{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div id='toc-container'><script type='text/javascript'>\n",
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       "\n",
       "\tvar toc = document.createElement(\"div\");\n",
       "\t$(toc).attr(\"class\", \"table-of-contents\");\n",
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       "            var lastContainer = containerStack.pop();\n",
       "            $(lastContainer).appendTo(containerStack[containerStack.length - 1]);\n",
       "            curLevel--;\n",
       "\t}\n",
       "\t\n",
       "\t$(\".text_cell_render :header\").each(function (i, elem) {\n",
       "            var level = levelOfTag[ elem.tagName.toLowerCase() ];\n",
       "\n",
       "            if (level === undefined)\n",
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       "\n",
       "            while (curLevel < level)\n",
       "\t\tpushLevel();\n",
       "            while (curLevel > level)\n",
       "\t\tpopLevel();\n",
       "            \n",
       "            var listItem = document.createElement(\"li\");\n",
       "            var link = document.createElement(\"a\");\n",
       "            $(link)\n",
       "\t\t.text($(elem).contents().first().text()) // Remove the pilcrow sign\n",
       "\t\t.attr(\"href\", \"#\" + $(elem).attr(\"id\"))\n",
       "\t\t.appendTo(listItem);\n",
       "            $(listItem).appendTo(containerStack[containerStack.length - 1]);\n",
       "\t});\n",
       "\t\n",
       "\twhile (curLevel > 0)\n",
       "            popLevel();\n",
       "\n",
       "        $(\"<a class='btn-update' href='#'>Update</a>\")\n",
       "          .click(regenTOC).prependTo(toc);\n",
       "\n",
       "\t$(toc).prepend(\"<div class='title'>Contents</div>\")\n",
       "          .wrap(\"<div class='toc-headings'/>\");\n",
       "\n",
       "        $(element).empty();\n",
       "        $(element).append(toc);\n",
       "    }\n",
       "\n",
       "    if (typeof(IPython) !== 'undefined')\n",
       "        $([IPython.events]).on('notebook_loaded.Notebook', regenTOC);\n",
       "    regenTOC();\n",
       "});\n",
       "\n",
       "</script></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import addutils.toc ; addutils.toc.js(ipy_notebook=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "    font-family: \"Computer Modern\";\n",
       "    src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
       "}\n",
       "\n",
       "div.cell {\n",
       "    width: 900px;\n",
       "    margin-left: 0% !important;\n",
       "    margin-right: 0%;\n",
       "}\n",
       "\n",
       "code {\n",
       "    font-size:10pt;\n",
       "}\n",
       "\n",
       ".text_cell_render  h1 {\n",
       "    font-family: Tahoma, sans-serif;\n",
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       "\n",
       ".text_cell_render h5 {\n",
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       "}\n",
       "\n",
       ".text_cell_render yp {\n",
       "    font-family: Tahoma, sans-serif;\n",
       "    color: rgb( 90, 90, 90 );\n",
       "    font-size:11pt;\n",
       "}\n",
       "\n",
       ".text_cell_render strong {\n",
       "    font-family: Tahoma, sans-serif;\n",
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       "}\n",
       "\n",
       ".text_cell_render a:link {\n",
       "    font-family: Tahoma, sans-serif;\n",
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       "    font-size:11pt;\n",
       "}\n",
       "\n",
       ".text_cell_render a:visited {\n",
       "    color:rgb( 10, 88, 126 );\n",
       "}\n",
       "\n",
       ".text_cell_render {\n",
       "    font-family: Helvetica, Courier, Computer Modern, \"Helvetica Neue\", Arial, Geneva, sans-serif;\n",
       "    color: rgb( 84, 84, 84 );\n",
       "    font-size:11pt;\n",
       "    line-height: 125%;\n",
       "    font-size: 100%;\n",
       "    width:800px;\n",
       "}\n",
       "\n",
       ".CodeMirror {\n",
       "    font-family: Courier, \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
       "}\n",
       "\n",
       ".warning {\n",
       "    color: rgb( 240, 20, 20 );\n",
       "}\n",
       "\n",
       "/* Pandas tables */\n",
       "/*\n",
       ".rendered_html td {\n",
       "    text-align: right;\n",
       "}\n",
       "*/\n",
       "\n",
       "table.dataframe td {\n",
       "    text-align: right;\n",
       "}\n",
       "\n",
       ".output .table-of-contents {\n",
       "    border: 1px #cecece solid;\n",
       "    background-color: #fafafa;\n",
       "    padding-top: 10px;\n",
       "    padding-bottom: 5px;\n",
       "    padding-right: 15px;\n",
       "    padding-left: 0px;\n",
       "    margin-bottom: 20px;\n",
       "    display: inline-block;\n",
       "    position: relative;\n",
       "}\n",
       "\n",
       ".output .table-of-contents ul {\n",
       "    list-style-type: none;\n",
       "    padding-left: 20px;\n",
       "}\n",
       "\n",
       ".output .table-of-contents .title {\n",
       "    font-weight: bold;\n",
       "    font-height: 11pt;\n",
       "    padding-left: 20px; /* looks better if it's the same to the <ul> */\n",
       "}\n",
       "\n",
       ".output .table-of-contents .btn-update {\n",
       "    position: absolute;\n",
       "    float: right;\n",
       "    right: 11px;\n",
       "    top: 4px;\n",
       "    font-size: 9pt;\n",
       "}\n",
       "\n",
       "</style>\n",
       "<script>\n",
       "    MathJax.Hub.Config({\n",
       "                        TeX: {\n",
       "                           extensions: [\"AMSmath.js\"]\n",
       "                           },\n",
       "                displayAlign: 'center', // Change this to 'center' to center equations.\n",
       "                \"HTML-CSS\": {\n",
       "                    styles: {'.MathJax_Display': {\"margin\": 4}}\n",
       "                }\n",
       "        });\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy.io\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from addutils import css_notebook\n",
    "css_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 Principal Component Analysis (PCA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before trying any ML technique it is always a good idea to visualize the available data from different point of view but when the dimensionality of the problem is higher, it's difficult to use some that kind of plots and it is necessary to do **dimenionality reduction**.\n",
    "\n",
    "We have already seen some simple visualization example made with scatter plot or scatter matrix on the tutorial ml01. In this lesson we're going furter by working with some of the mamy data projection techniques available in scikit-learn.\n",
    "\n",
    "In the first example we will consider the *digits* dataset in which we have many 8x8 grayscale images of handwritten digits. In other words, this dataset is made by samples with 64 features\n",
    "\n",
    "What we want to do is to obtain a descriptive 2D scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"e81e5b88-d1bd-4f1a-8a78-c354d8796746\">Loading BokehJS ...</span>\n",
       "    </div>"
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     "metadata": {},
     "output_type": "display_data"
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       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
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       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
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       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
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       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
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       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
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       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
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       "      safe: true,\n",
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       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
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       "\n",
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       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
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       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
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       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
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       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"e81e5b88-d1bd-4f1a-8a78-c354d8796746\");\n",
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       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'e81e5b88-d1bd-4f1a-8a78-c354d8796746' but no matching script tag was found. \")\n",
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       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.13.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
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       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n",
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       "  ];\n",
       "\n",
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       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"e81e5b88-d1bd-4f1a-8a78-c354d8796746\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"e81e5b88-d1bd-4f1a-8a78-c354d8796746\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"e81e5b88-d1bd-4f1a-8a78-c354d8796746\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'e81e5b88-d1bd-4f1a-8a78-c354d8796746' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.13.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.13.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.13.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.13.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"e81e5b88-d1bd-4f1a-8a78-c354d8796746\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import bokeh.plotting as bk\n",
    "bk.output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "digits = datasets.load_digits()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Digits images:  1797\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"0324e1e5-c742-4e40-8ef5-944866d4a9af\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
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       "  var render_items = [{\"docid\":\"fc2726c7-712e-4c40-b2dd-c12280ac3b4b\",\"elementid\":\"0324e1e5-c742-4e40-8ef5-944866d4a9af\",\"modelid\":\"afb9c704-f51d-4cb2-8554-4319fee25b78\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
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       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
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      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import addutils.imagegrid as ig\n",
    "from bokeh.palettes import Greys9\n",
    "\n",
    "print(\"Digits images: \", digits.images.shape[0])\n",
    "# print only the first 80 digits images\n",
    "num_imgs = 80\n",
    "fig = ig.imagegrid_figure(images=[ digits.images[i][::-1, :] for i in range(num_imgs) ],\n",
    "                          text=[ str(digits.target[i]) for i in range(num_imgs) ],\n",
    "                          figure_title=None, palette=Greys9[::-1],\n",
    "                          figure_plot_width=760, figure_plot_height=600,\n",
    "                          text_color='red', padding=0.1,\n",
    "                          grid_size=(10, 8))\n",
    "bk.show(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll start our analysis with Principal Component Analysis (PCA): PCA seeks orthogonal linear combinations of the features which show the greatest variance. In this example we'll use `RandomizedPCA`, because it's faster for large datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import addutils.palette as pal\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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\",\"dtype\":\"float64\",\"shape\":[1797]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1797]}}},\"id\":\"0eed6e60-bbeb-46fa-ad22-30602b78870e\",\"type\":\"ColumnDataSource\"}],\"root_ids\":[\"91f9a0a9-2924-4cf3-9272-9c37856d105b\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.13\"}};\n",
       "  var render_items = [{\"docid\":\"6b428a06-376d-44da-9df7-98669ee44663\",\"elementid\":\"405fd2be-e8b0-4ddb-9ce8-b25135113b2f\",\"modelid\":\"91f9a0a9-2924-4cf3-9272-9c37856d105b\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "91f9a0a9-2924-4cf3-9272-9c37856d105b"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import decomposition\n",
    "from bokeh.models.sources import ColumnDataSource\n",
    "from bokeh.models.tools import HoverTool\n",
    "\n",
    "pca = decomposition.PCA(copy=True, iterated_power=3, n_components=2, \n",
    "                        whiten=False, svd_solver='randomized')\n",
    "pca_proj = pca.fit_transform(digits.data)\n",
    "\n",
    "colors = list(map(pal.to_hex, sns.color_palette('Paired', 10)))\n",
    "\n",
    "pca_df = pd.DataFrame({'x': pca_proj[:,0],\n",
    "                   'y': pca_proj[:,1],\n",
    "                   'color': pal.linear_map(digits.target, colors),\n",
    "                   'target': digits.target})\n",
    "pca_src = ColumnDataSource(data=pca_df)\n",
    "\n",
    "\n",
    "fig = bk.figure(title='PCA Projection - digits dataset',\n",
    "                x_axis_label='c1', y_axis_label='c2',\n",
    "                plot_width=750, plot_height=560)\n",
    "fig.scatter(source=pca_src, x='x', y='y',\n",
    "            size=10, fill_alpha=0.9, line_alpha=0.5, line_color='black',\n",
    "            fill_color='color')\n",
    "\n",
    "hover_tool = HoverTool(tooltips=[(\"target\", \"@target\"),\n",
    "                                 (\"color\", \"$color[swatch]:color\")])\n",
    "fig.add_tools(hover_tool)\n",
    "\n",
    "bk.show(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can notice some structure in this data but it's still difficult to understand if it would be possible to effectively apply some classification algorithm since the different data clusters do not show enough separation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 Linear Discriminant Analysis (LDA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Principal Component Analysis (PCA) identifies the combination of attributes that account for the most variance in the data.\n",
    "\n",
    "Linear Discriminant Analysis (LDA) instead tries to identify attributes that account for the most variance between classes. In particular, LDA, in contrast to PCA, is a supervised method, and can be used just when the class labels are available.\n",
    "\n",
    "Let's see an LDA on the same Dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"804e3519-672c-4f74-9c3a-6aa13f0a5bb4\"></div>\n",
       "</div>"
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\",\"dtype\":\"float64\",\"shape\":[1797]},\"y\":{\"__ndarray__\":\"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       "  var render_items = [{\"docid\":\"6937fa95-65f5-4298-b447-e5d2b9fd77bb\",\"elementid\":\"804e3519-672c-4f74-9c3a-6aa13f0a5bb4\",\"modelid\":\"c08be04e-61b7-4a70-87c9-29196c6ffc62\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
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       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
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       "      attempts++;\n",
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       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
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      "application/vnd.bokehjs_exec.v0+json": ""
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     "output_type": "display_data"
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   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore', message='Variables are collinear')\n",
    "\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "lda = LinearDiscriminantAnalysis(n_components=2)\n",
    "\n",
    "lda_proj = lda.fit(digits.data, digits.target).transform(digits.data)\n",
    "\n",
    "lda_df = pd.DataFrame({ 'x': lda_proj[:,0],\n",
    "                        'y': lda_proj[:,1],\n",
    "                        'color': pal.linear_map(digits.target, colors),\n",
    "                        'target': digits.target })\n",
    "lda_src = ColumnDataSource(data=lda_df)\n",
    "\n",
    "fig = bk.figure(title='LDA Projection - digits dataset', \n",
    "                x_axis_label='c1', y_axis_label='c2',\n",
    "                plot_width=750, plot_height=500)\n",
    "fig.scatter(source=lda_src, x='x', y='y',\n",
    "            size=8, line_color='black', line_alpha=0.5,\n",
    "            fill_color='color')\n",
    "\n",
    "hover_tool = HoverTool(tooltips=[(\"target\", \"@target\"),\n",
    "                                 (\"color\", \"$color[swatch]:color\")])\n",
    "fig.add_tools(hover_tool)\n",
    "\n",
    "bk.show(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As in the previous example we don't see a clear separation of the different clusters. This is because this specific dataset present some non-linear features that can not be separate by linear projections."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 Manifold Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main weakness of the linear techniques seen so far is that they cannot detect non-linear features.  A set of algorithms known as *Manifold Learning* have been developed to address this deficiency.\n",
    "\n",
    "One of the earliest approaches to manifold learning is the Isomap algorithm, short for Isometric Mapping. `Isomap` is a global, nonlinear, nonparametric dimentional reduction algorithm. Isomap can be viewed as an extension of Multi-dimensional Scaling (MDS) or Kernel PCA. Isomap seeks a lower-dimensional embedding which maintains geodesic distances between all points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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\",\"dtype\":\"float64\",\"shape\":[1797]}}},\"id\":\"a18a3c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\",\"dtype\":\"float64\",\"shape\":[1797]},\"y\":{\"__ndarray__\":\"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       "  var render_items = [{\"docid\":\"8f55780b-6138-4bfe-b6c9-b9a1e630ba47\",\"elementid\":\"12e7e02f-464e-4bfe-a864-a7d3c2db9f5f\",\"modelid\":\"7420d682-eaab-43d4-97eb-7a51e60891f4\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "7420d682-eaab-43d4-97eb-7a51e60891f4"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "warnings.filterwarnings('ignore', message='kneighbors*')\n",
    "\n",
    "from sklearn import manifold\n",
    "\n",
    "from bokeh.models import GlyphRenderer, Quad, Legend\n",
    "\n",
    "fig_grid = []\n",
    "for i in range(2):\n",
    "    row = []\n",
    "    for j in range(2):\n",
    "        iso = manifold.Isomap(n_neighbors=i+2, n_components=2)\n",
    "        proj = iso.fit_transform(digits.data)\n",
    "        \n",
    "        df = pd.DataFrame({ 'x': proj[:,0], 'y': proj[:,1],\n",
    "                            'color': pal.linear_map(digits.target, colors),\n",
    "                            'target': digits.target })\n",
    "        src = ColumnDataSource(data=df)\n",
    "        \n",
    "        fig = bk.figure(title=\"n_neighbors = %d\" % (i+2),\n",
    "                        plot_width=340, plot_height=300)\n",
    "        fig.title.text_font_size='12pt'\n",
    "        fig.scatter(source=src, x='x', y='y', fill_color='color',\n",
    "                    size=8, line_alpha=0.5, line_color='black')\n",
    "        \n",
    "        hover_tool = HoverTool(tooltips=[ (\"target\", \"@target\") ])\n",
    "        fig.add_tools(hover_tool)\n",
    "        \n",
    "        row.append(fig)\n",
    "    fig_grid.append(row)\n",
    "\n",
    "bk.show(bk.gridplot(fig_grid))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These visualizations show us that there is hope: even a simple classifier should be able to adequately identify the members of the various classes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Another example with a specific test dataset: the S-Curve"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A canonical dataset used in Manifold learning is the *S-curve*, which we briefly saw in an earlier section:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PjxOMJ3EPn8V8t4vYZ1VVVjzxFLnoe/UmMGF3Apo3yZOET6fTKSGESxUW2dSFehHCriiKFfdtNBpRliXz+ZwkSbh+/Tq3bt3ic5/7HHmen+pYr8Iv8LOCquKpAFby2xoO/B77uovH16IOGq8sirHojrlaQjkcla/wWYXHk5Ex0QMCPla2LW27kXe0f2v9OBcFmDpGuk9F2Tp2gYAAjoQOPUKl+KTigD08FYKsuHjL225WDlILvLPhtWLOtBaQUp+VxZF4PELJjCk9BivPPS73cB2K8o1//+/4j994g4RkIVhPkHu4Lrx8Evfw4OCAyWRCWZbHCkbnnP2OEh07C8Uap8GulhNSVdWJihdEZCO9izbJJgXZkxB2qrpWwFVVRZ7nDIdDBoMBt2/fZjgckuc53/jGN3j11VfbKRjn2fdZeVbm1V6UI+jVMwsTJmFESRmDm5KSiKMvW3RddLIqLRnrQS1UGlnWOG20QopaTEWxF3BZdMcK5uSSg1KLx0YMrD9uQQgEMhIER0VJRdkKz4XXF8VTwAPg1BGoWmcuHFpX87ert6sEEh4fQgt4qnrfKSkKDJ7rsc8uAU9CWq/h0FxSKjxCAXTpHXHtHoeizJgwZ8qtV28wZg+Ho0OPjM4T7Xs4n8/Jsqzt/7iJyuXzuIeXGcuxe7pchQ8TdrWcABE58ZvDZQpXNlyWpsCqynw+p6oq3nnnnbaVSFVVdDqdNgfuzp07DIfDR7oNl62n3mXlaR2jNvlrPWEeZjh1HPCQKsSsuCiEojhx2mGkezhx5NKh1KINga6Kl0Ze6ZLUan6yeP0DnkLneKlQbUKiC0dt2VmLLlx00jrEKucqRGG3CL02Mi2Ks6oVfHELipKS4akOuXZxnQlJK/Ay6bRh2cYJWzw6CquizdWjDuJWDJ/vt0LTr+x/cV6ow76hXsdxr3R8TGgFakKKIEwZ1Y6gQ4O2QnbGFBByNpN7us493N3dZXt7m+eff/5E29iEezgej8/U9/Ci3UNz7IzTYlfLhrnqwu4k21FVZrNZ67w1xQzN+KzmE+jdu3cZDocX+qZ12V6rZ4FKS6YhChJFcerwVBTpnPym45PwAaqxAKERSiJRKAUNqETHaxJG5EkH1QBtmFFqUQZHHDc5+i0AJ64WX0ImKXOdEUVP43ItPzE6bD36dKXfbiMKo3Uf3upwan2dOFwt06Jwi6JqQdL+L6UjHcay3wqzlJwuPZL6bbdgTsGsdvjiMRfMopvYTUG0KehdWs3iWFy93kCgoCAjP+IQRvE4paJojz6+EkktKGvBqbRiOOApmJGRHxGjm+K0RQWbcA+/+tWv8tZbbz2VvofLY/am0+m53EPv/TPvOj4rCHAFBk+YsNs0nyZh13T/XxZvo9GIEMKRQfaDwaAVcL//+7/P3bt3N7qWs27jWV/D02YeZuzrLkF9XeSwVDHqAA+JujqwGYVVU1BA7WaVFPRkQKVlnXvnj+xnVYrV50ibf8ftOedw4to1dCQnqUOZFQVO81Z4ORFSMhwJfYb0k0UIPyOvN69LQqbJj6ulULrYT06POdNatmY0nlhCSp8tOtJFRRlz0K6Xek1jSgbs4HC1qHNLQjbU+9R6rJGDOtevWd/CmZN6afGZBbNWjHXpt8dRMI/nohXZ1OHrKCCPCxUHGrF9OYTdpjhN7uFxnMY9LMuSH/zgB2tzDxuxepxA/Jf/8l+24we/853vcO3aNXZ2dhgMBs/c+8Yzg2AjxYyjXEVh18z/nEwmzGYzPvjgA8bjMaq6IuBu3LjBYDB4anNPN8FleK0uqnGqp6LQOfMwJ+DJJKPr+tGpWXN+Qwjs6wMq9fi2enSJ+k1Rpf1nbXTFsGGT8O9w8cZei4aSgkw6zHW2Jni6tHEWFbHtnnXRnqBpT5JLHoWMODKNrpMjisBMOkfajySSkmtOSVnXnS5y5qjDmHk/xScFKb1YWCEuHpzEY3MkOBI8FYmkjNir17RwWoQET2BeFzuEOmRctVXAiyOPv0NL4kdXncf4/fqx9b5BKSnqgo8uilIyPyLqFlW7y2HuZo2yKh6NI5zGPXz48CFvvPHG2p89rnL5e9/7Hnt7exwcHPCbv/mb7QjD8XjMl770Jf7sn/2za7f7k5/8hC984Qtt8/S/8Tf+Bl/84hdXHqOqfPGLX+Ttt9+m3+/zj//xP+bNN9882wkxLh0m7DbMpoXdJj7ZnnRNTSLzsvs2Ho8B6PV6FEXRTmHo9/sX3lvpokXZZRTxx+G1YhomlBSggqds89IgiiKvGTM/ZSBbDJKtleerKg/1ft1KZDVnbSVUmKzmuCWSgDT5ZULQ0AqgngxqoRbIpYMgzHXaSitqSdKTIX0ZMmWEpxaVKpS+wCUOJObNVVRkZPXxRIduK9l57LkREYa6wwF7K3loiq/9RkcVSkTzmNEmscjDyUK0NSHMithrzku1NrTriO1WegxQtG6b4uptHC26akVmY9DhaHrmNcScOdrvF8zI6bReqlsSdb4u/mjEd1DPsoBrZF/6BMOwcHGO3WXice7h3/t7fw+AX/7lX+Z3fud3Tny+0jTlH/yDf8Cbb77JwcEBb731Fn/hL/wFfvZnf7Z9zO/+7u/y/e9/n+9///t85Stf4W/9rb/FV77ylfMf1BXgKlyWJuw2jHNuYzf7RjhsWtg1Am65AnUyiQ1dl+egvvDCCyuD7H/wgx+wtbXVdt+/SJ6VitSntYYQAqUWeCoyyUklW7ThyYT7/uPoxKhjzrRt6yGhrhIVrfPlEh7KvdZV6roeIo6ZTpYa8j7meGq3y4lrU+caMShO8CGusedii45Uciot6bgOuXbq0GwjMDKuuRuxgCkID7kfHb9aKMb/R0/OU5GSIcSgZnaK5P/MddjW60x1HCtkpSIhi9sTYTqf0cuaNi3Llbf1cbOo2D250xUfuwh7rmzw0LZZEVqN09aEl1cfG9qvm1XFSuD6NRfqcxhQiS9Qmif1OmJlbpf1vfcaty8Wh7hj8hJPxqdd2D0pXnzxRV588UUAtra2+PznP8977723Iuz++T//53zhC19ARPgzf+bP8PDhQz744IP2ecazjQm7DbNJsXDebYUQGI/H7O/v473no48+YjqdArQVqFtbW9y+fXtFwD2p9WySTdwUrsqNZeT32Q0ftzdmEDp0uZm+iODo3crqsGHM82pu8GiTRaaIKkFAXXTbpjpmyoRO6HLdPc9UxzHJX/2Ks7Qc4oNYyOBk6cONQGsPRYWHOCFQMdcZPenTlyF7+iC6eeJiK16NdZx9GbavU9f1ScM+AR/3FxpnLbT7j4FTbYsXTkMqGVtyjaCBfe7jJOGIa9ValKtBzCaM2oR8U/LajTtczBDI6bZ99GLTlHBkB6vntanXjb+fzVSMJsS8uv2FsIwZgB2KOhzbiLpmHyn5QuwlUm81xeGYyhinjoxOu6+AZ8508foLpJrH1iindPcuy/vIs8B53qfeeecdvv71r/On//SfXvn+e++9x2c+85n233fv3uW9994zYcfFDxPYBCbsTsBpq7eetrDz3h8Zo7U8yL6qKvr9Pi+//DL9fv/MF+5lEnawmZvDRfexO+l+jmPsR9wPHx76rjJnygfVuzwvt0h7KXPmRC3UiLrV4oTE1QJEFZVF9WWhM/bDw3bMViophS4cptaJW94GsiQgWAojSr3tKCEmHNDRLpnkbMk1JrqPV99ubyg7dFx35cg60o3tU9QxmU7Je526C1xVryeQ0WUgw5gHdwacrHeiRBYS63CD4ibkmRPX26XHmBJPWAqFxmrgTpOnV0uzpHX64rkJBFRDnFjTBmCT9px36sraGWOa+RjNaxGaNi719xoRWVERpHHyoiBu6ncVZTwasX3tOTwFKnGrXjxex2R0ScmYybj2SRfH31TbNsd9UiwUezLO8/4yGo349V//dX7rt36L7e3tx27XXo+rgwm7DfMkhd26Qfaz2QznXBs+vXbtGnfv3qXX67W/qD/60Y9IkqQdc7ap9VwkV+VN6HHHUfqCUXWAD54+Q1KXtjNNUWFP78XtLIkoaG7yJZ/oh6Sd1WkCLFVTCuDcwlU63GakqaDs0KWkJCUjiFJpgYjDNeFe4rWhQUmcHDNvYdEprgkZlsxJNaeUovbdlIycPltk7mjuUY9BO3KsOX8JKarCgCEd6a3kvj2K6EDNanESRVleu085XWaMaxHa5MDFs5pJvhgtuCRsIQpPiMJpwA5zpjGvkSh+OvTaYoamY96yG9dsq5hXdHo5C4kdvdUuPbr02/WXzFfOdUZOTodAoKKow9rRwQ0a284sT5do8F7xEvP9mp8JgkoswIgtaTiyzsYFzvT0rt1V+R1+Gpz2XJVlya//+q/zV/7KX+HXfu3Xjvz87t27/OQnP2n//e6773Lnzp1zr/NZR7AcO2MNmxA/VVW1w+u///3vM51Omc1mJEnSTmF47rnnePnll+l2u4/9pb9MgmyTXHSO3UZuTA6qUKK6mGerqoyrER8X79c92QAEFxx9GRBT1+Jou1LLxbYOLSeKBkXSxUSGI/Wmcuhp0siN1WrJjvQotWhbZAR3tHBGoqVFLt0lF205lNhMZnB1aC9Op5jIg+gI1oLMU3LALtt6nVRWxV0qGUPdZsQ+SebaaRVD2abD438XGjwVI/aWctcCU0aUzOnQpWBG0/zXA1k/hnxj9tkWUxlRUbVnSBC6DNoedRAFVJ/1k1EEoUOfigOa8WX1y4HDMR8V9HuxQllREhJyuivb79Ino9M2d05J6956nplM2hB1UxACUhfXLgt5RTVQTsv2dTq8zlh0Ua6VbY2gf1TrlHVcxfejy4Kq8tf/+l/n85//PH/n7/ydtY/51V/9Vb70pS/xG7/xG3zlK19hZ2fHwrA1V+EDhwm7DXMasVCW5Yr7Nh6Pmc/npGnaumvXr1/nc5/73LGD7De9pqexnU3wrPeQK0PBbnmP/LZwL3zI/rzDTnqdQbrFfrXLveJj5jprHZSmxceMCYnGPKimyOB4Yr5IHIVVh/7EoRr7aXmN1ZFVHS50Ept2xD5OsiLucumyhauH0jeC5nBTDAEXnaQ4BivUGW9aby+uISWjaanh6xYjy6JAiIn8E0Zsc/3IUeXSZRgc7777AS/97MtrZ8+uI9QOYUXV5oo1blmTR1ZS1C1DYp5clEWxQazTjAE7CMKA7Va8xgrc/Ei+2+OIkx1iv7vFdIok7rsTZ9QengF7mCac2qAoM5nQZBuu9hGMr4OnwmmsrkUgo0sxLTn+Wmpev6NlIQvH8nRYKPbJ8a//9b/mn/yTf8Ibb7zBz//8zwPwm7/5m/z4xz8G4G/+zb/Jr/zKr/D222/z2muv0e/3+Uf/6B9d5JKNDWPCbsOsmxW7PAe1CaUWRUGapm0I9datW+0c1OYN7w/+4A+4fv063e7p8ldOsqazbueyCLtNsak8vUorAp5RdcC42kdF6bo+19Mb5MlqEn8VSj6evx/dkkoRFbxW3Cs+wqtnv9qj1LIVG7BoQ9EIpKYZSGDhsB2+vaoGyqCtqMPVt2cRvK/wdaJdKjHPqtIKdSkZKSKgKgRVutInkYREenS0yz39oA7wrVZpLgdyY+J+3k43gHrEVt2OpCkiKKVoc9CWif3dyjrXbE2+G4IvwhFH7zjmzJgyOuRgLVd5BpJacEaHLK3340iJ+XzZ0NeNieORNDJsOXx5WhoXbsp4aSauMn4w5e52/7HPP0wM0Wtdr7JaSKEQw+dInYfncBqFZDGrYt6l6NHXVYWUDqXO1/5c6tm4xioX9V75y7/8y4/dt4jwD//hP3xKK3qGEHPsjEPM53PG43E7jWE0GlGWJVmWrbQQefXVV8nz/LHbu2xO2yaF3Xk/sV8Gx05VyXYS3pn+IOY7hRJE421eHfMwY1TtcSu/w1a26Kc28osiAbowY4b46K7dKz4klegULbexcLWDphpA0rZNRRMKq1fUPr4KnhC0TsAHrwEJscBBNEGlQjSKvECI/eYUfIiNipt7t8MxlEXitdQTHNr1HzkpccpDI6ASSRatNVC8xv5uPfr0ZYtdPlmzCW0rX6dM6NJfccMCnkJmXLuzxZRxLY6ODwN6KqaM6vDvul5x8cyFYx1QJe+lqAvMmLBoKbKoShWEPlsrodIdzcVNAAAgAElEQVSTkpAyZKc9Zofj4JM/Ql5ZiHpPuRRyzVpheXSlMYdyXU+85lgblzJlIYqLaUFCWofsFy5xI3jjY0OcFiLanrMmf+8sVbFX4Qb6KD4Nx2hcTkzYnZBGSDSD7A8XMVRV1Yq1LMt48cUXGQwGJxJwj9vnpta+CS6TY/c0qmIbN05UmYYpI7+PEuhIj3mY0b+bU4RZK1xQCDjSuqIx4LlXfkQv6ZPWxQBTPyFoYBamSBIFhcPVPeYKNER3xYd6qL0qWbb8q6r1RId4g1aNAc+mkEEVQoj/FokD3puKTh88idSVn5LQyhoRnAihbmciZKQSQ75Bwops6jFs58SuJNrDal6XKAkOJHpcqrFvWp8hPYm5Z7l2mDNtjurI+Z/JhDlTtrhGSkZJwZh9ggt0t3JmxJ/3GR5bmTln1n59nOBZ/tmRwgJ8O2aoyWFrHEpp57wGxhwwrMeFnQW3RpwqylRGKy5jRXRzezo8stZYY7v+XLaVyXr0GAE69Cl1RillW2STaU5WC7eMLgkZlZbUV3ndHNmtXAuPoj1v7mo4I4/ChN2zyVV4yUzYnZBvf/vb7O3tUVUVnU6ndeBeeuklBoNB2z38/fffZz6fc/360dyg03LZQp+bFprndew2sY5HsVvc5375EV6r+sbl6EiH1GU8rO5RUOCcHBELWueWRRdMqELJXrXLVrpDJlmcsRsmbdgv+JjHFT84QOkrUucgY2keatxHLDBYyWpDxOHLOUFT8k5GFcr2pyEEqsITsoUTFzTUYTlqTRfFX/OcRFISqd8aRNnjAT0dMJDYmLpDl670mel05dglOEY/mfBTr9xmSmxoLEuJ+jGkGvMEuwxYbvaxDkfj9ikj9tjmOmP26585QqD9+YTRsXluy6Jo4c8tPKdFDzxqoaY0rUka/1AB0djGpRExrSvZiptASUHnlK0/HkXBrB7DttrWxOPrauXVRsIOR6oZpYQ2BL9cuRvzLMHpqohsWqvk9Mg0jiMTXS2miKHntM6f9JQyp5QiXoOakGoeC2vwqChOV8PUFSWVKwjiefH1m5CUFDI7U0XtabmosX2XYRvG6bBZsZ8i7t69y2uvvdYOsj+Oy9Sg+ElsZ1O5epvYxqbfOIswpwhzRBzTasz98iNob6ZRsM10SuLLOmR1ZFU0YiFoFHY+BCoq7s0/4d74HlVRUZUFMgQJtQucaGw5Uk9/SPMorEotW/GwaImxdAtc6nDS7cQ2GnEGq0Ok6QfnQGJGXKkVCQmpc9GZU3ACoQiggndVHBMXoPJVFHv1yz13c37wwz8izJXuoMPwhT75II2TVoKiMygPApO9KfNxSdkv4utch3sXS5Za+EaXciYTRBeC5cjpXHrOjEkbqlx+bBNiLZi1rUCWSUjaMOZRWXeYgErM74vCJDqRaBRDMQS+4PCaw9rr4ijLxQzHiRpF2xzEwwLLAaUU5Ho0DNqhBwqFzFZEXSN61z1nGXnEmuIxBuZuSpMKAKDimcu4fn2kvgZjSkKu3TgIzs0IUmeF1i9C6WZ4reiGPk8yT++i3LPz7tN7/9h7jmEcxq6YE7K1tXUiIXHVhd2zFtKd+Ql71S6FzkklZye9Ts/FJs3Nm27QwCfFh0z9GFCCBgqNvccSiSKoeXuObkl1rMvUSAZFKcuSkhJVqCYzUnLyTo70FJXY7T9UAedcdDnqFnMqGitU62pWRetctbQWf8taKTps1Ll0IkImGaGKx+FUkLSZVkDday5mUXkCIcAw36YjXQqdEaQiTzp1k97FTSkQeOVnPkvuu4yThwuXS2u3p6cUD2fMZjN+/OMfs3W3h0uF4FfPkwi4NOHjH/+ATj9ncLuLc0sKdYk4V9a131+XH7fMcWHWnF4bjo3VxGHt6xfdLKlDog4vAafxvM2nczqDo07c0fYgj2750fQFLGVOI4wy7T5iesO6WtTlnx0ltl7pk2ucOuElfkBIND3SMuUsVFK0Ars5Ji+L/MRA3WZHHSLEULssi+Ba8NdfBzyVFGS6OafzMBfl2J1X2FVVZcLuKRLfQy96FefHrpgNs+lZsZvazmUSdk9rzut++ZD75cfx8Tgqpsz8mJ30OZ7LbwLxzfdB+QlTP2rnq/rgmWuci6qPkHD1hpfvUbQ3W6V2J4Q8ydl67lp74z6oYhK6aGw9UYWwmGrghEo9HRE6SQfasHUsgDgchk3kaCgzoW4crClbbov9sAtOqEJFKglZEpscE6p6WH0M1w3ckMJNcbKmRx2CimeS7R9yyxZfbb3UR9Kb/NTtV5kyZsLBSigOrcVmSBi+eI0ym6JJWOiTQxrGe89sWguy1LG7v8fgeh/1sRFyqH8uIkgijCYTZiEWK6VpSpqmJElCIrGf3IQRR0WSgCw3CW6qYutKT6nzANN5LWYSpM2xgya/rPl3zvE5tbEVyRhPSVPGEFDmMiWop3uotckiVL1OsDZrOf49wpFEB3PDmqa5ZhqCNP0KD61QohMciy20Ps9x7elyzqjEApdU1+fpKUqQeK2qxBBxqhmijz7+wzxtx86EnXFR2BWzYTbt2F3FNiVPIz/Oa8X98uN481t6rKpjr9plmG7Xj/OMq/1W1LXbpw6/HnveloJ5svDpmm8456KQImOQbK3cgDquS1kVBA2xWlXqxrEooimDpBcLH+qbfyMYU0moNDTfbde7nHvVrKebdHGSRfdxWtIddshdbHbr1aOAc8K23OBGemslnLkuEb7NB+SYatia/o0OJQVd+hTM6hBoXHHjRHZdn9nWZOX8NUexyHaDNE3It/K2H1u3141VwVl8SBgHkqQeyOWV8e6Yqqwoy5KqqqiqCu8X65VE2Lm5xeBaj7yfo14hKEln4TzF6HEd/JYo+rr02Z3vQmcRFtdWpIT2Vc+1v7YAoiFmUpbxeJZjwmg9gSOrxdoiJJlph7lMjrzOShScm0BRsk669nVfx3IYe1nUrt127Xo2j1uIfGIeALSh+OPwUuJdCSqgdYjazUlCRqonK067iFDspoRdkpy88bNxToS2CO1ZxoTdE8Acu8dzohm46plUIyZ+TKUVmUsZpjv0XH/tNppJDEqIlaftNIMlwVaLqFG1T+hW7Ln7VL4gl5zEZQQfKMsCTQGJDtPRZNrllPTFvxrX50Z6iyzJ2St3cZIsChFqEhK81u1MmgpFiesPqu2Ir8U2mxw/Ba1DsW5xXHLob0cCDrbcNh7PxI0ZpL329YvFE0omGdfleRBlzizmvelimsNyqA0eHwqNDxZmTNjiGts8x5xp3QxYyemQ0WHEXrvO5QrTVXG3LFa1HU6vsgiF572MNE0QEoZsc+uV49/OFGXGmELmhGbWbUIrqJtHhQAaAlURw40IfO9bf8xkPOHajW22bmyxfWNAkiXtOWk6v8wYMx3NSJOFY5imi+bJFfHaRGpFt3RZqQSmMqqvCaG/HYsiUjJUuyv5cgC59sge4Q6ehJjDF0O1d157gamrHVZ1JKSkmrIu7y3RrC6aWJ+puCoO6yrYWryvPm7pMSq18yc4Xe7fGFpRt9I/T8G7ksSvX2NzfI3bGeoPUE8Tc+yeReSpXydPArtiNsymQ7GXybF7mts5KPf4pPyAMhTtrcN54aDci27bod+9eZjxyfxD5mGOD2WcCCCOSmJriNzlSzcAZbe4T9WdE+YFiFLU8zwlxD5tqWbxhlI7KssibhG2iyR16NK5hC23zY38VltluFs+OOIaFlqQuy6pJMyrGOJbtKBQSl+Sp4seY7EIYSFyquDpuLw9BbqwfljcP2OlaJBAb9BpK1KbHLwufXoMmMmUKeP2BqgsPJimMlQQBmwxkdEhSXuUZVevyfVaLmiYEvMYF9MQFsJ4WRzH5/ZQQqw+XuoX11Rleg306jYnj3OaKkpKmSMIqaStOIwvSzw3zalzSU6exTXl2uXFX/gM3/jGN3j1Z14hpGV77bXXhCjBKyEERrMx491p6xhW1aKYYufWkFsv32hD9/G1kvaDQwgx51EEbn32BvNqSuY65K5Lpp22YCdW4Z7v5qMohZsuXisRVEItPCFoRSWOTui1lcutyNYUL9Vjhf6KcFv5uha1tcBVUZA4FaQ5rjTkJJrhpVp8+FnZdv0hRQKJrgq7mPNXElzVPloJ9ezdp4cJO+OisCtmw2w6FLup7TxLwm7mp3xSfBDdt6aigHhLCATG/oCQL7ZRhpIPZu9GUaG+7eAfHa7o/E39BC2g8h7JIFQBP/e4rWyRvA9IEhO+nTgccQh7pQXRNUrIpINzrjYZlIP7I27c3CGRhGGy0xZmAAzTbaZhysxP6xBbXIvD0XXd6EAFEJeAxJuk10ARSjJN6wKPel2NdydCmmSshn4XN1EFgnpSyQl1ZWysfpX20Tk9BmxTMF8Rdc1r09w0Y++yOI1hIgePDbvFZPmw0vj2MMvVxI2Ia0Z7xe/FORQpGT2GjNk/0sKkdRMDj80zayhk1j4X4vMWa1k+poVwTUhbUdrd6qyIuvjI5gshSePR3Lr9PN3b6+fDFjpn5g7aXUbndbF6dUpZlLFFjffcn9/jve99uLIN59yKG5im6UpO4bo/zh11tJrK5Cawmnfz9ut4bPE5hZuShS7eFa2QE6Jr59AovFbO3tIHjPYrB/WMFNTVQo4YWhVigc+hKSuVKxB/khDk0esxSEVw1Uq7Fg88f+d6+2HlaWCh2GeTK2DYmbA7KScVNZvOZ7tMVaibFHaPYq98QKUloYlx6ZKMEU+iCaFXofO4loPqIV49EoQizNEQogOWxFw3giAOkk5Kx0Xno9Ppsc8eJJC6NI7T0oCqR3AUFNzKb/NcFossJn7EbnVvITQFrqfP896PP+Y/vhvnMXr1TOoQcC45ucu5mb/AxI+Z+DjOasddA4QPZu8zDTNUouuQSdr2sqtCxcwXhLpoIpWU3MUbdCKxN1jQwLSak7uE1C1+jQUhBAhJ0yJFVn6mKHOmDNlu3bNHvUZNjtxyuHl9RWl9s1TWthxpqomb9iHNqmLrEmmdI4ejQ48ufZrigYryiHhrwqQnbQYcOFx4Ep0/reuOc+2QkrViJzs03WF4vXekuOPoMS6dhzU01cu0az/kQomj04sfGkYHE7avb/PiL95dCB6NruCyG1hVi5zCyWRy5GdVVbW/s6pKkiSkacr2jSE7t7ZQryRZEhtl+9CGTEM9IUSdUiTjeOC6aKLsXUkacvIwxOOZu3Esllg+RSptBe5CFMZq7/2HB+zsbEOiSP2YletKIUiJ0xTvyvaDxuLHtQA91I9P0SOibvHiCF6qE+flnZdNCDtrd2KcBbtiNsxlbXdyEXj1ePVxgsGheZ/HHZdXz8gftCOrFm/OzUitqPOCVty7d48HDx5QbE2RFJLE4bqCcwniXJ0Ir7h0se9BusWkGsWmv07rm6uQSrypBw3k0kEFesmgPXeDdIt+MqSoq2VzyVmeYTouR9wr70VxWK+3l3S52bnFMN1imG61x/fB9H1KLUE1jhJLhKoWPU3+3awq6upVYR5KylBxM3ueTDrMmVCqJ9GUThggujrkHa0geVSYLK5wfS++ozS3yDibduGurfZIi6/PwQcTXvjs6tvKjEk9mD4+S4gFCo0Iahw4R8I2z63ckDt0KY8p6KgKzzyfxdYxCB3tHdvKI/ayaxyqxXE1UqXP8NGiLD2Ze5Q+Iu8tITbxraREWCeOF19knaPHISKxyjdJ6HTOVjjhvY+Cj4KQedQpJHXepcRqY0QoZiVZFiuKCbGJtjhBtWQ2nuNEcIlj9/1RdAazlM5WTtZNSHOHhDpdoU4FFXUx1CsBNGFR4N1Y0svXa/wl9+JJNMdpQpCmHVD9wUIUF9a5tXVOH4fDs1G4xv2f6dSdGhN2zx4C1qDYOMqm8uKabV02p+1kRQ8Vn8w/ZOwP2u9tZ9d5PruFiFu7Ha+ee/OPGPk9Zn5KkzfmWE1mVZTZbEI1UZzkfOYzn2GU71FqHDY/9eMVEamidOjhqRgmW7zQucP74SexeCKpJwo0M1RrgZcnnSi8jjgqQkeO9toqQsEnxSdkLlsJe838jAfz+9zs3mq/N6qiaO27Pg/DLpo0uWUxr6yfDJiHgo7LSV1Su1zRdaw87GRD+gwppeQe91px2VbQ1v9qwlzraFwX14qdk9EIz8Z9ieOzkjaUOp+UFOMHK8+ZM2UmYxalEQvHKhYxNAaoY8jOkmgMlJSAktOlYMZCMsf/dns5lSzGhVUyJ9f+Wscw117bf221ujS6dY8Lz80nBf2tR/dZSzR7bI+4rg6YsN8KmZXebktkeUqi58+lO7LGWhjmZMzcGJKYf1b6sg75xfUM+r06B655Xn1cqmTbGRri2m/cinODq9Iz3p0Qgmfn9pDgA2mWIA58FSjmJVme4hJHVYwJwXPvgwdsXR+QdTKaRtZNKgASoM5bTDRHXIV3Fc2M3iRkJLp+Xi4qHPkgoIpz8tgK3E1iOXbGRWFXzIa5rI7dk9pOGQr2q4cUYUYmHTLJuVd+SKWx1UdTTLJXPsCHitvdu0fe7EIIvDv5IZNqQigDIQ3xkz5KEFka8B5FQafbpT/rkF3vsLOzgyuFT4oPYlK5uPYNNRCbqDpxBBW2s+uUoWDmZ5RaUpsHeEKcoUpCL+nRNF/tupM1TB1VBzG0dsiVzF3O2I+5Hqo2XDquYnf+qZ/F4wlA0mQiRUfMIXRcN/axIwqgKlTMwiz2gRPXuqDNv1fOpwYGDNpJDQ2NWI7ulJCSPNKzO5ovtfp9JVBIGcOn2kMObS32bZssibrm+dFhTMSRaYeUdKVBb8GMmYzrbdQ5XaQkGnP3EhKmMiJJj4qxQiakmh3J80tJ6eqwFpmLKtiM/Ej/uHUcPJjw3AvXVvIRV8+Jo8f63LplHI6+bjORvZhrphIFlCoq0mopVX1k65TzEkOiGZWbt30S2/w6dbSNsOtHLz0xOnAiOIH0Wk5zZe1IP+bQqdbCtX5eB3qDbtxn1SGg/OG3/zBO8sli8Yj6RagZYsR6PpnyH77zPUIIZHnKcKdPmqXMZyXVzLdh5cN/utsZLq3TFlz9QRKN4/n06d3yNvGea8LuKSNPP8IlIp8B/jfgNvGO8Nuq+j+fZ5t2xWyYT5OwG5X7fFi8SzvjlPsr4TmPp6MdnCQ4TRj5fablhLIsef/99ymKgoODA0JW0buT4yQhTzM0cXiqdupCM92gufHczF/kod+nue8N0y3G/oCxPyCTlEKLelqEI3M5lZZsZzt0pMt7s3cptCSXLlPGbUOPSLwJVKHkZn77iGA6jsIXS+Jz9XxBdDDT+letCAW7xcN459Imkd/hJKUMJRIcmWTkLj+6LV04PCLCttvmgX9ASkpSVy6WWtJ1XQayRULCmIPlrdBn2DpazZitdRzOz1t3bDPiWCkQCpkh2erbyXK7ieXvNAQ8XforeXKeasXha7IrPR4nURSVzFrjb90SC6ZrCzhyOmSa121HtJ57ejLxVM0r0rJDlc+PiDtHQkcHpxNiTR+85j9SBxFrnVfNPa7zZJL8FaWSguDq119iGgOtyRtFWeOk6qH8ROpQaPO9lTFr0rRzAQ6950Qxn5LlDucc29vb+GyO4tvehM16RB35dpc337pFEE9Iqih+NW4pBKUYhTiir84lLIqCyWTCw73A9vN9XCJUpUdcDBvf/+gBP/z2T9aKwUcVoCRJcuab/brCldNgwu7pcwGZSxXw36rq/yciW8AfiMj/rar/4awbtCtmw1xlYRdFVp2fpZ4Pi3dBY35UM7LpcJL9zM+QyrX5Ld/60TeZTqd473nhhRd49dVX2dddHpYPyFy8GQcNTP24Dfs5ce2EhevZDXby6+zJQbuWWZhR+JIy+HoGaULP9UlcSuZyttNrpGT8ZPrj2H6kHpdVhkBXu+SdnELneA10XY+d7Dl6SW/9SVhDlmTMq/nR86VRyMxCwW75kFE15qA8oNKKXHICcYaBUx/vlRJdvo7rHrmRePX1WDFHpRX71QGzMCVoYBZmJJKSu4ydZId+Eitzewzo0uObf/zv+Y9+5meig7okopRF8UEjuRbB3BgaHbO3IsZgIViX/6so2ilJssX2j5Y7HL0Gx7LHUHfaUOhcpmscvngtVZR1k99Hh4+bFhnriJW+Z0ueTzSjq31KijgTVpREM1LyU4VMKylA3aG8sqXzVa/9vKO/1hGb+87wUrf3kXhOqiqQtg5oE7Ksi2ZkKX9zebEqbcHE4mfLBTZu6XpqcuNCPHbidSQqIEl9zAvHUNvVai3q6sSMJiUvUfrbGUlYbf6tS88MUoGrQGI4OM8yXnttK1bHV+FIAUojDA8Xnyw3uQYeWYG8LBTn83n9offsIVnvvVXFXnFU9QPgg/rrAxH5NvASYMLusnDVhJ2qsl/t8qC8xyyb4m8G7hcfk0hafwJPqEIV86W0yZ9SfPB1rgy4BHp5D5XAKz/9En9U/JA7d+4wHMbQlRSrn2qdOLpJn3mYRuEoDicJW+kON/IXVh4781Pem/4YIU40AKi0okJ5Mb9DJ+mgqrw7/QmVViSStH3nBKGQkq1kiy5dSi253X3p1OdomG5xUB4cCYsWIeZ0PSge4JAockUIqpShJHNZHI2F0iGjl/bYya4x9dP25wBVqJiHOc+lz1Fpxb3yPgCZ5GQCHk9Qz7X02lGnD8fsoCDnaLJ9LCgIR9y5Rphn5Gxzgynj6JIBCVmd97dKIwC61zpL33Ok5FQUa0Wd0Ey7mMfB9XDsZIvGu5vJ+AT90zb/kbv9QCMVlZu1R+OpCMGTa+/E+1XqaSN1G5BDPwSE3Q/3ufHZ24/ZTt2vrW454jQ9Pu+MWJlaJpPF5ItjiK9lHSFG69As0VkD0LoNz7JTd0j4tWH8JbUqUDe/XvyOOE1rkelYzXMMOE1Q52OR0ZocSHUBQtxvrIYto9BsQtzLbXySmLdIUiFdR9d3EE7+4a3dp+rayuPmz2w2a4XidDplNpvxta99bWUbyyHk45zCyWTCaDRid3fXhN1T5gmFYp8XkeUL4bdV9bfX7PsV4D8BvnKenZmw2zBXTdjdKz5it7wXXS51qFZ8NH0fLWObjlAGJBVcVn86l3hTcEnTo0xx0oQyJE6NyGJPL9VYdTpMttjl3son20Si61ZqyQudu/STPqlbbdqrqtwr7gFu5WeZZJSh4EF5nxeTO8zDjHmY03Ed5n5GFaqlilalCAWJOAbJ43Ok1tFxHW7kz3O/uFcvjtgaQhw+KN0kp9ASEei4HB/izEuvvk4WT+glfRJJGKQDtrNtHhQPmPm47iKUZCFj3494UO2SkNJLF/l/KSkVsF8d8Hx+48Tr7jFgVDtyq5WusTlwUywxZBuII9jmTJlwwFploJBkLg51r1uU9HTAgcQiiMM0Yq2Ugo7Gm6zDrXXkmsa5JQVLJRhryfX0N+yToC4wd3NYOV/EnmtBTrzfOF2ijJXZSB3qrI9GIK067N8foZ+NoeymH2GyNAlCUYpkQhDfFgR4V+G1JPf9I+Iu4CldPb1i3X2rjQsvji0JGcHFRs4oOFKcplFAHTO/9ug2F9sFCElBScUrP/MSIalwmtZVr2Hp2XENSaibhK9ZcNNrUev8xJDM22s3On5+VXjW7U4QwAW8m0WBGlJcOHmRioiQZRlZdnyvxobd3V3u3bvH66+/vliG6qIyuVodf7csDL/61a/yT//pP2V3d5ePPvqIt956q30Pf/311/ln/+yfrd3nX/trf40vf/nL3Lp1i29+85tHfv57v/d7/MW/+Bf5qZ/6KQB+7dd+jb/7d//uiY7dOBf3VPUXHvUAERkC/wfw36jq/nl2ZsJuw1xGYQenS+RVVYqi4OHBLveSD2IzXx9oxlm5xCGZkLucrJvj1VPofOnNUZf+VlTjzWngdvjR9B38jZIP/fs8GN/nVucFttJtdrLr7JUPcPUn90BANXAzv812tnNkjdH5CoyrMajgtSKRlFRiY99UMsZVDNdWGh2NwheU6ilCHIcU6jYZcz+nl/a4nl8/8/ndyrboJb3Yx04DnaTDpJowYrTyOjoSMpdRaEnHdakqT5olBA30kz7dOgx7u3ubB/MH+DIwSIaoi6J3XI4RSjqar7iDCUmdW3i0mOI4Mjr0GDJltDivCDndYwsKmobA69qPAOTdjJHssnwzzrWzMhJLlv7XVKbOZRbDm0sCc0VsSrP/RtgczvtqzkMsxIAoZppK2KZi9Txunk+iQF0XJi5dQeYfPwEDINWc0s3bY5Q6PxLAqcP5FOeE0k1rURcdqMrNSUIeW6a4mOvnlsKWUdAEKjcnC93FOXBzgvPHiLGIW8phbf6bkJGGfOV1q1xd9PMoab1i3q15nMaCKXUVqpCEDiIelTheLoq9tD43tUg7dF6bayK2UYkflGR5AsVSv0AUxAmJuKVcg/ooXYV3gaTK1rqC52FdCFZEWlfuUbz++uv85b/8l/lX/+pf8bu/+7t86Utfarc5mUyOfd5f/at/lb/9t/82X/jCF459zJ/7c3+OL3/5y6c4kk8XF9HuREQyoqj731X1/zzv9kzYbZjLKOweZS177xmNRhwcHHBwcMBoNKIoCjqdDv3nu8g1odvp4pIE7z3FfE6v26P0JSISw3Lq2hscgDTixRdU6kESEnU8KO+TSY7zjlRitvT7s/d4qSs8n79AL+nzsHxAGQq6rsf1/Ab9R7hoMzdl4ifxBiBxBmzqEgbJsAkExd5fkuLVM/NRfHaTLmUo8c2NBMdL3bvk7nxD1VOXsu2223+Pq0l7o89k0YQ1TzoEHwsCVAKBwCAbcqtzq32tggYOqoOYvxjmoELuMpK6ErYIc7pH8gBPf6106ZPTbcOlKfkjCwpinl4S175GfC36ry3WUklR97lbV5AhqHjmTFj5QLDSlHohLBY4Qqhi0n/djDbTbhvSncuUsm2FovXXAiIkmpKH7qlz2NQdVxEr9UeYgJyggEIQOn7APBm3bhgSRV0nDPB4nru9U091qPvBSRYAmrUAACAASURBVB16rd1BL2Xcpyy5fTWekpROPO5k2pyCR4ZfF2ur89/q3+nlML2ibc9AqXvLHRVtjQ/bhGF1ZevULpvWIefgKlzISDQFPVp8I8HFmb5rrjUJrv2AxnFtTOr9rBR4HHlMzONL/GYbFz+JPnYiwmBwfBX3n//zf5533nnnXPv8NCOynD7wtPYpAvyvwLdV9X/axDZN2J2Qk/6CbnpW7KaEXQihzdtoRNxkMomh0OGQra0tbt26xauvvkqexze4/XKXD+fvkbj1FZ9b6TWKMKOUWBVaaWyym0p0oEr1ZJKTuw5TP8FrQN2iCMNJSkIMp8YmvttxDuwaGneuDCV5klO5kmkypSMdSsqYNyeL6Q+5y9hJrwHQdV28xpYmqUupQnQAxCeIU/Kke25Rt45u0uWgOiCtX8NMcgqNc08zl7GVbDGv5lzjOnd6L648d784YK88iMdVt4GYhoRcMqbMKNWz3Iyl0oqu653YrVsmDk87WWsXQRjqDiPZW8mHi07a+gKJ6HIlUFc5r2xv5fdqUY6hEueFIkLJaviz3arGPW/p9ZWfVRS1kGsS+ZtNR/nlpWSaVHRCj0xP87qvd6mO60X3KBISen6LQO02Bde6oRUV289t0Xibi73XPefcbOl4jtIUNFSucRhXa78fSW1yZeFR7mNUiU5jD0NdytkTYsqGOL/mGYdlnrRisS2oYClfzi2alKuGWrvVjwuOJBwvxERlofVa827peNqXLH6IiHNy17vQZ+Wy9rH7N//m3/An/+Sf5M6dO/z9v//3+bmf+7mNbt84Nb8E/FfAvxeRf1d/739Q1bfPukETdhvmMjh2VVW14u3g4IC9vT0mkwnf+c532NraYmtrixdeeIHBYPDIN55m8kLzBtW8Mcc1CTvZNXpuwCxMqTT2Myt8wcjvs1s+jG+msnDzHEKlJZosjsmRMA/rJws0TPyE96bv4UN9sxCYZhMkQDftxcq1egarqFDonK7rcD1/rj2PmWRMmTINTfUueBfINLp5lVZk8vi8mdPQc118qPik3K9HZwEoFRXdpAOi5EXGNRah5qYdykezjyh8RS9NYzWsC3GOrJaIxhYqQaN7UmrMZ9tKtja6/uNwJGzpdTxVbENSN1eeyNEK2gVKT4fMZEpop2xk9fSLw8+JV4wTR1cHjKR6TFHFKqUshOBC1B1dT+GmpP5kFa2qSuJTvCvWXqtO0xOPN1tee0K2JlJZO1Ir+9Al55JHnOfF44MsQtvRZVt1rqQWZqCM96fsbO/gNCXVo2HJKLaqOgpbV8lqzGdzJAT18bmhg3fzpqZhzXHJoWJgJbhi8dhQz02OlRvte4eIQIhtk6KbuFR9rQnqynYyRXN2Udp+mK1ibZ8kx7t8G+IyCrs333yTH/3oRwyHQ95++23+0l/6S3z/+9/f2PaffeSp97FT1f+X03wqPAEm7DbM0xR2jQu3LOJmsxlpmrK1tcVwOOTOnTt89rOf5bs/+A6v/dyrsRdYMjiRsxNbhVxnt7i3qEQUpVLPIBny/7P3Jj2SZFl25vfek0FnG9189vDIjEySycxmg92J5oo/oAByzdoUiAIXRSIB/gCu6h9wQYIbAuSuuOCGAFHc1opAVrLZjapiZVZGDh4+m5u5DTrJ+N7l4omIzmbm7uYxpR0gIix0EHkiqip69Nx7z4lUi7f5MWfFGU4cvaBH4XIm5cQPBqDIXU4hub/GVl5smMVj0kpt/HK1YnmRvPDlKzNTV8ZqhGjBYOgHA1KXUjj/BREScju+00yV1hAFkYSg/f7KskCUt0t5H6XrMpyV56C82XAhuVfeELqmy6P2Q0ITMs7HzYVkWk45yo7JXF552ymmdkKkIp9dqgyFK4hNxMD0KfA5oB3doRd0CdSX93FWKAJmRsBXmVQNiQklbkhJqXKSub66ZdRkLpJWZXQ8T6j8lGUkq8pSPWxQP27TeoAqO/RqhN44n5Dgy6CzfjSNInYfPrAhjW+jNKXXZqbhncrsuuofXVbINFTRYfUeFRpJNK9/c8zB/3Fv4xadLmaDDE1ect1DC1oMgfMm09J43C327DWH0iiIdvawekmVt958BqxX7ADtUOUqEVdiUM7Hoy1cL5VGlQYx/seDOAFT9QdKvaaK+Mr1f/6/jsRuMJhVRH7v936Pf/Ev/gXHx8fs7+9f2z5u8NXjhthdM66b2NVO7LWZ73wvnIjQ6XTo9/tsb2/z8OFDWq1FDzQnjmeTL1D3hRfpU79dNPdaD9YOJczDimVSTCjF+V/RCBL4X+r70R2eJl+Q2gSjfAnpJH9L5nI6uo2qiAlUv9RFcLUKMXetK6VgK9zeeAEcFT6CK14qlQYE5OQU4m1BOqYDpoOIUEje9J85cRxnxwzLEaUrsUphnGlsQWTOaPV9IAjDYsSoHCPi6AYd+lUu7LAY0tZtlFHVMIhXoTKXU2KJ1eyYRIS3+YkvFYuf2m2bNolNyF2GUjS9bV3dYyfYwSmvgn4MUvqu0GgoNaztQ1NE0pr7v+rrXcwcaVl9DXR1eQolxmHJVbZAVManU7b3bq3uTXwOcL03j/lnNpSJdyFMCkXsOt7ypBnKCAglWlG43gUOR2nSasIVaAtu7LzeuNx836xkg2ontX4K2oULCmM9qFErvYGL0RI0Njyb4Hv76n4/BRhEZr19qlLqgMZ6BVQzzKHU/Pn2MIEB7Uum80RNUPjUC1mI/2p6eOu4mIVzotAuQqRsyrdUQygKjSsDSiY4sattJdUMjrLrcmc/DF/HrNjXr19z+/ZtlFL8+Z//Oc459vauPkn/uwD9JSt2HwM3xO6a8aFZsc65pg/u9evXTKdTnj9/ThRFTRn10aNH9Hq9K/kbHaavGNshWDCVouPE8SJ9SqQ/W9OAP8Nx9obEpURVPmopJel0StBzvEyek7iUeM43zQfEQyberHdWwp2VYi0WnMKKBScEOmQ/Wv1yrpFLvvaCayQAlWOlJKxUIxFvXdIP+02E12F6yKgc+WQG5SjFUlL6qTwlGDG0dNwYAL8LnDjcFrzJjvxwhFKc5GecFyN2o20vbOhao5hN5GkUiU3oBp3mh8BZcc5ZPgQFzlkK53MxS6x/PynFIOgTKT9A8Sp/Qz0Z2jMdBkH/Kyd4Oosowhwdza/DK3vhmh4+jali1Oom/HmypYiq/jeFoiVdImlRKq/ouEw4ffGCh3uL741S5c2Qw1I339wts7/fNWJKoXxk2SUqXz3tOz98MH9f7T8nMCMj4ImcE+J2PMd1lzrTpCo0qxm5U8tkR0xl8F02SmC9LYUitO0rJ2VIpf7Nk+952xUF3hZF16TOEzCRavCjUcdmQzDpJGVr0F+vlFWPr3md5/4Xf9n6UnMIdvV10WiSs4LcZewdtGhqwQIKg7K+xHvd+CoUu9///d/nz/7szzg+PubBgwf88R//MUXhPzN/9Ed/xH/+z/+Zf/fv/h1BENBut/lP/+k/femlx687vg2n44bYXTOuqtiJCGmaLqhw9TBDt9ttSNzW1taCD9K7wErJWXnizYRlloyglaZ0juPsiNutOwje+23+Ay4inBYnjX0IzMhJ7gomduq/lCs1TavZ0IgTR6zjqvxYnRN8adeIIy9zgjBgP77FVrh9IaGKVMQ6ZUKj0db75OUua/r+OkGHW9EB5/mQt/lbTvNTWqZFoA0iQkCIlRIrjsAZQnyU2fuUMUfFGCJomzlPOWPIXM5Zcb7xAtGUpStM3JQk9fYVkYoYu4yx8+c3qKwwcilJXEZbt5jYhFhHaBUiIoztlEJK9sPdr/QirURx+PlbPvvBdymVJ+ShxBjWm+YqFB3XZ6pHVSm3LrUq2q63Qjw0hqj6Ak5dSmfQItUjTzxEYyTygwXMKTyXrfmKKs1VVXhBKHVaKVwexoWzMiWO3EwXyqGztcySH7RWzBSymsCpWWlW1q9fKQjsLHc3tG1PIrWfotUSYFy0mEByBQKyqLktPVYJoopmvQqFFamUt/myuMKUMUYCjl+dcvvuwZodKdDztdnqL+XA6WbI4l3hrDA+m3Kwe2fueOb1z+vHV0Hs/uRP/uTC+3/yk5/wk5/85IPWdIOvP26I3TVj3Qe5LMuFadTRaERZlrRarYVhhk6ns5At+OrVK5Ikee+15C5nXTOo4ChdwWF2yFF+TKAMsY6507rHIBxUjxEcjmDuy9WKxYXOq234L6LCFX5SVcc4Ee+jhs879Y393lsNPEm717nPkxdfsN86YLcabrgIvbCHzvWKomaxBC7ku93vkdgEhyeTsYp5mb1iVIypfbtSlzV9QaEKMNp779nK/HU72l5Qu5y4lZSKdRiWQ6RcjQyKVEhqM4xeXXcdM9Y13eY8j5jQD3rkRU5hS9/z58CJJXNlI3bkLuc0AZ35GDNtNEYbTGAQA4ma0jatBUf7MAyvrTXgKhCBiNZC6fUiaAxdt+UTHFSJQhPI5QMNLiy4/Xi/6acTZbGq/qwsFyzXT60qFA57ZduTq5AfT9rmpjkRbJWIENmO959Ty4bQs+c3xz23K1UlVNR0p+oSo/otU6leCi0aY6MFQuwVxgje08rDT63aReuSasdN75xaJKFANSw0S6qoD0iCAik1eVb4YQ6WBlEWTvG6oZr3I0r1Z+Bjk7nlfV5HKfYmeeLLg1J8JT52140bYneNqM0ji6Lg888/ZzQakSQJxpiGwN29e5fvfe97V3Iu/9B+vTr2a34bTiyJTb2/XLXmesLy2fQLPul+Si/ooVBEKvYEp/qiyOcUOC2VvYUIBZbC2io1wKGqfrLYxAQuIJeCvWiXO617vjT7DscVqIAHrQe8SF94Pzeqnho0cRIT6nBhSGJYDBkXY1o69tOitY8dPprIVmTPinemj8sOe+Fucy5O8zNO8tOGFPaCHvvRHlr7SbxaaRsVY07yM1wHjvNT2iamY7zdSH2Mu+Eub/MTrPL2KtMyqUrFPQRfds9cRjlxJOcTJuUU2xIIvR+fNorAGAId0FIxmSsIeyF7wQ5JkZK6lNJZtFOIFdIiwyaLbvZFUTCdTvnZz37mz13lnL9M/pYjjur/fhlfKvUgBlccYnA4iOxy1OocFnv2NqmF/g95t7mEi9albGM1sjCdiZ9Qzcz4Yj+1uXV7UjC/3kVy529UGBcQXGhNcjk2ERCf05p7Yics2ofgz5sWDWpN5JeaJ2y6+VtEcKYakHABYoqla0FdJvXb9X9XxFGD2Pe3JPkKph0/eBvX3WN3g98N3Lxj3hPzwwy1Gueco9Pp4JxjMBhw//592u32e19QPpTYRTqirTskduZUnrmsUdwMxv9EqdIZjDIcpq/o9b6HUopb0QEv0mdNeWU2+Si0TIvMZhTzXmbKN1YjwthN6NBGac3t+Db70a3mPKw7LhFhYicMixEAg7BPt7Jb6QQdvtP9DpNyQulKQhMyTaYM7WrqSu39VlucUJW/NBqrLFvhACeWXApak5jQzUrQx/lbTvLTprTsnOVNesTT6XMiFRMHMbeiXQIVcFS8JVAGf8SaqU0oXem3jyNUAYOwT8vEHKbHHOdvcaVD5b4n73n+Aj0BKYS402Zna4eD1m1OilNG5biKmxJCHdENOogTlPh+qYkkZDrDaEOE8c33rmRve4+9NekZP/vZz/jxj38MsDbOqP5vkiQr99X9oiLSZFxuIoL1c7Ms+6ik0FZ9du+D+alar3Jd3yXQDw4sxo0tlBSVm1vBgva2ui3r1vhHVs8Vv25TDQe8D9GZ94oL+3Dn0V5F4Mzio9RMnfdLnkV/aRugJcQFsxSNetuzWrGqQiBqkkZDfrUEKOtNiqVh6d5wWje9efOrqQc23uN4r0E9ex986D6Lorghdl8yvg09hzfvmCvi/PycFy9eMBqNyLKMMAwbFe7hw4cLwwz//b//d27fvn3JFi/HdUzY3m8/5Mnk12B8Kc9Vv/oXyx+e3FmxJC5tYqkG4RaFFBzlb7xBqO82JtZtYh1ROouSuvHdXzi7uk2gQjKXcbd9n37YX1vOXFQRHc+mzxnbSaOInRVndE2Xh50HaKUxyjRlYoCE9SVqh10ot/SCLuPSR2b5frwCrRS349skMm1KYaUrOc3PmkgvRDgpzkhsUp0ijbWWL6YJRml2o22iIORY3lZELiR3BalLcU7o5G2evHnCcDTkLBx5z724TbvdYrA1IIojSgqSF1N0z9Dp+kGKHl1Sl/lSlhI6gc9sFfEDFIaAtEz9VG8jOims8q/dZV9gxhiMMcTxuxsy16RwmRDWpDBJEiaTCb/4xS8oimJhiMgYc6EyuHzffEvCKjZZmKx0Zl3wfEXgruZh925YT+rq++o1btqrL31W5X1nEL1o6mxciPnAdXslLpsjU0KrG2NNhrZRQ3bdnEFwc2SimwK3UtpHmrnA+8ix5royO/S1UGIwtvLT0xYx9Q/FOk1iuWQ99/9KZlPYbpZAsvaYN34uqm2YejvKe+ldg8ediFzyPr4c1tr3+qze4HcbN8TuitBas7u7yyeffEIcx18Kq78OYhfpiO90v8f/+OJnbD/uYK1DU9Y7mN+b7/8Sb98RmZC2brMf32In2iWxU15MX3A+PSNuVVYhiM9fBAIV0g1mUTc1GVtH6pbP3Ul+wthOiHXU3OeHAiYc5285iNdYWmw4Nz3T5cgeE1Rv7UhHbIVbJGVCLjmDoM9OtE3btHmhkmYbvsw760ec2oTEpgRVOVsBkQ7JbEZicyyOSIWQQNktmZRTSlswzIaEQ8NOa5vBYMDdT+7R1WPawWrPWWlLnHH06JPalNBExDomVCGpZMSEiBMKKchcTs90iYg5d0NvDCw+U9d743WaXNzrNlqucRkpnEwmPHnyZMXJXqrkjGVCWBQFeZ437Qvz99WvS60UzhPAdi9m+15vbS9MM0GpVFNO90RFFsqkgYsJ3iF1wgfOOwqdV7mkqhpCmL2/69B6uZC6Vduj1uvmovgqtUxKR5FaWlv1sYByCmNb72yCvHbfqvSTw34qAfDDBQDOFKjSNCr9Va4+2gU45Zr0Bn8wC3XbGRQoq4jisFH5BIGg8PdVh+xPkNQVX1/atbOcYoxdtNbRfrhCNtiWrL+OCgTl4i8CVd1WmsVBjZpE1o+tiORFuK7hiau07dzg+vAtEOxuiN1VMRgM6HQ6X+o+r8sTL9ABbig86DziV+NfgvIJEIvw2aXOCc+SZ4AQ6ZhPOp/QMjG9oM/d6B7nnFG4gkAFGDS5OIwytOdsU+o1rxgEi5C4FGtsUw6u/dsUnlwpNJH25dFIh5zmp9yK9q98geyaLq/ca46LE+/XpRQGP2TwSecRe/GiZ9Osqdr3DNaY2sR/8dbJG6K8YlVYcsl5cfgcSYQiz2EiDFo9VNewt7fNne/O1NpxOWGUTNauVaFwSujSph13OC1OSWxOL+oRlSETOyEtcxQQEtHTXVCKge5RuJKyGszo6hahCshdvqDufF2glGpI4btCRFaUwrIscaVgouWhIP9vEeHXf/EFtrAo5V/7MAwJo5AwCjAqIAiStWrhJoVl+9YAG6WzfSlv8WFs7IcT8IMgNblbpxjOlK+6WDlToYJqO/UARqvjs179+94r5S7IUOWH9dMB3l5ljtTNNe1V+/JeccppXxldGnCo162daY5L2wiUH0byz5/xnhUVVcN3//YjCAqkDMFUPzQbhU6a/rpmGtgZlKu+rvQ8qZsrretK5XPrKwQr15CGqKnlB3sFr6zWo+2iqbrCE8tSe4K3AV9Hg+IbXI6bUuwNPiqu0+wYINYx/WDAeX4+K+9RF1IdCk1LtzGVNUjucn47/Q3f731/Rt7eKLo7PcblCKU0gQ5p6dbCVGkpJW3TXjAVPs+HvEpfedPj9oRU5YRZRNd0OC+GVKZv1XH7oYVQBQ0BvMq5SWzK0+Q5ubVkzvf9IH4AoyWGcZmwE8nMakRBSsbz6UtKsRVh9dYnpS2x1lEWvryZ5inKaFTgQ8n7gy327uzw298+4eDgAIViahP64WKsV6RDqEtrSxcMi0WBjwmzGbmzKDRS5ezuRLvEysc7OetIJUNX4ez9oLewrZrEfpnpE18GlFIN6Wq1Zqrn1A0bRa55bPVvrRV/90d/B+MirLUrwyR1H+BkMllREOdfp1opjFsR9753gLWu+jWvml/1pc5wKYSB/zHiTX9NNf06Ix/LZMy4qPFO0zJTmUT5fYhzzEiL8u+h+v6P4Lm2DgrtBxx0ufKDQbmAhVgvFIjBiPE9c5Qo59ddr31+oKQoqii5IKtaQWjInALEKVQ9gFHMIs68WrdM6ppnVcrd+vOzlthturzO29EEjWw4u78mf04t3s78Q75+BsU3+N3AzTvma4zrJnYA99sPUCjOizNKqTNWFULQkLp636EKKVzOsBiyE+349eTwqPNJs65hOeRFMptYBU8gH7YfNhe1STnlWfKcQAdEOiaVFCXwMn2FwVRTpLohhyLCuBzTC3rEen3Ze8XCRYQXyUuv8GCJdYvaN8yKo2PaTOyESTmhH/Zw4jhV50xNSjG15HlOUiYcq7eoFFSkcbFgAm/dYiPXlIhEhISE8yIA5XsTC1fSCzp0lgyfIx3RC7qcF6OqVGrRosilwOHITM5LOURNNXvRDlEQk5QpDkdqUzpR1WPnhJiIxGWEOmhUU6UUThy5y9kJt75yk+IvC6pqHZivm6ilL/p5UviuqJXCoihwpgTKmXqG4NsH/Wfg9eEzjl6dNM+rFcq7jw8Y7PaauqvCT3YiimyYEZiqnzBgJp4pu4EnVJ1tyrKcvPDuB1flsdb/2+y+HnCYvYe0CxHRiCkb5U5Zg7pg6EQ5XS2xku1EoebKpkoWCasnZEvbmCuPrk/12Ni0t/bm9yZZSyXrxf2L99xzH4/Y3Sh2XzKUurE7ucHHxccgdkYZHnYeccfdIXMZRgVMyykv0pdrpvD8NS2xCTssTlvWF6ytcIuu8QMKpZTEJqZnegsXtKPsqOm5q6Gr6PhROaKru0xl6r80ajsUJ0zLKTute+QubyLAFtY2d258VmyJVqbq/avLRAaHkElBgOHV+WtOJiHHyVvO1QhykI4jjmN2O7vYwGK2NKEOOMnPEGHm2yfeamNgenTDHqNihETgRNiPd9kKB2sv5N2gy2F6TGoznAh55e23F+5QStl48J2XQ3aUvy1SARYhsxmtygBZKR8fth1skbqUxKag/FzkbrhN13y5rQJfKQqvnG764jQfOO06TwpLnZFjK9PgZZIhPHj0gMcPvju7RaRSCAtcUaJjqKdCy8JhC4tox+nphNPjc4rcK4WdXotb9/YY7PSwzpHnVepKRQq1USSTKRTpQvn4XcmDdkFloDz7/DQT627RTNonOgRQXv18eqXPVCVfWeREK2VPVk/pbENgN5G6DX2MG/re1pIsp73qtqH9bmV374gbH7sbfFW4IXZfY3wMYlcj1BFhRZa8kfFmBFWv3Kb1BDpgO9re+PypnRLMNfQvZNniCE1IRzp+ArVSxHIpMUp4m59ynJ/QD/rcb99posKW12JlNuEHvjRprfWqiy2Z5lN0CW3T5k54QOdWD5UF4ITdnZlRsoiQuYxPu4+5HSc8nT7nND+jVoAGQZ9BMPC/6lSfSTLicefhxt4sJ4432TGdoO2zahFvJKu0T6cwikACAmUonFfptFI48YMpmcsbYlcfX6RDekEHK9YPF1T2Lr9TcIrx2dQrYkvwvm7Xp1wqMT5AfsMmV+K8Kq/AuuldnOCwiCkIW446Xa2/3eX+J3fQZYwLska9EoTAGFz1Wag/E84Jx69PyNKsKR1bu9iqcFV/wjAMIPK9akr5Hyfahhcqce90zmwAoqq4tFoJVCvZsJe2Cy5dbhQKsdr3uC2QO7mACG4YnnBVtvGyl6HCD0+gKvVyXTvI7Jg2Lv2mFPuNg++r/qpX8eG4ecd8jfGxiF3u8sYCpBf06AU9jFpNSaj7trbDrQ9aj1Hea83MTRCKCHVcuULRMi0iHVG6klE5QaHpmA6xiRERRuWYp8lzPu18snCxFBGyLGM4HDIshhRJThE7P9wWBATGEEUhg57PUr3bus12tMXno99gCo11ixftettOHP2wx+PuIxSK0IQEKlgodRo0mM3nJLUZh+kxb9NTSrGEOiDUhkIURhmsWDKTNZOORhlyKdgKekzLFCfW9+hV8Akfkc+lrR7/gX3032Ao3jw9YW/7FqXyaQ5aNIHEmCsaHV+GOnXB6QLVvO41mZgN3VyWM6pQnkCsNPzjBw6CZOHRdb+ZVvP9WwptQ77z6Xc27sc51/QSLvcOzk8eL5BCVX2G0ox+v38pIaz/NubiHxMK5fvznKmmXuvM5wX5buWYF1BNN68eaGVerGtfuwqXDDOsrld5JdLYKsas2mc5F10m+FKrmltrvU+nLlTybkqx30x8G34k37xjvsZ4VyKV2pSj7JhxOSbQIfvRHtvh1oKFyMvkFUf58cKk261on0ftR3yRfEHufIKEU54c3W/fb8qg70vsdqNdXqeHPr1h7kNjsXRMm5KSiMiTJuWNkAOtaZm42W+sI6ZlwtvxCeWk4PDwkNPTU05OTojjmMFgQH+rT7nrS2YTl2DwJr/1kmMdN8MN3aDDiNHKhdmKxegAEeEoe8u4nJC4lECvlrxKsegNXrnjYsLL5LAqtfreOutcQ8pmXxN+RrKUElCEaDSGUIecZuf4IHWDWEtoQvbDnRVi+224EL0vAomaqdTrhCDYIJ2Z6To9Jw5VpE40oW2vDEas3V6THbvmsWrpj6q/LwgCz3ecQbvwUgKptSaKIqLo3c7H2dkZh4eHfPrpp2t9Cushk/nbrLXNe2++bL3JnzBqhbR6QTMQEQTVjxJnFknVyolb01+LAhsgVmbPdRfHjW32lPPbws4Tt6X7y6pka6R57XGqUgc/rmJ3Q+xu8D64ecd8jfEuRGpcjvn15DdNCS8vc56UI7bDbR53PgG8X9yb7KixEwF/8XmTvaFlYr7f+z6n/04i9gAAIABJREFU+RmJ8yHzO+HOUhnw/bAb7TAqRkzs1Kt3SnAUdHSH++37vEhfktoMEFLrp1l7po8tLEk+Jcty8jzHGsc0nbAX7zAYDNBa86Mf/ajZjxXH6/SQs/yclopIXdYkV+xGO9yK9xrfvd1oh9cc+qixCk4cmcvZD3f47eQpAgTKoDEcZyf0gx790PcPlq5EAUFuVl4jJ47D9IjIhIQSMLZTFF7hK6TEKI2TyijaaUITQjWF3AoHHGZvKWxBL/RK6qRM6OsOB+E+RplquGTKuR35JA4dshX06Zr3Tzm5wSJcle86D139UFCiMTZe8LC7FBdGiTFTpmqOUzuDiMbYD/8MXgal1FpSOPOMqxZkvSo2T6JqpXCdcfV4PG5uUxq6gw7tTsRkkvDFr1+STjM+/f5DWp0WzjqUVmil0ManukzPC8JgRhLnfxwq1MbBhWVcTrIuuc8aT/6asu3lpf6bSLFvJr4N19Cbd8wV8a4v9nX8WrsqsRMRnkyfAoqo6kGrSyxnxRnD0veQHWZvCPRiCUUpRaADDrM37MV73G4dXLie94FRhsfdTxgWQ86LIbnL6EiH7/Q+xSjDp61POBofczY+w+WWQuW8LY4Jw5Aoiul0Omxvb1NQ8LBzn61wwNnZGdPpdGk/mvvtuxzE++QuR6EJdYiZm7it0TIxe+xwxFsSm1a9FZrb8S3OinO0MoTVudyOBphCMyrHvn9KBz7DtnOPU3e8crypzSoDY58O0dYxqc3QVf6nElVl6gqiPGFoB2221ZY3RUaz29qv9q/Iy5zD7C2nxZBIh+hqirhrWsQ6wuJ4k79lN9xiey6d4wbvD9cobIvwZVUBWxsgXzGYXjRrw22XP1PLTT5yfb2Cm3BRVizRkidf4L3ipJgNWbyrUigiPPn8f/DjH//YG1eXBSpwqEgak/SytJy8PieZpqvl4wpa6yv2E4bXMIQgKCPU82XiHM6qC3vs4MNJwo1id4P3wc075iOgMbX9kojd1E4pXbFiCKyUb1Z+m79FEDKX+7SEJRhlyGy+sOa6r21qpxgMW9HWQr/Xu0IrzXa0TU/3mA4nTLMJ/+v4fzEee7JUx7Ptb+/xWh8RaW/WWohXxqzyHm+9Kt3ionMT6nDlXKxDS8Vs530edB8iCLGOyFzOm+yY9pxSqVAMwj6BDunoFrfb+7PosTVYTh4YhH1yVzApE1RVEuqbrh+gcOf06PCoc59QBTyZPKcXzKaKM5vxIntDaUsCZbA4EpvS0hEtHWO0IsBgtOasHNILOt86L7uvBJcobC6c9cUpG6KXpkmXoW2EC1IWGv43OXboWQKKdj75ZNZPplYUs4+GoJ6cXeqLU5WKZz/8faa1Jo7iynNyNkEbBYrug60LnukHUpTx58VaRzLJGQ+nC7nH8+VkgOfPnwM0uccXlY8bshgGRC2fwtFccjQYLdiCd5vEfUfcELsvGQq+BW4nN8TuY+C6hh6uuh3HvJnp6jbKyq4jVAEOwSw91oprpk0BClfy6/FvSVxCKZbcFgiOgenjWuvNdtehHmoYjUYMh0Mmk0lzkWq32zx+/Jher7fS+6KzgF+Nf+ONe+esDR607n5QpFLprO/fU8HMpFhoevmguhhveH6gDIFeTNlY9xrFOgJm50krza14j5YeMyzHdIMubRPTNi3CXLEdD2ibFoUrfOfjHLk+yk/B+UlYRVWmUppcSk7yM0IT4JxrlMnUZvRuvgg+GI1dx8KNSw+qy6amwCnB2M0RZVoMYiPE5HNPnql9dWxdfY8x2k+WopAwWySaoqCMUNek5q37PEvt0baC6vNoXDUsujxO+n778wbHFw8jLDzeOAIDUp0DrQ3hTshgq4eUq71vX3zxBa1Wi9u3bzcRd+vKx0VRrJDCnd0+27tbZJl/7ZRSPs0kCigKy9nb0QJJrAnhfDTe++KG2H25UHDjY3eD9bhOYncVtHWbeSIxDyfCIOhzzBtuxbd4mbxCL/XYla7kXvtOc9vT6TMSmyJKkdm8mmVTnJdDyn3Hi+QV99t3F7aRpqmfTK3+SdOUKIro9/sMBgMODg7odrsopXj69Km3DhmsLxuWUk1/SohVjgBT+byNGZVjBmG/OcdOhNSmCELLxGuzaXNX8Dp5w7AcowCtDAdVtNjy6+RVyVXFVar+P+eEJ+PndII2O9H69Qc6YDfa5m12Rsv4oRAnDpTmVrzLvcq2JdIhv1bTZg1GmcrqxKGV78fLbE5oAqyzM59BJWQ2972QNsYojXE5SkFHtxtV88vGx7Tn+bKhXYidI3bGzKcszP3RePqWiI0uVNKMCxEXIMr6/r1gtv1F7ziB2s/R5BWpm5+kFSTIoYg/snK3wSuuhra+NFs/xKkqY/XiNX24kuXLorJsHCyC0jLLmt2wz/mIu025x/MwkWP+bV0TQ+ccnY5gcyHPi4YU1oTw7OyM0Wi0cKzLucebyshJktDv92987G7wXrghdh8B10nsnFvTl7OEQAfsR/sc5UcEeEsO5xy5+HSCvWiX3/BrbsX7TO2U8+LcX6jEX7i3oy1uxbcAyFzOsBwTqIDzcuj7uRpVAVDwKjnEnpekw4ThcEie57RaLQaDAYPBgAcPHtBqbS5VXnR+nAhH2QmhDtFKE8x7tDk/qVoTu9wU/GL0q2aQQaG53dpnP95tnmPF8mT8jEJKWlWKhRXLy+SQ1hpbjEAH7ETbvM1OaJm4IWVn+ZDUZWyHAbkrmGYJJ/kZLpC1x7IX7aDRvM1OGdkJqc2q6eI2J/kZd1q3Vp6jlWY32uIoO6GtW43djBOHiBCpEBFH7gosDo0mrohoKSVaNIlNyVxeqYY3eF/UCpsz+SKnuuA5ouylPnC14a+Iw631R6Mq+VXlzrV7VTO7jw3xWe+CBaJVRYAt2rqsm1YFwsrct2ZSWiAsIQ/WP+daIKiKTPol1z5//gogCCqw3vZEQKrIr+ucHp8nhkrB/v4+64735z//OQ8ePKDf95P4m3KPi6Igz/OFiLt//a//NX/5l3/JaDTiZz/7Gd1ul16vx87ODn/4h3/IP/pH/2jt2v7wD/+Q//pf/ysHBwf81V/91erZE+Ff/st/yZ/+6Z/S6XT4j//xP/L3//7fv5bz8m3BzfDEDdbiy1DsnDgK8X1XRhnut++hlOZN+obUJRRSVF/88Cx56X2+lOaT9iOe85LX2RtcZe2B6JlK5Lx/h8X314gD6yxOHM4JDkcynXLmAu7t3uHx48dX+tW7fFybCOtxdsJpcY6uG7OVph/0iE2EUaaanoXUZYzbKR0ZNP1wThwv00O0MuzF3jD5PB+RS75QPjXK0DIxQzWkK6sThwfxHkrBSXYGCLkryaVgP9prBipCPMHL2uvLLUopduNtpjYll5LtcDCbaLUJz5JXfNK5v/K87XCAFcdZfk5eEVYrjo5uecNiKVGi8DO1jtTl3k9PVT2VWjMpp8TvaHlxg1UYF6JE48Ks+XysSEEL6tDVvxAUemaQuwYXGSI3j1EO9S6TuRetRytPyqoBD39Y9YEtGQHPHjB3u5p50Rnnp0g3rfu9SZagQ7fa/6hAKa/gNS+Rri1pBFfoDyJ2zoIyrC0Tr6iGC/ct7nPeFmY+93gd/v2///cA/LN/9s/4V//qX/GjH/2I0WjE6ekp3e5mRf6f/tN/yk9+8hP+4A/+YO39/+2//Tc+//xzPv/8c37605/yz//5P+enP/3phWu5wTcPN8TuI0BrfW0lqWUCJCK8Sg95nb5pQuR3ox0eth9wr3WHcTkhLyx93SLQnkic5KeUt7yy9Dp7w5v8uCFKIsLb4pTJaMI9d5uz0TljPaa0FqLKRFhrjAkwRihK6A/67EV73Oqsqk5Xxfz5ERFyV3BejHg2eYFGNWkKThznxZBttYUCYuMJy6kdgkAwF4OmlSbWEW+yI3Yj7983qtTHZWjlXyOrVlUTpRQH8T570Q65KzhMjolU1JC6GpEOcQZyKYhZJbeZzRmVkwUbEqUUbRUztSlTm672GinFfrzDdtj3ZVhtOMtH+AACoXSWEu+6bwh8wgaOQAKMMV4J+paUQ78OaF6dS6qSwDv3vOkywi33zwFcLtJX+7seZUFE2L+9PTe1u0Timr+9+kWpUaFs8J2jmhq+lqUtolLpGi61zO8aD+lqndWCdOg+KE1ArEKbpRKv8nuwxeYNX+fwRN26sql9pcY//If/kCdPnmy8/7/8l//CH/zBH6CU4h/8g3/A2dkZr1694u7dux+0zm8TvgWC3Q2x+xj4UMVuWIx4nrxkVIxJ7+Z8MXnGvfYdQh3ybPqC19kbQhUSqcgTs+yUSTnlcecRo3JMuyo51muJCBlHcFac8zo9JCCgzC1pkVKUBWVpGQVClibcau2z195hqnwWqdF+1ELEmztg/e/4frga5fQu56fGuJjwbPqS1GVV4oQirFIZDIY6P3ZSTIlNxL3WHQASl6LXeFgZZUhsSikloQpR6M1E55LXyShDu3LYX7ZLmUFW0itqZG7WbL0MjfIRaqz3uwp0QKADPtH3se4Zb9MzUpeSW6/ERioixDQGsaVYCvFB7e3g4/uefdX4soyZZ2LcnDK1RrpRl/TXrYNCocsQF14c6bd2MhWupQwLoLWi06vfM/O9fl7+Eqtm+xJVnYp1E7NXw+y122QKvB5K1xqimhtPXdrEykvjy9ZxK/qA94vC5izZnYC9xO7kuiLF6mi668CLFy94+PBh8/8PHjzgxYsXN8TuW4YbYvcR8CHE7iQ75VeT36JQBCpAnPA6O+KsGPK93nc4zI+IVLRI3FREajPe5MdVA/HsYmKr6S8Rx18//Tl5WKKdJgwDwiCk2+0RBIZSSga7Ax71HlG6kl9PnpBL4fvXlA+a7+gW5zqnY9r0g/4Hn59JmfD5+AlGaSIdoZiggNz5L42MvPnq0BQ87Nxjq/JpC5RZLxhUU601EduJBpwXw5WLbOlKAgzBJW7+AL2gw7icEi59XJz4aeRNNjD6gou6Qy41uLXiOEzfYsXRD7o4JZy7ESKOSMcUUjQTziJQUtLWLdr620/sPjaEakChKpUuDsrNsQin0Da+NBVi8460V/rmPO68IqW8rYkNkDBnmbGo4t2J5CboJhZvQ0+sZjGDVWQdt/VrVIC9sBMRbYTv/51PMbHv0XNWefL4LsczzwnnSZ2s3442+gNJll+j3ZhQsWaJX0O7k01tIzeooNS34nzcELuPgPcldiLCF8lztNJ+ulN8/E6kQzKX8TJ53ShYK/sERtmIoigpkjr2x6GNJgwCUIq93X0matqUM5f3XW830AHf732XUTnmZfKaUTluSqNmqvjs4acXkpbLUO/nMD3yCp0OqX/9a6XJXY4V6z33FEjVUVaIbZ67E2xxpN+uXDwzl7MVbTXTsb2gy1Y04DwfVgMZisJ5ZWvf7DKW4aXr3Qr7HGdnC0MJThyJy4gzs9GCpW3a6A0ZvAD9sMtQnVI6S2qzyk5l9pE8yc+Y2IRe0KGkRGlNanNym+PEEihDIQXi/Pukazrcjvc+6LW5gYeYYkbqUCvVUeU0uowqVev9oVBQRH5/Zqb8nr8ds79929+ft3wkWSVyKRdc6zSsc/MK2rpfS2uGN0oDoV1UzhRzUVvroYwQRBpjdfNUFfhpVldcEtHlFMosEauaZKr6tvXPL/KSOLyOc3b1bXwdid2DBw949uxZ8//Pnz/n3r1717b9bwNu7E5+h/AuH9CrTrMuI7EphSvnerlmJQetNMNy5Amjmk1X1f9YLUR5AB2Iwoh2p+Pjd/AXmGyUc793l19Nf4MV10RrwWx8fzvcWsh/HIR9BmEfK5bC+UGNP//rP18gH+8LEWFYjJocWlC0TERiU6xYr1jqwH+HiKVn2hxnJ9yKd2mbFoOgR1hoEpcRKP+FUIqlpSPuzk2cKqV42L5LP+hykp9ROst22Gcv3mVyNmZ8hbUGOuBx9z4vk0MSmzbbPYj3SPPNxNAozb3WAS+S10BJqAxlNQ15O/bxYOdqQk7JaJKBwHbY46C1j1Ga03xIa2m6tWUiqPI2+6aDrZr6DZrYxFcyZr7BxWhitOaw8OkXhSk/UBVVzveiiSeJykY++xQYn51z+mbIre071b4Vyn2817UsLEU+TyCWfpSuI2pOQ668ZUvdI1jqzfmpSlDGoY0nks7N+4d4VVBpX+LcCFGzfrfZhv1dBfhW2jVla4E0yeh137/K8D74OhK7f/yP/zH/5t/8G/7JP/kn/PSnP2Vra+umDPstxA2x+wh4/w/zzKTUiiV3BS4SpkUC1kEBBSVj54cGgiAgjCJa7TYWy/fvfEZqE54lL72VgoATi0MIRpr23RaP2g94Mn2KU5pABZRSMi58r9evRk9omYj77TvsRrOweaPMtXop1YqmVmbBMLljOkzLtDJrVTgsTryxcidok9qMUTGhbVoYbWhPIj7tPuA0H+JwbAV9tqL+ipedUoqdaIudaNHJfqomV1ZWYxPxae8hmc1xOCIdYpThufriwuf1wy6f6oecFUNSm9HRIduRn+R9OnnFVGW0iemYFiLCeTEml5KH7Tve7kRr8iwjy3MCY4h1SOIyBEcn8pO+vr+uYPcmTuyjolHJ3uXjrQRMOZt+dVXX/bL5bxGgrqln7n3w9vCcB5+2UEuDHGL15j4yUVBc9hUiXpEz0pw3bRTt7uKwkdRDF5dkv4pVWFFo4y1PxFVlXFFIsWZqVvjgqdgPwXX02L0Lsfv93/99/uzP/ozj42MePHjAH//xH1MU3ungj/7oj/i93/s9/vRP/5TPPvuMTqfDf/gP/+GD1vdtg+JmeOIGG/C+pdhQQsQKo2KMxVbb8OHwKLjV2uVWd5+n6QtUNTnqEEqx7EbbDIIeW2GftmlzmB2R2JS2aXG7dcAvRn8NwF68S6hDXqWHTMoJkzJFK+0nN9GUzvLryVNKsdxe47V2HagvdvvxDq/To8auRCsfGVbmJUYZAh3S0jEtE6//LhUaVfHLwqYy9mXPuW32F25LbMa4nBAzi6JSShEScDR8y/jVOUf5CSk5OjKAJrAKlQulLnEGxsXQWygoQ9fGPNPpgvN9/Xftsm+M+Vb0j3z1uOI5VK7KWp2D2fBeCUuvgMmXT0JExJfzFwYaAFSjsF1GuDZBaWYKWyWmiXjnALVmBuIKWwQHbh0JFoXLNZX7T+XV6Z/zVRA759yXrtj9yZ/8yYX3K6X4t//2337Qmm7w9ccNsfsIuEopNs/zhaSGyWTiTS9vhdi+L0VqrXHWViVVxVRn7Lf3aYftiphNiXTI7fge+/FecxFZR3Zqe4/6/n7Q4+nkBePyuS/V2pzYxAQ6QIvmefKK/Xh3bZLDu8JP1HpD3XqNThyxjilcSVKe0TItIh0iCEYH7EfbCyXfeiiiH16eFXtVXNc23geZzXDOkeUZNrGMKqNnEwQEnZB+Z5ft7T2GbkpbhzgnWAStFF3T4mHrjrdbcQ4p3YLZaVEUZFnGZDJp/v6Lv/iLlQD15Qik+u/l237XCKFCIdaslGMbCIiSy+1GgvLddmysL2cC/e2uf76ozeXN5UXVLWaOKzx+Ef3tbvUDY83gQeBw+UXDDYKqlyh1ObX6sRK4tXMWXqGj4ZGqUt8+HJ74Le/zq1LsPhTvqtjd4MPxTXyfLOPmHfMRME8YRKTJTK3/SZKEMAzp9/tsbW1x69Ytut0uWmueTl+QT17glGua7EMVEOuYUiznxdCrc++oUi2v6beTpzydvsSJreKrChKXMggHBMpQupJJmTD4AFsTEeE0P+dFckhqsyozdRcjcBycczZJMGgs3m8u1hGPu/dJXc5Jfgbi1aiyKkvvRzuNuncRMuufn9qMtmmxE22tVdquC1chh9ZahsMh5+fnDIdDzrIhec9hrCaOIvb294kiP+08LVO0CmmhiVzEsBhXkWSQ2gJx8IvyC+95F25xN96/0PB0NBqtuMvPO+DX/5RlSZqmjEajhezMmhCKyEok0vw/1lqKoiBNvXLoVZlv5kVS2RDR82U91fAapYAoRwqDcpsuobIha/UCaN8/u3XQQWhX6p74hIdCbzD99YbAOpCGWKFASrU2M3XtSkXo9tqbH1BzunWHowQTSeMvVytlNseT0qXdi6xfkbhL+us+EF8Fsfs69tjd4BKoG2J3gyWICNPplOl0yhdffMHnn39OlmULcVv37t2j3W5vfPOUrmhyREWE88k57a3qoisWK+/n/DlP7M6KIUf5iSdNSGMN4sQxLidsVVYml2oEIozLCaf5EBC2oy36Qbc5tqPsLU8mLwh1SMvECMJhekwmGbnOOdA+GqyN7y9LXIZC87jzgJ7pcJi9ZWpTIh3yoH2XW/Hu2uOZx1k+5LeT5yCC1prTYsTL5A170TaTKm6rbWJuV1mxHwPOOcbjMefn55yfnzMajQAaIv/48WNa3Ta/njxlfDr2vXNVekcdH5ZT0DUtlPFDJWmZU7qSw/KUREaecIvwLD3kuDjn7/a+Q2yu3mD/LlmZ86jJ2zzxK4qC6XRKkiQkScIvf/lLiqJoVOt5QnhVhfCrhp9WjRFtISwqbqMWG3BC65v2N5K7d4QAkU8bWSE5oatishYHA3RkFxMqavIZCCiLEuVTE5Tfpiv1hrLq+yjXntTBrKRab8VEgs3w6uHS7IVzizF88j52J98AXJeP3Q2xu8G74uYd855wzjGZTBaUuLIs6XQ6lGXJ3t4e9+7duzQ6Zhm9oMdRfgIs/nKoL4Rdc8Ev6wswT4SOsmMfN2YiirKc85T3OaqFFL7vLuhs3J4Tx6/HTznJz5oesdfpEVvhgM/6jwHh2fQ1sYmbCVyFomViTjlvzHXn1xfrkMPsmDvtW9xq7bEf7zaDFOsSGpaJXelKnkyeE+mgKSGLCGfFiM8nX3AQ7dHSEYUr+c30OQPbvZaEkMlkwtnZWaPGWWvp9XpsbW01WZHryMq91gF/rc+qRImSUnx0253WPofZyexY0UQq5KQc4rAEOphFm+mQaZnwPDnku70HH3wsl6EmhOve19PpFGstP/zhDxduX87InCeF0+l05bb5NoZNCqFzjjzPGY/Hzf3XTQgVqlLd9IwwLT4ACS3kGtalTohiJVXiIljtVbpNypWxUM4u2Sp0F8aOKQOq9qcTz0lN6HCFQtziVPx0khK3LiD5a3zulGZjn5xSfv/OaoxxC48REcqyRBNWquLHxzdVsbNVK84Nvjx8C9xObojdVeGc4+nTpwyHQ0YjbzvS7XYZDAYcHBzw3e9+l6jK5/zFL37B1tbWO5M6gL14h+fJK3JXEFZRWCJCIQWDcEDnArJ1EeaJUOFKdGUnEmhD6az3PlMKcZZSSj7rfroxbUFEeJO+5W1+tpBy4UnUkFfJG7bCnu+Xq7ZRivdqK12Jxa39ba7x9iXzlit1OXdiE0IVXFhWPS9GOJGFvkC/3xwtGodvZg5VgBHDSX5GC997OLU+aUMrzSDorrV0ERHSNG2UuLq0WhP5g4MDPvvss0ud4uvXYSvqc8ttk5ocowydoMVOuEU7aDG2KalNm2N1OKYuRaNXos1iHXFcnPPY3W28/iIVfG1KCu+SkTmPmhAuq4M1IcyyjKdPnza3zZP0ZYVwmRzO/33pF+dlw7BzvXELTyq193q7Cko/IHNhFtfCLmTO0209Nq1Xh4LNFona+DxhZ29xanz29lEELXClw5VzypqSjTqfAEoJYjWuUOhg9lilFePhlJ3B+13L3gffVGIH347S4A2+XNwQuyui/nDdv3+ffr9/oTz+IU35Rhl+MPg+n49/w7RMEA2FlOxE23yn+/i9trm8pn7QY2KnBAT0gx6pzchchnXeSPf7/e+yG20Dvl/tKHvLxCa0dIwN/DZepUdEOlxR3SIdcZgeMQh61IWZpMwYlmPqLhxByE1JanPvy1ahFEtnLlc1szl/M/otmcvQaAThefKaR5177JjBqmIndmVUPXN5dZvCzUkhtYlvZkp+NX7KsJw0dSStFJ907tFT7YbEnZ+fk6ZpU1bf2dnh8ePH/PznP+ezzz6j17u8FzGzOW+yE05zX5rdjnwpeps+D5bUtoPWDr8dvyB3BQEBzvmey0CZxiS5gQiZLfjl5CWCNL2Ze9GA7bDL5q/frzfmCeEyptMpeZ7zgx/8YOW+eUK43EM4Ho9XFML599Ey+dveH7Bzq7/RtFQp1qhyApFd7LGr/xTlSZyS2fOs8YrfReqesFhCveS7/lIqMNczJyKIgMsMKnAoIwukrlbkdeUT58mdPxa14d2lAFeVjcVqrJ0NWEzGKa+eH7Hzg48zdb8O31S7k+vaxg2uBgUrlj/fRNwQuytCKcWjR4+u/NgPKfG1TMwPB3+b1KX8v0/+J//n/R9+cPP//JoOWvu8yY4bM+S2adHSMZnLuNO63ZC682LEL4a/QcT5fjU5Z7pfcJgck7tixTwXvClv4QpaQQutDIUrGJZjtNLo2r8OjcVyVow40LtopXDiKKTkUcu7oIsIv5k8o3AFnbnysxPHF9OXtLqrZSPfx7cEmVWRArX0dlcwCTJMOaGtItI8I0szkizhtXvN1qTNXm+Hra0t7t+/T6vVWlsSvgoym/Or8TOsCLH29i1n+ZgRQ+7KTnPM4zLhNB95X75wQFIpiVas985DL5hLA0xshqCIdEDqckZlQimOk2LMTthl2vakcHPe7TcPF31RzxPCdvvqrQt1iXCe9JWpJ37KS1Arz3FOODo85uUXbxpC+J2//ZBABXPPqfrQHEim0Xq+ZOyNe1U1QSuiqp8/anFeQbEU6zV357V97yukNCgcBMK6dAsdgCurH2hus12JCCy2A6umb9CWH24DcoMbfCx8G96aN8TuinjX5InrsNFomzY6U9c20VmvqWVi/tbgM349fuIVrer+O60DHna8C7kVyy9Hv8UoRWBmJGpoFU+mz2kZP6UbLpGl0nkCEirDo849fn7+K5xYjNI48QQjJsRZjTWWUTmucmLhYeeZYB1rAAAgAElEQVQuO5FPv3idHvMqPcKgKVxJO2gRKINWPk3jbX62co77QZeWiUltTlypiZEOsWKJVdRkutaTytNkyrRIyV/6id04jmm1Wux197BG2Iu2+KS7GLdTuNKXyasBl6viKDvFitCeO5dtEzMEzpjiRHg+fcNJPsJUJLh0EyId8knnHsoJe8UWfzN5SmFLQhNQiiMpUsY2p6vbvEjfUkhBV7dpG99LKCIUIRxl59xu7Vx5vb+LUEo15GweUlokLKrHLD5HK8XB7l12+wde/dOOIAqWjE79dKgox998/jeMh1P/XK35u3/ve7TC2JMe5alUoBd7BQWwmVqyV/EDBypYf50RagFww3VrqedtQXnXrCV18/fXliY2Z+1UrCu+XsMQ31S7kxvc4H1wQ+w+ArTWH0zsrhvLF7V+0OXvbf2AqU2wYmmb1kIc1XkxohS7QETAf5E5hLZpcVYMMaIbJajuBXzceeCtOOId7rRv8Wz6ClvZqnSDDrpUJC6hG7Y4iHfZjbbpBR0CHVRWLM95lR5ROl9aHZcJE5uwG201iQ+Zy1eOUSvNd7uPeDJ5zrickkvJtEgoncWVCa/Gr7FpiSjBtAI6tCiCkocH9xsyXtS9gKXllBGPOv4LwYrl+fQNb/NzqpQitsIeTsuVXuvTfLRaQgVCDFPJOM9HnORDOmamCkY6JLE5R9kZ96JdbsU7WBG+SF5xnA0pncOKA6VxSrCupBTHUKYMaGOUJpUSY+GkHLMvWytq3w0uhxLDX/3P/8UP/6+/5e065qW0wqDQhKH2hDAo8ZFvq9Da8Hd++LdmaQ26RIeVmlf9e15V9bFbvkya5gl/9f//0q+nUiSjKOLRd+7S7XWqQQbfl1rmjjyxdPrRqvqguMSTbkbQNt4//3YXhc2qQQ0lOOHSCddvcr/bDb790Del2Busw3UodtcBK5aj9ISj/ITT/oSj/IS2tJvhAqXUxsnX0tmNDggK30v3oHOHF9NDYPZlcLd1wMGclch+vMNpfk7LtJovmcxmgA9X3493F7zyzosxR9kJHd0iUSlKaUIFVhznxYj9aAfrLN2oxdnSORYRbFbSG8W8TU44ZQQWIh2gWpq8Zen1+wzCLrdbe5hM8f8d/7V/njiG5bTKglWUzpJLyd+MvuB7/Yc8mbziLB81xMtn3Y45jxPcFV7rTX1uNUl4mw8J9eLAgxOHUYrTYsRBuEWoAm7HO0xsRqynOIFxmZJKTmJzykoZReDEjRkEHVom8uqLsJIRfIOrI00yVBb5aDDtfK+crXxEFuD7zjZBaaneCwod0sh68/+uMT/U0ev3+PH/83+DU02SSFEUFGnBWTrGBJqyLBmejcmy3MdIKbh7/xY7uwNQijTJOHx5zHSSLgyVDIdDgiBgOBwShiGxhIRtvd5vbr4EPHfMYmE9nd1wHm6I3aX4OnyH3OCbiRti9xHwdSB2hSv4y/NfMi0TjDKUxvK0eMXZ2f9m781i5MjPa8/ff4mI3DOrisXiUmRz6Y2txbKWe69n5s6MnwwIcD8ZsPxiA4YMPUiAngzpwTAMw4AeDRiC4QcbEGDAkB78IGGAEaC5GlwPLFmSZclq9cpmc2eRteYe23+Zh4hM1s4iWexms+sAbHRVZUb+IzIy4uT5vu+cIR9vv7hlstJ5RzcfFKbAwFw4Q0VGpZXBzgui946GrhURZ9Ecg3wIQF3XSF3OUrKCFopO2KIdNIlUSOay6bCF92CEpaarNHV9y7ZX0/UiTkxpIhuSuRwlFBKB9Y7UZoUaGM5yw15leXl5OtyQpinVapVqu46tCxajU+hNFhjGFUbHLzfPE6iAQT4AK7idrGKdJfWGSGgiFaKEpK2bDPIxV4d36OXDLWqaEIKarrAmHSMX02b/nNaZsMlGNtyhgOZYqoQYXyRzTN6PjWzI2KYIIHeWhljnbO0YicsZ25RIhixnPTwFKZ1OElMM4BhnGdqYjq7RpyiV6SNS95gQ4FTxby9YCXofp919uMWDaIcQhfmPlJIwDKdT+Jsx29llIMGVLRg64NTJyo4pY2MMWZZx586d6e/Onj9FZ7YN3pc+hBLv4faNZaxxj5VS8kFdGz9sxG6CD+u6P4x4uhoIHh1HxO4J4GkgdjfGS4xNTKUkErL0QhuZMbfGS5xvnAEKVe+N/rv08+G0r+Zesko7aFJXNUZ2TCTD6T55WXinzUaFNUIoA+aiGXJneLN/haEZT9cgheBC/QwvNS9weXiNuFTqcnICq3ixeW7HRSv3Zjqx2g4adPMBmTPgPbkz9NIBta7i3/s/I7Yp1wd3CBsRJxfOcKJ5DCUUS/EKw3G+hdRB0buU+pyBHTOr2myYAUY5QhGR+hzpIcOQG8tCZZZIBQResZxs7JgAnkAAYxs/8P04Hs3Sy0fENp0OnRT9jYIONSJdLfrrUKykPXJnCaWeqjsb+QCZFHFi3XxE7g1jm+KgSA+hUOoMDhB4AQqF9R6rYCZo7js88WFUNJ5KPChmbPNDndhiWbJvCdQ/3La3opxqlYoo2mlKba1FKcWpU5v7SYsvAyIopo9M7kjGGc1Ga0oKHzWlJMsy0jRlMBhs8SB8kuffB309PsKHBOKoFPuRw0EJ20GyYp8kvC8SHnY093sIVcDdZJVz9aIP7uZ4iX4+nJK3yfO7+YDF6gmUkKVVSQHpBC9Wz+3IkH13eIORGZdKX7Gd3Bt+3btcDH94qOsKx6JZAqlYXrlLuEvPWSdo0s+GuKzIUTVpSu5znPYopTmrFzh5cYFV3+fXd97GthUxhuvZXZa7XV5pncd6t89kk8f5whJkKV9DW8nxygxLscE6h8WVZd8RUqhCYRNssUrZAiGQPNgYV0vNmeoCa1mPoRnjgU7QoC40ygmORW3Wsz6jPCZzhkgVySO5M7R1g0gEbORDxiZhYMZIoVAonDdFhJNwaCRBmR8bSEkgiv69MIf5cKei6LxnPRuwmg/JnaWmAo5HbZr60Uyw4egGCoAVZRzYLnD3NQFvJGKvPNrtELukURwidpKqcuo1K0khinotoF6r73zyHtjLgzBJEtI05datW9PfPUxKyeafD2pKffTF5QgfJRwRuyeAD1qxm3iZiU0TqxPzBIHAcv9b9d2SAO70o9Msp2t8dubjxTBDvIL1FotnPetRi6oEZYRVYrOij26zWTGeQT4sS6mSpm6Qupyro9vUfYV+NOT66A7HwhnMOLufoTrsMZjL8aHAa/A1oLT4iGTEshpirWQ96+OdZ2SL4QiAUR7zphCcr59iKV7ecTH3vtj/hq4S2xSHR5bGElpoYjcuy5mC1Oasp32qKqSmK0gkxtktE4sTv7iG3JsIOe9Zite4m2zgy0b4TlDnbH2eSIXc2riFxVJRIRcap3i9e7Xw47OAELSCOjVZmUaN3ct6gCh65QQlGfV473ACWrqK8566quDxHI/a3I2HO9Q67z0341V6+ZiqCglkQO4sV8crLFZmmQ0fPiP46MZZwOcKocwef9tsWSJwqSpiwXY5dJPD6T247GC5r4+CJ3WtmqSUbEetVmN1dZUXXnhh17U453b4Dz5OSonWevr8SqXyRFJKjvDs4Fm4jB0RuyeAwyZ2D/ttUyCo6Sqpze7bkZR2BMabaZ6rLbNntycZQFG6TWzKm/33WM96hFJjjCGNDG+Mr/BeeouztVOcry+SuWw6kTdBYpOCCAlVKmgCax39bEjX9RHO8eult8HDvGlxoj7PmTNnWKyc5bX+FRKbkLkM64qbnvOejo6IZMT10d1iPVGhvulSPTTOcme8wtnqCRpBnWGpIE588mKXciycoaIixiYpj21BQnNvChkegReF154WioGNOVmbZzZo8Vb/emnnogmUwgONPCLax/bk1niFu8k6VV1BiWJaum9GvDPIeKX93PT9BWjoKs/VT3BjvEJVhWhZ2Lt458EV5C11hoaukrgMjycoj69F4HEEUtPUVQKhSGzOfNjm7i7rGtmUfh5TV/fJeCg0ykvuJBu0g9rRoMVjwCcaEdj7yp0T+FztLKeW5A7hUZEvlblyDKF8aNHr+mTX+36S8gd5EO4XW7ffNvdSCEejEVmWcevWLYwxGGN2JYQHUQiP4r2O8GHAEbF7AjjMUuyEJAohGJmYu/EKY5tQ11VOVo/vaMafPOe52ine7F9BejEtmzrnQAnO1opeGokkkuEOJQqKFIdABWzkPaoypG9GZC5HeIFGkTtT9LLlI1pBk5GJsdJSLdWtxBb+eMYZnLEs95ZJoiLKDFnEmc3PHsPhMc5ycvYUWij+s/sOoQwwzjIqI7RA4LxnNesxFxVEbGjGCH8/QQJAK4W1lqV4lZdaz3EzvstaWmSxSiE4VTnOqWrRXF5VEYHQOFGUOwWSigxJXV5Oo2osjpqqYKzhRr6C8RA7w8imhDbg5dYZunZ5z/cuc4bltEtd30/TEEJQ1RVGeUw3G+64wXXCBnfidbTUW/bNeleUX0VBOBuqSu4MTjgCoUlthhfQUIW6l3rH6crclmSPzejnMVLszOBVokj4iG1GQz98JN5HGUJ5VOCnhMwZiUsO0o4tin62iUKHL9VlOfkFUvvSG+4Iu2G/lBKAtbU1Xn755R1K3UFSSjYTxd1SSvYigtZasixDa/3IhPCoteH9x5Fid4RdcZiK3WRbS/Ey7wyu4SlUpbWsy634Lq+0nudYtNN4di6a4fnGc1wd38K4rOjBEvBS4zwzYXu67TO1k1weXkd6OSUSzjuMt7RkHYPF4KYlVTtZEx7rLHeSFbr5AOssXTuglw4IUkmqDF6CkoKGbiA6AmdjtNDkLgcFqcuRQuK8ZSPr0w6ajG2CForYpggh78cZUdzw+vmo9HdLdyQweV9k0w7MCC0V5+unOVM9gfUWLfUWBUoIwZnoOKtijcRmeO/RUuEpFMBm0JgSzKV4A4sjd668R0usd1wbLdPA7flexzYtMzN3XimUVPTyERNanjtLajMQgoXKDPeSdZRUqDK9wzjLc7XjWO/p5UMqKiRS9w2XPZ7ZoMls0ERLRUvXCHdRYrecW4/wl/1g/KQs/NHrZ5LasV24lRqk8hTi8AOOx8Qbb7eHiSd7s3m/36+nKd7rMFNKNvcQ5nlOlmW88cYbGGP2jK3bjRgCjEYjZmdnP3KfoyMcDo6I3RPAYRO7xKZcHlxDlYrNBNZb3uy/y2/NfZrc54xNUpbiilLrieo8xytzDM2YaxvXOFE5zvHK3JbtH4/mSGzG7bgo2E1SkM7VF0lMysCOMc5s8WGb9PANzRjvHcN4SOA0siJwwpFEDiFUMa0pFEZRjhcUJVHrHbl29PJhmYzkGeQj2qWf3UTt23xJmxzP3DmUt1vjlsq/W++IVITeRGi0VGgU1lvujFdZSjaw3jETNpiTdWZGFToLrWItXtIOmkVPXXmchyZh7DKEF4RKF6sSHuMd3XwE+2QG7+4EVsB5jyqP0TIjbqy+zdAUZtGhCJivtKjIEI+nGTRpRzVqOuJCbYHXBwmpyxFCFnYUQF1VeLFxivoBVbZWUGU1H+yyLocAKurgqRqJzbk6XuPOeINePaG3dplz1TnO1Ga3qI7PLvwOUjeFKJS8wrR3ny0Uw8z7//0J4aNA7A77NfdKKdmMXq/Hpz71qR3r2E4EJz/HcUye59y5c4e/+qu/otfrsbKywqc//WmUUszOzjI7O8vf//3fU6/vPsTy/e9/n69+9atYa/niF7/I17/+9S1//9a3vsWf/umfcvr0aQC+8pWv8MUvfvExj8azA4E/moo9wu44bGK3kqzj8ATbep6UUKQ24+cbvy4VrqIZp6oqfKz9fJHyICStoEHFh7vGBAkheK5+ipPV+dLyBFpBk0BqNrI+S8ky1licdWTeYZ3DZTkoARI0mnqlRl3XStPeEUMTU5UhrlT14tKPzWHJfTmwsKlEnLuc2/EKZ2onqKkK67ZffJNGFb1vXmDwRX+Sn5QfQ1KVTAcnfJmGEQjF8W0KpvWO13s3pmqfFIKVpMddt47Es1hbIBAhy+k6VR0VfW3eF+SpNPatqYj7d16BLr3iYpnt+V7Xyxi03FmCTaVuX07lzoZN3vbXWPMjfK7QShGiyb3lXtrjmG/yic45QqEKw1mgE9b5WPMsN5IVUlv0BdZUyJnK/IFJHUBdRbRUlb6NqcqgzPi1pD7nVDQz7Vt8EDJneK1/h418hPIQ+sLv7I3hXUY251JzAeMdG/mYkckIpWImrFF7zJi8p0kVfFArotRgHzT86gvytte23AOI4REejKfhfDkIIXzppZf47d/+beI45tVXX+Xf/u3fyPOcbrfL2tranr2H1lq+/OUv84Mf/IDFxUU+97nP8eqrr/LKK69sedzv//7v881vfvNQ9+tZwgd/ljw+jojdE8BhE7vM53v+PXYJeW6o69r0dWOX8svuW/yX2U9OByO2rym2CbfG99jI+wRCc6oyz7FwhtFoxN3lpWJKddAn6eTYmsBrTyA13jukVmihi+lNwdQrz1OQISUkFV0hkgEjExcRXd6ghcJhUSh8WcJ0uNKWRbCadTnfOE1vY4R1CVporLekpVyhKErADV0ry36ghS4HDfQ0Au1k9diWY7Sa9Ojloy2DAlUdspb06bVifrHxLviibJyYogQMnnbQYD4MWe+N7kdJbcN+1mJSSC40TvDO4Da5M4RSY31R1j5RmSmsZHxCXk7FTtTYUGhSlxPbnHtJl7O1rfvTCRu0gjqpK86Lyh4ee/tBCMHZ2hyr2YDVbEDiDBWpeS6apx3unkYCYJyjl4/pm5RAKjKb083H1FSIwxFTJH1IIbiTdJkP69zNBljv0VLSt47lbMhipc181HyoNT/bKHJXdVR8RosvaRSTzymP4WH3YHwUFLv3G4dx/TfGTHsGgyBgfn6e+fldDKhL/PSnP+X555/nwoULAHzhC1/gu9/97g5id4RnH0fE7gngMLNihRDUZXVXta2YavXU1X0POiEEoQhIbcZyssbp2sL095M19fIh/9l9i9wavC1KA7e7dwliyQnTod1qc/r0aS61LoGEW+N7XB3dKox4haBKBEIUgfOqvkl5s3iKi3YRZC9pBnUauk7qUkIZsJ71cN7hREHqAqFpBU2MMwzyMaeq83yq8wL/sfE2IxszUccKUuhQQhFPc2IFI5MwMDGB1DR0jXO1YzvUpnvpRhErtulm0s/HjG2K9xDJglQlLgMkL7fOUFEhoQzoZUW/nsWi2ZrWgYCqC/d9r9tBnY+1nmM57TI0MRUZcb6+QDuos5EPi7I27JhAlSWJXc8GO4gdFEMj1YdQvXa7mUohOR61mQ9bRe/mA262ic15d7RC5ixaSByepaSHdZ66irZ4/WmhSDC8PVpmJqxTUZttYjy3kx5NXXmoku/TigeVSf0BrerwApPARreHVIJOZ6Z87rNHgj4KxO5x99EY81C2LLdv3+bMmTPTnxcXF/nJT36y43H//M//zL/8y7/w4osv8td//ddbnnOEI4PijxwexqD4MIndjG4RyoDM5wTo6fYTmyKFmPrJbX9ezww5zcK0r2NjY4Nur8t78i6GwuYk0AG1sIJSmqyec6p9hvlodsu2nquf4mztJOtZj1/dfJ2oEdKo1NC5vj+5B1D23oUqIBDBprUACCIVUlc1FJJu3GW21kaJwnE+xRdGxkA7bPLf53+Ta6M7XB0ukbgMJSWRCEitmU7wesB6gRCKqqwSyJDLw9vk3vBcfWH6+s5vTbF03jM0caE4CaZktKoiRiZmaBJaQdHD0gxqhXlw2id35n5/u4CmqtJ0D552q+mIc3phx+8lEspBlB2ee1A67B1smm5sM3JnCKR+6DLnJIrsQbgRb2C9p6HvT2JHQtH1Cbk3O3oirXcY5wi3TVzL0itwI485+QwQOxC4fI8+Ow/OPMwNXpDERdZruzn74IcfAj4Ixe5Zx2ERu72mfPd6ze3Yvobf/d3f5Q/+4A+Iooi/+7u/44/+6I/44Q9/+FjrPMLThyNi9wRw2MROIPiNzsu83r9c+K+Vm67rGmqqXt2HLw0+B6MeP7/8c5IkwTlHo9Fg9tQxIiq0N5UlJ5BOcide2UHsJuuYizrMJ23OzJ+h3W4zMjFv9K9Mo8K892ihaerGlrLlpOR6prrAFXeLNM9RTk6HHKx34D0VGXF5cBvnPceiFhcap6mpCpeHt6nrCstpd0pCrC9sJZQozItHNqEZ1tBCcn28zIkyEgxgLmpyfbQyLUsbb8p1gfBsUfi01GxkQ05ViyETKQSXWmd4vXt9WvrEFykYF+on6K7fe+T3uhlU0UgUAuMdQbkOXyatSwTHK/tn0KbOcGW4zNCmZfy8p6krXKzPP3Aq9mGQ2JyhSalvI42toMqGiUmsobrJENt4h9pHVZRCYA4sZT39cKb4zKuiqwAolDqbHcTuZCeeZUXrqBR7MDwssVtcXOTmzZvTn2/durUtJg7m5u4Pz/3Jn/wJX/va1x57nc8SNtsOfZhxROyeAJ6E3UlN1/jszCcYmBGpy6iqiKqs8OO1X5JkSVFSzQ3WGpACGUiOR3MsXJqnWq1y7do1oiiiPttEbdzb9cIqebibbV1X+ezMx+ibIanNqaiQ2KS8M7xOaguzXOcdmTPMRW1mwhaX1Hn+c/0djHQkNivKdx4CGfFm/0a5LsGdZI12UONS8yze3+JeskFiCxIrhUSU06CpN0XjufdsZEPaQR3wdPMhC6oYoliozLAUF8+Pyn4+6z3CewIjtxwL6yzDPOG13nW0UCxUOswEdX5z9iKraZ9BHhOpgPmoTV1X6Im9feweBCUkJ2WLhIzMWZy3CCQOR0WGNIMqUSq4sXyD0Wi0a/D6lXydDEe9VNG894xMyuXhMq80Tx7aDXRCpLdvr6Er1FXI2GZoJaZ9lrl3nIjaWL+7/Yn1bgdJ/HBD4K3AWL/ldx8GvN8K2keB2MHjk/OHJXaf+9znuHz5MlevXuX06dN8+9vf5p/+6Z+2PGZpaYmTJ08C8L3vfY9Lly491hqfRYijUuwRdsOTMCiG0q9sbIl7Q+72bjMYDPARZPMWqSRhNQRZ3ODP1xd5rn5qx/bqqvBqct7tiJky3jK7S6boXuuZ/NwOmlCWoVpBg0iF3BzfY2CKKdSztZOcqM4hhKCha/xm60V+dveXzB+fIZIB1sG18T1qm1RE7z3dbMTlwW1yZ0sbDjG1WilsUyDYdPOMbUbuLA21dWoslAGf6Jzj2vAe69kA8GghqamQkbs/mJJbw0o6oBFUMd7h8SwnXRYqHV5qni5UvEePUd0VLVXlrGujWw3ujNYZZTE684j+kEE64Ha9T6fTodPpTI1UJ8apfZOwrBOUgbUyLq5w7pesaoFfGdDUFfI8Z2VlhTAMCYKAMAzRWj/UjSeSCuELo+jNvXhSCI6FTQSebjbGCE8oFRcqx1iszXA77rKejanp+32gic0JhaYVHPLBfCrw+ITlgyhVfhSI1vuJD6LHTmvNN7/5TX7nd34Hay1//Md/zMc+9jH+/M//nM9+9rO8+uqr/M3f/A3f+9730FozOzvLt771rcda4xGeThwRuyeAw1DsvPcMh0PiOOby5cvEcYz3nlarRavV4uzZszSbTaQsor+WkhX6+ZCKijhZmacVbM36nKxJS83Z2gmujm8TycICxXpXmPgKzanK8cfet07YpBPuPfGopaaWBrzYPAvAv629uWO4QZRlvOvje7R1g2ZQZ5CPGJgxCkla1qMLGxVPqHRhQeINqctL5e4+qiriUvtskdbgPbFN+XX3GlYWyRfWO1bSPqHUdDY9t8jT7TIXtZiPdpLeR32vnXMMBgNWVlbo9/twd4VaGHKqJHHts23CMJyuIcuyHTeKpaSHi9enah0UZXhrHQMTUxENKq74iA+Hw6lfVpZlGHM/y1RKuUMN3O3fsbDOcjakoUI8ENucxBkk8Kn2aWyac3n5XT5x/uKU/J2udkAI1rMRExfemgo5W51BH0WW7Ylnuefto6DYHcY+OuceSrED+PznP8/nP//5Lb/7y7/8y+n/f+Mb3+Ab3/jGY63rWcezcFU6InZPAA97s/feE8cxvV5v+s9aS71ex3vP/Pw8CwsLe37IKyrifH3xwGs6Vz+N9/DO8AaJzcuJSMmZ6sIOFe9x9+0g20htXlqe7Hxc7gsPuIkfn5Kafj7EewGiMDsOpEYLXap5nkgFe0ZpTfrsIhXwG+3z/ORuDyUlAYqKCreQuskaAqFYitd3JXYHRZqmdLvd6T9rLc1msxiOmZnh0qVLD30jCOTOb/NCSrSUhCJktt5hNqxz8+ZNzp07t2es0W6RSpuVwQkZzE3OMILbIcRBaSsoBBGK4WDEWV8lTzP6vd4WQni2OsOJqEXmDEpIqo84MGGcYy2LWc/HZGlGKoqpcPWMk4T3A8860Xq/8UEMTxzhCBMcnTVPAA8iP0mS0O/3pyQuTVOq1Srtdptjx45x8eLFqYHla6+9RrPZfOwP+OY1CSFInUGiaQVhaVciWMt6/Hzjbf7L7KV9Cd6DiF3mcm7Ha9xLukjgZHWOk5XZ6TTr9uPT1FVGNiEUW2/41rkyveG+lUtDV1FCsZb2yK1nttokdhnGW5SQ1HWFuQeUkyeoqohmrPn0zPOMTEI/f2/33kMhyZzZZQu7v9fOOfr9/pTEjUYjwjCk0+kwOzvL+fPnp2rcvXv3GAwGj3QTaOtq0Re5LevXOItCHLjU+TCh65mz/GzjJhvZmNxZyugQ1nxO4g2zxrC8vLyFIE5wUGUwCHb68mXO8uZgldjmhFKRWsOasrwzXOXFxtwOu5gPM571qdEjxe5gOCJ2HwyOeuyOsCs23+zzPN+ixMVxTBiGtNtt2u02Z86c2feGeliDGJu3E9uU2/EKlU3+dwCRDBjkY1bTHscrO/NnJ9vZD7HN+Pf1d0hsVmavwpv9m9yOV/nMzAsEcmdv13P1BX7VfW9LZJorkx9OVGZJXEaN+8doYsirDBOyk/0AACAASURBVLTDOi1fLyLPPIxdyonq7mvf75hUVIgURVl6O0nIvWE+2JssZlnG3bt36Xa7U7W12WzS6XS4ePEijUZjyz4778mcOXC6w14IpOJifb70ljNIUWTYCiF4oX58S6nTe896NmYp6ZM5SyuIOBG1qOuHG2BYz8YMTOH319jknl+kjqTYVpUXX3xx1+ceRBncTgaFEIRhSDcSjLWgrjROKZzzBMaxOh7QQLPY6DxTZOFZNgw+InYHwxGxe/8hAPkMnJpHZ80hwlpLv99neXmZ9fV1/vVf/xWt9ZTEnTx5kmq1+lAf+MMkdpOBjl42hLLRfvtjBLCadvcldvut5/LgNonNqW7q+wqlpp/H3Bgtc7FZDHRs3sZc1OKF5mmuDJfISoLmBZytHWexOsd/dK8wMgmRDPAUimA7aNAbdUlsViY6eFKbMxe1mN2nv2/7vkyghORMbY6ro2VqKpr2iGXOIBCcqhYWMLk13NxYZq3fJR2NSVb71KIK8/PzzM3NbVFbt8N5z43RGjfG6xhfmPzWMoHCMsgTGnqnBc2DMBPW+aQKWctHxDanqgLmwgbRNquTq+N1lrIBQUme7yVD7iYDXmmeYCY8+BDDwCQkNqe2rZwqhEABfbX3VPXDKIMTWGvJ8px/7y3RcYBzWGtJs5SxNWS9Hr9c3+Du8P6w0oQMaq2nAyMHVQaPcITDwGEQO2vtQw1PHOEIExwRu0fEpPm91+vR7/fp94t801arRaVSoV6v85nPfOaxP9xPQrHbf033M1wfdj3WW5aT7q5pApHS3IrXuNg8tes2FmvzLFRm6OYjvPe0g9rUsPizsy9wpyztFo89wcnqHD+6/hPaCw16+YhQal5onuJkde6BfYKbsXkdZ2vzeO+5Ga+Voxke5SUnTZ0b715lpb/Bcs0gQ00QhAQzAVm1wYXGSS6ceLB7+9v9Je7EXWo6IkKzlo24kQ1RwPraNWoq4JXOKdoPOS0aqYBTqrPn31PluZMOaG4ijoEsMmzfGa3wueDMA1MnJgilxrHHTUsI3CETJaUUgSjyNZvll4WRyViRllhogkqFzFtOnpjjY81jVHWAtRZjTNEX+BDK4ITs7UYKrbVkWYbWes9excOC9/6Jv8b213u/Fbv3c/8+CBwpdh9eHJViP2JYW1tjaWmJfr8/Nfxtt9ssLi7SarWmF6vRaPTIfVPb8SSI3WzYKhS8bZYn3ns8nnZQ5/LgNiOT0AxqnKrOTY1m91uPK5+/6+sjyUtj4L2OSyA181F7x+9DGXCufoJz9RNbf28En+ycf8CeHxzee9p5SD6MWBt0ScZxoTx2Ambn5liegTnYQlxXk4zL6Rpn3KldhxkmGJqUpaRHQ1cQQrCRjRjmKZGQZN4SSkXuHb9Yv8l/PXZ+x4DB49wo4qBwadn+/EAqhiZlYFLawcFUtONRHYkgd3bL/uau6HGsHo7LzxYoIaipgKyMrLubjgDIgNwZNILLoy4r6ZhPd06wUKmjlCKKov03vAkTMjgdFNlGBrMs44033tiTDG4mhbv5DT7tROb9Vi6fdaX0iNgd4YPE0VnzEJBScuLECV588cV9P3BPwqD4MBFIzYvNM7zVv44URRar9Q7jHU1V45fdq8VrI7ibrHNleIdPzzzPsV1I12ZooaipiMwbArH1+GQu3zLU8EE3iHvvSZKELMt488036fV6OOdotVp0Oh0+fuEl6vX69OK8mg7INiwNvZUABUJi8KwkfU7V9u7t6+djgCmhHuQpoVQY5wFH4nJaQZVhnnJn3OVic2vY9343Ce89WUms9C4EYhJPthsmdjcHRVWFvNSY563hCqb8YuDxKCRNFdIwuw+ZPA6EECxWm7w9XGdkMgSCsTVYIBKCpi5K57E1vDVcpxmEO0rFD8KkTLwXGez1enzqU5/a8jtXJrxstpDJsmxPZXCiVO1WEt5MCI0xe5bznwQ+CLuTZx0fhI/dEQ4B4qjH7iOH2dlZrH1wMoOU8qkjdtu3c6Z2nJqKuDpaYmhiqqrCycosbw/uEEi1pRxrnOUXG1f47eO/gRCCkU25V5ZcW7o2vYAJIXi+cYr/7F1FIKaTmrkr0iEulIrbB/FtfdL/OJlUHY/HRFGEc47jx4/zwgsv7EvWU2vYQ4xEeE9s893/OHkMYvr0vOx1vH8c/JR4hVLRzcYH2ifvPXfTIe+N1smcwXtoBxVOV1vMhtVppFhkweyy+El02cMOULzUnEcKwa2kh3MeLSUVFXBa1en5+KG2dVDMhjWer3t+vH4b4yypLyammyq8PyRSnuPLyZhz9Z1fQqx3rGUJq2mCFHA8qjETHLyv0Zb5t1pIpBBIKYmi6KGUwYOQwcFggHOO27dvA3tPE28vGT+OMng0PHG4OKweuyPF7giPgqOz5gnhaSd2AHNRm7lNKtz10XIZSA+9fFQMDghBJAOUkNyKV7miNkhyS7ARAp6GrvKZmQvUSyVroTrDx7zl8vAOiclAeCIZ8onOOdrhVo+4J4WJGjchcb1eb2ru3Ol0ePHFF6nVCkL6ox/9aEt+4m6w3tHLYjbyMQOTUtMBDV0pp2cFXkDtAfFYnbBWmCmXyQ2erefIpLxrvSNUB/tY3kn6vDVcpSILc+aVfMRyNuTKeJ25oMrZWoeL9TmqRiBkwNhkVFUxMGC9Y2wzTlfaOwYt9kLuLGtZQu4Mx6IGi9U2sc2L3lIdYdKM7hNUY+ajOudqHZaTEbl1eJ9Py8GFKlkoqLEzpYrpkOJ+P+Evuqv0TUYgJd7DrXjEiUqNV5qz+/YYjkzOUiD4f1du431hiH2iUuNirUldF+/bQW/iByGDN2/eRGs9jX7aTAY3k8LdlMEJoditTLwXGfwoKGgfBI5KsR8+CPymr+AfXhydNU8AHwbFbjekZSTXwMb4MoQe74ltBnje6N0iFTmR11RkUKRjmJifrL3D/3H841ObkNO1Y5yszjIyCSCmfWVPCtbaqZ3MxDeuWq3S6XQOpMbtB+McP1+/xlpaDHWkPifLDIM8ZaHSwuBQaOYr+0/iVlXIufoxrg5XCIQmEIrMGSyOCopAKnypCJ2q7l/yhoIAXhmtU1PF+3AvGyIp0joyV+hzN+IuAoFEcKl5nOtJEe8FRRTYc9UZFqt7D11sxmo65rX+ypaybV2H/GZ7gUpJRO0jvsdjk3MrHrCaJWgpOVNpsFCp70q2TlebrGYxArB4Elco6N57mjrEAcY6frx+l1Gpos6FVSQwsBntYFNKh/fcTcbMBhGnqo0drzUwGT9bW+HdcZ9xpGmOh+XxhBvjIT/bWKGqNDNBxMlKjYv1Jq3g8PNvH1cZfNAASRzHdLtdtNb7ThAfhjIIH8ywxvuNox67Dy+eBTH56Kx5AjjsHrvD2s6D1tTQVRKbAWzxclMU5cOxSaigtpReKyIkthnLSZeTpSUIFKa+zaB2KGvfjElKR7fbJY5jfvzjH2OFR7drNBpNzj1/kU6jefDymvBcGaxwfbRG7g2zYYPZoA4C6jpibDLWszENHVFRAevZEOsdmTMsJ30qeJ4PZrcYBG/G2GSspiM8cCxs0uhE3BitkfmQXu4IvUB6x9hkWO9YrM4wewBlc2QyrPdUhKSbx+BBlTdbJSSxNcxHdW7GPep4QqG41FwgcwbjXBnBdrCbc2INv+ovE0pFbVNCyMhkvNZf5rOdk7seb+s9d+IB1+PCO68dRJyvtZndZK/Sz1P+vXsP74s82sTkvNZf5V465pPt+R3kbjaocKba5M5owADPOEuLfUZQVyGJzbllDXUV0tJR6d+XsJSMOF/bSpiL2DrNzXi4g9j1soz/a+kGI2vISvLYyzKUlNS1xniPcQ6FYCwMq1nCSprw32bnH5vcPS4pMM6TOkcYBDQOQAbffPNNFhcXqdfru5LB0Wi0ZcrYGLNlwv5BZtMTlXBCBj8KvnmHcf0/InZHeFQcnTVPAJs94w5jW++XYtcO64UI7T2+9LSblAwFAotD7HHK9PLxFmJ3WJiocZt742q1Gu12Gx0EzF06x5XxCh7POiNuDoY870/wfPP4Ay/mmTMsNTz31q+TOovFcWtcqFztsEpVBvTzmIoM6OdJEVcmNbWyJ814x0Xq1MXORnfvPW8N7vHecL047uXBPFuf4dOz55BCkFnDO8u3WMrWOV5pcrLSZiasHegmJMT9gkHszBYC5Cm+dU5Kvlbd/1soNeFDii130yHe74wwq6mAnkkZmoxmsJVAOO95rbfMvXSMAIYm43Y85K3+Op9oHePjJWl7o7+GQlCZ3sAkoVQspzHLyZgT1Z0Rb3UZUpUhORlSiCJyDsFqFjMTVmnqkGhTyklNFT6HfZMyr7Z+2VBCkm5LFfHe85P1ZVJnCaXEIjEUypnznlFuUEKgpEAJycga5kWFHM87wz6f6cwxMEUmcUPrXQdatsN6z3qWkjvP2DkehRo673l3MOTd0RDrPcILFmtVLrVaROrBSTKHqQyOx+MtfYSTMjEUht5BELC6unpgMvg4+LAqdkc9dh8M5JHdyRF2w9M6Ffug7QgENRWR2Ay36bFaSCpKMy7VvInHm/GO1BpyZ8id23Ex896XUV/qQD5pm9W49e4G98Y9cuVoVxssNo/x8ssvbzF4vrpxl3dG96iqYFNihePtwRI1HXC6tj/RvDZcIwlAOVsQLedRQpZTqwmtaoWxM4xK41+BILYZYyeYD+v7+v3djntcGaxR1+F03733XB9t0NAhFxrHCJXmRNAg8CkvtU898PhsRkOFREqROYsWopiuFZR5uY66qk7ta+Rjnj5Dk6N2GRUrDK0FibNsL0SvZzHL2Rg8rGQxUggiqTHe8YveMiC4WG8zsDmtbcMbRV+n5E4y3EHsAK6M+3RUQOgC2vUZ8vL9M86xnCYcC7eTN0FFKvomYz7a+rfUGTrbSOnA5GyYjEBJrCvPdlGEgwshyJ3bEo+H9+TeU1OKW/GIbpYzLoeslBC81GhxcVv6yGaspik/W18n9w4PDLOUE3iOOXcgUjjB670+7w1HNIOCTDrvuRGP6ec5/+v8sX0zdR+VhDwKGXzvvfeoVCq0Wq1dyeD2nsHJ+g4aR7cbGfwgFLujUuwRPigcnTVPAE8jsTtI319VhTR0hUBqwOO8Ly00FLFNCYUuyp7e089jEpdPCeCV4T1im/PZ2fOA4MrwHleG96bRWefr87zYOrmlxGuM2aLGxXFMrVYj7DS43shwrSoOz5K33DC36fS6HE+bXKjP0w5r9KqexqYYMihKwJHUXB7c41R1Zt+L643RGlYWDffOO/AehECWP69nhdrkSiorhUAKhfOO1WzEyUqLUKhdj+uV4SqR2kpoJ+rRleEa5+tz0yb3R3l/hRC8XJ/nV/27aKEwZAhX9J1VZEBNBSTO0NYVhC968lbiAV2TEkrNyUp9hyXIRpZwZbTBep6gheS5WoszlRaBkKTWUtkWB+e9xzlHYg2v99eIs5SxdBjnuJeOkcBKnhBIOT0OoZCA59q4x1xU3cOEpTjWZhcbFuMdsTVUypt3KBVhSbKMsGTeYpxlYA0jkyMRtMOQlg5ZyxOs91OCk7vC4ue52lZamnuHpDgdQqmIS0VvMqCxGYEUpNYjgdRa7iUJYVXT0sWxMs7x634XJQXn6zv7+EbG8OO1VSIpqZWDGB7BirW81uvxmzMHi8cbG8vV0Zh2GEyPtRSCThDSzTJW05SFh0j8eNIIw5BGY+fx2AsPUgb3I4NKKZIk4dq1aw9FBh8HR8Tuw4ujHrsj7IqnkdjBARQ7IbjUOsPPN95FCTm1y0hsRiA1n2id5xdr7zLyGbn1Za6eoCYrRDJgKd7g3UGNkU25MVojlJqqCrHe8c7gLqtxn/OmSa/XYzgc8rOf/Yx2u02n05nGrTk8/+PuGwgnqamAQR4zNikeWI77rKUjfrVxm3ZQZaShtQs10EIyMil+k43IbshL4lCQCL/jrh2XebfO+q0ZskJgnOV0rYOId7f3GJqM+i5ealoqhibDeEfwiFmxI5OTOkNdh3y2c5rr4w2y2BAbQ0OH1FXIyGYEUnGpOc+vxT1+tHGHuFS2nPe8M1zjleYxniv7zpaTET/v3UUJSaWMaPt1b5Wfb9yjIiVdk7KeJcxHNZplD9nY5CTe8aveKkoIvHNsBJ5/XbtNUwekzhWK4S69fELAIE9RCDayhIEx5N5RVZrZICJ3luNRjaHJuJck3I6HIOB0OVSxm/eep1Dmroz6OAq1zHvomYxQSl6otxnbnElmnZKCTzTndih2dRVQVZqxNSgBFalIKYlsOdVsvKejAzLryJ2jm2f0spxQKOrlzbj4niCoKsVbgz5na/UdqtmN8bjoL9zkVyaEoCEkN8djLrVaVA7gZdbLi/3aTRlXQrCc7E3sPgz2I49TJo7jeNrC8aSVwQmOIsU+nCjuaUel2I8UDvpBPeyL5GH12B0EC9UZPssLvDW4xdAUpGU+anOpdYZGUCVdG/BLv0QgJVpoKiqYliRDqXlnsIT1jooMMMYyNgl5brDOckfHtLXkzKlTdLtdfuu3fmvH66/EfVJnqKmQ3FuGNivKo+UEpHJFo3w/TzDSs5wNOVlpbiEPDk8g1b6kDmA+bLBEtzCOLeqYU3JXPLeYKA1loQpOFCQhClPcubDBgN2JXV2H5M4SbiNvxrny2D28QhBbw3/277KWxtMS4MlKg4+3jhdTr3GPlXSIFIITUZOFSoNASO5EUHF2SsigUPBe76/SCSo0dcjrg1Uiqe+rX97RNykWT0PVWAjr3E1HXBt3aemIdhghvcR7QVOHhYWKNcReMHYGZ/yu5Gui8AZC43yhsN5M+lSEQkrJIM9YTWM0gl5u+P9W76GFYD6qEEjF64MNrHNIV6hqE3jvGduchopYcTEaiULihcc7T2odC1Gd09UaQ1vk/7aCYIvaO0FFKc7VmoxNTmwtgVAEzmOVIBeelirUuJExpNZTVYqVNGFoDDUZkFiLcZ7lNCGxDgQEQrCSJJyobo2L28gywh39bx4pBU4Uil7mHG/3h9yOY7QQnGvUeKHR2EIG1T6nugf0U+S6+n4RyQkZnJC148ePP/A5j6MMbv6XJAnGGDY2Nh5ZGTxS7I7wqDg6a55yHJZ1ysMof8erHeYrbXJvkZuMhgEioRFImnprk/8kkmlgU7COzImpfUIUVVBKMjYZQbPJTHvvEunYZtN1JiYD73EUnmQAksIY1nqHdkW0VT9P6ZSTlt57EmsONDzxUvsEv167Re6LmzdTfzlXKpZFD1ukNAuVFrbsgRJA5iy9POFt10emkmxY4XStPR0wuFif45fdOwRCTtfhSyPjl1sLWyaLD/K+WO/56cZtRjanXnrRee+5kwzpm4zUWrJNREoKxclKk6HNSRTMbBt8UEIiBNyKB5ypNos+uU29br08BSEIEPRthnWFvyFe0M8zQqFpBZqKFDuOc10GhbWIjljPUjQSKQuVzTjPTFABUeQH903OiahGP8+n6Se5cwhZpKGIkm8vpwlnag3aOqSbp3gPsfAMTV4eH8dcWOVOHHMmajK0GWM78WFU9I3h/1lZ4kSlxov1Fs83W/v2nF1qFUrmlVGfYZ4jgMVqjU+250DASprwWq+H1n4aeabRZM5xdTjCURg3R0qW77vlx+tr/M7CCWqbbtZ1rVjPUtimzBT9kRBby/9cWQUPNa1x3vNmb8DtccL/efzYlNzNhCFaFv1/wSby4LzHes/JfcqwH4Up1cP0GdwO59yObOIkScjznNXV1R1kcLL/u2USB0HAvXv3pj6c9fr74/15hPt4er4CPTqOiN2HAO83sZs8PhQ7Tw8pJaGRJHkG1pGbHGcdSilkoIh0gAol9V2yRwUP7l+oqmAa6WLKG73zUFCWsiRaajXKQyADBiad3uCch9mozsXGg7+dN4MKp3uwtqDIrEEiMN5OJ4GtzXFAUP6spcI4y9jmOC/4VXcJ4wr15xcbt7kyXON/mz9PpDSLtQ7dPOH6aH06ESsEnKq1Od94+Onh1WzM0GY0NhkhT0jL1XGX+bBOoyRm3nuW4hGSFc7WWuVx36NkbbNde8dim6OFwDrHoOzLC6UiEpqsnBa9Ou7R0lFZFg6mCpoQhdL5idYxrPPciPtoLwmkYjasgPfMBBFjW0zzNnRhTZJ7x51kRL2MuOubnEgW9jqZs3TzlPmwSlMHDIzlnFO0qg3wRXqGFoKlJCZUillVZZaCgK3nKVJItBRoIXitv8FGnvFfZ4/tecNXQvLx9gzPN5qMjOH1117jv186P32883AszGiVJE0IQV/m3EsTBnlOQ2uCSS+f97SCAOc87w4HfLJzv2/ubK3O1dF4S+8fwNh7ToYh7w5GSAT1QJfrEnTCkI0s473hiEvtIqYvkJJPttv8x0YXLQpCmTtP4gwX6w064eH7631Y8KSJpJSSMAwJNx1j7z3VapXnnntu1+fsRgYnyuCPfvQjfvjDH7K0tES32+Uf//EfAdBa8+qrr/Jnf/Zne67l+9//Pl/96lex1vLFL36Rr3/961v+nqYpf/iHf8jPf/5z5ubm+M53vsO5c+ce/yAc4anCEbF7yiGlPBTrlEft1fPeMxqNpgMOa2tr6CoM54r+uUa9MVUVE5fzYmOBK6OVaS/S5u0g4ERlb/Pd3FnGJmNs86KPzOab+uQK+uHw0ylI5QXNoIL1ntPVGTxwotphPmoeaAoXoG4k//vip7g6WuXOuMdS3J+qdYHSCAQb2ZiVdEgzqKCloqNrrKZjmmGFUVaoQrUgop8nvNVf5jdmTiGE4BOdk5yrz7CSjvB4joV1WsGjmTXfTYbExhTedVJN0yLGNt/xvgohqOuA28mA52qtHSkXExjnaOuIhg7RUmI2TWFKIUitZWQtdjrd7KiU7/VKlpJYS+4SIqVYzRJmS2KZOctGnvEvq/eweFpBDSU8kVQoKVmsNni+PsPr/bX75VRRqLHG+cJixAsc9897LSSjPGc+rCIRWKCJpK0jftFbZ2T6eO/pmhQfQTsIyb1jPS9KnblzVKQmkJJ2EHA7HrOeZ8yF+yszFaWpKE3VbyXHQ2NRYqta2QwC+iZnIyumyosvJqCF4FhUfNG5FcdbiN1MGPLxVovX+30EoKRg4BwtHfBKs8X/WF6lvUs5rq41V0fjKbEDWKzVqGvNe8MRG3lGK9B8qt5mobL/Pj7rit0H5WO332vuRgYn+NKXvsSXvvQl/vZv/5a5uTm++MUvAkyVwL1greXLX/4yP/jBD1hcXORzn/scr776Kq+88sr0Mf/wD//AzMwM7777Lt/+9rf52te+xne+853H2NNnDOJoeOII7xPeT8Uuz/Mtk6ppmlKv1+l0Opw+fZpOp0OWZww7mmvjFVJvwBbbP1Ob41J7ESEkl4d3CYRCl71pubOcqc3R3sO0eGhS/ufyO0VEFYqxjXH4ktLdH4IQFGW3ioqQ5OTWcqE1zyc7i/vvl7PT1IXZsLbFky1SAS+3TmI99PKM+jaD2flK0W/1v8xdoBlU+L+X3qK2iwltVQdcH23wyU2Gvc2gQnMX9XKCSbzX1eEGV4YbpNYwX6nzYnOOTljBe8/rvWXeHK4R2xxlCypUVZrjUY20JLnbbyITKxLnPQ0LI5vTlPfLwrmzCCFYrBYlyZcbc/yqv0yEJhQShWBgCkVNTY+7Z2AMWki0LDz9HB5NUdZdy1JqeK6OBkRSUw0Lf7m0nJz9WHOW843mtK9tPqpyMxneX3P5n8l5WpMBxjt0WSKfrD12llkdMCDntbVlIilplFOombPciEecF6Kghd5TOMGIqXFwMY0Md5P4gcRuL3SCgGvbCTVwPIxYTVMqqiCxbaVoBgFaSDLndi3/Pt9sslCpcCeOSZ1jfjTmbL1OVetiAmMXTKa1jXN0c4MEOmHATBjymdmPrjq3G55GYncQbO+xm5Rq98JPf/pTnn/+eS5cuADAF77wBb773e9uIXbf/e53+Yu/+AsAfu/3fo+vfOUrH4rhmfcLR8MTR3hf8CQNirercf1+HyklnU6HTqfD4uIilW29OXEcIxB8cuYsFxrHWUn7RapC1KQVFH1ul1qnaOoKl4d3GZqUmgq51DrNc/W9S18/W7tGaouhCeMcYzKEt0XjeVkCdRQlWUlhjjsUGTUpudiY33O/vfdcHqzy697daeO+FIJPdk7yfPPYlseupCOCXYxcC5sTgS2nDnNnp0MGWx6HwJY9geqAnRrOe66IlHT9NmFp3XJz1OPGqMd/P34W6z1v9Fdp6wq5tygKEhdbw0ZepC54oLIt73XiYRdKxckU8qDChsmmPWtaSD7dXphmnS5Wm2gheGe0wSBPGZX7KEuyNBVNKQheVQhyoK2CwtzZF2XyroSqVJyo3O/BrCiFFoI3hxucb9y3Flmo1GgOQ4Z5Tl3rwutOSEY2ZzasUlcBd5IRwjuM98wFFVJrMd5xodLgZ/0hCjDe002KY1HXmoZ33E1iGroghgGahUplx3v2OLey09Uar/d7JNZOp1a99yTecSyMaAUBjW034bGxfGKTwrYZhVGyZylOGRlHJTfMi2LAI3GOqlIY58i9R5eDGw0d8M83l7BlP15NKf7bXIeTtequr7EXnnUF7aNiUHz79m3OnDkz/XlxcZGf/OQnez5Ga0273WZtbY1jx7ZeC4/w4cYRsXvKcZjEzlr7/7P3XkGSXPeZ7++cdOVdu+me6ekxMANHggDoQFKCQEqiKF1QltLVDcaupN3Qy93Hu4GnfdgIRXAfb4RuBEPLNdx7g8sVtSuRkijRiU4kSACEGwIgzPhpb8pXpTvn3IfMqvYzPdMzmAHYX8QE0NXVWVlZWXm+/P7///exvLw8JHJhGA7VuCNHjlAqla46tbVxfwpOhsJOvXRCMJ0fYTo/sqd960Q+a2EPT1g0Q5++itbLcCbpK5rIlOmrkL6KiY0iMpqcEnywepy8fYVA9V6DFxpzZCx7qBQpo3m+PkvW2nz6Z6RNyCPlXwAAIABJREFUc4djPSBJTtrvVfVytKNgmJE6IDyhVpRdb8dJy92wHPWpoxi33OFCYEtJqBVPr85SsNzEqw1JyfZoRQGJrQU0oj5VJ0Nxh5wCX8cUbZei7WIheKA4ji8TGxZbSkac7Dbz20OZAhNenr6K+drSBfJeYvmxGHTRgCslAkFPxSnBFlTTHNZAK3pxRCPsUnO3l5ttKelHikYUMuIm54wtJB+oTfBya42FIFFTi46blMKROEIy6mRYDn1EWiKxpeDB0jheENEwBhNFdGM1LOk2ooicZVGwbR4dGeeHq0tUHHcYtzb4PDWGiczeCNBO3z/PsvjQ6Bg/WllNrUYS1FyXD9ZGeWptlXYUk7OtJK1CKUqOw4kdvNsaYcQ3FhYJtcGzJC2teabbo7m6xgPlEt9fXmG+16cRxoRpz6knBSOex3jGG36OvlJ8e2mVj0+OU/NuX9Xudh6euJ1wrVOxO52nW9/3Xp7z8453wuE4IHa3OfbTG9fpdIYkbkDkstkslUqF6enpbWrczdyfK8FPBxD6KqanIiRgIVEoMEn011LQScyShaTiZvmVQ/dyeulFClcgdUkZcxEntSsZ7LclJJaQvNJcYuPM2bHCCHP9JkauLzzGmIQMCYt+HFGwPe4pjfPD5fPEG64AsU7KzfcUdy8J9+KIVhzgSYtK2ms3F/aGiQYbYSNo9nusxS0IY0S677YQxBZomZQTjysL35bM9rtIKZPEAZH4uT1UOTQ0QRZCUHZcys6VS49CCNzUWFkKQdFxyVg2S0GP2Bi0ToZLtDFMZNZ92TKWTRDHuObarooZy+bh6jiBVkkfnGURKMWZbov5fpe87XCqWGEsk8WVFvnUaqQZNAmAMFZ4G0rRxhi6KkYKOJLN80C5xiutBlnLwpWS2Bg6cczRXJ7aPjNda67HxycnWQ4CQq3I2zZVJyHoHx2f4LV2i7m+jyUE9xZL3FEobFMNjTE8tbqKBspuovCFQuBIybluj+lsBkdIloKIWBuESG50urEm1AFjnpcQx1ihTaJevtpq86Gxvd1UDfbhnby4v11LsdfqY3fkyBEuXbo0/Pny5ctMTU3t+JwjR44MDeJrtRsfBXmAW4sDYnebY69EKgzDTb1xG9W4o0ePcuzYMc6cOcOpU6fekv25FhRsD200HRUOSc4gn1ZjwECMwhhDJBQZ4w7TIK60LxpDOw5wkKxEXUKVJAh4lk3R9qhHfTZ2/E14BY4XRjjfXRv29K0EPrHRlOwM3146R85y+Mj4MR6pTfNSc54gtRixjeGh2hEmc9tLbbHWPLM2x/luI0k0IFGmPjR6lNhoBAwn5AZTctKyMI5F2cuic4lp8KD/zGhNrDS+jhlziug4Jh9pllSAr2KyoSYfKH52cRVIyuevvfYanucNczi3/te211MlbCGZ9PLMB10KtoMjJVOZAr6OaUUhFSGRwsLboExGWoMQHNKCjtZk5OaFLbHhENvMgAfwpDXMd7VtybvKI4m1yBUwmJQWG/ZDCIEwydQqwD3FMgXL5medFq04IistHqzUOJkv3pDFXgqxo/FvyXF4b+3q5KoTK9aCkFJato21pqU0RigcBM83Wsz7Aa6UFGyRGkxDy8TExnCm3cUIkbYZJP9tBBElx+H1Vi/x78u6PFApMn6VIYq3Cu/00u/gNfebZnGtit173/te3njjDc6dO8fhw4f54he/yBe+8IVNz3niiSf4/Oc/zwc/+EH+6q/+iscff/wdTeqvB5K3vnR/o3FA7G5z7NYbt1GNa7fbWJY17I3bSY3r9Xq3xDZlL8hYDtP5Kqfr88OykhACrZPFe3DPmrFdPMslUDGvtBZ3vCCFWnGpW6ce+uRtB200y1Fi6DsokQZaEQRdqm5uU5+VEIIHK4c5kq1wrrPK6501bGEx4uaGpTxfxXx78Sy/cfgUH8+VeO3ieYwxnJo6vmsJ9unVWc53G+Tt1H9OG5p+n787/wrlTkjPiom1JrQspC0p5kpk7SRX9T21KZ5enR1OGQshIC3V3lUeZaqU9BfuphMaY3j++eeHfTUD4jjordwY1D6AZVlYroPvGXpS4AmLQEDbxEgkh/MVIqFpx9FwpEUKwUPFGo21Lq7jsRYF5C0bSyRZsqHWvLc6fkXvuGuBIbl4SSEJzfpQgjImsfuQFoaEeB3NFziaL9yWylRk9FBRbUcRl3s+oQYr1hgVsRzGGGPIbIinE4PmbmNYi2JqnjMkxZFSrIYR35hf4UguS8aWzPcDLvd8Hp8YYTq/vfz8TidaPy89drZt8+d//uf86q/+Kkop/viP/5j77ruPf/fv/h2PPPIITzzxBH/yJ3/Cpz/9ae644w5qtRpf/OIX97WPB7g9cUDsrgG3YlEQQhDHMUtLSzQaDZrNJmEYUigUhmpcsVi8pt642xHvqUzzWmuZKDWVhUGTvzX0YcvZCVl1LZtznVWOw9Dwc8Fvc6a9ypnuKhIxtKJohok9gIMYdstLA3FqILsVQgjGMgWkkJztNnEswVroE6bTp3nbQQnNhW6D6VwZH402hkhrrB0GLzpxyPluA0cngyoDk1LbtlG2pFyrcrHXILAkVrqLy0EfEQoeHT3M0VyZThTySnOJgeuNAA5l8pwqXF0REiIxdM7lcjtaK2xF4t+nCMOQw4HPuV6TV/0Ofa2wtUBqxWvBKhjDdBBjkZSHq9Kma/Xod3vM9GM8IZiLfLSAETfDI9VRJnN7zwa9GqQQFBE4nkeoNZ2UmJYdB1dKspa9zfLmer+/e1mkA6WIjCG3JR/4aijaNlKAHysu9wKkEDgisT1RQiSG0HGMDVh2Mp8sEGlGLcPSbLqnBDoZ3IlSsmsJQdGxCZTmhyt1fjeX2Uaub+frwo3C27EUez3JE5/4xCf4xCc+semxf//v//3w/zOZDF/60pf2tV/vdNxm937XhQNid5tBa71JjavX68OLRKVSYWZm5ppc0Qe4mdO1NwKuZfOuyhSvNpMIKSEEjchPbR0gv8GYVyIITGLXEaqY7y+8wUrYpRX5qRGwIGPZFGXyN5qkWX4odGBwpY2v4l1F91YUDAcCkhH45NvejkIEhpcbSzy9OkcYJUkZr116lXdXJrivPEYYhtTrder1Ohc7DXrZxArFdVxyudyQhPsqZiEOsYzAlTZhmmxhS4kjLFpRiBCCe8tjTDo5lqMeShtG3CwVx7spi5UQSWKIbdvkcjlUxuPMckzNcoiNoasiMEkEW7/s8ltTM2itCcOQbrdLv98n67ociSImlCYIA+Jmg9nZJS6b7RFMG133t5aILcu64ns8iuSCNhRsh3LaL6fSHrr3VSs3/NjshFYU8dRKnUu9JFoua1s8XC1zd7Gwp8/HkZL7yyW+u7SCMgZHShQQaoNvDK5Ifm7FClsbSk6igmakRYckVk3pZLhHmaQHL2MnamVsNHaqd3uWpBlGrAURY5ntBP+drti9HYndtSp2B9g/BGZdEX8b4+CsucUIw3DTgEMURRSLRcrlMjMzMxw6dIh6vc7dd9+9r9e5HYnd1ovffeVJ6mGflaCDZt2ry5MOWWvdOiLQMROZItDm5c4yy34nmYo0YA3MklWMnZYIjTE4wkJKASSkzxEWkVG7Wl44UtKNk5zajc9JjHs1836HMS+PQKKNxkQRT82f48LrbzAuXCqVCmNjY1SOHqa+cpGcvd1/SqeN/q4QVDM59MAqRUgwhsu9NqFSiQdfFOAJh/Hc9mnWq2E/n9mbncSwuR1HrKX2KgM045CLvQ4z+SLZbHZoujo5OXnFbQ7yODe67odhSKvV2vS4Umr4Nxsjl1zXRSlFIQi4u1LmNb+PkImSlZTTq8zchCgmk063AuQtC19r/nZ2MY1jGyRkaL63vEqsDfdXdrY22Yp7SyXOtLq8EraJNEQGQmNwLYuMlMQm8cCLtaYZxhQcC2UMBdsiY1m4lkQCJcemHsb042TAZaeyt9lyK7Poh5zWDqcvLJFzbO6r5LmrlL9hJfOdcEDs9oaDrNifHwghPg783ySdR58zxnxmP9s7OGtuIrZ+ubeqce12G8dxhr1xO6lxq6urtxUhu5klXUdaPDZ+B4t+m/l+i3bU51K/NYyVMsYkPUnA/eVJLsy1eL2zip9GjWmTHGM7Pea+jnGlha9MYhbrrvcX9eKQY/kqmu6O+2KnhG7bBdoYNKC0otNpE0cxRgqk6yJtB/9QkfceXTcE1cYkE6Mqxttgr6JT7zFHyGG+ghRJFBcwrAf8aHWOM+3mMLnDQvDB2iGO5XcmDY0ooBGFZKTFuJcdKo2tOOJct8lK6FOwHU7kinRVTCuOKdsOx/LJxGagYub6fRxLMuVlCbVGGc1aFCTlbQSGJDc2MoYfrS1zNLc3dWqAa83jNMZsIoBRFNFqtYijiHK7w31hyFocJ2RPa/qLyzxvWVdUAwcDI32tibShmCphu6EhJH91aZ61MASg6jqMeS49pSg765+rKxOS9ZN6g1Olwp5IuBSC+yolVsOYrC1ZbXVoIsikf+tKyYjrshZGhFpjjGHC87i7VOD1dpeS42zoMUzsUyquM8yMVdqwGkbUg4inlpvcXcpxspjjci/gnxbWaCOYtCSB1vzzUoNLvYCPHapdU0n5dsYBsTvAniEYRlq+ZS8phAX8P8AvA5eBZ4QQXzHGvHK92zw4a24ShBD4vk+73aZer9NsNodqXKVS4dixYxQKhbesN+52axofTr7u0Ad1KFviUDYhLhe7dZ6vXyZQiVdYznJ5pDbNqJfnaVvT0fFQlTMYYpMsbq4ABZQdD1/HGMzQoNhXEa60uK98iNPM7rh/UkjylkdPhcRapb18A8u6pHcpl83RtBIzX4EBpWj3OvxoeZb3jyaxYlIIPjx2lH9aPEc3TvNXTbIv95THWGq3uRiE214/1pogjnmtuUbBcQeJasRa8/3VefK2w5i3TlQDpfjuynxi6JuSw6xl8UtjU6xJeH55FkSSlTrX7/NsfQVPWkMvvx+tLVG0Hc52u8OJ44y0OFUs0Y6j9F0LYqMJ09IfwKV+j9c7Le4u7h4Vt18IIYbxS4NQdM/zUEpx1113bXu+MYY4jreRwX6/P1QF62HIK0bQkhIMOALukHA8DWXfSArrWvOi5VCJIop2UtrsxDFvtrs7ljVtKenHMWthtOdJ1KP5HFmrOfyuD77xkdYYA6EyFCwbLMO7ayV+YXwEWwhytsWL9RaDc1IbQ862yFmJf5428Ea7i680I55LI4z57mKDl5tdOpEiZ0kikpxaWwo8KbjQ9bncCziav3Y7pL3gYHhibzggdj83eB/wpjHmLIAQ4ovAJ4EDYnerobWm3W5vUuNOnz5NpVKhWq1y/PjxPTWvb8WNJHa3MnP2erdzNF/lSK5CJw4QJNYoQghirZiz42HU1UYYDKGBnLTQGCpOlqlsiQW/jUBwLF/jvvIExR2sN4IgoNFosFJfI1Q+tjFgS7AsbGmRtRyWwj55xyMwhq5OFERLiDSTFV5prVB0XO6rJBOro16OX5+6kzfba6wEfbK2zclCjXEvxwVtcbFdJ9JqGHPWCkPWwpBIa2Tac1W0HKQQ2FISGc3LrVUeG1ufhR2QuuyGvrRAKb62eImODXmTmOoaIVgNAyQQak3ZkThSstDvM+v7OEJgC4kxGl8pXmiukbFkqtApwg3HWiAwBr69vEDN9ShxewzobOzh2wmdOObHF2cxRjORHq9QKc7FMSPFAicde0gIO50OP+yHGKXwWy38IeUSKClZ7Cqk5SOl3PRPaQ3pDcFeFnhXSn55coxvLS4TGoNKo9gCpbCw6Cc6KaE2zPXD9bJztcxMPseFbg9faQ5lPGquw0uNNmc7PZZT/7sj2SxFJ7G0ydoWs72AWGtmCtnB21k/dgLebPduGrG7FXg7KnYHPXa3Bregx+4wcGnDz5eB9+9ngwdnzXViQAAG/5RSw0nVEydO0O/3eeihh/b9xbzdpllvhYIohaC0JeFiJU0qWPe8Y1gmhHXFwxKSXxo/zlhm+0SmMQatNZcvXx5Gqtm2TbVaZWJ0jA/ZNX7SWMQWSQqCIRl4GJj8tuMQBjm2JukHLDiJ9cRLjSXuLa9HqOVtl3dXD23bhxE3w13aYUkkiQ7dKKYVRXhW0kclgU4U4ceKsUwGKQSulKyE62HgjSjYRuogIXIrfkBHCjpRhIgiXClROpkIVkbTVzGSpCRJegyT4yqxU4XQQmKEItADvTJ5nkSiRTLM8lx9lceqb49YopebLQKtKG4gfgNT5pf7Pg9PHB2WUI0xfPPMebJKUatWh883BqwwYCGIsB0HDBijCcKIttJgNK+9+jMu6O19gruViMuOw+8cmeTHvQ7PaYueAQsLL1UJlU6UxVYU80qrw7sqSTxb1XWoupsV0w+P13jvSJn/enaeyUxmW0k4Z1lcDiJ2gkxV5b3CmIRsvtHqE2nDdN7lRCGLu8OU+OD5Bz12V0ccx9dkUHyA/UMA+3Mf3BWjQohnN/z8F8aYv9jwsluxr0X2gNhdA/r9Pi+//DKdTgfXTRrka7XajmqclPItVbbebtuB/ZdIkgQEhqa/MCB3yWMZ6fKbh+8betANVNXBxGq328X3faIo2jFSbRTI2i4vNhZpRyFSCO4o1ri/PM4PVi6yGqwl2020ujQZwUUI6MUxkda4e7gwV43FR6ZPsdjv8rez5xj1slhSsuT3EAgsKYi0ph/H5B0HZcww4xWgEa4rOBvhK0UnVihSw1Sgr5LMXWuDoe1GFc4Mar4ppABfa2qOy1Kw3mcn0sXfk5K8bXO534cqbwtc6PaGvm8bYUtJEMU0oojRDf1/FoJ4y3OFgLzj4MWKQFpkLYtOrFiKAhCSkuPxYqbA/ZUCvzBeQ8COAyOdTmfT43Eco32fOxyXH3ilRJFWKvW6g3HHxtGaF1bqnMolhtO7EQghEpoeacN8z6cdJ+py1bWpuFbSuqCTFoONn3moDDN7VOu0MXx/scmrrR52aq9yttPn+bUuv3FkhKKz/Tj/PBA72L9KeKDYvaOwYox5ZJffXQamN/x8BJjbz4sdnDXXAMdxOHHiBIXC1ZvFbzci9U7bzqiXT++skinShFqZYWJF3k5Kl42UxNXrdcIwpFgsUq1WufPOO8nn8zz11FMcP35819c5Vqgyk68QG40lJFIIQq1whYMxDKd3HSFTC5Iki9ZKy6Z7hRQC0oVxUJL1pIWvFRbJUEVPK3LGJtKaU4V1FpXZgTwaY1gJQlRKeTXr5NeQDD4kryXXiXHq72fQ64MSBhwp+KWxSf7y8gW0Sec6jMGVkqrrpRYtt1cP55XgSIneRtXWM4E3DlEIIbijkOPHnQ69np+QdSmpugnBfqRWYTKb4dnVBstBQN62qDgurpRoYzjdaFOwLR4ZqQx7966G119/nZO1Ec6tdhDGEGiFBWQBjCYOY7q+5pVXXiFKc2qNMVhbBkYcx0GHMa8HOlV6k/e1EkSsBhHT+QytKB4eCW0MrUhRcW2OFfaWo3uu7fNqs0fNszdcEy0aYcwPlpp8/PCtj6u6VT12+8VBj92twS0oxT4D3CmEOA7MAn8A/OF+Nnhw1lwDbNumWCzu6bnvVMXuRmG/d7O2lMwol5/JAJ2WYgeQxhAEIZkoZKm/RLVa5ciRI9eUjRsoxZvtOqthn5LjcWexSt62MMbwtbnzzPY75CyHngrTPFvNaugz6mbwleL+8ti+pwpLjkcc9olNQliVTkqnE14OgWDJ7zPmZRj3smTTjFUvJXmBMgSD8uoGEW6dwIErBVnLphPFpIlgye+MISYhbhq4q1BiJl/kXeUqZ7odXJn05TlCIgS0opCZXIF6tHNpD6AdRZxutrjU65GxLO4vlziez9/0ycsBwe3EyfRqzXO5p1jg28sreFJuOg99rSm7DpUtvXmxgi4SGcdYQtCLFZ04ZtRzef9IlZLj8Garh+8mgwsDSCHIW5Ln1lq8p1a+JguRjCXJ2Bah1lRdB0/K4WfYiWOOZjM8ODW26X0qpTapgWEYEsUhSmmkMEQqbT/AECGxGh0mbMlrSjHXaGJJyVHP5sGMg9/poNIS8ZXKgS83e2Rsue37XHYsLnYDerHadEwgmdKd92PisE/RsRjPODf9PHg7RooppXbtEz3AOwfGmFgI8X8CXyOxO/nPxpiX97PNA2J3DbiWi8PtRshu1IXtdinFGmMYjSTHnCznTT8xIEbgisTsV7oWv3ziLka9a/czW/J7/O3smWQikYQ0Pr0yz8cOzZC3Heb9DllpARahiomFBmMIlaIdR0xlC7ynNrGn19p4PMe8LJYQxFpjS4klBKNell4c0Y0jpjI5fA1nOj3Od/sYoOy4fHziML80NsXXly7Ti5Mp4VacTNomuR2JRYveeLhNYi/TjmJWg2jHvpJQa0qOwy+OJr2BHxgZYynwCbROhy8UK0FEoA2h6vF6q4snJUfDkOoGZWrR9/lfl2cJtcGRSQn3QrfHncUCv3po4qYt6s0o4u9mF1kJwvQowFQ2w68cGmUym2G+7+NJmXoTJskij42PbfqurAYhr7S6lLXByjj0lAIBGWmj9Lo9zXIQ4u3QU2ZLiR8n3nIFZ2+X21AbvlfvstQPaccxFoKMbXEk56WT0YaHqpvtbjYaS2ezidrWjRWyPc9Rz7ASxomBMeAKwZRrYzklHj9cpfLCCxydnMKoGOKYsNNmrr42JIgbh6629giudMEIQajsZHDEkkghh2XgQJtNecxrQcz3Iw9rvoUlk7aJEc/h44crlPZ4fK4Vt6rHbr84UOxuDW5Sj90VYYz5KvDVG7W9g7PmJuF2I3Y3CrfqfRljaLVa1Ot1Go0GnU4HpRQnvDHGymXeCJvp85JG+EdHpvdM6jZe+JXR/P3sWWKjh+oXJEME31y4wIPV8UQhTMtaWWETGwWWRaQVx/JlPnro2HWRFVtKPjA6yfeXZ1FqoJglctvhTB5fC+phQCZVmrTWLAU+X7h0lsfHJnni0Azne22WQ59ZA/1UTdQM+qjWYQlBpASjGY9ebCg5DpHWdOKQKC0w2wgeH50kmy4uZcfltw4f5afNBue6HdaCEG0ENcfBlhKtFG0h+KvLl/n0zAwZK1E4/3FhMe0LXD+exhhebbZZC0LWosQG5p5SkffWquRvwGIWa8P/vDhPO47JWXJ4vs31+/zd3BK/Nz3J6+0Or7TahFpzrFTk3ZXyJkIKcLbTw2CwgZLjUt4goLSimAvdPvdVihRsm3YUbVO3VNrLuBPp2w0/CWA5ChnNuHiWRTOK6CnFm50+M7kMv3xohEPZq9uoDIaKSq5NyXUI0gluT8phykkmHaw4Mj52la0lPapxHA/7AcMwpOb3ueBHqDBAa41WCm0MCogQnPnpAhk3IYPCtvlmR+ArxTgKRyZksBFG/P3lOr9/bPSmkPy38/DEAbF763GQPHGAXXFA7Pa3HaXUMFJta3/cHXfcQT6f59VXX2VqcopKpcJDWrEW9rGEoObm9rxAbL34Xuy2kx66LQu0LSWBilkOesPJUUjKbZYRZGyXnoqS3r99XNBPlWtkbZtnVxdZDfwkcqoywpjt8Q+Lc0NSF2vDWhgPSds/LMyRt2yemDrCA+URflJfobG6hK812ohtI1axNoQo6mE0NLJ1pKTqrperB4MWG1GwHT4wMsY9pQr/7fx5Ks56GU4IgUMytPFau827KxVWw5BWFA3NdgeItKEZR3S7ilHXRRt4rt7gjXaHP5yZ3hO5u9LCea7bpR3Hm8ikEIKcZbEShCwGIfdXytxf2d1/b6Ef8NNGh0YY4yDIG7OtnDqYHn2wWuQbC6t4cn1BN8bQiRX3lgs4aWvG2U6fF+ptOrFiKuvxUK3IiLdOJutBxLyCqiuxpKTiSkqOTaA1vVjxcK3EyeLebljytkXZsekrTdYWZDaQy36oeXft2rJ7B8kiG/sEf6ES8T8vrpC15JC8amOoBzEfGinw7nJ2SATfbPXpax/XaPx+n37aXqC1ZtUIvrZ0kQlHbFMFBz9bts2FwPBaJ0IIwV3lDHeVspve11YoY1gOFL3IMKn0NRHs/eCA2B3gVuLgrLlJuN184253bMxXbTQaGGMol8tX7Y8bHBtHWkzsYGmyF2y8CPfiaNfjbQA3TcHQxmwicNok+aknClc36g214mfNBq+3mmitKBrN/VoPp3dn8iVm8qVN+/HcymKqFCYEYS2MEjsUIUAkykxsNH8zd5k/OnaCU8UyzzfWsNHU9ebeN2NAkiQNNOOI3A4TogO1Z6uCNcCSn+T47rZ4vd5uk7UserHacWK3EUVgQMpB4gbYlk07jnmu3uAjY/uzTlnoB9vis0j3VxnD6XqLix2fgmNxVylPdguR/+FynR+tNAm1JjSGAEHQ9ZnMeniWHE4ZD5Szu0sFLvd8Xmt1kzKkScrf4xmXD41VE9uUhTVeanRSr0DBT4MOLze7fPLwKMeLScFyObUg2XhuSSHIWhZKw3w/5ME9HgMhBB8eL/O3l1cxGLJWMmTUiRKC865qYfi860XNc/jVySrfWWxQD+L0XBQ8WCvw0EgRKcSwT8zEFrm+IA77VCoVxAayv+ZHHJ2Y4e6it2lKOAxDgiBgtdXhKw3DYiwQqY799JxhTCo+klGUPXubfcxiBD9uRLT8EKPhpTOrPDyS49213E1X8A587N6eEOzsPfJ2w8FZc5NwoNjtjoF/3Pz8PN1ud5N/3MjICCdPntxT0/DNuDiXXW93+wjgUDbPiJflmdWFdJrUEBmD0YoHq+OU3SuXyHpxzBfOv0ErHTTQxqCkpn7xLL939MRQPQM2KT+etIaLfaCTBviNi79IJ1wDrXmj3eKBSpWPHzrMPy7MMuB1qa6GTPufhCG1LNk8eGGMwdeaEddjchdC7e7SGG6AVhTRimIu9Xy0MfSUYsR1h2qJMonR7k7b8YTklVZ738Qub+/c8B9qQz2MeL7expESgeCfFtf45OFxTqTkar4f8KOVBlngrMAQAAAgAElEQVTLIp8OMPSNRpNkq05lXXpKc7KQYyxV26QQfOzQKPdXirzZ7hFpzbFCjpl80jd5uedzutGhaK9/jq4lCZTmH+ZX+dNC8jzvCtPFW8vZW6GN4VzH53S9S09pjuY93lXN88SREZ5aabGSksYThSwfHCtT3KWn7XI34OmVNgv9iLwteU+twH3V3K7DH0cLGf6P3ARLqRnyqGeT3WE/87a1I9kGQEDOtrb1CUJyPv7XN5dZFX2qWYmUybR2qDVNY3g141K0JH4UM4lhWoe0Wz2+3TQ4JkbEERhDx+/x9yuSS57iZFZeMW7O2uIJea04UOwOcCtxcNbcJBwQu3UYYzb5xw28u0ql0o7+cde67f1g6/s5nC1QsB3acbgp2zXSCltI7ixWyVg2Y16WF+rLLPfa5IXFhyaPMbNLfutGfHtxlmYUDn3UtDEEwHy/y7OrS3xwbLuJMcBMroBMByuUScqvG9cNb4Oh7mqaZ3okm+e3p2b47JnXMWKd0A1gABvBbx6Z5qvzs3TjOB0VMYx5Hr8+eXjXxelILocjJZHWm8hoO31PJcselh8DpVkJAiYyGWy5Hv8mgLy1+RI0UEP3izuLBb6/vEaszdCKRRvDXM9HGXAsSdaysIQg1Jovzy7xr08eoeDY/LTRTrwQ0/c+6jksxxGRSRJNurHioVqZR8eqm46PEILJbIbJ7HYy/HKzm5ifbjmeniVpRzGXez4z+SxHchkcYfCVQiNohkk5PG8lhtGnyjuXYZNp7TovN7rYIokHm+8HPLfa4VPHxvjUzDihNliCK9rw/KzR46uzdWwpyFqSntJ8Y77B+Y7Pb0zvnh9rScFk9spWLuMZh26k6WlJPtZknUTJ7ceajCU5kt/5pmjZj3mz5ZOzElIHybnvScmyH/FSM+Cecg7X9ng91lwyktGcRU3ElF2LTqeD1ppSqUQQK1aV5hencsTpBHEURbTb7U0TxUqtG0vbaczclQymt/oJHih2b1/Igx67A+yGn2dip5Si2WwOiVwQBNv641544QWmp6fJ5XJX3NZ+92Uv29j6828cPsnfzp6hG0fDkqsjJZ+YOkEmJSLT+RLT+RJLS0s0m02O7aEEG2vN660mjti8sArAFoIX6qu7EjtXSn55fJKvL84Rm6TEP1A/8tbmAPvyBrWz6Di4BkKxmQQnJs6CMc9j1PP49Mxx5vw+vVhRdhzGvM3KZS9WPL22xk+bLWJjOJHP88GREb6/vExfKex0slQhyEprPbkBUoJgaMcxWctCm8QLLiutbSpQoBX3l69OkK/2uRcdm8cnRvmnxRUCBQjDUj8mNMn7bkQxjSim5trkbJturHil1eV9I2VaUbxpvySCPIZCPksnVnzi8Bh3l66t7B/EelfFSyCIUgXTkoKHbMM3Ak2gg2Ry1EA7Uox6DtldesTOdXxebnQpO+tKU8aS9GLFV2dX+aOTh67aXxZpzTcXmuQdOVRSbRIV8c22z8VuwLHC9cWMvbDa5XuLLWJtWNUWzUafomszlrHIWJJfP1LD2UWtXA1itIGtXse+Sm5yHCnI2kmPX86WNMKYF1YD7iit7+vgmHi2RVeBzOSoFa9uHj7IHd5YGo6iiG63u4kIxnE8fL5t2/R6Pc6dO0c2m91RFXQc56o3sweK3QGuFwdnzU3CzxOxC8Nw06DDxv64w4cP79gfdzu9r637UXY9/vDYPcz22jSjkJxtczRX2lHpuJb3EWq9SQnaCInA3xA/tROO54v8wfRxTjfr/Gh1FQPkbRs73V6sExPlu4vrxMiRkiMG5kTiSRcZAyIpeVoIZvJF/vuFS6yGIVXH4f0jtW2krq8U/+38BZpRhC0SP7VXW23eaHf49akJ5n2fuX6fQEi6QUTOTS4rzTCmr1ISasATgo9OjjPiuTTDkL+bXyTQGjd9LT9V/x6p3ZgIiwcqJQ5lPH7abPPjlWZiCUISM5fsUzKAMlAc66nSeTjrcb7rb99gSgonMomypIzhXKfPkh+Sty3uLOa2ebYNcDTv8Wa7t+1xnaqXE5l1tatpBDlLkrUF3ViDgJKdGNd8a6HOb05vn2A9nSp1W29UspakESqWg4jxjIsxhnOdpNS67EdUXJuitnnEGOZ6SSl1Y7k31oZmFNMMFV+bbfCpY6NUvWtbNi51A76z2KLsWFQ9G6vXxsrlaESKEdfhk0dHyNo7k5x6EDPbS+xqQqU3lXj7Sg9vijaSwrJjcb4d4Mcax7U2fT8TNdjsSiK34mq5w1sx8BM8ffo04+PjCCEIwxDf92m1WkMyGEXrvbxSbi4L//Vf/zX5fB5jDC+99BKTk5OMjY1tKk8f4ObhoMfuALvinUrsBheu2dlZ6vU6rVYLy7KoVqvUajVOnDix5/64G11GvZGQQiSq3A3cZsZKoqeCtKy7EZExTGSufuEuOy4fHp3gjkKJv5m9TGQ0cTqkYwnJJw5Nkttyl3+3AZPJsBJF2OlQhBSCku3y9GoDnaYtdOOY2ctzvK9W5bGJdfLwzGqdZppfO4BlCUKleWq1zh8dnwHglbU6X+72EULQCGP6aYSVEIly11WKbyws86d3zDCe8fikEHxvZZV6mPR+TeeyPDY+uuvAxvVgLOPxgBA8s9qi4tisheuJE4OybzdWOFIykr7u/ZUiT6+18JVOJy7NcP9PFHJUXIdmGPPfzy/QSP3hLCH4mljjfzsywj3l7WreqXKBH6+2aEcxBdsaDnF0IsV9lcKmfrczscC2BWuxHtrUtCKFMYbTusuvTY1sU996scbagawM/eRUsqFnVjt8Z6GJKwWelKwFEW+YLIX5BieKWTZGVPZizcVukHznDVzs+vyXM4v8ylSF+yt794f8yWoXV4phSVxiGM24VD3DaqiwdlhJY2341nyLnzX66HRfAm2INRTdQXauQSOYyrnb+k3LrkU71hSczcepEWpOFjM3bTp24CcopaRUKuF5V7elGRhLD9TASqXCwsICnU6H//gf/yMrKyssLy/T7/f57Gc/y/ve976rbnNtbY3f//3f5/z58xw7doy//Mu/pFrdfsNkWRYPPPAAAEePHuUrX/nKtb/pdxCEMAel2J83vJ0Niq8XW/vjBr0oYRhy+PBh7r333n07rN9KvJXHVwrBB0Yn+Pbi3KbhB01iivno2N5MjQEOZbL80bETvNFpsxYGlGyHu4qlbaQOwBGCJ8YmWBNwsdvDloKJTJa/vDiLFAxJppUSnafX6ryrUqaWDgacbjaHKtem7UrBsh/QiWIKjs1MNoNFYncyUFMGXxkhEnWxpxQvN9s8VKtwoljgeCFPXyVlymtZbI0xrGnDM6tNbCG4s5jb1QC4GcbI1EvOEmp9mpjk7tzXiRI0IGQFx+Z3pyf4yuwSPaUw2hAiuLeQ49emxjDG8D8vLtEIN9upRFrzlcsrTGQ8at7mm5uMJfn9mQn+cW6VuX4wNDZ+qFbkI+ObF9zAQD2MEVJuimrTBhphTD2MObSln+1o3mOuH2wr1SpjUhNgm06k+N5ii5JtDUmgLS36GJ5f63JXKYsgIZwSweVekChiUmK0ZsRzyFkWX59rMJ3zKLt7Wz5Wg5jMDuzNlgIdG3pK427Z76eWOrza6DPiJSTYEVnOdnxakU7aI1Jz45prbTsWgdKMZxwO5x3OtUMilRDvMEh67t4/fu2m5deDva4XlmVhWdawsvGv/tW/AuBrX/saf/EXf3Fd19fPfOYzfPSjH+XJJ5/kM5/5DJ/5zGf4D//hP2x7Xjab5YUXXrjm7R/g9sYBsbtJeLsSu9364yqVCnfccQeO4/DSSy9dMV91L7hdFLv9Njhf6z48WB2hp2KeWV1Cm3VbkY8dOszxwtV7yzbCsyzuL1f2vJ/TuRzTuWRRe3atvmPs0WBA42ftNo96I0BCDnY7TEIkEWSQEICHjeIZ7ZD6Kg/1n5xlYQuB0oaznR4P1SrD/dqtfLkbIq35ynKL8z5Y8ytI4B8EPD5e4wNj21WJomOlBhmGEc9hJYjSEmjaEyUkvz09sYmkTeUy/Os7ppnr+bSDkLUL5/nwdEK8F/oBS35IbgsZcaQkiBUv1tv80qHtGakV1+EPjh2iEUb4SlNx7R1zfjOAIildb4UQiXK2lcy8q5rnubUO3VgNDZmVMbQjxUO1Ajnb4uVGL8mU3aLsiVSRvNwLeWS0wI+W2wgSRcwWgkhrPCkpOslEr4nhtWaf943tLV6x4los9SM2imdCpOcVYhsZDZXmpXqPirveL1jxLO6xssx2Q2wJ91Vz3FHK8MPFDj2lh+850oZmpHh8ssSpcobL3ZCnL/QwUvLARJETRW8bibwZ0FrfkKn9693Gl7/8Zb7zne8A8C/+xb/gscce25HYHWA7boLZwluOA2J3k/B2IXYb++MajQZa6yv2x23sDdkPbhdiB29tSLgQgg+NHeLh2hhz/S5hENK+cIF3VUd2fL5SavjZDKbzBv8cx7lijueVEGuzzXx4AI0hVOu/PVnI89NmG2uL6qKMIWfZm6KgRjH82uQEX55dSPzyRGKMO+gDNJg9KXNzPZ+frLVoRBFT2QwP10pU3EQF+/r8Khf9EMewyRT3nxbXGMt4nCxuHsgZ81zGMx7LfkjWlkxkXHylCXViYfLHxw9zOL+9D9QSgul8ltCxeGVDeaYZxQix86JrCVj2d8/MBYbvYzeMS80lJTd5JSblUEPesjjT9nmt6dONNdN5l/ePFhnNOHxqZoyvzq4lal8y3MzDIwV+YTwh0bHe/TwX6e8/PFEia0m+Od9ICbug6Nib8lylgHZ85X7QjXhPLc+XL9bJ2usGz8YYGqHigWpu2/nQTUvQ9hYCmrUlRwtJ2fW3ZhLiPOrZfGehzVoYI0jI9S9OFLmnnEEIwdGCB0WJ49hMVn5+etQWFxeZnJwEYHJykqWlpR2f5/s+jzzyCLZt8+STT/Kbv/mbb+VuHuAm4YDY3STI1Ophv7iRXm3GGHq93pDINZvNa+6Pu92ya/eLt1qxGyBjWZwolPBtn5c3/PmAyK2trVGv14dEO5fLpb9rMLfS5uJSkyiKmSh7jJRcHHvdoHXjBJ7rusRxPCTkg/d7OJfBSvd9q02DIyRH8+vk6AMjI7zW7hAojZsutsoYtIHHxrfHQN1bLvKNheVti/PgtR6oXFmZ/OflOt9ZXEuJDZzv9PnxaoP/fWaSyWyGlxptXCHQG15WpkzmqZXGNmInhOC3jozz3y/M04pUmiucTBr/yuTIjqRuKzYeo5JjYwzbjh0k5dLRzPp3yBhDPYwJtWHEszdZw+yGSctQwsI3ZkjGhICa69AMFS/XexScRAF9cS3idL3HHxwf5Vghw788OcFKEBNozYi72U/ucM4d7tOmzzx5BWYKHlIIHhopMJ5x+MLZZcquhSXlpoZybRLrkq0wxhAbsLeQ3uMFj/ePFXhmpZMYJBuJHSqO5Fw+PL5d9cukRspbTcAh8SEcz64vW5M5lz84XqMeJiX2qmtvI4TJ8Xtrrzc3wu7kateVj33sYywsLGx7/M/+7M/2/BoXL15kamqKs2fP8vjjj/PAAw9w8uTJa97XdxJuj5VpfzggdjcRt3roYWt/XLfb5dVXX6VarTI1NcU999xzS/vjfh4Vu61QShGGIa+//vqQyFUqFWq1GseOHcN1k0nGMAyJleY7z1/g4qogmxvFAhaCGFeW+Mj9RzB6vQk7DEP6/T6tVotut8ubb76J1nq44Fi2TcF2qZNMiibngSFGMOa5TGfWm75HPJc/nJnm6/NLLPjJtGjBtnlsfJR7N1iTDBYyR0p+fWqCr8wu4GuDnWYFGBLSN5PbXTlZ8gO+s7iGLdh0bkba8KWLC3z62OHh8MdWxdGWgpUg3HG7ZdfhX98xzZvtHgv9gJxtcaqU39WkdyO2nh+HMi5jGYdlP9rWYycEvLuakJX5fsiXL62w7EfDdI131fL0Is2Zto8t4cFqgQ+OlzZtZ1waJhyHtVDTjTV9lRDchlaE2nAobw9TSlwrsf34m4tr/Jt7JrGEYGwH0gUJ4TxVzvJKs0/JtrBlUq7tITmVc5ne4CNnDHSV5nIzxEqP30TWJtSGnC25q7TZQPh0vcd359tc7of4ylB2LN47mudDE0Vqns2j40VOlbOc6/i83lriIzO1bUMPA2RtyV3lDK81+9Q8OymvBjG+SoytH5/cbC0khKB2hUndt2tW7NXwzW9+c9ffTUxMMD8/z+TkJPPz84yPj+/4vKmpKQBOnDjBY489xvPPP/9zT+wOhid+DrFXMnGjFLtrwU79cYVCgWq1ysmTJ+l2uzz88MP7eo3bqcR8K3tYNv79tbyPOI5pNBpDRS6OY+I4plwuD4ncbvjZhVUuLbU4vKW36dJSizcuN3jg5PiOlghBEHD8+HHy+aS/buDNdcz3+dbyCmf6QZKAYQyTwvCufpeXXnxxaNI6yAh9r+OgHQfLcSi7Lp6K6XQ6Q4VwI+4pF6m4Dj9erTPX9ynYNo/UKpwqFa54zF+ot9Pm+K39a0n/1EoQogGR2rZsOrbaMJ7Z/ZJmCcHdpTx3l/bXPC+E4HeOjvOFc4u0ojiJehPJ9n/j8CgjnkM9jPmvZxbQ2gz7v3qR4muzdfKWpJZxiJThWwsNfrjc4rePjnJvJZeaSBt+YbTAfzlfT+xpDEQa+qm2thLEjGacYVkzY0m6kWKuF24iZzvhE4drlJwWz691Ej83YIaQ35kZGZKsi52AL5xdISMlBUvip2kdzTDmrnKG350Z3VQ+/dL5Nf55oU1fDax0BHUd8825Fk8td3h4JM9DI3lmCi4PjxTQZ8NdzYgH+IWJIvUg5mzLZ8FXyTFGUHIsvjXXpupZuxLYrXg7Erv9/v0TTzzB5z//eZ588kk+//nP88lPfnLbc+r1OrlcDs/zWFlZ4Qc/+AH/9t/+2+t+zQPcPjggdjcJb8XQw279cZVKhampqW2L/I0iQrdTKfZ2V+y2ErmBIjcyMsLx48fRWnP69GkmJq4+EfvTc0uMlrcbOo+Wc/z03BIPnNz5rnwnE2bHcag5Dr9XLNJXilYUUbTtHadqt9oxDBTBQYLI4HGtNb7v89xzzw3LwA+6Lu/NpX2BaALfH/YG7nQOtKN411KIARSGU6U8L9dbWBs+Np0SvQ+M7G2YZL+ouA5/eudhznT6LPVDcrbk7nJ+qLw9s9IiUobCBlfdZqSQgK8NvVhTD+I0u1Xx/55dZCaf5dPpZ/iTtT4V1yY2sBZEWFKkEXDQCBWBNhzOueumx4JhTNuVYEnBLx4q8+h4iV6syNqSF56dHRI1YwzfmGtiyWSKueRYhDqJzetFmuP5zCZC9b2FNt9daGN0cvwlgsAY0Otxez9c6vBGy+dEMcNvzezNozBrSz5xpMyfvxoy4iV9miVHkrEknVjx1+cb/Mndo7uaPm/E25HYDXC923jyySf51Kc+xX/6T/+Jo0eP8qUvfQmAZ599ls9+9rN87nOf49VXX+VP//RPkVKitebJJ5/k3nvv3fc+v50hOCjFHuAKEEKg9W7t6deHfr8/VOOupz8O9n/BuZGE9Z2i2G3ERiK3traGMWYTkdv6GQVBsKfX0drQD2Oqxe2KnOtYrLbUdX+22dRfbzdstWPYDWEY8sorr3DfffftSAIH/78xskkIsWkgJKeSiUIF6wMKQjAwdKs4NmOuS6Ag1OAFMZ4lkFLwcK28bzXuWmBJwV2lHHeVtpPtN9s+7oZhkzglR1IkPWprwaA8m5RoYw1Lfsj/urDCuw2c70UUXYvLvQhLJHFwMev2JZE2tMKYimun070wcQUFqxMpnl3p8GqzjyUED9byvLuWw5Vyixm1ZrEfUXYlnUiz4sf04mTCM28LXlzr8fEjCTnzleZb800sIQiEQRqGQxuKZJBEmGRquuhIzrR9nlnpsDedDd5sB7hSMpnbfG4WHIs1P+ZyN2SmcHWfuOu9zjQCxbl2QKA0kzmHI3l3R6/A3XAr+4hHRkb41re+te3xRx55hM997nMAPProo5w+ffqt3rUDvAU4IHY3CfslQMYYOp0O9XqdXq/HD37wAzKZzLA/7tSpU9c8ETnYp9thcOF26o/bzzaUUvR6PV5//fU9EbnrhZSC8Uqedi+kmNtcrm33AsYqudvicwWuyalfa72JAN7jBzzX7+DHCiu1KDEm6f0racXnf3YBHzmMUwuUwROC3x4vcbSYDJhcKcD9cs/n7y6tcKkf4knJh8fL/OJ4edizthv2cmw3frc8S6C3tvulp9nAR29jcq8hSXw43w04llRfCbUZmh9DQpTidDOBMsz1FcuBIpuqcIWtmVsp1oKY//zGEt1YkZFJAslXZxs8t9blX96xPcVCacO5dkgjXL8xtYWhrZOJ1aV+xHjW4VI3hEFFfJN6mjyWDtUOjiAFx+KZlS4f3OPXrRFodhugNgg60d5vnK/1u/HCSo9/XugMXHvQwFjG5pPHKuR2Sck4wDsDBz12B9gV10pclFK0Wi3W1tZoNBr4vj/sj/M8j0cfffS2WLhv9JTufnAr+vTiON40tRpFEVJKpqenr4vIXct7ePcd4/zjj8/iuRZuWvILI0WzG/Do/TcyI+Otg5QSz/OGDv0jwJ/UAv7HxXk6kUKkCtexXAaM4I1Wj4xM1HClFFIkqQQ/XaoTLy9uyu0cqIGDCeGz2uLvm/GQg7RR/M2lFZ5eafF/3Tu9K7m72udzvuPz9bkGFzoBtkzUsHuKOWa7DYxMh1VEovDFOunH2zRlChRSMiqBAMFkxmYh3GwpklDBZBpZm2QLoU7UwFebfX7tiNmxNPm12Qa9WFPeMCiSkYaFXsSPl9ts1BuTUqemlZImmYqlKlXhKlLwT/Mt/uDESBITZ20gndvbHrFksk1LgAXUI01s4LWmTytSlByLE0Vvx4iv0YyF2qW8LASU3b3d2A4I92I/4tnlHhc7IRlL8OBIjvtr2W2vPdeL+N5Ce9uE7Zof8+3ZFr8+89aU+w9wa3DrV9n944DY3SRcbcGOomhYVm00Giilhv5xW/vjLl++fEMI1aCX4nZIirgdSOoAV/qcthI5Y8ym8ne322Vubm7XqbPrQbMbcH6+QS+ImKwVhsMS0+NlHnvwKN998SJL9R5+FFPOe/zqe09sG6h4O+NQ1uPf3DXDbM+nEytGPZeSY/Nnp88NS4dGGKSQOLaD0IZz0uJ377tr03YGauDlTp9/Xm7zbMtPsnoBSAiWBmZ7Af/l2dO8x4p3tIsBhpYxtm1vOndfa/b4/84uA5C1kkndZ1falBybwzmP2V5C9qSAjISOBk9KgjSZQ5OQp6KTZJpqIC8MvzRe4H9cbg3fhxACRfJ7DemwRpreoJP81+8stPjolonRQGneaPkUtqhMQghyluAnKz0+suHxs+0A15Joo4YL3IBcY6Ds2rzZCoi14UjewRKSEc9iyTdgzND4GdJSrBBMZJJj1o8TI+GvR0Xc83VMWrrN2ZLfP15jMrf5pujOUobvLnToxXqTStYKNSOexVRu78MTs33Ft+bW6EQqiSdThlfqPvdWM3z6zpFNBO7ltT6OkNtsU6qexdl2SCdSu6qjBzjA7YADYneTsJXY7dQfV6lUqFare+6PeyfhdjEo3qlH7kpEbuPntNLocfqNRRYWVymPtZgaLe6bsL58bpnvvngBgcCSgu+/eJFyweO3P3In5XwG27ZASAp5j6qVxbEkp8+tMDVWpLZD/93gPd5q651rhRSCqWwGmZKDZhiD2PmGQAroqe2GuVJKzvRjvnCxjv//s/feQXZd953n56aXc+cINCIRSTAnURRFUTQpUaIsW9YEWWNpxl57bG2Na8ZTU7U13qpxeWp3a2tc9no867U99o5kybLEpSQziKQkkiZFggBBAATQRGo0Ovd7r18ON52zf9z3XvfrADRIgASl/rK6yG6+d+658XzvL3y/rmgRDkEz+uWRDwFc9MX48p6htrSwZVlUq1VqtRrVapW3334bx3FaESBdN/ieE8aRCj5VwRUKiqoSUL353pQMcSDlOULUXcGNyTAdPoOX54uMV+oIvGhWwqejqypl22VT2E+0JhgO+/nS1i7+fjzDhbIJ0jOuNxv5TQWP1DWvEyEEP5ktrCB2dlMHb5VjrCkK1rI64JmqjaEq+DVPCqVhMYtPVTyXEeE5V0ggpGvc3R3hpdkivQGdBdulbIvWtmKGR77Chobjes0ipguu1Ojyaa3oYsURfGtsgd/c1YVvyUtnUFf5xc0JnhjPk60vRmGTPo3PbkqskEqRUjJbc6g4gqRPo6PRIe0KyUsZi6ytULJdjIZvreUKDqarDIUNHhxcPG65Rt3mciiNWseKIzaI3c8wlI1U7AZWg5QS0zRbNXLlcvk918ddDVxPC/z1QuyEEGSzWSYmJi5L5JqQUvLjIxd45fgEtmVRKhY5l3mLGzZ38pl7d2JcgUXWUqKSzlf48ZFxelMhcuU6J8czmJZLZczixFiaL31yL4dPz9GdCOFbsrAUqyY/evMin/vIDtQrKO6+XnEkW+K5mQUypo2hqtzWEeXBviQ+VfWIxXIyLiXDoZWNHbYQfGvci6ZpaoPBNbD8qqm7Al3X0XV9RTd5rVbDtm3279+/+H0pmSnXsE/PEVAW/yZc19MLFJLXJud5WCmyFRVVU0laBj6fwWcDBqc0ndfKXlSsarvoqqDTb/CLmzu4cGoOgE2RAL+7Z5BT+SovzRcYK5mUEejKIqlrQlWg1PRRXXJ8wrpKzKdhOmIFWam6gu2xACzp32l6usYMjZIjCC4ZyxICW0q2RXyt9OW9PRGiPpVX5spomkpfEPYmQmgKHFmoYkuPKM1VXQRQdwRSaozmTfpCOq6EguViuoLvjRd4ZCjeFp3rD/n4Vzu7GC+bXjrZpzEUXql/l607PDmeJ1N3UPFO9XDYYF9HiMMlhQumgylVwobaOm5BXQPH5fvjeU9KxaexPe6nK6CTrtcJLotyetFISV1UfegAACAASURBVPR9IHXXy3N6Ax9ObBC7qwAhRJt+XL1eR1VVAoEAW7duJRK5tHbX+4Xridh9UFgekatUKhiGQU9Pz7ojp6PjGV5+a5zhnjimaZJTLfq7Y5y6kKE7Eea+mzZd0Zya5+T0xAI+Q6Vcs3nz9BzRoI9w1EcyEmB2ocQ3XjhBVzxEX6q98zMW8jOdLZMuVOlJvn9dodcCL87meHZ6AQHoioKQktcyRc6Va9zbFeeF2Vxb9KnpY/tA70oZjbOlOq6UXkptlTp7Ib2IHazupLAUa0nGqKqKvkqFv90goC9pMRYsByTEUHgoFmSTD262LEYMk3NVh4rjEnctOkomo0cmqdfrnDx5Er/fj8/nI2gYfDriox4N8n9cqKDRHoGTUiIlhA11BeFRFIWP98b47sUciiLwNfQ168KL/N3XG2Mqu/j5nYkgz04Xifk0Ko5H5HTF68p2JdQcgSXgUKbC3mSQgKZ6HbbJEJbwoorNOdzTG2WyYvHyTAXTsQHJnJAownP+OFu08KsKhqrgCHh9vsJszeFXt6fayJOhKmyLrd2RbbmCb53PYbqClN+rVTQdwStzFX46XyEkIGNLJJ7cTKgxtiskRUvgCsnB+Qp+TeGl6RKbIj7ypke6E3690QgiWTBddicD70vzhOu66KtID23g2kKhWarx4cbGlfMuYNt2Sz8ul8u11cft3r2bYDDI9PQ0pmkSjV4/tU/XE7F7vyJ2l0utnjx5kpGRESKRyLq3+9rJKVKxYFuxvaIo9KUivH5yirv3Da262F8OhUqdoE/nzGQOv6EtRuUUBUPXUIHpbJk9m1d2MiqKgmmv37/zekTdFfxwJoeEVlSuuahmTZuwrnNvd4JX0vk2SY3PDnStsBEDr76s2Zmpqwqa4qUXl6LZwfnpgdW9eptwJRzMlDiY8dKq26MB7umOEdI1aq7blkIETzbEciUhXRJoRLfKjuTvZ6t8ZVs32zoD9AN7VtnWW2+9xbZt21AUpZUStm0brDqDmsu4q6I4XtGbCkjFW4y2U+fcuXMr/IR3Rnx8ejDB8zNFSo1rJObT+PRQkv6Qj8klxyRmaDwyEOcfJvMk/RplW1BxXFzhnRO/pjFZsRgvW/xkpsS/2N5JR6OGbnlEMKxr9Id8zNULpBpjNT9hiWY9ntJywEj5dfKWy8szZR4Zbk8pXwpnCnXKtttKvQJMVDy/XiEhooKhes0dRVtgaCq64kUKXSEJ6ioRn4beGOts0aTDpzFTtfGrCgMRA11VGYn6+Ejv+p8T7wWO42wQuw28a2xcOVeI48ePU6lUWvVxmzev7hZwPZGoJq6nOV2rCOZyIgdcMrX6buaxUKySCAcb3wcpJAulGtlijWyhysRckZH+tTvnilWTmWwZKaErHmidk55khPG5ItlSjcRSeyfh6V8MdMU4fHoOV4g2Uum6glypzthsnlLVYrArSvwyyv7XI8bKtZZdGHgSIJYrG2b08PxMjt/dPcS93QlOzmUoFwvcs3PzClLVxGDY39B482ri4oZOwXZa5E7iRQU/M9jBzvjakU5HSH5o+lgYz3oCporCq/USb2TLfLw3zguzhZaPrgTqrsQWEp+mtjk0+DWFuit4eirHb8f61txeMxro9/tbbiHgdf+Ga/MoxWojAOk1a/gVhc1hg4cHI+iu1+RRr9cpFostUujaNvcJSUnRMDSNTmHgzJS4kPVh2zbpdLpFBm9MBugLdXE4WyFdd1BQeKdQp8Ovt0UES5bLd8Zz/KudK180mshbbuucRgzV07xjMaLpStlKr0cMDSnhaK7Ow0OxVe3GVsNMzWEpp6y7gpLtElAVTCGxJXT5NaZq3lxqjiCoec0cuuLVD/oUeCdfb5BXCBoa2xIBpqoWPlXhl7ck6Aoa71vmZYPYfUBQNmrsfi6xb9++dZGj64lENXG9zelqROwcxyGdTrcEgQFSqRSpVIqtW7eu6+G4dB6VukW1bhMJ+gj6V0/P9SYjZApVktEgrpCcmixgTdaQEuq2w9efP85tu/r5+IERMsUqNdNBUxVCfoMz0wu8fnK6qbeLKwQxCtx+u2T7UIo33pnxdNtcgaoqWLZLvmKyqSdKVyJM0K9TrFokI15qyrQcXnp7Cl1TmUxXGJ8rcfCdWW7d0cO+kcUF93o67+uBkJKq254/natb/PE70/z2zn62hXxkqsqapA6g02+wKx7iZL6KoXq1ZwlDo+566duH+5Pc1RXDf5l616P5GnNCJawri364eCTtlXSJj/fGOZprkCDFqzF7c6FCaJWorV9VmKxa2I205WqQEi5UbI5MlSnaLiMRP7d3Rfj+xRyzNZv+gI+qK6g6LlJ65PSx4Q5646s3z5wt1nllvky27tIT1LmrI0iPIRcjgUCpVGo1jtRMixlHxZIKQ5rgpAwjXZ26sL0GAlX1Sk0UmCxbzFctukOrW+FFdE83TzZq/4bDPs7mLc8pBFr1bsNhP5qiIPGInpBe3eB6EDW0VpMHeERcoXmuvKjmYEin4npEs+YIQMVQvTq7vpDRqE9s6A8KL9qrq95803UHifK+kTrwiN0HUYe9gY1U7M8lrmev2MvheiJ273YuTZmYhYUF5ua8IvPe3t4rInLL5wFQrds88/pZ3jrrjakqCrfv6ufBW7e0NSoA3Ll3kK//8DiRoJ8Ls0UyRZPh/hgLxTo37+hjqDvO84fG+OmJKco1m7HZAkIIYiEfpi2478YhuhrWYLbj8vpbk5wYS7N3Szefvns7c9kSB9+ZoW4LhJDEwn6S0QBT6RKfu3cHxarFdLaMqiicnlrAb2jctWcAISTFqoWiSF5+e4ruRIieZPi6qO9cD0YiASQeqau7K4viVGC2ZvHTTJH9vvVFW7+wuYsnLmY4lqt4lmQSBkJ+vjjSvW6v0UO5Gops354pvKhQ0XZ5eqrgWXX1xHiwL46mKBzP11ritksh8a6ttUiLlJI3LIOz57yXFFVVOFcy+fFsCVsIooaG3SAucZ+Bv+ETezBTYfsqxO6F6SLPz5RQAZ/q+cyeyNf57HCC27u8usQLFy6wZcsWwJM7+d65BeqqFyWWSOqOIOIDXW00iAiB4zgIITFdyaHjb9OpeF2ruq6vkIzp0WCm7rlkBDSVXsUhoxvUbMFAyEdnQG/rkB0IGSukRi6FnXE/L82UWmTZUD2CaDUigSHF+/fuVJAzeRNNgURAY6IkGQrr9IYMLpas1jlxpWzV0TU7YYuWS8865VWuBjYidht4L9i4cq4RrjaJuhqOEdfTAr/e47OUyOVyOU/uIJmko6Oj1b24adOVNSssh+sKvvXi21yczdPXGUVTVRxX8OrbE5SqJl/4+N62z28dSPHwHVv54RvnOX4+jRCSfKnOSH+Ckb4kNdNmfLaAKyXBgI/eZBhVVTh6bo5kNMAbozN8ZP8Q0aBnUZQIGxwcnWbPSBcDnVF+4c5tnJ0p4LiCZDSAz9CYz1eo1m2+9NAektEgmWKNYsWkZrts6okxkS5xbrqAxLtOKjUbn67ylYf3vadj834ioGl8oi/JM43miaXw5D1UBJLX0kX29a+v1smnqnxhczePDrhkTJuwrtIVWD26tBbqQrQRNM/Oy23Nq0kIXpgpEtQ0Ptob46ZUmDezZULLOqRrrmBfMrSmx+lY2eKk7SMaUNCWRPzKlkvBdinbLo3MPOA1FiR8OrM1Z8VY6brNCzMlwrrS2p5P8yJaT17MsyfhNQI0nwt50+FvzmYbunqL3rFFyyXjwpZYe3pfSIl0BPftHWmkUSWu67bJxdi2zV1Bix9UBTN1E4TAdiU+aXnFgfUyZcvrGrZRMaXCJzoUSqVSixxeTncz4df55GCMZxu6f01yV3MEuxJ+nHIdFG++vSGdL25NETZUXpwuc65oggS/riLqzWgfdAUXl0YpJWHj/Y3jbBC7DwYKciMVu4G1cTW9Yq+mFdjV9q99t1hrXy5F5LZt29b2sJuammqlkt7LPC7OFxmbybGpZ7EuTtdUhrrjHD8/z0cPlOlNtROJ23cPMtKXZG6hhC5Ndm7dRDjoEYaJdBFD15hOF9k3EsFovP1rqkKlZpGKBrkwW2ilSgOGSqFq4zSiVEfHMjx69zaK5WYtnmT7QAJHSMbTJTriIU/yRNcIBQyyhRqnp/KkIoGW3EnQp/H2eJZz04X3dHzeb9zfm8QRkh9MZReFbvFInaIoKFKuy+x+OSKG9q61x7aEfczXFjVBqq7bFo3TFKUhmgzPzxS4pzvKQ/1xThdrlO3FxgpLCEK6xi8MrOzgbeJg2rOxWi5b49cUbBNsvPSl2hAotoUkY9rsiHukq+4K3sxUOZarMVezqdgu4WUEQVcVpCsZLdS5uWOx6eSNTBVHSGJLHB0URaEroDNesduEeaWUFG3BgY5g62+etp8nGRMKLY7bLyVaR51nJ0vM1Wz8tTKf39NPUIWnJ4uUTBchJUFFcm9UEK0XmSxlW8Sw+czSdb1NOHppVHBb0Ef31jijRZuCLbi5M8T5osl83aXkgGUK/IbKpzfFGYh49+knh2M8NV7gQsmzRrManTTbY/5WbWTRckn6vaje+4kNYreB94KNK+ca4WpG7K7WWNdTxA68xeFKiNxyXK39mUyX0FeJCjTHn11YSewAOuIhNvXGKRVyLVIHkC3WEFKiqyr+JWQi6NMp171I2ny+CnjHIF20UJ0izx8ZpyMSoGY6dCdCBFMGPalIKxJSrtlcnC9y87YeAEIBr5j9/EyeSMBoIwOWIxjsjHB0LM2u1IfrDfSjvUlemCtgu67nqbrkPEsJO2Kr15JdK9zdEeJQptRqkGiK/kogqC1GvHTVE/zNWw6dAYPf2dXHy3NFji5UkcCtnWHu64mR8K19TRdtF3WZyp6UkgVLLIliSoRUcCUYDVeIwZCPku3yp6fSZE0HTfHEeKuOwBY2A2GjrRmhmapc+sI4WbFWTYH6dc9dwhbe/GhEDPckAzw6dPnu1R9Nl/jJTBlDhYRPJV2FJ8byPDoc52t7e8jWXSSSzsBic0bdFUyULaSEwYiPoKa0ooFLRaQrlQr5fL71e9h1CTX26UbdoKT5mVZqdPoVtiVDRN0qpZLTIoT39UVwRZHTuTrdfg1bCmqOwJVek03E0Hhs80ox5GuNjRq7Dw4bNXYbWBPXK7H7oGvsmkRufn6eer3OxYsX103klsNyXLLFGl11i/AVpteaUBQFv6G2irlX+QTGGg9YVVW4c1c/33puDiFki1jpqkq1btMRC7YJxnYkQixMLHjRCd3b5tvjWY6MF7n7xi4m0iXeOjfPmckcvckQ/mUEwHZdkr5FPS+frrF7Uwcvvz3F5p5FWR3bcXGEZKQ3Qalm4Yrri9BfDoaq8Im+BM9M5bzUMh65caWXWn2gNwnV0vs2n5RP5+GAxSEtSM5aTHkGNZXgkmtDNuy0Ao1oT8zQeHQwyaODa0folmMk4udkpv181VxJzfGuT5VmGtazF7MkRHUFXVV5aqJApu4QXRJxqzkCU0hy5qIciJRejd5guP2eSfg1zpVW3gdSSnyqwld3dmA16ur6gkZrvJojuFAykcDmqL9N5y1Td3hptkzcp7bSwSFVEjVUnp4osCcZaEt7Ahycq/DcZNHTKARQ4GP9Ue7pjbRFAi+FZh2gZVlETp+mM+ZDuA4z2So4NsKxma06vFT2I5CENDAUDVNqlC2T/UmD/oiPLXEfftfEtuUKO7m1cDWesUKIjYjdB4SNVOwG1sQGsfOwVkQuHA7T19fH8PDwmt/Nl+vMZssEfDrDPfEWcXJdwbNvnOMHL5+gbtrEYuPcsrOfz35kJ9HQlct8bOlL8JNjMziuaNOfM20HQ1MZ6VtbuuTGrd2cOpNgOlNqiK5BKOBjqDdOyG8wn6+2pEs0RWFLf4L5fJVdw50cP5/m7fEMW7qD3Li1G1VVSEUDjM0UeOP0LPfuHWxtR0pJqWrz0f2p9u1v6WJLX4yZhQo+Q8N2BHXLZWt/nKppEzA0NFV84IT+SvGxngQKiqdr14gQdQcMvjjSRVfAYKH6/s1FSkmPDv929wBzdZtX50u8Ol/CvyRaB14qb2vU/57spm7vivDshXlMVxBo1OeVrEU7tKahWKPhE0WBgK4S0hWOLNQILakFC2gqPk3FcoXnrxrw6szKjmRLxMdgyGj50ALc1hnmcKaKK9vdPaqOoCOgMxz2te2vEILvXMjz3FQJ05VoiqeP95nhOPf3e/Z6p3K1hhB0OyHSVU98+mzR5KYl6eDRXI1/uJgn7tNbXcOOkDw3WSRqaNzYuT5ip6pqK12r6AajbohjORtH6Pg0hdu6Q0wbFl0Bl5hPQ0iBcAUdrst8zSGiq/SqFvlsmXQjQug4i6TeMIw108JXg5BtpGI38F6wceVcI/y8Erv1plbHx8eRwE/fnuSFw+fJl+psHUjyyTu2MdQd47svjvLiWxc8o3QJHfEgX3n0ACP9Sb7z4il+8tY4sbCPRMgglohw6J1pZrJl/s0X7rwicWBFUUhGA3zy9q089dpZwgGDUMCgXLUwbYfP37+b0CW6J1VV4bbtHWzedgMzjU7Vga4or7w9yWsnp7Adl6lMGQVJ0K9zw3Anm3ti7NncxY+OXuT+m4ap5eba0qh37ernR0fHGZ8r0hELYDkuhVKN3Zs6GepsF7zWNZXP37uTZw9foFAzmUhXCAV9zBXqjE7muXdPP0J+uCJ24J2Xj/UmuLc7Trpu4dNUOteQn3k/59Qb9PGpwSSTVYuJitUotvau0ZCu8vlNlxY6vhziPo1P+Ku8oYco2oKaK6gu8bkFL40qpYKhNgWWFbZHAwiZR13S5qEo0B3QydRtaq6k6niSHjcmg3x2U2JF9Gkw7OMT/TGemy4BAnXJfn1xS2rF5//mzALPT5daIs82UKs5/M3ZBUKGyh3dEUwhUZbMfunjR7LoZdvEizNlgpraJgWjqwphXePF6RL7O4JXVIIhpeSVokquVqMj5FmhmY7gmfEiRcvlxk4vra8qKqquous6nZrBlFR5aBUh8OaYzXTw0rRwrVbDsixM06RarXLw4MGWPMxSErgaITSMdo28DWL3weHD97RciY0r5xrh54XYNYlcNpsln8+jKAqpVIrOzs5LplalhL9/6SxvXyzSEQsS8OmcGEtz6J0ZdgylODeVY6gn1hLizZfr/NG3X+df/+LtvHzsIpt64lQrFSzbQlNVBrtiXJwrcGo8w74t3Ve0D1JK7t0/zGBXjNdPTpEuVNkz0sXtuwcY7Ipd8rvNh3EiEiARWUyTPnTrCLs2dXLs3Bznpwu4QjDYHeHAtj5GeuNomsqxCxkMXWUi1z5mNOxj/5Zubt7eQ6ZQpcMIcu/uPoa6Yqt6wW7pi7OpN8YTr5wjEQmgqp4F1J7hDhxXMjpTYXjoig7JdQNDVeh/F1HYK4UrJT+eKfKj6TxF2yuY/+RAgnu6VzrH+DSV/2lnL0eyZd7IVrCEYE8ixF1d0aviI9qlujw+FOfPz+SoO7LhnuGF6JpNG16NnIKuwD/d0kHcp5Fo2IAtdYDQVIWoT2dbQOeXRpIkfO1NJMubsj7aF+WGRIAj2Sol22U44mN/MrTCNzVbd3hxttzSm2uO0BRo/ttzC9zeFWZzxMdLrGz+aqaDB5Y0JUgpma3aJH0rj2FAU1gw3Ybw8/qX3umKzZSpMhzV0FWFsuUyXrKo2A5FS3A4LRmJ+ekM6i1NPQUvSrgWFEVpkbLV4LouR48e5eabb279vpwELhWQbkYDpZQcO3aMr3/960SjUbLZLH/4h39Id3c33d3dDAwMtMa8FL797W/z+7//+5w6dYqDBw9y6623rvq5Z555hq997Wu4rstXv/pV/v2///eXHXsDHw5sELsrxHrfFn9WiZ1t29i2zalTp8jn86iqSjKZpKuri+3bt69K5Cp1rwg60mgwmM9V+POnTvDkq2OkYkFsJ8HmvgTdyTD5cp2/+9FJPnX39jZ3hUQkwNR8iadfO+N1Ba5CcHy6xjsXs1dE7Jaez8193jyuFKsdU0VRGO6OMdy9NjEc7IxweirfWK4XUbccEmE/d+3qR9M8PUTLsta89lRVwe/TuWt3nydBISEZ8RMN+nFcwcmzaexVdOGuBT5sKV/w5vxno7Mcy9VaQrezNYdvnMswVTH5VM/K9J+hKtzeFeX2rqtvGWgLybfP5zFUpUGcPIcJpEfpll4HH+mJcGMjlfnQQIxvnc+hKbLVBGE3rLseGYqvqKlbCz1Bg4cHL90UcSJXxXKbIsOLUBo/2bpLyRZsiflJ+jSmKhZxn0ZIVxBSIWcJdsb99C0hdoqiENLVVcmbK8GnKVekbwdwsWS2xq7ZgtP5OrqiENZVqo7EFoKxoomiQGcjMl+2XW7veffWYcvvAU3TCAaDLXmmS+GWW27hscce4+WXX+bb3/4227ZtY35+nkOHDnHo0KF1Ebu9e/fy3e9+l1//9V9f8zOu6/Jbv/VbPPfccwwODnLbbbfx2GOPsXv37svv4M8wPPmiD98zbDk2iN01wvVI7N4NLMtqpVabRM513UsSuSbGpnN884UTjI5nQIEdgyk+dvNmvvHc2xw7M41hePpVZyYXmM6WuHuvF1ZyXUGpaq1oHoiEDCbTS4rmlfbUjiskgVXe9i+Ha3lsXVcwPl/k1MQCrhBs70+yrT+BoWvctLWHE+NZ6ks8Xh1XMJer8ombN7XpmLmui6Zpa5K7fNmkMxZq68IFL1UrpHxffGSvt67r9eJUocZbC7UWvW6Ur2FJ+MlsiTsTHiESUvJ6usxPZksUbZehsI+H+uOXNKh/N5gWOjUhsAXYYlGzTml0EjSjZIYKnxlefBG5pSNExRE8O1XEdrzXBUNV+MJIkp3x1ef4bq99u/GesNYZVxTI1Cy+c67MbMWibLnMV20MVSGqKDzQFeLhwdiKa+bOnjDPT5boUBe7oaWUFCyXe3rDV9ydqipKqy5xtmqjoKBrHv30ay5SKqjAVNkm5dcomIKArnKge22LucvhvUhTaZpGd3c3Q0ND9Pf380u/9EtXPMauXbsu+5mDBw+ybdu2ljD1r/zKr/Dkk0/+3BM7aN5nH25sELtrhOuR2K1HW281Irc8Ivfqq6/S0dFxyYfX+GyBP/ibl9E1lcFGOmsyXeTf/enzbO6LEwka1EwHQ9OIhzUKFZMLM3kGuqJIwFllnqbtsmtTJ2cmc9RMB9eVzOZqzJWz+A0V15Xs39pzxcfkvRzbSx0DxxV8/7VznBzPEg4YqAqcuJClLxXmlz+6k65EiMfv2c6ffXuCqUwZJGiawkf3DbFrKMn8/DzZbJZcLud1XDbm2SwMb9bq+P1+NGGSKTp0JkLouo6qqigoXkPIMtmVDbTj2cn8CpeIJrmzJRwvmIyg8Jdn0hxbqCHwiNWJXI3RQp1/MtLBnd1Xzxx+xtHJ2V7hmmzNpP0lRuA1kySWac59tDfKnV3hRv2fwnDEt6Z12dLvXSk2Rf0YKljCm1dziGYGM6QpPDNRYqJskvJrdAR0bOE1cYi6yScGYvhWqYW9ozvMWNHifNFsReccIRiK+PlIf5Sq7fLabJkj6Sq2kOxIBLi3P0r3GjpzWxv6fgJPaLl5Gwgp8WsaQxGDdM2laLnMVR12JgPcPxhvafkJKSlZrudlu86XxquhOXqta+ympqYYGlqszxgcHOT111+/ZtvbwPuLDWJ3jXC9ErvlWA+RW2s+l3p4fe8fR730RmIxjRWPBChUTLKFGh2xADMLldb/CwcMJuYLbBlIEgn6cJ32/XVdQc20uf/AZm67YYA/eeINTl5I4wqBz+ejbjoMdsfIleoM91xeW+tqYq1zc3wszcnxLMPd0daxSgGTmTKvnpzmwQOb2NQT55Gbutm6awcLuTxYFSr5cQ4dGiOVSrXOg+u6rTGEEG3q/pZlMZQwGB1PY1byIAWu6yKlJFNx2dppMDVxkUJuoa1ou/lzqUjgzwNm6ytdG2CR3GVNB91ROV6uNYSBvWOlaZ6J/TfHFjjQEWqJ2l4JpJTM1x1cCb1BHSHhpONF11RY4cABjftYgl9VVz1vfk29ZBRRSslkxWasZKIIF+VdyOFsifrYGQ/wdq6OZJF0Sjzh5P3JIJNli4Rv8doyVJWkX2GmpnAsW+WOVdKdCrAv6Sdft8nUHbpDOvf1J9mdDGILyV+cTJOp2UR9Gn5N4e1slZO5Gl/e1cVgZGWquTNosN1vM13ztPJcAS7gSEl/yKA75KMjIEjXXH5zXw+JwOLzbnShyosTRUq217wyFDF4YDixJolcenyvBrG7lI7dgw8+yOzs7Iq//8Ef/AGf+cxnLjv+WuUjG2CFjuSHERvE7hrheiV2tm0zNzd3RUTuSucjpeTwO7P0dYaX/R38hka6UGV7fw+RgEGpahIO+FAUsGyXibkCX3n0AKcnskzMFQkFDSzbxbJcHrp9GzuGOhBCEo8GScYC1GomHckII30JYiEff/XsMf5jz70ko+sTsb2WNm2HzszTGV/ZxdebDPHW2Xlu3hynkM9h1muMjR4jkUjQ0dHBjm1b2gqzmwLFTaiqSiAQIBBYXLz7+yGS6OTpwxeZyVWxXUEiZHDXTb0MBsp0dqTw+XxYlkW1Wm0TdW3KOCyViFjr53rq1LtaC1Hc0Miaq5M7gOGQwdGS59G6nLxpjXthtFDnxtT6pDiaOJWv841zCxQs4cmWaAp3doWRKPg1ZYnDxtLWBI84xQyVjHnl6XXLFfzV6SynC2ZDJ05imxHqU0UeHLh0o9BSqIrC1/Z281/enudUvr4YqdMVdicD3NwVZrKSX3mOpEQFLpYt7lgSXBdSMl22+LuzC2RqNn5NRQNmyzYvTRbZFvNzeL5CuubQFVwkVsmATtFyefpCnn+5d/Xa2hsDNrcPx/nBeJGzBZOEX2FTyEfC713LBUuyKxVcQeq+dzZHzK/RFdSRUjJXtfnb0Qy/uqer9d3V8H5E7J5//vn3NP7g4CAT9fDl0wAAIABJREFUExOt3ycnJ+nv739PY27g+sH185T+GYOqqtcFsVsakZudnSWdTtPT00N3dzc7dux4V+rm65mPpikIIVm6DhqaSjTkZ6FURddU9m3pYDZvM50tUavbDHTG+KcP7efjt4xQNW0OjU7zzsUMsbCf23cNsKU/iaIonJ/J4biSO27opVar09m5KDEhijUOn57l/ps2rVv25L2ep7W+X66ZJJd0ylqWRblcplKpMJEucfacRn9vN4FAgHvuuec9zyFXtVF1jd5UGE1TUSTMFeqkNAiHw8Tjl45kLu3eM02zpeyfy+VaJLBJMFVVxe/3t5E+VVVxHIdardaKBF4rXM26yI/1xRg/k6ZJkxaTn16N2oFEgDdm1yaSEq7Y5ux8yeTPRjNI6dXKKYrnbfqDiQJCKEQNpSXKvAgFvwpdQQMhlrfcrA9PjucZzdeJ6CqKoiKloGJJnrpYYDDs44bE+usFQ4bGfzjQx8WSyZFsDU2BHYkA22J+zhbMNevvBBDWVQ7NlTmcrpKt2eRNh5ItKFkuQV2lP2wQb5Cn2arNjyeLnCuYLQ/bJppize/ka5xaqHJDcuWLlKLA7o4QOzvCfOvMAhdLJoaqUnMkFdsl4tP4+NAiqRVS8uJEkZhfa3UDK4pCwq+TqTm8OVfmgeG1m6yuBrFzXfeavkTddtttnDlzhrGxMQYGBvjmN7/JN77xjWu2vQ8LFGWjxm4Dl8AHFbFbSuRyuRyappFKpeju7m5F57q7r0wO5N3M9yP7h3nxrXEGGl2DUkgmMyXShRrFmsXLJ2bY0hNhz0gvnYkQriv4X7/yMQYbXaSRoI/7D2zm/gObV4xfrlnemBJYsrxVajZjswX++InDfP+18+ze3MEjt29h6BKSJdeyMaU/Geb0xBw+bGq1GoZhEI5ECMcS7O/s5bZb9ntetRcvvudtzeaqHB3LMtITayswL1YtDp7LcMOWwUt828OVdO8tN3tvkkDLsjh79mwbCdQ07bKRwA/SPunWzgg/mS0yXjZx5OIV5VMV/tnWDjQFNhuCSWvld2WjC3lklTTgpfCDi56zQtOlwnIlecvTmZMoZE2BAvg0cIW32DQv0/mag0RyINXubHI51B3BwXSVkN6ewlUVQFH40VTxiohdE8NRP8PRdkmaLTE/AU2l5og2qRRHeBp8o9kaL9UdkJKpitU6BhFDRUgYL1mMKApRn0bMp3FovkLUp7UtunVHcL5oYroCR8D/GM0yEDH4Jzs72yJqTaLlU1V+ZXuKU7kaxzI1HCG5rSfC/s4g4SU1qCXLpWS5dK2Sco36VM7kTR5YW1f9A6+xe+KJJ/jt3/5t0uk0jz76KDfddBPPPvss09PTfPWrX+Wpp55C13X+5E/+hE9+8pO4rsuv/dqvsWfPnvc05w1cP9ggdtcI62lUuJKx1iIflmWxsLDQSq0uJXLLI3LNIvxrOZ8mDuzs4+9+fJLR8Sy9qRAV02FivkgkaHDb7hFOjc9zZGyBhYrgF+7cyi8/sOeymnEA09kyPzw8xqsnpwgYKsmQxs2hGLqq8tOTU+RKde7Y3c9QV4SxmTz/5TuH+J3Hb2W4O0rN8pwkDP3qkYilx8JxnJamXy6XI+TYFMs1BruT9Pf3oygKluMyna3w+M0Dqz78F0p1zkznKddtBjrCbOmNY6wj8nhmukDQr69Y5GMhH+drDrmKReLKlVzWxGok0LZtSqUS+/bta/vsaiSwXC63/X45Euj3+1vNIlebBBqqwr/Z08dz0wX+ca5EzRUMhj0h4l2JIKVSiZ1+wVGhkbfcVoRNSImQcHNHuCWVsV6cLZr4Gs0BQkrylrssOucRTNMFrfHfEjAFKHjpzNF8nf9+eoEv70iti9wVG53RS10gmoIlPlVhttaejq7YLkcyVSbLFh0BnVu6wqQC61sydFXhn+3o4K9GM+RM75g5AoQU9Osu8zWbVEDnQslEVzwZk7rjUnclYUNFCpguW4R0lZLl4krJA4Mxzpcs/JpH/s410sm66qWuu4Ma2ZrD/xjN8Jv7e1rHZCnRMjSV/Z1h9neu3fWqq0qjbnAlQXMF+PVLH+sPmtg9/vjjPP744yv+3t/fz1NPPdX6/ZFHHuGRRx5513P8WcXPQMBug9hdK1zNQtSl5GEtItfT08POnTsvuei9X3p4Pz4yzl89fZRELIiQ8M7EArlynX1butm/rZdQwCAZ1ilX69QcjX/+yRvpSly+Pmk6W+Z//7vXkVIy0BElW6yQLZn849uTdCdClOoWiUiA/g6vWaErHiJTqPFfv3+ESNDH+dkirhDcsr2HLz24m0Qk8J7OkxCCfD5PtVrl9ddfRwixwmVj564czxwaYyrrNYromsLDt25mz+bOFeO9eXae549OoKmeP+3hs/MkIn5+6e5thHyXnme1QVpXg6IouFeYKryauJJIYNPfc2k6uFQqkc1mWySw6QMqpWylfdf6UdX1peP9msqnhpJ8amh1X1cd+NVtnXx/Isd42UJTPAmN+3ojPD68fi/YJnyq13iB4kWelp+epelgiUfuwBMcDqgQ1D2PibeyVU7kQuxLXf7YRgwNKVk1ymcLSe+SCNWFksl/O5HGdEUrWvjsRJEvbk9xS9f6pEBGYn5+98YeDqcrTJRtUgGNfXGDPz9SJRzUUICKLVoEV1e8eUgpkUKQtkTrOCgKPD1eIBU0sIWgbLmUTNvr9hYwFPfOdSKgkqk7XCiabFlD4uVyCBsawzE/sxVrRS1dyXa5o+/SHdAfhlTsBtbGho7dBtbE1YrYNa1qxsbGqNVqV0TkrhUuRewyhSr//ZljdCXC+A2Nzb1JUrEQJ8YzFGo2voY2naIo+A0NSyqMXsyui9j9w+tnkUBvKkIiEuDgyQkyeZtS1WI6U2K4J8Ydu/rxLU2rVE1eGZ2lq5HulULyzsQCzxwa4//61x8H1q7XmkiXePH4JGemcwR9Bnft6mX3QJRKMU82m6VerxONRlFVlQMHDqyqRL9jMMmWvjhzuSpCSroTK7XmAObyVZ4/OkFvMtxG0NKFGs+8Oc7n7tx8yQVjuCvCxXSZWKh9Do7rWUPF1hlp+aCh6/q6FrRMJkMul2NgYKAt8rdUzb9JApvjXi4dvBoJlFLyj5k6388GkLk0AugNGjw2HGdPMthKpV4p7ugO8ZOZMkFVaUv/NqEqtLpN9UZjRXQVuQ2J5NW58rqIXUhXuakzxOF0pVFj521ESG8/728QFkdI/uJUGiFlS/YDPNL1t2cWGIn61x25i/t1Hlgidlyr1bAlRBpkrrmfChAwVMqWwJWSYqMTVWukicOGClIwWzYpWRo1R+AIiS1cOkN62zyFhIW6w5YlJaVXSrQeGIrzt6MZMjWHqKHiSo/U9Yd97L2MX+0HHbHbwAY2rpwrxLV2nlgtIieEoLOzk/37978nIqeq6lUhm5fsBH1nBillG3mReJEqx5VkC1V6kuHFPr91+pgKIXnrbJqBTm/xCfh0bt3Rw1y6gBEK8+qJKT6yb7jN19VxBaNTOap1G0XSamRIAXO5Cn/4zYN87ZObVt3emakcf/ncCQxV4lNcsuksf3H6PJt7Ynz5wd3s2rWLUCiEZVkcPXp0TXsh8ESCm/NeCycvZhuETjKeLjKZ8eyaBlMRynWLhbJJKrK2tdZIT4zD5zIslOokI36vA7ohdryrP9Iiu7YjODtb4NRkHssRjPTE2D2YIBr8YH1YrxRND85QKEQodPmFdrV0cKFQaLN6Wo0EvmX6eD7vpeAMxUuITlUkf3l6gf94oJdA8N0Ru4cHYxxfqLNgLe/G9Wr23AY5UGiSm9XHURWoON6886bDq3MVLpZMOgI69/RG6F/mNvG5zQnSNZvJio0rBFIKHOChvmiLHJ7O16naYgWRNFSvwePNdIUHh9obcSq2y8G5CkfTFVRF4ZaeMLd2h1eVgOnzCbK2S9yvk/TrZOsOPtXb15ChYjsCV3pyL4qiENQ979i640mV6MD2RICpsoWhQr7ucipTpTNkkAzoqNBmm/Zu0BUy+NKeLo7MVziTqxPQFO7oi7C3M7Sq/t5ybBC7Dycucat9qLBx5VwjrJfYLSdyuq6TTCbbInKjo6NEo9GrEp1zheBHb47x/VfPslCssmO4k899ZCe7Nq1MDV4Ka+1boWK2WYEBpGLB1ncsZ5FYClegKCo7hlKrjmXZLkfPz3Po9CxSQrpYpScVxKd6l62qqERCOqlUhMGuGNlSrY3YFaoW+bKFT9eILotkRYI+pjJlzs2W6EwtFp9ZlkUmk+W/Pfkm9XqdWCiAPxxioK+HLZv9nJ8tcDorsA2TLlcl4n93C/ty5CsWmqbw2jtzFCom4YCBApyaXMByBNli/ZLELujT+fRtm3jpxAwzCxWURt3SHTu6CTkLgEfqnnlrgslshWTYj6apHL+Y5dRkjsdu23TJ8T/MUBSlFQlcDwlspoOrdZMXT5UQwqtpE0IgkSgSagL++vAZHgybl4wCGoaxaiQwamj83o09vDhT5qfzZcZK9op7SkqJVEBDQUVZNYUqJOxKBDmdr/OnJ9Itj1MpJS9Nl/nFLUnuH1i0PQvpKl/b282ZgsnZYh3pOMSKc9y3efEeKNrumh23CrCwTGalYDr88bE5cqZDQFOREr57doGfzpT5zX3dhJZ5094UkTxfh5oj6AoalCyXuutZbPSEDCqOS8VxiPk0T1y5scum650HU0iSfp2JkkW+LhBSknEFVcflYlFhKOpvCROvhYWazblCHceVDMX8DER8K8hYwq/zsaE4Hxu6Ml3MjVTsBj5obFw51whrETvTNNsEgVcjcusd60ohJfw/T5/k8Lkc8bAfv0/jyOlZDp6c4ne/cAf33bh69OpK5rO1P4kj2h/8sZCPvlSEc9O5VpoxW6xzZirHzTcMMp0tk4oG2poaqqbNHz3xJuemc0SDPiReWvKFIxe5/8ZhAobWeuDP5as8escWpjJlJjNlehJBVFUhW6h5em7RlbU2UoKuK2RLJsVikVwuRy6X82RqjAhSC7B7R3uDQ65scuriAqen8uzd3AkS9m5KMuRbn55YsWqxUKrj92n0JkJtY/enwvzo2CTFqknHEg0+Q9eYyJQYncqzvf/SC0wi7Oex2zdTrFpYjiAWMvDpGidPZZkv1snMmlzMlBnuXFzoA/EQubLJq6NzfOrWS7T6/ZxAURQMw8AwDBYwkGoFHYkQou3eVKRk3hdn797uFZHAarXa9nvzXmk2fyz9uSPk485tEf7DsRylRvBuKSWQQrI57mdT1M+r8xUCWsMmS0rqrqerd1tXiP/85gxCyrYO1Lrj8lejab5/IUfCr3Nff4R7eqPoqsLORICdiQDVapXz1fZ7uTtoNOrqVhIUCfSH26O7P7iQJ2+6JJfUo4UMlZmKxU+mSjyyhDRKKen2wb8Y6eI75xYoWi6dQZ2a43XEdgR0uoI6T13Io6uLB0M2GlWk9MbWlGYdokRVPdKrNP4RUmK6grmqzehCjbNljVS+xuZ4ABV4caLIK9NFGiWOXolE0ODjmxMMx/zrishdCu+HQPEGrhXkRo3dBtZG88ZejcilUil6e3vXXSN3NYhdvlznqTcu8sKRSXaN9LQ03jrjGplClf/8jZ+yY6iD3tTlrZEuNZ/9W7rpSUaYy5XpToS9zwLJWIC7kwME/Tqvn5pmZqFEKuqjarn80ROH6U9F+OLHbiAeCTDQEeHZQ2Ocn8mzqdvzk3RcQUc0wOujs8wsjLKpO8ZQZxCrVqOvN8Lj9+7A0DReOHKB10dncIXkzl19mK7kwmyhNT8pJbZtUyxX6QzrWJU8xWKA4eHhVsPDzEIF//F2cdWa5fDKyWlyFc9U/GK6xHBnhCPn0kzoVe69e+3jZTuCH751kcPn0qh4huZd8SCfu3MLvUkvgrRrKMVsrtqWEpVSkq+Y7OhPcLbR+KGv43pZWmd3YiLHE0fSBIIVzqbraIpC0NDpii+Sx0TYx/RChYrpEL6E8OrPG3yq0qo/W+v/N0lgOHzphoKlkUDLsjBNE9u2qVQqnC07SNcgjKQitSX2ZhIdcKw694UkdlzjUN5Ba8yrN2jw5R0ppisW1jLx5JrtsmB6jhZF2+sq/buzOd7K1Pitvd0tu67l+yakxKdAVNco2i5RY1EapeYIAprKzUtqzGwheStdJepbSYYihsprs+U2YtfEtkSAf3tzH3NVG1dCT1BvvfQJKXlzvsJc1SaoqSgt31iPiQ1G/BQtF0WBVECn5giEVBiK+EgFDXJ1h788PsdC3UVVIF/TmT2RZnM8wG29YV6eKtAVNNBUhfmKxUTR5J1sjVMLNQajfj6+Kc5N3eF3Tc6uxkv4Rir2g8NGKnYDK7CUyJXLZY4ePXrFRG453guxc13BXz97nCdfeYex6QXyZZOFis3uTR34DZ0T4xnqpoNpu/zzP/gev/jRG/i1X7ixrQHhSubjMzR+74t38V+fPMyZqRyaCq6Q3Ly9l68+eoDpbIn/9PWfsms4gePYpJJRphfKPH3oPC+/PcnOoRSxkI+5XJUtfQkURaFcs3j+rXHS+RqapmDaLtlijbl8ldtGovy7X76j1Xzx+ftu4PP33dCaz/4t3fzOn77ATLpAwADbcbBdlVQ8yI7NXdx7YJCORJSurq7Wd7riQcIBnZrpEGwQndHJHGNzRaSUDHVFqdYdjpzP0BULkLYrFKom8dDq6Z8fvnWRg2fmGe6MoDYW1FzZ5P/9ySi/8fBewCNju4ZSTGRKLJTrnk+ogP6OELuHO5jJlhGCxfbIdeDMdIHnjk0RC2ik4gHSFZe65XLoXIa7b+gh3iCA3gLmCUpvYBHdAZ2UX2O+JlhKW6T0HFzv6VmdzOVMhwXTpcOvtboql0YCl5NAO1fDqKTRVYUQUKub6IYPVZFYrhf9EY7DPX6LvXGL+bqL5trELYfpkxOccYOYVgBFU1pkJGd651JtdLT6NRWfKjlTqHMsW+XmJZ2tze+cztf5+jsZ8qaDlFBwBFVbJdQgdyFd4XMjSY5kqmiKwg3JAH7NM2BaLcalqQplu72md2k0S1UU+sIra1NVReH3bu3nPx2cJlu3wfVInaEqxH06UUNloe42eR6qorAp6mtZfZVtl4Waze6UJ1YsSpKuoM6FQp3xQp2IX0NTFXI1m/N5k4CmkAjoVG1BSFP4h3MLhA2VHVfoJLLaPr5buK6L3/+zWRqxgWuPDWL3HmGaZqtGrlAotEXkcrkct99++3vexnshdt95aZRvv3iKvo4Is5kiNcNBVeDo2XkUVcHQNYKNurRExM9Tr51FAX79sZvf9Xy7EiH+ly/dy1SmRKFi0hUP0Z30FpKXfjxByG9gGCq2bTGfr/DWuXkiAR+m7dIRC2I7LkfH5umKBxFBgx8fm2A+XyPiN5BIapZDMODjpi0pcvkSgWVRplqtRjabJZvNUiuV+I0HBvn6qzPkqy5Bf4iBZJjhnji/8eh+ZDW7am3Tvk2d/H+vnaMrFqBcd3jh6CQ10yHg8/w8Az6NoF9nrlAlIG2eOTzOeLqM6Qh2Dya5d3cfPYkQpZrF4XNphpaQOoBkxM9EpsLJiwutv92yrYtE2I+uqziuIBIwCAcM8hWTgY4whr7+FJGUktfOpumKBig6ZQC6Y0EuzJcxdI0L8yVu3Ow5dlRNh2jQ+NBF6661t6WiKHx5e4r/8/g8lpQoctHtoSeo87G+aNvnS7bLn49mOJWro6mexMzeVJCv7Oy4ZDH/SEPc15USrdEwYTQ6JjQpuXswwXD/osajLSRvZ6ssmC6dAY0DCF45mW2lkEzXk09RmrN1bCrVhgiwVHh6dIpYwbOPE0JgmiZn5vP86ak8qqoQbnTM+jWFki3YlwpyS3eIl6fK/N/H59FUxZunAp8YitHh1yg7guAyfbeKLdgSWyQnrpSczpucKSs4mSo3JANrpj17Qj7+6L5h3pivcK5gEvNp3NUX4afTJV6fq1B1XCwhQFHpDHrp2yZydZeBkN52fSiKQiqg8+Z8mVt7vfM2VbYxVI+AQlNWRSHm03l5oviBEjvHcTCMD1dD088KlI1U7M8fLMtqea0uJXJ9fX3ccMMN7XU4V2nhedcdtrbL3784SncyhK6pJCJ+MoUauqZSdEyEgK6kzxtbgUQkgKoq/PDQGF94wNN5e7fzURSFwa4Yg13tf5/NVQj5DRQ8k/oz03n8uoZP17AcF9N2SIQDJMMBjl3I0JsMU6pa+HUNRVVwXUk44EPTFM7PFIn74fREhoGYSjabJZ/P4/f76ejoYGRkhGg0yr2Kwi//gsvoxALpfJVUNMCu4Q6Cfp2xsYW2fbkwX+Svnz9FqW4BCk+/OUHddnEcl0jAIB72ky7UkRL6UmECusY7E1V+OjrHpp4oQZ/O8fEsRy9k+JcP7cEVXsG7pq68FiIBnfF0mcHG2nbnzl7emcoTUDU6ot6iUq7ZFKsWD980sv4TD9Rtl2LVoj8Zotj4W38qxGS2giMk6WId8EjdQtnk4ZsG24jnBjzsiAf4n7dF+N54jimp41cV7u2J8ImBaFs9m5CS/+3oLBNlC1ssype8mamQrTv8/i19a4oIB3SVTw3HeXK8gFBkS2vOEpKkT+eu7sXyiPGSyR8dm6PmSNyGZV9YV+kK+kjXHYKagoZEUWxAQVUUEiE/WkNWRHVc9KBOMhlsE4p+8p1ZqiYEkZRpdAeqCgYKh6ZyHJzMk7GaLhUQMzQ6QjrPXixwX3+Un85V0BTRImpNbb6Hhr260HTN5s+Pz5OpmtRNhTdOpgnqKl/Z283m2OqRKVVVuaM3yh29iwT6U1tS3NEX5dz/z96bh9l112een7Pf/d5abu2rFlubJXkXNjYGL2DAGEMINIE0SRgzWaDzZHqS7mQmySSdpbsTJtPZm3SSDpANmh3bYMDGYFuWZUuydqkklVR71d3Xs//mj3PrVpWqSoslGTup14+ex1LdOts9y3u+3+/7vkWTb57K4wtB56KqX6kh7FgpNUKVJTRZomp76CGFiu0RUuZNooN9VmUJXZGCFrEvVrxuL4Y1u5M1/KixduZcJqrVKtVqdUUid60gSRKW7bJ/ZAbP87l+oI1Y+OIRRpliDcvxmuKB1oRBOKNSsxx8P1DIep6PabsMdSWb7VdJgolM+YqI3WoY6kpxbvYcLZGg8lWqWcRDOqJh8xDWgxvy1qE2fnhoAst20TUFx/XxfYHreXQkw2iSYCZXRk2qHD9+nMSmPrq7u9m8eTOyLJMrm7x4apZ8ZYaBdJwbhtvZsS59wW0r1Ww+88RhwrrCQHuciK4xnq3iuB6ZUlCFURSJiKKQLZu0JUJkyiYC2LTI2LarJUKuYvKNF8/wyK71q7Y4LccjEdEg4Fh0piJ8+C3X8eT+McYzFZCgNRbiQ3dtoLclfFnHXJUDA9vFxsQhTeHm9e0cOpcjX7WZytdIhDXesbOP4c746gt7HeJaxcCthM6QzPWGh49C3ROBgvM83eihvMlYxcE6z03I9uFM2eJovs7WC1SA3t6XIKbJfO1skZwNjg+3tEf4wLrWJoE0XZ//98AMlucH83QNUlJxfDzhMhDTGK86wbVE0LVPh9X5jwVCASRu6ozT1hYQrnK5jOM4ZAtRWqJi0exdYy7Q8xgtO0gSKJJomhUXLAfLsYlKghdHq9we93mhqlMkmImLqjLv74/SqXqYts1fHZyjaLkkdRnDg3hIpep4/Mn+aX56a5p1yRChS6xIp8Ma6bDG9akwnz86x2zNCeaiJImkoXBLOkLF9Tnf9s9yfXpiBnXXo1h0KJouRQLypsky61MhFFnC9oJZwlf7nrOmin3jQmLlsYI3GtbOnMtES0sL8fhr+xB8/tgsn/3eCEIK7lSyLPHR+7fxb+7desEbSDQcVOPm3zxVWWHLQAuTBYtTEwU8P7Bw2NjXymBncKMXQuD7QVVsNVwJsXvrjgGe2n+Ouu0hI5AlGU8IaqbDQDrR9L9LRUNsHWznzEwJSQgs28VTIBFW8V0LWyggyUTCBg/f/2aii2xO9p6c4X9+9yi+L9BUGdv1SEYMPvmeHfScJw5ZfPz2n57Dcj06U4GwIFOqo8gSyUSImUKNlmiYUt1GAmzXZ6ZQo1iz2dC5/IFtaArPHpvG9QRT+Rq267G+e0HV6no+luNxw2A7Z49PNP+9ry3Gx962iWLNBgHJaGDDYNsrBJVeAJoqs7mvhaMTBTxfULM9jLAgaqh0t0b58TvWcV1PkqihXvOW5hsZpuvzu0dLjNdV5hn4iaLF184W+OUdnWxvkLVDuRqWPx/QtRSugN2z1QsSO0mSeHNXnDs6Yzz74kvcfvNNy9qU+zK1BVK3CCFVxvQE9/XG6YjozNQcDmRrvDxXaz6khBDUPEFMU3hT1/JrQFckCpZHWJKbbVZJkqhYAp/AJFmVF5iSgsAW0B3XsT3Bwzd2cb9pMV4y8VyHpOTgOiVGRzOcKbucy6vEZEG50c6eKZSZc8D2Jf7oxbGGkXGMewdb0DTtks7JlpDKz+3sCmxPLJe4pjCYNDhVMPn8kdmm/x0EFdC87fHAYJJnx0qcyptoCpiuhPADf8J5oUyu7nJnX+KKxBNrFbs3Lv4l3A/XzpzLxGv9pe8fmeEvHjtCMmqQSgQPBsf1+Mw395OIGLz7jo2r/m4yanD75l5eODZJV2sw46apMpsGA6sOTwhuGO5YMruVK5v0puMMdq6e23olx6AvHefn33Mjf/qVvRTKJlFDZaZQY7g7yebBYOZLIJjIlLhvWzuZPp2nD80SM8LUHEEyGkbTVArVwDbk7Ts6l5C6TKnO//zuUdriIUL6wumdLZt85olD/N8fun1Zy3GepE5kK0QWveYrjcxIWZYDc2MJBtJx6pZDoWbT2xYlYuj0p5aWaXJlkxdOzFKsW2zsTpKI6Ow5OcNUrsqWgVYs18d2PO7d3kdHMsw3J2s899UDVOoOA+kY92zrYd0Fjv+l4sbhVp46PMUgrrS5AAAgAElEQVS+kRzhUAVdL9AeN7h3WzfbB1ubyug1rI7PjWQZry+3s/EE/MGBGf7kzgESukK+0QJc7coYrzqXtD5ZkghJYsXZs4mqjeuDsUKTwPF9MqbHzR06/TGdm9IR+qIlvjVWDFSjwMakwYc3Lp33czyfp/MSYzWLkuUhSxJxXW6qRsuOT0iR8JGWEBapYTZSdTw6I0GWr2EYtCQXzlshBKMli8x4CaoVEjEd33Up1ExmnaAipjaqgLJn87WRLJnpKa43gpcYWZabXoCGYazoE6goCoMJg0EW2rkbUyEeHG7lydECAkHRk5BMlzt64nRHdVwheFN3jLzpca5sYXtBrNm5kokqS6xLGezqefUv71erYrdmd7KGV4s1Yvc6x+e/cwhNlZckOWiqQkssxN99+yDv3LXhgrNR//t7bmR0usBkpgzCw7Fd1LrgPXduJBExeHzPaXRVRtcUaqZDNKzzSx+4/aI3pitphd18XRe/+7Fd/HDfSVLpbr6++xT5co2ZTJ66aVIomwx2xLhraxfR+PVk7UOUaza263J2psxcsUbU0Pil925nOLG0kvXSyVl8IZaQOoC2eIhzc2VGZ0us61qonM2VLYr1GrYapzUWwlyk4utIRTg+UcAXEA1pbOhJMpmtIisSEUPlTZu76W6J8tizh5q/4/uCl09nAEFnMkpnKgJIdKbCHDqbIxHRg9bwYBudqTD/8INT7D5T4catXSQiOtmyxV9/9zgfuGOYHSvkyV4qhBB85/A0sYjG9r4YdV/FCIWQpWB2ao3UXRyOL/jhdHXVn7sCfjBd4V0DSQZiOsxUF1mVBJi/SlIrxIFdLtpDC23VxRAiyCTLNEx31yUMZEni7QNJ7u1LkDNdwqq8YiTZP54u81JZIhlWcDyB6foULY+669MaUtFliZCi4CEoWD4qC6RFCIHjw9v6lr+EVGyPzxyc4WS+jukJSo5H0fLojiiU3IDAarKEQBAPqbSENSKez4iAD9/SH1i6+P6KHoGFQqH5d9cNzP/mSaCu60iqhmnLXBeWsZEZtm0e3J5GVlS+f66AAoRUhe6YQmdUo2B6ZE2HsuWxqyfOvUOpZkv61WCtYvfGxhu/XrdG7F7XMG2X5w6PU61alOsuPe0KsXDQpoiENGbzVYpVk5b46jmRbckI/98nH+C5w+M8tfcEMj7vv/cmtq/rQJLgjhv6+d7LoxQqJtvXdfLWGwcuuDy4Or56miIx2KoSDdV4eKvOyRmfs3mfSGeKe3au45bru5rk7D988DYee/E0zx+ZYkNfCzuG0zy0ax1tUYWTJ08uWW6mVF8xixWCC7bUUAdWTIfPPnWcPUfPocgykf1ZooZCuW5jOSEMTSEZ0RnuTHD4XJZU1GB9Z5L2eIhcxeJ9b1rP23b0U6xaPP3iEabyNTqSYQpVi1LNRlNltgy0MH+biBgafe0xBjsSPLCzH4CTU0WOTxToSuqEG/vaEjMIGyrffGmMzX0t6OqrIwST+TpnZgIz4lmvRjQaJRqLIYTg2GSJXRtN2lcwbl7DAmpukGqwGgQwXg3Op1vTUb5wOo+zQu6rLsHtHRf3h7wYbumI8oVTeRxfNFuMri+Yawz6PzNR5vsTZdJhlU/u6KIroqHKUtMGxPEFBSsgeTFNYapq80reIiKDLst0RTUqjk/ZcnEFbG+LcFtXjL8+MkdClbE9Qd0NXIL9Bnm5ozvGru7l+/bH+ybZN1sNLEmkRh6u8JmoBsoSXZ2PTQvyZCGwZMmbLkXbpTUUJHaEQiFCoYufp57n4TgOs+U6/3gsR960kYSH6wnKdYlXnjqG7wsKDpR9iYGITDqsBIkkikKPoZCTJLoMAb4H8qt/NK7N2K3hR421M+d1imyxzi/+6ZOMz1XwPA9JkpgtWnS3RVnfnQpijiSJsHFxSXwkpHHfzcPc0BehXC6zYUNn82fb13WwfV3HZW3basROCMHoTIlC1aIjFaG3beGG73ke+XyebDZLLpdr5nKuW7eOTZs28bYVYpfm0Z4M85P3beWj925BCJoVylqttuyzAx1xnjs6ueK2CaC9EW/22aeOc2w8T08qjKzIJBIxchUTy/OZzFVRFRlNkYmFVG5a30FvW5S67bKuO8VPbe1huFH1S0R03n1DCyWjhVfO5siWTTRVZtf1XaQTSwmypspU6gstucNjOSIhlXJl6baGNIWM6zGZqzHUEbSEHM8PVHsrlWxWwGS+hrLCZ+cfOLOla0PsXktRw7VGTJVRZQnHW3mfJAKTYICuiMaujih75mq4vmhW7mQECU0lW3fYO1tlR3ukScoue3s0hZ/d2sGfH55tmPIKiqaLL6DVUAJPOSGYrbn8l5em+P07+tAVGV8IvnW2wBNni9hesG1bW8NsTAXf/zwHkZGIqDKuHyhGz5Qs7utP8JaeOE9PlIlrMhE1EGuossRPbU5zZ098GYk5NFflpZkqWkNsBCD7gpofcCYJwA+sXQZj2pI5OAGEFlWTq47Hi1NlDsxWAw/JuMFgMkRXTKc3FswBz9YcCqZLTJP51riJr2gMNUyULdfn+dE5SrLB9nSYHkXhldkKc54gKuukdRnP86ibFrbtY89NcGD6DJ4XtNYVRblgZNx8O3gx1ip2b2BI0tqM3RquHf7wCy8wma0w1JXk9GQOQ5WRFZmpbJWWWAjH9bj/lnXLWo4XwtWKJltpOdP5Kn/0lX2MzhQDU1DfZ2N3nB+7tROnFijvWlpaaGtrY/369dTrdUZHR2lra7us9Z5/zZ2/HTvXpfnq7tMUqhap6MLczWSuyvW9KSKGyr7Tcxw6l2MwHaNULDWX0RoLUak7vOPmQUKaQrFmM5COs6mvZdXjLEkSibDKO+7YyHt3eWTLJn/yzYO0raAortveEvWp8OdnlVbH2UyF7x6c5PR0EVmGHYOt3L3IXHg1aKqE8Ff+WWDrcPVbsf8SboiLocgSb+9L8JWzxRV/rkpw16Jq1aOb07QYeZ6eLCMIhBeOF5CvfxrJoSkShizzyzd2rWrxcTFsawvz+7v62D1T4XC2zsuzVRK60rRSkSSJsCpRsFz+nxcmyJkuddfD8aHFUAhrAdE7lK1xNF/Hcn0KHniWiSRJeKKRiwuMly1+98VJ1sV1eiMqGdNDU+AtvQnu7U/QFl75pfK754rNbXEX2f1EEdR9n5QCqirTH9ebaRMARctjS2u4mS1bslz+cv80edNFk+BM0eQHYyUMRWYgYdAd0zFkiemqjSRJ1GyX8bJNZ1QnU3OIGwol06XiCITr8PKUT1xX0GUJyxOMV116kglc18eWfN57fYpbe5a2lT3PW9YOnreImf9zPgl0HAdFUZa0h1cjgathrWK3hivB2pnzOkSuVOeFo5O0JyOAIFOoUKrZqCIgVCMTee7c1sej7955Wcu9WsTufNiOx2//w25ypTpxTWBZNo7jsO9khWrN4nd/6i7C4eXt3dW2RQjB2bkyzx+bplCxuL6vhVs3dhA/z+JlJSIRD+v8wkM7+O+PH2RsrtxcXmdLlJrj82uff4FCxeJUI6KrLQSL/ShDukqhavPBu1YXpawGXVXoboly84YOXjw5S29rFLVRRZkr1WmN6WzuW7BF2dzfwstnMsuWYzkeqixjuR5/9d0TGLpCZzKELEm8ci7P6ZkyP/PWjcRCq1drh9rjCGka11vK7mzXR5Yl+tpenfnqtYDnC/I1G1mSaIlcmiLytcL7h1s4ma9yuLRU/KBK8MmtaVoXmTqrssS/2dDK23ri/P7LUxQcHwF4zKdASFR8j/+8b5o/enP/MnXravCF4KnxEo+fLZI1XVoNlQeHklyfCvFKprbMH8/yfAqWh+l66DIU7ED1WXN92kIqCV0hqivM1RwqTkDkVFnC8oM2qS9JqFLwvWRth+mKzbz3cFRTqNs+W1pDqxK7yaqN4wtsz1uoBkoSYVVGFrA5DqlUjON5E10WyHJQWUsaKg9vWHjRe+pskYLp0hZWOThbxRdB29Z0fUzX46WpMgLB7d1B1fB41SZXD2bl2iMqs1Wb2aqD5EFID8hlWJOp2B5JXaXqBtXNwZTBQ70J1qWWv4wpikI4HF7x/nU+5kng5OQkjhOcL4tJoGVZzU7FSpVAwzCYmprCMAxs214jdj8CNGwa3/BYO3NehyhWLRRZarQcJTb2piiUTUqmj+16dLXG+LNffAeRCzzYV8PVrNiZpkk2m+Wpfac5fmaSntYIkhwi1ZJCVVW6hWAiW2UsZ3Jdb3jFZay0fV/fM8oXnxtBlWV0VWb38Rm+/PwpfuX9N9PXHlv2+fMx1JHgtz7yJkamClRNB0NT+bunj5OvO/S1xYiGNM5lKhw8m2O4zWCofSFeyXI8WmKrV1Ns1yNbttBVmbZVWpkP3TKEpsjsOTnDfFTXcGec9+1aWmHd0JVguCPOsxMT9LkeuqpQqtvkyhZv3tzJb/2v/WRLJoauchDBho44G7rijOdqPHlwks29KeIhjZ6W8DIylIrq3L2pg6cPz2CaHqruUS+b1CyXd+7sJXIZld4rgecLzuVqHJss4QrBhnSMdR1RjMbs4PHpMs+NZJqilWRE457r0/SkLv4gfS2gyhI/vz7GKxMZDkpJirbH9ckQD/QlSKwgRhBC8EcHZpipOUuEFIJgZi+myViez97ZGneuMJu2Ev72aIYfTpZRJImQLFGyPf7+eJahhIG6AgkuWF7DwzCIBVu8bTnTxfEFLY0ILU0KFL6eaGyttNBGrrs+ni+asV2aImF6PjXH4zOvzPJbd/Y35+MWryNTc5i/LOe3zheCqu2hyLAzpfLWbZ0cydbYO13B8gXb2sLc3BlrVut8Idg7XSYVUimYLpYnmn5+hiozXXVQpGD5ZSeIfMvW3UZbVyCQkKVAzCRJQQVSV6SG6leh6ngMpkJ86pYekqGrcy3Mk8D5ucDe3t5VP7s4N3j+T6lU4ktf+hJ79uxhbGyMp556ilgsRjwep6uri4997GM8+OCDF92OL3zhC/zmb/4mR48eZc+ePdxyyy0rfm5oaIh4PI6iBLOGe/fufdX7/i8JF+uivBGwRuyuMV7NvEU6FUGSJBzXR1NlZEkiGdXp7oiSKdS4e0f/qyJ1V1oJcRynGZ82OztLOBymra0NU4qSbm8j3XpedqYU2IVMZCpc19uy4jLPx+npEl98boSelugS5WamVOfPHz/Ef/rIgmL3QhVIVZHZ1NcKwLf3j1GuO/S3B23QVNQgFtKwXY8zc1X6WgMSYTlBS+XGFYyMhRA8c2SKx18ew3I8fGC4I84H71y/7LOaKvPQrUO89YZe8hWLiKGuSAJVRebDd22gOneOfMXGdgPz5YdvG+TrL48zVzRJxzVsy6ZuWuw9UWI2G6Zo+rxwfIodgy3IskJfW5QP3rGO1vMI6W3r03Qmw3xr91EsAcPtUW4caqP3VUYlXS5cz+eJg9OcnKkQC6koksTp2Qrt5wzee2MvM0WTbx+eoTNu0BoNHugV0+Wr+yb5wK19tF+AYL/W6DHgLRsvPos6UrSYqS+3NgnoBtgNr7up2qX5Ek5UbJ6dLGPIC7M/mgSqgNGShSxJy8QUbiNGwfEDwuPNP6ikgPJUHQ+9MfumyaB6PjVfphFAA5KP7UsoBMpfqZFagWhUHR0fTZHYO13h3sHUku0dLVkoEhgyTSGJaCzDB3pDMutjCqossT0dZXt65bxdIcD1Aw/muuMvedRKjf1UFAkhSdRdn6rloSkSIVWh6no4XmBorisS9UA4S7RpwC5he4KkoV01Urd02wXyRUYdVFVFVVUikaXX4m/8xm8A8KlPfYpHH32UXbt2US6XmZmZuWT/1G3btvGlL32JT3ziExf97FNPPUV7+6tX36/h9Yk1YncNMU88LpdQxcI6D71pI1985hidLQs3PtN28YVYEnJ/udsz3wq4FHieR6FQaAoeAFpbW4lGo3R1ddHZGYgwjmXP4PlLBQu+L8iWTbKlOjPFWiD2WDQ0vhop++GRSTRFaZI63xdkGss5OpbnC8+e4v6dfYGv3CXi0LksiUVtXFmSuHFdmhdPzlCpO0zkatR9DQH8xN0bSSeXV4u+f3iKLz5/mp7WKIamIIRgulDjj795iLf0Lvc5A4iFtAu2SyFo/d48EGPXrp14vkD4Lt944QTjk9NYtRpVWcfQDRKJOLrtsn+iQmdCJxFWiSoemXKVH07O8crJc3zkphSGpixr77xpMEQqlSKdTqPrF08sWYxCzWY8V0eSoLclTGqF2b6ZoslUoY4kCar2wvl1fLrMyZkKA4vavsmIxnTRZPdIlpmKRVtUX6JijoVU6o7HK2MF3ra5kwvh9dSyncdE1Q5SH1YRXfgCQopE+yUSigOZGp5Yvq+SJOELwa0dEfZnatRcHxkJpzFYGZKhvuIMp9SY/wvOWdP1cV2QJR/Hp5m2IMs0/hIkwrhC4AmB8AWmCF6Cvng8gypL7OqJN9vKUxWbiCrjhzSKposA/EYShiZL3NhmEFC85bBcn2PZGkXTpTWs0Z/Qmas5jdzcBdieT0xXAgIrguXano8iBabFVtXH8QNjdkGQJBBS5eDvQmA1vpd7BpLLN+Iq4GqqYiVJIpFIkEhcuq/l5s2br2jd/9rxOrytXDbWiN01xJXMtD367p0Uqybf23cWx3EQvk8sqvCrP3EHmwcv7Q3LtF1+eHiC778yjixL3DyUZDAFNcvBcX0SEX3JDUgIQalUIpvNks1mcRyHVCrVzF2dD6U+efLkkjfS267r4nPfO4rluBiaSrFms+/UHFXLQQjBF354kt3HZ/iPH7il4eu2+rHJlk1CWrBsy/HYe2qWXNmiWLMwHZ9f+/xu/urJBB+4cz0fvGP4ko5vWFdxz3vIJiI6b97Szd4TE1zfHeeWLQPctD5NOhHmldEsT+wf51y2QmvM4C1bunni5bEmqZvffkNVOD1T5pl6nXvv9l+VN5zv+7iuy8jISbLZLLIsc2LSZagnjavWMB0PT8C5TJVK3SFXc0CS6EhFOTDr4fkKkhJhtuzwvZkIv3DfRsIqzZme+TZPLpcjn89j23bzmKmq2iR/i4lgYAqr88ShWZ48PIPj+yRCGi0RjTs2tnP39emgouz5PP7KFMemy0FFxhPMzpQJdea4dbiV/ecKtMWWE8F03ODgRBFVkelfoXqYimiczdYv+1heK1zONdxiqMHMmrRQpVviayeCtJVbO1auVJ0PX4gLrF/QHdN5/4ZWnpkoM1ax6YyoPD9VoWgFVUNJAlnMUymBhBTEhSEhhI/jBORn/vKYT6CTGlW/+TUHHK9BlhoJDY7n809H53h+oswv3tJDSJWJaIFoYCCuUAmp5Buq3bgeiDbSIWXFkPVzRZO/PTBN3fWb65QksHyIGwqSFEQgugIcT7AuFeJ0PkgCSRkqdcenZAWt3pShsjkdoWx7nMnW8CSPHR1RsnUX1xekDJm2iMa2ziu3oFnxW7lKqthrbVAsSRIPPPAAkiTxiU98gkcfffSarm8Nrx3WiN1l4nIu2Cshdrqm8GsfuZOPvWM7u185hedYvPstN11yC7ZUs/mV//EMp6eKzbmu7+4bpW7ZtLccR5ElBtJxfuItGxhMyWSzWarVKolEgra2Nm644YYL+kct3q/2ZJhHH7yBv3jsIJ5f58i5HJ4vMDSFHevStCcjzBZq/P4X9vKHP3PXBQ2VN/akeGU0S0sMjozlKVZsynUbCQldlUknwswV63xj71lsx+X2Cxd1ALhjUxf7TmdojRtLvr+a5bGlN8lP3DnA8PAgAN95ZYJ/fv40LVGd7lSEmu3yN0+dIFcyedsNPUAwZ7dvNMds0cTxPI7Va/DPL/Pxe69nuOPi7ZJarUYmk+H42SleGi0yWaizuRLnvp2b2diT4ox7mlMzJbb0p3jq8DSTuRphTUaWJaTGQ2P/WJGNnXFamgHoEjOFOl/aO87P3LNhyXdnmmaToC/+/lzXbZI/y7KwLItyuYxlWXzjcJbHj9eIGhKKJDEuBZF0IxMZaqU8t65r46XxKofHKwy2x5BlCc/zccsKTx2dJR03qNke8RUqU8oie4uVgtYdz2+S+9XwWtuqXOp1v7U1jK7IVJ0gYN5s2IvMI6TK/LvtHc224MWwrS3Cl0/ll5EFIQSqJHFDW5iOiMaPbWxt/mx90uAvDs4CS334JKTA4FiSeO+6Fr54bA6r8bNGca65rZ4A3/UD+wcCcup4AamTG4QvbqhEVZlzJZNnxoo8MNxCX0ynUHc4V6gH1SZDoTOqo8oSVcdna0oDx12yj6br8zcHppEliY7owotAyXLxPBdJyOgyTFeCTNiIJnM8WyOqKbSHNXJ1B0MJqnauEGxtj9AW1mgJqRRqDhXPJqIppEIqVcdHCHj/lvQVmRBfCK+F3cl9993H9PT0sn//nd/5HR5++OFLWsezzz5LT08Ps7Oz3H///WzatIm77777VW/zvxTIazN2a7gQroYKtbc9zt039FIoFC5rru7z3zvKqali00vOtF2OFE1qpk3Y0OiIa5w8O8mv/u0U/+fD23jbzRuJRqOXdENaab/u2d7Php4Uf/nYQc7MlOhtj9PTGiPcGK7uSEWYyFQ4MpZj22Dbqsfmzs3dfOPFUWYKNaaLNYQUPPyRAsWrpsq4nozteDx/fIaNsYu/dW8baOX2jR28cHKWRERHVxWKVSuYcbt9oPm5ct3hqy+O0tsaaRoDx0IaA+koR8/lyVctWmMhDpwNSF0yolG3ZSKoyBL82beO8mvv20kqurRK5bouuVyOTCZDPp8nFAqR98I8dsrD0FuxxTQTJZ+/+O4J3nVjHzeva+PA2RwD7VGSEY1KXcN0grmhSEijMxliqmhRrDskGuazCEFnMszZTJXpQp2u88QH5x9rSZLQNK1ZhZ2H4/mMZqrsmS2yvreNiBFUYMdyNWo1j9mayV/+cJJcuc7hqQoxHUbPZprb4DoOdjHH43uqJCIGE7PB3KCqqaiKiizLVC2X1qhOX2uYkdkqnYmlLxDZis1bNy2fc3wjQJUlfmlHJ/9l3zSOL9BlEbRSgVs7onx8S3rFBIjVMBjX2dEeYV+mFszWyRKeL3CE4Ia2MOtWsE25vSuODHx63zS1hniikRWBJEnc1RPn4fWtfP7wXKB+DTyHlxBQCVAadiVSY52LBRGyBEXTJRTViWoKz06UeFNvgj/bN4namKfD98nWfLI1h55EiI9uTZNUTWru0nvM0UwV0/WXkLqK7TJWNBkvmhiyhNdoYYc1hfaYTtJQkARsS0fpThjMVB22tkc5Vajj+oLZqo0QcN9QEjlfwUuGKJouG1sj3Ngdpz1y+TPKl4rXwqD4O9/5zhUtH6CnJ3hR7ejo4JFHHmHPnj3/6old473nDY81YncNcTXtRS5nOb4vePzFM6ST4SCWx7EZmSxg2Q6GKjGdr7OuO0UqlaJct/navjkeunvnJd+MVtuvvvY4G/taGJku0X2+kILgwZEp1i+4jNZ4iF9+30383hdfwrRcTNfDE4JE2GgKEFRFpm67yHKIufLFh9AVWeZj925i53A7Pzg6RaXucPP6Xu7e0oNVzvHCyVn+ds9LHJ8sMJ6rctNwG10NAQtAPKQTi2icnCqxtV9huhCQOgDLcemLqyQiOsVMlX1nMtyztZtyuUwmkyGTyeB5Hq2trXR2drJp0yYcT/Bb/2s/nakYEUPFLsl0JMO4ns9j+8b59w9tY9fGNM+emCVbtulujVC3HGQCn7FS3SWkKZTqgfqwULWpOx6SDJIvUao7S4jdpXyvtuvzg5Nz7D2T49hUhdFslQ1KQJrP5eoYqkJIV6jbHqqhc7SoUFdibB9cqBS5nsfp0XMo4RijJYcHe0KMzGXxXRONoOVsOR7Zus9dwxHiZoRqweJQBpIRA1lRqXuC9Z0JhtsjnJqrci5XJ6wprO+IkH4diSkuhI2pEJ++s59nJsucLlmkwypvaeSUXi4kSeJnt3fy9TN5njxXwvR8dEXmnX1JHl7fsup3G9MUIpJAUyVq3oLSVSUQNkxWbIxGRVGXgtas01CQzlflOsIqM3UHVYK4HrRVJQlcT+CKQIVatDwSuoIiw28+M8pk1aY/EaIjqpOru43WqqA3ovGmngQzM/Vl25yru0tqJGXL5ehclart4YuAzNqOjyJJ6LJEzXTZ0hpBluFErs4DG9q4q1EZ9nzBRNnC9gTpiEZEERw6NMmNm1+7F4WrRezOf+m6mqhWq/i+Tzwep1qt8u1vf5tf//Vfv2brW8NrizVidw0hy/JVIXaXsxzf95mezVAoVRB2oKTTdZ2S6RE2dHzPpe747DuTx/F8khGNiKGSKdVJJy9NLXkhwtqZiuCtItCQJEg1Hs4XuvGt707yBz99Jx//46fIV0yyFYvkooei4/qkEyEQgfXBpUCRZW7e0MHNGxaUjUII/vT7kzxzbJbBrjZSUZ2R6SJ7RjJs7UuxoXthuHp9V4JS1eLMbAnX9zEdD9P26GmN0qLUcF0P4Zg8u/8YWuE08Xic9vZ2duzYgWEsJSSnpwpYjkdnMkzZdBjJ2BwtTCBLEDVUXjqd4aGbB7i+N8mZmQqGptDfEqanNUi/+M7hKapVp+lr5/pBte7F00EL/EO7Bi/pmCw+Dl/ZN8HRyRLdqRBhPZiVGs/XmzYX8wkCnh/kbPa3hvnOkVl2OElCjbbiRMFk75SDFq4RM1Sem/To7ggeqKbjYRCkObxnfRubu2NYlkV/n8mJqRIjMyWEb7I+KROxZ/nDL4+SNX0MRQJJQVIUbhuIc/tQCl3XqdVquK6L7/sXVSD+KBDXFd41lLr4By8BmizxvvWtPLyuBdP1CakyykWIw7dGC8iyTKum0CIWiJ0A9k5XeGtfkpiuYNZ8fAKBA9BsxxqN6phcD2xb2iIqFdsLRBqBKwqGIuELmK45RFWJQt3FE4KTuRoJXUFC4PoQ0xUmKxYly22SHiEEJ7J1nh7Nc2SuymTZxvcF7SbWNFIAACAASURBVFGNsaKJaIg1NEXCR0JTZHwElucjhEym5tAV15GAuapNqkHsFFliILlQAbZt+zUX2fyokye+/OUv88lPfpK5uTne9a53sXPnTr71rW8xOTnJxz/+cR577DFmZmZ45JFHmuv68Ic/zDve8Y4r2uZ/KVizO1nDBfFaVOxWEjwkk0kGOhNULUGqoR5VlCqu61IyPZBkbNdDliQyZQsnV2P/6Tnuv/HSCMGFblq3X9/FZ793jKrpEF3UOs5XTFqiBlsHFio8i/epbrtUTZdkJGi3pqIG7751kK/uOUOuajVVtZ7n4wlBS8wgGdHpSV5+FWQe5zJVnh/J0ZMKNVu0hqYS1hSOTRToa4sR0gMFrK4q/PJ7d3JkvMDo7AniIY316TB4DvmShT8xhSlUrtvSz513brrgMbJcH6RAcfrs8VlKVZfudgVfCMZzNb645yxv2dLNpp4UP3H3el46naUzoSOAsK7w9ht6+NKLY5iOT1siRDoeQlUkKnUXTYFvH57m+u7EBWcZF2MiX+fYZJn+1sAPLxnWSEZ1ijWHfM2ms9HuE57Adn02dsaJ6BrpmMFYrs6GjiiFusuBsRKGAoYmc+NgitaIxlje5NahFDv7kwgBrbGFtAFVVQOFdbqNxQ2gr78yTTxdY2PSaM4C2rbDgdka/S02bSGLUqmEaZoUi0V830eSJFRVbYo/VhKEKIryqh64V+NBfTGYrs/uqTKnCiaVssZgzWlmvM5DkaRLns2brNro8oIt0PzWL/akS0c0fM+j7PiYDWG3ABTA8wRjZSuYtfMFZdtjvlnrN0gdBF5384RRkQOhRt3xmSx7xDQZVZGpVYMs27GSxfyU5/NjRb5+IktUV+hPhJiu2pzI1sjXdSpWcG/yG4rXkCJR8YOKXc3xCYcVyrZLF3qQO3sB0dJr8d1di3VeCbF75JFHmqRtMXp6enjssceAIMrxwIEDV7SNa3j9Yo3YXUNcrr3IalhcsRNCUKvVmkRuNcHDJ/wkv/33LxA2PAxNoSsV4fhEHteHlpjWfLgqPoQiOv/j20d4245+lEusfqxGNFNRg3//vpv4gy/vI18xUWQZz/eJh3V+5cduRlMXVKVCCCqmw+e/f5KnD00GlQJV5qHbhnjvbUN86K6NFGsWX9szykS2hiIHbdj+9hi6qvBzD26jMHFy1W30fJ+pfGDV0Z2KLCM6h87lkGWpafEQ0hXWdcQZaaRSZCtBnup0oc62/hY2d0Xo0Gq8fFRhslDm6DiYnoRle0SqPqkovGlz/0Vv6j2pMELA4fE8siwRbQgjZCQiuoovYPfJOe67oYe3bunixFSJsVwtEEoIKNYddgy2cHK6QkhTqFgOiGAe8ObhNmaLFmezVYbTl6b6O5erIcsLhL23JczoXBWEIFO2KdVcIobAdHzWd0QZTkfxfEFfa4TrO+OcylQ4MVOh7nh4rmBHd5y2RoW1J2Wwf6zI3de1Nyt7F0LFcjkxU6U7tVDZnZ8F7BAqM16YW9d1MTc3R6VSYXh4GGioNB1nicu/aZqUSqWmQMTzPIQQTdf/lcifYRho2mubfjFRsfnt3ePUHA/XF3iezkvfH+WjW9LcP/jqqn4dYY0TZkD0F8NvVMJaQyr/dmsHn94zRlwNqrBl21uikFUlCUUGyxfkqg62LwjJgCQ1/fMAImpAwuKGylzVxvYEMsFsYahxcSkSfO14hkf6ZHxX8MS5HO2RhfvQjo4Yh+YqTJVNkCQ0OSCj6Qa5rdgeQgrqjp4QGIpM1faI6gq9F4hn+9dI7NZwZVibsVvDBXG1Knbz+YQHDx6kVCo1jYE3blxd8PDmbb188uGd/NUTh5pCAV8EIfKaGlSHbMdHkmBzfyulqs3JyULT1PdK9mvnujR/+rNvYc/xGWaLdfrbY9yysYOIoS1ZhucLfvVzL7B3ZA5fCCKGSmcyzN8/c4Jc2eTRB7bwqXfv4JFd63nu2DRHxvIYqsy2wVbu2tJDMqLx4vjK27Hn5Byf+8EIpYZZbFvc4GP3bGR9Z4JS3SYR1huu+kuP3cbuJGFdZf9ohqlcDc+22N6lsyWa5+RJi/b2dj7+4E38/N+8iOX5RHQF27ZACoyJd49k6G+/MKHqSIbZ0pfih8dn6U1FcAgeBmXTIRHWWN+R4IWRDPfd0EMyovOz91/P7uPTvDJWQALeubOXQtXm2ZMZNCWIHosZGi0xvREvJSjWlpvkrgZNkVn8dUYNlRuHUrwyVqI9HljjRA2Vrb1RbhtuRZIkZoo1tvcnefeOHmZKJn/59Bl6UyFE1WOwbWG+UpWD865iLcwFzpQtVFmmryW0JCsUCGYFJZbFZAGENJlizV3270Bz5OBSfPo8z1tiBWNZFoVCofn/83FQALquB21Bz2N8fHwZIbyYJcVMzeHF6Qqm57OlNczm1qUpIUII/mDvBGXbxVDkYJ4sEKPy2SNzXN8SZuAScmWFEJwqmIwWLSKazN19CY7l6nhCNNu2Qghqjs+NnVEShkrCUPm5TXGeHCtzzlapuz62J9AkAvNfIfCAroiGgoTr+7SENXQlMPit2R6TFStIeGiIG2w3MAZW5MBnz/UEju+jCMFTowWeP+0RUSUiEYPW8IKCPGao3NaT5HS+juUF8WLZxgyprkjEDZVc3SGiBf6AUsO4+MPbOy+obn2t1dPzuNbiiTVcO6y1YtdwQbxaYjevosxms+Tz+eay+vv7SSQSlzRTJEkSD+1az303DnJiIo8kwZ9/4wDPHhnH9gOPOE1RiBhBNqoiBQP0V2u/PE8wVajzzJEphIDTsxUeunVwSQLD0ycKPPZylpAmo6kKNdtkplBnoD3GkwfGee/tw3Qkwwyk4wykl9uI+L6/4nYcGM3y3544THvcaKYs5KsWn/zr5+lIRoiGVGRJYlNPAsfzEGL+wQeWbRGRLPpi8JM7dK4b6KKzI00qlQIkRmbKfPGFU4RDGoNxAwFUFJtt13VjqApPH5ni7Tt6SaySozmP99w8wNdfGqNiOVRtH6nu0JkIBa1qAbbnYbs+RyaLTORqRDSFn3zzMMmGQfBLZ3KAtEz9Oo9YaHnU02oYTkeDSs0i65F0PMQdG1U6EzpD7TGmi3VaogaFukPd9uhMGNyzKZhX7EyE2DGQZGSmgmktvSnOR1IZqsLjh2fYO1pg3iQ3pMm8b2cXGzoWiHDcCL4b11vuC1ixXIavQsatoihEIpFlrv/nw/d9HMdhdnaWfD5P1RHkKiV0XBzHWZL9eX4bWNM0nphxeXLSxEfgN1qGQwmdX72tj0hjNvRkwSRnes22aXMbpSC79Tvnivz0tgsnXlRsj0+/OMFo0cQTQXVMliS2pSMcztXxG75zqizRF9f5t1sWltcTUfhAv87Q0BAvz1T4T8+PBQkZjYzhVkOlLaTi+IKy5VO1PYyw2pjzA1GBmhUIJKZKQdasEOA0ziVFgprjU/eD9UdVmartkylYaLLM1o5os0QiyxKpsMZ1rWHOFk10RWK8ZFK2wfV9EoZCXFe5rj3C7X0JdnTGaLnIdQavvZH11SCTaxW7NVwJ1s6ca4hLJXa+7y9JePB9n9bWVtLpNNdddx2VSoWxsbEGubg8hA2VHY2IrHtu6OHgmWlC4Sinp4s4nk+57pCvBm5W3gpO+avt14WQKZn8yt/tJlexmrmrX91zhu8fnuT3P3p7Q2Ah+NK+LJoiLZrFC0xMz2UqDHXEOTlVpGOFFIgLQQjBF3aPkgzrRBdVCE/PlJkrmeiKzHXdHbiezytnc5TqDqZZp2ra4DkIWaPiyrz3zs08/NaFhA/H9fmrp4+z93SWkekyNculZLp0JkJ0JTTCmorbIJozhfpFiV06EeLNmzrJVWzmZlyGB7sJN/wGx3NVdg628ntfP0S2YqPKMrbr8pWX4KN3DLF9IMWmngSGJlMx3SUkrlCzSUa0Jfm3F/u+2mMGd21s5+njc6QiKhFdpWK5lOsOP37bALcNtzKer3NsqozteqxLx+hvjXBwvMjuM3kqlksqrDFTMon6S8+h6ZLFjr4EL50r8L1jGRIhFUOTaYloWK7PP7w4yaN3DTbn+EKawk0DSV4YzdObCjUrd3Xbw/Nge9+rTwvI1xwKdYeQJtN1nqfhSpBlGcMwKLgqT475EHJAkmkJR3nbdW3c0CCZC3OACxXAl+fqfGvChobSVEbgOB4nsi7/9ZmjfKg3MIc+WZWaM4LzdiTzkICZ6sVV33+5f4rTBRNNDmb16n5Qpds/U+Xf3dLDZNXGdH2uaw2ztS2yYjUUYChhEJWhaAXnsQAyjo3t+LRHNdojGt0xg2PZGrIEuapDtRZkzyqSwFdktEZbVpICEqfLAbk3lMACRZMgaUiYJkyVTAZTIWINSyQhBK7nc3tfgvvXt/LM2QKKLFG2PNojGjd1x7m1N0HbZViV/KhasVcq6Fkjdj86rLVi/xXiahgUCyEol8vNOTnbtkkmk7S1tTE4OLisnXS1Wrpv297HZx7fz/HxPFFDRVbkQIzgQ2dLhP/65X189pfuWzJn5/uCg+eyjGeqJKM6N69PN/dhNfzzs6fIVSx6FlmehFtjTOWq/NMPT/Gpd9/AyakSjidQ5aWtLFmSkGWJXNla1qY7HysdF9PxOJep0Lco0aBYs5krmbTGDHJVi7ppUq/XUJ06vuuwqTdK3gvhIZMI63zwxj7euq1nyXKfPjLNnpEsQ+kopZrDVKFO1FCYLtaZduocyU/gej6OJ3jxdIZ1nbGLzis+fMsAf/bt4/hCENIUfF8wWzIJawojsxVMx2eg0db0PJe67fF3z43yH1s30xYz+MidQ3zu2VFyVRtNCZIg4iGNn3zz8AVTMIp1h1LdJRlWmwT0nk1pelvCvHA6S6Zs0Z0M8chNvaxrzOn1t0aaKRGu5/O5PeOcnKmQjuu0RQNT2mzVYbbmoKfqyARZn0PtEW4aTPFLXzxCxXKbbTNdlbl5IIkiw0vnCrxz24LT9B3rWrAcjwMT5cAMVwTVvUdu7KJ9hSSLi8F0PJ44Osex6QqyFMxodcR0Ht5+8eVNlyy+cjiL6guGU0G1uWK5fHHfNB+6pZu+VHjJHGA0Gnxfz50eA8lF05beL4QQHLcU4u3taL5Lu1ML0kd8gS9EQ3EqsG0bV0DEKjEyMrLiPKCqqoyVLPbPVhFCkDV9aKpOfcqOx5OjeX759v5V928x8ak5HuUGqdMVGd8X1C2HyapNpiTzkR1dfHhbJ4czNT73yjS249Gf0Jms2Hh+YGBs+0HrNKzJOJ6P6QQVW09IxDUZWfiARNKQyZsemZpNzFBxvMDvbl1LmHUtYRRZ4gNbO/ixLcH95tWSsx8VsbtSrLVi13AlWDtzriHmiYcQgnq93iRylUqFeDxOW1sbW7duJRy+cFXqahG7eERne3+CiaKP5bjg+WiKzIaeFrpbo8wW6xw+l2f7UKBdmyvW+fV/2MPZuUpDlQoRQ+PRu/vY1LNywoIQgqcOTa6Yt5pOhnn68BS/8M5tmI5HPCSTNUUzJLy5DIIh7y39LRfcn5Vu2KosN01c1YZyL1uq4TgONdfG8X1q1SrhcJhUKkXFy9HXkeA3HrwVr0GwViJk3z44SWcyhCRJ9LZGGM9VEUKhYroUKh6bYzKyBCFd4tsHJ0GS+PAdwxfc/o1dCX7+gev5k6/MMZ6rAhLbB1oY6ojx98+fZWPn0mMc0hR8AfvO5rlvaxfr0jH+jwc3cWK6RL7qkI7rXNeVWJK9uhgV0+VL+yY4NN6IAENwU3+Kh2/sIaIrXNcV57quiydnnJitcmKmwtCitmh7zMBQJE6PVXhgcweuL+hJhelNhfjb3WNkKxa9LeHm9Irl+uwZLXDbYIpzuaXxYaoic/+WDm4bbiFTsVFkid7U8nm8S31gP35kjuMzFXqSRrNalas5/ONLk3z8jv4LijpeGM1jKDLhRbY6MUPF9QXPnc7z4zetfO3O1ILxhvMhSVJgCqxH6IkbaHEH7/hpyo15Vwic7+Oqii5LvGdzmoTsYds29XqdYrGIbduU6xbfyUocqKhUvMASRAFUObiWpIbx8O6JMpbrYagr76Pr+VQdH9v1+MrxDBFVomQHhK5ac5vpILW6w1cPTHFsqszdwy2YjsfOzhjTFZuIIqPpMp4IYsa6YhpVLzAwdv1GSoUmk1BlbBuQJOKagukElcrZSvASd/dQircOtSxJIrlSUvajmLF7LQyK13BtIDX+e6Nj7cy5RrAsi3q9zsjICKZpEgqFaGtrY/369cRisdcsmuz85Viuz4aeFPGIjuf56JqypDVTqgWtHyEEv/3PexnPVuhuWXiAV+oOn378BP/5Q9sYWLaGAK7nL4uJgmCGxvODmKPBdBxDlelpjTCZraKrMooi47g+dcvlY/dcR+wykjbmoakyb9qY5rsHx0jpAsuyqNaDY+fJGpv7krS1JXE8n6OTJY5OVpirWBzMvMhDN/Xzjh09y5YphCBftehvVM9aojpD6RjHJ4tUTAcJQc1yURWZm4bbiYU0vnd4moG2KLmqTVhT2D7QQmdyacKC4/lUbI/OuM62LT10JUN8//gcTzw1wshMhdFMlc09CfpaIvi+QAgfXRbMFOt4XuBPEdZkdvSnLtr68YXgr589y0ShTk9L0OL0fcHL5wpULI//7e6hSz7G+8eKK0aFRXUVVwi6UiF6G7N/hZrDyGyVqKGymMEbqkzd8RnN1XnzhpUFO8mwRvK8lnbJdDk+U2FspkRCcenp89Ev4GWYq9ocn6nQm1zaem2NaByeqvDH3z+DLMu0hDVuH0qxuTO2RD19KlMjFVawzKVilLih8NJYkbLlYbk+Q61hbhlI0hEPWsodEY1TBYvzLwMhgnm7FkPFF4Lf2T2OQKBIQatSCPCAsu3xf+3qY3iF2VIhBL+3e5wTTo1kRKJasUEEv+8I0PyAWPhCYHuCT3/nFe5KBbFb81U/Vdc5XvDZPV6h7AhmXq5QdEWTXBarNmI+Dk0EPpAFx+fZsRJ7pyogQT0VRMbNW50ojYei5cHWtjATZYuYKjOSqRFX5SXH33J9uuIG/+HNg0R1Bb0hHLkWeCOqYj3Pe136M67hjYE1YneVsFjwUCgUUBQFz/Po7e2lr6/vii7Sq0nsBttCnMzVaVXk/5+9Nw+T67zrfD/vWWvtquqq3rulllqyVi+yLW9xNmJncUICIUxWyIRkgCFhgHsnE3gyF+59Bgi5w2UYbrgkPEwShkASCAwJ4Nixnd2JF3lJJMvat1bvXft6tve9f5yqUre6tUu2E/r7PC1VnapTZ6lT7/s9v9/v+/0ti4B0JpyOovPQdJkjs5UVxfmJqMliWfL9Q3lu3LZ51W3cvDHH3lMF+nqWr1usOVy/vhdD1+hLRdk1GuNIxWT7WIapQoOm42EaGrdO9PHvX7/joo+r4+XX6fSw3vBImIqSo5FLZzHiksOLc/QlLNb3JZFKsed4gXythWUINuSiRE2Dz333GIWaw8+9fGLFMY1lE1SaLqmYhRCCrcMpGk5AteUjkWwa7On63rm+5LnTJf7w/v309USRSvHFx0/y1lvHeMONwwghKNZd/vjBg0yXGxQXHQ40Jtk3WWKiP8GGvgTTxTCK9eTxAkophlMRhNBwg9COpBMJ7qBD9DrnA8Iasc61c2yxycnFOuuX1N5pmmCsN8bB2SqnCg3W9V6cMEG1U4arQSBY6vBTbHpYhsZQyma+6tKzhBAammC+6nDruourHX1uusLf/2AWqcBtNmm6LvsqJ/i520a79ipno9DwQrpx1kR7qthk/1yV0XSUm0Z7qLsBX3pmhtvH07xmS47j+SYnCg2myw79EUV0yepSKZ45XeHoYoOxdBTb1Nk/W+OH01XeccsQ470x3rKxl//+zMyySb6jMt3dH+dkocHfHcrzfL6JJBQ82O3fo+cHCAUPHS/yt88vstDw6I0a3Lcxw0+sT3O01OJgvknCDL/fTnq5Q8KUJvBV+G1I4IfNCKdJ8Bu7RxhL6DiOw0OH8zxxuo4tfaZdDVd6+DJ8vx9IPC80Ivb9kHRqpo6GwtZDQUQrkMzV3O736AdhhLzjPVdzA7JRi/fdNMj/8+hJpssOcUtHSknDB90QvHNbH32X0Y3jUvCjancCLzwhXUOIHwc6vUbsLhMXEjzous7zzz9PIpG44juvq0Xspgt1Gl5ApeHiB5LRbLLdQkgxW2qwe/MA69tN7OdKYYH0aoOLqeucyjdXLO/gnS/fxA/+6vFQPNEeuEsNF8cLeM8rr+u+7007Mxx1szz47GnW5eIEEraNpvn3r9+xzNx4NbRaLfL5PI1Gg0cffZSenh5yuRy7du3CsizuvMPjuwdmefzwAkLA+159Hc+ezFNuuLT8gNlSE1MXbBoII4cRS2csG+dre6d5w00j5JLLo2tv3DXCn37tIDHbwNTDCTUeMYiYOhP9+rIuFfuny9Qcjxt6MgwvqUv7uydPsbE/ydbhHv7no8dZqLVY3xtHaxSp+mHkabJNsDIxk3LTI2EbHJipMpKOUmsFRCyD3RP92EuEIR1lZofsKaW656dQKNBqtVg0+sP03BICCJ20t2Sq0FgW1TrfNbt9KMnzs1UyseWTsuNLTI2uEAIIJ3MFWweT1Folig0PUw9T5ZWWz6u35JjouzChLNRdvvTsLNm4GXr36T6uF3rrfenpGX7x7nWrXqsRQ0Ox/LfjBor9szVipk627aVm6hpxW+fRY0X2zYSefJauUXd9vjlVY1vOpK/dlWqx7nF0sc62gWS3RrE/aVNzfP7luXl++WXr2T0Q5w0bMnz1eBFfyrYqVjAcNfHKLf7rZJlFP+z6ACARNL0AhEC0TYG/c7qKpYcihOPlFn/69Azfm6qyayCGLyVChMN32tZZbPrd79MLQjNvnTBAmrINvEDxx3um+aN7NiKlxvMlyeahXk7my7hNF6HrqCCg5Us0QtKvZNhaDA1QKmxpFwSIIECh4boe00WP9UmdaUfQdMNWY2lLIAON997Yx7qUzW++fJy/3z/PntMVGr5itMfi529dzy3nKOe4mlgjdmu4JJxjzvtRwxqxu0QopXjmmWdoNBqk0+lzCh7g6kbaruRzlFL81bcO8ZmHn6dWr6OZNkdnK0wu1tjQ34MQgts2D/CRt93cXac3GUGeY5t+IBk4T8eHTUMp/su7dvMXDx/g6GwZgWC8P8n779nK1pF095gMXfC+12zlbXdNMFdqkIiYDGZWn+SllBSLRRYXFykUChiGQTabxbZtXvayl634MSajJm/YNcYbdp0pHN9/usSDPzjN15+bJRUz2TmWIWZIWq1QFdxJHx+dq64gdrdsyPKOO8f5hydPLTsvI70xslGn+9zxJafzDWK2sczaxdA1YpbBI/tn6U2YPHe6xEgmilQSy7I4enIhPLdKsP/UHBO5GAdaAdWGR9OTHJwu0Z+K8kuv3rRCcatpGlLKbtSyUChgmia5XI4tW7YQj8f5/pE84nh9me9a55oSCGxDW2am7fv+Cr+1DtnbMhCnP2kxWWgwlIpg6BrVls9CpcWdo/ay1Gh/0mZ9b5T5qsOdE70s1BwWqy4IGBOCf3vHhQ2dAfbNVBGwoh4ul7A4XWwyXXYYSUdWrDecipCKhiS5k9YtNjy8QKJr2jISqgnBqWKTeN1l9/qwvjMdM2k0HfbOtxjINsnGTfZOV0jYJhuWRD+lUtimzlylxULNZbDH5j1bc7xmrIfHZ2o4gWRzKsIj++dwhaActNOvnU5eqvsARTtrTUhCvSDoikgen64yWw/bZDV9SdnxafmySyY6Z9IkJHkagrm6iyKsv/vuZJmhmNntQFF2A6quRLC87ZjQBIEMUIRmwbqmITQdTWgkbIOoCklcoBRWNMKGCORbPiMxjbv7dcYiPtWp4zx13EUpxZ2G4O5NBp4XELElvbLMwkJrmSDkQp6Al4MfZWK3hjVcLtaI3SVCCMGOHTsuygj1pULs9hxZ4NMPHyCbsLFxSWdSrO9Lcmq+xoahFB/92VtW+MRtH80wlIlTqLboXUJQmq6PpgnuOEddVAfbRjP84XvvoNxwUQrScWvFYKeU4thclWLdYSAVXUbqlFLU63UWFxfJ5/M4jkM6nSaXyzExMdEtLJ6dnb3oQXT7aJrto2mGexPc/+xpsskIrVYTzororFYfKITgdTeOcOd1/RyZrXB4tsreqRKzhxf5/qRDQy8z0Z9gvuLQ9Hxu2ZBdJmJQShGzdGZLDYq11rJUZl9fjnQprLmTUiF1QU8ixs0Ri2LNYbLY4lVjgvEeh/lj+5g/BqZpYhhG12zX87wVUctl38dwEu3p0Ny1Q7yEEGEPV8tg+2iGSNt2YmkEcLXnlg4/f9sI3zyc5+lTYZeObNzijVuTRJstfN/vfr4Qgrfc0M/nnphiqtTENnTSMROl4E3X9zOYWknGVkOh7mKbq0cRhRA03GDV1zRN8FM3DvDFp6Y5XWphGxoH5mqcLDQZy0SZqzqMagLL1Gl5AYWGz9ASsmfpGjcOxbE1yWzVYTBlM5aJcqzi8C/Hi+iaIBE3KQehqlUHhk+U+Pnr+9GEYChu8VPt38q+mQotX9HUQkLUrLvoUbObQhUiJFRnXY4hQRMh9QoUHC820TSB3/YIpO1bJ1UoRGrUXDxLa0d1JboIyXvDDfizJ6e4b2OGquMzqBQ1t90hwtDwZZhiDzPCWrjddm9aV4ZecromiJkaLV+yPRfjVMVhIBmlP25y51iKrbnV7VQ6nUFOnDiBpmkYhkGj0VhmDN2JJuu6fs6uIJZlveCdQS4Va8TuRxs/Dt/cGrG7DNi2fVFEa2krsCvBlRK7L33/KJYRmgB3PkXTNMb6ExydrdATW0lSNU3wO2+/ld/6q8eZLtTDOh6pMA2NX7l380XZTgghSMdXd82fKTb4f7+7SP27j3UnpevXpXnvHYN49TLlcplYLEY2m2Xbtm0XNJO9FNyyoZd/enoSeZbnmuMHGFpYUyUpnwAAIABJREFUP3cu9ERN8nWXLz8zRcLW2dAXp1mvsW+qwnylxSu3DlAeSTOSiVFquEwVGzi+JBMz0YHdG7NkEzZShdGaTleA0UyM/dNlNAEjvYnu8bZoce/4AO++dwtKKcrlMgsLC+TzeXzfJ5FIdP0NXdcln88zPT3dJWOmaXYnxJeN6HztcJGIaZCMWrQCCCS85451obihjbPTsKtFUmzb5k3Xm+weNJhbWMRtFEhpKQYnJpbVlEkpSUV0/t1doxxeqDNVapG0DbYMxMkm7G5ksNjweOJkmYPzdeKWwR0b0uwYSnZJ9lBPhGenqiv2I6wNVaSiK4eylhewf6bG0XyDsUwUU4NvHSnS8AIysbCDwv7ZGsfzTe7ckCFoC1RyieXXrKkLxlImQ/1JfmJbHx/86mFm8w0sUyeasGg4YbcMs13bdv+JIo5S/NKNg8s+p9gM7V4UUKk6OC2fKGDFTGhH5MJ/2udvybqBDD3eENCouximjmnpYeqI8LcpRGj9bBoCt+XTavn0piLt1yXNpo/X8vn7/QsIpZite9TbtXRSqe6EZrTb7Ak0TML6ufB1nWzUpOVLsjGLQMHLxlL88m2jK8792VjaGSQWi9Hff27T5Y4n4NLuIPV6vfvY87wueTpXa7jO47WI3Rr+NWKN2F1DvFQidpOLNaKdiXvJ5+iahhBQqDqrErB1fUn+x4dexWMH5zg2VyHXE+HubUN4jTK1Wu2y98fxAv7zF59iruKxflDHcV2cVotH95WZXyzyf7/7VrZv337NVGETA0lun8jxwA+nSVoQ0yX5aoua4/P+V20+rxq32vL46++dIBEx2He6RNMNaLUkti0otwLuu2mE8b4En/veCRYbLhoCXROcyjeQSvELr5wgE7e5bWMvjx3LM5aJhRYqmSinCnXmKw6ZmEXD8Sk2XEwNXrHOZu/evdRqtW5UbsOGDRe0Q+gY5zqOg+M43J5wGEgYPHmyzGy5TJ+t2Nan48wcYM9C2DnhXH+6ri+Loi4uLiKlJJvNsmViA8lkctlkdrrU5KmTJYpNj43ZGDeOJNm1PstN69SKCOBUqcmnHp3E9SWpiEGp4fLp71W4cTTJO28ewtA1ruuL8vABqDRdkhGzWzc3W3HY1BfvqlE7KDY8PvndkxzLN2i4IfHyJRgC7t6Y4chCgxOFJglbp+lJnpupkkuYZGImPRGdcsvj6GKDhboLgU9Mk9w0YfHfn54BU8c09FC40BY8SBWmTRFQ8yT/fLTAzf1xbuyP893TFb49WWax4tCqu4z3Rmk1fUxD4HsSv+pgWAa6ruH74b5altk9P0qFfY/DcQA8N8AwdQIvQNO1LqELvPZvW9dwpY8MJKWag20bNJp+t94uULA5E+V4oUkjkCRMaEi6PnqBClO46ajObYNJ9s9WKbR8bFOn5kmyUYOopZG0df7N9QNcbRiGgWEYF9UZpEP2OkSwVqstI4We5+H7PvV6/bwk0DCMq0rGruSzXqw2aGsIb6l+HEj5GrG7hhBCLKtbupLPuZIf+3hfkiePLhA9qz4pkBIFZHvOnQ6LWAavun6EV10/0l021yhf9v60Wi2++uQRjk4tkrQUjWYT27aJZ7Nkc4LZUpO5pkZv77UhdZ4v+cx3jvLtg/O4QcC+6QZCSu67Jct/eP02dl7AO+/QTOgL9vx0BSll2PUhEFg6lJoOH/vyXj76lu1U3YBO0VIgFaYuGErH+Oq+WW6fyPKO29fT9AJ+eKqEakddNg8kefttY5ycr1CqlBmPBdw4ZJO2FLnh8cuyyekY5yYSodp5eBjuunH5+84mgB2rnlKpFNrFtKMlQRB023Elk0lisRi2HUbdGo0Gtm1jGAaPHFzgKz+YRQiYr7pMFhsAvH5HP2+/ZZRNffFl2//HfZNYpsFg2kK1o6i9cckPp2vcsq7JjsEEPVGTd946xBf2TDG1UKbRbBCJRNkxZvGm7Vk8z+ueGyEEf/3kab53PGzHZ+kanlSczDfCcy1gS38C29Q4kW8ileJEvsmbdvRzx3iGhw4scqLYwNA0opZO1ZXMVT32z9c5UfMwNUFfLka9dUawEG6Ybp1boOBjj51mIGZSaIV+cFIq5gpNjhRbRA0NT4AfKFSgcD2vLW6RWJaOZRqgwmsHwhSrJsD3AnQzJHMoCLwgvMza9XrdKrv2QscNyV9H/FBp+cRsnUzMImnr7JmqEEgYjJtoWtgDtuYEaCiMtj3S7rE0P7UtR8kNOF5s4gaKzdkYOwcSRM5jNbMarmY0S9M0IpEIkci5x6+OU8H4+PiK/sDVarX7uFM+0Ok2cr408IVuONfEEz/a+HE462vE7hripRKx+9mXTfC9g7N4S1qGKaVYLDd5/c3ru/1Hr8X+BEGwTPRgmiZHZj3i0SiGaq5ok6ZU2FJs20h62bIjc1WKdZfBdLTbjeFy8NnvHOWBH0wzkoky0htjIhdjtlBlrtLq9pU9H3wpKdZcHD8gYRsoBbZlI6XEEHByscJnHvoBOdMlGhO0fIFhaGTiFrYhODhVYP+JWTYMpPjFV2xgtuJyarGK06iREg2cxjy7tyTJ5TaRzWYxzUv38rtUnE0AW60Wi4uLlMtlWq0W2WyWXC5HOp1GSrmCAJbL5e7z2arH559v0RvVOVyW1FxF3NbxFTyyf47JfJ1fvHucm9eHdWcLVYepUovRTGiNI9qpV4FOOmbx1GSVzb0Wi4uLlBYWuKdP0RpOEUmMMpJNMZwKI3VL7V8KdZdvHM4jUCQjJm4gWag4eFIRSMnB+TrFhs94NsJdG1IEEuaqDi+b6MU2BP/wwzn8QKEJRc3xQcHNg1Fmag6gdYU/kfZxnRGhLJ8UGq7PMccnGw2V1OgwlIszOVcFXyJ1LSRdHdGDUqFVjBD4vsRxfSIRE6UEQkCr5VGrupimhm2DEmFaV8ozaVTa5C8U+ChQAtVuMaa36/ICqYgYGpqpsS6h4wmNTMIi07aiqboBC3WPV65Pccdomk3ZaNca6ebhniu61l7oNGVne53r+0IIgmAZ+XNdt2sK3flb+pmrkUDf96/KDf0a1nC5WCN21xAvFWK3a2MfH7rvev7sgeeo1H2a1DA0jZs39vGh+3Ze0f74gcTxJTFL7y5fmq5zXZdMJkMul2Pz5s3ous6UOsm3jtYhWF2ksDQVOlVo8LGv7OXkYr1bi3fDugwffuMO0pfogVWsOTy0b4aRdsuizvZS0bA36jf3z/HTu5fbLi8VECilWN8boe767Tb2gADDNFBKYUrBYG8cGY0zGlGkohZKSXw/IAgCgsBHSZcT03O0CtM0Go1uvZBt2xCLkcvlsO3QdqRer3dTodfSrLRTu9cRqhiG0f2+Oi2yOtB1fVkE8Gx8+QczDA3mCQKJUyqTiYd1prqUVB2fVr3Kn33th/zbHTa6Jii6gmLRJeLbGIaObhihB6TvU6k0OViY42iiRC6X48Ybb7wo0VKl5FJuBQz22AjCqCEIIqZG01N4gaInanCi0KIvbhG1dDIxA1uTzJVdcnGTzbkoVcfH0DRM6RIEPtLSOdkKwnpTX1Kru1jRlSm8johhMd9ESYUTMejvjWKZOrals34oyfGZKppSWJrAVaFyQrVVFKap4TgejhPgeQFOK0A3QlGFroPvS3xPYpg6Szfdeex7AYIwgmeYWlfx2rmWo7rWFe8YmuAnN8Q56VkcyjcQQG/U5F13DLJr6NrbkbwQuBQiqes60Wj0gt2AlFIr0sAdMUij0WDfvn1dcmcYxnnTwC91Mci/Nvw4fBdrxO4a4qVC7ADedtcEr9o5zGe/8m02TGxi60iG7WOZy7qIhRDUWj5/8tXnuP+Z0zheQDqi8fqtSXZkFfF4nFwud852aXdt6efT3zyE5y4/prrjEzF1drVbmrW8gI/+7TNUmh6D6Uj3POydLPK7//hD/uu7brmo/Z0pNfm7J07yL89Oc2S2wrpcnIn+RNh8vH34CSusmfvp3euW+cEtvfMWQpBLRrhjIseXnz6NbeoYukYgFU3HJ5OwSUYNNvUneOZUiXQMhNCwLA0pdRqNAM8PML06ZjLJxMQE2WwWy7LwPG9ZJKxer1MoFKg2WjwxWePpGRcvgO0DNndv6GEoHVtRB2dZ1kUTQM/zKBQKLCwsUK1Wu7V74+PjV9TKqGNIfLzUImoZmEvS/x4+A30pHF8ytnUTY5kIjZbLNxYOousSr50e8/3Qdb/QUtw2aNBsNpmZmSGfz5+zBnDpPttGx5gZPKVotZWdmtBpuLLdKUHDNnROlRwGeiK84+YhIraN1pAITWAbgsD1aNQbtDyfTG8GF8FEzOBYzWduoR5+jqljLOkHK6VCoWjUvVDJqoW9Zf2FOmMDCXRdw9A10qko9Wqre4OglERJiEUNNE3QankEEnQp6H6lbUEDSAIpwQfD0LqdMnw/wHfCaJ1sizBMQ0fXwtcEEDd1ku1620rLJ2lp3DwQ5c0jw9TcAF8qUrZ+zSa3Fytid7UhhOhee2ejVqtxww03YBjhDV9Hub6UBHbKGzpp4E7byT/4gz+gv7+fZrPJJz/5SYaGhhgaGmJwcPCijO4//OEP80//9E9YlsXExASf+cxnVmRFAB544AF+7dd+jSAI+MAHPsBv/uZvXrVzs4YXH2vE7hripUTsAHI9Ue7amOSuOycu+N65cpP7n57k4HSZ4d4Yb9w1xsRgD4dnKnzm64f5+8dP4UnFQFwnHdWptQw+91SBX753G+/etem8n92fivKh123jd7/4GFqpgW3qtNxQkfrRt95IrD3xPH5kgXzNYShzhhwKIRhIRTg4U+HgTOWCxzFTavLhzz9N3fHJxi1O6hqzpSYLlRa3T+SwNACF40t6okZ3kF26vbMnht943RaePVmkUHdxPB9NCNbnEuSSFrap87O3jbF3qkyh2sRQHs1mkyCQlH2dV24d5J5XrBSGdO7ek8kzUZKWF/DxBw9zKB/Qm06ha/B8xeHIXodffXkvEQHVapXFxcXuxNG1JGlHBZb+KaWoVquUSqWu8GFsbIyenp6rNvltzMZ4ZrLMmeRkCNX2Z4tZBk7ghuSn0WBhYYHrIjW+ecphLJtgYGAA0zTJN3ySAn7uNRP0RM7Yuiz9q1Qq3cdLrTI0wyJj+syXPaKmjpISqcJ9iZga6ahJpeXjBhJDF3zwpkF2jaXDybY0T6WQx6tAJpkgm81hWSYCwWSpyc/u7OcfDiwyrRSmqdOsucSTFroR2oP4gaTZ8PDa9iud66flSap1l1SPja8U6bhJzBTUmv4y+atCUas5SAlKKoJ2TWA7qBd+vyLsNoEKo3eeF6ABga+6Hou6HqrgTV2wPRvDDSRT5RZOoIgaGnNVh5hl8LObE93odcK6+j5yLzZebFWsEKIrBjk7+n02fN/nE5/4BJOTk/zWb/0WQgieffZZvvrVrzIzM8PnPve5ZePDarj33nv52Mc+hmEYfOQjH+FjH/sYH//4x5e9JwgCPvjBD/LQQw8xOjrK7t27efOb38z27duv7MB/TPBSi9cJIf4r8JOACxwF3qeUKp1vnTVidw1xNYndC4mnjy3ykb/ZgxdILF3jsSML/P1jJ7htPMF3Di1SabhUWhJD15iqSoQVZbwvgedL/ue3j/LmW9eTjJ6/nuW1N45Sm+mjYA0ylW8wMZDkNdcPL+tLe3i2ymo3qKJdOX4qX2f1hOAZfPGxk9Qdn6F0DKUUcdvA9QMCBQdnKmzMRajU6jQChw3RGKdOncK2bSKRSDcKdrbdx0Aqwv/xUzv41DeO4gWSqGXgBWEk6Odu7aM8c5J7B1v80xEHVxnYdhxhatyzMcv7Xr7hoqNq3zm8yKG5Gusy0e41EOs1WKg6/MuhOh+9b8uq63XSRM1mk3w+z/z8PNVqFV3Xu5EtIQSLi4tUKpVzRsEsa6X34IVw87o0D+yfJ2HpLNZcImaYiq22fAZTEZxWC6deZ/LADyjGouRyOd7zmpvZcrrOg/vnWWhIFA4bsjF+ZtdQ11T4YibHpdGRd3tz/OWemXYv1wA/CMUsSRN29oBuSEqO4GVDGmLhKN851cSyLHK5HG+/Y4KvPF+kogROS5FQARXHJxe32DWW5u/2zmFqYe2aApo1l1jSxnF8ymUHs03yzkbd8UlKC6XgrZszfPYHc3hnvVFJ1RZO+DhOQMfgLqzBCwmeoZ9R42oibPclEGCeodOKsM1Y0tTosTV8pSGlTSpqcOdoD2PpKDcMJliYmfqxiKCdb3svNC73GA3DYGJigo0bN2IYBr/0S790yZ/x2te+tvv4jjvu4Etf+tKK9zzxxBNs2rSJjRs3AvCOd7yDL3/5y2vErg3xkqN2PAT8llLKF0J8HPgt4CPnW2GN2F0GLpawXS1i90Ki5QX85799OmyxZIowChSEacDPPVZm51iapicwXIeoHRrNThXq9PVEiLcbm+8/XeL2zX0X3NZgj8lb71qdnACh39s5a5AFPVETudLarAulFN85uEBfMgKEPl/bRnp45kSBSstnoe4yXXGQSmP3+iQ7NgxiCrlMEeo4TjcduzQKti5i85F7RtlzssxUvkbG8LiuVyettcjl+nnbddfx1nvhyHyNhhswkokycB718Wr4xsFFemMryVUuYXFwrkap4ZGOLSfQjuN06xsbjQaZTIbx8XEymcwKQtmxi1gaBVsqhHDdsBfo0rTTan9La4QStsEHX7mBv3j0FMfzDWbKTUwBvbbEclpM5i1+/rZR7rx+3TLC/PJNEW4fz1BouFi6Ru856ielVJwut3B9yVCPvcx/b2l05C23biASj/PQgQWO5RvMVx1ycYsbR3qIagGzhQq2cNneGyGZTJLNZnFdl0ajwenZBY7POCy0FL4MzX939tv8m805TkzN8OhkiSBQmIaOpoGSUK+0MNr7EqZ6wdQ0pFJ4bQIoFTTcgFevz3DnaIZPPzN7Zt9ZTkJMUycIJL4fqmZFO7Ksaxq2bXSNia22d16gIGkIAkRbJAIjcYNXjvdyvNgkbum84aYcd61LYV+ikvVq4sWIoP2o+dhdLeHFpz/9ad7+9revWD41NcXY2JmOPKOjozz++ONXZZtruPpQSn1tydPHgLddaJ01YncNcbXsTl4IdEQPD+w5ymKhTCqigWliWhbxeJxC3QFc6q6kGz7gTMH2YqVFvC8Rtiq6SvPGXdf18dlvH8XxgmVdHGotj5htcNP6Xp6eP/8xKSQKiZRhLVy16VH3FZ3DGMlEGUhFaHqST31/nt//metXHZQ7zvlLo2C1Wo2NhsbmYR0hwiL6YrFIvV5ndnYW27ZJ2DbZmE1EeLiudkmF0o4vMc7RBUMAbhAKOjqtxPL5PJqmdbtzxOPx827rYuwigGVK2A4RXEp8OwSwYxWhaRpvGnS5Tpc8NRcw71pEI3EmBnp4485BdpxDWWkZGoM9ESaLTR46OM18zWE8E+WODRn6EjbH8w0+8/gk81UHIULCde+WPn5y58CKbiG6JrhvxwAvn8hyYqHCw89N8fiJIntPzhGxTLYO9vDhN06w7iwl9PF8g+8dOMrWdWluNjXcQBL4AXPVFntmPL55uoTjBvi+wvEkmhaKMjRN4Ps+hg4mCqNN6gRgCvBV2Dc3guDJyTIPH1nE8dvK1TNSHDqJIE0TWJaBrkv8QCIA3dAxTb1bU6epcAAfStloSnG66iJQGJrghr4oH75rlFybIJ9JDS6vG/1xN9N9sY7vSrYZBMF561zvueceZmdnVyz/vd/7Pd7ylrd0HxuGwbvf/e4V71st2PDjfA1cCgSwypB7NZATQuxZ8vzPlVJ/fhmf8wvAFy/0pjVidw3xUo/YeZ5HPp/vWlvEYjGaHkQiUTJn9WztWCp4viSXtMlXW0sGTYEvJY4XYOgaO0bP7wV3sRhIRfnQa7fwJw8eAMA2NRxPYuoav/3WG4iYOnVX8qUnT/GtA/PomuD2jVlGM1EyMQNdE1iGxjOnSoyko0wWGhQbHg03QCmFoWs0vYB0zEITcGCmwv7pCjtGlnee6Nh/LC4u0mq1SKfTrF+/nkwmsyJNe64o2Pz8/Kok6HxigF3rUjz8/CIRM/RhM4RA0wTVlostfGZPHOZorUoymSSXy7Fu3bprYo+iadp5lYIdVe3c3FxXVZtIJLhtc5pbJySNZotmy0EFeaqnCjxx+tzH/vjpOl98dhZNCKKmzr6ZKg8cWOBdt4zwhaenMXXBcLsNmRdI/vm5OXQBP3n98i4PjUaD+fn5MN3sSGaqOpF4AseVtBScrkvqXrDiOP7H46c4MF8PFwjIxS0mslFGMgm+dLCMr4FlGUCAH4SCh5YbEInoaAjsqEm96oIXCkAUCiXBtnXiwkN4Po0Aar7WvisSXU+6s28Bw5skgaXp3bZiMcKJpyUVtqHxig0Z3n/zCINJm9mqw1S5yXDSpr/dGeZsM+iOIEhK2VVCj4yM4HleuM0ltWFLJ/urpcr+cRFPXEtciNg9/PDD513/L//yL/nnf/5nHnnkkVWPfXR0lMnJye7z06dPMzw8fPk7vIaLwaJS6tZzvSiEeBgYXOWljyqlvtx+z0cBH/jrC21sjdhdQ7zUiF3HiPbw4cPk83kAstksIyMj3U4PkakS/+PRmRUDYrxtQRK3DVIxg4Rt0PBkWE+kwh6ShbrL//7GHV3xw9XAvdcPs2U4xcP7ZpguNtg0kOQndgzR3xNhodLij75XpBw0aHo+pbrHF584SdzSidsmVSdgoMcmX/c4XWqhZNivtaOKzMQsyg2fk/k6G/sSBEpxaLbKtqFkd9LreO917D9isRgH52rsy7dINapcP9KDoZ+Z9C42CraaGKBWq3Uf+75PpuFzYrbBk8cJ+4ECaVMRNeF9t/YxMjxEb++Oi564Ds7V+ObhRearLptyMV69JcfgJaaHO/B9n3w+31XVplIpcrkcmzZtumAz93Md+2y5yaeeKpE0FZomcISGpeu4UvD7X91PNm4ymo7ieaFIwtA0BntsHjywwD1bcjiNWrfdmm3b9PX1sXPnTv7k0SkW/RqzdYdmm8wt1l1+5e+e48/fvpPNfWGl5gMHFvj20SKWLmj5iprrs1hzObLYYLjHpuL4DGeiVD1FNKrheQG+LxG6hmGHvw9NCBI9Nq7j4wcytEuxdXzHZ6ahMZKyaEmFoSm8ztjQcc4RZxrDhNFm1a6Xay+TikCEPnTZqMnrr8vx724b60YrB5M2g2d14Fj6XQRBsKzmMp1OMzExQSqVWkb8Ov8vjex1xCkdLCWAS/9/ocx7LxY/isTO9/3LVqY/8MADfPzjH+db3/rWOTt37N69m8OHD3P8+HFGRkb4whe+wN/8zd9cyS7/GEG8KDV2Sql7zve6EOK9wJuA16iLIBVrxO4a4mr1ir0SNJvNZTVXnueRTCZZv379qp5gW4dTbB9Ns/90ib4eu0tOW15AbzLS7qcp2JCNUPE1JhfraELjhnW9/NtXbeaOzefuAXm5WJeN8wuvDJW2nfMZBAGf+vphDuV93MDDDRR+EA7iRd+n5gTELZ2FaovrR3p46mQJRykabfVtJm5h6hqapjhdaDLeG8N1XOamJ3ncnSSdTpPL5di4cWN3cizUXX77S3s50o7oCCAdM/noG7eyuf9CMo4QpwoNThaaxC2DncPJcw6+Uko++53DCH0KS3NxAkEgYNHV2JGyuS6jcezYMQ4fPgyc6Ql7rr9/3jfPF56awtI1IobGobkaDz6/wP/2mo3cMHLu3rhL0Ww2mZ+fZ9/JefbNtzAicXZPDHDH7m1YxsUrKjvdK84+9mPPz5NOC0baETmpZNv/L2BfvkRPJKDRbCLbywIpUVKRb0m+8vACY+kIPT09jI2NEY1GKXuCrx4ssGeyTL7uIJXAbgsbYpqg1PT5Lw8e4dPvuoGWJ/nKvnlSEYPZmouHQhgaulLIQIXLAsloT4TTtTDqapk6uqFhnn0joxS2bWALIJC4boAmwlKAmYqLrmtYpo4MFG15RBsCIdSSjhPdxehAXFdkLcFwVHFbb4txNcVTe2bP+70DXTLXaDQuSwm9NOq3WgRw6Rh3IQJ49vuvNV7s8fdy4Pv+BW+OzoUPfehDOI7DvffeC4QCik9+8pNMT0/zgQ98gPvvvx/DMPjEJz7B6173OoIg4Bd+4RfYsWPH1TyEH2m81O4DhBCvJxRLvFIp1biYddaI3TXGCz2wBEFAoVBgcXGRYrHYVfp1zGa///3vMzi4WsQ3hBCC33/nLfxfX3qWZ07kQy8upRjNxvnT99/JV548xf3PnMJ1A2zb5O13beQ/vfl6+i4z8nMxWM1XzvEC/vHZKQI04hEdp+5iGqF3mRtIXB9SEUHLD5gpVDCEJGqDEyh0TRD4HioIj63pSeYXF0EZvO7W6xgf7F0x6Sml+P37D3BssR4a37ZfLzc9fufL+/nkz+2i5zw9ZuuOz3975BhPnSq17wgVCdvgP752EzeMhDVnrut2Sfhcscb/etZlU3+SeDSCG0ikAlsXoeAjs57d45nuvp3LB89xHCaLTT71bIN0RKAZBoGvEdd1Wr7gD776PL/9ugnW9yWJ2Pay417NuPj7eYvvTQkMPYHWFDz7xDxfO1LlP927iZ7IlQ0nlZa/rKZQExqaoWEaJhHLRDMjpHoiNJstms0GUkrsaISEqXPbLROkzDBtfmi+xt89d5pjJQ8/8JmqhTVuEA7aOqGyNGJoTJcaPHsyj2mayLZq2qu7oWFwewWpwvyHJsI2fNtzMfbO1whkGFl0nbAPq97xlOtG6sO7f62dcu0EAtwgwDQ1NCFIWRp1X+LJDlGCXjv08PPDxhGYGrxqPMNHXrmx60HXwblsYCqVCo1Go5vWsyyLWCzWHR+Wml9fyCR3aRTufIRjKek7+69cLrOwsECxWFyW+l2Kpenfi40AXgz+NUXsjhw5sury4eFh7r///u7z++67j/vuu++ytrGGFxyfAGzgofa1/JhS6pfPt8IasbuG0DTtmotA5pbCAAAgAElEQVQnlFLUarUuIfA8j97eXvr6+rjuuusu684vHbf5b++9nRMLNaYKdXoTNluHUwgh+PCbr+edt4/w9PNHuH3X9Qykzu/QfrnHpJTi0GzoVWcZGrvHe0nFzO7g76uAxaqD1TYIDhHWKwkEktA+wBYavtBJxU0cP8AUAZkoTFdkN1oS0TSKLXjTVpu5k4eZO9led0nk43RV8vx0iaFUdNkdXSpqMl1u8r0jeV6/89yE+U+/dYI9J0sMp86Qp6rj839+ZT+/eXcvNEuhAXI7Stha9IgdPkoiFhJme0lEzNI1njxZ6hI7IcSqPngdHH56mt7MLEMpmyCQBDKg0nQ5WmyyWPP5wOf3YetwQ1bwE+tMMpbqpu2j0SipVIrx8XEOlySP/nCakVQUfcmEe7LQ5K+emOSDr9hwWd93BxuzMR46uLBiueu5xPUgrFWUVWLRKKl0GtMwyTdctvZHGO/PUHcDPvV0kW8dLbFY8zA0QbkFvuy2Tg2jYQKEDHuiGkLyw8MniWs+xaLLSUfHsg1MS293b1C0mmGnEV2Gkc6iH4TRYU2EtaciJHFSBghNYFl6V2Ck2q914nK6BkEQ+s/pusZQwsLUBF4gKbQCXrcpy3CPzaMnilSdgE25KPduyrG1b3UhTCf6qet6dxwIgoC+vj76+/u79jBnE0DXdanX693nHaK1Wu3nUjX4xRLApXWXhUKBZDLJwMAAW7ZsWRG9W+2vg7MjgEopNE27aAL4ry0Vu4Yrx0vN7kQpdX5j2FWwdvVcQ1yrGjvXdbuih0ql0u30cP3111+wtutSMN6XYLxvZYoxHbcY741cNKmbK7f4/GMn+PrzcwD8xLYB3nnH+LL3LB3Uay2X3/2n53nyeBGFQhNhn8v/cM9m3nhjWOSbsI0wmsjqA3c4lYa9QZGQsRTHax5oGnVpYdkSL5B4vsKKmKR7e3jfG26hN251I2A/nCzyyJFFHLeBDHwc16Va9ZEy6NZCaZqG4yqeOHCKnWl/VR+4+arDY8cKDLX7mrZaLVqOg+e61FzBnpkEH3jVTctS40ahtGx4aXkBNScIo41SYeoXP/hUml67Dkug6zpOAPvmHaQMrTGKLgglub8q2TPn8zM7M7zjlhEikciyKND/2rOA33DJe22PGRF+ni00vvl8k9euN8kmz3TE0HV92SS+UHfRhCAbW50cXD/cQ1/cYr7q0GMqWq0WjWaDkqexayjBSC7Nk5NVPEMHHxYaLeKWzs/vHkUIwV88Nsn+2So1xydpG+QbLnI5r6Lz1JdgGho+GvN6htOVFlNuGV8TXTuQkAwKojETJcM2XvNt4c2KiG7nH6m67b4gJJAJU6Paru2TKqzDM3WNpKXR9CRNIFCK63Jx3nXTEDFT574tF7YL6qTG5+fnEULQ39/Pjh07Vh0DzpX+PhtLuyQsjf5eiAB2yF9HMV0ul0mlUvT397N58+bLirydLwJ4sQQwCIJlN9jXsjXf1cIasVvDlWLt6rmGuFrETkq5TPQghOjWyqRSqRfljvRij2u61OQXP/MEpYZLum02+/d7Jnl4/yz/bqdGs9lcMYh98hvHeOJ4gYElKU/Xl/zR1w6xPhtn52h4zLvWp3nyWIGoZXQJD7SbsYuQQAVKY7A/Rn9PlKaqkW/41F2JrWvYhsb4SILBVITZcpO/fvwUv/oTm5AK/tvXT/CNQ4tt+bug0vQo1BXjA+ll6UIpJfVig9FsGClbzQfuSDHse6o5YXW8aZpYtk08HsNwFXOOsaLecctgAkMTNL2AY4t1ZspO97wHCt5+68Wr2LYOJvj6ocXu88liA98PaHk+XiBJWqHSU2HgCY1HZyR3uxFuHTyrFdFelyFLEW2Tlo4hcCADan6LUq2Fchq0Wq1l3SCOV+FrkwFFV6FpOiM9Nj93yyA7R9JdAhgEAZVigfuGfT6/t8BxVycasTGiGV6xOcV7bxslZurcOVvle8eL1F2fHYNJ7hjPkIqaLNRcnpmq0BM1EAgcP8CTqkv+VdtZpOMnJwREdIGjFI9PluhPWNiWQbXh4geSWMzq2ooAoSGwr9AEyE5keMnvTnQpIwSBDHu7IsD3cYCIJkhHdOqe4rpshN+4Y4TZpmLPTB2E4I6xFLeM9GDp5ycetVqtq/Y1DIP+/v6L7qF7MbgUAui6Lq1Wi0KhwNTUFI1Go+sjqGka1WqVer3O9PT0qp1QLiUCeD6cTQA7av+OEn3z5s3da3EpAeyMYZcSAXwhcCU1dmu4MoS/6xd7L64ca8TuGuJKiN25RA/j4+PXxNLiUnApx/UX3zpKueF2zXmVUvQlbWbLTT67V/CPB76NrSt2j9hs67MJdJsvPzVLOmriOC6apoXtkXQdQwi+tGeSnaNhsf9vvHYLv/43z1CsO5iCbvcHQxfkEhZVR9KbsEDTma95vGXXMN86UsTQBaYmSETMrqIwm7D52v55PvTqCR58bo5HDiwwlI6066MgmwhTrvunK9wwekZs4AYKyzJ44y0busfYsZI4dGqW+5+bZ+9iwGwDYtEI2Vho4iyDgFqtxkLNZ51Z47HHSsvSv5FIhDdvTfKH35qm1PTpiRpIBY6vSEcNPr9nijs29DKUunCE9pZ1abJxk8l8hbjwmcy3AGh4YU1ZPHpGSdlwfUxd51/2zXHruuXEbjwb4+lT5S6x6xgCq0AjFoWdmzcQPast1b7pCv/4tcPELIvhaDixLtQcPvbIMd6/I0JatPA8DyklVtsz8dfuGqLsG7joDKbjjPQmsNpecTuHkgynIri+5Lm5Kn/ynRMAjKUjoMDSNFp+QMNvGxUK0NSZkJ1oX7aGFqZkTV3Qn7C7XnSariEDheP4RKPmmUFehdYj/jnP8hlioJQCqYhqAt026bF1EpZG0w3oi2m8f2sMrzRPwnG4ywzbwImZWZ7LryQ/nT7CxWKRfD5PJBJhYGCAXbt2vWjjgJSSUqnE3NxcNzI3MTGxqgl2hwAuTQMXi8VVI4DnIn8XQwCDIGBhYYG5uTmazWa3FCWROJNxWC0CuNrzzn4vxaWmgK8EF7I7WcMaLoS1q+cycLERskshQFcqenghcbHHJaXkkedmu+nNziquHzBTanFsIWDLUJJAwd6izz3bevmpG/uwzDymoXcjlUEQIGWYNt1zsMFTT4XRK+F5/NQEPHhM4Kmw9VcrgLHeGHdM9PLy6/rwA4UbSK4bSDKUjvKNP3mUbNxe8R0amsD1Q4HCPzwzQ8zScTxJxAwHc13TuGE0xd7TZaaKTSxDw5cKTYNff80mMhGNmZkZFhcXqdVqlInxZ0/V8LFJRHWEXuO5+SYj6Sg7hpJoIqyragqX979+O5v64vi+v2wC3NarETUUvqmoNV1MTdEbEQglOTjj8p/+9il+/eXDrMsmVm0D1vHfW1hY4A39TR50NWaaJpohcX2JbUgysTORns53Grc05irOiu/zDdv7eeJEiZYXEGmTO6kUs1WHn9w5sILUAXz+mRniltGN1vq+T49SzDkuj5xs8h9eNkpfXx+xWGzZ8ccdJ4z8leZ5fm4S13U5UvJ58LRk0YH5ZmgFMpw0iVsGT5yU5OsB6zIRPKWW9KpVIbnTBUgwjLAuLmKEvVTjloaBpF5v4nsuWttXJvDl8jv3C/zkO+dOytAc+Q9fu5kdA0m+fqzAd0+UUCju2p7m3k1ZUquIbM72PyyVSt0omK7r7RscHcdxmJ2dpVgsLiM+kUikW2d5LSL4UkoKhQLz8/OUy2XS6TSDg4Ns27btvNvTdf28HogdnIsAdpat1gXFNE08z6NWq+G6brc+NZFIrLpPlxMBPPv5hQhg5ybF9/1lYpBLIYBrxO7FxUutxu5ysHb1XEOcjwBdC9HDxeJKC4rPt+7Swc/zA7xALlkv/P/4YgPXl+iaRrrdMksqxUP757lhLIOm6VjWmVSYUuFg1yo36E+Ebc6SySS9vb28e3iYN+5qsn+6iuO6jCZCYqJpVeyaG0560Qi6IymXWlzXF+VUyaE3vtzvq9Tw2DHSw+lik+8fK9D0AjQhMDTB+myM4VSEdMxioj/Je+9az1ylRY+p2JqWUD7BD34QegKOj48Tj8f54Bf2opsmuTZxumGkh71TZU4Xm9iGRjJioBS85/bRrlWKaZqYptmNMlT0Gv3pIjvb3mQLVYfn52uhOlgpfjDn8DsPnea9N6XY3qu3FbANnph2mWtIBmKCl61LsGkow40DA+zeaVHyNB46VOLBg3lOF5tLEohhp4tUxMQNFBtzKyfiTX1xfunu9Xz6+5MUm16XqL9iope37Rpa8f6WH3B0oU42IqhUKjiug67p2BGbsb4M862ADRvOCC7OJwB5brbKVw4cIRIViCDsgiKEYLrqM5GGjKGY8Tz2z3vEdIFE4bHESqSdfhUqTM/apqDuBygVcKJQY6gnwlA6Tr3QRAarW3Io2anbku1jV8t+40IIdAH/8eXruWu8F4Cf3jHAT+8YWPFZq6FerzM/P0+pVKKnp4eNGzeSzWaXkYJLMcC+3AjY0m11UpqVSoVMJsPQ0NAFydzl4GIJoOd5zM3NMTs7S7PZJB6PE4vFiEaj1Ot1nnvuOWD1NniWZV0UAT6bhJ1rLO4QPt/3WVxcZHZ2Ftd1GRkZWfZ65z1nb281M2ghxFqN3YuMtVTsGs6Ls4ndUtFDuVwmkUhcE9HDxezTlQ7MZxuaSilX3M0ausbN6zM8N1Um025t5AWSStNDaJCMGGfuaEXYmulr+2a5c1OO7x5eIG0LfN/DdT0QGr7UeN9rdnLn1uUkYh1ww1n9q5eqADs1X5VKhVcOKf74RJV6tYqhhUbFAQIngLtuSvErf/00XiDRRdjiKlCKw/P10IYibhDVJVsjZUbcciha6c2Ry40vq3E6WWgwWWzSv8QsNmLq3Lwuw4l8g4ip87Zdw9y9qXdFS6ulSNg6UrXtTKTiwHwdU9PQNYHjSzJxk0xPhM/trfHRu3p4+nSd/3VMohsR4hGT+bpk737FL8Y1rre9rgHyDXaLJ6kzFfgUW4qooRGosI5sKGFRbTrcs3kUKeWKSe7uiV5uHkuxf7aK40s25mIMnWV104k+z8zNU6tWsKRJLBIBKwoIbEtHSoVtXHyZwl8/NY1tCJK2ycH5OhEzFGa4vqTgaWztTzAsmxwrNqkjEAYYUuEHEk2A0gSmoWGaeqhmRRERobp1riEpuU02py0iusDzwTC0dn1e+0aoU78pQuGKL1WX3IXLBZYu+JkdA/zsedTRq52npcSpoxw9V4TnctrAXSgFejbhc12XcrlMs9mkt7e3a2D+YqlLpZShBdDcHLVajVwux3XXXUcymTznPq3WBm81AryUAK5GhM9FAJfuU71e7+7T0tTv0vfC6hHAzv+dZVNTU3z2s5/l0KFDV3jW1vCvGWvE7hqj1WqtKnrYuXPnJQ+ULyXpvuu61Go1TNPsTkKdO8+l+/iLr5rgVz/3NOWmR0/EaKc7w6jJyFlty3QBpxfLvH1zD3uPtpivCHTDQNejaELwvpet4+4tF540JwtNnjpVQim4eV2K9UNnWpxt2QJF4zh/9PAR6o6PQpKKGvz6K0Y4WfKoNj2GkzrHC2H3h04679BMiYG44K3bEtiWyeDmzUSjUWzbZq7m8YVvH+E7RwtoAnYOJWl4AYt1F10IUtGwlk/XBANJm6GUzbtuG73gcYykIkz0xThZaOIH4XnTNQ2pJH4QEEfRrDo0fZ0jjQhfm4vQm9KxdIFthnYdLS/gs8+W+PR7blrmM3fzzQEPPj/P//ft48xVXeKWIBPVabo+b5iIYVam2LPneHfCOXvCWx/tpAC1bsF6J+3bIQRjI8O89oYoXz9c4NiCg+M323Y00GMbvOfWkWXHq5TieKHJ4ydLeFJy03APO4eSeIHi8OL/z96Zx7dRmOn/O7ol34ckn0mc2Lmcixw0wC5NIEA5yk1IoBDKtkC7bKHttqQLZQvbAt2ypdtCy3YJJG2BkJgmXAGWEAI/oCRNSDgTcidObMmy5Uu3NDO/P+QZRrJky1figJ58/JEj65gZjWaeed/3eR4/zlwTMnKP+CG+jxn1Ap3BGEe7QhzuDKsxXTKADvSCDlkGq8WAIMQvIAShx1vOpEOOiggyhEUJT1Ck0qqjURSRTQZAxoBMNCYhSjJ6QCZexdXpZAwCVOabKLKamWy3cdm0MsYW9l1xUqo7LS0t+P3+hOSX4fxu9xcDp0AURYLBIB6PR53ntVgscYGPyURHRwcdHR1x9XMfBMhgMAzr8ivVQrfbTXd3NyUlJYwZMyZjY+VM118hgNoqaCoBlGIpBKj35+fn43Q6qaurw2zuPd6hXRYtkiuAHo+HdevW8de//hW9Xs/ll1/OD37wg37XMYuRQbYVm0UvBAIB1dC1uztuC1FZWTlk0cNwHTQHI+hIrsrpdDpyc3PZvXs3kUhEJZxKq0OZ+TGbzYwtMPOrxdN5ZNMB9nvibUSTQcfY0hxyzQaikSiRaJRYNEpXROYfa4s5dVY9a081s+1QOzuPtJNrNvCPE+2MLc3pczklSea3bxxg3c5mpJ6ZPr1O4IJpTv71nFr0OoG/HfDy1PYmauy56HVCD/mRWPtxJ8U5Jkry4yauuo4IvrAS0h4nBGfUOfnGGeXEohG8Xi+hUIgj3gC//ruPUEwmz6wDdKzZ1klXWMJq1KmEbqI9h9I8C/5IjFPGZNaaEwSB7y0cz13P72af1084KvaQTXDmGSkvycNgMBDuDLGlKcg+TwCp57My6nXUlNiw55roCMb4++EOzp5Uqr621aTn0pnlXDKjjMPeIPs8fkwGHdMq8ii2JSosZVlWT3xK9bOzsxO/369WASHeSrbZbBQWFmI0GgkGg8ywG1n19yCSDBZj/AQXjkl4gzF1Tg/is3p/ePcIr+9tQ5Lic3HrPnIztSyXOxaORy/EjYL1OgGbUU9YlDDolIoaHGgPqeueuH8LGA09Fx3KpynLCD2pMCaTHjkmE4nJtAQlJpcV8JNzK3nyg2b2tvopsBgRZZljXWGCMYlco4DNoKO+2MCS8SaEWIRIxI8kddO8201bCtKjeMwphtGlpaXU1NSknQU7HhBFMWXFKR1xyiQCD0gggOkykNNBmeNzu910dXXFLw4GmJIxUGSSg9zR0YHL5cLr9ZKbm4vT6USv1xOJxI8Dzc3NvQhguhQQq9WK0Wiku7ubF154gYaGBjo6Orjiiit48sknqaqqGjUX71mcvMgSuyEiFoupooeOjg7MZjMlJSXU1dUhSRKHDh0aFtHDcLVQMyV2qdIelOfr9XqmTJmS8Hhl9kc58WsP/HI4zLeninRH4irTjQfg1b0+pDAYDUZMRiOyxYbNIPPtRfXqQXb+hBLmTyjJeN1e+MhFw/tNlOaaVLWrJMm88KGLcSU2Fs+p4A9vHcJq0JOnqV6ZjTLuzgD7uvxY9RLNfkCnozBHjyTFSUdUkumIClSUlyV8Bg0v7MZklSnvEYgcbPUTleNGtBFRIkenQxJFPm7qpDynC6tBxxi5hV27fCr5TVX5UE5y3R4P140LsslkYMMBkeIcM858S8LyR0WJdw60E46J5JgNPT5tMp+5fQhCLpIs4wun1nMKgsC4EhvjStK3hJV2lclkUhW/Sh7r2LFjsdvtmM3mlCf/zZ95KLVATJToisQHzYtNAga9jv999wDmWDfzqgt43x3mlV0t2HNNaoVDlmU+afbx8DtHiMoyW491YTHE/d/8vhg6QRdvmxsEYlFZrQYm7956xdy552OTe/YLXdx9hopCM7IcX8YHL5qMIAjUleawascxNh9oR5JlyvPM/MPYQs6sKaKqwEpBipQNLQH2+Xy0tbXR0dGBKIrqTJtOp1Mv+lJ9/pnOvw0GSrVQUY4OhGBmaoOSLABSRiCU3xWxgaIAN5lMiKJIIBC3ySksLKS8vPyEtn5lWaa7uxuXy0VbWxv5+fmUlZX12SJXkG4GMhwO8+qrr7Jy5UrVjqWiooJZs2bxla98hbq6Oqqrq4/TGmaRDgLxTO6THVliNwgo3kxtbW2q6MHpdDJ58uSEL77P5xs2g+Lh8sRL9zp9zcolt1dTId3sj0IEWltbEXpiqZadVo3J2sHGPR1EohLdkbji8xvTc+g4/ClbGz+f+0k++VkslrTDzE9uPUqexaCSuvhyCeRbDTz996OcO8VOY3uQ0hwTMVEkGokQiUaQZcgxGAjFDARlEIlh6TGpRQdRScJiFDjsDbDb7WNKWXy4PxKTeO9QO6U58TkcUZJpC8SwGPSYDXoCURF0OpB1yLKEwWzjkWtnUJ1v+Pyg7wuyu6kdgxzFIkfU6ocsy5jNZvLy8qgdW8nkOjMt0aN4AjFyTZ/7yLX6onQGY/jDImFRJhaMYTbE47LQCxxqC1BdaGVM8eASQpQ5MI/HQ2dnJ3l5eTgcjoQMXQV6vZ6IYORwIIbNlEfdGCdN73VSUWxUTX+DUZHdLX4iUYmoKPLIdi+FH7ejk2WEmEh3dzh+AQMIOh3hqMzqHX4cOUZ0SHFD36iAQS/EyaosI0o6zf4Zz1tN3sV1GlKn3ArC5wbXEVFiTtXnnpA2k57vfGUM35xTiS8sUmAxYOzHYy4UCiUYBtvtdmpra3tVg1Kd/DOZfxtM+zMWi+HxeGhpaVFtQPpSjg4Vio+dkniRCso+1dTUREtLi0oYc3NziUQiGWUgK1Wx4RSZ+Xw+XC4Xra2t5OTk4HQ6qa2tHZCiNfk4GIvFePvtt1mzZg3btm3j61//Otdeey0zZszA4/HQ1NREc3PzsPkQZjF0fBEqplliNwgEAgFMJlO/oofhTJ4YCWLXV1UuEzKXDuFwWBWJ+P1+CgsL1eqA0oq5dxL8S3eY3c1dWIx6ZlQVYO5pzSVXfkKhkHrVHwqF1GVNbnkcafXhzDPHqzEacmc16mnpCtPa1kY4FKY9GsBoMGAyGcnLzYunR8REysxx4uHujsTbtEK88qUDxttzCEZE9rX48YVFdh7txKCLt3GVzRSOSer2AxmTXscp1QUEoxLRmERZvpmJzjgpNJrMPPtpIw3vNxGJxghHY0wo1PHPp1cya2wZZrM5sf0ZDHBDvYUV73vZ3+yPG+X2tDc9PjE+90U8PD4YlYmKMjkmHb6wiCPfzIyK/Iw/PyWzVjsv158aMipKPPL2YdZ95CYUiyuKqwos5JsNREUJs0GHDHFSJ8Zn1qKijCcQoyuiIxyTmVGeh8nw+UlUFCUOun0ICOSZddgMMp0hEX9UIorAvBKZ/SEjHTGZWCyx/aold3I87qHXMss9s55xgYXA0pm9lb0Wgx6LIT15UJSsHo9HNQyeMWOG2npLhUwFEJm2P5Pj7/R6PcFgkK6uLqLRKHa7nQkTJqQc7D9ekGWZ9vZ23G43HR0dFBYWUl1dTVFRUdp9Som1065/IBBIIMHKsSAdAVR+0pGzQCCA2+2mpaUFs9lMWVkZNTU1QyKMkiTx/vvvs2bNGjZv3sxpp53GsmXLWLFiRcLrVlZWqgraLLIYTmSJ3SBgt9t7+Relwmgjdkor1+/3q6+pff3BEjltWLzX60Wn06meUjk5qTMuAex5Zux5vaOTMmn7aNteCvkpMAt0+oMYdQphBZB7CJdAu6uRaU4ze7wihTnxg70yKNsRjLF0biUmg47fbNqPPyISEyUKLCbGFFuwmgwEIiJPvNdIRzAan+eSwdUVwh+OMbksF4Nep6ooo5JMoc2IXqcj16yjQ4ziyDcjSRLt7e3896b9vLa/i0KLgUKrCUO+FXdQ5Jd/6+CyoJWPm7rJNRs4b4qduWMqEASB8cDpp8gc8gbx+MLkGnX8+LldWE1BkMGoh0BUQpTibWA5LGHSwdfLg3z6ycdpq6A6nY5AIKAmGsiyTGlpKRMmTOCYH175zINrj5uJDh/nT3HgzOtNWn69+QBPvd8ExOcRJVnmsxYfJr2OsjwzOSY9Hn8UX892lXra1XqdjogY/4w+cfvINeuxGHTYc0w95C9OEsVoBKPRSHmhGYPegC8SQ59nxqoL0+2LEEMiXofTGrgo+bCJ35se32IkINcgUGwz8S+nj2FiPzOcyn7n8/lwu920trZisVhwOBwjYhic6fdA7DG7bmlpoampiWg0isViURMgPB4PHo9n0ORnsFDm09xuN+3t7RQUFGTc0oT4MSnZAijd+0Sj0QQC6Pf71ZnGSCSScDFoMBiIRqNq6k1paSlTp04lJydn0NtAlmV2797N2rVrefnll5k8eTLXXnst//Vf/9Unyc9itEE5OpzcyBK7EYQ2o3A4MBhil1yVs9vtHDhwID771ofoQfk93bCz1rrF5/ORn59PaWkpY8eOPS6O+FqbAgU3ninw36/vw6wHMRZDpwODwYhfkpk/Lp8HtofY3xqiPRDD3RXCaYt/gf1RGUeOgVl5Pl47FKI9GEXX8x5d4RgHvUHGFFpp80eQ5HhyhkJWTQYdu90+ctqDVBdZyTcbaA9GMOp0VBXGKzLRmIgvGKLepmPLli3orPm8cyxCtb0Qg+ZEYjPBx83dNHaEKM2NE5vNe1s5e1IpdyyqRaeLk++aEhs1JTa2HekAQYcz30pTZwizQUe+Xo8oy0RiElajnvOnlnL+P0xMmH0MBAJ4vV58Pl/892CMTzt1hGQDtaU2Th1TiMlkYu2OJp752AuCgMmgY8exLv76oZt7zq/jlMrP0ze6QjHWfuACUNuV+p6DYzAqquKDQ94gEbWqCYJOIBSVMOrjIgh/JP7YLr1ASyiGDpAFHSUWPfn5ieRG19M+jc+tCej1IIqKPOJzCxKdLm7jIklyz8ULmA0C4/IMnG7XMyFHIl/wETr8KVuOpB98D4fDeL1evF6v2qYbN27cCfUbi0Qiaus3Fotht9uZOXNmSiLYH/lRjgfQWwGdif2H9n06Oztxu914vV51Pm3ixIkjFtOlHMPSeSBCfFu53W5V6FBQUEBpaalaEdy3b58qBNNug3QKYIPBgGnAnXMAACAASURBVCzLHDt2jLVr17J+/XocDgdLly7lzjvvTLscWWRxPJAldoPAQJInhgu6HhVff+hvVq6qqoqqqs+tNvoSPYRCIbUyqdiaiKJIKBRCp9NRVFRERUVFyiih44VYLKYSzMpwJ7MdBna0xBB0ccKnlwTKC41sOerHatRTXZJDUU6M5s4wrZG4CvTcKXYumFrMXlcXL+/dhzPHgMcfQ5YlZAk6/CLhcLw92xUUCUfiubdmo54co47qQgvBqIjHF1FFDTajQKcviDsSRQDOm1TEJfPjPldbD3dgNHYnkDqAQ95gj28dqjWJJMu8/lkrp48v5qu1iUKSHms1HLkm2gMRgtG4UlShNyaDjlv+Md7+zs3NxWq14vV61ZD2vLw8DklFPLHbiyiBJEts8UZ56YiX66cX8uTOFqx6GUEGOSxhAEIRuGv9h/xyoZ28nLjdy9bmMOGYpM7RAWrVMCbBIW8Ak1FPTIq3rQWBnlZ33E8uLPYoeQ0CguY1JEBv1BNOIRyKiDKLakt46qMWrEZ9XAGtl4nFPr+Q0ut1jC2yYNAJ+CMidaU2rptVwVRHDjZTavGDtgKcLv0hFArhcrlUsdRAlJ9DhULm3G43oijicDiYMmVKv7YemZAf+LwSrj0epLL/SDZAliQJn8+Hz+dTK3N1dXUnPHO1paUFl8tFLBbD6XQyY8aMflvgyd2AcDhMd3c3ra2thMNhfvjDH9LS0kIoFCISiTBlyhTOOussamtrOfPMM7Ok7iTHyV+vyxK7EYWibhwu9JViMdhZub7mfaLRqDo439XVhdVqVStzypXu4cOH1UFnxeogufqnuL0P10He7/eriR2iKFJcXExVVRVTp07ljNPhM7ePLYfakSWYUp7LD5/9hEKrEUNPNSnPaiTXYqA9GOP2sycwvybuc/ebNxsxGg04CqyU5Iu0+iI9CRngDcRAlAmHZUCkJSBSkWsg36zDgojNIPPDaTpkSUSQJXZ36jgcMFBakM/Zk+zUVxZisVgQBOFzYYYG4ZhEICqi6yE96ufTUy177kNXL2I32RlvT8kyTHbk4vFHaPVFkCSZAouB5edMoCxHT1NTU695ucmTJ3O0M8zjaz7CZtAnzLZ1BKM8sr0Dg9FIfk5v65OOQBS3ZKPYaCAYDNLe0dkzDyUiCCDKENFMKsiCQFQGQa9Dp+zCgmI9Er/VCcTNg4VEFymTXiAUk2kPxSi2GpFkme6QSKHVwEVTnUiCwJ93NhOJSYgyCEqOLTCh2Mpjl9eTa87sMKeoIRXD4MLCQmpra3tduKSafUul/EzX+hzo9yEcDquVOUmScDgcTJ06tV8yNxikqoSngiiKqs9ca2urWvUvKCggEomwf/9+9u/fPyT7k8FAsXFxuVyEQiHsdjuTJ0/uV82rRapt0N3dzYsvvsjatWsBuOWWW7jyyisxmUw0NzfT1NREU1MToVBoWNcni+OPrHgiiz4xnDN22ordUBWs6aCNOWtra0OSJNVQORMvKYXsKVf7SstP2+pRDprpWr+phpaVuTQlR9disVBaWkp9fX1KQjq5LI/JPcrV13d7EARBJXXa7YQs88aeVpXYHfYGsPZ4rVmNeqqLrLi6QhxpDyJJPe3DHqIly9DsF7GZDYQlkZo8HWPKSikpKcFms/GVWEzdDqGQnwMHvOpJPybJSJEQrZEQNlN8Diokfv65FucktrKNeoH2QLTXeuZbDFwzt5JVW4+SZzJQlmeh1GaizR+mzCZQFjrKBx8cVeflkucdN3zagiTJCaQOoMBiYH9bgAJr4uFBlsEXkQjEJNpiBioqKgAockb47/e39hgoC4SjUoJ4QRGyxElb3GC4x6pOVamaera7rseyhJ45PZNBh04nE4xKdAkxZGBudT63zB9DgcXAN2aVk2PS85edzbQHo/FEDquR608p55KpzpQkWguFCLS0tODz+TJKWsh09k07+B8KhVK2PlP5nin7dFdXl2ps7nA40u7vxwsK8VXInOLpNnXq1LRig4Han6SaAzWZTH2KGRQzY5fLpXryDYdYJBwO89prr7FmzRr279/PRRddxEMPPcTkyZMT9g1tBySLLEYDssRuBDGcxA7iB0lRFIdVwar14evs7InJ6ok5G+jQbyZWB9qoH23UV7LiVZlhiUQiiKJIXl6eOsNnNqd3eU9Gn1u/hzwoqC6y4epsV41zG9uDtPjCKqkz6AUioowoifE5Ppl4+9Vq4nsXTGPK2KJ075S4TLLM3XYP976yl+6ohMUgEYrGc3XzTSCH/XSG4/NgOp2OrojMjBI9Lperl/px6ZwKCix6/rylkaNtfpBE5leYuP4rVdRUlvX5GR7tCKW08BAEAYtRT1T8fNv4wiIH24PEpLgQ5ZdvHOTdQx3cf+EkCm0mLp3upOGDZqKijCjJKmnT6eiJ4PrcYkQvyEhSXDwh92S46jT7sAygxC6JInqgvtjA9VNzybdZKMmzYZbDhMPxYfjL651cMsWBNxjFatSRm6LNqkU0GlUtQEKhkLpf9RVRNVBkOvivtT5RLqo6O+MVUMXPThCEPlu/fVkADRXJYhGbzUZZWVlKu5tUyOSYMBD1q0KCFf87v99PMBikqKiI6upqCgoKhvQZiqKYYE9y9tlnc8cddzBnzpwT2lbO4ngiW7HLog8MhdglV+UKCgr46KOP1PzOVO1O7Qm/r9dV0jFaW1uJxWIJ7bmRPnilc3pXqgFKtJEkSeTn56tVEW3Wo+LzpVzlp9oGCvmbVVWATNwGRNvilOX47NhX6z5vb149p4ItB71x1SbQ5o+oZpU6AQwCyD02IzE5/lohUeAnX53AvAxJHcT3i3+oc/CHohwadjTzaXM3RTYjc8bp2N7YSW5OPIJMlmV8oRhmo8jX60vUuS+FBEejUWKxGFZJ4p8nGjHa8nGWFpOXY1NVjn2ZWo8vsfH3I5297pdlGZtRj8Uo0BWKYdIL7PcGkOILDz3ChY372uj86yc8cfUMlp89Ab0AL33aQlhNIYirXvV6HYIgExHl+OyfXkcUuYe4xkmkxSAQVPJYAUkQ0AsCORYDUUnma1PKqXGa+5z5Sqf6tVgsiKKYIDQoLS2ltrb2hFqAQHy/drvdeDwedDodDoeDyZMn9yLkfVkA9df+VbZHpu1fWZbx+/2qp5vNZsPpdA7ZBiQdBkKC29raaG5uxuVyqccRq9VKOBzms88+S1sF1W6HZANoSZLYsWMHa9as4Y033mD+/Plcd911PPbYYyNGmLPIYiQhDJB4DF/56SSGKH4e7dQXJEliy5YtnHbaaRm9bl+zctpbper1easv8VaSpAS1q8lkIhaLEQwG8fv9alWutLT0hLZ2lGqhMsOXm5uL3W6npKSkX2Wt9io/ef2VH4if8J8/EOXl/SFsJj02kx5RBl9EZnplPn9YMiOhTfuXrY3879uH6QhEaPNH1Zkxi0FQD/JRUcJmivubXTuvkh8uqh2e7SFKPPL/DrHhkxa14pVrNvCTc2uZO6Ywpb9caWkpVqu1l/VLstmtXq/vRYDbIwI/eOkQJqMOq8arrSMYpdaeww8XjOPnr+3no+YuuqJS3AhAiGelIvSEl8uw8qoplOnj5rweX4T/3QstIRmDXsAbFNH3nEMj4uevIcswvTyX75w2ltpSK/e8tp+P3T6CPeIHg16gwGIgJsmMLbTy6GVTMfVhEKwlPsr6+/1+uru7CQQC8dc0GLBardhstrRzb8djvkbxTtN63zkcjiGb1Kb6TiT/pCI+yv4giqKaKqKQObvdfkLJjVIxVEimks9aXFyclqSmMoDW/kQiEf70pz+xZcsWbDYbR44coby8nLPOOotzzz2X+vp6xo4de5zX9EuPUVEmmzprivzU6yuH/XVPKZ2/XZblucP+wmmQJXaDQKbETpZl/va3v3H66aen/TsM/6wcxAUGSvskHA5jtVoTQqyVK/xUVifK7XAHewMJ1UIltcNutw+5hZIOoigSDIX4644mnnrfRZs/ilEHC8aY+dpYA6aeaX6DwaCeELwhiVePCmw+EqE010SLL0IoJqkq1liPOKHIZuTPN8ymqp/g94HC64+w1xNX8Y4r0NPeFidzir+c3W7v0x8wFWKamT/tiX/bUR8rPwkQ65l7M+gEynIN/OvpDsoLbZhMJpatO8DhjnCP3UrPC8ogE2+pLqjQ8aN/qMLhcGC1Wtnj8fOD53cRjIm0B2Nqbq9BJ1CWZyIQlTh9XBE/P6/u8/arLLO31c+6T1p4+3AHwaiIXidwbl0JN51aTV6GAgitYbBer1dJk9lsTrD8SCY+isIRUic+aKuAgxn4TzYyVkjTiUgc0BIfhch1dXXFSXvPd16JDkwnehjJ9i+gVgw9Ho/a/i0pKRnSeyr2JA0NDaxfv57S0lIWLVrEtGnT6OjoUAUQdXV1fPvb3x7GtckiA2SJ3TAiS+wGgUyJHcC7776bQOwyrcoNFMkCA7PZrFbl+gq4Tg53194q66i0d7TEL11bI9VydXR0qObFmSzXSEGW40P4FoMOQYDOzk619Ws0GikoKMBqtSJJEq1dAb7z4jFMujgpcfkldU5MlqEsz8jd54zhzDo7Fotl2PI9ZVmmq6uLlpYWNY/Vbrereawjge5wjC2HO+gMRqnI0TOpxEhUs1/85K1WdrcrlTdZYwEsIMpwzvh87lk0LqHqdaAtwJ+2H+Ptg146QjEMOh35lniO7aK6Um77h7G9RBsKJFkmEBWxGPTx6mAfUCo6irmyyWTC6XRSWlo6aNIkimIvyw/t7+nanskD/4rps8fjUZfLbrcfF5/HvqBNWzCZTJSVlWG323sR1lRVUO1Pptsh0/GOYDCIy+Xqd7kGitbWVtavX8+zzz4LwNVXX81VV12F3d7bHD2LE4ZRQezqZ02Rn3p91bC/7qzSr2SJ3WjHQIjdO++8w+mnnz4iVblQKKRWv5QB4tLSUoqKiobtalpp74RCoZTkLxqNIssyBoNBJXwGg0FthYVCIYqKirDb7RQXF5/Qto7ieefxeOju7lZNStNVAp78+1F+/9YhjPq4RUlHMIovHGOq3co9i8oxIarbQqn2aKscqWb/Up3k0uWxDrVCMVQopPwvWw/xx4/88YBsHSjHYEmOz8ndekoB/1Bm6LPq1RLWEUZPrT0fZ2HOkCsvWvJrs9lwOByUlpYeN8PgVIa/oVBI9XJTvB6NRiM2mw2r1dpr9m+kquKpoG3/Go3GYSOZ2uNDutZncvtXux0EQaCrq0utsJaVleFwOIa8XD6fT7Un8Xq9XH755SxdupTq6upRZWfR2NjI9ddfj8vlQqfTcdNNN3HbbbclPEaWZW677TY2bNiAzWZj5cqVzJ49G4BVq1bx85//HIC77rqLZcuWHfd1GCaMig+lftYU+alNfxr2151VcmqW2I129EfstFW5t99+u1eVS/l9oJUeSZISoruUOJzS0lJsNtsJO2Bpo4O8Xi+SJGG1WjEYDGr1A+hX9DESwo1gMKhW5aLRKCUlJdjt9ozsWwD+3742Vr7XyIG2AKU5Rq6eU8mlM8p62acoUAyc083+KSc5o9GotsRisRgFBQUqOTmRFR3Fn6ylpYXu7m415/eavx6kubtnbrFHTSwIUJFv4a/LTiHHlHm1J1Xeb7LtTXI1WCGZLS0ttLe3jxrym6watVqtasVQae8nr7v2/9q811TEbygekMFgUK3MKe3f4SBNg4G2/av4UHZ2diKKomp+PtT2bzgcZuPGjaxZs4Y9e/bw9a9/nWuuuabPjOMTjebmZpqbm5k9ezbd3d3MmTOH9evXM3XqVPUxGzZs4He/+x0bNmxgy5Yt3HbbbWzZsgWv18vcuXPZtm0bgiAwZ84ctm/fTlFR5kKuUYRR8QFlid2XGJIkqUPp0PesHHx+kkuueikVL0hUeGpJj3JF29bWht/vp7CwkJKSEoqLi09onFFylSknJ0cVPqRrgaUiPdrfFdKT6iSv3PZ3Etfm1ra1tWE0GrHb7Sek9ZuMQCCg2mxIkkReXh45OTkJiQfJ84+ZkJ6hQrH/UEQZJSUlOByOBPLb6gvzved2sdfjRyKubK3IN/OfF01mQknm5q9apBoF0O4TiupXsfhRDHCLioqwWq0jekHQ33Irfm5aoUFpaemgSGYqz7vk2b9U8X+pZv8UlW1LSws6nU4lcydilk+LWCyGx+PB5XIRjUZxOBw4nc5e30ntsTJV9U/b/n311Vdpbm7GZDKxZ88eDh48yIIFC/jWt77F/PnzT0p7kksuuYRbb72Vc845R73v5ptvZsGCBSxduhSASZMmsXnzZvXnf/7nf1I+7iTDqCF2T48AsZt5nIld1u5kkNDOyPXnK6e0ZPqS8mvbne3t7arZpizL6PV69Hq9qm7t7OwkFAr1SnYY6avSYDCoqjIjkciAbVL0ej05OTkZ+dxpCWBXV1eC4hfoRXIikQg+nw+/309BQQF2u/2EZ3mmm5ebMWNGv/NySqtPux2UDE6t2jXZ8iVVqysVQqGQOv8liiJ2u71PU9fSXDNPXjOTfa0BGjtDlNiMTC/PQzeEfU7r8J+fnw8kGgZHIhH1YsFisahzb8q2UEhPsgo8HekZyvdD+SwVMqeY82bq59bfdhiI552W9Hi9XgKBgBoDCPHvhhIhJ4qiOnN7vImw8lm63W4CgQB2u52JEyf2+f3PxPxZFEV27NhBW1sbu3btori4mDFjxjBhwgRcLhe33347Cxcu5Je//OVIrNaI4dChQ+zYsYOvfOUrCfcfO3aM6upq9f9VVVUcO3Ys7f1ZZJEldoPA8uXL2b59OxUVFVRVVVFZWalmsFZWVqonqUwRiUTUvFOfz0d+fj5jxoyhuLg4oW0SS0gzCKn5hdrZJm2sV3Lrd6DkT9v6bWtrw2QyUVpamlE25WCRzucuebmUionb7SYajaonb6PRSHd3N93d3Rw9ejSt6GOkZpvSzcvV1NQMiGRqsz37QvI+4ff7aWtr62X5orj3RyIRgsEgBoMBu93OlClTMo5bEgSBOnsOdfb0J+bBIBqNqmROqRgO1DBY2+pTtofX61V/T9fyTOV9qCA50F75LCdMmHBC2r/a+D+lMtfZGfchHDNmjFqZS2X2m5x4ASSsd/J2GGxFWJIkvF4vLpeL7u5uSktLqampITc3d8jEes+ePaxdu5YNGzZQV1fHNddcw29+85sRExUdT/h8Pq644gp+85vf9Dp/pOqqpfNIHa0t55MHAqOkeDgkZIndIHDffffh8XhobGzk6NGjHDlyhLfffpujR49y9OhRuru7EQQBu91ORUUFlZWVKvmrrKykvLycjz/+mKNHj1JbG/dAy+RkpoS591f507Z6lRN9JuRPuZrXkkxFYDBQYjLcUComHo8nYb5w1qxZKUlgqjaf4mTfn+JXuc305JbsL1dUVHTcDJ/72ie0xERpS+fm5lJYWEgsFsPn8/Hxxx8nVEHTtcCHmwgrYfaK4bRSMRyojYsCLekpKChI+ZhUPm9K2oMigFEq8ZIkEYvFsFgsFBUVUVdXpwogTtRMXzgcz4x1u90AOByOlAkxA028ULaHNulB63+YivxpjxeyLKtdhs7OTjW7eagWRrIs09TUpNqTFBcXs3TpUpYvXz7gi+eRxo033siLL76Iw+Hg448/7vX3X/3qVzz55JNA/Bi9a9cuPB4PxcXFjB07Fq/XS35+Pvfddx+XX355wnOrqqpobGxU/3/06FG1qLB58+aE+xcsWDAi6/dlgvAFIHbZGbsRgHJyaGlpobGxkcbGRvbt28fbb7/Nxx9/jMfjYcKECZSUlJCTk0NJSYlK/rQkcDgjjrRQZt2Un+7ubjo7OwkEAmrr12QykZOTk5YAHo8rQ2WQXxm0zsvLU1tzw0Ey+1L8JitdtdtAOZH6fD68Xi/AoP3lhhtKxcTj8dDR0UF+fr66zfpLJEk35J+KCKcif/1VhJX2b0tLC7IsY7fbcTgcAwpoHwkoxEQrzFDm+FLNACbPQKbaHsM1A6kQYLfbjSRJ6szc8TIW72v2LxAIqJF/RqORvLw88vLyeu0XA90WbW1trF+/noaGBmRZ5uqrr2bx4sWj2p7krbfeIjc3l+uvvz4lsdPihRde4KGHHmLTpk3IskxeXh7XXnutOiuXjJdeeomHH35YFU9873vfY+vWrXi9XubMmcP7778PwOzZs9m+fTvFxcXDvn7HAaOCTdXPmiqv3vTnYX/dGSVzszN2JzsUdVd5eTnl5eWceuqp7N+/n0AgwF133cXcuXPR6XQq+Tty5Iha+XvrrbdobGzk2LFj+Hw+NQBcuULT3lZXVw+6xaGoRTs6OrDZbFRXVyd4fyULHZR2jnaYW7G0SNf2HUy1SrFw8Xg8hMNhSkpKKC8vHxFlm3a2KS8vL+3jFPKnZOp2d3ej0+nQ6/XqPKVioXI8Fb/a5VOUrEqQvdPpZNKkSRm/ryJa6YswJFtbpBsH0KqfdTqdagOi2FlMmzbthCaewOcqW7fbTUdHBwUFBTidTiZOnJhx7Fay2XGqqLNklWeqCnkyIpEIHo8Ht9uNKIo4HA6mTp16QsQ/2qxXbQpEMBhMSIFItjxR4v+0ArFUitdPPvmE8vJySkpK2Lx5Mw0NDbS2tnL55ZezatUqxo4de1K0F88880wOHTqU0WOffvppVeDwzjvv4Pf7efvtt5k1axYQ7wgdOXIEgFtuuYULLriADRs2UFtbi81m44knngCguLiYn/70p8ybNw+Au++++2QldaMH8cTEkx7Zit0ohlL5c7vdauVP+VHavoFAoF/yl5OTw8GDBzl8+DCFhYWEw2HVW66wsHDQpKMvtW8q8pdMApXKn5IR29bWhl6vV6tfJ7qSk25eLpUiOVnNl3yrqBrTtX0zUfxqoVRyFCGLomQdqSpvplBa5s3NzbS1taHT6bDZbBgMBpUIpVJ4pmr9DjcUE29lNq2wsBCn0zmk70B/0F4gpVJ7Km1wxf5GmYssKirC6XRSUFBw3Lzu0kFJsWlpacFqtVJWVjYoBXDytvD7/dx1110cOXIEt9uNLMuUlJRQXV1NZWUl3/72t5k/f/4IrdXw49ChQ1x00UV9VuwCgQBVVVXs27dPJWE1NTUUFRUhCAI333wzN9100/Fa5NGEUUGn6k+ZKj8zAhW76cXZil0WPVAqfxUVFVRUVPRSS0Ei+Tty5Iha/du4cSMfffQRe/bsoauri7KyMurr66mqqqKwsLBX23cwLcRMFWzaE1owGMTr9dLd3U0wGEQURfR6PVarlby8PDXHMxwOq0ToeNoWDHZeLpNtofU0UwhwOsVvqkqo0mZtaWkBwG63M2nSpBNOgJPVv1arFYfDQW1tbVqClqzwVKp6yv+1thbpyF8mLT5lm7ndbrq6utTP83h5m/WlBFdsZlwuF5FIhIKCAsrKyoB45drlcnH48OE+FdBaVfxwfk+U929pacFoNFJWVsbcuXOHRLiVkYbt27ezdu1atmzZwllnncWdd97JvHnz1C6Gx+Ph2LFjlJeXD9v6jBa88MILnHHGGQmVtXfeeYeKigpaWlo455xzmDx5MmeeeeYJXMovO0YFxxwSshW7Lyi2b9/OI488wkUXXcSiRYuw2Wwq+Uuu+h07dgy/349Op8PhcKhkL7nyNxQT5HA4rBKmUCikBtgXFhaqf09V+UtV7UpV/RvKSU3xlxtqHutwQDvUHgwG6erqoqOjA7/fD8RPjn3NuSnJHyO93IopdUtLS4JidDgNg1NZviT73MHnhEE736a0A/1+PyUlJWr160S39RQ/N8W2xm6343Q6+7QAgd5ed8lVYa3XXV9ih76ImSLOUFIQhssDT5Ikdu7cydq1a3n99deZN28e1157LQsWLDihgqxk9CeA2Lx5M5dccgk1NTUAXH755dx9990AvPLKK3z3u9/l6NGj3HvvvSxfvjzle1x22WVcddVVXHPNNSn//rOf/Yzc3Fz+9V//dZjW6qTBqGBT9adMlddsenLYX3da8eysQXEWxx+yLCOKIi6Xi8bGRrXyp8z7HT16lGAw2Iv8lZeXU11drZJAhfxJksS+ffswGAy0trai0+kSCNNAofW3S3WiV7zM0pEdi8Wikj+twlaxcRnpPNZMoQzyK+rfnJycXnFZWsIzkIxf7bYYzHC/tmLY2dmppmUUFxefUDPYWCymkvO2tjaCwSAmk0lNfujL+Fr5fSSVrrFYjNbWVlwu14DI3GDQV9JFKBTqle+qeEAqnplOp5OKioohz0DKsszevXtVe5La2lqWLl3KBRdccMLnK9OhPwHE5s2befDBB3nxxRcT7hdFkYkTJ/LEE0/wne98B4PBwNNPP52QHgHxbOqamhoaGxvVz97v96tm5X6/n3POOYe7776br33tayO3oqMTWWI3jBg9l0tZnFAIgoDBYFD9+E477bRej9GSP23l77XXXlNJoFZEMGHCBC677DJsNpvq76f4Lw2UVGTqb5eu1alNMpAkSTXFraysxGazqZWuEwFllq+lpYWuri6VMNXV1aUkTFqPu3S2D+mEDoooJVnxm070IUlSQsSYYko9GmKatGbGPp+P0tJSJk2alDIuLp3xtfK7NuIsXfLJQCqhyrIpQgO73U5tbW2fFiTDgUy+J7FYjObmZlU4oljgaGPblNdKV/lLNRMqyzLNzc00NDSwbt06ioqKWLp0KXfccceosydJhYEIILTYunUrgUCAq6++mtbWVmw2Gz/96U/V9IhbbrkFgHXr1nHuuecmEHq3281ll10GxD+Xa6655stI6kYNvhgudtmKXRbDBFEU+epXv8rcuXO56KKLqKmpobm5WSV82rZvMBhEr9fjdDrVOT+l3atU/qxW65CJg3ZeLhAIqO1fxcYiVds3OdkiFekZjupOsilvcXExDofjuLcLk33dQqEQwWBQnYGUJEkNss/NzVW3yfFS/CZDFEU1li0QCFBaWjpsohHF+zCV2EFbCU1n6s3ZgAAAIABJREFUcmw0GtVZQ2XZnE7nkM15hwOSJKlEU0mBUJYtHdLl/Wq/K8888ww7d+7EarVy+PBhDAYDixYtYvHixcycOfOkU2n2JYDYvHkzV1xxhTqe8uCDD1JfX09DQwOvvPIKjz32GAB//vOf2bJlCw8//PDxXvyTGaOCT00boYpdfbZil8XJCL1ez9tvv51w34QJE1I+VqkmNTU1Jcz7vfLKK2pUTigU6pf8KVm6Wvh8Ptra2hLm5VIZ3/Ynckgmft3d3b2qO+lEDunIXygUUkmJKIppl+14QrGzMBqNalSXEuWltAuTq13BYJCOjo4RU/wmQ5lLU0jwcKUZJEM7n5YOySbHwWAQl8tFV1cXkUgEvV6vbk+/309TU1PGNifDjWThSElJCePGjcuYBPclCPL5fLz00ks0Njai1+uZPXs211xzDdFolKamJlatWoXNZuP3v//9SKzaCcHs2bM5fPgwubm5bNiwgUsvvZS9e/dmEyC+aPgCfHZZYpfFcYfiHzd27FjGjh2b8jFa8qed91MSO44dO0Y4HFY902RZVtsaCxcupKKigrFjx6Ykf/1Bm2KQDlpDX22KQbKqU6/Xq8TIYDBQVFTEuHHjVBuLEwkt0ZQkKa3KdqQUv6lanQqUiqYiMlBI8Ei3MvuDolQPBoO43W41NiuZMKVSg3d0dPSaCU1l+ZJqe2QKRdTicrno6OigqKiIyspKpk6dOiwV8I0bN7J27Vp2797NhRdeyH/+539SX1//pSAy2nbyBRdcwHe/+11aW1vTJkNkkcWJQpbYZTEqkQn5e/3117n99tsZP348s2bNoqKigtbWVl599VW18hcOh1Vj3HSVv8EkaWgNfbURVlrrD0U0UlxcjMViUX28jh07xoEDBxISDFIpfUdi7i8QCKj+d4r/YX19/ZAH2jOZ7UpFhpVcW6XVGYvF1O2Sm5tLcXEx+fn5KuEZzHzmcECZNVTInOK3lmqeDzInw8nJFj6fL6XQId3cn5Il3dXVhcvlUqOpysrKBmRQnQ6iKPLOO+/Q0NDAe++9x8KFC/n+97/PqaeeekIFM+nQn7L1ySef5Je//CUQ37/+8Ic/MHPmTADGjRuH2WzmyJEjzJ07l23btiU81+Vy4XQ6EQSBrVu3IkkSJSUlFBYWsnfvXg4ePEhlZSWrV6/mqaeeGvmVzWIEIHwhIsWyxC6LkxZnnHEGO3bs6JP8KArSY8eOJbR9P/jgA5X8RSIRDAZDL/KnZPtWVlb2Sf4U49uWlhY6OjpU64/x48f324JMnutSEi6UqldyfFWqtm9/6+/3+1UyZzQacTgczJw5c8g2FgNFKjKsTVlQVJmKylbZHtq2r9bTLZ36ebjivJJbmcOVgaog03zbdAkXfr+fYDBILBZT/fKUi4hYLEZXV9eg5iAlSeKDDz5gzZo1bNq0iTlz5nDttdfy6KOPnvAqc3+44YYbuPXWW7n++utT/r2mpoY333yToqIiXn75ZW666Sa2bNkCgMfjITc3l1gshsvlYsWKFer+dsstt9DQ0MAf/vAHDAYDVquV1atXq6Kzhx9+mPPOOw9RFLnxxhupr68/buucxfDii0DssuKJLL70UMhVcttXEXw0NTUlkL+qqipKS0vp6Ojgk08+4Wtf+xoLFy6kvLycoqKiYa9kpLM3UX5Xhvq12aUQt1Lw+XzYbDacTid2u12t8JxIKKkZLS0txGIxHA7HgDJjUyl+tbfJcV6pRDDpiHpyOkVRURFlZWWjwgMP4hVXl8uFx+PBYrGon6tSDU2XcpFqDtJsNuP1epEkibFjx+J2u2loaOCll16itraWJUuWcOGFF45ae5J0yCQBAqC9vZ1p06Zx7NgxIF6x27ZtG6WlpcdjMbNIxIn/cgHTTqmXG954ethfd0rRzKx4IossjieUE15NTY1qPpoMhfxt2LCB//qv/6KpqYnx48czduxY3n33XZ599lmV/JWXl6et/JlMpkG1ffuzN1FUj263m+bmZpXk5efnEw6H1VSS5CSH42VsrJjfKvN8DoeDKVOmDCr/dCAZv1qC4/f71dZvcuQdoD5OyY2dNGnSiPrbZYpQKITb7cbtdqsXF7Nnz+5F0pVM13RINQe5adMm1q1bR2trK21tbRQWFlJbW0tBQQF79uzhiiuuGOnVO2FYsWIF559/vvp/QRA499xzv+zRXll8AZAldkPA2rVr+dnPfsauXbvYunUrc+emJuSvvPIKt912G6Io8q1vfUt1JT948CBLlizB6/Uye/Zs/vznPx/39lgWmUEhf7Nnz+bxxx9n4sSJvR6jVE2SK3/vv/++WvmLRqMYjca05K+ioiJj8pdcXSooKKC8vJz6+vqUVcPktl66NqfW2DhV2zdT8hcKhVQyp7RZh2OeL1NoA+yToRhBu1wu2tvb1TamwWAgHA6rcV59KX5H0tw4EomoZA7A6XQya9asIR0flDnIYDDIhg0bePbZZ4nFYnzjG99g8eLFOJ3OhEgvr9c7XKsz6vDGG2+wYsWKBCV/Ntoriy8Ksq3YIWDXrl3odDpuvvlmHnzwwZTETnElf+2116iqqmLevHmqK/nixYu5/PLLWbJkCbfccgszZ87kO9/5zglYkyyOFxTyp53507Z9m5ubE8if4pmlkMCSkhK2bdtGOBymvr6eoqIiHA7HsAXZa9ucqdq+qciflvgBqtmyIs5wOByjop2nKEbdbjft7e1qZa6/9nlypSv5dqCK33TQZsfGYjGcTidOp3NYtp3f7+ell16ioaFBVY8vXbqUcePGjYoWsxb9CSBkWea2225jw4YN2Gw2Vq5cyezZswFYtWoV//7v/05zczN//OMfWbZsWa/nf/jhh1x22WW8/PLLKS/Q4Esd7XWiMCp2wmmn1MvPbl497K87uXBGNlLsZMOCBQvSEru//e1v/OxnP+PVV18F4P777wdg+fLl2O12XC4XBoOh1+Oy+PJCIX8K2du3bx8bN25k27ZttLa2MmnSJEwmE6FQKIH0KZU/JeptuEQEqZZPO+PW3d2N1+vF5/MhSZLq5daX2nekli3VsnZ2duJ2uxMUo8M9C6lV/CYTv3QKV2U7BAIB2tvbiUQiKpnLdN6wL0QiEV5//XXWrFnD7t27ueCCC7jmmmuYNm3aqCNzWvQX7bVhwwZ+97vfsWHDBrZs2cJtt93Gli1b8Hq9zJ07l7/+9a8sXbqUcDjM9u3bKSoqUp975MgRzjrrLP70pz9x+umnq/dno71OOEbFDhknds8M++tOLpyenbH7IuHYsWNUV1er/6+qqmLLli3qPItyJV9VVaUO8aaD1+vl6quv5tChQ4wbN441a9YkHLQg3mL4/ve/r/5/9+7drF69mksvvZQbbriBN998U1XgrVy5klmzZg3XqmYxTFDUo7W1tdTW1jJr1iwaGxv5t3/7N6ZPn67GsinWKdrK39atW9XKXywWw2g0JpC+ZPI3mLk6QRCIRqNq1JjBYMDpdDJ9+nS1VZhs5Jvsa6cIHAwGQ9q272DJn2I5o7X/cDqdaSPahgNaxW9fyxWNRgkGg2q7MxQKYTKZ1Hau2+2mra0trdFzf216URR59913Wbt2Le+99x4LFizgtttuY/78+aPSniQV+ov2eu6557j++usRBIH58+fT0dFBc3MzmzdvRqfTcf7559Pa2orZbOaOO+5Qq3m33HIL9957L21tbXz3u98F4vvftm3bstFeWXyhkCV2/WDRokW4XK5e9//iF7/gkksu6ff56VzJB+NW/sADD3D22WezfPlyHnjgAR544AHVk0nBwoUL2blzJxAngrW1tZx77rnq33/1q19x5ZVX9rvcWYweFBYWcs899yTcJwgCVqtVJX+poJA/pfKnzP299957HDt2TCV/JpMpofKnEMDq6mrKyspU8vfRRx9hsVhob29XyVy6uS+twKEvU+Hktm9febapyI5CdBQypxCjvLy8ESdzA4EyD6mkVJSUlDB58uRePnipCHG6bWI2m3nhhReQJAmLxcKuXbvYuXMn8+bN47rrrjsp7EkGg1QXy4p10Q033MBdd90FwH/8x39gtVrVrFaAxx57TI3+0mL8+PF88MEHI7/wWYx6jIrS4RDxxfvWDzM2btw4pOencyVX7DJisRgGgyEjt/LnnnuOzZs3A7Bs2TIWLFjQi9hp0dDQwPnnnz8sbZ0sTj4o5K+uro66urqUj5FlmWAwmED+jhw5wrvvvsvRo0c5dOgQbW1tyLKM3W7noosuorCwkPLyctVGw+l0DlpRazAYyM3NzYj8aePdWltb1UgvxdjYZDKRl5dHeXk5NpsNk8lENBodlBJ5OKC0gRWBRmFhIRUVFX2mQGRKiKPRKHv37qWjo4MPPvhA9cSbMGECu3fv5ic/+QlnnnkmDz300Eit3gnDcF4sZ5HFFxFZYjfCmDdvXkpXckEQWLhwIQ0NDSxZsoRVq1b1WwF0u92Ul5cDUF5eTktLS5+PX716NT/4wQ8S7rvzzju59957Ofvss3nggQf6zMXMpPUL8erB9OnTARgzZgzPP/88kFX9ngwQBAGbzcbEiRN7DZL/z//8Dy+//DLLly/n7LPPpru7W235Hj58mHfffZfGxkZcLheiKGI2m9W2r1L5U27LysrQ6/VDJn+yLOPz+VTT4Ly8PNVnTksAfT4fra2t6swbDM7XbqCQZZnu7m5cLhdtbW3qTN/EiROHXDmUZRmXy8XatWtZv349BQUFLFmyhPvuuy+lwbEy1/dFQ7qL5aqqKvXCV7l/wYIFx38BszhpIZA1KP7SY926dfzLv/wLHo+HwsJCZs2axauvvkpTUxPf+ta32LBhAxAf9r399ttVV/I777wTgAMHDqjE55RTTuEvf/kLF154YdrW77Jly+jo6FDvKyoqor29PeWyNTc3M2PGDJqamlS/q+bmZsrKyohEItx0001MmDCBu+++O+36/fjHP6a4uFht/ba3t6esEObm5uLz+Xrdn1X9fnkgyzKBQKBX21f5SSZ/ydFu1dXVOJ3OtOTP5/PhcrlobW1VDZdLS0sHZDWiRLqlUvtqfe3SCT76In8K2fR4PNhsNsrKyigtLR2WNrDX6+W5556joaGBaDTK4sWLufrqq3E6nUN+7ZFCOosnBd///vd54403gM9j7pRjm16vZ9KkSRw8eJBzzjlHvVBU8NJLL/Hwww+r4onvfe97bN26Fa/Xy5w5c3j//fcBmD17Ntu3b6e4uPg4rHEWQ8SoYFPTT5km//XNNcP+uhML6rOq2CxSY9KkSWzevJny8nKam5tZsGABn332WcrH/vd//zeffPIJf/zjH1P+ffPmzTz44IO8+OKLQ36/VMROad1lVb9ZKNCSP63gQxGAuN1uRFHEYrFQWVmJxWKho6ODPXv28Itf/IIJEyYwfvz4EW2tKuQvlbI1mfzp9XrC4TCBQACz2YzT6VTVyEOF3+9nw4YNrF27FrfbzaWXXsrSpUupqakZ9e3FviyeUuF3v/sdO3bs4PHHHwfiFVq73U5raytOp5N77rknIdpLlmVuvfVWXnnlFWw2G0888YTqSPD4449z3333AfHuxDe/+c3jsMZZDANGxU79RSF22VbsSYSLL76YVatWsXz58n5bt08//bRqraKgubmZ8vJyZFlm/fr1TJs2rc/3y7T1GwqFmDt3LgaDgeXLl3PppZcOSvWbxRcbgiCQk5PDpEmTmDRpUsrHyLLMM888w3333UdeXh7Tp0/nlFNOYePGjTzxxBO0tLQkkD+t4EO5dTgcg277Kpmr6RIcQqEQLpcLl8uFIAjk5uaSn59PNBrF6/XS3NyckGiRqvqXLrs1EomwadMm1qxZw6effsoFF1zAfffdpyqhTxZs3bqV2tpaxo8fD8CSJUt47rnn0hK7p59+OkEcZLFYaG5uTvv6giDwyCOPpPzbjTfeyI033jiEpc/iy46T55uWHllidxJh+fLlLF68mBUrVjBmzBjWrl0LwLZt23j00UdVtdehQ4dobGzkq1/9asLzr732WjweD7IsM2vWLB599NE+Vb+Z4siRI1RUVHDgwAHOOusspk+fnjL6KpOTUyZzfTt37uQ73/kOXV1d6PV67rzzTq6++mqArKXLSQ5BEDjjjDN4++2308anybKM3+9XjZ2PHDnCvn372Lx5M0ePHsXtdiNJElartZfNS2VlJdXV1TgcDnQ6XUb7pJJt63a7VbHI7Nmz+5wXFUUxoeoXDAYTUj5kWWbbtm1s2LCB/Px8vF4vhw4d4tRTT+Waa67hoosuGhWmzoNBOounVDh8+DAHDx7krLPOUu9LdaGYRRZZZI4ssTuJUFJSwuuvv97r/rlz5yZI+MeNG5eyOrZp06Ze9/Wl+nU6nWqVr7m5GYfDkfJxipp3/PjxLFiwgB07dnDFFVcMWPULmVm62Gw2/vSnP1FXV0dTUxNz5szhvPPOo7CwEMhaupzs0JKCVFAqZVOmTGHKlCkpH6OILLRt371797J582YaGxvVzFqr1ZpQ+VOqfvn5+WzcuJHS0lJqampwOBwDikPT6/XYbLaUinRJkvjoo484duwYfr8fu93OGWecwYUXXkhzczNPPfUUDz74IKtXr2bcuHEZvd9owkDUqatXr+bKK69MmJVMdaE4YcKEEVveLLLQ4osgnsgSuyzSIpPWb3t7OzabDbPZTGtrK++88w4//vGPB6X6hcwsXbTqzYqKChwOhypgySILiBOJvLy8jMifUvk7cOAAzz33HH//+9/p6upKaBenIn9VVVXY7faMKn+yLLN//34aGhp44YUXqKmpYenSpTzwwANYrdZhXffhQH/ih5UrV/KjH/2IyspKAG699Va+9a1vAfHIrqeeeoo333yTu+66i6amprQXdatXr+7VVk11oZgldllkkTmy4oks0qKtrY3Fixdz5MgRtfVbXFyc0Pp99913ufnmm9HpdEiSxO23384//dM/AalVv33Zq0DcjDdT5S/E53mWLVvGJ598gk6n44YbbuBvf/sbZrO5X0uX/k5e4XCY66+/nu3bt1NSUsIzzzyjVlDuv/9+VqxYgV6v57e//S3nnXdeJps0i1GMo0eP8vvf/56lS5eqsVuKfYm27atV+3o8HiRJIicnJ2Xb12Qy8eabb7Ju3Try8/NZsmQJl19++ai+CMlE/LBy5Uq2bdvGww8/nPBcRZmqzPFedtll5OTk8Mwzz1BfX5/w2M8++4zzzjuPgwcPqsQ4+ULxtNNO63M+L4svDEZFmWz6KdPk9W82DPvr1hZMyYonshgdyKT1e/rpp/PRRx+lfP748ePZunVrr/uHY64P4mKQ6667jlWrVqnD6Pfff3+Cpcsvf/nLlJYuoijyz//8zwknr4svvjjhBLJixQqKiorYt28fq1ev5o477uCZZ57h008/ZfXq1XzyySc0NTWxaNEi9uzZMyDrjSxGH6qqqlRFpQJBEMjPz6e+vr4XMVGgJX/Kz65du9i4cSMbN27kBz/4AevXr6esrOx4rMaQMVDxgxavvvoq5557LpdccgmLFy+mra2NU089lfr6eu6++27mzp3LxRdfDMRFE0uWLEmodu7atSvhQnH58uVZUpfF8YMAJ5FOKS2yxC6L447hmOvr6uriwgsv5Oc//znz589X71dUvGazmW9+85s8+OCDKZ+fycnrueee42c/+xkAV155JbfeeiuyLPPcc8+xZMkSzGYzNTU11NbWsnXrVk477bQBbYcsvhjIhPydTMhU/PDss8/y1ltvMXHiRB566CGqq6vV515wwQVccMEFaqwXwL333pvwfOW7pUVfF4pZZJFFZjjxIYpZZKGBMtcHpJ3Li0QiXHbZZVx//fVcddVVCX9TbBL6s3RJlzeZ7jEGg4GCggLa2toyem46vPLKK0yaNIna2loeeOCBXn//9a9/zdSpU5kxYwZnn302hw8fVv+m1+uZNWsWs2bNUqseWWQx3MhE/PD1r3+dQ4cO8eGHH7Jo0SKWLVuW8XOzyGJ0QxiBn+OLLLHLYlRh+fLlvPbaa9TV1fHaa6+pc2/btm1Th7PXrFnDW2+9pVqZzJo1i507dwJxS5fp06czffp0Wltb1UDwZGRyAhruTEql/fvyyy/z6aef8vTTT/Ppp58mPOaUU05h27ZtfPjhh1x55ZX8+Mc/Vv9mtVrZuXMnO3fu7OXGn0UWw4V0kV1alJSUqLOr3/72t9m+fXvGz80iiyxGFtlWbBajCpnM9X3jG9/gG9/4Rsrnp7J0SYVMTkDKY6qqqojFYnR2dlJcXDzok1cm7d+FCxeqv8+fP5+//OUvGa1PFllo0Z8w6Ne//jWPPfaYmvLw+OOPM3bsWADOOOMMjEYjU6ZMYcKECTQ2NvLUU08lPF8ZlwB4/vnnVeXxeeedx7/927+pgqf/+7//62WUnkUWoxlfBLuTbMUuiy8l5s2bx969ezl48CCRSITVq1f3am9q28INDQ2cddZZCILAxRdfzOrVqwmHwxw8eJC9e/dy6qmn9vueA23hrlixgvPPP1/9v2LcOn/+fNavXz/QVc7iS4KhVoZtNhvr1q1DFEV27drF4sWLVfGDUin+7W9/S319PTNnzuS3v/0tK1euBKC4uJif/vSnzJs3j3nz5nH33Xdns1qzOGkgjNC/441sxS6LLyUMBgMPP/ww5513HqIocuONN/ZS7v3TP/0T1113HbW1tRQXF7N69WoA6uvrWbx4MVOnTsVgMPDII49kpIgdSAv3L3/5C9u2bePNN99U7xuKcetQfMlWrVrFz3/+cwDuuusudZ4qi9GJ4agMK+IHLbTih/vvvz9tJS4b65VFFicWWWKXxZcW/Z28LBaLGtuWjDvvvJM777xzQO+XaQt348aN/OIXv+DNN99M8OAbrHFrJtYuAFdffXVKX7J77rmHbdu2IQgCc+bM4eKLL+4V85bF6MFAIr0gfWU4G+mVxZcSJ38nNtuKzSKL44VM2r87duzg5ptv5vnnn0+wemlvbyccDgOoCR+Z+ntpKzgmk0mt4GSCV199lXPOOYfi4mKKioo455xzeOWVVzJc4yxOBAZTGf7Rj36k3nfkyBG2bdvGU089xe23387+/ftHbFmzyCKL4UeW2GWRxXGCtv07ZcqUlLNLP/rRj/D5fFx11VUJtia7du1i7ty5zJw5k4ULFw7IuDXT2b5nn32WGTNmcOWVV6qVxaFYu0D/9i7f//73VWXzxIkTExIZsvYug8NAK8PPP/98v5XhLLL4siA7Y5dFFlkMCP21f9OZNw/FuDVTX7KlS5diNpt59NFHWbZsGZs2bRqSL1kmLeCHHnpI/f13v/vd/2/vjl2r7O44gH/PagcXkYopvJVkrIXyUnQREdtbHAxCBrMEcVIQQSgV2sm/oCC4vIvo4gVdpKASqmToYKAVSkGQDNZCsUPgujucDiHB8CbxRnNzH8/9fCDDfe6TJ0+2H99zzu+3qYhYb+8yib5m3N3z58/z4sWLHDt2LLdv306/3//Rqdb1ZPjZs2c/Soa3mv0Mk8KpWKDzxtWXbLdLwA8ePMj8/PzQ/1erhjnV+um4uxs3buTmzZtJktevX+fhw4d59OhRaq25cOFC5ubm9iUZBrpBYgeN+3Rv39GjR7dMcEbRl2w3m/jfvXuXt2/f5syZMxvXJnUT/16Mu5udnc3s7Gx6vV7Onj2bZPTJMDTh2w/sJHbQumH29o2iL9lulnH7/X7m5uY2tY35mk38ly9fzuHDh7cdKVdrzfXr1zM9PZ3jx4/n1atXG9/du3cvMzMzmZmZ2ehjuJ/GNe4OaIPEDibAOPqS7WYZt9/v586dO5uufWl7lyS5dOlSrl27loWFhS2/f/r0aVZWVrKyspLl5eVcvXo1y8vLnWjvMo5xd8Aae+wAtjFMe5ckefPmTQaDQU6ePLlx7WvauyTJqVOndkwWHz9+nIWFhZRScuLEiXz48CHv37/vRHuX3Yy7S7In4+6AdijsgJEYZgk4WTs0cfHixU3J0qg38W+3ZNmFpcxxjLsD1mh3ArCDzy0BJ9k4BPCpUW/i7/JS5jjG3QFr5ya+/YVYhR0wgbZbspyamsrS0tKm66dPn97399vvcXdAOyzFAhPn/PnzuX//fmqtefnyZQ4ePJgjR46k1+tlcXExg8Egg8Egi4uL6fV6435dYF+UpIzgZ59J7IDmzM/PZ2lpKaurq5mamsqtW7fy8ePHJMmVK1dy7ty5PHnyJNPT0zlw4EDu3r2bZHN7lyS7au8C0AVlqz0lO9jVzQAAn9GJrW2//NXx+vRvf9nz5x79yXf/qLV+v+cP3obEDgAgHakwv5I9dgAAjZDYAQAkYznssNckdgAAjZDYAQCkjVmxCjsAgDg8AQDAiJVSfl9KqaWUQ5+7V2IHAEy8tVmx3cvsSik/S/KbJP8Z5n6JHQBAd/05yR8y5JAIiR0AQEnnNtmVUs4n+W+t9Z9lyFYsCjsAgNE5VEr5+yeff6i1/rD+oZTy1yQ/3eL3/pTkj0l+u5s/prADAEgZ1R671Z1mxdZaz275NqX8IsnPk6yndVNJXpVSfl1r/d92z1PYAQCkW4cnaq3/SnJ4/XMp5d9Jvq+1ru70ew5PAAA0QmIHANBxtdbvhrlPYgcA0AiJHQBAkmFbinSZwg4AIN06PPGlLMUCADRCYgcATLwODp74IhI7AIBGSOwAAJLE4QkAgBaMbKTYvrIUCwDQCIkdAEAcngAAoEMkdgAA0aAYAIAOkdgBACTanQAAtMDkCQAAOkViBwAQhycAAOgQiR0AQOLwBABAK779ss5SLABAMyR2AAApDk8AANAdEjsAgLTR7kRhBwDQyOgJS7EAAI2Q2AEAE28tsPv2I7tSax33OwAAjFUp5VmSQyN49Gqt9XcjeO6WFHYAAI2wxw4AoBEKOwCARijsAAAaobADAGiEwg4AoBEKOwCARijsAAAaobADAGiEwg4AoBH/B6r6KqWZAAAAA0lEQVQbV5WcJq5rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1234a5d710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, y = datasets.make_s_curve(n_samples=1000)\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12,8))\n",
    "ax1 = plt.axes(projection='3d')\n",
    "s = ax1.scatter3D(X[:, 0], X[:, 1], X[:, 2], c=y, s=50, marker=\"o\", cmap='GnBu')\n",
    "fig.colorbar(s)\n",
    "ax1.view_init(10, -60)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a 2-dimensional dataset embedded in three dimensions, but it is embedded in such a way that PCA cannot discover the underlying data orientation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "seqcolors = list(map(pal.to_hex, sns.color_palette('GnBu', 50)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"3b4a96f8-ff12-4769-a7c0-92edf697d07b\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[1000]},\"y\":{\"__ndarray__\":\"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       "  var render_items = [{\"docid\":\"894c8cbf-5490-4c00-941a-fe82fb30da51\",\"elementid\":\"3b4a96f8-ff12-4769-a7c0-92edf697d07b\",\"modelid\":\"2bfb0197-a517-4cde-9bde-fe1cc6d21fcb\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "2bfb0197-a517-4cde-9bde-fe1cc6d21fcb"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_pca = decomposition.PCA(n_components=2).fit_transform(X)\n",
    "\n",
    "fig = bk.figure(title='PCA Projection - S-Curve',\n",
    "               x_axis_label='c1', y_axis_label='c2', \n",
    "               plot_width=750, plot_height=500)\n",
    "fig.scatter(X_pca[:, 0], X_pca[:, 1], \n",
    "            size=10, line_color='black', line_alpha=0.5,\n",
    "                fill_color=pal.linear_map(y, seqcolors))\n",
    "bk.show(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Manifold learning algorithms, however, available in the `sklearn.manifold` submodule, are able to recover the underlying 2-dimensional manifold."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"fc1b3154-bffa-428f-868c-c8562273c96c\"></div>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
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\",\"dtype\":\"float64\",\"shape\":[1000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1000]}}},\"id\":\"e8642fe3-9ea2-4c92-a7b5-23dc632cf2e0\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"below\":[{\"id\":\"1f0dfe5b-56aa-4216-a52e-6fde90a90908\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"13b8bcf9-649c-43b6-95d1-e0c266b05892\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":750,\"renderers\":[{\"id\":\"1f0dfe5b-56aa-4216-a52e-6fde90a90908\",\"type\":\"LinearAxis\"},{\"id\":\"a3f41e1c-660a-41ca-a2f5-64fdd1557759\",\"type\":\"Grid\"},{\"id\":\"13b8bcf9-649c-43b6-95d1-e0c266b05892\",\"type\":\"LinearAxis\"},{\"id\":\"a0b44407-2008-46bb-b315-b2ded326dbe1\",\"type\":\"Grid\"},{\"id\":\"174f000f-99de-440f-9402-55961eef3699\",\"type\":\"BoxAnnotation\"},{\"id\":\"1d639033-6005-4d0a-b08f-7af239439d58\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"404f598a-5731-4fc9-857c-663519166e32\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"3f878171-640e-4fbf-b8f1-40193cf582c2\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"4cf76e11-be61-47f8-b396-8de40b289311\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"6b52b4e7-52ef-4037-957e-7e38ac192fbd\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"ce09ce19-9a30-4829-a623-1d6bcee24446\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"cb5805ee-0b61-4488-8668-22727f16e4c1\",\"type\":\"LinearScale\"}},\"id\":\"27e9c675-0c13-4f05-b02f-a85d1e0f0979\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":null,\"text\":\"Isomap - S-Curve\"},\"id\":\"404f598a-5731-4fc9-857c-663519166e32\",\"type\":\"Title\"},{\"attributes\":{\"callback\":null},\"id\":\"ce09ce19-9a30-4829-a623-1d6bcee24446\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"27e9c675-0c13-4f05-b02f-a85d1e0f0979\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.13\"}};\n",
       "  var render_items = [{\"docid\":\"b37e9a8b-082a-497d-9bc7-1d080f11b228\",\"elementid\":\"fc1b3154-bffa-428f-868c-c8562273c96c\",\"modelid\":\"27e9c675-0c13-4f05-b02f-a85d1e0f0979\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "27e9c675-0c13-4f05-b02f-a85d1e0f0979"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "iso = manifold.Isomap(n_neighbors=25, n_components=2)\n",
    "X_iso = iso.fit_transform(X)\n",
    "fig = bk.figure(title='Isomap - S-Curve', x_axis_label='c1', y_axis_label='c2',\n",
    "                plot_width=750, plot_height=400)\n",
    "fig.scatter(X_iso[:, 0], X_iso[:, 1], size=8, alpha=0.8, line_color='black',\n",
    "            fill_color=pal.linear_map(y, seqcolors))\n",
    "bk.show(fig)"
   ]
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    "`LocallyLinearEmbedding` (LLE) is a local, nonlinear, nonparametric algorithm. The main idea behind the Local Algorithms is to make the local configurations of points in the low-dimensional space resemble the local configurations in the high-dimensional space. LLE seeks a lower-dimensional projection of the data which preserves distances within local neighborhoods. It can be thought of as a series of local Principal Component Analyses which are globally compared to find the best non-linear embedding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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\",\"dtype\":\"float64\",\"shape\":[1000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1000]}}},\"id\":\"40977469-8d88-4de4-a7e5-6625add969c4\",\"type\":\"ColumnDataSource\"}],\"root_ids\":[\"6191e661-d838-4124-9c55-7e1705af701d\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.13\"}};\n",
       "  var render_items = [{\"docid\":\"2ccf22ed-e5a4-4756-9484-7dd975c73be6\",\"elementid\":\"914d0610-1e11-4992-9ea4-fd32581ba9c1\",\"modelid\":\"6191e661-d838-4124-9c55-7e1705af701d\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
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   "source": [
    "lle = manifold.LocallyLinearEmbedding(n_neighbors=15, n_components=2, method='modified')\n",
    "X_lle = lle.fit_transform(X)\n",
    "\n",
    "fig = bk.figure(title='LocallyLinearEmbedding - S-Curve', x_axis_label='c1', y_axis_label='c2', \n",
    "                plot_width=750, plot_height=400)\n",
    "fig.scatter(X_lle[:, 0], X_lle[:, 1],\n",
    "            size=10, line_color='black', line_alpha=0.75,\n",
    "            fill_color=pal.linear_map(y, seqcolors))\n",
    "bk.show(fig)"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 Some Tips on Manifold Learning practical use"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Make sure the same scale is used over all features. Because manifold learning methods are based on a nearest-neighbor search, the algorithm may perform poorly otherwise.\n",
    "* The reconstruction error can be used to choose the optimal output dimension. For a *d-dimensional* manifold embedded in a * D-dimensional* parameter space, the reconstruction error will decrease as n_components is increased until *n_components == d*.\n",
    "* Noisy data can “short-circuit” the manifold, in essence acting as a bridge between parts of the manifold that would otherwise be well-separated.\n",
    "* Certain input configurations can lead to singular weight matrices, for example when more than two points in the dataset are identical, or when the data is split into disjointed groups. In this case, solver='arpack' will fail to find the null space. The easiest way to address this is to use solver='dense', though it may be very slow depending on the number of input points."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3 t-SNE t-distribuited Stochastic Neighbor Embedding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`t-SNE` give more importance to local distances and lower importance to non-local distances. In other words, it try to keep closer in the projected space the points that are closer in the original space while neglecting the others.\n",
    "\n",
    "Moreover `t-SNE` has a probabilistic way to find pairwise local distances: it converts each high-dimension similarity into the probability that one data point will pick one other data point as its neighbor. This make `t-SNE` almost insensitive to bad feature scaling.\n",
    "\n",
    "On th other side, the relative local nature of `t-SNE` makes it sensitive to the course of the dimensionality of the data.\n",
    "\n",
    "t-SNE (TSNE) converts affinities of data points to probabilities. The affinities in the original space are represented by Gaussian joint probabilities and the affinities in the embedded space are represented by Student’s t-distributions. This allows t-SNE to be particularly sensitive to local structure and has a few other advantages over existing techniques:\n",
    "\n",
    "* Revealing the structure at many scales on a single map\n",
    "* Revealing data that lie in multiple, different, manifolds or clusters\n",
    "* Reducing the tendency to crowd points together at the center\n",
    "\n",
    "While Isomap, LLE and variants are best suited to unfold a single continuous low dimensional manifold, t-SNE will focus on the local structure of the data and will tend to extract clustered local groups of samples as highlighted on the S-curve example. This ability to group samples based on the local structure might be beneficial to visually disentangle a dataset that comprises several manifolds at once as is the case in the digits dataset.\n",
    "\n",
    "The Kullback-Leibler (KL) divergence of the joint probabilities in the original space and the embedded space will be minimized by gradient descent. Note that the KL divergence is not convex, i.e. multiple restarts with different initializations will end up in local minima of the KL divergence. Hence, it is sometimes useful to try different seeds and select the embedding with the lowest KL divergence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsne = manifold.TSNE(n_components=2, n_iter=500)\n",
    "tsne_proj = tsne.fit_transform(digits.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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\",\"dtype\":\"float32\",\"shape\":[1797]}}},\"id\":\"15f8678d-067a-4558-b323-e3574e3d4f56\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"callback\":null,\"tooltips\":[[\"target\",\"@target\"]]},\"id\":\"db74906d-c845-4682-92e8-06b997c89e10\",\"type\":\"HoverTool\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"08101e9b-947f-44a9-9e92-8da3fc01f0e7\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"1d868f0b-09af-4bd3-b99f-5bea5cf0c6ff\",\"type\":\"BasicTicker\"}},\"id\":\"a58ce547-e640-482b-bb8a-4a6b86c40629\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"6e6bfffd-9c60-4f90-9c30-1270e817cf55\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"source\":{\"id\":\"15f8678d-067a-4558-b323-e3574e3d4f56\",\"type\":\"ColumnDataSource\"}},\"id\":\"3b4fbe81-271d-4e01-920a-35a67989bf62\",\"type\":\"CDSView\"},{\"attributes\":{\"data_source\":{\"id\":\"15f8678d-067a-4558-b323-e3574e3d4f56\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"cdef2331-936b-4c2e-9ec6-a32e588c7068\",\"type\":\"Circle\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"73d8ca4e-bdb9-4528-9df3-d698511852d6\",\"type\":\"Circle\"},\"selection_glyph\":null,\"view\":{\"id\":\"3b4fbe81-271d-4e01-920a-35a67989bf62\",\"type\":\"CDSView\"}},\"id\":\"27f0f9d7-4451-41fc-bae3-b029e4e04c96\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_color\":{\"field\":\"color\"},\"line_alpha\":{\"value\":0.5},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"cdef2331-936b-4c2e-9ec6-a32e588c7068\",\"type\":\"Circle\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"d42dbcdb-2c45-48f6-8fc5-6044d9248cf7\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"62026ee5-4bc9-4080-b693-5e5e44e3a544\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"a0a2897b-4c9a-4edd-8339-abaddb422e68\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"cd17a482-3125-4412-b571-7f7d1b754f46\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"73d8ca4e-bdb9-4528-9df3-d698511852d6\",\"type\":\"Circle\"},{\"attributes\":{\"overlay\":{\"id\":\"d42dbcdb-2c45-48f6-8fc5-6044d9248cf7\",\"type\":\"BoxAnnotation\"}},\"id\":\"0031ffd5-350b-4a37-9b06-0e5d80d8373c\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"62026ee5-4bc9-4080-b693-5e5e44e3a544\",\"type\":\"PanTool\"},{\"id\":\"cd17a482-3125-4412-b571-7f7d1b754f46\",\"type\":\"WheelZoomTool\"},{\"id\":\"0031ffd5-350b-4a37-9b06-0e5d80d8373c\",\"type\":\"BoxZoomTool\"},{\"id\":\"7764a519-158a-4666-a527-28fa254dca81\",\"type\":\"SaveTool\"},{\"id\":\"cc06afd7-a899-4da8-b3e7-55d8965e3fe1\",\"type\":\"ResetTool\"},{\"id\":\"61c6badf-812e-4d21-9d6a-c587400b9675\",\"type\":\"HelpTool\"},{\"id\":\"db74906d-c845-4682-92e8-06b997c89e10\",\"type\":\"HoverTool\"}]},\"id\":\"aef060bb-7343-40df-848c-d45ffc759a90\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"7764a519-158a-4666-a527-28fa254dca81\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null},\"id\":\"3b465cd1-06a4-439e-be03-75571f1b5674\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"cc06afd7-a899-4da8-b3e7-55d8965e3fe1\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":null,\"text\":\"t-SNE - digits dataset\"},\"id\":\"4eb91d2f-33fa-4407-9914-af0497f92fbf\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"61c6badf-812e-4d21-9d6a-c587400b9675\",\"type\":\"HelpTool\"},{\"attributes\":{\"callback\":null},\"id\":\"8cc9bb0d-c2fa-4825-b10b-b125a420b71d\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"d1988bc4-65d6-4b67-ba1d-a770951646c4\",\"type\":\"LinearScale\"}],\"root_ids\":[\"08101e9b-947f-44a9-9e92-8da3fc01f0e7\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.13\"}};\n",
       "  var render_items = [{\"docid\":\"e809d7ce-e542-4cf8-a283-3b3a72cc35bf\",\"elementid\":\"6b964179-ad1c-4ce4-b2b0-8dae2ba30456\",\"modelid\":\"08101e9b-947f-44a9-9e92-8da3fc01f0e7\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "08101e9b-947f-44a9-9e92-8da3fc01f0e7"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame({ 'x': tsne_proj[:,0],\n",
    "                    'y': tsne_proj[:,1],\n",
    "                    'color': pal.linear_map(digits.target, colors),\n",
    "                    'target': digits.target\n",
    "                  })\n",
    "src = ColumnDataSource(data=df)\n",
    "\n",
    "fig = bk.figure(title='t-SNE - digits dataset', x_axis_label='c1', y_axis_label='c2',\n",
    "                plot_width=750, plot_height=450)\n",
    "fig.scatter(source=src, x='x', y='y', fill_color='color',\n",
    "            size=8, line_color='black', line_alpha=0.50)\n",
    "\n",
    "hover_tool = HoverTool(tooltips=[('target', '@target')])\n",
    "fig.add_tools(hover_tool)\n",
    "\n",
    "bk.show(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Visit [www.add-for.com](<http://www.add-for.com/IT>) for more tutorials and updates.\n",
    "\n",
    "This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-sa/4.0/\">Creative Commons Attribution-ShareAlike 4.0 International License</a>."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:addfor_tutorials]",
   "language": "python",
   "name": "conda-env-addfor_tutorials-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}