DryLabRebel/PY0101EN-5.3_Requests_HTTP.ipynb

## PY0101EN-5.3_Requests_HTTP.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://cognitiveclass.ai/\">\n",
    "    <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/Ad/CCLog.png\" width=\"200\" align=\"center\">\n",
    "</a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> HTTP and Requests</h1>\n",
    "\n",
    "Estimated time needed: **15** minutes\n",
    "\n",
    "## Objectives\n",
    "\n",
    "After completing this lab you will be able to:\n",
    "\n",
    "-   Understand HTTP    \n",
    "-   Handle the HTTP Requests\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Table of Contents</h2>\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "    <ul>\n",
    "        <li>\n",
    "            <a href=\"#index\">Overview of HTTP </a>\n",
    "            <ul>\n",
    "                <li><a href=\"#HTTP\">Uniform Resource Locator:URL</a></li>\n",
    "                 <li><a href=\"slice\">Request</a></li>\n",
    "                <li><a href=\"stride\">Response</a></li>\n",
    "            </ul>\n",
    "        </li>\n",
    "        <li>\n",
    "            <a href=\"#RP\">Requests in Python  </a>\n",
    "            <ul>\n",
    "                <li><a href=\"#get\">Get Request with URL Parameters</a></li>\n",
    "                <li><a href=\"#post\">Post Requests </a></li>\n",
    "\n",
    "</ul>\n",
    "    \n",
    "</div>\n",
    "\n",
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"\">Overview of HTTP </h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you, the **client**, use a web page your browser sends an **HTTP** request to the **server** where the page is hosted. The server tries to find the desired **resource** by default  \"<code>index.html</code>\". If your request is successful, the server will send the object to the client in an **HTTP response**; this includes information like the type of the **resource**, the length of the **resource**, and other information.   \n",
    "\n",
    "<p>\n",
    "The figure below represents the process; the circle on the left represents the client, the circle on the right represents the  Web server.  The table under the Web server represents a list of resources stored in the web server. In  this case an <code>HTML</code> file, <code>png</code> image, and <code>txt</code> file .\n",
    "</p>\n",
    "<p>\n",
    "The <b>HTTP</b> protocol allows you to send and receive information through the web including webpages, images, and other web resources. In this lab, we will provide an overview of the Requests library for interacting with the <code>HTTP </code> protocol. \n",
    "</p\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/reqest_basics.png\" width=\"750\" align=\"center\">\n",
    "   \n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"URL\">Uniform Resource Locator:URL</h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Uniform resource locator (URL) is the most popular way to find resources on the web.  We can break the URL into three parts. \n",
    "\n",
    "<ul>\n",
    "    <li><b>scheme</b> this is this protocol, for this lab it will always be <code>http://</code>  </li>\n",
    "    <li><b> Internet address or  Base URL </b> this will be used to find the location here are some examples: <code>www.ibm.com</code> and  <code> www.gitlab.com </code> </li>\n",
    "    <li><b>route</b> location on the web server for example: <code>/images/IDSNlogo.png</code> </li>\n",
    "</ul>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You may also here the term uniform resource identifier (URI), URL are actually a subset of URIs. Another popular term is endpoint, this is the URL of an operation provided by a Web server.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"RE\">Request </h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The process can be broken into the <b>request</b> and <b>response </b> process.  The request using the get method is partially illustrated below. In the start line we have the <code>GET</code> method, this is an <code>HTTP</code> method. Also the location of the resource  <code>/index.html</code> and the <code>HTTP</code> version .The Request header passes additional information with an <code>HTTP</code> request:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/reqest_messege.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When an <code>HTTP</code> request is made, an <code>HTTP</code> method is sent, this tells the server what action to perform.  A list of several <code>HTTP</code> methods is shown below. We will go over more examples later.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/http_methods.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"RES\">Response</h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The figure below represents the response; the response start line contains the version number <code>HTTP/1.0</code>, a status code (200)  meaning success, followed by a descriptive phrase (OK). The response header contains useful information. Finally, we have the response body containing the requested file an <code> HTML </code> document.  It should be noted that some request have headers.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/response_message.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some status code examples are shown in the table below, the prefix indicates the class; these are shown in yellow, with actual status codes shown in  white. Check out the following  <a href=\"https://developer.mozilla.org/en-US/docs/Web/HTTP/Status\">link </a>  for more descriptions.\n"
   ]
  },
  {
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n5g19v+zDMSFoji+si3z2mnBIx3bh6XFTdFBnVwMJIMSivSBGiJ3VOq3TkeH0CeoPJ5aR2okQGylz9cgsQqwHIA43kgBCzDd7UULspPaI3eT3iI0fFvmjR/W9hlDrIVchpmU5qcLuppjwM0U8rEMjv/YZv7B25Rryo8fGdbz8yzpePstSbHo0pLLYgDD1J1AdIRZrGHdBf157L3b0Pa7W8C8dG32ge/eVxmSv92Qa92qvfXg4mhmauKNDE7u+ItYlb+FDJp/bmk+7mKFqvWfis6Ftnu3vZN7tkfDapnlRgks4vmxxmXjPaV2+Y0DrcplyvlTjzbzoeWYWwmx2CufPpNA7j+c14pYftBLQoYB9zXQYi1/juFfPD/uCa0KpaNnDeY7FFw2ov8JhzcFe4YMIrE3tnjL8yKQ1+HVmzu5dvuHsZ9IIFoRYwIItCFgCCDGfRFFC7G39kvzcfxL5b/87kdtvtNiDdd5CzNxNH9Yb1deDJDpb8ZfbT+h09bc6pqtvT+PbOa37RqHpxW+K3bPCUQjUlUBlhNj5PXnmyyL/ecMn/bP6/qvWI1fZhr/WB6/9hcgf/7HObKcPfyKLDsc+rL3v907qlPNXRY74P+z1viff1AdKb/x//u4f6EQdibHTIkf0gdHPxKK5UtO47/bYzvhPzeMbKyLf1Py98Lx+RiQ8a4MNq/FMfUrkU3eI3PIr2vNmy2ePd9Y2z/6OHnzeeEHk3z2iQiKcpuHyOzrh0kNmlEQovh5xmWF6L//vOhOvcrDfT7PZGleh+lu/LXL3Z9ojL+z+8PqtkyL/UTk/Fp6C0AQYa9vpt9VONybsFMpfKzJHQ17z9frfKNcXNX/f0rzFJllpnab/JvX95U8q43/5L3W0RoKvn44yePaPRP6LxtladP1I/J6lvaMzd+pRG8YG1d+3fU4/ZXBVOM+aX7X/s/9B5C9P+wHfo3ZWVp9p3Z/DYc1xR/n800w8++VHJu3hr7OU8im33OxnWflrhFgMCD8hoATqIMTEy2E5c+aMpzxaf2fOXKgx5vVnspf+tzrXTtOmbdY6NLHrOUHe3OE2jyfjjMe7u+4Ooz1nPdJOHi8uvbxsQDyBz8BiFFm8+OK7WnXTJZeY6y8vG4o3P5GsB/Q7YqlpbOmxcF1lttvhxdtY1rrLr0PjYeK/p7Te203Ui+1y7awl04ifn/p7TLyziXiDOmttUTxttyfKkBqfH3ZWz3PX41FbdOOzcLh7ujp9eoR7t7jWl8RTvZSpHEsbsbxrOrOT2c49shA7N+F7oeMa74Leu3qxdB2fV9+J8m1zdTFwnZ+2T0d3RJiaNFxxtsPFw5o8xPPV/r2ffpTXddauR0LlK8B+8bpqazXpH+32TvQ6ip/Hb/jU2QeM5rB1mNEio7iYmmTopU5CzNw8XA0sY+hF/6Y877oRj4u3mXLjSbsh2f3FpEflU+fKh7Jl9+/KCDFHQ2pehdPKfLKBZW8saevkA6c2D1dDOS0O1/4VbVDaeim87iWEXHGF941Pi7eTqB+jNnQ1NOeV2eKR3nx0JILmO4jPGZdh7Xh4F86na9sy2TqVXSzbeKIP54L8tfPaZr2j8Q4icG0aZj0dEbu+Lzj8LXxOr+1kI1+FmCPOwBfd5auEH+V8nZVhv7A/m+109nHu/I6z43d9fQIh5ku4ugmxtB4v0aey646n2uaGZhpU4RtOP9vFpFffC49KFdv24wNVFmK9GsPdjs9GekLaPmEa9d3O6XospUdsfmqIOEM9T2MqqKJiLOrHroZm1/yG4m6LpSC+YeJKpKn1/obW71l70eLn2wd4SZ9t3zNWMvSEjalt4vHGf1vBaNMZVpSPuXrEhhBio+BHcabmt+s6azMu1n7Wjnbt8umkWA6uAXsea5jU2QcQYjUVYkZELekTXFel7NpnGhjJoUL9CbP806PyqXPlQ9my+/eoCbFp7SFbW9cedu2BX9Gh0lNpjXAdGrnV6WWyPMRb1iHSR3VY3IL507hcddacPW7XR7XnqTWsMlpvLXcRCVPaUF9RgbK1o/Xfrq7Pireqw/6OuEYM+KJJv68YemBl89xeuxqaJu9xETKldfO8lutISCAOKsTmlNW6ct5QAbug5XGxSts3qfkw5d/cbNtpMsVOvYbuuYbYmzIuqT3ObgW8dpXzugqhI44hsSaPk8qk/QDQ56o2WbL29X0hISY1rgVl0PKVUNij6g+rWq5oPTN4j1gV/Chux+GuM8O4zbsw+4V6eI0dXNcHQixah0T9lWNN4IEQ06rILHXrEWtVsHrTm/QbD/EKPP57WRsgtlIeeJ17elRCTaiEKGNvPx8ZIaYC5lSo4R2uS+ZSxM3xVmM53GCO1UXaGE/UY9r4jvZMxc7xG5iexp1ouPt1YuLdKXuOv17Txn28nrS/Nzpho7ZzNTQj6avQWemUt53nXeVlhFCbVRCfKy6bvlmPaS/XprIJMzbbGynvCIfPNdsLKoji53oa33SKGFtvlTnIX/u6bccRbsgf0aGTG3ovSMTdYdY+djQkQjt5G7fv+Nl0YvE4fEFnTeyRlo3LrAcUYhXwow4j47+5XGdtHoZJcfYLs0eIca+L+gM82jwQYlo1m6WWQkwr2PUujQlbsU/pk8NeN82sx/NNj4uWigofMD4wCkLM/Q5VqG5RweGazCOof6ytQ+eYxrvrAY822IOetFh4c47/tzzjFlNLHeEThLXnhNer8+7zg6FeNs/tdS/xpDPXdvIWTifYDuLrFpdh3W0Ew/Ee76R1K3/aMHPzrluyPvLLo+Va1p7E9X4e6KWIm2jPYIyXwxeC97tiYTt+EDA1nF1cgzjCYc12O84q+VF+11lQPnONFWO/KM909tFwST/jOEzq6wMIMa1qzVJXIWZuJLPaaLGiK7HWY8HT3bQbWX/780uvvhcelSq27ccHqi7Eku9OuesM1/DlZCM4dq6j8a0fdO4txPQ8nSE9UfcdWYzF32mwu/fPuOpP7Y1qC6GoH7samrbODd6zcqfTbvQH8aXFlYV1t5knj+swRisw0tZzjjK7Z9PsHVdaGmb/nGOIYnT2yFj8Dl8I/CcWtmPXgKlJ08U1iCMc1mxrnBXyoyy2N3nOdp355etwSuOXvr+3/aI809lHw/VTNxIWdqPuAwgxo8J0qbMQW9dx87YxEF8HY//TK9vWzaiPyjq/9KhgRr2CIf/5+HClhZg2prPOtnrWMVFQshEcq4scje8sQixtooc1x3C+bnVcWi//eiueqH1dDU1T50ZnHoyVL1K3BvE548rKWvN22CFC271a3dJvHwsPVbP3jLnW+3dB/trXdu+4urF1zbZbtR6xyvhRVturP2W7zowti7Zf1F9cPt2+/qPhuG/Ao0k+gBBrybAaC7GUp3n25mrW2Z7UZqywc02PyqhJlRFlTff3Kgux3u/oBHVHekPMhLHlD8K3GooDCjHXsELTo9B341N7kCLvefkCZ6k1DM/mub12lc+8z5NlGGU7X0F8rrj6Ye0UOcoyS/nX5pMP7yZb72IF+WvbK1t8aWm6BF/VhFhV/Kgf2zt9Z9baKmxDu2+wdW/7hdPiHbGgjotyYX+zeSDEai7EllLekQgLMdNQyPTie4anZ/mm1+yLk8oZ+1sfqLQQ6zTwMjTmXO+J6TC49keYrb1j8QwoxBYck0EE73bF0uhRt804JrBwDdVzNoB7TiYRzotl0K3RGg6fvu0UYso/TRSF9+/o+2CRe4SKT3fPRbb4zGyJZkZKMymJ/TOzKR533J+qJsQq40e5X2fG14q2X+DPpi5zXh+tckXD2XqPNVya4AMIsRoLsbSXruM3WPN70AZKuCLPPz0qoSZUQpSxt5/XRoi5RJUOuWr3GFkOscah65wM74i53l9pi6dY/Bkaoy5Rk1mI9dOA7vQKdmu0Zsu/K89tkdP7/OwNZndcZ9fFOzavwyP1IV986n7X/Se8r2pCbCT9yHXNJK4zc70VbT97TbfX2f0qeh73CHjU2QcQYjUWYq4bsWhlPOV4EdvcCIedtCP/9Kh86lz5ULbs/l1rIdYRVZZHrHHoalR2zomFDTUsXfXRoELMNXnF/JpJ2+a5vU5vaKbnM9oYDuIbNi5X+YsWYpvak3Y45f4SFlvdtqsmxFwcK+9HXa+ZwMeivqe9lbnbL5xWt4cL0XDx64rf8KmzDyDEairENlO+JXNM33fYdQw7MTfGYBrprI2GIFwx6VH51LnyoWzZ/RshFhsqV7IQO6L1Y1w8zGk9GvfhYcVTOL5h43IJiCKF2JL2/MUZDfK7zkKsND8aQIgVY79oHZfu09Fw4euAbdjU3QcQYnUUYjpjlmva5rHpQDgd1SEjrpvkQB92Liw9KqC6V0CUL5uPI8Ri9VXJQswlahiaaHy3fU9Z029Ruu4ndt+UTvc/q+/KHdUZfBf8v2PH9OPRjvtQnYVYaX7UpxArzn7R+g0hFuXB/Q8exgcQYjUUYispTybb32dp3zjN+1yumcAGmVWsuPS4SKmo8QHjAwixWEM/gxBzvdvT7sUKHkhZIdFrnR5X1D/TG5pZ0wziGzYuV6O/kB4xnYBj3NFjaETYgk553+3D067ZGasmxNJtn9WmQbj0uAK7m+t9WNt3/wh6OC3NW6H2C6fVrVzRcNz34NEkH0CI1U2IpUy1PKkvTscbG66PPpqb59HWuw/J8PHzW78LTY/KqEmVEWVN93eEWP9CbFGnqrc9MnY90PDrLZ0x0CE0oh8ebttu6AZ06J2zYeMqS4i5xJThvaa9Ms57Rug9vt7Tn8ficPT0BN+hi4XtpBO+rvr/oPNI+pGDU/DtvSiPYu0XTgshxj0u6g/waPNAiNVMiKUNOTzVuSmFblYpDQxTYbenkw6FdZ2v+4pNj4uWigofMD6AEIuJqgw9Ys4GZh91mxURzvdfdTr79keso/45rHgKX+/DxlWWEHOlM7PU+95h+I6CEBtJP+pDiBVrv6zXRzRc+DpgGzZ19wGEWI2E2NnlWGPFf4o7rRN32EZFfO28yeh5RxbTz7FxFJ8eFVDdKyDKl83HEWKxui2DEHMJGdNTYyYssnVYlvW84z2mcf3+VfvcqP1cafbusbFxmXUQ37BxuRrYRQxNdA23W8zIOA8hZmYC7v7B7ICpsVl3ruGwZtsdvvJ+1IcQK9Z+UZ7p7KPhwtcB27Cpuw8gxLSqNcuZM2c6w1gMlPwMH77JJrddN6LeN26bv2h8rhmZsvRuHfYFmx2+Y9e9hpYUn54tJ+v8/BGWo8gSIda/EPNSJhES/dBz1g/Yb2rPjq0Pw+uFU7bujV5P6Q1NG77XOohv2Lj2U4hlGd6+q2Jt0nHv6fcdMXOPa/dOprENmKYJq+CeGw5rtjXOUfSjIYVYfvaL8kz36Wi4UayjyTM2HNQHEGJGhelSKSGms0u1bgDmJuD8sw4fHF+ddzcY2t+6CcK54nMOvdEb5HiXD5GWk54tJ+tBL3DOq4fvIMRi9VuGHjFT1y2nTFwUNLzT68atNfeERtEemKh/pTc009OJ1slBfMPGVZYQc71DNdHpMXSXe0eFrOu9OyN2uwqxlOH03Xs5A6aGdXeu4bBmu53/kfOjPoRYsfaL8kxnHw3HfQseTfIBhJhWtWYpUoht6axEG/r0b1PXkb+zOkzG8UK5mblwU49thMPr+SaO9gxU9iL1b3IazjlrlU4Z3G3GKnuTMetZbdiEn/jabecNrrT0bDlZN6lSoqxJf0eIxeqnjELM03rUWTdqg39Me8aWVRDE68gdPef4fCy9UM9NtLcgaqv0hqZbkITr4PZ2EN+wcZUlxFyjOsz9Y1qnp0+WT4WWTl9v7y+udVchpr1TzhEcYxqv3pdseptq1wV9oHlcxXS0PhlMiI2cH/UhxIq1X+DPxg7pPh0NF7UZx+BRbx9AiGk1bZaihNhZnb7XdbMZdN+kNhCCi7J941nQBoUrvuOhG5O9QaWtd/SG5YpDJpPDeMpLr94XX2BHygmL7j6AEIvVT1mFmD5k6vWNJNFG/KTWoYf1wdVEygMpWze269+gwR/32/SGZvicbtuBHwwbV1lCrNv052bY4NxR8RYXxZufSRfFlq9ZdxVias9ljSccPrw9oe+LhT/L0n6XL2Bq7n/duYbDmu3AViPlR30IsWLtF+WZzj4aLn5d8Rs+dfYBhJhRYboUJcTSvrEVvnn0sz3RGrZoL0qd3TBF6LXDBTeR8A0lbftYiqCb0UlA7DnlpmfLybrOlRBl6+3fCLFY47sPIWbqrmWtN/upZ11hp5xDxqO2S29oBnWorUvd6yC+YeMqTYgp37Sh6i6Ovfb1EmLmG5i94rDH258rCJga5t25hsOa7ajdRsaP+hFihdovyjOdfTQc9wR4NMkHEGJGhelSlBBL6/a3N4p+1+13G+xFqk8Z9QmgK441HcIRv4n0/K1DH8NPEzvxhho95aZny8m6SZUSZU36e1FCbM7RAzSrD3fSbLDlePCT5X2rTt3jesdH89D+XIYtd6zu6npOLGys4dxJV/evaa9Mp04LDTXMsm8udTp2m+f2emg+4VkTh2Ttmg2v/e2z3sxcDeb2O8PR8ob5LnbpqXIxnphWUaS2nYrZIvp9NndeV+az2dLZI9aVa3r5bFlHwo+6XjPhMgZ8i7FfOC0dmpjKPhourf5hP5zq6AMIMaPCdClKiJmXktPeUXDdnHrta09Fby9GFWI6dDB+TtZvuNgbS3i94npyrGnY6YHLTc+Wk3UdKx/KlN2vixJirkkI2jMCpuRNhzvHJ1mY0kZxuA7puq1P6uPv+JjGsvPdVyuqHO8FjekwwqwzH0byow3UY1rHTehwxHi9mfitAnFW32fa1DxH4rD5aq1jnIblExJiZsjYMKyPKaN4mXrNhGvL6RqqHr332HJH2WxoQ/twysNBm5dxvZ+0393Sc5VtXIittni747f5M+t1Fcdd7ag2XtKHi9F6Rn935WrTteto+TrpV92PMl1npozR8uVvP8vRX6eyj4ULXwdsx3wYVtFrevR51EGIXaBeam44Qy3r6+ty7bXXtuJQKHLw4FDRlXTyXiud7W2R8+fbSV52QOTSi4ZL/vw5ke0dPw6N64DGGY6yvPQuHK4gnA2BmhB46SVPbrvtp3LJJSLnzuV1XbTrj/D1HtQfaWnoOVrXtOoAZXuRXz/0i9nWIdHzbZrtfMXjdJ8TD5X99/bbIuvfE/lHXf/wJ+3zLr5Y5IqrRX7hgyJXXZElLptnG3ZYPuH4ho1LfUXvDTvm3uCox22OU9fGznofMPeWiy7T+8ClJmQ4f+a321bn3lG2Z0TesmwN1ytF/usPiVyp95PIYtIx9zDdmfQ/d/zh8995S+TMP4j84Ee6990i732vbz9Nr72E8+zHF0rT7YP23N7pV9OP2vl3XzMOHra4/jo/+8UiNv7iZB/OU/wcfkOg3gRUfqj+aNc12imk+uPgyBW4wUJs5GxFhiEAgQEIFCPEBsgIp0AAAhCAAAQgkBsBhJiPcjR7xHLzAyKCAAQqTAAhVmHjkDUIQAACEIDAgAQQYj44hNiAHsRpEIBA4QQQYoUjJgEIQAACEIBA6QQQYj5yhFjpvkeCEIBARgIIsYygCAYBCEAAAhAYIQIIMd9YCLER8lqyCoGGEUCINczgFBcCEIAABBpBACHmmxkh1gh/p5AQGEkCCLGRNBuZhgAEIAABCHQlgBDz8SDEuvoJByEAgX0kgBDbR/gkDQEIQAACECiIAELMB4sQK8jDiBYCEBiaAEJsaIREAAEIQAACEKgcAYSYbxKEWOV8kwxBAAI+AYQYrgABCEAAAhCoHwGEmG9ThFj9nJsSQaAuBBBidbEk5YAABCAAAQgEBBBiPguEWOAUbEEAAtUigBCrlj3IDQQgAAEIQCAPAggxnyJCLA93Ig4IQKAIAgixIqgSJwQgAAEIQGB/CSDEfP4Isf11RFKHAATSCSDE0tlwBAIQgAAEIDCqBBBivuUQYqPqwuQbAvUngBCrv40pIQQgAAEINI8AQsy3OUKsec5PiSEwKgQQYqNiKfIJAQhAAAIQyE4AIeazQohldxpCQgAC5RJAiJXLm9QgAAEIQAACZRBAiPmUEWJluBtpQAACgxBAiA1CjXMgAAEIQAAC1SaAEPPtgxCrtqOSOwg0mQBCrMnWp+wQgAAEIFBXAggx37IIsbq6OOWCwOgTQIiNvg0pAQQgAAEIQCBOACHmE0GIxV2D3xCAQFUIIMSqYgnyAQEIQAACEMiPAELMZ4kQy8+piAkCEMiXAEIsX57EBgEIQAACEKgCAYSYbwWEWBXckTxAAAIuAggxFxX2QQACEIAABEabAELMtx9CbLQdmdxDoM4EEGJ1ti5lgwAEIACBphJAiPmWR4g19RKg3BCoPgGEWPVtRA4hAAEIQAAC/RJAiPnEEGL9ug7hIQCBsgggxMoiTToQgAAEIACB8gggxHzWCLHynI6UIACB/gggxPrjRWgIQAACEIDAKBBAiPlWQoiNgruSRwg0kwBCrJl2p9QQgAAEIFBvAggx374IsXo7OqWDwCgTQIiNsvXIOwQgAAEIQMBNACHmc0GIuR2EvRCAwP4TQIjtvw3IAQQgAAEIQCBvAggxnyhCLG/XIj4IQCAvAgixvEgSDwQgAAEIQKA6BBBivi0QYtVxSnICAQhECSDEojz4BQEIQAACEKgDAYSYb0WEWB3cmTJAoJ4EEGL1tCulggAEIACBZhNAiPn2R4g1+0Kg9BCoMgGEWJWtQ94gAAEIQAACgxFAiPncEGKDORBnQQACxRNAiBXPmBQgAAEIQAACZRNAiPnEEWJlux7pQQACWQkgxLKSIhwEIAABCEBgdAggxHxbIcRGx2nJKQSaRgAh1jSLU14IQAACEGgCAYSYb2WEWBPcnTJCYDQJIMRG027kGgIQgAAEINCNAELMp4MQ6+YmHIMABPaTAEJsP+mTNgQgAAEIQKAYAggxnytCrBgHI1YIQGB4Agix4RkSAwQgAAEIQKBqBBBivkUQYlVzTfIDAQhYAggxS4I1BCAAAQhAoD4EEGK+LRFi9XFqSgKBuhFAiNXNopQHAhCAAAQgIIIQ870AIcblAAEIVJUAQqyqliFfEIAABCAAgcEJIMR8dqdPn5brr7++9etb37pQrr56cKicCQEIQCBPAq++6sn99/9ULr5Y5O/+7sI8oyYuCEAAAhCAAAT2icDGhsiv//peK/VTp07Jddddt085GTzZCzxdBj+9fearr74qt9xyy7DRcD4EIAABCEAAAhCAAAQgAIG+CJw4cUJuvvnmvs6pQmCEWBWsQB4gAAEIQAACEIAABCAAgYEINFqIhYcm/vVfXygf/OBADDkJAhCAQO4ElpY8ueee9tDE06cZmpg7YCKEAAQgAAEI7AOB731P5Fd+haGJOmvJulx77bUtE5w5c6EcPLgP1iBJCEAAAg4CTNbhgMIuCEAAAhCAwIgTYLIO34AIsRH3ZLIPgRoTQIjV2LgUDQIQgAAEGksAIeabHiHW2GuAgkOg8gQQYpU3ERmEAAQgAAEI9E0AIeYjQ4j17TucAAEIlEQAIVYSaJKBAAQgAAEIlEgAIebDRoiV6HUkBQEI9EUAIdYXLgJDAAIQgAAERoIAQsw3E0JsJPyVTEKgkQQQYo00O4WGAAQgAIGaE0CI+QZGiNXc0ykeBEaYAEJshI1H1iEAAQhAAAIpBBBiPhiEWIqHsBsCENh3AgixfTcBGYAABCAAAQjkTgAh5iNFiOXuW0QIAQjkRAAhlhNIooEABCAAAQhUiABCzDcGQqxCXklWIACBCAGEWAQHPyAAAQhAAAK1IIAQ882IEKuFP1MICNSSAEKslmalUBCAAAQg0HACCDHfARBiDb8SKD4EKkwAIVZh45A1CEAAAhCAwIAEEGI+OITYgB7EaRCAQOEEEGKFIyYBCEAAAhCAQOkEEGI+coRY6b5HghCAQEYCCLGMoAgGAQhAAAIQGCECCDHfWAixEfJasgqBhhFAiDXM4BQXAhCAAAQaQQAh5psZIdYIf6eQEBhJAgixkTQbmYYABCAAAQh0JYAQ8/EgxLr6CQchAIF9JIAQ20f4JA0BCEAAAhAoiABCzAeLECvIw4gWAhAYmgBCbGiERAABCEAAAhCoHAGEmG8ShFjlfJMMQQACPgGEGK4AAQhAAAIQqB8BhJhvU4RY/ZybEkGgLgQQYnWxJOWAAAQgAAEIBAQQYj6L/IXYXkDZtXVeZHtbZGfXP/hukcsPiFx6kStwfN+F8R38hgAEakwgXyHWo24yHGP102WXi1x2qUjv6om6qcZuSNEgAAEIQCBnAggxH2gZQuydN0VOvCLy/HMiTxxzW3J8UuS3JkRuv03kGhVm7oXGjpsLeyFQTwJlCLFz74h8a1Hkz/639PppQuunT9wh8i9+XeSGq1ysqZtcVNgHAQhAAAIQcBFAiPlUihRib50U+fdfEvl6ivhyGcbsm14QefSzrqM0dlxU2AeBuhIoWoh986siE4/0R29MRdn8H4gcujJ8HnVTmAbbEIAABCAAgW4EEGI+naKE2LNfFLnrK91M0P3Y+BGRY18WiXaO0djpTo2jEKgXgcKEmPaCPfx+fUg0BK61He0d02GL7YW6yZJgDQEIQAACEOhFACHmEypCiJ1+RuT6e3qZoPfxyXmRp+4Lh6OxE6bBNgTqTqAoIfbVj4g8sjocveUtkY91nhRRNw1Hk7MhAAEIQKBJBBBivrWLEGKvPy4y9mDSncb0HbDfuVPkn10n8t6LRf5hTeTpr2nPV5cG0dJZkVuusHHR2LEkWEOgCQSKEGJv6IOiD6c8KDo8K3LvvxD54AdEdB4h2doU+ZtlkQWtp56O1VMrKsQOIcSa4IaUEQIQgAAEciaAEPOBliHEJqdFvvA5kRudL7nrRB4q3G51CDeTxQltGD33kLU+QsySYA2BJhDIXYjprIgPq8JKDEkcE1n5y/h7X1HCb+o7r1//t/qnEw+ZhR6xNgf+QwACEIAABPolgBDziRUhxE4/q0MT79IExkWWdHjhLdf0Ns9r3xD5+Ocd4TSOrZftu2IIMQchdkGgtgTyFmLn3tDp6D+cxHVsXeQzGeopc+brWh/91fdF7r7b1ktmL3WTocACAQhAAAIQyEIAIeZTKkKImajfekvkSu0B6/39HT8j53RI0GU6/Mf/GV6t6zfHrmlFRGMnzIVtCNSdQN5CrPOQKAxOZ0HceUq/ZRje1/c2dVPfyDgBAhCAAAQaSwAh5pu+KCE2iGe9rFPdf/Kx5JnBECAaO0k67IFAfQnkLcRc769OzOnw5weGZbhfdVOGj1SboumQzHM6y6M+02q9/Nb9I9WmLEXFazKQMW4Nub2tWde8m+UifRh3mb6T1/vhXtgW3dM6rw8Ad5SLSeIifRDYm4vJSRFxmnhZIAABCDSHAELMt3WVhJirkWSyGbwUb2+we3Jahwf94Z+I/JP12feI/PN7RT57yO7ovn7jBZHH/yw4/z1XixzWKfdNz1txcdv8d88bRyEAgTaBMoSY5N0j9s6efOPfi/zd/+tbUeum3/o9/SD0dRmtquLgSf2+2V9vBOE/ped/5kZX/ZEuCrZ1VMIrL4k8/5z7Q9XmI9V36BDyT+vw76s6k46YNE06RcVr4k+PW7Tsr2mej+m3JL/ytAmbXCYP66dRfkNHvt8SHhoaDhfmlEzrnTc1fr13PKf3gGOvhM9rb09MKZd/LnL7bXo/SHAxYYqIM5kP9kAAAhCoMwGEmG/dURBiyR6xPXlGZ1+8x/Gh6CBsuvumvSdizy0u7nADIT1/HIEABNoE8hZibzypMyben6S7qr0iNw41NjG4trdP7snlN0XTGJ8RefkL0X1pv7Z1UhD3+UEawblJUWDEzJP6Hcb7EzOSBGfFt47Mizx6nx2eadIpKl6TsiNu3fvaM/qe8D3mePZlYVUfvt0YDx/mFE3rWR11cZdj1EU8Bvt7ZlEnmrrd/rLxFhGnTYM1BCAAgWYQQIj5dq6SEHMOTdSntZva+3VlK7/BjTBNTI3p09IVnWq62/AV1zeExqe1ofRoG0pxcdv8N+Mio5QQGJZA3kLs3Os6/ExnSEws2jt09imRzpcyEgF67Qiu7e3XVYjF0ojO/to9rm3No/v8II0ghqgoOK+9YPdr735KZ1JwmmtL684drTsvdfSI5RevSTiaZ7Pn8XtFHhwo0yLT+kDu0c+YWOwS5hSk9dVP6LfjHD1g9iznWu149m+sX9h4i4jTmTo7IQABCNSWAELMN22VhNgXL9DhKHGX0wbS1lN2CEr0RnhCh+/c+kj8BJG5FZEHUoYopn1DaE1fnrghpN6KidvmP5ln9kAAAkkCeQsx8zLQAzp9/RPJpMQMUTz1RyLXRYajuQK69gXX9r4JsXdE7ny/DrdzZS/jvkUdDnn7VaYsgdiQXOM1GQnFrb8e19END3bJtBlC+QEN90QXoTZzXHuuVGi1l8AWNq3UWXn1hPEJkavV5hta9lccQs2OlAhmxmznP984bd5ZQwACEGgGgToIMfFyWM6cOeOpyVt/Z85cqDEO+2ey1f/f7no7DzYvdj11NByXzZu/b1c8Hc7fyb89R8bE23DlYVM87WBLhJ9ZCqdRZNw2/6yH9zMYNoHhiy++q3W9XnKJuS6HtXn72l6dT9YBnbpD64fZY+LtuOqPrvuCvG2tJuPXHrHM9WL6+UEaAYsg3qOTyXRtuY4eF+/slpZrR9daD67o78MTyfAzy5ZzUfGaMgRxLysXm8fwemxKvGW9J+yGwnpa3y/r/SAcLrytw0v9uMOcdN+GeNqxlThvak68zc457XN3zoq3tCCearNO+OBeYuMtIk4bN+vAt2EBC3ygzj5gNIetw40WGcXF3DmGXqoixJamgxufNYxZH9ObcXDjthdlsG9TRVQ4vN2enA/C2PMX9OZuj3fWui+t0ZV/3Db/rOtcuVC2/Py7CCFm6oNpfVjTqQNCje7wPiPIzmrj39Yf3ddBmdOFVLa40s8P0gh8rB2n65xWWVScbXQpw7rWn+GHUwunTHwmnaLiDeL2VBC6BNKkCiSbvmu9o/eEsFCyNptSAdUOH+Yk3tZK0tb6zl7XNIzoW1LRN6c+EOTBxltEnDZu1oFvwwIW+ECdfQAhprcXs1RCiKU8sRR9YrsVfiLaeSIevjmK5xRY2rg6rjd6exNNE1VL+gTUhnGt842bSqXOlQply9+/ixJiRgToiLeeYsw08qf1oc5mFzHTrjeCsrtEUdE9Ys56ajxlZECkTtX6T3vKZs1DKg2v32zU+tCUpV0v5h9vELerN0zf8Y32gsXz6v/e0p47K8A6axXXm63jgS1MOVw9oAsq5mwZs69tvEXEaeNmTT2KD+ADzfABhJjehsxSBSHmvNlrA2h+LX6ztM4Z269iKvxUt3Njtr1d2rjQ99ATN+7gCWosvvDNP9e4bf5ZU9HiA1l8oDAhZq5xFSDTKj469YWjjggfm9Eel7PhuiGyHdizdCGmotJV/yXrzy71XKIsGraQeA0njVvrZNew8sXQw7NeAmnGYbugR8/aQ4dhOoY/DsamyDht3Kyz1AuEwU/wgdH3gToIsQuMkNKGwlDLfk/W8fYJfRH7VkcRVDntfi0++6F9CTv6src5+/SzItfrN3Hiy6xO3HHzt0VuejB2RFsuwWyMsWOxn/nFbfMfS4CfEICAk0Duk3U4Ujn5TZF/q2PdXnEcc+06tqbf9LohfiS4tsuerMNZh+qYv02d7a8922w8r71+m7LsSTHxmrT3xDUzbZYZb8M5d3130tT3Dx0KbJFWDpPWq3p/6W9eFhuvm81wcYZLxjYEIACB+hOow2Qdoy/E3kmf5SuYqSrsjMGNMLzXbn9DZ836fMbWlD45lc9eZ8/svc4nbpv/3ukRAgIQEClDiLU4n9fPV+isfA/fL6Kfpuq5TOv3pR7tfF/KBA+u7bKF2Mlv6IOmz0ezPDkv8tR90X3Zf5my7Ekx8Zpc7Ilr9lodoSCPfzZ7Lt95TeT9H4+Gn11WIfaxwBYt0dflkwVryu6GK6JxpP+y8aqQzD3O9FQ5AgEIQKCOBBBivlX3s0cs7bsuOouhfOEWl9sFN0LX0XOn9RtB17uORPeNz2qj66Hovl6/8onb5r9XahyHAAQMgdKEmMWtH0M+8Z9EHtPe9V7PdNqNfnticG2XLcSevFO/HRab/n1O1eQDN9q89bs2ZdmTYuI1edmT1/TTIx+PfXpkQj96/eivifzoJxnye7GOmNCeyU+qcA4v7e+1BbYwaZml24O0KU33935LP+h9TTgm17aNt4g4XemxDwIQgEB9CSDEfNvulxD75hdFJr6SdLDuHz6N3giTZ4vzBh8Pd0q/GXZd6Jth8eNpv12Nh3jY7nHb/MfP4jcEIOAiULoQC2Xi9Re0h/2O7oIs+P5gcG1XQYi1h+iFCtPXpimLW4gNH6/JyF7Pb4f1ld1Q4DQhdv5N7TU82KO3U4enHtUHdJ/WkRXuIYvWxm0hlm+coUKwCQEIQKABBBBivpH3Q4i99rg+DY2/s2Xyo9OYBR9vdnlh9EboCmE+2PqwfrD1686DIke0t+3Lt6Qc7LV76Lht/nslxHEIQMAQ2E8h1rKAXvPPflnkrsfc9pg8qkMA7zbHgmu7CkLsqPYW3Z14j81dhuReUxa3EBs+XpOaO+5kPvrfkybETEzbb+jDvw93F9Y2RZ2YRf4HHSYZFWTWxm0hlm+cNmXWEIAABJpBACHm27lsIeZ6N6CVFX25fH1F5JquPVXJG2HCXXVo0QOXiTyRONDeMdS7E0PHbfOfkjl2QwACEQL7LsT83Jx8UntUYsPgWofGRc6+LHJFxYSYfpZDbsn87lMEuf5IF2LDx2vSKk6ItYdkhuvZQDS1Sql1+LN6c7gr9k5d61j8n96TVr+lQxY7HG28RcQZT5zfEIAABOpNACHm27dMIXb6mzqzoQ7/cC0rWyKHoo8fHcFSboShkC/rkMdPOoY8hoLI4obI7VeF92TbHj5um/9s6REKAk0nUBUhZuzwzYe1R8XR1d6eWCi4tqvQIxZ9f61fLzJlcYul4eM1eXEPTdQPOcvv6zti/6RDxwdZ3vOzOuS8Va8HtjBpOZdtfU/4z/XdsXtEYq/XJYIHw81tvEXEmUiWHRCAAARqTQAh5pu3LCH2lj41vvqTbp86rsLoE5mEUfcb4bbOZHW5PsXsufQcApmMIZ+4bf6T8bMHAhBIEqiSENs+qfXLTck8th8iBdd22ULscZ2s48GYmpjT0QUPHErmNdseUxa3WBo+XpMDt8gbboKRcMkCW6QKsVDwN/W+8Sd/KPLIE6Gdoc1xnczj5S+YHTbeFCEWOqf/OEMnswkBCECgAQQQYr6RyxBib7+m3wr7uNurFte1d6rnbFX23O43wi9eINKjM8xGJEcW9V2xyPTTnUPOjXzitvl3JsFOCEAgRqBKQuz8Wzo88erkhA+rOzp87dLg2i5biD37gA61i4mI6eM6A6FOOjHYYsqyJ8XEa3K0J65vgA01bDxS0MAWWYSYPfVtFWRT+iAvpmlbh9fUxjd0bNxbiPUfpz2DNQQgAIFmEECI+XYuWoi9oze396f0Uh07pR9Gva4fh7M32OSN0PXNG9F0t/5G5E/1iXF8emeTarsB1Tv9/OK2+e+dJiEgAIEKTNYRMoLrI8TmcGJo4sm9RM9Z0KsSijBl09XzlpyEwp7sFjVm4qOdp0QutcH6Wpt6qqh4TUb25E0dpn4wPkx9SvOsEzkNludwAcP1bPJeEQ6Z2FaxfaeK7bgYi9q4iDgTOWEHBCAAgVoTQIj55i1SiJmGy8d0lqpVhyst6Kxen+17Vi97g43eCM00wu8+mExkXtO4T9NIOz52RORvdEa0bkvauYPFbfPfLUWOQQAClkCVesTeekGHV99hcxas2+8QBdf2udN7zu8ZbngiPUdgn9NZXy9LzvraTYi5Pmxscjf4xBqmLHtSTLwmZ3ty/rTW2Y5vPi6f1XvGFSbMMEtgC5NWv8sLD4vcEXsXMNrrWUSc/eaS8BCAAARGm0AdhJh4OSxnzpzR5oG0/s6cuVBjHPbPZEu83XXxdEKxTtw2DbOeX22HMeH6+7N5i543O55MR0VWJO7l2WQYkxd9LyESLp6ffOO2+Wc9vJ/BsAkMX3zxXa065JJLzHU6pM23xDsyId7UtHindDt+rXf9vSOedjIl6rOxwzaeUN40rHb2JML2qmu8XfGmx5LnmXpKhVhK+XW/lsWVnvbCZS7j0rx4Y5q2CiE/naLiNZza+XKVtV3O7Pm2cUXXIVv0fY8Rb1HvHeH7ldnWHrEQ//7z1zvOcJ7ZHvpaH7au4PyQv+OP+GMxPmA0h61rjRYZxcXcDYZeChFim+6GgQE+uAhz3whPHU3eNE06+gK9sgn9aSNHR750jG6Nr8MXPX1SHQ3r/84/7mKcmUoCrnX1gTyF2NZK9Pqf1rpjU0VTpJ5w1QVal8w4HvaYOkQ/cOyfH/bBFEGldc26K36zT+vMw3q8Uy/F6qquQkzPdzX0TVxHjtn8ude7KrxmVJzadGeWTThTlnb4/OMN4l5LqbuPLLjzavMUX+8ou+Ulrcc7tozaYl7F8qT+rWi4+LmJ32prl+DWHjGfSzv/+ccZzjPbda3PKBe+jQ8EPoAQ09uKWYoQYq5epNaNXm/4y9pwWdKbZj9/xzX82VbDwBrQv6HqjdXV63Y45Ua+eTxocNiGh1lPzjtu0IXEbfPPmsoIH8jiA7kKsVX39W96yI5rvbSpjfBdX4CY3qmzGypwtG7QV007QiVcb+h7WN6WDR95gi7emp4XCWvjUEG3vB6qbzSdFRVLqWn45/USYjunUtLT8ye1fGtalrDo2NL67dhc8pwFjadtl3b4/OM1fu/nRcWNS/QYbhMmz12E067aalXvC9NTQRkmlHk77tC1peHCvYVTM3pejIXNjxF002qfhN10X9vOfrxFxBnxn1D+2e/7I0yy1JeEwU9GyQfqIMQu0BrK3DSGWvJ+R+z8m3ty00H3e2HDZHTyqMhTd9ux/+0x+s/cK3LP07FYVZlt6lT5V8Z2259P6jn3x8/Rg/FvixUTt82/zQ1rCECgG4E83xHbdkyi4Upbh+jJquvF1ljgpU39aHKnoglf21o/vaOf5Hi/yCuxczo/NY2Ja3VSiPisEJ0AuqFh7Au2KsTkuYfCadiA7brQ/Hrhi/pu01fsfsfaT3PrjOYrpXzaIyZf+JhJp6h4Tb6CuLt91qRVAq3PD/+6yLUf0F8/FvnB90VOah6POcC2GZmzQpzO7cmd+s5dArPGe+R2kV/8oAb/f/Rd4W/re3mO+4KJLZiy34+3iDhNQiwQgAAEGkSgDu+IVVKIZW3s9OtrUyrEHg8JsbQb+FGdoOPuG7rErrNifcQxBbXoY9Ot50TMN6WLizvUQOiSRQ5BAAJtAnkKMdEG9APaKI/N9D4Q6uRkQ+Fruy003nhG5MP6weB+lzkVGgf+WB8yhTKaRYiZdFzfFOsn/WCa9kAs5RuviS0a9+vPqua8q59cusNOzKlYfcAcC9kiTTS5o0jsjc522UOIJc5273DG6Q7KXghAAAK1JVAHIWbGYQy95D00cVeH3eiDV9NTl+vfePhl9ZT3veITdNghJ/H1isblyt+MDnUxQ5Jc75LlEjfDTNRfGToAg+w+kOfQxFY9oO9Ezen7Qq7rP8u+MR0Kt6ZD0+J1StSmwfFlx/C/buksrrXPnQu9t2XC9xqaGM7P0QHKN6bDLNeUTTseYx+7Hazzidcd94a+m6adVAPbxbzruxLJv/Ux3Z82TLRHelN6n9iJcCgyThs36+i1BA944AN19YE6DE00d8ihl7yFmLmBz+lNvVtjY5Bj7Uk+/Asy5d2C9gvVQcPB1Zho7VOx5XoXoPVuWZFxI0LUX6lUYZDdB3IXYn7DekvfE1pQkTShDfgs9ZGZ7OG4L5Lc9Uq4TNE6yIiMKde7RyEhMK1iof0ebPvchdC7TyZ/U3rc7TfRtGze1vWdtyMZ6uEJU67VeBymLPF97d/Dx5set3kItqTv9/ZiZe01pkyP6DtfS5r/zrt9rXwnbbG1rhNFTWd7SGhsHXmPr8PCxttmkW+cNm7Wbj+HC1zw6iAS3QAAQABJREFUgbr5QB2EWCWHJupNsoRFh7acF9ne0ZWu5SIdyqNjCnXV13JuWz8gas7X5SIdsnTg0vZ2cXGHhsz4SbGCAATSCeQ6NDE2JM6mek7f59rQ973e0mHLP/qhyE/0wMUXi7z3Cv3u1y/ot8OuyvKR4fC1HR16Z9PZflvku2dE3ta0bBpXf0jkQ9e549/W+snUb0HdFE7DxupOyx49r3G8ua5/GyI/NInq8j4t189pmQ5eo3Wes9I06RQVr8lB97hNCFM3b2iejU3eUZu0FrXJFe9t5/0DOrz8Cltf+4eDVZhTMq13NM7vfV/kH9UeYSZXKZOrU5mY2G28RcQZ5J4tCEAAAk0gUIehiQ0WYk1wUcoIAQjkK8TgCQEIQAACEIBAFQggxHwr5D1rYhWMSx4gAIF6EECI1cOOlAICEIAABCAQJoAQ82kgxMJuwTYEIFAlAgixKlmDvEAAAhCAAATyIYAQ8zkixPJxKGKBAATyJ4AQy58pMUIAAhCAAAT2mwBCzLcAQmy/XZH0IQCBNAIIsTQy7IcABCAAAQiMLgGEmG87hNjoOjE5h0DdCSDE6m5hygcBCEAAAk0kgBDzrY4Qa6L7U2YIjAYBhNho2IlcQgACEIAABPohgBDzaSHE+nEbwkIAAmUSQIiVSZu0IAABCEAAAuUQQIj5nBFi5TgcqUAAAv0TQIj1z4wzIAABCEAAAlUngBDzLYQQq7qrkj8INJcAQqy5tqfkEIAABCBQXwIIMd+2CLH6Ojklg8CoE0CIjboFyT8EIAABCEAgSQAh5jNBiCWdgz0QgEA1CCDEqmEHcgEBCEAAAhDIkwBCzKeJEMvTrYgLAhDIkwBCLE+axAUBCEAAAhCoBgGEmG8HhFg1HJJcQAACSQIIsSQT9kAAAhCAAARGnQBCzLcgQmzUXZn8Q6C+BBBi9bUtJYMABCAAgeYSQIj5tkeINfcioOQQqDoBhFjVLUT+IAABCEAAAv0TQIj5zBBi/TsPZ0AAAuUQQIiVw5lUIAABCEAAAmUSQIj5tBFiZbodaUEAAv0QQIj1Q4uwEIAABCAAgdEggBDz7YQQGw2HJZcQaCIBhFgTrU6ZIQABCECg7gQQYr6FEWJ1d3XKB4HRJYAQG13bkXMIQAACEIBAGgGEmE8GIZbmIuyHAAT2mwBCbL8tQPoQgAAEIACB/AkgxHymCLH8nYsYIQCBfAggxPLhSCwQgAAEIACBKhFAiPnWQIhVyS3JCwQgECaAEAvTYBsCEIAABCBQDwIIMd+OCLF6ODSlgEAdCSDE6mhVygQBCEAAAk0ngBDzPQAh1vRLgfJDoLoEEGLVtQ05gwAEIAABCAxKACHmk0OIDepCnAcBCBRNACFWNGHihwAEIAABCJRPACHmM0eIle98pAgBCGQjgBDLxolQEIAABCAAgVEigBDzrYUQGyW3Ja8QaBYBhFiz7E1pIQABCECgGQQQYr6dEWLNcHhKCYFRJIAQG0WrkWcIQAACEIBAdwIIMZ8PQqy7o3AUAhDYPwIIsf1jT8oQgAAEIACBogggxHyyCLGiXIx4IQCBYQkgxIYlyPkQgAAEIACB6hFAiPk2QYhVzznJEQQg0CaAEMMTIAABCEAAAvUjgBDzbYoQq59zUyII1IUAQqwulqQcEIAABCAAgYAAQsxngRALnIItCECgWgQQYtWyB7mBAAQgAAEI5EEAIeZTRIjl4U7EAQEIFEEAIVYEVeKEAAQgAAEI7C8BhJjPHyG2v45I6hCAQDoBhFg6G45AAAIQgAAERpUAQsy3HEJsVF2YfEOg/gQQYvW3MSWEAAQgAIHmEUCI+TZHiDXP+SkxBEaFAEJsVCxFPiEAAQhAAALZCSDEfFYIsexOQ0gIQKBcAgixcnmTGgQgAAEIQKAMAggxnzJCrAx3Iw0IQGAQAgixQahxDgQgAAEIQKDaBBBivn0QYtV2VHIHgSYTQIg12fqUHQIQgAAE6koAIeZbFiFWVxenXBAYfQIIsdG3ISWAAAQgAAEIxAkgxHwiCLG4a/AbAhCoCgGEWFUsQT4gAAEIQAAC+RFAiPksT548KTfddFPr16c/fYG89735QSYmCEAAAsMQ+P73Rb71LU/e9S6R3/zNC4aJinMhAAEIQAACEKgIgR/9SOTP/9xr5WZlZUUOHTpUkZxlz8YFni7Zg7tDvvrqq3LLLbe4D7IXAhCAAAQgAAEIQAACEIBAQQROnDghN998c0GxFxdtLkLsO9/5TkeF3n333XLgwIHickzMEIAABPog8L3vfU+ef/55ufDCC+Vzn/tcH2cSFAIQgAAEIACBqhLY3t6WZ555ppU9Mzrvox/9aFWzmpqvXIRY9B2xM3Lw4MHUBDkAAQhAoEwCL730ktx2221yySWXyLlz58pMmrQgAAEIQAACECiIQB30B0KsIOcgWghAoBoEEGLVsAO5gAAEIAABCORJACHm06wDiDwdg7ggAIHqEECIVccW5AQCEIAABCCQF4E66A96xPLyBuKBAAQqSQAhVkmzkCkIQAACEIDAUAQQYj6+OoAYyhM4GQIQqCwBhFhlTUPGIAABCEAAAgMTqIP+oEdsYPNzIgQgMAoEEGKjYCXyCAEIQAACEOiPAELM51UHEP2ZntAQgMCoEECIjYqlyCcEIAABCEAgO4E66A96xLLbm5AQgMAIEkCIjaDRyDIEIAABCECgBwGEmA+oDiB62JrDEIDAiBJAiI2o4cg2BCAAAQhAoAuBOugPesS6GJhDEIDA6BNAiI2+DSkBBCAAAQhAIE4AIeYTqQOIuHH5DQEI1IMAQqwedqQUEIAABCAAgTCBOugPesTCFmUbAhCoHQGEWO1MSoEgAAEIQAACghDznaAOIPBnCECgngQQYvW0K6WCAAQgAIFmE6iD/qBHrNk+TOkhUHsCCLHam5gCQgACEIBAAwkgxHyj1wFEA/2XIkOgEQQQYo0wM4WEAAQgAIGGEaiD/qBHrGFOS3Eh0DQCCLGmWZzyQgACEIBAEwggxHwr1wFEExyWMkKgiQQQYk20OmWGAAQgAIG6E6iD/qBHrO5eSvkg0HACCLGGOwDFhwAEIACBWhJAiPlmrQOIWnoohYIABAQhhhNAAAIQgAAE6kegDvqDHrH6+SUlggAEQgQQYiEYbEIAAhCAAARqQgAh5huyDiBq4pMUAwIQiBFAiMWA8BMCEIAABCBQAwJ10B+j2SN2/pxsb+/Izu5u243efZlcfuCAXHpRQV6l6b1zdkv81DSRd8tllx+QA0UkWGZaBeEiWghUiUAVhNj5c9uyvbMjtsoyfN592WVyQOutoqqtKtmAvEAAAhCAAATyJoAQ84mWAeKdN1+XE68syvPPvSBPHHvFacvxycPyWxOflttv+4Rcc8AZJPPO89tvydKLz8qfPP1canpj45Nyz39/j/yriV+X6664NHPc8YBlphVPm98QqDuBfRFi596W17+9LIuLz8sLzz8hr6ymUx6fnJLbP/kpuWP843LjNVemB+xy5K0TT8r0E8dlc3u7FeoD135Cfu/Rfy03XpFV5p2Xk8/+kTx+7GWNo53QgQ/8qjz8v/yPcujKrHF0ySCHIAABCEAAAjkTKEN/5JzlZHReDsuZM2c8jbn1Z7bzXDZWjnmHJ9px2zSyrKcXVgfMxpZ3fPZwpzxZ0jJhJmcWvbN9p1hmWn1njhMgUAsCL774Yut6vuSSSwovz+7ZNW9+erLv+qNTz4xNekeXTvWZzy1vbjxZR84sZ6+R1o6667zpPuLoM9MEhwAEIAABCAxFoEj9MVTG+jhZ+gibGrQYEGe9hSPjgzdoVByNHznmbaXm2nVgw5sdQPR1GlGTc96mK1rnvjLTcmaAnRBoBIGyhNja4sxQ9VWnHtG6a+zwvLexm9U8W968o96aXckmxLZW51PyPeWt9leBZs0w4SAAAQhAAAJDEyhGfwydrb4iqOw7YqefeUCuv+cJbZsMt0zOr8pT992YIZJteeaBy2XYJMeOLMrKl2/v8d5HmWllKDpBIFBjAsUPTTwvJ75xv9z6+afzpTg2LWuvPSo39Bz1vC1P3nm53H8smrwKMXno0BXRnfFf75yQO99/q8RObYWaX92S+24ccox3PD1+QwACEIAABHIiwNBEX/MVoUhX5yacT2nHJg57s/ML3vGlZW95eclbmJ/xJsaSw3LUxv75495ShgfDa0ennOmJjHnT84veqY2z3s7Ojre1temdWl3y5g6782fSnT6+0VUNl5lW14xwEAINIFBsj9iutzSTXheY+mBsYsqbO7rorayueesbG97G+rq3trriLS7M6bDrsZR6x6+/xqa9Uz17xgbtEdvwZhxDGk2ejxzrd3hkAxyJIkIAAhCAQKUIFKE/yi5gZYcmxoXY5PS8t7qRNk5mx1uaSxNS4k3MLnfnunncG+sINyvgdD0+7a2lJakxrh9PG4p0xFtPS7HMtNLywH4INIhAkULs1DH3u1WtB0GTM97yeu+nQFsbq/pgJ30Ytvaye9212CBCbNdbPOIWgeMzSw3yDooKAQhAAAKjSgAh5luuCBCnFnxhNX7EW1rvooZC3rM8m/Jkenyu67ti7vMmveUMya7NuwXg3Ir75DLTCqFhEwKNJVCYENta9iZcD3B038TsUg/xlDTHSkpdYkTdwno3Kda/EDu1kCIgJ492rSuTuWYPBCAAAQhAYH8IFKE/yi5JZXvEPG/H29jY7K8xs7PqTTobRtpDldqOWfeOOM45vJDapxWzkfv88RlXL5w7bDFpxbLJTwg0lEBRQmwl5cHP+PTx/uqtkF3ShjmOHTkeChXf7E+IpU7OkWkYZDxtfkMAAhCAAAT2hwBCzOdeJRDHp11DfCZSe7d2Th11vKNx2OvnDYm1ecd01WMziRkUy0xrfy4JUoVA9QgUIsR217wpxwMcGZ9NXPf9Edn0Zp3vbU16KZ3sGn0fQuzscsrDqglvKfuUr/0VidAQgAAEIACBAghUSX8MWrwK94gNVqTVOYcokonURoxr4oyx6f7ekdg9teAQc+Pe8VjDpsy0BqPHWRCoH4EihNjm8WnHNS/e/NrO0ADPLs864z6ymDYJUFYhlj45h86QOHS+iQACEIAABCBQJgGEmE+7SiDShJj7fa8d7+hkaHIO/wl3r1kPE06W8nR8NvIIu8y0EjlkBwQaSyB/IbbjLUwl6w3TG9Z7ao4MZtg95R129bYdPpYy5DGLEDOTc7hGC5gZErMOw86Qd4JAAAIQgAAESiJQJf0xaJFr1yPmHJqYNlxoZ8U5TOfoqX6fam95c44Pqk7OrwV2KTOtIFW2INB4ArkLsZQHL5HrfUjqx10zGjqGO7eT6S3E0ibn6Dmj7JDl4HQIQAACEIBAUQQQYj7Z6oBwT4YhaTOBqThKznqWPowx3ZHcU0FPzK4Ep5SZVpAqWxBoPIG8hdjuxjHn5y4W+n6Ak24a99DHtLqpuxDbWXO9B6s9elPMkJhuAY5AAAIQgEDVCVRHfwxOqlY9Yrvrrne1xJs6GuqZCrNyzbKoT53T3sQInxrfdg2JjAoxx4yORaUVzxy/IdBgAnkLMfc7XIe9tdSZWQeAr98bHHcMT5x3ftgwRYitas9+Sk+86AyJ6TPJDpBfToEABCAAAQiUTAAh5gOvCogl54yJ4h1LaXE4ZzGc6P7NsTQfi3+A2nz7JyzEykwrLY/sh0ATCeQtxFbmHN8rHLDeSLVHioCaXXG9heYWYvMra968Y8i06ORFy65oUjPDAQhAAAIQgED1CFRFfwxDpj49YhuLzuFC0qWBtLU6l5ydrMfHn9Ngu97BCAuxMtNKyyP7IdBEAnkLMVfvtwxYb6TawzmUWbx+hJh5GJT8G/OOOnvVUnPCAQhAAAIQgEAlCSDEfLPsP4iUWcy0IeIeytPOeJ7iaGdtPtno0caZffBcZlqVvFrIFAT2iUBZQsxe67kU0zVsWuuzuchMrDYld49YUoSJ1++nOWwKrCEAAQhAAAJVI7D/+mN4IrXoEdtcmkmKIPM0OHW65za4PMWR672RsSOLnemmy0xreLcgBgjUh0AZQizc+50PubPe7FiyR+uo8ztlXYRYIg7TI9bvrLD5lIhYIAABCEAAAnkSQIj5NPcVxNklx8yHpgEz6bm/HRa4QJ7iyBlXaFik8/iAw5mccYXSCkrIFgQgUIYQk4l5L9dPImuP2JRjaGH2oYlj3vTcjHPCDxGdWAQtxoUBAQhAAAIjTmBf9UdO7Ea8R2zDmxlPPjU2Q3JmljZ7InIKmgHFEe+I9cRNAAjsC4FShFhoGHIuhczhHTEzLHt9Yco9WmBqwUOL5WIpIoEABCAAgX0igBDzwe8PiB3vmOujpyrCsn6k1CnEBuxZ6jVrYplp7dP1QLIQqCSBUoTYgPVGKrAcZk2cbb1PtuUdnXQ/rEr9rEdqpjgAAQhAAAIQqA6B/dEf+ZZ/ZHvElucm3U960z7e7OC2c8rx3TH9vk4R3xErMy1HUdkFgcYSKEWIjc92JubJBbTzO2Lj3pJzRhD3O2KdYYxbK96kY5ijGTnA+2K5WItIIAABCEBgHwggxHzoZYNYO3rYLcL6/Uipc2Yy/cbOAC97uKa0Hp9dCdyyzLSCVNmCQOMJ5C3EtlZmHfVPvt/m2jw+7UjjsHfK+dHoHkJMPWBrxfGpjpY4m/LMd59ZIAABCEAAAqNGoGz9UQSfkesRO3XsiKOBYobeTHnOmZ27UXMO/xn3jvd+vSwWqzaEHMN/Iu+plZlWLHf8hECTCeQtxHbXjzm/WTiT21eSd73Fw2PJei51QpDeQszYfyVtFMHU0XwnGmmys1F2CEAAAhAojQBCzEddFoiN4ynT1MuEd3zD+ai4uzPokJ0Jx5Cd/htU6950Yppo8/HVUNdamWl1LzVHIdAoAnkLMW93zTmjYW7f6EqJf3J+NcVu2YSYp4Mn5yZ4XywFIrshAAEIQGDECJSlP4rEMjI9YpvLaUNrxr3F9QFEWIuquwHT9zeBNhYdT8gnY0N+ykyrSJchbgiMFoHchZjON7gw5RI0aUMH++O1ueQalijeQmo9565bOu+IhZNP/dyHeGaWRRYIQAACEIDAqBBAiPmWKhrE2dX55DCdVk/WuHfs1HAvOKzNOyb96HMGNNfU9aKThsRzVmZao3IRkU8IFE0gfyHmeRuL7iHSRxbXhyzOhrN3XbpOBtKHENPcbS6ljSzgfbEhjcfpEIAABCBQIoGi9UcZRal8j9jO2oKjt8k8jR7zFnJ4gruz5hJ5Y96xzEMd3Q2nwwunEvYrM61E4uyAQEMJFCHEPOfkO6ZeGuQdU2uYXe/49LjzodORxW5zufYnxExqSzPudMwDJPrFrD1YQwACEIBAlQkgxHzrFAVid33RG3e8w2WmXZ5fdc7j3L+/pLyPIRk/eLrunDwkpTFWZlr9k+AMCNSSQCFCTEmlihk57K0OoGZW5lM+vixHUmZLtObqX4hpn54343iv1dSt6e+i2fRYQwACEIAABPafQFH6o8ySVbdHbHPJOZGG6QmbH6SV04Vq2lPowwtrXc7SKaFXj7p761TEpb21VmZaXTPPQQg0hEBRQszT963SHhSJTHqLaxmnX91a944eSemhUmE03XMa10GEmBpf321Ny3/edWxDXI1iQgACEIBAiQTqIMQuMLz0KehQy/r6ulx77bWtOBSKHDx4cKj4RN6Rb3zi/fL5VxzRTMzJ8qP/jfzkRz9xHEzbtSu78jPy0VsOyRWOIOffekFuuvoOWXUcm5xZkN+/7za57soDnaPnt9+Wv/7zr8ut93ylsy/YGJfjGy/JJ666KNgV2iozrVCybEKgsQReeuklue222+SSSy6Rc+fO5crhzW9+UQ5OuOqBdjJjE4fl4Qd/Q24Z+2dytdYhl16k9cL583JuZ1s21v9W/o8/e1oefOyJ1DyNzyzJS1+4Rdy1iT1tW56883K5/5j93V7rZB3y0CFXjReEe+uFL8nVdzwW7OhsTcnqzuNy46WdHWxAAAIQgAAEKkUgf/1RfvEqKcTOv/lNuenghFMYDYNo8uiaPHX3Dc4oTj/7sFx/19edx1o7xydk8uoDsr2xKsdecUm29qn6sr58+fZr0uPRI2Wm1TUjHIRAAwgUKcQMvpNPPiA33Z8upgZFPD69KH/x6O3SWwsNLsRUFcoLX7xJ7viKo06bnJetp+6T4BHUoCXhPAhAAAIQgED+BOogxCo5NHFrZdb00uX+N3W021DDHW+xy/CgLPmZnFvO2CFbZloZs0QwCNSUQGFDE0O81o65p5zPUm+4wkzNL6cObw4l628OODTRRrR7yjuSUt92rzNtBKwhAAEIQAAC5ROow9DESgqx3fVj7nevUhoLroaMa9/47EoPL1GBNOOYzj5DutMLaR9bTUuyzLTS8sB+CNSfQBlCzFDcOnXcOzI+5AOk8cP6blm/ExHph5od6Tq/I5Zi7t31hZQHX/l8Gy0lWXZDAAIQgAAEBiaAEPPR5Q9iw5ubHEtpGAza0DGTfGRr4Jw9tezNHckiyMa9I3PHvFNn06bm6O1bZabVOzeEgED9CJQlxCy5jbVlb37msDeeMith4iHR2Lh3eGbeW17rNkW9jd29Xp6N11f6eY8+v7G4ftzxfbHxaS/1O9LurLAXAhCAAAQgUAqB/PVHKdmOJFLJd8S0oVKN5fy2vPXmupx+c0Pe+aGdHORied8VV8o1131Qrrnqyh4v0fdRjDLT6iNbBIXAqBMo+h2xbny2335LNja/L//4j2+H6hCRi993hVz5cz8nP/+Bq+VKncSj+2Qc3VIIjp0/ty3bO+d1x0Vy2QEzMUhwLPPW+XMax67OJ6Lx6MQiBzSeQaLJnB4BIQABCEAAAgMSqMM7YgixAY3PaRCAwGgQ2E8hNhqEyCUEIAABCEBg9AggxHyb1QHE6LkfOYYABLIQQIhloUQYCEAAAhCAwGgRqIP+oEdstHyO3EIAAn0SQIj1CYzgEIAABCAAgREggBDzjVQHECPgb2QRAhAYgABCbABonAIBCEAAAhCoOIE66A96xCruZGQPAhAYjgBCbDh+nA0BCEAAAhCoIgGEmG+VOoCoooORJwhAYHgCCLHhGRIDBCAAAQhAoGoE6qA/6BGrmleRHwhAIFcCCLFccRIZBCAAAQhAoBIEEGK+GeoAohIeRSYgAIHcCSDEckdKhBCAAAQgAIF9J1AH/UGP2L67ERmAAASKJIAQK5IucUMAAhCAAAT2hwBCzOdeBxD740KkCgEIFE0AIVY0YeKHAAQgAAEIlE+gDvqDHrHy/YYUIQCBEgkgxEqETVIQgAAEIACBkgggxHzQdQBRks+QDAQgUDIBhFjJwEkOAhCAAAQgUAKBOugPesRKcBSSgAAE9o8AQmz/2JMyBCAAAQhAoCgCCDGfbB1AFOUkxAsBCOwvAYTY/vIndQhAAAIQgEARBOqgP+gRK8IziBMCEKgMAYRYZUxBRiAAAQhAAAK5EUCI+SjrACI3ryAiCECgUgQQYpUyB5mBAAQgAAEI5EKgDvqDHrFcXIFIIACBqhJAiFXVMuQLAhCAAAQgMDgBhJjPrg4gBncDzoQABKpMACFWZeuQNwhAAAIQgMBgBOqgP+gRG8z2nAUBCIwIAYTYiBiKbEIAAhCAAAT6IIAQ82HVAUQfdicoBCAwQgQQYiNkLLIKAQhAAAIQyEigDvqDHrGMxiYYBCAwmgQQYqNpN3INAQhAAAIQ6EYAIebTqQOIbobmGAQgMLoEEGKjaztyDgEIQAACEEgjUAf9QY9YmnXZDwEI1IIAQqwWZqQQEIAABCAAgQgBhJiPow4gIpblBwQgUBsCCLHamJKCQAACEIAABDoE6qA/6BHrmJMNCECgjgQQYnW0KmWCAAQgAIGmE0CI+R5QBxBNd2bKD4G6EkCI1dWylAsCEIAABJpMoA76gx6xJnswZYdAAwggxBpgZIoIAQhAAAKNI4AQ801eBxCN814KDIGGEECINcTQFBMCEIAABBpFoA76gx6xRrkshYVA8wggxJpnc0oMAQhAAAL1J4AQ821cBxD1d1dKCIFmEkCINdPulBoCEIAABOpNoA76gx6xevsopYNA4wkgxBrvAgCAAAQgAIEaEkCI+UatA4ga+idFggAElABCDDeAAAQgAAEI1I9AHfQHPWL180tKBAEIhAggxEIw2IQABCAAAQjUhABCzDdkHUDUxCcpBgQgECOAEIsB4ScEIAABCECgBgTqoD/oEauBI1IECEAgnQBCLJ0NRyAAAQhAAAKjSgAh5luuDiBG1QnJNwQg0J0AQqw7H45CAAIQgAAERpFAHfQHPWKj6HnkGQIQyEwAIZYZFQEhAAEIQAACI0MAIeabqg4gRsbryCgEINAXAYRYX7gIDAEIQAACEBgJAnXQH/SIjYSrkUkIQGBQAgixQclxHgQgAAEIQKC6BBBivm3qAKK6bkbOIACBYQggxIahx7kQgAAEIACBahKog/6gR6yavkWuIACBnAggxHICSTQQgAAEIACBChFAiPnGqAOICvkVWYEABHIkgBDLESZRQQACEIAABCpCoA76I5cesVOnTsmHPvShlllefPFFufrqqytiIrIBAQg0ncBf/dVfydTUlFx88cVy8uTJpuOg/BCAAAQgAIFaENjY2JDbbrutVZbvfve7cv31149cuXIRYq+++qrccsstI1d4MgwBCEAAAhCAAAQgAAEIjDaBEydOyM033zxyhUCIjZzJyDAEIAABCEAAAhCAAAQgYAk0WoidPn260x148uSF8gu/YLGwhgAEILC/BL71LU/uuuunOjRRZGPjwv3NDKlDAAIQgAAEIJALgX/4B5FDh/ZacZnXpK677rpc4i0zklx6xKIvy10oBw+WWQTSggAEIJBO4KWXPB1D/lO55BKRc+cQYumkOAIBCEAAAhAYHQLr6yLXXtsWYmfOnFH9cXB0Mu/nFCE2ciYjwxCAQD8EEGL90CIsBCAAAQhAYDQIIMR8O9EjNhoOSy4h0EQCCLEmWp0yQwACEIBA3QkgxHwLI8Tq7uqUDwKjSwAhNrq2I+cQgAAEIACBNAIIMZ8MQizNRdgPAQjsNwGE2H5bgPQhAAEIQAAC+RNAiPlMEWL5OxcxQgAC+RBAiOXDkVggAAEIQAACVSKAEPOtgRCrkluSFwhAIEwAIRamwTYEIAABCECgHgQQYr4dEWL1cGhKAYE6EkCI1dGqlAkCEIAABJpOACHmewBCrOmXAuWHQHUJIMSqaxtyBgEIQAACEBiUAELMJ4cQG9SFOA8CECiaAEKsaMLEDwEIQAACECifAELMZ44QK9/5SBECEMhGACGWjROhIAABCEAAAqNEACHmWwshNkpuS14h0CwCCLFm2ZvSQgACEIBAMwggxHw7I8Sa4fCUEgKjSAAhNopWI88QgAAEIACB7gQQYj4fhFh3R+EoBCCwfwQQYvvHnpQhAAEIQAACRRFAiPlkEWJFuRjxQgACwxJAiA1LkPMhAAEIQAAC1SOAEPNtghCrnnOSIwhAoE0AIYYnQAACEIAABOpHACHm2xQhVj/npkQQqAsBhFhdLEk5IAABCEAAAgEBhJjPAiEWOAVbEIBAtQggxKplD3IDAQhAAAIQyIMAQsyniBDLw52IAwIQKIIAQiwr1b2sAXuHOy/y9tl2sHdfJnLFAbN9Ye/zCAEBCEAAAhDISAAh5oNCiGX0GIJBAAKlE0CIZUWejxA7/6bITQdFVkPJTh0VefxuhFgICZsQgAAEIDAkAYSYDzB/Ida9QXBen7bubOvfrp+Bd4tcrk9cL70oi0VpDGShRBgI1IUAQiyrJbvXu1lj2T6p9fFN0dATsyLPPeSqe9tpvqnnvOIrt/e9X+SXx0WuoRctCrHwX9iicMQkAAEI5EoAIebjLEOIvfWGyLdeEll8TuTpV9x2HJ8Quf1OkX+l6+uucIcJhsfsydt68/83XxJRTddZfukOkUcfUFHX2ZN9460TIo/8QTS+33xU5O5D7TjKTc/V6MleFkJCoC4EihFi2mjViuPZeZGT39f6oleFocc/cKXIf/XzItd+SORD12WpY8q+hnMSYq+rEBuLek83IfbmN0UOap0dXzY8kasYzhjHUuDvPcEWBeIlaghAIHcCCDEfaZFC7LSKm9//PRVf/tPSrFY8rA2kr9znauzYxs2evPGkyIfvT8Z4ZFHky7cn93fdo42yOy8XORYLNK5Pgl9+qL2z3PRsOWMZ4icEGkagKCF28hs6BO/zg8M8MifywN2258cVT9nX8P4IsWf1wdddTyTLv7wl8rEDZTNI5qM5e/YEWzTH2pQUAnUggBDzrViUEHtSb9D3O27QmZ1nSuTs4/qieOQEe2PXRkeKeDLB13TY4w2Zhjq2I39Ze9Y++VgkodaP45sin9An4a2l1PRsOf20WUGgoQSKEmKPa+/7g/EnLwMwnj0u8tAnXCeWfQ3vjxB7XMv+4CvJ8q/uiNx4adkMkvmo7h63vbb1PtNadMj+gV49tZEexz3BFtW1NjmDAASSBBBiPpMihNjpZ0WuvysJvd89k9oz9tR94bPsjb19Ezv9jKZzT/h4e3tCn1Y/p0Iwy2JeTn/3wWRIVxzlpWfLmcwXeyDQJAJFCbEnVYjdn4MQM7Y4vCDytc/GrVL2Nexu2Mdz1ev39uv9DU1Me4hFj1gv0jF7ndMeVp2hMvzssj1JSrd4wj62J9iiGyuOQQACVSOAEPMtUoQQO6k9WTc9mDS5Gc7z2V/T9yw+IHKR9lidfVvk28/r0JYuQ4RWdIjLodaL3yY+e+MJbmJf+ojIY46hj5HerGRWOnvSGmSntFftOkevWjnp2XJ2sskGBBpJoEwhNqa98P/6kMiPfxygPvcDkdPfFVl+OjqTYBCivXX0lL5Pel14b9nXcFAnhnPR73a/QsyEv1nfKQtXwRMz+v7dF7SO79TX/eaiCeFj9nKMuGi/m9eNRdjH9gRbdGPFMQhAoGoEEGK+RcoQYnP63tbd+t5WR0/FvOGc9kr97kF9lyy23/yc0qfNj3eeNtsbT3ATc83y1YpGG1W7KggdWqqTyjsnRN5/a+dnZ2P6uE764RxupCMiTyZnFcs/PVvOTpbYgEAjCZQpxObWtFfihnTM5p3X39X6wjEST2RSZ4J9Kvxea9nXcFAnppeg95F+hVgrRvPdMX2opiu5SHt1ruyMJy+bQe/yVSdEzF7aI3avsgvfA/sVYtiiOtYlJxCAQG8CCDGfURFC7M0XdCatO1RE6ZPR/1WfjHbuy13skiZwojcje2OP3sTSXlKe08e0D9yYnugXL9BJQeKHdQawrefSRaMJXnx6tpzxzPEbAs0iUKYQm13R9720R6zrooLjXu3RDzeYbfhj6yKfucb+KvsajtaJNhf9rgcSYqmJlM0gNSMVPBCzV15CLLWk2CIVDQcgAIF9IYAQ87EXIcRaUbcej/Zn269qL9Qj8cfN2rO1oz1b7feW7c0kdhPTxtFHtHEUHh7TSnlcZPNlfULryMYb+n7Zhx3vly2s6/DJTmPKcaLZVXh6tpwp6bMbAg0hUDkhptzTetKjQq7sazhWJw7oHwixAcH1fVrMXgixvglyAgQgMNoEEGK+/QoTYgP4h3NKaRVTZ1VMtXvVbOMmdhPTtNLeSzusL+R/7TOxzDjG45sQ49qD97L24GVZik3PljNLTggDgfoSqKIQM2Pwvqiz2sV706OfzjDXcLKeSrOUmS3PfOzeLOb92ct0HHe3YdXtkOF6Ilta4XRMGpfGEilHiGXL63kVJ9s7bR4HNK+DLOHyFsnV+MQ5zau+WqyzP6n99MlhDG0o+w7f0PPv1fOeDoVyTRgVOqyb/di/n7BBKtYGdo8Zetp7NkcbOpym2ZfN7iakSXdHeZpLwtitt/3jaZlYWCAAgSoTQIj51qm8EMvSI2bKojX2w3oj+7rD69a0Qr+h3aXWOnriSyK3PpYM2J5yObnfuafQ9LipOJmzs3EEKinE1Arf0N77z8d676MPcsw13KXhqQ3N117SbxfqO7BfCbe+QxaePKwTGf2GPiC6JW2odLieSE/r9GsiR/9Y5E91Sr74qIHxSZ2gROvYOzUNIxz6FmJaDz77H0T+8rSf8feIfOq3dYjmjeZ3OH/+cbM6vyfPfFnkP2/4+35WJ1zSOvkqkwFd3nhB5N89oqIknFmdEOTw74h86aE0Fu1zpUSu22/p+4Jqw+d1KPsT+sAvvkwo2zt09uBP68PEqyJCUrkog2f/SOS/aH5bi64fid+T9LyZO/WoDWOD6u/bPqffabsqzFftn9kW6b5i4nhjReSbWp4XdCKtV8I28NMXtcXUp9TOd4jc8iv6kNS3mz0crMP507097G7Sfu0vRP5YfTXB09hfR7Dcq0wPXRWkEGzF0goOsAUBCFSUQB2EmHg5LGfOnPHURq2/M2cu1BiH/TPZGuxvfqKdD5sfs9Z3xELx2byF9wXbm8eT58fj2F13h9Ges1A62baLS8+Wk/Xw/gjDUWb44ovvatVNl1xirsm8bCmeq67RoYWZ64DZsWQ9otONh843eQ3/DraXNVy4jsuyvbAanB/EG+aRPL6jdd2UI5/O9MbFWz4r3u6pZN7adXA4Lbst3pYyi8engtQvuw0XXbvOsewXDifjC8ev0+LvO1dvR/2nRz7DeTbbR+bF2+n4w4VObvFzuv1uMw5z7ccWboZri+Kp9kvYs1s+zLFZPS/wyfB2OH/uMlu7byzrvT5j2lNz6qcdlja9aFr51RXEC0t8oCgfMJrD1i9Gi4ziYmqgoZfKCDFtBLgq4mTjxlwUtvJNrl0NLGPoxY122PlJx41GGyGbXeIsPz0u/KIufOIdLd+qpBDbVYHjaDTORYScu56ac9U/jrjszSm8nk48LArbMloXbq2Jp50InZtcOJ5u2zMqouLHuwoxFYju8CY/4fwF21uOc+Z13+KRZFzxuHXUgrP+L4vrrt5HtFMmUeZ4Pp2/Vby1xZiKEgcD5zkpaSVtokLMEWfwIDPg77qf9RLAvfI2Pm3LFrZPOE13mefVT1fm++cZlMumF00rzffYDyd8oDo+gBDzJVxVhNjClLsy1u+IhW681oHC+6LbaT1eojfBdcfTW3ODMTcD180py75i0rPlZE2l2WwfqKIQS+sJj9Yjxm7RemXO0eMfbuDqUDZvqodQm9Fe/yDesG+E9m8O1rMRzkt4O9not+n20/i357gb5OH0um1H7wftMpfGNeVhYbf8xo+1Hwi6e4fiYbv9Hmv1OgZMjU8MKsTmU+693dJ3HRtTIR30+hnbhPM3nN1d6c1qL5r7WoimG88Hv+GDD1TDBxBiWoWZpQpC7Jg+TXNVtOORYYnhij1cASe3l1Lic6Vhbh7JYQ7JOIMKP3ks//SqcZFQWWGH/faBygkxbYw7e0S0V30rIryM7wR1xbLWZc76RxvBy+uxOkh73LoNXwx6hcL+GaSVNirApD+7oA+kVKid1b/VJR0y10McmnPKEmJjY1FGU1qPz89rHkNCIS7EyuR6tItIPqoC+aw+NNQJJlpsV/T3YQfbmZZ4ULupjZfUFgv2T8uZ6MHU8xe0F7QTxg97VIe2rqr9otfmYEIsjZ+xu35+xlvRh5RbWqZdze+W+n7LZ7pw0G9whvw+7J/Zhdi0sljTa2JTex8Nx9ThtconuOaiaUXZcAwe+EAVfQAhptWlWfZLiO1opb6yqI2a2M2301jRSjY5XNBeTOHK3rGtNw5nY0lvLp34/W3zXkS4wTTQdu7p2XKyrmLlQZ7K88syhZh+d7BrXXBKhUvaOzT2XZeg/jCM/Pi00ZxoZGv9M6nvunTC2LChtXnHyzlcWxvk7fPCdmjv21lL1nGtOk/r03VtTLvSM+8GxevF8O8yhFiEj94TVlpCI8jvroqczdg+r0Surt6mFiMVJRspXA3r9ZjPLJwyZQr5hrW3xhG/Z+msiU57BTaM2t+Vx2AIXzRsK44UfqZcS/5Q/iCtaF7WVCCGfSS8vWHL1G+PmLI8FRkBE6SZNvT0eMcnwuVjm3sUPjAKPoAQ0yreLEULseMz2njRp8UT2hCwf/Enn61KXG++9mY8pk9A3Tc3e3EFFXTajWK9y43C3jSi75/1jjMtLbM/3/RsOVmPQmVCHovz0zKF2ITWVUv6BH5RhYn5O67bOquhN6s9M2kCzNQlbkFlmLTrFFevw5gOlc7SE7+lPSi2vuqsta5sP6QKc2+ndTzlPaugF81dz3V7p6wMIdYpm/LUWW477CxD17pMrs6h83pfC0RHlzyruJg1vXoavi2GA9/olEvLnBBi2ovaOd4RN+F9Ufv3K8SW1d/D3O32UkfchNNKbq/Ou88PhgyG89e9R8z9jlkoTWXofCihvYNtRtG0qJPhgQ9U3wcQYlp9maVQIZZSedoK37We1yeI6Tcf61jdwgTHZvXG50qjtS/rTdR5AwzSCOc1v/RsOVlTmTbbB8oUYql1hYqDtGOHOw3BeJ1g7Kb7tKfDNbHHYsbGroljxlGPBT0r1j80La1v4415k2/9vlmXOjU4ZnrT7MOwcHnLFGJ2UqVwvercLpOr2solxKPvBAYcnfmN3Ed83wjvK1uIaXouv8zqK7aMLt8072O3HzJY32yvXULR+Fny3TI3S9crAO4ev2i63EPggQ9U0wcQYnprNkvVhJh+o8Q7rE8C17VRYSv7YG2dyXUsuW9dn2aHGxTh7WCK5eR5QXr9HcsvPVtO1lSgzfaBqgqxCf/drvS6wthN3xlScROud1oNz05DNVv9sqpD1OJxtIdChn3D/Y6QOa9Xb1i4DBuLybTKEmL9fEKkTK6b+nAwzt/cp5JD57PZs12nxcKWLMRcnxAwZVzrMswy7Cd2O20kSNDzF/ioU4g5X0GIsfEF61nHZFsIsYAv90pYjJoPIMSMCtOlUCGmFei0Vu6Jm1jGfXORWZFM5WwvNHdFbW8OrXXKE79wXjI/fQ0/uUzbzjU9W07Wgc1h0UQWVRVivd8tNf6qDVvtMQvXOWZ7qvOOV4Z6TOM46xie2B7+Fb4mUoZHq2CMzmTXPc2d1WR+SxFi+n5QMPFC9zyWzXVFHwzGbTg53zuPrfuQ837R9o3I8ZKFmGtYoemZiuTJmfdYGH2XzNWLunTWhAv7p3toYu/34IL0XEIOIRZlHGfOb/hU2QfqIMQu0JrO3CCGWtb109bXXnttKw6FIgcPDhWdnrwXieD8tsipjcgu0RmY5Ae67zv/p8hzfyryymr0ePjX9KLIo7fbPRf6G9E07NHw+sRXRW59JLzHsa3jeHaeErnUcajfXfmmZ8vZby4ID4F6EXjpJU9uu+2noh90lnPn8rou9uTJO0XuPxZjpePPDn9I5J/83d9d7l43La6L3H5NLI7OT5PXPXlN66GPx+ohfRdNHv01kR/9pBM4feNikd01kU/eHw2iDVB57qEwjz05+bjITQ9Gw03Oizx1X3Rft1/br4tcri3r8JJMyx7dk/TwJkw4f/Yc0XP2kmnMaXkeCML02iqTq8tXdGIXeeDGXrlMO972jcjRcyL3XibydGhnm3toR2IzzLcfW+zJs8r6rieiEaq4l4c+Ft2X5ddXPyLySOwerj228tChcP5S7N7y4yypaBhtS9x5uUjkstVr9uzLIlek+FrGmAkGAQjsAwGVH6o/2u157RRS/XFwH3IxZJJGiA27FN0jluUJm5mNzPUiruIxQtNLzowUPCVzxb+7nnyCaeOKr4MXi7vH6UrH7ss/PZ7iVPkpDnkrzz/L7BFzzZp4VuuS1kQLfl0Urz9OpQ7lMozE6/WNq3h8WX+3ewLCdtAhiI4hjNGPTPeu49J7HcJp2e3/n71ziXFlOe97GdJ9xbpClCC2ISnWNa4CZGMunBgBYisytVHgLBgg2YkKtKK9SibL2RjhkrswKzqb8cITJKADaLwZ3wuMbVESQAQYA6EXNOQRNEo0QigDc425DniQOXalit097MdXze4mu9ns/g1wDslm1+v3fayqf9dLng7p5c2mFdwXfXWnsTt/QZ1bJVfpOIDkLpnZ8+5xid1f8YiYxK9omdx8Dmx3gZEyUxu9kdRoWi7f4zqc8IH6+EATRsRsTb73Xx2E2KZxNR0aceGv7QCZNRXe9JrAgWKNWGwKhdQw2Ap7ICx6tx2fTDtfxdIIOgT29fDpBeXklUqz3T5QpRBL64jOhOlptu7oOne2s3Zz1A0OUZdVhNn7JCEmTaFLK1O4Dgveu0WS5IfHE2JinVsSVymty2V6GxTwlF8934h8J4iMraB1pRW2SR5byH6Z11eC/E+EdtXbyCScP8fUROfvRyizwMjuRIkQi3KmzYTHqfgAQsyXcLURYlbomHnlrpEx7yDP4AcmVNK+UFqZLaelDs2Vmcv+LKx/sPfus419OekF5eT1VCoU8lmOr9ZFiNlO56Xdglzo7HvrYeJ1kuUhd3ilOPJe80bvwszN6JvQIc7buW67EJO4SkJMtnncB1yfPd8IhMzmVRAZpyLEzoXfRJIjQow2Ilxf8R5/+IRughA7iTVipoOR6+9Pf0epTmw9hI3APGFT3/iHwZxzxxqx12be/htKxaa+q85Qqf/5W142/svXlfpaeCK+d1mZxffqn3zG/5D1pbT0gnJmzQj3QaCZBKpcI2ZEi1nXksLxJ0p95WfNurHYLWbDAWF9k/0N/7X6bbMW7Tcji1qUMueOqf/wZbMWzayVLfL3t/6uUu9/1oYM1xNmjdh/MmvE/l00RjM1Uf1GWpmit6es+QqnFQTKsy4pCHOAtUImqiq5SmvEiq6n8ih4vrElYt5VvEZMLNMu/49kePvBHVfUZ8S1gXnWiAmMzIiYejJrxN6N/Ba2eeMdBCBQXwKsEavjiJh5giw9kTVupC/MaNb2CYL8pFGammPDzkNb4dv1XNIuT0V2jCovPZ4WbW0NizazqNOImB25uBnKo2LJbb+t38ojYtJatMjoiAmX7XP4tyGvETObHWWMy7tPqn+T0yCDdOX6ejuSE9wXfXWnkT2v0ihVWVyl9VR5195F7Wl5xMpa8YiYWKZNGxvLVzyfwmd3XAe2u8CIqYlRxm1uKyj76flCE0bEbI2591+tpiaaSl5qpDMJMcc2uv2LZMMiHQxp08g177/U9E7vB0UliM3K8IG6CTHXxjxDMyU62rm2/iCLI6lOioaNx+X6HPY5pW+FzTrynpco1b91FGLSxiRlcZ0KU1KT9nbZSLru+UbE5oLI2ApaKQ57LWp/t+2S916breptmxf+V2iKvnnIKS0n8B5+hvPH1MSovaJs+A4ebfQBhJgv4eomxKRzbGxjET03J9kwXZpzaMKNSvD+TniCpx2Nh3269ijdL1wrNz0qpTZWSpQ56fd1E2K28yyNxmx3bwvqJluWw5ztFemwR+qiMC9HWjnqNJuOdNBvHYWYeJBwzjPTsnKVRJ8y7U2e89miaXm+EblWsRBbXgjtZU5fsfkX10i/HHYd9k+EGPV71B/gAQ+EWE2FmGu0yjt8OXDcoLPjvUoHnlohlvbUUmyITJjz62jckcbS7wSVn15QTl6prNvtA3UUYg+mjgge9IRfp/fhusPazWwQdCffu/tA6HBcrvdh33CnlfngevOAamDqwHCZ7Ps6CrEqubrq++Ibdni+EWlbBCGWFPdxP4jaP8+ImHSvtbXd1CqSL7/Nc127EB6Abkdhw/lDiNGWRf0BHvBAiJUlxExjfn2l9HKVr0LfVPSO6X4q8YQtGre0a1OW0a0zodNhG6OlaRRdDY+9Xn56/ECppPEB6wN1FGJa6jSbemPbAbX1h7WfV48MTf0li5v0eiYI734N+4gXl1Q3ZVr/asp0LuSzrkLMMqmMq2MGRdTe6bacXZi1yYavJ8C3vvFiW8mnzAjVyvehl/sin6P2l8TVdnpj9F5tjouRRLfKMaq4Mud/xv3afp6ahw9efsNpIsRo06L+AA94IMRMVWn/Dj01MTyN48ysWbg3jZjciESvPxvh5hJGfdOIRSv24LNZg2G+kxoD7xyT7X1SHsRpFbZDlXK2STXp8QOlksYHrA/UUoiZzrBr5H7x8hDH2s+rf5aXch11Pk2vn4Lwweva1JFz0/l9iKQR+IkX13wkpzUy4YJ44q/P5gGY2Ck3dWGdhViVXKU1VZbNuXnoGOcZ/vz8aM7HNGdYBm3UaG7v3/rGy70OsZc+QhXY3osvlxAzvjk37VyQr/DrVry5y/a0lDe9io7ihfOHEKNNi/oDPOCBEDPNgf0rU4gFlXvPHMh8bRqglSDKnkzn4sYhpoLw2x3JAsf1GwgT1uxem2xMTHrPfifopaFzfB6bp45BOuFXsQGsLL2gnLxSWbfbB+oqxNaOKYfbqc3Wbn49JY12BCJnmD574NnUmQsjooahDSN6pr704g77hnfNtZmIrdvOjSB8NCMh4XzNHSIxXBfWcWripgwVcnXZ23LqWxsaMfvC1djdtmtXwuYp3mhRyDcCHzF2ER9EmlG0WxNXEPfK+N3UxHtjhFC0bpQ3utqKqqSv2HM7xfbTlKlj/G1u0oq3o2sTJq29jm54FU4TIRa1V5QN38GjjT6AEDPVuP2rQoiFG3U7zbBnnhD2zT9pG/nIvaZB8DbpCBqi4MfqfZZ2s7Lhb0INV9CAuV7XpkGLp7n53E8uxq4uvaCcvLaxcqLMW7+vqxCz9Yn4EMc82PE2/LFlCOotM4rlOGj+pe4x4c5Mh35sOtljM1IxNLva9cy1l+9NvRa8T+1cmzRdozcv4U3dZuvf4LP4aurp4HpthZgpa524Bm1bN8QuYBi8OkfETFlco5k2rG0zw+2lNy1y+zuxvpZ3RMyGcY0qBvm1ZeobUXZmHm66/DG4t3+x9XfP98P5Q4hRr0f9AR7wQIhtZNjhhZhT2IQ6EkHFves1eQZO4Lims3O77SiE4zGHq0Y6QF6DkH7tKvS0ORyX12h6YatNLygnr1TW7faBOgsxcec+U8+5Rj0WZipiuH4p+n5bx4V9I1rHjVLEQFq6YyMYL2L1YZ2FmK3fq+QqnZmVxjP+nbf+2Notai/7OW00Mx6Pt9V81P5FhJhNdy6M3MXT2/V5ILa74fwhxGjLov4AD3ggxEoSYrZivzONuWvKw64KffO9eRJ8c59sqLY/XMcW0qYTtJ3GKIV3XDPTSsJPG1/yaPLx5DeY4pbVpaXHD3Rra1i0mUVZQmwijDaNzcMdqYPsvOZY17PtJCfjezBTtPeqG43Aun0M4g3/NoJr/quZtjcUyvhSt5m6K/7+ajPdTek4m1QhJjwQk0fstnl1b5EfK4Nf9zr5h76vjKtJ89KMDsXZ7frcMaOQy4jd5LLeXmSLWxwRy2yLZNrL62zpSuWcONcfbm1u67C97S793oyPb0ego+m1ud6k7PjCKfgAQqxEIRY0nEvT6RiZKTaiyBE6Aj3zJPbKhInPSw/i2zqWEWKmYYs3CmkL0rdxJBsh+510GKo9K+ZFiFWaHpXI1tawaDOLsoSYtFHBdrc3uY6Q6hApHm+dmPVbRzxmPdDMjI4NMgqljrnvfGTCLOJ1Y/i3Iad1azaT6O0YHRuazn947Vh8amPffC/7oLlupoHHD/QdbO53hTF5Tg0jl8PJMsy4Qq73RvScC21CvE2y66NvjN2i+U/xDVOeeyNsUm1m7DnbrEmL2T+Va+zeMLfgvRE6dl1batpBu218cmx8eGUEf7Rs4c/hNM371PyFwznem7Ti6+isIPX6C7G0NhuicE3+3cIFLvXwgSYIsZ8yNaAVI3v93d/fq1/4hV/YxGGgqPfe2ys6E/ivxQg++olSq5VSf/EXSn30V/4tbyr1mc8o9dmfU+pzn1Pq7U+KQUMXP+G/99L4+GOlXr/2Lr3zbpbwoaiEt69fKfXx2v/C5OVdE2c4S9WlF5RTyCSXINAiAh9+qNVXvyE0d+gAACp2SURBVPo36q23lHr16lC/C6/+sL/3tfm92ypkn/ojHM8n3zH1xtvWQDavcl1ovw3+Xpk67OFBqR//OFYv/rRSf++zSv2sqRc/s4kvCBF+DfNIT+sjE//3vm/q4I+88G9+ytS5X1DqH7xv6s1wlP57m6+1ARMtT/xGP01z36ZuNF9/0q83vTvD+QuHNeGcYcL3FX9fFdfXhtMP780/Y8O/+n9efj9l2jRru/cM33fDDchLcbL5hrXZD/63Un/5f03AN5T6aeMTf//zpr38mSCiMN88tvDvDaIRXj827fX9j0x7bV6Dcr35pvFF44+bPJgy7v4L58/efRi7B+1wNl/bnUvugAAEjkPAyA+jP7z6yOxXYfTHe8fJyB6p1lSI7VEigkIAAhAIEShHiIUS4C0EIAABCEAAApUTQIj5yA8/Ila5LUkQAhBoKAGEWEMNS7EgAAEIQKDVBBBivvkRYq3+HVB4CNSaAEKs1uYhcxCAAAQgAIFCBBBiPjaEWCH/IRAEIFABAYRYBZBJAgIQgAAEIFAxAYSYDxwhVrHnkRwEIJCZAEIsMypuhAAEIAABCJwMAYSYbyqE2Mn4LBmFQOsIIMRaZ3IKDAEIQAACLSCAEPONjBBrgbdTRAicKAGE2IkajmxDAAIQgAAEUgggxHw4CLEUL+ErCEDgqAQQYkfFT+IQgAAEIACBUgggxHysCLFS/ItIIQCBAxBAiB0AIlFAAAIQgAAEakYAIeYbBCFWM88kOxCAwAsBhNgLCt5AAAIQgAAEGkMAIeabEiHWGJ+mIBBoHAGEWONMSoEgAAEIQAACCiHmOwFCjF8DBCBQVwIIsbpahnxBAAIQgAAEihNAiPnsEGLFnYiQEIBAuQQQYuXyJXYIQAACEIDAMQggxHzqCLFjuB9pQgACWQggxLJQ4h4IQAACEIDAaRFAiPn2QoidluOSWwi0iQBCrE3WpqwQgAAEINAWAggx39IIsba4POWEwOkRQIidns3IMQQgAAEIQGAXAYSYTwghtstV+B4CEDgWAYTYsciTLgQgAAEIQKA8Aggxny1CrDwnI2YIQGA/Agix/fgRGgIQgAAEIFBHAggx3yoIsTq6J3mCAAQsAYQYfgABCEAAAhBoHgGEmG9ThFjznJsSQaApBBBiTbEk5YAABCAAAQhsCSDEfBYIsa1T8A4CEKgXAYRYvexBbiAAAQhAAAKHIIAQ8ykixA7hTsQBAQiUQQAhVgZV4oQABCAAAQgclwBCzOePEDuuI5I6BCDgJoAQc7PhGwhAAAIQgMCpEkCI+ZZDiJ2qC5NvCDSfAEKs+TamhBCAAAQg0D4CCDHf5gix9jk/JYbAqRBAiJ2KpcgnBCAAAQhAIDsBhJjPCiGW3Wm4EwIQqJYAQqxa3qQGAQhAAAIQqIIAQsynjBCrwt1IAwIQKEIAIVaEGmEgAAEIQAAC9SaAEPPtgxCrt6OSOwi0mQBCrM3Wp+wQgAAEINBUAggx37IIsaa6OOWCwOkTQIidvg0pAQQgAAEIQCBOACHmE0GIxV2DzxCAQF0IIMTqYgnyAQEIQAACEDgcAYSYzxIhdjinIiYIQOCwBBBih+VJbBCAAAQgAIE6EECI+VZAiNXBHckDBCAgEUCISVS4BgEIQAACEDhtAggx334IsdN2ZHIPgSYTQIg12bqUDQIQgAAE2koAIeZbHiHW1p8A5YZA/QkgxOpvI3IIAQhAAAIQyEsAIeYTQ4jldR3uhwAEqiKAEKuKNOlAAAIQgAAEqiOAEPNZI8SqczpSggAE8hFAiOXjxd0QgAAEIACBUyCAEPOthBA7BXcljxBoJwGEWDvtTqkhAAEIQKDZBBBivn0RYs12dEoHgVMmgBA7ZeuRdwhAAAIQgIBMACHmc0GIyQ7CVQhA4PgEEGLHtwE5gAAEIAABCByaAELMJ4oQO7RrER8EIHAoAgixQ5EkHghAAAIQgEB9CCDEfFsgxOrjlOQEAhCIEkCIRXnwCQIQgAAEINAEAggx34oIsSa4M2WAQDMJIMSaaVdKBQEIQAAC7SaAEPPtjxBr9w+B0kOgzgQQYnW2DnmDAAQgAAEIFCOAEPO5IcSKORChIACB8gkgxMpnTAoQgAAEIACBqgkgxHziCLGqXY/0IACBrAQQYllJcR8EIAABCEDgdAggxHxbIcROx2nJKQTaRgAh1jaLU14IQAACEGgDAYSYb2WEWBvcnTJC4DQJIMRO027kGgIQgAAEIJBGACHm00GIpbkJ30EAAsckgBA7Jn3ShgAEIAABCJRDACHmc0WIleNgxAoBCOxPACG2P0NigAAEIAABCNSNAELMtwhCrG6uSX4gAIGAAEIsIMErBCAAAQhAoDkEEGK+LRFizXFqSgKBphFAiDXNopQHAhCAAAQgoBRCzPcChBg/BwhAoK4EEGJ1tQz5ggAEIAABCBQngBDz2SHEijsRISEAgXIJIMTK5UvsEIAABCAAgWMQQIj51BFix3A/0oQABLIQQIhlocQ9EIAABCAAgdMigBDz7YUQOy3HJbcQaBMBhFibrE1ZIQABCECgLQQQYr6lEWJtcXnKCYHTI4AQOz2bkWMIQAACEIDALgIIMZ8QQmyXq/A9BCBwLAIIsWORJ10IQAACEIBAeQQQYj5bhFh5TkbMEIDAfgQQYvvxIzQEIAABCECgjgQQYr5VEGJ1dE/yBAEIWAIIMfwAAhCAAAQg0DwCCDHfpgix5jk3JYJAUwggxJpiScoBAQhAAAIQ2BJAiPksEGJbp+AdBCBQLwIIsXrZg9xAAAIQgAAEDkEAIeZTRIgdwp2IAwIQKIMAQqwMqsQJAQhAAAIQOC4BhJjPHyF2XEckdQhAwE0AIeZmwzcQgAAEIACBUyWAEPMthxA7VRcm3xBoPgGEWPNtTAkhAAEIQKB9BBBivs0RYu1zfkoMgVMhgBA7FUuRTwhAAAIQgEB2AggxnxVCLLvTcCcEIFAtAYRYtbxJDQIQgAAEIFAFAYSYTxkhVoW7kQYEIFCEAEKsCDXCQAACEIAABOpNACHm2wchVm9HJXcQaDMBhFibrU/ZIQABCECgqQQQYr5lEWJNdXHKBYHTJ4AQO30bUgIIQAACEIBAnABCzCeCEIu7Bp8hAIG6EECI1cUS5AMCEIAABCBwOAIIMZ8lQuxwTkVMEIDAYQkgxA7Lk9ggAAEIQAACdSCAEPOtgBCrgzuSBwhAQCKAEJOocA0CEIAABCBw2gQQYr79EGKn7cjkHgJNJoAQa7J1KRsEIAABCLSVAELMtzxCrK0/AcoNgfoTQIjV30bkEAIQgAAEIJCXAELMJ4YQy+s63A8BCFRFACFWFWnSgQAEIAABCFRHACHms0aIVed0pAQBCOQjgBDLx4u7IQABCEAAAqdAACHmWwkhdgruSh4h0E4CCLF22p1SQwACEIBAswkgxHz7IsSa7eiUDgKnTAAhdsrWI+8QgAAEIAABmQBCzOeCEJMdhKsQgMDxCSDEjm8DcgABCEAAAhA4NAGEmE8UIXZo1yI+CEDgUAQQYociSTwQgAAEIACB+hBAiPm2QIjVxynJCQQgECWAEIvy4BMEIAABCECgCQQQYr4VEWJNcGfKAIFmEkCINdOulAoCEIAABNpNACHm2x8h1u4fAqWHQJ0JIMTqbB3yBgEIQAACEChGACHmc0OIFXMgQkEAAuUTQIiVz5gUIAABCEAAAlUTQIj5xBFiVbse6UEAAlkJIMSykuI+CEAAAhCAwOkQQIj5tkKInY7TklMItI0AQqxtFqe8EIAABCDQBgIIMd/KCLE2uDtlhMBpEkCInabdyDUEIAABCEAgjQBCzKeDEEtzE76DAASOSQAhdkz6pA0BCEAAAhAohwBCzOeKECvHwYgVAhDYnwBCbH+GxAABCEAAAhCoGwGEmG8RhFjdXJP8QAACAQGEWECCVwhAAAIQgEBzCCDEfFsixJrj1JQEAk0jgBBrmkUpDwQgAAEIQEAphJjvBQgxfg4QgEBdCSDE6moZ8gUBCEAAAhAoTgAh5rNDiBV3IkJCAALlEkCIlcuX2CEAAQhAAALHIIAQ86kjxI7hfqQJAQhkIYAQy0KJeyAAAQhAAAKnRQAh5tsLIXZajktuIdAmAgixNlmbskIAAhCAQFsIIMR8SyPE2uLylBMCp0cAIXZ6NiPHEIAABCAAgV0EEGI+IYTYLlfhewhA4FgEEGLHIk+6EIAABCAAgfIIIMR8tgix8pyMmCEAgf0IIMT240doCEAAAhCAQB0JIMR8q3z/+99XX/ziFzefvvvdT6jPf76O5iJPEIBAGwnMZlp9/et/o958U6k///NPtBEBZYYABCAAAQg0jsCPfqTUr/zKX2/KdXd3p95///2TK+NPafO3b66/853vqC996Uv7RkN4CEAAAhCAAAQgAAEIQAACuQh8+9vfVr/6q7+aK0wdbkaI1cEK5AECEIAABCAAAQhAAAIQKESg1UIsPDXxW9/6lpmayNzEQl5EIAhA4OAEbOX8jW98w0xNfFMtl8uDx0+EEIAABCAAAQhUT+BHZm7il7/85U3CrZ6aGN2s4wfqvffeq94apAgBCEBAIPDhhx+qr371q+qtt95Sr169Eu7gEgQgAAEIQAACp0agCfrjIFMTmwDi1JyP/EIAAtkIIMSyceIuCEAAAhCAwCkRaIL+QIidkseRVwhAIDcBhFhuZASAAAQgAAEI1J4AQsw3URNA1N7byCAEIFCIAEKsEDYCQQACEIAABGpNoAn6gxGxWrsYmYMABPYlgBDblyDhIQABCEAAAvUjgBDzbdIEEPVzL3IEAQgcggBC7BAUiQMCEIAABCBQLwJN0B+MiNXLp8gNBCBwYAIIsQMDJToIQAACEIBADQggxHwjNAFEDfyJLEAAAiUQQIiVAJUoIQABCEAAAkcm0AT9wYjYkZ2I5CEAgXIJIMTK5UvsEIAABCAAgWMQQIj51JsA4hgORJoQgED5BBBi5TMmBQhAAAIQgEDVBJqgPxgRq9prSA8CEKiUAEKsUtwkBgEIQAACEKiEAELMx9wEEJV4DIlAAAKVE0CIVY6cBCEAAQhAAAKlE2iC/mBErHQ3IQEIQOCYBBBix6RP2hCAAAQgAIFyCCDEfK5NAFGOixArBCBwbAIIsWNbgPQhAAEIQAAChyfQBP3BiNjh/YIYIQCBGhFAiNXIGGQFAhCAAAQgcCACCDEfZBNAHMgniAYCEKgZAYRYzQxCdiAAAQhAAAIHINAE/cGI2AEcgSggAIH6EkCI1dc25AwCEIAABCBQlABCzCfXBBBFnYBwEIBAvQkgxOptH3IHAQhAAAIQKEKgCfqDEbEilicMBCBwMgQQYsc11auPfqweVk/q2WTjjXc+rT73hc+qt4+bpdqkDpv9TAG//fgRGgKnTgAh5luwCSBO3RnJPwQgIBNAiMlcqrj6+oe/r954rxdJqju5VX/4G78UudbGD7DZz+rw248foSHQBAJN0B8nOSL2+vUrtf54rdbP9hmr+XvjHfXpd99Vb3/S+3jw/016Hz16T3S9uN9Q73z6XfVuGQlWmdbBQREhBOpHACF2PJt8/Ce/rT79j34zkoHe+FZ989+WLcReqx/+yUz90eJ/bdL+1N/5efXL3X+mvvBuWY1EpIiZPhyPTabslX+TaeterZ83I6WmEVfvvPO2+mQO87SDX/39uHxHIQUIuAkgxHw25YN4rX78Z7fqjz/8QF1/87+r3/2jhWiVbm+g/vm//BfqX/V+Xb3/mRw1uhDb649/rGYf/J76b7/7TfWfr/5IuEOpTrevvvZvvmbS+zWTXvHJNlWmJRaEixBoMIHShNjrn6g/+N3fUbPv/aV6+23v9//qlVJ/+ws/r/7xP/119ZVf/JlyqL76sfqD//p76n987/8ok/AmjVcm4bd/7pfU1wb/Wr1fvCo6eH4//lMjxDq/GYm3CiH2w9//9+q93n+MpKvUUD3o31KfjV091sdjsTlWedXrj9Wf3X5XffjBB+oP//gP1ZXQjne6PfWVX/uK6na76ku//IsqrVltA79T8OOj+RMJQ8AQKF9/VIBZH+DvBz/4gTZZ3fyz7w/5dze71P2OF3eQRpbXs4uZXhfKyJO+GZ+9lCdLWvae/uhaP+ZOr8q0cmeOABBoBIEPPvhg83t+6623DlqexaSXWk8MLhcHTW8T2Xqpz/y6Vqyb+tOC9d7hs2pjfFpMEoyMECsnsZdY13o66CTSVaqn508vNx39zXHYHKHYzyt9PTnXnTS/dXw3GE31ncNmzed3Gn58BI8iSQi8EChTf7wkUvIbdYj4ywGx0hdiY5pDlA0uc4qjBz3u5Yg/3nj0J3qVGWiVaWXOFDdCoHEEyhFiT/piZ11x+I7/7Thd/KnuJGedV665i3eWn/XT05P3b/2cM5OPetKV6vGBXhR7Opcz/Wy3F2eTLf463PW4mGqzQlAQxXmudfR4dp8oTvP5nYYfJwzDBQhUSKAc/VFhAUxStRVid9PBnpW3V9H3L5YZiT7py0GexkG+t3N+rXd3G6pMK2PxuQ0CDSVQlhCb7BRiSg8us9Y/GeA/L/Ug1qlNjDIYIeYYQMiQwOFvKdRZNqN+8XLm5XgzZETs8NbMF+P99eggbXgw8nt1H21ZC/lWviIc/e5T8OOjQyIDrSaAEPPNXwaIW3HaT1efT6b6dnmvHx/t09JHfX93q6epUwn7+jZDz2R56RJ+HT28uNZ3D496vV6bNFf6bjHTkzP3k+nhzUPqD6PKtFIzwpcQaAGBsoTY7hEx87CmM9TptUF2Azxcn+/u2DZBiD3dJkZR8k5nfFpcJqbC9UY3GR6SZbfHvnc2WUjcXw93+GpXnw3Henp9o2fzuZ7dXOvLyVif9brOcOPb6OT/JvMLfOsU/DjIK68QOAaBMvRH1eWo7YhYVIj19OR6kfqkd31/o/uxp8XBk7TB9C6d6+om0WhvwnaHepki4u5vXE/8znVyIoWfhSrTSi8130KgFQSOKsRMnTRZpFQimS0Qn6a0HfGJjIo1QYitbxN1eV4htsH6/KRXDw/6wfxbPdZoTqJv86YKifXy0imm7Dq9y9kydR3j+vFeX02S67TbKMROwY8zV2HcCIESCCDEfKhlgLj3n/4OcmyC8XSbXBhuBdWuRnwurrvoZ1rYvbyQR9ImjmG4KtMqweeJEgInR6A6IdbX45FQH5xd7T0Ss75Ldm67gzPdi29khBA7Gf9sphB70MO4TwYPSHtjHZtdmG6rx6WehNaJj+btGxFLB8S3EIBAGfqjaqq1HRHbgIhOCc/AZqVH0iLtQdpOYvf6PGgoQq9nU+eYViwfcvjuaB67z36U7y0nLSF5LkGghQSqE2IDPb+7SUyrs6MAs2gfMrcVbs63I2DeSH9HT29nibVUdrOOQ4y/5c6gI0AhsXGoETFHnupyuRCbumTekQ/n9NnuyD1LxBGXd/lZL64m+uxsnJid0kR+qSj4EgIQSBBAiPlI6gRC3FWsO3buJCY9aVbqTO+YzBhxhuVFPzkVozNK7KBYZVqRDPIBAi0mUJ0Q6+vF81pfCZv+5N1sImKup3lS3HUv9JPZ1CIxHbsJQux5kShXb7KIIDn6B2Pnp8dHs1bZ/DO7Oz7nfmhY1tb+3m6Tm3yZvD09rfcejc3O2jwIFUfD9n8QIeUhjxB7tuu7fXtZJmX+Pa+fPL8I0su962eZuTNxG2ddv+xIekj/KN/3tnY0ewQYmxb42ZUMl+irJlAn/VG07PUeEStQKlGIpYyISRtndIazXCk/302TQkx19U1sL/sq08pVAG6GQIMJVCfEevrW9PGe5sLa0T027ZDqjfNrU7kYwZLYGnyXEHtc6PH5mR4MBt6/s6G+cR3UJPnE+k5fDEPhB+f6auEe7svUWX5+MBsujfRoZP+N9WgoTO/sDvRobL7b3BPcO9JDs+HD/EHoWNs4R+ehcqbnc1PU53t9EWJzZs6wilbhT3pxc6nP+vKGEr3BUF/N7zJ3DjOxkWwQv7Z+0POrC33ed20g1dH9s5G+MmuzyhwtlcpjR2/7F+WIaCm96DKEJ317faEHvfhost1Ex2wWMrrUtw8HIGLWIi7nV3p0PtBdUYh66Q3OrQ0W+jGPeijix3H/MJ+fHhb66mJkWEi+29G9/pmeXM10bhwV+N7j/a2+ML/lXlewozJ5N1O0J9MbfX8AUwrouFRzAggx30D1ASGf7ROtnMNetdaX/eQ29Lt2PQzHsHkvbCttG6BxZJ1YlWklcsgFCLSWQKVCbNMZuBMPXS62aYc0ndk/D0uYwrdrauLT7Tjx0EieRi27S97wuzvLppMo5Mmbfpmsm6Xr3VHygGgpzl3lTIbpvqwTXi2uEqN0Ul4218wmT1n2Z8nCRrZCcHWt55cZdtIMTbm302Sni6i8DGLb9zU5fdba7/Bn6QX5TOO3us1+ftlgMs8snoO0g9fl9Vh3I3yz+GxXj6+XQRSpr0mfVHqXH0ciXJuHC2eS+HLn8/xilrqZihd/Fb630tOh6+GCnP/RdZ65TBFSfDhRAvXRH8UBNmtE7HGWfEJsKknntCCpI2Puv7wTnrCmMn7S0plCkTPMqkwrNa98CYF2EaheiGktjswX2LTjcS4JJ3/EXqpTdoyIpXVes3hF3vBZ7pfucYocodMrPWiT4pTuC5c5Gaavl2b0YnGZ3MFvd/4GO49NSaa3e2OpbX5XeiI8RNydL68DO7w6cIf1WX74oAr4/LaM6e8kfoOLub6d5hWnlru0pjst/Uc9zSlw4rbpDq93Ch6pjLv8OMj188Ms+8OD+O/qLG1dfRW+dy+v94/nM/65416GEnDhtVkEEGK+PesBYq2nwtoM+0QuMjAV9kHTkUlM7Um7Pxw28v5ZXycW08ca1SrTiuSNDxBoN4FjCLHnhyvhSIy8a2XkUfRpsPVcU4TYniNiHWFjpCIdWClMf5DviXyks23WJqeNPUnpZetkm45w6mHidqqZmXrqnKroibHRjvMuc9UaD9eCvys9nKURyJVC4maJX4R/vJO+4/M4titjIsGXC4/6QuxryKM0aXnqnKeLMamMmXzkUVhXuqP80Xx29PWDNIeyGt+Td5f2+HZ7Pd3v93VXnKpY3gjsi/l5UysC9dAf+yFpyIjYo75yDGF30550rZOLwpXZZKPIAayLSXLDjkiFWWVa+/kEoSHQKALHEGJmwp2+EDrLztF5ibjUue1dbNf5NESI6eeVnk2nerr5d6WnF8Nkp7431NMr893Lfd79l5dXerFKzmAo0oGVwkQ7p15H8Gw81bd3D5sNGR7u5mZdWbLuD8KlnWEppRdpMySfMNdcndTOwKyXu19Fp9k9P5rpi8PEdFQvf/4UV0c6eS4/SusizTrpfXcLTcuDxC/gvn3t6OHFtV7em7PkHu71rVnjN3Ct4wr/tlISdvG3aQ7surPlg7eRxGZDl5VezK7M+j1pfZPnT2lLIaQy7vaRJ3HJhcekry9vzDo1s2HJ2m4qsvKYnAl1Vfy4AIvEVfaD+p5U71m2kxu9im18Ys+cm03HoQfqw0L9txRz81XNCSDEfAMdC8T6cbVZjNt3VqzpTyTFXQx7xbZ/XkyST07DFWaVadX8d0P2IFApgeMIMa0fboQOcI5NO6ROzzC8A1BThFjcGw6wa2KRDqwUZtuhN53m3kgvHTstrObyGZZKuTuGUnrhNiOOZfN5dZMUqaaT2jfrnNL+1vfXoc6qJwA2wmF6mCmK4lRcs/uwndpZ1p/EL2Kv/ljL+9C4ptYlN9hK5H0lj/wpNdAzcQRpG8PySqgPNqNUh/URJ5f+RKdl8X52EVnvNo0v0ajI96TzYLujHRuomQcOs8ux2XCknI1htlbkXd0IHEt/HJLDCYyIrfWNOSS12+3pnhmS9v51dUcSX53OSyPVGaRXOhaiWGHtWGPhgn83Ta4jCDeqVablyiPXIdBGAscSYtqMgg82Ha1tx9d2FDNt2mG2pk+GjXVsmyrEhHKF69IsPizVt7vikMIEHfuOWTOza1O2hXSMibG3a82xlN6uPErivJNxHdaTsN7QzgA5xORBaUaIyjjClMWe0j0Sv8BeO9dfSUdCGFsNLtOF6XwkbXxhphxnhLi4EHYENem6pkVKZUz3EccSDXOOW6aZPk9LPR6YMpoNZ4IZ0AH7qnwv+TsyZybGMxNkitfWE0CI+S5QKognaR1XtGMTVL7ea0dfzO4zOadUye3adcwV8Xp5kZz+YURdsLFzlWm58sh1CLSRwNGEmIE9GwodtwwdZ+lg3EQHTBAsu+ovqR5KxJviJHnD571/k7RQrjx5tHEUSVcKs2lTzPEnu0SYh0zesMK1EYSUXmo5xd15zVqejCJAG8k16ibbzsTIh1eYXP+LQqzgQ82sCUv8rL0651c7N8GwaUi/zVT+jgcr59eZJI5fLNkGrk1NpDKm5tGMWkm7OF4sk9N3s3Le3Feh70mjq3vnP1dhufmUCJSqPyoCUf8RsdxCzDQ09owQM49/17kSUiW3qyPjsou0u5ldiBvMzKgyLVceuQ6BNhI4phATpySbDYHS18486nGiwywsnhcEy676S6qHUjt2MYfJGz7v/ZvkhHLlyaONo0i6UhiVdSTB5ySOmJhNO4IHcv5tmxcpvbRySg/7so6GBelKU+jHt1LughDZXmsjxMzSgqy69FHYJCaNvzRlzk5JzDv98v4qOXtGqfPECJQln9dHVjPpDMP9Rz2r9D2pDJ2zy4wPQ7L5K3c1hwBCzLdluSAe9NA85YqOemX93NGTuftplVTJ7erIuNxXjCu03kz8vuATQzGuUFquPHIdAm0kcEwhZkchkqIq5UgNY6D18jJZ3/Uvk0/5BcGyq/6S6o60zmfcX/KGz3v/Jj2hXHnyaOMokq4YZpJvzYn0QE4dSIhJB3unbQYSt539LG2q4ZoWJ4V3XauLEOvlsJdo75TNvZJT5uzo240Lifu6uBmFvLGJnMfkuXlBYtJo0iEO1K7S99YLx3pLs+bPtUYzKD+v7SNQrv6ohmf9R8QMh+enB71cLiP/FotbPbue6vHwzH2avS/ghtfyVEWpktvVkXGZhTViLjJch8BxCRxXiGktPgF3btohH4UxmgvP+QXBsqv+kuq8PCInb/i89288RShXnjzaOIqkWyRMwrPFtUfyltp505uPhA2hRlf6dj7Xs9ls9z9z381F8oytvGwTZTYXaiPExm6Rksi3NNsmtJwger9de5Xc+bCYiH3QI2GNuzQymc9H5J1aM61JjRY28ala35MfXgUP4+3OlIv7/UdxE4XkwkkSQIj5Zjs+iGd9N7sUd4XyfrwdHd5sLPA2qZJTBUeWpCkf4QauyrSC8vEKAQhofWwhpsXOuWPTDvH8HzNtSTKkIFgQYh4oqb4N18cSziJhEvFINjFTUefCIrN86T3tODss6yyR5H27uCTKKFxwCbEyu8v5+AmZlmzlbP9l/mPnIaVCei+XZMFUlhCT4n3JSqY3ctkDYbTPq8v3nu+lcxhjvtsbbLbiF35amUrFTc0gcHz9sT/HkxgRy1zM55TT2M0C+fhy1fXdNDkFyPmkOj0XUkMUrmSqTCs9p3wLgXYROLoQMytFpQPfpQX6S2FXNed0K6kjuWO6876d17zh896/8UyhXOG6NIv3Fkm3SJhEXqRRFrOOaBFvfEzAfOnJnfd9OsFB2LxsE2U2F6QpcUr19a1Qbil8kWv5+AkpCH7mfpAh8y8mch71JLEGVOmLZVJS5CujnMfLfTfqMKuzpDMRA//Z5zXN956WU3HjkWR6XT2azllDJrh4Gy4hxHwr1wrE48wxMtbTiYdX0iHLjqeXuxxaEmLd8DSJKtPalVm+h0CLCBxfiNlOt7CramLTjnt9nlgPm3K2Ua6OpGfwfB27pJPkDZ/3/k2KQrnSOmzJXOYVOYdhs4lldZV8uGcFSbKPXRshdoipa9IGC0p19FWJ244X8q2wswh+Vo0QWwm/c3mEPF8ZJcG0a2OgMBDXeyne2OhUot7K9v1O31vf6+lY2txEiL9zrhdlDsG68HD9qARqpT8KkmjWiJgPQVpUa5+iJJ44SRWxSun4OCGbiqqfrBhG4cNFqkzLmU++gED7CNRBiJnjnfVQWBcyuFy+GETaSEGZrdODnVdfbgzeSHUKI2IbOvk6sB7QImECU7y85njgli89eXpYf3Kj78z66cViUejf3YOgEF8Kk/3NszS7xLS5eTcTyZ5iMbEdiT/X70cWI8VGxLLHlddHpJGrYuvYwqRq4Htmn4Cby5HjIXu473Wu75wVZrhMvG8KAYSYb8m6gZAqr40QW8QaHXEaidKjed7HKvdiJysyf7zKtJryC6McEDgAgXoIMa2lncfUy1Totb4UHuakdvRydSQ9kFLdmGe0KW/4vPdvcimUK08ebRxF0i0SxqMa+l+s581B3MIUvXzpyZ33iTTnMZSdyt6K50yZDrJz84v9c5aPn5Ce4GdpI2KTXrjD773fOaIjJGv2rhTX+0lx5SujLJgm0nCsmC/XxTr53rO+X9zokT102jEK1x3NXQXhegMJ1E1/FEHcyBExqfIShZhj7nPeRl+L29H2Y+sC5MqsnLSKuAJhINBMAnURYvpRPmx1sjCPcFfXupPoWAzNOFrKX66OpBePVDfmqYPyhs97/yaXQrny5NHGUSTdImE8qtv/pbOpVO9CXL+SNz1pQ6hDbE2+zf0+757NroJJoWLb3cs7QYXuk5QfNi+/RJKCn7mFmLzOMzyinYjfdUHcvOcQG7rIOzsOpZ3KXHlzXK+j760WU8cImTnbrRyXc9Dh8jEJIMR8+nUD4TqHQhqiX170k09WnDsnye4mbV2vhHN/qkxLzilXIdA+ArURYma7IKmz2h1e6ZtJsh7qh6YtilbL1ZH0YpAOpe2OZmL00sWnvIfgCmcC7RRVQrl2holltkgnXQqTh43NwmwkPKl3jApJ6aWV8/4qufW8nbpalz6nOLXWPlwoKY95+cVcxBzYd6v78YcfKVN7xfbbYdtEWqELq5thss/RkQ9dzltGaa261BcJZSfT29r63sONIMZkUZupoNx0cgTqpj+KAGzkiNhsKDSGZuHw9UNy8rB0YvxmkbFwrwxYXvtxNr1L3F5lWonEuQCBlhKojxCzB+qOk52weGdw8znDIvucHUlrfnH3VrVj5C3wm/VSnwl5TRMPeTuSm6SkcuV8OFYkXSmMHdEZS2e4BUwir3ciH9eolZReGsvnO+Ggb7u5VN6Z9JE8H/KDtNmMN0omtYeZU14/6Plsru/jKwuKiPxwopKfpQgxyV5eXyEc6a73a3E9uWs6nZRmmo/I9Yt8WPSunIa/r6/vmZHKs/j5bvIupeHy8L45BBBivi0PDuLpTl9fXevlKimcdrqPOE3QNAaOJ07aNbc941M88UmRa8OPKtPaCYobINAOAnUSYlrLnfXEeoeza/cmHYHZcnYkN8FMmJ4gpqT1KUEym9fnO3EdrM13Wscwb0cyyGNypGKshSOtI1kMfyiSrhQmsMvF7W61I64BdDwAtHmV0ktj6drwpTeuz5qYu+nA+aBheJ18OBm2mfT+fn75soV5d7KI3JKfXyR47hExd1/hMvOo5GomP4iZOqZv5i6juEZR6ewju2s9M4d+dzpnMYEvP3A+vu9JU0YZEYt5eqM/Hlx/HIFWLUfEwvORzybX5klYNkH2vJqLTyRtY9q/WDrx3ogjaEqfTd1hbGRPi0thXYc3FcOV4yrTchaYLyDQIgL1EmLmzKVJz9lZfen4xzcWkuxVRIiZo6Gl3RvtpiH3Uhr22upWnwk7PgZ5TRMPuTuSNj2xM2m2Qk9dMGcDbv+KpCuFCcpoX0c3TkL6aSmNVpm2IGUkT0ovjaUtnSz2lD7f0VZtyXjv1qu7zSjTw8HnNbpHxSzD/uhKZ0nz8W5uNmSIjnTE12MV4RfhUOD3Mx/Lv93eePf0XnsuVnIdqPUReQ2hzWv+MkrCxKRh2J9fpQvh58eFHoU2JIlvWlaN7630xVlP98/G+naVwTlNXZF4aGOOi6jLHjYRf+NDKQQQYj7WQ4OQ5jn3zkb6er7Uq6fkj/Npda9vzFOccKMZfW92rXIpI1OGZ9co2qbhmOq7VXROxPPTSs8uXemZ7e9TpjVWmVYpXk+kEDgxAnUTYvLmPl5naVNvuUbv49wLdCRtFOJaF1PXqe5Qz+9DIz/Pj/r2aiR3Hu39/r808ZC/I2kyaEbfpCmQypwTdPsyS+JZr+5u9XQy0TfLUJ59RkXSlcIEZQxee+cXZqZGqD2wjKajFxbBfcFr5AgTP2/Bi5ReGstNOHF7fM8WveFlNG9BQv6rbbcWsys9DO0417uIjjLFghT6uHaJ0pDP9M/H+np2q+8eHvTj46N+XD2Ybfhv9fXlRA96UQEWsOxNbiP5KcQvHEOR3485p7QbKkeQN/vaGYz1/G6VGMleP6b3T9IOXC5SxrU4hdXzkb71kdiRBU9GlF9N4md1dXRilK4K34ttZDIYXepFLL+BCdfmAdFQOBjbveFKEJLXJhE4tP44Bpv/DwAA//981HWBAABAAElEQVTsvQ+MI9l93/lk7d9II2PkeDc3Y2VnsRbOzkEMvIKtGKd1QvmQtSLEVJQ4Z3hpx45iShfklDYOsa8DnHztQxJ0ckncQWBwdYioi9XGxS0naiFOazduKe5VcFSCXsO9CLh36s1wLHNgjuOehCMdJ+5R3r0iq1j/flWsIquKxeKngRkWi1Xv/d7n96tX71vvTymdwd/Nmze1Umryz9pe9u+s3Zyl56Tr+6zVdaPR1M1GQ9fsfH2/B/btdS/mmnR+sBWfZ72hm82mbtRrscdtH/VLlddcYzgAAhUn8NJLL02u2UcffTTDko50pzGt89y6p6FPR0mykM5102odnCdJROvxqW4G6jpVb+u5Jlwc63rwPO/3WsPUr/XYek7VXHsbe6eR9o7O2qF04o53EuruRuffCNT79d2uc9rsc5F8pXNc37rlneyz7gfGjsjfLZ7N/VhfSPklYTM43onP19i2tbOr99ptvbe3q3e2W5H3rST5zaCm2Bh2w36PZeWNv4jtrUP/vXVRfrNiLHj99PZb8fxN+6TZ2tJbW9HcHRbNztnMHGljsTJe6qPt+HaKmrShGrruuY4dm5zPXaHdlHvsGZ80JP/Xm3p7d0939vd1x8T0VjO6fmifzm/vSazZt54EstYfq6Cgssg0axDjXie+opMu1Ih9O0cJGzV6bCqv6IvbqZziPpvtcINA5ltkXrIF7IXAphAonxDTehjZmE4q5oz3FmxIWn6f25iMqE/b3TO93/I38uIa84s1JLW+7B8kvge09nuhUF4kX+kcpYwojWARdy9QtR19fhkyy7dDyi+Opffks3kPDhPa3GjHCwFvnmm3R72DeMGf0EaLc2PnKCRql+E3KcsS10933sPiBGVrJWgvLF7GoW6HHhQFHibE2tjSvbHs8VxjL0qIxdrqlqu+eyIbzd7KEshaf6wCVCmFmAXi/Li9XCVe39LH/bnPhgPMjUDandMbF1Eh7BykvaEVmVegmHyFwAYRyEeIXeh23W0ATBvlDd1NWuVc9nRLqEtq28fJPTMSnh6bHrGkz4PTNSab+qhnFW4cauDFiYfR6V5IUMUd7y38aWdOz4PNT+wRWyBfqdHb7BiRZzhvxfQchARZY1efRzRiveVbho2VzqDbWe4eWdvSuXcejM51Z2tOz6FwHcyYmvv40dnQi222vSw/y68hkV3fS3z99I52Q7E9szuuTKqm2yf+3r1ZoQIby5VxqPe30j9crjV3dW9OJZJn7CW97oOsW3vHpnbib9MIIMRsj+cHYqR73UO9a4ZWJBmCaF2YjdaOPuye6zkPI2Nj9eK8q9vbSQRZXW+3D/X5xeK5FZlXbKH5EQIVJZCPENO6uxdsYLb0WYqWQLjBUdeH/RR1yWVf7wTFYCt+OFzQxYPugW7FDreu653OsadxOtYHLb8AbVliJepveBJq7MYeH0inf9LRjTgRZMTEyUBgtkC+khBzReNIn3R24u9D9ZbuHJ8lv/csYGMAj+k6HOqTg705PnT9VTPDFrd3O/rkrJ/czlCm6XeMhj192NnVzdhYs+00Q2O39/Z191wWYLPcl+U37umtgGCyelSEaJplGdoY9fVheyc+Rp08zPC6vYMTPUxRR+hly2gM7p8e6u2YoXyOoGls7erjs0GoiJE7coy9Uf9Ud3a24q83m2tza093Uz90jywVP6wZgfz0R3Eg3mRlZS7Epf76/b56+umnJ2kYKOrGjRtLpSef/EDdvXNHDYe/o373d++ou1/7/elhjzyirl69rq79oSfV9etPqMceks9eaO+De+r2rb5649bAzU89ot569Qn11DPfpp669oTKLLsi81oIBidBYD0JvPzyy+r5559XZo6Yun//fqaFeHD/nro3fqDUQw+pK1eupK4PvOc//viVheqv+/fuqfGDB8aEx40Njy1Uvnt3bqmv3PwtdWd4V1k16yOPXFXX3/mMeucz11Q4xQfqnsnTZKkeMjZfmVfpPrhvjh8rc7ix0Rx/JW2taer+27fUza/eVv/x65dKPfywestbvlW949tMvf/Elejypsz33msvqrfVPupLzwgx9dmPPevuM/X0rfOvqDf6d9TXfn9CSl198rr6w0/fUE/F2eKm4N9KaaP/ZP+3+/fuqMHgt9Xt24H741uuqm+99ofUk9evq6vzfOVPMpdv9+/dVcM7Q/V7/+E/qa9PGFrx9hb1zX/wW9Tbn3hSPZEmhpfm54nlJa4fC9S9O7dV/7e/qn73zl07NqxyvVVdvX7NxOoNde1q+EpKBHjpMk5zeWC43+rfVLcGbuy+9aoVG+9QN566plJflh7j84s969ofqN/+nd8yXL8+u+Ysu68Zu68vabenCGyuKYFi9Ee+cNZIiOULgtQhAIFqEshTiFWT2GaWKpEQ20w0lBoCEIBAKQkgxGy3VAFEKSMMoyAAgaUJIMSWRrgRCSDENsLNFBICEKgQgSroD3rEKhSQFAUCEAgTQIiFmbAnTAAhFmbCHghAAAJlJoAQs71TBRBlDjRsgwAEFieAEFuc3SadiRDbJG9TVghAoAoEqqA/6BGrQiRSBghAIJIAQiwSDT94CCDEPDDYhAAEILAGBBBitpOqAGIN4g0TIQCBBQggxBaAtoGnIMQ20OkUGQIQWGsCVdAf9IitdQhiPAQgMI8AQmweIX63CCDEiAMIQAAC60UAIWb7qwog1iv0sBYCEEhKACGWlNRmH3f/9U+px7/zJ3wQartd9Zs//R7fPr5AAAIQgEA5CFRBf9AjVo5YwgoIQCAnAgixnMBWLtn76rUv/HN1+ltfU//5P/9n9eiV/0q9+7/7k+pdTyz4It7K8aFAEIAABMpFACFm+6MKIMoVWlgDAQhkRQAhlhVJ0oEABCAAAQiUh0AV9Ac9YuWJJyyBAARyIIAQywEqSUIAAhCAAARWTAAhZjugCiBWHEtkDwEI5EQAIZYTWJKFAAQgAAEIrJBAFfQHPWIrDCCyhgAE8ieAEMufMTlAAAIQgAAEiiaAELOJVwFE0cFDfhCAQDEEEGLFcCYXCEAAAhCAQJEEqqA/6BErMmLICwIQKJwAQqxw5GQIAQhAAAIQyJ0AQsxGXAUQuUcLGUAAAishgBBbCXYyhQAEIAABCORKoAr6gx6xXEOExCEAgVUTQIit2gPkDwEIQAACEMieAELMZloFENmHBylCAAJlIIAQK4MXsAECEIAABCCQLYEq6A96xLKNCVKDAARKRgAhVjKHYA4EIAABCEAgAwIIMRtiFUBkEA8kAQEIlJAAQqyETsEkCEAAAhCAwJIEqqA/6BFbMgg4HQIQKDcBhFi5/YN1EIAABCAAgUUIIMRsalUAsUgAcA4EIFB+Agix8vsICyEAAQhAAAJpCVRBf9AjltbrHA8BCKwVAYTYWrkLYyEAAQhAAAKJCCDEbExVAJHI4xwEAQisHQGE2Nq5DIMhAAEIQAACcwlUQX/QIzbXzRwAAQisMwGE2Dp7D9shAAEIQAACMgGEmM2lCiBkF7MXAhBYdwIIsXX3IPZDAAIQgAAEwgSqoD/oEQv7lT0QgECFCCDEKuRMigIBCEAAAhCwCSDEKgSCqIYABKpJACFWTb9SKghAAAIQ2GwCCDHb/1UAsdmhTOkhUF0CCLHq+paSQQACEIDA5hKogv5gaOLmxi8lh8BGEECIbYSbKSQEIAABCGwYAYSY7fAqgNiw2KW4ENgYAgixjXE1BYUABCAAgQ0iUAX9QY/YBgUsRYXAJhJAiG2i1ykzBCAAAQhUnQBCzPZwFUBUPVgpHwQ2lQBCbFM9T7khAAEIQKDKBKqgP+gRq3KEUjYIQEAhxAgCCEAAAhCAQPUIIMRsn1YBRPXCkxJBAAIWAYQYcQABCEAAAhCoHoEq6A96xKoXl5QIAhDwEECIeWCwCQEIQAACEKgIAYSY7cgqgKhITFIMCEAgQAAhFgDCVwhAAAIQgEAFCFRBf9AjVoFApAgQgEA0AYRYNBt+gQAEIAABCKwrAYSY7bkqgFjXIMRuCEAgngBCLJ4Pv0IAAhCAAATWkUAV9Ac9YusYedgMAQgkJoAQS4yKAyEAAQhAAAJrQwAhZruqCiDWJuowFAIQSEUAIZYKFwdDAAIQgAAE1oJAFfQHPWJrEWoYCQEILEoAIbYoOc6DAAQgAAEIlJcAQsz2TRVAlDfMsAwCEFiGAEJsGXqcCwEIQAACECgngSroj0x6xH7jN35DPfvssxMvfehDH1Jvfetby+kxrIIABDaOwO3bt9Wv/dqvqTe/+c3qhRde2LjyU2AIQAACEIBAFQl87WtfU//0n/7TSdFeffVV9V3f9V1rV8xMhNiXvvQl9dxzz61d4TEYAhCAAAQgAAEIQAACEFhvAq+88op673vfu3aFyESIeXvE/vyff5PpEVs7DhgMAQhUlMBgoNRLL2nTI6bUX/gLb6poKSkWBCAAAQhAYLMImA4x9cu/rCeF3ugeMf8YzTerGzc2KxAoLQQgUF4CL7+s1fPP/xf16KNK3b9v1Bh/EIAABCAAAQisPYF+X6mnn/7GpBw3b940+uPG2pUpkx4xhNja+R2DIbAxBBBiG+NqCgoBCEAAAhtEACFmOxshtkFRT1EhsGYEEGJr5jDMhQAEIAABCCQggBCzISHEEkQLh0AAAishgBBbCXYyhQAEIAABCORKACFm40WI5RpnJA4BCCxBACG2BDxOhQAEIAABCJSUAELMdgxCrKQRilkQgIBCiBEEEIAABCAAgeoRQIjZPkWIVS+4KREEqkIAIVYVT1IOCEAAAhCAgEsAIWazQIi5QcEWBCBQLgIIsXL5A2sgAAEIQAACWRBAiNkUEWJZhBNpQAACeRBAiOVBlTQhAAEIQAACqyWAELP5I8RWG4jkDgEIRBNAiEWz4RcIQAACEIDAuhJAiNmeQ4itawhjNwSqTwAhVn0fU0IIQAACENg8Aggx2+cIsc0LfkoMgXUhgBBbF09hJwQgAAEIQCA5AYSYzQohljxoOBICECiWAEKsWN7kBgEIQAACECiCAELMpowQKyLcyAMCEFiEAEJsEWqcAwEIQAACECg3AYSY7R+EWLkDFesgsMkEEGKb7H3KDgEIQAACVSWAELM9ixCraohTLgisPwGE2Pr7kBJAAAIQgAAEggQQYjYRhFgwNPgOAQiUhQBCrCyewA4IQAACEIBAdgQQYjZLhFh2QUVKEIBAtgQQYtnyJDUIQAACEIBAGQggxGwvIMTKEI7YAAEISAQQYhIV9kEAAhCAAATWmwBCzPYfQmy9AxnrIVBlAtUQYt9Q9+8qNRgqdWmc9fDjSl1/SqnH1Jur7DrKBgEIQAACEIgkgBCz0SDEImOEHyAAgRUTqIIQe3DrG+rhG36Q9bZSX/gIQsxPhW8QgAAEILApBBBitqcRYpsS8pQTAutHIHsh9o30EB4odX887c2yTn7c9Gg99NC8ZFyRde/Vb6i3vdt/fGNPqc9+zD3G/+vUxluvKvXFs+kvb327Ut9dV+qpK9b3qPP8qfANAhCAAAQgUFYCCDHbM9kJsQUaOMaG1z+v1Iv/TKmbZtiO83flSaXe9b1K/eSPK3XV2Rn4vGMaKf/Tzyl1z7P/j7xfqY9/xBryk/7v9itK/czf9af35z+u1I88O02r2PxoaKX3IGdUkcBKhJgRXq+fKvXyS6bX6l8pdfjFMNmaEUXv+xNK1c3nc99t6qlQpeNew/deM0Ks5k9jnhC79TmlbjT851jfBlqpawixMJhc9ph7mrnBfKaj1Ku/Y+4rIR8nz/T+faX+3F9T6tnJDc2NjeQpcCQEIACBahFAiNn+XKUQu/tlpd7+x6IDa880hj5mC6HgUa9/Sqnv/IngXqW2j5T6mz8Q3h+7x9xsP/g20+AKHFQ3T62/8LHpzmLz40YdcAVfN5RAoULMCLDP/yPzQOajSp2l5N3aVeqn/welnpn0WFknu9fwIkLsM+aB0g99ImxEd6TUe664aYePYE92BL6hXv0HSr37r2aTYqNtekGNX72xkU3KpAIBCEBg/QggxGyfrVKI/fU3KfW3YmInTohZTyol8WQl1zMz4r9j7tAhN+MvmJ617/9Z97uzdTw0T72fsL8Vmh8NLccHfG42gaKE2N3XlPoJ02sVfBiTlv7eiXl49Jx1lnsNLyLEXnyfUh8VeuLOzBDJdz3mpp3WvvU5/huiqfdMPTz5e1ipK3N7qJbl9A314geNH5YNCtvkaS+o9WVZu+wE+YAABCCwxgQQYrbzViXEonqYvDEVK8TMgW/8klLf/oL3jOm2++Qx/Ftwz4NbZhWzG8G9SklpFJcfN+qwR9iziQSKEGK3Pm+GAb4/O7qHfaV+8Cn3Gl5EiEU9HNqcHrGAEDND+z7yuFLeTsLWvhnW/iNxfnN9EHdU9G/fUJ8yQuwnshJi9IhFo+YXCEBg4wggxGyXr0SImaWc3/d2MxF9TtjNE2LW6T/3R5X6WWEcka83KyafqBvtuelVe0boVSsmv2UbEDEF5icIrBGBvIVYEhG2taPUf/s9Sj151YD7ulJf/YpS/9YMgf75iAb6tN5yr+FFhNg900P3XtND563aGrtmvtJPm4VCNqJHJSDEhBEJbg9TVEC7Pog6In6/LMRqTaU+bOYFWvO+kv5Zh/6ZnzS9mVYMbYT/kpLhOAhAYFMJIMRsz69CiH3up0yP08/PD70kQuzeqyq0Itkk5ZZZ5exFq9ES/Xf3FTNH7fvCv+8cm0U/zNAg6a+Y/JZtQEiWsw8C60cgTyF2/3WzAuJ3RjPZN8MMP/Rc9OI/1rvBXv5lU5eZOWXevyyE2CQ9M2ftzh2lzId6yPQGPTFpxFu/bEL9EBBiRsn8qGHw6QmY6X+rEmJto44/8i6PIak3N8F/qaFwAgQgsGEEEGK2w4sWYpKQqZsnzv/7t5tJ0YFhhkmEmFWMqInt826Y4hy1hlKjz5r5BzEXRP75caOOwc9PG0QgTyEW1butTB3Q/4xZKj7uKY7XB0aQvfg/m7lE9ri53a5ZuOM97jW8SI+YN/nwtpt2+Leq7CmvEEt6X4r2xCb4L7r0/AIBCEDAIoAQs+OgaCEmNX66ZgL6N/9f4VUQE9/wzFPjP/qkfxjPpHh1pYZfME+S7bJ6P14388u+MyD8rN8P+maZ4ae8RwrbuefHjVqgzq4NJJCXELv9eaWuv18AauqMvqkz5lUBwpnqtc8p9Ukz3vojP2cWC/KsbIgQk2jN24cQm0eI3yEAAQisMwGEmO29IoWYtNiFM+H6NTOMsCYO8UkWZq+a898dON86c8vM4/j7PxhIQ5hvYB1R3zXL1Zs5GEn+8s0PIZbEBxxTfQJ5CbG//UfNMvXeCVg2ypML816w2RDAZfi613C+QiwgWGJMtlYcfGCNczR/1gupHzfd/vM7/dxyTM+0/k+e5wMzpHBsHrRNhleazK7EDTWYZODkF8jDJPCjZqXET7tGiAsqeX42m05a/r3Jv8lzxBI/IIzMKGhXoKwR51ks7xmWlu/8HL3pLZtWRObCbsce5ydr+Oz8lSydo702O/uWtV1K00mbTwhAoGwEEGK2RwoTYmb4zgffHlge2kxGH/ym9YJSpZYVYtad/qfMjVqaetYzN6/veMwNwVfME+vv+1n3u7M1XRra+TbnM9f8uKHMoc/PG0IgDyFmLYQRfMGyhbPZUeoXf9zayuLPvYYXEmKmfvnM31PqX75h2/IHlPrAXzSrMU7mJrlpx4oi03D/8sumzj0wrwnxKhhP8Zpb5n1lHzIPoZ6LGo7tzcs+8cE31C/9TaV+fWB//xazYJKpU68ZgTD5M7Z/+V+Y3sFPmlUOzYMw35+p87fMSIQfbZqXG1sVf+jPzs/k8ZlfUOrfmzJM/sznzwTrbNN7uftB86tzjHOo+f78XzLvW7sm2G4fk+yjICE2h+frn1fqb/yMEaHeBwcWxw+bxao+ZvnNU86l04ohY/xqvej8c8ann/9Vs9iW1x7nNGNX6wMmVk1v83Pfa1507sSE8/vs02Ozs29p24U0nbT5hAAESkegCkJM6Qz+bt68qY13Jv9u3nyzSXHRf5Y50f+Otqd5OHlZn+bJ4uycs3b873FpO78Nj8NpWPmYSd2zfC778jGm52x2jJPevM/88lvUB5y3ePzCrozsXnrpmyZ106OPWtdnFj5S+lioi6x6wiwNn7oOiK4jXFtHZ+E6Z1onucf4y6b0yNSN3rrS2jY99rZ93vOcff7P7n74/GB6we8Hxs5webx5Tbcl25y6fNA19a2xNZi29L1l6vzL0D0jOg8pjah9U1Zh2/2c5/2udKcRLotT1jAriZ+0z59vHM+DrXD+3jJPY9ZNb/m0JHuV7h2Z+EvoV699e+Y8mZNrs+OT5W0Pp+mkzSdsiIHyxYClOZz6wtIi6/hn1XBL/xUhxMY94WbS8t+EsxBiVoUv3TgtRx8NpjeETlOwpa70MNQgiLqB+Pfnk1/5LhgqMXyyihjIXIhdKm06gWaVv3MTUKbBGxYF/mtdblBGHePGy0JCLFK8Wfm5aUs2taU6TiqzsG8n9EDKm9d0WypPx9Txpx2Bq5DHjLn5zfuQbFqW6Dy8583bjhe64TL5mTq/y/eTzIWY4OuO2Sc9vAyW24zi8MWD6JtUaYXjeZ4YDNoU/G4W49Lj0P3VYex+Lm+7m5bsT36HCzFQphhAiNkSrgghtmuETrByNu/5Mha4/7ISYlE9XlZDqy88ZbbsshoRXlvSbOeTH5VFmSoLbFldPGYuxMwDGTN6KlQf7ZwsXgfI9YXLTGpgxgsF0yMmNM5d0eKmHcy7LfTgeOvehhFprTlCbdeMLHDT9eY13ZZs8+aRdnvP9KIF85N6R9KkW5v0HoZtT3ctr06IJS3r6chi55ZzGd9M0/L6wpTfPDBNakvccTXTC+0XY67Njv3L2x5O00mbT9gQA+WLAYSYqb6tv7yFWN88YQ1W0E0zJMW98U63sxJiVron5glcMM+o79YNYtkn4dnnV74LhkoMn6wiBrIWYhem0S/VBWaRjlCdFKyj0n1340VqYOYhxLpmCLZUtpppTHf7gXrO9AzGDV+c9rRYTNxyONtSeaR8d0wPWc/kOzTi99SIu1ZNts+8LkCPZg/l7PyMfScHSh84/0xaIQFtzjsw95fZMfax+2ZY5tnkQV/YdqcMyT5lIWZei7JkrPjtiuJZC/Bqmftax3DY9oijpEIseVpu2aLiyfJ1ywjdU/MAc2R65C6Nr0bm+jkzDzO2Y0S+eT+nh5ufgeWPLDkk82/YBs6DCTFQXAwgxEyVaP3lKsTM07qm8PS5P7vpuhVzlkJMm5uDlK/UWOhm0QDLPL/iLgQqHViXOQayFmKnEWKlZxqT6YTWvOPduJIamJkLMSM8QkLF1L3SQy9vOcdGKElzulpG1EyPc8vhxIlUHl/dahrj55OeGicN9zNq2KQ7QsLJzz1nYofxT7BObwgP9Lxlc+xd/FMWYttG/F0Y3gMjMJP8Cz/oc8o4/ZR4+nxpBNnpRFi6TC4N3+Fsn5ve8mnZeUTEk+XnE1NuP2f/957h44sHTxtgMLv3uzY7/lne9nCaTtp8woYYKF8MIMRMVWr95SnEjoWeKfOyU5Nr+F+mQsykL/XEBW8OZul80RbJvnn7ss2vfBcMlRg+WUUMZC3EpHrG3yOTVZ3gxovUwMxaiEm9F7WE895GUi+hafxP58265XD8L5XHqVvl+UAepkZAiMJvVhc7+XnOse4XwsMud6hm4NjZ/cVJa9FPWYg5ZU362ewE7fPbE8fTysOs+jvnPuWmt3xa07y6u7KYOpmJv3ibzkyZJT7uMFTX5iRxlZaDkyafYc4wgUlZYgAhZqp26y8vITY+Fypi86TUP07crcylBtKyk6L3hLlps5uD+c19OufaMU9wxf2eXX5UFGWpKLBjtbFYiBAzdYE7NC6busAbN1LjOFMhZnqLWp5eB6eOO0rYaLbqNGke74Gpw73lcLal8lh5hucBySylodyuqHLiLXDuGgsxt2xOmZwyTj+jeFpMnUWm4u47jl+sz+XTMjYa1lI8bR859if7lGLKXRTHzyAb28NpetmwDR9ioFwxgBCbyLD8hFhbEEFxN5U8hFjfDK9xGiXBT3cp6GQ3lfgb4TSN7PIr18VC5YU/VhUDCDG3DnMb9N54NA+3eu4xTj2XtDfMqdei619vXtNtsbFv5mslXXn2Qlg0KVy2QL28xkKsbobDOpynn36mIk8jwpK/UsVNb/m0zEMJwT9WXKUdvhs1SqQ/GQbs2uzULcvbHk7TSZtP2BAD5YsBhFiOQmxgnpw5DQLn073RBm9K0+/RDQH5eP+NTTjG3Lilp3qOPdZnnDCcm/5s+Iudd6b5le+CoRLDJ6uIAYSYW5e6dag3Fk0D2Qzr89Zr1rY7x0uoG4N1l/kuLWIyHUbmzWu6LTWY58/Xcu0Qz5+JFSc/9/hJXbzGQsyaU+a/nzhljOapzOiR5L20bnoS23RpmUU3OuF4sno7/WVI8N3MJfPNdTNxacXmdGEc12anXlne9nCaTtp8woYYKF8MIMTyEmIRgmTe07SshdhJxBh3X4MlZqhk2ptOtvmV74KhEsMnq4gBhJjbKI4SYtJ8noap/07N3K8Ts5Ld3H/muGOh8T3NLxz3UoPZtS1BA12aJ2ZGUFxMBKKTXyCdEgmxqHnO0j0jvFCHVS6njNNPkefchUi8fNz0lk/LrELpWZXRuV+6c7u8+c7f3jVzDZ00nM/plAPXZofH8raH03TS5hM2xED5YgAhlpMQkxoF/mVr5co7SyEW+W4v+4mcc0OwPhe9wXhvutnnV74LhkoMn6wiBooSYlMRINdN3ms9+bYbL2IDc9ID5B7jZ2t6Q87CDVhX7HjPU3reu8O89V2a7dyEmCCq3AVTnLIFfCGc4/IIHDsRdNY+J61FP+XFOpaduxy0K97XUWXz7nfLt3xacjwtWuaO8F67VEJs1lPqLW/UtsshyJjvsCEGyhcDCLEchJgoSBIOsZCEWNuMVU/e8HGPlSp/60bfEuatWQ2TZRftyD6/8l0wVGL4ZBUxkLUQi1q+/tQ09Bepa6LPceMlunHsHuNnm06IifWP8NApjQizji1UiM0WTHGYBPyBEIuJT4eZvFjHfMHqZy3F06JCTJor3ulZ+bk2O9vR14nfviTXnJMmn2HOMIFJWWIAIWaqQusvy1UTj8w48uDN3qrAx2YoyoV5X1fUP+ulkNLQPmuVprH5zTlvnOBdP0Pz0sigDdb3QzNe/VJ4ymz9tswy9vnkR0VRlooCO1Ybi1kLsaEZqifWD/2kjb2kx7ncohuY7jH+OCuHEJu+uDhsY3R5ErIxdXrwnWAKIeaLy3TiyfXR0r4xvYlZCrFtc38NXm+5xZUg7vzXlcuJ/bAgBlYfAwixqQ7LVIjtCOPBg5XwUt/NzTp2Za6IZZxrO24DYd/00Ek2LPRi59zyW/0FQiWFD8oQA1kLsctz+fpPu7hF9FN5p65x4ye6cewe42edTohJQxOtFzmf98zCC+bh0yL/zs2Dq2kZwzZGl8c5Z84nQsywdbkuzTPTtLIVYtGizi2/wyJLDk6afIY5wwQmZYkBhFjWQsz0ekkv6pREzzL7zsxNPKoRFDXsqGtsc86xhk9KKzktsipUfvlRUZSlosCO1cZi1kJMRzw8sXpksp0n5nKLbmC6x/jjLJ0Qkxq7014Ht95z6r/0n2Ebo8uTMD+EWKmFmCTsF42n6LRyiCuPIPVfT+G8+B0mxMDqYwAhlrUQMzfXlQqxiKVym2Y1sGDjQ3qhqCUO93vhY4Pnzr7nmt/qLxAqKXxQhhjIXIiZoVfSqnCT69/0ls2u79mCD4vuc+MnWri4x/hZpxNi0vzaplDvLVa2sI3R5UnICiFWaiEmTTFYaPh+xMPZ6YPRHOIKIeaLK3+dEubN7zBZdQwgxMwla/1lOUcsatjfMj1gvnNjhiZG5X0uNagibhBpnornmx8VxKorCPIvRwzmIcSkd2ZN6hmzbPdYqi8W2ufyixYu7jH+eEsnxMQX52ZWlrCN0eVBiCUTu36mS/P0CJDl0zLvpTMi3nffteZ5LdBjLM6fNtMXptML/Ays+F/e9nCa/uuK3+FBDJQpBhBiUx2WqRCzbkLOwhppPq3FOo6F935ZL8L0LvQxilisI6phFbdsvnizMTcca4GQeTfT/POjsihTZYEtq4vHPISYdX1LiwhYjc+tg/nXf2T9YOqxrlkMpD8ZCu0yi25gusf4YyydEIua97bQvNeQ6AzbGF2ehOwy6hFzl7yPyjdsu5/zvN+znS/lxo0/36V5ZizEJHusa8Na8Motw/ztjjAfu27u89M0/Awsv0j5LrpoSTo/h23hfJgQA/nHAEIsJyGWpqL2HisNr0m6fL3YqErwBG/LetIn/OuZhoLXtuB2/vnlfwFQycB4HWIgLyF2bgSXdO1b+3YSPIwJ1gl981Lkul2X1Ccv43XjK7qB6R7j90U6IWbZIi2UlK4RG1XnhW2MLk9UGoH9WQmxmBESU/+Ebfdznvf7ZgqxyHmUKXpZo1YnPZgN/w2zXzquPII0nZ/DtnA+TIiB/GMAIbYGQizJu0vOOnKDavqukkADIPC0Vxw6YRpT9ZiXSBaTX/4XAJUMjNchBvISYlZDXXygYouppnlyP5jzQMZK48I0LHdNA9Ur6qbzadz4im5gusf4fZFeiPX2/TY49myn7OEbD6e9em7ZwzZGlye+vp2KI3PMIkIsYjh5fC9N2HY/53m/y0Js0YUrZuUPCIaleXrSWz6tqQ+75h7oxJD3M4m4H/XkBbH8PZhh9svbHk4znb85H17EQJExgBCrghAzjQbnKbT3ZqG2zDvDAqLLvQn6Gwt75qmq71y7ISbe4AvLj8qgyMqAvMobb3kKsbFpMErXvndf07wb8cgMN7SWc58MtzZ1gLUs/JERPi3zknjvsc52YwU9YqK4seuyxo6Z92PsjqoDL43IOTNl3PEIykbHOT4cG0s3mBcRYmZYujiCwcw5OvWUbWiE8YHhf2x8tPx1LQuxlmHTM+mfnSX/d2repzk05Z76wM90aZ45CDFt3vsp3ltNTNVMnHQN5+A9dmzOOTZsnOsg+OlfDMvPwPJVlhyW933YPtKECTGQbQwgxCogxKJWPzv23JijGh/O/sjGWDM8cb+4/LINdioPeK5rDOQpxKw6YGiGFAYbjMt+3zJzW728oxuYUXGZvkfMKssg4mX2s/KYh05bRpTtGaGyZ3o8dozIbEQ8iHJ7PsI2RpfHERpzPhcRYqZ83d1oXzWMKPa+lmQ6Fylsu9cv87dlITbjaQvdxN9nDwj9di3NMw8hZnhH9bLOymtEcNOIsi1Trqg4co5tdoIx4Wdg+SJLDvN9G86fc2BCDBQbAwixNRdiF+YJo1PJez+nT6ODlX7890PPk2BvWrumkeYItmLzK/ZioPKBd1ljIG8hZl3f1lCqqKf/3vogybbV+zQyaXp5Rjcwo+JuMSFmleUsZu5bEvudY9x6NGxjdHnc+tKpN8XPBYWY9Q5Ix755n8HhoV5/JN9WWnoP1ry8I38395npqpx+pkvzzEmIWb7rGtEeWZ6EQrQ16SEOxoafgeWTLDkk93HYDs6FCTFQTAwgxNZBiHmEUPCGLr3E1Lph9CJWVgye7/tuhh15n6bObjzmafG0URX9ZDSf/Iq5CKhs4Fz2GChCiE3qAjM8r2Oe7M+u/YSNzNnxpq44MkPV3HrFja2R8NBo2uPkHuP3g6l3Is/xizw3PzfvgWfhkJl9acpjDfczw8ymaYdtjLfNOS/m07AOvXPS8Ju+UNvJTz7/tJPMR1n1iEW9c3IhrqbXLijSLb8vzdMrxGLjRmYqxZB3X+8oGXOJSdsMefWm5W47fnY/s+Tgv57cPNgPC2KgPDGAECuZEJOGQcQNMZSWxt2NrPSjbgbu/lPpyZ8ZnjgTYmY7eKPJL7/yXChUWvhilTFQmBCb9GKZ690Maz40jf2mEQbB6z303QiWbTPEz5ov4zYwnW1P3Jg0g8LDmmcUzdX8FnlO8Dwnv8CneSB1YnrHWknKYURazRy3bYb+nRgx6Z/74ymH0+CPtS1gh83Vx8f0iAXne1nCaZqvk190On1TzzcM+5A/HLFpfjsxD9ei+Tp5zPs0PVjGt00n3SU/3VcjBPJdlqfjF+tz6bQiuBvxfGjukbHcHT4mlvZM7Llz4qQ0AwwysV1I08uG7QyuCRgvX6/A0GFYBSH2JnNVWTejpf76/b56+umnJ2kYKOrGjUWT+8aiJ87Ou39PqfGD6dfHryr12OwXeeOeOf6Bc/wVc/xD8nFJ9z64r9S9sX20SeuKSdObZHH5vTmpyRwHgUoTePllrZ5//r+oRx9V6v79LK6L5PWUVR8N7yj1e/9Bqa///hTzI48o9c1/UKm3P6HUE6Z+iP7z2mryNPXUpP4wJzxk1y1KeY/xpmTbKJ5jHec9b355rHIMBkrdvq3U3a/Z+ZhyXH2LUt96Taknr5vtyMrWm5djY1R5nN+TfTr1qcvDOs/Jb3657pry3PyqUv/x6+a0h5V6iynPO75NqWvGN9M/Jy3ne1k/l+XpLeeyac1ndM9cE/3fVup3zefXPNfFVRNHE/7m3j3/z2uzc/SytktpOmnzCQEIlI2AkR9Gf0zr+ps3bxr9caNsJs61p2RCbK69HAABCEAgFYHshViq7DkYAhCAAAQgAIEcCCDEbKjZ9Yjl4CWShAAENpoAQmyj3U/hIQABCECgogQQYrZjEWIVjXCKBYEKEECIVcCJFAECEIAABCAQIIAQs4EgxAKRwVcIQKA0BBBipXEFhkAAAhCAAAQyI4AQs1EixDKLKRKCAAQyJoAQyxgoyUEAAhCAAARKQAAhZjsBIVaCaMQECEBAJIAQE7GwEwIQgAAEILDWBBBitvsQYmsdxxgPgUoTQIhV2r0UDgIQgAAENpQAQsx2PEJsQ68Aig2BNSCAEFsDJ2EiBCAAAQhAICUBhJgNDCGWMnI4HAIQKIwAQqww1GQEAQhAAAIQKIwAQsxGjRArLObICAIQSEkAIZYSGIdDAAIQgAAE1oAAQsx2EkJsDaIVEyGwoQQQYhvqeIoNAQhAAAKVJoAQs92LEKt0nFM4CKw1AYTYWrsP4yEAAQhAAAIiAYSYjQUhJsYHOyEAgRIQQIiVwAmYAAEIQAACEMiYAELMBooQyziySA4CEMiMAEIsM5QkBAEIQAACECgNAYSY7QqEWGliEkMgAIEAAYRYAAhfIQABCEAAAhUggBCznYgQq0A0UwQIVJQAQqyijqVYEIAABCCw0QQQYrb7EWIbfR1QeAiUmgBCrNTuwTgIQAACEIDAQgQQYjY2hNhC8cNJEIBAAQQQYgVAJgsIQAACEIBAwQQQYjZwhFjBkUd2EIBAYgIIscSoOBACEIAABCCwNgQQYrarEGJrE7MYCoGNI4AQ2ziXU2AIQAACENgAAggx28kIsQ2IdooIgTUlgBBbU8dhNgQgAAEIQCCGAELMhoMQi4kSfoIABFZKACG2UvxkDgEIQAACEMiFAELMxooQyyW+SBQCEMiAAEIsA4gkAQEIQAACECgZAYSY7RCEWMkiE3MgAIEZAYTYDAUbEIAABCAAgcoQQIjZrkSIVSamKQgEKkcAIVY5l1IgCEAAAhCAgEKI2UGAEONqgAAEykoAIVZWz2AXBCAAAQhAYHECCDGbHUJs8SDiTAhAIF8CCLF8+ZI6BCAAAQhAYBUEEGI2dYTYKsKPPCEAgSQEEGJJKHEMBCAAAQhAYL0IIMRsfyHE1itwsRYCm0QAIbZJ3qasEIAABCCwKQQQYranEWKbEvKUEwLrRwAhtn4+w2IIQAACEIDAPAIIMZsQQmxeqPA7BCCwKgIIsVWRJ18IQAACEIBAfgQQYjZbhFh+QUbKEIDAcgQQYsvx42wIQAACEIBAGQkgxGyvIMTKGJ7YBAEIWAQQYsQBBCAAAQhAoHoEEGK2TxFi1QtuSgSBqhBAiFXFk5QDAhCAAAQg4BJAiNksEGJuULAFAQiUiwBCrFz+wBoIQAACEIBAFgQQYjZFhFgW4UQaEIBAHgQQYnlQJU0IQAACEIDAagkgxGz+CLHVBiK5QwAC0QQQYtFs+AUCEIAABCCwrgQQYrbnEGLrGsLYDYHqE0CIVd/HlBACEIAABDaPAELM9jlCbPOCnxJDYF0IIMTWxVPYCQEIQAACEEhOACFms0KIJQ8ajoQABIolgBArlje5QQACEIAABIoggBCzKSPEigg38oAABBYhgBBbhBrnQAACEIAABMpNACFm+wchVu5AxToIbDIBhNgme5+yQwACEIBAVQkgxGzPIsSqGuKUCwLrTwAhtv4+pAQQgAAEIACBIAGEmE0EIRYMDb5DAAJlIYAQK4snsAMCEIAABCCQHQGEmM0SIZZdUJESBCCQLQGEWLY8SQ0CEIAABCBQBgIIMdsLCLEyhCM2QAACEgGEmESFfRCAAAQgAIH1JoAQs/2HEFvvQMZ6CFSZAEKsyt6lbBCAAAQgsKkEEGK25xFim3oJUG4IlJ8AQqz8PsJCCEAAAhCAQFoCCDGbGEIsbehwPAQgUBQBhFhRpMkHAhCAAAQgUBwBhJjNGiFWXNCREwQgkI4AQiwdL46GAAQgAAEIrAMBhJjtJYTYOoQrNkJgMwkgxDbT75QaAhCAAASqTQAhZvsXIVbtQKd0EFhnAgixdfYetkMAAhCAAARkAggxmwtCTA4Q9kIAAqsngBBbvQ+wAAIQgAAEIJA1AYSYTRQhlnVokR4EIJAVAYRYViRJBwIQgAAEIFAeAggx2xcIsfIEJZZAAAJ+AggxPw++QQACEIAABKpAACFmexEhVoVwpgwQqCYBhFg1/UqpIAABCEBgswkgxGz/I8Q2+0Kg9BAoMwGEWJm9g20QgAAEIACBxQggxGxuCLHFAoizIACB/AkgxPJnTA4QgAAEIACBogkgxGziCLGiQ4/8IACBpAQQYklJcRwEIAABCEBgfQggxGxfIcTWJ2ixFAKbRgAhtmkep7wQgAAEILAJBBBitpcRYpsQ7pQRAutJACG2nn7DaghAAAIQgEAcAYSYTQchFhcm/AYBCKySAEJslfTJGwIQgAAEIJAPAYSYzRUhlk+AkSoEILA8AYTY8gxJAQIQgAAEIFA2Aggx2yMIsbKFJvZAAAIOAYSYQ4JPCEAAAhCAQHUIIMRsXyLEqhPUlAQCVSOAEKuaRykPBCAAAQhAQCmEmB0FCDEuBwhAoKwEEGJl9Qx2QQACEIAABBYngBCz2SHEFg8izoQABPIlgBDLly+pQwACEIAABFZBACFmU0eIrSL8yBMCEEhCACGWhBLHQAACEIAABNaLAELM9hdCbL0CF2shsEkEEGKb5G3KCgEIQAACm0IAIWZ7GiG2KSFPOSGwfgQQYuvnMyyGAAQgAAEIzCOAELMJIcTmhQq/QwACqyKAEFsVefKFAAQgAAEI5EcAIWazRYjlF2SkDAEILEcAIbYcP86GAAQgAAEIlJEAQsz2CkKsjOGJTRCAgEUAIUYcQAACEIAABKpHACFm+xQhVr3gpkQQqAoBhFhVPEk5IAABCEAAAi4BhJjNAiHmBgVbEIBAuQggxMrlD6yBAAQgAAEIZEEAIWZTRIhlEU6kAQEI5EEAIZYHVdKEAAQgAAEIrJYAQszmjxBbbSCSOwQgEE0AIRbNhl8gAAEIQAAC60oAIWZ7DiG2riGM3RCoPgGEWPV9TAkhAAEIQGDzCCDEbJ8jxDYv+CkxBNaFAEJsXTyFnRCAAAQgAIHkBBBiNiuEWPKg4UgIQKBYAgixYnmTGwQgAAEIQKAIAggxmzJCrIhwIw8IQGARAgixRahxDgQgAAEIQKDcBBBitn8QYuUOVKyDwCYTQIhtsvcpOwQgAAEIVJUAQsz2LEKsqiFOuSCw/gQQYuvvQ0oAAQhAAAIQCBJAiNlEEGLB0OA7BCBQFgIIsbJ4AjsgAAEIQAAC2RFAiNksEWLZBRUpQQAC2RJAiGXLk9QgAAEIQAACZSCAELO9gBArQzhiAwQgIBFAiElU2AcBCEAAAhBYbwIIMdt/CLH1DmSsh0CVCSDEquxdygYBCEAAAptKACFmex4htqmXAOWGQPkJIMTK7yMshAAEIAABCKQlgBCziSHE0oYOx0MAAkURQIgVRZp8IAABCEAAAsURQIjZrBFixQUdOUEAAukIIMTS8eJoCEAAAhCAwDoQQIjZXkKIrUO4YiMENpMAQmwz/U6pIQABCECg2gQQYrZ/EWLVDnRKB4F1JoAQW2fvYTsEIAABCEBAJoAQs7kgxOQAYS8EILB6Agix1fsACyAAAQhAAAJZE0CI2UQRYlmHFulBAAJZEUCIZUWSdCAAAQhAAALlIYAQs32BECtPUGIJBCDgJ4AQ8/PgGwQgAAEIQKAKBBBithcRYlUIZ8oAgWoSQIhV06+UCgIQgAAENpsAQsz2P0Jssy8ESg+BMhNAiJXZO9gGAQhAAAIQWIwAQszmhhBbLIA4CwIQyJ8AQix/xuQAAQhAAAIQKJoAQswm/hu/8Rvq2WefnXz7sR97k7pypWhXkB8EIAABmcBXv6rU5z6n1ZvfrNRHP/om+SD2QgACEIAABCCwVgTu3VPqH/9jPbH51VdfVd/1Xd+1VvZbxr5Jm79lrf7Sl76knnvuuWWT4XwIQAACEIAABCAAAQhAAAKpCLzyyivqve99b6pzynBwJkLMUqHvfve7J+V5//vfr97ylreUoWzYAAEIQEANh0NlVdDf9E3fpD70oQ9BBAIQgAAEIACBChD4+te/ro6OjiYlOT09nY3OW6eiZSLE/HPEbqobN26sEwNshQAEKkzg5ZdfVs8//7x69NFH1f379ytcUooGAQhAAAIQ2BwCVdAfCLHNiVdKCoGNJIAQ20i3U2gIQAACEKg4AYSY7eAqgKh4rFI8CGwsAYTYxrqegkMAAhCAQIUJVEF/0CNW4QClaBCAgFIIMaIAAhCAAAQgUD0CCDHbp1UAUb3wpEQQgIBFACFGHEAAAhCAAASqR6AK+oMeserFJSWCAAQ8BBBiHhhsQgACEIAABCpCACFmO7IKICoSkxQDAhAIEECIBYDwFQIQgAAEIFABAlXQH/SIVSAQKQIEIBBNACEWzYZfIAABCEAAAutKACFme64KINY1CLEbAhCIJ4AQi+fDrxCAAAQgAIF1JFAF/UGP2DpGHjZDAAKJCSDEEqPiQAhAAAIQgMDaEECI2a6qAoi1iToMhQAEUhFAiKXCxcEQgAAEIACBtSBQBf1Bj9hahBpGQgACixJAiC1KjvMgAAEIQAAC5SWAELN9UwUQ5Q0zLIMABJYhgBBbhh7nQgACEIAABMpJoAr6gx6xcsYWVkEAAhkRQIhlBJJkIAABCEAAAiUigBCznVEFECWKK0yBAAQyJIAQyxAmSUEAAhCAAARKQqAK+oMesZIEE2ZAAAL5EECI5cOVVCEAAQhAAAKrJIAQs+lXAcQqA4m8IQCB/AggxPJjS8oQgAAEIACBVRGogv6gR2xV0UO+EIBAIQQQYoVgJhMIQAACEIBAoQQQYjbuKoAoNHLIDAIQKIwAQqww1GQEAQhAAAIQKIxAFfQHPWKFhQsZQQACqyCAEFsF9c3O8/7d22owHKlLg+Hhx9+mrj91TT222UgofVYEHtxTdy7Gk9Ss2Lp6hcjKCi3prB8BhJjtsyqAWL/ww2IIQCAJAYRYEkockxWBB7c+px6+0fAlV2+fqi985FnfPr5AIC0BK7bebWLrzHNia7+nXvyR7/DsYRMCm0OgCvqDHrEk8frgvrp7MX26OT38YfX4266oK489lORsjoEABFZIACG2QvgbmPW9V19Ub3v3R30lb+ydqs9+DCHmgzL58kDdevVEffHstybf3vr2P6y+u/596qkr3FvDrJQitiQq7NtkAggx2/urBvH65z+lXvxnx+rm8N4sHq88+bR61/f+afWTP/4+dXW2N/nGg3u31clLn1H/5NOfVZ84/KJ4Yq3eVC/82Avqzzb+hHrmanbDA+689jn1t/6Xn1dfuPl7dr7foj789zvqY+97SrSDnRCAQDSBvITYG59/Uf2v7SPl1DpP/pH3q5/++EfUM0tUBXfNtf9zf/tA3bw3TfXKk8+qv/K//XX1nidomEZ7uFy/3HvNCLEaQiyJV2597qfUjcbPBw7dUQP9cXUtsJevRogRW4QBBHwEVq0/fMYs+kVn8Hfz5k1t8p/8s7aL/Lvo7s3ydmzwfu6dXqQ0Z6SP97Zi0/Sm72w3d4902pxCho0Hen+7IeZd3zsNHc4OCEBgPoGXXnppck09+uij8w9OfMSF3qtP6zynDrA+d7vL1QKne/XQ9b9smomLxIGZEBidtUM+ND1imaRdrUTG+qBVC7FSqqG7o2qVNKvSEFtZkSSdqhBYpf7IiqHKIqHVgejrbVsAehtD3u10Qmyg9xrhxpU3vdjtZlsPFwR6ftLR9ZiycCNfECynbTyBfITYSHeEuiJdfRN2zVm7GWqYLptmOBf2xBO41KPRaPpvfBl/qPArjWUBirjrQreFhxlKtfTZWDxh43cSWxsfAgAIEFid/ggYssTXtRZivU640RIUSskbMSO931pChNkiqrZ9pFPdui96ek98Kui3BSG2RJRz6kYTQIhttPvTFX7c063AAzGzGEKqNGgsJ8d1vEOPWHJaWhNbaWhx7CYQQIjZXl4JiIuT2B4kR5AlFWK9/VboSfQ0jZre6Rzp88GFHo/H5inpUJ+fnej2ljyE0Dpn53iQIP4v9dnhbkSefhFmpYkQS4CUQyAgEECICVDYJRMYnWqz3qGvXk5b99JYltFKe0dn+7oW5L17nO5hppRwRfcRWxV1LMVamMBK9MfC1sonrmmP2KU+3JKepPlvoJaASSTEhsehm8FEhNV3dC9mrHr/OEpIbeu+zHu6d9TTO8KwpkmegZuSsy9tYyAue36DwCYRQIhtkreXLOv4VDcDdXDaupfGckofXI70cDDQA/NveMGYxDh6xFYcHX7bRAIIMdvrRYMYnYYnQ9d3jvSp0KuVRIh196TerWaiCcO9jtyT1j6NVnBnYn5GRNaa+qg31GdCOdI2BjbxgqTMEJAIIMQkKuwTCSDERCzsLAcBhFg5/IAV5SFQtP7Io+Rr2CM20Du1YM+XWWXJPEiT5ozNF2Lygh9bB7F9Wh5fyOfXd7ueY/yb0oT8nf2udqSb9DtCzM+QbxBISgAhlpQUx2mEGEFQYgIIsRI7B9NWQgAhZmMvEsS50FvkTKaWBMw8ITY+3/fNB5gOBdzS5ylCShKAqrYbuYLiqadHrL7V1r0L//IeUjkQYikcwqEQ8BBAiE1hXFpzXC8u9IX5NxrlMwTs8tKaRzvN48JaedDkuVZ/l2fhoYnts1RFSNNYLsInlvGX49HE75bvJ/5fYDXIVBDsg51884q3RWxKf850Fc0ZO3Pt+O/Y6VOUz7Dysa+di5GWXJQmtuQ82AuBahEoUn/kRe5NVsJGfCz1V9gL1e5+WX3w7X9MHXqtrZmXP/7m9OWPr734o6r20U97f1VGiKmPPRv9SufXf+kj6jtf+ITvnNrOifrNjz/n2xf35cEbn1EPf/sPBQ6pq+PhF9T7ngjsNl/vvPoZ1f7nt9X3/JkfVj/wrvABUjmMEFOf/diz4cTYAwEIxBLI54XO99SnPvg29RO+ykjNrW9iDTU/Std+bB324Lb6pb/5d9SvD/6/adLf8sfVz/7cj6hrzvufH9xVX/4Xv6w++clfMC+mP/NnX6urrRf+kvrR5p9Wz1674v8t6bf7d9Vrv/ll9cWXXlJf+FdfUIdfDOQxSaemmq0PqO//QEP9qT/1HpXo3dR3X1P/4O98Uv2737PL9Qeuq//+r/yUet8zCe28/4b6FrUE4QAAQABJREFU1N/+h+r/driob1Ef+Ct/Tf3guwL3AsPvM7/wafXv71uGmjdx3/936md+1n8/UPWW2v3gf2N+mxw0I3P//mPq+b/UUu+55n+D9/yX7t5Tr37+V9SL7b+fj08sCx/cU6+fflF97vBX1ed/9RNKdktdtT7wA+oD73+/eu5736WuOjEzK2HMRmzcPVCvf/4fqb/xMx9Vn/aGgxVvH/5p9XMf+wE186LF/+/9Q/Uv3/i9aWZ/wPjpLwp+ckwxcfHi/3Gk/pPzPdXnN6s/3vwLIX+JSdy/rb788svq8OCz6m99OnCRT04wMb31gvqhD/2gqj/3HW55xMTidt5Xb3z5ZbX/yU+qX/nEofLiss6qN7fVX279mPqgycNyz/zYisuL3yBQPQKF6Y880WWh8IpRpJf6aDu8QIe3x0vqSfL+Hi7rWO83g8Mck6566EntMrzksfGZWSjEGWzoOTbBplQOesQSgOMQCAgEqtwjNjoNv9DeqXcG3f3QCoBWvST9a7W76Z7yj/r6YIEX35umpe50568qK5Urbrh30O1Jz5eOk/hE7avvhl/UHNdrMTw9yM8nNoTe0V6iFYX9ZarrvaNeEGPkd4nbNO5G+iB2Ia26b+61lE6cn8/a0nxuOab95ZseYx6yRpZp+sNYd/e3xWtESm+6r6EPztK/QXTcP9at0DSLiLLUt7X1rvjL807INtoGc1zKz5UmUIz+yBfh2swRG/fCFZBqHfgaD5KAiRViwnwAq2LdP087nGak28IqiM1O8hub181SOahsvYTYhkByApUWYmfhhYs6ZsGf04hFhKIbk9YrMqLntXppj88PF2jo+xuYO0fxc3DjxIzXlqjtpOdLx8UxCv4m1ctSmq1OV58epG3gJ/fJlMOFEUH1UEM9aHPcd2vRqyR3P6mMnbO++LDUn5//Zc1SOhJTx8/SvdGfvj/OQr/V97TRMxF/Q90WHsyG0oh4mLFzmHxCw6gXXrZ/fj4NvbsbXhwsjldEQdkNgcoQQIjZrswfxFDv1oMVbF0fBx5CSZX0PCEWfGeMUg2dviNL7q1btIKUyrFoWpW52igIBBYksGlCbH6DLliXut/3rMfuc/68c1zlvGq6NvdJf3w9m7aBHjQ56flSj4xcJpeR9/easCiTlLf3nLTbSXyijbzotGQb0+ZX254vxhYvY9N3f5XSibvXLd0jZsomz+8yIkx4mOqyq+lGs6Vbzfgeud0k7xA1r8upR4g5N7/kvozjFbwu+A6BqhHIX3/kT2wtesT6h1uhp3xNYQK1JGDihVh4Yra1yMb8gTNhx0h5L1pBZplW2FL2QGCzCCDEpi+l7/XNe5oGfX16vB89JKrRma3eGhUlUv3U2mnrk9NzfeFZBMRaqKF/dqy3Ixq4zU70IhhpG+hBWxOffznUJwcH+mDy71AfdHbC75Rs7OiDQ/Pb7Ljp8fv7h/psGO4/kvION7Cz9Yn8CpZpY761u69Pe4PJwimTxVQuzCtSTg71djM81N+xc2eOoPCX0U0nKMBbO3u609nT2y1HwPgFuD+dqb2x983Rud5vt3W70zHpyv/a7Y7e78i9j1GjVKL41Vp7utsf+sXb5YUZvrgTapNM2fl7/IJxqc3V1Ym4HqyHwHsHJ7o/NAt2DAdTHzVcttP0g9+tXtPw8NhwvuyBQDUJIMRsv+YKYhR+waZS8guTpQZCnBATV0xstOc2RKRwlp7ULVpBSuVYNC3JVvZBYJMIbLQQa+7pc3GqatQwrPBIg2CseOu67faRHoS1SOCUC73fCjcgVb0dOUwsdQM9kOPC5+e0aqIjcCafWftkeBQWj5Mel5Y+Gcj9Pw6u3mGUoNiJfSAZ5mt6Qb29PLVtfTr0531pVgQcDv3BGE4nG2FxcbIrCCXzmht/9lMMpofKZ7tdjqaZNxn3N+4fifP9WgfRQxTFKRZWfo1d3ffjmmXdO5LK4vaY0TaYoWJjAwnkqj8K4ln6HrHjnfCY991uYEyiDUsSMHFCTLoJWI0Dqa6e54/zg3Cv3aIVpFSORdOaZze/Q6DqBDZViM2d7zPqyg3J/eiG5CRWxgPdPenqfuC1G7FxJIoF/zA17/lS3ZymDlz4fGHecJp8rTJIeTtCLA+fdHfD90ird+VEvk16MU+2zyLmE8YNiYwro/WgtDdXnE/NkNJJyztUoIi43oqYwyX1htW2Dv29YKFMbPu74cVy4l5dcywsOKbUvF40E1O9A1EsWnG1NK+IsrEbAutAACFmeykvEGKPVXM/cjKxJGCKEmLik66YJ75xAS6Vg8o2jhi/QSCawCYKsdr2YWQ96SV1IjzoyqeuuRDm4ET0UBgDl22gL3x+jkIsF5+Mz3TL2xNlb28fpRlgL83BNj0uMWJE4jsVm3V9NKcXzht/UjrLxd+lPpRWbTQjXcTZj+KKxzV9lFDEavO20PD8daUPpAW/xNE9Sif11ThCjC3Hy+sNtiGwfgTy0h9Fkihxj5i5cYcW6DAVZEwlLwmYooTYhfBkzJr0HDHaINbHUjmobGOR8SMEIglsnBAzjc6k7cgLYfn7fOoaaW6Mf76Q14HLNtAXPj8vIZaTT0an4VUzrR6WXsobjzQPezIFICIdia8lxLYO41fD9PrY2pbSWSb+pPuwUjV9GDHuT3qAmrQ3zCmLd6iu0/MptTuksibpDXPysT4HR+GhpMvw8qbNNgTWkQBCzPZaHiAGR+HJtvMqHEnASBWiE2xixbjg0EQxrYXnmzVD49vnld0pE58QgICfwKYJsYawkJGfiPtNqreSLmPvppJsK1w/b44Qy8snZ53wvaK2fZzMId6jBtI8s7o+EbuRZAGlzGiVtMP65fhbcPEJsXdLaWlhL6fovf3wcvBxc7yc87yfF93wHC5pWGf/MNymsV7Bk3AU5yTLsfC6CtoGXm+wvWkE8tAfRTMsZ4+YONxia+5TvvCN3nqpcsSdxJCWbgLMESs6BMkPAvkS2DghlmYVNTNcKvQKjwWHVDtevByP9ejCWphhOPt3YRZqON51Vs5zFhrYICGWi0/G+kBYBEUSAY5voj8Held45UDU/VO6d6YRm44dYjppWDkJmU9pPrmqxS860g3FpJlztXuoT7tdfXJyMv+fOe5YWKFREkenwsuoo1Zx9BTLt5klL1/CfIHAmhJAiNmOyxqENPl4J/jSMCFoMhFiC/diBRsZi0+ilcohVewCAnZBAAIBAgixABDvV2EonkpZB170z/ShWaJ8y7xjKbh8uTNUS/5EiHldMdtO7JORMO/OeviYtl/KylkaOhr9IDMrQZBdOp3QKBIr5jq9OBYyPzlWnYcHyT6l+7V0X2+n9FVWvGaxxgYE1pxA1vpjFThK1yN22T8MV6jNTqIhD2kruvH5QTivOU/Qopwk5S1VxlHne/dnmZY3XbYhsIkEEGIxXpca/QmHZw/PDvVWaB5vsobqtLGLEBM9k9gn6cSTmNdspzQnO1rIZCUIskmnr3eE3rz6zsmsdPKGzC8vISa9CD2qx1G2Vx7Fs2g7IyoP9kNgnQggxGxvZQfiUh8Jy7vunQ71eDTSF2a4S9S/kXl56IkwzGD76FyPzW/OeWPv5GMzBLIZWnEqeiWvuOCUxFN9wSEWUlpUtnH0+Q0C0QQQYtFsdOJGvzeNS32yF56blL4BixDzUp1tJ/aJLCTSNu6n+Q71duheqHT7TO5RykZAZSMspCF/Ss2fyhDVC5g+jsMPH8LcZKGb1ldZcZ/FGhsQWHMC2emP1YEoWY/YQHyylUXFOEujvueuKCbd8NT8F5qG3WVuiM1wZbyb9EUugQQRYgEgfIXAEgTyEWJywyrcAEtj+KU4zyWusbZ0w0yqA+f0iEkLHMzqV1N/tra29V67o/cPDvSB/e/w8EDvNIMvdUaIidGR2CdZCrF0aS0dd3bBl03nsi+MajGCcrcbPTfcZS4PTWy2j/V5r6fPzs4W+nc+kMWr1CPG0ETXG2xBYBECCDGbWmYgpInjwlM696YfFj/zf2vqM2eZooj8klXi3pCRh0YsNlZfa4SYly3bEFiOQD5CTIs98M3O2RLGyg3DUgmx4bGui3VyUx+c9mNf19ELrfCHEBODJYUQazfC98DFHgaYBwsp0lpWQDnlXi6dod6ThsbGvP/MyXf6KYvP9qyB4D962W/SfX0n1fvesulBXLYcnA+BMhHITH+ssFDl6hEzN6DQCl7iTT9885kvwJxzPEIsYoJy6mGA4tK/3nzSeViqsFPblC5LjoZAZQnkJcSk9wfVdhZYOnxGXnqgE//uxOUasibjxI3+qZG9Tni578kwMOfh1qws4Y1wvYYQC1MyexL7RB7K39rvicnG7hx1hXtv9DD9pePONmaZdM6FpeeVirZZKr90DS/3MEXKZbpPGkJZ3503j82f3jK8/CnxDQLVIIAQs/2YHYiR3heG+CUXWY7Yivn0Dk009oef0ppzU64adn6wFV70w7xTJUHbRLwSwg2WxVdgFDNgJwQ2iEBeQkx6f5CyhjYnGRUl8B+ehF/Waomcc++81sB5SzfMEjf6rYzlHoTdqJdNBWwN12sxQkx4UXGaRuto0RdVCzzSPgQr0ifi/WuB1w8Mj4XYq+26w/gDvly6jHZ6C6cT0TO7fdQPWBr/NYt3e8Xn4P4qvjTbtEfSVBcLx7VrBlsQqBSB7PTH6rCUq0dswmE8W1jDWWAjyedoLL2nRuntQ7NYh3mHjZPGKNCoGfekZW9r+nAQODDSR/K8tq2D88gz5v0QbrAgxOYx43cIRBHIS4jpixNxmF4aweDaPNS7CwyzWrgh62QsCI/odylKQyfr+ihhXRmu16KFmLiirYp/J5RTJD3u6S1hJEUiQSXxSPlgrkifSHkpZd2/ZjQSbIzFOc713W7kuVK+ifgGUlwsHfNAQHpg2+gkWl3Za8Ll+X74IarVq5ZGHXkTjNm+lFZpNr5KPDrRTKVoLRrXMXbxEwTWmQBCzPZeWUCEb/Rm1ad57+m47ImVW9I33otP1BZa8MO9FKRyLHKTc1NkCwKbSyA3IWb6vKN68Pe6w1TAT9vSkD+zfHjEqnVO4os1ZJ2zzackPCIX65CEmNL7vfl9/5eDY3GF2sjq2dglDVOfO//p8jxywadEdajIw7PAkwdd1GahPom8fyUfkTE82RPEiNIH59F+XbqMNrxF0hkcbQv2mgcC6S452wL5QWpjL1qERvl9/v6+uDJlbfto/qnm4cK2sES/NVooUVzPz4EjILCWBMqiP5aBV8IescWLIwmYuInuTk7HO3WhYld666DnHCJ+js72dU14QmWJuKT9aVLCUjka7VPpUPZBAAJzCOQnxKzJ81KP+nRo9O5RfP0xNXukj6OWgk/whH+RhqwPlyg82hE9C9acpHBd2YjpObHyGp8fiaLKms8TKcS0NF/OcDXveYwcfDY81VsRjdXEDVZxAad0PUzF+kTr7l5DvH819ubPPxr1DuR72JzYW7qMdhCmTsf4J/zKGaUXmhdn2xC1Cuj2nPu/ffrsYzw8192Trh5E61fd3Q1fP1Zs7p5Ed2FeDrryw2K77YEQm7mAjQ0kgBCznV4WEJKASSLELsXFNqaNqebugT4f+pejvRwN9cm+9FTOOsfMEUkwVGc0HOjBYKCHw6Hnn/l+MdSHwrvUatuHk98G3uPN+YPBxVKibwOvW4q8YQTyFGJGZuiD1rSuEOeyNrb1wfGpHlyM3Ov00gy/No22k8O2bsYIh7geCceFqRuyzonOZyohZq3oKjf6dw4l0TnSpwfC3KPZw6s4IRYxf9c6t76ju33P2LHLC316uCsLilleCXsOTI+aNKxR1bb16dB5vHaph+en+qDd1sc9jx0206J9EjVE1orHWmtPd8+HbuzZNo4v+vq4E3UPm9/LuXQZF2TVFd4Vat1zTwbDyf3UuqdG/ev3+7pv7pehP/F9otNrurGzr3uB+7/3fKstcHZyqHdarsBqxKycGrXcvuWr7f0TfeGEmJXJeKi7+3HXj23jgu8r9ZaDbQisK4Gy6I9l+NEjZtMTF9zw3MRVvaGbzaZu1IPvwvE3wpJMFr4QJpKLjThv/jHbzY7UCFomLDgXAtUhkK8QM5wintJL13StFl9/OOfM6413vLN0gzilENMRiyRM7K63dHv/UB8dHerO7rY4f84p3/QzXojpi6il8u06t9bQjYbbAPan7Rzj1s9Jew6iei2s9BuNhk/wSfOoCveJCYaoXp0Zk1pdN1tbemurNfcelmTVwKXLaAdwunTkd/fNyhhzj/Qe0xGG0g6kxUq86Zn7/9bOrnk/Xlvv7e3qne1ojvFxJq906bWvYdoZzRzi2qkz+IRAlQggxGxvlgXEoj1i02KMxWE33gpy3naznWxcufRix3lpx/3eaC/z7qIqXZKUBQJhArkLMSvLi/hhcXHXb/A3uXcpXC5rT7qGrJBGWiFmkjgLvQ/MFTvBssR/nyPETF5zBYa3sezZbnfP9H7LL3rjG8gum7hei2B5pCFxq/CJZX233RSHKAZtjvveSngPW7qMNu506cirdsaVR/otap7hmbT6sSempLSkffPvx329G9MTLqXp7NszveudBePajXC2IFAdAmXRH8sQrX6PWKrlj4wY213sZrZzkFwMRQ3vcSrbtJ9JGxjLBArnQmBdCRQixCZwzLDiBeuPyTVfa+mjc/8w6HnMl17OWpoTNXdJbauelIcoRtVdjZ0jPRqdBea6JHvnUzqB0dRHPYvhOPSC4jT15Kn4vrSw4BR7xIQRD2nytnpYQwuVzPXJNFJ6R7sLirGabp9Ezr4LheHScWenmC4ds1iMtLJoSrEUN11h0O0k6MkNx8Es7mtb+lQY/RgCODaLyqQqS1MfOnEdOC9VbIUMYQcE1psAQsz2X1lAhJ+eNvTxbFx/8mC7OO/q9nYSQVbX2+1Dfe4b2D0/n/H54XKVfeDGs3Oc/AY63zqOgEC1CBQnxKbcRgPTG7NnhuYlfOrd3NrVh13zmo1FsA9PQo32VpqhysJS79by+96pKlFmDU4P9VbD3+s0a5DadVS9uWPmUdnL2Zm5OP7lt5O/9H7QPdCt2GHhdb3TOfa8kyk8dy8VF1Po/klHN+J8aBrdJ9J84BX6ZOKrUV8ftnfibXfuIfWm3js40cO0wbdsGZ2gSpXOpT6JWtjGKc/cT9MmkHzm2GN9Xpo54Ad7c+LNFWM1M2xxe7ejT876ia4bNyszh/Jwb46f7LieXZDhBXOSDCV182QLAtUiUBb9sQzVN1knm5vnUn9mEqx6+umnJ2kYKOrGjRtLpbfMyffv3VPjBw9MEg+px69eUY8tk9iDe+r2rb5649ZA3f3a79spPaLeevUJ9dQz36aeuvaEyYU/CECgzARefvll9fzzz6tHH31U3b9/v1BT7925rQbDr6rbg7vqa79v1yGPPKKuXr2urr3jSXX9iSfUY8tWIg/uq3v3xmpS6z10RV25kjbBB+b8e8qqNh966HFzfrpa8/7d26p/05TxztCU0eC1yvfEDfVfv/OGeiKYlsfWx69cTV32e3duqa/c/C11Z3hXTbO6qq6/8xn1zmeuCXW9p1yPGy4LgX6g7t6+pW5+9bb6j1+/VOrhh9Vb3vKt6h3fZvz3xJXoWPKU86EV+MQxzIq//m9/Vf3uHTf+Hnnkrerq9WumDDfUtavpfO2kO/lcuox2alml4zMumy/3791Rg8Fvq9u377htACu+33JVfeu1P6SevH5dXV0orrz2TWPs/33jlhre/drkh0feauL6qai4Vspp5zz0uLleH1vCh14z2IbAGhIok/5YFF/lhNiiIDgPAhCoJoFVCrFqEqVUEIAABCAAgdUTQIjZPqgCiNWHExZAAAJ5EECI5UGVNCEAAQhAAAKrJVAF/UGP2GpjiNwhAIGcCSDEcgZM8hCAAAQgAIEVEECI2dCrAGIF8UOWEIBAAQQQYgVAJgsIQAACEIBAwQSqoD/oESs4aMgOAhAolgBCrFje5AYBCEAAAhAoggBCzKZcBRBFBAx5QAACxRNAiBXPnBwhAAEIQAACeROogv6gRyzvKCF9CEBgpQQQYivFT+YQgAAEIACBXAggxGysVQCRS4SQKAQgsHICCLGVuwADIAABCEAAApkTqIL+oEcs87AgQQhAoEwEEGJl8ga2QAACEIAABLIhgBCzOVYBRDYhQSoQgEDZCCDEyuYR7IEABCAAAQgsT6AK+oMeseXjgBQgAIESE0CIldg5mAYBCEAAAhBYkABCzAZXBRALxgCnQQACJSeAECu5gzAPAhCAAAQgsACBKugPesQWcDynQAAC60MAIbY+vsJSCEAAAhCAQFICCDGbVBVAJHU6x0EAAutFACG2Xv7CWghAAAIQgEASAlXQH/SIJfE0x0AAAmtLACG2tq7DcAhAAAIQgEAkAYSYjaYKICK9zA8QgMBaE0CIrbX7MB4CEIAABCAgEqiC/qBHTHQtOyEAgaoQQIhVxZOUAwIQgAAEIOASQIjZLKoAwnUrWxCAQJUIIMSq5E3KAgEIQAACEJgSqIL+oEeMaIYABCpNACFWafdSOAhAAAIQ2FACCDHb8VUAsaExTLEhUHkCCLHKu5gCQgACEIDABhKogv6gR2wDA5ciQ2CTCCDENsnblBUCEIAABDaFAELM9nQVQGxK0FJOCGwaAYTYpnmc8kIAAhCAwCYQqIL+oEdsEyKVMkJggwkgxDbY+RQdAhCAAAQqSwAhZru2CiAqG6UUDAIbTgAhtuEBQPEhAAEIQKCSBKqgP+gRq2RoUigIQMAhgBBzSPAJAQhAAAIQqA4BhJjtyyqAqE5YUhIIQMBLACHmpcE2BCAAAQhAoBoEqqA/6BGrRixSCghAIIIAQiwCDLshAAEIQAACa0wAIWY7rwog1jgOMR0CEIghgBCLgcNPEIAABCAAgTUlUAX9QY/YmgYfZkMAAskIIMSSceIoCEAAAhCAwDoRQIjZ3qoCiHUKPGyFAASSE0CIJWfFkRCAAAQgAIF1IVAF/UGP2LpEG3ZCAAILEUCILYSNkyAAAQhAAAKlJoAQs91TBRCljjSMgwAEFiaAEFsYHSdCAAIQgAAESkugCvqDHrHShheGQQACWRBAiGVBkTQgAAEIQAAC5SKAELP9UQUQ5QotrIEABLIigBDLiiTpQAACEIAABMpDoAr6gx6x8sQTlkAAAjkQQIjlAJUkIQABCEAAAismgBCzHVAFECuOJbKHAARyIoAQywksyUIAAhCAAARWSKAK+oMesRUGEFlDAAL5E0CI5c+YHCAAAQhAAAJFE0CI2cSrAKLo4CE/CECgGAIIsWI4kwsEIAABCECgSAJV0B/0iBUZMeQFAQgUTgAhVjhyMoQABCAAAQjkTgAhZiOuAojco4UMIACBlRBAiK0EO5lCAAIQgAAEciVQBf1Bj1iuIULiEIDAqgkgxFbtAfKHAAQgAAEIZE8AIWYzrQKI7MODFCEAgTIQQIiVwQvYAAEIQAACEMiWQBX0RyY9Ym+88Yb69m//9gndf/Nv/o16xzvekS1pUoMABCCwIIFf//VfVz/8wz+sHnnkEXXr1q0FU+E0CEAAAhCAAATKROCrX/2q+p7v+Z6JSefn5+qZZ54pk3mJbMlEiH3pS19Szz33XKIMOQgCEIAABCAAAQhAAAIQgEBWBF555RX13ve+N6vkCksHIVYYajKCAAQgAAEIQAACEIAABLImsNFCzOoOfOc73zlhenx8rK5fv541X9KDAAQgsBCBf/2v/7X68Ic/PBmaeHZ2tlAanAQBCEAAAhCAQLkIDAYD9f3f//0To77yla/MpkmVy8p4azLpEavCZLl4TPwKAQisKwEW61hXz2E3BCAAAQhAIJpAFfQHQizav/wCAQhUgABCrAJOpAgQgAAEIACBAAGEmA2kCiACvuUrBCBQEQIIsYo4kmJAAAIQgAAEPASqoD/oEfM4lE0IQKB6BBBi1fMpJYIABCAAAQggxOwYqAIIwhkCEKgmAYRYNf1KqSAAAQhAYLMJVEF/0CO22TFM6SFQeQIIscq7mAJCAAIQgMAGEkCI2U6vAogNjF+KDIGNIIAQ2wg3U0gIQAACENgwAlXQH/SIbVjQUlwIbBoBhNimeZzyQgACEIDAJhBAiNlergKITQhYygiBTSSAENtEr1NmCEAAAhCoOoEq6A96xKoepZQPAhtOACG24QFA8SEAAQhAoJIEEGK2W6sAopIRSqEgAAGFECMIIAABCEAAAtUjUAX9QY9Y9eKSEkEAAh4CCDEPDDYhAAEIQAACFSGAELMdWQUQFYlJigEBCAQIIMQCQPgKAQhAAAIQqACBKugPesQqEIgUAQIQiCaAEItmwy8QgAAEIACBdSWAELM9VwUQ6xqE2A0BCMQTQIjF8+FXCEAAAhCAwDoSqIL+oEdsHSMPmyEAgcQEEGKJUXEgBCAAAQhAYG0IIMRsV1UBxNpEHYZCAAKpCCDEUuHiYAhAAAIQgMBaEKiC/qBHbC1CDSMhAIFFCSDEFiXHeRCAAAQgAIHyEkCI2b6pAojyhhmWQQACyxBAiC1Db7Fz79+9rQbDkbo0pz/8+NvU9aeuqccWS6q8Zz24p+5cjCf2WWW8eiXnEhadX3nJYxkEIACBCYEq6A96xAhmCECg0gQQYsW698Gtz6mHbzR8mdbbp+oLH3nWt2+dv1hlfLcp45mnEK39nnrxR77Dsye7zaLzy85yUoIABCCQHwGEmM22CiBiw+TBfXX3Yvp0d3rcw+rxt11RVx57KPa0tD8+MPmM743V+NJ6jmz+Hn5cve3KFZVxNtO0+R8CG0IAIVaso++9+qJ627s/6su0sXeqPvuxvITYA3Xr1RP1xbPfmuT51rf/YfXd9e9TT13Jtn72FqjoMhadn7esbEMAAhAoK4Eq6I9K9Ii9/vlPqRf/2bG6Obw3i5UrTz6t3vW9f1r95I+/T12d7U2+8eDebXXy0mfUP/n0Z9UnDr8onlirN9ULP/aC+rONP6GeubrIsJQH6vbrp+pfvfySOvrsr6hPf9H7fNXNst5oqR/44AdMPn/K5JNf48LNkS0IVIdAbkLs3i31mc7/qV79nfvqsccWuf6Vun9fqe/7sf9R/cB3LFJLldNH914zQqxWnBC79bmfUjcaPx+AsaMG+uPqWmBvVl+LLmPR+WXFiXQgAAEI5EmgCkJM6Qz+bt68qQ3oyT9ru8i/i+7eLG/HBu/n3ulFSnNG+nhvKzZNb/rOdnP3SKfJ6fxkXzdrU2ZOGkk+tzonepyyRBwOgU0m8NJLL02u50cffTRTDKd79dT1hHSN13a7mdq16sRGZ+0QF9MjlpNZY33QqoXyU6qhu6OcsjTJFlvG4vPLjxwpQwACEMiOwCr1R1alWHMh1tfbtgCUGjjWvnRCbKD3GunF0SzvZlsP53pmqDtiwyFFvq39VKJvrkkcAIEKE8hHiI10e5m6wlNv1XeOK0W/WJFyodt1qe5s6bMcn1gVW0aEWKUuEAoDAQhkRgAhZqNcFYhepyk8CfXflJMLsZHeb/nPnQksT6Np3r7a9pG+jAmx84PWXJvn5WH93uz0YnLhJwhAwCGQlxDrZCTEajsnjqmV+CxapBzv0CNWicChEBCAAARSEliV/khpZuzh6ztH7O4r6n1v/z71RaNK4v6MEFMfe3b+/IvXf+kj6jtf+ISQVE3tdHbVC3/yPer62x9Xl5cjdaf//6hf++TfVR/9+UPheKV2jgfq4++TZye8+uIH1bs/Gjyvrrbbf1n9uT/+3erpJ9+uHnrogbq4c1P921/9RfVDfzU498HJsqlOR7+onr3ifOcTAhCQCOQzR+ye+tQH36Z+InQpt9T2H/sWyQxhn1mYZ/y4qv/Fv6Z+8F3z6yghgVLuKno+073Xfkm9t/aCbwXDxu6x+sxPv0/lNaO2+DIWO++ulIGFURCAAAQCBJgjZmu84hXppT7ckp6Chnu0EvWIDY91Ter1qu/oXsw8g/7xbkTv1rbuR+jf03bDc05Dt4/OdEwWetw/1k3JNrOvdXAekQu7IQABh0CRPWLtPMfDOQUq+WfRPWITHJcjPRwM9MD8G17kOCbRZl90GYvOr+QhhnkQgAAEJgSK1x/Zg1/LOWKj0/Bk8PrOkT7dDw/7SyLEunteceSIuWaiyd69TjhPI9h1+1SWV/2j7YkQa6VY3EMqr5VHfhPgsw80UoTAqggUKcSS1Der4lBUvpsgGoouY9H5FRUr5AMBCEBgGQIIMZtesSAGeie02qBZIcs8BJXmjM1vGMkLfmwdRPVpBUNGPr8etxJa3CSyYPKT70O9K01Ibx2wgqLIi50QcAkgxFwWRWxtgmgouoxF51dEnJAHBCAAgWUJFKs/lrVWPn/tesTOhV6v1v504YqzdnjxjnlCbHy+7xkq6PSGbek0g/4kAahquwlWUJSdIu09lXrt6nusnijBYh8EPASqKsQuxyN9cXEx+zcap37C46GUbNPJczSKHv6XSjRcjvXIKcNoFLvQUTILszjqUo9GDteRlrCmKuNck4rOzzLIytONH8uf+UePyXXs+jsuhuYi4wAIQAAChgBCzA6DwkBcdHUjOF+qtqMHth2LCLGeIOzSrmJ2eX4giLm6Pp6/ln3iC0kUYvSIJebHgZtLoDJCzMyD6nUP9e52S9dDowLsh0i1um5t7+rDkzN9kaZlfTnQ+ztbutVqTf9t7+vB7PxL3Ttqh997aPLa2jsKzXGdL1JG+ux4X281pfew1XRza1cfnSYdkWDi2th+sLvt2r61rQ/P0rzV0bo2xvrcsN1pNcT5wvXmtj446c3Eyvwyzrveis7PKuJAdw87erspDcW34mfK/tCUUx5YH1Gm2Ngx51xemHzbutUQ5nVbMbS7r08HqXKMMITdEIDAphEoTH/kCHaNesQu9dF2uCL39nilF2Jjvd90esHcT7PqYTrklz3dCgpE830vYp5YusSto0daWiqbOWLpSXLG5hGoghDrHe3pulDHWHNFo//V9d7RdLTAPK+PTvdC6Uzrr5E+iF0YqR6aSxsnUi7ODiMXHwqVo7Gre9Edb7MiSbbHDg2fnTndsBZEakUJ2yDf+rbuGo13ed4J8UpaHxednyUyu/vTuckhxsHyzb439MFZsieJEn/n3jfo7ocfns7y8Mduq92dCd2Ai/gKAQhAQCSAELOxFAFi3Avf+JTpEZo9tDW2pBZi41OxUbB/nuDu7wsJ+eWumb3r6+JEvJk5QzJ9pvAFAhDwEVhvIXZhhJDUc+RvxMY1sK2FjObVaJJ46pz1xYdf/rzCL06W0mp1TvXZYVoxYJVxa+6LmaX8koqiUW9f7AHzlzHIuqF3d8OLNCXJs+j8tBkg3xYeNsaXzy3vzuH8QfoS/05vqE8jFrKKy7ux1/Vdu3yBAAQgEEegCP0Rl38Wv61Jj5i0WEV46N8iQiw01FE1dPqOLLm3LsmNeb4Tx/pAfNH0InbOz40jIFA1AusrxC50R7z23YZyXKPW+5v1ovk4MSY1pr3nR283Q/Xl4mlFlKvRjp0LK+WXqO41ry1J38sYYaPp5ZmbZ9H5WSIs9qXjNd1omqGokUMVp2XdnTNCROIfHS/R/Jxz9qwuR/4gAAEIJCCAELMh5Q2if7gVGgbSbJ+FXJReiJ2Fe8TMIhspByZO7JDynntjDpUguONCH+7I4/nrPDkMwuI7BEQC6yrE5NdqTBuyLWteTW+gR2bxg8vJghdDfXZyaOb/hIdvOw3cuCHX/sa0m0YtMGSvtbOnO509vW3mUk3TDT8Q8qcV1fCu6e32oT47H0wWG+n3urq97aQZPmcrpmdGym9+3SsP93bKtHdwovtDs2DHcDDlGprf5DJy+MbnWXR+WkfFT621p7v9oW80yWQe1/5O6D47LVu419N7oUn8HSbuZ03vdI50r2/e8zbo61MzRzByOGijk26OmtcYtiEAgY0ikLf+KAJm+XvERtLwQfmFyZIY8s4hCwIVV0w0T18XmTZ85ntR87QhEX9jDlrjfh9fmGEdR53w5HhnbH1jL9MVGd2c2YJA9QgUKcTaZ4vUHgLz4VHEkLmWPnFX0RBONK/xOIxqULsLGwVPDDema/78a9v6dOgdCG7mSZmVBYfDcHnDaQWEVXNPn4dPm5g0ON6VxYBnUab5ts/vnRKHulv1q5mX1vcXc5Zd7yjCNrtejqvvi85Pm963mnO/8Hw2zTysuL9x/0geBn8QPURxcX9HDZsMj3aJs5nfIACBzSWAELN9nyeI453w/IjdrjyJOK0QE28g9cWE2PlBuNcu7sZsTaA+NvMM6vWGbjScf3UdfAI9eaJYcxtFtVbbs5rZ5l58lBwCSQkUKcS2D86MOBno/mCgB3P+9ft9PRzJrf7ubrjeU2bY9Ilc9YVQnEXMz4ka9iXWhbMG/HaiRTMcI+LSqm8fzn3QdSq8hsSqB6Pm7kr5xde9Wh8LCz8pFd/zY5Vv1DsQBY5lX1yeRecn9YbVtg79vWCOwwKfo2544Za417FI/J2esLnzE0fCSsiGZWs/WvgFzOUrBCCwwQTy1B9FYS11j5jYY9Xcj5zrsEohJj7xNKIucrS76ekLz08LPDmeNYSs/TXdOekXFRfkA4HKEChSiDkN0OSfQi/V+ExchXX7KM2gaWleralHIhrj0Y3puj6a0wMXDJSotGpbCV9Af3mut3x137RejBI6Un5Rx05sFUdZKJ2U7zhCjEXmWXR+4iq+NX2UUMRbC3zs1sP3ooOIRawk/lb814zojpuX6MTNifCwNZKlcxKfEIAABAwBhJgdBvmAuNDt0M3A3ExiGgWrFGIXwlNEa4K8/LzbgEstxMyNcfLengPdjxjWw1UJAQiECZRbiDXCy7+ftoXheS3di6xMwmW29khza5Uyw7qFdKIa01uH6R/+iGmZ4dRpZKTYIxjxYEvKL64hLx2fpDfMS3lwFB7+GZVn0flJDwWT9oY5ZZSG2kcN8xfLZ4b4J9V9F8KrE6JYOvbxCQEIQMAikI/+KJZtaXvEBkfhpY7nVc6rFGJRN6NozTTQO8JT32RP0mu63U3TrCk2qMgNAmUisG5C7KzTDAmx2vZxeqQDaZ5ZXZ8I3fRi/WVGH0TXX9HmSGk1hMWVolPQ+qIrzMeq74kjDMT89k4jk+9Ly+ibV6Ek6b1xEh2fhcVy1P2p6Px6++Gl9Vsxc7ycMnk/Jf5phrWm8bfsv/i5bF5b2YYABDaXAELM9n3mIMShOVtznwivUoilnyNmTXYf6F6v5/t3dnaqT44O9N7Olq4HViwLirSdo/RPqzf3cqXkm0qg1EIstEKc9bqK8Ip8UY3geJ8O9K5Qh0g9G2JjOKV4cmwR04oRRs55vs8Lae5QuPfQOidtfqfCwkpp3/mYJs+i8+vuhlefbOwe6tNuV5+cnMz/Z4477iR/EJqGhc/HzhdpdEhE76dzCp8QgAAELAKZ648VYC1lj5g0LGXneP5Ah0yEWAlWTXTj4FKfn+zHzCWr6QRY3OTYgsAGEihSiO0c9yfLyY/NsvLz/o1GZun5kD/kl8PvpX+5oUlZXjI9sRBLK57ssizdMLfSGUur5WYjxKT7RDsl3zRlLDY/OX6CD/EW+R7V45eGhR0i/g/J1wveh/0J8w0CEKg6AYSY7eEsQVz2D0PDclSzk2iITNob3vj8IJxXzDLJcQEt5R1144pLR/ztsi9Onp7cTM3k+zRDasT02QmBChMoUogtJpi88JOLJ+9Z8rY0z1bpTi884HDpxrTHgEzSMo3z8GJG8qqGafM73Qv3GEni1FOk0GaaPIvNT46fRYRX8Jyo+1kaFiGQ1g5JiC24erGYPjshAIHKEshSf6wKUsl6xC71kbCs8N7pUI9Ho8mLPy8uzEs2hX+j8UifCEMyto/OzZNp99yx9xG0GQLZDM3Tkp+6znOQJMTqCz5RFvO6OBEaJtbKVuEXqornsxMCG0qgWCEmTMBKxV1uSKcVCtMsh3o7VL8pLb3rbOnGtKeMmaQ1FB7IqaaWOq7S5SeL07R8k+dZdH5y/ARF1SLfpbix3J6chSdIvJsIMS8NtiEAgRQEEGI2rOxAmAUshDkNi9w0Is8xE75ngxylG4Ba5GWS5ubXDC/3u5v0pT8Jg06axG+VU3rCnTBJDoNA5QlsrhCTG+WS6Fi6Me2JokzSSvGQLG1+Ug9VnkMTi81PHprYbB/rczMf+ezsbKF/54NwL6rj8rT8nfNmn9J9mB6xGR42IACBaALZ6Y/oPPL+pVw9YtKkXeGJbqTISnRsU585Y/ki8tvtpn2q3RcF5PLDlPzul254EyF2Fn2T9KfANwhsHoF1E2LtRvihTlRvRLw3TW9MwrSkuiVqKFp8nhn0kFgZSI1z88LlnlN3e4xIa7s0emEn1Tva0pWx2Pxk8d2e3fQ84DLaTMs/lK3ka4RYCBM7IACBMAGEmM0kMxCmQg7PCwg3SjITYhGT2VM3QMRloj2CLxw7C+2RbngIsYVQctIGEVgvISYPz27t99J7bJTfyoNxxkj1VNo6VUpDhVaYnFohHRuXn7SKYX33JK5Iod/S5Fl0ftI7wJqds1AZstqRhoWYJ0JMxMJOCEBgPoHM9Mf8rHI7olw9YkYY7QtD/JYTXgEh5x2aaLD2hHf2qJQrNklL1yvzDh7h4e1SjpTeXWOxWWxp66VM4WQIrA2B9RJiEXXSAst5D4/DLx1WtV13aLbHg0s3puekVd9N916orrCghopgkNZ28UXXEe8o8xTLtzlK8RLi4vMLLz2vUr4nzVfYOV/S8g8lhxALIWEHBCCQjABCzOaULYixuBiHtECHd99ofKGPpcU6Ds1iHSN3gY+Rd7EOY/+41wmvnKhq+nAQODAyJuR5bVspX6AZmbznh5OdumjrUWJbPYmxCYENIbBuQkxq2KpJnZTGYWNx3mqUIJLyjOtVirNESst6YNTuzmbnxp1ufuuLi4xE9epI+cXZfimtlmv4Jh6daIa0t4Rh8FF5Fp/fvnCfMItQpR1xP8dLzs9p+TvnzT4RYjMUbEAAAukIZKs/0uWd1dEl6xFbrljSWPy5k7Ave+JNNekTxP6h8PQxasGP0bk+OjzSvWFSkefhIQ5/NL19EU+4PWeyCYGNJrBuQkxH1knJe9mHJ3tCY1zpg3O5n37pxrQnwqS0pqMaarpzNl8NiCMMYh6OSflFiaKpmbLQq20feUoRsTnu6e2IBaWi8yw6P/nhYGMvXa9kBIHQ7vT8A0kgxAJA+AoBCCQlgBCzSZUFhCTEpBXCgg4+FnualN46iJ+XMTrb1zXhyagl4iSp5R27v9U+0v1g91zQMPv75bCrt6R8zL5mJ97GiCTZDYGNIbB2Qsx4RhyaZ673xt78uUyj3oFcL0XMsbICYenGtCeapLS8w8v3zEuvo/6sdzuKdWrMcHEpv2hRNM25uyuNLlB692QQZZq+HHTlh3Z23RyXZ9H59fb///buNzSS9MDv+LOsdv6cRwuyubU9s2ZnGRscgpt4bbAPdi7pfZH1YXy9EILxbd/ihEvHhMuhvAhBb2yUFwedI3A6wtFeyMoB68CRQ1YGR+slyhLtQtpgrTkZI/tOk+05r2avxz7N0ZpcC0vmSVWrWqqueupvV1XX89R3YFfdra6q5/k8j6rr10/VUy1lEF+K+EzzVn7Y35fd7a48UOf30dvT+E9shyA2wcETBBCIL1CW/BG/xP53Gj8iFieInQSNNtlBp70u9/uTsxKeDPpye001EmZfj2ZNfx9wqqAqKDYW23Kzuyf7A/8n3aDfk1urQduxt7Uo91SJz9/OvIJAZQV0DGLSum9g3TnAd4cY+3GttSK7+33flz3Dw/D9xZpqykGnV0x9MO3qXap1eetQX1qVu+4p0U8GcmdjRR3CrDqH3QpEtb2wUGQX9aS3rgwqdjmX1rbloXu/OuzL7priejtP+4Rts+jtSeX0/2fXSzeW16yzMiY/01zNJ+3Pt93tDbncugirjZDJPtL4u7ennCGTWRMniHiCAAJqAYKY41IWCFXQiRPE7GqoT4c5++AaHUTUG7LZbMpGvRb4AT76EN8M/rZXVb6JA5RaXTYaTdlsNAIPSNzvZ5IO9R8mryLgFtAyiFkVCBrVON8HWPuLZmtRLi62IvdLQddXjZ2mPpger8j6qVrXeZk94UXY+1Vrfxf4e/v9zVVrGqfgf6rthYWiszWpZ6d0l6Nh7e+bjYsw4v7d+WPXaYrh2yx6e1IeqCZrcftb9ovLbbnS6ciVlbZcXgruR2F1S+fvak9GxFwYPEQAgSQCZckfScrsfS8jYuciQ7m5FPGh6/4QUzxudsLPwVdPDOIKe4p1nn/ge363vLl/XnIeIIBAsICuQcyuUbfTDA8pnv2Can/Ritgv2duZ+mDaXonzz7+uptzYWgsc4VOV+eK1JRlwWdt4c1OUvSfbriB1sc3offLK1o5cbU1+KRcWVs4KW/T2pNxdX5y6/9gujU7w9Pf+9rZPod05b5/IBwSxSCLegAACagGCmONSFgjViFOyUSMrjLXTHfgsrwd/ULm7z/5WJ+UBiXNwUF+UW72w74fdW+MxAgjkE8SsmyXX/QfscUfgk7TK3mY75cF0TXa2g0fo3WVIMh27eznVY/+6GnLHPtWvtyWbMYLjeSCqt5U3cPZu07+9BEFguC+XFe14XgZfea1QuWfvf4e+9o8VPorenlXSg+7qdJ85tUW5EzLHylT+dmNas1D67h+a8HYC9mr4hwAC1RMoS/6YRt6oETH/qTwNuZVihsLD/a7sLMUJZHW51NmQ+xMXFMRpjoHc627ItnUqiPLCdN+Hv3Vg0VqWG91933UhcbbGexCoskA+QcyeUMO7j6gFzko4tf+gJzc6y7IRZwSn3pQr69uy77/sNLgY/W3fwXAr7URA/S3PgX9L7p6XxbrNSGcpfL9Xa8rOxk78+zBOXfaz69PCbetyeXXLde2Yfarh5BkUUad/XuAXvT1ryyfWdc3rK7IVcWr9OIDWrNMWl9qrcnu3F/2ZM62/NROldzIq+wbb7sv0Lux4hAACCFwImBDEHrGrY+18p/rX6/XE008/PVqHhSJu3rw51fqmWfj46EgMT0+tVcyJqwvz4so0Kzs9Evfu9sSduwfiwcNfOmu6JK4tPCGeuvWkeOr6E9ZWpv13Kh7cvy/6/b8WP//5/YvtXLokFhZuiOsf+qC4ceMJcWX6DU1bUJZHQEuB119/XTz//PPi8uXL4vj4ONM6nB4fiaOhs7+Zt/Y3BfydHt2/J3rv/kz8/P4D8fCXZ/ulS5euiYUb18VHnrwpri+k3OudHoujo6EY1WZuXszPT1GZ8brm5qz1zPv3k9a+9e7+X4q/ujfe51n71Q9a+9WPPC1uXV9I3kbj7VlLzqUuu7UvvndX/MWdu6L/4OGoDJeuLYgbT90SH7t1XflZMv68mbt6VcxfSepe9PbOWI+P7ouDg3fFvXN763X78+Z9C+LXr39IfPDGDbGQtCNP7X9q9b0jYX90z81ZlvNJLc/qxv8RQKBaAmXKH2nljQtiaSFYDgEEzBTIM4iZKUatEEAAAQQQKL8AQcxpIxMgyt/dKCECCKQRIIilUWMZBBBAAAEEyi1gQv5gRKzcfYzSIYDAlAIEsSkBWRwBBBBAAIESChDEnEYxAaKE/YsiIYBABgIEsQwQWQUCCCCAAAIlEzAhfzAiVrJORXEQQCBbAYJYtp6sDQEEEEAAgTIIEMScVjABogwdijIggED2AgSx7E1ZIwIIIIAAArMWMCF/MCI2617E9hFAIFcBgliuvKwcAQQQQACBmQgQxBx2EyBm0oPYKAII5C5AEMudmA0ggAACCCBQuIAJ+YMRscK7DRtEAIEiBQhiRWqzLQQQQAABBIoRIIg5ziZAFNNl2AoCCBQtQBArWpztIYAAAgggkL+ACfmDEbH8+wlbQACBGQoQxGaIz6YRQAABBBDISYAg5sCaAJFTH2G1CCAwYwGC2IwbgM0jgAACCCCQg4AJ+YMRsRw6BqtEAIHyCBDEytMWlAQBBBBAAIGsBAhijqQJEFl1CtaDAALlEiCIlas9KA0CCCCAAAJZCJiQPxgRy6InsA4EECitAEGstE1DwRBAAAEEEEgtQBBz6EyASN0LWBABBEotQBArdfNQOAQQQAABBFIJmJA/GBFL1fQshAACuggQxHRpKcqJAAIIIIBAfAGCmGNlAkT8ZuedCCCgkwBBTKfWoqwIIIAAAgjEEzAhfzAiFq+teRcCCGgqQBDTtOEoNgIIIIAAAiECBDEHxwSIkHbmVwggoLEAQUzjxqPoCCCAAAIIBAiYkD8YEQtoXF5GAAEzBAhiZrQjtUAAAQQQQMAtQBBzNEyAcDcsjxFAwBwBgpg5bUlNEEAAAQQQGAuYkD8YERu3Jj8RQMBIAYKYkc1KpRBAAAEEKi5AEHM6gAkQFe/LVB8BYwUIYsY2LRVDAAEEEKiwgAn5gxGxCndgqo5AFQQIYlVoZeqIAAIIIFA1AYKY0+ImQFSt81JfBKoiQBCrSktTTwQQQACBKgmYkD8YEatSj6WuCFRQgCBWwUanyggggAACxgsQxJwmNgHC+N5KBRGoqABBrKINT7URQAABBIwWMCF/MCJmdBelcgggQBCjDyCAAAIIIGCeAEHMaVMTIMzrntQIAQRsAYIY/QABBBBAAAHzBEzIH4yImdcvqRECCLgECGIuDB4igAACCCBgiABBzGlIEyAM6ZNUAwEEPAIEMQ8ITxFAAAEEEDBAwIT8wYiYAR2RKiCAQLAAQSzYht8ggAACCCCgqwBBzGk5EyB07YSUGwEEwgUIYuE+/BYBBBBAAAEdBUzIH4yI6djzKDMCCMQWIIjFpuKNCCCAAAIIaCNAEHOaygQIbXodBUUAgUQCBLFEXLwZAQQQQAABLQRMyB+MiGnR1SgkAgikFSCIpZVjOQQQQAABBMorQBBz2sYEiPJ2M0qGAALTCBDEptFjWQQQQAABBMopYEL+YESsnH2LUiGAQEYCBLGMIFkNAggggAACJRIgiDmNYQJEifoVRUEAgQwFCGIZYrIqBBBAAAEESiJgQv5gRKwknYliIIBAPgIEsXxcWSsCCCCAAAKzFCCIOfomQMyyI7FtBBDIT4Aglp8ta0YAAQQQQGBWAibkD0bEZtV72C4CCBQiQBArhJmNIIAAAgggUKgAQczh/uEPfyieeeaZ0bMvfvGL4tq1a4U2BBtDAAEEggQODg7Ea6+9Jh599FHx5S9/OehtvI4AAggggAACGgk8fPhQfOtb3xqV+O233xaf/OQnNSr9WVEzGRF76623xO3bt7WrPAVGAAEEEEAAAQQQQAABvQXefPNN8eyzz2pXiUyCmHtE7IUXXmBETLtuQIERMFfgvffeE1tbW6MRsS996UvmVpSaIYAAAgggUCEBe0Ts1VdfHdW40iNiJpyjWaF+S1URqJQA14hVqrmpLAIIIIBARQRMyB+ZjIiZAFGRPks1EaicAEGsck1OhRFAAAEEKiBgQv4giFWgo1JFBKosQBCrcutTdwQQQAABUwUIYk7LmgBhaielXghUXYAgVvUeQP0RQAABBEwUMCF/MCJmYs+kTgggcC5AEDun4AECCCCAAALGCBDEnKY0AcKYXklFEEBgQoAgNsHBEwQQQAABBIwQMCF/MCJmRFekEgggECRAEAuS4XUEEEAAAQT0FSCIOW1nAoS+3ZCSI4BAmABBLEyH3yGAAAIIIKCngAn5gxExPfsepUYAgZgCBLGYULwNAQQQQAABjQQIYk5jmQChUb+jqAggkECAIJYAi7cigAACCCCgiYAJ+YMRMU06G8VEAIF0AgSxdG4shQACCCCAQJkFCGJO65gAUeaORtkQQCC9AEEsvR1LIoAAAgggUFYBE/IHI2Jl7V2UCwEEMhEgiGXCyEoQQAABBBAolQBBzGkOEzHRMosAACCXSURBVCBK1bMoDAIIZCZAEMuMkhUhgAACCCBQGgET8gcjYqXpThQEAQTyECCI5aHKOhFAAAEEEJitAEHM8TcBYrZdia0jgEBeAgSxvGRZLwIIIIAAArMTMCF/MCI2u/7DlhFAoAABglgByGwCAQQQQACBggUIYg64CRAF9x02hwACBQkQxAqCZjMIIIAAAggUKGBC/mBErMAOw6YQQKB4AYJY8eZsEQEEEEAAgbwFCGKOsAkQeXcW1o8AArMRIIjNxp2tIpCJwOmRuH84HK3qsauPi4X5K5mslpUggID+AibkD0bE9O+H1AABBEIECGIhOPwKgRILnN79jvjUzYbYdZWxtbYnvv47H3e9wkMEEKiqAEHMaXkTIEI78emxeHA4ECfnb3pMXH18XsxfmTt/hQcIIFBOAYJYOduFUiEQJXD09tfF45/6ysTbGis74tU/eGbiNZ4ggEA1BUzIH0aMiP3ktW+Ir//3LfFO/+i8J85/8Gnxid/4gvgXX35OLJy/Gv/B6dE9sf29b4tvffNV8fLGG8oFa/WmePGlF8U/afwjcWsh+9Ml8qiXsiK8iIDBArkFsdN74rX//E2xffdvxZUr1t//8bEQVz4k/sHznxe//ZlbKUXvi+/8yR+L7/74b0bL/9qv3RBf+P1/I567NZ9yfYYtdnRXfHv1v4i3//r4zDxF9exm+s2X/rX43MfTfDKk2CCLpBY4+pEVxGoEsdSALIiA4QImBDEhM/j3zjvvSKutR//Zj4v8d9hdOd/2uAzunys7hwmLM5BbK4uh63Svf/y42d6USbcUVrDs6xW2NX6HgLkC3/ve90Z/z5cvX860krudRuB+ot7eTrWtwa5/f1Zrd1Oty8SFdlbqgebjfXGcn5jq0TsGux1fe1sjYnoUnlIigEDuArPMH1lVTvMg1pNLTgAM+vBNFsQO5ErjLFAGrS/09WZH9jNpmazrlUmhWAkCWgrkE8QGcjViX9HZHST20uvA80QOBoOz/4YnieuafIGB7ESYh+6fXZ8V9eWt5JtnicIF9Pp7KJyHDSJQeQGCmNMFZgWxt9r0fVvm/SCOH8QGcq01RQhzPuRrS5ty2kOSbOtV+b9TACouMKsgJuorib+Y0ebAc7gnW65gY+93rUkUcu5p0eHXu/8Pel5bTjdimXMFWb1HQJu/B0+5eYoAAsUIzCp/ZFk7fa8Re/CmeO79vynesD5pw/5ZQUz8wTPR1wL85M/+pfh7L76sWFVNLK+2xYv/+DPixvuvipOTgbjf+6n4n6/8R/GVP95QvF+I5a0D8dXnrit/F/lixvWK3B5vQMBwgXyuETsS33jhcfHP1LuAc9Gk+wJtrok5elu88PinhLv6+U+iEGBeb4mlz37g3Dz8wVAMh1dF/Z//W/Hbn4j+XAhfF7/NW0Cbv4e8IVg/AggoBbhGzImExSfSE7mxWIscDbNaTcYaEetvyZrn2117WVFflnshZxf1ttoBZViSvVRxOeN6pSoDCyFglsDMRsRG+5QluZ+AU5sRgOGObHr2mflfu6MeEevsDhMI81adBLT5e9AJlbIiYJBA8fkjezwtrxEb7Pgv4K0vb8qdtZYvGMUJYt0V1UX3TdkNCWHjpthb9W/TDnGdnRgLj1fi/My6Xp7V8xSBSgoUE8QuvhjyfqnTXI1/yp42B54lCmJx9vGV7PgGVFqbvwcDrKkCAjoKEMScVisW4kAu17zXcjVk1/pSVHVtVfSHtHpijMX1uGNa6uXriWc6y7peOv5JUWYEshcoJojZ+6SGbDVVs/pZ+6eY38toc+BJEMu+o7JGn4A2fw++kvMCAggUIVBs/sinRtqNiO0rRr3GF4nvdvyTd0QFseH+mm8UTYjFRKcTqQKgqLUTXaifdb3y6S6sFQH9BIoLYi3Z3duUdc8pe/YIedzp7PM48DwZDuTh4eH5f4MsZjg82fWfmtjZzblzqE9NjNrHZ1moXCyzLGCG6zoZDuXA6TeDQR6nf9qzbo775UCqumUefw8ZErEqBBCYsYAJQUyvyToefF+88P7PTlwgLmrL4uDPvyrsqTF+9PXfFbWvfNN6dPHP+pAOnaxDNUmHNaOW+POv3r5YScSj0zvfFo999J963lUXW/3/JZ57wvOy6mkO9VJthtcQqKJAcZN1NMTuyavi7/7wOfHZr73hoa6JzYMd8bnrc57XJ59mMjnB6ZH4yc4b4jsb3xWvffdl8cbu5DZGz2p10fr858Tnf+u3xO3f+IRYCC+WENbNq7/9p98U/9e6GbJ112rr5tU/Fv/ua57JjaxJM9ov/P2zG1u7Nnl8fEU8/3st8Znr0970Xj1ZR9Q+3lWU5A/zsByX4sGPxJ/80Svix3/zd2evWDfv/mKSm3cf3xHf+A//SfyfA2d58QHx+d+PmITEasc/+8M/Ev97vMwH/qH42r//HXHeLU8fiO//j/8qXnnlT8XLG56OY/WZxRd/T/xu8wvimetpbzB+LO58/3Wx9sor4r+9vCE8WxD15pL4V62XxAu3Py7sLpnJ38PYm58IIGCcAJN1OEm4mER6IjeXLq7DsHrTaCTL/W1o8hGxoVxrek9zFNKa6SxZxj/xT+Vsl28l1nViedQrWfF5NwImCxQ3ItaQO/bAweG2clRMtNYjb20x7QjA3uaKetuKUbrxPlSIulzZDL+ObbDjv9H0xfL+faj3d/V2FjfhLXZELC/L8d+ayjTJKe1pllctM/6cOuiuyUZoP7lo51anG9mXx/Uc/xz2tmTLd1nBxTon+kx9SXYPpTzZX/WdsZL/pDDjEvMTAQTKLlBM/shXQZtTE4d7/h2y98AmcRBTXOdgfxis7Sc9DUN9o9E4F+nnUq98+wxrR0ArgUKDmHMt2I5yAiAhVyNu8pw+iB3K9UXV9WkBB7qKA257wqOgPZ+qXBMHzor1uX+fzcFzUUEsX8vxH4/KNIlTmuVVy6zu9eVOwKRT7jb0Pm6sdMdVifw52FtTz0wc2m8ast32T4aVxCiyYLwBAQS0FiCIOc2XP0RftuveA4q63OpP9p80Qcz/DaD1rXbMC+svtq4e1Yr+wMipXhcF4xEClReYRRCTQ/81VKMD2XpHWl/0B/5THShH70cO5WoGN6O3y2ffkF4VxlQjKd4D87DntcSTF6mIighi+VuOa5aurcdLS5lmedUyYe0W9bsVe9gq6p91exjVdZNR6w76ffTfQ1SB+D0CCJgikH/+yF9KixGx3sai7/SEpuLC8ORBTHGwZE2ykfDExFErqbYd9YGRW73y7zdsAQFtBGYSxCyd/XX/fss+uFze9nyD5JJUHShH7UfUt984++Kq1V6TO3sHcmBNvHByYk++0Je72xtyqek/zXt84Ks8NfukL7fX1+X66L8Nub667B/haCzL9Q3rd+fvO3v/2tqG3O2r4p2r4rEe5h/ECrF06pqmrd1MaZZXLTNu94ufNbm8uin3egeyf9CTO1trwacUNlZl+PeW6jY721ZDrqxvy17fmrCjf3DWLxveful9LmTU34PbiMcIIGC2AEHMad9cIQb+G4cKob5hsioMua8h83ZH5YyJjU7EB4t3LWfPdzv+e5GFfmDkWC91CXkVgWoKzCqISeu27kvKU6/U+y+7dVQHyqH7kf6mPxCNttmS2wcnoQ2+t7Hs+4Lr7AB5OfrLqBLNmtiJON0zFMH9y4ItE7e1u6zW4zTLq5a5CGBWeG+uyH1lsurLjuJ6avv6Qu+ZKe5iKk+9t/tnoy17Ad1zb7Md0C/PvlwI/Xtwb5zHCCBgvECu+aMgvdKPiG0t+697aHfV3ygnDWLKDyXr1CHl51BEg6i+/Q77wMizXhFF5dcIVEpgdkHMnrdDfVDZWttXtoFqnxS2H+m2/ftH+35mIYNuE9vdDbg2KPKUM8X1tWHlnNho6ifq0ZWl9V3Zt0ZUegcH8iDiP2uGLdkfqBNA0ZZJ29rLlmZ51TLjIBZ2jeBo24OucjKPoL5sL7OlmGBLiJbcjRggHeytB3zBwIiYtx/wHIEqCxDEnNbPC0I5YtVcU17DYBdllkFM+c1fwPUgederyn+U1B0Br8Asg5gVxWSncfZN/viA9+xn82yGRU9hVQfKgQHHug6tpRhxW9pMcnK16jpVq7yLG+Gz4pUoiE26qqy9rylG/GZgmaitPf3EfppmedUytl9taSPwc9W96W3FF6OB/VN51oeQcfvnMCCMBW7PXVAeI4BAJQTyyh9F4pV4RMw6gPFN0FGTmyGn28wyiB12/dM72xe++797zb9eRXYgtoVA2QVmG8SkHFozxqnCgmqqctWBctCB52Cno1hvS+75dzqhTaS6VnV0+nfYerQOYg3Z9Zz2MAvLJG2tasA0y6uWEdbp+OpzTPxbPVTcxiCwf+6q+2fUaJh7qweb/tNng7bnXo7HCCBQDQGCmNPOeUAcbC75DjKidsCzDGJBH3Cez3tZRL2q8edHLRGIJzDrIGbdDUluLPonHVBdX6PajwTt93ZXm759ZG1pKx6K+10HquvM6nI7bEI8w4LYLCyTtLW7ucaP0yyvXEYx8dV4G96fyuUDprHvbfg/w+1bzkSclTixyaEizAX9PUwsyBMEEKiEQB75o2i4co6IKU8TWYz8pneWQSzWNWIF1avoTsT2ECizwOyDmKVjTeFdU5xG6D0FUH2gq7oZ8lCut/zhLvLaLmVDHci24ka7YRMdSZ2DmG+mv9lYxm9rZaNldmpiomBjnW7ou+VLwCn4O4oJrOLcW9Nd22mN3OviMQIImCdAEHPaNGsI1UXTy2FTMznlyCSI5ThrYlH1Mu9PjRohkF6gFEHMKn7Q1OhrexdjBPEPPNU3kV9JfhNEq2TqSTB0CWLLW73R1PxDa4r+qP8GA2saf19Xmo1l/Lb2FXj0Qprl0ywzsXVFALdPbfSe+WEvo/o87iTsn1OXd6LwPEEAAdMEss4fs/Ap3YjYSW/Dd7qNaK4qd/ResKQ7/uH+un9bNcWF3N4NKZ6rtu3+prHIeimKx0sIVFagLEFMNYo0unbMNUIT/8AzRXgK7AGq61aFXN1THV47K1EckLv3d4GbmuoXQXUOKWes7QWtN+zczKAVx7eM39bqbaVZPs0yE1tXtLsImGl4Z8V/S5fQcD+xobMnU5dXsU5eQgABcwQIYk5bZgdxIjcV092u7PTlcDCQh4fWjR8D/hsMB3K77d/xL23uW9+SXiw7dH8dap0q2PSdLuS/kDtOl1UFsfrK+JSigusVp8C8B4GKCJQmiFne++st/5c/1j5ofIAa/8Azy/DQV97vLPT+XIoD8tkFsTSByd35Z2MZv63dZb14nGb5NMtcbNF6pGh3dRBTB9JxP59YZ8iTqcsbsm5+hQAC+gtklz9mZ1GyEbEDuay4VkE141jq1+orFzNEqT5UIm5QqW4q64NccbPL9vnNfAqul7qQvIpAJQXKFMQCb/Js7ZfsOBF/coIsw0OKdSn2nQQx+88rvuW0ISPN8mmWmdhpKNpdHcSkVI2IcWrihCZPEEBgSgGCmAOYGYTqQmDfiJX3njBJnzcvbiYZsL12N+k3rD1lgDy/XiNgO6nDpNLEVa8pOzaLI2CSQLmCmDVvR8BNntvWnOone/4pv9UBR31dU+goVmCjWqMXinudha5LcUCuLmfgRlP8In7ISbby2VhOG4rSLJ9mmQlLRbsHBTHVWSLLie5xl+5eaRPl5QkCCBgtkFn+mKFSuUbErJ28b0YmZehIGr7c73cHFvUHe+IDCuX0z67tFF6vGfYoNo1AyQTKFsQCb/JcW5EH/a5vH6jeH6lPd26t7SXXH/i3KUTEKdqKA3J1OZMXJ3gJ9f466elu/vXPxnLaUJRm+TTLTHgp2j0oiKlmTay3tydWF/Vk6vJGbYDfI4CA1gIEMaf5soMYyDXFKX6Zjhy5T020yr+nuBdP0CxQQb1VNXW9aK657pdSfL2CysrrCFRNoHxBzL7J86ryWrHl9XW56PnyKSjgKPddAVOJh7V5f8t/01xRa1+cwq1aWHFAHlRO1eLpXssriAV8DuRsqbqJdJKgMkhwc+Wx99TBRtHuQUFMeaNw5xTccXmifqapY9Q6+T0CCJgjkF3+mJ1JuUbERg7DwAk5gibqsF8fDA/llmqyjg1rso7BxSQfA/dkHdb21AdENblx4HljYBupr/9aXN/3LFFsvTwb5ykClRUoYxA7u8mze6Q++HFQwFEdVAth77uSNPVQeX1rvd0NX4nqgDxgGvPwFSX5bX5BbBaWyll7RcxZe4d7vsBuf2EZ1FfGyqp6Ri0zXnb0U9XuAbMmnqhmJbb6Z+yzE61T+lueLyXi1HGivDxBAAGjBQhiTvOWBUJ1TnrkxcEne8qdvWitu0a0gvtxb2NJ8c12Xca47VnwSj2/SVUvzzp4ikBVBcoZxKzW6G+qb/LsOfgMPFAO3He5R+PDW72/vaLYfwm5vn9xbzPlGpQH5K6JkJQLTftifkHMujgv4HMgR0vLUHUqfui1eTbhyb7ymuQ4IaXIIBY0MU1taTO6I1hBcylg4q7Av4fotfIOBBAwTKAs+WMa1hKOiKWvjiqwxLl+YGu5rjwYWVwPv95isLumPpCyQlzc8bQ4tU1brzjr5j0ImC5Q2iBmwXcVo/jeU7HDDjyDbhLdWIm+Fmewt67ef7nuaxbYN5QTECUdjQtce8Avcgxidlso7nt1Fm7yslRP8iSse1n2AgRkf0cuBgSU8gUxu3+rP1vb28HDticHXXUodr6gCPt7CGLjdQQQMFOAIOa0a1kg0gaWE+VkG2enCjXb63K/P3nD0JNBX26vqUbC7GWs0bDYpzXG+8NIW694a+ddCJgtUOYgJq1A47+X4eRpiqEHnofbsu4ZQRsHuVprRXb3+74vhYaHPbm1GrT/EnJtL2I0zO4u1qiM91q20XZrS3KnP/4a6kT293fkeqcjt/aSzkSr6pP5BjE5A0vldX52e9aXZbfnMjs5lDsbbXVwdrV/aF+xSIsdEbO6SW9d+SWn3VeW1rbl4bir2M097MvumuJ6RVf94oRNVc/hNQQQMFOgLPljGl1GxBw95YQb7g+AekM2m03ZqNcCP1hGHy6bgd9lpm4nglhqOhZEQJY6iFnts7+mvsnzKNhY+6Cog+u9iOVFrS6brUW5uNiK3H81V3dj95ig0Y7RwXKjMREaIq85i7XVnIOYVYbCLQ+3AoP0qP1rDdloqEeVxv1DuEbIovpK0UHMvhZycyn8M7Nhfa42M6xjrK7EmxBAwAgBgpjTjGWBmC6wDK0PjIgPPHcwUzxudiIucE/Z7aerV8qNshgChgiUPYgFXUszPtCOOri2m6nbaYZ+QTReV9jPVsL9V9hoh3c7qabV9/W//IPYLCwjw5/is8b27XR35VprMuRE9ZXig5gt2pNtV1j09o2w5ytbO3I1YR193YYXEEDAWIGy5I9pgM0fEUt0c2YrjLXTHdAsr8f/JjlpgymDWKJ6Jd0i70fAHIF8gph1E+T65CmEkffeCiEd7Kqns7cPUusrOyFLXvxqb7OdMozVZGc73Uj+zmr4aN74IDubETGVuZBxrgO+UIr3qGjLZEG6KTf37NPlh74bcUcGsRRT3k+Iqa4NjDMl/dCaYMT39+L9+3E/b8qNcR09y0XVcaK8PEEAAaMFCGJO85YFwv/NYsOavdB9Enq8/ni435WdpTiBrC6XOhtyf+JE93jbSPKurOqVZJu8FwFTBPIJYvbkDt59xKKMc3lVkOtBd1U2vCMH9SW567pUKGjZ89cHPbnRWfavRzWqUm/KlfVt2Y9xSdj5+hUPetuKcru3V1uU2xldN+s3r0XP8Kgoc6yXCrY86K7LVuip73W5vLolL7rDUK633OFFyNZq+ARTsr/tm6kxchk3lmLafPveZ/E+ZQfWdW4rEX3TqeP5Cu1TGyfPVEly+qy76DxGAAHzBMqSP6aRfcRe2PrWcqp/vV5PPP3006N1WCji5s2bU61vmoWPj47E8PTUWsWcuLowL65Ms7LTI3Hvbk/cuXsgHjz8pbOmS+LawhPiqVtPiqeuP2FtpZh/mdarmCKzFQRKIfD666+L559/Xly+fFkcHx9nWqbT4yNxNLT2N3NzYn5+PpP9walVRnsPZu/DrlxJv4c5un9P9N79mfj5/Qfi4S/P9l+XLl0TCzeui488eVNcX5hq7+hxPBUP7t0V7/zsnvjb/3cixGOPife979et7dwQ15+Y97x3uqfn5vY+3jKfgih2QYq0PLp/V/zlO38l7vcfCLvVLl1aEDc+dkt87NZ1xefZqTiyPvPsj7y5q/NiPg7G6bG1zHDUx+bmrGXmk/Yx1zbnrlrLJ+1HZ33lL+7cFf0HD0dtcOmaVcenguooxPjzb+6qtb0rSbcXu5l5IwIIaCZQpvyRls64IJYWguUQQMBMgTyDmJli1AoBBBBAAIHyCxDEnDYyAaL83Y0SIoBAGgGCWBo1lkEAAQQQQKDcAibkD0bEyt3HKB0CCEwpQBCbEpDFEUAAAQQQKKEAQcxpFBMgSti/KBICCGQgQBDLAJFVIIAAAgggUDIBE/IHI2Il61QUBwEEshUgiGXrydoQQAABBBAogwBBzGkFEyDK0KEoAwIIZC9AEMvelDUigAACCCAwawET8gcjYrPuRWwfAQRyFSCI5crLyhFAAAEEEJiJAEHMYTcBYiY9iI0igEDuAgSx3InZAAIIIIAAAoULmJA/GBErvNuwQQQQKFKAIFakNttCAAEEEECgGAGCmONsAkQxXYatIIBA0QIEsaLF2R4CCCCAAAL5C5iQPxgRy7+fsAUEEJihAEFshvhsGgEEEEAAgZwECGIOrAkQOfURVosAAjMWIIjNuAHYPAIIIIAAAjkImJA/GBHLoWOwSgQQKI8AQaw8bUFJEEAAAQQQyEqAIOZImgCRVadgPQggUC4Bgli52oPSIIAAAgggkIWACfmDEbEsegLrQACB0goQxErbNBQMAQQQQACB1AIEMYfOBIjUvYAFEUCg1AIEsVI3D4VDAAEEEEAglYAJ+YMRsVRNz0IIIKCLAEFMl5ainAgggAACCMQXIIg5ViZAxG923okAAjoJEMR0ai3KigACCCCAQDwBE/IHI2Lx2pp3IYCApgIEMU0bjmIjgAACCCAQIkAQc3BMgAhpZ36FAAIaCxDENG48io4AAggggECAgAn5gxGxgMblZQQQMEOAIGZGO1ILBBBAAAEE3AIEMUfDBAh3w/IYAQTMESCImdOW1AQBBBBAAIGxgAn5gxGxcWvyEwEEjBQgiBnZrFQKAQQQQKDiAgQxpwOYAFHxvkz1ETBWgCBmbNNSMQQQQACBCguYkD8YEatwB6bqCFRBgCBWhVamjggggAACVRMgiDktbgJE1Tov9UWgKgIEsaq0NPVEAAEEEKiSgAn5gxGxKvVY6opABQUIYhVsdKqMAAIIIGC8AEHMaWITIIzvrVQQgYoKEMQq2vBUGwEEEEDAaAET8gcjYkZ3USqHAAIEMfoAAggggAAC5gkQxJw2NQHCvO5JjRBAwBYgiNEPEEAAAQQQME/AhPzBiJh5/ZIaIYCAS4Ag5sLgIQIIIIAAAoYIEMSchjQBwpA+STUQQMAjQBDzgPAUAQQQQAABAwRMyB+MiBnQEakCAggECxDEgm34DQIIIIAAAroKEMScljMBQtdOSLkRQCBcgCAW7sNvEUAAAQQQ0FHAhPzBiJiOPY8yI4BAbAGCWGwq3ogAAggggIA2AgQxp6lMgNCm11FQBBBIJEAQS8TFmxFAAAEEENBCwIT8wYiYFl2NQiKAQFoBglhaOZZDAAEEEECgvAIEMadtTIAobzejZAggMI0AQWwaPZZFAAEEEECgnAIm5A9GxMrZtygVAghkJEAQywiS1SCAAAIIIFAiAYKY0xgmQJSoX1EUBBDIUIAgliEmq0IAAQQQQKAkAibkD0bEStKZKAYCCOQjQBDLx5W1IoAAAgggMEsBgpijbwLELDsS20YAgfwECGL52bJmBBBAAAEEZiVgQv7IZETszp074qMf/eioHd58803x5JNPzqpN2C4CCCAwIWDvk1566SVx6dIl8dOf/nTidzxBAAEEEEAAAT0F3n33XXH79u1R4ff398WtW7e0q0gmQeytt946h9BOgAIjgAACCCCAAAIIIICAtgL2l67PPvusduUniGnXZBQYAQQQQAABBBBAAAEExgKVDmLHx8fiBz/4wcjiwx/+sHj00UfHLvxEAAEEZipg759+8YtfiEceeUTcuHFjpmVh4wgggAACCCCQjcCvfvUr8d57741W9ulPf1pcuXIlmxUXuJZMRsQKLC+bQgABBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0EyCI6dZilBcBBBBAAAEEEEAAAQS0FyCIad+EVAABBBBAAAEEEEAAAQR0E/j/SlJ9FonxAcMAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:25a506ff-7f4f-4001-8f2b-8c5bbec79ac6.png)<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/status_code.png\" width=\"300\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"RP\">Requests in Python</h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Requests is a python Library that allows you to send <code>HTTP/1.1</code> requests easily.  We can import the library as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will also use the following libraries \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "from PIL import Image\n",
    "from IPython.display import IFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " You can make a <code>GET</code> request via the method <code>get</code> to [www.ibm.com](http://www.ibm.com?cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ): \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "url='https://www.ibm.com/'\n",
    "r=requests.get(url)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have the response object <code>r</code> , this has information about the request, like the status of the request. We  can view the status code using the attribute <code>status_code </code>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.status_code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can view the request headers:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'User-Agent': 'python-requests/2.25.0', 'Accept-Encoding': 'gzip, deflate', 'Accept': '*/*', 'Connection': 'keep-alive', 'Cookie': '_abck=336901B2E603718CBB9506CFBE6C90F8~-1~YAAQrXzTF0Dej+t3AQAA+G8uBQWhLf4YAHgizfenHsDGzoSc9pfJ0a6qInLVaCNLc7gLe11dF2xWCxZuxbIKiPODke+0aVkwMSsw0zT7aIhTbIZ+cx0+UXqlh1o3/rpcef7eDRRac7hn5jkqWSMjmRyaVXdA7Ub2ysweb//J2Od/8radgLxRGwGq/4qcLYIbR+DH1gOlcEEL622l+ExaTfJQonhaJfNBY5jBMUo/6ulzyK6Nl55Nnh6SjuhVSizsN52xEAeD+HicPUud0s7LStHgjU5wkN810W490dUtKMoDOPIFhn1ZVnYvKo8M+aMcCBJIRyYFX0bqikmZIMSP/P7IqWJQ/30M7fo9xHzU0z4+4twO10E=~-1~-1~-1; bm_sz=6B34EF0C010D393E3EE4F486991F4D11~YAAQrXzTFz/ej+t3AQAA+G8uBQu1W23rEpXFPSN5rNv/zUF9A/VljOdzCcskLlebs7xAAjdHHvYWtDujXLnk516tKbhsTJVtTmZCqiRIc2+jJK46gCkR4bUyU+K4KlteifGgMzYksyKe0e0Xo2hLclvnyffCAOLzQBnbKy38rordRoSPkwwzJOQK1sOF'}\n"
     ]
    }
   ],
   "source": [
    "print(r.request.headers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can view the request body, in the following line, as there is no body for a get request we get a <code>None </code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "request body: None\n"
     ]
    }
   ],
   "source": [
    "print(\"request body:\", r.request.body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " You can view the <code>HTTP</code> response header using the  attribute <code>headers</code>. This returns a python dictionary of <code>HTTP</code> response headers. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Server': 'Apache', 'x-drupal-dynamic-cache': 'UNCACHEABLE', 'Link': '<https://www.ibm.com/ca-en>; rel=\"canonical\", <https://www.ibm.com/ca-en>; rel=\"revision\", <https://www.ibm.com/ca-en>; rel=\"revision\", <//1.cms.s81c.com>; rel=preconnect; crossorigin, <//1.cms.s81c.com>; rel=dns-prefetch', 'x-ua-compatible': 'IE=edge', 'Content-Language': 'en-ca', 'x-generator': 'Drupal 8 (https://www.drupal.org)', 'x-dns-prefetch-control': 'on', 'x-drupal-cache': 'MISS', 'Last-Modified': 'Fri, 05 Mar 2021 20:07:45 GMT', 'ETag': '\"1614974865\"', 'Content-Type': 'text/html; charset=UTF-8', 'x-acquia-host': 'www.ibm.com', 'x-acquia-path': '/ca-en', 'x-acquia-site': '', 'x-acquia-purge-tags': '', 'x-varnish': '146741505 147492433', 'x-cache-hits': '2', 'x-age': '11541', 'Accept-Ranges': 'bytes', 'Content-Encoding': 'gzip', 'Cache-Control': 'public, max-age=300', 'Expires': 'Sat, 06 Mar 2021 01:42:13 GMT', 'X-Akamai-Transformed': '9 12613 0 pmb=mTOE,1', 'Date': 'Sat, 06 Mar 2021 01:37:13 GMT', 'Content-Length': '12724', 'Connection': 'keep-alive', 'Vary': 'Accept-Encoding', 'x-content-type-options': 'nosniff', 'X-XSS-Protection': '1; mode=block', 'Content-Security-Policy': 'upgrade-insecure-requests', 'Strict-Transport-Security': 'max-age=31536000', 'x-ibm-trace': 'www-dipatcher: dynamic rule'}\n"
     ]
    }
   ],
   "source": [
    "header=r.headers\n",
    "print(r.headers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can obtain the date the request was sent using the key <code>Date</code>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Sat, 06 Mar 2021 01:37:13 GMT'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "header['date']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<code>Content-Type</code> indicates the type of data:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'text/html; charset=UTF-8'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "header['Content-Type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also check the <code>encoding</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'UTF-8'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " r.encoding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the  <code>Content-Type</code> is <code>text/html</code> we can use the attribute <code>text</code> to display the <code>HTML</code> in the body. We can review the first 100 characters:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<!DOCTYPE html>\\n<html lang=\"en-ca\" dir=\"ltr\">\\n  <head>\\n    <meta charset=\"utf-8\" />\\n<script>digitalD'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.text[0:100]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can load other types of data for non-text requests like images, consider the URL of the following image:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use single quotation marks for defining string\n",
    "url='https://gitlab.com/ibm/skills-network/courses/placeholder101/-/raw/master/labs/module%201/images/IDSNlogo.png'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can make a get request:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "r=requests.get(url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at the response  header:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Date': 'Sat, 06 Mar 2021 01:44:45 GMT', 'Content-Type': 'image/png', 'Content-Length': '21590', 'Connection': 'keep-alive', 'Set-Cookie': '__cfduid=dad5ddb8e8fca6a86cebed7ac01bbfd951614995085; expires=Mon, 05-Apr-21 01:44:45 GMT; path=/; domain=.gitlab.com; HttpOnly; SameSite=Lax; Secure', 'Cache-Control': 'max-age=60, public', 'Content-Disposition': 'inline', 'Etag': 'W/\"c26d88d0ca290ba368620273781ea37c\"', 'X-Content-Type-Options': 'nosniff', 'X-Download-Options': 'noopen', 'X-Frame-Options': 'DENY', 'X-Gitlab-Feature-Category': 'source_code_management', 'X-Permitted-Cross-Domain-Policies': 'none', 'X-Request-Id': '01F02KAP15DCNTEXKWVDHX80C1', 'X-Runtime': '0.055901', 'X-Ua-Compatible': 'IE=edge', 'X-Xss-Protection': '1; mode=block', 'Strict-Transport-Security': 'max-age=31536000', 'Referrer-Policy': 'strict-origin-when-cross-origin', 'GitLab-LB': 'fe-11-lb-gprd', 'GitLab-SV': 'web-02-sv-gprd', 'CF-Cache-Status': 'EXPIRED', 'Accept-Ranges': 'bytes', 'cf-request-id': '08a6ce6fe80000f9793e910000000001', 'Expect-CT': 'max-age=604800, report-uri=\"https://report-uri.cloudflare.com/cdn-cgi/beacon/expect-ct\"', 'Vary': 'Accept-Encoding', 'Server': 'cloudflare', 'CF-RAY': '62b7e6930ebef979-YYZ'}\n"
     ]
    }
   ],
   "source": [
    "print(r.headers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can we can see the <code>'Content-Type'</code>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'image/png'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.headers['Content-Type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An image is a response object that contains the image as a  <a href=\"https://docs.python.org/3/glossary.html#term-bytes-like-object\">bytes-like object</a>. As a result, we must save it using a file object. First, we specify the file path and\n",
    "name \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/resources/labs/PY0101EN/image.png'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path=os.path.join(os.getcwd(),'image.png')\n",
    "path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We save the file, in order to access the body of the response we use the attribute <code>content</code> then save it using the <code>open</code> function and write <code>method</code>: \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path,'wb') as f:\n",
    "    f.write(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the image:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=P size=800x800 at 0x7F643402BC88>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image.open(path)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Question 1: write <a href=\"https://www.gnu.org/software/wget/\"><code> wget </code></a></h3>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the previous section, we used the <code>wget</code> function to retrieve content from the web server as shown below.  Write the python code to perform the same task. The code should be the same as the one used to download the image, but the file name should be <code>'example.txt'</code>. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<code>!wget -O /resources/data/Example1.txt <https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/data/Example1.txt></code>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "url='https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/data/example1.txt'\n",
    "path=os.path.join(os.getcwd(),'example1.png')\n",
    "r=requests.get(url)\n",
    "with open(path,'wb') as f:\n",
    "    f.write(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for the solution</summary>\n",
    "\n",
    "```python\n",
    "url='https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/data/Example1.txt'\n",
    "path=os.path.join(os.getcwd(),'example1.txt')\n",
    "r=requests.get(url)\n",
    "with open(path,'wb') as f:\n",
    "    f.write(r.content)\n",
    "\n",
    "```\n",
    "\n",
    "</details>\n",
    " \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"URL_P\">Get Request with URL Parameters </h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the <b>GET</b> method  to  modify the results of your query, for example retrieving data from an API .  We send a <b>GET</b> request to the  server. Like before we have the <b>Base URL</b>, in the <b>Route</b>  we append <code>/get</code> this indicates we would like to preform a <code>GET</code> request, this is demonstrated in the following table:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/base_URL_Route.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Base URL is for <code>[http://httpbin.org/](http://httpbin.org?cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork-19487395&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ)</code> is a simple HTTP Request & Response Service. The <code>URL</code> in Python is given by:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_get='http://httpbin.org/get'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A <a href=\"https://en.wikipedia.org/wiki/Query_string\">query string</a> is a part of a uniform resource locator  (URL),  this sends other information to the web server. The start of the query is a <code>?</code>, followed by a series of parameter and value pairs, as shown in the table below.  The first parameter name is <code>name</code> and the value is <code>Joseph</code> the second parameter name is <code>ID</code>  and the Value is <code>123</code>. Each pair, parameter and value is separated by an equals sign, <code>=</code>.\n",
    "The series of pairs is separated by the ampersand <code>&</code>.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/images/query_string.png\" width=\"500\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create a Query string, add a dictionary. The keys are the parameter names, and the values are the value of the Query string.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "payload={\"name\":\"Joseph\",\"ID\":\"123\"}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then passing the dictionary <code>payload</code> to the <code>params</code> parameter of the <code> get()</code> function:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "r=requests.get(url_get,params=payload)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can print out the <code>URL</code> and see the name and values \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'http://httpbin.org/get?name=Joseph&ID=123'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.url"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is no request body \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "request body: None\n"
     ]
    }
   ],
   "source": [
    "print(\"request body:\", r.request.body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can print out the status code\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "200\n"
     ]
    }
   ],
   "source": [
    "print(r.status_code)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the response as text:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"args\": {\n",
      "    \"ID\": \"123\", \n",
      "    \"name\": \"Joseph\"\n",
      "  }, \n",
      "  \"headers\": {\n",
      "    \"Accept\": \"*/*\", \n",
      "    \"Accept-Encoding\": \"gzip, deflate\", \n",
      "    \"Host\": \"httpbin.org\", \n",
      "    \"User-Agent\": \"python-requests/2.25.0\", \n",
      "    \"X-Amzn-Trace-Id\": \"Root=1-6042eddd-61a4aa9319eaf3bb78ca6013\"\n",
      "  }, \n",
      "  \"origin\": \"169.53.191.162\", \n",
      "  \"url\": \"http://httpbin.org/get?name=Joseph&ID=123\"\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(r.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at the <code>'Content-Type'</code>.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'application/json'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.headers['Content-Type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the content <code>'Content-Type'</code> is in the <code>JSON</code> format we can use the method <code>json()</code> , it returns a Python  <code>dict</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'args': {'ID': '123', 'name': 'Joseph'},\n",
       " 'headers': {'Accept': '*/*',\n",
       "  'Accept-Encoding': 'gzip, deflate',\n",
       "  'Host': 'httpbin.org',\n",
       "  'User-Agent': 'python-requests/2.25.0',\n",
       "  'X-Amzn-Trace-Id': 'Root=1-6042eddd-61a4aa9319eaf3bb78ca6013'},\n",
       " 'origin': '169.53.191.162',\n",
       " 'url': 'http://httpbin.org/get?name=Joseph&ID=123'}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The  key <code>args</code> had the name and values:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ID': '123', 'name': 'Joseph'}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()['args']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"POST\">Post Requests  </h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Like a <code>GET</code> request a <code>POST</code> is used to send data to a server, but the <code>POST</code> request sends the data in a request body. In order to send the Post Request in Python in the <code>URL</code> we change the route to <code>POST</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_post='http://httpbin.org/post'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This endpoint will expect data as a file or as a form, a from is convenient way to configure an HTTP request to send data to a server.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make a <code>POST</code> request we use the <code>post()</code> function, the variable <code>payload</code>  is passed to the parameter <code> data </code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_post=requests.post(url_post,data=payload)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing the URL from the response object of the <code>GET</code> and <code>POST</code> request we see the <code>POST</code> request has no name or value pairs.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "POST request URL: http://httpbin.org/post\n",
      "GET request URL: http://httpbin.org/get?name=Joseph&ID=123\n"
     ]
    }
   ],
   "source": [
    "print(\"POST request URL:\",r_post.url )\n",
    "print(\"GET request URL:\",r.url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can compare the <code>POST</code> and <code>GET</code> request body, we see only the <code>POST</code> request has a body:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "POST request body: name=Joseph&ID=123\n",
      "GET request body: None\n"
     ]
    }
   ],
   "source": [
    "print(\"POST request body:\",r_post.request.body)\n",
    "print(\"GET request body:\",r.request.body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the form as well:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ID': '123', 'name': 'Joseph'}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_post.json()['form']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is a lot more you can do check out <a href=\"https://requests.readthedocs.io/en/master/\">Requests </a> for more.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n",
    "\n",
    "<p><a href=\"https://www.linkedin.com/in/joseph-s-50398b136/\" target=\"_blank\">Joseph Santarcangelo</a> <br>A Data Scientist at IBM, and holds a PhD in Electrical Engineering. His research focused on using Machine Learning, Signal Processing, and Computer Vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Contributors\n",
    "\n",
    "<a href=\"www.linkedin.com/in/jiahui-mavis-zhou-a4537814a\">Mavis Zhou</a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change Log\n",
    "\n",
    "| Date (YYYY-MM-DD) | Version | Changed By | Change Description           |\n",
    "| ----------------- | ------- | ---------- | ---------------------------- |\n",
    "| 2021-12-20        | 2.1     | Malika     | Updated the links            |\n",
    "| 2020-09-02        | 2.0     | Simran     | Template updates to the file |\n",
    "|                   |         |            |                              |\n",
    "|                   |         |            |                              |\n",
    "\n",
    "## <h3 align=\"center\"> © IBM Corporation 2020. All rights reserved. <h3/>\n"
   ]
  }
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