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	<title>Stable Diffusion模型及教程 &#8211; DeepHour | 暮云</title>
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	<title>Stable Diffusion模型及教程 &#8211; DeepHour | 暮云</title>
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		<title>SD教程 &#124; Stable Diffusion使用教程(四)：SD提示词的编写</title>
		<link>https://blog.deephour.com/2024/04/19/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e5%9b%9b%ef%bc%9asd%e6%8f%90%e7%a4%ba%e8%af%8d%e7%9a%84%e7%bc%96%e5%86%99/</link>
					<comments>https://blog.deephour.com/2024/04/19/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e5%9b%9b%ef%bc%9asd%e6%8f%90%e7%a4%ba%e8%af%8d%e7%9a%84%e7%bc%96%e5%86%99/#respond</comments>
		
		<dc:creator><![CDATA[暮云岚]]></dc:creator>
		<pubDate>Fri, 19 Apr 2024 07:07:01 +0000</pubDate>
				<category><![CDATA[Stable Diffusion模型及教程]]></category>
		<category><![CDATA[stable diffusion]]></category>
		<guid isPermaLink="false">https://blog.deephour.com/?p=6763</guid>

					<description><![CDATA[首先，和大家介绍一下什么是提示词，提示词的英文&#8221;Prompt&#8221;，&#8221;Prom&#8230;&#160;<a href="https://blog.deephour.com/2024/04/19/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e5%9b%9b%ef%bc%9asd%e6%8f%90%e7%a4%ba%e8%af%8d%e7%9a%84%e7%bc%96%e5%86%99/" rel="bookmark">阅读更多 &#187;<span class="screen-reader-text">SD教程 &#124; Stable Diffusion使用教程(四)：SD提示词的编写</span></a>]]></description>
										<content:encoded><![CDATA[
<figure class="wp-block-image size-large"><img fetchpriority="high" decoding="async" width="1024" height="576" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-129-1024x576.png" alt="" class="wp-image-6792" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-129-1024x576.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-129-300x169.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-129-768x432.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-129.png 1280w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">首先，和大家介绍一下什么是提示词，提示词的英文&#8221;Prompt&#8221;，&#8221;Prompt&#8221;是指在使用SD模型时输入的问题、指令或描述。它是用来引导模型生成相应绘图的起点。</p>



<p class="wp-block-paragraph">简而言之，选好大模型之后，我们就要考虑画面上要有什么东西，不要什么东西，有时候我们不太好确定不想要什么，这里也可以不填，或者填一些通用的关键词，后面还会提到。</p>



<h3 class="wp-block-heading"><strong>01.正面提示词</strong></h3>



<p class="wp-block-paragraph">正面提示词里写的就是你希望照片里会出现的内容。输入的关键词越准确，出来的照片就会越接近自己脑海里的画面！最开始的时候，提示词需要用英文书写，因此好多人在这一步就望而却步了，但是随着SD生态的日益完善，现在可以通过插件，我们直接输入中文，自动生成英文输入了（这个插件就是：sd-webui-prompt-all-in-one，这里简单提一下）。</p>



<p class="wp-block-paragraph">如下图所示，这里就是我们写正面提示词的输入框：</p>



<figure class="wp-block-image size-large"><img decoding="async" width="1024" height="135" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-108-1024x135.png" alt="" class="wp-image-6764" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-108-1024x135.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-108-300x40.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-108-768x101.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-108.png 1396w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">这里使用 majicMix Realistic 系列模型作为演示。</p>



<p class="wp-block-paragraph">比如说我现在想要生成：一个漂亮的小姐姐站在大街上。</p>



<p class="wp-block-paragraph">那可以写成：1女孩，漂亮，站着，大街（majicMix Realistic 系列范例），或者是：1漂亮女孩，站在大街上，又或者我直接输入这个短句：1个漂亮女孩站在大街上。</p>



<p class="wp-block-paragraph">上面三种<strong>单词、词组、短句</strong>的方式都可以，（这里可以参考使用的大模型提示词的书写习惯，不同的大模型可能对三种表达敏感度不同），还要注意的是，这里的短句一般是：<strong>主体 + 动作 + 场景</strong>的格式，并不是什么复杂句子都可以的</p>



<p class="wp-block-paragraph">我们比较常用的就是直接输入一个个单词，然后这些单词用<strong>英文状态下的逗号隔开</strong></p>



<p class="wp-block-paragraph">SD只能识别英语，这时候刚刚说的插件就派上用场啦，我们把提示词粘贴进去，就可以直接生成英文了如下图：</p>



<figure class="wp-block-image size-large"><img decoding="async" width="1024" height="133" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-109-1024x133.png" alt="" class="wp-image-6765" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-109-1024x133.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-109-300x39.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-109-768x100.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-109.png 1381w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">当然我们也可以直接使用网页翻译：</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="986" height="116" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-110.png" alt="" class="wp-image-6766" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-110.png 986w, https://blog.deephour.com/wp-content/uploads/2024/04/image-110-300x35.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-110-768x90.png 768w" sizes="auto, (max-width: 986px) 100vw, 986px" /></figure>



<p class="wp-block-paragraph">接着点击右边这个“生成”按钮</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="470" height="270" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-111.png" alt="" class="wp-image-6767" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-111.png 470w, https://blog.deephour.com/wp-content/uploads/2024/04/image-111-300x172.png 300w" sizes="auto, (max-width: 470px) 100vw, 470px" /></figure>
</div>


<p class="wp-block-paragraph">其它参数设置：</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="477" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-120-1024x477.png" alt="" class="wp-image-6782" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-120-1024x477.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-120-300x140.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-120-768x357.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-120-1536x715.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-120.png 1545w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">这样你在SD的第一张图就出来啦，但是不出意外的话，已经出意外了，因为图片可能并不理想，我自己也用这个提示词反复的除了很多图结果都是这样的：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-114.png" alt="" class="wp-image-6776" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-114.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-114-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-115.png" alt="" class="wp-image-6777" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-115.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-115-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">一个重要的缺陷就是，脸崩！！！</figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-116.png" alt="" class="wp-image-6778" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-116.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-116-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">可能细心的小伙伴也发现了， 这些图，一般都是全身，这个时候脸部占图片的比例较小，所以会发生脸部细节失真，那么很简单，我们增加关键词，比如：<strong>肖像</strong>或者<strong>半身像</strong>，我们再试一下！</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-117.png" alt="" class="wp-image-6779" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-117.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-117-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">1girl,pretty,stand,avenue,<strong>portrait(肖像),</strong></figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-118.png" alt="" class="wp-image-6780" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-118.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-118-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">1girl,pretty,stand,avenue,<strong>upper body(上半身),</strong></figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-119.png" alt="" class="wp-image-6781" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-119.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-119-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">1girl,pretty,stand,avenue,upper_body,<strong>photography（摄影）</strong>,</figcaption></figure>
</div>
</div>



<p class="wp-block-paragraph">这时候基本上已经有些味道了，我们可以看到当脸部占比变大后，模型反而可以更好的刻画小姐姐的脸部细节了，所以<strong>保证面部适当的占比，在人像生成过程中非常重要</strong>！</p>



<p class="wp-block-paragraph">是不是很多小伙伴已经按捺不住去试了试呢？别急，再等等！写关键词也是有模板的！</p>



<p class="wp-block-paragraph">在写跟照片有关的关键词之前，我们可以先写一些<strong>照片质量</strong>的词语，这样出来的照片会更加精致。比如说我们可以写：最高质量，超高清画质，大师的杰作，8k画质等等&#8230;翻译成对应的英文就是：<strong>Highest quality, ultra-high definition, masterpieces, 8k quality,</strong></p>



<p class="wp-block-paragraph">写完质量词，接着就是我们照片的内容,先写的就是<strong>照片的主体</strong>，和对<strong>主体的细节描写</strong>。</p>



<p class="wp-block-paragraph">比如我们是要生成一个女孩，就要写出来一个女孩，以及这个女孩长什么样也可以写出来</p>



<p class="wp-block-paragraph">也就是：<strong>一个女孩</strong>，<strong>非常精致的五官，极具细节的眼睛和嘴巴，长发，卷发，细腻的皮肤，大眼睛</strong></p>



<p class="wp-block-paragraph">翻译成英文就是：<strong>1girl, very delicate features, very detailed eyes and mouth, long hair, curly hair, delicate skin, big eyes,</strong></p>



<p class="wp-block-paragraph">这些照片内容大家都是可以随意改的，但是像精致的五官、细节的眼睛这类词语，大家可以都加上去</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="66" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-121-1024x66.png" alt="" class="wp-image-6784" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-121-1024x66.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-121-300x19.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-121-768x50.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-121-1536x99.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-121.png 1546w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">写完五官之后，我们就可以想一下让照片的<strong>人物穿什么衣服，裤子，或者加上帽子之类的配饰</strong></p>



<p class="wp-block-paragraph">像<strong>裙子、毛衣、牛仔裤、比基尼</strong>都可以，还可以写上<strong>衣服的颜色</strong>。</p>



<p class="wp-block-paragraph">比如：<strong>白色的毛衣、项链</strong>（<strong>white sweater, necklace,</strong>）</p>



<p class="wp-block-paragraph">最后我们就可以写上其的东西，比如<strong>背景、天气、照片姿势、构图</strong>等等</p>



<p class="wp-block-paragraph">比如说：<strong>在街上，阳光，上半身照片</strong>（<strong>street, Sunshine, upper body photos,</strong>）</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="75" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-122-1024x75.png" alt="" class="wp-image-6785" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-122-1024x75.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-122-300x22.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-122-768x56.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-122.png 1537w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">推荐大家像我这样，一行一行分开类型去写关键词，这样后面想要改词更好找。</p>



<p class="wp-block-paragraph">但一定要<strong>注意每一行的最后要加上英文逗号</strong>，否则它就会跟下一个单词连起来变成一个新单词</p>



<p class="wp-block-paragraph">总结一下我们写关键词的公式：</p>



<p class="wp-block-paragraph"><strong>画质+主体+主体细节+人物服装+其他（背景、天气、构图等）</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="89" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-123-1024x89.png" alt="" class="wp-image-6786" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-123-1024x89.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-123-300x26.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-123-768x66.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-123.png 1202w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">下面就是这一套关键词生成的图片了：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-124.png" alt="" class="wp-image-6787" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-124.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-124-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-125.png" alt="" class="wp-image-6788" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-125.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-125-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-126.png" alt="" class="wp-image-6789" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-126.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-126-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">看吧，基本上和我们的描述是一致的，接下来，讲一下如何修改或者加强某些特征。</p>



<p class="wp-block-paragraph">比如，怎样才能让“卷发（curly hair）”引起Stable Diffusion的注意呢？</p>



<p class="wp-block-paragraph">那就是给关键词加权重，加权重的方法有两种：</p>



<p class="wp-block-paragraph"><strong>①直接用括号把关键词括起来：（curly hair）</strong></p>



<p class="wp-block-paragraph">这样括号一次就是1.1倍权重，那括两次((curly hair))就是1.1×1.1=1.21倍，以此类推。注意：这里的括号也是英文状态下的括号。</p>



<p class="wp-block-paragraph">可以加权重，那我们也可以减权重，减权重就是用&#8221;[]&#8221;把单词括起来，如：[curly hair]。</p>



<p class="wp-block-paragraph"><strong>②（关键词:数值):（curly hair：1.3）</strong></p>



<p class="wp-block-paragraph">这就是在第一种的基础上加上数值，直接一个curly hair是1，大于1就是加权重，小于1就是减权重</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-127.png" alt="" class="wp-image-6790" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-127.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-127-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption"><strong>（curly hair：1.3）</strong>增加卷发权重</figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-128.png" alt="" class="wp-image-6791" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-128.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-128-225x300.png 225w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">[<strong>curly hair</strong>]降低卷发权重</figcaption></figure>
</div>
</div>



<h3 class="wp-block-heading"><strong>02.负面关键词</strong></h3>



<p class="wp-block-paragraph">当我们生成照片次数多了之后，渐渐的发现偶尔生成出来的照片多了几个手指，甚至会多了一只手</p>



<div class="wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-4fc3f8e1 wp-block-group-is-layout-flex">
<p class="wp-block-paragraph">那怎么才能避免这些情况呢？那就是告诉SD，我不要那样的照片！所以，我们就可以通过输入负面关键词告诉SD，我不希望照片会出现什么内容。</p>



<p class="wp-block-paragraph">比如说我不希望照片出现：低质量，多余的手，多余的手指，不好看的脸等等&#8230;这里就不用大家去想要写些什么啦，可以直接抄作业！</p>
</div>



<p class="wp-block-paragraph">(worst quality:2),(low quality:2),(normal quality:2),lowres,watermark,EasyNegative,ng_deepnegative_v1_75t,</p>



<p class="wp-block-paragraph">当然你如果还有什么不想出现在照片上的东西，也可以自己加上去。</p>



<p class="wp-block-paragraph">到这里关键词所有的内容就讲完啦！换了二次元的大模型，其实步骤还是一样的，只是把模型切换一下就好啦，注意如果使用一些小众的风格模型，提示词里面需要出现激发词，才能对应出现模型的风格的，注意一下就好了。</p>
]]></content:encoded>
					
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			</item>
		<item>
		<title>SD教程 &#124; Stable Diffusion使用教程(三)：SD的底模选取</title>
		<link>https://blog.deephour.com/2024/04/17/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%b8%89%ef%bc%9asd%e7%9a%84%e5%ba%95%e6%a8%a1%e9%80%89%e5%8f%96/</link>
					<comments>https://blog.deephour.com/2024/04/17/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%b8%89%ef%bc%9asd%e7%9a%84%e5%ba%95%e6%a8%a1%e9%80%89%e5%8f%96/#respond</comments>
		
		<dc:creator><![CDATA[暮云岚]]></dc:creator>
		<pubDate>Wed, 17 Apr 2024 02:39:03 +0000</pubDate>
				<category><![CDATA[Stable Diffusion模型及教程]]></category>
		<category><![CDATA[stable diffusion]]></category>
		<guid isPermaLink="false">https://blog.deephour.com/?p=6716</guid>

					<description><![CDATA[用Stable Diffusion绘图时，可以把自己想象成一个画家，在起笔画画之前，我们要先确定我们画的是什么&#8230;&#160;<a href="https://blog.deephour.com/2024/04/17/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%b8%89%ef%bc%9asd%e7%9a%84%e5%ba%95%e6%a8%a1%e9%80%89%e5%8f%96/" rel="bookmark">阅读更多 &#187;<span class="screen-reader-text">SD教程 &#124; Stable Diffusion使用教程(三)：SD的底模选取</span></a>]]></description>
										<content:encoded><![CDATA[
<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="576" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-106-1024x576.png" alt="" class="wp-image-6756" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-106-1024x576.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-106-300x169.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-106-768x432.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-106-1536x864.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-106-2048x1152.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">用Stable Diffusion绘图时，可以把自己想象成一个画家，在起笔画画之前，我们要先确定我们画的是什么风格的画，是二次元动漫、现实照片、还是盲盒模型、赛博朋克、玄幻修仙等等，在我们确定了我们照片风格之后我们就要去切换大模型，不同的模型就代表着不同的照片风格。也就是SD界面左上角的“Stable Diffusion模型”，</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="456" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-69-1024x456.png" alt="" class="wp-image-6717" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-69-1024x456.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-69-300x134.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-69-768x342.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-69-1536x684.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-69.png 1886w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">接下来我将为大家介绍几款，常用的效果炸裂的大模型。</p>



<p class="wp-block-paragraph">我们分不同的风格，每个风格会展示几种不同模型，模型下载网站是大名鼎鼎的<a href="https://civitai.com/" data-type="link" data-id="https://civitai.com/">C站</a>，不过需要科学上网才行，国内也有几个网站，比如<a href="https://www.liblib.art/" data-type="link" data-id="https://www.liblib.art/">哩布</a>，<a href="https://tusiart.com/">吐司</a>等都提供模型免费下载。以下模型网址均为C站</p>



<p class="wp-block-paragraph">同时在展示实例图片的同时我们也会使用简单的prompt（绘画指令），实际给大家生成一些图片，供大家了解不同风格的模型效果。</p>



<h2 class="wp-block-heading">真实风格大模型</h2>



<p class="wp-block-paragraph"><strong>1. Realistic Vision系列模型</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/4201?modelVersionId=130072">https://civitai.com/models/4201?modelVersionId=130072</a></p>



<p class="wp-block-paragraph">模型首页示例图：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-70.png" alt="" class="wp-image-6718" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-70.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-70-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-71.png" alt="" class="wp-image-6719" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-71.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-71-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">测试实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-72.png" alt="" class="wp-image-6720" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-72.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-72-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /><figcaption class="wp-element-caption">masterpiece, best quality, cinematic photo,RAW photo,(realistic:1.5),<strong>1girl,portrait,upper body,</strong></figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-73.png" alt="" class="wp-image-6721" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-73.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-73-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /><figcaption class="wp-element-caption">masterpiece, best quality, cinematic photo,RAW photo,(realistic:1.5),<strong>1man,portrait,upper body,</strong></figcaption></figure>
</div>
</div>



<p class="wp-block-paragraph">这一系列的模型在人物刻画上主要以欧美人为主，亚洲人效果较差，但是瑕不掩瑜，在其他方面Realistic Vision 在真实照片场景的图片生成中用的还是蛮多的。</p>



<p class="wp-block-paragraph"><strong>2.majicMIX realistic 麦橘写实</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/43331?modelVersionId=176425">https://civitai.com/models/43331?modelVersionId=176425</a></p>



<p class="wp-block-paragraph">模型首页示例图：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-74.png" alt="" class="wp-image-6722" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-74.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-74-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-75.png" alt="" class="wp-image-6723" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-75.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-75-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">测试实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-76.png" alt="" class="wp-image-6724" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-76.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-76-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /><figcaption class="wp-element-caption">masterpiece,best quality,cinematic photo,RAW photo,(realistic:1.5),<strong>1girl,portrait,upper body,</strong></figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-77.png" alt="" class="wp-image-6725" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-77.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-77-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /><figcaption class="wp-element-caption">masterpiece,best quality,cinematic photo,RAW photo,(realistic:1.5),<strong>1boy,portrait,upper body,</strong></figcaption></figure>
</div>
</div>



<p class="wp-block-paragraph">这一系列的模型在人物的刻画上可以说是牢牢地抓住我的审美了，近乎每一张图都画在心坎上，相比作者大大选图的审美一定在线，模型出图非常的的贴合亚洲人风格，图片细节丰富，非常逼真，是笔者最喜欢的真实风格模型了，灰常的赞。</p>



<p class="wp-block-paragraph"><strong>3.XXMix_9realistic 系列</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/47274/xxmix9realistic">https://civitai.com/models/47274/xxmix9realistic</a></p>



<p class="wp-block-paragraph">模型首页示例图：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-78.png" alt="" class="wp-image-6726" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-78.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-78-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-79.png" alt="" class="wp-image-6727" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-79.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-79-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">测试实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-81.png" alt="" class="wp-image-6729" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-81.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-81-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-80.png" alt="" class="wp-image-6728" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-80.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-80-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">这个系列的模型，虽然生成的图片质量也很好，但是‘一眼AI’的现象比较严重，基本上出图一眼就能被人看出来是AI做的，有一点点人偶的感觉，非常像一些3A游戏里面的形象，用来设计游戏素材，制作游戏人物还是非常不错的。</p>



<p class="wp-block-paragraph"><strong>4. chilloutmix 系列</strong></p>



<p class="wp-block-paragraph">模型下载地址：由于一些涩图的原因，该模型不再提供下载，但是笔者由于用sd时间比较长了，还有原始模型，给大家出几张实例。</p>



<p class="wp-block-paragraph">测试实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-82.png" alt="" class="wp-image-6730" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-82.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-82-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-83.png" alt="" class="wp-image-6731" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-83.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-83-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">这个系列的模型，当时名气非常大，尤其是NSFW，到最后设置作者都害怕了，把模型自己删除了，然后声明别人拿模型跑出来的图和他无关，然后。。就没有然后了，从此chilloutmix渐渐淡出了江湖，现在也比较少听说了。此系列模型拿到现在来看其实也没有很出彩了，人物同时呈现亚洲人和欧洲人的特点，不过在当时为数不多的可以画亚洲美女的模型，是不少AI画师的最爱！</p>



<p class="wp-block-paragraph">5.OnlyRealistic 系列</p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/112756/onlyrealistic-or">https://civitai.com/models/112756/onlyrealistic-or</a></p>



<p class="wp-block-paragraph">模型首页示例图：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-84.png" alt="" class="wp-image-6732" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-84.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-84-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-85.png" alt="" class="wp-image-6733" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-85.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-85-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">测试实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-87.png" alt="" class="wp-image-6735" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-87.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-87-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-86.png" alt="" class="wp-image-6734" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-86.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-86-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">这个系列的模型整体看起来效果不错，但是看细节的话，隐隐有一种怪怪的感觉，比如右边男生的‘逆天’长睫毛，细看的话有很多违和的地方，整体上是符合亚洲人的审美的，另外这个模型的特长在于风景和静物效果相当的不错，大家有兴趣可以试试看。</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-88.png" alt="" class="wp-image-6736" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-88.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-88-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-89.png" alt="" class="wp-image-6737" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-89.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-89-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-90.png" alt="" class="wp-image-6738" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-90.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-90-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">总结一下，以上的5个真实系列模型，无论是在人像还是静物风景上，足够满足绝大多数的场景要求，如果你也需要生成一些真实场景快来试试吧！</p>



<h2 class="wp-block-heading">二次元风格大模型</h2>



<p class="wp-block-paragraph">二次元风格大模型非常非常多，好的模型也是比比皆是，下面我主要对不同的绘画风格推荐我个人比较喜欢的模型。</p>



<p class="wp-block-paragraph"><strong>1. 万象熔炉 | Anything 系列</strong>:<strong>通用二次元模型</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/9409/or-anything-xl">https://civitai.com/models/9409/or-anything-xl</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full is-resized"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-91.png" alt="" class="wp-image-6740" style="width:386px;height:auto" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-91.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-91-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="712" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-92-712x1024.png" alt="" class="wp-image-6741" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-92-712x1024.png 712w, https://blog.deephour.com/wp-content/uploads/2024/04/image-92-209x300.png 209w, https://blog.deephour.com/wp-content/uploads/2024/04/image-92-768x1104.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-92-1069x1536.png 1069w, https://blog.deephour.com/wp-content/uploads/2024/04/image-92.png 1280w" sizes="auto, (max-width: 712px) 100vw, 712px" /></figure>
</div>
</div>



<p class="wp-block-paragraph"><strong>2.Dark Sushi Mix 大颗寿司Mix 系列：平涂风格二次元模型</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/24779?modelVersionId=93208">https://civitai.com/models/24779?modelVersionId=93208</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow"><div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" width="450" height="731" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-93.png" alt="" class="wp-image-6742" style="width:356px;height:auto" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-93.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-93-185x300.png 185w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div></div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="650" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-94.png" alt="" class="wp-image-6743" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-94.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-94-208x300.png 208w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">3.TMND-Mix 系列：治愈插画二次元模型</p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/27259/tmnd-mix">https://civitai.com/models/27259/tmnd-mix</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="650" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-95.png" alt="" class="wp-image-6744" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-95.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-95-208x300.png 208w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="650" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-96.png" alt="" class="wp-image-6745" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-96.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-96-208x300.png 208w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph"><strong>4.old fish 系列：古早风二次元模型</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/14978/old-fish">https://civitai.com/models/14978/old-fish</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-97.png" alt="" class="wp-image-6746" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-97.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-97-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-98.png" alt="" class="wp-image-6747" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-98.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-98-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph"><strong>5.三餡馄饨Mix ：插画风格二次元</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/20330/three-delicacy-wonton-mix">https://civitai.com/models/20330/three-delicacy-wonton-mix</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-99.png" alt="" class="wp-image-6748" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-99.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-99-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-100.png" alt="" class="wp-image-6749" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-100.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-100-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph"><strong>6.QteaMix :通用Q版二次元模型</strong></p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/50696/qteamix-q">https://civitai.com/models/50696/qteamix-q</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="450" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-101.png" alt="" class="wp-image-6750" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-101.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-101-300x300.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-101-150x150.png 150w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="450" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-102.png" alt="" class="wp-image-6751" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-102.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-102-300x300.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-102-150x150.png 150w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">7.hellokid2d 系列：儿童插画二次元模型</p>



<p class="wp-block-paragraph">模型下载地址：<a href="https://civitai.com/models/101254/hellokid2d">https://civitai.com/models/101254/hellokid2d</a></p>



<p class="wp-block-paragraph">模型首页实例：</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-103.png" alt="" class="wp-image-6752" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-103.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-103-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="450" height="675" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-104.png" alt="" class="wp-image-6753" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-104.png 450w, https://blog.deephour.com/wp-content/uploads/2024/04/image-104-200x300.png 200w" sizes="auto, (max-width: 450px) 100vw, 450px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">以上就是本次推荐的SD比较受欢迎的真实、二次元大模型，当然还有数不清优秀的模型存在，也有数不清的炼丹师在加班加点的赶工，相信未来，SD的模型生态会更加丰富多彩，本期分享就到这里，下一期将为大家介绍：<strong>上手使用SD, 你需要知道的几件事儿</strong>，希望大家能够喜欢</p>
]]></content:encoded>
					
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			</item>
		<item>
		<title>SD教程 &#124; Stable Diffusion使用教程(二)：SD的安装</title>
		<link>https://blog.deephour.com/2024/04/16/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%ba%8c%ef%bc%9asd%e7%9a%84%e5%ae%89%e8%a3%85/</link>
					<comments>https://blog.deephour.com/2024/04/16/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%ba%8c%ef%bc%9asd%e7%9a%84%e5%ae%89%e8%a3%85/#respond</comments>
		
		<dc:creator><![CDATA[暮云岚]]></dc:creator>
		<pubDate>Tue, 16 Apr 2024 08:01:43 +0000</pubDate>
				<category><![CDATA[Stable Diffusion模型及教程]]></category>
		<category><![CDATA[stable diffusion]]></category>
		<guid isPermaLink="false">https://blog.deephour.com/?p=6682</guid>

					<description><![CDATA[1.什么电脑能本地运行Stable Diffusion 为了大家能够更加顺利的安装和使用Stable Diff&#8230;&#160;<a href="https://blog.deephour.com/2024/04/16/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%ba%8c%ef%bc%9asd%e7%9a%84%e5%ae%89%e8%a3%85/" rel="bookmark">阅读更多 &#187;<span class="screen-reader-text">SD教程 &#124; Stable Diffusion使用教程(二)：SD的安装</span></a>]]></description>
										<content:encoded><![CDATA[
<h2 class="wp-block-heading"><strong>1.什么电脑能本地运行Stable D</strong>iffusion</h2>



<p class="wp-block-paragraph">为了大家能够更加顺利的安装和使用Stable Diffusion（简称“SD”），在正式安装之前希望大家先一起查看一下自己的电脑配置，需要注意的是以下两点：</p>



<p class="wp-block-paragraph"><strong>01.电脑系统是Win10或者Win11</strong></p>



<p class="wp-block-paragraph">为了避免一些奇怪的兼容性问题，不要选择更低版本的系统。</p>



<p class="wp-block-paragraph"><strong>查看电脑系统的方法：</strong></p>



<p class="wp-block-paragraph">在桌面上找到“我的电脑”=&gt;鼠标右键点击=&gt;点击“属性”=&gt;查看Windows规格</p>


<div class="wp-block-image">
<figure class="aligncenter size-large"><img loading="lazy" decoding="async" width="1024" height="796" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-44-1024x796.png" alt="" class="wp-image-6683" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-44-1024x796.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-44-300x233.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-44-768x597.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-44.png 1314w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>
</div>


<p class="wp-block-paragraph"><strong>02.检查电脑性能</strong></p>



<p class="wp-block-paragraph">这里是检查自己的电脑配置能不能带动SD（Stable Diffusion），需要满足3个要求：</p>



<ul class="wp-block-list">
<li><strong>电脑运行内存8GB以上</strong></li>



<li><strong>是英伟达（俗称N卡）的显卡</strong></li>



<li><strong>显卡内存4GB以上</strong></li>
</ul>



<p class="wp-block-paragraph">检查方法：</p>



<p class="wp-block-paragraph"><strong>①桌面底部搜索栏 =&gt; 搜索“任务管理器”</strong></p>


<div class="wp-block-image">
<figure class="aligncenter size-large"><img loading="lazy" decoding="async" width="1024" height="1015" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-45-1024x1015.png" alt="" class="wp-image-6684" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-45-1024x1015.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-45-300x297.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-45-150x150.png 150w, https://blog.deephour.com/wp-content/uploads/2024/04/image-45-768x762.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-45.png 1066w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>
</div>


<p class="wp-block-paragraph"><strong>②查看电脑的运行内存</strong></p>



<p class="wp-block-paragraph">在“性能”里面找到“内存”，这里的内存不是电脑的存储内存，而是运行内存噢！只要看图中划线的那一个参数就可以</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph"><strong>8GB：</strong>那就说明你的电脑配置内存是勉强达到标准的</p>



<p class="wp-block-paragraph"><strong>16GB：</strong>那就说明你的内存配置可以正常使用</p>



<p class="wp-block-paragraph"><strong>32GB：</strong>那么你就可以非常自由的使用SD啦！</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="647" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-47-1024x647.png" alt="" class="wp-image-6686" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-47-1024x647.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-47-300x190.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-47-768x485.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-47.png 1521w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>③查看“GPU”</strong></p>



<p class="wp-block-paragraph">GPU就是显卡的意思，首先先看右上角显卡的名字或者型号，必须确认的第一个是 NVIDIA ，代表的是英伟达的显卡（俗称N卡），这里是N卡我们才可以进行下一步，如果这个地方是AMD或者是Intel，可能你的电脑会不太支持SD，网上的安装教程也比较麻烦，如果是AMD显卡可以直接跳到第二部分，使用云服务器平台部署stable diffusion服务。</p>



<p class="wp-block-paragraph">接着看到下面划线的专用GPU内存</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph"><strong>4GB：</strong>说明电脑勉强可以跑动SD，出图的时间会比较长</p>



<p class="wp-block-paragraph"><strong>6GB：</strong>出一张图的时间是20~50秒，SD的大部分功能都可以使用</p>



<p class="wp-block-paragraph"><strong>8GB：</strong>5~20秒可以出一张图，基本上SD的所有功能都对你开放</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="544" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-48-1024x544.png" alt="" class="wp-image-6687" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-48-1024x544.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-48-300x159.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-48-768x408.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-48-1536x816.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-48.png 1919w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">好啦，如果你的电脑满足以上所说的配置，那么恭喜你！你可以顺利的安装Stable Diffusion并展开学习啦！</p>



<p class="wp-block-paragraph">上面这些操作是我们用来查看Windows系统的&nbsp;。</p>



<p class="wp-block-paragraph">至于Mac系统可以看一下下面的视频&nbsp;按照视频一键安装就可以啦！非常简单！</p>



<p class="wp-block-paragraph"><a href="https://www.bilibili.com/video/BV1Kh4y1W7Vg/?spm_id_from=333.788&amp;vd_source=6f836e2ab17b1bdb4fc5ea98f38df761" data-type="link" data-id="https://www.bilibili.com/video/BV1Kh4y1W7Vg/?spm_id_from=333.788&amp;vd_source=6f836e2ab17b1bdb4fc5ea98f38df761">【AI绘画】从此告别WEBUI整合包!魔法书现已支持一键全自动部署官方SD WEBUI包!支持国内加速部署,Windows,Linux,MacOS全平台支持</a></p>



<h2 class="wp-block-heading"><strong>2.低配置电脑也能玩Stable Diffusion</strong></h2>



<p class="wp-block-paragraph">（电脑配置过关的朋友们，直接看第3部分安装）</p>



<p class="wp-block-paragraph">刚刚查看了电脑配置，发现自己电脑可能带不动SD的朋友们也不用担心，通过云平台，我们一样可以畅玩SD，做出好看的图片。</p>



<p class="wp-block-paragraph">云平台就相当于我们远程控制别人配置更好的电脑，用别人电脑上的SD生成照片</p>



<p class="wp-block-paragraph">这里用的是“青椒云桌面”，如果大家还有什么更好用的平台也可以分享出来噢！</p>



<p class="wp-block-paragraph">点击下面的链接就可以注册：</p>



<p class="wp-block-paragraph"><a href="https://account.qingjiaocloud.com/signin">https://account.qingjiaocloud.com/signin</a></p>



<p class="wp-block-paragraph">云平台使用方法：</p>



<p class="wp-block-paragraph"><strong>①点击上面链接，注册账号</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="567" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-53-1024x567.png" alt="" class="wp-image-6692" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-53-1024x567.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-53-300x166.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-53-768x426.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-53-1536x851.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-53.png 1610w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>②登录刚刚注册好的账户</strong></p>



<p class="wp-block-paragraph"><strong>③点击右上角的个人中心进行实名认证</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="486" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-54-1024x486.png" alt="" class="wp-image-6693" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-54-1024x486.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-54-300x142.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-54-768x364.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-54-1536x729.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-54.png 1920w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>④在进行实名认证</strong>,下载青椒云客户端 <a href="https://www.qingjiaocloud.com/download/">https://www.qingjiaocloud.com/download/</a>，登录账号：</p>



<p class="wp-block-paragraph">选择延迟较低的区，如图所示我这里是“华北4”，</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="641" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-55-1024x641.png" alt="" class="wp-image-6694" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-55-1024x641.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-55-300x188.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-55-768x481.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-55.png 1270w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">点击“新增云桌面”， “标准产品” =&gt; 选择“AIGC尝鲜”，这个只能包天不太友好，熟悉一点以后，也可以选择一些能够按小时计费的“定制产品”</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="596" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-56-1024x596.png" alt="" class="wp-image-6695" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-56-1024x596.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-56-300x175.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-56-768x447.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-56.png 1194w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>⑤在新弹出的框框中点击“开机”按钮，稍等一下之后，点击“进入桌面”</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="645" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-57-1024x645.png" alt="" class="wp-image-6696" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-57-1024x645.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-57-300x189.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-57-768x484.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-57.png 1272w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">进入桌面之后弹出的全部框框可以直接关掉</p>



<p class="wp-block-paragraph">桌面就是和正常的window桌面一样的。</p>



<p class="wp-block-paragraph"><strong>⑥点击新打开桌面的“此电脑”，在C盘里面找到SD的根目录，点击“A启动器.exe”</strong>， <strong>如果桌面上有快捷方式直接双击打开即可</strong></p>



<p class="wp-block-paragraph"><img decoding="async" 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pqoYdXB1UPuRKc5Q3DTkv742zcDcMU3A3D5V3lo+919uGxJLi7/iqlfOH2Ti8u/yUWbpXn5KRdXfMtyX1z+TW+0XNIdrZf0wuWLc3HjksG4Y+b9qNfzEsRYx+C4pJNR21sH8Z5YuNxM/FZvGPAq5I3OD9l0QJpOSskr5D0yB3JVhbvSLoG8hF/8PiETl2qOBMi0ToFwZdeAQt7wPGTOG8zLfCHWud0sV8aXcoG7Yp1tMNsXKS/94rROUCiQV0Avo3tZR8DIqNJzzz23ADoSPArwlecxgaUJLaW+ulsB4bSSnH3Cf3ZkHaEu5zUm9i/nNI6bLLEtY0YtsJ5j5BzXSBooqs6pp+KUeb7i7Kf7ROfdWftV+1U1oBpQDagGVAOqAdWAakA1oBpQDagGVAOl10CpIC8dy1ZB8ufnLaT5a2HvuknA+peB9S8C6xjRG47q/X3hQGyek4Nt87OwYyEBbzfsWdgN+xfn4MBXPXDg6x44wOWav+VyzX3DSzZ/nwf8kAf8NAAHfroPf/z8EP5YNiYf8taqgODDgmWFEAqm4vRTTkV6KBXueBdi3XVxoucExJxyEv72QibuXvgIrls8AFd83Q+Xf9MPrb/JRetvB6D5V7lo8VUu2nw/CK2/ybPrWy3NBVPrb/MKUqulPKYfWn3dFy2/6YNwORdtvsrFNYvzcNu8+3HWw20RUz8GMYk1EOupDZenDtw26GVELwXD7+D9+Vt4+mMq/Y+JfWc6Hp2OSpYV8irkdTrDzbIJeQkiFPIqyK3sILeo+6+skNd8zjvnTAGXRVk5xjxPpPnicHVyvJyvOlhpM21R/UN4WFgSwEj9SVQvn73ME+pyJRYBvGLN53RVywuoFVtY+8ztzDv3M+sIdAXw0rJPvV7vIRBXAK85jub4FpU/Eq07z8v7Ej3R8tysO5Jr6LFH9i6t/af9pxpQDagGVAOqAdWAakA1oBpQDagGVAOqgeJroNSQ1+m4DQYCSPfXwj6BvBteyo/ofRlYQ+D7HPYsHYJti/pgx6Lu2L0wC3sXdsMfhLxLuodBLyHv0l7Ad32A7/uF0w+5wI95OPDTIOz/aYgNec+zl2uu2JA3LZSK+hkZSPR6UdNbGzGpJ+DK0Xfi5rn3o/USwty+aPZ1H1z6VW/8dXFvNFuSi2ZL8tDcTsz3RbMl3H5oavZ1P3tby8V90XJxPzRb1BeXLu6LSxbzPL3QfEkftFmUi7/N7I9gbjPEpB2Lk5JPRqyXkJffBKYDi3CXDiyFvEf7YWE6D03HpeQV8irkdTrGzbJCXoW6zrm1KperI+Q15xyZL2R+MK0ASrOusLycxzx3Vc5Le53W7B/pv0hWlgkW2MtnMJdvJuTlM5hRvgSWAnhpzed0VcsLvBVbnPaZQFf6iXUSDS3fP2bZOQbmOHEMnWXnuB5tLTvPL2XeB/P8Bw3ao31dPV/x/zjVvtK+Ug2oBlQDqgHVgGpANaAaUA2oBlQDqgHVQPE1UGrI67cCkEQnNCN7D4G86w3IuzY/snfzi8Avw/Hb/D7YvbA79i4IQ979i7JsyLv/q+52NO+Bb3vZ0bwHGNH7Yz8c+DEXB34aiH0/PoD9v44BIW+av2aFjeQNBlMRSk21IxfoRDw2uSbO6tkGd815FJfNzUXThb3QZFEvNF7UC00W9sSF83rh4rl98dfZfdFi3gC0WjQQTef3xIULutvpooU9EE49cdHCXrhkQR+0mtcPreflovm8/rh0YX80XZSLJov64KKFfXDxgn5oNrc/rpl+H066Ph0xwRqolRgLj0uidwl4FfJG40EhzkJa03EpeYW8CnmLcqAL5OUzVSN5FfhWZcBrvzdYXP3CQmr+fMnnI5drNSGcgDgnKDqaZblGccGO+Zwv6Twix/L+ZV440rbIeeTcYkt6b5Vlf2mf00o/0BbVpzLeYrk/wR4hpRl9SkAp0NKEmkU9wyvjNrbNTIW1QfbhdukPWvYRwTj7zoS7XImC/WqOizPPMTTrnGPK8pHq0nmOSNdg5C7vNTEx0U7UD/VxpNfW44v/B6n2lfaVakA1oBpQDagGVAOqAdWAakA1oBpQDagGSqeBI4K8PisAJsLeiJB3Lb/N+3I4MZp3A2HvC9g6vz92L+yB/Yu64cCSHIBw96se4Ld5D3zTCweWMpK3L/BDP+CnXBz4sR/wywAcWDYEB5Y/hgtCMUivyJA3lIpgahpCGemITXShzvkB3P7pELSanYdLF+Wi0cKeOG9+d5w3vwcumN8bF83ri9qPt0ZM/waoPaI1Gn7UDU3n9Ubj+d1xwbwcOzWc0w0XLe6NhnNycMZH7VHjocY4ZmBD+F+4CZfMzMOF83LRaH4fOzVe0A/nz+uLZrP647L/ZSPm9GNxfHJdeN0J8LgE7grwLZ1w9AcXud9M56HpuJS8Ql6FvIU50FmvkFfBblUHu2b7qkIkr/nMd8IkmSfNfTgXFAUgS7tN5hhauZ5cv6pZaV9h1uyLSHnCO+kns79ZZ87RjOxlIsAU2MvndFWL7BV4K7aoOcq5TfqG/UTAyzksFArZyx3Xrl3b1rqMU6Sx4DazXvY17ZHql+cyz2GeW7b5/X4bXHOcef8EvtSJbDeP13zk91/tF+0X1YBqQDWgGlANqAZUA6oB1YBqQDWgGlANlI8Gogd51xHuvpSfuGQzI3tfAda/gk3zBmHnghzsXZiJ/YvvxR9fZeGPJTnYv4SQty/wbS7wLZdr7gv8nIs/fuyLP37Oxf6f7gdWPI7zfGHIS6cMk+k0Lu+8ZQVhBYMIhFKRkhHCX5Jr4eqhHXHltAFoOKc7zp2TjXPn5eDced3RcH4vNJzdC3WebYuYPmfj2NxG+Eu/Jogd2QYXzu6NhnO7F6QGs7PQYHY2zppxL2KGNsJx/c/Hif0a4dj+TZAx/k40nZOLxnP7oNHc3jh/Xi+cM7c7Gs/vg0s+7wVv94sQE6iJBLcHHpcbcbFctrl8BFfVr2s6D03HpeRNB7JEwtBpauadTlQtVx8wrJBXIW95z2Flef3KCnmLO4+Z8wHzMg9IlCAhEpMJGp3bIm137i9lOb9Y5/VZLu69V8b9zPZKH0Sy7FOpl74zLaPJ+TsgwDznnHNscEmIWZ3nYlmSWd5XzOhdzluM4mWfmTqXPi6sTvRojls0dMf7kPNynFmWazPamG0xE9vDMrfJt3l5HI+RspxPrf4toRpQDagGVAOqAdWAakA1oBpQDagGVAOqAdVAeWsgipD3lTDYFdBrf5eXkbyvYtO8+7BzQTb2LuyMfYu6YO+ie7FvcQ72Lu6BA0vz8MfSQdjzzQPY8fVD2PXDMGz/YTi2/zQSO5c9hS3fPovzQjFI9de1AS8hb9AKIhCw8lP5QgI6rYOhEKxQKrz1LdRsYuGOCYNxyRd9ccbcbJw1Nwdnz82xIWyDOT1wxhc5qDG2FWIGNEKNvo1xXN+mqDG4GRrP6gtuN9O583oifUpHxNx3No7pex5O6tsEx+VdBP/zt+CiWbm4YE5vnD+3F86d1wNnzMm2r8O6pm90RUz6SYhLjIfb44LXoz+8aP3wTGelODhNq5C3+gDb0gABhbzl+/wuS8Cp1wrYSzVXxuWaC5s/zOc/8+az38ybQPFo583rOO/HLBfWhspcb7bP7AdnXkCf1DvHQOoZzZmenl6wwgJBpkSulibqtTRzQkU4xoxcZrsJQBm1SwBOy+1c5phw3NmXLJvjwjz7V+qoN8nTRkN/cl6OJxPvKSEhoWAs2R4ZT/mHO1qONRPf2wh35b6jcY96Tv27RDWgGlANqAZUA6oB1YBqQDWgGlANqAZUA6qB0mogSpD3FWDdq8AaRvNyyeZ/A2ueB9b9C1j/b2yY2x875nfDngWdsGdhF+xeeC92L8rBniW9sHtRb+xc8iBm/K8HRg28Fh1ubYirWqbhyhZpuLJlPXT4Rys0OjeE9DQffH4f/D5fAeT1VwDQG45MCtqgt+4pKQhlNsc1Uwfj/C964dRZ2ThtVhbOmJ2N02fn4LRZOThrbh+4x/8fYgY1wvGDLsExeX9FwjO3oOGMvjhrVk87nT27V4E9e3ZvxIxujpjchqiR1wTH3ncJzpzQFefP7INzZnfH2XNycOacHJw2Jwtnze+Jc2b3wmVTB+LEyzNwUpobdb114XEzqiE6zrTSCrGqHGc6K8VRbFqFvAp5i3LaK+RVyFud4G9VieSV5775rGc+EvAqqs55fGHlos5hbjOPl3sUW1XmXLMd0rbDWbNfmDf7jHnCStbL96EJBAl7CTQJ/Qh7GdlLEGgCUHm2m1GvUleZrbSRbWe72X4mtom/YenPwqLOixoPjp+53RzPo5Xn+eVcHEveN+9f2iVjI+NmWoG93Ifvb2yrnEut/vGtGlANqAZUA6oB1YBqQDWgGlANqAZUA6oB1UBF0EAZQd4XgDXPAeues7/Ju35OLrbN64rd8zti94JM7F6Yhe0LemD31/fj2/ez8PC95+O6FkFc2eJstLz0PLRudTEua30JLrv8UrRq9Vc0b3EJLm1+Cc5pcDaCloWAn2AgCL8VhM+y4GddoHxgAR1evKfU1FTUPSuABiNux0VTc3Hm9J6o/2UO6n+ZjfozslBvRhYyZmTh1Nm9cOr07kh69e+IfeIauJ+9BQ2m5OKML3vjlBk9cOqMHjhtRg+cPrMnTpsRTqd8mgX3uGsR+1hbBMffhfOn5+LML3vijBndcc6Mnjj3y1644Ms+aDK9Ly7+PA9Xf3A/zrq3LWICtRGX4oLLVRdud/whoJfRDaYjrCKIszLeg+msFMenaRXyKuQVh3Ikq5C3fJ7b5TVfVPfrKuQNLx0rc4TMH865T+plPyeULKosx8g5aHl+zvnO61SVstnWSHnpE7GR+o/HcTu3Cbzk75WQk89pQsKqCnnZLpmfBISyjm2WtvMdl3ph/wgUl/502khjIHU8h+Rpj6YGneflt3Y5foTV0i5pZ2GW7Za281juF+keq/LvKVJ7tU6dGKoB1YBqQDWgGlANqAZUA6oB1YBqQDWgGqg4Goge5F37CrD6JWANAe/zwOpxwJpnD4G8u+Z3xK4Fmdi5MAfbF+Zi8cQc/OOKdFzd7Ey0bnYBWjZvilYt/orWrS5Fq5Z/DadWzdCyVTO0sFNze9k4v59Ql4A3iKQgU/mCXkLetFAqTjojGU3H5+D0z3ri1Ok9UO+L7qj3RQ4yvshB+oxspM3MRoj2y+7ImNYT9af1Rr1pvZE+vSeCM7ojOCMH6V/m2MfUn9kD9WZ0t489hUB3em+cNb0PTp9GSNwL9ab1wBnT+6Lx5wPR4tP7ccOUR3DX1NHImfk8Hpj5GrKfGYJTLm4AV4oLCYl08NKZ5ipw9JoOKjOvP9aS/VhNp6LT0cmyQl6FvIU5k1mvkFchb3UCv5Ud8prPe+blmR8JGpp1sp/Tyvmc867Um9fgsXJO8zysEygp28Wa5ynqGuZ+kfLOYytb2dkms/+kX7mP1Ev/iRVY2KBBAxt8SlQrwSGX/mXUr0BEE5gW9ewvz228V7lf8z4EcJrRy9xP+sW07BuzbOad/W3qJdL7ZqQ68xhn3jy/bOM5ZAzT0tIKll5m3tlGsxwp7xxDwl4+u5z3ybKzjvcg96S2ZO/T2l/aX6oB1YBqQDWgGlANqAZUA6oB1YBqQDWgGiieBqIIeV8GVr8IrPlXOIpXIO/a57Fudj/8NrcLdszrgB3zO2PHghzs+uo+DO5wOq5pdhquaP5XtGnZHG1atUSbVi1wWcvmaNWimZ1atmyOFi2bo7mdWuCCRo3h9/ObvCH4AwJ5wxG94e/0li00CEfyBsOQ92w//jqxP9Km9kTa1O5I/7w7UqflIDQtG8EvsmF9mYXAl9kIfJkD//Qe+SkHvi+ykfxlFpK/yEJgehaC07MQ+iLbTjwu9AXPkWOf77TPeuLcKX3Q5KN+uHHOaPT96U08+9ssTN7/Az7fuwyz963Ckj3rsGzXBqzfuQUr163C59M+w6NDH8HFF19kf2fM6ZhyOqn0x1S8HxP7yXQ2mt/mjfQAACAASURBVE5OySvkVcgbyYksdQp5y/Z5XZ2AakVsa2WFvOZzXkASn/ECAQ9nua/zHGbZOeea28y8zCtOW9T15drO+co87+HyzvurbGVn+yL1n1nn7E9GrvI9SZZwFtjL57gA00jQVJ7zFdUK1OW9y3d3OScxsZySkmKDXGd/mH0VKe/sb1Mvkd43I9WZx/B8zjLreG3ZxjHid4KlTZH6XMbIHDNnPtJxrJOoXr/fX3BNaXtR7TXvW/PFf7fWvtK+Ug2oBlQDqgHVgGpANaAaUA2oBlQDqgHVQOEaiBLk5bd4XwbW8Fu8f4a862f3w9Y5mdg+tz12zM+0Ie/2RQNw7fkxaH2+D60aN8BlTRqgRaNzcGmT83Fp0wtxSdOmuLjpxbjkkr+i6cWXoMmFTdGoSVM0btIUlpUGKxCCxSWb8yN6uXRzeXyjVyBvamoajj/Lj6aTBiH4WW8Ep3RH6LMcBKZmw/d5NnzTspEynSnLTsmfZ0FS0rRuSJzWDQn5luWC/aZnIXl6Fqwvc5D60b246NM83PHFSLy0YRq+3PMjFu5ZgW/3rMVPu9fi5+1r8Ou29Vj1+0as3bIRm7ZsxpYtW7Bl8xZs3boVW7duwcSJE/G3v/3Nhr103NG5Rqs/msJ/NEX1jencE4efael0ZNSPLPUoDkRnpIjUq61eUFghr0Leighjo3VPlRHyyjPefK47oVeksuwvx5vziNSJNbcxL/ViI9XJ+WkjXd+s4z48l3mM1Mk1irLO+6tsZWfbnP3AvjLrzL5jnpHStWrVsvfhnC6RrvxmL+d2WRJYAGNFn9/lPglymdgGgmsmtsXn84HfsnX2g5TNvoqUd/a3qZdIQDdSnXkMz+csyzG8J25jxC7HQ9oW6V2qpJDXPBf7iWWOPa/F/mHbeR9Ftde8b82X7j1b+037TTWgGlANqAZUA6oB1YBqQDWgGlANqAZUA4dqIIqQl0s1FwJ5Z4Uh77YCyJuN7Qv7IvOqk9HjzmZ459+P4cNXn8CbTz+KPh1vw1XNL8TFjc7DhY0uwIVNmqBJkwvRpMlFaNKkKc4/vwlOP/3sfMgbsiN6uXRzOHEZ57L9Pq8NeUMhhFLTcMKZATR6vQ/qf9YfwU96wP9pNlI+y0bS1GwkTs1GwudZSPi8m528U7vCTJ6pXcHkzrde7jcty06ExPU/7Y5LPh2AQb++hQ/3f4elu1dg/e5N2LRzC9ZvWY+Nv23Exq0bbLC7ecsWbN60GVs2bcbWzVvtxPLmzZuxceNG2z777LO2o4oOMq/Xe4gDTX80h/5oiuoP07kXydlJh7A4gukgFMejmZc6tdUL8HK8FfIq5I0WUK2I561MkNd8tjPP57tArsKs7GPOBTyWcwhhkKSi5pRI2wRoyTa5N7lOYffDetknkpXzyD3y/JKPtE2uX9ms2RbmI/WFWefsT+c2lhnRSSAq87uAXoGBFXE+F2gpcJfAkvfNxLmI8JLvg9Sb2WYzH0lTzv51lk29OLXMbZHqzGPM87FexpCWzzm2Q/pd3q2krVI+0vEQQMzz8Jy8Hp9n7C+5P7k38941X/z3ae0r7SvVgGpANaAaUA2oBlQDqgHVgGpANaAaUA0UTwPlBnm3zOmC3+e2x/Z5HbF9fhfsXNwTiydk4r0X+uHLd8dh/oRnMOuNMZj22ihM/vdw3HbVJWh9SUNc1KQhLmzSCE0bN0bTxk3Q+IImaHBOQwQCqfmJoDcIK2DZqawd22HIG4QVCuKk0304Y/g9OHtyHkIf9UTSp9nwTsmCe0q3cJqaBffUbnZyfdYVkZJ7SlfYaWo3uKZ2Q/yULrA+yMKVnz6MZzZOxzysxg+71mL1tg3Y+NsmrN2w1ga7m7Zsyge8v2HzFqYt2GRD3U3YtHGTDX0JeRnZS9DLyN6ZM2fakRt04ImjSn9IxfshST+Jc0+cjqYzlHlGe4gT2HQ2mvkjdT7q8ZUXDivkVchb1nNWeV6vMkBe85luPted4K+wsswBch6ZKwiyJEndkVg5/5HcI+/VPA/zvKdIdUdyrxXtWGf7ZMwOZ03Aychetis1NbVgtQ7CRgGOsgwwYWB5zdF8z4iUeE+M3uW7CQEvl6GmNmvXrm236XD94Ow/Z7k4420ew/2dZTmHWS95biNk532XRf/KWIp1jieXtZZ/lqRG5BvZvF9ph9qSvVtrf2l/qQZUA6oB1YBqQDWgGlANqAZUA6oB1YBqoHANRBnyvgCseT7/m7zPAGueBdY+j/Wz+mHT7ExsnXsPts3vaC/ZvGtxDtbO6Id5kx7B/PefxdcfjMOCt8dg7n9H4vNXh+LNp+5Dp1taoUWTU9G8yZlocWEDNL/wfBv2nnduQ/gDqfBZqfZyzYzetQKBglSWTuwCyJsWQp3TA0jpfBkufDsPock94P44C65PuiHuk3sR92k3xE1huhdxU7qi7qddIqbYT7vY2+M+64b4T7oiYXJnXPhJHl78fS5m/P4zft62Fqs3rcWGTRtscLthw0Zs3LjZBrqEups2bbXTuvXr8du237Bhw4aC6F1CXkkEvUzz58/HOeecYzvY6Nijo08dU4X/gJwPF3E60kZyjCrkrbwA1unIjUZZIa9C3rKcr8r7WhUd8prPc8nzue4EuoQ4AnJM8GfOAXK8zBkCeGmlTqzsK1bqD2dlf7G8PvOR7tnZBud9yzki2cPdR2Xb7myjOW7Fzcv4yzuTE5yyXBgUjMZcUtQ5BfTyngihzz33XDvx/pKTk21AKZphew7XB87+c5aLowfzGO7vLJvn4D1Rr7IP21GW/ygn4yjW7Gveh8B9Ab3mvWu++O/T2lfaV6oB1YBqQDWgGlANqAZUA6oB1YBqQDWgGiieBqIIeV88+D1ewt3VTwNrxgFrn8P62X2xcXYmthRA3s7YvTgL62f2xZLJj+Krj/+FpZ+8gIXvPY0574zFtP8Mx0cvP4i3nuyDoT2uQ177y/Bw73/g+ssa49ILL8AZZ5yFFCsVKVYIPssPv+Wzl2wj6C1rJ7YJeT2nh3DsRSG0eKUvUif2QN0Pu6Huh11R96OuqPvxvajD9ElX1P6kC2p9nFmQan6ciZM/zsRJRqrzWRbcH3TBWR9k458bJmDenmVYvnUtVm1cg42bN2Ld+nXYsmUrNmzgN3d/t0Hvxo2bCuymzRvw+zZ+i3dLQfSuLNUsEb2//fYb1q9fjylTphR8f41QUn9MxfsxsZ/E6UgbyTFKpx9BHqNm6JgU52BZOijlmmorHnBWyFv2z+yyniP0egfHuKJCXj675Vke6TnuBKQCeSPtK+ehNedSgipJZr1zHnEe59y3qLJc27wv571HKpv7My/nEVvUNSvjNmlXca2zfxjFa/ZjnTp17DL7QpZtlmWQy3Ou57WZ+O4hgJfvIoSSjIR1totlattZX9x+kv2KownZl5a/C7Mc6XhuZ+Qu+7Ws32UE7oo1ry/jy23ynhfp/rWu+O/V2lfaV6oB1YBqQDWgGlANqAZUA6oB1YBqQDWgGihaA0cAeS34rXBi5GwwEECGvyb2rp0ArCPgfQFY9RywelwY8K56Elj9lF1eP7M3Ns3uHI7kncdI3s52NO+mWX2w9MNH8dWHz+Hrj/+F+ZOewsy3x+Dz1x/BJy8OwITH78WbQ+/Cf4e1x/hR2ehxz9VodmFDnH3W2fAHCHiDByGv5S9zwEvnfRjyhmClpiIhw0JMSk00fvAunPpub8ROzkLsh91Q56N7Ufuje1Hr466o+XEX2FD3o844OT+d9FFnnPBRJo7/OJxO+KgLTv6wKwLvZaHTkmfwGb7DD1uWY9PGDdiyZRPWr19nR+HOmzcf7777HqZO/QKM6JWoXsLe9evXYOvWjfa+XJb57bffxqxZs2yoS8i7bh0h8UEA3LdvX9vRpj+gon9Azv4xHZNOxyjLhLyyXLNC3ooHWU1nbVnmxfku2qDDnUs++nw+2/muYPAgGNS+qDp9UREhrzy3TWjHvNTTOrdJ2dxH8uacYM4XAnhpzXrmzWOYd24vSdk8V1H3Lm1wtpXHmOc40vspyb2X1b7O9h2uLGNrWmf/mWWBkVwlhc94zi0CA8tqnjGvJ/OMLCXNe40Ec2XszXZK3eH6yNxenHE09xfIK9d1Hs85gACViTBV5s+y6kuBu2LN60o/yzYph0KhgghpZ3u0XLL3bO0v7S/VgGpANaAaUA2oBlQDqgHVgGpANaAaUA0cqoFSQl4LBLv89i1T0AoiFPCjnu9k7FvzbhjwrvkXsOpZYNUzYbi78gnABr3PYMPMXtg0qyO2zr4b2+Z2wI55nbBnYResnZaFhW/fhwXvjsWCiU9h1luj8eWbw/H5aw/g03/1waQxHfH+iHvw7rB78MbILmh/fRNc0uhs1EvLQMgfRDAQhN8K5IPesCOc5UgpmqDACloIpqbCqpeOWkkenHBhBs57IxeeCTmIm5yNEyZ2wokfdsHxH2bihA8748QPO+GEDzoWpOM/6IgaH3ZGjY8yUePDTJz4QRfUntwNZ03oh/9tXYAft6+yl2jelL/EMpdg/uGHHzBmzBgMGzYcjz021l52ec3qNXYkbxj2bsS6dWsxb948jBo1CmPHjrUTj2NELyN4JbKX5/vxxx/tCAn+YOgA1B/OoT+cw/WH6bBkXhyjdF4y8qRBgwYayVtPIa84h+kIpi7MqCoCXoG8hL5M0Xxu6bmrDjytLGNZUSCvADmBSlKWJXilLNsPZ53Pf2f5cPNHNLbLPci9S5uKY+UYOQdtSe7RPK6kx5bkOkdrX+f9OsvSH5Gs2Z/cTg3x27ZcFYWwl2CVz3k+75kXCChzwdGwAhh5Lp6fZV6LkJmrRTCxnkszs22R2mHWOdvvLB9pvzvPJ5CXfcn7kD7lc43tcPZRNPrQeY0jLbPPee+cx9lf0mbpOynTSp3akr13a39pf6kGVAOqAdWAakA1oBpQDagGVAOqAdVAddXAEUDeMOA9FPKehH1r3gFW8zu8zwOrxgGrng7D3ZWPA6uesIHvppk9sWVmR/w+627smNMBu+Z2wr6Fmdj8ZQ4Wvtkfc98cjvlvj8GMN4Zi+vgh+OzFPHz2fA9MHt0eH4y4G5NHd8bI3jeheUMLDc5It6OIQ35GEwfhD1jw2RHGB+Guzwa/hL/hROgbTSe4FQzakDe9Xj3UrRuLGH88ErPb4rQ3+yBhYg8cPzETNd7vjGMnd8RxduqAGpMPJtbV+KBzOH3YBSd90BWxk7rhpvnjMG/3KqzftAEbN4W/oUswSyi7ePFiG96OGDHCttOnT88Ht5vzI3o3YevWrZg6daoNg0eOHGnv99VXX9nHE/IyMaqX56PNzMy0HWy6ZHPJH5Cmw455OirFeccIXkbSmM7KyuCkPFInpx5fONSmJiQyiVqgI1ghb3Sf09GcA/TcxRu7igh5BSgRzpmQ14RezrzzeX+4cnm+cMp8JO0sjpX2mu0qSRvM45gvybEVbV+zLdIvTuvsU9ERl3Fmewh7+bw3I3s5P/LZL6mo+VL2ERtpX16D9bIss/wTES3hLt/reN+8J+f9O8tmm6Mxfs7zC+Rlv/FeeL8CyAmsI7W3MtRxvHifbAvbxLZJf5p9UNE0r/dT8r8BtM+0z1QDqgHVgGpANaAaUA2oBlQDqgHVgGqgLDVw1CHv3tVvAaufC0fxrnwaWPkkQMC74jFg5Vgb9G78sjt+n9EBO2fejd1z2mPv3A44sKATds7ujnmv5WDGq/djxvghmPrSIHz6r3748OlsfPREZ0wedRfee/R2jH/wTlx4RhLOPas+goEUBAL8Dm/ABrzh6GLLzksEr8BdsdGGvMFQCKlpdLDVR5LHgzoJsYgJ1cFZg+9A4L/dccKErqgxsROOe68j/vJ+BxzzXns7/WVSe0iq8V5H2OmDTJz0flfEvd0VvVZPwtzfl2Hjpg02iCWMFci7cuVKvPbaaxg2bBjGjRuHX3/9FaxjFO+aNWtsgMv9f/75Zzz//PM26H3ppZfsbQS6kSDvW2+9ZS8vR4dbWYqyKlzLdNgxL05TOn/FWUnIy2Q6aiuzA7MyOFkr4j1y/KkDie6iBgTwaiRv8WChQtXK2U8VDfKacK4wyOt8tpemXJ5znNyvzEmmNdtv5mUf81jJ0x6uPea+xdn/cOcrz+1mW6RfnNbsO+YF8pr1hHwEsAS9EtXLMtORzFMCEnkeAbsyt/A5yfvnfcg9syz5wqzZZuaPdv87z8/74DUIovkPT9I/5rvSkfRReRzLeZ33z7bInJ/Kz7okJBRE9Uo/HO3+1fOpY0E1oBpQDagGVAOqAdWAakA1oBpQDagGVANVWwNRgrzPhr/Fu/IpgMs025B3TAHk3TAjB7/PbI+dM+8qgLx/zO+IPXN7YO4rnTHt370x7eX++OT5vvj42R6Y/HgXTBx5F94fdRfeefgWjO15NRqeEo+0kBe+FC8Clt+O0uU3gq1AONGZVV6Q17KCqH/KqUhLS0NCfCw87ljUTY5HzBkJSBt6F/z/zUGddzJRY2IHxLzXATGT2ofTxPaImXAP/jKpA46dcA+Om9QBf3m/E06YlAnX/7rgnzu/xPzfl9nf4iWwNSEvYe/atWvx3XffYcWKFYdsI8DlvvzuLhMB8NKlS+39WBbIy33MSF5G+UbDoVcdHirirDMtHZd0rtKxJ04+Ol8F9NIJKIlOSDNfHk5JvWbhkbcl6RuOtXN/ji3r6IjndkZ2M7HMfwJQyFs5oaXC5pKNW0WGvCaQkzyf4YXNieaz/nD58p4DI92fE/BJm2llmxwn/SDlw7VH9hN7uP0r8nZpg2mlf8SafSd52cbjmJeoXkJMvgeYSeZ+sc75I1LZOafIPw5xXuG7KP9Zj8tG8/qFjanco2nNdkZrXMxrSP/wWvyOLaHokYLvSP1VVnUyLnI9zvdmYr2z/dHqZz1v1f6DXsdXx1c1oBpQDagGVAOqAdWAakA1oBpQDVRfDRwVyEuwym/yZqSciD2r3gRWPwusfAZY8SSwIj+Kd/loYAVB7+NY92U2Ns9oh99m3YFtc9ph57yO2D23I/Yt7INv3uqKD55oh0lPdMHbYzrjnVHtMWFUO7w7/B94Z9gdGNenDf6ZeQn+PaI9TrOOQbrlhhUwv1XJbwXT0czo3nCEr0Twii2LSF6CmnoZGXDHxcIdH4c4jxvHMaL3VDdOve8WBP/bFSdN6oRj3u8UBr3vdUTMpA6IyQe9x0xsD6YYRvRO7IyEd7Iwav88zN/6CzZtWI+N+ZDXBL3MF1YW0CuRv7Kv1EskL7cT9NIuX74ciYmJdqSBPiRK9pAQp53pLKVjVSJ66PgTJ6xEqdDZJ/XiEDQtt0ky6zV/dGBsWfSjjB8tr0fnNZ3wEmnFfwBghJdC3pLBQoWrlbO/KgPk5TNcQJ3AMT7fq8IKFzJPiTXnKzNvtl/6gNvlONNWp3cFs91m3uw75s0+k7L0Kd8J2Gf8LXAekPmA7wfyT0DOuUnmEbOe4JD78zj57i73S0lJOWScnPfGsnnvkfLRHlPnNXlP/H1J1KvZzqqU55ixjZzz2QfR7mc9f8ne47W/tL9UA6oB1YBqQDWgGlANqAZUA6oB1YBqoLJooNwg76aZ7bBl1h34fc7d2Da3A3Ysysb6ef2wZMr9ePWxdvjv2M54Y2R7vDO6I94Z2Q5vPnoHHuveGo9kXoIHuzXH3OlPIhSKgWXFI5QahM/vg4/fsfT7EbC/uUtb9pDXCgQQCgWRnp6GehnpiOeyc/Fu1K1N0OvByQS99Wvj+AevRI3/tUMMo3ltsNseMe+GI3nt8sR7EMNkR/V2QtxbXTBs72zM3vSjDXnXrF5tR+4yepeJSzIzMS8Ru04r+9IK1KXlfqtWrbKt7MNzcblnClmdTyV/oInT0nSoilOXlg5MAj0zeofOWYF/kRyZ4tgtap9Ix2ldxYDA5vjJGNLBS6c+x57RVozqMr/Hq8s1V054qdC5eONWWSCvPMfluc55sTpDXie0lH6JZCvLy3Bp7jNSe1knehHr7C/Wm+8DBL2M7CXsI/iTb/XKP/8UBnxlTiHc5b6Eu7Tcn3MHrxPpfuS+xBbWDqkvTd+U5Bi5jmkV8pb8vbMkfa77av+qBlQDqgHVgGpANaAaUA2oBlQDqgHVgGqg6mggOpB31ThgxdPhSN7lY8Pf4/111MFI3unZ2DSjI7bOugvbZ9+F3+Z1xIq5OZg5LRcPPZmJh5/oiXGjMzF+ZEe89uhdGJd3PUZ0a41/ZjbHI9mXYcwj7fDgk73gOdsLV8iDxEASkgMpSA74kBwIL90cBr3hJZslgldstCJ5CXiZUoOEvKk26I2PcyM+zgNXHL9r60Xt2LqI8Z+MmN6X4tg37kbMxI6ImdAeMW+3Q8w79yDm3Xb2ks024CXknXAPYt7pgFpvZSJvy6eYuflHbFhPqLv6ELArkFdAr8Ba05r7yH5SR8jLJPU8bt68ebYjm443/dGX7EcvzkpxotI6nbp07DLKRqI5xKEr0TusZxJIKw5dAYRSr7ZiQNyixoHjKFFWBLsca4nYYplQkFpgMqN4FfIWDxYqVK2c/VRRIa/53JZnuXMOrIqQV9pKa/aBOXdFypv7mnk5n7PvqkpZ2ue0Zh8wzz6LVCd9yXcBSYS9/F1wviC0JbDlfGEmzhmSpJ7zCecZ/vOY81qHKzvv31mO9ng5r8ey1+vVSF53yd47oz1Oen4dD9WAakA1oBpQDagGVAOqAdWAakA1oBpQDVRMDUQP8vJ7vFyuuQDyjgRWjAZWPoZ1NuTthN9m34Ptc9phw/xu+OC9TOSN/D+0H9kNtw1sh0H9/w9DurXGw5kt8HBmSzzYpTUe7Xs9HhvaCQ+OzEKHET1w84PZqNeyEWLTkuEJpSAx6ENS0I8UKwx3CXrlu7xOGw0oQMAbzIe89TJSkZYWQlycG3GEvPFMbrjcHsT4a8I98lac/FZnO9V9qyviXu6AhFc6I3F8F3j/0wVx/8lE3TfCyfV6JqzxWRi47D0s/O1XrF27CqvXrMbqNWvstGbt2oI866QsAFfArVmOlCfYZVQvo3u5/fXXX1e4W0onm9NpaTpZxbFLK85Mgls6bRnBQ8cuHbyEhgJ5TcCrkLfiQl0ZL1pnnmWOMZ3yDRo0sPN0yDNylw5thbyVE1RGYy6pLuesiJCXz2rn81teYAl2j0aS81U062x3YfOWOYeZeXN/sx8rWjuP9v0U1W/OPolUlj4U0CvvBfzsh0T1EuJKErArlvvwvSAhIaFg9RWew3ktuU9zbKSuMGv2lWjfrDsa+UjXZls4X8o8WtQ/UVXWbfJOoMs1V8w/kI+GtvUcOraqAdWAakA1oBpQDagGVAOqAdWAakA1UBYaOGqQN9UK2N/k3b3yvwAjeQl5lz+en8YAvw4HVo4EfhmGdV90w7rp92DzrPbYvqArvvo8G/1G3o57xvTA7WPycEO/uzByeGc81v8GjOp5FUb1vhbjhmVixMgs5I3qgY4jeuD/hvfCzaPy8Pfh/XHhXdejdoYP7jQfktODSAgkw2cv1SxLN5cNPDAhb2pq0Ia8sfFxiI2PR7zbYy/XXMsVi5izkhB6NRs1/9MJ/hc6oGZ2c8ScUQsxweMRc34Kav3tPCR3aoOk7Kvh738z0u6/DacN+DtuHZuHb9b9hDVrV2LN2tVYTbi7dh1WrQnblavXhPNr1tqg1xnFK2Un4GUEr4Bd7iMRvR06dDhkqWZx8NGWhTirwjVM56XT4UrHrtTVrl3bBn10Vkr0jtjK6sCsrvdNx60k9gGd74zG4ngy0THPen7vms5dJgG8Ys1oXlnCWWx1AYDazrKZt8qzn8sL8gpMM635PJbndlWYg0rbBukDWpmnxAqULMzKfrTmeUp7L5XtOLPNpek/U5fMcyl/ziPyT0ICd+Wfwcz+Nvuc+Ui6dt5fefev835YJuSVubKqvkso5NU/9Mv7t6fXVw2qBlQDqgHVgGpANaAaUA2oBlQDqoGqoYFSQl46n/32EqOBgAUrYCHVsvIh7xs4sPJpYDmjeJ8Alj0GLB8dhrwrhmP/t/dj7fRO2DSrI9bP7oSVc3vg5ZfuQJcx3XDL2Ptwy5hBuC73Hjz13GA8N6oHXhjVHc8+1hP/HJGFnsOy0G54D9w6uh9ufmwArh2ZixvGDMRNw3Lxt16d4D4rDbHBJCSlMprXB78l91g2zvLwcs0WglYQ9TIyEEoNId7tyk9uxHncqJvgQkKzs9HkhT6oO+RGxDRLRkzoeMQk1UKdJBdqJblwrLcOYnzxiAnEISYUi5hQXcRYdXF8mhfTF8zAqtXLsWrNaqxaE4a6q9YQ9K5DGPKGoS+jeQXq0kYCu6wzl2lesWIFNmzYYEfzLly40HYq8oduQl0BvfoAKN4DwHReOh2xkRzk4qClM9dMdObSIVhVnZ1VqV0CeDlmhLvimGe0FbcR1hLwmsm5TLMAXbHlCeL02mUzf1THflbIW7x5pDzmW3PuMvMCDiPNX846mfPM45kvj/aU5TWd7ZV+KMo6+84EvdzG1R648oPMLwS/nEPYrqLOK9uc92SWy7JvIl3LvBfmec8KeSvusyHSGGqdjpdqQDWgGlANqAZUA6oB1YBqQDWgGlANqAbKTwOlhLw+BKykcAr4HZD3dRxYScD7DPDrU8AvBLwjgWUjgeXDsWVWV6yffhe2zG6PFbO74vMpPXDf43fgnjE5uHXsQPx9TH9ck9sJi1d8jy/mTMfET97B4McHo8uo3vjHqJ74v1G9cePovrhxdC6uH52Ha8b0x7Wj8nDH2PvRtlcH1EpLQlJaGPIGyhjyCvAOWiGcUv9UZGTUw4RJ72HO3LmY8eUX+OyzKZgyfSomTv8Ur83+GM9On4iXp07Cf6e8h/c+mYxJkydh/H//g9gEN072uHBighvHJ8ajRkIcTkyMR+1EF+5sfzdWrl5VAHgJdiMle9lmLt2cnwTmFmZXrlxZEMHLfFZWlh0B4vxxKuQtlmDj3gAAIABJREFU2Y/VdF6Ks1Ws06nLMh27jOrlPoQ+jGSRb7cyT2BIcKjAt+Is2ewcC3HCm99SZJ5Ai45rgbuM4JW8Ql4FqQp50+2odn6T1ARczEd6Vh5JnfP8cg0+d81ntnP+q07lwvpBIBz7qrhjIHMej2Ufyrmran9K+8RK+4trzX41j5HziZX9zH0i5WX/wmx5j4PzvtgGhbwle9cs7zHU6+t4qQZUA6oB1YBqQDWgGlANqAZUA6oB1YBqoPw0EAXIO/5QyEu4u2w4sGwUsGwY1n/eDhun/QNbZ9+DH2dm4alXO6DrmA74x2O98fd8yHt1bhcs3rgRX6/bhNe/+AxdHhuCW0fn4ebH++PmJwbixrEDcNNjA3DdqFxc89gAXD60F64a3gc3D+2Hhjdejvh0H5KDPiPauKwAggWC3lAw1U7BUCpmzp6DPfv2Ye/evdh/ANjxB/A704Fw2sr8fmD3vgPYvXsX3n//fbg9XngTkhDv9iLO5bYTl3uOjXfBk5iIV14bby/LLNG7RwvySsTvu+++Cy4Xa0bwyo9UIW/pfqyRnJiRnLGm01aWcOYyjea3+AT0VqXo18rcFifkZVsEzMtYybLMTkvIyzr+3iRqN5KtjgBQ21xW81b5Xae8InnlOStWIC+f0zLXqT0418m8L+8E7Cdz/pJ+LI7lcTIfVtU+lvaV1pp96+xrs//M/YrKO++jovW78/7YFs6Nulzzwd9gRRszvR8dG9WAakA1oBpQDagGVAOqAdWAakA1oBpQDVQcDZQS8tIpLEshh5drTgsGkZFyAnatyIe89pLNT4SXal4+MhzN++twbJjWEVu+aI9tszvh+5k9kTv2Dtw5Jhu3js7FbWMH4+aRech8eijmb9qED7/9Dp0eH447n3gYtz/9IG5+4j7c9Pjg/HQfbhg7EFcM621D3sse7Ymrh/bBtffnIL5BPXhD5QF52S8WLCtoR/GGUlMxddrn2L1vL37btROLflqBm7oMwOXt7keL9sPRrP1oNG8/GlfcMwQbdwG79u7FO+9OhMebCJc7AW4PQW8C4lzeAuv2JiEQTMVHn0zBsuUrI0bxrli5GqtWMa0qSIzOlcRlmRnhK2Va1jF98sknSE9P/5MTlk44/eGW/ocbyYlJR6Y4xc28WSeOWzrXOS5c8pcAMVI0L2GwpMoMTSvTvRPwcllmSRwXfneXcJftILCVaF2xhLry7V2Bvgp5yw80Kkwuv76vKJCXz1w+a3WeK94cJ/OZzE9iZe4qysq+co7K+F5R2L0LDHe2SfZ3WumLw1keF2kfqXee11l23k9FKzvvl21VyFu832JFG0u9Hx031YBqQDWgGlANqAZUA6oB1YBqQDWgGlANlL0GSgl5wxGrBJrhJYoD9jd56/lqYd+aCTiw8lmAkHfFWICAVyDv8rFYPqU3VnzeDyun9cOSmf9Ex0f+geuGZuGGEX1x8+iBuG5oX9w+ejA+X78KeS+/gNtGD8GtTwzB/z35AG5+8gH835MP2envTw1B20fDEbxtR/bDVaPzcO1jA3Hd8FykX3Up3KlcUlpAdNk6scOQtz5CqWmYOm0qdu/bg9/37saGPcD0H3ehbben0Lj9M2jY4QVc0P4FNLtnNNbbkHcf3n53EjzepDDkdSXYlsDXTp4kxLkT4E3yIa3eKXjzrXewnDA3/5u8YksKeQmDCXgnT55sw0N++02cbvKjZFnyakv+Q5X+FBvJYcs6cY6bedYx0owOZEJD+dYro1wIFQWKCuA1rWxTe/SXdxbAyzGQZbUJeFkmvCI8JMwVkBsJ8ha2TLOCx7J9Zmt/l09/K+Qt+VxSEeZfmcec1jmvyXzmtOZ+cg62i/mK0L7D3YN5z+a+JYW8cp5I1tlHZlnyPI75SMebdeY9VsS8ea/SJoW8lfPZUBH1pfekWlINqAZUA6oB1YBqQDWgGlANqAZUA6qBqq6BUkJeOoTDECNgpcAK+BDyB1Hf78b0//0TB1aMB1aMA1aMAX4dASwfYS/XvP+Hp3GeFYMzrWNwphWDQOhY3HJ/e1z5UFdc+c97cdWjOWjzYDdcNqgbnls0HbcMG4RbRg/CzY8NxE2P34ebnhiMm58MQ9+bRw3AlQ9m4+rhfXD1qFxcPToPfxudh+tHD0TLnHaIT/XBX26QN4SMjNOQGqqHz6d9jr3792LHnl3YvBuY8cNuXNXtGTRs9xTOued5nNfuBVxy1yhs2AXs3rMP7777HrzeFLhdCXC7vPBI8iTC5UlEHbcHtV1uxLo8SEz2YdDgB/DdDz/hp19+xdr1G/HLryuwfMUqrFzJdGj0rkTrLl++3I7klTIh74QJE2woRWcsHZV0tJnid5bNbZo//IMykhPT6aiVslinY5xl+V5lamqqDXsJFWVpYMJfE/Ayr3A3OnBXAC8jds2ltEOhkP0tQf6jBL8pKICXViCvgt3yAYoKcitev5cX5JVnrFg+W5nnXMb5T+e0w89pkfpI5jnpV9NGms9kuxxXWd4z5H6dfVAY5HXu5yzL+Yqy0le0Re0XaZvzehWt7LxntlEhb+l+gxVtbPV+dBxVA6oB1YBqQDWgGlANqAZUA6oB1YBqQDUQfQ0cAeSlw9iPgJUMK5BiQ94MfxLOS62JFx69C/tWvIE/lj8P/DoGWM7v8Y7Gvh//jVN9xyGQ7EaqlQhffR+uz+uEKwZ3weUPdcVlD92LFoMy0bTPPbh73FBcPywP1zzSC9eP6IdrR+XhmlH9ccPY+3Hz2MG4+qGe9rarh/XB30b2wzWjc3HtGG4fhBse7IXYtBSkBFIOAb1WIPpObl4jaIWQnn4q0tLqY+rUqdi3fx+27dyNxT+ux/WZw9Gs3WNhyNtuHBrePQ6X3jUc63YS8u63IW+CN6kA8HpdXjDFxcbD7UlArMdrg15CXpeHSzl70Piipnjx5Vfx87LlBZB3xYqDSzCbyzET7EaCvOPHj7cd26YD0fwB0glnljVfsh9nJCemOG25TfKmNZ3irGdZvh3JMkEil3AWyEjgSPhogl6FvEcX8rJ/BfCaEbyE7lxymWNC5zQBL61AXjOiVyFv9J/DCnQrRx8r5C3ZPFLR592i5rmi5jZzm5yjIre1sHtUyFs6PUt/iqUeFPKWri8r8u9G703HVDWgGlANqAZUA6oB1YBqQDWgGlANqAZUA9HRwFGAvD47kjcY8CM1kIL0gBv1A7XQu9NVWPPVeOxf+QL2/jQcWDYG+396CWdaNZEeDMBvpSAxI4Dre3bCVQO64fLBWWgxuBuaDeyCi/t1xJUP9UTbh3vhai7JzDSUMLc/rhnZH1cN7Ys2Q3LQ9uHuuHpoL/xtRB9cM7IvrhnZD9eOzMVtQ/OQ0eQcJFnJ8FnhZZutgB+SDn5P+Og6wgl4w5A3iPr1TkF6egamTPkUe/cfwNadQPfB49D87uG4sN1TuKDd02jU7klcdPcYNL/zQazeAWzfC7w2/nUkeD3wuJjCkbyM6HW7vXC5+W3eyImwN61efXTtlo1/v/gSli791oa569atsyN6CXcJexcuXIg333wTubm5eP3117Fs2TJ7qealS5fakIpONkIo/cFF5wcn/SrOTLF0ajJvOrsjQV6pM/djnlG8XDKYoJfwkWUBkpFAr2wT69xH6sU6t1e3MmE6E/uW30VmXzOlpaXZIJcOaWcyAS9/U5IIg53f4FUoeXSfxdqflaM/ywvyynNUrPzzDJ/B8oxWW/o5UOY105pzlvS7ac3t5nEcB7PMfEnHRuCr2JIeX177m+0278GsL01/mOeqCHlne6iF6gh5q8JYVgQ96T2U/tmtfad9pxpQDagGVAOqAdWAakA1oBpQDagGKqcGjhzy2vA0DHq5bLO9dHMgCfUCHlzT4jR8P/MJ7Fn2L2DZU9j78ys4LVALwUAAPssPTzAFZ7Zoimu6d8IVuffi8kHZaDWwG1oNvNdOl92fhTYPZNtA9/Ih3XHlI73txPxlD2bj8iHZNuS9ZkRvXDWsJ9o+ytQLNz/cG2c2b4xEKwkpFpdt9iHgT0Ew//6iCXnZtmDAQv169e2Iyk8//Rh7/wCWb9iLNrfnofHtw9Hg76PR9M4ReP6TVfj3x7/gijv6Ye12YMde4D//eQOJXg+8LrcNet1uLh3pgceTcEhiVC8jeSUR/kre42UkYaINpRo2bIjGjRvjggsusIEUIw3p6OQPlg6lm2++GVOmTLFhb8uWLe062a4/6uj9qJ1OTSmbjm6nA9xZNvflMs4EhwSPXMJZlnGWJZydUFbgrdiSbnfuX5XL7CP2IyOmCXhpWSZIpCOa/W4CXoG7tAp2KwdsVChcPuOkkDd6c0xFmL9lXjOtzFvmfGbmZbtY81jJl7RtAnfFlvR43T+6OpVxFcuxV8gb3T5XTWv/qgZUA6oB1YBqQDWgGlANqAZUA6oB1YBqoOpo4Aggrz+8XHPAh0A+PD0IeVOQFkhEfSseTc704JM3HsCOH57H9p9eR6qvJnz+APx+H6xQACmpAfjPrI9Lb78BbXt0QuvendGyX2e0ys3EZf274PJB9+Jywt7B2WjzQA4ufzCcGMnbZkg22j7CaF7C3R648pHudtQvIe/F17dBUjCl3CBvvQxG8tYDIe/u/Qfw7YqtaH5LLzS6fYSdXpz8DdZsB9ZtA956bxq2/L4Pu3bux+uv/QcJboG8kYXmcnsiRvQK5I1zueFyh48VYEvnGZeQFScaf8TMczshVffu3dGkSRO7Tn/gkfv9aPaLjIPTimOb1un4dpbNfRmJVqtWLRveE1gxordBgwZ2IvgVmFuYrcqQtrhtc37DmH3FfmT/EewSnLOOSzMLyKUjmnmxUi9WIW/5wEOFtpWj3xXyRn+uOZrzVknPxfnNPEbeR5zzm3Nuc5ZlrjPnS/O8h8sL3BV7uP11e9nq0hxX5jneCnnLdgxU89rfqgHVgGpANaAaUA2oBlQDqgHVgGpANaAaqLwaOELIGwa8hLwHQa8/HDHrT0bQn4gMvwf1U47H88PaYdPPkxFIqQu/ZSFAyOtPgd+XjCR/Mur6ExFqdA4uuLEt2nbvgLa9O+PKvplom9cVVzANuBdt78/BFffnoDUjfQdkotWgLmjzYBaufCi8dHPY9sCND/ZEm3/cCF96AL6QH75Aih3Jy2heJgLmaEAAWa45ZAWRkV4fGQWQdz/Wbf8Dt2Y9hAtueRA39f4X1uwANv+2C1t+24nft+3Gtt93Ys/OvRj/6uv2N3i99nLNkYVFgBvvAL114+LtSF63N9HeJs5MWkbv8kdq1pk/WtlOCGzWaz5y/x+NfnE6NZ1lcWqXxBL01q5d2/5uL8eUSwkTTMryzbQCPCPBXtlWXa1AXvmmMaN1JTKalss1E9oKwC3MCtg1Lf+Rgsnv9xekaDyD9JyVA27qOIXHSSFv9OaYozFPHY1zmO8dzPOcnNdMkHu4vMyD5jxZknuLdA8lOV73ja5OzXFlnuOtkDe6fa6a1v5VDagGVAOqAdWAakA1oBpQDagGVAOqAdVA1dFAqSEvQanfBqaEpmZivQ++QHh7yJeENJ8H9aw4tLr0PASDKWHAmg95uYRyMOhHIOiHPzWAlPQgvBlBnNGqKZrdeROu7d4RV/XoiMt7dECbPpm4rG8mmvfqgBZ9OqJlbmc70veKwVloPbAr2j7YHVcN6YGbBvdEq1uvQ2LQVxDJyyjjaC/XTMd90LIQJORNzUC99AxMnPQudu3bg6279+PT+T+hxe390X7AOKzbDmzZth2/bd+B7Tt2YtvvO7Bz+y68+tKrSHAn2KCX3+WN9GOLBHklipeWANiM5KWDk44znkucrJHOq3Xl/8M2nZ3i2C6upaPc3JfAl+CeQJeRqIxKFegrIFNgb3UDu9J+p2U/EOgyEYrLstd0OJvRumbehLnOfCS4S9CrkE9hrGogAIW85T/nlOW8L+8fAvLM+crM8x+W5DvJAoBlu8yRZXnfeq3o6lTGVCzHWiFvdPtcNa39qxpQDagGVAOqAdWAakA1oBpQDagGVAOqgaqjgUIhL6NSw05oC4EAk5TD9s+QNwx3w/V+pAT88Pn9sPx+hAIB8HypqSE7mi1AyMFoWn+KHc3LiN6gLwXB/HJKIAUuKxl1Qylwn5qKtIsaouG1bdD09utxRdd2aJvdAW2y2qFNzj1o26sjru6TiWv6dcUNA7JxaefbcM61rRGf6kOidXC55rKHvOmol56Ojz7+ALv37cauffvw+z7gs0Wr8NCT/7HzO/fuwc49u7Fr927s3LkL27ftwEv/fhkJ3kR4XF47hb/Je6jgIkHeONehSzgL5HX+WMWJxnrJi/OUVuqcx2n50DGIVn9I/9Oa41KcvBPyskxHOY8lbCTkJexlkujewiBvJPhZlUEw28tIXfn2LvuIoJf9VljErtQ7wa5ZVsh76LzhnEe0XL37RyFv2cwr0ZqvSnPe4sxxAnYjWZkLzfOY+dLckx5Tvjo0x495jrFC3vIdE/1NaP+rBlQDqgHVgGpANaAaUA2oBlQDqgHVgGqg8mggIuSVZYctG+5a9vLKXGLZb4Ud0jYAzoe0vkCyvRyyz4a6gXx4mx/Nay9NSkActJcoDYWsg7A3wGhfLp/MZZvDSzcT9hL8sj7R8iEx6IfLl2hH97oDKUhItZCYFkRCehCeND/c+cmTHijIu1J9cAVT7GOTLT98lh9+y4eygLzsF0bycrnmtFAqMtLTMWHCBLz//iR8OHkS3nnnHbz+9vt47a338dp//4fxb/wH418fj9fGv4ZXXhuPf7/0CsaNew6JCUlwu7zh5OZSy4dG9EaCvPFur/2d3jh3Apj43d7D/RCdjjWzfLhjdXt0fuTmGBSVF0d3UdZ0kMtSzlzCWSJVCX0JNQl6nQC3qkNetpltl8S+YL9IxDO/uyuwlloXoCtWtokVmFuYNZdp1kje6g02FWwfHH+FvNGZRyrL/Oyc42Q+M+euwvKyr1g5V2Vpu97nQe3L2InlmCrkPdg/qhXtC9WAakA1oBpQDagGVAOqAdWAakA1oBpQDagGitJAoZA3aEff5gNaK2gD3oOQlxG6AmSTwcjblEAAPr9A3oPfvvX5LTAFQwS9jN4Nf5Myhcs5E8DaUb38jm84uleWeub2FIsRwYS+PjsqmM5xK2jZifdiH2/xPEwpdgrY+TDc9QUtJKUkwUeIHPAXpACv5YhMPhplgbwEvYxaZmRgeKnkOLjj6sATHwuPNwHuhCS43F644l2Id8UhzhWPuvEuxDIa10XBeuDxJBjJm/89XS63nL/kssdrf4PXXKbZXqrZk4h4T2L4+7weL9yeQ4/1etxgcru5fHN4CeeiBKLbyucBIs7Owqw4tguz1J1sEye5LIHJMSXcZDSvgM1IkJd1Anud2ytLWSKVI1m2X5JEObO9fBYQ3hLY0hLsCsw1bWFAl/VOqOssH43njZ7jICzUvqicfaGQt3zml/Ke1zk/ydLNvBeZ55xzlsxdhVnZn1bOUd5t0+uXXNMydmI5ngp5S96Pqj3tM9WAakA1oBpQDagGVAOqAdWAakA1oBpQDVRPDRQJeYN2JG8Q/kA4ipdQlbCUQFa+b0vAymhZHyN9A0E7UpfbuV8Yph663LMdBewArOHI4DDw5RLPhLo2BA4GbMgbhrmEumGwy30YHWwvI21D3WT4rST4A0mw/MkI5cNhfzC8PwGAQJZowwACXjqugyELaRlpiI2PQ7wrHi63y07xdGi6vUiIT0RCfIINWuPdLsS5vQURuIzUlcQfppcOUbcLHnc83O7wufjdXUbvho9jFC/LUpeAWE84hSN83Yj3xMHtrosEVywSXXH551LQW1kffOIMLcyK87sw53idOnVseEn4SdDZoEEDO4pVIltZLyCX4FPylcUK1OX9Otsi7SHY5Td3Cbr5DxmhUMjuE6/XWwB1nYC3MLArz5fCbLSfO3r+ygk5q/u4KeStni+ehc27Mp+Z85bz27zmNsnLfMfjCzu31ldcrcm4i1XIW3HHSn9HOjaqAdWAakA1oBpQDagGVAOqAdWAakA1oBqoeBqICHnpeA5HvtKGIa0A1oOQN/yd3YMANhz1y/3DUcDh7eHv+QroNe2fnfIEJGHIywhewmPC3pR8iMxll8NLL9vWjhpm5HAy/IFEBKxkWFYyQgGfDaEFPgfyl5guK2e67bQOWgimhpCaD3njXC4Q7kpipG6CKwEJLq8NfuM8Ycgbby+znC+S/EgXAt4Egl5XvA1mw6CXwNhjw2JZpvkg5BXQGwbAdsSwfW1C3liFvO6K9yMszYNRnKGFWXF604oj3LR0nNeqVavge72EnfIdWkLPopZyrgygVyCv0xJiS9Qu28ztXJpZlmFm9JAkqTNBr0LePz+3y+rZqtepen2vkLdqzEelmcMiHSPzmcxf5px1uDyP4fGRzqt1FVtnMu5iOZYayVuxx0x/Uzo+qgHVgGpANaAaUA2oBlQDqgHVgGpANaAaqDga+BPkFZjr9yfDCqTYkNfiN3XtKFo6mfld3SCCVhoCgVD+93oDdhQvo2uDjOb1WbBsCGvB72fEbchI4QhcP7fbEb3hiF+JgGOd3AMjhMOwl5HCB5dk5r3x270EvAF/Iix/oh1ZbC/5HBAY7EfAis6yzEXBhkMhb7odyeuEvIzS5Y+A0b2MsI3zxNtRuS53Ajxutx216/V44XV7keh2I9HtCkNegl6XCx6XGx6XBx4X90mE24bD+dG8LgJgnp9Rv9yX+3EZ6HC9HRFsO0I1ircyP4jEGVqYFSe52KIc5Izq5XkYyVoU6DWBKUGvRMRWROhr3qvkBfAKxGb0LpdfTkhIAKN3aSOBXe7jhLvyvCquLeqZodtkLlBb3bRQUSAvn48KCcv/xZTzkP1uxPcVl6vgkwMyj4mNNJ/JNnNOrMxzfHW6d3PMZNwV8pb/77E6aVDbqnpTDagGVAOqAdWAakA1oBpQDagGVAOqgcqsgT9BXtvJbH8rNwWBAL9la0Tz5kf1EuaGgvx2ZRp8VqoNekOBZKQGkhCyl3I+HOTl93nzo3otHwIWIUoKCH4tK2h/czcQDCAQtMLf+rUC8Fn5SzLTclnmQDKCh6T8CF5/+Fu/VpDf7+X5wssnO220nOkHIW8qUjMiQ16J6LWXafbEw+VllC8jcwljuRyzG25PItyeJHg8iUhwe5EcH4ek+Hi4XYlwuZLhcSXayevm932TEOtORqwnCXGu8Lni3An4f/beA07Pqkz/f1ImmfLOvL3MzNumpCdAEBDZhaWsCEgHQQR13V13LQhiASwgKiqs6+7aXX+r7tpWURdMZhIMBBJIQtqUFJCWUAWkBQktyWSu//963rmTJw/vOy2TyZQrn8/53Ocp71PO+Z5zntzX3OcwMjgVjaM2UhCFY7FEYb1fE5l7HKl+Bxu3RzPU4+HZi9WZd585vM36neLe/d7pMClyNjU17RF7bc1aE0rNjnSRl8/HZ7W1hxm9S3GX78N9FGfpRDZh17vWrj/vF3i53Ze4e6D6F11XQvBYYsDGZUbT848u2P/wj05s/XCz/v5rKLfZF/J6tBr7RtYHvXdMY947bvkZsGPe34yHb4Gx8I7eOrN6lsg7striWOBM7yCmxIAYEANiQAyIATEgBsSAGBADYmCsMuCYk5WOYwoXWTcxzyhcCrEUS3Nw15p1o2wL0bGNeUbyNiFWyyjfHJrrqpCPTkRDfQyZNCNsucYur/PmlE5nka5vQH19BnV1caRqo6ivrwP3u9HADY3INTS46/zWpXNI1tYhWRdFsi6MVH0M9ZkUCpHGFKHTBTE6X79nuubmBq4NzP0HM5K3lMhbmE7ZplnmdMruVMucsjkeQTAeQ3UsgZp4GuXBWpQH6xCqSSAdqEKmugahcBaBaDOi0SzCQUYg1iMQTqEilkdFLIdANOGmydEcAokmxAIhZMNhJEIRJBj566Y4YpFCRPBYBXu8vZffSerfNge4Wb+D3L/Ndk+hlJG9FEa9AinFU0bxetNIi+Y1gdfEXU7NbOKuCbulonb7E7k7loQ2vYuE44PFgH1/DLfIa/2g17LP5LgRj8f1R049fwh2oMZR7/jkv0ex8vee760z/7jlPWa/8V9f2yPvP3RWV2ZZjxJ5R149qe2oTsSAGBADYkAMiAExIAbEgBgQA2JADIxMBoqKvOl0HrXpWUjVT0OmPo5cfQiZuqQbbcs1crkmblO+AQ0NM5BsmIsLL3kvnrl/GY5sLEM6UYFanptJF9bXpdjbM9UzbcGZnEd9XQNOOOHt2LbtGVxw4Zmoq0u5oi9F3lyuAdl8HulcA2rr8zju+JOw7eVn8e6Lz0YsGUKqPlFYqzfLNXyzbkpxPd9sPaZnk5ieSYCRxb2LvLY+sD3T0Ni+I3lN5E2C0zMXplqOI5KguBtFdTKNqcEkfvaL3+C8c9+FWCSG1Xcsw5HpPFJTwjjsbefi10s2IhhOIxFNIRmvRziewZmX/DMWrWxHRTiCskAQp170QXQ8+BSaMjnU1QQQrwkgFgwiUhNCLMzpnxndOzKhVGcx8Hox52gp63V+M+93jhfbZj1wCmcKpYcddpgr9FIopYBqoq5X6B0J0zfz2bwCL8Xd+fPnuxH9/CMWCrt0Hvcm8PpF3mJRuwdLFNN9h6afVjmOjHIcbpHX+sFi/aSNO8VERjsmO/CxqViZecvff7xY+XvPZ763MczqmJbn+q+v7aGpw6Esx2L1K5F35NXTUNa5rqX6FQNiQAyIATEgBsSAGBADYkAMiAExMHQM7BF56WylmMGpSJP10xBO/xXuWr0VbctvwbSEg0wqiFRdLWpzdUg3pNHIqZQzjajOzMG5l7wX27bcjkNrHcTCExBORFGfS4Nr6voTBeJMNo9UKo8TKfK++BQuvPB0pJJx1NVyGlROr9zgnlOfaUCqtgHH/s1JePEvz+DC95yBWLIGiboYkpl61GY5nXMedYwozsxAqj6L5ngZZqfK0JjtvfwKAAAgAElEQVSO9zKlKh3cJvIWopWHyunfl8jLKZkZvcvE6ZO5Bi+BjibiqIrWwqlpxLkXfQQb7r4L37vmMnzr6vfj4TtvxsdOfw/uvLkdx190Ld537Q8xNRBBuGIqQpVh1AST+OGvbsLvl92JV3e+ga7uLuwEsAtAd3dXIdf9Ch7bci+SiTgiYVvXd+hAUqM8uGXpd5L2te11hBdzmHOaVJs2lXVrwikje5ko/FLwHQkirwm7tBZ1zOejwMt97NO8oq7l/dMye8XdYsIu9w1VP6HrjAyRUfVwcOthOEVe6+esbyw1ZhUTGUudq/2DG/esDmj9ZdhX+dtvi/1hknefRN7B1Y2/PoZj2+rULOtOIu/oqb/hYET3EA9iQAyIATEgBsSAGBADYkAMiAExIAZKM+CKvJyKOZ/LI8uo2HQGifoZmHvc+9Dx6A48+9zjOHxOEvWJatSlEqjL1qMun0F9NoNktgnldTNw/nsvwbYHFuLwlINg9STUxGuR5vXc9XaZr0cq3+imTI5Cbj1StXkkk3VIJCrdxDVokylO4dyIbLYRuWweaU7VnGpENF6HWCKAaLIcsdowEvVJJDN1qM2m3YjeVLYBNZm5WHZPO778yUswN+GgOZ1AloJxph75TC3ymSTymRSymXRhf7bBvUdB7B06R7eJvA2NjWhq3ndNXq61S5G3sDZuz/q4bjRt1BV5KyIpVKbn44+Pb8e8hnp8+7MfxDevuggP3vFbfPiM9+LO1o341k3L8QSAVwA8+PDjqMvOx/wjTkRbxyok66owqWIynLLJqKiuwJTySZg8dRKqq6cgFHBQXekgGAogFOmZllKRvG9yMI/WzsKco/21dKJ6k9c5zjxFXh5nnmIvLac5pmjKqF4TerntFXotwne4ra0dzGmlKe7y/hTw6CimeGvCrlm/wOtfd1ci79D1iRJSVZalGBhukZd9GvvI3vr5vkTG3n6rY6U/Nr1l4x2nvPuZ76v87bc2PvnHLtvuT137763t/tXfUJeT1alZ1h2/N/jHWsP9LTGc9+P3E9+R3yX27kNdtrrewWFa5a5yFwNiQAyIATEgBsSAGBADYkAMiIHhZMDhlMa5bKYg8qZzyNTnEUo24MNf+g6u++li3HjTUvzT57+GmuoAMvGQK5gk0jlEMnnUpBtQnsjh3PPOwCsPLcT0KgdTJpYjGJ2JVDyHdDyGTDLgrrkbqJ+JYGaOu5ZupjaCSDyFcDyGUMhBZaWDqmA9aiIzkUhMR20ih3QyhXSyFol4A0LhFCoDExAITURVJIhwKuVG8yaSAdTWVaIiXIXJ9bOxeFUHrr/yYjTXOEhWB1CfzCKXjCKfqMS0ugrkExXI19cil86jIdOIfKbBjegtTCPNKL2hidSj45oib3NzM8KRMCLR6J4UjcYQjcSwx0Yo+sYRTURQFYvjw9d+HX9z3nsxYYqD675wOYCXAcbl7gTa123A1qc2I9IYwvduWoAPfOa7cCLH4vbVj+OW//oK0lMd3LX+HrzQE8UL7AbASN7XsOPVx3DI7BRqQlUIRqKg4DycoOleB7e8zYFYytKp6k3mKC9mKZDSMclk4iqdlZaKOUntmNli5wxkn13HIncpOpu4S4GW4q4lE3ZpTdz1i7rclrArMbKUGKn9B4aN4RB5rV/z9n0ajw7ueLS/5e+ty2JjFPex3nne/t5Lvz9wrHjr0dqp1ZuJvBzrB/JtMJrO5bt5RV6xduBYU9mqbMWAGBADYkAMiAExIAbEgBgQA2JgLDPgZHMFYbMhl0cmk0eqvhHVsRSWrlmJt555Lg6/6EqsemwXGlNRNEemIp7MI9V4CJ545pke+RCukPjq/TdjbtBBTSCPR54Arr/q8+je9mcexJWf+wIueO8H8VoXsKsb+O+f/A9ioShO+Ouj8MKzGzBtRhLh2kPw2J+An/7gp8Cu3UA38POf3oRoIIbjjjoSzz69GTPm1GFKpB7Xfu3bAHYAu57Hzh1PY/4xR+DebQU5FLsexMv3LcSshulYv3oz/uO6T+C1J9biT3+8C/Oa4sjVpZCtzyFPkTfLqGGbrtlE3v0Xeum4bjSRt8fRuNeZ1SPwRqOFv9yP9DSwRARlwRCccA5Nx5yAF/7yCM45861wHKeQJkzGOeedgzWbliMxPYHv//a3OOLsf8R7v/g7bOsGbvvhZ5HluZMdOFNDcMqmYtLkCSgrm4DyKQ6qpjqoqXQQqJkqkVcC956oEePS62BlvpTj3LufzlQ6KE1gpfWv2WsOVxNlzdr+gVj7rVneyyJ3eW+2OQq7Jur6RV4TeGkl8h4Y0U5iqMp1IAwMt8g7lj/mxuO7cfzyjknevImF47FcRss72/cHrfcbhNsSefWf79HCsZ5TrIoBMSAGxIAYEANiQAyIATEgBsTAwWbAyeQocubdaN5UfRqBuga86+J3Y9tDtyEfcuDUNOGPT+zER854G2ZWOghn34L7ngau/9RH0VDtoDyYxM9++UvseGAh5gQcVAQOwVPPAy8/sBaH1k7BWe+9Ci8B6Fz2e+RrHMz/q9PxxAvAW5tm4eyjZmLXS+1onh7FlMh8PPkksOWOFsyqcnDkMe/E09uAvzvzDJx2WBqvP3cPZs5JYOZfXYBHngeOmNaIfJWDeHgqykJxOJH5uOOe+/Dvl70d0xwHwYparFpxP/DKffjbaQ6yYQd1yQgydbXIpLkucCMy2Sbks3nks1n3/bPZdE807/4Jvb2LvD3ibjSCaDSMGFMsgmgsgsmhBJzQDPzHL2/GdZefho+e1Qh0s/S63Wje7//ov3HE2R/CCe//OO57cgMSzWFc95MF+KdPfQm3/eBTmDXZwar2tXixIIGjEMnLaN7X8NrL9+OQORFUB8sl8krkfZPI63W2+h2uxURfW7OX55qwS8GVYiuja028pSDLvAmzZu14b7bYudzH6zNql4l53j+RSLwpctdE3r7E3WJRvAMRqnSuhE0xMDgGDoTI6xWLTOiz/u1gf3Dp/kP70c969Qq73rzVvcp8aMt8KMvT2iWtt91ym2M6x3eO+b19J4zmY3w3/qEcv1X4zkNZtrrWyOVedaO6EQNiQAyIATEgBsSAGBADYkAMiIGhZqBH5M25a9Um0nlMSs3Ej//3Jiz+z6uRdhxMnBzDz365GK0/uBZ1Ex0cf8Gn0P4EcGh8KponO5gaSOKcCy52Rd65FH0DR2DLY8BHTzsc2QkOnPDR2PQ4cNmZR6LBcVAVPxT3PQ588NTTcf6hKbzx7HI0NNfAqZ6Pxx4FPnHqka5IWxGchttXPY4PvP14XHh4HF3P3YHG5io44UPwIAOEX+/G3535dkz9/6c1dqpjcKoOwZ0r78N3PnY8ZjgOKqbUY+2aR/Htj5+CQ8sdpKodxBOM8ku607LW5qajPjcdjZksmjJ1yGdrkc3VuWJvLjs4h7U5+vsn8lLsjSAWCSEWDRVE3nAtjr7kSvD1vvrRv3HLITbRQcVkBxVljNKdjNQRF+OnS+7FHbf9AJMYuVtWhZPPuRBLf3AF8tyeMhVORS2csgpMmjwJkyaVoazn9zVVDqqqJ0vklci7XyIvBV5LXK+XiU5Krs07f/78PdMm0/lKAZaWzszeUl+OWl6HzlBv5C6vR4GWzmBG/Zio67X+KZpLTcnM/dZ+Zfev/1P5qfz6y8BQirwmEnmFI8sP9YeTrjcyPsZZv15h15uXyDsy6qi3tmLtk9bar9XbeBJ5+f3CMuitrHRs5POsOlIdiQExIAbEgBgQA2JADIgBMSAGxMDBYsBJZ7kWZRrpdAbh2mmYmj8e9z7FUNDtwI4X3SVdGUeKHY+huSmGt57/aazZCswKT0JugoOJ5Smccd4leP3BFsypdlBZVRBrP3byoe70wWWBw/Don4DL3n4Imh0HlYE52Pok8MF3nIBz5lVh97ZlyDVWwak+3BV5P/6O+WiiWDkhiTvvegQfeceJuHBuCHhuGRryk+BMicJxcigrz2Lt2k3Yvms7TjzvPDgVs3HX2ofxnctPwHTeZ2oWK+96EN+77G8xb5KDZE0ZgrE0EskI4qkEqmtnIFw7A5lEDPlYJZKxciSSNUjX1yGbySG3ZxrngTvs+xR5OUVzNOWmeDSGeCyCSDSEyZEEvvjL2/C1H/8CN378FJw/1wFevh/Y9Sxef2ULsg0pOFPyWLVyI/7jipNQ74q8U3HWee/G0u9f5oq8P/hNCx4B8Ko7UXZPEDB2YfeOhzBnZjmqg2USeSXyvsmZ6HW2+h2uXuer5elMp9BrTvXKykrXSdvQ0OCKuRRkLdKWYiwFYCbmLfKXeb+4a+f5hWFG9DBK+LDDDnPFXoq7jNClc9Qv8Np0zWb7OzVzf4UpnTfwPlFlpjIrxsBgRV77IxP2P9YnmfX2ZQfrw0r3HZ6Peta1jUF+Sx54XHUxPHWxP+VsbdbaMC3bOP+oy/u9wDy/EfzfDaN1m99A/FaioL0/5affjnzGVUeqIzEgBsSAGBADYkAMiAExIAbEgBg4kAw42RynKKbQm3NFz5Mu/jz+tANozjYhWTEF5WWViMQSeOrPD+MjV34CTnQ+7vszcN3lH0RqkoOKmjrcdc96/OXBxZhe7aAqMBePPwJcdtpRqKPYWjUbT/0J+NjJb0Gj4yBcPQePPQ584O3H4oy5Vdi1bSUy+QAm1hyKJx4DLj35SPe86soMVq7Ygo+c+rc4d24EXc+uRHPjVMw+8m14z4c+D2dCAlOrU1izfjku/dTH4FQ04s5V9+EbV5zh3rdiShrrVz6E715+GmZPclAbrsZfnXAqtv3lWZz37vNwyN+cjSdfAt53/jk47Zi52L7tUVx00ZmoTSaQrssMg8hbi1iUKY5YLIpoLIyySBxOqBFXfOXr+Ponz8a5sxx0LPwOaisd3H33/+GDH/0Arr76enRvfxX/+vF3Is3o3knlOOec83HH9y91I6///X9bcMgFn4AzNYipU8tRWRlFTXUlnvnTCsyYNgEVgQkIhMKISuiUU60XBszpatbrfGWeDnUTWsxaVC9tc3Oz65ylMMtER6bXWUvnpjf5nbQ8l78xYdeuwevSIUqBlyKuN2rX8ibumpXIK4GxmMCofQefi8GKvF5Bz983WZ9FeyA/nnTtg/9xzjr2suDNkwsxcPDrqD/txNqstWWrV/bR/Bawbwd+J4x2kde+e/hO/K7h+8Tj/H/A6KgrPafqSQyIATEgBsSAGBADYkAMiAExIAbEwMhjwMll0z3r0eYRrW/Cd/53CW5d9zAmllciEChHdU0NplTV4Ce/uQULV3TAmVKLk8/7QM+qr6/htZ078f3vfxPPPXQnMozkrZ6Gxx7diX8+4wTkyhxEwtOxZcvL+PBZJyE9wUE40IQnHtmJvz/1FJx6aD1e/nMbMvkwyqqb8NjW13DpmSejYaKDUFUKK+/agPefehJOOyyDV59pR1NjDZyKcvzo1zdztmZ0d+1Ex/KbkaxyMGlqBNd86evAjmfw1APrUJeYifYVm/AfV1yE2QEHdbEwjjvxZGx76SmcdcHZmHv82Xj8JeD955+D04+Zh788vxUXXng6EvEw6mtrsT9TNvcZyes6n+nUibtia9QVeSOooMgbzOLT19+AL3/sbPzsM2dj+Xc+hRkVDp5+/knctuYerFu3Ep+/+uO46+47cNrZ58Epi+Pd55+Ppd/7kCtu/+uvWjH3gk/1iLwVqKyIo6Y6gD89uRxNzQ7KOWVzkNNDjzwY1UGMnDoxp6tZc76aNWe6Cby0XpGXedZnU1OTG43DiBwTes1ha85b2zbnJ60JvIwG5m/pCKVoS4GXYi6jd03E9VvvGrzM90fk9Qt+Jj55rf8cbR98kVB1MLrrwNpXY2Oj+4chbMvsO7z9CvPW31j/47XWRxWzGlNGzphyIOqCdW5s+C0Z4fEDcV9dc2i5KtZ2WZ+sQ47fnMmDid8KY0Hk5XvwG4ffJ4riHVqW1DZVnmJADIgBMSAGxIAYEANiQAyIATEwHhlwcllGrWaQy+cRr8uhIpHDpFAKU0MhVIVrEIqGEU6kUBZOw6mpx4RAAmXVEVRUVyJQU44qCsFVExEtd1AzhWv4RhGoSqOucjJqKyaiOpBCdXUtUpWTkKqYiGBVLSLVWcQmlSE2yUGwwkF5xQSUVSRQXVWLXFUFMhWTEa6KIRJMomaCg/hUB7GAg+rABFSEAqiKRlEdDiEcmILEZAfxyZyeuQpTymtQHZiCmqpyVE6NIFIRQUPAQWONg9p4DNF4ErF4AFXhACZEsigLZxGrqkBt5QREg2WIRquQTETdKZsPtMhLkZUp4qYo4vEoqiMxTIpm8Lnrv4ZvXPNh7HxwKU6qn4jMBAeTystx+nsuxo9//G04joOpsXosuud+TIlOw/lnn4k//OBypBwH3/ntYmx503TNwOuvP4Bp08pQEZiEykANojFFDozHBt/fd/Y7Xb2iCvPmUPeLMV6ht6KiwhVr6MSkU5NOWgq2TOa09Vo6PS3xHAq8FHxNtC02LbMd81q/qFtsHd6+xEETn7y2r9/o+OgWHFV/w19/1r76I/J6+yB//9Tffk3nja0PfXJgY5HfkhceV52P/Dr3t2duW/2xXvmdwaUg+F3AbwlG9PLbwD8DyEjY7s9zcazhd5G9txgd+YyqjlRHYkAMiAExIAbEgBgQA2JADIgBMTCSGdgj8mayOaTqs4im6hFJ1iGeSiGRSiKZSiKeSCKcqEUoVotgNIFwNI5wJIwIhdZQEJFQDeKhSkRrqhAOxd2UCAWRCNUgHI4jEkkgEQkiGQkiGkkiEk4gHgwhVlOFSLAS4VANgqGY+7t4sAbJUBDRcAyRcAzxcBDxcDWioSqEw9UIRcIIRiKujUVCSEWqkYzUIBqJIhKNIRqlY4/PFkcsHEMyFEAyXIVUMolEKuWufRuKhBAIx1EdjiPKe/E5QtWIRIJIJOKo57q82cE7vOm4Nqe1OarMmUMbiXJ6ZhN4Y4hRgI4V3qkyGEF5VQA1FQXhPDbFQXjKRJSXl2NKRQUqy8tQPnUyJpdXwJkaQHmoFhecdx5u+f4XkC538P2f34Rjz/sAJgWqURmoQnVNAsFgFI9s7cT0aXEEApWoqgq5UcQjGUw928HtOL28Fsub4GKOdRN7TeStrq6GN/E8Omkp6nKKQjprTdCltW1aS4wCNvGWEX42HTOtRe96BV0717uP+cGIvPvT/vXbwfedKrvxVXalRF7rV8yyf/GOpRofDu74MFLKn2OTMeK3xstIeVY9R/+Zte8L+/bgdMY2Owi/rfnNQDGVUb3+NBxC70DuaZHH/K7hchP8YzX/+/E9xUf/+VBZqazEgBgQA2JADIgBMSAGxIAYEANiQAzsy8AekTebzaE+nUGqttYVUCiYeMUSE1UosNQyJZP7pBSnUU0k9u5LpfaIMvZbszbdKv+SPdmTKMLS+dHf5BV8esu796yvR3067aZUbeG5/PdxnyWZdEUlikL7Izb0R+QtRPCa0EvRN4pwpBCxYOJYIBBAdVWxVIWK8qnuVNoTp3JK5qmoq3IQKXPcabYnBeMoq6pARVUFKgNhVAWCqKoqQ1mZg8rKAGpqIhJ5NV11r05Fc66WsuakNMe6X+SlQ9Y4puX5bFMUepnooDXBlxG7TF7HLfsftklr29Z3mC0m6BbbJ5F3fImG+9Nv67fDz4pE3n0/yPSBOrDy4PhkY5DfcsyReDaw8hwp/LHe7BvDm+c+PiO/AyjmUjg1EXU4xF27R18iL79vLNkU0/w+sXcyy3cTo6OT0ZHSVvQc4kcMiAExIAbEgBgQA2JADIgBMSAGyICz17GdQyaT7VfUmzuVcSaDnCfls1nsk3I5mAO3mLX78lr9mRrZovHsd7TFrmv7vOcVy/vPs+ubKFTsN/3dx2v3Fcm7r8hLsZcRvhE3mVMrQidlkRQJhRBhBHU4hOrqKlQHyhGumuROX11VE0BFMISqYDWqqhnNW+OmqkAFApxiu5rR0IVIYnUC6gRKMWDOx1LWnJTmWC8m8lpULy3PZ/uho5N/YME8xV5GtpjDlG2G+9kGTdw1awKuWe8foBTLW3suZfvblnXe8At/KvPxU+Y2Dtt4SfGG/YX1K17LPsT6o1L9lvaPrzGNPHgZ8eaNFzEx+piwdm7Wvjdo2T/we4N/BMnvAf5xmImvw2Xtm8Ws/74UdjljCS37OHLpn43A3o1WjI4+RlVnqjMxIAbEgBgQA2JADIgBMSAGxIAYGEkM7BF5KYb017nuF3n3EXcp3uRyyPch8ppz12x/772/59n9/JbXNUFoKO5hTmtzNHodOpyu+c0ibyGql9M4ewGJR2NIeFIyFgdTPBpFIh5FJBxEIh5BJFKDWCyMULgGkVjEFY3D0QiqQ6GeFEQwHHKnuY4nE+500d77KL9vuY/38vDyWixvTlevU92EXrNekZfXsDZGUZbOWYvKLWVN0OVx5v1irrVXWu8x737m97c96/fjR3RUXQ9vXXMc5h972HjJts7+w9uvWN7G0vHeN+v9947VHFeMD78VL3vLabQxU+ybw7uPdev9zvCLrN5ti6il9e7fn7yJu2b91+IsJRxLWO58bk437X1+f3601Y+ed/S2LdWd6k4MiAExIAbEgBgQA2JADIgBMTA2Gdgj8vqd270JJRR5/cKuf7uv6NxiIqv/GfZn265v1yj2PjzHjvvt/ohDvK45rc3RaE4dNiRbjzcaj+8j9oZ71uv1Nja/yEvB190XjyMWK0zzzKmeCyniTvnM9X0tuRHCjBJ21wDeez+/mOy9p/Jjs7HvT70av2bJtTeZg90cr37L37FdsF0xOtc/XbpF7PoFXxN6/SKvvz37t/3tWdvDK96pvFXe/WGAfUIxkdfbt1je+h7a/enL9NuxM76RBRt7/JbciJWxUdfets+81a31DVwSgvsp5DKC1i++eoXeAyH2ckYSCr2cPpoCrz2XPac9f6m+x46bLXWe9o8NnlWPqkcxIAbEgBgQA2JADIgBMSAGxIAYGGoGSoq8vTloR6PIy/fxCkG9vd/+HttfkZeOHqvoUiJv4TjPKwi6e8TcKNcs45q7tr8Q1euPHJbIq87EGOuPNeejWa8Tk3m/g72YyEsxx0Te3sRcr7DrF3ctYtfblovl97cN6/cSKcXAgWegvyKv9Ttm+9Nn6ZyxP8aRB//YY9smsImD0c+BtXuzVrf2HcLvDWOB3xYUeim2Unj1C7xDIfLaNXl9Crzc5rTRvLc9k1l7ZtpSLHrP6e28Ur/X/tHPuOpQdSgGxIAYEANiQAyIATEgBsSAGBAD+8PAqBF56Qz2pr4c8Hau9zyvGOTdP9R53nt/Inm9Tp7eRN54LIJENIhELOhG7lLoZQTvviIvo3ijiHBKZ6aeqF6JvOo4BtJx+J2Q5sA0a471Upa/p8jLtsao3f4IuaUEXe5nW/a2W2/b9h/znqf8gRfuVMYq4/4ywLGS/QKFEiaKJOxDrF8x6+9/BtJ36dyxO9aRi1JjDtnhcdX/2Kp/b19g/YPVtYm93GYfRKGX6+KaKGvWP73yQLZ5DV6Tiddn9C6/98kZ7+vtv7zP2huL/T1PLI8tllWfqk8xIAbEgBgQA2JADIgBMSAGxIAYGCoGBi3y9hbNy2NDPV2zibZm+3IiFzvPKwT19fvBHjendV8iryuy+qZrdtfqjUb3cUxS5C2WCABF3iRF3miwJ3K3MG3zXpG3sF0QdsOIxJi4rzBl9FBBpOuM/Q7J74T0OlfNsVnK2c79/D3bBNsHhRwTcHuz3vZaLO9to/7j3mPKS3QUAyOTARsvm5qaJPLGxv44MtTfChxXSo07HJd4fKjvqesdXE693yL2HWJr3pq1bxIuC8E+xsRdswMRde1c/tbynA760EMPdbcTicQezvhstu19TsuXYseOmy11nvYfXPZU/ip/MSAGxIAYEANiQAyIATEgBsSAGBipDAxK5KXD3ITcUnasO9VLiUrmtKagRce1/VW/OW/22B6h1QRXswMDJeoKvRR7C+vzsqHRqbk32XX3rtsrgXdgZazOq1h57eG4548SzNlq1u945zXYJpjYdvzirr899bU91vsXvd/IFCVVL0NfLxwz/ZG8/v6lWB+kfRqbyIl/rLFtjkU8Lk7GHif+/sG/bd8hZjl7CL89LLKX3+Ym2PZlTRg2kZfTMlPktVkHvIxZ3vs84m/s8ac6VZ2KATEgBsSAGBADYkAMiAExIAbEwEhjYNAi73h3dvtFKCsPTj1pYlZvIu9IA0HPo85pIAx4nZjMmzPVrDnazfLabA9MbCv+9jPQbWtvskMvuqlMVabDxQAFXt6Lool3umZ//zKQvknnjp+xjJzYGOO3HIt4XDyMPR78/YN/275DjAFa8kFhln0Np1juS9zlca/Ay+mZuY99FqN1eb3q6mr320eMjT3GVKeqUzEgBsSAGBADYkAMiAExIAbEgBgYTQxI5M0OzqHvF6XMKW4iL8Usir10BJmjyeuIGk2Q6FnVqfkZ8LLMvNepag5Vr9Odv5fIO7i+xvoWWZXfWGVAIq/GGP8Y059tjj3eccabt++u/lxH54wu/vzfH/5t7/eI9/uEfHDdXvtOZ79jEbpe0dcr7jJvf5zmvRbvIW5GFzeqL9WXGBADYkAMiAExIAbEgBgQA2JADIxVBiTyDpHIS9GXDnhzHjEqiXlzNvmdUGMVKL3X+Ogs/Twb52a9znbmyYVEXomUY1Wk1HvtH9ujXeT194eltjU+Du34yHL2jzW2zbGIx1XmQ1vmI7k8ve3OvkWMA2OBtqamxmWD3+iM0PWLutznTf7r2vZILgs92/jhXnWtuhYDYkAMiAExIAbEgBgQA2JADIgBibyDFHmLOfU5jZtN1UyRl9vmaJJTSI1tLHW4xrNZ49ysOdrN8t29Im+x9qN9+yeUqfxUfqOVgbEo8nrFJesnx9IYMBLeheVqY4zfWvmPhOfUMwzv95+1t1LWvlPMmqDLNXu55kypP4AAACAASURBVK533d14PO4Kwv5rsU65z2tVz8NbzypvlbcYEANiQAyIATEgBsSAGBADYkAMiIECAxJ5D6DIm06nJfLG1NmMxc7G7/A0Z6lZv8OdZSCRVyLkaBUh9dwHlt3RKvL21Q9af2jnjcWx4GC+E8vVP9bYNsuexw/m8+neB+f7z9pbKWvt0iyFXK7Xy8he9kWpVMpdd5fHyZOd572e6vbg1K3KXeUuBsSAGBADYkAMiAExIAbEgBgQA2LgzQxI5D1AIi+jeOko8juHBOGbIVSZjL4y8To7mTfOzZqj3SzrWCLvgRXKJESqfEcrA6Nd5LV+j9ZEIbPcZ/2lxrqhHetYrjbG+K2Vu8p8aMt8NJSntbdS1ttevW3W9nvbru3zX2s0lIOecfyxrzpXnYsBMSAGxIAYEANiQAyIATEgBsYnAxJ5BynyUsRl8jrVuW3TNXON3kQi4YpfXueQGtr4bGhjrd69TDNvjlCzfoc7318ir0RIb3+pvHgwBkayyMsoP+u/mbfpW62vo/X3d7btPceb5/W817Xryw7s+4Bjj5W137K8eVxlOrAyHQ3lZe3Qb73P7v9GKbZtjHjbZrG8/7fe+yg/9vhSnapOxYAYEANiQAyIATEgBsSAGBADYmC0MSCRd4AibzFxl45qTvNGEYtr8VLopaOIMNA5ZI4kr6NotIGi51Xn5mXAy7Ix7nWO+h3u/K1EXol6JurJigUvAyNZ5GXf5RWTvP2dv5/rbdv6R+s7vf0p87af1n9M28XHX5ZVqTK37y6VXfGyG8/l4m1rzFvb9Fv/eeO5zPTuakdiQAyIATEgBsSAGBADYkAMiAExIAZGLgMSeQco8tIxbUIvLcVdiroUd6dPn+5G9hJ4czCa00jOopHbCNRBDbxu/Dwb52b9jneWsUReCXteYU958WAMjHSR18YIir0mCvn7uP5uWx/Ja/r7Udu2+8n2PjaxvEqVO8uZx1WGvZfheCwfa2elrLVR//HxWFZ6Z7UfMSAGxIAYEANiQAyIATEgBsSAGBADI58BibwlRF5Ot2wOaLMm7lLYteSN3k0mkwgGg3ucwHQQyVk08huBOqqB15Hf+Wmcm/U73lnGEnkl6llfKisWvAyMNJHX3795t9nH+fu3gW5bP1nK2v00NvU+NrGcSpU9y5bHVYa9l+F4LB9rX2atDGy7lLXzZMWUGBADYkAMiAExIAbEgBgQA2JADIgBMTCSGJDIO0iR15zSjOKl4MtKNYetOYhs25yNtp92JEGgZ1GnNFAGvCwz72Wdeb/jndeXyCthzyvsKS8ejAEbT+vq6ty+w9+/DLR/2t/z7f7+fs22/f3b/mzbNb3W7r+/7zHWf89yKlX2LE8eH+tloPfb/+83m47dW5bWBsXQ/pevt1yVV3mKATEgBsSAGBADYkAMiAExIAbEgBgYegYk8vpEXkbwepM5oWkZyUtR1xzS3E4kEm8SuMy5KCfR0AOrTmBklKmXbea9AgXzfsc7600ir0Q9b3+qvHgwBmxMPdgib2/9mr9POxDb3n6Uz+Id77zP5t0/nvMsk1L1YN9h47l89O4j43tJ9aB6EANiQAyIATEgBsSAGBADYkAMiAExIAYOJAMSeX0irzmdvdM1U9idNWuWK+5SqKK4y6mZKfCycuho9Dpnzbkop6wa74FsvAfz2l62i/Hvd7zzWSXyStSz/lVWLHgZGGkir43n/n5suLbt/t4+3tvneveP5zzLpFSd2HfYeC4fvbu+QcWAGBADYkAMiAExIAbEgBgQA2JADIgBMTD2GZDI24vIa5G7FKfohGZKp9OuoFtTU+M6F72OV3PMmnPRe0yNaew3pvFUx162mfeyz7zf8c6ykcgrYc8r7CkvHowBibyhN/WZ7Ee9Y4q3z/XuH895lol/rLFt+w4bz+Wjd9d3pxgQA2JADIgBMSAGxIAYEANiQAyIATEgBsY+AxJ5S4i8dD5zrV0TphjZywZBB6JX0PI6Xkvt5zlqTGO/MY2nOvZyz7yXfebN0W6WZWNtyYQdWYl8YkAMkIGRJPJ6+zLrvw6G5XN4xxRvn+vdP57zLJNSdcPy4/HxXD56d313igExIAbEgBgQA2JADIgBMSAGxIAYEANiYOwzMO5FXkbrMvnFhunTp7uOZ4q78Xj8TSKWOYLNieh1wNo+NaCx34DGax37ebf2YNbveGc5SeSVoOfvZ7UtJkaKyMs+rVT/5e/PDvR2MBh0xUt9S/T+DcHyKVUXrEuVX+/lN16/X/Te4kIMiAExIAbEgBgQA2JADIgBMSAGxIAYGEsMSOTN5dyIXa67SxGqubl5T1SRTc1MZ6HfkWjOYHMi0nrTyIOEES2Kahl59TI6O1Qv68xbezDrby8sd4m8EvQk6oqBYgyMhEhebz/m77+Ge1sib//GRdZZqbrhWMTjGvP7V5YqJ5WTGBADYkAMiAExIAbEgBgQA2JADIgBMSAGRicD41bktQher7hLgZdTNPMYHYTmaDXhqpg1JyKtN42sBhFFPNaTolHEo6MT1pFVpuO7DL2sM+9vG37HO+tOIq8EvmICn/aJi5Ek8vr7roOxbd8e7Fs17pUea1k+peqHY5LKr3TZiSuVjRgQA2JADIgBMSAGxIAYEANiQAyIATEgBsYGA+NG5PVPycxtCrwUdWkp8HIfp2Y2p6HXgegXsWzbnIi03nSgG0g0FkWxVOy+8VgM8WgUiZ4kkXdsNN5idT1c+7ysM2/tway1IbN8Lom8EvMk6IqBYgxI5A3t+e5gnymRt39jNMceG2P8lmMRjw/XmKj79K/OVE4qJzEgBsSAGBADYkAMiAExIAbEgBgQA2JADAwtA6NW5KUg6xduuX4uk9+JbOfZbyjsesVdCrwmTtH6nYW27T3H8uZEpPWmAwmqibuRWASRWLgnRfaIvrx3PBr3pViPyMtjb4aI+4rtP5DvoWu/uR5GS5l4WWfe2oNZazNm+V4SeSXw+ftmbYsJMiCRVyLvYMY+jj02xvgtxyIeH8x19ZvR+22iulPdiQExIAbEgBgQA2JADIgBMSAGxIAYEAPjjYFRK/Lmczkw5bLZPSlLgbeEyEuB1yJ2KepaoijMSjdxipbOQq/1HvPnzYlI6037C1I0FgOTXce7zXwkFoUr8sYjiMTDiNDGCkJv4TdxxKIJxKMJJKJxJKIUeQvJL+YWIn0LIi/zdk9ZlUUpBrysM+9vF36HO68jkVeCnkRdMVCMAYm8EnlLjTW97efY4x9rbJtjEo/39nsd0zeOGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxMBoZ+AAiLyMpN0bTZvJZVEsFXP09nefCbv5bBbeZCIvj/NavG8u35NyOVfYpTOZUbw8zqmZa2pqXEegX6Tybpug5d1neXMi2jlmBw9GHNEYU0HkfbMtHI/E4igkCr5Me0Ve/ibsHk+4Qu++Im8hwteezyJ4/daOy6qTK8aAcW7W2oNZc7Sb5TUk8krg628fr/PGFysSeSXyFhtn+trH8cfGGL/lWMTjfV1Dx/WNIwbEgBgQA2JADIgBMSAGxIAYEANiQAyIATEwmhkYgMibQzbrTV4ntHf/XpHXxN10Lgsm26bdXyc+hVyvwNvAyF6Ku5mMG9lbuFfGFXnzuSwaGnKYPq0ZDQ15JJNJd807Crx0DJoz0AQqE65KWTvfjhMAy5sdKBQ2vXIslkDUTcWEXhOAvUKvibyM7OU6vRSH4wjHEojELJLXonkp8Bb2xWJx1/lp9/VaO8ZrDfQ9dP74KDPj3Ky1HbN+hzu5kMi7//3e/vab+r3qYCQyIJFXIu9gvh04/vjHGtu277TBXFe/GR/fMapn1bMYEANiQAyIATEgBsSAGBADYkAMiAExMBYYKCLymkjrtxRy8z0ph0yOqUe4dcVfRscy8bx9BV2/yOs/vuc6dr1+WF7DInq9liKvuzZvLoPGpgZMn9aE5qYGZDN1qK9LIhoNIxisQTgS7nNKZhOwrKJt22vt2P5YCqxJd1rlJPaKvBR79xV1ub1XgKWgW4jeLUzVTJGXgi9/UxCKC1M1J5GMMlHo7RF4own3PrxXLJp0UzSWxL7J7q+Gvj91O1Z/620DzJu4a9Yc7WZZDhJ5JTCORIFRz3TwuZTIK5F3MGMlxx4bY/xWIq++3QbDlH4jbsSAGBADYkAMiAExIAbEgBgQA2JADIiB0cZALyJvGtmsJQq+FG9NyG1AJpvvEXrzhTy33VQQgP3Crgm55lC37UFbE3M9a/By3V1OxUwxadqM6Zg2Y5obyVvnirshhCNBhCO0hXV3zSlozkATqPwCllWqfz+37dhgbTwWBadKNhHWRF5XgN0T1VsQYguCLAXaQhRu1Lsur5sviLyM4KXQu0fkjSSRjBREXq7TayLwXpE3hWjMmyj4SuQdbJ2Oh9/524K1HbPWtsyyTCTyHnwxzfpfWdXFSGJAIq9E3sGMmxyHbIzxW/uuG8x19Rv9Z04MiAExIAbEgBgQA2JADIgBMSAGxIAYEANiYLQwUETkpfPbonj3FXkzmTwKiWJvY09qQibbgPpcFvW5DOpzuT3Jpmg+EM5kN1q3R+i165vA29w8Dc3N05HO5BCOR1EdCSIQCqImHEY4EkE4HEEoVIjkNVGKzkJv3itisTK92978QCt637Vvo0hEmSKIxQqCcSFalwJt0k0FYTeFeLTWk1I90beckplr89qUzXtF3nC8MF1zglG8XpG3ZxrnQsRv3F2zt3Avuz4F5UKkb+FZ1JgHWsfj4XxvG2De2o5Zv8Od50jklbBofbVscRaKjWvjoawk8krkHcy4yXHFP9bYNsciHh/MdfUbffeJATEgBsSAGBADYkAMiAExIAbEgBgQA2JADIwWBkqIvF6hl4Ivt3PIZAopm8miMVuPpmwCTdkwmnIBNOSnoCE/GY35qWjMlbu2KTcFzbkpmHYAUlO2DN40d3o1Zk8LYGZjBWY0VCCbnIRkxEEk7CASm4pQLIxgJIZQKIpwKIJIeG+iI7BUsoq047Y9WOsVeRNuBG9B6GVErwm9kVgS1fE0KhJ5TEk2YGKyCU5qBpzaWXDqZsOpm1Ow9bPg1M+EUz8DTv00OPXNPakJTn0DnNocpiRzCMQzCMVqwesyyteEYXfN3Whhnd5YlMJxQTzeG0VciBge7Lvqd2O3I7T2YNbEXbPmaDfL80zkZcT9eBCu9I7FhUyVS+ly8Yu83B4P5SWRVyLvYL4XOK7YGOO3EnnH7vfHYFjRb8SDGBADYkAMiAExIAbEgBgQA2JADIgBMTBWGSgh8lKE2TfV19e5Eb6ZTBq5dBzT68sxu97BrLSDWfUO5mYcHJJ1cGhPYt67bfvNHsLzB5Hs97SH5Qppft7B4Q2Fe89MOpgWddAUdNAQdJCPOUiFHMRC5YiG44gGo4gGI4iEIohFYohGCgIvK9gEK1pzEDLvPTYUIMRjMXeKZoq88UgU8UgMCTdFkYhEEEzUFcTb3OFwckciceHlOPrrv8Lf/GQZ3v67DTj2pnb8tZva8Nc3rcdxv1uPE29pw3G/XYVj/vdOHP2TFsy4/ttwTjobTmYunNppcJJZVMRTiCSTiMVjcAXemDVsRgNT/DURuBAFXFgT2M6RHYq6HyvX8LYVay8m8NL6He48p7GxEc3NzZDIW1rkGw+Cnt4xW1g33rPkgFfctXw6zZk0CqyM9TYjkVci72DGRo4r/rHGtu0bbjDX1W/0vScGxIAYEANiQAyIATEgBsSAGBADYkAMiAExMFoY6EXkzSObtUTBlxFFaWTStWisn4JLTgniV984Bptvexe2rjgXT607F8+sOwvPrDvHTU+vOxtPrzurZHpm/TkYTPrz+nPgTc+2nYvnO84DLdMz687GM2vOxpMrzsT9S96JX/3HIXjPKQ7SIQe1kalIhGoQp8Abju4Rea2y/MIVt0sds/2DsQWRN45EtJC4dm4sWouaaD0mRtOuMJu/5Cqc9oM/4JSf3IXTbt6Mo2++H7NvfhDTFz6K/AJLjyC/YCsaW5keQkPLH9GwcBNmtXTiqMVteNtv7sAZv1mKU77zU0w+4R1wMjk4ySSm1NehKpFEKG6ibhzhWByc4tlN+0zprMY8mDoe67/xtxWvwFtM5OU+E3k5rbqJV7ISfMcjAybklrIsEwq7TGwvJvLa+WOtzCTySuQdzJgpkVffZ4PhRr8RN2JADIgBMSAGxIAYEANiQAyIATEgBsTAWGKg3yIvI3gp8OYydTj/HVk8t+4CvNE5H693zMarHdPwakcDXu3I47WOJrza0YxXOprwSkfjm9KrHY1geq2zacDp9c4mML3R2YQdHYW0s7MZe9M07Oycjh0d07CzYzpeb5+JVzoPxXPtp+FdJzqor3GQDDlIxSKFCNpoYTrieLzvaYn9otZgIShM18wpkpPgerlckzcWT6I60QgnMx+5916FU3+6EifevBVvW/AU3rrwKRy+8E84pPVPmLHwMTS3PIaGhY/2pEeQb9mKfMvDyLc8gHzrfWhafB+aF2/CjEWdOPQPnXjrknYct2Q1Tlx8O97+298i8g//AKexGU5dDuWJNGridQjHkq7IW5jGuRDFu8+UznsiftX4B1vvY+13/vYwGJHXhKuxJljpfSRc98WAibWlLNsGpzefNWsW5s6di0MPPRRz5sxxI+HH4h9JeEVe9iX+/mU4+k/es9gfqFhk6HDaYDDoRqjymYbj3UfrPVg+perFOBqt76bn1vemGBADYkAMiAExIAbEgBgQA2JADIgBMSAGxEB/GOhF5GX0bh65bB6ZDKeXTCOXq0U+E8YvvvcevLjmcGBDNbo7A+jqqMSuzvKeVIWdnQHs6KzCjs5K7OzkNvO2zXMrsbO9wpe4rwq72it7UgV2tTMVtnfu2V+JrvZKdHdUeRK3vfsC2N1WBWwMoaszhJfWNeOW7zZgTp2DdMxBIhpGjNMkHySRlxG8FHnDsVpUJeoxIdWM+LEX4oLvL8GZtzyAo255FHMXvoDprS9jeutLaPj9M2hqeQpNLU+g0RV5H0HDQoq7W1yBN9fyIHKt9yPXeh/yi+5F4+LNaLx1M6bdthnTlrRj5u2rMXfpMhx1+xK8c+kSnHXTLzHhhGPhpFNwkglUJhKo4ZrAyQSiCYq8nL65MKXzvtM6q1H1p1GNh3PoXPem/oi8FKc4XTMjeiliSeSVGNqXGDpWj5cSd23/7NmzwUSRd+bMmZg+fbpruc1UrFz422L7R/I+6wco8lLUrqur22epBG8f480fiD6W15fIO7rGeNaZRN7RVWcHou3qmmJADIgBMSAGxIAYEANiQAyIATEgBsSAGBjPDDjmZPU7gnO5PPK5gsib4/q8uQyyuRhyWQftyz6J7e1vATop8lajq6MKuzorCqkjgJ2d1XhjQ6Ur8u7uCGB3R7Ur9L7RWdi3s7MSb7SVo2tD4XcUfHd11KCro8Y9t7sj4Aq46Ay497BrdHVUo5DnNS1VYXdH5T6Jgm/X+vLC87VXY2dHHo8tOxwzww5ycYq8UXDK5OGseNdBbevvuuJyHJXJLJz84XjLJ7+FM3/3MI79/dM4YuEzmNf6HGYsfBHTWl7CtJYX0dzyLBpb/oSG1seRb3m0J3qXAu9DyLU84Aq82YX3uSJvrnUzcq0bXaG3eckmTLu9DTOXrsKcpXfgiGW34bjli3DKsptx9p0/x6E3XAYnG4STjmJqPISaWASheAzhHoGXEc6WhrOsdK/hZXMw5e0VXIrl/aIvtylCUeBl8k5By75nNApU/j5T2xKt/QyYaFvKct3d+vp6l3+2CQq48+bNc0VdE3Zp/Ynn8Fy2JWs7tobvaPjjCfvu4DvbH3/QplKpcSHyMlLXm4oJlewz2Tf3Z6aRwfThY+E3EnlH/rfCWOBM7yDOxIAYEANiQAyIATEgBsSAGBADYkAMiIGRzEAvIm/OFXkbcg2gyJvJZdDQGEUu42DTisuxvf0wdLcH0N1JcdZE3krs6qh2EyN3GcHb3V7tpkI0LyN7C9G9uzYE0LUh0BPVG8CO9hh2tKWwoy2JnW1x7G4PA53BPSIvBd5CYuSwCby0fpG3At2dJvIGgHaeU49n7p6N2WEH2ZgDTpl84CuF0yx6plp0Bd4oEpEYIrFalCeycNJzcea3FuD0/3sYRy54EbNaX8WsRX/BzEUvYUZrIU1reQHNrX9GQ8uTyLc+hlzLI8i1bEGOAm8rBd4/uuJutuVe5FqZNrkib37RJjTe2onm29Zi5h0rMfuOpZi//A84+u4WHLvit3j72l/grLv/C+f/6gY406rhpCoQqI+iOhFFJBEHI3hN4JWTeTh4GV33KCbsevcVE3kpgDFaj8mEXhPFTKiybVkJpmOBgVLiLvdTlDWR1x+1a6KuRfHatlnuZ6LQy99SNKVYzEjY0STy2h99sE/gcyeTSYm8ocL6vBJ5+x4TJfL2XUYH/ltXz6AyFgNiQAyIATEgBsSAGBADYkAMiAExIAbEwMFkwLFIGousMQcxLSN5vSJvviGCfMbBg2s/jVd6RF5G1HpF3oIQS+GXUbcFgZfnFKZtrixM7dxeidfbK9z0xvpy7FgfxksravHCikY8u3IanluZx462NN5YG8Qb6yuwo6Oi5/cUk6vc+/GeBYG3IPJ2tVf0RPMWF3m3rZ2POVEHmZgzjAJvQeilqJwMR5EKR5EMx1ARYwTvkTjj+3/AKb9/FEe1PI95Ldsxu/U1zG6l/QtmtlDk3YbpLc+jaeHTaGh5AvnWR5Fr2Ypcy8PItj6AbOsfkWm5F5mWzW7Ktm5GtnUTsq0bkV+0EY23drgi7/Sld2PW0tswf/mtOPruhThu5W/xt/f8HO9c/V84f9V38He3fQPO0bVwUlNRkYwgnEhI5B3mSO+D2QkM5t5eQbdYvpjIS2HLRB2JvBJxx4KI29c7lBJ5+TsKsmwHFrlrgi6FWxNzi1kTd3meib0UejkVugnHvG9fz3Ywj/P7gt8e1h8wz2fmHxQxqrVYn+LdN5g+q6/f8PrWbxWLrB3Kfd4oXlt/1399ibx9/+eAdeYvN9tm+fF4X/Wu432Xs8pIZSQGxIAYEANiQAyIATEgBsSAGBADYkAMiIGRy4BDJ6tF0ZjQa85fE3lpGcmby4XRmHWwte3qPkXe3T1TL1Pg5ZTOuxjt2yPM7uyI4oU1dXhqZSOeXjELz656G3Y//H7sfPjDeO3hS/H6lg/hz2tPxePLDsfjy5uxbX0DXutMYUdnyI0S3ivw7p2muS+R9+W2t2BuzEE6Opwib8SN5o1HKe5GEQ0nEIhl4KTm4tz/vBMn/+4RHL7gWcxe/ArmLKLA+yrmtP4Fc1q3YVbLi5jZ+gKmtzzrrsfrTtXcujeKN9t6PzKt9yHdshnplk1uyrRuRmbRJmQXbUR+8QY03tqO5tvWYPrSuzBr6RLMX74YR9+9AMeuuAknrfoZ3rHm/+Gdbd/CRev+HR+6/V/hNE/EhHQANckIIglF8qrjKt1xeQWXYnkTS7yWApSJOmbtj0pGuihlfaKsxOmBMFBK5KUgS2F2zpw5bxJ0uT5tMXHXu4/neM+z61H4pWA6kGc8GOf6RV5us38w0c7fp1g/YvsPVN/M6/NeJhQeKNubyOt9V76nZtLofRwqVUcsR9bngWJF1y1dLyoblY0YEANiQAyIATEgBsSAGBADYkAMiAExIAaGjwGHzmEKLowIoqWjlY5pV/DN5pDPFtbmpcibzYbQkHbw8LorS4q8XI93Z0cNdnZyKuZC5C3FXQq9FHw5nfOzK1N4bPXb8dKWzwE7bwZwD4BNAB4Auu8HcD/QvRHouhvbn/gmnmx7D55cORvb16ewsz2MrrYAutr3Crxck7cvkXd7+xE4JO4gE3eGyWlaiOKNRUOIRcKIRWKoZARvej7O+mYrTr3lKRzVuh3zFr2C2YtfdQXe2S1/weyW5zCr9c+Y1focZrY+h+aFT6OJUzXvmab5YWQXPoBMyx+Rbrl3j8hbv3Bjj9i7EdlFG5Bb1IHGW9ejackqTF+6DLOW/gHzly/C0XffguNW/hon3vM/OHnNf+LUtm/i7Lav45J1N+D9Cz8Lp9FBWWoKQsnCeoBqjMPXGEdTWZvYUsqaUOG1nE7WK+5QjOJ2MYHX7X9yuUI/lMuNeNHqYAhluufBF5xNxC1WF3aM1tbdJddesdbyJtp6hVs71pu13/nP4Xhu0bHWzrzPWKzNeY8f6DzLwf7Qw0RpRjazP6Fo5+03SvUx+9NfepcisDyvZ/ey+5cSEA/UfrsvLZ+Fz2TP57X78+5j6bfGS7H68JbhWHpnvYu+ycSAGBADYkAMiAExIAbEgBgQA2JADIgBMSAGvAw4iUTCdQZT7KWjmE5jOl2Z/JG8/RZ5Oynyck3ewhq8BZG3Bq+vi+LFexrxl81nAW/8DOhuA/A00PUysHsHsLsL2L0L6NoFdO8GurcD2ALgdrz2yCfx5N1H4aV7ctjZFsOudorGe4VeE3m7OopN11yH4RN5C+Iu17SNxSKIx4KIx8KIp+rgpKbjqE9/D2f+3yN4W8t2zFvchVmL3sDsW1/HnEWvYE7rS5iz6DnMbn3GFXlntDyL6S0UeR9HgxvF+7C7Fm924f3ItDCK917UL9wECrx7Rd4NPSJvOxpvXYemJSsw/fY7MHvpYhy+vAVH3/1/OG7VL3HiPf+Fk9d+F6e0/RtOb/8aLtj4ZXxkw1dx+jcvgNPgIFAbUASMpmwuyYCJIaWsV6ywPPsa/hEJBST2LxR5TODxi0oSeQ++gOmvE22/uU5MyC1VNuSdiSIvx1dG71KA9YuyQ73Ne8ydO9e9j92ftq/nLfUeQ7Xf2rW//fPZbD1eCnal+hXb7/2IGUzeK5ha3nsdu4/1XcVExKHcZ/ex+9La89jzea0dG++W5VSqHlim3nIc72Wl99d//sSAGBADYkAMiAExIAbEgBgQA2JADIgBMTA2GXDMuZhKpdyosC6lawAAIABJREFUOYq8FHw5hbMbaZNvdMXeXJ4O7kIk75b1V5WM5GWk7q6Omp4oXhNhq/DK6imuwLtzy2VA9xIADwLdLwDdrwPdFHV3AbBEgbcb6N4J4CUATwBdG4Hnf4KnV52A7esa8EZb+E0ibxcjein8Mop4fQXQWQ20cw3fWmxvf8swRPKawBtFNMZ8BIlYNaKxICoicdQefx7O/78H8Vct2/CW1jcwb/EuzL51R0HkXfwy5i3ahrmtL2BOy/OYtfBFzFz4vCvyNrc+gYZWrsX7EHItD6KYyFtHobd1E9KtFHk7kVvUhsZb16J5yd2YcfvtmL20FYcvX4C33nUTjl35Pzhx9Xdx8rpv4NT2G3Bm55dxTtvV+LvOq/HR9Z9G9VlBlNVP6YkiSiAWi+9xOKsjGJsdwUDr1StGFMtbv+K37GcsitAi+Uz4oS0mJpXaX+xc7XuzEKkyOXBlYqKp31K0ZLlb9DoFV+8aukMt6ha7HoVe3pPCsr8NWRscbjb4HBR4+X3B7wzmTeBlH2T9RbE+xbtvoP2V/3yvYGp5/znctnvac5USFAez365Ja/eh9T9Hb8/nP3e8bbO8SpW9let4KxO9r77RxIAYEANiQAyIATEgBsSAGBADYkAMiAExML4YcEXempoacI04OsXolDYHrCv05hvRQKG3Ie+KvH2tybtH5OUavO0V2O2uxRvFsyuTeP3B83sE3qcBvAKAYi56BF0TeLu4A9jJbf6jfQPoeh3AVnQ//Q08suwovN6RBdfmLdzDxOQiIm9HFbo6KfIevo/Iy0jb3tLgGkJB2KW4G4tFEY9FkIzXoCYRg5NswiX/tQQn/f4pzF/0BuYv2onDFu3CIYt24tBFb2De77dhxq//hLof3o/ItzYg9r37EPvBvYj/v42I/6gTM3//KGYs2IrpC7agacGDaFxwH/ILNyPdE8lrIm+mhVM1e0XeuzDj9tswZ2kL3rL8Fhx9169x7Mr/xomrv413rPs6Tmv/Ks7qvA7v6rwal2y8Av+w+aP44O3/BCfnoCpZhUiC70SRV0Lv4JgYmx2KV5QolvcKGJanM55laIIYRV77YxKKP5b8wpNfoPIf1/aBEzFVtr2XrbFsloKlJfJNkZXr7g5H9G4xodemc+ZzMM+2ZAJ0X3Vbqj329bvejlsELwVemzWE3xzsF9iPWF9RrE/x7tvfvtiE01LWru+9pzdfSljs7/5i72n37OuZ7DzZAjOlypxlzDpTOY3NbxDVq+pVDIgBMSAGxIAYEANiQAyIATEgBsSAGBADBQYcOsjoDPM7yui0zmVzaGpo2iPy5nJh9CXydnVUo6ujxhVgKfB2tQfwlzVpPNN2KoBfAXioIPB2v1EQeSn0ukovLQVebjLfs9udtrlnP14Fdt+LbQ99CX++Zwbe4Bq/nYzU3bsmrxvJu4GRvOVAZwDgM7iRvAWRNx13EIsnEInFSiYTfwcOSUHkdcXdaBSpaATJaBBltTlk3/d5vPN3W3H0wr/gsJadOGpRF45YsAPT/ucZVHxpDZyPLiiky1rhXL4IzuWtcD6+EM7HF8C54mY4l/4KzhU3IXjjMmR/1I55t9yPaTd3IrdgI5K3dBSieFs2Id+6CQ2tncgvbkf+1tVo/sMyzFjyB8y7owVHLL8ZR9/1K/z1ip/gxFXfxTvW/hve2fY1nLPhOrx709V4z8ZL8Xf3/RMu23gZ5l02yxV6a+qqXUdpPG4RvRJ8B87F2OtwvYJHsbyJGGatf+G5zFNAMsHHInq5TYGIfU9vQpGO9S48qnwOfPmYqEtroi4t15Vl+VNwLSbsmuhaTJAd6n28V6lr8hnZBu09mC/FTW/HSv3Gv5/lwutYW+cfd/Ac7re1eL39iAl0tm+o+1wTUgdyXXsWf59mfVt/rf3erlfsGQbzfMWuM9b3sQxLlbsxNNbLQO839r6vVKeqUzEgBsSAGBADYkAMiAExIAbEgBgQA2JgIAzsma7Z7yhjZC8vlM/m0dzUjKZmTq+YwPQGB1vbri45XXNB5OV6uVXY3RHAjrUBPHv3dOx+5gZg11oALwLdXdi9m1Mx7wAo3O56Buh+orA+L15FVxf39/zjtM27dwM7TQx+FdixHE+uOg4vr0tgZ0eoEM3bXoHuPdM1V2FXG0XeqsK+zhReaZ/vRvJS5I3GkyUFXhN/C2vqDhQmiryFCN5UNIoko0jiCTiZuXjnT9txbMvLeMuC13HY73dixk+fg/PJpXD+meLuIjiXLcGky29D2RVLMfWTd6LiyjtRcfUyTPnMMky5+k5UXr0UFVctweSrFsO58hY4V/8KzT9vw7RbGNHL9Xk3I71H5N2A/OI2NNy6CtP+cCdmLVmMQ+9YgCOX/w5vXf5z/NVd/4UTVn4H71jzDZy2/is4u/NavHvTlbho40fwvvv+Af+86YP4pyUfgDPNQUV6KiLRKOLxJGLRBKKxuJsGApnOHShHI/98EyhKWRMyzFr/wm3muf4mxR0Ku4zqY6IAROFHIu+BFyn9Ipy2B1bmJu7SMhKViSIvObapmUsJrCNh/7x589xIWhN5e4vu3V+Rl79norBL4ZllxHbPfZy+nf0B+xHrKyzv7VtG0hhiz2V9mfVtfVnv+9k1aIu9WzGRt6/fFLvOWN/HMilV7izvUuU71stF7zfyv6FUR6ojMSAGxIAYEANiQAyIATEgBsSAGBADYmCoGOhV5A0FQ4iGo4hFYkhn0mhqimNGo4O+1uSl0NvdSZG3Gq+vrMb2dX8DYHlhDd7dO4Dd3di1uwtdXdsBPI+OZd/Ca0/8EOhaDOBRADuxu7sLu7qBru7d6GY0726u0cu5nSkOP4jXHrgMz6+cgx0dqX1E3t0dle69d7VNRXcnp3GuwK7OJLa3HzYMIi/BNKE3jGg8gUAyi7nvvgJnLnjGjd59y4JdCN54L5wPL4LzsdvgXLoEzhV3oOyqFSi7eiWmfPYelH9+NSqvWY2Ka1aj7Lq1bppyzT0IXLcGVdfeg7Krl2LyVYvgXPFrVHztD2j6zX3ILbwX9a0bkW3djFxrQeRtXLwS029ditlLWjF/6c04avlNOHr5/+Cv7/5PHL/imzh59b/g1DVfxJltn8X5nZ/ABZ0fwsWbP4C/3/h+fHLzpag4YyKcWscVxOPRJJgKIjjXHFYjHKpGOBqv4xUciuVN0DBbzBHPYxR5KJBR/KEIZOKPCUMSHwcmPqq8Dnx5eYVR5skqueXatwdzauaBiMdsb3xeJubJjb0XrZcjvp93u795a8MsG/4Bh7Vx7rcpmvnHZOwb2IdYX2F5b78y0vpIezZ7ZrP+fs7209pv/LbYu0nk7d/3BcvSX+a2bWVerHy1r3/lq3JSOYkBMSAGxIAYEANiQAyIATEgBsSAGBADYmDkM9CryBsOhREJReDaaASZTNCN5O1b5K0BNoewuz2M11bGgYcuBnZvAHbv6lmDtydKd/fLwKv3oWPJZ/HYqnfjmfb3Ai//AuhuB8DI3pfQ3c21eLuA7l3o3sUI391A16PA8z/B0ytOxmtteexsK3cjdhnJ66ZORvKayFs+zCJvDPE41/sNozISw+T6WXjPtxbi1IUvYd7vdsD57D1wLlsK5+PL4Hz8Lkz+9D2YfNVqlH1uHco+34YpX+hAxRc7UfnFdlR+uRNTrt+Isus3ofz6zai8fhMqrmtD5bVrUHnNSlReuwyTPrsYzrULMP33DyK/8F7kWu9FdtEGNCxeh+ZbV2DmrUswd8kCHL70tzh6+f/imOU/xrF3fw/Hr/g3vP2er+KU1dfgjPVX4byOj7si70Ub34/3bbwYH9r8fpzy/ePhZBn5HEcimnITI3kp9Kpxj+8y8AsV/m2vuMG8Od791hzxJgQxyo9ikFfs7a+opPMOvMCpMi6UMYVQi36luEqxlNMzm5A5EMH1YJ/L9Xr5DPwjC76XTa1sIu3+iLwUd71tm9fi9Snu+vsI22ZfYv2C9Ssjdbyx57Nntnewfs627bz+vodE3v6NryxXK2u/NYb6W+Y6r39lrnJSOYkBMSAGxIAYEANiQAyIATEgBsSAGBADYmBkMeCY89GckWbpMPOKvMEwI24mIhZy8PC6K/uYrjkIbI5hx/o4nrs9Abx0NdB9b0GgdaNxbRne7cCuLbh36aewre1kPLtqBv685ig8v/E9wBu/BLrbgN3PAbvfANw1fHe6Yi+6nwd2r8PjK/8e29fP2BPJu7utMGUzp2nuctfkZTTxcEfyUuBliqKqNgun7lD882824YRf/xll166Hc+ltcK5YDufKNZh41XpM+kwHyj6/EWXXbMLU6+5F+ZfvR8X1f0QFRd2v3IuqGx5G1Y2PoOKGrai44WEEbnwAVV/ZiKovt6Hqi2sx9Zq7MfGzt2Hq9Usw83cPYPriB5FpbUfj4nswbfEdmHXrYsxbcjMOv/1XOHrZT3HMsh/iuLu/jRNW/Avefs+XcMqaz+H0dZ/C2W2X4vz2D+LdG96Hize+G5dsOA+X3/NPcPKFSF6KvMlIrRvNy2mb427i+rwjC2g9z/DUh/Ubpaz1I2b9DniKPN4UCATc6D6KQjZ1M/P7KzRJlJTwu78MeEVOTjNuUzNT0KVAWmzt3YMt3A70/nwXTjNNsZrtrlg0r7VFf3mWOpfXYeK1+VuWG/uD6upqt+273xjh8JsE3WJ9ykjr1/0irD2z9Xdmbb89v/93tl92cOMWy9c/ttg264DHVbaDK1uVm8pNDIgBMSAGxIAYEANiQAyIATEgBsSAGBADo4OBAYu88X6IvLs7QuhqD2PH+hSeX5YDXvsygD8WInIZict/nHmZ0zXvehh/XHo5Xlj9FuzoSGJHZwrb1s3AoyvegVce+RfgdQq9zxfW7nWnat4NdG8Huh7A1lVX4KV1c9DFtXjdNXm5Bm8V0Bk4qCKvwV+WbEDDhZ/GxTc/ivgXVsL52B1wLl8G59OrMeHqDjhXb8CEz92LSdf8EZO/cD8mX/cApnz5IUy5/kFM+cp9mPrV+1FxwyOouPFxTPnaI6j4l62oufF+xG7oRPqrq5G//m7krluGzBduR/Rzv0f0hlbMumUzGhe2YdqilZjBqZpvbcEhS36L+bf9HEff+WMcc+f3cNzyf8eJK76Gv111LU5Z8xmcvvYKnLXuIzh3/d/jgvZL8J4NF+KizrNx2eoPupG8sXgccUbyRmp7InqTSEjkHdfOYxMvSlkTOcya492sCbw1NTXwJl7PhCFGFppQROsV2/xCk7Yl5h5oBihmcnpxckgx1ATesSLyUhjmu/DdLJKeZWrirtneytnO4e/5xxpM3Gf9ANs92zst+wLbX6ofsf02po4U6xdr7TmLWe8z+3/nPab8wD+aWd42pvgt2eJxlevAy1VlpjITA2JADIgBMSAGxIAYEANiQAyIATEgBsTA6GFg4CJv0MGWtb1H8u5uD2J3WxC72urw/IpmoOtGAIzk5Xq6HpGX0zV3PYB7l16Kl9cfhR3tUbzRFsT29Um8sHY2tiw/CVvWXgPs5m9f6lGGqRC/BnQ9hK2rr8SLq2eD6/DuEXnbq4GOGnStrwAjeg9GJG88FkMiGsPE5DSc8s0lOOpHD8G57HY4l6+A8+k1mHBVGyZ+ZjMmfO5+TPz8A5j0hYcx6botmPSlLZj05S2Y/JWHMfkrD2Dy1x5C2Y2PoYwi742PIHDjQ6j7l/uQ/8KdCF58I6pP/yTCp34CdRd+EdM++SOkr/kFZv33Ssy+eT1mta7ErFtvx5xbF2Derb/G/CX/g6Nu/yGOWfptHHvnv+D4u76Ek1Z8Fu9Y9Wm8c83lOHPNP+OctX+HC9reg4vaL8AlbefhE6s+DCfjIB5PIBalsMto3hRSEYm86uQKnVwxUYP7TLwx63fAFxN5GeHH8yimUSSyaV4p9prgayISbW9ik45J9B1KBsikRfDa9MYURC0NNHJ2JJ1v78A2xudiRC8t25i1xb7anR23dsvoXeYpalLUZaS+/TGHtX22dRPiSvUjtn+k9bfFxFp7Vlr/89r5Zv3HtT24j2aWtX9ssW1jS2U7uLJVuancxIAYEANiQAyIATEgBsSAGBADYkAMiAExMDoYeLPIGwkjHLE1NMMI96zJGwoHEQ5NRCLoYOvaK/Fq+2FAewDdHQHs7qhCV2cFujqYAqDIiw1R7GpL4fmVDcCu6wFsBrq5pi5DeG265peB3fdj8x0fxbb1R2BnZy1ebavHC2um4YkVR+KFe/8ReO1mAA8CeNn9ZUEipsh7Px5d+ylX5O3urMGu9krs7uDzVAOdXpG3HDs74tjefigOiTtIx7nGbMJdV5ZryxZLhemWB1+BJvI6qdk455cPoOzqu+BcsQrOFevgfLoNzlWdmPCZP2LC5x7EhM8/hIlf2IqJ1z2CiV96BBO/vBWTvrIVE7/yMCZ9bYsr8Jbf8Ahqvnofar+0FsF//G84zefCyRwNp3YenNQhcOqPgJM7BsF3fQIN1/4YR9+0AocsvAOzFi/CnMX/h0Nv/SUOX/IjHHXbd3HM7f+OY+/4Go5ffi1OuusqvGPlJ3Daqktx5up/xDlr3ot3rbsIF62/AO9rexc+ufKjcNIOYj0ibzyaRDJSSIrkHTwfY6lz9AobzJuo67fmePdaE3v+P/bOA0yqImvDNTl0vql7ZshJJCMoSTGBCRiya866rllWEV3T6qqYVncxIahgWBXDqiRFUVQUCdM9qL8KgjkjkobJM9//nNtzoOjtgQEZScd9ak/durnqq7pDvX1OkSXAS2t1UqK1ThmoEagjL14GvQSOGCjRPsrvTJgn1xI4rGuAICcn1mbnzp03wV0GpInQtr7yxON2h21+VrL0PARoyZuX+ha9u97H9L7H9cRl/KMM6q90Ho0HHJqZ7L4CeZON7wx32SY7Rsq2/5sqkHf760x0JnUmGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0YBoYO/SgOIGpckyoy6FyDvChb0GQiETRshEyAjCDKUhElT4avFVKC3qCkQ9bqqNEWDNRnUs2wW+NTE/UBxEVZGFNe+FgVUXxz15a2qAmjrIW0lhl0sAfI6P5l2EVYt64LeFTfHtu93xc/FpQOlzQO1SAL8A2OB6AdOZcci7HsCHWD7vLKxb2AmIGaiO+VFT7ENtsQ9Y6gOtz4ulXlRHM1EZs7C+qDM6WwoFVnyNWQa59Vmulx21VJ8EYQ+5/yOoKxdB/TUKdcWHUFd9DDXuExfwqr99DnXtCqTe+BVSbvwKqTd9hbSbvkTazV8i5R9x2Jt20woEb/4UxuWzoY68GqrpYUjP64yccEv4wk3c5I00R26TtlD5+yEy8s8Y8OgLOPClV9Bh1ovoPPsZdJ09BT1eewC9X78H/d64E/3fvBmHz7sGR8wbg6PeuQSD3vsLCt8/E8M/OBmjF/0JJy4ejVMXE+S9CKogXl+2HXbX4SW4K4B3zx8ESJ96+j065+skgl19m+Eul/E2nUv3JmBEYIjgLiUCahQalxMDJAr/yl69icCXoZNYAbW/RwM61GTAS5YhL3m6MhDdHSDt730Ghrx8HdomkE31QO/NfZOsXje0rfdL6pvUd/U+zj/kSAZ56TgeO3S7o2ORnLfnf5e2tw1JN/wtSbSsr+29phy/7+lI2lzaXDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6KBPVkD/wN5CfAy5A0acchLoJchb94WkDcXiOaiNpaDmliWC3rJq9f1rI35URkNYv17AeDrkwB8BNQS2N3szAuUuWGXP5jzV3y1YAh+WnI0an8mr9/XgeovAJTHnX6rCe3Wuv+LQ95VQMl/8dU7hdi4aD8gZrqQt5rg7lIP8CF5E+uQ10wKeRur4QgcUx2qvK7o+c+lUFcWQ13xEdTYT6Cu+hRq3GdwAe/fVkBdt3IT5CXQm/b3r5B+89dI+ceXyPjHF/D/43NknD8T6uiboJoORJrRBqGQA8uyXThmWiassINAKITcSBOopu0x4M4J6PviNHSY+TQ6z3oCXWdNQs/X/o3ec+5Av9dvRf+5N+LwN8fiiLcuwdFvX4Tj3jkPhe+dhuHvn4BRC4/HiYtH4eRFIzBm/gVQ+Qr0Pm7IZovW5rVhUbKk4+/JdaBDFcrv6Lvo12G4k8zyBDx58xHwoWPIq43AGYM09uBNBLzhcNiFvVROkIk8BQko8Tq9OnjS878H9Mm5+y4o1jWka5N+cEAa3ZcgL/UDqgN6b8pT3TDYJY9fAsP0owsqcxzHBW40llD/pj7PkJe9eMlyGR2jjx+c39GxSM7b977JpBn+tiRa1pfoYt/ThbS5tLloQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA/uSBhoF8tYU+1FR7EN51IfyD7zYsPgQoGo+UL0RNTU1cJmtG7K5DLU13+D9tydg1ReTgeo3AHwK4Kf4urvkt1tdFYfDrg8vgV767wusXj4GP77fFRVFTVAbDaAq5kNlsQfVS3NQ+2EOqqPZmzx5y6PGroG8kS5oe8O7UFcuhbriY6irPoMatwzq6mVQ13wORZD32hVQ138BdcOXbiKvXnXDF1B/X4nsm5Yh65I3oY66Aym9/gzV/BB4nVaw7AgMK1yXHFjhMEzHgtcJQzlNcfRNt+Lg559Eh+lPoPPMx9B15oPoOfuf6P3abejz2k04eM7fcOgbY3D4Gxdg4Jvn45h5Z2HI/FMwdP5ojHh/JI5fOBx/WnAcLnzzdBfyEtglmGxYpgt8CfruS51kb3xXBipsG/KOfCxZOl7fpjxNqvPEur5NZTQBr+/jcMwEkAgcMeBlz13dEjwi0EtQmMoJ9jJoYq9eAlBUxnCWrst5sfsusN2RttchL+mS094MedmLlyx58hLI5nrgvkTbeuh0+qEFlVF/5L7P/Zz7PANdgbzyzWzIN2Z7j6HvTCLc5W3+3mzvNeV40apoQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0cCepIF6IS979BomwRxruzx545DXi8piH6oW52LV2+2ADVOBqs9A3rsEauOgtwa1+A1VVV8DNd/UhWYuRW0d0HV5rvt/7hkAKuIhnmsX4YfoIKxemI/qqIXaqA9VMbpfLqqXZruQt4og74fxcM27DvJ2RbNxc+Nhml0v3mVQ45ZDXb18S8h73co46L3+C6Tc8CVSb1iJtBuWI+PKhVDH3Y/MY29FeucTkNn0QPjspu4auSErgpCVB9MOu5A3EArC79jILmiGvpdchEOffxQdZzyCzjMeQreZ/0aPmePRa9ZN6Dv7ehz82jgc+vqlOPz18zFw7rk4+q0zMPjtE1D47kgMmz8Mo94bghPeG4wL55yBtALleu8S4DVsw4W87EW8JwldnnXLgTkR0DakfhLPoW06Ty/niXUq0/M08U7HEhBisEuW4S6HadbhLufpHM4T6NWvQxCPQC979vJ6oDqY2hHQJ+fsu2CY4SZpgAEv2X0V8nJfoB9RcF+jPPVL6ucMdnW4pkNeHfCKJ++W43BDxl05pv46Y/2x9nTL3x+pv/rrT+pG6kY0IBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdHAnq+BBkNe0zRgG+nIDyl8vWRc3Zq8m8M11xZno5a8aIu9brhmAr2ud22RBxuXNMe6pYVA5X8AfLeZ3VIQ5loKyVympaq6lXcJADPuJchL5bQ27xdYu+IefP9ed5QsDqEmFkRtzAuCulXFlHJQszQXVRSueZdCXgvK6Qrr4plQV/4f1JWfQV21HGrc5/HEoJc8eSkR6L1upQt5M29YieyrP4Qa/R+o4/6N0HG3ILPDSKTYneC3C1zQGoe85NFru168pm0jJxRERsRG9iE9cNgLD6DzjPvRZca96DbjDvSYcRN6z7oe/Wb/Df1fuxKHzbkYh79+Hga8cRaOevMUHPvWKAx5ZyiGvjsYo94txGnvHo9Db+uD9CZpLlQmT17bthC2wrIm7z7kyawDXD3Pg79eRnkqJ+89DslMZTTZToCMQC4BNEoEYRnyMujVYS4dz2GaGfCypXLeR+cQcCLIS4lCyBLopTK+lw7tGFiJ3Xch7rbaXtfLvgx5qX9SnyVLHr7Uv7hfcb+nvs1AlwGbvq178nKeLB/L19Etjy1i9/w/MBu7DUk3rKVESzqk/Y39DHJ90aloQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0cCu1EADIa8JgryWkYE8F/JeVQd5PUDUg9pYLmqLCfBS8rmQl9blraEQykUelBVZWLOwFaq/PBPAPAA/AgR33aV2q+ugbm1dWOY42iW8W41qVLoHVQJYC1R9Aqx7Gl+/NwyrP2iJ8iIvamLkrZuDqmiWm6rdZ4mX7XLIG+4O6+JZUFd+CnXlMqirPo8nAr1Xfw51zYq4Ry9D3rrQzdnXLYc673WoIZORety/YQwaD0+P06EiPeo8ee1NoZrdEMqOBTuSB6/jQDlBHHDxqej//D3oNP2f6DL9DnSfcQt6Tr8OvWdejX6zxqL/q5fjsNcuwOFzzsGRr5+BgXNPwjFvjsCgeYMx5O1jcfzbw3DuG6dDHaSQkZ+5CfI6FC7XCiNsOvG1efch2LkrO+muvLcOX7YnTxPsBHPI85YgEYNXhkQ64GXIS0CJQW5DLAFeTnQuXZs9DRlI8f0E+ArU3Rbc5f0CedujY8eObn+i/kN9l348QXkKnc7wjMYDynNiyEbbnGewq3vwCuSVP3p31jeNNMhaS7Ss0511L7mO6FY0IBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaGB31EADIC8B3i0h71dFBHm7AVGvm2pjHtQWE+il5EdtcSDuzRvzobrIh6qoHyWL/fjxvZao/XEMgDeA2u+BGoK3lAj0om69Xc6R9y4l+q8EwEpg7VP4ceEArF7YAqVFJqqX+lBdzIA324W99Cwo9qE6mrvrPXldyDs77sU7djnUVSvqIO8KqKs51cFe9ujFm0kOAAAgAElEQVS95nNkjvsYasgUqEETkTl0EnyF/0bgyHFQTQ9Drt0Ktu3UeafQGrkh15PXsCPIDoehmjsY+uBN6Pv8neg84w50mX4rur1yI3q8Mg69pl+BPjMux8EzL0L/2X/GobPPwOGvnYIj5xyPo94YimPmHovj3hqIE+cOx+B7BkK1UsiJ5MCyaU1eywV2ji2Ad3fsyI31TDrYZZjDk+cMefgYegbKkyUYRCCXoCslhrxUlgh4dcjL0Jbs1kAv7yePXroXHUugl67FYIrvqwNezjPQEyvwN1EDAnnjkJf7D/VX6mP0gw3u62z1MYEhG5VxXiCv/OHbWN8m/t6w1hItf6ca8/5ybdG3aEA0IBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdHArtbA/0Beg7xzTAOGReuvGptC3Rl1nrwRQ4Eg78ZoMshLsHdLyFtTRKDXg/KiLKxdFML38zug8quLgNpXgZqPgNqVAH4AsBqoXQvUrgdq19Vt/wDUfgnUFgHfP4if3h+KdYuao7woB5VRTxzyLvWgkkI1R3NQQ4CXwHOxDzUUrnmpB9XRTOyaNXktqLzusDlc81W6J+9KqHF1iWCv7tF7zXJkXVkMdfRDyCqchOwRU5E7fBICg++EajkEWc5+sOyI2y7UPoYdguGYMBwHGQURtD9jOIY8dSd6vzAeXaffhq6v3ITur1yHnq+MRa/pl6PPjEvQd8ZfcMjMM9F/5sk4fPYJOHL2CBw9ZygGzxmCEXOG4pxZp0G1UcgoSEUg7HchL03wc9rVopX7/3EDJ8McsjrQ4XKeSKdtaheyBFsZ6hJwJS9APextsjydoycd9jLQJZCrlyeDwAR96RgCU/QMHMaZ8gx4dYiXCPhkW6Cvrg9dq6Q32u7UqRPat2/vhjCmMMZ7ekp8F9qmd6S+Q/2Ix1vu87rVx4TEPEE3gbx/3FjN7bQvWdJiItzlbf427Uv1Ie8q/U00IBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdHAvqeBTZCXG588NgkemrYfluWHbRG8IU9OE5aZgTxT4evouE2Ql9bDJbhK6+DWLPWA1uKtKQ6gOuZDbcwHRH2ojfpcKFseDWLDQhur32+NVYsOAX4gr95nAcwFsAjAJ3GPXSwHahYAeA349R5s+Og0rJ7fExsXNEf5Ih9qYjmojhHkpXV//aiM0pq8ua4nrwt6i72oiWYDS6ls10BefyAIldcVxvnPIeXKGNTYj6DGfgJFsHcshW1eEQe9rkcvhW9eDnXtSqT87XOoE16GGvEYcoZPQtbIx5E5fCpyCh+EancK0pwuCFr5CJoOgjTBaRsI2iE3efZvhmGPjsfBz9yOA1+4Bd1f/Du6//c6HPDfq9Dz5THoNf1S9J55MfrOPA+HzDgZh00fiWNeG41jZg3DoJlD8adZJ+C0505zwzSnFaQg4Phg2EF3LV7SgG2H3UR51ovYvWPQ0MFNsnwiwNG3aVKdziEIRoCMoC57AdK2Dsq2ld8a6G0I4GXwS56HdC2CzDropW16psQkcFfgLmuAtMF5Xa/7GuSl/kZ9W+/r9eWp//M+Pc+Ql60O4Oj4ZN8P+jFRsnIp2zu+NTuzHUlrrKlES/qi/TvzfnIt0aBoQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0cDupoH/gbzxByQPXl8c8pqWu/5q3Ks33YW8X0WvQkm0mwtvad3dagK95DW71Ivq4sAmyEvr5ZJnbRzy+lEZC6BisQelC33YuDiMH+Y1w/fz+2Ptx2ej8tsbUP7dHaj4/l+o/P5urF02Bt8vHI5v3+6BDYvao3KRhdrFuahZkgUU58ahrnvvgBsOujpK6/DmoiaW6+7f1ZCX1spVkQ4wT70fuWPegRobg7qqDvK6a/Ny6OblccB79TKovy1H2jXLoEa/ADXiUWSNeBiZI59A5sgn4Rn9ODwDboKK9EaO3RoBOy8Oecnr2rEQskMIdGyJUY/cjgHP3oU+z92C7tOuRe+Xb0DPF67EQS9dht7TL0bfGRfi4JnnoP/0E3Hk9JE4dsZIDH1lFE6ZcSpOnHIi0g/KgGqaCp9D7U8TpKZA3n1g7WGaDN9aYoCjW5pUp3MIqBIMI4BKcJcsw1TyBOSkA7P68r8H8jLgJcsevXQ9uhdBO/bsZS9jAb0Cdhnm6lYgb9yTVyCv/MG6u/3Bmvg89P1JhLu8LZBX9JuoF9kWTYgGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0sDdqoB7IS3CPvGwM2CatwerUhW5OQ8RS+Co6tg7y+lET87teu1UxD6qKPaguDrqpKuZ1vW1dL9+YD5WxICpjIVTFyMs3iKqiICqWONjwQTOs+6AtfninJX54tw1+nN8Ov7zXFqsXtMaGxS1QuqQAlUUOqosCqCnyoMb12CUPXQ9cwFzkBYWErinyo6bIi9pYDmpj2XWevLsqXDOFT7aQltcGab3PQMGlLyHjisVQV30GNW4Z1Dhan5cShXCmMkqfuCl17MdQw56BGjEFmSMmI5M8eUc+gayRU2GOfADp3U6FcrrCazeBaYZgGxbCVhiG5SDVDKLZ0Ydi5EO34Min/4GDpl2HXs9dgz4vXIk+L16Mvi+dj34vn4eDXz4Th718Mo56+UQMfelknPT8GTjy+iOgWiik2ikIhkNuuO644Anyxj2rJFzz3jsINhTw8nE0gU56IIhK0JThrg7IGO4SQOM82/ogL5frsJfyuhcv5XWgmyxPkJdhL6/ZS9emZ+XEIJphrw76JL/vAmBdw6xHsqQnsvtKuGaBvHvveL+3/DErkFc0urdoWd5DtCwaEA2IBkQDogHRgGhANCAaEA2IBkQDogHRwI5qoB7ISxVa58XpQl4K10zevemImApfRsdhQ7Q7alxgG3BDJhPgrSz2omppEFXFBqqWGqiIWSiPFaAs1hylsdauLY/ZLuytLLJQRWlJEFVL/Cgv8qK8KBcVRfH1dWmNXQrB7IZhdoExQeMtE3kKu7DXBb0EeSlENEHerDrIS/t3UbhmI4ScvJZQzfpgvwseRc4V78ehLgFeN30et+TBe/WnUOP+D+qqj5F65VKooU9DjXoC6SMeRebIqcga9QQyRj4Oz4iHkTfibqjmRyM93B4BMw+OmYc8Mw/hcBN4LQdZeWGoZiZa/2U4+t5zCY599BoMf/o6FD55BYY9fTmGP3MpRjxzEUY+cz4GPXwyul7ZBym9MqAKFHIime4avwSNdUEJ5N37BxiGt2T1tqdt3XuX8wRRCYbpYZkTYSkDXQamvE1Wh2dby+uwNxH06tuJoFeHvAx7de9eCuHMz657HvOzihXISxrQtSmQN5R0LGCPSX0M4XGDvCo5VDNZ3cuSztPHGs7z94a3xe79358dbWPSGWsq0bIud/Tacp7oTjQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0YBoYE/QwCbIy16atu2AEj+87YZrtmCYBHmz6iDvtVgf7eF65ZJnbmWxHxXFHpQXe1FeHEB5sYWyWD5Kl3bAqsW98Wv0KKxeMhBrivqg7KPWKC2OYGOsDdZ/0AzVUdv1yK2I5aIyloXqaAawlEBvNiqjOaiM5qL2Qx9cT2HyFq5LlVGPC32roh5UUajmWBDVMT/KF6e7YLfaXZN310Few7SRY+QhraAj2p12Kzxj5kGN/Qxq7PK6RGvz0vandWGcP4Ya+yHUpUughj4DNeopZIyc6kJeArxpox5Hxsgp8I54GJFhd0I1G4DMcGcEjaZwzAgsM4KQ6SBgWci1DaTmhaAKglAFAagCH1QTH1SBB6ogF6ogG6oppSykF2QiO5INIz/kAl7HsWEkTL7zpDtrhLUhds8d5JIBGZ4U1/dRGScqJ7BKUJS8YQmUkk30iNU9IZPBUh321pfX4RrlddibzLM3GfBl0JsIgOlYuiY9J6/Xy8CXn5eei/Ni9y3gq+tX16FA3i3HAn2c0PP0XeDtRPDG2zymJPuG8Pcm2T4p23O/OY3RdqQz1lSi5e9ZY9xXrik6FA2IBkQDogHRgGhANCAaEA2IBkQDogHRgGhANCAa2F000DDIaxHkpTU7c5FnKaxYcit+ix6F0mg7bIy1Q0msLTbEWmN9tBXWRdtiXbQj1hb1xIA2Coe1UzikrcKA9gp/Plbho5l5WFPcFbPuVxjcXqEiWoDaDx2UxSIojTqojAZRUeRHWZGN0iILZUU+VEQDqIjloTzWBGWxAmyMUj4PlcURVMRMlEdNlBflo6IoL+4l7ILfXODD5JDXpEnoRl9n1UHAjCDTaoqcHsPhXPoy0sZ8gLQxi5Fy+SKkjVmE1DELkfLXhVBj3kfGlQuQfunb8IyZD1X4GNTIuPcugd70UVOROioOesmz1z/8ITjH3gjV+jikmp3gs1ojaBbANMKwDBuWEe9g/J5kCdyb1uZkOA5M24Zj2whbDiwzD7aVXxeaOe7FzSLlSXeBvHvPwMUQhi1DF7Z6OU2eEzAl8MmhjhnwMhAjqycdjPIxell9cJfLdbjG+UTQq2/rkJfyiWA32TYdR89E70SQl7172bOX4bX+3JLf+4GvrlfWHlmBvNsPeWk8SYRvtM3jDH9jdMvfG71M8nvPt2dntqVAXtHFztSTXEv0JBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdHAnqiBJJDX3rQGK70Qe/Kalg3T9CLPVlhe9CB+XHIBVi8ZhV+LRmFV0Uj8UjQcv0RH4Oei0fi56CR898FpLuC94c+5mPVoL8yZ0hRnHaNwxrEK30f/hKfuCuGI1gol0VbYGG2G3xZ3x9poH6yPdkDp0k5Ys6g71i7uhIoPm6ByaTNUxHqhJHo4Vhf1w+roQVhf3BPrluyPjbHm2BhtgZLFXVG6pLubr/oozw0hTZC3JpaFypiJ9UWd0cVSaGKpPwDwElS1ETJtBJymUJEu6Hj+Q2hy4bMouHAaCi58Dk0uehEFF72IvItfROTiF1Bw6QtoOea/aDfmv1BHj0fWyEdcL940F/AS5J0KyhPkzR3xCLIG/RPO0Nvh6XkOVF4/BPI6wAk3g2WEYRPotRwYlg2DAD0BbZvylKicAG8Ylh2GY8YBb8BqhlC4OYJBE7Ybqntzh+ZJd4G8m+tkT+zs+jMzxGXL0IWhDFnaxyGOCXgSCKXEMLehwFOHZnwOw9xtWR2y6Xkd8Op5HfYmA7t6GXv60jn0HOydzO9J2/qz87PyO4jdO4Gv3ua65gTyxscEHjPqs/o4w+NJIujl8UY/lvP8veFtsXvPd2dntyVpMFFbvM3fsJ19T7me6FE0IBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaGB30kCDIC89cBzyBvDazKfw8eJp+Oz9u/H5gpvw2YLb8MmC8Siadx2WzLsei+f9HUVv3YSiN27EotlXY8mccfhy8VX4MfonPHidwiHtFL6NnoXH7yjAEe0U1sc64b93KozsqXBYG4VrT1f4pegYnNpf4c6/KKz+oDkWP6lwTGuFL+Yeg3GnKgzooHDpcIXv5/fBulgXDNpP4caTFAa1VXj3UYXSqF0HeT11kNfC+qJOcchrKtg2iXDLtUd3bqOYsG0TISOE2a/NxZwPPsF/Fv6AyYvX4aFFJbh/YRn+taAM97xfhrve24i75q/DXe+uwh1v/YC/z/4a4RG3wjfiQWSOnOKC3RQX9E5B+qgpblnWyMeQPfIRZA3+N+yh96Dg6L8htdlhyC44AFl2R2Rb7ZBrNYfHKoDPbgKfXQC/0wR+O558dlP4nObwOa3gdfZDtt0R/lYHw2jTF36rJUwrr87rN+7xTJPucW/g+A8AGt8LWgaJnavHzeFT6wMzDF3Y0v0JghLIJNjZtm1b124v4K0PhDIw3ZbVIZue18Gunt8eyKsDX87T83IIZ3pvgtv6O+gAUC+X/N4DfPU21jUnkHfnQV725k02zgnkle9fMl0kKxPIK1pJpgspE12IBkQDogHRgGhANCAaEA2IBkQDogHRgGhANLAvaWAT5G3YSxt4/923gKr1QPWvqK1eg7KqSpQDWF8LrKsF1tYAG6srUVu1CihfiTdn/gsvPHY+Xpl0FP7UT+G84xRWxUZgyi2mC3m/ebsdjmuv8MjfFeY90w992yq88GAf3Hl5Kk4+WOG3hd1w9/kKFw9VuOPyTJx+tMI703rhjKMVbjxH4dcl/TGglcLJfRWeuz0Dq97PR1nM767dW1uci9pYNqpiFjYUdUJXW6GZrWBbwUaHvJZluOsYv/f+ApRXAyW1wG8Avq8FvgewEsAKAF8A+BrATwB+BjDpjc/Q8cRbEBx2r+vNS2A3ddQUpI2egvTRjyFz1BQQ5M0a/ihyhk6Gd+hEhAonwB48HnlDbkZWn4uh2gyDyjsQqZFOSA13QIqzP9KdDsgMd0R2pDOyIl2QEu6C1KYHI3DAKbD7X468o65FwWGXIr/jsfBbbRCy8us8f9kDeLN1gX+jh7uWgahhfTJ5PdUHcxPL6R4EVQju+v1+1zqOs2ndXQKdDDt1+NWYUHNb4Jf26/CN8gx6twV5eT9D3fose/MS5E2sg50FuhuzDuXaOw6ddZ3rOttXIW/imEHbWxubdEhLx9LYwt6VZAOBwKZt2ret6/EYRdfltLX7y77k34TduV64Xdk25FmTaUvXWUO11ZB7yTF7nqakzaTNRAOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBrYVzSwnZDXwnvvzkd1VQ02llXi4xU/4bRL7sCQc27HUefciQHn3o2B59yNIWffhA0VQG3lerw6fRK6163Ne+4AhWUz22Bd7FBMu9PBoa0UfosejoXP5uHfVymcP1yhdzuFR+7oh3lP93LDOS+etj9O66/w0HW5GH2wwoRrgviu6AI8Nv4A9G+rsHbpEBzdTuGxG9Px6+IjURprjpqPAqiOeVBb7EFtLBdVUQcbijq7kLf5Hwh5TdPA++8vQHVVNcrLNmLZyq9wxiXXo/DcG3DUubdhwLl34OhzxqPw7OuxpgzYUA08OSeKg864DZlH34qMkY8hrQ7ypo+egozRU5BJyYW8U5A17DE3ZQ99BDnDJiJ32APIHnwvPMfcDGfgZQgfejaCB50Mf48T4Ok8EsHuxyOv9+koOPhstBh4CSID/grrmJthDb4bxjF3oGDgtfA0PxQ+qy2CVsGm0M4c4nmzjXv27iudZE98T5oAb0jSoQu9JwFUXpuWQOeuWJd2RyAvwziGvWQZ6Caz9cFdPpbOJ1BKgJe8mDnpwJthrw4FGa7q+5Lt5+PE7jiMbay609uLdUVWIO/W4S6PkwzqyCYDcQJ55Q9s1gpbXTOU5/Kt2WTaEsgr2tqaZmSf6EM0IBoQDYgGRAOiAdGAaEA0IBoQDYgGRAOigb1RA9sNed995x1UVVejpLQMa8uBD5atxfFjHkC/c+/DQedNRO/zHsCR54x3oSXK12Pu9PuxYtGN+C12DDYWtUZlNB8VsQ547nYfDmmusOi5bjiyjcKt5yu89EBH9G6jMOXOg7A6Nggn9VO4cIRyYe7SV/riyNYK/Voo9Gut0LulQv82Cl+9fQgGtlZ48a5UlBT3Q0W0ABWLc1Ad87mpNuZDVTQPG4q6xSGvRZ68NFndsAnrHWt0urbhTnC/N38hqqqA0rIKrK+oxYJlP+H4v96LQ86dgD7nTkK/cydi4Nl34JeNQEk1MGX2IvQ7727kDpuAlFFPQo2eipTRFLb5cWSMfgIZo6ciY+QUZIyYgoxhlB5D5rBHkDVsIrKHPYisIRPgKfwXAoV3IDj4VoQG3wZj0G0wjrsV5nG3wjq2Lg0aD99Rt8J7zF0IHncXjAE3wH/AqW7o5qBJgDcikHcP9lbWAS95NCUmfT9pnOAmwS2Cme3atXPX3t0VgJfA3a6EvAx/KVQ1JYJ77M3L3r0EercFcbe1v7EApVz390Njgbzt0alTJ3dMIGiWOFZs65uoA7tkIE4gr/wxnaghXTMNgbysSfqu6WBXz4snr+gsUWeyLZoQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaGBv1MB2Q9536iDvho2lWFMOLPiiHMdedD8OPPdhdD/3MRxw7iT0P/surCoDairW4Y2X78Y30auwLtYdlVEPUEwAtgmeH5+C/s0Upk8wcUQrhbentsLLE1qhT0uFJ25vhd+W9ML9Vyj0aa1w4gCFDcVDcMEAhXEnKRRNPwkPXNsGV5+msLroCAxqr/DcbbQWb2dUR8MgsFsZ9brr8tbE/C5YXl/U3YW8TWlN3kYFvNRRGPIamP/uAhfyrt9Yjt8Iin9RguMu+jd6nTMJB5zzBHqeMxWHnn0PVpcDG2uAR6a/jz5/vhfmWdOgRj4DdfxTSB39BNJGPonMUU8hc/TjyBg5FRkjpiJ92BSkD3sMGS7knYRsAr1DH0T20PuRPfQ+N+UU3o/cwvvhHfoAPIPvg3fwffAMmgDfkAeQe+y/4D/uHoQH34Zw/wuRmt8bfqcVQiEKzexsJYkn7+4+GPAkOEOWRMhLk+H0DuyxSgCT193lcMhkdwU0bAjkTTxG97ikvO7RuzWvXoa6bBnuJlqC4HRPDt2sg0AdTFM+EfAmHrsr6lTu2XD4q7eXrivx5G3YD6N0YMfjjw7fCPJyaiiI06/ZEAi4u4/P8nxb/oNie9uXdVUf5OXvHR0ndb1lXUt9SH2IBkQDogHRgGhANCAaEA2IBkQDogHRgGhANCAa2Ls00CDIq0/AzZs3D1XVNdhQWo2Fn/6MQRdNQO9zHsKBZ09Cj7MfQY+zJ+Pgs+7Cj2VAReVqvPryeHwdvRLrirqiKuZFDa2RWxzGrAkKx+yn8M1bbTB2pMLANgpnHaFw2XCFc45QKI11wZJptrtG733XNUdpcV98PdvBmBEKR7RVOHOAwuLnW2PVws4YvJ/CWw8qlCxshtqYjcrFOagq9qKq2OOGba6IRbC2qCs62QpNKVyzTRN/jTP5Z5sWHNuCbRmwjCDmvzMPlVWVWF9ehYWf/YRhF96L/uc8hJ5nP4ruZz+OHmdPQf8z/+lC8ZIqYNLL83Hg+RPgv+hVqBOmQ42ehrSRTyF9xBPIGEnpcWRSGj4lnsiTt/ARd33enMKHkVM4EdlDHkDWEAK9D4Agr2foA8gdch+8hffDN4TSA/AOmQj/oAkIHnUz8o64DKmRbvDaLeJr8Zo2QqZVtyZvMtgrkHdXD4Q0eb21xJPciZbOIeDC6+4S2NWhFucZojIc5HLe3tWWny/R6lAuEfTq2xyWWbcMetkmgl6GfPTuBHv1cNb8HPXVC+9nW99xUt5wGNtYdaVrXdcTtz95ubZv3971eCev9z09Jb4LbXfs2NENT03jx+8Z63iM4nFIh72U53I+juzvuZ+cu3f9gZqsPVkrpJ369ET7+Lhk15CyvV8n0sbSxqIB0YBoQDQgGhANiAZEA6IB0YBoQDQgGhAN7M0a4LkvsjsEeSurgZJKYOz4x9DvrHvR7YyHcNCZD6Df2ffjkLPvwxFn3IwfS4Gyyl8w67+34pvoWKyPdkcVhVAuzkFFLIQ1i5pjXbQ9NsZaovzDDlgf7YN1RYdhfdHBKCnqidXvtcAr/1Q4rJ3CR7MPw8YlbVEVa4INsR5YW9wXJUsPRNmHXVD5UXuULC5AZbQpqqIR4CMLtXWAlyBvTcyDylgEa5Z0cSFvM6fxIW/YsuCYBmwjiHfffhMVVZXuertjxz+Cw8+8G71Pp/qaiN7nPIy+Zz+Ew8+4FatKgfWVwMSX3kXPv9wP72VvQ11WDFX4NNTIp5E+8glkjXwcWSOecBNB3qzhFKr5UWQPI8j7CHIKJ2ET6C18KO7VW3i/C3pzhtzngl725jWGPgjj6FsR7n8xVLgnfE5LmJbjJkMg724PGvROnCzP8ES35D1H4JIgFoUgJsBL6+/qsIwBF8NItvoxu0OenyvR6lBOh7qJeR3ucp7hLluqKz3P0JeOp/tSXSULb03liWl3qDN5hoYBZO4DVF+6ngTybv8fhjw28TiUCOV00KuDOT6P7N78x5i829Y1peuA89urJanjrdex1I/Uj2hANCAaEA2IBkQDogHRgGhANCAaEA2IBkQDooE9TwM8V0Z2uyHvm2++ifJq4MtfyzDg1Ktw4Gl3o/tp96HfGXfgsTe+xFNzlqPwlDFYtb4M5eU/Y9bzt+GbJeOwIXqAC3kriz2oKPairDiEsmILZcVhlMXyUVbUDBXRFiiPNkdZtA2mXKMwpL3CEzcqrC/q5oLa8iUebIzZKCkKo3yJjZqYg5piCzXFIVBY5pqYF5WLs1Bb7EFVcS5qir2ojfpQEyvAqvc7oLOl0CKsXE/bxhQuQd6IaSAcCuHdt+ahorIW367eiGNOGYO+p96Og069F/1OvwOT3/gGj73+FY45dRx+KanG2krgwRfexgHn3Yfg5QuQcsUyqIsWQo16FqmjHkfOiMeQM+IJZBPoHf4oskY8gsxhk5A1bDKyh05GduEkZBc+jOzCicga+hCyhj6IzEIK23w/sofcBwK9lPyD70Vo4M2w+pyP7LwD4Ak1gWnnu4DXMsMwDAchc2shm8WTtzH105Br6504WZ4nwtnSNQlYEdTVE8HeZPAvEZ4mO2ZXliU+H2/rUE7Pby/kJZDLgJcsA14uo/10TYa9HMaZ1zEmy3kdGu7KOpN7C+RN5nX8R3ry8niUDPYmAl86lse2hoyJcsye98dofW3G7c56SWaTaYiP4/PJ1ncPKd979CJtKW0pGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0cC+oAF9zkufO90uyEshXufOnetC3o+/+RVHnz4OPU++HQecdAemzl2Bb0uAXzYAs157D7+tXYeyjT9g5rTx+GrxNVgX64GKYj8qi72oLM5B1dIcVC4l4BtwPXsro37UFAfdVBELo6SoHTYUdUBpUStUxPLc9XXxkRflsSxUxHO7zWIAACAASURBVLKBYg/wUQAgkBvLRW0s2w0FjQ89qCXAG8sFin2ojdKavM3x3bwe2D+k0NxWCFt2o078ObaNsGkiHDIw/6133DV5P/t6FQadfiV6n3QLep08Ho+/vgzfbAS+KwFefO0DrFofX7P3geffQs/zJsB/ybtQY5ZBXVoMdcF8qOOfQdooCtf8ZNybd/ijyB4+2YW82cMfQfZQTpORPexhZA2d6K7RmzmEQjZTuOYJ8A6+F4HBd8IZdBO8B5wO5fREwGqOsOXAsR3YdhimFU/kzWtYyZNpCeTd1YOG3qGT5Xmymy2HFtbh49agH0NTtls7dnfYx8/JVge8yfIMfQnWciKAy3m2DHfZq5euRe9Llo6nuicPaQK5VLdUzwR8CaSTZY/e3aGO5BkE8u4qyMtjFI9HyQCdQF75Y5y/q4l62VHd0HX4mmJFX6IB0YBoQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA3uyBnjOjCzNl/Hc13ZBXlqblyBvRXUtfiutwemX34K+J92MU6590g3PvKakGuvWVmDdmo1Ys+ZXVJT+iOnPjseKRX/Dr8U9sXFpwIW81cW5qCrOdmEvefa6KUrr6FJ5LiqLfaiImaiIWaiMhVC9NFC3j86hNX1zUB3L3SJVRbNBia5NnryI5gIUHrrIi41F7fDKhBbY31JoHUlxAazdSGvybhaJiYgTxpuvvoGaCuC3khqcfuk/0Pv463HaNVPdNXhpXeN1JeVYu74MazaUu+GaH35hLnr9+R74L50HdfknUJd/CnXFJ0glj96Tp0ONehopw6e6YZpzyHvXTY8gh9boLXwUmYWTkVU4CZlDJiJn6CTkDJ6IwNCH4R88Aeag22Ed+VektjkaGeHO8FktYFh5sEyC3gRuKTHktWBa9afN7ykDQ2PVhd5pE/M86Z1ouYMTMKH+SmCPwWOit+neBP0Y7tZnE0EvQ162DHXZ6uWU18+neqO69fv9yM3Nhc/ng9frdQdWuj/VN0Fesgx5xZu3YYB1d9Ck3lZ6uxPUp21Zk3f7x3x9/NLHrIbAXv3cxhpr5brb36aNUWd6W/O3jPSSqBNdQ3qez098Ni5nm7hftneP9pd2kHYQDYgGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaGBf0QDPU9VnuR4S9+tzYZSn/Q2CvHRB8uIlsPH6G6+jvKIKG8qq8faSz3H4CeNw7jUTsaYMKC3ZiNJ1pShZuwEl69egovRnvPDkeCxffCt+KD4Ga4rboyTW1g3HXBprjY07nNpgY6xtvaks2hZli1uhMtYeG4o64vv3DsNJRyrsF1FoYma4kNcyjEb18HABqWHhzdfeRHU5UFENzC/+EgNP/hv+cv1krKM1i0s2oHTDOmxYvx4by6qwuqQGD/1nOnqdeh2aXPwisi6bj5RLFyL9iqVI/2sx0i5eCHXaLKjCx6FGPIG04VPdlDp0ClIKpyBt6FSkD30MmW7o5onwDrkfxuB7YR1zGwqO/TsyOp8EVdAXafZ+CDpNYVmOlv4X8rKQxO6awTWxA+vbememcn2bJsQJVLFnKUNe3YuX4ePuANV2xjPUB3e5XId1lGeIuzVLx9H59HxcX+TRS567BHgJ7HIi0EuJ2oH6C0NeBuvs1bsz3lWu0bjAWCBve3Ts2NH1VGc9/95vQH1jVyK8S9zWxzX9Gr/3eeT8XfNNS6x3vU31PLd7oh54m/cnWr7Gtu6TuF+2dw89SDtIO4gGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0sK9ogOex6rNcD/r+xLkw3m4w5CXAS2num29iY1k5NlZUoaQKWPR/P+OOCU+7IZyrKqtQWVaNitJKVJSWorLsN7zw9L/w/pzxWDrvTHw6bxA+f+s4rHzrOKx4a9DvSIOx4q0hW0mDsWLucfj41WPx9L2dceIxCs1MhTwjAxEzAMc0YTYy5CXvWMeK4K3X30V5aQ1KSiuxvgJ4/8NvMX7CkyirAioqKlFWVorS0lJsLKvA2pIKPPLUi0jL74zMg05G/qn3oulFz8J73kvIvvQ9F/Sqy4uRelkU6qzXoU55BWrUNKhhT0GNeAZq+H+QMvwpZAx7DL4RDyJ/1D1wjhyDQNdRSMvrgezwfvDazRGw8mFYYQ3wboa9puW4a/OSeFhIYnfN4Kp34MQ8d2CytI8sTYCTJ2rbtm1BYVnJMlzUwdXeCAkZ5tZnEyEvb+uQl6Eu79MBLx1H9UyeuwR2Cegmgl7aRyknJ8c9hjw/qQ14DWSC7QTaGRiTTfa8e2P77EnvpPcV1gJZ8eTd8XFQH7/0sYuhXUMsn6dfS75NO94mu7LuuA25TRPttvSQeDxfj23iu3E528T9sr1n6kjaTdpNNCAaEA2IBkQDogHRgGhANCAaEA2IBkQDooE9VQM8T1Wf5fei/cnmwriM+EKDIS9dlCbeZsycgdmvvorpM2fipVdm4eXpc/HCi6/i+edfxHPPPYdpzzzvpqefegpPTJ2EKZPuRlNHoQWFSrYU2lkK+5kK7UyFttbvSHR+PYmuvZ+t0DKo0NxSKLAUInYOyHvXMa1GX5PXbQDDRDAQwozpr+LV2XMxY8Ys/PflGXjx5TmY9sJsTHv+ZTz3/It4dtpzePqZZ/D0M8/iqaefxf0PTYbHboa0/A5QeT2gmhwG1e8iBE6eiNCfX4Bx0SxExryBJpfNRLNLXkLTC19AywueR+s/P4t25z2D/c75DzqeMxWtR4+HanYUVN6BSDFbw2cXwLCo0zO8pRDNm+Hulnl7UzxvFpPYP37ArK+DJ+vY1D7UoRnsMkzck+Da73nWZLC0vjId3CXm6RkYwvLz0HUI7BLUpUSevDQW0kBKsDc7O9uFuwx56VjOU1vRPXiNXvam5vZJ9ox8X7GN67FbX/0K5N3syUv63dljP49r/IcI2W1BPX0/Hc/X2NnPJtf7Y75z3H66BrZHB7oG+Fq6TWxHfR/lE/fL9h/T7lLPUs+iAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBoQDYgG4hpInK9K3OZ6ovLEOTTaJmc/Yg5du3ZtOOTlm9DFbZOS6cLSsOWAEt+U1naNJwu2FYJj+RCxshExU5BnKuQb8UTgNb+RUoGVgiZmKgrMNESsNNh2Fiwr4AJOuw702i7w3PmdiuopDlJDMIxA3bq2DizTgWXYcEJh2KEwLJPWvo17zVo2Wao3qjMThmkhaOXBazdFltMaaeH2UJEuUJHuUHmcaLsTVKRjPIU7I9XpgjSnKzKczshy9ke20wa5TjP4nAiCtgHDDsK0zLp71Qd4qVwg72Y973yN0LW5P23NJuu8PLnN+yh8MIFC8hJlT1ECiDrA2hdAYrJ3bEiZDnnpeAJ85P1M9UcDJcElHfByWGYqo0TbDHTJcrleRnkKd0/XZ89ehr38jPQcnE+0eltKvvHBr0DeOOSlsSX+PYuPVztzTORxj8cxtjrMrS/Px/I1+Bl35vPJtRrnu6d/+7gdydbX1snK6Xi97aX9G6+tpB9I3YoGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBpoHA0kzm/Vt504h0bRJolfdOrUyV1yb//9999OyGuYLuAlb9i4Ryx5xVoI2/Si7B3BNl5mWwYoWYYJy7Dq0uZj3LVrGwBctzyO1o+tA6TJvFHNMGwzAtsFqRYMy4Dhwk2C07abdlycDHHrb9w4SA0haATce9Ozu/c1bIRDlOL1R7Dchbsa5HVMA44RctcNpjq2CQ5zCGWCrwQI3Xcx694rBJPq16L3ctzkmA4o0T3JezfkAl4/DNvv1oPhXmcbnrzUXknbZdvvn/y8+utrXzy+vk6rl+sdmMr1baozCiFMHZrX3N1XQjMnA52JYHRb2zrI4+vROVROAJbrm9ffZS9ehry6ZbC7LUvXIHBG92PPXsonPis/j9jGB7rJ6ljXhv4jgH0tXPMfAXn18Y77nD7O1Qf59PLEa+yL35M96Z31dtbbMVle1wLlE9uat/ek95dnlb8FRQOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBoQDYgGeF6rPsvzYjRnRoyCtmnemuBu+/ZxJ50OHTpgC8gb984lqBhPiUJzb+ZC3jhMdMP72hEYTjzFPVFN1xOVvFE3e/TGoaBpEog0QTaeJ1ipp80ewP9z74TjGPCy3TLUcBz+GpYDgpkEOSnF7+XAsmk92rxNnrOJ9+JtWn+Y85stA062uhg3Pz/dy3Ac+I04XKb3JuBKnrymQdZExAy6ya2rTZDXhmPaCNN6vi6oJVjNKQ5tqX3iz0MeufH32gx4qW3qALzbjvT+YYQI6pIXrx2Hzlwf8TZK5tEbf8bN99p8zzjMT/b+fIzYzXqpvy7q67xUzh1Yt1xOnZo8TKlDE9xNDM/MwDAZvNrbynQYR+/G755o+b25nLbZk5YtAXLaT21HgyZ76VKeU32gl4/dGvilfbRWL4d25mcg2EvrJ9O7JCZ+brF/LOzVdbUtyEsfVGq/PTklvgP/kUCQl8cyGn843xg2cTzUxz7ObwsC8jUa4/nkmvV/y7a3bvRvWbI25TJud7LStjuv/re3veR4qXvRgGhANCAaEA2IBkQDogHRgGhANCAaEA2IBkQDO18DPN+VzPK8GM2TUYRQ4kGdO3fe5L1LcJcBL81LKwKFLrgzDDf8MnvpJoYzduGsC3kJNtLkL0HUsBtWOOQQNCVYqENiApoEIePep4YZ9zg1yZqhOPCtA7Bx6Miw8X8rjJ4x5KbNHrwhy4nDSzfMcV04ZM3rlcBmyCbISecwsHVg2k1gWAWbnjcuUB2YxgGmC1+NOJjeDDZpm1Mc6uqgNQ6dbYTccMth+A0LhmnAtqleCJxaMF2PZvLU9buJ7qPDaoK8lOJeuQx42ZKHLu+neqJniL97/Hg6j9YdNhB2YS+1UQRUVy7ktSh8tFEHhxlKs7UQB9t17RYiz+s4tN/8/lQ3/P6NO+m/tw8cyTqvXsYdWbdUJwQiCezSLzQITDIsZECog8y9EQ7ye9K76TCOtvnd2Sa+v15OcJfqjxMNlqR/GjgZ6up5KqsP8upwl/OJXr0EeBP3UXvTMxLoZdjMNvHdEt9FthsP/Op1r0Ne+piS9zz/Woo+oImAdE+GvfzsDHmpT/A4TFrlfGParY2BOvzjPFl9jKQ8X6Mxn1Ou/b9/p22tTrhNyHJ76W1IeRpj9TI+Tj93a/eQfdvXJlJfUl+iAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBoQDYgGdp0G9Dmv+vI0H01ztbTubrdu3dzwzAx3iQ/x3LSi0L8E8WitWgKDdtBEQSTfDce82ZMzfgw1um3muaGQ3fDL7rm0bl8Eth1GKEhhmW0E/YbrsRoKmXDCebDCYRiOBStswQiFXJjM1w7ZFoI2gVgCx5QIOm5ZuQSBA7aNgE3QMp7i23H4SxCXICd5v9LatwRN+TiCnJZN16Ww0SYcArxGAYxQHG668Lou/LHlPgeBTaqLEBwjGA817YJNAtO0TcmEZUZgmnGPYAK9Dq17a5gwnDACpoUQwdgw7bfcEK3uOxkGbCMIxwrA58uCYQZcIGxaEZhGGGEnD45tx6/PIZ7dsMu0fm88hc0wwka4LhwzvW98fd+4x6/jPm/8+ak+Im49hGwThh1wPXnjkJfenaE65emdQwg78Xc3QyEYQQOmC3pD7j7LCMGqA/QM6RPbSba31K1eH/V1VC6nCW2CKrr3HE9y03UYShIQJMhLkI9hFFsq00GmgMA4CKT6oUR1Q5ahKlmCdjoo0iEDw14d8DLoZcvgdntsIgCmbfbKpmfitZX5uZO1Y7J93PZkk50jZdsPhvU6pY8qJeqnHTt23PRR3dNgL40fDHTZ8g9H6L3oV2E0LtG4w+OTPpb9EXm+L1seC8nqfVTP68fweWT19+Dybb0D/eBDT9s6XvYn//ZxfZPV20dvN84z5NWP4/OlfpPXr9SL1ItoQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6KB3U8DPKfVUKvPh9FcGS0bSPO15GzEHryJcJcALycVIk9PgqMhE2HDQJ5luoDTNkKwTfbkpIqKhxymtW4dAosELGm/GYZj5cG28mDZeQiaeQhZ+TAMOoauFYAZCsATCsMON0O+349mfh/y67xkCfKSx60LeV0P4S0nV2mi1XQBL0PesOtBvAny2vGQxezhaplxz914qGaCvWEXuBoh8vgx4Q0WwHBawbbpPQwUOBQembxbCdCSd3DYndzNNz0oMHOQ54Rg2+SNS8fEQa/rzerCVYKo8ZDQ/kAIJr2/kw8/rQVM4alDARfaOk78miatwRuidYkNWGYuAiEPso0CeI2myA8E0CTgcc/hNXepg7pr+brgOg55qe6TQd44BCbAHfc+puOobej5gu6avAx56R2oPRnyUp4AOEFeytsurA8FArCCXuQb2W492Ibf9cDWPbFlAKH6aljaVofmjswT3mx5Ie2Gwj8BeVuCPIahDMkJoFIZbROsI7BAbZis/hsCeRn2JtptQd9E0Ev6IKBIgzdDaIa9ydqU30vfpwNJvVzyW2pie+pDr1P6QQD1R/ohBnn4UlsRFNUhL5UxON1dLf/Ci5+P34N+DUaao76QOF41dJzb2cfxc3D/ZMvjYzLLx7Dla+h2W8+pA17Kb+t42b/ld1Cva8pzW5BN1mZUlgh5+RpSt1vWrdSH1IdoQDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6KB3V8DPLe1NctzZjw3Rts0709wlxPB3cT5XIa7PL+rPIFmsMJtYQZsOEE/8mwvHDMbtumFZQTgenC6IYbj4Ybja77GQ/nGww+TJ2k+gkEK3dwEmUYBfHmt4A04aOLYiOQqOJ50hPK6YOXKUgxo2QZdsxRahPxwXC8bCldMYDcOih3biXuz8jq1dZDXDb9sEbTMcxOFIA6a5qb1djnMNAmcPH/j8NhCwDIRMk2EHQqfnAdltEZuQQf4A0E0s4No4vOiSTDogldvyEZWsCm8ARutnAw0DyrkmTlwbAOWTdc1EbKDboqHMLZg2FQW99z1GxHkGk0RsAqQb/lh+zJcj+hgMB62mgB4wGwHny8PzZ1c+H3paH/4n/DlGuD8wUegu1+hwPC5ns10L4K9vJYveSqTl3I8LPNmy57LQdtBoO7d6dniIZ8pZLWJoB1CyPLBtPyuN7Llwmr2zo5DYYK7tpMPXzAfkYKWWLxoPlD9K+648hS09CuEjRxQyG3SA/0AgN9fBpSGDShb68y0jzs0Wa5TglHUUQn6UVhhApPUyamc7fYAq33tWKojrjeCV5SoDgjUcX0zcEjc1gEv5RMh7ra2twfy0rEEfXNzc124RmCRnpPBvt5u9E560vfpQFIvl/zOgbwEdgn0cthmgr1U56Qr+kVV4seVP7K7q6WQHvRs9IcCaU3/0UPieMVj0h9t6Tnonvw8nKf+yn030Sbu475Nlq/D163vfQTyNuy7xvWn1yvl9TpPbI9k7cXHJLbRttqJ7y92+9pL6kvqSzQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0UDjaSBxrqy+bZ4no3lZmnNmr12OIqnPN2/NuUj57A5YsGgFUFUFVG9ATU05rrrqcuQHUlHgT4Md8rlr61qG44ZiplDAlAjwkreu38yHzyyANxBGMNwcry5eirUAKgCgFrjhynMR8mYh0+yJL74ABjVrjQNTFFoHfSBg7K5Ra9F6mBTyOYI45HVA3q/uWrq2Ew/3TGvr2hR6Od9NtM8w42vpuhOydR6VFB45DnnJM5cgbwh+y4LfyEeOPw/DTz4HZQBqqkuB8nXo1b4dCgJBhIIheK0C+Jt2wXe/rMH0qbegtVch7Fcu5KX70brAQRfy0tq2QRAsNQigEkg1bXhCefBFOmD+4k+BqhKcWngEHK8H4RCtd+vAZzZFoGkffPNzNX5ctgAtwulod0ghvl4P/HnI4eicq5AX9MTX0HXfh72n44B3s/cthaeOJ+qM9M4Emglox9c3Jg9g8sLW6sIkj0VK8efevLbuZsgbCIbht1rhmutuxsI3X0Rzn0J+hkJBtkLzEAHoVIQNnwuuZRDYvkGgvo7Mk9pkCSZShyZwRHCSIR/BXQZ1OuCjPJeLjYNvBuFcT1SPBOHIEqBz+4sGIWggpbrnxANrY0PeRAjMnr0Eemkf6YDegTSgtzO/F1u93QXy7jjM1euxvjzVL6/Ry7CXQC/9aIDKCZrS+giJv6zaHSEv/VFAz0rPRlrT+0GysWpXjve6Jy3nqb9yX22I5f6tv9vW3kkg745937ie2W5P29A53D5baxvZt31tI/Ul9SUaEA2IBkQDogHRgGhANCAaEA2IBkQDogHRgGjgj9cAz3OxpTag+S9uCy4nuEvzyYnr7lIZsYGGzC2rdKMD3pn/ES4c3A+tMxUO6HMEVm+oxvnH9UKHLIX8YJa71mw8LHMYkTCF+aU1acMwI80we+FSnH/tzcjw28i18jBj4UIcOvpPUB4b3fscjh/XrcbAkSdCBXthxUpgYLg5uiuFph4vQiGCvLQOaZ4b3th2Qy/Hwy1btuN64IZMWsuXQi6TRy4BTQcU9jgSjrjr+9IatlQxpmPDcGzQuro0aR3JC8OwDfitEDxWBNn2fjj+pHPxy2cL0SWiEPYpWMEcOCE/zEAIgaCDdH8eLrv1AZQDmD5xDNpnKeT5lLsOrwuVCfTaBHYDm9a4ZchLnsXZwQKkmx3x9qKV+PazpXhx4h1okZuO/Jwc5Nth5JgtcP4t/8FqAKuWz0NnRyEzOx0p2QGEcrIQ8eXADJBXseWC1IhlI+yQ16EF24nAtMMwCXq76wUSOCZxGjDNICyCuOR5TaDXNFyvW4K/pkHhRZu4oZZtAtKG3w3LbIbi3svxYw23LGjYyPA3xbRnnsdrD1+LlkohHIpgyYLFmHDFUHTxKzQ3c+LrACdZO5kFui9a7pT1WZ701q1+LEEF6tAEJKkD1weapDwO8hhyJrMEeqkeaRBkT95E2EDtQGVkqR24XRLh7o5ub4+nLx2bCH2zs7Nd72ECiAz9Cczx+9B7b00LOvBNlt/aubJvMyzW644BL3v0EuDl0M1URsdy/+UwzvQR3tqvrBrykd6Zx9DYwl7H1M48BnE/4O1EuzuN6fxs3GeTWe63er/n4/j83emd9tRn4bpky3Ws13uyPB9Hls9lu6fWhTz3H/+PJalzqXPRgGhANCAaEA2IBkQDogHRgGhANCAaEA2IBnaVBnguqz6rz3/xHBhZmrekZ6Y5M5o3TrbuLs3hUmro3LJKMTq7kPfigR3RLkVBZefjsWdexxsP/h1dUhUMTzp8Vh78PhN+bxBB04I/ZMKXYyJoNMOshR/iL9ffjDSPD6m52Zi5+D30HTEMKjsElWNg8osv4q7HX4TyHeRC3iPN5uiiFJxsP3L8jhtCOeD3ww6Q13AmckIhpPsM16PXCJnICjjICubDG8qH12cgGPDD582B3x9EKBCE7ffANoLIMSxkBELw+X1wjABCvlwXzgasIDLNPKhID7z67qc489heaJmq4M9UyMrJRNCb7V4ny1eAbocU4u2Pv8T0WS9gzkMXoFO6QoF3sycvgV5a85a8eOOgN+iu0+uGcbYcZAbykWJ2w7xFX+CZh+8CvluIvk2y0CRDwQk5yDRa4KWFK3DXxEnYsGI2upgKqWkKKdkGvBkeGNkUtpVgdj4itMaxPwjL73PfOStoIStkwx8MgNbLDfotBP0mggEPjFAO/L5sWEEPwoFsWP5cZHsDbsjsiJEHM8cLJ5QL0/DAH7IQCNoI+aje/PD5AwgGAshzz/MhxdcMTzz1PF59YCxaKIXs3AJ8sOhT/PvSgW59NPGnxtdbFsi76VcX1Cnr68xcntipuWMT3GWvTYaTDQV5+zKMY7ir1wGVUd0xaKP6pPqlgTNZ/XMZtRHnGQ4ReOX8jtjfC3nZs5ctQUR6P/buTvb+el3ocDJZXj9W8puh7tbqguuRYS9589LxpDk+j6AvfaCpjH59xaGQdyao3dFr0R8NBJ+pf5DeSdf0rJTncYrsrvrDqKH31Z+V+22iTQYW+V35WP06er6hz7EvH8f1xXXJtr5653I+js8nS/WYuL0v1628u/zjVDQgGhANiAZEA6IB0YBoQDQgGhANiAZEA6IB0cDurwF9PitZnufBdEtzZMSCaH6ZokJubd3d7ZkDVsrohnfmf4KLB7RHW6WgMvIw6T9v4LUH/o525MmZV4CVqypQXQ3UVgOrSkrRcr+uyA+0wepvK1yv140Avv5qGSL5Abzy/hs4eGQhVKYHKsuHR59/Dv+cMg3K2xMrPgcGGi1dyHtE36Px00a456O2Cv+8+mQ0DSrMWrQYdz/xXxieAGyfiWNPuRTzV5bBKOgF294Pq378HqgpRWUN8OjkqYhkK0QCWZiz+COMufUe/PTTD64Xbdt8C/mGH0bIj0yrGfL7n405n5Rj7szZQMmvKK8GHnr0cQTSFYzcXGTZXTB70fe4dOzVmP7UvXj7wfPQJV0hz6Ncb1nuWLSOMKU47OVQx/GwyFkBWvO3K95auAz/GDMK7069FHMfvADNMxWyc0IoPPFcrFhZjMvOPhxVn0/D/qZC214DsfI3oE/zjmiV5kHQbIUvfq1GTQ2AauDph/+FgnAQc6Kf4pJ/3IPvv/8O3y5fgaZ2R+RZVB/fAFiPytpKlJX8hv77O2jiUcgMFODqmx8AqgBUbUDtupXo0rE5PEYrhMId8OvPXwPYQBG1Ub6hFIe2stEsKwUPP/Mm1lCo7ervgervUFrtPgZQvQyVn7+CvEAGgiEKlb37dzRusz/CJuvIepnemTlPHZpAJMEXhne0TQCPoZHY+gEcg06yXI9Ul5SnuqV210EW13uipXbiMga6uxry6p699CwEe+kjQB8A0gq9I2uF31/XDQPJ+qzoqn5dJasbXWucXbbK1wAAIABJREFUp/rnH2RQPZPeKNw2tRW1GbUX/xprez7KjXEsee/Ss9AzsdbZ6uMU5esbL/Xj6jvmjy7Xn4ny/E70nttKfKxu+Xp/9HvsCffjutHra1t1nLifzqXr0PvSD3D09+br62WSl7+zRAOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBoQDYgGdkcN8FxWfVafQ+M8OQ0R3KW5WnIQIoec7fXaTTZ3rJRxAObNX4YLj+6GtikK3Xocgh9+q8EZxx2Ctl6FX1f9iIlTnoQn24/c3BAGnXAW1pUB3Zt0RCTNj/cWxXDRuKuQohTSMhX+u2Aeeo0ohMr2oFvPg/Dzrz/iqMLRUIED8eVK4FinLbqrVDz35MvwN+2EFG8+jh89HFi/BF1aKBx24mn44Kt1aBt2EMlMwaPTXsJZf/snlN0Ln34HDB86DIHsVHj9JhbMX4DbxpyHiCcFc5cuwzeVcF2YI94sNAl4URDywwoFkB5qip6n/gNfAhj71+vhT01Htz5H4cc1ZTht6JEwMxQef/ZV3Dv5RWRkpOO1//wL8x78CzqmK0RcyEuTkgR3LUQMC5E6wEnhkGldYXdtYctCHPJ2w9sLP8Xtlw/CmEIHWPcBOrQMQvmaYc7C5Rh7+Zk4t7A9aj9/Bq1DCnkHDsana4CDm3RCjxw/fvtxFe6fPBU+rwXLG0TEkwYz5MWs2DJ8VQW03a8dQp4QgnYPfPsj8OTkiQhmKWTl5mL0n0ahdt2X6NauCTr3LcQXvwAHtOmI/DQFO0vB61HIbdITy38BHnv4Plgegs8B/GnUScC673Bg26ZQnmaYOO1VvDDpJthKITXHwtvvRXHXZUPRlurDnw7DqlsvuW4d5N2xk/3Rz1RfZ+Zy7shkaXKbwRwBO+qYDI4YMBE04vy+bLleEi3VCZWRVyLXIeUp5DXVOUNahgx6/Sfm6Xgu2xbk5evxcfVZuv/2pESoy+dSOYFDug/BQ9qmZyW4yIBRh42slfrgLpfzcWIbBntJawzWdUv1Sd671F6kDWobsqwLai/q78k+vnoZAVh9e2fn6UcP9ByU6BnpuUj3PE7qeS5LtHQMp8R9f/Q2vwvfl5+L+zH3021ZPp4tX4evuy9aqlt+bz3PdcN1RXZb9cv79XPoOtx+uuV7ipV/uIkGRAOiAdGAaEA0IBoQDYgGRAOiAdGAaEA0IBoQDezuGuC5svqsPh9GeZr/JahLgJdAL8NdZhu/Zz5YqVA3vD5/BVD2C1D9LVDxG4aNGIq0rEwMKzwKPy1/C60tBX9WClLSfEgNtMPCRcvxz4vOQMs0hbeXfIBTx14NlZYJleXBS8Uf4zsAJQAqyzfi1MIj4EvPgPJ1x1dfAYcbzdBeKfgyPLj6H3ejhDxWyWW1/GO0bZ4CZbbA/31XinMKD0Mnr8Kar+bBaWGh0wl/xUfVgHt4TTWd5P73/IN3uSD2tYVFOGPsDVDpOfBl5sLyBhAJmbANAxmhJjjolOvx7tdAQSgPIZUKlWpiyrPTMW3yeJw/8iD88PkHKHC8SEtRePk/j2DO5HFonqJgehRMWoPYiq+Tm0eQ16C1gW0Ylr0J8hqWhUzy5A10xfwPPsW/L/t/9t4EXrKiPhs+d+7W+3JOd999mZUZZmBgZmAAZRMRRBGDirgmvkZNVFSIG6i4m3xfXrNpYtDE5DVGXxONMRqXT1FAQFFEBQUEFBQ3BFlmGBhgZp4vz+n7zNSUp+/tvnvf+x9+xb+qTp2q//LU6b71dNU5A6s6Alx21aV49//5DLY96wJ846d7UIhGY588eut/YrwUYGD7U3H9vcDhfRtw/pNOwc6bLsWqcoBcd4BSroRcbwq5coTPf+9GvOANb0HQ3YOgI4tjnnshrvzJHoyWKxjqDJDtzSNV6sfXrrsWL3nDm9ARbsTtdwGPPAw8+2lnoNgboCffhaOf9zp8/U5gIIzQ3xWgmAqRyffhim9djT96wwUI0hH++eMfw5cuOR/DJO7TQ7j8yh/i7159Bg4LAgzmgmVB8jaanJPV+xOXZbc9F7T13l0RdCSPSLSJfGsklzsZl0Ty0od8CIrcJZElco3kghuPJLJB1xkj5dlOfUjq3lak7m0kReJKknRLSiJ2/Wu8j+/rFY7oA5KPwglxpLzJqYncJHy5fuN1+piJPqd/9YMCxtjHBusYI0kS9SSD9eE9kw/tpHv1jgZdY5lfFmgD8T3dL0Xu88vNT7e/ub5POrrxSIqPe515zX9K9SE51zovxv5Fvko3+UJ+8v3XqKz2vl/ZL8dQ/ybtDzfDgGHAMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhoHFhAGthzWSWvfSdenOMq9xvYx1XEvWe3dJ8nL91l8jnukGoCAoHxmTvH/41JMwFgSo9gTIZFbERy0/9Zxn41c/vhorywGy3QGCziyCwhpcedX1+OPTt2NlT4CvXPddPPfCdyLozCBI5fHv3/4+tj7jXARd3chnelDrCpDmMdDpw+J38p5UXYlz1h+CPTt34n0f+icEPQVs2bYZO++5BqvGOxEEObzxnX+LT3zovfi7Nz8Ht132fmS6Amw65zX4ws+BsDqMbBAg09uJbHcHikGAqCvAl79Fkvct8THRmXQBYSFCrVxFNawgVRrCyhNeiC9ffx+GyxXkqU8XyczP4JP/8Gf48ZUfBfbdCey7D3vIIvNc6kd/hB0//E9USGpOLJLXoir6wxr6ohrCChNJ3gjVKATfyxvv5C1uxtVX/xB/8/InYCQIcMozXoiv/Q+pesnnrsZf/PN/IAjKOOesp+PhWz6LlTHJeyZuuBfYXF2P153xJDxw01cwWg5im3OpHKJsDpkcd/J+F79/4YUIelMIukrY9pw34ao7geFSGO+4TXVn0Zmr4MvfvBonP/0ZCIIagmAQPZk+fPMbVwF778HpZ52Obee+Dl/7yT70h1VEQYB0Zw7dqRBf+8bleMLTnxzH/WMf/2dcfsnLY/170kO46hu34O/OezI2BQFGCh2oVPtQWeLv5NXkbEVqYruS93MxmwQkiSIScSKKmGedSyYpv9RJOp9Uc/3QyHbV02/6hQvvo28VJz1AfeLGjYmf572q430khdzUiMCYrN69PykvclfSJ3GnKvO+dDodf1jwmAeR3fzQUHJ9KlyZTCZ8k/Do1ok85dylD/kBTdwIA4yx8q5UfHmdhD3vY79HHnlk/GGufmcq+cWAXwYojzjiiJiEpn4cX18wZio1xyhn2tdc3S8d3fnsxmOqvO6TVH+Sc6X3Yu5XtssnlFP5Udd1j/qQXMz2mm72B6VhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4YBw4DWsRpJrXtJan1Y7bmGrN27eveuezwz13Fnuias+4OgeAS+9vWb8fLTtsY7bHl0cS6fQ0+WpOUgbv/1/fi7f/wIunt60ZVK4/Rzn48bbr0dq0oFlLp68elv34rnXvTn6OrNore3C5+55moc88yzEaRS6E2lEWazSPWU0VnchttvBx5fXYtXPfFJ+PktNyNfiRD0FnDx29+CPQ/fgHWrOhAEXVi35Qn49s034sYfXomXnH4o+jsCBLlDceO9wOtfdx5yKwL0rAjwkUvej63Dw4g6e/GV71yPP7jwYgTpLDK5PIrlCGFYjY9YzpeGsCLagi9efTv++R/+tk4aH30C7n7gYbzgjOPQT6K4J0BPV1dMoH70o/+CSz/8BhzSFaAvK5KXhG4fqtEAKtFAvJuVu3erlTKqlRLCahnp0gCC/CZcc9UPcMl5p8TvOE4XRnHbPcCeXb/EIaNpBEEaTzvrbOy+5bNYWwwwdPTv4abfAkeXVmLzii784pc/x4tf91qs6M1iMKzgA++4EJV0gC9+5yq88KLXoSubQldvGd2143Dbb4B//uD74+OaO1NpPOOZz8Kvf3AV1oS9OPTIk/C8V7wt3vXLuFz3zc/jgvNfjqB4GH70K+DDH7wk3t3b3ZvDs595Lu76wZVYE3YiSOXw8X/7KC6/5JXYEATIZWq48qof4C/POwuHBAFqqQBRuHgX+WfrAazJ2IrUhHYlCUiSkpzQIuJYnozg5QNAhOZSJeVcAk1511bXfvqKxCUJNpG7lNzJqoen63OfYHCvJeUZY9XzXvbpJvXXinTvT8qL/JOcitT1r3NnqN7/SvKQ+tNnxBl95WJM/qV0fWz5A4Sv6yP5TrijP/mBSX8RK4yZYpqECWGJ0r2ue3g/f/jBWPF4Dn0Yz0SyL35ZoOQzh2Pr2TWdZ6LulWQfylNOp8/5uEe6SVc3Fm7ejctkefce9akx5sOe+R7DtVF5+WAyP+ma2kqqD1/Ot102nv1hZhgwDBgGDAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAw0AoG/PUst6y1L0leY55rZNyQxXVertXyvbuU7s5d5WeV5O0oHoLLv/49vOS0bVjXFSBMB8iVyvE7b3vz/Uj1rcedDwCP7asflXz3w7swvn49UkE3Ul0lnPeuv8NdAG6+6WasGu3HF79xOU74vTPRkUkjmy8iLFeQyfUj378Nt932KI4aXI91vVlce+XXsXvPY3hoD3DZ1y/DfXd/F+tWp9HRnULQHeJv/u2TuOGnN2N1KYh3qgZdg1i/9TQ8+hBH+xWw51686bWvQa0rhVJXFpd953q89KK3YEU2hyxJmrAS77atVmsoh4NYkR5DvrIGv/zlj7Fn7314CMD5r78IYXeAWg+PLe5CJl9GkIrwsX/7BP7rgxdhdW+AwVJ3TGryeOaI76KNBhBVBidIXh43GKJSKSOshsiW+9CVX4Nrrv4u/vK8p2I8CNDVGeLid7wPP/z6vyMkWd2TxllnPws7bvkqVhUDrDzqqfjxPcBxg+swGATYdPSJuGM3sBvA7vt34Lg1g+hLBfjqtVfiJRe+Ful8BplUCb2ZdShGh+JXv/wJgPvxKIBdu3Zi+3AWlSBATzrEhz/55bj+sT278Y2vfw7ZFI+pHkSuuB73/OZXwN6dePixfdj1wA4cN17CQEeAnkweH/3Yv+ALH7oIq7sDdK/I4K0X/xmw+07suOkr8Tt5K2GIanyE9eJd7G9lwia1dSdts3lNakkSRySKREy6RBIJo1ZIN/feVu5brETeVPb4JK8IXpJYw/xhRxQdRLTJ59ORegjzXj6IScaJtPCl+vfr/bIIvUZS5K6kT+JOVtY9lGxHkleEL48E1k5xkb2SSwE3s41nF2fCpPzlkryMu3xNv5OkdXEjXFC6zwu33s8TMxz/0EMP/R2iVx/y7oe+8klkMK/xC4TG5zPN1SPpGTdZnXsv85O1XczXfDsUA3++Niqrvfyq/hh/Jtnu5lXXjlL2Ubq2N/KP6t22bh/Mt6MfTGf7o88wYBgwDBgGDAOGAcOAYcAwYBgwDBgGDAOGAcPA8saAv8bllt21MOV5nevL3NRDcpe7dt1372ptVzJpjXe6dUG6WEE6m0OU7kAlE6AU5pCPysiXy8gUiujK5tGVziGdziGTzqE3k0UqnUU+lUOml9dK6EwXkE71Ip3qRle6F52ZFAoxYVJGsVhCoRghXRhAKlNFrjOLQmcKqa4edPek0dmTRWdPD3LZAL09AXpzEYJUGX/7yf+LP//H96GzM0CqM0BvthCnQqYTpUyAfKYbuUwa+VQGmd4MutIZdGYySOUKyBdDlOMjlftQrlRRjCpI58tI5/LIZLuRynShO5tBdyaLbC6NYiGNUjmHQrmIVDFEKpdHKRvERzXXygVUwgrKPJozInHcVyd7J2Ql4tHF9aOb8+UI6XwF2VweUTqI/ZnNlpDJhgizXQizncjkCshk8vHu21xPB4JUiCBVRa47jUJ3D3pSeXSmi0ilC8ilsgh7exCme5FKpZDKZFHMFRAVKyjk+5DLVZDJsr47tqUnnUa+twP53s6JfkroSWeQSvUgm+5GNp1GOh3GKZvJIJvtjWPPfCnThVKmO9Ytk82inO1AmF2BbKaAXKYQ21PLBKiW0ojKRVRC7mDmAu7SXMR1J+1keU1iST78SbaQKBJZJHKNhI6ST1apntK/xrIIKMmkNu1UJzskfd3lDxLkJHblT+5SdElYNy/CQVIxcWVSLBkz1bOt7pdMqtO1RrIRuduo3iVuk/KTkb5J1/i+WPrQJ3zpb9/Xy60sbLlzjX5RWT6jpB8ZM9fHjA/j7uLKLwtPkn5b9unGmTHghz6/BOiDntL/YNc11usdDtR7qi+d0qPZdmrvy6nun6/rrl7+mEmEq9vej0WjOezWu/ewL44pojdpPF+nxV6Wf1w7Xfsb5d32zKufxW6v6be8/0iz+Fv8DQOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwYBhoFQNa99J6GMtc32U/XNvlui537XJDD9d5RfD667ssJ637JrVrti7IF7PI5dPI57PIF0jwFlGolFGMiiiWC8gW0jERWsjmUcgUUczVUz5bQD6bRz6bQz6bRS6XQTaXiY96zk8cZ1kulVAqkTQpI18qxTt7RRane7PIpPNIpfMxcZzLZ9CbyaAr349Djz4Bt9/zMwyt60NHKkA6n471yOfTKOYyKOWyKOTyyOcLMaGa5U62LMfPolAMUQqr+0neUrWKUjVCsZxHoZBFOseURzqfQyqfR7pYQi6csDcsIkc9iyVkCnnkCiQzq3HiTl4ez8xU39VbQ0zwRv0x6RtGVZTCCHnel6dP60nkAPUtkIDOFZCL/ZZHLltAKptHb5xySNOPmRzyGfqV/i2gmCmglCmgkM6BMQgLZUTFEGEpRLlURqFIvxbqNtEupWwemYz8kol3+3HHH31WT/RfPeXyeWTyeWRZpo75YuwD+oH5WPd8BqVCNiZ4jeSN9i9ma3JT8vhgEi4iJH2S1yXTGpGbbhs3r/aS7rWlkBfBJlu4i5LkLh9k9CN3qJIYI9mgBymlX3avJeXdeCnPB7Hy6tMlNZLq3OtJ+UZkbqN6l/BLymuuNis5DvWmX0lWirhcqvgRblqV9Aexph33+kEBd4uTvOMOafrS9TvjMxXuhCdJH4u838WCvhAQ642+CPDDX18Q+IWBP4Dgjx7YV6tfStRe+kn6evpltaNUHwshJ9NjKtKV98qupLk7WZ3uYx9TjbMQfml1TPlRdlHSfskkX7htdb8vW9XD2tsfVoYBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4sRA1z3ol6u5JoZ13PJWZC/EMGr3bsieLVhZ7ZJXZ/8DcphAUxhuYSwXEY5KqNUmZBhMb5GUq9aLKNajBAVo5hgjMoVhOUIpTBEMSyjHJZRCssoUEZ1EqwSRoh4bHI0sRM2JDlZihMJylIpRKlEApa7hrNI8x20//eLePB/jip+42tfhHIqQCYdxGRzOSyBiTpG5RAR37lb5mJtiHLIfnidBC933JLYrU2kCsrVehDK5Qi5cg3Zcg3cdVso19uX4x26dR2LYQSmeCdyyPf69seJu3Xru1ZDRPERzQzugYVu2khbo3IJFe50LRfjfFgOEadY9xKiCf3DUjkmaUmA0/5i7Is6eRtOkLhhMUKlWIl9TruoZzxGWEUY1hBGtZjQLtKHcQoP2BT7uYhSuU7Wl+NYluJYFeUvXwfGv0R9KyiFTBP+nfATy/FiLt/JyyObF3ihfy4nvb9o7Zc1NnHHySxil8QLk4gjkkhJxJPINsmkNm6d2km619oxLzskZYPINj6oSLhxVzSJLPrbJReYZ0xcmXTdj1tSWQ9p9Rc/SzgXnMS6VpJL4E0nn0T0unUu6ThZXvfQr8QosUnfyt/LSRJrtFeYo9S8FRHO6/yxBn3KuOkobPqRdfKnjxFhR5hJwpmuJUntUGf/vJdfCET26ssAvxywjteIWerHvvj80fOoVSk9fZ18rPvXeV+rY81me+mdpEcz5Kvud+3ybU4qu+3Vhy9n08657ku6J9nq1rl2M6/7JOdaT+vf/sgzDBgGDAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwYBhYCAxw/YvrYVwr43osy9SD68lcqz3iiCMO2sGrtVxf+sTsbJaDKCqBiaRdRBI2qhO8YaWeD+NrZfRHVdRKFVTKJDJJ8pE4rcSEbqkSIYzqiXmSqjS0GvGddbV456uuV6MKakwT77TTDtlSNYxJ3o5wHJ35GirpAMO5AGGxByUSpDFxfIDkrO+wZZlEct2xdHCdUK6ivJ/k5Q7cuh4kRgthP/JhP4ohd96SgOa7dqkjj1yuoRxxFzAJTh75TOK3D2HYh0pUnTieuBy/g7f+Ll6+j5dpgtSuVFEl+cmjjONEn2rXJxdG634m+U0/MNXtp451HapRDbWoFvu3GrK/PkRhLT4quhy/A7CGalSviyr9KJXrRK9IWRKxMeEck8l1YrwUFsE4ksAvVurHTpMcrxPQBGmdrCdJTuL8ADFP/9TjWvdLte6vsALZsBATaz7G1OK1K/3FbZa5449kJCc1JyZJI5dEErHkk2nNtHHvabW9e+9izMsekeH0m4g2EpHUmWSNiAb62k1uXJh3rynvt2lUJp50jfdyTPUhKT2aldMhdt17RCY2kpMRu+417kRNp9PxBxDt1E5zYUJxoGSdv6Na7ZaClK3CHCUxR7zxGsldxZ9+VzySYuBjxMeg8NSq5Pi8h9jns4VfBvgOBybmtcOYsaQO6r/VZ6LuE7596ePcvy492U+rY89Ge+mfNP5ckrx+3OWXyfSZDXtnuw/pK/39ePtltVvouM+2H6w/++PQMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGGgEQa0hsbrXCum1Pq61mzdI5p9Ytctzyap6/cV1Hejugu1ESKSlhNJu1VjwjasIooTA0/ilCTl7ybW10gKk6ycIHnr7UioctdRH6oV9hEhrFVR6a8hrJaQLxeRiQaQLdUQ5lLoK6ZQKuYOHJEck4v145NJhlInkaUHZBWV6ABpS/KUqb4Tl/V98Xt1Se4yHaiv31MnfHmNPqiTsLKVdh3wF32mdPBE4Ltq6++rdevVljrXE/UsV/pQqvahyF251Dus+43+o42V+Djo/pioJiFM0rcv7EelxOskoElM10lgvjO4viuZu3zrBG05IlkdIqSv4+OmJ94pTIJ5Ysc1pchc5hXX+tHUdRvqR1TXY173g2tb++Vd26fKa4FbC98sk2zR7kiSvMyTCBNZthRIsZnYwIedn5L6o7/oOxJt9CPv4a5G+byRTIqZ2iZd8+uSMMw27ENxnk8pQrGRTCIaVeeSus3k+Z5Z7eolySkcK15JGGadUlIcF0udbKB0dRLOZKt+VCBbhR3GXDGQf30pXPiYmqwcP1Od5y3buhj075U+kv51tz+3n2by6kt9S8quZqTuUV/NjLtY2khn2UDZjM2N2rj9MK/+XbnQtru6uDpK92ZsUx8LbYuN337ftyxmFjPDgGHAMGAYMAwYBgwDhgHDgGHAMGAYMAwYBuYbA9wI4iZ/fK11NSO5dkbOgvwFiVvu4NURzSJyfeJ1PsuBb1zjMgk+NzUGJglXkbwiTdkv89W+UVSqA6gUUuiPMogqJZSrISo1EpEVZKMBpPMV9JVK6C/lUeVO2Wp9ty1JUe10JYFcH2NiZ7B2CO8nR13Stp4XoTu1nEsys+5D7XIuV+rHSpdr/QhrfahW+1AjCR7v9CXJO4BKdahOTJMgj4bQXxlErVjEQMRdxXxP8IH3BdfzdZK3TNIq4s5dEbz0Qz8iEsceyevG3Sfu3WtLJT/V5E1aCCf5o6OZSUqSMGoH4sslu+Yr75Jtymts+kwkGx+MfOCRbOTRzEmkg+pcOVX8prqehGPewzEaER7zWS+isZF0icdmiF23DfuknfyhAnEswpd4ZqxEfLpSOFedYrmYpQhs6kjbRPDSZibawg96xlXYUozpI9fHbhzUfiqMudeT8ObWuW2FQ+lE6V937201r/5lB/uX3c1K3ePq1qoeC9V+Nuz3/UQ/KPmxYnmhbNW4rk7S05W+PSqrje5XfyYbf/8135hvDAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwYBgwDCw8BlyCl3k/JlrvmkryPhK8XFsmj0GCl7t4tYOXJC85DvEc80nuaqwWSN7mA5NM8vL9tlVki0Px7tSxcoCRQoD+Sjo+/rharaAY9aM7WoVsZQwjpSyGsx2olLIOyUvysw+1ODUieSeOid6/i7hVgpe7fn836D4IZlrWzmMSqtxlG++25U4vHoOt45C5q7c8gGp5EGFlAMXKEHKVERTDGlb1FTCQCxCVSJSH8c5h9qkdt1FEYoBHb0cocodvtQoSymGFO3lJAusYaR01fXB8RfTO1M7FeP9UE5fXuchNKf05kUmAcbKSFGNyCS9eW8yE10LoJnLX9Y3IXRJwIuHoR/qbpJr8LpKBUkSDK5uJ4WRtFFdXsj3HcMdeqLxLKiblXQLSz7uEbqM83zXLRPtFgjIejA8/sBgTSeaVFgJHMx2TumvOcv7SLtrNeCu+wpbKS4Xk9eeAb6fsnYlUn/5YbtmdZ/ORd8d289J1JvbyXndO+n1pDFdKh7m2XeP40tWFeV/nRmXdp/7mWn/r/+DvYeYP84dhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4aB6WFgNkhero1p09+GDRv2E7x6tR4JXhKtS5Tk1ZHDB45rjkncUhXh4CZ885vfxXte/QxsKAXoK3TEu3Vr1Qpy5T5sPukZ+Nk9j+E5Z5yCNeVOVKICSmTaq9zFKgK2ftxx8k7e+rtu60TtgWOap96967adL5K3frQ0iddMGMWpUI4QlsqISnlUSgVU+R7kkMc1D6JQHUF3ZQxnP+d5+NWNV+KI4W6Ush0TJO8EuV0lqR2hEvEl0MWYPI6PcSbJq1ThzujpTY6l8FDRgrUrtZgtyWu0leQuJzIJMO7+84kwEkgioVwyU3XLWYrk5Y5R+Yn+40NPOynpX/qcJIN8T9JS+UbSjd1+EoRSAAAgAElEQVR08kk4Zj/SpRHpMV/1LomUlPeJXbfciNidrJ67qEl+MjaMkYtzkb2LHcsioimlM6V27tIm2uliTfEWzhTfhSZ5p8J0En6T6tSPb5/snC2p/n2p8ZN0m8s6jSspvWbLXndOJvXJ8VivcaXHXNrMvjWOpMb3ZZLOqvPbqi/Kudbf+l++38ss9hZ7w4BhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAZmEwOzRfLy1Yc6kpm7d4888kiQ8OWas3bSLrScg528deJSxyrH75Xlu2SrFWRLfegJN+Pqq3+Av3rNmdjYG2Cw2BEvHPZVQ+RKEQ47/um487d78bwzT8NQtgOZYgG5Pu5kJfEaolwtxe/v5ftwa/uPaD74yGbuaF3sJG8M2IjE9SjylVX40vW34i4AjwDA3sfwyM5fY/OhI6hWChM7ffuQr44giFbizHPOwQO3XoojqwEquQDZfB5Rle8arqFS5UJvEZUohyjMoVrhkc4Rav21+J3HhUqIYrV+fPNsTprF1pe7MD1Z3l/QZlmL2f39/fEOQE5Sl0ASibTYSa+F1I8+Esmr3aEiEKmX73eSJn6dW54shknXpoNH9sMxRXYspHRJpKnyLsHbbJ6EL9uK+E2n0/HuRJG9LsnLeJGoVzwX648ZNEdJ7ApztEM/KOAHu2LqYsvN6zplI7+r/XQw1uw9PqabvU/tdL90de2a67zGlJQulNJvtqU7hpuXDrNtcyNs+ONofFen2fCD359f1riSvl5+We18qX5nO17Wn/3RZhgwDBgGDAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwMJcYmA2SlwQvOQ2SvHoPLyXXm1mvJJJXZDCl6uZDzgHJy/fI1t+dS4K3nrgTt4J0aRCd4dG48urb8DevOQubugOMlrsQlUsYjNLxrt3O8kp0FlaiL1NAfyaDy75xLV510cVIp7oRFntRruRQqhTio4jbn+TtRyVciUy0Bp+69ia86G1/hq58GeV8Fn3lbkSFAKVyGuVaBYVKDZnaCLr61uBpz3omdt3yBWyNAkTpAJl8CcXaIIq1flT6IvT3l1At92KwlketGiGq8r2/1ZjcLdaKKFWL8e5fTSIu5PL4Zh3hzPp2X9yV/o2kv5jNRW/W0XY+AETkiuwSaSQiiXIhSdTFPrb8RP/xQcYHH8k37oqWr90YJNW51xvFsVG9sN2KZF8c0ydAFqLciERqpn4qolfELqWObZakrfSDjjcWYap4LhbcTUY0U2fijol6c7e48EU8uLjy826sG/la97SCrVbb+rhu9n7/Punq2jWfeY0vvZq1o9V26l9S40rOts0uNhr1zTa6Jj2kH2WrNia1d/tjXuNIavzJpNr6fbnlpLGtzv4QMwwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGHAMGAYWKwYmA2SlxufSORy5+7GjRtx2GGHxXmRu5IukSui162b6/wsk7zcbcvdqfXE9+fWE48QDtFbHEBQPhZfu+pO/NkrzsGqIEB/NkBfMYXxQoBaNsCK/ACC7BoUgj4MZkdw+dU34II3vSXesdqfD+IdqmW+bzYM23Inr97FG+82DmsIi0PoLQzj09/+AZ77hjejI5NDLpNGuZBCpZxDuVREb76AnqiKnr4RBIVBnHXWmXjoli9gM0ng7gDpfBW9lQF0RxVky1mUCp0YKgeo5QPkCwX0FqvoKfehNywjW+pCsdSJEvue2LUqgrcu+WCq1t8NHO+Ibs8HlbtA7ee1qO1KLoKL3NUvMUgSkTBiWmwk12Ih25L0kK/oP/qShCF3iNK/Ikdc3zeT92M4VXk6Hy7sk7pMRojM1zX5aTpyJiRvJpOBdvXSh4wlP6xEmro/dkiK/XzXCWsio4U5fnByJ74f06mw5sa3ke/Vx3Qw1uw9Pr4b3ee3k26Srj0LkZcelK6ujeyZbr36dsdz87Ntu4uNRn2zTdI1+WK6tvK+RvYmjdeoTv5RX5Ju/27dTPS1e9vze5TFzeJmGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4YBw0C7YmA2SF6uOZPfIMHL9/ByF6926YrgpZxrEneq/ueI5O1HJaqnatQf7+atVCP0FgcRlB+Hr139S/z9xS8H7rwC2P0AgEfxjj85F7VigEMffwZ+cg/wuENOwe6f7sajAB4E8JObvo2NYyWUCr0oh6X4CGKXMPXz9eOaSTpPN83NBJae3IVcDWsoFwbQmx/EZ669Eee+9iIEqTTSvZ0oZQJExQzShQEU+9fgrnvvxl4AO/g/ICZ5NxYC9HSl0F0YwZ2/vgt7sAcP79uLD/z9X+HXN38Nhwz0oCMdItW3Hr+678H4+mP7HsT/+ae/xkCRR2WvQLXMY53DiZ28FYQxsUtSnom+mxs/zHW/WpxOklrcdiXJKRJGJIncXYwikeabvFrs4zXyi+r5AKQvaQfJNvqapAcld/O6vm8mnxTHyer8h7hfTsIf+6MujUiR+ax3SaRW862QvNrVq528lKxLpVLxLl/6g74SyevOj4XEqIszzVeR0TxGgzozXtRfcW0GZ26MG/ld/SRhaL7r/Dkg3Vw7mPdt8a/PVVn6ULq6zraf1Lc7npufbftcfzbqu1Eb6UWdp+uHRvY20sWvd3VQX9KFz0rlTbbn9x+Lm8XNMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhoHljoGp+ACtiTWS9B8JXia+i5eJO3pJuIronYp8na/rQZIRMwMAj2vmTl6RvNzNW4138vYUBhCUjsFXr74DuP/7OH40QHpFgGee+1w8/NAdGF5bQ237WfjRb4HtfZuwOsjg69dcj//1ujeiq7sDpWwXojCLcpiP3887Mz0XbqKT6I2Pmi7XUM71oSc3hP/+/h34JclbvpL3kftx/WX/Hh/FnBt7HG69G3jX+S/FaCpAkCrhI5/49/i45nXFAEFpLW65h9f/CIPdAXqLfbjiW9/Gjlu/gPW1ACv6DsN1vwKeffbTUV4RoFQs47pvXI6/uuBpODQTYLTUgb4oRCWOUa2+i5c7eSdI3miRkrxJuHXrtIgt6V5z8ySESFxxwnHCkjxyd+6yLDJrsb+TVHrOpRS55o8hv9GX8iMfpCQc6W/FoZF0Y9JMfi7mvvT0CZHFWHYJJD8/FcnrXndJXv/4Zu7qVeIYPJ5Cv14iscqYs45YEC7cOeIeqazrU0kXV25fbr2b148JqA/bExfUVRgi3pRvRrr4bBR39TkXGGy2T9+WRnoLG41sma966efq7draqH6qNrpP/UvOl13NjqM4UPIe6indJV1bp8rzHtlK2aweGtsdf6qx7PrCfVc035vvDQOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwYBgwDMwOBrQG10i6a23M0+/kjHhEM3fyMpHc5UYjyfkicacaZw5IXu4CqRO9Oqq5TvJGqJO823HZVbfhva96CsaDAOmuDnTlQlx97Zfxsgtfg9Jx5+CH9wAn9B2CQ4MuXHHNd/HC11+EoKcXuVwa5TCHUphHGNUd3Y4gr1ZI8kaolasI89zJO4zPXHsrXvim9yBIZVDMrMAaHrdcSOH4cy/Gt28HNhUDrO0M0JEK8aSnn4Odt34Rq4oBjjv7fHzrduDQQoA1nQGCniqe+uzfx85bPoOV+QBHnfVK/Jxbfx97ENj9S+Cx+k7gz/7leTi8N8BoIaiTvGGlfkRzWN9dJLDTv9XK9HcczVV8pF8j6U9KlakP7+F7Okk4iZCkJEEpEkrElUsoWX50P+EtP4lko//kS5JtJHhJaBjJW2qJgGmWrHFJIz/vkrhT5V2SV7t5fbLXredYjC9JVcabH2raSUssNJojwstU0r2f47hl3ctxOKZ+UEAdNK9d/2nOSzZ6Vrj1akvp9uXmeY33tPps0zit3pfUXn1JX1e/xZqXrpKywZdJ9rLOb8ey+pJcrLZLL1dP5SlpSyO7/XrXbvU7ldRYST70+7fy7PzhYH40PxoGDAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwYBhYPBhIWhdz67R+JsnYuSSve1RzEunKNWqmpGtzXTcHJG89cCR264kkYQXcEdrL9+0Wt+LKq27B+175ZKwLAvQyFWu4+juX4SVvvAD5487BDb8Fjq+txoYgwBXfvg7Pf/2FCFIpZLIZ5MtFFKISQu4+XaS7TKfWK0K1UkY1rKCcH0C6MIIvfO9WvPCNb43fyVvKZTBUTKOYr+L457wT1/0UODTfgZEgQLCigqc88w/wwK1fwsoSSd4LYpJ3XS7AeEeAoKuGpzzrf2HnrZ+NieLtT38lrvkpsCbfGZPqhd4u9AQdWNkVYHVXgMFCBhUSu2EYp2pYRi3i+46jiVTPV6MI3IE8tW3z08adgEl5TUZJtiHhRfKRZBEJIpJFTCxLuqTScs6TYPNJNvnDJdtcoo31xAdJQpGLJAUVg8lkUgwnq5sLHHI86jgVYbIYrvvErluW71uRLtmrvCt5fDPL3NlLyXlEfIjcpyTx2mgeCTNJkrhSvTBGyf5VT8m+RSjzA5NlHv3NuAlnwsxkWOM1tfOle1+jOOv+VjGosVq9T+11fyMdXQw00n2x1bu2TOVX2u+3X2z2TKWP9Fc7lSVlo2LtSrbRdd0/lXT7dfty88KXyfn57mJ+Nj8bBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGHAMGAYmH8MuOthSXmto0kyRtyxy528JHh1VHMjwnZBSV4qy4XC2QYWSUEShSIGSQqk8n1YUTgcV111M26/7ONY3REgsyLAhW++GA/t+g0G16xEdMzZuPk+4LiBVVgTdOCya7+P57/+Tejo7UY+14tiWEaxEsXvkJ1tneevvzrJS3I1LPbF7939wrU/xB+8/s3ozGSR6lqBSqYH3V05BOWtuPU3wDvOeymqQYBMfgRXXnM97rv1K1hZ5nHNG/Cje4C3vurFqHUE6MoO4bKrrsOu2z6HdbyeH8PNdwEXn/cSDHYEKPQE+Pj/+Sccs3oV+jpXoDpxtGk9XiH6ojL6otKEVFlE7/xPvkYxSZqIbp0moyQJEL4bViSRpEgkn9BkWcklnpZLfirb+dByiT3GSf6XzylFQrh1SXndO5VshIfZqOfYrs7SfTFKl9Dz862Qu2rrErpuXtcp6Ru9s5dljjs0NLSf6NUPJzSn3LmiuiTJdqp37yEGWU8yVwQvx2AiucvPFGFJMWJZcdS1JNkIZ25b9elLjdEq5jRmq/e57V3bXL18DLjX2iU/lV9le7vYk6Sn8MVrjfJJ97l1vM8tJ+XVN6VwR+liyfKL5/uMxcJiYRgwDBgGDAOGAcOAYcAwYBgwDBgGDAOGAcOAYWBuMeCukSXl3fU05hkPErsieafapbugJC8X1Ul+0TAZ4hvZKsB4vK92glYqUbyLl33kClUUa5tw+ZU34qv//Rng0f9hJ7ELjzx4DzaPVbEiCLDq6NNx293AlsExDKzownkX/znY6pZbv4eNq6uIohLK8ftjeSz03AZ+bvsn0VtBWAqRK1Xwtetuwr17gb0A9j2yA9h1F37/nKcj6K3hrHNeBux+FNj7KB59ZA/+4e/fj7tv/grGSeJ2pLFmy8l4cOdOvs0XOx4BPnjJ+/Dwbf+F9fkAHR2d2HTUqXho18P1I5sfewBvfv156MunUS3kEJXru6L5juC+KEJfVERfVHCI3jrh6xL2c+uX5mIqjAqzrnSxTCKIRzOL1HUliSORSiSTlJ9MJpFRk7Vvt2sid11JG2Q3/cdfq5BoYz39S5LBjYfrf8WFbZSnVPtm5HzhTXonkSbtVOcTfkllkbS6JjKXBK/yrnSJ36Q88UJskPgXKSvMuPhpdp6xP97Hvog19kvJd2gzTknxEL4UR5Vd6eItCVe6znsajaE2Sfc3W6c+KBvdoza8rrxskW6KH8vKU+r6YpXS1ddP/pC9blm2+7FRX5J+n357//piKM+Wjq6PmJcfG2HM6pv7vmF+Mj8ZBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGHAMGAYaG8MaJ2skUxaV+MOXpK8JHsXNcnLhXMuzpPo1e6omQLWJXl5TDMTCc1SqYrO3gq6UjWk0wXkMinksp0oZwIM9AQod3Yi6CqiM1NFX28aUXcvgmwfgnQZuUyAai5AVC4iqtT2E8cz1XVh749ikjVfKiNIl9BVrCJXLCAqpjBQ7ERfoRvZXAE9mTLSqRwyvWkUsmnkegKEXQGK3XwHbwZBdwkdXSl0dvaiozuHc59xJnbd8nlsKATIsk13Dj35EnpzaeSzHSjnV6BczKJULu4/9vpgkpdEL3f0HkjtRvJyshLPJItEOrnSJaBIJjH5xKbql6OUL2g7fcXnhI4iIOHGHZw6KpdkoB6OIhb8h6JfVvtm5HzNUepCPRcD6TMTHUR2TSYZM/e6CF2X5E0icxvVcYcv40SsEB96+bw+X5LmnjsHlWc7/RCD97IvfoDyOj+jhCPXP4qZrimObjkJZ0m4Ujv16Y7DPOvVJun+ZuvUB2Wje9SG15WXTb5eLLvxTLq+mOuoO/WTP2SvW56u7Y1iuZj90Ypu8ouk6zvlG2HM6tv7jxOLn8XPMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDQHMY0DpZI6m1NUm2E8mrtW7xI5Q+6bugO3lF3lBR5rmQPhvA0Dtco0oVTDy2OSxHyBerSGdKKOaKKOXyyGezKGaziNIZlNMZZLNFZDJ5lHp6EGUySGfzSOULKOSzKOeziKIyokrjhfHZ0H0++4jKZRTLIXoKIVZkC8jl8ygVsijm0ijkM8jwPZiFIjK5AnK5PNKpXhTzKZRznUilu5GqjOOLV3wfh4yvRq6jC6XiCH5956/wnx98OwY6A+TTnUjlisiWCkjlepDLdqFcTKMUFlEiwVDlsac19FUrqEV6Hy+PZ3YTd2ZX9h+9PZ/+aTSWJqMmnSTreQ9JIe0sJK5JHolIcqVL4IrYpHTrl2NePvBJN/rCJdvod5Ezigml4tFIum2nyrsY4M5hJrdutvLSuxWCZTG2dcm+RvlGJK/IXspGhG5SPUleJo6n+UfskKRl4hycLLnELtvpHuJteHg47pO+pl5JmOI11ft4agUfupd9JcWW9WrTSr9+W/VB6V9TWW1YVt7Vy81TVzfWSbov5jrqTv3kD9nrlxvZMJntvp8a9dGO9bTNTfKbMGSyuS/55ifzk2HAMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhoGljQGtmzWS7hob82y3ceNGbN68ef+GpkVL8pLM4QI7mWaRYVxYny6oRcDUJogYkbzsLwojlEMetVlGVCyjmM2hmC+hVAwRFUNUimWEpRJK+RzCfA4DJHPLRZRLTCHK5QhRFIJHQNfTEgBe7JMQmVKIdLGEQrGIsFxGJptFngv3YRmFcglFLuaGIcokM0rchZdDMaqiszCIw486GY/t3AXsQZw+/KGPoLQiQC0VxIRwtlhEvlxAoZxDGHLXZQmlSogyYxSTvH2oVSPUKiR5Dxy1XSfq6+9VJkmv9ytPFxszva/RBGQ9F/kpeZwrMa1fUxDbLqmrfBJxy/uUkq4vpzr5if7jc4G2c+euiJCkh54bH/+6X3bbTpV3cWMkb2l/DBQLX7qEV6P8bJO81IHkbzqdjiXjzWPSiSMRtsSRyFx95rhlksJsw8T7miF3hSuOr7yPJxc/U+V1L/vy/aox1Gaqvia7rj4oG7VTG15X3tXLzVM3N9ZJui/mOupO/eQP2euXG9kwme2+nxr10W71tEvJ91cjTFn9EvjO2NavKTH/2xw0DBgGDAOGAcOAYcAwYBgwDBgGDAOGAcPAQmHAXT9Kyi+UXvM1bpLNbp3W2SR5rW1IXhFXXGDXIrsW5bnILlLFXYCl4+WAqYIQNljE5vHN9d29JG3rO31FIvK45/0EYyKh23hhfCp9Ftt1+pE+KlPyHb0xiV1/2LE+rqO/D1rYixCGZZTC+vt8s/kyCtlcnOo7oXMoZntQzvXEO58r1SpCvhu5VkG1Wk/7j9Gu1uox3k/uckcv00QMDhr3wENY8af0fSqi36+fTtkdp1Ge/fL4YBJDJIhI8DJPbPtSeDdZP6La9wP9JeJNZBvb6OHmy0Yxmap+OliY63uoM+1rN7JnOvq6pJjy7i5eP5+0e3eyOvfzgj+8cHFGjLnzknl+9rCNfmTh2+TjbrKyj71WcaP7fSxoTF1vtd+Zthc+fb18X7Vj2Sd5k3xF+9vRtmZ0Fraaacs2ak8pPEom+c7qDnx3MV+YLwwDhgHDgGHAMGAYMAwYBgwDhgHDgGHAMGAYWIoY0NqQpGxUWdJdV1pOa0uy35W+L9y1ObYjyct38iYd1+zu6uV1tzzf+cBffCfBQ5KXibt7ufhOspe7smgYDSVA5AwXLMqbnJ0HpYhYSd+viocIGR71rKSdemwTk67xrt36UbcuCSsSXzt1femPqbLiT6k6Sbd/1U0l3f6myuvhQyxyLJJEwiwlMSzSyMW35ZOJXfqFPiSpq7Pk6UfW0b8+qaCH31Rxmuz6VHhYiOvUl7a5D/Olmhex20jqmdJITkbw6tmjeUq/Ekcke/lZwuTPRX3ONMKbjyVhMEn6bVvFku73saCxdL3VfmfanuNKh6WGSyN567typ4qr4k8pHFLOFFt2/+x8ZzM/mh8NA4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGFgoDLhrRe56kV/vrz/51xdK/7ke17eTZXetjXnXN7y+adOmmOTdsGHDft4kicBdVCSvyB4uuJMo08uCSf6wzN2ScjaN5II8y3IIpa6bnJ0HWiOCV/6V7/cDMuSxzr+7AMxYuUn3T1dyXCW/D+HCr3fLuncyKZuS2nAMkkUkIzmxRPISuyQnfRLJyr9L8NJPmuuc35zn8h9jRb/rwaZYuDIpLs3WuVhYLHnqTvtk81KWjchd1Tcid5PqXcJXBK/fjv3St/KxpPDk4kZ1rnSv+/e67Zj327aKL93PvpIwoDFa7Xem7V27k/Rq57rlTvIydj6OG5WFz2Y+Z2eKObt/dr7HmR/Nj4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGDAMzDUGtGbkS3+NyV9D9K/r/rnWd777l12u9G13fcN2bUfy8phMnwjTjisSQNqSzDouLtJId5GRZTcwftm9ZvnpP9ToczfRl/S1m5L8697jxi2pbTN1k43XTP/u/cr7k0plXaeUbsSq+x5pkpM+fq38u8SufCKCl35j0s5d7tiX3yWTCAg3Jq3kFb/FKGkHbXYf5ks1LzK3kfRJ2lbKjfoUkUefMi98yedu2c8rNn59UtnHY6tY0/3sOyn+rGebVvudaXvXB0l6tXOdsDGZX3mtnW2cSndhmXZOloSj2f5MV78mp//9zHxnvjMMGAYMA4YBw4BhwDBgGDAMGAYMA4YBw4BhYKEwkLSepPWmRuuc7nqV21Z9LZQtczGubHKla7PvI7ZrO5KX5I/ehygiiNIng0j4so5tRQhpsVHOdx3FvOpNLp+HnI8Jxt7HBcucPEn1uqaJxvv7+/vjHeXaEk+SV3h0MWv5xuSuP6dF7srPzcpGMUuqb5d5L8y5H27LNT8ZUctrk5G+utf1nea5iy/3up9nO7dO9/v4cvtz8367pHIjXKqtr4P0kS6N7p+reuolG6XLUpFG8pZivAt7U2Eo6fN1qnvs+vL5/mWxtlgbBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGFgeWNgsnVErd1KuuuLWnvk/UsNQ1p3c6XslXR9wXZtSfI2IsdI6ipp5x8JNuZ5hDMXHN3Au45SfqmBwuyZ/EGZtAgtLDQj6V+14yQTOaljhXm0sI4XboRbqz9A9rrzV0db03/0Ef0rX0vqwdZIql0zsl3mCm2hve7DfLnm9SHfSDZD8vJe+a8RjlSvdpKql2yEM113pd+2VfzpfvYpfVzJerZptd+ZtueYstPVZynkhZXJ/MprS8HWJBtc+yfzwUwxZPdP/r3F/GP+MQwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGGg3TDAtSQ/zXQNUeuf6rfdfJKkr2xxpfwk6a7bsd2SInl9soyEkY54JdmrXb0ie+kAOtJ1mJ9PcrTVLe2HqI8Bt6yJJMlFb+KB2CKxS2KSmBNZSenj0sp1Utf3Ef1GH8qPJHeZp3/54JLPm5FuzJrNt8u8pj30gfswX655zr+ZJN9vU2FrqvbNYi2pXav4Ux+NsMB6tmm135m255jyo++vdi+7JGcjP9H+drezkf6u/QuBrUY+t/ql/Z3M4mvxNQwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDQPthgGtHbtJ6oS8brUM1W+/2547XrphxbVDetZF51zds0zYkrwih6RBkvJeEEQk4kkbc1csjnBloOcrNu3XtCgbTe/oPPsWfUn5069xJxaOZ+f5nYmvDhg0HEbxJWJ0JjpP6Wwp1JHeVOD85V+mnwcHBeH7m8/lE0siNg/LuA451bgwVy3aXtIm2ubYu1/xMCF4RVvSd8ONK+dmt8/3sXmPefU40k58JFtU/x/X1kk1sM5MxpnMvx5RfkvRq5zphZjK/8lo72ziZ7s3YPx3M2D3T/75ivjPfGQYMA4YBw4BhwDBgGDAMGAYMA4YBw4BhwDCwGDHANTI3ab1QcrI1qFauqT9Jd8zF6JepdHL1V162Sbr+YZu2IXmbJbP0vl5K3iNSjZIEkkgkkb3a1UvHyGmSdLjyklMFwa4vrofqVMcxK16Kr6TqJVmvSURJcpeY4g5x/XhARCXrm8Xrcm3nzkuSujpWnfNW5C4JBdfnzHOeqs7Nq86Xiud0peK/mKSw6D7Ml2ueGJluSsLPVDhpFV9ziRvpSp2S4s96tplLHZL6Fj4b6ZWka7vUNUNy0v52sadVPZuxPwkTVre4vhdZPCwehgHDgGHAMGAYMAwYBgwDhgHDgGHAMGAYMAzMJQ4GaMQAACAASURBVAbcdUt/PbXV9ahW2rtjSQdfzqXds9G3ry/Lrl3+miuvLzmS1yXNXLLNzZOUW7duXUwskewVqUSHKBBJznSvq53Jxf1AnIrkbRRnt54x5sOEC9wkd4kxEpNM+uEACV4XYy4Ol3Pe/9EFfUE/0V/0H+eiCF7uiJbf3QeX6ijdeubda63m23Xuyg+tfMAt1bbTJXhFVrWKp1bbzyXGhHfqlBRfzY+51CGpb+GzkV5JurZLnXBDG5NsZx2vtYs9rerZjP2N/GL1i/u7ksXH4mMYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDwGxhwF0f1Hpqq+tQs9FeY2uddLI1vdmyfab9UEc/uXYw7/qGbZcNySuizSWYSC6R7CXZxPq+vr7YgQyE70iVZxoku3/hH5aKZbOSMePx3sQHseL+QIC4YdLOcZGawttyk779KlPKVy7BS5Kc5C7JeD2g3IeWHyP3GvP+9VbK7ToXaaN85T7Ql2PeSN7GWND8mG+cC59LEaPNkJy0f6nOxWbsn2+82XgL/53KYmAxMAwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGHAxYDWBxd6jYzrk0rUicnVczHmpacrZYOk61e2W9Ik72QEGwknHa9L4o6ELyXv4W5NOZGOU55yMQbedGrtIerGc6o8JwwJSOKC+GAibnxsuWQm8/715VKWH2SvW9Z8I7GrHbyaa4VCYf8DVw8rf+5NFavlMj9pJ33jPsyXa95I3sZY0PyZ788H4XMpYrQZkpP2L9X52Iz98403G6+17z/mL/OXYcAwYBgwDBgGDAOGAcOAYcAwYBgwDBgGDANzjQGtDy70GhnXJ5WoE9Nc2z7T/qWnK2WDpOtXtlu2JC9JKHdnoYgn7ezl7kLu3lRQXKdOlld7k4vrYdkoZpwY7jWWtZDN+Ls/BiBJSZwQOy6RKyIzSYrsXOoyyXbVaa7Rd5pnQ0NDMRGiB9N0pRu7pPxSnIe0k/5yH+aWL7XsD/owCTOT1fk49dvOJ940diMsyL751IljUS/5aanhUp8NtLGRX3ltqdkte5qxv5FfrH5xfSeyeFg8DAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwYBiYKwxofVBrSgstF2qddDr+pe/8pLVWSdefbLusSV6RTy6Rp92a3GlIQopEH3dyCpi+g/3ydAJn98zdA9WPj1/WBKd0F7BJ8gsL2r2rHwUsdcJ2JvYlEbvcJa+d8iTKOacYBz2UWpF+/PzycphL8p37MLe8kbw+BvRsm+85IXxyfF+ndi+7nxGN/Er7293ORvo3Y38jv1j93H3PMd+abw0DhgHDgGHAMGAYMAwYBgwDhgHDgGHAMGAYWEwY0PpgozWm+a5fqHXS6cSEvvOTz5+4/mPbZU/yuoSWT/aS6OXOXhJTfB+rwOA72S1PJ3B2z9w9hN3YJOXdmDIOPD6YmCApKaKf8RfBSxLTxcxyz9Mvrg/kH+16FlHONoODg/uJXT6I/IdTM+WkGLp1szWX+MMOptnqbzb7ob30lfswt/z8kLwu1pLysxnnqfrS+I2wwHq2maqf2b7OMTWXlxoumyE5af9Ss1v2NGP/bOPJ+pu770fmW/OtYcAwYBgwDBgGDAOGAcOAYcAwYBgwDBgGDANzgQGtD2pNaaHlQq2TTse39J2ftNYq6fqTYxjJOzp6EEklMk9Hy5KkIuHHMq/5DvbLrQRusZJIrdiw0G2n8r9/3S9zQtAGEpAkKBlnxVu7UoUJSpKXLqm53PP0CX3g+oh5+pFzh3mRu/S1+yBSvhXpx88vzxYejeRtnTR1P1zaIU/c+fiZaXm28NdMP9KVdiT5W/Y109dstqFemtNJerVzXTMkJ+1vZxsn070Z+2cTS9aX/aFpGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4YBw4BhoP0woPXBydaZ5vPaQq2TTge7WvN1pdZaJV3fcQyRvOvXr4+5LW5cTUq8nlQ/X3XBfJNpIq1IVpHYI2GlnZ18n6gfINfpbt5v55YXI8nLHcvUUbpxUZf2SG+RX5KqbyRdXzSTb6YftaGuzfTptnEnNOtZZnwZW+0+Zex5XLNIXpfEnG8cLubxfP9wrvCBoKOZqbsePNOVbuyS8sLCcpHygetP96G+1POu3cxPZa/a++1UL39SNoMht32z9zTT73TbUIdGfmD9dPudyX3SqZFefizaqdwMyUn728mmVnRtxv6ZYMfubb8/2ixmFjPDgGHAMGAYMAwYBgwDhgHDgGHAMGAYMAwYBnwMaH2wlXWnuWzLdUrq5Ou5GMvU00/U302ur2jDYYcdFhO9RvJ6O3pFrrlkL4leEllMJLh4tK+AIJD4AdD1JCmi1JVJ7eazTnZQJ477lKc8BR/4wAdw11134b777sOuXbsOSjt37kRScts99NBDmCq57d3+7r333njsSy65BE972tMOmoyanL7PJytzAhQKhdg2kvUkd924kuhVYux9HKi83KTmgWs35wDrNSfkR9breHP34TOd/GSxFFbnc34s9Fjyh+tL96G+1POu3cxPZa/fXveoXv5sVyxRb9nk+4L1C4FX6dRIL1/Pdio3Q3LS/nayqRVdm7F/ITBnY9ofk4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAYWDwa0PtjKutNctuU6JXVqB4xQTz9Rfze5viKPZyRvA3KXZBbJKpFaJLNE/pEY1K5eElwktOhY3/l+mSBSHfMuuav8fAON+vhj0uYzzzwT73rXu7B7927s3bsXM/23b98+TJUmG4P3Pvroo7FOT33qU+O4UHeBW3n5t5EkwUtynoSkkkhKEZmuVPyXu5RP5AeVOSfkR16bLXLXjWujWLLex+5SL8sX8g+l+1Bf6nnX7mZs99u7ZflSsh2xQ90b+YH1C2GTdGqkVztjtBmSk/a3s42T6d6M/QuBORtz8fwRZ7GwWBgGDAOGAcOAYcAwYBgwDBgGDAOGAcOAYcAwoPXBydaZ5vMa1ympUztgk3r6ifq7yfWdS/LqlNVGxy8vu+OaSViR5FViWcQWJcktOosEIQlf7gqlc/0ANCoTUCJ2XTnfQKN+HFOSupxwwgm48cYbsWfPnv3E7GQE7Hxeo07UjTpSV4Gb+muyNvI56/W+XcaPsaMUcWny4PdTu/4Q9jkfmNeuXfqQZeJfsZhNOVkseW2+58tCj5fkD9ff7gN+KeZdW5mfyka/ve+/hY7nTMenPY38wPqZ9j+d+6VTI72mitlivt4MyUn7F7MNM9GtGfungxm7x/74MwwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGHAMLB0MKD1wZmsQ83mvVynpE7tgDHq6Sfq7ybXN+TItJPXSN5JdvS6ZJebF9kropcEIneJ1mq1/cSpAK0FbzdAPqgYEL9ursvUyx33xBNPjI9jdolb7cBlnfLNSrefZvJ+v43u4fHOJ598cuwv2kC/cgGakvbIz/IfyUkRvCJ3RVy6MbX8wUSvfEQyXIkELx8YlHx3MX3NB4v7oGk2rzg1koqfyYM/5Bv5y/e7+8BfDnnffrfs+2wpYIo20cak2LJ+IWyUTo30StK1XeqaITlpf7vY06qezdi/EJizMQ/+fDB/mD8MA4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGFhIDGh9sNW1p7lqz3VK6rSQPml2bOrpJ+rvJtdPRvJOg9h1SUCXANORtSQQ2UZkrwLCIDCQKlM2G9i5bCe9OAbfv3vTTTfFvKpPtrLMf359IxJ2Luqlg/q+4YYb8OQnP/kgUpd+FeBJtpPcZUzcnackKxk7N5bMs61ft9zL9BP9RR+6ieSu8Cx/T0e68yEpP5fYXyp9J/lN88B94C+HvI9B1zfCq+qWQvwnizN9sRA2SieOv9Qw1wzJSfuXmt2ypxn7FwJzNqb94WoYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDgGFg8WBA64NaU1poyXVK6tQOGKGefvLXvF1/LimSd2RsFHGaR6JORKGIMBG9lCISCRyBWoveCoofLJbnG2gak2B4z3vec9D7d11CV8TqXEtSyXU6efKR+J5gHt387ne/O/aZP1F5fDBjwKO0ueuUUvFa7sRts/YL1yR36T8m5vkDBhfTwvN0ZNIccOvmez60+3jyXdJzx334L9W8i0H6gn7gs82Nq+sjt74d87SFNifFk/ULYZN0aqRXkq7tUtcMyUn728WeVvVsxv6FwJyNuXj+iLNYWCwMA4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGND6YKtrT3PVnuuU1KkdsEk9/UT93eT6aUmQvGOj3JE5hpGxehrmzs2xEawfHsCWgSpOrJVwaiWPJznptEoep1VycXpSJQcmlk+PE68pFXBapYAnVEs4tq+CwwcHsDomkccwNjqKlaPDWDPch01DIbYPZXH8UA8eP9iF44e6cOJoD04eTePE/l6cVOnBCbkVOD4V4PhUB05IrcCJvUydB6XHp3uwNZfG+mIeQyEX6OcPeNwRu2PHjphZ9XfMTk631q+KnPUJWpb3Atgzkfzrft/qx69vVKbO1F0g50TlLlMezUxyl0Qvd+jaLt2Dj2FOInpdElwEL3+woGOuBwcH4wdMoVDYT2LI79OV/gPLL7fDg3ex6OiSmcrTn4qN+/BfqnnZSrsZF/rBT4slXrOhh+KbFE/6YjbGaLUP6cTxk/Rq57pmSE7a3842TqZ7M/a3ihdrb3/4GQYMA4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGFhaGND64GTrTPN5jeuU1KkdcEY9/aQ1b0nXd1z7but38pLgHY/TOEZHx2Oid3h0GIcM9+PxfSX82QlbcMdLzsbOP3gydv7+6XjwhadjF9MLTsOuFzwJD77gVOx44RPj9NDzn4jdzz8VO845GQ+c8wTcf84pcfrFU4/DN086Em8freBpYR6H9vdjbOVqjI+OYv3oALYO5nHBiWtx8zufgZ3/+yzc96en4rfvORm/fvcJuPc9p+LBt56Bn71wG75z7CC+fVgV127qw/cPH8ZNR6zCj7ceglu3rMUd2zfili2H4OubVuG9fUU8O9uNDYUsqjHJOz/g++AHPxjv4tXu3Uakql8vEleShC7/UT4GYDeAXQAeALATwEMT9fvJ3v2ZiRtbFNT3wx/+cExkkcglIakdp9pNLfJSRK+RvvWjqeUH+YV+cpN8yes8+tp9eCivB0sj6T+Q/HI7PFjbWUf5W/Fh3EjUJCXFtB2l7JO9koydCO92jmMj3WknbXdjJl9QNrpvLuulk6+Xq2O75pshOWl/u9o3ld7N2D+X2LK+l9YffBZPi6dhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAaWJga0PjjVWtN8Xec6JXVqB7xRTz+5673+mmvbk7zcjUiSl2Tv8MgYhkZHMTQ6jM2DFfzpKUfhhuedhruOGwe29R9IW/qALTWAcmsNOGoibasBW1k3AGwdBLYOAVuH47T76NW4/ugNePtAiBP6alg5NIQ1I8M4criMPz5mGHd94I/w4FuOAd66CXj7BuAtq4C3rQXethmPndOP21YHuGskwK6xAHvWpIF1BWBDFTi0D9hQAzaPAJtHsefwMfxw4yj+374CjsqnUSrk53w3LwFDIPz6179umeQlP7sPeyf+Ax4F8DCA+wH8CsCPAXz3EeDyHcCXdwBffwS4AcAdAO6aIH1JBLf6T0S0dhzfc8898THCJHf17l2RlUk7Vq3ud3f10l8kxZl4JDP9yDo+aCd7iCRdd9v7DyS/3A4P1nbWUf52YzJfH57zMY5rl2x1ZTvHrhndaSt94Pra9Ukzfcx2G+nk6+Xq2K75ZkhO2t+u9k2ldzP2zzaerL+l+ceexdXiahgwDBgGDAOGAcOAYcAwYBgwDBgGDAOGgaWLAa0PTrXWNF/XuU5JndoBc9TTT+56r7/m2tYk7/538I4NY3hsZILgHcXQ2AiO6S/imt8/A3ecuBaPHTUMHDngpEHgSKUB4Ig+4Mj+ietDwBFMw8ARI/V0ONuOYt/Wdfj21o04u5DGYbUIhw5U8YTRDH7x/hfjofecBLx1M/DmtcDb1wNvWVsnfF+9ETevDHDXaIDd4wGwqhNY3QusywMbysBhNWBjtT7mlhFg2yo8tm0NPrd6ACfkUqiGIaqVuZ3sAjeJUp88nZp83Yd9eAR1ere+a/cXAK54EHj/7fvw8m/ei2dc+huc8dX7cPJX7sNJX7oHZ331XrzhRuBj9wPfmyCE92/m3VffAazdwI3G9/W89957Y2KS5CQTiUojcn+XyKVPSNzKNyLCRezqvbskePv6+sBjmf0HSKtl/4Hkl9vhwdrOOvr+ZtmP4Xx9mM7mOLIhyT63rp1j14zuiqfrW/mGspk+ZrsNx3X1WUp5kZy0kb73fZcUj+Vkv+8PK8/t9zfzr/nXMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhoHFiIHFtkbWaC1vsfqO/nMT9XeTu97Y9iRvTO6OD2FonETvWJxI8j6ulsVPX3Ym7j1uGNg2QdxuHqyTqfulU795AIjrSe4OA5uZuLuWBPGE3LwKv9p+GN64bgzbq0UcNxzir553Ah573zOBN20ALloNXLQSuHAlcNE64I2bgHOH8dPRAA8MdWLvWAewtgc4JAscWgQOC4HNJHj7gCMmSOatI8CWcVy5diB+V+98kLwC8t133x1zqiJQGxGsB9dzH+8j2It98THMvwbwsdsfxeu/fT+edfVOnHjFwzj2amDj5cDqS/dh3deAQ/6/PTj8sw/gSZ//Dd72gz24EQBHfngfsG8f8Ng+vr93D/bt21uvOHjAxNIDDzwQk7s+iSky0+SB45ldklc7dylJ7JLk9Y9mdh8eSXn3YTOdvPBncn6+kChGbizdD4XFnnf1li2SyxFDtJ0+cePm+mghfOLr4+rW7nkjeYsx1hhjYm8h8GVjzs9nhfnZ/GwYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhgHDwHQxkLRmuZDrgu20lqW1ble6673+2mtbk7wk7kjyDowPYWCC5B0ZG8Pg+AiO7cvihy96Eu45YewAyRvv0NVO3SFgCwlcpiEnDQJbeG3iOnfXbhmt7+jdshr3nrgVb1gzilNGIjyhtgK3vO8VePDNxwBvXA28YayemH/TRuDVG3DD6gC/HA6wa7gHWNUDrO0FDskAG3LApiJwRHTg6Ogt/RNHRI/islURTk53ocajlOP38s7tA4VA2LWLb85t7R934HLXLe/80T7gH37yEJ5/+T0481vAcVftwbargCO/Dhx+ObD+UmDNl4HVXwHGPrcPaz/zMLb9xz149XeAy/bUiV4SvDHJu69O8opwdmWShtRdu1KN0E3ewSu/aJcz/aWdzyR3h4aG9i/e+w+NycruwyYpP90PArtvbue8Gys3vgv5YTvZ2K6OzEv/5Y4T+oH+cH3n+mq+/KN4JOnj6tbueZK8TC4GXduXs/3zhTUbZ24/G8y/5l/DgGHAMGAYMAwYBgwDhgHDgGHAMGAYMAwYBmaKgcW2Rqa1vJnaNR/3+2uN8qW75uuusbY9ycsjmwfHh2NilwQv08DoMLb2F/CxM7bgF0/bAhwzDsRk7QjAnbJK23g88ghw9Ers2b4a+7avwr7tK7F3+xhwNMnhsQMkMPPb1+K2Yw7FCys5nNyfwV8+bTN++xfPw943bAb+ZAx47QjwOsqVwJ8cih3PGcc31gS4dV0Ov1gb4t6NIR7aVAY2lYDDSsARIbCtWn8vMN8RzHcBHzWCR7eO4hMDaRzbE6BSLs4LyUtwTpfk5Tt1fwPgIz/bjRdffRdOu2Yfjr0G2Pb1PTjhG3tx+pUP45nXPIbfu+oRnHrpQ9j637ux9jOPYPSzezH26Udw+Cd34FXfRryj90EA03lHL3UniWlEb2OCV74hsbt27VqsX78e69ati4+2rtVqMWnmPigmyyc9aBrVzceDz8Zo/YsH4yW/ubFT3N0PioXKSxdXPz8vG5arpD/oJzdG8hvlQvhFOrl6uPq1Y961hXnh0Pev6mmj7mlHe32dZYuk7PTtt3Lrz2LzmfnMMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhoGlhgGtD/prTAtV1npeO/hZ626u1JqcpOvHtid5SeyJ3B0dHcfI6BgGR4exfijCueuquPK5p2DX49fWyVwSuluHYiIVR5PcHcHeY1fijpMOw/VP3IobTtmCH5xyBG54wmH48YmbsONxhwHbD4nb4eghPHDEED41WsBTy704dTiF29/1bOy+6HHAaw8Fzh+fIHrHgQtWA3+yBZ/dnMKnNlXwxS0juHTrOK44aiVu2DqKnTye+XDu4K0AR5HcZeoHtg0D28fxw419eEcxwLbcClQrRVQq4Zwt1BMAAvZ0SN49PGYZwLd2AK+89l488epdOOFaYPtVwBnffAyv/THwr/cDX9oBXPoA8Om7gbdc9whO/tSdWPnv9yH8t4dR/fgj2PKJ+/FPvwT4Pl/2B24R1ot6JZO28E7UGcnbmNwV+c3jmN1EspdHM7sPBuWnku4DZqq88GVycX5ZcZ8BjBHjyfi7HxTzndf4lNTHsNMYO43ipTk8374TnvRckB6S842lmY5HvdmH9Jddk+HSbaP7JGeqz3zfPx375xtzNl7j54P5xnxjGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4YBw8BCYIDrY4tpPYy6TLaetxA+ajSmu7aovHwp6a4RuiQvN/Zxgx839yUlbfxLujYfdYGOmz1YjmF0lGk8TiR5eYTzqtF+HDFUwr8+53TcdfIGkKTFUUPAtkFgOwleEqojuCoM8OZUgD8srMBLCh14aSGI0xtLnfjPDeO48/gjgOPGsffYEdxy7Fq8vdiBMweyeP0p67HrPU+Pj2TG+YcA568Gzl9ZJ3hfuxE/eeEheE0hwItL3fjDUideUuzAHxU78M50gHu3c2dxH3B0X53k3c4dvEzD2PP4Q/DpDQN4cSWF7UMRhgb5EDqY5FVgG4GglXotyPOe1kneffGu2/v2Av9163146Vd/iqdf9SBOvXovzrhyN95+B3AFgNsB3AtgB4B7APwQwPt+Ahz7qV9g1cfuwdqP3I+jPvxLvO7S+/HjiaOf95O8InunIHp3PXhgJ+/B+Jic/Gy3tiRlp9KZO3b9NqzjkcycqJTDw8PxQ80lL9y8HhaNpDDYjGwFj9Z2/r90uM8A+l8xVezdD4z5ymts6WK4aIwL+oj+8mMjH86374QnxU76SR9fz8Velt6Urk3MT+VbtXf7WOz2uvq5ek/H/qn8Y9cbz2vzjfnGMGAYMAwYBgwDhgHDgGHAMGAYMAwYBgwDhoF2xoC7JuiuN81n3l3b0jpdO/hUurrStYV514+06bDDDsOmTZvi01vbkOTlEb3jcSLZOzY+jvFVqzA0NIB1Y8N4/uo+3P3MY4HjBgCSqUdPEKoxyTuGq9dGOLdMQrWG7YMRjhmMcPRgBcdXCnheX4QvnfZ4PHjiejzw+DX4l8NX4txCJ86odeKKtzwXD110PPDH48AfrwJevQ44fw1wwXo8eP4WvGMswKmVFdg2UMW2WoTH91dxUl+IV1bT+O0J64GjuHOXO3mrdaKXem0fwo8OreGCWh5PGh/BEatJzK3EqlUr4/elMljuQutsAFIL8uyrNZJ3H/ZhLx7hUc17gQ996Wq897+vw4Wfvxl/+LXf4N23At9H/T27PIKZ7XgM824A9wG4CcA7b3gUT/6nG3Du+7+PF/3VdXjJ+67BDQ8CD7k7dh2SV1n3svIPPfgQxhj/BILTJzzbqeyTun6ZtugYZkm+c5ftSOSK3CWxyzzrhSP/wdCo7D5MppOfDZxaH/P7pUZxFibcD425zGs8jU9psU+OvesjxkTvipVkHf250D6UnortXOJntvuWzrJhOr7UPepLcrZ1na3+hB/pSTkT+23+Js9f84v5xTBgGDAMGAYMA4YBw4BhwDBgGDAMGAYMA4aBpY4BrilxbWm21q2a7cdd13LXttrF3+5anPK+Ta4vaBcJXhK9bbqT1yO5xvleXh7hXN/B+YT+Er5z9jHYcfI4cCxJ3j7gGO7mHQCOHcGN21fhnCiFjUNVrBkbxNj4CIZHRrB6aBjbBgfwzu2bceepR+COkzbiZZUcnljuweu39eNn734WHn71RuCV48DLVwHnrQNeswZ7z9+E7/7hkXh2FGDzUAmrVq3GyuFRbBoZxfaBGt555Brce9I6YHsNOLpST8wfOwgcN4IrD63h7DCHTaOjWLtyHKtXr8Tq1aviY3ZJ6PX39+9fcJ0NUDZP8h5MsbK0F3vB45rv2bELn/zk5/C5f/0vfOKjX8TffvY6fOWOh0Fyl1Sw+2/vBNl7P4BLf7EHF//jV/HX7/40PvjW/8D/vvhTuP2WvQeOaeaNB98ed5VQhaVK8vqE9FQkLwleJb17l0c0CzvEjP9AmKqsB8l05Wzg1PpYmC89jDnx4X5ozGVeWOS4FvPJY+7OR8ZE5Jwk6+jPxeJL6TufeJopVmfTf679i9UHrl6yfbHgx54Hkz8PzD/mH8OAYcAwYBgwDBgGDAOGAcOAYcAwYBgwDBgGFhsG3PWwma7TtXI/17XaeW1LfnOlbJJ0/cG4i+TdsGFDOx7X7JG83k7OI6tF/OnWlbjpKUcCjx8Fjq4Bx9SA7ZU47XjiGrx3XRGnVXuwcaQWH/U8PDKGlSPjOGR4FL83XMM3T9uKzx0xjLOiIp4Q9eIbrzgJD75hO3DeKuAVw8DLx4BXro4J3/tedTheu7EXTxgvYcPIAFaOrcQh46uxdXAAzxwJ8V+nbcHDJ68Ejq0Ax1SBY/uBY/qB44bx6yNr+FB/F04pp7FqcABjo8MYHR/FylUr48BwmzUJO+7QHBwchEvQagK7gVfdZNLto/FO3jqlG9O6+/bGvCvJWhK8FMgOvQAAIABJREFULDz281/hW5f8I37+vvfjzr9+P276l08CP7t7gqBlyzotq17i+wDsfOARfOkD/4rv/cn/gzte/m7c8LJ3A5//bn3brwjefQdTuiwpxYzvxP+WC8kr0pe7cpnX7l1KkrpMxAh37jKR8OUPAxhnd+LrYdCMdDE1nfxk+LNri//Lh2LuY8XF03Tzfp8ai9KwMTk2XF/R/yJ3JVlH/y4WX7r6+nFneboYms37pJera5L//OuTlX0cq63GkpxNO6bTl/SglI6Svg1Wnnxumn/MP4YBw4BhwDBgGDAMGAYMA4YBw4BhwDBgGDAMGAYOvBaQa0zu2pOfn85alnuP35/WtCTbLRbS25W+ja79bLekSd4jRgdx9nAJl571OOw+afUEuRsBx4TA0UU8esIArji6Dy8tBThqqIThsWEMj41jZHQl1qxag+39Ef5y+yG4oNqFU6oFvGB9Bfe+5fQ6qfuyAeCPB4GXjwCvWAm8chV+9qqjcGoU4JChClYOD8dk8Rru4q0U8LZD+nD9kzYCJw8Dj4uA46rA4wbqR0kfP44rN1Xw6myAEwZCrBrju1dH9u9IJqFHwk5EL0m9vr6+3yFC3MArPxmImyF59+3bAybSq3v27YuPXN458Z5dHq2868578b2//zB2/8WfA3/+buz94N8Dt90KPPQQ9u15DNhXJ3r5f6WYm/3FL/Gj9/41dvzRa4EX/QkeetEbgP+46v9n7zzA4yqu/r1u6tLuquyutu9KcgEbg3Gh92LTew3dBhISIJTwwRcgCSEESAIpf0LoEAwmlNAhGLAxYFNSCPkINaYXY9zV2/t/zl0d+7JZ2bKRbUk+5JmcuXPvnXvnzDuzeubnMxdaM9/ulWfINs9umVfyWoe7PPNN3oG3XbOKumpV1BUWVOR1R+6KwCtJOJHzwohMADrosyeDnhwrR+tqV8efnes/f/Bo/yszytQ3sVqXWK3fmOgZE+ovsdIHKu6qlTL1a1/yqfu9Ne/m4Jvw9E3u1XfQd1qdz/Qatdn3arnY7upxXyN5rUPsN2nH2t6rz5X7JO9+r+7e3cp7NkbNT+YnY8AYMAaMAWPAGDAGjAFjwBgwBowBY8AYMAa+Lvbq2pOuSeVaC3Of60le63Tb/ux3dzs0n+0H9xqgXNPvRV4VwHLZEdEwO0YD/G6nsSzavQ4mlcM2FTDJDxN9TkTt4p0i/K7awy6hIqKJaqrjUSIp2fY5wohYgO3DfnapKmDXcAH3nrYXS87cCk6PwekR+HZXOiNF65mb84fxQ9gxNJRUPEI8niQRTzpRuZOrSpi98whW7ByHnYOwYwXsGIAdJYo3zKIda/hNyseB5YVsGQ4435eNx0XIk5SJ2tT2iYAnUZoStSkCXyAQcBaSpaNzdbqWqc0GXMsbG7/2NdxMjGyHSqpiO0V/ZTnwH9luuR4e+xwe/dunPHnHQ3z162vh5z+C3/wC/vYytDQ7Cq0Ks+100Ib8vyi1nfDvt/js8qtoO/18Oo47ixXf/hFf3PQUM9/o4N4l8C/gE3C2fXa/RXZeqqtvqF8peqqfBoqVLZrd2zSr0CtWy4UFjd6VSG+J3s0e+N0da/93Z7N5seNN+48T5UR5cv+giMDoPs6V1/vEal1qja2es6U+Eyt+VnFXrZSpj/uiX93vL3nlIhcz66tMn6k2+53kWH2XfU7vyWX1Wr1X/jGVJi1Tq9fmqmd9tdtdr/u5+i7ybpLXdzTb83FpvjJfGQPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGgDGQmwFde3JbXZtyr1etKa/3uOvR/EDwvbbFbbXNat0+kusGtMhbE4uyeTjI8TE/b+8xAnaogm38MMkHE8oydqKPV8ZVcnDVUIbHqognIoTl27yJMPFENel4NWOryzi6tpDXz9ublu+MgmlhOLUrnRaGM+p4e+oWnBz0MD5c4kThSkRwMh5ndLSaU5IVfLTXSNg9CjtXwU6VGbtzCHZL8OpoP1MrhrF9uIqR0bAjDifiNWSSiMWZbwyLcCninoi7GrUpeRH7NLJXO1+B1mO1Wq5Wy3OKvBmp1xFmm4HPgacWw1X/WsF3X1rC1Gc/59wn3uP6O5/mg99cB1f/FK78CTzyACxZnLm7K+S2U2rpaM8IvCsa4eFH+ercC+k4+SyaT76A1079KX/8yZ845uY32OX+Lzhx5lJu/BD+D/gSEAk6IzVnontV7M2IvCsGrMibS6xWBnR75uHDhztciOAv/SmD3T3QdfDnstr/3VnlxGzuH6dNzS/KSTZLbt66y+s9Wof4TvNiNzVffpP2uv0m/lZxV62Uib/7ql/d7y95ZUNsd/z0drn7meqr7PdyH+s12fd1d6z3rq6f9ZpcdfR2e7Pr02fKO+hYXN272jn7DTAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjAFjwBhYVwZ0HcxtdX1KrK5dufNa5rZ6j7seza/ru/Wl+7QtbqttVuv2h1w3oEXeVCJObSzCXqFSntyllsW7RWE7P0wogfFFML4Yxpfw8XbVnBsrYPtqLxL9G4tLJG/USYlkjHGV+TxwxDiWf387OK0mI/JODYOkU0I0nzGGX+8cZofKQWwerSQek22fE86zt6mu5FfbjWLRlFrYVcXdKti5Anatom2HSh5MD+Ggqnw2j4WojWW2eU7GanCSExEc71bo1QhOEXtF/JNO1c5W6wZCgXWXSX51Iq9snfzvVrjurWUcO/tz9p6zgm2faWCnZxvZ9y8L+elD/8ebv7sVfn45XHYpbVf9DJ55BhYugpbWVXsut3ZAUxvMmcfS/72U5qnfgZPO5ItTfsg9597M969+gS1v/gj/ncvx37KU1M1fcMqLHTzZAiIZ6/d8u7TnlaahfuBE8mp0bra4K32rSfpaBV7pf/lGs3tgS177fk02m4PsY+XFrP2ACwPZfOhxNmduHvWcXpvNUnfl2dfZ8SoG1Wdixdcq7qrVOUDO90W/ud8/O6+8iHVz1Bt5d93Zz80+dl+r75Jd1pPj7Hr1WPpF826rdfZGe7PryG6HPLcv8mHvtGqsmy/MF8aAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMTAQGHCvf+XK65rYmmyue7VsoPop2yfuNT9p+4AWeSUCNhGPMj5QygXpIv6xe9oRVZkoAm9hJk0sZum2ldw3PsKhvsFsVR0gHosRT8Sce5ORIHtGCvnw7N3pnDYSpsbhFBF3q+GUCExNsuC0cRxY5WFMpILh0WqSsYhz/5hIFUdEyph14CSaJ8dhj0rYpSKTdiuH3QO8t3UJ14Y97FxVQDoeJh2LkYolSMbSmRRPOAKv0xaX0CeCnzuyV8Q+jeiULXtle0jpfAVcrYKux2Llulwib3snNHXCp8AN7zZw3OzP2O2FJsbObmX8CzDp2SYmP7OU8x74Fy/+/m6W/ewq+NEltF18EY1XXw0PPgRvvQOfLYDPvoS358MTz/LFJZfTdNqZcOIZcNL3eevbl3Ptj/7MEb/9J8Nv+YziO5sYdDvk395B6JavOGUevAosxflkb0Y0lgjhrijhxvoGZ4vrRCLZtb21+EbTqijobOG0Lx5ni7xuYVfFXRF4tVz6UwZ1aWmpI/Tod5bd/at9nD0Z5OIj+z7lxaz9MSEMdMeHludizM2Z1KFb16o1ttaeLfW3WBn/Ku6qlTL1e3/yr7tdypL7j5Z1zWtdbut+luSz/SRler0+V4/Xxa7uednn9Nn63G9i5V3lfn3n7Gdlt9uO1348ms/MZ8aAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAM9A4Dunala1nZVs+rHWh+13a5bbYP3GuFct2AFnnj8YxQOzLkY69QIfdN3pLFO1XDxGKYICJvAWxbSts2Pt4YV8lFJR52CJSRjEedLZdHpuNsmajgygO2ZvF3t4ETYnBKtEvgFZE3DqeN4aGdAuxdXUhtOEBttJp0NEwyHmFioJjrxod5X6J49wzBzmWwmxd2K4PdvXTsGeK+4fmcWuFhQqCUZCxMMholEY2TjCeclOgSeVWQVHFPBV61Ui4ioAqBup2zin4Cu3S4WoVEAJF8Q0PDyshYzcg3eBcBj37awtQXFrLHnEYmvdDBxOfb2W32Cg56ZgEnP/Mx/3v/K9x788P865obaLr8Crjkh3DxRbRc/EO4+le0XX0NbVf+is4rfsny719I06nfh5O+5wi8S06+gBe+fy2X/fIvHH3bm2x7y3wiN3xG8e0tDL0D8m5pI3brUi56A14HlsnLqcC7UuRtzGxxnZBvGIvQq6nvC70i6mYnd59qf0u/Sp+KmC/npc/KyspWLtxLP7oX8rMHfnfHykF3dqBNktaetfuxVSFW7Zr8l82Rzi9SvqZ77XzP+8btZxn3Ku6q1bmgP/td3l3nLf3DRY/Vanl3Vq9T6/ZbLt7c5/We7upem3Kty11/rudLmV6j97ifo2Vq3eckr+XdWa1bbXfvYOU9H4vmK/OVMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPrzkD2urOuW3VnB7qvc7U7e63PvSYo1w9YkTcTxSsib5i6WJBtasL8cOs0H+4Sh4klGZF3YiFsne8crxjv47FRXqZUFlAXj1CbSrFZNMBuoSHM+e5eNEzdDE4Iw4khODEIJwXhlBQfn7QV3yv3sGt1CSOjIWqiIdJR2XY5xORQPnP3StG5bxT2qIA9fLBHKexeAruX8dlOFfw0mc/kQCFjowFS8ajzHV8RdkXkzRZ4c4l/2WVuoVciPuvq6hzhV7b0VcHXDYoAIse5InlF9v1nE1z+9wXsN3sZO74Ek17oZO8Xm7l0PjwGvAZ8ALw7fwlvPTKbd372K5Ze8mO45FK48CI453w46zw481z47rlw+rkw9Vw4+Twavn0xy6+4iY55H/BFC/xNBOUWOO/vsMXdS/DeUo/nhjaKbm5ny7sbuWMpLFytyJt2CbxuobfvRvO6BV7pSzl2C/Yq2ks/jhw5EvnurkxkKuaIdQ9q94CXfnUf58q7WciVH+iTprVv9T/A+iOrdk3+ysWQlq3pXju/+r5w+0d9KlbGv3s+0DlB53b3ff0pL23LNWe5y9xzX668Xuv2l+bdvtAytXpfrjrXtUzrVKvPUqvvo8di9drubPa7dHedlLvr1WeZ7fmYM1+Zr4wBY8AYMAaMAWPAGDAGjAFjwBgwBowBY8AYWP8MuNewcuUHeh/kanP2mp97TVCu71cir4hfIoSpGKb5bJsReCUaNkoqXk1NPMiIaIiDgoX8Y6cEzSLyOt/kLcTZulm2b966iDcmBTm6YiijAuXUxROMC/n49e41fPbdbeGkJJxYDccHM+mEShqm1nLPvrUcWOFhj1AhO9ZUUxsNkoqF2CxawfkTknxxUB3s5c2Iu3uWwh4lmfzOZczZfBhHVg1mi2gVw6MRZ5vmVVGoSUfkzWw73HORUiM/VSjUb7dqZK9s6Sx5ERNF+NXF36amJg3gXWnlO7gPLYGpLy5gt+ebHJF39xdaufijjLj7JbAEaNbg2mXt/N8DT/P3q/7AgsuuoeXCn8D3fwBnngPfOw++cx6cfj5NU3/A52f8hAVX3wHvLYSOzPd2vyLz7d13gCv/D7aZ/jmlN7cw+IZOAjc38j9vwBc5RV7ZrjlJItE/RF63sOvOK8fSd9pvIvJK9K5cp4NZBq57ILvzeo3b5poYtGygT4rWvm/2w6virto1+VO5ymXXdK+d73lfuf0r438girzCg7udmnfPbe65Lzsv18k9bq60Di13H/e03uznrMux+1n6nrneyf1+ks++L/vZ2efdx+663D6xfM/HnfnKfGUMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGwPplwL2GlSs/0P2fq83uNT7Ju9cE5fp+J/Kq0Cuil+ZVHFO7SuSNkYqHHaE3HYuwY2URj+42kg+2C9A2sTSzXbNE8o7Lg3H5zB9TzBU1PiYHvWwVqWbnqnz+evIkmk6pg2NF3A3AcYGVQu+CqZtzZIWHPYND+f7oKs6bVMO4iJ8RwTJ2qS5m+r5b0HhgDKaUwuQy2KukK/mo36Wcu2uHsmtVPqlEJoI3E72biUB1RMtuonm1nbms+CRX0ohQEXhFQBSxV5IIiHJ9a6tszvz1/0TE/cW79Rz20jJ2fhl2eRmm/RseB+Sc+78O+V5uO7z17y+47+bHePTa+3j+yjv5+yW/4a2Lfsm7F17Dm+f9kv8795e8et6v+OiGh+GthdCIo/DKzsvtXR/ZlaJXG+GUxz/He91iPDdB3o1tHPx05vvA/71d88ASeaWvdGtm+b6yTFzZWzO7B7Z7UGvefT7XxKBlA31StPZ9sx9dFXfVrsmfypXaNV1v59etf9S/YmXMD1SRV/lwt1fyOr/pfJfLyjVyv7IrVutT665X6xSbq77eLHM/S/L6Hvpe2VbPu9ue6z21Xr1e61ar5dn12/G6jUPzm/nNGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjIHeZUDXr7qzA93fudqta35q3euUcn2/EXllu1oRJ0WQFOFLRN5cIqeWqdCbiMeciN5ELMLW1RWcHC1h1p6bsXRbP4zPh/EZgZctC1gxzseccdWcUexhSrCU87dJ8/np4+CkCBwXzAi8x1bAcSE6j43ywj4RJld52Ds4hNkHjuKFg0dzQHU+u4YK+X6ygNcOHUP7fgHYqxD2KoW9Regthn2reGX0UP7X62GHoJekRCgnoiRku+ZojHQs4UT1ppxtm+NoW7Rt62rFd3KviIhi3WJwru2aPwMu+Ndi9nppBRPmtrP3K5389P1MFO/ylQpv1wdyOzudiN63lsKVj7/JyXe/xXF3vsN3b/wH51/3Muf/di4/+O1czv/ti/zxifepl4/r/reu7NQqxRKx+6t/1BO9aSmeW8BzI2x11zI+lCs6O1d9lxdorNdv8vbdSF53xG523t0XIrwL63KNbM3sHrA6iMVKudu6z0leJwN3XsvcdqBPita+9fcjm+3bXCJa9jV23Dv94R7DMhcMdJHXzY277e55T+fE7DnPfa/m3XVIXutxz7cbIq/P7ck7y7vre7vv0/fUMr0ml9X2m+2dcWh+ND8aA8aAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAM9CYDudb0dN1Pra4HipXr+43Iq1GnKvSuSeR1hDMRMruE0mQ8xqhoiJ0jfm7aYyyfbFsB44Zm0lbDYGwezVsU8vZmxdxY6eEkn4eHj9uBhlNGwHGV8K2qrlQBx0dZcFQNF1d52KNyMN8ZHeSjQ2r44sA4l48u49gSD4/tGGLxIWnY1wuTReTtiuLdu4j6yeXM2Cyf48s9jvAcT8SIJSKO0JuOxamJJbqE3jipuGw7nRF6pU25BEIp1+QWblXUdZ+TvJa7r+1O5D37H1+xu4i8L3Ww+7wWrvoY3gBEo81ssiyCawd0tFMvEbjNcPacL9nm8RWMfKSViQ82svN9S9n1rs+Z/Mf5nPnscp5ugc9FnO3SeUUmdv/XTubbu9e8upTojYucSF7PrbD5H5fwvnNhtsjb1O+2a9Y+0ahdEXaVcflHDCKY6aDtqe1uAshVrmW9OQFZXQP/B025EZvd3ybybrj+d/eD/JhvqiKv+iF7jtRy5dR9LPns6+VY/Kjl7j+UNkRen6vW/b7uceYu13yue/RctnXXZfkNN17N1+ZrY8AYMAaMAWPAGDAGjAFjwBgwBowBY8AYMAaMgZ4wkL2eJ8e6/qfWvV4p5/uNyCtRjSJKqiimYq+KZSpc6rEjZsa7ImJjCUcolS2bh4cqOGOzat7ePpAReLccAmMHwxaDaBkzmOVji3i1bjA3DR/E+2fsQMfxMTjGD0dr8tF2XIKZ+6Y43uvhoKph3LrvViw7NEHr/hU8u52X/1flYenBETioAvaTyN0i2KcE9i2BKYW8vs1gzol72CGUz8hoJfFEmFgi7Ii8qViKdCy9XkRet28c/7i2ds4l8ko07Y/fbGDyi8uYNK+dHec1c858mA0sUrHV2Tu5DdpbWAo8WQ/HPL2AzR5cRupxSD0Mo+5vYqcHl3LGnAbmNMNHXZG68s3fFpxP8iLCrmz5LHqxRPLOb4f/fW4JwRsXO1G8Q2+FXR9tY77z/d8uWbjLNNQ3Id8y7g/f5FVhXTgWhvVbyXIs52Sg6tbMMuhzDWIdzGJzDfrssp5MHnaN/cj0hAE3W9nXm8i74Rhy94P8qG9KIq+bO7cfNJ89L8r17nNy3v2HkDvvnltXd537nt7Ou99B3nt17XW3Tdu4Ouuuy/Ibbryar83XxoAxYAwYA8aAMWAMGAPGgDFgDBgDxoAxYAwYAz1hINfannu9MHvNUursNyKvCF+ymCpRjiKO6ba22WKlW+yVKN5ULOkkyWe2bo6wR7CI53dJsWh8MZ1bDoMxHie1j/bQsvkQ/pP28N7eVSw6vgaOrYKjy+Bob0boPcrPp4dHOTc1iAPLPZydyOe1YyfSdnAQDvQxf9shvD7WAweUwQFFsF8h7FsA+xXB/qVwYDlPjPVwQJWHUdFy0vFgl8gbIS5bS8dSpGLpzHbNsVVRvLJls7T1m0TyukVeqS+ZSJJMpBy7UuTt2n1ZNNyFwE2fdHDkC4vYYW4r28xrZ7+XlnNTUyaad0VXNK5E5IrAK1G2P32znZ0eW8jIJzuIPwHxhzrY8qFGvvM3eKID3gVeWgz3fQwPL8DZflm+7yv3yxbQEg38KfDwQtj7ro/w31SP54Z2Sm5q5IR58EGXGLxSYwYa6hu7RF7ZhjrzTeOMle2pM1tUu9u+ofMq7IoVMded9JvI8o8YZICqwKt5GdTZg9h9nGvQZ5f1ZPKwa+xHpicMuNnKvt5E3g3HkLsf5HdxUxV5lUG3P2R+1GPNu+dMyXcnzPb0uu7u781yfRdti9tqu7Ot+xrJZ5+XYxmnmnKdt7INN47N1+ZrY8AYMAaMAWPAGDAGjAFjwBgwBowBY8AYMAaMATcD2et7cqzrhGrda5Byr4q8I0eOdD4FKtppriTnc5VvqDKPvnhJSYmzQBsOhx3RU0QyjerVaEgV1UTETEiEp5NE7IsRT0SYGPbxiwlJ5m0bYcVWRbC5B0Z56BzpobnOQ8OWg+HoaGZ75mNE3C2Bb/ngONmyuZqX9wmxb8DD5MAQZk5JsuTgajjQC/vkw34lmXRgMRxYBHsPgX3zYf8C2L+M93co4HcJD7tW5VMTizjfC3beS97N2Zp5/XyP1y1s6jd+UyLwxtMk4yka6xsc3dQJzO0SUkV4fbERzn7xM/Z4sZUJ82C7F9s59u/t3LkM/g38h0xk7ittcN1HsOfMpWz2l3ZH4E0/AVs8tILv/B1ebMtcO6ceTn/4Hba+423Gz/iYS9+DR1vhTTIC8L+A6V/Cfo+toPIPCxh6cztDb2olfstirl0An6zaJDrzvo7I2+CIuYmECLwq7KpdtZW12wfrK6/sqdXnyLFG7gqzyq0MwlwDVQfs6myuAZ9d5p4gLG8/GMbAwGBAx7nOD/r76LZyTq7bFPpc/SFWfZLLuv3TH/K52rCp9OmmwK21cWDMx9aP1o/GgDFgDBgDxoAxYAwYA8aAMWAMGAPGgDGwrgy41zVz5XOtD7rL5LljxoxxhN4+L/JmRyrpQqcIuyKeqVVxLWOzozrjxBJRNo9WsU+giBk7DOfzrUphpAdGeGC4h4a0B3bzwpGVcFghHFUMRxXB0cVwbCWLDg/zi5SHnUOFHFbn570j0nCIRO0WdqUCOCAfDiqAA/Nh32GwzzDYvxAODfHkFkM5w+dhQmUZyZXic0aIVPFVvsGr3+HVCF4VC3vDOlG88TgpieSNpZzUWC8xtF//1m0TGVH1preWcNicJew4Dya8ADvOaeX4l5u58J9NXPteG1e/2cS5ry7ngJlfMebJZpJPQuLRdrZ6tJHvvQZ/aQHZ+llE4+lvNTLljtdJzlhExZ8aGXnvMg54uoXz/trGj1/v5LTZy9nt/oVU3LSIvFtbGXxLO74bl3LYUy3M6sxEFzvbOq+UeKG+QUTeVd8a7g0frWsdX+cvsfL7x8Kn/IsI+fau1B2JRJxoKoncFZbdA7On+VyDPrtsXScXu89+mIyBvsuAjnOdK3IJlnJOrtsU+lH9IVZ9olZ8487n8lVfLZP3dr+btmNT6FNrY9+df6xvrG+MAWPAGDAGjAFjwBgwBowBY8AYMAaMAWPAGOgdBtzrmrnyuh7YnZUd+/qNyOte6BTBV8Sx0tJSxwpQso2xCGgipmmSyM5EYtUWvrF4kmgiQW08ytahcn63+zje3bIU6jyQ9tAmSbZuPiwCh/vhkHw4shCOLICjCuk8JshLU6KcWu5hh2AZF+w8mi+PrYNDijKC7sGFcFAeHDSsy0o+Dw4shP2LWbCnn2tr89jfP5Qtw8H/EnkdoVLESldaV7FxdfdlRN4YqURGTE7GYzTWy2bJHY7O60Tzdn3vtg34Zz389N8NHDKvnh1ehPEvwKRnm9jhmeXs8sxStntyIdvMXMEWTzYy4qlO6h5vYZunmvneP+GVrm2fZUvnZcATn3Rw2N1vUHvPEvz3Q+V9nVTe1Uh4+lKq7/iK4B+XUXZbPUNva2fYHTDk+qVs92Aj9y+GzyVqtyvK2C30Lq9f0WdFXv3HB/rtXekX4VV57m5w9qQ816DPLrPJtncmW/Oj+bEvMaDjXOcJnU/cVs7JdX3pvdfXu6g/xK7OJ27/9Oe8tHF9+dLqtbnOGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjAFjwBjYMAy41zVz5XWtszvrFnk1yLC77Zf7xHbN2hBZnM2O7JXGhEIhJ6pXInslJVNJEskEMfmWbUIE3iSJVA2JWIwRsSgHxSt4ZGKM/xtTzDsj8/lguIeOHfPhwDI4ogwO7xJ4j8x3onqXHRnmF5sVcEAgj7EVpRxTW8m7R9bB4T44pBgOzodDhnUlEXeHZtKhJXC05xqEAAAgAElEQVSAl1cn5HNKpYdtA15GJySSNvM93NUJsuvjXEZEVpE3Y5vqV0Dn1yN5NVhWYnyfXgoXvbKAI5/5nP1nLWHKs0vY+dllbPVsE6NntTNmNox+qpXxTzWz8+OLOet1mA0s7qqko7MDEXo/BH4+bxG737+A1F1Lqb63lbIZrZTeC8PubKXkHiia3knBLY2U37SYre9dym8+h/mARBa3Z+KN3To0fU3k1X9koAKv/uMD/e6usCsMC89uUUL57s7mGuTdldkkvGEmYfOz+XljMKDjXueKXIKlzi8b4/029DPVH2JX55NcfuqPZdLGDe1je57NdcaAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGQO8y4F7XzJXXtc7ubL8SebUR2QuyKpi5y2XL3GeeeYaXXp7H3JeeZ87c55g990WemjWbWbOe47lnZzPrmWd5+anHef/Re1n+wG003fhzHt8uBEcn4PBSOEKieIfCUZIK4eAS/rZrKYdVetgy4mVULMxOwSL+PDnF0mNly+ZSOCQPDs3LiLxiDx4KBw2Fw7007lPGvaM87F81iM2iAWpjsZyRvOtD1P3vOhMk4pkUi2Te47W//oN/vPo3/vryS7w8by7z5s7ludnip6cdv90/+2Wmz/kHt875J/9v9utc8cy/OPXJt9npqUVs9WwrE2Y2s+Njizlu1lJ+Mx/+CnwMjrArOm9nZ6cj0Eo07wfAzW+2cdxDHzNx+kekpy8keNcKyqc3UvnHesK3LWLUbZ9y1JNLuXcJvAMsASSq2PnPiTKWWF6RfGH58uUrt0WWiO7/bu/6+y5v9vbM8nz5BwbyryX027vyjw+ET2VYBqscuwUJPbc6m2uQZ5fZJNu7k6z50/zZFxnQca/zhfv3T/NyTq7ri++/Pt9J2ixtVz8MBOv+R23SHu1b5WBT7Of1yZDVbfO+MWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGwIZgwL2+lyuv67/d2QEn8qrgKw1+6aWXaG1robWtkeaONpa0wrIOqO/MpKUdsLwDWkU5bKnnvQduZ+aJu9D4rXiXwDsEjpY0FI4uYcX+fu7cbBC7VA0iHQ+SjkUZH/Lx/ZGl/PvErWg7qgoOy4PDhsFhQ+GQwXDwIDii0Nn6+V/b5/HTavmWbwGpeJiU893dpCO2xuOJDSpMZp6X+V5xKpl2xGYReVsbm+loa6W9o4P6VmjozPhI/Kb+amrrZEVLK3c/+Qw3zH2L819dysmvNHHOv+BXH2S2Z5ao269EfO0UYbaTzs4OJ0i4ozMjy8qWy7L18r+A374NZ81r5pAnl3Hosy0c8pd6zv473LYYXuuK/G0GWru2ae7aRbornleE3r4h8mr0rgi8sjWzWBGbVWDQQagL9HIsg1bL1WYPZC3X67PPZx9viInHnmE/cMbAxmVAx73ODzrPuK3OGZtaX4lv3H4YiHnp202tX629G3fOMf+b/40BY8AYMAaMAWPAGDAGjAFjwBgwBowBY8AY6H0GdJ23O6vrv93ZASHy5lrAFbF33rx5tLW2Ub+injff/YTjz/wZ+5x8OXtN+xW7n/pbdj31d0yZ9nPqReRtWsbr99zI7G/vReO3quGIwXCkpEFwmAeO9fO3nUo4u8zD9qESR+CticUYEwmyW3UR0w8azYrjonDEsEz07+GD4HAPHDHI+Z5v6xEB7t0yn2NKPYyP+EjEoyTjia5IXhFbReTdkEKvPCsj8sYSmWe/Mnee8z3ehvoG3pr/CSd9/zL2nXoZu0/7NbtM+z27Tv09+0y9goWOw9p59C9PsaQD3m+Ddzoy2zB/KYIrINs7izArgqwmkWM19lbib+W8RPVKhK4Ivv8B3u5KHwFS11L5Bm8ntHZAW0bPderoyjoCr/zfsmXLNngkr0bwusVdEXZla2YRd2XCc7Opg1DKNJ/LZg9m9zXZ53Id20Tb+xOt+dR82tcY0LGv84N7rtG8nJPr+tq7r+/3kTarDwaqlb5d3360+m3eMwaMAWPAGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAG1i8Dus7bndX13+7sgBV5ZWF37ty5tLe1U7+ikaWNMOfNZvY78ya2nXYDE0+7nYmn3cEuU3/NIlEbGxfz2p/+wMzTd6X+uCo40gNHiUAraQiL9i/ihs2HcYjPw9aRSmoScUTkHRWLsGW0grO2DvDh8Sk4rhSOFqFXBN6udNgw3t27mB/V5rFHVQGbx4LEEjEngjcZl0jejNi6sUTeqIi8iTgvv/gCtLVS39DIkmZ44Z0GDjjrBiZNvZXx0+5m4rQ72eXka1nQAM3N9Tz+6CMrRdbuMirwilWRV+zKY8l0/SfZlo5MpG9mE+auq1yKblt7x8p6XLduMJFXhF3dClryboFXonclyaSnwoIMMM3rIJRjzeey3Q3mXOU2wa7fCdb8a/7tSwzIfOJ+H50TZB7RecZtpVyud9/nzrvrGkh58YvbDwMtL/0qbRxIfWZtsbnWGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjAFjYFNmQNd6xQeaF5tLQ3KXyXrvmDFjGD16tPMJUQlClE+J5kojR47MWZ7r2vVR5tEXz16w1XKx7nOzZs2itbWNppY2lrTAC/Nh7zNvYsIpf2D8qbcy/tTb2PHkX2ZE3qbF/OPe65j5nV1YclwFHO3JpKMkireMV3ccxrEBD1tXlzMiHnK2W66NRRkeDbNZIshuQQ9zjkzQeGIVHCvf8vV0CcUeON7P4+M9HFDhYWwiQjoRI5qId4m88l3cjSfyxmIJojF5lzjznp8D7e00t7Q6/po7v50p37uRiSffzIRpdzJx2u3sdPIvWdAILS2tPHD//S551iW5dmZE3BYRbbsEXRVyxTrf5u3spJXOzFbOznd1Ox3hV8RdCazukC2enf/JNs+y3XPmPuf+HHV+9dVXK8XX3v4mr9QnSSN31YrAK6BL9K7kg8EgEkHu5rG7Qbi6Qeo+t6b8pjzpWdvtR39TZEB+tN1Crc437t8+zcs58ZHe475vIPtO5k31wUC00q/SxoHch9Y2m9+NAWPAGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGBgID2RrPmtqUfb2u/3ZnZc13QIq80mAReVva2lnW1Mrf3lvIgWf+hgnHX8P4k3/PxFNvYtK0m9j5xJ/zVaPsHbyMv95/A0+etReLTonAcfIdXg8cU8CyQ8u5ZfRgdg0VEQ9Xk0xGSSTCpOMRahMRUrEqxlcP5ccTinjv1BF0HO+Dowdl7v9WAV8e5ue3m3vYsbqIaDRKLJlwRF6JCE2s3KY5s2WyRomuf5t5XiwWd7aJXiXydrCisZl//OdLDv7etWxz/LVMOOlGJk27nW2m3cxOJ17liLxNLe3c/4CIvF3Rtk58bZfQmyXyrgrElfMi2HbS7oi8HbTSTqcj8oqsq9s5S4lE7HYJvY7Im7nPLRZrvr29nZtvvnm9b9esUbtia2trnSQCrwjAgUDga6JCdwNOy90DVcrcx2uTX9OEYOfth9AYGLgMyFwh80d3Qqack/7fVMRdZV380p1PBkK5/mZoe80O3DFufWt9awwYA8aAMWAMGAPGgDFgDBgDxoAxYAwYA8ZA/2ZgTXqP9m9318la4OrSgBR5tcHPPvssTW2dTlTqmZfdwC6n/IqJJ/4/Jpz4O7afdj07Tr2O3Y6/jCWOyFvPCw/cwR++tR2fnV4HJ8i2y4V0HBPg8W2LmVrlYVzQ60Rtxh2RNkoiGSWZjJBKhRkZLWO32DDuOmoMX54ch+NL4LgiGo8t557xgzmhysMWVcUkUyky98eJJTTFnO2b17+wK4KuOyXIiLyZSN7nn3uO9o5Olrd0cvZlv2PXU67q8tf1bDf1Zraf9gd2PuFyPm+AhtYO/nT/fY4UK3JsRpLVjZgz8qscrRR4HX3XCcd1onLbO3GE3vZOvSpzpfy/RPJKRG+XZNwVydu9yLtixQoOOeSQbyzyasSu20fuqF0RdGU7ZrEq7oZCIUdEEeFAonhVQFAGu7PdDdi1LdcJwGz/nuit/6z/1sRArrlB5hedc7Ktzj257tOyNT2zv56X9mX7YyAdS99KG/tr/9h723xnDBgDxoAxYAwYA8aAMWAMGAPGgDFgDBgDxoAxsKkwoGuxul6bbVd3Xs5lX5993C9F3uxG5DqWxmdEXnj/y2amnHAR2x1/NROOu5btjr+SG2Z+yM0z57P3t37Al0vbaG9q4tG7buOg4V7u2T/Kv49L8vYRER7dycv3oh72ChUxJlrtRN4mkgniyTjxZJR4MkI4WkU6XsXmUR8HpQu5e0o1bxyb5PVDq7l7m3ymhT3sUV3AqEjVSpE3W+CVb/S6xcUNlRdhU56VTCR4bvZs2jrgwy+Xsc8J57LtCVcy/vhfs93xv+DGmZ9w48wP2fO4i1iwAhodkfd+J9pWI24zsmwmWlejbLuzqzRfvT4j4nZ0dq785m72vRIBnOu/K6+80mmDbqm8rr7LFnndAq9E74qwKxG8YiORyMoFdt2iuScDTlnVgdtT29MJTwZ0durpvXad/bAaA32XAfdcofOI2DWJl+5r3XVIfqD2t7RtTX7pz+elTwdy/w1ULq1dfXd+tb6xvjEGjAFjwBgwBowBY8AYMAaMAWPAGDAGjIH1xYCuybrXad1rk+7y7Lzcq2uB7rz7un4l8uZyhruB7kZKfubMmTS1wTufLGfKcf/DjidcxfYnXM0dz7zJhw3wSQP8eeYclje20dbSxoMzZjAq5GOXZAmT43lMjgxl11Aek8I+NgtVMTweY3i6hnQi7nxXV7ZtjifCJJOydXOQEbEAYyM+dqjOY/fQYPYIDmOXUDFbV/vZLBokFRdRWLZJ7oqmFWHXSVLPxhF59V1E5J0t3zBu7+TdTxcy5fhz2P7Eq9juxF9w17Nv8kk9fFoPDz39MkuWNdPS1MZ999yXCdWVAN32zLdzM9sxSzxuRpCV/5eo3TaJ3HVH9opaq/putnLb0QGS1vCfiL7vvfceU6ZMcaJ4VbDWNvXEqrCbbeVeEXlV3BVhV8rkOvcA0ryyp8drsspyT+zaTC7ZAq8cr839dq39mBkDfYsBnSPcc4r7j4C1ybvr0HoHYn9L29bGL/3tWulHaeNA7DtrU9+af6w/rD+MAWPAGDAGjAFjwBgwBowBY8AYMAaMAWPAGFg9A7rOqlb9pce6Jru2a5B6n9tKne5jyQ94kbe5rZNlTXDMGT9m26Mu4ZiLbuXjBviyvoWv6leweMVyFi9dRnNzK/fNuJeAz084WEE6FWHUiBpG1KWpSaVIiugXjZOMxqiJi8gr0a8xkskY8ViYlHyfN5ZJ6VjEEXRTsQSpWLLru7uZrZlV5JVv4MbjIuy6k3sr5Q2bF5F31jPP0NbWwbLmDo4+42ImHvUjjr7oNj5rhMUNjSypb2JZfRPLl9bT2tjCvXf/aaXI64TfiqLe0AqNLdCgScqAFlgGfAx8CnyRlb7sdC7JyLqO+KsKsNiv/6cRvbJN81577bVym+aeiLqru0aFXrfAK5G7skWzlMngzDWIsgfV6o51YIvNHux6/E2sibyrn3C/iW/tXvPthmZA5xux+keAzC+aX1vrvlfy7vnIPSdt6Hb29vPc/lpbH/WH67XvettvVp/NccaAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGwNoxkL3GqseyhudOvbHu6K5P8/1S5FUnrck+9dRTtLa20dzWwYv/eI/dvvW/TLv0VhY2wvKGFlY0NFLfUM+SpUtoaW5hxp334CvxUuErw+8tJizRu7Vp6mprqKsbTk1NLYlEklQy5WxvnHTyaVKJtCPm1sRiDJfoTxF345JiJONREvEI8UQk893dZAIReDWtTnTckOcckffpmXS0tdHU1sGc1+azy7cu5ZRLb+erJqhvbKChsZHGhkZWLF1BU30TM+68O6O+drbCRx/y3hW/Zv53LuSTaefxxdRz+HzaOXx2yjl8cdL5zPzObzj2h3MZc/kHjL18PltK+umHmfSTdzj8d2/z8ifQKjWqvuvE/soXer8u9La2tPDOW287Aq9E2EajUSfCVv0lEbiaX5PVLZnVSuSuJrlXhF/lTAehDp51sVqX2N6YLHOJutllvfGcjVWHtGVjPdueu3Y/Zuav3veXzBMy77i/963zUG9YncN0Xhoofah+6w0f9cU6pN966zdkoPS5taP35x/zqfnUGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjIE1M6Brq7rW2p3t6TqjrAW7U3f36XNU5B0zZgzDhw+nrq7OsZLPTiNHjvyvsuxr1uexR53VU5sReVtpaWmmsR1m/u0jfvK7P9HQBo0NzY5g2dbaSlNTIy3NzUy/4y4qfZV4S4rxeUvweUupLPc7gmxKvsdaN4JUusYRAUXgjcdFsE0Rj6ZIxlKkY3FS0agj+CbjSVKJOKlElEQivErkdQm8mWheidgVUXKVMKnlsUQCSe5zaxIt1/V8RuR9hs62dlpb22loh7/87TN+/Lv7HN81NTXQ3NTgiMD1y1fQsKKBu+68KyPydjTDxx/x0U9+ycLTL2TZiefScML3qT/hbBpOOJvm48/lxdN/y9E//Ds1P1tIzc8WUPOzL6m9fBF1l3/FyMs/Z5/fzOflLzNbOjuSrvN/IvD+t8j7y6t/wYEHHEA8FnNEWBFlRYzVtvdU5HULuyIWS5K69Lu7oVDoa5G7Oph08KyNzcVsb0yQ2YJuruPeeM43qUPb3tM65Hq91kTeNf+IqK/M9n9f6VgRq/OLzDvrW+TVZ+nzs1nSeUXK+8OYlHbofD0QrfSXtDG7n+y4/88B1ofWh8aAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAM9C8G3Gu5us6ay/Z0ndIt8Gp+dfcKLyLw9guRV+HWheg12UcffZRHHnmEBx96iPsffJh7HnrSSXfdcx8z7vkTM+65x0nTp0/n9ttv5w+/v55QIIjPW+YIvGJ1cV0WtuPxJDU1ddTW1FCTSiNCr6REPGOT8ZgTvZuSCF8nJZCyRNeWzCpE6rbAsZhEoEaJxRNOkq2b5drM9XEiiRThRLpL6F1/2zdHYzHS6Roef/hxZj7xNI8++CgPPfQ4f3p4ppPEX/fcM4MZM+520l3T7+LOP97J3dPvomHZclqWL6Vp/nxe++31/POSn/P2RVfx3oVX8e5FV/DO//yUdy+4jL9cfD3nXjWbA699nQN+/RoHXvsaB137Oodc808Ou+avnHPba/z9kw4W1cPyFa2sWNHA8vplrKhfyrJFX7F4wZfccuNNHHrwIc7W2c722fpt4zXYXKKvlGnErgq78q8YZGtmEXe132Xw5BqQ3ZWtiUlleCDb1fkgV7vlevGn3pfrmuwyvdZts6+x4/71Y7gp95ebY/fcsrof7/Vxzj0O9Z36Y7/Iu68P//SVOrWf+mPf2DvbvGwMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGgDEwUBiQdUj3eq7ks9cQ13Q++3oVdntqpf6eirzrM0q3J3V7tON18bkntlycLAu+5f7/SlIuqaLrW6s+rxdJfp8Xn5N8rg7xU1Eug6+K2nRNRugVsbemBonyTaVE6JXIXUmJlcm9LfPXRd6MwCsCazSRJCaRwQkReKPOFs8i+IrIKykTzbv+RN5EKkU0Fqc2VUs6lqImnnJE6ngySXRlNHFm62IVqCVqVtomba1JxNk8GmV8ZRW7VITY0x9lb3+MKeVhppSH2Kc8yMSqNP749nhqJuOp3QtP3d4Mrp3M0LrJDK3dncL0dgTSWxJNjiCeqCUWl2fHnC2uR4i/JTI6Fu8SeEU8z2x7rdG7q7M9EXklilfaJozJoMg1OLMHY65jN5NuXjW/KVi3D9SPWibtV4Z0m22xgUDAiRDUKEH39e58Lv+t6Xyue6zM/pDoKwwIvzrnZP+gb+hjndN0TIntK35am/eQ997QvtuQz1Ne1sYndq3NecaAMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGQO8yoGu7sl7X3fqgrrl2Z7Pv66m4W1ZWhiS5X0TesWPHrnG75p4Isevzml4XeVX4FSHY6QyJ2vRlhF1/eeajyKs6qRyfrxyf14/P6yMWjTJi+HBna19H5E2nSCTjpFIJ0kmJ5E043+3VrZdFhBRxyzmORYlLSsSIxONEEyknxRIinIrIG1kp9K5OvOyNc04UcTJFdSRCKhEjGQuvfLdYQgRoEVrjTorGM3m12h5pa1q+RxypZkR1iFHhKJtVR9kiHGFsuJotwiFGhKNE4iOoSo6hIjmGqtQYgqnRBFObE0htRig1kkgs7Wx/7bxTQvySdMRe2fo6LRHTsaiTnG8exxLEYyp8y1bNq7ZrzvaLbsvstu4oXrlexEUZPDIouhtsPSkXXjTphCnHmh/oVtuuVtsrIq74X7bClj3hJUnefSzn5ToVfNVv2XVpnWrXdF6vM9u7P2Dmz97xp/ArP8Qy/2T/oG/sY5nzdBzm6m/9Rxm5zm3MMvXpxvbf+ny+9M3G9LE9u3fGv/nR/GgMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGQN9kQHWH7qzqRbIGKPnu1gL1OrG56nKfd9eTLfaqqJtt5bkDXuQtl+jMrqjdXFG9IuiKc90O/O8OkU5aJfJKxK8scIvQmUynSaZTJEXgTSe/JvK6BUe51hF3YxHisQiJZOabuyJqZq6LkUyKECwib0bozWzfrGJm79uERusmE8QTIjxHicajjrirkbQq8qoVkTeZElF7lZAt3/R13jWZEYSlPcl4lJTTjrDTnozwLRHPKWebazmW5NSTSpJKyrkEUdnCWoTleJJYLLMdtmx/nZbrJXo4lnBSoks0l3skuX3tzrsFXREV5V8i6Pd3w+HwSoFXB2P2oFrTca6BuSlNzNntF3+5y6QvRMCVqHdJ+v1jtVKmwq9YuV7GVnY9Wqfbt3KdJne55fvmD6P1S6ZflGWxwvl//964d5HYuPlc41D7Ucae5vuSFb/2ZZ/2xrtJv/Qln9u72JxrDBgDxoAxYAwYA8aAMWAMGAPGgDFgDBgDxoAxMJAYcK/h6jruuqzlyj2a3HWqr9xluZ6jYq+Ku6WlpU6woh7LWmO/EXm1sdr47qxeJ1a3a16TyOvuHHW42syCrB+v14/fV065z0+5O+q3ooJINEJtrQhYSWpSKWdb4biIkF3iYzqdcqJNJVK3tkaiUMOIwBqPi3AZIR2vJhYJkhKh1YmmzQjB8s1et2C5PvISsZuoSRNOJAlLVHFStolOrNyqeZUInRGZI9GoI9bJNru6HbWIsPFYgkQ0I8Amo7GuLZWlrSJuS5SyiLqpVSJtPEEylSaRSBNPpoiJ0JxKEBfrbActwnGCRCzuRPLWpWoy98blOEEiEqUmKb7uum6lWL5qa2mpR0VeFRWlT1Tc1X5397XmV2fdjOXKd8fmQCnP1WYpc/szGAw6vle/q5X+kD7QsSFWyuS8RvaK8Ct9pyKS+3luH6rAq9Z9zvL2R0VfYsDNsHtu6Q3Bb33XIe/rfv++5Ndc7yLvur59srHrlz7J1XYrs3nPGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjAFjwBjoOQPudc9ceV3LXd16oF4jVq/TMnedq+sXvU7v03rE6i60IuyKyOtOcr4fibzlzkLz6hwh59QZYlXkla2ZVejVbZrFev1d2zO7nO/z+fGXl+P3Z1LGmZlI3lwir9RRWlZKMBSgpiZFXW0tI7u2cpbv2lZHE4hQmo6HSMWDxBJRYrKlcypFKhphRDzI8FglNfEgNUkRRCOIuKspI+x2H6kqQnEmrWOkbyJKOB6nMlZHZWw4oViKSDxJOJ4k0lV3ZptpebdMkqhk+Q5xRoyNO5G5yWQt4eoYyWiculTaidiNRkXclYjcFJFYHdFYHamYCL2ZckfgjaeJx0VYli2ao0SjIVKJjMgtgnlmm+YYkbDck/FZnUQ8R6KOqCzbOcszHEHYJfQ67yZbSafTKwVEeW8VDnWwuK30tfu4u7ybsVz5NTHa38+726w+kjLxrYi74nPdu13ybmFXBV61Gb4z0b5usVcEX7lXBXl9Zi7faZ/mOmdlPf9BM1/1vq+UW7E6VjK/KRs3Qndt30HfXay0xc1KXxt/8n5r277+dr30g7sPLN/7Y9d8aj41BowBY8AYMAaMAWPAGDAGjAFjwBgwBowBY2DTYcC9jutey9V10dWtH+o1uay73tXxpNflqkOerZG7boFX8nJuwIi84gRxkjpDrGzFrKKuiLGOIOvzUtqVVORd1UF+vD4/Zd5M5K7XK/eIGLwakdfr7VLSSygtLSYaDjvbB6draoilaqmI1lIZipAKFJAIFOAPRymtThAKVFET8jMyVExtVT411T6Gp2LINsSxWKIriXCbifjNLeSqwKt27YRe2WJZtlWOxFJ4o2MojWxBRTBNIBilIhShIhQmGAwRDkkKUh0MZGwoSDgccr5DXB2pJppMEogmqKyOEYlEqQ6GCFaHiXZtrRwXH1RvQXloDKFQnIhTX5hIdZRwKEJ1KEKoOkw4HCBaXUq0uoR4LEQ0GiYZq3aeGYimqI6mqAkHSQfKSUZEcE45EcSZSOGM0OtsHe18HzkjpItQKOJuKBRaGWmqjOQaMFKm5x2GXOH0er37fK786gZrfz+X3V71iQg9ItyKv0WglWhcEW1VxF2TdYu+KvZKHVKXnBOxV3yn/dPf/Wjvv2n8gaDjRceJ2FW/N/1L6NX3do9BaZ+y7M5r2caw8h76rgPVSh9sDN/aMzeNecv62frZGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGNhUGcq3frs0arlyrSevqzq7Op3qP1iVWyvTYvW2zW+iV9c9+I/JWlq+K5PVXBimtijupvDJARWUV3ooQ/soAgfIiQuWFVJb78Kte+ZwAACAASURBVJZXUVheTb4vTLE3jNcboLKslIqyYkq95ZT5K6n0ep3k81VR5g/g9Vfi9Zbh9xY4yecvWyny+nwVeL3leH2VlPrKKRVBWEKky7wUl0lEbxkVpflUeYsIhiPEa2r5619fgvZ6rvjh2SQCRcydO4uW9lZm3DWD5iWLOOWgXRkdyqcmVEZtIrJS5M2IuyLwrkoasZpMyPdrVfxVu7po39zir/MdXdk6OlXLH+9/lgagtQ3a2qChA1o6gPYmaG+EzjagE/lv7rx5RBIpguEw8ViQ6nAl/kiECTvtysJFiznyyKMpLQ9QEYpSXRWkOpCiKrY9H33ZVYVTV1e+HeiAtk5oAVY0fsGWWyUpryhx6q9O1FISTBCo24q3P1zAViNqSVd4CVWGiATj1AZDDA+FSEfle8arvvGbTsv22TUEAkEnwlQHg3tgaJnb6mBaF7u6Qdqfz2X7QvylZdIu2bpbxF0VeMWujcArArDzzep43KlLBWGpQ0ReTXIcCARWCr36DmKz/dvXoguz38+OB/4fSsqnzi8DSXDUOUDbpsd9gWvx+0Dyda62iL/7gq/tHQb+PGZ9bH1sDBgDxoAxYAwYA8aAMWAMGAPGgDFgDBgDA4UBt2YgeUnZa7i63plrTS5Xma6Laj1uuy5+y75fj+XZubZtlvJ+I/L6vWWU+yXK1ktxZYzf3DuPR1/9jKKyAMUlXvIq0lx6xS9ZMP9FRkc9BMtLGFIc4Pyrb+eVDzoIJnfllRfehaZ6R3Rt7YDzL7yMYGEBwYICAqE6Pl7YKnojdDbx4wtPJFDmodxf0BXNK6JwFSX+agq8ISbuvCdfrWiiuaWN9k5Y3AQHH3Yk0RIPoSIPQ4rLuOQnP+Lt525jdLmHQLmPq372M959bjrJAg/bbr8bC5e0Me2QvRnl95AO+ZztmmtrRLSVaF5JIn5pNG8NyUQd6XiaVKxri+KEREquWxSvCmnJRMwR1qojKaoqo0SDUQJVUYb6Y9w1435+9d3jGFvgIVKW7whslcEglZEE/uhIpt/7ILQsBBY5Am1jl24rPlwugq1kOuHF5/5KILYbs1/8lJpgkPI8D0Vl1fir6qguCxH0hims2oxBgVoeeP5JUlvGKA948YbifO/K2/kYkKdI/XSIItziCMNScMDwEWzrK3OE3rq64dTU1pJK1xAKxfD7A/h85c6Cvw5OHXRu6z7nzusAWpNdl8Ha1+/prs3iH5k4xOrWzO7IXYm6VbbWxarYK/WIqCtJxWN5juR7soVzX/evvd/A/ONIxo30rVidS3L9+Pf3Mvc8oO0Uq+3fmHzLO/R3/67p/cXXG9PH9uyBOX9Zv1q/GgPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGwEBnQMVdFXzd67i65rmmtTk9r+uhUkdvrYtqXdlW380t9EoAqrxLvxF55dusAVHWKysZ5o+y8/E/Zu77ncSrg3jzBzGkcgR/efVd2ps+59gDt6W0pBBPYQW/vncml9/2FJ6S8bww6z3O2G930kM9TJy4M59/2cDJ++1JTckQPvn0S753wY/IKyil0l/ES7PvZuLYKvze/JUib7G/mryKEexzxOk0NLVw6EH7UlJUSFGJn3E77MvShlYu+8Fx+IZ58BT7uW3GPfzlxnNID/bgLQvwpxkPMeum/2HEEA+lJZX4K0cw3F/CmMpCEqGQs22yfIs3EQuRigUYnoqTTtYRjw8nFq0lHkmQDldTGwmTiiWc797m3sY5d+RuLtEtGo04Iq+IoqGqaiI+L77CQgr9EWY9+zy7xMoYOchDoDiP0tIiIpWFBCpLKapKcduMP/OzC6YRKPDwhz/ewh6HHcGQvALyirycf9m1nHHBZZSVlOItDlDk35Y5cxfxxH0Pk6gsZ+yEXXnlnx+SqE5RUljBXkd+lwdeeZN75v6Fis1C5FWUM7SqjtOuvpfD/vcWEtsfxtx//oe6cIBgwWAClVFeenouB8bj7FA4jC1iESfiM5ZIEAhW4/NVdqX/FnllQPQkZQ+k7o4H4sTnbqv6Sspk8lNxV767q1G7IsbqlsvfVOhVTrU+OVax17Zwtj80+tJ4c/8xoGNGx4v+2A90K+2VNopVH4jdWP0kz94UfL6x/GvPtTnYGDAGjAFjwBgwBowBY8AYMAaMAWPAGDAGjAFjoL8zoOu6a7uWq9e710E13xs+0bqyrT5X1j1162axctxvRN5xY8ey+WabEYlGGeYNk9juWD5eDtP22ZJEnofB5XU8/yE8Mud1zrrgUjwFfoZ4K3jy1efY4eCD8RSNYvZz7/Cdvbdm5GAPeYPzuWfGn3n8hiuYMtrL22/OwR8uI69gGCVFRXiLh+Evy8fnFTW8HK+/nDxfHE90V95dBJefexo1BR4qCgdRUlaJJz/M/oceS0PD2ySHF+MpDXHDvY9x3w2XUOXxMGRwBffOeJJHrruQpMdD6eACAqUJEnmF1JZJZyQoD48iGI4Rry5nZHUBNRXFxIIjCFdvQSAQI1xVzohwKbWBIhKhIDXJGmeLYhXF1sWmUkmqo0kqoiP48U+uhM4GaF2UiZZ1oprbnXxrq+yr3MIT15/P5l4PJb5ybrvrPha+Mxc6PqOFDuozOy870dCSb5L7gdtuvYv8sok888JyTjnpQq6/7g4uuvRKfnvj7Tz8l5l4ikq4/v5HmXrpJdz/8mOUjAzhKQ3j8W3OtMtu5dgfXIOnIMyUg47gtVkP4fd4KCryMXfWy+wRDTOuYDC1AREVKiivkC21fZSWlnxtoV8Hweps9sCRQZldluu4NwZvX6rD3Ua3v2TiE+FVI2vFyrFG32aizzNR6OvCYnf3yHbQek7EXt2+Wawcr24LZ3db+pKP7V36/x9Cwpb0o5sxHS8DXWTsrn3Sfrc/Ngbn8vzu3m+glIufN4Zv7Zn9f96yPrQ+NAaMAWPAGDAGjAFjwBgwBowBY8AYMAaMgU2RAfeapeZlja2n64W67qv35rK94ddc9UqZPj/byvuPHj3aEXolKK+urg6xfTF5xo4Zw1Zjt2SrceMIpTZjcHA8L7z6FteetQ/JwR72PPxkZvx1GdMuu5P7Z7+NZ1g5W201miWLXiOe9uIpTDP7hf9wxuStSXs8FAzJ45677+OR635EbYGHz798g6nnnIZn6BAGDx5CaeEQfMXDKC/zUu4rx+/zM8yfYNK3fsaL8zsZ5R3C8EEeKgs9TvTv0IIwxeUR3v3s7+x26I78csZjLHUkzk9g6RvMnvX3zBbDbfNh2b849vATWLoQdhuxFemCMiLhGj5YsIxW554W7r7hGtJVPlLx0XzwkUim0Na8grtvvoZUsIhIVQXxSPwbi7zRWIxQLEVpeBSXXHY1D996DTUlHiL+IsqKiqgo81PuraLIF+CKS8/jxRvOYGKph7KyQm6/6x5+fvZRhDwebrrjdnY/5Bg8niEMGpzPD354BWeffwmDBw9i6DAvw8om8fQLjfj945l+x+M01LcSS6a54LJfcuM9DzJr3hyC6XIenPcAhSOq2eWEs/gU+ApY0mUd0bh9IXR8RYt8Ili2g65fwSdPPkystJiyslJKSkvx+X34y71d6etRu90NEinPHoT6rzmyywfScXf+kMlCJw9pb67v7mrErlvczc6rONubVp6rkcMi9I4cOdJ5P+kvSfLu2kfu9mmZWftD5psy4ObKPVb0R7anfxwMxOvUB24f6dj8pn7vyf3y3IHo1+w2STt74g+7xuY7Y8AYMAaMAWPAGDAGjAFjwBgwBowBY8AYMAaMgU2dAfdapa5fis1ec8s+dl/rrmN9+dP9jJ7k5f36jcg7cvgIRgwfzpgtxpAcPoaS8FguuOgy3pl1KxUeD9fNuI/DL7qOiknfYtYbKwiWV3PqATswf+Y1TiStZ2iEZ59/n9P22ZGYx8OkCduwZGk9J03ZBp/Hw+TDj+Ez4IsWSNWlqcj3EC7yUFVSSMBXQdDnJd8fZstvXcysDyHt85LyePAVDKKo1EteYRVDSip49vUXOfbc0/EM8zP97hk89YezqB3sIX9YoSMqP339uc7zh0+YzH++gu0T45jgL2f5F+9wwy2/oNiXh7+qkvLyCLH4SD74fAEHHHaY893hysoq5r70PBdcdB6h6pAjbMn3ezOp51s0i+AmYpwIvNFEnGC8huLqkVx82VXce+PPqR7qwV84mJKiEgrzCigt8VNUFuJnPzyPF68/nQklHkq9w7hj+u18b8pmJDwe7ph+N4u7vsnrfIi3vYOLf/A/znbNeUXVDPPvwFPPN+IrHscJh36bL95+m5C/Ck/h5jz/8ic88IcrCQzx8MSLf6KwLoSnpApPSYg77p3Bqeedx6Qjvs1nLTAhUe7056C8SmY/8xq7V1QxzuOhetgwyn1+fOV+vOU+fOVeJ/nLey7yZg+a9TVQN2a92W3UY/dkJROZhvrL929FUJVtksWquNoTgTdb8F3bY+XUfV+2WCzRxPKvU8TKOXlfbVMuuzF9b8/un39MqUApVvtQ2coeN9l/BGzKx+Ib9ZP6bUNYeeZA9btuxSLtk3ZuCH/aM/rnvGX9Zv1mDBgDxoAxYAwYA8aAMWAMGAPGgDFgDBgDxsCqXRjXdh3Xff2GWOfUdVSx2c9e07GKvBIM16cjeVXkHTFyJKnhm1MaGM42O+7Fe/+aTToymGfnzWLbg47GUzKSR+Z9wKF77MZLt1/J3284k1rZLnlohOfnfQytX0HrR7Q3NXDoYUfi9XgoHuTBU1iOx5vgnMuupbGjg5dfuJeqEg8VpXkEfOUEfWXke4OMO+Z/mPNhG7GifGfbZV+BB19VkGElUQaXBHj65afYef+d8Awu5E/Tb2P29ac537TNyxvGjLvvYdb1Zzkib2LS/ryxGLas2Izz992Xr/7zPMnUEEr9eZRVBin0xTj4qJPooJU26mlrbaWzawvkm+66i4pgkHAkgnzDd11EXkdAS8RXirxFjsj7c+ATaHsPOurplAd2QHsnNDuxxB08//vT2WKYh8KiIdxx592ctc9ER+weMqwQT34FnsF55A0dSuFgD6V5g/EV55FfWMGgskk8M6+ZWHASn7/zFX/8/Y384KwLKSgZy6efwOvPPEGwwMPjz99HcV01njwfU444kffnv055oBTPsADx8Xvz1ivzSBbnk5cfZO4zrzI5UMTWHg/hYYO6RF4fXkfgFaFXInpN5HVP5u7Jwj1hqCgiE4ZcL1sgq7ir2yOrsKtCq1t87S6v166r7a5eKZc65Z00slcmMHlXOZbvBnfX7lzl7jLL2x9A3THgHj/uH1cdP2Z9XxNY1Uduv3Xn294ql2cN1H7Qf3wjfpV29pbPrB6b84wBY8AYMAaMAWPAGDAGjAFjwBgwBowBY8AYMAYGEgO6Hqnrk2JlzVBtrvVD97WS1zrcdn35yP2M7PdY03G/E3mHjxhOsmYkgcgovOGR/OPTBUw+cn/+8/qThP0ePENKuH76g/zi/NNZ+OwfuWD3tCPGDslLMOf5dzlz73GM9nioGOahoKCQ4sICSoqGUVTiIa9wKEOLqiipivH+kvl896KpFPvyKS/3UuH3UuAN4anejne+gCvOPJqaQR7K8z2UlMv3Y8ewzxGnQ/1bbJH04Bnk4Z7pt/Dc9dMYMcjDkPx8ps+4l1nXn03c4yE5aT9H5J1QvSVn7bW3I/IGAh6G5Q+moMRPWWUVhxxxIO//5xXCVUMY7PFQWFxGvr+KYb4KysorCUdWfat0nUW0rkjegurhXHrZZTzy/85kVJ6HUImHQCBEdShMeTDG4IoUP7z4ImZf/x1GejxU+YPMfu5NfvODi2HhQmeb6RWypXQ7dLZndlLupJ2Lzj6esvwhFFZsw9MvreCxR57j1htvJ780wXPz3uXRh2Zy9lkXct0dj7PnUVP58/OPUVpbTXjSfry/TJTlBmj5EqlbIoVbRXiWzwNLal7Bb0/dwenPUIGHcr8fvyPsdom7IvCW5x6M7kHTXb4nA9Yd5af5nty3sa7JbqtMEO4JTd5LWFKBV6wcy3bNKqwqa6sTYPWcXruuVuvJZaVOLRdhV6J5JeJYkuTlnaV96mv3ZKh+kDLN63Vm7Q8aZUDZECtlyovYNf1R4B5Xm2pex5z6UY5lnlR/qp9700rdA93f4sfe9JnVZXOeMWAMGAPGgDFgDBgDxoAxYAwYA8aAMWAMGAPGwEBiQNcje7pOqOuYavX+DeUTfZ5YfYeeWLm+34i8I7q2axaRd8So0URiIxjqT/CbR55n+tNP8/AtlxAfKiLvEPY79CjeeekpPp5zL9v4PAQ8HvKKa5k15w3OmDyOGhEp8zwUl5RQUOJl0vbb88STD1BQOITBQ70U+at5+/N/s8fB21NUNgy/r4xyfxnFZVV4/j975x0fR3WuYYGNbVlld2d2V81NlrSr4kYPkARIQggJIclNuCEJpBFfIEAC3FBC4BIghBqMIXSDu2XZsmTJ3bh33GXjRjFukmUbVwwu2H7v/Wb02eO5q2JbK6u8f5zfNzM7O7tzznNmVufRdyYhjL/+/RXg4Fbcev0F8LaNwXntDWRf/lNs3XsMT/3lJgTPicF557VCYf5ATHnzbnQ9NwbntI3F4IJRmPTmg0j9v+mNu17yPazbCZwfzEZe21js2/Yh7r2/N2JiYuAPJOOppx5H0B+HndvX44H/vgOxbVuhdatz8faAfgh3y4HH57MEbKdOnS0Jd9oSTbIeO2WgXUoYjz7xJMa8dp+VmRtsHwPT8MPj8SHRlOmTk/DIYw9j+ht3IysmBoY3DdPnb0ZnIwNmGw+mz12A6/7jRpwb0w7t2yZi9sKF6Pfuq+jkFWF8HhKTvob1lcBX+w8js2MHxLROwvU//yMG9u+Pc1u3QZdL/wPT1u3GjGWzYGYEERPbBVffeBcWTi9FYkwM3hlWgN/+95No5cnA7Hnr0MHogL4P34WX/3gJss6JQVJ7lbz6LF6vJX1N0zgu8ZwdpS7LdenAKnadsS7va+h99OIgnyvLzigXOtmWlpZ2fEpmnZ7ZyZUIVfe6StbqonP/01mu7rj6XSK9LoLXmX2cnJx8kvTRi6ObgYZuE35e4//h5GREuZH+IsvOWNcfCy1tP2edaX1Jncp2idHoA3Lc5l7P0aq7aLQHj9n4r3NsI7YRGSADZIAMkAEyQAbIABkgA2SADJABMtBcGJBxMynuccmaxgt1Xx2z1GM0ZJ3oZzq/u/N7Vbcs+zc9yRsKIRQKo3PnDPhSu+I7t9yNXUeBJ/58I7JiY5Di8yEpuQsqK7dg4bypMGRq4ZjWOC+hK6bNKsMt378CnSXrM+5cJCQmIs7jQ1tPEA899TJ2H7GnJT506AAeue/n8LeNgRnfGn6PFwFfAryeRLSRZ8W29uHiy76FfZ8fwpEjwFdHj2HfwcO44ac/QvvzYpDYLgaxsR6MGpaPCe88jo7tYtAu0YeB+aNQ+MaTSGkXg9BFV2PDZ8CFaV2tZ8xeetlVqNx/xJ6S+fO9uCiUAX9sHC667Luo3HvU2o6jn+OxB36P9OTzkBr0omOHDujcKfKzeHUa25rFWmd06NgJKelhtEnJwUNPPAt8VQkc2mhNDH1U0nLtGZux/6idVTvj9XssSf7IE8+idN4niIlph5iYtmjnScGseWXW/scOHsaNP/kePO1ikBYbg0C7dojzno9Zc7chtW2idb6tW8WiVbwf5yV4EdMmDjHnJCAmNgHTpxcitbMHMa28uPLG32P+rGLEt4rBW8OG4nd/eQLn+cKYNXct0swUvPjXO/H8nVcjvbWdUW1n8sqzeBNhmCIRfPAbBvyG3bEF+IbsmI3ps/TcJWrR7+d87m4oFLIyYWvmJjJzjeU9wr5+F5G9IqxlXaag1ou586Ko9aF1pPXC2HJ/3CgLyobwouwwnjwl86nWh/Y9rVtnrI8+J8c71e/U1PaXc6yPuuIxWu41jm3PticDZIAMkAEyQAbIABkgA2SADJABMkAGGgMDNY0NSmJdXb+j8zg6/liXMV3nvs5jnK3xN/d3kHXnd3SPY8rrTUbyinzSEg6FrIzDpLQuaJ8aRjtfElLiYhA2YpAeDCIl2BHeYBLaJSbA8JmWcG3VPhltYk3IM3QD7WPgi28Dv9+E4Q8g1puEGE8XnOvLwHkJAfh9cUhqE4O0tjHwt2+NgMeHoC8BPk8cvIaBVu19iGmXgtaeLlZ2b0JCPBIS26BN2xgketohPj4O7dv54E/wIdgmBr7WMWjdNh5t47ww2sXA1y4G58YZaN0+CG/MOfDFtEJMTCLOSUhDTKvzkNiuDQLntYa3dXuc0zYVMW2T4fEaSPPHIpzWGpkprZDZORkZ6V2taWklc1EklmY1quCS6BRezu32skjezgh0SEdschYe/PuzGPTGS0iLj0GykYi0lFSrEwWSkuDx+/Hko3/BxLceRXrbGEycPhsZX7sGn2zfjS+PAYeOAQ8++ATanNMWyV4PdlV8CGAPcGQ/ls6aj+S0i7Fw4RZkepPQJS4WRkKC9Szj+EAqfvbrW6ue+Qts+ngxOnXyYdLiFdhtKePPgaM78AWOycTN1mdZvvmwPCx4D3DwE+z+aCbM+FYwDC8M0wPTKip4DQTMlnnBjnRBcG6TC6RMaSz8SNGpmf8/J41b6tb0ffWfHfR5vXKOktnrnjJW6qWuNwzu17z6k2bhS7s6+4fePN03Tq6fmeR11p/WsdS7LNdH39JjyfGcn9Wclnm9al7XoPrgnscgE2SADJABMkAGyAAZIANkgAyQATJABshAU2TAOR7r/v51kbzO9zvHBXXcsboxQX1dovMY7u/Q0OvO76LLzu/qPh/Zp8lK3qzMTHTunA4Rvf7kVHRINpDZMQnpIq26ZCA1LQ3JKSno2iXdWvf5goiNjUdcu9YwPbEwE+MRMHzWlL5xCYloG+9Du0QDsfEJiI9vB1/cOQgkngczMQ5B00CyXzJC7We9xnsNtEn0o02CibgEHzweLxIT46z3JSS0h8fjgeELwNM+Ef64WPjj2yMx3oeEOA887dvAE9cGcfGJiIvzwRObYJXYOA/aJ/gQHxePxNhYeGNjEdemHdq2SUBcnIH2se0RH3sejMTWSA0moFMH+9ykHvQZpCrrNIrQUsmlUYWYLYQ7WZK3Q5cM+JI6wutPRrLfh4CnvXXOSUlJCASDCCQnI87jhZxbIP4cS1K3i4tD67hEtEtIQBt5rnFcAuLbxSGxXTsYUn/tz0GSpx1SfQaSfcnweTrAm5iCQIIXyV4vUgJJSEnpiEByB3jMJLRqF2c9t7ht21Zo0641zm2fYJV2seehnTwrObY9WscmIObctjivTSxanXsO2rc9x5L2kjHsSRQB74Xf9CBgeBEwDAQM0y4tTPJKx9aLjyzrhUq26QVBpmYWTnRaY1mu+R8CmqboVe61T+j5Sj8Q2av1o/XF2HJ/DAkLWrSfuG+aXK9/wat1LVH7n7SDLquEr8uPOnmP9mk5XnNtL2f9aD0xttxrF9uebU8GyAAZIANkgAyQATJABsgAGSADZIAMNFUGdDw20nhXpPFA5/7OcUVdrut4oOyvx4r0OWerPvU7OaOem0T3+cl+TUrySjaeZPNKJq+UzIwMdKmamrVDx47ompFhiSuZwjizawbCWVnICYWQl52NbMn+7dwZfr8Bw+uB6fUgJRCA4RNx64XXl2gVjycBUmTdMDzweT0I+A0EA6YV5RmvhmnAaxpI8Hrg9frg89qV6/EkWpVs+Awrg9j0mTA9hlWMRANSvAke+BK9dvHIe037ubeJiUhMTIAnMRHx7dujfWwsEkT4xsUhrm1ba1tiQhy8nnh45ftJlrLXi04dO1pyTuSV1I9mLOo0tSK3RPaq8JWoolee59slPR0dO3VGMMnObkxOSoJpGNbUtklJyZYoT0pJQVCea2oYMP0yFaYHgYDfqhuZEtn0eZCaFLBEeLLphZQOyX50SA4iLSkNqUkdkZKUBr8RQHJSCpKCSfAb8n45dwOJHgMJHgPt4xPRrn0c2rSNtSR423bt0T4+ARJj4+IRG2vXS7t2bdE2ti1i27dDXPv2kPVEb6LVjn5TBK9D8pr+FpPJ6+z47mXp/LJN5L6wIf1IospdlaEn2GiaUrem7y/nKOcr561F9peLuPOiLvV0ti7i/NyG/UHm7ieyXtNN030T5fqZSV/3DxNnP9S+IP1Ti26rKTrb8FTbR/5By1lO9f0Nsb/WUU11wNca9jrC+mZ9kwEyQAbIABkgA2SADJABMkAGyAAZIANk4PQYcI7Puuswknx17n8647jO98ix5DN17FGj+3s05Lrz/HTZ+Z3d44+yT5OSvDpdsxXDIUtoOqWvZLWGwva0ziJ1RfDmZmUhLxxCj2556NmzO7rl5SIjPR1JwaAlM0Va+gN+mH7juOj1GTLlr/1MV3nOq0zrrEWEb0CyXf0if70wfV6I1DUNgThgiTRb8oroNWBK8frs4jHh9wZheoJ29Pmr3i8y2WtnBIs4NnxW8VmZxvIZnhPF64HfZ3+u/dm2pJZ9pbHl+aoyBa/IXLfQEgEsWb8iuE5k/6YjvUsXdOncyRLmnbt0Qecu6eiS3hXpXaSkW9NCS51JkQxQKR1S09CpQxo6paWic1oKOndMRZdOaVbs1DHNel6wTPcs2cBSv4bIE8OER8Su17TEbqLHhwSvF/GJHiQmSjb0ieJJ9EJKovVaIjyJCZYET0xMREKix3qecoJs8ybaUt4TD8PnsUSvz/RZ0zbL1M12u53eBaYhO++ZfJZ2dneUY8o26fiyLEJT5aa0v4r/5pjBW5PslfPWItcP6RfSb/SmIXV2Ju3B9za+/qY3aI3aRtpnarpRum+cXD8zsVtb/WlbaNtoW51KlPfKcfSzGru41e/pjvq9dbuzbk6lPrhv47smsU3YJmSADJABMkAGyAAZIANkgAyQATJABsgAGag7AzpWqFHHyXTcrLao+0vUY0h0jxef7TZxfjddUc/UDwAAIABJREFUdn5393nKPk1T8orgDYeQGcqypK5k9YrUDWWJ4M1GKBy2Mn1zQiJ4w1bpnpeD7iJ6u3dH927dkJmZgY4dO8AfCBzPTrWe6WpNyeyFLQrt57oGJRvUL8BJNq+JoOlDkulBkpU1KtM4+0+SvCpcRRCbPp+VcStZt4bHgN+bBNOTBFNkr2T6WgI30ZK8Xq8BjwxMG4ZVLMkrz5k1EmEaCfD7EqwMZL+I5yrRezwT2XvywLvAqIAGg0FLzEoWp2b7ahTpl5WZgVBmVytmZGYhI1OyPLOQlZllZUtndc1AqGs6QpIF2TUTmRmZx8VvpsjfLp3RtUsndE3vhOQkybqSurIfii3C3GskwuPzWOcmYtdbJXo9PgMewy5ew4TXJ9MJS3Z1oKpuDPgMu0g9SvH5TMi+9naRudIpNXtXnsnrg8+UmGg9m1cyt892x2yIz9cOL1E7vXR4+WyR/lY7V0l+ze52i1Dhw72tOa+L3BbZLX1BpK+cv07hrPXZEG3Hz6j7zby+6krb19lfpN+4b5JcP/m+0pD1oT+4TqfNtV0jfV8VpxIjvd5Yt+l1Xc5N6kTu76dTN3xPw19vWOesczJABsgAGSADZIAMkAEyQAbIABkgA2SADJwaAzoGJlHH+nR8zBnrOpan79HjaWxs7aLfyxn1u0t0n6/s1+wkbziUi3AoB9mhTKvkhMLICWUjJxxGTjiEbnnd0LNHT/TsmYe8PBHCWZYA9cszXKsydn2mAY/fB6/pQ9AwkGL4IaJX9rFEr+lHklWCCJrJCJgyxbENqUznLNM/21m4tphUQSlZvX4re9dfleUrslYyc+1MXnvqZ3uqZ8NnVu0jWbsiedvDNOKsqab9lhyuEsgiPiXz1yV5ZV0HsyX7VYtus/f3IZgsUzGnICU5GWkpKUhJTUNqWgd06pBqZelKxq5VUpKRlpyElKQke7plS3r7rc+2z9XOXJaMZJkOW56R60lsD483Dh5vPGQqa3nNrgv7HCWzV4RtomEizjQRbwbg9SXD8CXBb2VBey0JLPsEvHaRerEkr09kpkydbWdc28/gNSyxa5qJCBhVz+a12vTULiCNrWNH+j7SeXW7s8PLsnR2eU3krkhMZ1HBq9m7TrHrXG5uclfOzV2kDrRIvYjsFRku+8k/Rmj9Mjb9/qN9RNtS+oj2Fb1JRrqGctvZlbzaTtpu7nbU7dVFbVuNzvZsjJK3uu+k9eA8f0repn9dqo5bbmfbkgEyQAbIABkgA2SADJABMkAGyAAZIAMtnQEdB4s0rucc46tuWd+nUY/njo2tnt3fT9b1HCS6z1deb9KSV7J5ZXpmfUZvdigbbskr2+wi2b5ZCIfCCGdnIzc3jB4989C9Rzd0797DykyVZ8ValWYaSBTJ65eMXbNK8ppVklcuMAEETRG8SUjypyDoT67KXJX/KrClo8he6/m9ItxEDltFjiGyWPaT11XyypTP9nTLIjHtDF+JMt2zyFyRvHEwjfiqdfs1nRba2cjuhlapG3kfHxJ9JiSjVgSsThnt8XjhEykrzxiWZWu6aa+VRSzfx/quVVJZMo8TPfZU07KfFJG89rOD42AYCVYmsk53HZQUeHm2ryFTOAdgmH54Ikhe+3M8xyWv35K8kjEt77HfZwNv121ARLBVrx74rSxrabsT4r6xddYz/T5y7nIMuw5OLMs2kbsiLUXuynTEIi5F2sp2iSo2Zdkpdp3LzV3y6vnpOUudSH1pvUmUKZy1fjXW1G6ULo33x5e2n/s6qNdLje6bJNfPnuSVune2l7ahxJr6ofM153tkWY/XWNvVKXnlu7q/v/PceL1pvNcbZztxme1EBsgAGSADZIAMkAEyQAbIABkgA2SADJCB6hmQMa5I41w6Lnaq43g6/lfb2FpjbRM9b2d0npO7PmS/pil5ZWrmKsErmbhhKSGRveEqoWtP1xwOZSHb2ibbZdnezxLD2WGEskPIyc1FXrfu6NmjF3r1Oh/yTNqklGR45Bm3pspZiU55K4PMAQTMAPxSZNmaylmkou5rS94T0lfeL6+J6JXphu0MXHmurkzZ7LWmM7anj1RZaglTS6rKlM0eWNNJW+snZ/vW1Mgqed2Nb71HpoX2iv0XOSsZuDKgL9tE+trC1iPTK3t88Hk8VvF6PMczhEUGO4sexxbGkp2caAlqQyR1lfQ2LcErWcoy4C7Fno7ZnqJanh8rn21LZ0smG5KtK2JcSqBK8orctAWnCnQRvFbdWpm7BoKmXezpmqW96i4GGmMHd3bq6pblYijyUgSlFJW5zqhyU6NKTl1v6VGf1avTmcu6TOEsdSv1rmw4l3UbY/U367NZN9JWNV0j3ddGrp9dsRup/rX99NonPOlyXftiTRw45Wqkz2/obXK+dT2vs9m3+NmN85rHdmG7kAEyQAbIABkgA2SADJABMkAGyAAZIANNlQEd89PxQOe4XE1jeLq/Rj1OU6sH/d7OqOck0Vkfsiz7NV3JK6LXkr3yXN4sa1kzet1RntdrC94TktfKAs7ORig7G9lVord7j57o3rOntS21QwdL9qqMlSmYbWEr8taeB1yiDYk+q1fEoonASVmWdsauyl6RkqZhwjCliKyVLF6Z3tkLb9U0z85Gi7xsVAnSKklalQUcaV93o7v3kdc1i1fFropeiSJ5ReRKRu/Jgldkr8gAWxLb8WQ5YIljnweGVexMZakzS+xa01HbU1Lrs4s1S1jWtZyo6xPPPdbn/Vp1r3JXo+PZyZZwt57J2/Qlr5yr1oW0obKnHVlkrWSiStauRJGTLV3Yns75O4W4iHKpT82E1uf1Sv03tZtDS/2+9vXGvvZIu7mvh1w/+Zrd2OtD7196LdTrYF34dr7HycXZPmflUs9N4qmcV13OnfvwDzsyQAbIABkgA2SADJABMkAGyAAZIANkgAyQgcbMwJmM3bnH1ZzHasznHOm7Ob+7LjvPzz2WKfs0fcmrstfK5D0xdbNb9DrXbTlsZwNnhrKQFQ4jnJNjyd6cbnno1qO7VXLz8iwZezwLVbNRHZJXKlEaQ8SuPLfXKv4gAgF5pqed/Rfp/Sckb9X0x1WZvZZUrkHa2g0qktdZTkgMZ4PXdVmF6onpn08cWyWuimA3RPr6/99uy4MTx3ZLXvsZvvKZ9pTUJz+/WDOeI4Fet20qdjU27Yu4dmiJ0q7yXytSDyIlRUIK0yp3VVSejuTkezodl+NSj07Rq7JXsnqlDZxtUjcmmzaDTeEcnW2ifUXaqrrrE7c3Lckr7aV9T6O0s7CpsTZOGxMjcg7u83CeS6Spamo7P77O6ywZIANkgAyQATJABsgAGSADZIAMkAEyQAbIQFNgwDlOp+Nk7ljd+K1zP+dx3MtNoR6c39H9/WXdea7u+pDXm5XkteStQ/rWuh4OQSRvhiV6Q1YGr2b2SkavTOXcvUd3S6AlJSVZokArVCtXojRCwNQSQNCfhEAgySF5T2T+yv51LfpZpxLreuy67ncqny37uiGr6f0igJ2C97jYNWxhLnXqBLwlLssgfzAo/zRgz02vdSzbJFtXM02d0zNT1J4QtfVRFzqFs0S5pshUzvK8XhUw0pdaIpuN8Zz1uqbXHff1iOtNT+rW1Gbaztrup8KkvkeP4Yw1fWZ9vOb8LP0eEp3fX68vzm1c5m8CMkAGyAAZIANkgAyQATJABsgAGSADZIAMkIGmyoBzvEuXZUzMOVbmXo40Fqf76LhaU62PSN9bz8kZ9XwluutD9mtxkjdbpmeWaZqtqZ5PlrwyhbMUyerV6ZxF9Pbq1Qt5eXmWVJNKk8qUKOLXWdnSKDIVc10bx/ne2padDVndshxDX9Pj6frZivo9IkadYrmmaE2/3DIv3FJnwpK0nc43Lxc/EZciGkXwitxVwet8vq4sO9frQ3a29GNIZq9kS0vdi/CV+tUpnJXvSH2f26Lff7X+Ner1zn3T43rzkLzavu6o10zpc87lmvqgmxk5ZjQ5cX5n/ey6fteazoOvRf86wzpmHZMBMkAGyAAZIANkgAyQATJABsgAGSADZODMGBC/oUXqsraxOPEi6kZkzE7H1uo6rqafpbGxt5/zvHRZzzlSXck+lLyOTF6VvJLNq5I3nJ2N7t27o2fPnsjNzbUEcYcOHSyYpAIFCq1sjZFAqW5ffc/pRmcDRzqG8/WzsRzpOx3fVpPc1ddauOTVupLMXZGsIhmdRbNMVcCq2NWo2xlPL7tX6lHrUqfBljoXsa6iXV6X9onU77ntzG76kepP+0SkqNe4aEo6Hvvsi2JnO+uyRicXyo9s02V3dO6vy3osjfXd5nrcmr6X+3tyvf6vJaxT1ikZIANkgAyQATJABsgAGSADZIAMkAEyQAbODgMiXWVsTMfJIo2/yWu6XffT8TtnrKkNVe5qrGnfxvCa87x0Wc/dWR9aL7JPi5W8ks0rAlfFbnUxFA4hJyfHqiitLBG+kkUpWXxawVrhGusKhO4frajf72zFGs9LRW5NsQVLXmFI6k84E8EozEkGukheEYvyzwYib+U1lbgqJDXqdsYzl7zOOtSsXhXuIn1lCmc373W9DnC/uv+YcNax+7qmNzfGsy9iz2YbKBfCil5Hdbm6vqavR+JLzkWOeSbnpO/X7yZRP7O678Ttdb8usK5YV2SADJABMkAGyAAZIANkgAyQATJABsgAGWi8DDjH3HTZOU4WadzN+bqOpel7NdbW5ip3Nda2/9l+Xc/LGZ314K4n2U+9pThPSUyr9TG2p/LI23rcN6a+vphO11xXySuVokW+gwpfEb2S4SuyRxpeKlcqVDP6ZPl0gHA2Xn0sOwE4G8u1nYPzObwRl1uQ5I3EjMpEnZJZ1rU4paMuU+6enszV+nNHqc9IdarbNKtX2keEr6yLlG8qN43TuUadjfc4ryM1XcfcNzmut0zZq4zofVn5qQu7uq9GPZbGU2FK3qPHqS7W5Ttxn8b7Bwrbhm1DBsgAGSADZIAMkAEyQAbIABkgA2SADJCB6hlwj4npGJvGmsbadB89htSzLmusre51nF5jbfuf7df1vJxR60Giu75kvxYnef+fLA6HINm61RUVvBrl/TJtszyjVypPoohfkT5SoVLJCpvMFR5tKJyN3WSXDdN6lrE8z/ikcpqiPNp1firHr61NhBfZR5mRjir/KCAiVzJ3VSJKdApIed25zuX6lbunUp8q3bWtpN3k/c7n9Z4KM9z3xI8Cd/9x3tAi3dTcNzmut0zJ62535eZU+5aTPz1GXaPzve5l5/eQ15zrXD7R/1kXrAsyQAbIABkgA2SADJABMkAGyAAZIANkgAw0TQbc42GRxtTcY3judX2PHqslsKDn6o5aF+4o+1Hy1pJurHJXo0heyQJW0avP6xXZK69pFp82QrTB089prjHa9Rft49fWLvIfJLKPXMAkijAUWahZoSpzNZ6KfOS+DSt+nW0n7SfZvfLPH5rdH23WmtvxnX3HffPSdfeNn+uUuk4G5B+tZF15cTLl7i9yLXZvc67re/VYtUXd33kMLjfNP0rYbmw3MkAGyAAZIANkgAyQATJABsgAGSADZIAMnBoDOjYWaQzNOX5X3bK+T48jsSW0gfN8nctaH+4o+1DynobkFZnrlL6a3StTOPfq1ct6TWWvGzxtGPf2013X4zXWeLrn1Vze52wX6YDOdVmWbSIX5Pm6IgaVLafkFXlIyduwwvZMBbkIXsnoVdkrz+sV2VubSGou3NfHeUj/kJu8iDot1d30uZ1yNxIDbm6cP4Lc1+LamJX9nfvo+/WYuu7ch8un9uOf9cX6IgNkgAyQATJABsgAGSADZIAMkAEyQAbIQNNkQMfGNOqYWaQxO/c23dcZ9TjO2BLYcJ6vc9lZN85l2YeS9xQkrwg4LSp5Ncp2yeoVyStFsn0lIzMSeFLxkbbLNmfD1bSfvt+9f2Nb1+/Z0qO0i1y83G2sgleEoIhBKe6pmc9UOPL9DSeIJXNXhK5Ie83IFtGr0t79zx/aX1t6/3Cev9aJ3Kykz6iok+j+AcB1yt2aGFB2dB/nDyDnsjDnZLAuy8qpO9blvdynaf6xwnZju5EBMkAGyAAZIANkgAyQATJABsgAGSADZCAyAzpGpmNuOh5XW9T9JeoxnLGl1bfz3J3LznpyLss+lLwOcasC1xlV4kp0b3eui9SVdYnyjF4VvjKtswgfgVGAlgaQZW2glgZpSz1faW9pf+VA5K7IV+FKBa9IQWbsNpyQjYb8FsnrPK60pwheaWPN7JXXJatXmIh082rJfUSvi1o3+iNABa9KO13X1xkpeyMxUBMv7h9D0u+Uv1Ppg6fznlM5PveN/IcD64X1QgbIABkgA2SADJABMkAGyAAZIANkgAyQgcbDgHs8N9JYnXubjs/p+JozttS2ddaBc1nryh1lH0reKEleeUavVK5EKSJ/JYtP5YRUvoDqbCjd1lIBbo7n7WxfuYjJOQoHmuWp4o+Ct2nLXRW7bsmr2yVKG0t7i9iXjG355w/hQ29ucoFuydcA7SvOG5XWjV43dZ2RUrcuDNQkeZ3v176nDDbHexHPqfH80cO2YFuQATJABsgAGSADZIAMkAEyQAbIABkgA82NARlXkzE255hbpGUd+9VxuOpic6ufup5PdfWh9eaOsj8lbxQkr2bzSkavPKdXsnklSmWL3BHJJ40h2ZyRGq2uDc79Gv/NQNtX2kraOy0tzWJAGBHhp9MzM4O3+UteaWMRvVKk3VX0JiUlHZe9yomw0tL6t/YV541KfwhQ8lLqKgunEil5G/89sqVd53i+ZJIMkAEyQAbIABkgA2SADJABMkAGyAAZaE4MuMd0qxu70zFf3b+22Jzq6FTOpbp60fpzR9mfkvc0Ja9OzSyyrrYi+2pmr0zjLEWEj7vBpLFl26k0Ovdt3DcFaU8RDRJF5onYk+l7nXK3JsErmaE1ZYc6M0W53DREsbS3U/iK9BX5L325JcpdvYbp9dB5o6ruRwG3U/rWhQGn5BWuqnuPvKb8SVQmGRv3/ZXtw/YhA2SADJABMkAGyAAZIANkgAyQATJABsjA2WVAx9R0TJfjb2fWHlqf7qj1646yHyVvLZLX+dzd01lWASzZvCJ6JbtXooheye7VLD5pHLkgaePx4nRmnaGh6k/bK1J0drjU1NTj0/WK5BWxp7JP5azIXN2mUV9jbBoCt7Z20naVKAwIC1JU8sqzeluq6JU+JH2muh8C3E6xGy0G9FotDDbUvYOf0zTu8WwnthMZIANkgAyQATJABsgAGSADZIAMkAEyQAYiM6BORMfW3GN3ul2i7qt1KWPgLXUcXOsgUtR6ckdnXTqXZT9K3gaSvCJ3tYjw1YqXZcnqFLkjDSIdQaGP1MjcFvmCcrbqxd3ZIq1Le4rkdWbxiuSLJASdErC6fSK9j9uahgR2tq9O2yySV57Pe7YYbiyfK31H+or7xwDXKXcbggH9cdRY+gO/R+O617M92B5kgAyQATJABsgAGSADZIAMkAEyQAbIABk4mQEdz61uTFfH2ySqN9E6pOQ9uS61XrSe3NFZl85l2U9doyScZmVl4XSSVRviPTEN8SHR/AzN6JXPkGXN7NVpnGWbM6NPGsr5nwzSWNrQjJE7wNmoF3dni7Qu30sknrSvZvBSyjYNKVvf7eSUvLIsPMiFV6L295ba1+W85brXEEKPn0Fx7GZAfxydjfsIP7Px3NPZFmwLMkAGyAAZIANkgAyQATJABsgAGSADZIAM1M6AehAdU3OPtcm6viZR99e6peSNXMdaT+7orEvnsuxHyRvlTN5I4liFr2b26tTNInzlNRGC0jgKvERZVwnk3M7lyJ2hoerF3dmc6/odpN1E6GVmZlrRKQ75vN2WJXvdklfWRfLKPwBINr8y0xKj9B25QUX6QcBtlLINwYDw1xL7Hs/57P6OYP2z/skAGSADZIAMkAEyQAbIABkgA2SADJCBpsaAehAVju6xO9mu+2h0niMlb2Tmta7cUevZHWU/St6zIHk1m1eEriyL5NHMXmkQkb0iBEUASqMJ/NJYGp0N7OwYTWE5YPrhLE3hO9f0HZ1tEWlZ3isXLM3YVMErbauCV6O+xtiyxK8IXunvwokyVBNzzfU1OXe53rl/EHCdgrehGND7bXPtYzyvyD+eWS+sFzJABsgAGSADZIAMkAEyQAbIABkgA2SADNTOgFPM6ji2Skcdv/N4PNb4rmzXfSSyfmuvX6kjZ505l7We3VH2oeQ9S5JXRa9m+orwFbmrWb0ifTXzUxtXo7NxI3WOCwJ+PJxs4NmUxleeSzHgLKf+HU08myKl8Z1bdd/puVQTL3VJwctd09CnczJe7JR0Uvlex7Tjz+dV+auRwrf5C195VrNb8mofj9S/m+s2OWe5SekPAkbK3YZmQPhrrv2L51W3H9KsJ9YTGSADZIAMkAEyQAbIABkgA2SADJABMkAGIjOgkleTlVQ4OsfwKHkj111dmVIv4I5a1+4o+1HyNhLJq9JXpnCWRpEiole2iwBSCNyNq9s13p1sAp28LE2sDkZ0DFiiV+WuRkreliV5pR87+7j265YQ5bzlJuX8UcBlit6GZED4awl9jed4Zj+2WX+sPzJABsgAGSADZIAMkAEyQAbIABkgA2SgJTJwKpJXxnpbYh2d6Tk73YBz2S13dV32oeQ9i5JXs3idUYSuiF7J6pUiy/K6PLtTGs7ZsLLshEYyeCl4m67gloxelbsaKXkpeZ19vDkvy/VMrnENKfX4WZTITgaEv+bcx3hu/AOUDJABMkAGyAAZIANkgAyQATJABsgAGSADZOB0GaDkjT47bv+n6yp13VFep+RtZJJXns8rUlclrzSQTOUs8lfEnzSiNqxEZ4f8W7JxXPKuTPPi2WTfSVMjO6dJrmlZ3qflmRQDUmSK5OesIss+PJvitcpzyT48n3zyFMw1HVv21fJc1fvs6Zd1Cmb5zlpOPq7s90yyXZ49hc+s6fvU12taXxKfSfIeL7Iun/Fyeir6dknBS52T0adT0vEyv+OJzOvHOyUfn7aZcrf5y11pY/nnDXkmr/T7YDB4Ut/Wfu7s4811Wc9Vb1JO8cZlitiGYEDZa659jOcV/R/hrGPWMRkgA2SADJABMkAGyAAZIANkgAyQATLQ3BkQ0avnKONp7nE7na7Z7a70PYw19xEdJ3dGHbeMFGU/St5GKHlF+Gg2rzyjV5Zlmwghne88UicRmaiZvCIXI+3j7kT63xfO7QqQIZl1Ab9VTH8QfjNodWDTb8IIeGH6vQiaJpJMPwJmzXDK8WUf2VdKUN9jBiDHNqwiyyKuDfitKMtOkR2Az7SLfDc5pumX99gXFucFxnk+DbGsdSbR3dnk80XSi8xLT08/SeSK8NU2k2XK3ZYhd7WdKXnt64b2H+077h8HXKfojTYDyl5D3C/4GbX/XmAdsY7IABkgA2SADJABMkAGyAAZIANkgAyQATLQ+BhwOhgZT3OP2VHynlmb6Ti5M+q4ZaQo+1HyNlLJqxm90kDybF4RvSIK09LSLLkpDeq+yJ2O5HUfw7lu+v3wBuwisjVwXLiKhPUg4PcgyTRsyWuYlsQVkVtdEbGrkveE6LUlr88fhM8StrbkDfgNSLGFryz7rHXTtAWwRBG9Knnluzq/e0Mv19Tp5Ls4Ja+IPZV8lLwtS+pqu2uk5LX7rfYfvVG5fxxwnZK3IRiIdF9t6HsJP+/s3stZ/6x/MkAGyAAZIANkgAyQATJABsgAGSADZIAMVM8AJW/1dVMf3Og4uTPqmHmkKPtR8jZiySuiVwSvNJIUmcZZ5JB0pEiD0WcqeZ0dVIAUcWqIPA0EEAj4HZJXhK9IV5+dyesPIGCY8Bvm8QxdFb1J8ppD/IrodRZ/VSauLWulg9gyOWCKNNZMXhOmaUteW/zaWbxOyVsfHehMjlFTp5PjUvK2bJmrUtcda5O8Z8JkU3qv9h+9UTWE0ONnUBy7GYh0X21K/YjfNbo/slm/rF8yQAbIABkgA2SADJABMkAGyAAZIANkoKUz4HRIMpbmHl9jJu+Z9REdJ3dGHTOPFGU/St5GJnlF5EoRwStFMni1kfQ1t+TVBpcpmnXqXxG+p3PBkWMfL47M24AZQDAQrBK2AXg9BkwjAMNnWNtU8Jo+H4KBAEzDRGpKqrVsSd6qTFtLzEoGrkhha5stde1pn01LFgfNAJL8QQT9QQQCSVaRKZ3tEoA/UDVttGlAMnq1nM751td7tA0kOjubXOTkMyh5KXndglfW3ZJX2HGyVF98Nvbj6Dlr33H/OOA6hWxDMCD8Nfa+wu93Zj+UWX+sPzJABsgAGSADZIAMkAEyQAbIABkgA2SADJw+A5S8p193deFOx8mdUcfMI0XZT/1hdna25RTVIza2GBPNLxQOheAs+lnhUBjOotsbIqrklYbJy8tDz549LeErn62SVxpQwNAGPx3Jq+/VY/m8XgT8fiQFg/B5ffAbAXjNFLQNpCMuLRttfckwkjrAH0iB4fMj6A9Y2bxBrw+pfj86BJOQKjLYMJASCCLZNJEWCFrbROSmJifbGcGGgWBAsoT98Hp9MH1+mEYKfP7OSPBnoF0gC62DYbRKzsE5KXZplRxGm0AXJAQ7wedPgk8Es0whbYgYs2VvXTpKNPZx1qOzs1HyUu5Gkru6jZLXvilq/9G+0xBCj59BcexmQPiLxv2Bx4zuj1/WL+uXDJABMkAGyAAZIANkgAyQATJABsgAGSADDcMAJW9061nHyZ1Rx8wjRdmPkrdK8GaHsiBFZK9KXFvwZiMckhI+vl1fj2ZUySufIdm83bt3t4pIX+lI2shy8dLl05G8zvfLskylrFMvZ+fk4Te978RF1/0CKdf0RuaND+KKW+7D6yPHY+7CJZgxdQp+deONuKhbNzz5wENYNHU6Ply8FOuWLMVHK1ZgzbJl+HDpMqxbtATrZLssL1+O1cuWYdWyZVi9ciUWLy/DjHmL8I8FFBwFAAAgAElEQVSnX8EV3/o5ul78M+Rc9yd0+9U/kHbjY0j79T/hu+nvaHv9/Wj37TsQk34lYlK6I87fEYYZqJLc9rN7RfTK9M8nl+h2Or15aBtIdHY2Sl5KXhW6kSIlr90/tf9o33HLN65TyDYEA8KfXtMZG+beyXpmPZMBMkAGyAAZIANkgAyQATJABsgAGSADZKDpMEDJG9220nFyZ9Qx80hR9mvRklezdLNDYeSFQ8gJZSEnHIaIVCnyek44p0ryZiMU0hJGKByqW3FI49OVwvJdpKE0m7c+JK8cwzqOPnu3agpl0+NFZpd0vPryK1i/ZTueHTAaV/R+Ap1ueQa97n4Nb89cg/IDwNJlZfjLHbej6O13MK+oBCNf+jf6/f1JDH36ecwrGIUNcxdgcclYLBk9FrOHjcCsYSOs9VVTpmN2YRHeHzMOHy9cgn0VO3Bw10Hs2vIlpk5Zgz8+PACha+9H6vX/g65/eAOd7x2G4L3D4fvzcCT/aTC6/L4PjCt/j1bJPRFvdoHXTIbPMKyMYIOS13pmcySZyG2NUzZHkrxysZaLc0v6caM3Lb1RNYTQ42dQHLsZEP5aUr/juUb3Rznrl/VLBsgAGSADZIAMkAEyQAbIABkgA2SADDQ3Bih5o8u0jpM7o46ZR4qyHyVvKAc5oWzkZmUiN5SJnHA2ssM5ltC1M3izkZEh0znnIRzuhqxQLrLC2cgKh5AVzqqKsmyXzFAWnMWSwWcgekXwihx2TtkcDOozac3jWbzSmKeayWvKM3EDARh+P3xVUumbl12OlUuX4ejhw5i57CNcc//ryL3zDXT63Yu4L38BNn4JrF2zBqsXLkLF4mXYMnkGdkyeiQ2jJ6BsQD4+HTkGW0dPwrr+BVg/ZBQW9H0TE554DjP+9SrWDC3E1nFTsKFoHNYOG4UxTzyHkY88jSl9++P9gWMxb+QcjB+9HO8OX4brfvsckr91L5J+8RJS7xkJ730liL17JAJ/KkDmHe8i8eLfo23qFYgPdIXXDMIMyDN77Q4mzwBu6ItndZ1OJIJ8Fz6Tt3FK1rMtvyl57b6q/UdvVG75xnUK2YZggJK34e+dDX2v5uexjckAGSADZIAMkAEyQAbIABkgA2SADJABMnD6DFDynn7d1YU7HSd3Rh0zjxRlvxYpeU88fzeM7FA2crLCyKuSvCJ2s0I5Vgln5yIUEuErRZZzkREKIzMcrlbyZoSyoEVkb31IXhG9ubm51nTNEutT8orgtUSvaSK9c2csW/A+vtr/JSrLKzB00gJ0+c3z6HrPYFzzZCFm7wA+3LIV+GIPVk+bjgPLP0BF4VgM6/0njH3gMax9ewi2jxyLnYXjUd5/BCoGjET54FFY/+5wLHimLwb89o9499e3Y8OAETg4cSYwZwnWvj0MK94Yio8Gj8GsV4Yj/5nBmDh8HsYULcXNd70C7zf+DN9/9oX/T0UwH5wEz31jkHJnAdpcdi/adv0h4lN7wuPvACOQbEtew0DANO1n9crzeqvEb7RjTZ1OPpuSl5I3klCm5LVvitp/9EbVEEKPn0Fx7GTA4/FA1oXFaN8vePzo/hhm/bJ+yQAZIANkgAyQATJABsgAGSADZIAMkAEyEB0GKHmjU6/Kq46TO6OOmUeKsl+LlrzZ8rzbUAi5WVmW5JXla7/3A/S+425c/LUrLKEbys5FZkgzdTOREeqKzOxMZEbI4pVsXhW8EutT8upzeSWjt34kbwCm387iDQSDCAYC6PvCv7CnvBIHd+7BiqXL8XT/YmTe+QbCD+TjzQUVmL1uK3bv24cNZUtwcPVqlL07CK/99FfY+OYgHJ00C3tLJqFi+GhsHjYKOwrHorKgBB+/MxQf9xuCT/sNRfmgkZjz92fR/+be2Dx4BDD7fRyeNR/r84uwOb8Em/PHYdPwKSh9/HW8fv/zGFcwF1f/5K/wf/M+tP/R80i5ZzR895TA13swzv3avYjv9kv4Mq9CYlIIXn+qdT5+S/IaCPilyGB9wwzY19TppINS8lLyUvJWfwPU/qM3Kqd84zJlbLQZUMEr/AmL+qOKsfo+y7ph3ZABMkAGyAAZIANkgAyQATJABsgAGSADZKDlMUDJG90213FyZ9Qx80hR9muxktcWvFnIDUnJtCSvPJv3sX++gEFFE7Dww3K8+E4+ftn7TvS85GvIys1BVk4IWTkieKWE7IxemU7ZUXTaZo31lcmrkrd79+71Knn9Ms2xYeLiXr1Q+cmn+KK8Evu3bkfZ0jLc+sgLyL33Hfyh6BP85IG+WLpuCzasX4+vKjbj09KxmPL3p7Cx32BsEZH7+gDsGFGK/eOnYs/Y94AFy4C5i4E5i7B5SCE+eWcoyocUYteocVj3xgCMuPM+7B47CccWLMbuSVNRWViKA+NnYNeIidg8ZAzevfOveOQXd+HRe1/C5dfeC/Mb98H4aR8k/7EAnpvfRszFf0Jcz9/Cl3MD2qf0QoLZ4bjkDZoGpIjoPduSV+SE3OwoeSl5KXmrvwHqTUtvVNGWejw+xXEkBoQ//nFSfT9l3bBuyAAZIANkgAyQATJABsgAGSADZIAMkAEy0LIZoOSNbvvrOLkz6ph5pNjCJW8WcqoEr/Us3pCI2xx84/s34tZH+uD79zyP2/sMxxulMzF75cd4rf8Q3HrbH9Hr/AuQk5uHUF43ZOV1R1a2PqM3bMlekbvpGRlWRq8sn6nklefxShHJq0ZeMnmdjazLz6UYQCevVWTZ2eEiX3wDCASSEDD8eObRR7F/82YcLt+KvZu24IMPVuMHvf+Ca54ahcseHo4b7n4BU+d8gAN79+GrDeux9PV+2FlQgiNT52BH0Th8OnA4NgwqwMbBI7F1ZCn2jJuCLQXFtuhdtALbisdh36QZwPvLgHmLsbTvG5jx1PP4at4iHJ2/GJWFY6z3Hp21CNtHT0Rl8QS88ru7cevXf4L/ufM59LrsD0i64s/w/fAZeH70As49/y7E9/ovmBf8DokZ30F8IN2SvJK9S8lLoRpJqDbGbZyu2b4p6jVMb1SRBBy3UcxGmwHhMPK9Mro/3viZrF8yQAbIABkgA2SADJABMkAGyAAZIANkgAyQgabAgNM5yViue7xOZ8zjONvp8azj5M6oY+aRouyn3lAe+5qVlWX5RPWKjSnG1OeXkWfyZof+v+TNCOfhaz/4BR7Pn4U/DlmG3w9aih89ORRX3vEkbn92IN4qnYfFH29Hn37DcFPvu5F38eXoGpbn9Mo0zTql88mxZskbRijkLLbQjXSuKnl79uxpZfI6G1mXT0fy+s0kpPiTMH10CQ5vKceRLVuwqWwlli1fiev+8N/4+sMDkXf7K7j7nwOwd89R4IsvsW3BfKwfNgJYvAJY9gEOzJyHfZOnY//kmdgwtBAHps7GoZnzsbmwFHsmTLX3e38Z9k6dBSxaDixfjQPT5mDsw4/jy6mzgUVl2D9hGioKRmP3+Ck4OH0uvpw8A4tefAP/+P6vcMc3fo6Hbnsemb1+De8V9yD+6keQcPn9aN/rj4jv1RtxoesRF8iIIHnP/nTNcpGTizMzeSmeI0lmSl77ZqfXML1RuX8ccJ2CtyEYEA6bwo9pfsfT+5HMemO9kQEyQAbIABkgA2SADJABMkAGyAAZIANk4MwYoOQ9s/qrjT8dJ3dGHTOPFGW/Fix55Xm8J6ZrlmzeruFuuOj6W/DX4Ytwa3Elbh5/EDeP3Yubi7fhF8M+xtVPluCKu/rgv54fgtdKZmPBui147Z2B6H3bbbjokkvQNSvzeDZv3aZrFsGbXVVkuXbJ26tXr/qXvEYQK6bPxLHychzZtAmVa9Zi6vRZ+N5/PYAe97yJi//7bazYvA9f7doNfLYDywryceD9+cDyZTi0cBEOzF+Ig3MX4vDchdgyagxQtgZY/SGwdAWwYo1dlq7AbpW8H6wDlqzAxpGjsfylN4DpC4Dp87Fp8Ejreb5fTZuL3SUTcWzqAvS/6U4MuPVRPPzzB3Hb755F4IJbYVz1AGIvuQdtL7gbbXr2RkLeT9Hekrx+BPx+BE3J5jURaMAB++o6HSUv5W4kuavbKHntm6L2H71RNYTQ42dQHLsZEA5r+6HF16P7Q5b1y/olA2SADJABMkAGyAAZIANkgAyQATJABshA42WAkje6baPj5M6oY+aRouwnj3iV0gIzeUXyqujNtJ7Lmx7uhguu/w0eGrkcvy7ZjZ9OBG6YAPx4MvCjcV/hpnH78bvizbj5nfdxwz8KcNWdz+Kufw3E6yUzMHP1Fvzr3eH4Re+70OOSy5GZ2w1ZuXnIys6pEr/ZyApnI5ydjXAoXFVkWSRv2J7WWaZ3rkb0aiZvvUtefxApRgDr5s4HtpTj6KZN+HzDBkydOhXf+80duPTOp/HvOevx2ReHgL2f4eDqD/DRmBJg0yc4tGIJDixaCJStAJaWWaJ3+4QpwIrVwPIPgLUfAavXAStX49jylTj8/hLsmToTWLUOKPsARxctx9o3BwCzFgEzFqAyvxjbR5Ri44Dh2DaiFIfGz8SM+5/G+D8/jQF3PY1He/8TF3zzDiRffjfiL/4zWvX8I1r1vB0JPW5CbJXklRtAwDxRGuqGUF2no+Sl5FWhGylS8to3Re0/eqNyyzeuU8g2BAPCYUPdM/g50f1BzPpl/ZIBMkAGyAAZIANkgAyQATJABsgAGSADZKD+GaDkrf86dXKq4+TOqGPmkaLsp5JX3GILm65Zpmy2JW9OKBNS0rO74cLrb8HDI5egd+l2/EfJl/jxJOCHk4AfTACuH38UPxx7ED8q3Y+fjN6DG4u244YBq3DxoyPR6+7X8KvnRuL1sYswa9Vm9B0wHL++/W70uPgSpIeykS7P7s3phnB2DnLC2cgJ5yKzaxZCWXbFZ8ozgUOZ1T7DVyWvTNcsHUkb1NnYzyb7TnomrxOO6pcDSDH8KF+x0pK8xzZvxqHyzVi9bDF+d/ttuPOxf2DLl4ewb99u4PNd2DxtCrD6AxxbvxYHVi3HlwvmAys+AD5YjQPz3sfB+QuBZZLBu8qSu1i9FkeWr8BRKcvKsOu9acDKVcBHHwNbKlA5ejzK84ssybuzcCx2FpRi84ACVAwtwsZ3R2D2357H7L+9iBUvDcXTv7wfd936LAJZNyLlsvtwTu5taN3zTnh63YL2gUz4AwH4A0Fr2ma/PwC7NGyn03ZxRql7TtdM2RtJ8sq2rl27WnxIv1aRJfxI366+30aX64b+XL2Oab/RemCk3G0oBpS9ltTvGrqf8/Oa13Wb7cn2JANkgAyQATJABsgAGSADZIAMkAEy0LIYcApeaXsZT3OP3fGZvGfGhI6Tu6OOXbqj7FdXySuZvtUlmTbE9np/Jq/9XF772bzyfF4ptuS9GX8dsQh/KN2GX02BJXmvnwxcNxH47gTg2+OBq8cBV40Fri4FvlNyGNcVf44fjdyGH72zElc+ko8Lbn0KN/9zEF4qfR+zP9mJ594pwM9vuxfh8y9DKKcHMjOzkZ4u0zPnISe3G9IzMiDTO8vze0U8S7Eq1ZHZGz3JayLFMGzJW1EBVJTjWGU59m/bgn5vvYKVq5Zg3+c7cHDvdmDXNnw4rhSo2Axs/gRH1q/F5/PnAkuX4tiSpTgwbz6+mDsPX72/yBa/y1fg8LLlOLpqFbB2LfYveB+7p83AF7PnARs2AGvW4cDs+Vgl2bxzFmHH8NHYWzgOnw0bjc8KxuCLkimY/tA/sfjJf2Nrv2L0/fk9eOz259Hjwt8i2Os2tOt5F1r1vAveC39nSV7rIhMIwvCL6FXZe2adqrYbVV06mxyDkpeSl5K3+r6o/UhvUu4fB1yn7I02A8qesFjbdZ+vV9+XWTesGzJABsgAGSADZIAMkAEyQAbIABkgA2SADDRPBih5o9+uOk7ujjp26Y6yn0peyeKtKZO3WUpeEb1aRKymZ3fHpT/+LR4pLsOvx+zCTyYBN0wCIkreMcCVpcCVJXb5xuij+EbhF7hm1F5cm78VV7+1DrkPFCH71j749bMj8PLoeZi/rhIv9xuGX//hLvS46BtID3VHTo9eyAiHkZ3bDTnZuegWCiMvK8sSvplV4leEb3Qkrwxmm0gxnZJ3C45u3Ywje3dgddlCHPhiJ77ctx1H9mzHkYqN2DhlIrCtHKj4FCj/BDvnzgRWrsDRxYtxYN487JsxE18tEsm7AlizGkfWrgE2bQA2bkDF1Kk4MG8BPh01GocXL8XRpWXA8lXYOLQQe0ZPwO6RY3FwzBTsL5qI7UNGYcu7w7G2Tz+sev4tVPYrwriHXsKjv/07fnTDg0jI/Dm8l/wZbS66B75L/4DYQCYCAT8Mf8CSvLboDcD0R7fj1dbZREzITY2Sl5KXkrf6vqj9SG9S0RZ6PD6lsZsBZU9Y5B8i1fdV1g3rhgyQATJABsgAGSADZIAMkAEyQAbIABkgAy2TAUre6Le7jpO7o45duqPsl5uba4lecYgtRvK6U4/lGbnZoTDSwz0syftg4VLcPG4vrp8I/HDyyZL3OxOAb423M3m/WQpcVgRcXgpcXApcWGLHS0YDl448im8XHsT1QypwXd8FuOiefsi7+TH89pmh6DP6fUz9cA+e7l+Mm/54L3IvvgwZ2d2tDN+8rDBysyTLNxuZ4WyEwrIcTclrIMX0YYtM1yyZvOWb8VXFJuz4dC3Wr16GA3u24ci+HcCeHdizugy7F84DPloNbP4Y2PQRts2eBqz/0BK9X86di70zZgArV+JI2TJg/SfA1nJg+1Zgy2ZsmjwZ+2bMQnlRKT6fPgtH3l8MLCrD4elzse6NAfiiZDL2FI4DJs/GjqFFGHv3Axh8S28sf/YV7M2fgJmPv46//vhu9L7pUXi6/AjeS+5Cm0vvhfey3ohNkuma/dZUzSJ4KXkpVauTqo1tO6dr9ltTU8sNSW9SbgHHdUrZaDOg7AmH/EMl+j9YWcesYzJABsgAGSADZIAMkAEyQAbIABkgA2SADDQtBih5o99ebrmr6zp26Y7yuiaIduvW7STJ687cda+7PWm01+t1umb3l7Ulb7YleS+6/mbcX7AIvxy7B9+fAPxgIvCDSfZ0zddOBI5L3nHAN8fa5etjgK+J4B0NXDQauKAIuKAQuGjkMVySfwCXDd2Hrw/dhauGbMPFr5Qh+a5BSP7Nc/jx0/noM3YB5n60FS+/PRhZ2d0RDuchHMpFVqg7skLdLNkbVclr+JDs82LTijIcKS/HkS0bcWjzp6hYuwJ7t27A0b07gN0yVfN2bJk/G3sWzsOeBXNw7KNVOLBqGTa8N97K7D2ybAk+nzMHhxctwpfvL8CRFcvtaZ3LNwE7tgGbN2H79BnYWjwG2wtLsHvMRGDBEiuTF3MXYe2r7+LLksmQ5/IeeW82dgwrxoev9kPFkGGY/fg/cGzyHCx+rh/+dNEN+OtNf0Nyl+uR+s17YXz3f5B8zb1oE8yA6TdhmCJ6G890zSIm5GbFTF5K5+rkMiUvJW+0BSaPX7sk1x9IlLzR/7HKP+BYx2SADJABMkAGyAAZIANkgAyQATJABsgAGWh6DFDyRr/NVOq6o45duqP0I5G8MmXz+eeff5LkdXvQFiN5L/zBr/BQ4RJL8lqC1yV5r6l6Lu9VDsn7jTHA5SXApaMByeK9sAg4vxDoNQroOQroVgiEC4BQPtC1/z6E+1Xg0gEbcOmLs5B7Rx987TcP4c2C8cjIEqmbV1W6IxTqhnAo25pSWm18z549IZ1JG9PZ2M8m+4BOXqs8l2LUIRvJhN8heb+qKMfR8s34cuMn2LhiCb7cvgUQybtrG7BzOzbNnoEvly7CvnmzgdUrsGf+bFS8NwHY9Cn2z5mN3dOm4ciiRdhYUmIJX5muGZ+ut7J4Je6cNgNr3nwXOwuKsT1/FLBgKbDsA2DJSlQMLsTWgSOxp/j/Knj2ImzPL0bZv/6NLYOH4vCkKdg3agJWvTQAL//w93jqP+9DOP1adL78dpjXPoqU79+P1sGuluT1+wPwm0H4/VICdaiDM+uYzvqXZW0XjZS8lLvVyV3dTslLyUsJW7uEjXYd6TVbruP8I+PM7ousP9YfGSADZIAMkAEyQAbIABkgA2SADJABMkAGmh8DlLzRb1O3b9J1Hbt0R3ld5K1k8YrkVbGr0zY7n9PboiTvgyMWH5e8ks173QTg2vHAtROA704AvjMeuHoccGVVJq9K3suKga8VA5eMkixeoFcBkDMcyMwHOg4BUgcBqf0Poeuwo0gfcghZ/Srx9X5r0fm3z+G1otnokp6H7Kw85GblICcrB9mhbGsaaXlucDQkb8BvImD4kFKVySuS9/DmDdi3fh0q132AXRs/wrG9O3B42xZgewU+em8iDi1djL0zpwEry1BeOhpbi4qAD1Zhz4RJ2F46BsfmzUdlcQl2j5uAQ3Pm4tgHHwDr1gJr1+HzaTOx8Jl/4ejYyVjx3Es4PGEK8P4SHJvzPvaPnoh1L/fDnqL/q+j5yyzJu+aVtzH/Hy+g7PlXUfb0a5j+l6cw86GnsfTVAtz+wztx8dd7I/X7/4MOP34Yraokr2n4ERDJa4leSl4ViYyNVzZT8lLyRltg8vi1S2T9gUTJG/0fq/wjj3VMBsgAGSADZIAMkAEyQAbIABkgA2SADJCBpscAJW/020ylrjvq2GWkKCJXnssrCaLiEaWo3NUo8rdZSl6ZptkuIlNzkB7uhQt/cDMeKFiMX4yxp2sWwXvdxCrJK6J3PHDNOOBb4+zn8oroPS55JZu3GLhoFHChZPKOBLoMADoMBFIHAymD7Zg6FEgaCnQecgQXDNqOwO//jZeL5iEr1BPZoVzkZmUjJxRGjlR8KBS1TF6RvEHDh1SH5D1WWY7Klcuw6+M12P3pOiuT90DFBmtK5jXjx+DwkkXY9d5koGw5No8ciU8HDASWleHLCZOwbVQx9k2YhENTpmHHiFH4fNz/PdR4yTJAnve7chUOTpuJSff/FYdHj8O0+x/GroIiYM4C7Bs7CfuLxmNt37ewY/hoYNZCfDZ8NCoGjMC6V/qjcmARFj/RF8fGzsaaF9/C9Mf7IP+RV/Cdr9+CLt9/CJ1/+lecG+hsZ/IaJgKmyF0t0e14tXU2kStyw+J0zY1Xsp5tAU7JS8lLCVu7hI12HekPJEre6N4z+Qcc65cMkAEyQAbIABkgA2SADJABMkAGyAAZIANNkwFK3ui3m9s36bqOXUaK4p5E7MqUzXl5eVYRqSuCV16T2Mwlry14JYM2PXwBLrju13igYBl+Wfo5rhtvZ+5K9q7I3e85JO/VY2zJ+81S4OulwGVVz+S9oNienjlrKNBlENB5cFUWb5XgTRsCSBHRmz74CC4cvAOBW19F31GzkBmWqZplemaVz7bgjVomr2kiyTTQwfBhy8qV+GprBQ6Vb8SOVWVYN3MqsGMrsHsb9nyyBti2GUtGDsdXSxZh27hxQFkZPhwwEGteewOYMw8HJ07Gsr4vY/3gIcDsOdieX4A9hcWW7MX7i4Ely/HFpPcw5/F/4LMhw/Hxq29iyzuDsHPoCOwtGI19BSVY2/dN7C0ah8OTpmNf0TjsGFqEZU+/gi+KJmPxMy8DU+bi6KTZWPDsaxh492O45bpb0fnbt6HjD+/EeYFOME0f/IYBv2HClNIA025qJ9Po7mSUvJS7tUlkSl5K3mgLTB6/doms1+6GuG/wD5no/yBmHbOOyQAZIANkgAyQATJABsgAGSADZIAMkAEyUL8MUPLWb31G4lM9kzvq2KU7yrhv586drSxdnQ1YRK972ubmKXnDIlDDVVMiy/TIuUgPn48LrrsF9xcsx02lX1piVwSvJXnHAdeOA747DvjOWOBbY+3pmiWT94pS4NIS4MISICv/KLoOA7pIpm5V6TQU6DDELh2HAloyhxzBRUN2wvz9v/FS0UxkhHOREQohM5R1PJ1aG0Pn1a7PZ/IGTBPJDsl7ZGsFjmzdgq3Ll+Ajlby7KrFr3UqgYiPKRo3A0cWLUVlSCixdhtVvv4MVL70MzJiJQ5MnY/oTT2Jzfj4OTJqEA2PHY3dBIda/9hYOlIwHFi3FvrHjrf0rBg/BnlGjsbn/YGx5qz/2FxTj8OgJ+OiVt/Fl6SQcfW+mFXfmj8bcvz2NjW8MwSdvDcKkhx7DtvwSrH1jKPr+53/hPy/9AXpd81v87MF/IT6pIwJ+Ebw+SIay329WPaM3uh2vts5GyUvJS8lbex/UfqQ3KUrJ2qUk66h+60jZExYj/cDittr7MeuIdUQGyAAZIANkgAyQATJABsgAGSADZIAMkIHmywAlb/TbVsfJ3VHHLiPFpKQkS/JKxq5k88rzecUnuqdndq+re2yoGFOvHxQOISscQsjKmM1BTkgkbxhdw93R67pf4L7hS3DjmAO4RjJ4J1Rl8I47dlzyfnts1TN5xwHfHGcL3tz8I+g6+DA6DT6CTkNOCN4uw4DOjtIlH9ASHnYMlwzdBf+tr1qSt+vZlLxlZThSXo4dH5Rhw4I52F62FNi5DdhVicqyRTi28WOsLSnGvqnTUFlYDMydj3X93sVHb/XDwQkTgTlzMPe557CtYAQq84db2by7Ro7C7iEF2D5gKI5OnoaP+/XH4hdfRNm/X8HHgwZhZ3EJ1r3yOra8NQD7C0uxdUA+9o4sxaGx7+HIxOn4fNQ4LHvyRVS+nY+K/sPx3oN/x2s//TX633InXv35bbjjyp/g7TdHYW35fhiBVIi0Dvh98Pt9MPwGjED0RW9tnY2Sl5KXkrf2m5/2I71JUWDWr8BkfdZen8qesMg/Rmrvs6wj1hEZIANkgAyQATJABsgAGSADZIAMkAEyQAZaFgOUvNFvbx0nd0cdu6wupqenW4mjInIlk1efzStR3WrzlLxhmRY5x3oerzz/Nj3cDb2uuwn3FizBz8YexHeqpmmWaZu/V5XJK8/jvXoc8I1xwBXjge4FQE4+IFm5XYceQ7pk8bpK13xAS8ZwQEtO/jFcOhJKhKcAACAASURBVMyWvH2KZkIkb2Y4bAtoS0KLiLaLplrXdybv8emay8pwtLwce1Z/gI9nTcc2kbyfVQKfbcXWxfNxbP2HWD+2FFuLRmN7YTG+mjoDGwYPxSf9B6CioADHZs7EildfRXlBARa88AJ2Fo/G7sIi7BteiL1DR2DPiCJsH1GIilGFWDt0EMrHjwU2b0JF0Wh8/O4gVA4dgZ35RagYkI89I0tx7L2ZOFg6CUufeB6LHn0G294twK78MZj2yDNY8fIAjLjjr7jnyh9jcsF72LH9IIL+ZARNA0kBo0r0Gszk7UTBWptgbQyvc7pmTtdMCVu7hI12HekPJEre6P9Y5R+ArGMyQAbIABkgA2SADJABMkAGyAAZIANkgAw0PQYoeaPfZm65q+s6dumOCQkJ1mNLU1NTrefvisjNzc21RK9k9Krkle26rM6xoWP9ZvKKOD0+XbNM2WyXLtk90OO6X+LPwxbjhsI9uGY8IFJXpmm+dgzw3bHAVWOAr5UAPUYB4QIgNBzIFMmbD0vwpkt0St18IMNRMmX/qpKXfwRfG7YLgd6vQSRveii7QSVvMOC3nsmbJs/kLSvDMcnkXboEW+bPwdayJThWuRnYWYnNs6cDn36MTWPH4JOBg/F5yVh8Xjoe5QUjsXbIYHw0ZDA29R+Ijf0H4uC8OZjywnPYlJ+PfUWjcbC4BLuHDUfloMH48J13gA/XYu2YYmxdMBvYvR3Y/CnWjxuHTwYNw64RJagYVIBD46dYz+U9NO49LLEk79PYPagYO4eOxaYhpXjvsRfxQd+B6Nf7IRS8lI/508uQEkhB0O9DUsBEst+PFMOPZCOAgBndjqedTKO7k4mYkBuWPOA6IyMD8h8VMke6ysU+nZKATl6ryLJuZ2w5gpqSl5I32gKTx69dIuu1W67l/CMjuvdN1i/rlwyQATJABsgAGSADZIAMkAEyQAbIABkgA02PAUre6LeZeiZ31LFLd9T9gsGg5ZZE3IrMFdErkleiCF7xU80rk7cqOzYcCiHbKpLRmw2RvN2/81PcN3AWbinehh+WHsZ1Y45BMnlF9F49BriwEOheCIQK7IxcEbYicTVqlq6syz4igrWIENYi27oPP4LL8ndbkvel4llID+UgM5yNrHAYISkhLXbDSKPUZyavSF7JfhXJu1kk75ZybJkzBzsWL7Ik78FN661s3k+nTgI+XIOt48ej7OVX8Vn+SOwpHI31g4cCG9dj47hSLOnzkpXRi/KNWDW6EOuGDcW2wkJU5udjf0kJKoYMQdkbrwMfr8PikkJ8tXUjKlYvw803XIu9a1dh4bv9sX7ocFQWFAHT5gBTZwOTZ2LR489i5l/+B58PHYMdQ8biwwHFGP3QP/HWz29D8X3/wMCH++CFB59Bmhm0sniTAn4k+wNINQJIMQIIUvJSHDfyjGZKXkpeStjaJWy060h/IFHyRv/HKv+IYx2TATJABsgAGSADZIAMkAEyQAbIABkgA2Sg6TFAyRv9NlNp6446dhkpyr6JiYlW4ookGorolSmbe/XqZUlekb7NM5M3FIJb8maE83DJt6/HLx/6F3739mz8vqQSN5buxw3jgStLgF4jbEkrUy9rdm7WcECKCF1L6o4EwiOA7BFAjqtkFwBa5LWeBSJ5JZP3dbxUPBvpIZmuuUryhrIRsoqI3uhJ3oBpILVK8mJLOcpnz8GXq1Zh8+KF2LFqBbBjK9ZPnoC9C+Zh13vvYdmLfbHxzXfx6RvvYPvoUqByCyrmz8Ka4fnYOKYU2PIpsHk9Pn1vAirfm4T5fftg68iR+Gx0MdYNGwJs+Agbl8zD/Mlj8N1vXoKPVi4CvtwDbK/A0uH5WPLv14Hpc3BwzGQcmzgNix5/BiN+czs+6dsfH742FMPuewwv3nwHNg0cjaXPvYVZT72CWa8PRLrPRHLQjyS/lACS/UlWYSZvy8mIbarZz5S8lLzRFpg8fu0SWX8gUfJG/8cq/4hjHZMBMkAGyAAZIANkgAyQATJABsgAGSADZKDpMUDJG/02c8tdXdexy0hR9pFpm6VIG8lssiJ1VeyK8JWM3tqma452pm/9T9dcJXlF9IZDdiZvVjgHWXk9kXnxVUj9+s/Q9caHcMWjI3Hli/Pw3QGb8PVBn+HCoV+ix7BD6JF/EN2GH7alrYhdeTbvCCB3JJArcQTQzbGs67Itr6r0GnEMl+fvRvAPr6Nv8ZwGlrwmAgE/An4DKZrJW16OT6ZNx8EPP8L8kmJsXLQAqKzAlinvoXLiRByaPhNbBgzBwiefwfvPvIA1Q4fiD9d9B4/d2RurJo7FzmWLsPPDlcD+ndhatsiSvXsXzsNnM6Zi79xZ2L1wHvZ/vAYDXnkBN/3oOuyq3AjgIPDVfuCL3cCOSmwuKgamzMBX49/DsUnTMen+h9Hn+z9Fn2tvxJ96XomiJ/ui4O8v4rMxs4C5H2D70FKM+/szyPSZkCzeYCCAoD+IoD/JKtG+WWgn0+juZCJX5DtwumbK5uokNCUvJS8lbO0SNtp1pNduuZZH+77B40f/BzHrmHVMBsgAGSADZIAMkAEyQAbIABkgA2SADJCB+mWAkrd+6zMSn+qZ3FHHLiNF2de5XdbT0tKOZ/TK7MDO5/NKUmlWVpb1ukRdbrKSNyQnY51IyJoeOSucja7hPHTKOR8puZeg08XfQYfLf4zcn/wZ5/fug++9NA/XD96EqwZuwRXD96JbwWHkjrIFr0zj3Eumcy4Aug0Heo4EelRN7yzRWboVAheMBL496gCS/vAG+hbPRddwt6qpmuW75FSVaGTyyiC2FMMqyaYPm1aU4avyCqydMQPzRxdj7IB38dHsmcDGjfhs6jRUjCwCZs7F/sISrHr5NawZMgQfTxoP7PsMk4ry8ZNrvol/PHwfPlmzFDi4BziwB19UfAoc3Avs2ALs3grs2Y5H7rkT99x2K77YuQ1ffbEHn+/ahiNf7MHBHRVA+SbsGD8e+4pLcXDcJCujd/pTz6L4gUdx34VX4k+XXouif/XHfT+7Da/f+TfsHD8XmL0CZe+OQIYvANPnQzAQhN+sKv5A1Afra+tslLyUu9XJXd1OyUvJG22ByePXLpH1h5Bc0yP9wOK26P+IZR2zjskAGSADZIAMkAEyQAbIABkgA2SADJABMtB4GaDkbfi2cfsn97qOaWp0jwN37tzZkrkiemX6ZsnqVbHrjCJ+m6TkVWOtJyPrWuSEwlUlM7sbMrpdgs4XXYvkK3+DDv/xMHr8+R1c1Wcurhm6BVeN2I2v5+/GN0YcwOWFwKWFwEUicQvxv+ydB5gUVdawW9LETlXdPTlPhxlAzLrumlZdE8Zd036uOa1pUcwJE+aIASPgioEkgpJzzjkpGRSQHAcGhpn3/0/1FLS9jAgySDg+z/VWVfd0uPXeqtv35ZxLEyld4KgucHT1MalFBp/QCc7uspmMm97n7W9G7pS81ucQyVtavS7vvk7XvFPwmj6DNJG806ZRsWwZK2bM5Mu336bPF+1ZMGI4VdNnsKHfQNZ26ca27r3Y2r0Xc9v+l+0zprFxzkzKJBq3fD1bN63ii88+ojSSx0cfvMn28nVUblkLW9ZYZevG5cycPIrLLjiLS845g8vO+StNT/8zF5x6Euf/6TiuPvMUtkyfzLJvurKm89dU9hvIpp59WN79W9b2GUDvJ57nwb9ewnv3v8BFR53FW3c8yhvX3cPmQZOY3aUvRUYaab4Afn8api9QXVTy2iJR6wNXNqvkVckbf/PV/d1L2X3dRvZASCXv/h+s6o83bXNlQBlQBpQBZUAZUAaUAWVAGVAGlAFlQBlQBg58BlTy7v9zFC914/ftOU273tWcqfQtcRD2Or27Er3iQ3dVbF+6L+paSdcsH8wWvFLHftCdkreEcKSUYKgRBeGjSA8eQ9aRp5F/0gXknXYloUvu4djbX+Oi1/tw9VdzOeerFZzScTMndaniuK/h6K/hmK5wbFc4/ms44Ws4sbqc0gXO7byRrJve5Z1vYiJ595PkFcEbL3nXzp5N3y8+Z9mMaayaNJFlPXrDkJFs7NyNZW3bU9FnAD98/jmsXMqWZQvp/00Hnmh+F5eeczpNz/wLj9x3J5PHDWPbljWUb1pFlYjebRuo2rqWyvLVsHkllK2AdUvZPG86W+dMpWzqGDZPGEn5yKGs7/Et67p2pWrAQCr692froL5UDB3Ewi868MmtzXjrhua8dv39tLrlQZ678lY+e+A5xnf4jnxvGgGJ4PUFMKqL6fNj+mq34/2WTiWdSNM1H7iS9Y8W4Cp5VfLu6uarx/av6LUHQip5a/eeqT/YtH2VAWVAGVAGlAFlQBlQBpQBZUAZUAaUAWVAGTg4GVDJu//PW7x/it+35zTteldzyi6XCzku50/W5RXJK+mbpZa1eu31emMlb6wr3VfbtSZ57Q8YK3mtLxOOEAmXEAmXWiVcHEFKMFhCMNzQSumcHWpEdsMTyDvxHPLP+ie5lzaj8X1tOe2t0VzaeTnndFzFmV+XcdrX2zjl60r+0hVO7gp/qq5P/7qSpp3XkntjK97tOpziSOOYdM2RWk7XHBW8hs8gEBPJO3PoUMZKyuQF81g5fjzj3n4fhoxia9cerPmiEz99+jmLOnXmp2GD+L+zT+OF5nczuuc3rJs3iy2SnnnDSqo2r7Ykr4jeys1rqJKydR1sXQObV0DZz7B6IZvnTqZ8+hgqJovgHcTK7l1Y2bkjm7/9lsq+/djSqyfrenWFMUP5qVNn5rfvwrz23zLjk67Mbt+DEe98xrt3PMwzN91NtsuH3xCpu1PyGip5+aMFpr7/7uW2Sl6VvLu6+eoxlbz6g2f/D5y1zbXNlQFlQBlQBpQBZUAZUAaUAWVAGVAGlAFlQBnYNQMqeXfdLrXJS7zUjd+35a5d72pO2X7M7XZbsjc7O9sSuyJ57SKi13altVXXquQVwWtbajHZkXCEknAJJeFSSsINoyVYSiRYSjhcSlG4hLxwhIJGR5JZ0pgzLruaM/5+HSdedC1/uuJOGl3yb4ovup1jb3+Zi94dzuUdF3NRp5Wc8dVaTutWxfGdt3PSN3BG13Iu7rScohtfp3XXoZbkLQ5HCIZDluwNhmU93tpak3fXkldSNm+YP4/vRw5n3oABjHrlLco6dWdzp25WmffOh6zo0JnZX34FC+axbeZUNk2byIapE6hY8AOsXgKbVliRu9u2rLYEb4UlftfA1vVUbl7F9o0/U756IWWLZ8KimfDDJDaPGsTMth8y6fXXqOrdh4pve7CqYweW9+wCMycy9cNPGPjMK3S482E63vEoX9zUnM9ve4jBb7Wh7VMvk+P2k+5PxzD9eE1/dTSvRvKqZN29ZP2j20glr0reXd189ZhK3tocIOpr7/9Buba5trkyoAwoA8qAMqAMKAPKgDKgDCgDyoAyoAwczAyo5N3//MZL3d3t20JX6tj5ZXtfaonslXMp6/U2btzYKiJ7ZVsEr539OHY7Nkh2byVwrUpe+VCSTtcu4VCYcChCJCSid6fkPbLhUZSUNub4k//CnQ88xH+7fsPQyVMZMXUGIyfPZOTEmYyYOJPB46bRtvN3XN2sBZFL7yLjkgdofM8HnPfeGC7uuISmXddw3tdruLT7Oq755mciN73Gu50GUBxuSFTyhndKXkv01s6avJKqOT6SVyRv5fLlrJs3h1m9ejG7zWcMe+Qpfm77OZu7dGfjV12Y995HDHn2edb170/VtMlUzJrKth+mwo9zYe0SKF9DxablsG0dlK+DTath46po2bAcNq+yonqr1i2B1T+yacZ4Zn/XhXEfvsfabv8/1LlPX1Z9/iUL27Zh68jBMGUCj5x+DgOffo2fO/ZkYdtOzHu3PVNe/4RP73qY1WOmkeuOjeQVyRstmq75wJecf7Rk/aPfXyWvSt7YG65u71+5a7e3PQCSgdLBPNjWz77/B9va5trmyoAyoAwoA8qAMqAMKAPKgDKgDCgDyoAycDgwoJJ3/3O+O6kb/7g9x2lLXXvu067l+SJ5JapXzqfsSxSvCN4mTZrsEL4SFLsvxG6sEK41yWtH8EotUbxWJG8kQlT0hq31eCMlDSkqCvHAA4/QpWt3Rk2cwtBJ0xgyeTrDJ89g1JRZjJn6A2Omfs+4ad8zaeYcRk2YykftO/NUqzZcduejRM68nKxT/0H+xXdxUrN3uPK9wdzcYSY3dpxD8F/P8X7n/hSHSwmGJR20pGq2S+1G8npN7y/SNbNihSV5t6/4maWjRzH/i44MffI5fnj3Q1Z92ckSvZs6d2Py628xo01btk6bRNXiObByEaz9CcqWQ/lK2PQzq+dMZnavr1ncsyuLenRhTvdOLBzcGzathC2SunkNW5YvYvvyxVT8OI/Fg/qxsV8/1nX9hmmt3uanL75kVtu2vHn1tdxSehL/ve1B1vceRsWgMaz86jsWfPQlg55+nZ/7j6TQG8Bn+JB1eA2fb0dRyauS94+WuLt7f5W8Knntm6zWf4zglXa3B0AysDkcBuX6Hff/oFzbXNtcGVAGlAFlQBlQBpQBZUAZUAaUAWVAGVAGDmYGVPLuf37jJe7u9u05zpokr8yDiuC1iz0fLedWonnFj9qyN9ad2tux0nZPt/dS8oqkjVglJBGxNZRjjz2OC5o25aqrr+bEk06ipLSUwqIiSkobEi4ppag4RChSyput3mHEmPHMnLeIkVNmMmLqLIaOm8LoSRLFO8Oqx02ZyczZC5gz70c6du5Oh296MHLidIaMncRrH3zKFXc8SMO/XUXWKZcTvvQ/nPngBxx51YN83Kk3wXApxZbkLalej1dEbzRlszSuLIYsDSwNbp+s2JP6UroXcj1WeTnD+JWJapnENrEieU0vaT6ThdOnsfXnZZT99JNVb1uxnLUzZzCv23cMe60VW4eOYvTrrVj6ZSfmf/Ip89p+xqSPPmHL9Mnw8yLYuBzKVrB9w9Ko5C1bztetX2XdyIFUjh4CY4exbdRgNo0bxprJY6BMJO+6aNmyHtavZmaPbsz/ujPlgwcx4Lnn6Hz/Azx8xlk8dlZTHvjz+bQ875+s+W4QjJxI5cBRLP60E3M+aM/wVh9TbKThM6PpmW3JK4JXJa9K3t1J1j/6cZW8Knntm6nWKnkP5oG+fvb9P9DXNtc2VwaUAWVAGVAGlAFlQBlQBpQBZUAZUAaUgf3FgEre/c9arP/7Ldu2N7Trmuaba3q8oKDAiuwVDxm/Tq+I3j0Vu7HP32PJK28ogteKio2UEIqUUBwMU1gUtMTtMccez23/voPPv/yK+QsX8dPSZcydt4CZ3/9Ar959aXZvc0457QxKGjamoChIMFJK6ZFHccxJJ3PFNdfzZuuPGT52Mt/P/4nRE6czauIMxkyaydhJMxkzYTqjx01l9PhplvgdNWkmo6fMYtj4afQfOYlu/UeS2/AEchufTPEJZ/O3y2/klbfepyhYYkXz7iqid99KXoExKnoN08BvGsybOZ1Ny5exfskSypb/zKpFC1m7cCGrp8+i94dtWDZiLN1efZMvH3uCGV98yejWH9KxxdOsnjCezYvmUbVpFZXlsu7uGti+3hK+80YOZMvEMTBhDIwfQeX44ZSNH86K8SNgkzx3I2xeDxvWsG7yeHq89hJjPv2IIa1bMbX9f3n1mn/xzs2381O3PjzX9J88+KdzmftJBxgzlW2DR7Lm277Meq8dXzZ/nCJvtIMZpsjraESvRPXW9gUuvmPZncOupRPJZ5BU4EVFRUgnkVzntlh8Izdth5iXbfu41oePnFbJq5K3pputHt9/0te+Zss1vbbvG/r6+39ArG2uba4MKAPKgDKgDCgDyoAyoAwoA8qAMqAMKAPKwO9jQCXv72u/2uBvd37KnvO0a5lvtrftOnYO2ul0WkGm4rLsdXollbMd5WuLXnvd3j1J6bzHktcyxGFZ21ZEbwmR0kYcd8JJ/PvOu/n0s89ZvGQpy5avZNGPS+jZuy/9Bgxi0NBh1vGVq9ewcPFPfD97Lt/17M0DDz/GyaeeTlG4hPxghIJQKUceeyLHnXQqV/7f9bzx9vuMGDuZmXMXM3LsZEvyjps4wxK+dpRvNNJ3BkNHjefNt0XollLasAmFxRFCkYaUNjqqWvLKurz/G9G77yXvTiD9psn4USOYYJVRjBs5mhFDRjJiiNRjGT5gNCP7jWRUz0FM6NGbid27M6Xbtwz8pC193v8I1qyB8k1QvoGq8vVUbl5trbu7fOYkNkyZQPnEsWybMJJtk0ZRNnUsG3+YBhvXwLbNULaRxePH8sadt3PXmaexdeYkPnvmMeb27M6L113H1olT+az54zx21qU8ftpFTHr1Axg4mu3Dx1hlUbsOdH/y+R2SNyqv5bsFqsvO7/lHdCLpIPK+KnkPH2m7p4JeJa9K3tgbqW7vP7Eb29b2oEYlb+3eM2vjPqyvqedMGVAGlAFlQBlQBpQBZUAZUAaUAWVAGVAGlIHaZ0Alb+238Z5y/Hslb+z86K62xWvZGYalFk8poteWvLGRurvb3mvJe9wJJ3Lr7XdYYnfegkWW2JW6/8DBDBw81CpLf17B6rXrrWjeXn36WdJ39NjxyPFVazcwdeYPVunRdwB33Xs/J5/6V4IljSkMlVIULiXc6EiOP/kULr/6Gt55/yMGDRvF7PmLGT1+CmMmzWDomEm8/WFbbr3rXo48+gQipU0oDpYSCkXX4BXJGy5pTDAsgjdaJHVzMCTPkdTN0fWC7cb8/emad8Locrnxmz7GjhxOxZYy5L9tFbChHDZsh1UVsLoSVm+FjVuBKqgq20z/rt2YM3w0re64j5GftIfVa2FzGRUb10JFGZXbNrK9bDXr5s5kw4xJbJ4+nq0/TGHb4tmwZV1UCm9Yz6whw2n3bEvm9etLuxaPMn9oH+YN6U3P1q0onzGNzx9/im5Pv8J7197N8+deTZc7HmHTtwOpGjEOxkygrOcARr3zEYUeA391dHK0I4jkTcNXy9G8u+tE0jHk86jkVclbk/y1Ja9wYl9IRTgdTrLJ7ke2aLPbQes/Rngeju1us3c49bs9HTTq83eOnbQttC2UAWVAGVAGlAFlQBlQBpQBZUAZUAaUAWXgcGNAJe+Bx7w9r27X9hznb61/bR5YXkPW7k1PT7fErqRwFkcpRVI528LXju61JW9N0b17LXmv/r9rrCjd6bO+Z+r0mZbUFcErkbxr12+0Inl79OrDtz16IWL35xWrWLVmHVOmzeCrjl3o8s13jJ88jZ9XrWXl2o1MnvE907+fS7cefbjvwUc48c+nUBgKUxwpJdSwEY2POZaT/nIqV15zLXc1u5+rr72Ro44/mXCjowmWHElBUbha3kYFbjBUQlFxmHBJI0KRRpboFdlrlf0geaVjmobB6BHDqaqooGzTFmbPW8oNd7Xgohuf5LzbXuGsW17l3FteoemNT7KmHLZtr+K7b3uwaNpMPnm4Ba/dcAev3nUf3T9ux6aflsHmciq2lFNVviUqc9eugDVLoWwVlEmU7zoWTJnMa48/xY3nXsLD/7wBfl7GzP492bb4B6qWzmXNtAkMbteWhb0GsLjbAJ674BpeOO8aXr/gXyz/qieMngzjp8DgUUxp9wUFOySvrEVs4jMD+EyVvDWJRT1+4EhnSX0g/whABgX2xfdwE03xN6Ffu7noYyp+a4OBw7XvHW4/RvT7Hng/RvSc6DlRBpQBZUAZUAaUAWVAGVAGlAFlQBlQBg4OBlTyHnjnyZ5Xt2t7jvO31jXNs9p/L4+npqZaAWnZ2dlI6uZ4ySuy1xa8Uu9zyRsuKeXIo47h/KYX8fSzLRkwaAjTZsxi3IRJiNwdMWrMDrE7eep0OnTqwlcdO1uP/7xitRXJO3z0OL7t1Y8OXbox44d5luxdvnq9JXxnzZ1Pr379ufu+5px82ukESxtSGIpQEAwTLGlEMNKIUMmRVh2UiF2RwaFwdZGFimXt4FIrZfP+l7wmfr+sPyiSdxSVWyup2FLBprIqJsxexRX/eYPTb3mXP9/6Cafc8hFn3/waS8ugvAo6d+3GisVLGNmpK2/cfR/LRk3ktvP+zpUnn8t9/7yD1i+0Zvzg8axe8COUl8H65VC2kq3fT2bBoAE8dtPt/P2Uc7nz0uu4/eJ/QlkZ6xfMgjU/wvqlrJ42kY3TpjHhs048ft5VPHn2VTx5xhW88LerGf7cO1QNm0Dl8HEwdgo/9exHnttLeloafp+sMWziNwP4VfLqGr+5B47MrUms25JXLsT2xVO2D6fBTfxNqKabix5XwVtbDByufe9wus7odz3wfojoOdFzogwoA8qAMqAMKAPKgDKgDCgDyoAyoAwcPAyo5D3wz5U9z27X9pynXdvH7do+btcy92pvy3Pi52KFgYKCAkv2SmTv0UcfbUX1itiVQDYpdirneNm7V5G8YckNHY5QFApbpXGTozn6uOM59/wLaPnCS0hqZll3d/zEyXT++huGDh9ppXOWNXkl2rdXn/507PIN389ZgEjdtRs3M3TEGPoNHErPvgOYt2gJy1evZe7CxcycPY/p38/hm+960ez+h6wI35AleRta6+4WB0uQqN2o4A1Vm22RvRHC4T9S8krkq8HI4aPYvrWKii3bWbexigkLt9D0rlacfMvHnHBLe0665b+ccVMrlmyCsm2VfPNtD8o3bGTD3Ll0f+99pvUewC3nX84Nf7uah69/mFcfb80Lj7zJFWdfSt/2XzD4s48Y++VHLOr7DfP69KTt82/Q8t6nebtFK9555k3YuNESwVWrFrJ9yWxYvoQhbdrxwLl/p/lpl/DIGZfz0J8v5dULb+SdK25jfY8hbB8yFsZOZf3wseR5Dfx+nyV5A6ZJQCWvCt6DQPCK+P01ySsX0sNhoBN/U4m/eei+yt3aZiB28HI49Dn9jgf+oFzPkZ4jZUAZUAaUAWVAGVAGlAFlQBlQBpQBZUAZOJAYUMl74PNoz7PbtT3nxtoj5AAAIABJREFUadf2cbu2j9u1zMHa21LHz8nKMWEyKytrRwpnie5t2LDhjhTOdjRvrOyV7b2WvKFICaGIvfZttA6GS5DS5OhjaXrRJTz51DOW1BXhO2nKNEv4Tpg8xVqTd+nPKxk+cix9+g+m23e9Wbh4KWvWbWLZ8tUMGT6a73r1Y+DQkSz4aTmr1m1h2qx5TJ0xh2kzZvNN9578594H+PMpp1tr6waDdgTvTskbCZf8wZJXonl9jBw+koptVWzbBtPmrebSe97g5BtbccKNn3Dcjf/lhBvbccYNb1jpmisrKunetRtlK1eybckilk+ZyOwx4+jc5iu6/rcXbz3fnueeaMcLT3zMIzc/zMQuPfipd3eW9e7Ekr5fs2hwfzq93553XmlDq1fa8u4bn7B6yVK2rlpCxc/zYPkC1k+awON/v4pmZ1xI81Mv4bEzr+aBky/lxQtu4InTL2NIy7fZNnAsjJvB4p4DyPOKDDNV8h4kYrOmqNbD8bj9L1zkAik57qXYF1O52B5IN/La+izxN5X4m4fuq+StbQbswcvh0udqqy/r6x74g309R3qOlAFlQBlQBpQBZUAZUAaUAWVAGVAGlAFlYG8YUMl74HNjz7PbtT3nadf2cbu2j9dU1zQn63K5cDqdZGZmWpG79nq9InslfXO84N1ryStRsxLJK6VY0ifH1LJdUipr4EYfb9zkKM4593yebfm8JXxn/TCHQYOH8cVXnZg5ay5Lf17FipVrGTp8NP0HDrVqEb2r121i9vzFjBgzkd79hzJm/DSWLl/Lug1bGDFqHJOnzmDkqLGcd15Tfk3yhiMNrZTNwVCptWavXYes6N+I1TCS61oaSzqT3ej2yZD6pXQv5Hqs8nKGROjuDrpouuaA38eoasm78f8vo/vwix9xyvUvc8KN73HiDa350w3v8efr3+Hs61qycj2yKC89vu7KhiU/sXHuLMoXz2fSsBG0fPoVZv2whhnfl9Gx8zhat+pKx/e7sH76fGZ/+w0zv27PpqljWTBiON0//4ae341k8rRlrF4PkyfOZO3SJVSuWAxLF/DeAw9z/4VX8kjTq3nknKt58txraXbiRbxyya280PQ6njv3KlZ2H8TGAaNodce95FZLXms9XpG9ViRvAJ/P/xvaYXftVPPjse0v2/Z5sWvpBHIeRORJxKaEsufl5e2Isn0jN23HOZPtw1FyHu7fWSWvz8rpH9t/arp56HGVvbXFgH3NFg53f++s+Z6gf6ttowwoA8qAMqAMKAPKgDKgDCgDyoAyoAwoA8qAMnAoMqCS98Dnene+aneP23Okdl3TXKwdqGbPpRYWFlru0o7qjUiW5WDwF2WvInktyRuUhX53llA4TGyRlM6xJVJSQpOjjub885vyZItnGDx4OD/8MJ9Ro8YxYMBQa3vZslV8//08Ro4aR59+Axg3YTIrVq9j7foyJkyexsDBw+na7Tu+6fYdz7/wMhdddCklJQ13KXl3rs8rqZz/t4QjJVbYs9hvaaCjjjqKQCCwQ4rEnpS9krw+A0lvPLDfALZXwNLVm2l6/YP86frXOP76dzj1+pf4bNAivhg4nwuvfYC1m6pgexXfdOzIuh8XUrlkIZvnz+XVFs/TsuU7NH/2A6Yu3c66bTB7zko++7gjM8dMZ/uadayaP49h3/Zk2shxbFi1nq3bYF05LFoFDz/1NhPGz6TsxwWsnTmV9q++y+v3PcMj/7iZRy68licuuIEHTr2Clk1v5I3L/82z5/+Tj25tzuyve3NGYYQcry8qv/0mhs+H3/QRMP34dyu6f1/HjG1/2bbht2vpBHJBV8l74K+N+0fJ5ljJK/8CRop9kTwUBwO7+k52P4rtNzXdQPS4it7aYMBmT1jcFaN67PfdK7X9tP2UAWVAGVAGlAFlQBlQBpQBZUAZUAaUAWVAGTi4GVDJe/CdP3vevabanhP9rfXu5mVF7NqiV4JWS0tLLb8pKZz3UvLaaZFrrsUo76rIWrkiZpsceQznntuUFi2epXfv/syaNYfRo8czfNgoa3vl6rVMnjq9eg3ffvTo1YfX3nzLWve3YaMjadToSEvulpY2stbf/eWavPbniq7NK+8ZX+zPVtuSd1Df/pbkXbB0Leddcx9/uvYVjvu/l/ls4Bx+3AxLy6B7/1GsWb+FrZvL6dj+v/wwYQwVSxexYtYsXn76NSKN/8qnvabwUKuODJu5lHXb4fu5K/hh9lIqKqF8KwweMo4tW2HLdli3FfqOmUfzZz+m5Vsd6d17NOVLl7D9x4UM7PgdbV76iLceepn7L72VJy++jcf+di2Pn30Nr195Jy9ffiv3nH4hD/7jX4S9aWQZtuT14d0heWu/08V3jvjOINDLzUslr0remiSySl6N5N3dzVEfr32xbV+7VfLW/n1Tf9BpGysDyoAyoAwoA8qAMqAMKAPKgDKgDCgDyoAycPAxoJL34Dtn8f4qft+eE93bOn7eWl4/PT0dEbwieyUzsdTiOWtd8opJ3lnstXOljkbXRsKlNDnyaM444yzuv/8h+vYdwPffz2HgoCH06defN95qxcWXXkZp4yOJlDaiKBSOpoiujiKWL7Ezajf2vWQ79v1+ub0/JG+az8egfv2orIANm6u47p5nOPHKJ7jy4TYs2gQrNm1n5cZtrN6wmTVr11GxdQudvvyMtUsXsWDKBKaOGssHH3YmfPSFnH3VI3QZsZQ3O47k5f/2YfbKKkZMWcCmSpgyezEzf1rPiJk/80q7HtzxdGs+6j6a9zsN5Y4HXuOTDztStnABLF3EpL6DePfZVnz+3tfcevFdtPjHfTx1wW08fs61vPGvZrxw9R3cfNqFFDn95BgB0k0fPsPE9Pmssr9uErvrFCp5Ve7WJHft4yp5VfLG3wx1v/albnwb2wMZuabvr/uHvs/BNzDWc6bnTBlQBpQBZUAZUAaUAWVAGVAGlAFlQBlQBg5XBlTyHnzsx/ur+H17TnRv6/g51tTUVCvbrbxPVlaWFckr2YmPOeaY/St5JaRY1k+NLhAcIhIW0RuVr9HtCI0bN+HU007n/KYXWmI3XNKQwuIQUocipQTDJdZ6v1Zq6F8I5HjB++v7+0Pypgd8DLQkbyWby2H4xPmcftUD3PlsG1aUwfqyLawv28z6TWWsW7+e8vItfPnl58ycOZMly1bSa8BY7njwLU69uBl3P/1f2veZxT3Pvk+PkdN5u+0XtG7bjpmzpvP8C8/zXtv2dO47kqHTl9Fp6GxueupDEotO48rbW9Lh6+FMGj6OZbNmM3HYeN58+SMefeRd7rzuKZ6+5gla/qMZj55/Pa/f1JwH/3EDx+eEyPRUp2WulrwBf+2uwRt/Ad9dpxDI5W80kldlry1142uVvCp542+Guq+SN/5eo/sH3yBaz5meM2VAGVAGlAFlQBlQBpQBZUAZUAaUAWVAGTiUGFDJe/DxHO+v4vf3Vu7af7ereWwRvbIkpTxH+Jf1ekX01lok787o3V3L1mCwmFA4+MtiSdvo2r7BcJhoiVSLXZG7dolE1/8NyZrAv1xkWPZ3997y+O+VvNLx4jvfzhNpYJpe0gI++vbpxeZNZWwrr6S8AgaNn8vL73/Bxq2VbN5abpWyrVvZtGUb68u28tlXnWndvguPt+7MVQ+9w32vduOsa57imY96sWI7tHr7LU47McL9d/6dVs/dTufWT/DmY7dwy1XnceafT+Dj1p/Qul13Lrz7NUIX3Y/zyMt56v0+9B01jzk/lTF1/gbebNOL+55uy7/+9STP3/ESb976FA9efB3XnX4eDTNyyQmkYZoGZmBn9K5IXlmP1y61fRHd2ZamtU6yDbddq+RVuRsvdeP3VfKq5N3VzVCP7V/Ra1+z5Zpe2/cNff2Db0Cs50zPmTKgDCgDyoAyoAwoA8qAMqAMKAPKgDKgDBzuDMR7JplPi5/DdLvd1jGdYzsw+svuzkO834rft+dMa6rjz3/8vvQZp9NpOcp9KnnDoRB2sURrOESoutjH7ToULCYcjpZQWIRvtfQV0RsOEbSKiN7/lbyhcDRFczgURoodDfxb5K79nH0teSWdsWGa1cXAML0EAj66du1C71496dHtO777tjedvunNV19/R8dOnenQ4Ss6dOjAVx068kWHLnz2ZWc+bPs5Dz33Jv959b/c+WoHLr/ndS666Smefq8Dg8dNpU/3Dkwf3pUO7z/GBy/cxldv3c+3Hz/Hhy8+wEevPs26n36y1ua98fF3Of2m5zj20vt46M2vafl+F95s150X3+/Ei+934a7H3+aFVz+j2XUPcP3ZV3JK8ZEUGwEyDZmIN/CaXgy/fA8D0zB3yF2VvCpX42Xqgbqvklclb/zNT/f3r+CV9rYHKrsb+Bzug3n9/gfGAF3Pg54HZUAZUAaUAWVAGVAGlAFlQBlQBpQBZUAZ2N8MqOQ99JiLl7rx+/acaU317uaxhRn5W3le7UneHaI2Km3DoSARq4SIiAwWyRsSyVtEyCq/TfJG1/KNWHI3KnlF+Nrr8sp7VUcH7yaV8++VvBLZaqcwtter9Zom0RKVpD6/id/vs57nF1FqSCRsgPS0TGudW1nrNnrMj8+UyOA0/P50zEA2zkAuqWkFuAKFuAP5OI0MDF86aaaPDK+TDCOBDKMB6UYyfk8SOQEP6V4X2YF0TCODVF8Oyf4Cksx8Unx5JHkCuHxpeLxpGIa8RxZeM410M5McfxY+p0GGL0DAitY18Rle/D4Dn2FYgldE7/68uO0OeoFXPo+ma1bpXJNkVsmrknd3N0N9vPalrz1QUcl76A1W9+eYQN9L+VEGlAFlQBlQBpQBZUAZUAaUAWVAGVAGlIFDlQGVvIce2/F+K37fnjOtqd7dvLVEdu87yWtF6ko0bVS8isAVmStpk4tD0SKRubbkLQmHkRIVvjslbzBUSDBUbP1NkaRh/kW6ZonmjaZvlqhdK3o3GCK0o4RjtouxUkHvJ8lrRfBKFO8vionpM/BXS16fzyQ94CfNNEn3+a1iyVTDJGD4SDOjx0yPF78p8jiA3x+watNrEhABLLLVEq4BSxRbAtaKuPVhWnLYhym5uD0+/EYAnyEdQ8RxOqYvYH0e03QTMLxkBwL4DTey7zU8+ANpeGXtXX8Aw2uQ5vOT5pM1eSWC17Qk9f6eoN8d9Cp5Ve7WJHft4yp5VfLu7maoj6vkPVR/HOj3OvR+HOg51XOqDCgDyoAyoAwoA8qAMqAMKAPKgDKgDByaDKjkPfTOa7zfit+vSe7GH69p/lpez37u74vk3RGtGyEYKkWibCOhYkpCRZbUtdMuRyVvNIJXtqVY0bwhibotIhgurK6LKYhEKIiUUPQLySvr9Mpzo9G+dspnkb0Rq0QoDZZQEhTRXB3NuxvJa6dtLikpoVGjRjRp0sTKX203TGz9YpoHcqPl5QzDiiC10hb7/XgC0WL6RaT6MXwSvSti1rCKRPJK6ma/z0Oa31stT0XsRktU4PpIr96XC7W8jiVozQAZRoAMr0m610Oa6cHvk0WV5TNIZK25Uy77DbyGl4DXT5pXInID+MwAhiGfKyp5fb6oRBaR7PfJWrfyWiKkd669K+9vrb8r38N6jz+mg+0OepW8KnltmVtTrZJXJW9NN0E9Xvty125j+14q13T9IfLH3E+13bXdlQFlQBlQBpQBZUAZUAaUAWVAGVAGlAFlQBk4cBlQyXvgnpu97TfxfmtP9+051dha5ltj9+3tvZe8MevthkTIWpI3Qkm15JVIXWutXGv93MjOSFv774LR9XuD4eJqyVuIbBdEwpboLbbW4o0grx0Vw9VpmC3ZG0IkrQhdkcUloTClwUi15N0pg22R+2v175G8EvnqDQTwBAL4/GmWmDV/IXllUttvSVRLsPpE0ooA3il5JYpXSoYRFb3+HcLVb0XsZhhpZBoibn8peWWt3B1rAPtMvLJ+rkQM+9JIN9IsyWvJXEs+Syex5bAI5ID1uWxAbcDs/QOhtj+TXdvA2rUALZ9T0zWr7FXJW/NNML7/2OJN6/0nOQ/3trav2cLigXBv0c9Q8/VC20bbRhlQBpQBZUAZUAaUAWVAGVAGlAFlQBlQBpSB/c+ASt793+a1zbk9L7+3tT2nGlvHzjPHHt87yVsdwWtH5IpolfTMoWCQklC0hK19OV5ileLiEMXFksZZ0inLcyXtsqRhLqY4UkhxqIDiUCFFoSIKJd1zqISwFRkcTf8cCZcQjkSLpG4WgWwJ3uJiSoqLCVmvW0w07XMhwWDRb0rbvHeSNxppa8lSf7qVEjngy7CkbDTC1rBkrkhWn5mG6ZMi0bLR6FuJApZIXoneTTd8luDNrK5FAO8AzJTUzOkEzHQrjbP8nTxmyV2f30qxLJBIBK/HFy3ymGn4kDV0TdOwUjKbpqu6FtErryGff+f7HIiT7/Hwx0Ir2wK0fAeVvCp5VfLu7Mux/Vq27X5k95/YG4Fuq+jdHwzY7B2I95n4/qL7NV9LtG20bZQBZUAZUAaUAWVAGVAGlAFlQBlQBpQBZUAZqB0GVPLWTrv+kbza8/J7W9tzqrF17Fxu7PF9JHlFyhZRLGvqBiOEiotoVJBGaX46BQVhCgoaUppXRMO8PEKFBRQVhygMNqYw3NgSuoXBQgqKiiksLCRUkEO4MI9QUYhIMEjjYC4NgwXk5kXIzmtEfn6Eovwignn5hAryCRYUUFyQT1FhDoWF2RQV5VJcXEBhYT7FxUVWxO++j+SVtW6jEbF+XzYBXxaZpo8MSX9sGFa65WiK5DRL8oro9frSMCSNsy+VDDOFdNNLhmGSaXjINLykGZJiOW2HzJW1cKOSOMOKys02ksg2EwmYXrxmALcvG6cnHZ/Li8/lwulxkeDxUteTTj1POikeH253Kqa3Lj6jHl5vCh6PuzrNs8/6/LEXjz3dlg5S09/si84TD38stLItQMv7qORVyauSt+aboN2P7P4TeyPQbZW8+4MBmz1hcV/cG/Q1au7v2jbaNsqAMqAMKAPKwMHDgP1bWsdIB8850/6l50oZUAaUAWVAGVAGaosBe2xov77tP2Ln7txut+VEdPx4cHBoz8v/3tqeW/21eu8kr73uraROlgjaUBFFoQLyw8VkBBty403X06dNC470OcjKCTJkyDTOK23Mn9N8lORkUxhuhDf/KLz5TUjLySOQkUlO4ZEsXrSK049sTGnAS27ARzAvndKsRCI5JjmFf2Lhz0AVsAVuvuxygmlp5Ofm8fwLz1NetpITjgmTnWmSl5tFQUGeJQB/TfDKY3sayftSuteKkJW1cQ3Th8ubi2lkkedJIN9Tj4AhEjYdw5+D25tOmi+Ax+0h1ZdOm8/a8lXbl8hyOgikNiDN7STdVQ/TmYDHzCTFnUmq08CV6sSbmozP7cH0ZPDik4/Rt80TRJwOMo0GuOS5gVJGjJkH5cB2aRS49ZGnubllG5YDG6wj21kwdwgFOQ48rnrVF4HomsL2BUNqAU0uJLEXE3s/to79m9jjsX8X+5zfsx0PfzzEcoGT11fJq5JXJW/NNza7H9n9J3ZgoNsqefcHAzZ7wuLvuSfo39bcz7VttG2UAWVAGVAGlIGDmwH5PZ2WlkZWVpb1D9+Liop2/M6VbS3aBsqAMqAMKAPKgDJwKDEggX52KSgowC72mDYzM9PyFfb+4VDH+xWZT4uft1PJe3CP+eM5tuft96S251nj672SvLIWbjgUJByKpkkuDgXJLQ6SEwoTyCvkhqubMuzj/3CMy0EgvYBBg37gwqJGnOpyEU73kR0Mc8Etj7KMqKPcVgkbt1tWEsrKoWILVFbB1g28+8T1BL0OMnL/Qv+RG8jNOpZJA0fR9a3XoXw9VFVQXlUZtb/by639ZfPnUpiXa/0YikQivxrNu3eSV9Iee3B6fTjTGzNwxEzGD+9HpnxfSZ1sZuIO5PNsy5egYi1UrqP6EwIroHIJVMlnrWRb2SquuPwivGk5DBs73Xpe1M9WsHjhYjKygzzf4lEGtnmAcIIDn9NBvRQ/SYEm9Bv0PUcXNMI4oi4tWz7PLQ8+xc0tP6VFu/44UgK4zSTGjGhPfqZI3rrWhUHW8o2mjd7ZKQQkW9oKbLEXldjteBB/7bH45+7pfjzc8eDKRU5eUyWvSl6VvDv7cnw/s/uR3X/iBwe6r6K3thmw2RMW4/nU/Zr7rraNto0yoAwoA8qAMnDoM2D/Di8tLeWEE07gxBNP3FFkX8pxxx2nRdtAGVAGlAFlQBlQBg5JBo499ljsYo95ZD8QCFilNt3DgTbWjv+uMp8WP2enkvfQ+n1gz9vvaW3PtcbWv0vyRkT0BospLC4hUHgUA0dO5l9/v5Bmfz+JMR/cSmldBy5nOoMGzuOv6U04MdHLt+0/5N4nHuFP/3qQDhNWkOTLxvDn4s46hQVzKjkrq5hjE1PI8ObQ8qkWvP/gpTRMduD3H0f/UeVkZR7PlIHDaHbO8YTrOkhJdJBg+qiTnIYzOZ2Qx0fjgJ/iHEndXERtSF4Rpb40H0lmJgUnX8nwBVtZtGYNwZJ8UlNSMHyZ1PNk0KLFY7zzwKWE6jvwJDlISk3G5ayHx9UAl9tLqtdH/5HD+NslF5LgdJGc6sLlceJ0pZLsdHPUSafw4/qtbBf1W7UQts2VsF3ebtuRBG+YoaPnUWXLcaq478FHad7iddYBW4FtrOWn+YMpyopG8ro8Lrym15K8tuiVC0j8hVPAEkhiAfMZJnaRtYFjH5Nt+7F9dYGMf/1YaO1teS+VvCp5VfLWfIOz+5HdZ+IHB7qvkre2GbDZs+4TMWvB76t7hb5Ozf1f20bbRhlQBpQBZUAZOHAZkLGRzFfIRObRRx/NMcccY9VHHXUUWrQNlAFlQBlQBpQBZeBwYEDGQPY4SMZCMi4S2Sv/8E0ynMSLz0N5bBv/XWU+LX7OTiXvgTu23xs27Xn7va3tOVep91ryiuCVEioupqC4Md78E62I1usv/Cv3nBth1Pu3U+hwkJroYWj/GZyXfzTM/5Eubd6hvmlw3LVP0G7sahypadRt4KG+5xjmzd7Oqf48iuXvGvho2eIJ2jQ/j4jDgTs1wrylsG2z5CKuoNlZR1N6hIOxA3pQWBTB481j8bzVHFt8JPmeAIU5eVbYf1TyhgmFdlX2Ll2z1zRJ9RrU96bz72fe4blPe/BGhx78+6HH8SYnY6SkUs+VxtPPPsm7zc8l5HDgrOOgfkIiiclJNEhKpk79ZJLcJn1HDOGsSy/EkZjCEcluGjid1E9NpX6qG0dCCo4UFy2eeohvP3yUjDoOHnzyCV7777c46mTiqJ+Fw5GM44g61Kl3BC2eeYb3PvmKBq40Fi7/iaaXnEFiHQfOeg48KUfgdafgNTx4TB9Ow4/L8OMReWt68RtO/BKdbARwGQH87lTSPcn4vE4Mr4HXm4FpZFhrDvsMD16vieH1EvCmkOZNJmB48Mt6xLuIFN4XkNvQCvT2tryunapC0jrk5eVhC783ctMg12MV2baPa334SGH5BwBShBeXy2UV+2a4N0wejH9j3yTsPhM/ONB9lby1zYDNnrB4MPYh/cyH1gBaz6eeT2VAGVAGlIE/mgF7Ak9+x8pkpi13mzRpopJXBbcKfmVAGVAGlAFl4LBiwJa8dm2Pi0Rwn3zyyWRnZ1vzuvb46Y8ex9Xm+8d/R5lPi5+zs+e1dY7t0PhNY8/b721tz7lK/fslb1GQ9KwQSWnHMXD4HK6/4EzuvqAJVMyCioUsmT+feVO+h7XLaXbeqeR6kqnjyaTJNc/yQ/XasZLKWJaWtf7buh3KN0MFULGJds3+SqnDgZFayKARm8g1T2bWgCncf+E5LOjZmTMLStn0wxIm9OrJI//5Dw8/04q7H38dMz2PgvxCSkpKCYUkZXN8Een7S8krklDWwpGGlY5lN9SLaVFZKNJQ1uT1mH5SfVkk+9MYMm4wp196ESdc3owJC7YR8XnJS3BQP8XkkRZPAYugco61kHBFFWyvhO3brUzNVFVVsXXrKppedh5nXH4DsuTwemCTFYUrGau389jD9/L6E7cy8N0byTvCwX+eeoZnvhzCrc9+yipgY1W07TZTyUZgbXUUrzRfVWWZPIOlcydQnO4izZmI4fGQ4g3gzAoyZ/kGtlp5pMvp0O5NvO76NH/uTdZsg7+UFlCY7KDrlx8xdOhwElIK8AUa8fNSSTW9xVoa+dM2bchKdVDgdpBliV6J/pW1iqPRwvviwhcPuZwTOSa1vL5K3sNH2u6poP81ySsM7Qs+D/TXsPuPfS2LHxzovkre2mbAZu9w6XMH+jVBP9+h8UNAz6OeR2VAGVAGDh4GZF7BLpJBS+YbcnJyrEgVEbuHQ5SOfkeNRlMGlAFlQBlQBpSB3TFgi97Y50lEb3p6+mER0bsryWvPqdlzdyp5D57fALX5e82e75faZuR3SN7iaCSvSN7MCMmBExk8fD43XnAm91xwJH3ev480icBNSmTsoKGclpZEkcNBujOVOr4wDf/vBT4etwmHM5MGiU6SzRBz563h2JwcMus4SElI4eUnm9Pmrj/T2CFr0RYzZORmCnwnM6v/NJo1bcrCnt9xuj9Ms/OuYXrvPqTWq0+z51pz4+Nv4QrkkZcnkrchoVBJXBHh+7+SV6JB5QeXFLuBpI6XvG4znQRvAZf983oWzRuJ6auLwxNh5tIqbrvgVIrrO2iQ7OXBJ5/l6bsvJ6++A1ddB6lJibhSXSQnOUlJdFPvCAdJ9RzUTXDgSArgcBbS/NmXueeRh3EkNcBR7wjq169L7y9a89E9p5PlcHDH0y9y36dDcSQ0wpFSiqO+n2Snh2UrFtG67ce822EA341agOOIRBwSEV3PgdnAQVayg/TURNweH97MAuYsXcV5l12Bo05d3CkNmDa2D489fA8OZzYfdujNpx+8wS1/P4Vls4aSlxmggf8Yvl8Ol136d5LqOnCmepgwaiTP33s1QaeDHG8CaYbXivS10lnf4hIGAAAgAElEQVTvo7ScsdDa4NrHpLPIIu0iejWSV2VvvARWybszrbp9PbMHBVqr3N1fDNjsyXW7Ngc4+to60FUGlAFlQBlQBpSBA5kB+x+Ry0SlrLUr6QhV8uqEd+xEtm4rD8qAMqAMKAPKwC8ZEMkrQXoyt3Qgj/P2xWdTyau/ZX4rR7Ybs12Z9I+9lLySqtmWvCEyMktIDfyJoUPnccv5f+X+88MMe+8GMh0OGiSkMHTgRP7qd1uy1kwxcHgbEr7mJT4cV1YteT0kmaXMmbeBY3NyrbTEyYlJvNSiGR/ffRINJZI3pSGLllaHuW6C5hdfxMKevWhaeBzM38yyWSu5977nuL9la2579EVSvGlkZ+cSCUsk72+TvBLJK7JQxKFsS0oAaVyJ3rVT/8q228zmCFcJn3caSJePX8HrcOCol8CXnTrxXeuHyD3CQb0kN5917M5L917N0LZPACuhcj1sr45Zlghaqqgon0uoxIMj0UV9VxpdvvyAYEEq0xbPwixtjMNZwNBhk/j3346x2vOeF1vT/POxPNn5B4kRZoNEB29ezwl5HpLkc9TN5uiL76qOjC6HquWsnzeKRhkuzORkGngzueDKf1G1fQOwGSrl80h48SbaffIh9ZPSSfIX88PaVZSxitsvaYLH4eCkfz7AzOgzd/xfVv39rs0LFKY4yPUkku41CHh9+Az/PrvwxkIbC659XM6XSF77nNmiT9M1H97SV/qvSl6VvPtLZOr71CzNVfLqIPW3DlL1ecqKMqAMKAPKwKHOgIyLRPLKWnOSjlAl7y8ncnViW9tDGVAGlAFlQBlQBmIZkPGS/OM4yYZyqI8TVfLqb6HfyrjtxWJd2V5K3hDhaslbXCiRvFHJO2TwXG694ExL8g5993ryHA5SklMZNmAcZ/u8NHI4+MufL+CT/nNofO2LSBJjSTEsvlMSC1ve00rXvAG2V8D2DbzR/DLSHQ4SU4+h36hKsjNOZsawadx9wYUsHdCfimlzufmcK3HVz2DwyNl06jOK2+5/gmS3j8yMbEvw/q/o3XUkr4ghieIVuWtHh8oi369kmr+QvE4zl3rpJzFXpHPFBti2jO0VZVSxBTZ/T+OCFBxJafQf9T03XnQGAz5+ipvPbohf1uZNcJCS6iShfiqulEQGD2pHbmECjgQX5zS9gmfvvQ63w8HDzz7O9Q8/ReGfLmbC9KWEPSmWTP53y/dp+vinOFyn0nX8xuo2Ww9bV/DYf+7i5KseYl61C4etLJ89gCLTQUqD+tSt56JBsod/XHkFCxdMJ82XyBEOB3WPcNCgjoOkhLo46hrUceYwfcUKNlSu4sbzwjgdDo65sjl9foJUl2ntp9Q/gqQjHGTUc5Cb4CDbm0ya1yDN6yfgDeA3943o3RW08uPYPi7nzE7ZLNsqeQ9vuWuff5W80Ruj3U9s0aYysmYZqW1TO21jsycs/tbBij5PB7bKgDKgDCgDyoAycCgyIIK3pKTEiuK1Ja+KXp3Mjp3M1m3lQRlQBpQBZUAZ2MlA48aNrX8cJ/O98RL0UBsrxn8/ez5NanvOUtM1628k4d6e75fa5mQvJW+YcChMJFxCsDhEenYJSf4TGDhkjpWu+d4Lj6Jf62ZWumZPooPx/ftynt9NqaMuF1zZjCfaj+LYqx+jw/B5NHAFSHJlUC/teOYuquRkM82K+M12O0lM9XDsn8/iqz4T8R/zT9r1XY4joQljhs3n300vY3H/Hvz7rL9EJbCjHo66qTR/6gVua/4IKS6T9PRsgsHILqJ5I0Qi0SI/suSCIT+u5IIhUlckr2yLKJII0bfyM3ZIXhG+9d2ZnHz1IyypgCYihY9wkFjvCBK9Huas+IlbH2uBw9mIST9CKDdEtw/e4LZzjyWrroPkBAdJLg/JyQbu1GSGD/ucvJALhzefHsNm0yQjjb6ftKZyK/QdOol2X3Xmozaf4Kpfh/r1Enij4wD+8ejHOFJO4tuhyyjJKsb8/xL8xRYP8u8HHqfhlU/wUPtJOOpn4vGmMnX8V3hNBwUnnc/ijXDdhedQ6HIwb8VqbnzoKRz1U2hQ18Fnn7xMMJiOo36Aj77oR/uPPuTVR+9g5Q9DyPCn4vA2YdJSePC+O3HXceBOdvDph634U3EGmQ0cpBsuTMO0InkDXj9+U/6Fze8XvbuCVi5sArA8JudJIjZtKS/nTIpG8h7eslcivIUL6ctyA3S5XFY53G6Gdv+xL/j2oEDr2hGa2q7/2642e8LioTYA1++jg2tlQBlQBpQBZUAZ+K0M2GMhSTsoa87pBO7OCVxtC20LZUAZUAaUAWVAGdgVAzJmkiUuxN3ES9DfOgY7WJ4X//3s+TSp7fnGw21e+2A5d3/U57Tn/aX+HZI3Kk+Li4OkZYdIyjyR3kO/55oLzqT1YzdBxY+wdQnjh/dh/IBe/DXDZ6UbfvCZ93jh80E4UvKp480n1e0n2ZVOUvYJzJpXxl8ycgg7HAQSG1Av2UOzZ1rzXLv+3Pz85zzTbgiO1EaMGPYDd152OYsG9YRtq6vjgKvYDqwDbn/oCVK9ATIzcizJu6t0zbuTvBLRKwJRZFGs5BV5mOLLptXXI+g+ci6eug3Iqn8E7qQk6qQ4ea9zN74cPpXjr2zOV0Pm46jjpWu7trB1KZT/CBVlVvRtlYQtV1ZSvm0xWUGTgpPOYdkmiQyGF+5phunMYemyTSyYPZ0MfzJ169XBkeDkna+6cd2DL+FwHcXwsT8jwcOUl1FZVcW1Dz5L6RWP8QOwFti2fRuLFg3Cne4g44RzmLMG/nXuqVbkbeO//JU5m6y3o6piC48/dDMeT10+/PI7ps9ZRYHbRU59B5NH9mLo8CE46mTS6ISmbF67BLYvtVJPt3i0OWmJdchKTcTndWPIJL4h6Zp9+KxI3tqRvLEXOZHyInhF6MWmbFbJe3hKXvsfZsRKXuFFJa/X+ocR9qBA6/+VkdomtdMm9vXantj8owY++r46Ca8MKAPKgDKgDCgDBwIDKnl1EntXk9h6TLlQBpQBZUAZUAb+lwGRvJL9RCTvgTCOq83PoJJXf6vsKV/7SPKWEA5FKC4uxJ9TyAffjLQEK9s38s0nr5CdUgcjoZ4VRdf+s8+gYpslNbdvq+DvV/0fiW4fyR4/aWmZ+NNySDQLaN+hJ2ytgooK67lVVZVs2ryZi6+6ho5DxnL9g0+zsVI8aTnHZQfIrevA36AOPpcTw2tS32nwn5ZvcMtjz+EOSERu7h5JXhG7diSvbNuiN1YYvl2YRUZOHsm+LOs7uBs0IJCciCslmYTkFOolO3GkeHj1y66c/I9rcdRz8sWnn3LDeSeS28CBJ7EuLqcXV7JhpbLuM7QH6cUSQZtM3QYeXPUTSK2XQKIziwGDRnPdxWfjb+BgxPgJiANet2kFwXARRyRn0bffZI7KLsRfpx6PPf0KNzz8Midc+R+eadMLR1IWTpeHUWO+xUh34EioR70UJ56kuniT6tIgxUndVC8JKU6SU5JwptbD5UzE5faRkuzBmZBAcj0HyYl1SExJom6qn4RUH+6U+pipR+B1JeJ1p+J3u/CkJGN6vZbk9ZgmUkzfvumYsbDasiC2TktLs2S8CF47mlfkfOw5k205puXQbgMRvLHCX863rNmgkbw7UzeoyKwdkantWnO72tdrlbz75p64pwM+fb62uzKgDCgDyoAycGAxIJJXJnE1TfP/TuTq5La2iTKgDCgDyoAyoAzEMiCSV4qMmw71Ma1K3gNrzH4w8BbrzfY6kjcSKiESihAMFhHIySMhs4T6/gLczgb4khyku5ykGQE8Zhouw29FdnpTk0nzJOP3JGEYbjIyMynILyQvrwh/Zj5GWjZel0HAY5CdkUF2RsB6rtOZQB2XE4fTRb2kBFyJ9chMcpCVXJc0r5fMrFyyc/IwMnNJyCykflo+ZoYIrXyCwTChkEQdl1i1bFv7u0jXbEteW/RKqlc5FisMJao3vyCfrOwsMjICpJleDGcqrtRUK12xrEEs4tThlOLmiBQPyUlJBBIcZCQ6MJITcKW4cCV7SE1xUd+ZgCOxDnXqJ5Cc7LKem5CYQp0kH/UTXATqO0hPclAv1YUjJQVniqSGdlCnfjJJSSa++gn4GiThaODF4crBUd+HIzWD+kk+EhOTSUxxUKeBgwaJDpJT6pGSmkhKavKO1LUpTicpzlScLidulxNPqqwVnEpycjKJyUk0SEqgXmICCU4X9ZOS8LpTLMHrcaVYzze8hiXYDUvyGrh9Bh6/ibEfJK+IFelwcp7syE2RvfHnzJa8IgFV9B4aolfOZfz5lH2J6A6FQtZ5ljWvhJFUYVrTNWskr6dmEamStvbaRiWvDlIPhoGxfkblVBlQBpQBZWB/MaCSVyevYyevdVt5UAaUAWVAGVAGambAlrzSRvtrrPZHvY9KXv09sqfs7RPJGw7KurwSyVtMYShEIKcQf2YeAb9JwHCRk5lJdmY2GZlZpGdmkZGeQWZ6Ohlpfqvk5uaQX1BAMBgiHCkhN7/QErUZ6ZlkpKWTHgiQkRYgPeC3ovG8/gAefwCv6cNvmmT5TXLS/ORZaZXzyMnLIyMnF19WLv6sXDKzo6mW5fVDIRG9uyohZE3eRo0aWf8ixJa8ttyV/V0JQ0sw5edRUJBPYX60SEeUhvV6vFYEbUKKm1SPD7fbJDU5GY8rCY8rEY8rFY/TgzvViyvVjdOZQoorhSS3lyS3QbLLRYrTTVKqSUqKF7dE2SYnkJjqIsGZSorzCFJE9KYkkZySiicpAXdiA5JSUmmQ4qZBigd57+RkJynyHGd9kpx1SXHVJ9WdRKo7FafHbUU3ithweqPF7fXglbVuq4sV/eh2W89N9bhJ9Ro4vV7cXqe11q/bnYrb7cI0jerFnqX2YvoMDJ9E8u6b9RdjYbVlQWxttbnXuyPqWiSvMBmfYtuWgrG1Ct+DT/ja588+d9I/bckvUbzBYNA6/yJ4RezKP1ZwOp0qeb2arllFbu2J3F9rW/t6LdfqPR2s6PN1gKsMKAPKgDKgDCgDhxoDKnlrnsjVSW5tG2VAGVAGlAFlQBmoiYFDbUwY/31U8urvnngm9mR/ryN5QyJPgyFL0hYVF+9IlWuLUZEwtpDZVS2RlyLkRMpI5J3UImms50pq3Zxc8nLzyMvNtyJyJSr3lyUaybcjPWtREQWFheTlR4/L68S+vrzHrspvkbyv5wQg12MViQq1v498B7vI55DvLI3vdnswjQB+M52A14/X5cFjGnh8XkuE+gwD0+vD5/Xh98q2gdsM4PQFcBkGHsPA6/Xh8Zi4qkWry+2xom2d7kSc7gRcHpGsTgx3ilU8bmdU3LrdeN0uvG4ncszldeP0uvEYLrxm9eeoTqcsKZW9/mjx+f3/s4C5rLErUt1jynP8eP0ibz2YpshdqeX7iNw18FlSV2p7e99M6MdKXlvo2tIgthYpLW0v50DOhaTVjj1ncp7s82bXtijU+uCVvXb/kzW2pS/LubT/wYXIXSkioDSSVyXvr4lIfaz2BLB9nVbJq4PVPRmc6nOVF2VAGVAGlIFDlQGVvDp5XdPktR5XNpQBZUAZUAaUgV0zIBG9h+rY0P5eKnn194/Nwt7Uv0vySpSsyFlb1O5KosoxETA1Pbar4+FQNEpYIoWlRMKlcaXEek15XVvuhCMRpMjr2Z/Jrnf1Hvax3yN5bVkotXwOiSAVyZSZlYXbMHFZAlcij/34AiaG34Ppc+H3eaxjfiNAwPDhl+JPx+dPqxatBn5LlhqYPi+GT2qzWqi68Jlu/FZEs99KFx0wvfh8fkyfH7/PJGAaVhEgDF86hj/Tem0RuaY/gBmQ4rdSKovolYuIPxCwivyNvHZAjsnnNjMw5TWsvzFI87tJ97vxmZIqOVbkynZs2Tcd87dKXlvS2M+PT7Etwt8WvSp1Dz6pG3vO7H4n51POq0h9qWV9ZpG59hq8tuC19+3HhJXDRTjZ/cEWbXY/0br2pKa27S/b1mbvcOlzezMQ07/ZN+MFbUdtR2VAGVAGlIGDgQGVvLuevNVJbW2XQ52B2HW4Y7cP9e+9r79fbNvFbu/r99HX02uSMnBgMaCSNzrXJnPch9O89sEwtj9QPuNeSd54kWoLU7veldS1hWx8bf9NbG09J1wSJ3ZjRa+sryvpl6PRubGvaR/7rfW+krwiniT9tBVZHAqSU5iPPyPDisg1vD4M04vXdOPxuTFMN6bXTcDw4vdEo3q9RgZeEaoifE0RtRIl68Era/76vaT5nKSbTgLVgtdnZuE3M8k0vGR4XZaYNXwBJPo2mipZImr9eH1ZmGYW6aZBmuHGZ0Sjc71WlK5pPd9reK3a+lvDtD6D2/DjMtJxGtm4jQxMrwe/N5U0Q4qIann9nRMJliiujgaO/5cnsc/b021bUtm1LQzsOl6o2MdfTItGXks0r0T1ioCXc2OLXlsU2nWsRNTtA08Cy3mKPS+x51POqay7K6mZbZErNz37xieyN3ZfGDlchFN8v4nvL7r/SyGp7bHv28O+Jh8ufW5P73H6/J3jCG0LbQtlQBlQBpSBw4EBlbwH1qSxTuLr+dhfDMQKydjt/fX+Nb3P/vws9tqadl3TZ/q147GfN3b71/5GH9N+rgwc/Awcc8wxv/AQh+KYMd6n2PNpUsfPV+ocm/5uiu8Dey15YyXq7iJ5Y59rb8eKWdm2j0drEbhyTGTuroo8tlPy/vJv9yxyeG8kry2bbEH4CwGVn0eOlMJc8osLyckrID1dRKtIXq+VktlpGviNBAKeevitNW4DJJuFJPuK8JiZ+KzoXgPTMHEaftxeF5luBzkeB+lGCoaRhssowvTmk+tyketMwOdxWdHDTp8fl89npYY2JHW0kYnHaVDgTaDAU5d0r9uSuPLaInU9Inv9PiSiV/YNrxeX4aeBkc0RZgEOXxENvJmku1LI9ySSbbjJ8JmWiI4Xu7H78aDt7b4tqew69gK3q2256InQeyHg3pGuWdJtS6SncBIb0WufP/t8Si3pxmP3dfvAEL62nJdaBK8dNS8MiOC10zHbQjdW9goT9r5sy98cLjfD+H4TPyjQ/X0vNbVNf9mm9nX6cOlze3uv07/TAboyoAwoA8qAMnB4MKCS9+CfaFZZoOdwdwyIxJTniISMLY0aNaJx48a/OLa716rNx21JGvsZa/P9bLlrt8+evlfs55R23NO/1+dr31UGDl4GVPLunGuLnWez5311zu3w+B3xa78X94nkjZesv2V/TyVvbMrmqAD+4yXvrgRgTl4uuZbozSG/KJ+CoiAFhcXk5WZb69s2MHI44bSz6N2jPX63A6/fS5KZzVGnXkr3QVNJcadba/SmeZxW9GySL5t//N81dGrzErmpDgKpDXCm+jAzmrBgwUZOLApTmFIff0pdUlITSPSlkejPxCOpmX1+DH8uHb7sRJd2b5Nv1MF0J1lRvxmSttkr0tkg1W/iMaLr64rkdRoBLrj2Tl79vAdn/PMOVm+FYwvTKUp2kJ6aQKaVyrk6zXNM9G5tSN54eO2Ll31Bq6mOjeSVbflsInDt9L52il9b0KvcPTBk7q76lByT8yX/mETkrohe4UBkmkTvJiYm7pC8tsy1azua166FF5uheLYOxX37u9r9RAXkzkGRtsX+aQubPWHxUOxj+p10IK0MKAPKgDKgDCgDe8KASt6Dd4JZ5YCeu9/KQLzIjZWT9vZvfa3/x953gNlVlV2PYHommZapt05Pz0wmyaSSBEhAmtIFAQEpApEQILQUimASIAkd5ENBSDItoZdQpCifgnRE9FP0V7E3FFBRYP3POjdr2Dm5d+ZOcu+UO+88z37e3c/e715nnzPvuu8+6azHsbB/jUky1dd0SV03vrPX0bjZPhX97ew4rJ3tCYaB7sOAkbyf2PBcO5vsvmZzs/9HjOQdPRr8NR1fEkj0lZWVIRAIeHGmGegJymN/Gfit10RElJsfiQQRiZCcqox9V7i6CoFINXbLq8X4mfvi8Uc3YuSILGTl5CMrJ4LaGQfi7kefx6BhucgZNgilw7MwYkgWsrKLsfDI47Dpf1Zh34YyfPi3P+CjD4APAHz4IYB/M/IB8PFfsOy8U7FbXgmy8iIYllOInBEFGDqsELmjyvDWr/4PBx66AENGDkRObjYKhg/HyGFD8ansoRhUmI/hOSORw3PdR47AsJx8LDz6FKy+4x5kDc7HIUccjh8/1YqKgVkoGb4b8nN4XHN+7Fu+fYTk1XG9hYWFHknoHvfr9+gV8euup8W7jwTWepDMVSDBS6K3uLjYI3fpvUuvXZG5lApca+WL3JUUydsVQ0xfrquHvV4AjNj85KXIdNE9uhD27IXTXjj78l5qYzf8GgYMA4YBw0CqMGAkb/cZhM34brruKQxMnjzZ89ilrVEkpAhUl6D0j491Vd9fls40x+QS06m8FudDcob9T506NWXz6yldpVI31pftUYaB5DHQH0neeDZd2dhk31Yds7nZ/yq9nOTlscyxUOt9o5ff6eXxzb3juGaX+AuHQnBDNBxCMFCGYDCE8vIKVFVWoDQyBguPW4Et33kTH/7nbTz33Q04/7Ll+AuAPwL4M4D3AeDjf2PzTStQMSoLT7z8Y/yVefgd/v6jrSgvzMHAgXkYPLIGP3vrn2iITMS+48fh7RcfRrggC7c3b8a7iJHAH5EE/s+/gA/fw3/xb7z38T/xr488Vhj473/x4x/+EL/+21/xTwD/5SU++hj4+EOPN+ZYOCb25ZX+97d449ubUJozCEWj6JHVt0hebn4i//gPOsl8Eoj07BWBqPX0k7zm5ZtegtevX+pfa8P1YSgtLfW8AEXkulLrqjylKRlcMk8PwVQZaXp7P3rY6yXA1YXFu4fk7O96FvbshdNeOHv7fmnjM4waBgwDhgHDQHdgwEje5A26Zvw2XfVVDMyZMwckekXyikCdPn065s2bh4aGBs/RxD+/niIuSfLy2o2NjZg5c2ZKj0HWnEjwHnbYYTjyyCO9azHfnX9H5LfqsQ51t9dee4G6ZL6/H9U1afuHYSCzMECSN9PtSjyF1H0XjWfTlY3NLzNdN65eLB7/f7YeI3k7PtKZRzEnE6p93/LtejrRN3npzSuP3s48eUnuhoJBRElOhUKIBIKIhEIoj0QRDIZRFggiGAigKDoeX15zDzY9+3M8vvUOXLvyMFxx7ucxdOhumHr4l3HHc79B1oAiHHzIQXjkliWopifv4CH4zMGH4dGvX4Bxg7Pwzl9/4xGv73nkqzx5yeb+Ab9980kE87KRPSwPWcOKsfzii/HAzRegfPcsjByQhcGDB2Ho0OEYOSIHuSNyMHxYNgZl52BoTgFGjMxDXm4eskcMx+7D8xBuPBjfeuxHyBo4AgN3z0L2wCzkDtkNeSNGIC+354/d1EYn6d/c/Mc1xyNauHmS2NVRwCQWSTCSVBThK29uv1S5yV0jgHWPSb9cAx3LTEn90vtaBG48KVJXZUr7SV5iRHjJpAeCjkl356R5uvdFvHsgUZ7bjvFE9SzfiOJ4GOC9JwwJiy4+LR7/hcz0YnoxDBgGDAOGAcNA5mPASN7MMjobidA/15NkYyJS8rOf/SzOOeccHH744e0kJIlIEhSHHHIIzjrrLMyYMaOdnCQRzDJiSYSoiEvmz54926svSXJTZCwJWcYZWL7HHnt45Cf7J8msfjrDKefCvjg2Bn99d1xun2x36KGHeuQt50sSl2nlkdxWfdY9+eSTsWTJkh361/V0HaUp1V7xhQsXen0cd9xxCftx21u8f96jtu6Zt+79geT1/x8gexplPNus7G6Squ/vp6O0bMqSHdW1sl3/P0V6lkylTnspydt1srZj0jhxf6kgeUlEkaQiQUWyNxwMIBoqRXk4gFAojEi0HGUlZcguqsSazS/j8ju3YusDX0fZwCxUjMhC9pAszPj86bjwrqeRNbAEhxx+MLbefCYqds9C1qDBOODQw/HIjWcjlJWFLIbd8pGVXYufvvUvjCsZg30mjMcvX7wf1QVZyMvKwshBw5GVHcCySy7F2q/sg2hWFvJ2y8LgAUMwdHAusofkYNTQgcgbOhgDhxVg92HFGDgkH0OGjMCwwQPx6YHDUTnlILRufR3DBgxDzoBPIXvIAIzIHoaRI3OQ207y9hzZq41LUhuaZDIkL8kJtucN5ZKLJH1F+Ip89Esjd3eN3NWRzLp3mOYR2vxWN+9lEu1FRUUeucs1FYEbT4rUVZnIXUqXgGI/wksqN9Ge7iveg0Hz1P1A6eqis7jbrqttO+vbyjOfGDaSd9df/Hp6X7Hr2xoaBgwDhgHDgGEgPRgwkjfzDM9GJvS/NSVhyaC1d4nIE088EYsWLcKBBx7oeZzS65Rh/vz5OProo3H22Wdj//33x9577+2FBQsWQIEkhkt0ktAU8XrmmWdi8eLFHsHJPkiW+oPqst5+++3XPj6NM5HkXHaG5KV37mmnneaR2hwLr89rUzKt45mlr0Qkr+bsksIaq6tbxo3k7X/3m7Bgsn+vfX8kefUuLhuv357qt92qHqXadiZlU5bsrL6V79r/B9KzZCr1aSRvgm/yJuvJGwyHEAiHUBIMoLCsFEWBMpQEihAszkZZ4TCEgmUoC/Ao5wjySirQ8uxbOPHCy/HUo9/ASBKy2VnIGjYYMw/5Er52x8PI+nQ+PnfwQbjvxvMwioTugOHY58hjgQ9/gTeeuB23Nt+N3wB4R568/6E37z/x3s8eQ2VuFkbunoVhg3OQNbgETZvvBz74f8C//m+byy/wn494hDNw6j4zUT44C+csW+MdE/0e8/lHp+B//gdHHXYKXnr2R6jNHoHQp7IQGDkUBfyWbz6J0VwUFOR5Rzbz2OZUAjLZvtyNi3H/xtYRyevW5QYpcpCkIgle//d6Rei6RK/yTO4c2asjmUmmk9CV3pnmvafv7XJt/CSu1kvSLWecwX3wab1dzCSLs95eT3PiOBV3pebu6iOZuDVEMZIAACAASURBVNpJJtPG6mQ+eZvsGvMeJHaExd5+H9n4du0l1fRn+jMMGAYMA4YBw0DyGDCSt38bqY2kyIz1F2npricJiIMOOsgjPEnmipQlISvyVeTneeed115OUlTBJXl5DRLDJEtPOukkzzuW3rI87phSfSpP+azL/vbdd9+0kbwcG+dOefrpp3sevPQm5jHV9DSmRy/HTW9i6YpSJC/n6Q8ieCldvbokL/NJiLPvY489drt6bhuLZ8Z9Zuto6+higHsGbUz98Z1TtrXObHKy4aq+ZEc6E9ko2VFdK0v+fb8jXXWka62ZZEf9+MuM5N0Jklff3hXBR6K3sKQY5dVV+O0ff4+PPv4AH/37zzjh6M+htLQIgWDYI3kLSqLIyqvA2Olz8PRDN2JufTbeef8P+Du/x/uxvn/LT+C+C3z8B/zwe4/g4ed/5B3PfO8tF6JktyxkDcxB1m7lyBrRgJ+89TEmlE3AgjE1+M0Lm1Ezil68WRg4pACfLhyNrc++iuMPWYACevIOH4hhIwoxJH8MfvXWX7EwXIDqT2VhyIgyZOWNw8jSRnz36Z+gNq8EJbsNRMHQEvzg8e9h+qjBqN49C4Gc4RiVX4Ci/FwU5edgVAGJXm6uPbPBCuyJZEckLzdFbXyMixgkscj+iouLPdKR5KPf41REb/vaB4PtRzsrz2THxK906pK7PJqZuuW6iKRl3F0fkbqSWje/dB967INrKunfAPt62o9/ztMfXH0kG09FH8ley+plJjmse44Y7ev3mY0/NS+ypkfTo2HAMGAYMAwYBgpgJK8ZrV2jtcX7Hh5c0lFkpwjKM844w/PU5X3O45MZ5s6d60kSoCRk6eVLApb5zOPRyqynb+GyT16Dkt/vlecvsaLrsZz9MGg8lCRB6MHLNsmSvLqWPHlJoPpxyTpuGDt2rJfm9TgGHlHNb+UefPDB3nwOOOAAj4hlmzFjxrQTvSJ5v/SlL8ENHKs7b82T42AfGg/j8m6OR/KqrqTamex795mtma2ZHwP9meTl+7Ns253ZUGXPde3FHb1/i3CU7Kiule36/3Jcl4507a4b413RuZG8O0Hy8nu7CiR8GQ8HggiXBRAsKUawqBChogKESgo9r0SRvIXFEQzOq0T91Ol49v61CAzNwvCRA/CpkYX4n7YH8N6/PkBD2QhEsrIQHMrjlQd4xy7vd8ih2HrTIpTvloXFF1+Gld/6LrJy98SbPwPGFY1FWVaWR+QWDMhC9qAB+NSwQsw65mz87F/AuGgIxbtlIXfYAAzIHoWs3Dr85K3/Yo+yEMYPzEL+iFzslh3CoNyp+O4zb6N2ZDGKsz6NrKwCbG65F9cs3g/VA7K8o5qH5QZRlJ2DUM4IFOXLk3fXAd4VwCaq678JVhfnAqEcLzCuTc4vtTmKWFSa9crKyjyyV96mJG9JRIrEFeHrSpWZ3J7opY6oT+pFx2GT5JXXtPQuqXVSWsSuJNdLcdYR0av6ak/pYiMRfvpiPuel+VFq7slI6UsymTZWJzPJ2HSta1dfRvriPWhj7h3Pf1sHWwfDgGHAMGAY6EsYMJLXDNd+w7Wl+yYmRERSkuQ95phjPHKVRKZIX5ISDFpjfpOXBCy/ncs8kpH0dlVw67NfEsEieeXhyjYM8uRVH6zPOI+ClievxqjrS7JfksEkdtmG+SSaSfD6SV5+X5fkNMemuuqHkh7LnBevxbYkpjkGjs+tx3LqhvPRdSTp+aux+q/BfAUSya4nL+tqXP527rUt3jfvMVs3WzcXA7zX+7OdSTZg14ZHm66b9sdlM+5L78mZNlaumxu4JpwjiV43n/Fk5+62UxvmGcm7iyRvO9nrEbwlCBQWonTUKJSMKkRJUTFKSj85rrm0tBzZ+RWYNq0RP9h6HfI+lYXhI3bDfod+Hk9+5zkcdtBn8c6PX8SYkbuhaGAWRgzPQdaIMPY7+FA8/vUl3jd5v3H7NzH7s2cgK2c2fvdHev0C+OB94J1fY2JVAIMGjkTW8CDuf+ktXHl7K4Z9eghGDRyEEUMHY7dhuaiecRheeOPvqBiSi+juu2PooKHYLbsUg3Lr8eyzb6N8RKH3Xd+srGE4+HOH4LUn78CoT2dh8vSZ+N+Xf4aqQASBkSR5kwefAJdO6QKc8a6SvP6NkGmSiO4RzvxWLElJeaKSsHQJXsaN3N2e3PXrgwQv9ajjmUtLSz2ClpucG7SezHPXRqSkK91y9aH2fplODHZn35yX5urXkasPixsx2x0YcF8shUtitDvvCbuWGfgNA4YBw4BhwDBgGOgLGDCS14zWrtHa4n0TDyQUSbqSdCABScKUpCbJ1eOPP94jN0nkyttWkuUiOXWcM8voAczv14rMZP+My5OXXq8kkY877jjvmGIRyuxL+ZKsK5I3Eb5I3HK8JGdFjrokr8bB/Ypj4xhJsLI/1lcbpneG5KXe3MC5a6wkvHUNSY2HZS7Jy7QIdXdM6kvtlTbZN+83WzdbN2LASN4YWSibW2e2PtWj9NvGle4L7819fYzStaTWg/PiGjJdWFjo8Ul0hiNnQslTZl2PX7XvSBrJuxMkr45rdiUJPn5LtKS0BEUlxRhVUorC0jKUBkIIhiIIhSIIBCswclQ5pjVOwzMPX4+8gVlYvmIR3v3HO6iPVmPkp4bighWr8ff3/4sJwRIUDR2KrJwo9j38OGy5+WKc8Znx+OkzT+DPP/8jvnD0WfjFT/+KupIgirKykMujl+n5OyiKJ7//K/z4Jz9GYcEI7P6pbIwcEcSwYTkYMJTf9/0iXvvZbxDIGYURuw1C1rBCZI0MYUh+Nd7+7XsAv8370Qd4/okHkDvk0/jO91/GE997HUuWXYZbbr8TQ4cNQ35uTo8d05zo5vaDPFmS1930/BukiAuSvfRCdb8jS+9eBpfENJI3McFLXZHY5UZFPVKfXDPqVpuauxYsU9pdl3jkLutp/YkP/RrGxQrL3XRfjru64dxd/XQWl06lM6U7a2flRhYngwHhSfeb+0LSl+85G7uRBoYBw4BhwDBgGDAMpAoDRvKasdoIi76PAZKHPLKYgWQuCVMSofRMPeGEEzzCcq+99vLySZKSCGU5JYlZxknEMs02bC+iU2SlS/Kec8457e3ZjoFtFNQXJetSdnRcM8fAQI9eEifEpEvyMi1ilUQwx0iCmfl+4tRP8rLPzjx51YfkuHHj2kle6k3j41wUmMdxnH/++Z6UTlXXlZw/j3OmTuUBbfdd37/vbA379xoaybujRyhtcF2x1clmR+na0VP1jmv9bP//knQs6dcPyV1yJORL+D7BPY7PQ37mgGQvP23JOuI52I/Wzl1LxY3k3QmS1yX2GA9HwuB3eRnKQkGUhkIoDoVREo4gGClHKEJiqxxlwXLkFoUxbcZ0PPP4nbi39Wo89dS9GJWbjeJPD0Lx0AJkDQ9g/Ox98OE7f8F9d30LT7/wE7wPoOm29fjdi49j3MghqByRgz/86o8xQvaDfwMf/Rv48J/4+Vu/xOaHXsGjT72JnEFZyB2UhZE5ZXjmez/Ghx/T6fdj/OOjD7H/oYdi0G4DMCq/BI//4Ef4y8fAX977EJHyGuz+6QHIyx6MkmFZyBn8KQwtHI03fg+8+xFw0KEHY+DQIRiZl4t8ngdfsD14/WDtybSf5NUN5Ze6EfzSv0mK8KXnKYlK3oAkLuXV63r0Ch/9hfSlDjRnVyqfUjqjTrhBERuuzrUubh7jWgeX3NVaqK7aUvYk5tJ1bXd+iksvycpEulJ/Kk+2P6tnpK8fA8SQ8ETJ+8FI3t77jEzXfmX92pobBgwDhgHDgGGgYwwYydu/jdRGUmTW+tOTlEcQk2ylN6+f5CXBO3/+fI8w5dq7xzXToMv2X/jCF7x2jIvgZV2X5D3wwAM94y9JDtUjkcnANiQzKVnOuvFIXrdvEqIkSemdK8OySF6WqS+Og32zP86N+xfL3L5E8rIu64jkZVxEsaSOa/b3wbYKJM2PPvrouIG6InnLvk899VTPi/nII4/coS7z+F1glzxW/yY/0bXpwnTRlzDQ30le//u17LiUfvtcvLRb37Xf+fu1dMfv8V3Vj2snZZzObtQ/OaVEzyg+M/lsJtnLOiR7yUe5fbnrqfU2kjcFJK+IXsoY2RtGIBxBWTjiSZG8gWAE+cUB5JLkyqdH7CDk5g5Hbs5IjBqZg4KReRieW4jhuaMwKjfHC9m5o5CdW4Dc7CEYlT0Io4YNQf6w4Rj46UEY+OmBGD5wAEYOHojhQwZh6JBhGDgkD4OG5GLo4AEYNmQABg/JxqBhORgybDiGDB+OwdkxOSI7G9nDR2Lw8BwMys7FkOEjMWx4NoYOHYbhQwcjL3sQRgwbhN0HD8eAYXkYMGQIBg0ZhGHDh2Jk7kjkF+T3aqJ3TUle+zd5GXdvhERx/w2itG4Wl2jU93pJXso7VUSvS3T2tzh1QI92kd883pqbEfXFowa4GUqvHUmukVvuroHiLHfXkn0z7UptvspXuq9Id37x9CFddCTVzu1L81ee6lCyLzetvI6uYWX9i/R18SEMSQpblEbypvbl0NWtxU23hgHDgGHAMGAY6JsYMJLXjOp9yahuY02MVxphSbjOmDEDPP6YxCXJxxNPPNEjLEnukhzlkcvUI+uyHuvwW7gibOkhyzwRqPQ8FSlKwpNlJJC1FmzHa7FvBpcwZZwevMx32zCf7Sn33ntvr08SphoXr8cx8VoMupba8Zu8JHNJnup4ZNVh/sEHH+y1odctx0yimcQ365AkZqCeTjvtNM9Ll3NlXmNjo6cXzkn9+aXGwHzGFy5c6PVNvXHc/vqWToxZ043ppi9jwEje2HuvbG+Sss8la5dVfUr1IWn/W3T9fwvpLhlJ/ZIvGT16tPcspSSJ6waSuwrK53OXdelwSMc5XkvrqHUnZ2Ukb4pI3u3JPHr2xghekr08rpkhEAxjVEkZCopLUDBqVLvXoQzhrhQ4/IumxZPkImaTsM3O9n4NwF8EMAzLzvbC0OHD4Q8sG76tzfDhw6EwdOhQr58YmTkCQ4cN9sLw4UOhMGLEcOTm5fR7kpf6J2nJG4wkpr7XK+9e4kFE5/bYSHykcV+uJ69lzpk6ILnrkt/CcSLpx7s/7W+ncle6DyPmd5R2y3pr3J2bO3/d+8lKtvXrQ3NOdA33eowney2rl5lkr37govUVpoQf4YnSfY4p7pZbvOsvjaYz05lhwDBgGDAMGAYyBwNG8pqRvS8b2W3sMfySbBT5SPKW5AMJR3rB8pu4jJPkZZqkKQlPevUyrjwSsSRIlSfdivBUH2xLYpP5NPQysK5IXsZ1fY6FRyW7JC/LNFZKXpN9knzmNZhHGY/k1ZhI0JLA/fKXv9zuSawy9nfYYYd5Y2C/9Agm0cw46/Boas6ZY1q6dKknpQO2Zbn6iic1dpYxTl1QZ0by2l4aDy+Wl7m44F6WyLbZn96TZYdzpWvDld2uM+m28dv4TM/J/9/hroM/Lh3TpkqHuNra2naCl89ypjsKJHZJ+LIun9MkfZkmB8P1Zb/kAGWzNZI3CZL34mBRu1foG6F8rA0VdRKKsTZcjKu3BcbXhopxdagYVwWLcFWw0AtXBwuRKFwVGAWFK8sK2uPKk2TZ6pI8L3ytKAcKVxTlQOFrxZ/Emce06vnlquJcMKwuiYVVxTlg+FrxSE8qX9fsrfL1QG77ml1UnFpPXm2UvIkYp5cqiU0GHUssgpeyL5O3XRk756r5U3ID4wanHyBQX3pwaKNLJP0bI9PuQ9stZ368cn99N90b4+6cFHf1I9x1JtVGffh1485ddZSntKT66uyaVp6Z5G68dSUmhA9KYcdk8i+BpivTlWHAMGAYMAwYBvovBozkzVwDtJEL/WdtSTaKfJTxletP8pJHEjNO0pTf56XH7PHHH++RkiI8eeQwA/OPOeYYL06Clu3UL+P77LOPR4qSYCVpykCCU4SpSFORxSxjHZfk1VgpScCyXGQtr0HDcWckL+dI8pr9ksB1xyiSl/NlOY+A5lHJjLMex0Sd0AtY4YgjjgAD63A8HEei4F6LdYzkTayrRDq0fNNZJmDASN7Yu7Nrj4sXlx1XMp5dL16e6pvNr2v/o8RbAzePzi/ki/gcZZB3LglcErx0GnQDHQnlTMh81SO5y2e1+qHTYVFRkWeTJdFLB04jeZMgeacHytoJQ4RyLN7HdDB31I5EhHvDxYu7m1u8zc/NE3nJ89Hl2UuSU6RvfyB86bnLuXPOnK+rH1eXycbjrYmb15FhjBso66qOP6383iTdufl15OoyUdxto766Mj+/x6X6UL+Jrmv5/Yfc5VoTD8JGInwJS65MVNfyu/byaPoyfRkGDAOGAcOAYaDvY8BIXjO2Z4Kxvb/PgUZW6UAkKdMkeelhSmKSgcQoCU/WJ4krgpVGXpGXqss89qE04/LKPf300z1PYJKz/BYtA/tiYJzHIDOQRGYgeeoe1ywCmf2QMCZRq/FTdkbysg4JZxK6J510kjdGtuFYmcfjmvfaay+P0OVc9X1i1uH1eNwzCRp5FVNyTBwngzsWf1x6Ur6RvLaHCgsm+xcWjOSNvQPLJiep/w2UdqVsupSd2W/dum4fsu3pOkwrbjLmdEZ9UReu3hTnd3VJ0FIyuJ67LrmbKC4imMQv28u7V+8e5GC4JiR6jeRNguSlG/SSYLGRu32M3CUhv6kkN6nNRzefpLu5xdsMVe5ukryhmM8bjDeniE+X/OyKZ2xvqst7wA0cG+dJMltHM7OcG4t0k0i6OhNx5NbVGiQr/RtpX3zIuHN1daG4X2duWnXcPlKlA/Wpa7jXtXhmE7xac0rhQDJV+LJ++r6h2tbQ1tAwYBgwDBgGDANdw4CRvP3LKG0kRGauN42rXFtJxUnyktgVUUtvXXqy8ju4/FYtSVl69pLgJGEhI62LE7UlWar2brni7JcEK+uzrtqRVOZ1SBAzT4TqggULPAKYRK/6kOQ4OjqumfX4DV0Ssrwu48xj/yJ46a3L8XAs9BjWEc7UCT14eQ2WufNmfRLXGoekv57y6SXMY7A5P/e4ZulRUmPj+ESeqw+TmXlP2rpm/roayRt735RdTjLee7jKXLtesjZctw37Yf8ievsjwStdJpLUl/TCOozzxFeSs3yW8bnE55DIWpfMdQnfjuKuZy/bi+hlvwrkaYzkTZLkJYFFj95LQsVYFyrqNPB45o5CMn10pc41kRJcGy3F+nAx1oWLsKY03zvCOXb8Mo9cjh3DLMljllcV5WCNIxlfXZyLNSWxsLo4BwrK217mee3ZrjeGeB688TY/5vlvVndTY9zdDN0yN19noDPP/V6vyF55uZIc7U0EbjJjIf7depoTJTcbHhHAj39Ll66Ouhr3r0W8dKJ1ZL42V9Xxp5XfGyTnlkg/xJHKXJwxz59mP+mYj6t7jUXSHYPFM4Pw1dpSumufLnylA7PWZ9cMzaYv05dhwDBgGDAMGAa6FwNG8ma+IdrIhsxfY5GJlFpvxkmAiuSl5w5JCXq+8nu8JDNJTpIAVRtJEbRMMy7J+myreq5MluRVf2xLoplkrtsP4xx7ZyQv50Lids6cOduNUf2TzD3xxBO9QOJX/XIORx11VDsRTYM0r8f+SBqT6PWPh2XSLY3kugbr0QuZ7UiAs55b5u+nozJ/XUtn/n1ra9y315j3u9mmduQvOnqPd+16rr2P8c7suKrPPnqzXb2j+aeizNVhvLh0yTJyIyRryZPw2cXAZx7fB+KRvC7hm2xcZDCJXnr2sn/ubXxmGsnbBZLXT3S5pNf28TCC4QgCCQLLQqFdI/pIFPoDSUSRblU11QhHoxhVXIScvFzkkkxyQn5BgXdDk5gkELcHPtP8ji0N/bHA9PbB36Z7/znefry7fu14N6qbp83NL91NUSQvJb162Z5HOHNNGOj1qjXbHi+h7QjU3lbGMfP7uhyXewQ158QybmKcr7DEefv15Oqys/iurq0ePpQKu9pnutpTF8SQX19Mu/mKS7Lc1WO6xhevX1433vg4Ngt9TwfxsCdsxVt/y9v1543p0HRoGDAMGAYMA4aB/osBI3n7tpHZSAJbPxlTaVAVESlcuCQvy+ix29jY6JG/Imx5rLHqS5KMdAPz6bFKMpPEqupJsm5XSV4aguVVpH4kOdaOSF53bIyrnfLpqcv5ca70sCUxzTj75Rz4/V23HdvruOZ4nsUsZ32SOgpqT69oEsPyiKaRW+MxafenYSBzMWAkb+zdWfY6Sf//FLKDyzauctX32wAT2XHdempLqf76m3R14MapP+qCnA/JXD5n9R3dZInbZOuJ4BVhTDKZ3Ayvx+etkbzpInlDMaKXhO4OwSN400PykoSLlpejgsRidRUi5eUIRcLbEbwkfXUTC5i6OWM3LG/a/HaCl0TvjgRvZt3Y0kMiGW9zc/Okz3iSuuUPBHjj6ehmEqZ9hfB1SV4dz8zx84HB+bp6YJw6jJeXSLfCXqqkHmSJHmypuk5X+4k3f+nLxQ3zlPbrUfXZV1evn8r6/jXWeE32HZI3HrZcfPU0xlKJV+ur/xrSbe1t7Q0DhgHDgGGgt2HASN7MNUAbudB/1pbGVAV33Ul00pOXBCZJSXrO0oOXXq4kM5cuXeqRniRBjznmGMydO3c7cpdtFNgP+5s3b94OJCbrdIXkJcGrft3xKs65dEbyqg8asHVcM0kXeu1ynMcff7w3TpZxbPRgZjlJXpbzm8GcNyWPdqZkfjxPXh4tzXbUG8tZj7pj/Pzzz/e+88sy1WG5Gw455BBMnz59B71pvib7z71qa505a20kb+yd3m9b9r/nJrKFu+1ce2BHdly3nt9e2N9shq7+3Dj5EXnukuRlIOmaLHHblXoiedWG12VgPq/Zr0leKYEvK3ypIRFHj0V/YL4CFy+5QBK3o5BsP8nXIxnHsUWiUS+EI2FPlldUgIFpHqlLL14XkNwQdkzTk/eTQNJ3+5C5BgNXF53F/RueNkfm07OVadfDlyQ8iV6/Z6/WjjhLDl/J4yKZ/vyEM8ehPEqNmXEeRa15+qVfH/EeAtSp/yGUqel4+HF1wrhfh27a1afbV0/rS2Nxx+eO2427dRR3yy3e/cSw1kFS6ynZ0/iy62fu89XW1tbWMGAYMAwYBvo7BozkzRyDs5EH/WctRejGky4OSDqSnD3wwAO979+KiKQnKz1bSYCSgGQ9EqEMjJO8POGEEzwiltc46KCDPIKTxx+zfxG0rhSpyTx6zy5atMgjUdkX+6UnMPtyx+em2Y7esByjxkkpstZtx7r+tiznvHg9EdskgEnEcP4kckXyar4aM9MMTLM9+3bDwoULvfJzzjlnO11JZ51JkbwctzsPi/efe9bWOvPW2kje1PwPIbuf7IHJ2GRVl1LtKVPxTu/2l6o+UzGueH1o/pTkRkis8rlHXpGnSjDNIE9bkbGpkH6C198nyV4jeX2evH6Cl2kRvD1FwCVD0vnraMwk5eh9qcA0PwAtsOoGcm8qlrlp1VGb/ib9uvCn3c2Om6PS2ihdkjc7O9vbCET2UnJNGLiGPYUxjcEviRuOkZL3grDBOWp+rtTcXenXV3/CU7y5u7pJpEfp1K3bG/Wm+bnj5NjddLy45meyewledy20dn7Z3/Z3m29q/lEwPZoeDQOGAcOAYcAwkBwGjOTNPMOzkQmZv6YuAemPu+tPwpLELD15Tz31VI8w5T3PNA3B9PBhfZKPzDvggAM8gpRkJwlg1mE+yQx6+mq/YH03sA9+k5aBcXoEiyxmO3rCyttW1/O3p1GaXsJsR3KXRC3Hw+uzjRvU1s1jnNc49NBDvfGyDsdPKUcaxtk/SVfG3fZMH3300V6Ip1OWK7jtOourjSs7a2Pl26+36cP00RsxYCRvcu+Zyb6PyxZIO2EytlnXnsi42id7vUT11I9konq9IV/zJqHK55w8d+W9mw5yV2SukbzV1R26R1NBZNj1AkKCLRNJXhF39MYkEClJ2vFbqryReaPoZqL0p90yxXvDzdWdY9C840l3o6M+ldYm6ZK8zCPRyzr81YfId5GpIntF2ousl1R+qqUwIslNRN7GvCc4bnkm8+gHjl/zc6Xm7sp4OuvOtevOa/nn6urBjbs688fdeoy7fXbnXJK5ljs2xf3jd9P+uVq6+0herYPWyV1f5VG6+RZP7Uu06dP0aRgwDBgGDAOGAcOASBuSGr3RiGpjMuO+YWBHDPhJSDctfSW6p/11ST6yjfIZZx4JDJKk6sclKRXXtShJxoqQZVvlMc4Qr43bXtdhnupScgxuvY7irM9+aFOVXZXSnYe/vfsNXdZTXemDsqGhwRuT5ufvo7O0Ox/GO6tv5Tti3nRiOultGOC+Zjar1L1Hu3ZA2QvjyUR2W9V1+9mZ9dnV9un438o/JvIhpaWlnoMen3G8N/gsU5D3bjpJXpG9iaR58mYoyStCkFJkoMg7Sn0blgAggacbU5I3CON+ULvpdNxEvblP/9zdtBuXDinjbYTM5+ZAOWLECO+7tvSU5ZrwRuWauN697lq666l13Vnp4kFx97r8IQD75vHenAfHyjFzrpoX04mCq5N48d681rsyNv9cXf1Ib51Jt43625UxdUdbjdMv3bkw3tncrTx9pK/WgmtETCT6Tkd34MWukboXc9Ol6dIwYBgwDBgGDAN9CwNG8prhvLcZzm08nWPSJSDjxUV2sswlPN260rMIWZGbymcfzGPaT26KtFRdt1/FWcb2vL5IXtX3SxGf6ldp1mN//vqdpdnenZd/bm77RP1rHpJqk6i+yuNJzYtjkk7j1bO8zrFvOjId9RYM8H6WPcvefVP37uu34zIt+2FHdly3DuPqp6tro3aSXW3fWX3X9sl4vPr+fI2FknMjH0NvXT5PGEjuksdxj2fuSYJXxK8d15zhnrzxSECSejqCV56k/EUCQU0AE/CKuzetC3J/3H+TsL0b/OV9Le3O1x27m8+4qy/GOyKt5BlLApVeqBi3EwAAIABJREFU1VoXro0C87SG6SR5eT19d5dx/zy6kvbrxNVXpsT9c/Snpa+O1t8tU31Kf199UWf+ObhztXj6iFzplnuL9hdhy12TvogpG3PqXuJNl6ZLw4BhwDBgGDAM9BwGjOQ1g3lvMZjbOFKHRZKKfnLSr1+RlW5d5aluvLTIU9VJRorkVF2NTVJjUDmlyjqTqqu27EtxthXBy7jyd1V2NiaVu9eRDtzxueUWTx3+TZemy+7AgJG86X13dW2GisueSCl7o1+6ddSOUv9ruHluvsq7W/rHwzT5K46D/IzKmSZXQyKXpK5OqRChSqkjlEXwulJlbv10x43k7Wckr7w2JUUm0oOUeQQwgcybVMCmzMvNQ35e/ichP3+7cv9N6RK8uln8dTIh7eqIcXdzS7QJJsrnRkn9i3AlAa91ItErr95UkL7sl9fhL0+49jrKm9fQ+vvnkmzar5NMWOdEc3DnGk9v/odfvLSrV7c/xRNduzfna+ySmmO8+Vteeklf6V5rQdmbsWNjS++Lu+nX9GsYMAwYBgwDhoGexYCRvGYM7w5juF2j+3EWj2iMtw4iHePVZ168Nl3N0zW62o71d3UMmteu9rMzY7c23Y9707npvLswYCRvet9fXZuh4rInUnZmu3XrMq4+/LKn/w/xj4dpjskvyZvoZI5E39wVkevKeORvusld9W8kbz8jeUUQijyUJOFHUpFkH+MiZj3w55HkzUdBXkF78Ahfh+j136T9leT1bxbuJuffEFXm5ssDj2Sv1oOSayKiV2voSq6jm+4ozrruenPNmcejmfmrFY5HY5P0z6sraT82MiGt+Us/klpLf1r5rlQd9SW9bHfv9VFCTnPyS81Z0tWHxVND9kq3kv41YFpYM5nel2TTr+nXMGAYMAwYBgwDhgE/BozkNYN4dxnE7TrdizWRm8nqPV793kCM7uoYNK9d7SdZPVq97sW56dv03VMYMJI3ve/U8WyHsitSdsVm67Zj3O3b/16c7rR7bcU1Pn+aYyFfQu9dnkohL15KEbkiVCWVL8l8xSlVrzukkbxpInk98jQSI96C4TAYQpEIwpGwFzoi4bqjTOOQ5DWj5VGUV1R45GI4FEZZWRnyCwqQk5OLfI/gHYWCvEIU5I3y0roZKP03pZG8MU9nbRyu1MaoPKUpRfIyTtKVmws9bbkZUMq714+RjkhelUmyLT142Rc9d7nOHIv/eFeNj9Jd62Tifjz09bQfz9KBqyPG3bXsKO6201pzvd3r9HWdueOXvij9c+9IT1bWdeLX1a/07q6FxdP7Ymz6Nf0aBgwDhgHDgGHAMNARBozkNQN5TxnI7bqGPcOAYcAwYBjoqxgwkrf7369lU3TtjMnaad026ofSfUeWk5Obl+q4e23FOTbFNSZyJSRl6bVLD14e0SxyVwStyFulKZWXSLp10x03kjdNJK9IuGAkjEAkgkCkHGXhCILhEEKhoCcZTzaESBg7wd/OLUsmHgxzDNuHUCSESHkUEXr1RspRWV6FUCSKgqIij+jNyy1Afl7xthBzZXdvCsVTfUP2lf40/0TS3eC4KSrtbpAiWpXHdHFxsUf2yvvW9ewlzpiv7/VKCn+Saktyl4H5/A4zx5Cdnd2+ufk3Oo3RP6e+sibJjrMr81Nd6YZS6yXplvnLVaZ+kh1jptTTvCmlC+nNZNdJXepMeqR09ct4puDG5tH9L/Smc9O5YcAwYBgwDBgGUo8BI3nNwN5XDew2bsOuYcAwYBgwDPQUBozkTf07aTLv+bIxunZHxpO136qd+knmml2po34TSV3fLzl+tuFJquRJiGsSvC65K+I23eRsqvo3kjctJG/MczccLkd5qBKV4RqUh2pQHqhGZaASlWXlMcl4kqEqWAU3+Nu5ZZ3HK1EVZKhoD5UBjomhApWlFagursDYyGiMrhmHUKQcpWUBlBSXYlR+CQryimKevdvOLPffSF25GTO5rl8v2lCYr7hkR5ujiF99r5cevQwkbumdKylC1/XYVR43DG5arMs86p3j0HU5Dv943XQmr5N0EW++ynPnz7zO1k3lfqn+XOn23V/imr/0Ixya7DrJKx1SSq+u7C+Ysnn2zAu/6d30bhgwDBgGDAOGga5hwEheM5D3lIHcrmvYMwwYBgwDhoG+igEjebv2vpmq93PXvsi4bJDJ2m9VX9Ltj2P0p7s6brd9MnGOgzwLvYjJj5DIpeeujmcWsUuZKvK1u/rptSSvjqhNpyK4YHS95mLyexH0ggwEAjsE5iuINOtI8mjm0nAUkXA1xgfGo6GsHvWl9agvrsfk4jpMLpyIyYWTOggsZ5jQHqYUT4Qb3DLG3bKdibv9TSmciMZRk7w+awOjUVUxGtVVNSiPRBEsKUPJqGLk5ea1e4j5b6Ku3pCZXN/VjbuhKe5Kd4NUvpsnspcY5Xd0RdwyzqCjnEnkMjAtr1+RwtzE2A+/vUvJ67hjTBTP5DXi3Pzz1nzdfK0Jpbsu8eJuXbePeP0qrz9K6Ub6iqdLy4sRv7xfFagT6Uw6FH503Ik/X+Ume+bF2PRuejcMGAYMA4YBw4BhgBgwktcM7H3VwG7jNuwaBgwDhgHDQE9hwEjennmPlm3RL2WTlExku1V5POnvc2f+V/L30Vma4yTHR69dErsK5AfTyUF2R9+9guQVS94dxK6r1HSSvGXhKKpDY7H1pofx9PVP4LEbHsXD1z/ihYeuewgPX/cQHrnuwU7CA3jkuljYev1DcIPyJd2ynYmrH8rHr30I37v2cWy++E5MCkxETflYVFfVoqqyEhWhCKKBIEqKirxvxvIG1A20MzdjpreRbii1oblx5VFqQ3Tz3HyWk+ShZB/clOidq/uGcRG7In4lSfwwaDy6htKdyUxfp0Tzk16kL61RZ1L11V79ax2U7q/SrwfpSXqj7EzH/a1cBC+lX0/8nnMmf9O5v94nNu+e+SfG9G56NwwYBgwDhoF0YsBIXjOQ95SB3K5r2DMMGAYMA4aBvoqB3kDy0pbpf0eMl+evk4lp2XElZaf022qVL6lypdWecmf05LZXvKN+yAWS4KWzJ4M4SUqXM+yL8W4jeUlEMZB0kgLpQcs8paVAElUir9ROUnVSIXnddHjyhkJhhEIRTCgbjy3nbcI3j7sFi/c8GyfvtQgn7Hk6vrjnqTh+z1Nwwp4n44vzvoQvzjtxW2D8JJww/2ScuNep3R5OmH+Kd83Fey9G8ym34bbj12NySR2qI7WoKK9GRUUlqssrUEmP3kDA+1YsjxD2b2i6qSQ7urkyvUw6oNQGRunmK+6Wu3FtgJQieuiJy0Bih17lIncl6clLEpjlujbbu9dSPJ7M9HVJND+/LrQO7hrEi2tdWKY26ivRtSz/EwOidCXd+WU8nfeHPOHKlcKYdGY4+gRHpgvThWHAMGAYMAwYBgwDvR0DRvKagb2vGtht3IZdw4BhwDBgGOgpDPQGkpfvmHJakezt753pHp9skztrx1U79dPV8aodJftSmutDWyr7I3dFXpHYJbFLPlKkLvPFMfr5SeX3FdltJC8VIiWKXCXByg8aM0iRjFPBJKtE7LoKT6ViNY5UH9ccDoURDkUwqWQCHj53C67f72rsWbQPGoN7YkLRTIwvmo7xRY0YXzQN44um+gLzWNaICcUz0hYmls7EpLJZ24WJpTO89LzA3rjjCzfi5sOvRF3BeFQEqhCNVCISLUdVeYUXSPLqaOuysjLvhuENpJvJlV29QTOxvquPRHH/xqa0pJ/UEvFDvZeWlnpkL4ldxouLi70Hj9pK6tpMKx5PZuIaxJuT5q4ypSWlN7/u3TTrKK36ak+pvk0mNjq6+nLj0qek9NzfpO51Ss6d+pCeDFeJcWW6Md0YBgwDhgHDgGHAMNDbMGAkrxnIe8pAbtc17BkGDAOGAcNAX8VAbyF5e9t7ZU+PR7ZJv5QdVzKRHVflrp3T7auz+bl13Tjtp0yTXyT/p2OZKenJy7xUcoy9oa9uIXlF4FKSUJ0zZw6WL1+ODRs2YNOmTWhra8N9992Hb3zjGzj22GM9JZMA7ojkTcVisI90ePJGwhFEwlGP5H3k3C1YNe8SzCiZjzHB6agNTUVtaApGhxu9UBtuhD/UhKahJjQV1cEpaQlVwQZUh6egKtywXagMTfbSjeE9cMuR63HLkVdjSmk9KgKVCIfKPe/kimg5GHiT0FuUXqQiFo3kTWxEcTearsbdDY9xl+RRGTcvevayjP2rnuqqXrLX7mwTzZRyVx/SUTyZzMOI7dRfpuinp+chfWpNEq1DJuZrzq6UPih7em3s+on3e9ON6cYwYBgwDBgGDAOGgUQYMJLXDOx91cBu4zbsGgYMA4YBw0BPYaCnSV7XHpconujdrz/l+3Ujm2Yiu63K40n11ZH+VMcv6QAnr11JcoDiKHsDKZvqMewkyVuD6uqOQvUObPi8efOwcuUKtLa24q677sLFF1+Ms88+G0uXLsV5553nkb6XXnqpR/xu3boVt9xyC44//vgEzHrNtvwdZWxcO14/nuLSTfLWlUzAo+dsxvp9rkBjYA9UR6agMjoZldF6VEYbUBmdgsrINFRGp6EiOhXl7WEKopHJXoh4sh6RcB3KI/WoiNR7sjwyGQwVkVg/sfr17e1YFg3XefVjbWL1oxHWqUO0vH6HEInG8qdE5+Cmz6/D14+6Gg0lkxAuiSBQGvK8k8sjMZKXx26T6BXJS69e3kDxiN6Obsb+UubfbPzz9pf709rsuCkqzjqKsz9tmFyD7Oxsr4z5qkPp7zdR2j++TE2783f15I9Lt5L+crefTNVVT85L+pXetQ6ZKjVPSc1fsifXwq5tRmvDgGHAMGAYMAwYBgwDO48BI3nNQN5TBnK7rmHPMGAYMAwYBvoyBmgT6+53UNnhJGWnk1S+X3b3OHvj9agT6SmR/Vbl8aR02tHcVEeSdXlKMJ1M+cMA12tXBC9lPJ6wr+d1meSNKYIEby2qqmpQWVntSaYZpCh64c6ePQsrVizH5i1t+Na3bsfll1+GM844HWedtRiLFi3C4sWL24leeva64atf/Sqamprw0EMP4fbbb8cJJ5zgLVI7615DT98ajB7N451j44mNQcTvNqK3pgrV8UJ1tTfWdHjy8rhmevLWl4zHY0tace0+l2NGcA4qw/WorZ6GiorJiEYneWRtdWgaqkKNqIhOQyQyBaHoFISjDYiE6xEO1yMYYahDJDwR5eGJqAhNQnmoziNzy0kah6ehMjw1Vj9ah3C0HpFojNCtjNSjKlyHqjDJ4RhpHI1ORIShvA4RH9H7Cck7GzcftQ63Hr0W9UXjES2LIhKi127MQzkaiXnykuh1vXl1fLMRvV3/p1+bESU3JDftxuNtel3Jc/tSvKPNMlPKNFdJzUtp6TDeQ4dlylc9V6oPSfVtsuv3QSKdSbeU0r3WJBnpHnesI4+TaZdsHY1JsrN2HdVTmaTmnkg3lp86nJkuTZeGAcOAYcAwYBgwDKQLA3qnmzp1qudZQK+CvmxotbEbUWAYMAwYBgwDhgHDQHdgoK6uzntn4rtUut7T4vWrdzfZ55KRaiMZr9/+lEc9+PXm2kwTlbn50iWldKc8pmnn5Xd3yVOR3CXJS75PQVxlXydxOxt/l0ledkjl1NZQWWNRWzMGFRVVGDNmnEfyzp07DytWrMDdd9+NO+/8Fi655GIsWbIYi75yuhfOPHMRYuErcUneiy66CG645JJLcMUVV3iE71NPPYU77rgDJ598SjvJzOvGSN7R7SSziGBv8h7BW4nqGjfEPqrMeaSD5A05JO/jS1pw3T5fxczQHFSHJ6MqOBnVwQaMDk3FuEAjJpbOwsSSORhTOgOjAzNQE5iJmsAMjC6bjtGB6agJNHphTGAqxpXFwpjSqagpa8To4EyMDc7yyqPByYhE6xGO1oFkbXkk5sVLYpkhRvKSAJ6AcHRCUiTv/3xhLSYVjkE0EGkneUn0hsNRz4vXPbJZHr08upnf6NXNJqmb0GR8w4n0ROnqyM1n3N3kdibu789/PffamRSPN283T7p0HzSKq8yVblt/PJP01hvnQn1zLbQ+ycjeSvIKU5qD0pTCVW9cAxtT/H3c9GJ6MQwYBgwDhgHDgGEgEQb0bmckrxnEu8MgbtcwnBkGDAOGAcNApmCAJC9/HMd3qUTvWenId+2Prr0ung3PLTeb3if/D+j916+fRGnpVlL11I+7ziyjoyG5KBK7xAg9d0XyevxlhnrtxiN8d4nkJbkaDpdj3rw9cckll+H++x9Ea2sb6IV75pln4swzv7LNc/dMLF5MUveTwLJ4nrwieEkU07OX8sILL2yPr1q1Cs3NzXjssSewYcMmHP/FE1FdPdojmenVuwM730MkbzAcwcTicSDJe/3Cr6KxdBZqA1NQH5yDeZX7Y0H0QOwf/RwOjByKgyKH4YDIofhM+BDsE2I41JP7hg7GZ8IH4zORg7Ff9BB8JnoI9qs4BPtWHIK5gQMwJ7g/JubPRl1gLmqD01FdPg3R8EREoxNQHpnoHctMr96YZy+J34kewRsqp5zkkcEkhBXCEXr51qEhMgs30ZP3mLWYWDQGkUAE4W2evFxvkrz04FVwyV7eWOFw2PsFRWFhYTtR0d0bsXvT9+W4NjFJbW47K9WPZF/WTVfGrvkm0pseHvGk2qgPSv+1Oyrz17X0Jw/7ndWF9K21oYy3dsrr7SSv5qF5uXJndWTtdh1npkPToWHAMGAYMAwYBgwDqcKA3u94XDONUObJa8b3TDG+2zwMy4YBw4BhwDCQTgykk+TV+5lfyk4nu2JXpU4RdPtN1TtlX+rHnX+8uPQs6dez357Lz1OyTnFxsRdI6hJ7fK8WuUuHzngkaKbn7RTJG/vuba13VPO4cRPwxONP4sknn8bq1VduI3dJ6i7G4sVnYtFXzvDIXXrykuSlVy89eRd9ZRHOOuss77hmfZPXPa555cqV7cc3i/gl2ct8jwBetgJfvewKtLS04amnnkHTphacesqXvW8F86hoLlxtLY9urvZ58dKjV+Xp8eQNhsIIhCOYUDwWjy9p9kjemaG5GB2YhiNmnYibzrwdG5e04P4l9+OZpU/jhfOexyvnvYTXlr6C15a+hteWvo5Xl76OV857FS9c8AP870X/iweXPop7zn8E95z/MO5f+igeX/o0HlvyFDYc14q1B96AkyediQOjR2BGwVxMLZuNsUEe5TzZO/o5HOVRzTwemuRuLESSJnlHIxIIe9/jpRevQjhMj95wu0cvdS5vXh7bTG9eusq7N3Bf2oR6y1hd/aUj3lvmme5xSHeJHhr+h4jSqs/27hj5SyE3uGUWT78xUOspqXWS1PpJ+l8KlJ8qqetKdtYv62ns8aRhKP0YMh2bjg0DhgHDgGHAMGAY6AkMGMlrhvB0GsKtb8OXYcAwYBgwDGQaBtJ5XLNscrLnSXZm1+uoXDZI1nHtf3rvlD2ZacaVn4lS+pXUHJWmlM4pXb1SjyNGjNgusJx8E3koHs1MrIvgjXGBn3xKNtNJXf/8dprk1RHJY8eOx+rVV+Gee+7Da6++jldeeRX33XcfeMzykiVL2r13SeyeddaZXhDJSyL4nHPOQTySV568JHhJ/kq2E8HLVmD5spW4+OJLsWLFxbjiilXYvPluPP30M95R0UcddZRH8sa+x+se1dwzJO/UYh7HPA37TjgMp81bgiXTz8G189fhsQMexNvH/h/e/cJv8J/P/wn//fxf8N8j/4YPjngH7x79J/zsiNdx/8LNWDt3HVbucTku3/Nq3LrPN/Dckd/FH0/6Jd7/8l+Bc/+L9xf/FW8e+xpuGn8tvjTqRDTm7YExwUaUhxpQUTnV89CNfQeYZO8kj/SNOl689OCN78kbn+TlkdQkeenNS09e3lxMk+hlWt68/ptXaZPJGVXcTS8d8XStQ1fHmu5xJHpguA8Pxd2HitppPukap/Wb3P3g15PWhVJrFU9qbXtK6gWPkmNwx824f16W3jk8mN5Mb4YBw4BhwDBgGDAM9HYMNDY2YvLkyebJO8mM8JlmhLf5GKYNA4YBw4BhIB0YIMnLkI53PNnnZEvcWbuha/dz4+pX13HnkOkErzvXRHHphXqS7qk/P7nLNOtUVla2H808fvz4HTx2dzjht7p6hzp+cjRT0l0meWPKqol9/7ZmjPdN3tNPX4TNm+/xvGqbm1twzz334JWXX8arr7yCLXdvxlcvv8zz4F2y5CyP5I0d2xw7znnp0nNx/vnn46JlF+GiZctw0UXLsGz5cixfscKTjDOwXHEvfRGJX9ZZ6YXlKy7G8hUr0dTcjDfeeAOtra2oHV3ree3W1lb5vHnT68lLAjQYDmOi58kbO655WgmPa56KCaUzMb1kPuYW7I0j84/EqsCleK7x2/jbjLfw0ZTfAw1/BBr+hA+n/Bm/a/gptpTfhXNHLMahuUdi79wD8ZmCw3Bc4clYX34lnqp/EL+d8RO8P+t3+Oe8P+Afe/8GP5v1Eh6esgVnlJyBvYsPwLiyGYiG60FCN0by1qM8Uu8d5ZwqkpdEL28yShG/lKWlpd4vUnjD8kbUjUuZ6Oa2/MSGGVd/qYqnS9/+8fnX31+eqnH4+1Wa12dwHxh66CpPUnUl1QdlqsZp/STGeVd0466N1iue1Nr2BsnxueM2XKUGC13BjdU1nRsGDAOGAcOAYcAw0N0YkNcGPXlpALXjms0Qng5DuPVpuDIMGAYMA4aBTMKAvDXr6+tTbpOVbY52ulTaC2VvpmS/slPqet39DtqbryedSEeU0h/LSO4yzVNjeQwzg767258J3XjEdJdJ3lgnNZAn75gx43DiiSehubm1PfC7vK0tLdi4YQMefOgBvPTKS3j19ddw7/0xD18e40zC94wzTsd55y3FBRdcgAsuuhAXeiQvSd0VHsl7IYlfErxxwrIVK7FsxcX42qo1uPOujXjuBy/i9R++gYcfeQTXXX89Tl90Bmpqa1BVXYnuJ3lDCIfCqCsaiyeWtOL6hVd43+StDjegoqwOkcIJqClpwOScmTgq/yjcN7MFf5n5c6D+HaDu77FQ/xe8Mfb7WFFwAQ7IOQhTR83H2KKZGFc8B9MKF+BzxUdhdcVq/HzG6/jvlD/hw4a/4YO6P+GDyb/FX2e8he9NfQIrA8sxK38v1IQavKOaY0c0T0E4MgXhaD3CKfDkJZkrYpcevAz05lXgGem8KXmT6sal7M0bTF8Ym6vLnYmne47umHQtfqOZxD+P8nYDN2od7a26XZW6nvtQcOP+h7UeGHrgxnvoqk+OxY13dWxWP/1GRK2PX3aEAT8m0pn273/+cRpG0o8R07Hp2DBgGDAMGAYMA4aBnsQASV7+P0SSlwYqfWIqnpHG8vqP14Wtta21YcAwYBgwDBgGEmOARB6J3l0hef02OKVpq0uHLTCezbkju7PG05PvqT11bc1ddlO+L1N//PYu88gr0bGQP1zgDySJBSN3498vXSZ5qciYMmtRXc0PGY/GggX7eN/E5Xdx+Y3clpZWtLa0oq21FXdu+Bbu2ngn7tpIwvchvPjii3j99dfQ3NyEy756KZaS5BXBu2w5ll20HMt5FPOKlbhg2TJcuHx5nLACG5pa8PwLL+GlV1/Hgw9vxfU33YK111yLK69ei6vWrcORRx2FqppqVFbHjmeu8b7NS4/ebcH7Zm96vskbDpHkDaHeI3nbPJJ3etlsVMqDtrwe5RWTMbp0GvYu3A93zLoNf5r5FjDpPWDS+8Ckd4Epf8fzlU/g1BEnY4+iBRhbNgOV4amIhqagJjAdEwvn4PjSk/GD6c/gX42/Bya/C9T/G6h/H5j8F7w/8208OLYNB+cfgYnBmagK1yHifY+3AeFo6kleEr0VFRXejSeCl5IEHm9Y3pi6YZnuqc3Drpte447WVpu0JMldYoE40Y8BJLlZk/RV251ZI11HOJNM9LDWA9d9yAqf/uvb8RnpxYxf38mk5Qkh6W8jPEgKD5KJcJHqfF1P4/CP09K9D1u2JrYmhgHDgGHAMGAYMAykAwN8bxXJS4LXSN74BiozdJteDAOGAcOAYcAwYBhwMTBmzJidPq5Z9jhK2egkU20DTKY/XdsvOb50vH/29j61PtQH43xfZpw8AvkCkro8lpkYIB/JH0oy396jd9wjukzyxm6yGtCDl968lNOnz/S8eDdtbAKPa1ZoaWlBU/NGbGrZiKbmJu8oZeY1Nzfj7ru34JVXX8Zrr7+C+x64D6vWXOl9Y3flhStw8UU8gnkFzifpe/HFuGjlSqy49DJ8a+MmvPDKq3j1jR/h3gcfwfU334rVV63DVeuv88Kaq9djzVVrseaqqzF/r71RVVPjEb0ke/2huqa6HRwEDH8NEAwGPSKKZJQbmK/gEpgdxcOhIOqKx+DxJW24buEVmB7cA5XRBkQ8D1qSvA2oDUzD7JJ9cMPMG/H7WT8D6kjyvgfU/QOo+wuer3gcZ+SegblF+2J8YBYqw1O8UBWeirHhRiwo3B+3j7sVv57zJj6Y8meg7p9A3ftA/d+BqX/Ba/X/i0Vl52B6yULUhqYgEp2AmDcvCd8dQ1e/yeufP0leBhJ51BfLKXXD+mVv32hsfIkNPFxLbrp8gPnXVWmW8xc3+m4zSV1hRD8I4MbMoHxih1691D378a+BNn2V6VqSLNe4knm4so7aqA//NS2dGAc9pRuRu5KJxqE1pdQ6dxUfyeIoXj1dU+NINE7L730YszWxNTEMGAYMA4YBw4BhIJUY0Hvr1KlTPTuEGad2NE65Bl2Lm34MA4YBw4BhwDBgGCAGSOwl68kr+1s8KRtdPPtdT+RpPJIaM98/9d6YynfR3tCX5kip8TBOHdAhi3FySTySmVxdoqOZ+R5tHr3b7w87TfJWV8c8eWtrxmDs2PFoa9uCpqZmj8ClJy89epuaW7DJI3c3eZ67JHeZz6OdvfrNzWhua8bd992DF196GT/60U/w0H3f99YXAAAgAElEQVQP4bp11+Gi5StxwYqV2NDSiu+/+BKef/kVPLD1UVz/9VuxZt01uOqa67F67TW4cv11WHXVei9OsnftNQzXYvqs2aisqfWI3orqqm4neUOhICZtI3mv3edrmBaYgwqP5J2McHQyyiumoDo4DdNLF+Ca2Tfgd7NJ8r67LfwdmPQn/KDicZyZvxh7jNoXEwKzULWN5K0MN6C2YiqmF87DV2suwQ/3eh7vT/ttjCQmUcx+Gt7FTye8iAuKLsL8wgMwNti4jeSd6Hn0xiN7d5XkFZmnb/OKBObG5N7E7o2sG9pk3zWiaG3dhxJ/pU7ClgQupUhcV8qTl1LYUVwPM0phQ3lMC0P+ayf7UNZYKdWHpK5nsvdiUliQTLRWWlNXcs2Txcmu1hPOdP1E47T83os1WxtbG8OAYcAwYBgwDBgGUoEBvbfyuGYapYzk3d4wZYZ804dhwDBgGDAMGAYMA/EwIJKXtrXO3slkf3OlbHO7auNLZ3u/fbqzefbVcnddGOf7MfXK+dPpix679NwlwSsPXq6/n9C19+gd94pdJnl5XHNlZTVuu+2b7SRvU3PzNoK3FZuaW704j2duaWpBc9M9aGJobsOm5hY0tbWhZfNmtG3Z7Hn6PvDAw3jhpVfx6o9+jOdffRX3b30UN932DaxZfw1Wr1vvhVVr1+NrV6/DmvXXYfW6a3HlNTdg1TbC96r11+KKNVdhzIRJHslbWVODniF5Q5hUPBaPL9mMaxeuwrTAHqiI0pu2ayTvV/LOjEPy0qO3AQ3Fe+DUslPx3fmP4r3GX8a+5et5Af8DmPwefjH+FVw6ahn2zTsA4wPTEY5Oag/pIHlJ5pGsk2cm0yR66WLvv4n76mbU38fNdaQOZKTQuuphxA2ZRy+TzBWJS0yI+Bcm9AMAeXwrzXrcqNmeeexP13ClHtCSyTxoVVdjdfvr7+va1+Yv/EkmGj/X2F/GPGEhGdx0pY76lXQxFm8s/rFZ2ozIhgHDgGHAMGAYMAwYBjIbA0by7miUimfQtTzTk2HAMGAYMAwYBgwDxMCukLy0z3XFrteTdePZEjPt/wLOUXZZSnrv0lGMXBJJXXps88Rd3fvkCOIRuvHy1Ka/ypSQvOPGTcBVV631SF568W5qavbI3Y3NbdjYvAUbmu/GhpaY3NR0H5qa7sXGplZs5NHObW1eaGlrRROPd25rw52bmnHdLbdg1dp17UEE75prrgFJ3iuuXoe1N9zskbwke6/gUc3rr8Pla67CRRdfgvLqGlTWjkbPk7xbtpG8c3ea5J1TsM92nrwV4SmIBiejITAPR5cegwfntOEf0/lN378Bde/EyN6Gf+Ct8S9iZeEFWJj/GYzzSN46hKOxkOrjmkXekaQjQScPTubre6su4ZFpm1SmzsddM8X9c2U+N2kSbiJpudmS5BUuSNiS0FUQqetKlbEd8eP+WEBknsagB19XHr56kKgPdx7qX9Its3jvM7RpnSQ7WyPVo2RdYVY4ouwKlvx13X6EL8nOxmblvQ9ftia2JoYBw4BhwDBgGDAMpAsDRvKawbq/Gh9t3oZ9w4BhwDBgGOgKBui9ydBVkte10fntd709rbG7NkXZMvlu6sbT9a6azn45P/avedK5i/Z/eu6S3GVwvXbJL7CcuHHzu4Kj/lJ3l0leHtfMcN55F2BTE7/B24oNm5qwkbJlM+5quRe3tzyIW1u34ra2rbir+T40tWzBxpYWbGjehObWZngEb2srmkj0trXgruZNuOHrX8fqbSQvCV4SviJ6SfLSc5eBnrwkdxVfvXY9Tj1jESpqRqOiphYV1bHv8dKb1/XoTfc3eUlexTx5dyR5gxF+k7eT45rr/owXKp+Ie1xzeagB0dAUTCiehc+Hj8ETBzyId2b8FJj0V6Dub0D9X4GGP+HF2iewqPAMzCjaC7UhHtdcH/dbvCJ8d/a4ZpJzJPMkdSQvCT/qgd831s2rTYoynZuG9Z0aw4y7Xoq7GzLzuCFz/UXwcwPmursEr0vmJoqzvtrIC5hSeHJ/LCA8Sfof0vwlEAPzVUfjpzR8pAYfvUWPHa1tvBcg1Rc2/NKPp0Rpfzv121v0YuPILJzbetp6GgYMA4YBw4BhoO9jwEheM3D3F2OjzdOwbhgwDBgGDAO7goGukLyyx7l2ukS2PDdf9mPZkN208tz63RnnXPjuT7umQl/7X0DrIsk5MU49UpJD4BHN7rd3XTKX5Qy7gqP+0naXSV4e10yS9/TTF3kEL49n3tjUgg1NLbij5V7c0PQozr3+bnxhVRsWf/MZfK3t+1i3+SnctGUrbtt8LzbSk7e12fPqpRdvU1sz7mregBtuuWU7klcEb4zw/YTkFbkrSZL36OO+2E7y0pO3qiZG9LqyJ0ne0DaStybgfJN3lu+bvB2QvPTkrSpv9EjeU8edjje+9EKM5K0Tyftn/KfxN3gw2ozDc4/CpLI5qA5PTRvJ65J2JOlE0BnJ2/eNENqE/ZIPFR6nwLWXxy3XnWuudXdx0ZW4yF71RUmil/3zBwO8rh66I0aMAEOih6we7vHG39cejDbexPeTu75+PXVE8rrtGBdeJOPhimXMVx1Kfz/+MVg68dqZbkw3hgHDgGHAMGAYMAz0JwwYyWsG7/5ibLR5GtYNA4YBw4BhYFcw0BHJ67fDyaYXz47XV/Nkb4xn1+wr787+ddKcKDkH4oMELwM9tv14MZI3+T0kZSTvwZ87FC0tm7GJRzTzKOamZtzc9ADO+eYzqD3tduSdugXDz3gI4RVPY851z+Hku76Pr7Y+idvvfgAbW5qwoal529HN9PDd2CHJu3pdzIuXxG47ubvuWs+rlyTvvAULez3JW1ExBS7J+/udIHnH5jfi6oVX489LfoV3ZrwV8+Kd9A7Q8Ee83fAGri9aiwX5B6A2NA2V4cmIRurS4snrEngk6EjKiehlmXny9l3DTbzNmJsw15TrrCMTRMiKoHUx0VmcbTqro2uR7GV9eo1zHCR4+WBwH9hMK2j8feXhZ+PcuXtF60zp12FXXobUj/Dj4opx5VOqbrxr+sdg6Z1bV9Ob6c0wYBgwDBgGDAOGgUzDgJG8yRur/IY+S5vuDAOGAcOAYcAw0H8wkAzJ69rp/Da8rqbZV1fbpLO+5ubaH914X3hHdseruObFEztJ7PKIZnrz2r29a/f2LpK8taiurkVNzWjstfdCNDW3YVMzj2jegju33I9r2p7AfiubUXzSRgw47UlknfUD7HbOsxh5wZMIX/gADr/5KVx7z1O4o3ULNjS1oqW1zTu6eUPTJtxwy/bHNbuevIlI3jUketeux9QZMz2St7KmFlW91JM3WZJ3cf5ZmDtqP0wom42q8FQv1ISnY3RgBhaEPounTnoC75z0Nt6d/kug/m/A5D/jnen/Dw+NuRun5SxCQ/4eqIw2dEDwTkIkGgvhCGUdGiKzcNPR6/D1Y9ZiQtFohANhhEMRhLYL8Yk5kbwiepk2krf3Gme0wbqSDwmmJRnXBlxaWtruvcvNl2S+vqVLojYZwtZP6CbThtdgO5fsJeHLB4L/IayxUmpefeHBZ2Pc+ftE6yzcurrsCsmrdurPxZLiKlNdkzu/bqY7051hwDBgGDAMGAYMA/0NA0by7poBywyApj/DgGHAMGAYMAz0DwzEI3llk5ONzpW7Sriyr13tI9Xt3fkxrvlT9oV3aHe8imtOtPOT3DWSNzX38y6QvDWoro6FmtrRmFTXgI1NbbhrUxtua7oH6zc/ijX3PYczv/ksGs+/D0NPehiDTn8a41a/jOLzH8PQ859FZOXTWLb5ZdzS9ijuarobba2b0dLaig1NTe0kL7/Lu2bdeu/oZsZjYT1I6Lph9dprvPSV665BzeixqKwZjaqaWlTX1IBHM+8Qtn2wWb8Y4AeeSSSRkPQHkVgimvwkVaJ0om/y6rjm6uA0NJYtwPrZN+B3s33HNU/8PV6ufBLnFpyLefkHYGLZHqgONaIq2IjaoumYXfYZXH/QLXj3wj/jjwt/hn9N+x0+mvoX/G3aL/FM3eM4teArmDNqP9QUT0V5+WQEy+tQFp2IcDTmzRuK1CEUmQR+hzcanbiN6K3z6k6NzsGNR6/DLcesxfii0QgFSOhGEHRCKBSf5KUuRPTq+F7qTTewbmi/7AsbUyaN0a//RGmtm8hdrim9dxNhPt35xJaLLxK9HE9xcbF3jDPXiHMRsad5ZdLa2VzSbwwVbvzSdJ9+3ZuOTceGAcOAYcAwYBgwDGQyBozkTY0hywz8pkfDgGHAMGAYMAxkPgZE9NbV1bVzC7JVU6aaVO2N/bnzdeO0Wfb2d2a/XZVprRvt+SR4GXRUs31/d+fv6Z0kebe/IEneqpoxuGtTK5ra7sWlN23AUes246Drv41Dbvgejv7GTzBlxdOYdsl3cFLb2wif+wAGXPQKsle+goNvfRkrNj6D25ofRKtH8vK452bcuM2Ttysk75XrrsXFl13ukbxVLslbvf149RDgRtETJG9w2zd5E5O8/wDq/4pfjH0JVxZ8DYcOPQrzCvZHff5c7BE6AIePPQG3HHUH3r7iN/jzSb/G/5v3Q7w95//w5vRXsLmqCefkL8X8ooNQUzYd5aHJiJbXI1g+yQvh6CSP6A16JG8dIuG67bx8y6OTsQPJGwx7BG8gHAFDMEyv3uRIXnl6ahOKd3P3hU2pt2+aOzO+RGvBfB2DzO/f8kcPJFMZRNwn432bLsI3HtHLcTFfZK8eyprjzujH2piB0TBgGDAMGAYMA4YBw4BhwDBgGEglBozkjW+bkY3GpOnHMGAYMAwYBgwDhgFhwE/yyt4rnkHp/iA1Z8m+YPPWGF3J8XO9SPKOHz/eSN4EvKXugWRlykjeypoxuGzVVbhjYysu3/g4Rq98CNnLnkX2Bf+LxnWvYuXdb+KSDc/iy1//DuqWPYihy17Bpy76IfLPfxJH3vaCd7RzUxs9eTdvI3lvbffeTdaTlyTvaYvORHXtGPQVknd66QJcs4Mn77vApHfxn4bf4YcNz+H+KZvRemAr7jj0Ljxy6mN4/aI38KuLfonXjnkRT858EPfXt+L62uuxJHgePjfq85iWvyeqi6cgFKSHbh2i5fTeZZyevC7JOxmR8BREI1MRidTH6kbqUkLyknAj8WYkb+82iribrBsvKioCvXd5PLK8ZSlFsKaLwO1KvxoLMcYHA4PIXpLTDDTIcF5+w0y8PH8dS/du7Nr62PoYBgwDhgHDgGHAMGAYMAz0NQwYyWuG62SNdVbPsGIYMAwYBgwD/R0DiUje/kDqdjZHP9nr2vUV7+n3ZI3DlfFIXq4zsW6evDu/56WM5K0ePQ6XXL4aG1rvwbK7vo3Clc8i6+KfImv5j1G6/Flcfs/LuKHlUVzZ8l0cdPk9KFu6FbkXPovC8x/Dqff8P6zb/ASatmzxSN5NTS248Zaukbw8upkk77HHn7iN4HWOa07AiPcGT96EJO/kf+Jf9b/Fm9NewFPzt+Keg7dgw+Eb8M0D78CtC27D6vGrsTywDGfnLMbJOafgwPzDMT1vb9QH9sCYwDSMLp2KsWWNGFs2HePKZmBiKeU0VIYnozwyGVXBqRhdNgPjSudifNlcjA7OQHV4qlc+zX9c80548hrJ27sNLtxcudG7m6yb1sYqD96ukK/dWVdEr74BTaKXDwTm0wOZxzbz4eF/qGn+OtZZ0l/P0r0bx7Y+tj6GAcOAYcAwYBgwDBgGDAN9CQNG8u688aq/G7pt/oYdw4BhwDBgGOhvGDCSN6fDI6lF9Pql7P09/Y6scbhSJC/t9/LkNZJ31/e2lJK8J5xyOr65oQWLbrwfOcufQ9bKXyLr0l8g76Jncdqdz+OatifxP5sfw7Ut38ZXvvkMZl14Jw5a+xAuvvdl3Nz2EJra2tDS0oamTSR5/wer18a+xUtP3u1D7Pu77jd5RfLuf+DnMoDk/QfQ8C5+UvsCVuVfgaNyjsXe+fthZtGemF60lxdmFO2NWNgLU4vnoz44D+NLZ6KxfD4+M/ZgHFL5eRxdeTyOrT4JR1ecgGPKT8DexQdgYnAmxgSnYX7l/ji4+mh8oeZkfC5yDOaHP4uJJXugJtCIxsg83HTU+k++ydtFklcknzx5mdZm497UbrynN51Mv76razeudaGk5yvJURG78oolgao17Y1SRC+lxkey1/U85pw5R64z5ykdMG0ErxkGM/3+t/kZxg0DhgHDgGHAMGAYMAz0DgwYybvrRqz+ZuC2+RpmDAOGAcOAYaC/YsBI3o5JXtfb17Xxu3bvnvwfQONwx6a4kbyp3ddSRvJWVNfiC1/8Er61qQ2XbHgKRRd8G1nLfoys5T9B7fW/xD5XPoY1m7+Hb7Y9jNta7sf6+76P85q+j7NbX8OKe17H2pYncXvbw2jb/ACaN7XiJo/kvcYjetesI6nrD9eCxO7qtawTC2uvvQFz5u7ZK45rDodCqCsei8eXbMa1C1dhWmAPVESnIBydDH2TtyY4De2evLN+BtS9Gwv1sW/yfj/yOBaN/ArmF+yH+tJZGB2agprQFFSFp6AyPAUVkQbPKzcamYzKymmIlNZh1tiFWHbEZXjonEfxw5Vv4o1z38RTJ34Hq2ZejePHfRlTI3tidMk0nLLnWbj1xG/hsUVP4ob9bsURY07EtNBC1JQ1YnpkvpG8Bb3DCJCqjVibqivZN9PcXEmQukczi+AlaeqSpyJRe5sU0avxMs05yMOXkuQuH36at3RrJG9mYV3ratLW1TBgGDAMGAYMA4YBw4BhoLdhwEje1Bq0+qvR2+ZtODIMGAYMA4aB/oABI3mTJ3lF+IpEpc2/p9+DxUNoTK40kje1e1iKSN5alFdWY8G++2Fj6xbceO93seeabyPvvKeRdfbzKL/qF9j/xldxyebX8PXNj+PGpgexouU5HHnz9zH50u9g7NKtOOKqp7B28yto3vwEWje24qabb2snb/0eu25aBK8nr1qHsRMm9TjJS4LXI3mLSPK24dp9voapgT1QHp2C0DaSt6JiCmoC09BYtgDrZ9+A3/tJ3oZ38HzFEzgzbxH2LNoHEwLTURmuR0UkFnjkMgMJXhLHpaFJiJZPQWVgMuZH98eq2VfhuaOfw5sH/Bj3TX4QJxR+GbNG7YNxgTkYE5qNhrK9cMKERbh51q24ILwM8wr3w4TgbNSGGjE1NNdI3n5A8nLzLy4u9r5ly43V/aatiF2XPO1txK47Ho1TUmSvvMnp1cv5MZ9kr0vs9oaHXk8/dO36ZgA1DBgGDAOGAcOAYcAwYBgwDKQfA0byptag1R8M3DZHw4xhwDBgGDAM9FcMGMnbdZJXZC+lS6qKcO3O931d0x2H4kbypnZfSxnJW107GlMbZ2BTy2bc0rYVi2//DqrPbsOgRU9i4FeeRXjJIzjr7l/ja/e8hnPveBrTLmrFtLUvY9iZT2Pwl59AzTmP4eJ7f407Nj+D5g305E2O5G0nfK++BpdevgpVtWO2P665usb7cHO8zZAbxejRozFu3DhMnDgRwWDQ+44nv+XpBuYruMRSorhL8j62pA3XbEfy1iMYqcP2JO+N+P2snwOT3gcmvQfU/QMfT/wTXqh6EotHnYnZ+XtiXKARFZE6lLeHeo/gjUTqEY7WI1he7xHI9BaeXDoXXwyegnvn3483pr6GreUP4/TCs7BH0f4YF5iLMaE9MLl4Lxw7+jSsnXwNvjTyFMwq3htVgQb8f/bOA07K6ur/Y6XDwrJt+syW2aUtvQhS1NiS2Fs06qsxxiT2jsausYKKAmLBDizVgqJRBOwoYE1iYkyMb9obTaLGAlJ+///3Gc5yGWapCy5w+XzO597nlnPPPfc8M8v9zn2eqnhf9Us0LuQFvNkNbDd3brolP2C2h7HMvzZXu7aUcmLawC4nXVknYprySCQS3ANcW3lD8d4Uyg3uWmrzMdtJDfQCfg30mj9I8Yml5jefbv6NLu9j72MfAz4GfAz4GPAx4GPAx4CPge0lBjzkbdwNrXz7PL7M+9jHgI8BHwM+BnwMbBsx4CHvpkHeXODr7oNviT1wG8+4kJtyj/p38jbefbrRkBfablKVyagyUy0e2Txh0mTdO+Vx3TJ1rva5dJIKT3tazc54VQWnz9Exjy7VkFveVuKCp9X+4pdVcM17Cp27SKHTX1HrU5/VMXf/RndMf1ETJk3VmHVA3ut5VPNKAfTeOHKUTj3j7MCGisqMkMpAGnbW5oK8ARiLx1Vb2llPnTNVI/fLnuTNPq65h2LJWqXLe6sqZid5x+ofgz6SapdItV9I3T+Ten6q1yvn6YyiszWkZH91je62xkneVLKnkqkegSRSPQLYy8neztGB2qP0QN3af4w+GPKu3qmdr8tLr9D+HQ5X55LB6hwdoj1KD9YvBv9S53a+SPu1OUC9ooNUHu+uykRvDUgO05gf3Kw7fniTuhRXK+68kzeeTCuWSCoeX/X+03yQD1AIaLP3otpNbDd3brq9/Kd+c80z1592zXicWjX/c3IX4GknXO2RxgZDbS035EcN1qeppDYXNyVPPJpw7xObwGx7R6+tDb4y/1lqdT71G5A+BnwM+BjwMeBjwMeAjwEfAz4GfAxsbAx4yNvw/ozfkPe+8THgY8DHgI8BHwM+BtwY8JC38SCvney1ve586cb+fdtQPxvDuISbss4e8jbe/b7JkJcFyVRXq6KySjWdumj0mDv08JQZunvKTF09Ya72vX6ukmfMVOLUR/Q/Mz5X9ytfVunw57XjxW8odMX7Cl3ye4XOX6jSC57Tzya9p7GPvKCHJk/TaCDviFGB3HDzbcoVA7ykwWneEbfq2ONOVKams8orcFCNqv4/dK76Fk7yGuzqVtpZs+oh72BVpHoHQDae7F4PefsFj2vOA3l7farXKp/X6UXnanBwAnegypO9Aln1qOZVkNdgbzLVU1Xx/upetocu7H653tt9kT7s/bbGxcboB22OV5/wd9QrsqdOSp+qEUNH6Yepk7R7yb7qEu+nVKJrAJIHJIdozA9Gesi7FT2y2T40c1P78CwpKQlO5hrkdFMAqAFRi91tLbU5GuwF8CL4gTL8wxcS/iLN9WNDX1a+3G/w+RjwMeBjwMeAjwEfAz4GfAz4GPAxsL4x4CFv421muZvAPu/96mPAx4CPAR8DPga2vRjwkLfxIa+xAtLNvf9t+t0xLc/96iFv492zjQJ5AamVlVWBXHnlVZpQN0X3Tpyse6fP0pipc3XbjNd04bhZunrKQp374Hz1uniGmg1/UaFLf6PQ5e+rzWULdMi4l3XjY/N19yNP64HJ03T7uPG6fsRtgdxw8+1aXW7T9Tcj2dO8QN7rbrxZ3/3+wUqmK4JTvN825I0l4upe1lVPnzNNt+x7rfpHd1dlKvsO3Xiyp1LlfVQZ66e+kb118+55Htfc8z+aX/W8Tis6VwOL91dNbKCSqV55BNDrCu/q7auK8G46JnWK5vd9Qf8Y8Ac9UfmIft78VA0s3FtDw/tpTN/bdEuXEdqn6BDVRoeqKtE7C3mTteqXGKTRR90UQN6uJTX+JO9WAHvtQ9NNOcHLKVUAJjCTRzMj5DcE4m5rANiAL34A9OITvljwCf5ig8b1I/n13bTx7fwGn48BHwM+BnwM+BjwMeBjwMeAjwEfAw3FgIe8jbeZ5TfzvS99DPgY8DHgY8DHwLYdAx7ybl7Ia8DV9sEb+vt1Y8tNr43jpty7HvI23v3bSJA3a1CnTp109tlna1JdnSZOmaIJU6Zo0uSpmjT1UT049UmNqwP6PqefjJ2l6AWPqOCyl9TqgudUdckTuvqxBbpzxlO6f/pjASAec+d9unHk7VnIO/J23eDKzbevAXmvv+kWDRo8rP5xzd8m5E0ks48y7hnupmfOnq5R+16nAbEhqkz3UTrdR4lUL6XL+9Q/rnnUYCDvH6Tu/5V6/Ffq+blWrIS8nOQdVLy/qmMDg3fuxlO9gv75gW8WAqeSfZRODND+0R9oVp+Z+vNu72lht5d1Y7vrdWD7I3R08nhN2f0hXVo8XEOLvxuc/C1P9lQ6WauKVK36JnfT7Y0IeYFpdhPbzZ2bbuyHhe+3agMl16fAXcAlj2Tmg5N0Y4DtxvTZEIj8bbZlbgZ7efw8PsKeXF/6OFsVZ94X3hc+BnwM+BjwMeBjwMeAjwEfAz4GNi4GPORtvM0sv7HvfeljwMeAjwEfAz4Gtu0Y8JDXQ15/j6/fPb7JkBcw4jr7pJNOCiDvhEkTNWFyXXCqt27ao7pvwlQ9MPkR3Vc3XaOnPaPDrp2kcx/9rS6culDXz3hFd894Vg9Pf1x10x/XgxOnaMy48bphxG0B6L3pljEacetYkQawNw/k5SRvVXVnVWZqnPfxZk8Yu/a5eT4oampq1KVLF9XW1or3kEaj0TXE3k9Kur5AKplIqFe4m2afPV23fOda9Y/toYp0fyXTvZVM91J5eR/VRPvpO+UH6fZBo/WvYR9K3T7Lgt7aT6Ue/9HCyud1dsdzNaQoC3ljqV4B6AUSrw3yJpO9lE711cDS/XRT5Qi9M2Sh/tz3d5peNFk/a3m6ru51ncbVjtZP256sQaV7Bo9oTgXv9q1VOl2rnvF+uu3IGzTu2JHqVtpJiXhSsXhSUd7FuxHv5PWQd+M2ADZk4wQoaS9Tp5/BS06pco+6cWvQdmPi2tWzNeXdubr3Mb4wXxGnQF6D4by/GL/yAwVS/MrpaGRD1sa33fzx733sfexjwMeAjwEfAz4GfAz4GPAxsDXEgIe867dR5e7b+Lz3mY8BHwM+BnwM+BjYPmPAQ97GhbzGDiy1Q3mW2qGnxvqb2vSZfjflnvYneRvvvt5kyOt+yAKTDjjgAE2cNEkTJiN1enjSZE2om6qJU6Zr4pRpmjRlsqY9+SvVzXtTT775kZ545W29+vbvNO+l1/TCS/M166lnNbFuusbeMV7X3zRK1954a73w+OaGIO9lV16jykynesj7bcgW3K8AACAASURBVJ7kBfDGolF1j3TWzOF1uv6AK9U7OVjlFX2UrOihRHk3pVLdVBmp1YDYYP1yj2v0+r7z9Peh7+lfg/+gL3b7SEt7/kOLUnN1bsFZGla4X/C45jVO8SZ7CaC7mhgATvZS78ge+mnsNM3dc7b+0u8DLYy/rHtj9+rBQQ/rl9XX6KjCo9Q7zLt+a5VAUt2VSndXj3h/jfKQt0mDPE7pAhv5sOSD2SAkP1IAUgJ3SQGXyNYEZLe0rQZ688FebAH22pebfTnZtU/9ZqKPAR8DPgZ8DPgY8DHgY8DHgI8BHwPrGwMe8jbeZpa7F+Xz3q8+BnwM+BjwMeBjYNuLAQ95Ny/kzQd7be/b0vX9GzdfO9Phwl3Lc796yNt492yjQl4WZ9iwYXp44kQ9WDc5EPJA3yeeekZzXnhJr7z2ml574y298tZ7mvf6O5r/xq+14M13tWDR21r0xjuBvPzKAk2bMVN3j39Yt95+Z3CK107ycpr3pltG64abbxPv4kVuvHmUTjvz3ADyVlVnQe+3DXkBvVWxCv1u7m/02zm/0fwX39DcF+fruRde0ex5L2r2nOc197kXNPepuVr05Ov6cMb7+uShv+qLMR9r4X5z9Gmf9/W7zCu6rPhC7dV+X3WODgwe05zilO5KIZ8rBnwp7xLZTfuUHKTxA+/Vn3f7vf7V/S/6be+3NKPHNJ0c/okGl+ylLrG+Kk/2UCLRPXi3bzrdSz1iA3TrEdmTvLXhLv4kbxN/Jy8fmEBfTqjayXo7jWoAc0uD061tPPOTpYBxQLkLy3lfL19++b60fJnf2PMx4GPAx4CPAR8DPgZ8DPgY8DHgY2BdMeAhb+NtZvnNfO9LHwM+BnwM+BjwMbBtx4CHvFsG8hrsdVNgLMxhXX/brq3eQ94td382OuTt3LmzJtZN1sSp0/XIzCc0d+5cvTZ/vt58+10teusdzX99gRYuekOL3nhbCxa+qUWL3tIbb7ythYveCgDvG2+8o1deXaCnnn5OdVMe1YS6GXpo0jSNvet+3X7HPRpx6xhdPyILdoG7Jief8nMH8larqgrJrPYo6dwPfj4oeI8wj2vmlwNAssZ4XHMimVQikVQyntSiVxdp2eIVWi5psaQvVkifLZc+XSH9e5n0+Qrpi6XSiqWSPpd+P+kdzTp4ij4b+oE+7fuBHkiN0Qntj9eg4n3UJTpIXaIDVBPvq4pE7wD2ppI95UrwGOcA/vZUJtpX/SN76qo+1+l3A9/VZ33+oT/2/o3ujo3TgcWHq1t0gDJx9PRUMoGeXipP9VbP6G4aFUDeEaoNd86BvCnFErxzOPve4YZgHr4ElJWXlwep/UrDbu7cdG0fCL5uzc2Sdu3aBY8RBjxy0hQ4ia8R8vjfgGVDa+TL42uccDaf4T8EHwHMTcLhsAe9TfxHD/7zYs3PC+8T7xMfAz4GfAz4GPAx4GPAx0DTiAEPebfcZlfu/o+/9r73MeBjwMeAjwEfA1tXDHjI++1C3k0FvcZ/jAu5KfeiP8nbePfjRkPehj4UgaaPPvqoFixcFMDc+fPna9GiRXp9wSItWPhGvSxa9KYWLnxDpFl5KwC9wN5XX1uomU/+SpMmz9DEyTM0aeojmjLj8SC9/+E63XP/wxp56+0aeettGnHLKN008lYdcPChwaOaKzMZIVVIVZWqMpV5pbo6Iz4oALyAacQAbyQSqc9bmUEfS+NxANCaEkvEFQ8gbyqAoy89/4KWL12m/371td7+4C864mdXaO8fXa1hJ9+kISffqmE/Hq39f3SDPvk8S4HfmPCKHj/8Yf1r6Pta1uf/9FG/NzWt5kGdXPxz7d3xIA0q3FO9SwcpE+uzEu72UDJ4n66lPZUMwG8PVSZ6q1tsoI5P/USvD5yvvw34k57v+qwuaj9cQ0v2V1Wir8oT2ZPBqWRvIasg7/Uad+xNqg3zTt6EorG4oolEIFnIuyYgc6EhfsoHed2b2T4o7IYn9ZsP2c0HfGGPYyaPr+wUKXnq8DFQlzg3uOuugc+vPUbXxz9AX+IYscdfU8ZnhPtuXh+7TWPTzH9++HXwMeBjwMeAjwEfAz4GfAz4GGjKMeAhb+NtZjW0J+XLvY99DPgY8DHgY8DHwLYRAx7yfnuQFw7hcpwN/fuavXITV4/luUc95G28+3SzQN7Ro0dr3rx5WrhwYSBA3oVA39Wg7pt64423HMibhb0LF72pV19boCdmPaO6KQDeGaqb9mgg5CdMma4JddM0ZfojmjBpsu68e7xuH3uH9vzOPqrMVAeAtzID3F3ppADyVqgq40qlDPISTABe4LQB3fWHvFHF444kYlod8ib04vPPa9nSpfpyyTf6ZIk07w9Ltd8Zd6v/T+5Sn588oH4nT9Cwk8bon19J+kZ6uW6ubtn/Os3uO1O/7b1Ab+/2suYN+5Ue/t5E3XzAaJ27+wU6oPowdYr1DyDv6oAX0NszkFSyh8qTPVUV76uDksdo5oAn9ObghRqdvF0/aHWc+oT3UjoAu9lHPidXQt6KVG/1Ck7yGuStUSIeV5RTzglAbzw7x/jaAZqHvJu2ucKHYC7kNajIo5kNoAN3ydsJVNL1gZe+zdrjN59/8K2d6MXv5DnZy5eTrdeGfuH59pt2n3j/ef/5GPAx4GPAx4CPAR8DPgZ8DGxNMeAhb+NtZvkNfO9LHwM+BnwM+BjwMbBtx4CHvN8+5DXYu6F/bxvgJTWw66bcux7yNt792+iQF2B62WWXafLkyZo6daoee+yx1YBvFvxmgS/Q1xVO+gJ5X57/uh5/4ilNmjw9gLwB2J2SzQN6A/A7dbrqpkzTpMlTNbFuijp17aZ0RZWqqgG9Gw55a2pqGhXyxuPJ4CTvC/PmaemyZfpiyVL9c4k05w/Lte8Z96jvSePU68f3qM9J92rIj27RP76Wln6zXLOmPK0Duh6so8PH6ZTw6Tqx7Gf6acUZOrvHeTp/wIU6o9/Z+n7l4eoUG6Dg0cwroa7BXSsD8iZ5z26ip/oV76Vbuo/SlMFT9ZPo6RpS+D11jQ0OTu7yiObse3yzJ3krU73VO7qbbjuSd/JyktdD3g39ENvU9nz48QFqH4aWB+4CFt13xRrUtTQfnPRlGw50G/IZfrZTvawFsJcfNNhaGYjf1Bjw/f1mpY8BHwM+BnwM+BjwMeBjwMeAj4FtLwY85G28zSy/se996WPAx0BTiIHKysq1viqwKdi4uW3wPvD34uaKMQ95v13IC5PwkHfruL8bBfLaDUfKTQ2F32uvvXTaaafprrvuUl1dXQB9Ab68o/fVV+drwYKFWsAjnFcKsJdHOi964616yDuxbloAdA3sGuydOGV6AHbH3/eAbrhppK646holUuUB5M3U1Gww5OUUL7Y35kne7DtrE3p+3vP6Ztlyffr1N1rwx0/0vVNv1qAfj1bfH41V7xPvUJ8T79Dg/7kugLxfLV6iaVMfV02yh7qFB6h3ZA/1KB2mXsXDtHvHvbRH0d7as2Q/9SrcXdXx/lk4m+q1EvauTFe+jzc4yVveW/FkD3UpG6QT0qfowl6Xaq/YwaopGahMYrcA8gaAN9VLqTSPf+4tIG+f2ECNPurG1SAvJ5T9Sd7Nv8ng/rrFwCFwl9Pl/NFkJ0jt9C6AESDpIW/jgdxcwOv6Fn8jubCX9bBHOLNu7oacB7+b/75x/e3z3t8+BnwM+BjwMeBjwMeAjwEfA001Bjzk3To2yjbXZrXX69ffx8C2FwPs1dl++Pa6vi7k3d59sb3GwOaaN/GE9OjRo/5VhgYefbrlADAncDf0b2vjGi7r8Cd5N993YKNAXruR3Q9ywClAirR///4666yzNG7cOE2cOFETJ0zUzJlPas6ceQHktffzAnntJO+sp2cHJ3kBusHJ3WmPavL0x3TXvQ/qpltu0xVX/1KXXn6lzj3/Qh16+JGqqu6k8qpMcJK3oor38K50WoYvW67XfFxzbW1t8E5eTvEyByCNK0Bfgzq54Cf7Pl7nUc3BY5uzwI22vLeW99jOmTNHS5dLny+Vzrx6jIb+6AYNOGmM+p0wRgNOHKvdThylocdfof/7UvpqyRJNnvqoKsq7qDzRVRXx7qqM9wrev9sl0k9dI/3VOdJf1dF+qkhw8nblKVwDvQHgzT5+OZXsqUSCxzf3UmWsr3qGh6l3ZE91ig9URaqvylN9A6ibSPRUKt07gLzJRC9VJHrVQ947jx+hbmXVweOas4+hTiieXCn+cc0b/OGW78PQ/cADBiJ84FFOnhjk5C6nRgGJ5A3wrhmTmw90+rHy+xbYy9rYCWuugfLFxcX1j6LIt+6+zG88+hjwMeBjwMeAjwEfAz4GfAz4GNj+YsBD3s23uWX7Uj71PvYx4GOgMWMAgOlKrm4XcLI35LZ163L7bS3X65oPLMDmydM9DcptLfPzdjbtzwuLJw95txzQzQfPPeRt2vcJn2ONCnntg9GFveSBqHZTDhs2TD/72c80ZswdevDBhzVxQp0eeeQxPffcXL32+sIA8s5/faFmPvm0Jk97VEDeO+65TzffNlZXXnuDLrvqWp134S90+FFHq//AQarp3DUAvEBe3smb73HN+SBvp041wYljO8ULkOb9mnaa19LGgLzfLJf+8u8vtd/x56jfcdeq+9EjNOj4kbr72b/pnmc/1N7HXaCPv1weQN66qdOVqqhRIt1JiVQXJVK1SqWy79cFwJYneym9UoC89aB3NcDbS4lUVoC8wQndZL8A7ibTvYSkU5zc7aNEYuUp3nRfJRO9A3jMSd4xP7hJAeQtXQV5YwZ4ST3k3WTIa4CXD0qALh+i7dq1C+AgoBAf5z6a2T1Vuq418PX5wWxj+8U91ct68VnC50dpaekmx4jf+Nv+Nv78mvs19zHgY8DHgI8BHwM+BnwMbLsx4CFv098ks30tn/q18jHgY4AYMMjZUDxQ7+6Du30MfjbUd2srd+djfmHuVm4p8zIOsLXN0dvbtO57iyMPeT3k9ffm2u/NzQJ5c50O9AB+UJ79wM+osjKjPfbYS6eeerpGjLhZDz00QePH36cp06bryaeeCU7xjr1zfHBqF7B77vBf6Iijj9OA3YepqqaLyquqg5O7mZrOq0Heykxmjcc154O8tbXdglO8ZiugpvEgLxA0oVgsoeeem6Mly6X3//4f7XnMGep73PXqc9wIPfDMH/TXrxXIlF+9ok+++FpfLlmiuslTVV7RSel0rVLpXkqkeyuZ7qPyVB9VJvuoIpWVdLK3EABuriRSvRVP9wmEvgDdikRPVSR7ZuFuuq/SqX5KJfsqwYlgrsv7K5mgXR/1je+usceMzD6uubRayeBkclxA3nrQ6yHvJgO83McVAHk5AUoscs+YcHLXTu96yLtlwO26QDDr4K4FUJc+9llHyi84DfbaKW2/Ybftbtj5tfVr62PAx4CPAR8DPgZ8DPgY8DGwrhjwkHftG1S2P7OhqQsWGurbWG0a0r+x5etj18bq3pr6eT9s+r2xKT5cn760ySdbU5xtjK25czboxIEmxE6vurrdPm55Y+QZvyE9jNtQXWOUu/rzzXFttjXG+F7Hpn9ObG0+tPvNQ14Pebe22N3S9m4RyGtffDY5btAuXbqqOlMTSOfOXTVkyFD95JSf6tZRt+mhCRN19z336aprrtMPjz9R/QYODsBuRXVnlWc6qSLDqV3evVtdL1XVNULyQ94qVWV4ZPMq4cOBU7wGnzmxa5DXTu+66ZrQh0czN/S4ZiBvciXkfU6c5P346+U65uxr1O+YK3Xoeffo74ulT76QPvlymf7z9TJ9/Nnn+u9XX2nipDqVp6pVleipTLyvKhNZqY73UQ0S66uaeF9xnU8y8T6qWglrAbaVsd7KxHqpJtpD1ZHuqor2VlWM/v0CqYr1UXWyn6pTA4Jy9O8WHaxxR4/UncfepNqVkJfHNGcBb1zx5LpBG74DTAK7SN1nrrt5O81q6br+U7y119s8cwEv8wII2qNdSA0iGlC0dM1YXPd6+D6b30esj8F41s9O9VLuIa/f8NvaP7u8/T6GfQz4GPAx4GPAx4CPAR8Dmx4D2zrk3dgNfhcc2L7RhqSb2p+xDFiQb2geueW51xtis42zqbZvjA30ccXsdsssb3UbktJ3Q9rTFj/Qb2P9sTFjmo2bMlfTsT5pro251+ujw9rks3ljfYfO3L5cm9iYdp2bWn1TTjfF17nz7d27t1zp2bNnAHrZA0Jy26/LL7RfVxu3nj1299qd24bqQo/b39WbL5+rn2vs6d69u/h+69u3b+Ab23PPp8OXbX+gdlPW3D7rPOT1kHdT4mh76LtZIK/7BZGbz15nVMX7cxuS4DQuwLZGFXkkKK/kj5CsVGUyWl3W/AOlpib7x2J1dSZ4TDNfQHwR2ZewC3mBbbniAl/ya38nbxbyouOpWTO1ZOk3+uybFZq96APtddwvdPIld+qTr6TPv1wcyGdffKnPv/xSX3z1lR5+eKJ6dOqtfuUDNTA1VANTQwIZlBqsrAzRoBTC9e6ODNLA1JpCm8HpIRqyUganh2pwethKGard00O0e8VQ7VY+VIMqhmlw+VDtl/yO7j/uNo374Q3qHe+meCym7Dt540okI4Fk598wOPOQd9UGgIFdF26T5+Qu8I/3QNsfggbFgYUGDD3cbTjOmhK8tnWy1NYQ4GvQnsdwsznG+ltc+M2yVfeK94X3hY8BHwM+BnwM+BjwMeBjwMfAthwD2xrkZYPfFTbR2GexTVlLKXOF//fahpvl+T8x7UmtztKf//znYoM3H2Cw8fk/V9euXbXvvvvqe9/7nvbZZx8NHjy4Xh/t+vfvrx//+Mdr6LdxTD92nHDCCUE7yrg2O5nHj370owBmUG59LaX+sMMO0/e///2gztrkO+1Hne0F0J88/ZkLdSaUYQcHFQBKe+21lw499FAddNBBQRvrS0q7XDHbvvvd79bbZWXrk/bq1Uvf+c53AtvQva4+2M38a2tr69tSdvTRR4tXuJFnTuZTrtFLmk835ficutzxqTPp0qVLkP/pT38apKbT/Orqpow1IaUcHdiDj91xTj311MBW6ocOHVpvB/ZT5upcV572AwcODPTZmIyHmL7TTjstWH+rpw/zICbcOKAcOeOMMwKohg7mQllDdpjvjj/++NXuJ8qtDn30t7L1SbmvuF/MJvrYnMzPuTpPOumk4H5158l9i7j223zQiS6EvKvPLbf2pNjg6jK7WGfyCD51/cr9tcceewT31gEHHLDaONbnscce06OPPqpHHnlEM2bMEPcV42GHraONTYzRz+ymnYlrG3n6EsO0p43ZldsO3b/85S+De4y2Vk8518TppZdeGvQ3e2hjdtx9993B54j1I2U8S1mDsWPH1l9buekyu9z795JLLhF+ccW1zR3L5z3k3ZAYsPvFQ14PeTckbrbHtpsF8m6yIwPIyyndLOhdM+WPnNX/6MgdM/fLxK75ggXw8uXHBwVfSoAigCwneQFuuYCX6w2FvDyqOZlI6umnntDXX3+pJZI+WybNeeMjXT3qQX2xZIUWL168SpYs0eIl32jChEm6+uJrNOqCUbrjvLErZYzuOG/0SiHvXlN+u+4477Z6GXfebbqzXm7XXeePWSljddf5q8ud54/RuAvGaOwFYwO588Kxuv+8O/XoOQ/plqOvVpeyTAB5g8dPJ7KQN54Ir4TcwOz8AM5D3lWbMwbz3JSNC+INIEgMmnBtPjVY6JZZnU/zx9236Zfc9eI6F/QauGf9iQcPe1fdJ9vyZp6fm19nHwM+BnwM+BjwMeBjwMeAjwFiYFuDvOzD2F6L7clwkgsA6QrQ05UjjjgiqAeoAAzoa/szdm36SM8888wAGDIWsIvUoIQLT4C6Rx11VABp9ttvv2BM9NHHAMwpp5wSAC7KrczG4hq91AEVgTy2d2RtGAOIaOWAZbOFFNsOP/zwYGz6UEafc845J5Dzzz8/AHPMydqbbnQSI/gOHwHOEMajPQDu5JNPDvQDswGG7HHRn76mJze1cYDCBx54YIPtcvsxF/bPfvazn+mYY46p9z3luW3da/yHncAiABjzYVx0MBf8anWkxMHadKKPudOGvDsWc7Nr6rk+66yz6tcE+4888kgdcsghgU/xq11Thj76IMQu8BHBftJzzz1XJ554Yn0Z68APBShD1ma3a5fZDvz+4Q9/WP+IX2w47rjjAgAOBCdOgLC0oZw8fU1Mp6WsjcFq9pVsLm5KW67RgT9yITg+IPaJIXxnPrExqbM8uixv6W677RbYzRjuPWX12OX240cDrCftbSzyxEVufFobdGEf9yXrwn1ha0CZm+fayuhPX9Nj9xefR/gXPaw1cB2gz9qyJvyoYcCAAavZbfMB7AJ5H3/88UAHupkfnz3Tpk2rrwN40ob25C3FX6wZfrH7Fh3Ma/jw4brooot0wQUXBKnd3+g3wWcjR44M/GX12GY+puyhhx7SscceG6yHOw6fP+PGjQva2mcp/WwdSPmcqKurC3yGfeibOnVqALUNbpPyYxMbk89BwLD5hvmaTWa3T1etoffF+vuCewPxkNdDXn/frP2+2W4gLx8IfDHxS0K+fAgMvuiALgZ1AbybDnmzp3hjsaTisaRmPTFLTz/1lGY+OUvTHpmpyTOeVN30mcG7h6dMmaLJkycHMnHSpOBL+J57xuuEo07QaYecqnMPPMuRM3XugYiVnalzD8ov5x14hpDzDzxd5x94hi446Mx6ufDgs5WVc3TBQWfr/IPP1LnIoecEcv4hZ2v4wefo4u+fq+MHHKWKEh47zcnlpOLxlBIJUgAb8zRZE7h5yJvdxDCwa6d4+Y89pznxD3/8IvxhZYDw24SUfuw143hDfJK7htn7Jl7/2G0+a+w/Bejls4aT3MSG3/Tzm34+BnwM+BjwMeBjwMeAjwEfAz4Gtv0Y2F4gLyDLFeCNARwgjsFG9mf4P5ILgYBwAC5XABMAQiAKIMwEWOdCkiFDhgTjACrwNe2BiLSnPykwB5iCfvqTsnlsG8n0RSf7Ru4pTvu/HH133333YE+JPuwtWWrzMchrAIb2nEZGr+lxYZptXFK/9957B7YCgjghyWNh0csJPwMxjJcL3qhz600nbW1O+B3gajZYam0tRTf98AtAkLUENuIva7O2lJOQQDTmAmxn7YG9rAU2kFo8kOaDvOZTxsGPQC/spTxXzBbzr/mWcqAmYJbTjcQHawEcR1gTdLm+w8/4G2H+9CWPHuYDEOSa+ABU4isbv6HU4oBxaIM/gZBco5f5MxaCTtacPOtPavPGp6wBcUxsYwvtydu94d43lmdM7GRuwFB8Thn+Qge2kBLbQG1+CGHX1BkkBH6effbZawj+Zn1IqSdFD/ca/S2e2BPB3+gnRmjj9gFw0x+fu4J/6IfNzJfT4Pa4ZPwDzCSmgPT4EwEkM74bK+79RRxwj+XeXxYLjGX3h5syFwO8999/fxCb5ktiAn3A4SuuuEJ8bmGH2cp6sg+MTabT8qSczsXvxAdrDTDGHncOlr/pppsCGG16XHvpw32HfdaeFL8Ab+1+oy/zYX0RG4t79MEHHwyuiV38ZnbThrE4xcw9xTU60IU/DQYb5KWc9l68DzY2BiyGudfZP+WpmF62vA82Zu/amIgdcjI2Yikxwecm302sM9f+M2PjPyu2acjrBgZBwxcaqX1xAVoM8K4rBdi40tDjmhPxhBIr38cbLouosqJK0XA0ONXLyV5XgEIGkRifL1XATzqSVpeSzupRVBtIz5LuyhWrI82t47pXca16F3cLpE9JrVaX7updXBu06VlSqx4ltepWXKvuwTgry4u6qUekq8qjqZU2ppSIp5VMpJWIU4YAfFfNweZCiq/4A445kdoNnJu6Nzz5bWFjI3dOzNnKXMBrvsE/biy4fvT5TQOv35b/7LOC8Vlb7mvKDATzxQXc5zQ3oNfiflu5B2w+Pt32Nyr9Gvs19jHgY8DHgI8BHwM+BnwMrH8MNCXIaxtqG7vxav3cfRfbjLW6fGlue9oAEUjpD/QBULgC2AF8AHIMFgKDOcWIPtMJxKMe6ABYAYYBWfA7gIU8AIZrVwAZ/P+c8QFjdpLSIJWd+OOUH2WAMoAYqW1OohegRbmBMPLoAyjl2so8sdP1Edc8ZhpIzN4VNlHPHpYrtnbWnxQfAgCxNZ8wJ6A1vrQTwpYyhvmQPLqYDzYD9qwOQAz0dW0mb/ZYOaAKf3ONTYyDTdiA2LikjEV/xnD1uHnaAADRx/+jqXOFcnxsgJG2zJO1Yh+QctNnwJXxAImUs4b4mjLiB/uZO3OlLym+Q9BNHQKkZF1s3g2l6LV2rBVjASRpT0wSV8QKgn7GtzLinnbYSWxwgpsUYXyusRkh74rdQ4yPDuaJ3YyPT7GB8e3eIE9cUs79Y/CZvthterh2BWCOv6l329gaWTnXnGoHrls7ytDFNfGV70cItLEYB5wynt0PlBNjnCqljLkh9MEmylhzGwe/8dnBmJQhtLG8pTY/s93sZbzHHntMM2fODOywcuISPdb+sssuC07bWj02AUEnTpwYtHH9aTZcc801AcCmD7oAqdTdc889q8n48eMDAPzwww8H5cwfe+kzevRo3XbbbYHQbtSoUfVlgFt03n777UE9ddaPtb7rrruCw0cPPPBAALLvu+8+IfyoAchrPiHlhDI+Zx6MSxm2Mj5jUG++cPv5/Or3jvfHuv1h96SHvFse7LowHbaxoX/vGwshzeVBXBP/HvKu+x5Y38+JrRbyBu/gbeCXVUzevkj5MCBg+FKyP76pA64gpaWl9fDWBb0GaSxdExZxujW6miTiMSWAOgHkDCsWC6+8TigeiysZTwYCCAb2GvDJBXy0S8cqVBGt2kipVGW0Yr2kIlqhilil0tFKlcczqojSN9u/PArQjSueiAenkpOxtBBgbxb0esib7wPO/RCzPO2INYAufwTxB54/wbt1Atw1Pws2bB7c76y9rT/6lV0GcQAAIABJREFUiouL638IkC+mfNn6b5x5X3lf+RjwMeBjwMeAjwEfAz4GfAw01RhoSpCXfRP2SywF8CBWlruvwnWu2L6LldtmLNf8nze33trlpjYmKeAqtx7wxAYv9fx/mnpOkQHdgFU2DqcDDcAByYAf1NHGAAw60GWA0WCbtQMWAi9c4aQgAI4yHuPKiU5SxrN9JsYAJrH3hF2crGQcIKMLeQ3uMKfceWIbEMrgMnARsTmRWhmnIU3wBX2BSNjmCjYC/ujHmMzFnRt5swMd+AEwzRyAaZQxL+wmBf4CRzkZzZxtPdDBNWMbXOMa8A1ExM/4w07BAhFZa1s7UhsfCGjgiHL29AyoUm7trC/XjE+KML6BPoO8Nkc3xc+0t9hgfqwb8+b/68wVP1BPHWsOgOWaudmcXZ1u3uzJTd026DJ9xBK+Nb3M222LHvxNe05bEpPmf1LsBpK647n98asBUk7zAt6t3voQI2YPKfXotr0s2uEL6vA/fiC+8bnpotwV+yxgLWiH36kn1vkhhkF/g9v2gwDi0AAm7dEPBGddzBeMTzvi3OZAO/L40uy0Mu4F9/6yU8uM3ZAwP/MFcwHyGsREr9lG3sa5+OKLNWvWrOD+tzJO91JOe9NHHb7FXiAv9lGHAEupZ77cQ4j9OAWYim+4dj+DuL/Nn5YCbRmba/uRBT9QwffEGOvJOMQGnyHcawBhrhmbOk7okiLYjw/wOdc2F1LiD7upt/Y+XfO70/tk/X1i9zXfH4BBFzz6/JYDvx7yrn/Mflv39xaCvBlVVbmyDsesxzt5cyGv60A+ALgm5cuODwL7AwzAArg1yEtqIHdDIG8W6OaHvEnAaCyclQQwmDGzJ3w55YusDfIG7enDieB8kkgqhuSrC8oafoxyLqCKJeKKJROKJBKKJlOBzuxp5Cysjgf2M5+EkrGUUrFUkDIH/7jm/JsnBnbtlyqknOAlvvjj2OCeQf7cNfHXGwZNtzZ/se78EU8ckHLNDwDYiLLYaaqbUt6u/Pe894v3i48BHwM+BnwM+BjwMeBjwMfA+sRAU4O8bMqzqQ94cYVyE4NI7p5Lbt42Ydl3oZ/tyeS2a+ja2pNycjK3HbAGQES5AQnsNliEjYAHyoAM2AGc4JGn+Bw4SjlCO049ArkAjZzqM7vRb3NxU07WApLcesbEFlLXfuYPKMM28kAhYAmQlbFNXMhLmekGfDEWKfAW4fG0axPAKToYDz3kbQ+MMnwArATq4AN3bm4ef+FrO/WLzfQDDpIixAlgzNoAe21sfiRAf8TGpx0wCPs5xQkwwx/AZXS5NmM7wnjWH934GX9xUtt8gg50md/ceXDa09bFIC/jINaOPOPbtUFhwClrRx0pcyElLm1upFafL15tHpYyBvuSBtrpj0+YI7GJLhsHiMl4+AAhDzi3GMdu+rEWBvdsDugkdvCZK/QBXjMGNqATob/5BFvpQxvAH+WUMRZ5xucaW3g0M+1YE+aPYDdwkHKbD1DR1hEbsRk4bbFvp/NZX2yhzu5fGwt7zTZSWwfsJ28pefQyvgl2MD7zoi82cF8BkS0m7b6yuMqXsnY2f3QBMO1ELnpzBX/dfPPNwWlb5kM9dtg7eZ988smgDj3EGzqxjcc180MC00c9eerob74kRT+n7MlTTzv02Oej6SDlZC/3qemiPW0R9qXQQZ565glA5lHRPDnB4iD3JC+24UP60NdsoD19zXbqvXgfbEoMEFuIh7xbDujmg+ce8jb9+3gLQl6+dBBg7zocswGQN1cXXygIX1J8uSFcG9wFpvDoVJONgbzZ07qc2o0GsupEL2XA3IQSUcBoTEBUAGo4nlA0eJ/t+kBeIJeBWmCqK1ZuqVu3NvAKbHbFQFpM8WRc4URc0STwGPvjSvG45eBkcnacWHASOaF0LKFUbGWZ87jpXNAGOAdg8YcyKR8G+cSglqXr8x/jpt7G5uKmxBk+wh8Gd0lz/eavLS63vnRD1pW23BcIf1Rzv/BDAIuZph7j3j6/ieljwMeAjwEfAz4GfAz4GPAx4GNgw2OgqUBe9kvYS2G/BCACIAGIIOQBoC48yN13yb2202AGeAy8kAJ/gC9rE9vEZe/GYI3bfvjw4fXgxi2nLbbw/2xAAxCRd/6iD8jLSTdgINCPdkAmrrGTuQN5OdFmAM3soK3lSXMhr/nP9p9IDZIAafAjgAuwQh1jAqtoY2K2M5b1ZSxO8hmIpZz+ri358mYvqQk+QQDA2INvgEL4x9q4KeMAZJmb2UO9O561t3r6AF4ZhzwnIYkd1oi26MIflOUTIJLpMt2k+SAvAJH1I6YsVkk5IezaSJ71JcUmg7zotbGoI48u60s8UEYfUtacNaSeeVDOXLDN+jA2kA7dlLlzcPPWHh0IsJ11Nt2kQE7rY3ZyTd4VYpVYIkbQZeOSGuQl7wr2A9Wxn3hg3gaOgZrmV4AzdfiPNeSak9iMb2PRjx9G4C/sIyUGaM+YXDMe8QZMJU85a43NnEZlLelLPOIH9DMvIK/dv5QBZPG3+YGU+4Z7G71cI/iTuWGjfRaQJz7MTtphBzoZl2vGpJ3paSg1/9OfNpziHTlyZIP90AsoZXx7Ly7joIf+pDwemROvfAaZ3uuvvz4AwTwKGkgKDKY9nx88epl+pofx8ZfZRjvztemjDHEhr5VZP3f+9OeHGsyPR0RPnjw5+IEIfeydvNYf+wzyosPGRC9tqafMyq2fT1d9RntfrJ8vLI485PWQ198za79nNh7yZqpUtVIqqjIqz3QLpDJTU1+edX5GmapqZapqVF1VrU5VFaqpKlemqlKcxk1X8CXZSZ0qq9SpqlKVmWqVZ2pUkakO8qQVmRqlqmqC8qpMpTJVFcoEX1aZoA12dMmk1DWTUpdO2T8q+APJHm0COHNP7pI3yGvvygSyrM9J3izg5dHLsUCyJ3rJR1eWAXgTSq4UYC2QtyxIsxAVexLJZCD5oB5jcBo4ufL9vut6/20WCBvszULaNfWuBLyJqOJIAHwBaYDoqMLJmMKppCKJtGK8ezcAvfHsXHi8dKxE6XiJ0rFIAH854RuzU76cXF4pwclgTgdvp5DXIB2pQW3yxJZBPXzjAe+qmLHY2Z5SA8LEBP8J4ZofoFj8+A2zDd8w8z7zPvMx4GPAx4CPAR8DPgZ8DPgYaOox0FQgL3s1BkkAOoATYCxCHlhHGzZX2bRf18aabcKS2oY/eUAPAMmAQr7UxiGlLzbkjodNQBH+72Q2GViyfuhmPGAieXwNqAMIAZXMNmAUj3KmDZAOiGV1nAwFXACMXAFW0YcyIBdgDGhGnjJ8iT7sx3dAMIAW8AmgtKGQ10AXe1pAOROuEfa7DKYxNuMyPnAJH5n/aMP6cmKSemwBDDFfE9ra/K0MfQi6Tb/bzsqtzmAZpyIpM+CHn/CRK0A299pAkdlMSsygB3u4tnlgE9fMxcT6me2kxBDzBIayxmaPtbXUhbzoAwgTM/iM1J0neebHjwJYA9YW/cwFfWar6c6Xmo2cqiVuaINefoSALQZbSRGDlNjG3PEDP1zAPvKUYTPwgxhBJ4/rJT5MrB1tWSdik/HRaeOb7fwA3ey2eq7J05d2rB822Fyot3vR2pFyL3KqmPnRhvGxifvR1oO4RLAf4SQ5fmdO+Jh3CnNq3Gwi5bMAUIw+Yh2xk+/op43NB/+586APOhmTdvjG7qmGUnQyB/qaXgAmjz9Gh4nV2TWAFB/cfffdwWcFdpgttAWg825c2ltfTvICva2McUwfj3m++uqrAx3oyYW8zMUec03qCu/V5R3BVs+POUyIBcZgfgj+vvLKK8X7flkL5kF9LuR99NFH80JedNDHQ95VsWFr6NON8wn3B+Ihr4e8/h5a+z20cZA3U6XKDEC2UhVVFYpX1Khjqq9KKwaoOJrKwr8AAGYfVcz7WxPxcqWicVVHS1RR1kGVKSBhUtFUFyWTndU5GlOnWFTRZKWKEhWKJNNKlVcEsDed6aRoVWdFyytVnipVJlWi8gSPvq1SorKTyivK1TPdXv0q2qu2pkJdunRVZWVVAB4BJ4hBXhfuWh4AB3hbmwCgVgFeg7CceM2ebi2PxVTFKdiyiJKRmNLRhCoSaaWYYzQanOIt4TRnkpOzSBb4RuPRwF8AU4OmANZ0DEkoGU9pFeTNQlnAbACJksDiiBLJaPCYZdplbcy+G3gVNLNTv7xfN6J4glOlrE1WH5C3NBFWcSKhgtK0OoYrVRqOKVwWUSycVEU8plTxzqqM7KpEpL2i0VJFE2FFE5HAZgOWAN6yZFYi9Mlzktcg1trSpv4f83z22XwM7JLa4w3I88cysmpNtm/I6f0QD+5hu0eIDT6PiC2LJTfNF3O+zG9i+hjwMeBjwMeAjwEfAz4GfAz4GNi6YuDbgrwuYGCTzKACeYARAjxBADBAE2vnQsO1bbAZwLA2jIFeoAplQCLaAPUAJ0AJ2lBOPXUAAmwwHZZSBuSlPfaQ2olcVwdQkTENlnGSFshn4JixgHR2epf1sJOY2AS44/Qm4BcgQp62jA8w4trKgL70BZZgA/YzFtfAKiAvNhvQNJ/aXO00o+s35g9YAdYxT+xAn9nM2AZnSNHBHOiHDQj6gVJAK05BAvWsziCv+dVNgYRAS5srKfCR1MrwI+KW8ehr5mBjo5MYwp+Mz/wBg7QzX1gZsWFr49rC+ll8UE6edXXb5OaxH78zJm3JUwYwxB585PbBXoO85j/swvfMjzpswxbTSQxwjZ+oY71Nr80f3xvYNDjIuPjIBEjKOPShDXpJ2RcwW/CfO2faMifGpj06aQvUtRixOsqIGWKYk6I2Pv4GLuITYpNrdBBDtHOFuXFt963ZhY/wJ7GHD7CRa1LihZRyyrifXJ+TdyEvuohxu6/wOT+SsHi3lLmbsDbAU+5/s5t5clLY3llLiu2u/xgbH3N/GUhlLMa3cSzlcwMfMgd7T7mNTwrA5HHJ5PELusnbZyXxziOLuQf5MQgndolh+6zDNiAp7bDJdPNOXtpzjU5O1KKfPVfKOBWMbcTRiBEj6k/y0pZ2t9xyS3CCmJO7AOQ777xT48aNC8ZiPOopp56TxlzfeOONgW30x15gLvH50EMPBTovv/zyIKU/Nth8ucZWuybFLuZIHT7CLi/eB5saA3Z/eMjrIe+mxtK23n8TIC8AtkLlVRUKl3dRz31O0v9+qey/5cukFcu1fMUKrViRLVqxXFqxTFr65b/Ut2eNIom4ihJV6pjsoXkvvKs9u/ZQTWF7TZo0UYcfd6zKYsDPuDi5m66uUXFlrXbb9yC99eu31a1zhSoAlbG4opW1OvHkU/T4vderb2JndakIq7KyQpFIOIC7DUFe99TuxkPelIqK4wqXJJQo6qhkUaHCRaWKlyWUKI0o3rFQ6ZI2ShS3VqSsRNFESoXhiMpiYaXCBUoUt1I0UiyAaJTTrwnAH2AXwBsLQC/vwQWSZ0/rApqzj4hOBoB3FeS107x2shjYuzpIW/lo4ADyRhzIGw/GjqSTKgjH1G/YQXpk1ksqKi5RKgHoTWiP3Qfp1WcfVEVpSLGSlkomAbxhheNAXmAVp4iz9q+CvHElPeQNQC+Qlz/2kNXXJHeN/PX25h+DvMQGn0Ns0rlw1/J+827r2rzz6+XXy8eAjwEfAz4GfAz4GPAx4GMgXwwAJdiwZDN8S242GVzKNybQABhi4I48J/PY8LfN1Xz91lbGeABF4Bg6gFe0B2hQDvwxH7i2AQqwg9NkrlAGVAViIcAZACuwy4WBQF47pQekAugAg+jP2Pgfveji/b3AIIO82IGt2Gk2ASwAYsAnxrVH7FJOW+x154duNqIZF7E5c6oUcX2Gn/l/oIEf6sgD7ADh6CUPFCPvCm25RgewzmynDJ2U4RvzM3Yia4O86DC9Npa9rxl9BqOIC5sHZWY/fawcOIY+fMY6EE8IcwHQkcf3CL61fpbmg7zoNLtyU/rhd0AfUI62zBcbgKV2TazQlnLsZmx02bXNAd+ZX9GDbmLHnSt9gXX0RaeNx3wRfENdPmFdAGToY0ygqMW7xTjXvPvWbEI/8I35YB/lCHOiDiH+7VHK1FFmPgWy04+Y4f7hvqcMOwG2/AgBu4CblmeONg/TZ2ORMjfmin/RS3/3fqQN8Wg+pz0xZWvJvQlYNTuJd05Lm82W2lz5HKEv7bCT8TiJyrwo456zOVCOTYxJf3Thb9rhe66By9hj+t0UmxirIcgLgKW96SePr9CLP3n0MnVcA28BqhY/QFbgKXXumJzUBbxTRh1w2NXPDwOAtJTlQl77gYDrb+xhLQG3kyZNqp+36WQM8tiFMF9ijrh44IEH6u0n/mfNmlXfDr0GeemHDosTqwPyUs4YXrwPNiUG7B4hDt0DVXawyqdbBv7i+3x/166tzPa0SemfK8QFf1PwvWafe/5zY+M/LzYS8lZmAW91hVKVlSqpqFXn/U7RnF9/qcpwlVJt2gWnWSPRuMKRmMrK4iouTapDaVRPv/ys4rUZ7Vgc1w4lndQ81k+zn39Pg8q76MDuXfWnt19QOlmggvatFImUKh0HgkbVOlmrUHFn3TXtWd1x7wSVFrZVtKxEhcla/eDEn+uR+29Sqk1IRe1C6ljUWh07tg/ecdmYkBcAZad5U/G4SkuTKk311Yuv/k5atlha/qXg2xdeeLVK2xXqqQl36fdz7lWXopASpe1UFE6pTbSzLrvql/rPb5/SkHRI0Y4tFYklAwAcC2Au7+zlpHBk5SOguQb08hhmew9wRMlkTIlkIgCsyURy5eOdqc8Kp5JXB2Y8ohlxQSLgN6VovFzFsZQ6RMo1aK/DNXPW8+rYbleFi1qqfWGJBu2+u1741YOKtQ8pUdRMsbKOKg2HVRzJnlAOHj1t4/Ju30RCUd7hm0oHf9ABsuxGdm/whvJr+4BoqnU2F5tnbsofWsjq/nfXwue3R9/wi0yLDSCvxVFu2lTj3tvlNy99DPgY8DHgY8DHgI8BHwM+BnwMrH8MNBXIy8a8QRo21ICXwABOCgLibJPNNlfXtUFr7WlHns1YA5D8f4ex0EUKBACycorNbMAe+lJHP4OClgJxOPUHAOKRyqSAUPJ22pD+lBskohyQxXyAvIwFtAJCsQ6c4KMNqdmF7TZnyth4BEIBjoA9AGHgH3U2V1L6ANgASOjgccv4kjzCGMAk2powT+ZtwIly9ALGAWfUAaGw1fS4KW2ZF23Nx/iP+eMv1pQ29LE55YPNZo+ljEsfNl4BjvgYP1DGulIGnEWn2WN9LcUuG5f58Qht4DuQkvnZ+3kBvmaj9SXNB3nxl83DUutjY6GLMtqabdhskJ861h8/IfgJXZST2tyBXcB99CGsK/FKPde0RWfuvYJfsN3gMW2xA/1mD6md5LWNbewwWGtzIwUWktLf1phrxsB+sxed5PEnsUre+mED/Yl1hLzZhQ70Mj7x7dpKufnRxidFbC5AR4Axa0xbwKo9/hfoiA0I9iCMi4/wr9kBlEbwN7Hl/ojAHY88PuIkso1vepkznwc2L1KEedk41h/fcc9wzb3N/UXeFebOtUFet448ABPIiT3ma+aJP5kHUJUfHHCNHaRjxozRddddF8jYsWODclsjS4HB+ID58NnFaWDGYEx0uOvjPq6Zeuyg3vxMns+qBx98MFgbYo73+lrMmQ8ZG2FdJk6cGNjP5xePXGZMdPODA8A0eYQ5AaBZd2LO4oo6PiPtJK/Za/18unqceX+snz8sRj3k3TIwtyFoDufY0L/33b3tXE7CNfeAh7zrdx+sz+fFRkLeqgDyVmQqA8hbXNFdlXufrNm//lrxgqRSzVqptE0LtW/XSu3aFahd23YqattSHdo30xMvP6kWlXFFd9tfdzzxtkIlffXEnPfVpayLnh0/Xlr6obT0j9KKxdkjwEs/1hsvP6t7Zjynv0n6t6Ql1Cz9XFdedqEK4t104JEnSMv+LC1/T1rxT/3pz++ppLSo/h27+R7XvDEneQ1CAWFTsbiKS1JqG+6ruS/+Ticf9B2Vtwqp/4Bh+s/nK3Tc9/fRmUcOkz5doH41LRQpbqOCkpSaxftp3oLfadR5P1DNLqHgpG8klgWt0US5wol0AEmT8bBS8YgScR7xyztygb5h8S5cYG1FolTlibASiSrFE9UBCKZ9ebw4AOPxGKd1sxA4+zhl+iGAXU7eUpdWPFGpcKJK7SMVOvSHJ+v55xdoyX8X67UXn9Uvr7lUrMJSLZf0kbT8T1qx9Evd9/BkdSyNqLgsongyFbxbOMmjqusfAW2QN/u+UQ95/Uleu3d8ujrMdyEvP8xwvwDd/IZ+kfr267/R5n3lfeVjwMeAjwEfAz4GfAz4GPAxsKVi4NuGvLaxzyZ9QxvwBhzcDaWG2tLGdFobIAOgApBnkMN0An4oAw4AYAAOrg7qAbvu2OQBSGzwopv+po+8QR/mxEk+YCq2AOAATgZ5OfkHKKYdOoGgrAegh2t0k9qGMnnqgFhWB9QCUgLEDHzSzvqZX3lUM5CXciAN0A/4Y3ZTDkCiPfopx2agDPoNMgGHsd/GcFPaAxrxC+U8mhhQj18BL+Zb6mxOa4O8ZoP5GL9yos8gE2vDmAAyQJn52bXJ8sBJWyfzna07EIh523jozBV8QHv0UUd75pXbzq4ZA320py0nY7GbenzKNevN+iMAW4S4MlvMTlLam19Za9qhjzKzxwCg+YexLR5ZF+xBN2J+sdRiEXiMftob7ATGWd4gL/GAPpsj95fpZUxsog7AT38bx2yjzuZHe65ZR8AofZkf8UM/rk3wuekixQ7q0IuNrCVxbY9Op84eKQ00pI+NzfiMTTzjO4PA9OE+Zc157DJt3DFNB3qIOca0esoQ5uxCXurRa+trvgJGci/m3l+mx1Lrj50WBzYmKZAXwQfMi36Mge2smQFRyqjDFtZ55syZAbjl/sQG2tMGoc21114bvHeXeEAuvPDCoL/ZQ2r6ciEv/amjDTbx2XbXXXfppptuCsopGz58ePAIZ9aaMSmjPYItfPZSDqAG+KKT63vuuSe4f6wt/QzyAqP5DKMd9YBk8w/9rY9PGw/kbG++JK4R7kXAYEMQ0pdvXgjsIW/Tv4c3GvJWZaqCRynzPtz20YzSe5yoZ3+zRCVty3XrRb+Qlv8zQLIreE6zlunpOy9VYpeQnnlxcgB5y/ofqPGzP1KoRRc9Nu9/deZpI6WvpNt+vrcqdgqpdYtmmjxpis48qK86tw2pdceIQgWV2rFZsVrs0lxtdgmppKildiyI6sBDj9RTd5yjzI4hFbUOqUNxoYqKi4PHNQNzeR+v+/7dXMDLde77eNcGo+xxysVFCbXs2EMvvfhbnf69fsrsEtIuzVprQt10PTn2EnVpG9JfPn5XP7/kLLVp307NCmLK7HOK3vu31DsdU+d2IcWKChRPphWJlauwLKGCREptS0sULylUqrREpWUpFZfFFCtprWhJKxWWlqk0XKbqcAulOzZXSVlG7Yo7q7g0pUhJB5WX7KJ08U6Kh4tWwlyALpIKoG4iQZpSPJFWLFmhskSlOiaq1TKc0SVXj9CC2U9r/lOP6fIrrtJpF12pUNuIDjviEP3v8+MU2yGkfY/8kX55/6/Usn2pSosLlUrEFQDeZBYcZyFyXPFYVKlkMvjDZVuHvC6My/fLFL5o+AOOP4TWFle+bnUAuj34Ix/kJYbcmCK/pTad/Dh+g9PHgI8BHwM+BnwM+BjwMeBjwMfA5ouBbwvyrm1T2MDA2tpsSB2gBpDCo4GBLwgnUjm9CzQCoCGAQiAXuoEB/H+5ISgA8LATtAYeSAETLhQFAHEqBF1AJiAMUInxbBzbMOaa9cAGymx8/u8OCMQ+YBzjmF20A4QwPwCoq8vNA7oM8gJ8EQNujEtbABJlwFTKmAsQFn9hC2VAZmCc6baUOgQdgCsAC3XAc+Au19hseuzaIK/NyeaFLtONTfiU9cN3CPAQSMoJPwSoY+DT1eHaZSDN9GIDYNUgr9lMH+xEWGNgmD1Om2vmhw8Yj01+8rRxxfozJnpZb5sjfYgf7HeFNSYeaY+gA1uxh3aAME5n4wtSTjSzHtiPH4ktACf9zH+MyTV6WQf0sR9mes0/do+wXrQHDBKLCCDT/G5xa/0sxSbzH7oZl3XjRwgAU5u7pbRhLGIL3+JLUtaSfsQ6c6E9cUh79BPnlJn93FucyLb4YI7AWmx250y80MbeS43drA26WD/iljxzRyd+5QcNCHnuMdcO+nONPayF+cFS7mEgr9lNyngGebm2+wv/2JrZ/YUt+YS4Ic5y63hUM6dVOWmLn8wOgGddXV3gD8agDh9h99SpU4N3FgNuAaSXXHJJ0A7/0x8beVwzcWnjmV43pR3Cu3S5RxmHa/rQjjFZT2y76KKL6m2zORNr2IKvLUZtPEuJC97Jiz4eH40u/Gf6GQ8fUIc/8SPz4L6wU7yAXtdun2/6gKiprpHFvIe8mxfirguSe8jb9O/hjYO8K/+g5AOAL84OAeQ9Sb969xsVta3SrRddohHnH6tkQUgdOrTTjVderOfvOEs1O4c098WJalGZVEm/g3X3s39RqHlXPTbnIz07811NvmWcZt9xrsKhkHZu3l5zX3hLp+zXS5XNQuo7aE+98u7fFCuOa88eXfTRG88oE2ur0M6tdMhhh+mZceeoeoeQCpuHVNChQMUO5DXAS5oP8G4M5E1FowLytujYUy+9+J5O3beXkqGQdth5Fz04YYJmjTk/mMfouoc0bf4bate6tQradNBPrxqnx1//UK122kXh5jspXlaikkhKHWPdVJTqrj9+8i8tC84wr9CUe+9VpEMbXXv5cH39+cfq0rWTWhWHNWHKNC2a+4SibXdVWaxGH/xjiZYELH2xpt4/QuniHYNHKsdidmq3XPFYRokEkgzetVueiCuVSCqcKFdhPKNmJRk9NHWWpo2/Uy8+8ZhCO7dXqEOlQq0iOvjg7+mZsacH8xlCfTpNAAAgAElEQVR2xCm6/P45atuhSOlwQXCaOMkJ3mRKUd7NG7xXOJaFvKnso2g95C0I/vDij6rtAVz6Oa4/rM6FvPYjAQ95N9/Gmt+09L71MeBjwMeAjwEfAz4GfAz4GPi2YqApQt7G2NhlX8j0ALCAo2z4AywAPpxcA1yxSQvUARgAlQBB1FlfAxV2bSlgDZCAbkAKJ1bJGzxmExjIgD7yADkDrcBeYBnABriUK8Au7KcfAItrTkoabMEGwAk28396xmEdGRuIBOwzOy1lbE4VYwcQF2CIfqtHB1CMNgAZ5k0b7AeYWVvGoB22u/Yzrs0DCEp/bEToy7XZCijFX4AwHrsKmDE73JS+2EUb0w2cwheAHAAhp7PxCxAOgMe65Fsz+uEvswtohJ+YD3DJHdfyjI8vbGxLbe42f3fuVsdY9GccfIrPuWZ8Yo4+BrRsPPyELeYvdBCLzJEYYy14bC7xQxvzD/7EB8yd/vjT5okOfEV/g2rWlzoTfGonXWmHfWYvKfcMY+ADs9dNWSPa2XyZM8IaM3e7tpS2gGsgO/ch68y4NiZ+5B5BsIVrUmKPNswBQT+CT5kL86acmKUPNlJmscf9xJoyHu3oY/cjMUQ8ECvM1+ZHnnubueNf/MlnBXDX4sraWso6AbgZB/Bp9x9j2xy5v7he2/1l8cTYludeZ06u2ElVYO3FF18czJe44BHHjM2YzIPTtjy6+corrwzuGfMXPxDh1C7wdPTo0cHnicWG+dAdz/K8Lxc4TMo7c4k9WxvGxGYgMyd4WW/zj6XWlhjnMc6c1uV0L/qtDSl6qWNOwF7WwGxgbbmXHn744eDR0+PGjQvikM91bOK0Mv4B9ro6fb7pA6KmukYWtx7yesjbVGO0qdi1iZA3o/LySrWPdlJy2Ml6+t3lKmqb0ajhl+j6M45WpGVIrVq31FWXnK/n7zg7gLzPvVSn5pUplfY7RPc8k4W8Tz33vgaWdlKXHXbUnKm3q1mLkEIFNZr5/IeqLC1RcfMd1Kwwqaeef0vd4xHdNfwUjT79MMV3CmnXXZvpkEMP0eN3XqrkjiEVNw+pqH1LlRQXBu/kBeA2NuTl/bjJaFwdi1PataiX5rz4vk7ab7BKQyH17ttHH3/6L510QH+1CYVU0W9/ffAvqU+kVBW7hvT8q8/rp8PPU/MWO6qofSuVlZaoMFqj1hX7662/SQcddIg6tNpZBW2L9Pb8l3XzmQeovHlIdXWP6/YHntYBx/5E77z/oSLFcUWKY/rTP/6pfQ49VC1at1VBu7aa/+ps/eLiM1VaUqRIJCZAb7gsqXBpJ4VLMyotK1W8rEDVpe2ULmyrRCSmkmilCuPd9KsXfq3hF16jWbNeUShUplDLcoV2KdKhBx+oR++4SEXBSd6Tdf34R9W+7c6KtgupIlqoVJx386YUSaQUS0QVT0QUjUWVTPmTvEA7fg3DH0KIB6DrD0C3B195yOs3GL+tDUY/ro89HwM+BnwM+BjwMeBjwMfAlo+BbRXyuhtcwAaETX82Z/l/sG3SWjuAAWVANRcwuHlrS4ougCmAiBRAxCNiyQNHGA/AA/RCB3ACyGFwiTLTbfYxPuAHAGrggj7oZUy3D3n6UU4/sw3AyglCu7YU+7ANGMIcra/p4RrYRh3QiXLaAsWoszEAapx8pMzKqUPoA9DjpCF1XLv22TU+YAzmhb3M1ezMTaljPKCa+Y6xDILbOJSRx1/kc/Uwd/ogtCPumSvrh97c9lyjh/GxG+EasfWlzOpz+5sNzI95sv6UmQ+wgb6U2WOnrQ5dlgdcc+IVe4k56uhLP+Zi43NNHl/RnjrsBO4CGa2f6Ua/K6y1W8e6U2/6eVwugh9plyv84MH8ytoCFIk5fEyfXMFedGCnpYxHOSkAn3WxuVKOYJdbbnZgp9lKGTEI3LR+lJG3tXP7WZxThu34GRusDXkEW4gX5sU19yrrSrm1tdR+QEI7ACUQE1/Qhzkj9DMgj230tfvL7LaUOnTZ/UUesfEAmPboZUAvPwigHr+bbq7tSQKM7+ow/zE/1hnbrL6hlHUA2ht8px9tzWbSK664InjCAHY2dJ9RR1vG5IcE6ESPzY0Uf/JDAsoBvNhLH+ZBSjlt8LM90p33DAOt7ZTzjBkzgrauXp9f8172Plm3T4g5xENeD3n9/bL2+6WRIG9nJYb9RE//GshbqduGXywt/kha8Xd9s2xp8FbXZ8ddpPKdQ5r90hQ1q0yrpN/huueZvyrUrEpzZ7+pPdqXqjIU0sP3jdcehx2lgQf9SDffPUNtWrZWcYdCNStM6b66J3XN+efq109P0eDorhr3ix9LSz+RVvxHWvxnSR9Lyz7VET84XEXFRfWQ1wW9jXGSF8ibiMZVWJzWzkV9NPulD6Qln0rL/k+Lv/5MBx56oIpahFTQYheFWlfpufkf6bqfn6SDOnfQV/9YoExVW7Vqs4OKwx1VFi5WQSSjPf5npP7BCd7lS6XFHyt4yvWKpXpm7Nnq0iqkdoU1eu9f0j+XSfsedpR2bVaiIw4/Qd9osZboc61YsVTLl6/QkhXLdPcD96qwqFjhMk4uxwPIm05211//8nlwRnj54v/opEO/q87hjqqIJ1QWTaugpFw7t02qc98DNfXpd1Xd5yD95TPpv8HqSVrxb2n5f/S1FMjL855UeVlzJcraByeDOcUbSSQDyBsD8sajSqRSSpeXB4+naeiEYu6Jxa3x0bTuHGyebgrk5T8S/GG0PYBLP8f1B9ku5MVvFjduTG2N94TfMNzyG4be597nPgZ8DPgY8DHgY8DHgI+Bph8D2yrktc1/24y1tKENOYMKBjcaamd6LKU9wnj0QY8J10Alrq19rl7qKaMePXbt9qGceutLHmDilpkOyvh/vrW11OyzPuinjtTeReqOQzl9sAd9Vmf6SXMFfbRz+1Jm7WxM2rg6zcZ8KX0Q2lt/9JEnRZc7humgzvKk1tcts/J8ddbfxgIEWhntXcnVyTVtLQaxEaHM5uGuh43POuTqsvihjY2PDvJmg9uHMoNp7hi0sXHc9pZHJ/2sjdlptlNusWBtrC8pfV37zVZrk6+P1eWmtHXFrUcv8zIf5POD9XXXzHRYHdfkSW1tyKPX2uZLGc/WxPrlztXtZ+PZWLl1BtfRYXpy27p1jJlbj06zhTryZiN9c+fk6qMvfUwndfS12DF91sbaufOw8RnH7LAxbHz0kbd+pt+uLXXHcfNWT8o41LljUE6Zu+Y2po3bkD5Xt8+vHdh4/2T9Y7HnIa+HvP6eWPtnxqZB3kxVAPEKeBTwsJP0zG+XqqQgqVEXnKMRZxymRMuQ2rUv0JVXXqNH7rxOpbyT95XpalaZUsnA4zXh5c/1h08kfblE+xYVqjwUUvdeh2jynN/pj3//kw46eJAK2uyooo6FalEQ1vArRuq5ea9r1pO/0i47hHT9RSdpxKl7Kh0KqXgXTg3votvqpmroUcerWUGH4JHNvGvXBbu5796161wwZeWWuvWJeFyV6XJ1KE5rl9L+evaF93XKvgMCSN2xZUhtC1qrqGMbtWrXVqGCpM657EbNn/OYxlxyrD6cfYsqm4fUofUOKizpqJJwW7UqLtWgH1ylBX+Uqju0CE4E7xTivcQtlNw1pPDOIe3SupPe/af092+kPQ8+RKFQax1w4KH6/e9fUlHHkHbZMaSdd2muXdp10E5t26t9R95JXLbyFHNM4TJO9MYVDpcpWlaqVEmZUiVhRcNRhaNxFZXF1bwwpcrdjtZDT/9eO7WJaac2ZQq1LdfYqc/qX98sVrw8ph1CO6pVs1bBqeHSsuJAH6DK/BNLxIRE4nElUuntAvKymWJQziAdqT3PnryHvOsPPi2WtofUQ96mvxHnN0v9GvkY8DHgY8DHgI8BHwM+BnwMNFYMbKuQl40329zPtwnnbviTp42l+do3dpltEpve3OtcW6zeTa0vKe2pc8vWlaePjbOuvrn1Zoc7Rm4bt25debPF7Fmf9rRxx3Tz6+qfW2/jWzm6zBZLrS5fav0tzddmfcrcsdY2n7XVrW0cV3++dq7962qbr/+mluUb02zKV+euU76xG/KTq8vauGXosmvqrU2+MRqjbGP1b4ptGztmY8zXdOBj87OVkeYry6137XfzbruG8uvS31A/X752oLO9+MfuOw95PeTdXmJ+Y+e5kZA3o6qqjKoyGaXL0wLyxoaeqKfe/VqxorSKQyGFdwiprHlIzZs3U/MWbVSwY0gdmoU0a84EtUmX6idXjdefvpai1f31yrPzNKyoWInQDmreskbv/VN67uVn1LxFSK0BogVt1bIgrFCLEl18xQ3BadRPvlyie+8aqVGnD1VVKKSOu4QUararRkyargGHH6NdNyPkBT4l4jEVFMe1Q2F3PffCb/XT/QeoaoeQiluEVFJapIKO7VUYjmrX9hH1Hvwdffyfv+pvv5+r0/ZLqmqnkIrbNtPAoUP0788/0ncPP0ihwu56//+ky049SZEdQ2q2Y0j3jb9HfTIZtd+5tR6eNFs33/2ozrvmJr3z4YdqX1ikdm1a6K9//Y3OOusENdt5B+26864af9+9ynSuUWHHQoXD4XrAXVpaKpNwaVix0lggwaOs43GVhqNq2TGl8kHH6/5n/qTQriUKtSrSPkeerMdefEt7HHKkfvOnP6msqEgFLZqrfbvWKi7uqEgkXA948QuAN+ohb/2JTIO+/KqNX8BtD+DSz3H9gbaHvH7DsLE2DL0eH0s+BnwM+BjwMeBjwMeAj4GmHwPbMuTd2E2pLdXPBRO2adzQ2Fbv9nHbGrQgtXxuvdW59W7ebZ+bb2jc3HZb6trs3hJ22Vhbam7f5jjuXN38t2nTusbeVDu3RAytaw6+fnV4uK41XVe99+fq/vT+aFx/8JmBeMjrIa+/t9Z+b20C5OVXizy6o0LtozUK736C3udZvt8gS6RlX0larBVLlwRQVsuWS4s/1ddf/UGRZAuFdt5FoZ06KtQypTmz31Hv4krdddGVWvrZ5/ruIYdqj8N+qE+WSEcd8l0VtW2pB6bO1n9XSK/Nm62CXUMK7dxWF11yufT1+9Li33IcWEuXfaN/L/1Sexy0v1oVtN1sJ3njiZiS5Ql1KI2qdVkXPTfvDR2/927BCd1IuxYKl5aquKxMJeGY2neIqF1hRHNef13vffCuUh1CirUMqaigg3Yftoc+/vTP+u6h+yjUolC1/ffWp59+Jn3zX2n557r04vPUvqBQkydO0Qe/fkuJcIl2al2olxe+qdfnzVTbXULqOWCYPvla+oanYn/zta694GQl24cUKSoITvECkTiNvNp7icMRxcMRJSJRxeMxxZNJlUXialtcoZrdj9eDs/9XoV1TOuuqW/XZF1+oPB3XTs2a6+IrrtF/v1oSXJe130Gxwh0VLWqjZPBO3uzjmqMJ3s8bUcQ/rrke9HKiF8iLeAC6/gB0e/CVh7xNfyPOb5b6NfIx4GPAx4CPAR8DPgZ8DPgYaKwY8JB37RtUW8sGnkEPUsuvj+0b0nZ99G2pNlvS7i051pbyX0PjuHN18w21bwrlW4udTcFXW4sN61rTddVvLfP0dm6d378e8n67cNd9SumG/i1sTz0ltUNwbso9yXvZ3Ue/+8+bjb9PNxnypssrVBitUuWQozX77X8p0jGhkmYtVNyunaJlZQqXFKu0Y5GK2xepsG0rvTB3iqoq2qp1ix3Uqk0HtSzM6Oln39GC/8fee4BJdpTn/qO4aWLPdJjOPbO7CiCDLP6AwTg9jteJx5hwAZtrY/s6cUm+JNtgYZQl8DUmGpExCoCwBMjGNkIEgQEDNpYFMgiJpF2BkIS0ebXv//md3ndUe9QTd3anZ/bT85SqToWvvqp6z+nZ+nWd/vBndeNHPqHCyQPauOlEDZw8oZMmpvWZT16vz3ziOq0rtLR+rKnSphOy37tdP1TSS156rs5+3u9qct2AKiMbNVEY0zsve6t+9dd/ScOjQyoWixngXO7XNXNatdqsaaJa1YbRmkaGy2oOnazO0PGaniyp02yp3Z5Wu71Z1VJd4+NVnTRa1AmDwxobXK/GxJhK42WVJ2uaqAxpcPQkbRwa0bpNBa0fHtfw2JiKYxtUHN+k0WJZY+MTqg2foMmhE3TiuiGdtGFI5cGBDHafPFjXicNbNThcUaM4plPGj9eWwoDqpTE1Gk21Wu0ZsDjz6ulGQ61GvRvazQzyVuut7Hd5f+hxT9blH/mqXv2eT+pDn75RY8MbNbHxeI0MDevkjcN65ON+XPfuuEfvvPRinVLfqPbkqDoZ5O2o2uqo2q6r1u5C3nannYHNTqczczOnN/hs6cU+NFa6fjqO9GHltCFvnOQNwJsH1wF5Y8NwpZ9f0X9oMDQQGggNhAZCA6GB0MDR00BA3qVvXq3kBr03mR2vpC/R9+rUUKxbrFtoIDQQGli8Bvy5Gyd5Vxb2wjgW+++F+XgJ90NA3sXfE7M9R5YGeU85RVsOhukt02pt3qLx+mZtKtQ0PDim0ui4GtWqmrW62o2OOq0pVUoljY0OanDwBA2PnKzyZFHFyZqGi3UNjlQ0vG5YY+s2anTTBg0NDWawc/1wQUND6zUyvEEbRwoaHCtqYnxUE4VRDY+Na2SkoNLQoMpDmzQxMqrCWEEjI8MaHRvRWGEsO8kL4DXcJM5DlqVcN1pNVZt1Veo1Fcs1lSbKqk2MqlkaU6dWVafR1lRzWs1aW81qXZViRWPjZY1PlFUan1B5fFxl0sWiJiZGNTExpuJ4WROFSY0XyhovTGhibETjYyMaLRSysVRGh1QZHVZhrKjRsQmVCiMqFUY1MV7TxHhDpYmaKhMl1YtjqhXHstdJ13OQ94GxttRq8ju6LTWI2x3VGq3sd3k3TbR10lhLJ4zVtG6srELW17gmJkoaHS9qcKygYdagOKRycUiNWkntJr/D21a11Val3dRkm9/kravdaQXkPfjbvADegLwBeR+4B7tzEZD36G2oLfaPkagfaxMaCA2EBkIDoYHQQGggNLDcGgjIu3ybWbNtch2NfE6aLCYcDZ+ij7WhrVjHWMfQQGggNPCABgLyrizcjZO8D2ix3+/LJULerdpySjdMb9ms6c3TajTqGVQdLxRVLlVUr9bUqNfVanbUarZVr1c1WS2pPFlStVFVo91Se/O0KvW6RgrjGhoa0sjwsMZGCxobG9fo6FgGa0fGhjRaGNZoYVSFiQmNlyuaKANMxzVRKGQnhEtjJU0UAKZFFccnuqFYVLlczn6TFrhr2JuHLEu9rjUbqtXrmqxUNFkuq1IuqVqtqFVvaKrR0lSjo3a9rVatofpkVfwObm2yNhPq1Ybq1bpqk5MHA7bqqlZqWd1KuaJKuaxSpaRypaRquaxquaLywTBZOWgTu1madjVVJ+uq0mejlQVA7oPH2AW8zWZbjWY7g7yNVkuTtYbGyzUNj1c0ND6hkfEJTYxXVC7WNFGsaJxTxcUJFUoTmigXs98ebtSrajbqAihXmy1NtgnNDPJ2Msg7pTjJO5oB3oC8AXnz92JA3tg4XO6Nw7AXmgoNhAZCA6GB0EBoIDTQvxoIyLt6NsvSzTxvMjtOyyK9Otc01i3WLTQQGggN9L8G/LkbJ3lXFvbGSd7+v1eWBnm3btXWUxjcKdqy5RRt3rw1O7E5NTWlqanNmp7eoi2bN2vrli3aeuop3XDKtLZmYbO2bNmsTqetycpkdtQbcDkGwC0BZiezUCqVM2hcKpVUJJQBxJOarNW7oVrN2gNPZ+DmJCC1rFoV4DqZ/Q6tT/EuN+TNTgU3GhnIrtdrGbgGXjcbDXWaTU01muo0ODHL65Lb2WlXfru202qqk71CeVqNJqGlequpWhY4Wdutn52ybTXFq6HrrcbB8qaqbU7NNtRpAJO70AxAS79NrhttNRrY6GT99oa82G1lgfLuK527/VZrzew10pXJcgaw69WmGrW2anUgcF1l5p25nayoWZ1UM4G8tWws2G1m0P9Yh7z+tgsx90ZA3oC8AXn7d8MtNkNjbUIDoYHQQGggNBAaCA2EBo60BgLy9v8mWa9Nf28yO+5VJ/JW59rGusW6hQZCA6GB/tWAP3cD8gbkjft07vt06ZAX0JtB3lMzyLt5M6+rIe9UnbL1VG3dslWnUOfUrTr1IafqtNNP0UOITztF09NT2enVaqUiQqVSyeAhALEMqK3VVa1Wu2GypskqoZqdnK3VOUHbyH5vFqjZqHVDvQ5YBHQCWqsCvBrwpnEesizlutUEptJXN2Cf1zfzimLS7WZTnWY3Bra2WlNqt1oHAW9L7RYAdrMahFY7a8dv2WYAN4O8HdWanIzltcdAXiBwS9U2kLeuRquuqUY3GAA3D/YHVDZYBi7zWuZDQyN7lbPHzVjaGXSmbiebz2atoWatdjB0wXGr1cmgMCd2GWOrVlOrVs1+19cneSkzVOZkN69rnpqeVpvf5C2MZaEwPi5C+l72fPpI/8N6ue2n/vt3eIkD8gbU9X02WxwneWMjcbmfR2EvNBUaCA2EBkIDoYHQQGigfzUQkHfuDarYwIv5CQ2EBkIDoYHQQGjAGgjIu7Jw12wjTvL2/z25DJB3awZ3u4D3lBnIe9ppp+mHzjhDD3v4w3TGD52h008/LTvBW6tVVSwWu6855lXHByFvZbLSPalruAvUrdWywClcAq9HJsycys1OrnKKtaV6Bn6Bv4DWB36H13AFMOn0csTAUQfscXqVGKDazkIzizPQmkFeQC9hWu3W5i7kbUxlULTerKmzuZ2d0M1eb92aVqXVULXTUrMzlUFixtj9HV1egV3T5nZD0+2GWu2Gmrz6utXOTgjz+7itLHRPEdufZr2jVr2lVqOmdqOaQWhOHBPwtwuHu6+Y5lXTU412dhI5Ox188Pd7DXCz+Usgd3c+/Qro7jzUAcGddgZ5W52ORgtjh4QM+o6NPQj2rsYNidkgr4EvD8Tp6eksdOcq4GfMw8HnRav7u9XogzmxZlJNkV6N90X43L+bi7E2sTahgdBAaCA0EBoIDYQGVkYDAXn7f5PMG8sRx1qFBkIDoYHQwGrXwHy/H9/v4wvIG5C33zXaL/4dJuQF8HKC12GrTj/9IXroQ8/QGWf8kM44A7h7uhisgS3xzCndajU7xcs1p3kJpNO6pA150xho28ggLydNOV3aPWHazV9eoLtQINU9McurmTtqHzxRa2jbak3Lod7colLzdE00TtNEdUqT9Xb2O7q8trpaq2myVlO5WdVkY1KtellbWw21a3W1683s5CxjrNanVKu31ayXNd2aVIdXOLcAzPXs1dD2pRt3VG9sUaPW0tZ6QZ3SBtUq49krrfmt33adU8ddvzv1jqYbU9lvCncanO5dGpCsA5o7HXWmp7M4IG9A3oXeR8dSvTjJuzKba7GpGfMeGggNhAZCA6GB0EBoIDSwEhoIyBvAoF82A8OP0GJoIDQQGlj7GniA2ZjdHBr3uwYC8gbk7XeN9ot/hw15udk8GE7vAngf9rCHZYF8oG25XJ4JKcxNYW+aXjjk7YLePOBd7lO7C4dOnIjtqNWcmgnNJnB3c/c0Lr9ZW69rvDal//HMF+niyz6uE0sP1ejkQ1Qsc7p3Wjff+hWdfuZWjU4Mq1Ud1+aJ43VqeZ3alWL2KmVOLBer03rLFZ/U3779WtULg5ounaROYyJ7TXWjXjv427wG303VGtMqVE/V05/+v/SBN71Cz3rSo7V37516yFkPU6VcUrNa7Z7mrbfVrnOKd0qdBqCa8QB5Fw/NA/KOzZzK5CQvv8cbv8m7tC8MLPz+W332A/LG5uJKbC5Gn6G70EBoIDQQGggNhAZCAyujgYC8a39D3ftjEcdahwZCA6GB0MBKayAgb39AUr/2eLXG8brm/n+WHTbk5aQuAcBL/JCHPCQLwEzgbqlUyk7mkvZJXQPdPMyd7To9weu0T+zOFq8MGOKVxfzebhp43TKgdyp7pTRjH5ns6Cd+8wX6y3dcr4c87kn67g+k3Xuk+yXt0n3aqR9ojw7owN6deuWLnqnTCgOqFYZULtc0XmlosDilic6P6Wvf2qtnPOnxmhwcUK08pAqnc8sl1bLXYJfFK7Ar1aqK1bZOHGnqqU//X3r/6/5cmzcN6GlP+2X9yyc+qlJhUI3SWPb6Zk5Et+vtmVO8XcgL4A3IO9cmSPpqXb9uN40D8q4++Hq0nh8BeVdmc22u+znKYk1CA6GB0EBoIDQQGggNhAaOlAYC8vb/JtlKb8hH/6GR0EBoIDQQGlguDQTkDci7HGA5IG//P5Nmhbz5h0D+4UI5JxOBug996EOzQHpqaiqDuT6965O7KeCdDeY63yA3jfMw92hBmMX149+lJTbY6oJfQG+91tH01Kn6+Gdu1PckfVfSTV+9Q5Pljk48aVjDhXH997dvVHlrRac86if0uS98WQ+b3KSPvOuvpf17tGMvEFi6T9JuSfvEf/sl7ZG0VzqwR1/598/rzm9/I7u+X/u0X/dnpTtpQ9V9d0i7v6UD95OzX5+//hptrWxQp1kWvw3cqjc01Whlgd/r5fd9A/LOvcmxEMjLb67GSV7fExH7+RCQd+5760htroXdmPfQQGggNBAaCA2EBkIDoYGV0EBA3v7fJMvvfcV1rFloIDQQGggNhAZWRgPxuub+gNQBeVdG/4t57iwa8vrmAuxyepdXM/Pbu+QDYtOTuz69uxjAC+hN4a7TqwPyAq8Meg2yuG6r2ZzKIG+53NCmibZ+8mnP1wVvu1bDI0XdtX277j+QYVrt1t3aoR26i1O990t33vhv+uHSehUHN2jdSFnPPef1uuRtH9CJg+PaNDSi4bGCChPjKk4MqVIcVqNcVK1UVLkyrmIWShqvVLV+tKxHPOpR+viH363Rkwa0cf1xmhgbUn30RG2dHFK7WVG9UT8U8jYC8i7kH/6zQd70mzJ8+SEgr++JiAPyxqbiQp4tUSd0EhoIDYQGQgOhgdBAaEkj+IUAACAASURBVGBtaSAgb/9vki1mQy3qxnqGBkIDoYHQQGjgyGnAHOrMM8/MfhYx3WuP9NEDwAF5j5zGl+v58SDIywldjPc6ycuN5dcxO6YuINavYE7Brk/xuozYp3XT2CB3rnh1QF4DXqCuX9lMuntdr7dUqzd1wlhL/99vnK0/e/vHNHDc8TpxYEDHHb9eG0bG9JXbvqBiZ1RbH/mj+sKXvqZThzaqfdyAJjau0/rCpP73OW/SM/7stRo4eVwnrxvSxo2jGhkcVHn4eJWGT9TISEFjxZqGx0Y1Ojaiwui4CiNFbdg4qsc+9hG6/h9fr6ETBzQyPKCxwqgmCuOqFMtqNlrZb/6265zi5ZXNbXUa/CZvnOSdb2NlNsjrVzbzoROQN8CuwW4ax0netbVpN9+zIspjvUMDoYHQQGggNBAaCA0c2xoIyNv/m2TLtdkWdmKtQwOhgdBAaCA0cHgaCMh79EDuXNA8IO/h6fhoPAcWDHmBvtxYnODl9C6QF1gByC0Wi9kJXiCuwa5jA94U6s52WteQNw90uU7BSP+mgaKEjlrNqYMB2NsFvdVaQxPFigaG6zrraS/VVyX940ev1/sue0v24uXuy5fv1B79QPdK+upt39OWkVHVBgZU2LhBJw1P6K/f80/afvAFzTONeDnzjm/q1x//OG0cHtZLX3Gx9t4v7b+f/+3OXvW8Z9dePfWpT9SnPv0e1eoDWr9xQGPjBZWrLVXr02o0OmrUmxnsbTcBvIcJeRsNtTodTU1PZ/FoYUxpGCuMZd/ASQEp6dW46ZGOwWA3jQPyBuCd7ZkVkPfY3uRbjc+78Dk0GxoIDYQGQgOhgdBAaGDpGgjI2/+bZEdjIy76CB2EBkIDoYHQQGhgfg0E5A3IG/fJ/PcJczQDedOTu7xW1oFK3FC8mhmwS0yZIa5jA15D3TTOA9485O0FdfN5s0GSfspvZb9h2xKQtN2cOhjaXfDb6qhSbaoz/VB97DNf0TZJF739ag2cvEEnHT+gwroTVBw6Tl++9WMqnzKqUx/zk/rUF2/VVKmq0sknqzhe0Wipon++4Tr9whN+USdvWK/R0bIKY9OarHX0tW99Vlt/aFQjhQ0qVxoqFjtqNNv65Kffr3rzJA0NbtDgWFHX3PBRTT50szaMbtL4xLjqjbaqtaYmazVNNuqqtlqqtxhDS53DeF0z69c+CHmJM6gL2HUYO7YgL7/JS+gnvYYvKw+fA/IufYMsNhdj7kIDoYHQQGggNBAaCA2EBlabBgLyLmyjKjb0Yp5CA6GB0EBoIDQQGgjIG5A3ngMLew4MpHDXk+Yb6PTTT89+b9e/u0tdAK2BrgEvcQp18+kU8vq0bhrngW6v69UApIC87SwASTsHQ/d0b6PJidm2iuW2No239bNP+yNd+PZrNHByQS966dm64i2vV3FwQF/+1g0a3TykgeNO1MBxgxpbt0HFjYNaN1TWrz316dq785s6dWqTNm08TqPjFa0fbKlY7eiWb92gLaedqKHB4zRRKGt0tK3xck0f++xVmmgMaP2G4zSwblivvuqf9Iw/O1cnDg+rXBxRszKsRmVE1VpZ5fqkqu2Gai1+i7epTrOx5Nc1s4adTicDm8TpydY0nZ6CXcsnef2lidWg4/Dx6MHfgLyxMbnaNibD39BsaCA0EBoIDYQGQgOhgaVrICDvwjaqvDcVccxXaCA0EBoIDYQGjl0NmFHFb/KuLOyF5Sz27/+U+aQsyGnu6zPOOCN7azDrzDXsMe73pd3vD4K8gF1eycwkE7jm9C7QLg93U5ibgtx8OgW6vdK9oG4+bzWAp0Mhb/c0LCdiyQfy1ppNTTaaOnGspsc87f/qT9/5cQ2sn9L/+7sP6ld+8ec1Mjigm+/6sr6ru7VH+7V7x7165JYplQaHtH5yq67/4o267PVnq7FuQGNDAxqcKOn44YZ++NGP1S3/eY2mxgc0sm5AE2M1DY+2NVSs64M3fEDrygM6ef2ABk7eqEc/6f/oshu+lp0g/vFHnaZbP/c+PWLqJDWqI6rUq2q0ur/B2242RGg162pmv8u7OPAVkLd7UpkHF69rDsi7OP2shvt9OXwMyLv0DbLF/nER9WOuQwOhgdBAaCA0EBoIDYQGVloDAXm7G1drdRNvrY7rSG+4xrwtbUM3XRdvkKd5/ZSebY1nyz9avi9k3lbax6M1F9HP4d+HveawX/TTS+v94luveXMefhMC8gbktSYi7v2sehDk5ZXMwF1O7wJ4OYUJmC2Xy9krmlOwm6bzYDe9XirYTUHvcgCVI22jN+TtnooF8k7W6iqUKjpuuKwffcqz9dK3/pMe9cQ/0Ic/f7Nu++bteuJTnqAvfvsmjWwpaeCEAW08cUDFkwZUGlyv6z7zBX351tt06sSJqp88oMHhdTqxUNRJEw09/olP0Pf++5/1kCK/3XuyJiZamihNa7BQ0de/e5t26m5Ju/WRT35aA4WH6oP/drv+4eOf1l++7Dl672ufr9MLA2pNDqlWr2Undw14A/IubBNkvm+mAHl5VTOg90hrMOyvLpgckHdh99hKb8ZF/7FOoYHQQGggNBAaCA2EBkIDy6GBgLy9IW+vzeejuYnnTWTHvfqey0eX9cOGuX3pNYZ8Xr5uek06vc635XohdfLtetlk3myrV3nexnJfp32m6V79zFfeq83RyEv9Ip2G5eg/1XaazttO/UjL2A9Lr53uZauXjTQvTdvOUuOF2Orl41L7c7u5+p2rzO2PdoxPeb+cl8/P+3Yk5s992PZ8Prj+UmL6cD9Lbd+r3ZH0Oe3P/ThOyw5nXKmdI5nGb0JA3oC8R1Jna8H2AB+0nNTl9C5gl0AaMAuo5VXMswHe+UCu4W4Ka2dL5+HUQuvl263k9aGQl9c189u83Vce1xstlattVRun6fpPfkl7Dkive9Nb9NnPflLlSlHD4x3dum23dkjapd3atXendP9O3Xbz53Xdh96lf73uvZrYMKDh449Tabyi6z5/k7YfkHZK2rP3Pj3jV35EpRMGVJoo66Of/KL4b8c99+qMzR2NrDtew0PrtWlkTJvGNmvD+Cm65fs7dNeuu/TMX3uMTgXyVobUqFdnXjfd4jd143XNC3oVwWyQF7jrMDU1FZC3uboA7NF4lgTkjc3C5dgsDBuho9BAaCA0EBoIDYQGQgOrQwNrHfKyYczBATZk+aJzftOMfMqpd9ZZZ2V7T95k5pABaW/oErNXRUw+6by9/LVtUfe3fuu3xHx7z8u2sEe7tJ98+ud//udn+mZ/7Pd///dn6vdqSx598+/+H/uxH9PjHve4WQPlaR3myWP0m/Sw47Hg/4tf/GL92q/9WnYQg/w0eA7I89hI/8iP/Ije8573ZBvj1GH8Dvnx2h75z3/+8/W7v/u72RzZ5i/8wi/ol37pl/TLv/zL+sVf/EU94QlPyK7dX94e4/id3/mdzI5t//mf/7l+5md+pucaup+8nfy1xzpb7L4cU480miONPa6f+MQn6tGPfvQhmnr4wx+uX/3VX83qWSuz9ZPmYw8tMzbacZ2Wp2nKf/iHf/iQ9Ucr1oTjxzzmMfqJn/iJnnaw73vL8+N+f/Znf1ZPecpTerbDj7Q+bfLB5fSRD7R3Xjom8n77t39bP/mTP5npM61HGTbJQ8do8ud+7ufE/YWOHvnIR2Y2KWON0NnjH//4GT9p7zLssGb2Ed+xS+y81K80TTn3sfOARU972tN0zjnnZD7/xm/8hn7v935Pf/AHf5Dplvvd1/iKH8w598Cv//qvHzIP9I/e/+Iv/iLTlX3Cb/vlmHqs/9lnn32I7/brD//wD7M5oj55aexnC/NGn/h0wQUXZPNOXa4dMz6ef6973ev0pje9aeY5a3vMBWnGlM4fefRDjK8ErqljH+0XdRzIY1zoAD+e/OQnCw3bnzR22p8D1Cewtswv68Iz6FWvelU2NsqYS3wg5vqZz3xmNof0b3vEzM2f/umfHuKXy2nLeD3mZz/72XrpS1+a1cW25+Hv//7vMy36mvYE2tH3Ix7xiAfdrz/+4z8uB+5h0ty/P/VTP3WIf9hA/5dffnk2t9hlDOiNZ64Dz070h/aog++sAzHz88pXvjJLu4x8Av7ZJnGaZr7TcbqMdq7br7F1FpD3AcZg1nA043hdc+/Ts/103wzw0PZv7hLjHIAVgJue1M2nU8BL2kC3VzwbsE3z80AlLSOdL+/H60Mgb8OQt5698rjRbKvW2KyJ8maVK5tVKkyoNLwuA7dDJw/oxPUlnTTU1vHrN+nkDSdr46aNGh7epJHRk7JXMzdHB1TdNKDiyLiGxlo6qTildZNTGiyVNTE+pPGTB1TedJxGx0oaK7dUKlU0WSiotG69yhs3aWR4UEMjBRVG6xottDQwPKEThzdpfMOAWiMDalYK6oJdwHRbrUb394Vb2auaFz//rFn8Jm/3lc08dP2B3I+6DZ9WDj4H5F0dm3GxaRrrFBoIDYQGQgOhgdBAaCA0sBwaWKuQl01YbzCzrwSQZG/JG+WGbN6IJgasPPaxjz0EvpD3m7/5m4eEZzzjGSI89alPzfKp8/SnP/2QkG6y4Qf1gUVsqtP38573vEPCc5/7XP3Jn/yJnvWsZ2XAwJvIjgEkhk1s6hvy0o/HmfbpfNr/0R/9UQYLAYb5gE3mhgAswg/25GiHjZ/+6Z/O4ACwDkAAOCNmw/9d73pXBhLTfNIEt2e+sYPNt73tbXrzm9+cjfsFL3hB1tdznvMcATcAER6r14S5Iu+FL3xhtjakGSvxZZddphe96EVZGbaAzh/4wAdm+s3PBTbf+ta3ZuPBF9bgyiuvnJk77KaB+taK/Upj7AOmgEf5tc9fow8CGgCIkGYNGR99ABpZd/xiDQz/mBNs4Zf9Adbkx5ZeUw+9A+foi30fjyutRx7jAYTRJ+uJnunvSU960oPGZNDF88JtAaLoBQBmPaNh0vSPfQAvoCztO00zVu45IHevgG8EIL7vYexaV/jCWpKHXfKZR+AUUCsdu9PeF2Su0D8gDs3SD75SDzvEvFUSwEUf5NFPGtAh46dv7HJ/AOV6hauuuirTnP3FPvPzhje8QZS9+tWvzsZJn29/+9szbaNrAvNKDGhkzj2HgMt3vOMdGcRjPL4/+fIDNn/lV34l0zz3MdCfcfqLJowDH4CZr33tazOb6MX+MV408bd/+7cPGr/nmXLWm3sRbQJ5ibnGl5e85CWZbb7cAXTGH8AY/dIP9/bVV1+t97///Vm49tprs5j5w38C5Y7f+973ZnYYKzY8D+makCafceEbae4xNIG/aTv0j69ASuYfCP3ud78784E+3/nOd2bgnXsWrXDf0t6BvvCFemjHzyxi+qU+GuFLF4yXPGLmmTn8m7/5m2x+0QA2rrjiCr3xjW/Ua17zmqyM5yXjJ486rBNlHiM2mEPaoQP66hUYE+WMifXx/NEerTD/5OEfedTjWcB8ce/zGXjxxRdnz2ruL+q4Ls81/CKP5xi2rH+eyaTJ8zrin+eNucC+5wab6fpw3Y8B/wkBeQPy9qM++8mnAT7QuMF5QAB7SqXSIa9lzsPc2a57wV3n5YHtfNAW8LEawdMhkDc7xfvASV4gb6XaULHc0Nh4WcWJCRULIxof3qDCyCYNjxQ0NFbU0OiYxotFFcbHVSyXNFIc11BhSOOFjSqODapYKGpysq3iZEujE1UVJsoaHy+oPD6kSnFYpUpZE+WKyqWiCsPDKo6MqVIoZidSx8bHVSiUVBgva2SiqMHRYZUmhlUtjalaqapZn1K72YXTAXkXvokx20le/5B4QN6Vg6j9/hwJyLvw+2w5NtXCRsx3aCA0EBoIDYQGQgOhgdDASmpgrUJe9pO8WQyMAsSwKct+EzAHOMdmdbpZD+gCmlCPTTI2vdkQ90koYBTXAM8//uM/zk7Gkkfw6UfKCbTHDsCN02RAKvpLN98oJ+Cr+3R5WkY5bdlA53QnNvGVuvY/H3tsxAYdtt0rZqz0A5yzP/gAGAA4AWhJAyIIQIN8IJ86BGwQ8AsfgFMXXXRRBqgMAhkPvgEomCP3S4w/HgP1gdz4gz38xx/KSZNPGjBBOh2f58WwinJsA3wuvfRS/dzBU5yc2OSUmgPzTF3Xd9oxfdAnIIn1RyNzBXTFeOmH+sBNxsnep0944yv2OBVIGjBFGfpFr4B9YBNgIR0jaUMl/KYe4Ab4Qrt8Xa6x77EBVxk3vjjf43RMG2A80MrrRBn1GQ99kqaMurYFxKeN7Ti2T4a8+S8f5K+BgwTaYcPtuZ+Bl4yVNTZ0x1fmDoDkfOA1aesLf3kWML+sJeMA1FHP7ajPvQ7wch5glvq0Z7758gCQi7GQlx+jrz031MF/bNCeZwcapw/X4bQrZdR1fewYqNPe+UBq7iHs+X7lCxh8iYF7l/uSawK+Aovpx34xfkM68oFwgDmgHOGaa66ZSXONTe4hAnOF7/5iACeRgbs8G7BPfbSPXfyz36TRLOsHAMUHYiAu+mbs6IYAHOaLKpRz7XmmPfcLgc8xpx2zntas8/CTutYPfqF9nuncm/jOHKVfosFX6hEYk8dAmjUA/nIS1nXQx8tf/nKde+65GSBm3gHIPP/II6YudnhmMD/4yolf1sGfOeiCNKAUv/jSgsvsC2vwspe9LPsiAnNpHxx7jX0/8ozELu3on7ExftaJeSWPtkBZp6lLe/xjPpl3j50YAAx4Zi74bGItWScAOmm0yfhIs7asI+3oh/p8aYG69Ldaguc1IG9A3tWi2ZXyMzvJy0ODk7q8ljn/aubZoG4+30C3V3wsQd4u6G0dfFUzcfc3eZvZb/I2NFEsa7Ja685zuaTJSkW1yUlVq2WNTxQ0USyqVK6oMjmp8uSkxqu1LBQr3bxata7J8mQ3VKoqlSZVq/Fq7UmVyuOarFa6oVLO7NarDTUbLdUbTdUbDU1Wq9las37VWlUTxQk1Wi1NTjbVqE+plUHelpqNrt9xknf+TZBekDefxz3Gh3C/Q8fw7+gC6YC8899fK7kJF33H+oQGQgOhgdBAaCA0EBoIDSynBlYT5GVjdaEbVWwgG4IAy4BNtCUfO2xWc7qNDWyuqcurUdls9ga4y2hHHW9us7GLPcpdh/I0uA3wkk107FPOacQUGuAPwbZpx4lA4jTQD5v4tAVYpBAirdcrzVgZ22wBsEugnLqeI/z1HNInIAR4aCACXGJsgDFiIASb9vhAW3zGX073AU7I59rlgAMACSfUqO8yzwl2OcEGJAFecZKMepQDDjjlRrlPCAMq3DYdA22wAcx037Q3vMoDLfIBF7TrFbBB8J4Kac+Ty/IxcwHQBnQwTvxj/IBD1hLYjH8AIqAHIIYA3AL+kaY+/lhzaR/YQ+esIXNqf/hyAXlpXdK2RRrwBVimH/p3TNoB3/AL/90/vtCeLxwAbkgzFp4p1CGmDXCbmMAc5L900GuO83nYToPHRz38B8YChtEhGsUnxg64Q0dolhgfsIN/xD6dSRr90hboxjgJjIFgSEgeAIv5xgf6JwZ0GrLZPn0QKHegzIE80uiB+4559z2A3g15qeP2nFqnLnnYts4BofiFP5Shd8ZPHeaA9umcuh33FPcfQBgQyRxRBiBnDgF/Pt3LlyKsXWJs0gdzCsTjlc/nnXdepjfWHD98T2LH/pJvUEvaAf+AvJ4X+8tr1flSBtfpfHremHvrCl94NjswX4Bx6pDH3PnZ6THQP7ZZv7/6q7/K/HffxEB+5shz5vve4+E55LcX0D8a4YsHBE4G4wOfNWmgbTpuxsznCs9hzzF9c8KYdu7bvnLtNJAXOGyoDGh/xStekQFm0g6AZyAvYBnbPL/58g1fKGCd/vqv/zoD6qwNz0R88nxTn3VgfPSd9s8XLAx57RP1GQfPL04rp+MlTTn2eQ6hFebM87EaYvwnBOQNyLsa9LqSPg4A+4rF4syrmfkNXoJfz2yYC7x1mrgXzHVeHuoeS+AIyNtqttTilcdZMDRqq9lMQze/W590+krk7knmWr2eAdh6q5XF3XnE9gMBeNwNXRuNRj0DifV6Tfbl0Dr259C40cAOPtu24fSh9Ra6lmjAr2Uh9qnWXnEKREkv5z+ij4at1P9e4+MkLx+shIXOX9Rbmu5W27wF5I1Nw6PxjIo+QmehgdBAaCA0EBoIDYQG+kMDAAxvuK7kRhA+uH9vIrMJ7OCyhcapPaANEABbtMc+UIrNezaZvanOZjNgxZCVfy+7jf0gpg6b3fThflyPa6fpB9uGAoZRLvdYbMPXtKMOvgGv8As4wRgAFbxelNin+vCFYLDBeO0HscdOGtuGUfaPfoFgnGrE37w/XAN8ALV+NbJfI+sYgMBGv+cX/9kABwwRgEmXXHJJBi0AKQAFAAYwCxACbKAc0OTfd8QXoDtwgbVKQQAwGfvMEVCCMRHwleDXoZJmvgC31jrzRh/4SD6ginQavBa0J227vWJ8oA595uvaDjH9GsShLeYfyEv/ACFO6fkEI/MN2AX80Se+WRcAYfLQFXNEGSd8gVec+KMePtEHMfAX/dAX9a1r20CXlBlCGVD5mpg8ACrtrWfaAwXp2/6xFoAq+gW6AoA8B6wfWsYGbZ1PzLUD/hN8na9Lffojn/7wH2DluaAtUJC5SPtAM9wjjJ+22ODkL4Abn5k/gKj7dj3qcn8wHjRmHdHevpOmPuWkXYYtp5kT+0g7ysjDPvcv8+ixcc/4BD33HYEvM3DKFj27Pfacxg6B+5+25OMrAM9j8dhcFz0Ct7kH0Yn9oR5foCAPO8wPMNH+e0x8CQBdk49NIK/nnTxgofvEDnXwhbRj0i4D8pKmDX1ggxOkrCf1uXZbru2H29OOOoyDANwlj/J8wBf7xr3H3LLG1LMd5pG14FnjvimnX/rHPidzueZexYbLufarlbmXmU/74LHjA6eAyeczibXCFp9BnFxn3Xk+8OUDAl9K8HOONrTnd3x5/vpnBbjXecU418B67kGeJ6wTWmdeGB/3DuvPGrJOgHp/WYNxA695PhPwg9d2p7CdL36wXjxDOW0MQOazBp+8LoyNZzc+e17o13NPGu37y0EeE/FqCDyv2V/vte8+Vx5tIhz+HDDHi/23RC9ekq4F2kWv1ql1uxr02I8+Dvjk7mxw12DXAHch8bEMebuQyeA1HxvyOn/tgqyAvN3f4+UhyAOMP8z5w2K1Qcjw98jeowF5+2OzbbF/qET9WLfQQGggNBAaCA2EBkIDoYGlaCAPLFZqk4hNX/fNhi8ngNgwBi74hJs3jl1vrji1B/QA7lCfzW3sUM7mtyGGAVDaRx4iUEZgwx/YyUa6XzPJv6+9cU07p22Pk15sdpPPpjqwKw2MFx/JI83mMXYMGwAMpAk+XYkt7JNHXTYl2cTn1CFjpYw63nhnwx8AkAb6AvABt9AC7WiTn1tOgwJwAAT5Mq4BOwBaj50Y6Ek+cAKIwDoadBOnaWA2AV/I97wZ1OA7flEH6ACEADwAWTjB5mtAGBCZ9swZfXNqFwjBvOAPvrDe1AFQAE6wnYb8GPNz4rrMPfMOQGH9iJlv1hHfqMdcYI8yQ17vx9CeOvhCPc8veWiTOaMOYyGPvvxqa2wyV6wnWiamX3SWBvKBPNTxetMf9giMH30aYtEHfdo3YvrCP3TClwFIUw97QBr6Y/z0RR7z7nzsUh9QDMj0WFIf0vkmP73Gx/Ta5Z4PQC0QFj9tkzlirenL42Bu8QldMv/YZCzMM3UAcfjNXADI0Bo2sMk6AMG4pj/6TueFayA4oAtQR/DvkQLCnOY1uMAzjwfdoke3oT1QE8iARpljB/J49jCX9p32nML165Hxg/4YF3W4p7HpOXe/1CNgm/vCJ1UZG6eAsYevBEAd/hHz27qATM+zIS/l9MP9RJoxcX8S0w4fuQ+xR5q5on/mEKDJ2mAT3z2v+IrfwGX0S33qEJgDYsq539Ac+kOHrDF6oD16xLbr83lCGwIaoIzPB/rFV68ffnLNfGAn9clzSBntOEXLGGnDfOMXmmK8rBdtCawrJ65p7y+E4Ad9kpdCXurzRRSeZ8wjgTSg2Ket6Yc5AfKid2xgj9dzs6aUMW5ssU58scZ909b1+YIEa0YedWlHGYE8bDrP8+ZrNMmzGf1QRnvbZbzMIZ+VaCa1zfixzfxTjtbdp237up/jgLyHD2pTwLrYdEDe/v8yxAzk9cldx4a7jhcCd10nIC9gKA9yfe34yMKjlYZzAXm7cNcPTT5U+cBf6XWJ/vvrvgvIG5uDS9kcjDahm9BAaCA0EBoIDYQGQgOrUwMrDXnZ6CV405sNXUBVCsxIs7HN5q836xe68YttNvEBAQANNpqxga00cJILaEuZbdu3/DUb9wA8fMJXTjexSW3b2CBNe2JsMwaDKDbgAUppAHoAaIFI5Lt93gd8oW+AExvkbKxTh3zGw2lEQCLX5JPH2AEa9MvpMKAeEAgwwOY/p9fIJ49TfR4vbVO7wBmgBlAiHwAcwA774nbEgDMgAnNkm4zPYyQ2SPA+BXa8FozXYBN/Ac604SQZcIdTbKwxY6QPTgTTnjnCT07C0T8nSQHEzLXBD/CNMVGeBvxOx8J1r4AfbPSzvi5njOSTRxrdUZZCXtvGD8AU4zAgZb0YD9CHNAFw5UB97GPb80KakPrga/oiWJe8rpV6boMu6Bt/0/6cTvunDvNqSMrYsEvALuOhL/QEKEXT1iPrxdxTl3r0T78E7iP7wDjph5CWU8eBPmiPXgDdtLEd/EUz1LUdwz/WgLaMn5i2PiHOuPAbGM2zAPusC/MDHGTOuT9og17JA3qifV55iz2Hl7zkJTOnHskDflpztPU6+f4FrHKalj4I5DsA0kgz1wRf45/tfOhDH5pZUzQPpCXmnqWMGF8Bj/6igdtz7VP4+EpfXh8AIvqmrn3zGMkz5CWNX/TD69ndHsiHVmjLcwfwx/pTn0A9j4uYexE75NsPfOAZSz6+EHvc+GIASm80cwAAIABJREFUTJ774bQ71+iCL+JQDyjLl0ioQ9/4YTtck8/zg2cE88E1gf6YN57Lnh/a4Qu6QjesHW81wA7XjPv888/XC1/4wgzOGpqzJnxuuF/GiDa4TiEvnxnMJX3zPEPT2Kae/ccX8jw/ni+e42jYn0n4iUaxz7wSbIOYe5Jnn30CugKVGRPwFm3zbOckLz75fqF/2nCP80pm0vaRZz5riQ3uIb7cwdjpj3m3BrDBPYmv7t82fN3PMXPrPfbZ4l4nemerG/mLg8YBeXv/XdJP98xA/gRvQN7+gkCrFcoF5D30JK//8bRa1zP8PjLPhYC8q3NzLjZVY91CA6GB0EBoIDQQGggNhAaWooF+gbxs9nrTmk1fNueJ2XAG2AAv2Zxmc9ibywvZyKIuwAx7bDAT2AxnI5l/EwMgqAMIBHZ68zndaE7T9Ak0AB6Rpi3wCqCUB9H4y6lAygCTgAfbz/vOyS82y7HnYPvpNf4DsyjjZCab+faPGBjCZr7bkmdAwMa7T61Szu8DAySwST1OaQK5KCOQxyY29giMGyDEJn8+pPnAGtsg5qQY0INxAFpIA004ceZTfgAA1pm1oQ3zxPpwzeuagQ3UB9JwzdjRBnPBb04CEgCezKFP8jIu1oaYPoF1rAk2ySMAPzwnjNcBH/CX63Qs+TQ2mCPrwe3IJ4/2jIV89GzA5nGSz/oQUxf/GBPrwr2JZvDD5faP2GMgxh5tCVxTThsCZQ5uYzv2LbVHXddzDMBlXd3OMfaxQb++xyhjndA0GuO+oA5rwxp4Xm2DGDvYp66hXb7c4yHGBr7RhjU21KMN9zR98Zpp6tA3MV/OSOeautz36Ule+gfkGp7z7GA9GAd9cj8Dee0D42ZNgWJeJ/ri1DsngV0PiEZ/lJGHj1wz14BS9InGgYKU+wQn8Bc4CySkD14dTEyf6dqhY9phk3x8oQ80hG33TX9u53VmjNjHNuvscTA39IXP5KXBfTFGdO0xc19zzTxjn76pS+D5w72LHXzAJ+5pxkjMaU/GAWTlGp8oAyxil2ueF9TjWUR7As9WbOID1/jNs4w8tMRc0T9Q3nNjH3yNNnhu0Dd64J4GPKJXytAFfvC8pS326I/15wsBtGO85ANdOXHLc4kynqk8L+kL/eC/n5H46zniGYtOsM9bEdCFx8jYGYfHSD71iOmPOeC10awXc4ZN68Wnxa0pvoCANrwGzBX10TnjQINAWXykP/fL+NCi59O+8Sz2FxSwybOLdeLzFNDNvDMv/E4wGqed+yZGL8y155Vy6q+GEJB3cVB2uSF2QN7+v08yyAvY9Yldxz6VO1ucP62bvw4odGSg0GqZ14C8AXlXi1ZX0s+AvLE5uJTNwWgTugkNhAZCA6GB0EBoIDSwOjWw0pDXG7ls8AL12OAFjrHhzOYvAXjk1/V6I9jt5orZlCYAMVK4w8Y1gQ1m2pNmI5p65HGdbjST9jX9s+mPT7S1DU5cARSAQ+RRHxABdAUasGHvV4jSDjtpAALQ1uOZbZwASWxSD/v4TVv7hw9sPDMG22AuKffpSiAIEA4wwGY+kAxwRf/ADOrSFhvUZcMeYAAsABQAg4gNDbgGDvAaWgAGvxlqf7BDv8ABfGYesOVy5oo6rDNlnns2/QF3wB7a+jWnnKbDZ/QAQDn77LMziA7UI48x+FW1nkti4BFapy+C19mQ1/mOPQe0JW1/gTpOU4a/+IpmSXvtsYNGqAtQoS5jBJCk7clHm3wRgPqcDKQe40Q3jJU62MA+c8L6GoCz3r5fsAMoxw5p1p2YgE0CdYHu6TzjP5rmXiFNoA/y0Bh9Mq9co3PKGAP1GQ/6A1DRL/cQYMxzTZp1oo1PIDM3jCkN2MMGdYCszKPL0SRpt6OMvrkmjX65t7DhOnwpBKCWtgNaMQfUoa7bMk/4TgyYoh0+05Z63CfMGdecsEwhL+XMAdq3z8RoFiBIGwLwjjmnb2Lbpj3gi9OvvBKa05KMn3wCddEoa5C2YyweB7aoQ0y+15D5BNoC8JznGB8ZC6c0gZdARCAs9y718ZfYgWsCJ9/pCzCIP9yzzBtf3gBqArfxn9jwkL7wlecAQBI/84Gx8lzjlcLU59rj80lVtyGfwDU64Asero9P6MEnxrl/WFPWjOcDtmlHTEC7zD/j5EQtY2M+eI4xXsrwibEBKclH29jgnmRdWGvewECa07z4gD/YJJ9+mDfuZ9pRRh5jYD38BgTs0rfHzdioyzPHwN1jtxa4JznpyzixSX3uF/omTX9ognH52vXQLdDdbzIA7lKXmPud+nzeAL9J0zefBbSjf/zCR/rmJC95PLcYA89j2jBvrKvHwvOcexwfmD9s8hlm3zw/xP0c8JfA+o2MjMx7mtdw06d6fR3x4UHiw4W8/n1e7LAWrCXa5HOOe8G6RKf9rMd+9i0gb/PYhrFHCnAF5D0U8vKBSjhS8x12V+d9HJB3dW7OxaZqrFtoIDQQGggNhAZCA6GB0MBSNMDGMhtZK72JRf/2AXAFrDKYIs2pPDZUF7uZhU3GiC1vvgOcgACU8W9iYAcbzWxEewPcm3v0Rzq9BnwBhSizz5R74x2b2KHMeQuBvGyMe3y262vs4x9ABTBh25ya8oY6eZSzOUkaH2gPBOGa9sTYAhICQ4By7gNfCfadeoAfNvBJM2+AG4AaMTDB18A82gI5mBvStME2wIyTXqTpE8iLH1y7Hie+ADG+phyAgX1DB/LokwAw4nTlq171qqxPYASBfNaWvrHlAPRgrOSngXzmBxCUBgCZ54U5Bmx47pxv/9El8w7gYB4Aa/QFHEzrokHseF48B0BY28ZfrgFC2OCUHDEQDT+ZP9bBfXt8rC1pfAXkolHy6IsNa/tBHutLoD6ABv0AYrgH8BlAyppxTQyUYU2pxzXl+EDALwJfGgAQEnO6EyjFmOiD+5lXN6MlwJB9ycdAToLHZh+ZA9aW+8pzRmw9MyeMmTHgv4E5fjIG5o0YPzj9bRv4RlvuJ/rkOWA94y9zh5YYEzbQBM8h2ngNsUF7vgBBGtvo09fYxU+AocE888TYKEPzaJ/5ZeyMkzlizQn4xCl35hRdsb7k04/HgS2/8hfA5sDpVwKvawZEpgGf8Bdfscn9iR1sMjbWmpOh+OgADESXlBNYD55rwE/Gi7ZJ47N1ZriI3bkgL33gA+tEW+zbF0Ne92t/iLn3WG/uGT4n0AFp1o3xAdpZO+pQlzFih7bYZ65ZX9YVPdOGMp4FzDtp6vAswi/GwPpRj/VgTplvYDBAE21Qhi3W3D6TZp7p3+Oznq071oJnGhqgf/oij2tirvEDn2wDe5wa5ostrA1rwL3HvKNXB/ThtCE1ffDcoi1j9ZzzvOU+9zwY8jIuNIDe/RlHHeA54+f5h24AxMwZ8wvsZ/49r/jH84gy5/H88JpgL01z3Y/B64qmAINzhRTkBuQ9PKibziXpgLz9eX+k9+zAUl/PnD+5m78O6LQ6odNyrVtA3kMhL38MEJZrfsPO2ri/AvLG5uBSNgejTegmNBAaCA2EBkIDoYHQwOrUQL9AXjZN+fcpm79ASoAHm8NsGrPBTVm6cTRfOt0oZjMeAEAMlMAuwIm+qAcYAi4ABOjHG7juI70mzUY7IIFybDimjGs2wNM05UCa9GSfbTtmHXx6yvaI3Tcb4thwHfrxRr9PCLOxzjiJactY8BW4BXxkQx8IwvhJMwauASAEwzz6ZAzYAAD4lBZAihOLQBd+W9Mx0BYoRn8AAkCax0/8yle+csZvxsCpX/KBBQaE5LE+jMub//YBex43PrtvwAIn5AiACPzhZBohnTv6AuYyB6QJlBOAL4AI2qYBX/CD+WOuCMAJt/W6c00+PgJXmCPmzGnXp6885LUPjAltsI7EXBvysSaAIyAU9X0f4Bs+YJ88+0p9TlIa9AOb0DcAiDrUpV3qP/nACuqxJlyjIfRFTN/ch9aV/aZvB/LQEnGaRz8eE5ApLbMdYsaL7/jhfI8Lf9BsCpcoIzA+5hodsWacwmX83M9ALNKcpiQmMA+GTPQDQMYuftIekIYNxktdfGIegL/0wVywHrSlf2LG5S8uALo4rYjOPQ7GDGQjxl/fT/gBHMUm+gI20gbdX3zxxRn0BHzSllPz6J1rTq97HvGb+bF9r6ufQWjepzrdhph+iBkb4/cXOcinDeCSZ6T9wTdeA0xfjJt+6IPnKc8cTrFi69xzz83mGaBNnRQeMre+N7GbBuaCPrHhfI+F+xKAn8/Hf3zAp7QM/yjDB+ab+4l1IY9gHdKGPgho218YwSZgFVCKbdadE6zoh/bkeX4ZP3bwm3zKsYd2AOyUkcca8IzvdDpZXdfDDs8OQD/zyKuUOc3NswLwjw+kKQOw8myx3x4noJn54TQ2J41pQyBNGfnow9eMhX6xg8+cUk/XCYjN85ZyviiBTx4HttCH+wZQs6aMj3uAdp4H2qAHbDBeB/JtjzzXz5e7Xj/G9hV9zQV4KUvBZEDe/oe83Bs8jwhoE/35WdSPWux3nwb8euZ8nH9Ncx7izncdEGptQKilrmNA3oC8S9XOsdQuIO/q3JyLTdVYt9BAaCA0EBoIDYQGQgOhgaVooB8gLxum3khjM41NNmJvsHHN5jgby/NtaOU344BdnOpioxyI5VOe1KOMTXNOIrHxD0jitFXat31zjE+GvM5LfadtPp9yQ17KHNKxpJDX7V2PGL+BaIALt/NYmRfmiNObjBPgQBn5ACkCJ6gA57bNODg1BrigHZv1gA768DxjA4D2mte8JstjrgAu9E97rw8AgjkkH8iLD/aROkAvoAc+AouAAaQZMwCaeccX2rDOhl22AXTAPv64T+oAvoBT+Mwro4FIHp/bOjZkcblhEvCDMZKfBvqhP+oB/ABFzI/bY9f12QxmDLbpfOozl85nXlgHj8H1yOeLDIBExgDwQ4eAKSAkNvCFPmnrVxNzTb77AGwCbOiXMuaSciAeEB+QSr7b2aavKWcc3BcePzEQkvknbZ8dk5eOD1+4P9AV+fjC/DEmxud29sMx/QJjU59cRhs0TB36S/2gD/QLHKYtdWlHn/ht35xPW2zRF/U4sch4qcecsw60Ix9wxhqgVdrRBmBNe/tGPvMLmAOKAvbom/48FtpzD/BlBHQIQGSeqAMUo280zDOC+fL4qEOak7hA1BSAY9vl+IiO7RMx5fTLfQfAoy6BfAf6xz7zx32EH1zThvuSMfE6Z56b2DDkxC42qIvP3BseL88Y7mt8oD/aUZ/rPOSljX3mdezcz9h1nuM85HU+/mKDmDEwD6wfzwa0AoDDd+aWNcU29SnDhtuy/pzC5ZXZ5FMPX1kr12PNgdB+1bn99Bjom35f/vKXZ/NCmt/VdZ/YQl/MGdCT2OPg+eaT42iML524HWCWujxjgLM8gylzYE2YY/tNTL9oFy15jNTxNfbsN2meJx4rdRg788XzAEiMT4wH/aEL5ou15ZkCTAbkcm+nn02eN8pYA4+Vft03eYyL+ybNc91+jj0OnnUBeZcX3KZQfL70cp/kpT90jC4JPFvQIfdbP+uxn32bgbyLhbrHEoiJsS4eWAfkPRTy8ocWH8yhpcVraS3PWUDe2BxcyuZgtAndhAZCA6GB0EBoIDQQGlidGugHyMsGlTd5l2MzLbXBJjbQJYW75LFRzQktNsNJ08anCYE29sebZ74m9ulO57kONhzSPNLADwARbewf/x7HF645HQVI49/prkNMYBPc0II2bu++fM1mPePBpgOAg81KIAgb9cAiYjbr0wAgZIOf+vRp/wGgACCuAR1ALGAD8CENvPaXDVGADyfTqI8PnIQEFHFNOSddfeox7z91AAycbsQHj8Eny2hPORCDk2+sEzHQhDXhtzOBCj4RjD0HYAT1fe0xAsc48en8NKY/+wjQABrRzmtEXdvxGrg9+WmgHBhuyEsZ4yNmzkhbD6wBWkQT6MY2KSedgknssm6sH6CcNgTADJpnvhgfugC0pmPy2GyfGI1yv1CGT+RxstUnqV2XOUBXAEHAGn5in8B6cM19BbwCBKI/fECj2MAPzw8QCJ3gP3Vpyxixgz3mhznhHkC7tLMfs8X4yxy4D+qRZq7wCSiHD/Rre+gGWMUccC8aZjEXtGc+gF/cB85jfjmFzilQIKHH5/7cv2P699xiz/mMj7G5jHyXc8+xlviLXWygBeowFu5H4CKnfFkr6rktYNEAz32lMWPkvqAt7QgeG/PBK5sZH6dIOUHMvNG3+8dnyjgRnwbgIHPLnGCPwFz5JC8+eE6xQX3uDde1D9Th5D7r6frE9I/++BIE+iGgG+aJL6zgO883tM8cGOzSlnvZc4R+eT697GUvy+aVcvtqeGpf0QVrwZxTj7ng9fTAaZ6FpNEwWqctvmCL9jx/+Kxl7ZhrvlREGfPPlzwYH2X47jmjHSdnifGXk9TYZ23pnzzGBaBmPrDFZxo+Yot2BNJogHLakWe/eKZx/7J2ro997j90xf1IPqeKGSeQmWvsMP8E0vnA8wE7ecjreu6LOUT7/gKBy1dDzBhYa8YKbDTsJc1vvfo6f5p3PnAZ5QuHxssJebHF3PPlKHTNlxq4x6z31aDJfvQxIG/8Ju8RAY8BebsPLH9g8O0U/hBYy8AyxrZ4gB2Qd3VuzsWmaqxbaCA0EBoIDYQGQgOhgdDAUjTQL5DXm1NsPju91DjdlCPtDW82nfk3MKCTzXE268nzhjdpNuaBS6mNvB9s/qWnVV2Onbz/vmbzHQDj/mjDBiKb9oBPAIXhgfsm5nWgADw2422LtqSxRXugE/bZmAcy0Y5xAgwYC2mgAjCFNn5dKfUcgKTMC5v5zqMfbANPSWMPf/Cb6zTQHqhDXcAcZWzcAz8ALtjEZzbFyQP29AqcHsQO7akPOOE1tcwNAUDMmF0O5AUe2hfmkfq+dmzI4rERUwb84HSe6zmmb3TDWBkzc+cxUMft0/r5NHWAIqwvsByYwdyzBqyJN5A958AowCRQE/jENfCK8WKHtcAWkCrtH5iFDQJltMFnNAFYQxOsAXYMcBlfGrCHT8RscOMnXy4AkuE788r4aEMdxoCv2MM30jxL0KnL0B5tPV5gInn4ZjvYYv2wT19AVHQG/AFWe6Md37CNNtAa7eYK9Ms8oBm+gGD9AAW597GFHeYO/7jvGQeQl/5ZK4IhM2vCPc+9aMhLDMyjPnPDXHOinC9FAA05gQqg5HW3pNEqAI/Xl9t3awbb+Em+gS065vdW+SICJ4Ff+9rXzgTWFl8BcTxX3D/X3EOcBuXe8T1Gmr6B0UBG5hf94Z/9Yh6YM159DtjlBD/rAhxkvni+AGP5sgJ1uT+I07FYU/gDlETHHiN6or+0PnMMJKbM9fIxc8k60Z91Q7+k0ak1x3jIZx1YN6AsvlMPzTE2xoNm6QM/8M/Ql/aU4yPzxJzTlnzqo0H0yTzQFn2iR/rhGv/QF+24F+0jZcwbkJz1YG65x7gvmWOeh+SxLqwda+hXc/N8Ip966AAgzZdc8IdnKXOMDukbnQGFuRftM/VIo1NgJGli3+t+VTT9YwOdkKZ/6wr/mQe+eMLr+nmVOHn54Dkl37oA8nLPU5aW+5p54P5hnewfZfTnOv0c80xjDPjI22iHh4c1NDSUhYC8C4e15hSLjZcL8tIvtlgzDpxyn7Cu3BPWcj/rsJ99C8gbkPeIgMeAvIee5A3Iu3gAeixA44C8sTm4lM3BaBO6CQ2EBkIDoYHQQGggNLA6NbAWIW+64cWGs6+d5tQUm/vepKbcm+LkGSK6XRqzOU5dYJvtOWZjOr857Wsgm+Gq7WHLQAt/AFqU2R5p8rzRSIw9+verMQENABvgA3G6IckmpU/HAbSAQthO7dsX7AAygS1pOaAW8EEe9rBPcDvHbNIDV+gD6EI+fvJqWjbvPQ/kASEAemmgLX0Dmm2f8QJgAXAeV+o/NoE3tCGfa9ezX46BPsyByz1GIA33gOs59jozdoCh551yt3VdYo8vnzbkBcSw1syFfXXsV8BSjvY4WYc9ygG9aAfAQswapyeS6Y+1Y22YW9oR3A/jtW+kmSv76LqOyXd9bLEerBE+oMNe4yaPNg6sGXYYAz6TJrgedhgj9tMy9IwN8uxPGtuGgVpa1itNf6yr54wxOOAD64tOuW+oSxlzk/pFn+mcUo/7Ib1HsE++65JG36wpc8D8cQ8QaEce5dRzO9pax/jFGqMF+861g/O432jHXNKGNPOATcaE7nwCGoCM/qmLD/hCPerjJz5ijzy0BXwEIGKTYC25nLkinQ+uT0wZ9w6+eV2BhgbZlFMP4Ip+8cXPN8r8zLAda4Z62HN790k/Dqyr73Xq0oZ1ZO4Yr9vkbVCP9WWugOg8kz23tKGcmHbYtR/4SuCazwXWl3bUJ1Afu9aC1x+fyLcuib3OpNEAPpBHPWLyycMP5osvL5Dm/ufLC3zG2EfPB/0DW6lPOh0T8w+Yxi7tWH/6op59Z1y0IcZnTrm73HVomwbyuWbN7W9aPl/a7eert9Llhrw8UwjooFQqxUne0SMPeA1mF/tvD05Z54NtAXmLxeLM/ezPVd/rK6231dj/QP41zb4G0qXhWAAuMcblA3EBeQPyxv00//0UkHd1bs4t9g+bqB/rHBoIDYQGQgOhgdBAaCA0gAb6DfIuxyYWG9C2k9+co8zBdRyzsezgPMe2yWY3aTb/vFnu2HV7xXk/3A9tCYYatHVfvezQLrXlurZH7DzsOr+XrTTP9YjTfNK98vJ1uKZffHPa7cjDF8pn84nxAyEot23q2yYx+Xk/XU4f7sft05h6gET75DLa2LbziMmzz9RxXhqn9fN2XWb/iNMALOGadsT0RaCvFHZRbh+JuXagD+zQLs0jn2v3l/riMbl+Grud82hPHv26b9syMGLdnEcdp2nLtW14fMS0dT1i+0Sa8RDjQ1rHY7G9tGy2NDbwjzb04XTehq/xC589JvJdls6J/aXM848P5NPe80Ab8hy85raZ+u3xErscf9K+qG8/XJ88+uOamLYuczq9tm/YdhuX+9r9uz+u0zxfzxfbN4+Ba89Xao9+00C9tG06Lmz1qkuebbsONtK6pMnL++3+XMb6U5fXttpPt6EP8tMxpe1pl/Zvm8Sz+eK1cF36sgZpQ5/uw3PhOvaL2P3ShvpcO8/9U8+28nF6f6T1SKf95tul1+kYyadt3pbz8rHt+AsMvu7XGP/5EhXzxhoZ9OI/+6qAxMHBwSxe7AnVqL8wSLycJ3lZL8Ne1g/d8XcegbTvgX7VY7/6NQN5U6BLOgDN/IAm5mj2OQrIeyjk5YOIEJqZXTPH4twE5I3NvtjwDQ2EBkIDoYHQQGggNBAaOHY0sBYhb7rZNdtGsjfC003p2dKpvXwdyvJ56bXbOs/Xs8X428tmr/rY7JWPjdnK8vVn82uh7e1r3q7H4fzF2HObxcTpOtPO43K8GFvz1c2Pzf31auf+8+NPbaRp26B+r3yXz9Vnr7L5bKVt8r6mfc6Vdh+OXbeXvV55rp+2J50PrnckYvdt/9w3fZHnwLXruiyfx/V8wf24Xv7a+WlfzputrssXE3tcaUx7X/fq33PTK8733at96r/7SfNsI23rcte3j47JB8a4nvNTW6m/zideSL7rpO2Wkrb/qZ+2k47XeXPF9smx67oPXx9O3MvP+ewttE3e78WOfz4/lrPcvjoG8mLfABDYC7QH+BLDIQx747d5FwZuFwO4jwTk5d8/2OX126yrQS/rybr7vkrj5dTYWrO1CiFvS80mIWBRP89BQN5DIa+/1dXPaxa+Hf1nSkDeY2dDLzZvY61DA6GB0EBoIDQQGggNhAaONcg72wbyfBvSabv85t58bdm0c5v5NvC8eex6C23n+v0aL2SODsd3z1u6TodjL992Pv/z5V63NE5t2l/yevmct5e2XUg63979OZ7LRr7tXHXTsl7jSMvT9GzzQp3Ujv1N49TOcqTz/c1mcy6f3Sa15bxecS9bzutVf6F2e7VdSJ77ni2ez0a6PkvxNe0339ds9miT1rUN8tKyNJ3Wz6fTMcxVNps/+TZzXdvXXr4txX4v393HXH7MVZa2d9rxXO0WW2bf3W4p43fbIx3bV8eGvL4GCgJ6Oc0LHCTmmlcAAy/9O72LAZlRd3Y4vFyQFzvAeNvznJfL5ewZY2jPmnIPWKO+H9L4SGtwtdkfAMb1Cv0JfAx4HR99KNOf89J/8xCQNyBv3Cvz35cBeWOjLzZ7QwOhgdBAaCA0EBoIDYQGjh0NBOSd/7Qdm2re1FuuDTZvCs8WL1c/x4qd/Dwe7XGzyZv2mW76Op2WH21/j3Z/6Vh7pT0n+Xmjbt7XXte9bC41D/sLaTuXzwtpn9bpZct5ab2jlXbfs8Xz+ZFfo/nq58vTfvNlC12ftB320uv50vP5P1/5fPbz5cs93uX2D3/tY5pO8/JjWuq1fXd7rp3ut9i+Ok4hL74yP+krsoG8/L41vxNNG8PDiGcHt4uZG0PZxfybBZibD4a85GMLH4aHhzMoTxmnev1Kbk70Erj2mh+J+6LftL9Uf5YN8raaTREeDHYMZPNxr7rkuV6+3PltNZsErvN1VtO1x7PUuL/HGpD3UMjLq5r58Fndmu1vza3GuQ3Ie+xs6C3mD6GoG7oIDYQGQgOhgdBAaCA0sDY1EJA3IO9SN+/6qZ033R0fbd/Y5E379KZvGqfl9tNxWnYk0u7H8ZHoYzE2Z5sXbNjHueLF9DVfXfqZrw7lc/m8kPZpnV62nJfWO1pp9z1bPJ8f+bWar36+PO03X7bQ9UnbYS+9ni89n//zlc9nP1++3ONdbv/w1z6m6TQvP6alXtt3t+fa6X6L7avj2SAvJ3rxnXqA3vT3etmHz4NMv8rZcb48rntD4SMBeQ2AmXPssyYAX9KsHad5WU+f0rZGF/vMcbu1Hs9A3sUDEn63txtazUYGeLug1/kAIQNMg1nHzs9DI+c7bqoPMqtgAAAgAElEQVTRIrS6odlW42DoN8ibPw0993y21GgypvbSwsy85uevf66PFcjrBxIxD6FegYdVQN7+0ebc9+bR9TMg79rcvItN2VjX0EBoIDQQGggNhAZCA6GBXhpY65DXG61rfSMtxrcwWB/zFPMUGggNhAZCA0vVgAEvIPess87KQO5stgzFDQA5AerXOLP3yn69T4zGq5x7g9w84PY8ETN/Pn3b6+/b2fJSbtIrnecoeR/QQLqWPtWLDgDBs+nhWMwfWDrwqKvZ6oZWs652s5kFgG8X/gJLgLUGu/mYsjxQSesDQZuqZ6Gleqs9E4CjKwV5DXPzvjvfcb780Osu4E3HtJj0So7/0HHk1++B64C8DwDfgLwP6GKh+jlW6gXkjc2/2f4QivzQRmggNBAaCA2EBkIDoYG1p4GAvLHZfSxuPMaYQ/ehgdBAaCA0sFgNLAby2rYhLzAQOMgpUGAvQLBSqcz8Vi/gcmho6EEnffOQ8Vi+7gfIy/zDmAx6WUsC2uBAndc94q1aIuRtHAS8NTVbNXUhb6Mn5PXJ23zcG9JywtWnWwG7Xchba7VUa7WzAAxdCchpeEvM+8HzECotJ50vP/Q6IG/6TY38NzlW02ZG6ns6pjQdkDcg76H3/wPzEZB37W3crabnV/ga+gsNhAZCA6GB0EBoIDRwdDVwLEDe2GiLjfzQQGggNBAaCA2EBg5XA4cDeemb9ins5dW/QGBgL/v5QEz27A0zj2Wg22vsnhdiOAdztth/N6TcpFc65SekUz/cPzCetvV6XZzq5neXzzzzzAz2Hq7G1lL7w4S8VTVbhJrazYY6zbo6zUl1miV1msWDgfSDw1SzqKnmRC4kbVpFtVtFtVoTamVxSa1WRe3mpNpNwPJ8IPUBkDIbYFlIfh7eptdpe+c7D3hD8PWhcf9B3vnB9OLmE3udTif7VgVx/qZNr/M3+WIfGCtZP/U9HVOa5gEVr2tenH4OvV/WbtuAvEd3U20lnxXRd6x1aCA0EBoIDYQGQgOhgdBAQN7Y9F5LG4oxltBzaCA0EBoIDRwpDSwF8toXv77Z15wENRjkdC/7zuzdGyQSGzD2ynPZsRSn88BcwUAW+2+ZlJv0Sqf8hPRs8+v1wQacyb+97PWNeMknefmd3LoarZoaCeSdala1tT2u6fo6ndZZp9M7J+r01glZOK15/Ew6y2sep9ObAw8KpzWPUzecoFObx+uU1kAWTm2fqOnaCTq1NaitrXF1mtVZAOryASGDW2K+LeAAmMmLp1qtZsfH3WZuSHX4kLfRaB7Sn/s9EvHcY+k93/gRkLf7ymYeUAF5e+tkKdpaS20C8sZG32L/QIr6oZnQQGggNBAaCA2EBkIDq1cDAXljMzy/lxTXoYnQQGggNBAaCA08WAOHA3nz88kJUOwR+9W/gELe1gpc5Pd6iYGJ/J3tvBR0GjSmIHK+8rTuakunY2M+lgJ58/9m6QV60zz6SYPnzHlcs1bFYvEQ2Au49xr7t3pZ57wO1vL1Ek/yAnkBlV3Yy2/zdpoNbW5V9OLnPl1XvuVlet+bn6/3v/n/6Oq3PFsfeOtz9KG3P0/XvuNPDobn6cPveo4+/K5n65/+7jn653c/Nwv/ctnz9C9X/Ik+cuULdN17Xqzr3vMiXfe+F2Tho1f9qa6/6mxd/dYX61GnjWi6WTxikLcXKOWm5zg/sM7CQTwOHP+nDBAMhOplAxBMeQZo+V3h9tSsodGeEqFXHV5p3X3dNSeFlxoeDN3sM3D2cEFaQN4HHko8gALyPlhvh6uxtdA+IO/q3aDL/6ES17GWoYHQQGggNBAaCA2EBkID82kgIO+DN3HX8oZbjC3WOzQQGggNhAZCA0vTwHJCXtsihuH4t3qJyYPZABINFYlTyOl0Wt6rTr58NV97zMTMTT9AXuAu/gB68Qdex/3FKW1e42xm5/U+lu69JULethrNaTWaU2o0W9mrk6daTW1pFfW6Vz5fd932AW3/97/Rdz9/ob7zr+foW5/6yyzNNeHOL5ynu/795br7P/5C93zpbN1748t133/9pXbc9Art+Mq52nnz+dp584XacfMF2vHVc7Ow65ZLdOBbb9Der1+q//kzZW1pjswKIgGMSwFAhpzEwFiEYmgLpPO3PSyUNHYZrwOgb9qlAZsAnSy0AbwdtTrTPUOzM6009KzX6qh1GAGQS5jx6eCrpaempjJAvZT5S9sw3jjJGyd5U01E+sGgOyBvbATOtxEY5aGR0EBoIDQQGggNhAZCA2tHAwF5l7bReyxt0sVYQyOhgdBAaCA0EBro/qYu7AXmctZZZ2UwdjnmBXvpb/UCB88444wMFvYCtynsnC+9mqFu3nfG6rx+gbz2ybH9gzlwcpcA6CVGO+jF/G45tNPPNg4T8m5Ws9lWq9lUq1bVQ7ZM6g1/9RztvP2DOvDNt2n/1/5G93zpYt3xbxdo581v1I6bL9V9N79Z9978Jn3vP1+p7/3nRbrrxot1140X6Z7/ulD3/Nf5uvem83XfTedp/y2XaP8tF2rf18/Nwv5bL9D+Wy/R/q+/Wk/96SFtaQ5mMNVgNgVI5KXXC0nbDrEBL9/iAFT6Gx7EFki6qM4jNuzN98lR8Ve84hW64IIL9IpzztF551+ocy+YPZxzwYUi9KpD2/POu+Aww/k677zzZsK5556riy66SOecc47wNe//Yq+Zx4C8AXkXq5tjrX5A3rWzYRebr7GWoYHQQGggNBAaCA2EBkID82kgIG9s3Kd7SZEOPYQGQgOhgdBAaKC3BgznFgN53cZxr7l1GXYNfHl1s0+CwjOAmpwWnQ/q5ssNHddCbJBqwLsSJ3npOw3MK9e95pe/wVlbIC/rCehl/b3OpL32vXSx2vOWCHl5RTCv9CUAeVuaajW0pVXQ61/5LO3a9iEduP0KafsV0vevle7+uHZv+5T23/Vf0s5vSLu+qb27vq59u76me7Z/Qfdu/5zu+ub1uvOWa3XvrR/UPf99he688VLd8+U36r6v/q123kJ4g3bdSnijnvKzBU03Bg85cWpICyTy6dsUGLl8ITEneAG8iMDH9tOFRhDpdZq2WGhLmpOx+MEDAsB7ySWX6Jxzz9X5F16k8y+8uGc478KL5XDuhRfLwXlZu/Mv1PmzhAsuuFgOF114iQjnnHNelnf99R/XJz95gy644EJ97GMfywJ+3XDDDbruuut0/vnnZyeY07lbSjog7wMPIR488brmB59iXYqu1lqbgLyxETjfRmCUh0ZCA6GB0EBoIDQQGggNrB0NBOTtvZGb7qlEOuYoNBAaCA2EBkIDoYGUsSz0JK/bOF6sjgCDAELawzYMcQG+80HfFDwaTKZ5K5G2/wa2qQ/2MY1nK18OwMu/Z7CThvy/cdIy0qlv+TS+enz2e2hoKPu9XtaddSRwaJMAm8nrgjfyLlYj/Vr/MCAvvwsL4D0U8r7hlX+cQd59296jA9vfK33vH6W7PqUD9/yX9t/3Le3Zcbfuvvdebbt3p76794C+t0e6Z+8+7dx9l/bv2ibtuE36wVeke74off9T2rf9eu2+/Z+189vX6u5br9L3v3alnvGEh2rrVPcHlv264RT+cBOm16Rng7t+pXL+1cwc0wfUzrZws4mAfAfaIiIeEPTDadmLL75YF150kS64qDfgzYNfg13HlANwZwO85Bvw5mNO/1727it02WWXZ5D3sssuEwHIS3z55ZdnJ3mZ0/z8LfY6IG9A3sVq5lisH5B37WzY5f8wietY29BAaCA0EBoIDYQGQgOhgbwGAvLGpvVse0yRH9oIDYQGQgOhgdDAAxowkIPPHC3IC9NJT4LCdfhbzjAxhb1OG/4aNBIbSKZ5K5G23wuFvPY7D1u5zv9Nu5TrvN28jXy5/ekVzzWf1MeWX91MbNjrg5lr7V47LMjbBbxttZstdbLf5C3IkHfv9it1//bLpG3vlbZ/QPu++y/af88XtG/nd3T3zvv0jV3S9bfeo3/6xg596V7pjl27tWP3Pdq96y7t3XWn9u+6Q/fv2qb7d92uA7u+I+3drgO7vq19931D+3dt1113btfNN9+sq6++Wpdeeqme9axnzQkmU8hrsEsM3PXJ3fTVzDxIDmexDYGxg3gInJLdu3ev9uzZq9179mlXLpBH2JMLe/fsUz7s3r1Xs4UHtd+7f8bm3r371Q37Ml+6/uzR7t27tWPHjgxELwdsC8gbkHc5dLTWbQTkjY2//B80cR2aCA2EBkIDoYHQQGggNLB2NRCQ94HN28PZb4m2MY+hgdBAaCA0EBpY2xpYKcgLw/EpUOAgAV8Ah/yNDjwEmhryzgVS5wKRR6NsLt96gVNDVv9bxNfEzjucOLXXy2a+vJePad5cc8j6UJe9dwCv15LDmAa9xGvlOXLYkLfdfADybm6NH4S8H9S+Oy7X/Xe8U9r2bmnbFdq/7T3ad+c/a88PvqRt931PF//j5/T7l31WT7z043ry6/5BN3xP+sr3d+nWO76rO+68Qzt33addu+7V7l0/0O4svk+7d+3Q7l07s7Br1y6l4SMf+ciSIC+gt9ermb3Ysy20HzT5uFd96gB9OTELVL3/wAHt2be/Z3gAwu7Xvr37tX+WAPTNw1xfpzbStMu7MbC5C3eJCUBefqd3OcBaQN6AvMuho7VuIyDv2t3AO5w/eqJt6CI0EBoIDYQGQgOhgdDA2tRAQN61vSHdaz8o8mLNQwOhgdBAaCA0sHgNmLnAaI70Sd60L9KsF7Hf0GpAWCqVZk72rgbIOxcETWGp4ar//VEsFrPXHvt6uWL34zhv1/mOUx97pecaH2VuUy6XMzbHm3tZS9bV67tW7s0lQ95Go6Umod7KTvK2mw0BeV9/yR9p5+1Xa/8d79SB7ZdKt79Duv1d0h3v1oE73qf7br9WH/rch/XkK/5VP/q+23XmO27V+Iuv0c+/5gZ9ao90y4779cWb/kP/9sXP6Oabv6SdO+/Wrl0/0K5dOw5C3d3atYtwKOT9xCc+MQMnASeGQz7Bm57eJe38zZs3q9ermX0Sd6EL7YeB417tOckLTN27d19PwAv4NZQFxHJSd9+effrqV76qq977fr3r7e/KoO8d276rz33287r77h/o/v16UBvpgTzby8ecJjbc5RQv6Z07d2anjdP58zwuNg7IG5B3sZo5FusH5F2bm3f5P1LiOtY5NBAaCA2EBkIDoYHQQGgADQTkXfwm70L3ZKJezG1oIDQQGggNhAbWjgbMWI4G5J1NN/hA/4BBTveeeeaZ2TUHBgGIfg2y0z45Ox98XIlyfEz7NQAlNlRd7n+vGBY7ztt3vuN8uf2aLU7H4HQ6RtLOJwbST01NZWv58Ic/PPuJVR/0tN5m00K/5x8RyLvr9qt1gFO8298s3f426TvvkLa9Qwe2/Z32bLtK137hWv2Pq/5Dp12zS+3L7tbxL/2Uqi//tH7nqm/pK/fz6ua9uuveu3T33dv17W9/XXff/T3t3MnJXsDu/JDXsMggl9ivZuYmrFQq2VFtQOxyLaDtOO618JzkXSjkvemmm/XBD/6Dtm//rv7hHz6sb3zjW7r2Q/+of/30Z3TFZVfqhhs+rSuvfJ/27OFVzMDh+2dg7/59B2bSebjLdXqS16A3hbyev8OJA/IG5D0c/RwrbQPyxmZf/g+YuA5NhAZCA6GB0EBoIDQQGli7GgjIu3Y2n3vt+URerG9oIDQQGggNhAaWRwNmLCsNefGDk58cEgT0EvskKH+zA3b9u7yGvI7zwPFoX6eAE1Cav87D0+X+N4jhreO8fec7zpfn/ctfp+NZSJr29AW34rXNBNaT2HojXo338BGBvHu2fVDafnkGdnX72w+e5n2n9J2/y36j9yP//iH90lVf1OnX7FDnsrs18LJ/00kv/XdNvug6ve1L92v7/dIPdu+feU3zzvt+oLvu+n4GeXlN8a4dh57iBf6mJ3kNiAx3fYoXuEsZD4f0hjSxP5wFTIUwmxgWAnn9Guc3v/Xt+s8bb9KV73u/XvfGN+lbt2/X12/7pt531d/ra1+7VdvvuFPved/fa8/eA/rO7XdkkDc91dsL7jqvF+TlNdKc5MVHz9/hxAF5A/Iejn6OlbYBedfuBl7+D5O4jrUODYQGQgOhgdBAaCA0EBoIyLs8G7+Hs3cTbWMNQgOhgdBAaCA00P8aMGtZScjbSyf4xclew8FOp5O9whmAa7jr+GhD3Xx/Bp95OMo1/y7J5y/3v1UMbx3n7Tvfcb48799Crj3muWKv1fT0dAbsOdVrgJ8C317r3695hwF5m/Irm9tNXtn8wOuaM8i77Qpp2zvVhbwHQe933iVtu1LXffED+uWrPq/Tr7kvO8k78LIvauDPb9Km//tp/ejLP6pP3S1t2yPdu2tf9+Tujh36/p1A3t2aD/ICFwFEBry1Wk0E8ji5y4PBr1L2w8LXh7NItuW4l63FQN53X36lvvHt7+ibt2/XN76zTTffcqv++5Zbdett39RXbv6abvvm7XrdG9+sd/zdFXr35e8VJ3+Btwa5c8Up5OVVzenrmgPyLm7jIX24zPbw4MHBQ4NXgx8r8DLG2VzQWgfkXdz9lv+wj+uYv9BAaCA0EBoIDYQGQgOhgdWkgYC8/b+p3GsvJ/Ji3UIDoYHQQGggNHB0NWDG0o+Q174BBglogz1ew13Heeh6tK9hFSm76PU383zlvdosNM/w1nG+nfMd58tT35aSno3VkM9aYNO/1+u1BOCzvqvtfl8i5AVg8Lu3LbVmQvP/Z+9MwKwqzrzPzCTGFZWG7qa779Lbvd0NRhOTOCaZTJJJJuZzzTJJJpOYuCRfYvZVs06cZOKuUeMKKgrKJiDiviIo7gsKqCA7CsaAQnffpRf+3/c7t18oDvf2RnfTDdXPU0/VqeWtt95669x769d1jqqjI3Ttxd9Ty4Y7pDenSBtu6gg3Sutv0NbXJ6h9w1Q9uHCOjp35jOpv39IBeZ/XP/5msYb/domKz3pSn7r4GT3xjrQ+A+htVyaV0ca/b1JzU0rpdLbgO3kBuwZ5gUxhuGsL0CZpoCdsO+RtCd7Ly7t5w2H27Xdo5m2365Yp0wKo++LLS/Xyayu1cs0bWrNug1asWqulr63Sq6+t1tr1f9fKNRv04uKluv2Ou5RxIG+2lff+7vzuX+oQ7J28Bnk5De1P8vZug8S9yeS7eXjI2z3guTeCYQ95e7fmwh/6/trb0fuA9wHvA94HvA94H/A+4H1gKPiAh7zd2yC2vRuLbQ/HYsu32PIt5h/5++Kf+U3e7o5tnIXiwabf7tZnsPVv/mhxWD/Lt7in5eH6g+3axmVxV/pZPYu7qu/Lu3df9XbydhqKPmCfe+9///sHFXQzvQDQPLrZTvZy34JHhWGuQV83DtfJd+3WJ52vjptnXMJlFaSHwnfk3ugYHmf42uzR3dge32yneu1ziJg5D68h8smzOFw+kNe7AHl3BjdV0aIA8ra+CeSdLL15Y0eYIK2/Tltfv16t6yfr/oV36P/MfFZ1cxoV43HNv39G+5/1tA795dMaceYziv/yQX35kvt124sbta5F2tgibfj7ZjU2NiuVzioVvJd3x0c2z5s3LwC8QF47vYuB7Yg1i84WoBk43+RYWX/EO0JeQO+OYfnyFbrz7nu09o31enXZcq1YvVZLV67R4mUrNHP2nZp52x3Bqd0XXnpZry5fo4VLlmnlujd10y3T9beN7yidQR7v523rALw7Q960A3kN8BIDeAkXXHBBt04gdgXkmAceV8AJVuLOFlN4AfZmUe/ONq7++cbJzZZTvP4k7873jK78aE8v95DXb0buznuX79v7n/cB7wPeB7wPeB/wPuB9YGB9wEPe7m2y296NxeH9Gcu3OFzOXtBg2HAL69Xbaxtnobi3cvuqXVivvpK7p8gxf7Q4PC7Lt7in5eH6g+3axmVxV/pZPYu7qu/Lu3df9XbydhqKPmCfL4MN8mJL0w3IC39ygz3C2cBsGNZavgto86XD7fLVcfOMS7isYm/9ru/awOzSVYy9YVo8ittO9hLbO5iZc1tHbtrydme8y5A3EosoF6KqjHGS9wy1bLjdgbwTpDdvkDaM3w55X7xTx8x8Xok5zYpO2ax3/e5xfeAvi3X8+FV63x+f1Af/OF8f/MUU/etZE/W9iU/r4TelFX/PaEtjs5oyWTUBJdM7Qt65c+eKd+8CTaqqqoKFxQS4cNcW3+4yeGeQl5O06zds0LQZM/Xci4u0dMVKLX51mRa+vFQTp96qv7/dqFSmTVsaM5o+83Y9s3CJXnxlhV5bs163TJ+lGbfN0UuLlgQQXJIyLS1KB6FVgF0LqUxLAIMzGU5Eb7ehh7y9/3Hf1U2Dm62HvB7w5gPWHvL2ft3trV9S/Li9z3gf8D7gfcD7gPcB7wPeB4auD+wtkBc4s6v7LrZ/k28TrbMy69cAUV/oYjK7G/d1n90Z767qZvbqrhy3nqtfvvly6/YmHbZnuA/Kw3luP+H2VlYo38rdmLoW3PzupK2dxeE2lm9xT8vD9fv6Gr3yyQznF5oDG5fF+WS5eVbPYrcsX5p6+fJ9noea3geGvg9wXyEMRshr/oV+8Cc71WvQF1DIXjDf2w888MCCj3I2kOvCWktbmcWWXyg2iOmyir31d4NrA7NLVzF2Peigg8Tjo9mzZ04N9hpntLku9JlnfjHQcZ9A3opYRBUxF/LOdiDvDdKb1weQt33d+NxJ3hfv1GdmvqDaOWlFJ7+jfX4zT2c+IS2QdPFz0uOS5rVK3564UGPOmqHvT39Zr2zcqi2NqQDwNmXSO0HeBx98MIC8fLi7z862hUZsYaCNbP11Bnk51dva1qYlry7VzdOma8XadVq+Zq1mzLlLy9e+oZZ2KduSC283pjVlxu16efkavbR0pZatel0r17yuadNnKJNpUWtrewB5U4DcllYBdt3Aid8wJPeQt/cbBV3dNLhB+HfyesjrIW/v19je+oXEj9v7jPcB7wPeB7wPeB/wPuB9YM/ygT0d8hqU6QvoYvs3Ftu+CrHlsdFm+ZZn14Xi7uhmsiwuJCucb7ItDpfbtcl1YyvLF3e3Xr62lmc6EVvayojd/Hzl6JAvn7aufqRduW7aLXPTbp186XC/1paYQLmbZzKs3K7dONzOykyOXRNb3bAebh2rF86jTTh0Vae75fl0DbctdN2TtmZf2lhAbtgehWR2Nf5wu67qh8cU1iNc7q+HPujzc7j3zqHdcwYz5MU/TU+LDfgCCDnhy8HE4cOH7wR6Dd4SFwK3lt+dOkBMl1Pszb8jXDt0BXfNbsTY22xdXFwcMB3mEd4I6DWI734HHQz3qF5DXo4uEyqiFTLIWxUv0jUXfUctG2ZLG26RNnCCF8B7nfTGuOAkb8sbt+i+F+7QMTNfUGJOKngn7/6/fUS/eqxdiySNe3KzVkpa8/9Po541+SnFfz5LJ09frcWbpMbGlFJpHtncpOZU87ZHDAMoeVwziwYDhz/gbYHtboN3Bnnb2tp05113BSd5F72yNDjJ+/JrKzRp2gxtTrcEkJeTvM3pVqWyWzVt1h1auvoNPb94qRYuWaopt87U9Bkzg0c1A3rTmayAvK3tW9XMI64d0Oshb99uFBS6adhNmJjT5f5xzR70hkGvP8nbt2txb/7y4sfufcn7gPcB7wPeB7wPeB/wPjD4fWBPhbzsxbj7LezJsA/Db2Bit6y7adqxv2ObaO6+DhtsrmzSJpf6Pe3ToJLJsNj6pL9CdahLPdPB6hGbnibPYvItbX10Fltdt53lEVuflocs5gSdCJSH61ke/5DultGWa/qyeXX7tTmhnsmwft2Ycrcu1wRk2ZxaffJMT2KT7epPmnb0SWzykGF5pMnnd7bpxrX1E46tjunDdb765FFGMD3t2vrn2vp3+7F6FudrbzKsXViH8LXVKxTbfFmf4XrsTyHTlWtpyydm/l0ZVsfkhcvMjlZObHUsdsusL/LCst161tZiK7P25NuYO5Nj7Xy89wJDP/dDb+5tnQ9WyMv9B78yPV0f457IfRQ4SMx9qqSkZBvoNW4AUDQAbHmF4jCstHqW7zIK0nv7b4OwPcxOPYk5hQ3sZW6POOKI4GQv88mc22e6+YA7/wOd7hfIm11/286Qd30O8mYDyDsngLzJAPJu1gG/nasvT1ikWaukG574WwB535D026nPKHLmvfrS1A16caPUuAWw26hUaotSqaYdIe/8+cGCYQHZAjNjDpYP+c4gbzab1YyZM/Xq8hXBCV4e1/zqilXBSd4lr61Upk1q2yqls+3iJO/1k6YGp3gXLVul6bPv1NPPL1Qm2xpA3uDdvG1tAeS1k7yA3u1h58dd+5O8vd8QcG8Y+W4S3HA95PWANwx4ufaQt/frbm//ouLH733H+4D3Ae8D3ge8D3gf8D4w9HxgT4S87v6Lu/diG55unu3RdCdGrgv2XHnf/va3d3iCm222USesz3e+852CkA898unn9kUaEHrCCSfon//5n3eCVvRn0MwdF3tT//qv/6pjjjlmp/6/9rWvbQNo+fp35ZCmD8Z4yimn7KSv297Gjt1OPvnkoJ3tkVk9q+P2YXUos3psZP7Xf/3XDrpTRh2bF2Kr78ojzWa2Kw8b0g8ysZfVp863vvWtQA7pL3/5y/rYxz4WtOWacVs/5H/qU58K5JBnYM/tx+S6saujtaON1SGNLHSkrsm1coupF9bd5FjMGN/3vvfp2GOPDWS5fVPH6plMYvzkM5/5TFCf9u58kDad/+Vf/iWo47Z10ybfYso++9nPbhun1UUnN3zgAx8I1hN9WT51jzvuuKBtPp0pt34+9KEP6bvf/W6gt9sHc/nv//7v2+pZfVce/XH9la98ZZue5KHLJz7xiSA/Xzv6cXXFL7C7+QptSGNX08nHQw/w+Tnzc2brfLBC3kI+anpzL+MzBdDL45tJc28yOGsxPMHSncX5uIPluXzC0nv7bwWzgxPC8TsAACAASURBVMVmq+7ENg9AeDvZy14+30sIdrI3/NlZyCf6O79PIS/v5OUk786Q93pp/Xi1v3G9sm/crPteuL3jnbwpRac0ar/fPqIzH3pHExZm9Y2L79Il96/So3+TfjJ5kUp+8bC+NG1TAHmbtjQr3dykdAB6cyd5081ppZrTmjd/vuobGpQMfanHgCys/jZkd+R3BnkzmYyWvbZcc+66W9fdNFFLlr2ml15ZqsXLlmvqzNv12qp1SrW062+btmjqjNnBO3mfXfSqnnnpFS16dYVuvHmyXl22PAC9QN7mdLojZJRt5QRw15C3ublZ6MgJ7XxAqid5yOAl43xJJu5s8dhCs3io3YBMb+J84+Sm4CGvh7z51o+HvENvY26o3Z+8vt7HvA94H/A+4H3A+4D3Ae8Dg8cH9mTIy74Lv/2J2fCy0Jv9GGAmIJQNNDZDgUgAHyAfQAxwCzziGvBFbJtstjdDvx/5yEf005/+dIf9IPLdYO1MT7fM0mzKAu3Qi/rWhxuz98E1ddmMph66/sd//Mc2W5BHOOOMM4INQtLWrysrnDZw9eMf/3ibDZBtgccIIsfq0f5HP/rRNqCITrQlNmBmfZx++unBxjO6UIYcYiDv9773veDayoCxyPnZz34W2BXbooPJspj6zN33v//9bTogl/6BgQbFuaYuutpm6Te+8Y1gbqlPnoFX6n384x/X8ccfH7Sh7de//nWxpuiXsRNIAzYBjNThGlknnXSSfvKTnwRjQi90N4iJTuTZ2IgNzttYqIMcgo3TbIls/JW6jA2/QwZ1ycMfaM8Gv9ve5FDGOND/Bz/4QRDTjmBzyj8YIJM29GH+5upk+hBTj/bY1vpxY9ODOqyno48+OrA3G9fkIQNdrB56mFyTQz1szPiZF9pSn7rWN3KtPu1Njqs/cPbUU08NZNEemZTzDwGsO9pZMFnE1CXgJ/im+QJzSf/kY1u3jU97aOh9YGj5gK3zoQZ5XT/j/mX3Sz5buccRjJe4ENHAYqHY5Q4ujyDN9/18eXvz74CwPVz7dTfNXFDXYuaLz2EDvfa5ab7qxq4f9GeaPnsNeQ1YRGIREaLxmFzIu3XDzTs+rnnD9Q7kna1jZj6r5B1A3ibt9/vH9OvHWrRQ0jVPbdaCLdL4R1br2LNnqfSX8/T56Y16cpP0VuNWNacySjdzmpeTvEDfdBBcyJuoTSiZSG77IGeg/WnI7sruDPLyTt5MNqt3Gps0acq0APIufnWZFi1drucXv6qZc+7WTbdM0/RZc/Tciy/rhSXLtHjZKi18+TUtePoF3fvAw3r2hRfV0rZVU2+dodl33KHXVq4M3snbmMp4yDuy/37YuzcMu0GE8/iCyk3d1o2P927oC9zFB4j5kYN/cI3/uL5j6b35A9mPvf/uXd623rbeB7wPeB/wPuB9wPuA94GB9YE9EfKyH8JvXWL2XoB+QCNAIICJjc3u7plYPTbMADyAM2QCcoFIgDegD+AGkEewfNqYDsT0S/vPf/7zwaP1AKEWgG0EIBDBNlzpi3YAQDcA137+85/vADcBhhYMvll7IC56fvKTnwxOAFu/FgOhAFts9hLTzsZOulAwucBJNxhUNriGLPowmzDGX/7ylwFsPO2003aYE2yJHlbX9EAvZNjmNDoBhM2HucZGH/7wh7fpbm0pA24DZcnDpuQRI4MY/RkPcA7bEuM3+Az5nNamLnNDfQLyOFGNLOQChPkHAOoxRuqQ/4UvfCHon7TVpd2JJ54Y1EEmUBE4SZr2dkqbNpyC5mQobRk/dQDexJQTyLdAPsAZX6QMyIv/23wwHv4RwdqGY2SbLOsHwMqYyGdcyLR61t78z/VV0uhNQC/zTWtjMeXIxU+/+tWvBulPf/rTwj+szCAv/sF6xFdsjMhBPjoyb9TBv20e8BPas87M7y02HUx/dCRt48CW1MEHsJu1sxj9KCcmYBv8hzRrATmU49PY3vqzGJta2mQQW56PhxYE9PO1Z8+XrdGhDHnxUe47fCZw3+R+Scw9intmeXm5eCSwwV47NWqg1wWMYe7gfo8fNWrUXv94ZtcepG1f3WKzX3dj2lGXx2nbfBAfdNBBQT6fo/ZZyHwSyDO/Dd+f+uuzBrm7DHmjsYhi8ahi8ZiqoiM07uIzlHl9ltrXT5TWXxec4NX6cUHctu46tbwxSQ8vmqNjZjypujuaVD09pX1+t0D/96GMHpN0/TMbg/fxviXpN1OeUfkvH9TxM7L63i2v6Jq7F2pjU6uy6Ual001Kp5uVTWWUTWU1b96jqqtvUF2yXslE3RCAvFm1tO4YeGTz3Hnz9NAj87R89Vo9v2iJXl6+Onjv7pKlq/TK8jUifnbhkgD0vvzaKo2bMEnzHn9KEydP01ubNmvVmjd0z/0PasmryzTz9jl6c+Mm3XHPvXrmhYVqSmeVCU71ZtScSu3wuGtO8fqTvL3/gW83C1v84WsAnt3Qedm6h7we8uID/NcWH/IEPtRdv3HT4Q8pf937tept523nfcD7gPcB7wPeB7wPeB/wPrC7fMAAmQsZwhtAQ/GaDS7+cZUYWGagF2DXnQ0t+63MxpiNH1l2CpZNMx67amATKAScAvqSB/wzm1p/bKLSPwAPWARwAkYBg7imjJhrQJA91pX2BujQxeQBmNCPfgikCQBoAJXpbWUAaEAh+n3pS18KTgED0AjoT79ASmAjOlp7+sNPOKnMGA1mM1b6IbZxU47e1AGm0TdtmQPGCwA98sgjg3kBpNIHunAqmn6wMeCQtvwmpT2ykAsUBeqhP9fURWc22mlLXWBaPnjJfAGIaUOfXKMTQBiboyN5yCFgE/tdTJoxkU9b8qlLG8aNTxiQBcYyRmA6YJC6tPviF78YwH10tH+4B04SyKMOdmes9IFOduKUOQV6ItN04MSO6W55tMMn0AUdiGlDGj2xt80F/SCfxyKTR1v2ArAP8BTYjFz0NyiJDOaKPHRizvBf9Ke9G5DPPzRYnvsPDPgaemJD+rNAXeAofgLQJ6Ajc27gnn8MwD84wY4/oovbP7ozX/gv9sSf0RHZPH4ZWbSljID/GIC18SLPdDD9sTdjJp/21gfyGQ9r2/Qgpn/Ggkz8Fh8xW7POmRuumRtsYf1gC9oQLM/HO/qWt4e3x+72AVujQx3ymh1tPHb/4X5tn6u8rxeAmO/9vAYl/V7xrv2Gce2XL212tpg6liZ2ATzXzBXzxmcWny98PjGnzDOfTzbfFpsf9DZGZjggC3/adcgb7YC8sZiqIocGkDf7+swA8m5dP15af60M8vK45pY3Juqep6frhBnP6fA5Laq+uUn/9NsnVfqbR3TyjA3609yNWiZpFZB32vMq/cX9Om5Wi/75V7fq51fdobca25RN8ajmZqXTaQfyPqa6+jFKJupVNxQgbwB4M2ppzYWtW9uUyaS19vXXdePEmzXxlsm6avz1eur5l4JTuwDeRa+s0LMLX9YLi5Zq0Suv6ZXlq3T9Tbfo6edf1KQpt+qWqTM0afJ0PfPci+IU8JRbZ2jqjJl6+vkXNHHyVK15Y722cPI505IX8jY2Nurcc89VX0DIvelxzWwQuDcGd/FbPja1RQjcA+j1xWOxPSwemrCYE7wEfrzwQ4m4tLTUn+TtxxP3u2sjz/e7a1/AvP28/bwPeB/wPuB9wPuA94E9yQcAPLbx09sNnsHcjrGx0QRQAgABabqjL7+JzC5slCGDdqT5Hc1JF0Au0JQA6CEGPNljm6kL0KMdsgA9nNxEF/KAPbbxBuwBHJFPOYDMQDFt0RsdSNM3wWAobdCJ/gjIAr6a/uhAPsAM0IUO1KcdMhkrskjbHoEbUw9QBdziFDKgj7EQGDd5QEwLlm8wF2CI7YFpxLRn3EBHdATgAcvoH11NF3RmnABO7GFADRmMA0gGDKUfG2shyAtwM+hIP7Tl8cmuTOzGeAjMjRuwP7LpB3vxTwPoAMxDX3RiTAZ50Z02xLQBKOIXNk/EAF5sim1JAxyJsTfj4vQv10BtfINTrZQhD7mMAx1JI49rwCv2NZuhI5CTetgbXYHPjBtdie2UKjKwJVAXSGtrwMbBZjGgnJg+0Yt+aIdebghDXtrhk/yzAvYlbTFpfBO/N33tHw6Qj1/RnnGji2sD/MXWE/m0x5/QyeyELe0UOHOEnajL+OjXZJLHPggb4vRPDOigHmXMH/Yy25NP2nQzezFPjIk2lGN/2uEDzCN+xDW+wxxgK3TNZ0dk+OBt4H1gcPkA65Wwp0Feu2dyj+S+yucvae6LQMMwTIQv8H3YOINd70nfkQdiLK798qVdpkPa6li+e5rX0naqF87DXPLZR8x8WjA/7u39hc+scEAWfeE7hD6HvNfyTt4A8t6UA7xvXC29fo30+ji1rRuv7OsTNOOBGxT9yU0adeFalV/xlv7x189r318/r4PPelLx3y3Q/zwnPSnpRzNe08hfPqz/M22zjv/jrXpo8Zt6p7ldmeaMUs2tSqfalUm1KN2c0SPzFyhZP3bIQt5MJhWc7G3bKm18e3Nw4nb+gif1xDML9dyLr2jSlJl69IlntXDJMt0wcWrw6OYHH3k0iCdOnq4XFr8SvLd3ydIVemXZSj2/aPG2Rz4vXbEygL2c6uXRzZu3NHnI28cwyRY9sS1892YA1OVGzZdi/mPTA96hCWf7EqrjD/wwwSfwh+Li4sB3wh/a+NRAfND5PvwGqvcB7wPeB7wPeB/wPuB9wPuA94H+9YE9HfKy4cTvG2ALkA/Y1Z0NLTa/qEcMaANUEuzEKadFOSVpAXhG2sAvaTvdyYYaMAkYxOYXm2JARkCQ9cMpSWCbXQN/AIkGkugXfQwkASipYzrSjsA42ciz+vSFLgAm6gPMgLy0ox71accJR9L5NuzIA0QSGAsbd2xuMybGDdwGbAEXAb4AVeAl7QzCkaYP2vO7k74BfvRJHaAakBVdDCramGhDmnmgzIAgY0BmdyAv9jJobhud6ARIRSY6cG0gF9luQE/gJ7qYzdCJsXOqmLqUMW7mnXnCFviMtWV89EE9YuoxJuzKnBjMJZ+Tw+iMz1JOH6xV5NKW/oixP+Pnmn6QTdrGw6lubEt7/A1oynjxX+aRMSCTNtgFCMkawWfM1+iDvpCJTsiiL8aHzqYPMgjIdCEv1xawAfLNBsgB9gJmrY4bmzyzHWuINpbPGLAhc0se48M/TF9iIC9QFf9kDGZDyuiX8dEn7Qn8kwLzyvpjvZCHvqwh7El7/M70pL3VAYBzjR+hJ+vE7Mc1cmwMZjfWg9mDdcv6MV18vOM69Pbw9hgMPmBrf0+BvK5NbWzk8ZnAP7vwTzLc29h/BiK6e8I8jtnlD3xnd8v9d/iuv8O79suXdpmOy3Us38CuxS6MJ4854nOGz0vmlLkkzWeSfZ66PtDdNJ9hbkAW8q0P5PQa8tpJtNyjmnPvluQk73bIe6O0Hrh7VUe4Ru3rxqnl9es1bc5fVX365drv+49o2HfnathXb9ewMx7Vvj99WkVnPauKM+fp2CsW6jN/XaiiXz2mz926UVc/tkar3smqMQ3YbVMm1a5seqtSzVk1p7KaO3+BEnVD9yRvNpsOIG8my7t5W5VtbdOjC57Q1Om36cZJU7Xo5dd0/Y23aOGiVzVl+m36+9uNeuDh+Vq6YrXeeGuTbp46QwDehUte1ZKly/XEs8/pleUr9NyLi/TC4iXBqd6Va9cF7+bd0tTsIe8AQV67CXBKkxs0gJfA+ukOMOxuve7I8nUGD1gG6hrkJeakNx/G+It9SLsfNv6DuusPam8jbyPvA94HvA94H/A+4H3A+4D3gcHuA3sD5AWgAGY4bQlQMrgS3sjKl087IBswi/ZAHwNLgCwC0MsC9QC2BEAZm15skgKFOAmILvQLdKIOfdIHcNAez8w1sA3IxGYZ0Icy6tMPfQJI0Yt8K7N+6Yc8NmuRD9wyEAhEAooR2+lOoB+PweWaNIAKMEhbZDAGICRAlBgYDTAGqGFP+kVXABibwbQBumEn0owXGcgnNjsbCCPPQB2b5nYKkrbYwmwGHKMN0M6gGKckXR/GLvke1wygM4hMfwT0oi9OuNI/MpFPP4A5oC4xgTz0p43pT33GyTyQb/No/aA/tqI+fbj2oD7lFrgG7qIPc04bYCX+hq+YvtSn3NoDJG2uybN8fI55x69IYxPGRjn/aAA8Zo6ZM5ONDfBTTpgCORkPZdibduiEjsglzXpwbU2e9Y9P0Af6uvn4HfLII1COXe2aPu2EL/kE9GYtUYdr1gDyze+ZH8ZI3/SJ3ZDDNTHzSBvGjb6MyfpjnJRTl0Ad+qAO6w77Ym98jHkwmehIGr+3+acNfgbYR2f6wFboSRkBn6E/0gbisQGyiJHLGuTaB28D7wOD0wdYq4Q9EfK6Pmfj5H7FfZBAuqysLDjZyx6x7Rm733XJd699uvPfQu5ee760cRyLrY5du7GBXjcG+hI47MecGrTn84j5tDm3+e5OTBv7HCXmGv/gM5TvOnAm4HKvIe92YBRRlEc2x2Kqjo7ogLwz1P769dLrV0rrLpfW/VVaR/oata4dp8cevU4/ueYOxb8zTfudfqeGfWmmhp00Sf/wxZu179dnaP9TZqniZ3NVduajOvSsJ/WfM97UH6ferVn336WXlq5QU7pdbS1taklnc9AyldX9Dz0SPK65Ptmg+iH4uGYe25zNZtTS0qKWltYgtLVv1dp167V+w1tqbZXmPvKopk6boSeffk6t7dLmpkxwavfW2+7QnLvv1+JXlweQ94ZJk/XoE09p3A0TAsi7cMnLmvf4E8E7eqfeOkPN6fzv5PWPa+78RtDZjdIWPbG74C1NPqCXhceXS8Bed2Cvh7yDB8xuv+f1TCd3DoG7AF3XD5CLb/GhgL+Qdv2JdGe+58t6v2697bztvA94H/A+4H3A+4D3Ae8D3gcG0gdcQGYbPUM9ZoPKxmBpYqAUAIcyNqFsY8o2qqwNG1Wkra3lA4qAPlzTBnkEHhFLADABdQzs0Z4NNECQtaMtQAowZXKoBxQiRi5tAGGAWTbhAFHIJXCSEhAIvLNrZJNGBuDV8k1/28RDNicXgcD0jVw7mci11QeMmS6WB8gC8KIPddlDQC72NNiGfQCFxOgPEDTb0o665AHBsDH6Igd59Ik8TgQbTKNvAvnYAgAJIAP4AZkpA4bjw8igL2QyJq7dAKQ1AE2+jQs9kYlsTrfQ3sZIPbMd9aln+lBGPXTB3oB32qMPutq4GR/1AHfIIh8ZBsjpzwAyIJh6XBNjL+baQLP9o4CNC3nMIT5oegJRsR91AaGmLyfH8RnsbDbHbuTZiXD8gnkBVCIXXZFL/8ihX/IsxnZme9PJ+sMejJFr+qScPSf+UYATwCaDcoOaJtvmwK7Rj7HQBl/nHykI+B2xndCm3NYgfkjAb01/1ryNzXSiLevVrpEHaCXwjw/Y39Yb80gA7KAz+pmOxJQZ8OWfDRiblZMmmD3R1Q1WDqC2f8hwy316R3t5e3h77E4fsPW6J0Jeu2dhX9LcGy3PhXh8jvAIZ/f7anjf2K7dOj7d8984Zsd8sTEeYhfsdpZmz585Bcja5xqfTebXXa0t6plP8LmKX/C9FlnwBlenPoO8KG2Qt+X1Gdr6+nXS61dI6y6T1l4urb1CWnul2tZeo6fmX6kfnftXffJXM3TIKTM17HNT9E8n3qD3nHSd3vOFCfqnL96kYV+YpH86eZYO+d69+s28tzTpkcmaPuf3mnDLH/TCS/eq8e2VastuUXM2qy2ZVj00b77q6nOAtyFZr2QiqURHwCBdGW0gys877zxls9kOkJsNTu7aO3lzsZW1qK2tTW2tbWppaVOqOaO21q3KZFqUTmeVzbYpnWlTc7pVt86ak3s/77KVenbhYt15zwNa8NSzeqcppUcWPK77Hp6rR594Mnh8M+/pBfI2pdL+JO8An+RlwXNz5T85WIQsUG7SwD7AH4E1xDWxBRcQWp6Pt9tnqNmC+WSOud9wX0J/+9A1yJvvg8Tq+LjnH9DeZt5m3ge8D3gf8D7gfcD7gPcB7wODxQf2RMibby+F3zou5LUNKuoa4LF9GovDclzISx3gEac2gTLAUwAmMA04h3zqALbYPCOQRwAqAYPYEOOatgAz6w99AH3I4rca9dhEoy4nEemXNPWJqQ/QspOTbNxR38ZBTP/IoS5lXAMoOQlrepBnOpBGd5PB2IGzdm19A1SRA5wlRj+LTUeugdNATKAiYA35wDzkkCagFxCPuuTTl/UHnANgYhfqYkOD5XaKk/6QmQ/yAu2AsIyf9tSlL2QCRImxN3AOSAqspU/0JXDNvNKetswZsBLwy3wwRuxIW0AdfZiNWGPUYXzUIZ808wR4xmbIBqyiI3nAA+xgEJt8m1fam2xOmzKHZifq2ZomD11NX3QlTT7jIEZP/BZ5Zh/GEIa8+IK1JUYXbOraHhnIQy6QFzjLeLm2wOlhxmtjIM4HebEtp5iJmXP8y+oiy/5JAz3Mf8lnjbMWmE/mhHY2bnTDrtiamPr4NJDe9LMxUJc5xkdsDKYzcvEz2pDHPprZhnklnz7QkX+MAHbjr9iVNUpbYjdwD6Ed/ZqPIRu51q+PPdj0PjA4fMDuF0MV8nJfsdATn+JeyD2OexuBa+5X7Bm732nDe8humU/3/PdP2J7utQtU3XRnkJdTvbye0b5f8tnPfPL50xN/oA3fV+x7ANCf07uuHn0KeWtiRcFJXiCvdoC8gN6/BqC3dc1Vemb+ZTr1F7/UEd88T0XfnKphX5yqf/zcBL37pOu0z0nXBTHp/b84Xvsdf7Guf2Gp5r70S7362hf1wsKv6p67T9bj8y/XtMlXaOLUyVrw3IuaftttqquvC07xJqpqlUzwBYCQ3PZloCfG68u69mVkR8jLid0w6M12AOAWbd26NTjN296+VdlsawB5Ab6kgbyZbLtSmTZNnT5Lc+66T/Mfe1LPLVwchEmTp+mBufN0/cRJevK55/XMCwt10y2TNeeue/TaytVqbE55yDvAkNcWHTcHW9zcnPnyzkIPw1y7tniowUyv784gmrlkvgnMPcDf/IIPXku7HyCW9h/MPf9g9jbzNvM+4H3A+4D3Ae8D3ge8D3gfGGw+YEBoT4cJ7IEY5LUNWmLGzcYWaX4HExfae+GUH9CHcn4/ccIPEGWPMgYYUQ78og4boLZphlzSBmmtD+oA8oBSyLR8IJFtnJFnOgLEOHHJNfWJ2WimT6AU8hiT9UcMYAQEEgO8gJqk0R+oSR4gjTqkKeORvcAskwMI4+Qk8tnYow/aWDlyrG8gq6Uppy3jRnc2iNEbGWYnNgmBYIwFHewUJG0JwFcgOPXok76Rj124RqbZDYAWhoiU0ZdBTPqhf2xsfVIHmdgccEhdTmdja/IItKE++tspUuYeYE8+egGEWVNc0x79gXn0b+DUdKUMiIldgLU2XouRgV8wRsAl47e2xPTnQl6uCaYLaZOFLkBX8lwZpK0OMdeMwXTFJvgDNsYu+DvyOVmL3qwp6we7ADyJgbwmh/nnnyFox1iwrasDcujb5DCHgHLgM3Npj4+mDT7LPDBuxoO/clKeMnRFH/yPvpCJzsB6GyP5zJ0BaE4WM3+UU0ZAFmMwyGuyiQmMizXEPDNe64s05YyDMZBmDIyFgF4Exsu43IB9aecGk0Xsg7eB94HB4wN2P9kbIC9jNd+z+yT3R+633F+5H3P/cg8M8T3X9o6JB9v33qGmj2vLQmnbvw/H+WDv8OHDt536xRZ8hjGffDbzXcf8O19MPeacusRcwxKQg9xw/30MeUfq2ou+q7yQd81fghO9rWuu1LPz/6KvfPtUHfOzqzTi5EkaduKkAPLuc9J47XvSeO134ji9+7OX69ATL1PFiX/Ws5s26f75p+jpeUdr+dNf0MtzT9Xc6T/RuAt/rFunTNZNk2bolNP+b+4kb7JBDckGJRN8WXAh7/aTvXbC1xZO38Xb+8j3ZcGFvMFJ3bZWtbVxajfbEUjzqOaW4MRvNkvcEpzg5RQvAdDb1i5lOk7zNqWyWrtugyZOmqKFLy3Rc8+/pBdeXKy58x8L4O6Cp54JHtl848236G8bN6kplekS8tqp0l0BdcjgRxtfvIjDjudehxfNULsBoG94DO74LM1it8VNff7rwoCf2QmbAwMN7lq8K3Ph2+4MXAfKJswf/m9wlzR5+Iz5BbF7HfYlrofimvA6+01V7wPeB7wPeB/wPuB9wPuA9wHvAzv6wN4KedkfYaOSzS3AC6DINjMtDu/LuJCXjS2AEwDSAra006AGHukHOcRsCAMxDcbaxprBRuuPjVNkU04effG7jQ01oCNgC1AEVKY/gBMnbaln/TE22iKDNGOijDpALaAp4AkYZyd0KWfjDuiMrrQxHYCE2Ai4B0ijDL2RTTjzzDODPGwAyKNvdKaeySGfPthrYCyAMEAyuiDbgCUnH4FvyLB+gGUGeW1M1hd1qEsoBHnpm/bURQdsAJBHd+aEPGAspy2BeOTRhpOn5AEK7SQmMhgDtkRvQC86IcPgOO2YE/yAuUR/ykxP+sd+lDGXzCGBOsiiP4Pv1CMAiu3UKX1RDxhr88E1umADAo8b5vQ0fXBNGoCOHAL5xNQz2zA2xhmGvIwT2MuYqMP4OCWL7oyRPALgEhCM7shGFj6DbvgudjUbWIwM2nJNjF6Mj2tsbPqQZk4I/FMA/otc65s0tuBUrPklbaxPq0eZnQxmztGPMuYU/+d+wJpgLtCN/pCBLAJ52AMbWDt0tTkhD3tbf9aOPRjqYRtiN7htyactsdnBrevTO9rO28PbY6B9wNb23gh5Gbvdr7i3GRgEDpLP6wDdPeTwd26/n7zjd/CwffJdu/YslHb38910PsjLSV7LNzDLe5aZT3ya72ddBT734Wz0Ze/8dfu1dJ9B3kgkqppYDvJm190qrR3f8Zjmy6R1f5HWXCitvUTtr1+tl566Wr+74Dx91yxkzQAAIABJREFU7jcTNOqbt2jY527Wu068TvuecK32O+Fa7X/CNRr+uWtVdNyF+ti3r9DrWenKv35fnz9qmCb98N+lF2dIS6dp0q+/op/959d07cUT9K3Tf6xkw/tUlxyjsfVjHchbp7qkAV8+uC0AZPv65ozM7fJZcBbo65xzzgkew9ze3u48sjmjlta0eFwzwHc74OWxzFllMryrF8BLmrxcujmVUSbTqqamtDa9vVk33HCTlix5VQsXLtKzzy3UE089o2eefyEITz/7vB58+BHddc992vj25gDyNjU3qzkU7J28QKjuhkKwbG+DvO6NIXwTsMVGbAubNPU4Wh9+hDO2x34E7MuPNdfOlLvXlnbnzPJ8vHsBLz8s+PFCYC7wE27I5iPmB1y7adeffLrnH8reZt5m3ge8D3gf8D7gfcD7gPcB7wOD0Qf2ZMjLZiS/e9gDIQ0AAtCwkcV+iO2NABqBaEBc6gGL8u3NcJoS2MnjhjmZCMgB2BIAlIAfABFwK197oBB9oBOgiU0y9AEomS60A9wClkxHYuoTox9pNlR5nC86IAMdrJ4rizT5QDyAFnVpxxgJ2AJgBryjnH5ts5a29Ed7AJ+dxgRGsrHLOJHBb0zsh16ckOT0KW0sIIOAbOqwnwDIpj0gDTtQF7CJ/ZAJ6COmnUE49EIGeZQBgglcW1/IZB4AfQBR8hkjepmNqG+BjUwAHvJI24Y1dYFxjBVwif0oc+E3euM7pgP2ApCjA7oiD1sDjekPGwJPTSf0ArxSD1nYjTrUpV90oA7XyEUPmxPsSD5zh0zSFpBPmjqMCx3RifYGK5FDmdW1fkwmp10pA6Qyt+jFnOG7+D9+RHtszJogTaAuoJkx0R4dTFezJfVMP8ZNG+paQFf6Y8zMAeWMETn4BbpS19Y28rgmRheAutkC+aw7xksdy7cYgMx6s77pFz1ZkwTmDxnIJjDXtKE9epKHXtbeYoO8dk2MDuieD/Kyd4Ycmwcbo+ntyvHp7b7ibeFtsTt8wO4fQxXy9oXNsAFyzBbcs7jv8znBfRG2wHde22vuLB6M340Hs06d2dL28tnPd4Oxn0IxXID6HP5jLplHC8yrBT4P+Q6HfZBlPMHty033KeStjRdr3MVnaDvk5RHNO0LezKortGzhBI275UZ95Xc3qPir4zTsxOv1nhPGBXD3gOOv0QEnXKX9j79cI4/9X/1+/CPamJZunz5eX/uXes366Y+lF57W6hmX6OqfflmXnfU7/eexX9fHPvIZ1XVA3vrgnbwsAL581KsuyZeSXDoXU9Z/kBeonAPLuZO9tbW5L0QXXHB+B7TNwVogbjab3hZaeXzztlO8LuTNwV6Aby5k1dyUCk72btnSpBUrVuummyZpwYInNGXyNM267XY9/sRTAdidPHW6rrthgm6ZMk3PPPeCmtPZ4J28nUFeHMgFhp2lC0HEvRnyhm+s7oIjzcIkZnGS5j85aIPd+aLJjzabA9e+zAPXFrtllm9zFS7z1wMLe5lH20wgXVpaGjymmw8A5ryrD4nB/AHndfMbpt4HvA94H/A+4H3A+4D3Ae8D3gd65wN7MuTl9w+bVcAyICxwBjgFSCQPgMJvIwIn+4BJxAZYwhuhQF4gI3LYxATkALQApJzM5NG7gCFOS1JuATm0ARixUUY+fdMWqORuklIXGGcgyX7HUcd0JUYWunA60qAb1+hv46Ifg2gAVOTSJ6AKGZTTHzGw1WAn47f+iA3oIov62AHw6gJXgBdwDZCOPNpRF11MH8ZKHgEYhx6UUR/bAfXQi3LAHHaljDrkGeQljXxgmb3LlDwC0NQgLyeCyaM984KtaOfqxiYmUM/sQRl9croYH0E+/QB5qYMs8yvS9MXJVfoB0gJ0DQoCAPA36hGArcyD6UQ/+Bz2Jo1f0hc62Elr0wfb0BdtqUs++tDerikjWBkxJ7WZJ/SnjLmjD+aUa+ubutaWMfDPCPgqEBmd6YNx25hYT4wJOdiccrMPctxAGXL4JwJsQ1+2N2Hg2fomNptYHoAeyEt/jIV+XH3xafyePPrBzxgjsaVd3Ww+iJl7QLb1hQwCdmH+8UvqYQvq0T8+Qx10N/vT3g09hbz0gW2wPWvJ1hr5rlyf3tHO3h7eHrvDB+w+sTdDXrO72YL7PPct7pV8VnMP5b5r0LGzPWf//b1n3987s6XZO8x9urqGCxgbAtDD0Oxzk89r5huOw1zBjowfWX+FdOpTyFsTGxVA3sya6dq6Zry05nJpzWUSj2pefZG0+lI1Lrtc8+8+R/fNvVvn3fyQjvrhzTrgxCu1/wlX6YATrtb+QbhC+x3/F1V9+Xw9u7pVjY3Nuvf2cfrJ1z+l2877s16adbsu+9/f6/tnnK6PHv0xRcur9IPv/kBHHHa4kryDdzdDXk7z1tYmVVOT0Jgxh6mhYYwaGup14YUXKJ1Oqa29XdlW3qvbEoQ0p3UzabVkM2ptyb2PN/c457Zt0Bf460JeHtucTgOCW9XclNZLLy3Wffc9oE0b39Hs2XO04PEndevM27Ri1Rr9fdM7Wvraio5TvOkdTvJyetfCli1bdO655xaEiD0BhR7yFm0DeYUWty1qFit1WKSFHuGM7Q3uWhyeDwO8hcrD9f1134Bfsztg3gJ53KCJeQezzbXdxAvdkC3ff+j27EPX28vby/uA9wHvA94HvA94H/A+4H1gKPjAngx5+f3D6VPADOAE4AaQAswAd9i0og4xG5WAJE4KYhPbwLQY2IIceycv9e0kH2VcU5dNTmTYxqflU8amJ3UJAEe3HgCJumyQAnjRhfoE2gLTAKu0ASBxgpIy+jOZQEZALeMEuFLGxqvpghzApz0OGRDGmOgbO6ATY6J/9CCPtvQLvKUeoBGoDFSjLeCSa/QCeqG31QGGsTloOpjN+Sdy05kYQA6Ms7GiJzLMvlwTXMgLIEYn9ENPm0faoAMB+Ec7+sAeNi6uaWdyAaroSP/AYPzDBcJs5KMfsBOb0hf2IQ0MJSDLZCCf06HIARJzTWAOsQHyzCboa/8gALjnGlnMDdfoQznQGzvbXBLTP33YGLE1+djJZNGOemZb9ABe0g9jYv4oN7nIAsaSb3noSjvk4luAT+pZoA8AtelBTFti7IQ8xmP92D3H5hMQ7bZhTPRJHjF2Zz6wOzojm7SNi3I7vcs/D+Cn6EsdYuRYjD7MA/bAR+jLdDUd7Jox2Wlwsxl5yKIOMQAanWjrhkKQl/FgC7eupZk/fIm27nxZuY93tLG3h7fH7vIB1j/BQ97tPog9uL9x7+LeTOA7ADGPAoYtFDrdOxS+Kw8mHW2fvlBciPl0Jx+ZMCGTbXzIGILJoNxNW/1w3I+Qd1wH5L20A/JeLK2+XJuWXKpnHvqLXlz8tK667XGNOeVKHXTSlTrghCt1wPFXab/jr9KBJ1yuQ48/T//5p5na0Cy1ZlNavfoZ3XvnBE2++q+64rzzNfvOmTrjZz/Q2Pe9X3PuvFtzH35I7x3Lu3gTStbVKxmcpm0ITvEO7Ene3OndRDIZvCN47tx5enT+o3r88QWa9+ijeuDh+br/4QW656HHddeDj+vOBxbo7gfmB4D2vnvv0SNz5yqV4pSundrNxel0Wm4wuJtqzsgCsJfw4kuLg5O7QN53Gpu0palZjc3A3fS2d/I2kr9lyw5h8+bNwSOl+wIS7u2Q125I4QVn17Y4iW3x2mImj0c482OMD1G+zLpzQtq9Nlhr+fnKrI6P+wbsunbE3sBd5ssC5QZ3mU/m3Z1z84NCsfmPj/1mpfcB7wPeB7wPeB/wPuB9wPuA94E9xwcMuBgE2V2bpv3RL2Niw5GNRwKbkNaPbdIaLOKaugAnt57Vpx6nFymzUw3AQfogkA9gBRpx6tLaWWzQxq6BmEAu0wtoijyAERCWjVH6NF0oI98AFvKsb4v57QfE4rQmwNX0Mhmc5gTM2slIdLG2pKmHXACfgU/yAY34CbCRsdEeYArcIyYA2jhFSaAcsGe6AjqpS5np4vYNoGMzmDzGTR3bLDb7UAacQ3/SyOLalUMauMo8oA/X1h9ysC39YCfLpw6nmA3AAjCtf2uPjWjD+LEL5QTGRDA9DLIyb/RnMNdsbGNx+0Yn5gu/Qz4QGDnoj90B7Jxo5oQn/kcZ8oiZJ3yCNPoxNvRHJrATXwj3yTX6IQN59AO4xTewPWMGnhvk5doC5ehi4yem77Bvk282BoryjxHWBlmMFbuhJ75iZRYbeEUH7AEUZWyUM158kHwC88FJanRgXNjQBS+MF13olzEzV4wZmfgJNqAM2RabHvil+QO6sAaQYfVMXhh6U54P8lq7MOS1/ihnzvDHsE0p88HbwPvA4PABW7PuvcbPTe4+im34XODey/3MAvbhfb3sS9u+s/8t0be/JcyuxO5+f1fpcDs7DEY7uNCBBx4YyGO+KAvLd9uH030GecvLK8RJ3msv+q4ya6dp65prpTWXSqsvkdZcEsRtyy9VdtX1Wr1oqhY8NU/n3jxXh/9wuvb5/A064MRrtf9xV2m/E67RAcdcqJoT/0f3v9SozWkplU3rzkcf1EXXX6nvn/lT3XX/LK1cMVezZ1ymVSteVXMqqwcfeVj1hzWoJplUbZIvDISBflxzQokkoVbViRol6pJ67LHH1NrSqrb2NmXbpaY2qUnSxjbprTbpb23SpjYFf+2t7brnnnuVSqW7hLyZDCd7W4LTvJzoJWyDvalMAHObCsZpNadSAUwGKBPefvvt4ESvneQF0uYLLtzqLO0hb+7mEV5wdl1o0bOAWdQHHXRQsJCxI1+S+ULLjTvfY5xtHjzk7XuA25VtzeY2P8wXgD48vzbvFlNuaWL/Ydu3H7bent6e3ge8D3gf8D7gfcD7gPcB7wOD0Qf2ZMjbnU1XgzZd1e2qHhubXcnIV95Vu67KTWZn+nVXhsnqy7iQXuQTAHOd9VdId2ufL3bl0Z5APd4za6d7qUOeW7ev0j2Rm0//7uQxJuCsbaZ3pnshG3bWxsq6GovZ1+3D8pBhabc8nO/W6au06d8deVaXsbp6Wtt8+pLXlW1Mrhu78i3f7YeTvIBqg/PUydfG2vp4cEA/Pw971zzYmvWQNzfvdi80u9h9i/sY/7DCP9fYPxLxmQXo5WQv34ltH3owfj8eqjqZTbuKjRO49SzPYvfwn+WFY7d9ON1nkLcyXqXq6MgA8qZXT1H76is7HtF8obT6QmnVRdKaK7X51av16D2X6OZbJ+srv7lWZd+cqGGfm6R9T7xOBxx3pYafcJVKjz1Hv7riPr2xRWpKb1VjJqMrp0zRv331P1VUV63bHpih5saXtDX1ira2NAaPLAbyJsc2qJoP/6T7/t2BfCdvDvC6kHfBowsCyJtKp/Ty8tU69Ue/1+dO/72OPe0cHXP6hfrM6Rfo+NPOVmNGyqZbdNus23XB+Rfq/PPO13nnnbctAF+3B/Iv0HnnXbgtnHvu+XLDOeeerz+ft3M49/wLde75tD1fF1xAfJ4j91ydffbZeU+JGuzqbuwhb25TJbzgCl27i5ZFbad7iXnEAjCRGzc3c6Bvvnkw4Eicr9zn9R4Cu7YlbSd37b9y+eDEvnwo5bspF5p3yx+qH2Zeb7956n3A+4D3Ae8D3ge8D3gf8D7gfaD7PuAhb/dAn21i9vVmfl8BnP7Sb1fHW0gv8i101kch+1jbfHE+eVaPE8ZhmbYxHY5NTjg/3zV1yc/XJl+e6WNlPYlpy4llTrXSjn4NChbSjTZuH/nqmf5W5ta3fqxOuGxXr61Pk2/xrsrtSfuwjXrSdlfrMl7mkEdyA0Xc8bvpXe3Ht9+7YKSf7/6Zb9YkwUPezu2LjQz08iQIgj2lAEbj95+7/129J79rzK5dxS73KZSGARUqI9/6KKRfn0LeqkhRDvKumaz24H2850mrz5XWnC+tOl9tK/+izUuv0j2z/ld/vvwynXDmOBWfMkXDPj9F/3jcdTrwuCtUesLF+tdv/1VrGqVUi9Tc3KpUpk3/dtwJKqmu1olf/YqWr1uhVPpvSjW/qUx6szKZlObOnav6Bt6PkgyCneIlHrjHNXcsuGRCNcFjoxv02PzH1dbSruZMk7a0tOippRv0lR9frH87/XJ97Fvj9LFvXROA3k0Zqb1NmnP7HDXwuOkEj33OyXO/ZLBgI5GoKip2DJFITG6oiMRUnidUxOKKxOKKRnOP/DV4xTF+S/cFDPSQN3fzsAXYk9hd0AZ8yeO5+sBEvgzbu1/tZK/NncV9MYdexnYobHYlxubMA8Hsz/y68xa+MXc1/4Vu0D6/fz6EvV29Xb0PeB/wPuB9wPuA9wHvA94HdocPeMi7I/yyPY9wvDsBUFiXfNeDVb9CepFvId94usqztvnifG3D9fLVGai8sC69uUZXNstp2x29w310p81A1jFoYnuNFg+kDt21ZX/oxF4OY7Z/2nfH76b7o28vs3NQ5e3j7RP2AdYkwUPern0DO3FvJeYzi0fv8whngC8HxkpLS/2TJEf27e+frvb7rdxlBr1JmxziQr9f+g7yVlYqHhmlH57+Wf192XS1rBmvrTymec0FOchLvO4KvfnSJRp/+Xd17eSb9dmfXKGSUyZr2Odv0buPH6cRx16kD37tYj26rEWbswreQZtqziqdadcPfvwzXTX+Or25caPSLVk1p1N6Z8vbSqcblU43Be+ybajjnbw4NIDUHtlcp7rgZO/261zZdogavoHs8nXHI6OTyQY9Pu8JtWfb1ZRq1jstW/XUymYde8al+vCpV+tDp96gD502Xh8/5SJtaJQymVbNnjVbydrETpCXBYpeLEyALKA3GokpFo3vFKLRuCJdhFgsvg3qAq5Y7MjNB/ZcwBVO56tPnoe8uZuGuwi7m2axugvegKHF9r5e5oxgoNGdm0Lz4vO3g9vObIEt3XJs7NqZHwXUsfcbuKd3mWd3/kh3NfeFbtA+v28/fL09vT29D3gf8D7gfcD7gPcB7wPeB3anD+ztkHeX91r8uzK7BRn72s5haOled9YX+1i2l9VZvcFeZqehBoOeZk+Lu6OTzcNgicM6d6VXuH5/XvfErv2ph5fdNdDyNto7bGT3Bw95uz/f2Mw91ctnmOXtzu/AQ7Fvnq6aL7hj6WrPPx8nCHODQtf5ZLt9u+k+gLwGTWKKRspUU1mq/zjuSK1bOEFt6yZIay+X1vDI5ou1dfVf9ebCSzT75l/r2z/4jk76yV8UPWWi3nXSBB147KUa+5WLdc/Tb6opKzWn25ROZ4L3zKbTLVq0+GX97a2N2rylSS0trUqleW9tWk3NQN6UHnroocCBa2t5pC2OD8TNhdyH9PZry++3D4RkMneSN5HU43PnSy1blUq36ulXNujE71+uj552tY4+7XodddoEHXX69frEqZdoY8dJ3tmzblcOVueH0EBeAGo0gLxRxaMxVcbiQSAdhADgVioWqyoQKoOTvC7EsnQgO2pz2vvYQ97c5km+xRjOcyFgoUVtgJdy0txgsDH/eQhw5EeWgXryw8Hm18f5fdoF5AZ4+acHggFe7Iy9sTNwl7kA7rqANzx/4bm2a/cm7NN+o9H7gPcB7wPeB7wPeB/wPuB9wPvA3uEDHvJ2f5Oy3/ZrPCjud1DM/oQ7f7ZJv7tiV5e+TucbU7iPfHV6kheWF7ZvuNxf9+w+E54Lb7+e2c/by9urP33A1qeHvD3zMyBvGPQyT+xrc6KX/enhw4cXPBXqf5f07e8S4wG7Gnc2L30GeTldCFgCItVWleqj7xupJ+46V+mVN6h99RXSmsvUsvwSbX7lCrVtmqfX31ih259crfeecoWKjj9fH/7OON35YrM2NUvZVFaZVFbpdLYD8ma1aNESvfnmW9qypUmZTEvulG8qpUwmo1Qqpcceeyz4r4R8X3a4IfTnDWcn2cmEahM1qksk9PjcR6QWKfv/w6/OmaCPn3qZPvCNq/XBk6/Q0adcoQ9/83J9/Ot/1N+apGy2TTOm36pkba2SeX54MDYgbxSIx6nb8grFo4DeXIhFIiIAejnhy4newmHHk4oG/8Jw0ObUyrsb0w44BhgjDsMv9zrs4J057FArC4+tO9eubfKlgbwEbsbARqAjdsYP8RGuuztPvl4O+uaDvNgGW2JTA+n4NT5o80KaObXrcFxovoeaH3t9+/bD3dvT29P7gPcB7wPeB7wPeB/wPrB3+oCHvD3bpNxpryXPPomv4226N/lAd/Y38+2L7k026ulYDSJZ3NP2vr6/B3kf6D8fsHXpIW/PbYztOMVrj2zmGsjLHjj71+xZ+98jA/N7pBAf6El+V3PVZ5AXIGJAMBatUFVstA5PFGna1T9SdtVEbV11mdpWXKRVj/+PvnFCXFdddq6eWbxG/33NHfr2H2/UyiZpU4vUlG5VJp1WqjkdQF5AL2HOnDv1/PML9famzWpuSqm5qTkAvel0WtlsNjjJi7NyYw1/obH8gbrpBoC2tlp1iRo9+vAjam+R1r/VrmO/9hsdffJFOvLkv+hfvnm+bnhwjSY+sFLHnXyW3mreqkxrq2beOk31iWolEzv+5yNjInjIOzCLr6uF093ynixWqxsGheFrg7wWA3v5Lxxu0nayFzhpJ1ANYHqgm/8UL3YxG7kxNjQ7kg9Qx9bYPTwn7rXNI3F3/cTXG1rr2s+Xny/vA94HvA94H/A+4H3A+4D3gd74gIe8Pd+kHKh9HN+Pn5uh4APd2d8M74kOhXHtTh2xqRt2py6+b38f8j6wow/Y2vSQd0e7dNdPsB8sCdAL8DW+VFJS4iFvH7+ft7PfBS4r6Em6M5nhsj6DvEAQg0iVVdWqiFWqMlamhvi+OucX/0dbll6nllXjtfyxP+uI6DAlo0WqqT1Mn/3CN3TFhOl6/W+blM5kg8cwA25TqR0h71FHHR08eri+fow+85nP6tRTT9XZZ5+tCRMm6OGHH9bs2bMDwIvzArpcZyfPve7vdABoa6sCyDsPyNsmLV35jo4/+dc6+r/O0Qe++mfd9OAyrWmW1jdKs+97Um9tSas5m9H0abeotjq2S5A39yjnmCKRzkIOygPmexJsjruKkelP8uZOebqwz13IthjdPNIuMOwsbe3cOjxemFOnBihdSNnVnO3N5S7cJY3vYjtsAkDHxjyWuSeAl/mxOfax3wT0PuB9wPuA9wHvA94HvA94H/A+4H3AQ97ebVL29x6Ol+/nZaj4gO1vWtwdvak7lEN3xtjbOvns0ltZvp2/j3gf6HsfsDXqIW/vbQvcPeywwwLQyyOcAb3sd/vfJQP3u8QYTk/jnsxRn0PeikhEFbGoKmIRlUdLFY0eoqroe/S1k47Qa0/fqFcfu1xjy4cpERmpeKRakWiNItFq1dbU6vTTTtOMGbO0pTEVnN5tbkqLwEneI4/8YAAtefxwDl5Gg/dl8pjosrKywEFt4Yf/a438gbzR2kne+vo63XPXvWprk95uatUpPzpbH/ny7/X1X03Q+rS0salN72zJ6p3NzdqwcZNSLVndcvNENdQnlEzUKJHcfprX/tPCPcnLo5krAVIdwR7bvCuPa+4r0Ochb+5GYYvXFqVdE+fLc8sLpV2oa9DRTvVamYFee8wwMXPiPla9r+Z6T5BjYNf+QQRYbu8ocN+5a/Y2O4fj8JzZHPt44D44va29rb0PeB/wPuB9wPuA9wHvA94HBqsPeMjb+03KgdzT8X35eRpMPmD7gbbXafFg0nGo6mL7yG48VMfi9fb3rT3RB2xtesjbe/8G7HKS1wI2hRMM1u/KXq/e/Y7rBeTlxO72U7sGeOwkb6QD8FbEylUWHa2yWKkqoqMUrzhYnzy6RuMv+aESZcNUHS1WPFrZEeKKV0RUFa9UIlGvw484Umed9Ws9Ov8xvf32OwHk/fCHP6qqqhrnHbOxnSFvfb2SdXUB8HVvbDivez0Q6dramkCPe+65T62tUrZtqxY8v1THfO3XOuN34/V2RmpKpZVqbFLTli16u7FRW9Ip3XTTTaqurMyd5B1EkDfGI22jhR93a35gsYe8uQVp0M9uUHZNnC/PLe8sbXDRoGMY8vJYYR69wE3bwKWdTLU58vGO7+O108/YzGxvdu5ubO0stjn2ce8+oLzdvN28D3gf8D7gfcD7gPcB7wPeB/YkH/CQt/eblAOxj+P78POzJ/iAh8Dd92MDSG68J/iAH0P3fcDbanDbytamh7y9nydsaO/mtcc2wwpGjRq1jU3sSd+199ax9BDyGuC1eDv0M8gLOIrEOM1b3hG4BhBWqDI6WvFIkWqqRisSlJMfV2WsSrFopaKRuOLxapWVRwKQHIlE9ZGPfFRnn/0/OuKI9wWPa+Ykby5sh7yjy8pUk6hVXQfkDd+gceZwXn9e5/7LrkZ1dUndd98Dasm2KZvKKp2RnnjxDf350pvV1CKlM61Kpwgtakxl1JTOauLEm1WXqOsHyGtztt1+3YV8Bngt7k47D3lzmzGFYB/5+W46Vr+r2KBjIchLPqAXOfa+XntHLzHr1V2z3ZnTPaGOjZvYtQdgl/Hx3l1sy+ld9wSv2dviQvOTb059nt+Y9D7gfcD7gPcB7wPeB7wPeB/wPuB9AB/wkLf3m5T9uYfjZft52ZN8wEPe7vuzASQ33pN8wY+l+77gbTU4bWVr00PeXZ8fbHn44YcHJ3rxdw6H+d8ng/v3SSH+kC+/G5AX4ArMBRIaICTmejvkjQONoh11Y5EOiAvsrVQkCsSNByESjasiFlNZvELlsQrForHgNC+Ql8CjmCvjuXdhAgrpg5j8KCA4GldVVbWi5FWUB4+fBfJWA3kbGpRM1isZQFLAbjKAu8DW3M2aOE9IJnKPRk7Wqi6RCAKPXLbQ0xt98IWqtkbV1VWaPft23X/fA7p7zt2aM/sezbr9IU2deZ+mzbhd06bP0pSpMzV5yq2aNHmqpky7VVdfdU0H5LX+c/rW1CZUk0gEL8uORioUqahQrCKqqlg8CPEY9gWaMw9EYUsiAAAgAElEQVQ7z5WV5eYQO+ZsmasbC0A8MJ7gzqul7VHQBnottvJw7CFv7iZhiy580yQ/nMe11e8qNtjYGeSljsFe4CVzAszkxOqeDnhz9wy7d+3o0wZ47eQuMR9s/AeT2dXmwq7DcaH5yTenPm9wf2D6+fHz433A+4D3Ae8D3ge8D3gf8D4wUD7gIe+ub1L2dH/G1/c239t8wEPe7vu8ASQ33tv8xY+3+/7ibTXwtrK16SHvrtvehbykORQ2UN9/fT+9+61ViD/ky+8E8kYUjVUoEgSgbVwRIGwQdoS8wF1O6lqwdryXF8gLUKwE3gZQGMjLO3vLFImVCXhYyQneDggMDN4OkIE0BmoAwDnIDGCMV5QrVl6m8vIylZaVqbK2RnUNY5VMjFEyMVZ1SUK96uoSqqurVQKQGwBe4C+PdE5uC5TVJKuUSFZpTG2tDkvUqb6XkJcvUwaHc8A4GUBnHkOdSIxRInFYEGoTY1SbbJDFNck61SYBu4BmQjKAvZzqRd+aZL2qEkmNOWxMYGcgb7Q8qqpIXFUBsAXUAndzgDcS3X4d2CsaCWzNXPAO5Gi0RrFode4EdTSm8lhEZXHmi7lm7nO2N+gbj0ZUGchATk5WZ6C3EOTN54ThPL/wO1/4rr3C8LHQNad6KeMGzvtm8VMezWDA1064hmG9e82cutekw3ndkROW0R/XLuRFJ7tmvHyQAbsJvKO4kM3C+a7dvY927qPePt4+3ge8D3gf8D7gfcD7gPcB7wPeB3b2AQ95d32T0m+yext6H/A+4H3A+4D3gb3DBzzk7dt5Puyww4KTvLynt6ysrOBhs931Hd7deyc90HpwAMwNu9q/Kytfuiv5YXu4rCJc1gnkrdgGeXOwFjhbmTuZGwO2cjouBwKBvPFoeRAAvUDeaDyiaJyToTnwWBUBSNIm3nFqtEyxaJkqIznIux3uGuTNQeZA1jbQm5MV9BcpU7RitEaXlaqkbHQAeevHHpYDvLUA3jEdkDcZgN7czZ9Tsfkhb22ySslk5TbI21ALZAXQ0qZnCwrIayeCiZEBpK1JAqAbVJdo6AC+xMDfOiWSyeA0cTJRo7ogIKOu41QvADgZPJJ67GENOcjLI63Lc7arCk5LA85z9s4B3u2ncnMwFggfESepOVkdDQBvdXCKGjCcg7w5qB/YvAPw52RGFQ8et80jtyu2QV4APbLzQTqgGo/DBaQRmxOGHTDfdVcOvreXuzYzu3YWU9/KOdlLAG4yb4BebuzdgbNhoEv7cF535OTzl77OA2QTkItO+CBjNbjNNad3sQX+ZPYpFLs2J723+6Af/84bdt4m3ibeB7wPeB/wPuB9wPuA9wHvA135gIe8Pdtb6elejK/v7et9wPuA9wHvA94H9hwf8JC3b+fS3s1LDBsI73fbdVffZ/ur3Pq3uL/6KSQ3DGIL1etuflhe+LorOWYHi11uYXkWF4C82wErJzl5vHJ5LKryWGw75AUCRkcHQDcAuxFO5ZYHAHI75M09tplyYG68AigUU0WERzQDKKOqjsRVGcmdEM492hmQS70yRWPlQcj1Q19l28Ay5eUVpSotK1FJeaninOQdy0neetURknXBib3gNG8SkLrjY5rdk7wByK2tDuBqfaJWY5Kc5DXA2nvIm6zNncoF+lYn61WdzEFddEwkGgJdGxK1akjUBCd4c3A4B3mTjCeAxUmhU0OiUnW1MR02tj4Ha8sjipTn3mkcj/Goa2xW3nHyevsJ7MCWwYlqHo/Ne5KZkxygDwBtJPeIZ05sY+/KaC6QrohVbDvZm4O8lHnI29UC7O9yW7zE7uLuLG3vmDXIyzV6AkLdxxYDP4Gi+aBrGOjm1umOp3sHEvJaX6ZvvmvGw/js5C5jAO6aDbFHZ+/eNZtafYv7e469fL9B6H3A+4D3Ae8D3ge8D3gf8D7gfWDP8wEPeft2s9Jv5Ht7eh/wPuB9wPuA94E91wc85O37uR07dqw40TsUIK/tw7ux7dWHY7eOpXv6W6qnELYr+WF54euu2ts4LHbHbHkWF4C80eBxvTy2F8BrkDf3mGVO4sY6ACyncQG75Yq6kJfTvPFo7jRv8Ehm4GBMsYp4AHkBvTyemccM87hh0nZKmFOlucc/lysez4HHSKQD8AaQl9N5EVVEylVeUabRZaNVWjZaVbU1qh87NjgVC7TlPbxB4JHN2yCvLQwe1ZzYFnKQ13nMcrIuOH1LflDWg5O8nBTMPbI51xZwyynd2jpO8tarNpk7SVyXbFBDsk4NtTUdkDdXj/o8stlCfTKphmRCY5LVqq+N670GeSt4Ly+ALaZYPPc+Xt7VC2AH2MaCU9TAek70RoKTurwDOQd5O05bRzve7Rucxs09bhuYSzA5tCUA6sknzp3czp3i9Sd5B37jwRYvsbu4e5J24SZyXBBK2mAv4NTSLuS1tMUGhQ202nVfxybfYtPNvSbPAnCXE7xc8xgKg9w9sRV1XZuT7uom7MsHfl14m3ubex/wPuB9wPuA9wHvA94HvA8Mdh/wkNf2ZHzsoYT3Ae8D3ge8D3gf8D7QuQ94yNu5fXrqPzArAO/hhx8eHPwK73fb9WD5Pm362D6+7esXisN7+IzDBatdjcutS7qr+l2Vh+WFr7tqb+O32OwQHiflO0HeiggANRqcti2PdjwCOB5TrKoqB3w7ACAQsaKiTHFOgHLqFsgbi6i2ujL3ON/KuGJxYG5EMWBkBfC2SrFYLsSJt71/l3dmchI1KkBlJWCyAoCcA4oVFTxaNpZ7pCyPgQ7yY0JGaUmZKsoiwXt93zv2vWpoGLMN3nIjSCRrNXYs78LdcVHU19eppqZatbW5R7gCfWtqO0BrHY9OJt0RQm3DsoJ+ApibCB6pXMMJ3IYxqqpNKDlmrHjfbrKO9wDXqgbgm0x0nM7NvXs3ybt5OenLY5vrG1RN+/p61dXXKZnMwWd7zPRhY8eqKh4P3kUc2CoeV1VVZQB6sV8sgOTYOhacXsxBWk7ucjozHixgwBwgDwBXVj46AObMFfM+upwTvLGgHgC3Kh4N5pV68apKlfEeZABzBPCbe1SzATYX6FEOWPOPa+6fjRZb3IVid9HnS3MzdPM5zYos5g0/xT9sXi3N/FJOsLl20+RZGyvvz5i+OIlsOhjYRV87uUsddAifZA6Pv5AdLb+rm64v7x8/93b1dvU+4H3A+4D3Ae8D3ge8D3gf2JN8wEPeHfdlwnsr/trbx/uA9wHvA94HvA94HzAf8JC3b32Bg1BAXgJ76rbvHY4Hw3dvVydjGAZ3bZ/fYsu3esS0Hwzj6EwHd4zdSbvjC6d3grw8yrc8VqmRFTUaGanViPIKFY0u0ajiYhUXHarY6EMUGT1CJWXlKimrUHT0SMXKRgZwsLSsTJHiQ1VWdJBKS0pUXFysspIilZeO1OjSMpWWlqukdKTKyooDR+KxzTmQHFdpJK7RZWWqiRapqmy4IqNHBRARWFlREVN5WbXKRsc1enSJRo8uVklxqUpGlmj0iBEqLypS6YhRSlRVq2J0cQCcg9PCPMY4NlqxWGnuUcYBoAJg5x5BzQnkumix3lsTUaKmSsBZTt0m6wCxtUEIQG8PIG91TY3itUmNjCdVUjNGIyviqgQeB49erlZ9IqaGREz1tTx+GcCcVLy2QaOrx6q0qkHl8WrFa2qCk8nVCXTIPeo5VneE4skjVF83RhXl5SouK9eo0WXB0fry0WWKV1YKGF4biylRWaVItFplsRpFK6uCU9mVFWWKlJVpRGlExZFqFZfwztIc1C2tKFNJWalGlZXp4NIKjSivVlFppUaOKldpSalKS0apuLRExaXFKi09VCWjDg4AvMG1fGCPMg95+29DpquFH17oXV3bzZD/KOHEK5AU2GvAl7kEljKvNu927YLcfL7glvdH2vShbwCvQV764h7E2G18Foft0ZU9O7sh+7L+83NvW29b7wPeB7wPeB/wPuB9wPuA94E9yQc85O3bzUrbBPaxt6v3Ae8D3ge8D3gf2PN8wEPevp1T9vkHI+R19+Xtez954f1729cvFFv9fPKQWyjf+hzo2NWnO2kbX754J8gLGCmJ1uo9ZYdp3/iRuufpF7QxndKYuqQuPvvXmjn+XMVGvkv/fc5FeicrnfKl41Rx6Ht06OiYfvun8yQ1Sq2bpK3q+NsiiZD7S6XX68gjq1Q6epRKyypUFo2pNF6j4ZE6fe2007Rh6QP6YOU/qHzkASov46RoZQB4E9VH6c030oGQltbUdvFqkrYinw7b1dK0Xp/+2AcUj1TpU/92jFLNb0lqltRqKqhdUnqr1JZt0s+//GkdVfpujamuCE7y1iWS4hHJnKDlFHB3IK/7IcJ/RFQkxuqHF1yn08/+q4piSY3m/bmcfhw9QkdUHqT3VQ5XQ3VEiY5HRscSh+kXF96gS6fcp9LKhKLxmGoCuJtUdbJO0brDdWj1B1SaPEqlpRXBfyGMm3Kr/nrTFI0qiWjkiFEaVTJSFaNHqqroIEWKRujg0VU6sCKpQ0oBtUWqGX2gyksO1s/PuVwXTbxTRaVVKi+LqzxWq6M//kldeu1lGhEt0y/+91K90zFjGUlt26yGebM69w8/UHXZvopHSnaAfWF4x3g95O2/DZmuFn6+xd5ZHjdH++8X6nFT49n8+LMLeu1krM23AVa7HmjIS3/4GWsQPYHTQF67cTMuxmM3/0I26MqeA32T9/3139rxtvW29T7gfcD7gPcB7wPeB7wPeB/YXT6wp0Jefou5+yJDMb3tCW2d/JM/4+zrsfa1vHy239U+utu+u/VMx0L1C+Vbu8Ecd8ePCuk/lMddaEw+v28Bjbent+fe5gMe8vatz/M5M5ghb6F9e8u3/f1CsdULx/n2/XfXbwG333x6dZYXHpd7nRfyjowk9JlTf6t1kv7WAfzaW1qk1kap7U2pbWMASbOg1ZaM/vu3v9G7imL61Z8u0KwJF6t6+DCNHH6wPvzhj+ieO25USdEwDT9kuEZHyvTIvOlqGFOk4pJDVTy6QqXRao2qHKN9I+/Vl755it557S59qGKYSkfsE5RHIpWq4BRvcYNKRtYGJ4IBmgeNKNa5fzpbs68+W9X7DdPIg/ZVUdGhipYeqPoaHilcrY994jO6774ZOvjgYSoqGq4RRSM1YkSxDikq1X4jSjRpwrU66/NH6cMjhum9VaWqqeXxyYkc5E10QN5CX/DtUc7A2ERSlcnDFK87LDi1W5Y4TD/+yy16XQJBq629XdpKSOv5h2fo8MpDVBFl7FXBY7GLown96JzrdMHN92p4aUSlZSWKxMqDd+Hy/uPieL3OvHSK1ncA1/b2NlB6gM6BsODtFknZVLN+8B+f1diSg/T0wle0qV1ijtraMlr72iJV11Tr+3+6UufedJ/2PSSqUSOKFSkuUnHR/po0/Ub98Le/0bCDKzXswKTGfPRLmnb30zrg0DIddMgIHTj8EI045ABVFA1T1eh3K1YxykPekbtvc6SzBU+Zu8i7k3ZvjtxsAL7klZSUBCd47bHbAFUDvcRhyGuwd6Bi9AHq8iWHmFPInEYuNGazG+WW7k7s3oB9evf5vbe9t733Ae8D3ge8D3gf8D7gfcD7wFD2gT0Z8g40oLL+bAPY4s42wMN1TAZtKLO2Vi8cU99tY/W7G7t9WJ8mz/rqrqxCupgci5FnfbiyrX2hsnBdV56VhfNMppVbTD1LuzH185Xl08ltF+7XLSOdr9zy8vVXqL21CZeHr12Z9fX1ecdqerlxWE4he5h8i8Pt/HXfQhBvT29P7wODxwfsPvz+97+/4L3Vz1f354vPmb0J8hrvME7gMoDB8HvC1ac7aRtHvjiAvC6oIT2iIqF/O+0P+u2kBRp2YELD9h+td+2zr4bv8w86aJ9/0IH7/IP23/ddetd+B+nHf7hMp5x5sYYdENGZfzpHU8f9WaP3GaYD3/MeHfWho/TwXTdpxP7D9O593q2DRxyqefNvVX0dp+sOUFFxRAeXJXRg5L0aNrJOJ37lv9S47B69b9QwDT9wmA4aVaKyspgiZXFVlFWqbHQseAdvUXG59imK6g9/+L3uvfKnanjXMBXvP0wjikap6NCDdciIETqkvFYf+sSn1ZTaoPb2t5RtTSnbtlXtWznvK3EmeGtLo3564lh98JBhSpQPDx6N3K338CYTQV0epVyTqFGktkHDqz+gQ2qP0iFlUR1QXKaf/PlqfeusC3TAoSU6+MD9VVp0sCqKD1WsrFjRyko9sug1beo4KQuo5fTs2x16tatFW9ubtWbFyzr6yPfr0JK4zjjvZn3jv6/RPgcV6dCDD9LwEUUaPrJYhxaN0sFF5XrPqAbNm/+8fnjc0Tpi/2H6f+y9CZxlVXmvfbqraz515nFP55waemIWwuiEQQWRQSZREC9OnxMRFRFEQRQTY8xNzGAcYhSNQxxi1ESMmqhMUYy5GT6/e40ao4n35jrkKiIIdPf/u88+/VbvPlRVdzXVdHXx+vst19preNe71vrXpms9tdYOi1Oq1ttqtpuqtdo64eQz9MNfSD/e2Q+ndMHDN7391Zody6lem9C7P/JJnXLGs/W/70rPY6cgmXni1DPx5Ve+XNXSqJqVcUVhM71yOwvzBnXkJ3kP3AbM3rwYsnV4OfDiW+glQR7glPXlZK+dlmXtyQOsWtr0kNWC5T2Y2MCy2QXo4guBNPlczWwv78HYxpUdcza9Gl7s7sOB+3nxufe5dw24BlwDrgHXgGvANeAaeCg0sNYgL5uFFpbaZLVN2sE428bsZGMrB5zZLVOWR0zdQfA12Ef2mTZWH3s88/stgT6Irc5gO+vP/LNnfh81m4cccsi8zaXsZPvCnvlCG8rMHs9ZO/a8WJz12dI2b4M2szZsTBZbnzY28q292bVn6lJOXWKerU/rg7pmgzkmTciO2+qaPebB6mXLsumsDwvlb926NbWRLSNtYxjM39Mz68s4F6pnY8ZvyvE9e+uY+Wp923PWFm2y5dm0lVmcbefpvQccPlc+V66Bg0sD9h50yLty63booYeKwF56dm88m95f/ybO9pFN27498eCe/ko8m/1sn/trjFm72f72JW1+7028MOQNp/XLl1yha2/8ot74sa/pf+48KZq9vHfH9nv1xVu/rF953R/omVf/vnKTHV39+hukHd+Ttn1H2nZ//wTrds4Dc6Z1h+7Zvl133fvviqenNDo5qclyS69+wxv11j/+sHLlGZ194UW6659v0uHVnL7ytdv0klddq7hW1UyjoqjVUBC01WoFqrW7GqpN69rrr9VfvfWFOnIopyCfU63eUrXWUKkWKDfV0tbjHqlPf+bDGh4CMq/X8OiExsaLGpusaP14WR+88Z166ZM368ixnDYFU/2rme2E7mIneMmfh7xzKeQN5g7Rac+7Tt+VBDwlcEE04Rf37tCObf27q2++9Q5VmomKwYxGo40q9DYr6Eyr2gx15Q2/q99810e0biKvSr2k2elAs1FVSWlc1UpLz/3V9+mp17xNuQ2Tmhgb0WQ+r4n8lPL5SY3lqxqubtatt/2jnv/EY7RpXU7N8Q2amhhXeXKdSoUxDU02lRvv6AXXv0O/8d6/VG5DQ2+8/lp98e0v0yHDOU2N55SbbCg3HCk3HOt33/MxPeGcpys3NKHc0Jiufv0b9JIrr9Dk2Do1y+MK233IywshGwzkkeeQ98BtlCz3xbGnlwX2eKm2Wq30F19+seCXM37BYc2zEJa1Nx2sVIx9gv3SzS9Q6IuA7+bfYi9+q7PYvGRfwJ4+cLr1ufe5dw24BlwDrgHXgGvANeAaWMsaWGuQ1zbL7fc0ex6MbZN2MM7W43dMQjbP0i9+8YvTkyc8n3jiieLZygZtLvR8zjnnCOBHGTFtrZ5BVZ7JX8wH6y9bx2wC/2hvoM/qYgv75Jt9yp773OfKgDDP5pPZpr7ZeN7znjfvq/lsZYOxlVtMObbx44gjjtDZZ5+9mx+D7bPP2DjllFP0mMc8Zn6+bDxZ+9k2NneUZ/OZAzSSzaeu1c/WJU0+c/DsZz97vo61z0LWxfwwe9bHYD+2Hll/rA2x2bXYyp71rGfN+2N5Vp8xEkwT5NMvNsjDf3setJv1z8oG42x/+P/oRz96fm2pmy339MrBEJ9Ln0vXwIHVgL0LHfKu3DqsNsibZRKL7euvVH62r0FGsD9+/xjsY7nPWX/3lF4Q8jaDWBPVQLnKjG74yFf7cHG8rJHR0RSUDo3ldcyJj9GffeavlRstKTfRUC4f6zXXv1Z//tbLtHksp8mxUR197HH68mffqtZ4TqMb1itfa+svbvmk6nN15abqKjVj/dv3vqojjgLK1nX2hU/TXd/8pLaUctp6zHH69/+8TydvDnVEIafZdklB2FI7DlXvTGuoMa3rXned/voPXqSjNuSUlIfSb/y2WqEa7Y7Gyl0dfdIpuveeH0k7/lPb7/+Ftm3rn+Ll67zp131/8TNd8aRDdOx4TptbU9q0ceNuYdEXOSd4N81pjm/2zs0omNmqk5/9an3ojn/TRC1MTxQWKg0VKk1VynVN5ps68pHn6yOf+7pyE6HGa0l6XXSl2VKxXNLIZFFXvOF39eZ3fVTrx4uq1moqFfNqFEY0y9XXk2N63q/eqP+x8/pnzuCmJ5J3SDt2bNf2HTvSK5vvvutuXXrGY/S8c345/T5xOtrt/yHd+z1px936lVdeq+e8/m267sbPpzD3ute8Vre897X6zl+/Tdp+p37nxg/r8hveMX+i2D6rTPzz+7G2Q//+zb/T4TN1Ra1qepI3C3izcM8h74HdnFnplwYvU14mxFzlzPoCXfnlgl+yCABXg70rBXfNDnbtjwb4ueQXJHv5mk/2smPspLNzMPicLSNttjw+sLr1+ff5dw24BlwDrgHXgGvANeAaWMsaWKuQ10Aiv6sZcLKN2aVi23OhThZ0ZfMpu+KKK1JISfrYY4/V5ZdfPg/iAGvWh/Vvz1b2nOc8Ry984QvTeuQZ5GOj84ILLpj3mfaPfexjU/v0QXjpS1/6gPCyl71MhJe85CVpTB1s0S9zAQx8xjOekfrMuI455pjU7qMe9agUmr7gBS/QE5/4xDQNrCMfv6hrAV9OOOGEtG+bD4ttfAvFVofrGEnjD+Fxj3tc6pPNyWBb6pJHzPwA0wHMPNPmkksumZ8HG//LX/5yEaze4BpaH4yPOQLOYwubPDMvg20oI+8JT3hCCsOpz88NbWmDFrLxRRddlNqjnQUA+ote9KK0Df7ZWmZjbBAuu+yy+Xa0N5+zsfk0WNf6oy4+06/p0+zTJ+WsM77jj82fxejI9JPtdzBt/RHThrmxQN1suad36cHnwufCNXDwasDegw55V24NVwPktT38bLxSIHdv7GT7NUawP37/MNv7Gmf93FN6QcgbhKHqzYZGKoF+609vS7/Ny7dlgYnaca927Lg/hX63fOXvlJ8YUaVa0Uh9Wle9+tX67SuepO66nIaH1uuY447XrZ/+XdWHcxofHtLIVDmFvKWZunIjVV1x/Zv03j+6QfVyTrmpis6+8EL9/Fuf1JZiTrncBr3nQ5/R17/0aW3M5zTTKiiOmgqTUM3e7AMg73RtJP2+bRDGakczGq/M6JiTHq/Pf+7jGh3KaXx0vcbGJjQ2WdBovqx14yV98N3v1MtPPVRHrgfyFrVp46bdwsaNm9QPAz9Im+Y0u2lGc5tmtGXTRrWnt+qxl16jD37l37RusqpKuaypwpRKpbIqxarGxms69Liz9aGb/kFTra26+Y6v656dwJkTznw394fqX6VMmuuk+cYu//vbz31clYkRPe+Gt+vca96q3HhD6yfLmpiqaipfUmEqr6mpvEbGJjW2fr3quZyawzmNFmq68trX64arX6xgOKdoNKf8SE5v+eDH9dSrfl25DS1d85rX6jNvuyJdr6uvvUpvuvHjyo1Gyo02NTw6pEnsDG3QhqEJrR8paGRkVMFEThGB09VRNH+KFxjnkHf1bMgs9+WxpxeFgVR7URYKhfQKZwOvBnkXAr3LBb+D9QG6/JJJwD66Y3zmi42VK6V5IQOhLW+xeH+8uN3m6tG/r4WvhWvANeAacA24BlwDrgHXwGrUwFqDvLb5ygY6v7cBEy+++GI9//nP3y1YvcGYdpZnsI/4yCOP3C0Aysjjd0LAJ7DN6nBC1Wxk7ZEHALOyM888M4V+QDjy6QegCwCmjkEAg2bZGGBoEO74448XYJFy/KEt48YeefZ84YUX6ulPf3pq96STTtKTn/zkFOyedtppqR88n3766TrrrLPSfNpig/Z2WpX2nL617+cRM14LNge0scA48Ofkk09Owe7jH//4FJgCYs8///z0dC4ANRvom3bmP22B4jafNj78WyhQbj7jB/5xAhgwDIxED9ikzPoCcDKX2LN+KCdNHlAXaIrtrF/MCfNO3qWXXqqjjz46bUM7s0NMv4O2bY5sbwHwbYDa2psNq2s+0R82GZuth22U46O1pz51CfSPdigDdPMHBYyJ/MGAT/wMYZs/AhgM6BQ71CFm/uiDdta3xwN7txnw73Pjc+MaODg1YO9ih7wrt3723y44zkO9b279GYewvf2HOrb+ic2n/fF7g9ne1zjr557SORY0C+eAdSEQpdXUVIMrfovKTVSU25DXDde/Vn/8B29QZSSn9bmchofXqTqZUxkoW2zoVb/6RmnHdyT9i7SD87L8D3z5H5Lu1/3b79fPf/Fvas3UFB57ij7/T/+uMKiqmB9SrtDSWRdeqLu++ec6rJDTSC6nkXxb//rDH+uKa16pVnVKSaOsJI7V7m7ScHNW17/+tfrC2y7TI0ZyMsgbRola0azG65t0xEmP10/v4qroH0o7fqEdO3akp1H5Bm56kvfeu3XlGUfr6NGc5polzc5t1uwcYJd/WFrgeeAHadOsNm7qanYu0ebNG9XqbdUpl746vdaaK5o5+do/W7vzA8BkbJduveXLKhYbqhgq94wAACAASURBVDa6mmzMqRRuVDsMNVlr6f95wzv12j+6SbmxukbzdeVKXY03Z1Wr1jVZLOl3/vSzOvfqN+s3Pn5rOpt9CNw/a8v/p7N973Y9LqhpbmhII8Wufv8jN2tm0wn6wbe+p1Nm6poeyemWWz+lx517hnLjNb3qutfos3/wAvXW5fSKX32Trn3v55QrzOiK639N2v5Dadv3pe0/147t0r07pH/51ve1sTip3lhOSaP6AN3YqUsDvgYAiU2IeyPq/fFD5TaX3uRZal1YO162tob24qWN5dla8wuGAV9gLAE9AG4XC6ab7LuIumaTX2KwSbn1Zz6ZL9l80kuNhzLXw9J68Pnx+XENuAZcA64B14BrwDXgGnANrLwG1hrktb0Sfg8EOAERn/rUp+4GnoBThMWAGzZoS8xmLhCX64yzAaAFXLNyTkNyWhZ4SExdIKL5Y7YMvhkM4+QogPioo45K7WGXE6vZdviJLeAoIBY4TBtO3p5xxhkplAUuAmtPPfXUNAAr+b0V/wze0ed5552X2gbs0R57BGAhgBcbPBsAtc1sYsZLv1xZDIgkzXiZy8FngCi+ZMdLH8wNAX8XCtjixGl2/gGRzKfNCSDZym1s2bU06GhlgFP8BMYCNjm9arYsZnysIXNvtiiz8TMWADH9Mg+29gBv1oB86gL/mVuC2SZmA5txAQUIgGCCPbP+jIs1AabSxvxgDs0PiykjzRpkdWlp/MOG/RwA7klbG8qYC342gLiUmZ/oizLqWj+UsQdi4JxnAnUYG+O1nwnsMR5rjw0bi7XzeGBPd3CP159TfblOXCerUQO82wgOeVdOnwcK8trhLH6/sH38hXiD7fU/FLH5gU9Z/1bqd6A98Qnrfzlxdl6w32g0UmayMORNEpWDSO/70Psl/UTa8dP0dGmKL7d9V7r3m+mXZ7dv+7l+8O0vaCbakF63/M6P3aTrr7hU7dGcJibyOubY4/SlP393el1zOT+mQmlKX/jSx1TvFPXGGz+sx5z3bI2PT6pYKCpXSnTmhU/Tz775Fzq8kFN1JKcNo0W97PVv0te+/R3FQUvT7Ya6Uaygs1HDjYUhLyd5W9GMRupz2nT8Kfr4Zz+l3FBOG4ZyGhtZp5HxcW0Yz2vd6KQ+9N4/0guedIy2TuTUa1U1O7clBb1zm/gFgwDoXQzydrR564w2bt6semeT1rcOUW5qWuuKifLlQM1qTa1SXlGzoFZ9ShOTY5qcmFC9MKVyual3/umX9LxrflOlRktD+aJe8Gt/qNfd+BkNTTW1bqykxz/thXrTuz+psQpXZzf1ma/crhPPv1Cv+/AX9YjzXqihQlX5/Hj6Td6JfEETpbpu/9wX9MRWQ7O5nM4877n6L1e9Rbnhjm549Zv0psueqTMOL+tf/+ETagcjym2Y0PVveK3eecXjlORyevEbfktXvf8W5SYCXXndNbru8vOVjOVUHe+v5VEnPF7/+Pff0mHVqmZG1qlTrznkra38L/0r9RJZrp3lvnR4odDGXkKkAbr8MsEvecT8QmIAdzHAa/lWz4CwAV7sUMfGQ7/0mX2hWZ75Qryn8Zg9j9eOhn0tfS1dA64B14BrwDXgGnANuAZWuwbWKuRlYxhwZYAsu1HMmDnNmAVxtmk7GNOOekC8bABoAeWoDwQGambb0o5n65ffI3nGFmAXkMczNvGR31mf+cxnpicrrY3FtAWI8h1fgCUBmGjgF4AHZOUZSAhEpa61xz79YIeYfECctQceA2CxS5rAqVfqGhjEV2ArUJMxYIs22KEMqIgPPFPO6WkDhfRHHerTbjCYnxYPQl77Bi/j4Iph+qEu/lnAPnk2Rvy2fvCJerQnMHdWRkw72mchL/XJs3bAVNqSh3bQEGUAUSAv/TFeIDX2eDZ/iPEB+8wLgZPXQGdiAnlAZNYZLWXb4iP9ZgO+UAe/yCedDVbXxgzkZhOdfFsHg7zoh3HQDzpEm0Ba84H1NHsWWx6nw7HHnF511VXzafL4uTCfmCubE8vzePc18/nw+XANHBwasPegQ96VWy+HvKXduAIcgd8fDjbIi99hGM4fsFsQ8gZJT8VoTh/+8Af0lpc9SRvHcsoNrdO1179ON739anVyOY2OrNMvnXC0vvsPH9XGKKdcdUYfu/kbOrYbKlmf0/hETb904iN1y1/8vpobciqOrtdEfko33fJJVaZLyo0Oa/1kUfVqVfVmpFx5WmdceLHu/OandVgxp+JITqNjEypWqipVKqpVKmrX6+pyMrA3p5HGrF53w/XzJ3lnm2NKupz266jdmdPnvvbN+SuQ705PFN8p7bhT994v3ct9yOkh2Hukbf+p73/jawpaDc3Mbkohbx/wLgV55zS3sauZjT11Nm1ROe7pmje9WW9+1/s1d+yZuuPv/5c2NhM9/5xT9d9u/oDy+Zye8LSL9ZYbP6ygPKFSfly/87GbdeHVv63cZEm5kVG99Nd+T296z8eUGx7T+tFxnfa05+i3bvyEcmOBJqstffc7tyvs5fVrH7pJR51/mXKFqkbzYyk8npgc10SxqK984Ys6NYh06Lph3fylv1F99jDd+MFPadv9O3THbZ/STX/yG/rzd7xSwWhOudG8PvSh9+kdlz9a0+tzetGvv1VXfOBWvf7dH9Dvvf3Net1LzlV3tA95xyfzOuKEx+vv/+HbOrxS09zwkLoDkBcQlwV1nLo0UEdsAG5P8I3y1f6L+Vr0b0/rYutn8SBY5Yrkqamp9K9H0AJrbn95aiB3qZj6Fqwdv/DY6V3rz/Rh/po/9mzxWlwjH5NvWroGXAOuAdeAa8A14BpwDbgGDm4NrGXIaxvmtiFLTB6biUtBXoAUwAtARkwwWxYPQl7ApJURW5+WB+Cya46BXwYa6YvANc3AS2ApENjamc+AQCAsdckD2hFjlzUEEFNGO05nGrTDd9KAPAL9UAdYasCYGLB4yimnzINf6nGNNL8L04+BbOYOm5QxB+YPVy3zzV/7A2tgpcFZ+sMG4I/65qfNLTF5xIwHcGl1aGftAYsASHzhFCyQ2kA1/hrkBlIzJjvxm7VhfmT7tv7xj3HRnwFd/ADGMh6AJqeYba7xh7lmXmnDKWnq4AdzSV/YNntAXuwRzCfKrJyYtqwtaWtrbbIx5TzjM7YWCmaDOcUmMTZZa9IGeWnLuNAE88r8W9+UsY5ZrZBmvZlzA8e0xRfzi9PSBsKZS0C4/VGE+UpdDz4HrgHXwMGmAXuHOeRdOe2uVsjLHv/goa6H4pl++f3qYIC8cA/8bLVaCoJgNxa3KOSdak3rTz70x/q9K56sQws5jRfyetVrr9dfvO1qnX1USXf+7Mfapu362LuvV3ksp5MveI7+23fv0cZKTcnwBo1NNHXMCY/UbTe9XVWg74acxqam9Je3/YWq3YJywzmNTeZVLtfTk6/rSj2d/dSn6yff/Ky2lHIqjOVUqVaVBIEa1brK1bbKtUDtZlOtVqCRclvXXnuNPvV7L9fc+pyC4pBazZYa9YYqQONSpNxITZe/7jfTb97+67e+pqSVV77Y1u1f+e8p5P3Klz6n8ZGc8pMb1Gw2NDvLP+z4Lu+WNOw6yWvf5t0Zb+Iv+2Y0t2VOnc2H6MRfPkVf+8c7VI/C9LrjL/3Nt3TJaU9OvyX8v771Bc1t5frlpn73/X+mZ55/mlrFYb3zE19Mr10GQMOb+eYxV0jfpx26Z/s2zk/rze/+U+WmOjrj3Av0d196r8bX5/TbH/yz9Fron0q6V/dr+45+oM39d/1cJ4exztpyiO6/6y794v+ew778ildqqlTQf/znt/Wdb9+mjeWcKjmg/QZ9+APv0VsvP1VhLqfnX/9f9Q1Jb3zP+3Td666Q7v+edN/3pG136f4dff/++ds/0FyxounRESX1+m4neR3yHtybDQZH9zY2uGoxL12+0wvsJY+XDdCfX1KBt1nAm302sEtscJeYFxV2zJ5BXutvT3765tfBrUdfP18/14BrwDXgGnANuAZcA66BtaiBtQp5bROWzWODauTxDPTMXtdMntUntvrEwC42HznFmg0LQV7KgX7EnKQFAtrmNfDWICdXAgOF7TQkpyYpA+4C0LJXE5vPgMXsSV7qAxKBbVyvTBvgJpCQk7znnntu6jvtAWzUARQDIhkPc8D1zATKLE3MaWCDePjPKVS+h0uejQnoydXO2GeO8I8rjanPM6dSAX82furhM5AWW0B2YCMBqEhMHuXMLT7S1kA7MSCSMZDPWJlrAqdggauUYYcYMGtQEVvAW+aXuX7lK1+ZxqSz4corr0zBp4F2GytzSX+MlzHgCz5Qjo6Ye+A28wjI54pwxmL6IaYu9pl/yhcL+G5/gMA80o6rt7PaY8yMl4COiG0uLMZntMTYmXvzB9+Zf/KzkJc+qIN2aEffBNoCsRkXZQTS5KEV/AMYkzbdMhcGtClDN6wLUBh7FkwbHq8cKPG59Ll0Dex/Ddg7zCHvys01/00icLBqsf31/fFv8CxEtf39wf3+hwLqDvaBL4w3699Kjd/m18abjSnLPu9NGt7C6V3jLNkDl7nsA2kWOIoTtcKOmo26otKQmoUhjZbres0Nr9dH//B16uRzmspv0PjUpMqT61Sa3KB3ffAjetErrlFpYlJRraFKPdEjH/04ff6T79XJx83qpz/7se7T/fr6N25Vsz2siclRlaqB4plH6N9+cH8KJMGdH3n7deoVcmrUptRox4raiZqNrj7w8Zv1Mz6my//mv/d7v7Tj//TDfXwNV9px7726+dYv65pff6t+JunGd/+eSmM5lQtDKhQmlC9UlC/UVMgXdMG552jbfXfrj/7wbWrUa4qCSBvnNunQQw7Tls38grBZm9Orm/nlJBv4xWWjZjfOKJ6Z03v++H266ILTVS2OKl9p6zXXvl6f+MPfVjiS04c/8h5d9qqrNN7s6aSTn6C/+uT71JzIqVAsa6LU1BRwrFRMr1vmyuVCqaCJckmnXfxc/caNf6r1pUjvvvG9euaZJ2oql9MfvPe9eux5F2mYdtWi6vWKKtWK8rWG/urzf62Tej1FuZzKoyMaGxvT6Oi4hsdG9YXbP69TzzxFpWJJd3z5jnSu7rvrB3rcpqp6+Zze/v6P61nXvDn9/vK1r71Gb3jJRSmkbhUnVaqGOvyEU/Xlv/uWOvWmwvyEwkY9hXjohbCQjgB3/IOTeDGhmtgtXqkfIrezvE0hm/+F4sXWLpvPCxIgay9KTvVSbi8eftnIBvslBqCLRgjkceUzazdo2+ySbz76Gi9vjX2+fL5cA64B14BrwDXgGnANuAZcAwdWA2sd8tpmLDGb3/yOB0TkdKLlkZ+tB5Tj90GrD8jKQlDSg5CXk7lATgOmAEH6MtuALgOUQF7aWxmQEyBKv+QBSAGtADnzC/CGffKxDdgDquELz5QRgJHU4bQrbRkHdgmAXdphF9/wh2CQkDTwEWjK78rmH3NFPs/YAZ7aaVv6IM+gHs/YBxgOnkgGkAJQaQ9cZYOcmGcLnCTFFn0R8JP555QzfeIHfVg5Mc8WWAcbL2MgzbiAobQnXijYdcOcQGVtqEM72mOHMQEqGZP1T0w7wDSQlGfqsw5AVuC4jYH2rLsFWyPaWZ7FZsvGzhyxxtlg6w2wJk0ZNlljYvJYN3zAjs0LcwmgJ0YjrL3NJQCauafM/GZMNn5OA9OGMTIeYgJ1geqAX5sD5jBbB/3iC+UE69PjlYMkPpc+l66Bh0YD9h5zyLty832gIK/9DsK+vu3zZ1mC5T3UMawB3/YF8hqj2FOc5RyWpo2ls3F2/ORTz767C39bCPCSvyDkBdoBZ1rNpuq1qsrVmiZrbRVqFUXVdQqLOdWqeZW5WrdSVbVSVaFS1lS5pKlCQc1mOz15W6+31K5MqlYcUb40qXxlQpOTORUmaV9SEM2oFmxRpb1Z+WJT1VJB7Xwutd+oV9UMOgraHTVaM5pqHapCsFXtIFInqKtWmsyEvNq1ijpBW0G9pkoZf2MNT0ypOpFTczKn4tSwJqfyqX9ThaIKhaKKhYLyE2OqlKZUq5TVrNUVtkPFYaLDDj1cW7ceqs2b+KtB/iGVDZu0detmzW6cVdjpKI5DhdVxtSvjyhcKKpcKiqZyfZhbq2iyGWtoglOJJQWlDYpK69UqF1Rn7qrl9MRypdoUoVypaLJS1fpqqFwl0lCxqUKxpKgwpMpwThOFSU3U6hovFVSsFFWr7YS81XoKjpsjw4pGR1SbHFcxP6mpybwm85MazY9qw+S4RvINTRZbmpqaULs6oSg/rPr4qCYKdY1WY62brGp4ZESdwjqFozm1yiUVy22NlSINTVRVmMyrWSkqaDUd8j6Mv8lrLxl7CWVfQKR5SWcD8Jb3ikFdfnEh8MwfAfCC4oVFW16sZncwzr407T8OHh/YjSqff59/14BrwDXgGnANuAZcA64B18DeaeDhAnnZ/GZjllOIdtWxASors43bQQiVzbf0IOQFYALTBjfZyaMfTkAaWAbmUZ98YChg1tryOylrApAEilGHPimnjDS/s3Iak3bm+2C/5mc2BkBz0tNs4gMnXNmoBt7Rr13Xiz3qAYmBdQSzxaldgJ7lMR67Ypg6+Ir/tgFu7WzMlFteNqZPNnqBqfTNM30wVk4jAzANNmPDQnbs9GE2bb6wRaA+46NOtg1p6gI4mQ/6BHTii/kKeAeCAk9Jc4qa9cFX1oGrqrFD38wFYJZn2tM3NrFHP6RtLqgDdAV+W13m08ZvNm0MZsv8A0aTR7/Wn7Uhtjx0xjxaQL+c5GVMVgfgi1/2BwL4Y/4yVmyQhyYA2wZtyeNEM/bwg/Fl/bI889H88njlAInPpc+la+Ch0wDvMoL9N87n/sHPvUPelfsmb5ZTLJUe5Bs8Uz+bDxOxZ0vbyV2YCuxkHyBvoijqg94gaKgdNNSMAjVaNbWrkwprebWaNTXbLTWbzTRUmw0RavV6HxC3AoVBpIjrlWsVFctTKtUKKhRHValMqtVsKIwStcOugqinZjNQuVhQqzKloFZUu9lSGOBHR62wq2o4q0q7p3qjqUa9olq1qGq5sDMUVauUUlDLt3U5gdxqBykAbTem1G7k1WyU1WxU1WrW1WzU0pO79VpF5eKUmvVqCi25CjpocSV0W0E7Sq9vPuQQ/howC3hJ2z/oZpV0OwrDtqJ2XUGrplYQpHOQBA0FTcZdVKle11S6eOV0bI3ipFqtthrtoD+H7ZZarVitVqJGM1KtFanYijTVjFRqJirXWkqClurlKVVrVdWawOCS6vWq2ul4uM66pnKprLBcVAJAr1XScTXrNdWqZZXKhbRNpVpXpVJP56pWLqjdqKheK6cniiuNlkqVuirlqpoA9yrr0FSt3hRlU2WAcllB0FR753W8iIyAyLKBPD/Ju3e/6K+GDZGlXkSDZfbCyb6MePlkg9UhJp+6jNPujOePSNI/JGn13yFWfzEbVp71ZTXMm/tw8Gjc18rXyjXgGnANuAZcA64B14Br4EBr4OECeQFhnJAEPgGnDGCxUcszgf2CPYEo29zFDqdPecYuUNPaGpADdrH5i20AmZUDw2hPHtcrUx9/KKcNMVAYoEgZABH4RqANpzJpTwxkJB94ZzatHqd86d9sZyEv+YA+rgEGfAP7uA6aZ+wA96hDbAG/TjrppLQvygj4xzXKQE+eqUMeNmyeyaMMv6gHFCVwutnSnPRkLojtVDB+AxQNOnJaFf+wR5kF88X6oHwh/ynnxDSngrNtSNOG+QCwAlBpj33GwslmxgPI5JQsoJgNaX52sEVb5p91BeTbHxGwltignHEBh61f5gLbPAN5TUvkscbMndU1/7BjwWyjAa5BZi4poy7+W9rami3KsM14mAugOT4yx3Yimf7xh3za0Rd9cFrX7PDHAozVxoA90vRLH/hlPtgckG/tPX7wUMTn0OfQNXBgNMC7jeCQd+Xm3yHvAxkGvx8c6JO8HJaDf8A+8MVO79rhuCx3Wyi94EneBGiXhkhR1FYUtdI4DFsKmjUlER/2jRV3EkWc+o0iBXGUAs52EKRXrqYn96IovQI5aLVTqNtqNxUEbUVhqCgIFXO6b2fgOWi10nzSXJ0cx9hPFERcHx2rHcZqtJoKo1BNYG6roUaDQdfnny2v1QCA1gSkJvQ6USbEKRwNgasA4QaAFsDbEr6moLcVqNFg3EkKeznRu2lnSCHvpk2a3bhR0zMzipI4Dd3paXWnZzS3aVM6F8VyKb1KuR20VavXxPjjIFCz0UjH1E7HxvwROgqjbhqCqJuOtR111AySNDTwK4zUBH6H/blKwlDdJFYnZp4DRe12epq5G7YVB7sC4yQAswmMF0jLWqSgvt1MfQPYt+mnHYp1DFindGyR2lFb9VYjDe0wUKvd/+bqQoAXoTnkXVsbKFm4mk0bfF0MztoLinKrm21v7ewlli2z+tk4W36gN2i8/7WlcV9PX0/XgGvANeAacA24BlwDroH9rYGHC+QFbAHWAFMGnYgBU+QRDErZxrlt5AKwAI/ZQJ6BOSAv31sFbBHTD3WBg4At4CSAFbsAM4AcUBhgyjP9mC9sGvMM8AQcWj718BUYB9hlPLYpSowPQDquE+ZUKOUG4LBB3/hgkBS/8JGTqwR0gA3SXFlMf7QzwEua06kATDtpip/0wViwxzP9MC8AU/JoZ+NjfrjGGB84NZoNQGbAIdARv7BrfmMTWwapsZcN1LW+WRfSBnlt3mwu6BMfsJkNlNOvAWXrG8gMiGZMZosyAhCesdAWwMv8s2ZAYHygLfXMF67Xph71mQvyqQPQZ82wDzTGLr5Rxqlt0jY+S2OD+thhXQCw6ILx2algGx9tCbQBNgOqqctY8R8fbV1pwzqgWfKtLYAbKEwedkgDp6nP3Ni8Ux+/+BmgzMZPTGBMtDffPN5dhz4fPh+ugdWvAXsvOuRdubWyf8/AbrL77Nn0/vz3MP0YD4AbWPpAxXAHxrs/IW92brPpLPOwNH4EO/nqYtxtj5C3w73OSZKCwyQO1A+ROhwJjqN+fge42z+5mUJeQG8n2Ql8Oc3J9cUWc8qTdFfdpKdePK1eTEzoqhslOwP2Y3V39o+jgNwojpTQX4wPgTpxmJ4WjbkieamQdObH0Y0iEXoJ9rOBcSbqxIk6UZJe08xVzWE7SAOwk9O2rVagVitMw2GHHamthxymjZu3anpuo3pzGzWzaYtmt2zVxkMO09bDj0zBL4AUsAtx5+rqJOkpDpmXrqJON/W9k/rYTU8qp+XMW6d/GrbTIZ+16KbjYE1i8jq91FYn6alLWTp/cX98UaAu8J0543Qt6Z0B4MuJ3x72o1DddO4Sdfhmbm9G3aSjXne6v3bpesYKk1BBEqqdhkhhJ1aYWetOt39EfCFRkeeQd21tkGRfQAul7UW0UMxLeqH8wbyF7Fqe1bVn4v35Hxy3vbb06+vp6+kacA24BlwDrgHXgGvANbAaNLBWIa9tlLMZC/AEwAG3AFAGLg04AVSBUkBE27wlxkY2zpYNQl5gG/DKAn1aWwOgPHOaEygKDKau1QGA0R9wFGhnZdan+QKcAwoC2QyiGnzltKX1bzHtzDYnewF41APoAnMBzcA+4CP5xAYgbZ6I8QMAybXJBh/pA3+4Rtn8Iw9QbIDa+sYGY2P+bcy0sUA+dYkNGFpbs22Qmj7MJ+qbTezaiWrrg5h5MhuUszGP7WzAJpDXfh7ML4sZM3Y49cyY+V4v88Q60JYAKAV8kqYdPmbHwDwzh9aX9c8fAwBmWRuuwrY+zU7WhpVZbDA16x952LF2pFkP/APyAq1J4zvAG0Cc1T7zSX2bN/TFmqBd2mGfOSAAeDkBDlzGJ/qkHaeBeWYMtlaUsR62NjYGj3f9HPhc+Fy4Bla/Buw95pB35dbKIe+uk7wGmY0zZLnD3qSNVywWD9qgHnlWH2ZiB+TIH+RsDwryAj77p0PDFKoCEtMADN0JIoG6KcjbCf3mn3cC3TgGAAI17Srfjrop2DXI252HvJ0IgNsHycDGFF4mnRTwRkmkDmA2DtVLIWbY9yHpKiakwHSBONl5RzVjiTrqRdgl9MFuNu5EHRGSMElDnJ4i7l8lGwTAXSBvPwBsu70Zbd56qDYdenga5rYeopkth6jV26h61FWzHajNaeOAU7ttzcSxZhPGC6CdUdCZVaMdqhs0tDEJ0nlIkmkl3W569TMAttfBJ3zt+2yQN052h7wpnE06mu4kmk4CzXQ42dtfpz6U74N55pDvBifAePoCEnfi9GTzdNrftGZmtyrszCrodBT2EoVdwK6FWHG3s1twyPvw3SQZfEFlX072ktqXeCG7lmf27Jl4NWzSuA8P358DX3tfe9eAa8A14BpwDbgGXAOugeVqwKCWAaG1ssFsIAmwBtgDRAI0GS95nEYFUBlIA3wBr4iBXIPzYJu6FgP4AHPUwyZtrc/BtjwDwmhDDFwjTb61wQ/AMCDUoJiVUQ9wxhrhGxvL2AHE0a/ZpT11DXoC/mhjawvkBcwB/dhQBTQD+Zgb4CVpAvAXO9aWmDZASPywOaMNc0t/1MFfYkAxINrmkTza4CtpAvYHA/mM3eYmW45tO8mLLZ4NQlKPZwIwEhuWR0x9AmAWoGo+ZGPq0S8noc0/7JHP/DBOwCV/KEAeaw7wxC71gbecigXyMnbako8vWXvmO32Zz8wtWqKuldOH9W9pq2/52MUvygnWD/NuWiCfdNYua8wV2/wckEYLlNM/tq2u9cN6cmW4/WEB5fTBzwrzxR9QWH+UMRZOLVMHm0Bixsv8s2Zm1/z2+IE/Cz4nPieugdWrAd5hBIe8K7dGDnkfOshrPGOp2E7uLgR0F8obBMH2vNt1zf1TvDvhImA06p+25bQr1yZHO0/PWuPsSd40byfkjXZCXk6U2gldawNw7IckPXUax4EInEDldO90PKNePJOeAGYg03Gi6fTEKuCTE8Gc0u1DZEDywgEITT+06akTTe92KtZOZGW7ywAAIABJREFUK6dANIXYfbicAmbGsDNwmjYM+TZxlAZO9gJ660DfZFrR9Gx6+rb+f08Av/NPPqG3/NEHVeH0br2iVq2sXqumza2yNrUq6oat9ArmejinVjvRxuaEtjRHNZcE6nBCtzejuDudQu6Z9NQzp3h7ijrT6QleTkT3/e6oFxu07p9YTkF4Emi6E/bni3JOMO+cA67U5lRu0OupHm5UO5zRdLumuaCsbthITxPXwy2qRltVCTtq97oKd641fdqacYI76nbSwLeIbU0Xilk7/ybv2tz0yIJWSy/1stqbMrOznHi5Gypef23q0dfV19U14BpwDbgGXAOuAdeAa+Bg0cBahrwAJeAUcA7IRAwEJA0gBVoaiGTDlu/FUsacDG6w26auxdTLQl7g6WAbO13JyVbgnwEuNoZpzzNQjMAGJ9AM+EYfg7YA1Fzji8+AYOAecA0AR30AKKCR8WGDMQwCRiAr7ekPIIgPtCVNMMhIPfq3fGKemSurZ3NldTgZTB3GxIlP+9aw2SFmzvEdHxcK+EPfV199ddoX/VnAZ04Rm//4nYWS1OOaZNbYyii39pxWZc6sDH8Gg11fbfm2NsBs7NDWylhvrjTmZCx2zzrrrPk6XG3MONAHGmBcjBv7BNIWmAfqAtyzc4N9YDG6wAZ9ZwN+MPf0TWzXOpNv9cxXi7GDPfrkjwT4QwfS+EcgjT0gP8+MyfphLkkzDzYvPANzbU14xj4gHfvUM19Ye2zaM3U9+By4BlwDB6MG7D3mkHfl9Mt/Owiwm8X24ffnv6vp065mtpO09vxQx9Y/PjHmxeZjb9jGQnUWG4/V5ZOsfPK2w4HPztKsbSH+ls17AOTdBRLtWuX+aVIALwGoSh2MZCFvHwZ2FKenfXfVs1Oz/W/4cv3yzpBw5TNXP3PClBO6XKW8C/JyxTOQdjruaCbmJOy0uoTM6dbsQHZP9233fZpWJ55JIa/V6ef3r4fu2+uq15lWr8M1yH2IzFXJnEi20OtNp9c3R1Gs4098lH5yz/26R9L9ku7atk13Sbpzh3T3DmnbDknbt2nbT36kxxy+SVvCqua6oRrtWNX4CN3+N3+v33j5RTqynlOvme+feOa65O5MCtZnkj7s7QB4kxlFHaB3369upysL/cWP1enGSjptdQC9QHHqptc2c3Xzzu8aJ4Ga3WmVO0fpmEc+STf/5Sc0155UO2iqHEzr2JPP15997r+p2O6olZ6sbmkmbms6icRpX9YnvTp754leTvKaABcSoUPetb3RMvjSs5fTvsaD9vb0vD//Y+O217Z2fX19fV0DrgHXgGvANeAacA24Bg6UBtYi5LUNWNs8BkyRBoZZmmfqkZetB7gj3/IsNpsWA6yykBe4iC0L1i4bU2btOdXISVBALUAPQEsA2gLjsu1IA6uBblypbHYAb1kASD3sA3yBsKSzdbHN+MkDwNG/+WPPAEcg8WD/lJstyjjVyfgtn/4AfswDV/fSj4FHa4dtqz9on2fq0Q4bg+WMFcjNyVPSNjbsARXxmQAopy351CHGHyA7p03JM2A52AeQlZOplo8/BJ4HY6Ax+XxDmI1++sEuMQH4Sxv2pqhn88x6UY+5MfvWjpiDCeRTP9tuMM0z9Ux3pmvrZzCmPusNgGYu8JG8wUA77FI+qC2ra7aphy7NFnbRM5Df/qCButjhNC/5ZsPjB869z4nPiWvg4NCAvQMd8q7cejnkXf5J3n3lHVnIC1AuFArpVc3NZlMAXv59wr9d4GjGLfc13g3yYqQPQPvXGveSZP5btgZxrZyY+oBeguXvgrz9csvf5WAfwC70nJ68TeFuN/2Ob/9bvpzetWAnWPunS4HEi4do12neBHu703Dzq//dW4CyhT5MpW+CQV5O8wbtUI1GU60gUqUVqxAm+ofvf0/BoVs0MlnSaD7QROto/dWXv6O5zpyiYl7dVkNxu5lC0mqrp8nWsbrjq9/QWy4/XcdVcurW1qXfHO5Nz2q6t1HdqKe5Hn8ZOJP2Hwb4Masg7KoZJKqHsRpRrGYUqR2HOyF5W3GnpaQbKun25x2Y3kmvu+6koJfT0o1kVkPBMTr85Av0l5/+sGrFnEbqoda3DtVRj326Pvrpv9Vkua1Gragt7TFtrA9pJqpreporsaP0W8yDcNdA76713KkLP8n7sLpOeE9Qdk/lB2qTxfv1DT7XgGvANeAacA24BlwDrgHXgGvgodLAWoS8q2GjHAC2HD9s09jiwbaWb/Fg+Wp/NhC4Un4yD9iyeDG7C/XL2tg8WjzYfrnrZ+335I/Ve7Ax/pmPFi/V91Jly/VlsTnL2sn6BOAFxC90Qj7bxtMrB0x8Ln0uXQP7TwP2DnTIu3Jz7JB37yDvvoLdbDsgb/aZq5ntsORKgN0sj3sA5KUQAMpVv92EK3/71/72n/vwt//d112Q19rQjjTQN9vJ8tP9k8AGWvvwt3+i2PpOT5YuCXkNAC/my+59WF+D1z8b5CXm6uZGo6VKraF8uaENxYqueOMb9FvveZdy64Y0PFzSOz54s17wiv+q8Q1Tqk2MqVaYUKtRURgGKtS62lA/Xrfe/g299WVP1tETOXXKOXXTb/M2NZ2ESkLo/bTCmO8O99ITxjO9TWq0ZtRMtuiWv/sn/cpVV6naqqrRqijpBArCpqJOoLATpt/RjVIgGypJ1y5Jr8xO4lCVcFaPveRa/cmt39Ldd39fX73to3rVG16vH0hpuFPSz8Up5F/opnddr0c0c5qNSingDZNQBATI1dHpie70VHFHfEd4cI39JO/Da6NkTxB3T+UP1aaK9/Pw0qWvt6+3a8A14BpwDbgGXAOuAdfAatKAQ96V26Rczqa6QTqDYctpezDWXUnImB3/nuzuqTxrayXSD2V/ph2Ll+P/vrQx+3saI7aB6xZzlTdXaXNSmbZ7am/9eHxg3k0+7z7vroGlNWDvMYe8S8/TcnTkkHf5kDd7IjebzgLchdLUhYnYd3e5mpmwEEd7sNB3LyFvFvQCf/ne7WLwdKXyDcL2410nb/sQenAylvdstnedGN4d8jKG/jFpg5ozMxsVtOP0+7W33f6V9Erme7dL9+28shk2yv+4vpnQ/98Ofe2WT6nXGlUU1JWvdjVUP05fvP2f9ZuXPUWb1+cUFHIKmwXNNter19igVrulRjyrarujZhArajbUqrWVr27SVPtI/dUdX9dlV75CjdqoosaYgmYt/V5wkCQKunEKegG+/Wuwd36XN45SODvVntMLf/MT+sBt39ZnP3uj3nzteXr9Ky/RyOSYTrj4FXrPHT9UbiLRuec9RZ9/1yv1S5Wceq0xAY2jBJuRok63/43gTledDtdcx2noQ/dda++Q9+G1mbIniLun8tW08eK+PLy06+vt6+0acA24BlwDrgHXgGvANfBQacAh78ptUi5nQ9Pr+rw/WA0YqLX4wdrb2/Z7grTmD1dIA3Z5tjyDI3vbl9fznxPXgGtgtWnA3mMOeVdOmw55HxrICwvh94tGo5FezdxnjH3euDyOuYu3LdVuGZDXTvXuBIf7HfLu3QCWGtziZUDehQCv5VFu/VvdnuK4qyhKVG1GGq3Gyk3WlRsZ14bhYeUnxjQ2OqyR8QkNj+e1fmRS+fyEouqQeq0RhUFN+WpHQ/Xj9YXbv6W3v/pZ0r9/QdrxM4GKr7/yGQorORUrFR372NP1w59Ld94n3btjh1796usV1Lfof37/fnHa9m5J//yNv9VhG1vqhO0UPAfJtILejCKuVp6O1e0Gmu4E6iVBCuX5lnC+Nadf//BX9YYb/1yf/8w71BzOqT2e02RhRL/0tMt19fv/RrmJns56ytm66Q8u1xH5nDrNEcXdJP3ub6ebKE6/ydtV0jXIm6i387ruXXOWpFCZ75vwPRDihf6agbxB+PdQ/XLt/ezfjZzBdd3Ts6/H/l0Pn1+fX9eAa8A14BpwDbgGXAOuAdfAgdeAQ96V26Rczka0bRIvN15OH173wKztwTDvBl331ddB3S5mh37s+7zUYT9usbqe73p1DbgGDgYN2PvPIe/K6dUh74OHvItxrsH8hU7tLvbp0yxX25e0Q97dYG9PSbJw4LpmFiYM2xqvh3rUpa/Sv0gpdN0hibB9xw7dv6N/uvfOe+7WU847W7XqpNqtotpBTRPlQEO143XLl78j/eTv9ehOTvnJDTrn4ov187v/XZu3tFRuhnrXBz6tWuco5YqJTnnGc/XTe6XjW9Pq5SZ181f/Sf/lFVdraGJEldKEwnYzBc+taE61aE4FvtsbhwqbRfXaBfXihjpxoDiM0+ue/+xvvqPnv+oGfeHTb1V1KKexsZxyE3k9+mm/ojfc+FfKDbV19llP0Z+/4xptzufUrgwr6iTq9noC8na6QT8k/aPlMd8t7gDHs2DcIa9voCxvAyULgQfnjisNBvP8eXnz6/Pl8+UacA24BlwDrgHXgGvANeAaOPAacMi7cpuUy9mctk3iwXghG3tTZ6F2nndg1tbnffd5R78+J7vPic+Hz4dr4ODVgP032SHvyq3hwwnyFotFLRUKhUJabgcRByHtYs92ZTPllibmmd+3Wq1WenqXg4+DwNYh7/zJWjth+2BiO51rJ3ctZuKnFwjk861crmsONNro6vCLr9MV7/sb5UbrGpuY1PDoWBo2jE5qw9iEbvzAjTr9rNM0VSqo3qqrFVZUqAcaqp6gL976Tf36i5+o6Q05jY8PaUOpodu/9kW9+BUvVG6ipdzUrK674S362Q7pu3wvd5t0ciPWYbkh3XrHP+oZV75a6yfzKldKisJAYZCoFc6ou+lI/esPf6q7t2/Xjnt/qmdf9BTF7YriqK1O1FGl0dX62iYdevwjdftNv68nHFvQj+78n/qppB9J+j/bIdUcLL5Huue7+n+/9BE1GlW1kmnFUZyeCk6SmjrdpprtVgp3OcXLd5u5rpn5MeH6dc0HfgPhYNrEccjrejmY9Oq+ul5dA64B14BrwDXgGnANuAb2RQMOeVduk3J/btrbpvL+7MNtHxxaWA3rZHq0eCmfqLNUuZe57lwDroGDSQP23nPIu3K6dci7C/zuK+TNwt8s3LVv7+7vq5mNv2VjP8m7Fyd5O50+5O2fVu1qorVJx176Rv0PKQWk23ds17b/e63yth19RrpN0j3b7tI5Tz1LE4Wiqs2GmmFBo8WCcsVjdPuXv6PfePHjtHE4p9GhnMargW756l/rBa96hcrHna9v3Sd96I/eqeFcTo1HnqX/707pUY0ZHZob0a13fF2XvOJaDU3m078UiIJYYdBRK+yo3GinodZsqVGvKmzVFLRrCoKmglagWrOndeVZHXHcCbrjM29RazinQmVUuVJD7/zop3T3Pb/QL7Wm1Mvl1MvnVBgb1mglUSnYpE6rpW4tr6g9qWpjSsV2olYyo+lWSZuCgrphc0HIyzdB/Lrmtb8BwkssG5a74eGQd+1rZLma8PquCdeAa8A14BpwDbgGXAOugbWmAYe8K7dJeTBtUruvvu4PRgMGOSxeypZBXqtrz0u18TLXp2vANbBaNWDvMoe8K6fR1QB5DZJyyjZ7Enal00ud4qVsT5DXeIX5OxhTDg+xk7vZA5BZAPtQpBeFvJzM7C4SKOus6MnaB3Mqd1/acpJ3sdO8dqp3V2yQt5NeS9zTZHuLjrzoBl31x19VbrSq0dERjYyOamR0TKNjkxoZH9O73/cOnXHOkzQyUdDRx52oH9/5fT353LOVmzpEt3/l2/rGl96jBMg6MaSrXnO97vnFf6ox3dMR51+hm/91u+LKpMZzOT3/ht/R/94undic1lxuRDff8T90ySuu00hhQtXqlKIgVBx2FMZdpXC31VKr3Vaz1VS9UVcUtRXHoZK4o3Y0q/HajB5x3LG6/VNvVjiWU6E8rLOffolu+fIdetpTztLP/vvf6vDiUAqA82N5Hf6os/RvP5H+ywVP1WknHKE7f/QvOvu803X0Y0/Vf/zkbj33gidpc22DpsO6krivC7RhJ3kd8j48NmaygJf0cjdj7KVJPNh2X+wN2vDnh4cOfZ19nV0DrgHXgGvANeAacA24BlazBhzyrtwm5WrdkHa/fI33hwYMdOwJ2lr53tbfH766Tf8ZcA24BlZKA/Yuc8i7cppaTZB3paHuoL09QV4rB97CJBaCuAvlWz2Du1zBvNDVzA8F3LU+FoS8FALqlgpm4OCNDfQOxrvgbrLbKd+O+pC3o/HWJh3xjF/V1yX9RLv/b/sOadv2bbrnvp/pzKecoQ2jRR1z/GP045/+QKc/5QyNFhLdfOs/6Yt/+amdX/S9R/fe81Mdvamr0XXrNVSZ0V98+b/rF/ffp3t/cae+cNvt+tF//EjHtyKF68Z1+Wv+q/63pH/65t9py5aGorCmOIoUhB21uLY5aKsVNNUMW2oFLQUhd4AH6Xd742RW5Xqi4487Wrd9+vdUG87pdTdcoV/cd4+Omp5RITeiq6/5Vd35s216xHRHtbFRHfHoJ+tffyJdesGFetLxR+nnP/6uzjn/TB1x0i/rf/34Z3reBadpa32Duq1qCnkBvQQgLwLfE+S1H6KlIN9q/iXdffNNJNeAa8A14BpwDbgGXAOuAdeAa8A14BrYGw045F25TcqV2kB2O74mroG1rYG5uTllw+B6G0SyeLDcn9e2Pnx9V/f62s+lQ96VW6eHEvIudijMIClQlvQgnLVnq2ex5S8WG7Rdbmz2rJ/FYqvHuJrN5vxnS1cDH10U8q4G5x56Hwz4DoLefj7QEng51Z7RiZe8Wte//xatn2ppYnxCpVJZxWJJU1MFTeYn9ccfuFFnnH2GxvMV5YsNFWsVTRSnNDxW0sRUUxP5sorlkoqlMbWqk2pPjKoyPJaWbyg0NDxV0NjEmCaG16s+NqJ4dEzl9eNalw+VK7U1VRlWtZpTHFYVR6GSZEYxoZMo6kQKO5GiTqy4E6vTxf+eonhazVasE457hG7+yxv1iQ/9pm677dNqVguKxsdV3ZBXbjzQUY86Xdt/+hN99N3v0mQ90UglUrtcVjw1pmZxVKXihMZLdeVLVYWFDZqpjSppVtUB7O6EvOmp3k4n/YfUUtc180OTBbyk9+aXY6/jmyiuAdeAa8A14BpwDbgGXAOuAdeAa8A1cDBpwCHvym1S+sa8z6VrwDWwNxrIAl7Sg20MIlk8WO7PrjPXwIHTgP1cOuRduTVYDZDXWJDBVIOng7GVWzxYPvi8N3A32wa7g8/W12CMzwZ3wzDc7bOlDz3DfODNxg55H3DttIHewThJT6YCeevtKAW9E42OJqZKqpTLqjeaqtUbqtbqqlQrKlVKqjZqmipXVao3VajUNFmsqFBqqFRuqlprpMIoFfOqlfJql4pqFMsqluoqVBoqV6sqFqbUKNfUrjRUnyqrVWtrqtzWeLGmYimvVqOkOGylJ3mTZFoxodNJ4W6Uwt4khb7kxUlPSWdGrSBWrV5TozapWmVEteqkmtWiwlJJQammSrmhqXxZ1ckpNbibvFTSVKmoaiGvemFCtcJ46m+pWFC5VFK9XFAnaChsNdSJozQkcdS/utkhrwPrmm86HUybTu6r69U14BpwDbgGXAOuAdeAa8A1sP804JB35TYpfdPd59I14BrYGw045HWd7I1OvM7q1IlD3pVfl9UEeQdh72LQNQtil0ovBHkXq28Q18qzz6TxzWLgbqPRSE/ucgiUsBrAbtYHh7wPgLwPJOE2YXaSNwiCFNAGQVvVakXNRiP9Di7fwm212qrXGypVKqo1m+l3cuutQI12pEY7VrMdqR3EarUCtVttBa2WwlZLQaOpoNFSq9lWo9FSo95Qq95SuxGqVQ9VrTTVbIaq19sK2rHCdpiGOOR65I46QNw0dJV0d4U+9O0q6vRS0BvFnRRG1+p1lUpF1coFRa26wkZD7VpNYaOuVrWiOuC6Ula7WVPQqilsNxS1G0qCpsJmTe1GVe1mXe1WS1EUKmg11U2inaF/ZTPzxT+m/CTv/tsk8A0Yn1vXgGvANeAacA24BlwDrgHXgGvANXBwaMAh78pvVvrGvM+pa8A1sJQGHPK6PpbSh5etbn045F359VkNkHfw95aFYK9BV2IDsXuK9wbymj0DuIN904fVwU8ALyyQg5/GCFdj7JB3GZCXBWRBoyiaD2HE92eT+e/Rku50emqHfB83Tr+VG0ZdhVEiAGsfxPbUSbrqpqGjbgKkJSTqJrG66feQp9MrmA3cdpOeunFPxCnQjbtK4q6isJPGgN5+6M4DX07vEgC8SZfrmvs+RFGioA2YDRS1Q8VBqCQKlMQE0m3FIVC3rqjdVBy00/JOHMyD3E7qZ6ReEqoTtjTdwe9dkDf9nrNDXj/J6yd5XQOuAdeAa8A14BpwDbgGXAOuAdeAayDVgEPeld+s9A16n1PXgGvANeAacA2sTQ045F35dX0oIe9iMNfAqpXbMzGA1SDrINQdhLjLLTfbFlu/1h/2sWn5qxHmLuaTQ95lQl6byD7E7CoGznYBq0BOC32Yyzdw43hGccwpW77z278Cug94+8DWQG9qL20fpnb639idVbyzXS/uqRdPi5g2AN047iiK+pAXUJzaol5nRt3OjDodvtM7nULeiGucYyA1QLoPhDtRV/1AW3wP1UkidZJQSdxUErdS6BtzDXMSz4ckTfeB9HQSqBe1HfL6poVvXLkGXAOuAdeAa8A14BpwDbgGXAOuAdfAEhpwyLvym5W+se9z6hpwDbgGXAOugbWpAYe8K7+uqx3yGmA18Ap0HYS79rwU5B0ss2cDvBabfXum/2azmR7wXO2nd41TEjvk3QfIm5647XTU7ewCtyx6Jw41HTU1HbWVpEC1pzjmRC7B7urmxC6neO1kble9JFEvjtVLAWuUfkc37EyLEHcAyF314hn14tkU9AJ0+e4t8DUVWwxwtZPBQN5pdTvT6tA+PcnLdc2d1C5+cGoY0Gs+9OKuZuJE03H/NC6gtw98Q0WdKP3Gb9IB8vavsu4D6T7kxeduHKjnJ3l9M2OJzQz7yxyPD45r5HydfJ1cA64B14BrwDXgGnANuAZcAyuvAYe8K79Z6Rv7PqeuAdeAa8A14BpYmxpwyLvy67qWIO8g7B18BuAavB2MDSZbHZ757i43+BrctTgLU1dr2iHvPkJeA50GPvuwNdoJeVvpFcx9uAvg5SSvQd5k59XMdpIX2NoHrABTTslGnURhp6uQa5Z3Qtk+5J3ZeWUzkDZUHHMfOG0ArjtP8gJ7O700cG00J4GjTh/yRtiO+9dLA3oNDPfijmbijqa5ajrhfnFO7mIXwBsp7MQ7AfEDIa+dXu51ElnodrDDtdX+TV7fGFn5jRGfU59T14BrwDXgGnANuAZcA64B14Br4GDUgEPeld+s9I19n1PXgGvANeAacA2sTQ045F35dV2NkHehf9MDXQGzdgLXTtwayM3GVoc8S1uMDbOVBb1WTtnB8t3dpQCzQ959gLxMaPb64j4Y7V/FbNCT7+VyTXOcxv2yXQvRP83LCV37Fq/ZA/JSL+7025APBE4hbsxp3T4UTiFsh1O/keyULWV9e9ZfZzfIG3ewuzOk1zZzdXM/9L8DnKS2sBmnEDlUlBD6IHmX/4PjT9RNTzZzurkf0jlyyOune/10r2vANeAacA24BlwDrgHXgGvANeAacA2kGnDIu/Kblb6x73PqGnANuAZcA66BtakBh7wrv64HC+QF/BqUNSBrYLdQKIhgzxZbPYutfTamjPrAXfoIgkC9Xi89rJhlXwdb2iHvPkLe/ndps9+pBajugqv907u7f4t3lziy9UhzQha42we8Vq9/Wti+8wvo7QfLT3aDvP3rlO1kMTbwB1icfo83jZP0lDCg1/oYjOP01G6cwt5dPu3uV7/N7v5yajcbqOMnef2v6xf6SxzPc124BlwDrgHXgGvANeAacA24BlwDD0cNOORd+c1K39j3OXUNuAZcA64B18Da1IBD3pVf19UMeQGv2ZCFs6QN3hrUtdjyB2PaYI+YupQb3D0Yv7s7yPGyzw559xny7rq6uD+hBm7Jt3Q2HgSrVjaYv/tzH+juvP44PUHcT6cANj3Fy0ne/jXP/RPFffg6f2J3HvL2AS9XQS8FebPiWE46C3hJ09Yhr2/cPBw3bnzMrnvXgGvANeAacA24BlwDrgHXgGtgIQ08HCDv3NycBsNyN98Xa0++2bI69vxgYzaSs/b31d5K2NjXvleq3UJjYH5Wyv6+2Nnb9V7I9+X2t6829tZH/LE+ltNmoXGYnYXK9jZvJWzsbV/7o95K+78ce/ZzsZw2+2MO3ObKgzCf09Uxpw55V34dDmbIOwh97XkhuGtlBnl5Jm3f3V0O9zoY6jrkfZCQ98AtMjC3/93cB8Q7v6EL0F0oOOT1DYeFNhw8z3XhGnANuAZcA64B14BrwDXgGnANuAb2nwYc8u7dZiXAJBtssz0LUqzcNoANtljdxWLqmR2LqZvNX6zt3uRnbQ7WN58H87PPi41jsfxs22ya+ntqs5g/g2PgOWtv0O7gc9aPvU0vZYMyfJidnd0NNGfbkLZ6g31m6w2WZZ+t3uD4rY71YfUs32La2VxZ3mKx9WFtrN5itilfqMzsWPvBZ8sfjLO2rE02b7D+4DN1s2GwfF+ezd5y2+K/+W5x1sZCdhfKow22bD6yNiydtZ+1sVQba7tYbG2ztqlr9gfjQTv72m7QzmLPC83JYJ/W1sZiz4vVs3KP9+6/iQ/neTL9P+IRj9jt/f9wnpMHO/aDCfICZZcKBnKXigHAlK+F7+4uxSEd8jrkXfTq5qWEM1jmJ3n330aAb7L43LoGXAOuAdeAa8A14BpwDbgGXAOugYNfA2sR8mY39Q0GDMZ7uyE52A6oR2CT1+JBaDD4bH0N2rJnqz8zM5NuGBMTtmzZ8gC4Q10CZVZuduiH9PT0dGqH9NatW9M8s219mU8WH3LIIWk96pNn9a3cYut/odhjl/r5AAAgAElEQVTqDMZWl3zzNRtn861tttzSlPGNOqvD+LO2Ld9iGwPtqWv5xFmbPGMnW25p5oO2zKm1sT7tmdjqU4YuyMvWy5ZbX1ZObL5Sz+xaG8ZsNq3M4qwNs5u1ka1n9hgT9uyZeFBLg+XZuoNpmx/6Nz8ZD2mzgx+0Q2dZP81WNs98pox8C1Z3MKY+/WRtDNZZ6Hk59RkjATuMzXy0GFusE8/UMX9s/OTZOLL9ml3aWXk2bX5bP4Ox2cWOtSONLZ7p336mzZa1yfqRLbO02bPnbDvzNVtGmjb2M0od+iZvsF72OVtu9bP2yeOZehay7UlTbnG2LXoj39ZjsJ0/O9DdFw2Yxhzyrpx+HkrIuxSg3ZuypeDt3pbRD6d3wzCc/+5uHC/0adLdb9cdZF+r/dkhr0Neh7y1g3+zwDd8fA1dA64B14BrwDXgGnANuAZcA64B18Dq1sBahLxs2mbBgYGBbLzcjd1sW9IveclLdNhhh6X9HH/88Xrxi188DzJsA9jAg/WVtXHWWWfNQyOrZ+0MJll+tt1iaSAGwWBPFm7Qv9kmbUDXYBBlz3nOc+bz6cPam+/Z+HnPe968PbNrvmbrLZYG2uAr83f22Wen84YvNm7aLTRO8k855RQ95jGPSfu3+gaGsm2yfVOPDWSrb2XUJ01+NmCPQFnWps3vpZdeulsZ9U488USddtpp8/Zoh82l5sXm7tRTT533zfozH4mpR352nKwPsJEyG9exxx4rbJ1++umpH1n/zY7VpZ2NB9v2hwHkEbBtwXzJ9mV9Z/3F9uMe97jUV+oSrK3N53nnnbegtp761KfO18UmPtDW5pCYgB1i+jfbPB911FG79Wdlg3HWL9rxTH+D9QafqXPJJZc8oJ6Nn59/S1uMDZsDYn7m0aHlk8c40A7B6g72vdAz62VzSrsnPvGJ6bwwJkK2jc1lNo82C/WHrizf5sfs0d8LX/jC1L61txjbjDvbF+2e/exnP8CfrB/ZNLae+cxnztvHFjYf/ehHi5+57DuJ/Gxb85F5POmkk9Iymx/qMffYJ2+wbdaOp1cO2q3luTTdO+RdOb2sJcg7eE1z9ru7QGC+uwvcJURRNA95Vzuw3Rf/HPI65HXI65BXvhm0ujeDfH18fVwDrgHXgGvANeAacA24BlwDB78G1irkZdN/cDOfZwt72oBmEzdbx9pZ/PKXvzyFlPQD5H3pS1+aQgTakWebwIvZeNaznqUXvOAF830ANGjDRucFF1ww3568xz72sbrsssvmw+WXX66XvexluuKKK0SavokJL3rRi1IATdqgCP7Q3zOe8QwdccQRaZ/HHHNMavdRj3pUClGANwDCk08+eT6fvvGfMds4gCjZsdo4B2Orn7XB2LCFPwTGddFFF6W2rb21sz6ZF4M99A1gpg6wBiDEPODPYHj+85+fziF16Qv4CIjDB9oyN9YGG1k7zB3re8IJJ6T1WA/6Zb2wSzuemTMDqtQhbb7a3NMX/Q+OD7/IowybAG/aYPPpT3/6bvWZC+A2GqBvxoGPpNGAaQOfnvzkJ6d6tHkkpv1zn/vctB7j5A8UaI8dbNDenikjYAvfCNhg3lgvYCJgnrk3P7Bp7YF61Mv2b2mACLaxZXkWA+EAvTZfNmcWsx60Nc2fc8458zYApbRlvbJ6M9uDsdWxn6vB8sWemSvTpa2dzRH+sX5mm3oE9IA9xmVjp56NizR/YAGYtLYL9U9ZNmAP0Ese47j44ovndY1tbHCilnLzOWs3a4s07wU0gv54J1AX32hLX0cffXSqk3PPPXfe96wNfKFf1sL6o539zGXrDvrBM+W05/3FnNn8YIv3Eu8J7JntrA1LUw6I5x1GHj9XRx55ZJq2tcPuUjbMlscrB+/W4lyanh3yrpxO+O8CgdOsi52mXanfORazv7f5ezqtOwh5uZIZ0It9oK7BUsZqwfLWWnwAIG9HSbI3IRHfjo07sRJCkqiTCWttIZY/HuZk8dCfO5vDB8bL72/pI+t+XfPBv+GwUi9wt+NacA24BlwDrgHXgGvANeAacA24BlwDD9TAWoW8gALAA6CCjX9gQzbYxvNiG/5s4lodYiBcNgANAAj0A+QFlPEMLGGjEuAAUMjasLT1ecYZZ6RQA+Bq8AFgA/Sx/m0z2Z7NBjDGYBlrCATBBv5Ql3T2tCP+XHjhhSlApH+AGFDyCU94QgrumBv8ARIC3Mg3e+avQRROYzJOC4zbAicqCean+U1bxgaAAVgSGCfQiLzHP/7xuwVrbzH1AUD4RMCelRHjI4HxE1h3G7/NIePFBr7SBpBp/gGxyMc2dphP/KWe9Uld+gUeEfNMGesA5CQYiCVtpxitj6y/5r/Zo298ps6ZZ56ZngrOtrPxETMu6xcdmi2zv1A7fGGOaUd9/LT6rCMA2+aPesyNzSX1+BnijwSAiWgEyMs8mAapSz3sG+jDHnnE9Hn++ecLOIt/tMsGTiEDt01TxJRjjwBINlsAXeaIZ8sz+JzNs/RiMbpjnRYrJ9/mkjFQF1/IA4hmA2XMB/NGPidPqWtzyvzzM8u8EzPfxPxxAG1J2/uJNDoF/PLO4eeSvGzgjzbwg0A+OgCAE2MPP/Y0LmtvMb6iQ3tf8g4AYvGzgG/8XLPO1LO5sbbURRu0Na0Q44/lZWP8N/+YN9bX/lgAYE7a9IXuzBfmg59V9JQNzDUaMt3iKzbwj/8OMDfUp0/8tzGYDx6vHKx7OMyl6d4h78rpxv57sBYhL3DXrmVmfPAvYK8BXstbaS62Guw9xJDX4G5XcdJV3NkZkq6S3UJHYZIoSCIFSagwCdVJYnWTJA0Ge1fDBC7mwyD0HHxerN1aymfM/Mecv2hb6i8vBv96wzcDHrgZ4HPic+IacA24BlwDrgHXgGvANeAacA24Bg5uDaxFyGsbsGw2A2CBe+wDkG/QFxADGDA4NbgxTV3yiLEBkMwGAALAgToA0yuvvDI9LQu8AehgH0hoMMFi+qSN9Q3gBfwY1ALQ0J/1b35hC9DJWIA+1CMNkAWc0SfPXBlMwCfGZnbonz4BtMQAD8AYwI52+EA7u+7XTsNZe2IAEKcR6YtxGpwCrBAoI2bsQCFsZdvTB/CLACS0YHmAH9oyt2z4MnbWCzhNvtnCD0vb/Nj8km9wlzLyrS4xY2bOKQOkEdMX+QT6ow0gkWuhzT7jwT/GDrjCH2LqAsGwRZp5ZU0I1pZ5YkzAKzt5SzobKLeAXfpjnbDJydlsGfOMTerYyVbKyaOMwFwDEPEHG/jL2gDOWDv0Sh0CuqZPxkAdyqlH/4yB9hZ4RoeUM1d2gpM1Yc6Yewv2s0UMdMMuOrc5Zj5tzfEHHTC/5JFG1/iPH/jH+mGLcaJbmyfaks4GxpVdP/zGjo2JZ053M2bs2vgsppxAmc0h80p7e6YPxkMdyswOugY40h576IqxM276JE0ZdQC0zA1tgdz2xxXWlnzWn1PsvKsZN2AJ8Ikf/DybPfOX640pp63lES8WqGd1rQ7riV00Ssy7jrEvVJc2lDEX+Mi7h9PApFkTnhlrNlg/FjNPzAVtSDM2+iKNzhkPmkCrxP8/e2cCZndV3n+e//9pa0UWIRszc++dLCyCyCIC2beZ7CyGJevsCeBCq60Fi1VbWyDJTBagBa3WpdZ/ra3ValWUqli2LAQXwAVBCRBIQggQQpZJwvf/fO7km5xcZp+bbfLmeQ7n/M7ynve85/u7JL/PPb+L3rHnzzj60YfPHHzhiwpAZ+z57QOUGYM/gGLm9lzkjLM/kbetl4hNy+cC+gzIWzyddAbymtX09N8dttNW3h4vaquN07u0YdM5fpaUlOQBbwpy03JvYm6treXQQd5cucqSBPRNQS+QtzSbyQPesjzkbQG8KehtbUGHS10h1C28Plz8PJB+BOQ9sh9A9PSDPMbH/ocGQgOhgdBAaCA0EBoIDYQGQgOhgX0a4MG3H6b3loe3rIe1kKeJB/lc82AWQAMgSIFga+unj4FDagvIkEJeQx6DENtiTsqem3YAA+AEe1xjH1gGpADauK9tkAOOgD3AVxLzGfxyqhHoBkACcgDJAGSMYw7sG2CQY58HqtgBhgDtiAfXlKkDkDGO9WOHcUBDfDCABbYRA+YAngDosA3MAnymr6ClDz7TXpiwn9YBhqhzAlrRjg1sAixp87rwjTbb8RrxnXG2Q47v1NHHcIx4sX6AHxAJKFQIeakHxgG/mJ8yOXFi3ziRDMyzXYAXZXxwvPDRfton+nDCEfCMX6yJ+JFos/8eRztjbYtY0Q/9uI12xrWV8InxzImu7Ivj5Tlth3qXgYys17HHDrohdmgHX9I2xrF+5mEsbawXLdGXRKxJlIkre0w/bJPjD+vkmngznjK26Y+uKKeJ9jTRBkDl/nI/9guoTT+vmbXiG2ukH23sM1q/8cYb87m/KMEeMTc+0o7/fGGCtTCWehL3p+8T5vG96fvY/nAP4SNzYpux7Cv9AZPoki948PlFPLnX8Z8y9wj90Sc+Mb5w/Z6nMKcfdRyGwQfuccAqcUDHrAeb1NOPeQptsC584LQ2ibEkIDHxcr1zYoUNxx1/uQfxxZ8btLFm4K99pI5EHTb4/CYnPmiENmwREz6P2Dv0wpchgMPUkbwWfGDPsWGdF64trve/tyIe+z5/A/IWTxv8f4IEAG0Lvrq+p3+Ht5228rZAbnv1hrzkvJqZVzQfTTC3LZZ3kCEvr/zNKZPNqSyXU+meRJlEvUFvJpNTNpPdmwx3nXOat61FHS71hWA3vT5cfOyMH929UQLy7vvHfE8/FGN8xDI0EBoIDYQGQgOhgdBAaCA0EBoIDRzZGuiNkLfwITQgAEhgsACM4uE/10CBwv5c88CfMeQkwwXnhZAXmEH/NNmu5wAsAHs4qQs08RyMAdgCbIAqPmXm8eRAUyAuPtMfqGaQAwgBYABfaOPkq0+Scg1kYm7qmIc6gAz2iAUJiEkOeAI0kaMNfGRO5gDCGGzzcJs1sDb6AMw4OYevxBt/AHLMRR39AEeUqStMBkf0w67H0d9jWC9gFqADoMT/NOEzfhhcE0vs4rvX79PFrAlQxHyUOcXM+u0HYAv/PT/rARwB81gHYJhrHkpjg4Q96oCZ9p964mGfHG9fEzts45d1Csgz9MU3fLB99oD5SWgA3bnsHKDF/njvAND0JdEHGySf/rVN17sfc7MO+8CaiT/QjLVSxgbQDF0wn+OFv/abtTEvmiM2zGObnPikjWsS2qcdWIk9EraYhzJzOjZcs8f097zOU31Rx76icfSCPdqBp9as52c/iSnw2LZoYwx7T04f1gKMBAazBnzANqdxucfQImthLJAT/4GQaJuELZJPIbvdJ71pQ+/Mx/4xF/cj9zJ7y15gl7gzBzEkLuwdfYmN/W8rd4xox3f2kX0lLtaP+zAP2mYNrM028Y8yMSARFxI6Jw6sg2vupTThI3vMeHxFF9yjrIUvrGCTPeNzz+Cbz0diQh/sktsPdIFvjGHviAP75Hb2hzbmss9uQ0PMT04da3Zb5MWDeL0plr4vuE9607oO5Vq4X0lHMuQ1NGYN8KfusqvOcLEjpc8hgLwtcJbfjC3jN3fLc/mUJc+1vM45B+zNZJVzKuMUb27v65oBvQF5Dx7k7u6NEpD3yH4AEQ+QYv9CA6GB0EBoIDQQGggNhAZCA6GB0EDxNNBbIS8PYXmYnz7QB1QAKIABAAegmtsL+/KwkzqgAGDBJ9OcA2WwRz+gI2CINuAgCWCRQgXDKMAE0NEQh/E+fccpOmALANoPWw0cAIHAHkNCQBFlAAiAAgBC2bCGvvjOfEBD+gBMAEM8SKXOr3ZOX/NMHXaAkEAa/KA/EIV61kQd/tCXMnECEHHtdkAgcMcPw/GDuAORADBOwCkSEIacdkCXARfj2SeumQMoRx3+OdbUUWZ92CDn2qCOPQeOcYqQOOEz/hj64TewDjhOnOjPeANx+rMu4gRcw0d88fqIM+2MZ372lzHeO8roA3hm2Mz+EA9iyzh8c6ywgV7wMdUlQNCas31sUCYZEqMt4AMxs8axgz20RhuxoR/3AdckICHt3kPWxXjriLigUcYSJ+JAHXaZn33Ab89FHWW+XOA1su/EjTY+e9h3dMw9hC32Av2zH8TGNtAEfuEv2vMc+IIfgOQ0sRbHk9OwXBNX6lgTPrPH3LPY8jzcF77/vH+sH1+45+kLvLXGWBeJtZNTj01gL3qxDeeMp0xiL7mPqWNt7oMv3gPquGdZI/cg8SL3fcBY1sJ+oAX64i/j0v3HZmGij+cE4HJPMS/2yNlrbHJtLQBnWaNtMT9l9pjYkbjXnNB7awl/fZ+wP+jCc3OP4hda9P3KPPhCPeOIL/NyTSy4Zn+oI+7Mic8k6mijr2ND2b7zuYY20Bb1JMZEihi0pQHrhM/NtvpEfdf0w2cs6XCEvIa36Ulen9yljZO7XPfv3z//W7tHCoA9GH4eMsjLe7Kz0PY3ncjNqLwciJvRkMGDlCkrVS5Tth/gPZwhLzeIoSg5r+AgATwPxoYWYw58deLHqlkHP1LdVdsBeYv3MCAerEQsQwOhgdBAaCA0EBoIDYQGQgOhgdDAka2B3gp5ecDKQ3we6pMDC3zqEZAEuDC8KHyon8IRxnKdAiTKQAOAFmOBDtimHsBA4kSpARk+ABIMR+hveIJtQA+n4OyHgYuvGQ+AwW9sA1KAGoBGrmkDmnhe+jGH18E6iQd9AFB++AwcMSAxqKKdOtbN/IwFflDPNQmwBpRxjKkzRPE4YJS15XGsk5gBb0jYceLhLnU8NMeW94extAG2GI8fBmBeB31cpk967XrqiDGwjDqu0QRxAowDdImjy8TDkJf1A4RpJ6b4wnj2AVDHXnP6kLgDE7HLeCAZ8WD/0Adl+0MbkBU7zEk8KTOHwZb7kjMvcQEyAyHZe2An4Be9ANXJaacfcSROJOySWD/xQTvE0QnY6UR8CvfN4/GfWLB+oB77QpvXhX3aiAnax2/a6IP/xATQTTxoZ/2sG5+ZHzDHPcQcrId7xvaBvLbDuoHC2AE6EgviRvxJrAEb9CfRjzmwz7yuY0/ZN9rxlXrik4J07wHr8D1LP9ZuMI6G2U/0S+yAwNTRj/Fomb6Aa+YksVckbLJW/GMd5KyP8R5LzNApa/ZJXsZg38CZNdOH9RBL4o3PafJaaGNseo/5niIWrueNA/jHONczjpTapb99ZY9JaAudWWsu89mC3m2PccB95mGPiT/6BbqyJmwzH/Hw/eI9dM6+AooZR1+vM82xzf7gt+vTvujFcUnr3TfyrgG73h4vNELivu7taz1Y6+MzlQTvMVRtK+/o3x1tjUvrU2DbVtn93Q7IdXIdgBdOBZ/Cd6eu8qre2r/bkBc4+2ZA2/HpUsDfwFxOp2YzOq2sVKeXleqMslK9g1RaojNLT9FZmRKdXjZAp2dP0eCSfhqSKdGgTJkGZlt+lzd/0vdNcLjjuQ/mJiI04G5zc7P488Ybb+yX8pWH+X927dqV/0sZa2Hfuhq/gLxH9gOIjj7Ioz32NzQQGggNhAZCA6GB0EBoIDQQGggNdF4DBjrpw++D9VDvQM9jEOF5ABmAKGAKIMLtBgk8tDXsoOx2xnNtO+QAhRTyAinon/bjGphBHXMCEpgLGOOTiUAxYBZ9sUt/4AqQA9hEvSEK7ZSpYxywxL7bN/fHjutcTiEv44AmwClAET4xL5AS0IId/Aae0JdkewAmACft2AY+AR4ZQx/gC5AXu1zTj/EAPXLG2KZz+jAe0FIIkFkrcAuwCDyir32xfV/je2G7+xjyem34zPxAJoCuXytLf/RhyMv6eJiPXRIg0vPxUBrIlD7sR0NAR59YpS/6MHjDBrFxnAFYlOlHDoyyfef4TJs1xxzYYQ+9v1zTH+3Qj7LrWCfrR7c+ZZnmPoFJTLxvnpuc9QAnmQ8tG0zSn/3BN/bNiTH4TMJXYgaAxC/Hkjb8wi45GgRQUk9MiK3tAMld5jMLYIpdIC9jvE5iDEj05xr12OaEK3a5pg9j8dk6pZ45Aaq0M1eaGMs9S0479xJ+oxPm4wscJGAmsSEmzIEN7gf8ZA34xT3nnP1wmXp8IE7WAH6hL9+f7BPxAxADg9lrvtxBP3xjPr50gF3uF7ThddMnXRPXrIX9RJ/4xzjKJMqsmRhx7Zx6ypzAtn3mIBFT1sqa8BnblPlc4fOFE+vELvWJfWaP/LlAXFM/KWMD/4gPY4kp9YxhHSS0iR0+T9mTNDGWfUE3xI19437AFjFgvG0Wzh3X+98LEY+Wz1U0k37uR1x6phM+B0jwHsPVtvKO/o7f1ri03pC2uzm2+vXrlwe8HEI03CXvKqvqzf27BXkNeFvyjLK5jDJ7UmeCNThTpjMH9NHFuVP0nlNO1oiyARp68oka27+PKvr10ciTjtfF/Y/XBaecoAuyffXO0r46LXOKBmbL1AJ497zWeT/wyMa2lg4d/AVy7t69+4iFvIDp7sBdayAgb+f/sd/Rh2a0RyxDA6GB0EBoIDQQGggNhAZCA6GB0MCRrQEenvOwkofdve0hJWtK18U6gQDAF0AF8I52rqkHaNLHcUjHpmXagR4GacAMAwbaPI9t8uASGMM17fTnGiAGPKPegIEyc3GiDzAGgABWAE9IjGMuEmVgC4kyIMPt1AGEsAcIYd4U8jIHawC6AIN4fTAwiWts099xYT0krgHVzEE7NqgD5AB8qGM+kuPjuDEeu/RLE6A6TcQDsER/xrInaJR5gFnFgrzsPWsm7kAfYsApUAATcwPrgLT4wP4B3tgv1kBs2Quu0RF1Tt4nIBzjDKFYEzaBS4Am9pe+rIv5sEk78zhmxNOJPsyFrz71Sdyxi8+uAzQSe59GxT4JHQGz2TsDQ6Bbmthb7APkPK9zdEF8iAn7wTggGX4bdOAjiT7YsfaA5fjEyUwSJ5W5d1gnNgCi7AP9iBv1jpttsnbscY1/9KOMHtAMfjKOPtjDvsc6dx+uubcA1EBddMA44kQffCncA9pZA3MDjAGJPlULnCXRRmyIB3FmDPaYD70xnjJ1JPqxLkNG+4lfjik28A9wyr6hUyA88SVHT9hAB2iQzwDmQRvYcEyww6Efz0+9y/ji9VJHmcQeO+70IT5uw2f2iGv8YN3oh7kp4ysJP6w3YoD2iTllEn5hA3ueo7WT7Hw2cb/wWeE4+XON/aKOGGCDvUCDaWId6Au9OTdIZ13WWxoLypEiBq1pwBr0fdpan6jrmnb4/yXpcIK8had2Abt9+/bNv5aZtwEH0O2Yb3Yb8vLKZBJg1YB3X55VrjynMo5O57J5OHt6WYnOLu2v80/pq+H9T1TtuwbrbyeN0G1XTNTnZl+mr8+fo+99oF4/eH+9/mveLP3jjIladuU4fXz8Bao6M6fR/Y7XRQNO1nmn9NVZpQM0JFOq8iyve24Buzle8VwOcOa1wk6HlugDOdM/6WnetP5wLhvYOmdNnQW/AXmP7AcQ8QAp9i80EBoIDYQGQgOhgdBAaCA0EBoIDRRPAzyQ94P93vZQ0kCCHJhgeEMZGAEwoQ345VO2xII4UE/ONfCE/oUphbw33nhjHkIAGoAR9AW4MRcn6wCU2AMoAIjoA7ihPZ3P4AGfgIgeAwRhLGAEsMaJNup4KIoN9hFAyENnAJ/rHQPWAfQFimGTsYAPwylybACqAEWGLo4DY7ANQEv9xi5Ai/6OHWsgZvhlEIMd6gA8+FCYAGecyAQmMj+27Ds5a28P8tKfRFztBz6nCcADZMQeewDooy8n/MiJGTGnzN7R3yCLOtbImihTzzpZO765jnr3YR6uaSO2JOJMHCljH//oR1xZt22lflPGDv6huTQxhv2mDk3gE4k5AeSpHWAbew54AySmCbBGPbqlH+OwQY5/tgNQBSxi2xCQNsoG5PTHJ6+dWKNn/MMmiRiR2AMDW+ZlL7DnGFKmP34b7qJ/30/sJ3bpx7z0ZV3Eg/3CB9ugjWtsE2/uS9p8PzHewNC2aCcBBvGBccBDvjDhL0Zgh/Wzp7Szv9hkPs/JfcurtT0//uEnegXQs++GtuyB95DxAE7uOeYwWAaWsj7aGGc/8RudEFPaueazjcSe2KfC9TGeNvaQ/cIftIov3kf0wZpp83yMYS/QBF9S4POPPtzH2CJRpo57nBjSj3sd39kLbHEv8PlELJiT+4q9tQ7sV1rH3N4vytgmJ9k/59ikjO+M8bz0pQwAZ53o2m0eG/n+n6MRj5Z7Be1wr0c8iqMPPrdIhwry+pRverLXkJdXMlNPH//urjmUmZRzs6oAwC0AuEeQ169rBuSSynKZvSlTvu96SNkAXTzg7br2vNN017RR+nHDdK1quEw/r78kn35Rd4kerZ2qx2qm6vGaqXqsdop+VjNBP6udoF/UTNYjNZfovrrp+tyEofrIO3OaMuA4nVvSJ/8a53Jgbznzl6kMwHuYQF4LrqcAtzUwnNa5XDgP9T35Y7s9uVGIAX+Z4X/g6Y1bWPbN7TweIhTvIULEMmIZGggNhAZCA6GB0EBoIDQQGggNhAYODw0AJnhYyb+Te9PDStbEQ3ufhvWDe3LgBw/9DUcAVyk4YmxHsWA8oIa4AXAADNh24mElNmgHLLge+MJcAJ90DvqRsJsCnrQPfgE/OMUHEMMmawRyAT8AOfQ3hKHdPjAWiAJgAbgZOgFXsAVEchnwlM6LX9gCIgOZuAaUMA/+UId9+lAHjMIf+uGffTA8pl9hjBlHf3JiQB+u7QfXwCSAEWOBMbR7XvdrC/LSD1AHhOMkscEa9QAkoB32gZ3oA8hLP/xJ18De2S/2n/mwSWzS5DWnPnoc9vAF0GX4CQBPwSCAjZOzjPHagWz4xzzOiVU6r8vYRoOsD1+wwf56b7GbJvqwbuLi+8JrICehGdYKbMUuOVDPdtAX7dihvyGz26ljHLARjXBNf6AiffAPeOl+3AfUM4b7izK2SdRx33LK3dqhnbFozz5PL7gAACAASURBVGO5tg1yYgJwNEzGDveNY0+c2B8SbSRigp/4jA20z97whQW0jx/EBvhLP+KHPeZ2wi4+4Sv3GvcN62bfGUt/g1jWRz/mZjxwlC8fYJtx5PiPTXxgHyjTl5w1+iQ1deiYfTcYx65jYv+YD02xHtdhF33ZD+qJBTpkfJpoY//wzb4zjnXhE4l9Z72e2zlrY8/QLLFkjayBPWAc9wifm5QB48SLMnPaB+Yq9LW9Nq+Rcdgi9757nHP3jXyfno/2WKAXUkDe4mmCe57UGchrVtNWXsh4OrrGTtoHuMu1IS/twF18M1tLc4PdyN98srfbkNevbM5mc8rknFrAbjZXqkG5Ep2R7a/zM/10xTsH6fNVl+kn75uhR6+5XL9vmKq1tRO1vqZyb3qhukL70jg9XzVaL1SN0oY5Y7V+bqWeqZqix+ZM0srqKfr6jErVn5XV0H7H52HvOzIDVJ4tyYPeXLZM5fnXOnOa99Cd5LUAuwtaDVmd89rntsAt9fx+bvrH43qac1O1ljpzMwXkPTweJMQDndiH0EBoIDQQGggNhAZCA6GB0EBoIDRw6DXQmyEvsMGvOubULhACiAEMMDTgYTUP+QEhAAlyA4T2HmQDK1LI2xZgMCgAxjAGwAQMopyCJObEnmGWHyI7Nzgj58Eyp+AAKthhbuzTBlhjDL5jn/ltg7WzRgAQsWEu4gL8AdBhk2vsFa4dqASEYQ7bpz9AxvGinvmIsyGT108boMnXac5cvsZn1mSfsU3i2q+b9jzUG8zYBmMNF9M1MAaoxtoAofhNDJgXX9l3YJJfB4tu2Kd0j7ABkGJexgHXmc/+0U4ZuyRiRT9sAsaIPYkxxBN/AHv4ZIDqE7BARPxxXACL2GNN2PY8jr/ndG4t0J940B+4yNzscZrYRydgG58Jjp3XZu2kp3HpZ8jL2kmAUPYZjdp36oHaxN3xpx+28Yd2+hIDw1fmN0ykHa1SR5kEMGXt5PaVvcIme+RYYdfttHH/0U6cbI9xaAu/vWcex1yMI3lu+rM/xBAbtDHOCZ/YZ/pjx+O9x9YQ9zvxoB1/gKzc0z5JTR022Bv2Dm14fxmDbb70wBcC6Of1AEqIo+uo9xdZyBnLGqgnYRN/gclpG3bZH/owF/ZIfA74/nZ/2okJ68EWOiKeXJNTx35RZv2s1f7hi+NEDNEJc2IbYM4YtIaf+MQ1Ze4JxnGIh/7MhU3qbLOwjX5poj/zsE6+AMN1Gpu0b5T3j93RHA90QgrIWzxNHErImwJelw1++XdKyqA6w56izz7Y2y3ISwBbTvG2/DZuNluulsR1Nn/C9pyyk3XpaafoCzMma/l1wN3L9OS8KVpTN1HP1wJ3K7Shel9aXzVeTuuqDXlHa8PcMXpxzli9WFWpZ2eN0+9nj9dvqidpdcOl+tK0Yao+tZ+GDjhep5f1U3m2VPzeLwnQeyRB3kKAazjb3Nycf60J/wjgL3r8hYO/3HDNX4z4pix/Wd28efPe3/8F9gKF02R7Xc3Tmystd+YmCsh76B8ixIOc2IPQQGggNBAaCA2EBkIDoYHQQGggNHB4aKA3Q14ewvLAHzjCyUwgA7kBE5CAPgADHlgD4wAIgISOHmADBVLIy7h0DPMC17DNiTigCA8xU3AB0OCahI88RwFsce2HyM4Bp0AU/wYnoAQYQj39fYoSGMZpO9Zg0GEbgBZek8w1Y+iLD27Hf66BJelaKLMexmCTBCxyP8YDsMgZD0AnlqydOsaSAD/Mybg0pXXE9aabbnrT/F4jgIkydvGDshMP3JmDtkL/6QNAM8j1a6vTddHHMeBEaRpbQ1H85jkYUN2vnwUcGpK6n3NiADwiXpQN4ZkLLaIb64j9Z4+AfN5D+rGXwGASsBQg7WvGE2vWlSYANfc248kZg36IL/2xkybbA76hJa6JL7Ekrtw7+E+8qKcMeESHaaxpp57T0ZRpY51olXXZJnohlvjs/cJn4CQ+c49S9lz47X7cR1wTU+5h+uAj49gz2piX+UlokhijjRQgYs99GEv8GQvg5xob7mO/XcezT06Vsk/EzAn73MPWIfbRGmslVgBg/MEePqF9r5G+7JW/vOFYEBfG2Sd8cEKD+ExCO+ScmMcvf76xBhL7Tjt6Sr8IwbqtT7+2mLnYL2ziFz4yp78wwOcZNunnGJIbvJI7VtTTjzV4velaaKcvdeiKGDKfv0SBb56ffoBt9EgcGeM21oZP9GmvjXYnxpOIuT/D7Y/7RL4vXhGLllj4ngrIWzxtHCrI69O6Pr3rE7z9+vVTWVlZ/kskfC6aOcGhXG4r9yFL8rb6HC313Ya8LQHKKbMH8OayOQ3KZHR6WanefUofXXvRWfrWtTP0i2uv0pqGS7W2bqLW11dq07xJWjd3rF6sHr9f2lA1Tk7rq8bphfxJ3tFaP3eUXpw7WhvnjNbLjJs5Wi/MHKU1s0fr0aoK/aBmiv70nJxG9D9e7yrppzPKSjQkD3lbfqv3UG2kRZaerm2vDJBN/zz++OP5v+zxF1pA7sc+9jEBfDmx61O9ANsdO3Zo27Zt+su//Mv8X3S//e1vp2a6XTYM7kn8AvIeHg8S4oFO7ENoIDQQGggNhAZCA6GB0EBoIDQQGjj0GuitkJcH/zyITR/YGwCkD6rTOh7286wjbW+rDFAwnANYGRC4P/M6UWc/mI95AH+AoDQBGgA69KVfmgCngEVAjetZY7pO7NIGzAPqcc3c1NHP0JIybcztMfQDWgFPAEReh3P6eQ3kQECgDVCGPswH2MMmIBrIYtBjGwAj++K6whx7+MAcacJn9gag6jU7ByIC1kgAoUKbXLsvfrFf9o858Mnr8yubsUk97UAwnoPRBrzlN1i5BoYS69YSvgICmTtdh+fDNnFiXvtLHeCVfQA0ck0MqcMe8+BDOr8PWpCnCd8AqMwHdGU8dfRhPWlfytglucxc9s2ni+0nOmKf0Ss28dNt7B9zFl47BrYJyAPiOR7UMw9wnfWzl+lriJnLNhmH/rj2eO4N+jCWzzT3JSfOAFbWnfrq8dhAH/aR/tzf3Iv0xzeS9UwdOmPtrJc228UGsIL1Ucd1Chy5xg5t1HNP2D5t9psyCb+Yg760MS6tQ4/+0grt2GJ+Pi+4Zi76u419pYxNcuyliXloI5aAa768wPi0D+OcUj9tz7nHAKuJP/c1941j6fU69xcg/HvD7COgmfbUX8Zbd8xhXwx5Xeecdre5r3PHns8y/HR95Pv2OGLx5lhY2wF53xyb7urlYEFen9D1iV1DXn53lzLtPlBo/tQZsOu+ke87xUssug15W36HN6fSbE5lmayymRKdXtpP7znlZH2sYrgeur5aT1w3Q2vmT9dzDZfoufpJWlc/QRtqK7WxpnIv4DXYdb5+Lq9nHqN1c0frhTkj82ndnBFaN2uYNswapo0zR+jFWSP0/Mzhenr2SP167litqJ2iBcPO1oQ+x+vsU/ppyMBy5Q7hq5oJbFcgr0/cAlZfeeWV/P9A+Z8xr2IB4nbmD2P9h78AMpY/aX1adt+O8p7cMAF5D/1DhHiQE3sQGggNhAZCA6GB0EBoIDQQGggNhAYODw30Vsjb1QeNBg0djfPDXef0NyigjJ3O2krn8rjWxqawIh3jcnfa0zFp2TaLkXst5MyRrrGnZfxL7af+uj6ta69cjPVjo71UOH86Z1f9LbTFdRrPwvZ0rsK2rl63t8aurCO1gw/ptcvt+Zb2oVzYt6P2wv7Fvu7q/PR3/NL1pPvq9tZ87Uw/+9Ra3ppN12G7cIzbnLsP16n/bi/M7S/1LpP7urA/1/YhbSucK71Oyx7vsbYFPAbUAZaB5W6PvHjwrjfG0voJyFs8nXQF8hrQFiM35MVW375986d3DXkD7u4PbLvD43oEectyOZXmj0NnNLi0ry7K9NHfTRunn3ygWr+95iqta7hc6xou0/P107S2bpJeqJugF4G81RXtQN4xeci7fu5orZszUnnAO2e41u+FvMO1ceZwrZs5VM/PHKbnZw3TU3PG6idXjtft4y/S6H7H6cySPhqcKT2kx7Q7C3kNXgG9fDvK31TkmlO7bu8IxqZAd/v27Xrttdfy35zzb/ViJ00d2XPf7ojKYwLyHh4PEuKBTuxDaCA0EBoIDYQGQgOhgdBAaCA0EBo49BoIyNu1h5R+uOucB9gp5O3uA+1C0JHaYa70uhjlA2Gz0C9DG9ena+xpGZu279zzHIrcemgrb82nNAattXelrj1bB2KvC9fZFV9b69uaj15TW/09xnnaz/5R11p72vdAlLszf2s6dgyct+Wr25231s8+tZa31t912Cwc4zbn9HG5M7n9LMwZ21VbnZmvsI/XA1ji9dWcGvdp6cK+cd21/0ceDfGyfgLyFk8bBxvy+tSuQTGvZjbcNUMKyHsIIS+bwGleIO+gbKnOLeujD4+5QPe/v0pPXHO1nm24TOsbLtmbXqifrHW1E/RSzQS9VM1J3gptqBmv9dVjkwTgHbUnjdT6OSO0YfYIbSTNBO6O0IszR2jDrBF6YeYwvTBzqNbNHKa1s0bqqdkVerhmqm6+eIjG9f0DnVna77CGvIao5LyGmVe1cHqX1+EAeNM/9OnoT2Ef2+dVMYbFrivs25pt9/XN1p08IO+hf4gQD3JiD0IDoYHQQGggNBAaCA2EBkIDoYHQwOGhgYC8XXtI6Ye7aW7IS113H3CnsKPQRk/sFtrqTdeGQc4P5dpSPbRWbs239va8tf7t1bVn60Dop3CN7fnW3TavqbXxHc3fUXtrNotZ19b8hfW+bmtux4C8rT7Up/1a6+t52srbs01b4biO+nfUXuivrxnXmv8d2etOO5/bvCI6nY91dsdWjOna/0eP9Hj5fgjIW7x9P9iQl9cz8++Q0tLS/Jtv09/d7Q5vijGtA+Fun+QloEDeslxWp5f118xzBuvr9dP1aP10ra27VC/UT9O6+ila3zBNGxqmaX39ZG2onaiXaibppeoJBZB3jDbUAHuBvKO1Ye6o/AneF2YP0/pZQN6RecC7ceZIbZg1Ml/XAnmHaf1M0nCtnTFSv509VsurxuvPTj9JQwecqNPKSjWQVydnsyrfk7cI4cD/GHNHJ3kNWgG8/A4HJ3g5gev6QvBq6FpYX3jtk7tpPXN4fFv20/6U3b8nN05A3sPjQUI80Il9CA2EBkIDoYHQQGggNBAaCA2EBkIDh14DAXm79pDSD3fbyrv78NqQIwUOthXgofU9cqycO16HIm9LD65vzaf29ry1/u3VtWfrQOjH63Lenm/dbfOa2hrvuVtbX9rWWntbNotV39b8hfW+7mjejjTuWDkvtOd52soL+xdeF44rbO/qtf0szLFDXVftdac/kJd1OceGf7+4O/ZiTOuf070xLr4fAvIWb89TyOvTtc75ndw0ub47uX+Tt/DkbpzabR3S9oTBMbbbkBf6joHSbJmGn5bVl+ZM0f/OrtBjsyv1fP0lWlvD65kna33DVG0g1U3ShtpJerFmql6snqwNVeO1oWps/rXNG2s50Ts6D3g3VVVo45yxLZCX3+KdM1rrZ4/R+jzcBfC2QF7gLyd6SeuuHqYXZgzX2lmj9NsZw/Xg3AmanT1ZF5b002llZSrP5jQoU5ZPWX5DOP+K6QMPeomPYWmaG6JyYveqq67KQ15+e9eA1n27c6K3ENZ6rq997Wvatm1ba82t1tmHnggsIO+hf4gQD3JiD0IDoYHQQGggNBAaCA2EBkIDoYHQwOGhgYC8PX9I6Qe+vfFhdqyp5/qIGEYMQwOHtwb4DI89Orz36HDaH/8/PyBv8TTTHuTtDswtHMPrmanj3x7wQ7+a2XlPWFOMbRsQdxvy8pqF/mUlGnDGQF3XcKU+XVWpH1WN0+NVlVozd4Keq56oF2omakPdFL1YN1kb6wC8pCnaUD1J66vG68W6CXq+tlJPV1fod7WVerKmUk/MqdTTdZP1VM04/a5mlJ6uGaU1VcP1bNXFWjP7Aq2Z05Kem/MerZl5np7jeuZ5embW+fn09Ixz9NNZF+quSe9SRf8/0pmlA/ZA3owGZjPK5CFvuYC9B0MYhqWFOQD3sccey7+i+YYbbtjvFc20pYA3LbdKZDtZ+Td/8zd7QXJHQ+xvT2IUkPfweJAQD3RiH0IDoYHQQGggNBAaCA2EBkIDoYHQwKHXQEDenj+k9APfw+khdPjS832NGEYMQwNHhwYC8h4d+1ys+9n/zw/IWzzdHAjI69/d9endkpKSPHdLT+2m5Z7wphjbOujtFuQtz+Xyr0DuM6hMJ40+W3M/da0+cv2luqtunB6cW6Hfza7Qs3Mr9PzcCm2onqiNNZO0sYac3+Rt+T3edTWVerZ2oh6vqtCv33+l7qudpgfed7V+PP+9+vG8S/TwBy7XqvnjtKr6PP2s5iw9XvMO/ar2DD1ed7oerztNj84dqJ/NLNOjc7J6dE4mnx6bm9PjVeVaXTNE99S/U/Pf8X91btnblc2WK5eHuoBdAO+hh7yc3OU3eMeNG5cHr4BcwCqneadPn57/jV5+n5fTt9QX68/WrVs7ZS8g76F/ABAPYWIPQgOhgdBAaCA0EBoIDYQGQgOhgdBA79FAQN7iPaQs1gPksBN7EhoIDYQGQgOhgcNTAwF5i78vKeQFzqap8FRu4bX7tlYP4DXc5Xd3OfwXQLZ1IHsg4tItyOtNOm5IiS74y2qNbrxG7/341fqT+eP0X1WV+vXcCXp6bqWer6rQ+ip+fxfAO1Ev1kzQi7UVeq5+on49/xKtnP9ePd34V9r13/8urV4l/f730rNPS088pt33361NX79TT93xQT27dI5e/Yer9Po/TNPrd07Qjk9Xaudd4/XGp8dLnxkvfbZC+lyl9IXJ0pemSP9yqd741+la1TRVF+b+jwZm+yubP8V78OCuN8uwtDCvqanJv6bZ9Ya4mzZt0tixY/MgFsDLb/UCfgv7uX9XckByZWVlQN4+vechQTzwib0MDYQGQgOhgdBAaCA0EBoIDYQGQgNHhgYC8hb/YWU8mI+YhgZCA6GB0EBooHdqICBv8fe1GJC3EPYa7sZp3YMHdc0enXcL8mZyWfUvHaDs6PN0QdP7dNrt83VOY7Wu+qurtGTGKN1/9Xj9ctY4PT17bAvozcPdSVpXM1HP1EzUzxsu0a+W3CQ9tkLa+JJ2vbRTr70kbdokbSB/Rdry0m7p1de0a80vtObuO/TUvzTo+X+epo1fHqlXvnyBtnzl3drx1fdo138Mlb4xQvr2aOk741rS98ZJPxinTXdfpWsv6aPBJcfsAb05ZXNlyub4PeHMQfk2geEsefqHU7qrV6/eC1z9SuapU6fmX9Xs6+bmZl1yySXi5K/rUjudLTP/E088sff3fzsaZ78tlO7k8brmI+NBQzwQin0KDYQGQgOhgdBAaCA0EBoIDYQGQgMHXgMBeYv/sDIe7EdMQwOhgdBAaCA00Ds1EJC3+PvaHchrqJvmJ5xwgvr16xe/u5s9dGA35XXdgryluYz6lJfo3bWX6uzb3q8+t9cqd+d8jbp1rj5UX6Evzxyrh2aN1a9njNaaOWP1fHWF1tVO1tN1U/XL912pLf/vLmndM9ryarMefnKHPv/953XTP/5CH1iyStcteVg3fPYx3fXddVrxtPTsy9KWTc9p/erP66lv1Or5r4/V69+5WLt/cLF0z4XSj4ZK9w6XfjJC+t+RLem+EdIDI9T80OX6f7e8R+dkj9GQ7AnKZTPK5UpaEuWDsAmGpYa8nMqdNm1a/nXMhraAXP7Qh5O7/uMxtP/kJz/ZC4Sxkf5xP3KntJ0yNrDNK6JJHf2xnVQsXS0H5D3wDwniQUzEODQQGggNhAZCA6GB0EBoIDQQGggNHBkaCMhb/IeV8WA/YhoaCA2EBkIDoYHeqYGAvMXf1+5A3sLXM/PvDk7vlpWVKT29m5a7ypGif89gcbcg74DyjN52WonG3NSgU5deqz5/36BT/qFB5y+t0+U3vld/UTdWX581Wo9cOVxPzh6pZ6rGaG3DVP1i3uV69d/uzAPejRulL9zzvGqWPqqrFj+tKxY9q+mLntd7F72gy0mNz+nqpt9oyd2b9euXpa2vPqfNj39Bm++r0xv3T5QeGCU9OGxfemi45LR8pLR8lHYvn6rff+dyjRx0jM7I/qHKs2Uqz5buyVsg74EGvYalKVQFtl599dX7QVv6AWKfeuqpvV2p8x+A8Gc+8xmtWrUqf7IXG5/4xCf2Ql3P49zj0mvK3//+9zt1ItjjenKDBeQ9Mh40xAOh2KfQQGggNBAaCA2EBkIDoYHQQGggNHDgNRCQt/gPK+PBfsQ0NBAaCA2EBkIDvVMDAXmLv69nn322AL0A2vRkbmvltuAuMNepJ+woxvYM7Kbx6xbk7TOoTH1Gv1OjFr5fg5Zdo1Puulb9bqvVabfV6aJbZuuq6yfqzjmj9OMrh+rRWcP126qxerRqol5o+oS0fo1ee3W3bv3yzzWr6TFNW7xBk5Zu1aSm1zWlaZsmN+3QxKbtqmjarvELX9Ili9boxi8/rd+/KjVvfkqbf9GobQ/NkVZOklaNlFYMb0krR7RcU7dypLRqrLR8grY9+F5dV3GMzsoeo0G5jAbmMirPkrL5k7wHA/ICXA1NOYULoOX1y+kf2u+66660am8ZwMu46dOn65vf/GZ+LP0bGhp0+eWX5/vZvnMP9rVPDV9//fUBeeM3eRUPcA78A5yIccQ4NBAaCA2EBkIDoYHQQGggNBAaSDUQkLf4DyvjwX7ENDQQGggNhAZCA71TAwF5i7+vnYG8Kdw9+eST5cSBvjitWzwwm0Lanpa7BXmPH1yi8toKvXNRg8qXzlPZHfNVdnuDBt7eoFOX1WnK383WX80dpm/OHK4HZ47QT6sqtWL+VdIjK6WXmvX5b/9Gsxsf17TFGzWhabMmLt2uCU1bNbFpmyY1btOERVtV2fi6Khu3aGLjq7ps0TNq+s6rWrtN2vz8cm1a9Um9sfJKadUYaeWo/dMKIO9oaQX147T7oQn6yl9l9M4yfpe3Be4eLMDL5hiyckqXcmVlZf4kriGscyDs5MmT832oo2/6Z9y4cdq+fXse9rrNr23mN3ux39ofz0/OHF/5ylcC8gbkDcgbGggNhAZCA6GB0EBoIDQQGggNhAZCAwdZAwF5i/+wMh7sR0xDA6GB0EBoIDTQOzUQkLe4+0o8zznnHAF6S0tLxe/qponTvOk1sLdv3757X8sM4C18RXNP4WSMLw407hbkPXZIicreN0mDF9cpd9s8ld0+T6W31av09gaV3NGgCxfN1XUfmqTFsy7Sd2cO1/1VE/TU4r+W1q7XE7/brflNy3Xp4hdUuWS7KhZvy+eVTds0IZ+2q3LRVlU0btX4xm0a39isiYs264rG3+vHa6RNr76kTY9/TjtXcZp3dAJ094Bd4C5p1Z62VeP13cbT9K7MMRqYyao8m1Mun4oTwI6EaCBr2HrFFVfowx/+cGs8Ng+AW21opdJ2t23bprlz5+ZPBwOB0z+e031p+8Y3vhGQ9yD/Qz795naU45v8oYHQQGggNBAaCA2EBkIDoYHQQGjg6NRAQN7iPqyMh/oRz9BAaCA0EBoIDfReDQTkLe7etgd5CwEvsNdA16d3/Ypm5x1xsWg/OPyROHcL8r711BIN+ch05ZbUquS2evVdVqP+t9er/+116ndHnU5bUq1JN8/QNdeO1hdnXKjvzhqrLff8h3Zt2KJ/+s5aXbXo15q8+GWNW7xd4/ekcXmgu13jG0k78nB3XGOzxjbuzAPfqQvXacn3t+v5zc3avOYb2rayqgXkplDXZefL+d3eUVr1xeE6O3NMAnhzymZJBz7QBqwGrryq2XUpkKX8wQ9+MF/lVysXtqfXhTaw+8lPfjJ/0pcTvthwH+cbNmzQhAkTAvIG5I1v7IcGQgOhgdBAaCA0EBoIDYQGQgOhgdDAQdZAQN7iPqyMB/sRz9BAaCA0EBoIDfReDQTkLe7eGvLym7yFJ3n9m7y8mrlfv37q37+/eD0zyQzNcNe56yM/8Iyxoxh3G/KecdNMZZbWasDtdTp5WY363lGnPnfU6eQ76lR6W43OWjxHl/zlNN0y+yJ9cdYYbXv0fm3atEs3fO4JXdr4vCYu3qJxi3dofNMOVTQBdVvgbkVjsyoad2p8406N25MqaPu7jbr+c2v17GvS1vU/0pYV1XtO6+55XTMndw13nXPSd/kY/fabUxPIW65slrRPoB0FqSftBqzOL7300pTV7lfetGlTpwCsX9PMYOwa6nJKmFc+z58/f29dOgG/Azxx4sS98DdtKyxjl9STtfMhcOqpp2rgwIFK3+VeWPZ73Z3Ht9qPzm+1x77HvocGQgOhgdBAaCA0EBoIDYQGQgO9WQMBeYv7sDIe7Ec8QwOhgdBAaCA00Hs1EJC3uHv7jne8I/+6ZiBvSUnJfq9m5uQucHfAgAFt/u6u4S55T5hRjC0+FO4W5P3jU0t07t/WKrOsLn9696TbavYC3pP+vk4n316rU5ZVa8Qts/Qn143XzTWV2rnut3rhFamm8TFN43d4m7apsmmnKhft2JsqFu5QxcLmPYkyabsqF27T5Mbtqln6tNa8JjVvWq4tK2r3/RZv/tXMe17TbMBLvgfyvnx/zSGFvAam5Px+7oH8M2nSpPyrmwG+Y8eO3TsVc3O61yd8uW7vj33uyU0XkDce0PTmBzSxttB3aCA0EBoIDYQGQgOhgdBAaCA00BUNBOQt7sPKeLAf8QwNhAZCA6GB0EDv1UBA3uLubQp5Ocl7/PHHixO8/O4u0Je69BXNAXWLD2N7wtraG9ttyHv2J6uUWQrkrReQF7B70u21OvGOlkT5rMa5uvqm6Wq4ZrJeeen3WvuyVLvkV5pwy0ua2LhdFYuaVbmoWRPIF+5Q5cJmVS6gDOjdB3gnLNymiQu2ataiJ7Vms9S8sQuQd3WlNv5v1SGHvIar/BJC5wAAIABJREFUBxry+nd5mQ/Qe+edd+49uWtw2x7cdZv7tieejtoC8sYDj6488Ii+oZfQQGggNBAaCA2EBkIDoYHQQGigN2sgIG9xH1bGg/2IZ2ggNBAaCA2EBnqvBgLyFndviefZZ5+dT8Bc4C6ndwG8XBcC3o7YT7QfPhC4W5CX3+Q9/aMzlF1SrwG3N+jtS2vUh9c2316rt5Nuq1G/22o0cEmV3rNgtsb/xXQ99tRqrXtJ+ovPPanLmjZoQuPr+Vcy8/u7FaSFOzRh0S5VLtipCYt2atyi7Rq3aFv+JO+EhVtVcevLev9nX9Czr0qvr/2RXl9R0/5JXk73rhojPVyhJ781rVdDXgNZAC1l/1m7dq0uv/zy/erc1lFumz25WQPyxgOa3vyAJtYW+g4NhAZCA6GB0EBoIDQQGggNhAa6ooGAvMV9WHkkPtjnAav9TsvUFV67X2/KWePRsM5DuWddiW9b+9GejfbairHuztrvbL/u+HQgbXfHn+6O6S3r6O76Y9yR//9cNEw6//zz9/6/M/a1+/vKz2ryqmZAL8zHYLcQ7voEb0+4UIw9uAC4W5D32CElOuMjV2vQ4nkquW2eTlpaq5OX1eqkZTV5wMvJ3r7LqlSyrFqnLJyl8/62Sv/2wLe0/vU3dNt/P6sZTb/RxMaXNbaxWeMat7X8Hu9CTvTuVuVCXuGcQt5tmrBgsyYvWKdPfeMVPf+q9NrT/62tK6pafpM3fT1zWuZVzavGavcDo7TqSyP3QN6sspmscvnf4z14v8kLMD0YJ3lTwAvEffnll/O/0VtY3xHgpT0gbzys6MrDiugbegkNhAZCA6GB0EBoIDQQGggNhAZCA+1r4GiAvDyM5SGiH8ySHwkPZPE59dN+O0/b2ip73W5Px7rsnD5puXAs7YU+2e7hkqf+d9YnxnRnXHv2bdO5+6bXrcU37efykZq3F1PrKM0p+9pjnRODtFwYk/baCvu2de25W2vHPu0dzdNRe2u2C+vsh/O0Pa1Ly2mftNxWn8L6wuvURlr2+pzT1trYwrq0P+WOUjpnZ8q2l/Yt9CFti3L3gVzEruWzCM0F5C2OjrhXDXk5nBeQ9+CC2AMJvrsFeY8bUqpB116i0xuv0YAl89Tv7+fnIe/Jy2p0ErB3abX6LKvKp5OX1mrIwgZ96F+X6Ikdr+v+Z3aoZsGPNXnhWo1u3KoxTVs0dtHrqli4UxMWShULd6ty0a78Sd6xC6nfqkkLNuryBb/TD5+VNm5+TS/+8gvavmLWvpO8K0ZKhSkPecdJKyv13SVn6Z3ZY1Sezag82wJ5c9mDs4mGpc4P5OuaDXN37dqVh7QTJkzIn+Tluqt/7G9PxBcnedv/B348AIn4hAZCA6GB0EBoIDQQGggNhAZCA6GBo0cDRwPk5aF0Tx/4ezwPdv2QOy2feeaZGjJkiPhtOfoOHjy4QyBkO23lntO20/nSMfRzSuvxJ/WD8aSzzjorX4+vrmMc83gOcmz6mr6F/dO5bMc5bYzHJnna12V8a6/d/TqTe63Yc3/7n/rEnCT6e21uZ6x9so22co9Jc/oOGjRo7/xtjcUvEj7QhznJsUUdD7sp04eY41e6Ltulj8vk7Kv9SespF/ZN2x0L+5O2pWXsp9cu46PL5Mxlm5SJiddLfeE8jofzQltcO65eB30L+xXWub1wPtcX5u7HHCTWS6Kea+fpOI+hzuPI3YfY4Hthm9fqnP6+vyiz325zntq1Zhx7cvp5XnKuC322rdRv92VO+5nacTttqY/U44fn4drz2RfydIzrC+23dV3Y37FM+9tncseFsn2hnPaPcnHA3NEcR2suIG9xtMR9zv/3zjnnHA0cODD/G7zxO7wHhxH2hLF1Zmy3IO+Jg8uUuXqszrn1WpUunq+TltXvgbyc6K3TSUtrdPJt1Xr7siqdsKxeJU3zNLTx/frW+l/r0S07dOfdT+q9Cx9VxcJ1Gt/Eid7Ne17XvDsPeSsW7da4RTs0bsEWTVywSZfe8pQWf3+HntgsvfDsCq17+FPaufIK6eFR0koA74g3J+pXjZNWTdUXbsrorATytoDeg7OBhqXODyTkTUEuYJdXNXcH8MZJ3qPnIUM8UIq9Dg2EBkIDoYHQQGggNBAaCA2EBkIDB0cDRyvkLYQHHT2wpj/QAIjAA16uDS+4njdv3l4wQz+DutbsXnPNNZ2CDvbRD5SZ7/rrr8/PTVuaaLviiis0fPjwvI8GNsyf+ks/+27/7aPnczs5Y2lnTW53/zS3j84LIVXalzL90N6ll17art3CcW1dMx9tBpFeA2skzZ49W2PGjMnPy3W6P/aZMe9+97s1Z86cDvfHY9Kc+fFj8uTJ++0Ndtlz+lImFa7Dduwv1/Shr2NPm+tpM9Ci7PHt5YVz+jodwzO7cePGvck/1nTVVVfl6x1rxns9qY207PvFPnoN9HHZfrBOr5V2z5PO4XaPcU5/2jyPx/ja/drLHc/U/6uvvjrvJ+Nox+fq6ur8fcYcaV+vlTrP+4EPfGCv1tzXvnm95KyVesr0I8ee+5I7Xueee65mzpyZv7ZP9KeP10cZm/bJ9fTzWpjH/TzW87u/c9o9l+8Pr5Mx3HczZszY6yP9nbCB74X76fbCnP70dX/7QE5fbKV1+EGdE23Uee32Mx0T5eLAuaM1jmiKFJC3ODrivjbk5YscAN6AvAeHEXYG1PakT7cgb59BZTrx4jN00ScbVN40XyctbQG7nODl1c0kfqf37fm8Xn0W1ym7qFa13/4Hrdz6sn75uvSJr/5Wc29/UpMWPafxi15WxaLXVLFwm8YvaNb4hbs1euFOjbl5k65oXKsbv/iMfvWq9PKWdfrlfZ/SKyvrpZWTWwBvq5B3uLRyqLRyjF67b6rmjT9GZ/ZSyOvTu2kO2F28eHH+Hx28Jrq5uTnlv50qG0r3RFxxkvfgPCiIBzIR59BAaCA0EBoIDYQGQgOhgdBAaCA0cPhr4GiCvDxINJDo6sNpwA6gEJgBPLjgggvy0HDkyJEaNWqU3v/+92vixIn5utGjR+frCuEC18OGDdOHP/zh/eAQ9QYUaU69E/U8BGUsOclroAz4mT59en5+6qlLgQgnZGgHql522WX53GWugXskyvTDHnaYn/wjH/mI/vRP/zQPmf/sz/5MhenP//zPlSb6YoPx+GFfnVM/dOhQ1dTU5GFOum7Kntf928ptGwAJAPc4ftsPqEtiP5iHdY0dOza/N+wZ86R22Vf6GKAV+pReM09hwhYxRSuFbR/84AfzcwGuvC9oiQfaXkNb+4JP7M2VV14pDmmQAxd8qpG9Zj8+9KEP5RMaIfm6tZwvJXjtzG9/qUfb6VopT5s2La9/xjAvOfXcT6yJ8dTZDjnt7ANlr5n+aJExrJ/Eczpy22A9jPMY15OT0r5eA3HhzYFei/XpWDh3fWFOe6H/6HP+/Pn5+92+4DvgFv/RN2ukDZ8MFV2Hr9wHjoH9d04/J9+vtGGXzxNs0k4d89GHnM/s6667Ll+PP7bnmHFNO34yP2sl5wsMjHc99yvr5t72+mifNGlS/rMMO653jg7RN2vFH9/j3GNz587d6yN2nLDjfcJOW/HwOrxm7KM1rtPxrMWJe57ka3LWxJcSbCed33YiLw6cO1rjaK0G5C2Ojvhc4H7n84x7vqSkJCDvQXrbb08YW2fGdgvy9h9Ypre9o1SjbqrTkMYWyNsCdQ126/T2pS3ppKX1OmlxrfouqdHgxnm65eHvavmOHfrpdqnxO2s1o/ERXbbwN5q24HeaduuzmnrzC5p263pNuvlZXdH0OzV+b6t+9rL0zJZX9dADd2nDI3+inQ9fJq3kVcwjWz/Ju3zYHsg7Qc/+YLqG5o7RGdk/TF7XzCubDw6lN3w1WS32SV7b94ld8k2bNmnq1Kn5VzYDebvzJyDv4f+AIB7ixB6FBkIDoYHQQGggNBAaCA2EBkIDoYEjRwNHA+TlASKJB7MACqBGVx9OAyyAf4BebAGAeMYBWALuAvEAYdQB66gHMtDXc2GD+YF0gI408XAzTbQxnjFAPqAPcwAwKANqsEOiTBswx+1cMxYYw/wXX3xx/jQp8AM/yTn5CxSx3+Q8H6IOIGS/iRt15513Xr7O8Uxz93WOHwAgoJ5jUNgfQF5fX7/fuh2DFOy0BWlsjznpD5wCbnGNr+wFiXrgJScNuWbt7A/xsQ1yoBpAFBCP72myX879kN85c1JmLwBhrD9N7I2hGmXmMcizDfrjH3vgPSncHyAyawFee9341NDQkPefunRN9os5rCfWTZzcz7FGc/iFVnjgniY0DsQrtAfcS+G610KOPfwHhDAHwBRdkgwamY+9wC5aoR/7RB/7TL0BKnNxH9LGGKf3ve99+fWzJvoTa5etQa+3tZzY23ds4genr/HNflCHXpmLRAzJWQt9aU/9osz6iINtO0cDaWJ+4LpjUFlZmY8r15SJI31YPzadqKeMlioqKvJrZg40wj6yVtZDvwsvvDDvB/6idccFm/hOX/vH2ii7Dzm6wQ798YU1kzjZ6zK+YJ/x1BEvbOMDn4uM5/OX8e0lx8b+eJ+xxTjXp7k1wv3HPZ/uB/1sI/J9903EonuxsO4C8nYvfoW647MnIO/BYYKdAbPF7NMtyHtKeZlOPK1E76qfqsE31+Yh7glLqnXishqdmIe79TpxSa1OXFKnty+py7cPuL1e/ZtqNGjJtfrQg1/XKu3Ur7ZLD62VPv29NfrIZ1ZrftNyzVuwUn/x6V/pzh+8pJ88K/1mq/T77Zv1z99bqhWrPq5Nq2dq10PA3XZe1Zx/ffNw7Vp5ub5y84U6r/wYDc4cr2wmk08Z8oMIeQ1Mga3f+9738n+JBL4CZA1pnXcFyNqubXFil3+Q8Bcj/+mOXcbadk/iFCd5j5yHDfFgKPYqNBAaCA2EBkIDoYHQQGggNBAaCA0cWA30VsjbGsjhgSyA4oYbbujwgT/jARsGFJR5sAsYJQeSAL6AcSTsAg+BC4A6TowaMhgwAOPoB5ADgFAGhgC/SAAQlwElPEfBD/sAJDFcAUDyoJR27DMn9oAsQEra8Nl92GfAD9f2B+hDf9fRn3UBWHjtM/3cF2hG/Pi9PNvk9Czt9hFIxTja8YX10ub+5E6M4zStAZnX7bwwdh5XmBtiY48xQHj6cA30Yj9IwCbgIHtl0A20MuhlDOCUPWBPiBVr9v5QT6zsH/tgH7FB7NAGr/dlbpLjTz9sOR7UExeS56eMffo6ZuyxgZbXRF5VVZUHf14zdoGNXBtis2bW6eR65sMu68CW7TKW2LAfdXV1+S8j0AcgRxtaBPLin32kHr0wxl8AoM6J+KN19wdEAvZp99x8WYI50A7rpi9fhMAm8XQ/x4R4+LXArAVb+Mb6uLYesEmcaacOuwBy/MUm9thvYkcbsbfftAFI0Qz9gbTkzEGcgfCeBzCB1rnf7Stl7iF8JQGssc/nDponVqyPe5L7hbnQB/uCL07cX+wB156PMvc3sfR8joPXxTrwE9ushTjgI/PRh7mxQz/G4qttOefLI6yD8aydvsyJrqhjTdigP3qkP9cAae4d7wV96YMNYs0+s172nXWQ4w+vCOeaRDu+8/nEOPtEjh/4S2zSxH3PvYc2uGfxk74eix9pcn3k+z6TIxadjwXaIgXk7XzM2tMX92ZA3oC8e8FoaXmZ+gwaoAHj3qV33TJPpyxueV3zCctqdMKyOp24tF4nLKnbkwC+LaD3xKZqHbe4WqWL6tXwn3+vH2x8Wj/dtlWPbN6pR7Yqf7r3569LP98ikT+6Y6d+8Mwv9cnP36TP/lutnvrF+7T9p1Ok1SOkVSNaP8m7fLi0gt/pHa1dD1dp3pS36/TMH2hQtr+y2ZwymWw+UW5JB3ZjDUsNW8n5x4L/dPekbQpiKX/1q1/N2129erVN53PPu19lJy7sd0DeA/uP/HiIEvENDYQGQgOhgdBAaCA0EBoIDYQGQgNHhwZ6O+T1g0UeyAI6OHkIUHF9W7kBEQ8fDURcRw74AYIANUhAD64BWyTmAXR4DPMDIThlZnABOPQpP+AHUIn5GAc4AQgZqgI9AD74zoNl4BkAD/jDfPTHPr4ATQBJ2GFe1ggw8ak61kMbdUAo5qSP89YgL3XYZI2M54EsddgwvGR+wDe2gGzUe/7COFPPmniNMmVsOvm6rbGpLb862P7jF3XEGIgHPCIBDoFCAEHXEQPWTGIcEAuf7BugzDH0656ZB9usHX/tC/CSWDIn9eynQRbgiv5cA7CIGXXYZjz98ZnxvsYH4gcc9L6QU89a2GfK7seXBhgLGCVx2ALYhi5cB4hz/9YgL3Voi1gwl7WEn2gNW9Tjr31C30Bh5nMsqEOXxIyYu38KeV1HX+rpx3j842QomuZ+xR/HiTmJESCPflyTMz9xpYwNbBqaUs9cxBz/2Sf2D/+IGfvEOMeeetZP7Ngv7PkLAvjJngARsUcbvho6c01iPj5XSayBvabMZwT+2D7rIrEO9hnIS5nx+ESiDpsAaiAzIJ5YY4syCaDJXjke9Ee77DfPehnLZwJrxTY+8TnEWIA12rTvzokTUJ9Y4iMxA6TaL+4j6rHHPPjAWK6Zj9z+YIOybWPDZWzgG3F1XdrXdeSu9+cOe5AmYkx8+TJHCnkZhz+prSgXB84drXH0fRCQtzg64h7lc5HPgXhd84Flgj1hat0Z262TvNnyjEoHnqK3ntFfgz8wTac2NeRfx3z8Hsh7wrJ6Hbe0TsctrddxSxp0/JJ5On4x4Ldeb1tSI2Bv2aI6nbnoWtV86y41Pv4TfW3TGt29/WV9//VN+sbGZ9W0+oeq+9dlOvfjczXp4+P180eu02urp0oPj5Qeere0kt/dBeYCdUkjWlIe8o6Wlldo+acv0Pmlx2hIpp/K8yd3ByqTAfQCeMv3QF7KB2ZTeSW03ngjn3bt3JVHq5y25S9U5OkrljvBXd/UBRDr07sf/ehHWz0VHJD36HhYEA+FYp9DA6GB0EBoIDQQGggNhAZCA6GB0MDhrQEejPPA0g/Qe8tDW6/HgIJnHsAZHva3BjUK120QQQ4IMSwB3tKXHFhoqAt0oWzwS05sARzMCeihD1CX8cAJ/MA/5gCiAe88L0CKObgG9uI7ZcAw44EuAEWAD+OwA7ihL6CD/gZcjANYMT/12ABwAYKAYZRp45p2gJdhp/0xkAZ4YQvfgGusETjI/Iw3qGJtLju27IkTD3Rtw3O4H7n7uY4+3lPXEVvKgGXWTiIe9CUOhrmGvMAo4JRhPPGzXUAocQTyYRNgzZ5zzbwAPiAZbfhOvFgz1+wlawdWMS82gXZoDrvkxAObXAMFgfSe3z7Qh/hji/nYlxtvvDE/F/ORqGd/CiEve2A75CR0S4zxkUQdOQ/SsZ3WY486tGo7xIOYsk5izPq4Rnv0oZ49IL74bnvEy/dZ+vmC74UnebEDDCYxjmtgIrEh/twH2MI27SnkZW+4n3xPMNb9AJlcE0v6AB6xx/4DAVkD62EvsYNd1sM1a8RXxgBxAb74wCvMyQE77C/xwW/qrEXmp0xCL4b0XNsn/MEv68fr4n6hH75hE7+4xibxRVvExdAWHZPQNT5ix+tnv4DCrBkdoDvWwhc1gLvcx1xji/UyLk3EDn/xhXr8wV/ALxp1Yh3En0TMrF+0hK/2yX5xTWJdrA+76Jq1e//cN712HTmx4LONhL7SRF0KeT0f8xAT2rERKWLQEw2gTVJA3uLoiPuUz96AvAeGBR4oxtgZux1CXl6567TXYK5MJaV9ddLgfjpp/Dv17o9V50/0nr5gnk5bMD+fhtw6X4MXzFf5wmtUsuga9Vt2nd6yoErHLqnRsUuqxKnfExfOUcnCGg1aUK8zFszX2Quu1bm3kq7R4I/P0emfuFLn/vUULfvh9XrmpzP3nNy9WFpx4R7IC9gd1grkrdTOFTN1XcUxelf2/2pwNqfyLIC3fE868JAXwJuHvLvfkEhv8A7kFk67ffsOTZk6TTv2gN+dtHfxD/D2ySefzP8lx699NvTtoqlWu2OLtHfPuwHC43XNh/cDhngAFPsTGggNhAZCA6GB0EBoIDQQGggNhAYOngZSCNOTh56H21geGuITkAKoAmzhoSygIgVShSChcB3ACEAIEBb4BCzBJuCEOhIwxWVyQBLJEM9QB5BmsAMgpS/z4SvXQAiumRMIA9QBTgBqsEE94MV9sMUYP3AGcAKT6Qd4NJSiHeCETR5KU8++A3KBM1zT7pxTuIWQl5gBYugDzAFSAnsBNcxLbAA++It/xBufKbNOQFSaAJ5AJmwBQQGfaaLOkLtwj7xech4KE2v2gL0B3FHPnqX7QplYccLPJyC5xl9iRlx5yIy/5FwTQ8/FNX1ZL+tiHvYNLbBu5gOAsWfYYF2OBfaIKfUkbLIXADr3oR7gzj4YWgGkgI9cs2/k1KGVFPKyL+wHdvGNviT2hPXSTqIOnykD41J/WAPxYA77hDaIL3oiZgBNbAI3WROxwB798ZP5fW2dcO1ETAx5qUO/jGEsGqGOayAd19jFL8eUdvqiHXznmnmIJeNIXhP6YzzrAThih9jSzj6hNcCo9xx90x8btKFV1kwM0AHjbB9/0AOJPtTji+cm5xpdoRPskrBFLIkpc1P2ONZFPf0A9thmDSTsMZacdjTAejwfXy5hP2mzTexybV/QJ/cb9WgWMI9m8J99tK00x0fHzGvHR+an3lolXnwGWKPk7Is/67xG28Yv+4pd9gf4TJ3nYQxrYUxaxzV7hUbShC7RBb4QC5/kxQ4JG8SQNdmPyIsD6I7GOKInElo/Gtdf7DVzj/JZzOdLnOTtXaC3Q8gL5APWkbP599xzj1avXqUVD/2v7nvoXt294l79+/336Kv3/4++8sA9+vKD38+nz/342/qnB76npnu/rov/9jqVLqzXcYtrdezSWr1taY1OWFKrk5bW6uSlNeq7rFZ9l9Sqb1ON+jZW6+Rb5+jkm2fr1E9N1ezFo/TzJ/5crzxyubRy9J4Tu5zi3fPKZkPe5Xt+p3f5MO1Ydbn+Y9lonT/4GL1j4Ns1MJNRLn9yd6CyWdKBPcVrwDswl9NPH3lEq1eu0uoHV+nhB1Zp+QMr9aMf36cf/vg+/c+99+kH996ne+79X/3PD3+oH3z/bv3oRz/MQ9eECbcKYXfs2JH/S0LaCJQt1p+AvAfvH/rxUCViHRoIDYQGQgOhgdBAaCA0EBoIDYQGer8GgCA8rOQhW7Ef3B0Ke+k6WBfgACAC1OAa8ABQcT/qSKmvQBCuC+sBhcBH2hgPLAKcABhIXAMa/Fpb2wBWUu+5ABqGhvTBR8AF7di1zwZu1OET4ALgSwLaOAGcXXbOGM9HmYfRQB3KzEkcgFeARcMUYA9lfCmEvMQMgIhNoBLABBv4ij3ACutnPHWGvJSBYvieJiCloSz1+A2sBTpxTbu16RiRt5cAiIZi+OF9AfwQf/yjjj3zHuMfsIg9cszwgTrHDxhrWIddHkQDLN2f/cQv7OMDZU4nMp7+5JzIdX/iBqilr0EpY6wByvRlHtfZDmPZR/aAfiSgrUEn2sA3NM+e4bdPAVOHL9g15CUO6IBxBqIAO+qIJQ/eGYP2iR3xoh0fAHn4iQ+AOnRImT4GblzTB//xw/GhD5oEplLvfszFPABn6viihO8V2lgT+0kbNtk34s61E/3wnZw69tP7Rx1rwiY6854A4fGJ/vYXu2jSdtEBkJDEFxzobw0DpX2/uj97xGcBc9on2riPiBdl1sB8rIt9pB/XpFTPtHPiln0iZqyPMjFHz+yn70fWyvpI3KeMdUIb1oT7kLMHwFt8wgdyoD7rdJ2/NMHeMLfvW+LE/UIMnGgjeR9Zj+3YPnWU0SX3UFrv/oxJE31YO+1pYi+IJX3RJ3tO2QCbdrREjFN7Ud4/vhGPzsUDHZIC8nYuXh3pins5IG/vgrs+oNkh5E1P8ZaWlmrVqlXa2dysnc071Lxrt17dIW3eLW3eJb26W9q0S3pll7Slebc279quL37/Gxr3sfkqvxXIW6O3LqnKp+OX1ug4ykvn6I+Xztaxy6r0lqY5ekvTbL110Uwdf8sVOuuvR+obDzbouZ/N0LZVE6SVo6QVJIAuv8nLa5r3nOQF8i4fK62apDX3XKHJw/6PBmX/SLmSkzUox0leTtYCq9NU/E1tAbw5DcwN1MBcuVatXKWdO3ZIO3ZJzdK2HdJW4vWG9LKkTZJeVUvz7p3Nuvvuu/OctiPIu2nTJgF60z8BeXv/Q4F48BN7HBoIDYQGQgOhgdBAaCA0EBoIDYQGjkwNGKS19VC9o4dzh3M7D2GBEUAZAxxAiCGBoYjhAP29ntbikUJe7AFQgGHALqAoQITTbbaPPX5Tl5y5bJuTkEBN6piHE39AH8+JP0AXHiBTZjzzAWEApq0lYFeaOBDh+bDLPgMWsUMbddgzRHR8yJm7EPLSz6ftgCVcA86xgz1inMI6YkN//GedrCFN1DMHEMzt5E74YZ8Mnx0fr6swT6EYY70/PnXIXhFrAKWhEj5hl5y5edDMOogX9ST2C9jnfkBSQJnHGhgDu9gb/GJuwCFxSpPraDdA9DyAOMeCOmAgdayfuYgZtoFvhZAXyOc40Q+fgF3EmPUDBokJbYAuwBq23NdroY09YX2MZwy2gHWGqfSlDbBsCAxUwwfbcexZB/OQGzw7HnzBAL+4f9yH3JCXMczPPKyX9WEXyOuYAF4BjIxLE3HDFxIglHHoA5usGV/QLO2Mc3/aqMMv/OAeZO3c+5ywRfP0px8+EBviy5c/AJzcC4xnHu5xIDDXJD4XGJtCXvqRmL8tyEs7vnN/oy/sEEPgrut8qh6f0DaJuPrV0/jIvMxBPXuFz6wPPZPwDT+JOXOy344Z9awFeI9NA2dy6okX6yVG6IfPXeqJPZrGdmFyrAHPvh/dh/ldZm6XybmH2Dsn7meXyYkPe8Y4j3XZ16m9KL/59wkGAAAgAElEQVR5byIm7cfEegrI236cOqsj7veAvMXngQathzLvEuTlL8zLly/XTuDulu167KkNmv2hhapsuFXj59+hMfPv1Jj5d2jivJu1qVl6bfcOfeFuIO81eyHvsUvm6thlc/XWJcDdOfqjpbP1lqVzdNzSWr21sVpvaarScQtnqORvp6rmny7XL39Rox0/najdq8e0/B4voJff4uW3d5cPa8nz0JdTvpP16n0z9aHL/0Bn547RaeX9NTib0aBcucqznOYtUy6bUTafir+hPsFbngXyDs6/InrlihV6443dem3La/r1k8+p/k9u1SV1t2ji/KUaf83tGnft7Zoy/+Y8LN/V3Kz//va393Db9jHvI488kvLdopfjJO+R+dAgHvbEvoUGQgOhgdBAaCA0EBoIDYQGQgOhgcNTA70Z8gJgDHMANkARANFHP/rRPBgCTAEgeMDIQ1sDWR5MppDBDyrpn57kBcwANww0AF+0G+b4QTDjKTMXUCaFodQBKQxMPcbQBz+AMkAaoCz7RQLqpIm2wgS4YTwJSHXDDTfkfcM2CVAEMMEfyoZH1Bnyeu208xAWAARIAZYyDn+pB1KzfkAPdZwOZH7KwBzbcc66mQNgCRwD4tG3tbhT73FeT2s5QAqYZxv4zH4AotgnJwBmCrWwDRzDJ3SSnrpGQ6yF3D4YktovYkJbCnmJBfZYO+34Rdm+GaQ5PsQCf+lHnib2hXr2jJz9KYS8PhmKXccbXQJBmRPghk+0G/IxN+umP2X6kaM15qQv9wT16If12V9yoCHrph/XQFvK1BMzyl4v/QCLQErqnRjnuLqvIa/jhT+AQMagOfYUvxnbEeTFNr4QXz4L2BO+pMBauO+4h5iHeGOPRNx8X+Az+mH/mZ/4+z7xHrFun6S2DdZCHfe76xiHP61BXmxZk/RhPHpmjOOC73yGsX78AG7zxQ3bJ/deMgf3Fsn7lLZji3WhG/bWNqwH5iyEvO7jnHhQxl/n+OTPVXxhHrfRL03MQVtrkDftl9qnzH3AmtJE7Ljms4j7lzXhn+0wFwl/0nq3R77/3kQ82o8HuiUF5G0/Tp3VEfdmQN7iM8FDCXc9d6chLyd6+QvHAw88oJ27pZe3NGvDNulHTzRr0p/+ky6a93m9e96Xdf78f9aIhtu0fnsL5P389/5TFX913R7IW61jl8zRW5fOzidO8P7hktn6oyVz869yfltTrd6yiFc1X6rzPjFU33n0Rr34sytaYO6q4dLDe17RzCneFUDePWnFGGnlFDWvqtai68r07swxekfmOA3JZvO/x3vaoMEamM3sAb1AXjbTJ3qLt7H7IG+5yjODVJ4dpIcefDAPeTdv2ayXt0kP/nqr3vvBz2rkvM9q6DVf0sXXfFFj5y3RS9skIO9//dc39/x4b/uQd/v27XvB7u7du/eWi1UIyHt4PhSIhzWxL6GB0EBoIDQQGggNhAZCA6GB0EBo4MjUQG+FvH4Im4JQyoBQIAFlHtACbwBFhjFtPZTEXgp5gQXYAUBxQpRELMmBPrQX2gKuAZoATgYN5IaIzMHDTiAitgEutAPoACGMJVF2ch05QMoJeOPX0QJbAB8AWMMO7BKLFCLhL/XMjY/4Qx05/ThtB1wE8tIPOAvs5Zp6HtIC4ciBZIa8hXHgGj+AWEAoYgasYixrxTbJIA87AEr8YC20eR3OqTfkpcy+sg/YZo/SfcJf9p6x9LNd4B9xw3/mwA4gDNiVwir6GeqxFvqS088nedECpxqxjQ+UgVBcp8mxMERlbq8bHQD/sE+yHogV8cZ/xtMPv+nDvOwd+gYIolnm55oye+7+qR+UHQ98xR9sU09u/xx/96eNOq7RMXHFNwAqbcSXnIQ22SP8pH+a3IccyMt8tGMbv1gzAJFTokBO+tHGfUvcHQvbQX/MzZoZSz3aIj7cO8SEhOboh+bxCztojXi1tl/sB328ZnxkvakemIs+fJmAObzOzkBe+np8Cnnxkf3kiwrsof0mTtz77Ck+oVNihJ/Mhw+00x972GH97AVtJIAx16yD+R0H7k3igD/UozFsYosx7Dc5cxE/2kjUux/x95qwkyZiRBv+FJ7kLezHvvF5ho/sLafgnTi1m5bRHrGiP/pgzcTGievUfpT335eIR8fxQLekgLwdx6ozeuKzgP/38f963oZQUlIi3txbVlamTCbzpmSAGHnx+OGBimWHkJeJ/Zu85Pfee2/+Nc2vN+/SS83S/b/bpcnXf0YXNXxa77n2n3X+dV/RxQ23a912acsbzfrsd/49D3lzt9TpbU1VOnbxbB27hDRHf7x4jt6yeK7+eHG1jm2q1bGN1frjhTOU+eQoNX3zav3mkWptXTVZWj5CWj5UWrEncYKXVzXvTRO1bUWVvvDx83Ru7hidnjtRQzIlGpLNaVCmLP+bvC2neQcql/9N3gP3u7yA3myGlFN5bpDuu/c+vbHrDe3auVuvbpNW/naH3vsnn9Xw+n/SxfP+RRfN/5LG1C/VxtelnTua9c1v/qekXXtAb7GQbdftBOQ9Mh8axMOe2LfQQGggNBAaCA2EBkIDoYHQQGggNHB4aoCH5zys5CFbZx7GHSl9/BC20F/qgX9eL9eAAGCFgQR1rY3j1aMAKKAwoIWTsYATQAhgDTvk2PJ45iEBTgApnBLkmgeZ1AFMgK/0dz/AEPCFOoAE9bbnU6Zc81AUuIK/9MEvQDLXhlC2iU/4TD119MFvQ0TqCvs6DuRAG0ApwAj4xfzUEzOgKWUS87Mu+rtMX9t3Th2x4lXI1AGnWA/AjjWlYBW/sQe4MYCyHeesC8DKOgFGnIxmbeyPoSdAmj74yxoYiz2SgR8+G9DzAB9gBUBjbfhMYr/QAWWvmxyfDcVoY24AFuthb6izv5Q9D1oAoOGn2/EJH1m35/EY4JtfG0x/NAKYZd2sDZ2xTyTmJxn0ATBZo6EwfjMXtrFDjGnj2ok+wETgodfrtjSnD0AV7RJr+uIffcixS/xtgzwdTxkfiC1fICA+Bt60EQtgKpCXsbQDBVJ/mYc29h69sn+MRR/kgGLuQcokg1z2iDi05hv1xIz+aT9Dd/bWkNexRAfE3df4yth0v2jjmhzdshb7j7/Y5fMB/dNuv1mXbeMvv19NP+yQmAs9s1+Uua/YV+zR33MRa3+GOB5pzj7iU1rHGGKGnvDD83luA/p0DHO2dc382EK72Kaf98BjiAm6AdKT+AwkRwfomTxN6dsV+MzGN+9/oS+eI/J993vEouNYWKMBeTuOVWf0xD3OZ0FA3sMf2nYVBncK8tpoCnlf3dasR556UdOvX6qh1U16T/0/6Px5n9W58z6voXWLtW5by0nef/zvr2ncx65V7pZ6va2pWscunqO3Lp61J1Gu0lvzkLdaxzfN1kkL3quLbxmhh39+nV5dOU16uFJ64GLpoaEtJ3oNdjnJu3Ksdq6YolcenKOb5w3QhQOP0ZDM21SeLdOgTFaDM1kNypRqINe5/8/emYBJVpV3v2CW3ru6lq793lvVPTMMoICKCAqCCiKbC4sgq7sYJRo1iCYmKppN1HyfyafGJYoigkaNJnFDcQFZBE2MoiioiMiuMMAMs/T8v+d3a96ZM2X3TPdM9XTTvHmek3PvWd7znvf8b8mcX5972ydr25C3qTi2xInebi9soihKlMRNXfGt76TMds3DG/XfN96pE191gQ456z066MUf1oEv/YQOfNm/6rAXXaC7HpTWrV2nz33uM5I4mctJ3rn7P4e883NTwDdrfF1cA64B14BrwDXgGnANuAZcA64B18AjUwMLHfLaZiywgzfBseEIADKYQhnQAlAC/CCnbefGJHaAe0AjgA4bktgBvAC3gAmc+iRR3tkfmMmrokOQAaDAHuPhj8EI4CDAEBvmC/0ow46VAR851UY7+rJBCuTDFxsfu8yPcZgD9wY8gEcGrSijnn7EAR+Yo9lhHEALoIixrBwQhD/0BXoZ+CIGdrqQtoxLsn7kIeS1sc0P7s1P5m7ADkhntsKctvgHCAR4MbatD+sGFGKtiDlQiZjQn7kwFn2YG35xz5jAVGJpflNOAqIaZLUyctYH0B/OERhH7ACR4Zi0IVbk+EDMbV3JKaM95bRhfhZb9MfpRcrxjXUH8nJvyXzuvMcu9vHHfKeMBBRkPcN1t/5AV+Znfaw8zKkjjqwBNvDZbNOOuBn87exn99jAD05hMl/mQRn1rB22eY64p5y5oGGuaUtiXPzgxDUxpC1l+MSaAhS5NruMY8+B/UbQ3p5PdAQ4xA52bU5oBBucLsUufcxf5sAfQOAfZbQBgNOH9TLgzXNmf5BAOb7Qh4R2+IMUytEz41PObzbrhB82HvOkjv74xPMC2LW4sHam2c7fHGxhO0zYtrh2ljMH+6MInmHa0oaxeD75PQz7WB3PJ/PlOSPnHj0wT3yze2xaG9rZHIkvY7B+PBfEk/niD4kYs1bEnjHt+8j0ITb0ob7TN7/feu09HtuPB5oiOeTdfqymoyeecX6T+a3zk7zd5oFza2+HIO/aDUq/Ifvat39QT3vxu/XEF/6zHvfCf9YBL/8XHfjy9+uQM9+u2x+UVm14WB/490/rsDe9TG3Ie1YKdfvezSuaT1Hve4C9p6v/Xadq4F2nqPCuEzT2t0fp3Ve+Qbf86CzpB0dK1z1VuuoAiVc08y1evr+bpoO1/ppj9euvnaazjxvU45KMWpUejcUFtZpVjSf1FPCOxbUA8nKSN1KcNDa9rhnQO5uQN9EV3/6WJjZID62XXvu2f9FhL/oHHfji/6f9X/gBHfSyj+jgl75fh511vu54UHpozVp99jOXShv9JK9vWjwyNy183XzdXAOuAdeAa8A14BpwDbgGXAOuAdfA5Bp4tEBe25QFSBjUsDI2IbkGEgCRiEnnxiT9gCN2kpb2AAPgAXVmi43KqUACbQAV2AYmMxbXbHACXLkGVgBygRzWnj6AScppw3iMC+zAJ7NBe8qBafhJOWW8vpR7xrG22ATUGES0eZBjkzp8oT998JXxqOc+TGaXtvQBONGeDXCrC9vbNTAHIEMbG4e5UY9/XIf9DW7ZyWezQ047wBmw03w0cGfrQzv8Y0yDf4wbjk097YBiBk6xzeYz7ZiTATbra/2xC6hiPE400o4ThtzjO4CQBIgHalHOWLRhbS0O5i9asvVlToxDDuQFftm8WRc0h22gIPMm/iSuSdSTKGPNOyEvvuIX8wecYTtM04G8rBl2LG7MgzISvqPDTgjOGBY/Gw+Ia/EJ1x972Dfgan2JO88LbUmMx1yxaym0Qz/usUc8WVvac08i5iTWkDWgzHwjvsSPOHJNP070sya2Rpz6JebcA+PRKyDTfER79GO9bCxyAxz0xz6gFv9ZF4Amv0/c44/l+IddEmOZr+iN3wHGJtkfBtj8+OMFIDZ1+Grzs5z4A2xDLYQxxI79/ljMmS9gGa2YHcvxhzkQOxJjkjNvrklcW2yZP/fh80zcgOnEndgwLmMyBvFg3blmbvTnNw89U0diPpPN1Xz0fOtn3uMxdTxMUw55p47RTPTDs8xvmf0G8qpmf13z3MLZbh0+nTHkvfzyywXkveWu1Tr2rDfpyWe+W08483064Mx36f99/Tf64Ndu1jNOf4PuXLVOD6x/WB/6/MV61rkv015vf6kqf/ci5f/hLA2+63T1XvACLX33Keq94FT1XXCKBi44UfW/e5aOeu/T9e2fvlH3/fBE6epDpKs5xUs6VLr6COnqozRx7fO0+prT9F/vO0jHPTGj/VoZrUiKiuvVFPC2mhWNJZzgtRSplQB4m0rixibIywJ2/7u87YXhJG+sJE70nW99UxsmpN/es05HnfEmHXTGu/SkF/6TnnzmBfrQ12/VR772Sx15+rm6c9VECnkvvRTI2/7GLqdp5+r//CTv5P8o980Kj4trwDXgGnANuAZcA64B14BrwDXgGnAN7IgG2HxnwzLcwJ/J5tx8bWubsPjHtflp0MI2/62cNgADAEXY3uoBCIA1gyi0AbxyzzUJcAaYAKhYvzCnDXEmAQM5nUcZbQA4AA0gFjACX/CVtsANg1605ZQj0AhIBDihzOaDP/TBBuXYB/ZYOWVcMx87HUsZ/mCTOQA4sYcd8495sQFL2zDhJydvaM8caNcJ4sL24XUIeSlnLEtmFx+sD35z8m8yP2hHXGxu+MS8mSdl2AVqUYZ/k0FeG5vxOJFt4+ILEJb1BrgB6K2t5bQFThJH+gIibVzaUE9OGXEy6EbcgJ/MyeJtNqkjnvRlrQBg+E5f858+6MigLfMlUU6yccntms10a29jcfqSeZqv1t7y6UBe5maJflzjg9nlnmuzGeb2XJLjn/llc6At8yIm5NaXdpzYNb3bvHk2aGd2rL3l+MEaEV90z/zoS3vGN1/JKbN+th5hPeMDH2nDmKyVwWw0jm0ArM2FteZZt/Gwj12gKXYBtsAjYmFz5Y9AOI2OVvAXHXJNztiAbp4NGyOEvDwX6JffEGzyDFDGSWPWHU3Z/CznN4BXTodzN9u0sXLKSPiAX8Bre7W12QrzsB9rQF/mbG3sHj+5tvkDbrHPt3dtTdAC/bBDO1sT+lFHTDi9z5gk2vEMmU0b0/Otf9M9HtuPh2nKIe/2YzUdPfHM8rvLbyP/2+2Qd2EAXnjktCEvr2omffOb30wh702/vU9Hn/FGHXzWBXrKWe/WxZf9TL99QLr1Qelzl31Hq9as1eq1a3ThpZ9S5XF76HF/cqL2fdtLlJz/QpX+/kXq+9tT1f+eMzXwj2eo510nqe9dx2uvvzlU/3HtK3THD1+gieuOlq7i1C4neJ8mff/ZWnfViXroqrN0+YeP0vMPG9TeSUYr4j6Nx3mNJbUU4DabDZFaSayxJFYrjtTku8JxM32FMvCVD0nPFuCNklgk7PN93m9edpnWbZBuvPVePev0P9ehZ743TZd8/Qbd+YB01wPSl752hf6w6mGtXbtel1xyiSYmNui6a6+VJja201yRXildc1v7MJ/OXxnQnh8PXsGSy+WmTIVCQWHakX8sex/fZHENuAZcA64B14BrwDXgGnANuAZcA66B+ayBhQp5p7OxuDNtDFbYZu+O2jI7O9q/s1+nvc77zvbz6d58tRzf2L+Zjo/baoe90OZU9qbTxvqGNmfSz/pPlYe2wuup2nejfLbGwa6ty2yNYfMHWgMIAHgGR21sa7Oj+Wz7vqN+datfZ5wAVwDkcP22NVZn/221nYs65gHg5WQvkHgufPAxuwMD50sc0RTJIW931pXfkE7I22g0ZAlmFqbp8B9vMz9A8Ywh7ze+8Q2tn5BWrZVOe9XbdOApb9Xpb/pYCizvW7VG9zz4gO558H79/r4/6OGH1+hTF1+k2rJYg3tFyj9jX9XPPELLzztV4+e/WPV3nKnSO05V6Z3PV+0dJ+iFn3ixbvjR67T6+6dp7bWnaP21J2vdtafowavP0M+/9Hx96vwn6FXH9ejAcU7uDimK6kqa0R+lZhKrmSRqJckmwAtwbX8nl2/lAnpn5zXNbcDbhryA5Vjf+PrXtW7DhP6wdqNO+ZO36CknvU0vfOOFuudB6YEHHtqcVq16MIW8n/70JZrg6C//N7FRv7/nnvY1h3ottUt2yf8PwW54PZ0H2CGvb7DM5w0W98316RpwDbgGXAOuAdeAa8A14BpwDexKDTjk3bFNSjZ4u7Hh3C07U/ky2/anGndHymfLV+zOhm2zafmOzLmzTzdtddqe6n62xgzthtdT+bEz5ZyOJvkpzR37PQtBLaeOOYlMLBdCPE17nKq2U8A7ozXvu2MaW0hxQ1Mkh7zd0UIn5DW4a3kIeNuHJOcHwJwOh3q0t5k25CVQQDuDvGvWS1f88Nd6xml/oVf81Uf0+4ekBx9arftXr9L9q+/XH+77g9Y+vEYXfeLjiqKaqs2acs2SBlujGti7rsJT91btOU/W+EuO0rKXHanHv/pYfeCrF+gHV7xV11x6ur7yoefqon84XH/32ifoBUcUtG8zoxW1jPaIFmt5PKhWXE4hbxw3/hjyNtuQF9ALaCUBdduneDnJO3sC3XKSt+3DN77+Na3bsF6r1q/Xt/7753rGqW/S2X/5Id3bAXkBvqsfelif/OSnFL6leSPA1+Cu5bsE77YHCcFueD2dB8chr2+Y7MoNEx/L9eYacA24BlwDrgHXgGvANeAacA3MZw045O3OJuVC2sD2ubgmHqkaABaEwPKROo9d7Ten6GxM4BX7qwZ5F0o8DczZPD3337kd1YBpySFvdzTkkHf2mOB0WNlsttkhyLthYqMeXr9RD01Il13/G73jfZ/WmnXS6tUP6cHVq7R2/WqtWfOQHl6zWp/42L9qWaupsSTSWNJ+lXI81lBlWUO5FQ317VFT7x4VDa8oqrqsTyuijPaJMnpMPaPHJhmtjBdrLBpSklTar0FOeNVymBqqVEsdoLcNpIGMYfDCv0YIy7t5HULeVqupy77+Va3fsFYPrl+jVRulr193s97xfy/Smg3SmjVr07Rh/cYU8HJ/0UUXt+nqxEalgNde2TwHgBdHeNUyKQS8nXGdKn4OeX2DZT5vsLhvrk/XgGvANeAacA24BlwDrgHXgGtgV2rAIW93Nil3dLPY+3n8XQM7rwH2CImjQ94diyXQKtShxZHyhXCal1d4MxfycJ5+vWN6ebTHzSFvd3XjkNchbwpL+SDzl770Jf3Xl7+sz33hC/rsv39Jn/7CV3TJ57+iz3728/rcZy/VZz9zcZou+uSFuuiTn9AH3v9+tZrN9HXJvDK5lTTTVykDQ2tJrEqT1FC9WVOcjKqVDGtZPKiV0bBWRnkti0pqxnVFSaJG0lI9StTYfBKX94TXxWnerRMQeG4XLWnGarVi/ed//ru++rX/1Oe++Fn92xe/oM988cv67Be/ok9f+jldeulnN6dLLvlMeor34k9doocfXrfle7wGeTvyjRs3amfSVIeBzebExITWrVuX/o9yCHlnEleHvL5hsis3THws15trwDXgGnANuAZcA64B14BrwDUwnzXgkLe7m5WP9s1vn7/raa40ACiYq7EXyrgGd8P5eFz9mQ714Ncr0j8YAPT6Sd7uPBsOeeeWF86Eq8207YxO8m5lPInUiCPV41iN9MRspIRXJ8cNNZP2dSuJNT7WUhxFasZNNeOWmlFLSSPZnJqNWKSxRqQmH3qO62rENbUadY01GmldzHd041YKeRtJc9N4m07pcrI3AfK2T/e2fWB8e03z3CyeQd7x8aaSZl1xmhqKm/iD76Sm2t8ITjQ2tiy9bzXHtHzZcjXj9veE27ldx+k3hps7NDcbs50nSfOPTud2ntDd2ZPPDnl9g2U+b7C4b65P14BrwDXgGnANuAZcA64B14BrYFdqwCFvdzYpfePb4+gacA0sRA045HVdL0Rd78yc/CRvd58Jh7xzwwm3YqqzdDB1RpDXoB+AklO5wFtO0kZJXQ2gb9IGvump20YjBby8prkVR2o1ErUaTTUbTbWippoRr3BuaTxOtCxOtDzmuqWkmaQgtMlJ2ITUPv2bJGOKm2NqNJtp4iQwAYqSKE1A3mRTasZA5TbkbX+Pd9cvIJA3aUbpaV5yA9Fb4HMbthKriBPOY+Mp5G0AuzntHAN0gbthmjnkbX8k2wBvMx0jXb9pQt40xtGOnYzmBDA/HsDeXC43ZSoUCgrTrvxHto/lmzquAdeAa8A14BpwDbgGXAOuAdeAa8A1sCs04JC3u5uVO7Nx7H19LVwDroH5pgGHvK7J+abJufbHIW93nwmHvLueEe4KwMsY04K8QDpSkzyFp4BHA5E1JUktBa2c6I2SpqK4mULLer2mVlxXXKtuhrxt0JukoLcVJRqPIi2LIo1HLbWiVgo8AcbA2zg9EdwGm0BlYGg9aaqejpMoTqEycJm2BnUBvO20BajuugVMY9VM1Ia8gN5YAGvzhTwFuJvi2f6GLxC2DWCjKFaz1X6ldTveTbWSVvqa6zbwbkNvQC3x4ERuCoU3rU37hDD2Ns05ap9qNvuWT3WS19aafLMNYHoK9IH67RTWTXXN670d8vpmya7YLPExXGeuAdeAa8A14BpwDbgGXAOuAdfAfNeAQ97ublbO9eazj+/r6RpwDbgGXAOugdnTgEPe7sbWIe+uY4RT8bLZKp8W5LXBDVS2T5c21eIEaqOmZlRLISavHrZXMbdfQxwppi6qp69d5hQv9U1O9XKSN4W8jRT0Anl5lTOngesGeQ2IpmC5/UpmXtscxWPp644BpHW+7RsDhduLxGneZrN9qreZbAKs6anaNnA1+Gpz6n6+6bXRgN5NcNziFubtk7ptnznNmwB57XvDTb4/3Nh0QpnvGbc2QWJORbdP+JZrdSWbTv/ynWNOS9erNVXrnKZuqdniNdkNJZsS8LiRvva6DeHbMHj7wu6EvTOJF5B32bJlfpK36Jst832zxf1zjboGXAOuAdeAa8A14BpwDbgGXAOzrQGHvN3drPSNdY+na8A14BpwDbgGFq4GHPJ2d20d8m6fhc2Efc2ntjsMedswl+/ptkEiEBFICcAlxRHfm6WstinRLm6nRhxAXk7xRhoD8qbf3Y02QV6CbieHgbZAXsoAvOOKoqYaUaxSo6pak+/4Wj0wl1OoUfq6ZF6V/MdpNhe0DXnDRQ7hrpUDyjmd3OCbxsQlff0115GiZlPVZqJqk1PLY22onX7XmDglKeiN4prqfL8YsM4rr6OKViT19FQvfarxmBqA9EakMYBwxGlcTv9yYpj4tGNr/sxGPj4+nkJebPvrmn3DZLY3TNy+a8w14BpwDbgGXAOuAdeAa8A14BqYzxpwyNvdzUrf2Pd4ugZcA64B14BrYOFqwCFvd9fWIe9sMsG5tT0jyAusS7/xCjCst1O9EanWaKgWNVRvNBTVG4rrseJGK23ThryV9oneuJG+SpnTqK0o3nSSl2/y8qrmsRTy8ormKK52xkQAACAASURBVD3FaidOAaD2TVjgZEsRr3Wuj6veSFRsFJStDKpULYrXQwMy268kngzuWtmuDzqgN41fwneEea01p3WbqvIK6k0nluN6PY1hJUpUjJZrpL5M2UqifLmharmqRqmiqFxXozSqqDygamVQhUpF5WpFy0p9WlnuVbNWVLkWabi2QvnqCrVKde1Rrmqs1lDSaJ8CBgrP9jeLOQEM5CWhGYe8vtkynzdb3DfXp2vANeAacA24BlwDrgHXgGvANTDbGnDI293NSt/Y93i6BlwDrgHXgGtg4WrAIW9319Yh765ngrNxsHIymzsAeTmd2wa8jUaiaj1SqVZXqV5TqVpRrVZVxMnRakNJndc118Wp00bMd3vbr1wGMKaveo6a6Xd4x+IxNaOx9LXEfF8WQMj3ZgGh6bd202/cBidQk2Vq1PdQ3FqhG37zY63cv6VCKatqpZKe8AUEc5rXTvC2WpzuNcBLPncL2v4GL69U5sRyrGocp5AXCFyvN1SuN1VoLNN573ivXv2m89U3WtNfv/Od0sTD0oY10gZJExu0Yc3tOvnko9WTr+iUM1+m6775H9qr1KtWOZeeqD7kmc/VrXes0oF77aM9iqNanp6eBu62T/4yHt/8Tb/7a6+VnkE+mZjCMtaQVzU75PWNktneKHH7rjHXgGvANeAacA24BlwDrgHXgGvgkaABh7zd3az0jX2Pp2vANeAacA24BhauBhzydndtHfLOHRMMudlsXE8b8ra/zZpsegVzokYtVqVcT78B+71rr9N62KMmdN999+pJj99PUSGnVqWksfTUKidWY9XS06vtk7Z8Z7aZjCtJxtVsLUtP6I61lquVLFeSvpI5Upye6I0VN5uKeQVzM26/ljlZpkp1pWrNlbrh9h+p8diCcsUBVctAXvtmbxvsRlE9Bbxx+jpnIHMbNM9GMKdtM51XVVFS2XRqGYElGq019Zd//wE9KKVptaQ7Vz+kD3z0n/TWc1+oSn9GI309KhTy+vYV/6GjTzhKmcIe+vKVN+u0E05RNNinJJtTXBzV96/5nr72lS/qusu/piQ3rLhUUr1SU2tsXElrLP1mr50unrbfm04jb6s9OiG1Wq0U8PJdXj/J6xsuj4QNF/fRdeoacA24BlwDrgHXgGvANeAacA3MpgYc8nZ3s9I39j2ergHXgGvANeAaWLgacMjb3bV1yOuQNwV3gEheh1xvtFSqLtfBhxyph1fdr7867/UaHhnUSCGnKKrp+muu1N6tSEm5pGVjK1WPV6gcNVVu1NVsRWolDSUxJ3aXK0r2SBPf2m3UIi1LxtXilctRtQ15Ab7JsvRUb5XXMSex4mSFyqWVqjSW68e/+4Gqew9pMNercrmmSgRQbqkRRwLw2ine+QZ546Ssdqqp/YrqRKONcfVW91FffT99+/s/0evOe5MWDS3VW956jqRbJN0mbVgr/m/1xO915EnPVvSk43TxN36mfCHSbb+4WfsuW6kvXHSxPv4v71N+cJG+cPHHddGH3q/q8JCa6UlnTg63T0pvC9buaJ1BXuAup3iBvY1Gw1/XXPTNktncLHHbri/XgGvANeAacA24BlwDrgHXgGtgvmvAIW93Nyt9Y9/j6RpwDbgGXAOugYWrAYe83V1bh7wOebeCvJXGCg3V99eV196s97zxHDWXZjQ60qfhXE65fE7FfE7lQk7lYlmF0rjKjb1UqjVVKhcUV/rVKPYoqVdVr42pUtlT5fJK1WtN1cpFNasjikYH1KgVVKvVVCkvU7m0TJVKpHojVpnv05ZaqhdWqlyMdMNvr1Nxea8WDyxR/0hBuaSpbMTro6uq1Xh9dCU9vQvw3QJ67Ru/c7SwwUneOKlvgryxyvFy7ZZfqWed8hpNpCh3oz584T/p/Le/Um8751iNZjLqX7JYS/qG9J2rL9fTjz9Gf3Pxl3TgKWfrtW95mz700Y/okxddrCu+c4V6d99dizIZ9Sxdqk9/4kL9z+Vf1Xh+UI1KWbVG++TwjoLcbfUD6gJ6HfL6Bst832Bx/1yjrgHXgGvANeAacA24BlwDrgHXwK7UgEPe7m5W+sa+x9M14BpwDbgGXAMLVwMOebu7tg5554gFTuPtuNvibdOp26HXNefrK7THYWfpqh/fo33yvVqxJKPh/j71ZMta2j+ioYGsRvuHVBoaURwv1y233aP1bWqptese0BMet1L13ICiQkFJY7nuvuuh9gHVCWn1mjXab9/HqDrSp0Z+WEk11j133s9naLV6rfR/PnSxbrz594qyK1TNlvXTW6/R8LI+ZRb3KRvtpV/ffZdWa53WSfrwhz+sVnlIy6tDakbAXuCupblZ1PYrknkVNSd4SUDeRvo66pFqot748friNb/W5y+7Tn/+lvP11W9/TR/+0N9KE7+U1v9G2jihtRPSmvWrdNxpJ+h/V63X7yT95Fe36IL3XqDvXHuNrrzuet6dnf4f2fo1a/SZ979H/3v5fyoqjyputtLXQ09HIDNtA+QlAXlJAN96ve4nef0kr3bl5omP5Zt1rgHXgGvANeAacA24BlwDrgHXwHzTgEPe7m5W+sa+x9M14BpwDbgGXAMLVwMOebu7tg5554YHzpSv7Uj7GUHeJGmmcHC4tkwHnfFmXX3LOo0NDamRyegJTzpctz8sPTAhbVgjPaW5px6Tzeq+23+hj3zkH5XLZ1MI/MwzXqPfPiAduKKh/UYX6YE7f64LP/YBFXIF9Q1Heubpb9Ztq6QnjSXav7RY6++5UX/9plcrl81qYLSlz19/i67/zXpFQ3uo1pPVz393rQb3KipTebx+8DvpxOOfp1x/RgP5uq655jr9n9edoifkMlpeHU6/DbsjQepWHwAvqRlHSmJeWV1XM66n13xzeLje1CFnnKNPXPcbnXH+h/WC896jTG9Rf/HXb9bbXnOiRnfLaPdMRouW9ui7V35Zhx/7NGWWjOgV5/2tTjz2WPVkMsos2V2ZRYuUWbxE/f2D6u0b0lBvj8o9GVX7MqqN5lUuA7x3TtR8ZzdM2LNv8dopXnt1M5C3UChsM823f3y7P74h5BpwDbgGXAOuAdeAa8A14BpwDbgGXAPd1MBChbxsGloKN9ttczYs49raTpV3tu+8N7uWd9Z32u2s39692bV8e+07x+u87+xvdi2faX1n+/l+b/O0fHv+bi9+2+tv41i+vfazXW9+WD7b4y10+xZHyzvna+WWd9bP9r2Na/nOjMezEPbvvA/r7Hp7z4/5Zbn187y7MM3j2Z14mk4f//jHb/UseHx3LL78PjzmMY/Rvvvumx7O4xObYQpZD9c7y4+8/87xt5nEb4aQN0kXd6g6nkLeK29ek0Le5uKMsrlES0r7aCR+sm65eY0OrT9Gf/7sZ+vum76najmjwcElyvSPKlPeX1/+4e16+zkv158990Dd+YtvKaouVXZwQLv1R8qUD9NXf7hKb3/lq3Tucw7WfTddrmZldw309CjTW9EBZ75R3/n1hOKhPdRYMqif3Xqllu6R197Pf5Pu4OzqutXShnv18Ib2SdZvfOCv9ORcRis2Q15AdRtWzyRQ3WhrkLedt0FvG/LWlTRjFeIxvfPCL2hgvyP0kr/5iE479wJlFo/qbW99q7TxljSt27BODzPNdXfruOcdruUHPE2f/cpVKeCtDi7Rzb/7nR7cdIZ3w4Y12hQGrb/vTh2wV1Plwkh6snZn5zPZQx++ppnv8TKGneR1yOubI93cHHFbrifXgGvANeAacA24BlwDrgHXgGvgkaYBh7ztTclOCNF5v73NW9v0tbyz/UztdfY3u5Z31nfed47Xed/Z3uxaPtP6zvbz/d7mafn2/N1e/LbX38axfHvtZ7ve/LB8tsdb6PYtjpZ3ztfKp5t39t/Z+85xd9Ze2J9nI7yf7Hp7z89s+jeZP162YzDO49aOm+nVIW93dMTvg0PeXQded5a/zaT/tCGvATvgXq4yrqWNg3XjrRN6ybMO1R5LMyoNZdWbHVdv+Sn6za3SQaV99Lqjj9O9v7hS9XJGPX27KdNXVKawnz73vV/pzOOerVccdZBuu+EyNUoZDfQuUqavokz+AH3he7frRcecoD895lDd+bNvql7MaOlui5RZNKonnvZGfftXE6oPrlBjSb9uvu17GlhZ0GOef66+e7O0PN+raiajviWLNNjbr/GlGa3sz2iskk//MiGKWoqisU2gd9cvKoCXWEZJpChpn+blRC/X+UpDPaVlyvTXlMn0qXdRn3K9I/rhty/T6UfvqV5O6vYOKNOb19KeTJr+6+r/0f1A3fWrdf2V31TPYE6LBwZ07VX/oec956nK9I9ot/6yckNZVUaGVS4WdynkZa58W9khr2/APNI2YNxf16xrwDXgGnANuAZcA64B14BrwDXQTQ0sdMjLpnQIIWxzNiyzNp0govN+WxvcZpd8snYzsRX6Y7amsmttw9yubczOe8opC1Po/2RjhfVhv1153U0fQlvhfDtjZvOzcsutnDzsH5aH11ONF7aZrq3OPt26t7mRz9RmZ5/pxIQxbMyZjmd9w7xzzE6fdmSM6fbZ3vp21m/vnnE75zOVL5PN0+JqeWdfyqeyP5m9zv7h/VTtO+2bL1O1N5ud/azc861/sz0ecxcPNEpyyNudNeA3wSHvrueBM4G1O9p2xpCXgUq1MfUUHqu/eOs/S6vv10uf/TQVenvVP1DRoqE99fOfr9XjSntpRc+QVv325/rYR/9RfQO9WpQt6aknn63/+c0qVQaHVVmU0ao7b9LHP/I+Dfb1aOlAQYeedLZ+9OsHlGRLipcu0gN3/VJveP0rtXRxrxYNNXTp93+ra2/dqHp/ovqipbrp11dqaDyrTH4v/fhO6a2ve6VKmYyyPRl9/EMf1BNbicayQ0oq5QDy8k1aTvPO3aICefkWbxLX0tSI68qV68rF++jGWx/UHuN76XMf+7jOOPpo1XsyuveX39Vj98zqgxd9XK9681v0g/+5TsO5IWV271emZ0SLFmXU37O7du8b0V++/Z268KP/oOxgRm9469/o1ee+TaXsoOLCgGrlomr1+k7PfbKTvPYtXk7xkjjFS7tKpeKQ17/J69/kdQ24BlwDrgHXgGvANeAacA24BlwDj2oNLETIy+arAQU2wrm2TVnLrSzcKLc+U+W0pX+YW3+za/XWxsq5n8puZ/lkbW2cMLex6M81udWHNkN7Vk9uvpHvueeeW6XOdlYf9uHabNu12Q37b6tsMnvWt7NuMh+sbZiHvoTl4TW2QvtWZ3HjftmyZVuttdWRW1/aYcv6hznt7N7aW27lnflUtjrbhffYDO+5Dn2d7LqzvfVhzqHfk7WbrIw+4dy2Nw8bI/St067Zm2x+5m+Yh2PSx8botLu9+6nG21a/0NfJ+nfW4+u2Umd7u+/0IYzftq4n62d+Wm5twrh11lmbMLf25qP1sfWw8rDPtq6t/7baeF134JrHccfiaJp2yLtj8evUHb8hDnnnjgfOJoucEeQ1R6r1WIVKSz1DNT3x4GfpvgcmtGEtp0mlDeulCz/6CQ1nlmp4t37lspFuve0BbZS0YaO0avX9Wr4iUe/ijHoXL01f83zLbe0XDGtiQg899AetXJ5oaPdF6sn06LH7H6p71kjrNkoPbZTe9sFL9cOb/qDlww3t0T+gX918taoriukp4b0OeKbue+B+aeMD0sQD+us3vla17LCq2Zwa1domyMu3ZBtz+n3eJE7UihK10m/01hQnNUVRXSPVRM964ev1b9+7WZm+uv71I5/UmccdrpFMRksyGQ0MZHT55Zcoama19/4H6qof/Up9hYaOPeFkbdy4Qfc/sEpnn/sW/dcV12j3RRktXszJ3yF94lOf0t+87lQ1+SZvcVC1Bu9Ub79629Z0Z3NgLpAXuMs3eUlAXt7rXi6XlcvltkqdJ3u7+dfRbsv/2t414BpwDbgGXAOuAdeAa8A14BpwDbgG5psGFiLkDTcQ2Yw1CEG5bc5SNhOYYDasf2jLythzoJy2oX3qrSz0bapra0tubbBh0MTqO+0alLQ+YTtrS91ee+2lvffeeytfaWtjsIcSjs286EO92eaaZHasfFs5NqeCiObrZP1tLJt/Z5vQV65DP60tfpody7HHXMmtj/lIvzCe4Rhmk5y+xMbKaGeJsqn6mQ/Wj7HwBVv0oT6MlflHG0v0NTu2pmbD7E6Vm4+Wh+NZmeVmo/PeysmpI8cOvky1VpRbXLnutGl9p+qPfXvOzI7ZoA+gwPyi3tpaG6uze3Ir21Yetp9OH3suLMdvs8E4rBN5OF/ahIn5hPf0Z06U0df8sNzKaGNl5GbDYkMZKYxxOJb1tX7mL3Mx22bD2tLGfGNOoX2zY31oa2myMqvzfEucPBbzKxamaYe83VkXfgcc8j7KIS8Qz0BgFMWq1RsazFe0KNdSX3mFsrmKRvN5FUf61d+TUXagX4N9eQ0MjGk4u0K5XF2F3IgKw7srP8Q3epeqbzCnpUMt9Y+sUHakosLIoEYHMyr0ZTTc26OlvN55sKVMX6LMkhH1DmR1zMmn6ue//LWagyMqZDIa7M9oMalvSIv6cuoZyWkgN6RaaViN4rBqo6OqV+qqVfmQNIC3DXltLnOR88rmVkTiu7x1xUldUVRTvhbpvZ/6op5+2jnK9Nf1V2//e2ndH6S1d2ti/Xpt1Hpdf/XnNTKc0aL+gobKe+r2ex7UNy7/tgYGB1Qol/Wz2+7Wanj7xHpNbNyghyakjRvXSQ/+XK868clq1gqqNwC83YW8xJH/oOM/nsgBvJTV63WNjo5uBXgBvg55fcNlvm24uD+uSdeAa8A14BpwDbgGXAOuAdeAa2A2NfBog7zhZjkbteH9tq4NRgAyDI6EYORlL3tZuklpNg0qdtqk/uUvf/lm8NJZb/c2nt0z7jOf+cx0DK7Z57CxrC25tQ/ruDaoZOPvt99+aX/2SoAy+G99uDc7jGWgCvvck8J6+oU+cG2gx2xZGTE7/fTT0/70s/Sc5zxHhxxySFqOfdrbGJbjxytf+co0BjYe/Z/ylKforLPOSm1RTpn1sdz8pu4JT3hC2sZiaOtIW/rb/MKYmR3Lze+XvOQl2nffff9ovHD9J5uL9Td7FifL8QG/zLdTTz1Vhx56aOo3ZWyId86Tcfbff//N8TXb08lDf629xcLWknLz2/KwLe1p++IXv3gr32lz0EEH6VnPetZmEEh/WxOzy7y4xk6YbIzOnDZhGWMTJ9bD+lsMw3hybfWdNswea/+4xz0ufeamamNtyS0eYW7l5IyJvvHHdGVrbb502mNNqDN/6UufzjnRhrYnnHBCqhGzSxk2n/a0p+nAAw/crBfq6YOvNiZ6wq6tiz0bNl7nvKxfmIf2KA/72LWtA/fhvLkObfl1d+CZx3F24mh6dsjbnfjy/Dvkdci7CZC2QSknNCu1hkaKdQ3kyhrKF5UvjSpfyKtQLGg4O6JCvqJSPlEpF2s0X1Yxn1d5NK9KqaDcSFaFYknFUqL8aKz+oRENDw9pNDesamFE5UJRw4WGPvPtH6uw8hBldsupODisu373v7ro4xdoYHFG+cFB9Q/0anAkq+HcqIZzJeWKZRWKRVUKBSWVqhrlmurVhuq1SI0Grw/me7xz901ewGcSt+EugJfrOMa3sorlvAZHc+rJ5bRkKKel/UMqjAxpsGeRBvv7lR0e1MjQImWHlqind1iDw2VlswUNDw9rMDukbD6noVxRw7mCctkh5UaGNZTLK5vLqjSyROXhJaqPlhXVmkq69LpqYC7JXtXMP1oMnIevavaTvL5ZMpubJW7b9eUacA24BlwDrgHXgGvANeAacA3Mdw08GiCvQZHOnI3a6W6CAxFPO+20dCMSAAJMO+yww/TUpz41BStnn312CoQAcZQZ0AnhBeMBJF/3utf90bi2aWy5+WU+Yod+5OE8gLXA3ze84Q1p/etf/3r92Z/9mV772tem7WhvUMeADfUHHHBACmHYWGUsbGP3T/7kT/Tc5z43LaMv6elPf3pqj360szGApdyHiTrSOeeckwJZg4dAPuzjA6DW5mk54JdxuLdxO3NiDkDEX2wBjLDH2gAQKafMYhbGkBi99KUvTX191atepWOPPTZtR5y4x9/XvOY1m+dJedg/tMm1rcEpp5ySgkVrS069tSFnHmF92MauTzrppNQH7NIHUAmcI6Ep5nj88cdvvkdjtKW/2WfugD58Mh+2lZtPtGEc4sB6mQ/Eg7gQCxL3ls4999xU44997GPT8VhTtENCDzwPYZyZ31FHHbUZWLJujI/PjIm2GMu0ZDqye8tNg+EfSpi/2KIcoMk19k888cTUZ/rhM2OgoVBbFgdyixf1QF7mwzMWtgmvaWd9LDd/7J6cdsSOOuZOGT5aG7Npfh133HFpTJg3sSBnDqwD+atf/eo0xhZH+jM37IVryDXaISaMTTv6mA92/+xnPzvtz3qaX+RAc2Jg644vjGH+knOPNhmfhH8k68M1v0/U4TcJvZjv9Ld5h3b9ujsAzePY/TiiWZJD3u7EluffIa9D3q3gHQAP0Mvp2EqtpmKtokK1rMJoSeVqXcVSRfV6rKiSKCpHqpWqqpYrqpQrKpXKGh0tqV5vpCdsK5W6RisVlavtNu22VeVKdT32sGN1x1pp/TqOp67XRR9+p0b6M+rry6g4WlK+WFJhtCJeIT1aqqpcrqpRa6g6WlGLE6v40IjVaMSKIr7DO74pzeU3efkeb/sErwHRpFlXpZrXaDmrQimr3GhB2XxBo6Vy+s2i0UIxheTF/IhKo0VVyzUVcqMqAHRHRjQwNKhsbkRDQ8PKj+RUKuRUKRVT4J0rFJQv5DRaKKg2WtNYNN5VyGuAl398hZB3qlO8fpLXN1/m++aL++cadQ24BlwDrgHXgGvANeAacA24BrqtgYUOeQEbL3rRizYDCAMRlBn0mM4mOEAC4AHopT2wFlB45JFHpvDKgNYxxxwjgAnlIcSgD/dnnHFGCp6AeGECrpDY6ATM0Bb/bDMZSAo0AbK88Y1v3AxSADjAM+Ae7dksJQesYIdxsXHmmWemCZhKHTkJf2hDXGws89HsUU/iHpv4SHsrox/+AnpIXBu0sRywRvyoA/CEc+eauAJqAWqMwVhhohzwBYAGvnGPbcbGFyCWxY8c36iznJPCgFFiGPrNuoXtbH7EyPqSm24sx44BtxCAWj1l+NoZQ2yZXRuXNsSF+RsAZ47oi0Q5gBp4i75Yb6B1GGds4jvjok3is63EmIxP4pr+2LW1oTwEqfhjcWWfjbUEPrMG4XywBeDFN7ONXgzSmoaJL9q1dth68pOfnNqkLWsVJp4n+lg7freYL2OTbD6MDXgBUOIbaxCeLOYPM4ij6dJ8pz++YJOEJskt5p16tX42f8YNE2CU+GEXX2iP/8TETslSTj3apy5Mpm/a0IeT9mgBnxiTfmF6/vOfn8JYACqaxhc0QzmaZF3JKcev8PfPYkW8accYFlPmb/8bgR/YZ3yuSdbOnk2LCyfcWXdrg13iy1jok/jQ1mzZNbknj8F814Dp3yFvd7TK7wC/F/zOwnDabA++107tN+Dam3C3vNXX+JXn8xcQT/ubvCxyuJCbFz2JFG1OTDRJASInRUnpt2ejRM043pSo50Qt0NXydr/UfhQr5nXQ1ZpGSxUNFSsayJXSE6v54azy2V4V8/0qFvNpfbXeUJQkihg3aaap1WypxXUjVjNppmONjY8rbgJ2LXX/dcVhfLZ/3T7BuzmOUUP1elW1ekW1elXVGqnWTpWKarWaarXqllTlFdSkdnmlWhGpWqmqSvtKOU1cU1avtlOjWldUa6Qx3r6P2xcugDf8Fi+nem1O+Mw/ijtP8Trk9c2Sbm+WuD3XlGvANeAacA24BlwDrgHXgGvANTDfNWAb+GyyzfeN1en4xzws0R4QAtgAYAAZqKPMNmnNpvUhp4zcIIzd04+TgfQFhACeDMQB1wzAUQZMMsBBf64BN0Au4AugxaALAIdEnV1Thw3GxG/uGRM7XOObJfzgpCTj0J7coArX9APQkbORiq/2+lbK6MPY1HFNbteMxzjMiT6c3gXQWCxpx6lgAB1+AeHQFG3NH/rTHtCKfdYDKAR8Az4DnABTxIQyEmWMTXs2fvGPMuAROUCMNQJ2MlfKwkR7xmdvCBskfAAgkpMoYy6MQzL4BtAkRvS3+bMudtKYchLtzY7ZwKbZoYx7a2/2rC05c7A23BuAxK7pC10xb+qIGzCW9aAfifhiB70wb+JLe+ZKTNEb5czJ9GXAkTHxi/7kxNNeZ20AHO3gC7CZ9aYdvrDWNhfWnjFJ2GYcxsMuEJM44yf+8kcQ+G99Lbf40J81oK/5BRi0NccG8aEfNtEeMTFIjc7wFQ3yxw9ozGxzYpk/buA+TNixOQCfbS6mR8qww7wAncSE8fEPjWGLdSeFdvHVnif+QIPfAPRMbu2xQx/8sleWU4f/PEvMnbXgOeM0O+UWH/pxT3zpQ398Zz6MY7GkHc8H9RZvG5e21OOr1Ztv2DKQxVzDNaCP2QKmozP84HlEb3ZNjv/EzcrQKH0Zh3HDtcauJ4/BfNaA6d6ejfns6yPBN55/ficd8m6feXWDm+1KGzsBeYG0BngbipPGplcPN9VMxlK42uQ1vkm8KYWgtw1y26C3bccmbYCQU6BAwlKplILC8Buu/MOtzKngSk0NYHGyyZf0e7u8Chn7UZq4xmbcTNJ2Ns58y/HR/mpistziMlUezoc5N+NoU2rD9YTv/25KxCaNEXHawWSvaeavPizxH1vYs7mwdqybQ17fbJnvmy3un2vUNeAacA24BlwDrgHXgGvANeAamG0NLDTI27mhCUAAKNhmLECDDUXaGeTo7MM97ainLTYMRJBTx4YkUO3www9PE0CLayAZCahMWyCGjQWIBUABVikDhBgsAuAAVBiP+pNPPjmFO/gA5APQGJAFmJhP1AMfOyEv/hgIwQz1uAAAIABJREFUA1QB+4gDIAtQBZDhHiBDHb5QzjVlXDMu/jNf4od/tANQUUYdMaC9nQoG6JEYH20xT/MVeMj8GRffLC7Mmf5HHHHE5jiHcWfjF8BmfYgDsIl7/AU2YitMvB6We1tHrvEDv+hv9gFPgC1AGrCMnHjyal+zR4wZh3L6EjvmbPHjGnhlCbBIH0tmJ8ypwx/zD3+4xj77WOgLIGn6AjKyxsBW/KCO/taP9oyP/9gGfOIfbRiX/pyy5pq4oQP6kiyu1GGHMvoxL8pYd9oTK3TBGAZ5qWc8ytEI8JFr1prx8dPGxnfaYpdx0A9jMWfKuSYHThvEpIwxGDMEjLQjXvjJGPiDRujLs2L+MWfGNz9pOxnkJQb0xa75xdhhoo7xmB+axCb1+E+5JWyRuMcPnhl8P++88zZfo0P0hk3skELISzn9ODHNvJgDJ+z5XUB/lNn4zIl44wt7oeiDsYkh62ZjmM6JG21tXPJQh9zTh/781vAbRXvmhE/k1t9sEzO7Jmd8cjRjsaAsHJNr+lFOPplfne39fuvfOY/H3MQDbZPsvyt8HXZuHfg94X8THPLuOBPbUZY22/12EPK2T+ByajcFrEmkJKmloLeRtFRPWooSwG89/d4s353dAh3b14DGNuRtHwG3iRrENNBpsBfgW6kAdtunWiknWXv+x9WuDTTaPbnZn6+5+Rj6HF5P5be1CevbkNdOTm8Nee1E9Y5CXvOT/xA2uMt/IBjgZd1Yl3K5PCXg9ZO8vnky25snbt815hpwDbgGXAOuAdeAa8A14BpwDcw3DTxaIK/BVANKtkk71eYs9dSRc3oSOEkCalIOxAWmWAKGcG3gl2sgjsERoBvAw4AJJ/IAPzYOAMxenUwfQBXwhrGAMwBQxgT62ViMAeDkBGMn5AX4GWixeRiksVgYfGE8QJ6BNXxisxXoQl/rzz2xYHzakJgvEJk9GEA1ABi7wCXAE33x0SAV8zB4aOOzJsAs5kMZfcixz5j4yxjcmz8AOeKDL8wzTLQDRpnftAOq0Qf4yzVrQR+ALOvKCW1LvOKWeNp4tANYMlf8Il5m29pQzulU4sjaUh4m2ls/62v3rD0nIfEDKEm/Tn0RvxDy2tpjixjZiVXWgTLacmKWPTLq0QN+UcdmOvEx/3gVOOPiA2CfuTBn1gkfueZkLNqz+QMbDa5jh/XBRzTN2tt60x6faMNa0Q6/8MPGwT71lJGzTqZFi1En5LV5Um9t7JXmzAFNUU5MeZbMNlqYDPIyLr53+kI5ZST8JQFZDe4wBjZZjzDxhx7ohVhjg/U0TWKDsXhe8MsSzz/POvfYRadWZyd46cszRHyxSzvWl3L+EMH+0IBYkzg9jHatjjLa2BjkrAfPNRqw5xd/WUfW2MZhLP6AA5v4hm75ncBn5sMzRR/mSU6izMrDMtoQL2wzN/RFjBnD5uz5Fm14LOZXLNAtyX4HfH12bn147h3yLjzACxecNuRtQ0RecUzilcctRfGYasmY6gmndKtqxnXVo3FV4zGVo5LKUVHVerV9krZRUxLVFaepsRnITgYpQ2Bp9eQGfg00WruwzVTX1vaRknfOYyZ+TwZ5De5avrOQl/945T/0SPxHjvln8J1/TIcneDtP9IYns7meb//4dn98Q8g14BpwDbgGXAOuAdeAa8A14BpwDbgGuqmBhQh5bQOWHHAA5ADsADeAE1xbm6k2Z62evQUgCOAIEAkIBCDZa3MpJwH4LAEsSEAM4AvgBGAG+OGeMYE0tDFIwz313LOnwb0BHyAuPgCsyIEljE/CBuN2Ql7a2Fi0AcgAAokB/lJmOaCGk4GANObGONjEF2wQL8AbIIccyAMsBRgBsoBTtLPTk8SO8Q1iETN0ZqCM9QDsAHqwZzZZG8bANmAIO8SK+NkYrAd+0QYAhc/EydaLnHGwZdfcc00cGYs5co8dUqgByrk3OGf3nN4EfBlcZN6UsWbMBf9YA4s5/SzZ+JONA8DGBmsBZCOmtDN9sU62xuE17emHbeAm8Tawie/ED79sTOrxB/8Zk3r6Uk/8GBtwiz6YA3XATAAmcUMDrC+6YO60Jbf40J52QFxs0Jf1oZwY4xOAkDVnPCu3+FuOPdZoe5CX/vhOPxI+Mwd0wfjogjF5XvCJttieCvJij9Pb6CZMpnlyS7SzP2DALjFhbMYhcc0zxBoRazRLG0Ar7blnDPMfv0hoCI1ZLGyNuOcPD3h+6WOQ12JAjk2eMdYc30j8YQnxBkRRTuJZ4p72Ni5wn4RP/GEKvwdom98vxjM/8QONmT4YFxtWT45t+jMWNvjDABuTNeWaenRo49tpZ2Jl43m+c9DM4ze78TPtOuTtTpz5beH3mt8G2I6xNst3hkcZG/J8biDyjCFv+zu6LdUbY6o0xpWttVSIEsW1UcWlghqVZYqbe+nm22/Wc087VsXqaHqyE8CbRDXFMSd8t3zA2cTTKQDKwzJrN53c+oVtrWy+56HPds2DZtdT5eG8JoO89qpm8h15XXPnuPwo8B8q/McCPwp2qhpf7RTvyMhICno7ge5k9938h7Pb8o0Y14BrwDXgGnANuAZcA64B14BrwDXgGphvGliIkNc2uG0jFmAGdKCcTVlgLQCCTUX2Eay95YAMrq0/OfdAG4Op9AN8Aa6wR+IeGAOsoZ5+gBBgmPXDDrDDYJ61A5yG0AbAY5AUOwAbawvE4pr2ABcALuPaeOTAHdpQT19gC5AKcEM86GOJOAAQgVP4ZydtuQ4TdrFBfLDDnJgbJyXxhfkDqWjHfNCW+UwZtmhnsaAv41IetqMN7a2PQUnAGb4DzIB5Nr/w5K2VGdQ0G4wBeMR/ADpjcOoWoEiZgWZy+hI/wBf9iSF6wV/mbv4RN+ZCfyA5bcN5cB/CLIul+URuiX7AT1s37kN9MQ73ADG0hk/Yoz9lxJ39MMrQKWVmG7/RDH4b5EV/1DMO/bAHlKXc5geMRzusNXAUqIyOuA5P8jI2ABM9sVambdaJeNEPW6w1zyFt8Q84zbjMmUQcAai2FmgoTOFaASQNQlrMscs4+MMaYps1ZG1oQ2zwnWfW1sJyYoF9a2fl5NRZzjUxJHW2YWzmZHHFliXGRL/UkfDf2lkZbfCdPqwBvwHEj/Xh2UQDzIk1QMP0wwf7IwHWvTMRV+IOGGY9uAbGk1hbG5ucWPObwzWawV/iR05froHmXKMVxrZ44S+/rcwLP3kmOxO65RnkGQ5jxzX2bD6h3c52fr/1b7LHY27iYc+NQ97uxJ/fEYe8cwNhQ3Y3G9fbhbwAwy2nPnlNc6Jqo6VcfVyjYyt16z33aL02SBvX67orrlQlW1O9mugXd/xMR5/6TA0Xs6rWamrFdbViXulcT1/lHEVbg8ttTa4TMHJvf2FAP+4t77y2vtuyPx/qzM+p8pn4OBnktRO8lm9Z0+kJO/SL7/HaSV5e08y9xd8Ab+cp3snAblg23/7x7f74hpBrwDXgGnANuAZcA64B14BrwDXgGnANdFMDCxXysgnLxqFBNq5JABOABEADyGFgjPaUA1EMNthGrt2HkJe2ABSgCKfmODkI4AFiAToYizbsU5CTDF4AnYAljEU7/AAQUc9YlGHbwDR9gYzk1GEfgMIJWWAMfnFPX9qQA8xsTHIDQ1wDhYA92DJIAGAEwACggbw2Z3K7pi8gjM1Y2gKgmDfzwQ4QB3+wC6BCWzYns0NuMWZ+jIVdW5ewnV3TnnaAKsAeySAZbfAHiGknR7m3OVDPGuAn8B3/AYxALrNPPb4CfSkzn/GJsanHHutEGxLzJ+fkJkARu6yRlVFu9i23WNt9mBOzEPISE9MXcUJjaM18YJ2sv60jfVgTIKsBdupYH2LH+NwDYi0+3JOYJ/Fj3cwu0BSbxJs6/DOYzFpThk10D+ygH/ehtlgLIGFYz1i0YS7YtxOetMEWzwInPsPEWMSDtiTamt+sE/YAofhMPcAZ+8wdqEhbfJsK8hIv1hFbXE+WiD/+sRbE2eJJzjwNnGMDLdCGmNg9seOe+dsfKZhf2MBX5mnzst8R7nm+gaz05VmmLXbpxz2nfMNEW34fAK6U83vDbwL3xInEXGzNyEPISx0aoT3PNH4RO7TAs0YZY/NskOMLOmUM1jtMBorxgWeQOvqEifHZyw3L/HrrGHk85k880CuJ3yFfl51fF37j+A31k7zT42Ez4XFz3XabkLcNeCOl39RNEiVJM/2ObjFu6ZkveZVu3TChv3zz2YoLu6lcHNUZp75Yn/6Xf1U0mtXNd/1Iz3j+U7V0uEejo6NqRlU1o4oacVX1uNb+Zm+85bQuoHBbaXuBCiHkZNfb6z/X9ZP5HJbNxL/ZhLz2LV5yEn7hp53gDeGuXYcwd6rrbv7D2W35RoxrwDXgGnANuAZcA64B14BrwDXgGnANzDcNADPYrAxhw0LYtGROAN7OeVk5AAUQxD3gBNgEsCAP50+9JU6wAT2ox65BE6AFIAVwQj22aWN2rT/3wBJAmtmgDDAIPAl9xYa9vpT+gBWzQ38gDNAI8ATg4mQlvpOsPbYZh3sAFPAM+Ai8AYYBKjkRyDj0Yz7AI2Ae/SzRn2va4Bd2mSv+An7sJC8nEZkfwId2+EZfwA5jMgcbG1+AdiTKAWxhG66ZF2Ox+YsNrrFHDpAy//CLzWFsUQZcY37mN/2ZF/4YpLa1x1f6A6iYB3MiUU7CHnbwh3HZ1LfXzzIm/Zgra0EdgBEAyqlb+mKD/qRwfa3McupCyMs96wGoQ1/kllhLxjbfyNEu/gGw0aDZJRZ2qhWbJPoCIelniRgwB2xThr7QNHaJC6COPyYgrowTnjolvsQHXRIL1oExscUcSJQRe3KSnUTFT8bDL2IFmEWX5r/l+EN/2pnP5NTjD2MRe/zjN435UIcfBk5pPxXk5fnjOcQWc2A+YcIuOiXhB2uFfYspYxB78401IJ7YwxdiwLX5a/fhfIgp/eyPJYiT2aOM9ccWvqJns2dtzBezyVgkfgfpx7zQKP1ItKOeOlIIeSlnjsSAOnREH54hYmC2ybFDG+A3sWEN+aOKMLF+2ANWT3aSlzlgy+bi+ZZn02Mx/2Jh+nfI25214TfEIe/CA7zwue1C3mbcUJo4rdlsqRa3VIyb+vl99+pP3/I6jQ5lVB/OqJAf1UiuocpgQcXhAd149w166omHarf+HhUKeTWrw0qqwyrXahqt1lWvFBRXRhRX8qqWRzVabahQjVSu1lSpVlSqVlSpVhWVa2qUaypWKspXyxqtVFQtl9Qo59Qo0beiWqWiqJJVo5JTpRKpUm2pVqmqXimrVq2rUaurVS9prFFKvwsMlJwJNN0VbUOgO9n1THxow/lYdmq3M7f6mdi0tvxHJ//RAuAFypuvnOA1qNuZTwV2w/L59o9v98c3hFwDrgHXgGvANeAacA24BlwDrgHXgGugmxpYqJA3hGu2IWtQgz0ETtIB+gAXnEojASoMWoQb69Y/hLz0A2gA+QAfJGJJDiwBimDDxuSaDWHgJvCD/oxHDswht7GBcNhm05N+lAOZ7B6Yxh4IddjgZG4n5AXoUEcbbOOn+co8AHj4g7/YYgzAE/1sTJs39zYWfmGP+GIf4ASwox6/DEwD3QA7tg7U2xyBhYAi+gLCAFbYso1eA82UsVbEA9CIDeyRE2PscU1c8BUQyfhAWOJMGfXAJcAhffGfMuqwTzuAJzCQuZPjG/Hm+6T4RGJujMe19bcY8IphfMQmfegftgM+AsWpt3hwHSba4yda4JqxWA9bN3JsozH8NbiAzswuoLHzBCkxATjTBrsk2hEP5mGJWISQ105704/1oB0+MTeuQ8hrNmjLtY3DOljcbH1tbvjNtfUxG+h4spOegEODnug1XAvaG2Bl/qZpxrA+Zt8gL2NbGdeMC0SlrLNP6CPzIJ7Eh3L6kgDErB/98Y1YolnasFasJXXcU4/OzC62WA/0x7PEOuM7bdALCdiK75SH3+TFBgmfw0RfYo9NyrnnmSEnGbylr2kSH4md2cRP4DK/FTZPbKJF4mB9mRf39OX54g9JeK5IPEck1oU5oh80iT36WQrvmaOVe74lRh6L+RMLe0bsd9jXZufWhuffIe+jEvJGasWNNDWTRI3muPKN5TrhBafotl98S2OFjIaXZJQdWqpiuaJCKVF2MFZ/tqH/vfc2veWD79UDkjQxoR9+9xJFtC82dcU1N+q9579Juudn+v1N12tZVFVxbG/dePcarZe0buN6/eHhB/XYffdVPFjSinJTN95+m845/y26+4FV0sRa/d15Z+uVpxyjtMOG9frMR96uZjGjoeFIUfMA3XPb7dLEOmlCuuhfP6ax3O5aWV6Sgt75CHkNonYrN5A7VT7dcQC5dmqXnP/oD0/w1mo1lUol8f1dS52Qt/M+hLt23c1/OLst34hxDbgGXAOuAdeAa8A14BpwDbgGXAOugfmmgYUKeQ0aAESAFSGQAEYAOiijjtedAkKAn2zWWl/LKaMtJ9CAHsBJ4gY0AT5ZAuwAegyUdm78AjoYA0jFPgZgBBjKa0wZi2SwBBiCb9igDHBi94AW85M6/LfXNQObgCu0sY1octqRsAFU4sQg0Ihr5kMdfmMLPziVxzV9bR5cA3FoSxvuAUTcE1MgDnFhs9Z8tb6AG0Aa8wIwcW9w2SAdOesCBLdxsQ0kBZjZmOQGa81+mOO3nRTFP+4BU1yzzmYH2/iKL4A1/OeaMmAx7bFLe/rZvLmn3HwEjuEj95w+5traYItYElvAKDasX+gzsTDICzDGZ/4QAU2FJyIN5NKG/maP+bHmjEXsGR8/KDMATRnJdExf84Fr/tCBtWFs9Gb1aIo+wHm0xZyYi+kG37FDvFg/mzvjMm9sdiba045YkNMXYEJ/+lEWJmLAGtDe4se4zJW50xabPGPc27zoY+tIGfHEd9rjk/kBiDRgY78NNpbl1hboTYxsTPoxTzSKvnmmiTuJOp41tE9/s4Vf+E6iDv3ZH0hQRlviwBqQYxdt8nvGuLQ1W+S0ox+/TyTWyOrpRx3zsn7YDxNtmQPPMXPjt8FsEideb07OM0o5if74YuMY5OU+tG3t6EN/IK+tCTn+YQcfLaad/f1+6/XyeMxtPEzz9pvh67Fz68Fzz28Wv3X8t5F9DtVyO8xn+XT5kbebe3C8nZO8QF6+pVtPX9lcT8Y1Eq3UCSefpPtv/qr2LmSU7csoV8irXKurUh9XNr+H+kdX6Cf33aVLv3eZMr3DetKBB2r1/Tfouc95ivpG99SV1/5Suu8XOnKvPtX6Moqro/rdvffqAxdeqIHskIYKOR176hn6/f2rdXBzmVbmRvSbVb/Tlb/+ifKNSC84+SRp4g5d/90vaHgwr6cc+BQ9eM912mtlVj3lffTjW6WTjz9ZI0syKo6M6rorvqv3vvml2ruUUauWTwX8aBffdEC3AV4eev6DjtyuDe4CcIG72WzWIW/RN1Hm2yaK++OadA24BlwDrgHXgGvANeAacA24BuaLBhYy5GXjEMAC3AAsAIrIASzAVgAD+wls0AI1gBxAT/pZss1bNnWBsfQFegEmgLzYwxZ1nNYkUW6bwAY8eN0wINYADmPTB3jDGIwHBCEH9gEpuac/m5/ANaAap+rwE5CEL6Twm7xALNoZRKE/fYkBCfAEIAXY4A9AhxOXQC4DxIyLLpiLQSGLE0CTMvMX+wYx2fC21+oCfPABW8BTfABQARK5Zz/H5ktMiCOxYK6Uh/5jn3HxnTkwf+7xgdjhgyX6cqqTRJmNYwCJtaGfJcahHZDN1pW2JOtPPPEf29hjTPMRO/hjcaLc/DLtYIt4sFYAOCsPc+wayGRtAbTMkbgAxixxjy+sGf3NT+KCnxYH4gh0RGO0Y54kfAOE0pZr2lOP32ifMbGPDzZftGjgj5xyTrOiNYsfdihnjcgpZ8OeOdsY4Xyp5xmizPwg/jyv9KcsTBYbmx/9bC+QGNCWMoO83KMz4KStGfVoEN+pZ442Ps+EjWdzwI9wPNpybyd5mQNl/JEHzzcAnrhTRl/GYt0Zh3L6WlyA6FyTaGug0+5piz/o0tabOtbC/hjBfLOccbGD9mlj/pNTZzrFjs2Vcq6tnmfQAL9pi99GdGFQnLbYICfZOPhKHNGq/RaiV7smJ07UsyaMi7/ECN+op4xDPGbb852DZx6/2YmfPXMOebsTX557fiMd8s49lO02m9wm5G3GkcbiWpq45lXNufoyHXvC83TbLy/XWCWjvt6MCqWC6o1IjWiZ8sUVGio19ZO7f6GnnXKEMr192r1vSN+87nId+rxjlelp6aprfqb3/dmx2mNxRoN9u+uEk0/WPTd9R3uWMxrsyWjp0IiWlvfUFVf/WBe86nTtNZjRzXd+X4edcqQyuw9oYKSsX959g444/qla1FdQodLSLff+RAefdLj2Oe3NuiU9Dcz/e4hzxNKGNfq3fzlfK0cz6Sui+R+4bgdyodkzwGv/QULO//gDdyuVioaGhrYCuw55feNkvmycuB+uRdeAa8A14BpwDbgGXAOuAdeAa2A+amChQ16DEABNIAUAxOASdQaIABVAK2AZ0IZNR1K4SQ6w4tRdCE24tnbk2ANYhP0oZ1PYxuUeWIY9rklALPoCC4EsnAilD3YAsLQFwADtAKmUMzaJ107bScEQaJkPZsf6AL7oY34Bjkj4xziAGV5dC7SyvuSARU6XWszYlMVXYsbmrMWCk5TAHuAQ+zb0tcSJUKAXoAcgB1BjPMa2k6RALcCu+UtM8I97i5ddW86Y+EViDoAjxsQnfLC4AHnpg318ASyRow/iG8JUyunP2MSLOdI3TJRhEyhrvoQ514yPHSAYsWK+oQ1rw7yJCbGgj+nIYkc7Ys5JUvLQBnHhnnHIAZHY4hpbrB11zJuYEyfqsG058wf+ok3iYX3ph3360J6xsc8fI1DHHzlY3ICBaJR7Ymt6snrLaUN8AbXYQEfE2eZq62x5CHnxi8SaMjeSzZ85M0eeEeZjczA7aBrQCJwh3tTz7PC7gB17BvDbEutg18SO13MTI+Jh41puvpEzL8awk8OUsQ7EDphtPtkahPf8BvF7hV5MD/Snrf1Biv12h2MyB+7DOeEHtpkHa2fxMp/JefZYO2zTnsQceVbxgXH5TeCadWLu2KKc55O48rtCPbawQ+La7tEWuiIe1Nkzg7/EFf8sBuGc/Hrr3xyPx9zHA92THPJ2Zy147vk94X9P4Tx2gtdyO8Fr+ULjXQt5PlNCXl7zy7d4x5N6mlpJrKQ1rkItUTGKdNvdN+no4w5SdjCjcn5Q9WpVDepyNeVLo/rpHf+jp590iDKZjHbrH9a/X3OFnnj8icoMP0ZXX3OD/umcQ7XX7hn19CzSsSeeqjt+9l21hjIa7s1ocf+wMrlluuw7P9Arjj5YraUZ3XTHlTrs5Kcrs2hYiwfK+tFdN+jJxx+qzOKclgxW9ZO7fqonnnyM9jjlzfrmbdJIoaLhRRn1LdldQ0szqi/NaGVhN0WlkfRU8kJe1B2dG2DX4C4POv8ByMPPj6k9+PxDGaBryV7RHOadr2fuvLdXNIf5fPwHuPvkG0OuAdeAa8A14BpwDbgGXAOuAdeAa8A10C0NGCjg39kLafM4hFjsHzA/ygAcBjkotzlTTwJUWF+LibUDalkdZQaJsGH3wCBO0Zk9y80GbSkDKIdgFKACoAKqAJxoZ34CeehvNvCBaztdy4lBg3I2nzAHhtGH9vSjPfOkDfAMf6097ZgX0M3K6MepUPwL4TNgFb8BQviKbQNKzI16ys0O9djmxCbAh3JiQTk586Q/wAjAZadjsQUUtNhbTM0u9/hntoGO2CTRBrvk3AOhuAYwEQNOQZPTh7lZGfcGee2Er+1HkQOqWGtgNvW2VviCfYu1zY165ga8Y160CRP1nKS1vtgxSGlx4RQ3cQGIYcPGCu1QRgKw2vzZPAcMW3xYf/pQb23smrYAUtMLtqiz2Nsrm5k/NvAbe6wPdUBcgLhBXOJpMaU+TLZOtAe8Eh/zw+Zk8wkhL22snJy2lhvkZe3QX9gWX1l3ICV/OAFopC9aZ37U0544mR+WswY2Bqex0SjPla2z+UAZfbBHe8YiptQzJutHmdminPbklvCD9eKPAri2ttimDXGiLnwWrS859iyWAG90xO+K/S5N1pb52RwZD195puhv45ptYC82LQa0YV1ZZ9OBrbs9U9yz3tSjc9YcQEac8JX15TeMscMU+urXWzTisZjbWNjvgkPe7q2DQ96Fd4oXFjgp5G1/xzVKIS8neQG9rSQS5aVKVb35sl7zzn/UXeukFxx3uKL+jOJSQWedeqo++f7/q3phiW66/XodfsLByuye0dKBEX3x2u/p8c87UZmBlfr+93+q9736EO3fn1G2dzcNlpbrtnvX6v0f+oT6evu0eGmPjn7BWfrvG3+tZKigcu/u+unt1+uQkw5VZvdBLR2s6Ed33qiDT3iGMouy6h2q6oY7fqoDjz9Smfy++snt0htec7ZGFmfUvzSjT330gzqoWdU+o8OKi0DeRpriOPITvfEWYXcCXvuPKIQyPDy8Gewa4J0s7wS6k92HcNeuu/WPZrfjGzCuAdeAa8A14BpwDbgGXAOuAdeAa8A1MB81sFAhr22C22as3Vtu4IT7TshCWVg/2b2VGZDovLdyy20Mu9/ZnPGmSjaW+TSddlO1wc9t1YXzsPHCsvB6KjszLQ9tcm3jztTOdNqHsZxOe9qEfcLrbfW3eVibzvvp2Onsg63JymyM6dik7XTbmd2dyRmrm+OZLeIwWSzCsvB6JnMwn3e0fzjWTG3Y/EIbj6RrAC+gzP6ohPmHMQivH0nzcl+n/t+nhRAbe+Yd8nZvnfnDJZId6LNTvOR2gtfyHT1I6P228LZdFYs/grxtwMsp3jbktW/ycqqXVKuUNVSsKpMb15EveIW0cY204Q/SxDpde+V3FWWXqlFYpN/c8b865qTD1dvbo5Fey/ujAAAgAElEQVRCSf9x1RU68DnHK9Pf1FXf+6He/afHaN+hjMrZXg0Wx9VX2Ue/uGO91q3n/cobdffqhxQtW6m+3QZVGBzRjbf/RE8/8Rla3DeibCHSz+74lY54/nFa0l9QfjTSL27/uY448VhlltS03xOP1sP33S5N3CmtX6Xz/+I8jQ0NatnwUAqjk6imOGp/Z3hXBfqRMg4POH+9xl/IkezVzEDeMBngDU/wcj0Z1O0sM7Ab5vPxH+Duk28MuQZcA64B14BrwDXgGnANuAZcA64B10C3NLDQIe9UG8rAgxCQbAsmhO1Ce/SxRLldT5Zvr36yPtsqC/2wa/PTNqCtfKrc2k9Vv73yTv9o31nG/fbsbKt+Kh877W5v3M722xozrJtq/LBNN647/eu831V+dGMu89GG6WNbvnXGfFttJ6vb2f6T2VzoZZzS51SvnaRmvoDfhT5vn1/34OBcxJLfY5JD3u6to0FeDvuFgNch764Hs93khVtB3i2AdwvkNbhL3uIEbL2icrms/mJdfYWKCoVhlfIDKhbzKhYLKuWzGh5YqsFsj4byAxocGlRP/4B6R4a1eHBIi3qyGhnKKcouVquwVMXcsArlunqHSuodLGpgaFhD2SH1Z4c1lMtrsH9Qg/396hlcpJ7hpRoYympgKK++4az6s7n0emBwWNncgBb3LFL/YFkDA6PKDw+qmO1VuVhUuVBUXBxVq1xRs15XEjXaKY7T08ndDOgj0Zad4AXqcnqX+3q9LqBtX1/fVnDXQK9DXt/o6NZGh9txLbkGXAOuAdeAa8A14BpwDbgGXAOPBg08miFvuDm8I4DGwJH1De87r8OxuO6sn+59p53w3kCgbUCHdXYd1ll7q5tp3ukz/TvLuJ+p3bD9VD522g3HNT9CO53tw7r5cN3pX+f9fPDxkeyD6WNbc9jZmO9s/235ttDq7BXWzMuecYuf3S+0Oft8ugcE5zqWaJTkkLd7a+qQ95ENc6dij1NAXk7xbklJVE9P8QJ5eX1zVKtotFJRvlxRtphToVzU0MiwcoWCcvlcmrK5EeWLhXZZoaCRfF75QkHZ4WHlR3IpeK2VyyqXSyqOjqpQLKUpX8grm8tqeCSrQrGgfAF7fAN2UIXCSAqSi8VRZbNFFfJl5QtFFQp5jeZHVCoUVC5WNDKc12ihmI5VyBVUGa2oVq6oUa0prjfUShI1NwFewPZUwVnI5YBcS5zetRO8lHHCdmhoSIODg+krmrk3qGt55wleu+88tTvZfXiC164fDf+g9zn6xpVrwDXgGnANuAZcA64B14BrwDXgGnj0auDRCnm3tUlskMHybbWdqzrbZJ6rfGfnvTN+b29sW7dwDPp03m/Pjtd3bwPfY+mx3J4GHPK6RrankflSb/9b4pC3e5oF8nKyHwbkJ3kXDhfcCvICNZOYb+9aap905d5e30weRw3V6nVVajVValWVSdVKkKqq1mqq1uqbU6VSE6laqalWratRq6tRr6ter6W2arWaSJVqZdupUlGlUk1tYa9crabta7WqalVSPU3VSkWkWpXxtqSo0VActb8v/EgGvPZudMtnCqR5kA3u2gneUqn0/9n783DNs6pO8OXpvt0tdJLJYAICEZEjCSR0psK1HUpFr+NVlHLkOl7Hq4DNZGm3Xd1dT6uUQymOlAKCgFZ1KVWAllefUpDB6nKoBjQRxBzIIcbMyCEiI+KcExEZq5/PG/mN3PHL98Q5J+KciBMR64/9rD2uvdba3/17z9nfd//e2a1dBK80vbWL4A2ZG7laEjdkbmQfbFy8Bxu99r32jYHGQGOgMdAYaAw0BhoDjYHGwMWIgSZ51++QcrMcQF+MdoQgiu8rldOvZeO/MXBuMTDuVfl+XfO5XY/eDyvHv0nelWO0FhyJZ9/kvXCI3ZEPfBTJuxWJO0uPOHz8Nc6PEL9RsGXb1pKeuW1rPWPrlhPpmVuMveKktGXLthrT1q3bTrpBG7JyrfKZW7aUtNK4fDMh/eLD+SrjR+Rq/Qi5G2LX65mR6wjdkLuRTfL2wcvFePDSPjfuGwONgcZAY6Ax0BhoDDQGGgONgY3AQJO863tYuZaDze67MbF3YCy2OYhfrtzx35j4d1w7rmvBwEjyZt+uZXz3bbydbQzks6Vv8q4P9nyxwyvcpb7J+wj3uVpebTP3m0Pyzncwv9cbZ0LwhuRF9CZt2YbAPZnkfXT5ZJIXsMaUW6bzpH6xg0R0juXUhQCdJ6f9z7fy1KdT2T8vrh7KxvjH1Q1dN3JD6kbm1cyRub1LzrvBm7rc1j2V3Ih/mFtnH8Q0BhoDjYHGQGOgMdAYaAw0BhoDjYHGwGbFwMVG8uZw9mwfCvd863MYfDpxbJL33MX+dNarx1xc69Uk78W13hfC/s7fEU3ynhl2E0e3eBG8yF68UC5FRq6FbzoVF9Vt8/nVjYzLqkneqRHI3a1XbDuRQvCSSN5t266sbduuOpFWInkfpX+F27nT/iuVLzSQrtafELwhy93glRCyfnN3fC1zyF1yfDXzmA+Reyp5KnI3bZv1n+62qw+EGgONgcZAY6Ax0BhoDDQGGgONgcZAY2AjMHCxkbyrPWAOMaj/mM/4HE5erDJxOF15JnFb65xZv3HOtero/md2mN/x6/gth4EmeRsby2Fjs9bns6RJ3jPDrjgidv0WL5JXGZcWcjdytXzTSjxct59HJC+CdyR21/q65i1bjt/ADXjWuvgZt1q5Vv3nS/+p/+zOTWcSuZtXM5N+dxe5G4J3Hsmbm7uRucE7Ersha09XbsQ/zK2zD2IaA42BxkBjoDHQGGgMNAYaA42BxkBjYLNioEneRw4pp2TDZj1gvtjtsk5jEo/p2q1UzphRz1ryZ7oGa5nrQux7pvHr8Y88t873WMD36AOiZyx3/sJZ6wtlLZvkPTNM5jMNwfvc5z53RvJef/31TfJuPfsk7EZzjad9k3e8xTslfNfjJu9GO36h6A/JG39C7Ibcveaaa2Yf2M94xjNmt3dzK5ccb+4mPyV25xG8yN7TJXczbrP+09129YFQY6Ax0BhoDDQGGgONgcZAY6Ax0BhoDGwEBprkXfmwskmHR8coh7SnK8/ksH9KCq2kK+uXg/mUVxrX7Y9e945Jx2S9MTDdz70/G2PrjbH11pfPkr7Je2ZYRfAid93ilbdOOKXc4I0MzxQZvqnl5ieFm+S9QJj7kLu5tYvc9eGN3EXc5uZuyNx5MgQvOSV3Q86ul9yIf5hbZx/ENAYaA42BxkBjoDHQGGgMNAYaA42BxsBmxUCTvCsfUjbp8OgYnS65m3Hrfeg+6st65SB+ufI4pvOPXuOOScfkbGCgSd7G2dnA2XrOkc+WJnnXjt3Ezi1e5K7f40Xwqscb4YxC7kaG3I1scnfzk7tZo3Ujef1G7yMpv8nrd3mPp5N/k3dbbd0qnT+B2qy2IndD8Lq9e/XVV882qvxqXs0csnckeJvk7UORzXoo0nY1NhsDjYHGQGOgMdAYaAw0BhoDjYHzFQNN8q79kHI9D4vPV10ha09XbqTfy5G6OVxO+0ba0Lp7XzUGVoeBJnlXF6fG0+aJUz5LmuRd+5okdohdJO+NN9544havS4JN8l5YvOTpk7wrErQhcpeTF1YgzwUJHIKXPB1ydzliN7d4Rzn+Hu9qXtd8vv7T3Xb3gVFjoDHQGGgMNAYaA42BxkBjoDHQGGgMbAQGmuRd+yFlH7Z3zBoDjYHGwPpgoEne9Ylj4/HsxTFEZZO8a495YpdXNbvRq84tXlzSlOTN7d1Rngu+q+c8Pc50A0ne0zOoF3LluI03d33zQsrmzM3cU8kpuTve3B2J3THfJG8fcmzEIUfrbFw1BhoDjYHGQGOgMdAYaAw0BhoDFwsGmuRd+yFlH6Z3zBoDjYHGwPpgoEne9Ylj4/HsxTFEZZO8pxdzxK7f4pXE0jPARUFEbpO8K3Nw5xNP2STvijeSN8+CI3JD8NqQ2Zg2JRIWWXsqclfbPIK3Sd4+VLlYDlXaz8Z6Y6Ax0BhoDDQGGgONgcZAY6AxcK4w0CTv6R1S9oF6x60x0BhoDJw5BprkPfMYNg7Pbgyb5F17vLPPxS6vaibd4PXznrglv8HbJO/m4fzWg0xukneTkrw2XBZ4JHdtxtzeJZG7j3/84+uSSy6ZybWQvONN3ZXyfZO3D0LO1UFIz9vYaww0BhoDjYHGQGOgMdAYaAw0Bi4EDDTJu/bDyj5Q75g1BtYXAyFNIqfxRRCsZ5rq7/L6ruda4hnyJ2NgIPmW525dOvbLxz7Pqb7Ju3yM5uFH3PKa5uc///nlRm9u8LrFi+SVxlczz8uHm2q5+QnhJnk3McmbzZbXMYfgRfpefvnlhZh93OMeN7u9i+h97GMf+6ibvPNu7s4jdKck7rT85Cc/udaSLoR/wNuHPkhqDDQGGgONgcZAY6Ax0BhoDDQGGgONgfXCQJO8azuknHdw2XUdw8bA2jAQkiSy47e2+F1I8WqS9+Jd+/MVx3luNcm7PHYTo6wxQjcE74033jh7VTNuaSR3Q/KOsknezU/knops3wCS1w3Us5HO78CfalG05faub1nYpMryrtIjad3cze1dBG9u8M4jdU/ndcxN8vZBxnodZLSexlJjoDHQGGgMNAYaA42BxkBjoDHQGPj0apJ3+UPKHE627Bg1Bs4uBqa3djv+Zzf+ZzPeTfJeuGt7NnF0NucKgdkk7/LYTYwi8zu8bvBaK3wSMvdpT3vajFfCLU1f1ZyLhlOidyX+qts3Dz95BiTvltq6dUycCrl7RW3dejxt2XpFbdm2zunEPJsnkOsJ6hC8vmVhI+bbFm7Sjjd3kbsjwbuev7nbJG8fwvQhTGOgMdAYaAw0BhoDjYHGQGOgMdAYaAysHwaa5F3+kHK9Do2nJAa98+rWa75Rj3kcso51yS9nw3L9M24zyNH2MT+1TVvStG09yusdq/XUR9epYjP6v9p+45jl8qvRNa5J8qeS07mmc6QcHdP+G1XOvCvpj12RK/U/1+2r9Ws97JzOtZ57YD3sax0b/xl5vsUYRqUmeU/GRvZy4kPm9u7znve8CsEbQpd8+tOf3iTvJn2j73rwiqdN8m7buqW2bX3mw0l+a207Qb6eTPA+c9sVtZ5py+z3ah/5zdr1CMRm0RGC16uZEbzs8k0LBO5yt3dzi3ceyTvv1czqpiTuSuXpq5pX+kff66RPlVYa3+3rd5DQsexYNgYaA42BxkBjoDHQGGgMNAYaA42Bc4+Bi4Xkddg47yB5ufp5fU9VNx5qjjrl5xE76sYxU905LFU/6pv2m5bHcdqm82TOtE37q58337y66dwbVY7Noxz9GvNTG7QlxbdRT/qPdfLpSxqffqPMmLHuTPNuO61VR+w1bpqP7WP9PP36rdRn3rh5dZlzXttydcYkXXPNNbMYjHqWsy1jltN7qvrldJ5qzLRtauNyOmNn5KhnuTFjn9Xkozs2nYne6Fhp3pX6rcWG6FrLmJXs6/aTSbiOx/rEA0ali5nkzX6dhymxGV/PjOBVxishdUPsRo6k7/iq5r7Je/5fJD0tkvc4obulrtj6zIeTPJL3EaIXEZv0zG3baj3TcZL3/A/+SCy7Dj9u2pHc/bRP+7TZjd3c3M3tXa9hXivBuxyZOyVxVyr3AcG5PyDoNeg1aAw0BhoDjYHGQGOgMdAYaAw0BhoD5w8GLiaS10HjvAPJ66+//gSpNJ6BpK+6JH3lEVGrJSOi05fm6YyulcaP/fRVJjO3MnvoVTePHFPncNW4pNGG+DjKUxGNsWmU41h580zrUo4No4zd+ox65TNuKse2MZ9+Uz3mSL/RvtiRcZH6jv3Uu5EkiXdipE/mih/BU3TNkxlDGidFb+ae2myu1I3jRx9is3Y2pp96+lOmJ33Tb2pn+pJp45txY1vy+qQtefGST595kl3eFsiOcTwbM29sTXkq6VVHj7z+K6XoyFqmHBlblae61CWefJzal/76Rc8oM8coxzHJk7EvsRzHrDVP1zwM0WNttenDVjJ2zJtHrMf66J63nvSNfcd84qJuzCvHltgROY7v/PoQlx3H1ccxOGyS9+SYiYs9628tv7t7ww03zKR9jch96lOfOksuDobgbVL3wuISR15R/rRJ3iu2jiQvsvcRopfiLds2Nk0dOd/KubEbaRP60PYhj/DNrd3IkeANybuam7vLkbrT+pVI3Wl7HyScPwcJvVa9Vo2BxkBjoDHQGGgMNAYaA42BxkBj4Nxj4GIieZc7xHYwqW1KMEz7a//Kr/zKWb+MmfaZVzYuh8IhLdTN65t+ZMiYca4v+ZIvOTE/XdrUyUvRqT7+pJ+6UVf6IneiF0Ezjk0fUttYPlU+cy8nnTV93ud9Xn3rt37rSfOl/5kSWnwOCRed7J36/8pXvnJ2IH0qX+bFLToTd33GOJ9Kn7aMj4y/kSHbolOcXvSiF83sz5wkXcYkrxxb1EX/1B59gq9Ifafrn/Ehd1/xilfMbq+lPpKOzKuOTdL3fu/3zmwY508/7cZpY+sP/uAPniinjq6MNU5SN8Vi/I/u9D2VjN5xjtSRX/RFX1QvfelLZ3Mup8dYKX5kvP4veclL6sUvfvHMt/SLTL9IsfiyL/uyWczU8U8dPcZ81Vd9VX3TN33TLK8+47TLZ31SJqWv/uqvPoFvetiTPtERqd1z4Au+4AtOYCN4iL6pzFjx/7Zv+7YZoSMvicmYN5a+aayiQ7v+X/7lX37Cb693VbfcvBnb8mSyreOxsfEIHi9WkjfPMTJYy/71LPKM+szP/MyZxCchcpG6IXdD8CJ+m+Rtknf2yuCRRHVj9xGS9xl1xVbpmbVtC7L3+I3esf965AF1PfScLR3sXc5mxK5r8/7QTrJZ1eVmLnJ3JHZTP5Vu845p+nrmKZm7XHlK4q5U7gOCc39A0GvQa9AYaAw0BhoDjYHGQGOgMdAYaAw0Bs4fDFwsJK/zDWTBeCCJcAiJkfrlpANMB7rf/d3ffYKAyAFnDnynMrr0+8Iv/MJ6+ctfXq961atm6Yd/+Ifrta997SzJpz7yhS984ez364wNKYLwoCN6zecgFVE5nZuvIYP0Qd6M6Yu/+Itn5z10IX6++Zu/eUYUmW9MmYsN9DnAlabES/plrLIxyyX2Inm/7/u+r772a792RoghxZJGMgqx/nVf93VrSvSMB/Dmi42RbBU7/qQukn/aldmo36tf/epZkoeDb/iGb6gf+IEfmCUE5fd///fXy172svqhH/qhR+mL3sjEKXMg8OAg62itrZGEbMx81hDZKwXPX/M1XzMjAEeb2cBeGJuHL6Qxv81vjb7jO76jvvM7v3Omc7QteXazDT5f8IIXPAojCEqEonWzntbLGrBBnLKukdaUTvrpZTsCmUwM6LFvlNkY3BkDi2Ti6ewyNtKxUqIzvkXvOEadW2jWGk7HNnk31TJ/9GT++GMPi/1ybxCI7SR/vuu7vqs+53M+54Qf9rq5tFlja2YuZ7bf/u3fXp7d4mI8fBivv2da7H3Na15T7KCDXcrz7NGG3IXfzEmf/pJ1TJ6Ed2Pis3jZC7AR/+nhP53WVizhBzYSu8TAGDbCEF+U+WZffMVXfMWsrC4p41puLJnZ8Z0f3+Bw/Iy5kGM13a+jr2Jh73queA747FIeiV3kbn5/F8HbJO+FTeyOPOc63OQ9TvJeuW1Lbdsif/KN3nGyM8kvR5ieic6NHLtWkvcpT3nKjOAdid3pjd0pwat8KoJ3Lb+9uxKpO23vg4Tz5yCh16rXqjHQGGgMNAYaA42BxkBjoDHQGGgMnHsMXGgkbw5fyfEg8uu//utnBCnyC/GAkAi5M+2bcnTRg7D4/M///BkZJq8uB58/+qM/ehIBggRRZ3z6yJtPQh45BJUQOTkUTR3pwNQ8xiubDxHrtlzsogsx9yM/8iOPmp+PxuuLLEPKjAn5xw563bZEZCFVzBebtSXRg1hC1oyJ/UnInKTYuJxERIknQge59Lmf+7knJW36mB/JieQaE5IQCSXJj23yyKL477WRbGbnGANYWC6JH4JV7OkhQ4AlJggtdosdeyXkKzIrfVaSYi1G9PODPcYg5vkgqUcgI/niGxn/jLWGYkFXvrgAV0hX/qu33vQYa44QhLEBlmCM3uBgigVkH79Hv/RPLJCy1pP80i/90hkuxWeaxI2OzCMvvuzM/MhhMdXne77ne2b71vrxwXqGEI0t9oY1DgZPJc1hnH1Gj/WWgpOpHusy6kNWGht7rYH9KObiLOaS54xnrLoxxeZIevjqCwXy1oYtsRPRaf+lv7XOs1t/yVgkujHGkyHljUuZndGT9UXSZz6+0AdHeSZEZr30QTZHr3oYDDaUzSdm+kanLyl4HmVe482l3RzsRZwZK5bWQTk+Rsb+lo88ozsWZy8WweHFRvJO96196nniWej5Ju+5gcTFKYXQnZK8/Ru8TfKe8tbs8Zu8J9/mvXKbm7xPn93ovXKb27xu3s6/fRsCdDk5j3w9X0jeeT7xJ69lzgczmc2IqJ2SuymPJO68/PTm7lhe7tau+ilpu1K5DwTO/YFAr0GvQWOgMdAYaAw0BhoDjYHGQGOgMdAYOH8xEKJgPLy7EA6LcwhLIhWQBSES+DeSgGNfee0OLROHz/7sz56ReUg2JJibceKGuNIfyZq+kSPR5yAYOYYoQlAlIWWQrQgsZBCSJCSW8eawLpJ5ECDJO1xFpKkbyUjzuymH1Oav8tQ/ZUQ0Ekof5FZuFdMnTyLpggtj4ttyOqfzjP3ZK3bf8i3fUt/4jd84k0hFPrut57W46pPP2Pg7LatHdLExpOZo42gLwlT86WBHbDGXdY6PIee0W2u65ekixWS0wzj+ZLw+yEtrmH5TOdoYe5Bb8trEgT7rgtgLqStObELaenUv4jc+6msMkjNEYHQgyOEL2cZ+Pmbe2Bb76aMDuYbwg2txS4KLfKGARAxGlzgiGMWDtJZ06afO2o/JnOYj7Q9Yh0Pxs158ooPNbEH4ml+MzWkvsTM+nI6EG/qQvPaDfLBkDcfb5Gw1h3NTtomn/uqNEVe++tLCmMReUme/2/v8jD467UPkqOeMOJBs4rdYSGyx/mKlTKcxYxwRLPST1kzsfNmEVM76qaM78YMZ/vJLMkfWhn6Jner4HLyaRz1bPU/559kTYp5+z7FgFl6sqecxHXSN9utnXc2jHc7ZLP3Yj/3YLG708cV6iUFsYEenjsHZwgCMSvbK2ZrzXMyT/R8ZG/IssP/sc88wdbgmN3jz27sheSND7o6vaJ5yVnTMq5vHy3Xd5ieLz+AmL5L3ZKL3iq1IXukz6sqtl9eVWz+9rtiycjreV//lEz3ayauvfHpt2/rMUxLR5xp82STsQPD6QyQbVN4mu/zyy+txj3vc7DZuSN3x9u70pm5IXkTumA+xeypSN20rkbnLtfdBwvl7kNBr12vXGGgMNAYaA42BxkBjoDHQGGgMNAbOPQaQCg7ncpCfM4ILQeYgEnHgMDYETggGPoao0TdJ/ZhHriAkkQ2IRUQcYgR5op/6abzSJq5IGcSOuZBYIXG0pZ910CY5ODWfOraaA2mL3DAGEeO2JKKGrtwW1IbUQ7boY2zs0jYmusyDLAzBYx4Htmx1aMte442ja0yjrml+OqcyexBj/EMKjSnkFtIKEYTAiY5IxJGx441Q6+r3O9VpExP+y4sd+yUEHPKLnXxE0vMdicp3fdlAn/FwIt7Ic2PYrp4O9tBpPGLT+NhItzEwkrpTSf3p14cUX3q9ephuusQD2UxnXl3rNqS6jDHeWHYar8z+kTTnm7gii5Gv2s0f++ST+Ee3ONCZOLIpRKy8/umjvzUV+6xTMGp9xvWWpzM2s4V/SNKQ69rUGxt78kUNNo9fomCHPrF/NVKcMg4ezK9MN1Kan/a4mIeclrcm+ni99TiP+bOXo2debK0dzJg/saPTXHy3Nva+uexrRKa1k7d/SIQxLHquWJ/MR7JDspesgzU3p7y4K+dZE/usk/Uz3j4bca4uKXjLPNaIDvbDmvURK5jlm/5wan59ksQ7ujIvm62pvvTyzfPNcwhxLB4wZ77YM8r40rKJ3rOBgWDvQid5p7Hkt2eOz1TPMH8v2Lv4Jrd1k0LqKicfgpdsknfzk7PrxWGuA8m7tdzcPf67vJ9RV2x9Wl255Yl17Zb/pq7b8l8sm5699b+stabou/Lp/1VdufVpm4rkReSOi2LTKfuD0QeuD04p5C4yF1Hrt3cRvSuRvCFyTyVD5J5KLkfirlTfBwLn/kCg16DXoDHQGGgMNAYaA42BxkBjoDHQGGgMnL8YcODv4M5h+/RA73wv8wtJhNjIoWxIkKlMOxm/kycdbI6Enlu0ytrmkbyZU1wdiCJqxBph4SabRKd+pBubSC31iBYkEtud2ThIRSAhntiGhMntP+0IHeQPogpBhAxx5sNH9o1+pEyfA2okEsJX3xAuyBbjE4d52IieqcyYSO0ZTy9SVkIESYgfZWSQsji4tWe8sZFiLD5uieamZG6IIoDE0W1PefHRJg7iQwf/xAbRZTwSiV1ib17xEHe3ByX1xuXszBivYs4YbfTDwBgrNlhj7Ssl/tGBaOeXcXxUD18Ir6QpyZvYsWfEcuKNEERM8xPuEHDwhMxG6sFL4husxN7U6ysvBUvWAUmnLrEVL3YH22LAH3WIW3l1Y1JnLcxpflhkM+Ig/lhLa5L5kX7aJfbrZ3zWKvavJOlLH3Mri6N9BCPsEF/+q2MnH8VQHb/NmbHsYJN9FL30JU9/kvXMcyTz2t9ioz88jISzeRL76BglG9hj/mBTWR9j4To2q2fjGC9j1JvD3HyHE36HlCVhH56yV+XNyWZzkZ4l1pFO62O/W7Po5Lek3rOMjtjqiynqYZM++w1G6HVLGImsrzJbJb5L8uo7dQzOFgayBy8Wkpe/9pk97znhmSVv/yFxEbfklOSdR/A2yXvxELw4yNMmeR95Zdne6UAAACAASURBVPO2unLbtuOvad761HrN//Bd9Y43/e/1zrf8j/Wut7yq3vNW6ZX1nt96df3+219bv//219QfvOO19YfveHX90W8/kv7snf9TTdP73vk/1fH04/Wnv/fj9ed/8BP1737zlfXC6/6runrrk08iVUeC9WzmQ+6OErHLBnV5LXM2o9u5IXVzU5eUprd4044MXo7cPRWhO69tJTJ3ufY+SDh/DxJ67XrtGgONgcZAY6Ax0BhoDDQGGgONgcbAucfAhU7yIggQBg4okRfIm5BLOah1RpK8Q2L58bBY2WEu4iL1IbaUEYypj0SGmRPhkQNRBAniyk1gUl+ki0NTJIZbcOqRftFDh9uX5kOCsAVpol4fdiGGkSeIYRJ5EhJKH3k2jol9xokNApqN0UcHu8XFQa6YsXNMo655efoRVzkIZgNix3p4LSsfzU+qS0IMIqbYwoZIY8VJnVggg9MuJmKTmJjXjciMVY80zQ1FRB6SnD63J8UTqaUfUlEdu9huDolN8dNcdCPvEVsjXszrhrD2eWm0Wbux/OE/uxGJ6vKKW3ZI/CXjuzJSlc3pgygPySZeiDkEnz1u7eCCf/mCgvmNNyY6YNT8Ery7ARo/kGziIFbyfNEP6Uun/YWkkzeP+eQl9ZJ6iV7jxDg+iKvYw448gpjd4m5e5Kd145Obr7FrHj5HrM7Liw8Skf38EG+xFwfxQE4iZLWLozI/4Fj/rGNIRj6wW718+kSqEzO67LesvXY6YVCdsv1nb8R3MjFJLJTFylj7XqzEiF/min5xzHrxhS4xlzdWkleXW97KsOSLEhJMm0vM6Sc9w8Qpa2BO481lvL2WOMA1bPA7deItFub17OMzW2EEtmFPLOiHebphU94a2S/BTvolfrGp5fxnUMflzOMC49K4By7UuPLTvrXf/J3gc8+zzIXBkLjjjd0xn/bxFm+TvE3yroo8RfJu24rcTdpS12z79Pr1X3xNHdjxx7Xro2+onX/9M7X9L//32vnXP1E7/69/Xrs/+nO1+29/rnZ++Kfqgb/9qXrwpp+oAx/7yTrwsZ+oQ3/3E3XoEz9ZC3//ulr85E/X0j/8TC3d8nO1dOvP1+Ktr6+l236lFm97Qy3e9sZ66Zc+ua7deumq7FyO8M3rlHPjduwXwnasm+b1Sb9RyiN5pRC8NiOSFonr5u48MjdE70jsnu4rmZG7y5G1qe9/8M/9P/i9Br0GjYHGQGOgMdAYaAw0BhoDjYHGQGPg4sHAhU7yIiMQFUgHxIkkn9tyDjAdzubQVt5h5vTAFvkaUgg5iPhAUuiHeJn2R1iMdSFzxNvtyhAUCBD91I0pY9UhVRyyInHYGTIKMYSkRcjQhzRDnvFZH+QXPezVF0HmUFrSV1wQZohVpAnCRx3SJQQQvcY73DU+SQwRMw586UPupI3NyiGQEls2hORD+rAVqRNyUDyROIgkYxwks1/sxFidsj5iYi2RRchO5FXmEVMxUDaWfQimEFBuDSLGzMPvzMUXceMHUglJqU18ox+pFxLclwXoFTP2wAgyEPFLf+ynI+sZHKRsXbVLSETzxGc6Q7DRrcwvhJtx0c++EJ10mAP+2CUWxiqT6owP0UiP+CDQxNPvtbKFbhjhT/aDevYljuxUZz5SPb9DCMZ+PvgCg3p5+NBfLEkJnszFXpikm73wAkfs5Ke1pgtu4FI/6xbMkfwZ8Zk665q+8sYnhiGzsy+1W2dkY3DOT4nd5Lh2bIRRmCKnST0iFjkLY9FFssHziN38CcHJlvgudvZ64kUaJ6VOrLJ39LcW1ktezGBHWb11sL7mN485jRVz+kb72JQU/bFbX+NJ+8p+pMP+sT/4BHNsg7msRdaQf/JiSTf8jnGl136n25cn7FcJ3s3L/8QpNpLsG8udf2QNOxZnHgu4lLJnz+eYjnt93Df8sxftr3z+q8NFjTd2Q+pGInZPRerio0b+a15+ynd1+fwlhk/rJm8W/DjJe8XDRC+S90n1xl98WS3ueFfV9nfU0s2/Uvd+5HW1+z//VO3/5G/Ug7e8te775Jvqno/9St33t79QD/zNz9UDf/Mzte+mn659N/1UHfj462rhkz9Ti//ws3X4FiTvT9fSLf98Jhdu/ul66PZfqodu/9V66Zf8t3Xt1ks2Dclrk4TcRezmw99m8g87UtftXQRvSN6R6A2ZG6I35Xk3eOfdzp1XFzJ3OdkHCRfPQUKvda91Y6Ax0BhoDDQGGgONgcZAY6Ax0Bg49xi4EEleB5E5dEUgII8cVuZcRB7ZglTUNySFeqRDxkY6+ESS6a+PeoQEwkgbQid9IxE6yCBlBBKiCPGErEhKGXkjPyZEoflChNETkhdZym7zs5cNiFnETXwPAaKMzKKPDvarCzlE0sM/epBA+suPKX6RDrb5jySiKzehYYl+NpPq9TcHiaBDJCLy5CWxSx7ZjEjXTq9kHB/1Y48ysgeRhBASIwRS7NeHDgRj4m88wslrZ0N8IdpCPsIIIkpZu/5IPn6Ko3iLPZ/oR1aR2sw9vtY2t1etNz3slfRPSt1UIi7No55ua8FucU6CJWuJLKMv+NDfnGxhJ8w7mBdDZfGJHcrxwdoYq45ucyb29IuluMirtw5sGW1PG/vFFQ4QtWNSxxe2qzcmCf6Qgmxkg4TYC8mLgA5e+ZUYBR/0sCe+si/45FfwOOLT2sTPjNNXgit2mosd1p998ukTGbsQ3HnOjLFJno36Iqrt8/geKcbsgznYpT9fYiD54zmROrddxSl28Cf4kc+tV+shDxfmFjtSWdztdQRv9qB9MMZlGhv4SOzMrd2XNIzThlC2J6Z7CjGrjZ8h/+GBLjGgR/zsH3qznurd3PV8S6yN0Uc58R37GzPWd/7MSc2O4ckxhDHpQiB5p2vLL3vM88Fng88R+w3PFHJ3KnNjN7JJ3vOXlA2/ul5yQ0jehZ3vrtrzu1W7/4+qvX9Q9cCH6uCOv6jDez9R9eBtx9P+W6r2fbKO7P2bWrrnr2r/9vfWA3f+Ud1323vqnpt/t+7+h9+uvf/wW7X/1rfWgU+9uQ596tfr0KfeUAu3/ct66ZddtmlI3tzYza1dH5jq/AONpEXmSiO5OxK8827uNsl77v/57gOQXoPGQGOgMdAYaAw0BhoDjYHGQGOgMdAYWE8MIBYc6jk3mB72XQhlpAjCho/xRx7hkNueyAKHmM5QQjCM8ZBHiiDRECaIRYRLSMzlSN7E1YEpMsWhaW4TKos9gsVBqrYx6Wd8iA22h4BDOinrgwhD5LDPPGxDRsmzmw6EIGJ59E1bknqkX15ZmzmNNY9+kfoiQs2bfuYyB7ty6M0nYyR+IqSQOiSSj0RKIXbUI4r0k9eujKxjA/3xnb68WlieDdLYjiwOMcl2r93V7jXN5qWTbnPRZa7YQFfiRH/Gi0/iAQfqlSX9pbRrQ1iKgTw92pT1S536MYlHyFj1bBbnEN/8ktgi3mzVLzEQfySZOnqsOZySMIpchDeJD2yKLaT4m5ONYi7RlZu7+ofkja/aJWVzw6J9NZJ58mKPCGS79c0Y8yL17StYUA9D+qtHuNqrwQL7+KNfbGevssRmt2LFLQS49pCw5lbOFwDYjcQwP1yz33i+aBNbOmHEcwTZivDNHHTpxz5xDaEce0apX1Lq+SAhWc3pCwx5TbS5clPdnJ5lYoQwRZS6zWp+NtLLRusur56v1lzefOrHLysoq9ePj/RaI3WxK+P0leiPz/qoC4kMU3CZdm3yknHsS1uw5RkaPXyz3saZNylf6vDM1Jakne+ZQ7s9Nh0fPS0fiWnH4sxiEQzm8+5CiCef7CV7yF7yXJT3TMvtXDIEbwjdqVyJ4O2bvBcXAbyBJO87q3b/btWef18P7f1Q1YO3VB3YXUv376n9d++qg/fdV4ceuK+WDtxfRxburaOLu+vowl11bOH2Onbo5jry4E21dP9f1aE9f1YHd/5RHdr5B3X/p363Hrjt9+pbX/ysunrrE8/KTV43dMcUdj11CF2b0IedD0wbEHGLyH3sYx87u8Gbcm7qbhSxO97oXe4Gb+rX8x/V1tUHH42BxkBjoDHQGGgMNAYaA42BxkBjoDHQGDg1BhA7DvcctF8IB5VTH5CfiKWRDJBHAoXk1Qc5GgKCjjEe8pIDXSQQosQY/cRuOZKXPnPl8BQJYnxINqQcXewL+RaJ3EGEZCxd5lFGhsQfNuVglj/Ip4xjs/4OaunVj83GaktZHgHDFvpis7GSMSFj3AJE2BijX5I+bhciFemNTWxxq4+PfOcz8oo9CDs3niXEnbb0ESuEk8NmuvRNvJE+dBiT289s1y4hBxGDbJTUsYOPiHRl9eroTbxISRwzlhQD9pJsYZsDcPbxzVwSMlOdePPFPIll1hrZqD6xjVSH4GKPOnaEUEUgIuLsVYnPIXmd/cV+MeYjXTCCuGYLm5WNYbcYiJ159I2vI8mrPin9SPaFcE07qc3c5mFrkr5J7IGPPHOi15rHRrrgyBq7vRkfxJyd2Xt8NiZzi4M84jNY0F9d/ENi2h/qjFdPh2eB9UOyGgvfSfyBNUmdMn98kYJtfKDHvkAC02fNzTEv6Z80trONDtgVHzrNFbIFJvVPrBC+nlmjH74kwM7EBWnNTuMyJ0zBgP0cbEbqK+ajXRkXKQby8VFef/YiosVGm36wYj7JHlcWX1KyX2Iryd+QvNFLNyx4jXjWIHp84SG+0WUe8fHsjA+jntS1nI/Njsvq4wJX0vlA8q5mD+hjD/q8yGeEfYyQDYmLW0p+Klcidue9kvlUdeG5Wp7/hPDGkby7f69q57+q2v2vq+5+d9Xe99ax+z9SRx/4VNXivlo68EDt3b2j7rr9ltq1/bbau+eO2rvnU7X/3jtr6cGdtbj/zjq2sL1qaXvV4h1Vi3fW4QeN3VW1dG/de8+u+sQnPlHvfve7681vfvPsQwtoA8oxr24K6PRbTobE1S6ffvQo+5AOuUsq+4c2t3ZD6CJeV0Py+s3e5dJI3q42HzJ3Odn/fJ/6n++OT8enMdAYaAw0BhoDjYHGQGOgMdAYaAw0BtYTAyFcHNJfSIe8yA/+kCHlHFo6KwmB4sacPghbBAKiJTFw2Jl8DnSVEQjIBIRGCAqkQ/pEeh20vDnZoK9xId3cVDS/NoeqCA557cgWxBM7JWO1ZR7+KGtDTIXsRDqpQwzxx01fY5F7xsgjYcyNDMkNTX4h3+hHDCnTE//lJfqQlebRxr+xnzpEozgmDubUZyzLm98tWjGhzzj6Q9ZlHMlX5JC8sUgfSdy0SeKXNUP+hBQT/9iKyPMqWXPQw64QgvpJCFA2yWuX5HMjkg3Jiz2izTpKudFId9YqvitLUxJtjDF91s16wSQ72Is8leT1MX/Wlj0S39Vrj18hILSLD8k2PuqbGOjPDusQu5XFiV54sT4S+7TRNfaRZx+bEW7IVMlYKXXW3TNH/yR2ZI3VIUvZaA/w21zIczFGHtJhTeDcWGP4IG7wmdvasVG7fhIfkMjq6FCnnyRv3/I5uIrUTi//9DOfNnok+8v6j7jRJyn9IqOD3uBR/HyZgI38EGv9xCJ4zj5A8pqPDZkDQSo+7HczOKSzdvPqy36Sneroz/z2rZirVzfaqp9y1j9to/Qc8nzhk3pn0taaTeblA/xrTx+Sbsm6IqqjM3bzE/mtj7pIY5Vzsz+xhzVYjt7Rl+hu+cj+61isPRbBVp6x5zqGsSdyao96dfZL9j5pb9hHPk88Fzxr9EHajjd2Q/BGninJGz6r5flP4q60hhtI8npd829X7X5b1d3I3t+ro7v/qPbd8YHav+tjdc/OW2vfA3trafFALS48WPfes7se3HdvLR7cV4sH7q+9u++qfffuqgfv21EP7L2rHnxg96zt8MJiLR1arMWFhVoY0p/92Z+dRMSOpK4gjGX5lQITkneUeTWzjSnZpPQgUqe/uRuSF+nr9ctrvb07Er6rJXbHfsuRu6lfz39UW1cffDQGGgONgcZAY6Ax0BhoDDQGGgONgcZAY+DUGLhQSd4ccjrARMQhJxBGiEGkE5IWGeJA0+GmW3T6kCPxoN1Zi0NStwQREcglpCgSxTyIMUTGmEYyiA7j9TOXPDIVkWcu+pA6mcs8CBF96dfHWY/xyl7fS+rP3hzgksgfc+fw2VjEn7HmYD/9+mqjBxkXElAMENkhuswh6StmIcgQUshohKrxSEO6kVDmRyDnENkc8vS4+WoOh8pIOTFjC3Ioc4uH/sZJ4kCnOnkELx+yfmzjHz365CavseaMHuQPu/WL/xlnTv0ccvMhfmc83xCA7NVuHvOTdLFLXoI3ZJ2xiTHdXrGbm5Wj/uRzkzfxYRuyznqIs7W19ghFsTMX/eYXV/0RhGJrLn3iOx1sRMRJIdNiP90wAHfmp5ddiZWx0ZU5+a9OH4RebpKKYcaN0jgYcss39dFpLrFVpoddiF3Y1de+DVZgTYwzlmRf8Kk/HUjL4NN68E+MrCMbzGGs/tFhbePXqF8+hKX+Y2z0FzMyazlPTvWJB9xZO/Oy0f7iizb+0hOSV976ml8/pLe8xB820CNmIdK1Zb2MN4dYysd/ef3Eiy2xc1zz1Imf/lLq5PkOl7BHP32ekbHX/mWTfavO84n+zK2/PWbd5KObRPLCAj8yLymZz7M0+zd+0BO/R12dXzuh2TF7dMzgTMrn7LmOUeyJnNqjflpnf9irni/2j/2Ib0LkusEbkjdyJHanN3fHsrHTtFb+ayV+rNvPH3J4g0jedx3/Pd7d76ja/fbjac87qu753aq7/7Bq33+uWrq77r57Z9155221Z8+O2rfv/jp44ME6+OD+2n+//IFaWDhYC4f21YH9e+u+e3bU4oEHaunggTp8aKGWDi2cRPS+//3vfxRxG2ADZPKRK4F0JHeTH1/N7B8P/8COZO5afmv3VL+7OxK88iN5u9p8yNzlZP/zfep/vjs+HZ/GQGOgMdAYaAw0BhoDjYHGQGOgMdAYWE8MXOgkr8NN5yYOMd3kRCSM5EhILgeg6pEkCBPlHIw6CEUgGRuiQVvIEuSR8piQIXQgItSTdGc8whEZo4/DVbqd6WhHYiKn5GOHfAiWkC8kcgWhgbhjB1Iw46Ib6YmIFQNzZLzDXYQLMia2GxuyL/aLUW6WhkjiC5JbTBFOCEq20I1QHG8R0omIQVrlRh6d7OGTuc0luUmon/4IHP2M97pW9fqPCWHHFq+DRSRp05ddYp7ELn7qm6SvMRI9IXGNzziSXSHH2CIlXtqSJ7XBCjLXWGVxEWtxzdhRf/LWwjz685ud0U9K2sQGiR79vrSQLxzoAwt0iTUyFM4keRhXjywWa3GBN/3ZTz+JSGWvGIktWxKrxA+m9I2NCHRjUtaWlDp2Zn+pS+ILbCkjjGED4ez2LLLa/sizis362n/iZAz/2KofnLAx+ITHEZ8IbVhInLMmbDVWf/EZk33lFqp2tnqmmNcYutjKFmX1WdOpzJjExdzxIW2R/NFPLDwv1PuiBv/ZZi2Nta7ikecHexCu1pV+/UlJHPR3+xXhSmfmt49D8rLbOpD6SPYjvfEp9crmgDukV/Y6fcGT9cgbAHyhwzrpF/38VOdZFr2RSF52sV9dYixvPHzAL/tgxFxZi4yJrpaP7LmOxenHIvv3fCJ57QX71J6UPD8lvnh2hMQNqUumbpQhdKdE7nLlcF6jXIn/6vbzh8Rdaa02kOT91w8TvO+o2vW2qt1vqdr9W1W7/nXVfe+vOnJ3HT56eJaWjizVrp27avfO7fXA/btq4dB9dfDQgTq0sFj79++r++67u/bdd3c9sHdXHT70YB0+dKCWDh06ieT9wAc+cNJrlaeOjwCXn7aP5ZC65Hh71weXD151yNcQtcjdpJC+827ujuStsWN5zE+J3OWI2lPVr+c/oq2rDzYaA42BxkBjoDHQGGgMNAYaA42BxkBjoDFwZhgIcZLD9gvh4DcHsPNkCA1tIQJC2DgERX4kBvrII0aQKimLlUNRbfLj64kzZ9qjSz8EkXZ5JCS92tUhBh3A6oOwQdA460m7PiNJqBwiDsGUm7P6Z27z8JFfpPrMrx+SDhmpbpxHv5DCdEzblcdE/9hHGSmlzviQSurpDvETf7MmbJA3xg1l5FZ0hISkQ9I3/pHqMhaJ5+af+jFljLqsuTop9iOMEGmpj8ycKeufMdbJYb/1QYJZF77FLgQk4kkcxnHRRbIdmSUfci12JF6IfyQwMkydvuYIoayceeWRgNYBmYYIJvWFVwRcXmlLB79JyVgp/smnPvrJsY++8Mz/+DhKuBYftiPjMkck/drgg26kKn/5aT3FN/qMEcvcuo/dpD6jTroyTozlraW4kMGNMdrYgOSdJvFijzUxT/BgjFvTZOYd5Whb8trHfMYmptn3YimvPq/59pywfvZDbr2KA+KUHkl/64nED+FLl4SIRX6rt176s4VN9GYeOtSLP9wYI5kr/Uc/YT57zhcagk9xMoe4eUZZX+PVpw896TOP5EVGe/6O8zkbT5k+n2N8YgNdmVd+TBnT8vQJzo7dcbzC1WYledk2rpNy9pzPVeQu6ZmIwEXoPuUpTznp9u5I7MqH3CWXI3TVT7mulfiukfvq/IVD7mYtN57kRfDuelsd2/Wb9dCut9aR3f+6jtz/wTr20L46dKTq0ENVSw9VHT1yrI4dOVC33/5/1sLirbVw6P46dHCxFhcP19LiYu3acWfde8+O2v/Azjq8+EAtLR6sw0tLJ17ZjOSNUyFpUz6VnG4IfTM+JK+N6MPRBkLOPvaxjz1B6obcXekW70jiyo8k75TUVdZnXv2piN2xrf/5PrN/vjt+Hb/GQGOgMdAYaAw0BhoDjYHGQGOgMdAYWE8MXIgkbw43pwedqV+LXEnHPMJjnv7l+qlfaY55+k5nzKhnOXvGPvKr7Zdxo13ypxo/9s349ZTmTlpPvaOuU/mnbbU+TvVMy1M9KZNJ7BrzsTN1o0xbxozl1I395ad90i+SzbE7Y+eNUZe+kcv128z1K8VkJdsTq8Rjuf7ImeXa1qN+ugajXWeqf7kY0TttGzEz2jCtTxs51THam3Gn6jP273wTv6vFQLC1WUje0e7gPTaSniEhd325wpc4Vrqx2yTvhUe4noqL3Ki2jSN59ww3efd4ZfNb66Hdb6vF3f+qtt/xH2r7YtWnjlVtr6q9x6oWjlYdXry/du36j/Xg/o/WwqF7auHgoVpYQOQu1s7td9W99+yse/feUQuH9taBAw/UwYMHa3EREbxYU5L3dAMWYhepi9yVfOsQKet2bkjdSy655MSrmpe7vTsldkPaLlef9qkcydvV5tfzH9HW1QcbjYHGQGOgMdAYaAw0BhoDjYHGQGOgMdAYODMMXMgk73jwuVH5EA4r6V9tv5X0nO32M7X7TMefib/mTjoTPac71tw5cF9JxzRO0/JK46ft8Xs5OfZfbq5x7Nh/uXz6ax/9HvPLje365Qm2jY7fcuu/HmuyHraPuJratB76pzq7vDwWOzbHYwN30mYleWMfMjfkrtv9yF4c00jwrvRa5vEGb/J9k7cJ4NVynBtC8h7a+a4qJC9yd/aq5pNJ3j/7y39XX/8Lf1L/33+3VG+8uer/Oly1e6lqYWlf3bf3w3XvPX9dCwu769ChfXXIa5sPHZyRvHt27aid22+r//zXf14HD+6fkbwhes+U5A256/UceaWF/FOf+tQZmTsleac3d1d6PfP0Zu5I9E5J3Wl5tcTu2K//+T6zf747fh2/xkBjoDHQGGgMNAYaA42BxkBjoDHQGFhPDDTJe2YH2qslSFbbb7Mdop+p3Wc6/kziYe6kM9FzumPX4vu077S8Vhvi91TO03Omc0Vn5lJu8u3MniuJ6dmQ67X+G2XriKuNmqP1nj943QxrFRJ1M5K8iFz2kW7tInlJlwVD6F5++eUnEb3jrd3TJXKnb6Udy6slBLvfhUcebxjJe2wkeWdE7yM3ed/1gX9bL/znf1Fbf3ZfPed12+sbf+P2+thi1YNu9d79iXpgz0dq6dCuOnTovhNE7y0331w7t2+v7XfdXh+76aP195/4+AmSd2FhoT74wQ+e9LrmtYLVBpRyg9dmRLa6sYvQjcxN3nmk7vgK5pHETX5K3o7lkaCV1zatU17tP5geIqdKq9XT/fpQozHQGGgMNAYaA42BxkBjoDHQGGgMNAYaA2eOgSZ5+3B7Mxyatw1rw2FIhqlcrzjSO+qalse2eflp/2l53piuWxsGzud4wUMwEXk++9O2XzzYtdbB72YgeWNLMIjczW/uusmrjE9yYTAkLyJ3JHbHfJO8Fx7RulY+cj37n1WS9+iu35q9rvldH3pP3fDTH6lP/7mH6uk/u1TP+am76nUfqrqjqj71qZurFnfWzjtuqqNLD9TCoQfqwIP76rZbb60777yr/v4Tf1+33HJL/cVf/MWM5D10yCudVyZ5x281JC+QiF3fVHJr16uZXYNHpobMDcE7vpI5eaTuNIXQnSdHUnfMzyNzl6vLP9bLtac+/Vqe+T/iHcOOYWOgMdAYaAw0BhoDjYHGQGOgMdAYaAycKQaa5L24DqdzEHy+y9zuO1dys8VvHlE2xuZs2Jv5zsZcPcf5+9yah9Vez/N3PS/GtQuxei5I3jxnydgRidDNK5qtCz7pKU95yrKE7pTcPdVrmMe2cFirletJGrau84uE3mCS923HX9e867eqdr+lHtr11lrc+Tv1rg/9QX3mv/hEPfFnq574Ewu15Z/trG9+69666VjVJ2/bVffd9cnau/PmOrBvVy0cuL8WDj04I3j37r2v9u69t/bt21d//dd/XSF4yVPd5PUq5nnAROrmAw/Z6x825CzidiR55UPsjjIE7zxCV91I5M7Lh5Bdi8w/lSuNSb+WfRDRGGgMNAYaA42BxkBjoDHQGGgMNAYaA42Bc4+BJnn7cP1iPKS/0HzOOeJm8Wtqz7S8WexsO/r5Y9BY3QAAIABJREFU1xhoDKwVA55n0rkgeUdbQ+p6HfMNN9wwu8GL5MUn4ZyQuLm9OxK60/xqbu82yXt+kavzOMdzUbdhJO/x3+RF8v5W1a63Vu3+zRnJu7Tzd+o9H/qDuuF1H6un/kzVtp/cV9f9b7fV17xhZ32kqh44VvXAvXfXP3z8I3XnbZ+oxYP7anHhYO3YvqPuv//+uv/+vbW4eLA+8pEP19LS0uwW76lIXgRvko0n5Xd3kbzabLDHPvax9bjHPe4EuTuSufIhdEc5j9ydR+YuVxeidt4/29rm1Xfduf/HvNeg16Ax0BhoDDQGGgONgcZAY6Ax0BhoDDQG1oqBJnn7gHs8NO5842E1GAjJsVzfkdRdqe9yOrq+sdgYaAxsRgzkmXYuSN7MjeBF7no1cxJuCYHr1czSmZC8q72lu5p+54Jc7Dk3Byl9GiSvW7HH07at22rb1ivqilnaWtdse1K96fUvr4Wd76oZybv7bVU73lK18zerdr25ju16Sx3e+dv1ng/8ft3wkzfV0163VD+7veqGf/rRevGv7ay/PFZ1z7GqY8eO1ZGlA3XfPTtqaeFALS4cqk/ddnvdfffdtffePbW4eKA++jcfeZjkPVSHDh2sD35o/m/yInFD7obgtRFdtffNCEQtEje3dXODt0ne/od9rf+wd//GTGOgMdAYaAw0BhoDjYHGQGOgMdAYaAwsh4EmefsQfTMeordNmxuXIRqWWyftaVupb/q13Nxr3uvT69MYOI6BPNPOFsmLLxJ78+b2buTznve82U99IjVza5cc88vd3J13g7dJ281Bjl4oJPUaSd4QvFfUtm1X1hXbrqortl09kwjfa7Y9ud70+lfU4o53V+35V1W73lK14zerdry5aucbq3b9Zh3e+Y56zwfeXZ/10x+rp/3k/fWb91Z93j/9QL3kl++ov6mqe49VHT16uB46slB7dm+vpcVDtbi4WLfe+qm6++576u67kbwL9dGPfnRWv7CA5D1QH/zQB2rr1i2ztO2K4yDJDd7c3A3JS4bMjZySutNybvDOu727mlcz5zZvbu+ey5u649yjPWP9cv+Urqb+8ssv71vIn94HG6vBSvdpnDQGGgONgcZAY6Ax0BhoDDQGGgMXCwaa5O2D+z64bww0BhoDjYHGQGNgZQyE4EWyvuAFLzjxk5sbGTskrze/msPtXcSu1zMrI2VD6kauROoid8fXL0/zKxG9FwoB2X5sPKF9GiTvFbV1K5L3qofT1bVt29Wz271Xb/v0R0je3SF531y1/Y1VO369aseb6sjOt9e//8A76wX/7IN17et21Nt3V33Oa99T//gXbzuJ5D16dKn27N4xI3QXF5fqtttur107d89e2Yz0PU7yLtTCwsFZ+uCH3l9btz5zlkaSN8Tu1VdfPdukiMwQu6NcjtQ9Fbkb4nYtciRVN8M/sqM9TfL24cpmwGTb0DhsDDQGGgONgcZAY6Ax0BhoDDQGLkQMNMm78qHuRh7etu6Of2OgMdAYaAw0Bs4PDJwrknf83V2vZ3Z5MLd181rm1ZK8U1J3Wm6Sd+PJz4uFYN4QknfJTd5dv3P8Bi+Cd/tv1LHbf7lqxxvryPa31Z77Plav+d2b6//5zz5S79xT9Y/+yR/W173+ltlv8u49VnXk6EOz27y7d+88QfK6ybt37321Z4+bvPNJ3m1XuMn7zELy+taFh4FvYFhM70dH2I7E7pi/2EjeKbkbgjfvkfdNlTHlmylu6bq5nPH+8c7Y8Z/weXVje+f70KYx0BhoDDQGGgONgcZAY6Ax0BhoDDQGLiYMNMl7fhwsNwHQ69QYaAw0BhoDjYFzi4GNInnzSmbrmzlyazdcyHOf+9wZt/SUpzzlUbd3Q/COxG94k7yWOXJK6k7LTfI2ybteJPRZInl/vWqXm7y/UYfvemvt2PGX9d49VS/6X/9j/f7uqi/8kT+slzxM8vpN3sNHj9WRo0dqSvLu3r2n9u69d1Uk79VXX3XiKj1S8nGPe9yJ392dErrTcm7vRs57RfNabu+OfUOOnmsSlE2jLcoIXuS4B9v0g8xDTp2HFKJ3OtY/5uNrms+1fxfTQUH72gdjjYHGQGOgMdAYaAw0BhoDjYHGQGNg82OgSd5ze2A8Pefocq9HY6Ax0BhoDDQGNicGQsCu9+uaQ/KSdEt4D69lvvHGG0/wH9NbuyO5uxqCd6VXNSN8m+RtknfdSN7lwDR/Ar/Je/x1zcfllbV161W1deuVtWXL1rpq65Prjb/w8lrY/q6qne945Cbvjt+o2vGGEyTvn/7JW+v/f1vVy3/73vr97VUv+pE/rH/8+lvqw1V1N5L3Ibd5j9SuXcdf17ywsFC33HJbjSTvTTfdVH6PN69r/vM//0BdeeXWuvbaq+vZz0ZGPr182wKBi+AlQ9qSayV2R6J2NfmRBJ2XP1v/gE/nzrzqQ/Sqy4MzH2wedKdKxoTUpWfUO51zXjn9W27+g4heo16jxkBjoDHQGGgMNAYaA42BxkBjoDFw5hhokndzHiTnHKRlr09joDHQGGgMNAY2BwbCVawnyTtyHS65ubFLP4nozQ3cyNzQXY7gTb/IvqnbpO18TnXj4/KYMyN5Eb6I3inJ+++Ok7wPv6rZDd4Zybv912vpzrfUf/iTt9cr3vTh+p0dVX90d9WLXvPv6yU/f/OM5J3d5H3o+E3ekeS9+eZbZr/Je889e2c3eW+++R9mr3I+dOhASX/+5x+sq6++sryy+elPf1o9/vGXnCBy55G6FwvJO/4j7kayWJDq5T2EPNTy4Ixc6QPNGL93nFu9IYxD+CJ2x7k7f+YHAh3DjmFjoDHQGGgMNAYaA42BxkBjoDHQGDh/MdAk7+Y4OF7pvKPbe50aA42BxkBjoDFwbjEQjmIjSF6krpu7+A3p6quvnnEkIXWnsknejScpzxU5eqHMuyzJi/x9tJPjTV75R8rHb/I+qd74Cy+rhe3/tmrH22a/xVvbf71q+788ieT9wz/9N/Xf/9if1q/uqHr3nqovfs0f1D/+Fzc/8pu8Dx2tI0cPn3ST95N//w+1Y8eu2W/yHjp0sPbee3ctLh6cEbzK73//++ppn/GUesITL61LLnFz9/EnSF6/vbsSqYvwTFqP1zPPu7061p2Nf8ynRGsIXq9lRu76sMqDbPzg8hAdy2M+D9hI34DZtm3b7FXPCF6xyw3fs+Fjz3H+HnD02vXaNQYaA42BxkBjoDHQGGgMNAYaAxcTBprkPbcHxuPZRud7LRoDjYHGQGOgMbB5MRDu4UxJ3ughc2sXHyJv/fFfy/327pTsHcu5vTvKvsnbZPCj+dSzE5MVSV4EHuOOyxC7j5aPkLw/VAvb31m147fqBMG73auaf62O3fUva+nOt9YfvO9d9dx/8n/WF7216u13V73gVe+vF/+LO2ck771VdWQOyfuJT3yytm/fWbt3766DBx+sgwf31eGlQydI3ve970/rssseX5/2af/1jOBFaI7EbgjcUc4jc+fVIS/XmkZCd17+bPwjOyV5+Ybgveqqq2YPMg+3eR9my9VP+6afb7/QSbc4heSdzn82fO45+pCoMdAYaAw0BhoDjYHGQGOgMdAYaAw0BjYjBprk3byHydPzji73WjUGGgONgcZAY+DcYQDvIK2W5E3/cc0yfiR3n//8558gd3EZiNvc1FVOntQ2krinyk8J3v7N3bNDbp4rUnWzzfuYgDOgnb6++RGCNwsTgvfksnFXbXWT9wdrYfvv1bHtv1l11xuq7vq1qu3Sr8xu9CJ53/Ped9dz/scP1yU/dqSu/cmqLa++s/5f/+Le+mhV7Z2RvMdf17x7987ZK5kXF5fq4x//+7rrrh0nSN79++6tI0sH69CBB8tN3ve+70/r8ZddUpc+4dJ6/KWX1qVPuKwuHW7nhtydR+JO6+YRuvOI2lPVne1/KKe2+AaKOr6xRR4R6/3y48PuTPMeltHhIelmr7mlzGvusx2Pnq8PdRoDjYHGQGOgMdAYaAw0BhoDjYHGQGNgM2GgSd5zd1icc4uWvQaNgcZAY6Ax0Bg4PzAQ4vazPuuzZvxDypHz1jFcBY5C3q3dG2+88QQn4tXMCNiRzJ2XD1cW7mwqV0PqbjYisO0Jn3nhycdcc801JdkUQI6sBeL5r2tePgDHSd4nPkzy/m4d2/7m4wTvXb9addevVN31SzOSd/GOt9Tv/+m76nn/5D/Vf/vaxbr0R6ue8Mr76wt/Zu/sN3nvq6rFpSN15OiROjXJe08dWTpQCwelQzOS95LLLqnHP+GyuuSyS2cS0RtyN3JK6M4rXwgkb3xAtlpPDzQEr2+ueMjNewimLg/DlFcjjcmPlJMeGm70inuTvH2wspkOVtqWxmNjoDHQGGgMNAYaA42BxkBjoDFwLjDQJO/5cai8mjOQ7tNr2RhoDDQGGgONgY3FAL5BWg3Jm74k/gMX4kKa395V5/IbYhZZiyuZR+yOdU3yLs8DNlm8+WLzGICX8mPTCECgz2uaLRoCN+mRRfSbvY+kR0je/18tbP83dWz7m6q2h+D95RnJ+9Cdv1YP7XhH/dGf/Jv6R//kj+vyH76rLn31Ql328j31Nb94X/3tQ1X7kLyHF2e/yTuSvH/3d5+oO++86+GbvPtr/76768jS/oHkfW+F5EX0XvbEJ8xu866F3A3hG4J0lIjKtaSN/odxSpxObWO7h5EPG6Srh5sH2kZ/+IRAzgMVLthyqnhMfTlV327rw5jGQGOgMdAYaAw0BhoDjYHGQGOgMdAYOB8x0CTvxh4Gb/R5R+vv9WsMNAYaA42BxsDZwwB+QZqSvNZgynOkbwhel91wXi43InYRuC7DkSF5yXkpt3bn3dY9VV34s8hHeLTNRwq2bRfWmjzGBgB+CRmYbzhceeWVM6IXKIH30eBE8D7z4XScBL5qq5u8P1ALO0LyusGL4H2E5D26/e21e+df13+4reoHfnupPuuf3l7XvOyv6n9590LdfLhq576qpVWQvAceDMl7sBYOLtR737c2knckcFeTn5KoK5U3+h9O8+e3b801tccDLGvqwTeSr9OH4HIfTnk4zpPLjRnrjQvBzNZpSozYnnzLPqxpDDQGGgONgcZAY6Ax0BhoDDQGGgONgQsRA03ynr2D4fFsovMd9/XAQM7SItdDZ+tobJ4uBoLDyNPV0+Mag5sZA/AtrYbk5QdeC7kbPgKRidTNb++O5K76kLnLySmhG35stbKJ1AuLSN3M6/mYcSOPHww2hQ3hFc5u9YbojTNbtiB+n/FwOk4CjyTvQ3e9serOX66685eOpzteX8fuekMdvuttdfj+v6y9i1V7quq2w1V/8omH6k4E78Gq3fceqMWFhTp69HDt2rVj9pu8CwsL9bGP/V3dccedtWvnrjp4cH8heY8eebCWDh2qxUOL9b4/e189/gmXzm7wusX7hCc9cZY/1e3c1ZC76TMlUc/1P5wjySvPThI572GWh+C4vsmH8CWXSyMWMm45GX1pj07l5H1zBo5C9IqfvIcru891PHv+PkRqDDQGGgONgcZAY6Ax0BhoDDQGGgONgY3EQJO8fZiec5PzReZMZ5Tni+3rYefU77Wcla3H/K2jnxnBwIhFefXricd5+p3jZv6WjcVzgYHwGyF5RxuCWRfdvKFWCsGLHwmhi8xNyq1d5eQjEb1N6jYpG+7zfJNzSV4bCMGbbz24EfrobyisneT1umY3eWvff6z77r2rdtyzv/Yfeqj2Lxyr/UtVC0erDh5arKOHD6+C5L3noiZ5kddIUq+jlvcg8nBDpuYBuNKHfR6G8+T40Fwpb/zYJ/rGOrawTR0s+ceZ7XzYyH+iW3cf0jQGGgONgcZAY6Ax0BhoDDQGGgONgcbAZsBAk7x9SD6ek5xv+Zz1jPJ886Ht7T3YGDg1BrK/xQl51vE6dbw6Phsbn3AcU5JXfbgr8sYbb5yRvNbDlxNC6o4yZG7kvNu7TfI2yXu+kbux9ySSNw+mbCDkLmIuSb2N8oxnPL3m3eS9+oonnXhd84mbvHf84ombvEje2vU7VYf+svY/sLP23n+w7r13f913/4O178BCHVo8UocOHayjhxfr6NGlk27y3nTTx+r2T91x4ibvwQP31tHDB2Y3eZcWly66m7zeIR+SNOtjvazRuI7JbwbJtrxCms0etLnZ22RvH7pshkOXtqFx2BhoDDQGGgONgcZAY6Ax0BhoDGwUBprkXd1h8HiusRnOMi5mG3KO4yxHHEIARW6G2JwNvIxz8H0z+H2+2jDGcrU+nGrMqdpWq/986rfR/mZvT3G+0fOeT2uwGlsTLzL51YzrPif/nZD4heQNLhG74UNC9iJovZYZeYvI9bdcCN3IKbG7VlI3hFrLJoM3GwZOSfJmI5E2jD/qjqdnDySvG73HX9d89RVPrl9//cvq0I7fq+Mk7y9VIXnveH3Vna+vh+56Q9We/6Nq8T/X0cP31eKRY3XgwYO1fx+i94G69757a+89e2pp8eCM5N29e1ctLi6W1zWfIHl3eV3zg3XgwH11ZOlALRw8WCF5L72IXteMFPXg90DLh4VvWG32b1nFPnjKa6WRvRv1T3Tr7QOaxkBjoDHQGGgMNAYaA42BxkBjoDHQGNgMGGiS9+TD2+UOs3PGsVz76dTnYPh0xl7oY8azv3mx93Nuzp7EYSSANktMY/OZ2BMd41pP4zL1/UzmG+c5F/l5/q7Gjnk+z6uLrnltpzP3qcacqi12XCiSr0nr5dM0fs79X/SiF832+9g25leaey19V9J1vrYnBmTy56sv59LuxG8kedXhFLye2WcTsi0XyUgX45C68iF3I5vkbXJ2s5Gz62XPY3zgzvvQnW7gELw2j430nOdcV1dddcXDv9W7tbZu2VJXXXF5/eLPvbzuveOddeTOX6+662GC965frmN3vr4O3/Fr9dCe36068tF66Mi9tXTkSB05emT2aubFxYV68MD+2r//gVpYQPIerj17ds8IXiTv3/7t39Ytt9xSd9xxRz344P66//69tbh4cHbzFxH8/ve/f/ba4ic+6YklPcnv1Mo/cX7yO7Bnkjb6H8SpbUjd/L6wb5lM1+d8K48fcPDnt5/F1HptdGxbfx/wNAYaA42BxkBjoDHQGGgMNAYaA42BxsDZxsBmJXmnZ0LT8mrPG4zLgezLX/7y+qIv+qLZF9FTF/m1X/u1JdGrLjdyMq+yfL4k7gzqla98Zb3gBS84QTQ6ozI+Y0jpK77iK+obv/Eby4GwPvSn35d/+ZfXD//wD5+YN2Pi33ju5fA4dsm/4hWvqJCd6qVRf3TEx9in7BztpS99aX3xF3/xbFxscg4S2/gae0Zpnhe+8IWz9Dmf8zknpFh89md/9iwmcGWMOb/sy75sFoPMT2++YM/+b/iGb6iv+qqvmtWNPsTuSOO0W0OxN7c5rJsYa0vf+B6Z+sgf/MEfnPkev9gm7/WabM+4UUa/GPHz+77v+2YH+sYkWRf5+EonH9WPSZ14ZRw5tic+mZ/dL3nJS2Zxkv+hH/qhma/060NmvZT1yViS7WN5mjc+sYnO17zmNbM1YdtnfuZnnvBDOXPRu5x/xsSnqX8h6NkRWyPpk//2b//2+vzP//xZ3m9Zxq7Rdv3Y8t3f/d31eZ/3eSdioe+3fuu3zjBu78E6ffbbcnrsT88I7fz6wi/8wvqu7/qumU7zjMmcytbZOn7nd37nbC1H2+Th5FWvetXc2IsBHfyVN6d4yat72cteNttb8mOil41Zg2BtnJsO89KpPX1it/Hxx7jk9ZO3v9ku2Q/TZO/BqH1kjD1snxs72hFb1bMpbWJmD4t5xrA1a6OOremv32tf+9pZuzbY0ib/JV/yJbN1yli61Y8pek4l9efXj/zIj8zi9gM/8AP19V//9bN5Ygufv/mbv7m+6Zu+adY25o23Z6xVbIFfz4mUzZ+1oMt68y3PU89Bc37v937vLD72ubbMbzz98cOc0cdemBXHtJOeV4l9+pNS+snbH/bMaOvYrg876KdPOX3J7/iO75jFRZ9Rd3RE+syBG/gmff7xSSzgzPqR1iK4Myc/Ml90nW3JrzFZO7axX0zYx86QuSF0I6dkbsrTm7vT8vTnSteLgGs9TS5vNAZWTfLaWB5mxx8wz63n/3fX1w03+GPgurryiitryzOeWVdufVp9z3f9v2vXrf++Dt/19qo7frnqUz9fdfvPV935C7Vw6y/W4l3vqDr4V1UP3VdHHzpaRx86Ug89nLyiWTp27GgdPXqk7r777jp06NCM6P27v/u72rVrVz3wwAO1tLRUt956SyGGvd4ZCXyC5H2Y1EWSLkfwqp+SqGstb/Q/g1N7vJrZN1GsQz4wzvYDdqPm82D2gQtfHs4bHdvW34c5jYHGQGOgMdAYaAw0BhoDjYHGQGOgMXC2MeAQ1f/05/rwdPq//dSeaXnaf7my8yIH31/wBV8wI0Vf/OIXz/IIoTHlgBuBqC99mTMHuDmIJh3ufsu3fMvsUBzhII1EVsbTwQYEHdIFyZTzE23OHBx2O/i2Dg7Ic5CuXUJQOexHFujrMP/7v//7TxySyyN89ZHoMr8zDVIdQkUfNoxJvUN2Ur08iWRgJ4LBYbuYJIkRm77t275tluhlgxg66Ed4IX34xheS7cgYOsXP4b464zKvOr6pF4tpMg65wjbxDm7pNKd6RIF6fo9pXGt5cfy6r/u6mU+IGPuAHqTel37pl540lh7rQEa3/mJlzu/5nu+ZJb6kzOeMU8e3MVkTpJU648c2edjKXJnXGGuKtPzKr/zKWVzZBV/WwxoimeiV5F/96lfPkhhnrYMLepNCzJhTXr0xyNP4xM7ksxe+5mu+ZrZm1m1MyFLjxWTqm/K4x8zJj8Qs/vLJ3tU+r0/6IVWsG0Iy8SCtD8IoGPZFAKSctvg9Srgb4zrupdgwleYWL+P4jKCjPzEk2eaLCJ4P43zy1sINVbETWzYnXuZXT1o7sZT3LDGHeNGrzR4cEz3Wn03qlSVlMnvRc8xa2ANibW+wx95G+JHsMcbeltSLo1jYQ543fLOnpmvIR/jUNzFRp5/nhTVOTBNL7eqMy1qxkz/xGxatq37IZWVtMMDW6IyMzrGsbkzaPvdzP3cWT7ZaG88xMfNs0JfdnuFsIc1tjZCzGW+djGePvPjEbn1g0nhrmee5vWIezze62KGv+Ugpturj+SCFZBbHYCifS+rkrSHsezZGx1TSz0dYYuvYnvkjrVtsJ4M7zxqxTxvfYIcUh+gUN7ZZK58t+sjDsn7sDdZIevN8jo5zKRMHa8Muz8I8U5Gz443dkLvL3dhtkrdJ1o0mWc+1/jWRvDaXzX3ttb4pcm097/nPqRtv9A2Q59ezn3VdbduC6H1qfdPX/ve1/aa314M3/8uqO3+56rZ/XnXHz9aRW3+uDt76G3X47j+tXXf+Te3avbMOHHywDh/xSuaDM4ngDcm7e/fuOnjQbd1DMxL3j//4j+s//af/NLvN++EPf7gWFg7N2vQJyeu2a0jcC4nk5ddVV101+9CZfgicywfueszNH39geGjLe0if7X+2e74+4GkMNAYaA42BxkBjoDHQGGgMNAYaA42BjcSAQ0rnKpvxf3qHzg76/W++1v/z4w/yASniYNxhsQNqZYf3Y3K47JAcgSaJSQ72HWK73eVgfrkUMo3UB2nCBsmBv7MFxGQOhR24hyhz6O2AG2kRwjh+hyzgPx0O0Y3LWZh24xyUj6RI+ptfX/3MKR4OpBENyCcEhDnVkdqNyVkI28RObBB+SCx6MheJGDBW3jhz5dA76yaWSLSMo0MKWY581ycxYfOYEFB8tBbWkD3IhJBYYi7PFr5l3shxreX1RybwJ2vOPmRIxowS6YKIEGsS0S0e1hNRoQ5Bpp3/SWI56kmen4gdMchaaovP4ph6cYFZhJr48Tv9jNGXPnbwPbayKYmdYq0cG0bJbuMleTpCrqgz3tj4F/tGO+jjr4T8QlrqZ/+mPpIf+pPssib8sx4Sf60xMii+q7dPlI01t/GwZy7kZHBnXlgQX7HRB7GJ9EpcR//5pr9x6pXtNXMhsskxwQk9fIsd5jGHPSRebDE/XCBG+SmxRb15xCOx5AtSy7ODTm2xFbbpz7NQX23pZ84xwYH1M496GEos6IBP57m+0CD2sAxX9oI46s8+toktPMhLxibPR+ukr7H2RewiExPPGZgQnyRraW42mFO7fpI+dNJhDj744kLsgkPPA+3G2bv6e17RqV45Osa8eWEtybrKq/es+7Ef+7ETa02X50Ts4Ttd9q41kPccDe7UIZzZCSOeVeqUxV3csgeMVQ8fYmh92K1O3OjU1zqN9vssChkvVkj6fJFJ/CXlJPuGTXTQp794j4mePGONzzpEast4cVe2Rzwb2CJ24zNCm2Sd6PjRH/3REzEQF/uQX/z1TLe+PgPoMU/WTyzsQ3tC7BKHcy3Zxx4+siU3d0PmLidD6k7l9ObutNw3eZsMPtdk7enOvyqS14ZKygPyuuuuqWdd6wP22nre9c+pGzwUr7++rrn6qtr2jCfUF73wqfVXf/zTtXDbm+vY7b9U9amfqYdu+7k6esdbqh78j3Vscdfs1cw7dt5Vt99+a+3bd38tLh6a3eo9fGSpHnro6ImbvEjej3/847ObvHv27KlPfvKTs9c3e03zSAIjdS9UkhfxmQ+qc/2A3Yj5PbB9gPtw9YDeyH+sW3cf3DQGGgONgcZAY6Ax0BhoDDQGGgONgcbA2caAg1lnK85VNuL/6tPViVRwowkBkAP0nAGRK+nNYbwD9qRTHRY7YHbQ7xxAGudACDrMpode5yDa9QvpIn6Z0yE8+3NWlbMF7XTQpw/SIlLdmBAmfHSILA7Ii6/+6q+eERsO7N0cVOfAHMmApJFXp4195pPkHZ47TEfY5NYrEgi5YCyd9CAv2Gtukg/GI9voTr3bWaO9ydNpjnHNMiZ1yubTz9x58rGOAAAgAElEQVTsos/86iVzjglpxS8EREgR5Ju1GLGLjDHeHMaTUtYikt/68tGasIX+tGd8dCCREHBuziEoJDHJbUd5hA6iMHYnfrFhlPxgpz6ZY2wf67WLkXbryM6xPeNGPWNMtCvz07iMHfvzI7fnclMTuRX/SD7zb5xv1KFeWTJ2xGHqI9MXsYWksx4INf7Zh4g3Mc+XMsZ6WOMPP9SzCW7FiA5+mgfOk2DLGsOMtvgQieCkK3FDZPGX374AMhK88vZiYmkMHIa0Yg8b7QVJPjers09CShpn34oVyV5+0K9ObPjEPuWkkEvmZAffxkQPYs3+MhesyYecFAN2S/Lms/7Zo/xmu+fT6IvxknHxHzGKMDRW3BJ/7ezUbn94/loHSZ35EmOS31kvxCS7PAfNJ6bj81Kb/p5vPiOMM6/niDPcrGv8S9m4kLpwNibrb3/z2/zafC7AjGefsXne6OM55DkPH0hK/rFxmqKPfexhc6Q1t25iFRsRo3SaO3X6y7PBPPrrxwaf4Yhb0ucUmyRfKDCntbH2xtLBR/tqTNbYeti32q3/mKwfGyS67Ft5OunhA1vMHxtI8SKtYeb33DVXPpusI33inz3I7nzuiafnv7rEIHE5V5Iv1sC65/buU5/61Bl3sBzBq35K7qY8JXWn5SZ5m+Q9XZL1XI97zOls0uuedV1Jbu8eTx5+/ii9bvZQef7zrq9nXfEZ9VnXPbne+cbX1KFPvaOWPvX6OnzbL9StH/zJesk/+vT6tdf/s/r4xz9WS0teuXygHnjgvkL4bt9+54zwvf/+++qjH/3o7FXMhw8frve85z1100031T333FP79+8vBK/XNHt1M/m+973vxG/WTm/wTl99rHy2/5lb63xTm712wAP7dNbrfBmTB7cH7PmwRmtd0+7fh0iNgcZAY6Ax0BhoDDQGGgONgcZAY+DixcBmI3n9D+6gN2RIpEPeHBJHnupcIYfi6aPscBwJEcLDYXUSEsXBvv70Zw5nHg6okRW5AZUD+fTJHBnHZn3N6fDaIXv6jHbJ0xVSOHpDBmjnt0NxRAaZvDICiJwm9eYzPvMhKRzGZ07tym5kmTdzIyRCXMdm0iH/qBeZwk4H9cYiVuimT3xDZLi1mNuLSAm6xCk+GovEQnZoU05cE8+UtRknJiEG1CWlHxk9JDxZ25AIpPF8QvggkBBh6acuN9cSA/4mlrEr85La7CW6tCtHWh+YEFvzIi3kpeBbHRyoIzOH+RF7iCa+u9FJak8s46s6cVc/vf0XfaPN0cFWJBs71Y36xnFIPPZlXNrsKfV8j0+kfUPyR56v+thriSVbYRpJFH3a2GBvhszUlpjSk1uR+qlHHAZfsJ5bgYg69QgjMbTG2tQlVsrss0/pYw+f5JHxiK/YFmkN2KAsbvyILdqU2eX5gYCkU3v66aPd88EcdGQ/6+v2IzlN6vW1p+iS2ACf5kqM1ImTOWMzss16xI6MJ8XH8yB1fDaPGFn37G+66Mi86Y+kNzfyzt4xTt/0U86aqIv/yeembsbwJXnS2tkj8ubhg31hvPW2/mIiH5/1k2JD8nSbn01jn/SDBX0SJ3Ezb5J+MG1OzzqYHklP7T5rkJ7GxJ7ogxv67TlxE3sku2cgYtUeR9LSE5sj6WC78dY3pPhUWkvrZC30ZUf8I5OnV2zNmX6RniGZd7Ql88MF/z3TkPGIe0lePZ2e/+YeiXf7TJu4GSve1l8MPKfNaW7xsCesqTlHG+LDuZLBAv9C7o6vZg55O5VT8jblKYk7LZ9roq7nb5L5dDGwDMl7XT3rYSL3umc9qyTlpNQdJ3iffZzwffa19eznPKue89zn1PXXP68+84bPqudfd9WM6P2fX/FldfcnfqMO3PrGuuVDP19XXvqYesoT/ou6/PIn11d/9VfWG97wq7Vnz646eHD/7HYvwve2224rt3ZD5nqIP/7xj599E8OrA/yB+OM//uP1pje9qd773vfW29/+9pNIXiRhyN4pYXo+EIhTm5vkvXgPAvoQqNe+MdAYaAw0BhoDjYHGQGOgMdAYaAyc/xjYLCRvDpMdYocQcoid5PB4LYe80ZdDYGUH7w6OEUf8HhOiMSSvMTkUNw55wC6H0PqpkxzWh+jRPwfazor0z1iH+UhEh9sZG/0O1B3GO9Q3hr4QJKN+h/h0IBYQYvJjUocwQHyYY/Rb3mF5Dt4drItFEoII8aZeGsdHz5TkdUjv4F1CpPGR/c7G3EJjO9/MSTfSzLrqw07jzUuak0w+9hkvsRMOkDxJSBYkAZ3iRxqfvDnFGBGBKON/Xj2KvEIc6CNpR7TpE1INNuI7Sbe+bI7d6lIm+ciurH3W2HzWih51bCWts75iC5fqlOmVl/gvXiFBYND6pJ0Uf/sDNpOQdMiW5RLCLfaYU3/zij0/5McU/8Sf3YmN+fVnnzxd7JUPiSZu9gasiLv+I8bEfEryamcLQj92xm9YoD/JPCGEzW+P0Gm9kWa+cEGX/Yf0EhNrYrx1pg+W1Nnr/DYvXcbYe5krkk38gS9rIj5Zw8Qmkj1pG58X/IlP2Z/isNz+Vs928xoX/JjHnmO3vcIW/lordfLWhI/K/IptkcuRvPAnlvTz3bx0ZFyk259iKx7sZKP+aSdhgG1kMJQYWD8YTll/diqLmTWwt8RavWe1fWMM7PJbXj1bMtb4cc3k+TQ+P6w/n6yReT1DjDcvHLA5OuKTWOob7IXEzJrQmWcIG/TNWH3EgN2em7HZvPkMEj9YTJyMjw62+YzRXz/1iVukej7BfsZNfVAvFuLmOR2fjaVHW+Kob2zRbm/BFdyYRzn65cXM56wx6uGCDin7kg8jJvIFDHOb1zyk8bEtOs61jK/sb5K3CdDTJUAvhnGnIHmPk7chdJ913XV17XU+NNzivbauu+7q8spmN3pn5O9119S11109I3qvv/459bzrn1s3PP/6euENz65nX/GE+tovuar+/i/eWjf92a/VFZc9pp70+MfUpZdeUo993H9TT3zSZfW0z3hKfdu3/X/qXe/6t7V//7568MEHZzd0Sa9ktpkvv/zyk4jckcT1OuNLL710Ruxecskls5ugY/uUNN3s/yBP7W2S9/z/h36zY67ta4w1BhoDjYHGQGOgMdAYaAw0BhoDjYGNw4CDaAeWDlbP5cFpDpAd5jq8dkg+JiSFQ+e12DntiwhA2owHzvF5SvKGjIlddCHGEAs5gFbnIDokHv05lBbT6NbPgTcSRD2d6vQl+ak9h+rjWDqUkYTsHvWrT1KfQ/LoN5b+pOgi9Xfba/z9Tz6zYTq//lOSF3EXe8WOLuPoQxiwIbFLfchNZTcpYY/fUspuzbHNWP2k6FLPDnPJS9oRLAgHRCNf46c2PqmLPjYjrdjPbn3HZIxbZNY182qnH+EzxnIcJ88fPqYPXRJ8IL70UUa+0a/MHmQP8lPZWPhnN/+Qf9ZVHplinBTdZF4r6wayW3n0sUO9sfNSSN7EEdnETvPHjvhBmkec6TVGH0m9vel8VJ5tSNz4F7uzNubgR+ahIyRv9GkLMSvuyCC6Y4f9Qq86UgyRhOIPP0hVY+gTg2AycUNMhZSyLp4JfFBnj6aNfvnxOZQ8f2MvGxByIeDVs4nUhqDkozwfIjNenfWw1mxUnib1bIH9xJZ9MKpv5tImmQOO9FkuGZM0JXmR4+ajn132S/qG4FSmm4QN667MX/s5/bOP2InEhLXRbutGJx3xhaSLVG997BvPQbEXr+B6xLl6fhsjBrExdpLWJqRm6sXVGukPn+YwN7JSbNKPlNhLjzlgL/n4zFa4y/zWJL6ljlQv1vzyHKRbP/hVlxu95sncxvksMAe8S2Iojc9TfsB25hvHq7MG9NoDPrusm73Dn0hxojf9STa7sZ09z3dr77kjyXtW6qc/f8wTCU8woKyPPU6XdUS+Wz/Js4ZU57mfPU3nuU6JJbtzgzfydF7LPL25Oy1fDGRg+3hhkuUrkrzPRug+69o6QfJed1096zrlq4+nh0nea5519YzkVX/ds7UjgK+t51x3Xf13119XNzx3S/2jF2ytX33dy+spj3tMPfHx/4+67LJLTySEb8pXXrmtXvWqV9af/MmfzF7N7HXMHjCXXXbZCfIWCRrSV73f4s3v8SJ3pyTptLzZ/3Gd2nsxkbwesPzf7GvU9m3c4UfHtmPbGGgMNAYaA42BxkBjoDHQGGgMXGgYcICbg+VzeXDqoNj8DoNDpIzSbSPtDoZXa2f65kDWQbaDb4QB0mKacouKDWPKfAg0djgc9ypOB910ONR2oJ9DbfMZk3mTN04dIsnhueRg3WG9m3IO1tU5ZJ/abo6pvWMZGcE/JMd0XmWH5YgJfSR5yQF7Utr4Fpvj+5TkFUc20h3ihv/IOT4YJ4b/N3tvAmZZVd193x6qq2u447nzPN+qbmYBAQVHFEURFYEYJE7xjcE8ihpRCSoGpzhGlEQMyCgojmhAQXBCBuMXjSYOrwOK0XyaL6+gAtLT/3t/p3p1H663egKqqrtXP89+9j57r73W2mv/z+lz97/2PqaH+LBob77hDyQri/2W2KUIsQFpgRz6zQZ6iBWEBFgh0Y+5hNBhsZ14sBuPPhZr8wPfIEyQB1cWi2gMKdOObvqTIFvRQWyiuCHew4n+fAc16jfjgNSIkrzYJn7RhAx28JN2cuIHwQTuuEaeHJ8sjuTImTzXxN92M5ocui1ZH3Lq8BdyxvwBi8NxsWvmjbhYjOmPvJG46ATPyBtmwZe1Q6RRjw7zZxTJCw4gqMAicUYvNsmZP7PPXEEoGXaNnMI+MacverBp84c/kM3YhyxDF22QmkauW2yog4RDhmQ+k3ONXPRZwTVYNMKM3OLK8wL/7I8U0MEfFBAL7iH8Ipbk+BtNjId65tbsmg8QzIyfucGWxYI4MX6uuffoTxmsRMdBeZjk5TkHJhkPf4CAHuwyVvRYf4sT9yD+cg2W7BmCHOOjH2Vs05/nBLHmmucdzy3DFTqiY0QWPDM+xgo20GU6KSNvyeRoN/+QIXENZpgHrrFJHc83xkkfsABJDTaIJ+0k84kyxCPjJS7cr2Awii/amTPqkDOd2MQGCVyhn/ubeBFvnl+MlWcb/Zk3np3Wh/74QdzMB+KJHyT6kLBJbvNgY7C81WptiQWy/J8EQcz7AM9JSzY2s0uObfRQJlFmzrnvSZTBA7FF1mQMB8TZ7gHmghjwfOCPJLgPiBXX9GPc3DectMC13S+UFzNZHKMkr32Ld/iI5uj1jh7P7CTvnkl47o1E9miSN9y1C5nLUc0jSF5ucIje8IHHQ6+v3qCnOaK3F5bn+s4d9YyOfdb09bADZrW2X1M5n1B8eiIkZaenp0LyFqI2mvgxx/HMkLuvfvWr1Wg0QuJveJcuxK4RotGdu9sjepf6j0Ubk+V7A8kLnnh48yBe6vPj/vmCk2PAMeAYcAw4BhwDjgHHgGPAMeAYcAzsDAaWCsnLwrX9/oZwMIKXBXuIiZ1d0GVxOUoasFjMYjgL6ZT5nc9CNAv5JHaFsRMSO9YOCWHEAfIsxhtxAjFhxK4t/pNjM+qrLQajk4VqSCPasclCNj5ADEJEmS/kFg/TxcI3slxbW1Q3dZCkjMPaTTZ6bX1oY6HddhebDIv0+GgxMPss3EOM4TOkCwvz+Ek7diFJiJcR2FE7lCEbmEv00gfygrJdG7kG8QEmbe5ohwSEbMBfyCBiARlG/M0OOfFhjvEN8sD0ExMIEMgM5iBq2/rjE2X6mG1iQh3X4Amd5IybdUHGQzv1pod2kl3TRtwgHE0f/ZAxmxA6EB82B0byYpf+jBd9kOKQQJTpa4l+1tfI9KhPlIkLNm181hcbRraZz5Zz3yFPf5KNjT4k5LAL6UZMIGC4Js6mgz5G4tAGtiCfKJsM8WE+8Yl6CEbwhm3qwAMxYX5pp4zP2IQUYj7RCTFlMaMNrGKfcTDvzBnjsDFZDNCFfbs38cvGQl2U5MW+JfobbtEJAYk/2MBXy4kPzw6uIYXww8ZqOe3MLXpMP/IWI+qZWyMnrd5yG4vlNm76kZCjDRyYfWujnvuKmNOP+xtizZ6V5IwBv+jDvWR2TDe7MImV2bV2chsPZeaHP+LgHoBU5NkBvhkrctF+lNHPvWPPD+pM1vRaP8aIPLqZC8rmn/VBBlxAvlsbdcwx9yBl7kfuNcbJ/0XmE3YYH3MO5mx+mBPwRqI/cxx9jtKHmNNGogwm8ZPE/YF9xolfxB/dyOEr7VFf8Qc99MUn00tuvpJbm8lH5ayMz/yfFu1HGfxjn3HgC/ZNn8UBXHDf0Z/5R45EmXsUrPH/AuMx/egB58TPxk5/YsZzmr78X0g88BH5Xfn/3+w9lDn+gTMjd4d38Bqha/kwcRu93hvJPx/z3kFkD5G8dvQyRzNvj+SF6EV+ZvMu3zmitzcgp23rSxA3Ov+58MCwBxEPMYhYI3Yha61sue3O5UcTu3YhPI3ItdxJ3vvH+aF8qC6Ebh7cTvL6QsnOLJS4rOPFMeAYcAw4BhwDjgHHgGPAMeAY2B0wsFRI3uhve36Ds7gN8cHuHhaio+3bK7MIjYwtRlNmoZ1FZ8gC9FPHmpDJsbjMIjNrRLRHE3pY2EeGXVa0sY5k+tFjuqw/eocTu/CIN/XI0Z91KBa5WQi3vuZftD8EAAvjLHiTWESnn5UhAmiHnGCs5h8EGm3IW0LOFtnJiQttlFnUp0wdfqCLXWqQYCzKQ3wwBnLa8BHCG4KEMkQPvlr8qKNM3PGXMRMriG3smU82Dq5tJ6/FFV+ID3oghogTtskhBPGLnXe00wdSGEKYa4gISCTGgDxEvhEp6CRBTFsCa+jAT3yHpDA/LfZcM/5ovcUYX0nEwMbOHHCNTnzCX+wSE3LGYPGjDzFAjoTP3Ad8a5lrI3yQiyZwREywzT2DLPbMJuMgDjZn5IwT3xgLNhkPCR2MlfnCV9rsmjIJcsfihF7uV2yhFx9tbJCrkL60Iw8+sGd+4Sc+gCHKEI2GH+455Bin4Zh4sIPRxk4fsE5/MEA7vuGD+QymGYfVkdt9HB0DvqEXnSRiCn7QY/NqOaSo+YBN9ED24Sdl6mgnt3piY/XWl5wxQg5jh4SvFnebF4s75Ct98A9d4Jw262tyzCM6bE5NJ7FjDMyZYR1CGnwQJ+YGLHLN2BkLseK+sbig0+YFH+jPHOMX/SDpouOjzNjpgz7K4NmwxrWNx/RabsS2EcPowqaNi9zGRg5mGSPkm+k0v7Fj6//ImQ7DOXNHO88PYkFM8SOabCzYsjLYIwZc05/nIzqZK3zFPrYZu43ffIpijv9fjNy0/5eR4xlh8uTYwR7j5F6BgCe3Mtc8r8ntVIVofyujhzlmzilHE2PGBnFA3u5F5sGeF4ybe83sm027JkcGbIA5YoBesI5dysSHdiN5wQVy3KPkPBv5Q4Cob0ulTFyc5N07iEonpHd9nv+I5OW7u+G3d9nNy0vRqJ28m4lciOCtaY7cnY/k5cHATclDhYcHD2P+k+PhZaSu5UbuWs6OXr63y7WRu9HcdrtanZHBVj8qX+o/AId99p28vmix1DHr/jlGHQOOAceAY8Ax4BhwDDgGHAOOAcfA/BiwxWTWWpbK4il+2IIwi+I761tUnoV2iA8WjcltYd9yI0UsZzGacpTEYd0IPyCBIVFZM8I/6klmj3rkILaGY8nuJcgeW/RHjr6sQUEIQIpF+9DGNfKW6GN20cUiOjbNBxbKWZjHH/qYPuuDXDRBqJld5NGFLxCeNibIIBbv2dGGDP1ZO2M8JkMsGQf28AGyxOyYD9ghrvgC4Yodk7Ec/ZBWRvLij/WHcKOd/pAwzCfkgJGfZtt29+Ibesnx164tbsQumqiHNDEyGH30IWGX2JsvkK4QQIwBYsVig6zJWF+uiQdy1OETBBFELP3IadsWyYv/4BJdkB7Mj9khRydxAbPMFXVmy2LAGIiZ2bF65IbHRwzxEXlIO3CCvNmkj9kFbxA9RuKiCxIIX0iMEXxYu5G81h+9Fh/IH+4vs8WYzCZ1kGB2v1g9MtiETDKSF1kS9ZBcjIX5ApvWz2S4Rgc4jxJutNNGHc8QxhxNpoccbPDHB+jAJn1NlnawxRixE7VrNpChbM8EcuYZgo0+JOrI7d4wO3ZfRP0xfdxvyOGL2UUnMaTO4oOc/YGL+QgGILC4NhKOMv3AEDl2qKMvdZSJs9k0n6LjNN/suYw8sTMZsG79qQN/jJn70ohVdCAznJCnjnuFuSZmFlPTb36bH9Rbm5V5VvFHKGDb6iAl6UN/fMQX5Lh/sQfGwQr2wQHPCO4f/n+ljn7mD2XTY89Errlf2EWMHYhd2ogNcTU/zFd8wCb/15B4JljZrqlDZnis6MAn9HKvsgMemWhCBtuMgXrzmTHQl3bTTw6xb/YpU8c9CY6sDzqwSbzsvQM9YACs8YcEhkP6G5mMTNS3pVLGL/zmOGbbzTvqaGbfybvrBKGTq7t/7LaQvHMPER4mc6nf30zyDgaamRlowI0e7tyd2+FrZO58+fBOXm5IEnb4j5EHBQ9KEi8gRuhaDrELacs1hCc/FO16mOwdJkS5RnZUvdUt9R+e5qflTvLO/0N5qc+l++dz5xhwDDgGHAOOAceAY8Ax4BhwDDgGHAO22Mq6yGIunto3As0HW6uZWxfaNd/oa4v86EUnR1CykGzjpQ4iisVns01u7VESlUV4dhWZb7b4bjbIbREbmag+FrZtMZ02WyhHnsV8Iydps75WJmchHP2QCxAA6GYhHEIBMgI9kA4QbpTNf/MBGyQW/aOJOhby0Y+PRvJaP/wkEQfWyqzefGQhn91nEALYZoE/6jdlfMFX23nGzkBIFOyRsI1PtqhvmMSW6bIyhBNzwBipQzd+QQbRHzIo6iPt0VhY3K2vtYML/OfabBqBZv1ZJ4SQhaAi5sQKfZCTkIlGZNKfesMFBNEwyWvt+LG9nbzIEDPIbcpGvGCHa3IITmLJOKzO1jdpN9wz31F80GYJGewQY3QQT9og0qkjtozJ9IMJYgNZTl8bL/0sZhCKRuLQD7KTdtOBfuogQulj82pEpMlF48U9QD/ksWk+2HHNtOEPcYJss3uGe4V7HZ0kdFqZNosv9aYf4g6SGxvRRLuNHx2Mif52j5hucu4R9NAHWdNjtsmZFzAFyWd/QAGemFNy4oFu/IRYQgdjJ17YJcbDCUKX+8rub2wQC3Rh02JnfpjP0Wuwif+0oQdSk3YbP7oML8iClVHjo45+PB8YkxHnPPeIHTFmzkzO1ugZHylK8lrczY71oZ4xcV8SM3zGP/7wwQhr/KaOdu7LKNnM/c9zinESK+5r9NGHa3JsEWdk+IMU8MX4IZVp49lFO7ajz2eLGTooQ1yjE7+4Zoz8v8T8mwzPVHRxf1Bn9cgzBvMJH6mLJnzBB2Sot76mh3bGZ3MX7Wvy+M9zi2vkLTddtNsfIlCHDIky4zGSl2uwi5/UEzvTQQ4eiBv/vxJP7DA+sEs8zLb5ZX25XsyEH8wfJO62yN1RJK+Tl7s/eelzuGNzuIXk5WYdRNLsLA+NzUcyDwb3awtv7M1HMu8oyUsfbkpLPAB54JCT+A8GmXw+v2XXLjt7IWs5qpl8OBkBuiP57vaDenhMewvJCwZ4YNv4d7d5c3994cYx4BhwDDgGHAOOAceAY8Ax4BhwDDgGRmHACLXoQmq4vrKIC6i2UIwf5he5lXfEP5NnYZn1HQhQFpeNjLGFcdaD2IFEG2QVJATrQtRjx9aL0AeBAaEJGWMEGjny5CxMG2lBPyMjIM5YrEYOcgFCjsQiPn5BSkDU0NfqabNxQuwwT9hg0R4frc1yCArGCSHA4rqN39rt2nL8g1hhoZ46rvGPo4yNjLa+5Oi2mDFO/GYR3o5FRoaxQXZCnOArOqlHP7u0iLHZg2xCHzLoNlniSwy4tjorI0dCH6QK84Z95hT9+E+b+U2/6LXVU0fCPn1IxJ64UTZ7yCPDuJg/7EDWUY8c80Y7iXFBmBA//KedevxlTmiz3bvMIYQGux/JGTM7WCE4bOcr/bBjvhBPCB9yyDTs2XiQZS5IxBW/KBNvcIHfzAv4xj9IL/ObvuAZggk57GOTevRY/CAz0AXpAzajhBy6GQfkJGPELmNDF/cM9tBPG/cCerCB/9ghPui1sVqbjc/qkSWujJFydAzMHUQgfkEYE28jpZGHVCN2EFvEgfhF7SDPPRitY+zca8TMfLGcextZZBg3/hvmmX/sWU58kOG+Io7cO5QttmCLeKGPuQUHjC+aiCH60cs8IRtN+IU+YkK9xYl6ixPtdm/aOCw3XfSjjJ/YJK74YXL053kEZtDLHJN4JjDv+Ig8tsjRRRvxxm9kRj2/0AveuJ+53yw29CfWxJJ5xA/wYni3HLKR+wodJHTQF6xCImIXf81PMMh9Z/cR9sAwPoIb4kCZ5wxlu2eQQy8JX8iZe+LBnGLHCF/aeS6BR4srMeFewG98wSfkqMe+/RERddhCF/7bH/aYXeKMDv5fwF/GaYk6Ev4YyWukOTl28QvMU8Y29symxR6/8QmbVheVI3Y8k4g1448m5ov7xo6atv8L0UXsuUZXNM7gntigD708L/CRZ6PZXewc/6NpmOQ1Qpc8+s1dKxsxaNeWW73lVm+51Xu+Y8Six2npxCkWJXbnynNHNHfDvxLjCOYZdXsD9Xl563VDsjfc0bv5m707QvJGb8roQ8LqecjxsCHRzoOXH0RG9JEPE7xcR9u3Vx71A2sp1w2Px0leXyRYynh13xyfjgHHgGPAMeAYcAw4BhwDjgHHgGNg2xhgMZh1kOFF3Og6yWKWH4hf9IU8YeEdooVFaUggxssaDzk7iFmcZg2IhWnIBuRpY9zkVqYvi84srkM4WIJUsDI5ZJHFDN0slpOjh0VsFr8hBiBQ8IsyxBPlaB06IIcgYynjo7VTF02QZ8jgIwv4Ub/NF3IW0FlMJ2EPchO9FmfWwFtfMTIAACAASURBVCAQon2sjAxtLNLjL2QV47K+6CExRvyxuNHOmOlrpALkA2Vk6MOuOnbjEl9IC2xaf8qMC4IOsoX5gWiCHIPIiK7dmS9Rn60czcE942cs6GI8xGI4bpAu+ASRhQ9GyjAWyBdbMzQfjPDDV3xhbBDDyOIvcYHII6GbnDqIDBLX4Mv8sBy7tEOQETcIKBsPMsScGIJhfKOOHL8M6xA85rdhnj6MD3/RCz5MntigBzs2PrANnrlPbHz0B4s2NnL02XjJGRd1kHhRvcQHIoh6ymbbxmY580MMudcsPthnTiCE0EnZiGUbHzLIgxOLJUQpCd20k4MF221rhBRt/CEB4zE/RuWMHTwhjx18JUZ2j3MNbu2aHHvEFHnuDeYG/yDVkIeAjCb6Ex98g/yysURz2plPdPAMIF74REzJkUWGNGoc1IEPfOM5QzxsPqL9eXYw5+jBBpjBJrHHBnqQJ4EX7nXGBHYNX1H79CEW4I9YM1/oNxnaITB5tlLH84F4DydiaX98AhaQRS9l7nHGhs+GZXKLDXhmHpClHt+JJb5DIBNz/EMnbeYbsvRDlnsSvJh+ZLDHXIBPCEGLD3Gw0yvAA3ZIFkPkSPSH6MU2dqkjx0/uBe6t6P8DVgY7xJL5ifqMHuYXm1F/kKGNe4kTF/CFOeA+srFGc3wg1vgANpGNJuabNv7PtXHQn2cssaZsf/RB3LDD2HlOMFf2hwCMk3sJG8xf1IfFKNu8WE4MIWKj5O58BC9yRj4aeWu51Vtu9ZZbvedLh7z0udixudhC8kLihg/PkMyF6O2r0+mq1emr2e6G/7lB/HKMc39mVn3+M9lWYqfv5r9OsRtyVI4MdkPbm/9T4GHHA4WHMLt4+aFopGeU7LW6uRyZrXL3b5s77nl3+sE57P/eRPLykLbx705z5r5ue0HD4+PxcQw4BhwDjgHHgGPAMeAYcAw4BvZmDLBQzrqIrX/YmsnunjOm6BggR1h8p87GywJ6VI4ydRBllKMpqsvK0XbiR1/aLJa0m6zl0T7RdvpwbT7hL9fUkyAjTDckBz5GU3RsRsxE9VMmsWjOYjpEDYQEurFJbjrM1+EcGdbFTBc+mr8mSxt10fphvfQz3CHPNX5RB6FBHbZMJzk6IOwhFrg2csbkyEk29mjfUWVkh/0yObNvY7FrdNu8UAcREbVnPqEnGicIHcgO7NGPhIyV8cUIDOps95u1kyPDuqT9AYERfeYz7VYm59r8MT02L/gzLEsb8taXPoyPPFqHTDQG+ARxQ271pofccGA+ML82h+ilHoKH+Tf5qG9WJnbgA7LP6iBGqccGdYzZfIjW0c/iQzuyxJs6Ej6gd3h+TA7fzKblFheuzW9ysxOVow670TbKyGMT2WicmB/blWm5tUf1WkzJzQfIa0hF/tjAxm22kDE50zOcY8d8NXlkDM/WhhzzZnjkmTKsC7sk6xv1d1iWa2St3uLCNdjCFs8srqOxN3lys8dzLVoPEUpc0GM+mLzFDiyZ/agMZZ63jIF4cI0cZXykbHjm2uZpOM7MqY2JHD3mA9f2hy3YMd/xiTK6LO7Wj3rGafasD7nJ4Bt67Zo26rgHzRfrh350kcC7PYetfThHD/EcjrXJoYe4oIc6xmBtzCVlcvoTG/Tx/xnylPGZ3MYHlvGZOpLpWugcv6JpmOQ1Una+3IjB4Xart3x77Sbn+Y4RjR6nxYtTbKbPUcwDtTq9kMyFWG03m6qUSqrVGnr9OX+nD1x4qQqFssqliur1ppqNhrrNstqtqirtvsrtWdVaXdVbLVXaDVW6LVU6A1U7M2q0u+p2Whq0Kuq3amq0B6q2ZtRstNWsN9SoN1Qnb1CuqVmvhmlmMNB+++6nmcEalSs1JTOBEpmMUqRUSulMSukgo2SQVzIoKh3klcnkFGRySge5zfWUM8pm0iqFKaMcRHC2oEy2rHS2rEw2r2w2o2IQVylIKBcECrJzxPJi/vg0ktNyJ3l9MWQx8ei2HX+OAceAY8Ax4BhwDDgGHAOOAceAY+CBYYDFU1tQXegF04fSHmMy/cMLw7TZgrHJWG79yKOJdhbC6TdKhnarZ2Ha9JHbYr3VRfXaYjs+Wj12WBQ3fVHdpmM4p4/VmZ5o/1Ft1r6ji+YmZ/rRGS2bDVuYN/1Wb7n1ieaM12JL/XAMh3WaL6aTnDqTi9bvSBmbNheU0WU5Ok03Ob5CcJBzjX4jZ8y+9bexkJOYJytbHvVvVDtyyETlo+VofyubX9aPa/PNZKI5Y7Ex2DyAWxsj/e16OE7oidqzMjnJfLVxRO1G26wcbbcyesyu1Vke1csYhvVEx2ay5lvUP5Oz/pabnfly00F8zUezg076Wb3poA/ydt9yjazNv8lZbnrsmtz8s3zYPn3Qi23auEZ2lC7Ta2Ox3MbBtcmYbdPJ9XC71Vm9+UhuY47qi86byVq7+TDftdUPx5h6iGE72QB/0WXjtzGSW6JP1D6+ojfabjLkFmMrW1/kaTOfbMzDeuhHMjkbq92LtFkdfSmbLOOBL4nKRuVNt/XnGh30p6+1W45cNFn9qBw96LCYDsvQTt1wPizHNTbNLytbXG2ueN4SQ7OH3ChdD3VdND6UjeQdJmXnuzaycbjd6i3fXrvJeb545KXHfsdiH5vpc7OuUb23Rqe+8MXatElb/m2UdK+keyRt2FIrbVp3j95x1ovVr6d06OOfqY998bvKVvuqtNv6zNeuU+PQA7Ss1NVUYz/lGh01anntW53U2lpGJz//pbpzk7QJ5SjdqNDmhg3rJW2SNt6rb3/jlpBo7vdmtHZmf/X6+yrXaGm6UAiJXgjeVCaueJDW6lxdq7MtJbMVZXMl5fNVJYOyxoKyVqRzmkollE9OqZOcUjsRVyEdKBVUNB30NJnpaDpTUCY1qWYyplZqmQqZVEgCLzbRa+Su5XsLycuD23fyPrCFA1948fg5BhwDjgHHgGPAMeAYcAw4BhwDjoGlh4E9leSdb7HXFp3na1+o+lGL1LaAjA/4OUpmofx7IHbMb8u3pWtHZOi/o3I7K2u+bUv/ttqs/6icfrvad5S+4bod0R2V2Rl/ov2wa/eN5cO+bO96WJ/JD9cPX5vcQ5EzlvnGgx8PxJcH0ndXx7qQNh8KW1Gd0fKuxmN7/Wzuh/P5+pmctePjcB1tO+I7/Ug7Imv2Hsz8gdqNjvuB6mJcUX3D49xW27DsQl+zUxqyb3ukLO1OCu4YKehx2rPiFO7kheQtNnrK17sqVVshWZpJB4ons3rV375H5170Ca1YnVAikVI2E6gUxNXMxFQKVuvAx56oj9z4A01lakoV8/rkLTcoe9C+OvrUl+h/Nkn3QQ6vu0vnvfoUHVRaqUK1r0L3MFUrPbXKddUqdVWqNVWqFbVbNXUbJfWbVXVabbVbAzWb+6jZ2Ve3fOub+uotX1K7nFYpPqZiLq7pIND7rvyc3n3ZNVqVLCqeKWk6aCpR6OhLX//X0PZGbdT6u+/UEf2GKhOrlIznNBEvq1Zbo1/+8jdat1Fav/5u/cuNn1Y1tVLZNDuE84u+m9fIXcv3dJLX/iPhPyweyDZuX5hYegsTPic+J44Bx4BjwDHgGHAMOAYcA44Bx4BjYOcxsLeRvAu9CDyfvVEL48N1w9fz6Vpq9ea35UvNv1H+bMvXbbWN0mV1u9rP+j9Y+a74sSt9tuXvg61vW7YejDb8fSA+P5C+u+r/YtjcVV9H9Yv6Hy2Pkl0KdbuDjwsRp705Dkbybo+YdJJ3zyIutzff3r51vmOz/OVLf6Bqo6n27H764te/N7dzd5O0fpP0W0l/0BxZu3HDRmnDvfro5ReqXMzqI5+4Wr/TnMzd967Xsc84Tv/87X/Vr/9vn1e/4Z365td/oFahoXe/5qU6//Sn6NB0TL1yoEZzoGq1qWpI7lZVrVdVqZVVrpTUbjbUa3fUqDfV7q5VUNlXRz3+eP30x9/Rul99R8/YN6tHFJarm49rOlvSuZ+4SW+74kbFpgtalihqzaOfpV/8Xnr1K05TORFTkJhWo1bWrV/5rJr1olbG2zrh5NOkDXfpLaefqmB6TNOJlI4/6Tn6wMUf1nS40zdQhmObN6fF+PFqti13knfnf0Avxry5TZ8nx4BjwDHgGHAMOAYcA44Bx4BjwDHgGBiFASd5547LXIjFcLfhsXYMOAYcA44Bx8CegQEnebeSeU5seixGYSA20++H3+Stt9oKKm1NFGa1LN7Q+ERS45NxvfysN+t9F12lWGyFVqxYqcnxmKYnliuZjGtsKq1jTn6xrrnpO4rFlmnlxLg+etMtmmzPaHoq0L99+Vb1E1m9/5Wn6cynrNUBq2OqJ5apkM0pE34XN6dcNql8Nq4gm1Yqk1Y6zTd0AxWzGRVKNcUrB+pVb3ivrrzg/friJW/TeS95ko7IxrS2mlaq0NA7r7pJZ1/2RcUmSloe1HTdv35fp53xWmUmYipNxZSantbk1KSCYJlWTCzTyvIh+smvpTe/7LnqjMWUXhXTdCrQ8mRZK1IVTWWySgdpZYJMmAK+6Ztd+B+oRu5a7iTvws/BYsy72/R5dgw4BhwDjgHHgGPAMeAYcAw4BhwDeyYGnOTdMxabnTTweXQMOAYcA44Bx8DCYcBJXic2RxGbXrcVF7H+YKDuYEbVzkAf/tR1+s166fccYbxR2rhxg9Zv3BTu6N2wyT6hu0n3bfitrrjo/UonJ3X+x6/VryTd9PVv6Y5f/lp3bd7Z+9Of/lg/uO0rOrJS0Nc+8F69/OiDdNHrTpPuvZMv784d48xRzpvYK0yvDeEnejfxUeD19+o/f/ivWjPb13jlYH3+lp/r2U96ml70xIfrnh9eowPrMXXKcaWLTb3n4zfrdZd+WbGxmmYOf5T+43tfUTEX0/iqmFZPTmvF6rgmpiaVnIhp+eqYDv2TM3TTz6RWJqPqspiyU6uUTKcVT+cUT+eVyrCLN7OZ6J0jexfjB7aRu5Y7ybtn/shfDGy5TceSY8Ax4BhwDDgGHAOOAceAY8Ax4BhYeAw4ybtwC8K++O6xdgw4BhwDjgHHwJ6BASd5t5J5Tmx6LEZhINYb9NUdDFTrDpSuDrTfkSfq6i9+T8vHpjW+aqXGV63QqlVjGhuHMJ3SdTfdoOOe9SSlpmPKpqd163/8RJdfc7M+eNlndPRxp+p9l1yjY555qpbHYvrEBe/Qy48/Wrde9I86JD2h2lhMlWxa2VJdU8W+zvrbt+u/f/RN7V9nJ29G6VJN5WpdnUZVs62csrlAjzv1Vbr19g0qJ4qqj8f0m1/cppOefohKyTHlCw39/VU36/WXfFWxVW096cRT9NMfXqdaENOqVTEddPhj9au71oek8j13365yr6wDn/0a3Xi7VImnVYrFVEhOKpVJKZNOK5POhDuJOap5bievk7wL9Z+hf5N34RcYfFHHY+4YcAw4BhwDjgHHgGPAMeAYcAw4BhYOA07y7hmLzQu1TuJ2HC+OAceAY8Ax4Bjoy0leJzZHEZtetxUXsf6gq96gq1avo2S5qzWPfp5+erd094a5nbzhZltJ6/k27yZ24P5eTznhaK2YHNMZZ75BZ57xFl3zz/+PxlL76+qv/VL/+Mlv6sP/fLOOf8pReturn6uPvu8cfeOajysTiyk/OaVSrqig1FO8cbi+//N79NzjjlZ9KqZ4tqjxfFNBsaZisaxKpaKJXEVv/zTHMV+r2IoJrVoe06UfvUQfvOA8tZJxVZJlve+jt+rsS29WbKypJxx/on5xxy0qBzGtXhnTxERaE9NVBZWGfvj/fkPpmbwOOPkM3fozqZdJqMFO3unlCvIZpTLJkOxNZTimORt+kxei149rXpj/TJ3kXbiFBV/E8Vg7BhwDjgHHgGPAMeAYcAw4BhwDjoGFx4CTvAuzvuAL4h5nx4BjwDHgGHAM7DkYcJJ3K5nnxKbHYhQGYoNBR/1BW91+W8lSR+1HPk8f+tztiq1IaeXYSk1MrtbkdFwrVsU1PhXXl26+Rsc+87GKjY/pzDe+U49/zJ/oc//8bb3ydf+o57/qPXr7ZV/Rk045XVd94hN6xMEz2vTbX+h1L3uR0mMxFVNplUsdJbNdvfrs9+m88z+s5MqYMhMrdeFHrtZ5l31cpVJOhSChTKGqVH2gb//PXfofSXdv3Kh1m4+CvvPuDXp4LavG5Lg++LGv6c2X3qTY6pqmgpJ+9l8/1lOPe5TGl8eUWD2lyamy4tmCvv+Lm5TqTimW7Os7v5CefvSjVVwZU2pqubL5tDKZuDKZhDgeOZvNKcgEYXnueuF//NkxzZb7cc0LPwe+6OExdww4BhwDjgHHgGPAMeAYcAw4BhwDjoEHCwNO8u45C85OHvhcOgYcA44Bx4BjYGEw4CSvE5ujiE2v24qL2Ey/q/6go16/o2Sho+6RL9Dt90p/EDt510ub1oX5xk2aO/Z4w3/r2Gc8WmPTqxVbndPM4c/WZ756uy75yEcVWxHT319+tQ457kV656Vf0svOfI/u/c1d+tvT/5eKYzHVUlMqV/bTEUc8RT/55i3q5ie1fGxSK9N1LU9V9YY3naNPfuitGhSWKVuq6biT/1Tr7v6p9u1OaXI8pvHpnMay++qXv7pbf3/6M9RaEdNFH71W77jkBsXGU4qtTuj0N5+nX90nPfVJT9D0cr7Nm1AyndBPf3q92r0V4Y7gl535Lv32nnV6xjOP1/jEmBKJKf3JCcfr8gs/qEI6o3wmUD7IKhcs3o9ZI3ctd5J38ebiwfpB73p8Dh0DjgHHgGPAMeAYcAw4BhwDjgHHwN6LASd5F2Yx2BfdPc6OAceAY8Ax4BjYczDgJO9WMs+JTY/FKAzEBv2ewiObux1lim2tffTzdPl1P1RsZUpTk5NKZ5JKppNauWq1pqYnddPXPqvjjj9K41MrtTJRUveIZ+vS67+n2Ipliq2M6bzLP6xHPO1UxTIH6t9/KZ3ypy/Ub+74oZ77tEeqEF+hXPVA/fhnd+uUJz9S+bGYHnbY4fqve6TfciT0hj9If7hDn/rQ25QJ0rriysv1na9coerqmMrBpNLZqlZn1uiKK67WD278kHpTMV384av0vks/o/GphJaNTymW6Kh32FO04Q/3Sevv0YZ1sNPrdMVF52hqLKaxsZWKjaX01BNP1T0Q2ZI2bLhPt3z5RhWS08omEsql0k7y9hf2PwI/rnnvXejwRS6fe8eAY8Ax4BhwDDgGHAOOAceAY2BvwICTvAu7zuAL/B5vx4BjwDHgGHAM7P4YcJLXic1RxKbXbcVFrDfoqzfoadDrqFLr6GGPPUmXf/brmoznFWSyylUqOuJxj9ed99yn+9bfp9v/921qlMeVSo1rOijqoEefqMs+/x099pSX6NeS7vzDb9UetHTtTbfp0cedrNhYQg8/5GD98N+/rE47r1e99fzw+GW+9asNd+kn3/8XdVo5pXMppbJplQtZXfGh8/Vnz3qKKskVagSrVE6NqVJIq1goKpMuqpQrqZGNq5QaVyabUzIoamJiSvFkWsumUoqNTykxNa3sdFyT41OanpxUYiKm+OqY4lNxja9OamI6rdVTCU1MTSmdSiqTjKsQpBWk04u6g9d+2NoOXst9J68vehg2PHcsOAYcA44Bx4BjwDHgGHAMOAYcA46B3Q8DTvLu/gvNThb4HDoGHAOOAceAY2BhMeAk71Yyz4lNj8UoDMQ6m0nemX5H7XZHqWJHmVJPuWxZpWJZ+WpNxVZbE6lAU/Fp5VIrVcyMqVwOFBTLShS6Gi+s0bLSPlpZ6iiemVQyuUyTqQmNJxIaTwQam5hUNrNSqWBCy4OGVpXWanWqoOmpcZUzK1TLjykIppQt5JXNV1TMFdUMJtVMr1KzmFWzWlGjVg5Tp1ZVtVBQo95QPl9Qo9lQqVxSIpFQOpNRIj238zidTCodT4akbmI6ruT0tNKJpIJURpnNKZVMh/3CHcuplOLxaQVBRqlUSov9g9nIXcud5N39fsAvNobcvmPGMeAYcAw4BhwDjgHHgGPAMeAYcAwsHQw4ybuwi8K+CO/xdgw4BhwDjgHHwO6PASd5ndgcRWx63VZcxDozczt5IXn73bYajbnUbbbUazXV7rTU7LaVr5RVKJdDQrVULqpULatQrSpbaShbaStT6igoNxSUsgqKSeUKGWXzgTL5nIJcVsV8WgWuCxWlCjUFhbJy+YKKhZyKhaxKxYJKxWJILFdLZdVLebUrRfUbTc10uhr0uur3Ogq/IdzrqNVuqtFqaDA7q3K1qjTkbCatTDoIUyKZVCKVUDJJSiqVoi2jXCatfCatbDqpIJ1SJp0OyWEI4kwQhAlidbF/CBu5a7mTvEvnh/liY8PtOxYcA44Bx4BjwDHgGHAMOAYcA44Bx8DuhwEneXf/hWYnC3wOHQOOAceAY8AxsLAYcJJ3K5nnxKbHYhQGIjt5u5rptdVpNtRtNdVvNTVot9TttEKit95qqt5qq97qbk4tNTpct9RotdVskJqqtmqqNCtqNqtqNapqNGtqNOtq1Gtq1smbqtebqtUaqpLqLdXqrbBvq9GQpXazpW6rrdluX7O9gQb9/ubUE98R7vY76vQ72me//UL7HPUMyZvN5JTN5JUOgvD453SQUiqTUjrIhgTuHMmbVD6TVDadCHfuZoKs0kFOmSAXHlGdzTjJu9D/Wfk3eXe/BQpfVPI5cww4BhwDjgHHgGPAMeAYcAw4BhwDO44BJ3kXdlF4odc13J7Pr2PAMeAYcAw4Bh58DDjJ68TmKGLT67biIvwmb3/QD3fIslt20Oup3+lqtgvp21Wv11e3N1BvMBNJA/VnSH31Z3phgnid6fc0GHTDNDvoaS4NNLtZ/0xI1K7RoL9WA4jbXl/93iBMM/2B5trnyFzKc6kb9h/0ZzToz2q2N6PZ/pz93sxA+x9woNqdriBz00F6jqjNFpTJ5pXOZZXKpZXM0hbMfWM4yCofZJQPUspl0wqy2VA2Q59MXrlMTnm+RRzs+A+1h+JHre3gtdx38i7ufDwUc+w6fU4dA44Bx4BjwDHgGHAMOAYcA44Bx8DegwEneR/8hV9fTPeYOgYcA44Bx4BjYM/GgJO8W8k8JzY9FqMwELMdsiFB2+tqjmwdaBbCtj9Qd7BWvf4aren3NNtth7tpe4O+BjMQv311Z9aoN7NGMwMjc+d22qKvHx6x3AuPWp7ttzXb74ZELSTvbH+OrIW87fdm1OvNhKTu2n5LJOzTv9tvqdNvqR+SwLNa05vVoDurVn9fNfr7au1+B6rZaoUELyQvO3LTATt5swqCtHKZRJiCzBzJm83mlMsGIcGbzWbuR/IGmbzy6Zzy6aVH8hYKBa1Zs0Z76n9avpN371nY8EUsn2vHgGPAMeAYcAw4BhwDjgHHgGNgb8SAk7x/vAg9MzOzx65z7KnrNws9LsfIH983Cz0Hbs/nwDHgGFhMDDjJ68TmKGLT67biIrZlx+yAHbXsxh1ozcxsuHu22x+o2Bio1uxqn3peBzRzIdHbR3ZmRu3+GpVb+6vS2l/NRjc8jrlWq6lSrYi8XC6pUq2qWi2rUc2r26yo126FNiCQSb3BbEgkt7prw+OZ96untX89qX6zGn5zt9IpqdQqqN6sq9/pa/+1+6vXP0DZ1iHKdw5VtTWrYrmiZDqlyelpTcVTiidSmpqeUiEVVysxoVZiUoU0hG5+c+IHdSZMQTYX7uSlLRvklQ9TLtzJu5i7eW0Hr+W5XE7777+/eLmd7wUXotTSYj54H4jttWvXqlqtysZtuS0AEAeSXXvui0OOAceAY8Ax4BhwDDgGHAOOAceAY8AxsDtgwEnerYvkrF3Mzs6OXN+wdQ/LH8gaw0PRd5RfthZD/lDYfCA6t+XbfOtLD8Te9vpG/dlevMw/cpO1uu3Zod1s7Yisy2y9Pz0WHgvHgGNgKWHASd6tZJ4Tmx6LURiIzdqxyIOZuWOZ+/uo3Z3VzOysqs22KoODdONN39DzTjhWBzQCdevVkJxdM9tTuztQpXeYvvaNn0kbJd23Ttpwn7TxD6Ji/YYNWr9J2rCJqt/rhc85SZ1GNTzWeYbjngdzx0C3+mtV7h6gc97ybn3sQ+/X2kpCtUJWpVpZN9x6g2YPnlWhlFe1VFKrWlah2NBfv+Ui/WqjdK8U2rgP85LWbZQ2Sdog6Q933qUndBvad2pMpWRi7ru84fHMgYJwF2+gzBDJm9tM8uaDxd3Na+Sm5fxgtR9A873Q2survfgupYfxjvqyzz77OMmb9QWa3WGBxn10nDoGHAOOAceAY8Ax4BhwDDgGHAM7g4G9leRlDcOSrQ2wbtHlM2EjdvKa7Hy56bB8WM7qH6rc7EX1L+X1mG35xlii41iIctQfyjtiEz+3dbqd6Ryli7bFGOcoX7zOiTPHgGPAMbDzGHCS14nNUcSm123FRSw8hhmid2ZGrd4aFZoHqNY/RLVWR/laQw97/NN123fvULdZVzk1qXK+oFq5pG49o0o5q0RlH13/5R/oqJlDNTM+qZnESg2y42oX06pVa0oV2krlmqrmArWLGXUalbnv/4bf7+2p02mr2ppRsn2Irr31x7ru+ptC1nbTho26b8M63acNulv36r4N60Pi+L9+9K/aZ01XL3/rhfq7S7+oqWxd8aCmmSOeris//y2tns5r9URKU7mObrrxVh1TLejQ8ZiqiUmlg4wyuZQyuaQyubQyWSd5l9p/LJC8lUrFd/I60eu7tR0DjgHHgGPAMeAYcAw4BhwDjgHHwB6Fgb2R5GWticQfrVsysm4+gs/6zJcPr2MMyw23b+t6Ph+21Qd71m79yS1Z21LJzS/zNepXdCzR+oeyHPVnlE+Q/51OJ8QN/oEbMMN6UavVCsvU03c+/6m3NuTa7XbY3+oeyvG57p0ncDxmHjPHgGNgWxhwkncrmefEpsdiFAZCkndNb47khWztHHC0vv+fUKvS3Rs26LfsiNXmf+s3lzaul+79lQ4+cFaTPboFiQAAIABJREFUQU/XX/8dPaa+j37x+S/oRcc+TvXkSpWDuFLxhB79mGP0b9/6rjrVsmq5lJrVsnrdjnq9jvqDnhqttoqNvo573iv0ia/+b62I97ViVVmJ6UDpVFKf+/L1aq3ta3U8ofTUKg3SMVVTy/RXbzpfb7zkS1oRLym2Kq32Icfriuv+XSsm0lq1Oq4ViZq++Pmv6bhqUYcui6ken1Qm4MjmlIJcMtzJmwl39d7/uObdaSdv9OU0+pK8rYfiUm9zktf/En5n/hLeZR0vjgHHgGPAMeAYcAw4BhwDjgHHwO6Cgb2R5GUN4sQTT7xfOv7447e5K9MIOsuNHCa3OlsPIY+2U8bmsFx0LcT6UjeKZIzKjio/0P6jdD6UddsaY3Qs8/mwIzLz9R1VH12/GvbN2ujH57z23XdfPfvZz9bJJ58cYuhZz3qWDj/88LANWWQggKNpGA8md+SRR4ZYifo0bD/atiPlBzs2O2LTZZwMcww4BvY2DDjJ68TmKGLT67bi4o9I3mzrUE0V91ey0NIhhz9c//WrH6nZDrRiZUyrxsc0HY8rlZxWORhXamqVpuJN3fz5f9PjslXtF4vpWzffpg9e8mFNxtM66vDDdO9//ViHdIvKxlerVMirUa+Hf5HX7XfV7vdV761VvjmjG/7lW3r3hZ9QbOog/eQXnMFMWq91Wqd7tSk8llnr7tUrjt1PnVUx/eUbP6CfQURvPpr591JISN+zSbp34zrdAy99zzo9PpPQw2IxNaenlcvc/whm+x5vZvO3evkm71IleePxuIrF4v1+rNgDfdRLKXXbStZ3MXL8sr/MxL69gPNyzC7eVCo1719r+zd5fQFnd1nAcT8dq44Bx4BjwDHgGHAMOAYcA44Bx0AUA3sryfvJT35SV199dZg+/vGP69hjj92yG5P1gAsuuEB/9md/FtaxXnDJJZds2clJ+6Mf/WhdfvnlWwg61g6MXLP83HPP1TOf+cwt9fwBOX0e//jHb9l1a+sf9MEOOWsTVr8z+UEHHaQDDzxwl/tvzxZYwUeTe8QjHhHGx663ldMv2jcqy5iHU7Q9WkbuhBNO0Kc//ekt+qiLyjyYZfOZOWHeIHOpO/vss/WZz3wm9IP8L/7iL0IsmDy7e/GD6+c85zmCCMZP9Ji/hx12mF7+8pdvwRiy1p++yLF7mDKYo+2JT3yinvSkJ+kpT3mKjjnmmLBMTj058299zQ7XJNMftWFtnjtB5xhwDDgGdg4DTvJuJfOc2PRYjMJAbLbfU/hdXl6AZvbVZR+/QXdtkn4j6Xd8Z1e/lzb9Whs23qN1fGd37uO7ku7SHT/4d9XrD9Ot131bTwgKWhuLaTJe0D9c9bmQo93wuzv1mJm8WhMxlYJpNdsdtTqz6s3sq06/p06/q3qro9ef8zbdvUn6+ws+pWWpo3T9V+9SIdVWanxC13/pCyq0m4pNZPWNL39Fr33yGs2siOnFZ/+jXn3xTVqWrGhsIqF9Hn60rrr2q4qtGlNs1TKtnJ7WLTfcoCflg5DkbUxB8uZCEhciF0I32EzuWp7NLl2SF3IT8jOfz4fH0/CDhf8QeGnlBXR3+8+BF2ASf3XJWHjxLZfLWwhe+xYxefRHsZO8vkgSxYOXHQ+OAceAY8Ax4BhwDDgGHAOOAcfA7oKBvZXk/exnPxuSdNdee21ItBnxxVrGK1/5SkHQUv7IRz4SrhFceOGF4XoBOzj//M//PCTU3vGOd2whfo1QYz2EdPDBB+uKK67YsjZi5B59zz///D9aL2EdwtZQkDV/rG5H8o9+9KO6+OKL70fmoWdXdA3bg8SEDH/qU5+6xU+IcsjwYdlR19vyw9ZiovkoHdQhA8kLQW/jstjP1+fBqIdsZT7f+ta3hqQs80Ws8QMsvehFLwrjYD5h08Z8+umnC0Lc/DcZ7r2/+qu/Ghm/P/3TP9VLX/rSEJv0f8lLXhKSzODnpJNO0jOe8YzwDwhOO+20MCcmL37xi3XEEUdssTMcF/PH7D8YcXEdO0cKebw8Xo6BPQcDTvI6sTmK2PS6rbiIzfDiRhrMqNXuqlxtaTxoq3jYSfrct/5b5UxWU7GYxlet1MqJCU3EJ5WOr1BlMqZgLKZl4zV99Ybv6/HZgmZjMcVWZfWYZ79E2iT96nv/obXpmIrLYipmJpUr1VRu7q969yAVa1U1m3l1ygldcfEF+l8vPUvvvuB6xaYO0Y9+Lm3ivOjwqOh1+p026bcQzvdJf33MWnViMb30LRfqpNdfrNjqjGLLV2ntw5+gj137NS0fG9fKsRVaOR0PSd4n5wMdHIupPjWtIJMLyV0IXghdkhG86SArUpDJKh/klA/uv+t3oX80RklOIzrT6XRIgiYSCRUKhfAllpfd6LdK7EV9KfxHZi+1o3zBT/thVa1WtxC5Ntbo+KOxd5LXF3CiePCy48Ex4BhwDDgGHAOOAceAY8Ax4BjYXTCwt5K87L6EoLv00kvDdQzWMCB1IdM++MEPhkfysj4Akcn6wWWXXRaStxzR+4IXvEAvfOELQwLO1juQZb3B1kIg3F71qleFR/qyWxPi+IwzzgjrXvOa14Rlri2xC3fUOsX26ozIIz/11FNDAtTWPaL59vRsr52dy694xSvCuJgsJOSoXcnWHs3Nl2idxW5UHpWLlpF9qEhedEdtDZch/N/1rneFMhzFfPTRR4cYAkeQ4MP9wQJyxA2ilpyYQcwie+ihh4bXtmHC7NFGAlOQuU972tNCPeATknf//fff4gNYJLa0QTQzT1ybDtNJbnNAHq338p5DOvlc+lw6BhYOA07ybiXznNj0WIzCwBaSd8BLSLerdrOlbH2N/vwtH9Ev53hWaR2HIUvrOEF5033S+jv1yX96q4oTy7R8qq0vffFHOirXVDcW09+8/m36t5/+WqVcWe96/eul3/8f7VPPqpBcqVqloNl9Dtft//m7UNd99/1Gzz/xGAXxCR1z0kv0dx/6smLLeoqtaGjZiqSWL4/p+hs+oVorr9jqtG75ym16ybGHhaTxaX/7fv2cE5k3H9f8O3Ye4+NGTnneFNZvumejjk5nNpO8E0oHgVLZktLZkvJBoEKQVi7Ld3ozSpGCICR5cwE7fpcWyQvpCclrRG8ymRRkLwQpL6P2Umn5Yv9Hgx/2Ukt52B++q8KROvwYZ0xG6nINkTvfj3QneX0BZz5seL1jwzHgGHAMOAYcA44Bx4BjwDHgGFjKGNjbSV7IV3bOQpKRIF0h0SAv3/3ud4e7V1lHgORlHQGS9y//8i/D43rtyOdPfepTIkHoIcPaAtfo4Zhe5CHgIH4h6cipiyYIv+gaxag1i2i7lfGZsvlP2dY9ornJ72w+nx/ReuzsrF7k0TFfmk8f8lGS1/pvT5/JDec704+d0m9/+9tDnxkzuq688spwRzhzyhwM62demWerh4RFlmt2e4M/7sHh8YJJ8ATBC9Eb3QkOuYyexz72saEusMo1f6DwqEc9KtRl9qJ6Hww8RPV5eeHIJI+1x9oxsPQw4CSvE5ujiE2v24qLWJ8XRF6Y+G5Er6cWJG+1p1h6X8VW15Qcjym/OqbJqdVaNR3X35x1hv7z9u9qUEwqmJjWsomWbvzi7Xpc9yjpZ3fq32/8gorxMaUmVml6KqnXnv0u/fbudXrBiY/X/s1pNSsVtTtrVK7WVamWVSvllQhKOuKk0/WGS76i2Fhd51/2z3rZy1+rXGpc3775ctWzMa1cGdPkRFKFyUmlpuM675Of0ymveaPGkgmtmEyp8/Bn6PLPf1exlSmtWJVUbLqlr3zh33RMrqqDYrFw5/FkclIr0xWNp8rKJyZViq9QJjmmRGq1Eum4kpmUgkygbCZQLrv0fhwbERolfI34bbfb4UspL6aUR71kLvR/UvZSiy/YxjdexHlhNr+N4LXr+UhcxryUf6y7b0vvfvE58TlxDDgGHAOOAceAY8Ax4BhwDDgGlhIG9laSl92XJI7RZcclawWsD5BYH4C8gzjjG7oQvCTKJL6xyjHFfJ8VeXb+8i1U1hm4ftOb3hQSf+hkvYGFYMi34QRJd+SRR96P4OMP5g844ICwjv6sW5gOvhFsx/YiY+QhMtiGPLRjgenDkb98pxWf+DYwO4r5nmt0HYZ+2OSbxC972cvCnaXsNmXnKbtEkcUPiEV2Jts1OTtTsRPVB6n5vOc9L9R1/PHHh7axYWOhDLn5/Oc/P9zRil7amAP00E4ZvXxnlvGijzjRhgxjYe4o09fq6Qcpyk5ZjjQm7sigy2SIAfXMsfWHeMcfk0OWMuQpxymzQxrC/mMf+9j9SF5s086R3/ZNXrMT1Q3RzzU2GRN/KMCcEAdiyjzik40F2ySuiSGJviT+WIDv8aKHnPhwhLbFCsxGfcCuJ4+BY8Ax4Bh48DHAc3tHCL1arbZDcjuiy2W2Eogei6Ufiy0kr5G9vKiV6h0983kv1/9ZL11wwbkKksu1empKV37s47r5ps8rl1ymei6hbDKn8eSMbrjxJ3rtc/9GR5XXqDu+TP1glcrZhCaTgVakW0oWmjrmkWvVDWLq1YpqNtqq11uq1ZuqVGuaKrR0xKmv1ZmX8k3dimLTRV3xkY9L6+7UlR96gyaXxTQ5FtPk+JSyqZwyQaAbb/miSt2SVk2s0PLJjJoPP0mXfeGniq0sKTaWV2yirS9/4dt6TFDVSb2O1v9/P9OTn36s1h75ZP38rk065YTjdPTDZ/X7O+/QCSceq3hmOiR505l0SPIupR+C5ouRvEaIkvOdXhK7epFj/vjRYC/M9h8LL6zRZPUPVY4tXorJeenlpZoy392N+k/ZxmVE7qidvNZmsfDcF2scA44Bx4BjwDHgGHAMOAYcA44Bx4BjYHfCwN5M8l511VXhrlvWCYwYIz/nnHPCnbisF9i6AesUXLOuATnLcc8QlKx38K1Wdu/SBtkGQfzpT396S1/I0re97W1hYieoJb7pG90Zio1/+Id/EN//pWx+QVyya5idxez8JOfYYNtdbGsol1xySbjrkzHQ981vfrPe8IY3hLLYwQeIyih5i89vfOMbQ9IaUhjSkG/vQviyY9Z0QzBTzzUnoJETP8ZPGZtnn312GIszzzwzJIDxD5u0ETvkIF/RQ4w5thod5PhBu+l6y1veEsYQXbSzixZSEz1G8tp8oJ9EXDhSGfKZMvaZD4sj8uywhgjHHr5TRyzf8573bMEAPrCjmzkkfviALvsmL7aQoe+JJ54YYsFIXhuDjQPCHPLdfOCbzvhEXwhxSGf+WCC6E5hNEpDKkLvMFQQ0ZeogefmDAvwHm7SRs+ZG22Me85jQVtQPLz/45I7H1GPqGHAMOMm79ElGJ4IXd45ivOyQjOTl2OZWu6NSraF0qaZXnfN34THIf5D0wQ/+k1KrY0qNxZRNLlciGWh1ao1u/MIPdXB5rSqxZQqWxRRMjimXSSqVyWgikdbqyUkF8RWqZlerUghULVdCkrdaa6har2qqUNcjTnmNzrr0a4ole4olSrryI1fqYx+7THf8z8/1nR/9h6qFooKJKRXTcZ16wuP039+9WjPZmHKJlRqbLql52LN14XU/V2xlX7HVba1MNvXl627WUcWGnrl2H93z6//UE572VM088ljd/puNOukZx+kxh8zot7+5Q08/4ckhyZsIUoLkXaqEYpQMNaLUSF5+2HKEM/V8r5cXT15Eoy/EC/Gfotmzl2rzA3I3n8//EcHrJK8vyuxOizLuq+PVMeAYcAw4BhwDjgHHgGPAMeAY2FUM7M0kr32Pl7UCWy+AzLzoootCgo/1iquvvjokWCH8PvvZz4bXEImQsbZDk929rGGx9kDbE57whLA/Oqkf9c3V6FpIuP61mSh93eteF5KzrJ1QD3kMuchuUiMmsQNZCvHI+gbXyELyHnfcceFYkIVghVBl9y7tyEISs/MYghMZdvpCWEMSIoMuiF5IUtONr6eccsqW7xMjRx2EKfKUqWOnMv5aLCHDIaftKGpISuLIrmHksc8iOUQv5Cd60AfBTBzZrYwMdba7mbKRvCZPHaQw5DryVg/xyhxTZ2NjPo866qjQRyN5IXg/8IEPhCfQ0Rf9kMr4TwyoYw7x6a1vfWvoDzZJ7PZlTBCsXGOHhDxjYhcyRC8+kCBz7fvL7OSFkEY/JK591xc57EJGo4Odv/iMXuwwn/gGocs1eOOaHcHk9EenJ4+BY8Ax4Bh46DDgJO/iEohO4C79+MfsAcSLYb8/CFO321G7VVOt1VaiNlCivo/Sxba+ftttuuOHt6lXn1CxGFcyyCuZX6PbbvmxdB8fx90krb9P2rhem0ibNmjTpvV8yVcIvP5vzlC9WgqPhh70eSEbqNfvKt/o6onP/Wu9/Yov6TO3fE/3/l/p15z5asVTU4pNTWu/Rz5Kd/6fO6VNG/XNr9+ka646X+965dPUnYypXUwpmW2offBTdennf6CZI07Wz++Sfr9RuuPHd2hNKqtKbLmS4ys1Hk8oligrNplVYnKVMhMxJaaXazK+UtOZaYUkb5BRJsgs6aOBR5G9kKVG+FLmR2elUglffHnx5wXV5vqhzO1l2nK+GWz+4B++Q/ZGx2A/kKmj7Dt5fdHEMOG5Y8Ex4BhwDDgGHAOOAceAY8Ax4BjYUzCwN5O8kKKQm5B9EHQQiRCOEGqQgUbksZZA2dYUIOkg2tjhyfdSzzrrrC1rG0cccURIIEKcsubBuhakpR31bDm2KV988cVbTj6zHbKsj9CXBEkIuWw+QP6hEzLPSGrakEUXBCVl/GUnLySv+Y5edsPiG2V0cdywydCPeEA+chw116Ybkhcy03wjh+SdW7frhzGkL7bI0U1/CGp2PFPP7lj6mA7qkINUPvfcc0MZ2iBrGYfFGznqbZ4g15kf6ki027xh02TxA5/ZkWxjwT5HGiOD78hA8kLao4fErmcjX60fvkDy2s5ks8uuXOI5TPKih3HRj92+yHGvIceY6X/YYYeFx2LbuDg2mnHTZnbZxU1CD/WMBX2Q/BDAEMjEg3rqmDvTj7wnj4FjwDHgGHhoMOAk79InGZ0IXtw52kLyzr2cQfJCvvJC11a92VChWlemWFEGYi4fKJNLKJNLqlSvqVBtKMjXFGRKysUzKiZSKmXTKhezqpSKc6mcVaWcVbWUU61cVKtRV6fV1qDX10x/oF63p1anp2SxpnihqnS2oCCbVZpdtbm0Uvl8mLKFrHKFrPLFokqFnAqpMVWCCfXwMV/W+FRaK6cDLZvMaflkVssnkhpfPaXkqlVKrxpTYvWEJiamtWoqqfGpacUnx5ScXKGpqZVaPb1KiSChZDatdJBWkA3CtJR/SBpJCoFqyUhey+PxeEimch49f9loL6oPxn849kKOLrBjCRvY4sUZspZjpOcjbW0MOxNndI3StzM6XNYXiRwDjgHHgGPAMeAYcAw4BhwDjgHHgGNgoTGwN5O87NaEEGOtYHhNwohQ1hnYjQpZCBnKTlv6UM+xyhy5zI5K62/rEFFCFHn+0N0S6xPsaoVgJDei1HJb0yBnh+r73//+LQQkdtGHzWGS145rNl/YdcrxzNG1Er7fagQp9rDP+DgyGN/x7Z3vfOeWXaX0ZU2Fo5wZE9foJzfCljK6yCEg2QnNLmOOgYYYNZKXOkhS9GHL9EBS4gPXtFFm8RwZrqlnzOQkdr1GfUGG+cJ3kyGn//nnnx8S2eYfPrPjmDbmnfr3vve9Ou+887b0ZZ4hUBkPMiTkIZ8hgE03diFl8XeY5DV7yDLv7NKFsGcXM/3wlXsPkjY6NtNNjn0jeSnjAzkJ/ZDVEMnWZn057tn6k0cTtukbrfPy/WPk8fB4OAYcAzuCASd5F5dAdAJ36cd/JMnb78+q2xuo0+2p2Wqq3qiqUiupVCsrX60oV62p1umr3uqqWqupXC6pXKyoXCyrWi2pViupXquqEaaiGrWCmvWK2s2GerwA8ULKSxQ7hzs9tZstNZs11elXLqhSzKlQyitXzIdHD+eLeWVLWQWlnLLFknLFivKFskrFivqdvqqlspJTE4pPTWhyOq7V0xC5CY1PxTU1PaV4fEqJ6YSSiaQSyYSSqWllUlNhSqWnlUjHlcqmwwTJm9mNSF4jSsmN7CXn2o5vZucsZCsvmPyw4aV0Rx6g25Kxl11y9PKibIkdxEbE4suoH85Rv0e1z1fnJK8vxMyHDa93bDgGHAOOAceAY8Ax4BhwDDgGHANLGQN7K8kLSQjhx1HCo0gvI0JZU2CXKaQcZCUkL+sNrDtQD8E36qQyiEJbv+C7rhwHHE3/9E//FBKQEIzYN8LR1jXoSxl77KqlTB3+IA9RCWlqxB/5zpC8yJuuF77whSFJCunNjljIa+xBFpIjG93Ja+MyYtZ8Yzfsa1/72pA4Nv34CCHNNe0cA43/XKOHHKKUHb92DTHNjlTTa/XWB1I4SqIjx1wyD9G5pB7CGYKVeuaNXdGQo5Sps/nFN/TTh3GxK9bsmX0Ia0h96kno4Ijka6655n4kL3rRw1oX84oc8TvttNPCMn2RiR7XjI1oMv3s0IXoxU90cYQziflnNznHP7Pz/Mgjjwzr0ElfdIFZ7EJAc5/bOPAnasvL94+9x8Pj4RhwDOwIBpzkXfokoxPBiztHW0jeuRtq807ewRq1B/uoBdnb76ndaanZbqjeIjVVb7XUaLXVbLXVaDbUqDfUrDfDvNqoiBRObK0WkrvNelmtRi0kebutlnrtzhaSlx29XHdbTXWadTXrVTXqVdUapJoa9boazbpqraqqrapqzboarZbazbY6LY572VeNelO5ZDpMmVRGqVSgZCpQIp1RIhMoEaTDXboQuUE2oyCbViZIKhMklA6S4e7dTC4IyV0I3jmSd/f6cRwlTSnzwzZaB9kK0csuX15YeQHlZdReSHfkgRqV4SU6mnjB51vA9oMaW1H7Vj8q3xnidmdkR9nyut0L1z5fPl+OAceAY8Ax4BhwDDgGHAOOAcfAnoKBvZXkZecnRC47KaPrCla2naJ2nC9rDXy/lp2o7PqEVONIXwhc2+lpfZE1kpgyO26jaxWUWfcgh3Sk3/BaiBGF7IzFF9ZLTD9t+MJxz6aXNkhedrmaPnYBQ9pGZTiuGX3YQw+ykJfIWD9IQLtmrQbZKMlrbUbyIg/piD/ECz0k5CCOIcepZyerHQ1ttthJzI7fs88+O+zDOCFm+Xaw2UYPyXSPInkZO8cdG4GJPNjGR76by1jRh32uGRM+IA/By5xSxzVzjE/oMD/JiRMxtXr04evwcc02d+Qk/ObIbo7GhpDFBn35A4PTTz89tIH+aMIGsYDgJfbEDnKaMb7gBS8Ir/lOMxikjgSZC/GLbmywyxfSlzLt+GHjjtry8v1j7/HweDgGHAM7ggEneReXQHQCd+nHfx6SdzYkeduDtery8jPoqbcl9dUbULf1ITQzmBHf2OWbvp1+R+1+Z65fr69+D0KXxO7d3mZyl128c2nAyx4vgIN+mPo9Xsw66vQ66nQ76odEZFfdQVfdma76M30NZgbhLuCZ/oz22/8Atdsd5VKB8qlA2XSgTDqrbJBXkM0rFWSVzAabSd7UZpKX7+5C7iaVyWYi5G5WGcjRzWl3/CFpxCq+W9ly2+nLMc7cnLx02gvzjjxQozL0iyazF42Z2SWP1g+Xd4a43RnZYTt+7YtDjgHHgGPAMeAYcAw4BhwDjgHHgGPAMbBYGNhbSV7IVYhYdtSOWoNgZyjkGDs12YEJkQu5xi5TiFK+p8ouVXag8h1eW4tgjYKy7TSFcIPohFwzgs3K5PiAbshASD2+o/uud70rtI0efMDGOeecE34zmDUTdnJC3pLoZ+sio0heO67ZZIzkZZcu9iGrIUIPPPDA0G/sYYPc/OTaSN7oOKMkr33HmJxxQC6+6U1vCnXz/WDsWyzYDYsMejkGGj125DU2IXEhY/EVGb6VDKkNOYseiE/iho+m9znPeU4YD2KDHfqwI5mdw/iMXnKOb8Y+i/PIcKQ1cWOXNTKNRiP8zjL2IczNT0hWMAHJi01kbczMdfS4ZtrxjblBDt/oz70G8cp3nC2OtquYPtHEGPkDBOQ5Ohp/6WNjpkxfSGKrw5bZJp4WL2Qh0yGFmfcoZqI2vXz/OfB4eDwcA46BbWHASd6lTzI6Eby4czSC5GU370C9wUyY+oPBHKFrxK7lkZeiQX+wheQ1QhgSeNDvazDoaTDoatDvzV1TF0mQuKT71ZmNzTrQBbEM0byFXA4JZL63sZ9arZaymUDZTFZBmHLKZudI3iCbC4lbO4KZ7+1mw+OY2dFLmvv+rhG7li/Wj76H2q4RrvatXH7g8CLPi6i9FNvL6rYerrzY8sLKUdAcC21+m3679twXUBwDjgHHgGPAMeAYcAw4BhwDjgHHgGPAMZANiSd+e+/Ib+5t/R7f3drYfUmCuOO4Yvy3OEAS0sa1ffeWdnakQvpB1kEM8n1VCLiLL744JNpYkyCO9OcIX7uG5GXX5nBCj5HBrINwGhm7StGNbRJ1EKaQ0RC2JMoQp5C/yOAbtvADApH1FOqiO3m5JnE0MgQ3Plo/vvkLYYwvtDF2SM7jjjsu1M+YICqJFfawRV98QQ/X1J9xxhkhYQtpC8HK93/RTdzQgQzy73vf+8K+2GMnLGSl+Wc59ogDccQO5CzfDUYHBDtj5/u46CN29KMP8wUBTMwhzG0OsA+BC/FpMujguGP6QQbbOhQ22PkKiY8u5DmGmqOziSlzgsx73vOeMGbIQPJaXCw/6KCDwqOiOS4a+yTIdMhWyFuIX8hcxgUWGBc54+EPB8ALPtGP8UHUQkyjl5y44j/14BK/SKyjoQdi3uYGrD7xiU8M/bZ4Waw9dyLLMeAYcAzsPAac5F1cAtEJ3KUf/yGSd+dvsrkH09wxz5DDIQkLGWskcEjMRq6tfmfyLSTv1h3E9tLGSxUk79Zdo3NEbzYL0Usa9WN6juiF7J1Lo2T23Dpixa5ejm5woJK3AAAgAElEQVS2ZD8AeCnd1l8ampzpgOBFB/psDkbHfM+Np4/X59Yx4BhwDDgGHAOOAceAY8Ax4BhwDDgGtocByCB+UxuRtGXdZGfWR3ZDWYhIyDmISwhOdmVaHIgF9ZBikIsWG9oh3yAmIVONzIMAZHcohCOyEHP0h3hDBrIw+j1eyujliOBrr702tItuYo+8JepIRtpG54bjkaMENHZNh/lr8lbPtem0nN2y+DMsww5Rjl9GF/5AhBrxbSQh4zWfyRkv8tRbG3qpg2Ad9os+rPXYH/ebf9gz/6xMbr4gzzUJX5DlD/7NF2uLjilq29qpQwZ9+E5ufrOmx7WN1fyhjn78YQAYsgSRi17kaIeI5Xjmk08+OdRjvlkOMQvxSjtkrx3BTJzRg1w0sUPZ5CB2IZVJ2CVRZ8niz05kfIBQxg76bHxR3V6+f6w9Hh4Px4BjYEcw4CTv0icZnQhe3Dl6EEneuR3AO3Jj7pKM7e7d/PLFixzpj0neICQbt/fjam8leImLEbR2fLMRvZVKJXzB5YXbXqotJ9a8cHPDGplLf0jeKMFL2/Zj7z/+PUaOAceAY8Ax4BhwDDgGHAOOAceAY8AxsHdhYG8leV//+tfrzDPP1FlnnRV+D5Zvm9q6EEQYu0tZb6DM2gNtRuCxsMu1EX62FmRy1Nu3Vul/wgkn/NF6BjKQeXxzF71m23SZPasfzjmOFxLW6m2dJJpH2yijO2qLtSt2sPIdV9qtL2V2ifINWnzEVzuq2sZousmjpGTUf9NJe9RutK/JRPsNl00eP0wPc4NeZKmjzXSZvOXWh2vkLY+WqUPOxkKbEby0mW3qmX9ww/eYwRCJGNLfdt5SJr5mw/SbL9RbGzZtLFG80YdksuZDtJ46wyk6uDZ5s2k59dZuOjx3Mssx4BhwDOwaBpzkXVwC0QncpR//B4nk3bUb9IE82OxFatdJ3r3rx+Tw4oERvEbKGvHL8cvVajV8WeaF2RJ/CWpHM0MKG9Fr+bB+v9678eXz7/PvGHAMOAYcA44Bx4BjwDHgGHAMOAbuj4G9jeSFZLMEKWakW3QtCNLMyDArI2d1yHINITdMytk17Ub4sVYU1W/lqO2oDH5h12yYPHUkriGh2SFsbchG9dl19A/mTZbc7PG9YY6Itm/i4j+EJUclswuU9S2Oi+bo4/e+973hqXX0NVvko+LI2LFDu/lt47J684d2dEaT9bc6duramKhDF7npsjZy00vOeOhrtk3OZEy/XQ/3p324j8lGc/MlWmdl608Ohsjxh3bK5Nafaytbu8kYtqweOfSYLq6RxYbVIWv6zbbpszbPF3792GPuMXcM7P4YcJJ36ZOMTgQv7hw5yTvyOOf7/xDbE3+YGjm7rbxcLos0SsZ27+6JsfEx7fn49zn2OXYMOAYcA44Bx4BjwDHgGHAMOAYWGgN7G8m7vYX1UQSYkWfRvlG5KCkXlYmWkdkRuWifbZUhZSFi5yNxh/tG/bU2/IEM5Bhgjo/m+GqOrn7nO98ZHiVM+0knnRQePX3uueeGxDLy1Ef1GaG4s+MzefJRCT8hJknWbr5bbjrsmjzqW7TeytE+pjdaF5Wz+qic1Zncrubz+Wm20IvMsJzZj8bF+pDPVx+V2VWfvd/uT0z5HPocOgYeHAw4ybu4BKITuEs//k7yOsk7ksTlGGb7wUt5FNFLncl47gskjgHHgGPAMeAYcAw4BhwDjgHHgGPAMeAYmB8DTvJuf7HXSLX5Fsa31z5fvwdSz+7XUQTgjug00tD6k0PUWj06omOyeurYYWv9kLOyyQzbn68+KofeUcn8iLZF+1nZbGzLF5OxPpabbruO5tG2aDkqsyPlqF9RP6zedAxfUz+qzuTNp/lykyMflom2eXn7zwCPkcfIMeAYGMaAk7xLn2R0Inhx58hJXid5RxK4HMlsRzqPOp7ZSF//AT//D3iPjcfGMeAYcAw4BhwDjgHHgGPAMeAYcAw4BgwDTvJuf+Eagmx4cTd6vb32qOyDVebo3geqK0o4RnVB+A7vBkWWcZLTFpV/oOVhAtKu0Wtlyx+oreH+29IbbYuWh3Us1rX5NF8e9WtYJtrm5e0/AzxGHiPHgGNgGANO8i4ugegE7tKPv5O8TvKOJHmNxJ0vtx+pnvuChWPAMeAYcAw4BhwDjgHHgGPAMeAYcAw4BraPASd5d8+Fa0g7FpyH8+FF6G1dz0fyUh9tMxvb0uVtuyeOfN583hwDjgHHwK5hwEnepU8yOhG8uHPkJO9eSvLuyA9wI3h3RNZltv+D3mPkMXIMOAYcA44Bx4BjwDHgGHAMOAYcA3svBpzk3bXF3aW0KG4kLLmVd8Y/+kRJ3Z3pu6uy5uuu5rtq1/rtql3rZ3oWKzc/djVfLL/d7u7/vPE5/P/ZOw/wuMoz3x9ZliyNNPVMUR/Vkdxww8bgbnCTu61i2QYbAyFANoVN2SSQbOpdinuT3GQbkpByN9kbQkhISCDZTbIte3N37+aGJKRBIGCDsdzL/z7vGb3y0Xgkq1iakfT383z+zjlz5pT3+83onPOb9/vYhmQgygAlb2IFIgVu8sefkpeSt8NxdSl5h+7DBz54YtuTATJABsgAGSADZIAMkAEyQAauLwOUvHxgzwf2ZIAMkAEyQAbIQPcYoORNfslIEZzYNqLkpeSl5CUDHTLAhzrX96EO48l4kgEyQAbIABkgA2SADJCBocsAJW/3HuryITjjRQbIABkgA2SADFDyJlYgUuAmf/wpeSn4KPjIABkgA2SADJABMkAGyAAZIANkgAyQgT5mgJKXD6opK8gAGSADZIAMkIHuMUDJm/ySkSI4sW1EydvHN3H8lfbQ/ZU2255tTwbIABkgA2SADJABMkAGyAAZIAPKACVv9x7q8iE440UGyAAZIANkgAxQ8iZWIFLgJn/8r6vkrYxEYC99+SVcUVEBKWPHjkVJSQl0/Fit9SaKNW+oyQAZIANkgAyQATJABsgAGSADZIAMkIFEM0DJywfVffmcjNsmX2SADJABMjAYGaDkTX7JSBGc2Dai5GUmL7vkIgNkgAyQATJABsgAGSADZIAMkAEyQAb6mAFKXj58H4wP33lO5JoMkAEyQAb6kgFK3sQKRArc5I9/jyRvu2zdygpEKiWDt9IqVZFKVLVm9Pb8w12JSKTz0pbJe8NYFJcUw2f6rGKaPiurN9G/0OX++StxMkAGyAAZIANkgAyQATJABsgAGSADZEAZoOTlQ/CePydj7Bg7MkAGyAAZGJoMUPImv2SkCE5sG/VY8lZFKlAVKUekUkoFKiNVqIqMxPWTvFWIRDouFRURq7vmMTeMRbikGG6/Fx6/FyJ5/T4Tfn/AKgEzgHhFb7JY84abDJABMkAGyAAZIANkgAyQATJABsgAGehrBih5h+bDaUoJtjsZIANkgAyQgZ4zQMmbWIFIgZv88e+R5BXBOypSjlGRMlRaojcqeaOi15bJWxmxsnwl0/eqEunsgy1ZvCJ4R3ZQqiCStzxSAZG8RSXFluD1mjGS1wwiYAYRjCkiffv65o3b5wMCMkAGyAAZIANkgAyQATJABsgAGSADZEAZoOTt7DkQX6MAIANkgAyQATJABq5mgJI3+SUjRXBi26jHkndMRQnGVpRgVIVk9FZawlVEbjTDN9qFc0VlBB0VS/p2KHqvLXnLIyp5x6C4JAzT9MLvk2LL5KXkpczu4zGV9GadNR/ckAEyQAbIABkgA2SADJABMkAGyEBnDFDyXv3glg+zGRMyQAbIABkgA2SgMwYoeRMrEClwkz/+PZa8oytKMKaitL3krYqgsqoC5VWlCI8Mo3BUUQdFXgujIG4pRsGoYuSPKkH+qNLWUob8UdGSN6oMeaPLEBpVitCoEoQnVsKsyENm0AlnwA2fJXtN+K1umpnJ29kNJl/jAwgyQAbIABkgA2SADJABMkAGyAAZIAP9wwAlLx9id/YQm6+RDzJABsgAGSADVzNAyZv8kpEiOLFt1CPJW9k6Hm9VpMzK3K2MyPi4EVRUVaJkZClKJpTAN84H13hnu+Ic74RzvAvZE9xwTPAgc6IHGRM9GDHRg/QJbqRP8CBtghdpE3wYPsFE6gQ/UicEMGxCsK2kTAgiZVIOUm7MR8qUAgy/pRDGpBCMonQY+Q5kBdwwrWxeP/y+gFXYXXP/3LDywQDjTAbIABkgA2SADJABMkAGyAAZIANkID4DlLxXP7jlw2zGhAyQATJABsgAGeiMAUrexApECtzkj383Ja90oyxFxtiVLpmj3TJHu16uRElVCXLG+nH/5ntw166NuGPP+rZy++61uH33OqzfvR5rdq3H6l23Y/mu9Vi263arLN25HlIW77gdi3bcgdu23YFbt2/AnG0bMXvLBszcfIdVpj9+O6Y9vgFTH7sLNz1+N27Zfg9ufPQOjP1EPYziVAwLOWCaHgRMP4JmIG7hmLzxbzh5I864kAEyQAbIABkgA2SADJABMkAGyAAZ6BsGKHn5ELuzh9h8jXyQATJABsgAGbiaAUre5JeMFMGJbaMeSN6qK6I3UomKyiqrVFZFkD/Sj3dtrceGA8tRc2AJVhxcguUHFltl2f5qSFmyrxoL9y/B7ANLMf3gckzbvxw371uGqU1LrXJT4xJM2rsMY/auxMjGGlTuXY3Inmip2L0SUsp21qB053oU7bgd4cY7kLO9HrlbGzDyU2tg5I6A6Xcj4PchaIlekb3tiwhg3rQyBmSADJABMkAGyAAZIANkgAyQATJABshAfzFAyXv1g1s+zGZMyAAZIANkgAyQgc4YoORNrECkwE3++PdQ8raK3sqo5C2vjKB8ZCnyxntwV9Ny1DbPwvLDc7D4yK1YdDhaFjbPwbyDszH3wFzMOjAf0w5WY9rBZZi5byVmN9Vg9p7VmLu7BrN31WDG7jpM3r0G4/c2YFRjDcobV6KwaRlym5Yg1LgYob3LEdhbD++eBngONMCxtwZZu+tR8ncNMEqy4DOd8Pt9VjavCN14pb9u4rgfPjAgA2SADJABMkAGyAAZIANkgAyQATJABih5+RC7s4fYfI18kAEyQAbIABm4mgFK3uSXjBTBiW2jHkjeaJfNFZbgjaCisgKlVSUoHJOHBffOxKaDy1FzaAZWHZ6BZYdnorp5NhY1z8HCQzOx6Mhc3Hp4EeYeWoYF+2qwfO96fPB/fhK/xB/xB7yJP+NtvIoTeA2n8Gscw7sPPYx5WzZg0vY6lOxZidymZZbkDTQug9lYC3fTGmQdqMeIxhpk7WtAyWNrYZQ64Q96LcnLm2jeRJMBMkAGyAAZIANkgAyQATJABsgAGSADycAAJe/VD275MJsxIQNkgAyQATJABjpjgJI3sQKRAjf5499Nydv6hVMpcldLBUpGFiN/TAjv23EP7jm6GnVHZ2PV4elYcWQmFh+ejerDc1DdPAMLJJN33yIsPbAGu/73fvwKL+NNvIMTOIOTOIsWXMBZAC24aJXjOIPf4k187PkdGL1lNSoPrkHBvpUI7lsJb1MNnE11yNxfi/SmGqTtrUXBlrUwKpxICzrhCfjg95udFN7kJsNNLo+BHJIBMkAGyAAZIANkgAyQATJABsjAUGCAkpcPsTt7iM3XyAcZIANkgAyQgasZoORNfslIEZzYNuqZ5I1EEKmsQESyeSOjUFZVgfCoXHx4133YcGApVh+ZjRWHZ2HpkVmoPiIZvDOx8PB0LNw3BzX76/CBpz6MV/EKTqMFZ3AOLTiHv+AdvIK38Ce8hWM4jZM4jxM4i7dxBq+iBSt2P4CJOxtQtHsFzMYVcDVJ9m6tVTIaazC8sRa+7WuRWjsJRoEDmSFPazavyN7YovKXN9JD4Uaa50jOyQAZIANkgAyQATJABsgAGSADZCDRDFDyXv3glg+zGRMyQAbIABkgA2SgMwYoeRMrEClwkz/+3ZS80a6aIxGp5cunChWRMSirqkRBVRAPbr8bdxxYglVHZmHZkdlYcnQ2qo/OsiRvtYjfA9V47sRz+DP+jFN4x5K87+AUXsVxfO47O3B703tx5/6/xlO/+Q5+h+N4E6dxCuetDN+X8AYWbL0bo3c1IK+pFp5WwZvVVIPMplqM2L8G2TvXIP/T9TAqHEjNdceRu3bZK6KXN7mMARkgA2SADJABMkAGyAAZIANkgAyQATLQ9wxQ8vIhdmcPsfka+SADZIAMkAEycDUDlLzJLxkpghPbRj2QvFWW3I1ERiISGYWKyGiUVJUjb0wA799zN25vrsbKozOx9AkRvLPbBO/iQ7fhzqO34xX8CS1owWmcwWt4A5saH8DCnfWYsbcGN+1djSm7ajB5Zw2m7q7Bpi9/GK/hLZzDRRxDC17GCczafg8ie9Yj0FSH7H21yN5Xj4zGaJfNWbvrkCNdNlcOh5HnpOSlxKbIJwNkgAyQATJABsgAGSADZIAMkAEykBQMUPJe/eCWD7MZEzJABsgAGSADZKAzBih5EysQKXCTP/49lLwieKOlvHI0ikaWoOq2EtzftB4NhxZgxdGZWHJ0ppXFu9Aal/dWLG6aj3/GT3EMx3AOF3Acp3DP7vejurEeU/cvwaTmZRhzaBlGH1iJkQdWoLRxPiY3rsYPT/8Cb+McTuMC3sZFfOvE/8HErRuRu6cezn01yJJxeZvqMXzPKjj21sK1rRbGTU4YBdmUvLyRT4obef4ivu9/Ec8YM8ZkgAyQATJABsgAGSADZIAMJDsDlLx8iN3ZQ2y+Rj7IABkgA2SADFzNACVv8ktGiuDEtlEPJW+lNSZvRWUlyipHI290EVZ/fCE2HVyO+uZ5WHF0FpYcnY7qozIe72wsaV6AmgMr8Wu8BOme+S2cQeO/fREL96zFjP3LceOBRZjQvARjDy3DyP0rULFvOUr2VaNy7zJM2bEOX3v9p3gHF3EGwCu4gHmPP4DwrrVwieRtjEre9MZajJCM3l01MO67BUZBliV5A34TUvytJeD3QUp0njfByX4TzOMjo2SADJABMkAGyAAZIANkgAyQATIwGBig5L36wS0fZjMmZIAMkAEyQAbIQDwGqqqkR9kIKHkTKxApcJM//r2QvOWIVEZQXjkKuWPycP/+dVjfPB+1h+di6aFpWHzkFlQfmY6FR+ZgafMirNlXi9/hd5bkfRMtqNl3N2YdWo0pB6ox8eBCS/KOP7gcE5pqMa6xDiP3rUJk32qU76nBnF334HWcwkUAx3ARSz//VyjbsR6uptq2TF7HgQak7F6F4U11KNq8DkZhliVzA6YfUvSGMGiakELJeyUmGhvWjAkZIANkgAyQATJABsgAGSADZIAMkIG+YYCSlw+x4z3E5jJyQQbIABkgA2TgagZE8kqh5E1+yUgRnNg26oHkrUQkIiWCsrIyVJRXIG+UH/fuX42GI7NRe3QWVhydjsVHbsaiVsm77NBifPSZD+OP+APexjv4C05gaWMDbjlUjckHFmLSwUUYf3Axpuxfhdt2b8CcbRswefc6jN3XgLLGGkzfcyf+ghZcxCUcwxls3PUQyrevg7OxBo6mOoxorEN6Yx1SG2uR0liH/M1rYRS7EDBNS/AGzABMfwB+fwAh049Q63LeuPbNjSvjyriSATJABsgAGSADZIAMkAEyQAbIABmIMhAIyPMIP0Ty8iHu1Q9xGRPGhAyQATJABsgAGbAzIHJ35MiRGD16tFXC4TAoEhMrEhn/5I1/NyXvlS+bsrJSVFVFMLIygqIb/LjnwArUH52BmidmtJO8C47MgUjez7/4WfwZr+IkTuEveAtLmuow9dAC3GhJ3mpMPrwMM5pq8O/4Hf4f3sBnfnIIN29fj1H763Hjzgb8EcdxFudwAufxviceQcW2dXBZkre1m2ZL8tbBaKxDrkjevBHR7prNAAJmEKY/aEneHNOPHF/77F7eePLhAxkgA2SADJABMkAGyAAZIANkgAyQATLQFwyo5B03bhxGjRpF0Ru58mzJ/kCX04wLGSADZIAMkAEyIAyI5JVrprFjx1rTlLzJKxgpfxPfNt2XvJUViFSWo7y8BJVV5SgrC6Nogkje5VHJe3QmVhydYXXXvOjIDIjkXXqoGh96+kG8gj/hJFrwOo5bkvem5oVWV80TDy7ClOYlqP/yvXgZr6EF5/Ea3sLjP2rGhL1rMGlPA36JV3HcygJuQe3W96N8+1q4O5C8OVvWwih1whs0YfpMhPwh+PwiegOW4M2l5G3rvrovbmC5TT4YIQNkgAyQATJABsgAGSADZIAMkAEyEGVAJa88oJw4cWKb5K2oqGib5kNtPtQmA2SADJABMkAGyMAVBkTyTpkyBaWlpaDkTbxIpMxN3jbokeStrCxHJFKKqlFlqBpbikmLq3DXgaWoOzoDtU/OxoqjM7Hk8HRUH5lpjcm7pHkR6vfX4Lf4NY7jOP6C46jZcztm71+OydaYvIswaf9C3Lp3NX6FP+ItnMRpnMGreAvVu+/B9G3r8Pg/NeP/4lX8F97E9Ec3IrxjDdx7a5DZWIMRjbWt3TVHM3nNrQ0wbszB8EITTr8PoWAOTH8IfjOIHJ+I3gCCtnF6eePJhw9kgAyQATJABsgAGSADZIAMkAEyQAbIQF8woJI3FAq167KZkvfKg1w+1GYsyAAZIANkgAwMXQYkcze2/ceMGWP9OE4ELyVv8gpGyt/Et033JW8kgspIBSIVpSiPFKF0TD7e+/gmbGpeironZ6LGkryzsOTwDFQfFsk7F9WHF2Dl/qV4Cb/ESbyDt/AOnnn5OazYsRYzm5Zj8sFq3Ni8GNMPrcJ7vvu3+E/8EcfQgpM4h1dwAo89fxBzH78dk7c14IZd61Gycw1Ce+rgaaqFo6kWGU3RMXmHN9Vb3TU7djQg9LEaGAUjMCzHC38ghICZg6CZi5AZQtAqQchYvX1xA8dt8sEAGSADZIAMkAEyQAbIABkgA2SADJABMiAMiOQ1TRMieSUbZfz48daDzPJy+QH90H2gy3Nn25MBMkAGyAAZIAPKgIhee5k0aRLKysooeIsSLxEpcpO7DXoseSsrSlE1ugSFo/344N57sbF5MWqfnInVT87B8qNRybv48KxWyTsfi/ctwA/Ofw+v4zUrS/c43saDBz6MJbvWWKJ36oFlmNS4GFN2rcAHvv93+DWO4RjO4jTO4y94B5/+URMmbK1D+d565DbVwd9YY0nerFjJ21SHtJ1r4HtkPYzKLBj5HvgDInRzEPLlImjmIGCK9KXk5QMHPnAgA2SADJABMkAGyAAZIANkgAyQATLQ9wx4vV5IEdErDy1Hjx4NyeRlNi8fbuvDbdZkgQyQATJABoYyAyJ45QdwUo8bN866ViopKaHkpeQFJXPnkrlHkreqshIjI+WoHFWM8IQgHmy8CxsOL0LtkzOw6snZ7SVv8xwsbL4Ni/bfhtsPrMUxvIlzOGfpW+m6+bP/8AhW7FiPeY11mN60GpP3rMbUnfV473cfxX/hNZzEWWv9N3ACNVvejXFb61G0pxbBva2StzGayZvWVIdUyeRtqsPwXfUIbt8EY5RIXhcCAb8ldkXw2iWv389MXt7M9/3NPGPMGJMBMkAGyAAZIANkgAyQATJABoY2A5LJ6/F4LNGbn59vid6xY8dS8jKTmdncZIAMkAEyQAbIQCsDInilm+YJEyZABG9hYSElLyUvJe81GOiR5K2MRCzJWxzJwcJNN+M9+9bg9iPzopL3C7OxzJ7J2zwbC5pvxYJDt2Fl0wp85b+/hmOQPN63cBoteBPH8DL+hC//4Wl89PuP4iMvbMGsbesxc+9GvO+7j+H31ron0YIWvIa38fCPmzB25zrktXbXnN1Yi0zJ3o2RvO7N62BUDoeRl4VAwNeauStZvNFMXhmfl5J3aN9k8yEL258MkAEyQAbIABkgA2SADJABMkAG+osB6bZZimTzSi0PMadMmcIHu3y4Twb6kAF715+cbt8VKuPR9/EYylmZPHdmJXeXARnOQns7UcGrkldqZnN2ns3J+Azd+PRQ8lagKlKO4jF+fGBfA+48dBvWHp3VJnmlu+alh2dgiYzJ2zwb8w/PxbzD87Dg0GIsO1CDtXs34k94HW/gON7BCbRY4/SewJs4gWM4iZfwBm5rehdu3LEW7/3OI/i/+DOOowVvoQV/xEks3HIfSnaujXbXHCN5UxrrMGxnLVxb18G4wQEjzwG/3wPT54fpC8JvhhAVvJS8/XUjy/3woQkZIANkgAyQATJABsgAGSADZIAMkIEoAyJ47bGQLgnlwebEiROth5s33nijVcuDThbGINkZUF6FX8m8EpbtRZZJkfPQdfvjnGRf9tLR8dmPldPt247x6H08lH/9fu+IfXldi74nXq3raB27jrSZcH/TTTe1FfkxEQtjMBAYGDVqlPWjJxW8Ii1V8lJgDl2Byba/dtv3WPJWRspQONaDBw6uwPqj07DmiWmW5F35xCyru+ao5J2FRc2zLMl76+F5mHt4IeYerkb1wVV439c+gt/jVbyOv+AETuA0zuJttFjlZRzHuqc/gTGN9Ziwux7v+vZn8Uu8gT/hJH6Hd7DhyCdRunMd3E21iM3kFcmbsrMWWTvXw1g9GkZ+piV5raxdEbx+kbta2t9Y2W+yOM0HEGSADJABMkAGyAAZIANkgAyQATJABsjA9WYgVvLK9mWZvVzvfXJ75LivGFCepUtyGXdauiW3Fx2PWjnvq+OI3a798yTTHR2f/Vg53b7tGI/ex0P5F/5iGbXPy+ta9D322t4WbrcbLperrTidTmjJzs62tlNQUGDJMcqRa8sRxijxMQqHw1aXzDr+rsxruzCDN/Hto23BOnnboueSt7IMBWM9uL9V8jY8MQ11MibvEzOx4ugsLDs8E0sPz0K1dNd8eC5U8s5pXoS5B6sxf99SLG5chYYjd+EF/Cv+H/6AX+EV/CdexZNv/ABT9t+OiqZViDStxg171+L2pz+Pf8Kb+CnewI2PbkDhrgYrk1cl7/CmOgxrqodIXtpxuWoAACAASURBVGNPHVL2rEPgs/UwCjLg97tb/5Cq3GUWr/1CgtO82SMDZIAMkAEyQAbIABkgA2SADJABMkAGyAAZ6C4DlLy9F4F2gcfpwRVPFbXXS/KK4LVLXpW7WjscDuvHFpS8yStjKMo6bhsVuip9GauOY8XYMDZ2BnokeSOVFaisKkf+DW7cd2i5lcnb8MR01D8xA6ufmImVInmbRfLOxuLDc7DwyK247fA8zGmeD5G8sw4twMyDt2HO4WrM2L8EcxpXYdGuBizeeQdu23UHpu1dh7H7VqFs31IU71uG8v21KN+1BmP2bMTE3Xehcvt65OyptzJ5nY21cDTVwZK8++oxbF89jL31MPasRe7WjTCKRsCXb8LnN61xeTkWL29YunvDwvXJDBkgA2SADJABMkAGyAAZIANkgAz0BQMqyGTbmsXVF/vhNslvXzGgDAu/IrRiJaVKLtm/rttXx2LfruzLXjo6vtjj5fzgkqyJbk/lv68kr2T0quCVWiWvyDIVZnYRwGmKoWRmwJ7Ja8/mTeZj5rHxM5UMDPRY8kZGlmLUrCK8+9AyrDs6DQ1HpMvmmag9OhurjszBsmYZl3d2NJO3eW6b5BXBK2XagVsx/dB8TDuwCNP2L8P0/atw875VmNS0HGMaF2Pk/kUo378I4aZqhPevQH7TKuQ21iB/7xpL8Poa69q6a85orL1a8u5eC+8ja2GM8WJYvhvugImgGbREb8AMIGD6rWK/AOQ0b3rIABkgA2SADJABMkAGyAAZIANkgAyQgUQwoJJX60QcA/dJ9rvLgIrbjiSqSi7Zrq7b3X1cj/U7Or5ES0Duf2hIZeFPONbv945q/bxoHY8Pzea1Z/Rq983SXbO8h5KX4ikZxFNXj4GZu+S1q6xwvfis9EjyVlSWIzKqFOsfXIH7Di/DHV+cgfVfmIW1T85B/RO3YvWRuVjePBtLm9tn8sqYvLObF2HmoYWYdmgebjk0H1P3L8SUA9WYeGAJxh1YjDEHFmDk/nmo2j8f5fsXoHjfYhQdWI7cgysQPLAS/v218O+vh3dfe8mb2lhrddVsjcnbuAbG7rXwbLkDGetnwCh2wxEyETKDlugNmgEEKXk7HQvielxAcxu8OSQDZIAMkAEyQAbIABkgA2SADJABMtA1BvShP+PVtXgxTskRJxW3wq+IqVgppbJK2kvXTUTbdXR8scfL+aEhXfu7nYU/4V6/5zuq9fOidexxquBVqRsvk1feQ8kbX4RQEDEuZIAMDEYGOpS8VVVViEQicYtI3orRJfhU4wdx9/6FWHtkKtY9OQMNR2ej7vBcrDw4GysPz8Hyw3Ow9MhcLDp6G+YdmY85R6KSd4ZI3uaFuPnQQkw9tBg3HVqKG5uXYcIhEb0LMHrfPIzcPx8V+xaheN8SFO5bhrx9S5DTtBTBplUwG2vgbay1Mnmz9tZgxN4aDNtbA2NvbbTsqYOxex1GbN+AvMfugVHpxrDcaCavZPNS8ibHjUAiLuq5T7Y9GSADZIAMkAEyQAbIABkgA2SADJABMkAGrg8DKm47kqgqqyTeum4iYt/R8cVKNM5T8vYFA8KfcN+R3NXl+nnROvZYuiJ5ZZ3BKDF4TpRzZIAMkIH4DPRQ8pZh1IQKPLT7fbjv8FLcfmgGNh2sxqam5diwewUati9B/Y7FqN2xGKt3LsHKnUuxbNdyLN65AtU7VmDB9hWYv30Fbtu2ArduW4W521dj9vbVmLltJaZvWYppm5fg5s3LMGXLSkzcXIPxW2oxfksNbthcg7Gb12DU4w2IPLYGZY+tQfGja1D42BrkPL4GOVsakLu5Ab6t65C6Yz1Stm9A1qN3whjtgZEXHZM3YHXZzO6aE3FBzX1enxsoxpFxJANkgAyQATJABsgAGSADZIAMkAEyQAaSgQEVtx1JVJVVcqy6biKOu6Pji5VonKfk7QsGhD/hXmVuR7V+XrSOPRZK3viCg+KHcSEDZGAoM3BNyVtWVgbJ6tV63LhxqBodQcnofHx893tw/6GluL95KYxiAxkFqcjITUF6yMCwoAFDikznDrNKSm4KhuWntpWU/OFIyU+zipGfhmgZ3lqnw8gfASM/s7VkwCjIhFHggFGQBSPfASPsglHkhFHkgFGSCaM0A0Y4A8akAHzbNmH4rrvgemwTjDEeGPk+mP4A/P4g/FbNm4FEXFRzn+SODJABMkAGyAAZIANkgAyQATJABsgAGSADg4eBzgSqyippb0peCtRYaTlU5uVzoN95HQleXa6fGalj40PJS5E1lEUWz538k4H4DFxT8kqXzSNHjsTo0aMhglemc/KCcIUy8ckdD+KvG9fh/s01cOQMh9f0we/zwfR64TNNmMEAzEAQbq8Xpl9+seRrKzIfr/it9UwE5OKvddxcGT9Xx9CV5fJH0Qz6EcgLwmm6kF3gRsW8sci7uRSZOU4YYTfyPr8B6Vs3IOuRDTBuEMnrhU/e5w+0yt7BczGtFwms2aZkgAyQATJABsgAGSADZIAMkAEyQAbIABkgA/3JACUv5W2sjOR8eyYoeeOLCQobxoUMkAEy0HsG4kpee+bumDFjIGXUqFEoKSnBt7/1DP7lX36Gf/rpi/jhj5/F9/7pG/jOj/4ez73wLL73/PP43vd/gO8+9wN8+7vfxTefeQZf/trXEAgGYVpyVkSvyF2RrX74/IF25YqAlYxbf5vobSd5TblQNxHICcAddMGdl4VF91ajbuedWPy5NUjLdcDI98Bx5yz4Hr0DmY9tgLGoCkaBF95AdJ/R/fCCvz8v+Lkv8kYGyAAZIANkgAyQATJABsgAGSADZIAMkIHBxwAlb3uhR8HJeMQyQMnbe4lBEcQYkgEyQAbiM2BJXpG6krErRaZF6EpRuVteXg7pDsLr8eBnP/0pzp09i/Pnz+HchQs4cwFouQCcuAQcvxgtb50HWs5fxsnTp/D0M99CMEckrz1zN5pR25nkjXatHL3wlYzeYCDQVqR7F7fPA0/IA1dOJt77yANYv+cuLP98A9Jzs2DkeZDaMBX+zRuRtf0uZH1oFYwiX2tmcQj+QKhVOg++C2veLLFNyQAZIANkgAyQATJABsgAGSADZIAMkAEyQAb6iwFKXkrNWKnJ+fZMUPLGFxMUNowLGSADZKD3DBgicEXsSqmoqGgneeW1vLy8toHhfV4vfvTii7hw8QLeOXMKv/jNH1B738OYt+lTuPXezZh9707MvncvFt7zGF5vuYwLF8/imW8/Da/PBdMv3SVLkbFxTas7Z+nSWYtm98oFqCV4A0FLxoqQjVd8/pCVmesJuJAdykDZLSUITw7DGXTDyMlC6eZ7MWLXJozYcRdS7ltgZfJG98HumvvrIp/74Q0lGSADZIAMkAEyQAbIABkgA2SADJABMkAGBjcDlLzthR4FJ+MRywAlb+8lBkUQY0gGyAAZiM+AYc/aHTt2LKTIslAoBMmYlT9KVhav1wv5g/Tiiy/i/MWLOHnuPN44B/zwpbNY+N4mTL13P2689yhuvPeLmHXPbrx5Hjh74TS+9g9fgU+6T87NREbeCKTnj0Ba/ggMz5OSEadkIjXPgWEF2UgpcLYWF4z8bBj5Thh5Thi5Urth5Llg5GXAyEuDkTsMRlEGjIIMGFXZ8G7dBGP7Bvi23Q3j5nxrTN7oTYV0BR3tDpo3GYP7JoPty/YlA2SADJABMkAGyAAZIANkgAyQATJABshA3zJAyUupGSs1Od+eCUre+GKCwoZxIQNkgAz0ngFDxa52zSxBDQaDlti1/0GWP0ZSXnjhBZy/eAmnzl3CsbPAi786j+q/2ocpdzdh4j3NmHT3E5hx1068fg44dfksnvr2V7HknuWYde9c3HT/NEx8zxTc8FeTMfqvbsKov5qKke+5qa1U3T8FVfdPReSBm1HywM0oemAaCu+XMt0qBfdNQ8G7pyP33dPhv28mvPfPguu+GXDdNx3Z754GxwPTUPJoHYKb65GypQGObRtR9rmNMMqykJ7jhXT7rIUX+H17gc/4Mr5kgAyQATJABsgAGSADZIAMkAEyQAbIABkY/AxQ8rYXevbnqZxmbIQBSt7eSwyKIMaQDJABMhCfAau7ZumWuaCgwMrclaxd+wWIyl29YItK3ss4ceYifv6b41h+3xbMvGsnJm/ai0l3HcDkuw5gxsbH8Opp4OSlMzj8D0/gA1s/hE3b34WGXbdj1d56LGusRXVjPRY1rsGCvfVWmb+nDvN312PernrM2bUGM3Y34OZdDZi6cy2m7lyHm3asxeRtDZi8bS0mbFuLMdvXY+SOOxDZfjvKt0VLeGsDQttqEdzRgMDWO5H14DIYo9wwCpxwhUxL8PLmYvDfXLCN2cZkgAyQATJABsgAGSADZIAMkAEyQAbIABnoHwb0maH9eaJO63NFaQvpMTBRbdLZMeqxsqaQ7SsGKHnjiwkKG8aFDJABMtB7Bgy92LpWLRdDUn7wgx/gzIVLOHbuMt73uUbMuXsrZtx7CJPvbMTUu/Zi2qYduHXDp60xec9eOosnv/EFvP/zD+KBre/F3dvvxcadm7B+151o2HUn6ndtQt3OO61Su2MDandsxOrtG7Fi20Ys2bYR1dvuxMKtm7Bgy52Yv3kj5m3eiNse24g5j23EjEc34uZHN2Lqo5vayk2PbsLkx2TZ3SjctAhGmQkj34PMoMcaB1iyeH1+vzWWr4zPm6gLS+6XsScDZIAMkAEyQAbIABkgA2SADJABMkAGyAAZGAwMdCZQ9XmjnCclLyVqX0nUZN8uJW/vJQZFEGNIBsgAGYjPQI8k7+kLl/Dy8RbM3/gh3HT745i0fhemb9yKQ99/BUe/9zKW3PFhHDt5DmfOteCJrxyFu8CN1NzhMPIMGAWtpciAIaXQVuQ1XR42YIRTYISHwQinRkuRTg+HEZaSBqM4TinKtOSu4Xcjw+uGCF3tppmSlzdQg+EGiudAjskAGSADZIAMkAEyQAbIABkgA2SADJCBZGCAkpfyNtkla6KPj5I3vpigsGFcyAAZIAO9Z+CaklczeLV+/vnncfrCZfz3q8cwd92DuPmOzbjljq148rlf4vXTwLFTwNPP/hjvvNOCc2db8JWvfBFevwuegBuuoBOuYDayQ9nICmXBkeNAZjDDVjKRGZRlWcjMcSIzx4XMHDcyczxWycjxQEtayIW0XDfScl0YHlPS5T0hH5xBPzymaWXsquRNhotfHgNvwsgAGSADZIAMkAEyQAbIABkgA2SADJABMkAGBgMDlLyUvImWqMm+f0re3ksMiiDGkAyQATIQn4E2yasSN7aOvdgUyXv2IvD6qYtY94HP4ea1n0HDRw7htVPA8ROnceLtM2g5eRYn3n4LZ8+04MmjhxE0fQgF/Aj5oyUYkIt4X2vxwu+/Uky/z+pa2fSbVgau6Q8gfpGul014A76rii/gs17zBwJWF9M5oRCCgUC7EntenOeNFRkgA2SADJABMkAGyAAZIANkgAyQATJABsgAGegeA5S8lLzJLlkTfXyUvPHFBIUN40IGyAAZ6D0DRqzUjTevF7fy2rPPPouzFy7ixNmL+MG/v4S56z+Kex7aizdPXcQ7Le/gnZOncPLkaZw5cwanT5/Ck08cRdA0o5I3ILWJqOSVDNv2JSp2TUvQSrfKVtfKrWPoegN+eFuXSffL0XVFCLcvIo8DUkzT6qLZ72utOQYvxyAmA2SADJABMkAGyAAZIANkgAyQATJABsgAGSAD15UBSl5K3kRL1GTfPyVv7yUGRRBjSAbIABmIz8A1Ja8KXqnlou25557D2XPnceEy0HIJeP7nv8endhxBy/kLOHf+FM6cO41TZ06j5fRpnGw5iSeOHrUyaK1M3qskr8ja9kXlrtaW3BXB21pkucrgK9nA0axgS+62Cd72kjfAC/jregFv54LT3fuFK+PFeJEBMkAGyAAZIANkgAyQATJABsgAGSADg4UBSl5K3mSXrIk+Pkre+GKCwoZxIQNkgAz0noE2ydvxhWUAfr8UP+QP0je/+U0888wz+Pa3v4P/+Y2n8cWvP40vfeNpfOHLX8SXnnoCX/jSETz51FEc+cITaH7iKJr27WvrJvlKd83R7angVaFrrzt6TZfHZgEH/CJ1o0Ve023Jcet4vFJ3fJ58jbEhA2SADJABMkAGyAAZIANkgAyQATJABsgAGSAD3WGAkpeSN9ESNdn3T8nbe4lBEcQYkgEyQAbiM9CJ5JWulOWiVoRs0KoDgSBycvIRCIQQ9IfgNwPw+gPwBQPw+b0w/W6YARd8ATc8Mi5uMAAZF1fHww35A9Ai2xZhqzJW5a19Pt46HV1kisANthZZRzN/ZdoueZnRyxuVjhjicrJBBsgAGSADZIAMkAEyQAbIABkgA2SADJCB7jFAyUvJm+ySNdHHR8kbX0xQ2DAuZIAMkIHeM2DEXrhaQrTdWLkB+M0gAmYQfjMEnz8Ppj8Pfl8AAZ8fPl8AXtMPr+mFz/S0FhG+MlZudMxdkbySZWuNzWvVfohsFbHrCURFsYpYkcbeQDTTV4WsCmA51oAp24q+rscu64ngDbVKXtnWlfdE19fta63vZd29C3fGi/EiA2SADJABMkAGyAAZIANkgAyQATJABsgAGVAGKHkpeRMtUZN9/5S8vZcYFEGMIRkgA2QgPgPxJa8pcjY6zq3ZmskrkjdgSvZuXrRYkte0ZK8pstf0WaLXNL2Qou+XbpSDAZGzPgRNH0Ktslclrwhdnz/QloUr01JU3KrolQtHmRbBG7RKNEPXWt4qeNskr5WBbFqiVy84Re5qpq9M63LWjAUZIANkgAyQATJABsgAGSADZIAMkAEyQAbIABnoGQOUvJS8yS5ZE318lLzxxQSFDeNCBsgAGeg9A51IXs3GDcL0h6xM3qAZRI4viJBk9fpE8JoItNa+1kxe0/TAb7oR8HsQkC6cTR+s8XL9UckroleyemXcXM22lVoupEW+ijCOitz2UlYzcKUWmZvrixZdLstyTBW/sm0TckymdQze1kzi6DblPbxwZwzIABkgA2SADJABMkAGyAAZIANkgAyQATJABshA7xig5KXkTbRETfb9U/L2XmJQBDGGZIAMkIH4DMSVvFEBG+1u2ZTxeCWD1xqDNwemWQC/mQ+/zw+/zwfTF7Bkb9CXjaAvC37TZUneoF9Er3ThHO06OWS6kGO6LNkqEjfHNJFjCd8rF5Iiez1emQ9Z2bqamasZuFrL+wp9TqtIF9AyVrCsG5JunM0cmP6caNauLyqa/X4vApZkjnYZHZXMV/bLi3nGggyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADHSfAUpeSt5kl6yJPj5K3vhigsKGcSEDZIAM9J6BqySvXMyKbPUG/NFuk80ggtZYvCE4A0XICI5Gurfcyu71eTxw+XLxt3/7aXx5/xbkZhnwuUbA43bC9GTD63Yi2xuEx2ei0J+OPE8qvB4TpicHxW4vStwu5Eg2cCCIYDAAj8+HbDMIpz8HbrcXXrc7bgm4MlCQbaDEl4KgdA0dyIXb6YbpCyHLlQ/TG0aBy49Clwchnxc+rwd+nwdBv9fqMloyi0Vk88K9+xfujBljRgbIABkgA2SADJABMkAGyAAZIANkgAyQATKgDFDyUvImWqIm+/4peXsvMSiCGEMyQAbIQHwGOpS8nraxckXyBuHzh5DhK8DSDR/F8cvAZQC4fAnnrAkAF14H8Dpw6RSAS8DZE/j4Rz6INHcebrl1IV589ksocBvIy8nHj57/GaaWVKA4YwRCbieyHJlwuT3IcnuRZYawon4dLsl25b+45Qx+/sLfozSQCp/HCV+oEA5fIVKdBXDljMXvfn8SE4orUex0w+t0weN2I9eZhQJ3NkI+Eb7RbqT1YpQ1b0zIABkgA2SADJABMkAGyAAZIANkgAyQATJABshA9xmg5KXkTXbJmujjo+SNLyYobBgXMkAGyEDvGehQ8vpkTFtrnNyANR6v1wzA4c2D4SxDqrscmdleuN1uZGT78MmHHsJX934GQcOAM82AKyMVuZkGfI40GI58jJq+CD/8zlPwp0mmrwc//v5PcVNxBHcvWQJcPAVcOoMz5y7jAx962Nqu0+2zMnk9VjavF16XB163lGhmr8+djYAnA35PBnw+NxxmAd77P47iDwD+AuCMCOKLUs63Vhcxp6QYk71uFHjc1jjBMlYwL9y7f+HOmDFmZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIAPKACUvJW+iJWqy75+St/cSgyKIMSQDZIAMxGcgruS1j8nrt8a5DVpj6zp9ufDk3YDnf/oSLrRm8GoNvAlceAW42ALgPP7+4BaE3JnY89Xn8ZZk/eJt4MwfsLZhPf75p/8JnAV2fOxv8PN/fAbBUBY+/rnH8K6//luku3Ph8AThcpvwenzweXzwe034vT6YXh98XhM+qX1uuFzZcPsCSDdL8K7PfxENDx9GyS2r8c//57coDXjgSzXgcHvx4vMvYkFRASakGsjPzoJcfOqFKGvelJABMkAGyAAZIANkgAyQATJABsgAGSADZIAMkIGeMUDJS8mb7JI10cdHyRtfTFDYMC5kgAyQgd4zcJXkDZh+RMeslUxXE6bPbxWf6ceILC9SXcUwMguQmu5EyrB0DEt345MPfwJPNX0eHsNARoqBEakGPOkG3FnpMDJysGDVHfjPF76OUKqBlCw3nnnh57ghvwylmWn4j5/+A5zBFNz7qc9icu09MLKLYHiKkebwIsvhhNPhhDvLCVdmFpxZTmQ5PchyuuDMTocjy4FMbxGMrBLc/9kDWPfhx2Gk+bB4dQ3+/YVvwGkYyMp24Scv/ARzC3MwMsVAjiMDwUCAktffswt33vAwbmSADJABMkAGyAAZIANkgAyQATJABsgAGSADygAlLyWvStTs7GzItDAhPUA6nU6r1tdja5Gf9mXynq4W+/tkWrYVW2LXSdQ8JW/vJQZFEGNIBsgAGYjPQHzJa5oI+EXyapfGAeuPsy9QgENffg5nZAje1kxe6RXZ+nfpGHD5eHT68iXg8ls42rjNEsIHn3oWuHQMv/nZ/8Lv//InXJC1zp/GOy/9Av/+Hz+EWR7E1i8/ickr6/Cez+7AGxdhjfUrw/GevnBZRvgFLln/R3cl+79wGr/+7W+x8f6P4R0AJwArY1iOQI7P6rj5/KsybHB0AOFTJ/D7Z7+OYp8bPq+XkpeSlwyQATJABsgAGSADZIAMkAEyQAbIABkgA2SADPSSAUpeSl6VpypoXS4XHA6HJXBlWSAQQEFBASKRSLtSWlqKwsJC63XZhr6/K7XuU+tYwSvz+lqia0re+GKCwoZxIQNkgAz0noFOJe8V0SvdGweQ7Q4h3VOGG6bOxze++TWkpRtISx+GtPRUpKcZSBlmYES2Dz9+/nt4oHo88g0D6b4b8L2fv4nvf/MpfKP5U1i1dCK+/qXNuKd6HFyGgV1f+HvMXnsXDj/VBH8oFUb6cKRl+eB0BTDc4cF7Pvt5/MvLv0VuwESeKxuurCxkW78Cc0HG7h3mCCElK4AvfvUpPPDhD+GWuvvx2jlgYqETOYaBTEcOfvT8LzAnEMIoQzJ5R8AM+mH62WWz/uKSNX99SwbIABkgA2SADJABMkAGyAAZIANkgAyQATLQEwYoeSl5VaLa5ayIzby8PJSUlFhit6KiAlpE9lZVVbWV8vJylJWVWbJXeBJJLEW3Z5/WZbrPgVBT8vZeYlAEMYZkgAyQgfgMxJW8QdNE0PTZsnlNhEI5cJv5rZL3Npw8/TouX/4LLuO0pNniEi5YGbrnJYn24gX89YIqRAwDD35sN9790D58/9mvIT/LwH/86DBe+PtH8R9ffxwbFk/H+z+9H480P40Xnj2IUJoBZ4YBh9MLp68Arpxi/OKVP+C21UuQkZ4KT0Y6PNkOuJwOazzeLI+JNF8xqmvuwG9f+g/4gy4Yhh8lkxbi9z//F5Q7RyAtzY8fPfczzDEzMNYwEMocBrfPQ8nby19p9uSin+/hzSIZIANkgAyQATJABsgAGSADZIAMkAEyQAYGFwOUvJS8KlpFwIqQ1cxdEbkidEeOHInRo0e3K2PGjIEWeV3WEwkcDoet7Hq72LVP674GUk3JG19MUNgwLmSADJCB3jNwTckbCJgIBPwIBkPw+gswwluOG6beimee/TKGpRgYNtxAaloahqelwEhNwbAsH/71xy/gQ/MqMNow8IlPbcPU+Wvxwne/im2fvAOfenAVvtX8KTxUNx0/+tIRjJm0EsdPAY+8ZwHKUgyYmQYc3hwYriL8zWc246vNu+BJMTA8bTi+8JWv4fDBRrizUuFwDENqthvl01bh1bPSJfNJ4PLbaAGs7psh3UlrD8+XT6Pp/tm4Mc1AKMOg4KXgZVdMZIAMkAEyQAbIABkgA2SADJABMkAGyAAZIAPXgQFK3sEreTVrtiu1ikzJ3FV5O3bsWNjLuHHjYC/212Ra3jdq1ChL9kpmr+xXxvVVySs/ENFjEcmr01Ins/TV2Mjxy+elsyLraok9Jz1fiYcWiY8W6SJb1qE06b00YQwZQzJABgYKA92SvL5AoSV5x0+dg4vn/gicfxmXLp22xuc9ff6i5VSt8XDPnsGH5o9CpXSXPMKLsTfNxc9e+Cq++5W/g8Mw8HTzo3hw0VR8d89OPPThR3Gq5TI+997lKEg14BphINOTg8jN8/GT//1LlPtGIJgi3UKnYYTLg4cf/giOHNoFjycNI7wmDN9ozK5/AP/642/DPczAkS99He/+4CPIdlXgJz/+bwS8eXjsY/dj9wOTMSbVQJ7TaB1rmN0185ezg+uXs2xPticZIANkgAyQATJABsgAGSADZIAMkAEy0N8MUPIOXckrElIEozAnY+6KoB0/frxVJHNX5qVIpq6UzqblNc32Fdkr0lcygWW7Kjezs7PbyVxd3lEdK0kTNU/JS1k0UGQRj5OskoGBlWCsBwAAIABJREFUx0CPJO+NN8/Aj769C2aqAXemgXSHF0ZWPoy0HKSkB/Ev338B758/GeWGgeEp2Rg7aSpefLYRrhQDI1INfOXAbjww5xZMSDNw6g8vob52KX79p19hUc0yjMjywBsoxEuvvIrqVSusbOEpk27AmdPvSLqu1S30xUun0XxgB1IzM2G4yjB37f3453982pK8R7/0ddz/wUfhcFXiH3/8KwS8hXjkY+/HtvfPQWmqAV+GSF53q+jlhX9/X/hzf2SODJABMkAGyAAZIANkgAyQATJABsgAGSADg4cBSt6hLXkLCwstOWvPyhWhK10va3fN9vF3401LV806Tq+8VyWvZP2KNJYxe0OhkJUBaxe1HcldXW5fN5HTlLwDT5pQdLHNyAAZGCgMxJW8AdNEwC/FB3t3zWYgH5neMKZMvQX/+O0mFDoN+LJS4PLkYMKMZXjlhAzIC7z6q99htCsNxekGPM4AptwyDd//VhPWrZoI4CwutrRgdnEYLz/3LWtc3hFpBkZOn47v/+JXMPPL8dAnPoNLuGyN8nv60kX88te/Rk7QB0dGKtIz05CZNQJfevIgVtfV4tl/ewnHrb2+A1x+CxetPcCqo0cjbvgccOk3eOO/vwm/i5KXN1KD50aKbcm2JANkgAyQATJABsgAGSADZIAMkIGhzkBnXZ8O9dj0x/lT8g5dySvCVrJvtQtmFbiauSvzdoHb2bx9PRW+9uxemZauoIU3yegVtlXmdlQnUuza903JS1k0UGQRj5OskoGBx8BVkvfKxZ90ZxwtgUAAUvyBENy+ILKdLnidqfBlp8DjyobT5UO2JwiHK4CMTBeyMxzwjhgOX2Y6shxOZGVnw5U9DO7sFGRnZ8DpcMCbng5v2jA401OQmTEcw7OykJrlxAiHEw5HNjIcmchwZCDD4bBKliMTUhxZDjiyMuHMzrS2m5btQVq2G9lZ6cjOHI4RGQ6kZ7gwQkp6NjLSHcgekQ73CBHSBnyeLHbXfB3GW7nCCW+mGQsyQAbIABkgA2SADJABMkAGyAAZIANkoGcMtD1zsj2rsEvba8VV19UxLO21vHat9/P1nrWbPW4SZ4m7XWrptLaHrG89W7S1s30bfT3d2THqsQ6FOlaGxp5z7OsyL20o8ZNpkasyX1pa2jbWrkhekbKSuStFZe31qFUayz40u1cyhsPhcNu4tXJcmZmZcYVv7Pklal5ipoxLLDsr+pmROvZ4tX10PF6pdTxeqTkm78CTMxRqbDMyQAZ6y0AnkvfKRZ5ecEutf2Cif1RkgHv5tZr80fG2/bGXP/j2PzD2Pzz6x0fWiS3293T2mqyn2+zoPfJHLctWZHvyHjl++UOqf1hZX2lnxoKxIANkgAyQATJABsgAGSADZIAMkAEyQAb6kwF95mTfp12A2JfHm5Z19VlVrBCR5fHew2XXl/FrtYG2AyVv4jN+VRJqHfuZ0eX2Wp/ByjKRu5KlK10oS/auiFfJsO1rySv7lP3I/iZMmGDtW5ZJF85yDsKY/Zh1Ovb8EjWvnwH57rF/v8WblnW1xB6vnpe2idT2Z+OUvJRFvZVFfD8ZIgMDj4EuSV75AxR70W3/I+T1+qw/UPoHSGr76/Gm7evGm479Ixa7jm7Tvtz+Hlnuiyn6Hl7MX9+LecaT8SQDZIAMkAEyQAbIABkgA2SADJABMkAGesJA7PMm2YY+v+msluc+8rrU9udBOq3PizrbRk+Ol++5mvOutIPEjZK3/yWvSsGe1vp5CgaDlmDVMXJFttq7XtYsXq2vRxavbEMzeVUiy9i8Inf1OEQ2y7HI8QlfXT1PPa/+quX7SL87OvtO0s+Sfn/FHp+eHyXvwJMwFGdsMzJABvqKgW5L3ngXZPIHSP9QXa+Lttg/ePbtdzRtf0+8da71erz3cNnVF++MCWNCBsgAGSADZIAMkAEyQAbIABkgA2SADFwPBmIlb+xzJ3mWo8JD61jx0dm8vkdq+3Mhmb4ex89tRKW8xDdeO2j8JU6xbdufsVOO4h3jYF6mUrCntbSfCFbNohW5KtMqc69VXy/Za9+PbFNEr3ThLEWPTdaJPU+VobHLtc2VT611+fWuZfvKe+z3UOy8HovUsceh56HnxUxeSqO+kkbcLtkiAwOHgS5LXv1DFHvxrctja12vozp2/e7O63a7+z6uz5tQMkAGyAAZIANkgAyQATJABsgAGSADZIAMJAcD+nxHa3u7qJiLJztUfqj06KjW9aS2yxMVK/b9cbpnTGg72WOt0xpzia20caJi3Nkx6rEOxjr2c6HnGLtc50Uayvi20lZlZWXtumUWoarZu3bpap++XlJXt6OZvLIPXab7k6xemZZ15NhkrF4pJSUlbVn+el7xao2F1p19z+g6Pa1l28q+fvd0VOtnJt7x6HlQ8g4c+UJRxrYiA2SgrxnotuTVP0ise3bhy7gxbmSADJABMkAGyAAZIANkgAyQATJABsgAGYgy0JHclfiomIsnO3oiW+zyRKZjJQvbpGefS22neG2iMZfYUvImtrtmEYMqCaXW9pJpeU3Hcy0oKLCyYzVTVrNlJXtWpavKXhWvfVXr/uJJXpW9sm/J5tXjlWxjeS0nJ6ftHO1S1B4HjUFf1/I50O+X2O+d2Hn9zEgde1zafvbz4Zi8FEh9LZC4fTJGBpKbAUpef88uYPUPM2vGjwyQATJABsgAGSADZIAMkAEyQAbIABkgAz1jQMWfXXR0JjlipUdv5u37kWk9BrZl99pS4hZPSEnbaIwlptrWiYhvZ8fYG4aS+b0qBOPVKglFEMq0tJO0i8pSGedWpaksE8HbVyK3s+12VfLKNuQYpWj3zZLVK9m+IntV7Ep7aTyu1XYdMX2t98V7XeMrMdbvmY5q/czE278eu7af1JS8yS1fKMfYPmSADPQ1A5S8lLxtvyRLxEU299m9GyfGi/EiA2SADJABMkAGyAAZIANkgAyQgcHEgIo/FR52wRFPcsQTKD1dFrsvPYbBFN/+OBeJW0dtpTGW49C27o9jit1HZ8fYU34G6vvsbSWCUNpFMl+1u+Px48db0ypYRaCKLJXanlHbmZy9Xq/Zj0G3qRm8sbUco3QxLctF9Mp5qKwuLCy0smJVkkrdWfspt/ZYdbb+tV6T7SiT+j3TUd3ZvvX4KXkpjfpaGnH7ZIwMDBwGKHkpedsuMvRigzUfGJABMkAGyAAZIANkgAyQATJABsgAGSAD/cmAio1ryZLevq6SxL4d3bfUIl7687wHw746E6gaWzlPSt7ud9es8Yut7fwq0/ZaX9dl9nmZFrkrr8lDfBGiKnhFiko2rApUFatSyzL7vArYzmr7+n05He/YNKtXMpLl/KQb57y8PEvuZmdnWz9M0PhorXHSeOt8b2vZnn7WO5K7ulz3LXXsfvU4KXkHjnyhKGNbkQEy0NcMUPJS8rZdZOjFBmveyJMBMkAGyAAZIANkgAyQATJABsgAGSAD/cWASsJ4UiNWcvTlvMoVOZ7+OvfBsB9tv3htozGV86Tk7T/Ja5eBOi3tpNP5+flt3RrrmLsia2Nlaex8X4ra3mw79jjlXOySV+S1iF6pZT8ie4VNjUdsHY/l3iyTfelnXdqhs6KfGalj96nHSclLadTX0ojbJ2NkYOAwQMlLydt2kaEXG6x5I08GyAAZIANkgAyQATJABsgAGSADZIAM9BcDIjxUZojE0OlE1CJW5Hj669wHw34kXvGElLSfCis5T0re7kvea30GVPrF1vI++zKZFzEobSXdGovw1G6ZJZNXpGg8yRorT+OtkwzLrnWcKn1FaEtGr8heeY89RvGm7fFXlu3Lujot79XPurRBZ0X3I3Xs9vUYKXkHjnyhKGNbkQEy0NcMUPJS8rZdZOjFBmveyJMBMkAGyAAZIANkgAyQATJABsgAGSAD/cWACA+VGSIxdDoRtYgVOZ7+OvfBsB+JVzwhJe2nwkrOk5K3fySvxN0uA/UzJePVTpgwwZK7IjpF7orwvZYgTQaJ25NjkPPSIu8X0StFzlvOXyS3TEtchE/pwlrlqcZPY2dnuSffS/I50M96Z4JXP0v6uYndlx6XHqfUctxaHA6H1fZ9LRS4fUorMkAGyEDyMEDJS8nbdpGhFxuseSNPBsgAGSADZIAMkAEyQAbIABkgA2SADPQXAyI2VGbYpYou689a5IocT3+d+2DYj4qpeO2kskrOk5L3+klelX1S24WfLpc2UfEXDoetzFURm1Ikm1W6MhbhaZegPRGpyf4ePT+p7ceqwlfioMJb4qTxi1fH47uryyh5k0eGUEyxLcgAGRhsDFDyUvLyxoUMkAEyQAbIABkgA2SADJABMkAGyAAZIAMJY4CSd2D/oICS9/rJ21hpGE822pfZBa9My2uyDRG8wWCwLWtVumcWoWkXnTIdKz9jXx/o8x1JXj0vkb0SGxW9IsDlxwgSQ3uc7dOxbdSVeUpeSqXBJpV4PmSaDCQPA5S8vIlL2E3cYPi1Ks9hYN+Isv3YfmSADJABMkAGyAAZIANkgAyQgcQzQMmb+DbozeeAkje5JK8IRRG60jWzyEsZf1ZKPMmrsnMo1yJ6Re5KjET4Si3LJI4iy1Wkq+jtitSNXYeSN3lkCMUU24IMkIHBxgAlLyUvJS8ZIANkgAyQATJABsgAGSADZIAMkAEyQAYSxgAlLyVvbyRzV97bmYiOFXLJNK9isaNaBaTWkrkqklLlrow5K0UFr3ZTPJSlbrxz14xmkbz2Eq8LZxG2UrRNusILJS+l0mCTSjwfMk0GkocBSl7exCXsJq4rF+FcZ2Df6LH92H5kgAyQATJABsgAGSADZIAMkAEycC0GRICIKBFp0hVh0pfryLGIELzWMfP1K1x3JlAlniq4huKYvHr+Wseyq6Kwq7V+TnR9yTSVZfKwXeSuZKTqmLsiM0XuUuxGruqmOlb0xnbrrJm9ElMpBQUFVlav/TtK28Bex7avzut3itSdFeVEa32/1rovlfpS69jLUjscDut7lPIleeQL24JtQQbIQF8zQMlLycsbFzJABsgAGSADZIAMkAEyQAbIABkgA2SADCSMAREaIjHsAkWlRn/XciwqZChyr4jczmIh8dI2jG0vlVXyfkreKOf2GKm062otIs++roy7KxJXMnfHjx9vCUkVu7Eik/Mdy1675JVpiaGKXo2rLBeO9XtK28Henh1N63dKZ4JXP0f6mYn3mdJ9UvJSGvW1NOL2yRgZGDgMUPLyJi5hN3Gd3SDwta7dSDFOjBMZIANkgAyQATJABsgAGSADZIAMDHQGVGaoPOlIlPTHcjkWFTIDPa79dfwqp+K1jworOZahKHnjxcS+TKVdV2t5r8Q7JycHIh113F3pYlhkb1lZmbWcQrdjoRsvNrGSV+Z1PenuWuIrIl2mS0pKIHJd2uFa7aZtrd8pUndW9POitb5fa90fJe/AkS8UZWwrMkAG+poBSl5KXkpeMkAGyAAZIANkgAyQATJABsgAGSADZIAMJIwBERoiMURgqMxIVC3HokKmvyTpQN+PxEvbMLbdVFZR8nrisq3SLrbWOMYul1jLw2Idd1fko4hH7ZK5vLyckjfSPcGrMldqu+yVeY2rxFi7bpaYy3rSDrHtEzuv7ajfKVJ3VvTzorW+X2vdPiUvpVFfSyNun4yRgYHDACUvb+ISdhM30G9iePz8tTwZIANkgAyQATJABsgAGSADZIAMkIHeM6CCUASGyoxE1XIsKmTYtl1rW4mXtmFsu6msklgykzf6QwYVdfFqkXe6XGIp0zLOqkzn5+db2aQiGXXcXZGQsZLSPs/pnglflb0aP52XWmKukl2mCwsLLf613ewCVpd19L0SK3z186J17OdJt2ffB8fkHTgihtKMbUUGyEBfMEDJS8lLyUsGyAAZIANkgAyQATJABsgAGSADZIAMkIGEMSBCQ4VWrNTo7/mOZAyFb8fCl5I3fpauMq1irie1yLxQKGSJXBGLIniltmfvqohk3TOhGy9uKnX1NZ1XySuSXYq0g9SSQS1daNvlq0xrm3f0vULJS+HTF8KH2yRXZGBoMUDJy5u4hN3E8Qap4xskxoaxIQNkgAyQATJABsgAGSADZIAMkIGhwgAl78BmnZK3+5K3qwJYxtgVkTh+/Pirsndjs3hVSLLuvexVqaux1HmpZZnEXtpFJa+IXpHvIlbkezs7OxuSYaui1y55Y8WufV7Ws5fYH7moNLbLZGbyDi2ZQ3nH9iYDZCCWAUpeSl5KXjJABsgAGSADZIAMkAEyQAbIABkgA2SADCSMAUpeSt6+/kFDZyI6VqRdz3mVcrF1R5JX5KAca2lpKUaOHGll7tqzd2WZFAre3otcFbg9rWOF77hx46z2EuErXWuriJW2p+SllImVMpwnE2SADFwvBih5eROXsJu4vr6A5/YH9k0i24/tRwbIABkgA2SADJABMkAGyAAZGBoMUPIO7HbuTKBqVqJ8lgfjmLyx8jZ2PlYYi8SVZRKX2HVlXuSuSEJ75q6KXa1V8Eqt0z0VlXxf92WxZvXaY6ftECvkhXlpV+VAZa9m7+rno6Na36e1MqMCWWpm8lIUXS9RxO2QJTIwMBmg5KXkpeQlA2SADJABMkAGyAAZIANkgAyQATJABshAwhgQwSESwy5DVGr0d60Shj8w6Lp4puR1xxW2HfGsy1XUybzEULv/lYxQKZqxqzJXRaJdLnK6+5K2L2KmbSO1tJt23yxtKlJYZG8wGLRq/bxo3ZHg1e9F+3egsCJF2aHkHZhChiKN7UYGyMD1ZICSlzdxCbuJ4w1T12+YGCvGigyQATJABsgAGSADZIAMkAEyQAYGKwMqM1R+2aVGf09T8nb/c6ayKl5bqcASdodyJq+yrZJOao2NiEGRglI0E1REob074L4Qk9xm3whiFb0ieEXWq/AtLy9HKBRqy+KWz4Qy0FEd+5lSfih5KYiupyDitsgTGRjYDFDyUvJS8pIBMkAGyAAZIANkgAyQATJABsgAGSADZCBhDIjgEJmhIixWbPTnvByLSMvBKtT74rwoea+dyStsa9alw+GweM/JyWmTu7FdMdsFrGaJ6rJ43QXra6z7Rtx2Ja7STlq0jaTWDG2pRfiKTNHvmY7kbuxy/Q6k5B3YIoYije1HBshAXzBAycubON64kAEyQAbIABkgA2SADJABMkAGyAAZIANkIGEMiNCg5O1+Bm1fCNuebHMoSV6VbD2plXHJ5hQZKOPuSuauiD8VuSoHuyoVu7Ie1+k/8auSV2uJvXa7LdPS3tLumtUrnzf9/hM+OpK7lLwUQ30hhrhNcpXMDBQWFqI3JZnP7XofGyUvb+ISdhPXkxsHvmfg3vSx7dh2ZIAMkAEyQAbIABkgA2SADJABMhCPAZUcIs5UZiSqlmNhJm/3OKXk7TiTV5iWzF3J4pXuqlX6jRkzpq1rZsnwVBHbHcmr72HddxJX20Pra8Va5a7Wsr59WtpaJK+OuSyyNy8vz+rFIFbw6vei/btQf1zA7pop5663JOL2esJUGEVFYYSLitqVa8VS17/WekP99d4IXnnvUIrfkJG8AdMPKfFuJriMcSEDZIAMkAEyQAbIABkgA2SADJABMkAGyEBiGFC5YZcZ/Tlt378IS0re7nFAydux5BUZJ98rpaWlVkanyD0RvJLdqcJQBKJOs+47YduT2Krc1fpa21Chq7WuL/MyXVZWZtWSva1j9QoPwkcwGGwbt7qj779rSd7s7GzrhzLhcBhShpLk6OxcGYueCEy+pzOmRO5GBa9I3jCKi4qsci2Bq69r3fk+hnYbUPJ2vf2HkOQ1ETBNBJi5S9FNBsgAGSADZIAMkAEyQAbIABkgA2SADJCBpGHALll1WuuOZEdvlsdmDOu+pKbk7Z7gFYFJydux5C0oKGjrmlnlrr37XhF/lLzJJXZVzGrbqODtSjup3NXavi2ZVrkvtRT7eL3yuohe+UypzJXvJPt3nS6Pl8krgnfISd5wEYqkFEnWnmbuhVFYFC1REVfUJrxVrImQk2l5T7ioACVFeagozMHIggDG5PswLt+LiXluTMnNxtTcLNyUm4UJeW5ECkMIF+ZZ7yu09ivbiMq+5Ky7Lon6RjYmc2w6OzaNm50rXab1FclbbJO8ylaUL133Si3Lo+tH5XDn3Fx5X9+0T2K33xuJGy8esduLt85gXdZlyasXuabph+mTC75AuyLLrNdM86qbBOmOJLG/hhW52yp5RfS2ZvUys7f7F+6JbUceL+NPBsgAGSADZIAMkAEyQAbIABkgA2RgMDJw5bmT2W5cSrvguF7TKnntcpeCt+efq4EkeWPbPJYplWhdrUW26boq3mReHjaLwBOxKxmbKvdipR/nk1fw9kfbqAwWRmS8XinShbPIXmVVGBWm5HOmjNlrp9Npyd0hJ3nDRSgIF6IgXICi1lIYLkRhOIyCcIlVikvLUFBYiHBxGPn5+QgXFqKksAilhYUoDcvyQhQX5aCy0MTEgmzMCKZgVXg4/npqHvYsvwEvvmc+fvVwLf7rY6uwZWEVpuRkoLQggMKiHOQX5Vv7KgwXIzlLuPX4iiBCujvl+ogwlajFKCrqWSksSkRsNW7CUoFVLL7afkRgF6Pts3g1m7cz0RvN+pXM32KEO42Lxs++v8ExHStjuzIfy6T2VtDVLH3ZR+w2BtN8H0pekb3REgjIheKV+a5NX+visqPt6fvavx4wfQhaxUTQlMLumwfjTSHPSflnTRbIABkgA2SADJABMkAGyAAZIANkYGAxYBe9Kg5FdMSKuN7OizCRbahE0f2Sl57xom0Vr100xhLbRCaB6DHq8Wgde8wqbLtaq+SVWmSbyDnpeleknUheqUUW2rNBu5IR2h+CkftInGCO5UF+BCA/CBDJq+P1CkfKrV3qxk7HSl5hWwXIYJIY8c4lKnkLWyVvvlWL6C0Ii6grQnFxIcKFuagoykNlfgBj83yYkOvGlDwPbs53YWpeJuaXu/CeOZV4rOZGPPfgUvzX39bh95+pw2ufXIaWhxbgzN/MwdmPzcHvH1qKO0Y6MTY3C+XhHBQWF6GoOCqTVSr3TV2MgnBPiwhvkeFdLyqD48W7e8tEUvZM7ur7RPL2/Nx7816Nm0jeKFdXMsVFtKqAjUpeFbdS24usp1nlWsu5idxVwWuJbJHZV8VK9zFwxW5X5G1X11H29LutpKQEWnSZrGPfnr5Hl9tr+2uDYboHkjf+2CR6QSz1FYnrg9/vQyAgy6LTXat1Gx1dXOrrsdvU5Vq37t8fFbyhGNHLTN6O4svlvLEjA2SADJABMkAGyAAZIANkgAyQATJABvqPgejzpCv7EyEopSMZFyvnOpvXbWgt68q0/VlW7P7Z9lfa4lqxkNhJPOO1gcZctjEYJa+en8hdeeAskk6zd0Xy6lissVKPgjVxgjUZYh/Lg138awa41FJEQMhnTH54IEJXi/6wQDJ4HQ5HW5HPoV16DAaBEf8cVIKJWJMucAtQXJRrZeaGw9G6rCiIkUV+3JCXjWl5GVian4p3j8zGlgWV+GLdBPzbg/Pw648vwp8/vRyvf7Iabz28AGc/VY3TH78N5z5+Ky5+dBbw8VnAR6ej5ZML8YW6cZgXSsGYwiDC4RIUFpWgoKi074qVkXw9ZGX3Ja/I3vhx7+rygSx5JeYieqPZvO0zeZW7KwJbha0IXLu07Uj6CzftBbbsSzOIr9S9i39X26nv1rML13jTMpyBFn1d5nVazl++y+QHL9LDgf27W3tBsP+NlXXk77D9/RpDXdZRresN1LpHktflDyI9VISUnJK2YoSKoSW6vBgpOdEyLFfWuzKv00ZOMToupTByOivFMHLjFH1Pbknb62mhQnj9QYSsDF5fdGze1m6br3Whyte7flHPWDFWZIAMkAEyQAbIABkgA2SADJABMkAGyEBPGVCxa69VIKpM60gmxhOMKnP1vbKt2NLTY+X7rnCubRSvDTT2Eq+BKHnjnZN9mYg2eSgtYlcyMCdOnGiJXnkYreJOhZ79ATWnh7bk1fZXNpQVXS7iQiXv+PHjrR8LCGfaJbPU9gzeoSl5RU5FMydLiooQKczBDfkuTMrLwJS84bgldxiWlDvxrpsK8XcrJ+OLd83BLz5Ri988vBx//uQyHH94EU4/PBfnHp6Fcw/PxpmHZuPUx+ag5aNz8PaHZ+GsZPF+fB7OfGQm8NFpOP/x2fjP983GmqCBCXk+5OcVoaCoDPnh8j4ssv2ellLkh0t6VTqSlF1fLgK8rGel7bzlPBJRJHaa0SvdXYt8FYkrgrYUhUVlraUchUXRUlDUnoW8cAXywhHkxpTo8nLkhsuRU1yG3OJS5NraKhpf2ZcK5b4TsX0pNTsSqip2O6rlfXJcImzLysqs7z/9PtRaesnQosvke1O+S+V9Iof13HR7ejy6X53X13X9gfgjmR5J3rRgIYzCCTBKpl0p4VtgtJVpMMIxpegWGPZSeDMMKUUdlWkwimQb06OleAYMKSWzYJTMhFE8/cq+245jenQdaz1ZV9aZbh1rWrAIAZ+JgM8Hv8+HgP/KxSgvzBkLMkAGyAAZIANkgAyQATJABsgAGSADZIAMJA8DKnpVyqosjK3twi12WtfVbdhrtvX1a+tkl7ydHV9Xu2W2s6XvCYVC1kNmFbwiee3STqdV3LGm2O0KA5qhJl04q7xQmSFMSda4/LggMzOzLXtXhK+KXmFVZcXgraWLZsmyLERxuAjhvBxMLDT/P3vnAadVdeb/q7EEVHqZ9pYZei8W7BqTTbJJdvefRKOJxgYMDEUTjC1te3az7sY1ml6MGjtIBxt2ehGUItJEkM4M0+v7fv/7u/d94PI6A8MwwKBn+Dycc/u95/zOee/7fN/nHK7rdTb//aUYU28awtsTrmTrT77Gnn/8e/b8+CsU/fhLlNxzJTU//hwVd11E5b2XUvKjKyn6yRfY+9Mvs/Mfv8ZH//x1Pvzna9jKQz9sAAAgAElEQVT4z9ey6Z+u5cOfXs3uH/8d1T+8nORPrqT4J1+m9umfsW3xGyxasoJ5i99h7uKVx8zmLV3NvCVNtKWrmLd05VHZ3KUrOTpbxdylq5toq5i75N2UvcPcJSuOu81buoJ5S5czf+lyFixZwYIl77BA97ToXeYvXsX8xat9m7twFfMWr95vby1axZuLVvPmojW8seg93ljy/n57c+k63ly6ljeWruXVxat4fdlqXlv8Dk9Pf4HBF15BVrwXmdHuZEXy/HmlT2bQG4ao4bxBVqWaK1upttuy8urrbJ7y+lJ97oatvn3CsNbOH75W+J5O9r6ySZDXy+jGN55axCXPrdtvF098n4snvc9FZhPXcdHE9Vw06WC7cNJ6ZBdMXMf5E9dxnmxSPTZxPedN3HCQnTtxA75NWs+Qie8zeOL7DJr4PgMnBab8oInrGDRxfcqUX8ffPrEQL7MXXTp2oUvHzrhhmpvvRd59KXJl6TTgNOA04DTgNOA04DTgNOA04DTgNOA04DTgNHCsNBAGs/Xlw/AtPe8g7/HR5aEgqtWB9HGiInkPdX8GbBtKw5qyfXQ+AThFWNrwzIJxBufCIE+O6vCyyzvQ2xgNmJakszDs1Q8JpDUBCYFdgV4DvrYsnRqwEMSw/CcrPQB5c2M59I1lcuMlfVnw02+x7Z/+luIfX07V3cNI/OB8uHMY3HsZVXdfStmPrmLfj/+GXT/8G3b/2zeo+csdMOnfYO6fYcVz8MHr8OFc+GgRbFsMm96C9S9Sef9N7PvhVVT88PPw5E+hYhf6q01C9TG0GuBEWjVQdYLMrq30RJmVfa3qWnWRDEz1XlMHVTVQUQ1lFYGVloNsXykUlUJhKewtg91lsKcc9lZCYRXsldXA7hooTEIJsGVfJX95ZhpZeX3pGgkigjUUeDBX74Go1OPVjsORsEd6TYOnAqqHM0HerKws37Sv+kf9qEUA18BtGObaD17S0/A+4ePUf4aHcLZ7s+ez5YbSI332E7V/0yBvZh+GPbeJzjPLfesyq3J/vtPMcjrNrKDTzEo6pqzDzErM2s+qpN2sStrMrPDtnJkVnD0rzWZWcvbMKt/OmlGJWavpFcg+O6OCM6aXcvr0Uk6TzUiZv1zGadPLfTtd+82ooO/EjXhZA+jUobMPejt37Myx+vLhznt8vkC4cnbl7DTgNOA04DTgNOA04DTgNOA04DTgNOA04DRw7DUQBqv1lbe217f+WK2zCF87v0HE9PRw923Hu/ToNaSyVvmHgajlrV5UzicT5LX7D6d6FjmLBdnkUB4yZIiflxPZoFw6wHPRvA7qpmuiKcvSl8FewQ1BDKWKJhfUFeA944wz9kNfi1YTuDhR0OFYXzcW1/C5UbpFMjkv2olHxn2TTT/9GmX3XETy7vPhjsGg9O5hlN55CTt+/BV2PjSeyukPwYa5ULYZqndC9W6o3gO1RZAohWQZ1BVD7T6oKw32mfsE6//pasruvYrCf70GSjf7kJdkkHxS/08AdSkT5NTyocxg6JGmdk4dZ9fTupZQvInkgbtQNpm62UQN1FVBTTlUlCQOstKiWkr21bFvX4LC4iR7i6GwDIoEgCugsBKKamBvHRQloRjYl4A3lr1L51h3suI9iMS7E43noXl+NSz5sW5PTTl/Q2DU1jcEeAV2wxG8uraGZbbPVv2YRX2cluv7fLXPVUutT7XPYesrdbz6SQPAuo7uLf2+0tfZ/SttSrmciGOaBnmz+tNn6k5Ofx5azU7SblYVOdOLyZu2l9z9Vkh8WtEBm7qX2NQ9RKfuIWfabrKn7iLLtz1kTpXtTVn6sq0P0oype5F1mbqLzlN30eljtpsOU/fSZloRp00vw5udJHvydrzswXTq0AkBXgd5j/4F3n0JcmXoNOA04DTgNOA04DTgNOA04DTgNOA04DTgNHDya8CgqaXpdWqQrj6Yq2O03o6tb5/08x3psp27oVTXrM/C12no2MasD5/H5evXu8r/ZIe8YZhrEbuKkNTcp4qWFEyTw9gihOQ47t69u29yNJtzWc5myys157NLHew9Gg2YpnQO6U1R5PYjAy2rDVokr80TbaDiRACH43XNWG4ueTkZDM48h+d/egvbfvh5EncOge/1hwmDqbvrIvbdexVFv7gZ3noEStZDxU6o2AuJSqgrh1pZGdSUQFURVBdBTWEAfgV/y7fC7mUU3Z9P1d2XU3TvF2DFTKjcDSJ99icWmG5GL1NpiBfaUfvTZDKJGT5NTMHF9HMer+XUnely9hjKC8JWAuVAKVCRinIN31Z4//D69HxdEmTh9f5lG1iRFGFNt/1H21VDadLQdEBng/JNkEhofYrYJhKQqAPtm1Sqa+gGUn/abtdIJEnUJkhUJ335JCuC3wHUliSoKqqjorCOysI6yvfUULanluK9dRTtTbBnbx17i5J+dO/eEtijyN5K2FkFu2thTy0U1sFry1bSKa45fPOI5mrOXwO8xx/yWqTr4dqy9TP1peEfm1jeUkFefa7qOoKy+mxVv6bPVi2H4a71f5am96W2PpzaOXS+sGkf/VhLz2WwV/duebs/e57DPX9L2d5oyKsXWXtp87L603fqDlrPTtB5ZinegFvwenwlmCs3V3Phyi5PzZ97JV78Cry4zaN7MV7ehXh5w/DyLsLLs3l2P4eXJ7sCL+/yA+afR+cKmY7Ju7Rh63YlXs8v0+/p1Zw+vYTsKdvwcgb68/BqqGY3XHP9L+Xuy4orF6cBpwGnAacBpwGnAacBpwGnAacBpwGnAaeBT5YGDgcy66vvMLCzvMFe21/nVV7rldpyOnC1/ZsrtedJP1/6dW05fT+33Pz6Nn9hGJRaPqwb08jxroPw/RnAtdTuU8vK23qBMuU1/6kcykOHDvWd0OZENgd02Nls28LrXN7B3aPRgACuHW/6Uir9WdSbRakJZEi3anMa/lTwxECNAYtw2lLgRFPvwwcz0Qix7K4MjHbk96O+yo4ffQF+MBi+P4CaOy9k1w+/As/dB2XroXYP1JVBUmC2OojardwBJZtg+zuw4kWY+QeY8iA8/Z/wxL/AE/8MT/wT/PVH8LvRcMd5VN51EXWP/RDKN0BtKQlBQR8UWhqiouKFdVAnSwbDO2uo34T4YjKJokRldWlm6/fDRYOM6alOdJDVBcDyoHX+xfYDZAPJh0+DU9t96x4TiWp/+OidwIfAJmBrajhnn5OmGKwur+PSbyN92T+nnl3M1f7CgDfFW+04bdJ57S9g4QbHEwgCh622rpqkj6iDI1TzgtS1iYRfkrpn/y8FeZM+FE7Vj9Bu2rUSdYK8kJB8KgIJJRT0XVhH6Y5KSnbWUrorSfmOJGXbkxRtT7J3JxTthd17YFdhAHi3l8H2SthaDturYVcN7KmDl5etoWNuHzLjucRyTxzgbWybDPcn4bwBU4vWtWWl6pu0XtdQX6b+S5G7Suv7XLX+L5yG+0Llw9uUt+0Gei2iVxDZrqX+0u9DUkNKC/ym32/4merLN7acjsd+TYO8mf18yHv27FqyZxTi9f0WXmwYXlZvvKxeIdNyb7zM3pya2ZNTM7vjZeXhZeXiZcVT+Z54WX3wsvqlzM6h9Q1ZD7wsnasBy+mDFz+PKx6fz1nT9pA95SO87P50aN9+P+g93i+U7nrN/yXClakrU6cBpwGnAacBpwGnAacBpwGnAacBpwGnAaeBQ2vAoGh6ml5uBkXTQZeWFSEmcGAOMDnpBL90Dm1XagDPzpN+/mO9bNdNT4/1dd35DwSFSAvpdrJAXrtvgV3pXXoWIDOQJoew8uY0NidyunPZLTuo25waEOQNg94wwJAGw7BX8EI6zcvLIyMjY/88l+q3WzqgaAoEseGa49FsekU68dOvD+Ojuz8HdwwiMWEwe++8AmY/BMUbU3GnddTVpiI7k+Xw4Qp2/OmfWfWDrzPn6sEsuHoA73yzN2u+0Z2138xj/dW5bPhWnA1Xx9h4dZy9N/WCCUOoum0wxf/2Ddi1CGqLA4S4P/L2ABVUTjGgVYkg8lVD8gqOygoJhujVOuU1w6/WFwFlipDVPL+p4w/E0YYiVP0z6wrpJmppkacpgHmUiV3Bzrrz/y7xjxPXMuyOaZz3g1ncM2krmxPB3L3ax7+lRl5TkNfmvVVksEyRwYoUDkcLa85af0hjDWtsZZQIgG1Dl9J9qzQ0p7CO35EC0tt1rtSx2kd//j7JoPxVD3tVF4lgPuTULj6wrktAbU2SuhTkFdytK4SKPVC6D7bvhi3bYed22P4h7N4G27fD1j2wuRjWF8PGMthQAhtL4YNy2FIJ26oS7KyBl5a9T/vcfinIe/yjd9PbYX39RmPWGdRV3xM2vTvqeA3NLKir0QiUqi+zfjOct3VNTXUumX1uN9Rf6n51X3bfytc3j2/6s6eX14lcPgaQ1yCtYK9BWkHZAMyektmdUzJ7+OZlarv27xuy8HF2fHraOMh7+ePzaT1tD1lTtuJl96NDB33xOL5zxbiX/UN/2XTl48rHacBpwGnAacBpwGnAacBpwGnAacBpwGnAaeDYaSAd7qbDWEFRA3ECXYJcYdN2Oa7MOWawS043DVcr2Bs+h0HW412ndt309Hjfx6fxelb/BkrDqWlL5WLaO95lFL6/sLaVD9+r6V+OXA0dKWimyB+LMDJHc33gzba51EHe5tSAac1Ar6V2jTDEUN9s4ER5wV6DDulwQsu27WRN9Qw50QiRSDbdY1lcNziTrfdeRd2EgZTdPpTkb8ZA+QdQtQ8SwngKC9WQvBXw/kKmjfoKS67rz7bv9qVoxCDKC4aQuP18ErcNITF+EInxA0neNggmDPWXuX0I3DaIurGD2XfHFbDkaagpDpimT0IDHGrg0ADjHmAL8A7wzQff4+sPrWUF8B7w/v+texf4+kMr+X8PreJtQEj6oxSYDAaDDs77caCbJPhn8Ndw5LFLNTzzv09cQdao6ZyRP4/T8+fTcfQc7pi824/sVSkfyZ+eTGBX5aOoYDOVwYaQrQPWp0zbtCxYKyDc0J9KRaB4ewImb4QfTN/HFf+2kP94vdYvXz2L7ldQfRvwq1e387f/+SZjnivikQ2wKlUHVvp+RLPAb02S2pogklfkOVEEewthUyEs3wNL98Lbu2D1dvhwG6z/CBbvhlf3wivF8FYZrKyAdeWwoRw+qIBt1bC9Bl5cto72uf3JjOelInmjJ7yd1td32DqDog2lBnjDcFc/ltJnq0z55oS61i+mp9ZPWqrr2rus7kPr1Q8a7LXnO1zakvrOJkPeftN2Un8kbwryZgvWGtwNpz0J4G4q4jdTqY4xOJwOdOtbbjzkPWt64X7I2z4Eee1LzvF+sXTXO3ZfXF3ZurJ1GnAacBpwGnAacBpwGnAacBpwGnAacBpwGjhYA+b/CKcqozAMTQddWtZ27SdoIOBloEvOMZmWZYIOcoRZudtxtuzSg+vjk1geYYiarqWWBnnt/gz22rKlpm05gGUWAWSO6DB0awi4mSPZjkl3OLtlB4Ibo4H6tBZel34ObZNm7QcKSqVfrReMEHBpSVDi6O8lRjQeDyySzaVZZ7L6zqsoun0QJT+4GBb+BWp2+wzQn8vVx7F1UFtCYvmrvDD+62y64yvs+d6VbB93CbsnXMmOCZezbcJlbJlwqW+777qSXXdcRtFdV1D0vQupvO18qsadS8X3L4RH7oaq3QF71XjC/ti+fiyrv045Acx7fvkE59/yC3rkP027Ua/RZtQb5IycRLcRj9J9xKPkjJzI2aNfo83oV+me/yxDbvk1tz/4IoLDiuY99F+AlPW/gKWigvXEinoV4BRoPqo/I5waiTp1/isn/JUzR7yOd9sHeLdtwstfTK+75rIyBUWD4GI7sOGra4/KJLyyai9funsSPW5+lH4jHqH/8Id96zviL/QY8Re6j/gLvUb8ib4j/sig/D8ycPTDDLtnBg+/E0T1NnQFxWzvq4OvjHuQWP6znD36dU4bOY+M2+by8zfqWJuCygLG971eTo9xUzkrfw7njF9IhzFzGDj+ab8O9Nwyg7zVNUlqRN91gSIoL4JJc6u4fOxzDBg9nW7DpzJswsv88pVa1uyCR1/YzMXfn0w0fyKZt/6V8+6azEOLylhSDu9VwMZK2FIDW2vgBYO8sW7EU/PGHn07OTpQfDjQadvDgNSgr+Cu7t9GxdCPpmT6nLXPR/1YML0va65l6y/Tz2frdQ+6F4Fe9ZeKMFYEr92/ni38XPaslp7ouglf/xhA3lQkbnZPvM5xvIiGYjaga7DXhlnuVs+Qy9qnPrAbXndkkDdj8hY/krdjx/Z07nzifjn4SXyRd8/0yf+y5urY1bHTgNOA04DTgNOA04DTgNOA04DTgNPAyauBMNxV3urS4JvgVhh4aaha7SNnl5xeYWClvEEvc5pp2faT48vOX19q91LfNrfu5NVYS4a86fdmWldqw5BLl6Z3OXv14wU5fs0RrNT07lIHaI+XBsL6s7yAiOXr06X643A/bZHoOs7ghQGKxqRhiNDS8pFojJxYrm/Kn5d1NpNuGMKHEy5m+/cvge2vQq0G3tW8uHUkNJmqj+sqoaYIKrbBshdg4VRYOA2WzIL18+CDRbBjBex6F9bNhWUzqXvh9+z67QQ+/OFX2TXhIkrGD2Dnj78IRWugrhx/UlmDvP7QzcGwxYo0vfP+Rxh66y+I5z9Nm4LXaT3mTbqOnkL26GfoMnoK7Qpe5Mwx8/1teSOeZPBNDzDugZk+rD1sZKzoo+b6BV54p5RL75nNuXe/xF9XBcMTH/b4hghpPesFjAWeB4/4PWcVLMAbtwlv/Hq8se/QfsxrLE0NpVzPofWu0vkEo7824TfERkyi4/DZ5I16jj4jn6D/yEfpmf80nUe/QIfRL5Iz6lm65T9KzxF/Ij7ycTqMeZl+dzzvD3Nd78kJhloW9D7/1l/RNn8O3tg1eGM3cMrY92g1ZhFtC16j5w+XkXX7W7Qa+TpnFCzmlLHv4I1fiVewmIzRk/0IX8FdWU1dkto6Ad4kNVVJaiskoyTbS+CSu16jfcECWhUs5fRRS2hdsIheE95g7i64quD3ZI6eTeuC1+kwaiYZoyfR757neaEa3lZQeTlsrIZNVYrkfZ+O8X5ktRDIe7g+IgxALW+AVKn6HPVH9qNA+2wN96HaHl5uzny4rwz3l7Ze11Kfqc97+4GM8nofUH9nzx9+JsvbNktPdP/YdMg73SJ5i0Jz8qYAryCtInmzBXj74sXOxYueF1hsKF5sCF5sEF5Of7xov2DfzG54vnXHy6wH9GrdQab97Jhw2j24buxcLn98AYrkzZi81b+PIJL35H1pdl94XN05DTgNOA04DTgNOA04DTgNOA04DTgNOA04DTgNNFYD4ahay4ehl4EuwS7lBX41xKccXOaMkwPOnHDhvDni5Cwz8KtjdKyiN3QuwTOldm0HeT+Z2g1ryiJiLbUfE0izqv/Gare59gvfmwFeuzel0rt0rR8qyKRhi+A1jbvUgd0TpYEwmNA9GJxIX69t1j9bauDCNC1dq3822Kt5ew1QNJSeaHBxqOtHonGyY3m+RWJxBme347++3JN377iKrd+/DDbOhGpF2ioM1eIxNVxzNdRVQq3gbBlU74Oq4mC5pgJqK4N9FEdbVwGVRfgTr5ZsgCXPsv6fvs7e7w9ly/cvgCUTofQj0HE+5E1F9CpMNRXsqchaDc38OnDJb4s473eVTAYu++0Ohv1uL08CQ35fy8W/LfX30TDBW1NRs8FwzQ1hzADw6rKCuV+/42E65b9E61FvcME9z/vDPmso4mQyWa8d4qwHNllAbuoamq92wK2/47Oj5uON2YA3Zh1ewTucNfpN5qeiiBMkfZSeKoID50rLKUpZZXPurb+gc/5sJgIvAt1GPMliYB5wTsGb+9fH859kEfDy/w0ZffroeXQpeMEfsjnttPsXdX4h/oE3/ZrPjpyLN24z3riteOO24I3fhDduHd74dXijV+ONfg9v3Aa80WuD9ePeo93IGT7k1XNIPbWSUV3A82urEgHkLYENxdB15Et4Y9bijRH0Xo83/n1aj3qdN4rh3Ft+4wPl+0rh1/ugY8EsOo5/kYk1sKgS3iuH96tgQ2XypIO8NhyzgU8t6/1Py+pr1Oeo/7Ehka3/Su9P1Welr2uO5YauFz63rh0Gveo3zRSBrD7Ini+cpveZh+qrjse2JkPevtN3cdbsOrJm7MPrey1e7MJUxK4ibnvhRQbgCej2+wLekK/jXXQz3kW34l18I97F1+P1/Spe/HK8bpfhRYbiZfU5GOJa9K+lmr/3IBP0FegNWwoEZ/fDi53H5Y8v5KzpRWRM/ggvq5//xaJTJ71QHv+XyuZ6OXXn+WR+IXL16urVacBpwGnAacBpwGnAacBpwGnAacBpwGmguTUgwGVmsE1gy2BXmzZt9sNdOaHkkLOoXDnBDBaYA87SsINMx9i+5syTQ0/wTFBP17fnMsgbXmfbXHry6l/1KX2F4anlTXeq35YAee2+5LyV1uXMlW6VyiGcrvmw1l3ewd6WrIFw/xzWsQCGtK6oXtO8zdebDirSl48HnGjqNQLI253sWHei0RgDsjvw3b4dWHT3/2PrHVfAKw9A1Y6AzPmYzh90NzUvr+bnNfBbp1DfAzBY1FRQWKb1tVWQrAnm8q0rhPWvsvGuK9g64UJK/3R3MO9vbVkAeX2YHMyUq0hVDZmsuV81f+zND83nnNGv4o1bhTfmHbyxy/HGLUvZu5xZsJCv/vYj1qQAr8Dt4UBpXSLpD8ms6/zDHQ/TYdTLtCp4i/Pune3PW6trN9efgLOg7MARv6HV6Hl4Yzf6kbHemFW0GT2PhalI38Pds92Pnm8H0O/Gn9Ol4HmeA54HcvOf8mGuIO/ZBW/4kPclIC//aR/+vgKcNuot2o6YdkjIq/vdB3zhe4/SbuyiFOQV6P0Ab/wGvHHrU6b8hmD46fEf4o0NIpQj41/170/P44NeyaIOFBCeqK6juqyamrI61pdA1pjXA7hbsCEAyGPX8tkx83ijFAbd8CDtR7/CQzXw53LoNPp5zi54nokJWFgF71XCumrYUB3Mydsx3r/FR/KGYaeBXaVar75FfY7eA2V6Rwz3TS2lDw33kQaD7R3A3mVtaGn9MMaez569pfWVTYa8fabvptXsBJkzivH6XYcXN8ibmmM3s5+/7rJH3uS859Yx5LmtDH7uI4ZM3sTQ5zYw9Jm15D3wKt6NP8fr9w94kWF4WQPwMnuHInlT59J8vQcBXgHf9Mje0LIPec/nsscXcdb0fWRM3oaX1Z/27TvQqVMXB3k7nbxfHNyXPld3TgNOA04DTgNOA04DTgNOA04DTgNOA04DTgOH10AY7hqEMxBnEbxnn32277iSs8ucWXJypTvhDuWgs/21jxx7Ss1BJgefHPhdunTxYa+u7+ru8HV3spWR6csAajg91pDXdK40vdxsm+7BftggR600K72b5sP6Vj68nN4W3LIDvS1VA+m6tWWl+hGDYMvQoUN93Suv/jodVKQvNxXAHo/jBHlzYt18i8Si9M7pzKUZZzD9tr/z59PddvfnoXgVVO6E2iJIlEB1EdQUBxG6icogglfRvLWlULE3iNqtLgkifZOK+k3NaptMkqj16R6Ubab6T7fzwW3D+ODer8KeJVBTuB8U+0CQAL4KZAq07lLE6vD/pX3By3xm7HLOHLOEM8Ysxhu3lFPHLeasMW/RYfQcuoyc7sPSYJBpw6ENp/5Qwqn5eGcuL+aCu2cz4O6XeXhVEA2s4aJrksGwyAK0isTVuQ8/12/qmhqqOAVLBWQVYTzw1l/z2VFzU5G8G/AKVtJu1Bt+5K3mt23cXMJB9LHOef6oB+k8ajrtCuYQGfk0vYf/gcG3/pLew/9I+4KXaFPwGvH8iQwY/meG3PgAfUc+SquCN+k05tCRvLpvzYn84PT3iI+YyNkaYlpDNgvo+oBX974uNey0IO/GAP6OeZe2o99k3FPb/TmOVRIGef3fAtT6YzeTqKqhsqSSzWUwaMKLtC5YyOnjU/A+fxFtR7/EvBI474b/pevI6Zw96lU6j5xF9qhp9L5nDjOqYJkAb0WSjTVJPqw1yDuAzFg3Yi1gTt5wfyC4qWWDnEoNfCoVCFU/Y3BX74HqY2Qtsc9UvyjTvemdwEzrrL/Uj2IMVOs5ws8eLhvlj0efd6hrNBHy9qfXtN2cMTtJl+kleH0FeQVpU3PvKio3ewBe7mX0e2oVXWcW0ml6Odkv1JA9Yy85M3aTNbuMjlOLyZhRSqffr8Abdgte9FK87P54WeE5dw30KrV5ee064TS1LbsHXqQfXu4wLn9iCWfNLKXr5O0+QG7XoSMdHeT92Etv+kuwW/7kfeFyderq1GnAacBpwGnAacBpwGnAacBpwGnAaeDk1IBFvx5JqroOgzcDbUo1NLMgnPJybsmJZdG4WtbcjUfjkAs7zXRemZxnGsLPIjkNyHXt2tX5KD4BP8QPay0MeMN5q/Pm7od03rCFtR/WvX5oIB1K7xa5aw5o0+zR6N4d6+BvS9aAtG/z+eo+1S8bwJD+FdmeDi0Ot3wo4HB8oIeGUs0lEtW8vFHyol0ZlN2G+68Zxoe3nU/xqN5sKbgAHvsRrJkN+1ZB8RooWQvF62DfOih6Dz5aCitfgMWT4I2/wopZUPg+VO8BRehS50M+gT5/pteKrfDMv7Bx/IVsHnsuvPogVH2UQoGK4g3+lMoEWj9IaC7b++mYP4XpqaGIuw1/jI4jZzMbfLDb69Y/kpk/GUWqCsTaeVKnqzcR5E3FJ/vXMZBblAKc2qYneGolDLtnJuf99HX+sDpY17grwN4kDB37GLnDH0NDSV/xg6dpPWY+3mgNdbwBb+wqet69hDlA1xGzGDT2WXY34uYFwAW/zx9+P1n5k/3jl2tI65v+xQfFG4GsERP9IZzfAa787j+j59oEtB31iug6t0MAACAASURBVD9XryDxof4EevX8a4ph2nZFBmvYZkXwCvQqYldRvbKNeOPe47SxS/lzEbxZGkRf6x71p8dJaCRunVBWW0ddVQ3J2gSF1fDowhLOve0pckY8RUb+FDJGTafXqKdZUgiX33QfPW59lOwRk4jc8iQXTJjCQwvKWVwGa8tha1WSrdU1bKtJ8NKydXSIDyQj3o1obi768cKh2llTtx2ubdv2MNRsKF8f3D1ZPlPD96k+MtyH2/uBUvWV+lGY3h20n8rdyuhQaXr9pO+bvl39cNjStx9qucmQt+e03Zw+O0mn6aV4fb8dQN7s1FDNirxVNG3e5cSf2UDr56s4a1Yt3h/Wc/oDc+nw24XEnttG5swyPxq43YxKOvzvPLxef4+XMySAvP65BHttbl+lYcjbG0/X2W8hCBzp70Pey55YGoK8A2nXoZODvJ+ALw/N/YXAne/kdHS4enP15jTgNOA04DTgNOA04DTgNOA04DTwadDAkcBd21flYuBNQzIb7LK8HFkWqaBUpnVyXpmFnV1Nyct5JudY+nXs3sLpp6EeP8nPaFoLQ930vPY5FmUQBrx2jfT7kRNaejTAa5BX68JO3qbo3B3j4G5L1oD15+FU92v9stqC2oX6as2hmQ4hDrV8KOBwfLbFiEXjRKIxsuIRIrEseuZ0ZMLnerFp3HlU3JJN5c1Rtl2bw7JvxFl0wyDeLricJQVXsqzgcywffSVvXjuQBd/qx7Jvdmf513NZ9a1evPHNvrz6vW/ArtVQpzhczTKb+tN8vtXbqPrzXWwpGELhmL7w61ugUuhR8bEHIK+OqKxN+kMGawjm6PCHaVfwAtOAuUD3kY/TefRLPuTVfLY9Rj5Gu/wXeBXYDJQkodau20BqkNcHvYq6DVlwz0kfGF9293O0y5/FGWPeZOBP5/pwNcDD+5+s/iskg+O/+B9zfXj53Edw99Q9dB7zKqcVLOHUMW9zzriFFEyHh7fDOaPmcdl/rkERw4f703DKivq94NYHyMyf6pfDu4K5w3+GkPlaf+jmJ/15ildr2OWb/omSVNm0H/OmH/msYbAP9Zfwh88OnlQ11GH0SynIqzl5DfAK9gryrqb1mLn+9QSfqwR1UydXKsgbEHWR9SSJ6hpqKqvYVw1ra+CtKphVC8/VwjOV8HwVLC2GBXtgRhk8WQaPF8PMSphXASvLYWM5fFRRxc7qSnbV1PLSsvdp70Pe7gHkjZ4YyFsf0A1H7Wq7ltWX6DNU/Yn6kvBna0vuF+3eDvf5r+3qG/WjGHs+pVqvYamtf1R5WD6cpveD4W3Kp28PA17l07cfarnJkLf71F2cNhs6zijD6/sdvNwLUxA2FV2b3Rsv71Iiz27irNnVtJ+yD+/cAryef4vX/Uq8QX9Pm7sfI2NaMZ+dXkXnacV4N9yHFxsWDM2c3TcAxYLFyvvg2CJ3BXf74GVpvUz51LZMHTcYL34RDvK6L/zH4guEO6fTldOA04DTgNOA04DTgNOA04DTgNOA04DTQEvUQH2QS5G7GpZZ9ytHlBxUGn5OTrmwgysMAZQ3J1hzpRY5plTOK0X2tsQydPd05G07HaqmA14tmzaPtHx1XNjs+PA6+xGDUg3LrH0UuSuNhXWnvHSfrv3m0rg7jwO+LU0D6f26Ldt9CmDoM0Gg10CNzdcroJAOJcLLhwIOx2ebIIiGbI6RGY+QHcuhRzzCN3p1Yk3B+VTlx6kZnkX18BzKR3Zn9815bPtuHh99txvbvpvLrpvy2HNjnH03xym5NULx8Fz2jOzHmvzzWXNfPpS8D4kKH/QFsK8OasqhcC0b77iK0vweVOfH2XnHJbB7RTDksw3vnAr4VCTobQ9MIyt/Eqfmv4k3egne2Lc5dcxCvNGKhn3bn5/3tDGLOGXUArz8tzltxBtc+6vVPujVcMOH+jPuaLMLh1P/npOJYF7an0ym3cipfKZgLpnjZvsQNThv8GSHuobu4fdv7aLPyD9yzW/X8kIS7phRyfl3v8CQu+dw+8wa5iTh6t+up8uo5/n3+UGErs55qLML8graXjTiN3QYMYsOY1+jd/6j9Bv+OyK3PkFk1CTiIx+n18iHGTDidwy95UHOu/EX9BnxV04buYC2+XPYdqgb1/X9+gjuQkC44+gX8catC+bdHftBKppXwzQL+q6h9Zh5/rDTgs86yu5f6YFIXpF0zdVcS6Kmlj218Iel0PvOtzgj/y1OGbOcz4xdQceCV3irEoYM/zXtR83h1DHLOXXscjpPWMDPFsHiGg3VDNsqytlVXcaumhpeXvY+HeKDyIz1IJab5881fSzaUrgdh/P1wV0DugZ5tb9+OBX+bFU/ItM7Zfi90vqZkzW157HnUx+pvtKGcFYZqCz0rlEf6E2vu3BZK5++vQVA3us/DnlzeuF1u5ScZzf7kNefu7e3hnW+OACzmrO359/Q7ndvc87sKs6YUYF336t4eZfgde0egNucQXjR831g6x+Xdyle3mWB5V4aAOHsQXgZqXl8M3txioO87kuSi1Z2GnAacBpwGnAacBpwGnAacBpwGnAacBpwGviEacCglgBWOG/LSgW5bJvAms29q2GR5awyR76G7TST880c/+G0uZ1ydm45y2wuVDm5dN9munfLu/RAubT0slC9SXv1wV1b19S6NT1bamVhy0rDkFfLcrhK73LESvMy6U6aN0d0c+vbnc8B3pasAet/w6ndr9qK2oXai/pmmbalA4n05XRAcfyXY0RicbJjcTLj0SCaNyeHy7PO5s1bzqVwVA8qR2RRNypC8cg4+/J7UDKqDyWj+lIyqjclo3qxL78Xe0f1ZteYPnw4dhC7fvp38MIDsG8FVG2BpAZbTkCyBjR3b8UOdj/2b3w0aiA1t2RRd0sGm0f2g2XToa4EkrX7waCAa+X/zWf7vf+dQm7+k7TNf5G2Ba9x+uh5Ptj1xq/DG/8+XsG7nFKwhM+OWcBZo14na/Rsrn/obbakhlw+DMfcDyMNSh6UJpM+SJ24EXrfMZNzCl7lK79ejyJtk35YqmHMhq8iGKv9b/r5c3Qf8Rj/8JtNPLED3vq/qNvXgMd2wDW/Xk2PEY/yd/ctYCXBHMB2Hw2dWefV8Mvn3vQQ7Ue9zMRUhPMbQLsxbzAZeBNYlLKlwArwI21PL1jOOcNfbhTkTSTrqEsmfbDdftSLeGNDkNdAr4ZuHhtAXkVZK5JXf/YMlvpF5tPeJEnN0QxsqYLz73yJM/MX4I17H2/MRryxGzlt1FzmVEL//D/QasyiYL1gcsESetzzKq9WwfsVsL1sL7urCtlVVcrLy9bQIa45ebsTbwGQV2A33fQ5qs/UT8OPptQ3ppv6Sj27+kkD3SoTvXccro883PYTBnlPnZWk08xyvH43BMBVc+lm9sTL1NDKiuS9jJxnt9BqVjUdp+7F6/dtvLyLg8jc6EC8+CV43/8TnWbs5fRZlbT6/fIA8mZ0D46PDMUbcjXeqAdp98DrtH/4Hdo9/j5dnt1E5Nl1eLf8B17OBXgCu5qvN1NwuCdeTn9/+GgXyXvyfCGwl3SXujpzGnAacBpwGnAacBpwGnAacBpwGnAacBpwGmhYA2G4ZXlFLarMBLs0ZLPBXq2TEyrsjFMkQhh01ef0N+d/c6e6ljnMLKJYy3J86Vms3u25wutsm0sb1saJKhvVU0OQ1wCs7s3mZD7UfYbr3o611LaZxrU+fG3lpW2LSJQj2jQsnSlv+rP10qTlXepA7adBA/X1+dYu0tuP1gs8pMMJLRvUDedt3fFINUxzTiyX7FguWbEY2brPeB5Dup7Dr7+Ux0YNpzw8SvGoXDaOHciq8RewauwFrBl3EavHXsg7Yy7mvXu+xpb/GUnpMz+DFTOgdDPUFkKNZsVVnGl5MGSzAG7Zh1T/9V9ZeUN/ym6Jwc1dqLulK1sLBlH54sOp2Xdr/SlbjRDWJP0zoLlyBW3fA54vh7PHzKftj7fR8Ucf0HbMW0ytgGWp+WY1z6yuroGiNf3rof4EH8PRux/LJ0HRxB9ouOMfTiQ+6hme2BxA2ERCw0sf+s/nmZrXNgEbyuGG+14iN/9pOoyaTeuC1zmzYD7njH6D7FHTufp/5rGyIpjDV/hTQ0fr/hr6032pXIYO/zWdCl5hUmquYoHdNmPe8iGvIPLCFORdkoK82n7W+HfpOPpVDjdcs66tMhFQ1hDY7Ue/infbZrwx630Q6435EG/cliCy97b3OH3kG/5Q2rovK8v9gFfQ118I1iRqa6lLwFYg77bXOUWAd9xGvNu34n1vG6ePXcScaug78jd8drQA8Id44zfjjXuHTre9zIvVsK68ll2lW9lbvpVd5buYs+wdOuT2ISuWRzw3d38ba672ZO24oYjd8HqDu4KXur6Gc9dnqt7d9Bmb/i75aeg7098j7P1a5aIfySiqN9xfWr2Fy93y9aW2f1PSJg/XnDdlJ4eEvBpCOfcKsp/dSqtZtXSZXow34Aa8yPkHhmOOXIA3/jd0nrWX05+vou1j7+HlXhzA2px+eP2/SM/fzCU+ZQcZ0/fQYeZeWk3ZwdnTdtJ+xna8sb/yh4QOhmzWfL2CvN3xcvo6yBv6JeyhXp7dtpb35cjViasTpwGnAacBpwGnAacBpwGnAacBpwGnAaeBhjRgoEup7RNeZ+BLziY5ncLOODnww4DXnHLm9Lfl45HqvuQgk8NQpiFCDd6Fn8ee0aUtt02ovqQ7i9oNpwZoVX9HCnntvHYO03b6svYzvYed0KZ1A1jStTlpj4fG3TUcNG6JGmiov7d2onZjfbPak5brm6/XQIRgRX15rQtvs32aL40RieaRE8vzo3lz4kFU74DsDtxxflfeHnsJe/J7Ujq+P3zwLGx7ETa/CFtehY/egO3zoeQ9KNsE5R8Fkbh11ZCohZpSqNsH1TugdhtsXcTG/xrNyut6UnFLd7gli+RNnfzhoDeMHgRvzwyGayYEeVOgULHAigz9EFhcAtfdP58u+bP54sPVfO3P+4iMfI6r71/GW6WgeWM1BLEgbxmHn5NXuNFgZL1pMgC0y3fCZbf+Bz+bsZn1qQjjZCMgbxjQliXxo2EfmFfLhf/5Dh0nLKL9hOUM/fkm/nMB/nn3hQ7QvR3qT4i58P8g7t/e8We63jqRzHGvEbv1KfJGTuScW2bQcfQLxEY+Qc8Rf6bXiIfpM+Iv9Lv1z3Qb8TRtR8xh4F2v4UckJ5MkP2aQTBWI7kPQWZC9w4iZeGPfwxuzNoC84z/Cu31HAH5Hr/AjrRU5LMhrZRt+Dh/y+g+VJJGoo7q2zi+T/vfM5/TvrcMbkwK94zZxRsFbvFkHA/MfoPXot1JDRCuS923a5E/hxQqB83IKyzZSXLGJwortvLJsGR1ye5EVyyWeG9/frpraZuoDiVoXhrnhvIFdrbP9LHJXfYFMfYP6BJn1GS2xnzvW92TPrndZvcOqbJTXdW3IewFylanVg5WrLaenTa1nHdd0yDt1J6c0FMmboflxeweQ95lttJqVJHNGOd6Q4XjxC/EUqZvTB6/7ZXj/MpXWs0s4/YUqvAfexMu7MIjGjQylc/59RCbvpP3sCro+/h6t/2smZ/7rU3T4n6l0f2Q+3qif48UvwPOv1yMFeXvgRfrh5Q5zc/I60Lv/C6/7Mthyvwy6unF14zTgNOA04DTgNOA04DTgNOA04DTgNNB4DdQHQG2dIJqiCOR8E+C1iAtzRoXTsAOsIad/eJ9jkbf70f0aVJBTTMNL2zM5bTReGyeqrFRXAq9huGt5A7K6t+aAvIpat3MrL71LR9K7NCQn66fd+Xws2qo75ycHWB+uv1f7sR/hqE0ZvLAf46SDiHRQkb6cvn/zLceJRbsRjXYjEs315+aNxCL0zenA1yKn8+KIS9h5a0923doD5v0OylZCYicki6BuD9QVQm2xP++uH+tZq8GVNTRzFdQUQskm2LKQxF9+7EfvbvtOjKqboyRv6gq3dqXi+vYU3ZzFtp98GYrXQlLHH4i9FWMsTcL3H5hBbPjjdBzzMp0K5tAlfxYDJrzIi2XwZilc8r2nyBk51Y9mbTfmFTrlT+Hbv1rOhhToPRQoNRBZH+AN4GTCj2J9eNoCJr21aT881v6H/9Pcs0KxwTMpMrc0AYo0fjc0tLIikAWm9yWCqGG7l9rDXESbFc37/Dt7uPSOJ+k+6km63/oXegx/jLwRT5E34kl63PoIPW/9Mz1vfdi3XsMfod/oJ7nwrlk8/R7+fMMfB7zJYAJdu5EUpRW4HfbDOZw2UsB1Fd7tH+CNVyTvZn9O3tPHr2DAvXP9Z9Mw0la2qcOD4rJzqlRqVS5JH+B/8T/eouOExXi3rcT73np/CO7IvYtYUgef+/6DnKNhogsEl9dxyqiF9L93NvOr4cPy3ewre4/SivfZV7GFV5ctpUNuTzLjceK5mnM6elSW3hZtOQwbLW+poKTewfTZqjavYYnTfzBo726f9s8F9aUqA3uHtfdYewex+quv3G1dOLX9m5I2GfLmpkPe3AvxshVN2wsvU3PkGuTdzpmzoOP0Sry+N+PlfT6YZ7fbpXh/M5qMKds5Y3YF57xQinfno3g9UpA3+zz6/vtztJ1WzKkCxJffjtfna3g9rsDrdQVe/y/hDfwSXmwIXnYfTvGvrUheQd7+Kci7hLNmltJ18na8rAG069CRjp0608m3lv+SfKJezt11nTacBpwGnAacBpwGnAacBpwGnAacBpwGnAacBlqmBgx+Gjwz4CXHnEVcGPCSIy7dCVefc64+p399+6WfqzmWdc+6vq5nERE6rxyONgy102LL1KLVy/GEvNJ7mzZt/PnvpJtwdJF0Y07X46Xf5mgD7hyfHIDa0uqyvnZQX38fvm87xlIBC32mpM/XayAiDCnqy9t+zZ3GojFi0Vxi0Tyi0TiRmCKHs+kZ6cwFma149IZL+Gh4b/beHIPfjoCyZVC+CSp3QPV2qNkJVbugcheUboOK7VCxFTYvomrqg2z+j+HMu24A71+TS/V3s+G7neGG9lR8px3FN3Zl+/BubL3rClg5CWqEPgPoZ/BUS4rinfDLmcSGP0Gngpfoec8Crv3Thz7c/SgVsbu8GG76w1r63D2X9mNeomP+FK7/zQo/qlfRvAFuFGo82GzJuGM4DbYF/1fXQUlq2Gjtg8ZgDqfBUj3/az9/4GX8cYlT7FT3dPsvZzDk5vsZdMtDjPvlixrU2o+mTZCgJlnrRxfXc8KDVunsuh8Niq0I5nUpeLw6Naz12lS6BpBpvdL3U1G5igIWVk8vlwPLB2/S8NdProJhP55Du5FTaVMwh/ZjXqP18BdoVzCHXj+Yw6NrAmBdnLpT3V+qtII1qUJOiHj7f3V+xPXk9XDVv79G3g9epuv4l+j9o7n812JYVQFPLVjD+Xc+TWbBVLLGzmbAndP53ZI9rKmoYUfJRspK36WyfDUlFZt5zYe8iuQ9AHkFW82OtA2lt0e9V8n0vmh5Sy3qVNdQ2zfAq/cy6wssDfcXn+Z8+H1D5aDyUX8pU/kp1T4q03BEb3q92PKR1m94/+aDvIrQ1Xy4B0Hey8l6dhufmQ2nTSvD++Yv8L58L97V/4L3gyfo+vRmWs2u4IxZZXSeuAnviuF4sUHBeeLDGPyLGbSZXsipM0rwPvd9vN5fxcu9CC82FC9nEF7u0ADo5vTmlMwenOLPydsDT0M9x87n0scX0WrGPjo/txUvqz/tOnSgo4tuddGtTgNOA04DTgNOA04DTgNOA04DTgNOA04DTgNOAy1EAwZtG0oNpFkq8CnA27ZtWz/aVcsCpUOGDPGd8CeDw80ggznIzDkWdpDJsSjLyMj4WASoIkLDUaFWdlZGStP3CW9z+eaFxo2FvFbuVl+NSe3HDNrX6lVDIdqwkaYTOVOdA9rB0pOh/zsZ7jHcliyvNqb2Jnih9qchnDVMugEKpQJGh1oObwsDCuUNZIXT9H3Sl2P7Ix0jRGOyHOKRDHpHu3LnF/ryQX4fyr7bntKCPLjv7+GJe+HJf4GnUvaXe+HXt1H6r9+m8J6v8e413Vl3TYwt12Sx45ouFN+QRfVNGdRd35ba75xN5Xfbs/fmbD4YNYB9vyqA0rVQoxjRVBRwCAkaIhUU1XDNgrqKeFVewxprvY5SquGZNb+s7WNz8vpxtMk66uq1BHVJWfJjlkgNX2yIMsUmU2DSJ7IH8ofM6SmS/lMZ19T9jv/fyVww4n85f/ivGH//LP8ZdBoNVl1HIg1HH8CuwdmCZbsnzZercwqsHs5UbtpHwFYAXQg66V9P10y34L6Dx0v6Ec06VuWvetBcujKVuUyYXhG8Ata6J7s/w7kHF5M9SRAprfNKBTqv2S5FPteWUly1h20VpWwqq2BDaTmbS4vYVvwhhcXvUbbvbSr3Laa27F0qKj7k9aXL6Rjv688znduISN5we2pM3oCugGPYBHh1vNq02rfeJ5Wq7Vt/Zf1AeF34Hc72+7SnKh/1lTL1kxYFrff0MOhN7yvVt6XXYXp/d6jlo4O8s5N0nFmO1++GYBjmMOQV7M29jKxnt3LK8/CZ5+toPb2MnCl7yJm4nU5Ti+g4u4K2M0vJmroD78af4fX+fDDUcrQvXuYAuv/kL3SavovPzCyh7SOr8a7/GV6PL+LFL8aLDsHL6R8M+5zVk1Oze/qg14fMWl8v5G3vIG8L+RJrL/Yubd4vVq48XXk6DTgNOA04DTgNOA04DTgNOA04DTgNnFwaaAzoqm8fwV05jOR0N+B1sjvcwk7EsJNMICEd2ur5DfRa+YS1n75/eJvLN28bUfkLxlpUeTg1SBsuc6uvxqQWuav6lINTeldEoZzQGhoxrJmw8/nT7mh2z++Ad3NqwNqZ+mUbklTwQusFZQUswgDDYEU6yLD1StOBRRjuWj59n48v6zw5+y0nJ4tYPOJH9F47OItVt3Sj+sZzqPhOawqvac22b3Zi8zez2XR1hE1X57DlGxns/GYGhddkUP6tLtRd0w6uOQeuPRu+3Ybq69pQeG1bCm/qyrZbY6y+MY+S+66DJY9D2Tp/uOdkUjG7QoIf/xMKNFjYtFTosqF/2vbx8xt+/PjdNG2NzqcntDhlDbEskKno2w8AzYurden76WqHf/5DPV9Dz93Y9eHyqe864e0fL0cr2/rL88CTqf6TyVqSSaFhWTXJRDlJzelcu4Nk5SYS5e9RV/oOdaXLqStZQu2+RdQWL6SmeCG1JUuoK1tBVeVm3lzyNp3j/ciJ5dIckNegbnpqgDcMd/XZqjZtUNLafHP2I5+mc6n87AcxekdXXmWsH6lZuaf3h+Hl+vrIj/d/B4bzbjLkjU/diVcf5M3UfLyynnh5l5DxzAd4sxN4s+GM2QnaTi+n66xyOkwpIjJtDzl/XIb3zR/idb88iOIV4NV8vdFBfOYfxpPx9HpOm13G6bPKOGfqHs745Xy8L9+B1+OqFOjtixfR9Xrg6dqZffCyB+HFLqgnktdB3vBLtcs375caV56uPJ0GnAacBpwGnAacBpwGnAacBpwGnAacBo5UA40BXeF9dH457MyBJIe7TM73kx3y1ucAtGgIpYK9iuxVeSiSWWWRXjZHWv5u/6Nvs6qDYwl55ew0sGTOUulfkTH1acatc4DTaeDYaED9sECFzD571Ca1HAazBisOBXmPFGLUDzgOhrwartkg75VZp7Hi5m6UfrsVFdd+lsprW1F5XRsqv92B8u908q3iuvZUf7s9dde1I3FdG+quPYvkt1rBda1JXt+Ovd/NYt3NPVj9/Sso/PNdsOZFKP8AqndBXQn4YC9JMpnwLR2jHkCBDUNEg4kNp4KR9VnD56wfTKbfXWOWdabgOgZ5dZ+KMBbYlSmvddozHXc37vnre7bmWJdePunnTN/e8HL95Wlr7Sn19IK9VSSTFSTriqFmF4mKzSRK11JX/C51+5aRUORu0QJqihZQXbSQmpKl1JQvp6pyE28tWUqXeB8/kjeeG//YDyHS24C1s0Ol4TZosFeQUedSm1XbtaHYlddnq/pPfb5a3vWnR96fquzM1FcaQFeq8kyvSy2n12N9+zS0rvkgr4ZRzu7NKf78uL3xsnvg5V1M12cFees4dVYd3i9XcuqDSzj1Zy/i3fFEMGxz33/Ai1/iQ10fDGvI5Zxe/rk8zfP7/d+R8dxmzp6+h1OnFnL6tH1kPvcR3oj/xutxJV50IJ4N0yywrLmAcwa6SF4XseuGHnMacBpwGnAacBpwGnAacBpwGnAacBpwGnAaaPEaCEPKxuTlHJLDSI51Ody1LLj7SQS85iCT49GiILROjkqVlQFaKzeL7LX1Lj16gNuYMlT5NwXy6txWd+G8rVMqfav+TfNhvZvmTf+2rH2cuTJwGmh+DVifrFSfP2F4oWW1QYMVBpdsOR1gaLkhYNH49QdDXgO8Si/MPJNn/y6LD2/oSsn17am+7ixqr21FzbVn+bC3/Lr2FF/XnqLrOrL3us7svj6DrTdks+WmGFtu6ca6Ef2p/tUomP8YFK6Eim1QXQqJAHfWJYQ2gz8NZWxm6E9btefhTEMO12eHO64x23UPzWG6Vmp2Xv+B9aw1icBq9cCp57R97JqNuccTvU99ZV/fOrtPe7b0VMNm1yY0XLX+1VCXEOgtIVm9h7qKLdSWbqCmeA11JauoKX6XquJ3qCpZRWXJaqrK11JZ+RHzliwhI9bzmEBeA7xK9YM5tWG9V5npczbcZ4bbeni9yzeuX7XyEyyXqX/Ue7v6THufSe/nrI9MX9+Y5SZD3tiU7Xiz6ugwo+zg4Zoze3FqVu8gstaHvJvxZtfQemYp3uDheD2+5Ef4+mA3pmGXL8DLGYKX3c+P/j1FcDirG17XGF60Hz7o/fytZPxiJl2fXceZL5TjTdlLp+e24N3wb8H2DEXxdsPLzMPL6o4X6YsXO89F8rov8/u/8DXmS4nb5/h8+XPl7MrZacBpwGnAacBpwGnAacBpwGnA+I5HOwAAIABJREFUacBp4IAGwkBL+TZt2vjgS8MRa1nwTOVl85CGHWxyIoWXP4n59GeUk2zo0KE+TFC52HDAGtZXy1aeTmMHNHasy8J0Gh6mOT2vfcL1k15Pdg6lNs+0Rb4Y4A/DXAO69a37JLYD90yNc6y7cjr25WTwQtDCfoBh0EL9s0z7hCGvIgbDkMm2GdRoOvA9GPKGh24emN2WsYM7MOeG/nzwnSxKrmtL5bXnUHldOwqv68K263LYdH131tzYjxUjzmP+6MvYeP9Y9k78BaydA2UfQI2G3K2GRDIIVRXMTQFPDcxbHwwMrwsG7w2iXRXxmm4WDdtQagMANzVt6LyNXa85g2W6b3uW8LG2Xevq2yf9eVvacvhZjiQffg6rG6t3LVcmoTKRpKouQUV1JeUVxZSV7aa8fBdlZdspK9uWSndQWbGHqsoi9uzdyV+fmkhWrDvReJzcvIPnuw63Fcunt6mGljU8s6J3tV3z7qq96nNVn7Fqq/Y56vrPY9d/2juLytvKXhHUqgu936tO0/vFxsBd2+cYQd4+wZDNuZfR6ZkP8WZV02bGPryB1+PFhwVRuj4I1n6Cu/3wsvv6x2huXT8KOLtbkEYH4EWG4PX9PN5N/8pnNfzzjBK8qXvxfv4CXt5lwTDNgrtZeXg6LtIHLx5A3tYz9tHlua14Wf1p18EN13ysX+zd+Y/flyhX1q6snQacBpwGnAacBpwGnAacBpwGnAacBk5+DRjsstSgpQ1HLOe4nHLmDAo74eQsCi9/WvJyiskEGBQhIShobcHK0VJb79Jj11ZU1g1F8hrs1T6qA6sXS8PbtU5aFzyS81mwSM5Q1bVFCZoz2hym4WVb92lpB+45j51D3pXt4ctWnz9hUxtVW1W7VfvVchhe1AegDFY1lBrAaDhtCPJG6BXpwkVZrRkzuCPP/n2cud+M8u4NPXl/xGC23vlFtvz0agofup3Ch/+Ryhm/ofy1p9n51gw+WPgKKxe+wdIli5i39F3eXLqGN5au4c2l7zF36VrmLVnDvKUrmL90OQuWvMuCJSsbtPlLVtKQzVuyirlLZasbsFUsWLaaBcuUNsUaOm/j1r+1dDVv+raKeUvfYf7SFX6qvMpl7n5bybwlq5m/ZA3zl6xi3pKVzF26kreWrmTeUi2vbsBW+fs3VD7Hen1Q/ocrC9VP8DwNpfP9ulnJfL+MVE4qH+ljBQuXvcMipUuWsWjZEhYtW8SiZQtZ/PYiFi9bxNKli1myZDGLFi5i0qQpDDl3GNmROFnZmlv648P3preT+tqUrTOwq1Tr1Bbts1XtU2310/oOeaL7d7272g9ilNr7bHr9NtzvHZiL1/Y5RpC3L15mP7xuV9H+2a1+JO85ArMDbsCLB8M6e5kaWllz6Qr09g0gb3ZfTlE+R9C3F143za07JBh+OdIfr9vFeCPv5+zJ2/CmFtH2r2vxul2emgNYEcACvT3xcvrvH6659fR9dE1B3vYdgl+/uhf7Y/di78rWla3TgNOA04DTgNOA04DTgNOA04DTgNOA04DTQOM1YLDLUis7zT0r54+cQeZIP9GOqeNxfXtWS9OvqfVyVKpcBABlQ4YM8Yf9tOhnK0ulVp4ubbwmj7SsVM5Nhbw6VqBXjmjVrZydBnZV96YDpelacMuHB3GujFwZHQ8NhNup+mbrn/XjJG0TvBBoMuBkICodaqQvG8BoOK0P8mpdhNxoNn1jmQzKbsew7FZcGWnFlRln8LmMM7m865lcktGK8zNaMzTzbAZntmVAVgf6RTPpEcmiRzxGLBojO5ZH12guXWMxusbiZES7kRXtRk4kRiQiCBcnElHE5ZFbTiSX7EjeIS0S7UY0mtck07HZkcCyIsF9694ba5nRbmRG88iM5vqWHdUz5xCN5AT16T9/lGgkRjQnl2iOykXnzyUrmkO2LBJv8PlyInmoDJpSds1xjK5v5ZOe6jkCC+5R9xm2SDSPsEWjuUSjcWKxPGKxXCKxOBF/ndWd1sX8MsmJ5RCJ5RCL5hDLzqa7onZjOjaYgzcWj5GXFz9qyGvtTUMzqz0K7Mr0+ap3KNnx6BvcNT7+GaQ+0eog/MMYA+/6caf6yvT+8FDLRwF5d+DNStB2eilef0XoXhjA1szeAajN7o8Xv5J2T2/Bm1nN2dP34Q347n7Ie4oPeXviWUSvInn9aN7+AdTNO5fLfvIA3hXfwetxFZ7m/O3xebzb/8A5k7dxyvR9nPKrhXi5l+IDY8HdLIHeXvsh72WPL+Ks6UVkTNqKl9mfDu07uJd7N4Sz04DTgNOA04DTgNOA04DTgNOA04DTgNOA04DTQIvRQBhIKi9QKUePzKKhzIH+aXCW2bNamv7MitzVNq23yE05y8x5mV6eRwos3f5HDoNV5k2FvCpvOTT1gwYBIXNAW703pAPb7tKPO5BdmbgyOZEaCPfLas/2YyWtbyzcNZjRMNy1SLYA6ArqHmxBFKSAZE5OFtF4lIysDOKxGLkaHUMgLR4jGouQExFwi/qm7YK7ubFcYtG4D+uyBVziOWTHI2QL3gnIRaPEoxHi0RjxaLxJpvPLBAfrM9t+dOcXfMz1gaOg45FbnJxYYJFY1AfnedEs4tEc//lzBdMjEfIiMXIjeg5dQ+WaFVhU9XRsnq+p5WLHBeUblE8AaYN8LKq6zyXuW+PqVpBWupJJQ4HFicfyUpbrQ9xILOJrUVG60k9eJEpuTsTfPzsnx9ejNCmYfrhIXmtLlqb/gELr0+GuvTudyP7BXTv4fFJ/aKZ60Xus6svyWrZ+sL5UfWN4fZMhb3TydrzZSfwIXR/yXhQA28zeeDLB2/hldHpqM970Sh+2egO+g9ftklQEr6J4Zal9s/vg+aZI3kH+sM5ffuR1uj2zhtP//A7ef7/KaX9YwRnTi/BmlnDa1N149z4RwF8/ItjOZ5D3AgR5z55eROakLXiZA+jYviOdO3byzb20H/lLuyszV2ZOA04DTgNOA04DTgNOA04DTgNOA04DTgNOA03XgGCYzblrMFJRjAJkmi9NERcGK+XgcYCrflhzKEelyk9D/nbu3Nm3rl27InO6bbpuD1d2YcirYcbDZsMxS+OmeZ1PecFd6dx+0CDIa4DIOYLr174rF1cuLU0DDbVZgxUCFwK96pt17/qhjtq+AEU6qAhDC9t+eNBrwPfjqWCsjld0pJ3HgK5tC68XnItGIn5kZTSiY2MIbh4wnSc4V3CeAAoLDDfFgnPZOT+eNuWc4WMOd/7GbBe0zVF9xQTCIyELwLjKQbBb1z1wPoPuQRkeWB/ep2llFn6+o80f/X0FoD64jwPlEWjqwPMduM4Bjfr6i6g8A33lxKJkRyOB1kJtwyBuQ6ngrgFei/5Um7QfWKT/cEptsKE229L6lk/b/eh9SH2lmZb1vSBcx+oXtU4aC/eXRwF5d+DNhrM1DLNBXgO82QK3vfBiFxH/63u0n1ZIxuSteEO/gxc9D69zXgruhsDsfsjbBy9ngD8085W/f4mc5zZyxrRdtJq6h1ZTCzl9WhGfffYj2v9pCd6F1+NFh6agcQoW74/kNchbSOakD/dD3i4O8rovNu4X604DTgNOA04DTgNOA04DTgNOA04DTgNOA04DJ0ADAlsGuMLAS44aOXPkjJPZkG0O8h450FH5CRYKLMgRZoDSyt6WXdp80Fdla5G8YcCrfH2QVwBe8wPKzJlpESyHAvifNoeve94jb/+uzI5fmTXm88n2Ub+stq52rjrSD3EEesOgQhArDC2UNwB7PNMA3qYDuwNw7njeS0u5lkHulnI/LeM+DgbWTbkn07gB3jDk1baGwK6tN/hncFf3oPdHtTV7n9S7paCumesjj18feaRlrf5S9SVTPdr3AZ3HYK/VfXpfedSQt014rl0/gtfAbW+87HO58C8L6fHoCvr8aR5e9y/g5V6Al6GhlbWf0npMwDc2iK7XT6DXL2fS7Ynl5D6zltiTa8l75F3OufdxvAu/hZc3DC93cOpcffAyNb9v7wASx4alInkLyZi42R+uWZG8DvI230u8+0LkytJpwGnAacBpwGnAacBpwGnAacBpwGnAacBpoHEaMKhrEY0allnRuwZ3HdhtHsdb2EkmB5mggpxhKnfBRafXxun1SMrpUJDXoK/pXnNNy9lsujdHtOrtSB2ibv/maTOuHF05HisNGORVPywzaKH1Ar3qmy2qt6VAXoEyA71NAXfumE8TEDfQ27RnNlCXI6Ab0TDNB8xg3uFSvUfaqBiKlpeprelz1tqf2reDvCdPP291pe8F4TrVKAiCvdKJ6cLyTYa8kdRwzW1nFOMNCM3JK2ib3QtP0byxoXjdPofX/W/wen4BL+8SvOyBeNH+h4C8PfCye+JldMeLDvQjer0h/4B35XC8i2/C6/U1vPgVePHzggheXSfaL4C7gryynIF4+yHvXjImfuAg7wn4hfKRfCFw+zb/lyxXpq5MnQacBpwGnAacBpwGnAacBpwGnAacBlqOBgzyKlW9yBEsR5wiLgS85PCWA+dYOds/Dec1UGiOTQMLKmOVrwCjaxPN3yYOBXk1PLlMEb3azxzPFmkkJ6b0b3Vnzs1Pg17dM548TndXV02rK+uLLbUfd6jdq60rmr8lQl4HapsGLV25HVm5haFuOG8ArzGp2pa9SxoQVDtT+wr3W+nL4W0u37T+7XiVW7jf1DXDfaZppFGQ176A6EVYv3r0MvqR40PeOtrOKMIb9B283GEBnM3qgZfVPbCc3niRgXiRwQF4jQzAy+6bArI98DLTrTtepqwbns4jWJzTDy86GC96Pl70giCNDMXLtnNpLl+ds5c/F/ApgrwCyfELufyJxZw1bY+DvA7wui9xTgNOA04DTgNOA04DTgNOA04DTgNOA04DTgPHXQPyp6SbInjlbDO4a85vcxY5R1zzONusXOUcE1BQecsRKtAb9nM56Hv00FflWd9wzQZ4bR5qOSalb9WDRfAqr7oy/bu0efTvytGVY0vTgPXJ1vZ1f1on0CvAZUPOhmGXg4ZHBg1debX88grru768QTulahPhZb2/aFnH6UeB9m6jVO1Jn6/2DpmetrT+wN3P4T+jrD7VT+pdVmbvT8pbVK/00CjIay+8Arx6afO69mLAlA/oOLuM2JSteP2/EUTtZgnOdueUrG6ckhHHk2Vq/l2BX5kN09zQUM22XwoSH3Sc5tzVcMwp8+fwFdztewDy+qBXYLg/XnzYfsjb9dlNLpLXfZk/7l/mrd249Oi/MLoydGXoNOA04DTgNOA04DTgNOA04DTgNHAyaiAMeOVPkckJa44aOenM8e0cXod3eB1JGVm5WlnbMKFyhklLVjcno65a2j03BHk1VLMA7znnnEPXrl19mKM6NCelUtWP6upI6tbt27xtxZWnK8/joQHrkwWk1B9b+xfI0A9ADF6FwZeDli0fWro6OrI6Cuvb8mGQq3w63LV1Kmu9N+pzMzwahtqS2rBBQQO8x6Ndu2scu88Pq08rYy1b3Vv9a5v6zyOCvBpaReZ1zuWLf13I+c+u5XNPrcDr8Xm8SD/OzMrlM5ndUhbjM5lRTsmK42UZ6K1n/t2PzcmbAr3ZBoUFdwWFDQCnhnNWlLBMwzUL+GouXg3znJ2HF+mFl3s+lz2+kNZT99D1WQ3X3I+O7Tu4OXkd7HWw12nAacBpwGnAacBpwGnAacBpwGnAacBpwGnguGjAQKJBMEFeObrNua0hhM1549LmdZQZUFBqoFdOMZWzoqmtbloaMD0Z78f0LZ+hzcFrqSCv8orWM+e0AXcDvKojp//m1b8rT1eeLVUDau8GepVqORyRZuBLqQOIRwYQXXm1vPIK67mhfDrktWXBXotwVxuxtqNhmW10knA7NyjoIO8no/+3+rQ61rJpQPVvOtC7VKMgryJ4zebMmcPMBcv5zfId3LeynPuWFvHQvC088fq7TH51Kc+8spyn5yxl4stv8Nyc1/jj5Bm0imuO3m54Prg1WHsY4Ctg68Ndg7yK7lWkcOo8OT3xcnReWQjy5uThRQ+GvF1CkLdzx07ITsaXZnfPrt6cBpwGnAacBpwGnAacBpwGnAacBpwGnAacBk4eDRhINAgmyCvAa45tOWvMeePSY+OUUxnL5ASTQ0xlL8irulC9uPZ09O3J9N0Q5FVZm74N7qgdWN3U1w7C2+rbbudz6bFpN65cXbk2twbC4Mn6AaXqm/UjEIGtdAjmoGXLg5auTo6sTtI1nb5sQDecGty1VD8I1I+jBPZkajNqn+E2Vd9yc7dhd77j+7lgkDe9nq2utV56GDx4cOMgr73wCvTOnz+figTsArYAm1Lp1iRsSwS2uw5Ka6A6AZNnv8xZPuDNTYFewdpDgV5F7YaHc7Z9DfKmhnIWMLZoX0Xz+pG8Ar498CJ98XIv5LLHFtJq6m66TPrAn0e4fbv2dOzgXuCtPl169F9kXBm6MnQacBpwGnAacBpwGnAacBpwGnAacBpwGjiUBgS4wmbDVBq4SnfepC87p9rROdXSYaEcYhbJa/VmMN6WXdpwm7ayCqfStwHe8Dy8NlSz/InSteoiHMUrbVv9mNPS6f3o9O7Kz5VfS9WA+gD7fLMfOxnkFcQKQ64wCHNQ8cigoiuv41deYZ02Np/+YwbTvYBuOK9l/fjBojWtraS3b2tX1rbSt7vlT+Zngr07CfjLGhXJay+3Bnlr6xKUV9awcv0ObrztPr46/Od8ccR/84WRv+BvRtzP3w3/V0qroK42wZSZL3G2P1xzHl5291A0b0ORvGHIK8CbgrofS4P5f/3tiurVsM/+cM2CvP3wci/isr8upNWUnXSdGEDedu060LFjBzp1cqDX6vT/t/ceYJKd5Z3vmdSh8klV1Tl3dc+MRiOCkEBEgwWYbAkMeIElrTF3sVl7jX2x77N7fXefvWvjxOJ1ItvkICG4JLMWSRLBa2MMBktIILJQRNIojfS/z//UvDPfnKnq7urqCl31n+f55v1OqBPe73++c8776/c7ss1fXOQb+UYakAakAWlAGpAGpAFpQBqQBqQBaaBdDbiAl3WDXBZ4Swfm0tO2nuz2AnUWCDNLyMv4FiFlu207jL934a7VN4K8uVwu+R4vdU2wY/pne1DT1i6mb+l/ezo3/8nKf/2sAbu+2Re4oJdDuRvgSkMwQcvuQUv5ujVfbwXsurpuVreM3cnJyeQ6MLhLsMtnFvvjQMI8u3f283WuY+v8fcienWi3DXnvvfc+3HnsLtx2N3DVN27BRa9+Ax7xsjfg3Jf/Bc5/2Z/hZ176/+LGu4C77j2O9132CWSqi9gzQRBrQy8byHUzdtPQdzPAy2GbCY6X4E0THnP6RGEm7+L5OJ+ZvJf8GNX3Xguvehh1yOsjilj0MD+MLyM6ZwVopAFpQBqQBqQBaUAakAakAWlAGpAGuqkBQd7OB7s2Cii6gTDWBXnbu/4N7Lp2I8jLbN5qtXoyi9eC1WwLtptZa0ODQDYt29vrR/6X/3dSA3Z987o3yMs+mZCXgNEgmAvPBB5bA4/yV/f85eq0Wd003cga3OUy3if53V33urA/iuK8nbwOta3d36+zD3XLNjN5j+OOO4/hVkLea+/GE1/5P3DuS/8C57zszXjwy/4Kj3rJ7+PHx4A77gXedtnfwps6BG/uYfAWHwVv8dFO4fQjm5QL4C0+okl5eAJxvaXzkZTlh9ft4vnwFs+Dt/woeOtPxsq7/hn7L70R1fd+KxmuuVgKEIQ+wihAGIUIo/YebLv5Uqh9qa2kAWlAGpAGpAFpQBqQBqQBaUAakAakgd2ngTTkZUCb2RkWZLOgd7Npmy+7vaCcGwRjPQ15mdWr62rr15ULd62+EeQtFotgdhKD1PS9QV7TM9vE6matzWxadnval9/kt37VAK9xZp9ZpiLruxXyzs3NJccuuNo9uNovvm4Gdt35jeCuO890z2uVQzPzmjC462bu8lnRSr9e1zqu7t1z7DnJbMuQ9/LLL8e99x7HHceO44tf/zGe8srX4/yX/hnOfclf4iEveSMe8pK/wqNe/DrccAy49T7g9R/5DC5+00dx1vu+jvKlP0B46Q0IL70RwSU3IEzKjxFe0qj8COElP2xYgg/+AP4HvovS+69PSvG9306s//7vwH/ft1F8/3eQ+cD3sPeSG+Bddhsq770G3sQ68vxGSBjCjyIEUZRAXoHerT/I66VHvpIGpAFpQBqQBqQBaUAakAakAWlAGpAGWtOAIG/3gl6NAowWADPLIKp9k5eQUnpuTc8Gdl27EeRlJi8hb7PAdaM207zeXjPyv/zfaQ1Yf8w//iDQ4h+AGOwiAHMhWb8AvY2OgxmYHGKXhXWB3+EAvq5OG9VdmGtZu2ZN59SKXQe8T7Kehru8HgV4h69ftn7S7Y+b6WBbkPee+x5IsnR/47+9BRe8+I/xoBf+Gc77t3+KR77kDXjkS/4HHv/C/4Ib7wBuuRf4ow9/Gs96299i4YPfwuhHbsGBj9yB/R85hv2X3YEDl92+QfkpDlx2W9Oy/0O3YN+lNyVl7yU3Jnb/pTclmbv7L/0J9l/6Y+y75Ec4cOlPsPqur8KrriIX+CiGMfyogiCKBXmVyayXOWlAGpAGpAFpQBqQBqQBaUAakAakAWmgoxoQ5O1tYM6CZGYN8rJdBHlbA7wE4i7ctfpWIC9BTqPsJDd4qXpvrxX5X/7vpgasT7a+YTdBXhfoucdt4I7LOd/sRoBYy3YvEHZ10Kzugl7W7bu7XJ/aP+ecc5IMXtZduMtrkUDPrslmcM+Wyw5e/219pNu2zXSwLch7133AdTfehcf/m9fgoS/4QzzoBW/ABS/873jLJ6/D33ziX/GMX/x13Hrrcfz02P3480s/jpf+1Qfw6L+5Coff/XUcfvc36uWd/4LDTcvXcfidX2tYjrzr6ziL5d1fw+F3/XNSDr7jqyfrh9/Jef+EQ+/6Bxx+1z/iyDv/GU94y2fhlReQ9wOUwiqCaAJhVNZwzXqR7+iLvP4auPWXRflMPpMGpAFpQBqQBqQBaUAakAakgUHTgCBvbwNvFiQzK8jbXh9jYNe1G0HefD6fBLXdoZrTgWwLYLKNrC7b2+tG/pf/u6EBXvO7HfIa3DNYa9Nmbb7s7oW5zdrO2ngj60JeZvFyXV5bdk80yyxee05pdO01g3uN1tW8wei/G+mhmQ62DHn5jRIWDtd8130P4KvfuQFPeMFr8JDn/3c86Hm/h7d96hp87w7ghtuBj37sShy7/TiO3XUcb3rvJfCiOXiVI/AmHwZv4kSpPhTehuUh8KoNysRD4aUL13PnTXL6KLyJc+BNnAsvPgteOImCH8APKwgTyKtvrgzai7POp70XNflP/pMGpAFpQBqQBqQBaUAakAakAWlg5zUgyNvbYJsFycwK8rancRfuWr0VyGuAl+2RDkQ3mpdeR9O9vZ7kf/l/JzXAa363Ql6CP2ZlEtotLS2d7M9Y5zxbZgCwGSjU/N0Hf61NG1kX6qbrBHS8B9rnC9yhmXX/U9+a7lupibQu2oK8Bnir1So+/vGP457jD+CmY8fxglf/Ls577n/GL/722/H9Y8BNt9+DW2+7B7fdchfuuP0u3H3Pcbz1He/GaDQBrzQBz5+CVzpRWN9OCabhsYTT8KKZumWdxbYXTsGzEs1gTzSFLIdpDkMEYZQUvbi291Av/8l/0oA0IA1IA9KANCANSAPSgDQgDUgD0kBjDRj8ohXk7a/AXRryso06qWOLqW3XbnZsrtY6fS48lvT+ON0K5HWDlgxWukHNdDDTXaZ6f11Hag+1x05ogNd8I8hrcCwN0doFopttr9nyRvM5j99TJbCzLEzzCc+LsNdAL8+n3WPX73sDg63t6X+rmzWdNrP2/V1qgXCXzx/UO/Vhf/CUvg+ahmTVx7aigS1l8roPop/4xCdw7/H7cey+B/CZf7gaj3/+b+Hlv/PnuOnY/bj9jttx5+3HcMdtx3D77cdw+5134W/e+W4U/eCM4gfBGS866RefjaZLpRJYisXiyVIoFMDizuM6fuCjFPgIEsgb6psrGqa5oy9wm72AaXnjIIj8Ir9IA9KANCANSAPSgDQgDUgD0sCgaMAFYenYBofmY0DYgjfpAF962taT3ZmAnyBve/2Mq22rbxXyUvvUscHctNZtvrS+M1qXH+XHftcAr/ndAHkN4hncI9ylb9mnNeu3DOItLCyAsE+QtjeQth2/W3u71rSwmSXgJ9x1NU6tM3vXrkveA9P3QVsmq/67FQ1sCfLaS1alUsGnPvUp3Hvvfbj92N346T3AlV/9Pv7rn7wddx0H7rnvXtxzz3HcfffxJIv3jmN3421//Q6UgihVmFFbh632QNiqTb8kGfQ16y7ntl3Ay2k7J9n2Hu7lP/lPGpAGpAFpQBqQBqQBaUAakAakAWlAGjhdA26Mw41PsC7I29vAXbchb6evDVdr3Yh3pffHaeraEjEsAcOs+01eg7wWuEwHt5vBEltftrfXjvwv/++0BlwARhiXBmcuXGO9HWDH3262vfRyd5qglqOc0gcEdRv1V1xmhX/Uxb5ucXHxjOO37bd7Xvr99gEy28D857aH1V2b1udG06ZtPnOwpLO9qSNBXvWpO9WntgR5+dB22WWXgdm8H/rwh/HBSz+MD37ok3jPBz6C97z/A3jP+96Ld737vXjHO96Dt//1O/HX73gn/vwv3wg/GSqZwyVbiRC2mU3a6KGylXmdfsjW9k9/wZU/5A9pQBqQBqQBaUAakAakAWlAGpAGpIFh0YAbnxDk7a8gniBve/2Qq22rC/L2l8Z3Kmis7ahdO60BA2HMcCRoS0MzF7CxbjBuuza9PWbkstj20sttmsfF9Sw7l8dN39h0Iz8Z5KXlenaOti9a2747T/XtA9vt+I5tYL9z28PqZl1tEvi704T/nOa6y8vLCdC1P+hj2zfSh+apf91JDbQEeaOIGbAsAeI4TEoljlCWu4UsAAAgAElEQVSOCW0DBFGIIIoRRGUH6NbBLuedKnHbkDf9YmgPlmbTyzXd3kO8/Cf/SQPSgDQgDUgD0oA0IA1IA9KANCANSANb04DFJmgFefsrkLfbIK+rJdZ7fQ2mj8c0rkze/tL5TgaPtS21bac00GnIaxDXrMG8ZpaQzoV3nOa6BHW8d6SBXXo0gs38ZBmdHMaX2zWAaPtxp21es2PV/J2BwWmfu9OuFlhPw11Oc1hmLuOw3NQH4S6BPjN329XLZnrScvXNpoEWIS9fZlzIG6Ac18spyBsloNcPI9RLtyBvgDA8VU499NYfgJk53G728Kltbu2lTuvLT9KANCANSAPSgDQgDUgD0oA0IA1IA9LA8GnABWGCvP0VhOsXyOtqpJV6r/uTRseqTN7+0rgFfWXVLv2ugV5BXgN5BkptmpbAjuCOxbJx037c7jC7BoVtu7ZfHgf3a9Nm7fhkdwboNvKj+Tpt2R7NCuGuAV5u03TM5wtCXvvurrWz6cfa36Zl1UfvlAa2AXmZhRsjissIy2X45TJKtDHhboiQEDgm4A1PQF7W69m9jTJ54zACiz2kutN8cOR8e4C0dWhPrRcjiuITgNdHGNbLqazj+jHxmK1wfXdbqp/yv3whX0gD0oA0IA1IA9KANCANSAPSgDQgDUgD7WnA4hi0grz9FcTrB8i7kT7SeuG0u36vr033WKzeDPLye7z6Jm9/6X+nAsrajtp1JzRgcMyGMk5DtTR4awTptjqv2bDMtk/bF6f5/VyCOoN1O3Gu7jZ43pxmtictz4HQ0I7BrHtunOdOq7598Gv+bWZNE2lrcNcs287ALjVsmbvNYG6z+a42VFffuh0NtAV5g3IZxXIVpXIVQfKN3eDkUM5BGCAICVhPB7wJICakTUBtiHIYIk7WixDFMcpJ4fIwAbeEtUmGbnD6kDRcXofDJyBvFCCM/GT/HE6amcX14p8YSprHUR8mWhm97b2s9vqFQvtX+0kD0oA0IA1IA9KANCANSAPSgDQgDfSzBgx+0aahnX2nzYI46aBfetrWk92ZwF+/Ql4Od+wWVzeunlzdx3H3kxjcY7G6Qd70kM2CvDujWV378uOgaqCfIC+BHkEwwSvv0530uUFeQkHWzaahowtyBXm3D3VdP7Ke9jOn00CX0wZzbZlN848A+CzB4g7NbO1q2tHznPpu00Kn7TYgb33Y44Df4I1D+Ce+tRsHPspBCXHko1zmyyaBLwFtiCBklm85sRHXC31MRCEm4wjViMM981u+EfyYEDZEzHmhj8gvoBIH4G+iIETgG+iltWLgllC3lIBewt4wLiGIiwhok+8F8xhYCH1ZbFt6MXZfEFSXHqQBaUAakAakAWlAGpAGpAFpQBqQBqSB9jRg8IvWhXWsC/L2NujXK8jrasLVhQt2G9VNP/b7Xl+bdhx2XK41yFssFpMMXkHe3mq900FlbV/t264Gugl5DfSlgZ7BU4JW3h8sG7Pdc9vs9wYEzXJ9Ph8sLy+fhIuEijxuwudGYNLOSXZjANzId+l5BnJda1DXvrtrcNf+EICAl9neBuk3a3MtV5/ZKQ1sC/Im8DYBpQSrZURhBeWwjHIQoBLkUI3ziMLiiUxcg8IRSmGIYhijVMxjPspiIrcHcWEcoV+EHwbwE9hLOOwnsDjwA+SLZfilEFOlEVSyHsJSDvUs4TqorYPbCEHMaUJeHpNfh7sJ5CXo9U8AXnc9Qd5evxho/+0FDeQ/+U8akAakAWlAGpAGpAFpQBqQBqSB/tSAgTAX5hkME+TtbZCv25A3rYW0JhqBXXee6casuz1e/+npTvcJtj87HtemIW8ul9Nwzau91XunAsrartp1JzTQachrAJcQ1IV6BHmbfXeX59ftTEzujwCRfrHhpQkaebzu8VtdcHdjuGv+MX81sy7Ytbr5vVqtYmFhIYG5LtxlvVPDee/EtaVtDFcfvU3Iy5coZtzy27hlhOEEStE8gqCCqWAfpnwPUZhPvsvLoZGTrNlKiFwcYX95Fk9/zrNx8zc+hYfPepjxx5Ihmwl2k6zbJPOWUDZEPphCMH0errrya/ijX382Hlr2UC3uQykI4Ic+/DhAIQpQIhx2IC9/y2U+4e6JbF4egx1LPYtXkLfTD/7afn8GG9QuahdpQBqQBqQBaUAakAakAWlAGpAGOqsBA2G0LgRjXZC3t4G3bkHejTTgasIFuo3q7rrpursP1rtxXds+08fCaUHe3mpbQX35f7dpoBuQl2DPwJ1BPk53+ru722kLg8rMDCVE5DQBYzNYafNlG8Nea++0Zfu780wfBnY5bXW2I58b2B6NhmZmG1nZTpvrN+q3d0IDbUDeqP793JDfup1GJj6Iv7vqX/CFz38MccFDHBWcb+ASuJaQiWN4lUX83MUX4aff+DAeFntJNm8hl0cUlRCVSwjCIoLQT7J1s/4sRuML8Pkr/hWvf9UT8KBxD9MlL4HH9czfAMWTkLf+DV4C3jrkrYPeJIs3AcBcTtBbL9148NU+OvvSLP/Kv9KANCANSAPSgDQgDUgD0sDwaMD99qRblwaGRwO7qa0NhNGmYZggb28Det2GvAY/CUDTWtjOtIFg+62rNfcaYT/Zib7S9mf7T1sDvRyqWZm8vdX6TgSOtQ21YSc10G3IS3jXre/ubsdvBnnpFxbCXmaLcn6zIZsJKwV5N4a8BnE3soS6LO7QzPS9gd30sMzWVgK86iO3c63v9G9ahrwnHxJPPCyWwxC50hRqj/hFXHXdcXzn5puxtDaLfD6TfEd3olpBFEeIqxXkylXsiefwjF+4GLd/8zI8OPAQjnnIFwr1IZXjEsrJd3rj5Hu9fjCLfcF5uOKqb+ENv3Ihzhn1MFX0UJkoozJR324Y+ojjCGEcJ8NBh+UIYTlEFNdhbhDFiKvVZChoZvfy+7wCvQoCuC8+qksP0oA0IA1IA9KANCANSAPSQH9qwN4/01bt1Z/tpXY51S4GwgR5+y/41w3Ia+1vANTAbNpyeXpeq9O2D9tnp69D24/tN215/PZNXkHe/tP/TgeWtT21cTsa6CTktUxNy8pkRmy3vrfbzCcGBM02W6/ZfIO5dm42Lbt9yGtwlzpJD83M5wVC3vQ3dw3wsp2225bN2ljz1aduRwMtQ14+LHLY40KxiDLhqR9iLF/BK3/79fi9t34Cf/aBT+KXfv23UBwbxVSxgHI0hXwxRqGUx2g+C8+v4inPegruvPoyHPU9ZA/swUg2QL6UgR9lE+AbFUuYLoyhMJKDlz8Hl3/uavzxq5+BFc9DnPNQ9HOISvsRl0YQB2UUCzGKfikZwjlXKKBYzCMsjqEa5hGHEaK4Cj+KEtCroZpPvXR2+sFf25evpQFpQBqQBqQBaUAakAakAWlAGpAGhlEDBsJo0xBMmby9DeB1EvJae5tl27cKbVtd39WXqztedza9k9egbdPdr1sX5O2tvrcTHNZv1Ga90kCnIa9lZhLEGazr1blyvwYEzbZ6LBwyeHl5Ocnc5bkR7tq3ewV6zwS9BsM3yuDlMvqOlu3BZwQbmtmyeC2zulF7bbctG21L89QXb1cD24K8fDhMhnwpTyDrTyAfTeBzV16OJzztabjg4l/B3199Jw4GPhb370VhfB7xxBH8+IfX4fj9N+MOAPfjbtx59aU4WPAwNhIiG67hhzdchwdwM+7FA7jz9ltxwWKAqQMeDuTOwuVXfQ9/8tpX4Pj1nwceuBfH778b//U3fh7TGQ+l3CQqk0dx409+DOBuHL8fePub34z50h7M5j1MBsX6d4OjMsKojHIYJ4XfE97Jh1xtS/6UBqQBaUAakAakAWlAGpAGpAFpYOc1YEChmZXPd97n8mn7PnX16gIw1gV5exvE6wTktfZm+xJymm0V2G5n/bS+bNqOiXYnr2nbru0nbe0cbLjmQqGQDIFJ3bMwWG5BTAbHrU7rLnPnq97ba0b+l/87pYFOQ15m7xLUcajdjUBdp84vvV0DgmbTy1udNsirIZvrgNegrmtdwGtZu2a5jOsSlDcbmln3JfV/rV6XvVh/25C3XC6jFFYx6i/gKc96Lr57zVWoRCPwCjVc9xPg5RdegKW9Hvz4KK75EfBb/+GVCLIevFwWb3vnm3DH1ZdgreThQGEF/3oD8JY3/mnyLd+RXAbP/oVnA7deiwctzsAbqeHyq74P/PQ6PHLpAHLjo7jo2T8P3PV1HK0Vka2cjX/9IXDRM5+B3H4PuUwWX/r8Z/H/vOr5WC16qObHUA7LiKIKorCCSlhGJYzrGb4CvTv6oL+TLw3aVvtBBflQPpQGpAFpQBqQBqQBaUAa2K0aMIhglhCBdYMJNp92t56jjnuwr09Xo6Zbs4K8vQ0Ytgt53ba1urUtrUHObll3343qO91PNjpnd7923jZkswt5CVvcgLkgb2+vhV4EorVPtbmrgZ2GvAR2Bu6Y8cqMTBtq1+173GPoZt3grtl2983t2Ld6lck7mwBbF/BanZog2DXga9/d5XLel84555wkg5d100u7baPfq6/rpga2BXn5QBf4Por+BPaXanjru/4/vOdNr8OY58HbX8Bb3/E+XPY/X4PY8/DIi1+Bz337OBYrFVRGPHiZIp74rJ/D7VdfiiXfw8Mv+j9w5fXAYljG7H4PQbaETDHEp794OX7pN34TXu4cfOaK6/AH//5C1PZ4yO3xMJYP8dm/vwL/9jf/T5zzvN/B9QBwH4AH7gTuvwd44C687w2/i+W8h2pxPAG6cQJ2mcUbJYXDOCdDOQv0KigiDUgD0oA0IA1IA9KANCANSAPSQEc1YFCgkW0EO209Fxw0q3PdRtvQvMGGqP3evqZh2rR2BXm7G/hjYN8tacib1pLbdhvV2a7p9jXA2Q/WdJc+h/T5bmfatmn7SFuev0FeWgbWTfcbBdD7AcJ0MyirfXW3L5C/+8/fvOYJ1lhsyFwDcbQG6cymQabNd63BPALeQW9zZp8yW5m+sqxeQl8raX8N8rRpwNWPWzdd0C4tLSXPBaY9WvrS9LJTEN62J9t/fc+gtUnLkJfDNCdDHfs+Cv4UcrMPTzJ3ce9twH03ErfiAf53x9cxPzOCB1/8ClzxPWCqkEWUQOAMnnrxM3D71ZckkPcRF/97fOF7wHwpRtXzkNk3hn1jWfzdlZ/CY5/+dHiZI/jMFdfida+8MPkmb3Gfh0w+wue+9EW84D+8Foee/Vp87vtAkM0i9DyM7fOQG/UwPeJh5oCHaimXHG85DHF6EeTdzoO8fqNAiTQgDUgD0oA0IA1IA9KANCANtKoBAwKNrLstW+4CA8ICdzpdt9+421FdGu21BkyXtGnNGuyyABODiVanTU+7y1RvPVDoAl7WtwN5023o9kv9AHQ3OgY7dleT7V4f7rYaaZz75DER8Arytq5ZXefy2bBooBOQl1maBHnDAnkXFxeHFvIa2DXrQt10vVqtnjYsM58FWKgT6tC95gR51Qe7etgN9ZYhb/IgGISYiGLkg1k86vm/je/dB6xPzWJqr4dRL4NCOItv33IDXvSa34JXPIJv/gT43f/4cgSeh/FCCVdc9Vkcu+aDWCl42Jdfxjd/DLzlL/4U/qiH/WP7cdGzn4Effe1yzBVH4I3V8JkvfB//9Mn3YI6A98Ae/Kff+b+Am76DIzNT8PKHcPWNwG+/+iUoEhKPeHjbG/8Y5y1PJN/0rZbyJ+FuJQxQTkod+CqTVy/+7b7Y6PfSkDQgDUgD0oA0IA1IA9KANLC5BtJAwKYJAqzugoKNgEV6WSOA4W6TdbXR5m0kH+2sj1wNmkbNCvJ2N3jYDuS1Nkv3O7tx2s6F1tWn1VvpA+w3Zt1tp+uCvN3V+24IRusYpQnTwE5DXoI9Qd7hyeQ1uGvWwC4hv1uoCQ7fzecvZu3aMN6mQ1n1SbtdA9uCvISjE1EZ44UJ/OF7Po8Pfv46FPfnMLFvBMVRH/vGYvzP930I77/yn+GNLuOpz/ll4PhPgPu+h3vuuxd/+oY/xm3f+gRm+Y1er4QD+WXcdNMPAdyGu3EPjt15M86fz6PkeTgwOo3LP38NPvuRS4B76pnCd/30p3jEnJ9k/u7fP4HDD3o87r312wB+CNx/M377N38FE+N7MZcfR6VYQCWKQMBbh7w+4shHHIYarllD0inYIw1IA9KANCANSAPSgDQgDUgDPdDAZmCgVYCShgo2bftpBV5o3Z2FncPqT9MerenRrCBvd4OJrUJeV7PWfq32Sf2yvmXS0toxmQ5pXZ26571Z3f2d+cjdrlsX5O2u3nd7oFrHP1x66STkJcwbdD1xiOFBzeQ1cNuKNcjL3xjs59DV9BPBLjXBZzB+NsDVhkZQGa5+x237QalvA/LGiKIy4riKUjiBA8UpHMhVURgvwB/PIjuWx+h4EfszBewZL8Ebr2DfeID8+F4Uxj2MZ0YwNrYfhTEPxXEPI2M57B8vYSwzjkxmFOPj48iOj6I0thfF0X3IjBaQHSshPzaC/PgBjI/nkB3PIRjdh2B0PzLjRYyPF1A4sf1cZhSFbBblTAYTuRwqpWICd+MgQBz4iIMiorCIOAoUzOlBMGezFwUtV0BFGpAGpAFpQBqQBqQBaUAaGFwNGBhwAQDrBh92wrrbtv1JU4OrqX5tW9NeIwAmyNvdYOJmkNdtq3Td7Z8MmO5EP9WLbTQCvenz5fRWrqn079x+N10X5O2u3gclYK3zGA7dtAN5Ce/sG7OEegb4CPdYHwbIS1jJb/Iya9V8MSi2Edy1Nm5mLXvXNEB9cUhmaoGFsNe+C89l1s8I8g5Hf2PtPYh2C5CXD3hW7MUwRhiV4YdlFIoBisUApaKflELRR1JyReRzRYznShjPFZHNjiGXGUlsNjuOzPh4AnTHM2MYz2Ywns0jk8kjm8kil8shk80im8mgkBlPCudlc3lksyVks8VknVwug3w2m5RCPoN8Pot8voBivoQwV0SlWELF91GNODxzVC/M4o38E+dk5yO7lYd4rSOdSAPSgDQgDUgD0oA0IA1IA9JAOxowMGAQoJOgw/axVWjRznnpt7ou0howrdOaFs0K8nY3mLhTkLeT/VWvtk1N2r5Zd3Wb1rQ77a7XSOOmdVpB3u7qfRCD1zqnwdXQTkNeQj4DfIK8s7sa/G4H8rLtCf/ZZzSDu436E0Hewe1jGrX3IM7bBPIa3A2SzFdmv8YngG8YRfDDELR8oIvDGHFYRhDGCMIIURAh8AOUSj5Kfgl+qQC/mIdfLKFUCBCUIgSlEH7JT0qpFKDoB8j7flJKQZj8PvRLYEm2w3VKIQp+iEIQoBj4CPgQeuKhtOgXUUzWLSHyfZQDDtFskLeMclhFOSwnxxpFzEhm0cuofCANSAPSgDQgDUgD0oA0IA1IA9LATmogDQBs2gL/BhW6ZW2/tHYsO3m+2paun7QGTGe0rv5YF+TtbjBxq5A33U7d6p/6YT+W5Ws+cPWb1jan3eWNNG7boXUhL6GLZVE1CrK6mVWNlmted68d+Vv+7rQGBHnb09gwZfIyQ9nN2G6UzcusZldTHKKZGibEFchtT2ud7gu0/fba5wzIS2gbx8zUjRAmQJfDGhPuMgO2DnuZ2cvlQWIDxHFU/74twW7I3514wQtsSOQQUeAj4nQQIwoqiIIq4nCiDoe5rZDQOEIxCpMSngSw3IaPIAyTdQJmEEdllOIYQbkOafmNYD5kBmEAP+S69X2VwwDViIWZvIS73GclgdEcclqQVy/ijV5WNE+6kAakAWlAGpAGpAFpQBqQBtrTwGYAoJdQg9AhfXxq7/baW/4703+uxlzgxbogb3uBrFYDgWnIe/ToUVQqlTP6AWunXvZPvdg3IaxBXu4/3Uc2ur5dfbNuvmtkBXm7q/dWrw+tr/bppQZcIEeIlwZ36WxOdyjiRsM1u5m8vNf28ty6se9hgrxpwMtptjc1Q13Q32xzG5qZvmHpRjtoH+pHe62B0yBvHewS3kaI4hgR4W0cIo4DlOM66K3D3ThZh5C3WCwkENggroHWkKCV20mgbhlhECaFGb5RQOA6gYglqgNlAl4W/p7FAGw54vdziwiiAH7E/ZZPliiuJOsxi5jbJewNIz8pBNKEvOWohHICqO27ImbPfAlr9OCqefKTNCANSAPSgDQgDUgD0oA0IA1IA1vTQLPAfy/AxUb7TEOM9HGrvbfW3vJTcz+5mkqDL0He7gYD05CXQziWy+WTMNPaZ6M+YxCXuXDXrfNczSfWV6avdVffrLvrp+vcHoPxNnSmtUejgCiXNZqved29ZuRv+btbGhDkbU9rgw5509A/PU2462bvGuSlX+xeo/tKexrrVl+g/bTXTmdAXgJeK5bJyyzecswSJPA3jCdQCicQBGVUggImwjzKQQFRWEoALX8XRgS1BLsxwqCMkAA2ZEYvS4QorCJkicpg1q5B3jAMwGKQN45KiE5A3nrmMEFujIDbZUZvkr0bIDwJeYME8tazjy0DuXTiO7zcrhXB3vRDuqabv6DLN/KNNCANSAPSgDQgDUgD0oA0sLkGLPDfKMjfT5AkfXx23GbV1pu3tXy0sY9MS7RpvQnythfIajUQ6AZ6WXchr9s2/dRHdftY3Exe7tv1CzWcvt5dfTfSuPt7bs8gL7XvBtzTw2e6y1ptZ63f3etK/pa/d0IDvOYt81KZvK1rqt8h79zsLLZTZmdmYGV6mtm69TI1NQkrXL6yvIz19TWcfeQIjh49G4cPHUJtdRWrKyuJTeqcVpEPBlwDDSBvHbgmWb2ErSGHaWapg9Iyh3IOp1AMVhCWZjGbH8FiaQ8mgjFEYTGBrYSvBLwEqgS+HGq5nqXLeczwJSyuIIonkqzcBPQy4/dEVu/J4Z7jGH4cITgtm5iQlt/7jVAMAuTiArJxHqWYQzXXh5G2h09+P7g+xPSpoabdIadtPdmNX07lH/lHGpAGpAFpQBqQBqQBaUAakAYaaWCzQH+3QcVW9+cCCLdu59PoXDVP10ArGjAtNQJggrzdDbgSIriF/udnyrbaXwzDemnI654z+0hXz43qbj+arnNbgrzd1byAhvy9WzQgyNueVvsZ8hrcnZ+dRavFAO/M9BRmZ6YxMz2J6akJTE1Uk8J5K8tLOLhew5HDh3DO2UcSy+m11RXUVpZRox1wsLdbrnMdZ3vX+Vb8dwbktaxagtdiECEXxsiFEQp+CUEph3JpFGHRR1x9KL7zrTvxS0/5GaznPEyHowiTrNsyorBy8pu+dchL2Fv/Vm99OOUAYVxFGE8ijCqIwrIz3HKEsMx1w2S46LAcg4XDRpdPlhiBX0Zlehpf/e7XcOFzLkShXITPLODkW74nvtV7AvImwzZz6OYThaC3DqH1ktrKS6rWlV6kAWlAGpAGpAFpQBqQBqQBacDVQDrY3yi478KCfqmnj9Om7Xzcc1Rdmt+OBkxLtKYvs4K8nQ92uQExF/AaUGCbbgQ2+6Wv6ofjMN2aTWs6PW3rmeU5uJDXbRtl8nb3WnB9r7p83w8asD6Z2bw7nsl75AhWarWkrNZqWF2tgXaltnqyJPM4f8PSG60QUG5WmMW6sDCfZLcaVHUtfdqrYsexEeA1mNvIEvAS7s7O1C0hL6fnZ2ewvLRwEvAePXIWDh9ax3ptNQG8hLwJ6F1dSTJ6eZ+x0g+a1zH05noadL+fBnn5kMus2yBkNm8VucosPvqVb+K79wN3AXjg/mP4v//jc1DOecgGD8b3rgd++WcfgbPHPUwGIwgqMYqlAKUSAW0FpZKPaqWaDNHMrFoOw+wHAYpBjEJQQTHgsgoqYRnlkC+OYQJ4/WRYaIJYH5U4QCUOk7+wjPnNlMBHFFdRKk4gmpzGN278Jh5z8SOxL+uh5OeS7/7yG71xeCKL14G7grx6Od/Oy7l+I91IA9KANCANSAPSgDQgDUgDp2vABVhWt4A+bT+AiVaOwT121u2c1O6nt7v8sXV/mIZo0/oS5O1tgI8wgVoW5C213FentWz9ZaP5Nk+Qt7d6H/TAts5vd+urc5B3BoePnI2FtbWkrNTWsFpbw3KthqXaKpbWVhJLCLy6ym+BNytc3hsf1wFvHVgauExbZq4uzs8lWa6En26Zm51JhkruFeTlfuvHwONoXJiR27wwi5fDNJ8aonl+bg5LS4sJvD14cB1nHT6cDNG8tlYDSyMo3qv20357c90Mq9/PgLx80CXkJYAdiabwni/+Ix7+vBdhTyHEwx72YNx5y7/gmU//WewtnotvE/Je+Ggc3O+hnN+DYuSf+J5vBX40hSCaRBTEKAc+KmEhGfY5iKYRlBfxmS/8E17z2v+EahhiKoxQiSZQqUwnQzAHcQnVchFTlSKqQR7lMEQxmkQ+mkBcraJSriDIVRDEk/j6zdfg3Geej/3FfSiVMsn6k2ER5aCEKPBPZu8a4KVVJu/WX0z1Ei9fSQPSgDQgDUgD0oA0IA1IA9KAacDAlQXvaRnAt+lWwGo/rmvnQWvnatZ8IKvrYSsaMN3QurpiXZC3t4E/Qd7W4a7116ZlV9+NNG7r0fK3yuTtreaHNeit8+5/3XUS8h46cgQLazXMr9USuGtZvcu1VSwS8q4xo5dwd71J4bLeQ97aKoceblwIeRcWZhPIOzc7jdPLTM+yeE+BZR5D8zLDoZg3KPwWb/0bvIS901iYX8DqyioOHjyII2cdSSynWWqrhLxnFvUD/d8PqI3ab6OmkHc8F2BP3sf7v/B5PPyip8Hbvxf7xjL4y/d9GL/31o/DKzwS130feO7jHou5vR4mS/tQKI7CD30Uwyry4RKKwSLioIzJMI/JaB/KUQ5j2Vnk4yP49Je+gVf92q8hznmo5PYjn51EvriIbCFEEGRRKexBJe+hUhxPMoP3BQvYGy4gWywgLuRQHQ9QCSbwlZ9ci4c950J4Ix5yuVHM+fuwUNqLapDbIuStfwt4Ky9pWkcv89KANCANSAPSgDQgDUgD0oA0MMwasMC+BfyHwRJS8LyHud117ntH12kAACAASURBVK33e3atNAJggrztB7PaCQgK8grytqMf/ba316/8P1j+7wTknZicwNT0FA4dOZzA3DrQXcZKbRmrtdWkEPQuJUM39y/krR/rClaT4+axn1nW1muYX5jFJIcynps+rczO9QPk3Xi4aP4BULoQ7NbLNKYnpzA1MYWZqRnMzsxhaWEJB9cO4sjhIzh65GhSr63UYGVtdQ1WaqtrCfRVnzFYfYbas3F7NoW8o1kf+0sx3nvVZ3H+RU9NIO+e0Qz+6v0fx+ve/r/gFR6Nq68H3vP6PwDu/QHwwN34u89+FlEpi1J2HNWJBXz/B7cAD4ADPeOOu27F8uoKJqMl3HTD/bgTwO0ArrvmK1icijBRWcQPf3QM959Y/9idt+HBh9dQGdubQN1f/y9/gB/fz23dAxy7FQ9dOQthsYKv3Hg9fvPPX4fbANyP+/G/P38ZqnkP1bAOeZm1m5QTwzZz6Of6UM58SYvr3wPmN4Gj1l/a9Bv5TBqQBqQBaUAakAakAWlAGpAGhkEDBqwsO2sY4K6do52z+WAY2lvn2H6/ZnoR5G0cjOplkE6QV5C3l/rTvvuvT1Cb9K5NOgl5Dx85jOXaCpZry1heq0NeG86XkJdDN3MI5+ZDNfc2k5eQd6W2smGprdcwtzCHiakJzM7PYmZu5rRyKqN2Y9jaq/XOBLzTScYus3anpqYwPTmdQF7axfnFBOYeWj+cQN7Dh87Cem39JNQ1uGtWkLd317X61O77vjHkjcrI+VXs8at41xf+Hkee/ix4+8fxkPPOxS03XINnPeOZ8PLn4/ofANd+8t1Y3Oth7SGPxrW3AC962hOxXvBw7IZ/wdve9CfIjY9jfybGzzz3V3HTPcB5s1OYH/Hwd1/6Al74mtfC25dBIYhx443fw1ve+HoUxvdjZKyAJzz3V3DjncD50xN46jlLuP6m72Dq8CxKIx5msntQHC1htFDG12/5Pt7/hU/BOzCOI+c+DDfc/m089eJHI1cYQeD7iOMI5ThKwC6HfWaJwwhByUccllEqBChHVdS/48v1+D1fZve2/1KnbciH0oA0IA1IA9KANCANSAPSgDTQDxqI4xhu2eyY0oDKpg14GgAdFmvnbX7YzH9aruvetEJr+jGrTN7uB7/cgKMgb/uQ17RsOrfpRpb3CRuumb4n1LH2WFlZOVnnPHeZrSPb2+tF/pf/O6mBTkDeycmJBBSedeSsk5m7qzVmxHJI33p7riQAlZCXwzFvVnqogROZx5aBnLZr62uYX5jH5NRkHwzN3DpINshLqOsWAl6WyYnJpMzOzJ4civmsw2fh8KHDWF9fPzmv0TDNNq+T+tW2e3ht9Ohb2f3a5k0h70gugleq4AP/8FVcD+BmAMfuuhPPf/rDkdnrwcudh2uuA371SUcx5Xnwxmfw4Suvx4uf+Bi8+sln49ZrP4WJ0EN2/AC8zBQ8/1x89Mrv4fdf8SKseh4+8+Ur8LzX/A68/REufOZzcd21/xvVwEN+xMO+cR+efw4+fOV38fuvfAXOHvNw881fw63Hf4BnPe1xKO73UNw/imIhj6/+8Ot43HOfBG/fKEbyAT7+5U/hcc9+Avbms8j7EarlCJWwiDgowC8V4IcVRGE1+Q7wVBCiElSS7wGXE7hbh7xJhq8gr0C3NCANSAPSgDQgDUgD0oA0IA0MiAZcwMv6ZhDSAveNABWD+MMCd+087ZxpzTeb+VDLhxv0mk4aXUOCvL0NCgry9g7yUvsuyBXk7e210K/Bah3X8OiiM5B3sg55zzrrtD8iOamrBPAyS7Y+dPPJ+bsQGhF0LiwsJEC0V9m47ey3EeQ9CXgnJzF5onA9tpPp5dChQ6fdS3ZzG+rYh6e/62RbN4W8o4UYe0oR3nvFp3HBxU+DNzKCXGYchcxeeN4YvPwF+M73gVc96RzMeR725Bfwsc9dh3/35MfgVReu48arP4a45GFsxIM3GsMLzsWHPv1tvOKJP4uVvR4+/YUr8Lxfey08L8QTnvZcXHvNFxEXPIzv9+CN5OD5h3DZVdfi5T/3s5jxPJT2eBjPe/j4l7+GYwBe8qTHoFbw8O0bvoxHPfMCeN4ejI77+OgXPosLLn4GvGyMffkqwvwYJgp7MFMZR7GUwWhpCgV/Bkt+CQu5UVSLAcphFQnkjSKEUYwgihEOSDBHgYXhDiyo/dX+0oA0IA1IA9KANCANSANb0YALpBpBKYOdsqWTWZlpn9n0VvytdQb/ujQ9NLqeBHl7G9AT5O0t5HWDnIK8vb0W3LZQXW3RCw0YtGO/TFjoZnOybhDQrAsU5+bmTmavcjnXT7I/JzeBvIS5AwB42V7DBnkPHjwIPkPRpu8fvdCv9ql+s1800BDyhlEZY7kA42EZl115OR530ZOxb3Q/8tks8sUcvLEQXuk8fPu7wMuecE4CYfeMTuBvP3s1XvT4h+PgqIc7f/RVvPmNf4ix0X3YO1bEYy/6ZfzjN2/Ecj6LiT0ePnXVl/CLCeTNIVeI8JMffgdv/ss/SqDwntExPO4XXop/uOYHWCiM4QkHp/CrL70I3h4P3lgVl3/5avy3V70ciyMevnvD3+Nxz3okPM/D6FgRH7ni83j4z1+MmXMvxHdvA57z9Cfhieev4Z6fXoenPv1CnH3Bk3Hz7cCLn/IkHCqNYaoUIkqyeSvJX7MT8PqCvJv+Zb+CEoMflFAbq42lAWlAGpAGpAFpQBoYHg24QKoRlBLcPR2KNBqS1LJ87bpxs6dtnuxwXlNpvQjy9jYoKMh7en/WSv+e1rLdO9Lz3WlunwDm7LPPToLzbkA0HaR3s3zd9VTv7TUj/8v/ndJAzyDvLsjate8Hb2TX19ewsDCPqalJzM3OnlFcKN6PdYP3LtxvlMnL5dQg7982IkT6/tEpjWq76v92gwYaQF4O3VVGoRCgEET42Oc+jSc88yk4MD6CbC6Dgp/HWDHCSHAY3/nuXXjxUy7AxF4PY5kK/tenv4IXPukxiD0PxUyEH/zobuABJP9+ettPcHBtDqOeh7179+JVv/u6ZAjo6675GhbLAYLCLH70o3tw//38wT346a3fx+HaDLJ7PGQOHMDb3v9R3AbgbgBXfO5K5PeOIMpn8Y3vfg2PfdpjsX9kBGPZAj78mU/j0T//HCyc96QE8l781AsTyHvnLdckkPfoI38OP7zxOF745AtxsDh6EvIyk5cv3IK8w/PSrQCL2loakAakAWlAGpAGpAFpYNg1YAF6sxaYbyXoP+zrms/M0pemKwO9Ni07PH2OXVO0pg2zgry9DRgK8gry7oaArY6xt/2E/N8d/wvyNvdzHe6uYG21eTm4XsPi/BympyYwPztzWpmbnUmgbz/CXTumZpDXhmk2y/VcregPgprrRn3XcPrmDMgbhhHCgC9eMbL5PMYKeYzkcxjNjSNXzCFfyiFT9DFWmEYuV0Z4wEvKgQN55HIxins8+Ps8eJ6PfaOzyOUqyI+NIs558Mc9ZLMH4I3n4GVieDkfUc5DOOJhdH8Zo+PzyOaKKOb2Isp4CEYJiw/gwHgBXmYae4pzGD0wCj8zhgN7MzgwWsDezAgOFEYxmhnDWDaHkWIRXrYILz+FPbky/OwIKlkPYcFDvjgGbzzCaKaM+WIec5kDyXDNE+UplMMy4pDDNJc1XLOGqj4ZlFEQZniCMGprtbU0IA1IA9KANCANDIMGXPDE87Vpg09mhx3cbvf86T/zKf0ryDu8/YrpgNauK7OCvL0NwAnyCvIqCN7ba1D+l/9NAy64I/hzMzpZNwho1uAgbVvDNe+aTN4V1FaXmxZC3oWF2QTyzs1O4/Qyc3I4a9dv/VS3dnXb3YbcNsBLm4a8ph9Z9SXSQF0DDSBviCAM4McB8n4xAb2lIESmkEfBLyXLSiUfubyPzHgWpcwBlLIjyGbyyGTyyI3uRyEzimzWRyZfRiYfIZcvIcxnEBWyyGZyGMuVsD/vIxv4yOf2oZjdl8wfzxSRzWVRyI+jlB+BXxhDITuOQqGITDHCaNZHdjwDP59P9p0vlDA2NopCIYfxzCjypQKyxVKy/ZGsj9Fs4cR3hPk94Xom8niuhNGxPMrFEuJcDnEyXHN8AvIS9JYTwD0MAR6d4/AGHNT2antpQBqQBqQBaUAakAaGUwMGngxGGnRK2+1CTv2u+Td7dc0N1zVn11ozyMvvyTEwxQB3esjB9LQCWDsXxDSgwOuxWCxCfVZrwDd9rzCdp+e70/QxA/QarnnndKw+Qb4cFA1Yn8w/viF8dGHfsEPe+neDV7BaW25a1tZrmF+YxeTUBGbmpk8rs3ODAXmr1WqiC2qFfyRnz0+Dcg3oPNSf74QGzoC8fNANoxClqIRS5MP3g/rwzb4PPwyTv0qOghChX0KpWECxkEusXyrBD3yUSnxILiZ/qVosERSXUQwqCP0IUSlEGFTghxUUgxAFv4hCKYNiKYN8fhz5fAa5fBZByO2U4JeKiEIfccRjCBHwr6J9H0GphKJ/Yn/5AiLfR7GUR9HnvgOUSvxL2SA5hkKhgFwuB1o+fNa36yPwwyRzNwoiTFYnkzozea3oBXy4XsDV3mpvaUAakAakAWlAGpAGpIFh0ECjgHzyjsT3Padwnsr2fWC+NH/TDoO+dI6n+lG37U0PZi1ISZgryNu94B59vb6+nnzTj1oV5G29jzMNmzWd23Qjy3uJIG/3dL4TwWJtQ+3VLQ0I8m6gtdoqVmorG5baeg1zC3OYmJrA7PwsZuZmTiv9lLXb6Fi2ksnbDPJSO93SqfazgU53QVb8MLRfE8hbB71hMmxv/Ru9zOb1Q76wcLr+/VqC11PFXmbs5bU+9HEYVZCUIEbEkkyXEUZxAoWjBOAS4gYJXCZgZvGDEoKglMx316nXQwQE0YTOCZTmt3RDlAiZCaAjbt+Op7ENg/pxmtXLaGM/yS/yizQgDUgD0oA0IA1IA9KANDA4GkgH5AVyW4ccrfjMBR7me1pdU4NzTTVrS7e9XR2wbpCXQSdCx3TwSZm8nQkmMiDMDKBDhw4lSQBMBhDoba0PTGvZdJ6e704L8nZGz+l+Q9Py827UgCDvJrqtraKe0dvYrh9cx8LiAqamp5JM6Ln5ObilEVjt5TyDumYtc5tDNFuxYZoJd1k3yMtnJ44IkYa7fGbSc9MmOhKIPeNZezf2lxsdc0PIe/pLCmFtjCCMksL6Kci70YsZ1+PQx/USBjFY6tO09e8/ufsyYEvIy2zeMPQbQt4w4nDSdcgbRAS89cJMY4LoIOIxb3RsZ+7bPQ7VN/ad/CP/SAPSgDQgDUgD0oA0IA1IA7tLA+lAfCugUuu2BkGa+cugh7WFWV1Lu+ta2mp7WfvSWtub5bCUhI0MVKaDlQzgKFjZmWAlfU3AK8i7/T7NNGzWdG7Tjawgb2f0vFGwV8vk892iAfbLvCdquObtaZbPEouLi8lwxoS3/E6xW3oJdBvt2+Cu2a1A3kqlkgBgQd7taWS39AU6zvbadwuQt/7CFYQEr638xbEB3a1DXr4s1UEvh4XeGPIyc5dQ1wAvbR3y1ucJ8g7mi/JWX6i1ntpfGpAGpAFpQBqQBqQBaWAYNWABd9e6QfdmAFLztw89WvWd2x6su201jJod1HN22zXd5gYa3SxeF+y6dQW92gt6uf6zoZoFebff36W1bDpPz3enBXl3TsOunlWXXwdBA4K87emY97WFhYUEgjaCqv02z+Cu2a1CXq5nkDetez4z6bmpPR2lfarp3efPLUPe1l+8Toe8ltHrZvI23yZhcn0I50aWmbyEvC7gTdc3g7zN961gmHwjDUgD0oA0IA1IA9KANCANSAO7UwMWcHetBdubwUhbvpFt9lvN3xos4ZCwNixs2s9uW+m6253XXaN2c9s13ebMvLFsXgtMmlVgrXOBNfO7C3nVh22tDzM/pbVsOk/Pd6f5Wwb0Ocwmg/SuxtO6b5TZ7q6veueuD/lWvu2FBgR529PdsEBeDuUsyNueVnpxfWuf3WszQd5NhnVu9LKmeYPz4q22VFtKA9KANCANSAPSgDQgDQyCBizQ7tp0kN2C9JtZ/m6zdbS8NTDSyF/WPm6bWX0QNNnoHOz8XNtovUGY556jtbVZfmOOgS+CXga4l5aWsLy8fDITJQ2+FCRrLUhG/7mF/jOQQMusJ16T+XxefV2ptb7MNGzWdG7TjSx9LcjbmoZ1zctfw6IB65s1XPP2ND/okJff4+VwzXxu4h8KsaSvDbvfp+drenuakt92p98EeQV5k+8jD8JLtM5BAVppQBqQBqQBaUAakAakgWHTQKMAOwPq6UB7GjJaZqlll7rL+Vt3WvXWIEir/nL9zbq1Ke0g6NnOh36xumsH4RwbnYN7junrkcv4Db2jR48m34dlhikhL+cxuCbIu70AmwV6XUt/MgjODCD6m0Cd/i8UCklp1Ae2eg0P0/qNtEx/pue70/SPIO/2NK1gu/w26BroOOStrWKVZTVVms1Pr9fD6drqKjYrCeSdrw/XPMdv8qbKbh+u2SAvrSBvSsM91OYZ15OO5cw+pss+EeQV5B2IwEGjl2rNU5BXGpAGpAFpQBqQBqQBaWDQNWAgKR1Qd6dZT0MIQd7Ogtu0v1uZtrZj2w6afk2vro1jfupp8Poq9xytTdOW35hjoIyQl4FaBrs5Lci7vUCmC3dZp085NDMBL31L0Ei4m8vlkixe6wdbuT6Hfd20hk3n6fnuNH3mQl7TeSOtu8sURN7edSC/yW+7SQO85pnFuxOZvOxnOKwvsz6Tb7geOQsrtVXUeG89AXqTPqa2msznMpvfjz4zwLvG0SialINr61icX8D05BTmZ2dPKwZ8+wn0so3cstk3eQl3WdimGq5ZfVs/Xqf9ckwdhrx8WWtWNnqJ48ts8+/yhlEIlvR3eG2a3+PVN3k38q+WDWIQQeckXUsD0oA0IA1IA9KANDA8GrDAutl0QN2dZj0NJgxuNMpia7R++vea7hwkdtvO2rcfr20emx2XW7d5ZjnMHgOMDLxyHrVjy2ibQV7Ob7bM/X2/1q3taN02deu8/nj8zC51YaTByn4JHO2W4zC/0fKYzafMkKaW6O9MJnMyk9f6QfVnW+/PXP2ybjpPz7dp861BXhui3DRlbWXTgrwK4psWZIdDC92AvKsGeR3gS8A7GJB3DYvz85ienDwN8BL4DhLk1Td5h6M/UL+//XbuIORtN8BioLexNZDbzPbri56Oq11d6PfSkDQgDUgD0oA0IA1IA9LA4GvAAuebWQuku5ZBdXeadQu0y24dZvTaV2w3t/376bp3j8vqpjkeZ7lcxtzcXJJJyWzKdGFWBtfjb+28bDtmbf5WrP2mmd3KNjqxjns85p9mlj5hcIuZKiz0mYJdWw92ERQY5LVsHw6BzcCw+dy9pgV4t98Xmj83suZr83OSVXfWWQl4Z1sZzBXk3brG1R/IV4OogXYgbzpD1TJ5+cdl7HPW1textLqCFd4faqtYXFoCga/No+33TN7VlWU0KrXVFbAcPMjvzM9hcrKK2ZlpzM3OnFbSPur1tJvFy7pl8tLyfs3CrF0Wy+K1b/Lavd2uA7uPNJu2+bLqO4dBA30MeQc/cNOJl0htU7qRBqQBaUAakAakAWlAGpAGdr8GXDi0UX2jILu7zALustsHG932HduP+6SlBvrpum6kScIcF+4yY8+AZdpyGeEOA3jMsHS1ynqr59roeNx5rW5vJ9d3jyN9nmxfg2C09AV9YhmoHMaZfkoHMochWNXsHNO+4LQV+o3f7KPfGDxu5G+7js3vNi279b4x7ddG0+ZPDo9NXxvk3Wxo8nT7NtOB5itoLw0MhgZ4zfOZgIUA0oV+rKeh4EaQkusSEhrkXVpexvpZh7G8vobFleX60M0nwG8yjwC40fd6u/wtzY20vMLjTpXVGj9HUEsAL+tz8xwtZQIzM9OYnZ1JldnErxv5rZvL0u3ptrcg72Bc0xvpWcs618aCvAP47Z+dfCHVtnZ/gFBtqDaUBqQBaUAakAakAWlg92lgIzDkBtQZSHenm9Ut4C67dZDRT75iu7qaSNc7fY1zf9yHa91jsCGZDew+6EEPSmBbGu7aNEEcC6EcAz78PUGQe552Tu5+bF7auus0qqfX7+a0ezyNrk8uN63RBwbFmMXCbF76jH6lr4YZgNm5m7VAIacJDukn2oWFhZN/HJH2t/mZVpB3+31h2q+Npulj+/6xC3lNx9aOyuTtXMDXrhFZ+bifNcC+YCcgr8FDQsOT2aBTU5hdWsQCM3YP1rN6LZN3ieA3gbzM5q0P8d+PfmIfaYXHt7ZWSwrncbQKO2/absLa7e7LPV7WW4G81AmfHa2d7D7SbNrmy6oPHAYNCPIK8rb8V9LdfCHWvnZfQFJtpjaTBqQBaUAakAakAWmgdQ0wg4/FfJcGQy6cSNcbBdjT89K/0fT2AUcvfZduV9OJ6aZTlvtppk8uY6DNsigNtlkAksvSxeClgV7+lsG+ZvvgeXM/PD93HTtf80Mza+v1wrrHlG4/Oy+bb9oyAMnMaPqFfmJw0wKa9K35dBgCVzxHO3ez7nnzjwroE/qLbWw+N7+aNf/Smo/deao37hfNf2bNv7ScZ9O23Pyby+WSbyAL8irA7l6vqksPrgbYp3cC8nJUjMpEFZXpKUzOz2J+eQnrhw8lGb0cpnlpvYbFNWbydg7y1lZXsROF9zcrfF6i/whZbVhjPidsF7p2+3c8VrcI8qo/cPsD1bevB0FeQd6TgaRevPBqn60HAOUz+UwakAakAWlAGpAGpIHB10CzoDmD5QIRjUHEMPnFYIoLWEwz2+kf7LcbWcJV2x8tgRqzSAh1G0FIN1BjwUlad76BSgPEXGYQ1z1H22+jc+MxN5rfT/M28iuXuedqOnbnsU5fuX5qBDtd3w5SnTqzbxSbZpi1e8455yTaS/vK/G3zbdp8K9t6H2q+TFtXv65f7V7F9RnEX1paOpmV7mq3UZ8wSNrVuWw/YC3fDYfv2B90AvIm33SdnER5ahLhRAV+HCXQl5m8h46chaX1FcwuzWF1bRXr62vJswnvNTupuzrgXcHa6tbKem31tHX5LV5m7rKf5D2PzwAGdmkNkAry1q8V996yk+2obQ1HX7Tb21mQV5C371+I++nlXMcy+AFVtbHaWBqQBqQBaUAakAa6qQGDD7ZPm04H0t3gueqtA4pB9ZnpxHSTtqarzWz6d+lp7ofbILhhfXFxMYFuhLuEvCwMPjYLsG0EeQnvWGwYPm6T63O4RQLf9LHwOBrN2+wce7k8fbzpaWtHWtOqO4/D3vL4GdRloJc+Mui524NSWzl+6oqF52yZ4vQBA9z0C33m+itdN3/bfPOxbPt9KX1qfmT/wOzdfD6ftAf1SviQhrxumwvyKnju6kH14dMD+/adhrzsc5Ihm/l93ukpxFOTKE9UEVcriCplTM/NJJB3/cg6VtdqCdhN90U7oUWDvLXVZbRS1tY4WscKDPLSP3zuYtatfbeWlue5mwAvj9/N4rX7A8/D2ixpt8nJ5HmH2dhJRnalkkzbc6K1TfqZMz1t68kOX78yjG0uyCvIK8grDUgD0oA0IA1IA9KANCANSAM90oDBB7MGIdLWguiy7UOJQfRhWi+mp62CTVu/mbXtE9oQ5lpGCesMpBC+bRRcawZ5+Vv+joXbIsA7evRoYhnMY1aNew52fDweq9O66/Rj3T3WRnXzbzNrmrXsSPqFbUAfWVts5P/dHuwyjdj5MthtfwDQzGfufPO5zTN/yjbuT6mzrRb6ML0u+wkrBiTYZry+2YauHtNgZZB17J636oIO0kBdA7zm2S+wEAIa8DObhoLNhhdOr5cAxJkZTMxMo8pC4MvhmyeqCfCtTE9gfnkBa+v1PyBie3DEgR1tl9pq/Xu/tWWsbqEsry5haWURi0sLqK2t4OChdazWVk8CUAJP8wutnXMzn/TjfDtms+752P3C7h+CvOond/R6XB1sfwry9iiY048vnjomZa1IA9KANCANSAPSgDQgDUgD3dVAGj4QQjBobjDCrGBEYxghv5zuF9OL6Wqr17O7vtVdS6BGsMggrEFYA7sG4CwQY9OutWVmXehrkMdd3wAmszVZt2+t2vmZtWPc6nn2aj07zmbWzmcja1rnOoRqbBP6jj5iu9B/9C/nmS/N37vR2vnw2AkHeZ6c5/qQvqA2XL9xOadtPba51W1Zuo8138rW+5M0tGUmebNi61pbMDhvgXmzDNwb5GVbunq069/mue1u82QHOzCt9h3u9uU1vxOQ14CmwUPa6ZkZTM3WQe/k9DQmpqaSksDeqSqiSoyp6amTo0RY/2O2bW3WVpNv/vK7v1stSytLOHzkMA4eXsf07HRyj3NBqHt+rNt57xabPn733AR5h7svaPt6G3CIu5l/BHkFefv+r5579SKu/XY3wCl/y9/SgDQgDUgD0oA0MIwaMPhgkEKQ4XRoKX+05g/Tkemq2TVlyxtZwkNuh1CnUqkkmS0EbIQzzLZ14e5mAYd2lltmL4O/3D/3y2CgQT0epx2rex7uOds67rx+rLvH36zOa8HaN20ZkKa/6Cf6PB2gToO0dtplO7/l/lsp3AfhPs/HzonwkECR524+cus2z7XptuYy/kb9yun9ioHaZpbDL7uFfuS6nGdDiTNwv7CwkAwlSrjLvsMK247L2IcI8iqIv50+RL8ZXN3wfrWTkDcNO2fmZhPQO8UhnE+UickJVCeZ1VtBpVofCpi/Yz/FeymPye5ZbWsvyeZlRu+pwm3XTnxrl/M5Tct5i0uLmJufw+TUZNKHsm81EGqANH2Ou2nazsGsnRutIO/gXudtX0dDDnC34j9BXkFeQV5pQBqQBqQBaUAakAakAWlAGuiSBlwAYcBB0OF04CAA074/GsEvF3i5OuS6VkyThKMMuBGsGmjrJORNB1MZYLVisJfHwTqPyUCvgU/3fNzzHBTIa32EtVPa8pwJ0gyM0kdbkq+tfwAABxxJREFUCQh1ax1r37Rttn8eP/XG8+HwmTw/yyRl3T1/0yznuTpg3dWC1bme+pjT+5g03DVfm3UBL+tcn9/epY/ZTxCMMGDfKIuXwFeQV4H7Zte65ksbnYS8hKWEvMzoTUNFQtSJySoIfN2+i/ccHhPvP7Sd0Cjvhdy2WdsHp/nHMew32bfaMbt2NwHdRsfqngvrPE8rgrzqD+xakG1dC4K8XQrm2AuFrDJUpAFpQBqQBqQBaUAakAakgeHVgAskBBtOBw0CLzvrDwNhpjkXerFu812/E4oywGiwkGCVwI2lU8FOBnIM/llQh/uy/Vmdx2DZqrQc/pV9KY/fzsc9Ry4bJMhr7dnI0gcEb7Tp7/WaH823ZtM+t/mdsLYvs9wH67Yvt43ZzszqmpubO61ded7Wvq4PTMe23NZpdp/leq7mh7GehrrpacLdNNh1p+kzQhG2EYP0DOQzOG/zXGBiQzZzXWXyth60tWtEVr4bVA2w/+9UJi/7HQONabjIaYJeAkb2X3z24R+QWZ/FZww+C3XC77z/8bxpec/jfTs5ntT3zA1+usdu57NbrXsurNs5WjvYvcS9j7BtOG0ju1ibpJ9v0tO2nqz6z2HQgCCvIG/Dv25t9kKk+cMbkFTbq+2lAWlAGpAGpAFpQBpoXwMukBBs2FmoOYywZivn7AIxu4YNhNFaYWCTGSwMOBLuMpjGOosFzgzSuYCum4ETHotlFNPyOBjotHOgJdi189wt1j3+dN1tv2Z10wGXE9jRB/QN27FZ+1hbNlu+k/NtX7QMZnPbrNs+qC8W0xu1yLZLny99w/lpH6WnDe6bdXXAbZq/htWmoW562jJ4m1kG5nnd0TLw7gbn3QA9l1mgXpBXQXa73mWlBVcD7Pu7AXkNim4GGa3foiVcdI/Vrbv3MHd+s7o9R9Hyt2Z5PNZv0hr0bHa8Nn+32s38b76wewefBwR51Wc0u640/5Q2BHkFeXfdC7D7gqZ6+4FG+VA+lAakAWlAGpAGpAFpoDsaIIgwaDGscEHnvTNg23Rkdit+5brUIDNVCL9Y57XPusFdA6iEbe5QhRacZGDSAptuvVtBFjsOHhuPkRm9DA7zWBgYtXMatD6N58Vi7Z22bP/0PJumjyyD0rKSCFqt/dK2E22Z3ocFt2lNczw2tiGBo52vWTsXm25m0+0uyFvvb9IQNz2dhrnUEzN3OSQzC5fT54QK7CsMQriWgXm3uKCEQXpB3lOB2E5cY9qm/LtbNcD7QDchbxqOutCRfZoLGa0f4zq8j7nPRXZf28zvth7Pk/djrs8678PsG20f3K/1qe4xpY93t0+758a6nbP53vU//SPIq75ts2tMy+saEeQV5BXklQakAWlAGpAGpAFpQBqQBqSBLmiAQXLCiq0AOa2zMzB0UP1o0MvsVs/T1R/rDLAxaGmwlNaCmAxCWrEAigUrOe3WbXmnLY+H+7Dj4rFacJhZq+khnA368dqz+m60zaCm2/5WT1uDc/QZgSrhuPmx0+1l209rhfs3+Mz2ow4ZyCVY5PGnz9fOKT2/2bS1sSBvY8ibhrrpaXdoZgJhgw+EC4S1FqRvFJznum6Q3rKxBHkVqLf+QFZacDXA+4Hdx9nHuP0K69bfmG0FcrLfaba+u8y2TevCRuvPOM/6P3tGsvsa7WqtQZvWVlFbqyWF58jC+y/P3fZhlv0k6+5xWL3Z8e/W+XZeZnneVszfBr4FeRvoalXz3P5D9VN6EOTtQjDHXjBku5MhIT/Lz9KANCANSAPSgDQgDUgD/agBAgnCiq0COa0n0NtMAwa9zDZbz+Zb5h41yExeDn3HLJKjR48mhfCPgUsLllhA0qzN7zdrGccEhgaqeS4MGPI8XQjYj33CVo/JPY9GddPBZpZBbQbTrV3NdqtdqTG2E9uN7cSsUPqA+uR58fgbnV96XiO/uevYckHe9iAvA+zsJ6ibZkCEgXoL0Ju1QL1Zboe/Z5uzuHpLAIkTtKYm3eWqnwrgyhfyxSBqgNd8P0Feg49u30boyOcmPlewzntX8sxUW8XKiXIa6E3mrWClVh/9hOuyr+M2DWBa3fpNg7bu/lm3+YNi0+dn509r9wzzkSCv+rxB7PM6dU6CvIK8u/ovmu3lTVaBXGlAGpAGpAFpQBqQBqSBfteAQQwDb7KCuN3SALXH7DxCL0IbBlQNuBj0Y9CShcEHg3/9Dlzs+Ox4GUgluLZzYjCR52x9A/1g9d1kXYDZqL4Z3LXl1Bt/T8jKYn5jvVNBJ3e7lr3L/TKIa3DXjkuQtzN9ov2Rh9l05m56mhohUGBfQSvIq0C7ex2rLj3spAZ4P+gF5HWhaRo8utMGH3nPIoQ0AMnfE+y6kLfGP1JhVq8DedfW1zC/MI+JyQlMTU8ldnJqEnPzp0ZF4P6aHY87fxDqrm9ZF+RVf7KT/ckwb+v/BztmulGhAGv0AAAAAElFTkSuQmCC" alt=""></p>



<p class="wp-block-paragraph">大家进入的桌面不一定和我的完全一样，不过一般都会有如图所示的快捷方式</p>



<p class="wp-block-paragraph"><strong>⑦点击右下角的“一键启动”就可以进入SD啦</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="599" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-58-1024x599.png" alt="" class="wp-image-6697" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-58-1024x599.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-58-300x176.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-58-768x449.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-58.png 1174w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>⑧用完云平台之后，记得关机噢，不然会持续计费</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="638" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-59-1024x638.png" alt="" class="wp-image-6698" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-59-1024x638.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-59-300x187.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-59-768x479.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-59.png 1275w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<h2 class="wp-block-heading"><strong>3.一键式安装SD本地部署</strong></h2>



<p class="wp-block-paragraph">电脑配置能支持SD运行的朋友们，接下来我会手把手教你安装SD的本地部署，这里我们用到的是<strong>B站<a href="https://space.bilibili.com/12566101" target="_blank" rel="noreferrer noopener">秋葉aaaki</a></strong>分享的整合包，小白直接下载整合包可以避免很多困难。</p>



<p class="wp-block-paragraph">整合包点开链接就能下载保存啦（百度网盘）</p>



<p class="wp-block-paragraph">链接：https://pan.baidu.com/s/1GFClYmFszRVaYvQVvHJocw<br>提取码：6ai2</p>



<p class="wp-block-paragraph">具体安装方法：</p>



<p class="wp-block-paragraph"><strong>①打开上面的链接，下载整合包安装</strong>，存放到电脑本地</p>



<p class="wp-block-paragraph"><strong>②打开保存到电脑里的文件夹</strong></p>



<p class="wp-block-paragraph"><strong>③打开文件夹，“解压文件”</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="509" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-60-1024x509.png" alt="" class="wp-image-6700" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-60-1024x509.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-60-300x149.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-60-768x382.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-60.png 1300w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">④选择解压到<strong>D盘或者E盘</strong>, 路径随意</p>



<p class="wp-block-paragraph"><strong>⑤解压完成后，先安装一下依赖文件</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="581" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-61-1024x581.png" alt="" class="wp-image-6701" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-61-1024x581.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-61-300x170.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-61-768x436.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-61.png 1262w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">点击安装，所有选项选择默认就行。</p>



<p class="wp-block-paragraph"><strong>⑥打开刚刚解压保存的SD的根目录，找到启动器</strong></p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="982" height="815" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-62.png" alt="" class="wp-image-6702" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-62.png 982w, https://blog.deephour.com/wp-content/uploads/2024/04/image-62-300x249.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-62-768x637.png 768w" sizes="auto, (max-width: 982px) 100vw, 982px" /></figure>



<p class="wp-block-paragraph">鼠标右击启动器=&gt;点击“发送到”=&gt;桌面快捷方式</p>



<p class="wp-block-paragraph">这样下次进入就可以直接在桌面双击进入，不用每次都到文件夹里面找啦！</p>



<p class="wp-block-paragraph"><strong>⑦双击启动器，等待更新</strong></p>



<p class="wp-block-paragraph">接着点击左边第二个“高级选项”</p>



<p class="wp-block-paragraph">在显存优化里，根据自己电脑的显存选择（就是上面查看的专用GPU内存），自己电脑是多少就选多少</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="598" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-63-1024x598.png" alt="" class="wp-image-6703" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-63-1024x598.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-63-300x175.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-63-768x449.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-63-1536x897.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-63.png 1599w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">回到第一个一键启动，点击右下角的一键启动，等一下就行了！SD的主界面会自动在网页上弹出来。</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="598" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-64-1024x598.png" alt="" class="wp-image-6704" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-64-1024x598.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-64-300x175.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-64-768x448.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-64-1536x897.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-64.png 1596w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>如果在上面的页面出现了报错，</strong>可以回到最开始的界面，在左边点击“<strong>疑难解答</strong>”，再点击右边的“<strong>开始扫描</strong>”，最后点击“修复”按钮。</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="599" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-65-1024x599.png" alt="" class="wp-image-6705" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-65-1024x599.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-65-300x175.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-65-768x449.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-65-1536x898.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-65.png 1599w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">下面这个页面就是SD的主页面，默认的网址是：<a href="http://127.0.0.1:7860/?__theme=dark">http://127.0.0.1:7860/?__theme=dark</a> （我这里主题是黑色的，你的可能不是这个关系不大），如果看到以下的网页就说明，启动完成啦，接下来就可以愉快的使用stable diffusion画图了！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="466" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-66-1024x466.png" alt="" class="wp-image-6706" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-66-1024x466.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/image-66-300x137.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/image-66-768x350.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/image-66-1536x699.png 1536w, https://blog.deephour.com/wp-content/uploads/2024/04/image-66.png 1916w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">到此，SD的安装教程就结束了，本篇教程详细介绍了不同条件下SD软件的安装，当然如果你是大神，也可以直接在github上使用webui原始代码进行部署和使用，下期我将分别给大家详细介绍一下stable diffusion的各种神奇的用途，下期见~</p>
]]></content:encoded>
					
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			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>SD教程 &#124; Stable Diffusion使用教程(一)：SD的功能介绍</title>
		<link>https://blog.deephour.com/2024/04/15/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%b8%80%ef%bc%9asd%e7%9a%84%e5%8a%9f%e8%83%bd%e4%bb%8b%e7%bb%8d/</link>
					<comments>https://blog.deephour.com/2024/04/15/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%b8%80%ef%bc%9asd%e7%9a%84%e5%8a%9f%e8%83%bd%e4%bb%8b%e7%bb%8d/#respond</comments>
		
		<dc:creator><![CDATA[暮云岚]]></dc:creator>
		<pubDate>Mon, 15 Apr 2024 01:07:06 +0000</pubDate>
				<category><![CDATA[Stable Diffusion模型及教程]]></category>
		<category><![CDATA[stable diffusion]]></category>
		<guid isPermaLink="false">https://blog.deephour.com/?p=6662</guid>

					<description><![CDATA[1.Stable Diffusion能做什么? 01.真人AI美女 我们最常看到的就是这些真人AI美女的账号 &#8230;&#160;<a href="https://blog.deephour.com/2024/04/15/sd%e6%95%99%e7%a8%8b-stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%e4%b8%80%ef%bc%9asd%e7%9a%84%e5%8a%9f%e8%83%bd%e4%bb%8b%e7%bb%8d/" rel="bookmark">阅读更多 &#187;<span class="screen-reader-text">SD教程 &#124; Stable Diffusion使用教程(一)：SD的功能介绍</span></a>]]></description>
										<content:encoded><![CDATA[
<h2 class="wp-block-heading"><strong>1.Stable Diffusion能做什么</strong>?</h2>



<p class="wp-block-paragraph"><strong>01.真人AI美女</strong></p>



<p class="wp-block-paragraph">我们最常看到的就是这些真人AI美女的账号</p>



<p class="wp-block-paragraph">这些看起来很哇塞的美女，都是用SD模型生成的，你能看出来和真人有什么不一样么？</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="467" height="816" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-38.png" alt="" class="wp-image-6663" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-38.png 467w, https://blog.deephour.com/wp-content/uploads/2024/04/image-38-172x300.png 172w" sizes="auto, (max-width: 467px) 100vw, 467px" /><figcaption class="wp-element-caption">@你的AI女友冷月汐</figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="462" height="809" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-39.png" alt="" class="wp-image-6664" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-39.png 462w, https://blog.deephour.com/wp-content/uploads/2024/04/image-39-171x300.png 171w" sizes="auto, (max-width: 462px) 100vw, 462px" /><figcaption class="wp-element-caption">@你的AI女友冷月汐</figcaption></figure>
</div>
</div>



<p class="wp-block-paragraph"><strong>02.生成头像、壁纸</strong></p>



<p class="wp-block-paragraph">以前很多人花钱去找别人定制自己独一无二的头像或者壁纸</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full is-resized"><img loading="lazy" decoding="async" width="389" height="690" src="https://blog.deephour.com/wp-content/uploads/2024/04/AI.jpg" alt="" class="wp-image-6665" style="width:405px;height:auto" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/AI.jpg 389w, https://blog.deephour.com/wp-content/uploads/2024/04/AI-169x300.jpg 169w" sizes="auto, (max-width: 389px) 100vw, 389px" /></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="492" height="872" src="https://blog.deephour.com/wp-content/uploads/2024/04/微信截图_20240414192557.jpg" alt="" class="wp-image-6666" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/微信截图_20240414192557.jpg 492w, https://blog.deephour.com/wp-content/uploads/2024/04/微信截图_20240414192557-169x300.jpg 169w" sizes="auto, (max-width: 492px) 100vw, 492px" /></figure>
</div>
</div>



<p class="wp-block-paragraph">现在SD就可以用来定制个人的二次元头像、盲盒模型或定制壁纸</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/375789-768x1024.png" alt="" class="wp-image-6669" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/375789-768x1024.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/375789-225x300.png 225w, https://blog.deephour.com/wp-content/uploads/2024/04/375789.png 864w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">盲盒lora</figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/375787-768x1024.png" alt="" class="wp-image-6670" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/375787-768x1024.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/375787-225x300.png 225w, https://blog.deephour.com/wp-content/uploads/2024/04/375787.png 864w" sizes="auto, (max-width: 768px) 100vw, 768px" /><figcaption class="wp-element-caption">盲盒lora</figcaption></figure>
</div>
</div>



<p class="wp-block-paragraph"><strong>03.绘画辅助</strong></p>



<p class="wp-block-paragraph">绘画辅助：SD可以辅助完成动漫图画、插画等，例如线稿上色或获取图画的线稿等。此外，Stable Diffusion还有其他功能，如恢复画质、室内设计等。关于Stable Diffusion的实际变现方式和案例，我将在以后的文章中单独介绍。</p>



<div class="wp-block-columns is-layout-flex wp-container-core-columns-is-layout-8f761849 wp-block-columns-is-layout-flex">
<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="683" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/00227-4223992241-1-683x1024.png" alt="" class="wp-image-6671" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/00227-4223992241-1-683x1024.png 683w, https://blog.deephour.com/wp-content/uploads/2024/04/00227-4223992241-1-200x300.png 200w, https://blog.deephour.com/wp-content/uploads/2024/04/00227-4223992241-1-768x1152.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/00227-4223992241-1.png 816w" sizes="auto, (max-width: 683px) 100vw, 683px" /><figcaption class="wp-element-caption">线稿</figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="585" height="872" src="https://blog.deephour.com/wp-content/uploads/2024/04/微信截图_20240414193939-1.jpg" alt="" class="wp-image-6672" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/微信截图_20240414193939-1.jpg 585w, https://blog.deephour.com/wp-content/uploads/2024/04/微信截图_20240414193939-1-201x300.jpg 201w" sizes="auto, (max-width: 585px) 100vw, 585px" /><figcaption class="wp-element-caption">线稿上色</figcaption></figure>
</div>



<div class="wp-block-column is-layout-flow wp-block-column-is-layout-flow">
<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/image-40.png" alt="" class="wp-image-6673" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/image-40.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/image-40-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /><figcaption class="wp-element-caption">SD+线稿lora生成线稿</figcaption></figure>
</div>
</div>


<div class="wp-block-image">
<figure class="aligncenter size-large"><img loading="lazy" decoding="async" width="1024" height="829" src="https://blog.deephour.com/wp-content/uploads/2024/04/f848282280eba125f1230fc7ac84584c-1024x829.png" alt="" class="wp-image-6678" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/f848282280eba125f1230fc7ac84584c-1024x829.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/f848282280eba125f1230fc7ac84584c-300x243.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/f848282280eba125f1230fc7ac84584c-768x621.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/f848282280eba125f1230fc7ac84584c.png 1079w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /><figcaption class="wp-element-caption">老照片翻新</figcaption></figure>
</div>


<h2 class="wp-block-heading"><strong>2.Stable Diffusion是什么</strong></h2>



<p class="wp-block-paragraph">简单来说，Stable Diffusion（简称SD）是一个AI生成图像的软件。通过输入文字描述，SD可以生成与描述相符的图片，无需手绘或拍摄照片。 有人可能会问，在学习一个软件之前，是否需要先了解其原理呢？ </p>


<div class="wp-block-image">
<figure class="aligncenter size-large"><img loading="lazy" decoding="async" width="1024" height="521" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-1024x521.png" alt="" class="wp-image-6417" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-1024x521.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-300x153.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-768x390.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /><figcaption class="wp-element-caption">stable diffusion模型原理图</figcaption></figure>
</div>


<p class="wp-block-paragraph">很多人想学习Stable Diffusion，上网搜索时，大多数教程都会先介绍SD的原理，但这一步就让很多人望而却步。因为原理看起来复杂且困难。 但事实是：大多数人只是想熟练使用SD，而不是深入研究它。所以原理并不重要，就像我们只需要学会开车，而不需要了解汽车内部复杂的机械结构一样。SD只是一个工具，我们只需要掌握如何使用它即可。</p>



<p class="wp-block-paragraph">因此，我们的目的就是<strong>花更少的时间快速入门Stable Diffusion</strong>。</p>



<p class="wp-block-paragraph">下一篇，我们就正式开始去使用stable diffusion！！</p>
]]></content:encoded>
					
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			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>超详细的胎教级Stable Diffusion使用教程，看这一篇就够</title>
		<link>https://blog.deephour.com/2024/04/02/%e8%b6%85%e8%af%a6%e7%bb%86%e7%9a%84%e8%83%8e%e6%95%99%e7%ba%a7stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%ef%bc%8c%e7%9c%8b%e8%bf%99%e4%b8%80%e7%af%87%e5%b0%b1%e5%a4%9f/</link>
					<comments>https://blog.deephour.com/2024/04/02/%e8%b6%85%e8%af%a6%e7%bb%86%e7%9a%84%e8%83%8e%e6%95%99%e7%ba%a7stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%ef%bc%8c%e7%9c%8b%e8%bf%99%e4%b8%80%e7%af%87%e5%b0%b1%e5%a4%9f/#respond</comments>
		
		<dc:creator><![CDATA[暮云岚]]></dc:creator>
		<pubDate>Tue, 02 Apr 2024 10:59:10 +0000</pubDate>
				<category><![CDATA[Stable Diffusion模型及教程]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[stable diffusion]]></category>
		<guid isPermaLink="false">https://blog.deephour.com/?p=6409</guid>

					<description><![CDATA[原创&#160;吴东子&#160;吴东子AI&#160;2023-06-20 17:04&#160;福建 大家&#8230;&#160;<a href="https://blog.deephour.com/2024/04/02/%e8%b6%85%e8%af%a6%e7%bb%86%e7%9a%84%e8%83%8e%e6%95%99%e7%ba%a7stable-diffusion%e4%bd%bf%e7%94%a8%e6%95%99%e7%a8%8b%ef%bc%8c%e7%9c%8b%e8%bf%99%e4%b8%80%e7%af%87%e5%b0%b1%e5%a4%9f/" rel="bookmark">阅读更多 &#187;<span class="screen-reader-text">超详细的胎教级Stable Diffusion使用教程，看这一篇就够</span></a>]]></description>
										<content:encoded><![CDATA[
<p class="wp-block-paragraph">原创&nbsp;吴东子&nbsp;<a href="javascript:void(0);">吴东子AI</a>&nbsp;<em>2023-06-20 17:04</em>&nbsp;<em>福建</em></p>



<p class="wp-block-paragraph">大家好，我是吴东子，用奶奶都能听懂的方式分享可以落地实操的干货</p>



<p class="wp-block-paragraph">花了很长时间终于整理好了这份SD的使用教程！</p>



<p class="wp-block-paragraph">从手把手安装部署，到界面功能讲解，再到实战案例制作，到下载优质模型，每一步都有详细教程</p>



<p class="wp-block-paragraph">并且用一个又一个的例子展示，让大家不止是枯燥地看，而是看完立刻也能做出一样的图片出来&nbsp;</p>



<p class="wp-block-paragraph">同时，无论是安装包，大模型，lora，关键词的文件都给大家打包好了，不用再自己这找找那找找</p>



<p class="wp-block-paragraph">希望能做到让大家学SD，看这一篇就够！</p>



<h1 class="wp-block-heading"><strong>一、为什么要学Stable Diffusion，它究竟有多强大？</strong></h1>



<p class="wp-block-paragraph"><strong>1.Stable Diffusion能干嘛</strong></p>



<p class="wp-block-paragraph">我相信大家在刷视频的时候，或多或少都已经看到过很多AI绘画生成的作品了</p>



<p class="wp-block-paragraph">那SD到底可以用来干什么呢？</p>



<p class="wp-block-paragraph"><strong>01.真人AI美女</strong></p>



<p class="wp-block-paragraph">我们最常看到的就是这些真人AI美女的账号</p>



<p class="wp-block-paragraph">(我有一个朋友，每到晚上的时候，就很喜欢看这种视频)</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="705" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时508-705x1024.png" alt="" class="wp-image-6412" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时508-705x1024.png 705w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时508-206x300.png 206w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时508-768x1116.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时508.png 1021w" sizes="auto, (max-width: 705px) 100vw, 705px" /></figure>


<div class="wp-block-image">
<figure class="aligncenter size-large"><img loading="lazy" decoding="async" width="473" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3-473x1024.webp" alt="" class="wp-image-6413" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3-473x1024.webp 473w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3-139x300.webp 139w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3-768x1662.webp 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3-710x1536.webp 710w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3-946x2048.webp 946w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3.webp 1080w" sizes="auto, (max-width: 473px) 100vw, 473px" /></figure>
</div>


<p class="wp-block-paragraph"><strong>02.生成头像、壁纸</strong></p>



<p class="wp-block-paragraph">以前很多人花钱去找别人定制自己独一无二的头像或者壁纸</p>



<p class="wp-block-paragraph">现在SD就可以用来定制个人的二次元头像、盲盒模型或定制壁纸</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时586-1024x768.png" alt="" class="wp-image-6414" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时586-1024x768.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时586-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时586-768x576.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时586.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="674" height="890" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时589.png" alt="" class="wp-image-6415" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时589.png 674w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时589-227x300.png 227w" sizes="auto, (max-width: 674px) 100vw, 674px" /></figure>



<p class="wp-block-paragraph"><strong>03.绘画辅助</strong></p>



<p class="wp-block-paragraph">动漫图画、插画等都可以用SD来辅助完成</p>



<p class="wp-block-paragraph">比如线稿上色、或者是获取图画的线稿等</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="512" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时642-1024x512.png" alt="" class="wp-image-6416" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时642-1024x512.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时642-300x150.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时642-768x384.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时642.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">Stable diffusion还有很多功能，比如恢复画质、室内设计等</p>



<p class="wp-block-paragraph">关于Stable Diffusion的实际变现方式和变现案例，之后我也会单独写文章来说噢！</p>



<h2 class="wp-block-heading"><strong>2.Stable Diffusion是什么</strong></h2>



<p class="wp-block-paragraph">简单来说，Stable Diffusion（简称SD）就是一个<strong>AI自动生成图片的软件</strong></p>



<p class="wp-block-paragraph">通过我们输入文字，SD就能生成对应的一张图片，不再需要像以前一样要把图片“画”出来，或者是“拍”出来</p>



<p class="wp-block-paragraph">有的人说，我学习一个软件之前是不是要先知道它的原理呢？</p>



<p class="wp-block-paragraph">我的回答是：不需要！</p>



<p class="wp-block-paragraph">下面这张图就是我在网上保存的SD的原理图</p>



<p class="wp-block-paragraph">看得懂吗？</p>



<p class="wp-block-paragraph">看不懂，我也看不懂</p>



<p class="wp-block-paragraph">影响使用吗？</p>



<p class="wp-block-paragraph">完全不影响！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="521" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-1024x521.png" alt="" class="wp-image-6417" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-1024x521.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-300x153.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944-768x390.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时944.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">很多人想学习stable diffusion，上网一搜，大多数教程都先告诉你SD的原理是什么</p>



<p class="wp-block-paragraph">但偏偏就是这一步就劝退了很多人继续学习</p>



<p class="wp-block-paragraph">因为这看起来真的好像很复杂很难</p>



<p class="wp-block-paragraph">但事实是：</p>



<p class="wp-block-paragraph">大多数的我们只是要能够<strong>熟练使用SD</strong></p>



<p class="wp-block-paragraph">而不是要深入研究它</p>



<p class="wp-block-paragraph">我们还有自己的学习和工作</p>



<p class="wp-block-paragraph">因此，我们的目的就是<strong>花更少的时间快速入门Stable Diffusion</strong></p>



<p class="wp-block-paragraph">当然了，如果你的时间比较充裕，去把SD的原理也了解了也是可以的</p>



<p class="wp-block-paragraph">跟大家说这些是想告诉大家</p>



<p class="wp-block-paragraph">学习SD真的非常简单！！</p>



<p class="wp-block-paragraph">这篇文章就会带大家通过一个个案例，实际上手操作生成各种照片</p>



<p class="wp-block-paragraph">我相信在你看完这篇文章并且自己去尝试过之后</p>



<p class="wp-block-paragraph">你就已经可以快速上手stable diffusion了！！</p>



<p class="wp-block-paragraph">接下来我们就正式开始去使用stable diffusion！！</p>



<h1 class="wp-block-heading"><strong>二、三分钟教你装好Stable Diffusion</strong></h1>



<h2 class="wp-block-heading"><strong>1.什么电脑能带动SD，A卡和Mac系统也不慌</strong></h2>



<p class="wp-block-paragraph">为了大家能够更加顺利的安装和使用Stable Diffusion（简称“SD”）</p>



<p class="wp-block-paragraph">在正式安装之前希望大家先一起查看一下自己的电脑配置，</p>



<p class="wp-block-paragraph">需要注意的是以下两点：</p>



<p class="wp-block-paragraph"><strong>01.电脑系统是Win10或者Win11</strong></p>



<p class="wp-block-paragraph">为了避免一些奇怪的兼容性问题，不要选择更低版本的系统。</p>



<p class="wp-block-paragraph"><strong>查看电脑系统的方法：</strong></p>



<p class="wp-block-paragraph">在桌面上找到“我的电脑”——鼠标右键点击——点击“属性”——查看Windows规格</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="795" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1536-1024x795.png" alt="" class="wp-image-6418" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1536-1024x795.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1536-300x233.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1536-768x596.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1536.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>02.检查电脑性能</strong></p>



<p class="wp-block-paragraph">这里是检查自己的电脑配置能不能带动SD（Stable Diffusion）</p>



<p class="wp-block-paragraph">需要满足3个要求：</p>



<ul class="wp-block-list">
<li><strong>电脑运行内存8GB以上</strong></li>



<li><strong>是英伟达（俗称N卡）的显卡</strong></li>



<li><strong>显卡内存4GB以上</strong></li>
</ul>



<p class="wp-block-paragraph">检查方法：</p>



<p class="wp-block-paragraph">①鼠标右击桌面底部任务栏——点击“任务管理器”</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="906" height="751" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1675.png" alt="" class="wp-image-6419" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1675.png 906w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1675-300x249.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1675-768x637.png 768w" sizes="auto, (max-width: 906px) 100vw, 906px" /></figure>



<p class="wp-block-paragraph">②查看电脑的运行内存</p>



<p class="wp-block-paragraph">在“性能”里面找到“内存”，这里的内存不是电脑的存储内存，而是运行内存噢！</p>



<p class="wp-block-paragraph">只要看图中划线的那一个参数就可以</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">8GB：那就说明你的电脑配置内存是勉强达到标准的</p>



<p class="wp-block-paragraph">16GB：那就说明你的内存配置可以正常使用</p>



<p class="wp-block-paragraph">32GB：那么你就可以非常自由的使用SD啦！</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="723" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1815-1024x723.png" alt="" class="wp-image-6420" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1815-1024x723.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1815-300x212.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1815-768x543.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时1815.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">③查看“GPU”</p>



<p class="wp-block-paragraph">GPU就是显卡的意思</p>



<p class="wp-block-paragraph">首先先看右上角显卡的名字或者型号</p>



<p class="wp-block-paragraph">必须确认的第一个是 NVIDIA ，代表的是英伟达的显卡（俗称N卡），这里是N卡我们才可以进行下一步，</p>



<p class="wp-block-paragraph">如果这个地方是AMD或者是Intel，可能你的电脑会不太支持SD，网上的安装教程也比较麻烦，</p>



<p class="wp-block-paragraph">大家可以看第二部分，使用云平台去玩SD</p>



<p class="wp-block-paragraph">接着看到下面划线的专用GPU内存</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">4GB：说明电脑勉强可以跑动SD，出图的时间会比较长</p>



<p class="wp-block-paragraph">6GB：出一张图的时间是20~50秒，SD的大部分功能都可以使用</p>



<p class="wp-block-paragraph">8GB：5~20秒可以出一张图，基本上SD的所有功能都对你开放</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="724" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2090-1024x724.png" alt="" class="wp-image-6421" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2090-1024x724.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2090-300x212.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2090-768x543.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2090.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">好啦，如果你的电脑满足以上所说的配置，那么恭喜你！你可以顺利的安装Stable Diffusion并展开学习啦！</p>



<p class="wp-block-paragraph">上面这些操作是我们用来查看Windows系统的&nbsp;</p>



<p class="wp-block-paragraph">至于Mac系统可以看一下下面的视频&nbsp;</p>



<p class="wp-block-paragraph">按照视频一键安装就可以啦！非常简单！</p>



<p class="wp-block-paragraph"><a href="https://www.bilibili.com/video/BV1Kh4y1W7Vg/?spm_id_from=333.788&amp;vd_source=6f836e2ab17b1bdb4fc5ea98f38df761">https://www.bilibili.com/video/BV1Kh4y1W7Vg/?spm_id_from=333.788&amp;vd_source=6f836e2ab17b1bdb4fc5ea98f38df761</a></p>



<h2 class="wp-block-heading"><strong>2.低配置电脑也能玩Stable Diffusion</strong></h2>



<p class="wp-block-paragraph">（电脑配置过关的朋友们，直接看第3部分安装）</p>



<p class="wp-block-paragraph">刚刚查看了电脑配置，发现自己电脑可能带不动SD的朋友们也不用担心，</p>



<p class="wp-block-paragraph">通过云平台，我们一样可以畅玩SD，做出好看的图片</p>



<p class="wp-block-paragraph">云平台就相当于我们远程控制别人配置更好的电脑，用别人电脑上的SD生成照片</p>



<p class="wp-block-paragraph">这里用的是“青椒云”，如果大家还有什么更好用的平台也可以分享出来噢！</p>



<p class="wp-block-paragraph">点击下面的链接就可以下载青椒云</p>



<p class="wp-block-paragraph">http://account.qingjiaocloud.com/signup?inviteCode=R0JJ9CHY</p>



<p class="wp-block-paragraph">云平台使用方法：</p>



<p class="wp-block-paragraph">①点击上面链接，注册账号</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="616" height="651" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2613.png" alt="" class="wp-image-6422" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2613.png 616w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2613-284x300.png 284w" sizes="auto, (max-width: 616px) 100vw, 616px" /></figure>



<p class="wp-block-paragraph">②下载并安装后，登录刚刚注册好的账户</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="728" height="726" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2636.png" alt="" class="wp-image-6423" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2636.png 728w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2636-300x300.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2636-150x150.png 150w" sizes="auto, (max-width: 728px) 100vw, 728px" /></figure>



<p class="wp-block-paragraph">③点击右上角的个人中心进行实名认证</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="631" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2658-1024x631.png" alt="" class="wp-image-6424" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2658-1024x631.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2658-300x185.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2658-768x473.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2658.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">④在进行实名认证后回到主界面，点击新增云桌面</p>



<p class="wp-block-paragraph">想玩Stable Diffusion可以选“AIGC尝鲜”，一般新注册的会有优惠券，可以免费试用</p>



<p class="wp-block-paragraph">大家可以试试觉得好用再付费！</p>



<p class="wp-block-paragraph">（大多数云平台都是2~3元一个小时）</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="634" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2770-1024x634.png" alt="" class="wp-image-6425" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2770-1024x634.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2770-300x186.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2770-768x476.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2770.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">⑤在新弹出的框框中点击“开机”按钮，稍等一下之后，点击“进入桌面”</p>



<p class="wp-block-paragraph">进入桌面之后弹出的全部框框可以直接关掉</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="642" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2829-1024x642.png" alt="" class="wp-image-6426" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2829-1024x642.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2829-300x188.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2829-768x481.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2829.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">⑥点击新打开桌面的“此电脑”，在C盘里面找到SD的根目录，点击“A启动器.exe”</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="576" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2875-1024x576.png" alt="" class="wp-image-6427" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2875-1024x576.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2875-300x169.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2875-768x432.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2875.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">⑦点击右下角的“一键启动”就可以进入SD啦</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="598" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2901-1024x598.png" alt="" class="wp-image-6428" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2901-1024x598.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2901-300x175.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2901-768x449.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2901.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">⑧用完云平台之后，记得关机噢，不然会持续计费</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="628" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2928-1024x628.png" alt="" class="wp-image-6429" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2928-1024x628.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2928-300x184.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2928-768x471.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时2928.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<h2 class="wp-block-heading"><strong>3.一键式安装SD本地部署，解压即用，小白的福音</strong></h2>



<p class="wp-block-paragraph">电脑配置能支持SD运行的朋友们，接下来我会手把手教你安装SD的本地部署</p>



<p class="wp-block-paragraph">这里我们用到的是B站秋叶分享的整合包</p>



<p class="wp-block-paragraph">小白直接下载整合包可以避免很多困难</p>



<p class="wp-block-paragraph">整合包点开链接就能下载保存啦</p>



<p class="wp-block-paragraph">链接：https://pan.baidu.com/s/1hY8CKbYRAj9RrFGmswdNiA?pwd=caru</p>



<p class="wp-block-paragraph">提取码：caru</p>



<p class="wp-block-paragraph">具体安装方法：</p>



<p class="wp-block-paragraph">①打开上面的链接，下载《1.整合包安装》，存放到电脑本地</p>



<p class="wp-block-paragraph">②打开保存到电脑里的文件夹</p>



<p class="wp-block-paragraph">③打开文件夹《1.秋叶整合包主包》——鼠标右击文件——点击“解压文件”</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="751" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3210-1024x751.png" alt="" class="wp-image-6430" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3210-1024x751.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3210-300x220.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3210-768x563.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3210.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">④选择解压到D盘或者E盘，小心C盘被占满！！点击确定</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="616" height="581" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3241.png" alt="" class="wp-image-6431" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3241.png 616w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3241-300x283.png 300w" sizes="auto, (max-width: 616px) 100vw, 616px" /></figure>



<p class="wp-block-paragraph">⑤解压完成后，来到第二个文件夹，双击里面的文件</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="666" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3269-1024x666.png" alt="" class="wp-image-6432" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3269-1024x666.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3269-300x195.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3269-768x499.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3269.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">点击安装</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="808" height="574" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3278.png" alt="" class="wp-image-6433" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3278.png 808w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3278-300x213.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3278-768x546.png 768w" sizes="auto, (max-width: 808px) 100vw, 808px" /></figure>



<p class="wp-block-paragraph">⑥打开刚刚解压保存的SD的根目录，找到启动器</p>



<p class="wp-block-paragraph">鼠标右击启动器——点击“发送到”——桌面快捷方式</p>



<p class="wp-block-paragraph">这样下次进入就可以直接在桌面双击进入，不用每次都到文件夹里面找啦！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="667" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3366-1024x667.png" alt="" class="wp-image-6434" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3366-1024x667.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3366-300x195.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3366-768x500.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3366.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">⑦双击启动器，等待更新</p>



<p class="wp-block-paragraph">接着点击左边第二个“高级选项”</p>



<p class="wp-block-paragraph">在显存优化里，根据自己电脑的显存选择（就是上面查看的专用GPU内存），自己电脑是多少就选多少</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="602" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3447-1024x602.png" alt="" class="wp-image-6435" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3447-1024x602.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3447-300x176.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3447-768x452.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3447.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">⑧回到第一个一键启动，点击右下角的一键启动</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="592" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3473-1024x592.png" alt="" class="wp-image-6436" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3473-1024x592.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3473-300x173.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3473-768x444.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3473.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">出现这个代码页面不用管，等一下就行了！SD的主界面会自动在网页上弹出来</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="576" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3513-1024x576.png" alt="" class="wp-image-6437" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3513-1024x576.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3513-300x169.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3513-768x432.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3513.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">如果在上面的页面出现了报错</p>



<p class="wp-block-paragraph">可以回到最开始的界面</p>



<p class="wp-block-paragraph">在左边点击“疑难解答”，再点击右边的“开始扫描”</p>



<p class="wp-block-paragraph">最后点击“修复”按钮</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="600" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3579-1024x600.png" alt="" class="wp-image-6438" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3579-1024x600.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3579-300x176.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3579-768x450.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3579.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">下面这个页面就是SD的主页面，大家看到这样一个复杂的页面千万不要慌</p>



<p class="wp-block-paragraph">实际上有些功能在我们基础使用中用不上</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="509" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3637-1024x509.png" alt="" class="wp-image-6439" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3637-1024x509.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3637-300x149.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3637-768x382.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3637.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">接下来我们就把常用功能配合上实际例子来讲解</p>



<h1 class="wp-block-heading"><strong>三、小白快速上手Stable Diffusion</strong></h1>



<h2 class="wp-block-heading"><strong>1.用对模型，照片风格才对味儿</strong></h2>



<p class="wp-block-paragraph">用stable diffusion可以把自己想象成一个画家</p>



<p class="wp-block-paragraph">在起笔画画之前，我们要先确定我们画的是什么风格的画，</p>



<p class="wp-block-paragraph">是二次元动漫、三次元的现实照片、还是盲盒模型。</p>



<p class="wp-block-paragraph">因此，在我们确定了我们照片风格之后</p>



<p class="wp-block-paragraph">我们就要去切换大模型，不同的模型就代表着不同的照片风格。</p>



<p class="wp-block-paragraph">也就是SD界面左上角的“Stable Diffusion模型”</p>



<p class="wp-block-paragraph">假如现在我想生成一个真人AI小姐姐，就选用chilloutmix的大模型</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="545" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3908-1024x545.png" alt="" class="wp-image-6440" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3908-1024x545.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3908-300x160.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3908-768x409.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时3908.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">那么问题来了，我们这些模型从哪来呢？下载的模型放在哪里呢？</p>



<p class="wp-block-paragraph">在我分享给大家的链接里面，有部分比较常用的大模型</p>



<p class="wp-block-paragraph">（后续还有比较好的模型也会分享给大家）</p>



<p class="wp-block-paragraph">大家可以根据文件夹名称找到需要的模型。</p>



<p class="wp-block-paragraph">另外，这篇文章的第三部分会跟大家详细介绍去哪里下载模型，模型存放的位置，所以一定要看到最后！</p>



<h2 class="wp-block-heading"><strong>2.写好关键词，让你事半功倍</strong></h2>



<p class="wp-block-paragraph">选好大模型之后，我们就要考虑画面上要有什么东西，不要出现什么东西</p>



<p class="wp-block-paragraph">而这就是通过输入关键词来告诉SD</p>



<p class="wp-block-paragraph">我们最后要生成什么样的图画</p>



<h3 class="wp-block-heading"><strong>01.正面关键词</strong></h3>



<p class="wp-block-paragraph">其实要生成一张照片，最重要的就是关键词，</p>



<p class="wp-block-paragraph">关键词里写的就是你希望照片里会出现的内容</p>



<p class="wp-block-paragraph">输入的关键词越准确，出来的照片就会越接近自己脑海里的画面！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="86" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4224-1024x86.png" alt="" class="wp-image-6441" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4224-1024x86.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4224-300x25.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4224-768x65.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4224.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">那怎么写关键词呢？</p>



<p class="wp-block-paragraph">比如说我现在想要生成一个漂亮的小姐姐站在大街上</p>



<p class="wp-block-paragraph">那我就可以写成：1女孩，漂亮，站着，大街</p>



<p class="wp-block-paragraph">或者是：1漂亮女孩，站在大街上</p>



<p class="wp-block-paragraph">又或者我直接写一个句子：1个漂亮女孩站在大街上</p>



<p class="wp-block-paragraph">上面三种<strong>单词、词组、短句</strong>的方式都可以，</p>



<p class="wp-block-paragraph">我们比较常用的就是直接输入一个个单词，然后这些单词用<strong>英文状态下的逗号隔开</strong></p>



<p class="wp-block-paragraph">当然了，SD只能识别英语，但我们也不用担心，直接用翻译就可以啦！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="283" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4417-1024x283.png" alt="" class="wp-image-6442" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4417-1024x283.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4417-300x83.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4417-768x213.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4417.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">输入到SD就是这样的<img src="https://s.w.org/images/core/emoji/17.0.2/72x72/2b07.png" alt="⬇" class="wp-smiley" style="height: 1em; max-height: 1em;" /></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="86" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4432-1024x86.png" alt="" class="wp-image-6443" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4432-1024x86.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4432-300x25.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4432-768x65.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4432.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">接着点击右边这个“生成”按钮</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="435" height="255" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4451.png" alt="" class="wp-image-6444" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4451.png 435w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4451-300x176.png 300w" sizes="auto, (max-width: 435px) 100vw, 435px" /></figure>
</div>


<p class="wp-block-paragraph">这样你在SD的第一张图就出来啦！</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="512" height="712" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4472.png" alt="" class="wp-image-6445" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4472.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4472-216x300.png 216w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>


<p class="wp-block-paragraph">hhh是不是很多小伙伴已经按捺不住去试了试呢，出来的照片是不是有点不尽人意！</p>



<p class="wp-block-paragraph">那是因为我们上面输入的关键词太过于简略啦</p>



<p class="wp-block-paragraph">这里是我上面这张图输入的关键词</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="130" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4554-1024x130.png" alt="" class="wp-image-6446" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4554-1024x130.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4554-300x38.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4554-768x97.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4554.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">看到这一大串英文千万别害怕！写关键词也是有模板的！</p>



<p class="wp-block-paragraph">首先上面第一行的关键词可以先不看</p>



<p class="wp-block-paragraph">那是我们等一下要学到的lora模型</p>



<p class="wp-block-paragraph">在写跟我们照片有关的关键词之前</p>



<p class="wp-block-paragraph">我们可以先写一些<strong>照片质量</strong>的词语，这样出来的照片会更加精致</p>



<p class="wp-block-paragraph">比如说我们可以写：最高质量，超高清画质，大师的杰作，8k画质等等&#8230;</p>



<p class="wp-block-paragraph">翻译成对应的英文就是：Highest quality, ultra-high definition, masterpieces, 8k quality,</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="82" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4780-1024x82.png" alt="" class="wp-image-6447" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4780-1024x82.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4780-300x24.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4780-768x61.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时4780.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">写完质量词，接着就是我们照片的内容</p>



<p class="wp-block-paragraph">先写的就是<strong>照片的主体</strong>，和对<strong>主体的细节描写</strong></p>



<p class="wp-block-paragraph">比如我们是要生成一个女孩，就要写出来一个女孩，以及这个女孩长什么样也可以写出来</p>



<p class="wp-block-paragraph">也就是：一个女孩，非常精致的五官，极具细节的眼睛和嘴巴，长发，卷发，细腻的皮肤，大眼睛</p>



<p class="wp-block-paragraph">翻译成英文就是：1girl, very delicate features, very detailed eyes and mouth, long hair, curly hair, delicate skin, big eyes,</p>



<p class="wp-block-paragraph">这些照片内容大家都是可以随意改的，但是像精致的五官、细节的眼睛这类词语，大家可以都加上去</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="99" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5073-1024x99.png" alt="" class="wp-image-6448" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5073-1024x99.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5073-300x29.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5073-768x74.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5073.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">写完五官之后，我们就可以想一下让照片的人<strong>物穿什么衣服</strong>，裤子，或者加上帽子之类的配饰</p>



<p class="wp-block-paragraph">像裙子、毛衣、牛仔裤、比基尼都可以，还可以写上衣服的颜色</p>



<p class="wp-block-paragraph">比如：白色的毛衣、项链（white sweater, necklace,）</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="86" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5187-1024x86.png" alt="" class="wp-image-6449" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5187-1024x86.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5187-300x25.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5187-768x65.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5187.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">最后我们就可以写上其他乱七八糟的东西，比如<strong>背景、天气、照片姿势、构图</strong>等等</p>



<p class="wp-block-paragraph">比如说：在街上，阳光，上半身照片（street, Sunshine, upper body photos,）</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="101" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5283-1024x101.png" alt="" class="wp-image-6450" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5283-1024x101.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5283-300x29.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5283-768x75.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5283.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">好啦，这样一套下来，我们的关键词就写的差不多了</p>



<p class="wp-block-paragraph">推荐大家像我这样一行一行分开类型去写关键词，这样后面想要改词更好找</p>



<p class="wp-block-paragraph">但一定要<strong>注意每一行的最后要加上英文逗号</strong>，否则它就会跟下一个单词连起来变成一个新单词</p>



<p class="wp-block-paragraph">总结一下我们写关键词的公式：</p>



<p class="wp-block-paragraph"><strong>画质+主体+主体细节+人物服装+其他（背景、天气、构图等）</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="100" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5434-1024x100.png" alt="" class="wp-image-6451" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5434-1024x100.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5434-300x29.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5434-768x75.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5434.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="512" height="712" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5438.png" alt="" class="wp-image-6452" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5438.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5438-216x300.png 216w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>


<p class="wp-block-paragraph">好，现在我们新生成了一张照片，但是发现她并没有我关键词里的卷发，</p>



<p class="wp-block-paragraph">那我怎样才能让“卷发（curly hair）”引起Stable Diffusion的注意呢？</p>



<p class="wp-block-paragraph">那就是给关键词加权重，加权重的方法有两种：</p>



<p class="wp-block-paragraph"><strong>①直接用括号把关键词括起来：（curly hair）</strong></p>



<p class="wp-block-paragraph">这样括号一次就是1.1倍权重，那括两次((curly hair))就是1.1×1.1=1.21倍，以此类推</p>



<p class="wp-block-paragraph">注意：这里的括号也是英文状态下的括号</p>



<p class="wp-block-paragraph">可以加权重，那我们也可以减权重</p>



<p class="wp-block-paragraph">减权重就是用&#8221;[]&#8221;把单词括起来，如：[curly hair]</p>



<p class="wp-block-paragraph"><strong>②（关键词:数值):（curly hair：1.3）</strong></p>



<p class="wp-block-paragraph">这就是在第一种的基础上加上数值，直接一个curly hair是1，大于1就是加权重，小于1就是减权重</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="117" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5779-1024x117.png" alt="" class="wp-image-6453" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5779-1024x117.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5779-300x34.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5779-768x87.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5779.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<h3 class="wp-block-heading"><strong>02.负面关键词</strong></h3>



<p class="wp-block-paragraph">当我们生成照片次数多了之后，渐渐的发现偶尔生成出来的照片多了几个手指，甚至会多了一只手</p>



<p class="wp-block-paragraph">那怎么才能避免这些情况呢？</p>



<p class="wp-block-paragraph">那就是告诉SD，我不要那样的照片！</p>



<p class="wp-block-paragraph">所以，我们就可以通过输入负面关键词告诉SD，我不希望照片会出现什么内容</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="90" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5908-1024x90.png" alt="" class="wp-image-6454" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5908-1024x90.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5908-300x26.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5908-768x68.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时5908.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">比如说我不希望照片出现：低质量，多余的手，多余的手指，不好看的脸等等&#8230;</p>



<p class="wp-block-paragraph">这里就不用大家去想要写些什么啦</p>



<p class="wp-block-paragraph">新手小白可以直接抄！</p>



<p class="wp-block-paragraph">(worst quality:2), (low quality:2), (normal quality:2), lowres, ((monochrome)), ((grayscale)), bad anatomy,DeepNegative, skin spots, acnes, skin blemishes,(fat:1.2),facing away, looking away,tilted head, lowres,bad anatomy,bad hands, missing fingers,extra digit, fewer digits,bad feet,poorly drawn hands,poorly drawn face,mutation,deformed,extra fingers,extra limbs,extra arms,extra legs,malformed limbs,fused fingers,too many fingers,long neck,cross-eyed,mutated hands,polar lowres,bad body,bad proportions,gross proportions,missing arms,missing legs,extra digit, extra arms, extra leg, extra foot,teethcroppe,signature, watermark, username,blurry,cropped,jpeg artifacts,text,error</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="100" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6660-1024x100.png" alt="" class="wp-image-6455" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6660-1024x100.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6660-300x29.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6660-768x75.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6660.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">当然你如果还有什么不想出现在照片上的东西，也可以自己加上去</p>



<p class="wp-block-paragraph">到这里关键词所有的内容就讲完啦！</p>



<p class="wp-block-paragraph">分享的链接里还有常用的关键词分类，</p>



<p class="wp-block-paragraph">还不知道写些什么的，大家可以去看看！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="206" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6750-1024x206.png" alt="" class="wp-image-6456" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6750-1024x206.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6750-300x60.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6750-768x154.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6750.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<h2 class="wp-block-heading"><strong>3.两分钟打造你的专属模特</strong></h2>



<p class="wp-block-paragraph">通过输入关键词，我们已经能够生成一张稍微好看一点的小姐姐的照片了，</p>



<p class="wp-block-paragraph">但是现在我想要生成5678张照片，而且我要出来的照片都是同一张脸，这怎么办呢？</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="736" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6845-736x1024.png" alt="" class="wp-image-6457" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6845-736x1024.png 736w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6845-216x300.png 216w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6845-768x1069.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6845.png 920w" sizes="auto, (max-width: 736px) 100vw, 736px" /></figure>



<p class="wp-block-paragraph">这时候我们就要用到Lora模型</p>



<p class="wp-block-paragraph">简单来说，<strong>Lora可以固定我们照片的特征：人物特征、动作特征、还有照片风格</strong></p>



<p class="wp-block-paragraph">点击“生成”下面的的第三个按钮，就会弹出新的选项框</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="432" height="171" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6931.png" alt="" class="wp-image-6458" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6931.png 432w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6931-300x119.png 300w" sizes="auto, (max-width: 432px) 100vw, 432px" /></figure>
</div>


<p class="wp-block-paragraph">找到Lora，就会出现我们下载保存到电脑的Lora模型</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="162" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6963-1024x162.png" alt="" class="wp-image-6459" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6963-1024x162.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6963-300x48.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6963-768x122.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6963.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">点击我们要用的Lora，就会自动添加到关键词的文本框里面</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="119" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6996-1024x119.png" alt="" class="wp-image-6460" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6996-1024x119.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6996-300x35.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6996-768x90.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时6996.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">前面那四张照片用到的就是这三个Lora，由此可见，我们的Lora是可以叠加使用的</p>



<p class="wp-block-paragraph">但是建议新手不要使用太多lora，</p>



<p class="wp-block-paragraph">因为这样照片出问题了，你也不知道是哪个Lora有问题</p>



<p class="wp-block-paragraph">另外，Lora之间一样用英文逗号隔开</p>



<p class="wp-block-paragraph">每个Lora后面都有数字，这是用来调整这个Lora的权重的，</p>



<p class="wp-block-paragraph">正常情况下是1，我们一般只会去降低权重，因为增加权重照片可能就会变得奇奇怪怪</p>



<p class="wp-block-paragraph">每个Lora设置的权重不一样，出来的照片就会不一样</p>



<p class="wp-block-paragraph">想要生成一个好看的小姐姐，就要多去尝试不同的权重组合</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="716" height="42" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7235.png" alt="" class="wp-image-6461" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7235.png 716w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7235-300x18.png 300w" sizes="auto, (max-width: 716px) 100vw, 716px" /></figure>



<p class="wp-block-paragraph">现在问题又来了，我们怎么选择Lora呢？</p>



<p class="wp-block-paragraph">这个问题就要回归到你最开始想要生成什么样的照片</p>



<p class="wp-block-paragraph">你想生成真人模特，你在最开始用了真人的大模型</p>



<p class="wp-block-paragraph">对应的我们的Lora也要选用真人模特</p>



<p class="wp-block-paragraph">这样出来的照片效果才更好！</p>



<p class="wp-block-paragraph">一些比较好看的Lora已经打包好了放在文章的末尾&nbsp;</p>



<p class="wp-block-paragraph">后续挖掘到更好看的Lora也会分享给大家！</p>



<p class="wp-block-paragraph">大家可以通过添加不同的Lora，调整权重，</p>



<p class="wp-block-paragraph">生成你独一无二的小姐姐！</p>



<h2 class="wp-block-heading"><strong>4.为什么你生成的图就是跟别人不一样</strong></h2>



<p class="wp-block-paragraph">为什么有时候我们跟别人用的大模型、关键词、Lora还有其他参数都一样</p>



<p class="wp-block-paragraph">可偏偏生成出来的图就是不一样？</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7502-1024x768.png" alt="" class="wp-image-6462" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7502-1024x768.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7502-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7502-768x576.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7502.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">那是因为影响照片的因素还有一个“随机数种子（Seed）”</p>



<p class="wp-block-paragraph">随机数种子控制的是最底层的形状，就相当于我们画画最开始的线稿</p>



<p class="wp-block-paragraph">它会决定我们照片的基础轮廓，相当于决定了我们照片人物的外形轮廓，包括姿势和站位等</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="908" height="89" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7608.png" alt="" class="wp-image-6463" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7608.png 908w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7608-300x29.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7608-768x75.png 768w" sizes="auto, (max-width: 908px) 100vw, 908px" /></figure>



<p class="wp-block-paragraph">当随机数为“-1”的时候，SD就会随机给你的照片生成一个种子，这个种子就理解成不一样的线稿就可以</p>



<p class="wp-block-paragraph">怎么看自己照片用的seed值（随机数种子）是什么呢？</p>



<p class="wp-block-paragraph">在我们点击生成的照片下面，有一大串英文，里面的seed值就是我们当前生成照片的seed值</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="929" height="572" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7735.png" alt="" class="wp-image-6464" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7735.png 929w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7735-300x185.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7735-768x473.png 768w" sizes="auto, (max-width: 929px) 100vw, 929px" /></figure>



<p class="wp-block-paragraph">只有当我们所有参数，包括随机数种子跟别人的照片都一样时，我们才能生成跟别人差不多一样的照片。</p>



<h2 class="wp-block-heading"><strong>5.一分钟生成自己的二次元造型</strong></h2>



<p class="wp-block-paragraph">大家有没有试过花二三十块钱，把自己的照片发给别人，让人家帮自己生成一张二次元画风的照片拿来当头像</p>



<p class="wp-block-paragraph">然后别人含泪血赚19.9，还有一毛钱是电费</p>



<p class="wp-block-paragraph">今天看到这篇文章你就省钱啦！</p>



<p class="wp-block-paragraph">Stable Diffusion不用一分钟，不管你是要2.5D还是2D的照片，它都能生成！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7940-1024x768.png" alt="" class="wp-image-6465" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7940-1024x768.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7940-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7940-768x576.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7940.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">这里我们用到的是图生图里面的功能</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="238" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7961-1024x238.png" alt="" class="wp-image-6466" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7961-1024x238.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7961-300x70.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7961-768x178.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时7961.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">我们是要用自己的照片生成一张二次元的照片</p>



<p class="wp-block-paragraph">一定要记得换大模型！！选一个能生成二次元照片的大模型就可以</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="444" height="90" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8017.png" alt="" class="wp-image-6467" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8017.png 444w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8017-300x61.png 300w" sizes="auto, (max-width: 444px) 100vw, 444px" /></figure>



<p class="wp-block-paragraph">至于正面关键词呢</p>



<p class="wp-block-paragraph">我们只要输入照片质量和主体的关键词就可以</p>



<p class="wp-block-paragraph">比如我这里输入的就是：高质量，高清画质，大师杰作，极致的细节，8k，主体就是一个女孩</p>



<p class="wp-block-paragraph">负面关键词我们就复制前面给大家的就可以啦</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="249" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8118-1024x249.png" alt="" class="wp-image-6468" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8118-1024x249.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8118-300x73.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8118-768x187.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8118.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">接着我们就在这个空白的地方点击上传自己需要生成的照片</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="902" height="814" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8149.png" alt="" class="wp-image-6469" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8149.png 902w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8149-300x271.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8149-768x693.png 768w" sizes="auto, (max-width: 902px) 100vw, 902px" /></figure>



<p class="wp-block-paragraph">接着鼠标往下移，找到“重绘幅度”</p>



<p class="wp-block-paragraph">重绘幅度的意思就是你要改变你原来照片的程度</p>



<p class="wp-block-paragraph">当你的重绘幅度拉到1，这时候就相当于要完全改变你的照片，生成出来的照片就跟原先的照片毫无关系了</p>



<p class="wp-block-paragraph">这里如果大家是要生成二次元照片的，把重绘幅度拉到0.6~0.8就差不多了，</p>



<p class="wp-block-paragraph">大家可以多试试几个参数</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="919" height="76" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8293.png" alt="" class="wp-image-6470" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8293.png 919w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8293-300x25.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8293-768x64.png 768w" sizes="auto, (max-width: 919px) 100vw, 919px" /></figure>



<p class="wp-block-paragraph">这样设置下来一分钟都不用！就可以生成自己的二次元造型，大家就省下20块钱啦！</p>



<h2 class="wp-block-heading"><strong>6.随便画几笔，你就是“神笔马良”</strong></h2>



<p class="wp-block-paragraph">很多人都有乱涂乱画的习惯，但是大家会不会很好奇，我随便画的东西，AI会生成什么呢？</p>



<p class="wp-block-paragraph">看看下面两张图，左边的图就是我在电脑上随便画的（画的很丑）</p>



<p class="wp-block-paragraph">但是在我告诉SD我画的是什么之后，它直接就给我生成出来一张好看的图，</p>



<p class="wp-block-paragraph">这就让我觉得我画画天赋很高了哈哈哈！！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="767" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8487-1024x767.png" alt="" class="wp-image-6471" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8487-1024x767.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8487-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8487-768x575.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8487.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="767" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8490-1024x767.png" alt="" class="wp-image-6472" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8490-1024x767.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8490-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8490-768x575.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8490.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">这个就是SD图生图里的涂鸦功能，点击空白的地方上传一张纯白的图片，也就是你的画纸</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="902" height="814" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8535.png" alt="" class="wp-image-6473" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8535.png 902w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8535-300x271.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8535-768x693.png 768w" sizes="auto, (max-width: 902px) 100vw, 902px" /></figure>



<p class="wp-block-paragraph">右边的两个小按钮点开就可以调节画笔的大小和颜色</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="913" height="645" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8563.png" alt="" class="wp-image-6474" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8563.png 913w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8563-300x212.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8563-768x543.png 768w" sizes="auto, (max-width: 913px) 100vw, 913px" /></figure>



<p class="wp-block-paragraph">接着就在画纸上随便画画</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="895" height="676" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8579.png" alt="" class="wp-image-6475" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8579.png 895w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8579-300x227.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8579-768x580.png 768w" sizes="auto, (max-width: 895px) 100vw, 895px" /></figure>



<p class="wp-block-paragraph">然后挑合适的大模型，想要什么画风就挑什么模型</p>



<p class="wp-block-paragraph">接着输入关键词</p>



<p class="wp-block-paragraph">一样的，先输入一些关于照片质量的词</p>



<p class="wp-block-paragraph">再告诉SD，你画的是什么</p>



<p class="wp-block-paragraph">比如说我画的就是：河流，森林(river,forest)</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="217" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8678-1024x217.png" alt="" class="wp-image-6476" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8678-1024x217.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8678-300x64.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8678-768x163.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8678.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">最后我们把下面的重绘幅度拉到0.6~0.8，点击生成就可以啦！</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="921" height="71" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8714.png" alt="" class="wp-image-6477" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8714.png 921w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8714-300x23.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8714-768x59.png 768w" sizes="auto, (max-width: 921px) 100vw, 921px" /></figure>



<p class="wp-block-paragraph">是不是非常简单，自己随便画几笔，就能生成出非常好看的照片了！</p>



<h2 class="wp-block-heading"><strong>7.怎么给二次元老婆换衣服</strong></h2>



<p class="wp-block-paragraph">假如我现在有一张非常好看的照片，唯独我觉得她的衣服不好看，</p>



<p class="wp-block-paragraph">那我要怎么在不改变其它地方的情况下，给她换上更好看的衣服呢？</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8828-1024x768.png" alt="" class="wp-image-6478" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8828-1024x768.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8828-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8828-768x576.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8828.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">这里用到的是图生图中局部重绘的功能，导入要调整的照片</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="900" height="813" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8859.png" alt="" class="wp-image-6479" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8859.png 900w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8859-300x271.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8859-768x694.png 768w" sizes="auto, (max-width: 900px) 100vw, 900px" /></figure>



<p class="wp-block-paragraph">点击右边的画笔可以调整大小，把人物衣服部分全部涂黑</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="868" height="746" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8889.png" alt="" class="wp-image-6480" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8889.png 868w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8889-300x258.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时8889-768x660.png 768w" sizes="auto, (max-width: 868px) 100vw, 868px" /></figure>



<p class="wp-block-paragraph">接着输入关键词，先输入质量词（如：高质量，高清画质，8k等）</p>



<p class="wp-block-paragraph">然后描写一下你想要生成什么样的衣服</p>



<p class="wp-block-paragraph">比如我这里输入的就是：粉色汉服，精致的裙子，极具细节的服装</p>



<p class="wp-block-paragraph">负面关键词就直接复制我们前面用的</p>



<p class="wp-block-paragraph">点击生成就可以啦！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="245" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9003-1024x245.png" alt="" class="wp-image-6481" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9003-1024x245.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9003-300x72.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9003-768x183.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9003.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">同样的道理，我们还可以用这个功能来换脸，</p>



<p class="wp-block-paragraph">只是我们涂黑的部分就变成了脸，输入的关键词就是描写脸部、五官的单词。</p>



<p class="wp-block-paragraph">上面的方法用来换衣服只能整体去换，</p>



<p class="wp-block-paragraph">如果我想指定衣服的颜色就只能在关键词里面告诉SD要怎么调整</p>



<p class="wp-block-paragraph">假如现在我想指定服装的颜色，比如：蓝色的衣袖，粉色的衣服，还要有黄色的花纹</p>



<p class="wp-block-paragraph">这时候我们只靠关键词是不行的，出来的照片也不一定准确</p>



<p class="wp-block-paragraph">那我们就可以用到一个新的功能——“涂鸦重绘”</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="900" height="813" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9205.png" alt="" class="wp-image-6482" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9205.png 900w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9205-300x271.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9205-768x694.png 768w" sizes="auto, (max-width: 900px) 100vw, 900px" /></figure>



<p class="wp-block-paragraph">导入照片之后，在右边调整画笔大小和颜色，然后就可以自己设计衣服的颜色啦</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="904" height="812" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9245.png" alt="" class="wp-image-6485" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9245.png 904w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9245-300x269.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9245-768x690.png 768w" sizes="auto, (max-width: 904px) 100vw, 904px" /></figure>



<p class="wp-block-paragraph">关键词就像前面说的那样输入就可以啦，</p>



<p class="wp-block-paragraph">每次点击生成都能出来不一样的衣服</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9286.png" alt="" class="wp-image-6486" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9286.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9286-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>


<h2 class="wp-block-heading"><strong>8.两步拯救超糊照片</strong></h2>



<p class="wp-block-paragraph">SD除了生成新的照片外，还可以用来修复我们比较糊的照片</p>



<p class="wp-block-paragraph">出来的效果比大多数软件都要好！</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="768" height="1024" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9348-768x1024.png" alt="" class="wp-image-6487" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9348-768x1024.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9348-225x300.png 225w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9348.png 960w" sizes="auto, (max-width: 768px) 100vw, 768px" /></figure>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="512" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9351-1024x512.png" alt="" class="wp-image-6488" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9351-1024x512.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9351-300x150.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9351-768x384.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9351.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">这个恢复画质的功能在SD里叫“后期处理”，点击下面空白的地方上传图片</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="915" height="493" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9390.png" alt="" class="wp-image-6489" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9390.png 915w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9390-300x162.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9390-768x414.png 768w" sizes="auto, (max-width: 915px) 100vw, 915px" /></figure>



<p class="wp-block-paragraph">接着我们看到下面这个“Upscaler 1”，也就是放大器</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="916" height="83" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9423.png" alt="" class="wp-image-6490" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9423.png 916w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9423-300x27.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9423-768x70.png 768w" sizes="auto, (max-width: 916px) 100vw, 916px" /></figure>



<p class="wp-block-paragraph"><strong>修复二次元的照片就选“R-ESRGAN 4x+Anime68”</strong></p>



<p class="wp-block-paragraph"><strong>其他实物照片就选“R-ESRGAN 4x+”</strong></p>



<p class="wp-block-paragraph">其他放大器出来的效果都没有这两个好</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="909" height="337" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9501.png" alt="" class="wp-image-6491" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9501.png 909w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9501-300x111.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9501-768x285.png 768w" sizes="auto, (max-width: 909px) 100vw, 909px" /></figure>



<p class="wp-block-paragraph">最后点击生成就可以！</p>



<p class="wp-block-paragraph">这个功能还可以拿来修复真人的照片，但是上面说到的流程是不适用于真人照片的</p>



<p class="wp-block-paragraph">比如说我们现在要修复这张表情包</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="418" height="294" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9571.png" alt="" class="wp-image-6492" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9571.png 418w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9571-300x211.png 300w" sizes="auto, (max-width: 418px) 100vw, 418px" /></figure>
</div>


<p class="wp-block-paragraph">我们先把照片导入到SD</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="903" height="480" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9587.png" alt="" class="wp-image-6493" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9587.png 903w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9587-300x159.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9587-768x408.png 768w" sizes="auto, (max-width: 903px) 100vw, 903px" /></figure>



<p class="wp-block-paragraph">这边放大器选择“无（None）”</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="917" height="80" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9607.png" alt="" class="wp-image-6494" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9607.png 917w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9607-300x26.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9607-768x67.png 768w" sizes="auto, (max-width: 917px) 100vw, 917px" /></figure>



<p class="wp-block-paragraph">再往下看到这个“GFPGAN强度”</p>



<p class="wp-block-paragraph">这个是专门用来修复人脸的，把参数拉满（1）就行</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="944" height="72" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9653.png" alt="" class="wp-image-6495" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9653.png 944w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9653-300x23.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9653-768x59.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9653-930x72.png 930w" sizes="auto, (max-width: 944px) 100vw, 944px" /></figure>



<p class="wp-block-paragraph">接着点击“生成”</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="418" height="294" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9666.png" alt="" class="wp-image-6496" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9666.png 418w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9666-300x211.png 300w" sizes="auto, (max-width: 418px) 100vw, 418px" /></figure>
</div>


<p class="wp-block-paragraph">这样我们的人脸就修复了，但是也只能修复脸的部分，除了脸其他的地方还是比较糊。</p>



<h2 class="wp-block-heading"><strong>9.3秒教你获取大佬的咒语</strong></h2>



<p class="wp-block-paragraph">在网上经常看到别的大佬的图觉得很好看，想要复制却复制不出来</p>



<p class="wp-block-paragraph">但其实SD里面就有这样一个功能</p>



<p class="wp-block-paragraph">把照片导进去，它就能识别出来这张照片用到的咒语或者关键词</p>



<p class="wp-block-paragraph">第一个就是“PNG图片信息”</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="210" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9819-1024x210.png" alt="" class="wp-image-6497" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9819-1024x210.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9819-300x62.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9819-768x158.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9819.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">把照片导进去，右边就会自动弹出照片的信息，包括正面关键词、负面关键词，还有其他种子、大模型等信息</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="344" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9872-1024x344.png" alt="" class="wp-image-6498" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9872-1024x344.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9872-300x101.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9872-768x258.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9872.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">我们可以复制这一大串信息，来到“文生图”的页面，把全部信息粘贴到关键词的文本框中</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="241" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9917-1024x241.png" alt="" class="wp-image-6500" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9917-1024x241.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9917-300x71.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9917-768x181.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时9917.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">然后点击“生成”按钮下面的第一个小按钮，SD就会自动帮你把信息分配到合适的地方，用上一样的效果和模型</p>



<p class="wp-block-paragraph">这时候点击生成，就能得到一张差不多一样的照片（前提是有一样的大模型和Lora）</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="425" height="166" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10013.png" alt="" class="wp-image-6501" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10013.png 425w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10013-300x117.png 300w" sizes="auto, (max-width: 425px) 100vw, 425px" /></figure>



<p class="wp-block-paragraph">有时候我们把照片导入进去之后，发现右边并没有照片生成的信息</p>



<p class="wp-block-paragraph">那就说明这张照片不是直接从SD下载下来的PNG格式的照片</p>



<p class="wp-block-paragraph">那我们就没法用这个功能</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="295" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10090-1024x295.png" alt="" class="wp-image-6502" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10090-1024x295.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10090-300x86.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10090-768x221.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10090.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">但是我们可以用后面这个“标签器（Tagger）”</p>



<p class="wp-block-paragraph">它可以帮助我们生成照片的关键词</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="296" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10136-1024x296.png" alt="" class="wp-image-6503" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10136-1024x296.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10136-300x87.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10136-768x222.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10136.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">比如说我们现在导入一张照片，右边就会出来这张照片的关键词</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="308" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10169-1024x308.png" alt="" class="wp-image-6504" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10169-1024x308.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10169-300x90.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10169-768x231.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10169.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">anya (spy x family), 1girl, solo, school uniform, eden academy school uniform, pink hair, green eyes, female child, looking at viewer, open mouth, ahoge, meme, salute, child, parody, upper body, black dress</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">阿尼亚(间谍 x 家庭) ，1个女孩，独唱，校服，伊甸园学院校服，粉色头发，绿色眼睛，女孩，看观众，张嘴，阿霍格，迷因，敬礼，孩子，模仿，上身，黑色礼服</p>
</blockquote>



<p class="wp-block-paragraph">可以看到这样出来的关键词还是非常准确的，</p>



<p class="wp-block-paragraph">通过这两种方法，我们就可以获取到好看的照片的重要信息！</p>



<h2 class="wp-block-heading"><strong>10.一招让你自由指定女神的姿势</strong></h2>



<p class="wp-block-paragraph">现在我们已经能够生成美女的照片了</p>



<p class="wp-block-paragraph">可以定制出独一无二的脸，换上更好看的衣服</p>



<p class="wp-block-paragraph">但是我们怎么才能让照片的小姐姐摆出指定的姿势呢？</p>



<p class="wp-block-paragraph">通过关键词去描绘动作，可是出来的照片又不太准确</p>



<p class="wp-block-paragraph">通过图生图去生成，可是人脸又变了</p>



<p class="wp-block-paragraph">那我们就可以用到这个“ControlNet”功能，翻译成中文就是控制网络</p>



<p class="wp-block-paragraph">简单来说就是可以用它控制照片的线条，比如人物的动作、建筑物的线条等</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="901" height="62" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10707.png" alt="" class="wp-image-6505" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10707.png 901w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10707-300x21.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10707-768x53.png 768w" sizes="auto, (max-width: 901px) 100vw, 901px" /></figure>



<p class="wp-block-paragraph">比如，我现在想让左边照片的小姐姐摆出右边小姐姐的姿势,得到最右边的一张照片</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="384" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10749-1024x384.png" alt="" class="wp-image-6506" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10749-1024x384.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10749-300x113.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10749-768x288.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10749.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">首先，大模型和关键词我们还是正常的填写</p>



<p class="wp-block-paragraph">生成一张我们我们想要的小姐姐的照片</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="315" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10792-1024x315.png" alt="" class="wp-image-6507" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10792-1024x315.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10792-300x92.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10792-768x236.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10792.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">接着鼠标滑到最下面，点击“ControlNet”</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="897" height="59" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10820.png" alt="" class="wp-image-6508" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10820.png 897w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10820-300x20.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10820-768x51.png 768w" sizes="auto, (max-width: 897px) 100vw, 897px" /></figure>



<p class="wp-block-paragraph">①点击空白的地方，上传我们需要指定的姿势的照片</p>



<p class="wp-block-paragraph">②点击“启用”</p>



<p class="wp-block-paragraph">③在“预处理器”和“模型”里选择“openpose”，这就是用来让计算机识别人物姿势的</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="889" height="726" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10900.png" alt="" class="wp-image-6509" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10900.png 889w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10900-300x245.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10900-768x627.png 768w" sizes="auto, (max-width: 889px) 100vw, 889px" /></figure>



<p class="wp-block-paragraph">下一步就点击这个“预览预处理结果”</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="857" height="149" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10922.png" alt="" class="wp-image-6510" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10922.png 857w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10922-300x52.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10922-768x134.png 768w" sizes="auto, (max-width: 857px) 100vw, 857px" /></figure>



<p class="wp-block-paragraph">接着原来照片的右边就会出现人物姿势的线条，最后点击生成照片</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="877" height="681" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10956.png" alt="" class="wp-image-6511" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10956.png 877w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10956-300x233.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10956-768x596.png 768w" sizes="auto, (max-width: 877px) 100vw, 877px" /></figure>



<p class="wp-block-paragraph">这样我们一张指定姿势的美女小姐姐就生成啦！</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10982.png" alt="" class="wp-image-6512" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10982.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时10982-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>


<h2 class="wp-block-heading"><strong>11.插画师的福音，线稿秒上色</strong></h2>



<p class="wp-block-paragraph">随着AI绘画越来越火，很多人都会说将来可能很多画师的职业都受到威胁了</p>



<p class="wp-block-paragraph">但是，会用AI绘画的画师一定会比那些不会AI绘画的画师更有优势</p>



<p class="wp-block-paragraph">当别人为了给线稿上色，花了一天的时间</p>



<p class="wp-block-paragraph">而你一分钟不到就出了一张质量不错的图</p>



<p class="wp-block-paragraph">单是工作效率上就领先别人很多了</p>



<p class="wp-block-paragraph">下面这张就是我在网上随便找的一张线稿图，通过SD上色出来的一张照片</p>



<p class="wp-block-paragraph">这也是通过使用“ControlNet”这个功能生成的</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="512" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11191-1024x512.png" alt="" class="wp-image-6513" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11191-1024x512.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11191-300x150.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11191-768x384.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11191.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">首先，我们点开&#8221;ControlNet&#8221;的状态栏</p>



<p class="wp-block-paragraph">①在空白的地方上传自己的线稿图</p>



<p class="wp-block-paragraph">②点击“启用”</p>



<p class="wp-block-paragraph">③点击“反转输出颜色”</p>



<p class="wp-block-paragraph">④在模型里面选择“canny”的模型</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="878" height="721" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11275.png" alt="" class="wp-image-6514" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11275.png 878w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11275-300x246.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11275-768x631.png 768w" sizes="auto, (max-width: 878px) 100vw, 878px" /></figure>



<p class="wp-block-paragraph">接着去设置我们前面的内容</p>



<p class="wp-block-paragraph">①选择合适的大模型</p>



<p class="wp-block-paragraph">我想要生成二次元的图，就要选择相应的模型</p>



<p class="wp-block-paragraph">②关键词</p>



<p class="wp-block-paragraph">跟我们写关键词一样，先写照片质量的关键词（比如：最高质量，大师杰作等）</p>



<p class="wp-block-paragraph">接着我们就可以指定上什么颜色了</p>



<p class="wp-block-paragraph">比如我输入的就是：1可爱女孩，五官精致，精致眼睛和嘴巴，银色长发，白皙的皮肤，水汪汪的大眼睛,</p>



<p class="wp-block-paragraph">最后还加上一个简单的背景</p>



<p class="wp-block-paragraph">想要色彩更加细节，就可以通过输入更多的关键词来控制照片</p>



<p class="wp-block-paragraph">负面关键词只要复制前面的就可以</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="284" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11492-1024x284.png" alt="" class="wp-image-6515" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11492-1024x284.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11492-300x83.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11492-768x213.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11492.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">就这样不管再复杂的线稿，在SD里面都可以很快速的上好颜色</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="512" height="512" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11525.png" alt="" class="wp-image-6516" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11525.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11525-300x300.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11525-150x150.png 150w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>


<h2 class="wp-block-heading"><strong>12.小白也能进行室内设计</strong></h2>



<p class="wp-block-paragraph">“ControlNet”还有一个非常好用的功能，</p>



<p class="wp-block-paragraph">那就是进行室内设计</p>



<p class="wp-block-paragraph">比如说我现在想对房间进行重新装修</p>



<p class="wp-block-paragraph">我想看看我的房子弄成不同的风格是怎样的</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="384" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11619-1024x384.png" alt="" class="wp-image-6517" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11619-1024x384.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11619-300x113.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11619-768x288.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11619.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">首先先点开“ControlNet”的状态栏</p>



<p class="wp-block-paragraph">①上传需要进行设计的房间照片</p>



<p class="wp-block-paragraph">②点击“启用”</p>



<p class="wp-block-paragraph">③预处理器和模型都选“msld”，这是用来计算房屋线条的</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="891" height="719" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11698.png" alt="" class="wp-image-6518" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11698.png 891w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11698-300x242.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11698-768x620.png 768w" sizes="auto, (max-width: 891px) 100vw, 891px" /></figure>



<p class="wp-block-paragraph">接着切换一个现实照片的大模型</p>



<p class="wp-block-paragraph">关键词先输入照片质量关键词</p>



<p class="wp-block-paragraph">然后就是输入照片的主体：一个客厅</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="287" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11749-1024x287.png" alt="" class="wp-image-6519" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11749-1024x287.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11749-300x84.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11749-768x215.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11749.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">最后点击生成</p>



<p class="wp-block-paragraph">这样出来的照片既保留了原来房子的构造，又可以看到新的房屋风格！</p>



<h1 class="wp-block-heading"><strong>四、Stable diffusion知识补充</strong></h1>



<p class="wp-block-paragraph">这一节是SD剩余功能的一些补充知识，大家不用担心SD功能太多太复杂，</p>



<p class="wp-block-paragraph">这一节大多数功能的参数只要照抄就行！</p>



<h2 class="wp-block-heading"><strong>1.VAE</strong></h2>



<p class="wp-block-paragraph">作为新手小白，我们没必要知道它的基础工作原理</p>



<p class="wp-block-paragraph">只要知道<strong>VAE的作用就是加滤镜和微调照片</strong></p>



<p class="wp-block-paragraph">下面图片就是没加VAE和加了VAE的区别</p>



<p class="wp-block-paragraph">没加VAE的照片是灰蒙蒙的</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11964-1024x768.png" alt="" class="wp-image-6520" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11964-1024x768.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11964-300x225.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11964-768x576.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时11964.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">但在一般情况下，如果我们对照片的色彩没有特别要求的时候，只选定一个VAE来使用就可以。</p>



<p class="wp-block-paragraph">下面这个就是我比较常用的VAE</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="443" height="98" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12029.png" alt="" class="wp-image-6521" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12029.png 443w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12029-300x66.png 300w" sizes="auto, (max-width: 443px) 100vw, 443px" /></figure>



<h2 class="wp-block-heading"><strong>2.迭代步数</strong></h2>



<p class="wp-block-paragraph">简单的说，我们把在SD生成图片的过程当作在画画</p>



<p class="wp-block-paragraph">迭代步数的意思就是我们在这幅画上画多少笔</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="918" height="81" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12087.png" alt="" class="wp-image-6522" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12087.png 918w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12087-300x26.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12087-768x68.png 768w" sizes="auto, (max-width: 918px) 100vw, 918px" /></figure>



<p class="wp-block-paragraph">一般我们把参数设置在20~30之间</p>



<p class="wp-block-paragraph">看下面的图，20步以下的图质量都不高</p>



<p class="wp-block-paragraph">但不是说步数越多越好</p>



<p class="wp-block-paragraph">超过30步部分电脑可能就带不动，无法生成照片了</p>



<p class="wp-block-paragraph">所以，<strong>电脑配置稍微低一点的就设置在20~25</strong></p>



<p class="wp-block-paragraph"><strong>电脑配置比较好的就可以设置在25~30之间</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="201" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12211-1024x201.png" alt="" class="wp-image-6523" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12211-1024x201.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12211-300x59.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12211-768x151.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12211.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<h2 class="wp-block-heading"><strong>3.采样方法</strong></h2>



<p class="wp-block-paragraph">采用方法的不同就相当于我们画画的方式不一样</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="904" height="238" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12246.png" alt="" class="wp-image-6524" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12246.png 904w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12246-300x79.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12246-768x202.png 768w" sizes="auto, (max-width: 904px) 100vw, 904px" /></figure>



<p class="wp-block-paragraph">那这么多采用方法怎么选呢？</p>



<p class="wp-block-paragraph">首先，我们看到别人好看的照片，可以看看人家用的是哪一个采用方法</p>



<p class="wp-block-paragraph">如果实在不知道用哪一个，这里也给大家测试过了，</p>



<p class="wp-block-paragraph">用下面框出来的几个，出来的照片质量比较高，而且出图速度也比较快</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="905" height="213" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12354.png" alt="" class="wp-image-6525" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12354.png 905w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12354-300x71.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12354-768x181.png 768w" sizes="auto, (max-width: 905px) 100vw, 905px" /></figure>



<h2 class="wp-block-heading"><strong>4.面部修复+高分辨率修复</strong></h2>



<p class="wp-block-paragraph">这两个功能没什么好讲的，大家直接抄作业就可以！</p>



<p class="wp-block-paragraph">面部修复：用在生成真人照片上</p>



<p class="wp-block-paragraph">高分辨率修复：电脑配置好就可以用；电脑配置稍微差点的别开，否则照片无法生成</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="565" height="55" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12452.png" alt="" class="wp-image-6526" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12452.png 565w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12452-300x29.png 300w" sizes="auto, (max-width: 565px) 100vw, 565px" /></figure>



<h2 class="wp-block-heading"><strong>5.图片分辨率（图片大小）</strong></h2>



<p class="wp-block-paragraph">这里的宽度和高度就是用来调节照片大小的</p>



<p class="wp-block-paragraph">一般情况下：</p>



<p class="wp-block-paragraph">生成正方形的照片：宽度512*高度512</p>



<p class="wp-block-paragraph">生成长方形的照片：宽度512*高度768</p>



<p class="wp-block-paragraph">电脑配置稍微差点的朋友们，千万别看网上设置成什么1024、2048，我们电脑跑不动哒！</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="609" height="142" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12587.png" alt="" class="wp-image-6527" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12587.png 609w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12587-300x70.png 300w" sizes="auto, (max-width: 609px) 100vw, 609px" /></figure>



<h2 class="wp-block-heading"><strong>6.生成多图</strong></h2>



<p class="wp-block-paragraph">通过调整下面这两个参数，可以让我们一次生成多个图</p>



<p class="wp-block-paragraph">假如我们把两个参数都设置成2</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="270" height="152" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12640.png" alt="" class="wp-image-6528"/></figure>



<p class="wp-block-paragraph">总批次数的意思就是生成两批</p>



<p class="wp-block-paragraph">单批数量的意思就是一批生成两张照片</p>



<p class="wp-block-paragraph">所以一共就会生成4张照片</p>



<p class="wp-block-paragraph">在我们日常使用需要生成多张照片的</p>



<p class="wp-block-paragraph">我们只调整“总批次数”就可以啦，这意味着我们照片是一张一张生成的</p>



<p class="wp-block-paragraph">单批数量就意味着同时生成多张照片，这对我们的显卡是有一定要求的，所以这个不要用！！</p>



<h2 class="wp-block-heading"><strong>7.用脚本进行照片对比</strong></h2>



<p class="wp-block-paragraph">我们生成一张照片会输入很多的关键词，</p>



<p class="wp-block-paragraph">那我们怎么才能看到输入不同的关键词，</p>



<p class="wp-block-paragraph">出来的照片有什么区别</p>



<p class="wp-block-paragraph">或者加某个关键词和不加的区别呢？</p>



<p class="wp-block-paragraph">那我们就要用到最下面“脚本”里的“提示词矩阵”，直接点击就可以</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="920" height="218" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12899.png" alt="" class="wp-image-6529" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12899.png 920w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12899-300x71.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12899-768x182.png 768w" sizes="auto, (max-width: 920px) 100vw, 920px" /></figure>



<p class="wp-block-paragraph">接着来到关键词的文本框</p>



<p class="wp-block-paragraph">我们前面一直说在写关键词之前，先写照片的质量词</p>



<p class="wp-block-paragraph">那我们就以这张照片为例子，</p>



<p class="wp-block-paragraph">看看加上最高质量（the best quality）和不加有什么区别</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><img loading="lazy" decoding="async" width="512" height="768" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12990.png" alt="" class="wp-image-6530" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12990.png 512w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时12990-200x300.png 200w" sizes="auto, (max-width: 512px) 100vw, 512px" /></figure>
</div>


<p class="wp-block-paragraph">书写的格式：把需要进行对比的关键词放在最后，用“|”把关键词和前面的关键词分隔开</p>



<p class="wp-block-paragraph">也就是：<strong>关键词|需要对比的关键词</strong></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="119" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13052-1024x119.png" alt="" class="wp-image-6531" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13052-1024x119.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13052-300x35.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13052-768x89.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13052.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">点击生成就会出现两张拼在一起的照片，</p>



<p class="wp-block-paragraph">我们就可以看到加了“最高质量（the best quality）”的照片会更加清晰</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="1024" height="869" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13118.png" alt="" class="wp-image-6532" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13118.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13118-300x255.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13118-768x652.png 768w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">那如果现在想要比较不同的采用方法下，迭代步数不一样，生成的照片有什么区别，该怎么操作呢？</p>



<p class="wp-block-paragraph">这里用到的就是脚本里的“X/Y/Z图表”</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="904" height="208" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13188.png" alt="" class="wp-image-6534" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13188.png 904w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13188-300x69.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13188-768x177.png 768w" sizes="auto, (max-width: 904px) 100vw, 904px" /></figure>



<p class="wp-block-paragraph">在X轴类型里面选择“迭代步数”，右边的X轴值就输入需要进行比较的步数</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="911" height="85" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13226.png" alt="" class="wp-image-6535" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13226.png 911w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13226-300x28.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13226-768x72.png 768w" sizes="auto, (max-width: 911px) 100vw, 911px" /></figure>



<p class="wp-block-paragraph">在Y轴类型里面选择“采用器”，接着点击最右边的笔记本图标</p>



<p class="wp-block-paragraph">那样所有采样器的名称都会出现在框框里面，可以自己进行删减</p>



<p class="wp-block-paragraph">我们这里就选三个比较常用的采样器</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="913" height="98" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13306.png" alt="" class="wp-image-6537" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13306.png 913w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13306-300x32.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13306-768x82.png 768w" sizes="auto, (max-width: 913px) 100vw, 913px" /></figure>



<p class="wp-block-paragraph">这边X轴和Y轴的信息是可以全部换过来写的，看个人习惯</p>



<p class="wp-block-paragraph">点击“生成”</p>



<p class="wp-block-paragraph">就会生成这么一张大图</p>



<p class="wp-block-paragraph">我们就可以看到在不同的采用方法下，迭代步数为25的时候，生成出来的照片都差不多</p>



<p class="wp-block-paragraph">这样比较下来，我们就可以选择自己更喜欢的采样方法和迭代步数</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="1012" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13427-1024x1012.png" alt="" class="wp-image-6538" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13427-1024x1012.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13427-300x296.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13427-768x759.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13427.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<h1 class="wp-block-heading"><strong>五、大神的模型从哪来</strong></h1>



<h2 class="wp-block-heading"><strong>1.模型在哪下载</strong></h2>



<p class="wp-block-paragraph">除了链接里面给大家分享的模型，大家肯定还想去找更多更好看的模型</p>



<p class="wp-block-paragraph">而大多数的模型都是在Civitai（C站）这个网站里面https://civitai.com/</p>



<p class="wp-block-paragraph">现在就给大家说一下C站的使用方法：</p>



<p class="wp-block-paragraph"><strong>01.科学上网</strong></p>



<p class="wp-block-paragraph">这个没法教，大家只能自己想办法了</p>



<p class="wp-block-paragraph"><strong>02.点击右上角的筛选按钮，在框框里面找到自己需要的模型类型</strong></p>



<p class="wp-block-paragraph">Checkpoint=大模型</p>



<p class="wp-block-paragraph">LoRA=Lora</p>



<p class="wp-block-paragraph">常用的就是这两个</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="479" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13650-1024x479.png" alt="" class="wp-image-6539" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13650-1024x479.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13650-300x140.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13650-768x359.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13650.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph"><strong>03.看照片，看到感兴趣的就点进去</strong></p>



<p class="wp-block-paragraph">点击右边的“Download”，也就是下载，保存到电脑本地，</p>



<p class="wp-block-paragraph">文件保存到哪里在这一节的第二部分</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="440" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13722-1024x440.png" alt="" class="wp-image-6540" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13722-1024x440.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13722-300x129.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13722-768x330.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13722.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">另外，我们还可以点击左上角的“Images”</p>



<p class="wp-block-paragraph">这里就是看别人已经做好的图片，找到喜欢的点进去</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="467" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13774-1024x467.png" alt="" class="wp-image-6541" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13774-1024x467.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13774-300x137.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13774-768x351.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13774.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">点进去之后的页面我们就可以看到这张图的全部信息，</p>



<p class="wp-block-paragraph">直接点击Lora和大模型，可以直接跳转到下载页面</p>



<p class="wp-block-paragraph">下面的就是照片关键词和其他信息</p>



<p class="wp-block-paragraph">点击最下面的“Copy&#8230;Data”就可以复制图片的所有信息</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="470" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13878-1024x470.png" alt="" class="wp-image-6542" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13878-1024x470.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13878-300x138.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13878-768x353.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13878.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">回到SD，粘贴到关键词的文本框，点击右边的按钮</p>



<p class="wp-block-paragraph">这些信息就会自动分配</p>



<p class="wp-block-paragraph">要注意的就是，<strong>大模型是需要我们手动去换</strong>的！</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="1080" height="266" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13941.png" alt="" class="wp-image-6545" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13941.png 1080w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13941-300x74.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13941-1024x252.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13941-768x189.png 768w" sizes="auto, (max-width: 1080px) 100vw, 1080px" /></figure>



<p class="wp-block-paragraph">这样我们就可以生成出跟大神几乎一样的照片了！（电脑网络配置的不同，出来的照片有细微差别）</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="864" height="1152" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13990.png" alt="" class="wp-image-6546" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13990.png 864w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13990-225x300.png 225w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时13990-768x1024.png 768w" sizes="auto, (max-width: 864px) 100vw, 864px" /></figure>



<h2 class="wp-block-heading"><strong>2.模型下载到哪里</strong></h2>



<p class="wp-block-paragraph">这里大家就直接看我文件的保存地址，找到自己电脑里的</p>



<p class="wp-block-paragraph"><strong>01.大模型</strong></p>



<p class="wp-block-paragraph">这里的SD根目录就是大家在下载时，存放SD的那个文件夹</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="850" height="73" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14068-1.png" alt="" class="wp-image-6547" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14068-1.png 850w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14068-1-300x26.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14068-1-768x66.png 768w" sizes="auto, (max-width: 850px) 100vw, 850px" /></figure>



<p class="wp-block-paragraph"><strong>02.Lora</strong></p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="852" height="53" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14080-1.png" alt="" class="wp-image-6548" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14080-1.png 852w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14080-1-300x19.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14080-1-768x48.png 768w" sizes="auto, (max-width: 852px) 100vw, 852px" /></figure>



<p class="wp-block-paragraph"><strong>03.VAE</strong></p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="838" height="53" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14091.png" alt="" class="wp-image-6549" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14091.png 838w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14091-300x19.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14091-768x49.png 768w" sizes="auto, (max-width: 838px) 100vw, 838px" /></figure>



<h2 class="wp-block-heading"><strong>3.如何分辨模型</strong></h2>



<p class="wp-block-paragraph">如果我们下载了一个模型，但不知道它是哪个类型的，不知道要放到哪个文件夹</p>



<p class="wp-block-paragraph">我们就可以用到这个秋叶的模型解析工具 &nbsp; https://spell.novelai.dev/</p>



<p class="wp-block-paragraph">把模型拖动到空白处</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="312" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14202-1024x312.png" alt="" class="wp-image-6550" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14202-1024x312.png 1024w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14202-300x91.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14202-768x234.png 768w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14202.png 1080w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p class="wp-block-paragraph">接着就会自动弹出模型的信息</p>



<p class="wp-block-paragraph">在模型种类里面就可以看到是什么模型啦！</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="981" height="379" src="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14241.png" alt="" class="wp-image-6551" srcset="https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14241.png 981w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14241-300x116.png 300w, https://blog.deephour.com/wp-content/uploads/2024/04/耗时80小时14241-768x297.png 768w" sizes="auto, (max-width: 981px) 100vw, 981px" /></figure>



<h1 class="wp-block-heading"><strong>六、结尾</strong></h1>



<p class="wp-block-paragraph">安装包，大模型，lora：</p>



<p class="wp-block-paragraph">链接：https://pan.baidu.com/s/1hY8CKbYRAj9RrFGmswdNiA?pwd=caru</p>



<p class="wp-block-paragraph">提取码：caru</p>



<p class="wp-block-paragraph">好啦，希望这篇文章能够真正帮助到你上手SD</p>



<p class="wp-block-paragraph">之后我还会出SD的《Stable Diffusion进阶宝典》《热门Lora模型大全》《Lora炼制秘籍》</p>
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