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  <title>Golden Pigeon&#39;s Blog</title>
  
  <subtitle>GP</subtitle>
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  <link href="http://yoursite.com/"/>
  <updated>2020-07-08T08:52:14.743Z</updated>
  <id>http://yoursite.com/</id>
  
  <author>
    <name>Golden Pigeon</name>
    
  </author>
  
  <generator uri="https://hexo.io/">Hexo</generator>
  
  <entry>
    <title>Learning OpenCV with CPP -- Base Data Type</title>
    <link href="http://yoursite.com/2020/07/07/Learing-OpenCV-with-CPP-Base-Data-Type/"/>
    <id>http://yoursite.com/2020/07/07/Learing-OpenCV-with-CPP-Base-Data-Type/</id>
    <published>2020-07-07T15:46:19.000Z</published>
    <updated>2020-07-08T08:52:14.743Z</updated>
    
    <content type="html"><![CDATA[<h1 id="OpenCV学习路线（1）——-基本数据类型"><a href="#OpenCV学习路线（1）——-基本数据类型" class="headerlink" title="OpenCV学习路线（1）—— 基本数据类型"></a>OpenCV学习路线（1）—— 基本数据类型</h1><h2 id="基本情况"><a href="#基本情况" class="headerlink" title="基本情况"></a>基本情况</h2><ul><li>基本容器多为固定容量，容量可于创建时指定</li><li>运算效率较高</li><li>OpenCV根据容器的不同容量定义了许多类型别名</li><li>在使用时多使用类型别名以提高开发速度与可读性</li></ul><h2 id="基础类型"><a href="#基础类型" class="headerlink" title="基础类型"></a>基础类型</h2><h3 id="固定矩阵类型cv-Matx"><a href="#固定矩阵类型cv-Matx" class="headerlink" title="固定矩阵类型cv::Matx"></a>固定矩阵类型<strong>cv::Matx</strong></h3><p><strong>Matx</strong>处于基本数据类型继承树的最顶端，其他基本容器多由它继承而来或使用它及它的派生类实现。<strong>Matx</strong>用于储存已知容量的小型数组。它的主要操作列表如下：</p><table><thead><tr><th>功能</th><th>示例</th></tr></thead><tbody><tr><td>默认构造</td><td>Matx&lt;4, 4, float&gt; mat44f; Matx34d mat34d;</td></tr><tr><td>拷贝</td><td>Matx22d mat22d(other);</td></tr><tr><td>值构造</td><td>Matx23d mat23d(x1, x2, x3, x4, x5, x6);</td></tr><tr><td>含相同元素的矩阵</td><td>m1.all(m2);</td></tr><tr><td>全一矩阵</td><td>Matx22d.ones();</td></tr><tr><td>全零矩阵</td><td>Matx22d.zeros();</td></tr><tr><td>单位阵</td><td>Matx33d.eye();</td></tr><tr><td>随机阵</td><td>Matx34d.randu(); //均匀分布 Matx34d.nrandn(); // 正态分布</td></tr><tr><td>成员访问</td><td>m(i); //针对一维数组 m(i, j); //针对二维数组</td></tr><tr><td>运算与比较</td><td>直接使用运算符号</td></tr><tr><td>点积</td><td>m1.dot(m2); m1.ddot(m2); //双精度</td></tr><tr><td>改变形状</td><td>mat19f = mat33f.reshape&lt;1, 9&gt;();</td></tr><tr><td>类型转换</td><td>mat33f = (Matx33f)mat33d;</td></tr><tr><td>在(i, j)处获取n * m的子矩阵</td><td>mat44f.get_minor&lt;n, m&gt;(i, j);</td></tr><tr><td>提取第i行/列</td><td>mat44f.row/col(i);</td></tr><tr><td>提取对角线</td><td>mat44f.diag();</td></tr><tr><td>转置</td><td>mat34f.t();</td></tr><tr><td>逆矩阵</td><td>mat33d.inv(method); //method为计算方法，默认为高斯法</td></tr><tr><td>元素逐一相乘</td><td>m1.mul(m2);</td></tr></tbody></table><p>类型别名命名形式为Matx<u>abc</u><br>其中 a, b为维度，c为数据类型（f-&gt;float; d-&gt;double）  </p><h3 id="固定向量类型cv-Vec"><a href="#固定向量类型cv-Vec" class="headerlink" title="固定向量类型cv::Vec"></a>固定向量类型<strong>cv::Vec</strong></h3><p><strong>Vec</strong>类继承自<strong>Matx</strong>类。准确来说，它继承自<strong>Matx&lt;_Tp, cn, 1&gt;</strong>，即一个一维数组。<strong>Vec</strong>支持使用下标访问元素，当然，像一维<strong>Matx</strong>一样通过括号访问也是可以的（见上节表格）。此外，三维<strong>Vec</strong>还支持向量的叉乘：<code>vec3d1.cross(vec3d2);</code>。</p><p><strong>Vec</strong>类型别名的命名格式为<code>Vec{2, 3, 4, 6}{b, f, w, I, s, d}</code>其中，s表示<code>short</code>而w表示<code>unsigned short</code>。</p><h3 id="点类型cv-Point"><a href="#点类型cv-Point" class="headerlink" title="点类型cv::Point"></a>点类型cv::Point</h3><p><strong>Point</strong>是OpenCV中最简单的数据类型，它是Point2i的类型别名。在使用时，通常使用类型别名进行操作，如<code>Point{2, 3}{i, f, d}</code>。</p><p><strong>Point</strong>类型可通过点操作符直接访问其成员。同时，它支持<code>dot</code>和<code>cross</code>操作。特别地，通过<code>p.inside(r)</code>可判断点p是否在矩形r内。</p><h3 id="cv-Scalar类型"><a href="#cv-Scalar类型" class="headerlink" title="cv::Scalar类型"></a>cv::Scalar类型</h3><p><strong>Scalar</strong>类型可以理解为是一个四维的点，但它实际上通过继承一个<strong>cv::Vec&lt; _Tp, 4 &gt;</strong>实现。它可以通过<code>mul(s2)</code>函数与另一个<strong>Scalar</strong>类型进行逐元素相乘的运算；通过<code>conj()</code>函数进行共轭运算；通过<code>isReal()</code>进行真值检验（即判断s1, s2, s3是否全部等于0）。</p><h3 id="cv-Size类型"><a href="#cv-Size类型" class="headerlink" title="cv::Size类型"></a>cv::Size类型</h3><p>Size类型类似于一个二维Point，且可用与Point相互转换。</p><p>未完待续。。。</p>]]></content>
    
    <summary type="html">
    
      
      
        &lt;h1 id=&quot;OpenCV学习路线（1）——-基本数据类型&quot;&gt;&lt;a href=&quot;#OpenCV学习路线（1）——-基本数据类型&quot; class=&quot;headerlink&quot; title=&quot;OpenCV学习路线（1）—— 基本数据类型&quot;&gt;&lt;/a&gt;OpenCV学习路线（1）—— 基本数据
      
    
    </summary>
    
    
    
      <category term="OpenCV" scheme="http://yoursite.com/tags/OpenCV/"/>
    
  </entry>
  
  <entry>
    <title>weekly_report_1(Jan. 6th ~ Jan. 12th)</title>
    <link href="http://yoursite.com/2020/01/13/weekly-report-1-Jan-6th-Jan-12th/"/>
    <id>http://yoursite.com/2020/01/13/weekly-report-1-Jan-6th-Jan-12th/</id>
    <published>2020-01-13T07:18:19.000Z</published>
    <updated>2020-01-13T09:10:09.920Z</updated>
    
    <content type="html"><![CDATA[<h1 id="2020年寒假第一周周报-Jan-6th-Jan-12th"><a href="#2020年寒假第一周周报-Jan-6th-Jan-12th" class="headerlink" title="2020年寒假第一周周报(Jan. 6th ~ Jan. 12th)"></a>2020年寒假第一周周报(Jan. 6th ~ Jan. 12th)</h1><h2 id="本周学习内容"><a href="#本周学习内容" class="headerlink" title="本周学习内容"></a>本周学习内容</h2><h3 id="线性代数"><a href="#线性代数" class="headerlink" title="线性代数"></a>线性代数</h3><hr><ol><li>矩阵的基本运算：<br> -加减：相同维度的矩阵对应元素加减<br> -标量积：矩阵的每个元素分别与标量相乘<br> -点乘：行向量和列向量相乘得到一个标量或者一个1*1矩阵，依此规律得到结果<br> -转置：A(ij)=A^T(ji)<br> -逆矩阵：A*A^(-1)=I<br> -单位矩阵：AI=IA=AI</li><li>矩阵的行列式<br> -行列式=0，则矩阵为奇异矩阵，不可逆，否则为非奇异矩阵，可逆。</li></ol><h3 id="机器学习"><a href="#机器学习" class="headerlink" title="机器学习"></a>机器学习</h3><hr><h4 id="线性回归"><a href="#线性回归" class="headerlink" title="线性回归"></a>线性回归</h4><hr><h5 id="假设函数-Hypothesis"><a href="#假设函数-Hypothesis" class="headerlink" title="假设函数(Hypothesis)"></a>假设函数(Hypothesis)</h5><hr><p><img src="data:image/png;base64,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" alt="假设函数"></p><h5 id="代价函数-Cost-Function"><a href="#代价函数-Cost-Function" class="headerlink" title="代价函数(Cost Function)"></a>代价函数(Cost Function)</h5><hr><p><img src="data:image/png;base64,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" alt="代价函数"></p><h5 id="梯度下降-Gradient-Descent"><a href="#梯度下降-Gradient-Descent" class="headerlink" title="梯度下降(Gradient Descent)"></a>梯度下降(Gradient Descent)</h5><hr><p><img src="data:image/png;base64,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" alt="更新参量"></p><p><img src="data:image/png;base64,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" alt="向量化"></p><h4 id="逻辑回归"><a href="#逻辑回归" class="headerlink" title="逻辑回归"></a>逻辑回归</h4><hr><h5 id="假设函数"><a href="#假设函数" class="headerlink" title="假设函数"></a>假设函数</h5><hr><p><img src="data:image/png;base64,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" alt="假设函数"></p><h5 id="代价函数"><a href="#代价函数" class="headerlink" title="代价函数"></a>代价函数</h5><hr><p><img src="data:image/png;base64,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" alt="代价函数"></p><h5 id="梯度下降"><a href="#梯度下降" class="headerlink" title="梯度下降"></a>梯度下降</h5><hr><p>同线性回归</p><h4 id="正则化"><a href="#正则化" class="headerlink" title="正则化"></a>正则化</h4><hr><p>在代价函数中加入惩罚项，防止高阶特征的参数过大导致过度拟合</p><h2 id="本周工作总结"><a href="#本周工作总结" class="headerlink" title="本周工作总结"></a>本周工作总结</h2><p>本周我主要完成了线性回归和爬虫程序的制作，通过一遍遍的尝试，我使我的程序在变快的同时也变得更加精确。这不仅磨炼了我的毅力，也使我获得了更多的经验。下周继续努力！</p><h2 id="下周学习安排"><a href="#下周学习安排" class="headerlink" title="下周学习安排"></a>下周学习安排</h2><ul><li>继续学习线性代数</li><li>完成神经网络基础的学习并完成相关程序的编写</li><li>每天学习英语</li></ul><hr><p>#END</p>]]></content>
    
    <summary type="html">
    
      
      
        &lt;h1 id=&quot;2020年寒假第一周周报-Jan-6th-Jan-12th&quot;&gt;&lt;a href=&quot;#2020年寒假第一周周报-Jan-6th-Jan-12th&quot; class=&quot;headerlink&quot; title=&quot;2020年寒假第一周周报(Jan. 6th ~ Jan. 12th)
      
    
    </summary>
    
    
    
  </entry>
  
  <entry>
    <title>Obtaining Data From the MOT Official Website by Python Module Urllib and Re</title>
    <link href="http://yoursite.com/2020/01/08/Obtaining-Data-From-the-MOT-Official-Website-by-Python-Module-Urllib-and-Re/"/>
    <id>http://yoursite.com/2020/01/08/Obtaining-Data-From-the-MOT-Official-Website-by-Python-Module-Urllib-and-Re/</id>
    <published>2020-01-08T03:47:18.000Z</published>
    <updated>2020-01-08T09:03:28.190Z</updated>
    
    <content type="html"><![CDATA[<h2 id="基于Python-Urllib库和Re库的爬虫应用"><a href="#基于Python-Urllib库和Re库的爬虫应用" class="headerlink" title="基于Python Urllib库和Re库的爬虫应用"></a>基于Python Urllib库和Re库的爬虫应用</h2><p>获取交通部官网2019年交通固定资产投资额等数据并将其存入Excel表格中</p><h3 id="分析所需数据的位置及其上下文特征"><a href="#分析所需数据的位置及其上下文特征" class="headerlink" title="分析所需数据的位置及其上下文特征"></a>分析所需数据的位置及其上下文特征</h3><p>进入<a href="http://www.mot.gov.cn/shuju/" target="_blank" rel="noopener">交通部官网数据网站</a>。<br>通过右键检查表格元素，可以发现，每一个表格都被封装在一个html文件中，他们的网址位于网页源代码的872~893行，而他们的标题则位于864~867行。<br>代码如下：</p><figure class="highlight html"><table><tr><td class="gutter"><pre><span class="line">1</span></pre></td><td class="code"><pre><span class="line">        <span class="tag">&lt;<span class="name">div</span> <span class="attr">class</span>=<span class="string">"fl w100 mod_spsj mod1_kshsj_sj mart15"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">2</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">ul</span> <span class="attr">id</span>=<span class="string">"myTabs"</span> <span class="attr">class</span>=<span class="string">"nav nav-tabs hidden-sm hidden-xs"</span> <span class="attr">role</span>=<span class="string">"tablist"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">3</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">li</span> <span class="attr">class</span>=<span class="string">"sj_w180625"</span>&gt;</span><span class="tag">&lt;<span class="name">b</span>&gt;</span>可视化数据<span class="tag">&lt;/<span class="name">b</span>&gt;</span><span class="tag">&lt;/<span class="name">li</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">4</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">li</span> <span class="attr">class</span>=<span class="string">"active"</span>&gt;</span><span class="tag">&lt;<span class="name">a</span> <span class="attr">href</span>=<span class="string">"#jtgdzctzwce"</span> <span class="attr">role</span>=<span class="string">"tab"</span> <span class="attr">data-toggle</span>=<span class="string">"tab"</span>&gt;</span>交通固定资产投资完成额<span class="tag">&lt;/<span class="name">a</span>&gt;</span><span class="tag">&lt;/<span class="name">li</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">5</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">li</span>&gt;</span><span class="tag">&lt;<span class="name">a</span> <span class="attr">href</span>=<span class="string">"#yyxkhysl"</span> <span class="attr">role</span>=<span class="string">"tab"</span> <span class="attr">data-toggle</span>=<span class="string">"tab"</span>&gt;</span>营业性客货运输量<span class="tag">&lt;/<span class="name">a</span>&gt;</span><span class="tag">&lt;/<span class="name">li</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">6</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">li</span>&gt;</span><span class="tag">&lt;<span class="name">a</span> <span class="attr">href</span>=<span class="string">"#cskyl"</span> <span class="attr">role</span>=<span class="string">"tab"</span> <span class="attr">data-toggle</span>=<span class="string">"tab"</span>&gt;</span>城市客运量<span class="tag">&lt;/<span class="name">a</span>&gt;</span><span class="tag">&lt;/<span class="name">li</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">7</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">li</span>&gt;</span><span class="tag">&lt;<span class="name">a</span> <span class="attr">href</span>=<span class="string">"#gkscl"</span> <span class="attr">role</span>=<span class="string">"tab"</span> <span class="attr">data-toggle</span>=<span class="string">"tab"</span>&gt;</span>港口生产量<span class="tag">&lt;/<span class="name">a</span>&gt;</span><span class="tag">&lt;/<span class="name">li</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">8</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">ul</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">9</span></pre></td><td class="code"><pre><span class="line">......</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">10</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">class</span>=<span class="string">"list-group tab-content mod1_kshsj1_sj"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">11</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">role</span>=<span class="string">"tabpanel"</span> <span class="attr">class</span>=<span class="string">"tab-pane active"</span> <span class="attr">id</span>=<span class="string">"jtgdzctzwce"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">12</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">class</span>=<span class="string">"fl w100 mod1_kshsj1_a_sj"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">13</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">IFRAME</span> <span class="attr">align</span>=<span class="string">"top"</span> <span class="attr">width</span>=<span class="string">"1110px"</span> <span class="attr">height</span>=<span class="string">"820px"</span> <span class="attr">frameborder</span>=<span class="string">"0"</span> <span class="attr">src</span>=<span class="string">"http://106.3.149.173/CatsCategory/listGLJCSJ5?tableName=cats_jtysybsjk_csky&amp;pubflag=1&amp;code=C13"</span> <span class="attr">scrolling</span>=<span class="string">"no"</span> &gt;</span><span class="tag">&lt;/<span class="name">IFRAME</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">14</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">15</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">16</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">role</span>=<span class="string">"tabpanel"</span> <span class="attr">class</span>=<span class="string">"tab-pane"</span> <span class="attr">id</span>=<span class="string">"yyxkhysl"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">17</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">class</span>=<span class="string">"fl w100 mod1_kshsj1_a_sj"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">18</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">IFRAME</span> <span class="attr">align</span>=<span class="string">"top"</span> <span class="attr">width</span>=<span class="string">"1110px"</span> <span class="attr">height</span>=<span class="string">"820px"</span> <span class="attr">frameborder</span>=<span class="string">"0"</span> <span class="attr">src</span>=<span class="string">"http://106.3.149.173/CatsCategory/listGLJCSJ5?tableName=cats_jtysybsjk_gksc&amp;pubflag=1&amp;code=C13"</span> <span class="attr">scrolling</span>=<span class="string">"no"</span> &gt;</span><span class="tag">&lt;/<span class="name">IFRAME</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">19</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">20</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">21</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">role</span>=<span class="string">"tabpanel"</span> <span class="attr">class</span>=<span class="string">"tab-pane"</span> <span class="attr">id</span>=<span class="string">"cskyl"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">22</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">class</span>=<span class="string">"fl w100 mod1_kshsj1_a_sj"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">23</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">IFRAME</span> <span class="attr">align</span>=<span class="string">"top"</span> <span class="attr">width</span>=<span class="string">"1110px"</span> <span class="attr">height</span>=<span class="string">"820px"</span> <span class="attr">frameborder</span>=<span class="string">"0"</span> <span class="attr">src</span>=<span class="string">"http://106.3.149.173/CatsCategory/listGLJCSJ5?tableName=cats_jtysybsjk_jtgdzctzwce&amp;pubflag=1&amp;code=C13"</span> <span class="attr">scrolling</span>=<span class="string">"no"</span> &gt;</span><span class="tag">&lt;/<span class="name">IFRAME</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">24</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">25</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">26</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">role</span>=<span class="string">"tabpanel"</span> <span class="attr">class</span>=<span class="string">"tab-pane"</span> <span class="attr">id</span>=<span class="string">"gkscl"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">27</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">div</span> <span class="attr">class</span>=<span class="string">"fl w100 mod1_kshsj1_a_sj"</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">28</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;<span class="name">IFRAME</span> <span class="attr">align</span>=<span class="string">"top"</span> <span class="attr">width</span>=<span class="string">"1110px"</span> <span class="attr">height</span>=<span class="string">"820px"</span> <span class="attr">frameborder</span>=<span class="string">"0"</span> <span class="attr">src</span>=<span class="string">"http://106.3.149.173/CatsCategory/listGLJCSJ5?tableName=cats_jtysybsjk_yyxkhysl&amp;pubflag=1&amp;code=C13"</span> <span class="attr">scrolling</span>=<span class="string">"no"</span> &gt;</span><span class="tag">&lt;/<span class="name">IFRAME</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">29</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">30</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">31</span></pre></td><td class="code"><pre><span class="line"><span class="tag">&lt;/<span class="name">div</span>&gt;</span></span></pre></td></tr></table></figure><p>可见，上述网址前都具有属性<code>class=&quot;fl w100 mod1_kshsj1_a_sj&quot;</code>故可以使用正则表达式<code>&lt;div class=&quot;fl w100 mod1_kshsj1_a_sj&quot;&gt;.*?src=&quot;(.*?)&quot;\s.*?&lt;/div&gt;</code>进行识别。<br>标题与此类似，不再赘述。  </p><p>进入每一个表格的源代码，发现每一格中的数据都被<code>&lt;td&gt;</code>和<code>&lt;/td&gt;</code>所包围，故可以使用正则表达式<code>&lt;td&gt;(.*?)&lt;/td&gt;</code>识别。表头与之类似。  </p><p>分析好了上下文，就可以进入编程环节了。  </p><h3 id="获取源代码"><a href="#获取源代码" class="headerlink" title="获取源代码"></a>获取源代码</h3><hr><p>使用<code>urllib</code>库中的<code>urllib.request.urlopen(url)</code>方法获取网页信息该方法接受一个字符串，返回一个<code>http.client.HTTPResponse</code>对象，该对象的read()方法返回一个字符串，即网页的源代码。通过<code>decode(&#39;utf-8&#39;)</code>方法使源代码按照UTF-8标准编码。</p><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span></pre></td><td class="code"><pre><span class="line">response = urllib.request.urlopen(url)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">2</span></pre></td><td class="code"><pre><span class="line">    src = response.read().decode(<span class="string">'utf-8'</span>)</span></pre></td></tr></table></figure><h3 id="匹配字符串"><a href="#匹配字符串" class="headerlink" title="匹配字符串"></a>匹配字符串</h3><hr><p>通过re库中的<code>re.compile()</code>方法将正则表达式编译，并在第二个参数位置加上<code>re.S</code>以确保查找不会被换行符所中断。使用<code>re.findall()</code>方法找出源代码中所有符合匹配模式的字符串，并将其以列表的形式储存。为方便编写代码，我编写了一个<code>get_data()</code>函数整合了这个过程</p><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">get_data</span><span class="params">(url, pattern)</span>:</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">2</span></pre></td><td class="code"><pre><span class="line">    response = urllib.request.urlopen(url)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">3</span></pre></td><td class="code"><pre><span class="line">    src = response.read().decode(<span class="string">'utf-8'</span>)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">4</span></pre></td><td class="code"><pre><span class="line">    results = re.findall(pattern, src)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">5</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">return</span> results</span></pre></td></tr></table></figure><h3 id="储存数据"><a href="#储存数据" class="headerlink" title="储存数据"></a>储存数据</h3><hr><p>通过<code>openpyxl</code>库储存数据。<br>我编写了<code>fill_sheet()</code>函数以实现这一过程。该函数接收文件对象，工作表名，要填写数据的区域左上角和右下角的坐标，以及数据来源和开始位置(默认为0)，填写表格后返回最后填写的一个数据的下一位置。</p><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">fill_sheet</span><span class="params">(workbook, sheetname, pos1, pos2, src_text, reading_pos=<span class="number">0</span>)</span>:</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">2</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">if</span> sheetname <span class="keyword">not</span> <span class="keyword">in</span> workbook:  <span class="comment"># 若工作表不存在，则创建一个</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">3</span></pre></td><td class="code"><pre><span class="line">        workbook.create_sheet(sheetname)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">4</span></pre></td><td class="code"><pre><span class="line">    sh = workbook[sheetname]</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">5</span></pre></td><td class="code"><pre><span class="line">    workbook.close() <span class="comment"># 关闭文件后才能写入</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">6</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">for</span> i <span class="keyword">in</span> range(pos1[<span class="number">0</span>], pos2[<span class="number">0</span>]+<span class="number">1</span>):</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">7</span></pre></td><td class="code"><pre><span class="line">        <span class="keyword">for</span> j <span class="keyword">in</span> range(pos1[<span class="number">1</span>], pos2[<span class="number">1</span>]+<span class="number">1</span>):</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">8</span></pre></td><td class="code"><pre><span class="line">            sh.cell(row=i, column=j, value=src_text[reading_pos])  <span class="comment"># 在相应单元格中写入数据</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">9</span></pre></td><td class="code"><pre><span class="line">            reading_pos += <span class="number">1</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">10</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">return</span> reading_pos</span></pre></td></tr></table></figure><h3 id="完整程序"><a href="#完整程序" class="headerlink" title="完整程序"></a>完整程序</h3><hr><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> urllib.request</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">2</span></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> re</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">3</span></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> openpyxl</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">4</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">5</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">6</span></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">get_data</span><span class="params">(url, pattern)</span>:</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">7</span></pre></td><td class="code"><pre><span class="line">    response = urllib.request.urlopen(url)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">8</span></pre></td><td class="code"><pre><span class="line">    src = response.read().decode(<span class="string">'utf-8'</span>)  <span class="comment"># 获取源代码</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">9</span></pre></td><td class="code"><pre><span class="line">    results = re.findall(pattern, src)  <span class="comment"># 找出所有匹配的结果</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">10</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">return</span> results</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">11</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">12</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">13</span></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">fill_sheet</span><span class="params">(workbook, sheetname, pos1, pos2, src_text, reading_pos=<span class="number">0</span>)</span>:</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">14</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">if</span> sheetname <span class="keyword">not</span> <span class="keyword">in</span> workbook:  <span class="comment"># 如果工作表不存在，则创建一个</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">15</span></pre></td><td class="code"><pre><span class="line">        workbook.create_sheet(sheetname)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">16</span></pre></td><td class="code"><pre><span class="line">    sh = workbook[sheetname]  <span class="comment"># 获取工作表对象</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">17</span></pre></td><td class="code"><pre><span class="line">    workbook.close()  <span class="comment"># 关闭文件后才能写入</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">18</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">for</span> i <span class="keyword">in</span> range(pos1[<span class="number">0</span>], pos2[<span class="number">0</span>]+<span class="number">1</span>):</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">19</span></pre></td><td class="code"><pre><span class="line">        <span class="keyword">for</span> j <span class="keyword">in</span> range(pos1[<span class="number">1</span>], pos2[<span class="number">1</span>]+<span class="number">1</span>):</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">20</span></pre></td><td class="code"><pre><span class="line">            sh.cell(row=i, column=j, value=src_text[reading_pos])  <span class="comment"># 在对应单元格中写入数据</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">21</span></pre></td><td class="code"><pre><span class="line">            reading_pos += <span class="number">1</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">22</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">return</span> reading_pos</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">23</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">24</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">25</span></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">main</span><span class="params">()</span>:</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">26</span></pre></td><td class="code"><pre><span class="line">    url = <span class="string">'http://www.mot.gov.cn/shuju/'</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">27</span></pre></td><td class="code"><pre><span class="line">    <span class="comment"># 编译各种所需的正则表达式</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">28</span></pre></td><td class="code"><pre><span class="line">    pattern_get_graph_sites = re.compile(<span class="string">r'&lt;div class="fl w100 mod1_kshsj1_a_sj"&gt;.*?src="(.*?)"\s.*?&lt;/div&gt;'</span>, re.S)  <span class="comment"># 图表网址</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">29</span></pre></td><td class="code"><pre><span class="line">    pattern_get_datas = re.compile(<span class="string">'&lt;td&gt;(.*?)&lt;/td&gt;'</span>, re.S)  <span class="comment"># 表中数据</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">30</span></pre></td><td class="code"><pre><span class="line">    pattern_get_graph_headers = re.compile(<span class="string">'&lt;th style="width:120px"&gt;(.*?)&lt;/th&gt;'</span>, re.S)  <span class="comment"># 表头</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">31</span></pre></td><td class="code"><pre><span class="line">    pattern_get_graph_names_block = re.compile(<span class="string">'&lt;div class="fl w100 mod_spsj mod1_kshsj_sj mart15"&gt;(.*?)&lt;/ul&gt;'</span>, re.S)  <span class="comment"># 标题代码区块</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">32</span></pre></td><td class="code"><pre><span class="line">    pattern_get_graph_names = re.compile(<span class="string">'&lt;a.*?&gt;(.*?)&lt;/a&gt;'</span>, re.S)  <span class="comment"># 图表标题</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">33</span></pre></td><td class="code"><pre><span class="line">    <span class="comment"># 匹配数据</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">34</span></pre></td><td class="code"><pre><span class="line">    graph_names_block = get_data(url, pattern_get_graph_names_block)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">35</span></pre></td><td class="code"><pre><span class="line">    graph_sites = get_data(url, pattern_get_graph_sites)</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">36</span></pre></td><td class="code"><pre><span class="line">    graph_names = re.findall(pattern_get_graph_names, graph_names_block[<span class="number">0</span>])</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">37</span></pre></td><td class="code"><pre><span class="line">    datas = []</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">38</span></pre></td><td class="code"><pre><span class="line">    graph_headers = []</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">39</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">for</span> graph_site <span class="keyword">in</span> graph_sites:</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">40</span></pre></td><td class="code"><pre><span class="line">        datas.append(get_data(graph_site, pattern_get_datas))</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">41</span></pre></td><td class="code"><pre><span class="line">        graph_headers.append(get_data(graph_site, pattern_get_graph_headers))</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">42</span></pre></td><td class="code"><pre><span class="line">    <span class="comment"># 储存数据</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">43</span></pre></td><td class="code"><pre><span class="line">    wb = openpyxl.Workbook()</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">44</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">for</span> i <span class="keyword">in</span> range(<span class="number">0</span>, len(graph_names)):</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">45</span></pre></td><td class="code"><pre><span class="line">        len_gh = len(graph_headers[i])</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">46</span></pre></td><td class="code"><pre><span class="line">        fill_sheet(wb, graph_names[i], (<span class="number">1</span>, <span class="number">1</span>), (<span class="number">1</span>, len_gh), graph_headers[i])</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">47</span></pre></td><td class="code"><pre><span class="line">        fill_sheet(wb, graph_names[i], (<span class="number">2</span>, <span class="number">1</span>), (int(len(datas[i])/len_gh+<span class="number">1</span>), len_gh), datas[i])</span></pre></td></tr><tr><td class="gutter"><pre><span class="line">48</span></pre></td><td class="code"><pre><span class="line">    <span class="keyword">del</span> wb[<span class="string">'Sheet'</span>]  <span class="comment"># 删除默认工作表</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">49</span></pre></td><td class="code"><pre><span class="line">    wb.save(<span class="string">'results.xlsx'</span>)  <span class="comment"># 保存文件</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">50</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">51</span></pre></td><td class="code"><pre><span class="line"></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">52</span></pre></td><td class="code"><pre><span class="line"><span class="keyword">if</span> __name__ == <span class="string">'__main__'</span>:  <span class="comment"># 执行主函数</span></span></pre></td></tr><tr><td class="gutter"><pre><span class="line">53</span></pre></td><td class="code"><pre><span class="line">    main()</span></pre></td></tr></table></figure><h3 id="运行结果"><a href="#运行结果" class="headerlink" title="运行结果"></a>运行结果</h3><hr><p><img src="data:image/png;base64,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" alt="表1"><br><img 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" alt="表2"><br><img 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sBJ3NburuX1rYSiaWrQ961nCCki4pgwUC8DxQZs790uerUs2qMUGubQ0+iw+l2MigMMFxnN6KG97FhqrIT2WdGWrRzUZDzGlkGyoodsN/ga91O/jcbrgMqKKcMaaU3QkGImTkbfO5VRI5XQDvpdGPnYwUK/O0KxOlw2yJkcUGJVTGanwcPSPWYG6HpD3qthqq2ViRQzVk2DNYzOV1Nm6HXzHQxD7Andd/0s1hYszI7f+q3fEk30kvPrJwGrH3K9K1yVBpi1uIrMwGdieZlhdpuIxpbRe3H67ZGejJ5D7+oKpcEMLU3UgC1jnGRtX8vJtZHUL9NCZZpmnaDpRn4YYcJKo74okBbriIwn9vN53oddp8ryX93Q4chhoNdOITkwmY22reWUle/yOO+6ZyT1cxHt9iP89Fiudz+d8H/32XduJ9CU6T9OsGvNy5RX3bS43nTMbPnOYfbkev7i79X2tQxb0Na+X6XFfc7264tBz01wdVXCYLb6u5bYtOtY/pns8E1xx+A05zFAlUSK/dt0pXktTXzgT0iEGOLJEbosTdzdo9/0kb6qIe/TH1oxxnRX38p+mUKjagFwx4nG8o7J+hA7zrL7GVX7HO8+H9Ml27brG1+bOhYTcGoE2NqxDOL1NK5q+RCcRoQooTgm/vbnf4yfx38fv/frYVxtGz5bAoPhvAFcYKDEClxio8BlMszQ8L8Sa0jAKrrVhbhHtlidzTNcDDeJCfoWzjiSckaSQR5R0s9him5tiptM+BUVH8nDjWgjdJnwacKHOsltAvPxHKOOMjeK1usVblmmm7Ak3u2iTCyNU6uJ2gjId07zUu+LfrHMqnPBt9sKi5PpJ4BRYvVBy8tQ5lIXAVYPWcjYRmgs4z3y6Ncm3gf9/Mmg0kihzv8z0IDlswJZZ3Y4c6UrqvrF9CqKdueJT9PO7OhEJ7Cr659pzbAqojWMG53VgMXmuewmm+Z/VPVbEsH2Y1d9Ip8eVo7W3r82rbEO8o3rO5selzhj5wneKfS11/moOfJY3Maav1hRFdbzl92HyHec5177fpWW+UdWn/rmefZui/wHa5h8xkVCMEFwtBwnKtudaa6FV/+YOwhZftQOffUxHdViFz3TWfYSkyoYsjizOWynxM4OgrufsZV/4LzPUaqBzgkM5UxrCLOZDmlGCyGChGPiL/FvfvYad3//Nywb/Sb+IAxnmhdGCYVJlWXkMK7FGpJkFbNlzjLQGxeRW6sZYzcJdAtN3FAG3Ib0W+FlvPCZFIVscMXrN+OCN/jlNjDJQdtrKqCiWKsRlk38RlP4SE2WSeA34ylM3E61BazDkq+h0Lw5bHSKvcMeBshNV8NmBp/u1TD3fx7Sz7lPoH58RMVjxFVx/TYZdfuw9LURZWYMZcdJNAzL0zjjo9Yz2anMNlHSz0CpNN2aij8de6WHj6qNkR8MVzMB1ojpQ7tTxEfkMruHuAPTFB39OBneN7WXAzllzBmZFpqqv9l2Wc5oc8+eZcCeJ75tCPLZEl1UlzNNtomafg7q1H/e7F2fHDk9+8Lvk1zT16xrqCW8bCuLdRMKO5bbGqh3k6gON2dRbM6YmGKMCerpK4w9bThWbjwq3KTQUhDY+bnHylk+aN3v+k/MuHe54UuSChMkqrmteQxTpOx3vyyLuSp7fwVo2RGKfjMMUnnEuXPELyEau2584bLZvfzGD6OkCTgl4NHP2IA9e8HOgqfrY/C2YjC5glaKz2coEsdEwjHxu/jD23+Kv8Vf4H/9378IL0UuDHs9ZEc4I+wqMBaaNd6QrFpf28uf77g9tjEdnXwahZJPhRBpJuizitnTh2RbdrkdvyX9/OmiXgISuRvEkwINVYyPHrGGhWm0mlLK9GW1LV8mczEVH3tOT/vHKDHjcYRUowre4rmMJNY4zvynPM2RycdzuBNo3GB1i0ey9SqSVwU0b3YZt+6pj9P5gl6rP0GOT4nlhoPBDBmN3addRNWjlbWYobKYQe45lZn026nfAqNUw2/967ZHQtTSb/19O+eyjnN5bE+z5ddKYTXbjHciuEPeHIbnoPQbSY6KfkvaE/e0cw4f+czpW6P/vVQCN67v+FrxOuKVxaw0w34G3klPs2tUFw4P1sGt7exMr4iGfk4sqARrvxdOBWPK7r5vU8Oe6aafRnrqTOO3eH6eTpHr5DEu8OvxudeWHetjNSqdZe/G/0bR0G8DBeq/cOuT8OpjFxPvpRzBEvOlQTxVBqzlDAfWqb9ZWEvc8VJHc5Jg12J21+Zy2/UrsfyFxXKbzVllWzMmtmdG7UzjxsDcTlh+bvG1CZbludxplSbuXEs6S0Z2OEzH7JFzHs6EDHuoMlPE9VteLlyDu+405Kpx7qHFroXycTjLtKa1rDNTaJ/BR0s833CHH9pjlFidsV39OnZycjAL2TEWEJsQfBxggOJVDc1K5sJnhJ8fCccE49d/A/81vofrkBLjhhccPuss4xOwaOoE9+mzwrS0JbzX0toYddZ9TGHUWwVtrHfz6Ay3c1hM7yCf1nCVbmDQ2RGgJXJwI81/bSUmO3567/RbVdwLr3qJ5S/bk35jf8ts2Sl6Ez5UlF8GCTN6Oy65TkxHq8KM4fSUachajGbBqewvxSnhi+PgSqX4ikoN2rR/wLRXiXy8SEOhi3xn6HMN1iCaU6SduXsejZDJbsHeeUZDP806OcMW7CzBykQ/3nKmLLP3m+NrE9t8lGLmORIRY4bKoiEUn8pM+rmTwjsIeXh0a/zTfib91t/34txsypmqbNc0+QSz47lx2MM07reefM2g5AYsX7ffuWEdlIAYCbax62jpqmIipN+uNAmP+NtrxYErbb5W3PZL8BcwYV2b3NKYt6Y1u8MSfOuo6MfKZIeXSQ0TOw/wFf43TrnamDIfROwmDxT4aPwN+lN2lRvdDoaZTeacNGl91q7BbtcCLxkZ/TbSoED9F059El56PEl4L+UIktge9GLveAQnXgN3wkxZT7xbb4IHaODpS+Ur0OfP5Gt3zfOXlwNJlNUsCx7vYWy/d35bl8NjSQKpdhZXrD7CiKU+5dEfCVo6JuRcC2C8WOK3eAbLXuq3lgjxWTNbyZttLcsKYhEzIjDf2O8rxXoaSXj5Mi1uJycHu2cKCgW9dBMUm9CBL/+rQasb0C/eTj8vco6Jo+IuOOP23HO7dgavixI3K6+6f3wJPvMigU6VtadTZzqSUeohwWor7zzIjJfhAJN0Db1+HNrF7owgyn3Uby3/zb3qraHJKvg+mnVWyYJVsuy5MhaQLhx6Cx3DDndOMANmxD3kF778hTNflzvId8GadWbkAs2mtTQwTgFv3CbMoFjf4YdvbdZfj9LP381gwjowV+gWB+hU1o3A+cjH2uZZsXmHZvUYlm1I8VGeA2O0eUP6rd3UsDsIyFfFE6+Afsuk9FgHK2/aZd4xo26QmxQwrewyjtbbxR5SzPDn64bda4fXdkpafO1l7EZcvxUm9lrqnalgMHDi/BusY22P8u9nxzpETT++3rwxAW/CrWbPjmXk28mOxVnXIAvtqjz/ooiBOc9PvGwPYXciENftcm31xywvzj1D7KHyKKBv6fN87FOGo6bfHGXqvw0Oq0+Ol57DsdCf5Jm9OYHGjXw+M8Te8YQvg5jnKZERoLX8xYNK9ns1THIdVGD6BL+ceu5ksoxVweM9cKdWzIkF1kvkkbPjtKyfHUe1mLJnW3XCmO12SMAULYHUaD1wrYF6Notxw2cZRdBONTY8UOnE3absAY/FERysltVF9QmqnTxqmofryl7Cwe3kAKeAh+OHzxjSJtVloGgegHNSXTnpd8cmXLs0nxLddTt9iPBR2DGxht1I7j2MsoSPbHOnRswoLb5glTX3Cm9WKg7OVknDeWVNkH4O9t7tGdYwsvq1Ww/pojxvj0b2iFEvMJp31FksB5pBm85DnzMDLj4psZy0X0Cug2F5uI7OxhRBHmypje4kx2z1tQYn04LJOjCFWs82jGJr5++e9uc0fNyzb3amKGhpTBp8+y7Zxoz0c3eemLHK+jRDVmjEZpwooN8SZxeDvOkWIZNLotaX62gtttYOXMocaf3WUsWft8g6H/0SSqyrEFzOYvN6dm3WwCFEUL+Mzu9j2VPgb3RnC8R4Z+jR2eCd1d3GOp/mP4k7NsCUe4bWYj7Eq1W+xQAMk3VoeG+vzzqJkxq6fPR6MYIcQf2Uqv/cCZOoT47Ynh2ylMOo821T7Fk4NjFnucLu/fg8WMtftmOlxnezdZy4y3S7lnI4HeegZzKZIaixcmSXDTvGinvJkdHL2l7S7esELOHYxF6a096xvHdj+c1ypxTeX+pi6qyocupHPnNjRx7Y3KnGXvoD9yyb3s7tRkKAvfdJrmUvc65t/XG1hOPQcn7oLj7E6YmGY0IGuxJZH4k2YWkLTz73YvPdPXrILbcA4hVYEiKzOKPHAWsrSb8l4Uc0tpzpgAPuwa9Dy6Y9dp+5HNan4VnT1feZSgLpdBOa8JrFA9cIW000p5XtAFmL6OoeAUdjzLjc9q+xt6UVkDA7cIyDJmu0y+zdcQ/8fDus5MKYyGBoxlEqZKGVU0gV86hWDlveRPpt67dP0MKz67cO34Kv6BHgK1NBvha0Pn3nhe0ldou15EGR7COr3xInsN3Aft4MKnb09B4GIiN77B1M4nJzpiOpn9VnV4jbm3rrLd0e7ecOHa8B0+Ugg8djmnyb8MVocs8Zzc7EnCW4q1k9GrMHuuCBPnR9e2eOSOmnYP23SoNMfXLE9mzvpRyGrbEdrPaQWUwbrPIXn1WVRC7m3lZ5fcbEomMflCW19fqU/ce0adizZxfpdxxEnotvNrTYGLln+YvPvl067uydOnbUT6n82pIkx/HixOCIIVfMomdPmXC2tE2x59pdNtxlYju4rDObZJ+aeR0tkQo4g9UbqMx18PiryBKOHfAZG8mcvP1u8QyzWLJGHI3LdEwwY8xaVB5bRpnm9gyzFm6cYg3sKdN3Duw1tAl09l1bSfoJYVoetWkAdiTp3MLoa8FspG3nxOYWuBcB311n3mHaYhEwVWRd8qH5eH4ffWtxJI8dMkbDd1mSD9woiPGmmzvh2HVnzMA3nICmubzTCK/23+ZWdBGNRoIZ6F5GnEDeIf089TOaTdtxGogK+i3hI7+OZh6JgV5N4urAnY24ozOxNi0/FjNRStd9p+BGU7/1ZNVc67wX0dOzhQRL6+6twvhscFfguvF0OQPQNswFdhqLon58vTdyw7Vvxuwfjy0M550dz/0T+W4Nk/h8RoW1DJbI86825Y6O1pozI+kXlzBa+ilY/zmEUJ+Emp79sBxP1jxtGQ+N/TBZ/qmj1h1jxOMDeBihi/wVW9qpG9sqr82Y8NrSNpjMfMaOM6tjMXtLNDbosZbGcEdAu8fnEfVQHhUx8IgF58Ydd8Vrq9eexKz1VVwavzwY2+EQMuBsBHPoiJ3jLBKLQbSLhZOHZl4cG4UdE+vTnqZ205lwrRvYDn7pwLcIc6Y/eXmwt+ANlcsD5qxXPdbup+fiaJ6+e6JfEHb8tFIB2TZrBAIH4fhMibq99nN9nSoPGtroaihfWnAdPhJQS+w0Gu2AqezZtfRk52hn2Pl40bFZOILcRtIecMcU35M94xgn65G+OXwaZHyoe09D5FNXf+tf77g26eenX4ZVNE12y+97bGqyurZi+vFAwskqfG3FTAWNmrb31mR85Nt2dLqum0Gr2lsFe9y8VRT1c67kWYdyMpUGUhpfY+3dCtmzSMw6sshhtv6H5CqSPTfMRczw6OhnOUsRzb69Trs6C/yBz2WcwHLT3rpzYzEa7XziW4aPWUdYJChldPTz5tz1n5OII9Qne6dne5mC35aurrgO86C8ELXXXWjO0qSb+Ra2Hj9e5C+dl+Z8bmvnCXeMCf4FSw+PY2AGzbjiS5icHWHsGTslg6/c2bMD7S43e+O1Zf0c7ghIlWtIj0WDlR53xoQd3yZ5ddA2uoHOHv5Od211ajul8sFLG+13mvF1kNizNoScPIQsCta2ZH0AACAASURBVDsm1qc9scwy2/Zlbga/XJ0rPj2TN1QpeVea8vCpTMUdW3Ydyn3Rj8NHEPrTOG5uvP7K8mtrOA8wt6uCYw1404TW8loTG4PeaWDSvyCP7DywUqcTtwNQLV2N6w3ffJuz5GDADKgsslrbjmbttaNLqPnYKDlbAq5dLpbR0CyV1rYTFGTHdPmARIDbtl675dmQfrvJsMJYajIBv+/9d+X0c953dWf8Hace6GpZpDGwt8sOtqlK0Mp8t4Ix68Sxz8kkkkggkYszYzOHYiqLWrPCDPnNXnzU9OOM0WN1aMWzDoUzgm5yFQ14hciLsacoZZlWriHWBEvXqt7lMy+ErIjI6MfX1vPgcmWM2LUPbmF4YDmW7hpLYn4h3+asSTsm2GKtRcBARWT080CF+u9Y9cne6dne5YE7+W42HTUW+9yZrZwoYexAEZtv38iX2pg69HUp5vmriTaSuRY/1f1cG9uFbm+r6QF7Bp4nWwuPKO904wpXV7AdLMKzJezlN7ngeobZnc3l8uk55sReJrP2hdvJwdNULCPLt7Rd08PbcRZHPn+z3EaYsz1jgtUYA4l4PHC22+xdaSwP+gTh9CR4toQ1ne4MzmbwC8yDwu6E1WNTeDs4LLt95ek4Xyyl+4S8Y+Iffok7/A3wq7+ztw+NFnxqTpJV6htZljWyF9Q1xHIPYdkGYPvCF68fd0bw4F1j1rSZlXmjt77AdRGh3PWjKXpTbXttpfOD7c6B6886WnbDGLyvsupw7erTm2UDvv4srobPXks5/0PGRNy1Rnn9giHm4+Uo3GYzw9dd51BKpzHtCC6p4aOI/T6mcadxN4WnDPHgc87uCfj/toO/kX4i8O0fJ/gS2x0b9fRbve9A42Ye1T+dzUIbF92jwNwwLvDeSIcZxHWUDD4Nnwfay/mO1mrTIvo33vVRdPRbwAzwgMB7O+tN1jvJFdn/r68v4KPDB6UlSvrxtBZRhv9Iq9hlbpBPTZbyccOfdfddjoNcdeFIWM127S2223ZVClHSz32t89d/IdUnoaVn4zK8M2c7ANfeOSt7WjON9OTwWEs2mQrrcIv82MlfV1mRmawCjLooFJwArtukXM7NIPguKsXcYYniA4I8ngTfRtXZGbPndg5ypxl7z6lRGYVSHMN58IZ+b2ov2VhdiM+AYq83brpmvHjNdpny2S21/Pb2p8Jk0JoNWNnQ2PsXdbj7xE5Zw5zwQJ8+eWlR5kW8RebEc5acvaMH6+fs3kqUCBMJx8Rf4t/U/y3+/fyT1XvO/vs38Qf/qorf+/VQ0nZ0+NQcO4qt60vvLYOijFHvIjnY3G9ZnsvWjwf1ZIZUscHs/9nWdOEgxl2P9XQeEar9mPayKPNlIR7Tr6OBxaxH/YBAnv5rDUPLx/MRj9XU4Pk05yUaKnn2b62EuJf+PI9zAyXdZX0kZmCB92vc02zH0/Upo97TII1mfzmyth2UnvQL0m/5XL2xx0oY9fRbf99C8MB5A7AO0BhT04DGjPoY117L2gFz7ZgA7ByNGaF8x+F8PocbzfKOWHJTYd04Z7q1pmVcnbyo6Lc3vm2RtX+MzR1EST/eGfJ8cM+2aWob6lvbsFp9dFlfdbHJZ6ZlYmDFfDoGU9TmQfr0jPf6kSjp5yRNjfovlPokxPS4HpHv6mB35mZbnTk+G6nDnRbaFVJFwQ7qFh4zOljHstszXLESOIa9LcwItWZue+v6RBHCvgTT6bbmO+t2HQ9gyezgZMN2EBQ01ulOsY5wp7K1ZeU6XJ8aBh6BUT3OnXbRnd6s7azibKd6o9u5nR1NpPksocZ8VgBvD3rzpU9Wzm4vrsZ8BlF8HvR2DY+tNTleMSaWMTjWY/jtDd/tx7TzrmllxAbexru253S2se167TxjBxPtIm+KlXnu7GlPjFVAX/tLA31WIswwtn4lhJFwTPwu/pBVin8YXlqODs94o4mzu6813/bJ8eSygsYKSr3bZRX0yI5PcSmZcLnu2Ht+Epr9Hrp28CC+zm+3pXa/9GMVKG9pvGpOPmI01nCVTsEr1rCtZaqx8W0SyZwuvB0o31d5V0Bm9Qme7bHISyKEmY+NehZt1o63x12k7CnvjMQqKr3GjAvcVFEse01/59OhuYHbYQ2Yf+O8tSbXwxef2Rnli/QL0s95rrQ9nXp7JYx6+m29b/67Ot9CkdcZfBawR1o2o/rH+KiTu4PnRP7n0eZZHVyosU7DyL7eNkV77fS6LlHSTwzLNnp7rC1qe9bDHGd5QeCV+Ig931GCZfA28p4BnqOl39whk/T4k9fuCYsdNTaxA0iOl9sR2t0jVxHn6ZliMuFllqUpWfV9ymjp56BK/RdKfRJyfezM4mAddfZOOzs6c7zOmg2Aq2wWhYTY1H4tAWS1NLo+Gzzwd5cqcjfaWuSLef6azTQ72Lh2VUOxUUXuRrN31/Da9cJaeJk2O98szR3TmudLXt/WwSeu5avMDp4XgOHsxr5PVnO8HaliA52W7uro8nc0SbDfbI52cbuSlTntiuWr5TM6dXmquJbXl9tqLn6ns/vq8+fldnlldW3eXth71vIlTrCXmiye2Fqb4bSJX3wQ7pTiO7a0fbcwFSEWYPusweOj9Ph7K+84KYVi3v0N758UbOfM0CMPxnCTL6KbvcLV5pWKm6fuE4yVCI3rj34w+8UvfnHWg6eBH/sxmBVTxdnAFP+F2UjNUo3BbNBo+PxuMGuwv+9xSaUxfZ9z80SmZTH4uS9Zv/F4fO4kRJp99XPyklhOCTsfz0xTKI8OiqkZu9zeDBqb9RIvF7vvSPqt/U5IP9OuhxrzEyOl39b1izNmwJ643oyofmaDnSOilTlrFHfZB2J52L5OyisfR1U/lm7TfQbPfw3Pcsqf0ed6pkCCBixf+9poEdXPPk+F+s+fsOsT0fSYA1Y2eX7Z2yb3+QHPP3s898aVXflr9bVpP0+KlWnW/fE9in4ZxuTPzp8zIE/x+wzWX75zX54euffilxfMHXb54pSBf3lWCbuOPzSdPu9dcaLQ/2i1WrO3b98ujz/90z8N5br8OuvX5b6AK/6vPy385IyuEeB/7PzY/v//9JN/d9Z0RJF/9uN/ufUd6bg/X375Jd5///1zJyOykH5ykH5ykH5ykH5ykH5ykH4EQdxXolD/tdttPH78ePn5888/x+3trfR1X716hQ8++GD5Of3TH+LXpK9KEARBEARBEARBEARxIHaMiV/+8peYzdetbv6/13fH+BvHa/Sf8MdvZsSX25H0CAFINzlIPzlIPzlIPzlIPzlIPzlIP4Ig7itU/62wHRO//du/fd5U/PzFee9/Yag+JUhFojCVSmW4fsk/8Yqq5jB77h2RnXAg/eQg/eQg/eQg/eQg/eQg+0UO0k8O0k+OKOg3HA6DTwoJiV05wmP40c/w+vVrlH5Z8vw7NUoEEV2o/MpB+slB+slB+slB+slB+hEEQdwflHBM7IIapd0slnNEweNG3D+o/MpB+slB+slB+slB+slB+hEEQdwvlA5+SY0SQUQXKr9ykH5ykH5ykH5ykH5ykH4EQRD3D2VnTFCjRKiLgVK6h1ynhUxM7BdWs4Q6csjFBW8x7aE2yaHTykDwFkpB5VcO0k8O0k8O0k8O0k8O0o8gCOJ+oqRjghqlM2E1UaoDOb/es91ZTrDOsh7JznJYWM0a2sk8cib7ICzEmP1TQUvQk2FNa+zfuUjqTOVXDtJPDtJPDtJPDtJPDtKPIAji/qKcY4IapfMyHgMV31H6HrLdEydINawmCuUkBjMdGaOJpqVD38d7YBkwTL8/TtGrlTHOm+jwjwlNOrmnhsqvHKSfHKSfHKSfHKSfHKQfQRDE/UYqxsTdi2e4ffAAD+zjFs9e3EklxqtR4lPg01dXuLKPNEpNa/uHFp9aPz8nXYLhccr69bwusXWvtP95UWTXc+9FMh7JUfxwsNAsdJE3W8jwjxkd8fqeusYyyGRWhzatoTbV5p91tIYzDPfydKjDLqNSuNz5lPGwzhHhlPda55j6idSR4T2TBaOUnl/nCulSE+tXspqrv7kPlq4D78jZ1E/0PmE8t9i9HF1UbWOCOoVGib3LI5WFQ/KEX3rOxbZ+Au/baq5ptzoOeS4R+0VlG8cz/+1h2+3iXHU6QRAEsR8HOybuXtxCNz9E8+1bvOXH8DG+ep7GraRzYh1urBT4OvvZDDN+mHmMy9pGo80aLi1rjzLzc8wqkNU2jRneuDkGglYe+95L6yZQNWfz6yTQ1dJKNdz7E/zchDhGqYBuvuOaIZFpVYACM2IOtZguGrFyF1TGF2VzdU4Vie72OcF1RTBhpSccwtFPpI4MSz/beZfWUEtUYdrXGiDZLqOwdh1zAjQGTlqWx6CI4mDu8AsJkfuE9S5F7mWUuC4dDOd/N/NjlLfaKkUxSsi2t78OK9/snSd80qMSou87P5i5n3u2v3NaxH6Jno0jYtsFI9p+nKZOJwiCIHZxoGPiDn/2+gu89+EjXC++un6K5scP8YUZlmPCQr87QjK3tqwgpqPTSGE0Wc2Ft9f7pxrozBvyWKaCRqqNmqtByaDV6aBjNpDyvJeBepkZRh19GcwwltFRLY5QrkfCbPQh6Lm9mKBvGDC8jun9dW5ww8U2MrcMxhj0YQeJWgFpiRGdyyQo/4mUcX6OUzZX52SgV4sYdfvzkXixuiKYsNITFmHoJ1JHhqUfw6ijnBywcrK4VgaVwWB5b36vaaIK3RVrxUKzl0AlTK+E0H3Cepfiz7SuZ0zv2O+hp3wTw56l5uUFCK/c7Zcn/NKjHqd53yL2S/RsHDHbLvAqgu3Hqep0giAIYhdSSzlefvYmrHT40t7ZijuGUSp/s7a8IIabfGq7QYnF2P/iSHpeZoox+0t8o8+ZyRWB8TTaDdOu5/YkgZuMe7nB8oiLX+VycKbjFiZ5VOOmt8PG6GMyGoEHuKxpzjRQPn3d20lhwVr7bX/Cvpr07f9u8unv6YiMoIoikP92l3HOCFv9HC2B1MayouDriBFWekJBWj/xOlJeP6fDmNqIjRLLZFz31vWN3qZRxyQXdkBd0fuE8S7F7pVpzWC2NnvaKeVDyVhNPlNswDqF3n+Xzzf75Ymg9KiC0Ps2J5jI3kjEfomcjbOHbReISBk/YZ1OEARB+HJg8MtrPH31Fk83vr0zv8CTDx9JJ8qBj0TPoG98a05GKOYWjb3JOoRAsupuOmK8Az2aYK9NE/wI6zpE9LAMNOtTxCtDDDcygD2FGYsZFBlkZvOcalkw+n0wS9tnWjrraGZiy/zEY0x0cQNN44bscJnf1TMUj4FIGY/ZI1dX2TQSg85yVNWoT5Cv6Htc55TpORVh1ZFh6be6F3fmZdsj+9tUcbBj21vuzEiAFbEj43WfY71L/2eKrZ1j8A52srpVtygFD/bbzaMz1OxRZTdh5Zutm/rniZ3pUY/g951AQuNLtrJwiksKxUYHrbDiDInYL0raOGHZdoLthzJ1OkEQxP1GasaEi7sXaHz1MX4Ull/CC2aU1MaN1fROexQgBOwRyTGmG71BoxeN6aLEMbDYPxnordXUVyFiMWR8nRI76BeQLhn3xCGxg80yzsm0MBsk0c1quOIxF9IlvnXM7t1QvK5zzvScirDqyEP0m99rXCuhl+vM12oPkB9nXTEmXBh1dF2jokfC7z7HeJcBz+QEetSQnbAOdrjrV0KGB/udoDrcYzZLGOXOV78D0qMAu9/3BN36FLnOKkYHyhpK+0xCEbFfombjhGXbcUTKuMp1OkEQxD0iJMfEG7z4FGi+erqKORE6fPQa6BzFKMkgx9daFprLNYdGkxnXKIZ+J/WhGBMOfAr9Ce+md3Z34O4FPmWcR2bvOYHJzGqeGdhtZAvNHU6csOqKsNJzKo783KLkK2itFrLvWKvNR8bHyN8cu6DtuE/o7zL4mWL60Anml5ugoHDwQYtlgkl1n4CkYeQ/f/32T48a7HzfWg6dded3TEelkdpzeYyI/XKPbRyRMq5snU4QBHG/CMEx8QYvnn2N739yZKdEaYqb1obBs1fshN1kWiYayS40e6uoAmuwK6gkWEc8lYDiS4DDw5xgRDEmtuHLMzacNOuxIezD3h5RJj6EM51072CDF4NPGbdHSXvIzb+P2Vuqmhgky9A8hxX9rnOu9JyKsOpIef2SmwvZ+Vrt+fRrF1YfXeRxfL+E332O8C73eKZYpoVOA4oGHzRQn+SwFSJhx/mhlDtf/fZNj3p4vu/Y9hIne7nCnnEfROyXSNk4odl2ImVc1TqdIAji/iHpmHiDZydwSpR8DR4NiRRvw91NuDU9pLFlHcPWcL5d19Be48nXyqZOMc1YEWzdKNjTNnx5xoaT5ibBvk/crL6z847kaF6mgkFOu4ejNDvKuN1R2SzL7H1UGkhtGe+76opzpOdUhFVHSuq3Z2fC6ncxOuQ+e+J7nyO8y93PtH3FQzqhJ8Hood3Osg7s1fzQUGYPNipr9md3fy2scrdDv73SowrB79sySmiGknYR+yVKNk5Itp1IGVeyTicIgrifSDgm7uyZEj/acEq8efECYW0YanuymcFT2TB4jOZiip1XlGavaM5i9zJc2ygY6LVTJ5hmrA7yQcuI3ZiuHTm2Z170Uctq9ijN/Zk3EVTGsQx2Jn2dk6bnVIRVR4ahH58u7rFLA5+J5dGZ4PXNKdh5n5Dfpf+9mL5p1one6EFbqi6P42vuZ7O1w7R3wUg1TPvzauZCWOXOwVc/4fSogsj7NlDPttH16nzvPUAgYr9EycYJ0bYTKeNK1ekEQRD3l4MdE2+efYp3N2dK8ACY5ruhzZ4wSnXEN0dheHCtyarRjulVFEfl5dp8vg61PCqi6hW1yA6oxLeF8ljt3Cwgm607U/H5bgw8SnaxehnBj3Y89+ocpmu7CPJLHBPN3jpxfeYFH8Ea8jXG9mcdQ250Mytbuam1MuzIf4FlPKajWmwjux4YlJfPQhlYM1BF6gpnuc3uNf1hpSdUZPSDWB0Zln72KGM7i/TiJK5NrY1idXtJzGn65DvuI5y3gp878F5zUliNo1tGE4XyyEOb6BBWvpn/8ER54nTsft+OI892WLvOARprQTJF9BOxX6Jm44jVWwHaiJTxc9TpBEEQhCcHOibe4LOXL/HkwQM8WD/Sz1nfKzS3BHpt1lgsp27OD401Fq6NwDNomQMku86UTq0LDMzNKfUGSvPf8vGYNo+8vNGY2Y1gan4/rYZJ3rQ7iNEm+LmXZ9a7SA6iF1hMPSweksKb9ZgUAUdfenN7FQjKf2JlnK+NHiRqKCz/7pTP4dJAFa0rgtMbTnrCIhz9guvIsPSDbeQPzcbyXrY2VdNjRDuG04Ss2X2fcN/lrnvxrTVN5FGbr/Fn76E2QX7gpY1aLHaVWC2dWOTBEPONjVie8E+PSoi9b57/qljlPy3L2+HO3s4CEfslejaOiG0ncBWBMn66Op0gCILYxdX1Rz+YDT/62bnTgdevX6NYvAcRoo/El19+iffff/+g31rNEurxlreBzEcO+j10u2OMRswSLA4UN2YOw1M/9uyGz/zOaa9mB2mr5uIb32dRbqfQMIcbo1VpFNARNnT4+dqkGhmtZfIfQfrJQvrJQfrJQfrJQfrJQfrJQfrJQfrJEQX92u02Hj9+vPz8+eef4/b2Vvq6r169wgcffLD8nP7pD/Ed6asSkcZqNmHetNDy6y/z7f50dtwYKNX51t7R6CiHAnv2jI8u9jIMz+9n0Ftev0giv7lbwS7iVQxu7pHWBEEQBEEQBEHcW8gxcc+J6YLrm1knveXZ4SZEiOktT0eG7/mZ7W3kCIIgCIIgCIIgLhHJ7UIJgiAIgiAIgiAIgiAOx54x8c033+Dbb7/1PPhWXPv+7ZDfcPg6G+JwSD85SD85SD85SD85SD85SD85SD85SD85SD85SD85SD85SL8VtmPinXfeOXc67OCXyT/xD8k9ez47YWqiRxSCp6gM6ScH14/K7+GQfnKQfnKQfnKQfnKQfnKQ/SIH6ScH6SdHFPQbDocnu1cklnJQo0QQ0YXKrxyknxyknxyknxyknxykH0EQxP1BeccENUoEEV2o/MpB+slB+slB+slB+slB+hEEQdwvlHZMUKNEENGFyq8cpJ8cpJ8cpJ8cpJ8cpB9BEMT9Q9ntQqlRItTFQCndQ67TQkZwT0+rWUIdOeTigreY9lCb5NBpRXPbUCq/cpB+cpB+cpB+cpB+cpB+BEEQ9xMlHRPUKJ0Jq4lSHcj59Z7tznKCdZb1SHaWw8Jq1tBO5pEz2QdhIcbsnwpagp4Ma1pj/85FUmcqv3KQfnKQfnKQfnKQfnKQfgRBEPcX5RwT1Cidl/EYqPiO0veQ7Z44QaphNVEoJzGY6cgYTTQtHfo+3gPLgGH6/XGKXq2Mcd5Eh39MaNLJPTVUfuUg/eQg/eQg/eQg/eQg/QiCIO43EjEm7vDm2S1uHzzAA37cPsOLO7nEeDVKfAp8+uoKV/aRRqlpbf/Q4lPr5+ekSzA8Tlm/ntcltu6V9j8vSgjptw/JeCRH8cPBQrPQRd5sIcM/ZnTE63vmk1gGmczq0KY11Kba/LOO1nCG4V6eDnXYLL9WMz3Pd5sHK6Ork9by5+pIr4kqdB1BRMpD6GVGkIP0s08Mrv/Ceiax61gwSqu0p0tNnELBoE6NUXLnqwXhve/dzx1mPj4Gh7W/zjPLtpsi2lymfm788qgIe9dtitk4nuV3D9tuF1HXhiAI4r5wsGPizbM0GloTr96+xVt2DB9/hefpZ3gTYuK4IVLg6+xnM8z4YeYxLmsbDTdruLSsPcrMzzGrQFbbNFR44+YYT1p57HsvrZtA1ZzNr5NAV0tHunES048QxSgV0M13XDMkMq0KUGCGzqEW0wVjToDGwCmXy2NQRHEwd+zMyQ9m7nNmbueM6HWCWJTxVXmoItHVtpwgqpQZsecOrv9EnlsEMW0sNNMaaokqTPu8AZLtMgrnrnOMErLt7a/D0kbkucPKx6dC5H0bJf7MHQzn55j5Mcpb7W8wItpcon4ufPKo6L1E6rZo2Tgitl0wl6kNQRDEZSK1K8cX5mqKxPXTJj5++BKfheaZsNDvjpDMrS0riOnoNFIYTVZz4e31/qkGOvOOTCxTQSPVRs3VomTQ6nTQMRtIed7LQL3MjJ6OvgxmGMvoqBZHKNdVGIs5BDH9tpmgbxgwvI6pt1PnPsANF9sA35rNEIM+7CBRKyAtMaJzeViYsk6a7oqpwTpvvQQqe/UiwrtOv+uU8VV5yECvFjHq9ucj24eWmWMg9tzB9Z/Ic4ulR0gbo45ycsDKyeK8DCqDwTJ954HpVvPq8YWlDQSeO6x8fCrEy8L655jesfNfb69mU0Sby9Vvcb53HhW9V1A+jp6NI2bbBV7lIrUhCIK4VA52TDz65C2Gnzza+PYhtGvJFG3Q3mnhOI1/Kn+ztrwghpt8atuwjMXY/+JIel5mijH7S3zDds7kisB4epJpyMdit35eJHCTcS83WB5xT/UuHGeqcmGSRzVuejtsjD4moxF4gMua5kwV5dO4vZ0UFqy13/Yn7KtJ3/7vJp8GnlZjWrI8Mej6Ro+Bdd4muY3AqeYEkzCuI8QIW30CLYHUxvKk/cvMMRB5btH6T+y5RQiqj3nnKrURGyWWOe/OMlaTz3QasE6N11/D0EbkucPMx6cjqCxkWjOYrU3PQGrP8Dgi2lymfgt251ERAvJx5GycPWy7QC5NG4IgiMtFasbEygdxhzcvdLx+r4ynoTkm+Ej0DLMNo8ecjFDMLSd3sg4hD3vgblFivAM9miCUMc6wrnNyRPQjdmJxZ0EfqAwxbOm7Y0Pw5QdDdp5pYtDIo9rSfbYSjdkdlsV1bhLsq8QNNE2D3hpiNlRzWrI8vPPmNbqZYJ2YtXXEgeuw/a4TRMweJWtn02iueYyM+gT55cVULjNezy1S/4k8twj71cfuWAvG+Yx7Hqy2m0dH9+oph6XNIc99aD4+FeJlYd1RZvAOdrK6X0DgLUS0uRz9dudRwXvJ5GMlbZywbLtL1IYgCOJykXJMcO5e3OLBgzSemI/R/NHmDIqQYQ14bdxYGSO2pzsE7JkUY0w3rEijd+jUSkXZ1I/YgcX+yUD3dTD4EIsho+v7Oxf6hfN24I6NUUfXNfq1YIJufYpcZ7UOG2UNJb+BRt/rCJBpYTZIopvVcMVjzqRLfAua3Z0oVcqM13OL1n+HPLcIPvXxuFZCL9eZv88B8uPsmWJM8GC1E1SHO0bVw9DmkOeWycfnYkdZcAJTashOWAdbtrCIaHMx+gnkURGC8nHUbJywbDvOpWlDEARxwUg7Jq6fvnKCX35oQk/fSu/M4Y+BZh3oyDbgnmSQ4+sJC4so6nzkhxmZKIZ+p/Mhqh/FmHDgS39OeDe9c8YO3LHho5tj5G88BNVy6Kw7f2I6Ko2UzxToHdcRSoaBUs8JgmZW88wYbSNb2LVjxDHrnH049XOLsEObfAWt1WLtw2I2hIDFEjipBsxAClMb4eeWfJ9nYXdZiOlDJ2hgboKCVNBAEW0uRz+hPCpCYD6+DzaOD6QNQRBEZJB2TCy4fvQJmh8Dzz8Nc1+OBXxK/RQ3rQ2jyC9mxAFkWiYayS40expugTVKFVQSrCOeSuDQCZbq4KPfJuYEI4oxsY1lbTlp1mND2Ic9hVsmPoQz5fT0QRZPgNVHF3l49iNi2/EH7Om6Xmt7d10nOBFoFnrIzctAzN6a1cQgWYbmOT1DsMycAr/nFqr/9n1uEXZrszn92l7PffIp0Qbqkxy2wh+4CFcb4eeWysfnQLwsxDItdBo4PGigiDYXo59IHhVBLB9HysYJzba7QG0IgiAuGAnHxPbUiOt33wO++trjLzIYKPkaRRoSKd6HcXdhrOkhDUrMWeNvbyk1REuP2etBU1GbLrrFLv3c2LodEBDv4uHLMzacNIvYEMvv7LwjOfKVqWCQ0y5ukRlRwgAAIABJREFUOYfV72Lk9zejhKZgH2bXdQR+zDozm3UCe6+VBlJbThDxMnMK/J9boP7b67lF2KFNiI5iaYwe2u3sMt4DX2ZQZiKOypr92e6ThKXNns8tlY9PTlBZ2FbJ17EogIg2F6OfSB4VQTgfR8nGCcm2u0htCIIgLpcDHRN3eHGbxoNn7tkRd19/FUKS1rHskYbKRqNuNBdT7ryiNHtFcxa7l+HaRsFAr52K2HTRTYL0c6NGkL9LxnTtyLE986KPWlazR3Iuad4Ez1feGKhn2+h6GZ8eDjL/6wgiNGq/X5k5Bf7PLVj/hTZbIUgbPiXaYycCPhPr1COPfF35bLZ2mPaOB6mGaX9ejlKHos1+zy2dj09G0Ptmf0+zTvRGD9qSWPInos3F6CeaR0UQrNuiY+OEaNtdnDYEQRCXi9RSjodYzZu4e/MC+vMv8KT8FGFtzGGU6ohvjjTwAFKTVaclpldRHJWXa/P5ms3yqIiqV/QyO6AS3zrKY9Vvs4Bstu5Mxee7MaSzaBdlo4ufFxH9XN+3iyC/xDHRXDty8IOP0qx2/NAxnDmR3C9n+qgF/36K06GzHTaLs40mCnxP+a0Aeruug/lSmh1r22N8X/o2susBRnk55zdbM3T3KjMnYfdzB9Z/ws8doB/EtLFHIttZpBcX4veqtVGsqjH7xEWI2og/9+73qRKiZYHvcOkuvyPXc4voN/+1gDaXp1/wdcKp26Jm44jYdvdVG4IgiEvlQMfENZ6+GuIxGkg/eIAH7Eg3TDx+OcQnoW3MwT3WrEFZTnOcHxprUFybpGfQMgdIdp3pj1oXGJibU+oNlOa/5WMtbR6deaMxsxvB1Px+Wg2TvLm11Ve0ENVvfna9i+TgUreqPCUWD0nhzXpMioDDnklxEcSwKzQJX9tbRQ2Fef7UsjwfdjwMwt3XEYHfa5BY3WtRzofLm+1XZk5D0HMH13/Bzy2CoDasIzA0G8v02PeqmiGsoz+cxY4Rq2nyq7o/HG2wx3PL5+PTIPK++ZaYJvKs/GqL8lubID849H2LaHNJ+q3YlUdFEMnH0bNxRGw7gatcpDYEQRCXydX1Rz+YDT/62bnTgdevX6NYpCjIh/Lll1/i/fffP+i3VrOEerzlbUzy0YN+D93uGKMRs5qKg4tssD31Y89u+MwBnfZqdgC2ai6+8X0W5XYKDXPo6lxzw7OAjnCHh5+vTaqR0Vom/xGknyyknxyknxyknxyknxyknxyknxyknxxR0K/dbuPx48fLz59//jlub2+lr/vq1St88MEHy8/pn/4Q35G+KhFprGYT5k0LLb/+Mt/2TmfHjYFSnW//HY2OciiwZ8/46GIvw/D8fga95fWLJPKbUft3Ea9icHOPtCYIgiAIgiAI4t5Cjol7TkwXXPvNOuktzw43IUJMb3k6MnzPz2xvo0kQBEEQBEEQBHGJSAW/JAiCIAiCIAiCIAiCkMGeMfHNN9/g22+/9Tz4tlX7/u2Q33D4OhvicEg/OUg/OUg/OUg/OUg/OUg/OUg/OUg/OUg/OUg/OUg/OUi/FbZj4p133jl3Ouzgl8k/8Q+3PXs+O2FqokcUgqeoDOknB9ePyu/hkH5ykH5ykH5ykH5ykH5ykP0iB+knB+knRxT0Gw6HJ7tXJJZyUKNEENGFyq8cpJ8cpJ8cpJ8cpJ8cpB9BEMT9QXnHBDVKBBFdqPzKQfrJQfrJQfrJQfrJQfoRBEHcL5R2TFCjRBDRhcqvHKSfHKSfHKSfHKSfHKQfQRDE/UPZ7UKpUSLUxUAp3UOu00JGcE9Pq1lCHTnk4oK3mPZQm+TQaUVz21Aqv3KQfnKQfnKQfnKQfnKQfgRBEPcTJR0T1CidCauJUh3I+fWe7c5ygnWW9Uh2lsPCatbQTuaRM9kHYSHG7J8KWoKeDGtaY//ORVJnKr9ykH5ykH5ykH5ykH5ykH4EQRD3F+UcE9QonZfxGKj4jtL3kO2eOEGqYTVRKCcxmOnIGE00LR36Pt4Dy4Bh+v1xil6tjHHeRId/TGjSyT01VH7lIP3kIP3kIP3kIP3kIP0IgiDuN6HFmHjz7AFuX9xJXcOrUeJT4NNXV7iyjzRKTWv7hxafWj8/J12C4XHK+vW8LrF1r7T/edHBglFKh/tMyXgkR/HDwUKz0EXebCHDP2Z0xOt7ahrLIJNZHdq0htpUm3/W0RrOMNzL06EOu4zKXeVukU+v5vk0XWpi81SRekCortiD3WleYZRYmkOoLA7Sz2quPfPq2ExPcN0WXl0R9B6sZnorvc7B6u7DbmlzUPshqJ8Yu/PxsZ47LII6hf75PLj87oNfXo+efmJlKhS7QzQf72ErnZqD7T8hBPKowtoQBEHcF8JxTLx5hicvQ7mSC26IFPg6+9kMM36YeYzL2kZjyxoTLWuPMvNzzCqQ1TYNFd7gOAaCVh773kvrJlA1Z/PrJNDV0pF2ThglDbVEB8O5fmZ+jPKWNoQoRqmAbr7jmiGRaVWAAjOYyIrxILjc2c6eNM+nVZh2Ph0g2S6jsFbwFmVzVQ9Ukei66wGxuiKsNK+fXkK2vectQk5LfjB/5rVj3bklUreFVVeIvCtzAjQGpjvNgyKKg7nDLyRE0sIJ0k/wboH5+FTPfRR883nwcwveIDCvR00/kTIVpt0RnI9FbCV1CK9OF8mj0dKGIAjiUgnBMXGHF40jeCVYY9LvjpDMrS0riOnoNFIYTVZz4e31/qkGOvMGOJapoJFqo+ZqdDJodTromA2kPO9loF5mRk9HXwYzjGV0VIsjlOvRbprWtYrpHVub3s5HmqBvGDC8jqlAR+1C4UaSbWRudVhi0IcdJGoFpGmUZYOgcscw6ignB0zXRTnPoDIYLMuzUw84ZXNVD2SgV4sYdfvzUS+xuiK0NC9hBm/taF6JPdPih3jdtn9dsYnYu5qyDoLuirXCdOwlUAm1dymSlhARyMenee5jsCOfBz63KEF5PZr67S5Tp7U7xGwlVQixThfIo9HShiAI4nKRdkzcvdDx+vFLfPwwjORs095pGTuNVyp/s7a8IIabfGrb+IzF2P/iSHpeZoox+0t8w5bK5IrAeBq+EXsiMq0ZzNam1ZYKCF2QwE3GvdxgecQ91btwnCmghUke1bjp7bAx+piMRuABLmuaM+WUTxX1dlJYsNZ+25+wryZ9+7+bfKpp+sJGaXaVu3mHJ7WRIWOZzRgnI2zZoloCqY1lRbvrij3YmeYVVpPPoBkwAzac2x6UFnOCya7fC9Zth9UVXgS9qxh0feM+rOMwyR0joK5AvgnSTwiRfHzK5w4X/3wuWn4F2ZnXo6dfYJkK0+4IzMd72EoKIV+ni+TRaGpDEARxicg5Ju5eQH/9GM2n1yElZx0+Ej3DbKNhNycjFHOL70zWIeRhD9wte4x3oEcT7DtW6klY1zkT642vwQ3MZHW/YI33GYs7C/pAZYhhS98dG4JPmx2y80wTg0Ye1Zbus5VozDaKFte5SbCvEjfQNA16a4jZUM1pycdhVX7d63+NNWMwZo9yt7NpNNc8PUZ9gvxyqFSkrggZHgS1m0dHP3eA0gTr6Kytjd5nHfZG3SZfV4i8q014x+EYo96iaZHQb4lIPt7kWM8dMjvz+SHPHVrCIqHfwWVqb7sjKB+fwFYKlbDqdJE8GjVtCIIgLhcJx8QdXugmyq+e4hhuCU+YkVQbN1bGiD3iEAL2KM0Y0w1ryugdc5r26XCChmnITpiBqbolpwwW+ycD3dfB4EMshoyu7+9c6BdOZNArxLz8jmsl9HKd+TriAfLjrHv9b6aF2SCJblbDFV+Hni7xrWN2G/ibdUW4CUezMEF1qMJo7QTd+hS5zmodNsoaSouBxj3rNum6Yt93ZdTRdY1UhohQWgL0E0E0H69zzOcOjYB8fshzh0Uk9HPwLVOh2h0B+TgsW+mcHFKni+TRS9CGIAjiQjjYMXH34lOY5U/wKMzU7MRAsw50jtIZyCDH13UWFpGa+egGa8hQDP1O5yCmD52ATrkJCoGBtSjGhAOfVnzCu+md0xj0KpKvoLVaZL0dB4BHS+85QQzNap4Z821kC7si/x+zruD2cR2TqiIzW7QcOuvOs5iOSiO1NgV6v7ptv7rCg73eFR/1HiN/c6SCJpKWQP32ICgfrxJ23OcOCeF8LvzcoaUsEvot8C9TIdodYeZjJZGs00+eRwmCIIhDONAx8Qafmh/ik5N5JfiU+iluWhuNksA6cFEyLRONZBeaPdWvwIyDCioJ1hFPJXDuydphEcu00GnAP7CWOcGIYkxsY1lbTpr12BD2YU8TlYkP4Uw93z9YY/TZnEJrxwFYTqHlo7Y95OZlP2ZvqWpikCxD8xzW9qkrQsNAfZLD1tLxcxHbXs9vT0F2xY/Yv24LrCs82fNdWX10kcdx+peCaRHQT5Td+Xg9acd87rAQz+fCzx0WkdBvG68yFZrdEZSPQ7SVTo98nb4zj0ZaG4IgiMviMMfEm8/w8uUTPHjwYH6k8fwL4IvnafvzszdhJtFAybdR0pBI8bbXbUJa00McCjFnjb+9ndQQLT1mr2dMRWS6qDfbpvUuo9vWbSOgIAFnecaGk2YRG2L5nZ13JEfRMxUMctr9GcURMQjtTshmWWbvo9JAaisf76orQsLood3OLtcq8yna5REwKmv2572WAISAZZTQDLynSN22X13hnZh93hU/vYuR6LX3RTAtYvoFsGfH5qjPHRYi+fxMHbpI6GcjUqbCsTuC83GYttIpkazThfJoVLUhCIK4PA5zTDz6BG/fvl07hvauHA8/Htqfw5tJYdme8spGo2Q0F1MfvSIne0VYFruX4dpGwUCvnYrMdNFtnL27rzZ6StaO5RhHDRZIgAfZsnbOvOijltXsEd37MW+CT2X2iLzOZ+6sG4RCo69BdUVI8LgFs9naYdq7FaQapv35tDMpDNSzbXS9DGqXgzGobtu/rvBlj5FyXt8clcC0iOoXhGA+Xn4dgW61UD7f77nDIhL6CZepMOwOkXwcpq10KsKo00XyaBS1IQiCuEyktws9Jkapjvimp5wHQJqsjMaYXkVxVF6uzefrYsujIqpe0dbsIEd8CzmPVb/NArLZujMVn+/GkM6iXYz+DhZ8h7fV6GAThfIIxarH6APXtV0E+SWOiebakYMffLRsteOHjuHMiUR+UaM0O8qdPYLdziK9DERm2Nu7LfNoTEe12EZ2PTAoP6dQBtaMRpG6wlluIxg3YUeaT45vWhyj23Z4LU61yzjQWIsQJ1q3BdUVgfoJvqv5H3DUkDVCaRHTTyTfBObjJUd+7hMj8tzhlrto6RdUpkTKZrB+Yvl4L1tJAcKq00XyaNS0IQiCuFSkHRN3L243lnLc4sVdGEnjIwfMsFxOJZ0fGmttXXtSZ9AyB0h2nSmmWhcYmJtT6g2U5r/lYy1tHqV9ozGzG6bU/H5aDZO8ubVVVbTg222ZyKM2X7/KtKlNkB+YnqO6Rr2L5ECRgH6RxuIhKbxZj0kRcPR3b0ofEYLLHe9ADs3GsvzaZa/qzqN8HfYgUUNhWQc45XO4NBpF64qQ0jxnEW1/NcX9gGCRkmnh2lSx0kbL8nLccXVsguu2/eqKXQS/q9U9jx2yRiQtIvoJIZCP5yce/bnDZmc+F37uIETLXVT0EytTYdkdYvlYxFZShRDrdKE8GiVtCIIgLper649+MBt+9LNzpwOvX79GsXgZu2Ccgy+//BLvv//+Qb+1miXU4y1vY5KPLvR76HbHGI2YyVgcRNxh442nfuzZDZ+54NNezQ7AVs3FN77PotxOoWEOXUYhN+4L6Hh00Lzh52uTamS0lsl/BOknC+knB+knB+knB+knB+knB+knB+knRxT0a7fbePz48fLz559/jtvbW+nrvnr1Ch988MHyc/qnP8R3pK9KRBqr2YR500LLr7/Mt9bS2XFjoFQHKhHpKIcCe/aMjy72MgzP72fQW16/SCK/GRl8F/EqBjf3SGuCIAiCIAiCIO4t5Ji458R0wWjXrJPe8uxwEyLE9JanI8P3/Mz29m8EQRAEQRAEQRCXiNLBLwmCIAiCIAiCIAiCuGzsGRPffPMNvv32W8+Dbw22798O+Q2Hr7MhDof0k4P0k4P0k4P0k4P0k4P0k4P0k4P0k4P0k4P0k4P0k4P0W2E7Jt55551zp8MOfpn8E/9w27PnsxOmJnpEIXiKypB+cnD9qPweDuknB+knB+knB+knB+knB9kvcpB+cpB+ckRBv+FweLJ7RWIpBzVKBBFdqPzKQfrJQfrJQfrJQfrJQfoRBEHcH5R3TFCjRBDRhcqvHKSfHKSfHKSfHKSfHKQfQRDE/UJpxwQ1SgQRXaj8ykH6yUH6yUH6yUH6yUH6EQRB3D+U3S6UGiVCXQyU0j3kOi1kBPf0tJol1JFDLi54i2kPtUkOnVY0tw2l8isH6ScH6ScH6ScH6ScH6UcQBHE/UdIxQY3SmbCaKNWBnF/v2e4sJ1hnWY9kZzksrGYN7WQeOZN9EBZizP6poCXoybCmNfbvXCR1pvIrB+knB+knB+knB+knB+lHEARxf1HOMUGN0nkZj4GK7yh9D9nuiROkGlYThXISg5mOjNFE09Kh7+M9sAwYpt8fp+jVyhjnTXT4x4QmndxTQ+VXDtJPDtJPDtJPDtJPDtKPIAjifnN4jIm7F7h98AAPNo7bF3cHX9KrUeJT4NNXV7iyjzRKTWv7hxafWj8/J12C4XHK+vW8LrF1r7T/eVHFKF0hLftQyXgkR/HDwUKz0EXebCHDP2Z0xOt75pNYBpnM6tCmNdSm2vyzjtZwhuFeng512GVUCpc7vzIucJ196oFdCNUDId1rnUP0s5rpuW6bB0vTPum1mmvvYHXsXV8IXEc4zXtyaP4Lq/0QIez2LEy29NszT8hpY7H2KS3Q/jrnLdNSakKVZvpg/Y7wvkXa+lDsgRDZLr+ieSIAwfewTztEEARBHAep4JePX77F27fu49XT67DSZhuwBb7OfjbDjB9mHuOyttGgsEZdy9qjzPwcswpktU0Dlzf8TgOnlce+99K6CVTN2fw6CXS19OU4J4wSsu1zJyLaGKUCuvmOa4ZEplUBCsyIOVXvIVKIl7tVGa8i0fUo4wHXEasHghGrB8K5VzDBz21OgMbAScfyGBRRHMydZ3ukNz+Yua8zO8xJFnQdsTSHQVj5RuQ6wQjn9ZPkLTGC80Q42hglDbVEB8P5Pcz8GOWt57bQTPPzqjDt8wZItssoKNxIC+kX9vsWaesjYA+I5Qkxgt6DmK1JEARBHBuFd+Ww0O+OkMytLSuI6eg0UhhNVnPh7fX+qQY680YmlqmgkWqj5mpQMmh1OuiYDaQ872WgXmbGckdfBjOMZXRUiyOU6+cyCcOEGXQ1UStkgr5hwPA6pocbnlGHGy62kbTVUYtBH3aQqBWQPuHoZjQIKne8jDvlblXGM9CrRYy6/bWR0KDriNYDQYjVA+HcS4Rg/aask6a74pawst5LoLLWwz9dekUQS3M4hJVvgq8TjFheV+tdiRCGNg7r7XpM79jP3Vtvfo06yskBq4MXNkEGlcFgqVUUCf99i7T1+9gD5yUwT4SCmK1JEARBHB+JpRwmTlFlt3e2Qk6DksrfrC0viOEmn9ro2PCvY+x/cSQ9LzPFmP0lvmHfZHJFYDxVZqrooVhNPtI/YI26yNkJ3GTcyw2WR9xTvQvHmU5amORRjZveDhujj8loBB7gsqY500D5FGNvJ4UFa+23/Qn7atK3/7vJpyinzzc6ehR2lTubEbZsPy2B1OaSoZ3X2aMe2IVQPRDSvUTZ+dwx6PpGb5513ia59eC0guk1J5iEkd7A64ikOUTCyjeB+ViEoLx+4rwVhGieCEGbTGsGs7XpmUqthdlxOtOpjbg7sYzCuxYF6hf++xZp6/ezB85HcJ4QRDAf77Y1CYIgiFMgMWNCg3b9Bs9uF/ElbvFMIr7ENnwkeobZRsNkTkYo5hbfmaxDyMMeuE2TGO9AjybhOE7Cus654MEau3l09OgFUjw7FncW9IHKEMOWvjs2BJ8aOmTnmSYGjTyqLd1nK9GYbUwvrnOTYF8lbqBpGvTWELNh2NPZVSZmjxi3s2k017w4Rn2C/F7D56esB05wr4PhnbfNmQei6U0wg39trfvBa6z3vY5Xmk/FKd+lSF5XLW+FlSfEWHemGbzznKyuLZtbaeOOMWEoPHAQpF/I71ukrY+YPbA7T4gS9B5EbE2CIAjiFEg4Jky8/vRrfNicx5cYPgaep/HsTXiJ24I1qrVxY2XE2iOcIWCP9owx3bBwjF40pjv6w4M1TlAd3u/tPQ/DYv9koPs6GHyIxZDR9f2dC/2C4kb2kci0MBsk0c1quOJr1dMlvi3MnjudnLAeCOtex8Coo+safcUe6Z2gW58i11mtsUZZQ2nvQcQ9r+OV5lNx6ncZlNeVy1th5QlxnMCoGrIT1nl2rUdytBnXSujlOvP0DJAfZxWOMRGgX6jvW6Stj6Y94JsnhDkgH2/amgRBEMRJONwxcf0hmp88xaNFrMvrp/jRxw/x8rNjeSYMNOtA5yiNagY5vo680FxO1zaazABCMfQ7nRKLCTap7jsCTzEmHPj05BPeTe8obmQfCR6RvucEBDSreSTRRrZwrkj7Ua4H+MyDMfI3B2ZaLYfOuhMupqPSSO0/vXmv60imOWooldcFCCtP7EFMHzqBDnMTFLyCT+craK0CwHjEo1GIE+on0tYfZg+cn8A8EcTe7+GYtiZBEASxCwnHxCNs7r9x/e57wFdfI8wFHQ58Sv0UN62NhkJ6ze+KTMtEI9mFZk/1K7DOSAWVBOuIpxKIxqTHTQzUJzlsLdHchTnBiGJMbGNZW06a9dgQ9mFPL5aJD+FM9b5fwbb4CF4PuXm5jtnbpZoYJMvQ9hmWPWU9EOK9QsXqo4s8tvr4oumNba/Vt6eU7xtjZ5/r+KX5VJz0XQrkddXyVlh54qBbt9BpYCv49OayBztGx9mXUPkQpF9o71ukrT/AHlAMvzwh8MM98rGPrUkQBEGchIMdE3dvnuHFMZdtLDFQ8m0oNCRSvH3Z2I96eohDIeas8be3ixqipcfsNYapc00zlsXood3Oru3braE8AkZlzf7s1e+zddsMOkg4yzM2nDSL2BDL7+y8IzkalalgkNPUHP07BnbHdLOcMq0rDaT26vycsh4I817hYfW7GHn+RSy9llFCM4SB3H2u45/mU3HCdymU19XKW2HlCcG7bX1znE786QjWL6T3LdLWH2APnJ+APCF6FeF8vMvWJAiCIE7BgY6JN/j0yUu8/to9N+Lu66+A997dmklxOJbtva5sNBRGczH91SuCtVeka7F7Ga5tFAz02qnoTjPm65ld+3abdhTuVMPZL91r5ISCPR0b07Ujx/bMiz5qWc0eQVVyBPAYhDLaecp6IMx7hQcvu96IpNdAPdtG16uDtJejcr/r+Kf5VJz4XQbmdZXyVlh5QgTWzqdZB3mjd2y5lg7yZVYeOyfwWX5KzmoU0S+k9y3S1h9gD5wXkTwhgmg+DrI1CYIgiFNwoGPiET58wv//brls4+7NC+jPgY9/9CikpLFGoVRHfNN7zYMSTVYNSkyvojgqL9fm83WU5VERVa/oeXawKb5l23ZTw7fQymbrzlR8vhtDOot28ZAI0BGF69ougvwSx0Rz7cjBDz46v9rxQ8dw5kQHV8/QlsCv3MV0VIttZNeDfvKyVygDXob5jvIrUg84y212r1EWqQf2qnPCYMdzz0/ALns9OL1Op892nC2uaDTBX0NjLfpbsH5i1xFJc6hI5huR6wRqI5jXT563fNnnXUJOmzl890r3vUYoVlftvz27pJ1FenEhrl+t7TpHHcT0C6veulSC8kRYdZKIrUkQBEEcn4OXcjz6ZIgyGtAfONuFpp+8xnsvm3ga2nQJPlLJDLnl1MP5obEWxbWRdQYtc4Bk15mSqHWBgbk5pd5Aaf5bPkbX5lHRNxoz20BIze+n1TDJm1vbR0WVRVTr1dTN7YbcqHeRHEQvMJZ6WDwkhTfrMSkCjr7IxuvKE1zueEyHQaKGwrJ8O2Vv6OqIBV9HrB4IRqweCOdewYg8t51q7A7/Epxe/h6qWL0HLcvrg87ejlnx6wSlOQzCyjei72E3Ynn9VHlLLL3B7zIMbfh2jSby7F7a4l61CfID0z2SH9MxNBtLbWz9qqaCo/0OYvqF+75F2nqRc86PYJ4QIPg9iNqaBEEQxLG5uv7oB7PhRz87dzrw+vVrFItRiH6vJl9++SXef//9g35rNUuox1veDT4fler30O2OMRoxS6Y4uBiHzTqe+rFnN3zmXk97NTtwXzUX3/g+i3I7hYY5dBmg3BgsoLPRCfGHn69NqpHRWib/EaSfLKSfHKSfHKSfHKSfHKSfHKSfHKSfHFHQr91u4/Hjx8vPn3/+OW5vb6Wv++rVK3zwwQfLz+mf/hDfkb4qEWmsZhPmTQstv/4y35JNZ8eNgVIdqESkoxwK7NkzPrrYyzA8v59Bb3n9Ion8ZkT5XcSrGNzcI60JgiAIgiAIgri3kGPinhPTBdfnsk56y7PDTYgQ01uejgzf8zPbW5wRBEEQBEEQBEFcIgfHmCAIgiAIgiAIgiAIgpDFnjHxzTff4Ntvv/U8+FZS+/7tkN9w+Dob4nBIPzlIPzlIPzlIPzlIPzlIPzlIPzlIPzlIPzlIPzlIPzlIvxW2Y+Kdd945dzrs4JfJP/EP0z57PjthaqJHFIKnqAzpJwfXj8rv4ZB+cpB+cpB+cpB+cpB+cpD9IgfpJwfpJ0cU9BsOhye7VySWclCjRBDRhcqvHKSfHKSfHKSfHKSfHKQfQRDE/UF5xwQ1SgQRXaj8ykH6yUH6yUH6yUH6yUH6EQRB3C+UdkxQo0QQ0YXKrxyknxyknxyknxyknxykH0EQxP1D2e1CqVEi1MVAKd1DrtNCRnBPT6tZQh3K22p1AAAgAElEQVQ55OKCt5j2UJvk0GlFc9tQKr9ykH5ykH5ykH5ykH5ykH4EQRD3EyUdE9QonQmriVIdyPn1nu3OcoJ1lvVIdpbDwmrW0E7mkTPZB2EhxuyfClqCngxrWmP/zkVSZyq/cpB+cpB+cpB+cpB+cpB+BEEQ9xflHBPUKJ2X8Rio+I7S95DtnjhBqmE1USgnMZjpyBhNNC0d+j7eA8uAYfr9cYperYxx3vz/2bu72EbSO7/3v8kOchNf9EWw2ZExg6WbbPSqFexJpgfxinfyHO9QPRJknIVykc7ISCIJk72ggFlpTgAd9DaOgIUlGxAvnAGlg8CaKBcRFlhta1qcBWYFLA6odTAa5E2tbYhsc48Na5K96gsHyE2ap6qoF74UWU/xKb5J349Nu0UW6+XP53mq6l9PPaUt98/hhPXqdhv11w7xs0P87BA/O8TPDvEDgJvNcoyJkg6WJjU0NOS9Jpc2nXfa57dTcrvAJ197Ta95r6TmM8XGLxbdrvXn0yTnlfOZpHp+frNoWFay+XQDwzmJvord1Stps2EjdwbyKn40isrM7Gi6kFXK/TOV1p21kOUknlIqdfVKnK5o5TRx/nda2XxZ+VCZjv7R0foboo67cvOW5Vyt24qol+VqdVBu3W51MX5Gv3lEy6oWWP78YtOJNlJm2xTVdkelIX6msQlZtnwZ/w5FJ27Jq8/nM+qXCAadVHe6TJjUu7B1s5uiiJ8J3/l0qB0AAIRjkZgoaXMyqfXEgvJnZzo729bd7UdKb9qkJmoVM0nNuPfZl8squ6/CtI4XEnU7C+egKDHuXWV2pyksS+MJ5+CoZk7ugVPS2/EkFo6bLiuxM6zlQvl8PsPaSSQHPjkxvX8eu6rXoJ749lpufkY701s1PSRS2UVpxjnAa+to/HqLtP4GTlM9+bzGN9pd6+C2Irpl2a+LWbvVvfiZ/ebRLMtkXUza9MjbSJNt6mi5iU5wbEKWLatlFZVJJrQyvKyC9/m+RjYWNDMIO+kOl4mLsn5V75Y1vFNb70ym6VtR1ZcW8+FYCQB6r/3ExMEnenR3W09mxxTz3hjTh9vbyszGIlq1op7uHGpkquq2gnhaW+ujOjy56gvv3e8/uq6t8x1IPLWo9dENrdTsbFPKbm1pq7CuUd9l5bS2IK1vpS8HM4yn0lqeO9TCWjuHWIPsRE9zOeX8XqcGJ2rXlHtQtzK85XOgElc6v6XhlRkl271aeC1FV3/N6vjVcjMrNkewQW1FlMuyXRezdqt78TP7zaNZVpBetekm29TpctM94cqWpdyaFkb2nTb4onyltLi/f7ns/tXpMuHWu0pZv6p3KaWX53S48/S8R4nJNP0qqvpyfeodAFxXbSYmStpc39b9RG0SIjZ2kaSIzsZuq4PIyoHw6PSDqtsL4nowPdq4s43Hnf/e0YjvbE517Hxyp+74JjU1Jx2f9vlOu4XCiU5Cf2lYD1K1txtcvu74Ru+aq3QdnjmZ1vKdgn/CJvdUJ4eHcge4XElUusi6XYz9kxRFFau++9T9gU6eev/OuF2Uk+1dbexX9vU3RB13p864vVr2nZMji5Vu1VZEvSybdTFqt7ofv9a/ebTLaj5zwza9rTayxWINtqkr5SYKgbEJV7Zsl+WeVI7WjbsTT/X/U4u6UyYO1ZD7SwxrtObWS5Np+k9U9aXlfCJuBwAA7Wk7MVE4ku7ejtWNMXFgNcZELfdKdFnlbKrm3cLJoeamLt4rOCeE7rAHtbvVuHsCfXiipmMMhhHVfHpiWMOJqvt/++ye0r5XdJMFT6XFvPLZdOuxIdxun3lnukJB++vTWs6mmzxKNO4dTF/M58Gw89bwAyUSCaWzeZXz5+NXDLyo6m+IOu4OTLozra10FwYN7eay2tGT+Jn85lEty0LNdkfYRppsU7+XmxpBsYly/2u+rNoxJnL9feGgK2Ui7vV82BhPKlOVDc+tnWh6MRVimj4UVX0JnA/HSgDQD9pLTJRe6Lnzf8/Xl/T5exmduWNM5Lc18fxhpGNMNHB2LivH67rcj3pXxSLgXZE81mndfii3O+jd/k60s3aqqa2r+721kND8dbok3zFF5z8ppZsmGJqIx5VKp8MnF57O9P9Btq126q9xHXcHJj3Rcr4bj7Lt5rJaMGm3eh2/+t+8k8uqZtymR9VGmmxTn5QbYwGxiWr/G2JZxyvz2p3aOp9mX9PH4308xkQXy0Qqq/L+iHbGE3rNHZcmOe8+Xqv2iVEm0/SVqOqLyXw4VgKAfmD3VI6JD7U6dn7zRmxMswsPdbT3RYS9JqrllFmTtjpyUJfSlHvv8UzmsvtzLuMcAGku8iV1VWJKW9Un1vG0FtdHA7paM8ZEhduFvotLS2/1+UG2rU7WX/f8d00ny93pbdLNZbUWXbvVmW3y/827Ez/D2LTVRjYy2ab+KTeGIopNpMuaXlT2atCQvh4joatlwn0yym5lYMvC8rRGtKHxmbonlphM00eiio3RfLpZ1gEATVklJtxbOWrEErp/VOhAYsLtUn+qB9m6kxqD+8BNpbIFrY/sKOF145txDmAXtTjsnIiPDmsQOt36ijfef+t1s202bkbhRIeMMdGoWGxI0lSPDeG9vO7FNuNDVLra+g8SOOgs6q9RHc9p7WRK2a6c8XVzWcEC262exa/Jb97F+Bm16WHbSF8m29Rf5cZIUGwi3P+a/g71t414YyT05e2W3SwTbo+AXU2d17W499jpgvZHFpS46nJiME0/iSo2hvOJpB0AANhqLzERu627Ea9IcznN+x7guhIaHnX3HbW7juJpOwmFeOUef+8xUXll03Hv3ujagb0GSzE3r0yIYw4vbn0+EFZPuLdn1CVpLsaGuHzPKzuWV3dSi9qfSlyzAyHb+mswTW5XGxvjVc+fT2jhUDpcSHh/R3rc3c1lGQlqt3oRvxa/eVfjF9ymh20jfZlsU9+Vm2DBsYlu/xu4rCiTIN3QzTJRfKod1cfb2Wctrmv04sTaZJp+ElVsDOcTSTsAALDWZo+JMb33UNr+/KD27VJBR/cTET6Zo+hddVusO8DNZS66H/qNAO43UrjZsnI1j1HIaXdjVNMPBvU0Pae18Q3t+B00Nkk++A5ShwgVap7I0djz4qlWxhPeFaz+uwLYjijqr8E07r3TNc+fL3gjr4+uF7y/I71K3c1lGQlqt7odv4DfvKvxC4pN+DbSl8k29V25CWISm6j2vybLcm/N8Xnii9vLrx97NXa7TJj0GunLniVNRBUbo/lE1A4AAKy1fSvH2IePdX/7oSYvBrssHXiPEH24MBtZYiI3v6Y79Vfd3MHUTq52FvH0suYOFy7vzXfvJ1w4nNOy34hO3gBa7iOzGq8PuI+SGh9fq3TFd5/GkBzXxtxyHw8MFaRyIOedDJ+/U8xlNLMgrfuNwu3GdWNO5CU6KVHzRA735V7RvXriR1r5cuWpBn13oN2GqOpvqDrecn2S3mjrRsN4tGgrus6y3epm/Ex+824Jjo1ZGxmq3FwbZrExKVvB8TNblnd1f2NcyYsZub/pyobmlgdlMNH2BMYvntby3IbGqwdPdmPjBvAiQWQyzQCKpm6GPFYCAHRO7KPvls/Oztp75R+XH95X2ZmN87pffridb3te2Wy2XGu/PKeLede+RtcLtZMWnGlHzz8fnSvv133sP6/Rcu1squbhfDZXv4w+d3x87PNuoby/PloerdrmucbgePbn3M8CFrI/V1bgRIPJP37NFdy4+paRQrng87Y3/dx6eX9/3+i1Ptds/v2pMX5R1l/DacqVODer524Zb6z39UzaiuBlheVf/iJst7oSvxC/ecCywmoav8DYBLeRZuXmfG4G2xTldkfFav8RULbM4me6rPXa37RZQe6yVvsP2zLRdvwavmAyTW+0G7/o6qb5sVI/Cnv8glrEzw7xszMI8XPP0avP2f/0T/80kvm686mer5uTeM39n/xHP2k/sxGRvb09zc0N+FMweujZs2e6d+9eW98tZua1difr3z3SvarydFc7O8c6PDyU5va9K/rXjW/8nG3PNen7erq7oh1Na3nqTt3741rYGNV6IV9z1bqYSWpGW8obXqV2p0+cLA9MrG3KH4ifLeJnh/jZIX52iJ8d4meH+NkhfnYGIX4bGxuamJi4/PvLL7/U5OSk9XyfPHmid9555/Lv5I++r9et54qBVsxkVHiQVbbZ+bL7SLa083qQ0/ya+9jzwThRjoSz7akmcfFuw/B9v6x01u8bI5quH1G+lTvL2n9wg2INAAAA4MYiMXHDxdOG9+c6J+lZ3xNumIins76JjKbTpxofXwYAAAAA11Hbg18CAAAAAADY8npMvHz5Uq9evfJ9lcvl0J+18x2Xe58N2kf87BA/O8TPDvGzQ/zsED87xM8O8bND/OwQPzvEzw7xu+IlJm7dutXr9fAGvxz545Gmn5cflbu4NoNnEAZP6WfEz44bP+pv+4ifHeJnh/jZIX52iJ8djl/sED87xM/OIMQvn893bVkDcSsHOyVgcFF/7RA/O8TPDvGzQ/zsED8AuDn6PjHBTgkYXNRfO8TPDvGzQ/zsED87xA8Abpa+TkywUwIGF/XXDvGzQ/zsED87xM8O8QOAm6dvHxfKTgn9K6f55K6mtrJKGT7Ts5iZ15qmNHXHcBGnu1o5mdJWdjAfG0r9tUP87BA/O8TPDvGzQ/wA4Gbqy8QEO6UeKWY0vyZNNTt79k6Wh52T5fRAnixHpZhZ0cbItKYKzh/GgTh2/rOorGEmo3i64vzv1EDGmfprh/jZIX52iJ8d4meH+AHAzdV3iQl2Sr11fCwtNr1Kv6vxnS6vUL8pZjSzMKL9clqpXEaZYlrpMNmDYk65QrMPT7W7sqDj6YK23D+HE9ar223UXzvEzw7xs0P87BA/O8QPAG62tseYKG1OamhoyOe1pIM25+m3U3K7wCdfe02vea+k5jPFxi8W3a7159Mk55XzmaR6fn6zaFhWsvl0g6Wo3HzyPH6vKTmfkdVmjdwZyKv40SgqM7Oj6UJWKffPVFp31kKWk3hKqdTVK3G6opXTxPnfaWXzZeVDZTr6R1v1t5ip+vzqlWwS1Fb1t1puvvk8ggS3A5U6FXVb0V77Z7YuUf8OrQW3OUbtekitTmqM2/2AdTEtf82Fa49tynFY/vHr3vqG3f92MzYmGuJnXKfs99HFTLJhOZWXczxUM6H5sVK31cfPeJuMtI5xtMsCALSr/cREQXq8ndfZ2dnVa/uhHm6vaiyilXN3FjPuffblssruqzCt44VE3Y7d2dEmxr2rzO40hWVpPFG/M3F3xpWD98TCcdNlJXaGtVwon89nWDuJ5IAnJ5wT6WRCK8PLKngx3NfIxoJmBnujeiY3P6Od6a2aHhKp7KI045zM9NMRXp8wq7/S9P7551Wv2uRMcP2tkZvX+Eb76xzUDuTm3Tq1pfz5uhamj7XQ0ObYM4mfybpcbNPVfJY1vNPO72C01oFtjmm5sGfW7hvtY8KUv6ZCtscW5Tga3Vvf0PvfnsfGTHCdimYfXTiR1vcLtcvan9Pc/nkS3WNyrNQ/zLbJRHCMo1sWAMBGm4mJkl4kFjQ7Fqt5b/PzhD6MKivh7Eye7hxqZKrqtoJ4Wlvrozo8ueoL793vP7qurfOdfTy1qPXRDa3U7NhTym5taauwrlHfZeW0tuDsmLbSl4MZxlNpLc8damGtX3fbBnJrWhjZdw6ELmKY0uL+/mWs/J3oaS6nnN/r1OagfLC5B87eCWBD7OJK57c0vDKjZJ9dgeots/prJqj+1i43s9LuGYt5O1C9DfH0ltfm7EbaVJjHr/W6uPOpbNPVfFJKL8/pcOepXe8pP4FtTpTlIkhQuTFdlzDlr4VQ7bFNOY5I19Y37P63D2ITlbb20fWKOnVOutOpuoTH7rAWq86qzY6V+oXZNhkxaJMiWxYAwEqbiYmYZmfrMhAHn6jw3qxi/l9o20bLo/3KgeXo9IOq2wviejA92njQHY87/72jEd/ZnOrY+eRO3bFAampOOj6N/uC9KyoHb6N14xTEU0FPeRjWg1Tt7QaXrzu+0bvmKl1AZ06mtXyn4J+wyT3VyeGh3AEuVxKV7uBuV1H/JEVRxarvPj1x3jp56v0743Y1TfbvFax2tK6/8i5VnZjMqFX9rVLMuL1a9p0DbsMVrPmyWTuQypZVyNYfsY52ZEiQoPiZrcuhGs75E8Marb4ty/R3aMm8zQksF1ExKDdG62JY/poL1x5bleNIdHF9Q+5/ex8bQ4F1qt19dL240um6NsA5GT+Zqh6kOsSxUl8w2SYTJjGOalkAAFtt38pRq6TN9Sh7S7jcK9FllesOugsnh5qbuniv4JwQusMe1O4+4u4J9OGJIrn+FtV8uu4qNrX3Vub68CCkTxXdZMFTaTGvfDbdemwIt4tu3pmuUND++rSWs+kmjxKNewdFF/N5MOy8NfxAiURC6Wxe5fx16TpqUn9dw85JdNV9zzbjDbgDk+5MayvdgQxBXTtQfcCfc0+URpbDDYIayDR+QesS93pHbIwnlanKlOXWTjS9GPXvYNLmmG9X53VzXUK0x50sx8b6ZH3r9799ERtTQXWqU/to92S8/mp/F46VOspvm0y0E+N2lwUAsBVNYuLgE+1NvBt5b4kGzkHJyvH61Q7Du9ISAe9K2LFO6/ZUud0B7i56HpvjlXntTm2d3z+9r+njccaYMFJ0/pNSummCoYl4XKl0Onxy4enM9U8a1ddfz4l21k41tXV1j78WEpoPfUHdHZj0RMt5i6tcIduByoBpCY2fOCdK3TiK9Y2fwbqksirvj2hnPKHX3LESkvPuo3fqEikR/A7ttjkttqvrOrUuxrGJoBxHoZvra1zv+iQ2xgLqVKf20bk17dT0jFB0x0q94rdNJtqJcbvLAgBYiyAx4faWeK6JdzudlsgpsyZtdeSgJKUp937WmYuRmt0rj86OTHORL6nrpheVvbpx1+DecsaYqHC7bndxaemta540alJ/E1Paqk7+xNNaXB8N3dW/6Mz8ZNm2t0m4diCezlcGkZs60UzHB8pt3f61XBd3JP7dyuCXheVp5yRwQ+MzdSP/R/Q7eEK1OZ1s18PqwroExCaachyhrqyvWb3ru9gEMa1ToffRrbhX+481/aD3tSk6EWyTcYyvY/wAYHDYJyZKX2hPE+psXsLtUn+qB9m6A0are35rpbIFrY/sKOF19ZtxDooWtTjsnIiPDmsQOo02U99107u3vFnXzcKJDhljolGx2JCkqR4bwnt53URtxoeodLmPfgDAftCk/rrijfdTe92LQ43tktPayZQahlpoQzvtQDyV1da6OjhQbov4Ba6Le5V5V1Pn3417j6QtaH9kQYnq7hCR/A4V5m2O+XZ1XnfWpXVsoivHUenW+gbXu/6LTSDDOhVqHx2k+FQ7mlbDeXWEx0pd12ybQjCOcQTLAgC0zzoxUfpiT0dRrElTOc03PWBMaHjU3c/XHjoXT9tJKMQr9/h7j4rKK5uOe/cajw5ql742DkS8uFUPiIcK9/aMuiTNxdgQl+95Zcfyal5qUftTiWt2O0er+utezJ9XxvZ8PrerjY3xqmfPJ7RwKB0uJLy/w90WYtIONP5C7Z7EB2sdv8B18Q6069tCpzwvrmu0an0j+R1CtTlB29VNXVgXk9hEWo4tdX19A+pdP8XGUGCd6kCyoPh0R4e+n0R5rNRdzbfJQMgYWy0LAGDNPjFR6GRaouhdxVqsO2DMZS66fPqNKu03+rTZsnI1j1HIaXdjdIC79LndY31GnHd7RTQ5EOnNAHQ3SaHmiRyNPS+eamU84V3Jvh79JoLqb05r4xva8TtYDpMgc8dQqH7+fLngjdg/ul55Ln24q6xB7YCzTUnnZKjuTKjYkducguJnuC6BV18j+h2M25yg7eqmbq2LQWwiLceDtr4B9a6vYmPCpE6F30cHcffh/qI8Vuqu5ttkIlyM7ZYFALBlmZgo6cXzaFbET25+TXfqr2K5g5OdXB0sx9PLmjtcuLw3370PdeFwTst+Q+R7AyG5j87zubMwM6Px8bVKV3z3aQzJcW3MRT3Sfnd5V0U3xpW8uOHc3a6VDc0t+1wZdOO6MSfyEp2UqHkih/tyrxJePfEjrXy58pSAfr6CZSq4/lYOGr2EzcXHuYxmFqR13xEem9dfs/VJeiPjtx6H0awdcJ9UWLvOh/71yoJJ+xe4LvG0luc2NF49sKq7XW6QL09IzH4Hk/iZtDmm2xWZFuUm1Lq0nE80seknUa1vlPVucJjVKbP6Ehy/8y+rVX401LFS32i9TdHWu9bLAgB0nmViIqbbd6NZkUbuFRPngPqy6+b5K+Hs2WueSZ1StrCvkZ1Kl87EjrRfqO9Sn9P8+XfdfPiGOzp93c7M22mPni8vsaKT6ULDY+QGjnNSki+sX8bG267lgu/Vpdzajkb2B2hgsb5VdIek8Fc9JkXAy+tJMdDM6q97b/myVjRz/nli3C2HW3UnJMH198LF0ymuunmHG5QyuB1wHzFZ0LSzzomLdV450fS+f71qn0n8zNbFjfH+8FWML7YrXxVks9/BQGCbY9quRyGo3Jiui3n5aylEe2xbjiPRxfUNs//ti9gYMKpTIWIcLK7Ww0CZHCv1m6BtMpmFaYwjWBYAwMprsY++W85/9JNer4f29vY0N3cNnoLRI8+ePdO9e/fa+m4xM6+1O1n/gyH36sLTXe3sHOvw0DkSnNsf/ISND9/4Oduea9IH/nR3xRska3nqTt3741rYGNV6IV9zAOoeTM9oq+ZksBV3+sTJ8sDE2qb8gfjZIn52iJ8d4meH+NkhfnaInx3iZ2cQ4rexsaGJiYnLv7/88ktNTk5az/fJkyd65513Lv9O/uj7et16rhhoxUxGhQdZZZudL7uP1ko7rwc5za9JiwNyohwJZ9tTTeLi3Ybh+35Z6azfN0Y0XT8yeCt3lrX/4AbFGgAAAMCNRWLihounDe8Xdk7Ss74n3DART2d9ExlNp081PmoOAAAAAK4j66dyAAAAAAAAtMvrMfHy5Uu9evXK9+U+iivsZ+18x+XeZ4P2ET87xM8O8bND/OwQPzvEzw7xs0P87BA/O8TPDvGzQ/yueImJW7du9Xo9vMEvR/64+ZDI5UflLq7N4BmEwVP6GfGz48aP+ts+4meH+NkhfnaInx3iZ4fjFzvEzw7xszMI8cvn811b1kDcysFOCRhc1F87xM8O8bND/OwQPzvEDwBujr5PTLBTAgYX9dcO8bND/OwQPzvEzw7xA4Cbpa8TE+yUgMFF/bVD/OwQPzvEzw7xs0P8AODm6dvHhbJTQv/KaT65q6mtrFKGz/QsZua1pilN3TFcxOmuVk6mtJUdzMeGUn/tED87xM8O8bND/OwQPwC4mfoyMcFOqUeKGc2vSVPNzp69k+Vh52Q5PZAny1EpZla0MTKtqYLzh3Egjp3/LCprmMkonq44/zs1kHGm/tohfnaInx3iZ4f42SF+AHBz9V1igp1Sbx0fS4tNr9LvanynyyvUb4oZzSyMaL+cViqXUaaYVjpM9qCYU67Q7MNT7a4s6Hi6oC33z+GE9ep2G/XXDvGzQ/zsED87xM8O8QOAm81qjInS5pImh4Y05L0mtbRZsloZv52S2wU++dpres17JTWfKTZ+seh2rT+fJjmvnM8k1fPzm0XDspLNpxsUxUzyPG71LydG7c505M5AXsWPRlGZmR1NF7JKuX+m0rqzFrKcxFNKpa5eidMVrZwmzv9OK5svKx8q09E/+qr+NluWAbP5FJWbv6pfyfmMbJuLVgfltu2WyTZF3f5147eq1nb5q5Kbd37LttalUh6C4xd9uYlK0Emhf2xMtztY8G8V3bI6ob34KVT711QxUxW7q1ft8q5p/AKYHgd1ok0CAITTdmKitDmp5F5CmbMznbmv/IISe0lNWiYnqrk7lBn3PvtyWWX3VZjW8UKibufk7NQT495VZneawrI0nqg/8XZ3/JUdcmLhuOmyEjvDWi6Uz+czrJ1Esq923GEVTqT1/UpcLl/7c5rbPz+xRii5+RntTG/V9JBIZRelGecgpq2jyeutF/X3alnLGt6pX1ZU61xUJpnQyvCyCt50+xrZWNBM5I1FNO2WyTZF1/5177cKEno5uXmNb7S3rNy8Wx62lD9fVmH6WAsN5bhb5aYDmsTGbLuDmfxWUS2rJ5qWLZP2z8z0frl2X1+uTXJfz/gFMzkOMmv3AQCd1mZioqQv9qTHmVnFLt6KjWl24aGO9r5QNKmJop7uHGpkquq2gnhaW+ujOjy56gvv3e8/uq6t8x1wPLWo9dENrdTsUFLKbm1pq7CuUd9l5bS24Oy8ttKXgxnGU2ktzx1qYW0gdts+ijp1DoDTNWMaOAfGu8NabJmVONHTXE45v9ep/4nGTeAeuHgHdQ29GeJK57c0vDKjZLtXu66lbtZfd1mV+nu1rJTSy3M63Hka4oq02Tort6aFkX2nLFxMl9Li/v7lNkQninbLZJuibP+69VsFCbscp21cafPM51x1GYmnt7xyvFsdvq6Vm6i1jk3gdhvM3/S3sl9WLzSPn1n7F53rFj+T7wYfBxm2+wCAjrO4leNIhfoMRCyh+3dvXyUrIrDRcq9Z2aGMTj+our0grgfTo40Hn/G48987GvGdzamOnU/u1B0fpqbmpOPTvulqG45zwpyuy0A4B8YnU0EDVw7rQar2doPL1x3f6F1zle6vMyfTWr5T8E/Y5J7q5PBQ7gCXK4lKN1C3i7Z/kqKoYtV3n544b5089f6dcbt4JwfkCpahrtRfz6EajiETwxpt49ajoHV2D5JH68b/iKc69PSUiNqtltsUdfvXxd+qNfPlFDNub6h950StvSWlsmUVsvUZ39GqYWK6XG4i1Co2wdttKvi3im5Z3dU8fiHavyCFE50ETHL94mfC/DiodbsPAOiGNhMTMa93xPbDSW0eXJHBBUcAACAASURBVGUnDj4paOLDsYhWzb0SXVa5bkdaODnU3NTFewXnhNAd9qB2FxN3T6APTxRJrjuq+fSce2Ac1FsCNYpusuCptJhXPptuPTaE220270xXKGh/fVrL2XSTR4nGvZORi/k8GHbeGn6gRCKhdDavcv663GbTzfob966ubownlanKBuXWTjQdqsCHW+fasQJy/ZXAvIyfyTaZzCcqUf1WES7HHdB2Z1pbabsztKtSXFTOPZkaWa667WtAyk09g9i03m4T5r+V/bK6rGX8ojx+GdZwomqsiiZjJFyv+LU1Q5/jIMs2EgAQmfZ7TIyt6mz7rvYeJjU0OanJySXpw1XNRtldop6zk1o5Xr/aqXhX+iLgXd071mndfjy3a9e1t6/k1rRTc2UGrRWd/6SUbppgaCIeVyqdDp9ceDrT/ycptjpVf12prMr7I9oZT+g1d4yD5Lz7eBn7g+4m63y8Mq/dqa3z+5H3NX083v2xAtptt+q3qdvtX6d+q7aW4w5oe6LlfDSPQK4MtJfQ+IlzMlV99tNP5caYeWyabrepEGXCelldExC/KNs/nWhn7VRTW1djJGghoXmfTgDXJn7tMD0Oqm8jAQBd0X5ionSgpc8rg1/mFyZ0V9t6mN6MaHwJPzll1qStKHdSl1Kacu+nnrkYId29muAcQGou8iX1hnuV4FjTD0wixxgTFW539C4uLb3V5ycptjpZf1UZ2X63MnheYXnaOdHe0PiM7RMPWqzz9KKyVwMydGCMBBPttFt+29Tl9q8jv1V7yyk6wThZjq6XUjydrwwsOHWiGb/BQ/ui3JgJE5vA7Q5cmHmZsF5Wl0RdtlpKTGmrOokeT2txfdT39oSbGz/T46AO76sAAE21PfjlZvpzvbdaGfwyNjar1Sd5bd99pOTSQaQrWOF2qT/Vg2zdjqLlfczhpLIFrY/sKOF1g5xxDsoXtTjsnIiPDqvPb8EMVnyqHU0rcH9cONEhY0w0KhYbkjTVY0N4L697ts34EJXuzNdzsK1O11/3ytqups7nH/ceu1rQ/siCEn6XDI00Wedz9d2vvfvhe3DbV7h2q/k2da/968Rv1e5yclo7mVLDbfcRiKey2lpXw+Ch/VJugrUXm2bb3Vp7ZaK9ZXWLQfwiPH5xk1wNwzK7++sWY8QMfPzCMjoOat3uAwA6q73EROkL7TmHq7V3bcQ09uFj3X/+IuJeEznNN91RJDQ86u57a3e9xdN2DqjjlXv8vcdF5ZVNx717DEevwe0Pxac7OjSZzo1b5APQXQPu7Rl1SZqLsSEu3/PKjuXVndSi9qcSfXn1tH1dqL/eAWf99M5vtriu0bYGr22xzlGeTETCtN1q9TuEmY+lyH8ri+XkdrWxMX453oPbvX3BaSgPFxLe3+HyJD7381efGPZduQlgHJuA7TZhXCYiWFa3GMUvuuOXYm5emcDyet3iF07wcVBQGwkA6LT2b+U4KnTwto0LRS97vVi3o8hlLrp4+o1g7TfStdmycjWPUchpd2PU8PaH/uaeYJhOx2BPnVSoeSJHY8+Lp1oZT3hXCfvvCmo7ulh/I7vqHLTO7m0PPiO4u72NetK7yqTdCtom0/lEpFs9BIKW445rUC5XvQreyP+j6wXvb/OrtU58k84JU93ZUrHm1rd+KzcBjGJjst2GAstEhMvqBqP4RdX+5bQ2vqEdvwTH5YWG6xi/cFofB5m0kQCATmsvMRGb1cLDbT1cOrhKTpQOtJl+JE28G9njQnPza7pTn712ByU6ubqqH08va+5w4fLefPe+xIXDOS37jprlDjblPpbM5yn2mRmNj69VuuK7T2NIjmtjrs9HrDZSlNGxhxvXjTmRl+ikRM0TOdyXe5X66okfaeXLldHB++5EpQ1dq7/xtJbnNjRePXioW4dnFqSqA/zK7Tat76k2WWfvSu7GuJIXM3KXtbKhueVOjZ9h126ZbJPZfILjF7jOhr+VtQiXY7rd7tMMLyYp5jKaWTisKRNdLzddErTdgfEL8VsFLWvQmLR/weWvkvTyEt/n71RiI63Xjd543eJn3ia1Pg4yaSMBAJ3Xdo+JsdW8thPrSg8Nach9JddVmMjrSWSP5XCv2DkHK5dd+c5fCWdvW/Pg7ZSyhX2N7FS6+CV2pP1CfZf6nObPv+vmzDfckb/rdmbeAcLo+fISKzqZLjQ8PmowxWUyNERubUcj+9flUZW9VHSHpPBXPSZFwOtp0EPp+1536687RsL+8IpmLpdTqcP5UJlFw3V2TqTyhfXLdfaWtVzowFgFUbRbZtsUXfvXrd8qWJjlXDyp4Kq7eJhBAd3HDRY0rZXzMTqccrxyoun9ujLRtXITreaxMdxuA8G/VXTL6rbWZcuk/Qvmxm9ZV/FLjLv7862qxOJ1jZ+pVsdBpvsqAECnvRb76Lvl/Ec/6fV6aG9vT3Nz1+UpGN337Nkz3bt3r63vFjPzWruT9T9Aca9cPd3Vzs6xDg+dI4O5/WuSsKnlGz9n23NN+hef7q54A2ktT92pe39cCxujWi/ka642uwdXM9oyPvlyp0+cLA9MrG3KH4ifLeJnh/jZIX52iJ8d4meH+NkhfnYGIX4bGxuamJi4/PvLL7/U5OSk9XyfPHmid9555/Lv5I++r9et54qBVsxkVHiQVbbZ+bL7SLu083qQ0/ya+2j5wThRjoSz7akmcfFuw/B9v6x01u8bI5quH5G/lTvL2n9wg2INAAAA4MYiMXHDxdOG95c6J+lZ3xNumIins76JjKbTpxof/wYAAAAA11H7T+UAAAAAAACw5PWYePnypV69euX7ch/NFPazdr7jcu+zQfuInx3iZ4f42SF+doifHeJnh/jZIX52iJ8d4meH+Nkhfle8xMStW7d6vR7e4Jcjf9z88RHlR+Uurs3gGYTBU/oZ8bPjxo/62z7iZ4f42SF+doifHeJnh+MXO8TPDvGzMwjxy+fzXVvWQNzKwU4JGFzUXzvEzw7xs0P87BA/O8QPAG6Ovk9MsFMCBhf11w7xs0P87BA/O8TPDvEDgJulrxMT7JSAwUX9tUP87BA/O8TPDvGzQ/wA4Obp28eFslNC/8ppPrmrqa2sUobP9Cxm5rWmKU3dMVzE6a5WTqa0lR3Mx4ZSf+0QPzvEzw7xs0P87BA/ALiZ+jIxwU6pR4oZza9JU83Onr2T5WHnZDk9kCfLUSlmVrQxMq2pgvOHcSCOnf8sKmuYySierjj/OzWQcab+2iF+doifHeJnh/jZIX4AcHP1XWKCnVJvHR9Li02v0u9qfKfLK9RvihnNLIxov5xWKpdRpphWOkz2oJhTrtDsw1PtrizoeLqgLffP4YT16nYb9dcO8bND/OwQPzvEzw7xA4CbzWqMidLmkiaHhjTkviaXtFmyWxm/nZLbBT752mt6zXslNZ8pNn6x6HatP58mOa+czyTV8/ObRcOyks2nGyRG8Qtj5M5AXsWPRlGZmR1NF7JKuX+m0rqzFrKcxFNKpa5eidMVrZwmzv9OK5svKx8q09E/2q6/VdP6f1xUbj4ZWDejKusm8+lEW9G59s8sfmHa0eYMllXMVG3T1StpGcTOlT8zJmWin/cxQSeFufng38hkmmYCY9OhchOVxvgF14ViJtmwPZWXU//CrkBQ/R24+JnW30qcL7dnPqPQW9RGbGzKOgDAX9uJidLmpJJ7CS3kz3R2dqb8QkJ7yUnr5EQ1d6c9495nXy6r7L4K0zp2llO7M3B2xolx7yqzO01hWRpP1O/U3R125QAhsXDcdFmJnWEtF8rn8xnWTiLZVweOYV1s01X8ljW8Ux8/mMrNz2hnequmh0QquyjNOAdM7Z3FXWvG9TegbubmE1oZ3lL+fD6F6WMt1NXxqMq6yXy61VZE1f6ZxM+sHQ1mtixpev98m6peUSfkzMpEcPkLs6xWZWKg9zG5eY1vRDBNE6ax6Ua5iYpJXSicSOv7hdpt2p/T3P558tt8aUb1d5DiZ9b+FZVJunFeVsGbbl8jGwuaaaNShYqNRVkHADTXZmLiQJ88kh5nZjUWq7wTG5vVwsMjPfrkIKJVK+rpzqFGpqpuK4intbU+qsOTq77w3v3+o+vaOt+BxFOLWh/d0ErNjiml7NaWtgrrGvVdVk5rC84Bwlb6cjDDeCqt5blDLayFvm7RJ9z4VbbpKn4ppZfndLjztMUVhRM9zeWU83udtn/gPujcgyTvILPhQCWudH5LwyszSrZ9lfk6Mqu/wXWzovo78fSWV8d3L6tmu2Xdb52D5tOttiLK9i8ofubzMRG0rO4wLRNm5a81kzIxyPsY5+RvJegszGSaZgY5Nq0FtVunzgl1umbcISeOu8NaDJeViLT+9gfD/UduTQsj+85++WK6lBb39y/j0Kl1a7+sAwBaaS8xUXqh57qr27Hat8feeyg9f6EIO01oo+URbWXnNTr9oOr2grgeTI82npDE485/72jEdzanOnY+uVO3L0tNzUnHp+G7BfaNQ53Uj2eQGNZoy9sxhvUgVXu7weXrjm/0rrlKN9GZk2kt3yn4J2xyT3VyeCh3gMuVRKXLqdud1D9JUVSx6rtPT5y3Tp56/8643VGTbXTh7WOt6++5VnVTbq+UsgrZ+iP10bohONop634C5tPltiKK9i84fiHa0QBGv1XhRCch5tk+wzIRUP4CmZSJAd7HFDNuT7F950TXbprmXzaMTdfKTTSC60Jc6XTd586J9slU2MGlDevvgMXPFdT+uQmC0bqxmOKpNp5kFSI2VmUdANCS1RgTvo4KESUm3CvRZZXrduyFk0PNTV28V3BOCN1hD2p3Q3H3BPrwRE3HGAwjqvl0Xdy7OrgxnlSm6gw5t3ai6bCXY26qopsseCot5pXPpluPDeF2+8w70xUK2l+f1nI23eRRonHvwOliPg+GnbeGHyiRSCidzaucD9uFt1+Z1N8wc7tQVM49MBxZrrqlJqqybjmfSNuKaNu/1vGLth1tvSzXsHNyVnU/fBRj3/isRV+0fybx6+d9jDvY7860ttItBuI1maZdNbHpRrmJVnBdqOaeaIfvLWFefwcpfuHav9oxJnJtJPoMY9PJsg4AaDMxEbutu3quF3UZiIPPtyNYpRacncLK8frVjtu70hIB72rZsU7r9kO53QHvrpfKqrw/op3xhF5z76NOzruP3Aj3FIkbq+j8J6V00wRDE/G4Uul0+OTC05k2D6gGSH39Df119+AzofET58CwfiZRlfWg+fSyrbBs/5rGL6p21GRZnhPtrJ1qauvq3nEtJDQfdVehbrV/JmViIPcx7mC/J1rOt7qCbzJNAOPYdKncRKx1XaiSW9NOTa8H0wWY1t/BjN+lJu3f8cq8dqe2zrdpX9PH422MMWESmwjKOgCgpTZ7TIzpPXc8ifTmee+Ikg42l/S5Hka4avVyyqxJWx3ZKaQ05d7POnMxmrN7dcPZ2Wku8iV1lTtK925l8LfC8rRz8Leh8ZmgEasZY6LC7d7dxaWlt9o8oBoU9vU3ns5XBnabOtFM/cB4bZV1H4Hz6VVb0eH4RazlshJT2qpO+MXTWlwfNbvtJ4yoykQgkzIxePuYolPgTpZb9+AymSaYYWy6VW4iZlbv3N4Sx5p+0MGdzoDGr6JF+ze9qOzV4CRtjC0ko9hEU9YBAK20fSvH2Gpej+/uKek9LjStz/WhPkw8l+4nFAv+ekhul/pTPcjW7ZRs7guuk8oWtD6yo4TXjW/GOSha1OKwcyI+OqzB7LTnZvd3NXUes7j3KMqC9kcWlGh2iaRwokPGmGhULDYkaarHhvBeXldSm/EhKl3PDxtuir8OmtTfNsVTWW2tq2pgvDbKui+z+XS/rYi2/WuIX4TtaOCyKm82lAOv23mkYy1EVSbMmJSJwdrH5LR2MqWGIRJCT2PGKDZdKTed41sXLhSfakfTaisvYVp/BzZ+rfcf9beweOPIhL09KjA20ZV1AEBzFmNMxDS7+sR7VOjZ2ROtzsZUKhzp/sS7EScmcppvulNKaHjU3XfU7laLp+0c7MUr9/h7j4nKK5uOe/czjrbTtbIfeAc69TGIK7W4rtEmByJe3EIPFngDuLdn1CVpLsaGuHzPKzuWV1NSi9qfSvT5QWJYreqvqcaI1Bw0tlHW/RdjOp9uthVRtH8B8Yu0HQ1altuRYV6ZTl+kjapMGDMpEwO0j8ntamNj/PK+ffdWh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" alt="表3"><br><img 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NDFh0Lvv2LEtgzKoDrnHXvy3BMR472bJD42IBcv6R+LU8C9E8x1n1WKa1aMf1z/kBze/7A0/u4hGX1yszQU08jMQWnbtU/OFvShFudAgW7rmGzc/ox0LiymMw5W/os8FXlYOl+4R849sNbzx/IHHJIBDAAAABSPwESV0YO8LZnbAsmYCJDOGjAG4PmDEskn76kkAmdDTgEXJZ41yE3sMdqSdtnpNBhVmRRGQ3pXKjgw2CbT1tkUsS2ys904Z7tHJKbPWUy2DBqDzLzHYO7bEjCanO2zOVBN9y01at3SFZeOgd0yEuvLmRkwNtDh6Ql83GMfQ2WcX+N0avredL3oBpdjTwYFJJh7x+d1tyvPa1YvDSs3y3B/VA+w//NsVGS/JVNg+mFpPJL5ic5to8lvmnqzBvmeMwdSGQxORv9rn5w12h4uNCih2xx1f890rzSeyvVidqDkpf3rPWVN3O+thxXlo48+kvPnz8uFCxfk3XfflatXr8p1110n8+fPl5tvvlkaGhpkyZIlehuqX5AFzwCglixfvrzk+3zrrbcCa2su60pYEZioNmqA3Z0aYGfwkjERTWUJeEvFz5IrE2JySLp7JBUESYiKS0TbnbIGnFmfMusBfr60/1Q/rNRgd0DvNzb7Of2+1DBx6KLR78GMfl8a7pDdloBOpHWrtI93y3CiteA0ex0wWuN8fpJ+jCPzAAAST0lEQVRBCzUYthyTMSDuihvbu/dIJEcWQbk+fc+S855UBqTDOlKPqmvbJ8apcGlrXJp35g7YpN6o/zeIe8fPdbcr72u2Vnb1H01+a3zdFdZUDmMfnTpw4BBAcAiSaJFUpsfK7XLO6FvazEHZfmad7HKc/nFC9o7eKp15pobUasaECkicOHFC3n//fR2A+PznPy8LFiyQa9euyZUrV2RmZkaOHTsmv/nNb6S5uVkaGxvD7jJKoK2tzXcbw8PDgbUFAOXO/J0XhiB/Z5cCgYmqFM2YhuBJasCXFJFYc1SGXOscZMvMhFADrENS1278oz8al7gMJacmRE4mnxjbnlbbp5QkB3ARae0btHSxJ5V1MJQ9BcWkB7azT991T/TAPyrRaHpDKiChggFdclJHC+yD/+S0C6mzbsvsT6GmVYPxTZb9mBkhqm9jMtBhf5ZunLe42u487aUcn747ZYbE29vF6Z4suk6IJ8HcO05t+VGO10wHG47eVvwUjkAZg/z9ow7BgOJqTKjMi5dO7RP5h+zgwugLvbLjVIs0trgHWWotY0IFHlSw4cyZM9LU1CSrV6+W66+/Put9K1asMH4/xeX06dPy2muvyapVq+SLX/yizJtHTW0AAFA4AhNVzFNKvKRS321jw0isWaJDQwU8JU5mQsS7Um+enjaGEvWyRg9E66Str0uGO4ZlT3wss46Fx+KXs8fiHHQxX49vsrVjtK+fkg/GJKGyQNQ2PW3ATMY3+u24x0ty0dhd/SanXhVWyNCcWpAYn5Ros5pi0CEXNw3KmpOp6RuDbse+RdrqjGPrGbGcI3/TCeZSciqRLeNGBb1yxAJKoeh7J0sx191ssXyvmZr4cP/0PmnZdkye2v6UyIGHZYd1GpPbVA4JsuijCj70yktqekhARSRbHjgq51arwMtB+beVlsDLzEEZOLXUOF63oEQyg2RXMF2pGCooodI/1VOWRYsWub5XBSxUemd9fb288soretvatd7rd6A0EonZlYxisZJWQgYAwDMCE9Um0ip9qTx4PbaIuqeu6/oTts8l24lJc3RIhk4mZIuXf8gkVCZEXNJxicS4TBqj8MVyMfUGY2C2c1p6utXgsJB/GKWyCupV3YdYchCZnBeSHmCaT+kd0+RVECKWbMdZLFXPweFJtgqgxGxZAKnzmTHIdCiWmS0hFyej0rx1sci42bVB2amOx/oE3369jLa7h+r1NA9RS4l6CDTllOdemFuTMtTdIeaRqkH7VvXN1LS+MpGs1VHcgwCTlrZm2QMP/u6dIK671+BgTiW4Zi0rjcF5/3ZZ/8J66TxwXEafPCqd+pXUFAVr4EFP5bhgDOgDLEqZcn50h+yQh2S0gMKUnqjpHfbsiwP7RDb8zPEYzo9+R1qOTBS/v4iPAqIhm5iYkN///vfy9a9/PW9Qwkq997777tPpngsXLpSlS5fOYS8BAEA1KovAxO1Pt8o7/zEyp/tQxbtUkS54lZrOMXRSEsaIzT2UYAwAD1mncUynsgO2Gq1cnH2XClbEN0lfQWUrUgPL1Kgx0tongxFjQGgdmEbzZR0kj0el4zuWLsjIoHB6OVlQNFkw1P5q8tjVQFsPTrOWIzUP5KSMRZtlZ0QNuTOln6zr7JFUm8aAWmVVWHulj71VctRZSE2dcRiY63ZCf0g2GzQwg2GRSL3I5EXRC2zYAlv2z6TlrDGRPP6MLT7vnSCueyVdM51dkP4pGZT4ozF4H7YO6o1B/t6m9dK56zsiAQcnGlqekXOBFK7wuMynQybISnW8Zj8cVwZRbR+QOzK2JaeZvL2+spcLVYUujx8/LnfddZfceuutju/56U9/qr9++9vfznpNBSfUdI6xsTEKYta4bdu2SX9/f9jdAAC4KMff1aEHJlRQolRqMjgx6TKnPiXa7rzdnM5xMpFnWc/phIxPqvIJ5rssQQDLKFwP0rz3XNODw/R+MosoqtoFU0b/JvUxjrtnLFgLXXqQa7nH7HaHZWjSGFCb0RaVaSLdWUt96voSk2Oz10JlaBgnvqvZc5dsMjMQ0hy2lceqHPUSsZ/OxXUS1YErY4A+kBzkBzkWD+zeceLxumcq72s2+sJ6GVhkDMxXHZ9d9vOIc7HJlcYh7ti1Xg5vKKzmg9d+dOZaNSNH8Uun6STBTDGZ0Me5w77ZYVul15hQ2RIffvihLnJZLPVZNQ1EtbVs2bIAewc/Sjl9Q/1DFwBQGcotOBFqYKKUQQlTzQUnvE7lcGKdzrEm9y4Sw8YAz9jP1rz/9sm9/Gdm8EQVpWyTaft79dPtwcxjaTXvoWldu6HD+n5rLQvz8x7S4l3PSYbkU3M1DWB2LxFp3dou492ZS32mn5zbnohPj4zLpLUQaK4oURZ7NoHL03ePLc6ZSxctK3JYiopGIlIv43Jyz1QyW6KgyIAbh/vM771jb9/jdc9UztfshBw9JXJWUgP/pofkqcv7HLIAzOyAZ2R4pcoeMN5/OXvJUD905sYD9q2FFr9cKncEks2x1DZtxSVjIojdhUj93ahqRdxwww1Ft6E+q9pQK3oQmKg9BCUAoPKUU3AitMBEGEEJU60EJ2YHw7mpp8q54wnm6hzGYDJnYOKSHmhGm2Me5sE7TKdwK36Za+qF17bzchoYejc9sjs5VcB+AvVA3Phv94jEPARCsqdyeFHeT9+VZMDFGIzrlVnqJHuB2MVSFzWOQ88C6gswW6LQe6Gw9xd/3cv4ms1Myh/FmmWgBtv78nyoFopD1k7GhFr+M4gn62oaiLXYIsJXiuKXBCUAoHKVS3AilMBEmEEJU7UHJzIK93mRI5sgHdwwBs3OFhcREChU7kyLbHHHpTWdm1Urh9hWBPVKF6VUHRqQrFU+TZNDOVP7k8tGxkWtpFlwxoS9UGmyQ76CLEExl2Zt3zkog7ofyWsXbd6Zuresq50k9PcqO0EnJ+jpNs5LoxYv4Hun2OtextdMm/lfOSst0mWb+pBrqUw1CNdFIn93b/kVekwFWe7w287CzTLcv9m20Sljojr89a9/lQULFmRsM2tK2Nm3W2tOqDZUW6gdBCUAoPKVQ3AilMCEKnQZdnBiLoIS5jFZC3l63TYXvNZJcC7uV34cV92wSg1sPSsws8FK14yQPOdY9eekLu2YFSgyj0Wd+/ECMibyBpwcV6vQewx4wO/MLBiZpuuPRKV5U0J6OlI1HlQQLGZZdWPMUmDVMbPCgzxBpqDunUKve/LH8r5myvl3LxjdvVcabdvd6jSMnp4QWfSv5RWUUHSQZYl0+QgcuNa5UJyyKLQW2dvvtgRp+VLFKq9du+a7nSDaQGVR/5AlOAEAlS3soIQS2lSOMIMT1ZwpgRzSy4aaUgUX43FjYDxbIFQPYJ2mt6SflBvfTrdKq4dpMtZ9zg7YvdQQSE4tSHXT1qRt4G89nnJ5+p5mHOvuIZmMd0lfLCat5glThSg7BnRdkp19MUkY5+PQSJssVqGF+jXeA0S2gpYq86KQFV888Xndkz+W+zWbktd+5xxk+OO7xjVZ6VTTIVmT4v4Hs2tL5MqycBb8EH709KhIU6+vlp3rXCjVmzHxqU99Sq5cuZKxzb76htuqHCbVhmoL5aMUxS8JTgBA5SqHoIQSavHLMIITcxmUcMqA8LptLmRMEcgnOrs8hNsT3qw58k77cCwc6J5Sn7VyiMPUkuT0h3zcZ+fr7JBUJ9JPvbekRo36qXlqH5b9m5/RQQtJLjc57nXVjgB5mp6T8+m7eC7+GRiVLSHGPq33QiqYIMb5G0ydv9a+LrnY0S3dom4d870x2ZJVxMHGcXqEs2LunSCue2Vcs/+Tt6dFVn7OukRkvXSub5Ed+51XwdCMwf85h2wKz6thnN0ljftnf9RTQ45MuH8mx6oc6f7806QM5AiYeJU3W0LJmTFhiDxUftNbPPjsZz8rly5dkhUrVvhqR7Vxyy23BNQrVBKCEwBQecolKKGEvlxoKYMTtZYpUexUjtxPeP0opjhlpuLS8S1TBhS9OkOf80BPPenWB54MonT3SHJQGGs2hqxbU/tW71ljtFlA0Md1hQflUjpoo66Zrr5gHdAan0/uei6uyxxSgYM+h21ZwQQVhFCD/7lTzL0TzHWvgGt29r/lJbX6xCpbZsTK7XKuf3vJutHQ8oyc85lAMfpCr8iGn/laJjR3tkR1U38/vv766/LBBx8UvTKH+uzU1JR86UtfCrh38KMUxS9NBCcAoHKUU1BC+UTDk1/7eOzJ/WH3AzkcPnxYNm7cGHY3UKO4/yqPumaPPPJI2N2AR88++2xZ/H/so48+khdffFHuuOMOaW5udnxPvqkcJ06ckLffflseeOABXbMC5SGowMQbb7whbW1tvvszPDysvwbRFgCUO/U7b/ny5SXf71tvvRXY7+y77747gB65i//wwfAzJgAAQLhUIGHdunUyOjqql/xUf+zcaktcvnxZzpw5Iy0tLQQlAABAwQhMAAAAWbp0qbz33nvy6quvyn333SeLFi3y9DkVlDhy5Ijcddddug2Ul1IUvwQAwC8CEwAAQPvCF74gH374oU7dbGpqktWrV8v111/v+N6//e1vcvr0aTl16pTceeed+rMAAADFIDABAAC0efPmyT333CN1dXUyPj6up2c0NDTo7ImbbrpJ/v73v8vVq1dlZmZGzp8/LzfeeKOevkGmRG0w60OUW1sAgGyV9nuWwAQAVJEf/M8v5Qfbfhl2N1CAjRJ+8Uu7xsZGue2222RiYkIHIH7729/qgIQyf/58ufnmm/XqGyogQU2J2lCK4mcAgGBU4u9sAhNlrhyqtaN2cf8BtUsFHJYtW6b/AAAAzCUCEwBQRVj+GQAAAJVmXtgdAAAAAAAAtYvABAAAAAAACI2eynHhwoWQuwEAAAAAAGqRDkysWrUq7H4AAAAAnqnlbCsZ//4GgJRfMpUDAAAAAACEiMAEAAAAAAAIDYEJAAAAAAAQGgITAAAAAAAgNJ8MuwMAAABAqR08eNDX5zdv3hxQTwr3/e9/33cb3/ve9wLoSXEqvf8AgkdgAgAAADXJHlxQwQqv28LmZ2AeRGDAL3v/VZ+8bDO3Izy9vb0FbQe8IDABAAAAVDAvA3UyDACUMwITAAAAQIVzCzyQYQCU1rZt2/TX/v7+kHtSOSh+CQAAAABAmfvzn/8sGzZskF/84heO22OxmNx7773yzjvveHrt+PHjerv6o743qfbt+5hrZEwAAACgJjnVivC6rRw5ZUYwhQOoDipQ8Pzzz8s3vvGNjO0ffPCBfPe735Wnn35a1q1bpwMMjz76qH7/jTfe6Pra0aNH5Ve/+pVu50c/+pEOUExNTcnly5fl8ccfL+nxEZgAAABATark4pdOCEL48+tf/1ree+891/fccsst8uUvf7lEPQJmffOb39R/7JkMKpAwf/58HVRQ1NelS5fKm2++KQsXLsz52ooVK/Q2FaAwqeyKvXv3SmdnZ4mOahaBCQAAAKAKkDHhjxqsTUxMuL5HDeoITMDOrCmRb/tc1JyYmZmRm266SW644Qb9s/q6aNGivK+ZAYn3339fB+TU1z/84Q/S1NQkt99+e+D9zIfABAAAAFAFCEL4o54gqyfMblTGhJ2ZCl/rauk8fPWrXw27C2mTk5NZgQT1s9pufu/0mprasX79en0sCxYskB//+Mfy8ssvy1e+8pV0hsVPfvIT/b5SIDABAAAAVIFKyphw6mvYq4cUmwlRToPUUlBTXpzU2nmwsmdClHJVjmg0mhUUUgUuzevh9poKOiQSCf19X1+frF27Vp577rn0Zx577DEdsPv0pz8914dBYAIAAAC1qdqKX5ZrEMJJJfUVKHeqWKUqgqmmaqivf/nLX3T2j5rKkes1KxWsUFkTKptCTeVQgQj13iVLlpTsGAhMAAAAoCZVW/FLALVHTbt48cUXdeaDmQFx9epVqa+v139yvWZSAYgDBw7IE088oX8+deqULoJpshbHnEsEJgAAAIAKF/Y0CADhUJkQamnPb33rW3LlyhWdDaFW7jALXrq9phw6dEiWL1+enq6xYcOGdN2Jn//85xnvnUsEJgAAAIAKxrQIoLzMZW0JtWSonZqCcezYMcf3u73m1J65LGmpEZgAAAAAKgwZEgCqCYEJAAAA1KRKLX5ZDRkSBFYqV29vb9hdQBUiMAEAAICaYy9oidKphsAKgGDNC7sDAAAAAACgdhGYAAAAAAAAoSEwAQAAAAAAQkNgAgAAAAAAhIbABAAAAAAACM0nGp782sdhdwIAAAAAANSm/wfWBaq8N63SSgAAAABJRU5ErkJggg==" alt="表4"></p>]]></content>
    
    <summary type="html">
    
      
      
        &lt;h2 id=&quot;基于Python-Urllib库和Re库的爬虫应用&quot;&gt;&lt;a href=&quot;#基于Python-Urllib库和Re库的爬虫应用&quot; class=&quot;headerlink&quot; title=&quot;基于Python Urllib库和Re库的爬虫应用&quot;&gt;&lt;/a&gt;基于Python Ur
      
    
    </summary>
    
    
    
      <category term="Python" scheme="http://yoursite.com/tags/Python/"/>
    
  </entry>
  
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