2019第十届蓝桥杯C++B组题解（赛后重写的，不确保答案正确性，仅供参考）

先说一下这次的感受吧，我们考场比较乱，开始比赛了，还有的电脑有故障，（向这些人发出同情），第一次认真参加比赛，真正比赛的时候感觉没有那么正式，很乱，各种小问题，（例如博主就没找到题目在哪里，找到后又不知道解压密码，过了十分钟，才正式开始做题。。），好气自己赛前没有好好看BFS，不会记录路径啊，迷宫题凉凉了，然后没好好读题数的分解又凉了，太蒟蒻，灵能传输又凉凉了。

认真读题真的很重要，说的很对，阅读理解杯，读懂了事半功倍，读不懂寸步难行。

试题 A: 组队

【问题描述】 作为篮球队教练，你需要从以下名单中选出 1 号位至 5 号位各一名球员， 组成球队的首发阵容。 每位球员担任 1 号位至 5 号位时的评分如下表所示。

请你计算首发阵容 1 号位至 5 号位的评分之和最大可能是多少？
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" alt="" />

答案：490

试题 B: 年号字串

【问题描述】 小明用字母 A 对应数字 1，B 对应 2，以此类推，用 Z 对应 26。对于 27 以上的数字，小明用两位或更长位的字符串来对应，

例如 AA 对应 27，AB 对 应 28，AZ 对应 52，LQ 对应 329。 请问 2019 对应的字符串是什么？

26进制：2019=2*26^2+25*26+17　　　　　注意A是从1开始的，我第一次就做成27进制了，应该是26进制

答案:　　BYQ

试题 C: 数列求值

【问题描述】 给定数列 1, 1, 1, 3, 5, 9, 17, …，从第 4 项开始，每项都是前 3 项的和。求 第 20190324 项的最后 4 位数字。

#include<iostream>
#include<algorithm>
using namespace std;
#define ll long long
int f[22000000] = { 0,1,1,1 };
int main() {
	for (int i = 4; i <= 20190324; i++) {
		f[i] = (f[i - 1] + f[i - 2] + f[i - 3]) % 10000000;
	}
	cout << f[20190324] << "\n";
	return 0;
}

答案：4659

试题 D: 数的分解

【问题描述】 把 2019 分解成 3 个各不相同的正整数之和，并且要求每个正整数都不包 含数字 2 和 4，一共有多少种不同的分解方法？

注意交换 3 个整数的顺序被视为同一种方法，例如 1000+1001+18 和 1001+1000+18 被视为同一种。

#include<iostream>
#include<algorithm>
using namespace std;
#define ll long long
int check(int x) {				//判断x是否满足
	while (x) {
		int t = x % 10;
		if (t == 2 || t == 4)return 0;
		x /= 10;
	}
	return 1;
}
int a[2000];
int main() {
	int ans = 0;
	for (int i = 1; i < 2000; i++) {						//先把数组处理好，否则输出不出来。
		if (check(i))a[ans++] = i;
	}
	int k = 0;
	for (int i = 0; i < ans; i++)
		for (int j = i+1; j < ans; j++)
			for (int z = j+1; z < ans; z++) {
				if (a[i] < a[j]&&a[j] < a[z]&&a[i]+a[j]+a[z]==2019)			//各不相同，用<处理一下就可以，
					k++;
			}
	cout << k << "\n";
	return 0;
}

答案：40785　　　　（十分没有了哇，没好好看题，各不相同，，，，我还在计算，当两个相同时，三个相同时，各不相同时）

试题 E: 迷宫

【问题描述】 下图给出了一个迷宫的平面图，其中标记为 1 的为障碍，标记为 0 的为可 以通行的地方。
010000

000100

001001

110000
迷宫的入口为左上角，出口为右下角，在迷宫中，只能从一个位置走到这 个它的上、下、左、右四个方向之一。 对于上面的迷宫，从入口开始，可以按DRRURRDDDR 的顺序通过迷宫， 一共 10 步。其中 D、U、L、R 分别表示向下、向上、向左、向右走。 对于下面这个更复杂的迷宫（30 行 50 列），请找出一种通过迷宫的方式， 其使用的步数最少，在步数最少的前提下，请找出字典序最小的一个作为答案。 请注意在字典序中D<L<R<U。（如果你把以下文字复制到文本文件中，请务 必检查复制的内容是否与文档中的一致。在试题目录下有一个文件 maze.txt， 内容与下面的文本相同）

01010101001011001001010110010110100100001000101010
00001000100000101010010000100000001001100110100101
01111011010010001000001101001011100011000000010000
01000000001010100011010000101000001010101011001011
00011111000000101000010010100010100000101100000000
11001000110101000010101100011010011010101011110111
00011011010101001001001010000001000101001110000000
10100000101000100110101010111110011000010000111010
00111000001010100001100010000001000101001100001001
11000110100001110010001001010101010101010001101000
00010000100100000101001010101110100010101010000101
11100100101001001000010000010101010100100100010100
00000010000000101011001111010001100000101010100011
10101010011100001000011000010110011110110100001000
10101010100001101010100101000010100000111011101001
10000000101100010000101100101101001011100000000100
10101001000000010100100001000100000100011110101001
00101001010101101001010100011010101101110000110101
11001010000100001100000010100101000001000111000010
00001000110000110101101000000100101001001000011101
10100101000101000000001110110010110101101010100001
00101000010000110101010000100010001001000100010101
10100001000110010001000010101001010101011111010010
00000100101000000110010100101001000001000000000010
11010000001001110111001001000011101001011011101000
00000110100010001000100000001000011101000000110011
10101000101000100010001111100010101001010000001000
10000010100101001010110000000100101010001011101000
00111100001000010000000110111000000001000000001011
10000001100111010111010001000110111010101101111000

题解：思路就是先把每个能够走到的点到终点的距离求出来，然后从起点开始遍历

这么优秀的题解当然不是我这个蒟蒻做出来的，代码参考自这里：yxc大佬

/*   思路就是先把每个能够走到的点到终点的距离求出来，然后从起点开始遍历  */

#include <iostream>
#include <algorithm>
#include <string>
#include <string.h>
#include <queue>
using namespace std;
char a[40][60];													//存图
int nextx[4] = { 1,0,0,-1 }, nexty[4] = { 0,-1,1,0 };			//D<L<R<U		字典序直接把方向数组处理好就可以了
int dist[40][60];												//定义一个dist数组，用来存放各点到终点的最短距离
char dir[4] = { 'D','L','R','U' };
bool check(int x, int y) {
	return x > 0 && y > 0 && x <= 50 && y <= 50 && a[x][y] == '0'&&dist[x][y] == -1;
}
void bfs() {													//BFS扫一遍，求出各点到终点的最短距离
	queue<pair<int, int> >q;
	memset(dist, -1, sizeof(dist));
	dist[30][50] = 0;
	q.push({ 30,50 });
	while (!q.empty()) {
		pair<int ,int> t = q.front();
		q.pop();

		for (int i = 0; i < 4; i++) {
			int newx = t.first + nextx[i];
			int newy = t.second + nexty[i];
			if (check(newx, newy)) {
				dist[newx][newy] = dist[t.first][t.second] + 1;
				q.push({ newx,newy });
			}
		}

	}
}

int main() {

	for (int i = 1; i <= 30; i++)
		for (int j = 1; j <= 50; j++)
			cin >> a[i][j];
	bfs();
	cout <<"\n长度："<< dist[1][1] << "\n";

	int x = 1, y = 1;																		//从起点开始遍历
	string res;																				//存答案
	while (x != 30 || y != 50) {
		for (int i = 0; i < 4; i++) {
			int newx = x + nextx[i];
			int newy = y + nexty[i];
			if (newx > 0 && newy > 0 && newx <= 50 && newy <= 50 && a[newx][newy] == '0'&&dist[newx][newy]==dist[x][y]-1) {
				x = newx, y = newy;
				res += dir[i];
			}
		}
	}
	cout << res << "\n";
	return 0;
}

试题 F: 特别数的和

【问题描述】 小明对数位中含有 2、0、1、9 的数字很感兴趣（不包括前导 0），在 1 到 40 中这样的数包括 1、2、9、10 至 32、39 和 40，共 28 个，他们的和是 574。 请问，在 1 到 n 中，所有这样的数的和是多少？
【输入格式】
输入一行包含两个整数 n。
【输出格式】
输出一行，包含一个整数，表示满足条件的数的和。
【样例输入】 40
【样例输出】 574
【评测用例规模与约定】

对于 20% 的评测用例，1≤n≤10。

对于 50% 的评测用例，1≤n≤100。

对于 80% 的评测用例，1≤n≤1000。

对于所有评测用例，1≤n≤10000。

样例说明：1+2+9+10+11+12+13+14+15+16+17+18+19+20+21+22+23+24+25+26+27+28+29+30+31+32+39+40=574　　　只有包含0，1，2，9的数都算

题解：枚举判断是否包含2 0 1 9 就可以了

#include<iostream>
#include<algorithm>
using namespace std;
#define ll long long
int check(int x) {				//判断x是否满足
	while (x) {
		int t = x % 10;
		if (t == 2 || t == 0||t==1||t==9)return 1;
		x /= 10;
	}
	return 0;
}
ll n, sum=0;
int main() {
	cin >> n;
	for (int i = 1; i <= n; i++) {
		if (check(i))sum += i;
	}
	cout << sum << "\n";
	return 0;
}

试题 G: 完全二叉树的权值

【问题描述】 给定一棵包含 N 个节点的完全二叉树，树上每个节点都有一个权值，按从 上到下、从左到右的顺序依次是 A1, A2, ··· AN，如下图所示：

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAS0AAADMCAYAAAAmjPV9AAAgAElEQVR4nO29Z3dUSZb3+3yR536Eee66a83cZ7p77kxP3dXVXd1VRVFdRQNVVOMKZJD3HhnkvUUOkEMgBBKSEEJCCHkJCeS99z7lUqk05/zuixq43T1lUqDMVCrjt1a+0dI5EedEnH9E7Nh7x/9AIBAIzIj/YeoKCAQCwUEQoiUQCMwKIVoCgcCsEKIlEAjMCiFaAoHArBCiJRAIzAohWoIfRZbln/wJBKZEiJYAgK2tLQYGBqioqCAtLY24uLi/+8XExBATE0N2djbPnz9ncnISlUpl6moLLBAhWhaMJEmsra1RWVlJaGgovr6+REdHk5qaSmZmJrdu3Xr3y8zMJD09nbS0NMLCwvDz8yM6Oprm5ma2traQJMnUjyOwEIRoWSj7+/tUVVURGBiIr68vkZGRPHjwgN7eXhQKBWq1Gq1W+3c/tVrN2toabW1t5OTkEBYWhpeXF5GRkbx584b9/X1TP5bAAhCiZYEsLi6SnZ2N7TVbQkJCePnyJSsrK+h0Or3voVarWVhYoLy8HG9vb5ycnCgtLWVjY0PYvQQGRYiWBSHLMhMTE4SGhuLu7s69e/eYn58/kFj9IzqdjqGhIbKysnBwcCA7O5uFhQUhXAKDIUTLgpicnMTX1xdXV1eamprY29s7tHsrlUpKS0uxtbXl5s2bLC4uHtq9BYK/RYiWhbC8vExQUBAuLi60t7cbxP60v79PRUUF1tbW5OTksL6+fuhlCARCtCyA/f190tPTcXR0pLm52aAG8/39fYqLi7l27RrPnj0TbhGCQ0eIlgXw4sULLl++TEVFBUql0uDl7ezskJycjK+vL319fcK+JThUhGgdczY3N3F0ciQyMpKFhQWjlTsxMYGtrS3Z2dkoFAqjlSs4/gjROuZUVVXh4OBAW1sbWq3WaOVqtVry8/Px8PCgq6vLaOUKjj9CtI4xGo0Gd3d3MjMzTWIUn5mZwcHBgeLiYmHbEhwaQrSOMRMTE3z33XfU1tai0WiMXr5GoyEiIoLw8HCmpqaMXr7geCJE6xjz+PFj3NzcGBwcNJkxvKamBicnJ5qamoRBXnAoCNE6pkiSRHR0NJmZmaysrBzsYlnHxJvX9I0vsKP+sEDo5eVlHBwcKCsrM6pNTXB8EaJ1TNFqtbi4uFBdXX1gvyytcplbQW54xRXRP7/Nh8yPJEnC3d2dBw8eiIBqwaEgROuYolarsba2pqWl5YBpYyTmu6qJvW7D/3vaicdNA+zrfpAtWadla1eJWnuwWMWAgAAePHhwqGFDAstFiNYxZX9/H2tra1pbWw8kWrJ6k0f59yh98gj776+Qeu8ZyztqQGZ5sIH0ohL6phcPNPuKiIjg0aNHRnFsFRx/hGgdU/b397GysjrwTEsx0U5QaDJZ+fcJtP2WS+6JtI+uICGzOtyAe3wSDX0jSAdQraioKEpKSoRoCQ4FIVrHFLVajY2NDc3NzfqnnpHVvKrI405uAU+e1VKSE8/Xf7En9+lrttUSOtUaSQ+K6BgZP5BoBQYGCl8twaEhROuYotPp8PLyoqamRk+xkNiY6iAp5Q4tXaPsqvZRbkwRcfUiroE36ZtZR723emDR0ul0uLm58eDBA9Rq9Qc9k0AAQrSOLbIsk5CQQHp6OsvLy7/4/5Jmm9aSTLwCk3nRNYlKK7G/OUNusDtWNq7k17xmcvQ1ftFhPGjoYHtfv9nb3Nwc9vb2lJeXC5cHwaEgROsYU1FRgb2DPb29vb/o2ClpdxntekX9i0bG59dQ62TUO6v0dLTy4vlz2gammJseorzyMU394+yo9ROtp0+f4urqSmtrq3AuFRwKQrSOMTMzM5w9e5aqqqpDWZrJkg6NRo1Gp0Mf/VGr1YSFhREbG8vc3NwHly8QgBCtY41Op8PX15fU1FRWV1eNXv74+Di2traUlpYKe5bg0BCidcxpaGjA1taW5uZmowZNazQa0tLScPdwp7e312jlCo4/QrSOOdvb2/j4+BAVFcX8/LzRyh0cHOTq1avk5uayvb1ttHIFxx8hWsccWZbp6OjAysqK4uJiowiIQqEgKiqK4OBgRkZGhAFecKgI0bIANBoNObk52NnZ8eLFC4PGAO7s7JCfn4+joyMvX74UtizBoSNEy0LY2NggIiICa2trgwmXUqmksLCQy5cvU1hYyObm5qGXIRAI0bIQVCoVERERfPzxx1y+fJmnT58e6lJxbW2NgoICzp49y+9+9zseP34swnYEBkGIlgWg0+moqKjg1KlTxMTEEBkZiYODA1lZWUxOTn6Qp7paraa/v5/Y2FhcXFxITU3FysoKe3t7Ojs7hRe84NARonXMkSSJxsZGzp07R1hYGLOzs6ytrVFYWIinpyc+Pj48ePCAhYUF/QOr+SHJ4Pj4OLdv38bT0xM/Pz9qampQKBTvDP8+vj6MjApDvOBwEaJ1zBkdHcXa2hoHBwcGBgbeCdP+/j4dHR1ERUXh4uJCYFAgubm5NDU1MTU1xc7Ozt+ltNHpdGxubjI8PExtbS3p6elcv34dT09PMjIyGBoaemd01+l01NTUcPabs8TExLC4uGiSZxccT4RoHWMWFxfx9fXFysqK5ubmH013vLa2xsuXL0lPTyc6Oprg4GCuX79OREQE8fHxJCQkkJCQQGxsLGFhYfj5+REUFERUVBQ5OTm8efOG3d3d/3bfvb09CgoK+Oabb8jJyREHtgoODSFax5S9vT0SExP55ptvqKys/NkEfLIso9VqmZ2d5fnz59y6dYu4uLh3x3+Fh4cTERFBYmIieXl5NDQ0sLKy8ov2qq2tLeLi4jh37hzPnj0TOeIFh4IQrWPI/v4+RUVFfP311+Tn5x94lqPValEqlWxvb//dT6VSHTDf/A+paXx8fLC3t6etrc0k5y8KjhdCtI4ZkiTx/PlzvvrqKyIjI4+EPam/v59r167h4eFBf3//gYVPIPhbhGgdM3p7e7l8+TKenp6MjY0dCYGQJIm6ujouXLhASEgIU1NTYkdR8N4I0TpGzM/P4+rqirW1NW/evDlSPlL7+/s8fPiQb7/9loyMDNbW1kxdJYGZIkTrmPA2TOfbb7+lpqbmSJ4xuLOzQ2ZmJufPnzda8Lbg+CFE6xigUqlIT0/n1F9Ocf/+fba2tkxdpZ9kaWmJsLAwLl26xIsXL0RAteDACNEyc2RZpqqqii+//PJdhtKjbC+SZZmxsTEcHR1xcHCgu7v7SNjdBOaDEC0zRpIkOjo6OH/+PDdu3GBmZsYsBECSJF69esX333/P9evXGR8fN4t6C44GQrTMmPHxcaysrLCzs2NwcNCsPvy3M8Rvv/2WhIQElpaWTF0lgZkgRMtMWVtb4/r165w/f57Gxkaz9DZXKpXcvn2bc+fOkZeXx8bGhqmrJDADhGiZISqVirS0NL7++msqKip+NkTnqLO2tkZkZCTnz5/n6dOnIgeX4BcRomVmaDQaHj58yJ///GeysrKOxexkamoKX19fHBwcaG1tFaE+gp9FiJYZIcsyL1++5KuvvuLGjRvMz88f6Z1CfZFlmZ6eHuzs7PD09GRoaOhYPJfAMAjRMiOGh4e5evUq7u7uDA8PHyhp31FHp9Px4sULLl68SGhoqAj1EfwkQrTMhOXlZTw9PbG2tqarq+tIhegcFm9Dfc6cPUNmZuaxWPoKDh8hWmbA1tYWMTExnDp1ipqammNtrN7Z2SE1LZWLFy/y+PHjH00wKLBshGgdcdRqNXfu3OGLL77g7t27RzpE57BYWFggMDCQy5cvU1dXJ0J9BH+HEK0jjCzL1NXVceLECeLj4y0qM8LAwAB2dnY4OTmJUB/B3yFE64jydkft4sWL+Pn5MTU1ZVEfrk6no6mpiStXrhASEsLk5KQwzAsAIVpHlomJCezs7LCysqK/v/9Y7RTqi0ajoaKigosXL5KcnCxCfQSAEK0jiUKhICgoiHPnzlFfX2+WITqHxe7uLrdu3eLcuXPk5+ezublp6ioJTIwQrSPG/v4+WVlZfP3115SVlZl1iM5hsby8THh4OOfPn+fZs2fCMG/hCNE6Qmi1WsrKyvjqq6/IyspifX1d2HH+i4mJCXx8fHB0dKS9vf1Y+qkJ9EOI1hFBlmUaGxv585//TEhICIuLi0Kw/oGenh6srKzeRQSI92OZCNE6IkxMTHD58mXs7OyOXYjOYaHT6aiqquLcuXNERkYyNzcnhMsCEaJ1BFhbW8PLy4srV67Q0dEhshz8DHt7e9y7d49z586RnZ0tQn0sECFaJmZnZ4ekpCROnDhBTU2NRe8U6svW1hYpKSl8//33lJeXi80KC0OIlgnRaDTcvXuXEydOkJOTYxEhOofF/Pw8gYGBWFlZUV9fL3YULQghWibibW6sr7/+mqioKFZWVkxdJbPibcSAvb09zs7OItTHghCidQAkSUKr1f7d730M5m8/uAsXLuDv729xITqHhU6no7m5mStXrhAUFPReoT6yLKPT6f5bmwoD/9FFiNYvoNFomJ6eprm5mcePH5Obm0tWVta7371796iurub169esr6/rJT4zMzNcu3aNy5cvW2yIzmHx1rft3HfnSElJYXV1Va9r5ufnaW9vp7Kykvz8/HftmZ2dTUFBAU+ePOFVxyuWlpZE+xwxhGj9CLIss7KyQmNjI2lpaQQGBhIQEEBERAQJCQmkpKSQkpJCYmIiUVFRhIeH4+vrS0REBAUFBfT19aFUKn90tN7c3CQoKIgzZ85QV1d3rHNjGYudnR2ysrL461//SmFh4Y/aBiVJYn19nba2Nm7dukVISAgBAQGEhYURFxdHcnIyKSkpJCcnExsbS2hoKP7+/ty4cYM7d+7Q0dHB1taWmIEdAYRo/QM7Ozs8e/aM69evv/ulpqby9OlThoeH2dzcRKPRoNVq2d/fZ25ujtevX1NUVER0dDTBwcH4+vqSmprK0NDQ3xmIdTodWVlZfP7555SUlIgEd4fI0tISYWFhXLx4kZqamnfvXZZllEolzc3NxMTEEBAQQFBQEImJiZSVldHT08Pa2hpqtfpdmy4vL9PV1UVJSQmxsbEEBQUREBBAfHw8rW2tYrfSxAjR+i/eHteempqKo6Mj3t7ePHv2jOXlZb1CRmRZZm9vj6mpKXJycnB3d8fb25uSkhIUCgVarZbq6mr++Mc/kpaWxsbGhhi1D5G37efp6YmLiwuvX79Go9EwOTn5rj18fX0pLS1ldnaW/f39X3z/siyjUqmYmZmh+GExnl6eeHh6UFhYyOzsrGg/EyFEix9mQJ2dnXh4eODq6kpJSQkrKyvvbRyXJInh4WGSk5Oxs7MjOTmZp0+fcurUKfz9/VlYWBAd3kB0dnZiY2ODt7c3paWlREZG4uLiQm5uLlNTU+9tn9LpdExMTJCXl4erqytxcXEMDg4KR2ATYPGi9Tbmz9HRkYCAAPr7+w8tGFelUlFRUYGVlRV/+tOfuHDhAsPDw2Kn0IBotVrKy8s5ffo0J0+exN/fn5aWFvb29g7l/iqVihcvXuDp6cn169fp7OwU7WlkLFq0ZFmmu7uby5cvExERwcLCwqF3QJ1OR2NjIydPnsTJyUnEyxkYWZZpa2vj0qVLODs709PTc+gZIbRaLR0dHXh4eBAUFMTQ0JAQLiNi0aI1Pz+PnZ0dAQEBLC0tGUxMZFmmtraWCxcucPv2bZHIzoDMz88TERGBr68v3d3dBnNXkCTpnUkhLi6OxcVFg5Qj+O9YrGipVCoiIyO5dOmSUZw7dTodZWVlfPvtt7x69UrkgzIAGo2GO3fu4OrqSkNDg8HtTZIkUV1djbOzM0VFRYe2BBX8PBYrWp2dnXz++efU1tYazZiqVqu5ceMGN27cEMb4Q0aWZd68eYODgwO5ublGc0vY2dkhMzMTb29vuru7jVKmpWORoqXVanF1dSUyMtLoQcqjo6PvDl0VGR0Oj52dHSIjI/H392d4eNioZQ8PD+Pv709WVpZwFjYCFilaAwMD/O53vzNJCI0kSYSHhxMYGChOlzlEent7cXd358GDB0bP+KDRaMjJycHb25ve3l6jlm2JWJxoSZJEfHw8zs7OKBQKk9Shr6+Pr776ip6eHrHrdAjIskxOTg6hoaEMDQ2ZpA49PT14e3uTl5cn7JUGxuJES6VS8Ze//MWkp7rs7Oxw5swZHj16JEJCDoGdnR38/f1JSUkxWU4ypVJJbGwsMTExIjzLwFicaG1sbPDxxx+/l7+Uenue6qbXbCpVfIgJXZIkQkJCCAoKYnl5+QPuJAAYHx/Hw8ODBw8eHHiWo95e5k3nAEMTa+g+cF/k7t27REVFMTc392E3EvwsFidaQ0NDfPPNN6ytrR3wSomJ+jt8+pU99cMLaKQP6+Hl5eVYWVkxOTn5QfcRQHt7O8HBwdTX1x/sQlli8vUzfFz8SL/7gh3Nhy3VGxoaiI+Pp7Oz84PuI/h5LE60Hj9+jJub24EdPKW9FfLDQvniN7/DO/slqzsftrTs7+/n4sWL4iisQ+DZs2ckJCTQ19d3oOt06g1eVuRjd/or/ENTGVjc/qB69Pf3k5CQQE1NzQfdR/DzWJxopaWlERoays7OzoGuWxloIjn9GaVxHvzxu2AGZtaQZFAr12h+8oTq+h4299R6LxvX19f59ttv6evrE8b4D+Thw4dkZGQwNTV1gKtkNiZeUVlRwu24G3h4h3K/fhitDJJGyWhvOzX1LYwtbqLvpHp8YpyY2BgePXr0Xs8h0A+LE62kpCRiY2MPaCzd50laMFEZ+Ty8Hcqv/uVjHjQOsKeR2Foep7IglxDvKBqHF9nX0zCyt7fH6dOnxQ7iIVBUVMSdO3dYWFjQ+xpZs8uLwmwiwqJJSYnh7NlLeCc9ZGFXw/7WKm8ayklOvkl1Qzf7enrFTE5OEhERwb17997zSQT6YHGilZeXR1BQENvb+i8FVEvdhIaEkp13l4fFd3E5cwLruHIWNlUod7bY39+hPCyQ4leTbKv1E6D5+XnOnTvHwMCAWB5+IGVlZaSnpzM+Pq73NduLoxRm3yE+MZv79/Pwt7vMNY8IGgaWUCt3WJrsoaSwiLr6N3oPRKOjo8TGxlJWVva+jyLQA4sTraamJq5evar3IZ9alYLKm3HEl75hbWcfnU7LwNNU/uMrB0pah1GqdUjqbV4U3uP11KreHby9vZ2rV68yNjYmROsDqa+vJzw8nPb2dr3+X7u/TWtFEcXFFYwtbqHTqhmrL8Td1onYO9Ws7apYHHvN7awMHtW06j0QvXnzhpSUFJqamj7kcQS/gMWJ1tTUFJ999pmeR3ZJKGZeE+ZxnYKq12ztaQCJifYSLl28RFh6ObOrCmYmRml9M8SaYhdJTwG6desWLi4uYnv8EOjq7sLL24unT5/qMQDIKBZGuXczkYy8UiZWd0DSMt3zkhvenvhFZNEzscDu1irPSnIoraxkRamfG0VlZSWJiYmMjo5++EMJfhKLE63t7W1+/4ff65kDSWZrcYS21mY6u8fY29cAMouTfbS2NNHY2M1ITysZKSlk596ldWgBlR7b5hqNBjs7OxITE8Wx7ofA4uIi7h7u5OTm6BHPKbO1tkjvm1e09gyzuLkHspal2UletbbQ0tZBb0crDc9reFxWQffgMEo92lSn05Genk5kZOR7uNMIDoLFiZZGo8HGxoZbt24dSiqR1fEuigvzuX07l7axZfa1v9zBl5eXOXnyJC9evBAnIx8CarWa8PBw4uLiDsFZV2J9qp/nZWXUtfWxodRvR3hxcZGgoCCSkpJEILyBsTjRAih+WMzp06dNlh6moqKCy5cvMzExYfSyjytPnjzB19eX1tZWo5ctSRI1NTV4e3tTXV0tbJQGxiJFa3V1lS+//JLq6mqjz3S2trawsrIiOztbZDA9RObn5/Hw8CAlNcXogfAKhYKYmBhCQ0NF5g4jYJGiBZCVlYWtrS3T09NG9ZN6+vQpFy5c4PXr1yIbwCGi1Wq5d+/eu6ylxmpTnU5HbW0tLi4ulJSUiFmWEbBY0VpcXOTs2bOkpaUZLSp/amoKGxsb8vLyTJaN4DiztLREUFAQ0dHRzM7NGqXM6elpgoKCCAsLY35+3ihlWjoWK1qyLFNZWcnZs2d5/vy5wY2na2trhISE4ODgwMTEhPCCNxCNjY24urmSm5tr8J3Z9fV10tPT8fDwoLW1VbSpkbBY0YIfdhLT09M5f/48dXV1BhOuzc1NkpKSuHTpEk1NTWLH0ICoVCru37+Po6Mj9+/fN5hwbW5ukpeXh42NDSUlJWLH0IhYtGjBD0bUf/mXf+HUqVNUVVUdeudbXFwkIyODf/qnfyI5OVksC43A/Pw81tbW/OlPf6KwsPDQ/aZWV1fJzc3lP/7jP3B1dWV1dfVQ7y/4eSxetHp7e/nXf/1Xrly5wtWrVyksLGRxcfGDp/oajYa+vj7Cw8OxsbHho48+4vr166KDG4Genh6uXLnCqVOncHR0JDMzk7GxsQ8+dUmtVjMyMkJ6ejo2Njb84Q9/wNnZmZGRkUOquUAfLFq0NBoN/v7+nD9/npGREbKzs3FyciI0NJTq6mo2NzcPLF4ajYbZ2VkKCgrw8PDAw8OD+vp6iouL+eyzz2hpaTHakWWWiFqtJiUlBTs7O6qrq3n06NG7I+zLy8tZWFg48K6tVqtlfn6ex48fExAQgJeXF+Xl5Tx+/BhbW1tyc3PFkt+IWLRoTU5O8tvf/vadTUKj0dDW1oavny9OTk7ExsZSXl7O8PAwe3t7P7mdLcsyGxsbdHZ2UlBQQHh4OHb2P4TpTE5OotPpUCgUnDlzhhs3bojZlgEZHx/H2tqa2NhYFAoFarWazs5OIiMjcXFxITIykuLiYnp7e9ne3v7ZNt3c3KS7u5uioiIiIyPx8PAgJiaGrq4uNBoNGxsbBAcH4+XlxczMjJGf1HKxWNHS6XRERUfxl7/8hcXFxb/rvEtLS5SXlxMUHISHhweBgYEkJydTUFBAeXk5tbW1tLS08OzZMx49ekR2djZxcXF4e3vj6elJYlIibW1tfxcmJEkS9+/f59NPPzXoce2WjCzL5Ofnc+3aNerq6v5ulry+vk51dTUxMTF4eXkREBBAYmIi+fn5PH78mNraWpqamnj+/DkPHz4kJyeHhIQE/P398fDwIDY2lpcvX7KxsfGur8iyzJMnT7C2tqa4uFj43RkJixWtubk5/u3f/o38/PyfPGBTqVTS0tJCRkYG169fJzg4mISEBGJjY0lOTiY+Pp7IyEh8fX0JCwujoKCAoaGhn1wqbG1tcerUKTKzMoVB3gDMz8/j5OREdHT0jxrfZVlGqVTypusNd3LuEBISQnBwMDExMSQmJpKQkEBCQgKRkZEEBAQQGhZKXl4e3d3d7O7u/uisbHFxEU9PT9zd3UXGDiNhsaJ169YtPv30U8bHx3/RbqXT6djd3UWhULC6usrQ0BA9PT1MT0+zsrLC5uYmKpVKL2/o23du880339Db2ytmW4eIVqulsLCQixcvUllZqVeb7u3toVAoWFlZYWxsjJ6eHiYmJlhdXUWhULC3t/eL99FqtRQVFfH9999TXlEuPOKNgEWKlkKh4NPPPuXmzZuHkunhIMzMzPDJJ5+Qk5Nz4Dz1gp9maWkJB0cHfH19jW5fmp6e/sGMEBQo0tIYAYsTLVmWKS4u5rf/+VtGx0aN7sUsSRKRkZF89913jI6OipH5EJBlmdLSUi5evEhZWZnRZ7BarZaCggKsrKyoqakRnvEGxuJEa2dnhy+//JLw8HCTzXTGxsb46KOPuHv3rjiN+BBQKBS4ubnh4+vD9PS0SeowMjKCo6Mj4eHhBzp/QHBwLE60nj59yr//+7+b1Ka0v79PQEAAly5dYmJiQsy2PpD6+nquXLlCYWGhycJp1Go1WVlZ2NnZ0dbWJtrUgFiUaO3u7vLNN9/g6+tr8tGwv7+fTz75hKpnhx86ZEmoVCrCwsLw9vZmeHjYpHXp7+/H0dGRmJgYk/ev44xFiVZzczO/+tWvaGpqMrlPjSRJeHl54e3tzezsrBiZ3wNZlmlvb+fChQtHwit9d3eXxMRErl27Rmdnp0nrcpyxGNHSarU4Ojri4OBg9MyWP0VbWxuffPIJNTU1Yrb1HiiVSkJDQ7GxsaGzs9Pkwv9WRG1sbLh586bJRfS4YjGi1dXVxa9//Wvq6+tNPst6y+7uLtY21vj7+4s0ve9BV1cXFy9eJDU19cgsx3Z2doiOjsbe3p7+/n5TV+dYYhGipdVq8fPz47vvvmN5ednkI/LfUl1TzSeffEJDQ4MIpD4AarWapKQkbG1t9T6k1RjIskx9fT1Xr14lMzNTzLYMgEWI1sTEBL/97W8pKys7cp3obSB1UFDQIRx/ZTmMjY1hZWVFQkLCkVnuv2V9fZ2wsDA8PDyYnJw0dXWOHcdetHQ6HZGRkZz44sSR9FaWZZkHDx7whz/8gc7OThHaoweyLJObl4udnZ1RD7E4CM+fP8fW1pbCwkIxgz5kjr1ozc7O8q//+q/k5eX9ZGC0qdna2uLMmTOk3Uw7crOGo8jc3BwODg7Ex8ezvr5u6ur8KMvLy/j5+eHm5sbsrHEO2bAUjr1oZWVl8Yc//IHp6ekjZcv6RwoLCzl9+jRv3rwRs62fQavVcvfuXS5cuEBVVdWRnGXBDzP8RyWP+P7K95SWlh7pvmduHGvRWllZ4bPPPiMrK+vIzrLeMjc3x8mTJ8nOzhZpa36GxcVFbG1t8ff3P/KpYGZnZ/Hx8cHf31/YKw+RYytasixz//59/vM//1Ov9DOmRpZl4uPj+fbctwwPD4uR+Ud4Gxh97tw5ysvLj3ybvk2Xc+XKFb3S5Qj049iK1s7ODl99/RWRkZFmE5Q8OjrKx7//mPz8fJG25kdYX1/Hzc0Nf39/kwVGH5TR0VFcXFwIDg5mc3PT1NU5Fhxb0Xr27Bm/+c1vGBkZMZsRTq1WExoayoULFxgZGRGzrX+grk9qk68AAB5wSURBVK6OK1euUFRUZDYRBFqtlvz8fGxsbKivrxdteggcS9Ha2dnh3LlzeHt7m92MZXBwkE8//ZTy8vIjb4czJnt7e4SEhODn58fY2Jipq3MghoaGcHR0JDQ09Mh47pszx1K0mpub+ed//meam5uPTMiOvkiSREBAAK6urkxNTYmRmR9sWW1tbZw/f578/Pwj5yD8SyiVSlJSUrC2tubVq1emro7Zc+xES6PRcO3aNezt7c12F66zs5Pf//73VD6tNJtlkCHZ3d0lJCQEOzs7urq6zFLIOzo6uHbtGsnJyaJNP5BjJ1q9vb38r//zf9HS0mK2/k4qlQo7ezs8vTyZn583dXVMTnd3NxcvXiQ9Pd1sl1dKpZKEhARsbGzo6ekxdXXMmmMlWm8Do8+fP8/a2ppZjshvefHiBR///mNqa2vNbjl0mOzv7xMfH4+9vT2dr803R5UsyzQ2NnL16lXS0tIsuk0/lGMlWpOTk/zmN7+hqqrK7GxZ/8jm5iZ//etfCQgIYGFhwdTVMRkjIyNcunSJ5JRks13uv0WhUBAdHY2zszOjo6Omro7ZcmxES6vVEhUVxcmTJ49sPNpBkGWZkpISPvvsM9ra2sx2qfuh3Lp1CxsbG5qamszGdeXnqKurw8bWhry8PBFI/Z4cG9GanZ3l17/+Nbm5ucfG0Lmzs8P5C+dJTk4+FkJ8UBYWFrCxsSE+Pp6NjQ1TV+dQWFlZITg4GBcXF6ampkxdHbPk2IhWeno6n332GTMzM2Zty/pHioqKOH36NB0dHRY129JqteTl5XHp0qVjdZagJElUVFRw5coViouLj81zGZNjIVrr6+t89NFH3Llz59gZOBcWFjh16hTp6ekWlbbmbWB0UFDQkQ+MPigLCwsEBATg7e3N4uKiqatjdpi9aL1Noveb3/zGLAKjD4osyyQnJ/PNN9/Q19d37J7vx/jbE6MrKyuP3QxTq9VSVFTE5cuXKSsrs4g2PUzMXrSUSiUnT54kIiKCvb09U1fHIExOTvKnT/9EVnaWRQTdbmxs4OzsTEBAgNkERh+U8fFxPDw8uB54/djY64yF2YmWVqtlZmaG7u5uXta/JC8vj//5f/xPbt26RXt7OzMzM8ciZk+WZba3txkdHaWlpYUvv/ySTz/7lPz8fJqbm+nv72dtbe1YzEI0Gg2Li4v09vbS2NhIZmYmH3/8Md7e3jQ1NTE5Ocnu7u6xsFUqlUomJiZob2/Hzc2NTz/9lMzMTBobG+nr62NpaUnsKv4CZiFaKpWKsbExqqqquHPnDuHh4QQEBODp5YmtrS0nT57E2dkZTy9PoqOjyc7OpqysjIGBAXZ2dsyms0uSxNraGp2dnRQXF5Oenv4uSPjixYucOnUKJycnfH19uX79OomJiRQUFNDY2Mjc3JxZdXaVSsXk5CTPnz8nNzeX2NhYAgMD8fX15dq1a5w+cxprG2t8fHyIiIggMzOTkpISurq6UCgUZrOkkiQJhUJBT08Pj8sek5mZSWhoKN7e3tja2nL27FmsrKzw9vYmKCiIuLg4cnNzqa2tZWpq6lgMwIfNkRYttVrNwMAAWVlZhIaGcv36dby8vIiPj6ewsJDnz5/T0dFBZ2cntbW13Lt3j5SUFPz9/fH39ycwMJDUtFRevXqFUqk8suIlyzLr6+tUVFQQHR1NSEgIPj4+hISEcPPmTUpKSmhqaqKjo4P29naqqqq4ffs2YWFh+Pn5ERgYSEREBI8ePWJmZuZIO9aq1WoGBwe5e/cu4eHh+Pv74+vrS3R0NHfv3qW2tpb29nY6Ojqoq6ujuLiYtLQ0goOD8ff353rgdRISE6h7Wcfa2tqRFS9ZllEoFDQ0NJCSkkJISAi+fr4EBgaSkpJCUVERL1++pLOzk7a2Nqqrq8nLyyM6OhpfP1/8/P0IDw/n7t27DA8PH7sNpg/hyIrWysoK9+7dw9/fHzs7O9LS0hgeHmZ3d/dnl0SSJLG3t8f09DS3b9/G0ckRd3d3bt26xezs7JHr5FqtltevX5OUlISVtRVubm6Ul5ezuLiISqX6yfrKsoxarWZra4vGxkbCwsJwdnYmPDycuro6tra2jpxIr6ysUF5ezo0bN3BxcSE+Pp7Ozk42NzfRarU/WV9JklCpVMzNzXHv/j3c3d1xdnEmPT2dgYGBI/dB63Q6BgcHycjIwNnZGXd3d4qKipiammJvb+9n21Sj0bC5uUl7eztxcXG4uLgQFBREeXk5KysrRn6So8mRFK3R0VHCw8O5cuUK6enpTE5OvrfYzM3NkZuby/fff09ISAjd3d1HZiaiVCqpqqrC1dUVV1dXnj59+t6zh729PV69ekVISAj29vbcvXuXxcXFIyHSkiQxPj5Oamoq9g72pKam0t/f/15LH1mWWVlZ4eHDh7i4uODn50ddXd2RCaTe3d2lubmZwKBAHJ0cKSwsZH5+/r3btKen513sZXp6OhMTE0eiTU3JkRItSZLo6OjAzc0NBwcHGhoaDsXQLEkSnZ2deHl54ezsTGtrq8ntP0qlknv37mFra0tsbCwzMzOH0hkVCgU5OTnvDjI9rPu+L5Ik0dvbS3BwME5OTjx58uRQYgglSaK7u/vdDLOystLkCR+3t7d58uQJbm5uhIaG0tPTcyj9d3Nzk4qKClxdXQkNDaW7u/tYbMC8L0dKtAYHB/nrX/+Km5sbCwsLh768WVlZ4fr161y7ds2kwrW/v8/9+/e5fPky9+7dQ6FQHOqzajQaysvLuXLlCikpKQZ5l/ogyzKDg4P4+vri5ubGq1evDnUp99YWmJqaipOTE0+fPjWZcKlUKqqqqnBxcSE1NZW5ublDfedarZb29nZcXV3x9/dneHj40O5tbhwZ0VpdXcXR0RE7OzuWl5cN9pG9FS5bW1vGxsaMPgvR6XTU1NTw17/+laKiIoMta3Q6HbW1tVy9epX8/HyT+AItLCxw48YNXF1dDXqe4+rqKomJiTg6OlJfX290G5dOp6OlpQV3d3dSUlIMdlyYVqulra0NNzc3oqOjLTb7x5EQLa1WS3JyMufOnTPKoapLS0tcs7vGjRs32NjYMOosZGRkhMuXL3Pz5k2Dh+VIksS9e/ewsrbi+fPnRnW+VSqV3Lp1CwdHBxobGw1uR1xaWiIkJAR/f3+GhoaM1qayLDM6OkpQUBChoaFMTk4atDyNRkNdXR1OTk7k5OQcm+QAB+FIiFZHRwe///3v6ezsNNrMp7u7mz/+8Y9UVVUZbWTWaDSEhobi4+PD7OysUT6s3d1dIiIi8PLyYmxszGgfc3t7Ow4ODhQXFxtlySbLMj09Pbi5uXH7zm2j5d7a3d3l5s2buLm58fr1a6O8X5VKxb1793Bzc6Ozs/PI7RIbGpOL1t7eHleuXCEoKMioNiadTkdKSgqXL1826HL0b3n16hWnT5+mvb3dqDuYY2NjXLlyhcePH6NUKg1e3t7eHmFhYcTHxzM7O2vw8t7ydmbp6elJS0uLUQbA169f4+npSW5urlEdQaenpwkLCyMiIsLskyMeFJOLVmdnJx999BETExNGHzFWVlb47LPPePbsmcFnWyqVChcXF8LCwozubyNJEhkZGfj6+hrlPMXW1lZsbW2prq42unvJ7OzsO2O4od0gVCoV6enpBAUFGXxZ+I9otVoeP36Mu7s7bW1tRi3b1JhctLy9vQkLCzPJFq4kScTFxeHo6Mja2ppBy5qcnOTklydpaWkxiZ/Y6Ogo586dM7hAv10CR0REmCTYWZZlbt++TUhICENDQwYta2RkBF9fX7Kyskzi4DoxMUFoaCgpKSkW5QJhUtHa2dnhV7/+lUnX5YODg3z88ceMjo4adDnx4MED3NzcTHa6jiRJeHh4kJeXZ9ANgLW1NRwcHCgpKTGZp3pfXx/e3t6Ul5cbrF/JskxZWRn+/v60traapP/u7e2RkZGBu7u7wXYsjyImFa2uri5+9atfvdd2vE6tQqnW8qFdRafT8cXJL2hrazPYDEiWZa5du0Zubu57LFlk1Ko9NFrdBz/ro0ePiIyMNOhS5s2bN3h7e9Pa2nrga3UaNWq1Bp30YU+6sbGBu7s7aWlpBtsx1Wg0pKalEhMTc/BU2LKEWq1mX/Nh/U2SJJ48eYKLiwuNTY0fdC9zwqSiVVRUxHfffXdwsZAl+upLyKvqZ0/z4bOjoKAgHj58aDBD6v7+PidOnODZs2cH3qKW1Zs8ffiAtv4plOoPWwL09/djbW3NmzdvPug+P0dBQQFRUVEHP21G1jDWWkfNi1bm1nY/qA4ajYbIqEjCw8MNlvV0b2+PmNgY0m6mHXhppt5epPHlS160DaD6wJGop6eHgOsB5OXnWcwuoklFKyEhgfj4+AMvyyTVMomOf+F/f3ad8dVdPrStioqKiIqKMpjhdnFxkRMnTrxXnveNsTasz/wZ+6giplZ3Pmi2NTs7y9mzZ2lubjZYB4+MjCQpKenAjo+anUVywj35y0VvyltG0H5g9W7dukVAQAD9/f0fdqOfYG1tjfj4ePLz8w/2LmUdM69r8bj8PTZ+6Yysf5if1dLSEklJSSQnJ1tMTKJJRcvHx4eSkpIDvmyJ+VcPiYsI49P//TFFrZNodP9/p5G1O/S/6ka5r//Ssba2FmdnZ4PZekZGRjhx4gSDg4MH7OBqmkrySYn04E9nfKntnkb9X0sn5cYcjS/raB+YYndfv5nq2toa3377LTU1NQZbCnt5eZGamnrAjQ2Zmb5msm4n8cWZK0TmVLKw8zfuL7LE/t4eqn01+q4cS0pK8Pf359WrVweqv75MTEwQGxtLaWnpgdpUq1yj/kkpPlevYnXNj3t1o+hkkNRKxoZ6ePKknKrqJkYn1tDnq1Aqldy+fZvIyMgjkwjA0JhMtGRZxsnJifr6+gM1uqTe4E5UGHVDU9x2PsvFiFIUe28bS2Z1+hU3bAKZXdvRu4M3NDTw3XffGWwHcWhoiC+++IKxsbEDXafeGODW7UJ6X7/A/uQ3xBbWs7yjAVlL+9NcfP2DyXvWycaufgbvnZ0dLl68SFlZmcGWwi4uLmRkZBxsANBu87yklJcNDdyK8sYxIJHGoeUfBh1Zy+J4Py0NjQxOLbKn1W+Ae/r0KV5eXjQ0NLzXc/wSY2NjJCYm8uTJkwNcJbM82cOTmmqePC0j1seHsPgHbO7r0Oxu0PKyktjoYAIDEyipHECnR/+VZZnCwkKCgoKOXIoeQ2FS0XJ3d+fp06cHEq31iSYu2ofwqPIZudHO/F8fXaF1SoFOBp1qg1eNJfh85cr0sv6iVVtbi62trcHi80ZGRvjiiy8OFuQqaeirysQvPI2ihw/x/+4EZxxj6ZtaRZLVNFXeJ6/gLq2D03rbujY2Nvjuu++oqqoymCOvu7s7N2/ePIBxWmZnspObkYlkZOaTH+vNmW9syHvShkons7s8zoM7acSk3KJlYJo9PdeNjx8/xtfX9702BPRhYmKChIQEysrK9O6/sm6P9tpSUpLieVBSRJDLNexcb9Axs4lOp0WjUaNcnaCjpZX2wRW9Vgr7+/vk5OQQFhZm8swlxsKky8Pw8HAyMjL0Xh7Kuj1e3ksiJimFjIwMMm7G8+3/8ytC7r1Cua9isL2JxtbnRJxyYnROobdoPXjwgNDQUIPZtGZnZzlx4gRdXV16P6tKMcOdtDSSUlJJz8zkZmIgf/7iApXNfexpJSSNktcv7pNZ2ci8Qj8v99nZWU6dOkVjY6PBbFrBwcEkJyeztLSk1/9Lml0an5SSmJRC8s0MMtOTsbp4nojM+0xtKOltKCUxPZ2kmwU0dg6xua/f+7tz5w4BAQH09fV9yOP8JEtLSyQkJHD//n0936XM9sIwZYW3iYhOJCMzk5hgb67Y+5BW1oVKJ4OsZaq3i/r6NmZ39RuIFhcXSUhIIDEx0WJ8tUwqWvn5+Vy7dk2/ly2rGWh5hNWpi7wcWEInyehUK8Rf+i2/PunIk+edFN0uorquBNdPztPQN49WT9UKCQkhLy/PYNvju7u7fP7557x48UKvKbxWucrTu0nY+6XwenwZrSSzt/wG25OfYOUTQ/PAHCqNxOZsL3frOpnf0G+3bWhoiAsXLhjMzgOQnZ1NbGwsExMTv/zPun0G2qpx8Q7iVmULGyodqBXkRXly5vw1bpY0UFBwi5JnlVTcSuJOcSWDq79suNbpdERFRREUFGSwU5yVSiVxcXFkZmbqMRDJ7CnmqMpJIvhGIrW9C0iyzMJgPV623/P1xSBevplEqdqhvf01Nc19qPUcUwYHBwkODubOnTti99AYtLa28tvf/lavGY4s7VH/KA1Xl1Be9C2gk2Q0u8vkJgVi7eDKrbuNdHV10dnxnLCLbrSPLOklWpIkcfbsWZqamgw2vZZlmQsXLnDv3j29gofVm9PkpsUSeCOdN+PLqCWZ7dnXJEf64ewdRmVTF30db2hpeElL/xTbKv3qXV1dTWBg4MHdEQ5Ac3Mz/gH+dHZ2/vI/a3ZprCwmNOQGhc/bWd7VwN4qT+9l4eHiRWL+E4ruF1JSXsaTggwePHvJ6MYvi9b29jbe3t4kJSUZbPasVqtJTEwkPj5ejzaV2V4c4tGdFCJismnrnUYnSyyOv+ZWYjAunmGU1nSj2Fqnr6+XnmH93DRkWaa2thYPDw9qamo+/KHMBJOK1vr6Ov/yf/8LAwMD+o0Ssvzf/k/+r7+9+7OsZKDuFbsqjV42gdnZWT7++GMGBwcNumWclZVFcHDwgTyXf+ydyLKMrFHwuqaaurZ+1nf29XL5kCSJoKAgsrOzDRqytLS0hL2DPRUVFXrvZv3kcwKKmVHqnlbx4G4ZXQPTKPWwaY2NjeHh4WHQY+clSaK4uJigoCB6enr0vEr+7231N31ap95lY22NzS393CD29/e5c+cOrq6uzMzM6F95M8ekoiXLMpe/v0xmlj5TbMOUn5OTw/fff2/wIObBwUFOnTpl0GR4P8fi4iLnzp2jvLzcoDmY9vf38fPzIzExUW+71s8iS6j3lCiVKrS6X+4jsizz8OHDd+cBGJKenh68vL3Iy8szibvBwsICkZGRFuXuAEcgYLqmpobPP/+c1dVVo5etUCg4c+YM94vuGzytyO7uLhcvXiQ5JdnoWURlWebBgwfY29vT09NjUNuHLMtUPKnA3sGexqZGow9Ga2tr+Pj4kJCQYPD3vLu7S3x8PCEhIUbPIvo2M62Xl5dFLQ3hCIjW5uYmX3zxBXfu3DHqaCFJEg8fPuTPf/6z0XKol5WV8dXXX/H6zWujzraWlpZwdHQkPz+fzc1Ng5e3ubmJr68vGRkZRh2MJEmiqqoKd3d3qmuqjfKO6+rq8PDwoLS01KguB8vLy0THROPn72eSAd+UmFy0ZFmmsrKSzz//3KiZNWdmZjh16hT5+flGS0OsUqm4ZneN+Ph4VldXjfKs+/v73L59G3t7e/r6+oz2fp8/f46LiwvV1dVGSwk8PT1NQEAAaWlpBk819JaNjQ2io6Px9vZmZGTEKGWq1WoqKytxc3OjqqrKYnYN32Jy0YIfGsHNzQ1vb2+jfMzb29uEh4djZ2fH4uKiURv91atXfPfdd5SUlLC7+2GBwb+EJEk0NjZy4cIFgx6i8WNsb28TGhqKv78/fX19Bp/1bG5ucvPmTVxcXIyaKkaW5XfH0x3Mqfb90Ol0dHV1vTtp3dTHppmCIyFaAOPj45w+fZqoqCiDpo/d2dkhJyeH06dP09XVZXSjuFarJT09nStXrvDixQuDzfJ0Oh1v3rzB0dGRqKgok5zcMjw8jLe3N1FRUYyNjRnsXW9vb/Pw4UMcHR2NMhj8I1qtlrKyMpycnHjw4IHB+q9Op2NgYIDAwEC8vLwM5jh71DkyoiXLMs3NzXzyySekpaUZxPaytbVFXl4e586do6yszGQnmWxvbxMVFYW9vT21tbWHnrf97eG09vb2+Pj4GDzB4c/Vo7m5GXt7e6KiohgfHz904dre3ubx48fvbHamOCrtbT1yc3PfCedh10OWZUZGRggMDMTBwYFXr15Z3LLwLUdGtOCHEevJkyd8/fXXpKWlMT4+figfmyzLzM7Okp6ezrfffktpaanJj15aX18nIiICOzs7Hj9+zNra2qE8q1KppKWlBUdHR1xdXenv7zdpeIdWq6WmpgZ7e3siIiLo7u4+lJ1aSZKYn5/n3r172NnZcefOHaPZsX6KtbU1MjMzsbW1JS8vj/n5+UN593t7e7x+/ZobN27g6OhIbW2txcQZ/hhHSrTgB4Gpr6/H2toaf39/KisrUSgU7/VBS5KEQqHgxYsXhIaGYmVlRVlZ2ZGJhl9fXyc5ORk7OzuSkpLo6elhd3f3vUZQtVrN+Pg4+fn5uLm5ERQUZLIZ1j+i0+lobGzEz88PPz8/SktLmZ2dfa8PT5Iktre3aWtrIyYmBicnJ/Lz8w/HJ+wQWFtbo6CgAGdnZ6KiomhqamJzc/O92kGj0TA7O0tJSQnu7u74+PjQ3t5+JNrUlBw50YIfhGtqaorAwECsrKxISEjg6dOnzM7O6tVgsiyzvLzM8+fP34mCj48Pw8PDR84Jb29vj/LycpycnPDz8+P27du0tbXpLdQqlYqBgQEeFD/gRugNbGxsKCgoYGVl5Uh17rdtmpCQgLOzM9HR0ZSXlzM+Pq73rHdtbY2mpiYyMzNxd3fH19eXxsZGox7dpQ9qtZqGhgY8vTxxcnIiPT2dhoYGlpeX9WqT/f19RkdHKS0tJSoq6t3pQlNTU0eqTU3FkRSttyiVSl68eIGzizNXr14lOjqah48e8vLlS3p7exkbG2N2dpa5uTnGx8fp7++nsbGRhw8fkpiYyLVr13B2dqaiogKFQnGkbQAzMzNkZmbi4OCAm5sb6enpPH78mJaWFoaGhpiammJ2dpaZmRnGx8fp7OykqqqKgoIC/P39sb1mS2xs7KEtvwzF7u4uTU1N3LhxAwcHB0JDQykoKOD58+d0dXUxOjrK9PQ0s7OzTE5OMjg4SFNTE+Xl5aSmpuLq6oqjoyMFBQXMz88f2Y9YkiQWFhYoLCzExcUFV1dXEhMTKSkpoaGhgb6+PiYnJ5mbm2N6eprR0VG6urqora3l7t27BIcEY21jTWhoKE1NTRa5S/hTHGnReotKpeL58+dERkbi6elJaGgocXFxJCYmvks1GxsbS3x8PBEREbi5uREcHMyTyidsbm4eabH6W97ORgoLC/Hz93t3vFpSUtK750xOTiYlJYXo6Gj8/f3x9vHm5s2b9PT0mNxOdxDe2t4SExPx8vIiKCjoXRu+bdekpCQSExMJCwvDy8uLwMBAHj16dKTF6sdYWFigtLSUkBsheHt7ExISQlxc3Lv2TExMJDExkbi4OIKCgvDx8SE+IZ6WlhajHK5rbpiFaL1Fq9WiVCqZmpqirq6O+/fvk5GRQXp6Onl5edTU1DAxMcH29rZZGyplWWZ/fx+FQkFPTw9VVVXk5OSQkZFBdnY2JSUltLW1sby8zN7enll9wP/I2zadm5ujqamJ+/fvk5WVRXp6OgUFBTx79ozBwUEUCgVqtdpsBqB/RJZlNBoNCoWCoaEhampquHv3Lunp6WRnZ1NcXExzczOzs7MolUqLyY31PpiVaAkEAoEQLYFAYFYI0RIIBGaFEC2BQGBWCNESCARmhRAtgUBgVgjREggEZoUQLYFAYFYI0RIIBGaFEC2BQGBWCNESCARmhRAtgUBgVgjREggEZoUQLYFAYFYI0RIIBGaFEC2BQGBWCNESCARmhRAtgUBgVgjREggEZoXZidbe+hDPGnrY0EjI8j5TnTW0jS2jlWQk9QKN9U0s7Kkx36zpPyDr9hhqa6BzYpFdjQ7d7gTNbZ0sKbaRZInFkVe0jM6iUB2tI9EOjsz+xigdb7qZWtxEkrXMj3XRNT7BmkqHVrnMmzfdDE2voJbMMz/8O2QVC5P99A0NsaHWod5dZnCoj76pVTSylrW5YXr7epjfMp8DSkyB2YnW2kgxdkF3GN3VIElbPE9xIqayhz2thGa7nZCAUF6t7aAz9/6tXuVhbCCp1a9ZUmpQLz0jPCaFN+PzaCUtrx8nEVnWyIRChXk/qsTmaDlJ6beofT2JVlbRWpFF9tNqhhT7qFa7yUi/zcOXvWxrzftJkdZpr7lLfvFDxnY07Cx18+BhPgUv+tnV7THUXEJe/h3aZjdNXdMjjdmJlka5zPDkIns6GWQtG3MjTK/tIMkysnaLyYkptjU6M/+QQZY0rMxMMLe+jVonI6nXmZqZY3tvHxmZ7dVZplc3UWnNfU4J2r1VZucX2NhWISOxtbbAwtoGSq2EpNlhfn6BFcUu5q5ZyBq2NpZYXFlhTyejU++wvLLE0sYuOllCubnK4tIiW/vmPns2LGYnWgKBwLIRoiUQCMwKIVoCgcCsEKIlEAjMCiFaAoHArPj/ALqwPgTcRcuLAAAAAElFTkSuQmCC" alt="" />
现在小明要把相同深度的节点的权值加在一起，他想知道哪个深度的节点 权值之和最大？如果有多个深度的权值和同为最大，请你输出其中最小的深度。 注：根的深度是 1。
【输入格式】
第一行包含一个整数 N。 第二行包含 N 个整数 A1, A2, ··· AN 。
【输出格式】
输出一个整数代表答案。
【样例输入】

7

1 6 5 4 3 2 1
【样例输出】

2
【评测用例规模与约定】

对于所有评测用例，1≤ N ≤100000，−100000≤ Ai ≤100000

题目描述：用数组模拟就可以了，不要被树吓到

#include<iostream>
#include<algorithm>
#include<cstdio>
using namespace std;
#define ll long long			//赛后重写的，不确保答案正确性，仅供参考
int a[110000];
ll b[20];
int main() {
	int n,k=1;
	cin >> n;
	for (int i = 1; i <= n; i++)
		scanf("%d", &a[i]);

	for (int i = 1; i <= n; i *= 2) {
		for (int j = i; j < i * 2; j++) {
			b[k] += a[j];
		}
		k++;
	}
	int maxx = b[k-1], ceng = k - 1;
	for (int i = k - 2; i > 0; i--) {
		if (b[i] >= maxx) {
			maxx = b[i];
			ceng = i;
		}
	}
	cout << ceng << "\n";
	return 0;
}

试题 H: 等差数列　　　　//需要特判公差为0的情况

【问题描述】
数学老师给小明出了一道等差数列求和的题目。但是粗心的小明忘记了一 部分的数列，只记得其中 N 个整数。 现在给出这 N 个整数，小明想知道包含这 N 个整数的最短的等差数列有 几项？
【输入格式】
输入的第一行包含一个整数 N。 第二行包含 N 个整数 A1,A2,··· ,AN。(注意 A1 ∼ AN 并不一定是按等差数 列中的顺序给出)
【输出格式】
输出一个整数表示答案。
【样例输入】

5

2 6 4 10 20
【样例输出】

10
【样例说明】

包含 2、6、4、10、20 的最短的等差数列是 2、4、6、8、10、12、14、16、 18、20。

【评测用例规模与约定】

对于所有评测用例，2≤ N ≤100000，0≤ Ai ≤10^9

题解：排序，求每两个数之间的差值，求最大公约数、

#include<iostream>
#include<algorithm>
#include<cstdio>
using namespace std;
#define ll long long			//赛后重写的，不确保答案正确性，仅供参考
int  gcd(int a, int b) {
	return b == 0 ? a : gcd(b, a%b);
}
int n, a[10010], b[10010], maxx = 0, minx = 9999999999;
int main() {
	cin >> n;
	for (int i = 0; i < n; i++) {
		scanf("%d", &a[i]);
		if (a[i] > maxx)maxx = a[i];
		if (a[i] < minx)minx = a[i];
	}
	if (maxx == minx) {				//特判一下公差为零的情况
		cout << n<<"\n";
	}
	else {
		sort(a, a + n);
		for (int i = 0; i < n - 1; i++) {
			b[i] = a[i + 1] - a[i];
		}
		int k = b[0];
		for (int i = 1; i < n - 1; i++)
			k = gcd(k, b[i]);
		cout << (maxx - minx) / k + 1 << "\n";
	}
	return 0;
}

试题 I: 后缀表达式　　　//这题写错了，-号可以放在最后，，，，，不要参考了百度百科后缀表达式

【问题描述】 给定 N 个加号、M 个减号以及 N + M + 1 个整数 A1,A2,··· ,AN+M+1，小 明想知道在所有由这 N 个加号、M 个减号以及 N + M +1 个整数凑出的合法的 后缀表达式中，结果最大的是哪一个？
请你输出这个最大的结果。 例如使用1 2 3 + -，则 “2 3 + 1 -” 这个后缀表达式结果是 4，是最大的。
【输入格式】
第一行包含两个整数 N 和 M。 第二行包含 N + M + 1 个整数 A1,A2,··· ,AN+M+1。
【输出格式】
输出一个整数，代表答案。
【样例输入】

1 1

1 2 3
【样例输出】

4
【评测用例规模与约定】

对于所有评测用例，0≤ N,M ≤100000，−10^9 ≤ Ai ≤10^9。

题解：排序，贪心

#include<iostream>
#include<algorithm>
#include<cstdio>
using namespace std;
#define ll long long			//赛后重写的，不确保答案正确性，仅供参考
int n, m;
int a[200010];
int main() {
	cin >> n >> m;
	for (int i = 0; i < n + m + 1; i++) {
		scanf("%d", &a[i]);
	}

	sort(a, a + n + m + 1);

	ll sum = a[n+m];
	for (int i = n + m-1; i >= 0; i--) {
		if (n > 0) {
			sum += a[i];
			n--;
		}
		else sum -= a[i];
	}
	cout << sum << "\n";
	return 0;
}

试题 J: 灵能传输

【题目背景】 在游戏《星际争霸 II》中，高阶圣堂武士作为星灵的重要 AOE 单位，在 游戏的中后期发挥着重要的作用，其技能”灵能风暴“可以消耗大量的灵能对 一片区域内的敌军造成毁灭性的伤害。经常用于对抗人类的生化部队和虫族的 刺蛇飞龙等低血量单位。
【问题描述】 你控制着 n 名高阶圣堂武士，方便起见标为 1,2,··· ,n。每名高阶圣堂武士 需要一定的灵能来战斗，每个人有一个灵能值 ai 表示其拥有的灵能的多少（ai 非负表示这名高阶圣堂武士比在最佳状态下多余了 ai 点灵能，ai 为负则表示这 名高阶圣堂武士还需要 −ai 点灵能才能到达最佳战斗状态）。现在系统赋予了 你的高阶圣堂武士一个能力，传递灵能，每次你可以选择一个 i ∈ [2,n−1]，若 ai ≥ 0 则其两旁的高阶圣堂武士，也就是 i−1、i + 1 这两名高阶圣堂武士会从 i 这名高阶圣堂武士这里各抽取 ai 点灵能；若 ai < 0 则其两旁的高阶圣堂武士， 也就是 i−1,i+1 这两名高阶圣堂武士会给 i 这名高阶圣堂武士 −ai 点灵能。形 式化来讲就是 ai−1+ = ai,ai+1+ = ai,ai−= 2ai。 灵能是非常高效的作战工具，同时也非常危险且不稳定，一位高阶圣堂 武士拥有的灵能过多或者过少都不好，定义一组高阶圣堂武士的不稳定度为 aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFwAAAArCAYAAAD1yO8hAAADnklEQVRoge2YzZHkKBCFcQIrMAIvsCF9wAc8wICOwAIZwJ0rVwzAhLeH3WSQCnX9aeitGV5EXSQVJB/Jy5QElqZK/HQAf5sW8MlawCdrAZ+sBXyyFvDJWsAnawGfrAV8shbwyVrAJ2sBn6wFfLIW8P+UUsK2bW+PU0qB9/70/kcBDyFAa40QArz3kFJeAgkAvPfQWr89TkoJQgjUWof3Pwp4KQVCCBARUkowxnybTc9oAR8ohAAhRMtqIQRSSpeMvYAPREQwxqDWihgjpJSnC3tW/yvgOWds2wbnXDvCMcabI+29hzEGMcabMbiYOOdgrUUIocED0CA652CMQSmlLYCIEELYebZzDkQ0nOsVfQc8xghrLZxzCCG0eEa6DLgxph1nnlxrDSEESikwxrQjfww8pQSlVIMVY4QQAkqp9kytFbVWbNsGIQScc4gxgohgrcXX19dugzjbf7elEBGIqCUAr/msWF9mKTxRCKHtrlIKWmtYa5FSQs4ZQghYa9v/cs6QUu5OAgfVP8eqtUIIASkljDGPhve2RsCttVBKNdgAWuL113pdAryHwJC4Y5BStmN9LGrAr03pxVl8ZgdKKQghkHN+JLxLdAR+FuNoPc65tuZLgPcWwAMx3D4LiWi3+xz08fhxlpwFxeP8JHCl1M7ygF8wnXO769bau8CZxUPAnXPNTlgjKFLKXZDGmJtOggM6K1CllJbhZ4Xpd6gHzjEee3xOlO8K9RlwXtNDwPnh3reOcHv/5gI4Asu1wDnXnutFRC0bevvq53nH27dtG25kD9x7fwOWTznDLKW0Ik9EbR1nwHnMu8DZq/tFjopj79/c1rHHs7gl5Oy11qKUgpwzSik3BVlKiZwziKiNwW3is/13SgnOOSilbiyBgRyBcyw551ZAudvie977XeJ95+HW2vvAOdv6rBhlAF/TWrdWja2IC01KafgcZ04PgjdGa33aEbwiY8xd4KUUSClbovGGHxsH4N8T2483As7Jt23ba2+aIwC1VqSUbnY257zrlUfPcZbfGy/n3F4+XtUjwPv5j3bWx8m22SfeH/VqD6BlCr+53vsdC9yjwB8R+3rO+a6Ht/ifmuGHxQt85/vJlcDZv0cvdX8EcP6c8I7OgI9s7Z5qradWeKaPAs4FiruaKy1llj4KOLeir3ywKqW0j2j80euqT7vP6KOA98XpWTHw/reA/wVawCdrAZ+sBXyyFvDJWsAnawGfrAV8sv4B8gO08xkBwUIAAAAASUVORK5CYII=" alt="" />，请你通过不限次数的传递灵能操作使得你控制的这一组高阶圣堂武 士的不稳定度最小。
【输入格式】
本题包含多组询问。输入的第一行包含一个正整数 T 表示询问组数。 接下来依次输入每一组询问。 每组询问的第一行包含一个正整数 n，表示高阶圣堂武士的数量。 接下来一行包含 n 个数 a1,a2,··· ,an。
试题 J: 灵能传输 15
第十届蓝桥杯大赛软件类省赛C/C++大学B组
【输出格式】
输出 T 行。每行一个整数依次表示每组询问的答案。
【样例输入】

3

3

5 -2 3

4

0 0 0 0

3

1 2 3
【样例输出】

3

0

3
【样例说明】
对于第一组询问： 对 2 号高阶圣堂武士进行传输操作后 a1 = 3，a2 = 2，a3 = 1。答案为 3。 对于第二组询问：
这一组高阶圣堂武士拥有的灵能都正好可以让他们达到最佳战斗状态。
【样例输入】

3

4

-1 -2 -3 7

4

2 3 4 -8

5

-1 -1 6 -1 -1
【样例输出】

5

7

4
【样例输入】 见文件trans3.in。
【样例输出】 见文件trans3.ans。
【数据规模与约定】

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" alt="" />

题解：蒟蒻博主不会