1] + corner;\\n thisRowMin2 = Math.min(thisRowMin2, thisDistance + agg[c + 1]);\\n }\\n corner = Math.abs(from[n - r] - to[n - r - 1]);\\n\\n rowMin = Math.min(corner + rowMin, thisRowMin2);\\n rowMin2 = thisRowMin2;\\n }\\n\\n return totalLength + rowMin;\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n \\n for (int x = 0; x < t; x++) {\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int n = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> queries = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n queries.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.twoRobots(m, queries);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoRobots' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER m\\n * 2. 2D_INTEGER_ARRAY queries\\n */\\n\\n public static int twoRobots(int m, List<List<Integer>> queries) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int n = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> queries = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n queries.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.twoRobots(m, queries);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class WeekOfCode19qB {\\n\\n\\tpublic static void main(String[] args) {\\n\\t\\tInputReader in = new InputReader(System.in);\\n\\t\\tPrintWriter w = new PrintWriter(System.out);\\n\\n\\t\\tint t = in.nextInt();\\n\\n\\t\\twhile(t-- > 0){\\n\\t\\t\\tint m = in.nextInt();\\n\\t\\t\\tint n = in.nextInt();\\n\\t\\t\\n\\t\\t\\tint a[] = new int[n];\\n\\t\\t\\tint b[] = new int[n];\\n\\t\\t\\t\\n\\t\\t\\tfor(int i = 0; i < n; i++){\\n\\t\\t\\t\\ta[i] = in.nextInt() - 1;\\n\\t\\t\\t\\tb[i] = in.nextInt() - 1;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tint dp[][] = new int[n + 1][m + 1];\\n\\t\\t\\t\\n\\t\\t\\tfor(int i = n - 1; i >= 1; i--){\\n\\t\\t\\t\\tfor(int j = 0; j < m; j++){\\n\\t\\t\\t\\t\\tdp[i][j] = dp[i + 1][b[i - 1]] + Math.abs(a[i] - j) + Math.abs(b[i] - a[i]);\\n\\t\\t\\t\\t\\tdp[i][j] = Math.min(dp[i][j], dp[i + 1][j] + Math.abs(b[i - 1] - a[i]) + Math.abs(b[i] - a[i]));\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tint ans = Integer.MAX_VALUE;\\n\\t\\t\\tfor(int j = 0; j < m; j++)\\n\\t\\t\\t\\tans = Math.min(ans, dp[1][j] + Math.abs(b[0] - a[0]));\\n\\t\\t\\t\\n\\t\\t\\tw.println(ans);\\n\\t\\t}\\n\\n\\t\\tw.close();\\n\\t}\\n\\n\\tstatic class InputReader {\\n\\n\\t\\tprivate InputStream stream;\\n\\t\\tprivate byte[] buf = new byte[8192];\\n\\t\\tprivate int curChar, snumChars;\\n\\t\\tprivate SpaceCharFilter filter\\t;\\n\\n\\t\\tpublic InputReader(InputStream stream) {\\n\\t\\t\\tthis.stream = stream;\\n\\t\\t}\\n\\n\\t\\tpublic int snext() {\\n\\t\\t\\tif (snumChars == -1)\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\tif (curChar >= snumChars) {\\n\\t\\t\\t\\tcurChar = 0;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tsnumChars = stream.read(buf);\\n\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (snumChars <= 0)\\n\\t\\t\\t\\t\\treturn -1;\\n\\t\\t\\t}\\n\\t\\t\\treturn buf[curChar++];\\n\\t\\t}\\n\\n\\t\\tpublic int nextInt() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t}\\n\\t\\t\\tint res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic long nextLong() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t}\\n\\t\\t\\tlong res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic int[] nextIntArray(int n) {\\n\\t\\t\\tint a[] = new int[n];\\n\\t\\t\\tfor (int i = 0; i < n; i++)\\n\\t\\t\\t\\ta[i] = nextInt();\\n\\t\\t\\treturn a;\\n\\t\\t}\\n\\n\\t\\tpublic String readString() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tStringBuilder res = new StringBuilder();\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tres.appendCodePoint(c);\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res.toString();\\n\\t\\t}\\n\\n\\t\\tpublic boolean isSpaceChar(int c) {\\n\\t\\t\\tif (filter != null)\\n\\t\\t\\t\\treturn filter.isSpaceChar(c);\\n\\t\\t\\treturn c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n\\t\\t}\\n\\n\\t\\tpublic interface SpaceCharFilter {\\n\\t\\t\\tpublic boolean isSpaceChar(int ch);\\n\\t\\t}\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoRobots' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER m\\n * 2. 2D_INTEGER_ARRAY queries\\n */\\n\\n public static int twoRobots(int m, List<List<Integer>> queries) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int n = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> queries = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n queries.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.twoRobots(m, queries);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"twoRobots(m, queries)\"\n ],\n \"solution\": \"from collections import defaultdict\\n\\ndef dist(x, y):\\n return abs(x - y)\\n\\ndef solve(boxes):\\n boxes.reverse()\\n c = [0] * len(boxes)\\n c[0] = dist(boxes[0][0], boxes[0][1])\\n for bi in range(1, len(boxes)):\\n bx, by = boxes[bi]\\n cur_dist = dist(bx, by)\\n dist_to_prev = dist(by, boxes[bi - 1][0])\\n c[bi] = c[bi - 1] + dist_to_prev + cur_dist\\n for i in range(0, bi-1):\\n c[bi - 1] = min(c[bi - 1], dist(by, boxes[i][0]) + c[i])\\n c[i] += dist_to_prev + cur_dist\\n\\n c[bi - 1] += cur_dist\\n\\n return min(c)\\n\\n\\nt = int(input())\\n\\nfor i in range(0, t):\\n m, n = map(int, input().strip().split(' '))\\n boxes = []\\n for i in range(0, n):\\n boxes.append([int(x) for x in input().strip().split(' ')])\\n \\n print(solve(boxes))\\n \",\n \"template\": \"#\\n# Complete the 'twoRobots' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. INTEGER m\\n# 2. 2D_INTEGER_ARRAY queries\\n#\\n\\ndef twoRobots(m, queries):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n first_multiple_input = input().rstrip().split()\\n\\n m = int(first_multiple_input[0])\\n\\n n = int(first_multiple_input[1])\\n\\n queries = []\\n\\n for _ in range(n):\\n queries.append(list(map(int, input().rstrip().split())))\\n\\n result = twoRobots(m, queries)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":286,"cells":{"question_id":{"kind":"number","value":514,"string":"514"},"question_title":{"kind":"string","value":"Cut Tree"},"question_content":{"kind":"string","value":"Given a tree *T* with *n* nodes, how many subtrees (*T'*) of *T* have at most *K* edges connected to (T - T')? \n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"static int cuttree(int n, int k, int[][] edges)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.BufferedInputStream;\\nimport java.util.ArrayList;\\nimport java.util.Scanner;\\n\\n\\npublic class Solution {\\n\\tstatic long rooted[][] = new long [55][55];\\n\\tstatic int size[] = new int[55];\\n\\tstatic int outDegree[] = new int[55];\\n\\tstatic ArrayList<Integer> tree[] = new ArrayList[55];\\n\\tstatic int n;\\n\\tstatic int k;\\n\\t\\n\\tstatic void dfs(int u, int p) {\\n\\t\\tsize[u] = 1;\\n\\t\\t\\n\\t\\tfor (int v : tree[u]) {\\n\\t\\t\\tif (v == p) continue;\\n\\t\\t\\tdfs(v, u);\\n\\t\\t\\t\\n\\t\\t\\toutDegree[u]++;\\n\\t\\t\\tsize[u] += size[v];\\n\\t\\t}\\n\\t\\t//////////////////////////////////////////////////////////////////\\n\\t\\tlong pre[] = rooted[u];\\n\\t\\trooted[u][0] = 1;\\n\\t\\tfor (int v : tree[u]) {\\n\\t\\t\\tif (v == p) continue;\\n\\t\\t\\n\\t\\t\\trooted[u] = new long[55];\\n\\t\\t\\tfor (int i=0; i<=k; i++) {\\n\\t\\t\\t\\tif (i >= 1) rooted[u][i] += pre[i - 1];\\n\\t\\t\\t\\tfor (int j=0; j<=i; j++)\\n\\t\\t\\t\\t\\trooted[u][i] += pre[i - j] * rooted[v][j];\\n\\t\\t\\t}\\n\\t\\t\\tpre = rooted[u];\\t\\n\\t\\t}\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) {\\n\\t\\tScanner cin = new Scanner(new BufferedInputStream(System.in));\\n\\t\\tn = cin.nextInt();\\n\\t\\tk = cin.nextInt();\\n\\t\\tfor (int i=0; i<n; i++) tree[i] = new ArrayList<Integer>();\\n\\t\\tfor (int i=0; i<n-1; i++) {\\n\\t\\t\\tint u = cin.nextInt(); u--;\\n\\t\\t\\tint v = cin.nextInt(); v--;\\n\\t\\t\\ttree[u].add(v);\\n\\t\\t\\ttree[v].add(u);\\n\\t\\t}\\n\\t\\t\\n\\t\\tdfs(0, -1);\\n\\n\\t\\tlong ans = 0;\\n\\t\\tfor (int i=0; i<n; i++)\\n\\t\\t\\tif (i == 0)\\n\\t\\t\\t\\tfor (int j=0; j<=k; j++) ans += rooted[i][j];\\n\\t\\t\\telse \\n\\t\\t\\t\\tfor (int j=1; j<=k; j++) ans += rooted[i][j - 1];\\n\\t\\tSystem.out.println(ans + 1);\\n\\t\\t\\n//\\t\\tfor (int i=0; i<n; i++) {\\n//\\t\\t\\tfor (int j=0; j<=k; j++)\\n//\\t\\t\\t\\tSystem.out.print(rooted[i][j] + \\\" \\\");\\n//\\t\\t\\tSystem.out.println();\\n//\\t\\t}\\n//\\t\\tSystem.out.println();\\n\\t}\\n}\\n\",\n \"template\": \" /*\\n * Complete the cuttree function below.\\n */\\n static int cuttree(int n, int k, int[][] edges) {\\n /*\\n * Write your code here.\\n */\\n\\n }\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n\",\n \"template_tail\": \" private static final Scanner scanner = new Scanner(System.in);\\n\\n public static void main(String[] args) throws IOException {\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] nk = scanner.nextLine().split(\\\" \\\");\\n\\n int n = Integer.parseInt(nk[0].trim());\\n\\n int k = Integer.parseInt(nk[1].trim());\\n\\n int[][] edges = new int[n-1][2];\\n\\n for (int edgesRowItr = 0; edgesRowItr < n-1; edgesRowItr++) {\\n String[] edgesRowItems = scanner.nextLine().split(\\\" \\\");\\n\\n for (int edgesColumnItr = 0; edgesColumnItr < 2; edgesColumnItr++) {\\n int edgesItem = Integer.parseInt(edgesRowItems[edgesColumnItr].trim());\\n edges[edgesRowItr][edgesColumnItr] = edgesItem;\\n }\\n }\\n\\n int result = cutTree(n, k, edges);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"null"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n \\n private static List<List<Integer>> children = new ArrayList<>(51);\\n private static long[][] findCache = new long[51][51];\\n private static long[][][][] ignoreCache = new long[51][51][51][51];\\n\\n static {\\n for (int i = 0; i < 51; i++) {\\n for (int j = 0; j < 51; j++) {\\n findCache[i][j] = -1;\\n for (int k = 0; k < 51; k++) {\\n for (int l = 0; l < 51; l++) {\\n ignoreCache[i][j][k][l] = -1;\\n }\\n }\\n }\\n }\\n }\\n\\n public static void main(String[] args) {\\n /* Enter your code here. Read input from STDIN. Print output to STDOUT. Your class should be named Solution. */\\n // read inputs\\n Scanner scanner = new Scanner(System.in);\\n final int N = scanner.nextInt();\\n final int K = scanner.nextInt();\\n List<Set<Integer>> childrenSet = new ArrayList<>(51);\\n for (int i = 0; i <= N; i++) childrenSet.add(new HashSet<>(51));\\n for (int i = 0; i < N - 1; i++) {\\n int id1 = scanner.nextInt();\\n int id2 = scanner.nextInt();\\n childrenSet.get(id1).add(id2);\\n childrenSet.get(id2).add(id1);\\n }\\n // convert graph to tree, nodes[1] is the root\\n Queue<Integer> queue = new ArrayDeque<>();\\n queue.add(1);\\n while (!queue.isEmpty()) {\\n int root = queue.poll();\\n for (int idx : childrenSet.get(root)) {\\n childrenSet.get(idx).remove(root);\\n queue.offer(idx);\\n }\\n }\\n children.add(new ArrayList<>());\\n for (int i = 1; i <= N; i++) children.add(new ArrayList<>(childrenSet.get(i)));\\n // calculate\\n long res = 1;\\n for (int i = 1; i <= N; i++) {\\n for (int j = 0; j <= K; j++) {\\n res += find(i, j - (i == 1 ? 0 : 1));\\n }\\n }\\n System.out.println(res);\\n }\\n\\n private static long find(int root, int K) {\\n if (K < 0) return 0;\\n if (findCache[root][K] != -1) return findCache[root][K];\\n long res = 0;\\n for (int i = 0; i <= children.get(root).size(); i++) {\\n res += ignoreKids(root, 0, i, K - i);\\n }\\n findCache[root][K] = res;\\n return res;\\n }\\n\\n /**\\n * @param root the root\\n * @param startIdx the start index of children of the root\\n * @param ignoreCnt the count of children to ignore\\n * @param K the connection to rest graph from the children we take\\n * @return\\n */\\n private static long ignoreKids(int root, int startIdx, int ignoreCnt, int K) {\\n if (ignoreCnt < 0 || K < 0) return 0;\\n if (startIdx + ignoreCnt > children.get(root).size()) return 0;\\n if (startIdx == children.get(root).size()) return ignoreCnt == 0 && K == 0 ? 1 : 0;\\n if (ignoreCache[root][startIdx][ignoreCnt][K] != -1) return ignoreCache[root][startIdx][ignoreCnt][K];\\n long res = 0;\\n // ignore the child at startIdx\\n res += ignoreKids(root, startIdx + 1, ignoreCnt - 1, K);\\n // take the child at startIdx\\n for (int i = 0; i <= K; i++) {\\n res += find(children.get(root).get(startIdx), i) * ignoreKids(root, startIdx + 1, ignoreCnt, K - i);\\n }\\n ignoreCache[root][startIdx][ignoreCnt][K] = res;\\n return res;\\n }\\n\\n}\",\n \"template\": \" /*\\n * Complete the cuttree function below.\\n */\\n static int cuttree(int n, int k, int[][] edges) {\\n /*\\n * Write your code here.\\n */\\n\\n }\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n\",\n \"template_tail\": \" private static final Scanner scanner = new Scanner(System.in);\\n\\n public static void main(String[] args) throws IOException {\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] nk = scanner.nextLine().split(\\\" \\\");\\n\\n int n = Integer.parseInt(nk[0].trim());\\n\\n int k = Integer.parseInt(nk[1].trim());\\n\\n int[][] edges = new int[n-1][2];\\n\\n for (int edgesRowItr = 0; edgesRowItr < n-1; edgesRowItr++) {\\n String[] edgesRowItems = scanner.nextLine().split(\\\" \\\");\\n\\n for (int edgesColumnItr = 0; edgesColumnItr < 2; edgesColumnItr++) {\\n int edgesItem = Integer.parseInt(edgesRowItems[edgesColumnItr].trim());\\n edges[edgesRowItr][edgesColumnItr] = edgesItem;\\n }\\n }\\n\\n int result = cutTree(n, k, edges);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"cuttree(n, k, edges)\"\n ],\n \"solution\": \"line = input().split()\\nn = int(line[0])\\nK = int(line[1])\\n\\nadjlst = [[1]]\\nfor i in range(n):\\n adjlst.append([])\\nadjlst[1].append(0)\\n\\nfor i in range(n - 1):\\n line = input().split()\\n x = int(line[0])\\n y = int(line[1])\\n adjlst[x].append(y)\\n adjlst[y].append(x)\\n\\ndef dfs(node, par, adjlst, K):\\n conlst = [0] * (K + 1)\\n dislst = [0] * (K + 1)\\n conlst[0] = 1\\n for chld in adjlst[node]:\\n if chld != par:\\n tcl, tdl = dfs(chld, node, adjlst, K)\\n # print(str(tcl))\\n # print(str(tdl))\\n dislst[0] += tdl[0]\\n tcl2 = [0] * (K + 1)\\n for i in range(K):\\n dislst[i + 1] += tcl[i] + tdl[i + 1]\\n tcl2[i + 1] += conlst[i]\\n for i in range(K + 1):\\n for j in range(K + 1):\\n if i + j <= K:\\n tcl2[i + j] += tcl[i] * conlst[j]\\n conlst = list(tcl2)\\n return conlst, dislst\\n\\nconlst, dislst = dfs(1, 0, adjlst, K)\\n# print(str(conlst))\\n# print(str(dislst))\\nans = sum(conlst) + sum(dislst) + 1\\nprint(str(ans))\",\n \"template\": \"#\\n# Complete the cuttree function below.\\n#\\ndef cuttree(n, k, edges):\\n #\\n # Write your code here.\\n #\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport os\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n nk = input().split()\\n\\n n = int(nk[0])\\n\\n k = int(nk[1])\\n\\n edges = []\\n\\n for _ in range(n-1):\\n edges.append(list(map(int, input().rstrip().split())))\\n\\n result = cutTree(n, k, edges)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":287,"cells":{"question_id":{"kind":"number","value":29079,"string":"29,079"},"question_title":{"kind":"string","value":"Tara's Beautiful Permutations"},"question_content":{"kind":"string","value":"Tara has an array, $A$, consisting of $n$ integers where each integer occurs *at most* $2$ times in the array. \n\nLet's define $P$ to be a permutation of $A$ where $p_i$ is the $i^{th}$ element of permutation $P$. Tara thinks a permutation is *beautiful* if there is no index $i$ such that $p_i - p_{i+1} = 0$ where $i \\in [0, n-1)$.\n\nYou are given $q$ queries where each query consists of some array $A$. For each $A$, help Tara count the number of possible beautiful permutations of the $n$ integers in $A$ and print the count, modulo $10^9 + 7$, on a new line.\n\n**Note:** Two permutations, $P$ and $Q$, are considered to be *different* if and only if there exists an index $i$ such that $p_i \\neq q_i$ and $i \\in [0, n)$."},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int beautifulPermutations(List<Integer> arr)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n /* Enter your code here. Read input from STDIN. Print output to STDOUT. Your class should be named Solution. */\\n Scanner sc=new Scanner(System.in);\\n int q=sc.nextInt();\\n for(int loop=1;loop!=q+1;loop++){\\n int n=sc.nextInt();\\n int nprime=0;\\n long sum=0;\\n long[] f;\\n int[] a=new int[n];\\n int i,k;\\n for(i=0;i<n;i++)\\n a[i]=sc.nextInt();\\n Arrays.sort(a);\\n for(i=0;i<n-1;i++){\\n if(a[i]==a[i+1])\\n nprime++;\\n }\\n f=new long[nprime+1];\\n f[nprime]=fact(n-nprime);\\n for(k=nprime;k>=1;k--){\\n f[k-1]=(((((f[k])*k)%1000000007)*(n-k+1)%1000000007)*inv(2*(nprime-k+1)))%1000000007;\\n }\\n for(k=0;k<=nprime;k++){\\n if(k%2==0){\\n sum=(sum+f[k])%1000000007;\\n }\\n else{\\n sum=((sum+1000000007)-f[k])%1000000007;\\n }\\n }\\n System.out.println(sum);\\n }\\n }\\n public static long inv(int n){\\n long a=n;\\n return computepow(a,1000000005);\\n }\\n public static long computepow(long a,long n){\\n if(n<1)\\n return 1;\\n long prod=1;\\n if(n%2==0){\\n prod=computepow(a,n/2);\\n return ((prod*prod)%1000000007);\\n }\\n else{\\n prod=computepow(a,n/2);\\n prod=(((prod*prod)%1000000007)*a)%1000000007;\\n return prod;\\n }\\n }\\n public static long fact(int n){\\n if(n<=1)\\n return 1;\\n long prod=1;\\n for(int i=1;i<=n;i++)\\n prod=(prod*i)%1000000007;\\n return prod;\\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'beautifulPermutations' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int beautifulPermutations(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] arrTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> arr = new ArrayList<>();\\n\\n for (int i = 0; i < arrCount; i++) {\\n int arrItem = Integer.parseInt(arrTemp[i]);\\n arr.add(arrItem);\\n }\\n\\n int result = Result.beautifulPermutations(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n /*\\n * Complete the beautifulPermutations function below.\\n */\\n static int beautifulPermutations(int[] arr) {\\n /*\\n * Write your code here.\\n */\\n HashSet<Integer> used = new HashSet<Integer>();\\n int n = arr.length;\\n for(int i = 0; i < n; i++)\\n used.add(arr[i]);\\n int k = n-used.size();\\n long start = (long)1;\\n long[][] dp = new long[n+1][k+1];\\n for(int i = 1; i <= n; i++){\\n start = (i*start)%1000000007;\\n dp[i][0] = start;\\n }\\n for(int i = 1; i < k+1; i++){\\n for(int j = 2*i; j < n+1; j++){\\n long val = dp[j][i-1];\\n if(dp[j][i-1] % 2 == 1)\\n val = dp[j][i-1] + 1000000007;\\n dp[j][i] = (-dp[j-1][i-1] + val/2+1000000007)%1000000007;\\n }\\n }\\n return (int)dp[n][k];\\n }\\n\\n private static final Scanner scanner = new Scanner(System.in);\\n\\n public static void main(String[] args) throws IOException {\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(scanner.nextLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int arrCount = Integer.parseInt(scanner.nextLine().trim());\\n\\n int[] arr = new int[arrCount];\\n\\n String[] arrItems = scanner.nextLine().split(\\\" \\\");\\n\\n for (int arrItr = 0; arrItr < arrCount; arrItr++) {\\n int arrItem = Integer.parseInt(arrItems[arrItr].trim());\\n arr[arrItr] = arrItem;\\n }\\n\\n int result = beautifulPermutations(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedWriter.close();\\n }\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'beautifulPermutations' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int beautifulPermutations(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.beautifulPermutations(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class C {\\n\\tInputStream is;\\n\\tPrintWriter out;\\n\\tString INPUT = \\\"\\\";\\n\\t\\n\\tvoid solve()\\n\\t{\\n\\t\\tfor(int T = ni();T > 0;T--){\\n\\t\\t\\tint n = ni();\\n\\t\\t\\tint[] a = na(n);\\n\\t\\t\\tArrays.sort(a);\\n\\t\\t\\tint[] fs = new int[3];\\n\\t\\t\\tint f = 0;\\n\\t\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\t\\tif(i > 0 && a[i] == a[i-1]){\\n\\t\\t\\t\\t\\tf++;\\n\\t\\t\\t\\t}else{\\n\\t\\t\\t\\t\\tfs[f]++;\\n\\t\\t\\t\\t\\tf = 1;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tfs[f]++;\\n\\t\\t\\tint mod = 1000000007;\\n\\t\\t\\tlong[][] pre = new long[2][fs[2]+1];\\n\\t\\t\\tlong[][] cur = new long[2][fs[2]+1];\\n\\t\\t\\tpre[0][fs[2]] = 1;\\n\\t\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\t\\tfor(int j = 0;j < 2;j++){\\n\\t\\t\\t\\t\\tArrays.fill(cur[j], 0L);\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tfor(int j = 0;j <= fs[2];j++){\\n\\t\\t\\t\\t\\tcur[0][j] += pre[0][j] * (n-i-j*2) + pre[1][j] * (n-i-j*2-1);\\n\\t\\t\\t\\t\\tcur[0][j] %= mod;\\n\\t\\t\\t\\t\\tif(j-1 >= 0){\\n\\t\\t\\t\\t\\t\\tcur[1][j-1] += (pre[0][j] + pre[1][j]) * j;\\n\\t\\t\\t\\t\\t\\tcur[1][j-1] %= mod;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tlong[][] dum = pre; pre = cur; cur = dum;\\n\\t\\t\\t}\\n\\t\\t\\tout.println((pre[0][0]+pre[1][0])%mod);\\n\\t\\t}\\n\\t}\\n\\t\\n\\tvoid run() throws Exception\\n\\t{\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tlong s = System.currentTimeMillis();\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tif(!INPUT.isEmpty())tr(System.currentTimeMillis()-s+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception { new C().run(); }\\n\\t\\n\\tprivate byte[] inbuf = new byte[1024];\\n\\tpublic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate double nd() { return Double.parseDouble(ns()); }\\n\\tprivate char nc() { return (char)skip(); }\\n\\t\\n\\tprivate String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'beautifulPermutations' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int beautifulPermutations(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.beautifulPermutations(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"beautifulPermutations(arr)\"\n ],\n \"solution\": \"# Enter your code here. Read input from STDIN. Print output to STDOUT\\nimport sys\\n\\nmodval=1000000007\\ninvmod=[1,500000004,250000002,125000001,562500004]\\n\\n\\nclass Combination:\\n\\n\\n def __init__(self,size):\\n comb = [ [0 for i in range(j + 2)] for j in range(size + 1) ]\\n comb[0][0] = 1\\n for i in range(1,size):\\n comb[i][0] = 1\\n for j in range(1,i+1 ):\\n comb[i][j] = (comb[i-1][j-1] + comb[i-1][j] ) % modval\\n for i in range(0,size+1): \\n p = comb[i]\\n for j in range(1,i+1 ): comb[i][j] = (comb[i][j] << j) % modval\\n self.comb = comb\\n def NumComb(self ,n,r):\\n try:\\n return self.comb[n][r] \\n except IndexError as e:\\n print(\\\"IndexError NumComb({0},{1})\\\".format(n,r))\\n def clear(self):\\n for i in range(len(self.comb)):\\n del self.comb[0]\\n self.comb = None \\n \\n#_dp = [[-1 for i in range(1002) ] for j in range(2002)]\\n\\ndef getnumofpairs(a):\\n answer = 0\\n numofnum = {}\\n for i in a:\\n numofnum.setdefault(i,0)\\n numofnum[i] += 1\\n onenums=[]\\n twonums=[]\\n kindofpairnum=0\\n for k,v in numofnum.items():\\n if v == 2: kindofpairnum+=1\\n return kindofpairnum\\ndef calcinverse(kindofpairnum):\\n global modval\\n multi = 1\\n a,b = divmod(kindofpairnum,3)\\n for i in range(a):\\n multi = (multi*invmod[3] ) % modval\\n a,b = divmod(b,2)\\n for i in range(a):\\n multi = (multi*invmod[2]) % modval\\n for i in range(b):\\n multi = (multi*invmod[1]) % modval\\n return multi % modval\\ndef getanswer(n,kindofpairnum, dp):\\n global modval\\n return (dp[n][kindofpairnum] * calcinverse(kindofpairnum) ) % modval\\n\\ndef maketable(n,_numpair,arr):\\n dp = [[-1 for i in range( (n>>1) + 2) ] for j in range(n+2)]\\n #\\n # 4 pairs in n\\n # 1 2 3 4 4 5 5 6 6 7 7\\n # fn(n,4) = fn(n,0) -\\n # 4C1 * fn(n-1,3) * 2 [1 2 3 4 4 5 5 6 6 ( 7 7 )][1 2 3 4 4 (5 5) 6 6 7 7 ]\\n # 4C2 * fn(n-2,2) * 4 [1 2 3 4 4 5 5 (6 6) ( 7 7 )][1 2 3 4 4 (5 5) 6 6 ( 7 7 )]\\n # 4C3 * fn(n-3,1) * 8\\n # 4C4 * fn(n-4,0) * 16\\n # ) // 2^4\\n # fb(1,0) = 1 fpairnum+1) ] for j in range(n+1)]\\n\\n val=1\\n \\n dp[0][0] = 1\\n dp[1][0] = 1\\n for i in range(2,n+1) : dp[i][0] = ( dp[i-1][0] * i ) % modval\\n \\n comb = Combination(n)\\n for i,j in arr :\\n ijdiff = i - j\\n for jx in range(1,j+1):\\n idx = ijdiff + jx\\n dpp = dp[idx]\\n if dpp[jx] != -1 : continue\\n \\n tmp = dpp[0]\\n for k in range(1, jx + 1): tmp = tmp - (comb.NumComb(jx,k) * dp[idx-k][jx-k])\\n dpp[jx] = tmp % modval\\n return dp\\ndef read(fnc):\\n q = int(fnc().strip())\\n arrq=[]\\n for i in range(q):\\n l = int(fnc().strip())\\n a = [ int(item) for item in fnc().strip().split()]\\n kindofpairnum=getnumofpairs(a)\\n arrq.append((len(a),kindofpairnum))\\n return arrq\\n\\ndef resolve():\\n if False:\\n with open(\\\"in05.txt\\\",\\\"r\\\") as inputf:\\n arrq = read(inputf.readline)\\n else:\\n arrq = read(input)\\n maxa = -1\\n maxpair = -1\\n for item in arrq :\\n if maxa == -1 or item[0] > maxa : maxa = item[0]\\n if maxpair == -1 or item[1] > maxpair : maxpair = item[1]\\n dp = maketable(maxa, maxpair, arrq)\\n for item in arrq :\\n ans= getanswer(item[0],item[1], dp)\\n print(ans) \\nresolve() \",\n \"template\": \"#\\n# Complete the 'beautifulPermutations' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY arr as parameter.\\n#\\n\\ndef beautifulPermutations(arr):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n arr_count = int(input().strip())\\n\\n arr = list(map(int, input().rstrip().split()))\\n\\n result = beautifulPermutations(arr)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":288,"cells":{"question_id":{"kind":"number","value":5553,"string":"5,553"},"question_title":{"kind":"string","value":"Wet Shark and Two Subsequences"},"question_content":{"kind":"string","value":"One day, Wet Shark was given an array $X = \\{x_1, x_2, \\ldots, x_m\\}$. As always, he started playing with its [subsequences](http://en.wikipedia.org/wiki/Subsequence). \n<br>\nWhen you came to know about this habit, you presented him a task of finding all pairs of subsequences, $(A, B)$, which satisfies all of the following constraints. We will represent a pair of subsequence as $A = \\{x_{a_1}, x_{a_2}, \\ldots, x_{a_n}\\}$ and $B = \\{x_{b_1}, x_{b_2}, \\ldots, x_{b_n}\\}$ \n\n- $A$ and $B$ must be of same length, i.e., $|A| = |B|$.\n- $\\sum\\limits_{i=1}^n (x_{a_i}+ x_{b_i}) = r$\n- $\\sum\\limits_{i=1}^n (x_{a_i} - x_{b_i}) = s$\n\nPlease help Wet Shark determine how many possible subsequences $A$ and $B$ can exist. Because the number of choices may be big, output your answer modulo $10^{9} + 7 = 1000000007$. \n\n*Note:* \n\n- Two segments are different if there's exists at least one index $i$ such that element $x_i$ is present in exactly one of them.\n- Both subsequences can overlap each other.\n- Subsequences do not necessarily have to be distinct\n\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int twoSubsequences(List<Integer> x, int r, int s)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class WSATS {\\n\\tstatic InputStream is;\\n\\tstatic PrintWriter out;\\n\\tstatic String INPUT = \\\"\\\";\\n\\t\\n\\tstatic void solve()\\n\\t{\\n\\t\\tint m = ni(), r = ni(), s = ni();\\n\\t\\tint[] x = na(m);\\n\\t\\tint mod = 1000000007;\\n\\t\\tif((r+s) % 2 != 0 || r-s < 0){\\n\\t\\t\\tout.println(0);\\n\\t\\t\\treturn;\\n\\t\\t}\\n\\t\\tint as = (r+s)/2;\\n\\t\\tint bs = (r-s)/2;\\n\\t\\t\\n\\t\\tint[][] dp = new int[m+1][as+1];\\n\\t\\tdp[0][0] = 1;\\n\\t\\tfor(int i = 0;i < m;i++){\\n\\t\\t\\tfor(int k = m-1;k >= 0;k--){\\n\\t\\t\\t\\tfor(int j = as-x[i];j >= 0;j--){\\n\\t\\t\\t\\t\\tdp[k+1][j+x[i]] += dp[k][j];\\n\\t\\t\\t\\t\\tif(dp[k+1][j+x[i]] >= mod)dp[k+1][j+x[i]] -= mod;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tlong ret = 0;\\n\\t\\tfor(int i = 1;i <= m;i++){\\n\\t\\t\\tret += (long)dp[i][as]*dp[i][bs]%mod;\\n\\t\\t}\\n\\t\\tout.println(ret%mod);\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception\\n\\t{\\n\\t\\tlong S = System.currentTimeMillis();\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tlong G = System.currentTimeMillis();\\n\\t\\ttr(G-S+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tprivate static boolean eof()\\n\\t{\\n\\t\\tif(lenbuf == -1)return true;\\n\\t\\tint lptr = ptrbuf;\\n\\t\\twhile(lptr < lenbuf)if(!isSpaceChar(inbuf[lptr++]))return false;\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tis.mark(1000);\\n\\t\\t\\twhile(true){\\n\\t\\t\\t\\tint b = is.read();\\n\\t\\t\\t\\tif(b == -1){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn true;\\n\\t\\t\\t\\t}else if(!isSpaceChar(b)){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn false;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static byte[] inbuf = new byte[1024];\\n\\tstatic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate static int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate static boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate static int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate static double nd() { return Double.parseDouble(ns()); }\\n\\tprivate static char nc() { return (char)skip(); }\\n\\t\\n\\tprivate static String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate static char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate static char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate static int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate static int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { if(INPUT.length() != 0)System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoSubsequences' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY x\\n * 2. INTEGER r\\n * 3. INTEGER s\\n */\\n\\n public static int twoSubsequences(List<Integer> x, int r, int s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int r = Integer.parseInt(firstMultipleInput[1]);\\n\\n int s = Integer.parseInt(firstMultipleInput[2]);\\n\\n String[] xTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> x = new ArrayList<>();\\n\\n for (int i = 0; i < m; i++) {\\n int xItem = Integer.parseInt(xTemp[i]);\\n x.add(xItem);\\n }\\n\\n int result = Result.twoSubsequences(x, r, s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'twoSubsequences' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY x\\n * 2. INTEGER r\\n * 3. INTEGER s\\n */\\n\\n public static int twoSubsequences(List<Integer> x, int r, int s) {\\n // Write your code here\\n if(r < s) return 0;\\n if((r + s) % 2 != 0) return 0;\\n if((r - s) % 2 != 0) return 0;\\n\\n int l = x.size();\\n int mod = 1000000007;\\n long [][] dp0 = new long[l + 1][2001];\\n for(int i = 0; i < l + 1; i++) Arrays.fill(dp0[i], 0L);\\n dp0[0][0] = 1;\\n long [][] dp1 = new long[l + 1][2001];\\n for(int i = 0; i < l + 1; i++) Arrays.fill(dp1[i], 0L);\\n dp1[0][0] = 1;\\n\\n\\n for(int i = 0; i < l; i++){\\n\\n for (int j = 0; j < 2001; j++) {\\n for (int k = 0; k <= l; k++) {\\n int nxtv = x.get(i) + j;\\n int nxtl = k + 1;\\n if (nxtv < 2001 && nxtl < l + 1) dp1[nxtl][nxtv] = (dp0[nxtl][nxtv] + dp0[k][j]) % mod;\\n }\\n }\\n\\n for(int ii = 0; ii < l + 1; ii++){\\n for(int jj = 0; jj < 2001; jj++){\\n dp0[ii][jj] = dp1[ii][jj];\\n }\\n }\\n }\\n\\n\\n long ans = 0L;\\n for(int i = 1; i < l + 1; i++){\\n ans = (ans + ((long)dp0[i][(r + s) / 2] * (long)dp0[i][(r - s) / 2]) % mod) % mod;\\n }\\n\\n return (int)ans;\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int r = Integer.parseInt(firstMultipleInput[1]);\\n\\n int s = Integer.parseInt(firstMultipleInput[2]);\\n\\n List<Integer> x = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.twoSubsequences(x, r, s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoSubsequences' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY x\\n * 2. INTEGER r\\n * 3. INTEGER s\\n */\\n\\n public static int twoSubsequences(List<Integer> x, int r, int s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int r = Integer.parseInt(firstMultipleInput[1]);\\n\\n int s = Integer.parseInt(firstMultipleInput[2]);\\n\\n List<Integer> x = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.twoSubsequences(x, r, s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.IOException;\\nimport java.io.OutputStreamWriter;\\nimport java.io.BufferedWriter;\\nimport java.util.InputMismatchException;\\nimport java.io.OutputStream;\\nimport java.io.PrintWriter;\\nimport java.util.NoSuchElementException;\\nimport java.io.Writer;\\nimport java.math.BigInteger;\\nimport java.io.InputStream;\\n\\n/**\\n * Built using CHelper plug-in\\n * Actual solution is at the top\\n * @author Stanislav Pak\\n */\\npublic class Main {\\n\\tpublic static void main(String[] args) {\\n\\t\\tInputStream inputStream = System.in;\\n\\t\\tOutputStream outputStream = System.out;\\n\\t\\tInputReader in = new InputReader(inputStream);\\n\\t\\tOutputWriter out = new OutputWriter(outputStream);\\n\\t\\tWetSharkAndTwoSubsequences solver = new WetSharkAndTwoSubsequences();\\n\\t\\tsolver.solve(1, in, out);\\n\\t\\tout.close();\\n\\t}\\n}\\n\\nclass WetSharkAndTwoSubsequences {\\n\\tprivate static final int MOD = 1000000007;\\n public void solve(int testNumber, InputReader in, OutputWriter out) {\\n\\t\\tint n = in.readInt();\\n\\t\\tint r = in.readInt();\\n\\t\\tint s = in.readInt();\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor (int i = 0; i < n; ++i) a[i] = in.readInt();\\n\\t\\tlong[][] count = new long[n + 1][r + 1];\\n\\t\\tcount[0][0] = 1;\\n\\t\\tfor (int x : a) {\\n\\t\\t\\tfor (int k = n - 1; k >= 0; --k) {\\n\\t\\t\\t\\tfor (int j = 0; j <= r; ++j) {\\n\\t\\t\\t\\t\\tif (count[k][j] > 0) {\\n\\t\\t\\t\\t\\t\\tif (j + x <= r) {\\n\\t\\t\\t\\t\\t\\t\\tcount[k + 1][j + x] = (count[k + 1][j + x] + count[k][j]) % MOD;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tint ans = 0;\\n\\t\\tfor (int i = 1; i <= n; ++i) {\\n\\t\\t\\tfor (int x = 0; x <= r; ++x) {\\n\\t\\t\\t\\tif (x - (r - x) == s) {\\n\\t\\t\\t\\t\\tans += count[i][x] * count[i][r - x] % MOD;\\n\\t\\t\\t\\t\\tans %= MOD;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tout.printLine(ans);\\n }\\n}\\n\\nclass InputReader {\\n\\n\\tprivate InputStream stream;\\n\\tprivate byte[] buf = new byte[1024];\\n\\tprivate int curChar;\\n\\tprivate int numChars;\\n\\tprivate SpaceCharFilter filter;\\n\\n\\tpublic InputReader(InputStream stream) {\\n\\t\\tthis.stream = stream;\\n\\t}\\n\\n\\tpublic int read() {\\n\\t\\tif (numChars == -1)\\n\\t\\t\\tthrow new InputMismatchException();\\n\\t\\tif (curChar >= numChars) {\\n\\t\\t\\tcurChar = 0;\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tnumChars = stream.read(buf);\\n\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t}\\n\\t\\t\\tif (numChars <= 0)\\n\\t\\t\\t\\treturn -1;\\n\\t\\t}\\n\\t\\treturn buf[curChar++];\\n\\t}\\n\\n\\tpublic int readInt() {\\n\\t\\tint c = read();\\n\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\tc = read();\\n\\t\\tint sgn = 1;\\n\\t\\tif (c == '-') {\\n\\t\\t\\tsgn = -1;\\n\\t\\t\\tc = read();\\n\\t\\t}\\n\\t\\tint res = 0;\\n\\t\\tdo {\\n\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\tres *= 10;\\n\\t\\t\\tres += c - '0';\\n\\t\\t\\tc = read();\\n\\t\\t} while (!isSpaceChar(c));\\n\\t\\treturn res * sgn;\\n\\t}\\n\\n\\tpublic boolean isSpaceChar(int c) {\\n\\t\\tif (filter != null)\\n\\t\\t\\treturn filter.isSpaceChar(c);\\n\\t\\treturn isWhitespace(c);\\n\\t}\\n\\n\\tpublic static boolean isWhitespace(int c) {\\n\\t\\treturn c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n\\t}\\n\\n\\tpublic interface SpaceCharFilter {\\n\\t\\tpublic boolean isSpaceChar(int ch);\\n\\t}\\n}\\n\\nclass OutputWriter {\\n\\tprivate final PrintWriter writer;\\n\\n\\tpublic OutputWriter(OutputStream outputStream) {\\n\\t\\twriter = new PrintWriter(new BufferedWriter(new OutputStreamWriter(outputStream)));\\n\\t}\\n\\n\\tpublic void close() {\\n\\t\\twriter.close();\\n\\t}\\n\\n\\tpublic void printLine(int i) {\\n\\t\\twriter.println(i);\\n\\t}\\n}\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'twoSubsequences' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER_ARRAY x\\n * 2. INTEGER r\\n * 3. INTEGER s\\n */\\n\\n public static int twoSubsequences(List<Integer> x, int r, int s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int m = Integer.parseInt(firstMultipleInput[0]);\\n\\n int r = Integer.parseInt(firstMultipleInput[1]);\\n\\n int s = Integer.parseInt(firstMultipleInput[2]);\\n\\n List<Integer> x = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.twoSubsequences(x, r, s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"twoSubsequences(x, r, s)\"\n ],\n \"solution\": \"def solve():\\n mod = 10**9+7\\n m,r,s = map(int,input().rstrip().split(' '))\\n if m == 0 or r<=s: return 0\\n arr = list(map(int,input().rstrip().split(' ')))\\n if (r-s) % 2 != 0: return 0\\n sumb = (r-s)//2\\n suma = r - sumb\\n \\n def get_ways(num):\\n dp = [[0]*(num+1) for _ in range(m+1)]\\n dp[0][0] = 1\\n for c in arr:\\n for i in range(len(dp[0])-1,c-1,-1):\\n for j in range(len(dp)-2,-1,-1):\\n if dp[j][i-c]>0:\\n #print(j,i,c)\\n dp[j+1][i]+=dp[j][i-c]\\n #print(dp)\\n for j in range(len(dp)):\\n if dp[j][num] > 0:\\n #print(j,dp[j][num])\\n yield (j,dp[j][num]) #num coins, count\\n \\n a = list(get_ways(suma))\\n #print('---',suma,sumb)\\n b = list(get_ways(sumb))\\n res = 0\\n for i in a:\\n for j in b:\\n if i[0]==j[0]: #same length\\n res += i[1]*j[1]\\n return res % mod \\n \\nprint(solve())\",\n \"template\": \"#\\n# Complete the 'twoSubsequences' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. INTEGER_ARRAY x\\n# 2. INTEGER r\\n# 3. INTEGER s\\n#\\n\\ndef twoSubsequences(x, r, s):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n first_multiple_input = input().rstrip().split()\\n\\n m = int(first_multiple_input[0])\\n\\n r = int(first_multiple_input[1])\\n\\n s = int(first_multiple_input[2])\\n\\n x = list(map(int, input().rstrip().split()))\\n\\n result = twoSubsequences(x, r, s)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":289,"cells":{"question_id":{"kind":"number","value":16423,"string":"16,423"},"question_title":{"kind":"string","value":"Nikita and the Game"},"question_content":{"kind":"string","value":"Nikita just came up with a new array game. The rules are as follows:\n\n* Initially, Nikita has an array of integers.\n\n* In each move, Nikita must partition the array into $2$ non-empty contiguous parts such that the sum of the elements in the left partition is equal to the sum of the elements in the right partition. If Nikita can make such a move, she gets $1$ point; otherwise, the game ends.\n\n* After each successful move, Nikita discards either the left partition or the right partition and continues playing by using the remaining partition as array $arr$.\n\nNikita loves this game and wants your help getting the best score possible. Given $arr$, can you find and print the maximum number of points she can score?\n\nFor example, Nikita starts with the array $arr=[1,2,3,6]$. She first splits it into $a1=[1,2,3]$ and $a2=[6]$, then discards $a2$. $arr=a1 \\rightarrow a1=[1,2], a2=[3]$. Discard $a2$ leaving $arr=[1,2]$. This cannot be further split, so Nikita scored $2$. \n\n**Function Description** \n\nComplete the *arraySplitting* function in the editor below. It should return an integer that reperesents the number of times Nikita can split the array. \n\narraySplitting has the following parameter(s): \n\n- *arr*: an array of integers "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int arraySplitting(List<Integer> arr)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"\\nimport java.util.*;\\nimport java.io.*;\\n\\npublic class B\\n{\\n public static void main(String[] args) throws Exception\\n {\\n FastScanner in = new FastScanner(System.in);\\n PrintWriter out = new PrintWriter(System.out);\\n int T = in.nextInt();\\n while (T-->0) new B(in, out);\\n out.close();\\n }\\n int N;\\n int[] vs;\\n int go(int i, int j)\\n {\\n long sum = 0;\\n for (int x=i; x<=j; x++)\\n sum += vs[x];\\n if (sum % 2 != 0) return 0;\\n sum /= 2;\\n\\n long ss = 0;\\n for (int x=i; x<j; x++)\\n {\\n ss += vs[x];\\n if (ss == sum)\\n return 1 + Math.max(go(i, x), go(x+1, j));\\n }\\n return 0;\\n }\\n\\n public B(FastScanner in, PrintWriter out)\\n {\\n N = in.nextInt();\\n vs = new int[N];\\n for (int i=0; i<N; i++)\\n vs[i] = in.nextInt();\\n\\n long res = go(0, N-1);\\n out.println(res);\\n }\\n}\\n\\nclass FastScanner{\\n private InputStream stream;\\n private byte[] buf = new byte[1024];\\n private int curChar;\\n private int numChars;\\n\\n public FastScanner(InputStream stream)\\n {\\n this.stream = stream;\\n }\\n\\n int read()\\n {\\n if (numChars == -1)\\n throw new InputMismatchException();\\n if (curChar >= numChars){\\n curChar = 0;\\n try{\\n numChars = stream.read(buf);\\n } catch (IOException e) {\\n throw new InputMismatchException();\\n }\\n if (numChars <= 0)\\n return -1;\\n }\\n return buf[curChar++];\\n }\\n\\n boolean isSpaceChar(int c)\\n {\\n return c==' '||c=='\\\\n'||c=='\\\\r'||c=='\\\\t'||c==-1;\\n }\\n \\n boolean isEndline(int c)\\n {\\n return c=='\\\\n'||c=='\\\\r'||c==-1;\\n }\\n\\n int nextInt()\\n {\\n return Integer.parseInt(next());\\n }\\n \\n long nextLong()\\n {\\n return Long.parseLong(next());\\n }\\n\\n double nextDouble()\\n {\\n return Double.parseDouble(next());\\n }\\n\\n String next(){\\n int c = read();\\n while (isSpaceChar(c))\\n c = read();\\n StringBuilder res = new StringBuilder();\\n do{\\n res.appendCodePoint(c);\\n c = read();\\n }while(!isSpaceChar(c));\\n return res.toString();\\n }\\n \\n String nextLine(){\\n int c = read();\\n while (isEndline(c))\\n c = read();\\n StringBuilder res = new StringBuilder();\\n do{\\n res.appendCodePoint(c);\\n c = read();\\n }while(!isEndline(c));\\n return res.toString();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'arraySplitting' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int arraySplitting(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] arrTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> arr = new ArrayList<>();\\n\\n for (int i = 0; i < arrCount; i++) {\\n int arrItem = Integer.parseInt(arrTemp[i]);\\n arr.add(arrItem);\\n }\\n\\n int result = Result.arraySplitting(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.util.*;\\nimport java.io.*;\\n\\npublic class B\\n{\\n public static void main(String[] args) throws Exception\\n {\\n FastScanner in = new FastScanner(System.in);\\n PrintWriter out = new PrintWriter(System.out);\\n int T = in.nextInt();\\n while (T-->0) new B(in, out);\\n out.close();\\n }\\n int N;\\n int[] vs;\\n int go(int i, int j)\\n {\\n long sum = 0;\\n for (int x=i; x<=j; x++)\\n sum += vs[x];\\n if (sum % 2 != 0) return 0;\\n sum /= 2;\\n\\n long ss = 0;\\n for (int x=i; x<j; x++)\\n {\\n ss += vs[x];\\n if (ss == sum)\\n return 1 + Math.max(go(i, x), go(x+1, j));\\n }\\n return 0;\\n }\\n\\n public B(FastScanner in, PrintWriter out)\\n {\\n N = in.nextInt();\\n vs = new int[N];\\n for (int i=0; i<N; i++)\\n vs[i] = in.nextInt();\\n\\n long res = go(0, N-1);\\n out.println(res);\\n }\\n}\\n\\nclass FastScanner{\\n private InputStream stream;\\n private byte[] buf = new byte[1024];\\n private int curChar;\\n private int numChars;\\n\\n public FastScanner(InputStream stream)\\n {\\n this.stream = stream;\\n }\\n\\n int read()\\n {\\n if (numChars == -1)\\n throw new InputMismatchException();\\n if (curChar >= numChars){\\n curChar = 0;\\n try{\\n numChars = stream.read(buf);\\n } catch (IOException e) {\\n throw new InputMismatchException();\\n }\\n if (numChars <= 0)\\n return -1;\\n }\\n return buf[curChar++];\\n }\\n\\n boolean isSpaceChar(int c)\\n {\\n return c==' '||c=='\\\\n'||c=='\\\\r'||c=='\\\\t'||c==-1;\\n }\\n \\n boolean isEndline(int c)\\n {\\n return c=='\\\\n'||c=='\\\\r'||c==-1;\\n }\\n\\n int nextInt()\\n {\\n return Integer.parseInt(next());\\n }\\n \\n long nextLong()\\n {\\n return Long.parseLong(next());\\n }\\n\\n double nextDouble()\\n {\\n return Double.parseDouble(next());\\n }\\n\\n String next(){\\n int c = read();\\n while (isSpaceChar(c))\\n c = read();\\n StringBuilder res = new StringBuilder();\\n do{\\n res.appendCodePoint(c);\\n c = read();\\n }while(!isSpaceChar(c));\\n return res.toString();\\n }\\n \\n String nextLine(){\\n int c = read();\\n while (isEndline(c))\\n c = read();\\n StringBuilder res = new StringBuilder();\\n do{\\n res.appendCodePoint(c);\\n c = read();\\n }while(!isEndline(c));\\n return res.toString();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'arraySplitting' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int arraySplitting(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.arraySplitting(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class AprilFools16QB {\\n\\n\\tstatic int b[];\\n\\tstatic long pre[];\\n\\t\\n\\tpublic static void main(String[] args) {\\n\\t\\tInputReader in = new InputReader(System.in);\\n\\t\\tPrintWriter w = new PrintWriter(System.out);\\n\\n\\t\\tint t = in.nextInt();\\n\\t\\t\\n\\t\\twhile(t-- > 0){\\n\\t\\t\\tint n = in.nextInt();\\n\\t\\t\\tint a[] = in.nextIntArray(n);\\n\\t\\t\\tint z = 0;\\n\\t\\t\\tfor(int x : a)\\n\\t\\t\\t\\tif(x == 0)\\n\\t\\t\\t\\t\\tz++;\\n\\t\\t\\tif(z == n){\\n\\t\\t\\t\\tw.println(n - 1);\\n\\t\\t\\t\\tcontinue;\\n\\t\\t\\t}\\n\\t\\t\\telse{\\n\\t\\t\\t\\tb = new int[n - z + 1];\\n\\t\\t\\t\\tint k = 1;\\n\\t\\t\\t\\tfor(int i = 0; i < n; i++)\\n\\t\\t\\t\\t\\tif(a[i] != 0)\\n\\t\\t\\t\\t\\t\\tb[k++] = a[i];\\n\\t\\t\\t\\tpre = new long[n - z + 1];\\n\\t\\t\\t\\tfor(int i = 1; i < k; i++)\\n\\t\\t\\t\\t\\tpre[i] = pre[i - 1] + b[i];\\n\\t\\t\\t\\tw.println(go(1 , k - 1));\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tw.close();\\n\\t}\\n\\t\\n\\tstatic int go(int l, int r){\\n\\t\\tif(l == r)\\n\\t\\t\\treturn 0;\\n\\t\\tint s = l, e = r + 1;\\n\\t\\tint ans = -1;\\n\\t\\twhile(s < e){\\n\\t\\t\\tint m = (s + e) >> 1;\\n\\t\\t\\tif((pre[m] - pre[l - 1]) * 2 == pre[r] - pre[l - 1]){\\n\\t\\t\\t\\tans = m;\\n\\t\\t\\t\\tbreak;\\n\\t\\t\\t}\\n\\t\\t\\tif((pre[m] - pre[l - 1]) * 2 > pre[r] - pre[l - 1])\\n\\t\\t\\t\\te = m;\\n\\t\\t\\telse\\n\\t\\t\\t\\ts = m + 1;\\n\\t\\t}\\n\\t\\tif(ans == -1)\\n\\t\\t\\treturn 0;\\n\\t\\telse\\n\\t\\t\\treturn 1 + Math.max(go(l , ans), go(ans + 1 , r));\\n\\t}\\n\\t\\n\\tpublic static int gcd(int a,int b){\\n\\t\\twhile(b != 0){ int t = b; b = a%b; a = t;} return a;}\\n\\n\\tpublic static int lcm(int a,int b){\\n\\t\\treturn a*b / gcd(a,b) ;\\n\\t}\\n\\n\\tstatic class InputReader {\\n\\n\\t\\tprivate InputStream stream;\\n\\t\\tprivate byte[] buf = new byte[8192];\\n\\t\\tprivate int curChar, snumChars;\\n\\t\\tprivate SpaceCharFilter filter;\\n\\n\\t\\tpublic InputReader(InputStream stream) {\\n\\t\\t\\tthis.stream = stream;\\n\\t\\t}\\n\\n\\t\\tpublic int snext() {\\n\\t\\t\\tif (snumChars == -1)\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\tif (curChar >= snumChars) {\\n\\t\\t\\t\\tcurChar = 0;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tsnumChars = stream.read(buf);\\n\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (snumChars <= 0)\\n\\t\\t\\t\\t\\treturn -1;\\n\\t\\t\\t}\\n\\t\\t\\treturn buf[curChar++];\\n\\t\\t}\\n\\n\\t\\tpublic int nextInt() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t}\\n\\t\\t\\tint res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic long nextLong() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t}\\n\\t\\t\\tlong res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic int[] nextIntArray(int n) {\\n\\t\\t\\tint a[] = new int[n];\\n\\t\\t\\tfor (int i = 0; i < n; i++)\\n\\t\\t\\t\\ta[i] = nextInt();\\n\\t\\t\\treturn a;\\n\\t\\t}\\n\\n\\t\\tpublic String readString() {\\n\\t\\t\\tint c = snext();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\tStringBuilder res = new StringBuilder();\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tres.appendCodePoint(c);\\n\\t\\t\\t\\tc = snext();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res.toString();\\n\\t\\t}\\n\\n\\t\\tpublic boolean isSpaceChar(int c) {\\n\\t\\t\\tif (filter != null)\\n\\t\\t\\t\\treturn filter.isSpaceChar(c);\\n\\t\\t\\treturn c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n\\t\\t}\\n\\n\\t\\tpublic interface SpaceCharFilter {\\n\\t\\t\\tpublic boolean isSpaceChar(int ch);\\n\\t\\t}\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'arraySplitting' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int arraySplitting(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.arraySplitting(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"arraySplitting(arr)\"\n ],\n \"solution\": \"import math\\n\\ndef solve(a):\\n s = sum(a)\\n if s % 2:\\n return 0\\n s //= 2\\n t = 0\\n for i in range(len(a)):\\n t += a[i]\\n if t == s:\\n #print(sum(a[:i + 1]), sum(a[i + 1:]))\\n return 1 + max(solve(a[:i + 1]), solve(a[i + 1:]))\\n if t > s:\\n return 0\\n \\ndef solve0(n):\\n return n - 1\\n\\nt = int(input().strip())\\nfor test in range(t):\\n n = int(input().strip())\\n a = list(map(int, input().strip().split()))\\n if sum(a) == 0:\\n print(solve0(n))\\n else:\\n print(solve(a))\",\n \"template\": \"#\\n# Complete the 'arraySplitting' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY arr as parameter.\\n#\\n\\ndef arraySplitting(arr):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n arr_count = int(input().strip())\\n\\n arr = list(map(int, input().rstrip().split()))\\n\\n result = arraySplitting(arr)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":290,"cells":{"question_id":{"kind":"number","value":20053,"string":"20,053"},"question_title":{"kind":"string","value":"LCS Returns"},"question_content":{"kind":"string","value":"Given two strings, $a$ and $b$, find and print the total number of ways to insert a character at any position in string $a$ such that the length of the [Longest Common Subsequence](https://en.wikipedia.org/wiki/Longest_common_subsequence_problem?oldformat=true) of characters in the two strings increases by one."},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int tutzkiAndLcs(String a, String b)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.awt.image.ReplicateScaleFilter;\\nimport java.io.*;\\nimport java.math.*;\\nimport java.util.*;\\n\\nimport javax.swing.RepaintManager;\\n\\npublic class Main {\\n\\n\\tstatic long mod = (long) 1e18 + 3;\\n\\n\\tstatic ArrayList<Integer> x = new ArrayList<>();\\n\\tstatic ArrayList<Integer> y = new ArrayList<>();\\n\\tstatic HashMap<Long, String> hashMap = new HashMap<>();\\n\\n\\tpublic static void main(String[] args) {\\n\\t\\tFasterScanner s = new FasterScanner();\\n\\t\\tPrintWriter out = new PrintWriter(System.out);\\n\\n\\t\\tint test = 1;\\n\\t\\ttestloop: while (test-- > 0) {\\n\\t\\t\\tchar[] a = (\\\" \\\" + s.nextLine() + \\\" \\\").toCharArray();\\n\\t\\t\\tchar[] b = (\\\" \\\" + s.nextLine() + \\\" \\\").toCharArray();\\n\\t\\t\\tint n = a.length;\\n\\t\\t\\tint m = b.length;\\n\\t\\t\\tint pre[][] = new int[n][m];\\n\\t\\t\\tint suf[][] = new int[n][m];\\n\\t\\t\\tfor (int i = 1; i < n; i++) {\\n\\t\\t\\t\\tfor (int j = 1; j < m; j++) {\\n\\t\\t\\t\\t\\tif (a[i] == b[j])\\n\\t\\t\\t\\t\\t\\tpre[i][j] = 1 + pre[i - 1][j - 1];\\n\\t\\t\\t\\t\\tpre[i][j] = Math.max(pre[i][j], Math.max(pre[i - 1][j], pre[i][j - 1]));\\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tfor (int i = n - 2; i >= 0; i--) {\\n\\t\\t\\t\\tfor (int j = m - 2; j >= 0; j--) {\\n\\t\\t\\t\\t\\tif (a[i] == b[j])\\n\\t\\t\\t\\t\\t\\tsuf[i][j] = 1 + suf[i + 1][j + 1];\\n\\t\\t\\t\\t\\tsuf[i][j] = Math.max(suf[i][j], Math.max(suf[i + 1][j], suf[i][j + 1]));\\n\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tint total = suf[0][0] - 1;\\n\\t\\t\\t// System.out.println(pre[n - 1][m - 1] + \\\" \\\"+ suf[0][0]);\\n\\t\\t\\t// System.out.println(Arrays.deepToString(pre));\\n\\t\\t\\t// System.out.println(Arrays.deepToString(suf));\\n\\t\\t\\tint count = 0;\\n\\t\\t\\tfor (int i = 1; i < n; i++) {\\n\\t\\t\\t\\tboolean[] done = new boolean[256];\\n\\t\\t\\t\\tfor (int j = 1; j < m - 1; j++) {\\n\\t\\t\\t\\t\\t// System.out.println(i + \\\" \\\" + j + \\\" \\\" + pre[i - 1][j - 1]\\n\\t\\t\\t\\t\\t// + \\\" \\\" + suf[i][j + 1]);\\n\\t\\t\\t\\t\\tif (pre[i - 1][j - 1] + suf[i][j + 1] == total) {\\n\\t\\t\\t\\t\\t\\tif (!done[b[j]]) {\\n\\t\\t\\t\\t\\t\\t\\tcount++;\\n\\t\\t\\t\\t\\t\\t\\tdone[b[j]] = true;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tSystem.out.println(count);\\n\\n\\t\\t}\\n\\n\\t\\tout.close();\\n\\t}\\n\\n\\tpublic static long hash(String str) {\\n\\t\\tint count[] = new int[26];\\n\\t\\tfor (int i = 0; i < str.length(); i++) {\\n\\t\\t\\tcount[str.charAt(i) - 'a']++;\\n\\t\\t}\\n\\t\\tlong hash = 0;\\n\\t\\tlong prime = 31;\\n\\t\\tlong pow = 1;\\n\\n\\t\\tfor (int i = 0; i < 26; i++) {\\n\\t\\t\\thash += (count[i] * pow) % mod;\\n\\t\\t\\tif (hash > mod)\\n\\t\\t\\t\\thash -= mod;\\n\\t\\t\\tpow *= prime;\\n\\t\\t}\\n\\t\\treturn hash;\\n\\t}\\n\\n\\tpublic static long hash(int[] count) {\\n\\t\\tlong hash = 0;\\n\\t\\tlong prime = 31;\\n\\t\\tlong pow = 1;\\n\\n\\t\\tfor (int i = 0; i < 26; i++) {\\n\\t\\t\\thash += (count[i] * pow) % mod;\\n\\t\\t\\tif (hash > mod)\\n\\t\\t\\t\\thash -= mod;\\n\\t\\t\\tpow *= prime;\\n\\t\\t}\\n\\t\\treturn hash;\\n\\t}\\n\\n\\tpublic static long pow(long x, long n, long mod) {\\n\\t\\tlong res = 1;\\n\\t\\tfor (long p = x; n > 0; n >>= 1, p = (p * p) % mod) {\\n\\t\\t\\tif ((n & 1) != 0) {\\n\\t\\t\\t\\tres = (res * p % mod);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn res;\\n\\t}\\n\\n\\tstatic long gcd(long n1, long n2) {\\n\\t\\tlong r;\\n\\t\\twhile (n2 != 0) {\\n\\t\\t\\tr = n1 % n2;\\n\\t\\t\\tn1 = n2;\\n\\t\\t\\tn2 = r;\\n\\t\\t}\\n\\t\\treturn n1;\\n\\t}\\n\\n\\tstatic class FasterScanner {\\n\\t\\tprivate byte[] buf = new byte[1024];\\n\\t\\tprivate int curChar;\\n\\t\\tprivate int snumChars;\\n\\n\\t\\tpublic int read() {\\n\\t\\t\\tif (snumChars == -1)\\n\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\tif (curChar >= snumChars) {\\n\\t\\t\\t\\tcurChar = 0;\\n\\t\\t\\t\\ttry {\\n\\t\\t\\t\\t\\tsnumChars = System.in.read(buf);\\n\\t\\t\\t\\t} catch (IOException e) {\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (snumChars <= 0)\\n\\t\\t\\t\\t\\treturn -1;\\n\\t\\t\\t}\\n\\t\\t\\treturn buf[curChar++];\\n\\t\\t}\\n\\n\\t\\tpublic String nextLine() {\\n\\t\\t\\tint c = read();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\tStringBuilder res = new StringBuilder();\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tres.appendCodePoint(c);\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t} while (!isEndOfLine(c));\\n\\t\\t\\treturn res.toString();\\n\\t\\t}\\n\\n\\t\\tpublic String nextString() {\\n\\t\\t\\tint c = read();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\tStringBuilder res = new StringBuilder();\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tres.appendCodePoint(c);\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res.toString();\\n\\t\\t}\\n\\n\\t\\tpublic long nextLong() {\\n\\t\\t\\tint c = read();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t}\\n\\t\\t\\tlong res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic int nextInt() {\\n\\t\\t\\tint c = read();\\n\\t\\t\\twhile (isSpaceChar(c))\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\tint sgn = 1;\\n\\t\\t\\tif (c == '-') {\\n\\t\\t\\t\\tsgn = -1;\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t}\\n\\t\\t\\tint res = 0;\\n\\t\\t\\tdo {\\n\\t\\t\\t\\tif (c < '0' || c > '9')\\n\\t\\t\\t\\t\\tthrow new InputMismatchException();\\n\\t\\t\\t\\tres *= 10;\\n\\t\\t\\t\\tres += c - '0';\\n\\t\\t\\t\\tc = read();\\n\\t\\t\\t} while (!isSpaceChar(c));\\n\\t\\t\\treturn res * sgn;\\n\\t\\t}\\n\\n\\t\\tpublic int[] nextIntArray(int n) {\\n\\t\\t\\tint[] arr = new int[n];\\n\\t\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\t\\tarr[i] = nextInt();\\n\\t\\t\\t}\\n\\t\\t\\treturn arr;\\n\\t\\t}\\n\\n\\t\\tpublic long[] nextLongArray(int n) {\\n\\t\\t\\tlong[] arr = new long[n];\\n\\t\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\t\\tarr[i] = nextLong();\\n\\t\\t\\t}\\n\\t\\t\\treturn arr;\\n\\t\\t}\\n\\n\\t\\tprivate boolean isSpaceChar(int c) {\\n\\t\\t\\treturn c == ' ' || c == '\\\\n' || c == '\\\\r' || c == '\\\\t' || c == -1;\\n\\t\\t}\\n\\n\\t\\tprivate boolean isEndOfLine(int c) {\\n\\t\\t\\treturn c == '\\\\n' || c == '\\\\r' || c == -1;\\n\\t\\t}\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'tutzkiAndLcs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. STRING a\\n * 2. STRING b\\n */\\n\\n public static int tutzkiAndLcs(String a, String b) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String a = bufferedReader.readLine();\\n\\n String b = bufferedReader.readLine();\\n\\n int result = Result.tutzkiAndLcs(a, b);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n char[] a = in.next().toCharArray();\\n char[] b = in.next().toCharArray();\\n int n = a.length;\\n int m = b.length;\\n int[][] dp = new int[n+2][m+2];\\n int[][] dp2 = new int[n+2][m+2];\\n for (int i=1; i<=n; i++) {\\n for (int j=1; j<=m; j++) {\\n if (a[i-1] == b[j-1]) {\\n dp[i][j] = dp[i-1][j-1] + 1;\\n } else {\\n dp[i][j] = Math.max(dp[i][j-1], dp[i-1][j]);\\n }\\n }\\n }\\n int r = dp[n][m], ans = 0;\\n \\n for (int i=n; i>=1; i--) {\\n for (int j=m; j>=1; j--) {\\n if (a[i-1] == b[j-1]) {\\n dp2[i][j] = dp2[i+1][j+1] + 1;\\n } else {\\n dp2[i][j] = Math.max(dp2[i][j+1], dp2[i+1][j]);\\n }\\n }\\n }\\n \\n for (int i=0; i<=n; i++) {\\n Set<Character> set = new HashSet<>();\\n for (int j=1; j<=m; j++) if (!set.contains(b[j-1])) {\\n int v = dp[i][j-1] + dp2[i+1][j+1];\\n //System.out.print(v+\\\" \\\");\\n if (v == r) {\\n ans++;\\n set.add(b[j-1]);\\n }\\n }\\n // System.out.println();\\n }\\n \\n System.out.println(ans);\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'tutzkiAndLcs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. STRING a\\n * 2. STRING b\\n */\\n\\n public static int tutzkiAndLcs(String a, String b) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String a = bufferedReader.readLine();\\n\\n String b = bufferedReader.readLine();\\n\\n int result = Result.tutzkiAndLcs(a, b);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class LCSReturns {\\n\\n\\tBufferedReader br;\\n\\tPrintWriter out;\\n\\tStringTokenizer st;\\n\\tboolean eof;\\n\\n\\tvoid solve() throws IOException {\\n\\t\\tString a = nextToken();\\n\\t\\tString b = nextToken();\\n\\n\\t\\tint n = a.length();\\n\\t\\tint m = b.length();\\n\\n\\t\\tint[][] pref = new int[n + 1][m + 1];\\n\\t\\tint[][] suff = new int[n + 1][m + 1];\\n\\n\\t\\tfor (int i = 0; i < n; i++)\\n\\t\\t\\tfor (int j = 0; j < m; j++) {\\n\\t\\t\\t\\tif (a.charAt(i) == b.charAt(j)) {\\n\\t\\t\\t\\t\\tpref[i + 1][j + 1] = pref[i][j] + 1;\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tpref[i + 1][j + 1] = Math.max(pref[i + 1][j],\\n\\t\\t\\t\\t\\t\\t\\tpref[i][j + 1]);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\n\\t\\tfor (int i = n - 1; i >= 0; i--)\\n\\t\\t\\tfor (int j = m - 1; j >= 0; j--) {\\n\\t\\t\\t\\tif (a.charAt(i) == b.charAt(j)) {\\n\\t\\t\\t\\t\\tsuff[i][j] = suff[i + 1][j + 1] + 1;\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tsuff[i][j] = Math.max(suff[i][j + 1], suff[i + 1][j]);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\n\\t\\tint cur = pref[n][m];\\n\\t\\t\\n\\t\\tint ret = 0;\\n\\n\\t\\tfor (int i = 0; i <= n; i++) {\\n\\t\\t\\tboolean[] used = new boolean[256];\\n\\t\\t\\tfor (int j = 0; j < m; j++) {\\n\\t\\t\\t\\tif (used[b.charAt(j)]) {\\n\\t\\t\\t\\t\\tcontinue;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tint now = pref[i][j] + suff[i][j + 1] + 1;\\n\\t\\t\\t\\tif (now == cur + 1) {\\n\\t\\t\\t\\t\\tused[b.charAt(j)] = true;\\n\\t\\t\\t\\t\\tret++;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tout.println(ret);\\n\\t}\\n\\n\\tLCSReturns() throws IOException {\\n\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\tsolve();\\n\\t\\tout.close();\\n\\t}\\n\\n\\tpublic static void main(String[] args) throws IOException {\\n\\t\\tnew LCSReturns();\\n\\t}\\n\\n\\tString nextToken() {\\n\\t\\twhile (st == null || !st.hasMoreTokens()) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tst = new StringTokenizer(br.readLine());\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\teof = true;\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn st.nextToken();\\n\\t}\\n\\n\\tString nextString() {\\n\\t\\ttry {\\n\\t\\t\\treturn br.readLine();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\teof = true;\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t}\\n\\n\\tint nextInt() throws IOException {\\n\\t\\treturn Integer.parseInt(nextToken());\\n\\t}\\n\\n\\tlong nextLong() throws IOException {\\n\\t\\treturn Long.parseLong(nextToken());\\n\\t}\\n\\n\\tdouble nextDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(nextToken());\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'tutzkiAndLcs' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. STRING a\\n * 2. STRING b\\n */\\n\\n public static int tutzkiAndLcs(String a, String b) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String a = bufferedReader.readLine();\\n\\n String b = bufferedReader.readLine();\\n\\n int result = Result.tutzkiAndLcs(a, b);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"tutzkiAndLcs(a, b)\"\n ],\n \"solution\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n#\\n# Complete the 'tutzkiAndLcs' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. STRING a\\n# 2. STRING b\\n#\\n\\ndef tutzkiAndLcs(a, b):\\n # Write your code here\\n s1 = a\\n s2 = b\\n l1, l2 = len(s1), len(s2)\\n d1 = [[0] * (l2 + 1) for _ in range(l1 + 1)]\\n d2 = [[0] * (l2 + 1) for _ in range(l1 + 1)]\\n cc = [0] * 256\\n ret = 0\\n \\n for i in range(1, l1 + 1):\\n for j in range(1, l2 + 1):\\n d1[i][j] = max(d1[i - 1][j], d1[i][j - 1])\\n if s1[i - 1] == s2[j - 1]:\\n d1[i][j] = d1[i - 1][j - 1] + 1\\n \\n for i in range(l1 - 1, -1, -1):\\n for j in range(l2 - 1, -1, -1):\\n d2[i][j] = max(d2[i + 1][j], d2[i][j + 1])\\n if s1[i] == s2[j]:\\n d2[i][j] = d2[i + 1][j + 1] + 1\\n \\n for i in range(l1 + 1):\\n for j in range(l2):\\n if d1[i][j] + d2[i][j + 1] == d1[l1][l2]:\\n cc[ord(s2[j])] = 1\\n ret += sum(cc)\\n cc = [0] * 256\\n \\n return ret\\n\\n\\nif __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n a = input()\\n\\n b = input()\\n\\n result = tutzkiAndLcs(a, b)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\",\n \"template\": \"#\\n# Complete the 'tutzkiAndLcs' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. STRING a\\n# 2. STRING b\\n#\\n\\ndef tutzkiAndLcs(a, b):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n a = input()\\n\\n b = input()\\n\\n result = tutzkiAndLcs(a, b)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":291,"cells":{"question_id":{"kind":"number","value":33054,"string":"33,054"},"question_title":{"kind":"string","value":"Matrix Land"},"question_content":{"kind":"string","value":"You are playing a matrix-based game with the following setup and rules: \n\n- You are given a matrix $A$ with $n$ rows and $m$ columns. Each cell contains some points. When a player passes a cell their score increases by the number written in that cell and the number in the cell becomes $0$. (If the cell number is positive their score increases, otherwise it decreases.)\n- The player starts from any cell in the _first_ row and can move _left_, _right_ or _down_. \n- The game is over when the player reaches the _last_ row and stops moving. \n\n\n \n\nPrint the maximum score that the player can get. "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int matrixLand(List<List<Integer>> A)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int n = in.nextInt();\\n int m = in.nextInt();\\n int[] a = new int[m];\\n long[] left = new long[m];\\n long[] right = new long[m];\\n long[] prev = new long[m];\\n long[] current = new long[m];\\n long[] leftplus = new long[m];\\n long[] rightplus = new long[m];\\n \\n for(int A_i = 0; A_i < n; A_i++){\\n for(int A_j = 0; A_j < m; A_j++){\\n a[A_j] = in.nextInt();\\n }\\n \\n for (int i = 1; i < m; i++)\\n {\\n left[i] = Math.max(left[i - 1] + a[i - 1], 0);\\n }\\n \\n for (int i = m - 2; i >= 0; i--)\\n {\\n right[i] = Math.max(right[i + 1] + a[i + 1], 0);\\n }\\n \\n leftplus[0] = prev[0] + a[0];\\n \\n for (int i = 1; i < m; i++)\\n {\\n leftplus[i] = Math.max(prev[i] + a[i] + left[i], leftplus[i - 1] + a[i]);\\n }\\n \\n rightplus[m - 1] = prev[m - 1] + a[m - 1];\\n \\n for (int i = m - 2; i >= 0; i--)\\n {\\n rightplus[i] = Math.max(prev[i] + a[i] + right[i], rightplus[i + 1] + a[i]);\\n }\\n \\n for (int i = 0; i < m; i++)\\n {\\n current[i] = Math.max(leftplus[i] + right[i], rightplus[i] + left[i]);\\n }\\n \\n long[] temp = current;\\n current = prev;\\n prev = temp;\\n }\\n \\n long result = Long.MIN_VALUE;\\n \\n for (int i = 0; i < m; i++)\\n {\\n result = Math.max(prev[i], result);\\n }\\n \\n System.out.println(result);\\n in.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'matrixLand' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY A as parameter.\\n */\\n\\n public static int matrixLand(List<List<Integer>> A) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> A = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String[] ARowTempItems = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> ARowItems = new ArrayList<>();\\n\\n for (int j = 0; j < m; j++) {\\n int AItem = Integer.parseInt(ARowTempItems[j]);\\n ARowItems.add(AItem);\\n }\\n\\n A.add(ARowItems);\\n }\\n\\n int result = Result.matrixLand(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\npublic class Solution {\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int n = in.nextInt();\\n int m = in.nextInt();\\n int[] a = new int[m];\\n long[] left = new long[m];\\n long[] right = new long[m];\\n long[] prev = new long[m];\\n long[] current = new long[m];\\n long[] leftplus = new long[m];\\n long[] rightplus = new long[m];\\n \\n for(int A_i = 0; A_i < n; A_i++){\\n for(int A_j = 0; A_j < m; A_j++){\\n a[A_j] = in.nextInt();\\n }\\n \\n for (int i = 1; i < m; i++)\\n {\\n left[i] = Math.max(left[i - 1] + a[i - 1], 0);\\n }\\n \\n for (int i = m - 2; i >= 0; i--)\\n {\\n right[i] = Math.max(right[i + 1] + a[i + 1], 0);\\n }\\n \\n leftplus[0] = prev[0] + a[0];\\n \\n for (int i = 1; i < m; i++)\\n {\\n leftplus[i] = Math.max(prev[i] + a[i] + left[i], leftplus[i - 1] + a[i]);\\n }\\n \\n rightplus[m - 1] = prev[m - 1] + a[m - 1];\\n \\n for (int i = m - 2; i >= 0; i--)\\n {\\n rightplus[i] = Math.max(prev[i] + a[i] + right[i], rightplus[i + 1] + a[i]);\\n }\\n \\n for (int i = 0; i < m; i++)\\n {\\n current[i] = Math.max(leftplus[i] + right[i], rightplus[i] + left[i]);\\n }\\n \\n long[] temp = current;\\n current = prev;\\n prev = temp;\\n }\\n \\n long result = Long.MIN_VALUE;\\n \\n for (int i = 0; i < m; i++)\\n {\\n result = Math.max(prev[i], result);\\n }\\n \\n System.out.println(result);\\n in.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'matrixLand' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY A as parameter.\\n */\\n\\n public static int matrixLand(List<List<Integer>> A) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> A = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n A.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.matrixLand(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.util.function.Consumer;\\n\\npublic class Solution {\\n\\n\\n static MyScanner sc;\\n private static PrintWriter out;\\n static long M2 = 1_000_000_000L + 7;\\n\\n public static void main(String[] s) throws Exception {\\n StringBuilder stringBuilder = new StringBuilder();\\n//\\n// stringBuilder.append(\\\"4 5\\\\n\\\" +\\n// \\\"1 2 3 -1 -2\\\\n\\\" +\\n// \\\"-5 -8 -1 2 -150\\\\n\\\" +\\n// \\\"1 2 3 -250 100\\\\n\\\" +\\n// \\\"1 1 1 1 20\\\");\\n\\n\\n if (stringBuilder.length() == 0) {\\n sc = new MyScanner(System.in);\\n } else {\\n sc = new MyScanner(new BufferedReader(new StringReader(stringBuilder.toString())));\\n }\\n\\n out = new PrintWriter(new OutputStreamWriter(System.out));\\n\\n initData();\\n solve();\\n out.flush();\\n }\\n\\n private static void initData() {\\n }\\n\\n\\n private static void solve() throws IOException {\\n int n = sc.nextInt();\\n int m = sc.nextInt();\\n\\n pref = new int[m];\\n suf = new int[m];\\n\\n int[] m0 = sc.na(m);\\n int[] pref = pref(m0);\\n int[] suf = sf(m0);\\n int[] res = new int[m];\\n for (int i = 0; i < m; i++) {\\n\\n res[i] = m0[i] + pref[i] + suf[i];\\n }\\n for (int i = 1; i < n; i++) {\\n res = rm(sc.na(m), res);\\n }\\n out.println(Arrays.stream(res).max().getAsInt());\\n }\\n\\n static int[] pref;\\n static int[] suf;\\n\\n private static int[] pref(int[] data) {\\n\\n for (int k = 1; k < data.length; k++) {\\n pref[k] = Math.max(pref[k - 1] + data[k - 1], 0);\\n }\\n return pref;\\n }\\n\\n private static int[] sf(int[] data) {\\n for (int k = data.length - 2; k >= 0; k--) {\\n suf[k] = Math.max(suf[k + 1] + data[k + 1], 0);\\n }\\n return suf;\\n }\\n\\n private static int[] rm(int[] data, int[] par) {\\n int[] rr = new int[data.length];\\n int[] sf = sf(data);\\n int[] pf = pref(data);\\n\\n int[] pref = new int[data.length];\\n int[] suf = new int[data.length];\\n\\n for (int i = 1; i < data.length; i++) {\\n pref[i] = pf[i - 1] + data[i - 1] + par[i - 1];\\n if (i != 1) {\\n pref[i] = Math.max(pref[i - 1] + data[i - 1], pref[i]);\\n }\\n }\\n\\n for (int i = data.length - 2; i >= 0; i--) {\\n suf[i] = sf[i + 1] + data[i + 1] + par[i + 1];\\n if (i != data.length - 2) {\\n suf[i] = Math.max(suf[i + 1] + data[i + 1], suf[i]);\\n }\\n\\n }\\n\\n// out.println(\\\"-------------------------\\\");\\n//\\n// out.println(Arrays.toString(sf));\\n// out.println(Arrays.toString(pf));\\n// out.println(Arrays.toString(suf));\\n// out.println(Arrays.toString(pref));\\n// out.println(\\\"-------------------------\\\");\\n for (int i = 0; i < data.length; i++) {\\n rr[i] = data[i] + par[i] + sf[i] + pf[i];\\n if (i > 0)\\n rr[i] = Math.max(rr[i], pref[i] + data[i] + sf[i]);\\n if (i < data.length - 1)\\n rr[i] = Math.max(rr[i], suf[i] + data[i] + pf[i]);\\n }\\n return rr;\\n }\\n\\n private static final class LogTreePar {\\n\\n private final int[] levels;\\n private final int[][] parents;\\n\\n public LogTreePar(int n) {\\n levels = new int[n];\\n parents = new int[n][19];\\n Arrays.fill(levels, -1);\\n for (int[] x : parents) {\\n Arrays.fill(x, -1);\\n }\\n }\\n\\n public boolean ispar(int f, int l) {\\n if (levels[f] >= levels[l]) return false;\\n int diff = levels[l] - levels[f];\\n return up(l, diff) == f;\\n }\\n\\n private int up(int item, int diff) {\\n int r = 0;\\n while (diff > 0 && item >= 0) {\\n if (isset(diff, r)) {\\n diff ^= 1 << r;\\n item = parents[item][r];\\n }\\n r++;\\n }\\n return item;\\n }\\n\\n\\n public void add(int item, int parent) {\\n parents[item][0] = parent;\\n clt(item);\\n }\\n\\n\\n protected void clt(int item) {\\n levels[item] = levels[parents[item][0]] + 1;\\n for (int l = 1; l < 19; l++) {\\n if (parents[item][l - 1] == -1) break;\\n parents[item][l] = parents[parents[item][l - 1]][l - 1];\\n }\\n }\\n\\n public int lca(int f, int l) {\\n if (levels[f] > levels[l]) {\\n return lca(l, f);\\n }\\n return lca1(f, up(l, levels[l] - levels[f]));\\n }\\n\\n private int lca1(int f1, int f2) {\\n for (int r = 18; r >= 0 && f1 != f2; r--) {\\n if (parents[f1][r] != parents[f2][r]) {\\n f1 = parents[f1][r];\\n f2 = parents[f2][r];\\n }\\n }\\n return f1 == f2 ? f1 : parents[f1][0];\\n }\\n }\\n\\n\\n private static class P {\\n private boolean b;\\n private final int ind;\\n private final int parent;\\n\\n public P(int i, boolean b, int par) {\\n this.ind = i;\\n this.b = b;\\n this.parent = par;\\n\\n }\\n }\\n\\n private static void dfs(int start, int[][] neig, Consumer<int[]> onAdd, Consumer<int[]> onRemove) {\\n ArrayList<P> toVisit = new ArrayList<P>(3000);\\n toVisit.add(new P(start, true, -1));\\n boolean[] vis = new boolean[neig.length];\\n vis[start] = true;\\n int[] level = new int[neig.length];\\n while (toVisit.size() > 0) {\\n P ppr = toVisit.remove(toVisit.size() - 1);\\n if (!ppr.b) {\\n onRemove.accept(new int[]{ppr.ind, level[ppr.ind], ppr.parent});\\n continue;\\n }\\n ppr.b = false;\\n int i = ppr.ind;\\n toVisit.add(ppr);\\n onAdd.accept(new int[]{ppr.ind, level[ppr.ind], ppr.parent});\\n for (int kk : neig[i]) {\\n if (!vis[kk]) {\\n vis[kk] = true;\\n level[kk] = level[i] + 1;\\n toVisit.add(new P(kk, true, i));\\n }\\n }\\n }\\n\\n\\n }\\n\\n\\n private static int[][] tr(int n) {\\n int[][] x = new int[2][n - 1];\\n for (int i = 0; i < n - 1; i++) {\\n x[0][i] = sc.nextInt() - 1;\\n x[1][i] = sc.nextInt() - 1;\\n }\\n return pn(x, n);\\n }\\n\\n private static int[][] pn(int[][] x, int n) {\\n int[] ct = new int[n];\\n int[][] res = new int[n][];\\n for (int v : x[0]) {\\n ct[v]++;\\n }\\n for (int v : x[1]) {\\n ct[v]++;\\n }\\n for (int l = 0; l < n; l++) {\\n res[l] = new int[ct[l]];\\n }\\n for (int i = 0; i < x[0].length; i++) {\\n res[x[0][i]][--ct[x[0][i]]] = x[1][i];\\n res[x[1][i]][--ct[x[1][i]]] = x[0][i];\\n }\\n return res;\\n }\\n\\n\\n private static boolean isset(long i, int k) {\\n return (i & (1 << k)) > 0;\\n }\\n\\n private static void solveT() throws IOException {\\n int t = sc.nextInt();\\n while (t-- > 0) {\\n solve();\\n }\\n }\\n\\n\\n private static long gcd(long l, long l1) {\\n if (l > l1) return gcd(l1, l);\\n if (l == 0) return l1;\\n return gcd(l1 % l, l);\\n }\\n\\n private static long pow(long a, long b, long m) {\\n if (b == 0) return 1;\\n if (b == 1) return a;\\n long pp = pow(a, b / 2, m);\\n pp *= pp;\\n pp %= m;\\n return (pp * (b % 2 == 0 ? 1 : a)) % m;\\n }\\n\\n\\n static class MyScanner {\\n BufferedReader br;\\n StringTokenizer st;\\n\\n MyScanner(BufferedReader br) {\\n this.br = br;\\n }\\n\\n public MyScanner(InputStream in) {\\n this(new BufferedReader(new InputStreamReader(in)));\\n }\\n\\n void findToken() {\\n while (st == null || !st.hasMoreTokens()) {\\n try {\\n st = new StringTokenizer(br.readLine());\\n } catch (IOException e) {\\n throw new RuntimeException(e);\\n }\\n }\\n }\\n\\n String next() {\\n findToken();\\n return st.nextToken();\\n }\\n\\n Integer[] nab(int n) {\\n Integer[] k = new Integer[n];\\n for (int i = 0; i < n; i++) {\\n k[i] = sc.fi();\\n }\\n return k;\\n }\\n\\n int[] na(int n) {\\n int[] k = new int[n];\\n for (int i = 0; i < n; i++) {\\n k[i] = sc.fi();\\n }\\n return k;\\n }\\n\\n long[] nl(int n) {\\n long[] k = new long[n];\\n for (int i = 0; i < n; i++) {\\n k[i] = sc.nextLong();\\n }\\n return k;\\n }\\n\\n int nextInt() {\\n return Integer.parseInt(next());\\n }\\n\\n int fi() {\\n String t = next();\\n int cur = 0;\\n boolean n = t.charAt(0) == '-';\\n for (int a = n ? 1 : 0; a < t.length(); a++) {\\n cur = cur * 10 + t.charAt(a) - '0';\\n }\\n return n ? -cur : cur;\\n }\\n\\n long nextLong() {\\n return Long.parseLong(next());\\n }\\n\\n double nextDouble() {\\n return Double.parseDouble(next());\\n }\\n }\\n\\n\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'matrixLand' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY A as parameter.\\n */\\n\\n public static int matrixLand(List<List<Integer>> A) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<List<Integer>> A = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n A.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.matrixLand(A);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"matrixLand(A)\"\n ],\n \"solution\": \"import os, sys\\n\\nwith open('progIn.txt', 'w') as file:\\n for line in sys.stdin:\\n file.write(line)\\n\\nprog = r\\\"\\\"\\\"\\n#include <iostream>\\n#include <algorithm>\\n#include <cmath>\\n#include <vector>\\n#include <set>\\n#include <utility>\\n\\nusing namespace std;\\n\\nint main() {\\n\\tint m, n;\\n\\tscanf(\\\"%d %d\\\", &n, &m);\\n\\t\\n\\tvector<vector<int>> a(n, vector<int>(m));\\n\\tfor ( int i = 0; i < n; ++i ) for ( int j = 0; j < m; ++j ) scanf(\\\"%d\\\", &a[i][j]);\\n\\t\\n\\tvector<long> foundation (m);\\n\\t\\n\\t\\n\\t\\n\\tfor ( int i = n - 1; i > -1; --i ) {\\n\\t\\n\\t\\tvector<int> build = a[i];\\n\\t\\tmultiset<long> forwards, backwards;\\n\\t\\t\\t\\t\\n\\t\\tvector<int> pf(m), pb(m), l(m), r(m);\\n\\t\\t\\n\\t\\tpf[0] = build[0]; pb[m-1] = build[m-1];\\n\\t\\tfor ( int j = 1; j < m; ++j ) {\\n\\t\\t\\tpf[j] = build[j] + pf[j-1];\\n\\t\\t}\\n\\t\\tfor ( int j = m - 2; j > -1; --j ) {\\n\\t\\t\\tpb[j] = build[j] + pb[j+1];\\n\\t\\t}\\n\\t\\t\\n\\t\\tr[m-1] = m - 1;\\n for ( int j = m - 2; j > -1; --j ) {\\n if ( pf[r[j+1]] <= pf[j] ) {\\n r[j] = j; \\n } else {\\n r[j] = r[j+1];\\n }\\n }\\n \\n l[0] = 0;\\n for ( int j = 1; j < m; ++j ) {\\n if ( pb[l[j-1]] <= pb[j] ) {\\n l[j] = j;\\n } else {\\n l[j] = l[j-1];\\n }\\n }\\n\\n\\t\\t\\n\\t\\tvector<long> foundation2(m);\\n\\t\\t\\n\\t\\tint offsetf = 0, offsetb = 0;\\n\\t\\t\\n\\t\\t\\n\\t\\t//when we fill these guys up, we need to add: prefix, foundation, AND RIGHT BOUND. \\n\\t\\t\\n\\t\\tfor ( int j = 0; j < m; ++j ) {\\n\\t\\t\\tlong val = pf[j] + foundation[j];\\n\\t\\t\\t\\n\\t\\t\\tif ( j < m - 1 ) {\\n\\t\\t\\t\\tval += pf[r[j]] - pf[j];\\n// \\t\\t\\t\\tcout << \\\"ROW \\\" << i << \\\" COL \\\" << j << \\\": ADDED \\\" << \\tpf[r[j]] - pf[j] << \\\", since r[j] = \\\" << r[j]\\n// \\t\\t\\t\\t\\t<< \\\" and pf[r[j]] = \\\" << pf[r[j]] << \\\" and pf[j] = \\\" << pf[j] << endl;\\n\\t\\t\\t}\\n// \\t\\t\\tcout << \\\"ROW \\\" << i << \\\" COL \\\" << j << \\\": \\\" << \\\"Inserting (FB) = \\\" << val << endl;\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tforwards.insert(val);\\n\\t\\t}\\n\\t\\tbackwards.insert(pb[0] + foundation[0]);\\n\\t\\t\\n\\t\\tfoundation2[0] = *(forwards.rbegin());\\n\\t\\t\\n\\t\\t//cout << \\\"pf: \\\";\\n\\t\\t//for ( auto u : pf ) cout << u << ' ';\\n\\t\\t//cout << endl;\\t\\t\\n\\t\\t//cout << \\\"LJ: \\\";\\n\\t\\t//for ( auto u : l ) cout << u << ' ';\\n\\t\\t//cout << endl;\\n\\n\\t\\t\\n\\t\\tfor ( int j = 1; j < m; ++j ) {\\n\\t\\t\\t//cout << \\\"-----------\\\" << endl;\\n\\t\\t\\toffsetf = -pf[j-1];\\n\\t\\t\\tlong erasable = pf[j-1] + foundation[j-1] + pf[r[j-1]] - pf[j-1];\\n\\t\\t\\t\\n// \\t\\t\\tcout << \\\"ALSO SIZE IS \\\" << forwards.size() << \\\"; and just erased one!\\\" << endl;\\n\\t\\t\\tforwards.erase(forwards.find(erasable));\\n\\t\\t\\t\\n\\t\\t\\tlong val = pb[j] + foundation[j];\\n\\t\\t\\tint left_bonus = j == l[j]\\n\\t\\t\\t\\t?\\t (0) \\n\\t\\t\\t\\t: \\tl[j] == 0\\n\\t\\t\\t\\t\\t?\\tpf[j-1]\\n\\t\\t\\t\\t\\t:\\tpf[j-1] - pf[l[j-1]-1];\\n\\n\\t\\t\\tval += left_bonus;\\n\\t\\t\\tbackwards.insert(val);\\n\\t\\t\\t\\n\\t\\t\\toffsetb = j >= m - 1? 0 : -pb[j+1];\\n\\t\\t\\t\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\n\\t\\t\\t/*if ( j != l[j] && l[j] != 0 ) {\\n\\t\\t\\t\\tleft_bonus = pf[j-1] - pf[l[j-1]];\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tcout << \\\"keep debugging \\\" << endl;\\n\\t\\t\\t}*/\\n\\t\\t\\t//cout << \\\"left_bonus: \\\" << left_bonus << endl;\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\tint right_bonus = pf[r[j]] - pf[j];\\n\\t\\t\\t\\t\\t\\t\\n// \\t\\t\\tcout << \\\"i: \\\" << i << \\\"; j: \\\" << j << \\\";frb: \\\" << *(forwards.rbegin()) << \\\";brb: \\\" << *(backwards.rbegin()) << endl;\\n// \\t\\t\\tcout<< \\\"of: \\\"<<offsetf<< \\\"; ob: \\\" << offsetb << endl;\\n// \\t\\t\\tcout << \\\"lb: \\\" << left_bonus << \\\"; rb: \\\" << right_bonus << endl;\\n// \\t\\t\\tcout << \\\"lj: \\\" << l[j] << \\\"; rj: \\\" << r[j] << endl;\\n\\t\\t\\tfoundation2[j] = forwards.size()\\n\\t\\t\\t\\t?\\tmax( *(forwards.rbegin()) + offsetf + left_bonus, *(backwards.rbegin()) + offsetb + right_bonus)\\n\\t\\t\\t\\t:\\tleft_bonus + *(backwards.rbegin()) + offsetb;\\n// \\t\\t\\tcout << \\\"computed value: \\\" << foundation2[j] << endl;\\n\\t\\t}\\n\\t\\t\\n// \\t\\tfor ( auto u : foundation ) cout << u << ' ';\\n// \\t\\tcout << endl;\\n\\t\\t\\n\\t\\tfoundation = foundation2;\\n\\t\\t\\n\\t\\t\\n\\t}\\n// \\t\\tfor ( auto u : foundation ) cout << u << ' ';\\n// \\t\\tcout << endl;\\n\\t\\t\\n\\t\\n\\tlong b = -2000000000;\\n\\tfor ( auto i : foundation ) b = max(b, i);\\n\\tcout << b << endl;\\n}\\\"\\\"\\\"\\n\\nif not os.path.isfile('compiled.txt'):\\n open('prog.cpp', 'w').write(prog)\\n os.system(\\\"g++ -std=c++17 -O3 -oprog prog.cpp\\\")\\n open('compiled.txt', 'w').write('BRAH')\\n\\nos.system(\\\"./prog < progIn.txt > progOut.txt\\\")\\nprint(open('progOut.txt', 'r').read().strip())\\n\\n\\n\\n\",\n \"template\": \"#\\n# Complete the 'matrixLand' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts 2D_INTEGER_ARRAY A as parameter.\\n#\\n\\ndef matrixLand(A):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n first_multiple_input = input().rstrip().split()\\n\\n n = int(first_multiple_input[0])\\n\\n m = int(first_multiple_input[1])\\n\\n A = []\\n\\n for _ in range(n):\\n A.append(list(map(int, input().rstrip().split())))\\n\\n result = matrixLand(A)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":292,"cells":{"question_id":{"kind":"number","value":1617,"string":"1,617"},"question_title":{"kind":"string","value":"Bricks Game"},"question_content":{"kind":"string","value":"You and your friend decide to play a game using a stack consisting of N bricks. In this game, you can alternatively remove 1, 2 or 3 bricks from the top, and the numbers etched on the removed bricks are added to your score. You have to play so that you obtain the maximum possible score. It is given that your friend will also play optimally and you make the first move. \n\nAs an example, bricks are numbered $arr=[1,2,3,4,5]$. You can remove either $[1]=1$, $[1,2]=3$ or $[1,2,3]=6$. For your friend, your moves would leave the options of $1$ to $3$ elements from $[2,3,4]=9$ leaving $5$ for you (total score = $6$), $[3,4,5]=12$ or $[4,5]=9$. In this case, it will never be optimal for your friend to take fewer than the maximum available number of elements. Your maximum possible score is $6$, achievable two ways: $1$ first move and $5$ the second, or $[1,2,3]$ in your first move. \n\n**Function Description** \n\nComplete the *bricksGame* function in the editor below. It should return an integer that represents your maximum possible score. \n\nbricksGame has the following parameter(s): \n\n- *arr*: an array of integers "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int bricksGame(List<Integer> arr)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class Solution {\\n\\tstatic InputStream is;\\n\\tstatic PrintWriter out;\\n\\tstatic String INPUT = \\\"\\\";\\n\\t\\n\\tstatic void solve()\\n\\t{\\n\\t\\tfor(int T = ni();T >= 1;T--){\\n\\t\\t\\tint n = ni();\\n\\t\\t\\tint[] a = na(n);\\n\\t\\t\\tlong[][] dp = new long[n+1][];\\n\\t\\t\\tdp[n] = new long[]{0L, 0L};\\n\\t\\t\\tfor(int i = n-1;i >= 0;i--){\\n\\t\\t\\t\\tlong max = dp[i+1][1] + a[i];\\n\\t\\t\\t\\tlong min = dp[i+1][0];\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif(i+2 <= n){\\n\\t\\t\\t\\t\\tlong sc = dp[i+2][1] + a[i] + a[i+1];\\n\\t\\t\\t\\t\\tlong scm = dp[i+2][0];\\n\\t\\t\\t\\t\\tif(sc > max || sc == max && scm < min){\\n\\t\\t\\t\\t\\t\\tmax = sc;\\n\\t\\t\\t\\t\\t\\tmin = scm;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif(i+3 <= n){\\n\\t\\t\\t\\t\\tlong sc = dp[i+3][1] + a[i] + a[i+1] + a[i+2];\\n\\t\\t\\t\\t\\tlong scm = dp[i+3][0];\\n\\t\\t\\t\\t\\tif(sc > max || sc == max && scm < min){\\n\\t\\t\\t\\t\\t\\tmax = sc;\\n\\t\\t\\t\\t\\t\\tmin = scm;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\tdp[i] = new long[]{max, min};\\n\\t\\t\\t}\\n\\t\\t\\tout.println(dp[0][0]);\\n\\t\\t}\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception\\n\\t{\\n\\t\\tlong S = System.currentTimeMillis();\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tlong G = System.currentTimeMillis();\\n\\t\\ttr(G-S+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tprivate static boolean eof()\\n\\t{\\n\\t\\tif(lenbuf == -1)return true;\\n\\t\\tint lptr = ptrbuf;\\n\\t\\twhile(lptr < lenbuf)if(!isSpaceChar(inbuf[lptr++]))return false;\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tis.mark(1000);\\n\\t\\t\\twhile(true){\\n\\t\\t\\t\\tint b = is.read();\\n\\t\\t\\t\\tif(b == -1){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn true;\\n\\t\\t\\t\\t}else if(!isSpaceChar(b)){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn false;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static byte[] inbuf = new byte[1024];\\n\\tstatic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate static int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate static boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate static int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate static double nd() { return Double.parseDouble(ns()); }\\n\\tprivate static char nc() { return (char)skip(); }\\n\\t\\n\\tprivate static String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate static char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate static char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate static int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate static int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { if(INPUT.length() != 0)System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'bricksGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int bricksGame(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] arrTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> arr = new ArrayList<>();\\n\\n for (int i = 0; i < arrCount; i++) {\\n int arrItem = Integer.parseInt(arrTemp[i]);\\n arr.add(arrItem);\\n }\\n\\n int result = Result.bricksGame(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'bricksGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static long bricksGame(List<Integer> bricks) {\\n // Write your code here\\n int length = bricks.size();\\n\\n if (length <= 3) {\\n long sum = 0;\\n for (int brick : bricks) {\\n sum += (long) brick;\\n }\\n return (int) sum;\\n }\\n\\n long a = (long) bricks.get(length-1);\\n long b = a + (long) bricks.get(length-2);\\n long c = b + (long) bricks.get(length-3);\\n long runningTotal = c;\\n\\n for (int i = length-4; i >= 0; i--) {\\n long min = Math.min(Math.min(a, b), c);\\n\\n runningTotal += (long) bricks.get(i);\\n\\n a = b;\\n b = c;\\n c = runningTotal - min;\\n\\n }\\n return c;\\n\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n long result = Result.bricksGame(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'bricksGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int bricksGame(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.bricksGame(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.util.*;\\nimport java.io.*;\\nclass Solution {\\n public static void main(String[] args) throws Exception {\\n BufferedReader reader = new BufferedReader(new InputStreamReader(System.in));\\n int T = Integer.parseInt(reader.readLine());\\n for(int i = 0; i < T; i++) {\\n int N = Integer.parseInt(reader.readLine());\\n String[] strValues = reader.readLine().split(\\\" \\\");\\n int[] intValues = new int[N];\\n long[] cumSum = new long[N];\\n for(int j = N - 1; j >= 0; j--) {\\n intValues[j] = Integer.parseInt(strValues[j]);\\n cumSum[j] = intValues[j] + (j == N - 1 ? 0 : cumSum[j + 1]);\\n }\\n long[] score = new long[N];\\n for (int j = N - 1; j >= 0; j--) {\\n if (j == N - 1) score[j] = intValues[j];\\n if (j == N - 2) score[j] = intValues[j] + intValues[j + 1];\\n if (j == N - 3) score[j] = intValues[j] + intValues[j + 1] + intValues[j + 2];\\n if (j < N - 3) {\\n score[j] = cumSum[j] - Math.min(score[j + 1], Math.min(score[j + 2], score[j + 3]));\\n }\\n }\\n System.out.println(score[0]);\\n }\\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'bricksGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int bricksGame(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int arrCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.bricksGame(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"bricksGame(arr)\"\n ],\n \"solution\": \"INF = 10**18\\n\\ndef one_test():\\n\\tn = int(input())\\n\\ta = list(reversed(list(map(int, input().split()))))\\n\\tdp = [0] * (n + 1)\\n\\tfor i in range(n):\\n\\t\\ttake = 0\\n\\t\\tdp[i + 1] = -INF\\n\\t\\tfor j in range(i, max(i - 3, -1), -1):\\n\\t\\t\\ttake += a[j]\\n\\t\\t\\tdp[i + 1] = max(dp[i + 1], take - dp[j])\\n\\t# print(\\\"!!!\\\", dp)\\n\\treturn (sum(a) + dp[n]) // 2\\n\\nt = int(input())\\nfor i in range(t):\\n\\tprint(one_test())\\n\",\n \"template\": \"#\\n# Complete the 'bricksGame' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY arr as parameter.\\n#\\n\\ndef bricksGame(arr):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n arr_count = int(input().strip())\\n\\n arr = list(map(int, input().rstrip().split()))\\n\\n result = bricksGame(arr)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":293,"cells":{"question_id":{"kind":"number","value":1431,"string":"1,431"},"question_title":{"kind":"string","value":"The Longest Increasing Subsequence"},"question_content":{"kind":"string","value":"**An Introduction to the Longest Increasing Subsequence Problem** \n\nThe task is to find the length of the longest subsequence in a given array of integers such that all elements of the subsequence are sorted in strictly ascending order. This is called the Longest Increasing Subsequence (LIS) problem.\n\nFor example, the length of the LIS for $[15, 27, 14, 38, 26, 55, 46, 65, 85]$ is $6$ since the longest increasing subsequence is $[15, 27, 38, 55, 65, 85]$. \n\nHere's a great YouTube video of a lecture from MIT's Open-CourseWare covering the topic. \n\n[(iframe youtube 4fQJGoeW5VE 560 315)] \n\nThis is one approach which solves this in quadratic time using dynamic programming. A more efficient algorithm which solves the problem in $O(n \\log n)$ time is [available here](http://www.geeksforgeeks.org/construction-of-longest-monotonically-increasing-subsequence-n-log-n/). \n\nGiven a sequence of integers, find the length of its longest strictly increasing subsequence.\n\n**Function Description** \n\nComplete the *longestIncreasingSubsequence* function in the editor below. It should return an integer that denotes the array's LIS. \n\nlongestIncreasingSubsequence has the following parameter(s): \n\n- *arr*: an unordered array of integers "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int longestIncreasingSubsequence(List<Integer> arr)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\n\\npublic class Solution {\\n \\n static int CeilIndex(int A[], int l, int r, int key) \\n {\\n int m;\\n \\n while( r - l > 1 ) {\\n m = l + (r - l)/2;\\n if(A[m] >= key ) // ternary expression returns an l-value\\n r = m;\\n else\\n l = m;\\n }\\n \\n return r;\\n}\\n \\nstatic int LongestIncreasingSubsequenceLength(int A[], int size) {\\n // Add boundary case, when array size is one\\n \\n int[] tailTable = new int[size];\\n int len; // always points empty slot\\n \\n for(int i=0;i<size;++i)\\n tailTable[i] = 0;\\n \\n tailTable[0] = A[0];\\n len = 1;\\n for( int i = 1; i < size; i++ ) {\\n if( A[i] < tailTable[0] )\\n // new smallest value\\n tailTable[0] = A[i];\\n else if( A[i] > tailTable[len-1] )\\n // A[i] wants to extend largest subsequence\\n tailTable[len++] = A[i];\\n else\\n // A[i] wants to be current end candidate of an existing subsequence\\n // It will replace ceil value in tailTable\\n tailTable[CeilIndex(tailTable, -1, len-1, A[i])] = A[i];\\n }\\n \\n return len;\\n}\\n \\npublic static void main(String[] args) {\\n Scanner sc = new Scanner(System.in);\\n int N = sc.nextInt();\\n int[] arr = new int[N];\\n \\n for(int i=0;i<N;++i)\\n arr[i] = sc.nextInt();\\n \\n System.out.println(LongestIncreasingSubsequenceLength(arr, N));\\n \\n}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'longestIncreasingSubsequence' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int longestIncreasingSubsequence(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int arrItem = Integer.parseInt(bufferedReader.readLine().trim());\\n arr.add(arrItem);\\n }\\n\\n int result = Result.longestIncreasingSubsequence(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nclass Result {\\n\\n /*\\n * Complete the 'longestIncreasingSubsequence' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int longestIncreasingSubsequence(List<Integer> arr) {\\n \\n // Write your code here\\n int res=0;\\n TreeSet<Integer> l=new TreeSet<>();\\n for(int i=0;i<arr.size();i++)\\n {\\n Integer temp=l.ceiling(arr.get(i));\\n if(temp==null)\\n l.add(arr.get(i));\\n else\\n {\\n l.remove(temp);\\n l.add(arr.get(i));\\n }\\n }\\n return l.size();\\n }\\n\\n}\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\");\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .map(String::trim)\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.longestIncreasingSubsequence(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'longestIncreasingSubsequence' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int longestIncreasingSubsequence(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\");\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .map(String::trim)\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.longestIncreasingSubsequence(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.util.Arrays;\\nimport java.util.Scanner;\\npublic class Solution {\\n\\n\\tpublic static void main(String[] args) {\\n\\t\\tScanner in=new Scanner(System.in);\\n\\t\\tint n=in.nextInt();\\n\\t\\tint[] Array=new int[n];\\n\\t\\tfor(int i=0;i<Array.length;i++){\\n\\t\\t\\tArray[i]=in.nextInt();\\n\\t\\t}\\n\\t\\tint length=LMIS(Array,n);\\n\\t\\tSystem.out.println(length);\\n\\t}\\n\\n\\tprivate static int LMIS(int[] A, int n) {\\n\\t\\tint[] tailTable=new int[n];\\n\\t\\tint len;\\n\\t\\tArrays.fill(tailTable, 0);\\n\\t\\ttailTable[0]=A[0];\\n\\t\\tlen=1;\\n\\t\\tfor(int i=1;i<n;i++){\\n\\t\\t\\tif(A[i]<tailTable[0]){\\n\\t\\t\\t\\ttailTable[0]=A[i];\\n\\t\\t\\t}else if(A[i]>tailTable[len-1]){\\n\\t\\t\\t\\ttailTable[len++]=A[i];\\n\\t\\t\\t}else{\\n\\t\\t\\t\\ttailTable[CeilIndex(tailTable, -1, len-1, A[i])] = A[i];\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn len;\\n\\t}\\n\\tstatic int CeilIndex(int A[], int l, int r, int key) {\\n\\t int m;\\n\\t \\n\\t while( r - l > 1 ) {\\n\\t m = l + (r - l)/2;\\n\\t if(A[m] >= key){\\n\\t \\tr=m;\\n\\t }else{\\n\\t \\tl=m;\\n\\t }\\n\\t }\\n\\t \\n\\t return r;\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'longestIncreasingSubsequence' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY arr as parameter.\\n */\\n\\n public static int longestIncreasingSubsequence(List<Integer> arr) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> arr = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\");\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .map(String::trim)\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.longestIncreasingSubsequence(arr);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"longestIncreasingSubsequence(arr)\"\n ],\n \"solution\": \"def subsequence(seq):\\n if not seq:\\n return seq\\n\\n M = [None] * len(seq) # offset by 1 (j -> j-1)\\n P = [None] * len(seq)\\n\\n # Since we have at least one element in our list, we can start by \\n # knowing that the there's at least an increasing subsequence of length one:\\n # the first element.\\n L = 1\\n M[0] = 0\\n\\n # Looping over the sequence starting from the second element\\n for i in range(1, len(seq)):\\n # Binary search: we want the largest j <= L\\n # such that seq[M[j]] < seq[i] (default j = 0),\\n # hence we want the lower bound at the end of the search process.\\n lower = 0\\n upper = L\\n\\n # Since the binary search will not look at the upper bound value,\\n # we'll have to check that manually\\n if seq[M[upper-1]] < seq[i]:\\n j = upper\\n\\n else:\\n # actual binary search loop\\n while upper - lower > 1:\\n mid = (upper + lower) // 2\\n if seq[M[mid-1]] < seq[i]:\\n lower = mid\\n else:\\n upper = mid\\n\\n j = lower # this will also set the default value to 0\\n\\n P[i] = M[j-1]\\n\\n if j == L or seq[i] < seq[M[j]]:\\n M[j] = i\\n L = max(L, j+1)\\n\\n # Building the result: [seq[M[L-1]], seq[P[M[L-1]]], seq[P[P[M[L-1]]]], ...]\\n result = []\\n pos = M[L-1]\\n for _ in range(L):\\n result.append(seq[pos])\\n pos = P[pos]\\n\\n return result[::-1] # reversing\\ni=0\\nimport sys\\nseq = []\\ni=0\\nfor line in sys.stdin:\\n if i == 0:\\n i+=1\\n else:\\n seq.append(int(line.split()[0]))\\n\\nprint (len(subsequence(seq)))\",\n \"template\": \"#\\n# Complete the 'longestIncreasingSubsequence' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY arr as parameter.\\n#\\n\\ndef longestIncreasingSubsequence(arr):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n n = int(input().strip())\\n\\n arr = []\\n\\n for _ in range(n):\\n arr_item = int(input().strip())\\n arr.append(arr_item)\\n\\n result = longestIncreasingSubsequence(arr)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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sULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULVK0SNEiRYsULRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLRIaJHQIqFFQouEFgktEloktEhokdAioUVCi4QWCS0SWiS0SGiR0CKhRUKLhBYJLRJaJLTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTIjxb50SI/WuRHi/xokR8t8qNFfrTI7x+6/iZXkmYJssS2UqhxD0LE/7mWBHpA1oCTZg+qAQIE907Tc+y+IgqoN7mZ78uIG+FubqYqclRVWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpUWqbRIpUUqLVJpkUqLVFqk0iKVFqm0SKVFKi1SaZFKi1RapNIilRaptEilRSotUmmRSotUWqTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibRIpEUiLRJpkUiLRFok0iKRFom0SKRFIi0SaZFIi0RaJNIikRaJtEikRSItEmmRSItEWiTSIpEWibSIsIisiKiIpIigiJyImIiUiJCIjIiIiISIgIh8iHiIdIhwiGyIaIhkiGCIXIhYiFSIUIhMiEiIRIhAiDyIOIg0iDCILIgoiCSIIIgciBiIFIgQiAyICIgEiACI/If4h/SH8Ifsh+iH5Ifgh9yH2IfUh9CHzIfIh8SHwIe8h7iHtIewh6yHqIekh6CHnIeYh5SHkIeMh4iHhIeAh3yHeId0h3CHbIdoh2SHYIdch1iHVIdQh0yHSIdEh0CHPIc4hzSHMIcshyiHJIcghxyHGIcUhxCHDIcIhwSHAIf8hviG9IbwhuyG6IbkhuCG3IbYhtSG0IbMhsiGxIbAhryGuIa0hrCGrIaohqSGoIachpiGlIaQhoyGiIaEhoCGfIZ4hnSGcIZshmiGZIZghlyGWIZUhlCGTIZIhkSGQIY8hjiGNIYwhiyGKIYkhiCGHIYYhhSGEIYMhgiGBIYAhvyF+IX0hfCF7IXoheSF4IXchdiF1IXQhcyFyIXEhcCFvIW4hbSFsIWshaiFpIWghZyFmIWUhZCFjIWIhYSFgIV8hXiFdIVwhWyFaIVkhWCFXIVYhVSFUIVMhUiFRIVAhTyFOIU0hTCFLIUohSSFIIUchRiFFIUQhQyFCIUEhQCF/IT4hPSE8ITshOiE5ITghNyE2ITUhNCEzITIhMSEwIS8hLiEtISwhKyEqISkhKCEnISYhJSEkISMhIiEhISAhHyEeIR0hHCEbIRohGSEYIRchFiEVIRQhEyESIREhECEPIQ4hDSEMIQshCiEJIQghByEGIQUhBCEDIQIhASEAIT8g/iD9IPwg+yD6IPkg+CD3IPYg9SD0IPMg8iDxIPAg7yDuIO0g7CDrIOog6SDoIOcg5iDlIOQg4yDiIOEg4CDfIN4g3SDcINsg2iDZINgg1yDWINUg1CDTINIg0SDQIM8gziDNIMwgyyDKIMkgyCDHIMYgxSDEIMMgwiDBIMAg/yC+IL0gvCC7ILoguSC4ILcgtiC1ILQgsyCyILEgsCCvIK4grSCsIKsgqiCpIKggpyCmIKUgpCCjIKIgoSCgIJ8gniCdIJwgmyCaIJkgmCCXIJYglSCUIJMgkiCRIJAgjyCOII0gjCCLIIogiSCIIIcghiCFIIQggyCCIIEggCC/IH4gfSB8IHsgeiB5IHggdyB2IHUgdCBzIHIgcSBwIG8gbiBtIGwgayBqIGkgaCBnIGYgZSBkIGMgYiBhIGAgXyBeIF0gXCBbIFogWSBYIFcgViBVIFQgUyBSIFEgUCBPIE4gTSBMIEsgSiBJIEggRyBGIEUgRCBDIEIgQSBAIH8gPiA9IDwgOyA6IDkgOCA3IDYgNSA0IDMgMiAxIDAgLyAuIC0gLCArICogKSAoICcgJiAlICQgIyAiICEgICAfIB4gHSAcIBsgGiAZIBggFyAWIBUgFCATIBIgESAQIA8gDiANIAwgCyAKIAkgCCAHIAYgBSAEIAMgAiABIAAgP6/9r/uv+a/3r/Wv86/xr++v7a/rr+mv56/lr+Ov4a/fr92v26/Zr9ev1a/Tr9Gvz6/Nr8uvya/Hr8Wvw6/Br/+vva+7r7mvt6+1r7Ovsa+vr62vq6+pr6evpa+jr6Gvn6+dr5uvma+Xr5Wvk6+Rr4+vja+Lr4mvh6+Fr4Ovga+/r32ve695r3evda9zr3Gvb69tr2uvaa9nr2WvY69hr1+vXa9br1mvV69Vr1OvUa9Pr02vS69Jr0evRa9Dr0Gvf689rzuvOa83rzWvM68xry+vLa8rrymvJ68lryOvIa8frx2vG68ZrxevFa8TrxGvD68NrwuvCa8HrwWvA68Brz+u/a77rvmu9671rvOu8a7vru2u667prueu5a7jruGu367drtuu2a7XrtWu067Rrs+uza7Lrsmux67FrsOuwa7/rr2uu665rreuta6zvq5J3TzqfZ8bj7Vns7Np9qzuflUezI3n+pvLjf/lU+1JwXzqfacYD7VnhLMp9ozgvlUe0Iwn+pvPvD6r//1f/sv//W//b//z//2f//v/+3/8b//v/6v//5//l///b/+3/7Lf836L//f/+2//H/+6//z//j7f9Ru1n+Yopp/dEv9xzRcHoew+YdQJ4T0IYENck1UQ+fH1An8w9ybHzPi8x/IyvxYK2h+rPhmfqxwfn6sf+8vnXeZMrn5MQj0P4q/58dML/xHL5P5sbb7+bGim/mxwvj5sX6dH3reZdooz4+hO/8xFWB+zGC2f8y6mR9rm58fK6qZHyuInx/r0/ql511mvna4Z/Mu57QkYl1xRdaqD2t/3mW95bzLPJ/hoY8Xbd5lrfx5l2uYHDbMeZdrxumwqXNh189w8My7rK837zLXyos+77KO7nmXe3ADwot5l4lZQgg077I+A/dn/b8h9pt3mUvtTZt3WYHuvMtEzyEYn3d5ZggCCcO8y/oK8y7renCb178JiVe86fMu60bNu7xjEpG6zru809+d9HreZV2BeZd1OeddRlEIMkVcNPMu3+837/KN/o3EM+/yTetqZKh5l9G2glQ277Ju7bzLrBMX3bzL/2p5z2L+nxb41Bmzw94eHeRO18VGm+/fH4u9blOVmYgKc33IGp6Oyki/mmkqlq0z+f1Ha1yPctbaWgrzlvsQ+L6HPfY7CEyJvwQj7pmIy452XwTgd/8xOoKgan1YNIw8ppYnn7LX/DfzuLWh/3gkevtbH14+b/Z917x1/9g6Vvh85d8/houw4b/HQQ6W8x/Nvd5/TLD2QHovM91T6Yas5j2P//FYz5gWfvvxmbNe/yhPOshMOH5X7vYPRPxCfZ1/uA6//gOy/qHFEvR8Fyrm3I9rrI1/zBb7ywHWAXFeHAIvn/49Hx63C5Xi+JA+TqKKd37ho8C5ntFHjehjs37nfVf0NP9k2swb8R+EPw9fel0dUq9n1scMgf745ReBPZ/x9xrEse2sTOd45lI/J3vQ7+ARz04uYt77cWwSyf++5yC4v7lwr4HHrrfhoVzJ4oEEy9M/I86QWclrj/MjlzWgYud6BuqdT7Bra++bVOqYG+qhOG0/UafeLSJ9ZCCz5J8p9v7PsluXeC7rirXvT1+Kx41dYYY++iDzCToLc5qUzO8cN+0f/fBc7HNH33WVOIMyN3Hdormse9DsJHTz6b7vPRC2twWRuTLvyYMwHVMIRHeV58ERVy7z2l95tg4erpWYzN/OnwF5Z8nPvJP5KO8syGkyMjfzeewJFpWqedV6pmbBPSuUOBGnf1zKa77Pe/GW6+tfJlaPkRbJWefRmBZij+XJpJ03j9TwSG6jB3v5wVMzH+tdceY8iTrma+3O4znABCE0e+PKved+z2GObsMVWg8Hv6dcqG8mw/yj5t8Neu7nesEs2PXPXzKVuXgzReXh+ecu8c/XqXAgff2MOo554+93zWM59Z1bQuFQ6TdXaH1tsqqL+7F+wc0urVB2+MycPP5zyM/zd7CLDtQwB4dB3fQP//fXo++ZmhvdEM7Vcy7OgIwIC+/8WJv8xQJmob3avNe7HZjfXLHp+vJwk+duTWp7oTvN7R2/+8SpUOT/7ucfVPL3j9kffPXfbEzrv6GTH9yYtTWQrxML9KdS/3YnHGxunAd3/iY1sVLW/2aBTUHZv/8MaPueWVNsLmvT5WBf28+843sd3tXztgacR7Dcs7XeH1b6xxd+w6PhpvG75scMwWbnJt4Z4GL+xs7zzJShf0zPfTzCHoJQFvDYh/8gjuZ7HPzytQLnyridjvXMMtNxcztdacxj4DCLdSYfzvfWbLn3pXzvufEDFs4utg70/vsbjjg56q2jyOmhNH9/D+ftcfF9dAJ+v/l2K1GYK/YdxDkrLuIUXsfjRUBrmNRZ19cQlOTpF1/9m+h4z/Eqkdc90xG87/Ek4gA8bl/mL2CbXYcVEVvZgs8ZhDf3aW7ne7GJfCvq/bhN8wh/a4/+4YhwJ8tj9BxspmsP4vybzZ2wX1C9c709kddFyPVvZ3PjldRj9nOzvtzwPk+EizTFAJtAcu1cP+PljS9yZssRXur8E0UprxwcROfs5/d1WvP8Gqe93Lv7M9z+Zhf5PBzWZjLLaB2CF/sBMfHaSz+PfI7odRRdPJ/6Wzhk6w4cnO6zir5zdsPp20rEdNzsG9fHG7PIVcPXl5lruB7igwDone3muNg7CN4Fct/fNyfP+gvB5vX91Fz8oGcJ3IxO13F3kx5ogF5qlB+hwh7zral2lqDrWturEtC82bX+JSn+Q4TBt51bSSTFVRqVdFbc/cwlGFyOL6pOOGWr/xgpM9vXFKPypLOHrjOaGKbzzE3zFG7cgXSlTvB7D+7+vX27B4Gcp2ytEyLRtZcR8/B/rn/orjHfcThRo6u5lQaEM/eU54442gN3/AeCPtKF7+WIWp+QKPY0Nr8uDtCPA/5gJ1u7PW8/eMY/JPCPr2bCeeHPPly5lyjl4CZO+vLwCV5+84fI95sPt3agS1FvVw49yj4PURa71WSffKXLFJeI8drFdr13F1+SwRD3zPRylgAH0+cBc5C3zmgynurz3en7Dx9toq33IIha+/f8tnWFCa2/T0WexRriF8KY8+CwfSVavnI/B6j/x3zvjwxhVtZ0JeFc+RFArrhiLvEm0H4nW+9amQfuxac4wc74Y0d9posKJyOKL8nv8dv7PjHN0FqfMYoRKpe8/Mu1p5OIz9i1eVSOk9RA4yosiFHED01J3ky5l53tl7I5XbdB/J+BRJxAQPFOCvyPknqMFJ3K81Ut5xkyFFyv4m8H0fekKgdynTtHPM3mCVyPB6ngV7TkIz5ePzyMzMf//hIjs9l1zKlXYVmur+gpxsq/ON+nYftc7OdUWcw8x2vXYKEiDkzd8Ky0FQJ/brwIo5zoE33zF/KF4VaJwUkWfz4nbtAXycOx3eyDl9WneCIGH4B5zNa/4Iz4Lk8rk14NqRne9I82iSQWZKuva3FleWwT077w37aTps7sI4153NVnpa1djiT0eEjISEJnqvZsiDMFnPiXU5A8+/7Iae71lLGx/djf1kP/cL9uVemDX3P7tXvzQP7I2s65o7NPGSHPypkh6rMs7nCbZ/whj9TsUzVkH+CRA/m6ODafh9NAS4Dkfi0t9h+3+cklOC9/pFdrKfz+/WcA7v35/JPkrNsx/2S6PVwGR+jkm8f9zNPdbk4UlIkeeGtj5N9LNqrjtHYzNn8D9Pvm5FkLmyCXs2nmHNzE+rOlzHLc1ht7BctrdzC+ZhTpfK/P3P9mZ1/P8snOTuj6NR5KJZvYg4RJFCcO5Ek6L9fv9qFObZ6SzhKuPKq077S3ml39vPi1fJN1gVnjN/drxfVQAisaObksnrZEYd+3B5x/pCE8Qys3JLGpulm5tuuaiJt4Pa577xqz4I7dTmd9ShbjbGlvUZ7W0iKBXOmKAj6Mzq6slg66dnsFzqpdRn4eP5/t6IIgwR3IDSPNPD5KHAC/43VlIpmwp31ckvc1szw5y9cBY4b/4/oQGsdHaR06rK/zY5ueI3uFQoeay9zuFe8ZzedTH5kzbeU2P1S3l3ydv63cmX15bVS8sS7EiqE5jJ/q2RzcxHuT9SdfEBViXePDe0Gy9TfDUVvyZXM5d8xyERSoQq7tUEeBXPjwEX9OteW7nK6kqhObYr7sqsRTIA658lb4W2f9RA4TXrJB3PPRp2ERWzNa6zrHfuwaF3FaOZAOruvZ3z5Jf24hRg7XQWA8X2CdE+yO5hXzFwKO32GaQHRxKVVcbLynp8O6LSGHVjW88iodz81c+8T8e5f37EoH35HT5HsMRxGzrqkp/cf4JO4L296pFvsi7MyIuPltM0Hj39/I7nv3+iOlU5leaQ3AjN7bCqM529am8oOO4HOrEFtJtt6OC3kfxw4TyM1JhEelPv7zQK61SG65bsR81I902uf4XfsGcsXHkTWwL7eWXDEcr89HcLf59rWkD45qich11P+QYVEeX7TgmXCBUvYZ2JX4+mKjGdaeZIxDdJQEYwKCSTGXB/3uNAJcKcbLLb7Jo1Yox9oxNZteDl4pzsFj+3yndpahGfn9PJSsiQuJZsXjr9vwXoHzZddGeJL7V9clJNIH+zXw3jQNw0YgYJuhJW7CF9uTkUvZwb6/i6H5oI9o5neStT/sy4cB1P2w8gY2+HjO+d4Hz9olNf8dbDsrU3pIwr4L4YAsfATXg91NOOPY1Twal+w/64bzuU624LXbsg9hT1wmezMMUXHTrh+CVGba94yqJD4xDp2rNU0RFbuILidPmu3ZM19E7zlQbREAXzXsFVBcPz+B94106kdau3ZCNKigH00JByF1ZGF5MvZgynvGsyPr6Hh/D+nL/eNg/gmn/YztuT6OWLwVbE3/1/YU7EW0+LV+CGhfsshpAUW4h5T6ZsOWWvPugAeHwYEut+4oH+Awbt4iMZKx5YArRz5QEAmM4ib6lCti8ek7A6j/YYGTI2EVTefVG88GgWM9oWx4NzHDi3Y9vXJd5Jv8YOt6f9vBITN+XskUlkxU0lYGRa67lgeCym2korZ7c3JNm1rECeSCuVqzLixtemaKz4TTQm5jvhBrqDwbgMzvZT/fNdnmgMj566F92X9u2WB233X58MB+Zk/rkEb4OQjuPuwuRP7n2TwtsiLOwR4mtPYlgo8Vwsxj+rL9j25FNpat9mIKoJw+yMHnIXZ2IJT/Tj7gdqN/7ECjbnMoo589VXTfc5Z3zetaOLMnTjMhwttPMXHec09QvCesmc9DjLNexuG0EmzONHTEKdA/sDlQzteObMJD4Fj2sblIkyCeJOYrC+NxukkO7rUTz908eMpnUN1r2l2xTIR9Nt/1liTSK0edL3ZxCK2PNG+9Rzac0vv78q1N9Ld3XwyHE+johwH7mkLU/Xb6h+AMEOS8u8mA7sV3Y8mcuLEDO3OysnZWUF7P16ARiD/xfY5X4UBl9yrb6dpUyDlvNNOPw3Y94PzqtYA5+UheXqLiFR3N1jVLh//kE1X01JXdn58Cshk9+tO4y+qWN0lw1C1tEIFI86wIpPbNnHP8YAGtp59tZS23C/H33g67u6mezFefxIuFIA480xQ8Rsmv3/mS37HH+GI4jZhJdGw+cdYe8i8+yYs2MJksUTKCylUjEb2Z22w7oqUxxiG3VLxY0RixzdqojVU2IzQ7/ySTnFPw8mtrQwGRIPy23SvaT+5ZlNWpSkT5YBPKbtCBEIBNN0k7vhtJ03Rmz7+/ZgPHgRkwISUSLyfup8Z3lns+YuvcUgvnx2cmhGXzefi4a1OEAfWZnn64j58UWYOd4zgvjaXzJkJxFLMl+VZfr62Rj/cSaTy7O9XuQfo8zmfCyF6RIhvO6+NwsX3uyaWqxL+yCNe/45L8bo60U/yLePmxXHPdTbaaF/V7HcLEPI8MxGndHMUG660eVrdFbVz+FT1hj1jJcluvOpszWu67j3C5K/LBoqOt7Qa5dh1mD3GyAlG1dhC992DZKaDhk6DcfPe7g0MEcV3Fc60sNYkfduXPYgZ0rxJ6T38Nko2bLWFEj38MTCLP/23xn7BjHbmIlJAPZ0hqriBzfEUPmbSdrIEVd2P+35ZlrTQNlWDmCXOMkUoRS1YN+zNeXCdoVIhFg9mm81o7gNU23RhYhq/i3LUTBMCZh8j9wH04Zm4bWvejW8khSSpwz2ODQofCYPOA9d/YXVfIo8s1C2giJTK1TymDY2rELx5+mfT73Y2+sT7dcv+GP5/aCDNvnfuO8PWQXX1TYf7vbxrFc3bnzcR69yW4dXleEhOP+6zVupGjuW5TkYdSr6J8cITNkCtyIgd0G3UfboPD0fAvkRlHAA7HDSroz3xs1046J/1V4H1/s+/NFAr+m5b8RWx23eQ16+qozSATfTfrbIVLc0TcqrKjoRMy45NOUfVNEnmqmRAJf6/1Pb9DCQRx4cL9mOGArFMHsq8dE7kI9X1daNb1JccUouvPIq45i/UxAUDe7zULIzTisZ6ZguVK4+0EnXUltFoSp277aYFXrOv56t5oLQuBYAiTXkSzKf4ijeQ5WOfFw65TtEvrJO4P52MsYTIaIo0t16wHmozpj+gMm8+PhOX+q9vT0/lOD593k5JkSTNdnbUZHR6kgpfw49nFgxce0lpTn+4IIUaRaj5L9z8thz11YL7rzb4wu/XahUjaTYweVs4KB9XQMDInWP35ZQ/ClU8jcxeA3yZipAvrM3AOcGeev1MYf/7EdJoGCvgc227Fqj0hfo4g06+zA5vjeJX/da6zSw49WWTNsPRmOPhBCG5tC9LIDD8/ydN0qxAr1nkP1lfIuBXxW0BFNj3WHvLB5zN1Hf95TNfDU/PB6kOAtL1sLuvbWq3H/ThWEHHhaZIVn8T4Y07fHA5qzJ81nejbg5b9PJ/AmtiNxnJhW4BbWY83y/N5/qZx8Gh5q13rIyew+6HiXYdbrZWLis3PoR6IszbTU0gMkbrW84R9W7K+Cp99QT2axnbkJWrmezTfWQsYCGwEi6ezqqIWitqps/uTPLyVIvgas/8hYZgPz05NSs/Taaea9fCQtht2XpcgYHCqL7St2bTRZK3+05S+NniYywK9n0qUVt/a9TkXOCqf3WDKtkNbFOE91tX8TEBfMAdedYSEZnYz0oaHcApt6n2M/n92skCwulXx1gOE8FM5lZXw4+w8pEuFrczzd59ZgBh4a5uTWkGou9kyT/3Z4RROdnEO5VuP6cfiX0uSLLZ6oESAx4nKMP/XpUfD83lbH4BYdlwIUetG6vdw/D3uXs8e8vB85DuH1tnuSx3kojMbQ2dLvsAoNgM5BT5sSXygtYXhIq4Y5SaCxYeyE85lAHnf0KAD+MPK8J5jZOO6cGavmINgI4fotPVZ6+Ti4AJCffU3ZmWQdrJzll1uz3c9ia6GyHj/E1bNRY9WMyeUa3N9Zh7N3ajuOSFTCCVuE9FTwva5d7RBwHa8PJLGjl8iMm1FExH29ASHiYASPcXWLRN6Jabfaysa+hFb9jFlvGX8XvHVby1EwRos8yjKPexoX57djvJgJyQOsQjuLN9tOswQQJ7mWD9Rn/eHYIDz827LqnCJh+3SAd7Xzgeds94Q8QvG5bJtxYNg8nfGWXL06GjvDpHPHu33EbtPtwSzntdlQl53kXe/P/L1dcJulhKF5aefcn6ydL9NSqlkYKAfQBPXjpHv7u4Y+F6/Zze0OLVieZhvotG1KIkIJfGmMzJPJefTOpZYxu+hX/nDJ/rxTw615seHc7KoeTCwPa4QTV3n32hSSTxk8RVGIbWuo0ndwpolAru15LARQn57fsQu77kH9gIhnMdOz4jFHgXhRk3TJVW0oW3i3GQtkykGS4wtytv6Sqk+665iNcmLPGg0p61b1v0A3liXylsRjkW8ujnj2Xfh/w8LnE6dsXcXTx0aayeoX8UcPJfImA84r8nfj32u/PXhmp4jPuMViHIxzm+/sWDX807h4HTNYVvDTPxtBFgYXGHqsID1s1PQnwf0qL9dtxzrw3O3B9WvPdJnhUW5YisyWzKY9bBzup6mKQEJuQiZZrgK6Tymz8kTNq3fiARZaPayO8YMmI/sJbgNIC6TxgOr7jYpe2zotZbWQYzNZj34j1v3pttIS44q44EtnK+H84Xrth4L2Lef5O7DUTFQ+sU6yv9AYWISsM6sV/uZr/CeVqdusIDChqDRuHA+hZ4ZsMGrvpPdwWpo9665aHNf1oNDeKzpHsMEdM2/OQsXVQ3Pru2zkGpEWXLaU7kLx/x8b13H3QMAEOHZwxMfiK5hhxFx2Djfcwc4RPFqqysnx/65PHxL8HeET/Q9yFFV7jGqHK0Ru5nbsw4PcwbecSJmhB4JgR/s6kygRVnX8Pl9t7qLDowFLORfjx3gnre7tP0gbOPEX9sugZpNQVZC4yCanzfpgok+YHA/CfX7Q3Ob8WM/FqTMH1UC4l23ZWkjy862/fkQPZ8AoM/ZQ1C2VlLNgl82V2ovpu3G/G387LmKhzV0KHbH+ZmDH7s4i34QPSXZNAoOFD20v300/s0hJ9T/MBbWg3cQIsMqDJeDP3KZ+aFurRUKZe0COf9qpI+bbVNN6XRZ6jxNHR4igNX1PsVrK4Vn+MmJfyKll/D9gyT1CJ9OPQnBBiz856oeJYJwmkX0GsveAda7V3z2kObqbGJ518Dn3Q0nDry6/X9+bAO10v2+dKgxVQX0x7TGHsSuOPQ0X83C9RHRj9eRQvBIgnKVXG+u86Fop8P5kPlVK1e5+zZU/XCt9yD0tRAJLHWYLcMc5XheVslCJbC17Z/798zXX7cQVg56aa0Bzjo7ba6Qi/Tupz34+Tj+ZMgRse/XpO2UXiCFW0cAe0c5E8ef/ojNZf7wbshchl7HJOA9ppOADzEx/xQuzd2HUcuuDlpXC5eGqO9ozU/4IHpKr4VK63bxCKxXY5w+v23UHaa4JPBc3iBqHnqFk9POZ3ypzTjMNqefF4ctesHa8wm1D8KLW5pqZiTy8JPP7G6qExISLlhlXILeV1Z5Q7CH4egRlvYrhPW+bpaQtNN3M1hlMhVuuXq336ZPdk9bjqgVov5pPGpeArI2KVkf5PnP6bAeCzF+8pbn+kO/2Iw+nuZ1BlZtl2jm1P4DA91TYy8e0aG2+AKIGKLiLwj0Slt3QIjHXYTLa6P2H5UJK1TiOZVMnpOCE4MbTIY3zeu4LkRA00cKnQIoYwUGJIGnUtjjDXtYQUN3ofdjxmBX3D9FP4VyPvuIqaQmdjQZCfgf7VaIjICtZkLWy1bncnbtZbtjZCH9m/eHOCMwgIGz2xResTLq5DGsecHMtoRkeE91JdbC8whSX1t6eHWw5mPvXeUUqEXYWWGGuhU52PRxfZDGcTW0PdcdkBnmlDvu030K2GeFMI+xOZIeeabdZ46L0sKryEJrWZHCXHiftfZrPeTUDU6SNytITvBh779/u5Yd7G4F1YBMH7BGzNljgLt+nxUUPNrjuc2jisR/fwqxPzcGj+m1b744G5iPK8PASXiltXFTp27iYHFSMfnbV5JnegboXTz8dvnCL3seKgfOe9flS9iiHjya4yNNeDyTaZ23YT45X88tmcFQHArE65KDQ5y7ysHA8WBprAfw2Ja4diau5sEZtoJJ8PsT4/MZkoUvhOP7Ywddx8Hh7s35D6Zld9f33pHCsbODPedL9RYJufaWmCIWdjb2mBuofOWZUN/2g7r+5sAf+zMip0oDWoNwx9jYNrxjzh6KLsEgQI27iE7n9PzxtBir7HrWuXukJbNyCkWgj8W+/P1seVhTgIPPVgtBL7zs9UlFLwnmpnHZHN8WLrwHDuBXvGI1t7XUH3gDqRIbLV62xVq3BFr6JNReW+keGYjCnMvD5NS0IbKPPPgPhGE6X58EkmxlYiszj3G2soez4bXsb+IklXyfBFoSGcN3Nz94OfHWhTR4Uuk9YFQjgFn87HErSFFqlcmlGgVK/+5Z1KhKR0kT55DicCMX+f048OLVsvfk2vRUrZRln3OLgfpAqIfleR6XkCzxAAvcxSh23zyE1P4XpaZzu/+nStNDRFK3oNBla0uo6jjrmE3nRTmeSEk7ymZ4uH6HCOppf8RHdmCQtsdcHBECp2GGGmku2q9FzfsHZN1dTfb9tLNAfVaAie13IsO+2/g62SLWknGr20Jy0a4sOd83rNIel6ihz9nnvifoedmH4NozRmciFmL//PsVwREV3jD4fxWbNyf7Q0Y1XA5nASnIDB0jqrUq5r3U3Dw9H5DJnqCWQ16QX/21JECNvbrbrBHjWgh5YRE8Gk9P/lo5kqpdPEa2x1nHD79tHNH/xIYjWm85jygP/vlA5T7HqiPD+fCU7Lp2sLPFEoRRXeYmlZj6zOl5am8Z29AfnNbTaVfH44ca5uoVLtuNeTnjj2tXS7Iz1S43mG6zjT76ZCdBneErwMdhQ8hHw3TUr49faRWX6kOIZL5vDxPdzX0QNm+bGc5dQC2CeZkW1Bjf6KHfYWZrmt9rL6CfqQRDSx+5lLWfkrbuLhcfot5pLdCPXXBwb4/y+Vwf+e1gvqyqj73KEvIVTEBMhmN3Jhuwv9i2w64P5p3rrAPasRJqWmed+isPMaQ9VyAKbTo0zvLzb2P3x25a+agSBtN9wimO7kM1Tuk+0LIzD5u8SGJLAeiyNcSKnjhGPjLB97NsSxxhnWsESge3eFdevuM/z9WLJALb7GUb2+fitLtzSZOSM1Ybb123n7E3itiLuDBDoUh76OhQ7+fIkiYF9oahJHI97cq+pywKz87lvX7iHXeU7WcIapH9IGFEr1i2D8jD4YXLu/k7s/Gf4g2y6tqXdRClh35Ul65/Z2cvMI61XVk1w3F53bK1uHjTr4Ok9BPMxQzfWu5777NGtM9eUvJxT/VmL2iOuUxEluXb3ABGK7SV0cb3OWRU1nM6D/+tUTRYKvfM76MVX7OzmbVuFnSoqmjHkgTaO+GT/rYj0VS6kfoHLcbbP4MW+AbPNop4JIxgxZimMzzH90+/RbT5yG7aRaadWuMuX+cj/lgwLmZ1d7cSc0KzDt1BcfSItkgf159zSGzERj65AF4KId7arozxbY8nDXE9l2oFlQhfEViHiT7U7tgLooj92K7h6g5F2U5t7/FBBL0PsvXsE5xWnyQona6MAi5i/HnCUamcvfxcdp757EJwQpNOIPgP/r5Eymy41xacXwG+nx2wRK4UiX6AGJ+NsgSPp9CHc0CF4REs9PE4pGHfb28lpy0ZYNMOmH8NmcMen/eG6e9HegfML5GYubYuSkiAxztb/os6pRtCznAbRAUlZZqR88SLzXslVnCjeiBi/FMoP2xhor5r//fHKoDP5nWtewGFWWXB33uUn31Ha3HayaG6Ni5Wig0gvtdSDI6Ag34sl+uL/zDVOHzoy9EVHlfskZdQ3IwfIkAjo7tR+Of54lE03wpp9xiCDwrl/H/zlP+DiiYwIzZckY92onX4Nhy0cGEoETgC1asIa15E5c8PKf67XZHOZTgu+ZBPhoqj1MPsUjnqAem+UeMxSdgSKItdccO29+wriIM8w+DJ/228gi1UR6QMD80SwK0dg4azoOJ/SKRrecwnsJvA2cdOMkYm3yuAiV562HahCrlrL/MhMi8/gEwe+2NdqlgzJHs29dZMEYNySvhZO/g1jWG8XczuPVlaEej6iGxOvbNBLWadWwh32nxuTBEeJ6LjBx3xCXrolDyAb3B7ZkkgaLPej02PfbvXDCLQuHgcIqzL1+2cT/5XFX3QxOWxtQL9jx7h4U/M477Ya6YPx80HZrHYAP4MnvuWfaYslKhwpyjwI4+lAV8I3WeHJKCImiuf7eJJntEAl5LnAcpBsvr7CWUhmT03p9nwLPd/iJ71oH56ZGysjzbnQ7xZ+zuMCYuljOp0/7iU086aHeHayDlmynUZ9tlR+yF9WMfm/5/O8Oj5rzME3fWByZ+whFTQ5iKqbFN2h8+HyHHLakwvH2VuxH5kmkO15iwr2P4M6/oazLFRRndeFX38D6IQ21r39cZg9R/2KTmMGUux/ggKn3Ic4baxbC4hscd+n3/NoqlGOlWRxSRnMJSOF9jE+9kU/fGXH7D5D8t4fT6C7Z+uy8O+dtkNeRz8i8zHShx/+5YZKdI7LzT7KQ2aT1QItenWwMYVa9JwX3nUfqcdrvjgB27z46G0TjtaU639FQ26MoZeQgX8tdGgXh5ofivZm6VgA4bXXpdrm6IlzC2n+lOsfm5r0Djuv1Nw8DS7Uv89fYZWBICld8gkr0SSVeKGjEb2QHEde+iFbRie7N6pBHRT44Bmbeer+9naEirI9Qhq7HZ3JAAzP27rv+AIj1QKpE1U/VYaZI9QqRuUUAMrceJeouTAe2gSg8Tguh+3lr/9qShy2P7E+e5Ix4L6sKNE48jC3Velfbp94ceQlr72ibjP3SHHSPja4eH8w89JFlPvXnZXTNpDE9QOuevFNmgHtVzvYdk/yclMHmKrplfAeRHGFM5iTkxdKh7AV4PCFTONkR9ScPXaWoHMCphKDbZ2QrWxPz3bCbPWE8axv/vGeJgpNqq/zIH14+g5//31U1vrXEKEoHQaIejY8snXumS7Z5meLPyRjpHhSW++D+Fu+i4jgnj72BHWw2vjSc4dG/D/8GK/30/aHYl1xlNiennkS39OVx5T9D0U9SPPJxe6OFQHWiq3Geu7HuF897EvONXglOaiEgf9qBCyMdoGrqbzp+nGLo14CJ/toMYFmSK9OWK+19on2906zMAC/882X3UY16UHckg+HRLSV6iXGDnr0GF4uXT2xkLJqaPVDvv4rrwdrfujluAMJ8V7AlOV8owpwBPUoODqYRF/AkST1cwv/yj26rMbkXPZxmzgetXtze5S0ezdBt0hlRfW0fVaekGmf9qo/nhJot6/WVpuaWxUClLrxdjaEsQf8v/aMH74CqZcwSU7r1oCuquN7RJrhcZ0OmED9WktLOraoiwN2l3IbSovNjLliPPgFKBpMxiHvV8/n9rbnpaXTTQOe3W/t13lYiExp8eJtPS8UA3d6f5Rq5oU6b89fsQZAJZFzAyUA5PiMoWmAYyToS4n00xpyjyZh72lLqDfr4aB+uVWl4xsxl9iG2/Eibw4xWvLZycrIOjgdvN/ruuGE4jltk4cGxRY72Mzquyuiz9q4abPzEfSTcD3+9krGgX9s9Azr/00lXb2cPdIYTlJaD06JL43S/14f/aEc1aFfVWmagi5mKU7M58Oziaioj1r4EHFvuzR8tnZauMQK7I++Qa6pFbx4Y+tEx5Zd60GFgUGznrxz/2H4vPKf1gxuZJNPwJP4nRFuN2uiXHVu6UHj2OzNETN76d2+QqtGIkfNrAElV5RvcUZhHpDmLHMPjyehxLftQtguuWnoG55+It4ee7V/WOztPXp54SutZT+ynXYX94tkHOudU/kJqh5qImdMeQXEIEkyrnBcTYU9ErLHSYOJakkoX7spfaFGHrtzOR3PzzvVyZ3U0+vs77WJ2bnL4L3StSR3Pu4Am/71uIFfjp2+dga6kSH0aTY7rFFBlPn+D/s2kWBzzpubJ5jcSgFMZMykiCZJQJw5FHnN114L2Nfftnay6Rsdvs7+Lqpj3046n4sIfuSf6ch62Vbgt3hgWqv9TUgaj/KLwbMR11E2vmsXdDyWUcX+rKtlafwmI0Li3LUV3LTbw/JUMY/7UDhWAe7sDiX77ICaC1iDvVdcWOvtmkNx/GMMLUpL+LUEr6cpOWfHXEPz+0nPJ8DnP0QDIiVdA8fSOp7z3S2dHl6UbEbqBjITJxscpeRvO90UQs/OTCbDfX6p42/htZBorAbTb/diOI2anWcDBnLtGwjdaMe+N3jXO7DzIp78UyzKWI9jvHzsCoJL75Uib326j/wxc8b0W8dJByTn51wTtKZkUeI7oRvL7KGbOU0xPj3S0p0Ezrc9luIHZVmFBlxrQmpbds/L9Bh08x1SHLu2W7ltqiwv61t6X8oCE0wSS7JEXnajvYWD/mL/FbGC05hczxHO6z1Rjh4YRS9m52ws9pGl19wrttG9lOozNUzlKh1hIB+omfnQbT+dhfZsimsiMHO93ss1WPTtUdzCn3n8VxdOzQRlFTsOgPI0qfPLQIPXzyW3ofNZIxrNEfs1yHRyT9eW4SAAR4mZHfRk759QHK6XDHDIOee0YBVeeFI5MmajjqHMVr+47k9z2m3apa9EtsrqVbbs89IndvTAhDm2RPJCS4VLgdZ4iHg0LBLp/Rr9KhOm+1d2doY1WT3z8KdaxcaWtt9yPGgDn+HVY2WbJzozdNljDNJ++hTV1QaI469nZQ0tbcoRUK2Nf+kqmY6E2K0dbc/RnS/bNCz531rCj6cZ5evnpQRPAE/Zp0s116KB2IqYab6yXQkMDSE8joPy5IxTkcu4jw7did9JWUNtw8nf7dgyG3HPIXli5T/3SMAT0jwbrso6Lo1qr9e6itPW8V/v93Nvrtdq0V+Gq2idVrmjyzTjdQxxbncUDvSXAiwM8mHyPK08Y29oQL5ep4oODNhl5t5Uaxgx/yVRwr72yTpxe6fnpfsjnZaDbprbQF1WsHwmdPPOUpUyFnxo3CgDrusz8hUesNJERx/6PiPE8YG6tDqVtzXgcGkuA/sq++FBbkkwO+TbeNxKsY6wdgUNKtvo7Mz7Nazl7BSBS5FHm0dIHU+LYgfJdpDz0G3BJTqsv78BUSdft/oKxKPx+G8r8PBGay2qGS8yF4T93LR7Py6u5HIH0w+RZaokHfqD52grusUIEL6ES/NeAIsStvJfZSuvKFMYz0mZB06UDPs4+JeveY7im0q5Zp4P+vIHhuAEiKdIjffp2psSz/w7RmlirJ7WRhyIyQ5BfWoxf2HeOixm3Ls8vRKJZycWyJ+yvv2qrsEDN8ZVckTapGWHaBoJbQ+mu6TpYfXZ3GCAzHUwV+87fm88x6n8rFtl9eDhQ+mmHyehwM/EZuOB8Ps3KXIFqIeNiz+7bq6n3W6To5yyPDLEW6d/LSHRBUUtNaQOp2c/sjmvI4vXM/7Y3DlUAVMJxOSaw9cf2yOhnfYYw8fue2tZ4HrddjZCFS21/c3kZHU0CT9hladQ97jFlDPgaMr4IF3cdbUaYfeKYTRnWTPUgk8+zowgsBzDwo+DITuPfTrll74mdz/0C7XMcVp5Kcegv8jUrX3N9UlU/Z7mKahLf907q2Kql0KbAy9Yiu2ftuEOCpkBvGp6xIJ1V4ul9TDBWy6dmmEfEd9Pmrs42NzTJIxPRIUK1tTN4kr5TaYfG2/LdO975qlsYeT427tqrXe9TwoshGNPX+0Qo/jelaURIQbnCUr2saNCndU0Q/XfBYpQZk10R/7++Oggm8aTRibHJ6Y82GvnX+YxFt4cNg8f3pT8xzgGTx3/po3sWfSlHX9u8NUFmvd5gC7UZZZ+DQ5Qr1EcSWEeenQMK318Orwzsari4k/uqONGB2t5BtFwXAd/bAZD2ndSigFb7WUblplWg503VSzz8Riz2NVDXbkte3b6293kxYFkMgbi5TEbBdy0ODytIDquX+q+3ZnPxFtrNqeOT18DxfuugScM0AMUx7tvkl5bMzmnRDkOPbxWUlCucEHJ/xQCCens80V7C88ZgiiOtdwz8c7HjMckg7byq81de58XNX9JpKOMZCzN9Ghvssa19+GV1lh/hhlDluBoGRaxJ3yE4TG5BoktiteZ0HC3ArB3ahUIx7NF7c7zY1TeTn7a2AMUjT2I0dNvLfdmbfp6WEjpV69tZ5en93WjXTxFqqJfV12rnqdj3+T/DlIxN78bCLvQXA5TOKM+13VeW6PxBprfZpz9pBynsY46moDZGcb7j9UEbKHYLHe/zppWS9xWErgEImxO6uGxsb4OpmTfHZyIsx3+IXnM0O6KGqKvdfjDb/QRecc9sZYp0/c9ohFq/6/dmKfmeoXgtUWBh1bZ7207OZ9ayXYdHP0bLQzJLTHzhmPYz5nvgJnCO7Irn88fk4ZdEjd75DrJCL+7k3kE5ZcZqLTTQPZAIF0Dl78dsTc/lD/VlgipAivteIlm4V8t1utwqJF7z9DKqe43exMl00wPlL69RdDTRDZtTd2Z+csn8t29mj8vc3cHi7fZ0/gUYPQNm8flcPGRmwXM3KM4Fk3xCYd017tc+OdO4cR+9rQx8GBg9U/Cpw6aZDyP3ordUMCwT4Y/oYIhUOvdlSdMghcEHXll+42K3F9tpWIPKOtqtbmMLEVa8gdUMk/BB/7XR1IgF5w7UkMDx3rp3/Axxn7j4muHLSOJ3Ew0zQ04YggI7Pz1jrxLDKiLWBuvb0NLV17QoUDbz8F1EPd59pnxd/IM1Q5e97uFjF/lZKn1g6h8zr4fiqHtqzc0aATCE7Neytv3vwccYBVtS4eCZSk3TR8JS51BMtFDdWIK7d2LG/JVnXtfjzoBHYYnSfBvQol7XDQznU4pAYtbOp+iSn5xrvf2DRFerUbcTlw2aZKHOEVXXxadrAFE1yt1WimRlzbIwJd1y73Q7Gxu9O0ioRvECV9sHTW88h6+dEdbh13ujE4R5HI/iSDp6f4iz33M1K11BWj9bt5UkxxKiBQNbObjWt9AX/YRvEiyViL59KMJ/r+fU57tlfbHhNM/vlY9j1fChVXq7KkYZ9Nrl8z4clJyUbRY6b2j2TWnfET9ayt43fbZWHcn31CtTl+Ko8/4sbpeIcWz6E/pSoY/DyPL+0XJ3Yh3Lq3r4wC4MyzIeP5dLEe9rN7uiXELxJqnap17WarfI31YFMRzVX6NKofdImZXkQk6eCn7qa9v2s/O749m1d+O3X/R3PRj3AeTd+xpMVEjhHkaWXkeaEGOarits1Xt8/17M9JmLpWipyUYYk9vx4eyem2UqxkHn0xWls8r/+L7c/e3SsFsCUbwMVbWwue9n+5IaYGu0QqOoXTWDeHI0fr9Boh7vfSh9W7/AF4j0GJZnhbJGLngdB0dnRoospuF8sEB4Ji7udliMLnsifFtmRuC/Gd+qWdtj4IG/FjK4Tz3Ae9Mw2MCBPHDj4SV2hG3YW+W/3/PqMGLxQffaQJ9oZbDZ0UYYYCAH8oVGIinbvk10Edr4morWflekZUxoTD7Hh1Zu7doPDiItcxH7ft3u9ve8KwYa/TqL5XIscxD96pdVzTD9+pY68b1wiUhEck1jNv/uKOEXAflN6dZkgzvGmu+YxHm0eQUCA2DDsVPS47I4yQwPlF3/FsdYS+MiusF8TTYTvRSt/Xnlcl/b9sADudFD6CfgVDLIonO7JD7Alx3ghlsCM2r9jxoSUDt/1pp80K6ImZ80sutXYcx34r7LpjyZJNxwwiGzufWAs35oo+jB1dbfZ4Wov1MPVH+OiIj6Fdds5376sORJbxXTeGQ+BXO6TZl+agj1Neu1s2OyYnWDoejT18RsXW8/UQ3M0pLlKfuXrnv79mDqMV6VAc2F2/jXMbEZBQ6laYxw+kyA13jL3s7mF52jBL9f21DKiDC8Hl8LKo8A7AExxcu7PsDIMdxoMnQHCi74lpGc/9d5vdjheakSlEv/ZOUlKM//5Awxps2lgLmZJ/sSIaHns1oakgQF7ScHqFIfZwy3NPy3UmgKDEX47Fc1s7Yo87xuaHBX/bgu19NXmAB1YawNbhPL57t4TclQo/Z8g7Amkab93//lzIdblkzjHqVqLBVd+1KNetW20z2JcNfsVf1kLB3EKWjapz4CzeaAz78zuZWF3VR+d9HJLG821lz8eDOc3J4n16CVKprrkOq7TM8x1jv8IFlZntMZ97rrYhAuXPM2nh4zwHJLmUA0XE1qaNDv9zhoDjfL6TJ2FqWtEIjeS+mrooGt/4WNNalHCStHw67JqROVDEOgcP/em8x92/+z92UkuEzVzWNkc2bPA1/Tw8PTUk7fV4UWEWGKLzfRz8a1OO79xekHOF0G+b24VHdDdHlxrWoS/Ohia+fWrEOZVyRYHMYbu3GgFF/Thp/PYTqKzG0uLPPHztRHqNtALabta069akZcDI9+6RL+TgK+31irIU4JM+a+8+G/Hu2UmTnZLGmQAcrLvxb4t3Q1azOztbWPQ4Infajs1quJVJ9FP2JOZHy+AWDdwjeEtnuammIGyA9pnxXygpjgt87Wx47knjqv/OBIta4SleMl7jPtdPEksuztU9dPB2aViu7aZkFyTP/5/tl/jLNEr7YSAoi5LOrDtNzH1tmYumOXl2N4dDnhYbb7qWPHgA9G4WxPtsp7Vlx+EYD7YhTnRixXkqEeVf5La827gn4L9tla6X0ZcH8nVEVWz8n2s3k6N3r33Hp6EFkjd37LpFAQ22bc26azZkIU9Vw8d84tVUnakjBIZU8VPAMLDJ5i5QEG2Fo6S2LiSQmgHqcwiM/D5FcdVjNoKZPhkhDA5nehR/FgTVrn27NV0/O+iCVPV2EMWLhzT9SDi52Dh2P7/frnSPa+u0xJR/OJPh5/OgwUyx68fTbam2I6tsHjYL5vDKPdrHvIqgkgfe5X9p/q5D1xk01DN8qZ3Zfk6T4ZldJ/7uioo4rJw+uC/2Har//dQZck5ZSRyfsDVvwdSXeOiyNellL4LzsWOmV4JOqadY7nQxDGeqI4l3SbNtBgkfbb152WFnXD2MD6SAk+80zcGI0WuDLvSdqecheCBoPuRq33sP4/6ZWp4smhtVk9TsAQy8dzPgn83dbrv8vXKc0V/j2FnPi809/uZNiNzfe1Igautu5mxLJNH8GSmIYbFr5sk3pg38fHyj9bFvSUIQDFdkIwT2WgshbO3QhBm4+qqOoGvyZiuitVcmEfFz0htqsH/NdLKvk2x/Jhq9nMGMdQsA98CfbDU/K89wgR/baL06St0F5hd3ex7Om5PAod0cwwNycdRykDzvsbFJWytZin/df9I+Hx51ddhw1Tue2couPAJ2tkfObrvGgTVTvYxgCL2tDzps9znCCPJgEQttQPI9Hsb7lz9YstN1h630ZwWmQdjvNp+JHSL0lH7vnl0Bc+tYxem391Ml5N6zgOsZcDCpdqeEM1P1NPL7GW9xyN4SIy+rw65qXO7z8JSHpP0ct/MIww2BwF4oDvX8BOtRo87PCQmvw48vG6n22/gxYbxzloYGI0S8ZAl9egx7jQtmyCEJxWvTcC7CYy77CB30AbWfIXyELbuCcnf9JLCeaAytzf4Ua48sIgHK07F7iRCdf7udhSf7zVn5/f66MlsKjLTFjnB6BM7wFtwHO63Y5ChOp3iMSu/XoQK2Qrbe+3Fy9HFvP6MWsP30RmoLTPa1dS/t3q4RGa1om4pMykmKyzLeIx/HOX59pMjQL/sNnia14MgP80vGQ+W+/9Vh2o+fzl2vquh5egBc37b8ORJfG/Qd1tk41XtEUrKgS82b6HOlaIQ5ZYrPiloJw95agMxJ+f5tqfwGT+/zIbG67r95E+6Aj3f8p8y/B5gpTv0cDmkH4N9u1LLHIVoud52etrZg+pCDT+fZib9sOH5tHfalIPxcn+3n8bbrKXiu7DvxHhv2c9TQxS3/HkiXS1fbQOK12fHtgbzukp0fN8mkwoGXMqM0uMzE26cVa9Nq/8dphC707aYmEuuXwQNOVeTi52t8agbcHVyhlc1xdL+3PQGo3Jkki8v8OkTTpvIVnj4qxlI9AjCI2FNrhhhx3lg07JCq7K7ZDmtb9xFDI5aAvNaTvFAP3ZHddTmiyCnkKiK7WecJKH2eeH6TvpNHELTedr6yY/epCvXe8os3+vu8I8tMtt2GVsPNussSUl0/a7bsknHpuspq7yjU2j6n2JyOkXoNpYa51YanwXtRTqfnRLAWcF9+jtX5IwOcNKUstkJ3pA3HgE7/jZ8aOyHK7mjtnGxrO4dB2ZsolFJtAg88ZFA+aCAxSlRNd0M+Iu7apXDei0+L7nWe1VK2MuxXF4BDWJ3jc/+iw62nbOMHC1zXsaVR+UgwWqNxYoOOdY1qVmfeEZ/elt+MfoN7qY7uSIPRxaFY3NywG2snNnT5XKbP4YNfzk2e2eXzMBy2tXTbnwarUDqEeeurXWb13GEEzU87+Dyc+ufzfhPR3xYNvrsj3kn29Hy7qSNhRZ3cfcsJfY5gXgsIBeXZ/dI+Zw1aS/M4LOO0x+fPMvnnp7RsL5qftPLL91+Xx7lewBJVvT9NgQb3QDXZ7a5+5jzEKM+3jTzey2fo28B0yHkPrDg77VZ2jw5bsevnOlPp/rq7Y4VN6bhA2R/yt8sCtPPBNB/F4GIhUCogcfuxD3TPpTqt4fpuoewaqVs17GDfx+F9p23r1jNozrNnrl7mzLZOB5H43XuuMWLBzw+nM7mrLnffwWtPg3S87KXMNlsfp4I9LQ6Hlt6eM4IPjZPGX6O6w28vtPwi2U0szqPFlIzjZ9cZx7et680ZpPXbLeMW6fy3wWcZD9TLw1T8VMUyB3+p6ZgWdj+Ig//seusi/rQSSLl+wMnDfmhLO4SBgGiyIDRis66H7GyFlmhP9+U4xsdB2eB7z+cwFLrhAzd9xHq3Is6KP4mz7c0+VScITs4FsdXu6YS39WA6Q+fb47qRv3+Rm7SLgglTrLifIQU6nY5PQ0v91Wro2MrlsbExjdlmPh6JoQ1QI8Gu/JkHLeAxuD2FyV67VIwvyEZoAeyHhDTXkJwT2nYa2xB3UmE9c0X8mOxoBxbPKG/46q8Qdz1AJBZeXfbvcJwP4LE9lyam/FCsUPftDtvfLjBjPIl1rS+p56PfewuGzOQsOBSrF89jdzh0/C6U22dacynITytk7v6pF2Tu8jpy3IbtorHRuAhDOoZchTghcJgu4uTHSPW7ye1ofq/mG88qdMg0niIyOffOMAuEnes5PZy4wWufB8G/cOm+3BaD2coDDW4dJEZxP2MbkvvrtlpEJa726uI4vsgt7gtva21VOCtWeU2hJst1TwOrqb5jSB8K2t7dpsNxiacj8h43vkPtfj/lmsbnHjOjqfvZBbB/ZoXtK7H9XmshjxhUnKTcU7U++6AP+NCf/M1w9fezSR4XPK+tJF7M5nurICTsa+0dOlIESZa+HcdOedFFKEkdBfHg/CCgf+kGEhusVyF4yjxruLUjHy4hKdi9hyVxSRxs+Sq0Ool1XUX27RwORScK2p2JLBbMfRv2aa6I6dmsyMd13Qqsj5MdoHYC8DoPkza39bg9/N49GcgSxs82AVzaz7Zpe6Ly/am7YcRPszIEBIrxZowJKY2lXEWefEQJ5vietW970V5aAfZ9i1llfZOHdHVlVQKk9vG4L3v+WZTLgzw1Ix9aq2cjNuXKFaDjrKN/TnSbYXS07GllbUfjKVYlX+Fon9mtyMx+ZLr2HaQF84GDn8A6Njcu48CnlobLdDjK93H0t7r1C3xYj+zXuH63Pnt/tWPwa8MMAPtpJXhzYW0O/CoIGUEFa9s5orV9ymkXbGcMGSbsFrYTbZbd39C9m4vB6VftPexWv6IEn4/deQoDZQZKk7Pt0UOoAOiYl8Oh4hAEb/a3EZ7T8ucHO2p9GrtQqZRftrX/SfbZye9yPsusRQ762qrHUeehtGGE8PlYu8L+djT6i3V4agleHoJ1tX9WM07qRsiF/vIcqnTeqjqOgejrsUX1tw809MjPCVEQoNMln9XgJN/TFkZ7OHDq4Ctqki7K9gbX41E6VA62m08Q8OnnTjElioO22ynNctg36/qM090d0O1tRT4D9YKXiLgaB1PcDvxEx15rAibPMRDrykKXHBva/ol6UM1W27PMgOX5Le7Hk/rOyy9KEQbYnF/+NyLCLmCvDoKtUU57GDs0Zp3sqE7H67R406HNbJvsPvrEA4shLRILvPhPK46xdj9Ww9CVbYi2kMFEEohjJfYer6qDbRUdzDn2CbImvsV3owmuReuA38cJknUfoq/BjPL+YSI7qkn0Wnz+YmW+Dl6Yhnnu3I7kJhhat5uc56Ev1WXz/hct7X0BFz4baV2nZxkBzgpEgapuxIdhrD+SnU+PBe3QiowZdMWpx4N8OqbcRbZCUluuOQL4h0C2i6kmC3y1xUiVpMO4VeuXEmoZ700z7BC3cC1yqktZlZ5TowbNqnUU6EllTLWZL3qnvKdwvgrkZDwcnR76f6z4hnw4QK/P6u/b8Sr2Ns3hMBcbO++R8D8niV2X83lunxLk+Xs74za/3PVO10cd0unosdlaeFIlFHianjrXhpBuPd0weLXa0JaZY87MZ665hq0Oa9a5Lg0RihORX+2cw6kTe3TH5Uipjwr8aSjhSUO9g9b5+tys0Q8V7NmI5M2Jv2supxUwoQnRq2X8dVL5uvlsBXZoO1XUeu3lSDy3Thwr73ejS42UH0Mr6rjQ3Yj/1GS5js8sWsri2tIID9ZtGD7o+eMJcaP08/z+qB6eaS7qclSDWPFzOjdlY2bPNPJVl9TNA5KNAIch7PpF5v6UYk7IQRRDX721YrBTX2rK9gDdaQk5T5iDuqwKHRaVq/k4J/B08M3mwW0Knx1C2Nn81QK37sVBf4MuILCgitz2/t4azCnt6qilIfQQZPDnpr42iGhIH5ZbT8NxvGyHpXNWP+fuWI9+9/vj+6Arfj+H+bl8NCJnYu6l3cS6+dl+UN785PpOLQAE0V/9F/nLTUj33KBm/SwbwPg6nRxAfHY5G/x+zNqcZjPzFzheMWhfDa8pjCeguAQmAU3X8WCbCyrQZ2/78eUI744N2qMB3Pfr5E+bBjnObGRvgCCs2inW5hxHsfqsL/2cdHITjN+7wbWdrewgVjmt6e758/qytrk5cTDEpEaKtHCGNpNb8T2CxWM583NZI5odGXEY6xCeewjEIeB25685yUVcggRZ6EDrdO7o+G2TSEdkPay2sIvXjd08KpC3DeY/qqwfuhdMjwj8PpKpd9f0PeJdDmabNgEEbHSTnOiHPYRc9rOt8dqvZWOx1XrbKv5EEo2j0x9V5vHaeFo+wyz6XMe+o2tLZMGfr+uLkGoGqb8EG07lrooNXNitU192opXtfEoUljPjCDnwZ13DQ0tE4vd1tKgtgY3LLtNYYPNRR8gGT2Ngp3Bo2n2xh9dl07enu1ODTrTa908634kbEzQrq3LWvtcGP/Zk6e25UmbwkBWNgUL6HlugW5XImT72xc/ciCyPfpvELsOqu/+SkJyciOuQdJSL7OXvcTm+1vnTaWUKmoB0frY5JjKbnpr8N+rN5kux8RCK3g6ZulSzpqE227AO4iUWZ7/p7xGl/XG0r03PplyPBaXacJsK3RMirZr4zt1FUMrr1IYsFuAu4r3tI3l/tgViMkgs/BGUjepmbXe2HuDbC0AWeVmVsc8KFvWKFQj+6wRCgoR4ef3NcxMJ9hHgDuGfUFwUG79En0WRcgtk85CrhZKkH3VKu1UeX3ZxyGUs8vNfEATbUS46i5g7M85LG0MGdleIIYB/FipMi7AfEvFrKOnkx3vXeEF5ObT9tStI+WoRYZpxaYheDiaxhvhypMjQNPMFXlv27A5srujj5S5sjfxR2x0Fmb3iZzcE4zmd+8+xGtP46jCS49eS4azN7VKqqyqJD57d/Bk1WClpBMHPRpvr5Dn2PSTZ/5QRaMC6Hm7OjX1cGpA8+uP/Gfagf31vQ+7PuOCi2Od4F7UPQoDevUFwQW3b5cw8cFx5cMnH8vTPSoh3Wl//++tmPA3kWA12qP8s6Tgql/kIllLmlpdep+dHr9r50HvTJ/4hYI5zPg5nLb51HNwh8mEDbHsvPdukR7meVjGkbIwVvnc/5mtXKFB+Nbgeoju5x1EDEuW918Fhn37jIcvW203bSQePn/yMPU920H46ShjHb+0ZMKHWsE2fUsLiw4YEOpLns9sGKZCdTi1lXHL3qMSD8CwnG/B5Otdvp/I2vpx5Dj9dO+06B5EfFusi8UyehZb52aCDzJcD6jOTDB12OCIeEoohqBBVbB77fjb7Qp24LTyeyh+SRQ6Fd0eJ2hCHU0FWpsk2eLFNzHnJUeQGe8oAYKDGVjIzWwIrlAVoVVY00A+bzL0ybk7Uzv3sec5OM0W8ue0nOMuldQo7TqrM5mjlt08z/gBKz8oBSf/K6fjYXNhW9TMf0bUJOadEOV3/cPErQ2Ec7uj057wFd/8KSj91YFr7HxqXu0eTasH6DnvK5m8Lr5jH9PN99jwg6xNPlZjDiaDrKaOPUwEIk8962Spxa6d8PKxT+qDUiANxkiHMsGN/AxEZmeiMK/5INBnIebB9fnbD+ewN4yk3M8c4mbBiav/ghxPzeU/NdgsMN7r5WsOjP5kzDrdClIsuj7jIZL+cFjaOf7Foht/hnYnk1p5JhB0bBfpZB49H34xBuu32v59DHDjm9/i3OlreoTjTtZh41kIZIXzbY6yQBwX0ICxdcRwn1vfaEois4bIFTX5INGPXXJqv3/9yEgS3+n8aBaHOzZQ4m87/BHxxDZ0+y1OOmWifePtlYCWTxlpLMh8bUTkUqGPUCz1yx4PhRuXbpjABjH5OCeFllPk/7ik38rwhFzkR3xQRipeBBSOa/SxI5mWH5hF/nJfpd4uQ87JTZ5Q/mjvzx5tUgz+iL/Iy0VVehlvAMAu6r517OjmPCi+73I7//R8Ooj/tcbc7D/JHoRT+SO7Dy25TCTNIpHr+iG/Hy0iC3GYxxrB12P9OB+0AUZKDOBmXNPcn3c/LyEiJZoQ1qYLYiQ0vQyrfDZvmZXg6YNQcX/nZ3wFtSXyZfR4NhVXiNHi3JPoPsEp2O0hexgHx6rF1y6HJ7ujJH+dlrBJOToQ/u+aJ0sa5zKbwykH8EUiHlyHYWCdCeaMRnuQlLyNOYZXEzrYKVi8irJEwshZ/dPvnj2gDvAzUQp3LwjBeRpsShzxcykr8kaiIl/FUs0og61BbZHChaoKCpKjgOcAqoZs8RkEclsMqUYBglSDTHo6eovEzqwTx+dgTOl6UW6IZ5CIDG905/ngSLvNHvQD+SBDNy0gXjYfgrVgljoD+ueujf/OyT3RnjgSqM1glehe7pnxiDVaJo9ZZJXXmLS+z2NhUWHOAP2Lb8LIo4vFH4mWPbtRYXuboGg9ddDJeRhjJKqnTL3kZEadNvg7jK/5ISszLmCJpbwGUJ1ZJTXE0WNh2zSGIjHkZUb6TnrBYjS+o9WGVKOOzSizOZ5V0D37ijzizvMyshZeRcLFK1AAPT98bj4I/EvXysi328keMJ16GyuI8XHICZ9zjqbFKiIHsUenINFYJseg+6ymtcYo4FtX/r647um0zhqEwulER20FT76KukA26RQeueT7+eSiQl+AGCYHEIi8vKYniJT0I+FZ9d9cMOlvqNSHIlGOX0GppN52kNg8v6azSs3xnM5AEbJagOoxu5CWP3lxl1rE/ZkaiNAahEQTMPFjMSxoE0ZFWWbNzJMrX7uCvbACpVGa6rrykl555yaN5RcyaBMis63zM0tzMGt3L7L3GLKgMYaY7zEuojluPW+nG8JI6YKniXh1k5m4OL3GQwFugN2coHMi7OadlksutF5d65merKL/1ZkXAO1cAVfRpcAd7KoQ16ph93Q67PbYxAI4ZL2kiXPVzj0oza7gaMwcukzf2lnv4xaQ6XvLoUpHCg65q41ApDk11VNOOaINGQrFwmnd13khnaAQfi2bQQjYnB+k2szAcjoVpTCwM+GDR+S4roFqAVNKQ3VFIyx2yN33cjh15DE1JwkIXk0Vb2dAo5kouigwikSCaBSIiIFn9fHZjjhu02cVCRmFRQoEwPP/C1BDqhHAZhFwg0T7I6rOw+CysPYue4oSsPHeeFQTmwwXm/wbmTwLmt7+VrdjzP9na3sq4yfzh6zkpuNfHsU6V3Hotwfpb2ui17OuKCZn55nLTdMf4+pcPDxCBl4OXnl9ffl7eXzZ9ffl1hUbJb7hu4yaGRcYbVNGvDLARFzdLOxuOEbdct7FavMrLG8gFMzFwivIinQI5nzvMaQDZc+KHOILWOpFHnkMXnpglryJGT7STx1HAJ07KG8nuE2HlqbT+ic3e69NOKXiiurbb752CaPNfq28c4yJJkdERwxODihrHMFHmcyOqc1Qn7hVtbfmciLkOsm2WE2s301Cf/0TpItiVXRz+3OhuNO4pGYh8bS6O/1hWaCznKY00z2AIQzb5WDbRDpNUnss0ep/1oJaFnC2X0B7LUGZeXHkNe2krSG8fy2z6Bzzvuawn3ATpbRnRRoUM+1i21Ia9Ei0mVf3Ktx/Lsvr10u4zBr5vobgJ/NsSc3725/ffH/8A1nxzlA=="},"max_retries":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":294,"cells":{"question_id":{"kind":"number","value":3514,"string":"3,514"},"question_title":{"kind":"string","value":"Play with words"},"question_content":{"kind":"string","value":"Shaka and his brother have created a boring game which is played like this: \n\nThey take a word composed of lowercase English letters and try to get the maximum possible score by building exactly 2 **palindromic subsequences**. The score obtained is the product of the length of these 2 [subsequences](https://en.wikipedia.org/wiki/Subsequence).\n\nLet's say $A$ and $B$ are two subsequences from the initial string. If $A_i$ & $A_j$ are the smallest and the largest positions (from the initial word) respectively in $A$ ; and $B_i$ & $B_j$ are the smallest and the largest positions (from the initial word) respectively in $B$, then the following statements hold true: \n$A_i \\le A_j$, \n$B_i \\le B_j$, & \n$A_j < B_i$. \ni.e., the positions of the subsequences should not cross over each other. \n\nHence the score obtained is the product of lengths of subsequences $A$ & $B$. Such subsequences can be numerous for a larger initial word, and hence it becomes harder to find out the maximum possible score. Can you help Shaka and his brother find this out?\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int playWithWords(String s)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"/**\\n * Created by zhengf1 on 12/18/2014.\\n */\\nimport java.io.*;\\nimport java.util.*;\\nimport java.text.*;\\nimport java.math.*;\\nimport java.util.regex.*;\\npublic class Dec101_C {\\n public static void main(String[] args){\\n Scanner sc = new Scanner(System.in);\\n String str = sc.nextLine();\\n int n = str.length();\\n int[][] L = new int[n][n];\\n for (int i = 0; i < n; i++)\\n L[i][i] = 1;\\n\\n // Build the table. Note that the lower diagonal values of table are\\n // useless and not filled in the process. The values are filled in a\\n // manner similar to Matrix Chain Multiplication DP solution (See\\n // http://www.geeksforgeeks.org/archives/15553). cl is length of\\n // substring\\n int i = 0;\\n int j = 0;\\n int cl = 0;\\n for (cl=2; cl<=n; cl++)\\n {\\n for (i=0; i<n-cl+1; i++)\\n {\\n j = i+cl-1;\\n if (str.charAt(i) == str.charAt(j) && cl == 2)\\n L[i][j] = 2;\\n else if (str.charAt(i) == str.charAt(j))\\n L[i][j] = L[i+1][j-1] + 2;\\n else\\n L[i][j] = Math.max(L[i][j - 1], L[i + 1][j]);\\n }\\n }\\n int res = 0;\\n for(i = 1; i < n; i++){\\n int v1 = L[0][i - 1];\\n int v2 = L[i][n - 1];\\n res = Math.max(res, v1 * v2);\\n\\n }\\n System.out.println(res);\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'playWithWords' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING s as parameter.\\n */\\n\\n public static int playWithWords(String s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String s = bufferedReader.readLine();\\n\\n int result = Result.playWithWords(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\\npublic class Solution {\\n public static void main(String[] args) {\\n Scanner sc = new Scanner(System.in);\\n String str = sc.nextLine();\\n int n = str.length();\\n int[][] L = new int[n][n];\\n for (int i = 0; i < n; i++)\\n L[i][i] = 1;\\n\\n int i = 0;\\n int j = 0;\\n int cl = 0;\\n for (cl=2; cl<=n; cl++)\\n {\\n for (i=0; i<n-cl+1; i++)\\n {\\n j = i+cl-1;\\n if (str.charAt(i) == str.charAt(j) && cl == 2)\\n L[i][j] = 2;\\n else if (str.charAt(i) == str.charAt(j))\\n L[i][j] = L[i+1][j-1] + 2;\\n else\\n L[i][j] = Math.max(L[i][j - 1], L[i + 1][j]);\\n }\\n }\\n int res = 0;\\n for(i = 1; i < n; i++){\\n int v1 = L[0][i - 1];\\n int v2 = L[i][n - 1];\\n res = Math.max(res, v1 * v2);\\n\\n }\\n System.out.println(res);\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'playWithWords' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING s as parameter.\\n */\\n\\n public static int playWithWords(String s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String s = bufferedReader.readLine();\\n\\n int result = Result.playWithWords(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class PlayWithWords {\\n\\n\\tBufferedReader br;\\n\\tPrintWriter out;\\n\\tStringTokenizer st;\\n\\tboolean eof;\\n\\n\\tvoid solve() throws IOException {\\n\\t\\tchar[] s = nextToken().toCharArray();\\n\\t\\tint n = s.length;\\n\\t\\tint[][] dp = new int[n + 1][n + 1];\\n\\t\\tfor (int len = 1; len <= n; len++)\\n\\t\\t\\tfor (int i = 0; i + len <= n; i++) {\\n\\t\\t\\t\\tint j = i + len;\\n\\t\\t\\t\\tdp[i][j] = Math.max(dp[i + 1][j], dp[i][j - 1]);\\n\\t\\t\\t\\tif (s[i] == s[j - 1]) {\\n\\t\\t\\t\\t\\tdp[i][j] = Math.max(dp[i][j], (len == 1 ? 1 : 2)\\n\\t\\t\\t\\t\\t\\t\\t+ dp[i + 1][j - 1]);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\tint ret = -1;\\n\\t\\tfor (int k = 0; k <= n; k++) {\\n\\t\\t\\tret = Math.max(ret, dp[0][k] * dp[k][n]);\\n\\t\\t}\\n\\t\\tout.println(ret);\\n\\t}\\n\\n\\tPlayWithWords() throws IOException {\\n\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\tsolve();\\n\\t\\tout.close();\\n\\t}\\n\\n\\tpublic static void main(String[] args) throws IOException {\\n\\t\\tnew PlayWithWords();\\n\\t}\\n\\n\\tString nextToken() {\\n\\t\\twhile (st == null || !st.hasMoreTokens()) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tst = new StringTokenizer(br.readLine());\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\teof = true;\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn st.nextToken();\\n\\t}\\n\\n\\tString nextString() {\\n\\t\\ttry {\\n\\t\\t\\treturn br.readLine();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\teof = true;\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t}\\n\\n\\tint nextInt() throws IOException {\\n\\t\\treturn Integer.parseInt(nextToken());\\n\\t}\\n\\n\\tlong nextLong() throws IOException {\\n\\t\\treturn Long.parseLong(nextToken());\\n\\t}\\n\\n\\tdouble nextDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(nextToken());\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'playWithWords' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING s as parameter.\\n */\\n\\n public static int playWithWords(String s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String s = bufferedReader.readLine();\\n\\n int result = Result.playWithWords(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"playWithWords(s)\"\n ],\n \"solution\": \"def findMaxSubsequence(seq):\\n length = len(seq)\\n seqLength = [[0 for i in range(length)] for j in range(length)]\\n for i in range(length):\\n seqLength[i][i] = 1 \\n for cols in range(2,length+1):\\n for i in range(0,length-cols+1):\\n j = i+cols-1\\n if seq[i] == seq[j]:\\n if cols == 2:\\n seqLength[i][j] = 2\\n else:\\n seqLength[i][j] = seqLength[i+1][j-1]+2\\n else:\\n seqLength[i][j] = max(seqLength[i+1][j], seqLength[i][j-1])\\n return seqLength\\n\\nstring = list(input())\\nseqLength = findMaxSubsequence(string)\\nmaxScore = 0\\nfor i in range(0,len(string)-1):\\n left = seqLength[0][i]\\n right = seqLength[i+1][-1]\\n score = left*right\\n if score > maxScore:\\n maxScore = score\\nprint(maxScore)\",\n \"template\": \"#\\n# Complete the 'playWithWords' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts STRING s as parameter.\\n#\\n\\ndef playWithWords(s):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n s = input()\\n\\n result = playWithWords(s)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":295,"cells":{"question_id":{"kind":"number","value":101,"string":"101"},"question_title":{"kind":"string","value":"Interval Selection"},"question_content":{"kind":"string","value":"Given a set of $n$ intervals, find the size of its largest possible subset of intervals such that no three intervals in the subset share a common point."},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Medium"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int intervalSelection(List<List<Integer>> intervals)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.util.*;\\nimport java.io.*;\\nimport static java.lang.Math.*;\\n\\npublic class Solution {\\n\\tstatic class Foo53 {\\n\\t\\tvoid main() {\\n\\t\\t\\tBufferedReader br = null;\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\t\\t\\tint T = Integer.parseInt(br.readLine().trim());\\n\\t\\t\\t\\tfor (int i = 0; i < T; i++) {\\n\\t\\t\\t\\t\\tint N = Integer.parseInt(br.readLine().trim());\\n\\t\\t\\t\\t\\tint[][] arr = new int[N][2];\\n\\t\\t\\t\\t\\tfor (int j = 0; j < N; j++) {\\n\\t\\t\\t\\t\\t\\tString[] s = br.readLine().trim().split(\\\"\\\\\\\\s+\\\");\\n\\t\\t\\t\\t\\t\\tarr[j][0] = Integer.parseInt(s[0].trim());\\n\\t\\t\\t\\t\\t\\tarr[j][1] = Integer.parseInt(s[1].trim());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tint res = foo(arr);\\n\\t\\t\\t\\t\\tSystem.out.println(res);\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t} finally {\\n\\t\\t\\t\\tif (br != null) {\\n\\t\\t\\t\\t\\ttry { br.close(); } catch (Exception e) { e.printStackTrace(); }\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tDeque<Integer> deque;\\n\\t\\tint foo(int[][] arr) {\\n\\t\\t\\tint res = 0;\\n\\t\\t\\tint n = arr.length;\\n\\t\\t\\tdeque = new LinkedList<Integer>();\\n\\t\\t\\tArrays.sort(arr, new Comparator<int[]>() {\\n\\t\\t\\t\\tpublic int compare(int[] a, int[] b) {\\n\\t\\t\\t\\t\\treturn a[0] - b[0];\\n\\t\\t\\t\\t}\\n\\t\\t\\t});\\n\\t\\t\\tfor (int[] a : arr) {\\n\\t\\t\\t\\tint left = a[0], right = a[1];\\n\\t\\t\\t\\twhile (!deque.isEmpty() && deque.getFirst() < left)\\n\\t\\t\\t\\t\\tdeque.removeFirst();\\n\\t\\t\\t\\tif (deque.size() < 2) {\\n\\t\\t\\t\\t\\tres++;\\n\\t\\t\\t\\t\\tadd(right);\\n\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\tif (deque.getLast() > right) {\\n\\t\\t\\t\\t\\t\\tdeque.removeLast();\\n\\t\\t\\t\\t\\t\\tadd(right);\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\treturn res;\\n\\t\\t}\\n\\t\\tvoid add(int val) {\\n\\t\\t\\tif (!deque.isEmpty() && deque.getLast() > val) {\\n\\t\\t\\t\\tdeque.addFirst(val);\\n\\t\\t\\t} else {\\n\\t\\t\\t\\tdeque.addLast(val);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) {\\n\\t\\tFoo53 foo = new Foo53();\\n\\t\\tfoo.main();\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'intervalSelection' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY intervals as parameter.\\n */\\n\\n public static int intervalSelection(List<List<Integer>> intervals) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int s = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int sItr = 0; sItr < s; sItr++) {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> intervals = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String[] intervalsRowTempItems = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> intervalsRowItems = new ArrayList<>();\\n\\n for (int j = 0; j < 2; j++) {\\n int intervalsItem = Integer.parseInt(intervalsRowTempItems[j]);\\n intervalsRowItems.add(intervalsItem);\\n }\\n\\n intervals.add(intervalsRowItems);\\n }\\n\\n int result = Result.intervalSelection(intervals);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\nimport java.util.Arrays;\\nimport java.util.Scanner;\\n\\nclass Solution{\\n static int solve(int[][] intv){\\n Arrays.sort(intv,(int[] a, int[] b)->a[1]-b[1]);\\n int count=0, busy[][]=new int[2][2];\\n for(int[] x: intv){\\n if(x[0]>busy[1][1]){\\n ++count;\\n busy[1]=x;\\n }else if(x[0]>busy[0][1]){\\n ++count;\\n busy[0]=x;\\n if(x[1]>busy[1][1]){\\n int[] temp=busy[0];\\n busy[0]=busy[1];\\n busy[1]=temp;\\n }\\n }\\n }\\n return count;\\n }\\n public static void main(String[] args){\\n Scanner sc=new Scanner(System.in);\\n int s=sc.nextInt();\\n while(s-- != 0){\\n int n=sc.nextInt();\\n int[][] intv=new int[n][2];\\n for(int i=0;i<n;++i){\\n intv[i][0]=sc.nextInt();\\n intv[i][1]=sc.nextInt();\\n }\\n System.out.println(solve(intv));\\n }\\n sc.close();\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'intervalSelection' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY intervals as parameter.\\n */\\n\\n public static int intervalSelection(List<List<Integer>> intervals) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int s = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, s).forEach(sItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> intervals = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n intervals.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.intervalSelection(intervals);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.util.Arrays;\\nimport java.util.Scanner;\\n\\nclass IntervalsPicker {\\n\\tprivate class Interval implements Comparable<Interval> {\\n\\t\\tint start, end;\\n\\n\\t\\tpublic Interval(int start, int end) {\\n\\t\\t\\tthis.start = start;\\n\\t\\t\\tthis.end = end;\\n\\t\\t}\\n\\n\\t\\t@Override\\n\\t\\tpublic int compareTo(Interval that) {\\n\\t\\t\\tif (this.end != that.end)\\n\\t\\t\\t\\treturn this.end - that.end;\\n\\t\\t\\telse\\n\\t\\t\\t\\treturn this.start - that.start;\\n\\t\\t}\\n\\n\\t\\tpublic String toString() {\\n\\t\\t\\treturn \\\"[\\\" + start + \\\" \\\" + end + \\\"]\\\";\\n\\t\\t}\\n\\t}\\n\\n\\tprivate final Interval[] intervals;\\n\\n\\tpublic IntervalsPicker(int[] starts, int[] ends) {\\n\\t\\tassert starts.length == ends.length;\\n\\t\\tthis.intervals = new Interval[starts.length];\\n\\n\\t\\tfor (int i = 0; i < starts.length; i++) {\\n\\t\\t\\tthis.intervals[i] = new Interval(starts[i], ends[i]);\\n\\t\\t}\\n\\n\\t\\tArrays.sort(this.intervals);\\n\\t}\\n\\n\\tpublic int getLargestNonoverlappingSubsetSize() {\\n\\t\\tif (intervals.length < 3)\\n\\t\\t\\treturn intervals.length;\\n\\n\\t\\tInterval prelastAcceptedInterval = intervals[0];\\n\\t\\tInterval lastAcceptedInterval = intervals[1];\\n\\t\\tint lastDouble = -1;\\n\\t\\tif (prelastAcceptedInterval.end >= lastAcceptedInterval.start)\\n\\t\\t\\tlastDouble = prelastAcceptedInterval.end;\\n\\n\\t\\tint intervalsCounter = 2;\\n\\n\\t\\tfor (int i = 2; i < intervals.length; i++) {\\n\\t\\t\\tInterval newInterval = intervals[i];\\n\\n\\t\\t\\tif (newInterval.start > lastDouble) {\\n\\t\\t\\t\\tintervalsCounter++;\\n\\t\\t\\t\\tprelastAcceptedInterval = lastAcceptedInterval;\\n\\t\\t\\t\\tlastAcceptedInterval = newInterval;\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (prelastAcceptedInterval.end >= lastAcceptedInterval.start)\\n\\t\\t\\t\\t\\tlastDouble = prelastAcceptedInterval.end;\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\treturn intervalsCounter;\\n\\t}\\n}\\n\\npublic class Solution {\\n\\n\\tpublic static void main(String[] args) {\\n\\t\\tfinal Scanner scanner = new Scanner(System.in);\\n\\n\\t\\tint numberOfTestCases = scanner.nextInt();\\n\\n\\t\\tfor (int testCaseNumber = 0; testCaseNumber < numberOfTestCases; testCaseNumber++) {\\n\\t\\t\\tint numberOfIntervals = scanner.nextInt();\\n\\t\\t\\tint[] starts = new int[numberOfIntervals];\\n\\t\\t\\tint[] ends = new int[numberOfIntervals];\\n\\n\\t\\t\\tfor (int i = 0; i < numberOfIntervals; i++) {\\n\\t\\t\\t\\tstarts[i] = scanner.nextInt();\\n\\t\\t\\t\\tends[i] = scanner.nextInt();\\n\\n\\t\\t\\t}\\n\\n\\t\\t\\tfinal IntervalsPicker picker = new IntervalsPicker(starts, ends);\\n\\t\\t\\tint largestNonoverlappingSubset = picker\\n\\t\\t\\t\\t\\t.getLargestNonoverlappingSubsetSize();\\n\\t\\t\\tSystem.out.println(largestNonoverlappingSubset);\\n\\t\\t}\\n\\t\\tscanner.close();\\n\\t}\\n\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'intervalSelection' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts 2D_INTEGER_ARRAY intervals as parameter.\\n */\\n\\n public static int intervalSelection(List<List<Integer>> intervals) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int s = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, s).forEach(sItr -> {\\n try {\\n int n = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<List<Integer>> intervals = new ArrayList<>();\\n\\n IntStream.range(0, n).forEach(i -> {\\n try {\\n intervals.add(\\n Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList())\\n );\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n int result = Result.intervalSelection(intervals);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"intervalSelection(intervals)\"\n ],\n \"solution\": \"import sys\\n\\ndef readnums():\\n return [int(x) for x in sys.stdin.readline().strip().split(\\\" \\\")]\\n\\nfor i in range(readnums()[0]):\\n intervals = []\\n for j in range(readnums()[0]):\\n intervals.append(readnums())\\n intervals.sort()\\n # Greedy algorithm, starting at right side of number line select an interval with nearest far endpoint and remove it from the set of candidate intervals. If we have already selected two intervals, discard all intervals with near endpoints at same or closer distance as the far endpoint of the overlapping region of the two most recently selected intervals. Do this while there are intervals remaining, answer is the number of iterations.\\n selected = []\\n num_selected = 0\\n while(intervals):\\n selected.append(intervals.pop())\\n num_selected += 1\\n if num_selected >= 2:\\n # If intervals overlap use overlapping region to filter\\n if selected[-2][0] <= selected[-1][1]:\\n overlap_int = [selected[-2][0], selected[-1][1]]\\n intervals = list(filter(lambda interval: interval[1] < overlap_int[0], intervals))\\n print(num_selected)\\n \\n \",\n \"template\": \"#\\n# Complete the 'intervalSelection' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts 2D_INTEGER_ARRAY intervals as parameter.\\n#\\n\\ndef intervalSelection(intervals):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n s = int(input().strip())\\n\\n for s_itr in range(s):\\n n = int(input().strip())\\n\\n intervals = []\\n\\n for _ in range(n):\\n intervals.append(list(map(int, input().rstrip().split())))\\n\\n result = intervalSelection(intervals)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":296,"cells":{"question_id":{"kind":"number","value":58,"string":"58"},"question_title":{"kind":"string","value":"String Reduction"},"question_content":{"kind":"string","value":"Given a string consisting of the letters $\\text a$, $\\text b$ and $\\text c$, we can perform the following operation: \n\n* Take any two adjacent distinct characters and replace them with the third character. \n\nFind the shortest string obtainable through applying this operation repeatedly. \n\nFor example, given the string $\\text{aba}$ we can reduce it to a $1$ character string by replacing $\\text{ab}$ with $\\text{c}$ and $\\text{ca}$ with $\\text b$: $\\text{aba}\\rightarrow\\text{ca}\\rightarrow\\text{b}$. \n\n**Function Description** \n\nComplete the *stringReduction* function in the editor below. It must return an integer that denotes the length of the shortest string obtainable. \n\nstringReduction has the following parameter: \n- *s*: a string "},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int stringReduction(String s)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"/*\\n * Anand Oza\\n * October 29, 2011\\n */\\n\\nimport java.io.IOException;\\nimport java.io.InputStreamReader;\\nimport java.io.StreamTokenizer;\\n\\npublic class Solution {\\n\\tpublic static void main(String[] args) throws IOException {\\n\\t\\tStreamTokenizer in = new StreamTokenizer(new InputStreamReader(System.in));\\n\\t\\tin.nextToken();\\n\\t\\tint T = (int) in.nval;\\n\\n\\t\\tint ans;\\n\\n\\t\\tfor (int test = 0; test < T; test++) {\\n\\t\\t\\tin.nextToken();\\n\\t\\t\\tchar[] c = in.sval.toCharArray();\\n\\t\\t\\tint[] n = new int[3];\\n\\t\\t\\tfor (int i = 0; i < c.length; i++)\\n\\t\\t\\t\\tn[c[i] - 'a']++;\\n\\t\\t\\tint x = (n[0] + n[1]) * (n[1] + n[2]) * (n[2] + n[0]);\\n\\t\\t\\tif (x == 0)\\n\\t\\t\\t\\tans = c.length;\\n\\t\\t\\telse if ((n[0] + n[1]) % 2 == 0 && (n[1] + n[2]) % 2 == 0 && (n[2] + n[0]) % 2 == 0)\\n\\t\\t\\t\\tans = 2;\\n\\t\\t\\telse\\n\\t\\t\\t\\tans = 1;\\n\\n\\t\\t\\tSystem.out.println(ans);\\n\\t\\t}\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'stringReduction' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING s as parameter.\\n */\\n\\n public static int stringReduction(String s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n String s = bufferedReader.readLine();\\n\\n int result = Result.stringReduction(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\nimport java.io.IOException;\\nimport java.io.InputStreamReader;\\nimport java.io.StreamTokenizer;\\n\\npublic class Solution {\\n public static void main(String[] args) throws IOException {\\n StreamTokenizer in = new StreamTokenizer(new InputStreamReader(\\n System.in));\\n in.nextToken();\\n int T = (int) in.nval;\\n\\n int ans;\\n for (int test = 0; test < T; test++) {\\n in.nextToken();\\n char[] c = in.sval.toCharArray();\\n int[] n = new int[3];\\n for (int i = 0; i < c.length; i++)\\n n[c[i] - 'a']++;\\n int x = (n[0] + n[1]) * (n[1] + n[2]) * (n[2] + n[0]);\\n if (x == 0)\\n ans = c.length;\\n else if ((n[0]+n[1])%2==0 && (n[1]+n[2])%2==0 && (n[2]+n[0])%2==0)\\n ans = 2;\\n else\\n ans = 1;\\n\\n System.out.println(ans);\\n }\\n }\\n}\\n\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'stringReduction' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING s as parameter.\\n */\\n\\n public static int stringReduction(String s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String s = bufferedReader.readLine();\\n\\n int result = Result.stringReduction(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n int min;\\n\\tint val;\\n\\tString cat;\\n\\tboolean flag;\\n\\tchar redux(char c1, char c2) {\\n\\t\\tif (c1 == 'a') {\\n\\t\\t\\tif (c2 == 'b') return 'c';\\n\\t\\t\\tif (c2 == 'c') return 'b';\\n\\t\\t}\\n\\t\\tif (c1 == 'b') {\\n\\t\\t\\tif (c2 == 'a') return 'c';\\n\\t\\t\\tif (c2 == 'c') return 'a';\\n\\t\\t}\\n\\t\\tif (c1 == 'c') {\\n\\t\\t\\tif (c2 == 'b') return 'a';\\n\\t\\t\\tif (c2 == 'a') return 'b';\\n\\t\\t}\\n\\t\\treturn ' ';\\n\\t}\\n\\tboolean reduce(String s) {\\n\\t\\tint l = s.length();\\n\\t\\tmin = l;\\n\\t\\tif ( l == 1) {\\n\\t\\t\\tval = 1;\\n\\t\\t\\treturn true;\\n\\t\\t} \\n\\t\\tif (l == 2 && s.charAt(0) == s.charAt(1)) {\\n\\t\\t\\tval = 2;\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t\\tfor (int i=0;i<l-1;i++) {\\n\\t\\t\\tif (s.charAt(i) != s.charAt(i+1)) {\\n\\t\\t\\t\\tcat = s.substring(0,i) + Character.toString(redux(s.charAt(i), s.charAt(i+1))) + s.substring(i+2);\\n\\t\\t\\t\\tflag = reduce(cat);\\n\\t\\t\\t\\tif (flag) {\\n\\t\\t\\t\\t\\tmin = Math.min(min, val);\\n\\t\\t\\t\\t\\treturn true;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn false;\\n\\t}\\n\\n public static void main(String[] args) {\\n Scanner sc = new Scanner(System.in);\\n int t = sc.nextInt();\\n String e = sc.nextLine();\\n while (t>0) {\\n\\t\\t String str = sc.nextLine();\\n\\t\\t Solution r = new Solution();\\n\\t\\t r.reduce(str);\\n\\t\\t System.out.println(r.min);\\n t--;\\n }\\n /* Enter your code here. Read input from STDIN. Print output to STDOUT. Your class should be named Solution. */\\n }\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'stringReduction' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING s as parameter.\\n */\\n\\n public static int stringReduction(String s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String s = bufferedReader.readLine();\\n\\n int result = Result.stringReduction(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"stringReduction(s)\"\n ],\n \"solution\": \"#!/usr/bin/python\\n\\nimport collections, sys\\n\\n\\nchar_set = 'abc'\\n\\nif __name__ == '__main__':\\n T = int(sys.stdin.readline())\\n \\n for i in range(T):\\n chars = sys.stdin.readline().lower().strip()\\n count = collections.Counter(chars)\\n \\n parities = [v % 2 for v in count.values()]\\n while len(parities) < len(char_set):\\n parities.append(0)\\n \\n \\n # Check if the string is irreducible\\n if len(count.values()) == 1:\\n print(len(chars))\\n \\n # If the instances of each character have the same parity, then since\\n # the reduction steps flip each count's parity each will share the same\\n # parity throughout the reduction. \\n #\\n # Clearly, any reducible string much have a solution with len(solution)\\n # < len(chars). We will show further that the answer must be less than 3.\\n # \\n # Suppose, by contradiction, that we have a non-reducible answer with\\n # length 3 <= len(solution) < len(chars). For simplicity, take 'aaa' as\\n # our solution. This must have been reduced from a string containing an\\n # adjacent 'BC' term. However, any case we find that the string is \\n # further reducible:\\n # bcaaa -> bbaa -> bca -> aa\\n # abcaa -> ccaa -> cba -> aa\\n # aaabc -> aacc -> abc -> aa\\n # This contradicts out initial assertion of the string's irreducibility,\\n # and therefore we must have that len(solution) < 3.\\n # \\n # Back to this case, where the parity of all counts matches, our fully\\n # reduced solution must then correspond to [0, 0, 2].\\n elif len(set(parities)) == 1:\\n print(2)\\n \\n # Otherwise, pigeonhole says that two will have the same parity, and\\n # the other will have the opposite. This will continue throughout\\n # reduction, resulting in two even and one odd which corresponds to\\n # [0, 0, 1].\\n else:\\n print(1)\",\n \"template\": \"#\\n# Complete the 'stringReduction' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts STRING s as parameter.\\n#\\n\\ndef stringReduction(s):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n s = input()\\n\\n result = stringReduction(s)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":297,"cells":{"question_id":{"kind":"number","value":51,"string":"51"},"question_title":{"kind":"string","value":"Queens on Board"},"question_content":{"kind":"string","value":"**Queens on Board**\n\nYou have an *N* \\* *M* chessboard on which some squares are blocked out. In how many ways can you place one or more queens on the board, such that, no two queens attack each other? Two queens attack each other, if one can reach the other by moving horizontally, vertically, or diagonally without passing over any blocked square. At most one queen can be placed on a square. A queen cannot be placed on a blocked square.\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int queensBoard(List<String> board)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.ByteArrayInputStream;\\nimport java.io.IOException;\\nimport java.io.InputStream;\\nimport java.io.PrintWriter;\\nimport java.util.Arrays;\\nimport java.util.InputMismatchException;\\n\\npublic class Solution {\\n\\tstatic InputStream is;\\n\\tstatic PrintWriter out;\\n\\tstatic String INPUT = \\\"\\\";\\n\\t\\n\\tstatic void solve()\\n\\t{\\n\\t\\tfor(int T = ni();T >= 1;T--){\\n\\t\\t\\tint n = ni(), m = ni();\\n\\t\\t\\tchar[][] map = nm(n,m);\\n\\t\\t\\tint[][][] pre = new int[1<<m][1<<m-1][1<<m-1];\\n\\t\\t\\tint[][][] cur = new int[1<<m][1<<m-1][1<<m-1];\\n\\t\\t\\tpre[0][0][0] = 1;\\n\\t\\t\\t\\n\\t\\t\\tint mod = 1000000007;\\n\\t\\t\\tfor(int i = 0;i < n;i++){\\n\\t\\t\\t\\tfor(int j = 0;j < 1<<m;j++){\\n\\t\\t\\t\\t\\tfor(int k = 0;k < 1<<m-1;k++){\\n\\t\\t\\t\\t\\t\\tfor(int l = 0;l < 1<<m-1;l++){\\n\\t\\t\\t\\t\\t\\t\\tcur[j][k][l] = 0;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tint[] puts = new int[1<<m];\\n\\t\\t\\t\\tint pp = 0;\\n\\t\\t\\t\\tint block = 0;\\n\\t\\t\\t\\tfor(int j = 0;j < m;j++){\\n\\t\\t\\t\\t\\tif(map[i][j] == '#')block|=1<<j;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tinner:\\n\\t\\t\\t\\tfor(int put = 0;put < 1<<m;put++){\\n\\t\\t\\t\\t\\tif((put&block) != 0)continue;\\n\\t\\t\\t\\t\\tboolean blocked = true;\\n\\t\\t\\t\\t\\tfor(int j = 0;j < m;j++){\\n\\t\\t\\t\\t\\t\\tif(put<<31-j<0){\\n\\t\\t\\t\\t\\t\\t\\tif(!blocked)continue inner;\\n\\t\\t\\t\\t\\t\\t\\tblocked = false;\\n\\t\\t\\t\\t\\t\\t}else if(map[i][j] == '#'){\\n\\t\\t\\t\\t\\t\\t\\tblocked = true;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tputs[pp++] = put;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tfor(int j = 0;j < 1<<m;j++){\\n\\t\\t\\t\\t\\tfor(int k = 0;k < 1<<m-1;k++){\\n\\t\\t\\t\\t\\t\\tfor(int l = 0;l < 1<<m-1;l++){\\n\\t\\t\\t\\t\\t\\t\\tif(pre[j][k][l] == 0)continue;\\n\\t\\t\\t\\t\\t\\t\\tint ng = j|k<<1|l;\\n\\t\\t\\t\\t\\t\\t\\tfor(int u = 0;u < pp;u++){\\n\\t\\t\\t\\t\\t\\t\\t\\tint put = puts[u];\\n\\t\\t\\t\\t\\t\\t\\t\\tif((put&ng) != 0)continue;\\n\\t\\t\\t\\t\\t\\t\\t\\tint nj = (j|put)&~block;\\n\\t\\t\\t\\t\\t\\t\\t\\tint nk = (k<<1|put)&~block&(1<<m-1)-1;\\n\\t\\t\\t\\t\\t\\t\\t\\tint nl = ((l|put)&~block)>>>1;\\n\\t\\t\\t\\t\\t\\t\\t\\tcur[nj][nk][nl] += pre[j][k][l];\\n\\t\\t\\t\\t\\t\\t\\t\\tif(cur[nj][nk][nl] >= mod)cur[nj][nk][nl] -= mod;\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tint[][][] dum = cur; cur = pre; pre = dum;\\n\\t\\t\\t}\\n\\t\\t\\t\\n\\t\\t\\tlong ret = mod-1;\\n\\t\\t\\tfor(int j = 0;j < 1<<m;j++){\\n\\t\\t\\t\\tfor(int k = 0;k < 1<<m-1;k++){\\n\\t\\t\\t\\t\\tfor(int l = 0;l < 1<<m-1;l++){\\n\\t\\t\\t\\t\\t\\tret += pre[j][k][l];\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tout.println(ret%mod);\\n\\t\\t}\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) throws Exception\\n\\t{\\n\\t\\tlong S = System.currentTimeMillis();\\n\\t\\tis = INPUT.isEmpty() ? System.in : new ByteArrayInputStream(INPUT.getBytes());\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\t\\n\\t\\tsolve();\\n\\t\\tout.flush();\\n\\t\\tlong G = System.currentTimeMillis();\\n\\t\\ttr(G-S+\\\"ms\\\");\\n\\t}\\n\\t\\n\\tprivate static boolean eof()\\n\\t{\\n\\t\\tif(lenbuf == -1)return true;\\n\\t\\tint lptr = ptrbuf;\\n\\t\\twhile(lptr < lenbuf)if(!isSpaceChar(inbuf[lptr++]))return false;\\n\\t\\t\\n\\t\\ttry {\\n\\t\\t\\tis.mark(1000);\\n\\t\\t\\twhile(true){\\n\\t\\t\\t\\tint b = is.read();\\n\\t\\t\\t\\tif(b == -1){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn true;\\n\\t\\t\\t\\t}else if(!isSpaceChar(b)){\\n\\t\\t\\t\\t\\tis.reset();\\n\\t\\t\\t\\t\\treturn false;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\treturn true;\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static byte[] inbuf = new byte[1024];\\n\\tstatic int lenbuf = 0, ptrbuf = 0;\\n\\t\\n\\tprivate static int readByte()\\n\\t{\\n\\t\\tif(lenbuf == -1)throw new InputMismatchException();\\n\\t\\tif(ptrbuf >= lenbuf){\\n\\t\\t\\tptrbuf = 0;\\n\\t\\t\\ttry { lenbuf = is.read(inbuf); } catch (IOException e) { throw new InputMismatchException(); }\\n\\t\\t\\tif(lenbuf <= 0)return -1;\\n\\t\\t}\\n\\t\\treturn inbuf[ptrbuf++];\\n\\t}\\n\\t\\n\\tprivate static boolean isSpaceChar(int c) { return !(c >= 33 && c <= 126); }\\n\\tprivate static int skip() { int b; while((b = readByte()) != -1 && isSpaceChar(b)); return b; }\\n\\t\\n\\tprivate static double nd() { return Double.parseDouble(ns()); }\\n\\tprivate static char nc() { return (char)skip(); }\\n\\t\\n\\tprivate static String ns()\\n\\t{\\n\\t\\tint b = skip();\\n\\t\\tStringBuilder sb = new StringBuilder();\\n\\t\\twhile(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')\\n\\t\\t\\tsb.appendCodePoint(b);\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn sb.toString();\\n\\t}\\n\\t\\n\\tprivate static char[] ns(int n)\\n\\t{\\n\\t\\tchar[] buf = new char[n];\\n\\t\\tint b = skip(), p = 0;\\n\\t\\twhile(p < n && !(isSpaceChar(b))){\\n\\t\\t\\tbuf[p++] = (char)b;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\treturn n == p ? buf : Arrays.copyOf(buf, p);\\n\\t}\\n\\t\\n\\tprivate static char[][] nm(int n, int m)\\n\\t{\\n\\t\\tchar[][] map = new char[n][];\\n\\t\\tfor(int i = 0;i < n;i++)map[i] = ns(m);\\n\\t\\treturn map;\\n\\t}\\n\\t\\n\\tprivate static int[] na(int n)\\n\\t{\\n\\t\\tint[] a = new int[n];\\n\\t\\tfor(int i = 0;i < n;i++)a[i] = ni();\\n\\t\\treturn a;\\n\\t}\\n\\t\\n\\tprivate static int ni()\\n\\t{\\n\\t\\tint num = 0, b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static long nl()\\n\\t{\\n\\t\\tlong num = 0;\\n\\t\\tint b;\\n\\t\\tboolean minus = false;\\n\\t\\twhile((b = readByte()) != -1 && !((b >= '0' && b <= '9') || b == '-'));\\n\\t\\tif(b == '-'){\\n\\t\\t\\tminus = true;\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t\\t\\n\\t\\twhile(true){\\n\\t\\t\\tif(b >= '0' && b <= '9'){\\n\\t\\t\\t\\tnum = num * 10 + (b - '0');\\n\\t\\t\\t}else{\\n\\t\\t\\t\\treturn minus ? -num : num;\\n\\t\\t\\t}\\n\\t\\t\\tb = readByte();\\n\\t\\t}\\n\\t}\\n\\t\\n\\tprivate static void tr(Object... o) { if(INPUT.length() != 0)System.out.println(Arrays.deepToString(o)); }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'queensBoard' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING_ARRAY board as parameter.\\n */\\n\\n public static int queensBoard(List<String> board) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<String> board = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n String boardItem = bufferedReader.readLine();\\n board.add(boardItem);\\n }\\n\\n int result = Result.queensBoard(board);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\npublic class Solution {\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n\\n int t = in.nextInt();\\n for (int i = 0; i < t; i++) {\\n int n = in.nextInt();\\n int m = in.nextInt();\\n\\n String[] grid = new String[n];\\n for (int x = 0; x < n; x++) {\\n grid[x] = in.next();\\n }\\n\\n System.out.println(new Solution.SolutionHelper(n, m, grid).solve());\\n }\\n }\\n\\n public static final class SolutionHelper {\\n\\n private static final int MOD = 1000000007;\\n\\n private static final int WORD_MASK = 0xFFFFFFFF;\\n\\n private static final int[][] good = new int[50][32];\\n\\n private static final int[] validConf = new int[50];\\n\\n private static final int[] block = new int[50];\\n\\n private static final int[][] memo = new int[50][32768];\\n\\n private static final int[] rolloutMemo = new int[32768];\\n\\n private final int n;\\n\\n private final int m;\\n\\n private final String[] g;\\n\\n private SolutionHelper(int n, int m, String[] g) {\\n this.n = n;\\n this.m = m;\\n this.g = g;\\n\\n initMemo();\\n }\\n\\n public int solve() {\\n return (doSolve() - 1 + MOD) % MOD;\\n }\\n\\n private int doSolve() {\\n\\n int r = n;\\n int c = m;\\n for (int i = 0; i < r; i++) {\\n block[i] = 0;\\n int cmask = 0;\\n for (int j = 0; j < c; j++) {\\n if (this.g[i].charAt(j) == '#') {\\n cmask |= 1 << j;\\n block[i] |= 7 << 3 * j;\\n }\\n }\\n\\n validConf[i] = 0;\\n for (int j = 0; j < 1 << c; j++) {\\n if ((j & cmask) == 0) {\\n boolean valid = true;\\n for (int k = 0; (k < c) && (valid); k++) {\\n if ((j & 1 << k) != 0) {\\n for (int kk = k + 1; (kk < c) && (this.g[i].charAt(kk) != '#') && (valid); kk++) {\\n valid = (j & 1 << kk) == 0;\\n }\\n }\\n }\\n\\n if (valid) {\\n int sp = 0;\\n for (int k = 0; k < c; k++) {\\n if ((j & 1 << k) != 0) {\\n sp |= 7 << 3 * k;\\n }\\n }\\n\\n good[i][validConf[i]] = sp;\\n validConf[i] += 1;\\n }\\n }\\n }\\n }\\n\\n return doSolve(0, 0);\\n }\\n\\n private int doSolve(int x, int mask) {\\n if (x == this.n) {\\n return 1;\\n }\\n\\n mask &= (block[x] ^ WORD_MASK);\\n if (memo[x][mask] != -1) {\\n return memo[x][mask];\\n }\\n\\n int ret = 0;\\n for (int i = 0; i < validConf[x]; i++) {\\n if ((good[x][i] & mask) == 0) {\\n ret += doSolve(x + 1, rollout(good[x][i] | mask));\\n if (ret >= MOD) {\\n ret -= MOD;\\n }\\n }\\n }\\n\\n return memo[x][mask] = ret;\\n }\\n\\n private int rollout(int mask) {\\n if (rolloutMemo[mask] != -1) {\\n return rolloutMemo[mask];\\n }\\n\\n int c = m;\\n int nmask = 0;\\n for (int i = 0; i < c; i++) {\\n if (((mask & 1 << 3 * i) != 0) && (i > 0)) {\\n nmask |= 1 << 3 * i - 3;\\n }\\n if ((mask & 1 << 3 * i + 1) != 0) {\\n nmask |= 1 << 3 * i + 1;\\n }\\n if (((mask & 1 << 3 * i + 2) != 0) && (i + 1 < c)) {\\n nmask |= 1 << 3 * i + 5;\\n }\\n }\\n\\n return rolloutMemo[mask] = nmask;\\n }\\n\\n private void initMemo() {\\n for (int[] m : memo) {\\n Arrays.fill(m, -1);\\n }\\n\\n Arrays.fill(rolloutMemo, -1);\\n }\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'queensBoard' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING_ARRAY board as parameter.\\n */\\n\\n public static int queensBoard(List<String> board) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<String> board = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n int result = Result.queensBoard(board);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \" import java.util.ArrayDeque;\\n import java.util.ArrayList;\\n import java.util.HashMap;\\n import java.util.HashSet;\\n import java.util.List;\\n import java.util.Map;\\n import java.util.Queue;\\n import java.util.Scanner;\\n import java.util.Set;\\n import java.util.Stack;\\n import java.util.stream.Collectors;\\n\\n public class Solution {\\n\\n private static final int MOD = 1_000_000_007;\\n private static final int MAX_COLUMNS = 5;\\n\\n private static class Entry {\\n final int row;\\n final int queens, lshift, rshift;\\n\\n private Entry(int row, int queens, int lshift, int rshift) {\\n this.row = row;\\n this.queens = queens;\\n this.lshift = lshift;\\n this.rshift = rshift;\\n }\\n\\n @Override\\n public boolean equals(Object o) {\\n if (this == o) return true;\\n if (o == null || getClass() != o.getClass()) return false;\\n\\n Entry entry = (Entry) o;\\n\\n if (row != entry.row) return false;\\n if (queens != entry.queens) return false;\\n if (lshift != entry.lshift) return false;\\n return rshift == entry.rshift;\\n\\n }\\n\\n @Override\\n public int hashCode() {\\n int result = row;\\n result = 31 * result + queens;\\n result = 31 * result + lshift;\\n result = 31 * result + rshift;\\n return result;\\n }\\n\\n private List<Entry> getNext(int blocked, int mask) {\\n List<Entry> result = new ArrayList<>();\\n int unblocked = ~blocked & mask;\\n int newQueens = queens & unblocked;\\n int newLshift = lshift & unblocked;\\n int newRshift = rshift & unblocked;\\n int available = ~(queens | lshift | rshift) & mask;\\n\\n // entry without adding any queens\\n result.add(new Entry(row+1, newQueens, newLshift << 1, newRshift >> 1));\\n\\n Set<Integer> blocks = separateUnblocked(unblocked);\\n Set<Set<Integer>> positions = blocks.stream()\\n .map(unblock -> separatePositions(unblock & available))\\n .collect(Collectors.toSet());\\n\\n Set<Integer> placements = new HashSet<>();\\n for (Set<Integer> s : positions) {\\n Set<Integer> next = new HashSet<>();\\n for (int i : s) {\\n next.add(i);\\n next.addAll(placements.stream()\\n .map(j -> i | j)\\n .collect(Collectors.toList()));\\n }\\n placements.addAll(next);\\n }\\n\\n for (int pos : placements) {\\n result.add(new Entry(row+1, (newQueens | pos),\\n ((newLshift | pos) << 1), ((newRshift | pos) >> 1)));\\n }\\n\\n return result;\\n }\\n\\n private static Set<Integer> separatePositions(int available) {\\n Set<Integer> positions = new HashSet<>();\\n while (available > 0) {\\n int pos = available & -available;\\n positions.add(pos);\\n available -= pos;\\n }\\n return positions;\\n }\\n\\n private static Set<Integer> separateUnblocked(int blocked) {\\n Set<Integer> blocks = new HashSet<>();\\n int block = blocked & 0x1;\\n for (int j = 1; j < MAX_COLUMNS; j++) {\\n if ((blocked & (1 << j)) == 0) {\\n if (block != 0) {\\n blocks.add(block);\\n block = 0;\\n }\\n } else {\\n block |= blocked & (1 << j);\\n }\\n }\\n if (block != 0) {\\n blocks.add(block);\\n }\\n return blocks;\\n }\\n }\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int t = in.nextInt();\\n while (t-- > 0) {\\n int n = in.nextInt();\\n int m = in.nextInt();\\n int mask = (1 << m) - 1;\\n in.nextLine();\\n int[] blocked = new int[n];\\n for (int i = 0; i < n; i++) {\\n int j = 0;\\n int block = 0;\\n for (char c : in.nextLine().toCharArray()) {\\n if (c == '#') {\\n block |= (1 << j);\\n }\\n j++;\\n }\\n blocked[i] = block;\\n }\\n int count = getCount(new Entry(0, 0, 0, 0), blocked, mask, n, new HashMap<>());\\n System.out.println(count-1);\\n }\\n }\\n\\n private static int getCount(Entry e, int[]blocked, int mask, int n, Map<Entry, Integer> memo) {\\n if (memo.containsKey(e)) { return memo.get(e); }\\n\\n List<Entry> nextMoves = e.getNext(blocked[e.row], mask);\\n int count;\\n if (e.row == n - 1) {\\n count = nextMoves.size() % MOD;\\n memo.putIfAbsent(e, count);\\n return count;\\n } else {\\n count = 0;\\n for (Entry move : nextMoves) {\\n count += getCount(move, blocked, mask, n, memo);\\n count %= MOD;\\n }\\n }\\n memo.put(e, count);\\n return count;\\n }\\n }\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'queensBoard' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts STRING_ARRAY board as parameter.\\n */\\n\\n public static int queensBoard(List<String> board) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int m = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<String> board = IntStream.range(0, n).mapToObj(i -> {\\n try {\\n return bufferedReader.readLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n })\\n .collect(toList());\\n\\n int result = Result.queensBoard(board);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"queensBoard(board)\"\n ],\n \"solution\": \"def memoize(func):\\n pool = {}\\n def wrapper(*arg):\\n if arg not in pool:\\n pool[arg] = func(*arg)\\n return pool[arg]\\n return wrapper\\n\\nmod = 1000000007\\n\\nfor case in range(int(input())):\\n Y,X = map(int,input().split())\\n mx = [int(''.join('0' if c =='.' else '1' for c in input().rstrip()), 2) for i in range(Y)]\\n full = (1<<X)-1\\n\\n def is_wall(x,y):\\n return mx[y] & (1<<x) != 0 if 0<=x<X and 0<=y<Y else True\\n\\n def get_free(mx):\\n y = 0\\n while y<Y and mx[y] == full:\\n y+=1\\n\\n if y==Y: return (None,None)\\n free = 0\\n while mx[y] & (1<<free) != 0:\\n free += 1\\n if free >= X: return (None,None)\\n return (free,y)\\n\\n def place_queen(x,y,mx):\\n nmx = list(mx)\\n for dx in [-1,0,1]:\\n for dy in [-1,0,1]:\\n if dx == 0 and dy == 0: continue\\n cx,cy = x,y\\n while not is_wall(cx,cy):\\n nmx[cy] |= (1<<cx)\\n cx,cy = cx+dx,cy+dy\\n return tuple(nmx)\\n \\n @memoize\\n def rec(mx):\\n free_x,free_y = get_free(mx)\\n if free_x == None: return 0\\n #ignore free place\\n imx = list(mx)\\n imx[free_y] |= 1<<free_x\\n ans = rec(tuple(imx))\\n #place queen to free\\n nmx = place_queen(free_x,free_y,mx)\\n ans += 1\\n free_x,free_y = get_free(nmx)\\n if free_x != None:\\n ans += rec(nmx)\\n return ans % mod\\n\\n print(rec(tuple(mx)))\",\n \"template\": \"#\\n# Complete the 'queensBoard' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts STRING_ARRAY board as parameter.\\n#\\n\\ndef queensBoard(board):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n first_multiple_input = input().rstrip().split()\\n\\n n = int(first_multiple_input[0])\\n\\n m = int(first_multiple_input[1])\\n\\n board = []\\n\\n for _ in range(n):\\n board_item = input()\\n board.append(board_item)\\n\\n result = queensBoard(board)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":298,"cells":{"question_id":{"kind":"number","value":3994,"string":"3,994"},"question_title":{"kind":"string","value":"Police Operation"},"question_content":{"kind":"string","value":"Roy is helping the police department of his city in crime fighting. Today, they informed him about a new planned operation.\n\nThink of the city as a $2D$ plane. The road along the $X$-axis is very crime prone, because $n$ criminals live there. No two criminals live at the same position.\n\nTo catch these criminals, the police department has to recruit some police officers and give each of them USD $h$ as wages. A police officer can start his operation from any point $a$, drive his car to point $b$ in a straight line, and catch all the criminals who live on this way. The cost of fuel used by the officer's car is equal to the square of the euclidean distance between points $a$ and $b$ (Euclidean distance between points $(x_1,y_1)$ and $(x_2,y_2)$ equals to $\\sqrt{ (x_1-x_2)^2 + (y_1-y_2)^2 }$ ).\n\nThe police department asks Roy to plan this operation. So Roy has to tell them the number of officers to recruit and the routes these officers should take in order to catch all the criminals. Roy has to provide this information while minimizing the total expenses of this operation.\n\nFind out the minimum amount of money required to complete the operation.\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int policeOperation(int h, List<Integer> criminals)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n\\n\\tBufferedReader br;\\n\\tPrintWriter out;\\n\\tStringTokenizer st;\\n\\tboolean eof;\\n\\n\\tstatic class Line {\\n\\t\\tlong k;\\n\\t\\tlong b; // y = k * x + b\\n\\n\\t\\tpublic Line(long k, long b) {\\n\\t\\t\\tthis.k = k;\\n\\t\\t\\tthis.b = b;\\n\\t\\t}\\n\\n\\t\\tdouble cross(Line o) {\\n\\t\\t\\treturn 1.0 * (o.b - b) / (k - o.k);\\n\\t\\t}\\n\\n\\t\\tlong vect(Line a) {\\n\\t\\t\\treturn k * a.b - a.k * b;\\n\\t\\t}\\n\\t}\\n\\n\\tboolean badTurn(Line a, Line b, Line c) {\\n\\t\\treturn a.vect(b) + b.vect(c) + c.vect(a) >= 0;\\n\\t}\\n\\n\\tvoid solve() throws IOException {\\n\\t\\tint n = nextInt();\\n\\t\\tint h = nextInt();\\n\\t\\tint[] xs = new int[n];\\n\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\txs[i] = nextInt();\\n\\t\\t}\\n\\t\\tif (n == 0) {\\n\\t\\t\\tout.println(0);\\n\\t\\t\\treturn;\\n\\t\\t}\\n\\t\\tif (n == 1) {\\n\\t\\t\\tout.println(h);\\n\\t\\t\\treturn;\\n\\t\\t}\\n\\t\\tlong[] dp = new long[n + 1];\\n\\t\\tLine[] s = new Line[n + 1];\\n\\t\\tint sz = 0;\\n\\t\\ts[sz++] = new Line(-2 * xs[0], h + sqr(xs[0]));\\n\\t\\tdouble[] c = new double[n + 1];\\n\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\tint pos = Arrays.binarySearch(c, 0, sz - 1, xs[i]);\\n\\t\\t\\tif (pos < 0) {\\n\\t\\t\\t\\tpos = -pos - 1;\\n\\t\\t\\t}\\n\\t\\t\\tdp[i + 1] = Long.MAX_VALUE;\\n\\t\\t\\tfor (int j = pos - 1; j <= pos + 1; j++) {\\n\\t\\t\\t\\tif (j >= 0 && j < sz) {\\n\\t\\t\\t\\t\\tdp[i + 1] = Math.min(dp[i + 1], s[j].k * xs[i] + s[j].b);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tdp[i + 1] += sqr(xs[i]);\\n\\t\\t\\tif (i != n - 1) {\\n\\t\\t\\t\\tLine add = new Line(-2 * xs[i + 1], h + dp[i + 1] + sqr(xs[i + 1]));\\n//\\t\\t\\t\\tSystem.err.println(dp[i + 1] + \\\", \\\" + add.k + \\\" \\\" + add.b);\\n\\t\\t\\t\\twhile (sz > 1 && badTurn(s[sz - 2], s[sz - 1], add)) {\\n\\t\\t\\t\\t\\tsz--;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\ts[sz++] = add;\\n\\t\\t\\t\\tc[sz - 2] = s[sz - 2].cross(s[sz - 1]);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tout.println(dp[n]);\\n\\t}\\n\\n\\tstatic long sqr(long x) {\\n\\t\\treturn x * x;\\n\\t}\\n\\n\\tSolution() throws IOException {\\n\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\tsolve();\\n\\t\\tout.close();\\n\\t}\\n\\n\\tpublic static void main(String[] args) throws IOException {\\n\\t\\tnew Solution();\\n\\t}\\n\\n\\tString nextToken() {\\n\\t\\twhile (st == null || !st.hasMoreTokens()) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tst = new StringTokenizer(br.readLine());\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\teof = true;\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn st.nextToken();\\n\\t}\\n\\n\\tString nextString() {\\n\\t\\ttry {\\n\\t\\t\\treturn br.readLine();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\teof = true;\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t}\\n\\n\\tint nextInt() throws IOException {\\n\\t\\treturn Integer.parseInt(nextToken());\\n\\t}\\n\\n\\tlong nextLong() throws IOException {\\n\\t\\treturn Long.parseLong(nextToken());\\n\\t}\\n\\n\\tdouble nextDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(nextToken());\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'policeOperation' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER h\\n * 2. INTEGER_ARRAY criminals\\n */\\n\\n public static int policeOperation(int h, List<Integer> criminals) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int h = Integer.parseInt(firstMultipleInput[1]);\\n\\n String[] criminalsTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> criminals = new ArrayList<>();\\n\\n for (int i = 0; i < n; i++) {\\n int criminalsItem = Integer.parseInt(criminalsTemp[i]);\\n criminals.add(criminalsItem);\\n }\\n\\n int result = Result.policeOperation(h, criminals);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n\\n BufferedReader br;\\n PrintWriter out;\\n StringTokenizer st;\\n boolean eof;\\n\\n static class Line {\\n long k;\\n long b; \\n\\n public Line(long k, long b) {\\n this.k = k;\\n this.b = b;\\n }\\n\\n double cross(Line o) {\\n return 1.0 * (o.b - b) / (k - o.k);\\n }\\n\\n long vect(Line a) {\\n return k * a.b - a.k * b;\\n }\\n }\\n\\n boolean badTurn(Line a, Line b, Line c) {\\n return a.vect(b) + b.vect(c) + c.vect(a) >= 0;\\n }\\n\\n void solve() throws IOException {\\n int n = nextInt();\\n int h = nextInt();\\n int[] xs = new int[n];\\n for (int i = 0; i < n; i++) {\\n xs[i] = nextInt();\\n }\\n if (n == 0) {\\n out.println(0);\\n return;\\n }\\n if (n == 1) {\\n out.println(h);\\n return;\\n }\\n long[] dp = new long[n + 1];\\n Line[] s = new Line[n + 1];\\n int sz = 0;\\n s[sz++] = new Line(-2 * xs[0], h + sqr(xs[0]));\\n double[] c = new double[n + 1];\\n for (int i = 0; i < n; i++) {\\n int pos = Arrays.binarySearch(c, 0, sz - 1, xs[i]);\\n if (pos < 0) {\\n pos = -pos - 1;\\n }\\n dp[i + 1] = Long.MAX_VALUE;\\n for (int j = pos - 1; j <= pos + 1; j++) {\\n if (j >= 0 && j < sz) {\\n dp[i + 1] = Math.min(dp[i + 1], s[j].k * xs[i] + s[j].b);\\n }\\n }\\n dp[i + 1] += sqr(xs[i]);\\n if (i != n - 1) {\\n Line add = new Line(-2 * xs[i + 1], h + dp[i + 1] + sqr(xs[i + 1]));\\n while (sz > 1 && badTurn(s[sz - 2], s[sz - 1], add)) {\\n sz--;\\n }\\n s[sz++] = add;\\n c[sz - 2] = s[sz - 2].cross(s[sz - 1]);\\n }\\n }\\n out.println(dp[n]);\\n }\\n\\n static long sqr(long x) {\\n return x * x;\\n }\\n\\n Solution() throws IOException {\\n br = new BufferedReader(new InputStreamReader(System.in));\\n out = new PrintWriter(System.out);\\n solve();\\n out.close();\\n }\\n\\n public static void main(String[] args) throws IOException {\\n new Solution();\\n }\\n\\n String nextToken() {\\n while (st == null || !st.hasMoreTokens()) {\\n try {\\n st = new StringTokenizer(br.readLine());\\n } catch (Exception e) {\\n eof = true;\\n return null;\\n }\\n }\\n return st.nextToken();\\n }\\n\\n String nextString() {\\n try {\\n return br.readLine();\\n } catch (IOException e) {\\n eof = true;\\n return null;\\n }\\n }\\n\\n int nextInt() throws IOException {\\n return Integer.parseInt(nextToken());\\n }\\n\\n long nextLong() throws IOException {\\n return Long.parseLong(nextToken());\\n }\\n\\n double nextDouble() throws IOException {\\n return Double.parseDouble(nextToken());\\n }\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'policeOperation' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER h\\n * 2. INTEGER_ARRAY criminals\\n */\\n\\n public static int policeOperation(int h, List<Integer> criminals) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int h = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<Integer> criminals = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.policeOperation(h, criminals);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"import java.io.*;\\nimport java.util.*;\\n\\npublic class Solution {\\n\\n\\tBufferedReader br;\\n\\tPrintWriter out;\\n\\tStringTokenizer st;\\n\\tboolean eof;\\n\\n\\tstatic class Line {\\n\\t\\tlong k;\\n\\t\\tlong b; // y = k * x + b\\n\\n\\t\\tpublic Line(long k, long b) {\\n\\t\\t\\tthis.k = k;\\n\\t\\t\\tthis.b = b;\\n\\t\\t}\\n\\n\\t\\tdouble cross(Line o) {\\n\\t\\t\\treturn 1.0 * (o.b - b) / (k - o.k);\\n\\t\\t}\\n\\n\\t\\tlong vect(Line a) {\\n\\t\\t\\treturn k * a.b - a.k * b;\\n\\t\\t}\\n\\t}\\n\\n\\tboolean badTurn(Line a, Line b, Line c) {\\n\\t\\treturn a.vect(b) + b.vect(c) + c.vect(a) >= 0;\\n\\t}\\n\\n\\tvoid solve() throws IOException {\\n\\t\\tint n = nextInt();\\n\\t\\tint h = nextInt();\\n\\t\\tint[] xs = new int[n];\\n\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\txs[i] = nextInt();\\n\\t\\t}\\n\\t\\tif (n == 0) {\\n\\t\\t\\tout.println(0);\\n\\t\\t\\treturn;\\n\\t\\t}\\n\\t\\tif (n == 1) {\\n\\t\\t\\tout.println(h);\\n\\t\\t\\treturn;\\n\\t\\t}\\n\\t\\tlong[] dp = new long[n + 1];\\n\\t\\tLine[] s = new Line[n + 1];\\n\\t\\tint sz = 0;\\n\\t\\ts[sz++] = new Line(-2 * xs[0], h + sqr(xs[0]));\\n\\t\\tdouble[] c = new double[n + 1];\\n\\t\\tfor (int i = 0; i < n; i++) {\\n\\t\\t\\tint pos = Arrays.binarySearch(c, 0, sz - 1, xs[i]);\\n\\t\\t\\tif (pos < 0) {\\n\\t\\t\\t\\tpos = -pos - 1;\\n\\t\\t\\t}\\n\\t\\t\\tdp[i + 1] = Long.MAX_VALUE;\\n\\t\\t\\tfor (int j = pos - 1; j <= pos + 1; j++) {\\n\\t\\t\\t\\tif (j >= 0 && j < sz) {\\n\\t\\t\\t\\t\\tdp[i + 1] = Math.min(dp[i + 1], s[j].k * xs[i] + s[j].b);\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tdp[i + 1] += sqr(xs[i]);\\n\\t\\t\\tif (i != n - 1) {\\n\\t\\t\\t\\tLine add = new Line(-2 * xs[i + 1], h + dp[i + 1] + sqr(xs[i + 1]));\\n//\\t\\t\\t\\tSystem.err.println(dp[i + 1] + \\\", \\\" + add.k + \\\" \\\" + add.b);\\n\\t\\t\\t\\twhile (sz > 1 && badTurn(s[sz - 2], s[sz - 1], add)) {\\n\\t\\t\\t\\t\\tsz--;\\n\\t\\t\\t\\t}\\n\\t\\t\\t\\ts[sz++] = add;\\n\\t\\t\\t\\tc[sz - 2] = s[sz - 2].cross(s[sz - 1]);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\tout.println(dp[n]);\\n\\t}\\n\\n\\tstatic long sqr(long x) {\\n\\t\\treturn x * x;\\n\\t}\\n\\n\\tSolution() throws IOException {\\n\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\tout = new PrintWriter(System.out);\\n\\t\\tsolve();\\n\\t\\tout.close();\\n\\t}\\n\\n\\tpublic static void main(String[] args) throws IOException {\\n\\t\\tnew Solution();\\n\\t}\\n\\n\\tString nextToken() {\\n\\t\\twhile (st == null || !st.hasMoreTokens()) {\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tst = new StringTokenizer(br.readLine());\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\teof = true;\\n\\t\\t\\t\\treturn null;\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\treturn st.nextToken();\\n\\t}\\n\\n\\tString nextString() {\\n\\t\\ttry {\\n\\t\\t\\treturn br.readLine();\\n\\t\\t} catch (IOException e) {\\n\\t\\t\\teof = true;\\n\\t\\t\\treturn null;\\n\\t\\t}\\n\\t}\\n\\n\\tint nextInt() throws IOException {\\n\\t\\treturn Integer.parseInt(nextToken());\\n\\t}\\n\\n\\tlong nextLong() throws IOException {\\n\\t\\treturn Long.parseLong(nextToken());\\n\\t}\\n\\n\\tdouble nextDouble() throws IOException {\\n\\t\\treturn Double.parseDouble(nextToken());\\n\\t}\\n}\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'policeOperation' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts following parameters:\\n * 1. INTEGER h\\n * 2. INTEGER_ARRAY criminals\\n */\\n\\n public static int policeOperation(int h, List<Integer> criminals) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n String[] firstMultipleInput = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n int n = Integer.parseInt(firstMultipleInput[0]);\\n\\n int h = Integer.parseInt(firstMultipleInput[1]);\\n\\n List<Integer> criminals = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.policeOperation(h, criminals);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"policeOperation(h, criminals)\"\n ],\n \"solution\": \"#!/bin/python3\\n\\nimport os\\nimport sys\\n\\n#\\n# Complete the policeOperation function below.\\n#\\ndef cross(f, g):\\n return (g[1]-f[1])/(f[0]-g[0])\\n\\ndef policeOperation(h, criminals):\\n n = len(criminals)\\n dp = 0\\n stack = []\\n fpos = 0\\n for i in range(0,n):\\n f = [-2*criminals[i],criminals[i]*criminals[i] + dp,0]\\n \\n while len(stack) > 0:\\n f[2] = cross(stack[-1], f)\\n if stack[-1][2] < f[2]:\\n break\\n stack.pop()\\n if len(stack) == fpos:\\n fpos -= 1\\n\\n stack.append(f)\\n x = criminals[i];\\n while fpos+1 < len(stack) and stack[fpos+1][2] < x: fpos += 1\\n dp = stack[fpos][0] * x + stack[fpos][1] + h + x*x; \\n\\n return dp\\n\\n\\n\\n\\nif __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n nh = input().split()\\n\\n n = int(nh[0])\\n\\n h = int(nh[1])\\n result = 0\\n if n != 0:\\n criminals = list(map(int, input().rstrip().split()))\\n result = policeOperation(h, criminals)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\",\n \"template\": \"#\\n# Complete the 'policeOperation' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts following parameters:\\n# 1. INTEGER h\\n# 2. INTEGER_ARRAY criminals\\n#\\n\\ndef policeOperation(h, criminals):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n first_multiple_input = input().rstrip().split()\\n\\n n = int(first_multiple_input[0])\\n\\n h = int(first_multiple_input[1])\\n\\n criminals = list(map(int, input().rstrip().split()))\\n\\n result = policeOperation(h, criminals)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"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"},"max_retries":{"kind":"null"}}},{"rowIdx":299,"cells":{"question_id":{"kind":"number","value":102,"string":"102"},"question_title":{"kind":"string","value":"Unfair Game"},"question_content":{"kind":"string","value":" \n\nYou are playing a game of Nim with a friend. The rules are are follows:\n\n \n\n1) Initially, there are N piles of stones. Two players play alternately.\n\n2) In each turn, a player can choose one non empty pile and remove any number of stones from it. At least one stone must be removed.\n\n3) The player who picks the last stone from the last non empty pile wins the game.\n\n \n\nIt is currently your friend's turn. You suddenly realize that if your friend was to play optimally in that position, you would lose the game. So while he is not looking, you decide to cheat and add some (possibly 0) stones to each pile. You want the resultant position to be such that your friend has no guaranteed winning strategy, even if plays optimally. You cannot create a new pile of stones. _You can only add stones, and not remove stones from a pile_. What is the least number of stones you need to add?\n"},"dataset":{"kind":"string","value":"hackerrank"},"difficulty":{"kind":"string","value":"Hard"},"java":{"kind":"string","value":"{\n \"class_name\": \"Result\",\n \"func_sign\": [\n \"public static int unfairGame(List<Integer> s)\"\n ],\n \"script_name\": \"Solution\",\n \"solution\": \"import java.util.*;\\nimport java.io.*;\\nimport static java.lang.Math.*;\\n\\npublic class Solution {\\n\\tstatic class Foo57 {\\n\\t\\tstatic final long INF = Long.MAX_VALUE/3;\\n\\t\\tvoid main() {\\n\\t\\t\\tBufferedReader br = null;\\n\\t\\t\\ttry {\\n\\t\\t\\t\\tbr = new BufferedReader(new InputStreamReader(System.in));\\n\\t\\t\\t\\tint T = Integer.parseInt(br.readLine().trim());\\n\\t\\t\\t\\tfor (int i = 0; i < T; i++) {\\n\\t\\t\\t\\t\\tint N = Integer.parseInt(br.readLine().trim());\\n\\t\\t\\t\\t\\tint[] arr = new int[N];\\n\\t\\t\\t\\t\\tString[] s = br.readLine().trim().split(\\\"\\\\\\\\s+\\\");\\n\\t\\t\\t\\t\\tfor (int j = 0; j < N; j++) {\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tarr[j] = Integer.parseInt(s[j].trim());\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\tlong res = foo(arr);\\n\\t\\t\\t\\t\\tSystem.out.println(res);\\n\\t\\t\\t\\t}\\n\\t\\t\\t} catch (Exception e) {\\n\\t\\t\\t\\te.printStackTrace();\\n\\t\\t\\t} finally {\\n\\t\\t\\t\\tif (br != null) {\\n\\t\\t\\t\\t\\ttry { br.close(); } catch (Exception e) { e.printStackTrace(); }\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t}\\n\\t\\t\\n\\t\\tlong foo(int[] arr) {\\n\\t\\t\\tint N = arr.length;\\n\\t\\t\\tint MAX = 29;\\n\\t\\t\\twhile (MAX >= 0) {\\n\\t\\t\\t\\tboolean find = false;\\n\\t\\t\\t\\tfor (int val : arr)\\n\\t\\t\\t\\t\\tif ((val & 1<<MAX) != 0) {\\n\\t\\t\\t\\t\\t\\tfind = true;\\n\\t\\t\\t\\t\\t\\tbreak;\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\tif (find) break;\\n\\t\\t\\t\\tMAX--;\\n\\t\\t\\t}\\n\\t\\t\\tMAX += 3;\\n\\t\\t\\tint[] vec = new int[MAX];\\n\\t\\t\\tfor (int i = 0; i < MAX; i++) {\\n\\t\\t\\t\\tfor (int j = 0; j < N; j++) {\\n\\t\\t\\t\\t\\tif ((arr[j] & 1<<i) != 0)\\n\\t\\t\\t\\t\\t\\tvec[i] |= 1<<j;\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\tint MOD = (1<<N)-1;\\n\\t\\t\\tlong[][] dp = new long[MAX][1<<N];\\n\\t\\t\\tfor (long[] a : dp) Arrays.fill(a, INF);\\n\\t\\t\\tArrays.fill(dp[0], 0);\\n\\t\\t\\tfor (int i = 1; i < MAX; i++) {\\n\\t\\t\\t\\tfor (int state = 0; state < (1<<N); state++) {\\n\\t\\t\\t\\t\\tint bit = i-1;\\n\\t\\t\\t\\t\\tint v = Integer.bitCount(~state&vec[bit]&MOD)&1;\\n\\t\\t\\t\\t\\t//int v = 0;\\n\\t\\t\\t\\t\\tlong add = -(long)Integer.bitCount(state&vec[bit]&MOD) << bit;\\n\\t\\t\\t\\t\\t//long add = 0;\\n\\t\\t\\t\\t\\t/*for (int j = 0; j < N; j++) {\\n\\t\\t\\t\\t\\t\\tif ((state & 1<<j ) == 0 && (arr[j] & 1<<bit) != 0) {\\n\\t\\t\\t\\t\\t\\t\\tv ^= 1;\\n\\t\\t\\t\\t\\t\\t} else if ((state & 1<<j) != 0 && (arr[j] & 1<<bit) != 0) {\\n\\t\\t\\t\\t\\t\\t\\tadd -= 1<<bit;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}*/\\n\\t\\t\\t\\t\\tif (v == 0) {\\n\\t\\t\\t\\t\\t\\tdp[i][state] = min(dp[i][state], dp[i-1][state] + add);\\n\\t\\t\\t\\t\\t} else {\\n\\t\\t\\t\\t\\t\\t// find one to toggle\\n\\t\\t\\t\\t\\t\\tint curr = MOD - (~state&vec[bit]&MOD);\\n\\t\\t\\t\\t\\t\\tlong toAdd = add + (1<<bit);\\n\\t\\t\\t\\t\\t\\twhile (curr > 0) {\\n\\t\\t\\t\\t\\t\\t\\tint a = curr-1;\\n\\t\\t\\t\\t\\t\\t\\tdp[i][state] = min(dp[i][state], dp[i-1][state|(~a&curr)] + toAdd);\\n\\t\\t\\t\\t\\t\\t\\tcurr &= a;\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t/*for (int j = 0; j < N; j++) {\\n\\t\\t\\t\\t\\t\\t\\tif ((curr & 1<<j) != 0) {\\n\\t\\t\\t\\t\\t\\t\\t\\tdp[i][state] = min(dp[i][state], dp[i-1][state|1<<j] + toAdd);\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}*/\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t// when state == 0 and no need to toggle, try to find 2 zero to toggle\\n\\t\\t\\t\\t\\tif (state == 0 && v == 0) {\\n\\t\\t\\t\\t\\t\\tfor (int j = 0; j < N; j++) {\\n\\t\\t\\t\\t\\t\\t\\tif ((arr[j] & 1<<bit) != 0) continue;\\n\\t\\t\\t\\t\\t\\t\\tfor (int k = j+1; k < N; k++) {\\n\\t\\t\\t\\t\\t\\t\\t\\tif ((arr[k] & 1<<bit) != 0) continue;\\n\\t\\t\\t\\t\\t\\t\\t\\tdp[i][state] = min(dp[i][state], dp[i-1][state|1<<j|1<<k] + (1L<<bit+1));\\n\\t\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\t}\\n\\t\\t\\t}\\n\\t\\t\\treturn dp[MAX-1][0];\\n\\t\\t}\\n\\t}\\n\\t\\n\\tpublic static void main(String[] args) {\\n\\t\\tFoo57 foo = new Foo57();\\n\\t\\tfoo.main();\\n\\t}\\n}\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'unfairGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY s as parameter.\\n */\\n\\n public static int unfairGame(List<Integer> s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.regex.*;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n for (int tItr = 0; tItr < t; tItr++) {\\n int sCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n String[] sTemp = bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\");\\n\\n List<Integer> s = new ArrayList<>();\\n\\n for (int i = 0; i < sCount; i++) {\\n int sItem = Integer.parseInt(sTemp[i]);\\n s.add(sItem);\\n }\\n\\n int result = Result.unfairGame(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n }\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java15":{"kind":"string","value":"{\n \"solution\": \"\\nimport java.util.Arrays;\\nimport java.util.Scanner;\\n\\n/*\\n * To change this template, choose Tools | Templates and open the template in\\n * the editor.\\n */\\n/**\\n *\\n * @author muoi\\n */\\npublic class Solution {\\n\\n public static long MAX_BIT = 32;\\n public static long n;\\n static long a[] = new long[100];\\n static long b[] = new long[100];\\n static long c[] = new long[100];\\n static long dd[] = new long[100];\\n\\n static long bitCheck(long a, long b) {\\n return ((a) & (1l << (b)));\\n }\\n\\n static long bitSet(long a, long b) {\\n return ((1l << (b)));\\n }\\n\\n static long check() {\\n long res = 0l;\\n\\n\\n Arrays.fill(c, 0);\\n\\n\\n long sl = 0;\\n\\n for (long bb = MAX_BIT; bb >= 0; --bb) {\\n sl = 0;\\n Arrays.fill(dd, 0l);\\n for (int i = 0; i < n; ++i) {\\n if (bitCheck(a[i], bb) != 0l) {\\n if (c[i] <= a[i]) {\\n\\n sl++;\\n c[i] |= bitSet(c[i], bb);\\n dd[i] = 1;\\n\\n if (sl > b[(int)bb]) {\\n return -1;\\n\\n }\\n }\\n }\\n }\\n\\n for (long ii = 0; ii < b[(int)bb] - sl; ++ii) {\\n long mn = Long.MAX_VALUE;\\n long pos = 0;\\n for (long j = 0; j < n; ++j) {\\n if (dd[(int)j] == 0) {\\n long temp = c[(int)j];\\n temp |= bitSet(temp, bb);\\n\\n if (temp - a[(int)j] < mn) {\\n mn = temp - a[(int)j];\\n pos = j;\\n }\\n }\\n }\\n\\n dd[(int)pos] = 1l;\\n c[(int)pos] |= bitSet(c[(int)pos], bb);\\n }\\n\\n }\\n\\n for (long i = 0; i < n; ++i) {\\n\\n res += (c[(int)i] - a[(int)i]);\\n }\\n\\n return res;\\n }\\n\\n static void process() {\\n\\n if (n % 2 == 0) {\\n Arrays.fill(b, n);\\n } else {\\n Arrays.fill(b, n - 1);\\n }\\n\\n long mn = Integer.MAX_VALUE;\\n\\n for (long bb = MAX_BIT; bb >= 0; --bb) {\\n\\n while (true) {\\n\\n long temp = check();\\n if (temp != -1) {\\n\\n if (b[(int)bb] > 0) {\\n b[(int)bb] -= 2;\\n } else {\\n break;\\n }\\n\\n } else {\\n b[(int)bb] += 2;\\n break;\\n }\\n }\\n\\n long temp = check();\\n\\n if (temp != -1) {\\n if (temp < mn) {\\n mn = temp;\\n }\\n }\\n\\n }\\n\\n System.out.println(mn);\\n\\n }\\n\\n public static void main(String args[]) {\\n\\n long ntest;\\n Scanner scanner = new Scanner(System.in);\\n ntest = scanner.nextLong();\\n for (; ntest-- > 0;) {\\n n = scanner.nextLong();\\n for (long i = 0; i < n; ++i) {\\n a[(int)i] = scanner.nextLong();\\n }\\n process();\\n }\\n\\n\\n }\\n}\\n\\n\\n\\n\\n\\n\\n\\n\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'unfairGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY s as parameter.\\n */\\n\\n public static int unfairGame(List<Integer> s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int sCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> s = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.unfairGame(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"java8":{"kind":"string","value":"{\n \"solution\": \"//package hackerrank;\\n\\nimport java.util.Scanner;\\nimport java.util.stream.IntStream;\\n\\n/**\\n * Created by raggzy on 4/15/2016.\\n * <p>\\n * Sprague-Grundy\\n * We need to find such set, which gives 0 xor\\n * So we just DP from each bit pos till end\\n */\\npublic class UnfairGame {\\n\\n public static final int MAX_POW = 30;\\n\\n public static void main(String[] args) {\\n Scanner in = new Scanner(System.in);\\n int T = in.nextInt();\\n IntStream.range(0, T).forEach(tc -> {\\n int N = in.nextInt();\\n int[] v = new int[N];\\n IntStream.range(0, N).forEach(i -> v[i] = in.nextInt());\\n // building endvalue\\n int[][] endValue = new int[MAX_POW][N];\\n for (int end = 0; end < MAX_POW; end++) {\\n int endMask = (1 << (end + 1)) - 1;\\n for (int i = 0; i < N; i++) {\\n endValue[end][i] = v[i] & endMask;\\n }\\n }\\n // building f\\n int maxState = (1 << N) - 1;\\n int[][] f = new int[MAX_POW][maxState + 1];\\n for (int end = 0; end < MAX_POW; end++) {\\n int endMask = 1 << end;\\n for (int state = 0; state <= maxState; state++) {\\n boolean xor = false;\\n int minChildF = Integer.MAX_VALUE;\\n for (int i = 0; i < N; i++) {\\n int ithMask = 1 << i;\\n boolean containsIth = (ithMask & state) > 0;\\n boolean hasBit = (endMask & v[i]) > 0;\\n if (containsIth) {\\n xor ^= hasBit;\\n // we can make xor false by placing here 1\\n if (!hasBit) {\\n // placing here 1 and others to 0 and see result without this state\\n int prevF = end > 0 ? f[end - 1][state & (~ithMask)] : 0;\\n if (prevF != Integer.MAX_VALUE) {\\n minChildF = Math.min(minChildF, prevF + endMask - endValue[end][i]);\\n }\\n }\\n } else {\\n // just adding 1<<end\\n int prevF = end > 0 ? f[end - 1][state] : 0;\\n if (prevF != Integer.MAX_VALUE) {\\n minChildF = Math.min(minChildF, prevF + endMask);\\n }\\n }\\n }\\n int prevEndF = end > 0 ? f[end - 1][state] : 0;\\n\\n if (!xor && prevEndF != Integer.MAX_VALUE) {\\n // we don't need to compensate and we have prev state\\n f[end][state] = prevEndF;\\n } else if (xor && minChildF != Integer.MAX_VALUE) {\\n // we need to compensate and we have valid state to compensate with\\n f[end][state] = minChildF;\\n } else {\\n // either we didn't find any valid previous state or current column has every 1\\n // so we try to increase fathers bit and see what will happen\\n // we can do that only if father bit is 0\\n int fatherMask = endMask << 1;\\n int minTwoF = Integer.MAX_VALUE;\\n for (int one = 0; one < N; one++) {\\n if ((fatherMask & v[one]) > 0) continue;\\n int oneMask = 1 << one;\\n for (int two = one + 1; two < N; two++) {\\n if ((fatherMask & v[two]) > 0) continue;\\n int twoMask = 1 << two;\\n int prevF = end > 0 ? f[end - 1][state & (~oneMask) & (~twoMask)] : 0;\\n if (prevF != Integer.MAX_VALUE) {\\n minTwoF = Math.min(minTwoF, prevF + (fatherMask - endValue[end][one]) + (fatherMask - endValue[end][two]) + (xor ? endMask : 0));\\n }\\n }\\n }\\n f[end][state] = minTwoF;\\n }\\n }\\n }\\n System.out.println(f[MAX_POW - 1][maxState]);\\n });\\n }\\n}\\n\\n/*\\n Input:\\n20\\n2\\n19 20\\n2\\n17 7\\n4\\n30 16 11 15\\n4\\n18 22 18 3\\n3\\n13 23 27\\n3\\n21 27 2\\n3\\n30 5 30\\n2\\n10 22\\n3\\n28 12 22\\n5\\n10 8 28 17 18\\n3\\n7 6 17\\n5\\n30 15 29 22 3\\n3\\n4 30 1\\n2\\n29 6\\n2\\n10 7\\n5\\n9 26 27 22 2\\n5\\n30 29 15 9 2\\n4\\n14 11 15 5\\n2\\n5 18\\n2\\n4 22\\nOutpout:\\n1\\n10\\n10\\n15\\n27\\n4\\n9\\n12\\n26\\n9\\n14\\n3\\n25\\n23\\n3\\n10\\n3\\n5\\n13\\n18\\n */\",\n \"template\": \"class Result {\\n\\n /*\\n * Complete the 'unfairGame' function below.\\n *\\n * The function is expected to return an INTEGER.\\n * The function accepts INTEGER_ARRAY s as parameter.\\n */\\n\\n public static int unfairGame(List<Integer> s) {\\n // Write your code here\\n\\n }\\n\\n}\\n\\n\",\n \"template_head\": \"import java.io.*;\\nimport java.math.*;\\nimport java.security.*;\\nimport java.text.*;\\nimport java.util.*;\\nimport java.util.concurrent.*;\\nimport java.util.function.*;\\nimport java.util.regex.*;\\nimport java.util.stream.*;\\nimport static java.util.stream.Collectors.joining;\\nimport static java.util.stream.Collectors.toList;\\n\\n\",\n \"template_tail\": \"public class Solution {\\n public static void main(String[] args) throws IOException {\\n BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(System.in));\\n BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(System.getenv(\\\"OUTPUT_PATH\\\")));\\n\\n int t = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n IntStream.range(0, t).forEach(tItr -> {\\n try {\\n int sCount = Integer.parseInt(bufferedReader.readLine().trim());\\n\\n List<Integer> s = Stream.of(bufferedReader.readLine().replaceAll(\\\"\\\\\\\\s+$\\\", \\\"\\\").split(\\\" \\\"))\\n .map(Integer::parseInt)\\n .collect(toList());\\n\\n int result = Result.unfairGame(s);\\n\\n bufferedWriter.write(String.valueOf(result));\\n bufferedWriter.newLine();\\n } catch (IOException ex) {\\n throw new RuntimeException(ex);\\n }\\n });\\n\\n bufferedReader.close();\\n bufferedWriter.close();\\n }\\n}\\n\"\n}"},"python":{"kind":"string","value":"{\n \"class_name\": null,\n \"func_sign\": [\n \"unfairGame(s)\"\n ],\n \"solution\": \"#!/bin/python3\\n\\nimport os\\nimport sys\\n\\n#\\n# Complete the unfairGame function below.\\n#\\ndef unfairGame(s):\\n nimSum = 0\\n for i in s:\\n nimSum ^= int(i)\\n \\n if(nimSum == 0):\\n return 0\\n\\n # if(nimSum == 1):\\n # modlist = [x % 2 for x in s]\\n # if min(modlist) == 0:\\n # s[modlist.index(0)] += 1\\n # else:\\n # s[0] += 1\\n # return 1 + unfairGame(s)\\n\\n print(s)\\n divider = 2 ** (len(bin(nimSum)) - 3)\\n print(divider)\\n modlist = [x % divider if x % (2 * divider) < divider else -1 for x in s]\\n\\n print(modlist)\\n if max(modlist) < 0:\\n s[s.index(max(s))] += divider\\n return divider + unfairGame(s)\\n\\n increaseNumber = max(modlist)\\n increase = divider - increaseNumber\\n print(increase)\\n\\n s[modlist.index(increaseNumber)] += increase\\n\\n print(s)\\n print()\\n return increase + unfairGame(s)\\n \\n\\nif __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input())\\n\\n nums =[1, 10, 10, 15, 27, 4, 9, 12, 26, 9, 14, 3, 25, 23, 3, 10, 3, 5, 13, 18]\\n for i in nums:\\n print(i)\\n\\n for t_itr in range(t):\\n s_count = int(input())\\n\\n s = list(map(int, input().rstrip().split()))\\n s.sort()\\n\\n result = unfairGame(s)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\",\n \"template\": \"#\\n# Complete the 'unfairGame' function below.\\n#\\n# The function is expected to return an INTEGER.\\n# The function accepts INTEGER_ARRAY s as parameter.\\n#\\n\\ndef unfairGame(s):\\n # Write your code here\\n\\n\",\n \"template_head\": \"#!/bin/python3\\n\\nimport math\\nimport os\\nimport random\\nimport re\\nimport sys\\n\\n\",\n \"template_tail\": \"if __name__ == '__main__':\\n fptr = open(os.environ['OUTPUT_PATH'], 'w')\\n\\n t = int(input().strip())\\n\\n for t_itr in range(t):\\n s_count = int(input().strip())\\n\\n s = list(map(int, input().rstrip().split()))\\n\\n result = unfairGame(s)\\n\\n fptr.write(str(result) + '\\\\n')\\n\\n fptr.close()\\n\"\n}"},"test_cases":{"kind":"string","value":"eJzFms2KbclxhTXwgyR33IjMyH8/icHXeGD1QBpcSdACgRH4Iez39ffFPvcgilsNGqlbJU5Xnb13ZsSKtVZE7v/5l//780+/yX/+7Q98+Pf//vL7b3/6yy9f/rV8aePrt9b5qbfdOk85p645b618WvxiDz6tqLOde0qPuviPu8ttp9196i79zrlv7aNE3XdEXD7d2nZvZ5dV9x5rjShjnX7Xur3wp8UD9y2j1rlHzPn1G4u4/ay+5+D3a5zVNt+Iw517zOUav35bu3O3daNw83bv3a2suc6JXk+Zd9TGAjtLYe08MUo/re4Yc5d9Y5565y37rNvixCr31FjBmuauUeO0eOIxWFS9p0dZ/PLOOnaZg0WzsM0Gzpn84ZRGqHbd/ZSIethgtLJZ2OHqKKfPEzFcTvdJbRSiuC/7v6WvtQffHaWzukPUo8QkFtsFXCKyxpxjdC7ncW0QjTlO35XFlT0afw4/3ct3Kk8ZYzW3Xwtfun3Nstuag8Bsdjt3NKNIrNueZHfMXk7stdmA++QpmweWdsnyiLFKr/6NO5RWyR5B62VXAHLZFo+brdYzZ2mNB7bD/YgUK5ydGHeW0ibLYkG7zTa5i4H07iy6nsvtuAsJYM+dDbMyokocSX1ZnX2RgFH2aguonW62xq6dQBh/wFm5an/9doAEMQALQKWBZBA4iMoBUYWtr752gFlWdsAFQOmrdiNQokfnrxmZ7p1a7bFZ62nt1DYA47yLzfVKZqmROwfJA3qTDR5uQABJOw9aVEczSMB3mk6iMKdJ7DVYeyfLnb23fgmd2CJhlW8RwL1IZRusgIXc4Ht8g21eLurNb9TKXRtXr9ZnF7tkiPA3osG++BNrf4rE/ZzR3DsrtDpWGWyFx5OsPvbq5AUY930uKSoz7hQ6lFI/3NOYjzbZGRdShX3HWuWM7reokMP/iGRllY2NnTGNvsDZIJ00UHqXGqDoWoC71YknVUYsWvPeZGQSCQJBFRPwzP0O8ReV9czarX7wCVcQ6c1WeBgXEgq2CslQJuyWn7UqCKPuGnBJaiDZwWVWNfQxVyfUfVyjT9hOuGm3Ro7qPgKTdRE9Ml7urQtkADYqm0Bv9kDdEGrC8fXbl5/Kl5//+qef/+uXn3/3n3/8yy8vGr0dPNcpmd6kq+TVubyVlVwDluNyKJFPJ8nM4Fdhf9uA9rp/D2AVRxi0WFAFnAEXAX0urG6X3FP+frMTce5P3Nx8sIubNH4Czvjyt5/K37O8rMaKdms7JlssIJzCplYtDyq3ioK7F+UJFzRCCiLgvAOlskrIr4MneIs/wlkNnoA8ATFUx00sp2qRAMq9uFunMNjrqMPE7AnOKWc+DQLaDZQxWM3Q8kChRvZPLTwefHBzRaUTdEiMmqdK+BrFwKLZMtf3waNJ566L57IglhjcrPPoOwmf+MtvnksVwE9wygQ4yBwgYBWjm3pICAJASVKCqDyWQmig2uAJDZ4jscR/9JHAh3NgsJhgHHGEKkA75LgumymQzhG7IGps/of2SXrgCLIrwVfqQoaomeX6Vs8FBgWviCiHo1EniKpMT47UOUhgUUX5dAlI2SCot7V6QHqBEJAU6WKThA2WqZszICMVSgaCDBaFOlk4ZYOoEm3kV8RwT7ijTrSP6wfCbc5YPvzEYuEWag7MuhH+WKdMsI0u+yvKKPGo152jPv30h0f5Lbc4pJzVUre9ogPQEltFJfgiyril6Yb8EFLCiYJdqp5Kh3QpE+yGWWsKgWsHZ4N8oct8ke0ZI5DSiNHCTHAxOiVKweJ6Mg9cgALaQza3CVK/lC1kZUoEbIZ7Wm2UIUQVUOcUHFYfn6gvPATXs5zGcxERVxGqdJHD55jQzBC8KAeEhgVCdND5eZTiI5lBvICFRSClQIeyQtE62PgVRoFS8QKPFQFSVBKZYv3sh01JLoOi418WTu67nCEOSRX7QRpI0U5Ay0Hd71FX2LJkpkMdwShgag/uCKTkDuIGUuoH8hhPeA4GBFoPUBJ3pSEidw9JsW+IAi8EyFy24gjNV6/BIS5CoSorVBe9hX/gb5QC1JN3ahVgUDJbj4FHBMdglnjXVHfqVDBv7SdlBFMDNwzITU6AxEFdOrDDhy51d0ALiLaer0292ExHhQmBKjREeJpNrOB2XaICUtwe0HM3IIYyQWF7fv+4cBwwzKDKkGiitBU+0o0ZIsqqF2qMnlQQj2ixqs+Ta6FgWLlOtGz1AIklXKEFQimI30cO7/mUhsainCwcScL1rkRvigCGvMLW5fJLxRZYYm0VIciMEFcrWzYK/OPSo4d1TCF0JGmTNn5HclAvSAVInKH7I+g4Q7wJThMcH/0aAdZXTEkFtwYXoAtwDDWyZEb5BMg++kzC01jXp1PADuNrJO+l7ZT6dNIT68a/IZXMqk7gvNJMhB4f3QIa0HRBJdAFRQpWJocd/mVh+OSITwM+ERWkyoLAdnLHk+qDZoOPj2JZ041ovIAwvIeBQ4tOShrrr+IHUGzNk1KJUtJupHxM2yS2NDNCUDX4HjQ9xKA9WA5iA6DB6IBxtSTYUi3t0g8Ci7a5fVhNlNHReF+LxxzWbI5aUhuZBYXcgJwBSbYHXAnHkojhF0ocxH43hFhzbC84bmnfV3ZDGJzQwaKyEIlCxs6aSl200CyZe2pAG+ZJzaIBIs5a0Yts44fFFoZwz8e7s/UrYdopdf0zXk/bRENGegf1XtNPL1uueiIRTVy197SUk2Lj8l2fDWJ5kF1ggwpQ7To81oEobnuKrp+dqraEdpL9WWAx2BRgd6szDS+PTpWiKLJlsW1oUja+03LFndoiEofrtkg0Pr9BBehr0bSSX3sHeziuBedUBZEeshmeiXVCiZAs3c58ihFvTEJhAN0JllYs51PgLrogqpP6sO+DgbiOgOG7kARITONsU5mrptqr1hXNpIPiUxfFcvCw/Ub9rw4NS4G22pxr8W0W8PiG3+4Kt0bRjs+5CGwTHtUF7qXaZCPLE3YlumwqLEFrGZJNoaBPXHpX+Qu6xbLwWzN0kSlbmGm1XGtMedTPfayx+/LuFUXqCm0DbjgJ0kZDE/oqAK9Y8iycx5YUyDu2GbisDsRpypAUyEhBEN9Tf4jnGZo3o9iMGM0CNx8vllT4AZHQJXtDp+Yt0T0LndKBt9JKUhA4Fz4pimRCyOG5gUNRmrGhVC6cZIOh47RKs88DCbYaEGy2ac460DhKBuhJfPCfQqsVttHVwJ9EO25cv2URpDpIAvQR9dFDWp6pI6I7YZEsmw1eZyP2ol38AeWrncHYnqce1eIhHrAbWENSxlX4eZtc3D6BhmHQq+NIAVjnVU3wcxfoHjXQ2ITzEjbD/tFd8k6PBR0Q/Tayq3mandRMumB4Auojf9Sczta+2eYKa+722TEe06XiJeEubBhKhmTyNa0mGo6f495H7AO4YTHaNeParu6eMsKn4lsU7yPWveLYVd6HifQGSDT8A5ytfIUeTA8E0lYG63SHGbrcHSS0x7RufWVXJXWLtuS2/LpgGlXI2SmLDYkGk8cDTGSV0pUL2LYDCVUXG+Jjd2qbC+lOfaAwqfGyYPYtDbIrQqqPgnZEXn2xdej8ZXyyTU+mRBy1JCYAsO1eUiD2psO40lXPwVQ21Npd5BbwLMlOzgsyDTZbtvlnZQOVjg6gTqd6admcaFABLJRIomsYDUp/2IrwcTnLc7cyfGjVUOUFoOi5nDlNywLAoQfHmZ990DVpciQYpkhJLEvqT6t/lPPLNxSH4RxMOwVZU7CQW9eJaxNPy7vWhy4ANOFwbgXtEDRoQT++tOsASa8OEGb2TCfrhRXb29r7VUUg7TisY1JEpSpDN0yBgSzFAFxO8ftoEymtsBDVgsa60Z4qvu1Q2uP1zAJuIIcEzg2yMVzq9H2cIHUuN3OJOUJtVW2tbZr72M6/CDgQo0KnLTSqN+U21hzOhbqht5kKR4RES6UKRxV0Ktch5sa/7WFbCwNPm9ZAOni2rQvQrHCL2JsOTLvlUoV6f7ZJR8HtTfpybLbV82Rn/svuxbqVgOkleOgOu3WNjfAWV01DgxuyJSMBkKdOEtbEY8+cMtHUw6qgFTKFzDHtMAdGyqaQ61C0yImArVIIfsK00udhlJodOhdZQFVyQSSrJYL5GQDFR54H0oCJ2ykULAnM35xFcR+zSI3CJWixHQmiRJc4AEEbz4CJLlSlcwaOQai5W1yC3DlsssMSJoE8mxihw6wRuwsT7E/FFb9IPWloUoijZ8Ml9F1wVXAEjeM0rFWVgp2GwhnTjrRB2vzesSgrHPcZFdRsE5wV2ENKv1lj6Zu8iaMCihbWxDCaXQokh0PQJRhLmsE8UR+ONNBYwNlPuvXh/Pb5OJX42z8K937ytPUcBJ/4zXDkpNMhbvoQ8DdyOFEcnzjEJbjTkXSO1514sRCQr6jaZ5BlHT68ph9CGjCo3Tk9lU7CKuyfk+bh8JDoyExwS51G96a8OFfK2UNym0N9tAf6APAp3sSerTsPkZEg9nAegp7bm2ILkd+dczGugHT04igVVaJeNBtkEWhfC3PoAe3JZXE0I+eOUhKNuFh2VIlt3wblSuvtPDNThY565zHOqympZfyc7eUMycm4w2PucZwtUI6aQfstHt+soW3XI6RW8pCK2w1/UZUtOXw9/y+tU4L8J60DVhgCsP/z1GTaDEOhbGF6giNYnKZZT1OSh05BPlLhQ21nFDxHJmT71cMsm554YgSbsXecvcYR7sdEZs9284QCpUJN2SvE7JSIrbFMrGnCIBz+huxIV0j4nfWHc1SWm/dGWHFKLrdnAYN0m0l5l5VRIzZ/4aRXKB6HoB5Q5SodWoG86/zQzgB+hoAoJLA1nBh5UOKgBtTS8jqhXx7u2EJ7zAUa9LJ6G3Sd4uNPxUGEpaxDpECo/oreY7Z5WMvxGb5wq+jOHPFLM9stZ17qBau/yfQ5TahyOR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question_id int64 39 56.8k | question_title stringlengths 3 54 | question_content stringlengths 88 4.02k | dataset stringclasses 1
value | difficulty stringclasses 3
values | java dict | java15 dict | java8 dict | python dict | test_cases stringlengths 28 4.02M | max_retries float64 1 3 ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|
47,135 | Strong Password | Louise joined a social networking site to stay in touch with her friends. The signup page required her to input a *name* and a *password*. However, the password must be *strong*. The website considers a password to be *strong* if it satisfies the following criteria:
- Its length is at least $6$.
- It contains at lea... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int minimumNumber(int n, String password)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.u... | {
"solution": "DNE",
"template": "class Result {\n\n /*\n * Complete the 'minimumNumber' function below.\n *\n * The function is expected to return an INTEGER.\n * The function accepts following parameters:\n * 1. INTEGER n\n * 2. STRING password\n */\n\n public static int minimu... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n static int minimumNumber(int n, String password) {\n // Return the minimum number of characters to make the password strong\n String numbers = \"0123... | {
"class_name": null,
"func_sign": [
"minimumNumber(n, password)"
],
"solution": "#!/bin/python3\n\nimport sys\n\nnumbers = \"0123456789\"\nlower_case = \"abcdefghijklmnopqrstuvwxyz\"\nupper_case = \"ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\nspecial_characters = \"!@#$%^&*()-+\"\n\ndef minimumNumber(n, password):\n ... | eJy9VMuSmkAUzSKV7xgfWKJjikYRyErwgQM+cPBJCCkaRGGkkZeoqVTlI5L/DZXKIjUZU8wmd9WLc/qce/r2/fb2B3j35leta9nh45eig45JXPxwV6RaGlI2607FTcOSK4mWovSUoWlTKjoDXk6IiSkcxvTUCvEH3ScZTplP3FRnG56Givd3xe35uDXjrfXZT+LfVxLFr/d3f0iQGoK7m+jWMzRNaOgYEa00WlvEzOYZCXBLvNIPJgzkMN82YVs2xmW1VnDnrfnFqlihZQkbDOcTZjSXhHlvL7D8stxa5jbY1lDQFSQqvMkAzxgs0JD0... | null |
21,405 | Two Characters | Given a string, remove characters until the string is made up of any two alternating characters. When you choose a character to remove, all instances of that character must be removed. Determine the longest string possible that contains just two alternating letters.
**Example**
$s = \text{'abaacdabd'}$
Dele... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int alternate(String s)"
],
"script_name": "Solution",
"solution": "\n import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\nimport java.lang.*;\npublic class Main{\n\tstatic long mod=1000000007;... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class B {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"alternate(s)"
],
"solution": "def char_range(c1, c2):\n for c in range(ord(c1), ord(c2)+1):\n yield chr(c)\n \ndef is_alternating(s):\n for i in range(len(s) - 1):\n if s[i] == s[i+1]:\n return False\n return True\n \nlen_... | eJztmEmu5UdaxRmwCkYlj0uoyuUyNitBwghFfNH3fYeQWAQsjxkL4VyLASKdgxwX+aTMfM2NG/+vOed33r/99X/819/81a9//uE/8Z9//JfvbCpzfPf3v/vuhx//8EtK5Perl5iZd3a2/WKNNatirvpQY8PWJR1b4mbqbVSrRNy6BpJz62YH87dnGoLrm3TjbasnSvSSvdK2YVlZpbrnPHNn0mRe9y3sxZG+dScX04slzjJf2j6ufKzS99Ly9V3eaaVTKtWRlWO36jtMJ4/3WsWbIbYNb6Sph86m61V7tjw9fxYLNBkFYzVFfuzU3N8t... | null |
8,640 | Caesar Cipher | Julius Caesar protected his confidential information by encrypting it using a cipher. [Caesar's cipher](https://en.wikipedia.org/wiki/Caesar_cipher) shifts each letter by a number of letters. If the shift takes you past the end of the alphabet, just rotate back to the front of the alphabet. In the case of a rotation ... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String caesarCipher(String s, int k)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(Str... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.util.Scanner;\n\nclass Solution {\n\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n int N = sc.nextInt();\n String s = sc.next();\n int K = sc.nextInt();\n StringBuilder sb = new StringBuilder(s);\n for (int ... | {
"class_name": null,
"func_sign": [
"caesarCipher(s, k)"
],
"solution": "cnt = int(input())\nstring = input()\nshift = int(input())\n\nres = \"\"\n\nwhile shift > 26:\n shift -= 26\n\nfor char in string:\n if char.isalpha():\n is_upper = False;\n is_lower = False;\n if ord(char) ... | eJy9Vdtu2koU7UNf+hcJSaqGhMa38SVFVYxvgA22MeBL3TqAgUDSgYANhIioH9H+b4fqHKnCTKRezvF+seay9pq196z58vLb4NWLH58XoZ8Pj7kRnKZJ7vIgRzIh1I3Hw0rxnVn1ROWsEcLtWO78INdfTfu9pB9HkzT5Z7kfPB66xXeSZ5jOmYqWbc4PfkJjiBBqUdMIfLWpF2TTCmwxKIiWUpMqrajZkEylXYlcqeUFfggZCpvHjaoly2xXxUJTUS3Ntgq22pIcX4+qZUdpGX5Uc/S6ZWYY8CEsuk+XC0XphxCQ2ATF9tNlKstxBoCi... | null |
16,032 | Mars Exploration | A space explorer's ship crashed on Mars! They send a series of `SOS` messages to Earth for help.
<img src="https://s3.amazonaws.com/hr-challenge-images/16032/1453204202-9e3fd295bb-NASA_Mars_Rover.jpg" title="NASA_Mars_Rover.jpg" />
Letters in some of the `SOS` messages are altered by cosmic radiation during transmis... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int marsExploration(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] a... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class A {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n... | {
"class_name": null,
"func_sign": [
"marsExploration(s)"
],
"solution": "s = input()\nn = \"SOS\"*(len(s)//3)\ncnt = 0\nfor i in range(len(s)):\n if s[i] != n[i]:\n cnt += 1\nprint(cnt)\n",
"template": "#\n# Complete the 'marsExploration' function below.\n#\n# The function is expected to return... | eJy1Vc1OwzAM5oDEa0w9TwiGQIJbmqzpT5osdf8BcYAduIwdNgkJIfEQ8L44oYexbtVaQRRFjhP7c+zP7cfxV3RyZEfJULh9c54Xy/XKuRk5oOCf5t3CGY+c+ety/riaPz28rFcN5BmevI9HG0HoOEaDSpe48tDIpDQyo9zohVm5Z/Qhs3rfxzXVogvmoo1T04CLhJKwR7TXLS/WIG0so0EpmOx2ujHjfU693q45AaYqE2kAJRrnM0hI0ABkRV7INOPSbP0AvBAFYl8W7cfYk5TDZvoXJDrfFUHVsi+3NPXvrfgRtF3VkDiudsRR5zKT... | null |
345 | Running Time of Algorithms | In a previous challenge you implemented the _Insertion Sort_ algorithm. It is a simple sorting algorithm that works well with small or mostly sorted data. However, it takes a long time to sort large unsorted data. To see why, we will analyze its running time.
**Running Time of Algorithms**
The running time of an alg... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int runningTime(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "\n\n/* Head ends here */\nimport java.util.*;\npublic class Solution {\n \nstatic void insertionSort(int[] ar) {\n int count =0; \n ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n\n public static int insertionSort(int n,int array[]) {\n int i, j, newValue,shift=0;\n for (i = 1; i < n; i++) {\n newValue = array[i];\n ... | {
"class_name": null,
"func_sign": [
"runningTime(arr)"
],
"solution": "size = int(input())\narray = input().split(\" \")\narr = ['None'] * size\nfor i in range(size):\n arr[i] = int(array[i])\ni = 1 \ncount = 0\nwhile i < size:\n tmp = arr[i]\n j = i - 1\n while arr[j] > tmp and j > -1:\n ... | eJztnUuubdlyUCnQkKVX9kFr/mfQEiQeogAuUElcsCUkhEQjoEP0gRqNIcaInQlKnAYjJGRp++ot33PzrP1ZM2bMiBG///iP//N/+y//yP/7Z/81//LP//2f/s0vf/U3f/2nf/r86fz5l5/Y+zw/va2nv6c/P2Ov9fy0Ntdz19zP7DH//Muf/uL501/+u7/6y3/113/5r//lv/2bv/68wPrTf/iL5396wfHnX3rv8/lZ0eOZ7e4/vLX97tb1519u3vD8zH7vc1vPTzXuiaftHn/4Kvt3r7LzDc982zPWO59o5332avm15pp5XS2/0c/o... | null |
3,418 | Pangrams | A *pangram* is a string that contains every letter of the alphabet. Given a sentence determine whether it is a pangram in the English alphabet. Ignore case. Return either `pangram` or `not pangram` as appropriate.
**Example**
$s = \text{'The quick brown fox jumps over the lazy dog'}$
The string contains all le... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String pangrams(String s)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatc... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.io.PrintWriter;\nimport java.util.*;\n\n\npublic class Solution {\t\n\tBufferedReader reader;\n StringTokenizer tokenizer;\n PrintWriter out;\n \n\tpublic void solve() throws IOException... | {
"class_name": null,
"func_sign": [
"pangrams(s)"
],
"solution": "alphabet = 'abcdefghijklmnopqrstuvwxyz'\ndef pg(x):\n for letter in alphabet:\n if letter not in x:\n return False\n \n return True\nsentence = input()\nsentence = sentence.lower()\nif pg(sentence):\n print(... | eJztV7mu9lQSnGDCiZgXKN0Y8QCTed93+/MCCHnf9+3Yo5F4CHhfLERA8iPuFZoA3Y4slc5xn+5WddWP//z531/949cI/vV8fPvft3qY9u3tP3i7Qakclrev8ZaTKU+3PPth3Lff0GHcMMVDucT9d8Pb/77G704mSJGhQIkKDVp06DFgwowFKzYcOEFw4f7A3QGNoYg4y3mtWEmxoZKRYDqKk04z305sHWZQdkhdFHt0pusY2qgD4LIyj4DW8gVVB9POcCPfFbEerFzEVLaUvKqEXSdsqsr7EBpZnV4DKYI9psAZ9heS/VKiyM9CbZ/X... | null |
433 | Counting Sort 1 | **Comparison Sorting**
Quicksort usually has a running time of $n \times log(n)$, but is there an algorithm that can sort even faster? In general, this is not possible. Most sorting algorithms are _comparison sorts_, i.e. they sort a list just by comparing the elements to one another. A comparison sort algorithm cann... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> countingSort(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.Scanner;\npublic class Solution{\n public static void main(String[] args){\n Scanner sc = new Scanner(System.in);\n int len = sc.nextInt();\n int[] arr = new int[len];\n for(int i = 0; i < len; i++)\n arr[i] = sc.nextInt();\n displayCoun... | {
"class_name": null,
"func_sign": [
"countingSort(arr)"
],
"solution": "N = int(input())\n\narr = list(map(int, input().split()))\n\nfreq = [0]*100\n\nfor i in arr:\n freq[i] = freq[i]+1\n\n\nprint (' '.join(map(str, freq)))",
"template": "#\n# Complete the 'countingSort' function below.\n#\n# The fun... | eJzsvT2PdUuSnSdDlkyZsgrXHmPndyZ/iQA1QINsg05zjB6AAEFAP10Zz1pZd6DBSAJEYAQhJs/crrfqnH32XpkZnysi//f/8X/9X/7n/+l/+N/+6x//6W//+E9//+Pf/fwxvu/7y9/O+clXvvKVr3zlK1/5yle+8pWvfOUrX/nKV77yla985Stf+cpXvvKVr3zlK1/5yle+8pWvfOUrX/nKV77yla985Stf+cpXvvKVr3zlK1/5yle+/u9ef/zDzx9//S//+Nf/8Pe//sd//5//6e+uWf1+/v8wVHn7x3/7h59/Vo5bPn77b31vOXLk... | null |
2,223 | Gemstones | There is a collection of rocks where each rock has various minerals embeded in it. Each type of mineral is designated by a lowercase letter in the range $ascii[a-z]$. There may be multiple occurrences of a mineral in a rock. A mineral is called a _gemstone_ if it occurs at least once in each of the rocks in the collec... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int gemstones(List<String> arr)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputM... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.HashSet;\nimport java.util.Scanner;\nimport java.util.Set;\n\npublic class Solution {\n public static void main(String[] args) {\n Scanner in = new Scanner(System.in);\n\n int count = in.nextInt(); in.nextLine();\n\n Set<Character> gems = new HashSet<>();\n ... | {
"class_name": null,
"func_sign": [
"gemstones(arr)"
],
"solution": "import string\n\nn = int(input())\n\nans = set(string.ascii_lowercase)\nfor i in range(n):\n\ts = set(input())\n\tans &= s\n\nprint(len(ans))\n",
"template": "#\n# Complete the 'gemstones' function below.\n#\n# The function is expected ... | eJzsvVmOdD2SJaYHrUMoFKC3fqihB7VWIkA/IHCeL+dREKBNaL86Fl+mUGN3/tlZemoPj3D363cgjWbHzuElGf/3//j//M/rf/h5/G//E9787//nX7uvzPHX/+tf/fXf/c1vH/s3efB/9PiXr/Jf3+PPv+I/e/wbVfT/n6v8kwv+eVf5rxjo36r8f/Gr/Cn1+JOv8qee7E887e847Pdf+XeW6b/5BH9hw/1pV/mX9/q3udKfsOefU80/szz/7Vf+R1f5i5byzzjZrxP+9b/7q79WpygxlPw/8hx/TDz45v/6d3/1D1LR3/6n375ww1lX... | null |
20,389 | Beautiful Binary String | Alice has a [binary string](https://www.ics.uci.edu/~alspaugh/cls/shr/binaryString.html). She thinks a binary string is beautiful if and only if it doesn't contain the [substring](https://en.wikipedia.org/wiki/Substring) $\texttt{"010"}$.
In one step, Alice can change a $0$ to a $1$ or vice versa. Count and print the... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int beautifulBinaryString(String b)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(Stri... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class A {\n\tvoid run() {\n\t\tint n = in.nextInt();\n\t\tString s = in.next();\n\t\tString bad = \"010\";\n\t\tint ans = 0;\n\t\twhile (s.contains(bad)) {\n\t\t\tans++;\n\t\t\tint i = s.indexOf(bad) + 2;\n\t\t\ts = s.substring(0, i) + \"1\" + s.substrin... | {
"class_name": null,
"func_sign": [
"beautifulBinaryString(b)"
],
"solution": "#!/bin/python3\nimport re\n\nimport sys\n\n\nn = int(input().strip())\nB = input().strip()\nprint(len(re.findall(\"010\", B)))\n",
"template": "#\n# Complete the 'beautifulBinaryString' function below.\n#\n# The function is ex... | eJy9VUsKwjAQdSGeo2RdZKZpafEkghUX2oWb2kULgggeQnHnWU2TSQ0pKc0iDk1IwvTNm3n5PJavz2ohbfsWg92Nneuma9kmYrwoa0AAQNX1vTSUNqwDlDWLI1Zdm+rYVqfDpWsJAtk9jgzItKxRQM72T7iiQIEGCjiBkVgYKCCczmA5F5lgKCOpaD1bGhszyYfWQBcCdJHQ+AX1zMkgt+kKVx0AcHaWOWnlIQZXuRJPnQiNfkI78dKxuOCzGdCIT9UKI6pwdiOPnEEKEN78GOEfzLNG6hwE/ZyMOHdQolMarnNvUUeV6H4I2Dx007JN... | null |
2,343 | The Love-Letter Mystery | James found a love letter that his friend Harry has written to his girlfriend. James is a prankster, so he decides to meddle with the letter. He changes all the words in the letter into [palindromes](https://en.wikipedia.org/wiki/Palindrome).
To do this, he follows two rules:
1. He can only reduce the value of a... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int theLoveLetterMystery(String s)"
],
"script_name": "Solution",
"solution": "import java.util.Scanner;\n\n\npublic class Solution {\n\n\t/**\n\t * @param args\n\t */\n\tpublic static void main(String[] args) \n\t{\n\t\tScanner scan = new Scanner(Sy... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.lang.*;\nimport java.util.*;\n\npublic class Solution\n{\n\tprivate static BufferedReader in;\n\tprivate static PrintStream out;\n\tpublic static void main(String args[]) throws IOException\n\t{\n\t\tin=new BufferedReader(new InputStreamReader(System.in));\n\t\tout=new Pr... | {
"class_name": null,
"func_sign": [
"theLoveLetterMystery(s)"
],
"solution": "for t in range(int(input())):\n s = input()\n count = 0;\n for i in range(len(s)//2):\n count += abs(ord(s[i])-ord(s[len(s)-i-1]))\n print(count)",
"template": "#\n# Complete the 'theLoveLetterMystery' functi... | eJztfemuJEd2ng34QYT5LRjsJrub1JMY8DWM2Pd9D0OAH8IP7BNZt0mOhz225JE4I8WX3VVZGZkRJ85+6lZG/s//9F/+If/H//Bf/8cflI+t/uEf/u4Pn988Q4UZJPB0oYe2PacLG1KT1CPV1OubX0lKKZDrrHhbtPZLxSF3Lry66iNSzvU0uEUq4RiLV61zLLZFVAeTdBlG52mmevNEvnmVpx9URqxbUlq15GyJyM65mppuhFpKVWyt2k3rOLc2RkxM5mEHTy7HlWjPCqFQVVnSVKd6wDtHV1Q0qlSENWp8Yu+c9WnuybiXJbrWgKaa... | null |
49 | Insertion Sort Advanced Analysis | Insertion Sort is a simple sorting technique which was covered in previous challenges. Sometimes, arrays may be too large for us to wait around for insertion sort to finish. Is there some other way we can calculate the number of shifts an insertion sort performs when sorting an array?
If $k[i]$ is the number of elemen... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int insertionSort(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.InputStreamReader;\nimport java.io.IOException;\nimport java.io.BufferedReader;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.io... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n\n Scanner in = new Scanner(System.in);\n int t = in.nextInt();\n\n for (int i = 0; i < t; i++) {\... | {
"solution": "\n \n\nimport java.io.File;\nimport java.io.FileInputStream;\nimport java.io.FileNotFoundException;\nimport java.util.Scanner;\n\npublic class Solution {\n\n private int[] originalArray;\n\n public static void main(String[] args) {\n\n Scanner sc;\n try {\n sc = new Scann... | {
"class_name": null,
"func_sign": [
"insertionSort(arr)"
],
"solution": "def mergeSort(m):\n if len(m) <= 1:\n return [0, m]\n mid = len(m)//2\n l = []\n r = []\n for i in range(mid):\n l.append(m[i])\n for i in range(mid, len(m)):\n r.append(m[i])\n left = mergeSo... | eJzsvcuutFl2lU2DJhcRqrYb63zgSpBIiQa4QSehYSQkhMS1cJm0GM+zdhmwXQIbl9MF8fOnozK/+PaOeOda8zDmmGP+l3/6L/7bf/1n/+Rf/qff/dtf//1/+Ivf/fPP7+ovv/az7i+/nnHGuPfzx35d9bY9xh/993xfv6/f1z/8uttqe63f/HN8X7+v39fv69/19fZRyjq/+ef4h3qd+b9nz9/8c3xff6PzPvo++7f/HN/X7+v/T6+j5X+db936ff2+fl+/r9/Xv/m1rjH33/5vlVnbb/7Zv69/v6+7r9r3167f1+/r9/X/4rXXXdvf... | null |
708 | Anagram | Two words are [*anagrams*](https://en.wikipedia.org/wiki/Anagram) of one another if their letters can be rearranged to form the other word.
Given a string, split it into two contiguous substrings of equal length. Determine the minimum number of characters to change to make the two substrings into anagrams of one an... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int anagram(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n\tstatic void solve() throws IOException {\n\t\tint tests = nextInt();\n\t\twhile (tests-- > 0) {\n\t\t\tString s =... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.BufferedReader;\nimport java.io.InputStreamReader;\n//import java.util.Arrays;\n\npublic class Solution {\n\t\n\tpublic static void main(String[] args) throws Exception {\n\t\t\n\t\ttry(BufferedReader reader = new BufferedReader(new InputStreamReader(System.in))){\n\n\t\t\tint T = Intege... | {
"class_name": null,
"func_sign": [
"anagram(s)"
],
"solution": "T = int(input())\nfor i in range(0,T):\n\tal= (input())\n\tl = len(al)\n\tif (l%2==0):\n\t\thalf = int(l/2)\n\t\ta = al[:half]\n\t\tb = al[half:]\n\t\tcount = 0\n\t\tfor c in a:\n\t\t\tif c in b:\n\t\t\t\tpos = b.find(c)\n\t\t\t\tb=b[:pos]+b[... | eJzknNmuJslVhUHiLbix+tpIdrkZDC+CxJFQzPM8B0Li0Vnxt8sDHq64Auh2nzr1DxkRe6/1rczI/K+/+dd/+du//qt/+48fTMyj//DPP/vhH759xXzH5NqxlWc6negmNSuGTJ9ryGzM24I2kw11BLmteFri7Sk3corK1zDlUne30nwV7ZGa7NZJKQmVbNfpHhOUrWX2tk2tN5hw5panBi2Jy4KIqZfPx5ik9ih2c+67Nak4T9tt9dp7B45s5sTY6UPJumxlTQ19Q2IpzaPIJcmkuWQZSfRaubVdSpE0r3mI5rOqqicVpNi0Se9Ntscf... | null |
745 | Game of Thrones - I | Dothraki are planning an attack to usurp King Robert's throne. King Robert learns of this conspiracy from Raven and plans to lock the single door through which the enemy can enter his kingdom.
But, to lock the door he need... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String gameOfThrones(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\n\npublic class Solution {\n\n public static void solve(Input in, PrintWriter out) throws IOException {\n String s = in.next();\n int[] coun... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\n\nclass Solution\n{\n\tprivate static BufferedReader in;\n\tprivate static PrintStream out;\n\tpublic static void main(String args[]) throws IOException\n\t{\n\t\tin=new BufferedReader(new InputStreamReader(System.in));\n\t\tout=new PrintStream(new BufferedOutputStream(System.out));\... | {
"class_name": null,
"func_sign": [
"gameOfThrones(s)"
],
"solution": "string = input()\ncharacter_count = {}\nfor i in string:\n if i not in character_count:\n character_count[i] = string.count(i)\nodd_counts = 0\nfor i in character_count:\n if character_count[i] % 2 == 1:\n odd_counts... | eJwknFmuNTkRhJHgjU2gXgZS7wOJJ89jep55YelEHUB0N3/fe47Lzoz4wuWq//7tX3//869/+fd//nCpzPHHP//xh6VSgzo856oG1efifCFp10x3LBQxrOvvqsP2ybqI/ky9jNmc3HnZytDSNMfFuPvSwbhhzGmPpErsHD4GW4t8EltSopZC5a9ZcQpZeU0Kgk5k3bZ38TXyvOh3kuJZvlmdjOXlhajBBJl7uSmFfivzhpKsb653LJ9K9/l0fmSNUNTq9CF0vYwU0l07OXXHp77D7zD56k1GxarTWoe8araz1s0C4Su4nXLdycSYHIPv... | null |
5,187 | Two Strings | Given two strings, determine if they share a common substring. A substring may be as small as one character.
**Example**
$s1 = \text{'and'}$
$s2 = \text{'art'}$
These share the common substring $a$.
$s1 = \text{'be'}$
$s2 = \text{'cat'}$
These do not share a substring.
**Function Description**
C... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String twoStrings(String s1, String s2)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.uti... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class TwoStrings {\n\n\tBufferedReader br;\n\tPrintWriter out;\n\tStringTokenizer st;\n\tboolean eof;\n\n\tvoid solve() throws IOException {\n\t\tint t = nextInt();\n\t\touter: while (t-- > 0) {\n\t\t\tchar[] a = nextToken().toCharArray();\n\t\t\tchar[] ... | {
"class_name": null,
"func_sign": [
"twoStrings(s1, s2)"
],
"solution": "a = int(input())\nfor i in range(a):\n i = (input())\n j = (input())\n setx = set([a for a in i])\n sety = set([y for y in j])\n if setx.intersection(sety) == set():\n print(\"NO\")\n else:\n print(\"YE... | eJw0nUmyLTtyXdWQqaNJ0HIG6nIkMhM7p64RESgCAbCjnqattfx+JjM/37/v3DgIwH379hL/97//7//5//7Hf/s///mvV1pb/de//9u//td/pMv19Xh/n6fv4/79np6X2/v+un7ur9vz8T7d35fX7/Q5XS6vy/v3fp+f18/zdDq9Xpfr/fZ5/b6f2+V8et359ef1cjpdrpcnf3W6XR/n6/POZ7+f7+l0u7/vv8fv9/483vfHk7++vE6f1+PFN36e19Obr33+To/r9/E7nc+/J8/noa/H7XN53Pje6+n7+74efNXjzJKu7/vt8f1+Hqf3... | null |
21,584 | String Construction | Amanda has a string of lowercase letters that she wants to copy to a new string. She can perform the following operations with the given costs. She can perform them any number of times to construct a new string $p$:
* Append a character to the end of string $p$ at a cost of $1$ dollar.
* Choose any [substring](https... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int stringConstruction(String s)"
],
"script_name": "Solution",
"solution": "import java.io.IOException;\nimport java.io.PrintWriter;\nimport java.util.InputMismatchException;\n\npublic class CS1 {\n\tpublic static void main(String[] args){\n\t\tFast... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class A {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n... | {
"class_name": null,
"func_sign": [
"stringConstruction(s)"
],
"solution": "t = int(input())\n\nfor i in range(t):\n s = input()\n print(len(set(s)))",
"template": "#\n# Complete the 'stringConstruction' function below.\n#\n# The function is expected to return an INTEGER.\n# The function accepts ST... | eJzsvcmuLMmanaeBJhrpFS7uuCZVhCiRTyJACRDWm0XjEZHdLYogoEfX+pa5e/jOUg0408DSMk/usz3C3Zq/WX/r/8///H/W//V/+Z/+r//297G9//j97//5b3//51+2EFMutfVxuz+e2+v9+fW33//48x//+l//73VlXVlX1pV1ZV1ZV9aVdWVdWVfWlXVlXVlX1pV1ZV1ZV9aVdWVdWVfWlXVlXVlX1pV1ZV1ZV9aVdWVdWVfWlXVlXVlX1pV1ZV1ZV9aVdWVdWVfWlXVlXVlX1pV1ZV1ZV9aVdWVdWVfWlXVlXVlX1pV1ZV1ZV9aV... | null |
8,816 | Sherlock and the Valid String | Sherlock considers a string to be *valid* if all characters of the string appear the same number of times. It is also *valid* if he can remove just $1$ character at $1$ index in the string, and the remaining characters will occur the same number of times. Given a string $s$, determine if it is *valid*. If so, return... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static String isValid(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class _101HackJuneqA {\n\n\tpublic static void main(String args[]) {\n\t\tInputReader in = new InputReader(System.in);\n\t\tPrintWri... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class A {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"isValid(s)"
],
"solution": "s = input()\ndistinctList = []\ncountList = []\nfor c in s:\n if c not in distinctList:\n distinctList.append(c)\nfor d in distinctList:\n count = s.count(d)\n countList.append(count)\n#print(countList)\nkey = countList[0]\nfl... | eJyMnLmuJkkVhDHmQUZtzxNgY4OLBBLKfd/z5IaQeGtconocTMSImb793/qzMs+J+KIqq/79y1//9J9f/vC3f/5wudL88cdffxxaNod04o72bT1mtoHL8pzdLtoUWKqhJG3DVFJ5G1Po5UTBhlZ3mqLuZtOY40IqnfJ95/QnlSxrtqTajHbttZmM1Q2XbOuPDknrFsnMRsc363i0ffh1HVUVTssjzha8c6PG3UlkIqM2KbNkXGf5aFraNWEAbzBdawjcd2vWS+w92ZN1Icwi29n8LblEuoYROTNYHdSaH+m0K4tgLtvafW++dBdm7uSZ... | null |
5,393 | Sherlock and Anagrams | Two strings are [*anagrams*][123] of each other if the letters of one string can be rearranged to form the other string. Given a string, find the number of pairs of substrings of the string that are anagrams of each other.
**Example**
$s = mom$
The list of all anagrammatic pairs is $[m, m], [mo, om]$ at positio... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int sherlockAndAnagrams(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n \n private static int count[]... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.Map;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.io.OutputStreamWriter;\nimport java.util.HashMap;\nimport java.util.Set;\nimport java.io.BufferedReader;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.util.Random;\nimport java.i... | {
"class_name": null,
"func_sign": [
"sherlockAndAnagrams(s)"
],
"solution": "for _ in range(int(input())):\n was = dict()\n s = input()\n\n n = len(s)\n for i in range(n):\n for j in range(i, n):\n cur = s[i:j + 1]\n cur = ''.join(sorted(cur))\n was[cur] ... | eJy9GFuO47gxHzlCDjDo70Vgt9vu7pwkQLxYUCIpvt+URAUBcojkvqmipmdn1vYgCGZTFutNtsQii8X+5x//rf/0hw5/pcD87e9P0oVanv7y6el4uLoSSygxBMAdIjwhgiJE0AUUY+dK5wraQEaKzl0FGIdBFPc+gMNnBXBXNwuhtRCzFjOgGSk00AEGA4jI7oYuCrF77N4z9ELog3RL74TK7iHQ4epySinnxHlKvJOd4xxZNGTggaBX7g15UIEhozfSzuWd7UPw3Qf9QXl1QkYJAAg5mIAIVIAghegG8cGgB7T4qxq9JWLRRcAoIocD... | null |
660 | Common Child | A string is said to be a child of a another string if it can be formed by deleting 0 or more characters from the other string. Letters cannot be rearranged. Given two strings of equal length, what's the longest string that can be constructed such that it is a child of both?
**Example**
$s1 =\text{ 'ABCD'}$ ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int commonChild(String s1, String s2)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(St... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.Scanner;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n String a = sc.next();\n String b = sc.next();\n \n System.out.println(lcs(a,b).length());\n }\n public static String lcs... | {
"class_name": null,
"func_sign": [
"commonChild(s1, s2)"
],
"solution": "import sys\n\ndef main():\n a = [l for l in sys.stdin.readline().strip()]\n b = [l for l in sys.stdin.readline().strip()]\n\n a = [l for l in a if l in b]\n b = [l for l in b if l in a]\n\n print(len(lcs(a, b)))\n\ndef lcs(a, b)... | eJzsnbuOLV2WlTF4kFbZbTQN3Vy8ue73+51fwoA2cH7aaCQkhMRL8HQ8BR4mI44wkIoSFmohclWp6pyTmXtHrDXnGN/YGSviP//D//Lf/+s/+DXOf8Mf/uV//MO//f1v//3f/eFf/Nkf9gxbxeiuWtVybp1g8Vqljsjt2VdfWeJEUzVjojY3bAw3q95fiWY/zf1bzOtme0jZC7XFoCKq8msuCnxvWeLRxt60uKqpzN6WxAt7Edziu5rybpW6aTanw1dPSLcXdXzrc7QYpwinD6WV9V3bnqMgP1WTPRCfws6ZpzReljZjaNkkekxs5Ya6... | null |
2,335 | Morgan and a String | Jack and Daniel are friends. Both of them like letters, especially uppercase ones.
They are cutting uppercase letters from newspapers, and each one of them has his collection of letters stored in a stack.
One beautiful day, Morgan visited Jack and Daniel. He saw their collections. He wondered what is the lexicograp... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static String morganAndString(String a, String b)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.math.BigInteger;\nimport java.util.*;\n\n\npublic class Solution {\n BufferedReader reader;\n\n int nextInt() throws IOException {\n tokenizer.nextToken();\n return (int) tokenizer.nval;\n }\n\n String next() throws IOException {\n tokenizer.nextToken();\n ... | {
"class_name": null,
"func_sign": [
"morganAndString(a, b)"
],
"solution": "import io\ndef pick_smaller_char(s1, s2, idx1, idx2, len1, len2, i1, i2):\n if(len1 <= idx1[0]):\n idx2[0] += 1\n return s2[idx2[0]-1]\n if(len2 <= idx2[0]):\n idx1[0] += 1\n return s1[idx1[0]-1]\n... | eJzs3cmuJct1Juga1Kxe4iLGnCgrc8KZ9a1b37hZBaCBdIHS5IiDS0CAIKDeoF651iapFCklkVKCJVLU/wHq4o/Y27e72bK1zj4C/5///f2//9//43/7v/7+2998/eKXP337+Q/f/uL7Vxs9+Z0N3/1+/+rfv7797IdvP/7dL378q59+/Ou//Ntf/vSbv9r67/zFb//wsx9+94UYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAwB8KF1LhPzYVAAAAAAAAAAAAAAAAAAAAAAAA... | null |
20,191 | Build a Palindrome | You have two strings, $a$ and $b$. Find a string, $s$, such that:
* $s$ can be expressed as $s =s_a + s_b$ where $s_a$ is a non-empty [substring](https://en.wikipedia.org/wiki/Substring) of $a$ and $s_b$ is a non-empty substring of $b$.
* $s$ is a [palindromic](https://en.wikipedia.org/wiki/Palindrome) string.
* The l... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static String buildPalindrome(String a, String b)"
],
"script_name": "Solution",
"solution": "import java.util.*;\n\npublic class PalindromeBuilder {\n public static class State {\n int length;\n int link;\n int[] next = new int[128]... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.Comparator;\nimport java.util.InputMismatchException;\n\npublic class F3 {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\... | {
"class_name": null,
"func_sign": [
"buildPalindrome(a, b)"
],
"solution": "from os.path import basename,exists,expanduser,splitext,isfile\nfrom os import getcwd\nfrom sys import stdin,modules,path\nimport sys\nfrom array import array as ar\nfrom collections import Counter,defaultdict as ddict\nfrom functo... | eJzt10mOZUlWAFAGjBiygpCPoxAJCFCuBImPUq/v7fVtKSUWwXpYG/aThCplpNcIKQGdI1co/P3/rLl27Zr5v/75P/3lv//Fn/3z7z+aMO3bx/dfPv7hFZ62r5o1lH0emmUvt6Xsryubr7DOZVFdWdV1ydgl83mFJDnKV7hfoc33kB9reQ31vJ3dk9b5VF3PvRxlbGou0rJNivoV+qUrhy5J03PMYk/JffbVMd/5tKXJPnX3Fpaqv49XOPOlyKayq6sy9rBk85kUyTGV25M38z1kT+x2DGVdJn0Xv1Cux1yH+Qxdnu3jVe3bWl3FXHdr... | null |
48,866 | Cards Permutation | Alice was given the $n$ integers from $1$ to $n$. She wrote all possible permutations in increasing lexicographical order, and wrote each permutation in a new line. For example, for $n = 3$, there are $6$ possible permutations:
1. $[1, 2, 3]$
2. $[1, 3, 2]$
3. $[2, 1, 3]$
4. $[2, 3, 1]$
5. $[3, 1, 2]$
6. $[3, 2, 1]$
... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static long solve(List<Integer> x)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.regex.*;\n\npublic cla... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.*;\n\npublic class CardsPermutationFinal {\n private final static long MOD = 1000000007;\n private final static long INV_TWO = inverseElmnt(2);\n private static final long Y_DISP = ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n private static final int modulus = 1000000007;\n private static int[] knowns; // known n... | {
"class_name": null,
"func_sign": [
"solve(x)"
],
"solution": "from bisect import bisect_right, bisect_left\n\nMOD = 10 ** 9 + 7\nN = 3 * 10 ** 5\n\n\nclass SegmentTree:\n def __init__(self, arr):\n self.size = len(arr)\n self.tree = [0] * (2 * self.size)\n self.build(arr)\n ... | eJzs3dGqZMuWmGdj/CDJuRY4Y4wxY4zUkxjcoAupL3TT1kU3CITAj+74otxgcfrIAoOQYSqa1FZrRu1d81+1Vs4vI6L+z//lf/tf/+l//p/+9//0l3//D//hn/7xL//685f1/bt/WJ/45Kc+z2d/+jOf32d9//KvPn/5+//4H/7+3/7j3/+7f/N//NM//vPlf/cPf/nP/+rzX/wC37/xS3zW+qz4rPys+qzns/Zn9WfNZ/0+8f3EmROfyE/UJ55P7E/0J+YTv09+P7k+eX7J/GR98vnk/mR/cj75+9T3U+tT8anzb6xPPZ/an+pPzad+... | null |
63 | String Similarity | For two strings A and B, we define the similarity of the strings to be the length of the longest prefix common to both strings. For example, the similarity of strings "abc" and "abd" is 2, while the similarity of strings "aaa" and "aaab" is 3.
Calculate the sum of similarities of a string S with each of it's suffixes.... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int stringSimilarity(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n\tprivate void solution() throws IOException {\n\t\tint ts = in.nextInt();\n\t\twhile (ts-- > 0) {\n\t\t\t... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.Arrays;\nimport java.util.Scanner;\n\npublic class Solution {\n\n static class SuffixArray {\n private char str[];\n private int MAX_LOG = 30;\n private int n, nr0[], nr1[], rank[][], index[], step, cnt;\n\n private int M;\n private int minusOneHea... | {
"class_name": null,
"func_sign": [
"stringSimilarity(s)"
],
"solution": "# Z Algorithm\n# Followed demo from:\n# http://www.utdallas.edu/~besp/demo/John2010/z-algorithm.htm\n# to implement\n\nif __name__ == '__main__':\n N = int(input())\n \n for line in range(N):\n string = input()\n ... | eJzsfMmuJMt1pBba6Cv6odZckCJakPglAroAwed5np0Q0J/eFhfaNbTXwg3EIVlVNzPS/RwbIjzv//3Hf/f/65/+4f/8/ZeJefRff/vj119+xxBTLq+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sorr7zyyiuvvPLKK6+88sor... | null |
1,031 | Pseudo-Isomorphic Substrings | Two strings A and B, consisting of small English alphabet letters are called pseudo-isomorphic if
- Their lengths are equal
- For every pair (i,j), where 1 <= i < j <= |A|, B[i] = B[j], iff A[i] = A[j]
- For every pair (i,j), where 1 <= i < j <= |A|, B[i] != B[j] iff A[i] != A[j]
Naturally, we use 1-indexation in ... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> pseudoIsomorphicSubstrings(String s)"
],
"script_name": "Solution",
"solution": "/* HackerRank Template v0.21 by Sergey Esipenko\n * \n * v0.21\n * - fixed RuntimeError\n * */\n\nimport java.io.*;\nimport java.math.*;\nimport java.ut... | {
"solution": "import java.util.HashMap;\nimport java.util.Map;\nimport java.util.Scanner;\n \npublic class PseudoIsomorphicSubstrings {\n \n public static class ST {\n \n public static class Node {\n private final int valuesFromRootCount;\n private final Map<Integer, Edge> edges;\n ... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.io.PrintWriter;\nimport java.math.BigInteger;\nimport java.util.Arrays;\nimport java.util.Collection;\nimport java.util.Comparator;\nimport java.util.HashMap;\nimport java.util.Locale;\nimport ja... | {
"class_name": null,
"func_sign": [
"pseudoIsomorphicSubstrings(s)"
],
"solution": "s = input()\n\nprevs = dict()\na = []\nfor i in range(len(s)):\n if s[i] in prevs:\n a.append(i - prevs[s[i]])\n else:\n a.append(i + 1)\n prevs[s[i]] = i\n\nclass Node:\n def __init__(self, **d):\... | eJy8fcnOw0rTFgtugt2vb83Cc3dzJUgcCcWZ7MSJEyex4yAk7oZr4O54Br+IJSvO0Tmp127bPVTXXNX/49//5//1P//Dv/sv/+1f/f3xef/rP/3bv3bt/4d///Uf/+1fx+/juH8fD/91/Ly3b+f/3It/7uU/9+qfe/3PvfnnHv65x3/u6Z97nuE/3M/RIEeLHE1ytMnRKEerHM1ytCvQruB70K5AuwLtCrQr0K5AuwLtCrQr0a5Eu5IfRLsS7Uq0K9GuRLsS7Uq0q9CuQrsK7Sr2DO0qtKvQrkK7Cu0qtKvRrka7Gu1qtKs5BLSr0a5G... | null |
33,387 | KnightL on a Chessboard | $KnightL$ is a chess piece that moves in an `L` shape. We define the possible moves of $KnightL(a, b)$ as any movement from some position $(x_1, y_1)$ to some $(x_2, y_2)$ satisfying either of the following:
- $x_2 = x_1 \pm a$ and $y_2 = y_1 \pm b$, or
- $x_2 = x_1 \pm b$ and $y_2 = y_1 \pm a$
Note that $(a, b)$... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static List<List<Integer>> knightlOnAChessboard(int n)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static vo... | {
"solution": "DNE",
"template": "class Result {\n\n /*\n * Complete the 'knightlOnAChessboard' function below.\n *\n * The function is expected to return a 2D_INTEGER_ARRAY.\n * The function accepts INTEGER n as parameter.\n */\n\n public static List<List<Integer>> knightlOnAChessboard(in... | {
"solution": "\nimport java.io.PrintStream;\nimport java.util.Arrays;\nimport java.util.Scanner;\n\npublic class Solution {\n\n private final Scanner in;\n private final PrintStream out = System.out;\n\n public static void main(String[] args) throws Exception {\n Solution solution = null;\n tr... | {
"class_name": null,
"func_sign": [
"knightlOnAChessboard(n)"
],
"solution": "#!/bin/python3\n\nimport sys\n\n\nn = int(input().strip())\n# your code goes here\nA=[]\nfor a in range(1,n):\n B=[]\n for b in range(1,n):\n P={(0,0)}\n c=0\n f=True\n V=set()\n while f:\... | eJztWs2O5DQQ5sCDtOa8QXHZcdI8CRIDHGAOXIY97EpICImHgPfFVV+V4yR2fmaEEKi3s5m04ypXlevX1X98+dcLfSH/vvk+PXz729PPrx8/f3r6+vZEw/Pr04fb08uvH19+/PTy0w+/fP5kr8LNxZsjvqb0ifK1T08hfSZ5E2/U31y40cRvfEyTQvp2C9Pt+XUFzfc0lF4T3xgFL0F8j3xLqPgut8DwBXDE8kFpCLyo00FdRx7sb7oEgRJOuMlyCTw/6gr5kebHdD2/ZvDOCd+yZHoGgp75Tt+oBy8yrbwYAWifRGTT4hkfKp5ZatGW... | null |
14,104 | Short Palindrome | Consider a string, $s$, of $n$ lowercase English letters where each character, $s_i$ ($0 \le i \lt n)$, denotes the letter at index $i$ in $s$. We define an $(a, b, c, d)$ palindromic tuple of $s$ to be a sequence of indices in $s$ satisfying the following criteria:
* $s_a = s_d$, meaning the characters located at ind... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int shortPalindrome(String s)"
],
"script_name": "Solution",
"solution": "import java.io.BufferedReader;\nimport java.io.InputStreamReader;\n\npublic class Solution {\n\n\tpublic static final int MOD = 1000000000 + 7;\n\n public static void main(S... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class B {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"shortPalindrome(s)"
],
"solution": "mod = 10**9 + 7\n\ndef sum_multi(A,B):\n return A[0]*B[0] + A[1]*B[1] + A[2]*B[2] + A[3]*B[3] + A[4]*B[4] + A[5]*B[5] + A[6]*B[6] + A[7]*B[7] + A[8]*B[8] + A[9]*B[9] + A[10]*B[10] + A[11]*B[11] + A[12]*B[12] + A[13]*B[13] + A[14]*B... | eJwcnEmy5FoRRBkwZBFYLYOVYMYobt/3PRM2xEZYFa40mvq/Xr5M6UaE+3HpKv/z13/+779/+8u//v3HpjLHn3/8/Q8rZoRsbr5lZ3F4TEpek8SYfV+r5duqXiqHuRH2znwur00ON3nFn9PMlOq0457Mpc5kkC28V7xcVdXeYg06eC1nLcPawLOTJj9mqMj4wlrbNh4vF80OE1a/SdqX19E6tb7lsjF713O5ZqkWQrnzqclT8ZW3O4zaW4Y1WgzihRvbbaF2nWRvlcs6SAmauyzN6E0z16lnTJFmKZ7HWqbF24ceZjWjcudI6FnfNnHr... | null |
13,331 | Beautiful Quadruples | We call an quadruple of positive integers, $(W, X, Y, Z)$, *beautiful* if the following condition is true:
$$W \oplus X \oplus Y \oplus Z \neq 0$$
**Note:** $\oplus$ is the [bitwise XOR](https://en.wikipedia.org/wiki/Bitwise_operation#XOR) operator.
Given $A$, $B$, $C$, and $D$, count the number of *beautiful* quadr... | hackerrank | Medium | {
"class_name": null,
"func_sign": [
"static int beautifulQuadruples(int a, int b, int c, int d)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main... | null | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class D {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n... | {
"class_name": null,
"func_sign": [
"beautifulQuadruples(a, b, c, d)"
],
"solution": "#!/bin/python3\n\nimport sys\n\n\nA,B,C,D = input().strip().split(' ')\ntemp = [int(A),int(B),int(C),int(D)]\ntemp.sort()\nA,B,C,D=temp\n\ntot=[0]*4100\n\ntree=[([0]*3100).copy() for i in range(4100)]\ncnt=[([0]*3100).cop... | eJydlE1q3EAQhbNITuFNobUx9f/jkxgck0Uyi2wmXowhEAw+hH1fl5yBcXqiJkQtNb3Q+/p1vZKePr4snz68XTcXvbj9tXzf3z8clmtYKDBAGYhZgYzw8365hGX383739bD79uXHw+H4plBqlDmGL4+X8I4R1VJqDgsVUGRsQtxNJdIrTAaKu7QBLjBcIaGbEEpJQ9X2wgOkXWDbQAG2XgXZJqXQlDHVi2ygsKEDsztEP6Q28YLVDI3eTXHASCgwRRM8q13VpC7KicxV5eORGN3AU6ArD6mybUUwUsi0mEZGqcEaTkTXVnGScoQkqplp... | null |
3,470 | Absolute Element Sums | Given an array of integers, you must answer a number of queries. Each query consists of a single integer, $x$, and is performed as follows:
1. Add $x$ to each element of the array, permanently modifying it for any future queries.
2. Find the absolute value of each element in the array and print the sum of the absolute... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> playingWithNumbers(List<Integer> arr, List<Integer> queries)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class C {\n static InputStream is;\n static PrintWriter out;\n static String INPUT = \"\";\n... | {
"solution": "import java.io.*;\nimport java.util.*;\n\n/**\n * Created by witalia on 12.12.14.\n */\npublic class Solution {\n\tpublic static void main(String[] args) throws IOException {\n\t\tInputReader in = new InputReader(System.in);\n\t\tPrintWriter out = new PrintWriter(new BufferedOutputStream(System.out));\... | {
"class_name": null,
"func_sign": [
"playingWithNumbers(arr, queries)"
],
"solution": "from collections import Counter\n\ndef q(arr, queries):\n positive_n = [el for el in arr if el >= 0]\n negative_n = [el for el in arr if el < 0]\n pos_size = len(positive_n)\n neg_size = len(negative_n)\n ... | eJzsvcuubDuynueG3sHdiWqfBAbvpJ7DDQMqQA2pGuqUTqMOIEAwYL+54/9+5m3OXHvtOjbsDneh1owcOQYHGQzG5Y8g8//8D//7//W//a//y3/6n3/5b3//13/7x1/+49df8hX//fXvN/394p9DHvKQhzzkIQ95yEMe8pCHPOQhD3nIQx7ykIc85CEPechDHvKQhzzkIQ95yEMe8pCHPOQhD3nIQx7ykIc85CEPechDHvKQhzzkIQ95yEMe8pCHPOQhD3nIQx7ykIc85CEPechDHvKQhzzkIQ95yEMe8pCHPOQhD3nIQx7ykIc85CEP... | null |
774 | Subset Component | You are given an array with $n$ $64$-bit integers: $d[0], d[1], ..., d[n - 1]$.
BIT(x, i) = (x >> i) & 1, where $B(x, i)$ is the $i^{th}$ lower bit of $x$ in binary form. If we regard every bit as a vertex of a graph G, there is an undirected edge between vertices $i$ and $j$ if there is a value $k$ such that BIT(d[k... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int findConnectedComponents(List<Long> d)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.math.BigInteger;\n\npublic class Solution {\n\n static int col = 0;\n static long[] a;\n\n public static void solve(Input in... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n private static int findConnectedComponents(long[] nums) {\n Result result = new Result();\n ... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.ArrayList;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\nimport java.util.List;\n\npublic class Solution{\n\tstatic InputStream is;\n\tsta... | {
"class_name": null,
"func_sign": [
"findConnectedComponents(d)"
],
"solution": "from functools import reduce\nfrom operator import or_\n\ndef get_integers():\n from sys import stdin\n return int(stdin.readline().strip()), sorted(map(int, stdin.readline().strip().split()))\n\ndef dec(s):\n return ... | eJyVls1uHUUQhVmw5CFaXkeo/rs7T4JEEAvIgo1hkUhICImHgPflq7GdXDMeK/hK1r0z1d1Vp8451X99/c/bb746/r5zvnz/x90v9799/HD3dtxpvLvPuSXWthi23SXnnEMlUnm4bXiKxdbpQ1WlZHqtYTJlL5XcQ5PXe2rKMJaJz+Bh8T/Cdr9fhKWpsquY+iJ4qM1gz60+dk5xTrKhM+eaZanv7u/ejLv3v//2/qcP73/+8dePHx4TzloRk9d/vhk3deS7e022JznhcDbJCM5LKeqSIZcb6jY5bedsN/hcp6F2WqSbVR6mewIbaZAN... | null |
5,595 | Dijkstra: Shortest Reach 2 | Given an undirected graph and a starting node, determine the lengths of the shortest paths from the starting node to all other nodes in the graph. If a node is unreachable, its distance is -1. Nodes will be numbered consecutively from $1$ to $n$, and edges will have varying distances or lengths.
For example, consid... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> shortestReach(int n, List<List<Integer>> edges, int s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\nclass Node implements Comp... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.ArrayList;\nimport java.util.Comparator;\nimport java.util.HashMap;\nimport java.util.PriorityQueue;\nimport java.util.Scanner;\n\npublic class Solution {\n\tstatic class Pair {\n\t\tint vertex = 0;\n\t\tint dist = Integer.MAX_VALUE;\n\n\t\n\t}\n\n\tpublic static void main(String[] ar... | {
"class_name": null,
"func_sign": [
"shortestReach(n, edges, s)"
],
"solution": "import heapq\n\ndef find(V,N,S):\n dist=[-1 for x in range(N)]\n visited=[False for x in range(N)]\n Q=[(0,S)] #use a priority queue\n dist[S]=0\n while Q:\n mindist,minv=heapq.heappop(Q)\n if not ... | eJy0vcuqbVuXrWXi+B6DSJ+A3nq7+ySCP5jQg5gJTZwDggg+uvX7Sp9/CGJOg4jYe+015xi9t0u9lFpqqf/nf/hv/+v/6T/8V//d//4v//O//a//5T//y3/z+5fxj3/r/df/8W/v/L3n18fb2z/+bf1a+913jfuPf2u/89vrGbt+pn56999860fa/o3xG3us5S/Xf7/9nPqbsX7r+Y331r+fXxu/O9f1t3+jPvX0e+rX72/t39xz1He386tfas9u9X3vb9UHjOd969EOP7X789Rf7F/fv3bPnvUdv/m7qz/1QKv9dj3jrP+pX6iPbfX1... | null |
28,277 | Real Estate Broker | You are a real estate broker in ancient Knossos. You have $m$ unsold houses, and each house $j$ has an area, $x_j$, and a minimum price, $y_j$. You also have $n$ clients, and each client $i$ wants a house with an area greater than $a_i$ and a price less than or equal to $p_i$.
Each client can buy *at most* one house, ... | hackerrank | Hard | {
"class_name": null,
"func_sign": [
"static int realEstateBroker(int[][] clients, int[][] houses)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\npublic class e {\npublic static void main(String[] args) throws IOException {\n\tinput.init(System.in);\n\tPrintWriter out ... | null | {
"solution": "import java.awt.*;\nimport java.awt.event.*;\nimport java.awt.geom.*;\nimport java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\n\n/*\nbr = new BufferedReader(new FileReader(\"input.txt\"));\npw = new PrintWriter(new BufferedWriter(new FileWriter(\"output.txt\")));\nbr = new Buf... | {
"class_name": null,
"func_sign": [
"realEstateBroker(clients, houses)"
],
"solution": "# Enter your code here. Read input from STDIN. Print output to STDOUT\nimport sys\n\ndef kuhn(v):\n global house, used, buyers\n if used[v]: \n return False\n used[v] = True\n for buyer in buyers[v]:\... | eJzsvcuqLUuapacCPYgT7WrY/aInEShAjapEqBOqRhYUCIGeSs+n8X02dyIyiCIL1FBDGeTZ56w9l093c7P/Osb4/8///n/8X/6vf/ff/U//+1/+17/9p//8z3/5H76/tG/+9W93t9PaLeerfZV1bs0PZ+u1lL2/1XefZY7117+N0tu69+xvtLturev89W911dvXXPVb+4y+271//dtqu87Zyv72ab31kQ+Oecus8+SD8/bRZs0Hey65W1/fWeuU1Wo++Jd///3ln/7Lf/qn//DP//Qf/+f/7T//8+9ea/7m//j33//j7mvh9uuXG/3r... | null |
22,036 | Demanding Money | Killgrave wants to use his mind control powers to get money from the Justice League superheroes living in $N$ houses in Happy Harbor that are numbered sequentially from $1$ to $N$. There are $M$ roads, and each road $j$ connects two different houses, $A_j$ and $B_j$. Each superhero house $i$ (where $1 \le i \le N$) has... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> demandingMoney(List<Integer> money, List<List<Integer>> roads)"
],
"script_name": "Solution",
"solution": "import java.io.BufferedInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.util.HashMap;\nimport ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n /*\n * Complete the demandingMoney function below.\n */\n private static long maxMoney = Integer.MIN_VALUE;\n private static Map<Long, Long> soluti... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class D2 {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\... | {
"class_name": null,
"func_sign": [
"demandingMoney(money, roads)"
],
"solution": "\ndef solve(C,G) :\n minLost = {}\n def getMinLost(housesToVisit) :\n# print(\"getMinLost %s :\" % str(housesToVisit))\n if not housesToVisit :\n return 0,1\n \n key = frozenset(h... | eJyNW0uObEkNZcBCQm/cQjccf1aCRCEG0AMmjx50S0ioJRYBK2LGqgj7HPvem596j5dkZmVVxsdhHx8fR//rt//53/qN/e8P/91v/vjPL3/7+tMvP3/5ffoiI7WPr2WmOpLUVGoaklpLcugnuen7UtLIaR5JJI2Zxn5TUm1p1bRKyjn1oe/b/m1NvSbJH19XymuPm6R/fK0pi77Px8fXnGTP9+WH9OXHf/z0419+/vGvf/77Lz9zMVnmTPnLrz+kywqnfa/k1Hra62y2wr0w2UMNHXbqU9Whpz7td5LKx9eehv7Y9cem7/ZnQ//k3eT9... | null |
14,770 | Find the Path | You are given a table, $a$, with $n$ rows and $m$ columns. The top-left corner of the table has coordinates $(0,0)$, and the bottom-right corner has coordinates $(n-1, m-1)$. The $i^{th}$ cell contains integer $a_{i,j}$.
A path in the table is a sequence of cells $(r_1,c_1), (r_2,c_2), \ldots, (r_k,c_k)$ such that for... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> shortestPath(List<List<Integer>> a, List<List<Integer>> queries)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nim... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class C {\n InputStream is;\n PrintWriter out;\n String INPUT = \"\";\n \n void solve(... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class C {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"shortestPath(a, queries)"
],
"solution": "import sys\nfrom heapq import *\n\nnum_rows = 0\nnum_cols = 0\nnum_queries = 0\ntable = []\nquery_dict = {}\nquery_results = []\nshortest_paths = []\nvisited = []\n\n\ndef read_input():\n global num_rows, num_cols, num_querie... | eJx8ncuuNEuSlRkw4S1CNe6B3y88CRJHYgA1YFL0oFtCQi3xvrwEtr5lkZlVRaEj/WfvnZERHu7mdnNby/73v/9P//Z//sO/+8//60///S///K//8qf/+PypPvWPv9S92x9/6X/8pTz89//64U//9Pzpz//zn//8X//lz//tv/yPf/2X9/t89fvvn/7tn56f249n/vGXtu962hrnaa23p+05nlpGPK+OGp+c0p969oxP2o1/ajyuldbj8hGXn7ufNu5T14yxtrr1wdKFtz3ncIMV94pv1Wc8TW9U4n/9iSfEneOHoY9qvEh/Pxr6gQ/1... | null |
32,559 | Marc's Cakewalk | Marc loves cupcakes, but he also likes to stay fit. Each cupcake has a calorie count, and Marc can walk a distance to expend those calories. If Marc has eaten $j$ cupcakes so far, after eating a cupcake with $c$ calories he must walk *at least* $2^j \times c$ miles to maintain his weight.
**Example**
$calorie = ... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static long marcsCakewalk(List<Integer> calorie)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void mai... | {
"solution": "DNE",
"template": "class Result {\n\n /*\n * Complete the 'marcsCakewalk' function below.\n *\n * The function is expected to return a LONG_INTEGER.\n * The function accepts INTEGER_ARRAY calorie as parameter.\n */\n\n public static long marcsCakewalk(List<Integer> calorie) ... | {
"solution": "import java.io.BufferedWriter;\nimport java.io.IOException;\nimport java.io.OutputStreamWriter;\nimport java.io.ObjectInputStream.GetField;\nimport java.math.BigInteger;\nimport java.util.ArrayList;\nimport java.util.Arrays;\nimport java.util.Collections;\nimport java.util.HashMap;\nimport java.util.Ha... | {
"class_name": null,
"func_sign": [
"marcsCakewalk(calorie)"
],
"solution": "#!/bin/python3\n\nimport sys\n\n\nn = int(input().strip())\ncalories = list(map(int, input().strip().split(' ')))\ncalories.sort(reverse=True)\nprint(sum([2**j * calories[j] for j in range(n)]))\n",
"template": "#\n# Complete th... | eJy1VstuHEcMzCGX/AWxZyNoks2Xv8RAFORg65CL4oMMBAgM+COcb8vN35JiTyQIOzsTH2wNene009NdJKuK/enHv7/89MP6e/MPbn756/L7w/sPj5fXdNG6e2BJ8goKpphGpfg2oSmTbBSVG7FOEg6yKBL8L5ibQ/Ea7kXJsgfNHpqk6pSMMZyMJ+HtMCYxozTMXCsoBR4nNolJHonbgZlKE7+l8t3D5RVd7v98f//28f7db398eHzCPCZH4VM8PDDt4yt6EZKMu4eJXbgmsTtJFvlM7OqkPihFgGIukFpJ3HGMjr0hAGkANJ77RA6Q... | null |
898 | Sherlock and The Beast | Sherlock Holmes suspects his archenemy Professor Moriarty is once again plotting something diabolical. Sherlock's companion, Dr. Watson, suggests Moriarty may be responsible for MI6's recent issues with their supercomputer, *The Beast*.
Shortly after resolving to investigate, Sherlock receives a note from Moriarty bo... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static void decentNumber(int n)"
],
"script_name": "Solution",
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\npublic class Solution {\n\tstatic BufferedReader in = new BufferedReader(new InputStr... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.BufferedReader;\nimport java.io.InputStreamReader;\n\npublic class Solution {\n\tpublic static int intValueOf( String str )\n\t{\n\t int ival = 0;\n\t \n\t for(int i = 0; i < str.length(); ++i) {\n\t \tival *= 10;\n\t \tival += str.charAt(i) - '0';\n\t }\n\t return i... | {
"class_name": null,
"func_sign": [
"decentNumber(n)"
],
"solution": "T = int(input())\nfor i in range(T):\n k = int(input())\n n5 = k\n n3 = 0\n done = False\n while n5 >= 0:\n if n5%3 == 0 and n3%5 == 0:\n for j in range(n5):\n print('5',end='')\n ... | eJzs3c1O7DgaBuBZzIVEXtciifPLfu5hpLHEArJgY2qRkpAQrbm7ua1JjlBG3Wqd7jnNwQU8z4JPTmzX60JUqYA4//77P3/5zz/+9q/n8JDPlzXcVKHpUp6HOvYpNzHGlOPcdNuxbmqnOeW2j9PWin3XtimPXTNNKfdjM26lbZo57j2neevZDO23c8PYDduArf8+IA7j1iWcqrA8nZe7dbm/fbysr4/dAwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA... | null |
4,879 | Chief Hopper | Chief's bot is playing an old DOS based game. There is a row of buildings of different heights arranged at each index along a number line. The bot starts at building $0$ and at a height of $0$. You must determine the minimum energy his bot needs at the start so that he can jump to the top of each building without hi... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int chiefHopper(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.util.Scanner;\n\npublic class Solution {\n\n public static void main(String[] args) {\n\t\tScanner in = new Scanner(System.in);\n\t\tint n = in.nextInt();\n... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.lang.Math;\n\npublic class Solution {\n\n public static void main(String[] args) {\n /* Enter your code here. Read input from STDIN. Print output to STDOUT. Your class should be named Solution. */\n Scanner input = new Scanner(System.... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.StringTokenizer;\n\npublic class Solution {\n\n\tprivate static class InputArray {\n\t\tfinal StringTokenizer strt;\n\t\tpublic final int length;\n\t\t\n\t\tInputArray(String str, int N){\n\... | {
"class_name": null,
"func_sign": [
"chiefHopper(arr)"
],
"solution": "N = int(input())\nheights = [int(n) for n in input().split()]\n\nmax_h = max(heights)\n\ninterval = [1, max_h]\n\ndef get_final_energy(e, heights):\n\tfor h in heights:\n\t\te = 2 * e - h\n\treturn e\n\nwhile interval[0] < interval[1] -... | eJzk3U2uJE2WFmAGiDFLCNUYJHe38xesBImWGEAPmDQMuiUkhMTS8fNEllSo1StgULfyy7wW4W72mtmxxyPz/p9//R//7b//N//qP/2vv/y3f/gf//SPf/kPn7881/13/3B/ns/5xCc/9enPfL6f+/rc9+d+Pvf53PG583PX5+7PPZ/7+3muz/O2eT7P+TzxefLz1OfpzzOf5/s51+fcn/O+5Pmc+Jz8nPqc/pz5nO8nrk/cn3g+8b5jfCI/UZ/oT8wnvp+8Pnl/8vnk+eR7QfnJ+mR/cj75/dT1qftTz6fOp+JT7/XWp/pT86nvp69P... | null |
1,905 | Sam and substrings | Samantha and Sam are playing a numbers game. Given a number as a string, no leading zeros, determine the sum of all integer values of substrings of the string.
Given an integer as a string, sum all of its substrings cast as integers. As the number may become large, return the value modulo $10^9+7$.
**Example**... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int substrings(String n)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatch... | {
"solution": "/*\n JAI MATA DI\n */\n\nimport java.util.*;\nimport java.io.*;\nimport java.math.BigInteger;\nimport java.sql.Array;\npublic class CP {\n static class FR{\n BufferedReader br;\n StringTokenizer st;\n public FR() {\n br = new BufferedReader(new In... | {
"solution": "import java.util.Scanner;\n\npublic class SamAndSubstring {\n\t\n\tprivate static final int MOD = (int) Math.pow(10, 9) + 7;\n\n\tpublic static void main(String[] args) {\n\t\t\n\t\tScanner in = new Scanner(System.in);\n\t\tString input = in.next();\n\t\tin.close();\n\t\t\n\t\tlong cumSum = 0;\n\t\tlon... | {
"class_name": null,
"func_sign": [
"substrings(n)"
],
"solution": "import operator\n\nMOD = 1000000007\n\ns = input()\nn = len(s)\na = []\np10 = 0\nfor i in range(n, 0, -1):\n\tp10 = (p10 * 10 + 1) % MOD\n\ta.append(p10 * i % MOD)\n\nb = [ord(c) - ord('0') for c in s]\nprint(sum(map(operator.mul, reversed... | eJzs3cuqbluy1XERH+SQZQvjfvFJBAULegpW1MIRBBF8dOP3H3OLsHM/gDpTOTlzrbm+b1x6jx7RorUW//Nf/Ov3H/75P/s3//1v//E//Zf/+k9/+1f/8Lf32a7jed/lOK71vpf12p7tPrZnWbftepft+tu//Ie//eN/+y//+O//6R//w7/7z//1n37+4bMt+7u/x/Vv/9Pf/se//If/4yPXbT/O637e5f/un/7ixs972+YZnc+fbny7t2M5luU+r/U9lvt91+d851m+z3s+13Fs63pf5/U8y/ley7Zc57tt+7tuyzG/9xzbfm7zp8v8... | null |
21,650 | Decibinary Numbers | Let's talk about *binary numbers*. We have an $n$-digit binary number, $b$, and we denote the digit at index $i$ (zero-indexed from right to left) to be $b_i$. We can find the *decimal* value of $b$ using the following formula:
$$(b)_2 \Rightarrow b_{n-1} \cdot 2^{n-1} + \ldots + b_2 \cdot 2^2 + b_1 \cdot 2^1 + b_0 \c... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static long decibinaryNumbers(long x)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] ... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n int max = 600000;\n int size = 20;\n \n int[... | {
"solution": "import java.io.OutputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.io.BufferedWriter;\nimport java.util.InputMismatchException;\nimport java.io.IOException;\nimport java.io.Writer;\nimp... | {
"class_name": null,
"func_sign": [
"decibinaryNumbers(x)"
],
"solution": "#!/bin/python3\n\nimport math\nimport os\nimport random\nimport re\nimport sys\nimport bisect\nimport array\nimport timeit\nfrom itertools import repeat\n\ndef decbinValue(x):\n ans = 0\n p2 = 1\n while x > 0:\n ans ... | eJx0vbuudduSpYWByUOU0i6j3/voGDwHElvCgDJwkjKqJCSExHvxcrTvi7kSVFKdk9q5z/+vNecY/RKXFi1a/N//7f/4//wP/91/8z/9n//yv/3rf/zP/+lf/vt/9y/f2P/8656tfae3e7959vjnX2dfZ47v3XVPf/P7519X67edOdfc495//rXP77737pzt+/rr+Ylv3vGttfYZJz/6z7+O9s799run7fyXT+lj3z2/b51vvZ4/+e7X9ty9tdbXd/InM9+wz1trzLvWzHflHyMfm9+db8z3z7+e++5tvY/7jb5Hvvycs/a67a7e1njt... | null |
658 | Mr K marsh | Mr K has a rectangular plot of land which may have marshes where fenceposts cannot be set. He wants you to find the perimeter of the largest rectangular fence that can be built on this land.
For example, in the following $m \times n = 4 \times 4$ grid, $x$ marks a marsh and $.$ marks good land.
....
..x.
... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static void kMarsh(List<String> grid)"
],
"script_name": "Solution",
"solution": "\nimport java.awt.Point;\nimport java.io.*;\nimport java.math.BigInteger;\nimport java.util.*;\nimport static java.lang.Math.*;\n\npublic class Solution implements Runnable {\... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n static int m, n;\n static String[] land;\n\n static int[][] row;\n static int[][] col;\n\n public static void main(String[] args) {\n S... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\tprivate static StringTokenizer tokens = new StringTokenizer(\"\");\n\tprivate static BufferedReader in;\n\tprivate static BufferedWriter out;\n\t\n\tpublic static void main(String[] args... | {
"class_name": null,
"func_sign": [
"kMarsh(grid)"
],
"solution": "import sys\nm, n = map(int, sys.stdin.readline().split(' '))\nland = []\nfor _ in range(m):\n l = sys.stdin.readline()\n land.append([0 if c=='.' else 1 for c in l])\n\nnext_free_below = [[-1]*n for _ in range(m)]\nfor i in range(n):\... | eJztfe2uZbeN5QAzmOco1G9DKLsdJ86TDDAZBOikfhjotg3EBgQEAeYh5jXnHcb3nC2S4pconX0r3UMuu+49Z2+JpLhISvvz/u//9j/+6//97//lf/794w8//vzrLx//+OHj1998+PrT93/6sUXRnz8633D9/G1Pb7i3i75v/4Q62Ux2sluIjdDluYmokx37ZGvXG9mqFcv56ExxqLmzzbo/ep++XgB13bXbMYl5WBcztpqh0uewkNLk3jEebjkZsKdu+qhr7qIxNYO54bc9v6nDLnOo6zHX571gOaFDV/6wTo5OsY1sImk2deljAMae... | null |
530 | Alien Languages | Sophia has discovered several alien languages. Suprisingly, all of these languages have an [alphabet](http://en.wikipedia.org/wiki/Alphabet), and each of them may contain thousands of characters! Also, all the words in a language have the same number of characters in it.
However, the aliens like their words to be aest... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int alienLanguages(int n, int m)"
],
"script_name": "Solution",
"solution": "\nimport java.awt.Point;\nimport java.io.*;\nimport java.math.BigInteger;\nimport java.util.*;\nimport static java.lang.Math.*;\n\npublic class Solution implements Runnable ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n static final long MOD = 100_000_007;\n\n static int alienLanguages(int n, int m) {\n int[][] t = new int[n + 1][20];\n int nb = n / 2;\n\n for ... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.Scanner;\n\npublic class Solution {\n\t\n\tprivate static final long MOD_VALUE = 100000007;\n\n\tpublic static void main(String[] args) throws IOException {\n\t\tScanner in = new Scanner(new... | {
"class_name": null,
"func_sign": [
"alienLanguages(n, m)"
],
"solution": "# Enter your code here. Read input from STDIN. Print output to STDOUT\nmod = 10**8 + 7\n\nfor cas in range(int(input())):\n n, m = map(int, input().strip().split())\n v = [2*i > n for i in range(n+1)]\n for i in range(n-1,-... | eJx9VruuVEcQJHDAZ4w2Rla/H/4SJK/lwL4ByZrgXgkJIRGROYP/pfpcBJbPDpvsnjMz3dXVVT378Zcv/758cXxef8KP399f3tzePj1eflsXu96YltN8rjehxdeb0lI8GL76eru8WpeHd28f/np8+PvPf54evx1s7ejOnvPXW5J0Oun1VinUGghz+fBq/SeTIzxOyFIPk0kmgif2aovrrRuvV4q5YKk1fWWUFFakiFfSc9D7aCqZsQ+73cjVGhElTbQFFbZ5dwxWCcTiPoFDZF778OdqbGJx1cruSqTwymWoi4YRlfKlmoaiuwTwZ8X3... | 1 |
776 | Red John is Back | Red John has committed another murder. This time, he doesn't leave a red smiley behind. Instead he leaves a puzzle for Patrick Jane to solve. He also texts Teresa Lisbon that if Patrick is successful, he will turn himself in. The puzzle begins as follows.
There is a wall of size *4xn* in the victim's house. The vict... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int redJohn(int n)"
],
"script_name": "Solution",
"solution": "/* HackerRank Template */\n\nimport java.io.*;\nimport java.util.*;\n\nimport static java.lang.Math.*;\nimport static java.util.Arrays.fill;\nimport static java.util.Arrays.binarySearch;\... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.math.*;\n\n\npublic class Solution {\n\tstatic BufferedReader in;\n\tstatic PrintWriter out;\n\tstatic StringTokenizer tok;\n\t\n\tstatic final int N = 220000;\n\t\n\tstatic void solve() throws Exception {\n\t\tboolean[] used = new boolean[N];\n\t\tfo... | {
"class_name": null,
"func_sign": [
"redJohn(n)"
],
"solution": "# return the number of combinaison for a wall of length N. Use memoization.\nnbCombMem = ([],[])\ndef nbComb(N) :\n if N in nbCombMem[0] :\n return nbCombMem[1][nbCombMem[0].index(N)]\n if N < 0 : return 0\n c = 1\n for i in rang... | eJzNVsuO1EAM5MCNnxhy4rBC/U6aL0FiEAeYA5ewh1lpJYTER8D/4nK5M6NMOkIsSKwSJelxt8vlsr3fn/989eKZ/r19KS/vvg6f5/uH8/DmMPh0nP1xDk5uvEa5p+McR/mWp/dcn+xTlmORZzjOw91hOD3enz6eT58+fHk424FyUIG1S9ydxHRyoywVn3kQfkr2HeXn4pIs1+Hb3eEKGSA1X0FgyWuUXQEQgDDyfC9mCCITfIA1QIuFs08ad/Cac9mds9lO8pJKwNljhcucoiIHGhqpZy+7qrw4tRxtxXHDKhrj2XMrAkBcsB8Z00jS... | null |
32,644 | Organizing Containers of Balls | David has several containers, each with a number of balls in it. He has just enough containers to sort each type of ball he has into its own container. David wants to sort the balls using his sort method.
David wants to perform some number of swap operations such that:
* Each container contains only balls of the sa... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static String organizingContainers(List<List<Integer>> container)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n publi... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class B {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"organizingContainers(container)"
],
"solution": "#!/bin/python3\n\nimport sys\nfrom collections import Counter\n\n\nq = int(input().strip())\nfor a0 in range(q):\n n = int(input().strip())\n M = []\n for M_i in range(n):\n M_t = [int(M_temp) for M_temp in... | eJztnNuOG0UQhrngQVq+jlAf58Ab5I5LJBaBgBWKlGxWSiIhISQeAt6Ch+T/u8f2jE87tudQveqtrHdm3Kev66+qdi7899f//v7fV/Hn+59x8cOfm3dPz18+b75VG//wZB6e7MMTLrxyyihca1xYhScB954XeKyCCrGlqytlDXu1rbKhwRN2gbGd6f3ZvFGbxz+eH3/9/PjbTx+/fO7m/O7jp0/vfnn/+PD09sPzyetti81fb9TRYjl+nENzlu7VpPn3j9JfXHVr6x6ZYcv9ALuWZtdyx7S76U/U65jap5bDyfRwzEF3c9i95ZY6FYJy... | null |
1,331 | Service Lane | A driver is driving on the freeway. The check engine light of his vehicle is on, and the driver wants to get service immediately. Luckily, a service lane runs parallel to the highway. It varies in width along its length.
You will be given an array of wid... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> serviceLane(int n, List<List<Integer>> cases)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n publ... | {
"solution": "import java.util.*;\n\npublic class ServiceLane {\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n int n = sc.nextInt();\n int t = sc.nextInt();\n int[] arr = new int[n];\n for(int i = 0; i < n; i++) {\n arr[i] = sc.nex... | {
"solution": "import java.util.Scanner;\nimport java.util.ArrayList;\n\npublic class Solution {\n public static void main (String[] args) {\n Scanner stdin = new Scanner(System.in);\n int freewayLength = stdin.nextInt();\n int numTestCases = stdin.nextInt();\n ArrayList<Integer> freewa... | {
"class_name": null,
"func_sign": [
"serviceLane(n, cases)"
],
"solution": "import sys\n\nN, T = [int( item ) for item in next( sys.stdin ).split()]\nW = [int( item ) for item in next( sys.stdin ).split()]\nfor line in sys.stdin:\n i, j = [int( item ) for item in line.split()]\n print( min( W[i:j+1] ... | eJzsu8tuJVu6neeG4ecI7PZpcM651iKprl/CgAtQQ6qGOlunUQcQIAjQC/qdHMEscnzfmJF1BLthwz5g7UwyYl7+y7j8ZCX/+//8v/2v/8f/8j/97//1j//05z//y9/++HfHH58fH8fH51/+HMc65jHO/9b5Mb4+Gz9fr6+36+9P18+qX5/Nn53fu8bXu+/V6+9/53meLN05/n7S+LnVe7/Xf0cx//7V/Nm7dML3HevnxPFz2vrZ3VkmltzxnVn2rrp7anfOzd6hPbk/kX6vT01Si4ksGBlP6c+ZYyrAr7/7k6i+s134ej9n/OxZWMtq... | null |
4,432 | The Grid Search | Given an array of strings of digits, try to find the occurrence of a given pattern of digits. In the grid and pattern arrays, each string represents a row in the grid. For example, consider the following grid:
<pre>
1234567890
09<strong>876543</strong>21
11<strong>111111</strong>11
11<strong>111111</strong>11... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static String gridSearch(List<String> G, List<String> P)"
],
"script_name": "Solution",
"solution": "import java.util.*;\n\npublic class Solution {\n public static void main(String[] args) {\n Scanner cin = new Scanner(System.in);\n \n int T = cin... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.math.*;\n\npublic class Solution {\n\n public static void main(String[] args) throws Exception {\n BufferedReader br = new BufferedReader(new InputStreamReader(System.in));\n int cases = Integer.parseInt(br.readLine());\n MAIN:... | {
"class_name": null,
"func_sign": [
"gridSearch(G, P)"
],
"solution": "def pattern_here(G, row_i, g):\n i = G[row_i].find(g[0])\n while i != -1:\n found = True\n for j in range(1, len(g)):\n if G[row_i + j][i:i+len(g[j])] != g[j]:\n found = False\n if fo... | eJyV3b+uLkuSFXAMHuSo7RGqzKrKykJ4CBcMHBAXYUAbOJcxeiQkhMRDgHhd1m/VvtJI/BENMz19ztn7+6oyIyNWrFgR+d/+4f/4p//zH/T//at/kv/yb/7Ln/7j73/7d3/50z/+9afzt9/n82vev/1+3tc51vOOMc/5Pus9nms9z/Pmn9Zc53WtN3+z7+d699zXvq/nt9/XOY/3Otc7xzj3+c5n5c/jPn3g+V77utca73Udx/3c485v5rvysfOa9zPGNeZaz7mf+175r7/9/uZTrvzGu9d9Huc459zPe1/Xb7/n89481Twfn7WPMZ/8... | null |
13,512 | Ema's Supercomputer | Ema built a quantum computer! Help her test its capabilities by solving the problem below.
------
Given a grid of size $n \times m$, each cell in the grid is either $good$ or $bad$.
A *valid* plus is defined here as the crossing of two segments (horizontal and vertical) of equal lengths. These lengths must be odd, a... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int twoPluses(List<String> grid)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\n\n\npublic class Solution {\n private BufferedReader in;\n private StringTokenizer line;\n private PrintWriter out;\n\n p... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.regex.*;\n\npublic class Solution {\n static int twoPluses(String[] grid) {\n int n = grid.length;\n int m = grid[0].length();\n ... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.Arrays;\n\npublic class ProblemC {\n BufferedReader rd;\n\n ProblemC() throws IOException {\n rd = new BufferedReader(new InputStreamReader(System.in));\n compute();\n ... | {
"class_name": null,
"func_sign": [
"twoPluses(grid)"
],
"solution": "\ndef solve(y, x, y1, x1, l):\n i = 0\n s = True\n t = True\n ans = []\n while True:\n if s:\n a = l[y + i][x] if y + i < len(l) else \"B\"\n b = l[y - i][x] if 0 <= y - i else \"B\"\n ... | eJzlVr1OwzAQZmDhLazMFWrSpAHGW+4VkAAxQAeW0iGVkBASDwEvwsbbEd+f7aRuk5lEdS7n+/N3n51+nn//XpzRdfvTC3fvxct2t++KG1eUlVvdbwHAD9gP6CXEROclpIFmIRmKhSs2b7vNU7d5fnzddxq4+Fi4OFHjWorsLx/OPzkDsNBnoMReT2WwjRjLlDfhMkErkjjsJgFB45AAkQ1NZWqumkHRjSuXFIjToMhocliPiIBmD0cy1cNMfR98KoJAkEGU5aLhBqrndMMSMKyUEQPxTWwUQ1sJg88zASXSZ8q/OtDdmiNyt0wejdY/... | null |
16,411 | Larry's Array | Larry has been given a permutation of a sequence of natural numbers incrementing from $1$ as an array. He must determine whether the array can be sorted using the following operation any number of times:
- Choose any $3$ consecutive indices and rotate their elements in such a way that $A B C\ \rightarrow B C A\ \ri... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static String larrysArray(List<Integer> A)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n static int[] aux;\n \n ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class B {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"larrysArray(A)"
],
"solution": "import copy\n\nt = int(input())\n\nfor z in range(t):\n input()\n realList = [int(n) for n in input().split()]\n sortedList = copy.copy(realList)\n sortedList.sort()\n listLen = len(sortedList)\n for i in range(listLen -... | eJztnLvOZklyXWXoQQ7aHggn75n06ZIGHQpqSYY0Bp0WjSFAgCDAh5Deix5fR7FW5Fdd3dNVwzHkaTDVdfm/S57MyIgdO3bEv/zH//Nv/+0/+L+//df4w3/5px/+7qe//4c//PAXzw/lx59a/P8pT/3xpx9+9/zw+3/8+9//jz/8/n/+9//1D3+4r/nPf/k38bN//t3zy/eV943/PPVpT3/GM5/17Oc85X1KeUp9Snxqf8p4ynzKesp+ynnq+9R4T31qe2p/6njqfOp66n7qedr7tPK0+Mj2tP608bT5tPW0/bTz9Pfp5en16fGN/enj... | null |
33,299 | HackerRank in a String! | We say that a string contains the word `hackerrank` if a [subsequence](https://en.wikipedia.org/wiki/Subsequence) of its characters spell the word `hackerrank`. Remeber that a subsequence maintains the order of characters selected from a sequence.
More formally, let $p[0], p[1], \cdots, p[9]$ be the respective ind... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String hackerrankInString(String s)"
],
"script_name": "Solution",
"solution": "import java.util.Scanner;\n\npublic class LCS {\n\n\tpublic static void main(String[] args) throws Exception {\n\n\t\tScanner scan = new Scanner(System.in);\n\n\t\tint q ... | {
"solution": "DNE",
"template": "class Result {\n\n /*\n * Complete the 'hackerrankInString' function below.\n *\n * The function is expected to return a STRING.\n * The function accepts STRING s as parameter.\n */\n\n public static String hackerrankInString(String s) {\n // Write your... | {
"solution": "import java.util.*;\nimport java.io.*;\npublic class Main {\n public static void main(String[] args) throws Exception {\n BufferedReader br = new BufferedReader(new InputStreamReader(System.in));\n int q = Integer.parseInt(br.readLine());\n for (int test = 1; test <= q; test++) ... | {
"class_name": null,
"func_sign": [
"hackerrankInString(s)"
],
"solution": "#!/bin/python3\n\nimport sys\nimport re\n\nq = int(input().strip())\nfor a0 in range(q):\n s = input().strip()\n \n pattern = \".*h.*a.*c.*k.*e.*r.*r.*a.*n.*k.*\"\n m = re.search(pattern, s)\n if m is not None:\n ... | eJyMvMuu7Li2pncM+EEOdrsaokjq4n51yw13bHgCBsWreL9IoijDgF/Cz2c/h1secVAFuKrOMZzYSGSuvdaMCGqM//++CEX+7//t//Hf/F//9C9//Y//9//5T//0P/+v/zhjvq9//Hf//A9E/6Ln93Esx3rSO79jHm+9+EXGIPq+rDFuLy9ejGjh/p6UlnO/c/gqO4UfbEtJzqc9wkdxKqnyc+euye84qvIOawl/kMXzkk/qvGMarev32hU/1hSOTbka/dvDPBcx1R2taHqvnoQ+mMTbodrd8js7ktybgg2Ob9HGx/LNvzZx8bznIal8... | null |
360 | Quicksort 1 - Partition | The previous challenges covered [Insertion Sort](https://en.wikipedia.org/wiki/Insertion_sort), which is a simple and intuitive sorting algorithm with a running time of $O(n^2)$. In these next few challenges, we're covering a *divide-and-conquer* algorithm called [Quicksort](https://en.wikipedia.org/wiki/Quicksort) (al... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> quickSort(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "\n\n/* Head ends here */\nimport java.util.*;\npublic class Solution {\n public static void main(String[] args) {\n Scanner in = new Scanner(System.in);\... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.ArrayList;\n\nclass Solution\n{\n\tprivate static BufferedReader in;\n\tprivate static PrintStream out;\n\tpublic static void main(String args[]) throws IOException\n\t{\n\t\tin=new BufferedReader(new InputStreamReader(System.in));\n\t\tout= new PrintStream(new Buffe... | {
"class_name": null,
"func_sign": [
"quickSort(arr)"
],
"solution": "size = int(input())\narray = input().split(\" \")\narr = ['None'] * size\nfor i in range(size):\n arr[i] = int(array[i])\np = arr[0]\nless = [ ]\nmore = [ ]\nfor i in range(size):\n if arr[i] < p:\n less.append(arr[i])\n e... | eJztnUuOJFmSXTngQgw5biNM/0+5EgJMgoNmDchBsgfVAAGiAS6CXBu3QznnPrWfm3t4fKoyspmNrkiPcPuoPn1P5MqVKyL/69/+n//2f/+N//cf/rF++I//85f/+ts//fNff/n3p1+Wbfz1t3ObhtM0jqdtWE7n+u8+7afzOq+nNp3Ow+VyqX+d+aNeN6zr6byM9cLGT+Ow1Uta/bLxsn0YT+dt2U7LNtTL1u207/XDtvOqpdUL6lXjMtcP83Qapvk0z3zSfFr25dT4y3qZ6t310esw8bL1NC/1yUu9dr3sp72+er3U9V4aX1zX2Lig... | null |
33,549 | Separate the Numbers | A numeric string, $s$, is *beautiful* if it can be split into a sequence of two or more positive integers, $a[1],a[2], \ldots ,a[n]$, satisfying the following conditions:
1. $a[i]-a[i-1]=1$ for any $1 < i \le n$ (i.e., each element in the sequence is $1$ more than the previous element).
2. *No $a[i]$ contains a leadin... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static void separateNumbers(String s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.StringTokenizer;\n\n/**\n * @author Aydar Gizatullin a.k.a. lightning95, aydar.gizatullin@gmail.com\n * Created on 17.02.17.\n */\n... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.util.*;\nimport java.io.*;\n\npublic class University_Codesprint_2_B {\n\n\tstatic BufferedReader br;\n\tstatic PrintWriter out;\n\tstatic StringTokenizer st;\n\t\n\tpublic static void main (String[] args) throws IOException {\n\t\tbr = new BufferedReader(new InputStreamReader(System.in))... | {
"class_name": null,
"func_sign": [
"separateNumbers(s)"
],
"solution": "for _ in range(int(input())):\n s = input().strip()\n n = len(s)\n x = ''\n for i in s[:-1]:\n x += i\n y = int(x)\n z = ''\n while len(z) < n:\n z += str(y)\n y += 1\n ... | eJytlr1unFUQhilouAtr6wjN35mZQ08LBRSgLKIAF2mWFImEhCJxEXC/PPMZJQivnRhi2f6Od8+cM+/PvOvfP/3z+WefHF/ffcvi+W+nF5eXr1+dvrg51fkiLktky7ZekckrGUtWZ7auZWo7sttk+aoM3+dL72oR7dKp1PPFIndQLO6amxO0RNi3kgKR4oDc4rpCyruVV3T1+eIuWy3cM72KN8+X07Ob0+2vL29/enX784+/vH71d59ffX2+XP85vXl28w9AnLprV+XKEJ0utwCD5srPlzAaMm7lVxqP5A9JlkphxQasLRDRsUtJ+k7Z... | null |
6,568 | Funny String | In this challenge, you will determine whether a string is *funny* or not. To determine whether a string is funny, create a copy of the string in reverse e.g. $abc \rightarrow cba$. Iterating through each string, compare the absolute difference in the [ascii](https://en.wikipedia.org/wiki/ASCII) values of the characte... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String funnyString(String s)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMism... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n int lines = sc.nextInt();\n sc.nextLine();\n outer:\n for(int i = 0; i < lines; i++) {\n String s = sc... | {
"class_name": null,
"func_sign": [
"funnyString(s)"
],
"solution": "def isFunny(s):\n for i in range(1, len(s)):\n if abs(s[i] - s[i-1]) != abs(s[-i-1] - s[-i]): return False\n return True\n \n\nif __name__ == \"__main__\":\n num_cases = int(input());\n for case in range(num_cases):\... | eJztvNeOxNyaHeYLP8jg3PhGEJiD75hzznQbBnPOmYYAP4R1rVc1f2NsCEfWaPIZ+fS30OhifdVVmzusb63qTf4f/+N//Pf/6X/4vyP8n74H/8v//qdmnI/9T//z3/wJ/BmPuzjrObuHIuvqcm2q9E7yYty7657b4V3OLi/7ZV2Xqt7TcmjaedzXujreuezrcxvSLW+v/tib65rbrZ+ucbymfmvn62r2o7/afEuH7az7cn6Pql73cW6boUz3uvrjXfsy787lHdr5vrp9LPLkTqtmLesuK4Y7m+uzuI+f8U//7m/+VNxzke1F/r9Nx/63... | null |
4,099 | Alternating Characters | You are given a string containing characters $A$ and $B$ only. Your task is to change it into a string such that there are no matching adjacent characters. To do this, you are allowed to delete zero or more characters in the string.
Your task is to find the minimum number of required deletions.
**Example**
$s = ... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int alternatingCharacters(String s)"
],
"script_name": "Solution",
"solution": "import java.util.Scanner;\npublic class Solution {\n\n\t/**\n\t * @param args\n\t */\n\tpublic static void main(String[] args) {\n\t\t// TODO Auto-generated method stub\n... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.math.*;\n\n\npublic class Solution {\n\tstatic BufferedReader in;\n\tstatic PrintWriter out;\n\tstatic StringTokenizer tok;\n\t\n\t\n\tstatic void solve() throws Exception {\n\t\tint t = nextInt();\n\t\tfor (int tt = 0; tt < t; ++tt) {\n\t\t\tString s... | {
"class_name": null,
"func_sign": [
"alternatingCharacters(s)"
],
"solution": "def f(s):\n return sum(1 for c1, c2 in zip(s, s[1:]) if c1 == c2)\n\nt = int(input())\nfor _ in range(t):\n print(f(input()))",
"template": "#\n# Complete the 'alternatingCharacters' function below.\n#\n# The function is... | eJx0lD2yZUuTFREYCNbGCBBBihwFZjABlDYEkFCYHrPCur8Kd499qqveq3vP2Znxs5av/X///X/9f//lP/67//Z//ul//PP//N//65/+83/4p//03//5zb/8/dd/3r/8fP/y81//nfnHN/vjXx/8+fCPx/vhH3cmV//8Ojn2j4Lz8ss/Cr2h257e797bs2/P7iUq0sG/k1l2JCab2Wn/dODn/OPPP3qMi3QrvxiKWvOMgmor4ewCrPqm8k3KZ8rz7x8/Xt35c5uuqvfn+XfUaL139+JYqK2O0PtnPXFaTP3TLxNEyM8Qntbx1YOTa71/... | null |
21,083 | Highest Value Palindrome | Palindromes are strings that read the same from the left or right, for example <em>madam</em> or <em>0110</em>.
You will be given a string representation of a number and a maximum number of changes you can make. Alter the string, one digit at a time, to create the string representation of the largest number possi... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static String highestValuePalindrome(String s, int n, int k)"
],
"script_name": "Solution",
"solution": "import java.util.Scanner;\n\npublic class Solution {\n public static void main(String[] args) {\n Scanner scanner = new Scanner(System.in);\n\... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class B {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n... | {
"class_name": null,
"func_sign": [
"highestValuePalindrome(s, n, k)"
],
"solution": "n, k = map(int, input().split())\ns = list(input())\n\nf = 0\nfor i in range(n // 2): f += s[i] != s[n - 1 - i]\n\nif f > k: print(-1)\nelse:\n for i in range(n // 2):\n if s[i] != s[n - 1 - i]:\n f -... | eJzs3cuqbtmW3XeB9SDBKcsw7xe9g+sGB7hgZUGVsAopEAiD31Ev5P77zxXGhPOkcBqBCnuTnIzYsdb3zcsYffTeemut/5//+n/+L//T//Cv/pf//Ld//8d/+I//+Ld/+9vf7t/W9fc/luPcj/f6/Y+//Zvf/vYP/+k//MP/9o//8O/+1//9P/7jz0+935+//R//5rf/x+/uv22//7Fex9//teuvv/L+dv7+x/ts5/pc7/PPfd+zPv/EN66/re+x3r//sa/7eS73uTzXsmzvdqzX+m7X/rznsvuBf/5O/t6fv37f/dt7Xdtc87PN83m2... | null |
17,338 | Bear and Steady Gene | A gene is represented as a string of length $n$ (where $n$ is divisible by $4$), composed of the letters $\text{A}$, $\text{C}$, $\text{T}$, and $\text{G}$.
It is considered to be *steady* if each of the four letters occurs exactly $\frac{n}{4}$ times. For example, $\text{GACT}$ and $\text{AAGTGCCT}$ are both steady g... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int steadyGene(String gene)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] arg... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class B {\n\n\tBufferedReader br;\n\tPrintWriter out;\n\tStringTokenizer st;\n\tboolean eof;\n\t\n\tstatic final String GENES = \"ACGT\";\n\n\tvoid solve() throws IOException {\n\t\tint n = nextInt();\n\t\tString s = nextToken();\n\t\tint[] a = new int[n... | {
"class_name": null,
"func_sign": [
"steadyGene(gene)"
],
"solution": "\ndef solve(S,n) :\n count = {}\n for c in S :\n count[c] = count.get(c,0) + 1\n\n for c in count :\n if count[c] > n//4 :\n count[c] = count[c]-n//4\n else :\n count[c] = 0\n\n if ... | eJykmrGutVtyVQnIeAmrYwfYEkYgEZQqqBeoAAlLBNABSeOgLSEhJN6W1+DsGmOufVqIqNvu2/f+95y9v2+tWlVzjrn+97/8j//h//yrf/Gf/ucf/tuf/umf//yHf/83f/j7f/MP//in+iv/03/lf+av/M/+lf/5xz/94W//5g9//B//9Mf/8uc//tf//N//+c+uzr/++Tf/62//5td6/d3f/yxX7/vq/++v/sP/+6v/7t/+3d/9/HH3rVjNVs3U/Hza5xP75x9//my7fv778381n//r+vnBz1/75y/7+ffzWa/++d/5/PbnH/bzfz9/... | null |
66 | Find Strings | A substring is defined as a contiguous sequence of one or more characters in the string. More information on substrings can be found [here](http://en.wikipedia.org/wiki/Substring "Substring"). <br>
You are given *n* strings w[1], w[2], ......, w[n]. Let S[i] denote the set of all distinct substrings of the string w[i... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<String> findStrings(List<String> w, List<Integer> queries)"
],
"script_name": "Solution",
"solution": "\nimport java.io.* ;\nimport java.text.DecimalFormat;\nimport java.util.*;\nimport static java.lang.Math.* ;\nimport static java.util.Arrays.*... | {
"solution": "import java.io.* ;\nimport java.text.DecimalFormat;\nimport java.util.*;\nimport static java.lang.Math.* ;\nimport static java.util.Arrays.* ;\n\npublic class Solution {\n public static void main(String[] args) {\n new Solution().solveProblem();\n out.close();\n }\n stati... | {
"solution": "\nimport java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.Arrays;\nimport java.util.Comparator;\n\npublic class Solution \n{\n\tstatic int sa[],rank[],lcp[];\n\tpublic static void main(String args[])throws IOException\n\t{\n\t\tBufferedReader br=... | {
"class_name": null,
"func_sign": [
"findStrings(w, queries)"
],
"solution": "import sys\ndata = sys.stdin.readlines() \n\ndef get_suffixes(string):\n suffixes = set()\n string_len = len(string)\n for index in range(0, string_len):\n suffixes.add(string[index: string_len])\n r... | eJztfduO7DiWnQ34Qxr1PDDifvGbgXkZwPCjYcBpGLxJJEVSFCleRMOAP8I/5y/wb3hRWT0YdHfVTPdUd9U5qdh1spQKhcR9W2ttZWbE//53//X//r9/+2/+2//8QTmf1h/+w+9+ON8+nNW0xXmhrbk4EtZcMHWyha7WjlGo1ZZAFz5J49IkiCdxImkwLRmyljgyI7VcS+NLVWHwyigtnG5qyVxx73wcMxV0G9zgtbfJ22byMi2pNRU+nFLZzXab/LIZGhJfsoy0ri5LMSvf+LyOwg55C06weajRb3ktkys81JVOKo6OC7rYNjKXk2N1... | null |
21,767 | Gridland Metro | The city of Gridland is represented as an $n \times m$ matrix where the rows are numbered from $1$ to $n$ and the columns are numbered from $1$ to $m$.
Gridland has a network of train tracks that always run in straight horizontal lines along a row. In other words, the start and end points of a train track are $(r, c1)... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int gridlandMetro(int n, int m, int k, List<List<Integer>> track)"
],
"script_name": "Solution",
"solution": "/*\n * Code Author: Akshay Miterani\n * DA-IICT\n */\nimport java.io.*;\nimport java.math.BigInteger;\nimport java.math.RoundingMode;\nimpor... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.Comparator;\nimport java.util.InputMismatchException;\n\npublic class C {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"... | {
"class_name": null,
"func_sign": [
"gridlandMetro(n, m, k, track)"
],
"solution": "from collections import defaultdict\n\nn, m, k = map(int, input().split())\n\ntracks = defaultdict(list)\nfor _ in range(k):\n row, c1, c2 = map(int, input().split())\n tracks[row].append((c1, -1))\n tracks[row].ap... | eJzsvUuuLTuuLWYDbsjCLb+C/h+3xIAP4IJ9C66kX+E+wIBhwN11L8wxBknF2nlPC5wnc0ux5pwRIVH8DFIS9f/8D//T/9v++//uf/6//u1//8d//W//8W//48+/1braTzvt7p86+1//uMcu7IP11z9G6T9t9Hb0/V//mHfYd7es8dc/2rDb+rTb/Ms+8GXdtdlT+rLP7XLGt7tPfrvK/esftY7zU5s9KL4+/eLrM/bC19PacFcv+eyJZ88y7cu2f87o2aazD+6cpR9roH2Jh+S3dTb0ZozZ/vrHqvVn4FHRnbnsy3G2Xd/Wfu6478ba... | null |
27,771 | Minimum Loss | Lauren has a chart of distinct projected prices for a house over the next several years. She must buy the house in one year and sell it in another, and she must do so at a loss. She wants to minimize her financial loss.
**Example**
$price = [20, 15, 8, 2, 12]$
Her minimum loss is incurred by purchasing in y... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int minimumLoss(List<Long> price)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\npublic class b {\npublic static void main(String[] args) throws IOException {\n\tinput.init(System.in);\n\tPrintWriter out = new Pri... | {
"solution": "import java.util.*;\n\npublic class hello\n{\n public static void main(String []args)\n {\n Scanner sc=new Scanner(System.in);\n \n int x=sc.nextInt();\n long a[]=new long[x];\n \n HashMap <Long,Integer> map=new HashMap<Long,Integer>();\n \n ... | {
"solution": "import java.awt.*;\nimport java.awt.event.*;\nimport java.awt.geom.*;\nimport java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\n\n/*\nbr = new BufferedReader(new FileReader(\"input.txt\"));\npw = new PrintWriter(new BufferedWriter(new FileWriter(\"output.txt\")));\nbr = new Buf... | {
"class_name": null,
"func_sign": [
"minimumLoss(price)"
],
"solution": "n=int(input())\n\nl = [int(item) for item in input().split()]\nl2 = l.copy()\nd={}\nfor i in range(len(l)):\n d[l[i]] = i\nl = sorted(l)\nm = float(\"inf\")\nfor i in range(len(l)-1):\n if d[l[i+1]] < d[l[i]] : m = min(m,l[i + 1... | eJx03c+Krd+yJmQb9ryJw2lXY/yZMyKGVyJYYENLsHOsRgmCCN6Cd+x63vlbBxtajcwPag4Oe7+xV2Y+X4yI/+u//u/+5//7v/mv/vv/41//l3/7z//bf/nX//Zf/vXz3vuP//Zda/2Lx3/583Q8taePp6+n8nQ9jaf952k7MU5sJ8aJ7cQ4sZ0YJ7YT48Rxop04TrQTx4l24jjRThwn2onrRDlxnSgnrhPlxHWinLhOlBMfJ75OfJz4OvFx4uvEx4mvEx8nvk58nfg48XXi48TXiY8TXyc+Tnyd+DhRTlwnyonrRDlxnSgnrhPlxHWi... | null |
458 | Missing Numbers | Given two arrays of integers, find which elements in the second array are missing from the first array.
**Example**
$arr = [7, 2, 5, 3, 5, 3]$
$brr = [7, 2, 5, 4, 6, 3, 5, 3]$
The $brr$ array is the orginal list. The numbers missing are $[4, 6]$.
**Notes**
* If a number occurs multiple times in the lists, ... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> missingNumbers(List<Integer> arr, List<Integer> brr)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n ... | {
"solution": "import java.util.*;\npublic class hello\n{\n public static void main(String []args)\n {\n Scanner sc=new Scanner(System.in);\n \n int x=sc.nextInt();\n \n // HashMap<Integer,Integer> map=new HashMap<Integer,Integer>();\n \n int f1[]=new int[10001];\... | {
"solution": "import java.util.*;\n\n/**\n * Created by Bruno on 05/08/2014.\n */\npublic class Solution {\n public static void main(String[] args){\n Scanner scan = new Scanner(System.in);\n\n //Construct A\n int n = scan.nextInt();\n Map<Integer, Integer> A = new HashMap<>(n);\n ... | {
"class_name": null,
"func_sign": [
"missingNumbers(arr, brr)"
],
"solution": "n = int(input())\nA = [int(i) for i in input().split()]\nm = int(input())\nB = [int(i) for i in input().split()]\nvals = {}\nfor i in A:\n if i not in vals:\n vals[i] = -1\n else:\n vals[i] -= 1\nfor i in B:\... | eJzsvcuO7TqyJNiD7v8InPEdiKKeNerPaKA3UIOqHNRk9x3kBQooFNDD/uxeorubGRmkQrEfJ09mBe65K1csSXz4w9zcSWr/v//7//V//n//x//2f/+PP/7b93//j7//8Z/e/ji289v39JbOt/n13/qW0tuyvq3HW97f9reU33J6e/39+t/1+un1+bq8pOu+1/fX9bRftyzndU96m68Pu7ZcD75azOf13+uvZX+b92jnLO28eng1vl7dv5pa8tXOq4n9+niNJ1+t5XL51dCars7KQF//+3p8TqVrG8Z63b2UIb9uuL6UgeUynHX19pPd... | null |
1,629 | Cut the Tree | There is an undirected tree where each vertex is numbered from $1$ to $n$, and each contains a data value. The *sum* of a tree is the sum of all its nodes' data values. If an edge is cut, two smaller trees are formed. The *difference* between two trees is the absolute value of the difference in their sums.
Given ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int cutTheTree(List<Integer> data, List<List<Integer>> edges)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Ar... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.*;\n\npublic class Solution {\n static class TreeNode{\n int value;\n int number;\n ArrayList<TreeNode> children;\n public TreeNode(int value,int number){\n this.value = value;\n this.number = number;\n children = new Arra... | {
"class_name": null,
"func_sign": [
"cutTheTree(data, edges)"
],
"solution": "from collections import deque\n\nclass Node(object):\n def __init__(self,index,value):\n self.index = index\n self.value = value\n self.children = set()\n self.parent = None\n self.value_of_s... | eJzsncvKNUl2nj0wvo5NjXuQccg46EoMLtBAqoE8KPWgGwRCoKv1dTie5439dSPTMxtsMFLXF3/uzMjIiHVeb6z49//8X//7//gv/+m//esv//T7H//8p1/+7vPL/vX3+ZZPKZ/Vn/O/8Vm1fdpz/s7xaXN99vv++nv51F9/r5/26+/t03/9vX9e/jn45+TXdbr57F/+8Pnlt3/542//8Kff/vHv//nPf7rvqKWeZ375tz98/urFvb3nybrm563vZ6/6We28//20eprzvOG8+x31U+b7mbOc28bn/P+7+qedu89o32d/3k8v/bPH49+3... | null |
11,782 | Gena Playing Hanoi | The [Tower of Hanoi](https://en.wikipedia.org/wiki/Tower_of_Hanoi) is a famous game consisting of $3$ rods and a number of discs of incrementally different diameters. The puzzle starts with the discs neatly stacked on one rod, ordered by ascending size with the smallest disc at the top. The game's objective is to move ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int hanoi(List<Integer> posts)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static int[] readIntArray3... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.ArrayDeque;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\nimport java.util.Queue;\n\npublic class C {\n\tInputStream is;\n\tPrintWriter ... | {
"class_name": null,
"func_sign": [
"hanoi(posts)"
],
"solution": "#!/bin/python3\n\nimport sys\n\ndef getRod(position, disc):\n return (position>>(disc*2))&3\n\ndef setRod(position, disc, rod):\n position = position & ~(3<<(disc*2)) | (rod<<(disc*2))\n return position\n\ndef getPosition(rods):\n ... | eJylU0sOgjAQdcFBJl0TQz+CeBKNGE2UhRt0AYmJIfEQel9nKAuc0koCkwKLeZ95bV/R5xQtume7w5/9U1yre1OLDYisqCRoLIXLgCoqEYMoH/fyXJeX462p+0aZijaGATIlpOmQiPXjNMOhREhHsXZkViADgJXrS4N1hm+/L46TOI+3OxlzhQKTx+hyVpRw5yuQcz4vr9w6IyH5V0ybOSFgZyBfdwwVyIu3y4QCc2qytzWdgp/yh8BPqNW2+Q2Wl8A4KSa0ZxrY8hPwTSQCBU75CfihsQSkKmHw9WcwRmD66Ky6CV4nnYn28F5+AfbG... | null |
28,492 | Red Knight's Shortest Path | In ordinary chess, the pieces are only of two colors, black and white. In our version of chess, we are including new pieces with unique movements. One of the most powerful pieces in this version is the *red knight*.
The red knight can move to six different positions based on its current position (UpperLeft, UpperRig... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static void printShortestPath(int n, int i_start, int j_start, int i_end, int j_end)"
],
"script_name": "Solution",
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\ni... | {
"solution": "DNE",
"template": "class Result {\n\n /*\n * Complete the 'printShortestPath' function below.\n *\n * The function accepts following parameters:\n * 1. INTEGER n\n * 2. INTEGER i_start\n * 3. INTEGER j_start\n * 4. INTEGER i_end\n * 5. INTEGER j_end\n */\n\... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n \n static String[] sym = {\"UR\", \"UL\", \"R\", \"LR\", \"LL\", \"L\"};\n static int[] di = {-2, -2, 0, 2, 2, 0};\n static int[] dj = {1, -1, 2, 1, -1, -... | {
"class_name": null,
"func_sign": [
"printShortestPath(n, i_start, j_start, i_end, j_end)"
],
"solution": "from collections import deque\n\nsurround = [(-2, -1, \"UL\"), (-2, 1, \"UR\"), (0, 2, \"R\"), (2, 1, \"LR\"), (2, -1, \"LL\"), (0, -2, \"L\")]\n\ndef printShortestPath(n, i_start, j_start, i_end, j_e... | eJydlM1KxDAUhV3oexyyHiQ3f218A6ErQRCsCGoXA2OmMB0QRPAh9H09cboQh5ZpmhYK7Zd77slJPs+/64uz3+tO+HL/rtap3w/qCqpqk0eAhbRJraC6t757HrqXx+1+GH+xbbptwKE+VviD+jYZgm4GvX7tt7vd+mnT/WNZ1pLV0MvZOrMBgrCcNSwskXWlgpTwkU07mJoCjFvOO5omEAenYXyBb6zvuGB5xaoC/SIsGiJrw9DCAgViTZtqmAjrEKctsFR6g+WjOek+jiKjxCjO6MlyJlmSM1Ek2zD/E1sgbwK73Mhw0CwwhVtA5wws... | null |
25,952 | Roads and Libraries | Determine the minimum cost to provide library access to all citizens of HackerLand. There are $n$ cities numbered from $1$ to $n$. Currently there are no libraries and the cities are not connected. Bidirectional roads may be built between any city pair listed in $cities$. A citizen has access to a library if:
* Thei... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static long roadsAndLibraries(int n, int c_lib, int c_road, List<List<Integer>> cities)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class S... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.regex.*;\n\n public class Solution{\n static int unionfind(int index,int [] parent)\n {\n while(index!=parent[index])\n {\... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static class Edge {\n public int u, v;\n public long w;\n public Edge(int u, int v, long w) {\n this.u = u;\n t... | {
"class_name": null,
"func_sign": [
"roadsAndLibraries(n, c_lib, c_road, cities)"
],
"solution": "from collections import defaultdict\nfrom collections import deque\n\nfrom math import pi,cos,sin\n\nclass graph:\n def __init__(self):\n self.nodes = []\n self.edges = defaultdict(set)\n d... | eJw03TsObMlWBmEkmAZS645g53plJiNB4k4Ap4UBFg4TZE5QGdFOeWv34/ynan9W/M8//ev//vM//sO//fff/v3P//iv//zbv/zxt/X3P/v7/ojvrPkj/4i//7n4yN9H/T769zG/j/37OL+P+/tY3/tc7/MdrXe13tl6d+sdrne53ul6t/Fu490G/9R3G+823m2823i38W7j3ea7zXeb/Mu+23y3+W7z3ea7zXeb77bebb3berfFf+m7rXdb77bebb3berf9bvvd9rvtd9v8b3q3/W773fa77Xc773be7bzbebfzbof/x+923u2823m3... | null |
784 | Journey to the Moon | The member states of the UN are planning to send $2$ people to the moon. They want them to be from different countries. You will be given a list of pairs of astronaut ID's. Each pair is made of astronauts from the same country. Determine how many pairs of astronauts from different countries they can choose from.
__... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int journeyToMoon(int n, List<List<Integer>> astronaut)"
],
"script_name": "Solution",
"solution": "\nimport static java.lang.Math.*;\nimport static java.util.Arrays.*;\n\nimport java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n publi... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.math.BigInteger;\nimport java.util.ArrayList;\nimport java.util.Iterator;\nimport java.util.LinkedList;\n\npublic class Solution {\n\n static boolean[] visited;\n static int N, L;\n stat... | {
"class_name": null,
"func_sign": [
"journeyToMoon(n, astronaut)"
],
"solution": "#!/usr/bin/env python\n\nimport sys\n\n\nif __name__ == '__main__':\n N, I = list(map(int, sys.stdin.readline().split()))\n \n # Count astronauts from different countries\n astronauts = [-1] * N\n countries = [... | eJws3Tuu7tqWXGsZMlWIibRl/Bx8qyQCdCogZ0MQ7rXkqOjqX+NxIhugZMyuXGPHWpOdQf7f//zf//d//S//6X/8n//4n//8r/////uP//b3H9v5+/3+tpHfv/4Z+Nc/29/61z/73/Gvf46/81//XH/3v/65/55//fPO/9r8P8//kv+t9bft8z/2v23+N7fzb7vmf1x/2/xvb8/f9s7/eP/WXLDGcBzX+ltzwTr+1riu82/NBev+W+O8nr81F+y/v32s9+1vN8L+t4/1fvztc8F+/e1jvd9/+1ywv3/HWB+/v2MuONbfMdbHDG3q8+8Y... | null |
5,580 | Breadth First Search: Shortest Reach | Consider an undirected graph where each edge weighs 6 units. Each of the nodes is labeled consecutively from 1 to n.
You will be given a number of queries. For each query, you will be given a list of edges describing an undirected graph. After you create a representation of the graph, you must determine and report ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> bfs(int n, int m, List<List<Integer>> edges, int s)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "\nimport java.util.*;\npublic class BreadthFirstShortestSearch {\n public static void main(String[] args){\n Scanner input = new Scanner(System.in);\n int test = input.nextInt();\n while(test > 0){\n int n = input.nextInt();\n int m = input.nextInt();\n ... | {
"class_name": null,
"func_sign": [
"bfs(n, m, edges, s)"
],
"solution": "class Graph(object):\n def __init__(self, N, M):\n self.N, self.M = N, M\n self.alist = {key:list() for key in range(1, N+1)}\n for index in range(M):\n t, h = [int(value) for value in input().split... | eJzsvcuKLtmT5SeEHuSjxl3g++rueg+BQAEaSD3QpNSDbhAIgR5ADy1f67fM42Sek3Xrqv7nIMlDRGTE55d9sduyZbb/3//hf/6f/r///r/7X/7vv/s//uE//Zf//Hf/4+fv2tc/9Pnp5/76h/bp+jL0ZerL0hf/4dSXS19ufWmHvzZ/9UXNVzVf1nxd84XNVzZf2nxt97Xd13Zf231tf67tenj/+KelL1tfTn259OXWFz28++HdD+9+ePfDux/e/fDuh3c/vPvh3Q/vfnj3w7sf3v3w8fGXpS9bX059ufTl1hc9d/i5w88dfu7wc4ef... | null |
5,686 | Kruskal (MST): Really Special Subtree | Given an undirected weighted connected graph, find the Really Special SubTree in it. The Really Special SubTree is defined as a subgraph consisting of all the nodes in the graph and:
* There is only one exclusive path from a node to every other node.
* The subgraph is of minimum overall weight (sum of all edges) amo... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int kruskals(int gNodes, List<Integer> gFrom, List<Integer> gTo, List<Integer> gWeight)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\nclass E... | {
"solution": "import java.util.ArrayList;\nimport java.util.LinkedList;\nimport java.util.PriorityQueue;\nimport java.util.Queue;\nimport java.util.Scanner;\n\npublic class KruskalMSTReallySpecialSubtree {\n\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n EdgeWeightedGraph ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.util.*;\n\npublic class Solution {\n\n private StreamTokenizer in;\n private PrintWriter out;\n\n private int[] parent;\n private int[] rank;\n\n class Edge {\n public int v;\n public int u;\n public int cost;\n\n ... | {
"class_name": null,
"func_sign": [
"kruskals(g_nodes, g_from, g_to, g_weight)"
],
"solution": "import os\nclass DisjointSet:\n def __init__(self, n):\n # Initialize parent and rank for union-find\n self.parent = [i for i in range(n)]\n self.rank = [0] * n\n\n def find(self, u):\... | eJxE/U2y7MyOdAd/DXW+rkaw7R0BIxi/0kRkpjsBdcrUkFrqaOjCWs48da3qPMjcmcwgGUQgAHfH//s//W//8//6/////e//z//4P/7r//y//6//8b/8/Y/+PM/fqn/+81/tr/+9Zb3/+a8y/vbZffznv96/8ff2/ZY5/ubfuHve//zX/Ft/a7e3/+e/1t/+G3O/9bX9d/7aPafePX/3b5zd/vNf9689f3u+49RPPH+t/a3VnzpGWa3/nX6fVS/6X3vr/+5TP4Q1/sZz65hltPm37+On5l9bf3OtUQcuq+2/+byMuKxWPz6nLxhGjXo9... | null |
54 | Clique | A clique in a graph is set of nodes such that there is an edge between any two distinct nodes in the set. Finding the largest clique in a graph is a computationally difficult problem. Currently no polynomial time algorithm is known for solving this. However, you wonder what is the minimum size of the largest clique in... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int clique(int n, int m)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatch... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner input = new Scanner(System.in);\n int t = input.nextInt();\n for(int c=0;c<t;c++){\n ... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n static int getMaxNonMCliqueEdgeNumber(int n,int k)\n {\n int g1 = n%k ;\n int g2 = k - g1 ;\n int sz1 = n/k + 1 ;\n int sz2 = n/k ;\n int ret = g1*sz1*g2*sz2 + g1*(g1-1)*sz1*sz1/2 + g2*(g2-1)*sz2*sz2/2 ;\n ... | {
"class_name": null,
"func_sign": [
"clique(n, m)"
],
"solution": "import math\ndef s1(n, m):\n ga = n%m\n gb = m-ga\n sa = n//m+1\n sb = n//m\n return ga*gb*sa*sb+ga*(ga-1)*sa*sa//2+gb*(gb-1)*sb*sb//2\ndef s(n,c):\n l = 1\n h = n+1\n while l+1 < h:\n m = l+(h-l)//2\n ... | eJyVVstuXUUQZMGSBTu2I68Rmn538yVIGLGALNiYLBIJCSHxEfC/VM2Nrxw71yjRie058+qurqo+f3/57zdffXH+/fA1/vjxz7vfHt6+f3f3/boTv3+wTl+RnZX3DxM6S8V8pDlXkitmb9+Y87Dlsq1K9P4ho5aMa90/VOfS3nsCq2brstIww3m+x5d4jpZgDu+wsM22z/1DY7yk9tgOHBiZOFG8zRtbK3CQqkVbNhbvwd7YNeocTuny3TVu9w933667N3+8ffPLuze//vz7+3cf0sOhl0fs8kseX1zGyDDOo3d/fbue4oL5ToQOAFrH... | null |
93 | Matrix | The kingdom of Zion has cities connected by bidirectional roads. There is a unique path between any pair of cities. Morpheus has found out that the machines are planning to destroy the whole kingdom. If two machines can join forces, they will attack. Neo has to destroy roads connecting cities with machines in order ... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int minTime(List<List<Integer>> roads, List<Integer> machines)"
],
"script_name": "Solution",
"solution": "import java.util.*;\nimport java.io.*;\nimport static java.lang.Math.*;\n\npublic class Solution {\n\tstatic class Foo51 {\n\t\tstatic class No... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.ArrayList;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\nimport java.util.LinkedList;\nimport java.util.List;\nimport java.util.Queue;\n\n... | {
"class_name": null,
"func_sign": [
"minTime(roads, machines)"
],
"solution": "def leader(x):\n if P[x]==x:\n return P[x]\n if P[x]==x+10**5:\n return P[x]\n P[x] = leader(P[x])\n return P[x]\n\ndef same(x, y):\n return leader(x)==leader(y)\n\ndef canJoin(x, y):\n return not(leader(x)>=10**5 an... | eJxrYJnKxgABPUzRsVP0ABkLAyg= | 1 |
17,340 | Recording Episodes | Dave is a die-hard fan of a show called "HackerRank", in which a young programmer uses her problem-solving abilities to solve crimes. He splurged on a Digital Video Recorder (DVR) so that he can record HackerRank episodes and watch them later. Luckily, Dave managed to get his hands on schedules for all the episodes in ... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> episodeRecording(List<List<Integer>> episodes)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n pub... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n static class Graph {\n int[] ptr;\n int[] nxt;\n int[] suc;\n int index = 1;\n\n public Graph(int nodes, int egges) {\n ptr = new int[nodes];\n nxt = new int[egges];\n suc = new int[egges];\n }\n\n ... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class F {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n... | {
"class_name": null,
"func_sign": [
"episodeRecording(episodes)"
],
"solution": "#True if two intervals interesects\ndef has_intersection(I1,I2):\n if I1[0] >= I2[0] and I1[0] <= I2[1]: return True\n if I1[1] >= I2[0] and I1[1] <= I2[1]: return True\n if I2[0] >= I1[0] and I2[0] <= I1[1]: return T... | eJx9vc2uLcmSVU2DBwnddgmF/7vzJEgkogHVoJNUo0pCQkg06NGFl+NpsDHMY9eFzHO/u77DqZN7rxUrwt3cbNqc0/77v/zf//P//Av/v3/zP+Iv//a//uU//f4P//SPf/nXz1/qb7/39dvv5W3vU0Y/TynvfMra47ff96jl2evtzz5rPqfW89vvZ7X2nLXij1N2/NF4i3esp49znl7q+/Rd+m+/j1HPM8tpzzh9PnP197ffay/taaXWp+7ZnnpOfHot833qGPOpbcZ/WS0+aNbx7P0+Kz6l9LfFj7X46Dr3ip+I62n9jR8bp8Z7l/U+... | null |
52 | ByteLandian Tours | The country of Byteland contains N cities and N - 1 bidirectional roads between them such that there is a path between any two cities. The cities are numbered (0,...,N - 1). The people were very unhappy about the time it took to commute, especially salesmen who had to go about every city selling goods. So it was decide... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int bytelandianTours(int n, List<List<Integer>> roads)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\n... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n private static final int MODULUS = 1000000007;\n\n private static class Node {\n Set<Node> neighbors = new HashSet<>();\n }\n\n /*\n * Complete... | {
"solution": "import java.util.ArrayList;\nimport java.util.Scanner;\n\npublic class Solution {\n\tpublic static void main(String [] args){\n\t\tfinal int MOD = 1000000007;\n\t\tfinal int MAXN = 10002;\n\t\t ArrayList<Integer>[] G = new ArrayList[MAXN] ;\n\t\t long [] fac = new long[MAXN] ;\n\t\t for(int c=0;c<MAX... | {
"class_name": null,
"func_sign": [
"bytelandianTours(n, roads)"
],
"solution": "import math\ndef tours(adj, N):\n facts = [0]*N\n z=0\n for i in range(len(adj)):\n vertList = adj[i]\n z_count = 0\n nz_count = 0\n for neighbor in vertList:\n if len(adj[neighb... | eJxU/b+Khcu28Oc5MPg2mhMrmFXjX01ficEbHEhf4GRbwScwCIHuyJHuT727nlrg7CSrNmet39vd831mjfG//1//H/+//+P/9n/5f/6v//X//vf//L/89//6v//81/rXv9fn869/f37+83/97H/9e//Ev/4dP/mvf+dP/evf9dP/+nf/zL/+PT/nX/8+P99//fv7sz7/+ed+1n/+ofWzfv+xtX/W7z+44mf9/qMrf9bvP7zqZ/3+46t/1u8Ba37W7xHr/KzfQ9b3Z/+esj8/+/eU/fu//Z//8f2zf0/Z8bN/T9n5s39P2fWzf0/Z/bN/... | null |
42 | Quadrant Queries | There are $n$ points on a plane. Each point $p[i]$ is described by $[x[i], y[i]]$, where $1 \le i \le n$. There are three types of queries needed:
1. `X i j` Reflect all points in the inclusive range between points $p[i]$ and $p[j]$ along the $x$-axis.
2. `Y i j` Reflect all points in the inclusive range betwe... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static void quadrants(List<List<Integer>> p, List<String> queries)"
],
"script_name": "Solution",
"solution": "/* Enter your code here. Read input from STDIN. Print output to STDOUT */\n\n\nimport java.io.BufferedReader;\nimport java.io.InputStreamReader;\n... | {
"solution": "import java.io.BufferedReader;\nimport java.io.InputStreamReader;\nimport java.util.ArrayList;\nimport java.util.Arrays;\n\npublic class Solution {\n private static final int[] BC = new int[1<<16];\n public static void main(String[] argv) throws Exception {\n prep();\n BufferedReade... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n \n public static int[] arr;\n static class SegmentTree {\n public int[] c;\n public int start, end;\n public boolean lazyx, lazyy;\n public SegmentTree left,right;\n public SegmentTree(int st... | {
"class_name": null,
"func_sign": [
"quadrants(p, queries)"
],
"solution": "#!/usr/env python\n\nimport bisect\nfrom math import sqrt\n\n_Rx = [ 3, 2, 1, 0 ]\n_Ry = [ 1, 0, 3, 2 ]\n\ndef create_test( N, Q, fp):\n from random import randint as rand\n r = [ ( rand(-2, 2), rand(-2, 2) ) for i in range( N) ]... | eJzsvcuOJEuyZUeA/BBHjXtg+lblNMacnwQLIAHyDjgp9uA20ABBgJ9OWUvUIvPUrazb3TMCRBVOeoRbuJvpQ1Qee2/5f/6HP/6n//W//+/+5//rL//H3/7jf/rXv/yPn7+M569/K5/617/VT//r39pn/vVv/bP/+rfxKfHO/JR4a31KvLc/Jd48nxLvludT+cP4y3i/1E+NC0r71Lii9E/lkvFpXDI/jUvWp3HJ/jQuOZ8Wl9Tn0+OSWj6dG4g7iEtq+/S4pPZP55Lx4Q7r/AwuWZ/BJfszuOR8RlzSns+MS1r5zLik1c/kQeJJ4pLW... | null |
1,090 | HackerX | **Update:** A slight modification in the problem statement (see below)
Evil Nation A is angry and plans to launch **N** guided-missiles at the peaceful Nation B in an attempt to wipe out all of Nation B's people. Nation A's missile _i_ will arrive in nation B at time t<sub>i</sub>. Missile _i_ communicates with its ... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int missileDefend(List<List<Integer>> missiles)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.Arrays;\n\npublic class Solution {\n\n static class Point implements Comparable<Point> {\n int x, y;\n\n ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n static class Point implements Comparable<Point> {\n int x, y;\n\n Point(int x, int y) {\n this.x = x;\n this.y = y;\n ... | {
"solution": "//package hackerrank;\n\nimport java.io.*;\nimport java.util.Arrays;\nimport java.util.StringTokenizer;\nimport java.util.function.Function;\nimport java.util.stream.IntStream;\n\n/**\n * Created by raggzy on 4/17/2016.\n * OOOh this was hard.\n * 1. Build graph i,j <=> fj-fi <= j-i. This transforms in... | {
"class_name": null,
"func_sign": [
"missileDefend(missiles)"
],
"solution": "n = int(input())\n\ninp = (map(int, input().split()) for i in range(n))\n\np = sorted(list((a + b, a - b) for a, b in inp))\n\na = list(y for x, y in p)\n\nd = []\nfor x in a:\n\tlow, high = -1, len(d) # >, <=\n\twhile high - low... | eJx0vcuuLUuSXaeGPmQr29WI8LfzSwToAmyQ2WAnWY0sgABBQJ8uG2PGPiBKqATyXPe1Y8WK8Ie5PaZN+3//z//7//pn+z/+n//5t//2j3/9t3/+7T/9/O396x/z5+29/fWPv/3Lz9/+/j/+9e//5Z9//6//+b//2z9/r/jb//qXn//tG+Ovf7Sfud+9abT3vfXd/jPOucebrXb2f3i38e/u1jp3efszXu5y5mz3r3+Mnzl6rz+t+tPZl8a5/a3fvj977v389Y/3+Wn9PPW39/25a45ZrfYz7jubrbrn5br+s049U7Xmzz7vS2v/3HbP... | null |
4,941 | Grid Challenge | Given a square grid of characters in the range ascii[a-z], rearrange elements of each row alphabetically, ascending. Determine if the columns are also in ascending alphabetical order, top to bottom. Return `YES` if they are or `NO` if they are not.
**Example**
$grid = \text{['abc','ade','efg']}$
The grid is i... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String gridChallenge(List<String> grid)"
],
"script_name": "Solution",
"solution": "import java.io.IOException;\nimport java.io.OutputStreamWriter;\nimport java.util.Arrays;\nimport java.io.BufferedWriter;\nimport java.util.InputMismatchException;\ni... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.io.PrintWriter;\nimport java.util.*;\n\n\npublic class Solution {\t\n\tBufferedReader reader;\n StringTokenizer tokenizer;\n PrintWriter out;\n \n\tpublic void solve() throws IOException... | {
"class_name": null,
"func_sign": [
"gridChallenge(grid)"
],
"solution": "def solve():\n\tn = int(input())\n\ta = [sorted(list(input())) for _ in range(n)]\n\tfor i in range(n - 1):\n\t\tfor j in range(n):\n\t\t\tif a[i][j] > a[i + 1][j]:\n\t\t\t\tprint(\"NO\")\n\t\t\t\treturn\n\tprint(\"YES\")\n\nt = int(... | eJwknGuuJEcVhBFiIdYsASwZsxIkWrLy/X6/kz9euiN7hICZO7erqzLPifiiMqv+/Md/6R9//9v//v/DxDz6j//88uPXT/wd/yXXemValJ5HU4fsVfq9WdmxFSnUZso5khwpa0dCpjxNWj4in03uoEtf7lLNs9r31ClxoCKotERoX50Mn+gIpSuxcOUlZ3k1y+G5UzKyOz1W5c9cvAqWpdNKSisqK4sIMrPsl5tyArsnRakl8TiglG0WHcuKjrORPnGr0ZvaomjX8OGyzrzUnEj9LbXxcZjwa1Cz0/TBpm7szpmaRLTHl4zLCO8qZGm8... | null |
21,401 | Maximum Perimeter Triangle | Given an array of stick lengths, use $3$ of them to construct a [non-degenerate triangle](https://en.wikipedia.org/wiki/Degeneracy_(mathematics)#Triangle) with the maximum possible perimeter. Return an array of the lengths of its sides as $3$ integers in non-decreasing order.
If there are several valid triangles havin... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> maximumPerimeterTriangle(List<Integer> sticks)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n pub... | {
"solution": "//Greedy approach\n//Constraint = sum of two sides is greater than third side\n//Perimeter maximization\nimport java.util.*;\npublic class MaxPerimeter {\n\n public static void main(String[] args) {\nScanner sc = new Scanner(System.in);\nint n = sc.nextInt();\nint[] a = new int[n];\nfor (int i = 0; i <... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class B {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"maximumPerimeterTriangle(sticks)"
],
"solution": "from itertools import *\nn = int(input())\nl = sorted(map(int, input().split()))\nans = (-1, -1, -1)\nfor i, j, k in product(*repeat(range(n), 3)):\n if i < j < k and l[i] + l[j] > l[k]:\n ans = max(ans, (l[k],... | eJztmM+Oo0kRxDnwCtxLfV5Q5d+q4kmQaMQB5gCHZlealZDQSjwEvC+/+Ja2F297EAdua2s0lv1VVWZkZGRU//3n//zmFz+7Xr/5Mx9++7eXP719/e3nl1+Pl9ivb3vvOfe00Sdyzd5n7HP8RK8YZb69Vuew3bNjZo/qHXayz8g949SIszvW8hg5IypWsZnZ8mmrhucxqz422Dx6W420eSzP5BM7Rhyfw2bu0zXnyK7cbj3MVwZx+Ngem+eD3XxZRebUWe6l72x28+ReI9NWnFw+yok3Vo6uVXsHZzlZkeAcdbIOCfBUrs1evseylbtt... | null |
16,828 | Beautiful Pairs | You are given two arrays, $A$ and $B$, both containing $N$ integers.
A pair of indices $(i, j)$ is *beautiful* if the $i^{th}$ element of array $A$ is equal to the $j^{th}$ element of array $B$. In other words, pair $(i, j)$ is *beautiful* if and only if $A[i] = B[j]$. A set containing beautiful pairs is called a *be... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int beautifulPairs(List<Integer> A, List<Integer> B)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public stat... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n private static InputReader in;\n private static PrintWriter out;\n\n public static void main(String[] args) throws IOException {\n in = new InputReader(System.in);\n out = new PrintWriter(System.out, true);\n\n int n = in.n... | {
"class_name": null,
"func_sign": [
"beautifulPairs(A, B)"
],
"solution": "input()\na = [x for x in input().split()]\nb = [x for x in input().split()]\naDict = dict()\nbDict = dict()\nfor val in a:\n if val in aDict:\n aDict[val] += 1\n else:\n aDict[val] = 1\nfor val in b:\n if val ... | eJztnU2uJUlShRmwkFCNWyj8352VIJGIAdSASdKDbgkJIbEImLAZZqwL+z6L10JVnSiLHlRVErxKMvPlffd6uNvPsWPHvP/1z//9v/7jz/y/v/rP+MNf//N3//D5t7//3Xd/eX1XPn3udX36vEb86bvfXN99/0+//f7vfvf93//tP/7+dx+v+e5ffnP9j5+pnz6Xcu1+f/q8+7x2bV/9o+PT53bHj6x5tbWvM8ZVzvn0ua51jX1fva+rzPjH/fXvWeNN95nxs/2qc18j3nz2dpV1rlnjfWe856lXm/1aY15n1/i9XKdfo/OtfvXarnnf... | null |
2,149 | Priyanka and Toys |
Priyanka works for an international toy company that ships by container. Her task is to the determine the lowest cost way to combine her orders for shipping. She has a list of item weights. The shipping company has a requirement that all items loaded in a container must weigh less than or equal to 4 units plus the ... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static int toys(List<Integer> w)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n private static Reader in;\n private static PrintWriter out;\n\n public static void main(String[] args) throws... | {
"solution": "import java.util.*;\npublic class PriyankaAndToys {\n\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n int n = sc.nextInt();\n List<Integer> arr = new ArrayList<Integer>();\n for(int i=0;i<n;i++) {\n arr.add(sc.nextInt());\n ... | {
"solution": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.util.Arrays;\nimport java.util.StringTokenizer;\n\n\npublic class Solution {\n\n\tpublic static void main(String[] args) throws NumberFormatException, IOException {\n\t\tBufferedReader bfr = new ... | {
"class_name": null,
"func_sign": [
"toys(w)"
],
"solution": "#!/usr/bin/env python\n\nimport sys\n\n\nif __name__ == '__main__':\n N = int(sys.stdin.readline())\n W = sorted(map(int, sys.stdin.readline().split()))\n\n cost = 0\n last_chosen = -5\n\n for w in W:\n if w > last_chosen +... | eJx0vbuubVm2XCdDgH5jI+1rjPeDnyFLgAqgQZZBJ3mNugABgoA+XaO1mDslFFBOISvznL3XmnOM/ogeEf3/+d//r/+z/B//2//9P//4b3/++3/844//9PPH/tufda2fcW77WaWvn153+xmj7Z/bdv/Zdbw/8se//fzx9//x73//L//4+3/9z//9P/7x+5f/+F//9vP/+2H9b3+uWttPK33+7HL7v/yb/Z/+5vzbn7eV+9POXD+3rP7Tyyo/89TxL3/G/Kefccr7KXXc+XN2KT9rz/Zz53n/t70f2nZ7P57v1fsuP7Xt+b7r+7Bz3vUz... | null |
3,583 | Jim and the Orders | Jim's Burgers has a line of hungry customers. Orders vary in the time it takes to prepare them. Determine the order the customers receive their orders. Start by numbering each of the customers from $1$ to $n$, front of the line to the back. You will then be given an *order number* and a *preparation time* for each ... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static List<Integer> jimOrders(List<List<Integer>> orders)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimp... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.InputStreamReader;\nimport java.io.IOException;\nimport java.util.Arrays;\nimport java.io.BufferedReader;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.util.StringTokenizer;\nimport java.math.BigInteger;\nimport java.io.InputStream;\n\n/**\n * Built using CHelpe... | {
"class_name": null,
"func_sign": [
"jimOrders(orders)"
],
"solution": "tuples = []\na = int(input())\nfor i in range(a):\n x, y = map(int, input().split(' '))\n tuples.append((x+y, i+1))\n\ntuples.sort(key = lambda x:x[0])\nprint(' '.join([str(x[1]) for x in tuples]))\n",
"template": "#\n# Complet... | eJzsvcuqds22paXghbyscgpjxGFEhFciuMCC7oKV5S5kQoIIXrrteXp8G/l1JQiKFhIx1/7+Oef7jhGHfmyt9f/tv/pv//W//i//i//uf/nb//SPf/0P//5v/83vb+vv/1jfbmv93uf7xt//sb/neb/f/mY7Lf8c7x7719/+jvzuPt+38s/99Wf//R9nrSc/bU9/vvP3f7Td++q/efp8+t//MeYa7/m935kjH/W3f/f727/8x3/9l//h3//L//jf/8//4d//eYLf+/t++avf+LW//a//7vd/eLrv7/94ez58/M77ff3wmf1869dWXytf... | null |
833 | Permuting Two Arrays | There are two $n$-element arrays of integers, $A$ and $B$. Permute them into some $A'$ and $B'$ such that the relation $A'[i] + B'[i] \ge k$ holds for all $i$ where $0 \le i \lt n$.
There will be $q$ queries consisting of $A$, $B$, and $k$. For each query, return `YES` if some permutation $A'$, $B'$ satisfying the re... | hackerrank | Easy | {
"class_name": "Result",
"func_sign": [
"public static String twoArrays(int k, List<Integer> A, List<Integer> B)"
],
"script_name": "Solution",
"solution": "/* HackerRank Template */\n\nimport java.io.*;\nimport java.util.*;\n\nimport static java.lang.Math.*;\nimport static java.util.Arrays.fill;\nimport... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.BufferedReader;\nimport java.io.InputStreamReader;\nimport java.util.Arrays;\n\npublic class Solution {\n\t\n//\tInput Format\n//\tThe first line contains an integer, T, the number of test-cases. T test cases follow. \n//\tEach test case has the following format:\n//\n//\tThe first line ... | {
"class_name": null,
"func_sign": [
"twoArrays(k, A, B)"
],
"solution": "def isGood(listA, listB, k):\n n = len(listA)\n listA.sort()\n listB.sort(reverse=True)\n for i in range(n):\n if listA[i]+listB[i] < k:\n return False\n return True\n\nT = int(input().strip())\nfor i ... | eJyE3b3OLc2SHGYZ1H0sHJtGV3V3dTd9XoEcCfoAGdIYdD6NMQMIIATwknkJjCdqDw3K0BzMnD17v+9a/VOVlRkZEflf/t3/+u/+6//8P/3v//kf/+nvf/7Xf/nHf/j94/7r7/f+re+8nmO9X/6/75vfuZ75u8d85/2s8zfedazzuO7fvd5zfNd6f9d7nN/1O793nc8z5+86zvM+n/v4rTGeeYzn+s3rG+Ne3/HLp5/rHdfvGsc3ru/In/KJ5/mN7zeO6/3W9X2/a93XO8f9G/O5zlzH+L3zfPPzZz5tPuM+89e+a87b341jrfzku37X... | null |
24,761 | Cloudy Day | Quibdó in Colombia is one among the cities that receive maximum rainfall in the world.
____________________________________________________________________________________
All year round, the city is covered in clouds. The city has many towns, located on a one-dimensional line. The positions and populations of each to... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static long maximumPeople(List<Long> p, List<Long> x, List<Long> y, List<Long> r)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solutio... | {
"solution": "DNE",
"template": "class Result {\n\n /*\n * Complete the 'maximumPeople' function below.\n *\n * The function is expected to return a LONG_INTEGER.\n * The function accepts following parameters:\n * 1. LONG_INTEGER_ARRAY p\n * 2. LONG_INTEGER_ARRAY x\n * 3. LONG_INT... | {
"solution": "import java.io.OutputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.Iterator;\nimport java.io.BufferedWriter;\nimport java.util.InputMismatchException;\nimport java.io.IOException;\... | {
"class_name": null,
"func_sign": [
"maximumPeople(p, x, y, r)"
],
"solution": "from collections import defaultdict\n\n\ndef maximumPeople(towns, cloud_start, cloud_end):\n towns = sorted(towns)\n cloud_start = sorted(cloud_start)\n cloud_end = sorted(cloud_end)\n\n cloud_start_i = 0\n cloud... | eJzsvcuubVuSZYUEHzLl5SyM94MvQeIiChAFKpcsZEpICIlP4hPprY11IZUhlzyBFBWPCHkcP2fvteYcD3t069btf/+v/pv/7v/4L/+L//Z//dv/9Oe//ff/7m//9fe3tuYff557ZxnjnG+32epZ+dPpbY46Rv/uXH2Xevu3z2r5x7W+NWvZe6/+rTZKu3N/tdZbRp/ty2fc0Vq937qt7zXm+vrYY7d77nfHqSOfsr9R7u2nzPrVVWfLp5xv9DJvfit/mqXlj/myfE1+e47yjdZX6eWer68929j5uX7HWCc/+rWT35tln2+2Pms/o311... | null |
22,923 | Flipping the Matrix | Sean invented a game involving a $2n \times 2n$ matrix where each cell of the matrix contains an integer. He can reverse any of its rows or columns any number of times. The goal of the game is to maximize the sum of the elements in the $n \times n$ submatrix located in the upper-left quadrant of the matrix.
Given the... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int flippingMatrix(List<List<Integer>> matrix)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static voi... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner sc=new Scanner(System.in);\n int t=sc.nextInt();\n while(t--!=0){\n int n=sc.n... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class C {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"flippingMatrix(matrix)"
],
"solution": "q = int(input())\nwhile q > 0:\n q -= 1\n \n n = int(input())\n A = []\n for i in range(2 * n):\n A += [list(map(int, input().split()))]\n \n ans = 0\n for i in range(n):\n for j in range(n):\... | eJx0/c2qtcuypAcKSn3dwuS0s/HGf4SuRFAb1ChlQ50tNTJBIArq0hXPYzFWligKzl5nre+bc4z3J8LD3dzM/P/z3/9P/+v/43/47/6f/+d//K///t//63/5j//x7z/6v/5d7v+Nvf9G2//6dz2t/Y2y/vXvc/94z/1XSll/319bpf2VtftfLX381T3WX9lf+auj9r8z/kob82/2+9uj/bXd9v3B0/7q19df++7f9ernr/lXxl87X79/vM79/XZ/ed1vqLX8nXX/bvZ+/2S1v30/qvRS/tq4f//dixnj/trmG9u5f3I/cN5/4SPun46/... | null |
28,615 | Gaming Array | Andy wants to play a game with his little brother, Bob. The game starts with an array of distinct integers and the rules are as follows:
- Bob always plays first.
- In a single move, a player chooses the maximum element in the array. He removes it and all elements to its right. For example, if the starting array ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static String gamingArray(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.math.BigInteger;\nimport java.util.*;\n\n\n\npublic class B\n{\n String line;\n StringTokenizer inputParser;\n BufferedReader is... | {
"solution": "import java.util.*;\npublic class GamingArray {\n public static void main(String[] args) {\n Scanner sc = new Scanner(System.in);\n int g = sc.nextInt();\n for(int tst=0;tst<g;tst++) {\n int n = sc.nextInt();\n int count = 0;\n int max = 0;\n ... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class A {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n... | {
"class_name": null,
"func_sign": [
"gamingArray(arr)"
],
"solution": "#!/bin/python3\n\nimport sys\n\n\ng = int(input().strip())\nfor a0 in range(g):\n n = int(input().strip())\n a = list(map(int, input().split()))\n \n idx_sorted = [x for x,y in sorted(enumerate(a), key = lambda x: -x[1])]\n ... | eJx8nbHOLTuQlQlIeIutGxO0y3a7ezIQMaSguRIBTEBymWBGQkJIPB6PRX/f6vYgJEj2+c/e3W67XC67q1at+p///N//7f/6F//sb//7H//lr7//x3/4429+f7T686/Zn49a/ey/Wkfnc9T9fLZ2PZ99Lr45yl/n81nt5HM0Pou/x8mV7eKaVn6/Bp/z+fW8F6317jf5dfD3Mfm7Hzyxt9uWD1o4vf6wD8tetfJef23c24Z/D59404fDb45z2oI9pw/nfdmaT+zT1ibfDJ8+jlxjm46u3Yz3uLo9p+V+2+cz/Vca3af3yyfy92je1abS... | null |
15,305 | New Year Chaos | It is New Year's Day and people are in line for the Wonderland rollercoaster ride. Each person wears a sticker indicating their *initial* position in the queue from $1$ to $n$. Any person can bribe the person *directly in front* of them to swap positions, but they still wear their original sticker. One person can bribe... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static void minimumBribes(List<Integer> q)"
],
"script_name": "Solution",
"solution": "import java.awt.*;\nimport java.awt.event.*;\nimport java.awt.geom.*;\nimport java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*; \nimport java.... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\n\npublic class HourRank4qB {\n\n\tstatic int pos[], arr[];\n\t\n\tpublic static void main(String args[]) {\n\t\tInputReader in = new InputReader(System.in);\n\t\tPrintWriter w = new PrintWriter(System.out);\n\n\t\tint t = in.nextInt();\n\t\t\n\t\twhile(t-- > 0 ... | {
"class_name": null,
"func_sign": [
"minimumBribes(q)"
],
"solution": "\ndef count_inversion(lst):\n return merge_count_inversion(lst)[1]\n\ndef merge_count_inversion(lst):\n if len(lst) <= 1:\n return lst, 0\n middle = int( len(lst) / 2 )\n left, a = merge_count_inversion(lst[:middle])\... | eJzVnc2uJMmRnbXQgyS4Hgjh/x56Di0EiIIgjAaQNpxZcAABgoDZ6QWkB9Ebyr7PPKuyb99bdau6SUKDaZJdFZkZEe5uduzYOe7/8q//z//6v//K//v3/xL/4z/8jz/8tz/90z//+Q//9vGH+sc/xf+XR/xHj/9/1Ed5tD/+6Q9/9/jDP/z3f/qHv//zP/yX//SP//znc/X1xz/9u3/8x8ff/9f//I9//m9/H5f9z797/PLLSvfbHu3RH+MxH+txP/ajXI9SHiW+vD284npeNeI6rtpxHX/6wQ+XuP7dn9uvP7fiq/KLXn/uUcajzEdZ... | null |
15,577 | Prime XOR | Penny has an array of $n$ integers, $[ a_0, a_1, \ldots, a_{n-1} ]$. She wants to find the number of unique [multisets](https://en.wikipedia.org/wiki/Multiset) she can form using elements from the array such that the [bitwise XOR](https://en.wikipedia.org/wiki/Bitwise_operation#XOR) of all the elements of the multiset ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int primeXor(List<Integer> a)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\npublic class c {\npublic static void main(String[] args) throws IOException {\n\tinput.init(System.in);\n\tPrintWriter out = new PrintWr... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import javafx.beans.property.IntegerProperty;\n\nimport java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n static Scanner in;\n static PrintWriter out;\n\n static int N = 4501;\n static int M = 8192;\n static ... | {
"class_name": null,
"func_sign": [
"primeXor(a)"
],
"solution": "from collections import Counter\nfrom math import sqrt\n\n\ndef primes(n):\n x = [True]*((n-1)//2) # Representing all odd numbers >= 3 and <= n.\n for i in range(int((sqrt(n)-3)//2)+1):\n if x[i]: # Number represented by i (c... | eJxMvTuy7UqyXEuBDQFvC5BAZiLBPlCnGasDVMoo8ElPYavYPs4cwwPrCFW2z95rzQnkJz4eHh7/5z//9//73/7Lf/of//9//M9//6//73//x389/mP869/rvv/1796efvTWx9HP8R69P7//u/v6/d85jvsd7bif/uwf+f1pXs9xr/b7z/P3p35d8/evz+8fxtv3z63fj7zt98Pr97ujn78/3b/feNrvH97r/f3uun7/cM7fBzz37++e8/d/a//Dtf9z//Dbf/857t9T9fn71+fdf/d7tN+X7/87f383rrG/6Nqf8vuO6/l9/Br7e688... | null |
15,974 | HackerRank City | HackerRank-city is an acyclic connected graph (or [tree](https://en.wikipedia.org/wiki/Tree_(graph_theory))). Its not an ordinary place, the construction of the whole tree takes place in $N$ steps. The process is described below:
* It initially has $1$ node.
* At each step, you must create $3$ duplicates of the curren... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int hackerrankCity(List<Integer> A)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.In... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n /*\n * Complete the hackerrankCity function below.\n */\n static int hackerrankCity(int[] A) {\n int n = A.length;\n long[] cluster_size... | {
"solution": "import java.io.OutputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.io.BufferedWriter;\nimport java.io.Writer;\nimport java.io.OutputStreamWriter;\nimport java.util.InputMismatchException;\nimport java.io.IOExcep... | {
"class_name": null,
"func_sign": [
"hackerrankCity(A)"
],
"solution": "import sys\n\ninp = sys.stdin\nn = int(inp.readline().strip())\nlengths = list(map(int, inp.readline().strip().split(' ')))\n\nf = 0\ng = 0\nh = 0\nm = 1\nfor a in lengths:\n f = (4*g*(3*m+2) + 4*f + 16*a*m*m + 12*a*m + a) % 1000000... | eJzs3bvOLUmWJGYK8yALKbeQcY/oJyHAAkaYKaGVnBKqgQEaA8xTU+Y529fnFqeLORLBJoiNQt7i/P/eER7u62LLzOp//qf//bf/8z/9b//Hv/32L3/87V///ts/12/778t6/OWPp85aav/x1/Xjf/ePfx4//rnUWs+P/62f/zo+/37++Ofy4+/7j3/un//ef/z89rl+/Pi3+/On54+f3/oz9h+/f33+/vy4dn1+8ufvHJ/v+/kd6+d7x3esnyvX5xOuzyf+/Gv/3MP54/d/ft75+Zanf/P+fMr1+bTn8/ef3zR+c3zmeJr78/et7+j4... | null |
11,859 | Summing Pieces | Consider an array, $A$, of length $n$. We can split $A$ into contiguous segments called *pieces* and store them as another array, $B$. For example, if $A = [1, 2, 3]$, we have the following arrays of pieces:
- $B = [(1), (2), (3)]$ contains three $1$-element pieces.
- $B = [(1, 2), (3)]$ contains two pieces, one havin... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int summingPieces(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n public static final long MOD ... | {
"solution": "\nimport java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner in = new Scanner(System.in);\n \n int n = in.nextInt();\n long sum = 0;\n ... | {
"solution": "\nimport java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class D2 {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t// 6+9+11+18\n\tfinal ... | {
"class_name": null,
"func_sign": [
"summingPieces(arr)"
],
"solution": "def coeff(n):\n a = pow(2, n, 1000000007)\n res = [a - 1]\n for i in range((n - 1) // 2):\n a = a * 250000002 % 1000000007\n res.append((res[-1] + (a - 1) * pow(2, i, 1000000007)) % 1000000007)\n if n & 1:\n ... | eJxM3TuubV1znOky5FcXFn6bxrxf1AS1QEARKKNEoxyWDAoQIAhQj9UF5fPOLaD4geDhOXuvNS9j5MiMjIj8H//uP/7P//B//h//13/7x//7r//5v/zbP/797x/n+8//ul7bse77u/7O9dm25T6233Pt+3Idx++61v14lvP8Xe+zrNv1u+b/LNe+vL9ne69rO9/zdx7vex33u/3ubV3u/bre3/rM72/3Mf94rsf67Mf8wvz4fa/Pz///vvf7/u5zeZ9ze57fc9zX/OD2/vb3nL/e1ut3vOf+HMd5/659vmx9t+M313tt731cv/t41/d4... | null |
61 | Lego Blocks | You have an infinite number of 4 types of lego blocks of sizes given as (depth x height x width):
```
d h w
1 1 1
1 1 2
1 1 3
1 1 4
```
Using these blocks, you want to make a wall of height $n$ and width $m$. Features of the wall are:
<br>
- The wall should not have any holes in it.
- The wall you build should b... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int legoBlocks(int n, int m)"
],
"script_name": "Solution",
"solution": "import java.util.*;\n\npublic class Solution {\n\tint md=1000000007;\n\tint[][] ways = new int[1001][1001];\n\tint[][] waysRestrict = new int[1001][1001];\n\tpublic Solution(){\... | {
"solution": "import java.util.Scanner;\n\nclass Solution{\n static final int mod=1000000007;\n static int[] f;\n static int mult(int x, int y){\n long z=x;\n z*=y;\n return (int) (z%mod);\n }\n static int pow(int x, int n){\n int r=1;\n while(n!=1){\n if((n&1)==1) r=mult(r,x);\n... | {
"solution": "import java.util.Scanner;\n\npublic class LegoBlocks {\n\n\tprivate static long[] f = new long[1001];\n\tprivate static long[] g = new long[1001];\n\tprivate static long[] h = new long[1001];\n\n\tpublic static void main(String[] args) {\n\n\t\tScanner in = new Scanner(System.in);\n\t\tint T = in.nextI... | {
"class_name": null,
"func_sign": [
"legoBlocks(n, m)"
],
"solution": "MAX = 1000000007\n\ndef calcLevels(levels):\n\tN = len(levels)\n\tM = len(levels[1])\n\n\tlevels[1][0] = 1\n\tp = 1\n\twhile p<M:\n\t\ti = 1\n\t\twhile i<=4 and p-i>=0:\n\t\t\tlevels[1][p] = (levels[1][p] + levels[1][p-i]) % MAX\n\t\t\t... | eJydl02OJUkRhFlwAI4QqvUIRYT/RXASJAqxgF6woJhFjzQSGolDwH35zKuA4dGvEVMtVWW/l+nhbm5ubvnXn//98y9+1j+//hMXv/nLyx/fvv3u88uvxst9fTsxMrf+nuF3vr7dmmPVeX0L32O9vtlZ497SRYw4/vq27YzkBrt7+OKWNdfweH17+Wa8fPr+20+///zpD7/783efP05x33bNZ+rOs+ec9vpW5cE1YQhQdmZFKA8+t7m3c+nn1IlVnL19znXXUZ5zxT728sM340eV6MmTY6+PRNfcT/Ph1BXkXDrtzJk2H6LxTayRm/P2... | null |
85 | Brick Tiling | You are given a grid having N rows and M columns. A grid square can either be blocked or empty. Blocked squares are represented by a '#' and empty squares are represented by '.'. Find the number of ways to tile the grid using L shaped bricks. A L brick has one side of length three units while other of length 2 units. A... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int brickTiling(List<String> grid)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.Inp... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n private static final int MOD = 1000000007;\n private static final int[][] pieceMasks = new int[][] { {0,7,1,4}, {-2,2,-1,2,0,3}, \n ... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n public static void main(String[] args) {\n Scanner in = new Scanner(System.in);\n int T = in.nextInt();\n for (int t = 0; t < T; t++) {\n int N = in.nextInt();\n int M = in.nextInt();\n ... | {
"class_name": null,
"func_sign": [
"brickTiling(grid)"
],
"solution": "def memoize(func):\n pool = {}\n def wrapper(*arg):\n if arg not in pool:\n pool[arg] = func(*arg)\n return pool[arg]\n return wrapper\n\nmod = 1000000007\nshapes = (\\\n ((1,0),(2,0),(2,1)),\\\n ... | eJzNV0uO1DAQZcEFuEGU2o5KceJ8miU7boDEIBYwCzbNLHokJITEIeC+xK6PK3GcyQwgdcvtOP5UlV/VKzs/X/5+++pF/L17Mzfef6+/nO8fLvXrqva356lqb8+I+383VW5uxQLSsAVMYzXBnXitDsHWwlwgDbk+qT5Y6puqvvt2f/fpcvf549eHS9psQ6X+cVMtURiqIewUAYNiAKSd83t4hvfQD7Ef16g8tcxruyCJ1IUKbRXls1Kp6JUNkj5YCQCe0pF4tFUBl2YHFzLTahH1pCppJoMhn6yVMVgFuKby0WLaOFma6rwnq301RsXI... | null |
330 | Stock Maximize | Your algorithms have become so good at predicting the market that you now know what the share price of Wooden Orange Toothpicks Inc. (WOT) will be for the next number of days.
Each day, you can either buy one share of WOT, sell any number of shares of WOT that you own, or not make any transaction at all. What is the m... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static long stockmax(List<Integer> prices)"
],
"script_name": "Solution",
"solution": "\nimport java.io.BufferedReader;\nimport java.io.IOException;\nimport java.util.StringTokenizer;\nimport java.io.InputStreamReader;\npublic class Solution {\n public s... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\nclass Solution {\n\tprivate static long[] getElements(String elements, int size) {\n\n\tString[] elementsArray = elements.trim().split(\" \");\n\n\t\tif (elementsArray.length != size)\n\t\t\tthrow new IllegalArgumentException(\"Number of elements in the list does... | {
"class_name": null,
"func_sign": [
"stockmax(prices)"
],
"solution": "test=int(input())\nfor i in range(test):\n n=int(input())\n a=list(map(int,input().split()))\n c=0\n i=len(a)-1\n while(i>=0):\n d=a[i]\n l=i\n p=0\n while(a[i]<=d and i>=0):\n p+=a[... | eJzsvc3KNMuWpCeErkKjYI9rkMtXeHhmX4lAG3pQdQY12XUGp6CgadDN6D5lj3mmo4kQAglajcGON23HF54/YfH7hLut/+1/+l/+x//9f/4f/tf/8se//vX3f//HH//p+mP8+dfb0/Wu6/261uda72utaz3Xmte6r9XXGteqa72u53M97+tZ1/Ncz7ye+3r6esb11PW8rvm55vua65rPNec172v2Ncc165qv6/5c9/u613U/1z2v+77uvu5x3XXdr6s/V7+vXlc/V8+r76v76nF1Xf26xuca72usazzXmNe4r9HXGNeoa7yu+lz1vmpd... | null |
9,200 | Two Robots | You have a warehouse with $M$ containers filled with an infinite number of candies. The containers are arranged in a single row, equally spaced to be $1$ meter apart. You also have $2$ robots that can pick up $1$ piece of candy and transport it between any two containers.
The robots take instructions in the form of *q... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int twoRobots(int m, List<List<Integer>> queries)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.Arrays;\n\npublic class HR_two_robots {\n\n public static void solve(Input in, PrintWriter out) throws IOException {\... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class WeekOfCode19qB {\n\n\tpublic static void main(String[] args) {\n\t\tInputReader in = new InputReader(System.in);\n\t\tPrintWriter w = new PrintWriter(System.out);\n\n\t\tint t = in.nextInt();\n\n\t\twhile(t-- > 0){\n\t\t\tint m = in.nextInt();\n\t\... | {
"class_name": null,
"func_sign": [
"twoRobots(m, queries)"
],
"solution": "from collections import defaultdict\n\ndef dist(x, y):\n return abs(x - y)\n\ndef solve(boxes):\n boxes.reverse()\n c = [0] * len(boxes)\n c[0] = dist(boxes[0][0], boxes[0][1])\n for bi in range(1, len(boxes)):\n ... | eJzsvU2uLE2zpQUSA0nddjXC/z0YCRJHogHVoHOpRpWEhJAYDDNhYth6lrnnqXvv10SiIDvxvvvk3pER7m5/y5aZ/R//zX/3f/5f//V/9d//b//0P//zf/hP//Gf/tvPP9U//9xa/5Q//1zm8+nPn3+e/f2U3v/8c53tM/aKT+r+1B0flWd8Sol/aW/9tBJ/NPb8lB2/PJ/26fqruHxmmfE7a33GE7/TZv30GX8Vf/xM3aXGB/HF9Vmfvt8//7zbZ/aqr45/aFv33/EM8RtNX6hv3vvThv4nPokvjY/id0dreswafx1/NMb8NL5nx20e... | null |
514 | Cut Tree | Given a tree *T* with *n* nodes, how many subtrees (*T'*) of *T* have at most *K* edges connected to (T - T')?
| hackerrank | Medium | {
"class_name": null,
"func_sign": [
"static int cuttree(int n, int k, int[][] edges)"
],
"script_name": "Solution",
"solution": "import java.io.BufferedInputStream;\nimport java.util.ArrayList;\nimport java.util.Scanner;\n\n\npublic class Solution {\n\tstatic long rooted[][] = new long [55][55];\n\tstati... | null | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n \n private static List<List<Integer>> children = new ArrayList<>(51);\n private static long[][] findCache = new long[51][51];\n private static long[][][][] ignoreCache = new long[51][51][51][51];\n\n static {\n fo... | {
"class_name": null,
"func_sign": [
"cuttree(n, k, edges)"
],
"solution": "line = input().split()\nn = int(line[0])\nK = int(line[1])\n\nadjlst = [[1]]\nfor i in range(n):\n adjlst.append([])\nadjlst[1].append(0)\n\nfor i in range(n - 1):\n line = input().split()\n x = int(line[0])\n y = int(li... | eJztWMtuJEUQ5MAf8AOlOa9Q5aNefAkSRhzABy7DHtYSEqzER8D/UhnRbte0py0tEkJI60P3PFzVmRGRkVnzx5d//f7VF/j79mm++O63y8/X908fLt+ki4wkD1dJGhd7uFryeFXiUuNti1f94appPFw9SX649iQSXwkWyVw1N3F8Mte1JHOhaJIWq2SurUnm4su7dHn89f3jjx8ef/rhl6cPWwTWLx/fpSWkkhmDxnKLi8dlbl0ipBIhtQhJIiRFSIqQFCENhCSCmBQxKWIqCCm+iMUZQUlJOtdLSxob5KSKf1FDDuqxn5ZIWmsAoA2f... | null |
29,079 | Tara's Beautiful Permutations | Tara has an array, $A$, consisting of $n$ integers where each integer occurs *at most* $2$ times in the array.
Let's define $P$ to be a permutation of $A$ where $p_i$ is the $i^{th}$ element of permutation $P$. Tara thinks a permutation is *beautiful* if there is no index $i$ such that $p_i - p_{i+1} = 0$ where $i \i... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int beautifulPermutations(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void ... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n /*\n * Complete the beautifulPermutations function below.\n */\n static int beautifulPermutations(int[] arr) {\n /*\n * Write your code... | {
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.InputMismatchException;\n\npublic class C {\n\tInputStream is;\n\tPrintWriter out;\n\tString INPUT = \"\";\n\t\n\tvoid solve()\n\t{\n\t... | {
"class_name": null,
"func_sign": [
"beautifulPermutations(arr)"
],
"solution": "# Enter your code here. Read input from STDIN. Print output to STDOUT\nimport sys\n\nmodval=1000000007\ninvmod=[1,500000004,250000002,125000001,562500004]\n\n\nclass Combination:\n\n\n def __init__(self,size):\n comb... | eJyUvcuuLMuybQUSHzJ1yhTC/B18BiUkjkQBboHK5hbulZAQEl/EN5Lu1lqsiH32KnAeM9fIkenhD+v26N0ixv/z3/1P/+P/+9/+N//z//Vv//s//vN//S//9j/8+bf493/Mf/9H+1P+1D9x/r/8+z/+7b//82//6f/8z//pf/0v/+l/+1/+j//6X/hsaePf/u///s/323H9+z/qn/773/Kn/f43zjB/P0i927r+4zDj3/9RmMTv+3//7X/x1bvvWbTxJ674fftq/ffP9ZvJVe793v6vWPu9+cfPVT9S4/nt/kXZ/1X25+q1fzH9SN1D... | null |
5,553 | Wet Shark and Two Subsequences | One day, Wet Shark was given an array $X = \{x_1, x_2, \ldots, x_m\}$. As always, he started playing with its [subsequences](http://en.wikipedia.org/wiki/Subsequence).
<br>
When you came to know about this habit, you presented him a task of finding all pairs of subsequences, $(A, B)$, which satisfies all of the follo... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int twoSubsequences(List<Integer> x, int r, int s)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimpo... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.IOException;\nimport java.io.OutputStreamWriter;\nimport java.io.BufferedWriter;\nimport java.util.InputMismatchException;\nimport java.io.OutputStream;\nimport java.io.PrintWriter;\nimport java.util.NoSuchElementException;\nimport java.io.Writer;\nimport java.math.BigInteger;\nimport ja... | {
"class_name": null,
"func_sign": [
"twoSubsequences(x, r, s)"
],
"solution": "def solve():\n mod = 10**9+7\n m,r,s = map(int,input().rstrip().split(' '))\n if m == 0 or r<=s: return 0\n arr = list(map(int,input().rstrip().split(' ')))\n if (r-s) % 2 != 0: return 0\n sumb = (r-s)//2\n ... | eJzllzGvZLcNhVOkD+AitfBqIxBFiZTySwLkGSmcLdK8uFgDBgwD/hHx/835qNmFkcUas0WaZBcz7869EkUeHh7y/vz7X/741e/q31/+oIu//vjyj7fvvn//8uf2Yr233uyc8/pm7X/h/+i9v3zdXt798N27b9+/+/vf/vn9+0ew/fXt5aev26/Cz9kitz7x+rY8mvWVbQ9dzBUt9dhsCB8LF0jztHF0xlpaOHQnbDfzKACz2eBrrqEVOdqaejgWD/dqc3tLw9SR0eDLU8t7LBacZqlVMq1NU4fMqRXZ5ckZMjh3Njcs+2y1cbn2DNee... | null |
16,423 | Nikita and the Game | Nikita just came up with a new array game. The rules are as follows:
* Initially, Nikita has an array of integers.
* In each move, Nikita must partition the array into $2$ non-empty contiguous parts such that the sum of the elements in the left partition is equal to the sum of the elements in the right partition. If ... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int arraySplitting(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "\nimport java.util.*;\nimport java.io.*;\n\npublic class B\n{\n public static void main(String[] args) throws Exception\n {\n FastScanner in = new FastScanner(... | {
"solution": "import java.util.*;\nimport java.io.*;\n\npublic class B\n{\n public static void main(String[] args) throws Exception\n {\n FastScanner in = new FastScanner(System.in);\n PrintWriter out = new PrintWriter(System.out);\n int T = in.nextInt();\n while (T-->0) new B(in, out);\n ... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class AprilFools16QB {\n\n\tstatic int b[];\n\tstatic long pre[];\n\t\n\tpublic static void main(String[] args) {\n\t\tInputReader in = new InputReader(System.in);\n\t\tPrintWriter w = new PrintWriter(System.out);\n\n\t\tint t = in.nextInt();\n\t\t\n\t\t... | {
"class_name": null,
"func_sign": [
"arraySplitting(arr)"
],
"solution": "import math\n\ndef solve(a):\n s = sum(a)\n if s % 2:\n return 0\n s //= 2\n t = 0\n for i in range(len(a)):\n t += a[i]\n if t == s:\n #print(sum(a[:i + 1]), sum(a[i + 1:]))\n ... | eJzsncuuZUlyXAVBHxLogUYcxPuhLxHAAjSQONAkxQEJCBAE6NNly9x3VnWLTYIzAUxWo1mdee85e0f4w9zcPOL//If//B//9t//u7/9X3/67z/+/h//4U//qfxp/PZjrvvbj1HP3quVtt8eo+1T1h711v1uWU1/9dZr5Y1aZxtzldFWHb2uU3qf+rFzV7m1tbvP6GXMfnofdZc72tuvzVZ2H2Oc20a5p98xt37jrfPGfVu/O++eR79cun7w6kdf0ffvcfRkZVw9wu6nlrlnnfrz5U+pa+pT2njjtdW6nv702vQxpa97+9Hjzaqfm2vq... | null |
20,053 | LCS Returns | Given two strings, $a$ and $b$, find and print the total number of ways to insert a character at any position in string $a$ such that the length of the [Longest Common Subsequence](https://en.wikipedia.org/wiki/Longest_common_subsequence_problem?oldformat=true) of characters in the two strings increases by one. | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int tutzkiAndLcs(String a, String b)"
],
"script_name": "Solution",
"solution": "import java.awt.image.ReplicateScaleFilter;\nimport java.io.*;\nimport java.math.*;\nimport java.util.*;\n\nimport javax.swing.RepaintManager;\n\npublic class Main {\n\n... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class LCSReturns {\n\n\tBufferedReader br;\n\tPrintWriter out;\n\tStringTokenizer st;\n\tboolean eof;\n\n\tvoid solve() throws IOException {\n\t\tString a = nextToken();\n\t\tString b = nextToken();\n\n\t\tint n = a.length();\n\t\tint m = b.length();\n\n... | {
"class_name": null,
"func_sign": [
"tutzkiAndLcs(a, b)"
],
"solution": "#!/bin/python3\n\nimport math\nimport os\nimport random\nimport re\nimport sys\n\n#\n# Complete the 'tutzkiAndLcs' function below.\n#\n# The function is expected to return an INTEGER.\n# The function accepts following parameters:\n# ... | eJztfdfS3MiSni70IBvnekMBb3QH0w3b8F5UKOC991AoQg8hvZyeRk1yzhzOkD/dzOxunOiPCWRWVmYhy6CqwO7G/7//8/9d/t9/+gCvfQr/7X/+reyGdfnbf/2XvwUdhWaGbdzlKiGcZtDZvKnWGNuY613HR/PUHq5vTVg5KmRQChKX30RDZ7IEhiV1tt3cMCMAlX3qwUNS7php5uEUjvsdp+Q2YYoy5dL7vZ6gw7GXxwZniVdEtIPcUTERJsq9oPGcSVlcIpIZCocK/vav//K39BjSeEmT/9Gvyy9xwjj6rvvb//rXf/kkdoRd45yL... | null |
33,054 | Matrix Land | You are playing a matrix-based game with the following setup and rules:
- You are given a matrix $A$ with $n$ rows and $m$ columns. Each cell contains some points. When a player passes a cell their score increases by the number written in that cell and the number in the cell becomes $0$. (If the cell number is posi... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int matrixLand(List<List<Integer>> A)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n\n public static void main(St... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\nimport java.util.function.Consumer;\n\npublic class Solution {\n\n\n static MyScanner sc;\n private static PrintWriter out;\n static long M2 = 1_000_000_000L + 7;\n\n public static void main(String[] s) throws Exception {\n StringBuilder string... | {
"class_name": null,
"func_sign": [
"matrixLand(A)"
],
"solution": "import os, sys\n\nwith open('progIn.txt', 'w') as file:\n for line in sys.stdin:\n file.write(line)\n\nprog = r\"\"\"\n#include <iostream>\n#include <algorithm>\n#include <cmath>\n#include <vector>\n#include <set>\n#include <util... | eJztvUuO7EiWJVho1EIIH4cVKH+RXEkB5YUcZMYgJ54xiAASSCTQi6h99hZKzufSXmgwuiwaHu1qCcLxTJ1CKlUoIvfccz9y+X//1//+//yv/+u//I9//+lffvnDn/740z8cP/Vj/fzLR67l2H8q/jT86fgzrv9r19nCq+8unHdf4dV3F667r/DqmwvbefeV/w/3/hv6/dPvjp9+/29/+P0//fH3//yP//qnP3q89on/+N3xwwCmY3ck5XHM8/izj6/fou6v8Gly3j+eMRUZPc3oS0avMvqX0dOMhytn/J/axnVdu77LifrqvUr6wl15... | null |
1,617 | Bricks Game | You and your friend decide to play a game using a stack consisting of N bricks. In this game, you can alternatively remove 1, 2 or 3 bricks from the top, and the numbers etched on the removed bricks are added to your score. You have to play so that you obtain the maximum possible score. It is given that your friend wil... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int bricksGame(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.Inpu... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.*;\nimport java.io.*;\nclass Solution {\n public static void main(String[] args) throws Exception {\n BufferedReader reader = new BufferedReader(new InputStreamReader(System.in));\n int T = Integer.parseInt(reader.readLine());\n for(int i = 0; i < T; i++) {\n ... | {
"class_name": null,
"func_sign": [
"bricksGame(arr)"
],
"solution": "INF = 10**18\n\ndef one_test():\n\tn = int(input())\n\ta = list(reversed(list(map(int, input().split()))))\n\tdp = [0] * (n + 1)\n\tfor i in range(n):\n\t\ttake = 0\n\t\tdp[i + 1] = -INF\n\t\tfor j in range(i, max(i - 3, -1), -1):\n\t\t\... | eJzsvb2urE2SnSdDru6h0PYY+f+jKxGgD6AhjUHnI40hQIAgoNvRXep51ntakCDSl5GdM3361N5VlW9mZMSKFSvy/B//4//y7/7P/+l/+F//yz/+/d//8T/92z/+598/6l9/t/LX3+VXf+3Xf+M3f+u3f+d3f5UX66+2X+2/On51/ur61f2r51fvX3//419+//jX//wf//V/+7d//d//3X/4T//25wPv4kf/9V9+/4/vGH/9XWfl9XNW7/W319pn/vpes/5uqbOXX9tz9vZrqza+ZZ0z+Jpzz+2/eeoe/Kjs085v3tEKb65rMcHW1zz7... | null |
1,431 | The Longest Increasing Subsequence | **An Introduction to the Longest Increasing Subsequence Problem**
The task is to find the length of the longest subsequence in a given array of integers such that all elements of the subsequence are sorted in strictly ascending order. This is called the Longest Increasing Subsequence (LIS) problem.
For example, the... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int longestIncreasingSubsequence(List<Integer> arr)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\n\npublic class Solution {\n \n static i... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.Arrays;\nimport java.util.Scanner;\npublic class Solution {\n\n\tpublic static void main(String[] args) {\n\t\tScanner in=new Scanner(System.in);\n\t\tint n=in.nextInt();\n\t\tint[] Array=new int[n];\n\t\tfor(int i=0;i<Array.length;i++){\n\t\t\tArray[i]=in.nextInt();\n\t\t}\n\t\tint le... | {
"class_name": null,
"func_sign": [
"longestIncreasingSubsequence(arr)"
],
"solution": "def subsequence(seq):\n if not seq:\n return seq\n\n M = [None] * len(seq) # offset by 1 (j -> j-1)\n P = [None] * len(seq)\n\n # Since we have at least one element in our list, we can start by \n ... | eJx8ncmubsl1nG3Afg+ixhpk5spWr+GJAV/AA1sDTcoakIAAwYAf3RFf7FMULNECeENk1V73NPHvbL7V/J//9F//y3/8z//hv/3Lb//4+z/95c+//f2ffluttV+/D/2n3q/f1/31+zm/fn/71++9L/1RU3+s0h9n6I/X9S93PzH0r4+pf39sPTCunqimJ2roiZp6oraeqKsnpv+O2fXELD0xl56YR0/MpydW1xOr9MRaemIdPbGenthNT+yhJ/bUE3vriX31xGl64gw9caaeOFtPnKsnztMTt+uJW3riLj1xj564T0+8ride6Ym39MQ7... | 1 |
3,514 | Play with words | Shaka and his brother have created a boring game which is played like this:
They take a word composed of lowercase English letters and try to get the maximum possible score by building exactly 2 **palindromic subsequences**. The score obtained is the product of the length of these 2 [subsequences](https://en.wikiped... | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int playWithWords(String s)"
],
"script_name": "Solution",
"solution": "/**\n * Created by zhengf1 on 12/18/2014.\n */\nimport java.io.*;\nimport java.util.*;\nimport java.text.*;\nimport java.math.*;\nimport java.util.regex.*;\npublic class Dec101_C... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class PlayWithWords {\n\n\tBufferedReader br;\n\tPrintWriter out;\n\tStringTokenizer st;\n\tboolean eof;\n\n\tvoid solve() throws IOException {\n\t\tchar[] s = nextToken().toCharArray();\n\t\tint n = s.length;\n\t\tint[][] dp = new int[n + 1][n + 1];\n\t... | {
"class_name": null,
"func_sign": [
"playWithWords(s)"
],
"solution": "def findMaxSubsequence(seq):\n length = len(seq)\n seqLength = [[0 for i in range(length)] for j in range(length)]\n for i in range(length):\n seqLength[i][i] = 1 \n for cols in range(2,length+1):\n for i in ra... | eJztnduqbUlynvvC+Dmauhamq6WWuvQkBtuYPEeez0cj8EPYz2v/s/GFqdYWajC4ETPHZFBr7bnmyIyM+P8vVlXl/u//7n/++/CbP43/+L/8b37zn/7bTzaVOX76x9/+xJ5mS3DLJP3n9NPf/PYndYoSQ8n/muf4P+/525/+6W9++3/9jGZVxfkC15fnmnP94U/+/Ptf/Whtj8sn/tWPqksI9Xx3ud7hgyVprZAm78hZkUnqSI+NmuSoVMer+8gT7e18hiT5qXvvQ2dxo388x59/+dVDKewVjMCn+baq7WuOHUU6cTtd54yJq7jUTtJZ... | null |
101 | Interval Selection | Given a set of $n$ intervals, find the size of its largest possible subset of intervals such that no three intervals in the subset share a common point. | hackerrank | Medium | {
"class_name": "Result",
"func_sign": [
"public static int intervalSelection(List<List<Integer>> intervals)"
],
"script_name": "Solution",
"solution": "import java.util.*;\nimport java.io.*;\nimport static java.lang.Math.*;\n\npublic class Solution {\n\tstatic class Foo53 {\n\t\tvoid main() {\n\t\t\tBuff... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.util.Arrays;\nimport java.util.Scanner;\n\nclass IntervalsPicker {\n\tprivate class Interval implements Comparable<Interval> {\n\t\tint start, end;\n\n\t\tpublic Interval(int start, int end) {\n\t\t\tthis.start = start;\n\t\t\tthis.end = end;\n\t\t}\n\n\t\t@Override\n\t\tpublic int compareT... | {
"class_name": null,
"func_sign": [
"intervalSelection(intervals)"
],
"solution": "import sys\n\ndef readnums():\n return [int(x) for x in sys.stdin.readline().strip().split(\" \")]\n\nfor i in range(readnums()[0]):\n intervals = []\n for j in range(readnums()[0]):\n intervals.append(readnu... | eJx0vc2q9UyTpmewD0TUuAfK/0wficEFHtg18KTcg2owGIPBB+BTdlxXaEmb+qo+6H6j9Ky9lpTKjN877vh//of/6f/7f//7/+5//r/+6X//1//63/7tn/7H65/6P//r+ud/PWWXs+7SL6V9Snsujr5PXjzj/C6u0sdzsbXxu1jP+8l9PxfnapuL9b7LfX7fWfNi/NCo5Xex3fX55L1qXIzbWqfGV/UyL6XSdvldbPN+LvY1fhdX3GteLOV+L/bfxXneT+79+/My2u/iLL+Lde/fxdPG74fq/j5Zr+ef93zvs63fD8334mj998lZ3+8c... | null |
58 | String Reduction | Given a string consisting of the letters $\text a$, $\text b$ and $\text c$, we can perform the following operation:
* Take any two adjacent distinct characters and replace them with the third character.
Find the shortest string obtainable through applying this operation repeatedly.
For example, given the string... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int stringReduction(String s)"
],
"script_name": "Solution",
"solution": "/*\n * Anand Oza\n * October 29, 2011\n */\n\nimport java.io.IOException;\nimport java.io.InputStreamReader;\nimport java.io.StreamTokenizer;\n\npublic class Solution {\n\tpubl... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n int min;\n\tint val;\n\tString cat;\n\tboolean flag;\n\tchar redux(char c1, char c2) {\n\t\tif (c1 == 'a') {\n\t\t\tif (c2 == 'b') return 'c';\n\t\t\tif (c2 == 'c') return 'b';\n\t\t}\n\t\tif (c1 == 'b') {\n\t\t\tif (c2 == 'a') retu... | {
"class_name": null,
"func_sign": [
"stringReduction(s)"
],
"solution": "#!/usr/bin/python\n\nimport collections, sys\n\n\nchar_set = 'abc'\n\nif __name__ == '__main__':\n T = int(sys.stdin.readline())\n \n for i in range(T):\n chars = sys.stdin.readline().lower().strip()\n count = c... | eJzFVs1u1DAQ5sCRh1jlXKHddCnQJ0FiEZoZ9sBl6WErIaFKPAS8GTdeBs/3jRMnsaNdCYSbto5jz+833/j785+/XzzDePcrTd5/6z6fHh7P3f2m6w8nkfSri5/DqbvZdMevD0c7Hz99/PJ4Ho/s0senm00h5/ZwMh8qomaiqibmgsXXrKJjTX5Vxc6l/Y3R1Px6u1C63x9OyX7zR90Hiyf5m1xNn9L3tCA+MfiJN3/1UOCv/zP3OWISQnJIXAP+plGECVMbAukmqMfWprH0Fxevwl2uThl6F5kWTKHCswI7BBbStsjM6JWG3LDEnUry... | null |
51 | Queens on Board | **Queens on Board**
You have an *N* \* *M* chessboard on which some squares are blocked out. In how many ways can you place one or more queens on the board, such that, no two queens attack each other? Two queens attack each other, if one can reach the other by moving horizontally, vertically, or diagonally without pas... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int queensBoard(List<String> board)"
],
"script_name": "Solution",
"solution": "import java.io.ByteArrayInputStream;\nimport java.io.IOException;\nimport java.io.InputStream;\nimport java.io.PrintWriter;\nimport java.util.Arrays;\nimport java.util.In... | {
"solution": "import java.io.*;\nimport java.math.*;\nimport java.security.*;\nimport java.text.*;\nimport java.util.*;\nimport java.util.concurrent.*;\nimport java.util.function.*;\nimport java.util.regex.*;\nimport java.util.stream.*;\nimport static java.util.stream.Collectors.joining;\nimport static java.util.str... | {
"solution": " import java.util.ArrayDeque;\n import java.util.ArrayList;\n import java.util.HashMap;\n import java.util.HashSet;\n import java.util.List;\n import java.util.Map;\n import java.util.Queue;\n import java.util.Scanner;\n import java.util.Set;\n import java.util.Stack;\n ... | {
"class_name": null,
"func_sign": [
"queensBoard(board)"
],
"solution": "def memoize(func):\n pool = {}\n def wrapper(*arg):\n if arg not in pool:\n pool[arg] = func(*arg)\n return pool[arg]\n return wrapper\n\nmod = 1000000007\n\nfor case in range(int(input())):\n Y,X ... | eJztVktOxDAMZcEFuEGUbEdRPk0/nASJIhbQBZsyi46EhJA4BFyIHbcicVraijjTEYw0FekidtLYTuxnO6/n758XZ/BdfVjm+pk+tNtdRy8JlULUrSSybnndKqIsZXXL7EQT7SbczVjP4RvHPcAljUlj0pg0/lONdENo87Rt7rrm/vZx1w3F1qqo28ruAyYfmLTyc4W+bMi0T9lfhhjrXff9NWFH0OkJhoRcylJJFbqnFIAsJ80YIAsQx/etIaZMYUJWjHDeZAxE10P4KRxiKcHLQADdE3DHxYPhlK40RYQEjoGjZFQiPcEwUMmsFJUO... | null |
3,994 | Police Operation | Roy is helping the police department of his city in crime fighting. Today, they informed him about a new planned operation.
Think of the city as a $2D$ plane. The road along the $X$-axis is very crime prone, because $n$ criminals live there. No two criminals live at the same position.
To catch these criminals, the po... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int policeOperation(int h, List<Integer> criminals)"
],
"script_name": "Solution",
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n\tBufferedReader br;\n\tPrintWriter out;\n\tStringTokenizer st;\n\tboolean eof;\n\n\t... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n BufferedReader br;\n PrintWriter out;\n StringTokenizer st;\n boolean eof;\n\n static class Line {\n long k;\n long b; \n\n public Line(long k, long b) {\n this.k = k;\n this.... | {
"solution": "import java.io.*;\nimport java.util.*;\n\npublic class Solution {\n\n\tBufferedReader br;\n\tPrintWriter out;\n\tStringTokenizer st;\n\tboolean eof;\n\n\tstatic class Line {\n\t\tlong k;\n\t\tlong b; // y = k * x + b\n\n\t\tpublic Line(long k, long b) {\n\t\t\tthis.k = k;\n\t\t\tthis.b = b;\n\t\t}\n\n\... | {
"class_name": null,
"func_sign": [
"policeOperation(h, criminals)"
],
"solution": "#!/bin/python3\n\nimport os\nimport sys\n\n#\n# Complete the policeOperation function below.\n#\ndef cross(f, g):\n return (g[1]-f[1])/(f[0]-g[0])\n\ndef policeOperation(h, criminals):\n n = len(criminals)\n dp = 0... | eJx0nUvONct2VSkg2pG6ZRcy3hG0BAkkCuACFeOCLSEhJFpCQ2gdc4zYe59zffG1T/zry8ydz3isx1xz/e9/+x/+z//9d//mP/7Pv/y3f/jHf/6nv/z75y/1fd9nvJ///ad/KE8pby/nadN/dutr9Sfb3tk7O0/j317G2uepjROsp6623/M+7d3vbPl3zvOOnGWPWmp5eq99nvPkZHVkez+1zNOesVtpZT1zzTJaeVaZpe/xrLPeUeezR6k507PnO7iPfXr2z+eU3to6ua9SaykzQg5dc+QOZ8tdNISzi8LJ3+t9cqq9z1gRVp+zZlfd... | null |
102 | Unfair Game |
You are playing a game of Nim with a friend. The rules are are follows:
1) Initially, there are N piles of stones. Two players play alternately.
2) In each turn, a player can choose one non empty pile and remove any number of stones from it. At least one stone must be removed.
3) The player who picks the last ... | hackerrank | Hard | {
"class_name": "Result",
"func_sign": [
"public static int unfairGame(List<Integer> s)"
],
"script_name": "Solution",
"solution": "import java.util.*;\nimport java.io.*;\nimport static java.lang.Math.*;\n\npublic class Solution {\n\tstatic class Foo57 {\n\t\tstatic final long INF = Long.MAX_VALUE/3;\n\t\... | {
"solution": "\nimport java.util.Arrays;\nimport java.util.Scanner;\n\n/*\n * To change this template, choose Tools | Templates and open the template in\n * the editor.\n */\n/**\n *\n * @author muoi\n */\npublic class Solution {\n\n public static long MAX_BIT = 32;\n public static long n;\n static long a[]... | {
"solution": "//package hackerrank;\n\nimport java.util.Scanner;\nimport java.util.stream.IntStream;\n\n/**\n * Created by raggzy on 4/15/2016.\n * <p>\n * Sprague-Grundy\n * We need to find such set, which gives 0 xor\n * So we just DP from each bit pos till end\n */\npublic class UnfairGame {\n\n public static ... | {
"class_name": null,
"func_sign": [
"unfairGame(s)"
],
"solution": "#!/bin/python3\n\nimport os\nimport sys\n\n#\n# Complete the unfairGame function below.\n#\ndef unfairGame(s):\n nimSum = 0\n for i in s:\n nimSum ^= int(i)\n \n if(nimSum == 0):\n return 0\n\n # if(nimSum == 1... | eJzFms2KbclxhTXwgyR33IjMyH8/icHXeGD1QBpcSdACgRH4Iez39ffFPvcgilsNGqlbJU5Xnb13ZsSKtVZE7v/5l//780+/yX/+7Q98+Pf//vL7b3/6yy9f/rV8aePrt9b5qbfdOk85p645b618WvxiDz6tqLOde0qPuviPu8ttp9196i79zrlv7aNE3XdEXD7d2nZvZ5dV9x5rjShjnX7Xur3wp8UD9y2j1rlHzPn1G4u4/ay+5+D3a5zVNt+Iw517zOUav35bu3O3daNw83bv3a2suc6JXk+Zd9TGAjtLYe08MUo/re4Yc5d9Y556... | null |
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