{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# recursive quicksort\n",
    "\n",
    "sort an array by choosing a point in the array, called the pivot point, then creating two smaller arrays:\n",
    "Keep in mind an array of size one is already sorted, so no need to sort that.\n",
    "\n",
    "- choose a point, called the pivot point\n",
    "- make an array containing everything smaller or equal to the pivot\n",
    "- second array containing everything bigger than the pivot\n",
    "- so the answer is just quicksort(smaller_array) + pivot + quicksort(bigger_array)\n",
    "\n",
    "first to generate some random data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[91, 18, 30, 16, 41, 69, 44, 95, 34, 30]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "import numpy as np\n",
    "random_data = [random.randint(0,100) for i in range(10)]\n",
    "random_data[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[16, 18, 30, 30, 34, 41, 44, 69, 91, 95]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def quicksort(data):\n",
    "    if len(data) < 2:\n",
    "        return data\n",
    "    else:   \n",
    "        pivot = data[0]\n",
    "        less = [i for i in data[1:] if i <= pivot]\n",
    "        more = [i for i in data[1:] if i > pivot]\n",
    "        return quicksort(less) + [pivot] + quicksort(more)\n",
    "\n",
    "quicksort(random_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# using a random pivot\n",
    "\n",
    "Quicksort works faster when using a random pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[16, 18, 30, 30, 34, 41, 44, 69, 91, 95]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def quicksort2(data):\n",
    "    import random\n",
    "    if len(data) < 2:\n",
    "        return data\n",
    "    else:\n",
    "        p_idx = random.randrange(0,len(data)-1)\n",
    "        pivot = data[p_idx]\n",
    "        \n",
    "        less = [i for i in data[:p_idx] if i <= pivot] + [i for i in data[p_idx+1:] if i <= pivot]\n",
    "        more = [i for i in data[:p_idx] if i > pivot] + [i for i in data[p_idx+1:] if i > pivot]\n",
    "        return quicksort2(less) + [pivot] + quicksort2(more)\n",
    "\n",
    "quicksort2(random_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## some tests to make sure the algos are working correctly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert len(random_data) == len(quicksort(random_data))\n",
    "assert quicksort(random_data) == quicksort2(random_data) == sorted(random_data)\n",
    "\n",
    "a = [i for i in range(10)]\n",
    "random.shuffle(a)\n",
    "assert [i for i in range(10)] == quicksort(a) == quicksort2(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "13.3 µs ± 834 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit(quicksort(random_data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "38.9 µs ± 1.67 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit(quicksort2(random_data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## visualizing quicksort\n",
    "\n",
    "there are many better visuals on the web, heres my stab:\n",
    "\n",
    "I modified the quicksort function above so it only does one sort step and returns the list:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from IPython import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[18, 30, 16, 34, 30, 41, 91, 69, 44, 95]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def quicksort_onestep(data):\n",
    "    import random\n",
    "    if len(data) < 2:\n",
    "        return data\n",
    "    else:\n",
    "        p_idx = random.randrange(0,len(data)-1)\n",
    "        pivot = data[p_idx]\n",
    "        \n",
    "        less = [i for i in data[:p_idx] if i <= pivot] + [i for i in data[p_idx+1:] if i <= pivot]\n",
    "        more = [i for i in data[:p_idx] if i > pivot] + [i for i in data[p_idx+1:] if i > pivot]\n",
    "        return less + [pivot] + more\n",
    "\n",
    "quicksort_onestep(random_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here I add the list after each sort step to an array `qs_steps`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "it took 235 steps to sort 100 items\n"
     ]
    },
    {
     "data": {
      "image/png": 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9dyAk08KQJQ7sr0exdZweL7LUnTepzxvoQJ80C4Ayl0TpTD+HugWOhkXiG57j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\nzsPxbo90RtnScBRXKiScryHEjx7fxL0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/D2wUjc+/2IKZM2ahr+0sJM4e99zGliZw4TAu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9vfZs2aNZx33nn/6M87LmZPreX//esZZcvDQoisGMLk/wDJSIJQvXvTzJvdwu7eygYJ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\npe4XQrwoE3JYqnhtYryUoMoN75PU5hKVyyOSxZ7IHiF3lqzpQsi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5noVbKtfezQlFliTF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//Fjb/7e1z+x++/gs6aZs8vXHbO3GvhaOIXjx7k0JTX9jn1TEQnBrx1XS8DPRlyrsXaLov9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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a6c8128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def compare_lists(a, b):\n",
    "    \"returns True if two lists contain the same element at each index, false otherwise\"\n",
    "    assert len(a) == len(b)\n",
    "    for pair in zip(a, b):\n",
    "        if pair[0] != pair[1]:\n",
    "            return False\n",
    "    return True\n",
    "\n",
    "random_data = [random.randint(0,100) for i in range(100)]\n",
    "sorted_data = quicksort2(random_data)\n",
    "plt.plot(random_data, label=\"initial data\", lw=1.5, ls=\"dashed\")\n",
    "\n",
    "qs_steps = []\n",
    "\n",
    "# first quicksort step\n",
    "d = quicksort_onestep(random_data)\n",
    "qs_steps.append(d)\n",
    "plt.plot(d, alpha=0.5, lw=0.8, label=\"first pass\")\n",
    "\n",
    "#rest of quicksort steps\n",
    "q_pass = 1\n",
    "while not (compare_lists(sorted_data, d)):\n",
    "    q_pass += 1\n",
    "    d = quicksort_onestep(d)\n",
    "    qs_steps.append(d)\n",
    "    if compare_lists(d, sorted_data):\n",
    "        plt.plot(sorted_data, c=\"r\", ls=\"dashed\", lw=2.5, label=\"sorted\", alpha = 0.9)\n",
    "    else:\n",
    "        plt.plot(d, alpha=0.7, lw=0.8)\n",
    "\n",
    "print(f\"it took {len(qs_steps)} steps to sort {len(random_data)} items\")\n",
    "# make plot bigger\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## use animations to visualize quicksort\n",
    "\n",
    "`qs_steps` is a array containing each step in the quicksort algorithim.\n",
    "\n",
    "Using [matplotlib.animation](https://matplotlib.org/examples/animation/index.html) to animate this.\n",
    "\n",
    "Github doesn't render videos for some reason, so see this [notebook at nbviewer](http://nbviewer.jupyter.org/github/khalido/algorithims/blob/master/quicksort.ipynb) for the pretty animations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# to display animations inline\n",
    "%matplotlib nbagg  \n",
    "import matplotlib.animation as animation\n",
    "from IPython import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "it took 234 steps to sort 100 items\n"
     ]
    }
   ],
   "source": [
    "# the data\n",
    "x = [i for i in range(len(qs_steps[0]))]\n",
    "y = qs_steps\n",
    "\n",
    "# the figure\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(8,6)\n",
    "ax.set_title(\"Quick Sort steps\")\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "\n",
    "# this displays the data to be sorted as a scatter plot\n",
    "original_line = ax.scatter(x,y[0], alpha = 0.2, label = \"original data\")\n",
    "# the final sorted line.\n",
    "sorted_line = ax.plot(x,y[-1], lw=2, alpha = 0.7, label=\"sorted\")\n",
    "\n",
    "# this displays the data being sorted in a scatter plot\n",
    "scatterplot = ax.scatter(x,y[0], label=\"sorting\")\n",
    "\n",
    "def animate(i):\n",
    "    scatterplot.set_offsets(np.c_[x,y[i]])\n",
    "\n",
    "ani = animation.FuncAnimation(fig, animate, \n",
    "                frames=len(y), interval=150, repeat=False) \n",
    "\n",
    "print(f\"it took {len(qs_steps)-1} steps to sort {len(qs_steps[0])} items\")\n",
    "plt.legend()\n",
    "#ani.save(\"quicksort_animate.mp4\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video controls autoplay src='quicksort_animate.mp4'></video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display.HTML(\"<video controls autoplay src='quicksort_animate.mp4'></video>\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another animation, this time using lines instead of a scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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b968IcgJyH0AXgdwtSRJy8xm81bfxRiNxkk0JxUsVKlUtKaOsizTv5WazeaR1N5oNJZJkrSmUYQsNJlMfQCQcKOgezrxsTaeXIyVZfkyi8Uyw0uA2CRJmuh0OmmPl1I6Y1qPxWKZ0shqJe2NAv1lWbarVKo7KbZFkqS+vimKk+ne47UwASbABP5sAixA/mwL8PxMgAkctwTy8/MHU+VwSZKGkpAAsB8AxUHQCcFjsiwvU6lUtxQVFW3r0aNHO41G8waA8yRJol/uqUr6KkovG0iAkI4xGo0PS5JEL8adZFmml/hX3TEZ/goRNqbufbjxZMQTgO1tpN69e7e32+0kJM6RJKkzzUOnBwA+02q1r5Hrk7s9vczTSQaA/o2B2wucTuc/fOuA+J6AUEyJ0+kkV7CTAdAeqUJ8k2vkyJGaPXv2UJ0OCijvRMH0six/q1arn9i8eXNZowgjoUcxGbqGhoZepaWlOxoTAUwAQNwpbmSDJEmTioqKvqU+Xml4aU4Sen0pba/T6fxXcXHxV+5F0EmWJEn/lCSJRA3FlZA9KJuXX27H7Y3OG2cCTIAJ+BBgAcK3BBNgAkwgCQlQrIZWq71Po9GM37hxY3USLjFllxToVCZlN8wbYwJMgAkkmAALkAQD5+mYABNgAkwguQmwAElu+/DqmAATOPYJsAA59m3IO2ACTIAJMIE4EmABEkeYPBQTYAJMwA8BFiB8WzABJsAEmAATYAJMgAkwASaQMAIsQBKGmidiAkyACTABJsAEmAATYAJMgAUI3wNMgAkwASbABJgAE2ACTIAJJIwAC5CEoeaJmAATYAJMgAkwASbABJgAE2ABwvcAE2ACTIAJMAEmwASYABNgAgkjwAIkYajDm+jAgUo5vJaxt1KpJLRsmYHDh2vgdCZs2tgXziM0IcB2TI0bgu3IdkwNAqmxC/4+sh1DEWjbNpvfoUNBCvI5w4sBnhJdEylANBoVcnMzUF5eA7vdqcR2eMwEEGA7JgByAqZgOyYAcgKmYDsmAHICpmA7JgByAqZQ0o4sQGIzIAuQ2PjFvTcLkLgjTfkBlXzApjy8JNog2zGJjBHDUtiOMcBLoq5sxyQyRgxLUdKOLEBiMAwAFiCx8Yt7bxYgcUea8gMq+YBNeXhJtEG2YxIZI4alsB1jgJdEXdmOSWSMGJaipB1ZgMRgGBYgscFTojcLECWopvaYSj5gU5tccu2O7Zhc9oh2NWzHaMklVz+2Y3LZI9rVKGlHFiDRWsXVj09AYuMX994sQOKONOUHVPIBm/LwkmiDbMckMkYMS2E7xgAvibqyHZPIGDEsRUk7sgCJwTAsQGKDp0RvFiBKUE3tMZV8wKY2ueTaHdsxuewR7WrYjtGSS65+bMfkske0q1HSjixAorUKn4DERk6h3ixAFAKbwsMq+YBNYWxJtzW2Y9KZJKoFsR2jwpZ0ndiOSWeSqBakpB1ZgERlEk8ndsGKjV/ce7MAiTvSlB9QyQdsysNLog2yHZPIGDEshe0YA7wk6sp2TCJjxLAUJe3IAiQGw7ALVmzwlOjNAkQJqqk9ppIP2NQml1y7Yzsmlz2iXQ3bMVpyydWP7Zhc9oh2NUrakQVItFZx9eMTkNj4xb03C5C4I035AZV8wKY8vCTaINsxiYwRw1LYjjHAS6KubMckMkYMS1HSjixAYjAMC5DY4CnRmwWIElRTe0wlH7CpTS65dsd2TC57RLsatmO05JKrH9sxuewR7WqUtCMLkGitwicgsZFTqDcLkMBgy8sPY+3aNRg16kzRaNiw/nj99Xdw6qn9FbLGsTGskg/YY4NAaqyS7ch2TA0CqbEL/j6yHUMRYAESilDwz9kFKzZ+ce/NAiQw0okTx0OWZYwb97RoVFZ2CNnZOdBqtXG3w7E0IP+hPJasFXitbEe2Y2oQSI1d8PeR7RiKAAuQUIRYgMRGKMG9WYAEBj5hgkt4uAVIgk2TtNPxH8qkNU1EC2M7RoQraRuzHZPWNBEtjO0YEa6kbaykHVmAxGZ2PgEJwq+goCBNpVKtliTp3qKionnU1GQydZdl+X1JkgYD2O50Oh8sLi7+yT2M0Wg8U5KkVwH0kGV5GYBbLRZLabhmSkUBMm3aF/jii89ALlTdu/fE/fc/jL59T8a2bVvx+uv/xoYNfyA9PR0XXXQJbrjhFqhUKnzwwbsoKbGgsrISpaVbkJ9fgLVrVwuM7dt3wPTps5q4YF122QW4+urr8cMP34t+Xbp0wxNP/B8KC3uJPrt378ILL0zEhg3r0LFjJ5x77hjMmDFVjHOsX0o+YI91NsfS+tmOx5K1Aq+V7ch2TA0CqbELJb+PLEBiu0dYgATg161bN31aWtrnsixfrFKp/tIoQCSj0fg7gPUAJgAYK0nSkw0NDb1KS0t39OjRo4tGo9kE4Cmn0/mDSqX6J4BeFoulLwA5HFNFKkCcsoy6ens4Qzdro1Gr0KJFOo4cqYXd4QxrDEOaBiop/NvGYinCHXfchAkTXkT37j0wbdoUzJ37Ez7+eAquvfZyDB06XAiHnTu34/nnn8V1192EK664RgiQjz56H4888gR69+4jRMNzzz0r1vjQQ48hNze3mQCxWuvw2GNPolu37njhhQlwOOx4++0PYbfbceONV4l/v+WWO1FcbMGLL05ETk4OC5CwrM6NEkFAyT+UiVg/z+EiwHZMjTuB7ch2DEWABUgoQsE/D/9NMrZ5jqneBQUFJ6hUKhIfxOcktwAxmUyjZFn+1mAwtFu3bl0NbcpoNP4CYJHFYnnaaDQ+I0nScLPZPJI+y8vLS8/MzNynUqkudJ+ghAIRiQDZuO0wfli2HdXW6AQI6QgSISQ+5LDkEZCp1+DcQV3Ru1vLUFsRn8+f/xvGjx+HyZM/QY8e+airq8PGjeuxdWsppkz5FFOnfgONRiPazpw5XYiOb775UQiQb76ZgW+//dEzj68LlncQOp2A/OUvZ+Keex4Q7Rctmo8nn3wc8+Ytw4oVyzBu3GOYOXM2MjIyxefvvPMmfvnlRxYgYVmRGyWCAL/wJIKy8nOwHZVnnIgZ2I6JoKz8HErakQVIbPZjAeKHn8lkukuWZWN1dfW4zMzMGrcAMRqN/5Ak6Vyz2Tzc3c1oND5N7lhms/kck8n0E7ldWSwWOvkQl8lkmifL8o8Wi2VSOKaKRIA8/781sDY4whnWb5toBAgNpNeq8fg1p4Y1r9Vqxb333o6iok0wGk0YNmwELrzwYnz88WSUlZVh0qSXPOOUlBSLk4o5c37D1KmfY/nypXjvvY/DFiB0ekJuXHStWbMK999/JxYtWoXPP/9UiI0PP/zMMxYJlFdffYkFSFhW5EaJIKDkH8pErJ/ncBFgO6bGncB2PLbsSD+kqlUSJB8PDSXtyAIktnuEBUgIfkajUfY6AXlDluU2FovlSi+BcReAe81mc2+j0bheluW3iouL3/ESKF8COGSxWO4Jx1SpJkBoz06nE7//vgaLFy8QJyI2mw2DBg1BVVVVEwFC7lo333wtvv/+F0yf/qWI+XjzzffCFiA333w7Ro++oJkAITFDsSEffvg/z1gLF87Da6+9zAIknJuS2ySEgJJ/KBOyAZ6EBUgK3QP8fTw2jGlrcOCX1buwrmQ/0vU6XD6yAHmtMzyLV9KOLEBiu0dYgEQgQIxG4weSJGnMZvMN7m6FhYU3y7L8D7PZnG8ymbY4nc5ni4uLP/ISIJ8AsFksllvDMdWhQ1WyShWeWTaUlmH2UnLBaghn6GZtJEhQqyU4HDLo/8K5MvVajB7cFSf2aBVOc6xfvw6rVq3ETTe5tk/iY/ToM3Hllddg1qxv8NVX5ILlSqM7ffpU4Xo1e/YvmDz5XaxZsxpvv/2+Z55//esp4Sr2z3+OF/82aNCpeOut99CvX3+MHXs+br31DowZc6H4bPXqVbjnntuxbNkaLF++DH//+yOYNetHZGS4Hkzvvfc2Zs/+DjNnfh/WPpK5kVqtQna2AZWVdXCEGcuTzPs5XtfGdkwNy7Md2Y6pQaDpLuwVFYBaBU1mVtJsb9/hWkz91YIDlRXQWZ2wa4Guee1wy/kneNao5PexZcvM8F7WkoZYci2E4UUmQN4C0Mr3BESW5bssFstJJpNpo9PpfMP3BESSpP1ms/n+cEzvdDpl3yPEYP2cThm1UQqQcNbj2yZdr0W4Aon6bt68GZdffjmeeuopDB48GCtXrsS4cePw9ddf46abbsKIESNw6623YuvWrXjyySdx9dVX4/7778cbb7yBFStW4NNPP/Us4ZlnnkFxcTFeeukltGvXjtzb8Mknn2DgwIEYNWoU7r33XlxyicsFa/ny5bj++uthNpvFCcyYMWNEe2pDY9AaKAj9119/jQYD92ECTIAJMAEmcNwQqFi/ASqdDlkm45++Z6oHtmT9Xnw9zwx7Qx301U5ITqAuW4WenTvgvr+ekpA1SpG8rCVkRcfWJCxAIhMgFANytjvInLoajcbxkiQN8ooBWUIB6e5hTSbTfFmWfwg3BiSSE5BYbzUlfxnwXtucOd/jo48mY9++vSKF7m233YmzzjoHZnMRXnnlRWzatBEtWuTi4osvxQ033CzS8L7//jvNTkA2bFiPxx9/WGS1+uGHuRg8uF9YJyC0Fkr5O2nSv8RcXbt2E6cmS5cuwdSpX8eK8U/vnyg7/ukbTfEFsB1Tw8BsR7ZjahBouovqDRsgabXIMJn+1O1R1s+ZC0uxcft+aBvsSKuT4VRJqMuQkKY14KbRvdGxjSvZDF1Kfh/5BCS2W4EFSAQCpDEL1sy6urp2O3furGsUIHMbs2A9RVmwAAyxWCxn0mdeWbAuKioq+i0cU0USAxLOeMHaKOkbGeva4tmf6o9YLGYMHEilW1zX559/giVLFjWJMYnnnIkc63ixYyKZ/hlzsR3/DOrxn5PtGH+mf8aIbEcfAfLH71BpdUjvddS9KdF2OVBeiylzLThcXQWD1QmNTYYtTUK9Xo2OLVvgshH5aJmtb7IsJe3IMSCx3QEsQCIQICSmTSbTH7Isr3c6nf9Sq9UXyLI8zm6396Y6IIWFhd1kWd4MYLzD4ZjVWAek0GKxnKxUHZBYzK/kFzOWdcW7LwmQSy45XxRAHDx4KHbu3AFK6UtZsy699K/xni7h4x0vdkw42ARPyHZMMHCFpmM7KgQ2wcMeD3a0V1VCk5UdFtnqtatdJyAnnhRW+3g3qm9w4O2Zf+BIVRUyap2islpdugSnRofBvTrijH6dRFkB30tJO7IAic3KLEAiEyDIz8/PV6vVHwAYCKBEluUHLRYL1QIRl8lkOk+W5VclSeosy/ISSZJuM5vNW8M1E5+AhEsqsnaU9Wry5HeE+MjNbYmxYy/Ftdfe2CxlX2SjJkdrJR+wybHD42MVbMfUsDPbke14LBCQHQ5ULFqIrAGnQZ2eHnLJVStXCAGSeXJi4it8FzRryTasKt6JzCoHZElCbYYEgy4dY4f1hKlLbsD1K/l9ZAES8rYJ2oAFSGz84t6bBUjckab8gEo+YFMeXhJtkO2YRMaIYSlsxxjgJVHXVLejo6YGVatWIvPUU8M6BalctkQIkKx+AxJupZJdFfhs7iakWW3Q2mRUZ6rQoXVLXDnKiJwMXdD1KGlHFiCx3QosQGLjF/feLEDijjTlB1TyAZvy8JJog2zHJDJGDEthO8YAL4m6prodG8rKULNhPTJO6gttbuATBLdJ6LRE0mmRfdqghFqJgs7f/mY9qqsqkV4jw5ouQaU34K6L+iI3Ky3kWpS0IwuQkPj5BCQ2RIntzQIksbxTYTYlH7CpwOdY2QPb8VixVPB1sh3ZjscCgfrdu1BXUoKME3pD26ZN0CVT2tuKBfOhIgEyeGhCt/f1glL8XrobmdUOONQS6gwaXDi4AP1MbcNah5LfRxYgYZkgYCM+AYmNX9x7swCJO9KUH1DJB2zKw0uiDbIdk8gYMSyF7RgDvCTqmup2rCspRv3u3Ug3FULXvn1wAWK3o2LxIkgqCTmnj0iYlYq2l2PKvCLo61oenegAACAASURBVGzQNsiozlKhZ15bXHuWKez4TSXtyAIktluBBUhs/OLemwVI3JGm/IBKPmBTHl4SbZDtmETGiGEpbMcY4CVR11S3Y82GP9BQdhiG/HykdewUlLyzvh6Vy5aKNjmnD4ekap5tKt6mowLL/5n5B2prqoXrFWW80hrScdfYviHjPrzXoqQdWYDEZnUWILHxi3tvFiBxR5ryAyr5gE15eEm0QbZjEhkjhqWwHWOAl0RdU92OlNVKtjdAl9cR+q7dgpIXAeurV4rUt9lDhkKl1SpqKXL5mvZbCTbt2IcML9eri4eZcHJ+64jmVtKOLEAiMkWzxixAYuMX994sQOKONOUHVPIBm/LwkmiDbMckMkYMS2E7xgAvibqmsh3pBb9y0QJoWuRClZ4OQ8/8oOTtlZWo3bgBTpsN2QMHQaVvWuwvnmazO5z4edVOLNu8CwarHeoGGTVZKpg6t8eVowrCdr1yr0lJO7IAic3yLEBi4xf33ixA4o5UDFhcbIbVakWfPn3jPsGwYf3x+uvv4NRT+0c8Nv0heOGFifj55znIzW2FadO+iXgMJR+wES+GO0RNgO0YNbqk6sh2TCpzRL2YSOxYv2c3nLW1MOQXRD1fIju6XarSOneGbLcj3WgKOn3D4cOwbikB9aM6IOrMTEWWW1ZhxfT5JdhTfgRpVgd09TLqMiToDBm45+K+yDREfvISiR0j3RQLkEiJNW3PAiQ2fnHvzQIk7kjFgJdffiFuuuk2jB59QdwniEWAkDC66aZr8OKLr6Fnz3y0bdsu4vUp+YCNeDHcIWoCbMeo0SVVR7ZjUpkj6sVEYsfazZtgO3AAGb17Q9s6eEapqBcUx472I0dQa96MtLxOoGrolAkr2NVw8CDqd+0QAiS9V29ocnLiuBrXUH9sKcP3S7fA1mCFoVaGyinDapBg1+pw+XATendvGdWckdgx0glYgERKjAVIbMQU7s0CRBnAl112AW6++fakEyBr167GfffdgYULV0Z8tOwmpeQDVhlr8Kj+CLAdU+O+YDsef3asWrMaqrQ0OCorkNl/AFTa4MXx/mxCtn17Ydu/H9o2bWEvO4SMPicFXZJof2A/5Hob9D3zoW0ZnRioqLHhYHlds7k2bTuM1Vv2QmNvEOLDqQJq01XQaNJw/sAeOMUYvahT8vvIAiS2O5lPQGLjF/feqSZADhzYjzfeeAWrVq2ASiXhrLPOxd13PwCdTofZs2eJ/z/llH6YMWMqHA4Hzj//Qtx770Oel/GZM7/C//73Xxw5Ug6TqRceeugxcVLg75o79ydMnvwO9u/fh7y8jrj99nswfPhI3Hvv7fj99zWiy3nnjcG4cU+jtLQEr7zyIjZu3IB27drh8suvwiWXXC7afPDBu9ixYxvS0vSgMelU4p57HsCwYf7TD9IJCImbn36ag4MHD2DIkNPx6KP/QHZ2thgv0Fxr1qzC/fff6dkKndDccssdWLx4IT744B1s27YNeXl5uO22uzBixCjRjvZC+1+yZDEcDjs++2wq6upq8OqrL2LJkqXIzc0VIuuGG26BWq2O+/3JAypHQMk/lMqtmkf2JcB2TI17IhI7UorazJP6wrpjOyBJIU8U/mxC1q2lcDY0iBgQ2+5dyDzl1KBLopohdGpCJyDktqVrE14NDveg9TYHvlu6Feu3HYRMkezNLgf0dU5R5bxBJ8FqUKFtdjYuG1mAdrnpMeGKxI6RTsQCJFJiTduzAImNX9x7p5IAaWhowHXXXYHOnTvjzjvvEyLi+eefFS/oDz74iBAfL7wwASNG/EW8eG/evAkTJjyNl19+HQMGDMKiRQvw4osT8NhjT6JLl6744YfvMXPmdEyZ8rXn5d5tgPLyw7j44tF47LFxIhbj119/EWJk5szZosmNN16NK6+8Vryca7UaXHXVpUKMnHvu+di+fZtYx9133y/+NwmQTz/9SIila665AYsWzcf777+Njz+egu7dezSzOQmQFi1yhbDJzW2JSZOegdFoEv+7vt4acK4zzjgbS5YsxLhxj+Gbb36AwZCOzZs34uGH7xNrGTRoqPj87bffwLvvfozCwl5CgJjNm/Hvf78JrVYHk6kQt99+A3r3PgGXX3419u8/gBdfnIhzzhmNG2+8Ne73Jw+oHAEl/1Aqt2oeOZUFSMOhg6A4tUhfOFPhrgj3+0gxFCRAcoYOg+x0onrVSujzC6BrG9lLeiTMaB6q40ExJ9GkxCWXMVVGhojlsJZuQVb/04JOb92+Dc66Ojht9dC1bQdd+w5hL3f3oRp8Nb8YZdVVQmRo7M0FiNT4T5Rq167Rol/PDjh3YBfotLH/iBauHcPekFdDFiDRUDvahwVIbPzi3juVBAi9uD/99DjMmDHbIxiWLVuCxx9/CHPm/IZ58+biuef+hTlzfkVGhiuo7eabr8HIkWfg+utvxt1334pRo87EZZdd6eF8880kIsY0+Tf60GIpAn32yitvYcCAgeKP5sqVy3HSSSdDr9fD2wXru+9mYsaM6fjww888406f/gVmz/5O/BsJkG++mYHp02eJkxq66MW/sPAE3Hvvg34FCJ3MXHrpX8Vn5Fb14IN3i339+uvPQedyn4IsWrRK9P3HPx4Vcz799ATPPE899XcAEsaPnyjW0apVK4wfP0l8TidL48ePw5IlS1BRUQe73SmE28SJ4zF79ty43588oHIElPxDqdyqeeRUFiA1mzZCUqtFsbrj7Qr3++ioqkL1H+uEAKGL4iVqLWZkkStWWpoi2NxB5NkDB0KlN0Q8B7mM0UmGSqcDiZHsQUOCjlG3pQSQZXEComnRImTdEBqM/gYv37QfP6/eDqe9Hum1TpDQqE/z89opAXaNBJ1WjzFDeqJPj1YR7ylQh3DtGM2ELECioXa0DwuQ2PjFvXekAsTmaEC9oz7AsWbw5WnUKuS0SEfFkVpQ6rtwLgkS0tRp0KlDZ6P47LOPhQvTRx997hm6pqYa55wzEh999D8UF1vw7rtviV//3Re9YNMJBrk0nX/+Gairs0KtPlr0yGazYezYS4UrlvdFDzsSNkuWLBKnJeQudcEFY9G5cxfRzFuAvPnmq5g2bYpHXNDnDodTuCz9/PMCIUDolOGFF171TEFuZOSWRcHivhedgLz//n/Rq5crkK+2tgZnnz1CiJmffvoh6Fy+AuSaay7DRRddir/+9SrPNNOmfYHvv/8WH3/8uRAgvXv3wV133Sc+/+qrL/Haay8LkUUM6HI6naivr8f33/+CnJwW4ZiV2yQBASX/UCbB9o6bJaSSHalWBKVpzeh94nFjP/dGw7Wj7eAB1O/ciaxT+3kY0Uu97LAj48TgsRXRQnVUV6Nq9SrhOqVpdPWNZCy3yxi5i1WvW4ucoad7utPfkbp6R5N3ivoSCyStVsSASAY9dJ27Bp3O1uDEDyu2o2jnQWgb7NBbZTjUEuoMErQaPdL1Td8f6EW0a7scDO+bh1Y58U3xG64dI+HnbssCJBpqR/uwAImNX9x7RypAqmzVcMiOqNYRjQChiTSSBpm6jJBzTp06BXPmzGoiQCorKzF69ChMnvypiI348MP3xEmD+6IXbIoJIZesc88dKVy3+vscD2dkZAhXJ3/Xpk0bxAnAggW/Yf/+/fjPf95HQYGpiQChF/bt27fib397vNkQnTp1FgKkpKQYkya95Pmc+uzevQsvvPBKsz4kQD744DPhDkVXdXW1WPsnn3yJWbNmBp3LV4DcdNPVOO+8C5oIkC+//J8QIDSeNx+aa+rUz8Uc7777DioqauFwHD3ebt++AzQaTUg7cYPkIKDkH8rk2OHxsYpUsSO5+VQuWgh1ixxknnTy8WE8r12Ga0eK+3DW1CC91wme3hRfIVyxunePyF0pXMj2I+WoXrcuqqxbbpcxKigIhwOVy5chZ/gIEXe5/3AtvvjVgvKapoHi7cp3oV5rgMbRAFmSUJYdRrZG2e5yuWqQYdNLqNep0aVNS1w6oidaZCpzMuSPX7h2DJe9dzsWINFQYwESGzUFe0cqQJL5BITcrZ588jHMmPE9srNdafuWLl2EJ554GN999wsWLpwXVIDcdtsNOO20QSII232RaxEFlvsGhFMcB72Iu12k6Fec6677q4jpuPbaG5uk4f366+n4/PNP8MUXX3sCtX/8cbaIQaHYFBIg9L/pc5XKdfpy11234OSTT8Udd9zjV4BQvAfFlNC1cuUyPPaYy81szpzvgs7lK0C83a3cE/3f/z0BWXbi2WdfaCZAli5dDOqzYMEC2O0q4YJF85M72ZNPjudAdAW/q/EeWsk/lPFeK48XmECq2NH9K7s6K6vJr/vHgu2pLgfFKYQTH0HB1ZJG06y2Rbh2JHcrqgyu94kPbCgrQ23RJhFfEW9XLHLzIvc4Q0EB0vI6RmQSb5cx7/gVmyzhnW/W40hlJdJssqh67r5yasth06RB5XRAkmVUG1wJVoJd6sYfw+jUw6nR4fQTO2PkKXlQN/5NDdWfBLBt3z6k5eWFahr083DtGM0kLECioXa0D5+AxMYv7r0jFSCxLEDJLyati7Ja0S/67dq1FycZFRVHRMwHxWXQyzEFoQc7ASH3reeeexYPP/y4KCBIcRmULYtcutyuVe79l5UdwhVXjBVi4+yzz8PWraX45z+fwKRJLwsRQ2KEgt+vueZ6cSpwxRUXY+jQ03HVVddhz55deOaZf+LKK68R2aNIgHz00fsiaP3CC8fit9/m4r///RCffvolOnbs5FeAtGnTVgSd6/UGTJo0XsShPPjgo8IdK9hcvgKEsnLdffctuOeeBzF4sCsI/T//eV0EnffrN6CZAHEz7tq1C2655U5UVFTi2WefEqdGjz/+ZCy3B/dNMAGlv48J3s5xO12q2JHqWpArkdpgQNZpA48Ze9KLa8XCBSK1bDjpYqt/XyvEh28RwXDtWL3udxFwruvQ/EW5avVK6Lt2i3ttENvePai1WKDv2hX6bt0jso23yxj9UFexYD6yBw3GnDV7scKyE5lVDsgS4FQdfT1sUXMYdbp0qJ0OqB12VKWHrgNCY9TrJWTqM3Dx6fno2TF0H++NuAVwzunDwxKSgSCEa8eIIDY2ZgESDTUWILFRU7B3KgkQwrRnz2688soLoBft9PQMnH32uSI9blpaWkgBQv0p/oFckA4fPiwyUFF2KHoR93ctX75UZIzasWO7SEd7xRXXeFyZZsyYhrffdmXXmjjxRZjNRXj99ZdF1ik6nRkz5iIRd0InHiRAaCyKJaFsWiR2Hnjg4YCVzskFi05epk//UoisUaPOwt/+9phI40tXsLl8BQi1/+WXH4Uw27t3j1gDrcs7Da/bRc3NYP/+PWIvy5Yth8FgwF/+cibuvfcBz/wK3q48dBwJKPmHMo7L5KFCEEgVO1q3bUXDoUOQG2zIHjz0mLG702ZD5dIlSOvUCYYAKdvdm6ETgMoli6Fp3bpZ6txw7Vi5fKkI0qeUtr6XECftIssaFQ5ocvuybt0KXYcOIauY+45Hfenl3l18sGLRQhzskI/PFm2DzmqDziajJlMFWXU0TqPzoVKUZbaB1tGAdFsN9uZ2DrlMtaSCsVNLnD+4W1QVzBsOl6Fm/XpkDxkSU12VcO0YckN+GrAAiYYaC5DYqCnYO9UEiIKoFBuaBAhlsnrzzfcUmyOeAyv5gI3nOnms4ATYjqlxh6SKHWs2bhBZkmx794oYgWPlctTWgoLn1RkZIhNVsKuh7BBqNmwQgdy+tTDCsaM4bVm0ANmnDYJK3zx4mhhqsnNExql4XnWlW2DbtQualrkRB7qTy5ik0cLQw5VSvmzRIkzZChy2OZBeI8OaLkHSG3DL6BORle4SIbWrliOtwASn1Qr7gf0w9OkbcjtatSqmNLruUx46faNTuGivcOwY7dgsQKIl5+rHLlix8Yt7bxYgcUca8YAsQCJGxh3iQEDJP5RxWB4PESaBVLFj1YrlSOvaFbVFRYjVDSZMdHFpZq+qRM2630VNjuyBg4PGX9QVF8NecURkrKK23lc4diSxQ8Hm2eQmJDV/nRLxITpdxG5SoUDQuI7KSlH0MKtf/1DNm3zu6zL262ffYWWNBqoGPZxqCbUGDcYMKsCAwqN1TOiUiFzanPVWWLdvj3jOiBbY2Ni6bRuo/ghlF6M4pGivcOwY7dgsQKIlxwIkNnIK9WYBohDYCIZlARIBLG4aNwJK/qGM2yJ5oJAEUsGOssOBisULkTVgIEiIZA8eIl6kj4Wr4fBhWKluhVqNtI4doWvXPuCy6aSEgtWpMriviAjHjuQmZN2yBVkD/BfyE/UznLIIFo/nRScrFGBPAfRkm0gub5cx845yLJg2B1W6lnBCj+osFXp0aItrzzZB5SWoKE4kc8Bp4gTEWmxJSEwQiSw6fcs4qS+0uc3d28Ldczh2DHcs33YsQKIlxwIkNnIK9WYBohDYFB5WyQdsCmNLuq2xHZPOJFEtKBXs6MqU9LuoDyFePvsPgDo9PSoeie5EQda2XTtFTAYVzksv7OV3CfQyTeIqa+AgVC5b2izWIBw71u/eDXt5WUA3KJGit7Y24BqiZUOB85rcXHFCkHO6K4VuOJe3y5gVGvxn5jpk7ClBA3JRkZ0Gjd6Au8f2RY5Xmlx3UD/FYjjrrKjduCFi0RPO2nzb1Gz4Aw1lh0WsirZNm2iGEH3CsWO0g7MAiZYcC5DYyCnUmwWIQmBTeFglH7ApjC3ptsZ2TDqTRLWgVLCjbf8+2PbsEXERlUsXI/3EPtBkhU69GhWwOHei2AHbwYPQd+mC2s2bA74si3b79yPz5FPEaU9m31OapOINx47uCuG+GbTcW6J0wPbDgQVKtFuvohojXbuJVLyRnE65Xcayhp2OGQtKsWHbXrQ9VIEGjQqHW+Rg7FAjTilo+rLvDuonNzyntQ7Va1YjZ9jwaJcedj/KIOaorkG60eg3w1i4A4Vjx3DH8m3HAiRacixAYiOnUG8WIAqBTeFhlXzApjC2pNsa2zHpTBLVglLBjnWlpZDtDSLDEp0S6AuMMbnBRAUyyk5UlZziQOjko3LJImSefGqzGh80NL28U6A6vchXrVoBffee0LZq5Zk1HDuKIPOcHKR18h9kTgKHhA6JnHhelOUrvfeJqFn/BzL7nux3f/7mI5exSrMFv1rbYMP2/dBb7ciuroFdX4/WphNw9ZnGZqcpjro6VK9cIRIR0IkSnRa5CxfGc0++Y1HciXCjy+sYVhA/uQ1CpWq2/nDsGO0+WIBES44FSGzkFOrNAkQhsCk8rJIP2BTGlnRbYzsmnUmiWlAq2JHcXzS5LZHWsROq1qyGvnOXmNxgogIZZSeK56BK5CSexD5ycpu9wFL9CxFYTSc7OTmo/mMddG3aNPmlPRw7ipOI7t2hbdXa72pFjEjpFlGMMJ5XxcL5yOw3ALWbNkDfoye0LY8Kp2Dz7NxYggUL1sNiaA2D1QmNTUYajkCvVeOKG85BdnrzOB9yxyOhQ5XTvQsXUvFGpS6325e2VUuoM7PCCuInW1M8j7Z10xOccOwY7T5YgERLjgVIbOQU6s0CRCGwKTyskg/YFMaWdFtjOyadSaJaUCrYsXL5MqSbTCKOgmJBdG3jX8siKrhhdKLMVlCrYOjRE/W7dsJeXi4yOHlfIlPWH+tEfRMK5q4t2gyV3gB9t26eZuHYkVLwZp7ST5yk+LvsFRWobXSTCmPpYTURCQIWLRQxK7WbNoVVZ8Qpy1i+cT/W/LYcTqcDVnVLSDJQa5CQY63AWSe2xwkj/YskCnSvNRche+AgeBcujHd1d+/NU3xO5YplQgBDlpsVifQHyiUGezQ5xaJ24dgxLPB+GrEAiZYcC5DYyCnUmwWIQmBTeFglH7ApjC3ptsZ2TDqTRLWgY92O7l+53bEFodyMooKkYCeq3q4i16ouXeGoqUH12tXIHjKsSTVtUYyvqgoZvU8UK/E+NXEvLZQdPe5Iw06HpFb73ZGjtibuMRPeblB1JJwa9xoIaa21AV8vKoVl1yG0P7wPdmSiVq9HXboEgy4dF+Ub0DlD9rDwHYdqpVBRyqzGAsChRFc8TOsWbrqOHcMO4hfZvQp7QZPToskSQtkxlvWyAImFHtcBiY2eAr1ZgCgANcWHVPIBm+Lokmp7bMekMkfUiznW7UinA7WiArWr+jn9+q1K0zc5HYgaTgI6Crerlq1E7ABdIl6iV68mlcqpFgZlVnK3EcHiZWVNTkpC2ZHqh9AJRLA0uB6xQHVCVKq47J6qmFevWysylIVK87t9XxWmLyhGVW0N9HVO5FZVojpdh8rMDHRp0xKXjegJQ/Vh2A7sR+ZJJ/tdn28cizv+hIo3KnVRJjOK5aEUyvbyw8JVLtRFp0KUNMH3NCqUHUONG+xzFiCx0GMBEhs9BXof7wLk3ntvxymn9MMtt9wRku5ll12Am2++HaNHXxCybbAGa9aswv3334lFi1aFNc6ECU+LduPGuf4b7KqtrcH8+b/hvPPGhGoa9edKPmCjXhR3jJgA2zFiZEnZ4Vi3o23fXtj27fMETofK9JRsRqAUtboOecI1iS5yr5J0aZ7K3+TCVLl4kahr4a6w3XDooKvoXeOv/NQvlB2JEbEKFmDuSWEbxzoq9iPloBoZVH1dBNxXVjQ7vSCXqwXr9mDBHzsg221Ir5UFi9Y1O7C3VRcMOjUfI07Og1qlQsPBg7Du3CEK/vm7fDN5hZOUgLJlUYV5Q35+E+EX7r1Sv3uXqHFC8RzhBPF7OA9qXngylB3DXZO/dixAYqHHAiQ2egr0Pt4FSGVlBTQaLdLDyDlfXl6O9HQD0tL0MVlCSQHy4YfvgcZ/8833YlpjsM5KPmAVWzQP3IwA2zE1bopj3Y6uX9WdMBQYhUGoIjW9UAaqp5FsVvONBaBf8CkWxF0xnALDKU6EYhrcl++pTzgCJFwuroDx/lCn+48TiZSft2AQpxN7dotf/t1XZa0NMxZswdZ9ZdDZHEizynBoJdh0ThSW78ApV1yA/M4tPe3dhRsDFVMUtUxqapDe6wTRp2r1KuHeFqw2B41JsS+ALDKEpXXpGtEJUF3pFsDhECdZ5B6X1X9AUEzeqYJ9T5qU/D6yAIn07m3aPrzqNbHNwb0jIHC8C5AIUMWtqZICJBFV1ZV8wMYNMg8UkgDbMSSiY6LBsW5HynikaXXUhUkEclc0/5U9WY1RuYxcrnqL7FZ0iZfTZUtc9TK0OuG2RKcglCXLfflzlQplRxG4bjCINL7Brni7LLnrnGSe1BfiNMRs9oipkl0VmLGwBLX1NTDUylDbZdQbJNi0ahTm6nFGbh3aDj+9yXLtlZVBiwv6xseQ+xq5RunaB64w73bbovooFJMjabVCwIQbuO6O4yEbEufsgYODMg4WaxPKjrHcxyxAYqHHJyCx0VOgd6oJkAMH9uONN17BqlUroFJJOOusc3H33Q9Ap9Nh9uxZmDXra7Ro0RJr1qzEww8/gW+//bqJC9aXX/4PU6Z8htraWowePQZbtpQIdyZyu/J2wSLXrQEDBmLdurX4/fe1aNu2HR566FEMbHxwbd1aijfe+DfWr/8DDocdhYUn4LHHxqFbt+7ihCKYCxaN+eqrL2L79u0YOtT18Nbr9cIFi7KCfPrpR5g1ayYOHjyAnJwWuOiiS4RrGO1v4sTxnruEXLyozWuvvYRVq1aivt6K7t174MEHH8VJAfxvw7nFlHzAhjM/t4kPAbZjfDj+2aMc63YUL/CFJ0DTwhXMK1yyqGBfX/8xAn82b9/5/cUCUFG7tM5doWvb1lXzo2v3Jr/gi+xOC+cj+7SBIhsWXaHsWL12DXR5HT2uXoE4VK1cAX3P8FPlhuLpfSIhXrxXr0LGkNPx25rdWLxpF1R2mxAfkIDadAmSJg1/ObkLBrSVYPdyrXPPEypQvq6kWNTXoKxidNVsWN+YotkVY+PvEi5UlH3sxD5C7NEYFGNjMBU2y1Llr79b5KgzMz3xLsG4iKD1zRuRPWhIs2ah7BiKd7DPWYDEQo8FSGz0FOidSgKkoaEB1113BTp37ow777wPR46U4/nnn8WQIafjwQcf8bygX3/9zTj77PPQokUunnzyMY8A+emnOXjppefwxBP/J4TCu+++iSVLFuHvf/+nXwGyefNGIWL69j0F77zzJjZuXI/p02cJK1155cVCoFx99fWorq7Gv//9PFq0aIHnn38lqAAhN68rrxwrRMWYMRfh559/xEcfvS9EEAmQOXO+w1tvvYann56Ajh07YfnyJWLNH3zwGbp164b3338HGzb8gQkTXkCrVq1x3313IDMzC3feeS+cTifeeecN7Nu3F//97xdR301KPmCjXhR3jJgA2zFiZEnZ4Vi2oycD1hDXaQFdwuVnx3aPC1NSQm9cVKBYAHLpkRsaRD0JypZE6XdVWm2TrbhOTk7wZFEKZUdRIb53H4QKxg5XqITL1eWeRC5yBaIux965v2F2fTvsLK9EWr0DOqsMu1aC1aBCTkYmLh2ejy7tsgK60oUKlPc96fHOMhZozZQ1i8ZNNxV6mpCIrSu2iLolaXl5Qbcr4kzyC0RAeTiFDxvKygK6aoWyY7jc/bVjARILPRYgsdFToHcqCZBFi+bj6afHYcaM2chuzJixbNkSPP74Q5gz5zfMmzcXkyY9g19+WeiJ4/AOQr/zzpvRv/9puPXWOwXpyspKXHLJaPztb4/7FSAkYJ599nnRtqSkGDfeeBVmzpyDjIxMfP31NFx88eUwGFy/bs2c+RU+//wTTJ36TVAB8tVXUzF16uf44ouvPRVWb7vtenTr1kMIEDo9sVqtGDJkmOduuOiic3DXXffj3HPPh7cLFv3KNm3aFxg5cpQ4oaFr+fKlePTRB7BgwYqo7yYlH7BRL4o7RkyA7RgxsqTscCzb0ZX+dIN4QXdfDeXlqCt2BT0n+0UFCKnAYI5PalyKSaA90MmHbS/FTDQPuKZ0vbpOnaFr01ZsgIT5ogAAIABJREFUM5gd/Qm1QGx8s3LFypAC0FU6nRBTG7cdxrrps7C1RUdobFqoHTKsegkNWg16dWmDi4b2gCHNVTAwkMvY0boizUUZ9RNpmFu0cNXkAISIgFrjCer3tx/vWizen9fv3g374abZxvz1d6f6JZetisWLkDN0GIIVPgxWcV7J7yMLkNjuZo4BiY1f3HtHI0DoVx8KGoz0oi9mixbpOHKkFnZ7mP1VqrCDyT777GPMnfsTPvroc8/Samqqcc45I/HRR/9DcbFFnFR8++2Pns+9BchZZ52Op56agGHDhns+v/nma3DZZVf6FSB9+vTFHXfcI9ru3bsHl19+oTgBad++g3Dh+vHH2Sgq2oQdO7bBbDajZcuW4vNgLlgvv/w8Dh8+hAkTXvSsgf7Naq3zZMHauHEDFi6ch+3bt8JiMWP//n34xz+eEmv0jQGhU6FffvlRnIps307rKEJdXW3YGbj82VjJB2yk9xS3j54A2zF6dsnU81i2oyu+4ECTlKz+ArSTibf3Whx1daheuQI5w0c0WaLIfLVkEVTpGcIFiF7efS/feifB7ChS4f6+VgidUFc4JwbBxrA7nKhvcHiaWDdvhJSVgyUHJKws3otOB7aiRtsWNq0GdQYV1Jo0nD2gGwYUtvX8aEadg53EHFkwr4n7mfd6fAtRep/ABFp3oD2HI2Z9q60HW5t7fnfWLHddF+91Kfl9ZAES6u4P/jkLkNj4xb13NAKEgtwo0C7SS62WkJ6uQ22tDQ6HK01fqIt+eQmW99y7/9SpUzBnzqwmAoROMUaPHoXJkz9FaWkJKEuU202K+noLkHPPHYknnxyPYcOO/jG56aarcfnlV/kVIN7pe90CZNq0b0VcBp1a0H9JzBQUmIQIodiScARIWdkhTJx4VIC8/vrLqKqqEgKEYj9ef/3fuOCCi2A0FuLEE08S8SR0auMrQMjlij6jvmeccRby840gQTJu3KMsQELdeMfB50r+oTwO8CXNFo9lOwp/f6BJ5WlHbS2qV61s9lKfNMC9FkLFBSmI3l3DpOmL9DoRl0CxLO74Fu/Pxa/2KgmGnvnin4PZ0V/a3kA8fMcNlxuJjl9W7cS6LQdgcxwVIB3LtqEyPReVhgzorU7kVlShTq/BkZwMtM7KxmUj8tGhVfOMW8FcxuiUgbhQzIXvVbVmNfSdu3hiZihdsbMueFY0IVratBXpkL0vd4XznGGB66K4i0dSG7qCrc09drA1Kfl9ZAES7t3svx0LkNj4xb13NAIkWU9AyN2KYjpmzPge2dmujCRLly7CE088jO+++0WcGgQTIHfdRS5YAz01Qej0ZOzY0SK43F8QeiABUlq6Bc888yS+/34uNBrXcfR//vMa5s79GV999V3QE5Cvv56O//3vv/jyy5lQN1a7JZHUoUOeECC33HKdEBMUW0IXiYsLLjgLjz76D5x//oVif+40vCS4rr/+Ssya9TNyc3NF+xkzpol4lIULVzb5tSqSG0vJB2wk6+C2sRFgO8bGL1l6J7sd6ZRD07pNsxgI4kcvjtrWbZv46AdLcZoszN3r8K6R4bu2+p07RK0P36ronpdYn3SzwewYqP6GPx4iHsJma5J1KxS3fYdrMX1eMQ5WVSLN6oTKy0Eht/oQavRZsKt04t/TGw6hPi0N3fr0xujBXZGmbV6VPZTLWOXyZSJew58wcwXR50Pb0pW6N9hpg3tfIlVv166ijof3RW7IlYupYGC/ZgUD3e1EWuCSYmSdNlD8U+WKZYKdpoXrb6a/S6SOJuHcKB692yj5fWQBEupODv45C5DY+MW9dzQCJNpFKPnFpDU5HA7QiUW7du1FEHpFxRE899y/RMYnOtmgLFHBBAi5Kr300iQRdN61a3dMnvyOiBuhF38KAvfNghVIgNAJxt1334rx4yeK7FeUkYuyWlFsCLl/BXPBohObq6++FKNGnYnLLrsCixYtwLvvviWC5mkdf/vbvQI/ZbIiN6/33nsLK1YswyOPPIGxYy/D559/KjJ7vfLKm0LA0Jrvv/9v4lSHguZffvk5HDlyBHPnLkZaWlpUplTajlEtijtFTIDtGDGypOyQ7HakbE/0Yuiu6+ANUaSMPeFoClv6TIliekoZznUy4T9gnkQAnYC4CxT6rsG3sGAwO7riINSezFDB9hOJWKEX9JVFB/DTqm2wN9Qjvc4lPuyao69qraoOoiI9Bw0aHerTJLSvLceQEzvhpBH+CwmKv8UhXMZ8a6c0uyd6n+gJthdZ0YJUTheiYflSUTdGk+PKpOZ9UUYySl3sK07cbYQd9u/zZF0LJGa8xwyWElnJ7yMLkNi+ySxAYuMX996pJEAIzp49u/HKKy+Il/z09Aycffa5uP32e8TLdigBQv0//ngypk//EjabDRdeeLEQIBTnQel8wxUgdFpBQodOG2icnj3zRUYrEkN0OrNz546gaXgpToOE0JYtxSLDVps2bUX6XRIgFMdBqXYpnoVONeg0ZNeuXSLDFqX53b17lxAphw4dFO5eCxbME3uqrq5C585dcdVV1+LZZ5/CW2+9L9y3ormUfMBGsx7uEx0BtmN03JKtVzLb0R1wLKnV4hdv72JyzgYbKpcs8Rvw6yqmNwDqMArE/pn2COflOND6fOMTgtmx+o910LZujbS8wKloj75Qh35hp7Z19XZ8u3grNu04AK3dDn2dDKdaQp1Bgqw6mrGrx74i7GzdHXaNHt3at8A5nVTIVtn9Ckr3GkK5jPlWj/dmJALCT+3nKaRIMUIkqgJVTqe+7iByymLle9Vs2ihcvaiYob/Lt/BhOHVHgqUGVvL7yAIktm87C5DY+MW9d6oJkFgArV27Gnl5HcUJCl12ux1jxpyJiRNfwqmn9o9l6JTqq+QDNqVAJflm2I5JbqAwl5fMdhQ++ORuU1gI65YtyOw/QGRUEs/XI0dQW7TJby2FcFPOholIsWaxFE30rYcRzI7kFmTINwq3pNI9lViycS+cThmDTmgPY+emv/p7pzGusTZgwe97ULy7HA5n07hLq82O+gYr9HVOaBpk2NIk1OvV6NgyF2OHdUeGQStqatRS+t+Bg6FNS0OaTh1WnZZQpzCBMnWJ+igL5iN70GBPEcFQldNDnZj5S9HrfUP4ni75ZuHyd/MEE1BKfh9ZgMT2VWYBEhu/uPdmAXIUKQV7U+HARx/9uzg9mTZtChYunI8pU2ZE7a4Ud4MlwYBKPmCTYHvHzRLYjqlh6mS2IwVp06/3lNaUfomGLMOdOah+z240HDoEqrDte7nrMrjjACKxFKXGhcPuKfAXSd9I24Z6uQ023tE4CVc62kB2pBfsykULkd6vPxYUlWPRhp1wSA1iaEnWYlBhHs7q3xlqlYR9uypQe7hCxE1Ut+mCxRv2oK6hHjKaJ32RZAfS6gGnpEJdugSnRochvTpiVL9O0KhVYnx/NTsaDpcJMZk14LSA2wvlMhYoa5VvRiohVIMU/Qu0Ru+FkXuVbe9eZJ58it/1+gqOWnMRVGl66LsFrjgvikv28F/sUcnvIwuQSL+hTduzAImNX9x7swA5irS2tgaU8nbZssWor68XLkoPPPCIqB7O11ECSj5gmXPiCLAdE8dayZmS2Y7kZmQttogAX3K5ql65UgQYU1yEeEmlitd+AnkpE1Ja56M1MiLhR4Hftj17kNm/v6e4YST9I2krsnhJRzNZRdKX2npXUQ9kR6e1DvsXLsbs+g7YUXYEsupohiqXCFGjQ1YW+rTMhL2uARrJif1bdqDUkQ5ZatrWe316mxUauR77W+UiPS0DY4f1bHaaImI51q1FztCj6X9d//a7EJWBLuHG1LZ5Vip3+0C1PdwnZpTWWJJcr4uh4kn8rdF7XaHSOvvea8ECzN3jitglrzgV7/mU/D6yAIn0G8YCJDZiCvdmAaIw4BQcXskHbAriStotsR2T1jQRLSyZ7Wg7cAC23buQecqpYk8UG1BrNiOr/wDQr+C69u2ha9+h2X4DpVUNBwwVzmvYt0/Em/gLfA9njHDbBAtGDmcM75OeQHbcvH4rVv+yFMWtOkOWmp9kkPtUeg2gltToP6grtu4pAzatRklevhBHLpEiAXLTbFWtK/fBUF8HbZ9+uHhYD2RnuFzjmry8HykH8fQuChlOlrIKyjx10slQZ2X5xRCotocrJe6aJvVO3KKkxYiRfscKlomMOvieNPkO4psIwbptG5z11iZV1X37BItRUvL7yAIknG9V4DZ8AhIbv7j3ZgESd6QpP6CSD9iUh5dEG2Q7JpExYlhKMttRVKIuL0OGV8ILemmX7Q1wVFYh/cQ+nmxH3giEW0x2jjgFifQily9NTg5su3dDX1DgqTQe6TjhtA8nXiDYOK6A53ZChPnakQoC/rxyJzat3YiM+nLsadXIQpaghQ4SZKjqbNDVO2HXSqhLp5m0UMk2dN9vQWn7AjhVakhONfI7tMLAXu2hahQk4sW81Iz0+mp0PGtUwCWKeJKdO5oEgIs4jYXzAxYSpBObqhUrkE3V4VUuVy7fSwR+19aKzFVNBI8fdytPtfkA1cnDCVIPFFMk4kcWLRACS6XXi6WESvt7tJL7EL8nbEp+H1mAhPOtZAESG6UE9mYBkkDYKTKVkg/YFEF0TGyD7XhMmCnkIpPZjv4KttELJRUapF/SyY1HaqyV5L1Rlx9+mt8K4qGAuOpI9BQB1Nbi4iaB7/760i/k/tYQah76XAQjt+8gTnKiubxPULztuL+sFtPml2Bv+RG0qjgISXaiPKs1JFmFHH06zuzfBYd2V2CD5SDK1Q2oT5M9px0UZ5O/14xtbXsC6gyccUpXDD6xqfgQa1/3u0gEQNXVKUuZv8tVqf5gszgdf+mT3f1dQfDbkNVvQEAkLmF6GBkn9mnSxl/AuSfI3Csw3bsTxRLZy8qQ0SdwVsdAdvIX4+Kbltd3E/76eLdR8vvIAiSab9nRPnwCEhu/uPdmARJ3pCk/oJIP2JSHl0QbZDsmkTFiWEoy2zFQjAS9aJJrVqCXRuGHL8tNKqSHi0jEVZx8iki96hv47j0GvdhaS7eAXmBFtXI/NSRCzSlqTHTrDm2r1qGa+v3c5YrkgKHA6DkBmbdyO75ZVIKGBisMtTIy66rhUGlg0xjQMtOALu2yoFFL0Bu0yD+xHRZvPoDVW/ZCVtk9c/TYW4LqjoW46KyT0Llt82rj1JCEGlWdzxpA6Y6bp6+lNr4pat0TiFoZXbo2Savs/sy6tdRVCNFUGJBJoMBwOs2w7dopCgd6X76peb0/C6dSOrmRUaC/3iee0198SLDaLjRvqJgTJb+PLECi+pp5OrEAiY1f3HuzAIk70pQfUMkHbMrDS6INsh2TyBgxLCWZ7Rgo21Go7Qo/fGtdMxedUP18syiJwPdVK0XGIl1jenXxEllbK2JQ6KJq3A1lh8Qv9oFOAgLNG6yid6i10ufC3ae8XJwEOGQZv67dg8Xrt0HdYIeB6nKogBbWPajJbIOhQ/ugb34rT3C2RquGSuV6pVpfWobvlmyB1dkAyBKGOg5gyPnDkNkusDCqWLxIxEeQCAyUbSxQrEagNLq0lpr1f0DTshXSOgauWRLoJT/wictil7teVnYzrOGIVapKb6+qQsYJvZv091evRMSUmM3IHjjIrwntFZQ+ejOyBw72+7mS30cWIOF8qwK3YQESG7+492YBEnekKT+gkg/YlIeXRBtkOyaRMWJYSjLb0VVArw3S8vIi2mG09TX8ZUwicUEvjFn9TxNuXbb9+0UGLl2HDq5fxCUJNet+hzojE4aCgojWKYKt+7pOW8K5bA0OFO+qQFmlVTRXVxyG5uAe1OefiPVbD+JwTTW0VXZobDIadBKsBhX6Vu7CkIvPQPtObYNOUV3XgOKdR9AqR4/cXUVBq3+73Zqo0KPINuYnEQBNJk4OdLpmrnCB/p36uNyzTgh6ohQocDyQ3akOSrrRBE2L3GYMwkkEQPeAdetWkfzA+xLuW4ebxiiFyvIlxtq2NaCLmZLfRxYg4XzLWIDERimBvVmAJBB2ikyl5AM2RRAdE9tgOx4TZgq5yGS2I6U41Xfu4tdVJ9jGRIXx/fuFa1QkV0NZmXCr8q1RQS+p5BZEAoTiBQxUlb1VK8/Qjro6VK9eJVKranObv+T6W4OnaN7AowHMwda6+1ANps8rxuHqahFATlearQ7tjuzBjrY9oaIaKXUyZIcs6nLYNVr079YGQ5w70fL04RHFqXgHt/tbkzuOgVLlqgzpAWteBAqyF/VPyM3KaGoyvCc+IkBsj7sx1Yehk5LsIUOb9BfuVNbmGaiEy1fXrkLM+l7BTmM889XWCPtmDxvuOUGiz4S7WENDk33QyVvliuVoMdx/1q1QMSJKfh9ZgETyNGjelk9AYuMX994sQAIjLS8/jLVr12DUqDOj4j5hwtOi37hxrv+myqXkAzZVGB0L+2A7HgtWCr3GZLZjtC5K3tW8QxM42qJ+zx6R6te3uCG5GlG8BhWYo9S8JER8L/o1nFx1hCuWn8B43/b+iub5fdmXZSzfuB8/r94O2VGP9FonJKerpUp2IquuChXpOaCXI1mrQo0B0Gn0uGBITxS2UqN200ZkD276oh6KSagsYm4BQKdAvi/g3mO7Kn53aOK+Rp/7Ozmgfw8kAH3XKwTfyhWgeh/eVyB3qkDroL7Va1dD1yl4zRh/2a6orzg90RuaCLBQdg11Oqfk95EFSKg7P/jnLEBi4xf33ixAAiOdOHE86FeuaAUEC5C43648YBwJKPmHMo7L5KFCEEhmO3oHhEdiSCpgWFfctP5EOP39/aLt7kcvllCrm/wC7jsmuYyROAkWQO3u469onu94tdYGfL2wFJbdh6BtsENvleFQS6h3ZXwVgfZdDm7Drlad4VRroNJp0a5FDi4d3hMts/WgEwFyCXJXjw+HgXixDuA65e4vhMLWLdDldfIr2Nztqih+pnuPJqdFQmgcOgjr9u3I6te/yZLECQal1+11QtClUmxO5ZIlyKGTHa9UvYHWHeyUg9yzDAWmkCdXol2+sUm8i796M6FOtgKd/rg3rOT3kQVIuN8A/+1YgMTGL+69WYAERhqrgIi1f9yNHacBlXzAxmmJPEwYBNiOYUA6Bpokqx1DpU8NhjZU9epAff39oh2JCUlU0ElJeuEJzV66fccJlQ1p+74qTF9QjKraGujrnKCCgTa9hHqdGu1zc9Ayy6VCcreuR1WHHkBmFk4qaIuCvCw0emiJNL/atu0ijqERJwlOOWBMi9vFLa1TZ78ua+69Bkq3a6+sRO3GDcgePKQJFtfJSzbSOncJit1zbwweImJM3BclBqB4Gt/+wZIZhBuHI0RMbtPg+KpVK0SCAm3Lo+54tJZgY9YVFwNqFQw9evrdo5LfRxYgkXybm7dlARIbv7j3TkUBMm3aF/jii89ALlTdu/fE/fc/jL59T8a2bVvx+uv/xoYNfyA9PR0XXXQJbrjhFqhUKnzwwbsoKbGgsrISpaVbkJ9fgLVrVwve7dt3wPTps1BVVYVXX30BCxcugMFgwMiRo3D33fcjLc31h2TdurV49dUXsX37dgwderr4N71eH/UJStyNHacBlXzAxmmJPEwYBNiOYUA6Bpokqx1D1UsIhpayVFH2Kl8XnVDmCBX7EKo/fU4+/nSSktm/v99Cc+4xqIYG1Svxly2pdE8lPvtlE2Q7uVy54j3qDBJkjQ6n9+mMESfnQd34y787vsHQvh1yczNQXl4Du90pMlRVLlmMrNNOE25CkVyBCv25x3Cn16UXfRI5VAvE3xWo4rc4/VmxDDmnj2hyokQudwZj6NMI8ZK/cD4y+1EKYFFBUVwig1ar1s0EV6A0upGIXH/uXYGERuXypSIDm7/UzKEyuyn5fWQBEsm3oHlbFiCx8Yt771QTIBZLEe644yZMmPAiunfvgWnTpmDu3J/w8cdTcO21l2Po0OG4+urrsXPndjz//LO47rqbcMUV1wgB8tFH7+ORR55A79590LFjJzz33LOC90MPPYbc3FyMG/co7HY7br/9HtTXW/Hqqy+JOf7+93+ivLwcV145VoiaMWMuws8//yjGO++8MSxA4n7X8oDxIKDkH8p4rI/HCI9AstrRX0aq8HYEEeBMv74HK5Lnbyx/bjbhzundrmbDekg6XbMga+82gbIhkQvPWzP/wOHDR5BeI8NBVcoNEjL1Gbh4eD565uU0WZL7l/mMrp2bCBByk6rbUiyqdEd6BYrRcI/jrs+i79oNlI7XX0HIYBW//b34uyuWU2A51dwIdZG4Su/TNLWuK9YjT1SH974CxYZEcp/4xgcF218g17NgIsm9XiW/jyxAQt1VwT9nARIbv7j3jkaA1NXaYG9ojKKLYEX0xczJMaCiok78whPOpdGqYEg/ekQbqs/8+b9h/PhxmDz5E/TokY+6ujps3LgeW7eWYsqUTzF16jfQNAYYzpw5XYiEb775UQiQb76ZgW+//dEzhbcL1e7du3DVVZdg9uxfkdmYcnHLlhLcdNPV4t9+/HE2pk79HF988bXnF6Hbbrse3br1YAESymj8+Z9CQMk/lH/Kho7TSZPVjsFOCEKZKpJftr3Hcv2q3j9gYb1Q87o/91cfwrdvoGJ6+w7X4u1Z62CotUGSgdoMNXq2b41LhvdEpqH5izn9ui9ptMgy5jcRIEIkUDHGAmO4y/a0owxiVFODCjL6u7x/xQ8UpxPqBIuECwX7q7OyxBSu+hl0IuS/PobvOvyl1g304h+o2KCDslutWY2cYcNDMvJdX7BTtliC3pX8PrIACWnmoA1YgMTGL+69IxUgDTY7lvy6Jap1SJKEtDQN6uvtIrg7rEuSMOQvPaDVacJqbrVace+9t6OoaBOMRhOGDRuBCy+8GB9/PBllZWWYNOklzzglJcW48carMGfOb0I8LF++FO+997FfAbJ48UI8/vhDwvXK+yKBM3nyp/j++29x+PAhcfLivl5++XlYrXUsQMKyHDdKNAEl/1Amei/H83zJasdoM1m5bRmpmPAENg87PeKCgr73TzgxKKKI4JEjzQLEf12zCwv+2IrMKgesBgkZOdl44P/Ze+/oOLL7TPSrzrmRAxNIAESDBAkwxyE5o5FGsmXJIyusrdWubPk5SGv7yOvn9/bIfsfeI9vrbMk5e3e9tiyPoiVZljSyhjmCBANINkCABEEQDEidc9U79zYbaDS6u6q7qhqF7nv/GYl9w+9+X1Whvrq/8IFd0HH5X38yL9euHX3LBAipVG7ZsiVv6lmx6z0x9yId8b4DebumXdXaYGproxXRLV0r4yDEYlxo/MSWrsVYmdjkJJJ+n+SA+XypdQu5PhXKPCVWFDB784uC6sX1UazgIDkBM9Q35C2mGLh0EZatPQWD3tW8H5kAEbvyi//OBIg8/BQfXaoAIQZo+QSE2MfzPIaGruLs2VMgJyLxeByHDh2hMRzZAoS4a33sYx/BN77xJr7whc/TmI8//uO/zCtATp16C7/xG79KxUZua25uxh//8WcxOzuD3/iNJQHyh3/4e3TNcrNoKU62QhOq+YBVyEQ2jQQEGI8SQFoDXbTKY6Gq1lIh9Z8/C1vfThrULKWR1LIkixVxJ5LbxL7+k/nzfZUnH9b+6EvX4Zv3wRoWEHTpcaRvM17bv7GgSWmcnqFuz55FARIPhtMxFkdekpQSeIWA8vlepO9dHiSe6ZcdfF2oWGShYoGZOWgGqZbWxSKG9FTFZqMFEKW0bBGU6U9PVQZ2rSjsWOhaknJSlW1L9mlPsVMimsyA7GVTx4qtENcxUj0+c/KT20HN+5EJEClXVuE+TIDIw0/x0eUIkHKNUPPGzNhEAswHBy/T4HLSiPh473tfw4c+9GF8/etfXeaC9aUvvYG//du/xNe+9m3631wBkp2GlwSwkxiSz3/+KzQ+hDTigvXXf/3n+NSnfgVvvvkt/MM//C/6u16vp7+Tk5j29nVMgJR7wbBxqiJQiftR1Q2wySkCWuUxE+gslpK1EI30S3P31mVpU4tRXqjadTmXCU3Fevokjb/QWTI5c5fPlC8u4fFMCH/xjRtp9yuSDtdmwk++ux/rm+wFzaCnFWNjqD98aFGAhB9NIT49DcfuPeWYDzHXpOyX6EKpb+kJFqmLsmdvXhtyX9LpSQrJKJVV4LGY8fmKHPpOnYRj/wHoczwNiECLP5qEY/dyWzLizdEvrWAlPXXZ1EELY5KaL8lAAPbtfSvMzMTIWLu6V/y2cOotuA4cLJgYQM37kQmQsm6HxUFMgMjDT/HR1SZARke9+Imf+Ch+4Rf+G/btO0BPQn7zNz+Nv/3bf8AnP/kJHD58dFkQ+vve90H8+I//FI0ByRUgv//7v0UzYv3Kr/wamptb8Au/8HMIBPz4+Z//Reh0ehrE7nK58JnP/CnNnvXhD7+fFi38wAf+A86cOYW/+Is/wWuvfR8TIIpftWxCJRBQ8w+lEvaxOaQhoFUeCwUOS9sVQKqomzcWLzCXPVdsagrJ+VnYd/RLXaJov0IpaDODSLwDqRli2bxlcZ7vXJnE2VsP4PCnaDVzV50bP/f+gaK1RzKuTo0nTiwKEP/NW0UrlIttsNgJTm58TfQBqT4eoVmfspvYCVZkfAxI8TTVb6Z4n+vQ4bxFHvPZSwWM1bp4YlIsKLyQSxkREQQ/qSI3O/almMgoVOtDrEih2h8EmAARu/KL/84EiDz8FB9dbQKEAEQCwknMx9OnT9Da2kYFxtvf/k4Ql6vPfvb3cOfOMOrq6mnGKpIFK5OGN1eADA/fwqc+9Qs089XXv/4mfD4f/uAPfhvnz5+lpxwHDx6mYsTtrqO8eL138bu/+z8wNjaKgYHdVLTIKWSoONkKTajVFx6Ftlcz0zAeq4NqrfIotyZHviJxxRiLjI8DqWRZQdv55hUTQPQLvtsNUkuDNPKs/+wXhhD0+WGJCAg69Ti2cwte3Zs+MS/UMrErjSeOo6HZjbnL/aVrAAAgAElEQVS5IOZPn4Gtry9vGlgpV22hOhtkbK44ydQEIa5P2U3sBCs7LiNJXb5IXRDpFdtz62ksZrTKKU5IbCoU65EWQSnJnGeLrdDtYRicpGbJSvc4Gs8S8K84HZFSfFLN+5EJEClXf+E+TIDIw0/x0dUoQBQHiU24DAE1H7AM6sohwHisHNZqrqRVHvMVfisFh3RRO3feF8R884jVZyhlbdI3n4tQ9hy5MRCPngfxV/96A7ZQAgIHRGwmfPw9A2hrWKpzUcgG4u5Vd+AAmja04PnDJ/ANXgVJZ5tdJbxU+31nTsGxZ++KjGC5sTKJuTlE743CeeDgsiWyTzjyrU1jKB5PUTcxevo0N0tjI6S23Kr1NCvV4GVaWyS3FQqIz3cKVWz9tM2PqCtX8NpVmNatX5Hyl4wvdPqTtmOoaJyRmvcjEyBSr678/ZgAkYef4qOZAFEc0qqfUM0HbNWDp6ENMh41RIYMU7TKI33BW78BppaWsnZX6sslTZ3a1k4zOynRIqMjgF5fsOJ1bhanb116iPO3Jxbdr+oa6vAz7+sv6n6VsZMEnDu3bUNL5wZMD91GbEF6NqlCe6UuZH07VgTxZ2JOnPvTGbJovMjglRUv/oViQzLrZWeRolyZTLBs6ZQMfa77FBFGpBAhEV65jbiI+S9dRN3xl5f9JCYSVwiZrEQFNOOWZxsMdWkPhuxWKP5FLDCfzKHm/cgEiOTLK29HJkDk4af4aCZAFIe06idU8wFb9eBpaIOMRw2RIcMUrfJYahB5LgSlxpCQKtw2jweGunoZaC4NFXNByq5jwQsCPvPGEML+tPtVwKnHy/1b8Mqe4u5XmdWIeLJuWI+2bV14+L0z0NU35U0BW8rGsjNdZY8jld5JDZOMy9Vi/MaRI8sqv+e6mK14mc8SLoHBy7Bs2kyDu6U2UhgwOTuzeGpS7OW+UIrlQoULC9mQvdfA+fN5A97J2MT8PKKjIytOhcQC85kAkcr+6vRjAmR1cC+4KhMgGiNkDZij1ReeNQCdpkxkPGqKjrKN0SqPYulKxTZcKDg63zgSf+E/fargC6XYWvl+z31Rz+2Tvb+HTwP4m3+7ueh+FbWZ8In3DqClXtz9isxL3MdMLifadnpw/2v/BttuUkxR2thCeyvkYpRPWPnOngbJJJWdWlbsRGnxZf7wEQQuFH6ZL2RfbhrcdErdCTj37lsxpFBMS6EaJsX4JidDJHA+NDwMd4GaMYVOY8QC85kAKedOq9wYJkAqh7WklZgAkQQT65SFgFZfeBhJpSHAeCwNL6321iKPNI3tqZNwHSycxlYMz0LF5/KNk1K3Q2y93N8LfQXP9MtOGfvNixO4eIe4X/GI2Dk0NNbjv7wuPR6CnPbodRyaOjdi+tJV2PcfKtXcFf1pDE5DI8zr1i/7Ld/JUroC+RYYG5sW+xaqSp49GYkzsW71IHJvBO6jx0qyOTE7CxIH4ty3n44rVFl+EW9a5X7/MmFGRKBt504aTC61kRgOvd0OIoAK1YxJRSIIXr4E9/Hl8ShSsm6peT8yFyypLOfvxwSIPPwUH80EiOKQVv2Eaj5gqx48DW2Q8aghMmSYokUelahKXig7Uz6okn4/wrdu5o0fKBfaVCiE4LVBuF86vmKKpZSxR4nTP37/n68h6g/AEhUQcOnxykAnXt61/MW/mB0k65IQCqCupR6++QDMXT3lmr04rlBQfr5/zydW/BfOwbaNZOJyF7SFuKGRl3+SwSo3i5bYBnIzW8UevwhkL5BGOd+JmlhNjnw2kNiWlN9P8pbBWaBSfKHrV0qmNTXvRyZAxK6q4r8zASIPP8VHMwGiOKRVP6GaD9iqB09DG2Q8aogMGaZokcdiGY2kbpX62z/M75KTO0cpfaWuX6zmQ/aJy8SzIP7uW7eWuV/9zA/uQlOdVepSiD97huT0FOxWI1JNbdA1LJ1ESJ4kpyNNc6vjkFtMLzd7FxlGXso5gxHWzqUgcpKZy7GXuIIVLqJI3LT4cBjG1tYV64jZnZvZSjTmhsb49C4GjUupyZHPBiL2SIYvQ309HP0Dec3MrZWS6UQD843GosH2at6PTICIXVVMgMhDqMKjmQCpMOBVsJyaD9gqgGfNbIHxuGaoKmqoFnmkdSHuDMN16EjZIBMXqMiol1YjF2uxqUdILizA3rdDrGtJv9NUtrv3Uped7JY+HblKYwi+cf4BLnsfLrpfNTU14OM/uLOkdchpQPT2MKwWPYwD+8DrDCWNz9e5UDG9fK5VuS//xYoCZq9FamkQ8Wfr7YWptbTsY5maGnUn0pmtxE4XaKD75iU3sUJuUmLAEdev0K2bNFsaETSFWr40xsVqh2TmUfN+ZAJEjF0mQOQhVOHRTIBUGPAqWE7NB2wVwLNmtsB4XDNUrTkBkpidQfT+/UX//nKQLpaWNXc+GtfACzS4WG4jGa0mngTw6FkQ5pEbiK/rAO9Y7oakCwdgmhxD1LMLF25PIx4MLrpfvX1XF44NrCvJDPIyHR68BHdbM3S9O5BM8iWNz9eZFtPzr0znmy9uggbcP5mGY9duOpXUmBpSTZzUACFxHLkiTWwDfCIBYguJw+AMBuQWJswdn5vxirrdDZPih6WJXHI6R4PXOzqWVbHPXY+mMd6+3AVNSnFMNZ+rTICIXVVMgMhDqMKjmQCpMOBVsJyaD9gqgGfNbIHxuGaoWnMCRCyDlBTkS/nCnf4y7YR54yYpUxftc/bmNL49OA4OPNrnHiFgdSFoXR7kbI2F0BCYwVRTB40lsIUE8HogajXh5963Gw0uS0l2kBOH4PkzaN7Ri2RTuyIChMbQPHtKs1tl2qJrUU5ygOyaHqRvocJ/uZsiJyexhxNwHT0mqd5J9vjFRAWHDkNnNiN89w50NhssmwimKxupEWJobIJ5XVrcpYPYxwrGcRQigGDgP3Malu7uFQH62WPypTHOrf2Sbw01n6tMgJR0W63ozGJA5OGn+GgmQBSHtOonVPMBW/XgaWiDjEcNkSHDFC3ySL++B/ywb+8re2elBLIXq2pdigE8L+C3PneFxjWYIwJs8TBSnB4xo3nZNMZUAuZEDEGLY/Hfw3YOrS2N+Kn3lOcGFrx0HuuP7EcIJkUESL60toVONjJiz3XsOBUSuYKkEIYkdoVWQ39xclIK1qRvtpuTWFFBEjyvdzgWRWbuqU0pa1N3ri1dMDY0FByWr5Bmdu2XQgPVvB+ZACmF5ZV9mQCRh5/io5kAURzSqp9QzQds1YOnoQ0yHjVEhgxTtMijmD+/lO0WCgTONzadsWk7DO6VVa2lrJXpM/ksiL/+5o3FgHJbYg6cwGPeuTwo3BHxwxqP4Lm7NT1UAFJ6A95/rBf9XY2lLLnYVw8eDc1uzM+HFBEg+Qr7pU82hlakn83FWkrBPbptgWw8RV2oymnZ1dqJXSSOpFAl+9zK7KWkac61jQSwi9mcLzMYrZcysJsKISZAymF8dccwAbK6+K9YnQkQjRGyBszR4gvPGoBNcyYyHjVHSVkGaZFHKdmCpGxWSiYm+vJ85hQNVtdZSnN9yrXhraEpvDU0Doc/hYiNQ5MQQ4dNQKB9KTsUGWOdfwJ9LIpg22Y6hUGvw9YNbvR3lZ+9Smke84mNxNwcomP34Nx/YAX82bEhUgruSeFPrE+6kGA3PYkIXB2EZeOmgtXUaZwPwb6rm/6X1BAhcSS2Ho/YMmX9npuuWGptG6V5zDaenYCUReXiICZASsSvu7t7o16v/zNBEEgy8jmO4z7j9Xo/Q6bxeDxbBEH4K47jDgOY4Hn+k6Ojo98uZQkmQEpBi/Wlf2wNOtTX2xX7UsdQXR0EGI+rg7vSq2qRR+pO43bDvGGjrO36z5+FrW8nDK7CheYy2ZTcxH1Ip5O13t984zamnjynMR1Blw7HN7iwvyEF5569y+YlaVyR4hUJes9MrDSPfDQC/6WLcB87sRifUcxticY3bOqgAkAsJa4skLMGkzorpg0bYWpuQeDSRVi29sBYX593+uiDB+Bj0cXMVZHREUBvWJY6WCm7yDy58+cGzRdaS2kemQBRjlUmQErE0uPxnBcEYcJgMPx/qVRqO4B/FAThIyMjI1/p6ekZAnATwK8DeJ3juF9OJBLbxsfHH0pdhgkQqUixfmr9oWTIrg4Cav6hXJ0d1eaqWuQxnbGoveTUrLkM0pfS7q1FffVpyt/bwyVnQ8pdKxpP4rc/dwXGaAz6pICQw4SPHNyI1vnJFXMrdcKTbYPSPOark0EqeScDgbyxOdkxGGmBlYJ1q/yCiMXuyuCN6zA1N8PUvg7Z7lj5xuTGFUlJiSvniZDrRig1KYLSPDIBIofF5WOZACkBy507d9bHYrE5vV6/886dO7fIUI/H80VBEKY5jvuSIAj/YrVaW69fvx4iv/X09LwJ4MzIyMivSl2GCRCpSLF+TIBU1zWg5h/K6kJK27vRIo80gxAJ8m0sLx4igzhxyzFvTH8hL9RoIPTUJK3XIafdnZjH5753G45gAgkjB95qwS/+0A5Erl6m1dCzT1fUePlVmsd8LkPUjUkQYO1ema44u3BhbryFHFyLjc3GMV/djeyxxC0sMTMD+85++s9iMSNybSZijbixkdgi0khShfCtm3AdPlp0aqV5ZAJELpNL45kAKQHLzZs3W8xm86wgCH/ucrn+WzAY7BQE4SSAXxIEoZXjuHd5vV7imkVbT0/PrxJ3LK/X+06pyzABIhUp1o8JkOq6BtT8Q1ldSGl7N1rkUexrtlREpdRdKFTvQuoamX7/emECl+9MwB7gQTJadWxoxX9+Rw98p0/B9SJVbKZv9pf7Utcp1F8NHn1nz8AxsGsxaDo3riHblmy3K6Vc6MSwCXvvQme2wLxpU16clwkQKjQfwbF7D/3ndEHFpcKEYmuV+nvs8WMkZ5cET7H4mey51eAxMz+LASmVxeX9mQApEb+enp4fBfDHHMdZBEHQcxz3P71e7495PJ4/EgSheWRk5IczU3o8no8D+Bmv1ys59yETICUSwrqzGJAquQbU/ENZJRCtiW1okUffqZNw7D8AvdUqC0P6Iuxy01OQQo0UwwPHLQYnl7vgH35xCP55HywRAQGXHq/t6cbRne2gcSg7dsLgXIpDyY5dKHe93HFq8Oi/eAE2jweGunRcRTFBF3/6NJ1Sd/ceUBe6tvaCGamU2nMmsNy8qWNZUcJ886frfowvFrdMZz5bXihQKbvIPLkna+n/vySAKikkmQBRhlkmQErEsaen57c4jtvEcdzv8TxPEoz/kU6n+2me59/GcZzB6/V+NDNlb2/vxwRB+JTX602niZDQZmYCgk5XGVr0eh1cLiv8/ghSKfmVXiVsj3VRAQHGowqgrsKUjMdVAF2FJbXGI4k9WDhzGnUvHRNNdSoGR+gu+UJugnXL8ixU2eOCt27SgHeSQancNh+I4fffuAJzKA5OACIOEz7x3l1Y12SH//JlWDZvprEKmea7dBE2kdiUUm1Rg0c/OSXoWLLdf/kSDdo2Nq7M1pVcWEDozm24Dx9BsX6l7qtY/8iD++CjMVg3b4bvwnnUv/xKwe7Uvrt34D5Ecu4A8ydPwrV/P/Q2m5ImLc5FTjzC90bhPnCQ/hup+E5EkKM/7QJWqKnBY2athgZHZV7WVEF09Sdl4JXAgcfjeVUQhH+ORCIbJicnI2RoT0/PLwH4CIB/B9CYewIiCMLHR0ZGit8hWTbwPC+QwkOsMQQYAgwBhgBDQC4CyXAEM2fOoO21d8idCgHvCEiaXde23oJzzZ6/CPuWDlja2spe7/zNx/inN2/AtpBE3MrBUufCp3/yJZCPc/NXr8Hc1AjbpiWB8+x7b6F+z24Y3e6y16zEwLnLV2Bpb4dtw3q6XDG7M7y1vuPteH7yNOp29cNUJ6+uitgeQw8eILHgg72rE3OXLqP11bcVHJLwBzB/5Qpa3vYKSOX4p29+Fy2vvAydySS2TFm/xxd8WBgaQsvLJ+j44Pg4ksEQ6vp3ljWfEoM49rImC0b2plsCfB6P5/8B8ENer/dQZlhPT8/3cxz3BUEQfo3juNe8Xu/LWb/9d47jDpUSA8JOQEoghHWlCKj5hYdBXDkEGI+Vw1rNlbTGY9LvR/DmDdQdfUn2tiMk9WokAvu2bQXnWjh3Fg7iIlUkVa+YIZ//7iiGx6do/EfIqcPOrg344NvSjgQhrxc6o3FZulc1vr6rwWPwFkmH7KKnQyQofeHkW/QEIV+9FCL0Fk6dpCcgvosX4Nq7D3q7XQw6Wb+TOIv48+f0BCQ0PAz3kSMF5yNZqEha4foTL4OkXiYnJnUnXl5MMSzLkDyDU6EQ/INXUH88LUDC99IB/LatKwP4s4erwWNmfnYCIo9lJkBKwM/j8XxEEITPGI3GdcPDw3Ey1OPx/FcAPw7gZwVB+EokEmnNOh357ossWL8idRkWAyIVKdYvg4AavsoM3cojwHisPOZqrKg1HqUG60rBIjb1CMT1xt5HvI9XtlKqpRdajxcE/M7nriAZDMMUExB0GvD6UQ92b027XNH6E9EIbL1pEbS45uEjin59V4PH7GxWfDxOU90Wq5dCkwds24bg9etwHTkCnVGd04UMF/HnzxB/NAlzx2ZEx8fg3LeyQGKmL5+Iw38ubT8fCoEkAnArIHILXhc5eEnNDKYGjxkbWRC6lKdG4T5MgJSAX2dnp9tgMNwF8B29Xv9ryWTSw3Hc35EsWCMjI3/t8XhuCIJwk+f5T+v1+vcIgvBLyWSyj9UBKQFk1rVkBNR8wJZsDBtQNgKMx7Kh09RArfFIg5mnH8Oxa7dsnGjhvKdPaCanfI0Ig8ClS3CRIoRluhJPPQ/iL//1BmyhBAQdELWa8PMf2Au3Pf3yna4K/gyO/rQNUl7ky9m4GjzSIG9eoAUT05XRr8F99FhB80hwvbG5BZGxsaJCpZz95RuTEavmzZupECmWSnlR+B05glQgiOi9UThfxGcoZU/2PLlCU2pmMDV4ZAJEGYaZACkRx61bt27X6XSfBUA+DTwnGbG8Xi/5/0J3d3e3Xq//GwAkSuqeIAifHBkZIbVAJDd2AiIZKtbxBQJqPmAZyJVDgPFYOazVXElrPIqdWpSCRWLmOaITE3Du3Zd3GDkdCXvvwHUwHZhcTjt9/THeHBqD059C1MqhrrEOP/O+gcWpEnOzy77Op8IhBK8O0togSjY1eMxOrUtf9kVe2slLNqfXIzE7U1SoKLVv4q4XHr5Fg/yJK5ajfwn3fGtksqulAgFJGank2uk7fRKOvelAd6l1R9TgkQkQuUymxzMBogyOis3CBIhiUNbMRGo+YGsGRA1slPGoARIUMEFrPEZJZqN4HLYej+zdJRfmQVxfXAcWwyCXzanEacvfffMOJh8/gy1E3K90OLR9M951cCngPPfkIPPS7DpcOF6hnI2rwWPs8RSSc7Ow7+inJ0nx6emiJ1PkxIRgLiRTcB3Mj3k5eys0JiPmLB1baKE/+/biFQQydU2SPh+S8+l9qdmyUzAHBkk2NPG6I2rwyASIMiwzAaIMjorNwgSIYlDWzERqPmBrBkQNbJTxqAESFDBBazzSitp6HaydXbJ3R750h27egOtI/urT2V/4y1kslkjhtz93BfpIFIakgJDDhP/4tu3o2biU/Wkx9oCkFSanA+QkYewenPsLxyuUY4saPGbX9qAFG0Ve8kkfUmtDZ7cXPHUqZ2+FxvCxGPwXzsPS0QHyv22ewtnOyBz+i+dpLE5yfmFZXI6SNmXPFbh8CZaubhgbGhbXNriLZwZTg0cmQJRhmAkQZXBUbBYmQBSDsmYmUvMBWzMgamCjjEcNkKCACVrjkVTb1jscMMuoy5GBhWQ+Cl6+BPeLTES5cEVGR0havrLFzsjkAv7h32/DHowjaeCQtFjw/354H8xG/bKlsl1xMoHTxeIVyqFVDR6z3cey40EK2Uf2Fr59G4b6elF3qHL2mDuG1Iwhpxqm1lZwJNNYV/ESZunq551Izs8pUnxSbA/ZBSd9Z07TIo1imcHU4JEJEDGmpP3OBIg0nCrWiwmQikFdNQup+YCtGpDWwEYYj2uAJAkmao3HYtW2JWxnWZfc04fc8SFShLC+Hub1G0qdmvb/t4sPceH2AzgCPMJ2DhvXteDHvm9lyt/siuIkdWxydgb2ncq6/6jBY7a7WPjuHeisVlqYsFCjKZSvXYWppQW2bdvLwrTUQQun3oKhro5WvCcuTsUatW39Boo/OaWxbOoodbmS+pNMW6QApbG1Db7Tp+AiKYzN5qJzqMEjEyAl0VawMxMgyuCo2CxMgCgGZc1MpOYDtmZA1MBGGY8aIEEBE7TGY2DwCnWpMTYtVQ4vd5tiaXapX37H5rLX+pMvX8fc7AKsYQEBlx6v7u7C8YF1K8wNDl2DqX0d/VIfm3xIM0op/YKuBo/ZAfOZl2myj0It4xJlXrcO1q095dJW0jjf2dPQmcwwtbXDvHFjcQHyQhCQgHVyfRE71Wyh28MwOF0wtraKpjDO2KEGj0yAKMMyEyDK4KjYLEyAKAZlzUyk5gO2ZkDUwEYZjxogQQETtMZjxk9fzFde6tbT7k/7oLetLIrnP3cWtp076UtisRaKJnDnwTzCseRitxQv4OSNh7BE4uB4IGw34ie/vx/rmx0rpkq/iDqpW1lkfBxIJRV/QVeDx+yUwcSdSCyImhQrJHiTkwWx0wip/In1I9eLkEjA0tktKigygiD+7Cm10dgsX+QWs4/W/jAaqQCRmvlMDR6ZABG7iqT9zgSINJwq1osJkIpBXTULqfmArRqQ1sBGGI9rgCQJJmqNR9+ZU3Ds2ZtXMEjYzoouNBNR38pK50IqBeKXT7JR6UyFC+aFown81deHMRcKghOEZfMLEKj7VdzMweCw4Rd/ZB90eeqJ0PgJQYC1eyvScSeGZZXRy9lX7hg1eMyuZREcvAJb3w7RivFEEBCXNvOG4qcRSuyZzEHiOkjVcXKiRFy/igoC713ozBaa0YsErBPXLTVbZHwMSPEwtrQgfHuYXmtiTQ0emQARQ13a70yASMOpYr2YAKkY1FWzkJoP2KoBaQ1shPG4BkiSYKKWeMwuFqdUFe3sTETZcND0uNcG4XqpeBHCN753D8MT07AHU/SkI18LOThs27IeH3olfxB0dgYpEmSvRvyBWjxSQbh7L4i7muvAQegs1qJXFY3hIe5mzcXFgIRLU1IX4t5G0urad+yEsbGx6JjIvVEafJ5JJ0ySHajZMlnWjC2tiN4vXqk9Y4daPJL5WSV0eWwzASIPP8VHMwGiOKRVP6GaD9iqB09DG2Q8aogMGaZoicdMDIGbVCbX6WTsamlodiai7AmjEw9oLIa9b0fBdW7dn8Ubp7ywRBIwJAREbNyKamTkTETQGfHRd+7Alvb8rlzZ6WxDt27A0NAI87r1iuxP7RdX//lzsPb0IHTrFtwvUgkXM5ycLEGnK7uyfKmgkDTLJLWxY9cuiLnt0Roz0SgIH1ICwku1Jbd/po6KsbkV8enHRWuoqM0jEyBy2WSFCOUjqPAMTIAoDGgNTKelF54agFu1LTIeVYO2ohNricfcon1KAFEoeDpw5RLMGztoYHi+FowkQILM45EQrCEBETsHo8WOLe3uZd2NBj36NtfDs6m+oLnZFdczmZjE3IVK3btaPBKcTK1ttKI8ESBaa+REKf7sGa07InaiQRIAJGZn6YmJkiK3ECaZQpck1iQ5P09PacSaWjwyASKGvPjv7AREHKOK9mACpKJwV8Viaj5gqwKgNbIJxuMaIUrETC3xKFa5vBzEM4HH2RmSSMxA8OoVuA4fBWcwrJiWBFN/7rujGHn0BPYAj6SRQ9RiwAdP9GLHluJuPvlszNQjcR07jiDJvNXZBWND6fMU279aPBLBpLPZkPL54DxwsBwKVB1DAr2JS5XroLh7GDmRICJESCQrIqaI2CGFGYkA4SMRWgRRrKnFIxMgYsiL/84EiDhGFe3BBEhF4a6KxdR8wFYFQGtkE4zHNULUGhIgahTpo5mITKZlWZmIKw4RIYXcr4ZGZ/Dls15YI0noU6TCuR7bO9rwwZe7y3Ityg54J8LHtq0PBvfykxS5V5Na9yNxGROSKWqeY9duuWYqPp4EepMYG1LtnmScKtbIiUTYe4cGorsOHlLcltwJk74FkBMa44t4GLFCiWS8WjwyASKfbiZA5GOo6AxMgCgKZ01MpuYDtiYA1MgmGY8aIUKmGVriMeMzb9+hXJG+7AxUGahIYLp58+a8gdK+UBx/+pXrSEbCtL4HKTBoszvwidf7YbMUf8EtRgWp2O3oH0Dw+jVFs3xl1lSLR/ICTdyH9G530XgZmZdh2cNJLE/0wQNJLlWJ2Rkay6J3OuHcs7fsNaUOpCdt167C2NQkWsRRbR6ZAJHKWuF+TIDIx1DRGZgAURTOmphMrT+UNQGehjbJeNQQGTJM0RKP5GVSqquK1C3nzknjTIaupt2v9Ppl0xDXq7//jhfjj5/R9LoJ4nplNeFHXu5Fb0fhGA8ptpB0sZbNmxEaHlYlAFotHiOjoyDCsJLFBaXgmekTm3qE6PgY3MdOiA4jLn7B69dhqK+nYlDtlkmqYGxsgKG+Eeb14okH1OKRCRD5bDMBIh9DRWdgAkRROGtiMjUfsDUBoEY2yXjUCBEyzdASj/S0AoAUVxWp2yYvqCQIPONuRQoBCrFo3krkV+4+w9cujC66XgUdeuzqXI/3He+UulzBfiQYntSdiN6/LymbVKkLqsUjcVcjAehEPJGq8Vpr8SdPaIpbIijFWioQQODqIK0XonQl+nxrZ1zv9HZb0YQH2WPV4pEJELGrQ/x3JkDEMapoDyZAKgp3VSym5gO2KgBaI5tgPK4RokTM1BKP4bt3aMAzqVKtVCMvqKTwnGNgF53Sf+kCrCQIvGl5Fez5QAx/9pUhCNEozJG065XD6cLHf3AnrOaVgeql2hf23gV4Honnz+E+Lv61vmMAftUAACAASURBVNT51eKRxFeQOAvr1h7RSuOl2qxE/8TMc2qf64B4TEcqHAZ1v1u/nhaFrERbOPUWTSlt294nKfGAWjwyASKfbSZA5GOo6AxMgCgKZ01MpuYDtiYA1MgmGY8aIUKmGVriUY0aGeQFlXzBJ2layRfw4PUhGrCcXWeEFwT8z2/cxrPJGVrvI2bhkDCb8JFXt6N7gzLB4uQkgWRFEmIxur7STS0e40+mEfZ6Ye/rWyHalN5DOfPxiTiS8wuiVdDJ3BmXqEqe5vjPnQWfSMCxe49oFXlio1o8MgFSztW1fAwTIPIxVHQGJkAUhbMmJlPzAVsTAGpkk4xHjRAh0wwt8VioaKCcLWan9iVfyoV4fEU61JOXHuLSxQfkFZXW+0gZ9NjfvQE/cEQ5lyMSRxEdu0czMKmRzlYtHomAI3ErJAOW0pm75PBaztiMSxQ5/ZASj1HOGrljyIkbH4nCuf8A9Dab6JRq8cgEiCj0oh2YABGFqLIdmACpLN7VsJqaD9hqwGet7IHxuFaYKm6nlngkL2u2Hg8MdaUHfI899uH88BM8Xwgv27AxHkHrzAMY9xzCwdQUmnZuh7ExXYODBJ3fuvkEb568h7ieR9gOCByHRpsLP/2DO2E2Lg9Sl8O42hmY1OIxE7gtpc6GHHwqNZa4RNl6t0s6MVHCpsDgFZDEB64jR6AzmkSnVItHJkBEoRftwASIKESV7cAESGXxrobV1HzAVgM+a2UPjMe1wtTaESC+s6fhGNgtWtE6e0cpnse/X53C2eFH4LkEkPOWYEzEseH5NGacbWgJzmPL4X3Y1O6iUyzMhnFx6DFmEUfUKgAcBx1vxI++sw+b29J9lGqZAGi1MjCpdT+Sl2fyEk2qoOdmDVMKm0rOQ64x2/YdMNaXLnLLsTN4Y4i6iEmtvK4Wj0yAlMPe8jFMgMjHUNEZmABRFM6amEzNB2xNAKiRTTIeNUKETDO0wqPA8/CdPlVSiloSOP7Fk/cwObcAgUsXy8tuHC/AHkyhPuBH3Gik2iRkcqG93o4t7S48mY9geMGHpJmnwzhBh8OeTXjXwU0yUV05fDEla3Mz7Nv7FJ9fLR6FZJJW8yZB6NXQSKY188ZNtDhlJVpo+Bato0IEnJSmFo9MgEhBv3gfJkDkY6joDEyAKApnTUym5gO2JgDUyCYZjxohQqYZWuGRj8fhP39O8pfiOw/m8NWzY4ikohA4YREFTtATPyoYEjysER7kl5bQfQj6BJ7UrUPY4qBCo8XpwlwgggQXS48VODQ7XPjp9+6A0aCc61XGMOLu5Tt9Eqa2dupmpnTTCo9K72utz0eynxE3NtfBw5K2oiaPLS0u9g4tiYX8nRh4MsBTYygTIGqgWt1zqvmArW7ktLU7xqO2+CjXGq3wmAqHELw6CPdLxxe3cu+RD8MP5hCNJ5dtL57gce/JHARdYunfBQ5GmPBy/0ZwoTjmpgNw1luxrqsBj7/7PUzMBjDetoW6WWUEB/3vC/FiEIz4sXftxMYWR7lQio7zXzgHY3OLonVOMotqhUdREGqsAzlxIQLEuXe/pJ2rySMTIJIoKNiJCRB5+Ck+mgkQxSGt+gnVfMBWPXga2iDjUUNkyDBFKzwmfQsgdUDIl+JYIoVvXpjAtfEn0KWS4Og5RuFGTjTcVhvesXcTwrNhhIIxdPY0Y31HHTiOoycrDyJ6fO0xhxgfWxQdmRnJqcmx7Zvw9n0bZSApPpRk+TI0Nila54QJEHHcV7NHdOIBLYSZqUMjZoua9yMTIGLoF/+dCRB5+Ck+mgkQxSGt+gnVfMBWPXga2iDjUUNkyDBFKzxm6nWEt2zHG2+N4nnAD0uEhzEuIj6gQ4PDio5WJ/R6DlabCdsG2uF0WxZRIfVFzBs7MC+Y8IWT9/DE54PApeM+iOtVq6sOP/WePhj0OhlIig8lX8MNLjeMzcuLIIqPFO+hFR7FLa2tHqTwZNLvk3zqpSaPTIDIu/aYAJGHn+KjmQBRHNKqn1DNB2zVg6ehDTIeNUSGDFO0wmPs8WPcGRrF12ctSCZjsIV56HggYuOQKiAMjJwJr+3rQH9XIz3pIM1o0i/+73ywJJI8vn35IS6PTFMRYtGb8KPv2o72RrsMFFd/qFZ4XH0k1rYFavLIBIi8a4MJEHn4KT6aCRDFIa36CdV8wFY9eBraIONRQ2TIMKWSPJJA7IdPg3j4NLDCqWpudAyPJ59gztkCS0QAr+Oo+DAZLTiwbR2MhuWnEzazAT2b6uCylZfNaGomhOmZEDrXudDgWjotkQHlqg6tJI+rutEqX1xNHpkAkXfxMAEiDz/FRzMBojikVT+hmg/YqgdPQxtkPGqIDBmmVIrHcDSBL58ex8jUDDi8cH/Ksrsh8By6pBFRvRNxM4eYRY91DXX44InuqhAIMiiSNLRSPEoyhnUqGwE1eWQCpGxa6EAmQOThp/hoJkAUh7TqJ1TzAVv14K3CBkkAZfzJNGy925atznhcBTJUWLISPE48CeALp0YRCIdoXIchsTyuQyfwsMdCiBuMmHdbwRtMONS7Hm/ft0H1uAwVIF2VKSvB46psrMYWVZNHJkDkXUxMgMjDT/HRTIAoDmnVT6jmA7bqwVuFDRLf/NjkQ7gOHmICZBXwV3tJNe9HXhBw6vpjnLrxEEIyDls4LTyiFg7CC48qSyyMxsAMImYbZl1NsJjteP2lLng2VaZStdr4Vmp+NXms1B7YOoCaPDIBIu8KYwJEHn6Kj2YCRHFIq35CNR+wVQ/eKmww+nACsYcTy+ozEDMYj6tAhgpLyuWRxHU890XhD8aXWUfEx7nhadx/MgtTPAVzVEDKyCFi5eCw2LGx2QnbzBQs/lkEWzYi7mxAa4MNe7Y2w2UvL65DBXjWzJRyeVwzG61yQ9XkkQkQeRcPEyDy8FN8NBMgikNa9ROq+YCtevBWYYOR8XF6AuI++hI4g2HRAsbjKpChwpJyeFwIxvDl02N48MxH8tmusI4TkrCGBeiTAmJWDnGjHl3tTXh9/zpw90dof9u27dDbbCrsrLamlMNjbSGl7d2qySMTIPK4ZwJEHn6Kj2YCRHFIq35CNR+wVQ/eKmwwPOJFfHoazv37obctpSqtBR5jU1O0crZ53bpVQL4yS5bL492JeXz17D1EYhFYowJ0qXwChJbZQNjGgTOY8crAJhzcbEPk1k2YWttg6ewCp1O39kZlUFz9VcrlcfUtZxZkI6Amj0yAyLvWmACRh5/io5kAURzSqp9QzQds1YO3ChsM37mN+LNncAwMwFC35JdfCzwGr11FMuCHsbEJNk/vshOgVaBClSVL5TGZ4vGdy5O44H0M/Yu4DiIy4qaVf57JvyeNOrjtDrz/eDc2NloRuHoF5vZ1MG/cpMp+anXSUnmsVZy0vm81eWQCRB77TIDIw0/x0UyAKA5p1U+o5gO26sFbhQ0Gb1xHcn6eZsEytbYuWlALPPovXYBlcycSz54gFQpTdyGDy7UKLKi3ZCk8zvqieOPkPUzPz8Mc5WGKCUiaOEQsOliNFphNSy56xGJSWXzr+nqc2LUOVrMBkdERpEIh2Ad2FS0WqN5uq3fmUnisXhTW/s7U5JEJEHnXBxMg8vBTfDQTIIpDWvUTqvmArXrwVmGDwWuDSAWCsGzphHnjxpoSIL6zp+EY2A2d3Y74o0eITtyHpWMzTBs2Vs0LtNT78cbYDL5+fhyJRJTGdeh4AVErh4TBgJ2bW/GeI1tgNukLXqGJ+XmEh2/BsXcf9FbrKlzJ1b2kVB6rG4W1vzs1eWQCRN71wQSIPPwUH80EiOKQVv2Eaj5gqx68Vdhg4NJFGgdhaGiAtau7ZgSIwPPwnT4F1+Ej0JnSWZmSfj+IS5reboOtb2dViBCx+zGWSOGbFyZwbWwahmQSVlqlnMR16GA0WPB9B7dg99amolgIySQCg5ep25V53fpVuIqrf0kxHqsfgerYoZo8MgEi7xphAkQefoqPZgJEcUirfkI1H7BVD94qbNB/7iz0bjcNFiYuSJlW7Tzy0Sj8Fy/Afez4skBp8jLtO3cGrgOHoLNYVoERZZcsxuOTuTC+8NYongf8tICgMS4gYeYQtejQ4q7DB1/uRkud+GlG2HsXfCwGR/+Assaz2WrmfqwVqtV8rjIBIu8qYgJEHn6Kj2YCRHFIq35CNR+wVQ/eKmzQd+okdb0iX/8dA7tq5oUnFQggdPMGXEeOrkA945qldzhWgRFll8x3P5LaHle8z/Gty/eRTMZgC/PQ8UDExiFpMGLf1nV414GNMBoKu1xlrEzMziJ89zace/dXhWBTFn3lZmPPVeWwXM2Z1OSRCRB5zDIBIg8/xUczAaI4pFU/oZoP2KoHr8IbFFIp+M6cpgHosckJOPcdqBkBkpibRXRsDM79S3vObN5/4Rxs2/pgcLsrzIiyy5G4jvO3p5HkgUQiCeFFJl2eF+CPRGBMJmEhLlf6dAFBk9GC9xztwo4tjZIM4RNxBK9cofFDprY2SWNYp/IQYM/V8nDT2ig1eWQCRB7bTIDIw0/x0UyAKA5p1U+o5gO26sGr8AaJ24z/wnk49+wFyYZFihFmmhI8kvlJ05nNFd6Z+HLxJ08QfzINx67dKzoHLl+CpasbxoYG8Yk02mNsyoe/f/M2TaVrBAc+JSwrJahPAYaEgLiZQ8yix/qGenzgRBcaXNLdzki8jJBKwr6jX6MoVI9ZStyP1YPG2t2JmjwyASLvumACRB5+io9mAkRxSKt+QjUfsFUPXoU3mAoGERy6BueBg/CfP7csHkIJHiP3RmmAe3Zwe4W3WHC52OQkrQFi3963og/JDEYyYZmaW7Ribkl2RGJJ/NlXbyJI9hcSAD0HPnP88WImUsMjauHAG0w4vG09Xt27gabVldqIGxdx3yMnSKzSuVTUyu+nxP1Y/upspFIIqMkjEyDyWGICRB5+io9mAkRxSKt+QjUfsFUPXoU3mPQtIHz3DpwHDsF3+iRcBw5CZ0kHHSvBI6myzhEBsrWnwjsTXy4yPgakUnltC94YgqmlFaa2dvGJNNjjq2fu4+q9R3AEU9S9Ku40IMVziy5YGZOdZjPee7QLPRvrSt5Fxn3PdeQIdMZ0FjHW1ENAiftRPevYzFIRUJNHJkCkspC/HxMg8vBTfDQTIIpDWvUTqvmArXrwKrzBxOwMovfvw7lvPz0BsW1fintQgkcibkgjMSZaa8Q2IrYsmzevMC00fAuGujqY12/Qmtmi9ngfzuMfv3cXlkgcxoSAkEsHz6Z1ONjbglTqRRAIAKNBhw0tduh10k89shen2cLOnqFue5xheYFCUSNZh5IRUOJ+LHlRNkBxBNTkkQkQeXQxASIPP8VHMwGiOKRVP6GaD9iqB6/CG8yOgwgMXoGlowPGpmZqhRI8khgBKkCy0vtWeIsFlwvdugFDQ2PeuhVUnFittCjhWmrhaBJ/+pXrCIeCsIUEmtXKaLXhlz92hJ72JEk0ukKNBKD7z52D+6Vj4PTi2bIUWrZmp1HifqxZ8DS0cTV5ZAJEHtFMgMjDT/HRTIAoDmnVT6jmA7bqwavwBmNTj5BcWIC9bwdyX8iV4JGcJJBG5tdaC1wdpOmH88V5REZHAb0O1s4urZld1J4vvHUPtx5Mwx5MIUUzWxnw/uO9ePXgZszPh5QVIC8SGOTWUVlTgK0hY5W4H9fQdqvWVDV5ZAJE3mXDBIg8/BQfzQSI4pBW/YRqPmCrHrwKbzD64AH4aIS6SJF4DVIR3LJ5C7VCCR6JqCGpl+w7tZclyX/xPGyebdTVKrdFxseBVFKTsSuFLpHhB3P455PE9SpBs1uFnDps3dCK//zOXjQ0OJQXIC8KOdadeLnCV21tLqfE/VibyGlr12ryyASIPK6ZAJGHn+KjmQBRHNKqn1DNB2zVg1fhDWZnqYo+uA8+Hoetx6OYACHB3ESAZBc4rPAWCy7nO3MKjj17obfZV/SJPpwAHwpp0nUs34aCkQT+9Cs3EA2/cL2yczBZ7fjE6/2od1lQX29XXICkIhEEL1+C+/gJrVBa1Xaw52p10Ksmj0yAyLtGmACRh5/io5kAURzSqp9QzQds1YNX4Q1mxzrEHk8hOTe7WNNBCR5Jil8IPBy791Z4Z8WXE8vgFJuaQnJ+DvYdOzVldz5j5vxRvHHyHqZn52AP8EgZOUQsBnzweC92dDYqcpKVb91UOITg1UG4XzqueYyqwUAl7sdqwGGt70FNHpkAkXd1MAEiDz/FR9eiAEmFw4jcG4Gjf5fieNbChGo+YGsBv0ruMXTrJgz19TTbU2LmOaITE3Du3afcCci1QQg8D+fe/ZXcluhaxO3Mf+ki3MdO0DTBuY0G5z99osmTm2xbb43P4mvnxhBPRGENC+AEASGHHts2teFDr3TTval1P9IaMtevwX30mCjerIN8BNTiUb5lbIZSEFCTRyZASmFiZV8mQOThp/joWhQg5EWMfBlmX/bKu5zUfMCWZxEbVQgBckJham+HqbUNSb8f4eFbcB0+opgACQxeBniBFqvTUsvda65tuWJMS7YTWxLJFL558SEG703DkExQ8cHrgLBNB4fVjo+/3g+7xagYj/n2nwoEELp5A64jR7UGT1Xaw56r1UGrmjwyASLvGmECRB5+io+uRQFC3C+IbzzL7lLe5aTmA7Y8i9ioQggErlyGZUsnjI2NNBg9+1RACR4Dly9B4FNwHTysKRISs7OI3h+n9U/ytcT8PKKjI7RCvNbas/kwdbl65vPBEuFhjAtImDhErTo0O1340Nt60FKXLiZJmhI85sNATMRpDbe1bo9aPK51XNaa/WryyASIvKuBCRB5+Ck+uhYFCMmAE5t8CFbht7zLSc0HbHkWsVGFEKCZoHq3weCuo65SvtOn4Dp0GDqzWZEXV/+lC7T+hOuwtr6Sx59MI/7saUE3S62+XE8+C+J/f+s2EskobGEeOh6IWDkkjUbs6WrH9x3cBJNxeU0Ote7HpG+BnhRrTVxW692uFo/VipdW96Umj0yAyGOdCRB5+Ck+uhYFCPmjGn/6lLqN6G02xTGt9gnVfMBWO3aV3p/vzGk4du+B3p7OBEUqW5OMVXqHQxkBcuEcSMC31uIExLJcqRVgzcdiICes1s7OkqmOJVL4s6/cgC/ghz1EXK64dKFBowU/cLgT/V1NeedU634kp0SRUS9cBw6VvBc2oHQE1OKxdEvYCDkIqMkjEyBymAGYAJGHn+Kja1GAkNShyfkF+mJmcLkUx7TaJ1TzAVvt2FVyf7knHmTtwJVLsHR2wdigTPYk/7mzEFJJGuytpRYZuwcIAqzdW/OaRYSC/8J5mmI2X5B6uXtJzM0hMnIXrkPpOJtS2tfOPcCV0Uk4AikqPsJ2Hdrr6/HBE91odFsKTqXW/ZiYm0V0bExz8T2lYLqW+qrF41rCoBpsVZNHJkDkXSFMgMjDT/HRtShAiN86yYRFiqcZGxoUx7TaJ1TzAVvt2FVyf3wiDv+5c3C/dAycPu22E7w+BFNrK0xt7YqcgPjOnoaQTEFrxepo+mGbDZZNHXkhF5JJehrkPvoSOINBMVoSszMI371L5y2l3Xvkw99/9zYs0TiN+Qg6dOhoa8Z/es0Dg15XdCq17keyl+j9+wXjaErZH+srjoBaPIqvzHooiYCaPDIBIo8pJkDk4af46FoUIOSliRRPs/Z4YGppURzTap9QzQdstWNXyf3lKyQXvnMbOrudvpgrwaPv9EkIvKC5hA7BG9dham6GqX1dfgEiCPCdOgnXwUPQWQqfLpTKV/z5M0RIhr0SToQisST+9Ks3EAoEYAsJiNo46CxWfPwHB1DvNIuaoASP+RZJPH+O6ORDOPdoq8aLKCBrtINaPK5RONas2WryyASIvMuCCRB5+Ck+utYESObLp8HlhLG1DeZ16xXHtNonVPMBW+3YVXJ/yYAf4Vs3lwWIU9ckXoB161ZFBMjCybfolpQ+SZCLU2DwCiwdHTA2NRecKjc+Ru6aZDypLxL23i3pROjLp8YxND4FRzCFlJ5DxGrAew9vxV6PtI8jat2P8WfPEJ96RF1VWVMfAbV4VN9ytkI2AmryyASIvGuNCRB5+Ck+utYECHG9Cg5epi8mmS/BioNa5ROq+YCtcugquj0SjxC9N7os1WxschJJvw/2vh2yBUgmxoRsKpNZq6IbLLKY/8I52Lb1weB2F+zlP38ONoKDgnFgpNp8ZHR0mdtbMUzuTszjc2/dhSUShzEhIOjUoWtdCz7yDo/k2BS17kdSqDE+PQ3Hrt1aobWq7VCLx6oGTYObU5NHJkDkEc4EiDz8FB9dawIkuTCPsNdLg3Ch18Ha2aU4ptU+oZoP2GrHrpL7I+5A8UeTcOxecqEh2d/ij6fSCRgMOtTX2zE/H0IyyZdsGsl+RU4RqAA5eJC6DWmlEfcqB8lyZy1sE4kFs3R1KxoHFns0icjYGC3epzOmCwUWaqFogma9CoeC1PUqYudgtNjwidcH4LKbJEMpl8dCC4mlMpZsIOsoCQG1eJS0OOukGAJq8sgEiDyamACRh5/io2tNgNAXsOnH9Mson0jA1uNRHNNqn1DNB2y1Y1fJ/cUePwap+O3oH1hcNiPASeyDXB7J/UOyYJHm3L8fels61e9qN6kB5oGrg7Bs3ARjc2E3rVL3QtL/ksBtsRMhQRDwxvfu4fbDJ7BnuV790EseDHTnT7dbyBa5PBaal1w/ydkZmqyDNfURUItH9S1nK2QjoCaPTIDIu9aYAJGHn+Kja02AkAKEyUAABqcLxEfevr1PcUyrfUIlHrDk5VVIJFgdFhUvlny1MGj9i8ErNEhaLo+ZVLacQQ/HwG5aW0QLjbpZXrlMU+wWa+mMYG0wtbUpZnb0wX1EJyao21ux05fxx378r2/fgjWSgD4pIOTUwbOxDT/8tq2SXa8yRsvlsaAAmXqE5Pw87Dt2KoYPm6gwAmrxyDCvLAJq8sgEiDwumQCRh5/io2tNgETujQIcR198iYuKo3+X4phW+4RKPGBjU4+QmJmhRfFYUweByPg4kErCurVncYHs0wGjxSTLBYuPRuG/eAE6kwm27cXjLdTZYf5ZaQXvO7dFa3GEhm/BUFcH8/oNipkXGR8DibNx7t1XVJD973+9jen7z6HnBYRtHCw2Bz7xej8c1uJuW/kMVeJ+zDdvdryQYgCxiQoioBaPDPLKIqAmj0yAyOOSCRB5+Ck+utYECH3pcLlp6k2WYrK8y0mJByw5iSJf6F1HXir5i295VtfeqPCIF5zBuKIqt+/MKTj27IXZ5ZQlQDIJHTizmboyGurqNQEycTujpxB79xW1R6xWSDmbIQHoJBC9WJFT7+gMvvZvdyBwKYTtHHidAe85uBX7eqVlvcq1S4n7Md9exarJl4MPG1MYAbV4ZJhXFgE1eWQCRB6XTIDIw0/x0bUmQILXrsK0fgN0JiPIC5rrwCHFMa32CZV4wGZ85cVcVaodSzX3R04BiFuUeeOmZcuQUwubxwNLU6M8ARIMInj9GnRm82J1dTX3I3VuqbELkdERQG9YIdCkrENcqIYfzGFdox0D3Y2LxQLJM4VmjhoYWCHIeJ7H2N3nOHdxEtPRECI2QNBxcBrt+OQHdsNoKF5wsJBdStyPeQXIxAPwkQhsvdukQML6yERALR5lmsWGl4iAmjwyAVIiGTndmQCRh5/io2tNgPgvnofNs41Whg7dvEGz1az1RtxqlKzmLIaHEg/YjK+8bft2mJrL+/IrZmet/16oGB8V4evWw7a+XZ4ACQToPUROQMRqblSSi6jEF+d8LmpS7JyeDeGvv3ETCSTACTpsaKzDB05006KBRPSR+hn2nTvTmfZetHAojjtDjzG/EMXlqTlELAnqCkrGv61/C07sKr8ekRL3Y14B8uA++HicJeqQclEo0EctHhUwjU1RAgJq8sgESAlE5OnKBIg8/BQfXUsChGSe8Z8+RdNzchzgv3QRdcdfVhzTSk5I93TuDE21SuJaKtGUeMCSlz/ihkW+zls7Oythds2tEbw2CNOGjSsEXsYN0b6lQ5YASfp8CN8Zpul3ScVxU2urJjDOxHlZu7qL2kNdjMLhkr/w/8uZ+xgcfwSBE+j8nMDBqrfgvUe70BEimcdmaHKLTHatp4/9GB1+CpPZgFkdcGF8CgKXTntsghk//8E9sFtKj/3IbE6J+zEfUOUKNE1cBGvQCLV4XINQrGmT1eSRCRB5lwYTIPLwU3x0LQkQ8jWPFB9zv3QMEAT4zp7RXAXnUgnO7MnW20sz+lSiKfGAJRW5ST0KvbtuWZrYSthfK2sELl2EZWsPjPXLYzNInAKI64+nR54AITV1Rrw0nsrU0gpTW7smoC3kepZrHEmEkFxYoEUZpbZkisfvfX4QoVRkxRCON+JlaxD9zXo4t/dB39iM0TvP8HTKh5Z2Fzb1NOGPvjSEMJ8eS4TLga0b8e7Dm6Uun7efEvdjXgEydo8+J63dW2XZxwZLQ0AtHqWtznophYCaPDIBIo8lJkDk4af46FoSIKlAAMQtxX30JZCTA1KsjNRDIC9Qa7WlgkEEBq/AvGEDxL74KrVHJR6w5Cs1sZ18ga4GNzilsFVyHlKjw7ZzJ005nd0ywcWunTtkCRBaaX3sHnRWCwwNjTCvK9+NSMl9p9Prigui+JMnINW+S8nENjK5gH/499sQdMlFEZE5CSH/sGHmEVr1AvpPHMCM34BoJImt21vQut6Fi7ef4puDYzT4nDQ9b8TPvL4bjW55zx8l7se8AuRFxsBKPVeUvAbW4lxq8bgWsVjLNqvJIxMg8q4MJkDk4af46FoSIInZWUTvj8O5bz/F0Xf2tKbqF5RDbmJuFqGbN2k60VJepMpZKzNGiQcsDQDmOJoxyHXwMA1kZk1ZBApVA6cVrp8+Rd3ePfIEyOwMSCwPccEihT3NGzYqu4EyZwtcuQzLlk4YG5diMPJNlXj+vORMeF8+NY6hB8SF2/B33wAAIABJREFUSgAEwKyzIZ6KLwqS9c8nYIoDYVM7NnW345VXuuBwWsDzAv7wi0OYiwbSpggctq1vxY+8upQiucztyq7nUmhdOUH65e6llscp8VytZfy0snc1eWQCRB7LTIDIw0/x0bUkQHIrQ6ezAfXSl/e12sjLZHR8HILAw330WEW2kXo6DYfNgER9K5LJtC97qS3svUtFB3kJtHSSl8XSqj+Xul6t9RdSKfjOnKanSzrj8vgCIlqjY2OoP3xIlgAhdXTijyapANHZ7bBs6tAEzP7zZ2HbsfLkJ9e4zAmOc/8BSXYT96vf+dwVRIQo7c8Jenz/vm6YjDr868X7iCWjWP/8OXQpA8JWPebc9RjobMe7D3dg9NEC3jjlXTo54Y348XftwKZWp6S1i3VS64WHuteZTLBs3iLbRjaBOAJq8Si+MuuhJAJq8sgEiDymmACRh5/io2tJgJCvtaR6MxEdpBHXJS1l7ymHXOJOQ1yZkqSo3/4DRasvlzN/vjHRu7fhdNsgbOwsX4DcvQOdzQY+FKL/tXTI84NXam/VMk+mSjmpBs6RjAtZjVwvJH1u44kT8gTI06eITz+m/GnlRZW6Vp4+CdeBg1QYFWtJvx/h4VtwHT4iiXbvw3n84/fuLIoIPW+iAeQumwkPHi7gm9/yQj/3FDpdAEG7FXPOJprlqsnhhE6nw1P/PECoEIBNDY348XdvV6QGjlovPLROitXK7k1JV4f8TmrxKN8yNkMpCKjJIxMgpTCxsi8TIPLwU3x0LQmQ3C96aV/xNpjaKhO8rTh5ADIZf0gwLfkCncm8o8ZamTlDVy/D3dIAbN5avgB5UaOCvJEl/b6SAoHV3Fu1zJ0RGflOxTKJCxpfeRkNjU7Mz4fK4pG6cj17Cr3VDuh1sHZ2rTp8fCIO/7l0ogmSartYS4VCICmJaVIKCe2LJ8dwfeIxOfqgImJLczN+9F29ePRgHuMjM7A7TPDfu4nxGT9CFjNmXS/SSwscOOgWYz843oAPnehF3+YGCauKd1HrhYcE82vpZEscibXdQy0e1zYqa896NXlkAkTe9cAESIn4bd261cxx3O9zHPdhAHEAf+P1en+JfEfzeDxbBEH4K47jDgOY4Hn+k6Ojo98uZYlaEiCkZoGhcSlYlqYj1ZDveim8LYqB28M0yDgVDqW/Qm9RN6WtwPMInjuNuo3t4Lp6y3pxJbZnsCeF8og7FokDYU05BJK+BZAv2PlwzZwS1B8+jKZ1TWULEBK/k5ybhc5KKuppI1tSWlQMwv3ScVEw+WgUxA0z3ylR7uBEMoXf+adBRLPdr3Z3whZLYW4mhA2bG7ClpwnBC+cwFeJxanQejx31i6l6s+drtLrwsz80AJ1OmT+Har3wZNI1mzdqI7ZHlNA13kEtHtc4LGvOfDV5ZAJE3uWgzBNXng1rarTH4/lzQRDeBuAjHMc5BUH4JwC/PDIy8pc9PT1DAG4C+HUAr3Mc98uJRGLb+Pj4Q6mbrCUBkg5O3bIYb1ANPs7BoWu0BgMpRkheBu07+6VSX1Y/8mU9PDQI97pW6Hq2ly9Abt2Aob6RZisi6ZBdR45AZzSVZRMbtBKBxIsAcefedMKF3EbSUbv6d6J587plAoSIExJ8TE4zxIpbZtLYkvozfCKhiYJ15CQwLWgPiV4W5J6Rmor79oM5fP7k3UX3K2PKiBPrm2DQcfD0t6Gx2UHXI3E3hvp6BBMC/uWRDo/mFhZPPsjvHK/Huw9048A25WqmqPXCE7p1k+7FvH6DKJasg3wE1OJRvmVshlIQUJNHJkBKYWJlXyZASsCvr6+vIZFIPBUE4e2jo6MnyVCPx/PfAJDUKf9HEIR/sVqtrdevXw+R33p6et4EcGZkZORXpS5TSwKEpCUlL+h6Zzrwk9Si0MqXW6l8rXiRvHQh/eLH6RC+TfzZ1a3sTrInxUbvwtXaCP22/rIFSHaVbvIV2krqVTQo45JSLpbVNI6mmH0yDceu3Xm3ReKf7J1b0NqzeZkAIUkBQreH4dy7D+R0qlgjhSSJICVuOuUU9FMD70xgPCnMKdbIaZ7v9Cm4DolnYXvje/dwc3I67X7FC+jQO7BtnRt7j3TAnFVEkGQeMxKXzlQKpp5efO/qFM7efgSeS1BzXCY7fvb9u2A2FncPE7M9+3e1XnjSJ8ZNMK9bV4o5rG+ZCKjFY5nmsGFlIqAmj0yAlEnKi2FMgJSAX29v73t5nv/bkZGRFSmCenp6PsVx3Lu8Xu+ir0FPT8+vEncsr9f7TqnL1IoAyfeyUW4lZKnYVqKf78wpOPbshc5sSWc9kvAyJccuksY4NfscdocVhh27yhcgWfE3aVcPF62KzpoyCIgV2QvdugFLczPadvQsEyAkJoIEZzt276GcFGvRiQfgIxHo7Q4kA35a/Xu1W2xqCsn5Wdh3SDsJzNw/epu9oOmxRAq/+0+DiCGd/coU5dDrdOHlV7rQ1Lok0jLPGOKyRHDJFDgcm/Lh7K1pOvbVvRuxvqnwWuXgp9YLT/DGkKYKTJaDzVoaoxaPawmDarBVTR6ZAJF3hTABUgJ+Ho/nk4IgfATAHwL4FPnbx3Hc33m93l/3eDyfFQSheWRk5IczU3o8no8D+Bmv1yv5TaBWBAgfjcB/6SLcx5ayApX6slICdRXpmnEhyaRaDVy+BEtnl2j9AznGEbGgN+hgTkZhHNhXvgB54TpGXLAyhfFs27bLMY2NzUIg+uAByDVv692WFxfifmi0mrFuz85FAZL0+UCECafTwbatTzQ9Nc0qF4+nBcj8HOw7dq46B3Tfsehipjsxg6Sk7L11fxZvnCLuVylwvACXT4e3H+3EwN7lhRcz9yNx80z5fKq7Q2b2ptYLT9q9s50m6mBNfQTU4lF9y9kK2QioySMTIPKuNSZASsCvp6fnlzmO+0VBEG7xPP9/63S6dgB/AeA3AWznOM7g9Xo/mpmyt7f3Y4IgfMrr9XZLXWZmJiAoFQwptqZer4PLZYXfH0EqVV79CLE1Cv1OfMNDt2/DfWQp5SZ1J3o8BefuPeVOu6rjSMCt/8oV1J84Qe0g+yMpUa2b1Utp67twAdaNG4CnU7DuP1w2j/7BQVg2boSppQWkQGT43ijcEvz2VxXwNbR4eHSUpny1dW/Na3Xk/ji4ZBLtB3Yv3o/BW7egs1hA6oSQcWIuceGxMYBPUQESf/4czoGBVUeICCsSuyI1Ixe5nm0eD4z19QVt/8fveDH86Akg8LCFgCarHR/76F4Yc9yoiBjzkerzPR5a6NG5O7/7m9IgqfVcDVwdhHnDBnoKwpr6CKjFo/qWsxWyEVCTx4YGB3uHlnG5MfBKAI/EewiC8D8MBsPm27dvT5ChL05FPgHgOwAac09ABEH4+MjIiDT/AwA8zwu5dQJKMHHNdI1MP0F4YgKNhw4u2hx7/hyBkVE0HZVWB0Brm43NzsE/PIzm4+k0oqEHDxCfX0D97l2qmEqK2z1987toOLAfc5cH0fba28teZ/b8Bdg7O2FpbUEqFsPzt06i5W2vrCiaV/YCNT7Qd/MWSHC4oyt/VrTww0nEZmZQvyf9kpwMhzFz5hyajx3F/LUhOLq6KDfFmv/OXXpaYnA5EX74CI0H8we8V5KKhaHrMNa5YZcowrOvw3x2RmNJ/PJfnEZciMIQFWAJCXj1Hdvw6rGVuKYiETw/dRp1A/0IPVj+rKkkBkqtNXv+Iuydm2FpZQJEKUzZPAwBOQhwtfCyJgcgkbFMgJQAbk9Pz0c5jvtzr9e7WFHL4/F8H4AvCYLwaY7jXvN6vS9npuzp6fnvHMcdKiUGpFZOQKKTkyAuJo4dOxYZoC4nw8PLTkVKoGfVu9ITnKlHcO5JB9wm5udp6lW3xMJqpW4gGQggODREK2hHr16C9eBREo9bVvNfugRr11IF9IVzZ+HYLu72U9ZiNTgoSAKI6xtg2ZA/gxE5sYhPPsTGV4/TE5DAnTsQkinYt29H+nRK/Mt35rRB73RRNzrX3n2rjnTgWtptyCyxto9Y/+v3ZvDGqTsAn4QjIIA3GfHz/9dhWM2GFXvNnEg6dvQhMj4Ol8QK63JBU+uLq5+4dG7phKlpRQiiXJPZ+DwIqMUjA7uyCKjJIzsBkcclEyAl4Nfb2+vhef6uXq/33LlzZ4QM9Xg8/1UQhJ/gOO6/CILwlUgk0jo5ORkhv/X09Hz3RRasX5G6TK3EgNCMV7wA69YllxRSOyN4VVrNAKl4VrJf7FFaVGWCXUkqVJLpS62UtpnMSu5dA4hfvQjTnoNIQVfWlgOXLsJCMl+9cH0hsQfkhZml/CwLzhWDxPz3SaB59O4wtrz7Ncw+ncf8uXNwDOymGeKkFugk6W5J8gMyhiQncO5b/RMQGgfV1S3qPpYBjF53DY2I1zXjGxceYHqWJhRcbOQEJJIKwx4CdLyAdT3t+I+vefKSlC7+OAR7Xx+IOHMdEE8FrATbavmcp7HsgrGhUQkz2RwiCKjFIwO+sgioySOLAZHHJRMgJeLn8Xi+DqCBuFbpdLo2QRD+XhCEXxsZGfkTj8dzQxCEmzzPf1qv179HEIRfSiaTfawOyEqQ81X15WMx+C+ch/vYcepKstZaZHyMpvskKWwzjaa07Snu017uPsl6JNDWua0X8cvnaBA6rzeWNR2x0+bpXQx0pgHN0WjBoOmyFqmCQQRvGuhts5W0m3TNG3LClP/lkQSoh65cwpbX343podsg7nyOgbTrntT0q5l7ip6AjI7AeWDJvbEkYxXsTOp6OPoHFlNti01N9gCbDf/nRhDTM3MwJNNVzrObjgeMcQFhuwGvv9yL/q78JwJE1IWHb8G2vQ/hO8NwHaqMaycXi6CxvREL/mjZSSHy4eS/RNJjq/MsEeOlFn9X88W1FvFcrT2rySMTIPJYZQKkRPw6OzvdBoPhjwC8j+O4MIA/8Xq9nyaV0Lu7u7v1ev3fACB/+e8JgvDJkZERUgtEcquVE5B8X4QXU/MePkKriK+1RtytdFYrLB1LQedqprTNnFLYOzYhfuU89NsHIJgsZcHmv3AunWnJ7abjEzPPQTIYaeErelkbUmlQuZna/BfPUzFncNfltSxT0b7jXa/i4XdPw0zrsKTFCr2G6upET6NIvRCD0wU9iQEpUHVdJVgK7klqXY/MBOSk4tr4PL43mYAlmqL/LOT5KxU3cxAsFvzif9gHsyl/DY/kwjw9+bBv30FPQtxHX6rI9sPXr6J1hwcRs1NZASJyDVVkczW0iJovrjUE46pvVU0emQCRRy8TIPLwU3x0rQgQ8jWPZKcx1C3PduM7fRKOvftL/sKsOBFlTEjz9De30EromaZmSlv6UuvphaWpEYlrl8F19wLW8moaEFcx286d9AWWNHL6QThyv7Q2T6PKoE/SEFLsLzG3dDohadCLityklofeXpif4IWzaOzejPmH07DtWYrfIKcCpAihWF2WdKXsBlovhJyakHTQq9nKOdGcuHwTXz89iYjBhoSZQ8TCgcPK+A7yr99/oLNoBXOSPSw6PgYbESCDl2nK70o0cpLV2r8NUZtbWQFy/hxsfTtE68FUYo+1sIaaL661gJ9W9qgmj0yAyGOZCRB5+Ck+ulYESFpo7ENuwTH/Gv4jG7hCgkSX1/0gKW3JS5BT4QDYxZojh4/AZLMgeeMqsKkTcBQvVlfogvWdPZ2OOciqtk3cZ+z9/YuiRPGLfQ1OSIr9JedmIaWyd2Z7Uit8h69egZlLARs2Q9+8lOko38laPugy1ez1LjdIAUP3S+lsbEq0qZkQro08h9tuwuEdbTDoxV0k0zEY1+A+mrbjyVwYQ6MzsFsN2NvTDFtWxXLy+/xcGF/8xwuIR6OYrbcjYeJgEEx475FuOHL6ttRb4bIXPyUlVeSjkw9pQUbiYlh3YjE/iBKQFJyDCMnW3TsQs9crK0DOnaW1TEiMD2vqI6Dmi6v61rMVMgioySMTIPKuMyZA5OGn+OhaECCZ4GziEkFqBGS3UoNWs8eSl/Lc+RQnqMiE+fzdF78C59mrHNuof/utm/QrN3nApoaHwLdvAufK7+Ijtla+CtTkRMfY1ALzuqUTHbF5qv13EtxNRGUprml8Ig7/uXNUEHD6/O5CBLfIreuwIAlD/15kl+WJjI4AelJLI38K3wzmmWB1vduN4OVLcB9X5ov/QjCGP/vqDURTUUDQoW9TCz74cjfEMlCSLHAkFsW+/wDO33qC716bgJCKQ8dzsJsteMfeDqxrTMfSBAMxnD0/gZnnz2HgFvCksR2coMeJHR142578mcPErjWSlS4+/Ri2vj5J+IvNJ+V3QRAQPHsKbXv7EXM2KipA8n0kkGIT61MeAmq+uJZnERtVDgJq8sgESDmMLI1hAkQefoqPrgUBQr+MDl3L+4WWfLk1rScpR4vXPMgFnrzok0DfSvl5565f7Cs3PdXZvr2g/385F1H8yTQtrkYClckDlr97E8nGNujqy8uQ4zt1Eo79B6C3LmaYRibInbjKsZZGgGRvS8zOlJRRidSjkCIIEg/vw91Uh7hr+YsrzRgHwNpVvJ5p5t4hcTw0mcPxE6IiQQqv/3bxIc57H0Lg0sVKOd6ADxzzYGdn8WuNXJ++Bw/xLZ8Lo4+fw5RIwRxdCirXQYf2BgfaG+0IRRO4+cwHgzALRzSAxw2b0O6uw0/8QJ+k05Z8+yDig6Q3JlnpfGdOU7GuM5aXpEEKTqQP+QiSPgHZibi7SVkBcuYUHHv2rjg1lmob61caAmq+uJZmCestBwE1eWQCRA4ztDYva1pCoBYECPGhj47dy+uWlEnDaV63viRaSArfwOXLFXOzWCGAMjETx1a+9KmR0jY7jTF5wAqjtxF3NkDfVJpwy+xj4eRbcB08RCtvZxr9gvz4UUnuRiWRtgY7R0ZHaYC+q4TaLsnAi9Oqw8VjMgr9oSQ1LJBKLsuulg+6wOAVWDo6QE5ApJy4SIE/EkviD964iqgQXdbdrrfh46/3w2Ur7AY1du0uzpy/g/u2RlgiAgwJATELh7h5aSqO16OjpR6hSALPwgE4oj7UhebxtLEHP/EDO9HWUFq2sWwj0wkD5mjcBBHYrkOHoTNnLS4FgBL7kNip0JWLaBnoQ6K+RVkBkucjQYnmse4lIKDmi2sJZrCuMhFQk0cmQOSRwwSIPPwUH10LAiT7630ugPnS80oBmZyqkBew1Urhm0n5me/FlKa0jcVowLhSjfj7G5uaQIQaecBi3IuYxQF9S3vJSxQ6vaF1WQavwHX02JpMi1wyEBIGkKxKiefPFuMaJAyhQeuFBHf2+EJ/KEk2Mj4WFb1+Mql+ScYspb74n77xGG8OjS+efmTs5QQOPe0t+PDbe1acsvC8gLeGpjB8bpAKp6g+fVISsXLgDSYI4CHo0hmuSCNzkW9h5ITFFg2i2TeLnne8imMD8lz/SMIAUqyTxIDkO+GTwl2pfchzKDw0iJb+7Ug0tCoqQPJ9JCjVPtZfOgJqvrhKt4L1lIuAmjwyASKPHSZA5OGn+OhaECAkkJePRPLWmCBfmKHXwdrZVRK25Ctz8OpV6oK1GnEgNG3txASceapP02DYhw/g3KtcYbh02ty0Wxd5wHIT9xDRmWBoL91fXkilXrywHoHOuPRFm/iz+0lw+q49y4LTSyKmyjqTgPDEs2clxVfEnz9D/NGk6ElSQQHycAJ8KET5LtYyxSSpAFHgi38yxeOzXxiCLx5cIRSocOANeP3IVuzY3ACBTxfr8Ifj+OqZcUzOLKBpYQbgLQjarIhaOTitDrzvWDcez4Tw70MTSCK+4gzeGotgW8KP9/7UB6DTyfvzlP2cqVT8BEn9G7l1A807epFsaldMgEhNZFBlt9uqbkfNF9dV3ViNLa4mj0yAyLuY5D3h5a3NRudBoBYESLGgWnpaEI/TFL2ltKRvAcGhoYr4eeezK/Z4CsnZWZqlJreRInOBS5fgIkHIChRYXMyA9cKnnTxgdY/+f/beM7iOLDsT/J73DwBBgAAdABIEQILek0WyqmvbS+puTatbZqSVnZFaUuyMdidCMbMbsbM7sbuxo52QNIrRjHqmNfJSe3WpSm3L0BS99wABECQAEiDh7fO5ce5jPiYSmXlvmgcCZOaPrqrGdXlOZr773XPO993HTM6DwNr1ZszG2srjaYE3VlewejWCq+pMj/sydiCtDQKUZiJt6UePkBsZ1nw2lDbS+6FM9/chNzHBahmMLqXWiBMn/sRY9e3THaVohbcQQCQQwExutggcJAnJVADb6ysRCvhAxeq9g5PIFfKQICGWnkEqDIwnKrFpzUp87sgGxCPFGoyHQ1P45okujM/NzIuuxLMSfm5dHms/9qbtx0eZuibKrkfpksRkZ0SXbLQwdhBx9zZqtrQgV7vGOQCic0hg20juALoWKOfG1TX74lmgnH50AYg9P7oAxJ79HO/9KgCQol5BlaawWrqvDxTNoLQJMxedPE5fu7Yoed5a6+KlWZlVhDa6dwJbs7dvl+oQ6APre/wQ03NZBNY3mTEba0uAjzZoWptqUQpY05Mu0w707BILlplIm6gWjC4AIXA7OoLY1oXgVmlG5SabUrB4uiNGLqDo13/+zk0MTo49AxseNNWsxGtb6/HX792BR8ogMgv4csCK+krUVMdwrWcIBU+uFNVYNdaPmfhKHDi8nVH3ej3zf26ovuQ7H/bgTt8wQPTDkh+f2r4abVP3UXnMPmWusnhfT3dIbQOyYaS1tSQCafYxpfTSdFcnVrY1I1+3zjkAksuBviFmnjuza3fbz7dAOTeurq0XzwLl9KMLQOz50QUg9uzneO9XAYCwYtn1DQjU1CywH6sPeTKE+PadpmxLefZMfE1VSG1qEBuNqTaAGHbCTdpUqYwitXa+SKHV6ehEPTv8pGQj+sD6nwxgcmIGwSZjpiStOUtUwRqsSTxgZfUelms/qr3JjY2ZArqiReR6P5SZwUFkhgYZ45nRxUDujp0sXY6EJe1oRnQNTOAvf3QLkjfHpqR0q3/65ha0rKvEN757F71dQyh4JcxGPZC8fgY6JAIRzy4P0fVODODgp1/D+o36aYEEdG73jqF7YAKN9QlsXZ90roBeQV/MNHo2bOQCCwJu0bY2BFYu/DaJPLN0gJJ50IPqlg0orG5wDICIUjmLrNFtI2aBcm5cxVbgtnLCAuX0owtA7HnIBSD27Od471cBgBilQxTrJbRrKYyMTdSoMzdvIrH/wDwqWccdpDNgkemqGqE12uxdRdaqApfJSGS9c133WLNI8yb2T/rABkYGMf50HKHmFpEh5rWhFLHJ8+c0T52NCANMT/QSdCD6aEqHMvOcETj1+ANcHQ9dAPLkCTIDxEa22xiAKGhalelYVsz+F9+/i66hp1QhzrrXxivw6z+xFT13n6L/wThuDU5g2J8CNOo0CKy0r6vBm95HqNq7x1T9kJO1Dsro3dTlSwivW6956KG0DxV6R9s2I7jquRCkGfsRYM/2P0T1piYU1jQ6B0DSaUeplc3c06vatpwb11fVpi/ivsvpRxeA2POoC0Ds2c/x3i87ACltMHQiFZRKRRu25P6DpmxLwIXy80kgzmr+tqkJVY2NojrU1ElKW3U0hT6wwfGnGH30BOGWzaZvIz87i+lLF1BxdKFwnVV/mF7EMukwfeUScpNTjGxAqRpvtHxidqO2oXXG9Tl6P5RGBAfKeZV1H3JBeqCqyrRlSbH8v/zDNRS8WdaXqHI/uaMJ/qk0UnNZNG9ZhRmPhL/60Z1SG9ZQ8iDoCeKT+5qwe1M1Jkl749BheIPGiuXqBU6cPI74nn3wRa1T8NKY9D3wJxLM7gQcg/VUy6QPLGQyhmhLC2tr5SISjdzQI6zY2ABp3QbnAAjRfC+imruVe3/Z+pRz4/qy2Wop3085/egCEHuedwGIPfs53vtlByDEk08/pHpFvPmpKVCai1lBQdrg04mnmY2hk84rig22g0TgtC4nN/KTZz5EdMvW0lz0gQ1NjWLkfj/CW4wLlbXWZiQMKYvoJY8ec0TUzkmbv4ixpi5dQH56hkUj/Mmk0BLoeQ7W1HA3tboAZHQEqZ5uJPbu152PUpmUzFcyJW+g2rww5bdP9OBq7wAkin5IEioLYeypr0I0FsSWnfWIxYtaGu+c6cX5zgFWpE4pVzWJBL7w+iasWhFltNNMDJGeG5PEC3bTx2QjFWvNVrCopIgP5FooiizqRTJ5DqdvUGFiDFVr6yA1NDsGQNghAQmtOqRuz7sP9+/FyHJVVQxjYzOO+dG16+JboJx+dAGIPX+6AMSe/Rzv/bIDECO9DDKmUTqQkbEpT362466pjaFTzmObv5PHkdx/AN7wcyVx5fgErFiNymFjMTremkq54Aq6YfrAhmcn8LSzB5GtO3hDLPi70dqcTIkxvbAl2GHqwnnQZjC+Ywf8lWLRBYqaBNeuQ7DGWCRS74dSBLzKp/dxijgQU9WVy0IpR2oTT85k8AffuIKcN83AR3TGg8ZkArt31GPj5lr4fN5SF6Lp/dHFftwfnEDzmkq8vmM1ggEf+7ud5120YJz3eChBx8ytmyB64tAa/XoUAtsUOSIK8NC6dbzhNf9OqZieTAbJmkqgqcWxjWt+Zgb0HFUcOWZpXW4n8xYo58bV/GrcHlYtUE4/ugDEqleK/VwAYs9+jvd+2QEIr8bDiBLWEIA8foTZzk7Ed+5k2hiLeRmxSMnrMEpzMrPW3Pg4ZjvuIHngUKkbfWAj6SkM3exEdMcuM8OxtjxQqNQcMT34S9aBoncUxYtt28YtaJZvXTQdSheATExg9vYtQ/X1fDaLK197B8c99ZC8PhwLT2D7oXaETdAnE5B+58wDXOjqhzefR3RGgl/y4/Of2YL1DStMeTJLUZvubiT26Udt9AakKFO4sQmB6pWm5lQ3VqZdiaTByWKm4cZGhBsaLc1Nc/r8XsQTEXg2tjkHQKanQamXZiPDlm7C7cQsUM6Nq2vixbMvboUYAAAgAElEQVRAOf3oAhB7fnQBiD37Od77ZQEgVKhLp+fqHPT0QD9jEYpt3aZpu1IqiUk2q/TAAKg428zJtFPOYylM164YqmPbSUlRrlNLb4Q+sNHcLAYv30R0917Tt8Vofe/OBzXKQUTy501Pukw7UKodAU6iidZicdO6LdGUIr0fSl40gYn/vX8XuHEeXaubIXm8WDM8gKq16/HpH99f0t5Qr21ibA79vWNMRDCTy+N69wiGxqeZLoc/J6Hg9aJt2xp85pg5UVCahzF3DT5GfKd5QOzU86asy6LoqDcUBoELvYu+WTQ31YxENmiz2fEeW2LbCiQTiAW98DRvdgyAEDX57M0bSB6yF0Hlrd/9+3MLlHPj6tp58SxQTj+6AMSeH10AYs9+jvd+WQAIbWipLiO0di2jppXzwEUoSa2oFpNY21x3t6mTaaecJ3LaqxYPtDo3E3H0ehHZ+Jxulz6wMSmDR+cuIbb3gOmheSk+dHrsjcUYdfKrfhHVLSAxBjJRcUZRUUBdADI7g+nL2uk3Xf0T+PapLqTmJtDwpAtd9a2Ax4P60X7MBeMoVK1h6uMb1zyvTSKQ/7BnFL1dI4jFgpjN5XHl3lOkchkmIEhX3gfkQ0H81ud2oboibNrtvIMGowEZo9yKaoRWazPKiS5GSb1LxeHweVl6ld4lU3nTN0v5fonOR+0IoIbrViEsZeBtaXcOgFAU7M4tJA8eNrMct60NC5Rz42pjWW5XkxYopx9dAGLSGarmLgCxZz/He780AOTObcDnY7ngtCGKbt7C6HFFhO0ozSXa2sZytkUvou5N3b+P2NattlM3ROeU24lQ1VqN7KjXwk6H6+oRrHuuTE4f2Lg3h/6T5xBXpGaJ3gdtvFLdXbrpMqn7PShks6bV6UXnX07tJk6dgCcQZKfkodV8piQzwFPvh1KrLorqL96/PIAPb/ej4MkikM+g4el9dNW1MnPWjQ8gFYhgPLYCXimAo1vX4Y1dq5HLFHD3+mOMj85i3YYV6J/N4IPrfcgh8zwhVwLr86l9G3Bgi0U62ocPUJiZYe+92UskXUpkTGUtCaPBlorAUReAPGPSI79GNpmns6Zx6fmINTUhODcFb9tW5wAIS728y3SO3GtxLFDOjevi3IE7C1mgnH50AYi9Z8wFIPbs53jvlwWAyAw0wfp6xuBDQmqRTa3IPH7EqDBpE613sdSJhgZTYmCpB71I9fYiumULt9jXaaeJKl3bVaemdVM6T3TbNvgTzxmY6AObCAAP3z2OxOGjpm+PNFRIvyCxZ59m36Lw4VPEt5svcDe9mCXeYfzEB/DF4uwZDq3lFyobiTyqb1UXgKgYpcam0vjm8S70jY6XxP+C2TTWDT/EaNNu2mcjPHgPaX8AY4kiCxZR6SYQQGi2KCyYTwaR83kwlU4xFiv58kgexINRFjVpVkRNzLqFCVhmMpZAKxP1DAZZHYidS6k3JLIemciCfEtaIGYvmbAhsWUz/GNP4duy3TEAkh0bQ+peJ9Ofca/FsUA5N66LcwfuLC4AWdrPgAtAlph/ljIAoRxpPZpZtRnVtJe0gZ3t6ACouHUrFfDqF7UynYtVdfNO+Xluog1G6sEDWyJivDn0/s7SO7webtqGkQCjyNylzayCAUv+wCbDXjz43rtIHFmo5cEbmxED9D1EYvcezaYsQtJ175Xf/MgbTH9VJWPAEklJE6kPko2uC0CyWQY8qQD5Tv8k3vqwG6nMHAI5oskt9g7m8tgoTWHrm4dA0barZ25iaCqFqWic/d0rAYG0hFzAg7koIGkKCPqwoa4a/+ToBiSi5rQ71A+OSMRB930SiFbwnmn6u1IZXuSQgOqr6F0O1tZaityUyCh2bod3sB++9p3OARABKmYRm7htxC3gAhBxWy3lluX0oxsBsed5F4DYs5/jvZciACHq17mOu8iOjCJ5QJ9qVmkMrUJSYg8ioBDeuBHegP4Gh1FmVlQInTDLc871dCPd18dSt5TpSY47SGPAouBZkkvdKcqGpLdmvUJU+sBWxALofecHiB86Ao+vSIUqemU4Stt5qkG4dBHJI6+2FoicTkXF55ROSLVNvItX4K/sr/dDSRS7oyeO45x/Hc71DMOfyyAyW0QekscDH3xoWhlBVX6mVDdBRA/Dkyn0TAMFUIRDQjrkQYYkPDyqz74E+BHEGzvW48j2enjVf+fdpMbfWa2Sz2+pmJsimYV0ir3Ldq6ioOFe+KIxUI0YHaDE2vV1ctJ9D0E1aqSdokeSYbQe9p5cvoTkzp3w9PXAv223cwBk+CkoyqsXpbRjJ7evtgXKuXF1bb54FiinH10AYs+PLgCxZz/Hey81AMJoX+/ehi+RRG5sFPGdu4UUoKcuX7KkQ0AGtZKCQSeu6f5+lrstkpvvpONEWXuspJYp16m3maUPbGUyjPtvfRexA4cMwZ3WfVN6XOaxPmORrDGRPHgI3lBRhO5VvGQNFkorJJAnUqjMS28TASBPxmZx5i+/jWvx1QhkvSySkQ16kIp4sTKRxE+93owaX3ZejQABcuQLGK1ajW+d6MLw1Iyuy6qiEZZy1VCXcMytIrVeepPRQQKBbWIas3ONH/+A1Ux4w2FQGmFuZBixbdt1h2RR1IcPWHTLSrphic56x3ZI9zsR2LHXMQCSefqEHbDoRSnt2Mnt6wKQl/kZcAHI0vWuC0CWmG+WCgChNI70wwegU8EwCXOtXgOmwL11fv2BnvnsKDFbSd+gE1faZNhRMbb6KIgKp1lJLVOuSS8PXP7A9nz7bcT27tcVQ9S7P6rLyTw1rvGwmz5m1bZLqZ+cAkcF6FJOrChfTUebyeZx7s4QSPBvT2st6lZES7eo9UN5vXsY/3CmB2v6b2E4th6AD3MRD3J+P3ZuqMenDzUgFPBBnSanrHkoSBIej8xiLlWs/1BeoaAPa2pijkQ9lOOKRgW1/CvyPPKei5KA5mESZgwK0QLTdyf7ZAjeSNQSfTBjwyPF+vZ2SF13Edi1zzkAMjTE6ues0BrzbOX+3QUgL/Mz4AKQpetdF4AsMd8sBQBCGy06wZSoiJTYq+LFPPLJc2dYjYWI0J/oplzL/Cxfe3bWVCEoRU3oFN+OirHVR4GYb+K797BUD6NLLswPrbFGL5odGQExUiX2zi8Wlz+wFAGJbN8FX8x4Heo1Mm2R0RHEtuqfDjM17zXrWH682YsiKJT2I1Mxm+2/VNqTUvb0hfMINTYKP5+MjnZ8vJT6886ZXpzvHKCqcAS9IfyzH9+G2soIu8VcNg+vx4vJyTnkcwX0Dk7iu+fvA1IOtaNjmIomMBUPIBAI48cObMCO5mp4nqVLqZ8NkZqHctrVDpUuLyVQZN3E2ibXzXj8flAEIdPfh/gu7TonGpO+IfnJCcDrsxRpINpxAgmJzW3I372J4J4DzgEQ0lUZGkR8x06R23fbOGCBcm5cHVieO4SgBcrpRzcFS9AJOs1cAGLPfo73XgoAhE7qPYEAY7ChH2/5mrpwHuGNzYYF5HJbOyfmIhtiteFl3ZFwU5NQcbBTjjOj3G5XT4MK+anQPrFnvthgCYC8/QOEt7TPY8gSuU/1Jlmrj521k28ohc8q8BK5h8Vok5+ZwfSVy0zMjldPIK9HWc+QzuTxe1+9iAzS7M/EOLWmagV+7ce2MPBx+cwDeOBBOp1DNpvHrd5RZApZ1rZybghPqqtRVbOqmHL1DLTI86iJBERqHsppMzvRPj2gbWa9auFPkTHpGad+FN1K7DWv4C5/t+ItLcjfvobg3kPOARCBKKUZ+7ht+RYo58aVP7vbwikLlNOPLgCx5yUXgNizn+O9XzQAoR/gqXNnkaDcaVW+v5kaBiUDjVkjySeJZtINaPNAJ6e0OQw36Ksdm10Lr71coF1xlM8+xWpbAgGh4mWtefVOhuUPbO9330WoeRPLYTdzieTcF2sK8pb0ESjy44snDFWozaz3RbWVFclDjU3cegJ5jXNd91j0h+pFSGn8m6fuzqe9Lfjw5o5GrJSAyfEU3vzUZszMpPD197pwZ2CIqZLT1fjkAep27cJH32hHwO9dYAL2zjwaQHzXbvY3KyDeSbuyiNnadZYosc0U7uutWY5WVRwrvpc8sU1qQ88piXzmp6eQ3G9eb0OO3MabNyJ7/RJC+19zDIC8aH86+Wwsl7HKuXFdLjZ4GdZZTj+6AMTeE+ICEHv2c7z3iwYgdBqeHR7WDPXT6W9wzVqhNBzRtCQtA5ZyqU2cQhJzFq07vH695Q2+FWeyjU1Hh5BAmJXaFuWaWD2BRhqG/IF98IP3EVjfxFh8zFwi6TpsAzQyYljEqzcnUTITAIls4LNGmVn3YrelqAepURP7lVHRvnJdymLsv323k4EKeJ5x5z5rGEkHsHNlEgdea0TrljqcuPgQf/fBHUjeYs0GRUoO5kbw0c8d040+qp8NJo75ZAjx7S8mZcdODViRuvgqox22esnRqoojRV0c2XdGSuI0py8aZd+R5CHziuPs/S5IiG1oRPbaRRYByRfxo+1LJEppexJ3gHkWKOfG1TX14lmgnH50AYg9P7oAxJ79HO/9ogEIMToFamtLdJ7KGyymVRiLCMrtlQw0Zo3ENgu3b5naBFDOORXikjgc1YEs1qU+eTaa1y69qJ4gYAmA/OgE/KvXmD51JnrPwtycYc1NMYWl21JqCj1TVEdkpEK9WP6yM498ih5p2miom6Kco1j3U4XCyjr8f1+9hKznefqV5JHgKUiITwLxRBRf+uV9CEVC+HdfOY3p3HPWqpgvil9uyKKqrUUXXKpZnqxEEe3YRt3XTg2YOnphZV2MsvrGDSQPv8a6i4AaYu4jfaL0wIAl8COz90Ub1iN75TyCuw8gj4XRKiv3IxKltDKu20ffAuXcuLp2XzwLlNOPLgCx50cXgNizn+O9XyQAIZ0O0qpIEN1qcKFOh2hhaYmB5tBhzXF4RpP59CuOHOM1Lf2dTtnzU5NMwHAxN7psYzBprC8gL9LuJoKdgo6NLdAokD+wD98/Bd/KWkOVeS2DUmE7Fe1SzY/eVTxRvgQzPpHHoo0dARCj8YUd/QIbypE5YoVjbEcCEboiRXM9bk/68e3THaX0K28+CMmTQ2Q2D19ewkzcjzd2NmF8JourPX0oPFMY9BT8+MKxVjSM9RrSWqufDb16ocUyH6sB27rVdD0SrU+mO644eswycYE6jUvkm0I1bsHVqxnRg5XnnOkXJSsQXb8WmUtnEdi1HwWPOU0ePf+IRCkXy7evyjzl3Li+KjZcCvdZTj+6AMSeh10AYs9+jvd+kQCENsjZsRHdtA1Rak0zhdlaBlQXkIoYmaIzxJwVWLnSUp2CyBxabWS9hcimTdwh7NKL6gEY+QPbd+IMPMkq08XeIvdQ0gJ5RmvKvVlFA0rHIWYuYlRbzpe8qad6jtmOu0Jpd3Iq0lcvD6PzMaVfMfVAtNTXYmp4BjNPpzAbB1Mo90lBkIZktpBh8MMjedG+bhW+8EYzZij6WL+aRSC1LvWzYSWN0UnfTJw6yepRzDKy0RrUFLpW1qWmJabDlclzZ1H5+hu6wxHLX7hxA2MANGqnN8D09asI1q5CZHU9MhfPMB2Qgi9gZfkL+ohEKR2ZyB2kZIFyblxdMy+eBcrpRxeA2POjC0Ds2c/x3i8SgLDC0bp6ttHRukTFxawACOV8ViIoVJ8iZbPwVVYu6kk7s0k0KsS8ZZdeVI+euARAPjwPTyQG0qkwc7HcdYArrEe0ptFtYjowyvkpHccXixuqUJtZ74tqK/sv3NyM2Zs3kDxUTO8xumhT62lqwe9/tws577P0q4IPn93fjOHuUVzpG8VMnJTKi9jE7/Mily9AkoBkMIbf/Nx2RMMBUIQvWFOj+26qnw2Romve2u38ffzEB0juP2Bak0aec+LEccT37WeK81YutQBkKapy5CgTkdS6iDiDQPLMjeuwEn2RSToidauQPv8hAtv3oOBfGEm2cj9KXRcr/d0+5i1Qzo2r+dW4PaxaoJx+dAGIVa8U+7kAxJ79HO/9ogBIZnoGU+fPI3FIX0lblMWpkJrD5PlzqDymf9rIM9zEyeOI79nL1daQx6E0H9q1sZP2ts284R37Ozv1rKnV3RgqJxKhAjVamN4mRP7A9p+9BMkXQLixydT9zd27B/i83NoZ2mCF1q83XWMyefZ0EYAYqFCbWvALaiwXelOKHwFeucDZaDkUCehOrsd3rvSX0q+CUhCfalmNbCqLVDKE9288YH9TAhAUAvjZN9rQ1lBkNGPpj1XVutEt9myk04i2trH2IkXX5TKjlQME9VrssOjRWGrdj+cRvNcYE50mACHQs3sP6DmnAnglBbmIreS6l/DKahYB8W3ZASkYFunKbWOHhY47uNtA0wLl3Li6Jl88C5TTjy4AsedHF4DYs5/jvV8UAJm531sUTDPYJCopRY1uXM1AY8VIZnVEKNWFNgxEHbyYqT5TF88j3LRRiHmK7CuauqNls7meHiCfW5BiJn9gB85fRb4gcSMZ6rHl4lkecJFz3EPr1plyKUVOvLHYshdRkwu9Kd1OBGDLG/G3p1egc2T8efpVsgrrwgFs37sWyRURfOWd2xgYG2PsWBQBId3GHQ2r8ZPHnrOG8dIf1c+GTBksF2GbcpjNxnZTMGl6M6KnWstVs4JJkgSKqiSpvk1FL079S6Dp4CFMnj2j284QbH54ij3jocokMpfPwdfSDin8XOnejlntMujZmftV7VvOjeuratMXcd/l9KMLQOx5dFkDkJaWlr/wer2/dffu3Sl7Zlg6vV8UABk7dx4hotitq9M1ht4GWN3Bic1PUfRwIwIrxChlqb03EgY83kVN9WEntdt3wJdIcB8iu3bRS5WSP7CPLl1HLp01XQMjmlon04yK1LsojUGUzBSZMlKh5hpvCTSQqVAjm1pAAJmXpkOF/cPHT+BP+sPI+oppVr6sFzuTFdi8uRYt7cV6jifjc/jyP1xHFmkGQOKBGH7jM9sQCT0XAeWl+qmfDZGi63KZtJSCeez1klK72bns0PjSXFq00UZpXSXl9CNHMfHhSST2HTCV/sUAzsnjTD8kGI8ie+UCPM1tQCRm9tY127MopbeoJ+Nei2OBcm5cF+cO3FnIAuX0owtA7D1jyx2AjHo8HgIfv9zR0fGePVMsjd4vAoAMPxrG+JmzSBBrlU56AllHtBDSCSExM5ojtDZWZxBPAIU8Ylu3L4ozlaemWqeqC4DZ7CymL12AiGih1g3M3esEfP4FeholAHLlFrLTM6ZT0ERVzvVYuHjGpnoAXzSGxN59vKZL+u/pvoeMzpUACAFPXpoOFT7f+M4P8K3UCkjeAksRrJjx41BbHQ4cbYJPISjY92Qa713pRyIWwkd3r0EyOr92gBelKj4bvlIanRNpkFadkbf5nNO8Zt9/9Vq1lOAJWMR37GKMbOpLLlIn4cJJOlQwWUCvjPoEwkGmA+Jp3ATE+AcTInYWTX8VGcttI2aBcm5cxVbgtnLCAuX0owtA7HloWQOQDRs2rAoEAn8M4LMA/lM6nf7d3t7elD2TvNjeLwKAPLp6C5mxce7GXd6A8VKcsmNjSN3rRGL/AcvGFKX8lSegOgN/1QqWB08RicW42Kbl/FkGKDwe/qtktzhfbxMqf2AfX7+L9OiY6QgQL71HtiUr7L1/3xSQkEEaRaesqEsvhh9F55ABeKSlFRMnT3DTdCgV8ft/+TbORutZ+lVwDlgTiOAnP9uOyhULU3OMfih5dTrqZ8PusyZqE612IpobvPGp6D6wsgah1dqEGLz+WrS1RmmdyrRRShmkVFSRqKa8DuW3IBDwIXfjMqR1G+CJJ3lLFfo7pW56Q2GEGxuF2ruN7FugnBtX+6tzRxC1QDn96AIQUS9ot+PvmuyNvyi9N23a9HmPx/Mf6SDc6/X+wt27dy8uysRlmORFABBS0PavXss0NIwuEujKjY0u0KFQ91Ez0Fgxk+ipfAmAnPkQgZpadkId37nLypSm++QmJzF766awYKJIIazRIvTScOQP7OCtTqSGnpou9ma1HZWVLAXP6CpuLK+g4rWiurTIJZ8Me0NBGKlQi4z1otso9VJEWJrGh4bxnb/4R3TXNcKbJ8FBD/btXIvXFbUdynsyBCDEVCZJuho36mfDiToMq/Z2ogBeFBTrrVGLsIFoeKlIn5519aV8l63UnyhBF/kxf+sqCvXr4UkunMuKXXkpeFbGdPsYW6CcG1fX9otngXL60QUg9vz4UgAQMkFbW1uiUCj8nx6P59clSXrL4/HMKk3T0dHxK/ZMtTi9FxuAJALAwx8dR/zAIS7ri6iOhZqBxorleCe+6jEpvSK0eg0rpKf0icW4rIi92VGI19uUyR/Yobs9mO3rNw3ARKNN8qaWCpuNUvWUtpfpT4kggFKWlvOlLAQ2SueR7/HC+Q7cOHEOvbUNiE0DQcmH3/y1gwgpajtEAQiPhrX4bCRKFMxOaGlY9ZUTEVC7J/5a2jaMMGKDdl2ZkraYxFjDm1oQqCoykIlcyv4MgNy+jsKq1fBUrBDpzm1DBzKUOmaWYps7sNtA1wLl3Li6Zl88C5TTjy4AsefHlwaAbNq0qcbr9f4egF8AcFGSpHkApLOz8yP2TLU4vRcbgARGhzD26AnCbe3cG8wMDYFACC/CoGag4Q6s0YC34VoAQE6dQGh9A7JPnyKxZ6+VKU33YYWuoyPc1DXlwEygbad2HjpvATM3b8BfRUKD8yMVJQDS2YuZnvum718WUCMNGN4lsvGeB0CeCcB5fF5L6tK89Szm35WgWISl7a+/fhqzfV14kmhAaA5oaKvHFz7eYmnDo6cBIw+mFcWyA3bt2NWJCKgo457eOrUOMIiqO7xuPQI1NQu6Kdc8dekCo7IOVK8UNoPyMILex8Ldm8hVr4K3SoxEgzcR829FBUJrzTHQ8cZ1/65vgXJuXF27L54FyulHF4DY8+NLAUBaW1t/TZKkfw9gzuv1funu3btv2TPLi+u92AAkf/sa8ivr4F2x8EdZbQXa3NNGiLfBl+lK7eg+6Kl+63mGUmKINSvz+LGpGgU7njYLkmgukY2r3ppIIM1fvXJBXrz8gX3S3Yfpjk4k9u03dVvTV68gWF/PTcGjQdnmrKGR5eeLXFSQTAxldFlRlxaZw+k2+UIB717sx/2hSbStq8KxHatZjY+yzkLWfPBXap+ST85k8F//4l3EUuOY9tcjE/Tj859qR+t6/VN1ox9K3vug9WwUtXT2wRd1hgpW1M52BTdpHivvlnJ9WvVSxedcW01eebjCBFnXrjOld5MZfIzMkyHEt+9krDuFztvIVVTDWy32nvBsy9OB4fV3/27eAuXcuJpfjdvDqgXK6UcXgFj1SrHfsgYgzc3NzV6v98sej+cNSZL+KpPJ/E+9vb3j9kzyYnsvJgDxpOeQv3sDgR17kYeXe+PZ0RGkerqR2Gu8wdVioOEOrmqg/EHn9ZU5/qOtraCNmtkNOG98vb9bYaYp0gs3I7DCfGrG9LWrDCSoqZLlD+zT+wOYvHnTdK2FGcYhsyexlBtPwm508WhrrfrB6X5nbg3iexe7i+KABT8+c3AT9rTWQJmHr6aJHR6awvRUUemcrju9Y+i4fQ+hTB5TkSQKFRH8q5/dy2h29S5DAMKpvyo+G6ugjGKZjVY5ZUcz767enKKEF7rv5p3bTHsmvL6h1MRITZ4iu9nhYVY/pfeeGdlHCRDJj1LXHWTilfCtLFIt273sFuXbnf9V7F/OjeuraM8Xdc/l9KMLQOx5dVkDkNbWVkqzGpUk6dc7OzvfsWeKpdF7UQFIahaR3BwylTXI5QpcA7A8544OJA8cNGyrxUDDHVzVwEx9hZzvHt2yBameHu76zK5Fr72VU0mjNBDeuvSAQgmA9A1i4hIViZurtTCzJrOpMVTcO3P9GqgA30ztCM8W5fz7l//hFvrHR0pTrIwm8dv/ZAfm7tyGP5EECTEqT8nTqRzOneiBz+eF1+sBAeJLnU+A2Un4Cjk8rU5iR/NafO7oc2FBrfUb/VDy6q+0Tvcnz3yI6NZtbM2LeYmSVRhu6Cm9cWTENKGCPKYWUDYiW2CHJpOTiG1ph16k0Wi9yogNAyDdd5GJJOCr5ac1ivjGCigSGddto2+Bcm5cXbsvngXK6UcXgNjz43IHIH+azWZ/p6enZ8KeGZZO78UEIGZfTFHWJ7vpE+QNZVEnzztycXRs2zbMdXaYjgDwxtf7u9l0JBrHzkaCIgnhhoYF6U+yH4cHnmL87DmQloGZy4zom9noVlH9/Q4KqTSXttbMmsvVdjaVw+999SLy3kxpCoqC/MzrbVg/PcConkNr1szz4/3Opxh4MI4Db2wAUbDe6BnBN052YMX0Y3gLeQwn1+HXPrUN62oX6k8o78MQgAwNsvRCvforLRBphc3JCbvajV7QGkTrzfTWWwQR1YyYQr6MCrmVGkdmo3w0vrLmhPyI+51IBaPwr7JGI6y+L6P0MSd85o6x0AJmfx9dGy5NC5TTjy4AsefzZQ1A7N360uy9lAGIKA2rFgONWWub0RKQmZbiO3di9tYtdtK+GBfpBUS3mTthLhaSFzexZi89oCB/YEcGRzF66kPTqU5m0sLMRKbo/rKjo0h1d6EwN4f4vv2m1KXN2seJ9rfuj+JrJ+6w9KvSJQEN1Svx0+uyCNbUsDoCmTnMX1uPsx/0oG5tEhvbaln048tv38LA2ChWTg6xLNdY0xb86o9t4S7PEIA8fYJMf5+umnzx2ZhfOG3Gr9zFmWjgxAGE3UJ2LaBvxKyl/GaZpQAn0yj7kB89D7ow5w3CX29MbS1qVit1KaJju+20LVDOjatr88WzQDn96AIQe350AYg9+znee0kDEEGFY7NpOlpGNKPkLIuuJXbvATE6mdGpsOpAsyro8jxWNjdyXz16UPkDO/p0AiPHT3AVutX3zCuoVrbPT02B8tFF07yKgKUXJNSmp0Jt1a/GYG4AACAASURBVAfl6PfWh/dxqbsfkkeaN7ynEMAvNwKr25pYHY5MiTxciKPr7lMcONaEcCSA+48n8Wc/uAnJm8Oq8cfIecL4+I8fxeZGfs2P0Q9ldmQEpEOipyavBTassDk5YVMlXbHV8YqRs7uW0ym1NuxqtXjl2op/8yOyYcM8sgHR9SuprBkA6evBXMEH/xpnWKv0op+i63PbmbdAOTeu5lfj9rBqgXL60QUgVr1S7OcCEHv2c7z3UgYgJXXlY8bK33qK3WaMZUZIjakQnzuLxL59mL58aVHoXkvKx0eOwePlF/CXAEhnBzz+ANvomL30UmpKAGRkCiPvf2A61clMqk4hmwVFfgiAkLYH75IZkQhQRtu3wZ9c3HoE3vqUf6foxR984yrGUlPFj6PkKQER+vdD0gTe/PR+xo5EBemecBjXH0hIVIaxZUcx1eavf9iBjsdPqDPqRgcQTq7EL/3SR+H18D+1hgBkbAype51I7D+geUtaInsv6tRcuZk3Y39lWwK6lEZlNZqpBb6MgJGSYMCsBhGtm9VnrV7DiADIj96BXsxkJQTWPi+Ct2oL6mcmTdLOPG7f5xYo58bVtfPiWaCcfnQBiD0/8n8V7Y3v9jZpgSUNQLIZTJ4+jYojR+Hx+XTvzM4pvzyozGxFBe/ecNjQikT1On3pAmO/mjx/DpXH3jBpdfPNmdrz7VvCKujyDHZOh/UofJUf2JH33jed6mSWGtiMlomsCUOATU+F2rz1y9NjZCKFP/r7Kyh4s0UAUgjQ/0DyFNOxGp704zOffx01jWtAm+yRyQK6n3qw+1ADEhVhPBmfwx9/52qp/5rhAezZtxV7j2wTWrDRD2VuYpyBnuSBQ9oA5MxpRLe0M60I+TJDryy0QMFGbDMfiTC6ZquX/E5XHDVXzyTPx6KFzZvmsc0ZpYYpC9TZO1qQENm0SXj5SpFD8qPv8UNMz2URWN8kPIZRwxeVTufI4pfpIOXcuC5TkyzLZZfTjy4AsfdIuADEnv0c772UAQgxGdHmM3n4MLyBoO69Wyni1Bps4sNTiO/YyRSAja78zAw7gWQA5OwZVoRNug3lvEjtnVH+7t5jahplsaupjgD07DEPgBw/bjrViSIaRD/qSySElmTmNJaJNY6MoJBO6apQC026CI3O3xnCOxe6SoAjGYghmy9grjD3DID0Yt3Onfj4/7Ads133cOPuFEI1Ndh5oJhmo07fah4dxOe/cBSx1WJMSIYAZGoSszdvIHlIu75Jy4dGtLPlNKecnkZsYVavQibDNHOsUjdrRfWM2PmUtrJSw6IE8QyADPZhajqNYKP5SKeWzcykSVq1udtvvgXKuXF1bb14FiinH10AYs+P5d2l2VvbK9l7SQMQSQIJ/iUPHoI3FNIHIDevw79iPgONFWcW00paoSf2Jo9JBetE9Rrft68YoTlqLi3KytrSA/2gPPVY+1ZT3c2ySCkHnzh1AvHde+CLxubNqfzAjp46hejm+SfhvAWyiMau3fDF5o+r188M/bB8vxQB0WLw4q1tMf/+t+924s7AYDExVfJgd9MaxMIBnLrzAJKngMYn3RiraMSXfv4opu/14Matcex8cwuqa+PstPsPvn4ZGU9RC8QjefHJyDT2vrkPgWoxNWyjH0oeAYSWD41oZ8tpV2U9hNV5RA879MbXIogweveUFNdWaMSV7yb50f9kAJMTMwg2NVs1wbx+ZtIkHZnQHYSl0lVVxTA2NiNEU++abGlaoJx+dAGIPZ+7AMSe/RzvvZQBCN0sAZD4XmN1ZTtUs0qDihZeyvTAFAGhKIFofYId5xVZc/KIbGoxNQxPz8FoMGZ7DSYp5Qd27PSZBaknvAWaVcxmOfJeDyIb+ZsreTNH9UN6KtS89S3G30n9/N//zUXMSakigCj48PkjbWioS+APv3kZOU8GTUNdeFy5Dkf2tSM5PILZyTkc+tw+Fm17/3I/PrjZy4AKXUEphH/elMWKbVvhr6wUugVDAMIhgNB6L41oZ4UWZLGRU+//+IkPkNx/AN5wxPRKtABZ+tEj5EaKYoPqSxnVM3tIUCKkOHQY3mCQbVz9w48xMTKJ0EbxNC6jmzSbJmnaYG6HBRYo58bVNffiWaCcfnQBiD0/ugDEnv0c773kAciHJ7kpPmaUtY0MqKXurNVezo8nhXaRFDEnnGa1zkUuyqaIg5mrVBOjEX2aB0DOnTcdaTC70VOqPvPuIdXby9KvGAB5RmHL6/Mi/v5waApf+d4Nxl5Fl7cQxL/64h7EIwF860QPrvUOoGmoE/3V6xAOVWFXyIumWi82HNuFTDaP3//6FczkSRe1WLy+Z+NavOF5ZCq1zeiHUiZaqHxdu75p/PgHjDFKWS/lRC2GFV84VfxuR8ldC6zL9UiU1qm+iilObQwssrTB0RHEti4EKlr2UKeLkR8Do0MYHxpFaFOrFRMuXJ/JNElHJn3FBynnxvUVN+2i3n45/egCEHuudAGIPfs53nupAxCRkzin6D9Fa0lItHCus5NFB0RSxJxwmtVTXh6dqt7ajFJSlB/Y8YuXTEUajICN3lrM1L/IkSICIP6qKoTWOKOL4IQPlWO8f2UAH9y4X4pgrK6owm98plg8/nhkBn/y9nU0Dd3Cw5oG+NNhbAz5sGOdBF/bVtwfnMSpWw9L2iHeQgC/+dmdCF0/z40WKtdgCEBkAgiN9EL1Cbw8JhXKE1NZuMmZOgRRm5upETIa02rakR5FNj23eloqpBpPgIPqoIyAitZ687Mz89j3GAAZe4Lxx8MItbSJms2wnRniB0cmdAdxU7BekmfABSBL15EuAFlivlnyAITVZRRPCvUupxhbROl8s6MjSPV0gyIgxdN8PnOWXbdrseyIjCkrg+uxGekCkFxON71sHgC5fMVUpKG0WeMQCyjXlaOC6Bs3hChSZU0YKZNhZAKhdetFzLTobf7bO7fwcHSEzUv1G0e2NOBje58XUf/F9+8CV0+id+UGRGd88HrSiGdHMFBNTE/Sc+FCyYPW1bX4uTc3YeLkCW69lCgAMaKllv9GlLXeQKA0JGNzAoRS5Zw0uFMF00pmKTPr07OHEfhX1nAUo5T6oo/qtcgpoMlDh9mf6H0MTgxjtG8Q4Ta+AKXIvRXTJPcuqP8S6eu2sWaBcm5cra3I7WXFAuX0oxsBseKR531cAGLPfo73XuoARGRTYPXkUm1MUTrMompyLxJ79sJsPYNVB7INy649woXb8jxW9Q2MWIGUH9iJa9cZFWtorRgDkRm9FfkeSmvh0DFTewYiAwGWgkW5/OFG69SsVn3F6zeXzuH3vnqR1XkwAFLw4wuHNmF2cBr5fLGmY2wyhUd3OjERrYTk8SAfmsGK6RH01cy/H+r7y5/YivXVkaJeioCN5PUZ/VAaCV8WdOix53p6gHzOdJ0Sz168v4tESXlj0N+tpnKV7KGKFlGklJ5HOqBQXuoooFkVduUBiAxAQlOjGLnfj/AWcyQVenYxmyYpYl+3jbEFyrlxdW2/eBYopx9dAGLPjy4AsWc/x3sveQBy6SK3xoDSGaJbt8GfsCc6J0qHqUytYHnjO8UZnaw40MqmvQRA5uYwfeE8owo2cxnVACg/sJM3b8EbjSK8XkwATW/zarQ2Myrwch0CRUBkpWkz970Ybe/0juLvjt8pRTGCUhAfbaiFz+dFTV2RAlrK5XH+u6fQHalGLuhBsDCLlRNDeFj7PL2Jaj/WVa/Ar356C6R0GhQJMKNJw/uh1NuE6gmEyvU3FLFczMtO7YZynVZphPXeFabdc+cWkgeLkQr5Ur/P2dFRpLq7GK23yJUZGgKRS8R37mLNyY+hmTEMdz1EpF1MA8bwfRNkHxRZq9tG3AK891F8JLfli7RAOf3oAhB7nnUBiD37Od57qQOQorjZaqb4q3c5la8sSoep3ACY1bSw4sCi7og1xXWr+gZ5A+AyD4DcvmNKab20eTVJXazHyKW2p6wJUcikAUlCpNkZViArftPr886ZXpy/11dUPZeAxlASzVVR7DnUgFiiSDdNQG3wveM47l2HwfE5hNIzqB7pw6PVzzf3dSti+PTBRlTEguDR5mqthfdDqUfDTCrzWgKcou+Pk7aksUSfDd68ojVg6nFYTcali1CLGBZ9cpWx5Ckv9TvAE31Uz6cuWic/hmcn8LSjB5FtO3i3yf27Xo0Pt6PbwJYFeO+jrcHdzotmgXL60QUg9tzoAhB79nO895IHINevIlhTy0CILgDRoYs1ayxRtiVWNPpkEPHtO5l4WbR9K/xJe9EXo7WyE9Kue0jsP2D2lmBV30AWW6SUHvWl/MBOdXSa2ujz2JV0fSzAhkZ9Z27egL9qBaRsBgS+oi3OsAKZNrxBhz/8xlWMzE2yFv6sB63hOA4fasC6phWlXuooAy+Vjp22374FuS5AZL28H0o9IUp1EbQ8l1WtGpG16rUxEx3jzWOVxUsPaOjZSa26zmqcDEQf1etmQG92FtG2zcVniABIagpPb3cisr0YFbFz6dW02BnT7cu3AO995I/gtlgKFiinH10AYs/DLgCxZz/Hey91ACJvKENr1mjeuxVWJT0jitJhKvn9mXhhWxv8FWLaC1YcaJYlRz2HlXxuow2v8gM73dVtaqNvFFkxso0o0JPTaArZ7LxNmhW7l6PP2FQaf/ityyh4swy4JSa8ONC+Gkc/soHpe8iX2k56m1m5vdk0HnnjaiR8pmdzvWiLke5FOWxJY9pJT1SvSSYwENGbUfZVF4XLf9MD2+p3i9nz6hVWvyNysVo1RXSP3sdIZgZD128junOPyBCGbejdYfVErx1hrGbutTgWKOfGdXHuwJ1F5Ltqx0ouALFjvaLmr3stIQsseQBy+xb8iYQum5GTp3WZwccgRpr4duM0hvTAAKjAlFTJGTvVphYEqqrK5lW7qS1WcuSNTtTnAZCe+yjMzCC6WYx9h7eR1jOiKNORnLJHERC6B7PK8WVz4rOBL3U8wVvn7kHy5BGelRDP+fGrv7gXsXgx9Uq+1BEoXuQo+/QpUn0PkdgtvgHlbXgYuNZgoNM7sbcLlK3Y3mpKn9Zcqfs9oM232aiZXrG5bnH6xDgo2iIz05kF5Wq2PvJjNDeLwSs3Ed2114oZ5/WxmrZpe+JXfADe+/iKm2fZ3H45/egCEHuPgQtA7NnP8d5LHYDw0iKsFDXrGVFd3KnXTpmqxTQINmxAYEW1476RByR9Bfh8iGzYaGmOybOnEd3cztiqRC+2qeroYGJz6kv5gZ150Ifc2ChiW8WKX63UKtD8oloPU5cvIbxuPauhyI2MaKpQi9qgHO2+9n4XbvY9gj8nIToNrG1aiZ/5ifYFU6lPyfU2s3JHK5t/3g+lHr21Xs2CVdFLO3Y2u3k3mssq0FezUslz6NLzKmi8qa1ZEKWuVWEApJDC4wtXEdsjVshuZAc9kgE7fnL78i3Aex/5I7gtloIFyulHF4DY87ALQOzZz/HeSx2AFDfffkQ2aIub8U6GzRiMTpHT/Q8Z3a3oRmVKgKXLzBq02rINR2WlZVE9KzopRik9yg/sbP8AMk+GWD2MyGU2310eU5QiVQYqUjaLzNAgtFSoRdZZjjaFgoTf+7uLmMnNIjEpoeDx4uMf24xdLTULplMzKD2v5ZmvvSF3ZFE5E0CQ+vF+KPWebb0T/+zwU6QePGD01It1WQW0WusTTcFU92XRp4cL71svPVQtUGg25akoSroKwbp6thTyYwwZPDpzEbF9Cw8MzPpCj2TA7Dhue3MW4L2P5kZzW78oC5TTjy4AsedVF4DYs5/jvZc8AOGIm6kLOu0YSFQ1PPWgFwR8KD1FdGNsZ110qh9at44V41u55KhAoGbhRldvPCNtgnkA5NGgORE1HWpS3n2JKsHLqVq0qdNToebNVY6/T89l8a2T3eh+PIzwXB6BrISZeBC/88W9SMaCCwGISkOCV+tk5fSe90M5feUygmvWIlg7/7nTO/G3Uodi19Z69RdWxiXAmnn8uERvKzqGUeRUi6GrmOr5HLSbJYpQA0MGQDw5DHx4DvH9h0SXrdvOyW+q7cW8QgPw3sdXyBTL+lbL6UcXgNh7NFwAYs9+jvde6gCEl5ft5AlodmwMqXudXLYp5ZpEaILtOo0VA28xl0KlnFN0867soz6lVf5N+YGdG3oKskdi7z6h2ywqs9/VTO0yGmDm5nX4V1QjtFqbjEDuK6ebUfqLmXUJLd5io55Hk/jWiXuYTs0gMifBl5UwF/VgZU0VvvTZ7Zqjam3yjUQvrYgA8n4o9Z4bvUiHVd9aNCvrpheNsTImG4tqM1S6HbyxSJMj8/SpZu2YVv2VFlvY+PEP2DvhDYd506FYm9MKf2Wx7oz8GPfl0X/8NOIHX+P25zUwYsDj9XX/bt0CvPfR+shuz8W0QDn96AIQe550AYg9+znee8kDEIo2zM2VKCfVBnDyBFSUj3+upxsoFJjGxDTRBNc+T4dw2kGMZvTUCaamLLI50ZrfSgqX0amu8gObGh7RVHvWs4MoyFP3l/U9KBJkdMm6LAUCIAJg0ml/KcejlKsPrg7g5I0+eHIZBj7omo144AmE8Asf24Kmem36Zq1Nvh4tLo05d+8e4PXADIMT74dy5sZ1+KtXIrR6PgW2Hjh18l0U9YtZFXGjceldmyS65z174YvGRJcAo/Q3LSYxrWiVEbhUL0T9HJAfEwEJfe+dRPzQfM0R4ZtQNKT6I2KTU+uXWBnL7SNuAd77KD6S2/JFWqCcfnQBiD3PugDEnv0c773UAQhPm8PRE1BBPn4lXWfxZH7hJs0pR5ktUNWalxXym1ArpzHUaSLKcecBkNFxzN66Kaw/IZrmpr4PHhmB3F4Wz5OyOU0Vaqf8whtnYiaDbxzvwsMnowhl8gimJOQCHqQiXiSiMXz+WDMa6/S1Y7QKuo3IBETto+fHXK6w4Jb0gKteqpKeHgbPVnb+7nThO228A9XVpuqt0n0PkZuaQmzLQjIBLSYxraiuKFNdKRVPES1hACTkwcMfvI/Ea8fsmJP1fRFA0vaiX4IByrlxfQnMs2xuoZx+dAGIvcfABSD27Od47yUPQB4NIDc6gthW8VQVq0YSTedSFsZbiS6YWR8r2r5xA8nD1lMreIX8WusxKshVfmDTE1OgWgFRDQOrhcqi9yBrnhAAoRN8EbtRupaTegcdD8fw96e6MZeZRWRWgi8vIRX2IBvwo2XNSnzu6AbEwgHDx0CL1cqI8tmKijfvh3L2zm14YzGE1zfMW6teyhGrHbh8ERVH7G+CRd8RI6AsOoayHTvwmBjT/d5ojclqwnSitFMXzyO8YeM8ljwtvRFRnRst3RPyYzLsxYPvvYvEkdet3Pa8PqKRYNsTuQPMswDvfXTNtTwsUE4/ugDE3jPgAhB79nO891IHILwNhtUNrZYhRYsvizz8IYQbGyGaGmTVccX760Vij1iNhdY8LGUsX0Bk0ybhZRipWis/sJnpGUyeP4fKY28IjW1UW2I0gFp8TautUhVbyucwffkSdzNMmy3aENqxr7yWXL6AH17sw9m7j+CjlKtZiSkfzUY98PhD+NjuRhxoXwWvQnBQ7561RP2mLl1AuLEJgeqVC7rJAozB+vnpUkY25f1QUq2ONxRmz/m8TbrOoYCTjHRCDxNgmP4kOoayXVEU8DKSh4/A4/UKDUH1N1JOWz+EFYyvb4CSAEL5/ZAnENW5kRmqKo6+XhKuZAAk6seDf/wh4oePCq9b7+acjCoLGdBtxCzAex9dMy0PC5TTjy4AsfcMuADEnv0c773kAcjQEDKPBhDftVvz3kW1O0QMJ7qBUqY0WUlvElmL3MYqNahyDqMTWt0NcN9D0GZMS2BwHgCZTYFObyuOHhPa+Fj1V6r3PldxXam7gHyeFetWvm4MjIhCda6rE8lD1iNMZMORiRRLuXo0No5QKo9gWkIu6MFc2IsV8QR+6vVmrKmJC7teCwDqsVLRoEZ/05uU90OpF3VK91OUYKHI44sQsKP0J73nVNjYqoaTZz4s6uZUVgoNwcAxoFl/o0VSQZElX5zEVZ/XM2lFSrQm10pzIz9WxIPoffv7rAjdbjTvRbCZCRn6JW/Eex9f8tt/aW6vnH50AYi9x8QFIPbs53jvpQ5AeBEOXoTEjMFEN1DKDYTeKbGZeY3a8ljARObR2zAazmuQVqL8wGbTWUycOonk4cPwBhbSyarnsCKYR2OI0MwqxfoIjIgAI1rPXGcHKo5ZT1250TOCt093I5NNsaiHtyAhFfEg6/ejfX0tfuK1JkRCfhFXldpobayNCA9EhRqVi+D9UOptrPV8oZUeZOqmLTRO9faikC5SYjt1sUOFUAjhJm3tIfU8RumBWpEpLUY3UT0hregE+bEyGcb9t76L2IFDQu+hka2s1mk5Zf9XdRze+/iq2mW53Xc5/egCEHtPgwtA7NnP8d5LHoCMjiLV3YXEPm2FXysCbHpGFN1AKes+aPNBJ46imxWzDmSboXBkQRqMmXGMaEL1xjECPvMASDYP0joQpRC1shZao1FKmHwPygiWngq1+n7p+aEULKph8fh8ZszK2t7qHcXXj3eUUq4KXkq58sLvD+FT+5uwu6WmlCpjZnCtqNXMzRvwV61AaM1CKuLJc2cYU5y/QuzUntbC+6HUo/bVi6iVUuAOHYY3yAejZuyh19ZKeiFvXgaSH1PU1ViQVB7HiABAq0asGBWpR3BVXWkponTeWgcyDIBURHD/O//IhAgJPNm5eIc+dsZ2++pbgPc+urZbHhYopx9dAGLvGXABiD37Od57qQOQorbAHSQPaAts8ViyzBistIHinOYrTzC1CkrNzMlrayW3Xz2mlboLo42d+gMrM0+JUJdaBYwEXLLDw4ht0yYjoHtW1vAo60GMNmR0mp+6fx/Jg4eENm7kD6Jf9kWjKEgS/uib1zA5MYHIjIRssMhyVZtM4qfe2IRVVVGee3X/rgUAi5G3OELr1i/ox6hZt++AL5EQnpP3Q6kXXTACp2b0LIQXatCQ0Q/7vIhs2OjEcGwMxjx37gxLy/MGjMkCqH2xDoxSqhb6RctnWtEOFt2qqQWvhkcr4iv7sefbbyO2dz87sLBzWfle2JnP7Vu0AO99dO20PCxQTj+6AMTeM+ACEHv2c7z3kgcgHGpcK/UNRkZkGyjOZpSBgtpaBOvqIVIcbcdpLDe8aSOjBrV66SlXG41nBKzUH1hZe0Nk82slHYzWKaJSrWYx01KhVt8zbaZTDx8isW+fkPYD0aVSfUBgxQrc7h3FVz+4g9hMDhT5mIsGsGdjPT55YD2CAfPRFOXatJ4ro3Q/kXtV3zvvh1Iv1cromTcDRq0+z8p+5UqBpJS2UEMDAwW8yygypbW+qQvnEW7ehEBVUUiQgRiD6JZyfq0DlxIA+ft/RHTXHgaO7VxW67TszOn2dQHIy/IM8L6rdu7TBSB2rMc4YdxrKVlgqQMQHjWuEzUSSn+IbOSUKRQ0P6X7RDa1lMWtovoARpNbodVkTD2BgGZq2QIAwpSZ24SKdq0WDVOxeKrvIRK79dNi1PoFIrYjoEVRGSI58Cf1dTnIvrIGQ6y9nQn0feWd2xgYGkZsRsJszIO62pX4Zz++xVLKldp/Wif7eqf9VlOfeD+UemlvRuDUSCyxHC+IVkG3E/MQyJLyeURbWrnDGUUptepDmJ7Llq3znjdRNj0tMgbZj/ff+h4i23awKJmdy2qdlp053b4uAHlZngHed9XOfboAxI71XABiy3qtra3vAHja0dHxSzRQa2trkyRJ/9Xj8VB+0oNCofAv79279wMzkyx5ADI3h+kL53WLhI0YaMzYQW4rsmlljENr17LT0XIUwcproQ2QmQJvvfu1IhBnlNeu/sCKMvjQ+tip+uysrrK93j2IRHGK6Xp3WT0KXYzNqH2bIbCg9rThim3bNk+rQWsdhWwWFO2JtrVhEDF85Xs3EZnNwFsAZmJ+fOH1Nmxtsh6pUs5ZpGoNMtpd+WLPekFaQKdcKr43WcfC+6HUogKmtRiBU1E9CyvvplYfrYJuJ8am540An/wsGY1pVL+hFS3S+saICklqgdASAHn7+4hs2WYqDU/rvqzWaTlh91d5DN77+CrbZjndezn96AIQe0+CGwGxaL+WlpafAfC3Ho/nz58BEE9LS8tVADcA/F8APufxeP63bDa7uaen56HoNEsdgJSUwI89571X3puoQJ2oPUTSiZQ53FY31CLrYTUNFy/YYmiiefIcEKe1Fj0ROmq7AIBcvsQoRUXSVUTodLXWowYXWm3U9KFaKtTqfnTyTNEVohumtDqji+xIYoCkp/LtuzPoeDCI2FQBczEP4skk/sXnd8LrdeYTp0XvrGc7WRtCVItFvkfeD6XeSbjRZlnE5iLPvmib6WtXWTF3sO55QbdoX6N2BP4nqa5m3374IsY1FVpaH/LYWj6TxTKVtRoE6jz+ACIbjJm3tN5L2Y+97/wQoVYiIqiwZYJinZa++Kutwd3OuhbgvY+u6ZaHBcrpRxeA2HsGnPl1treGZde7vb19RS6XuyZJ0mOPx3ObAEhra+ubkiS9FYlEVl27dm2GbqqlpeVHAE51dnb+W9GbXPIA5Nmpc8VrRzT57UVPDkXtIcImpKQ8dbIIXr1GRrnZ0SF0Cmt0f6L0wsoxjJS11R9YM5tAPWYlnn+YIvzNG4Z6HWr2HpZrv3G+CvUCAHLjOgi4EKgIrV7ILqVsn5+awtTlS0jXrsV/Of8UwVQG/qyE6YQfn9rbjIPtzm2CtVJy9GoyeGmKerbl/VBmnjxBZqB/gQaPETgt2ryZ1cgsxjV95RKCa8XAr9n10HNNAoK858IoAqj2mR7RhWgkVyviUwIg330XoeZN8Fc+ry0xe8/U3mqdlpW53D7PLcB7H11bLQ8LlNOPLgCx9wy4AMSC/VpbW/8UwCAAJnNMAKSlpeXfeDyeT3Z0dByTh2xpafm3lI7V0dHxdQ8z+AAAIABJREFUCdFpljoA4aUhGTEDidpA2U5EkVhZRCpCD2tlHdTHqWJQng211meU2qL+wJpJg7FatJ+fmWFie0SXq3epN8wi2gqUPpObnGCpTqRYbXRlx8Ywc/0aLk4GcWokh/hUAamwB/5oFL/zxd0I2Sw8nwcANYqS9Z41EgWcvXMLyYOHTT1qvB9KPTpWI3AqYnNTi+Q0tqJ/Ijo/gQcCnbH2rYZdjL4Z6s28UqtGqbQuCsy1BCdLAOT77yHYSIDbHvizWqclale3nbYFeO+ja7flYYFy+tEFIPaeAReAmLQfRToAfHl2dnZbNBr9zzIAaW1t/SNJkmo6OzspNYtdra2tXwLw2x0dHe2i0yx1AEL3YUTtqcWzL3rvWu1ENjTKNBOWJz86jNhWfXpYq+uhjUCONkBbhN2pO5VW2ofRuowKaxcAEEZDmpyn7Kw3tlXaYpE0I3XKkIi2wtSlC5CyWQRq67jpL0RPOn7tBr7RMY2xQCVCaQlTCR+ObG3Ex/Y+V7W26m9lPy376+XmW1Wu5v1Q6tXdGAFOK4rsduwlcmBgdXwCH0SPS3S8SrCgHs+o7kVdR6P3HIuy+WlF9WQ/PvjBBwisb0CgeqXVW2b9yplWamthL3ln3vv4kt/+S3N75fSjC0DsPSYuADFhv8bGxnAoFLrh8Xh+++7du99vbW39MxmAtLS0fMXj8fg7Ojp+UR6yra3tVyRJ+jcdHR3NotMMD09JTuWt8+b0+bxIJiOYnJxDPl/gNS/9fez4cST37oUvFlvQZ+raNQRZmgQLDtm+Ji9eQLihkY2pd02cPg3GhFRRgfTjxyxSkdi50/bc6gFmSePAA0SbN9kee/zkSSR27RJmyJm6UhRLC2nk1qv9OHP3LrzhECKKgmm9BRdz3f2mdRsojWzi9IeopFogr1dzeMpdz4wMI7F9B/u7yLMxcfYsPIEA/Ik4l/GINpNXfnQO50aymMNKpvuRi4Txv/z0HiRjzgrvadmfnrP0owEkdu2ed/8U+SGGsOSevaaeE977SBEfSgGsOFgs6pcvI7tOkcheXR1CdfWm1mK18fjpDxHfakw0YHVsxnomj29QVzF+6iTiO3fCH1+owZIefMxIDhI7d7FlULoc+bby6PxIHlFB56anEOccNmjdr+zHvvdOILh2veG3S8QWc733UUilEWtzTl1eZN5XvQ3vfXzV7bNc7r+cflyxIu7uoW08CK7xTBivpaXl//F4PI0dHR0/S91UAOQ/AahWR0AkSfpSZ2en8HF8oVCQPJ6l7ZYn772Pqr17EUgu/IEfOXcB0fVrEal3ZsMjMt6T9z5A1d7dCCSTmHv0CHP9A1ixf58Jz4o1Hb96DYHKCsQaG8U6GLR68sEJVO7YhqBCe8Bo0JGz5xBrbEBYoLh38s5dBgoSrXwq4olbt+ALhRFvNiccV8jl8OTd91D75kd0xeFmeh8gOz6Oyp1FADJ2+QpCK6sRXb9QIE6+9ycfHEewshLweFC5w/i1mejqwd/96ffwxBvHrG8FZit82LelET//yc22/aMeQMv+qaEnmOnpQfWh+YBgbuARew5X7DMHQHiLzoxPYPzqVdS+8fq8pqPnLyCydg0iGqCf2bymBtF1a3nDO/L3oXffY+9ewIQAo5mJx69dhz8WM3xeh374I1QfOgR/fOEBSWpwEPRcVh88wKbVs+nMg4fIjIygancRqOhdRnOJfLtE7n3qXhcI8Fe0bxFp7rZxLeBaYJEs4Fnqm7VFsoPVaZb2TtfqXZWpX0tLy32Px1MnSVL+2RShZ/9MA/i/PR7Pxzs6Ot6Qp29pafk/PB7PQTM1IMshAmJ0yjl56SLL3TeKWJhxj8gJrjKaUDx97kNyj74+hZn5lW2p4Dm0Zi2Cq1ZZHaLUb+L8OUSpOFhQ0NAoEqQ+4Znt7gbyOW4EgRYzc+c2vNEoIg3mQBWdRlMqXsWhw7qK5akHD0C1IrEtxY3TNKWGxRMIGwCQsRPHEapfjfzcbClyomfsy+9dxNXTlzHjr8NEPIF0NIjf/OxO1Fcv3HjaddjkhQsINzUhuPJ5Og2lWs123UPF/uJmVr5S/f0gwgKKBJi5eCd1dCI/ffUqKlV1N5OXLiFMrGcarGHTN28yPZjw2sUBIGMkHLr/AJepyoxdlG1ZhPPxI0P9mbEP3kcFiZeGwwumyY4Mg+o7kvv2s79lx0Yx29mJimdU0XIHiq5lnj5FYkcRPGtdVMA+fuI4Kg6/xiia5Uv2Y//x0/DX1tqOPrH3uZBHtEzaRlZ98bL3472PL/v9vyz3V04/uhEQe0+JC0BM2G/Lli0NmUwm8PyHxvf/0r/n8/nf9fl86yVJ+vu5ublVfX19c/T/t7S0vPuMBet/F51mOdSAGOV5i9RsiNqC2okUVCvVnvUKdc3MqdeWMXIRrSad0Nu8zLIFGTH7qHNcRfPX6RbskAZMnDyO+B5SLNdWelZrsjCGtHAEYZ0IkiwsGNmwEeRHEiPUu/KFAv72v38P6ZERZDwr8KQ6gaY1tfgfP1GeNBUtNik9QUmrOfu8XOX87AymL19CxZESzwUzj1GhuRFDls1HeEH3EqMUbf5D8tmMs7MUUinQ96fisDYLnx6rlbwKSmObu9eB5P5i1ErveyFCOFGiJD96bF4aouzHh8dPw1tZbTsdVZSRy1lLu6Px3kfXQsvDAuX0o1sDYu8ZcAGIDfspU7AA+FpbW69LknSjUCj8O5/P9xOSJP2vuVyu/WXSAWEbHqrLaNqgeXrvdBGqSFG7sqA7OzICUkNP7HU2BYs2x5MnTwjpEIg8UlRMG6xdhaBgbr6RXdUfWDNUxEYMSrz74Klsz/VQJCZfUqXnacSQgj2NSRog6Qe9SDw7pVavY3w6jW8e70b63k34skFIAB7X1uIXPtqO5jX2NBf0wedCdXkqip65cR3Jw6/N6ybKoKSei/dDqVcwbQROSdjRGwrrgj6ej838XfafHkW3mbGM2jIw2NSEwMqFdWGyOKXeGtQMZZmhQWQeP0b8WU1ICag8fcrqeBK79SOpeoBQ9mPfybPwJCpY1NTOVXxvfKbrtOzM6fZ1ldBflmeA9121c58uALFjPVcJ3Zb1VAAEzc3NzT6f7ysAKCejS5Kkf9nZ2UlaIMLXcoiAUCpSeN16xsmvvhgDzZZiQbgTF+8EVz41Tz47daUTztS9TiRUaTF211LS7jCpbq03rwiwUvadPHsa0c3adl0AQB4NIDcqJlw2Q/SyK1ZwtRW07oOnsq1m2OJR/sonylRAPHv7NpKHFtLY3nkwhrc+7MJceg6rRsYAyQ+fZwK55m340me3olwpuVr3qrcB1VLHFnn+eD+UeifuRuCUB/pE1iXaRm99ov1F2xkpv/PWUNRouQoCKHQRiYDWu1I8yOhGYm8xVUvrYmDm9q0Fz2kJgJw6B080IcRGZ3TvRvcrajO3nXkL8N5H8yO6PV6EBcrpRxeA2POoGwGxZz/Hey8HAFKkU61nisfqi3cqbtZgvBNcdcqFiEK32TVQe6vicnpzaSlrG62LFOGj27Yxel31pf7A6p3qao1vRO/LsxMv2qXeOFFkik6ooy2tmkMzpflLFxDfs3dBqlEuX8APL/ThbMcj+HIZRGclxFOTyAazSGTn8JGf/ywa6haSIvDuQfTvWs81Swc6dxYVxASmII6wKsbJ+6HUizAYiXXyQJ/o/Yu0I2X66QvnmT3KebHUvtQcom0LyQZ4a1CDRr1oIRMd7XyeqqV1P3q0yLIf+09fgBSKcPVseLay+jzxxnX/bmwB3vvo2m95WKCcfnQBiL1nwAUg9uzneO9lAUCuF6l2g/ULqXaV9RhOGId3gqvelOUmJzF766bm6bmd9YiciJoZn3dfC4HdScR3aNP2qj+wWYH0EXl8M6rp6jXx6n3UGydebYSc0kQAZPLsGVQ8y60fm0rjq+/fw+OxMYRSBQTTEqPcrZ16AG91Hd5cF0DDxz5ixvym22o91yURO1VUzGpaG++HUk/AcvLMh4gS9a0GOOWBPtOGMOjgNEjXm0pPf4Xa8wQyZdBY+XqRK0RdpyTPqRfdUK5Jr06kBEDOXILkD9pOf+NFgZ30oTvWcwvw3kfXVsvDAuX0owtA7D0DLgCxZz/Hey8HAGKUPmQkUmjFWLwCTPUmUC8v38rcyj7EisMKo59pWtgdT10fwRvPqOB7AQAZHUWqu0u3hkI5l4g4oN7aeIX0MypBRLUKtXpcOXpFtR8TJ08gefgw4A/gj//+BkbGxxGZleAtSEhFPMj6/ThaGMLBjx1A/kGPoSI7z7Yif9d6rvUAgdWoEu+HUp1uKK974kN9cGqGkEDEDkZtygX+1XMaHQbkpiYxe+PGgroceQy18rlehEidqqV133rpW7IfB85dRh5Uu7HBlmnV75GtwdzOwhbgvY/CA7kNX6gFyulHF4DYc60LQOzZz/HeywGA6J3IldKhiJpVQUtpx0i8gt5SzvezNJhyncLqnZRavTezG0MjYKf+wOqxM2mtlQcijO6PFz1h9SVVKxBas4YNo7dhk+dQEgjIgGs0A/zJ168gnMqi4AVmo14E/GF86kATNgzeQmzbDsxcvwb5RNuqP4z66bE7lQDBgYPzKF+t2lTkh3LixPEFRAhGUcd030OWPkiF/eW+RNKWnFiD0TvOe/bliCkRB3gDAZZmRf8kUg3lpVffo2yjF9ErAZDzV5EvSIhsFNah1TSP2XoxJ2zsjuEWob8sz4DId9XqvboAxKrliv1cAGLPfo73XhYARIdZpxwsOLyNv5oZSK4jqDjqbB6604Wg6QHSihhHrH0r9xni0ZuqP7BmokBGFK68hfEoktWRAFKgpvqU+A5tlXrScMkM9DP6XUorCra14/SVYVy5+QiZoIS5KBD1RfErn25HTTKEiVMnkdi3D1MXLrAIiMfn4y3Z0t+Nnmutzb8RK5XRAkR+KLWiHUoWOPX4Zp4zS8ZRdCoXA516XXqpb9SOtFlSXfd0SSjUUSS9wxR1qpaWbfSiJyUAcvE68pkcIps22TIt7z2zNbjbWdcCIu+ja76lb4Fy+tEFIPb87wIQe/ZzvPdyACB69Qs8BhorxmKnjDMzuie4asChR1VqZW5lH6Jb9VcTp3/xNN/ulRl8jMyTIcS3a2/GleOrT23Vcy8AIDp6EVprtrpZprF4qSGU3uWpWYXO2QCCAR82RjLIPRpAfJc2takyt3/wxBncT1Xg4XAa92ankQkR2S6wsbYWv/iJNpSetdeOMOpeYsxyKupmZsNL5ACxbdvhUyh/GxWF2wUg6noPHjg1qpew+wyr+2eePkGmv0/Xv07OpxUJYgBkZBip3vtI7NGn4Vb21YsulFjvVBofyntghxJBqvFomndr8vv46PINZOfSQoKgRraxmtLnpL1fxbHKuXF9Fe35ou65nH50AYg9r7oAxJ79HO+9LABIdxcgSYg0zz/ZK8fmn1c3oE7HUKdkOeWgqUsX2EYjUP1cCdvO2GY2a0YnvrQG9QfWjA2mzp9DeFMLAlVVpm+Hx85D0ZXvdKdxj8lyerAhDHxiNVB3dCG9LrUgX2fHxzGRWIu7p24jXlOJB54Abj4eZLFaj+TBodYGfPLA+nnFxkYRANM3pdHByJ5aYMMqE5zID6V6Pr06FPk2zDCi2bUVL8Jld3xlfz1RUJH3ShlF0tPjEYnm6pENlADIlVvITs9osnWZsQUv1dHMWG5bcQuIvI/io7ktX5QFyulHF4DY86oLQOzZz/HeywGA0AkjnRCq6VR5DDRWjMWrG1CnG/E26/Ia6PQyWFsLf6XYxtuIBtfKfelReGqNxYssLQAg2SxovSKCcEQjG21ts6TuzmPy6vvgFP6mYxYz0TC7rWhqFmumRrH7Jz+J9qYVC251qrsH9zrHMOWJoxqTaN62Gl+5MIKhqXHW1iP58JkDm7CntRbKXH+jImwrvlH3MaJ21VJI1zud561F5IdSDRh5wnsiG3LeukT/zntXRccRaTd95TKCq9cguGrVvOYiIEip6aJXr8OLLNGkRWCwUExU9uPja3eQmZi0XX9jhyhCxJZuG20LiLyPru2WvgXK6UcXgNjzvwtA7NnP8d7LAoBQWtTs7IKTPTO1B6KG46UqqZl3RE4u2ebhyiWmQq5FJaxem8hmRPR+5Ha8YlnleLzIkvoDa4YMwEjgkHdPPI2Jm2/9EG8PSpiNFAFIODOLurHHeFDThn2b6vGJ/esR8HvZ3ybG5nDj+G3kcwW0H92MyMgDIBbHf/hgEDlvughACn786ie3Yf2qBJT1BjxBRN598P5uBKzVNTRmbK+eV+SHUk19zAOnzE69PYYpSbz7F/07aWrkp6dsb7hF5ium/5HI3/p5zRkIGhlhaXF6lxJ0G6UgUmQtse8AfJGI5lB69VMlAHL9LtKjY0J1Xkb3bJXUQMSObht9C4i8j679lr4FyulHF4DY878LQOzZz/HeywGA6KVFmdlUixpOj2u/tJEfHweJFSYPHGT/l1qYUG8e2siRmGJozVruUmQAQIXtTiltm2Hr4jHyaH1geZsn+aa1ahi4BnnWQC8SJvc//Tdv4/hsEHOhIgAJZVNYPdKH+3Wb4JG8WJWswOdf34jU6Bx6u0YQyU6hZWMSlZs3MXai8bSEP7k8BsmbZf29hSB+92f2IhLys2L2zOPHiO/cBTtpZCL3agSs1afTohE4rXlFfihpMxpaux6Bmho2BK9YOjs2VizK3qev6C1iA5E2PMIIkTFE28x13QM8ngUMU7yUTRpfCToYGGlrg7+icsHURHJAhAi+WExzWUUg07ogiir7cfBmJ1JPnyK2VR8MidyvHaIIkfHdNtoWEHkfXdstfQuU048uALHnfxeA2LOf472XBQChU8bRkQU/rGyzc69Tl4HGirF4onrqOfW0EtRzk4o3RUDC6xu4y2LA6s5tJA9q1y5wB9BoQGk9UxfOofJYURDN6OKBFa0PrGhakmg7rfXxCAK+9+Vv4JI/iXQgzOo3Atkc1o10o7u+hQ3nyQOJOR+21Fdi85Za1OafwheNItzQCNJJ6ekfw9fupyF586x9ZSiB//mLu9i/K9mdWH1OQyMCK4ubcqcvJkp355am/9UFwrxoldHaRH4o1YCHx/pWjkMBvXsoatsUbLM+ifiP6IVzU1OIbWmf15z3TFJj5YbeCIDzwLneu1MCILfuYW6QiCZ2iNySbhsGmJo2IlBdbWsct7M5C4i8j+ZGdFu/CAuU048uALHnUReA2LOf472XAwDRy7NmDDT37yOxV5+BxqzBeNSeWn8XKUqmtB2KgKgZbLTWR3n0lF6S2K3N3mT2nqi9WhDNaAwmrnbzBpKHXtNspvWBFU1LsqNcz6N4/cbv/xXuVK5C1h+Cp+DDjtUrkL5yFnfqSBehgMSkxIDJuuZV+OlPtUHJSEQbyUvXHuIHYx5IngK775ZVq/DzH29l/67UUSl3jryRvoWaRYkHFm0DkOvXEKypKaUOsvmuXtEVYuQ9O1aeXV0Acu8e4PMismGjk8NqjsUio4xRbfd8AKJTn6ZspHxejAQ+jdjM9DRgaJ4SALnTjbn+ARals3OVO8JnZ20vc99yblxfZrsttXsrpx9dAGLP2y4AsWc/x3svCwDC9BoW0m2Wo+CVF1UhdfLUgwdI7Nlb8oXIppqYioJ1dUIiYeWgMhVNFaOb4p1iawKQ82cZSQCvyN5qwTSty8gu6WweX/sPf477qxqQ8wdY/cZvfHIL8lfO4x9SqzA8MonITB7TSQ+S0SSLbCijCemBAbz3/k2cKURKDFivtTXg4/uLOf+s/gRg/itSJK9EaPVqx99HGtCIMECtI8HzlV0AohZ35NVd2QFEZo1JqZDeUBjhxkazXU23Z6Cwo6OUeikPIBKFkZ+zwKo6TJw8geTBQ/CGQgvWYLTxN6o1k9/HoY77mH3wwDYtsR2iCNOGdTuULFDOjatr5sWzQDn96AIQe350AYg9+zneezkAED2ufREGGrMG423otECPSFoRnXwG61YLpYvwTvrN3pPcXnTzz1OY1vrAitIGGyms8+7LqD6nb2gSH/z3r6Onrgl5nx/+QhD/+md3Y+bMaWTad+O/ffM6Apkcpio88EpB/M5P7YGv8yaCa9YydjIa+1vf+hC340XaY2LA+tyhFuzaVEyzUlIAsyhEsgKhdet4S7b0dy2QKw9U3HSHSpE0M+xm6sWI/FCqtVeM0sNofCMGL0vGMOhEYMwXjy8oDHd6HnZfs7OYvngBFcfmC47OURTGu7A2RLkGOWoVJADy4Sldtrhiwb829bZRXVgJgHT2YqaHNEmeH45YsYUdoggr87l9ihYQeR9dWy19C5TTjy4Ased/F4DYs5/jvZcFANFRG04/eoTcyLAhA41Zg/FSSLR0Dni523L6BEVAiIKWd4nklfPG0Pq7qF4Eb1Or9YFlNKXPNvN6a7PL7mW0Mb9ydxA3v/M2uus2ouD1oTZWgd/63DZ24hw/cBB/9GeXkZaymI17WHrWF49txvqRboSbNrBcdyre/Zs//wF6VxVBBUVQ/vmnt2NNTZz9tzL1iadHYsU3yj5KhXb1WOoNr50ooMgPJbtXqpN5VrukFwmQ12lGE8aundTRGbvjGfXX0z/REwdUjiUDpUDtKkyePcNAjBa5hBH7FEWeKJJCVNfqS/bjk66HmL53D4m99ggA1OKT5bSrO/ZzC4i8j669lr4FyulHF4DY878LQOzZz/HeywGA6EUlyhEp4KWQaNH08k4M5c0LnbRHN2/h+pDH9sQdQKeBqGK20UafhtYEIKpaAa0lPN/EvQZvIGD6NrIERLu7NBmWfnC6G0Mn30NX/SZI8GLrutX44keaQVGf2N59+PO/u4nB3BzSEU9JYPAwHpU0SR49eIzvf+2HuF9XTOchBqx//XP7EAr42H8X8/jrQafYRT0SX9lqD4wie+qUHx5ttJGRRX4o1RtsIx/QXHZYucw+EHqifmbHEW2vFelUp8RpjSWnigVqazB9+RIqjhzTnNJIANAoKlkCID19mL7TYZuUQ/SgQtRubjsxC4i8j2Ijua1epAXK6UcXgNjzrAtA7NnP8d7LAYDo5Z2XI1LAY/nREj/j5UzLm7LAypVCHP0ieeVWHgQjDQLleMUT+IU1N3IbrQ+sujhaE4DkcoYpKLx7MkqP++t3riN/8yy6Vrcxyt03tjXhI7vWgKhN0dyO7777AJ3paeQCEptmbWU1fqZ6nEXPfIkErt/sw5V3foju1VSwDlRHkvgXP7WztCSlHkbRP3lENhXZtZy+jCJ7aupZOyBc5IdSTT+rlw4p20CuVUgetgYyzdhSJOpmZjxeWy12KD11cuVYsoAmFfPP3LyuS+5gVFvE2Pkezq89U7+PT+8PYPLWLSQPHOLdiuHfeXTAtgZ3O+taQOR9dM239C1QTj+6AMSe/10AYs9+jvdeFgBkZga02ag4cnTe/bNIQTotlNYkajiezoHWhk9LnVo5nzymv6pKiCKTpdmUgd1HVGBMK81MeT9aH1iRk2BSsye2rIqjx+DxFgUBzVxGBdD/8a/PomLgJqPclVOsSP2c0kkmVjTi2q0xXJicgOQrUuz6CyH8duMcKvbtZ1S8753twcDx93CvfhPTe2itX4V/+tEiAxZdyuiRkhHLzPr/f/beA0iO7DwT/MpXdVV7NNBooGEaQDcw8N5jht47kaIoiRRXuyceudpQrNac0W3E7p1iT9KeFArdreGeREm8XVF0EsmhyCE5nOEMZgbe+24ADd8G7au7unzVxf8SWZ2VlZnvZWVmowvIF8EIDvrZ/8/Met97//99onWNQAXRwdItnXyTxkC4hkinyFgiP5QMbBUKiKxdx7rkMbRZDbMTmbdcRzTvyEyfRnXVFMhUVwINrQh1LNNtKgtoEm3zbN8NNOyRNITUxQjMGN10yX4cuTeI+EUCONbou42YuuyypdtPpQVE3kfXbgvfAk760QUg1vzvAhBr9rO9dS0AED2tAyduCnibZKLHpTwRpR6AWi1a7SS6VSGQ4m9sFKLIdIrdRzRkhcfCpQlA+nrhDQYNaYat5gfoCSQm0zn86X97Gx0Tt9FPooOFAH77E9uwuCkCup16UGxDIufFT24PI+fNMPd48j58sXUaq97/LpbU/c1XbyBz7ihrX/T4ceiFVXjfrrkkc+WpMHsG4lNCt1nVvLBqkKHsg9i6chPjiG7azP452d8P5HNV3caI/FCqwwF5Qp00JxFa6mrsom5DrFGR7m4u85odY1EfLB8mHClj3TIKm5LHlW0YaF2E1J1+XdpwIxCv9d2R+y8BkAdDmDp7XjNPxIwNJKKIvWytbpk/C4i8j/M3G3ekai3gpB9dAFKtV6R2LgCxZj/bW9cEAEmnpeRN1cm5njqxFSMZ0V1Sv1onzjzlYDqxpjrE2CPCUOMUu49ImBStUb3JVdtT6wOrpKnVs78V0TzqU+926v7wNP77y6ewdOoe7ixZi0AxhP/113fD7/My4HdlPIq2FW147eYwHk1NsOn58kV8JDiJnZ/9CDx+P/7suxfQ3H8ad9u6kPeG8elDPdiyRmLEUp/qO0F+oLSZ0Q2L+iRcDu+JdHWZfuxFfijVz7tIzokILbXpyWo0ENWesWMs9u7f6Uchm2V003Jht4rLOhmTml6RQ0WJujnz6GGFlojcziih3SgvTPbj6MPHmDx9WjfHRMQOosKqIn25dcxZQOR9NNejW/tpWMBJP7oAxJpHXQBizX62t64FAKIHCkQYaMwajKeXoY7Bp/55sehEXUpJzBTqU7+bz1DjFLuPKHuT0WkrrVfrA6u1OVPbnpdfw/OVnpji2d7H+NnRi1gSf4i7i9dgSX0TfvuTW1h34ydP4+JgEBv3rsbZexM40XcfRU8R/lwW+zOjeO+XPotsroA/+MZprHh8FQOtncj4YvjyR7diaWuU9aFOrBa5BeCtxejvRrZUM2SpWarMjCs+c5GzAAAgAElEQVTyQ6l+FrRyoNRj8ljhzMzRqK4I/bVdY1E/WmsXCQNLP3wA+gYEWlqQGRnRDcM0Cr00+lsJgAyMYvL4iQqqYDM24H3/zPTl1jVnAZH30VyPbu2nYQEn/egCEGsedQGINfvZ3romAEihIAl47T/AwnzkYmXzZWRII60KrZAXJUOSVr/EYDNz8SK84XCFkJlWfRYq1ba4pD5tl9NFc0t4yf2aAIRyERIJQ5YvHsMYb516LFqvnLyHi5euY1F8CPfburBlxTJ85iVJHfv+0TO4NerHwQ9vRN9AHN996waK3jyC2TTWTgzhV/7F5zEwNov/90cXsWK0D48b25HxN+H3Pr8HAb+Up6LWtpBYwu6ifudu3pSr+rucMyDnXSg7USeBi95qaU1E5IdSfRsmkvTOY4WryigajUR1bewaT8vvTDxw7ToGLvSKfGPmb2lBbnJSN3SP+b1Q1NQKMgrPkv04NjSO8bff0aX5FbED7wZYpA+3TnUWEHkfq+vZbTWfFnDSjy4AseZJF4BYs5/trWsBgNCiteKSRRhoqjEYS8LctQe+SGUMtNbmUCs5tXzTOAa61fAGA7oMOMr6EqDpQHDJkmqmr9tGNF9A65ZH2anWB1ZkY8pT0eYtVi885Os/vYGh+7fRMj2Gh4u68J6tXTiyVVIpv/azU5jIhHDwo1sxMZ3Gn/39ORS8WYQySSwbH8LHvvQreDAyg++904vlY7cxXt+KSMsy/M6n5xiw1Now2YkJpG72WaY71VuvEVBUjy2a11MtAFHnAxnlp8hjxE+dYGFK/qZmnkur/vt8JrvLk2TPweXLIIav0lpPHkfd+g3wNzbprkWmVSYSCiPCAKMwK2LP8rdoJ7uXAMjwBMbfertqkgdawHzSKFft/Ge0oZMb12fUZAtyWU760QUg1lzuAhBr9rO9da0AEK24cqMfZSuGMgrt0Mo74c2DmIOSvb1sSmomL6158nJKql2bKGMSD6hofWB5ies051w8jtmrVyyx9Ggx9PzxN8+iEB9EU2ICj1q68LkXN2DDKulE+uQPTiHSGMOWl14AAZg/+fZ5xDMziKRnsWTiMXZ86sMYmUzi7Wt30TF+D/FwIzrXrcfn3iOxPlFRb/rtWIeRD41CC9VK5KLMZlUDkOFhkG9j27azLkQYwBgpQ1cXAi2t1T6q3HZP46S+RKKgyEWjcLO6zZvhr2/QByAjj5F5+AC+xmZDwgCjm0ejME/5fRwfmcLYm0d1lda5RiUAopNvJ9LWrWPNAk5uXK3NzG1txgJO+tEFIGY8UVnXBSDW7Gd761oBIFpx5SIMNNUYzEgJmG0OAwGmoC0XXhgMnYCm7t1BMZ0Ris/m0fpWsyZqI3JLQfWMQoDo75oAhDaqA490E2ypnZGOh+ia1CJpiVQW/9e3ziCaGkVDcgoDzWvwO5/cjtbGMAqFAt749mmsXtOE1bulxOFv/+IWrjwYQDQ9jdbpcbTvO4zJRBp9Q8NoH3+EdDCKrXt34N07lpempFYbtxpKxlurUbiNNPaFEtORqLZLtQCE6U88uI/6HTslAELU15lMWSK2uu/pc2cRXrECRDvrVHkaG2V2A/fWm4xGl8IpqYhoZmTHxlgCO7slMaDXlnNFohs3VZhN+ias0QR1JQAyGsfYG2+i4cABeANzoapmfMCjITfTl1vXnAWc3Liam4lb24oFnPSjC0CseMZlwbJmPQda1wwAOXEMdRs2MipbufCSv6s1l5FiuBZFLo+1ipJXM4ODTL9BRANDVLHc7PpEGIwYAOHokGh9YHkCdQyATE6AAJyeDoLIetT5BXeH4virn15BQ3IEdekExlrWsPwNr8eD+GQSp39yCVs2t6Bto3SjcfzKEH5y7haiqUk0JSaRW70F6WweE6lpLJ4cRN4Twns+fBibuuZO7ymGn+L/Y1u2sj6ssnnx1pm4dpWdqIc652iA5TbqRH4rz4rID6W8ea7fJeW7iFBfOxVCqLSbOi+HZ1O7/s6Yt16Y+w6J5KHIN2i+hgZ4IxGEV67SnI5Rgr8R41cJgIzPYOz1X6Bh335GLV1NeVp2rWauz1obkffxWVvzs7geJ/3oAhBrT4x7A2LNfra3rhUAwpI913Uj0DwXV84YaFausv2kVWss2fBap9O8ZHg62cyOjyM3MSEUHuEUi5D6JF/vYeKxi2kCEIG8CLJB6vYtISYwvbmpfXPq+jB+dPomGhOjCGeS8K7ehC9/XNLIeHh3HDdP3cKeHa2IrpWS0h88nsFfvHKpBFgeN3WBtNEL3gwWTT2Gp+jDZ3/9A1jSUleagjrvQY+Ny66X0yikT62lYoUJSuSHUh1+JkJ9bSUvRdSGTt9C6T5/584yYEgkEaJ5KHLYnK+hURdY0nhyrkhs61z+kTwPKfRwF3x1EjObsij9OPr662jYU72Gh57Wjqhf3HrVW0Dkfay+d7flfFnAST+6AMSaF10AYs1+treuGQBCceWruxBonTuZdipUyUhYUOt0Wtqwh8oEypSOkmO7iUJV5HTSKR0FUQDAo+vV+sCK5EWI3JLwHnA17emPjt/FqZsP0JQYRTCTwdLtu/FLR6TwuKvnBzA7OIxN3bGSkncuX8Af/s1p1CUGEc4mMdy4ktUtenNomR5FOFvE//DPPsU0ROSizomZY+OqPtTFaJ1GpAakQ0EAlXKJPD6fJdE/kR9KddiciO4ILyeK52ORv4s8byL9mK2jDLeU81AoKZ3CMvUKkS+QT/0NDSAtkFCHRJCgLhLF8gPEtkvhbnIpAR0VC6D8d6Ufx954A7EdOzWBishanxawE5nbs15H5H181m3wLKzPST+6AMTaE+ICEGv2s711rQAQrWRbK+EnRoZkMeydKxBoq4xh18r34G3KZF0HCoESOZ00ogG28gCwzeT1a2jYd8CwG15ImdYHVmTjos4nqGYt6rC7v3rlGu6MjjLwEMjlseWlgzi8pYMlnJ94ox/N/iRWLAmU5Sx87UfXMH3vBvz5LEYalzF91KInj8bEBDq8Hvzqlz5eNjUt/zqpFm0UwqTUafB4fSwHodqYf5EfSsZcduVSib1NKwRR7UejELJqfK7Vxo5wvmrmIj0LPkS61ggzRsm3Cr5YvSG7nR5A5+W7lAGQN99EbOt2JnpaTbHKVFfNmG4byQIi76Nrq4VvASf96AIQa/53AYg1+9neumYAyMULCC5pR7C9vWQDo2RxK4Yy2gBKp7vlp5i8sBQ5qZtCLGLbd8AXrQyjkOfrpBCYCEigefCS6jUBSDKJmdOnDJPs1SJ61fhIGd5DIOM//O0ZJPJJtMYfw5f34H2ffDd6VjQjlczi5Jv9WLfUg6ZQnlGlyuVnpx/gxslTFHiF0cYl8BQJgBRRn5jC5qgfH/zCh8qmpgXIRJKPq1kfteExW8kAlRKa48eOCeUVac1F5IdS/cwYJcjLY/BCEqu1i7KdOjfFjj5F+lAyVYkmbMv1fLEowqtWI9C6SHMovRtKXliU0o/jb72Fuk3GrFxG63xaN0sitn/W64i8j8+6DZ6F9TnpRxeAWHtCXABizX62t64VAJK4fKkifMFK/LuRIY1i2LX+xhJzC4VSmI+6b/kEPTs8yN0clEJsDh6Cx++31d+iydNatlZOROsDyzulpfaZ4SGWjC9TulazOKVK/PRsBn/ynbNM12PR1DA8xQA+/48+hOb6EB4PxnH94iB2dofhSU6Xib9dvzuO115+HXmfB2MNc7dcsWQCR1p92Pfp95dNTSskyigpuJp1KdsYhQBSPTlEDx4vF/QZzUXkh1KdlCxyu8HLIbJqH/YsPaG2VYcr2dG3UR/KPA0GDM6eQePhFw2HlXOGvKGgpBmio4+ixxLHckiuXdWlry4DIO+8w9UlMQQgdEt64zoa9u532pRu/yoLiLyPrtEWvgWc9KMLQKz53wUg1uxne+uaASBXrzAGrNDyOWYgEQaaagxmFMOudTsih1iR+JpWkXMqKASLJ1qmTjKuZv56bURFxnj0xlofWJF4eBGtEN56lbcR/QNxfP3VKyx/o21yCD5fBF/+ykcZA9bNa8OYGJ3F1rVB5MbHEN20pdQ1AZf//ucvIxX0YSI2l1MUSaXxiaUevPDR95YDkPNnEVwuJR7LxUmxPV5uk0xSAI+njJKXZzv130V+KNXPoxIA6o3HY1EzO0+t+kYJ23b0r9cHu6W4dZOJUKopkfXayO+Gx+tBdOt2lguiVdSCl3Id6bbnNup37dFsVwZAjh2zJAL5tELbnPRZrfQt8j7Wylqe53k66UcXgFh7slwAYs1+treuFQCiDv3QU8W2w0BGCuta4TFMnC2VQl3Pes3h5VNjAiDhNWsRaJFE8rSKmmbVjvXIffCSWeV6PBpVTQBCGglH3zRMsjeiGRVdpzIH4cS1Ibxy5haKngKWTAyiubkNv/aFd7Ouzh67h2gsiK7FHnbzomYW+pv/8n0MeTyYis6xqoXSeXxxZRHL3yf1IRddBjaDcBrR9WjV4+U2yX+ntlZOq0V+KNWg1ShBXl4LT0fGim3ktnY8S9XMI59IsBC5xkNHhIU15W8VjUd0xnohmAzQXDhfIVaaUYlBquet9OPE8RO6eiEi6xUlqhDpy61jzgIi76O5Ht3aT8MCTvrRBSDWPOoCEGv2s711zQAQxjQVZDHUVOaYiIwZaKoxmFGcu5ZKuZGCMY0v36hQ+FF45UpD2mDRPI1q1kVtRG6NjJLwqQ+9D6yWSrlynqJCiEZrU56u//CdOzhz+yHL32gfH8DqVSvxoU/sRz5XwNuv3cK6DYuxKJJhKtTqUJ1Xv/EKLsTzmI7OnUZHcl58uSuL5hffVTYFLbVrHkir1j/UjhfeJd+QAEWk+vVPxnlzEPmhVN9s8W7HaEwRsULe3Hh/Tz94ALoxiL6wkVfV1r8rFdjzM9PCujb03hEQadg7J2KonpieBkf60SPkJspv8ZRtywDIyZOGeSY8Y7BE+Dt3GFByy/xaQOR9nN8ZuaNVYwEn/egCkGo8MtfGBSDW7Gd761oBIOqwDtFwomoMZsT0w+Lzu7rKFIl5myE5b4TCRoJLOxBcskR3Wk4ngaqVxLUmwstB0PvA8vRLeHYS8ZVSCI/YrO6Nj7JmHWMD2LZtPfa9tA2T47O4eOoBdh5chVBmWnNDdf7l1/DqYAYzCl2Fjlg9PtcyVaHVogXaRG4CRNajVYeX2ySDYNrQaoEr0XFFfijVWhci4p8MkM/OliX+i85JtB67dUwmHR1Dby4sB2f7ThTSKWEASD4t5vIwouzVy6Pi2VPpx8nTpyvCBUVtSvXsYKozM55bd84CIu+ja6+FbwEn/egCEGv+dwGINfvZ3rpmAAgleucLiKyTFK1FGWiqMZgRra5WOA47oZycKEt0Vo4rb9ooBCvY1sZAiF5xOgabF95D8+LlIOgCkJPHDXNceDdFIr5K3b3LNn6R7h784TfOIFlIsmbLRgfw7pd2YN32bty7PYYH/eM4+N61yE1OInWzj8XsK8v914/iG7fSmI08UYwuAltXdOA9nodlp9R6mh9GYXoi6zCqYyQ6R+3k2xcU8iwZO7alUrhOZA6iP5STR98o0Udr3QCqx7IDaPLmr9Zm4dW38+/sG7B2HZDPg57p+p27uN0TY18hkzVkLNMjoOCFtJUBkDNnuYccRpO1g6mOawy3gqYFRN9H13wL2wJO+tEFINZ87wIQa/azvXWtABB1WIeTuRLsBx9AZM3aCnvHT55A3fr18Dc2lf6WHhhAbmwU0c1zic7KhrJ4HoVg+ZtbEFpG2hPaxWl60ekzpxBevaZM0FE9E7bGnvXwN82tUVlH7wPLAy52nFrLquTZFWvxp9+VGLCodI48wi996hCaVy7DxVMP4fN5sWX3cuhpn0wdP4a/uJ7BVEASHPQUvXjP1i5snbldpqOgRwrAE2u08qLydGDk2xe6nSCAFd24qarhRH8olcKYvNsxmoiUnzGO6CZJkd6JwqO+dmJMuU85DI1IAIhYQYTVjd6pYjptSFOtB3Z5rGJlAOTcOQQXL0GwfWlVJrCDqa6qgd1Grg7IM/IMiH5Xq1muC0CqsdpcGxeAWLOf7a1rBoBQWEcigboNLzAbOJkrYXS6qhWfzxh5Hg/pnkTLG/Ps8BATCAt1rtD1o9P0oiyJflkngovnGJ0qAMjxY6jbuEmXrUcXgBgIONIYPLYwkYdbiocfx2DTCvy3164yBiwqa0YH8MlfOoJbDzNIJDJ4YWsHFi2JQU9YjUJifjrVgKujcZZD4in48Zsf2ISWe1fLbnH0njOe+KTIWrTqiBAFyDotlI9gJQxJ9IeShdZt2cqeXa0bQPU66KaPTtJjW7ZWawZuO96mnNuBhQpyjhipn2dGRoTWScC/kM6w8D6jogU+ebdtSj9OXbgAf0srQh36hxxG40u+G676Vs2CWZ/7pqLv43NvqAVuACf96AIQa853AYg1+9neulYAiDqB2clcCTnMR4vVSivPgcdSI4c9EVDxhsIIr1qlD0AIzGiwNtnleJHcBV4uh94HlpegrMzfqHY98gbpkncJfnruNmPAorJpegJLOrsQaYzhhW1LEWsIS0CVtBrOSaxFykJhRenurfjOsfsYjSexq3sJPrJ/FdN1CK/uKt0Q6Wkz2LEWTQCSy4HydGijqqcDI2+ACYAowxLN2lT0h1IJukVC+Hjvg9l5atXXEoe0o1+RPiTf5+GtizIwLHLTQ6FrxVyWq6+hReQgvVf6txplAOTiJXZzGVq2XGQpFXV4t7lVdeo2ErKA6Pso1Jlb6alZwEk/ugDEmltdAGLNfra3rhkAogpzYrkSvb0sXt/uYpSrwBKEt5WrmfNuLeQNPW2e4fMj0tWlO2Wn6UV5p6k0MZ7Kt94H1kg/hfo1Cm0T9aEco/5aohln+x8yNfPILLAqk8aWPWuwftdq+PxSWBUVJr548iSaXnyp9G/KUBePP8D+3eORPk1SfsVSBJe0s/9mrEB376B+ZzkrEAOpKfuToEvkCoePwOOdW4fSPvLpfzGb5T5PRnYV/aFUap7wGLqYzUZGkHpwH/U7doq61XQ9ET0S050KNpAPQ0jPIzc9LcTERc8V+at+t7aWhzy0FgEBL++mDIBcugx/fb3hLavRMuUbRhFQJWgut5qgBUTfR8Hu3GpPyQJO+tEFINac6gIQa/azvXWtABAW5jQ0p6KdHR8TZqAxa7T0wwcg9WGt2HqtE0ppk3pXNxlVjqGnHBAUi7qK6TRPpxN4RXIXeFS9eh9Y3qm0HQJ1mdERXD92CT+ciiGXT6EuUYS34MHu5iQOfmw/E6tUlkImw2htGxUbeqNNvnpjq37u5L6d8pOIEKWc/0AbWm9dHcIrVpp9xFl90R9KljfUtYYxv4mwqDmdx8SA4qULlnIdqjLYk0Z04ED+D7S2CofA0c0j3VjxQJkWwJNysnp0FdSVfoxfuWrpmTD69lmxmduWbwHR95Hfk1vjaVrAST+6AMSaZ10AYs1+treuGQAy8riMcjQ7OoLUPTEGGrNGM7qFkBiByrn8eWBIjusmAEUbYj3FdJonj3LT7FrU9RkI8Ho0E+yprojAoy4AUWm1qMe2GrefyuTwk59fwtjVqxhsXoFwsoiC14NkxI/PL01i1aG98NXXlw2r1G2QQ5r09BaooRqg6WmXsGdkbEyXeKBaPxnNTe5TzlGiZ8lKuI3oD6XyBF6ZkK63RqeZ3BgAOX8OwWXLDXOZqvUBrx0dTsxeu4rAknYWVmX0Pst9EbClmze1IKZ6LC2wwaNlLgMg166X6SXx1qL+ux1MdWbHdOtLFhB9H117LWwLOOlHF4BY870LQKzZz/bWtQJA1KeqTsaZ6yVi6m3OacOV7KukemUb+kIBU28dRcP+A+wGR5lIr+VMOxK1jR4S2rwabZpEkqD1PrC8ECuR2xe9uT8aTeC7b9zE7MRjLJqIYyq8CJmQB+mwD6sWt+JTscfsBsqn0PUos/++/fCGJMpdIwIDNbuSXqiVU2xBktL2uQo1bKVdZDaxQiZt6RZA9IdSudnn3Y7RPNkG/fpVNOw7YPv3Su5QZpYLtC5ybAy9jhkF+KkTUqK3Rx/MK9vT7WAxn0N0kzZTXmlditsm9vwWi0w81EjAUOnH6es3LIXl2cFUN+8OeUYGFH0fn5HlPrPLcNKPLgCx9ti4AMSa/WxvXTMAZGKiTM/BSbYWPXCjR5Opl6hMzlJy+9OmlUebytvEW30AeCecWjcG6jH1PrA8BWwjhXmjdZ24NoRXz9xDIZdGbCaL+uQ0hlqbkQ8EsW99B963qxMz7xwtaVWo+1Jvmo02yOo16PnDqRs4PdYu5Zrk8K9iOmVJdE70h1ImFwgsWSJthhVgTstvImuw+hyLsHFZHUOvvQzSKQSLEtGNcrrkPkjcFIVCicVPr29227RiJQJtbayK2fdxurePtdOiEBexB+8dFunDrVOdBUTfx+p6d1vNlwWc9KMLQKx50QUg1uxne+taASDqTaOTyZJ6SbR6mwEjRi5lTD/lgBjphZBzWZhSIMCYmJwoPLuJJEHrAhAVVbJ6/olrV+Gvb0Cos1N4aef6RvCDY30IZHMIp4qAJ49FifsY7tyMTxxcg/Urm+dumXQ2xiypftt2RiNLJTs+jtTtW5oJwercDr1bG9bHrZsVAofCC9OpKHJ7IIcIFpIphNesRaClpaphRX8oJXKBRQi2t0u3eQcOwBsI6o4pcotT1YQVjeInjqFuw8aKnB+r/Yq2J2IJTzCAQNtihFfqs9rJ/RFtM91m8MK1ZJFJYr2iwkgUTp1E05E5EgX1HMtuQPpuAfkcIuu6RZdSVu9pCjxWNeFnqJHo+/gMLfmZXIqTfnQBiLVHxgUg1uxne+taASDqU1WnkoDZBnVsjGlW1O8qZz7S25xTSE/i0kU0HDhY4R9lTL9I2A7b8FpILOY9IHpJ1XI7kSRovQ8sD9zI+hWiFKET02l89QcXkUslEZktIhP2IO8rYkdyAAe/+EtoqpeodnmnxKRCXbdpMwM/zL8GLE3qmzW9OYsABZ4vtP4ukj/BfDg8hEJy1tImXPSHUrYBMYPxKIJpTSJ5LNXYRtlGJBne6hhG7SkErDA7i/Cq1UKMU/RuoFhAaLkx+GbJ9W2LmZo5s+X0NCiB3Ug/ROnHmVu3uXlmRuviqa47adPnvW/R9/F5t9NCX7+TfnQBiDXvuwDEmv1sb10zAESl5+BkrHJWFe7F25wbnfgq8w1E6ElFaHKtPAS80CGRzaPeB1beGOsl2son6aEOaXNlVArFIr7+kxu4NzyC2HQB2aAHqXAAR9YvxY7kHTQdfhEen491wbu1YdoVPRtKyu5G81T7SE3LK8/ZKSFMCfzeRv0ufbpWmfY5PztbptrOs6n676I/lHLoHNETx4+VM4ppjVkCsQZUwmbnqq6vxUZntU8z7elZzo6NM0a70LLqRP+0xlOzsIkA0jIAcrtfmJlLa/ynqTBvxv7PYl3R9/FZXPuztCYn/egCEGtPigtArNnP9ta1AkBY4ufJEyU9ByeTtfVyOigcYvrUKTQeebHMD2zTfuYUGg+X/ztVUoZnidCT8rQ0rD4AeuCqtLFmSdCVwn3KcfU+sLR5Tz+8j9h2bf0HM9SpJ68N48enbqFuNgdvoYiZeh92rV2Oj+5bwXRKlGFA6mdDbSNZiV4OVTK6qVHbZ/rM6TJhwpKdyOenK58Fy/4RYHeTnyMSWWzYsxfecKSqYUV/KCl/gQQ0GQA5cZw9/7JuiiYAyWZBIUqNhw6XQGJVE9RpJMLUZud4Wn1RqCSFVNZ1d5duK+wYUx2myADxfWO2P6UfE3fuMpKFug0vVDUdChXjaRVV1bHbiGsB0feR25Fb4alawEk/ugDEmmtdAGLNfra3rhkAotJzcDJUIDcdx+yVy2jYXx5SpaeqbbQBVgomipxm8tTErT4AEiCqXFtpYz0zA5qDaMhHLicpkVNheRH9t3RP7/VuE9RrGptK4asvX0IxnUR4tohE1IOGhgb8009sQSjog0xr7A3LauezmDl7WhMAUt9qITejRHx1qJ+e8reWvohV31B7RoAw8Aix7Tt0u2PP0fXrLNSGl49hNCfRH0p5U0oARAR06ZE12GEf6oMXcmfXOEb9EDsa3cLWrd/AVMrtKuqcIxGyjTIAcu8+l+jCaK5WqbLtssPz2I/o+/g82qaW1uykH10AYu1JcAGINfvZ3rpWAIh60+HkSZ1eeI3evxuFnCg1QoyS1WXH0u1DcHkniwN3ouiBKHkskTnqfWCN2MCofxHtBgq9+ssfX8Ojx2OIzhSQCXqQCQfxxfdvxOqlUg6HWouCFw6lTuw1uj1Th6DpqcLPbbIPMtIAuwovjI3GIR8lSFm7WCwTWDQ7B9EfSpkJjAGQc8a3YwwgyNSxHLYss/OV6zsF/szMJzM4gNm+PqaCLjNWmWmvV5cAgMcfKDFrieS6lQGQ+w+QGx/j0v3qjk85aJGIUGK9Het1+5izgOj76NpsYVvAST+6AMSa710AYs1+treuGQAi62k82dRY0ZTgGZFi67VO1PXoRUs5CBohJ8qcAt5GmealF/LDm7Po33lJ5kQTTCE3pDugV/Q+sNL69G9Pps+dRXjFCgQWSRSjWuWdy4P42dnbqJvNw1MsIhHzYV/PCnxo35zaN4X3RDdvKYkO8kCTOrHXKM5d6UvSeGCsTxobaRF9BlGfKOsZiWDK9cjOdKtDYVDqcEAzY4r+UMrMSJQYzbsdk8cX0QsxM1dlXRFmqGr7Fm1HBwuJy5cR3bSZKaLbVSp1aO5wk8qVfpx9+AiZx8OIbdlW1ZSqpcquajC3UZkFRN9H12wL2wJO+tEFINZ87wIQa/azvXWtABBaOKmQ1+/eC18kAvqhJFrVUOcK222iF1Klx3xkFBKiZL4SSfAmgTOi6vQ3Ndu+LuqQF75iRFErT0gXgHDyIpTgihiuKNRKWUjp/Ptv3wLSKSFsDFgAACAASURBVKZynoh50NzYiC9/fDOCASnhnIo6LIoHmtSJvXJOQ3hVJX1qSYhx336mGM+SrnVyGdhNzPad8EWjtvlKT3ldOQA9R6SDQcruRqFyvEmJ/lDKhA/BjmWYvXqFiWryClPv3rbDVtvIY84HzS9vfTIIjG3dauu7qqbBTd68Cfi8iHSt0Z1SGQB5NAi6nSHa6WpKNVTZ1Yzjtqm0gOj76NpuYVvAST+6AMSa710AYs1+treuJQCiDIcxS+lqxnB6IR56G10j9XDaDGRGRhDbshW82we2uT5+DHUbN8HfIIUb2V14J/ciifJ6H1heaIycDH5uKItXTt9BEXP5I/I6PYUcYhR6FfIgGwriNz+4CSuW1JeZQZ1UzgNN0qaqvgRWeZssOcQLHq9hzoOa3tcOX/GEImkM+TnyhkNo2Lu/6mFFfyjTD+6zxOZgRwfo5lFkTLINqX776st9V/VkFQ2lHC0xIGTHeFp9yDdllKtj57uqZvcTuZEoAyCDQ8g8fKBLBMGzh5PfVd7Yz/vfRd/H591OC339TvrRBSDWvO8CEGv2s711LQEQZegNceMH29psZaCRjat3S6C30TWKeVeeaJdU0Q3YgdjJ8dY50TzbHc5yKN5iSc5aJ/ciVMF6H1heXgTd7kwt6sRfvf0A3nQaoXSxYnmeIlDwAomYH4deWIn37a7UTVAnlfOohdXheonLl+BvXQQ9OmBZ5I5uQLTICORJO3FbJUIvLT+f5D+1Vo2Z50X0h1J+hukGJHWzT0h8US9538z89OqKkDnYMQ6vD0YFTDdgTwQuefVF/i6DPZnFSoQVT+nH5NAwS46v31muYSQyNtWR3o1WhDrsoxYWHft5ryf6Pj7vdlro63fSjy4AseZ9F4BYs5/trWsKgJCew/oN8Dc2QZRRqRqD6d1oGN0O6MW8K0+0S/0aKEk7GTtf2jgb3LIwFiZOCIcuAJGTj/fug8xQpbT/5PFj+M5dYCCZQzRRQDbgYWCjrHiArN+DtqZG/I8f3wy/T10BT3zfUWIfyjx+jMyjh7rMUWrCAnVSuvoZmT5zCmEW8uIxVDt3Il9HRIlafo7o5N2ILYv37Iv+UKYHBpAbGwUDIBoCnVrjSLZZjUDrIt40TP9d5JbOdKdVNKCbGFncsormmk0Y2JuYYLklVESIG8oAyOMRpPqNdWSM5mqGKtuuNbv9SBYQfR9dey1sCzjpRxeAWPO9C0Cs2c/21rUEQJShNyyhuXOFrQw0ZZvlN99gidjKjbTRSbuamUnuK3W3PIlUTSGrHNNp9iB5LHUIk3IOIixMRh9YdruyYwd8dZV5Ecf+5od4YzYCf8aPoseD2Tof6sMR+FQgY3FzHT66bxUaYyHN5119+8Wbs5qymVSsScFab3PMAAqdAHtgGM4isjk0+8KK0ktTPhTlCVFoX7VF9IdSti8J7qXuGWtSyHOR6KSXINi+tNrp6baThRj19GZsH3AeO1SGbNKw0ru6BoEW/UR3pR9To2MgJq2GPfokEoYAhJ79pUtBqvdumV8LiL6P8zsrdzSzFnDSjy4AMeuN8vouALFmP9tb1xQAUWwcnTh9VhpXS2nZ6KRdL3SKbSgLRUTWrWPd6wEV+pscWtNwwF5qV/VDYwTe5NNuYpnSK0YfWL28iPvD0/jF1/8ew7EOePMBzMS86FjUgn/ykRfg81bechg96Oo4dR5zlJp2lxc6JYe9EAIh0Km3yXciDFCUXpqAnr+5GdGNm6r+Joj+UMrPfXDZcsObJuVEnCSJ4AHOqg2yABqqbyBFcsLKAMjYuHCejtZynQDVC8CsNTEF0fexJhbzHE/SST+6AMTag+UCEGv2s711LQEQ5Y8jbxNp1VBagELJaKXuX2/jrWaxUVPIKvvhJXFbXZPc3kjsUISFyRCAaLB4ZbJ5fPXly4jduoip0HIkon4gHMaXPrYFi5vMq3irE3PTDx+AGMr0NuMsDG52loXvUeElj8v9U91CIqGrKu1Ewq7E0BViNzRGhdbgb24pramaZ0P0h1K++QsRABkeQmwrn+JVhL2pmjlTGx7grLbfhdBOnYMlHYTs0rxRlOdbBkAmJg3zlnhrdPpmmTf+8/x30ffxebZRLazdST+6AMTaE+ACEGv2s711TQEQFtbRjmB7O+REYX9jo+020dukqsMjlAPrzUdN+Wo0byNFdTsXabRxpiTY3PQ0E1jTK0YfWK3wpldO3MOJ3vtYPjiCqVgjpmMhvH/nGhzcXF14jlqtmcccxcTc4nMAxegWitYs30Kw9edziKzr1jQFS26vq0N4xZxGiVU/ibAesefz5AkWliPfrFUzrugPpUy+EFq+vMToxhuPlMIL6RTqetbzqpr+u4g4n+lOF0gDKb9FyuEwYtdTTlfpx/RkHDMXz6Px4OGqVsQLT6yqU7eRkAVE30ehztxKT80CTvrRBSDW3OoCEGv2s711LQEQJSPM1Dtvs5NYOxloygCFIuFd/nejk1e9Gxl1KArpN4TXdSPQXKnzwVMpt8v5Rhtn9W2B1phGH1h1gnf/QBz/36tXEUxl0DYxgeFF9Vi6dCl+88Mb4PVU9zkwK9am9JtIno0cskVrV6pSq20hGi5lxm8MHDY0ItRZyf6l7IcS5f0ti0qK2WbGkOuK/lDK9NOh5Z3ITYyXEqSNxkw/eoTcRPWK3EZ9izCFVWOPhdBGyfBVou0+fAQegzDFMgASnxZSq9dbq0zAYJRzshDs9CzOQfR9fBbX/iytyUk/ugDE2pNS3Y7D2phuawML1BQAUWzOeKfYVp2uBRSMwpP0ErvVtw1GJ4x6SutW12Jm46xOmhcFIOf6RnDy+iDqH93CbKQRiVgLazqbziKXTiKaKKJ19gGG27vwW5/aidbGcNXLqhBr678N5Au6twHKnAGeECNNSqZCpf9vJHYpmjBuZqEitKvUH4XKBBYtsnT7IvpDKSvNMwAyHTe8HZPXKuWNVK9HYWQzEaYwMzZfSHWZ2Om1q0zsUfRAogyATCcwffokmo68VNWy6CAlsq5H84Ckqg7dRsIWEH0fhTt0Kz4VCzjpRxeAWHOpC0Cs2c/21rUEQJQn90ZsUnYYSSvJXc3RrxxHLylenag8c/4sgss7EWxbXDHN3NSkpQRS0XUbbeCSnM08jaH+wPben8Df/uIGfLkMWqfGkPEHkQjPCdAFM0VGt7s0fhvrP/IB7Nm8XHSqmvXUJ+DqGxF1I+VmWORUWU7Ep9sSI60ZJ8KMGA1q22Kuvg3dNAXaFoOYqaotoj+UJEJIeUN0K2OUE6OchxmtDsp9QiEPb1gsH4jn72rtsRDaybYmhXslGDGam9KPmUQS8RPH0XjkRXiquGF0Ur9lIdh3Ic9B9H1cyGtw5+YsnbILQKw9YS4AsWY/21vXFADp64U3GERoxUpMvXWUnRLSfztRtJIxjcKT9JI31SFJRgngPEVvu9ZptA6RzZ3yhzI+k8Z//v4lzCZmUJcooi6bQN7jRSo4t5kkyt1kpIg9qUG8/7c+A18gYGkp6hwAlhMSCCC8ukuz3+zYKOhmh8TZ8rOzmDl7Go2HX9Sdg0zzShX0wCL9TSRfxuxCeRolcn90G+draLCkQyG64ZFP4kPLVwjndUgbabFcBHbrlkzqJvurbajOATJr44VcX3nrocwHEQYgyRTix46hkRO2pdefCOvWQrZfLc9N9H2s5TU+D3N30o8uALH2BLkAxJr9bG9dSwBE3hyHV64C5YDQKaHH77fdJtSh1kbQKDxJj75SrdptFGLDU/S2a6FGoWQieQ3KD+zfvtqHq/cGEZ3JI+/zIJYdQcHjx1hD+Q3PonAQn2meQPt73g2Pz2dpKepcHF4yeHZioqTgLRLmJgNBFIu6+ToMgAw8Qm7c3jyH+WQhEv2hZOQIp06AAIhRUr7SqSI3TXJ9AhTFdBpG1M/KvkUT9S09ZE+psZKIQkQUlKap9GM2lbH0bTRi6XtKJnluhhV9H58bg9ToQp30owtArD0ULgCxZj/bW9cUAOnvZxsgugFhYQZVnvKJGFFLEdgodEnvZkMtJJa4dpWdWmslGYtuOETmb1THSEdBzdql1Y/8gT165j6++cZ1hJNZ+LNFJOq92BrKY9OKRnhWkpK4VAJ+L9obfEiePmWLz9j8Hw8htkWigzWyKf2dhbZdv4aGfQcgJ1STyKRekXMeCIDQpthXPxdOpmzD5jE0iNi27VZdUmrvtL6NcqKiP5QyPbQc7hVZK2naGJUSg9O+/YxW2KgkrlxGMZuBqLCgE/THvPXM19+VVNyZwUGhRP4yAJLJSbfDBw7AGzB/O6ynZzRf63+exxF9H59nG9XC2p30owtArD0BLgCxZj/bW9cSAJFj7sMrVyJ+qvpESxEjat1UGCUd64nSEV0qUZH6m5rYsOy0PhIB3eKoixHNr8icReuotQaU7UROl+kD6wsG8PtfO4b07AwiiSKSUQ+CkSh+a2cjwsVchT6FnRTDUojUQ8S272BTpw0saWLo5UMobz2ksJZ+1O/arWsuFgZz9gxQBGK798AX0c5NMLKjqC/U9YxY0qrtU6+d6A+lnLhPyuaeYBCRrjlwaTQn0c0s5UUVc3nU794jtEQnBCCFBp6HSkqSBLphU+rXiPgxm81j6uibaBAAflr9OU3uMQ8mrNkhRN/Hml3gczJxJ/3oAhBrD5ELQKzZz/bWtQRA5CRwugGhTUvjoSO220PukJ2yNjaCmH/kYiSuphdapRa9M8pXkKhLxWhOrSzcKNeEd5tA4/p8Hvzd0Tu4eOs+6uIF5AIepCIB/PKRHqwLzGqKAuaTSczQDcgR/dwL0TUxEHG3n+V0UOFtSJVx9UZq9vL48ik0/beRKr0TOTvzmQQs+kMp32YQ65YvGuWKJMp2FBULpTWjUEDD/oNCj4BonoxQZwuskvLmiAQ26RaOd+Ok9iMBECPgbAgaLbRdYKasuemIvo81t7DnbMJO+tEFINYeJheAWLOf7a1rCoA8eshCaEj4LXH5EtscOlW0bgKMwIMWYKG5Tb39Fjupp40bFXaLAiCyZm3F1I1YtuxcpxxiREn86sK7TaD6l++M4Qfv9ME/nYEvX0Qi5sMLK9rxy+9ai+zQoKZYnSilqMg6iWEp2deH+j17JQBy4TxjjaITeq1SSCURP3kSTS++BJFbJnkTSH0ZsQkpQ7tE5i1Sh6fSLtKHaB0zP5TEOke3ePQ/rds7rTGNGN+U9Untm26bRMEpy6tatQqB1kWiS62pepNH30D97r2M5IBINsKrVhvOvwKAvH0UsR07DdXT9Tp0ml2wphwxz5M18z7O89Tc4UxYwEk/ugDEhCM0qroAxJr9bG9dSwBE3jxSCBaFMjXs3W+7PeQOtXIhjMKn1IKDcj/q00hZ5K6uu6di7k7QumoZKJ9IgJLmGw9VqiXzbhOmEhl89QcXGRtScDqPRNSDumgMX/nkFkTDAejdMCjpRa06jdGTXr/Kcjqo8BK3y+LqKXF8ak4VXW8ubFPs9RoqStu5ptLz8s5biG3d7pjApnK9Zn4oyR7euiiCixcj1LlCyIUimiZyyBEDe4cOCxEUzGeYmtBCba4kH1oQ6YX6FlZrqAoAUqVIq5m8HZuX7HanQW/uGqU2LWDmu2p2hS4AMWux8vouALFmP9tb1xQAGR5mJ9ihlatKrEa2G+RJh1psUEb5EVrgROsH3UjFWUSDw471yvkYWqf7RjTBo5NJfPuNWxiZmkD9TBEZH5CMBPGrL63H+pWSsrtejgUJ2M1euSwcZmO0TvXGn5e4XRZX/+ihRPm6foOhKekmggCIEci1M6ysBEDeehOxnbvhq6uzw9WGfZj5oaR8Dk8ggNCy5ex/IoW9E+EIu63QK4wW+cxpkOaKaN5C/MQx1G3YyDbnz2KRmajoexBc0o5ge7spP1Z7i1bM59mNbbUJ7M+iL+ZzTWbex/mclzuWOQs46UcXgJjzhbq2C0Cs2c/21rUEQOSkXwoB4SUSWzWUVqiUUX6EljaBluq2WsNCOU+jHBOr61G2N1ID16ITps3hxVtj+NHJfmSzKURnC/DCg+mYF1tXL8Onjszpb+gJ0KlvLaysR63lwcs1KIurf/TQUDVdnhexl8HrKeWZaM3XDNWssj09R5Qw72+UiAmUZT5DYMz8UDJABjDwH+oQEz8UAdSy+GYxmysLVTR6PoiCO7Z127zcEll5TqttK+cBJW/dAt32Bha1mQMgJ48zgK31fBl1ZPRdqHYtbjtxC5h5H8V7dWvOtwWc9KMLQKx50wUg1uxne+uaAiCMweg22wRlHj4Qpu2sxmhalLtG+RFaNybK0B+P18umYaQdIUKBW81a1G2MQi3UuiXpbB4/Pn4PF/oH4c/lEEkWUfQC6QYfouEYvvzxzYiE5rRY9G46ROhvRddW2vg/UXsWORGXQ+HouYHPj0iXtmihPAfKX4DHa0ixK2/YjBLVtdZEtwnhFasqqJhLfnFQYFM5HzM/lLQpLmYyiKzrRrB9qZCrRHKaiNGMQHkxk2ZChCKbZgoHm69bIqGF2lxJDjFL9vWWMejpDaP2Iw+Q6/VTyGYkEUPBUDibl/3cd2fmfXzujbWADeCkH10AYs3xLgCxZj/bW9cSAJFP12nzZrf+gtqwWvkYlPjub12EUEdHhR+0bkxY8rOKLthQg+P6NXiJZWjFSst+TqZzoHyNxc0ReD2Vr50e3eb0mVMId61BoKUVg2MJfPfNWxidjiOcLCCQKSIb8iAd8aKzbRE+fWQNmqLlWgN6yeZMDPDWTWGqVSMDFLJZUJiKLEQpIp7G4uq3bQcxC3nr6rg2plwYEkyMbtykOxW6GTJLeSrPPbh0KdR5QPN9Am3mh5JuhOjmiU7W9ZL91YaidzTzeLik16JlSIn5bQyFVJop2QdaWw2f/WpsbvllmucOpJDC1SzPTSQfSO1H5TtsZurV3uiZGcOtq28BM++ja8eFawEn/egCEGt+dwGISft1d3cv83g8f1YsFt9NJEoAvpXJZH7v7t27qZ6entXFYvHPPR4PZWPfKxQK//zmzZs/MzNETQGQeByzV6+wG5Dc2KiwcrIZe8h1U/fvoZBIsFNZuRjlR2iFm2gle0saFtq3N9UIrBWKBWTyGQS8Afi8ksL4vaFp/M2rfcjmC1jVXo8vvL8HXm/5q6cXJ06np5F1PRgtBPG1H19BPptGJFmAtwAk6zzI+YPY29OBX/vQBsxMp5DLFcrMq76dkP8oor8h6if1TYGIdoG83vT9+4zJiZfHQGFSdGvFyxURGVu5Lrohmjl3juUvqAUMSyfQDgpsKudi5ody+uxp5GcSqHvhBQTbylXu9fyWHRsFJVLLdMla9ejvdFNIehcEyijnwahUe+sk+mwthHqMPWxZpySeuXcfvOGw4bQqAAixhAmEbqk7tVOrZyHYsdbmYOZ9rLW1PU/zddKPLgCx9iS5AMSc/Tw9PT3HisXiRKFQ+Nder7fF4/H8JYDv9/b2/k/d3d0XiBUVwL8H8EmPx/Nvstnshv7+/vuiw9QSAJGTjymplUJ6jE6nRdevV49OytVsSUZ0r/JGSnmqrRTAm9uI62/KeAxUWnOdySaQK+Tg9XjREJQUu//yR9fxYGSmVP2Th1Zj69pyylIZaASam5HPF3Dh5ANk0jmW5O9vacW1gRlMzs7CUwTyPg+SEQ9CwQg+fnAN66u5OYqJiUQFANE7xc+OjiB17x7qd+6y6hrWnqhKG/bsZUnOyv+v1zmLq+/ZgNT9uwguXsINI2IhdV6vJl2ycgy6fanbvJmp24sUYglL9l6Hxx+AmgZ5vjeAZn4oaVOci08jummTMP0ty/u5drVinUo7ydTWBNb9zc1cYKgV1ihi91qqQwcdpLlCOSDyLZ/R/NV+FKU/VvfpBKlCLdn9ac/VzPv4tOfqjq9vASf96AIQa0+eC0BM2K+np2d9sVi8nsvl2vv7+4epaXd3968C+GOPx/OFYrH4ciQSWXLx4sXEk7/9HMDbfX19/050mJoCIMSYc/Y0uwFR306Irle0nlauhtEPuxa7lZxgq2RSYqFIN+c0LJTz4elZqOdO4SjxzDSKJKJAonnBeuRyRfzRN86hIP0TK2uXNeLX39dd1lyZ6zE6PI2r5wfQuboFqZs3UGxfjpfPDqDgybF8j2zAi2UtLfjll9aiuT4Eow+sXn6J0c2PqE+U9VhI1Y4dDIBMvXWUy6BEIUThNWuRvncHweWd3FN8usmh4g2FDKenVrrnrYVu1gg85yYmKjaX870BNPNDSc8mA+SbtyDQ0sJbJvu7yHqkvKpmEFj3RiJcjRFZpb7xsHVBS6FFPIVKFOrpjcaQfngfTUde4s6gAoAwXRz+bZK6Yzu1eriTditUWMDM++iab+FawEk/ugDEmt9dAGLCfqtWrWoKh8N7b9y48VO52RMA8ucA/k+Px/PB3t7ekhx4d3f3v6NwrN7e3g+IDlNLAEQ+IabwAtog1vWsF12m6Xpa8esUhkKiYFoCaFohW1pK2UZsUOoEcN6k6eaDbkDkEg1EMfA4ib/+yY2yppQD8q8+t60sWVwCO9Im5drFAcxOZ7Dr0CpQgnRfZDn+4coAip486yfiCeNffW4nAn4pxIv3gdVKEs48oVBWhx3x1qj3dwqpim7awjatxIrEOymWbUu5PeGuLpbjYkfhUQCrx5DZ0ij3IbplS9nNiXTDd95Qe8SOOct98PyoHItu5wg0xbZuhb9JolzmFZGcFjncKB+fAjwe7o2TnWxqvPk/rb9TKCblH1HYIj3XvFIBQC5dELrlU/c7388fb13P29/NvI/Pm21qab1O+tEFINaeBBeAWLOft7u7+y0Aox6P536xWGzr6+v7nNxlT0/PVwD8s97e3o2iw9QUAHnC0kIUpnToH1m3TnSZputpbZiNkju1Qra0wo60wrLkycmn9KInzKlcGql8qrS2sC+M09fG8Pq5RxXr/fiBVdjePUfnyUTimlvhb1+K46/fRmdXC1auaQXlNHx/NIbb8RnAA3iKHmxdtQy/pKDa5X1gWVL4lq1lNKlGyfemnQOA3TysX88SyhlzDydvgtELdyxD6m5/VRSlenM0G+4i5REtQWZwkM1HmdBt9GxUYyNeG54fle3ppoI2xAQgzehvqIU41XOSb5DoVojELXmHCiJ5Jbx1L/S/U+4HkRUQiUXDnn3c6ar9KCIAqdWpnVo93Em7FSosYOZ9dM23cC3gpB9dAGLN7y4AsWC/np6ePwbw216vd3c+n/9dj8fj7+3t/aLc5fr16/9xsVj8vd7e3rWiw4yOThfVCcqibc3W8/m8aGiIIB5PsrwDs4WEsibfOso2bZ5AEHVrhZdpdihkRkZAtxoNipyFqRMnUNfTA8qbUJfUo4fIjY8jtnlL6U8EYiiUq377jtK/Uax7/OwZNB+pDCGZOn4MUaIibarUh9BaQCI7i2w+W/pT0BfE935xH70PJiuqr+loxBc/NHdjlLh2Db5oFPFgC66ce4R9L3WhLhrEwM9+jj+/60MmIL2qnqIfn3/PxpLQIP0bz49a60gPDCAzOoL6LVtN+0KrQfzUKUTWrmWCfVMnjqP5pXcZ9jt9Qdr4E1lAbMtW+OulfBmrRe43tFSMmpZsQ8QGBEC84RAiq5UaKpNIXL+Gxv2SwrvThedH5fgzV6+AdHgoh8eM7SaPvYPYps3wN2jnyEwcfZO9YxSaSCx3VNeopAcHkRkeQv227U6b56n1n7hxA/npOLsRati1mzsPtR9nKKytqRnh5WKCkfIAdLuUuHoVjQfm5/njLuw5q2DmfXzOTFNTy3XSjy0tMXcPbeFpcI1XpfG6u7v/yOPx/MtCofArN2/e/Lvu7u7/BKBVfQNSLBa/0tfXN7cL5oxXKBSKHg2a1iqn6WgzynkY/tmrCLW1sU1Q/TrnAEh6ZATTfbew6CARjEll5M230LhlE4IaAGT24UOkhobRsmtnqf7sw0dIDQ2V/RvFxY8cfQvtH3h/ha0ev/4GmnftQEBns6ZuMJmcQuFJ/gf9zefx4T/81SXMpuZAidyGfPx/fGk/YnUSbe7U1WvwBoPoG/VjNpHB4fd2MzXqo3/xHfwgHkXOL+mW1AXq8PtfOozAk/8WcfDoO8dQ392NUNtc4vvs/ftIj46heYc9G8ex4ycQ7eqCPxbF2LHjWPK+9xpObeLceYQWtSJ+ow+LDh2A3yal8YnzFxBsaUF05QquaQhAD//8NbS9eATJgUHkpqfRtHXuVU2PjSN+9RrajvDDbriD2Vxh6vIVJAcG0HpgPwImwNvoO8dR372WvbPqUsjl8Pi117H43e9C+vEI679ltzFJQeLuXWQnp9C0zR4ga7OZbOkufv0GUoND8DfUl307RDufvHiJfUOiq/UV6LX6yoxPYOrKFbQdOSw6lFvPtYBrgXm0gKdWNmvzaBMzQ7kAxIy1ntTt6en5fwB8pVgsfr6vr++b9M/d3d2/5/F43t/b21vKUuzu7v7fPR7PPjM5ILV0A0LrnnjzDQY+/K2tiKw09wNrxvTZiXHM9vWhce9cCITRaW6aNA+Gyk9mtW5FiMVn6tg7aKKQIZ+UUyEXut2p37GT3UzwCtHvxtPTZdXG42n89Q/v6Db92MHV2L1eolCdvXUL+VweZ+8Cq9ctYuFXtEF++T/+Lc7E2lHwkrigB7vWdJYpnVNb3glP/OxZhDs7EVw8R9eaeiCxisU26etq8Nas/Pv0+XNMkZtsNX3+PJoOG2+a6ATfF4shdecOu2HgJZeLzkW+SaK8JF5ht19nzqDpyBFkR4kN7S4ads+dcFN4EQlgNuzew+vKlr/z/KgcJNHbyxjSiHmMbp1EyzTlGrW3I6QhXkhgnHRyml98CRmyx507ZfbQGoNusCi3RK2hIjqfWqhH7yaFdAba2hAz0KGR16L2Y+L6dZYbFVll7vuo9c2rBXs9K3M08z4+K2t+FtfhpB/dGxBrT4wLQEzar6enbw1cSAAAIABJREFU598Wi8V/4/V6f/XGjRvflZv39PS8u1gsfj+ZTC558OAB6YMQKHntCQvWvxUdppZyQGhNlCTtDYZYAnVoeafoMk3X02KwomTn2NZtZbkNcsdaOSNaStC0yScGJy31bBE62dJ4+Sxmc7Nl67pyZxw/PzECDyVvaJTV7fX4jQ9KYVjE2vV4II47UyHsObIakbogJiZn8A9f/RZuLV2DotcLT8GPL7xnI9YubyzrjRfjOsOSYNvZxlMuIqrYZpwkUxYTWxBpw6gpbdV9kaibJxBA+uFDW5WeZRpZEtHjFaaF0n+biTGyhN8L59B4qMQhwUKcKOzPLqpi3nx4flS2T966CUqcF9GlULYjPRWiKA51Vr6r7B0jrYt9Bxgz2GzvdSgZ47TmLyfxExnEs1qI0psoq7XEKrXWrPZjtTbKjj95PnfNDwB+Vv1X7brMvI/VjuG2c94CTvrRzQGx5j8XgJiwX3d39waPx0M6H3/g9/sp5KpUrl69OtLT03OpWCxeLhQKv+/z+T5WLBb/t1wut/FZ1QGhxRP7ERWi4qUTcKeKVkImo37dvkPzhoJtHh/cZzcYcmFq6qlkmZidnpKzWlyPt65kLol0PsOqUehVvpjHq2ce4urNaXgg3axEgj4kMxKTFRXSIvzdz25DLEIb8Qe4enEIaFmMHful0/t3zt1D/6uv4ubSdSz+POqLMPYrn1cKx5IL7wMrUau2gJEFPCmMJeyJkjZvbSJ/l0UbfQRAem+wjbFRIV0POjknHY7GIy/Crpvs5O1bQLGIyFo+IUKa8oQmxhl7lxZdsd1MYTw78vyobE83D+kHD7h0x+oxmZ6Kz49IVyVAUwIuUQYm5vfGRkcPH3h2c/rv9K7QbRCBtkjXGu5waj8mb94EfF6htsrOn4cEf64xn2IFM+/jU5ymOzTHAk760QUg1h4/F4CYsF9PT8//UiwW/0CrSV9fn2ft2rVrfT7f1wDsBXCrWCz+876+PtICES61dgNCrDnFdBqR7p6yE3bhBQtW1NoQGTH6aP14UzgN8jlE1pVrcGjR1IpQliqnPp2ZYaCDSsQfAQGSr/+kF+OTeXiLFD4FvHv7MrxzeRBphVr5h/auwJ4NS0A5K8eP3kfPgfVYvkrSdfja984h0HcGtzrWM/arXWuWg8K21IX3gaVTbW80ivCKubAkLaFGQVdoVpPH8MXqkbp9i90qGBUCChQClY/H2Q2IXcXMutRgRWKA6inR2jLq5+Fhdss2H4XnR+Uc5FN5rZs7o7ka2UeptSNTbPPAoZI+ej5s9DTGoMOB5O3bCK9eXfYO6c2lAoAQKKbvwhpzOXJahyhPY/3P65hm3sfn1Ua1sG4n/egCEGtPgAtArNnP9ta1BkCIqjZPJ+kbXijLMbDbMDQGiR4qBc8m33xDNwRFS/ODwla0tA0ojCy2dXtZKBfpmsRPHOfSydI62S1KJs6WTLcfdf4IRmam8J9/cAWegg/eopRo/k8+vAGnbjzG5f6xknlWLI7hNz+8AQ+v3sWN849w+DN7EAoHMB5P4b985wSWj93C7aXdLPzqi+/bhK6OSvYi3gdWKyxJD4xV6zc5zITldQgorKfu9INCTIqZLDdcy8yczISWyaJ7oWUSOxGFkZHitXyTpyV+aWYuZuvy/FgGQJ6cyhN4U+cuGY0r3fpMIKrBbsXAyRM9HxmA8wCOERW22fUv1Pr0HNAtBtGMi9zyVgAQnYMP3nrZDdzAI3bL65b5t4CZ93H+Z+eOKGoBJ/3oAhBRL2jXcwGINfvZ3rrmAMjZMyx+PrpxIwKLKpl17DKQfCLb9KKU46+n8C2PRxSitClW8vbrxWLHiYp146YyalIR1Wh5rGwhh8QTAcKQLwjS/7h47xH+/q1+eIpeeAsh+H0e/M+/tgO3H03hm69LJ6Jy+d1f3or+s3eQejyKfZ85yP75rUsDOHr6GpaN30N/+zrUB6L4l5/dAS2KZt4HVissyUyokogPZXDnq29A5tFD7qaJcl4yAwNs81y/hy4M7SmUF5GbGGNhVbzCNs+r1yDQKokgqgGqlpYMr08rf+f5Udk3hV9RGBZPb0U9Hwp50/MPvR8ef6AUnkU5UPW798IXiegui0Iw6zbq0/pascdCaUtkFhRWKHrIovajmVs55Zrt1upZKPaslXmYeR9rZU3P4zyd9KMLQKw9US4AsWY/21vXGgChEAxiU4pu3gJRwb5qjEZsVQQU5A2XUfI49a+VtK4VikR146dOMBYfpaK0aAw8tU/lUkjl02xZdf46BH0BvHL2Jo5fG2QCjb5CBJ2LY/jHH96AXL6AP/nmBaSyc7kg79u+DJn7Y+jwT6H7QxLl61dfvoKx0QF0jD3A3SXd2LOuEx/Zr82iw/vAam2A9G6DqvEN27w/OeVlAGR4iBu2RBtougWh0DA7k7zNbNqk0Ltd8NVJLGcMvIyPsWeZ+ZXyZBIJtvGcj8LzYxkAoVP5WzfRdKREuic0RdL3SN3s0wR9ch6PfCPEBCw3b4HPgOaXJ2woNKkFXolAG307ops3I9AigVWjUgFAqsy3IpYz0j8inRy3zL8FzLyP8z87d0RRCzjpRxeAiHpBu54LQKzZz/bWNQdALl1AbmISsW3b4G8UE+yrxmjqnAxSJqYNUuPBQ/D4pRwLZdFKWtdLmJ0+cxrEmiSfhFM/uXhciM2J6s5kE8gVcmz4hmA9vB4v/uqnl3DnsSRA6M2HcHBTB963S2Ie+v5b/bh4ey4Mq6MuiHURPzY2jDFNitGpJP7j9y8gmIujfWIA99p68Jsf2IRV7dricbwPrFZYklEycjX+oRuNQjIJX0ODtInn3EDIYS2UwExq3nYV0bh5rRA72pwnb87dmjHSAgE1cLvmzvOjchzKTyEAomTtEpmHBKwvsPdGXZg6/bLlpVBKAuaRddpCn9TWbJ6UyPwWYp3s6AgTBKRQKD0BR+W81X4ksE3fo+gLG00tb75DAE1N7jmobOZ9fA7MUbNLdNKPLgCx9li4AMSa/WxvXWsAhOLoic40tmMHo/d0qqhZqdQ3IupxtTZaicuX4G+lGP+OsurT584yhptg25xOhlYIl97aptLTKKIAD7xoDNWjUCziD79xEqmCxIrlzQfxuXf1lNTLbz2cwt/8vK/UXSSRxaENi/CCf4CdaL954RFev3QH4cwMFk8NYWL5FvyLz26HV0egkveB1drISOFoIYRNahPo2UDeZNEGjd2IcfQS5LCWQGsLF6yYeaZEqUuVlLNy/yzM79QJtqn3eL2lWx01aYGZ+Zipy/NjGQAZHkbyVh8aD5pL4DfKbVIn4Wu9F8o5UJji9OmTpm9hzNhkIdSlfDL6dtTv3l26LTOaVwUAobybyUnuO6Huk+XrVNFuIdjsWZiDmffxWVjvs7oGJ/3oAhBrT40LQKzZz/bWNQdArl1legkURkMJyE4WZdK5OiekAoDMJjBz7mzZCbEeY4/WvzONiDv9qN81J0yntbZ8IY/p7Az7U8AbQDRQh6HxWXz1h5dQ8EoAhBLI//VndzO6XSr5ghSGRZS8nkIR0ekM2jvr0Z28g+QLO3H+9hjGknHUpWbQFh9Bx6GX8KG9+sJ6vA8shURlBgfLbhpIh8NbVyfE6iPiUxnk+BoahcKW5LAWEke0M8RJK/ROa/4sVGuo3CZEJhAnQgISn6yLguXJVMFeJGIvrTo8Pyrb0DtHAKRhv5QzJFqM6KWn3j6K2PY54U1Z2yW4tBywy2Np3TKKzqOW6tEzNXPhAiNL8AYlQgmjUgFABgaQGxsthfbx2st/r/bmRLR/t545P7r2qk0LmPmuml2hC0DMWqy8vgtArNnP9ta1BkBoI0tsLZRIbJSsaoehlHS5vCRxrb/rnehq3YxkRh4j8/AB25AZlUw+g9kc051kyedhfwhnbjzGP5y4g4JPygtprovgdz+9G9lMjiQqWHnlxD1cuD0Kfy6DcKqA6XoP1jzuw53Fa5H3+VD0FBFNzaA1Po73f/4TWLGkXncavA8shZComakopp0AY6hzhR2uYarzBHQopIpup3jK2ESTnLhyRVjcTXSS+elpxmalFWKk7EPJ+KT8dxaOt2oVI1SwO0yNtwaeH5XtCSAzALJ3P6/bir9r6efMsV4dgDcgbbIl0cJ63WeE3TbdloQcn+VCQGvm3DnhhH+1Hxmd8+NhxLaYo3Oe7xykZ9mH1azNzPtYTf9um/mxgJN+dAGINR+6AMSa/WxvXXMApK+Xna437NsPbyhkuz2UHSrpcvMaNxzKulo3JFq5HmyjpSGmJprMPJtNIvMk1CoWiMLv9eN7R/txsX8UBV+KTWnjilbsW96OuzdHS1OMJzLoezTBQrdyAQ9mYx6sGezD/bZVyPqlDWAsGceyTAq/+tuf1g2/onq8D6wWJbHdAnIyYPNRHlC+wChLjYoc1hJavty0PoJRv1p0zVr19QgJaNNNwIw0U4j5yBsK2xamxns5eH5UtqccpWRfL/eGTmtMdagV1ZEBe8PhIyVRSJ6qvNbNGm+Ntfh3sk3i/DkQJbFIqQAgRKc7OGA610nOq6pbv0FkWLeOzRYw8z7aPLTbnY0WcNKPLgCx5igXgFizn+2taw2AUJhK+uFD9uPsDUghRk4VRvm5aTPLNTFKpqXxtXJEtNiuqK7WZjQtGDYhCxB64GEJ6KTo/X9/9xImZtIoeFPsJuPI+nYExoroWNGElkUS4xLliXz7zesYm0ki7wOKXg9WD93EQGsn0oEwY89qmE3gpY4Qdn383YYm5X1gKSdj9vpVNOw7UOqHaWC0tAjpGoj4Uw5Z8zc1aWqtqPuQw1rCK1civKpSXFFkTK06ovotM+fPIriss0K7RnkzogdSqp0brx3Pj+r2dGuhRcDAG4etfbkq50njGeFpxTxPOQpmbF0BQARvU9V+q5a+l+d/9+9iFjD7Por16taabws46UcXgFjzpgtArNnP9tY1B0D6+0EsS2YF0aoxXPzkcdBpILFt8eLPSyxZCqE2Lb0PBkBYQnawbCMsogFRKBYQz0yzpfg9fsSCUcwks/iTb12QQIYng6Inh4OLW9ESi2LngZXwer3sb5Q7MjA5jvO3RjE1k0UQETTdvYqZxSuQqyMmLQ/WBFNYV59DPSd0g/eB1aIU5sX3m/WPnLRPVMZqW2r1RaFSFBInqi4tOh9RZiZiUKvbLIFZZVGe6tt9S8RbA8+PvPaif09cuQR/S2sZ+NQK0+OFALkbZG2Lq/1I4YZkq/qdxvlk6t54AFDU32696iwwX+9jdbNzW4lawEk/ugBE1Ava9VwAYs1+treuNQBCYQJEV9p45MVS6IbtRnnS4fSpkwiv60aguZkxLc3euKYbA6+lE6KleE5da2lisM0XKbwbhD9k81kkcrNsdiFfCBF/GDfuTeBbv5CSlwueLKLZHLZ3tGDXgVVobppL0ldqh8i5I9NnKf9gNQKti1h7URpO3ge2kEoifqqcrYioWINL2hFsb7fFXTJtsb+5WSi5nULopk+fFlaXFp0kU6U/+qZhSKBWvoPcP1vHlcvsRk9roy46j2rq8fxYTZ9abRgBQSSC8Mo5XRn2rI3NaaBIz59x8rSUI+NDpGuNXVN7JvqpACDj40jdvmU6V8ZusdBnwrjzuIj5eh/ncUnP5VBO+tEFINYeKReAWLOf7a1rDYAwQbm7/Wg8/KLttlB3qMzh4NHkarH9KJPYlX1rnTQSAxbdohglUydzKaRVAoSvnnmAY1eGWPfeXBaLi0UcPrICXWvaEPaHS8PKoVv0D7J2iMTG1YHgkiUSAHn4QIjSlveBLWQziB+bE3GkvtVjWXWefMvib25htwpEa2xUGCg6eRJ1PettA0HyeHp+lv9uJDI5B04OsrC14OIlCLYvtWoeofY8Pwp1IlBJa2PLNE9SyTLAzSNi4CWpC0zlmayi9iPvW6VnhOTNm4DXY2uO1DNpcIcWNV/vo0PTd7t9YgEn/egCEGuPmQtArNnP9tY1B0AePZIAiEk9gmoMx0J2Olcg0NYGrcRqdZ9K2l6jk3GtzZcIBetMJoFcsVyA8C9/fB0PHs+A6K7qZjJYvjSCD350DUK+IOoCdWyKSupeOXSL/l194s4LgZHXy/vAzt0GzTEcaeUBVOOT0qY+mcTM6VMsr4RASGjZMmMA8kTZPrpxI2OcsrPwFLyZWOH9e7oK7CzXaONmpPpvlwFCO+eo1RfPj3aNr/VcaTF+8d6xmUsX5hWg2bV+p/upACAa+TUic+CRAIj04dap3gLz9T5WP0O3pYgFnPSjC0BEPKBfxwUg1uxne+taAyBEMZm6c4dx5DtdlKf2LOn5br9hXDWF4sR272H0wFohWfJ8eUrhlDBOAMb3JH+D2jHNiAwJEBaZ8jndYuTyBfzRN84hly8ilMwhkM3j8PuXo3t1M3weH+qDUgiWMvwq4o8wcEJFTY0ryoIj8oGdPPoGGvbshTccYWNNnz0DSgC3a/MvJ39TEjrd4PBuDeSbhujmLQi0tNj66LBcoZ4NYAnxGoX8nZue1lWmZs9Z+1IWAicDXlsnqNOZiB/tmAcxMmVGRhDbsrXUnVa+Cy/PioUMrpQoi90yZ4EKADL9JKzPpGbLfLOwuT4st8B8vY+u3Z21gJN+dAGINd+5AMSa/WxvXXMAZHiYJVg27N1nuy3UHSpPXNkp9oP7qN+hr9PB9A527GCicqUwJEVSegmAPHqE3MQ4ops2l4aU4+TH6hbh22/cxEwqjT0bluClbR0s14US0FNPwq+C3gC73Xj4eAZf+/F1+HIF1CWySIX9+K1fX49AQHrNGoMNrK1W+BUDIKpkeJEwMGon8oFV57+wcLauLgRaWm3xmwwofLEoQstXlMLI9DqXQ+Ri27Yz7RA7y/SZUwh3rdFdG9nZ4w8g0tWlOax88kwgN7y6C4FWe2zEW6OIH3l9iPxdSji/WwbeZ86fQ7BjWZnfGKXxmdMsv0urxE8cYyKSRArhFn0AYhTyZ2Q3u8VCXR+Zs8B8vY/mZuXWNmsBJ/3oAhCz3iiv7wIQa/azvXWtARC2mSGGl13Oi5EpQ5RISTsz8MiQW3/qnbcR27qN6ToYKadrCYVRfLu3vh5/fmoco4k48ORN+cDuTmxcLZ3YD92LIz6RZgroAa8fl/vHWPiVN19EwedBrKMe/+ija5ApZFn9+oB0AyIrpyvDr+jf1bH5okmoIh9YNQOYMqHfjodYBhTecAiRrrUsTI5X6Famfscu5h87Cy+8jAHZtsUsvEqryDckhZmZEumBnfPT60vEj3bMQ4uWmSiqI+t6GMGDXIxAO9VhyulPVOPtmNez0ofajzzNIr112y0W+qzYd77WMV/v43yt53kdx0k/ugDE2lPlAhBr9rO9da0BENqk5CYn2YbO6aIMExERCmSb7k2bJN0QA+FCUnJXC4UR2Lmf9OOb1yZR9Ep5HlRCfh9+44M9yCVyuHlxBA3NYdSFIhibTOH0jcesTtEDpMN+7H5hCd61qx2pvCRIWOevQ6GYL92cKMOv6O8sFyWdYonZVLTYubRsLPKBVQMOSYxuvW6YUjW+pJA3Spqt27BR6NaAbB5Y0g6PIrStmnHVbXgMX3p6MHI/Eqi+i2I+V6J9tmNevD5E/MjrQ+TvWmKNmurohQKm3jqqySimlVckMvbzUEftRy0WOhE7zDcNtMicnqc68/U+Pk82fRprddKPLgCx5lEXgFizn+2taw2A2G4Agw6VwnBacezqpkrdENKdIO2LxoOHKkbQ0kCgTezL12dwI1OQbj+KgLcoCS2uWlyPNYEAYo1hbN6xDNkc8NUfXEV8NlPqO+j34suf2IRYnbdE1Rv2hZAt5JAv5lk9mf1KbkSMYhR3H31hI/sn0SRUkQ+sOueDhc+8sAn+hnIdDCv+pDCvYi6P2NatID2Qp1WYyKJOIjy7qXn7aFk+jHqeMlj1eH2aWiFOrUvEj3aMXdLIOXiICRkagQktYEJzEBV8tGO+tdZHBQBJpxE/cdw0VbnRc1xrNqnF+c7X+1iLtqmlOTvpRxeAWHsSXABizX62t3YBiL5JlUmZkkZGed5GBQA5dYLR6NJmWCvsRK6vxfZz94138J0bM5iOSknbnoK/BEDCs1msa4vhIx/bgFA4gO8d7cel/rGy4T+6fyV29iwuY7yiZHXKHaHi9/oRC0iq6HJRgyotvQYt64h8YKUE/qVM+4MKMT1FN22Br77etmeY+ixksiwszu68DjOTNFIwzz9h62o4fERXt0YGKQQ663faHyKmtxYRP5qxg15dxgj31pslECaf0BOVNuUoKYtenoeU13BBE9DbMcda7qMCgMg02Br5Z0brTFy+BH/rIoQ6tEMFa9lGtTD3+Xofa8EWtTxHJ/3oAhBrT4YLQKzZz/bWLgDRN6mSKlREI0NKRl7LWJayExNI3exD/Z69FQPkpiZBm/2GvftLf/vpX7+MC5kAEhEJJHjzIXjghT+bR2Q2h1wsiN/67FYMj8+WhAflxms6GvDr7+subeam0nHGlqUs6vAr+hvLa3n0ELHtO1hV0RhwkQ+smuJXT5TRygNNYV2Ua0PEAHYCG7Nz0lK2l/tgYPPWTc3noGzjfeoECskUE4/z1Un0yU4XET/aNQdGNbxJUoJn4PzaVU0mO6X2jnJsep+SN3vRsMd58gm71jxf/aj9KBM00O0r3TiJFimUkM8oJ9qfW8+cBebzfTQ3M7e2GQs46UcXgJjxRGVdF4BYs5/trV0Aom9SpTaHFnWuuqVSWTw7Nsrogut37a4YgNGNXpbUr6mMx1P4wX/9LoaaFyEZqoOn6MOGZYvRd28C0ZkMcn4vUhE/OhfXY2I6hZnUXI5IOODDVz65CQ1RiVqXipL1Sv43dfgV/TujFr7TX5ojiwFvakJo2XLD50zkAyuJxs0JBDqRQEyAL5+YRf3u3Yx57GkVIw0XujnLjo6WUdBqzZMAW3ZsnLG7ecNzApJOrknEj3aNr2QK02LFksdR35zJ/84TKbRrnrXYTwUAkXNp9h+ANzj3XeCtzW6xUN547t/LLTCf76Nre+cs4KQfXQBizW8uALFmP9tbuwDEAID09wP5HCLruhmNaCFZrtxcAUAUwoVGG6Z8IgGiIW08dJh18cqJexh663UMtHQgHYwg4o3gdz+zHd//4TU8GogjEQui6NV+dT5xaDW2rV1UNpXZbBKZwlx+iFb4FTVQ38Soby30LCPygVVrCig1Uux6iEkoknJtGvbO6Y3Y1beZfoiVrZDJaKrYM3BSKLBnyKhQvfTDh+xWwMym0cw81XVF/Gilf2VbJbBIDwyAQIhSF0SuK+UhNFeAYCkEcoyF8bmFv3FViqKK2ovH5ibaj1uvOgvM5/tY3QzdViIWcNKPLgAR8YB+HReAWLOf7a1dAKJvUiVLlNEmU+5BeYJoxJqlZKmZTeXwp985h2VDl/GwtRNZfx0OvbASWzoacfXCAK5MzGIiKyWRq0tPZxN+5d1rK+LoU7l0iQmL2tT5Iwg+ER9U9qGOqxdVmhb5wKoZtarZEPEedrI3hfM07NsPbyjEq+7Y340U5NmtUkMjQp2dhuPTppxC/syGzVhZlIgfrfSvbKu8ETMC83p5SCIHAHbNtdb60fJjNYDfbrHQWrPj057vfL6PT3utz/L4TvrRBSDWnhwXgFizn+2tXQBiAEDu30MhkWDiZ0nFbYheCyUdq9GJLZ2WE2Vv4+EjeOvyEF672I+uoRu437YKRV8MX/nIFvSdH0BLWxSRJVF8/Se9FUNGgj78009tRiwiMWUpSzafLTFh0b9rhV/Rv8sJ0rLwm2gIhsgHVilqKGt22H26T0mzlGMxn5t2Ld+nNYQl5Xqi6t25yQnMXLzIngm7aYL1nlcRP9r1wVHmU0n/34dI15qK7vWooEUpou2aby31owlASDNl+074ouKhiXr5N7Vki1qe63y+j7Vsp4U+dyf96AIQa953AYg1+9ne2gUg+iZVJp4bxfnLPRDtbrCtjQnOqSlulaPISaLRfQfwZ9+7jHhmBmsHe3F38Vps6FiGzpAfxSKw6+AqBII+/OTkfZy8Plw20c+8uKYkUKheATFfxTPT7J9JtDAa0E5qLgm/Pdn0ioZgiHxg2a3A7CzTtZijXT0Ib6ASMFX7UNPtAuVXzOemXWuuRrddjFZ223au+CH5InHpEhPaUzNDVWsfXjsRP/L6EP278gbR6FZIrU0j9++qdOtbWhOAKERRRX00ffoUwmskEg23zL8F5vN9nP/VPT8jOulHF4BYe45cAGLNfra3dgGIAQBRxJ0nb94EfF7NU1u5ByWPvlHIiHwjcGfROnz/zF3Ak0XXQB8Gm9Zj29JFWNIewwtblzLKXSrZXB5//UovBsYS7L93dLfhYwdWGT4L6XwGuUIOpAXi8/o066pvJpRJ9Eadi3xg048eMsHI6MZNqJaVh/ew06aURB2bXnyJV9XRv+vl+5RuukzSoTo6WUXnIn60ay7K58Hopk1ZTzm2SxFrDoAwUdSN5nR3eIKZdj0Lbj/aFpjP99H1gXMWcNKPLgCx5jcXgFizn+2tXQCib9LM0CAyj4cR27JNEukLBhFetVq3wfSVyxhM+ZBqXoxV+Un4kddMTKYOJo6+gW8N1WEglYIvn8Py4TEUWjvx3hfXYtW61opT8Fy+gGt3xxEK+NDd2WTbKbkyVlz0BFTkA6u0nTLkzM7wIvJJdngIpCfxNEt2fAyp/tuo37WnbBq5eByzV69o0s0+zfnKY4v40a55ElAk3Rm6DaKNbmRdDwLNleKRerdJRDhAeTTBtsV2TemZ6UfLj0pRVNGFVtNGtG+3Ht8C8/k+8mfj1qjWAk760QUg1XpFaucCEGv2s721C0AMAIhi08QT6ZuYTuPn330Nj2ZzmIi1YqNnFh/ZvxLRJ+xH+XwB+ZwkCkjl1o9fw/dGgsj7vYjO5NE4G8fuj+3H1o1LbPexUYdTilAN0RN8mOSpAAAgAElEQVRQkQ+s8lagpGJ9pFJ4zspiKSyOgE7jQYlN7GkVuukh1i+i0FUWtukeeFTSWXla89MbV8SPds1ZKb5pFJbG6Kvv3kH9znL6atFn06751lI/Wn6cPnUS4XXdmiBPb23V3JrUkp0W+lzn831c6Lao5fk56UcXgFh7MlwAYs1+trd2AYi+SbMjI0g9uM+E7ozUrulm4uV3bqN+7A6yfj/G6xdh8cQIXtrRhU2HtmN0eAa9V4aQU7BZ3b/Wj1FvEHmvD0VvHmvyj/Gp3/mcbTcbog8KO/Xs2cD0PyQV6o1cVXGRD6xSY0TJ+iU6L5F6lOhOJ+aU3P40C9EqUwKvx+ctn0ahiMCSJajrWf80p6c7togf7Zo40SVTGFX93n0gAKJHSCCBuXKRTpqDE0KWdq3tafejCUDOnEZ4dRcCra3C04sfewfRzVueqqin8GSfwYrz+T4+g+ZbMEty0o8uALHmZheAWLOf7a1dAGIAQBRCfSxxtrERoeVzdKrZXAE/O30fp/oGUfRmsXhyCDmfBECWTAyisXER9u7ehIH7k2hdHMPS5Y1ssJHJJN75/msYbWhGKhhGIJ/DxxZlsPlTH7Ldv7wOlcw3ohsQkQ+s8lYgPzuLmXNn0HjoCG86pv5Oie6ZwcGKmwdTndhUmUAW5dSoizcUhsennYNj09BVdyPix6o7VzUkxXpSrq/fsxfTp0+ysDmtZHuJGvp82a1WKVfpKdMt22ULu/vRBCBnzyC8ciUCi9qEh3NBnrCpHKk4n++jIwtwO2UWcNKPLgCx9pC5AMSa/Wxv7QIQAwAyMYHkzV407NkHZYI5tRidTOI7b97C0NQUih5p49k2NYwCPBhrXIz28UHkCk1Ys2oZtu1Yho4Vc3kbf/fmbUyeeRsjjYsxG4qirejBF9b50PQUTvJJEDG4bDmCixezk+nY9h1c6k6RD6x84k1q71qbSjseZGIpIwBSv7s898KOvp+HPkT8aJcdZCa06KbNSPbdQMP+g5pdy0CFqKFlgOJUDpFda3va/Wj5kTHaLetk77VomSLq3h074asTp+4V7dutx7fAfL6P/Nm4Naq1gJN+dAFItV6R2rkAxJr9bG/tAhB9kyqVwpUUu4NjCfz1K1eRLKQBT7HUQdvkGPweH0YjjVg0Po2sP4Cm7k78xkf+//bOBLyN8z7z7wxAALwlSpZE6pbIGUrUacuW5StO4qROaifpOkk3aZLGadxtmrZP0t22eZJ0u92m2+3TY52mbtI2V9vdtjmczTZx66ROLMuWZEmWrMOUOKBEXZR1khJPAASIb59vSNCkBAIDzAwwGL6TJ08c4zt/78xw3pnv+//XT5UZGE7gi997Fc3XouivX4DRcCPevnYBNoWGyvIgLecl35KGW1ow8OILqLvjTgRqsoftzUzCyg3W/Opx8ID5pnu6GXHyBJbJ++TG5vo7tjnZ7Jxpy4qOTsKQD7jhFSuRvHrllj0emX4yEdOkcc2EbJZL3OQDtdNf0JycWznbympADr+KUHMzQouXWB7ajV070XDXdqiRast1WNA5AqW+Hp0bOVuaTsBNHWlA7J1rNCD2+DlemwYkhwEZGsTosWOQD0PTkwz+3109OHzmAkTGfAgFYTWMR5YHcO1qAodfT6F27BqG6qowUr0Qv/ruLVg0b+KP+o/3n8PurnNY2ncGN2rnIVmzCL/xlhXAxd6yPEhPz1BtNVu5lRvs1Mbz+x8wv4C4EQ1qemQlxy+MOdCgFR2dxCCXYMlljPKLRt2mzbM2fXMW79n2hTg5tkpuK6sBmZaTyOrczOufy9ys4nK8XKmvR8cnwAZNAm7qSANi7ySjAbHHz/HaNCCzI52+dGh67oInv/Mq+uMTif4UoWJJYyPe+6ZWoPc8Dr/Wj6MjCuoGohiom4+RSCPuWLMM77pvNeJjKfyvbx9CTMTR0nfe/G391o146+pqjF3oLUu0JBm9Se5TCK9YgYEXd826ObjQNzzTc3+MjwxDRhFr2L7D0fNXLuuRS3YKyfbs6AAqvDE3/1BmQyND6coMm1IvmaBytuPmvUjJa1cRP3u2LAa9EiTOpuPIa0cRbFqAcMtSS1O4OSeQpUos5CiBUl+Pjg6ejU0RcFNHGhB7JxoNiD1+jtemAclhQGIxDB/YD7keXT48RZavQKy2EX/+nYNIq8kJA5KuwifftRkLGiLY969HEBDjGFm2BD3PP4++hgUYidQhJML41Ptux9FT1/CjQz0Qyjia+y9gLNSIj3zoragd6Z/KN+K4wHkajJ3sBhQFkZWrIEPyNt57H5RgMGctKzdYIQTkm2z5RjUdGzXzqMi9NDy8Q8CKjk6OVkbBSt24jlDLUlSvbZ216ZtDyMpldmNXr+b8auLkOCutrawGJEvQjFzzyuzRmb70rdI4VPp4S309Vjovr47fTR1pQOypTgNij5/jtWlAZkea2RArM21nsoSfHFLxzy+cMEPnyqNarcbvfHAberquovdELzaurkK4vR1P/9W38XpjE2LhWvMryX3rV+JYzzXcSEx8OZGb1JctW4p3PXYfEhcuIHW9H3KDbqkPmXNBLomJrF6NwT170Ggha7fVG2xmU2s6nkC85+QtifpKPVf2N5OAVR2d4pbJXF+9Zq2ZVHC24+akgzLaWXpkBDXr3thL5dSY/NBONh1zhQ3PNud0Mgn55cnKCwg/MPPiHEp9PXqRgR/G5KaONCD2zhAaEHv8HK9NA5LDgCTHJh7K738AwzKs5dpWPH9yGLu7zk7s/xCAtmQxHtm2HEf2n8fyBcDimiRqOzZg59//P+wdq0YsHDE7CIyHkVbGIdSU+f8X91/Fo29ahxVb1iNx/py5T6IcD1iZviNr1mLw5b3m155s4VGnU7J6g80spUmPJbIml3P8ZGaDBRGwqmNBjeYoLBNHJnp7UdPennNz9PSAD7I5WQ9pgeq2NqeG4qt2shqQrhNQq6vNL5tWDkYas0LJ3TKlvh7dnc3cbd1NHWlA7J1XNCD2+DlemwZkdqTT9zEMHXoFNZqOb+5+Hef6+8xK8svGgxtWomYoiVAkiHXLVIybXzI2ofe55/EPZwRi4YnlTLKsQHoiDpwANipxPHLvWsi3wfEzZ5BOxMuSsC7x+gWk+vrMh7vB/fsw74EH855jVm+wctOxTMInksmphI55G2eBkhGwqqNTA5JfMuKnT5vJ7qqammZtdiIwQj3Cy1eYZTL7lCKrrD1MOzXeSmknqwGJGmYUMZmM0MoxFTTCwgsIK+2xTOEESn09Fj5C1rBCwE0daUCsKDB7GRoQe/wcr00DksOApNNTG7PNuPpt7fiTH0aRVBITpiIdxNvWtkCMJrHtvpUIDFybWqsulx89OzgPndcGZoTqzdT7QGs1Vi6uQ3VrG2I9PcD4eFne8GYiSVVrGoYPWQt1avUGm0lyKNeXl2uTveMXjI8atKqjU1OWezlGo1FzM3mgrm7WZuV+oekPzxM5eOYjvHSZU0PxVTvZdIx1dwMB1XzBYeWQiTStvoCw0h7LFE6g1Ndj4SNkDSsE3NSRBsSKAjQg9iiVsDYNSG7YmdC00oBcX7waX3/xzNQyqlAiiHuam6BvWIylK+dj7NIljF2+hLrNWyDrXV/VgW/u7J4qn+lpYU0DPn57A5BMml9VMhvBc23MdeuUSPZdM5dH1ejrzFDDcg14vsPqDTaT5BAibbKRXHh4h4BVHZ0asYxmNdLZmTfS2oQhT6G6TTO7Ns+jlqUILV7s1FB81U5WAyKXrQlhvuCwckzP22OlPMs4T6DU16PzM2CLkoCbOtKA2DvH+AXEHj/Ha9OA5EaaSc4nH4I6q5bgR12XJjKfC4HmRBj3bFmKTduWmfsmxq5cMd/0127eYn45qd9xD772oyh6r/dPpeBU0gE8ur0NG2piUxtrzTe+oRAiq1Y7rm++BmVUolHDMPefWM3VYfUGm1nLL8fAKEb5lCj971Z1dGpkMrGnaXLvz73P6OZN50MH9pv7r3It23JqjJXYTlYDcpOJyzeviWSPh8wgFDzKQ6DU12N5Zun/Xt3UkQbE3vlDA2KPn+O1aUDyGJDdL6Ju81YMHz6E54abcOTKhJkIx4EVoVq87/2bEKmuMhtJXr1q7nWQa9wzEWU6zw/gO7uMqa8gdcFafPp9W5C+fBEywZrcsF5oxBonT4JMlvKajg7LuTqs3mBHZCjQefPMML+p/j5zbwwP7xCwqqNTI5aRlhJnzuRdaigz3Kf6rpnXkTxuzgvi1Hj80k42HQvdVzaR88jaF1C/cPPaPEp9PXpt/n4Zj5s60oDYO0toQOzxc7w2DUhupIN7d6Nmw0bz7eA3z4XRLybyf9QOApvXLsbDD+tTDST7+hA/3TNhQCYjSgkA3/ppN7p6+6AKBe99UEPHqiZMz22QeVAvxxr3zNKLmg2bEO+Oov6u7XnPMas3WBl2Va2pgRIITJmtvI2zQMkIWNWxZAOa7Gjs6hWM9Z5H3dY7YOaTefEFNNy1HWqkutRDqYj+shqQAkMXp4YGMfraMTTsuLci5uzHQXr1evQjazfn5KaONCD2lKMBscfP8do0IHkMyL695v6IK/sO4OsXwhirkpvPBRoGFDz6M+ug6be9YUD6+xE/dRI1HRsw/MoBM6StPORD1OXrMdRVV5n/lYfcKzJ28SLqtmzFzWFHHRc5R4OZ6De1HR1mNK76bXfm7d7qDTbWHQUCQXNDsXzAqV3fkbdtFigdAas6lm5EEz0lJ6+j+jvvAvNT5KefTcfE+fMFXXNyeZx8YdCwfUf+DlnCFQJevR5dmayPG3VTRxoQeycODYg9fo7XpgHJjdTMyry2FdHn9+LpwXqkqhSE4gINY0H8yhPbEQq9kTXc3E8RNVC7fgOGj7yKxntnX0+dWa5Vf/sdGD78KkLNLWXZZJvJgFyjaZBLX2SEonyH1RtsrOcUMJ6GEg4xkVw+qGX43aqOpR7a9Lfx5he6aWa+1GOphP6yGpALvUhdv245uWnm3tVw192VMGVfjtGr16MvYbs4KTd1pAGxJxwNiD1+jtemAcljQF45gPCKldj3zC78VFmI8YCK2kGBxfMb8NEPbp1ROTUwgNETnahZvyHvhu5kfx/iPafM7OBDMsnhypWoWvjG1xTHhc7R4I1dO80N8DIfSN3W2/N2bfUGGz97BulYzEyIJrPKy5wgPLxDwKqOpR7xdNORGhzMey2Venxe6y+rAblpH02+MU//6pSvLH93h4BXr0d3ZuvfVt3UkQbE3nlDA2KPn+O1aUDyGJBDBxFubsaz33keB+ctBYSChgFg05bleNsDM5N8Zd7cmhGlogZyvU2c/sax3FF+Bna/iNCSZjMbu5VQuVZvsJllIAFpQCZDDjt+ArPBoglY1bHoDoqsmE6OYXDPHjMikwzUIPdVWVkaWGR3FV8tm47TQ4JbmWBm/xo5W6HlThmvXo/uzNa/rbqpIw2IvfOGBsQeP8dr04DkRiqXR4nG+fiXb/8URvNahBJAJKbgscc2Y/XSxhmVJyLJvIqa9vV5H5qmv9nNZAw3I0aV4RjctxfBxnlIj42hbtPmvCOweoPNRDNSa2vNpVgy2zoP7xCwqmOpRywyCUDv3mEuI8rk1in1OCqlv6wG5PJlM9CF3GNm5ZA5WuJnz1pagmmlPZYpnIBXr8fCZzK3a7ipIw2IvXOLBsQeP8dr04DkMSBHD+PyWBB7ntuH7qVtqB0SUJUgPvXEDlQF1ZkGZHTEzCYuN63LcLxyf8dsR8asyH0imUhbwfoGx/W10uDQK/uhRiIyt7ulNeNWb7CZLOuB+npzGOVItGhl/nO1jFUdy8Fn4KUXzeWAqf5+pAYHzHDVPLITyKbj9D1mVrhNjzxmpTzLOE/Ay9ej87P1b4tu6kgDYu+8oQGxx8/x2jQguZGOvHYUR3tH0X3kNZxa3Ib6QYGGJfPwy++/Nav3eCyG4QP7Ua3rUxGuZjUgk2VlpKzMw1ZAfikowyGzvMtDCUcsRaqyeoPNZFkPNswDAgFUr5m5ZK0MU2WX0whY1bEc0AZf3mMmx5QGhMv3ciuQ1YBMhgS3uqQq87LA6heTcpwTfu/Ty9ej39k7OT83daQBsacUDYg9fo7XpgHJY0A6X8Nzhy/i+oWz6J3fhkgM2HDXKjx898pbKmZC2sqlRnJDdyaRWrYeMmVNA1LmPAcyDHA6HkOwoRE17evynmNWb7CZfS7BefPLluk972TmcAGrOpYD0dArBxBZvQbSxMowzvKfeWQnkNWATAtlbIVboXtGrLTJMoUR8PL1WNhM5nZpN3WkAbF3btGA2OPneG0akNxIh4934ls/MRCIX8eVmlakVRWPvqPDTCZ48yH3UAzu3YPI6tWQGcZzLRvJ5DdouOdeM9Nzw457zIf0chwyEaI0C1W3LUKN9kZixdnGYvUGm9nnEpw/34yEFVm5qhzTY5+zELCqYzkAToSmbkby2jXTGIeXLy/HMCqiz2w6mubfMNCw3VpY3emJUSti0j4cpJevRx/idm1KbupIA2JPNhoQe/wcr00Dkhvp6weP4Ae7ulCViqE/vArxmir8xgfuREPtrWZBpFIY2P0SwstXQCTi5hKS2Y7MRluZbE1GwWq89z4owTdyijgudI4GZQIyuQQj3NKC6jYtb9dWb7DjIyNmBvmqBQsgN6JHVtz61ShvZyzgGgGrOro2gBwNj7x2DNK4SgMSWrwEoSVLyjGMiugzqwGZDAnecPc9luaQeP0CUv19qN2wyVJ5FnKegJevR+dn698W3dSRBsTeeUMDYo+f47VpQHIjPfyT/dh/9CSUpIqB6iUILG7Ap9+fPVdGJqmffJCX2c/zfU248cJOc6OtfEhvvP8BKOrMTe2Oiz1Lg7GT3UhcuIDwsmWWNopbvcHK3B8ywlfVwoV8i10qMQvox6qOBTTpWFFpiuVXM7mZWi6/kiaWR3YC2XSUX2BHjh2F/MJq5UjIxIU3bnCzvxVYLpXx8vXo0pR92aybOtKA2DtlaEDs8XO8Ng1IbqQ//t4unDt9BunxevTVN0FbvwyPvWlt1kqZrxqhRYugVFWhujV32NmBl3ahZl2HmWhN7gUp1yHzLMTPnTO/3FjZKG71BpvJ5yDfZMsHyPDSZeWaIvvNQsCqjuWAJ00xFAXJK1dQ07EBwYbyRIgrx9wL7TOrAZkMCS6j7Fk5EufPISWXja7vsFKcZVwg4OXr0YXp+rZJN3WkAbF32tCA2OPneG0akDeQpoVALJGawfjpf/wpkv2XkUrPx5UF8/D2HRq2r188qw7yq0bVgiaoNXV5H+bl3o/ImrWIneqG1QcFx08AAPFzZxE/fdrMxi4zouc7rN5gM4ZMhuGViQ7llyEe3iFgVcdyjDh+5owZGEEakLptdyJQU1OOYVREn1kNyOgohg8eQOP91l5syHtAenTUUhCKioBSgYP08vVYgTjLNmQ3daQBsScrDYg9fo7XpgGZQPra6T78YE8PEqmZBmT+0BXUjY4iiTpcXNSEX35kC5YunD1croxoFahvgIz8FFmVe9O1TAAovwrIjOFyE3q5Drn+O9bdbW6et7JPo5Ab7MCuF6BEwma70oTw8A6BQnQs9ajlkiAZASt1/Ya5jEhGwuKRnUA2HTPLH+e96UFL2EzDJ/et6e2WyrOQ8wS8fD06P1v/tuimjjQg9s4bGhB7/ByvTQMCXL4+ir/5wTEgGUfV2EzENYkRVMcTGA8K9C1ehs/8wjYEcuzVkDk9ZFK/0OLF5pKmXMfQ/n2ouu02yCRgDXdZi1bj+AkAmJmmR7u6UL1mraVoQ4XcYAd2v2gmOKxubTU3E/PwDoFCdCz1qGVY2PjZiYdi+RZfUfinYzYNshqQRAKDL8sXHEvNpWzTj0BDA0K3LZrx7+QyTOZbKfVZPrM/L1+P5SVTWb27qSMNiL1zgX9F7PFzvPZcNyDj6TS++sPjuNjXj7rhNMYDCsS0s7R6bBR1sUGkQmk0bL4DH3hr7ihRclkVAirCy1ZM/PHPcQwdPGBuzk4N3ED9trsc19Zqg8lrVzHS2WmaBCv7NAq5wcqEcunEmBkRTO6N4eEdAoXoWOpRy68fMjy0GqyyvJG61GP0Sn/ZdJRBMBJnz0AGxphxCIGxSxdRt3kr5NLIzBHrOQWMpyFzGPEoDwEvX4/lIVKZvbqpIw2IvXOCBsQeP8drz3UDsvPwBTx/+DRqRyb+UI/UqVDwRjjchpHruG3wIiJNC/CWn38YCxojOTWQeUDkH/3qtWsRas6950FGv1LCYcjlEvW33+G4tlYblDkDho8cMUPwWtmnUcgNVoYYHh8dRW1HB6oW3mZ1SCxXAgKF6FiC4czoQpry4cOHzb0fMlQ1j9kJFKqj/LKUvHoFdbdvm4q8Fzt10uygem0rUZeJQKE6lmmY7DYPATd1pAGxd/rRgNjj53jtuWxAXr82gq/+6zEE4gmEEwIjtSoWNs3HR96uQ1UnTtXk5UtInoyiZtFtOTObZ4SR+zrS8YS5mVMuw8p1DB89DAgAQqBuy1bHtbXaYGpoEMOHDpnrv63kWyjkBjt06OBEUsYNGxlK1aogJSpXiI4lGtJUN+PDwxg6+AqCjY1lvTZKPe9i+itURxkcQr78CM5vmgqUIfeAyS+3chkmj/IQKFTH8oySveYj4KaONCD56Of+nQbEHj/Ha89VA5IaT+Ovf9CJa/3XUTuSRiKsYDwSxsffuREt0zaZywR9MieBDCMrH6LzHXJfx3gsZumN/8hrR5FOJKCGwpbMTb6+i/19fHQEQwcOWF4mVcgNdvjI4Yn8Ahs3oarp1uzxxY6Z9ewTKERH+70V1oK8LuQeBqvXXWGt+6t0MTpOJAk9iNqNm02TNxo1zI3+MucKj/IQKEbH8oyUveYi4KaONCD2zj0aEHv8HK89Vw3Iv79yHi91nkXt8OTSq9oA3rxlNR7cMnPfRmZ/hNwsbiVG/tAr+zE+MmrpgXvkeCfGBwfMqFm1HRsc19Zqg5mHPTk/Oc98RyE3WGmyknJ/zebNZmQwHt4hUIiOpR61SKUwsPsl84scIzPlpl+sjjL3x9jFi6i7Yxti3VEz8WNkZe7IfaU+D+ZSf8XqOJcYVcJc3dSRBsTeGUADYo+f47XnogE5f2UY33j2GILxMYQSAsN1KpoXNOHjj6y/JcJVsq8PI68dMzdQy43U+Q65bEQuH6nbsgXBxnk5i8svK9LgyL0RcslWuY7Mw57VZVKF3GBHTxzHmMzlYIFHueY/V/stRMdyMJIhnENLl3JfQh74xeooN6qPHH7V3IwukkmotbWWwnCX41yYC30Wq+NcYFNJc3RTRxoQe2cCDYg9fo7XriQDIpdN7Tt+Gf1DCWxtW4hlt9Xl5HHq9QEcPdmHsdTMSDC914YwPDyE2mGBRLUCEY7giUc3YvH8W5OdZTZoy/0cVkyCXNaQGhxC3e23I1ifO3uzfOuYeP11hJqbUaPpjmtrtUH5ICIf9mo3bUbV/PxfKQq5wcqlHeZb1q23M5u1VUFKVK4QHUs0pBndyIhyoWXL+FDskgGRzcoAEcOHXoESCiHcvNRSGO5ynAtzoU+vX49zQQMn5uimjjQg9hSiAbHHz/HalWRAnt13Dnu7zgNKGlVKCL/0zg1oXjCRFDART2F4MD7Fp/fqCH748imMIynTUNxyRGICQlEwWhPA225fi/s2ZU+Sl4nGY9UkDB9+FamBAdTL7M21sycslAOSkWcSvb1muN7q1vKGv5T5S2o3bsz71UaOu5AbbGaO9XdsQ6Aut2F0/ORmgzkJFKJjOVDK/VTh5cvzRpMrx9i81KddHWXSx9jJk5bDcHtp7n4ai10d/cSikufipo40IPbODBoQe/wcr10pBmRodAxPfvdVJJXEBAOhoLlxHp54pAMiLfDKS2cwlpjIYp4aFzh+ph+J8ZuyCk6np0yE3F26aAE+9o71U1GvbgYsIzjJSE7hlqWWYuTLyFZm9ubt26FGqnPqJZN/xc+dMxMWVq8p7+ZPOe7qNh2B6txjLtSAxM+cRvzsWUuGzPGTmw1WtAGRy/dCLS2WTPFcltruA4/8Ajp6vNOM2sdQ2eU7k+zqWL6Rs+fpBNzUkQbE3rlGA2KPn+O1K8WA/ORgL3Z1noFQ0lMMFBHAAx0rsbQqgGtXhrF1+wpUhQJ4Zu9ZHDnz+lRZxcwsOPPUk/+qpiqCX/rZDVjYOPtDdyYcaHjZMktr0UeOHUWyvx8Nd++AGg7nNiDnziJ++jQiq1ZV1ObPQm6w8ck5ylwOMqcDD+8QKERH74yaI7mZAHX0xzlBHaljPgI0IPkI5f6dBsQeP8drV4IBSSTH8eR3DmFkPHbL/MNjQWxpasAddy3HkqWNMM5dxz8+3wWhJs2y0nwsa2qCvnzm3oZQlWr+u/n1uU2CDKk7sRTE2lcKmb05ee0aGu+9D0rwjYSG2YRL9J5H7NQpM/a+XGpSKUchfygTFy4gdrLb0hehSpm/X8ZZiI5+mbMf50Ed/aEqdaSO+QjQgOQjRANij1CJa1eCAdl/4jKe2X8SQp3YTC6/fAhlHEpaoG4QqKmN4IkPbzOXXv3V949gcGxk6oNHtRLBJ96zGfPqchuN2bBnQtRGVq5EZNXqvOrI0LrJq1fReP8DU1mGZ6uUeP0CZAKw6rY2c4lXpRyF/KEcu3QJo0aXpS9ClTJ/v4yzEB39Mmc/zoM6+kNV6kgd8xGgAclHiAbEHqES1/a6AUmnBb70vSPoiw1OkBEKaoM1GB2LoTo+jkBSYKQ+gB3rV0LuEzl27tIbS6/SQbxnRxu2avlzW8xqQJJjGNyzB5HVqy1F4zHDzl69gnkPPJhXyczDudUM5HkbLFGBQv5QSjMmTVnDPfdArQqVaITsxgqBQnS00h7LlIcAdSwPd6d7pY5OEy1Pe27qSANiT1MuwbLHz/HaXjcgnWf68e0X5JKqiQ3mSjqIj759A378Yg+GLw1gtBZIhnw0Ch8AABgDSURBVBSo6SoI+Z9MOaFAa16EDz6kQVGKP+0yOTLkJnG5DCvfId/2m19A7rs/X1HTqIweP46a9esRum1R3vJeKVDIDVbuh5H7YqwsSfPK/ObKOArRca4wqcR5UsdKVO3WMVNH6piPAA1IPkK5fy/+SdBev6w9CwEvGxAZneWrzxzH+f6+iSVVAlg2fwE+8jYNL/30FF4914eh2skcH2LmPvPaQLW59Kqhxt5bd5FOY+DFXZZDVMq8F6m+a2jYcW/ecy6T5LB2wwZULViYt7xXChTyhzITxlgaMiUQ8MoUOI4CwykTmHcJFHI9encWHBl19Mc54KaONCD2zhEaEHv8bqm9atWqSCgUekpRlMeEEHKX9p9Go9E/s9qNlw3IuctD+Nqzr72xoTwdxHvv16BcT2BwII70gmr8++HTU3tDMnOWX0nee7+OjWsWWMWQs9yNF3Za3qchN1wnpQHZviNv38nr1zFy9IjlBIB5GyxRgUJusJkoYlb2xJRo+OxmkkAhOhKadwlQR+9qU8jIqGMhtLxb1k0daUDs6U4DYo/fLbV1Xf+SEOKBdDr9uKqqKwH8naqqH+vq6vqula68bED+6SdRnLhwWe46N6fSFK7Do5uXo/d0Pzq2LkXTolp8899O4Oy1PojJMopQsX7ZYrz/za22ll5NZzfw4gtmosBQc0tepDLxXqq/HzLsbL5DJiyUiQvrtmxFsLExX3HP/F7IDTYdj2Fw/z5Le2I8M8E5MpBCdJwjSCpymtSxImW7ZdDUkTrmI0ADko9Q7t9pQOzxm1F78+bNtfF4/JqiKO/o6uraKX/UNO3ziqI8ZBhG/l3QALxqQPoG4vjL77+K8clwuuq4iq1N8zEvFMRqbSFWTH7d6B+M4yv/chTxtMyCrqA+VINPvHsT6qqrHCM9sPtFVK9tQ2jJkrxtxnp6kLreD5n5O9+R+TpQaVnCC/1DmRoaRLC+IR8O/l5iAoXqWOLhsTuLBKijRVAeL0YdPS6QxeG5qSMNiEURZilGA2KP34za7e3t9wghdgWDwZrOzk4z7Xd7e/uDQoh/MwyjFsAbWftm6beUBiQQUBCqDuPG9RGkxnMPTSYePHiq1/yyEUwKNIwGsG3dEmzY2oJ5TTMT2l24NoLnXjmHgKri4btWYOG8/Nm8C5FhcO9uRKQBWZR/o7jM/J26ccP8qpHvGB8dxdCB/ebXkkpK0ufmDTYfM/7uHAHq6BzLcrZEHctJ37m+qaNzLMvZkps60oDYU5YGxB6/GbXb2toeU1X1KcMwpl7Na5q2DsBxIcSi7u7uq/m6K5UBkSbh6V3dGIwlMD6ehphYVTXrYUa0UpKIxIBwAli5fAHe/bPrzEznpT4G9+1F9ZpWVN2WP5yvzPxtGpBNm/MOMx2PY3DfyxWXI8PNG2xeaCzgGAHq6BjKsjZEHcuK37HOqaNjKMvakJs60oDYk5YGxB6/GbV1Xf8wgC8YhiH3fpiHpmlrAJwSQizv7u7uzdfdtWtDQlXdl+WrP+zEuYtXUT0GyNweVg41LaCmgWQkhF//8J1oLDKZoJW+cpUZ2PcyalpbLUWqip87Bxn5qW7jprzdpsfGMLBnNxrvuRdqyF60rrydOVggEFDR0FCNwcGYaSZ5VCYB6liZut08aupIHf1BwB+zcPN6bGqqc/9hzR8yZJ0F4Tkorq7r7wPwpWxfQKqqqhZ0dnb25+sunU4LO3ky8rWf+f0vvvUqenovIhSzZj4y9caqVdzZsRq/8HC71a4cLxe/dAmhpiZLJiE1MoLxeALhBU2WxjF6vhc1y5dZKstCJEACJEACJEACc5OAUoqHNR+jpQFxUNzMHpDm5ubIzp07zUx97e3tbxZCPGMYRp2VPSCl+gJy4eowvrOzGzdG40iPmwusLJBQsPy2Bnz47e2oDgctlGeRUhBw8w1PKcbPPiYIUEd/nAnUkTr6g4A/ZuHm9cgvIPbOERoQe/xm1G5paampr6/vA/A2wzBekj/quv67AGQUrDdZ6apUe0AmHnisb0I3y6sKIiEaDys6lrKMm2tcSzmPud4XdfTHGUAdqaM/CPhjFm5ej9wDYu8coQGxx++W2rqufwXAfQAeB7BU5gERQjwejUa/Z6WrUhoQNy9MK3NlGWcIUEdnOJa7FepYbgWc6Z86OsOx3K1Qx3Ir4Ez/bupIA2JPIxoQe/xuqT35FeTLQojHAAwoivInhmE8abUbGhCrpFguQ8DNGywpl44AdSwdazd7oo5u0i1d29SxdKzd7MlNHWlA7ClHA2KPn+O1aUAcR+r7Bt28wfoenocmSB09JIaNoVBHG/A8VJU6ekgMG0NxU0caEBvCmKmqeXiKAA2Ip+SoiMG4eYOtCAA+GSR19IeQ1JE6+oOAP2bh5vVIA2LvHKEBscfP8do0II4j9X2Dbt5gfQ/PQxOkjh4Sw8ZQqKMNeB6qSh09JIaNobipIw2IDWH4BcQePDdq04C4QdXfbbp5g/U3OW/Njjp6S49iR0MdiyXnrXrU0Vt6FDsaN3WkASlWlYl6/AJij5/jtWlAHEfq+wbdvMH6Hp6HJkgdPSSGjaFQRxvwPFSVOnpIDBtDcVNHGhAbwtCA2IPnRm0aEDeo+rtNN2+w/ibnrdlRR2/pUexoqGOx5LxVjzp6S49iR+OmjjQgxarCLyD2yLlUmwbEJbA+btbNG6yPsXluatTRc5IUNSDqWBQ2z1Wijp6TpKgBuakjDUhRkkxV4hIse/wcr00D4jhS3zfo5g3W9/A8NEHq6CExbAyFOtqA56Gq1NFDYtgYips60oDYEIZLsOzBc6M2DYgbVP3dpps3WH+T89bsqKO39Ch2NNSxWHLeqkcdvaVHsaNxU0cakGJVmajHLyD2+DlemwbEcaS+b9DNG6zv4XlogtTRQ2LYGAp1tAHPQ1Wpo4fEsDEUN3WkAbEhDA2IPXhu1KYBcYOqv9t08wbrb3Lemh119JYexY6GOhZLzlv1qKO39Ch2NG7qSANSrCr8AmKPnEu1aUBcAuvjZt28wfoYm+emRh09J0lRA6KORWHzXCXq6DlJihqQmzrSgBQlyVQlLsGyx8/x2jQgjiP1fYNu3mB9D89DE6SOHhLDxlCoow14HqpKHT0kho2huKkjDYgNYbgEyx48N2rTgLhB1d9tunmD9Tc5b82OOnpLj2JHQx2LJeetetTRW3oUOxo3daQBKVaViXr8AmKPn+O1aUAcR+r7Bt28wfoenocmSB09JIaNoVBHG/A8VJU6ekgMG0NxU0caEBvC0IDYg+dGbRoQN6j6u003b7D+Juet2VFHb+lR7GioY7HkvFWPOnpLj2JH46aONCDFqsIvIPbIsTYJkAAJkAAJkAAJkAAJkEDBBLgEq2BkrEACJEACJEACJEACJEACJFAsARqQYsmxHgmQAAmQAAmQAAmQAAmQQMEEaEAKRsYKJEACJEACJEACJEACJEACxRKgASmWHOuRAAmQAAmQAAmQAAmQAAkUTIAGpGBkrEACJEACJEACJEACJEACJFAsARqQYsmxHgmQAAmQAAmQAAmQAAmQQMEEaEAKRsYKJEACJEACJEACJEACJEACxRKgASmWHOuRAAmQAAmQAAmQAAmQAAkUTIAGpGBkrEACJEACJEACJEACJEACJFAsARqQYslVeL1Vq1ZFQqHQU4qiPCaEiAH402g0+mcVPi3fD1/TtKWKonxRCPEWAFK3b42NjX32zJkzcV3XVwsh/lZRlB0AzqbT6U91d3f/2PdQKniCuq4/A+CqYRgfldOghpUlZltbW1hRlD9XFOWDAMYAfM0wjM8BENSyMrRsbW1dHggEviyEeABAv6IoTxqG8SSvx8rQT16DqqoeVBTl17q6unZa0U3TtIekzgDWCCFeBvDxaDTaUxkz9s8oaUD8o2VBM9F1/UvyhptOpx9XVXUlgL9TVfVjXV1d3y2oIRYuJQFF1/U9Qojr6XT6t1RVbVIU5esAvm8Yxm9rmnYYwDEAfwjgPYqifD6ZTK7r6ek5V8pBsi9rBDRN+48A/klRlL+bNCAKNbTGziuldF3/yuTLgA8pilIvhPhnAJ+PRqN/Qy29olLucei6vlcIcTYYDP7u+Pj4egD/KIT4UDQa/T419LaG8kVqOByWev2cqqpvnjQgOe+ja9asWREMBo8D+L10Ov2sqqr/FcC6aDS6Wb448PaM/TU6GhB/6WlpNps3b66Nx+PXFEV5R+aNgaZpn1cU5SHDMB601AgLlZyAruvtQogTqVRqSU9Pz2U5AE3TPiC/XimK8mEhxL9UV1cvPnLkyMjkb88BeCkajf63kg+WHeYk0NHR0ZRKpY4IIS4qinJcGhBd199CDSvnxJEaJpPJy0KIh7q7u1+YfPP6GXlZAvjf1NL7Wm7cuHF+IpHoDwQCG0+cOPHapIZPT16X36OG3tWwra1tvaqq0nzI59hNGQOS7z6qadp/VxTlgcyzTktLS01dXd0lVVXflXke8u6s/TUyGhB/6WlpNu3t7fcIIXYFg8Gazs5OuWwA7e3tDwoh/s0wjFoAaUsNsVBJCaxatWpeJBLZ3tXV9aNMx5MG5G8B/A9FUR42DEMuIzAPTdP+m1yOZRjGz5R0oOwsLwFd1+WXq0sAWmRhaUA0TfssNcyLzjMF2tvb35VOp78ejUYX3jwoaukZmXIOZPINep8Q4isNDQ2fGR4elktypJn8nBBiMa9H7+qo6/onhBDa8PDw5+rq6kYyBiTftafr+o/lsqtoNCq/fJiHrus7hRA/ikajf+TdGftvZDQg/tM074za2toeU1X1KcMwlkx7WF0H4LgQYlF3d/fVvI2wgBcIqJqmvQhAfs06J4S4LRqNymU9mZvqJwD8mmEYHV4YLMcwpYvcv/M3o6OjG2tqar6cMSCTyyKpYYWcKLquf0ou1QHwFwA+CyCkKMo3DMP4Q13X5T4talkBWmqaJvdf/aWiKBEhREBRlG8ahvE4r8cKEG9yiJqmiWlfQOTy8lmvPU3Tjgkhnuru7v7KtOefb8m/o9Fo9JOVM+vKHykNSOVrWPAMdF3/MIAvGIYh936Yh6ZpawCcEkIs7+7u7i24UVYoOQFd1/8UwCdVVb1zfHz804qiBA3D+MXMQNrb2z8mhPisYRitJR8cO8xKYPKN67HJDZM/0nX9mxkDomna16hh5Zw4k8tWf0sI8Vo6nf4vqqo2A/hrAP8TwHpqWRlaapr2x4qirFAU5c/S6fQGAF9SVfVX0un0W6hhxWg4ZUDy3Ud1XT+VTqe/0N3d/Y1pzz9/L4NIRKPRj1fGjP0xShoQf+hY0Cx0XX+fvMlm+wJSVVW1oLOzs7+gBlm45AQm/2j+53Q6/fPd3d1Pa5r2FIAFN38BEUJ8IhqNbir5ANlhVgKapv2RoiirDMOQe3fkp//pBoQaVtB5o+v6Z4QQfxQMBlcdP3787KSe8qvIrwL4d16P3hdT1/W3CiG+HYvFlp0/f15GFZQv42QUM/ll66fU0PsaTmo23YDkvI/qut6ZTqe/dPMXEEVRLhuG8RuVMWN/jJIGxB86FjSLzB6Q5ubmyM6dO1Oycnt7+5uFEM8YhlHHPSAF4Sx5Ybk0AIBc/yojtcioO/KPptw/8PbpQQQ0Tft9RVHu5h6Qkks0a4eapp1WFGWJEGJ8slB48n8Tk/t4qKF35Mo5Ek3TflFRlK8YhlGdKajr+jsAyM3Lf8Dr0ftC6rr+2wD+g2EYd2dGq2naOxVF+a4Q4gvU0PsaZjEgOf8WTu4B2TM9OIuu6y8IIZ7lHpDS6k0DUlrenuhNRn2or6/vA/A2wzBemnxz97sAZBSsN3likBxEVgK6rv+eEOLzqqp+YHrI5MnIH9+PxWKLp73J+8lkFKzfI05vEFi/fv3KsbGxqsxoAoHAH8t/Hh8f/51AILBCCEENvSFV3lG0t7fr6XS6KxAI6CdOnIhO3kd/UwjxhKIon6SWeRGWvYCu6x8SQjxZVVXVkgnIouv6bwL4JQC/Tg3LLpGlAdy0B0RGE5z1PiqjYAG4JxqNPiQbnxYF691dXV3PW+qQhRwhQAPiCMbKa0TGrwdwH4DHASyVeUCEEI9Ho9HvVd5s5saINU1bpyiKzPMhl33Iz8xTR2dn51Vd148KIY6l0+k/CAQCjwohPpdKpTqYB8S758f0JVgAAtTQu1plG5mu6z8E0CSXOqqqKr9s/YN8cx6NRp+ilt7Xcs2aNY3BYLBLLpkLBAJfSKVSugwkIKNgRaPRr1JD72soRzjdgOS7j7a3t6+S4ewB/P74+PgPJvOAtEej0S3MA1JavWlASsvbM71NfgWR2V8fAzCgKMqfZLK/emaQHMgMApk159mwRKNRpbW1tTUQCHwNwHYAJ4UQn4pGozIXCA+PErjJgIAaelSoWYY1+QArl0T+nKIoowBkdME/kA8y1LIytJzMJ/FFAHcBkBEg/9IwDPn/qWFlSHizAcl7H5VLJeWXL0VRlgsh9iiK8oRhGKcrZLq+GSYNiG+k5ERIgARIgARIgARIgARIwPsEaEC8rxFHSAIkQAIkQAIkQAIkQAK+IUAD4hspORESIAESIAESIAESIAES8D4BGhDva8QRkgAJkAAJkAAJkAAJkIBvCNCA+EZKToQESIAESIAESIAESIAEvE+ABsT7GnGEJEACJEACJEACJEACJOAbAjQgvpGSEyEBEiABEiABEiABEiAB7xOgAfG+RhwhCZAACZAACZAACZAACfiGAA2Ib6TkREiABEig/AQ0TVsD4DCA70ej0Y9MH1F7e/sdQojdAD5tGMaXyz9ajoAESIAESKAcBGhAykGdfZIACZCAjwlomvZRAN9QFOXnDcP4tpyqzBpeVVV1SAhxMBqNvt/H0+fUSIAESIAE8hCgAeEpQgIkQAIk4DgBTdOk8XhICLGpu7u7V9f1pwFsSSaTt/f09Aw43iEbJAESIAESqBgCNCAVIxUHSgIkQAKVQ2Djxo3zx8bGjgI4LoT4LoCnFEW51zCMA5UzC46UBEiABEjADQI0IG5QZZskQAIkQAJob29/sxDiOSFEWlGU3zEM48+JhQRIgARIgARoQHgOkAAJkAAJuEKgpaWlpr6+3gCwVAhxezQalZvTeZAACZAACcxxAjQgc/wE4PRJgARIwC0CmqZ9TVGUnxVCXFEUJTA6Orrt/PnzMbf6Y7skQAIkQAKVQYAGpDJ04ihJgARIoKIItLW1fVBRlP+jKMp7hBBnAOwH8NVoNPrJipoIB0sCJEACJOA4ARoQx5GyQRIgARKY2wRaW1tbVVU9JA2IYRifkDR0Xf9tIcQfA3gkGo0+M7cJcfYkQAIkMLcJ0IDMbf05exIgARJwlEBHR0colUrtBRC5acmVquv68wDWJZPJjT09PZcd7ZiNkQAJkAAJVAwBGpCKkYoDJQESIAHvE9B1/YsA/pMQYns0Gj0yfcTt7e2rhBBHhBB7otHoOwEI78+IIyQBEiABEnCaAA2I00TZHgmQAAmQAAmQAAmQAAmQwKwEaEB4cpAACZAACZAACZAACZAACZSMAA1IyVCzIxIgARIgARIgARIgARIgARoQngMkQAIkQAIkQAIkQAIkQAIlI0ADUjLU7IgESIAESIAESIAESIAESIAGhOcACZAACZAACZAACZAACZBAyQjQgJQMNTsiARIgARIgARIgARIgARKgAeE5QAIkQAIkQAIkQAIkQAIkUDICNCAlQ82OSIAESIAESIAESIAESIAEaEB4DpAACZAACZAACZAACZAACZSMAA1IyVCzIxIgARIgARIgARIgARIgARoQngMkQAIkQAIkQAIkQAIkQAIlI0ADUjLU7IgESIAESIAESIAESIAESIAGhOcACZAACZAACZAACZAACZBAyQjQgJQMNTsiARIgARIgARIgARIgARKgAeE5QAIkQAIkQAIkQAIkQAIkUDICNCAlQ82OSIAESIAESIAESIAESIAEaEB4DpAACZAACZAACZAACZAACZSMAA1IyVCzIxIgARIgARIgARIgARIgARoQngMkQAIkQAIkQAIkQAIkQAIlI0ADUjLU7IgESIAESIAESIAESIAESIAGhOcACZAACZAACZAACZAACZBAyQjQgJQMNTsiARIgARIgARIgARIgARKgAeE5QAIkQAIkQAIkQAIkQAIkUDICNCAlQ82OSIAESIAESIAESIAESIAEaEB4DpAACZAACZAACZAACZAACZSMwP8HG85M0dSPH5MAAAAASUVORK5CYII=\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "it took 234 steps to sort 100 items\n"
     ]
    }
   ],
   "source": [
    "x = [i for i in range(len(qs_steps[0]))]\n",
    "y = qs_steps\n",
    "\n",
    "fig1, ax1 = plt.subplots()\n",
    "\n",
    "# why the heck does line need a comma after it?\n",
    "line, = ax1.plot(x,y[0], lw=3, alpha=0.8, label=\"sorting\")\n",
    "line2, = ax1.plot(x,y[0], lw=2, alpha = 0.1, label = \"one step before\")\n",
    "line3 = ax1.plot(x,y[0], lw=0.8, alpha = 0.4, label = \"original data\")\n",
    "line3 = ax1.plot(x,y[-1], lw=1, alpha = 0.6, label=\"sorted\")\n",
    "\n",
    "fig1.set_size_inches(8,6)\n",
    "ax1.set_title(\"Quick Sort steps\")\n",
    "ax1.set_xlabel('X')\n",
    "ax1.set_ylabel('Y')\n",
    "\n",
    "def animate(i):\n",
    "    line.set_ydata(y[i])  # update the data\n",
    "    if i > 1:\n",
    "        line2.set_ydata(y[i-1])\n",
    "\n",
    "ani2 = animation.FuncAnimation(fig1, animate, \n",
    "                frames=len(y), interval=120, repeat=False) \n",
    "\n",
    "print(f\"it took {len(qs_steps)-1} steps to sort {len(qs_steps[0])} items\")\n",
    "plt.legend()\n",
    "#ani2.save(\"quicksort_animate1.mp4\")\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video controls autoplay><source src='quicksort_animate1.mp4' type='video/mp4'></video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display.HTML(\"<video controls autoplay><source src='quicksort_animate1.mp4' type='video/mp4'></video>\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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