Parse Vericold Log Files.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas, glob, os\n",
    "from matplotlib import pyplot as plt\n",
    "from datetime import datetime\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_timestamp(data, index):\n",
    "    return datetime.fromtimestamp(data['Time(secs)'][index]).strftime(\"%A, %B %d, %Y %I:%M:%S\")\n",
    "\n",
    "def get_minimum_temperature(data, plate=\"MC plate RuOx\", tmin_readable=True):\n",
    "    y = data[f'{plate} T(K)']\n",
    "    exclude_zeros = (y > 0)\n",
    "    xmin = np.argmin(y[exclude_zeros])\n",
    "    if tmin_readable:\n",
    "        tmin = datetime.fromtimestamp(data['Time(secs)'][exclude_zeros][xmin]).strftime(\"%B %d, %Y\")# %I:%M:%S\")\n",
    "    else:\n",
    "        tmin = datetime.fromtimestamp(data['Time(secs)'][exclude_zeros][xmin])\n",
    "    return tmin, y[exclude_zeros][xmin]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prerequisites "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook can parse through converted Vericold log files to show historical trends in temperatures, pressures, etc. To run the cells below, first make sure that the `.vcl` files do not contain spaces in the filename. If they do, simply fire up a terminal and run \n",
    "\n",
    "```sh rename.sh```\n",
    "\n",
    "in the directory that contains the log files. This will remove all spaces and replace them with underscores. Next, you need to convert the proprietary `.vcl` file format to readable ascii, which can be done with the following command: \n",
    "\n",
    "```sh log2ascii.sh``` \n",
    "\n",
    "in the same folder that contains the `.vcl` files. This bash script will loop over the available vcl files and convert them to comma separated values format. You are good to go now.\n",
    "\n",
    "These scripts were built on top of the code from this thesis: \n",
    "https://etheses.whiterose.ac.uk/2786/1/uk_bl_ethos_509042.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.system(\"sh rename.sh\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.system(\"sh log2ascii.sh\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load available files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 15, here are the first few:\n",
      "['./log_201207_150641.csv' './log_210111_171203.csv'\n",
      " './log_210126_132631.csv' './log_210423_131643.csv'\n",
      " './log_210520_090928.csv']\n"
     ]
    }
   ],
   "source": [
    "# Adjust this to the path that contains your csv files\n",
    "log_path = r\"./\"\n",
    "files = np.sort(glob.glob(os.path.join(log_path, \"*.csv\")))\n",
    "print(f\"Found {len(files)}, here are the first few:\")\n",
    "print(files[:5])\n",
    "\n",
    "# The following header works for Vericold in QNL but may have to be adjusted for Oxicold or Snowflake.\n",
    "# You can find the header in the vcl file, when you open it with a text editor.\n",
    "header = [\"LineSize(bytes)\", \"LineNumber\", \"Time(secs)\", \n",
    "          \"PressureM1Condense(Bar)\", \n",
    "          \"PressureM3Tank(Bar)\", \n",
    "          \"PressureM21Still(mBar)\", \n",
    "          \"PressureM22Forepump(mBar)\", \n",
    "          \"PressureMDewar(mBar)\", \n",
    "          \"PressureFPSafety(Bar)\", \n",
    "          \"4K PT t(s)\", \"4K PT T(K)\", \"4K PT R(Ohm)\", \n",
    "          \"4K plate t(s)\", \"4K plate T(K)\", \"4K plate R(Ohm)\", \n",
    "          \"Still t(s)\", \"Still T(K)\", \"Still R(Ohm)\", \n",
    "          \"MC plate cernox t(s)\", \"MC plate cernox T(K)\", \"MC plate cernox R(Ohm)\", \n",
    "          \"MC plate RuOx t(s)\", \"MC plate RuOx T(K)\", \"MC plate RuOx R(Ohm)\", \n",
    "          \"MC internal RuOx t(s)\", \"MC internal RuOx T(K)\", \"MC internal RuOx R(Ohm)\", \n",
    "          \"chan[7] t(s)\", \"chan[7] T(K)\", \"chan[7] R(Ohm)\", \n",
    "          \"chan[8] t(s)\", \"chan[8] T(K)\", \"chan[8] R(Ohm)\", \n",
    "          \"70K PT t(s)\", \"70K PT T(K)\", \"70K PT R(Ohm)\", \n",
    "          \"70K plate t(s)\", \"70K plate T(K)\", \"70K plate R(Ohm)\", \n",
    "          \"Heated Load RuOx t(s)\", \"Heated Load RuOx T(K)\", \"Heated Load RuOx R(Ohm)\", \n",
    "          \"chan[11] t(s)\", \"chan[11] T(K)\", \"chan[11] R(Ohm)\", \n",
    "          \"chan[12] t(s)\", \"chan[12] T(K)\", \"chan[12] R(Ohm)\", \n",
    "          \"chan[13] t(s)\", \"chan[13] T(K)\", \"chan[13] R(Ohm)\", \n",
    "          \"chan[14] t(s)\", \"chan[14] T(K)\", \"chan[14] R(Ohm)\",\n",
    "          \"chan[15] t(s)\", \"chan[15] T(K)\", \"chan[15] R(Ohm)\", \n",
    "          \"Still heater (W)\", \n",
    "          \"chamber heater (W)\", \n",
    "          \"IVC sorb heater (W)\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load a sample log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./log_210111_171203.csv\n",
      "Time axis starts at Monday, January 11, 2021 04:06:40\n",
      "and ends at Tuesday, January 26, 2021 02:26:40\n"
     ]
    }
   ],
   "source": [
    "# Use pandas to load the second file in the list\n",
    "file = files[1]\n",
    "print(file)\n",
    "\n",
    "data = pandas.read_csv(file, names=header, index_col=False)\n",
    "\n",
    "print(f\"Time axis starts at {convert_timestamp(data, 0)}\")\n",
    "print(f\"and ends at {convert_timestamp(data, data.shape[0]-1)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take a look at the file structure and make sure the headers are correct. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LineSize(bytes)</th>\n",
       "      <th>LineNumber</th>\n",
       "      <th>Time(secs)</th>\n",
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      "text/plain": [
       "       LineSize(bytes)  LineNumber    Time(secs)  PressureM1Condense(Bar)  \\\n",
       "0                  480           0  1.610410e+09                 0.827662   \n",
       "1                  480           1  1.610410e+09                 0.822779   \n",
       "2                  480           2  1.610410e+09                 0.822779   \n",
       "3                  480           3  1.610410e+09                 0.827662   \n",
       "4                  480           4  1.610410e+09                 0.822779   \n",
       "...                ...         ...           ...                      ...   \n",
       "42875              480       42875  1.611700e+09                 0.957060   \n",
       "42876              480       42876  1.611700e+09                 0.957060   \n",
       "42877              480       42877  1.611700e+09                 0.957060   \n",
       "42878              480       42878  1.611700e+09                 0.957060   \n",
       "42879              480       42879  1.611700e+09                 0.957060   \n",
       "\n",
       "       PressureM3Tank(Bar)  PressureM21Still(mBar)  PressureM22Forepump(mBar)  \\\n",
       "0                 0.002344                  0.2220                     7.2600   \n",
       "1                 0.002344                  0.2220                     7.2900   \n",
       "2                 0.002344                  0.2240                     7.3100   \n",
       "3                 0.002344                  0.2210                     7.3000   \n",
       "4                 0.002344                  0.2200                     7.3200   \n",
       "...                    ...                     ...                        ...   \n",
       "42875             0.493863                  0.0771                     0.0709   \n",
       "42876             0.493863                  0.0772                     0.0709   \n",
       "42877             0.493472                  0.0772                     0.0709   \n",
       "42878             0.493863                  0.0772                     0.0709   \n",
       "42879             0.493863                  0.0772                     0.0709   \n",
       "\n",
       "       PressureMDewar(mBar)  PressureFPSafety(Bar)  4K PT t(s)  ...  \\\n",
       "0              9.870000e-07               0.860378           0  ...   \n",
       "1              9.840000e-07               0.859597           0  ...   \n",
       "2              9.800000e-07               0.859206           0  ...   \n",
       "3              9.820000e-07               0.859206           0  ...   \n",
       "4              9.840000e-07               0.859206           0  ...   \n",
       "...                     ...                    ...         ...  ...   \n",
       "42875          5.720000e-02               0.071877           0  ...   \n",
       "42876          5.610000e-02               0.071877           0  ...   \n",
       "42877          5.490000e-02               0.071877           0  ...   \n",
       "42878          5.390000e-02               0.072659           0  ...   \n",
       "42879          5.300000e-02               0.071877           0  ...   \n",
       "\n",
       "       chan[13] R(Ohm)  chan[14] t(s)  chan[14] T(K)  chan[14] R(Ohm)  \\\n",
       "0                    0              0              0                0   \n",
       "1                    0              0              0                0   \n",
       "2                    0              0              0                0   \n",
       "3                    0              0              0                0   \n",
       "4                    0              0              0                0   \n",
       "...                ...            ...            ...              ...   \n",
       "42875                0              0              0                0   \n",
       "42876                0              0              0                0   \n",
       "42877                0              0              0                0   \n",
       "42878                0              0              0                0   \n",
       "42879                0              0              0                0   \n",
       "\n",
       "       chan[15] t(s)  chan[15] T(K)  chan[15] R(Ohm)  Still heater (W)  \\\n",
       "0                  0              0                0          0.001800   \n",
       "1                  0              0                0          0.001800   \n",
       "2                  0              0                0          0.001800   \n",
       "3                  0              0                0          0.001800   \n",
       "4                  0              0                0          0.001800   \n",
       "...              ...            ...              ...               ...   \n",
       "42875              0              0                0          0.001901   \n",
       "42876              0              0                0          0.001901   \n",
       "42877              0              0                0          0.001901   \n",
       "42878              0              0                0          0.001901   \n",
       "42879              0              0                0          0.001901   \n",
       "\n",
       "       chamber heater (W)  IVC sorb heater (W)  \n",
       "0                       0                    0  \n",
       "1                       0                    0  \n",
       "2                       0                    0  \n",
       "3                       0                    0  \n",
       "4                       0                    0  \n",
       "...                   ...                  ...  \n",
       "42875                   0                    0  \n",
       "42876                   0                    0  \n",
       "42877                   0                    0  \n",
       "42878                   0                    0  \n",
       "42879                   0                    0  \n",
       "\n",
       "[42880 rows x 60 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot temperatures for the cooldown "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can take a look at the temperature vs. time for a single cooldown. We use the data file that we loaded in the previous section. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "        fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 overridden (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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0.0, 42879.0)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "xaxis = data['LineNumber']\n",
    "\n",
    "plt.figure()\n",
    "labels = ['70K plate T(K)', '4K PT T(K)', \"Still T(K)\", 'MC plate RuOx T(K)']\n",
    "for label in labels:\n",
    "    plt.plot(xaxis, data[label], label=label)\n",
    "    \n",
    "plt.yscale('log')\n",
    "plt.legend(loc=0, frameon=False)\n",
    "plt.ylabel(\"Temperature (K)\")\n",
    "plt.xlabel(\"Time axis\")\n",
    "plt.xlim(np.min(xaxis), np.max(xaxis))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pressure graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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",
       "        fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 overridden (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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0.0, 42879.0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(xaxis, data['PressureM3Tank(Bar)'])\n",
    "plt.yscale('log')\n",
    "plt.ylabel(\"Tank pressure M3 (bar)\")\n",
    "plt.xlabel(\"Time axis\")\n",
    "plt.xlim(np.min(xaxis), np.max(xaxis))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you're interested in the minimum temperature during this cooldown for a specific plate, you can use `get_minimum_temperature` and specify the desired thermometer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('January 25, 2021', 62.9423)\n",
      "('January 25, 2021', 4.67638)\n",
      "('January 15, 2021', 0.666573)\n",
      "('January 12, 2021', 0.022953900000000003)\n"
     ]
    }
   ],
   "source": [
    "print(get_minimum_temperature(data, plate=\"70K plate\"))\n",
    "print(get_minimum_temperature(data, plate=\"4K plate\"))\n",
    "print(get_minimum_temperature(data, plate=\"Still\"))\n",
    "print(get_minimum_temperature(data, plate=\"MC plate RuOx\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot historical trends for many cooldowns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tmin = 0.0228003 K at 2020-12-27 20:33:20\n",
      "Tmin = 0.022953900000000003 K at 2021-01-12 19:53:20\n",
      "Tmin = 0.022990599999999996 K at 2021-02-06 17:06:40\n",
      "Tmin = 0.023442700000000004 K at 2021-04-24 03:26:40\n",
      "Tmin = 0.024711700000000003 K at 2021-05-20 15:33:20\n",
      "Tmin = 48.8766 K at 2021-06-10 14:20:00\n",
      "Tmin = 0.0227612 K at 2021-06-24 00:33:20\n",
      "Tmin = 0.022737900000000002 K at 2021-06-29 22:13:20\n",
      "Tmin = 0.0232278 K at 2021-07-15 16:00:00\n",
      "Tmin = 0.0232331 K at 2021-07-15 21:33:20\n",
      "Tmin = 0.023237999999999998 K at 2021-07-27 14:06:40\n",
      "Tmin = 0.022947099999999998 K at 2021-08-06 10:13:20\n",
      "Tmin = 50.2409 K at 2021-09-10 17:26:40\n",
      "Tmin = 0.0229171 K at 2021-09-19 04:13:20\n",
      "Tmin = 0.0231722 K at 2021-10-26 19:00:00\n"
     ]
    }
   ],
   "source": [
    "tmins, Tmins, T4ks = list(), list(), list()\n",
    "max_tank_pressure = list()\n",
    "min_dewar_pressure = list()\n",
    "\n",
    "# Loop over all indexed files\n",
    "for file in files:\n",
    "    data = pandas.read_csv(file, names=header, index_col=False)\n",
    "    tmin, Tmin_mc = get_minimum_temperature(data, plate=\"MC plate RuOx\", tmin_readable=False)\n",
    "    print(f\"Tmin = {Tmin_mc} K at {tmin}\")\n",
    "    _, Tmin_4k = get_minimum_temperature(data, plate=\"4K plate\")\n",
    "    \n",
    "    max_tank_pressure.append(np.max(data['PressureM3Tank(Bar)']))\n",
    "    min_dewar_pressure.append(np.min(data['PressureMDewar(mBar)']))\n",
    "    tmins.append(tmin)\n",
    "    Tmins.append(Tmin_mc)\n",
    "    T4ks.append(Tmin_4k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* global mpl */\n",
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       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            '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",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
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       "        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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
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       "    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",
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       "\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
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       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    var resizeObserver = new ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 overridden (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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.one(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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jh1rPtfgReAMDsdfJiKrVq0SPcRQ09NPPy2DBw9Ovfy7774TPdBSk37XmDFjQhatdW3VqpX5XB+GevfuHU41Msxr+8ZwrSEUhAACCCCAAAII+EiAOVpknRmLAEi8nyH0zEJddaJJn3X0mSeQeIaIbFxwFQIIIIAAAgggkAwCtp8hCIBkMsoaNGggK1asMEu9dW/cbNmyBb1CDwMMbNmk20rp9lJO07Jly6RRo0Ym+4gRI0Tf5gqV9PBy3X9X66HnfKRdeu70+3766SfRgw413XvvvfLaa6+lXnry5EnJkyePnD592hyUrm9zhUpa10DwRNvQsGFDp1XINJ/tGyPTCpIBAQQQQAABBBBIQgHmaJF1eiwCIPF+htAXnnQViKbzAyA8Q0Q2LrgKAQQQQAABBBBIBgHbzxAEQDIZZfoLfv1Fv6Y1a9ZIrVq1gl4xcuRIefTRR81nixcvlptuusnx+NWDBYsWLSr64NCsWTNZuHBh0Gv1c12RcuTIEalTp45ZyRFJ+uyzz1KDFQ888IC88MIL5xSjgRwN6FxwwQWi56CECrJoXbWtOXPmNPny588fSXWCXmP7xnCtIRSEAAIIIIAAAgj4SIA5WmSdGYsASLyfIdKeObJy5crUFeUBEZ4hIhsbXIUAAggggAACCPhdwPYzBAGQTEaYHsAdCHr07NlTJkyYkO6KM2fOSOXKlWXz5s1SsGBB2bNnj2TPnj2ssXvLLbeYwIeu7NADJYOdeTF79mzp0KGDKVfP8Bg0aFBY3xHInPbhZerUqdK1a9dzytGy9ZwQTW+99Zbccccd6b5HB64eeqkrRbTuH3/8cUR1CXWR7RvD1cZQGAIIIIAAAggg4BMB5miRdWQsAiBak3g9Q6Q9BF1Xi+sh6PoSVNrEM0RkY4OrEEAAAQQQQAABvwvYfoYgAOJghAW2wdLgxPLly83qi7Rp1KhR8tBDD5kfDR06VIYNG3bO59OmTZNu3bqF/Fw/SLuE/dZbb5X33ntPsmbNmlqOnkNSvXp12bZtmwmybN26VQoVKnTO92iwQh+CChQoELJVuly9Y8eOJnCh+bScwNklgYv0gaZs2bKiDzplypSRr7/+WooUKZJapl57++23y0cffWR+5vb2V1qm7RvDwbAgCwIIIIAAAgggkHQCzNEi6/JIAiDxeobQLW//8Y9/SO7cuYM2TleatGnTxmzDq0nPLgycSZj2Ap4hIhsbXIUAAggggAACCPhdwPYzBAEQByPs22+/NUu8jx8/Lvny5TPnXuh5F/p3XZXx+uuvm1L0XI1169al2wrKycOLXq+rO7Q8TVr+gAEDpHTp0rJp0yZzWPmWLVvMZ7oKRVejnJ9uuOEGE6zQQ9Q1aFOhQgUT5NCzQn744QeZO3euLFiwwFyWJUsW0dUfd911V1ABPRekV69e5rNy5crJY489Zg5H37FjhzkY/dNPPzWfaZ1nzZrlQDG8LLZvjPBqS24EEEAAAQQQQCA5BJijOetn3SLq559/Ts2sLzMFVm/rc0WPHj3OKej8Fdn6YTyfIfR5o1WrVlKvXj0z99dnHj3/ULfFHT9+vPz++++mvvp8odvwnv8CVaAxPEM4Gx/kQgABBBBAAAEEkknA9jMEARCHo01XO3Tu3NmcvxEsafBDt4G6/PLL033s9OFFAyr6dlUgSHF+QSkpKTJkyJB0K0wC+TQA8vnnn2faIl058vLLL0unTp0yzKurWZ588kk5e/Zs0Hy62uTdd9+VXLlyZfqd4WawfWOEW1/yI4AAAggggAACySDAHM1ZL2tA44033nCWWSTofNtrzxD6gpW++HThhRfyDOG4Z8mIAAIIIIAAAgggYPsZggBIGGPwt99+k5deeskEOrTj9HBwDXi0bdtW+vbtK7ofbrDk9OElcK0+WOg1GzZsMG9elShRQurXr2++4/ztt9J+3/bt2+WTTz4xqzM2btwou3fvTj3EXA9Z1xUcenC5boF1/vZZoRj0Da9x48bJihUrTHm6/VbVqlXNll6B80jCIHSc1faN4biiZEQAAQQQQAABBJJIgDmas86OZwAk2mcIXcG+dOlSs9pDV43rahV9BtFnG12Nruch6rz/pptuMqvInSSeIZwokQcBBBBAAAEEEEgOAdvPEARAkmOcJVwrbd8YCQdGhRFAAAEEEEAAgTgIMEeLAzJfEbEA4zNiOi5EAAEEEEAAAQRiJmB7jkYAJGZdS8HRCNi+MaKpO9cigAACCCCAAAJ+FWCO5tee9Ue7GJ/+6EdagQACCCCAAAL+ErA9RyMA4q/x5JvW2L4xfANJQxBAAAEEEEAAARcFmKO5iElRrgswPl0npUAEEEAAAQQQQCBqAdtzNAIgUXchBcRCwPaNEYs2USYCCCCAAAIIIJDoAszREr0H/V1/xqe/+5fWIYAAAggggEBiCtieoxEAScxx4/ta274xfA9MAxFAAAEEEEAAgQgEmKNFgMYlcRNgfMaNmi9CAAEEEEAAAQQcC9ieoxEAcdxVZIyngO0bI55t5bsQQAABBBBAAIFEEWCOlig9lZz1ZHwmZ7/TagQQQAABBBDwtoDtORoBEG+Pj6Stne0bI2nhaTgCCCCAAAIIIJCBAHM0hoeXBRifXu4d6oYAAggggAACySpge45GACRZR57H2237xvA4D9VDAAEEEEAAAQSsCDBHs8LOlzoUYHw6hCIbAggggAACCCAQRwHbczQCIHHsbL7KuYDtG8N5TcmJAAIIIIAAAggkjwBztOTp60RsKeMzEXuNOiOAAAIIIICA3wVsz9EIgPh9hCVo+2zfGAnKRrURQAABBBBAAIGYCjBHiykvhUcpwPiMEpDLEUAAAQQQQACBGAjYnqMRAIlBp1Jk9AK2b4zoW0AJCCCAAAIIIICA/wSYo/mvT/3UIsann3qTtiCAAAIIIICAXwRsz9EIgPhlJPmsHbZvDJ9x0hwEEEAAAQQQQMAVAeZorjBSSIwEGJ8xgqVYBBBAAAEEEEAgCgHbczQCIFF0HpfGTsD2jRG7llEyAggggAACCCCQuALM0RK375Kh5ozPZOhl2ogAAggggAACiSZge45GACTRRkyS1Nf2jZEkzDQTAQQQQAABBBAIS4A5WlhcZI6zAOMzzuB8HQIIIIAAAggg4EDA9hyNAIiDTiJL/AVs3xjxbzHfiAACCCCAAAIIeF+AOZr3+yiZa8j4TObep+0IIIAAAggg4FUB23M0AiBeHRlJXi/bN0aS89N8BBBAAAEEEEAgqABzNAaGlwUYn17uHeqGAAIIIIAAAskqYHuORgAkWUeex9tt+8bwOA/VQwABBBBAAAEErAgwR7PCzpc6FGB8OoQiGwIIIIAAAgggEEcB23M0AiBx7Gy+yrmA7RvDeU3JiQACCCCAAAIIJI8Ac7Tk6etEbCnjMxF7jTojgAACCCCAgN8FbM/RCID4fYQlaPts3xgJyka1EUAAAQQQQACBmAowR4spL4VHKcD4jBKQyxFAAAEEEEAAgRgI2J6jEQCJQadSZPQCtm+M6FtACQgggAACCCCAgP8EmKP5r0/91CLGp596k7YggAACCCCAgF8EbM/RCID4ZST5rB22bwyfcdIcBBBAAAEEEEDAFQHmaK4wUkiMBBifMYKlWAQQQAABBBBAIAoB23M0AiBRdB6Xxk7A9o0Ru5ZRMgIIIIAAAgggkLgCzNESt++SoeaMz2ToZdqIAAIIIIAAAokmYHuORgAk0UZMktTX9o2RJMw0EwEEEEAAAQQQCEuAOVpYXGSOswDjM87gfB0CCCCAAAIIIOBAwPYcjQCIg04iS/wFbN8Y8W8x34gAAggggAACCHhfgDma9/somWvI+Ezm3qftCCCAAAIIIOBVAdtzNAIgXh0ZSV4v2zdGkvPTfAQQQAABBBBAIKgAczQGhpcFGJ9e7h3qhgACCCCAAALJKmB7jkYAJFlHnsfbbfvG8DgP1UMAAQQQQAABBKwIMEezws6XOhRgfDqEIhsCCCCAAAIIIBBHAdtzNAIgcexsvsq5gO0bw3lNyYkAAggggAACCCSPAHO05OnrRGwp4zMRe406I4AAAggggIDfBWzP0QiA+H2EJWj7bN8YCcpGtRFAAAEEEEAAgZgKMEeLKS+FRynA+IwSkMsRQAABBBBAAIEYCNieoxEAiUGnUmT0ArZvjOhbQAkIIIAAAggggID/BBJhjnb48GHZu3ev7N+/X3Lnzi3FihWTokWLSvbs2f3XIbToHIFEGJ90GQIIIIAAAgggkGwCtudoBECSbcQlSHtt3xgJwkQ1EUAAAQQQQACBuAp4cY62cuVK+eyzz2TFihWyevVqOXbsWFCT8uXLS/369c2fpk2bSvHixeNqx5fFXsCL4zP2reYbEEAAAQQQQAABbwvYnqMRAPH2+Eja2tm+MZIWnoYjgAACCCCAAAIZCHhljrZz504ZP368TJs2TbZv355a47Nnz2bYf1myZDGfZ82aVZo0aSK9e/eW5s2b0+c+EfDK+PQJJ81AAAEEEEAAAQRcEbA9RyMA4ko3UojbArZvDLfbQ3kIIIAAAggggIAfBGzP0TTY8dRTT8nUqVPl1KlTEgh4aECjUqVKUr16dbOyo3DhwlKoUCE5fvy4HDhwQA4ePCg//vijrFu3Tvbt25faFRoQufLKK2Xo0KHSrl07P3RRUrfB9vhManwajwACCCCAAAIIhBCwPUcjAMLQ9KSA7RvDkyhUCgEEEEAAAQQQsCxgc442fPhwGTVqlAlqaOBDAx3t27eX1q1bS40aNcx5H07SL7/8IkuXLpVZs2bJ8uXL5cyZM6KBkJo1a8rEiROlcuXKToohjwcFbI5PD3JQJQQQQAABBBBAwBMCtudoBEA8MQyoxPkCtm8MegQBBBBAAAEEEEAgvYDNOVpKSoqpkG5dNXDgQGncuLEEfhZpX+3YsUOmTJkiY8aMMStFhg0bJo8//nikxXGdZQGb49Ny0/l6BBBAAAEEEEDAswK252gEQDw7NJK7YrZvjOTWp/UIIIAAAggggEBwAZtzND2rQ4MTtWrVcr179OD0cePGSf78+eW+++5zvXwKjI+AzfEZnxbyLQgggAACCCCAQOIJ2J6jEQBJvDGTFDW2fWMkBTKNRAABBBBAAAEEwhRgjhYmGNnjKsD4jCs3X4YAAggggAACCDgSsD1HIwDiqJvIFG8B2zdGvNvL9yGAAAIIIIAAAokgwBwtEXopeevI+EzevqflCCCAAAIIIOBdAdtzNAIg3h0bSV0z2zdGUuPTeAQQQAABBBBAIISAF+doN954o6ltly5dpFu3bvRdEgt4cXwmcXfQdAQQQAABBBBAwAjYnqMRAGEgelLA9o3hSRQqhQACCCCAAAIIWBbw4hwte/bscubMGfnkk0+kYcOGloX4epsCXhyfNj34bgQQQAABBBBAwAsCtudoBEC8MAqoQzoB2zcGXYIAAggggAACCCCQXsCLc7QLL7xQdu3aJevWrZNrr72WbktiAS+OzyTuDpqOAAIIIIAAAggYAdtzNAIgDERPCti+MTyJQqUQQAABBBBAAAHLAl6co91yyy2yePFimTVrlrRv396yEF9vU8CL49OmB9+NAAIIIIAAAgh4QcD2HI0AiBdGAXVIJ2D7xqBLEEAAAQQQQAABBNILeHGO9t5770mbNm3kH//4h3z66ad0WxILeHF8JnF30HQEEEAAAQQQQMAI2J6jEQBhIHpSwPaN4UkUKoUAAggggAACCFgW8Ooc7c4775QZM2ZI165d5eWXX5a8efNaluLrbQh4dXzasOA7EUAAAQQQQAABrwjYnqMRAPHKSKAe5wjYvjHoDgQQQAABBBBAAIH0Al6co7355pty9uxZefHFF2XTpk1SsGBBadGihVx99dVSqFAhyZo1a4ZdqcETkj8EvDg+/SFLKxBAAAEEEEAAgcgFbM/RCIBE3ndcGUMB2zdGDJtG0QgggAACCCCAQMIKeHGOlpKSIlmyZEk11WBI2r9nhK35/v7774TtDyp+roAXxyd9hAACCCCAAAIIJLuA7TkaAZAcW5PNAAAgAElEQVRkH4Eebb/tG8OjLFQLAQQQQAABBBCwKuDFOZoGQCJNGgA5ffp0pJdznccEvDg+PUZEdRBAAAEEEEAAgbgL2J6jEQCJe5fzhU4EbN8YTupIHgQQQAABBBBAINkEvDhH++2336LqhjJlykR1PRd7R8CL49M7OtQEAQQQQAABBBCwI2B7jkYAxE6/862ZCNi+MeggBBBAAAEEEEAAgfQCzNGcjYo9e/bI2rVrzZ+vvvrK/Nm/f7+5+K677pJp06Y5KyiMXLNnz5apU6fKxo0b5eDBg1KyZEmpX7++9OnTR2rXrp1hST/88IMsWLBAPv/8c9mwYYPs2rXLbCNWokQJqVmzpug5KbfcckuGW4t99tln0rBhQ0c1Hjp0qAwbNsxR3nAyMT7D0SIvAggggAACCCAQHwHbczQCIPHpZ74lTAHbN0aY1SU7AggggAACCCCQFALM0Zx1c0ZnkLgdADlx4oS0bdtW5s+fH7RyukWYBhuGDBkS9HOtjx4kn1lq2rSpaJBFD5kPlgiAZCbI5wgggAACCCCAQHIK2H6GIACSnOPO8622fWN4HogKIoAAAggggAACFgSYozlDTxsAufjii+Wqq66SJUuWmIvdDoB06tRJZs2aZcrWFRj9+/eX0qVLy6ZNm+SZZ56RLVu2mM8mTpwoPXr0SNeAxo0by9KlS6Vw4cLSpk0bueGGG+TSSy+VbNmyybfffiujR48WXSGiqV69emaVSLBzV9IGQKZMmSI1atQIiVW8eHHRP24nxqfbopSHAAIIIIAAAghEL2B7jkYAJPo+pIQYCNi+MWLQJIpEAAEEEEAAAQQSXoA5mrMu1C2eNACgf3QbqV9//VUuu+wyc7GbARANRmjAQlOLFi1k3rx5kjVr1tRK7tu3T6pXry7btm2TQoUKydatW9Ot4Ojatatcf/31pl45c+ZM18A///xTdPXHypUrzWe6WqRLly7p8qUNgHz66aep9XIm5k4uxqc7jpSCAAIIIIAAAgi4KWB7jkYAxM3epCzXBGzfGK41hIIQQAABBBBAAAEfCXh9jqa/eH///ffNORb6y//jx4/L2bNnQ/aArtQIrJCIZTfFKgDSvHlzc3aHBj30Oy666KJ0zdBtqzp06GB+/vzzz8vAgQPDbup3330nVapUMdfdeuut8sEHH6QrgwBI2KxcgAACCCCAAAIIJIWA7WcIAiBJMcwSr5G2b4zEE6PGCCCAAAIIIIBA7AW8OkfTQ8fvuOMOsz2TplBBDw14pP1M/3769OmYw8UiAHL06FEpWrSo/PXXX9KsWTNZuHBh0HacPHlSihUrJkeOHDErPb744ouI2qtlaFCpUqVKogGR8xMBkIhYuQgBBBBAAAEEEPC9gO1nCAIgvh9iidlA2zdGYqpRawQQQAABBBBAILYCXpyjnTp1SmrXri3r1683wY1rr73WnIHx8ccfiwY4OnfuLAcPHpRvvvlGduzYYX5WrVo1qVy5ssGaOnVqbNFEYrIF1rJly6RRo0am7iNGjJBHHnkkZDt0Cys9g0TP9dAtrbJnzx52mwsUKGCCKLoSZOPGjQRAwhbkAgQQQAABBBBAIDkFbD9DEABJznHn+VbbvjE8D0QFEUAAAQQQQAABCwJenKPp4d49e/Y0gQ09fFvPsvj+++/NL+rPX+GhWzf16dPHBET0LIvWrVvHRTEWK0DGjRsnffv2NfXXsz9atmwZsi16MPrYsWPN52pTsWLFsNqth6Fr0EhT27ZtZc6cORkGQOrUqWPOHdGVOXnz5jWHqutZJffdd5+UL18+rO8OJ7MXx2c49ScvAggggAACCCDgRwHbczQCIH4cVT5ok+0bwweENAEBBBBAAAEEEHBdwItzNN3+SVc33HzzzWbVR+CX/MECIPqZnvlx3XXXyd9//21WhVxxxRWuO51fYCwCILri49lnnzVf9dVXX5k2hUp69segQYPMx4sWLTKHmoeTNOgxd+5cc8k777wjbdq0SXd52i2wQpWdkpIiQ4YMET0kXoNT4SYdfxmlnTt3Ss2aNU2W33//PeiZKOF+J/kRQAABBBBAAAEEohOw/QxBACS6/uPqGAnYvjFi1CyKRQABBBBAAAEEElrAi3O0UqVKmZUGM2bMSD3sO+0KEA10nP/L9mHDhskTTzwhvXv3lldeeSXmfRKLAIiuZHn11VdN3Tdv3ixXXnllyHaMHz/etFWTBjLCWfny7rvvpgY8qlevboItwYIXGgDp2LGjtGrVSurVqydly5Y1W27pSpCPPvpIpk+fLrpdmaZHH31UnnnmmbDdwwmaEAAJm5cLEEAAAQQQQACBmAjYfoYgABKTbqXQaAVs3xjR1p/rEUAAAQQQQAABPwp4cY6WM2dOs5pDD/fWs0A0/fTTT1KhQgXzi3o9t0K3YUqbVqxYIf/4xz/M6o8ffvgh5l0ViwBI9+7dzZZfmnRViwYcQiXNp/k1aSBCz0Vxkv7zn/+YFRV//PGH5M6dW9atWxdy+6xjx45Jjhw5Qp4vsnbtWrnpppvk8OHDpl909c0111zjpBqpeQiAhMVFZgQQQAABBBBAwBMCtp8hCIB4YhhQifMFbN8Y9AgCCCCAAAIIIIBAegEvztHy589vDvbWlQmBcyp2794tujJEf2GuqyPOP3dC89aqVUvy5MkjR48ejXlXxyIAEusVIHpgfN26dc0B7uo4c+bM1BU2kYJpGYHgS48ePUTPbwknsQVWOFrkRQABBBBAAAEEvCFg+xmCAIg3xgG1OE/A9o1BhyCAAAIIIIAAAggkRgCkUqVKoisV5s+fb84BCaQCBQqY4Ma0adOkS5cu5zRGf3b33XeblSG6uiHWKRYBkFieAXLgwAFp0KCBOTBdkx6g3q9fv6iZdKVO0aJFzSoQXX3z448/Rl1m2gJ4hnCVk8IQQAABBBBAAAFXBGzP0QiAuNKNFOK2gO0bw+32UB4CCCCAAAIIIOAHAS/O0TS4MWvWLHnyySdl8ODBqcwtWrQwh6LrqhDdHku3ytKkv3yvU6eO2fpKDw7/8ssvY941sQiA6NklgaDEvHnzpGXLliHb0b9/fxPE0KRBjYoVK4bMqwGhRo0amRU1mtT1X//6l2tGuqWWlq2rb3TbLDeTF8enm+2jLAQQQAABBBBAIBEFbM/RCIAk4qhJgjrbvjGSgJgmIoAAAggggAACYQt4cY4WWM2hQQ0NdASSBj80CKLbN5UrV05uu+02s1WWHsit7dCfa1BAt5KKdYpFAGTZsmUmUKFpxIgRoitCQqWmTZvKkiVLzKHkgbM6guU9fvy4WUXz+eefm48HDRokzz33nKs8NWrUMGeJEABxlZXCEEAAAQQQQAABzwrYfoYgAOLZoZHcFbN9YyS3Pq1HAAEEEEAAAQSCC3hxjnbo0CFzmPbZs2dFgwIa7AgkPWcicFB44ABtzadJgwIaJElJSYl5d8ciAKIrNXQ7qZMnT0qzZs1k4cKFQduhnxcrVswcBq9BolWrVgXNd+rUKRMkCpTTq1cvGT9+vKs2ugVWkSJFTF0uv/xyc1i9m8mL49PN9lEWAggggAACCCCQiAK252ieDoDo8vS9e/fK/v37JXfu3GbirpP87NmzJ2JfU+cwBGzfGGFUlawIIIAAAggggEDSCCTiHG3y5MkyadIks/WT/gJez5648847RbeF0hUR8UixCIBovW+55RYTsNB2/PLLL3LRRRela87s2bNTDy/X1Ry6quP8dPr0abnjjjtk7ty55iPdVuyNN94wq2TcTDNmzEg9j6V79+6mX9xMiTg+3Ww/ZSGAAAIIIIAAAl4UsD1H81QAZOXKlfLZZ5/JihUrZPXq1SH3hC1fvrzUr1/f/NE3t4oXL+7FvqVOUQjYvjGiqDqXIoAAAggggAACvhVgjhZZ10YSANGtvbp162a+cOjQoTJs2LB0X552G6xbb71V3nvvPcmaNWtqvn379kn16tVl27ZtUrBgQdm6dasUKlTonHJ0RYwGI6ZOnWp+3rp1a3n77bfPKSezVh88eFA2bNggN9xwQ8isa9euNc9uumJHAyv6dz2Dxc3E+HRTk7IQQAABBBBAAAF3BGzP0awHQHbu3GmWVusEf/v27amqgaXpoZgDbyPpBL9JkybSu3dvad68uTu9QinWBWzfGNYBqAACCCCAAAIIIOBBAeZozjpFX+z6+eefUzNrICKw8qJu3bqiW3OlTV27dk1XsJMAiF7UoUMH0VUemho2bCgDBgyQ0qVLy6ZNm+Tpp5+WLVu2mM8mTJggPXv2TPc9AwcOlNGjR5ufV65c2az8yJEjR4YN1XxpUyDAc/XVV5vD2DXoUqpUKRNE0eCLnrsyffp00W22NMXibBEtl/HpbHySCwEEEEAAAQQQiKeA7TmatQCIBjueeuop86aRToQDAQ+dJFeqVMlMmnVlR+HChc1bSnog34EDB0TfLvrxxx/NwXn6IBFIGhC58sorzdtR7dq1i2cf8l0xELB9Y8SgSRSJAAIIIIAAAggkvABzNGddqAENDSQ4TcFe/nIaANHnpDZt2siCBQuCfp2ecTJkyJCgK0j0gksvvVR+++03p1U1+c6vb9oVLhkVpM96WpfHH3/c9e219HsZn2F1I5kRQAABBBBAAIG4CNieo1kJgAwfPlxGjRplgho6edZAR/v27c1y6xo1apjzPpwk3ed26dKlMmvWLFm+fLmcOXPGTKRr1qwpEydONG8wkRJTwPaNkZhq1BoBBBBAAAEEEIitgNfnaHrGxwcffCCffPKJfPfdd+YFKk36UpU+GzRu3Ngc9B3rsz/iGQAJ9Lg+E2nQRLei0m2mSpQoYbYM7tu3rzn8PFRyIwCiB61/+OGHZhtj3dpKX3bTl9VOnDghBQoUkAoVKpjtsXTli35frJLXx2es2k25CCCAAAIIIICAlwVsz9GsBED0LSRNunWVLrnWB5HAzyLtrB07dsiUKVNkzJgx5kFH98jVN4tIiSlg+8ZITDVqjQACCCCAAAIIxFbAy3O0999/X/r16yf6XBBIgZUKaQ/z1q2ZXnnlFbNVE8lfAl4en/6SpjUIIIAAAggggIBzAdtzNCsBED2rQ4MTtWrVci7lMOexY8dk3Lhxkj9/frnvvvscXkU2rwnYvjG85kF9EEAAAQQQQAABLwh4dY724osvyoMPPmiINOihAQ9daaCrIPTve/bsEd2mKW1A5IUXXjDnZZD8I+DV8ekfYVqCAAIIIIAAAgiEL2B7jmYlABI+E1ckm4DtGyPZvGkvAggggAACCCDgRMCLc7Q1a9ZIvXr1zHa4F1xwgTz22GPSrVs3KVq06DlN0i2Z9PzBZ555Rg4fPmwO6NbDymPxUpYTS/K4L+DF8el+KykRAQQQQAABBBBILAHbczTfBEB27twpupyd5A8B2zeGPxRpBQIIIIAAAggg4K6AF+do7dq1k7lz55qzJr744gupWLFiho3evHmzXH/99XLkyBFzePjbb7/tLhKlWRPw4vi0hsEXI4AAAggggAACHhGwPUezFgD59NNPpWHDhq50w7Zt26RRo0by008/uVIehdgXsH1j2BegBggggAACCCCAgPcEvDhHK126tOzevVuefvppeeSRRxyhjRw5UgYPHmy2yNIXqUj+EPDi+PSHLK1AAAEEEEAAAQQiF7A9R7MWANEzOhYtWiR169aNXE9EtmzZIjfeeKMo5OnTp6Mqi4u9I2D7xvCOBDVBAAEEEEAAAQS8I+DFOVru3Lnl5MmTsmrVKsfbWX355ZdSp04dyZkzpxw/ftw7wNQkKgEvjs+oGsTFCCCAAAIIIICADwRsz9GsBUBSUlLMHr2LFy92/KByfn/r8vXGjRubt7b0oEMCID64I/63CbZvDP9I0hIEEEAAAQQQQMA9AS/O0cqWLSu//fZbRAEQPSh969at7gFRklUBL45PqyB8OQIIIIAAAggg4AEB23M0awEQfdvq77//NkGQTz75RKpXrx5Wd6xfv16aNm0qe/fuNdfddddd5lBDkj8EbN8Y/lCkFQgggAACCCCAgLsCXpyj3XvvvTJ58mQZMWKEPPTQQ44a/Oyzz8qjjz4qd999t0yaNMnRNWTyvoAXx6f31aghAggggAACCCAQWwHbczRrAZB58+ZJ+/btTRCkUKFComeCXH311Y60165dKzfffLMcPHjQ5O/Zs6eMHz/e0bVkSgwB2zdGYihRSwQQQAABBBBAIL4CXpyj/fDDD+Zlqhw5csiaNWukfPnyGaL8+OOPUrt2bTl16pSsW7dOKlSoEF9Evi1mAl4cnzFrLAUjgAACCCCAAAIJImB7jmYtAKL9M2fOHOnUqZPZuqpo0aImCFKpUqUMu27FihXSokULOXLkiMl3//33ywsvvJAg3U01nQrYvjGc1pN8CCCAAAIIIIBAMgl4dY6mZwt27NjRdMXjjz8ud955pxQuXPicrtGXp95880158skn5cyZMzJz5kzzUhXJPwJeHZ/+EaYlCCCAAAIIIIBA+AK252hWAyDKpQ8eun3V2bNnpVixYvL555+HfAtLt8q6/fbb5dixY0b6scceMw8wJP8J2L4x/CdKixBAAAEEEEAAgegFbM7RbrzxxgwbsH37dvnpp5/M2YD657LLLpPixYub/969e7f88ssv5plD0xVXXCGlS5c2ny1dujR6GErwhIDN8ekJACqBAAIIIIAAAgh4UMD2HM16AET7ZNq0adK9e3fTPaVKlTJBkHLlyp3TXfPnz5d27drJiRMnzM+feuopGTx4sAe7lCq5IWD7xnCjDZSBAAIIIIAAAgj4TcDmHC0lJcUELAJBjLS2+nNNwT4L1geBcvR/dTU6yR8CNsenPwRpBQIIIIAAAggg4L6A7TmaJwIgyjpx4kTp1auXEb7oootMEOTSSy81f587d6507txZTp48af6uW17p1lck/wrYvjH8K0vLEEAAAQQQQACByAVsztFuuOEGEwBxO+k2vCR/CNgcn/4QpBUIIIAAAggggID7ArbnaJ4JgCjtuHHjpF+/fubBpkyZMiYI8tlnn5nVIXpYuv781VdfNYee20jbtm2TsWPHyscffyz63zlz5pTLL7/crEzp3bu35MmTx5VqzZ49W6ZOnSobN240B72XLFlS6tevL3369DEHNmaU9BDIBQsWGLsNGzbIrl27jFuJEiWkZs2aZj/kW265JcOHRzVv2LCho7YMHTpUhg0b5ihvOJls3xjh1JW8CCCAAAIIIIBAsggwR0uWnk7MdjI+E7PfqDUCCCCAAAII+FvA9hzNUwEQ7eoXX3xRBg4cmPpL+z179phDCrNmzSqTJ082v8C3kTTooQe2Hz58OOjXV6hQwQQeypYtG3H1dHuvtm3bim73FSzpsn8NNgwZMiTo53qWih7smFlq2rSpaJClYMGCQbMSAMlMkM8RQAABBBBAAIHkFLD98JKc6rTaqQDj06kU+RBAAAEEEEAAgfgJ2J6jeS4AovTPPvusPProo6l7/GbLlk1mzJhhVlrYSLqS4vrrr5c///xT8uXLZ+qmKySOHz9uAgm6fZemK6+8Ur766iuTJ5KkAZZZs2aZS7X8/v37m8MZN23aJM8884xs2bLFfKbf16NHj3Rf0bhxY3OIY+HChaVNmzai2wToNmLq9+2338ro0aNFV4hoqlevnlklokGV81PaAMiUKVOkRo0aIZujB0vqH7eT7RvD7fZQHgIIIIAAAggg4AcB5mh+6EX/toHx6d++pWUIIIAAAgggkLgCtudo1gIguoVURkkPOZ80aZL5Bb2uCrntttsy7eVLLrkk0zyRZNBghAYFNJCwfPlyqVOnzjnFjBo1Sh566CHzs+HDh8vjjz8e9tdoMEIDFppatGgh8+bNM6teAmnfvn1SvXp1s/VWoUKFZOvWrelWcHTt2tUEanQliG7PdX7SAI6u/li5cqX5SFeLdOnSJV2+tAEQ3RM5UK+wGxXFBbZvjCiqzqUIIIAAAggggIBvBZij+bZrfdEwxqcvupFGIIAAAggggIDPBGzP0awFQDSw4eYhhlqWnhPidtIVHXp2hiY9e2TChAnpvkK36KpcubJs3rzZBCd2794t2bNnD6sqzZs3N1toadDj119/NQfBn590tUmHDh3Mj59//nmzVVi46bvvvpMqVaqYy2699Vb54IMP0hVBACRcVfIjgAACCCCAAALJIWDz4WXt2rWp8/JYaOvLQjoPr1ixYiyKp8w4CNgcn3FoHl+BAAIIIIAAAggkpIDtOZrVAIibPaYBkNOnT7tZpCnrscceM9tPaVqzZo3UqlUr6HeMHDnSbI2lacmSJdKkSRPHdTl69KgULVpU/vrrL2nWrJksXLgw6LUnT56UYsWKyZEjR8xKjy+++MLxd6TNqGXoipJKlSqJBkTOTwRAImLlIgQQ8LnAHydOya7DJ+TYydOSN0dWKVkgl+TPFV6w2+dENA8BBJJAwObDi74opHNlPRMvoy1aw+2GY8eOySuvvCIvvPCC9O3bN6LV3OF+J/ljI2BzfMamRZSKAAIIIIAAAggkvoDtOZq1AEi3bt1c772pU6e6XmaDBg1kxYoVkjdvXjl06JDZBitYWr16tQlKaNItsHQrLKdp2bJl0qhRI5N9xIgR8sgjj4S8VLew0gCL1kPfUgt3pYkWXKBAARNE0ZUgGzduTPddBECc9hz5EEDA7wJnz56V1Vv3y/TVv8mSf++W02fOpjY5a0oWaVqphHSuXUbqlC3i6qpGv7vSPgQQSFwBmw8v+sLQgQMHzL+3Ou/WrVzbtm1rVmBHknRb2JkzZ8qcOXPMPF//zddASO/evSMpjms8IGBzfHqg+VQBAQQQQAABBBDwpIDtOZq1AIgneyNIpQKrJapWrSrr168PWe2DBw+aw8c16YOYPkg5TePGjTNvm2nSsz9atmwZ8lI9GH3s2LHm8++//z7sJfp6GHq1atUyrGfaAIied6LnjuzZs8cEgfRQdT0T5L777pPy5cs7bWLY+WzfGGFXmAsQQMB3At9tPywPzFkvP+4+mmnbypfIJ6PbXSOVLyyQaV4yIIAAAoksYHOOpvPtoUOHyuuvvy66MloDIfoykM5Na9eubVaFXHvttVK8ePF0Ly3pyz8//vij6Pa2upWWvoCkbdGkgQ9dGa3n+ukKE1LiCtgcn4mrRs0RQAABBBBAAIHYCtieoxEAyaB/T5w4Iblz5zY59IyO+fPnZzga8uXLJ7qEXh/AdEWI06QrPp599lmTXR/KrrvuupCX6tkfgwYNMp8vWrTIHGoeTtLgzNy5c80l77zzjrRp0ybd5WkDIKHK1jNchgwZYh5CIznLJfDAGar8nTt3pu7x/Pvvvwc9EyWcdpMXAQQQCEdgxU97pef0r+XPk863VsyTI6u81qW61L+iWDhfRV4EEEAgoQRsP7wols4NdfvZN99808y9NZ0/H82TJ49ZGXL8+HGzukPP7EubNOihSV8M0rl1u3btIprTJlTnJUFlvTA+k4CZJiKAAAIIIIAAAmEJ2J6jEQDJoLv27t1r3iDT1L59e9FDyDNKJUqUMCsl9ED0TZs2OR4Iffr0kVdffdXk14PUr7zyypDXjh8/PnVZvgYyWrdu7fh73n333dSAR/Xq1U2wJVjwQgMgHTt2lFatWkm9evWkbNmy5i06XQny0UcfyfTp0+XUqVPme/Xck8AZKY4rEuQhNaNrCYCEI0teBBCIVkBXfrR7bXVYwY/Ad2oQZE7POqwEibYTuB4BBDwrYPvhJS3M4cOHzfxcV17ry0f68pKTVKZMGfNyk26hFep8PyflkMd7Al4an97ToUYIIIAAAggggIAdAdtzNAIgGfS7/uL9kksuMTn0AUnfMssoaV69ply5cvLzzz87HlHdu3eXKVOmmPxbtmwxAYdQSfNpfk0aiOjcubOj7/nPf/5jVlT88ccfZlXLunXrQm6fpW/S5ciRI+T5IrptwE033ST60KkBlG+++UauueYaR/UIZApn1QgBkLBoyYwAAlEI6BvBTccsd7TtVaivqVAivywaUJ83iaPoBy5FAAHvCth+eAklo1ti6cs9q1atMltb6YtMel5Irly5RLe01T96/l39+vVZWezd4RV1zbw6PqNuGAUggAACCCCAAAIJLGB7jmYlAKKNvuiii2LabTt27JDSpUtH9R1+WQGiFnXr1pVff/3V/EJOD3vs0KFDVDZaRiD40qNHD5k4cWJY5bEFVlhcZEYAgTgJrNqyTzpO/DLqb3vrntpSp1yRqMuhAAQQQMBrArYfXrzmQX28JcD49FZ/UBsEEEAAAQQQQEAFbM/RrARAdAXC3XffbbZPcjsQ8vbbb8uTTz5p9vF9/PHHoxplfjgDRN98a9CggTkwXZMeoN6vX7+oXPTiv//+W4oWLWpWgVxxxRXmUEk3k+0bw822UBYCCCSOQO+ZX8uCTbuirnDzKqVkXKdqUZdDAQgggIDXBJijea1HqE9aAcYn4wEBBBBAAAEEEPCegO05mpUASM6cOc0v0LNnz24CFZ06dZImTZqIHqwdSdKzKd566y2ZOnWq/PTTT6JbmIwYMUIefvjhSIo75xpdLr9v3z6pWrWqrF+/PmR5Bw8elMKFC5vP9aBx3YvYaXrllVdSgxLz5s2Tli1bhry0f//+JoihSYMaFStWDJlXt7tq1KiR2Q5AkwaG/vWvfzmtVqb5dEstLVsPmQwcQJnpRQ4z2L4xHFaTbAgg4COBP06ckmue+B85fea/B+NGk7KmZJH1jzeR/LmyR1MM1yKAAAKeE2CO5rkuoUJpBBifDAcEEEAAAQQQQMB7ArbnaFYCIHo+xgMPPCDz589P3SNdDxu/7bbbpHbt2lKjRg3zi/1Q50RoQEJ/8a5nUSxdutTs9atBD/2jAYvhw4fLvffeG3FAJe0w0dUTK1askLx588qhQ4fMYeDBkh68eP3115uPdOWJ1sFpWrZsmQlUaNLAzSOPPBLy0hPlnXkAACAASURBVKZNm8qSJUtMPQJndQTLfPz4cbn55pvl888/Nx8PGjRInnvuOadVcpRP+0nPEiEA4oiLTAgg4HGBn3b/IU1eXO5aLT95oIFcXjy/a+VREAIIIOAFAdsPL14woA7eFWB8erdvqBkCCCCAAAIIJK+A7TmalQBIoLvXrFljViUsWrTIBC/SBjz0EO4iRYpIoUKFzB/9hb5u56QrLXTbpUDS6zSVLFlSdHVE3759TbDCrTR48GATlNCk9a1Vq1bQokeOHGm29NK0ePFic0i406QrNXQ7KT28sVmzZrJw4cKgl+rnGuA5cuSI1KlTxwR+gqVTp06ZYFKgnF69esn48eOdVsdRPl3Bo/2jdbn88svNyhs3k+0bw822UBYCCCSGwPrfD0nLcV+4Vtn3+9SVay4u6Fp5FIQAAgh4QYA5mhd6gTqEEmB8MjYQQAABBBBAAAHvCdieo1kNgAS6Q395PnnyZHnnnXfkl19+SddLGhgJBDrSfqhbaenKiS5dukirVq3MllpuJ11lEgh69OzZUyZMmJDuK86cOSOVK1eWzZs3S8GCBWXPnj1h1+WWW24xAQtd2aEGwc5GmT17durh5bqaQ1d1nJ9Onz4td9xxh8ydO9d8pDZvvPFGyNU0kXrNmDHDlK2pe/fuMmnSpEiLCnqd7RvD1cZQGAIIJIQAK0ASopuoJAIIWBZgjma5A/j6DAUYnwwQBBBAAAEEEEDAewK252ieCICk7RY9z0O3nNLVDYqzd+9es/IjV65cZvWD/qlSpYrUr19f9AwKXSkS6xTYBkuDE8uXLzerL9KmUaNGyUMPPWR+NHToUBk2bNg5n0+bNk26desW8nP9IO02WLfeequ89957kjVr1tRydNuv6tWri/pokGXr1q1mZUzapEEiDUboWSiaWrduLXoofNpyMrPSFTYbNmyQG264IWRWDQrpVly6JZgGp/Tv1113XWZFh/W57RsjrMqSGQEEfCHg5hkg2VKyyLecAeKLcUEjEEDgXAHmaIwILwswPr3cO9QNAQQQQAABBJJVwPYczXMBEC8OhG+//Vbq1q1rtuHKly+f6LZYDRs2NH/XVRmvv/66qXb58uXNmRj585+757uTAIhe36FDB1OeJi1/wIABUrp0adm0aZM8/fTTsmXLFvOZrkLR1Sjnp4EDB8ro0aPNj3VFiq78yCxApPnSpl9//VUuu+wyufrqq81h7Bp0KVWqlAmiaPDlo48+kunTp4tus6UpFmeLaLm2bwwvjkPqhAACsRfoPfNrWbBpV9Rf1LxKKRnXqVrU5VAAAggg4DUB5mhe6xHqk1aA8cl4QAABBBBAAAEEvCdge45GAMThmNBf/Hfu3NmceREsafDj448/NudhnJ+cBkA0oNKmTRtZsGBB0O9ISUmRIUOGpFthEsh86aWXym+//eawRf/Ndv7WYoEASGaFaEBE66IHvoc6rD6zMjL63PaNEU3duRYBBBJXYNWWfdJx4pdRN+Cte2pLnXJFoi6HAhBAAAGvCTBH81qPUJ+0AoxPxgMCCCCAAAIIIOA9AdtzNAIgYYwJDS689NJLJtChHaerKzTg0bZtW3P4ep48eYKW5jQAErh41qxZotfoVlS6zVSJEiXMll/6Hedvv5X2C90IgOhB6x9++KGsXr3abG21fft20e23Tpw4IQUKFJAKFSqY7bF69Ogh+n2xSrZvjFi1i3IRQMDbAhoUbjpmufy4+2jEFa1QIr8sGlA/JsHhiCvFhQgggIBLAszRXIKkmJgIMD5jwkqhCCCAAAIIIIBAVAK252gEQKLqPi6OlYDtGyNW7aJcBBDwvsB32w9Lu9dWy58nT4dd2Tw5ssqcnnWk8oUFwr6WCxBAAIFEEGCOlgi9lLx1ZHwmb9/TcgQQQAABBBDwroDtORoBEO+OjaSume0bI6nxaTwCCMiKn/ZKz+lfhxUE0eDHa12qS/0riiGIAAII+FaAOZpvu9YXDWN8+qIbaQQCCCCAAAII+EzA9hyNAIjPBpRfmmP7xvCLI+1AAIHIBXQlyANz1jvaDku3vXqhXVVWfkTOzZUIIJAgAokwR9u6davZznXXrl3y559/yn333SdFixZNEGGqGY1AIozPaNrHtQgggAACCCCAQCIK2J6jEQBJxFGTBHW2fWMkATFNRAABBwJ6JsiarQdk+ppfZfH3u+X0mbOpV2VLySJNK5WUzrXLSO2yhTnzw4EnWRBAIPEFvDxH+/bbb2XAgAGycuXKc6A3bdokFStWTP3ZuHHjZPjw4eZ8u3//+9+SPXv2xO8YWmAEvDw+6SIEEEAAAQQQQCBZBWzP0QiAJOvI83i7bd8YHuehegggYEHgjxOnZPeRE3L0r9OSL2dWKXFBLsmfi1+aWegKvhIBBCwKeHWO9vHHH0ubNm3k5MmTosHrQMqSJYucHwA5evSolCpVyqwOmTt3rtx+++0WRflqNwW8Oj7dbCNlIYAAAggggAACiSZge45GACTRRkyS1Nf2jZEkzDQTAQQQQAABBBAIS8CLczTd6qp8+fKigY1KlSrJ888/L/Xq1ZP8+fOb1XnnB0C0wV26dJFZs2ZJ9+7d5fXXXw/LgMzeFfDi+PSuFjVDAAEEEEAAAQTiI2B7jkYAJD79zLeEKWD7xgizumRHAAEEEEAAAQSSQsCLc7SHH35YRo0aJWXKlBHdBqtgwYKmL1JSUkIGQCZPniz33HOPXHvttfL1118nRd8lQyO9OD6TwZ02IoAAAggggAACGQnYnqMRAGF8elLA9o3hSRQqhQACCCCAAAIIWBbw4hztmmuuMas8XnrpJenbt2+qUEYBED0npEGDBlKoUCHZv3+/ZVW+3i0BL45Pt9pGOQgggAACCCCAQKIK2J6jEQBJ1JHj83rbvjF8zkvzEEAAAQQQQACBiAS8OEfTw8x1+6vVq1dLzZo1HQVANmzYYFZ/6AHof/31V0QWXOQ9AS+OT+8pUSMEEEAAAQQQQCC+ArbnaJ4KgHzyySfSuHHjsHvg1KlTMnjwYLP0neQPAds3hj8UaQUCCCCAAAIIIOCugBfnaHny5DFBjHXr1pmgRiBltALk888/l4YNG5rtsg4cOOAuEqVZE/Di+LSGwRcjgAACCCCAAAIeEbA9R/NUACRbtmzSv39/GTFihOTIkcNRF/373/+Wjh07mmXvp0+fdnQNmbwvYPvG8L4QNUQgsQT+OHFKdh0+IcdOnpa8ObJKyQK5JH+u7InVCGqLAAIIICBenKOVLVtWfvvtN3nnnXekVatWjgIgI0eONC9QVa5cWTZu3EjP+kTAi+PTJ7Q0AwEEEEAAAQQQiFjA9hzNUwGQwFtaVapUkZkzZ0qlSpUyhNV9fh999FE5ceKEOeCQAEjE49BzF9q+MTwHQoUQSECBs2fPyuqt+2X66t9kyb93y+kzZ1NbkTUlizStVEI61y4jdcoWMf+GkxBAAAEEvC/gxTlaly5dZNasWealqOnTp2caAPnzzz+lYsWK8vvvv8t9990nr7zyivfhqaEjAS+OT0cVJxMCCCCAAAIIIOBjAdtzNE8FQPSNrffff9/8Iixnzpyib2b9n//zf9J1/86dO6Vr166iW2bpL9jy5ctnDj3s1q2bj4dKcjXN9o2RXNq0FgH3Bb7bflgemLNeftx9NNPCy5fIJ6PbXSOVLyyQaV4yIIAAAgjYFfDiHE2fCW666SbRl6kWLFhg/ltTsC2w9KyQO+64w+TTZ47zt81yS3fPnj2ydu1a8+err74yfwKHrd91110ybdo0t74qtZzZs2fL1KlTzYqWgwcPSsmSJaV+/frSp08fqV27tqPv0zqOHTvWPJP9+uuv5lnrsssuk5YtW5rnsiJFijgqR89jefXVV2XFihWya9cuc9h81apVzTOc+scqeXF8xqqtlIsAAggggAACCCSKgO05mqcCINppkydPlvvvv98cZKgPJU2aNDEPCDqB1/Tuu+9Kr169zF69OiHXyfyMGTNEl76T/CNg+8bwjyQtQSD+Ait+2is9p38tf550vi1hnhxZ5bUu1aX+FcXiX2G+EQEEEEDAsYBX52iBF6l0G91+/fpJ27ZtzXOCPk/oeR962PmSJUtkwoQJ5hfymu68804TMIhFymhlo9sBEF0Nr+2dP39+0KZoIGjYsGEyZMiQDJuqQZrbbrtN9GWzYKl06dLywQcfyHXXXZdhOU888YQMHz5czpw5EzRfixYtZM6cOZIrVy7X6b06Pl1vKAUigAACCCCAAAIJJGB7jua5AIj23ZYtW6Rz587y5ZdfmoeWwoULmzeR9KHlzTffNIEPPS/kX//6l/mjk3qSvwRs3xj+0qQ1CMRPQFd+tHttdVjBj0DtNAgyp2cdVoLEr7t89U16zsyWPUfl94PHReSsXFwoj5Qrni/qs2Y4v8ZXw4TGuCDg1Tmabmv1z3/+Uz777LMMt1XU5whNjRo1MgEDXXUei5Q2AHLxxRfLVVddZZ5lNLkdAOnUqZPZAkyTHuyuZypqsELPSHzmmWfMs5WmiRMnSo8ePYI2d/v27VK9enXZvXu3ec564IEHjKcmdRo9erT8/fffUqJECfn666/lwgsvDFrOpEmT5J577jGflStXzpyzotsb79ixw6zY//TTT81nWmd9ic3t5NXx6XY7KQ8BBBBAAAEEEEgkAdtzNE8GQLQD9Y0hfXtIJ+062Q48ROhDy+WXX24mzDVr1kykvqauYQjYvjHCqCpZEUDgfwX03+emY5Y72vYqFFqFEvll0YD6nAnCqHIkoGNu1ZZ98tInP8naXw+mu0ZPlqlxWWEZ0OgKqVPO+VkznF/jiJ9MSSrg5TmaPj+8+OKL5pf1oVYx6ItVDz74oDz00EMxfYlq6NChUqNGDfNHgwa6nZRuJaXJzQCIrm654YYbTLm6smLevHmSNWvW1NG5b98+E9jYtm2b2YZq69atUrBgwXSjV7emeuONN8zPdXWGrihJm/SA+Xbt2pkf6bbDU6ZMSVfGoUOHTBv1fy+55BITKClatGhqPj2v8fbbb5ePPvrI/Ezr3qBBA1fvJC+PT1cbSmEIIIAAAggggEACCdieo3k2AKJ9qJNkPcxQJ9waANFfSBQoUEC+/fZbufTSSxOom6lquAK2b4xw60t+BBAQ84vojhO/jJrirXtqm19WkxDISEBXG/We+bVsO6ArPjJPlxTOI692qpbpCiPOr8nckhzeEoj3KqVEmKPpy1N69oae76FncegzhZ5dce2110q9evVituojo5ERqwBI8+bNzXkmGvTQ77jooovSVUPPBunQoYP5+fPPPy8DBw48J4+u+tAVHerUtGlTWbRoUdCmNGvWTBYvXmy+S1eMaGAnbRo1apQJLGl66623gp71oeNHn+P0u3SFSSAY4tZdlQjj0622Ug4CCCCAAAIIIJAoArbnaJ4NgOjbSbo0Wh9eNPCh21zpW10aCNHJtr51pJNwkj8FbN8Y/lSlVQjEVkB/Gb1g03/3VY8mNa9SSsZ1qhZNEVzrcwE9Z6bHG+vkr7+D7y8fqvk5s6XIpLuuC3nWDOfX+Hzg+Kh5NlcpeXGOplvkaqpQoYLUqlXLkz0diwCInpmoKyz++usv81y0cOHCoG0/efKkFCtWTI4cOSLXX3+9fPHFF+fk062x7r33XvMzDZa0b98+aDlpAymvv/566lZXgcx169aVVatWyQUXXCB79+4VPY8lWAoEUnT7MV2hki9fPtf6zIvj07XGURACCCCAAAIIIJCgArbnaJ4MgOhhhLp37bFjx0zwQyfJr732mrz88stmSXsgENK7d2/RN41icYBego4n31Tb9o3hG0gagkCcBPQN5Gue+B85fea/e6tHk7KmZJH1jzeJ+uyGaOrAtd4V0BUabcavkhNhBj8CLcqVPUXm9ro+3UoQzq/xbp9Ts3MFbK9S8uIcTV+U0pekdNVBYJsmr42bWARAli1bZs4y0TRixAh55JFHQjZbV3boGSR6voeel6KHwgeSHgY/ffp081fdOqxkyZJBy9HP9GwRTXpNYMss/bsGWfLmzWu2Ls5oFUmgrno2iCZtg55b4lby4vh0q22UgwACCCCAAAIIJKqA7TmapwIgBw8eNG8S6d61GvjQwMazzz4r/fr1S+1fPdhQ9839/fffzYPOlVdeKTNnzpRrrrkmUccA9Q4iYPvGoFMyFoj3dhv0h/cFftr9hzR5cblrFf3kgQZyefH8rpVHQf4Q0LnBTS9+Lj/tORZVgyqUyCeLBjQ453wxzq+JipSL4yTghVVKXpyj6dkWurpBt7zSba68mGIRABk3bpz07dvXNFefn1q2bBmy6fpy2dixY83n33//vVSsWDE1r55Tona61bCe35FR0jxqrdfoSv1A0jIrV65s/qrfNWbMmJDFaF1btWplPtc26EttbiUvjk+32kY5CCCAAAIIIIBAogrYnqN5KgCie8/u2rXLBD+uvvpqmTVr1jmT80AnHz58WHr16iVvv/22+eWFvsE0fPhwefjhhxN1HFDv8wRs3xjx6pBECiTY3G4jXv3B90QusP73Q9Jy3LlbakRemsj7ferKNRenP6Q1mjK5NvEF3DpnRiXSnjXjVrkZnV+TSP/eJ/5I8WcLvLJKyYtztGrVqsmGDRvkf/7nf+TGG2/05ACIRQBEV3zoy2KavvrqK7nuuutCtl3P/hg0aJD5XM/40FUagaQrPvQckEqVKsl3332XoZ8GOTTYodekPWhey7z55pvNtbpCXw+aD5U02KIBFE3aBl294jTp+MsoaZ1q1qxpsugLc8HORHH6XeRDAAEEEEAAAQQQcEfA9jOEpwIggeXrAwYMMBPhUPvGBuhnzJhh3nrSt5A0EKKH6ZH8IWD7xoilYiIGEmxvtxHL/qBsdwRYAeKOI6VkLODWOTP6LWnPmnGr3PPPr0nEf++9PAaTOYikY8krq5S8OEd78sknZejQoWblwYsvvujJYRyLAEifPn3k1VdfNe3dvHmzWRkfKo0fPz51pcXcuXOldevWqVl16yrdFkvPT1mzZk2GfppHV37ouR1//PFHat533nkndfsx/S59WS1U0roGVqDos5xuc+w06TOf00QAxKkU+RBAAAEEEEAAgdgK2H6G8FQARFeA6CGGgb1sndBv27ZNOnfubA7zIwDiRCwx8ti+MWKllIiBBC9stxGr/qBc9wTcPAMkW0oW+ZYzQNzrHJ+UpGOs6vAl4sIxM0Yka5Yssn5oE/PfsTi/JhH/vffiUCGI9N9eiccqJaf978U5mr4MVbVqVbMiYcGCBZ5cBRKLAEj37t1lypQppuu2bNkiZcuWDdmNmk/za9LzPvT5KZCyZs1qzlisX7++LF+e8XaWDRo0kBUrVoheo+d9BJKWqeeCaJo8ebLcfffdIeuydetWKVeunPlc6zRp0iSnwy9160InFxAAcaJEHgQQQAABBBBAIPYCtp8hPBUAOXDggBQuXDhsdX04HjlypDz66KNhX8sF3hSI940Rj7dKEzGQ4JXtNrw5SqnV+QKxeoseaQRUwO1VRlqmnjVz9qy4fn7NzsMnpOf0r+XPk85XpubJkVVe61Jd6l9RjA7/XwGCSP9/KHjp39d4z9Gc3hA///yztGnTxmzP1K1bN+nYsaPZUlfPBwln1YDT7ws3XywCIMm4AoQtsMIdeeRHAAEEEEAAAQTsC9h+hvBUAMR+d1ADrwjE48aI51uliRhI8NJ2G14Zl9QjYwEvvaFMX7kvEE6gOJy8Tmvq9jkz+r161owmN8+veaFdVRny/ndhBT8CBhoEmdOzjlS+sIBTFt/mS8SXBmLVGW6usMuakkXWR7nCLh5ztHAtdTVCIOn8JZyAh+ZNu5Ih3O92mj8WAZBkPAMkM28vjs/M6sznCCCAAAIIIICA3wVsz9EIgPh9hCVo+2J9Y8TzrdJEDSTwy+wEvXksVjtRx7pFMs9/dTiBYm3M6q37Zfrq32TJv3fL6TR7VekvXZtWKiGda5eROmWLhPXLyQBSoqwAubRIHvl1/58R922FEvll0YD6ERlF/KUeuzARXxqIJaHbY19XPl1ePH/EVY71HC2Siuk5gpGmeJ0jGIsAyCuvvCL9+vUzTZ83b560bNkyJIOejzJ27Fjzua6SCZzBoX/Xw9O//vprKVCggBw6dChDSs2jW47pIeZ6Fkgg6eHpVapUMX/V7xozZkzIcrSurVq1Mp+PGzcu9WySSPsw7XVeHJ9utIsyEEAAAQQQQACBRBawPUfzVABE375atGiR2Vd2w4YNsn//fjPBvuCCC6RIkSJmb1/dm7ZZs2aSLVu2RO536p6JQCxvjHi/VZqogQQvbbfBDZM4AvziMnH6KrOahhMovqRwbhHJItsOZP6L//Il8snodteEvcrB7TNAAmfNqINbZ4CkZBFXzih5657aUqdckcy6yJefE0hN361ur37SlU/XXFww4vETyzlapJUaPnx4pJea6/QA9VinWARAli1blnp24ogRI0RXhIRKTZs2lSVLlphnqGPHjkmOHDlSs+rZHXqGhyY9R6VkyZJBi9HPSpcubT7Ta954443UfCdPnpQ8efKYMxn1u/SZLlTSug4ePNh8rG1o2LCha/xeHJ+uNY6CEEAAAQQQQACBBBWwPUfzRABEH3ZHjx4tL774opl0Z5Z0Un7//ffLAw88ING88ZXZ9/C5PYFY3Rg2fjmbiIEEr223YW8k8s2RCMQ7yBhJHbkmY4FI+jAc00jPu3Dr31Ota/MqpWRcp2qm2m6VW/KCXLLryIlwKILmTVu3qAtLsAIS9aWBWDKzAiSWuvErOxYBkD/++EOKFi0qGnzQF8QWLlwYtEH6ebFixcyLZXXq1JFVq1adk+/111+Xnj17mp/Nnj1b2rdvH7Qc/axDhw7ms9dee03uvffec/Jdf/31snr1avPy2t69e88JsqTNqHVdvHix5MyZ0+TLnz/yFUnnVzRWzxDxGyl8EwIIIIAAAggg4D8B23M06wGQ3bt3mwMLAxNxDYY4SbpcvXbt2jJ37lwpVaqUk0vIk0ACsbgxbLxVmqiBBK/9siWBhi5V/V+BcFYP6JY/em4C5x54Y/hEEygOpwWRnHfh1i/HtZ5pV1m4Va5bK0DcOKchnL7wUl63glF+CiK5OZcIrHzKnyt7xN0eizlaxJVJoAtjEQDR5t9yyy0m8KErO3755Re56KKL0qmkDVw899xzMmjQoHPy7Nq1Sy688EI5c+ZMhqs3AoELfQFt+/bt6VaKaNkPP/ywKfutt96SO+64I11ddPxceumlZqWI1v3jjz92tRcZn65yUhgCCCCAAAIIIOCKgO05mtUAyOHDh6VBgwaie8bqL6dz5colt99+u9x6661SrVo1KVGihOTNm1eOHj0qGij55ptv5MMPP5T3339fTpw4YfbHrlSpktkyS/ejJflHIBY3hlu/4Apna5JEDSR4bbsN/4zs5GqJ/ru+ZusBmb7mV1n8/blnQugv4ZpWKmnOhKhdtnBSn3fgpVHhRqA4nPaEe96F1u+mFz+Xn/YcC+dr0uWtUCKfLBrQIHXcudHuaM/+OL+S0Z7TEBWQpYvd/EW/34JIXgoMxWKOZmnIxfVrIwmATJs2Tbp162bqqdt0DRs2LF2d026Dpc9Q7733nqQ9FH7fvn1SvXp12bZtmxQsWFC2bt0qhQoVSldO2m2w3nnnHfOCWtqkP2vXrp350V133SVat/PTgQMHpGzZsqLPeGXKlDHniug2xoGkQQ991vvoo4/Mj9ze/krLZHzGdVjzZQgggAACCCCAgCMB23M0qwEQnWjPmDHDQOkbQBMmTAj61tL5kr///rv06tXLvO2kQZCOHTum7lvrSJ1MnheIxY1h45cHiRpISNTAjecHdhJXUH+xufvICTn612nJlzOrlLggl0TzBnISU8a06W4FisOpZDhBZS1XV6i0Gb9KTvx9JpyvSc2bK3uKzO11fboVR9GsfNHVLE/eVlkGvrMhojoFuyjacxpcq0gcC+L/e0Jju3Vvhnu/BatRLOZocRxmcfuqlStXys8//5z6fRqICKy8qFu3rvTo0eOcunTt2jVd3ZwEQPQi3ZZKV3lo0vM0BgwYYM7q2LRpkzz99NOyZcsW85k+awW2ugr2fKWBEt2SSleTDBw4UP75z3+abPPnz5cXXnhB9LxG3UpLX0oLttJE8+rWWPqcpqlcuXLy2GOPmcPRd+zYYQ5G//TTT81nWudZs2a53h+MT9dJKRABBBBAAAEEEIhawPYczVoARA8511UemjSA8eabb4b1BrC+rdmlSxczcdZl2PqGkR6STvKHgNs3hq23ShP1lzluermx3YY/RjWtQMD7Am4FisNpaSRbFekZJT3eWCd/hRkEyZktRSbddZ3Uv6JY0CpGcvZJ4DwTPf+jyYvLw2l6hnmTcQVIor404FqnZ1CQG6uUwl1xFao6bs/R3PB74oknoirm8ccfj+r6YBdrQCPtIeGZfUGwbYCdBkCOHz9uVmwsWLAg6Nfos9KQIUOCriBJe8GXX34pLVu2FN0SK1jScxh1JX6tWrUybI6uVnnyySfNCv9gSV98e/fdd83qf7eTF8en222kPAQQQAABBBBAINEEbM/RrAVAHnnkEdF9Yi+55BLZvHmz5M6dO+y++/PPP+Wqq64yS50ffPBBefbZZ8Mugwu8KeD2jWErEJHIgQS3fhEayS83vTkqqRUC/hZw89+rcKQi3apIV2zov1PbDhx39HVliuSRcR2rZXrWTKTn17jpl6yBY1v/X+1oAHkgU7SrlOb0rJPp+HfSTLfnaE6+M7M8+gt+XRUeadKtmdxO8QyABOquL4Zp0ERfNDt06JDZTrh+/frSt29fc/i5k6QrVV566SUT6NBtuzRddtllctttt5mVJWm3tMqoPD3fcdy4cWarYt3KWLff0pfVdEuvwEHqTuoTbh4vjs9w20B+BBBAAAEEEEDAbwK252jWAiDXXXedozeDxQAAIABJREFUfPvtt2Y/22jeutI3vnQ/XF1Nsm7dOr+Nj6Rtj9s3hs23ShM1kOCl7TaS9kag4QjEUcDtXz6HU/VIVzvo28Wrt+yXl5b+KF/+cjDdV+qvQ2teVlgGNL5Capct4vgXpJGeX5Oo/96H01exzEsQKXPdaFYphVr5lPm3npvD7TlauN8fLL8GQMJJGixJuzpBD/8m+UPAi+PTH7K0AgEEEEAAAQQQiFzA9hzNWgBEl1DrHrNLliyRRo0aRSy4dOlSadKkiRQvXjzkcu2IC+dCawJu3xhu/2IvnF/WJWogwUvbbVgbiHwxAkkk4HagOBw6N8670F+eb9171KwIySJn5eLCeaRssXxRnzUTzvk1ifrvfTh9Feu8BJEyF450lVLmJTvL4fYczdm3Rp9LV47/8MMPMnPmTHn55ZelRo0aZhsmXSVB8o9Aoo5P//QALUEAAQQQQAABBNIL2J6jWQuA5MyZ0xykp2d3XHPNNRGPjfXr15vVHzly5JATJ05EXA4XekvA7RvD5luliRxI8Mp2G94andQGAX8KuB0oDkcpnKByOOXGO28i/3sfb6tQ30cQyVlPRLpKyVnpGedye47mRp3CLWP58uXStGlTqVChgqxZsyYmZ1GEWyfyuyPgh/HpjgSlIIAAAggggAAC3hGwPUezFgApVaqU7NmzRxYvXiyNGzeOuEdYARIxnacvjMWNYfOt0kQOJHhhuw1PD1Yqh4BPBNwMFIdD4rfzLhL53/tw+i1WeQkihS8bziql8EtPf0Us5mhu1CvcMu6//34ZO3asPPPMM/Lwww+Hezn5PSrgl/HpUV6qhQACCCCAAAIIRCRge45mLQBSs2ZNs/pjyJAh5gyPSNPw4cNF/1SvXl2++uqrSIvhOo8JxOLGsP1WaSIHEmxvt+Gx4Ul1EPCtgFuB4nCAmlcpJeM6VQvnEs/nTeR/772ASxDJC70Qug6xmKPZaPGyZcvMS1h6MLeeS0jyh4Bfxqc/eoNWIIAAAggggAAC/xWwPUezFgAZPHiwjBw5Ui6++GLZvHmz5MmTJ+wxcezYMbnqqqtk+/bt8tBDD8mIESPCLoMLvCkQixvDC2+VJnIgweZ2G94cpdQKAf8JuBUoDkfmrXtqS51yRcK5JCHyJvK/914AJojkhV4IXodYzNFstDawjW6+fPnkyJEjNqrAd8ZAwC/jMwY0FIkAAggggAACCFgTsD1HsxYA2bhxo1x77bUGvlOnTvLmm2+G3Ql33nmnzJgxQ1JSUuSbb76Rq6++OuwyuMCbArG6MbzwVqkfAgnx3m7Dm6OUWiHgPwE3AsXhqFQokV8WDagvWbJkCeeyhMnrh3/vbWITRLKpH/q7YzVHi3dr3377benQoYMQAIm3fGy/zy/jM7ZKlI4AAggggAACCMRXwPYczVoARJkDAQz9xUfz5s1lwoQJUrp06Ux7YMeOHdKzZ09ZsGCByduxY0eZPn16pteRIXEEYnljeOmtUgIJiTMmqSkCySIQTaA4HKM8ObLKnJ51pPKFBcK5LGHz8u99ZF1HECkyt1heFcs5WizrnbbsQ4cOSb169cwq9Bo1apiD0En+EPDD+PRHT9AKBBBAAAEEEEDg/wvYnqNZDYAcPnxY6tevL9999515+zNXrlzSqlUradGihVSrVk1KliwpefPmlaNHj8quXbvM/rwffvihzJs3T06cOCH6UFypUiVZuXKlFCiQHL9ASZabJ9Y3Bm+VJstIop0IIBCJQCSB4nC+R4Mfr3WpLvWvKBbOZeRNcgGCSN4YALGeo0XSyuXLl2d62ZkzZ+TgwYOybt06mTp1quzevdtcM27cOOnVq1em15MhMQS8OD4TQ45aIoAAAggggAACsROwPUezGgBR1p07d0rr1q1T37xysg2GBj401apVS959911Hq0Zi14WUHAuBeNwYvFUai56jTAQQ8ItAOIHiMoXziP4/87YDf2bafN326oV2VZNm5UemIGRAIMEE4jFHC5dEt8N18gwRKDfwLHH77bfL3Llzw7o23LqRP74CXhyf8RXg2xBAAAEEEEAAAe8J2J6jWQ+AaJecPn1aXnjhBRkzZoxZ6ZFZKlGihPTv318GDRokWbNmzSw7nyegQLxvDN4qTcBBQpURQCDmAuEEirUya7YekOlrfpXF3++W02f++7KCpmwpWaRppZLSuXYZqV22ML9sjHnP8QUIxE4g3nM0Jy3RAEg4Sc8N7N27t9xzz/9j7z7AoyrWPoC/JJRQQofQS6hSIzWhFxEEURCIdKR9cAEFERBEukoTBJReJdSIwqUTBSQBAigSpAkYpDyUAEoJHRK+5517d2/Kbvbs7tmd2bP/eZ7vUZM5c2Z+M+d+c/KememL/z2yB84D8qo4Pj2ADVWEAAQgAAEIQAACLhWQPUdTIgBiEn7+/Dnt3LmTeBn78ePH6fbt2xQfH0/+/v6UJ08eqlq1KjVo0IBatGhBGTNmdGnHoHC5ArIfDLmtx90hAAEIqCdgT6DYnrzqtRQ1ggAE0hJQcY62b98+m53GQRJ+pyhZsiS2zrWp5bkZVByfnquJmkMAAhCAAAQgAAF9BGTP0ZQKgOhDilKMICD7wTCCIdoAAQhAAAIQgAAE9BbAHE1vUZSnpwDGp56aKAsCEIAABCAAAQjoIyB7joYAiD79iFJ0FpD9YOjcHBQHAQhAAAIQgAAEDCGAOZohutGwjcD4NGzXomEQgAAEIAABCHiwgOw5GgIgHjx4jFx12Q+GkW3RNghAAAIQgAAEIOCoAOZojsrhOncIYHy6Qxn3gAAEIAABCEAAAvYJyJ6jKRUAuXz5sn16KXIXK1bMqetxsToCsh8MdSRQEwhAAAIQgAAEIKCOgIpzND5H8Pz58wKpVKlSlClTpmRgT548odGjR1N4eLg4Y5DPAeFD0AcNGqQOLGqii4CK41OXhhmkED4j7Ma9J/TwWQJlzehLBXL4kb9fBoO0Ds2AAAQgAAEIQMCagOw5mlIBEF9fX4dHSrp06ejFixcOX48L1RKQ/WCopYHaQAACEIAABCAAATUEVJyjcWCjU6dOlDdvXrpy5QplzJgxGdYbb7xBERER9PLlS/PP+d2BAyCzZ89WAxa10EVAxfGpS8M8uBB+7qIv/E1h0Zco4nQcJST+7zn09UlHzSsGUNfg4hQSmIf4uUSCAAQgAAEIQMB4ArLnaEoFQHx8fBzuYZ4sJSQkOHw9LlRLQPaDoZYGagMBCEAAAhCAAATUEFBxjta7d29avnw59evXj+bPn58Matu2bdS6dWvxh9XChQtTzZo16ciRI3T16lXxs/3791NISIgauKiF0wIqjk+nG+XBBZy8eo+GhsfQubgHNltRNiAbzQwNokqFc9jMiwwQgAAEIAABCHiWgOw5mlIBkG+//dZm7z18+JDOnj1L33//PV27do3q1KlDffv2Fdf16NHD5vXI4BkCsh8Mz1BCLSEAAQhAAAIQgIB7BVSco7366qv0+++/06pVq8RKkKSpffv29MMPP1C5cuVE4MPf35/u3bsn3iH++OMPeu+992jp0qXuRcTdXCag4vh0WWMVLzjq/C3qF3aUHj3T/pFiloy+tLBbdapfJp/irUP1IAABCEAAAhCwR0D2HE2pAIg9cLzX7wcffECLFi2ijz76iKZNm2bP5ciruIDsB0NxHlQPAhCAAAQgAAEISBFQcY7GKztu3LhBBw8epNq1a5tdEhMTKXfu3BQfH09z5syhgQMHmn/HK0X4vzkwcubMGSmWuKn+AiqOT/1bqX6JvPIjdGG0XcEPU6s4CBLeLwQrQdTvZtQQAhCAAAQgoFlA9hzNYwMgJuHGjRtTZGQkbd++nZo3b64ZHhnVFpD9YKitg9pBAAIQgAAEIAABOQIqztH40HM+C/C3336jqlWrmmH4v2vUqCG2uoqNjaUSJUqYfxcVFUUNGzakLFmy0IMHtrfnkaONu9oroOL4tLcNnp6fz/xoPitS07ZX1tpaLsCfdg6pjzNBPH0woP4QgAAEIACB/wrInqN5fACEDz3s2LEjtWzZkrZu3YqBZRAB2Q+GQRjRDAhAAAIQgAAEIKCrgIpzNN7W6tGjR+Kg86ZNm5rbO2vWLBo6dCgVLVqULl26lMwhJiaGqlWrRhw8efz4sa5GKEyegIrjU56GnDsfjL1NnRcfdvrma/sGU0ipPE6XgwIgAAEIQAACEJAvIHuO5vEBkGPHjlH16tUpf/78Yuk7kjEEZD8YxlBEKyAAAQhAAAIQgIC+AirO0SpXrkynT5+mSZMm0SeffGJuMAdDfv75Z+rcuTOFhYUlg9izZw+99tprVKRIEbp8+bK+SChNmoCK41MahqQbD1h9lLafcP69vFXlgjS3SzVJrcBtIQABCEAAAhDQU0D2HM3jAyD8UtOkSRN8vaXnqFSgLNkPhgIEqAIEIAABCEAAAhBQTkDFORqfC/jNN99QQEAAcWDjlVdeoc2bN1Pbtm2Fn6XD0flMkCFDhlDNmjXp8GHnv1ZXrqO8tEIqjk9v6or4J88paOKPlJD40ulm+/qko5ixzcjfL4PTZaEACEAAAhCAAATkCsieo3l8AKRnz5707bffij19L1y4ILc3cXfdBGQ/GLo1BAVBAAIQgAAEIAABAwmoOEc7f/488SqQ58+fC+lcuXLRnTt3iM8i4BUef/75J2XMmDFZL7z55pu0Y8cO6t+/P82dO9dAPeTdTVFxfHpTj5yPi6dmX0Xq1uSfhjag0vn9dSsPBUEAAhCAAAQgIEdA9hzNYwMg/KIzY8YMWrRokTgc7V//+pf48gvJGAKyHwxjKKIVEIAABCAAAQhAQF8BVedo3333HfXq1YsePnxobnDOnDlpy5YtVLdu3WQIvG1u8eLFxcHp33//PbVp00ZfJJQmTUDV8SkNxM03jrlyl9rMPaDbXTcNrEtBRXPqVh4KggAEIAABCEBAjoDsOZpSAZDAwECbvZCYmEh3796l+Ph4kZe/7OLl7r/99hsVLFjQ5vXI4BkCsh8Mz1BCLSEAAQhAAAIQgIB7BVSeo928eZO2bdsmzgXk94K33nqLcufOnQqID0tfu3at+Pns2bMpe/bs7kXE3VwmoPL4dFmjFSoYK0AU6gxUBQIQgAAEIKCQgOw5mlIBEB8fH7u7Jjg4mJYvX07lypWz+1pcoK6A7AdDXRnUDAIQgAAEIAABCMgTwBxNnj3ubFsA49O2kStz6HkGSHqfdHQMZ4C4srtQNgQgAAEIQMBtArLnaEoFQPg8D1uJgyT+/v5UsmRJatiwIQUFBdm6BL/3QAHZD4YHkqHKEIAABCAAAQhAwOUCmKO5nBg3cEIA49MJPJ0uHbD6KG0/ccPp0lpVLkhzu1RzuhwUAAEIQAACEICAfAHZczSlAiDyuwM1UEVA9oOhigPqAQEIQAACEIAABFQS8NQ5WlxcHG3dupVu374tPqRq3bo1Zc6cWSVa1EUHAU8dnzo0XZkiDsbeps6LDztdn7V9gymkVB6ny0EBEIAABCAAAQjIF5A9RzNMAOTXX3+lGjVqyO9R1EAXAdkPhi6NQCEQgAAEIAABCEDAYAIqztHOnDlD48aNo3Tp0tHChQuJDz9PmjZv3kydO3emx48fm39ctGhR4p9XqVLFYD3k3c1RcXx6W4/wGZ3NZ0XSubgHDje9XIA/7RxSXzzTSBCAAAQgAAEIeL6A7DmaxwdADhw4QJ999hn9+OOP9OLFC88fEWiBEJD9YKAbIAABCEAAAhCAAARSC6g4R5s8eTKNHj2aGjRoQD///HOySvPB6KVLl6YHD1L/MZaDIKdPn6asWbOiqw0ioOL4NAitXc04efUehS6MpkfPEuy6jjNnyehL4f1CqFLhHHZfiwsgAAEIQAACEFBTQPYczWMDILt37xaBj8jISHPPJiTYP8FSc1igVrIfDPQABCAAAQhAAAIQgIBnBEBee+012rt3L02dOpWGDRuWrNLjx4+niRMnUvr06WnatGnUtGlT2rVrF40cOZL4S/UZM2bQkCFD0NUGEfCWdwg+bPzGvSf08FkCZc3oSwVy+JG/XwalejHq/C3qF3bUriAIBz8WdqtO9cvkU6otqAwEIAABCEAAAs4JyJ6jSQ+A8IvHpk2bxAqOK1euiJeTEiVKUPv27alu3bqpdPnlhr/wOnz4P/uK8vWcXn/9ddq5c6dzvYGrlRGQ/WAoA4GKQAACEIAABCAAAYUEVJyjlS1blmJjY8W7QLNmzZJp8RZXp06dop49e9KSJUvMv+vXrx8tXryYGjVqRHv27FFIGFVxRkDF8elMe5Jey++90Rf+prDoSxRxOo4SEv/zHszJ1ycdNa8YQF2Di1NIYB5lto7ilSBDw2M0bYfF217NCK2KlR96DRiUAwEIQAACEFBIQPYcTWoAhAMeb7/9Nh0/ftxil3AQZM2aNeTr60t///039enTR+zVy8kU+GjVqhWNGTOGatWqpVC3oirOCsh+MJytP66HAAQgAAEIQAACRhRQcY6WK1cuun//Ph09epSCgoLM7HzgeUBAgPhv/tiqSZMm5t9t27ZNHISeL18+4gPSkYwhoOL41EPWnkBC2YBsNDM0SJlAAr+3H7rwD4Uduki7TiUP3KQXgZsCInATHJhbmcCNHn2GMiAAAQhAAAIQ+J+A7DmatADI8+fPqWbNmvT7779bHQ986NngwYNp6NChYk/fS5cuicAH/7xt27b06aefJnvJwcAyjoDsB8M4kmgJBCAAAQhAAAIQ0E9AxTlapkyZxFmAfDZgcHCwubG8yvydd94h/v3du3fFP03pt99+oxo1alCGDBno6dOn+gGhJKkCKo5PZ0GMtJUUb90Vd/8JPXiaQNky+VJAdvW27nK2v3A9BCAAAQhAAAKpBWTP0aQFQMLCwqhHjx4imPHKK6+IfXirVasmVnvwYYRfffUV7d+/nzJnzkzVq1cX/86pZcuWYn/fihUrYjwZWED2g2FgWjQNAhCAAAQgAAEIOCyg4hytYMGCxIedr127lkJDQ81te//992nu3LliW92oqKhkbT5y5IgIlvDqEV5pjmQMARXHpzOyOEzcGT1cCwEIQAACEICAKgKy52jSAiBt2rQR21kVKlSI/vjjD8qWLVuyPklMTBQvK6azPnx8fMQLDO/Xi2R8AdkPhvGF0UIIQAACEIAABCBgv4CKc7QWLVqILa54Syte9cHp8ePHVLJkSbp165ZYNT5hwoRkjf3uu+/o3XffpfLly4uPr5CMIaDi+HRUlnc+aD4rUtP5Gdbuwedq7BxSH1tLOdoJuA4CEDC8AK9Mu3HvCT18lkBZM/pSgRxqrUxTvX6GHyBooG4Csudo0gIg/EJy+fJlsdLjgw8+sAjKLzLNmzcXE7ZOnTrRqlWrdINHQWoLyH4w1NZB7SAAAQhAAAIQgIAcARXnaCtWrKBevXqJd4YOHTpQvXr1aP369WJLLP6I6uTJkyLQkTQNGzaMZs6cKVaXb926VQ4m7qq7gIrj09FGHoy9TZ0XH3b0cvN1a/sGU0ipPE6XgwIgAAEIGEWAA8zRF/6msOhLFHE6+dlEvuJsogBxNlFIYB4pAWTV62eUcYB2uFdA9hxNWgCEV3zwl1kpDyRMys9L2QsUKCD+B4e/5uKvupC8Q0D2g+EdymglBCAAAQhAAAIQsE9AxTkarxxv1KiR2DKX3xtMif+A0Lt3b1q8eHGqRgYGBorzBadPny7OG0QyhoCK49NR2QGrj9L2Ezccvdx8XavKBWlul2pOl4MCIAABCDgioNoKBt5acGh4jKbVdWUDstHM0CCqVDiHI0136BrV6+dQo3ARBIhI9hxNWgCEv8biF5QTJ05QhQoVrA4GUz4+qLBq1aoYNF4iIPvB8BJmNBMCEIAABCAAAQjYJaDqHO3hw4c0btw44q2tbty4QXwuCJ83OGbMGEqfPn2yNm7ZsoXefvtt8S4SExNDlStXtssAmdUVUHV82ivGfzAMmvgjJSS+tPfSVPn5a+aYsc3I3y+D02WhAAhAAAJaBFRdwRB1/hb1CztKj54laGmGyJMloy8t7Fad6pfJp/kaRzOqXj9H24XrIMACsudoHhMAsRUowXAyloDsB8NYmmgNBCAAAQhAAAIQ0EfACHO0O3fu0P379wVI8eLF9YFBKUoIGGF8MuT5uHhq9lWkbqY/DW1ApfP761YeCoIABCBgTUDVFQxcr9CF0XYFP0xt5CBIeL8Ql64EUb1+GPEQcFZA9hwNARBnexDXu0RA9oPhkkahUAhAAAIQgAAEIODhApijeXgHGrz6RhmfMVfuUpu5B3TrrU0D61JQ0Zy6lYeCIAABCFgSUHUFA69IaT4rUtO2V9Z6tlyAP+0cUt8lZ4KoXj+MdgjoISB7jiY9APLZZ59R4cKFrVq+99574n9gbOXjArp3765Hn6AMBQRkPxgKEKAKEIAABCAAAQhAQDkBzNGU6xJUKImAUcYnVoBgWEMAAp4moPIKhoOxt6nz4sNOk67tG0whpfI4XU7KAlSvn+4NRoFeKSB7jiY9AKJXr3OQ5MWLF3oVh3IkC8h+MCQ3H7eHAAQgAAEIQAACSgqoPkf7888/aeXKlRQdHS3OAnn8+DHt3LmTSpcubfY8efIkXb58mbJmzUoNGzZU0hmVckxA9fGptVV6ngGS3icdHcMZIFrpkQ8CEHBAQPUVDANWH6XtJ2440LLkl7SqXJDmdqnmdDkpC1C9fro3GAV6pYDsOZrUAIiePc4BkIQE7QcZ6XlvlKW/gOwHQ/8WoUQIQAACEIAABCDg+QKqztESExPp448/plmzZhH/O/8xhhO/I6Q8S3DHjh3UqlUrcTj6X3/9leZqdM/vMe9qgarj05FewB/EHFHDNRCAgAwBlVcw6BlQ9vVJRzE6B5RVr5+M8YR7GlNA9hxNWgDk22+/1b1He/TooXuZKFCOgOwHQ06rcVcIQAACEIAABCCgtoCqc7S+ffvSsmXLROCDt9cNCQmhDRs2WAyAsDCvCOHgx8yZM2nw4MFqo6N2mgVUHZ+aG5Ako8p/UHSkPbgGAhAwroDKAVvVtxRUvX7GHbVombsFZM/RpAVA3A2tx/14qfycOXNo27ZtYtl8pkyZxMtTaGgoDRgwgLJkyaLHbWjdunW0fPly+v333+nOnTtUoEABql+/Pg0cOJCCg4PTvMfZs2dp+/bttG/fPjp+/LhY+s9fvgUEBFCtWrXEOSktW7bUfHATbx8wb948ioqKEmXlypWLqlatSnw2S8eOHXVpr6VCZD8YLmsYCoYABCAAAQhAAAIeLKDiHO3nn3+mJk2aiPntqFGjaMKECeTr60s+Pj5WAyCcb+rUqfTWW2/Rpk2bXNoj7niH4PeGb775htji6tWrov1FixYVK10GDRpExYoVs9pGntfb+3Eav6vwdUkT37tx48aaLMeNG0fjx4/XlNeeTCqOT3vqnzSv6lvKONouXAcBCBhLQPUVDDFX7lKbuQd0Q980sC4FFc1pszx2uXHvCT18lkBZM/pSgRx+5O+XIdV1supnswHIAAGdBWTP0RAA0dihHPTo0qUL3bt3z+IV5cqVE4GHwMBAjSWmzvbkyRPq0KEDbd261WIZ/BLHLwpjxoyx+HteAcN7HttKzZs3F0GWnDnT/h/tiRMnihdI3kbAUmrdujWFh4eTn5+frVva/XvZD4bdFcYFEIAABCAAAQhAwAsEVJyj8Uc5PCflP/Zv2bLF3AtpBUA2btxI7dq1o1KlStH58+dd1nPueIfgYMKkSZPM236lbEz27NlpxYoV1LZtW4vtdCQAcvDgQbHKJmlCAET/YaTyocL6txYlQgACniig+goGd9aPA9fRF/6msOhLFHE6jhIS/7MdJyfePqt5xQDqGlycQgLzmD9Kdmf9PHF8oc7GEZD9DoEAiIaxxCsp6tSpQ48ePaJs2bKJL8v46yY+VJEDCYsXLxallC9fnn755ReRx5HEAZY1a9aIS7l8Xo5fqFAhsW/xF198QbGxseJ3fL8+ffqkusVrr71Gu3fvpty5c1P79u2pUaNGVKJECbG/8bFjx8QSf14hwqlevXpilQi/GFpKS5YsId5KgBO/GH7yySdUuXJlunbtGs2ePZv27t0rfsd1XrVqlSPNTfMa2Q+G7g1CgRCAAAQgAAEIQMAAAirO0YoXL05cr++//57atGljVk4rAMJz9tq1a4uD0OPj413SM+54h5gyZYp4N+FUsGBBGj58uHhv4cRBimnTpolV3Lxyfc+ePebfJW0wrxjhVedpJf49v1vwh1FlypShc+fOpcqeNADC25HVrFnTapH58+cn/j+9k4rj09k2Rp2/Rf3CjtKjZ9rPu8yS0ZcWdqtO9cvkc/b2uB4CEHBSQOtKACdvI+1y1Vcw6LlCJb1POjpm5QwQDlgPDY+hc3EPbPZF2YBsNDM0iCoVzkHuqp/NSiEDBFwsIHuOhgCIhg7mYARP6DmQEBkZmeprp+nTp9OIESNESbxiYuzYsRpKTZ6FgxH8UsGJV1bwV2m8dN2Ubt++TdWrVxdbb/E2VBcuXEi1goO/3uIXHl4Jwi85KRMHcHj1x/79+8WveLVIt27dUuW7e/culSxZkvifvFz+6NGjlDdvXnM+PmyevyAzfWHHdW/QoIHdbU7rAtkPhq6NQWEQgAAEIAABCEDAIAIqztEyZ85Mz549o99++01s1WpKaQVA+OMgnltnzJiReBW2K5Kr3yE4cMEfKj19+lR8NMVBHf5n0sR5eBtc/oiJbdjI2gdQaRnMnz9fbPnLiVebfPrpp6myJw2A8MdSpncbV9haK1PF8alH++35w1q5AH+aEVpV/GENCQIQkCPgyEoAOTV1/q6esILB1WeUOBuodnX9nO9llAAB5wVkz9EQALHRh/wiwS8NnPr160cLFixIdQV/CVWpUiU6c+aMCE7ExcVRhgyp9/ZL61a8ZJ+30OKgx8WLF6lIkSKpsvNqk06YwNczAAAgAElEQVSdOomff/nll/TRRx/ZPQJPnjwpVnJw4j2P//3vf6cqI2lAZ+3atRbP+uCBy6tLOBjy5ptvJttuwO5KWbhA9oOhRxtQBgQgAAEIQAACEDCagIpzNF79zNvU8kc+SbdlSisAwnNg/qCHz8m7fv267t3kjneIGTNm0LBhw0Tdra0Q598lXdnNW+3ye4e9iV0PHToktuzgw+N51U3KhACIvar25ec/qB668A+FHbpIu04l31qFv0puXrGA2FolODC35vMe7asBckMAAloE7AlYJl0JoKVsFfN4wgqGg7G3qfPiw07zre0bTCGl8iQrR4+tCu8/ee6y+jndaBQAAZ0EZL9DIABioyNHjx4ttp/ixJN+XipvKSVdfh4REUHNmjXTPEQePHggVljw11stWrSgHTt2WLyWv2zLly8f3b9/X6z0OHDAsYOcuAxeUVKxYkXigEjKVLduXbFknvcLvnXrlvgyzlLiuu7atUusNuHyHN36y1LZsh8MzZ2HjBCAAAQgAAEIQMCLBFSco/FKjpiYGPr666/NqxS4S9IKgPBWr0uXLhXbzvIWsnond7xD8Nkn69evF1XnfilcuLDFZiTtM14xzgeY25P4jJSyZcuKS3hVh2kr3JRlIABij6pzefkPjnH3n9CDpwmULZMvBWS3fLiuc3fB1RCAgL0Czq4EsPd+quRXfQUDB5Cbz4rUtD2VNVNeXbdzSP1kAWa9yt0xuB61mB2le/1UGR+oBwRMc9WiRYsKjCtXrlj88N+VUgiA2NDlrZ2ioqLE/sC8JRRvg2UpRUdHm/fU5S2weCssrYn3423atKnIPnnyZBo5cqTVS3kLKw6wcD14Syt7V5pwwTly5BBBFF4J8vvvvye7FwdZuK0vXrwQ22Xt3LnTal24rnw2CCduA79A6pVUfLnWq20oBwIQgAAEIAABCHiqgIpzND4DY+rUqVSlSpVkWzxZC4Dw9q78wc/z58+JP2LiczP0Tu54h3j99dfpxx9/FFXntlh7T+HfmT5o4m1ueStde9KYMWPos88+E5fw2R49e/a0eDkCIPaoIi8EIGA0AT1WAnjq1nWuXGGh1zhxRf/o2W5/v/QUujDarvOeTDZ87lN4vxBsfajXYEE5LhGQ/Q6BAIiNbjWtluA9c/nLMmuJDwbk5fecOnToQOHh4ZoHzNy5c2nQoEEiP5/9kfTwxpSF8MHoc+bMET8+deoUVahQQfN9OCPvd1ytWjWr9eQyeTsvTnyvWbNmWS2f6/rOO++I33MbTPsC21UhK5llPxh6tAFlQAACEIAABCAAAaMJqDhH43MueIUCn+XBKxx4y1r+SMhSAIQPSu/fvz/9/fff4qMg3nqW/6l3csc7BG/htWnTJlF1Xo2dJ0/ybTlMbeLfcX048RZWvPo8S5YsmprMX7cGBgYKJ76GD1T39/e3eG3SAAhvmcVnF968eVN8XMVb5/LqkX/961/m1SSaKmBnJhXHp51NQHYIQMADBfRaCZByhYGnUOjV/u/6B1Pc/af08FkCZc3oSwVy6Lu6Te8VOnqvfNG7fp4yflBP7xCQPUdDACSNccYvUXyoIifeK5f3zE0r8RZQDx8+pODgYOIVIVoTr/jgr9Y48X7BNWrUsHopn/1h+kqNV2fwKg17EgdnNmzYIC757rvvqH379sku5zLfeOMN8TM+C8S0r7Cle/z6669Us2ZN8StuA68I0Zp44KeVeC9m09krMpZGaW0H8kEAAhCAAAQgAAFvEpD98mLNmrez4m2t+A/8fBB469atRSCE/3vIkCFi5fRPP/0kVj/wH2r453y+Hs+N9U7ueofgldim+TcHdkwfJqVszw8//EDt2rUz//js2bOagxD79u0zH2bepUsXWrVqlVWupAEQa5k4KMUrSsaNG+fQORV4h9B7tKI8CEBADwE9VwKkPGNCj/q5owxnVlhkSu9D1YvnosN//UMJiS/N1fUV5xsFiPONQgLzOPT/N1K23Z4zWnjbqxmhVS2urNDz7BNuZ8zYZuTvl4H0qp87+hz3gIA9ArLfIRAASaO3+PyL/PnzixzvvvuueElKK/EhivyVE6+gOHHihOZxMHDgQJo3b57Izweply9f3uq18+fPN6+04EBG0pcZWzfkFyNTwIP3SuZgC7/8JU0cFAkNDRU/4nvxF3LWEtfVtAKFV7DwvstaU8r7pnUdAiBaVZEPAhCAAAQgAAEIuFZA9stLWq3j7Zk++OADEeywNNfkwAcnPr+OgyM9evRwCZa73iEOHz4sPrzixKvV+bxCPz+/ZG3iYAznOX78uPnn/BETvwtoSb179xbbXnGydc4hB0A6d+4sAjH16tUTK0d4Wy5eCbJlyxYKCwsTW3Vx4m3LTOcsaqmHKQ/eIezRQl4IQMBdAnqvBHBXvfmP+DfuPdFtxYUjKxj4T1L//X/PaTZbzwPjeT5w6MI/FHboIu06FZc86JKOqOkrAdSzbkkKDsxtNehyPi6emn0VqVtX/TS0AZXO/58VlmnVL70IChUQQaG06qdbxVAQBHQSkP0OgQBIGh3Jf3gvVqyYyNGtWzdauXJlmt3OefmaUqVK0Z9//ql5iCR9sYiNjRUvC9YSv4Bwfk78EtG1a1dN9/njjz/Eior4+HixqoVffCxtn8Vldu/eXZTJX9L16tXLavn8BR23lRPXacmSJZrqwpnw8qKZChkhAAEIQAACEICAMgKyX15sQXD9eAvXzZs3p5qP8yHhb731llhNzVsyuSq56x2C6//222+LtnLiuT4HFXj7KU68Ip1XiRw5ckScAcJn/XHi8w05QGErcfCEP/DiswPZjgMZvILDWuKV8Hwfa2cUcj343JJ79+6Jd4HffvuNgoKCbFUj2e/xDmEXFzJDAAJuEHDVSgBXVZ3/uB594W8Ki75EEadT/PFfhxUX9qxg0Br8MFnwWRcLu1Wn+mX+s62jM8nksHz/X7T7j5uUZOEJaVl5EnPlLrWZe8CZKiS7dtPAuhRUNGeq8nh8xd1/Qg+eJlC2TL4UkF3fbcF0awAKgoANAdnvEAiApNFB7vp6y9UrQK5duyYOeuS9e/mlYfXq1dSpUyeLLXfXChAsX8f/NkIAAhCAAAQgAAHPE5D98mKPGP/hnldnJyQkiPMx8ubNa8/lDud11zsEV/Du3bti+1pe/WEt8Za1vEJ9+fLlIgufa8grRmwlXv1uemf4+OOPxYHxziZ+DzF9wNWnTx9avHixXUXiHcIuLmSGAATcIODKlQB6V9+e4IQzKy5srWAIDsxDv1z8h56+SLS7iXoc+K2Hgyf1u93IuAACLhCQ/Q6hdACEl0jzl0EnT56kf/75R/DzQeM8geeDvK19XaRXP7lr/15XngHCbg0aNBAHpnPiA9Tff/99q0TuOgPEVh/JfjBs1Q+/hwAEIAABCEAAAt4ooOIcrUmTJqIreMV2z549pXeLu94hTA3llR28nS4HE06fPm1uf4ECBcS5KKNHjyY+v4O3w+V06dIl8yr3tLBatmxJO3bsEFn4XcLS6nF7sV+8eCECUbwKpEyZMnTu3Dl7i0gzv4rjU9cGojAIQEA5AXetBHC24Y5sT6XHiouUKxjy+2ei9gui6VzcA4ebxGdzOHpgvF4Oeq784W2tjv33DBCHUXAhBBQXkD1HUzIA8uDBA5o0aZLYgunOnTsWuzBXrlxi26VPP/2U/P3/s0+eK1K+fPno9u3b4isp/lrKWuJ6cnCGEx+mGB4errk633zzjTkosXHjRmrTpo3VawcPHiyCGFpeRHi7q6ZNm4qzPjixKXullTjYVLlyZZGF78VbCFhLXFfTYYtz5841n02iueFpZJT9YOjRBpQBAQhAAAIQgAAEjCag4hyNP4pKTEwUh5w3btxYCXJ3vENYaigHFnjVS7Zs2YgDIKYto8qWLUvnz58X7028aiStray43Li4OLHtFa+e4fNCePtcvRJv1cXvJ1myZCHeNkvPpOL41LN9KAsCEFBPwBNWAjhzQLkeKy6S9prMA+P1dvDUs1/Ue4pQI28QkD1HUy4Awgdrt2jRghjGdFChtYHAE/qiRYvSrl27qFy5ci4ZL7x6gvfJzZo1q3hZ4IP8LCXeY7dOnTriV2PHjqUJEyZors+ePXtEoILT5MmTiVeEWEvNmzcXBxByPUz77FrK+/jxY7Ecft++feLXvNfxtGnTbNaJvyDjlxF+2eF78YoQa4nryvsKc+I26PnCKfvBsAmFDBCAAAQgAAEIQMALBVSco/Ef6m/cuCH+SP/qq68q0SvueIfQ2lAOZhQsWFC8W/Fqmd27d9u8dObMmfTRRx+JfLZWkNssLEUG3pKL+woBEHvlkB8CEFBRQPWVAPy//c1nRUpbcZGyz2QFDVzhIDOYo+KzoGqd+Bm9ce8JPXyWQFkz+lKBHDhHRUZfyX6HUCoAwgGGihUr0vXr10Vf8FZXPXr0EAf68QF8/D9Y/EUTfzH07bff0okTJ0Q+funhlQs5cuTQvQ/5D/z8h35OvLdu7dq1Ld6D98QdNWqU+B0HZPiAP62JV2rwUnAOPnDwx7TUPOX1/Hv+moz3M+bDDQ8ePGjxFrx1GB+IaCqnf//+NH/+fK3VEYEcDuhkz56deA9jPszQUuK6clszZcok8um5Ekf2g6EZCxkhAAEIQAACEICAFwmoOEfjrZp4TrpmzRp69913legNd7xDaG0or+j+8MMPRfYFCxZQv379bF7Kh5MfP35cbDnM5wnqdX4Kb4HF57Hw+0zp0qXFqhQ9k4rjU8/2oSwIQEBNAVl/1NeiodIf6fUMFvFB5TF2bBvlCgdXBFW09Cny2BYwHXIfFn2JIk7HUUKSU+61HHJv+w7IYa+A7DmaUgEQDiBMnTpVLNWeOHGiWF1gWradEpYHMwcmeEsnzsMH833xxRf2+tvMf+TIEXPQg18W+KUhZeIl9xys4dUrOXPmFEEae88nMe2xyys7/vrrLypSpEiq+yQ9iJBXc/CqjpSJV2507NiRNmzYIH7FeyFzsMiaoyUALps9Oa1du1aUlzLxwC1RooRYKcJ137Ztm01LezLIfjDsqSvyQgACEIAABCAAAW8RUHGO9sMPP1D79u2pYcOGtHfvXiW6wl3vELYay4EGXinPK2T4PeXy5cs2P1rij8yqVKkiiuaPqjZt2mTrNpp/v2rVKvF+wom3M16yZInma7VkVHF8aqk38kAAAp4t4Io/ruslolJwRuZ2Ya5y0HtbLb363ZvL0eOQe2/2c1XbZc/RlAqAvPLKK+IgPP5yi7/g0pI6depE69evFxN7DkC4IpmWsHNwIjIyUqy+SJqmT59OI0aMED8aN24cjR8/PtnvV6xYYT6Q0dLvOXPSbbDeeust4hc5X19fczl8Dgnvv8svLfzycuHCBeJzUJImDgrxi8Ty5cvFj9u1aydskpajxYcPTg8MDBSHExYvXpyOHj0qvtQyJQ56tG3blrZs2SJ+pPf2V1ym7AdDixPyQAACEIAABCAAAW8TUHWO1r17d+I/rr/33nv09ddfi+1rZSd3vEPwynlenWHp4yteZc7n9fHZKJw42MDvCrbSsGHDaMaMGSIbH5xuOvMvrev4PEReMdKoUSOr2TgoxFvs8qp//jiL/7tGjRq2qmPX71Udn3Y1ApkhAAGPE1B1JYDMFReWOlHWgfGudtDrYHWPG/gKVhh9oWCn/LdKsudoSgVAeB/Yp0+f0vbt28XkWEvi5e581oWfnx89evRIyyV25zl27BjVrVuX+FwNPlCQV6bweRf837wqY9GiRaJMPlyQ97NNuRWUlgAIX8/BHC6PE5c/ZMgQKlSokNjq6/PPP6fY2FjxO2tL13mfXt6vlxOvSOGVH9a2rzIhcD5LaeHChcRbZ3EqVaoUjR49WhyOzkvgeRm96es6rrPWYJU98LIfDHvqirwQgAAEIAABCEDAWwRUnKOtXLlSbJX71VdfiXkzfyzUunVrsYqBPxiy9TEQB09ckdzxDvHll18S/x9vG8wrYPisD171wVv3zps3T3w8xalnz560bNkym83kD534jEUOrOTOnVv809b7BBd68eJFKlmypDBv06aN+HCL68L2XAf+cCosLIx4q15OWs8ntFnhFBlUHJ/2tgH5IQABzxRQcSWAzBUXlnpRVn3ccV97Vh2UC/CnGaFVqVJh/bfx98ynR59aq/gM6tMyY5Qie46mVACEz/nglQ72HGDILxY8weYvn3jrKVclnrR37dpVvFBYShz84G2geC/blElrAIQDKrx8nwNAlpKPjw+NGTMm1QoTU17ekurSpUt2EaR10DyvVpk0aZLVw+h56yv+KoyDT3on2Q+G3u1BeRCAAAQgAAEIQMAIAirO0XiOnHS7V57fat3+lfPxuRSuSq5+h+Dgh6VtcU3t4RXs/JEUbxXMTrbSzp07xcdlnAYMGEBz5861dYn4vSkAYiszB0T4fWbs2LGa+8hWmUl/r+L4tKf+yAsBCHi2gGpfn8tacWGtF/VciZHeJx0d03gGiLsceP5x6MI/FHboIu06lfzcCa5v84oFqGtwcQoOzO2S/x/o2U+Pc7VXdRWWc60y1tWy52hKBUBee+01sbKAz50IDQ3V1NPh4eHijApeMbF7925N1ziaiYMLs2fPFoEO7jj+GooDHh06dKBBgwYRr2CxlLQGQEzX8ooKvoaXkfMScQ4M1a9fX9wj5fZbSe+ndwCEy+aD1vnFJyoqiuLi4sQXdVWrVhVfkfHqD1cl2Q+Gq9qFciEAAQhAAAIQgIAnC6g4R9Pyh31r5hwA4VUPrkyufIfgbXH53YG3pOXV4vxBWKZMmcR5gq+//rrY8qpixYqam9elSxfz6m5eRVK7dm1N1z579ow2b95M0dHRYmurq1evig/bnjx5Qjly5BDbFfP2WH369BHnCLoqqTg+XdVWlAsBCKgpoNJKAHesfLC3F1x1Fkda9ZDhwMGeuPtP6MHTBMqWyZcCsvuRv18Ge7mQX6OAyufwaGyC4bPJnqMpFQD57rvvxPkfwcHBtH//fptfKfHh47w1FU+yeeLP1yIZQ0D2g2EMRbQCAhCAAAQgAAEI6Cug4hzN3hXQKUX4zDskYwioOD6NIYtWQAAC9gioshJA1oqLtKxk/KFaRQd7xhPy2haQEVizXSvkSCoge46mVACEYUyHeL/55pvibI0CBQpYHDG8GqFfv37iSyNejbB06VKMLAMJyH4wDESJpkAAAhCAAAQgAAHdBDBH040SBblAAOPTBagoEgIQcEpA9koA1f4wLGurItUcnBpUuDiZgJ4BLl+fdBSjcWs1dIN9ArLnaEoFQPgAQ0685dIvv/wizpbgpds1a9ak/Pnziz3yOPDBv4uIiBAHpteoUYMGDhyYprqrDja0r6uR2x4B2Q+GPXVFXghAAAIQgAAEIOAtApijeUtPe2Y7MT49s99QawhAwHUCMlZc2GqNjMOqVXSw5YTfaxOQscWZtpohV1IB2XM0pQIg9hxgqPVwQ1cfbIjh7BoB2Q+Ga1qFUiEAAQhAAAIQgIBnC2CO5tn9Z/TaY3wavYfRPghAwF4BWSsubNXT3QfGq+pgywm/ty3grkPubdcEOdISkD1HUy4AovdwccfBhnrXGeWROGS+aNGiguLKlSviIEckCEAAAhCAAAQgAAG5AqrP0V68eEH//ve/6aeffqKTJ0/SP//8I8By585NlSpVotdee43efvttSp8+vVxI3N0lAqqPT5c0GoVCAAIQsCEgY8WFlk5x94HxqjposUIe6wJYAeIZo0P2HE2pAIizBxha63IcbOgZD0PSWsp+MDxPDDWGAAQgAAEIQAACrhdQeY62adMmev/99+natWtmCP7ikxN/FGVKBQsWpG+++YbatGnjejDcwa0CKo9Pt0LgZhCAAARSCLh7xYXWDnD3gfGqOmj1Qr7UAnqeAZLeJx0dwxkgLhlmsudoSgVAXCKMQj1SQPaD4ZFoqDQEIAABCEAAAhBwsYCqc7SvvvqKhg0bJlpv2iq3RIkSFBAQIP775s2bdPHiRfHvnDggMmPGDBoyZIiLxVC8OwVUHZ/uNMC9IAABCFgTcPeKC3t7wl0HxqvuYK8b8hPhkHv1R4HsORoCIOqPEa+soewHwyvR0WgIQAACEIAABCBgQ0DFOdqhQ4eoXr16lJiYSNmzZ6fRo0dTz549KW/evMlac/v2bVq+fDl98cUXdO/ePfL19aX9+/dT7dq10e8GEVBxfBqEFs2AAAQMIuDuFReqssFB1Z5xrF445N4xN3deJXuOhgCIO3sb99IsIPvB0FxRZIQABCAAAQhAAAJeJKDiHC00NJQ2bNhAOXLkoAMHDlCFChXS7JEzZ85QnTp16P79+9S+fXtav369F/WgsZuq4vg0tjhaBwEIeLKAu1ZcqG4EB9V7yHb9cMi9bSPZOWTP0RAAkT0CcH+LArIfDHQLBCAAAQhAAAIQgEBqARXnaIUKFaK4uDj6/PPPaeTIkZq6bcqUKfTJJ5+ILbKuX7+u6RpkUl9AxfGpvhpqCAEIQAACEPB8ARxyr3Yfyp6jKRkA4a+yFi1aRFFRUXThwgWKj48XS9rTSryP74sXL9TubdROs4DsB0NzRZERAhCAAAQgAAEIeJGAinO0zJkz07Nnz+jgwYOat7M6fPgwhYSEUKZMmejx48de1IPGbqqK49PY4mgdBCAAAQhAQB0BHHKvTl+krInsOZpyARD+Gmvs2LGUkJBgPqRQS/dxAISvQTKGgOwHwxiKaAUEIAABCEAAAhDQV0DFOVpgYCBdunTJoQAIH5TOH1whGUNAxfFpDFm0AgIQgAAEIOAZAjjkXs1+kj1HUyoA8t1339G7774resrHx0ccZli1alXKmTOn+G9bady4cbay4PceIiD7wfAQJlQTAhCAAAQgAAEIuFVAxTna//3f/9HSpUtp8uTJNGLECE0eU6dOpVGjRlGvXr1oyZIlmq5BJvUFVByf6quhhhCAAAQgAAFjCeCQe/X6U/YcTakACAc8eOl64cKFafv27VS5cmX1egw1couA7AfDLY3ETSAAAQhAAAIQgICHCag4Rzt79ixVr16dMmbMSIcOHaKyZcumqXru3DkKDg6m58+f06+//krlypXzsF5Ada0JqDg+0VsQgAAEIAABCMgTwCH38uyT3ln2HE2pAEj27Nnp4cOH4guu9957T40eQi2kCMh+MKQ0GjeFAAQgAAEIQAACiguoOkfbuXMnde7cWejxdrrdu3en3LlzJ9O8c+cOrVy5kiZNmiTOF1y9ejW98cYbioujevYIqDo+7WkD8kIAAhCAAAQgAAGjCcieoykVAMmTJw/dvXuXjh49SkFBQUbra7THDgHZD4YdVUVWCEAAAhCAAAQg4DUCKs7RmjRpIvyvXr1K58+fJz4bkP+vZMmSlD9/fvHvcXFx9Ndff5nPGCxTpgwVKlTIar/xNbt37/aafjVKQ1Ucn0axRTsgAAEIQAACEICAowKy52hKBUBCQkLoyJEjFBERQU2bNnXUFNcZQED2g2EAQjQBAhCAAAQgAAEI6C6g4hyNzwrkgAUn3vNZS7KWn3/OZfA/ExIStBSFPAoJqDg+FeJBVSAAAQhAAAIQgIAUAdlzNKUCIAsWLKABAwbQwIED6euvv5bSIbipGgKyHww1FFALCEAAAhCAAAQgoJaAinO0Ro0amQMgemrt3btXz+JQlhsEVByfbmg2bgEBCEAAAhCAAASUFpA9R1MqAMIHEb722mvi8MINGzZQ69atle48VM51ArIfDNe1DCVDAAIQgAAEIAABzxXAHM1z+84bao7x6Q29jDZCAAIQgAAEIOBpArLnaEoFQLjz+AyQHj160LZt26hjx44UGhpKZcuWpSxZstjs22LFitnMgwyeISD7wfAMJdQSAhCAAAQgAAEIuFcAczT3euNu9glgfNrnhdwQgAAEIAABCEDAHQKy52jKBUAYnQ8c7Ny5M92+fVtzH/A+vS9evNCcHxnVFpD9YKitg9pBAAIQgAAEIAABOQKYo8lxx121CWB8anNCLghAAAIQgAAEIOBOAdlzNOUCIEOGDDGf/6H1EEPuMBxU6M5h6/p7yX4wXN9C3AECEIAABCAAAQh4ngDmaJ7XZ95UY4xPb+pttBUCEIAABCAAAU8RkD1HUyoAsmrVKurevbvou+zZs1Pbtm2pSpUqlDNnTvLx8bHZp7x1FpIxBGQ/GMZQRCsgAAEIQAACEICAvgKYo+nridL0FcD41NcTpUEAAhCAAAQgAAE9BGTP0ZQKgNSuXZt++eUXKl++PO3du5cCAgL0MEYZHigg+8HwQDJUGQIQgAAEIAABCLhcAHM0lxPjBk4IYHw6gYdLIQABCEAAAhCAgIsEZM/RlAqA5MiRgx48eEBr164Vh58jea+A7AfDe+XRcghAAAIQgAAEIGBdAHM0jA6VBTA+Ve4d1A0CEIAABCAAAW8VkD1HUyoAkjdvXrpz5w4dPXqUgoKCvHVMoN1EJPvBQCdAAAIQgAAEIAABCKQWwBwNo0JlAYxPlXsHdYMABCAAAQhAwFsFZM/RlAqA1KtXj6Kjo2nbtm3UokULbx0TaDcCIBgDEIAABCAAAQhAQEkB2S8vSqKgUsoIYHwq0xWoCAQgAAEIQAACEDALyJ6jKRUAWbp0KfXt25e6detG3377LYaJFwvIfjC8mB5NhwAEIAABCEAAAlYFMEfD4FBZAONT5d5B3SAAAQhAAAIQUEUg/slzunHvCT18lkBZM/pSgRx+5O+XwWXVkz1HUyoAwspvvfWWWAEye/ZsGjRokMvgUbDaArIfDLV1UDsIQAACEIAABCAgRwBzNDnuuKs2AYxPbU7IBQEIQAACEICA9wm8fPmSoi/8TWHRlyjidBwlJL40I/j6pKPmFQOoa3BxCgnMQ+nSpdMVSPYcTakASGRkJD179ozGjBlDR44codq1a1PHjh2pbNmylCVLFpvwDRo0sCG277wAACAASURBVJkHGTxDQPaD4RlKqCUEIAABCEAAAhBwr4CKc7QrV65Q0aJFHYJYs2YNde7c2aFrcZF6AiqOT/WUUCMIQAACEIAABLxN4OTVezQ0PIbOxT2w2fSyAdloZmgQVSqcw2ZerRlkz9GUCoD4+Pg4HGHiyNSLFy+0uiOf4gKyHwzFeVA9CEAAAhCAAAQgIEVAxTla+fLl6cCBA5QnTx67TFauXEm9e/em58+f23UdMqsroOL4VFcLNYMABCAAAQhAwBsEos7fon5hR+nRswTNzc2S0ZcWdqtO9cvk03xNWhllz9GUC4A4qsoBkIQE7R3p6H1wnXsEZD8Y7mkl7gIBCEAAAhCAAAQ8S0DFORp/RFWtWjXau3cv+fv7awJdsWIF9enTh3grALxDaCLziEwqjk+PgEMlIQABCEAAAhAwpACv/AhdGG1X8MMEwUGQ8H4huqwEkT1HUyoAsm/fPqcGW8OGDZ26HherIyD7wVBHAjWBAAQgAAEIQAAC6gioOEfjoMejR4+It8PduXMnZcqUKU2wJUuWUP/+/SkxMZGqVKlCMTEx6gCjJk4JqDg+nWoQLoYABCAAAQhAAAIOCvCHPs1nRWra9sraLcoF+NPOIfUd3rHJVK7sOZpSARAH+xOXGVBA9oNhQFI0CQIQgAAEIAABCDgtoOIcbffu3fTmm2+KswRbtWpFGzduJF9fX4ttXbhwIQ0cOFAEP4KCgujHH3+0e+sspxFRgMsEVByfLmssCoYABCAAAQhAAAJpCByMvU2dFx922mht32AKKWXfVrMpbyp7joYAiNPDAAW4QkD2g+GKNqFMCEAAAhCAAAQg4OkCqs7ROOgRGhoqAht8qHlYWFgq6nnz5tH7778vtr3iLbMiIiIod+7cnt4lqH8SAVXHJzoJAhCAAAQgAAEIuFtgwOqjtP3EDadv26pyQZrbpZpT5cieoyEA4lT34WJXCch+MFzVLpQLAQhAAAIQgAAEPFlA5Tna8uXLxaHmfDYgr/KYM2eOmZr//cMPPxTBjxo1aojgR86cOT25K1B3CwIqj090GAQgAAEIQAACEHCXQPyT5xQ08UdKSHzp9C19fdJRzNhm5O+XweGyZM/RlA2A3L9/nzZs2EDR0dF048YNsa/vsmXLqHjx4mbsa9eu0d27d8nPz48CAwMd7gRcqJ6A7AdDPRHUCAIQgAAEIAABCMgXUH2O9uWXX9KIESNEEOTTTz+lCRMm0MyZM2n48OEi+FGrVi3atWsX5ciRQz4maqC7gOrjU/cGo0AIQAACEIAABCBgQeB8XDw1+ypSN5ufhjag0vn9HS5P9hxNyQDI3LlzafTo0RQfHy9g+WWFX2JOnDhBFSpUMGOvXbuWunTpIgIgDIkl7A6PQ+UulP1gKAeCCkEAAhCAAAQgAAEFBDxhjvbJJ5/QlClTxPtDy5Ytafv27eJ9Ijg4WBySnj17dgUkUQVXCHjC+HRFu1EmBCAAAQhAAAIQSCoQc+UutZl7QDeUTQPrUlBRx1dPy56jKRcAGT9+PE2aNEm8pGTKlIkqV65Mv/76q8UACO/xW7RoUbFCZMGCBdS3b1/dOhYFyRWQ/WDIbT3uDgEIQAACEIAABNQU8JQ5Wv/+/WnRokXiHYLfK0JCQkTww9/f8S/X1OwR1CqpgKeMT/QaBCAAAQhAAAIQcKUAVoAk11UqAHLs2DGxJy8nXtnx9ddfi+XpPj4+FgMgnG/IkCFif9/27dtTeHi4K8cOynajAF5e3IiNW0EAAhCAAAQgAAGNAp4yR+OgR6dOncT7Qb169WjHjh2UNWtWja1ENk8V8JTx6am+qDcEIAABCEAAAp4hoOcZIOl90tExnAGiX8f36tWLVqxYQXXq1KH9+/ebC04rALJ+/XrxclOuXDk6c+aMfpVBSVIF8PIilR83hwAEIAABCEAAAhYFZM7R7D3z78WLF3T16lUKCAgQW+ZaSrxCJDY2Fr1tEAGZ49MghGgGBCAAAQhAAAIGERiw+ihtP3HD6da0qlyQ5nap5lQ5sudoSq0AKVWqFF28eJFWr15NHTt21BQAOXz4sFjSni1bNuKD05GMISD7wTCGIloBAQhAAAIQgAAE9BWQOUfjj6L0ThwASUhI0LtYlCdJQOb4lNRk3BYCEIAABCAAAQhYFDgYe5s6Lz7stM7avsEUUiqPU+XInqMpFQDJkiULPX36VJz58eqrr2oKgMTExFC1atUoQ4YM4lokYwjIfjCMoYhWQAACEIAABCAAAX0FZM7RevbsqW9j/lva8uXLXVIuCnW/gMzx6f7W4o4QgAAEIAABCEDAugBvCdt8ViSdi3vgMFO5AH/aOaS+OJrCmSR7jqZUACRnzpwUHx9P0dHRVKtWLU0BEN7Pt1WrVpQvXz6Ki4tzpi9wrUICsh8MhShQFQhAAAIQgAAEIKCMAOZoynQFKmJBAOMTwwICEIAABCAAAQj8T+Dk1XsUujCaHj2zf8Vzloy+FN4vhCoVzuE0qew5mlIBkEqVKolzPJYsWUJJv/BK6wyQDz/8kGbPni22wTpw4IDTHYIC1BCQ/WCooYBaQAACEIAABCAAAbUEMEdTqz9Qm+QCGJ8YERCAAAQgAAEIQCC5QNT5W9Qv7KhdQRAOfizsVp3ql8mnC6fsOZpSAZAPPviAvvnmG6pXrx5FRkaaga0FQC5cuEBBQUH08OFDGjNmDI0fP16XTkEh8gVkPxjyBVADCEAAAhCAAAQgoJ4A5mjq9Qlq9D8BjE+MBghAAAIQgAAEIJBagFeCDA2P0bQdFm97NSO0qi4rP0w1kT1HUyoAcu7cOeJVIHwQYdKAhqUACJ8TwgelcxDEz8+PYmNjqWDBghjjBhGQ/WAYhBHNgAAEIAABCEAAAroKYI6mKycK01kA41NnUBQHAQhAAAIQgIBhBPhMkEMX/qGwQxdp16k4Skh8aW5bep901LxiAeoaXJyCA3M7feZHSjTZczSlAiCMM2nSJBo3bpyArlGjBrVr145Gjhwp/nv69On0/PlzioiIoJ9//tls+dVXXxGvHkEyjoDsB8M4kmgJBCAAAQhAAAIQ0E9A9Tna33//Lc4T5I+k+GxB/rDKVho7dqytLE79/vLlyzRnzhzatm0b8b9nypSJSpcuTaGhoTRgwADKkiWLU+Xzxb///rtYSc/vSFevXiVfX18qWrSoOCtx0KBBVKxYsTTvUaJECbp06ZLNehQvXpwuXrxoMx/3wbx58ygqKopu3LhBuXLloqpVq9J7770nPmJzVVJ9fLqq3SgXAhCAAAQgAAEI2CMQ/+Q5xd1/Qg+eJlC2TL4UkN2P/P0y2FOEXXllz9GUC4CwHr+EfPHFF5SYmGg14sRRKw6KcF4OmCAZS0D2g2EsTbQGAhCAAAQgAAEI6COg6hzt5s2bxGcDbtiwgV68eGFXY7UESewqMElmDnp06dKF7t27Z7GIcuXK0fbt2ykwMNDRW4h3If6IjN+PLKXs2bPTihUrqG3btlbvoWcAZOLEiTRhwgTxLmcptW7dmsLDw8Uqfr2TquNT73aiPAhAAAIQgAAEIOBJArLnaEoGQLgDeYurKVOm0M6dO+nRo0fJ+jRjxozUtGlTGj16NNWpU8eT+ht11Sgg+8HQWE1kgwAEIAABCEAAAl4loOIc7c6dO1S7dm2xJa61IEBanWTtD/XOduzx48fFuwq/y2TLlo1GjRpFjRs3psePH9O6deto8eLF4hbly5enX375ReSxN/H7EpfLibcDHj58uPn96ODBgzRt2jSxAoNXnezZs8fqu5MpAPL222/TZ599ZrUa/B5WtmxZq79fsmQJ9e3bV/y+VKlS9Mknn1DlypXp2rVrNHv2bNq7d6/4HQeFVq1aZW9zbeZXcXzarDQyQAACEIAABCAAAYMLyJ6jKRsAMfU7f8F1+vRp4q+6+OusPHnyUMWKFSlz5swGHxre3TzZD4Z366P1EIAABCAAAQhAwLKAinO0jz/+WGyVy+n111+noUOHUvXq1Sl3bv33L7ZnXHCwg7ekSp8+PUVGRlJISEiyy7nOI0aMED/jFRP2bsXFW11xkOHp06dUqFAhEUThfyZNnKdWrVoiAMFbUP3222/E5yumTKYASI8ePcRqEUfS3bt3qWTJksT/5C23jh49Snnz5jUXxe9yvAply5Yt4mf79u2jBg0aOHIrq9eoOD51bSAKgwAEIAABCEAAAh4oIHuOpnwAxAP7FFXWQUD2g6FDE1AEBCAAAQhAAAIQMJyAinM0XkFx/vx5cd7F5s2blTDnYAQHHjj169ePFixYkKpevPKkUqVKdObMGXFGRlxcHGXIoH3v5RkzZtCwYcNEubyapE+fPhbbnnRVxtatW4VTyqRHACRpQGft2rUWz/rg8cP34mDIm2++aQ6G6NVpKo5PvdqGciAAAQhAAAIQgICnCsieoykVAOH9YjnxYYBJvxZKq3N5yfvXX38tstj71ZSnDhpvqLfsB8MbjNFGCEAAAhCAAAQgYK+AinM0PkScV0HwWRrNmze3t0kuyc9b9fKZhpwOHToktuiylJJuYRUREUHNmjXTXB8+THz9+vUiP/dL4cKFLV6btM/4EPLly5enyqdHAKRu3brE227xmSO3bt0i3i7LUmrRogXt2rVLbMt1+/Zth7b+soak4vjU3KHICAEIQAACEIAABAwqIHuOplQAhJdj88HmJ06coAoVKmjqct7rt0yZMuI6Vx5gqKkyyKSbgOwHQ7eGoCAIQAACEIAABCBgIAEV52j58+env//+W2y5FBQUpIQ2b+0UFRVFWbNmFVtC8TZYllJ0dLT5XA7+mIu3wtKaeLuvH3/8UWR//vy51Xvw70zBCN6i6sKFC6lu4WwA5NmzZ6KtvH0xB6H4HEdrafLkyeJsEE58LglvFaZXUnF86tU2lAMBCEAAAhCAAAQ8VUD2HA0BEE8dOQavt+wHw+C8aB4EIAABCEAAAhBwSEDFOVrTpk3FWRs//PAD8SHeKqR8+fKJ1Q187kZMTIzVKvFqdj6rhFOHDh0oPDxcc/X5PI1NmzaJ/HwvPivRUuLfcX048UdjDx48IF41kzSZAiAcIOHD2E0HygcEBIitvDp16iRs+XpL6dSpU2I7L06DBw+mWbNmWW3Hxo0b6Z133hG/nzt3rlj9r1dScXzq1TaUAwEIQAACEIAABDxVQPYczeMDIH/88YdYLcJfNT158sRTxwHqnUJA9oOBDoEABCAAAQhAAAIQSC2g4hyNgwa8HRT/UX3Dhg3Su43fSTJnzizqwedt8LkbaSUOODx8+JCCg4OJV4RoTbyKgldTcPr+++/NQYWU13NgqF27duYfnz17lsqWLZssmykAkta9eYsr3nLL0lZbvOLjjTfeEJfzWSCms0kslffrr79SzZo1xa9GjhxpboOWdvP4Sytdv37dfPbKlStXqEiRIlqKRR4IQAACEIAABCAAARcKyH6H8PgAyLp166hz585iIs6TXCRjCMh+MIyhiFZAAAIQgAAEIAABfQVUnaN16dKF+L3g888/F39Ul5n4/AvelovTu+++K+qVVuJVFjdv3hQrKHgrYK3p8OHDImjCiVea8Fkjfn5+yS7nYAznOX78uPnnHICoXr16snwcEHnllVeIt9XieuTIkUNs3cUBmfnz55vfszgP/4x/nzR99913FBoaKn7E+fv372+1GXzou2m740GDBpnPc9TSbmsrUCxdiwCIFlHkgQAEIAABCEAAAq4XkP0OITUAsnLlymTCfCgfT2o/++wzq4f4mS7ggw55afayZcvEnr+8JJu/bkIyhoDsB8MYimgFBCAAAQhAAAIQ0FdAxTlaZGSkOAtwzJgx4o/z/Md9/kCqfPnyqbZ6sqTB53XomfgP78WKFRNFduvWjVK+86S8F+fla0qVKkV//vmnXVXhd6DNmzeLa3irKj54PSQkRPw3W/AqkSNHjojV8nxOByc+m6RevXrJ7sPBjpw5c1q8d3x8PLVv3574kHZOH374Ic2cOTNZ3rCwMOrevbv42dKlS6lXr15W28FnkHBbOfXu3ZuWLFmiuc0IgGimQkYIQAACEIAABCCgjIDsdwipARDToeem3nj58qX4V3smtnwNl7N7925q2LChMh2LijgnIPvBcK72uBoCEIAABCAAAQgYU0DFOVrKdwp75Pm9gw/u1jO5awUI15kDF7z1FK/+sJZ4uyle1bF8+XKRhc8k4RUj9qR79+6JoAV/eMaHnf/zzz/mg9W5HHetAMEWWPb0GvJCAAIQgAAEIAABNQRkv0NID4A40w38JRNP6EeNGkUtW7Z0pihcq5iA7AdDMQ5UBwIQgAAEIAABCCghoOIcjQMgjiYOgPDqET2Tu84AMdWZV3bMmzePFi9eTKdPnzY3pUCBAtS3b18aPXo08RZhfE4Ip0uXLplXqNjTbt6uig8t53TgwAGqU6eO+XJ3nQFiq74qjk9bdcbvIQABCEAAAhCAgNEFZM/RpAZAePJtSrySIzAwUKz+2LVrF5UpU8Zq33Me3t82T5485Ovra/Qx4pXtk/1geCU6Gg0BCEAAAhCAAARsCKg4R9u3b59T/eaKVeT58uWj27dvi5UWvOLCWrpz5w7lzp1b/LpDhw7EB7o7k3ilBp8nwgercwDEtLKez/g4f/48+fv7i1UjjgSNOMgycOBAUT2uJ9fXlE6ePEmVK1cW/zl48GCaNWuW1WZs3LjRfGA7B1QGDBjgTJOTXavi+NStcSgIAhCAAAQgAAEIeKiA7Dma1ABIyj4zLV/nw/9MB+N5aL+i2k4KyH4wnKw+LocABCAAAQhAAAKGFMAcTVu38rkifNYGbxfFAYf06dNbvJDP6TCtpBg7dixNmDBB2w3syBUXF0cFCxYk/uCsSZMmYutgRxIHK3gVCKeUARBehZIlSxaxmqZ58+bEK0KspcmTJ4uzSTjt2bOHGjdu7Eh1LF6D8akbJQqCAAQgAAEIQAACugnInqMpFQDRTRUFebyA7AfD4wHRAAhAAAIQgAAEIOACAczRtKHyH/j5D/2c+HyO2rVrW7xwypQpYjtfTrwK/vXXX9d2Azty8WoMPric04IFC6hfv352XP2/rLz6g1eBcNq/fz/VrVs3WTkcyOGATvbs2YnPQeHtii2lFi1aiLZmypRJ5ONVKXoljE+9JFEOBCAAAQhAAAIQ0E9A9hwNARD9+hIl6Sgg+8HQsSkoCgIQgAAEIAABCBhGAHM0bV155MgRc9CDAw4ceEiZEhMTxeHkZ86coZw5c4qtqzJkyKDtBhpz3b9/n8qVK0c3btwQ97h8+bJDAYekh6DzSg8+BJ0DGEnTtGnT6OOPPxY/Wrt2LXXs2DFVLXn8lChRQqwU4TMct23bprEl2rJhfGpzQi4IQAACEIAABCDgTgHZczQEQNzZ27iXZgHZD4bmiiIjBCAAAQhAAAIQ8CIBzNG0d7ZpGyze/ioyMpJCQkKSXTx9+nQaMWKE+Nm4ceNo/PjxyX6/YsUK6tmzp9Xf8y+uX79OefPmtRg4iY+PF2dt/PTTT6KMJUuWUO/evVM1gLer4nNQMmfObLFxXE779u0pIiJC/P7999+nOXPmpMrLQRE+05GDJcWLF6ejR4+KMxtNiYMebdu2pS1btogf6b39FZeJ8al9fCInBCAAAQhAAAIQcJeA7DkaAiDu6mncxy4B2Q+GXZVFZghAAAIQgAAEIOAlAqrP0WJjY2nz5s10/PhxcQj548ePxdkX1hIfEu7omRi2uvzYsWNimyiuAx9Kztti8XkX/N/r1q2jRYsWiSL4gPJff/011coMLQGQL7/8kvj/evToIYIYfNYHr/rgbbd4uype8cGJAynLli2zWOVGjRoRn8HIwZJ69epRqVKlRH357BLe0mr+/Pl05coVcS2vJjl48KD54PaUBS5cuJD69+8vfszljB49WhyOfu3aNXEw+t69e8XvOnXqRGvWrLFFaPfvVR+fdjcIF0AAAhCAAAQgAAEDCMieoyEAYoBBZMQmyH4wjGiKNkEAAhCAAAQgAAFnBVSdoz169Ij4jIqwsLBUAQ8OgHCgI2kyBUX457wywVWJVzt07dpVBCUsJQ5+8DZQpUuXTvVrrQGQ4cOHW60+rz756KOP6IsvviAfHx+L+TgAsm/fPpsEvKKFgxaFCxdOMy+vZpk0aZLVwBNvffX999+Tn5+fzXvam0HV8WlvO5AfAhCAAAQgAAEIGElA9hwNARAjjSYDtUX2g2EgSjQFAhCAAAQgAAEI6Cag4hyNgxl8sDZv9cT/zltCFSlShGJiYkTgg1c13Llzh86ePUvPnz8XP+PAQ4ECBYSLaVWCbkgpCrp06RLNnj1bBDrYjw8H54BHhw4daNCgQcRnalhKWgIgFy5cEEEJ3k6KV7/wOSJ8Nge3nw9U5y2vKlasmGbTePUJr4Lh1R5sxCtnePUH16tQoULiLBNescHlpQwkWSuYV4nMnTuXoqKiKC4uTpw/UrVqVbEShctyVVJxfLqqrSgXAhCAAAQgAAEIeIqA7DkaAiCeMlK8rJ6yHwwv40ZzIQABCEAAAhCAgCYBFedo4eHh4sBt/uP82LFjacyYMXT69GmqUqWK+JlphcfDhw/FORj8ez7vglchcHAEyTgCKo5P4+iiJRCAAAQgAAEIQMAxAdlzNARAHOs3XOViAdkPhoubh+IhAAEIQAACEICARwqoOEdr06aNOPejTp06tH//fuF66tQpcfaEpS2ufvnlF3FeBp9zwatEeJUDkjEEVByfxpBFKyAAAQhAAAIQgIDjArLnaAiAON53uNKFArIfDBc2DUVDAAIQgAAEIAABjxVQcY7G2z1dv35dHPLNh4HbCoDw7/lcjK+++opGjBhBU6ZM8dj+QMWTC6g4PtFHEIAABCAAAQhAwNsFZM/READx9hGoaPtlPxiKsqBaEIAABCAAAQhAQKqAinM0Pkybz/b4+eefqX79+sLn3LlzVL58ebEC5MGDB2LLq6SJz8x47bXXqEKFCnTy5Emppri5fgIqjk/9WoeSIAABCEAAAhCAgGcKyJ6jIQDimePG8LWW/WAYHhgNhAAEIAABCEAAAg4IqDhH462sHj9+TEePHqWgoCDRKl4RUrhwYREA+fPPP6lkyZLJWst5a9asSf7+/nTv3j0HJHCJigIqjk8VnVAnCEAAAhCAAAQg4E4B2XM0BEDc2du4l2YB2Q+G5ooiIwQgAAEIQAACEPAiARXnaGXLlqXY2FjauXMnNWvWTPTGy5cvxRkfT548IT4kvV27dsl6af369dSpUyexMoQPR0cyhoCK49MYsmgFBCAAAQhAAAIQcFxA9hxNyQDImTNnaNGiRRQVFUUXLlyg+Ph4SkxMTFOZv+568eKF4z2BK5USkP1gKIWBykAAAhCAAAQgAAFFBFSco3Xo0IF++OEHmj59Og0dOtQs1aRJE9q3bx81atSIdu/ebf45vzPUq1ePjhw5QlWqVBEHoSMZQ0DF8WkMWbQCAhCAAAQgAAEIOC4ge46mXABk5syZNGrUKBHM4C+3tCYOgCQkJGjNjnyKC8h+MBTnQfUgAAEIQAACEICAFAEV52jz58+ngQMHijM9IiIizC6rVq2i7t27i22wOOARGhpKjx49onXr1tGxY8fEzydNmkSffPKJFEvcVH8BFcen/q1EiRCAAAQgAAEIQMCzBGTP0ZQKgPCy9ZYtW4oe5BeS2rVrU/Xq1Sl37tzk4+Njs2fHjRtnMw8yeIaA7AfDM5RQSwhAAAIQgAAEIOBeARXnaDdu3BDnffD7wtmzZykwMNCMwu8W/I7B7xZJE39o9eqrr9KBAweID1FHMoaAiuPTGLJoBQQgAAEIQAACEHBcQPYcTakASIsWLcRXW7ly5aLNmzdT3bp1HZfFlR4tIPvB8Gg8VB4CEIAABCAAAQi4SEDVORpvl8tBDV9f32Qtf/r0KX322We0dOlS4kAJp5w5c1KXLl3o888/p+zZs7tICsXKEFB1fMqwwD0hAAEIQAACEICAKgKy52hKBUDy5s1Ld+7cId4Ga/Dgwar0EeohQUD2gyGhybglBCAAAQhAAAIQUF7Ak+do//zzj9hmN1++fKlWhCgPjwpqEvDk8ampgcgEAQhAAAIQgAAEPFBA9hxNqQBIlixZiL/S4gMJeesrJO8VkP1geK88Wg4BCEAAAhCAAASsC2COhtGhsgDGp8q9g7pBAAIQgAAEIOCtArLnaEoFQMqUKUMXLlyg/fv3U0hIiLeOCbSbiGQ/GOgECEAAAhCAAAQgAIHUAirO0Xr16iVWdPBWVwULFtTUbbdu3aKPP/5YXMfbYyEZQ0DF8WkMWbQCAhCAAAQgAAEIOC4ge46mVABk6NChNHv2bJo6dSoNGzbMcVUXXXn58mWaM2cObdu2jfjfM2XKRKVLl6bQ0FAaMGAA8QoWPdK6deto+fLl9Pvvv4stwQoUKED169engQMHUnBwcJq3uHv3Lv3yyy9iFY3pn9evXxfXNGzYkH7++WebVeQ8jRs3tpmPM/DB8+PHj9eU155Msh8Me+qKvBCAAAQgAAEIQMBbBFSco/Hh5xzIOHHiBFWoUEFTV8TGxhJ/fMXXJSQkaLoGmdQXUHF8qq+GGkIAAhCAAAQgAAHXCsieoykVALl27RpVqVKFMmTIQMeOHRN/+FclcdCDD0u8d++exSqVK1eOtm/fToGBgQ5X+cmTJ9ShQwfaunWrxTL45Y6DDWPGjLF6j5IlS9LFixct/h4BEIe7BhdCAAIQgAAEIAABCCi6ShcBEAxNk4Dsl2v0BAQgAAEIQAACEIBAagHZczSlAiDMc+DAAWrbti1ly5aNvvnmG2rZsqX0cXP8+HGqU6cOPXr0SNRr1KhRYoXE48ePiVdrLF68WNSxfPnyYtUF53EkcYBlzZo14lIunw+CL1SokPia7YsvviD+Uo0T369Pnz4Wb1GiRAm6dOmS+F1AQADVrFnTHFBxJACyQ6KAHAAAIABJREFUbNkyUYa1lD9/fuL/0zvJfjD0bg/KgwAEIAABCEAAAkYQUHGO5kgA5NSpU1S5cmXy8/MTc3wkYwioOD6NIYtWQAACEIAABCAAAccFZM/RlAqANGnSREjySpBz586JJek5c+YUy9NtbS/FeXfv3u14T6RxJQcjeFuo9OnTU2RkZKrzSaZPn04jRowQJUyYMIHGjh1rdz327dtHjRo1Ete1bt2aNm7cSL6+vuZybt++LQ6G5623cuXKJc5KYZuU6csvvyReBcJBi2LFiolfsw0nRwIge/fuNdfL7kY5cYHsB8OJquNSCEAAAhCAAAQgYFgBFedojgRAFi1aRP3796fixYvTX3/9Zdj+8raGqTg+va0P0F4IQAACEIAABCCQUkD2HE2pAIjp5YWRXr58qWm08B/3Oa+r9u/lFR21atUSdenXrx8tWLAgVb0SExOpUqVKdObMGRGciIuLE9t42ZNatWolttDioAdvYVWkSJFUl/Nqk06dOomfc6Djo48+0nQLBEA0MSETBCAAAQhAAAIQgIANAdkvL1y9iRMnJqslbxHL891//etfNlcmP336VKyq3rx5M/G/89x61apV6HeDCKgwPg1CiWZAAAIQgAAEIAAB3QRkz9GUCoDwCgjTH+sdEebVCnqn0aNHi+2nOB06dIhq165t8RZTpkwRW2NxioiIoGbNmmmuyoMHDyhv3rziJaxFixa0Y8cOi9c+e/aM8uXLR/fv3xdbcvF2YVoSAiBalJAHAhCAAAQgAAEIQMCWgOyXF65f0o+m+L9NH07Z8x7B1/D2V9HR0VS1alVbzcbvPURAhfHpIVSoJgQgAAEIQAACEHCbgOw5mlIBELep23GjBg0aUFRUFGXNmpXu3r0rtsGylPjliYMSnHgLLN4KS2vas2cPNW3aVGSfPHkyjRw50uqlzZs3FwEWrgfvV6xlpQkCIFp7AvkgAAEIQAACEIAABNISkP3ywnXjAEjSZJrrallBzkGPggULinn7sGHDEPww2HBXYXwajBTNgQAEIAABCEAAAk4LyJ6jIQBiowt5xQWfv8FfhsXExFjNfefOHcqdO7f4fYcOHSg8PFzz4Jg7dy4NGjRI5OezP9q0aWP1Wj4Yfc6cOeL3fHhjhQoVbN7HmQBISEiIOHfk5s2bIgjEh6zzSh3eYqBs2bI27+1oBtkPhqP1xnUQgAAEIAABCEDAyAIqztEcOQPEyH3kzW1TcXx6c3+g7RCAAAQgAAEIQIAFZM/REABJYxw+efKEMmfOLHLwGR1bt25Nc9Rmy5aNHj58SMHBwWI5vdbEKz6mTp0qsvOZIzVq1LB6KZ/9MXz4cPH7nTt3Eq8IsZWcCYBYK5tfNMeMGUPjxo1zaNsyHvhppevXr5vPXrly5YrFM1FstRu/hwAEIAABCEAAAhDQV0D2y4ul1vAHOjzf/fHHH6l06dL6NhileZSAiuPTowBRWQhAAAIQgAAEIOACAdlzNARA0ujUW7dumQ9SfPfdd4kPIU8rBQQEiJUSfCD6iRMnNA+XgQMH0rx580R+Pki9fPnyVq+dP38+DRgwQPx+w4YN1K5dO5v3cSQA0rlzZ3rnnXeoXr16FBgYKLbc4pUgW7ZsobCwMHr+/Lm4L597YjojxWZFkmSwZ49mBEDskUVeCEAAAhCAAAQg4DoB2S8vrmsZSjaCAManEXoRbYAABCAAAQhAwGgCsudoUgIg/Id0UypWrJj535P+3JGOTlqWI9envIb/8G4qs1u3brRy5co0i+W8fE2pUqXozz//1FyF3r1707Jly0T+2NhYEXCwljgf5+fEgYiuXbvavI+9ARBexZIxY0ar54scOXKEXn/9dbp375742u63336joKAgm/VImgEBELu4kBkCEIAABCAAAQgoISD75UUJBFRCWQGMT2W7BhWDAAQgAAEIQMCLBWTP0aQEQHx9fUWX8x/BX7x4Ye5+088dGQ8py3KkjJTXeOsKEC12q1evNgdf+vTpQ4sXL9ZymTkPtsCyiwuZIQABCEAAAhCAgBICsl9elEBAJZQVwPhUtmtQMQhAAAIQgAAEvFhA9hxNSgCEz48wBUASEhLM3W/6uSPjgQMgSctypIyU13jrGSBa7DhwlTdvXrEKpEyZMnTu3Dktl2nOI/vB0FxRZIQABCAAAQhAAAJeJIA5mhd1tgc2FePTAzsNVYYABCAAAQhAwPACsudoUgIg3377rblje/ToYf73pD93pOeTluXI9ZauyZcvH92+fZuqVq1KMTExVou9c+cO5c6dW/y+Q4cOFB4errkK33zzDb3//vsi/8aNG6lNmzZWrx08eDDNmTNH/P7UqVNUoUIFm/exdwssmwX+N0OtWrXEoe1ZsmQRh7/rmWQ/GHq2BWVBAAIQgAAEIAABowhgjmaUnjRmOzA+jdmvaBUEIAABCEAAAp4tIHuOJiUA4kld1qBBA4qKiqKsWbPS3bt3xWHgllJ0dDTVqVNH/Grs2LE0YcIEzc3cs2cPNW3aVOSfPHkyjRw50uq1zZs3p4iICFEP01kdtm7kqgBIzZo16ddff0UAxFYH4PcQgAAEIAABCEDAIAKyX14MwohmuEgA49NFsCgWAhCAAAQgAAEIOCEge46GAIiNzvvkk09EUILToUOHqHbt2havmDJlCo0aNUr8bteuXeKQcK0pPj5ebCf17NkzatGiBe3YscPipfx7XpFy//59CgkJoYMHD2q6hSsCILwFVp48eURdSpcuTefPn9dUF62ZZD8YWuuJfBCAAAQgAAEIQMCbBDBH86be9ry2Ynx6Xp+hxhCAAAQgAAEIGF9A9hwNARAbY+zIkSPmoEe/fv1owYIFqa5ITEykSpUq0ZkzZyhnzpx08+ZNypAhg12jt2XLliLwwSs7/vrrLypSpEiq69etW0edOnUSP582bRoNHz5c0z1cEQBZtWoVdevWTdy/d+/etGTJEk110ZpJ9oOhtZ7IBwEIQAACEIAABLxJAHM0b+ptz2srxqfn9RlqDAEIQAACEICA8QVkz9EQANEwxkzbYHFwIjIyUqy+SJqmT59OI0aMED8aN24cjR8/PtnvV6xYQT179rT6e/5F0m2w3nrrLfrhhx/I19fXXA6fQ1K9enW6fPmyCLJcuHCBcuXKpaH2RPYEQPgsk+PHj1OjRo2sls1BId6Ki7cE47L5v2vUqKGpLlozyX4wtNYT+SAAAQhAAAIQgIA3CWCO5k297Xltxfj0vD5DjSEAAQhAAAIQML6A7DmatAAIBxL0ThyocEU6duwY1a1blx4/fkzZsmUj3harcePG4r95VcaiRYvEbcuWLSvOxPD3909WDS0BEL6AV3dweZy4/CFDhlChQoXoxIkT9Pnnn1NsbKz4Ha9C4dUolhIf1J7ysHZT8KVcuXKpzhdp3769aJMpXbx4kUqWLElVqlQRh7Fz0KVgwYIiGMPBly1btlBYWBg9f/5cXMKrUHg1it5J9oOhd3tQHgQgAAEIQAACEDCCAOZoRuhF47YB49O4fYuWQQACEIAABCDguQKy52jSAiA+Pj7mlQl6dB+vROBzKVyV+A//Xbt2FWdeWEoc/Ni2bZs4DyNl0hoA4YAKByS2b99u8R5sNmbMmFQrTJJm5tUn9hzAztttlShRwlyEKQBiy5EDIlwXPvDdtMLE1jX2/F72g2FPXZEXAhCAAAQgAAEIeIuAinM0nkNnzpzZoS7gD51effVVh67FReoJqDg+1VNCjSAAAQhAAAIQgIB7BWTP0aQHQF6+fKmLOP8RPiEhQZeyrBVy6dIlmj17tgh0cMdlzJhRBDw6dOhAgwYNoixZsli8VGsAxHTxmjVriK/hrah4m6mAgACqX7++uEfK7bdS3tDZAAgftL5582aKjo4WW1tdvXqVePutJ0+eUI4cOYhXkfD2WH369EkWONEbXvaDoXd7UB4EIAABCEAAAhAwgoCKc7Ty5csTz5+rVatmF/GUKVPEh0U8z0UyhoCK49MYsmgFBCAAAQhAAAIQcFxA9hxNegDEz8+P3n77bWrWrBnxCgdnUo8ePZy5HNcqJCD7wVCIAlWBAAQgAAEIQAACygioOEfjd4gMGTKIVdAff/yxzdXJV65coW7dulFUVJRwdfVHVMp0nhdURMXx6QXsaCIEIAABCEAAAhBIU0D2HE1aAIRXE8THxwscXr3Bqxw6d+4sXkaqVq2KYePlArIfDC/nR/MhAAEIQAACEICARQEV52g5c+YU29TyOwWvmubz6ooWLWqx/qtXrxarqjk/r0Tnlc179uxBbxtEQMXxaRBaNAMCEIAABCAAAQg4LCB7jiYtAMJLzf/973+LF5SIiAhxfofpLIlKlSqJQAgHRPgQcCTvE5D9YHifOFoMAQhAAAIQgAAEbAuoOEe7fPkyde/enSIjI8X7RPbs2WnevHnUqVMnc4Pu3btH/fv3p/DwcBH44K1sJ06cSMOHD7e5YuT/2TsPcCmK7G8fQCWbIyoGDKzK6oqYUFFRzIKoiIIZc17Fv8gqhlXBnHVNiAlERARzBLOYI7gKCgiKYiRJku855dd3515m7vTMnZmuPvXW8+zDeqe6un7vqequU6erKj8VcvhCwMf26Qsb6gEBCEAAAhCAAASSIpD0GC2xAEgm8B9//NHt26vBkPfff9/9pM6LLmfXr7LUoenatas0bdo0KTtx3woTSLpjVFgut4MABCAAAQhAAAKpIODrGE2DGldeeaX069dP9Ew79SU0AKKBEPUvdKtcrbvm22STTeSBBx6QLbbYIhXMqWR8Ar62z/gKyAkBCEAAAhCAAATsEUh6jOZFACTTrOPGjZP77rvPBUR0f94oGNK4cWM54IADpGfPntKpUye+1LLXF6opSrpjGMeLPAhAAAIQgAAEIFAUAd/HaB988IH06NFDxo8f7/yFlVdeWX766Sf5888/nV7d/koDJXoOIckeAd/bpz3iKIIABCAAAQhAAAL5CSQ9RvMuAJKJbPTo0S4YMnz4cLdPbxQM0fNCdIusAQMG5CdMjlQSSLpjpBIalYYABCAAAQhAAAJlJpCGMZputatb6Y4YMcIFQXTVh26Lpdtf6YdUJLsE0tA+7dJHGQQgAAEIQAACEMhOIOkxmtcBkAiZOjHqwOgWWc8//7w7L0S/2pozZw7tyiiBpDuGUazIggAEIAABCEAAAnUikIYx2i233OLO9pg3b54LfmjSQMjRRx8tN9xwA9vq1qkF+H1xGtqn3wSpHQQgAAEIQAACECg9gaTHaKkIgKjzogem62oQDYAsWLCAAEjp26JXJSbdMbyCQWUgAAEIQAACEICAJwR8HqP98MMPLsjxzDPPuMCHnh943nnnycCBA2XixIkuCNKqVSt3/sfWW2/tCVGqUUoCPrfPUuqkLAhAAAIQgAAEIJAmAkmP0bwOgIwZM8at+hg2bJjMnDnT2VWdmTXWWMNtgdW/f/802Zq6FkAg6Y5RQFXJCgEIQAACEIAABIIh4OsYbdSoUdKrVy+ZMWOG8xc0wPHggw+6gMfs2bPd2R+DBg1ydlpqqaWkb9++csEFF0j9+vWDsV0IQn1tnyGwRyMEIAABCEAAAhDIRSDpMZp3ARA9BF2DHuqwKJwo6NGkSRN3CPoRRxwhHTt2xFkx3qeS7hjG8SIPAhCAAAQgAAEIFEXAxzHaSSedJHfccYcLfDRo0ED69Okj/fr1c/8/Mz366KNywgknyM8//+xWg2yzzTZuNcj6669fFAsu8o+Aj+3TP0rUCAIQgAAEIAABCFSWQNJjNC8CILpcffDgwS7w8cEHH1QFPfSLrF122cUFPbp27cp+vZVtm4neLemOkah4bg4BCEAAAhCAAAQ8JeDjGC1axbHuuus6f6J9+/Y56X333Xdy5JFHygsvvODyNG/eXH777TdPaVOtQgn42D4L1UB+CEAAAhCAAAQgYI1A0mO0xAIgNQ82X7RoUdUhhZtttpnb4qpHjx7SokULazZHTwwCSXeMGFUkCwQgAAEIQAACEAiOgI9jNA2A9OzZU/Twcw1oxEnXXXednH/++TJ//nxRP4Rkg4CP7dMGWVRAAAIQgAAEIACB4gkkPUZLLACy7LLLuv14Nely9dVXX10OPfRQF/jYYostiifKlSYIJN0xTEBEBAQgAAEIQAACECgxAR/HaEOGDJHu3bsXrPSTTz5xgZOPPvqo4GsLuWDy5Mly4403ypNPPin6/xs2bCgbbLCBdOvWTU4++WTRrX7rmj7++GO5+eabZfTo0TJ16lS3/dfaa68t++yzjzv/pGXLlrXe4osvvpCnnnpK9AxG5fH999+7bcJWW201d56Krsjfe++93d9yJb23rt6Pk3SLsosuuihO1oLy+Ng+CxJAZghAAAIQgAAEIGCQQNJjtMQCIPqllg6gGzVqJPvvv7906tRpiX16C7W3DsxJNggk3TFsUEQFBCAAAQhAAAIQKC0Ba2M0XQGyzDLLlBZSRmka9NBV7bm22dp4441d4KEu55BoMOHSSy+tWk1fU4x+eHbvvfe68xSzJd0S7L777svLYI899hANNi2//PJZ8xIAyYuQDBCAAAQgAAEIQCBIAkn7EIkHQEpldQ2mLFy4sFTFUU7CBJLuGAnL5/YQgAAEIAABCEDASwKM0eKbRVdSbL/99jJnzhxp1qyZO5xdV0jMnTvXBRLuvPNOV1jr1q3lnXfecXkKTf3793flalpjjTWkd+/e7p6a3njjDbnyyivdag5ddfLSSy9V/ZZ5n912201efPFFWXHFFeWggw6SnXfeWfQ8laWWWsqdz3jttdeKrhDRtMMOO7hVItG5K5nlZAZA7rnnHmnXrl1OOauuuqro/0qdaJ+lJkp5EIAABCAAAQhAoO4Ekh6jJRoAqTu+/5WgARD27y0l0WTLSrpjJKueu0MAAhCAAAQgAAE/CTBGi28XDXZoUEADCa+88opst9121S6+6qqr5Nxzz3V/u/jii+XCCy+MX7iI2+qqVatWMm/ePHduogZRap6fqHl0C6tp06bJ5ptvLu+///4SwYujjjrKBUZ0JYgGSmomDeDo6o/XXnvN/aSrRXTb4popMwDy8ssvu0BKpRPts9LEuR8EIAABCEAAAhDITyDpMVpiARD9cqjUqUOHDqUukvISIpB0x0hINreFAAQgAAEIQAACXhPwfYymZwt++OGH7hyLGTNmuNUW+rfaUqGBhzgG0mCEBh40nXDCCXL77bcvcdmff/4pm222mYwbN05WWGEFmT59uiy99NJxind5rrnmGjnnnHPc/9fVJL169cp67V133SXHHXec++2JJ55w54IUmj799FNp06aNu0y3L3788ceXKIIASKFUyQ8BCEAAAhCAAATCIJC0D5FYACQM86KyWAJJd4xi6811EIAABCAAAQhAwDIBn8dogwYNcispJk2aVJAJyrGKvG/fvnL55Ze7erz11luyzTbbZK1T5hZWzz33nOy+++6x664Hvz/88MMuv9plzTXXzHptps10tcfAgQNj3yMz4yqrrOKCSptuuqloQKRmIgBSFFYuggAEIAABCEAAAuYJJO1DEAAx38TSKTDpjpFOatQaAhCAAAQgAAEIlJeAr2M0DThoMCHfag+lo1vnZubTlRilTjvttJO8+uqr0rRpU/n111/dNljZ0ptvvll1LoeuRNEATtzUqVMnef755132BQsW5LyH/hYd9L7eeuvJxIkT496iWr7llltOfv/9d7cS5OOPP16iDAIgRWHlIghAAAIQgAAEIGCeQNI+BAEQ800snQKT7hjppEatIQABCEAAAhCAQHkJ+DhGe/vtt935GhrY0AO99WwNDWpsueWW7m8LFy6UX375Rd5991257bbb3PZNepj3I488IquttlpZgEWrJfTcDd2SK1fSeunh45oOPvhgGTp0aOz6HHDAATJixAiXX1dmrLTSSlmv1d+0PpqUx6xZs6RJkyax76MZ9TB05VlbPTMDIGqPyZMnyw8//OCCQHqoup4JctJJJ8lGG21U0L0Lyexj+yyk/uSFAAQgAAEIQAACFgkkPUYjAGKxVRnQlHTHMIAQCRCAAAQgAAEIQKDkBHwco+m2Tnowt06y//e//3UrIT777DO3UkEn/GtucaVBkFNOOcUdCq7Bk2h1RKlg/fHHH9K4cWNXnJ63oedu1JaaNWsms2fPlm233VZ0RUjcdP7558sVV1zhsj/66KPStWvXrJcOHz5cDjzwwKrfvvjii4KDEBqcGTZsmCtDA0cHHXTQEvfKDIDk0lC/fn254IILpF+/fs42hSZtf7Wl7777rurslSlTpshaa61V6C3IDwEIQAACEIAABCBQYgJJ+xAEQEpsUIorDYGkO0ZpVFAKBCAAAQhAAAIQsEXAxzGariiYMGGCOxT8zDPPdMBrC4Do7zqhr4GBzGtKZakff/xRVl11VVfcIYccIkOGDKm1aF2Foisl9ED0Tz75JHY1NHijQRNNGszRs0YaNWpU7XoNxmgePRQ+SroSpm3btrHvo8GVKOCh1+kB79mCFxoAOeyww1wgRlfYrL/++i4YpStBRo0aJffff7/bqktTnz59qs5IiV2R/7+CJW5+AiBxSZEPAhCAAAQgAAEIlJdA0j4EAZDy2pfSiySQdMcostpcBgEIQAACEIAABEwT8HGM1rx5c5kzZ44888wzVYeIjxs3zh3WrRP1GgRYeumlq9ll5MiR0qVLF3c4eSGrLuIYVyfeW7Zs6bIefvjhbnVKbUnz6jWtWrWSr776Ks4tqvJ07txZVIumrbfe2gUVdPspTapLV4mMHTvWrXKZP3+++7ueTaIBijhp/PjxrtyZM2e6VS0aPNlkk02yXqqrWPQ+NVlHmbUeem7Jb7/95uzy/vvvyxZbbBGnGlV5Clk1QgCkILRkhgAEIAABCEAAAmUjkLQPQQCkbKal4LoQSLpj1KXuXAsBCEAAAhCAAASsEvBxjKarHnRlgU6o60oITTr5vc4667iJdv3/LVq0qGYSPdNCVzPouRm6YqOUqVIrQLTOesD6Xnvt5VZ/5Ert2rVzq0sGDhzosuiZJBGn2nRPmzZN2rdvL998843j+OCDD8qhhx5aJ1RaRs+ePV0ZvXr1kjvvvLOg8tgCqyBcZIYABCAAAQhAAAJeEEjahyAA4kUzoBI1CSTdMbAIBCAAAQhAAAIQgMCSBHwco6299tqik/W6BdOOO+7oKq2rHfTwbT0M/bnnnpOOHTtWE/PUU0/Jvvvu61Ys6AqRUqZKnQES1Vm13nrrrS6Y8Pnnn1dJWX311eW4446Tvn37So8ePdw5IZomTZpUtUIll+6ff/5ZdtppJ7eVmKYbb7xRTjvttDpj0gPpV155ZbcKZMMNN3RntpQy+dg+S6mPsiAAAQhAAAIQgEAaCSQ9RiMAksZWE0Cdk+4YASBGIgQgAAEIQAACECiYgI9jtD333FOef/55uf32292Ef5R0eyU9U+PYY4+VO+64o5pWDQgMHjzYHZw+ceLEgjnku2CVVVaRGTNmuJUWuuIiV/rll19kxRVXdD/ruSRDhw7NV3Stv2tgQc8T0YPVNQASbRml56R8+eWXotuF6aoRPYw8V9LtrjRgpGd9aLr00kvlX//6V53qlXmxbqmlZTdp0sQd/l7K5GP7LKU+yoIABCAAAQhAAAJpJJD0GI0ASBpbTQB1TrpjBIAYiRCAAAQgAAEIQKBgAj6O0S677DK54IILpHv37vLQQw9Vabriiivc6ged7NezMPRAcj0rZNCgQW7FhAYHTjzxRLnlllsK5pDvAl09oWdt6CoUDTjoYeDZkp7Tsf3227ufLrzwQrn44ovzFV3w79OnT5c11lhDFi9eLLvuuqu8+OKLOcuYO3eu21JrzJgxLk/v3r3lyiuvLPietV2gW3LpWSIEQEqKlcIgAAEIQAACEICAtwSS9iEIgHjbNMKuWNIdI2z6qIcABCAAAQhAAALZCfg4RtNtmtq0aeNWPWj9ll12WVd5DXbo2RfRGRaZijQYoCsvdHXGWmutVXJza8BFAzCa9HwOPWw9W+rfv7/06dPH/fTss8+6Q8JLna6//no566yzXLG6SuaEE07Iegs9R0UPVX/66afd7xocuu2220paHd0CS89d+f3332WDDTZwq1JKmXxsn6XUR1kQgAAEIAABCEAgjQSSHqMRAEljqwmgzkl3jAAQIxECEIAABCAAAQgUTMDXMZquWNDJ9X/84x9VW0qpOD3vQg/dfv3116tp1cDI/fffH+sw8IIhicjYsWOrgh4acNDAQ82k55NoPcaNGyfLL7+827pq6aWXLuZ2Oa/RQMPGG28s33//vbvH5MmT3TZYNdOiRYvcCpphw4a5nw4//HC3UibaQqtUlXrggQdc2Zp0a7K77rqrVEW7cnxtnyUVSWEQgAAEIAABCEAgZQSSHqMRAElZgwmlukl3jFA4oxMCEIAABCAAAQgUQiCtY7QvvvjCHeitQRI9fFsDJeVO0TZYuv3VK6+8Itttt121W1511VVy7rnnur/169dPLrroomq/33vvvXL00Ufn/F1/+O6779yh4tkCJ3qWR9euXeWFF15wZWiwQYMONZOuhtG/Dxw40P104IEHysMPPywNGjSIjUjPMvnoo49k5513znmNBoX22GMPtyWYBlb0v7faaqvY94iTMa3tM4428kAAAhCAAAQgAIG0Ekh6jEYAJK0tx3i9k+4YxvEiDwIQgAAEIAABCBRFgDFafGwffPCBtG/fXvRcDd2eS7fF2mWXXdx/DxkypOpgdj2gXM/EqLkyI04A5Oqrrxb935FHHikdOnRwZ33oqg/ddkvPOdEVH5o0kHLPPfdkrfzZZ58t1157rftNV6Toyo9lllmmVqGaLzPpNmPrrbee/P3vf5cuXbpI27ZtXV00iKJ1GDVqlFtxo9tsaSrH2SJaLu0zfvskJwQgAAEIQAACEKgUgaTHaARAKmVp7lMQgaTFPGlGAAAgAElEQVQ7RkGVJTMEIAABCEAAAhAIhABjtMIMrRP/ugWXBiWyJQ1+PPnkk+48jJopbgBEgwm5kq4+0QDH5Zdf7g6Dz5bWXXddt1VYIUlXjWSmKACSrwwNiOiB9Xrge6m319J70z7zWYDfIQABCEAAAhCAQOUJJD1GIwBSeZtzxxgEku4YMapIFghAAAIQgAAEIBAcAcZohZtcgws33HCDC3QoP11doQGPgw8+WE499VRp0qRJ1kLjBEAmTpwoDz30kLz00ksyYcIEd45Iw4YN3cHueqC6bm216aab1lrpUgRA5s+fLyNHjpQ333zTbW01depUmTFjhvzxxx+y3HLLuXNIdHusXr16id6vXIn2WS6ylAsBCEAAAhCAAASKJ5D0GI0ASPG248oyEki6Y5RRGkVDAAIQgAAEIACB1BJIeoymZ2mUOulZHSQbBJJunzYoogICEIAABCAAAQiUlkDSYzQCIKW1J6WViEDSHaNEMigGAhCAAAQgAAEImCKQ9BhNt3Eq5dZJWpYejE6yQSDp9mmDIiogAAEIQAACEIBAaQkkPUYjAFJae1JaiQgk3TFKJINiIAABCEAAAhCAgCkCSY/RogBIzTMoioWsAZBFixYVeznXeUYg6fbpGQ6qAwEIQAACEIAABLwgkPQYjQCIF82AStQkkHTHwCIQgAAEIAABCEAAAksSSHqMFgVAGjVqJJ07d5bdd9895+Hece135JFHxs1KPs8JJN0+PcdD9SAAAQhAAAIQgEAiBJIeoxEAScTs3DQfgaQ7Rr768TsEIAABCEAAAhAIkUDSYzQ9UHvmzJkOva7eWG211eSwww6Tww8/XDbffPMQTYLmDAJJt0+MAQEIQAACEIAABCCwJIGkx2gEQGiVXhJIumN4CYVKQQACEIAABCAAgYQJJD1G++OPP+Txxx+X+++/X5577jl3fkd0Jshmm23mAiEaEGnRokXCpLh9EgSSbp9JaOaeEIAABCAAAQhAwHcCSY/RCID43kICrV/SHSNQ7MiGAAQgAAEIQAACtRLwaYz2448/ykMPPeSCIe+//76rtwZDdJusnXfeWY444gjp2rWrNG3aFKsGQsCn9hkIcmRCAAIQgAAEIACBvASSHqMRAMlrIjIkQSDpjpGEZu4JAQhAAAIQgAAEfCfg6xht3Lhxct9997mAyJQpU6qCIY0bN5YDDjhAevbsKZ06dapaLeI7Z+pXHAFf22dxargKAhCAAAQgAAEI2CCQ9BiNAIiNdmRORdIdwxxQBEEAAhCAAAQgAIESEEjDGG306NEuGDJ8+HD5/fffq4Ihel6IbpE1YMCAEpCgCB8JpKF9+siNOkEAAhCAAAQgAIFyEkh6jEYApJzWpeyiCSTdMYquOBdCAAIQgAAEIAABwwTSNEbT80JGjBjhtsh6/vnn3XkhjRo1kjlz5hi2UNjS0tQ+w7YU6iEAAQhAAAIQCIlA0mM0AiAhtbYUaU26Y6QIFVWFAAQgAAEIQAACFSOQpjHavHnz3IHpuhpEAyALFiwgAFKxlpLMjdLUPpMhxF0hAAEIQAACEIBA5QkkPUYjAFJ5m3PHGASS7hgxqkgWCEAAAhCAAAQgEByBNIzRxowZ41Z9DBs2TGbOnOlstHjxYlljjTXcFlj9+/cPzm6hCE5D+wzFFuiEAAQgAAEIQAACEYGkx2gEQGiLXhJIumN4CYVKQQACEIAABCAAgYQJ+DpG00PQNejx4IMPitYxCno0adLEHYJ+xBFHSMeOHaV+/foJE+T25STga/ssp2bKhgAEIAABCEAAAr4TSHqMRgDE9xYSaP2S7hiBYkc2BCAAAQhAAAIQqJWAT2O0H374QQYPHuwCHx988EFV0EODHLvssosLenTt2lWaNm2KVQMh4FP7DAQ5MiEAAQhAAAIQgEBeAkmP0QiA5DURGZIgkHTHSEIz94QABCAAAQhAAAK+E0h6jFbzYPNFixa57a00bbbZZm6Lqx49ekiLFi18R0n9ykAg6fZZBkkUCQEIQAACEIAABFJPIOkxGgGQ1DchmwKS7hg2qaIKAhCAAAQgAAEI1I1A0mO0ZZddVmbPnu1EaOBj9dVXl0MPPdQFPrbYYou6iePq1BNIun2mHiACIAABCEAAAhCAQBkIJD1GIwBSBqNSZN0JJN0x6q6AEiAAAQhAAAIQgIA9AkmP0XR7q3r16kmjRo1k//33l06dOkmDBg3qBFq3yiLZIJB0+7RBERUQgAAEIAABCECgtASSHqMRACmtPSmtRASS7hglkkExEIAABCAAAQhAwBSBpMdoUQCkVFA1mLJw4cJSFUc5CRNIun0mLJ/bQwACEIAABCAAAS8JJD1GIwDiZbOgUkl3DCwAAQhAAAIQgAAEILAkgaTHaBoAKWXSAIieI0KyQSDp9mmDIiogAAEIQAACEIBAaQkkPUYjAFJae1JaiQgk3TFKJINiIAABCEAAAhCAgCkCSY/RxowZU3KeHTp0KHmZFJgMgaTbZzKquSsEIAABCEAAAhDwm0DSYzQCIH63j2Brl3THCBY8wiEAAQhAAAIQgEAtBBij0Tx8JkD79Nk61A0CEIAABCAAgVAJJD1GIwASasvzXHfSHcNzPFQPAhCAAAQgAAEIJEKAMVoi2LlpTAK0z5igyAYBCEAAAhCAAAQqSCDpMRoBkAoam1vFJ5B0x4hfU3JCAAIQgAAEIACBcAgwRgvH1mlUSvtMo9WoMwQgAAEIQAAC1gkkPUYjAGK9haVUX9IdI6XYqDYEIAABCEAAAhAoKwHGaGXFS+F1JED7rCNALocABCAAAQhAAAJlIJD0GI0ASBmMSpF1J5B0x6i7AkqAAAQgAAEIQAAC9ggwRrNnU0uKaJ+WrIkWCEAAAhCAAASsEEh6jEYAxEpLMqYj6Y5hDCdyIAABCEAAAhCAQEkIMEYrCUYKKRMB2meZwFIsBCAAAQhAAAIQqAOBpMdoBEDqYDwuLR+BpDtG+ZRRMgQgAAEIQAACEEgvAcZo6bVdCDWnfYZgZTRCAAIQgAAEIJA2AkmP0QiApK3FBFLfpDtGIJiRCQEIQAACEIAABAoiwBitIFxkrjAB2meFgXM7CEAAAhCAAAQgEINA0mM0AiAxjESWyhNIumNUXjF3hAAEIAABCEAAAv4TYIzmv41CriHtM2Trox0CEIAABCAAAV8JJD1GIwDia8sIvF5Jd4zA8SMfAhCAAAQgAAEIZCXAGI2G4TMB2qfP1qFuEIAABCAAAQiESiDpMRoBkFBbnue6k+4YnuOhehCAAAQgAAEIQCARAozREsHOTWMSoH3GBEU2CEAAAhCAAAQgUEECSY/RCIBU0NjcKj6BpDtG/JqSEwIQgAAEIAABCIRDgDFaOLZOo1LaZxqtRp0hAAEIQAACELBOIOkxGgEQ6y0spfqS7hgpxUa1IQABCEAAAhCAQFkJMEYrK14KryMB2mcdAXI5BCAAAQhAAAIQKAOBpMdoBEDKYFSKrDuBpDtG3RVQAgQgAAEIQAACELBHgDGaPZtaUkT7tGRNtEAAAhCAAAQgYIVA0mM0AiBWWpIxHUl3DGM4kQMBCEAAAhCAAARKQoAxWkkwUkiZCNA+ywSWYiEAAQhAAAIQgEAdCCQ9RiMAUgfjcWn5CCTdMcqnjJIhAAEIQAACEIBAegkwRkuv7UKoOe0zBCujEQIQgAAEIACBtBFIeoxGACRtLSaQ+ibdMQLBjEwIQAACEIAABCBQEAHGaAXhInOFCdA+Kwyc20EAAhCAAAQgAIEYBJIeoxEAiWEkslSeQNIdo/KKuSMEIAABCEAAAhDwnwBjNP9tFHINaZ8hWx/tEIAABCAAAQj4SiDpMRoBEF9bRuD1SrpjBI4f+RCAAAQgAAEIQCArAcZoNAyfCdA+fbYOdYMABCAAAQhAIFQCSY/RCICE2vI81510x/AcD9WDAAQgAAEIQAACiRBgjJYIdm4akwDtMyYoskEAAhCAAAQgAIEKEkh6jEYApILG5lbxCSTdMeLXlJwQgAAEIAABCEAgHAKM0cKxdRqV0j7TaDXqDAEIQAACEICAdQJJj9EIgFhvYSnVl3THSCk2qg0BCEAAAhCAAATKSoAxWlnxUngdCdA+6wiQyyEAAQhAAAIQgEAZCCQ9RiMAUgajUmTdCSTdMequgBIgAAEIQAACEICAPQKM0ezZ1JIi2qcla6IFAhCAAAQgAAErBJIeoxEAsdKSjOlIumMYw4kcCEAAAhCAAAQgUBICjNFKgpFCykSA9lkmsBQLAQhAAAIQgAAE6kAg6TEaAZA6GI9Ly0cg6Y5RPmWUDAEIQAACEIAABNJLgDFaem0XQs1pnyFYGY0QgAAEIAABCKSNQNJjNAIgaWsxgdQ36Y4RCGZkQgACEIAABCAAgYIIMEYrCBeZK0yA9llh4NwOAhCAAAQgAAEIxCCQ9BiNAEgMI5Gl8gSS7hiVV8wdIQABCEAAAhCAgP8EGKP5b6OQa0j7DNn6aIcABCAAAQhAwFcCSY/RCIAU0DImT54sN954ozz55JOi/79hw4aywQYbSLdu3eTkk0+WJk2aFFBa7qxDhgyRgQMHyscffyy//PKLrL766rLjjjvKKaecIttuu22t9/j111/lnXfekbFjx1b9+91337lrOnToIKNHjy6ojm+++abceuut8uqrr8r3338vK6ywgmy++eZy1FFHSffu3Qsqq5DMSXeMQupKXghAAAIQgAAEIBAKAcZohVu6Ej6E+g0333yzG+tPnTpVGjRoIGuvvbbss88+cuqpp0rLli1jVfynn35y/s6IESPkm2++kcWLF8t6660nXbp0kdNPP11WWmmlWOXgQ8TCRCYIQAACEIAABCAQBIGkfQgCIDGbmQY9evToIb/99lvWKzbeeGN56qmnZP31149Z4pLZ/vjjDzn44IPliSeeyFpG/fr15aKLLpILLrgg5z3UQVFnJVsqNAByySWXyMUXXyx//vln1vL2228/GTp0qDRq1KhozbkuTLpjlFwQBUIAAhCAAAQgAAEDBBijFWbESvgQ/fr1k0svvdQFK7KlZZddVu6991454IADaq28fkTVuXNniT6eqpm5RYsW8vjjj8tWW21Vazn4EIW1EXJDAAIQgAAEIAAB6wSS9iEIgMRoYR999JFsv/32MmfOHGnWrJn06dNHdtllF5k7d67oao0777zTldK6dWu36kLzFJM0wPLQQw+5S7X8M844Q9TR+OSTT+Tyyy+XCRMmuN/0fr169cp6i3XXXVcmTZrkfltttdWkXbt2VQGVQgIgd911lxx33HGunFatWsn5558vbdq0kWnTpskNN9wgL7/8svtN6/zAAw8UI7fWa5LuGCUXRIEQgAAEIAABCEDAAAHGaPGNWAkfon///s430bTGGmtI7969nd+i6Y033pArr7zSreLWlesvvfRS1W81VeiqkbZt28r06dNlqaWWkn/+85+y7777umz6cda1114rCxcudP7Fe++9J2uuuWZWEPgQ8dsHOSEAAQhAAAIQgEAoBJL2IQiAxGhpGozQ5eTqDLzyyiuy3XbbVbvqqquuknPPPdf9TVdMXHjhhTFKrZ5lzJgxsvPOO7s/6sqKxx57zC1dj9KMGTOcU6JL6HUbqokTJ8ryyy+/xH2uvvpqt0xdAx/RUvd69eq5fHEDILqNlpah/2oZ6uSsvPLKVfdatGiR+4Js1KhR7m9a95122qlgzbVdkHTHKKkYCoMABCAAAQhAAAJGCDBGi2/IcvsQGrTQD5XmzZvnPprSD7H038ykebbeemv3EZNuY/v++++LriqvmXR720GDBrk/6wpvXZWemR555BG37a+mo48+Wu65554lysCHiN82yAkBCEAAAhCAAARCIpC0D0EAJE9rU0dCnQZNJ5xwgtx+++1LXKFbRG222WYybtw4F5zQL6eWXnrpgtqx7s+rW2hp0EO3sFprrbWWuF5Xmxx66KHu7xroOPvss2Pdo9AASGZAZ/DgwVnP+tCGq6tNNBiiX4dFwZBYFYqRKemOEaOKZIEABCAAAQhAAALBEWCMFs/klfAhrrnmGjnnnHNchWpbIZ65KkNXc6jfkZnUd9EVHTqu32OPPeSZZ57JKnLPPfeUZ5991vkrGljR1SCZCR8iXtsgFwQgAAEIQAACEAiNQNI+BAGQPC2ub9++bvspTW+99ZZss802Wa/IXH7+3HPPye677x67Lc+aNcutsNCvt9SxePrpp7NeO3/+fFlllVXk999/d8vXX3/99Vj3KDQA0r59e7dkXvcL/vHHH2WZZZap1QnSJfW6QqXYrb+yFZ50x4gFlkwQgAAEIAABCEAgMAKM0eIZvBI+RPfu3eXhhx92FVK75NqWKtNmutJj4MCB1URo8OT44493f9MPrg455JCsIjM/xrrjjjuqtsuNMuNDxGsb5IIABCAAAQhAAAKhEUjahyAAkqfF6dZOr776qjRt2tRtCaXbYGVLb775ZtWeuroFlm6FFTfpfrwdO3Z02a+44go577zzcl6qX2VpgEXroWeSxFlpUkgARIMsqlX3+K3tC7Corno2iCbVoMv8S5WS7hil0kE5EIAABCAAAQhAwBIBxmjxrFkJH6JTp07y/PPPuwotWLAgp5+iv0UfNOk2t7qVbmY64ogj5P7773d/0gPQV1999awi9bdoiy29JtoySzPjQ8RrF+SCAAQgAAEIQAACIRJI2ocgAJKn1emKC13doHvmfvjhhzlz//LLL7Liiiu633XPXN07N2665ZZb5NRTT3XZ9eyPLl265LxUD0a/8cYb3e+fffaZbLLJJnlvU0gARMvU7bw06b2uv/76nOVrXbt27ep+Vw0nn3xy3rrEzZB0x4hbT/JBAAIQgAAEIACBkAgwRotn7Ur4EHom34gRI1yF1F9ZaaWVslZOf9P6aFK/QFefN2nSpCqvnh347rvvynLLLec++KotaR5dja7XjB07tiorPkS8dkEuCEAAAhCAAAQgECKBpH0IAiC1tLo//vhDGjdu7HLoXrm6Z25tSbeAmj17tmy77baiK0LiJl3xMWDAAJdd9wveaqutcl6qZ3/07t3b/a778+oqjXypkACIlrnXXnu5InUf32hf4Wz3UEdJnR9NqkFXr8RN2vBrS1OmTKlaUaPO1RprrBG3aPJBAAIQgAAEIAABCJSJgK4CiM7H+/rrr92ZcKTqBCrlQ+hK7Gj8/eijj1Z9mFTTHsOHD5cDDzyw6s9ffPGFbLTRRlX/rSs+9ByQTTfdVD799NNazakfSmmwQ6/RthAlfAh6AQQgAAEIQAACEIBALgJJ+xAEQGppm3r+xaqrrupy6F64uu9tbUkPAvzhhx/cCopPPvkkdqs/5ZRT5NZbb3X59SD11q1b57z2tttuq1ppMWzYsGrOTK6LCgmAPPLII9KtWzdXlN7rxBNPzFkXrWu0AkVXsNx0002xNUd1in0BGSEAAQhAAAIQgAAEvCKgH6lEH8N4VbGEK1MpH+Ltt992H15p0tXqel5ho0aNqqnXYIzm+eijj6r+rh8xtW3btuq/dftb3VpXzzrUMmpLmkftrh9+zZw5syorPkTCjY7bQwACEIAABCAAgZQQSMKHIABSS+PQVQgtW7Z0OQ4//HC57777am1KmlevadWqlXz11Vexm92xxx4r99xzj8s/YcIEWX/99XNeq/k0vybdq7dnz55571NIAETL1D19Nd19991yzDHH5Cxf9w9WrZq0TnfddVfeukQZCIDERkVGCEAAAhCAAAQg4CWBJJwXL0HUqFSlfAi9befOnWXkyJGuBroy5/LLL5ftttvO/beuSNdVImonPQNEz+nQpOcb7rDDDlW1btCggfz555+y4447yiuvvFIr4uhsE71GzwyMEj5EGlomdYQABCAAAQhAAALJE0jChyAAUovdK/X1VogrQPJtgaVfq40fP150VY3uWZzr8PlKddvMpVpWt+SyptGanlxt3bJOy9oie1rXaF2f2jEEjdZ1YsPCRlM66a1jZE1t2rRZYsVBYaXZzF0pH0Lp6Zkdun1tbSs3dJWOrlAfOHCgA67nGuqKkSilaQUIPoR/fcbaM9SaHnwIm9tpW2+n1vVZH1tnPncs29KytnLYMGkfggBILWPISu3fG+IZIP4N3WuvUdKH9VSClzWN1vTkagOWdVrWFtnTukbr+tSOIWi0rhMbVmKUEdY9KuVDRFR1ZYdup3vnnXfK559/XgVbz+k47rjjpG/fvtKjRw/Rc0I0TZo0qWqVu/53ms4ASVtLCuH5Yk2jNT34EFNkrbXWStujI299rbdT6/qsj60zG7BlW1rWZtGGBEDyvFp09cGMGTPcV1L6tVSu9Msvv8iKK67ofj744INl6NCheV9aUYabb75ZTjvtNPefjz32mHTp0iXntWeccYbceOON7nc9gDA6g6O2mxWyBZYefKhf82nSe11//fU5i9a6du3a1f1+yy23VJ1NElt4ijKG8GCzptGaHpwXnJcUPTKrqhpCPwxBo3UnDRum8enif50r4UNko/Dbb7+5Mwn1jA4NbER+gB56/uWXX0rz5s3dqpH69etXXb7VVlvJe++9J8stt5z7rbakeX7//Xd39ouuio4SPkR2aiE8X6xptKYHHwIfwv835pI1DKEfhqARHyKNvc9ufyQAkqc9Rvvc6tJwdQhybcWke+xuv/32rrQLL7xQLr744tgt/aWXXpKOHTu6/FdccYXoipBcaY899pDnnnvO1WP27NluP998qZAAiH5B1qRJE1m0aJHovZ555pmcxWtddV9hTaphl112yVeV1P4ewsvJmkZrenBecF7S+AANoR+GoBHnJY29z67zkhZrVMKHiMti+vTpssYaa8jixYtl1113lRdffLHapXr+n57hoUm3c9DASbakv7Vo0cL9pNcMGjSoKhs+RHZrhPCOsKbRmh58CHyIuO8Kn/KF0A9D0IgP4VOvKr4uVtoqAZA8bUAn+HWiX5PurbvNNttkvaJ///7Sp08f99uzzz4rnTp1it26Zs6cKSuvvLI7mHDPPfeUp59+Ouu1+rt+TaZfXenhhm+88UasexQSANECNZCjAZ1ll13W7fGcK8iidVWtDRs2dPn0izKryUqHr80+1jRa04PzgvOSxudrCP0wBI04L2nsfUvWOZS26ou1KuFDxNWqK7rPOussl/3222+XE044odqld9xxR9XfhgwZIoccckjWovW3Qw891P32n//8R44//vhq+fAhwux31p4t1vTgQ+BDxH1X+JQvhH4YgkZ8CJ96VfF1sdJWCYDkaQO6tDsKeqizoE5DzfTnn3+6gwXHjRsnyy+/vFt2vvTSSxfUuvbee28X+NCVHV9//XXWfSoznY4rr7xSevfuHesehQZAtOz/+7//c2UPHjxYunfvvsR9tAOsu+66bqWI1v3JJ5+MVZe0ZrLS4QmApLUF5q635bZpWVtkUesareuzPqjPfPJYtqVlbaHY0Me3e6V8iHza9cOpjTfeWL7//nvnp0yePHmJj5b0tzXXXFPUp6ltBXj08ZNunzV16tQlVorgQxAAmTIl/ZPNvBPyPVX8/z0EG1rXaF0fPoT/z5E4NQyhnVpqqwRAYrTqaAm7BideeeUVt/oiM1111VVy7rnnuj/169dPLrroomq/33vvvXL00Ufn/F1/yNwGa//995fhw4dLgwYNqsrRc0jatm3rnBZ1XiZOnCgrrLBCjNpL1d6/HTp0kNGjR+e95ueff5b1119fdA/hddZZx+0JvNJKK1Vdp0GPAw44QEaNGuX+Zn37K0sdngBI3uafugyWX7qWtREASV1Xy1nhENqp9fcgNrTTH31TUgkfQrel0pXk2T6+0lXmel7fCy+84NDcddddcuyxx2bFlLkN1iOPPCIHHXRQtXz6t27durm/HXnkkaL+Tc2ED7Ek2hCeL9Y0WtOT67loWadlbfgQvr3pi69PCO0UH6L49uHTlVbaKgGQGK3qgw8+kPbt28vcuXPdgYK6pF3Pu9D/1lUZumxckx4u+O677y7xVVWcAIher0vKtTxNWv6ZZ57p9tn95JNP5LLLLpMJEya437ItXY9k6EHtNQ9rj4Iv+vVXzfNF1LlRTTWTLms/8cQT3Z9btWolffv2dYejT5s2zR2M/vLLL7vftM4PPfRQDIrpzmKlw9dmBWsarenBeUn/F4XZbGi9nVrXZ31Qn9lmLdvSsrZQbOjrKLMSPsTVV18t+j8NSujHTnrWh6760K17b731VvfxlCb1B+65556cqPTLff3YSre11Y++zj77bNl3331d/ieeeEKuueYaWbhwoduO9/3338+6Wl3z4kNURxzC88WaRmt68CHwIXx9R4Y0NxGiHxhptvxMtazNog9BACTm20BXO/Ts2dM5FNmSBj90G6gNNthgiZ/jBkA0oKIBiaeeeirrPXS5+QUXXLDECpPMzLr6pJAD2HW7Ld3KKlvS1SyXXnqpOzAxW9Ktrx599FFp1KhRTIrpzRbCg82aRmt6cF5wXtL4BA2hH4ag0XqgBxum8emSnjqX24fQ4Edt2+JGwYzLL79c1JeoLb399tvSpUsXt11WtqSHo48YMSLnmYjRNfgQ/6MXwvPFmkZrevAh8CHS88bk2ZlGW+Wrs+VnqmVtBEDytWzjv0+aNEluuOEGF+jQhq6Hg2vA4+CDD5ZTTz1VmjRpkpVA3ABIdLGuqNBrPvroI/n1119ltdVWkx133NHdo+b2WzVvWMoAiJatB63fcsst8uqrr8r06dPd9lubb765+4osOgTRuNmRBwEIQAACEIAABCAAgaIJlNOH0G1x1XfQLWl1tbieRdiwYUO3QqNTp05uy6tNN900dt112131dzTQ8c0337jr1ltvPencubNbnZ65LW5theJDxEZORghAAAIQgAAEIACBMhNgBUiZAVM8BCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAAClSdAAKTyzK7bF8UAACAASURBVLkjBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACZSZAAKTMgCkeAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACByhMgAFJ55twRAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBMhMgAFJmwBQPAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBA5QkQAKk8c+4IAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIBAmQkQACkzYIqHAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCECg8gQIgFSeOXeEAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCECgzAQIgJQZMMVDAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQeQIEQCrPnDtCAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQZgIEQMoMmOIhAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCoPAECIJVnzh0hAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhAoMwECIGUGTPEQgAAEKkVgxowZ8vnnn7vb7bTTTpW6LfcpAYFFixbJTz/9JEsttZSsuOKKJSiRIiAAAQhAAAIQgAAEIJCfAD5Efka+5sCH8NUy1AsCEPCNAAEQ3yxCfVJJYM6cOaIDR00tW7ZMpYa0VlrZz5s3T1ZYYYWsEv773//K8OHDZdKkSdKsWTNp06aN7L///rL88sunVXLOej/88MNy6KGHSv369WXhwoUm9KmOd999V6ZOner0tGjRQrbaaitZeumlU69P2+7tt98ugwcPlo8++kjUgdHUuHFj2X777eWkk06SAw44wEud9913n2y88cayzTbbeFm/UldKg1Nvv/22e9ZstNFGsummmy5xi6efflruuusuGT9+vAtkrbfeerLffvvJkUce6f47TenVV1+VMWPGuIDq5MmTZebMmTJ37lxp3ry5e9Zusskmzvaqb9lll02NtB9//FFGjhwpr732mowbN06mTJkis2bNctq03+k7Yu2115a//e1v0r59e/euWHXVVVOjr64VZSxTV4JcD4HCCdDvCmdWqivwIf5HEh+iVK2qMuXgQ1SGcynugg+BD1GKduR7GWkZyxAA8b0lUb9UEBg0aJAcc8wxUq9ePa8nnh988EEZNmyYTJgwwU2St27dWg455JBYk6yfffaZCx74Mrn+7LPPyr/+9S95//33XRtZeeWV5cwzz5RzzjmnanL83//+t1x88cXy559/VmtHyy23nNx4443Ss2fPVLSvuJWMnBdth9FketxrfcunE65quzvuuENmz55drXpNmjSRXr16Sb9+/bwNZD3//PPyf//3f6J1HT169BIT4DpJ3rlzZ/nqq6+ctsWLF1fTqDbUtM8++7gASdOmTb0ykT4HtI4bbrihm+DXvqQTx9aSBuDOOussF6jKfI5ogOqee+5x+jX17t1brr322qzyNVjw1FNPec9nwYIFcsstt8iVV14p06dPr6Ylap9Ru4x+1KBBjx495LLLLnPPYF/Td999JxdccIFo4C7z2Viz32n9MzVqOz/iiCPk0ksvdcFX6yktYxnrdkBfWATS0u/wIf5ql/gQ/vdPfAh8CB9aKT7EX1bAh8CH8KE/RnUgAOKTNahLagmo83L00Ue7iRMfJ55/++039yWrfvWaLekX9dEX3bmMEAVAfNB4//33O976Qs2cwNK66USs2kMnJ3WSPFfSia0HHnhAunfv7mW7U3sUmvQL9dtuu821w4EDBy5xuU7k+ZD0y3jlr0GsDTbYYIkqTZs2TTp16uS+0M42QRlNUmoA74UXXpA11ljDB1nV6nD66afLzTffLF26dHErkDKTfgn0j3/8w61qUX0NGzZ0q1o0gKDPDw1Qfvjhh27CXW2pQRD9at2npPaL7BD926FDBxcMOfDAA70L2BTLTldUDR06NGuAStvx2LFj5YknnpCjjjqq6harrbaaaDDh559/rvrblltu6VaQNGjQoNiqlPW6H374wa3m0NVWuYICuopF26qumMhM2kZ12zYN1O22225lrWcxhb/33ntOmwZ1MrXpyhXtcxpcVF26ukeDrboq5Pfff6+6lerTVSCjRo1y/dRy8n0sY5k92sIl4Hu/w4dYsm3iQyTXX/Eh8CGSa32F3Rkf4i9eOo7Gh8CHKKz3lC83AZDysaXkgAj47rzstddebrI5Svql7vz586smefTFpF/yatCgW7duWS3nSwBEJ4114lsnqnQbpI4dO7oJrJdeekl++eUX95J95pln3ISkTkCeccYZ7kv7VVZZxU0462SmrirQiWadtNPJZv2ay7cUfWFfaL1yfWXh0+qkSNsnn3zittKpmXbccUd5/fXX3Z9XWmklF6TSfKpNt+TRlS4aRFBNOumutvcttW3b1gUxdOXAcccdV616Z599tlx33XWu/vrb5ZdfvsS5H19//bWcfPLJrt9qvscee8wFMX1JkQ21btHKiOjLeV310rVrV/flvPbPtKbnnntO9txzT8dfnxEadG3VqpV7Ztx7773y66+/ulVKOvGvwbrDDz/c2XLNNdd0kj/99FPRQJiuANIyNOCqzpBvSZ+F2223nQt+aNKtn1S3BnJ04uuVV16RJ5980v3Wv39/1y51yzYNqD/00EPu/2tq1KiRW+my8847eyNR3wF///vfRYOqmvbYYw/3btDnxuqrr56znt9//73bAkztHL07dQWIPrNybbfojeg6VMT3sUwdpHEpBLwl4Hu/w4fAh8CHqOzjAx8CHwIforJ9Ltvd8CEKs4HvY5lIDQGQwuxKbghkJeBzh9cJqX333ddNwOnElq4QiPav1wla3brk0Ucfdbp0UlO3htIJrprJlwCIbnuk25FowEYnFtu1a+eqql8wq76JEyfKuuuu677i1YmrXXbZZQktGgTRSXVlol/p61kLvqVogjnXCohC6+vDyp2ozrUFQB5//HG3JZvWV1eBaLCj5hkD+nX2wQcfLLrNVBTw2n333QtFUtb8Ormq5w1oMK5m3XSCXCdYNUCQbaVOVDFdOr3DDjvIO++844IfGgTxJUU21ElinRTWVVlvvfVWVfWiYIhq1cCA/k8Dl2lKGqzQ9qfBUw0OZG7x9e2337rVAHp2hK6IyGUfXVWgjqwGSHyzYWSLO++8U0444QS3OkXPMNFVPDWTBjt0JZJq1bNOtG9G6ZFHHnGBPO2XegaWBik1COZDuuiii+SSSy5xwXLdvuWggw4quFqqT7f50kCRbqOlZVpNPo9lrDJHFwR87nf4EPgQ2kPxISr7nMKH+GsLL3wIfIjK9rzqd8OHKIy+z2OZTCUEQAqzK7mNEdh1111LokgnM3VPf58GiJEwnejXCX+dfNTzMvQr3ZpJAyB6honumaoa9OyMPn36VMvmSwBEgxw60Xrssce6lRyZKZrIUw36le/dd9+d0746macTebo1ik66+5aiCWbdekXPkojz1bFusaMrDlS/ruapmbJNbCahu7YASNRedSJV21yusy90IlYDeToRrbqy6U1CW3RP7We6DZJuv7PFFltUVUWDIvplvdpIv+7Rw5ZrSzr5quf06DZf0UHwSeqK7p3NhnqeiQ5+dKL5m2++cVkzz1PQQID2S7Wxrr7yPelqD9Vx1VVXyT//+c8lqqtnfuiZQ6pRAwS6iiJb0ufUiSee6IIDEReftOt7UANZxx9/vAuQ50p6Pshpp50mev5Jze0U9dmjK7c0SKBB9FNOOcULidr3NEB37rnnyhVXXFF0nc477zx3NoquJtEPB3xLIYxlfGNOfSAQQr/Dh8jezvEhkuv/+BD4EPgQyfW/mnfGh8hvC3yI/IwqmYMASCVpcy/vCBS7zVA2Ifqlvo8BkPXXX18mTZok//nPf2o9E0MDOHvvvbeboFMdNSeMfAmA6PZdutWVnqugW1tlJq276tX6Z/s9M69ubaJBH10toqtGfEu33nqrnH/++e6rag2CXHPNNe4r5NpSWg5Br815idqrbiWkgZ/akm7Ho4w0iKDt06e01lpriR68rF9P6rY7UdIgwUYbbeTaqK4O0D1Ra0sffPCBW0GwzDLLyB9//OGNxHzbmOm2SXqOzbBhw6pttacC9Gt8fdboChhdnZaPQVKiNfimzHWLNd0yqWbSoIGuMFNbakBOV6VlS7qCZ5tttnHB5zlz5iQlJ+d9NbimK+h0y6/atizTMzQ0r+rVrbGaNWtWrUxdBaJBZ2Xy4osveqFTty5T22h71OB5sUm35NMAT/PmzZ1231IIYxnfmFMfCITQ7/AhsrdzfIjk+j8+BD4EPkRy/a/mnfEh8tsCHyI/o0rmIABSSdrcyzsClrcZimBHk3h6WK9OpNaWosOndQsTneTSraF0iyhNvgRAdCJYvzLWL45rHkir55roJKPWXbes0YOmc6U333zTTYjpJF7mgbc+NVKdQNcvqUeMGOE06cSifqG94YYbZq2mhQBI1F5ffvll2WmnnWo1RzQBrZOcGhTzKelh0KpBVwgMGDCgqmo6Gatbeqk9dfVKvgPco3MoNAimK818SfkCIFE9Ncij7VeDIapF+66maGWIfsWlW03pFlnRdna+aNSAhj5TXn31VbfqoWZ644033BZlqkW3wtJnU7akK+/0WaUHbWs+35LWS7dbq7laqWY9NY9qVL1ffPGFbLDBBtWy6GHwus2XT6uVll9+ebeyMZQAiMUtE33rL9QHAhEBfIjqbQEfwq++gQ+BD4EPkVyfxIeozh4fwv+PqELxIQiAJPdc5M4eEIj24tevkOuyDZLPe97pXuw6CamTdfoVcr6kE8n6xboGEHSiS7/S1u2FNCjSpk2bxFe56KHYevhwri1n4k7Mfvzxx25rIt++rM9mH22bp556qtsCSScrdXWOrnzQ/5+ZLARANCClk8S68kG3m6kt6eHLGuTSFQXaxn1K0XZBGuzQ8x8yAx3RNm4aGNEASW1J+58enq0HS/t02HvcfpapTVcZqBY9LyQ6OFt/1+eMTwdsRnXWLau0z2nQUbeHqpmira207hrk2HzzzbOaUg8K79mzp1eBgcyKRl9v6WodPX8nV8pcvaQTXbqVW2bycbVStAWWribTVWXFJt0SUvurvgMz226x5ZX6uhDGMqVmRnkQqCuBEPodPkT2VoIPUdfeU/z1tY0/8SGqc8WHKL6d1fVKfIjqBPEh8CHq2qdKdT0BkFKRpJxUEtDJHp1c1sPGdEKn2ORzACRavq6TcHqWQJykX6lrUEi/mtXJPT04VieAttxyy8QDIBtvvLHoS1TPRujatesScuJOzOpX3bqtjTqwemC670ltontI6hkfGqHX8wl0kj3zgG0LARCdRNazMfSAe91yprYULSnVQ6p1ex6fkm51tMkmm7i2pf/qAebRF/N6MLou39bVShoQyNaOVYueOaA21z6odtcthnxJcftZrvqqjXULicGDB7utwnzcPjB6P+gzVCc7Mg/2VvtqW508ebJbPdGrVy+3zWC2pCuZtK3qweF67pBvSZ/1ulWb1k/bZq6k56Bcf/31otsQajCrZtKgtGr1abVSv3795NJLL3VBUm1rufpabTbR7RR1H3xdvfSvf/1LLr74Yt9M6AJX1scy3kGnQsETCKHf4UNkb+b4EMl1/9rGn/gQ/7MLPkRybVTvjA9RnT8+BD5Esj3yf3cnAOKLJahHIgT0i1Cd0NDJNz0nQ/ftLyb5HADRF/DIkSPzHnBbU7fufa+TRTohpnw222wzd5hs0hOVOuGvX8JfffXVctZZZy1hLt0WSdPWW2+dc09+/f2uu+5yTDSoo6td0pJ06y+dCNcJZLVFt27d5LrrrnNBvLQFQPQMF92iJjOp/fQsF916Tbdgqy3ptkp6qLaPZ4BovXULLD0oU1en6Gqdww47zAUT9bDsO++8s+qMk2233Vb22msv9/zRSdYJEya4baN0myENdun2SW+99Zao0+dLqmsAJNLx559/uq2xNBCk//MpRQfQaz/TSaAzzzzT/atnBt1www3OTjqg15UTGgjRiXFdaaCT7Zp0az39XVfQaRkasNTD0H1Lemi9bkGmddRzkfRwdz3rIkoa4NEziHTVmaZjjz1WdPVLzRStetJVF7oixof0888/u3eXbh+n+vbcc0/3zNDgtwZqciUN8OizaODAgfLss8+6fqgrZfQd6OPhmyGMZXxoT9QBApkEQuh3+BDZ2zw+RHLPgmj8iQ/x1zmJ+BD4EMn1RhF8iCXp40PUq9ryOsm2meveBEB8tAp1qhiBF154wX31qhMj+bb/qK1SPgdA9ItdnYTTraN0lUs0ORcHsk586f78jz76qGPkw0HvOgmnh19rvfSlW2zSZcF6/ZFHHukmKNOU1C76Zc+///1vN7mu2yzp/19hhRXcVjtJB6nysYxzcKieJaCrJmpLGsBSJ7RLly7u0Hsfkz5jtK3+9NNPVedeaD313BJdRaBnTETnYdSsv/Y3DdDp2Qoa4PIplSoA4pOmbHXRc3d0IrymjdQ2+kzVbZ+GDh3qtjLTPBo40BU/2kc1SKn9U/Nq4EQnz3MdlJ4kBw1C6bZsGlxVDXoOjwbpdIsrPfBbg28zZsxwOvRZ8+GHH8q66667RJWjrd1OPvlkuemmm5KUVO3eegi9Pk90lVimHbUPatBRt8zQrRC1L+pKOz2bJ/Ogc9Wtq8xGjRrlAus+phDGMj5yp05hEwih3+FDZG/j+BDJ9X18CHyI5FpfYXfGh8CHwIcorM9UIjcBkEpQ5h7eEtBJDv1aVdNpp53mAgXFJN0TXL/Y1qRbbviU/vvf/0rr1q3dxI9+tatf7xaSdHJMt3fR7Wo0JT25rpx1ZYpOzunWOcUk/TJbJ75mz57tdOnXz2lMuhWYflGuK2LULrqaQs9wSdpG+Vjq5GmuSf/oWl0xMXbsWDfhmi3pCiW1oerVgFjv3r3z3Tax33XyWLey0i14Mg/BjhhkO3RMJ1x1Uv30009f4qyXxIRk3DiUAIg+K3T7o5pbQ2kb1gCqBgo06UosDaJHz0j9N7KrrjTQVS75zrRJ0q66QkK3ZdPgRqaGTB3aF3VVTOa2e1Gddas3vV6TrhbRDwt8Shr81+C52kxXWUUp23Mosz9qO+/Ro4dcdtllRa8QrQSHEMYyleDIPSBQCIEQ+h0+xJItAh+ikF5S+rz4EH8xxYcofdsqdYn4EP/zhfAhittlptRtMlt5IYxlMnUTAKlEq+IeEEiYgK5y0Amgtddeu+jVDmeffXbVV/Zff/11Yor0K93ozA49B6OYNGTIkKr9+vVslMwDqospL+lrNIijAQBdZRANijMn+ZKuXznur9vSaOBDk0646koJ35MOMPQrcv2i/vPPPxfdnkeDcHoWiK4c0P656aabunMU9H8+bXlVk61uI6TOl24Bkvb+E6fd6JZOeo6HPn822mgj2WOPPdyqgSjppLluAaWryfTQ+6WWWkrWW2892W+//apW4MW5T5J5NKioW8/p1nK6eiVKal/dakKDeHqoY5qTLkvXLSF1/3a1k75LZs6cKao96ocaWNVVPDvssINbOVLzsPc066fuEIAABAolgA9RnRg+RKEtyL/8+BDJ2gQfAh8i2RZY3N3xIYrj5ttVBEB8swj1gQAEIFAEAV1loNtB6ZY7mnxbiVSEJC6BAAQSIqABAV1dpdth5VqFlVDVuC0EIAABCEAAAiUkgA9RQpgUBYHACeBDBN4APJdPAMRzA1E9CEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAECidAAKRwZlwBAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEICA5wQIgHhuIKqXDAE9P+HLL790+4PPmjXLHVzcuHFjadasmdunf4MNNnB7vKc5WdNoTU+utmVZp2VtkT2ta7SuT+0YgsaQdKb5PU7dIQAB/wiE8I6wptGaHnwIfHf/noz5axRCPwxBIz5E/rZOjuQIEABJjj139ozA77//Lnfffbc76Hvs2LGycOHCnDXU4Ee7du2ka9eucuyxx8pyyy3nmZrs1bGm0ZqeXI3Isk7L2iJ7WtdoXZ/aMQSNIeks9IX90UcfyeOPP+4uu/DCCwu9PDX5Q9GZGoNQ0dQQCOEdYU2jNT34EPjuaZyfCKEfhqARHyL3cCWUsXVadBIASc3QmoqWk8A999wj5557rjv0VdPixYvz3q5evXouz/LLLy8DBgyQXr165b0myQzWNFrTk6ttWNZpWVtkT+saretTO4agMSSdxbyHBw0aJEcffbToe1+/3rOaQtFp1X7oSoZACO8Iaxqt6cGHwHeP2kCa5idC6IchaMSHqH3sEcrYOi06CYAkM1bmrh4R+Pe//y39+vWrCnosu+yysu2220rr1q3ddldNmzaVhg0byrx582T27NluW6zx48fLW2+95b4K1qSDjYsuukguuOACj5T9ryrWNFrTk6vRWNZpWVtkT+saretTO4agMSSdxb6g0zKoL1ZfdF0oOuvKieshEMp73uL7gfd6+v3bEGxoXaN1fRafnSHOV5RitBPK2DotOgmAlKJVU0ZqCbz99tvSvn17+fPPP6Vly5ZuJYdua7X00kvn1bRgwQJ59NFH5bzzzpPJkydLgwYN5LXXXpNtttkm77WVzGBNozU9udqCZZ2WtUX2tK7Ruj61YwgaQ9JZl/duWgb1ddGo14ais66cuB4CoTw7rb0HrenBh8B3r9kG0jA/EUI/DEFjKO/Buo54Qhlbp0UnAZC6tmiuTzWBI444Qh544AF3qPmbb74pK620UsF6ZsyYIdttt51MnDhRevToIffdd1/BZZTzAmsarenJZXvLOi1ri+xpXaN1fWrHEDRa16kfJ5QiPfLII9K7d29vt8AKRWcpbEkZECgVgRDeEdY0WtODD4HvnqsN+Dw/EUI/DEEjPkS80QQ+RDxOlcpFAKRSpLmPlwTWW289t3pDDz8/6qijiq7jwIED3WHouorkm2++KbqcclxoTaM1PblsblmnZW2RPa1rtK5P7RiCRus669ev74IWpUh6NpivZ4CEorMUdqQMCJSKQAjvCGsarenBh8B3r+155uv8RAj9MASN+BDxRxP4EPFZlTsnAZByE6Z8rwk0btxY5s+fL2PHjpW2bdsWXdf33ntP2rVr584KmTt3btHllONCaxqt6cllc8s6LWuL7Gldo3V9ascQNFrXqYGBUiafAyAh6CylRsqCQF0JhPCOsKbRmh58CHz32p5jvs5PhNAPQ9CID1HYKAIfojBe5cpNAKRcZCk3FQRatGgh06dPlxEjRsh+++1XdJ1HjRolnTt3ltVWW02+++67osspx4XWNFrTk8vmlnVa1hbZ07pG6/rUjiFotK5Tz/PSM75atWrlzvsqNn311Vfy+uuve7sCJBSdxdqP6yBQDgIhvCOsabSmBx8C3722Z5uv8xMh9MMQNOJDxBtZ4EPE41SpXARAKkWa+3hJYM8995TnnntOOnbs6P4tZqsMnVzZfffdZfTo0e7fZ555xiut1jRa05OrsVjWaVlbZE/rGq3rUzuGoNG6zs0331w+/fRT2XbbbV0Ao9jk+8F+oegs1n5cB4FyEAjhHWFNozU9+BD47rnagM/zEyH0wxA04kPEG1ngQ8TjVKlcBEAqRZr7eElgyJAhcthhh7nAx/777y+33HKL++o3bpo2bZqccsop8vjjj7syHnzwQenevXvcyyuSz5pGa3pyNQLLOi1ri+xpXaN1fWrHEDRa13nccce5M750K4KZM2dKsVti+e68hKKzIoMmbgKBmARCeEdY02hNDz4Evnu2NuD7/EQI/TAEjfgQ8QYL+BDxOFUqFwGQSpHmPt4S0K2vnnzySRfAaNCggVvF0aFDB2ndurWstdZa0qxZM1lmmWXcWSGzZs2Sb7/9VsaPHy9jxoyRF154QRYuXCh6sNE+++wjutTUx2RNozU9udqMZZ2WtUX2tK7Ruj61YwgaLeu844475MQTT3Tvd90Le4sttijqFe278xKKzqKMx0UQKCOBEN4R1jRa04MPge+exvmJEPphCBrxIfIPMPAh8jOqZA4CIJWkzb28JDBv3jw55phjZPDgwa5+hWyDpYEPTbrq45577pFGjRqhsQIEQrCZYrSs07K2qAtY12hdn/U+mPmotmrLDz/8ULbcckv3Xr/99ttFV0oUk3x3XkLRWYztuAYC5SRg9dlp+f0Qgs2sj19CsKF1jdb1We+Dlt8RkbZQxtah6IzsSgCknKNiyk4VAV3RceWVV8pLL73kJp7zJV0VomeHnHPOObLLLrvky+7F79Y0WtOTq5FY1mlZW2RP6xqt61M7hqDRos5FixbJZZdd5lZpbr/99m6FZzFp9uzZMmPGDHfpOuusU0wRZb0mFJ1lhUjhEKgDgRDeEdY0WtODD4Hvrm0gbfMTIfTDEDTiQ+QeQOBD1GFwVYZLCYCUASpFppuAPqTGjh0r48aNkylTprh9w//44w+3uqN58+ZuW6xNNtlE2rVr57bHSmOyptGanlxtyrJOy9oie1rXaF2f2jEEjSHpTOP7mzpDAAL+EgjhHWFNozU9+BD47mmcnwihH4agER/C3/EJNfuLAAEQWgIEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAALmCBAAMWdSBEEAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIEAAhDYAgZgEdI/tqVOnutwtW7aMeVW6slnTaE1PrtZkWadlbZE9rWu0rk/tGIJG6zqxYbrGK9QWAmkiEMLzxZpGa3rwIfDd0/TMDMVHsj62zmxzlp+plrVZsyEBkDS+CahzIgQ+++wzadOmjdSvX18WLlyYSB3KfVNrGq3pyWV/yzota4vsaV2jdX1qxxA0WteJDcs9wqB8CIRLIITnizWNtKhseAAAIABJREFU1vTgQ+C7p/EJHEI/DEEjPkQae9+SdbbQVgmA2GiLqKgAgajD16tXz33tazFZ02hNTz7nxWLbDMGG1jVa15c5qLfYBzOfO5ZtaVlbKDa0OC5Dkw0CITxfrGm0pgcfAt89jU/TEPphCBqt+0rYMD1PFwIg6bEVNU2YQAgPNmsarenBecF5SfgxWNTtQ+iHIWjEeSmq+Xt3USht1TvwVChoAiH0O2sarenBh8CHSONDOIR+GIJGfIg09r4l62yhrRIAsdEWUVEBAhY6fD5M1jRa04PzgvOSrw/7+HsI/TAEjTgvPvauwusUSlstnAxXQKB8BELod9Y0WtODD4EPUb4nXPlKDqEfhqARH6J8faSSJVtoqwRAKtliuFeqCVjo8PkMYE2jNT04Lzgv+fqwj7+H0A9D0Ijz4mPvKrxOobTVwslwBQTKRyCEfmdNozU9+BD4EOV7wpWv5BD6YQga8SHK10cqWbKFtkoApJIthnulmoCFDp/PANY0WtOD84Lzkq8P+/h7CP0wBI04Lz72rsLrFEpbLZwMV0CgfARC6HfWNFrTgw+BD1G+J1z5Sg6hH4agER+ifH2kkiVbaKsEQCrZYrhXqglY6PD5DGBNozU9OC84L/n6sI+/h9APQ9CI8+Jj7yq8TqG01cLJcAUEykcghH5nTaM1PfgQ+BDle8KVr+QQ+mEIGvEhytdHKlmyhbZKAKSSLYZ7pZrAwoULZerUqU7DOuusk2otuSpvTaM1PaHYLVNnCDa0rtG6Pm2vIWi0rhMbmhzWIAoCXhAI4fliTaM1PfgQ+O5ePAwLrEQI/TAEjfgQBTZ8T7NbaKsEQDxtXFQLAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACB4gkQACmeHVdCAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCDgKQECIJ4ahmpBAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQPAECIMWz40oIVBF49NFHpXfv3lKvXj2ZMGGCSTLWNFrTk6vRWdZpWVtkT+saretTO4ag0bpObGhyWIMoCHhBIITnizWN1vTgQ+C7e/EwLLASIfTDEDTiQxTY8D3Nnpa2SgDE0wZEtdJFYNCgQXL00Ue7AMiiRYvSVfmYtbWm0ZqeXGa0rNOytsie1jVa16d2DEGjdZ3YMOZAgWwQgEDBBEJ4vljTaE0PPgS+e8EPLg8uCKEfhqARH8KDzlSCKqSlrRIAKYGxKQICaenwdbGUNY3W9OC84LzUpX8ndW0I/TAEjTgvSfWg0t43lLZaWmqUBoG6EQih31nTaE0PPgQ+RN2eYslcHUI/DEEjPkQy/afUd01LWyUAUmrLU16QBNLS4etiHGsarenBecF5qUv/TuraEPphCBpxXpLqQaW9byhttbTUKA0CdSMQQr+zptGaHnwIfIi6PcWSuTqEfhiCRnyIZPpPqe+alrZKAKTUlqe8VBG45JJLSlLfDz/8UEaMGOHlFljWNFrTk6sBWtZpWVtkT+saretTO4ag0bpObFjYEMfnsUxhSsgNgfITCOH5Yk2jNT34EMX3c5/fd9bbqXV91sfWmb3Osi0tawvFhtneEARAin9vcqUBAvXr13dBi1KkxYsXexkAsabRmp5cbc+yTsvaInta12hdn9oxBI3WdWLDwkc3vo5lClfCFRAoL4EQni/WNFrTgw9Rtz7u6/vOeju1rs/62Dqz11m2pWVtodiQAEjd3pFcbZBA9GDTAVApko+HoFvTaE1PPufFYtsMwYbWNVrXl+m8WOyD2Qa+FnWG0E5DaqulGKdRBgRKRSCE54s1jdb04EPUvTfju9edYaElhNAPQ9BoffyJDQvt2X/l9/GZmqmEFSDF2ZWrjBBYbrnlZNasWbLTTjvJRRddVLSqZ555RgYMGOBlh7em0ZqeXI3Osk7L2iJ7WtdoXZ/aMQSN1nViw8KGNT6PZQpTQm4IlJ9ACM8Xaxqt6cGHwHev7Unn6zs9hH4YgkZ8iHjjDF/7YShzFjWtRAAkXrsll1ECHTt2lJdfflk23HBD+eKLL4pW6fOhP9Y0WtOTq9FZ1mlZW2RP6xqt61M7hqDRuk5sWNiwxuexTGFKyA2B8hMI4fliTaM1PfgQ+O61Pel8faeH0A9D0IgPEW+c4Ws/DGXOggBIvHZKrkAI9OnTx63c0CVuP/30k/vit5jk84PNmkZrenK1N8s6LWuL7Gldo3V9ascQNFrXiQ0LG9H4PJYpTAm5IVB+AiE8X6xptKYHHwLfPY0BkBD6YQga8SHijTN8H1uH0lYja7ECJF67JZdRAsOHD5eDDjrIbV317LPPym677VaUUp8fbNY0WtOTq8FZ1mlZW2RP6xqt61M7hqDRuk5sWNiQxuexTGFKyA2B8hMI4fliTaM1PfgQ+O5pDICE0A9D0IgPEW+c4fvYOpS2SgAkXnsll3EC3377rbRs2dKpvOyyy9wXv8UkDZ7079/fXapbavmUrGm0pidXW7Gs07K2yJ7WNVrXp3YMQaN1ndiwsNGIz2OZwpSQGwLlJxDC88WaRmt68CHw3Wt70vn6Tg+hH4agER8i3jjD134YypxFTSuxAiReuyWXYQKTJ0+WxYsXS/PmzWXFFVc0qdSaRmt6cjU6yzota4vsaV2jdX1qxxA0WteJDU0OaxAFAS8IhPB8sabRmh58CHx3Lx6GBVYihH4YgkZ8iAIbvqfZQ2mrip8AiKeNkGpBAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBQPAECIMWz40oIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQ8JUAAxFPDUC0IQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAASKJ0AApHh2XAkBCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgICnBAiAeGoYqpUuAosWLZKpU6e6Srds2TJdlY9ZW2sarenJZUbLOi1ri+xpXaN1fWrHEDRa14kNYw4UyAYBCBRMIITnizWN1vTgQ+C7F/zg8uCCEPphCBrxITzoTCWoQlraKgGQEhibItJPYM6cOXLdddfJsGHDZMKECVK/fn1p3bq1HHLIIXLSSSdJo0aNahX52WefSZs2bdx1Cxcu9BKINY3W9ORqNJZ1WtYW2dO6Ruv61I4haLSuExvaGct4OcCiUkETCOH5Yk2jNT34EPju2dqA7/MTIfTDEDTiQ6R/ntC6DTOfjwRAgh6yI14JTJkyRXbffXf58ssvHZDFixe7f+vVq+f+XXvttWXQoEHSoUOHnMCiAYZeo9FP35I1jdb05GovlnVa1hbZ07pG6/pCeT9Y1xlCO7VuQ9/GVNQHAqG85y0+W3gnpN+/DcGG1jVa12fx2cl8hc15wpDaqpvjXRzN9jKWhUCABDRYsd1228m7777r1C+zzDLy97//XebNmyfjxo2rWs2hKzuuuOIK6d27d1ZKPgdArGm0pidXt7Os07K2yJ7WNVrXp3YMQaN1ndjQzlgmwCEqkj0nEMLzxZpGa3rwIfDd0zg/EUI/DEEjPsRfu76keZ7Qug2zvSMJgHg+uKZ65SUwZMgQOeyww9xqj4MPPlhuvfVWWXHFFd1Nf/zxR7nyyivlhhtucIEQzXP22We7v9VMPgdArGm0pidXC7es07K2yJ7WNVrXp3YMQaN1ndjQzlimvKNBSodA4QRCeL5Y02hNDz4Evnsa5ydC6IchaMSHSP88oXUbEgApfGzLFcYJdOnSRUaOHClbb721vPnmm1XbXmXKfvvtt11w5Ntvv3W/H3fccXL77bdXI+NzAMSaRmt6cnUxyzota4vsaV2jdX1qxxA0WteJDf/3hkn7WMb4cBR5KSQQwvPFmkZrevAh8N3TOD8RQj8MQSM+hIiFsXUobTV6X7ICJIUDbqpcOgJ6vse0adPk/vvvdytBcqXp06fLPvvsI++//74LgnTv3l3uu+8+adCggbvE5wCINY3W9ORqc5Z1WtYW2dO6Ruv61I4haLSuExtWf8OkeSxTupEfJUGgNARCeL5Y02hNDz4Evnsa5ydC6IchaMSH+OsJnPaxdShtlQBIaca+lJJyAo0bN5b58+e7M0D+8Y9/1Kpm1qxZsv/++8vo0aNdEGS//faTRx55RJZeemmvAyDWNFrTk6vRWdZpWVtkT+saretTO4ag0bpObLjkGyatY5mUDzepvkECITxfrGm0pgcfAt89je/0EPphCBrxIf73BE5jPwxlzqLme5IVIAYH5EiKT6BZs2Yyd+5cee2119xh6PmSHo6u22E98cQTLgiy2267yYgRI2TixInSpk0b9zc99MqnZE2jNT252oplnZa1Rfa0rtG6PrVjCBqt68SG2d8waRzL+DSuoi4QsP7stDqW4Z2Q/ndCCDa0rtG6vlDeD9Z1htBOrdsw2xuPAAhj+KAJtG7dWr788ksZOHCgHHHEEbFYaICjZ8+e8vDDD7uAR/v27WXAgAHuXx8DINY0WtOTq9FZ1mlZW2RP6xqt61M7hqDRuk5smHtYk7axTKwBGpkgUEECITxfrGm0pgcfAt89agNpeqeH0A9D0IgPseQTOE39MJQ5i5pWIgBSwYEyt/KPgJ7lMXToUBf8uPfee2NXcPHixXL88cfL3Xff7YIea665ZtUh6b6tALGm0ZqeXI3Osk7L2iJ7WtdoXZ/aMQSN1nViw9qHNWkay8QeoJERAhUiEMLzxZpGa3rwIfDdM9tAWt7pIfTDEDTiQ2R/AqelH4YyZ0EApEKDYm6TDgK33367nHzyyW6rk++++06aNm1aUMX/+c9/yvXXX++CIPqw83EFiDWN1vTkanCWdVrWFtnTukbr+tSOIWi0rhMbxhvSpGEsE08JuSBQOQIhPF+sabSmBx8C3z1bG/D9nR5CPwxBIz5E7eMN3/thKHMWBEAqNy7mTikgMGXKFFl33XVdTXUbq3POOafgWl900UVyySWXuOt8DIBY02hNT64GZ1mnZW2RPa1rtK5P7RiCRus6sWH8IY3vY5n4SsgJgcoQCOH5Yk2jNT34EPjuudqAz+/0EPphCBrxIfKPNXzuh6HMWRAAyd9OyREYgX79+sm0adNk5ZVXliuuuKIo9TfddJMMHz7cXfvyyy8XVUY5L7Km0ZqeXLa3rNOytsie1jVa16d2DEGjdZ3YMP7owvexTHwl5IRAZQiE8HyxptGaHnwIfPdcbcDnd3oI/TAEjfgQ+ccaPvfDUOYsMq3EGSD52yw5IAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQSBkBAiApMxjVhQAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAID8BAiD5GZEDAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBlBEgAJIyg1HdyhCYNGmSjBs3zh2CO2vWLJk7d640btxYmjVrJmuvvbb87W9/k3XWWacylSnTXaxptKYnl9kt67SsLbKndY3W9akdQ9BoXSc2tDOWKdMQiWIhUDSBEJ4v1jRa04MPge9e9AMswQtD6IchaMSHSP88oWUbEgBJ8CHPrf0i8PXXX8v1118vI0aMkG+//TZv5dZcc03p0qWLnHHGGdKqVau8+X3IYE2jNT252ohlnZa1Rfa0rtG6PrVjCBqt68SG2d8waRzL+DCeog4QyCQQwvPFmkZrevAh8N21DaTtnR5CPwxBIz5E9Sdw2vphKHMWqpMACON3CIjIhRdeKAMGDJCFCxfK4sWLYzOpV6+eLLXUUnLuuefKpZdeGvu6JDJa02hNT642YVmnZW2RPa1rtK5P7RiCRus6sWHto440jWWSGD9xTwjURiCE54s1jdb04EPgu2e2gbS800PohyFoxIfI/gROSz8MZc4i0kkAhDF98AROOukkueOOO6oCHxtvvLF06NBBWrdu7ba7atq0qTRs2FDmzZsns2fPdttijR8/Xl555RX3r4sk1qsnvXr1kv/85z9e8rSm0ZqeXI3Gsk7L2iJ7WtdoXZ/aMQSN1nViQztjGS8HWFQqaAIhPF+sabSmBx9CBN89ffMTIfTDEDTiQ6R/ntC6DWu+IwmABD1sR/yzzz4re+21lwtgtG3bVm666SbZZpttYoN566235PTTT5d3333XlfH0009Lp06dYl9fiYzWNFrTk6sNWNZpWVtkT+saretTO4ag0bpObBhvlJGGsUw8JeSCQOUIhPB8sabRmh58CHz3bG3A93d6CP0wBI34ELWPN3zvh6HMWRAAqdy4mDulgMCBBx4ojz32mGy55Zby6quvuoPOC01//PGHtG/fXj788EPp3LmzDB8+vNAiyprfmkZrenIZ37JOy9oie1rXaF2f2jEEjdZ1YsP4wwvfxzLxlZATApUhEMLzxZpGa3rwIfDdc7UBn9/pIfTDEDTiQ+Qfa/jcD0OZsyAAkr+dkiMgArrF1bRp02Tw4MHSrVu3opUPHTpUunfv7g4e0y2yfErWNFrTk6utWNZpWVtkT+saretTO4ag0bpObFjYaMTnsUxhSsgNgfITCOH5Yk2jNT34EPjutT3pfH2nh9APQ9CIDxFvnOFrPwxlzoIASLx2Sq5ACDRq1EgWLFggY8eOdVtgFZvee+89adeunTsrZO7cucUWU5brrGm0pieX0S3rtKwtsqd1jdb1qR1D0GhdJzYsbFjh81imMCXkhkD5CYTwfLGm0ZoefAh899qedL6+00PohyFoxIeIN87wtR+GMmdBACReOyVXIARCiM5b02hND19v8fUWX2+xei7JV67lZ6plbZltJhSdSfYT7g2BmgRC6HfWNFrTgw+BD4EPgQ+R5NvZ8jPVsraQfQgOQU/yicG9EycQ7c+oqz9ee+01t4Kj0OT73n7WNFrTk6u9WdZpWVtkT+saretTO4ag0bpObBh/ROP7WCa+EnJCoDIEQni+WNNoTQ8+BL57rjbg8zs9hH4YgkZ8iPxjDZ/7YShzFjWtRAAkf7slh2ECzzzzjOy9995Sr149t4XVTTfd5P6Nm3TrrNNOO03eeecdV8aTTz4pe+65Z9zLK5LPmkZrenI1Ass6LWuL7Gldo3V9ascQNFrXiQ3jDTPSMJaJp4RcEKgcgRCeL9Y0WtODD4Hvnq0N+P5OD6EfhqARH6L28Ybv/TCUOQsCIJUbF3OnlBA44YQT5M4773QBDE2tW7eWDh06uH/XWmstadasmSyzzDIyf/58mTVrlnz77bcyfvx4GTNmjPtX0+LFi+XYY4915fiYrGm0pidXm7Gs07K2yJ7WNVrXp3YMQaN1ndjQzljGx/EVdQqbQAjPF2sarenBh8B3T+P8RAj9MASN+BDpnye0bkMCIGGP01Gfg0Dfvn3lqquukoULF1YFQuLA0sDHUkstJeecc45cdtllBV0bp/xS5rGm0ZqeXLa2rNOytsie1jVa16d2DEGjdZ3YsPbRRJrGMqUcF1EWBEpBIITnizWN1vTgQ/z1EWOclKb3nfV2al2f9bF1Zn+zbEvL2kKxYaZOtsCK86YkTxAEJkyYINdee62MHDlSpk6dmldzixYtpHPnznLmmWfKhhtumDe/DxmsabSmJ1cbsazTsrbIntY1WtendgxBo3Wd2DD7GyaNYxkfxlPUAQKZBEJ4vljTaE0PPgS+u7aBtL3TQ+iHIWjEh6j+BE5bPwxlzkJ1EgBh/A6BLAS+/vprGTdunEyZMkVmzpwpeoBRo0aNpHnz5m5brE022UTWW2+9VLOzptGanlyNy7JOy9oie1rXaF2f2jEEjdZ1YkM7Y5lUD8SovEkCITxfrGm0pgcfAt89jQ/XEPphCBrxIdI/T2jZhgRA0vh2oM4QgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQjUSoAACA0EAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABcwQIgJgzKYIgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhAgAEIbgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAwBwBAiDmTIqgYgm8/vrrMmzYMJkwYYLUr19fWrduLd26dZMtt9wyb5Fffvml7LHHHlKvXj13va/JmkZrenK1G8s6LWuL7Gldo3V9ascQNFrXiQ3tjGV8HWNRr3AJhPB8sabRmh58CHz3mm0gDfMTIfTDEDTiQ+Qe/6ShH4YyZ6E6CYCEO1ZH+f8nsGDBAjn66KNl8ODBWZl07dpVbr31VllllVVyMvvss8+kTZs2LgCyaNEi79ha02hNT64GY1mnZW2RPa1rtK5P7RiCRus6seFfTyQLYxnvBldUKHgCITxfrGm0pgcfYkkCFt531tupdX3Wx9aZvc6yLS1rC8WGNd8QBECCH7oD4Mgjj5T7778/JwgNaqy66qryyCOPyA477JA1n+8BEGsarenJ1fgs67SsLbKndY3W9akdQ9BoXSc2/OuJZGEsw4gVAr4RCOH5Yk2jNT34EEsSsPC+s95OreuzPrbO7HWWbWlZWyg2JADi28iZ+iRK4LXXXpOddtrJTQxsuOGGcs0118jOO+8s8+fPl9GjR8uAAQNk7Nixro6NGjWSIUOGyP77779EnX0OgFjTaE1Prg5gWadlbZE9rWu0rk/tGIJG6zqxoZ2xTKKDRW4OgSwEQni+WNNoTQ8+BL57GucnQuiHIWjEh0j/PKF1G2Z7R7IChCF90AR066tBgwbJWmutJR9++KGsuOKK1XgsXrxYrr32WunTp48sXLhQllpqKRk4cKD06NGjWj6fAyDWNFrTk6sDWtZpWVtkT+saretTO4ag0bpObPjXE8nCWCbowSrivSQQwvPFmkZrevAh8N3TOD8RQj8MQSM+RPrnCa3bkACIl8NnKpUkgY033li++uorF+Q444wzclZlzJgxbv/sX375xR2QfvPNN8uJJ55Yld/nAIg1jdb05Gp0lnVa1hbZ07pG6/rUjiFotK4TG1Z/w6R5LJPkWJF7QyAbgRCeL9Y0WtODD4Hvnsb5iRD6YQga8SH+egKnfWwdSluN3pesAGFMHzSB5s2by5w5c+TNN9+UrbfeulYWGuTYY489ZNq0aW7LLN0e65xzznHX+BwAsabRmp5cjc6yTsvaInta12hdn9oxBI3WdWLDJd8waR3LBD1YRbyXBEJ4vljTaE0PPgS+exrf6SH0wxA04kP87wmcxn4YypxFzfckARAvh9RUqlIEdN/MBQsWuHM+2rZtm/e2X3/9tey2226i/2oQ5F//+pdcfPHFXgdArGm0pidXo7Os07K2yJ7WNVrXp3YMQaN1ndgw+xsmjWOZvAM0MkCgwgRCeL5Y02hNDz4Evru2gbS900PohyFoxIeo/gROWz8MZc6CAEiFB8fczm8CLVu2lKlTp8qwYcPkgAMOiFVZXQGy++67y7hx41wQ5Mwzz5RjjjlG2rRp4/570aJFscqpVCZrGq3pydUOLOu0rC2yp3WN1vWpHUPQaF0nNsw90kjbWKZSYybuA4G4BEJ4vljTaE0PPgS+e9QG0vROD6EfhqARH2LJJ3Ca+mEocxYEQOKOaskXBIG9995bnn32WXf+h54DEjf99NNP0qlTJ/nggw9c0GPXXXeVF1980csAiDWN1vTkanOWdVrWFtnTukbr+tSOIWi0rhMb1j6qSdNYJu74jHwQqBSBEJ4v1jRa04MPge+e2QbS8k4PoR+GoBEfIvsTOC39MJQ5CwIglRoVc59UELjiiiukb9++suaaa8rkyZNdACNu+v33390E2RtvvOGuW7x4sZcBEGsarenJ1d4s67SsLbKndY3W9akdQ9BoXSc2zD+iSctYJr8SckCgsgRCeL5Y02hNDz4EvnvNNpCGd3oI/TAEjfgQucccaeiHocxZEACp7NiYu3lOQFdw6NkfGsAYOnSoHHjggQXVeO7cudKlSxd5/vnn3XU+boFlTaM1PbkanGWdlrVF9rSu0bo+tWMIGq3rxIbxhjRpGMvEU0IuCFSOQAjPF2sarenBh8B3z9YGfH+nh9APQ9CID1H7eMP3fhjKnAUBkMqNi7lTSgh06NBBdL++v/3tbzJy5MiCa62HqHfv3l0ee+wxLwMgKsiaRmt6cjU6yzota4vsaV2jdX0Wn508a2y+40NqqwUP0rgAAmUkwHswP1zf/KQQbGb9nRCCDa1rtK7Peh/MfPJbtqVlbaHYkABI/nEaOSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEEg5gXqL9eACEgQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhAwRIAAiCFjIgUCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIG/CBAAoSVAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBgjgABEHMmRRAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIEQGgDEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEImCNAAMScSREEAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAAARDaAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAuYIEAAxZ1IEQQACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAT+H3v3AaVFkTV8/MIwZASGJDiIooASJElSggFEVzASFEUFdUkG1iyuBN1FFBVUUBQFAQUEVAwgoiJJQTIiQUZQmFdyzmlmvlP1vjMfAxOe0N3VXc+/z/GsDN3VVb+qcm/P7a5CgAQIYwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQSsEyABYl2X0iAEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAgAcIYQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAesESIBY16U0CAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAAIhqDsAAAgAElEQVQBBEiAMAYQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEDAOgESINZ1KQ1CAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABEiCMAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEELBOgASIdV1KgxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQIAECGMAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEErBMgAWJdl9IgBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQIAHCGEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAHrBEiAWNelNAgBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRIgDAGEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwDoBEiDWdSkNQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAARIgjAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBCwToAEiHVdSoMQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECABAhjAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBKwTIAFiXZfSIAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEECABwhhAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAAB6wRIgFjXpTQIAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEESIAwBhBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMA6ARIg1nUpDUIAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAESIIwBBBBAAAEEEEAAAQQQQAABxwUuuOAC2bRpU5blduvWTUaMGOH4PSkQAQQQQAABBBBAAIHTBUiAMB4QQAABBBBAAAEEEEAAAQQcF1AJkH379knv3r3PKvvyyy+XNm3aOH5PCkQAAQQQQAABBBBAgAQIYwABBBBAAAEEEEAAAQQQQMBVAZUAUcdff/3l6n0oHAEEEEAAAQQQQACB7AT4AoSxgQACCCCAAAIIIIAAAggg4LgACRDHSSkQAQQQQAABBBBAIEwBEiBhgsXC6VdddZXMmTMnrKb++OOPoq7jQAABBBBAAAEEEEAAgegEduzYIYsWLdL/LF68WP+ze/duXei9994rH374Ycg32Lx5s7z55psybdo0Uf9eoEABufjii6VDhw7Ss2dPKVy4cMhlhXuiSoAcP35cBg0aJH///beULFlSrrjiCqldu3a4RXE+AggggAACCCCAAAIRCZAAiYjN7ovCTYDkzZtXP0ydd955dsPQOgQQQAABBBBAAAEEPBDIkydPtncJJwGikh533XWX7N+/P8vyqlWrJtOnT5fKlSu70qrsNkG//vrrZdy4cVK6dGlX7kuhCCCAAAIIIIAAAgikC5AAYSycJfDnn3/K4cOHc5RZs2aNdOzYUZ/TqlUrmTlzJpIIIIAAAggggAACCCDggMDpCZCKFSvKpZdemhFvh5oAWblypf7a4siRI1K0aFF59tln5eqrr5ajR4/KxIkTZeTIkbqml1xyif7CRJ3j9PHCCy9IixYtpEaNGvrLE/UMMWDAAPnmm2+kSZMm8tNPP0lOyR6n60N5CCCAAAIIIIAAArEnQAIk9vrckRY//fTT8sorr+iy1Ntbd999tyPlUggCCCCAAAIIIIAAArEu0K9fP2nQoIH+p1y5cnoT8QsvvFCzhJoAUcmO2bNnS758+WTu3Lk64XD6MXjwYHnqqaf0j1RSom/fvmexqy800pfeCqVPQlkWNzU1VSdF5s+fL19//bXceOONoRTNOQgggAACCCCAAAIIRCRAAiQitti+SD20nH/++XodX/Wm2Pbt211dOzi2tWk9AggggAACCCCAQKwLhJsAUV90NGzYULN169ZNRowYcRahiulr1qwpa9eu1XtzqJg+Pj4+03kPP/ywHDx4MGT+Z555Rn9RktsxatQouf/++/VXKQMHDsztdP4eAQQQQAABBBBAAIGIBUiAREwXuxd+9913ct1112mA++67T0aPHh27GLQcAQQQQAABBBBAAAGXBcJNgDz33HMZiYWFCxdKo0aNsqyh2pxcJSHUoZa0VUvbenF8+eWXcvPNN8ujjz4qQ4cO9eKW3AMBBBBAAAEEEEAgRgVIgMRox0fT7M6dO8tHH32ki5g1a5ZeS5gDAQQQQAABBBBAAAEE3BEINwHSvHlzmTdvnhQpUkT27dunl8HK6liwYIHeJ0QdagkstRSWF0d6gmbIkCHSu3dvL27JPRBAAAEEEEAAAQRiVIAESIx2fKTNPnTokJx77rl6k3S1DJZ6GGPjwkg1uQ4BBBBAAAEEEEAAgdwFwk2AlClTRnbt2iW1a9eWFStWZHuDvXv3SkJCgv779u3by6RJk3KvTIhnqA3PK1SoICVKlMh0hdr7Q31pkpaWJuvXr9fPFBwIIIAAAggggAACCLglQALELVlLyx0zZoxe9kod6s2t//znPxG19H/+539yvO7YsWOybt06vemjeoDL7q21iG7ORQgggAACCCCAAAIRCZw6dUp27typr61Vq5YULFgwonK4KDyBcBIgKo4uVKiQvoHaYFxtNJ7Tofb0Uy83NW7cWNQXIU4d/fv3l1deeUWuvfZaueCCC6RAgQLy22+/6aW28ubNq/cleeCBB8K6Hc8QYXFxMgIIIIAAAggg4AsB088QJEB8MQyCUwn1AKOWvVLH77//LlWrVo2o8nw1EhEbFyGAAAIIIIAAAr4RWLRokTRo0MA39bG5IuEkQFSCqmzZspqjY8eOMnHixBxp1AtHO3bs0Buir1q1yjHGOXPmyNtvvy3Lli3TG6yrxIy6V9OmTeVf//pXxibt4dyQZ4hwtDgXAQQQQAABBBDwn4CJZwgSIP4bB76tkXrjqlKlSpKamhr1G2I8vPi2m6kYAggggAACCCAQkoCJh5eQKmbhSeEkQJKTkzOWlVJ7940dOzZHEbUElbrmoosukj/++MPXejxD+Lp7qBwCCCCAAAIIIJCrgIlnCBIguXYLJ6QLDBo0SJ599ln9x3feeUe6d+8eMU5un6+rh7D0DRnVxChfvnzE9+JCBBBAAAEEEEAAAWcEtm7dmvHm/p9//qmXNuJwXyCcBIhfvgBxQ4VnCDdUKRMBBBBAAAEEEHBXwPQzBAkQd/vXqtJr1KghajNDtX6vGrglS5Z0rX3q4aZixYq6fJUMSUxMdO1eFIwAAggggAACCCAQmgAxWmhOTp8VTgLEL3uAOG0QSnmMz1CUOAcBBBBAAAEEEPBWwHSMRgLE2/4O7N2WLFmSscbz7bffLlOmTHG1LaYnhquNo3AEEEAAAQQQQCCgAsRoZjounASIqmGZMmVk165dUrt2bVmxYkW2ld67d68kJCTov2/fvr1MmjTJTAMduivj0yFIikEAAQQQQAABBBwUMB2jkQBxsDNtLuqRRx6Rt956Szfxyy+/lLZt27raXNMTw9XGUTgCCCCAAAIIIBBQAWI0Mx0XbgKkefPmMm/ePClSpIjs27dP8uXLl2XFFyxYkLHsbN++fWXAgAFmGujQXRmfDkFSDAIIIIAAAggg4KCA6RiNBIiDnWlrUSdPnpTzzjtP1HrC6m2yLVu2ZPsQ5ZSB6YnhVDsoBwEEEEAAAQQQsEmAGM1Mb4abAOnTp4+89NJLurILFy6URo0aZVnx0/f4+/bbb+W6664z00CH7sr4dAiSYhBAAAEEEEAAAQcFTMdoJEAc7Exbi1JffNx88826eY8++qgMHTrU9aaanhiuN5AbIIAAAggggAACARQgRjPTaeEmQBYtWpSR9OjWrZuMGDHirIqnpqZKzZo1Ze3atVKiRAnZsWOHxMfHm2mgQ3dlfDoESTEIIIAAAggggICDAqZjNBIgDnamrUW1a9dOPv30U928pUuXSr169VxvqumJ4XoDuQECCCCAAAIIIBBAAWI0M50WbgJE1TJ9GSy1/NXcuXOlSZMmmSo/ePBgeeqpp/TP+vXrJ/379zfTOAfvyvh0EJOiEEAAAQQQQAABhwRMx2gkQBzqSFuLURsjli9fXo4fP67fEFu1apUnTTU9MTxpJDdBAAEEEEAAAQQCJkCM5k2HzZ8/X/7444+Mm6kNzZ988kn95yuvvFIeeOCBTBW57777zqrY8uXL9blHjx6VokWLiloW6+qrr9Z/njhxorz33nv6mqpVq8qSJUukWLFi3jTOxbswPl3EpWgEEEAAAQQQQCBCAdMxGgmQCDsuVi5Tn8v36NFDN/eVV17JePByu/2mJ4bb7aN8BBBAAAEEEEAgiALEaN70mkpojBkzJuSbpaWlZXnuV199JXfffbccOHAgy79XyY9p06bJxRdfHPK9/HRijRo1MlVH7V2YlJSkf5acnCyJiYl+qi51QQABBBBAAAEEYlLA9DMECZCYHHahN1q9Nfbzzz9LXFycbN68WSpUqBD6xVGcaXpiRFF1LkUAAQQQQAABBKwVIEbzpmudSoCo2m7atEneeOMNnehQ/Zc/f36d8Gjfvr089NBDUrhwYW8a5cJdSIC4gEqRCCCAAAIIIICAwwKmnyFIgDjcoRTnjIDpieFMKygFAQQQQAABBBCwS4AYza7+tK01jE/bepT2IIAAAggggIANAqZjNBIgNowiC9tgemJYSEqTEEAAAQQQQACBqAWI0aImpAAXBRifLuJSNAIIIIAAAgggEKGA6RiNBEiEHcdl7gqYnhjuto7SEUAAAQQQQACBYAoQowWz32Kl1ozPWOlp2okAAggggAACQRIwHaORAAnSaImhupqeGDFETVMRQAABBBBAAIGQBYjRQqbiRAMCjE8D6NwSAQQQQAABBBDIRcB0jEYChCHqSwHTE8OXKFQKAQQQQAABBBAwLECMZrgDuH2OAoxPBggCCCCAAAIIIOA/AdMxGgkQ/40JaiQipicGnYAAAggggAACCCBwtgAxGqPCzwKMTz/3DnVDAAEEEEAAgVgVMB2jkQCJ1ZHn83abnhg+56F6CCCAAAIIIICAEQFiNCPs3DREAcZniFCchgACCCCAAAIIeChgOkYjAeJhZ3Or0AVMT4zQa8qZCCCAAAIIIIBA7AgQo8VOXwexpYzPIPYadUYAAQQQQAAB2wVMx2gkQGwfYQFtn+mJEVA2qo0AAggggAACCLgqQIzmKi+FhylQo0aNTFecPHlSkpKS9M+Sk5MlMTExzBI5HQEEEEAAAQQQQMBpAdPPECRAnO5RynNEwPTEcKQRFIIAAggggAACCFgmQIxmWYcGvDkkQALegVQfAQQQQAABBGJCwPQzBAmQmBhmwWuk6YkRPDFqjAACCCCAAAIIuC9AjOa+MXeIXIDxGbkdVyKAAAIIIIAAAm4JmI7RSIC41bOUG5WA6YkRVeW5GAEEEEAAAQQQsFSAGM3SjrWkWYxPSzqSZiCAAAIIIICAVQKmYzQSIFYNJ3saY3pi2CNJSxBAAAEEEEAAAecEiNGcs6Qk5wUYn86bUiICCCCAAAIIIBCtgOkYjQRItD3I9a4ImJ4YrjSKQhFAAAEEEEAAgYALEKMFvAMtrz7j0/IOpnkIIIAAAgggEEgB0zEaCZBADhv7K216YtgvTAsRQAABBBBAAIHwBYjRwjfjCu8EGJ/eWXMnBBBAAAEEEEAgVAHTMRoJkFB7ivM8FTA9MTxtLDdDAAEEEEAAAQQCIkCMFpCOitFqMj5jtONpNgIIIIAAAgj4WsB0jEYCxNfDI3YrZ3pixK48LUcAAQQQQAABBLIXIEZjdPhZgPHp596hbggggAACCCAQqwKmYzQSILE68nzebtMTw+c8VA8BBBBAAAEEEDAiQIxmhJ2bhijA+AwRitMQQAABBBBAAAEPBUzHaCRAPOxsbhW6gOmJEXpNORMBBBBAAAEEEIgdAWK02OnrILaU8RnEXqPOCCCAAAIIIGC7gOkYjQSI7SMsoO0zPTECyka1EUAAAQQQQAABVwWI0VzlpfAoBRifUQJyOQIIIIAAAggg4IKA6RiNBIgLnUqR0QuYnhjRt4ASEEAAAQQQQAAB+wSI0ezr0yC3qEaNGpmqf/LkSUlKStI/S05OlsTExCA3j7ojgAACCCCAAAJWCJh+hiABYsUwsq8RpieGfaK0CAEEEEAAAQQQiF6AGC16Q0pwToAEiHOWlIQAAggggAACCLglYPoZggSIWz1LuVEJmJ4YUVWeixFAAAEEEEAAAUsFiNEs7VhLmsX4tKQjaQYCCCCAAAIIWCVgOkYjAWLVcLKnMaYnhj2StAQBBBBAAAEEEHBOgBjNOUtKcl6A8em8KSUigAACCCCAAALRCpiO0UiARNuDXO+KgOmJ4UqjKBQBBBBAAAEEEAi4ADFawDvQ8uozPi3vYJqHAAIIIIAAAoEUMB2jkQAJ5LCxv9KmJ4b9wrQQAQQQQAABBBAIX4AYLXwzrvBOgPHpnTV3QgABBBBAAAEEQhUwHaORAAm1pzjPUwHTE8PTxnIzBBBAAAEEEEAgIALEaAHpqBitJuMzRjueZiOAAAIIIICArwVMx2gkQHw9PGK3cqYnRuzK03IEEEAAAQQQQCB7AWI0RoefBRiffu4d6oYAAggggAACsSpgOkYjARKrI8/n7TY9MXzOQ/UQQAABBBBAAAEjAsRoRti5aYgCjM8QoTgNAQQQQAABBBDwUMB0jEYCxMPO5lahC5ieGKHXlDMRQAABBBBAAIHYESBGi52+DmJLGZ9B7DXqjAACCCCAAAK2C5iO0UiA2D7CAto+0xMjoGxUGwEEEEAAAQQQcFWAGM1VXgqPUoDxGSUglyOAAAIIIIAAAi4ImI7RSIC40KkUGb2A6YkRfQsoAQEEEEAAAQQQsE+AGM2+PrWpRYxPm3qTtiCAAAIIIICALQKmYzQSILaMJMvaYXpiWMZJcxBAAAEEEEAAAUcEiNEcYaQQlwQYny7BUiwCCCCAAAIIIBCFgOkYjQRIFJ3Hpe4JmJ4Y7rWMkhFAAAEEEEAAgeAK2B6j7d+/X3bu3Cm7d++WQoUKSZkyZaR06dISHx8f3E6zuOY1atTI1LqTJ09KUlKS/llycrIkJiZa3HqahgACCCCAAAIIBEPA9DMECZBgjJOYq6XpiRFz4DQYAQQQQAABBBAIQcC2GG3+/Pkye/ZsmTdvnixYsEAOHz6cpULVqlWlWbNm+p/WrVtL2bJlQ9DiFLcFSIC4LUz5CCCAAAIIIIBA9AKmnyFIgETfh5TggoDpieFCkygSAQQQQAABBBAIvIANMdrWrVvlnXfekQ8//FD+/vvvjD5JS0vLsX/y5Mmj/z4uLk5atWolPXv2lBtvvDHwfWpTA2wYnzb1B21BAAEEEEAAAQSUgOkYjQQI49CXAqYnhi9RqBQCCCCAAAIIIGBYIMgxmkp2/Oc//5HRo0eLWiopPeGhEhrqS4L69evrLzsSEhKkZMmScvToUdmzZ4/s3btX1q9fL0uWLJFdu3Zl9IBKiFxyySXSr18/6dChg+Ge4fZ+eLimFxBAAAEEEEAAAQTOFjD9DEEChFHpSwHTE8OXKFQKAQQQQAABBBAwLBDUGG3AgAEyePBgndRQiQ+V6OjYsaPcfvvt0qBBA73fRyjHn3/+KT/88IOMHz9e5s6dK6mpqaISIQ0bNpSRI0dKzZo1QymGc1wSCOr4dImDYhFAAAEEEEAAAV8ImI7RSID4YhhQiTMFTE8MegQBBBBAAAEEEEDgbIGgxmh58+bVjVFLVz3++OPSsmVLSf9ZpP28ZcsWGTVqlAwdOlR/KdK/f3/p27dvpMVxnQMCQR2fDjSdIhBAAAEEEEAAAd8KmI7RSID4dmjEdsVMT4zY1qf1CCCAAAIIIIBA1gJBjdHUXh0qOdGoUSPHu1ZtnD58+HApVqyY9OjRw/HyKTB0gaCOz9BbyJkIIIAAAggggEDwBEzHaCRAgjdmYqLGpidGTCDTSAQQQAABBBBAIEwBYrQwwTjdUwHGp6fc3AwBBBBAAAEEEAhJwHSMRgIkpG7iJK8FTE8Mr9vL/RBAAAEEEEAAgSAIEKMFoZdit46Mz9jte1qOAAIIIIAAAv4VMB2jkQDx79iI6ZqZnhgxjU/jEUAAAQQQQACBbARsi9GuueYa3dLOnTtLly5d6PeAC9g2PgPeHVQfAQQQQAABBBDQAqZjNBIgPhuIu3btkr///lt27twpu3fvlkKFCkmZMmX0P5UrV456s0afNTfb6pieGEFxop4IIIAAAggggICXArbFaPHx8ZKamirff/+9XH311V5Sci8XBGwbny4QUSQCCCCAAAIIIOC5gOkYjQSI512e+YYHDx6UL774QmbPni3z5s2TP/74I9saFSlSRBo3bizNmjUTtZFjvXr1DNfevdubnhjutYySEUAAAQQQQACB4ArYFqOdd955sm3bNlmyZInUrVs3uB1DzbWAbeOTbkUAAQQQQAABBGwQMB2jkQAxNIqWLl0qb7zxhnz66ady7NgxXYu0tLRca5MnT56Mc6pVqya9evWS++67T1RyxKbD9MSwyZK2IIAAAggggAACTgnYFqP94x//kG+//VbGjx8vHTt2dIqJcgwJ2DY+DTFyWwQQQAABBBBAwFEB0zEaCRBHuzP3wlTi49///rfMnDkzU9KjfPny0qBBA6lfv76ULVtWEhISpGTJknL06FHZs2eP7N27V9avXy+LFy+WX3/9VU6ePKmvVwkRde6TTz4pjz76qBQoUCD3SgTgDNMTIwBEVBEBBBBAAAEEEPBcwLYY7bPPPpN27dpJixYt5Mcff/Tckxs6K2Db+HRWh9IQQAABBBBAAAEzAqZjNBIgHva72lhx3Lhxep1hdaglrO666y65/fbb5fzzzw+5JidOnJC5c+fqN9U+//xz2b9/v06EqDJU+U2bNg25LL+eaHpi+NWFeiGAAAIIIIAAAiYFbIzR7rnnHvnoo4/0V9VvvfWWdV9WmxwvXt/bxvHptSH3QwABBBBAAAEEnBYwHaORAHG6R3MoL2/evJI/f36599575fHHH5eqVatGfffjx4/L5MmTZeDAgbJu3Trp37+/9O3bN+pyTRdgemKYbj/3RwABBBBAAAEE/ChgW4w2duxYvQztkCFDZNWqVVKiRAlp27atXHbZZfpr7Li4uBy7QSVPOPwjYNv49I8sNUEAAQQQQAABBCIXMB2jkQCJvO/CvlLt1/Hss89KYmJi2NfmdoF6cFOJkJSUFLnzzjtzO933f296YvgeiAoigAACCCCAAAIGBGyL0dQLSqfvsadi6tP/nBOxOu/UqVMGeoFbpgvUqFEjE4ZaJjgpKUn/LDk52ZXnLvQRQAABBBBAAAEEwhMw/QxBAiS8/uJsjwRMTwyPmsltEEAAAQQQQACBQAnYFqOpBEikh0qAqJePOMwJkAAxZ8+dEUAAAQQQQACBUAVMP0OQAAm1p3x63po1a6R69eo+rV3k1TI9MSKvOVcigAACCCCAAAL2CtgWo23atCmqzqpUqVJU13OxswK2jU9ndSgNAQQQQAABBBAwI2A6RiMB4nG/T5gwwbElqpYvXy6tW7eWHTt2eNwK929nemK430LugAACCCCAAAIIBE+AGC14fRZLNWZ8xlJv01YEEEAAAQQQCIqA6RiNBIjHI0Vtgq6SILfffntUd160aJFOfhw4cMDKT+9NT4yoOoeLEUAAAQQQQAABSwWI0SztWEuaxfi0pCNpBgIIIIAAAghYJWA6RiMB4vFwUusMx8fH6w3Lb7rppojuPnfuXGnbtq0cPHhQb9Jo49rDpidGRB3DRQgggAACCCCAgOUCxGiWd3DAm8f4DHgHUn0EEEAAAQQQsFLAdIxGAsTjYVW8eHGduFBfgnz++edyww03hFWDmTNnym233SZHjhzR1z3//PMyYMCAsMoIwsmmJ0YQjKgjAggggAACCCDgtQAxmtfi3C8cAcZnOFqciwACCCCAAAIIeCNgOkYjAeJNP2fc5eeff5brr79eDh06JAULFpQvv/xSWrZsGVIt1Ll33HGHHDt2TJ8/cOBAeeaZZ0K6NmgnmZ4YQfOivggggAACCCCAgBcCNsdoP/74o0ydOlVWrlwpu3btkqNHj0paWlq2rOpL7A0bNnjBzj1CFLB5fIZIwGkIIIAAAggggIDvBEzHaCRADAwJtYTVP/7xD/0VR6FChWT69OnSokWLHGsyadIk6dy5s5w8eVKfN3ToUHnkkUcM1N6bW5qeGN60krsggAACCCCAAALBErAxRtuxY4d+yWjOnDm6M7JLeqiEx+l/Z+tStMEakZlra+P4DHJ/UHcEEEAAAQQQQEAJmI7RSIAYGoezZs3S+3ioN8uKFCkiM2bMkCuvvDLL2owdO1YeeOABOXXqlN7zY8SIEfLggw8aqrk3tzU9MbxpJXdBAAEEEEAAAQSCJWBbjKZeLmrcuLGsWLFCJzfq1q0rFSpUkGnTpum4++6775a9e/fKsmXLZMuWLfpn9erVk5o1a+qOGz16dLA60PLa2jY+Le8umocAAggggAACMSJgOkYjAWJwoH377bdyyy23yPHjx6VYsWLy3XffScOGDTPVSCU7HnroIUlNTZW4uDgZNWqU/hLE9sP0xLDdl/YhgAACCCCAAAKRCNgWo40cOVK6deumExsqzr733ntl9erVUqtWLf2zlJSUDKYvvvhCevXqpRMi6gWl22+/PRJCrnFRwLbx6SIVRSOAAAIIIIAAAp4JmI7RSIB41tVZ30i9XaYenk6cOCFqg/QffvhBv1WmjiFDhsgTTzyh30aLj4+Xjz/+WNq1a2e4xt7c3vTE8KaV3AUBBBBAAAEEEAiWgG0xmtqbb+bMmXLDDTforz7UkV0CRP2d2vPj8ssv119mq69CqlSpEqwOtLy2to1Py7uL5iGAAAIIIIBAjAiYjtFIgPhgoKnNFjt06KAfpEqVKiXff/+9fgB7/gUGXBEAACAASURBVPnndfJDbZau9gBp06aND2rrTRVMTwxvWsldEEAAAQQQQACBYAnYFqOVL19e1B4gH330kdx5551nJUDSl6A9vZf69+8vL7zwgvTs2VOGDRsWrA60vLa2jU/Lu4vmIYAAAggggECMCJiO0UiA+GSgqQTHXXfdpZe6UgmPY8eO6eRH4cKFRSVIWrZs6ZOaelMN0xPDm1ZyFwQQQAABBBBAIFgCtsVoBQoU0C8h/fTTT3ovEHUkJSVJtWrV9BJYBw4c0Pv1nX7MmzdPWrRoob/++P3334PVgZbX1rbxaXl30TwEEEAAAQQQiBEB0zEaCRAfDTS1xJVad1glQdRxzjnnyNdffy1Nmzb1US29qYrpieFNK7kLAggggAACCCAQLAHbYjS1D9+RI0dk8eLFGcvQbt++XdSXISoBsnbtWqlatWqmTlLnNmrUSL+odOjQoWB1oOW1tW18Wt5dNA8BBBBAAAEEYkTAdIxGAsTjgTZ37twc7zhmzBgZPXq05M2bV1566SX9cJXb0bx589xOCdzfm54YgQOjwggggAACCCCAgAcCtsVoNWrUkHXr1umXjtQ+IOmH2ptPJTc+/PBD6dy5cyZZ9bOuXbvqL0MOHjzogTq3CFXAtvEZars5DwEEEEAAAQQQ8LOA6RiNBIjHo0MlNtTbZE4dqiz12b5th+mJYZsn7UEAAQQQQAABBJwQsC1GU8mN8ePHy4svvih9+vTJIGrbtq3ek69evXp6eSy1VJY69u/fL02aNNFLX6nN0H/55RcnWCnDIQHbxqdDLBSDAAIIIIAAAggYFTAdo5EA8bj7VQLEyUMlQFJSUpws0hdlmZ4YvkCgEggggAACCCCAgM8EbIvR0r/mUEkNlehIP1TyQyVBVKx90UUXyc0336yXyvrqq69EGaifv/nmm9KrVy+f9VBsV8e28RnbvUnrEUAAAQQQQMAWAdMxGgkQj0fSgAEDHL9jv379HC/TdIGmJ4bp9nN/BBBAAAEEEEDAjwK2xWj79u2TOnXqSFpamsyaNUsnO9KPBx54QEaNGqX/mP4FtzpPHa1bt9ZfiDj9cpMf+zxIdbJtfAbJnroigAACCCCAAALZCZiO0UiAMDZ9KWB6YvgShUohgAACCCCAAAKGBWItRvvggw/k/fffl9WrV+tlZ6tUqSL33HOPPProo5IvXz7DvcHtzxSItfHJCEAAAQQQQAABBIIgYDpGIwEShFESg3U0PTFikJwmI4AAAggggAACuQoQo+VKxAkeCqhN7E8/Tp48KUlJSfpHycnJkpiY6GFtuBUCCCCAAAIIIIBAVgKmnyFIgDAufSlgemL4EoVKIYAAAggggAAChgWI0Qx3ALfPJEAChAGBAAIIIIAAAgj4X8D0MwQJEP+PkZisoemJEZPoNBoBBBBAAAEEEMhFgBiNIeJnAcann3uHuiGAAAIIIIBArAqYjtFIgHg48hYtWiQNGzZ07Y5HjhyRv/76S6pXr+7aPbwq2PTE8Kqd3AcBBBBAAAEEEAiSgM0xmtrj44svvpDvv/9efvvtN9mzZ4/umoSEBKlZs6a0bNlSbr75Zvb+8PGAtXl8+pidqiGAAAIIIIAAAjkKmI7RSIB4OEDj4uLk+uuvl/79+0uDBg0cu/Phw4dl2LBh8tprr8lDDz0kffv2daxsUwWZnhim2s19EUAAAQQQQAABPwvYGqNNnTpVHn74YdmyZUsGf1pamv73PHnyZPysfPnyOu6+5ZZb/NxNMVs3W8dnzHYoDUcAAQQQQAABKwRMx2gkQDwcRqVLl9ZvkqmHqCuuuEI6d+4s7du3l5IlS0ZUi/nz58vHH38skyZNkn379ol6SFMPZD179oyoPD9dZHpi+MmCuiCAAAIIIIAAAn4RsDFGGzJkiDzxxBOaWMXTKla/4IILpFy5cvrPO3bs0F9Zn54QUS8e9e7d2y/dQj3+T8DG8UnnIoAAAggggAACQRcwHaORAPFwBO3du1f69esn7733npw4cUI/XMXHx8tVV10ljRs31l+F1K1bV8qWLXvWp/UHDhyQ9evXy+LFi0UtpTVr1ixRgyf9QU1tADh48GD9hYkNh+mJYYMhbUAAAQQQQAABBJwWsC1GW7hwoTRt2lRSU1PlnHPOkeeee066dOki6sWl049du3bJ6NGjZeDAgbJ//35RX3arl5EaNWrkNDHlRSFg2/iMgoJLEUAAAQQQQAAB3wiYjtFIgBgYCsnJyTJo0CAZO3asqOWr1HH6p/Xqz4ULF9Zfhhw9elR/3aEeyk4/0t9Aq1evnjz55JPSoUOHs8ow0DTHbml6YjjWEApCAAEEEEAAAQQsErAtRlMx9JQpU6R48eLy008/5bqX3tq1a/WX3OrlpHbt2sknn3xiUe8Gvym2jc/g9wgtQAABBBBAAAEERL/EX7FiRU2hfi+emJjoKQsJEE+5M99MvT02ceJEvYTVggUL5NixYyHVplKlSnLjjTfqJbRsfevM9MQIqSM4CQEEEEAAAQQQiDEB22K0ChUqyPbt2+W///2vPPPMMyH1pnqRqU+fPnqJrK1bt4Z0DSd5I2Db+PRGjbsggAACCCCAAALuCpiO0UiAuNu/IZeulsRSy1v9/PPPOiu2c+dOvV9IwYIFpUyZMvqfWrVqSbNmzTzPkoXcCAdPND0xHGwKRSGAAAIIIIAAAtYI2BajFSpUSC9Nq2LwUF8s+uWXX6RJkyZSoEAB/bU2h38EbBuf/pGlJggggAACCCCAQOQCpmM0EiCR9x1XuihgemK42DSKRgABBBBAAAEEAitgW4xWuXJl2bRpU0QJELVR+saNGwPblzZW3LbxaWMf0SYEEEAAAQQQiD0B0zEaCZDYG3OBaLHpiREIJCqJAAIIIIAAAgh4LGBbjPbPf/5TPvjgA3nppZfkqaeeCknz5ZdflmeffVa6du0q77//fkjXcJI3AraNT2/UuAsCCCCAAAIIIOCugOkYjQSIu/1rRem7du2SUaNGyRdffCEbNmyQvXv3SqlSpfTmNc2bN5fbbrtNLwPg5GF6YjjZFspCAAEEEEAAAQRsEbAtRvv999+lfv36kj9/flm4cKFUrVo1x65av369NG7cWE6ePClLliyRatWq2dK1VrTDtvFpRafQCAQQQAABBBCIeQHTMRoJkJgfgjkDTJ48WXr06CG7d+/O9sSbb75Zpk6d6qik6YnhaGMoDAEEEEAAAQQQsETAxhhtxowZ0qlTJ91Dffv2lXvuuUcSEhIy9Zh6AWjs2LHy4osvSmpqqnz88cdyww03WNKr9jTDxvFpT+/QEgQQQAABBBCIVQHTMRoJkFgdeSG0Wz3kdenSRT/klS1bVidCmjZtqh8It23bpr8G+eqrr6R48eKiEiVOHqYnhpNtoSwEEEAAAQQQQMAWgaDGaNdcc02OXfD3339LUlKS5MmTR/9z4YUX6vhX/fv27dvlzz//lLS0NF1GlSpVpEKFCvrvfvjhB1u61op2BHV8WoFPIxBAAAEEEEAAgWwETMdoJEAYmlkKrF27VurWrSvHjx+XZs2aZSQ6sjr5xIkTetkAJw/TE8PJtlAWAggggAACCCBgi0BQY7S8efPqhEV6EuP0/lA/V0dWf5dVv6WXo/43JSXFlq61oh1BHZ9W4NMIBBBAAAEEEECABAhjIEgCLVu21G+0lS5dWlQyRP2vlwcPL15qcy8EEEAAAQQQQCA0gaDGaFdddZVOgDh9/Pjjj04XSXlRCAR1fEbRZC5FAAEEEEAAAQR8L2A6RuMLEN8PEe8ruG7dOrn00kv1jfv37y/9+vXzvBKmJ4bnDeaGCCCAAAIIIIBAAASI0QLQSTFcRcZnDHc+TUcAAQQQQAAB3wqYjtFIgPh2aJirmNrcUW0AqY7Vq1dL9erV9b+rzR937dql9wApVaqUqxU0PTFcbRyFI4AAAggggAACARUgRgtox8VItRmfMdLRNBMBBBBAAAEEAiVgOkYjARKo4eJNZW+88UaZPn263txcJT3Gjx8vr7zyivz6668ZFVAbQ957773y+OOPS9GiRR2vmOmJ4XiDKBABBBBAAAEEELBAgBjNgk60uAmMT4s7l6YhgAACCCCAQGAFTMdoJEACO3Tcq7hKbvz1119Su3Ztadq0qQwfPjzbm9WsWVO+/fZbqVChQlgVUgM/p2Pr1q3SsGFDfUpycrIkJiaGVT4nI4AAAggggAACCDgvYPrhxfkWUaJNAoxPm3qTtiCAAAIIIICALQKmYzQSILaMJAfbob78OHDggBQoUECOHz8uJUqUkEGDBsltt90m55xzjqxatUovkfXNN9/ou15xxRUyb948yZs3b8i1CGcTShIgIbNyIgIIIIAAAggg4KqA6YeXSBu3aNGijJdrIi0jp+uOHDmiXyBKXzrWjXtQZu4CQR2fubeMMxBAAAEEEEAAgeAKmI7RSID4cOxs3LhRFixYINu2bRP1MNWjRw8pXbq0ZzXNly+fpKSk6PvFxcXJ/PnzpXHjxpnun5qaKm3atMlIgkyePFnatWsXch1JgIRMxYkIIIAAAggggIBvBEw/vEQKoWLa66+/Xvr37y8NGjSItJizrjt8+LAMGzZMXnvtNXnooYcy9tFz7AYUFJZAUMdnWI3kZAQQQAABBBBAIGACpmM0EiA+GjDLly+X3r1764TD6Yf64uL0t8nUklQDBgzQe3SsWbNG4uPjHW2F2tNDPcyp44477pAJEyZkWb7aIF0tgaUO9XXIp59+GnI9WAIrZCpORAABBBBAAAEEfCNg+uElUgj1MtGePXtEvYSjvl7u3LmztG/fXkqWLBlRkSpe//jjj2XSpEmyb98+SUtL04mQnj17RlQeFzkjENTx6UzrKQUBBBBAAAEEEPCngOkYjQSIT8bFtGnT9BcUJ06c0A9Q6Yd6SDszAXLo0CEpX768/jpkypQpcuuttzraClW2+vpEHWPGjJF77rkn2/LV3hx///23VKxYUTZv3uxYPUxPDMcaQkEIIIAAAggggIBFAkGN0fbu3Sv9+vWT9957T8fbKsZWLxFdddVV+ktn9VVI3bp1pWzZsqK+hj79UEvDrl+/XhYvXixqKa1Zs2ZJ+ss8Km6vUaOGDB48WH9hwmFWIKjj06wad0cAAQQQQAABBNwVMB2jkQBxt39DKl0lG6pWrSoqsaEeoF599VW9+XixYsX0w9mZCRBVqHprbfz48XL//ffrBzknD7X5uHrAU8cPP/wg11xzTbbFN2nSRBYuXKj3Czl27Jhj1TA9MRxrCAUhgAACCCCAAAIWCQQ9RlN7y6m97caOHZvxxfOZS7MWLlxYfxly9OhR/XWHWvr19CP9ZaV69erJk08+KR06dNAxO4f3AurZ6fTj5MmTkpSUpH/EPoLe9wd3RAABBBBAAAEEshIw/QxBAsQH4/Lpp5/Wb41VqlRJ1DJYatNxdahNxbNLgHzwwQfy4IMP6jfVli5d6mgrunTpIh9++KEuc+bMmdKqVatsy09PlhQpUkQncJw6TE8Mp9pBOQgggAACCCCAgE0CtsRo+/fvl4kTJ+olrNTee6G+yKPi9RtvvFG/jNSoUSObujaQbSEBEshuo9IIIIAAAgggEGMCpp8hSID4YMDVqVNHf+Xxxhtv6M0T04+cEiBq3eHmzZvrt9N2797taCtGjx4tXbt21WW+88470r1792zLV+spq/urL1h+//13x+phemI41hAKQgABBBBAAAEELBKwMUZTS2Kpr59//vlnvbTVzp079X4hBQsWlDJlyuh/atWqJc2aNRO1/CuHfwVsHJ/+1aZmCCCAAAIIIIBAaAKmYzQSIKH1k6tnqc3M1dcT6u0z9UVFKAmQlStX6q8/1NrFx48fd7R+KqGh9gFRn5Crrz/UVyBZHXPmzNHrJqtDLcX1/vvvO1YP0xPDsYZQEAIIIIAAAgggYJEAMZpFnWlhUxifFnYqTUIAAQQQQACBwAuYjtFIgPhgCKl1hlUSY8mSJTqpEUoCRCUfrr76ar1clnpDzemjZ8+e+usPdUyYMEHuuOOOTLc4ePCg/gJlxYoV+udqQ0i1eaRTh+mJ4VQ7KAcBBBBAAAEEELBJgBjNpt60ry2MT/v6lBYhgAACCCCAQPAFTMdoJEB8MIYqV64smzZtksmTJ8ttt92WUaOclsBSmzf26dNHatasKb/++qvjrVCf/l9++eWyefNmyZcvn14GS9XtnHPO0ct1vfzyy7Ju3Tp93x49esjbb7/taB1MTwxHG0NhCCCAAAIIIICAJQLEaJZ0pKXNYHxa2rE0CwEEEEAAAQQCLWA6RiMB4oPhozZRHD9+vHTq1EnGjRuXawLkyJEjUr16dUlOTtbJh2HDhrnSirVr18pNN90kf/zxR7blq71CRowYoZficvIwPTGcbAtlIYAAAggggAACtggQo9nSk3a2g/FpZ7/SKgQQQAABBBAItoDpGI0EiA/Gz/fffy/XXXedqC8+pk+frv9dHVl9AaL2ClHLUanz8uTJc9ayWU435/Dhw3oprClTpkhSUpLeq6Rs2bJy5ZVXSrdu3fQyXG4cpieGG22iTAQQQAABBBBAIOgCxGhB70G768/4tLt/aR0CCCCAAAIIBFPAdIxGAsQn40YtLzV16lTJnz+/PPzww9K+fXtp3LixTnKo/T7UFxZqM3L1tcW2bdt0re+55x4ZPXq0T1rgbDVMTwxnW0NpCCCAAAIIIICAHQLEaHb0o62tYHza2rO0CwEEEEAAAQSCLGA6RiMB4pPRo5a1atOmjcyePVsnPbI70tLS9F9de+218vXXX0uBAgV80gJnq2F6YjjbGkpDAAEEEEAAAQTsECBGs6MfbW0F49PWnqVdCCCAAAIIIBBkAdMxGgkQH42e1NRUGTJkiLz++uuydevWLGuWkJAgTzzxhDz11FN6iSxbD9MTw1ZX2oUAAggggAACCEQjQIwWjR7Xui3A+HRbmPIRQAABBBBAAIHwBUzHaCRAwu8z1684deqULFq0SO/vsWPHDklJSZFSpUpJ3bp1pWnTptZ+9XE6rOmJ4XoncwMEEEAAAQQQQCCAAsRoAey0GKoy4zOGOpumIoAAAggggEBgBEzHaCRAAjNUYquipidGbGnTWgQQQAABBBBAIDQBYrTQnDjLjADj04w7d0UAAQQQQAABBHISMB2jkQDxwficO3eurkWDBg2kUKFCIdXo2LFj+isRdTRv3jyka4J0kumJESQr6ooAAggggAACCHglQIzmlTT3iUSA8RmJGtcggAACCCCAAALuCpiO0UiAuNu/IZWu9vJQ//z6669SvXr1kK7ZsGGDVKlSRV+nlsyy7TA9MWzzpD0IIIAAAggggIATAsRoTihShlsCjE+3ZCkXAQQQQAABBBCIXMB0jEYCJPK+c+xKlcTIkyePrFq1KuwEiLpO7RFi22F6YtjmSXsQQAABBBBAAAEnBGyP0TZu3CgLFiyQbdu2yZEjR6RHjx5SunRpJ+gowwMB28enB4TcAgEEEEAAAQQQcFzAdIxGAsTxLg2/wEgSIElJSVKtWjXJly+fnDhxIvyb+vwK0xPD5zxUDwEEEEAAAQQQMCJga4y2fPly6d27t8yfPz+T65kvKA0fPlwGDBggxYsXlzVr1kh8fLyRfuCmWQvYOj7pbwQQQAABBBBAIMgCpmM0EiA+GD2RJEC+++47ad26tZQqVUp27tzpg1Y4WwXTE8PZ1lAaAggggAACCCBgh4CNMdq0adOkXbt2+qWitLS0jI7K6gvtQ4cOSfny5fXXIVOmTJFbb73Vjo61pBU2jk9LuoZmIIAAAggggEAMC5iO0UiAGBh8mzdvznTXCy64QC+BNXPmTL2vR07H8ePHRe3/8fzzz8uyZcukWbNmMnv2bAOtcPeWpieGu62jdAQQQAABBBBAIJgCtsVoaqmrqlWrikps1KhRQ1599VVp2rSpFCtWLNslajt37izjx4+X+++/X957771gdqSltbZtfFraTTQLAQQQQAABBGJMwHSMRgLEwICLi4vLdNf0N81UEiTcY+TIkdK1a9dwL/P9+aYnhu+BqCACCCCAAAIIIGBAwLYY7emnn5bBgwdLpUqVRC2DVaJECa2a0xfaH3zwgTz44INSt25dWbp0qYFe4JbZCdg2PulpBBBAAAEEEEDABgHTMRoJEAOjSD1QRXsULFhQHnnkERk0aFC0RfnyetMTw5coVAoBBBBAAAEEEDAsYFuMVqdOHVH7fLzxxhvy0EMPZejmlABR+4Q0b95cSpYsKbt37zbcI9z+dAHbxie9iwACCCCAAAII2CBgOkYjAWJgFI0ZMybTXbt06aI/sX/xxRflvPPOy7ZG6hyV+FDrDqs3zooWLWqg9t7c0vTE8KaV3AUBBBBAAAEEEAiWgG0xmtrMXC1/tWDBAmnYsGFICZCVK1fqWFxtgK6Wp+Xwj4Bt49M/stQEAQQQQAABBBCIXMB0jEYCJPK+c+zKSDZBd+zmPi3I9MTwKQvVQgABBBBAAAEEjArYFqMVLlxYJzGWLFmikxrpR07x+Zw5c+Tqq6/Wy2Xt2bPHaH9w88wCto1P+hcBBBBAAAEEELBBwHSMRgLEB6NIPUSpQ711VqhQIR/UyHwVTE8M8wLUAAEEEEAAAQQQ8J+AbTFa5cqVZdOmTTJ58mS57bbbQkqAqCVo+/TpIzVr1pRff/3Vf50UwzWybXzGcFfSdAQQQAABBBCwSMB0jEYCxKLBZFNTTE8MmyxpCwIIIIAAAggg4JSAbTFa586dZfz48dKpUycZN25crgmQI0eOSPXq1SU5OVl69Oghw4YNc4qWchwQsG18OkBCEQgggAACCCCAgHEB0zEaCRDjQ4AKZCVgemLQKwgggAACCCCAAAJnC9gWo33//fdy3XXXiVryavr06frf1ZHVElhqr5A77rhDn6f25jtz2SzGi3kB28aneVFqgAACCCCAAAIIRC9gOkYjARJ9HzpaQlpamqxYsULU5oq7du2So0ePivpZTkffvn0drYMfCjM9MfxgQB0QQAABBBBAAAG/CdgYo6mlr6ZOnSr58+eXhx9+WNq3by+NGzfWSQ61VK3a7HzmzJkyYsQI2bZtm+6Se+65R0aPHu237on5+tg4PmO+UwFAAAEEEEAAgcALmI7RSID4aAiNGTNGBgwYoNchDudISUkJ5/RAnGt6YgQCiUoigAACCCCAAAIeC9gYo6llrdq0aSOzZ8/WSY/sjvSXkq699lr5+uuvpUCBAh7rc7vcBGwcn7m1mb9HAAEEEEAAAQT8LmA6RiMB4pMR8txzz4naUDG3rz1UddWD2ennpaam+qQVzlXD9MRwriWUhAACCCCAAAII2CNga4ym4ukhQ4bI66+/Llu3bs2ywxISEuSJJ56Qp556Si+RxeE/AVvHp/+kqRECCCCAAAIIIBC6gOkYjQRI6H3l2pm//PKLNGnSRCc2WrZsKYMHDxb1EFavXj39s1OnTsnevXv1OsPvvPOOfPHFF9K0aVOZPHmylCtXzrV6mSzY9MQw2XbujQACCCCAAAII+FXA9hhNxd2LFi3ScfeOHTtEfWldqlQpqVu3ro6/+erDryPzf+tl+/j0tz61QwABBBBAAAEEshYwHaORAPHByLzvvvtk7NixcsEFF8j69eslX758snr1aqlVq5ZOgJy5xJVKgvTq1Utq164tKnmi1iu27TA9MWzzpD0IIIAAAggggIATArbFaCoGV0e1atWkUaNGThBRhkEB28anQUpujQACCCCAAAIIOCZgOkYjAeJYV0ZeUNWqVWXDhg3y2muvSe/evXVBOSVA1N+rzRk/++yzTNdEXgP/XWl6YvhPhBohgAACCCCAAALmBWyL0dRSVuqFowkTJkiHDh3MA1ODqARsG59RYXAxAggggAACCCDgEwHTMRoJEB8MhGLFionafHHGjBnSqlUrXaO1a9dKjRo19APZsWPHJD4+PlNNv/zyS7nlllv0m2oLFizwQSucrYLpieFsaygNAQQQQAABBBCwQ8C2GK1kyZJy4MABveSVWuaKI9gCto3PYPcGtUcAAQQQQAABBP5XwHSMRgLEByOxYMGCcvLkSVm2bJle1kodycnJUqlSJZ0AUf9eoUKFTDVdvny51K9fX69JvHPnTh+0wtkqmJ4YzraG0hBAAAEEEEAAATsEbIvR1J57K1eulO+++06uueYaOzophlth2/iM4a6k6QgggAACCCBgkYDpGI0EiA8GU8WKFWXLli0ye/Zsadasma7RiRMnpEiRInoz9JkzZ8q1116bqabTp0+XNm3a6P0/1Bcith2mJ4ZtnrQHAQQQQAABBBBwQsC2GO3FF1+Ufv36yaOPPipDhgxxgogyDArYNj4NUnJrBBBAAAEEEEDAMQHTMRoJEMe6MvKCrr/+ev3W2YgRI+TBBx/MKKhOnTqyatUquf/+++W9997LdIO77rpLr1WsNk7fuHFj5Df36ZWmJ4ZPWagWAggggAACCCBgVMC2GE0tf6W+wN66dauoF4z4CsTo8Ir65raNz6hBKAABBBBAAAEEEPCBgOkYjQSIDwbBf//7X3n++efljjvukPHjx2fU6KWXXpLnnntO1OaMffr0kY4dO+q9QsaMGSNvv/22Xh6re/fuMnz4cB+0wtkqmJ4YzraG0hBAAAEEEEAAATsEbIzR/vjjD2nXrp2sXr1aunTpIp06dZLLLrtM1P4gKt7m8K+A2jPx9EMtK5yUlKR/pJYRTkxM9G/lqRkCCCCAAAIIIBAjAqafIUiA+GCgqYetWrVqSdGiRfWmMOecc46ulUp21KxZU/7666+zHr7S0tIkISFBVqxYYWVgb3pi+GBYUAUEEEAAAQQQQMB3ArbFaHFxcRnGKr4OJ+Ghzj116pTv+iiWKkQCJJZ6m7YigAACCCCAQFAFTD9DkADxyciZM2eOfoCqW7euTmykH5s2bZK7775bfvrpp0w1VYmRcePGZWyaUZ6tiAAAIABJREFU7pNmOFYN0xPDsYZQEAIIIIAAAgggYJGAbTGa+tI60kMlQFJSUiK9nOtcELBtfLpARJEIIIAAAggggIDnAqZjNBIgnnd5ZDf8/fff9Wf5KklSpUoVnSix+TA9MWy2pW0IIIAAAggggECkArbFaAMGDIiUQl+nNlDn8I+AbePTP7LUBAEEEEAAAQQQiFzAdIxGAiTyvuNKFwVMTwwXm0bRCCCAAAIIIIBAYAWI0QLbdTFRccZnTHQzjUQAAQQQQACBgAmYjtFIgARswMRKdU1PjFhxpp0IIIAAAggggEA4AsRo4WhxrtcCjE+vxbkfAggggAACCCCQu4DpGI0ESO59xBkGBExPDANN5pYIIIAAAggggIDvBYjRfN9FMV1BxmdMdz+NRwABBBBAAAGfCpiO0UiAeDgwxo4d68rd7rnnHlfKNVmo6Ylhsu3cGwEEEEAAAQQQ8KsAMZpfe4Z6KQHGJ+MAAQQQQAABBBDwn4DpGI0EiIdjIm/evJInTx5H76jKUxuj23aYnhi2edIeBBBAAAEEEEDACQHbYrQXXnghKpa+fftGdT0XOytg2/h0VofSEEAAAQQQQAABMwKmYzQSIB72u0qAOH2oBEhKSorTxRovz/TEMA5ABRBAAAEEEEAAAR8K2BajRfuCko1xuA+HXchVsm18htxwTkQAAQQQQAABBHwsYDpGIwHi4eDYtGmTK3erVKmSK+WaLNT0xDDZdu6NAAIIIIAAAgj4VcC2GC3cF5TUy0dpaWkZ3ZOamurXrorJetk2PmOyE2k0AggggAACCFgnYDpGIwFi3ZCyo0GmJ4YdirQCAQQQQAABBBBwViAWY7QjR47I77//Lh9//LG89dZb0qBBA/n000+lXLlyzuJSWtQCsTg+o0ajAAQQQAABBBBAwGUB0zEaCRCXO5jiIxMwPTEiqzVXIYAAAggggAACdgvEeow2d+5cad26tVSrVk0WLlwoBQsWtLvDA9a6WB+fAesuqosAAggggAACMSJgOkYjARIjAy1ozTQ9MYLmRX0RQAABBBBAAAEvBIjRRP71r3/Jm2++KQMHDpSnn37aC3buEaIA4zNEKE5DAAEEEEAAAQQ8FDAdo5EA8bCzQ73V0qVL5fvvv5fffvtN9uzZoy9LSEiQmjVrSsuWLaV+/fqhFhXY80xPjMDCUXEEEEAAAQQQQMBFAWI0kVmzZumYvHbt2rJ8+XIXtSk6XAHGZ7hinI8AAggggAACCLgvYDpGIwHifh+HfIclS5ZIr169RP1vTsfll18uw4cPF/W/th6mJ4atrrQLAQQQQAABBBCIRoAYTWTFihVSr149KVq0qBw4cCAaTq51WIDx6TAoxSGAAAIIIIAAAg4ImI7RSIA40IlOFDFp0iTp3LmznDp1StLS0nSR+fPn119+qD/v3btXTpw4kXGr+Ph4+eijj6R9+/ZO3N53ZZieGL4DoUIIIIAAAggggIAPBIjRRD755BO58847SYD4YDyeWQXGpw87hSohgAACCCCAQMwLmI7RSID4YAiuW7dO6tatK8ePH5d8+fLJgw8+KF27dpU6depIXFycrmFKSoqsXLlSPvjgAxk5cqROlBQoUEB/dn/JJZf4oBXOVsH0xHC2NZSGAAIIIIAAAgjYIRDrMdq+ffukadOmsnbtWmnQoIHeCJ3DPwKxPj790xPUBAEEEEAAAQQQ+P8CpmM0EiA+GI1dunSRMWPGSMGCBWX69Oly1VVX5VirOXPmyA033KATJvfee6+MGjXKB61wtgqmJ4azraE0BBBAAAEEEEDADgHbYrS5c+fm2jGpqan6a2y1TO3o0aNl+/bt+hq1JG337t1zvZ4TvBOwbXx6J8edEEAAAQQQQAAB9wRMx2gkQNzr25BLPv/88+Xvv/+Wp59+WgYOHBjSdX369JFBgwZJYmKibN68OaRrgnSS6YkRJCvqigACCCCAAAIIeCVgW4yWN29eyZMnT8h86UvV3nrrrTJlypSwrg35JpwYsYBt4zNiCC5EAAEEEEAAAQR8JGA6RiMB4oPBUKhQIb2/h/qyQ31SH8rx008/SbNmzfQyWEePHg3lkkCdY3piBAqLyiKAAAIIIIAAAh4J2BajqQRIOMdll10mPXv21EvWhpM4CecenBu5gG3jM3IJrkQAAQQQQAABBPwjYDpGIwHig7GQ/gXIL7/8IpdffnlINVKf4Dds2FDOO+88SU5ODumaIJ1kemIEyYq6IoAAAggggAACXgnYFqOpF5ByO1SSpFixYnLhhRdK8eLFczudvzcoYNv4NEjJrRFAAAEEEEAAAccETMdoJEAc68rIC7rzzjtl0qRJMmzYMOnRo0dIBb399tvy0EMPSceOHWXChAkhXROkk0xPjCBZUVcEEEAAAQQQQMArAWI0r6S5TyQCjM9I1LgGAQQQQAABBBBwV8B0jEYCxN3+Dan0xYsXy5VXXinlypWTZcuWSZkyZXK8bseOHVK/fn1R/ztv3jz9JYhth+mJYZsn7UEAAQQQQAABBJwQIEZzQpEy3BJgfLolS7kIIIAAAggggEDkAqZjNBIgkfedo1eOHj1aunfvrpe0ev311+Wmm26SM9ckTk1Nla+++koee+wxvWm6+gqka9eujtbDL4WZnhh+caAeCCCAAAIIIICAnwSI0fzUG9TlTAHGJ2MCAQQQQAABBBDwn4DpGI0EiA/GRHoSY/ny5bJy5Uq9oWLJkiWlbt26UrZsWf3n7du3y4oVK2TPnj26xrVr15Y6depkW3t1zQcffOCD1kVWBdMTI7JacxUCCNgscPDYSdm2/5gcPpEiRfLHybnFC0qxgvE2N5m2IYAAAmcJ2BajnTx5UpKSknQ7L7roIilQoECmNh87dkyee+45vVztrl279D4gahN0tRQth/8EbBuf/hOmRggggAACCCCAQPgCpmM0EiDh95njV6gvPVTCIv1IS0vT/3r6z9Sfs/v5mRVS56lrU1JSHK+rVwWanhhetZP7IICAvwXUf08XbNwt4xZskplrtktK6v/+91kdcXnzSOsa5eTuxpWkSeVSZ/03298to3YIIIBAZAK2xWgqsaH24ytdurQkJydL/vz5M8HccMMNMnPmzIw4PD1GVwmQN954IzJErnJNwLbx6RoUBSOAAAIIIIAAAh4KmI7RSIB42NnZ3eqCCy5w5Rdnf/75pw9aF1kVTE+MyGrNVQggYJPAb3/vl8cmrZD12w/l2qyq5YrK6x3qSM3ziud6LicggAACQRawLUa7//77RS1F261bN3nnnXcydc20adOkbdu2Ok5Xy9Q2aNBAFi1apJeiVT+bP3++NGnSJMjdaV3dbRuf1nUQDUIAAQQQQACBmBQwHaORAInJYef/RpueGP4XooYIIOCmwLykndJt3FI5ciL0L+kK54+TdzvXl2ZVyrhZNcpGAAEEjArYFqOpJWd//fVX+eijj/SXIKcf7dq1k88++0yqVaumEx/FihWT/fv3yxVXXCHr1q2T++67L9BLzhodSC7d3Lbx6RITxSKAAAIIIIAAAp4KmI7RSIB42t3cLFQB0xMj1HpyHgII2Cegvvzo8O6CsJIf6QoqCTKpWxO+BLFvWNAiBBD4PwHbYjT1Zce2bdvk559/lkaNGmX0c2pqqiQkJMjBgwflzTfflF69emX8nfpSRP1ZJUbWrl3L2PCRgG3j00e0VAUBBBBAAAEEEIhYwHSMRgIk4q7jQjcFTE8MN9tG2Qgg4F8BtedH66FzQ1r2KrtWVCtXTGb0bubK0ob+laNmCCAQKwK2xWhq0/NTp07JsmXLpHbt2hndqP58+eWX6/+Wb9iwQdSStenHvHnzpEWLFlK4cGE5dCj3ZRJjZWz4oZ22jU8/mFIHBBBAAAEEEEAgWgHTMRoJkGh7kOtdETA9MVxpFIUigIDvBX7esEs6jfwl6npOeLCxNLmoVNTlUAACCCDgNwHbYjS1rNWRI0f0RufXXnttBvfQoUPlsccek4oVK8qmTZsydcOKFSukXr16opInR48e9VsXxXR9bBufMd2ZNB4BBBBAAAEErBEwHaORALFmKNnVENMTwy5NWoMAAqEK9Px4qUxftS3U07M978Za5WX4XfWiLocCEEAAAb8J2Baj1apVS9asWSMvvvii9OnTJ4NbJUNmz54tnTp1knHjxmXqhlmzZknLli0lMTFRNm/e7Lcuiun62DY+Y7ozaTwCCCCAAAIIWCNgOkYjAWLNULKrIaYnhl2atAYBBEIROHjspNR54TtJSU0L5fQcz4nLm0dW9G0lxQrGR10WBSCAAAJ+ErAtRnvkkUdk2LBhUq5cOVGJjUsvvVS+/PJLufXWWzV7Vpujqz1BevfuLQ0aNJBffon+q0E/9W/Q62Lb+Ax6f1B/BBBAAAEEEEBACZiO0UiAMA59KWB6YvgShUohgICrAknbD0qrIXMdu8f3jzWXi8sWc6w8CkIAAQT8IGBbjJaUlCTqK5CTJ09q3pIlS8revXtF7QmlvvD4448/JH/+/Jno27RpI9988410795dhg8f7oduoQ7/J2Db+KRjEUAAAQTcFVAvwW3bf0wOn0iRIvnj5NziBXmJzV1ySo9RAdMxGgmQGB14fm+26Ynhdx/qhwACzgusSN4ntwz/ybGCp/a6UupULOFYeRSEAAII+EHAxhht8uTJ0rVrVzl8+HAGcYkSJeSrr76SK6+8MhP7tm3bpFKlSnrj9E8//VRuueUWP3QLdSABwhhAAAEEwhaI1V/+q5ccFmzcLeMWbJKZa7ZnWgFAfcnfukY5ubtxJWlSuZTkyZMnbFcuQACBswVMP0OQAGFU+lLA9MTwJQqVQgABVwX4AsRVXgpHAAFLBGyN0Xbs2CHTpk0TleAoX7683HTTTZKQkHBWr6nN0idMmKB//sYbb8g555xjSc/a0Qxbx6cdvUMrEEDADwKx/sv/3/7eL49NWiHrtx/KtTuqlisqr3eoIzXPK57ruZyAAAI5C5iO0UiAMEJ9KWB6YvgShUohgICrAk7uAZIvbx5Zzh4grvYXhSOAgBkBYjQz7tw1NAHGZ2hOnIUAArEpEOu//J+XtFO6jVsqR06khDwACuePk3c715dmVcqEfA0nIoDA2QKmYzQSIAEflYcOHZKiRYsGvBX+mxjWgdIgBBAISaDnx0tl+qptIZ2b00k31iovw++qF3U5FIAAAgj4TcD0w4vfPKiPvwQYn/7qD2qDAAL+ETD1y3+/LLOlkj8d3l0QVvIjvfdUEmRStyZ8CeKf4UxNAihgOkYjAeLxoPntt9+kZs2ajtx13759cv3118vChQsdKc9PhZieGH6yoC4IIOCdwM8bdkmnkb9EfcMJDzaWJheVirocCkAAAQT8JhCLMdr27dvl66+/ll27dsmFF14obdu2lUKFCvmta6iPiMTi+KTjEUAAgdwEvP7lv9+W2VL1aT10bkjLXmVnWa1cMZnRuxl7guQ22Ph7BLIRMB2jkQDxeGiee+65MmfOHKlWrVpUd969e7e0bNlSfv31V0lJCf3zvahu6uHFpieGh03lVggg4CMBgmMfdQZVQQABXwrYFqOtXbtW+vXrp3+h8e6774ra/Pz048svv5ROnTrJ0aNHM35csWJFUT+/7LLLfNlHsVwp28ZnLPclbUcAAWcEvH6+8eMyW7zk5sxYohQEohEwHaORAImm9yK4Nm/evFKhQgWdBLnooosiKEH05owq+bFmzRr9sEYCJCJGLkIAAQSyFPD6DSm6AQEEEAiSgOmHF6etXnrpJXnuueekefPmMnv27EzFq43RL774YlFLzp55qCSIisWLFCnidJUoLwoB28ZnFBRcigACCGgBL3/5b2qZrdy6mmWOcxPi7xFwX8B0jEYCxP0+znSHuLg4/efExESdBLngggvCqoEaMNdcc41s2LBBVCa/VatW8u2334ZVRhBONj0xgmBEHREIkoBf1n4N1cyvwXuo9ec8BBBAwC0B22I09VLRjz/+KC+//LI88cQTmdj69+8vL7zwguTLl09eeeUVufbaa3Xc/cwzz+g4/LXXXpPevXu7RU25EQjYNj4jIOASBBBAIJOAV7/89+tLZOo5tM4L30lKalrUIyMubx5Z0beVFCsYH3VZFIBArAmYjtFIgHg84oYNGyaPPPKI/nKjUqVKMnfuXJ0MCeXYuHGjfvDatGmTPr1NmzYyZcoUyZ8/fyiXB+oc0xMjUFhUFgGfCvht7ddwmcL5fFutCftah9psjBcuMucjgEDgBGyL0apWrapfLJoxY4Z+sej0Qy1xtXr1aunSpYu8//77GX/VrVs3GTlypFx11VUya9aswPWhzRW2bXza3Fe0DQEE3Bfw6pf/Xi+zFY5c0vaD0mrI3HAuyfHc7x9rLheXLZZreUF7ATDXBnECAlEKmI7RSIBE2YGRXD5kyBB5/PHHdRKkcuXK+ksQtSxWTse6dev0sldbtmzRp7Vr107Gjx+v30iz8TA9MWw0pU0IeCkQTvKgarmi8nqHOr5MHqhgfuHGPTJu4V/y7ertmd4cypc3j7Suca7c3biSNK6cwIZ4Xg4w7oUAAsYEbIvRSpYsKQcOHJClS5dKnTp1MlzVhuflypXTf/7uu+/0F9jpx7Rp0/RG6GXKlBG1QTqHfwRsG5/+kaUmCCAQRAGvfvnv5TJb4fbDiuR9csvwn8K9LNvzp/a6UupUzLxfWPrJQX8B0DEkCkIgCwHTMRoJEEPDUn1m/+yzz+pfmFWpUkV/CVK2bNksa6M2Or/uuutErUOsjs6dO8vo0aNF7Sdi62F6YtjqSrsQ8ELA1uWj1Fs82w8ck0PHU6RogTgpd05BPn/2YkBxDwQQ8JWAbTFagQIF5NSpU/LTTz9J48aNM6ynTp0qt912m6i/37dvn/7f9GPZsmVy+eWXS3x8vBw/ftxX/RPrlbFtfMZ6f9J+BBCITsCrX/57tcxWJBpeJYFseQEwEmOuQSAUAdMxGgmQUHrJpXPUmsJqbWGVBLn00kv1+sPqTbLTj8WLF8sNN9wge/bs0T/+5z//Ke+88471bxqbnhgudTnFImC9gF/XfrUe3mcN5JNvn3UI1UHAQQHbYrTy5cvrl4wmTJggHTp0yJB6+OGHZfjw4XLllVfKvHnzMgkuWrRIJ0vU1yO7d+92UJeiohWwbXxG68H1CCAQ2wJe/PLfyWW28uYR+azHFSJ58kiR/HFybvHoXzhzsn5qBYDlWewBYusLgLE9e2i90wKmYzQSIE73aJjl/fvf/5aBAwfqhEatWrX0OsIJCQm6lPnz5+t9PtRn+ep49NFHRS2fFQuH6YkRC8a0EQGnBfy89qvTbaW8swX45JtRgUBsCNgWo11//fV6iSu1pJX66kMdR48elQsvvFB27twpKlYfMGBAps6dPHmydOzYUS655BJZs2ZNbHR8QFpp2/gMCDvVRAABnwp48ct/p5Msp1OqTcdb1yinlxxuUrlUxC8Cu/mFCi8A+nTwUy3fCZiO0UiA+GBIPPXUU/Lqq6/q/5irtYdVEmTJkiVyyy23yOHDh3UN1XJZ//3vf31QW2+qYHpieNNK7oKAXQJ+XvvVLmn/tYZPvv3XJ9QIAbcEbIvRPvzwQ+natauOw9u3by9NmzaVTz75RC+JpZab/e2333Si4/TjiSeekNdff13+8Y9/yNdff+0WtVXlfv755/L222+LWj7syJEjcu655+qvaF555RWpWLGiY221bXw6BkNBCCAQswJu/vJfoTq9zFZ2HRXNvpFuPafyAmDMTisaHoGA6RiNBEgEnebGJf/617/kjTfeyFgOa+PGjXLs2DF9K7VUlnr7LJYO0xMjlqxpKwJOCbgdXDtVT8pxVoBPvp31pDQE/C5gW4yWmpoqV111lf7yWiVB0g/1S437779fRo4ceVaXVK5cWTZt2iSDBw+Wxx57zO9dZrR+yrF79+7y3nvvyUUXXSStW7eWYsWKyZYtW2TOnDny8ccf66STU4dt49MpF8pBAIHYFXDrl//pom5+AXJmrxXOHyfvdq4vzapkXjo+t951IlGRWKKQzHv66kyxgtu2ubWLv0cgSAKmYzQSID4aLb169crY30P9B1od6sHq8ccf91EtvamK6YnhTSu5CwL2CDj5ebX61HlFFmur2qNlT0v45NuevqQlCIQqYGOMpr647tevn6ilrbZt2yZqX5B7771Xnn/+ecmXL18mmq+++kpuvvlm/QuQFStW6CVsObIXePPNN/Uyvuo5R73sFRcXl+lktQH9mcbReNo4PqPx4FoEEEDAiV/+VytXTGb0bpblElROPgeG0lsqCTKpWxOpeV7xUE7POEc9t7R752c5dio1rOvSTy4Yn1emdL8i0315ATAiSi6KUQHTMRoJEJ8NPLXJ+fvvv68/uX/rrbekR48ePquhN9UxPTG8aSV3QcAeAaff/Pn+seZycdli9gBZ2BK3H6YsJKNJCFghEOsx2t69ezP256tUqZIVfepWI9ReKomJiVKiRAn5/fffHU10ZFfnWB+fbvUl5SKAQLAF3H5pyalEQKjKOSVksitDPbs0fflH+Xvf0VBvc9Z5p9/XycQPLwBG3CVcGCAB0zEaCRCPB8uZbz1Fe3v19pl6c8rp4/QlAHIqu0WLFjJ79mynby+mJ4bjDaJABCwXcHrt16m9rpQ6FUtYrhbs5vHJd7D7j9ojEKkAMVqkcuFdt2PHDlm0aJH+Z/Hixfqf3bt360LU1ylq75JQj82bN4v6EmPatGmi/r1AgQJy8cUXS4cOHaRnz55SuHDhUIsK67wvv/xSfy2jlgkbOHCgvv/69et1QqRly5a6Dk4fjE+nRSkPAQRsEXBz2VqnngvCsZ7wYGNpclGpkC9xqo7p9+UFwJDpOREBLWA6RiMB4vFAVF92OHmoREVKSoqTReqySIA4TkqBCFgtQABodfdm2Tin3vS6sVZ5GX5XvdgDpMUIBFTA9MNLQNnCrnZOsXg4CRCVdLjrrrtk//79WdahWrVqMn36dFH7mjh99O3bV1588UV56qmn5IsvvtBfgaQf6plI7YH46quvOnpbxqejnBSGAAKWCagvQR6btELWbz+Ua8vU1w6vdagd0lJTTnwZnmuFzjgh3GcIp59deAEw3B7j/FgXMB2jkQDxeASqTRZDTS6EWrUff/wx1FNDPi+9jmoJLvVmWHZHkSJF5MILLwy53FBPND0xQq0n5yGAwP8KOPkJcL68eWQ5e4D4emg52d988u3rrqZyCJwlYHOM9scff8jYsWNlwYIFei8QtYTTjBkzMn2p8Ntvv+mvKFQMrL6Edus4/XmhYsWKcumll8rMmTP17UJNgKxcuVKuuOIKOXLkiBQtWlSeffZZufrqq3W7Jk6cmLHB+yWXXKK/MFHnOHmozc/fffddve9HvXr1ZPjw4body5cvF7Xs77p16+Ttt992dMlfm8enk31DWQggELsCKlmxcOMeGbfwL/l29XZJSf3f/WfVoZ7DWtc4V+5uXEkaV04I63dX0SyzFUlvhPMM4cazy7b9x6TVkLmRVD3La1gC2jHKswpS/a/66/CJFCmSP07OLV5QihWMd++GlJylgOkYjQQIAzNLgfSHLrUhZP/+/T1XMj0xPG8wN0TAAgGn36qxgMTaJvDFj7VdS8MQyFXAxhgtNTVVnn76aRk6dKiof1e/HFKHiodXrVol1atXz3D55ptv5MYbb9T7Wfz5559y3nnn5WoWyQkqBm/QoIH+p1y5cvLXX39lvHQUagJEJTvUUrWqrnPnzpUmTZpkqsrgwYP11xnqGDBggKgvNs48SpcunbH0VijtUC9mqRe+1KGSHCNHjpRChQqJSi5VqFAho4jVq1fLZZddptuk/s6pw8bx6ZQN5SCAAAJnCqhfDG8/cEwOHU+RogXipNw50f1iOJJltqLplVCTBm48uyirOi98lymBFGlbeAEwUrnsr1Ox3IKNu2Xcgk0yc03mRJ9KnrWuUU4n+ppULhVWos/5msZOiaZjNBIgsTPWwmopCZCwuDgZAQRExOl1VUH1rwCffPu3b2yuGW9v+aN3TT+8uKHw4IMPyqhRo3TiQyU0VKJgypQpWSZA1P3V3hUq+fH666/Lo48+6kaVzioz3ASI+qKjYcOGupxu3brJiBEjzipTJXtq1qwpa9eulZIlS8r27dslPj7zG5EPP/ywHDx4MOQ2PvPMM6K+KFHHk08+qZe4atasmU7AnHlUqVJFJz/UxvJqXxAnDhvHpxMulIEAAgh4JRDOMlvR1inUfSPdenbhBcBoe9Cd68MZg1XLFZXXO9QJaak3d2obO6WajtFIgMTOWAurpSRAwuLiZAQQENG/OGo9dG5Ia8pmB6bWmp3RuxlvYfh8RLnxFtXFZYv5vNXRVY9f3kfmx9tbkbm5eZXphxen26a+kLjmmmv0/++oJaLUlxBqySa1R0VWX4Co+6vzXn75Zbnppptk6tSpTlcpy/LCTYA899xzeuNxdSxcuFAaNWqUZbmDBg3S7VGHWmKrVatWjrXn/fffF5Vcatu2ragN0c881NctS5YskS1btkj58uUdua9t49MRFApBAAEEPBbIaZktJ6ti8gsQ9ezCC4BO9qYzZUXyFVLh/HHybuf60qxKGWcqQSlZCpiO0UiAMDCzFCABwsBAAIFIBKJZ+1UFHpO6NeHti0jgPb7GyXV0bf7km1/eRzcweXsrOj+3rjb98OJ0u+644w6ZNGmSXtbqq6++yig+pwTI559/LrfffrtcdNFFkpSU5HSVsiwv3ARI8+bNZd68eXqvkn379ullsLI61H4nap8QdaglsFQCyKljw4YN+msZ9c+ZTidPnpSyZcuK+t+c6hduXWwbn+G2n/MRQAABvwmcvsxWHkmT295eICn/t9RkNHUN5xnCrWcXXgCMpgedv5bfRYRn6vULeqZjNBIg4Y0PI2d/8skn0qlTJ/0W2qlTpzypQ3oCRK15rO6pNnuMG90sAAAgAElEQVRUD07nnnuufki677779CaKbh2mJ4Zb7aJcBGJBgLcuYqGXRfjkO+d+5pf30c0D/jsSnZ+bV9sWo1WqVElUmz799FO55ZZbMuhySoCo5aXUFxUquRDO8lDR9Eu4CZAyZcrIrl27pHbt2rJixYpsb62Wn0pISNB/3759e50McvJo3bq1/rJE7QXywAMPZBT94osv6oTL3XffLePGjXPslraNT8dgKAgBBBDwiYCpZwi37ssv3f0xsEhGhdYPJl/QMx2jkQAJbYwYPUslQO68806dAElJSfGkLukJkJxuph4SP/zwQylevHjYdVIDP6dj69atGesWJycnS2JiYtj34AIEEDAnEM4vf9WyV691qM2XH+a6K6I788l39mz88j6iIZVxEQ+S0fm5fbXphxen26c26D5x4oQsW7ZMJwvSj5wSIMuXL5f69etL/vz55dixY05XKcvywkmAqDqpdqlDfdny9ddf51jHokWLyuHDh6Vx48aivghx8lBfgaiXp3bs2KHrovYHUX6zZs0SlXxSy3OpF6xCPXiGCFWK8xBAwC8CXr9l7Zd2Z1cPU88Qbt6X2N/8qHOzf823zpkahPM7Gjf2RjH9DEECxJlxFHIp6kuKcA+1Zu4jjzyiEyDq4Udl7E4/zj///HCLzPV89UabWtf42muv1Q8q6sFo586dMmfOHL2J4u7du3UZLVq0kO++++6sDRNzu0EoCZb0MkiA5KbJ3yPgT4Gc1n5Vnyy3rnGu3N24kjSunMCeH/7swky1OvPhrdw5BaTdiAXs+XJG3/HL++gGM29vRefnxdWmH16cbqP6+mH//v0yf/58vfl5+pFTAuSLL76QW2+9VcqVKyfqpR0vjnASICpmV8tLqaNjx44yceLEHKuo2qESFGpD9FWrVjneHBXLq689ZsyYoZ8hVMJDPWeon6XXM9Sb8gwRqhTnIWCHQFCTBybfsvZ7z5uK9dy+bzi/XOYFQOdHqVtf+DhfUzMl+iFJZ/oZggSIx2Mv/WEq3NumJz3ODPrdWhZLrcVbokSJLKv5/9i7E/ivpvzx4+/6qr7tK6XFkgoVRWhByhIj+5DQIoNmGLvx0xhCvyHjh8ny+9mpbENjwvBT6RcVJVImhBTpb2kxUUrp+63/433m9/n+Wr7LZzn3nnPPfd3HYx6Tuvcsz3PO93vOfd97z/Lly+UXv/iFeXpLjzFjxpgATS4Hi5dctDgXgeQLbP3t13q1iqR5g2KpX1wj+RULvAZVLd40ePXuF6tlY8nmnCVC3PMl6oVVzsgJvICnt/xvNNeLF9tC+iaHfiLqnnvukYsuuqgs+coCILqx9yOPPGI+Bzt16lTbRSo3vVwCIBpwyDwgNXjwYBk3blylZdRz9Rrd0+Szzz6LpT75ZsIaIl85rkMgOQJVzT+P7dTcPETVs21TLx+iyuVGeBRPWSehpV09MBR1vjwA6Kb32dzjpah6NZl/wzFB3auIut9n2+qu1xAEQLJtKUvn6WLK5hHnZ7G2LveSJUtk3333NZ8MKG9jw6rqyOvrVQnx7wgggIBbgVwWb9WqieSyl6EGPx4Y3E0Ob7+z1UpG8ZRgLmly877w5uTprcINo07B9eLFdv1GjBght912m+y///7mM1iZuXpFAZC5c+fKoYceajbvHj16tPzud7+zXaSCAyC+vQFiE4g1hE1N0kLAP4Fc5p8+Bg98eMrav1Ytv0SurOLK19YDgLmsRZLS9rbLuWj5WjnmrunWkn3tyt7Sbpf61tJzmZBPD+i5XkMQAIm5J2YWU/q693HHHZdV7p9//rlMnz7dPN0wZMiQHa557LHHskrH9kknnHCCvPzyyybZr776Slq2bGktC9cDw1pFSAgBBBBIoEA+C4NsgyC2X/mO4inBfNPk5n1hnZ2ntwrzi+vq0OZoOoft0KGD2cvj3HPPNZ96rVGjhgmE6NxbPwnVsWNHw6sbpf/61782n3HSPfD0rYx89sLLp61yeQPEpz1A8qlrIdeE1j8LseBaBJImkM/8M6qHavKx8+Up63zK7uqaXAJeNtcQrvLN1jnftUi26Yd23vxl38sp971prVoTLz5UurYp/4s41jKJKSGfHtBzPUcjABJTp8tkM2DAAJkwYYJZUOn+Gv/5n/9p3qCo7HCxCXo2LNdcc43cfvvt5tQ5c+bIwQcfnM1lWZ3jemBkVUhOQgABBAIUKGTxVmun6nLQHo1l9pJ/Sunm/9uvKqo9X3JZvGT7lGC+aXLzvvDBwNNbhRvGkUKIczT9nJV+1krn5/pAz4knnmgCIfrfl19+uaxfv15ee+010Teg9aaE/r3uq3HGGWfEQW7yyCUAoufvvPPOsmrVKrOxu37iq6Jj9erVovug6KH1efbZZ2OrUxQZxd0/eTI3ilYkzTQKFDL/9OGzqj49ZZ20/uPqs1Gu8q2qffJdi1SVbsj/zhqi4tb16QG9uOdo26sQAHHwU0Dfmrj44otFN0QvLi4WffX+2muvrXAjcV8DIPrK/3/8x38YQQIgDjoSWSKAAAKWBWwt3p77dQ9ZsXaj/LixVKLa8yWKpwQLSbNFg2JevS6wP/L0VoGAMV3uevESVTUfffRRs6edBjvK22cisx9frVq1THBk6NChURWl3HRzDYD07t1bZsyYIXXr1hXd22+nnXYqN91Zs2ZJr169zL/ppuQ33XRTrPWynVkc/ZMnc223GumlXcDW/PPVyw93tieIT09ZJ7k/2fpsVK4GrvLdvpyFrEVsf1o4V0OX59t8EE0f3JsXyB4gNl1s7I0Sxxytsn5IAMTRKF23bp1cd911ct9998nmzZvNq/f6Nohuprj94WsApH///vLKK6+Y4mpHbtWqlTVN1wPDWkVICAEEEEiQQFIWb1E8JVhomqNO7ixXPfe+tdYO6dXrbFF4eitbKbfnhTxH07r9+c9/lhdffHGHzcB1nnvSSSeZPT/22GOP2Bsh1wDI73//e7n11ltNOWfPni3du3cvt8y6j4k+jKXHpEmTpF+/frHXzWaGUfdPnswtrLV4Y6Ywv1CvTsr8szJ/n56yDrWfhF6vQtcizw7vKZ1bNQydqcL6MQZ3pPFtbRX1HK2qzk8ApCqhiP/93XffNa/cv//+++ZphbPPPlvuuOMO0T1CMoePARD9BMA+++xjNoBs27atLF682KqU64FhtTIkhgACCCREIAkTxyieErSR5h5N68gX36231tIhbb6XLYrNp5RCenorW7+4zkvLHG3NmjWyYsUKKS0tlaZNm0qzZs3iIi43n1wDIPp2diboMXz4cPPWyvaHPoTVuXNnWbhwoTRq1MjUV/c/SfIRZf/kydz8egZvzOTnlqarkjD/rKw9bM5fbDxlnaa+E0pdbaxFdI8Ul29BuW6LEAKptg19e7s+yjlaNnYEQLJRivgcXVhp0OPmm2+Wn376yWymqE9s6WJFj7gDIC+99JL84he/qPBV+eXLl5t/nzdvnimflv3KK6+0quR6YFitDIkhgAACCRBIyuItismtrTSrVxPZauuTvFs9zTfvk34TJO9GT9CFoc3RjjzySKM/ePBgGTZsmLctkWsARCuS+QyWfv5q+vTp0rNnz23qp3v56Z5+eowcOVJuvPFGb+ufbcGi6p88mZttC2x7Hm/M5OeWpquSMv+srE18e8o6Tf0nlLraWos8fUEP6blX01BYcqoHQaQduXz72RTVHC3bjkIAJFupGM7ThY0GPaZMmWLeBjnkkEPM01off/yxnHXWWebvNFgS9aGv9eubHb/85S/NQkn/u3bt2mYjxddff92U6bvvvjPFOOyww8ymkPo9ZJuH64Fhsy6khQACCCRBwLcJUkVmUdwgt5Wm7gPy7ZoNBTd3//12lfvOObDgdJKYAAtA/1sttDmavvGgb0LofLa8T9G6apGZM2du8xkunYfr57f0OPTQQ+X888/fpmjnnnvuDkXVh5X0XH3Aql69eqKfxdI66n/rJu4PPviguUY/xatvpdevX99Vda3lG0X/5KZKfs3DGzP5uaXtqqTMPytrF9+esk5bHwqhvrbWImleQ2g/4GGFbUeDzQCzjQf0opij5TL+CYDkohXTuU888YRcddVVsnLlSvMWxkEHHWS+3RtnAGTp0qVV1lYDJA8//LB5Zd724Xpg2K4P6SGAAAK+CyRh8WZzEpf5xIC2S9ebp0iphVc3bL0BwtNb0+XT5T/mPWTS/gmAvOGyvDC0OZru7fHtt9+aAMABBxyQpUL0p2lAY+zYsVlnlNmkffsL9M3uQYMGiX7Sq7xDgx8vv/yytGvXLuu8fDqxU6dO2xRHH+JatGiR+btly5ZJ69atCy6uj4FZ3/fS4CZUwd0uNQkkYf5ZVWOEEMSpqo78e3QCUaxv6hcn+3OWhWgTfN9Wz6fgmus1BAGQQkZWhNeuXr1arrjiChk3bpwJfOiiJq4AyBtvvCH6v1mzZonu9aFPnOmiSZ8ca9OmjfTq1UuGDh26w2v0NjniHhi+LyJs2pIWAgggUJ5AEhZvUZRxyxaRY+6abq1TFLoXCDfveXrLWmeMKKG452gRVaMs2eOPP95s/v3UU0/JmWeeGXV2WadvKwCiGeqDTWPGjDGBDm2/mjVrmoDHGWecIb/97W+lTp06WZfLtxPjCID4cvMgKXtp8MaMb6PE7/JEMbdrt0u8b7PZvIFt4ylrv1uc0m0vEMIY8K1Vc/n8oq697hjQJdgN5H16iMP1GoIAiG8jdbvy/M///I/86U9/ko0bN5p/mTZtmucltlO8OAZGUhYRdkRJBQEEEKhcIAmLtyieElSVU+5701r30An09RM/kPU/5/7Jyjo1i+TZ4T2DnYDngszTW7loxXtuHHO0OGv0/PPPy+mnny5HHHFEaubZcfrGnZft/mnzd2MhmxvncjOnQ/N6cueArs5+l/h0syXu/kd+uQvYHGMugwe+BEpzbwGucC0Qxfqmaxv7X2lx7ZRr/nq/b/aSf8r42V/IpA+Xb/O2v/6sOLZTCxnUY3fp0baJedg81MOnhxJsz9FybTMCILmKcX4sAlEPjCQtImIBJxMEEEBARHxfvEXxhJTtN0Beu7K3fPPDBhk+fm5OQRANfjwwuJsc3n5n+uL/CuTyuzr0p7d86hRRz9Fc1HXIkCGin6DVty7uueceqVu3rotikKcFAdv9M4rfO7k+nZ60gLDvcwkL3YwkLAuE0GcI/FnuFClKzoffM6Fza6B1+ZoN8uPGUqlXq0iaNyiWNH0mzJfPUtqeo+XabwmA5CrG+bEIRDkwkraIiAWcTBBAAAER8X3xFsVTgtrwtvYA2frJQ27e2xlSPL1lx9FmKlHO0WyWM9u09HOz2s/uuusuWbBggdnb7sQTT5T9999fGjduLEVFRZUmpcETDn8EbPdP10/m+nLTItsWtvl7upA3ZrItL+f5IeD7/DMbJZ+ess6mvJzjj4DNn5su34LyR5SSlCfgw31Q23O0XFuaAEiuYpwfi0BUAyNpi4hYsMkEAQQQ+F+BJCzeonhKMIo0lZSb93aHVtqf3rKrmX9qUc3R8i9RYVdWr159m08fZPbdyyZV/WRCSUlJNqdyTkwCtvunyydzk/A7eftmdekVUxcjmwgEktjXy2PgXkMEnSMlSUa1FkkJH9XMUsD1A3q252hZVrvsNAIguYpxfiwCUQyMUCZWsTQAmSCAQGoFfF+8RfGUYBRpbt+BuHmf2iEVXMWjmKO5RNIASL6HBkBKS3Pf7yff/LiuagHb/dPlk7lx/G6qWjS3M1y/MZNbaTnbJwHf55/ZWvnwlHW2ZeU8fwSS+PPeHz1KkouAywf0bM/Rcqm3nksAJFcxzo9FIIqBwS+VWJqOTBBAIAABnxdvUQSzo0gzgG5AFRAoVyCKOZpL6qVLlxaU/e67717Q9VxsVyCK/unqyVxX+RbSIrwBUoge1/o8/8yldVw/ZZ1LWTnXDwHWIn60Q9pKEfcDelHM0XJpMwIguWhxbmwCUQyMJC4iYgMnIwQQQGA7AZ8Xb1q20+9/SzZs2pxzu+lm488O7ymdWzXc5tpQnjzMGYQLEMhRIIo5Wo5F4HQEKhSIon+6eIjK5psnce6lYbPcfMs+nQPd5/lnLi3i8inrXMrJuf4IsBbxpy0oSTQCUczRcikpAZBctDg3NgHbA8PmZDzORURs4GSEAAIIlCPg6+JNnxA8f+y7srEktwBIrZ2qy8NDD5LD2+9cbnuH8uQhnRmBKAVsz9GiLCtpp08giv7p4sncJL9JwUNn6Rt3tmvs6/wz33rG/ZR1vuXkOvcCrEXctwEliE4gijlaLqUlAJKLFufGJmB7YCR5EREbOhkhgAAClQj4sngr5Omo4p2qy4Tf9Nrh7Y+tqx3Kk4d0ZgSiErA9R4uqnKSbDoFOnTptU9FNmzbJokWLzN8tW7ZMWrdubQWikN89Fb15WFnBkryXhos3Zqw0Mol4KeDL/NNLHAoVpABrkSCblUqJiOs1BAEQuqGXArYHRpIXEV42EIVCAAEEHAjE9RRuaE8eOmgqsgxYwPYczSeqkpISeeGFF+S1116TDz74QP75z3+a4jVp0kQ6d+4sRx99tJx88smy0047+VTsVJclrgCIIsf5ZG6SH96K63d1qjs+lUcAgaAFWIsE3byprZzrNQQBkNR2Pb8rbntgJHkR4XdLUToEEEAgPgEXT5Xy5GF87UtOyRCwPUfzpdYTJ06USy65RL7++uuyIukNCD2qVatW9ne77rqr3HvvvXLKKaf4UnTKsZVA1P0zridzbX6+18VeGnG/McMgQAABBEIVYC0Sasumr15Rz9GqEiUAUpUQ/+5EwPbASPoiwkkjkCkCCCDgmQDfFfesQShOKgVsz9F8QLzrrrvk6quvNkXRoIcGPPbYYw9p3ry5+e8VK1bIF198Yf6cCYjccccdcvnll/tQfMoQYwAk00dmL/mnjJ/9hUz6cLmUbv5Xv9BDgw3Hdmohg3rsLj3aNtkmeJZrQyX9d16cb8zkasv5CCCAAAIIIBCvgOs1BAGQeNs7q9z027Xvvfdeua/eH3jggVKjRo2s0knySVEMDB8XERqY+faHDbLu51KpW7NIWjQslvrF4bdvkvsmZUcAATcCNgPZRdWryfwbjuHnrZumJNeEC0QxR3NJMnv2bDnssMNk8+bN0qBBA7nuuutk2LBh0qxZs22KtWrVKnnsscfklltukR9++EGKiopk5syZ0r17d5fFJ+/tBOLun1E+mevirUfbHSquN2Zsl5v0EEAAAQQQQMCuQNxztO1LTwDEbnsWlNqPP/4oo0aNkkceeURWr15dblqNGzeWX/3qV/KHP/xB6tevX1B+Pl8cxcDwZRGhTw/OWvKdjJ+1VCZ/tO1TY3pT7thOzc1TYz3bNi3oqbEo25fATZS6pI0AAuUJ8ClD+gUCfghEMUdzWbMBAwbIhAkTpGHDhvLmm29Kx44dKy3OwoULpVevXrJmzRo5/fTT5S9/+YvL4pO34wBIlA0Qyl4afMs+yl5C2ggggAACCCRDwPUaggCIJ/1EF1PHHXecaIfIvF5fUdH0tfw2bdrIpEmTZO+99/akBnaLEcXA8GERkctTUB2a15M7B3SVzq0a2sXNM7UQAjd5Vp3LEEDAA4H5y76XU+5701pJJl58qHRt08haeiSEQFoEopijubRr2bKlLF++XP74xz/Ktddem1VRRo8eLb///e/NJ7K++eabrK7hpHgEQuufoe2lEeUbM/H0MHJBAAEEEEAAgXwEXM/RCIDk02qWr/n++++lU6dOZQuozp07y9ChQ+WQQw7Z5tvD77zzjowdO1YWLFhgStCqVSvzmSx9Yi20I6qB4XIRkeTv4CY5cBPa2KA+CKRVgDdA0try1Ns3gajmaK7qWbt2bfn555/lrbfeyvpzVm+//bb07NlTatWqJT/99JOropNvOQKh9U+tYpLXEHRSBBBAAAEEEEBABVzP0QiAeNAPR4wYIbfddpv53NHNN99snijTP5d36FP4t956q/kElp7zb//2b+ZbxKEdUQ4MF4sIl4GXQvuGC69Cy8z1CCAQnoDNPUB0k9p57AESXiehRrEIRDlHi6UC22XStm1bWbp0aV4BEN0ofcmSJS6KTZ4VCITWPzPVzOVhpL2b15c7BnTx5i1yOisCCCCAAAIIIOB6jkYAxIM+uO+++8qnn34qZ555pjz11FNZleiss84y3xzWT2Dp57NCO6IeGHEuInz49Fa+/SPJgZt868x1CCDgr8BFT86VVxZ8W3AB+++3q9x3zoEFp0MCCKRRIOo5WtymF154odl/Tx8wuuaaa7LKXh9c0geYzjvvPHn44YezuoaT4hEIrX9urcZeGvH0IXJBAAEEEEAAAfsCrudoBEDst2nOKdapU0c2btwor7zyihx77LFZXa/7f/ziF7+Q4uJiWb9+fVbXJOmkOAZGXIsIXzZfz7X9kxy4ybWunI8AAskQSOrP02ToUkoEshOIY46WXUnsnPXJJ59It27dpGbNmjJ79mzp0KFDpQnrQ0s9evSQTZs2ybvvvhvsfnx2dONPJbT+WZEge2nE37fIEQEEEEAAAQTyF3A9RyMAkn/bWbtSN1BctWqVWUQdcMABWaU7b948s1hr1qyZrFixIqtrknRS3AMjykVEUp9Y5kZjkkYMZUUgHQIEZtPRztTSb4G452hxaLz66qty9tlnm6xuuOEGGTJkiDRp0mSbrFevXi3jxo2TUaNGyebNm+XJJ580DyNx+CUQYv/0S5jSIIAAAggggAACuQu4nqMRAMm9zaxfcfTRR8u0adPk6aeflgEDBmSV/rPPPisDBw6Uvn37ytSpU7O6JkknuR4YtqxsfrO+qHo1mR/jN+uTGrix1XakgwACfgrwaT4/24VSpUcglDlapsWOPPJI88evvvpKFi1aZPbY0//tueeesssuu5g/L1++XD7//HPRIKwe7du3l5YtW1bY6HpNiPNzH3t5p06dtimWvpmj7ajHsmXLpHXr1j4WmzIhgAACCCCAAAKpEnC9hiAA4kF3e+6558z+H/o6/cyZM6V69eqVlkqfOjv00ENlzpw5Zs8QvTa0w/XAsOW5aPlaOeau6baSk9eu7C3tdqlvLb2KEkpy4CZyHDJAAAHnAjMWrZTh4+fK+p9Lsy5LnZpF8sDgbnJ4+52zvoYTEUBgR4FQ5miZmum8WwMWemQCHFW1e0Xn699rGvr/paXZ/3yqKj/+vWIBAiD0DgQQQAABBBBAwH8B12sIAiCe9JFf/epX8thjj8kJJ5wgDz74oLRo0aLckukTaMOHD5cXX3xRhg0bZjZtDPFwPTBsmc5f9r2cct+btpKTiRcfKl3bNLKWXkUJJTVwEzkMGSCAgDcC+ibIlc/Ol0+X/1hlmfZuXl/uGNBFOrdqWOW5nIAAApULhDJHy9SyT58+ZQEQm22vb3dzxC8QWv+MX5AcEUAAAQQQQAAB+wKu52gEQOy3ac4p6veE9bjvvvvknXfeMRub9+vXTw4++OBtXr3Xf5s8ebLZMP2ggw6Siy++uNK89PvFST1cDwxbbkkNJCQ1cGOr3UgHAQSSIaBPWs9e8k8ZP/sLmfThcind/K/P0+ixU/VqcmynFjKox+7So22TSG5wJkOJUiJgVyCUOZpdFVLzRYD+6UtLUA4EEEAAAQQQQOD/BFzP0QiAeNAbt371XouTeXW+vKJV9m9bn6+v3peUlHhQu/yK4Hpg5FfqHa+y+SkpvZk3L6Y9QJIauLHVbqSDAALJE9Cft8vXbJAfN5ZKvVpF0rxBsdQvrpG8ilBiBDwXCGWO5jkzxctTgP6ZJxyXIYAAAggggAACEQq4nqMRAImwcbNNuqo9P7JNZ/sASJK/Pex6YORjXtE1SdxMPKmBG5vtRloIIIAAAgggsKNASHM02jc8AfpneG1KjRBAAAEEEEAg+QKu52gEQDzoQ0uXLo2kFLvvvnsk6caRqOuBYbOOby1eJWc/9HbBST59QQ/puVfTgtPJNoEkBm6yrRvnIYAAAggggEB+AiHN0fIT4CqfBeifPrcOZUMAAQQQQACBtAq4nqMRAElrz/O83q4Hhk0e/WzZsX+entVGvRXlqxv4vnr54bF+wz6pgRubbUdaCCCAAAIIILCtQEhzNNo2PAH6Z3htSo0QQAABBBBAIPkCrudoBECS34eCrIHrgWEb9YOvfpABD8yS9T+X5px0nZpF8uzwntK5VcOcry3kgqQGbgqpM9cigAACCCCAQOUCoc3RaO+wBOifYbUntUEAAQQQQACBMARcz9EIgITRj4KrheuBEQXojEUrZfj4uTkFQTT48cDgbnJ4+52jKFKVaSYxcFNlpTgBAQQQQAABBPIWCHGOljcGF3onQP/0rkkoEAIIIIAAAgggIK7naARA6IReCrgeGFGhaEDhymfnZ/U5LP3s1R0DusT+5sf2dU9i4Caq9iNdBBBAAAEE0i4Q6hwt7e0aSv3pn6G0JPVAAAEEEEAAgZAEXM/RCIB41JsWLlwoDz74oMyYMUOWLFkia9eulc2bN1dawmrVqklJSYlHtbBTFNcDw04tyk9FPy01e8k/ZfzsL2TSh8uldPOWshN3ql5Nju3UQgb12F16tG0S654fldU5iYGbKNuQtBFAAAEEEEirQMhztLS2aUj1pn+G1JrUBQEEEEAAAQRCEXA9RyMA4klPGj16tNxwww1SWloqeoM820MDIHpNaIfrgRGX59oNm2T5mg3y48ZSqVerSJo3KJb6xTXiyj6nfJIYuMmpgpyMAAIIIIAAAlUKpGWOViUEJ3gpQP/0slkoFAIIIIAAAgikXMD1HI0AiAcd8LnnnpMzzzzTlKR69epy2GGHSZcuXaRRo0bmv6s6Ro4cWdUpift31wMjcWAxFzhJgZuYacgOAQQQQACBoAWYowXdvImrXKdOnbYp86ZNm2TRokXm75YtWyatW7dOXJ0oMAIIIIAAAgggEJqA6xgYAYwAACAASURBVDUEARAPepQGPN566y1p1aqVvPLKK7Lffvt5UCq3RXA9MNzWntwRQAABBBBAAAE/BZij+dkuaS0VAZC0tjz1RgABBBBAAIEkCbheQxAA8aC3NGjQQNatWyePPPKInHvuuR6UyH0RXA8M9wKUAAEEEEAAAQQQ8E8g6XO077//XqZPn25g27RpIwcccEDWyO+9955o/fXo27ev1K9fP+trOTEegaT3z3iUyAUBBBBAAAEEEIhXwPUcjQBIvO1dbm5NmzYVXYzNnTtXunbt6kGJ3BfB9cBwL0AJEEAAAQQQQAAB/wSSPke76KKL5IEHHpC6devK22+/Lfvuu2/WyB999JH06NHDPLh02WWXyZ133pn1tZwYj0DS+2c8SuSCAAIIIIAAAgjEK+B6jkYAJN72Lje3nj17ypw5c2Ty5Mly1FFHeVAi90VwPTDcC1ACBBBAAAEEEEDAP4Ekz9GWL19u3vooLS2Vu+66Sy699NKcge+55x4T/KhZs6Z5G6RZs2Y5p8EF0QkkuX9Gp0LKCCCAAAIIIICAWwHXczQCIG7b3+R+//33iz6NdvHFF4suqjjELCh1gaoHGxjSIxBAAAEEEEAAAT8EkjxH06DHVVddZTbGXrJkiey00045o5aUlEi7du3M/DTfIErOmXJB1gJJ7p9ZV5ITEUAAAQQQQACBhAm4nqMRAPGgw2zatEmOPvpomT17tkyYMEFOPPFED0rltgiuB4bb2pM7AggggAACCCDgp0CS52gnnXSSvPzyy+bNDw1e5HtoEEWv1/QmTpyYbzJcF4FAkvtnBBwkiQACCCCAAAIIeCHgeo5GAMSLbiBmD5ChQ4eaRdnAgQNlwIAB0qFDB6lTp06VJdxtt92qPCdpJ7geGEnzorwIIIAAAggggEAcAkmeo+2xxx7mzY3nn39eTj755Ly5XnjhBTn11FNl9913l88//zzvdLjQvkCS+6d9DVJEAAEEEEAAAQT8EHA9RyMA4kc/MKWYOnWqnH322bJq1aqsS1WtWjXRV/FDO1wPjNA8qQ8CCCCAAAIIIGBDIMlztPr168v69evNW9cHH3xw3hy6d59uhq4bqa9duzbvdLjQvkCS+6d9DVJEAAEEEEAAAQT8EHA9RyMA4kc/kMsvv7xs/48tW7ZkXSoNgOhGjqEdrgdGaJ7UBwEEEEAAAQQQsCGQ5Dmavlm9ceNGmTVrlhxyyCF5c7zzzjvSvXt3KS4uNgEVDn8Ektw//VGkJAgggAACCCCAgF0B13M0AiB22zOv1J544gkZMmSIubZBgwbmlfr9999fGjVqJNWrV68yTf10VmiH64ERmif1QQABBBBAAAEEbAgkeY6mn6zS8hf6CawXX3xRTjnlFLOZ+pdffmmDlTQsCSS5f1oiIBkEEEAAAQQQQMA7AddzNAIgHnQJfYJMnyTbZ599ZNq0adK8eXMPSuW2CK4HhtvakzsCCCCAAAIIIOCnQJLnaH369JEZM2bIZZddJnfeeWfewJlN0A8//HB544038k6HC+0LJLl/2tcgRQQQQAABBBBAwA8B13M0AiAe9IOGDRvKjz/+KE8//bTZ/JxDzNN5bdq0MRS6WaU+YceBAAIIIIAAAggg4FYgyXO0UaNGyciRI2WXXXaRxYsXmz08cj3WrVsne+21l6xcudKkdcMNN+SaBOdHKJDk/hkhC0kjgAACCCCAAAJOBVzP0QiAOG3+f2XerFkzWb16tcydO1e6du3qQYncF8H1wHAvQAkQQAABBBBAAAH/BJI8R/vkk0+kc+fOsnnzZjnvvPPkoYceyhn4wgsvlIcffliKiorkgw8+kL333jvnNLggOoEk98/oVEgZAQQQQAABBBBwK+B6jkYAxG37m9wPO+wwsxnjyy+/LMcdd5wHJXJfBNcDw70AJUAAAQQQQAABBPwTSPocbdiwYTJ27FipVq2a6J/HjBmT1ZsgP/30k1x++eUmaKLXDh48WB5//HH/GijlJUp6/0x581F9BBBAAAEEEAhUwPUcjQCIBx3rkUcekQsuuMAspHRBxsEnsOgDCCCAAAIIIICAjwKuFy+Fmvzwww/So0cP0bdBNJDRokULMw/v37+/eRO7Ro0aZVls2rRJ5s+fbx5S0rc+vvnmG9myZYt560MfXmrUqFGhxeF6ywJJ75+WOUgOAQQQQAABBBDwQsD1HI0AiBfdQOSkk04yiyt9Cu23v/2tJ6VyVwzXA8NdzckZAQQQQAABBBDwVyCEOdoXX3whJ554onz44YcmCJI5qlevLro3n+4Nont9aLBEP5elhwY+9OjYsaO89NJLsueee/rbSCkqWadOnbaprQatFi1aZP6OfQRT1BGoKgIIIIAAAgh4LeB6DUEAxIPuMX36dPn555/l+uuvlzlz5kj37t1l4MCB0qFDB6lTp06VJezdu3eV5yTtBNcDI2lelBcBBBBAAAEEEIhDIJQ52oYNG2TEiBHmk1br16/fhk6DIpmAR+Yfateubd4UufXWW0X/zOGHAAEQP9qBUiCAAAIIIIAAApUJuF5DEADxoH/q02ZbP32WS5H0upKSklwuScS5rgdGIpAoJAIIIIAAAgggELNAaHO07777Tp555hl544035P3335dVq1bJ2rVrpX79+tKsWTPp0qWLHHHEEebhpKZNm8asTXa5CoTWP3OtP+cjgAACCCCAAAI+CrieoxEA8aBXaAAk30MDIKWlpfle7u11rgeGtzAUDAEEEEAAAQQQcCjAHM0hPllXKUD/rJKIExBAAAEEEEAAgdgFXM/RCIDE3uQ7ZqhPnBVy6FNpoR2uB0ZontQHAQQQQAABBBCwIZDkOdqKFStkl112scFAGp4KJLl/ekpKsRBAAAEEEEAAgYIFXM/RCIAU3IQkEIWA64ERRZ1IEwEEEEAAAQQQSLpAkudoNWvWlH79+smQIUPk5JNPllq1aiW9OSj/dgJJ7p80JgIIIIAAAgggEKqA6zkaAZBQe1bC6+V6YCScj+IjgAACCCCAAAKRCCR5jrb1vnsNGjSQM844QwYPHiyHH354JFYkGr9Akvtn/FrkiAACCCCAAAIIxCPgeo5GACSediaXHAVcD4wci8vpCCCAAAIIIIBAKgSSPEfTQMdbb70lW7ZsMW2le+npsfvuu5u3QgYNGiTt2rVLRTuGWskk989Q24R6IYAAAggggAACrudoBEA864Nr1qyRCRMmyKxZs+Tbb7+V9evXy6OPPmoWZpnj66+/lu+//16Ki4ulbdu2ntXATnFcDww7tSAVBBBAAAEEEEAgLIGkz9GWLl0q48ePlyeffFI++eSTssbJBEN69OghQ4cOlQEDBkijRo3CarwU1Cbp/TMFTUQVEUAAAQQQQCCFAq7naARAPOp09913n1x33XWydu1aUyp9Ok0XYwsWLJCOHTuWlfTpp5+Wc845xwRAtAM1adLEo1rYKYrrgWGnFqSCAAIIIIAAAgiEJRDSHO2dd94xwZBnnnlGVq1aZRoqEwjR/UL69+9v3gzR/y8qKgqrIQOtTUj9M9AmoloIIIAAAgggkEIB13M0AiCedLobb7xRRo0aZYIeuiHjfvvtJ++++265AZDNmzdLmzZtzBsi999/v1xwwQWe1MJeMVwPDHs1ISUEEEAAAQQQQCAcgRDnaCUlJfLqq6+aYMhLL70kGzZs2CYY0rRpUznrrLPMfiEHHXRQOI0ZYE1C7J8BNhNVQgABBBBAAIGUCbieoxEA8aDDzZs3r2wxpW923HPPPdKwYUPJbNS4/RsgWuTLL79c7r77bjn99NPl2Wef9aAWdovgemDYrQ2pIYAAAggggAACYQiEPkfTz9E+99xzJhgyY8aMHfYL2Xvvvc0nsnTO3rp16zAaNaBahN4/A2oqqoIAAggggAACKRJwPUcjAOJBZzvvvPPk8ccfl169esnMmTPLSlRZAOQvf/mLeRJNF2ELFy70oBZ2i+B6YNitDakhgAACCCCAAAJhCKRpjvbll1+W7Rfy8ccflzWgfiZL/9e3b1+ZMmVKGA0bSC3S1D8DaTKqgQACCCCAAAIpEHA9RyMA4kEn22uvveSLL74wmzEOHDgwqwDI22+/LT179pR69eqJPqkW2uF6YITmSX0QQAABBBBAAAEbAmmdo+mnaTP7haxcudJQahCktLTUBitpWBJIa/+0xEcyCCCAAAIIIIBAJAKu52gEQCJp1twSrVOnjmzcuNHs+XHAAQdkFQCZP3++HHjggVKjRg1zbWiH64ERmif1QQABBBBAAAEEbAikdY723nvvybhx48yG6RoA0X37CIDY6FF200hr/7SrSGoIIIAAAggggIBdAddzNAIgdtszr9QaNWoka9eulVmzZskhhxySVQDkv//7v6V///6y8847y/Lly/PK1+eLXA8Mn20oGwIIIIAAAggg4EogTXO0ZcuWmTe09c2PrT+BpcEP/VTtUUcdJZMmTXLVFORbjkCa+icdAAEEEEAAAQQQSIqA6zkaARAPekrnzp3NPh4PP/ywDBs2LKsAyBVXXCFjxowxn8F68803PaiF3SK4Hhh2a0NqCCCAAAIIIIBAGAKhz9H0oaQJEyaYoMf06dPLNkHXoIceHTt2lMGDB8ugQYOkVatWYTRqQLUIvX8G1FRUBQEEEEAAAQRSJOB6jkYAxIPOdumll8q9994rhx12mFloZY6KNkFfsmSJdO3aVdatWyfXX3+93HjjjR7Uwm4RXA8Mu7UhNQQQQAABBBBAIAyBEOdomzdvlldffdUEPV588UXZsGGDaaxM0KNZs2Zmn74hQ4bIQQcdFEZDBlqLEPtnoE1FtRBAAAEEEEAgRQKu52gEQDzobJ9++qnoWyC6ieLWAY3yAiC6T4guwDQIUlxcLIsXL5Zdd93Vg1rYLYLrgWG3NqSGAAIIIIAAAgiEIRDSHG3u3Lk7bGyeCXrUrFnTfG5Wgx76/zvttFMYDRh4LULqn4E3FdVDAAEEEEAAgRQJuJ6jEQDxpLONGjVKRo4caTZT1CfLfvnLX8q1115r/vv222+XTZs2yeTJk+X1118vK/Fdd90l+vZIiIfrgRGiKXVCAAEEEEAAAQQKFUj6HO3LL78s29fjk08+MRyZoIf+WffjGzp0qHngqHHjxoVycX3MAknvnzFzkR0CCCCAAAIIIBCLgOs5GgGQWJo5u0xuuOEGueWWW0Rfw9fAR3mHLtD03/RcDZiEergeGKG6Ui8EEEAAAQQQQKAQgSTP0fr27SszZszYYV+P3XbbzezpoW97dOjQoRAero1ZoFOnTtvkqA+NLVq0yPydbmLfunXrmEtEdggggAACCCCAAALbC7heQxAA8axP6ieuRo8ebb5DvH79+m1Kp6/iH3XUUXLddddJr169PCu53eK4Hhh2a0NqCCCAAAIIIIBAGAJJnqPp52UzR7169cwb1xr00MAIRzIFCIAks90oNQIIIIAAAgikS8D1GoIAiKf9raSkRD766CNZsWKF2RukadOmohP82rVre1piu8VyPTDs1obUEEAAAQQQQACBMASSPEcrKioyDxNp0OO0006TOnXqhNEo1KJMIMn9k2ZEAAEEEEAAAQRCFXA9RyMAEmrPSni9XA+MhPNRfAQQQAABBBBAIBKBJM/Rvv76a2nZsmUkLiTqh0CS+6cfgpQCAQQQQAABBBCwL+B6jkYAxH6b5pzizTffbK656KKLpFmzZlldv3r1arnnnnvMubofSGiH64ERmif1QQABBBBAAAEEbAiEOkdbuHChvP/++/Ldd9/JmjVrpEGDBuYN7C5dusi+++5rg440YhAItX/GQEcWCCCAAAIIIIBAZAKu52gEQCJr2uwT1u8R68bmCxYskI4dO2Z14eLFi6V9+/bmOv1EVmiH64ERmif1QQABBBBAAAEEbAiENEfTuowZM0bGjh1rAh8VHU2aNJFzzz1XLr30UmnTpo0NRtKISCCk/hkREckigAACCCCAAAKxC7ieoxEAib3Jd8yQAMiOJq4HhgfdgiIggAACCCCAAALeCYQyR3vggQfkqquukp9++km2bNlSpbM+dFRcXCz/8R//Ib/5zW+qPJ8T3AiE0j/d6JErAggggAACCCAQjYDrORoBkGjaNadU8wmAfPzxx+ZtkZo1a8qGDRtyyi8JJ7seGEkwoowIIIAAAggggEDcAiHM0a655hq54447DJ0GP2rXri29e/eWAw88UJo3by5169aVH3/8UZYvXy7vvfeezJgxwwRK9NBAyOWXX152fdz+5Fe5QAj9kzZGAAEEEEAAAQRCE3A9RyMA4kGPyicA8swzz8jZZ58trVq1kmXLlnlQC7tFcD0w7NaG1BBAAAEEEEAAgTAEkj5He/jhh+XCCy80jVGvXj0ZOXKkXHDBBWbPj4oO3RNE3xgZNWqUCYxoEOS//uu/ytIJo2XDqEXS+2cYrUAtEEAAAQQQQACBbQVcz9EIgDjokePGjdsmV/2msC6k/v3f/90ENCo7Nm7cKLr/x6OPPmq+VXzyySfL888/76AW0WbpemBEWztSRwABBBBAAAEEkimQ5DnaDz/8IO3atTNz6N12202mTp0qe+21V9YN8dlnn8nRRx8tX375pei+IDonb9iwYdbXc2L0Aknun9HrkAMCCCCAAAIIIOBGwPUcjQCIg3bPvPGRyTrz3WENgmR76DWaji7cjjjiiGwvS8x5rgdGYqAoKAIIIIAAAgggEKNAkudo9913n1xyySVSo0YNmTt3rnTu3DlnuX/84x9y0EEHSWlpqdlA/be//W3OaXBBdAJJ7p/RqZAyAggggAACCCDgVsD1HI0AiIP218BFIYfu+3HwwQfLiBEj5Pjjjy8kKW+vdT0wvIWhYAgggAACCCCAgEOBJM/RdN48adIkGTJkiDz22GN5Kw4dOlTGjx8vxx13nLzyyit5p8OF9gWS3D/ta5AiAggggAACCCDgh4DrORoBEAf9YOnSpWW56pscbdu2NZ/A0gVZ+/btKyyRnlNcXCxNmzaVoqIiByX/V5a6ceTtt99elv+0adOkT58+VsvjemBYrQyJIYAAAggggAACgQgkeY625557ms9XPffcc3Laaafl3SL6+dnTTz/dfEbriy++yDsdLrQvkOT+aV+DFBFAAAEEEEAAAT8EXM/RCIB40A/y2QTdVbHff/9989p/SUkJARBXjUC+CCCAAAIIIICAIwHXi5dCql2nTh3R/fTmzJkj3bp1yzupd999Vw455BCpXbu2rFu3Lu90uNC+QJL7p30NUkQAAQQQQAABBPwQcD1HIwDiRz9IRCk2b94sPXr0kHfeeUd22WUXWbFihSk3b4AkovkoJAIIIIAAAgggULCA68VLIRVo1KiRrF27VmbMmCG9evXKO6m33npLDjvsMGnQoIF8//33eafDhfYFktw/7WuQIgIIIIAAAggg4IeA6zkaARA/+kEiSvHnP/9ZrrjiCtlnn33k1FNPlVtvvZUASCJajkIigAACCCCAAAJ2BFwvXgqpxd577y2fffaZPPTQQ3LeeeflndSjjz4q559/vvl07SeffJJ3OlxoXyDJ/dO+BikigAACCCCAAAJ+CLieoxEA8aMfeF+KZcuWSceOHeXHH380b3y8/vrrctNNNxEA8b7lKCACCCCAAAIIIGBPwPXipZCaDB48WJ588kk56qijZMqUKXkndfTRR5v58FlnnSVPPPFE3ulwoX2BJPdP+xqkiAACCCCAAAII+CHgeo5GAMSPfuB9KU488UT5+9//LkOHDpXHH39cbrzxRgIg3rcaBUQAAQQQQAABBOwKuF68FFKbCRMmyIABA6RatWryzDPPyBlnnJFzcs8++6wMHDiwoDRyzpQLshZIcv/MupKciAACCCCAAAIIJEzA9RyNAEjCOoyL4upC78wzz5QmTZrIxx9/LDvvvDMBEBcNQZ4IIIAAAggggIBjAdeLl0Kqr/vZ7bfffrJw4UKpVauWjBs3LqcgiM6J9WGgn3/+Wfbdd19ZsGCBCYRw+COQ5P7pjyIlQQABBBBAAAEE7Aq4nqMRALHbnsGlphs76gLv22+/Nd9L1u8d68EbIME1NRVCAAEEEEAAAQSqFHC9eKmygFWcMHPmTDnmmGNMEEOPE044QS677DLp27dvucGMLVu2yNSpU+Xuu++Wl19+WfS/NXiin9DSjdA5/BJIev/0S5PSIIAAAggggAACdgRcz9EIgNhpx2BTufDCC03go1evXqILxsxTboUGQLTjV3Z88803csghh5hTdP+R1q1bB2tMxRBAAAEEEEAAgaQIuF682HDST2ENGjTIBEEyc9s6depIly5dpEWLFlK3bl2z750+APSPf/xD1q9fb7LV4EeNGjVk/Pjx5lNaHP4JhNA//VOlRAgggAACCCCAQGECrudoBEAKa7+gr9aAR+/evaWoqEjee+8988mAzFFoACSXzwUQAAm6m1E5BBBAAAEEEEiQgOvFiy2qefPmiW6K/tFHH5UlWd78VIMemWOfffYxwY9u3brZKgbpWBYIpX9aZiE5BBBAAAEEEEDAqYDrORoBEKfN72/m+kRc165dzTeSf/e738mf/vSnbQpLAMTftqNkCCCAAAIIIIBAVAKuFy8266XBjRdffNHsBTJjxgxZtWrVDsk3a9bMfOpK9/446aST2PPDZgNEkFZI/TMCHpJEAAEEEEAAAQScCLieoxEAcdLs/meaCXDstttu5sk4/RTA1kehARA+geV/H6CECCCAAAIIIIDA9gKuFy9RtsjXX39tgiBr166V+vXrS9OmTaVVq1ZRZknalgVC7p+WqUgOAQQQQAABBBCITcD1HI0ASGxNnZyMPv74Y/MNZH0L5IUXXjBPu21/FBoAqUrD9cCoqnz8OwIIIIAAAgggkEYB5mhpbPXk1Jn+mZy2oqQIIIAAAgggkB4B13M0AiDp6WtZ13T48OHy4IMPStu2beWPf/xjudfp5pF//etfzb9df/310rFjR/PnE088cYe3RbLOeKsTXQ+MfMrMNQgggAACCCCAQOgCzNFCb+Fk1a9Tp07bFHjTpk2yaNEi83fsI5istqS0CCCAAAIIIBCugOs1BAEQj/qW7rehgQf9BvGSJUvM6/ebN2+utIS6WWNJSYnVWpx77rkyduzYvNL8/PPPZY899sjr2q0vcj0wCq4ACSCAAAIIIIAAAgEKMEcLsFETXCUCIAluPIqOAAIIIIAAAqkRcL2GIADiSVe78847ZcSIESaYoRsyZntoAKS0tDTb07M6jwBIVkychAACCCCAAAIIpE7A9eIldeBUOCcB+mdOXJyMAAIIIIAAAgjEIuB6jkYAJJZmrjyTV199VY4//nhzkgY0unfvLt26dZMmTZpI9erVqyzhyJEjqzzH9gnsAWJblPQQQAABBBBAAAH/BVwvXvwXooQuBeifLvXJGwEEEEAAAQQQKF/A9RyNAIgHPfO4446TyZMnS+PGjeXFF1+UQw891INSVV4EAiDeNxEFRAABBBBAAAEErAu4XrxYrxAJBiVA/wyqOakMAggggAACCAQi4HqORgDEg47UrFkzWb16tehnsC677DIPSlR1EQiAVG3EGQgggAACCCCAQGgCrhcvoXlSH7sC9E+7nqSGAAIIIIAAAgjYEHA9RyMAYqMVC0yjTp06snHjRpkzZ4759FUSDgIgSWglyogAAggggAACCNgVcL14sVsbUgtNgP4ZWotSHwQQQAABBBAIQcD1HI0AiAe9qH379rJkyRKZOXOm9OzZ04MSVV0EAiBVG3EGAggggAACCCAQmoDrxUtontTHrgD9064nqSGAAAIIIIAAAjYEXM/RCIDYaMUC07jyyitlzJgxctttt8nVV19dYGphXO56YIShSC0QQAABBBBAAAG7AszR7HqSml0B+qddT1JDAAEEEEAAAQRsCLieoxEAsdGKBabx9ddfy/777y81atSQefPmSYsWLQpMMfmXux4YyRekBggggAACCCCAgH0B5mj2TUnRngD9054lKSGAAAIIIIAAArYEXM/RCIDYaskC03nzzTfl1FNPlXr16sm9994rxx9/fIEpJvty1wMj2XqUHgEEEEAAAQQQiEaAOVo0rqRqR4D+aceRVBBAAAEEEEAAAZsCrudoBEBstmaeaR155JHmSn0T5NNPP5Vq1apJo0aNRPcG0Q3SKzv03KlTp+aZs7+XuR4Y/spQMgQQQAABBBBAwJ1AqHO0hQsXyoMPPigzZswwe/OtXbtWNm/eXOU8vKSkxF1jkPMOAqH2T5oaAQQQQAABBBBIsoDrORoBEA96T/Xq1U3QQ48tW7ZkVSI9X8/V/y8tLc3qmiSd5HpgJMmKsiKAAAIIIIAAAnEJhDhHu/POO2XEiBGiwYxs5+LqHeo8PK6+FEU+IfbPKJxIEwEEEEAAAQQQiFPA9RyNAEicrV1BXn369CkLgORTnGnTpuVzmdfXuB4YXuNQOAQQQAABBBBAwJFAaHO0V199tezTsxrQ6N69u3Tr1k2aNGki+pBSVcfIkSOrOoV/j1EgtP4ZIx1ZIYAAAggggAACkQm4nqMRAImsaUm4EAHXA6OQsnMtAggggAACCCAQqkBoc7TjjjtOJk+eLI0bN5YXX3xRDj300FCbLhX1Cq1/pqLRqCQCCCCAAAIIBC/geo5GACT4LpbMCroeGMlUo9QIIIAAAggggEC0AqHN0Zo1ayarV68W/QzWZZddFi0eqUcuEFr/jByMDBBAAAEEEEAAgRgEXM/RCIDE0MhkkbuA64GRe4m5AgEEEEAAAQQQCF8gtDlanTp1ZOPGjTJnzhzz6SuOZAuE1j+T3RqUHgEEEEAAAQQQ+JeA6zkaARB6opcCrgeGlygUCgEEEEAAAQQQcCwQ2hytffv2smTJEpk5c6b07NnTsS7ZFyoQWv8s1IPrEUAAAQQQQAABHwRcz9EIgMTYC7788suy3HbbbbeyP2/99/kUZ+u08rne9rDZSAAAIABJREFUx2tcDwwfTSgTAggggAACCCDgWiC0OdqVV14pY8aMkdtuu02uvvpq17zkX6BAaP2zQA4uRwABBBBAAAEEvBBwPUcjABJjNygqKjK5VatWTUpKSspyzvx9PkXZPq180vDxGtcDw0cTyoQAAggggAACCLgWCG2O9vXXX8v+++8vNWrUkHnz5kmLFi1cE5N/AQKh9c8CKLgUAQQQQAABBBDwRsD1HI0ASIxdoXr16mUBkNLS0rKcM3+fT1E0ALJ1Wvmk4eM1rgeGjyaUCQEEEEAAAQQQcC0Q4hztzTfflFNPPVXq1asn9957rxx//PGumck/T4EQ+2eeFFyGAAIIIIAAAgh4I+B6jkYAJMauMHbs2LLchg4dWvbnrf8+n+JsnVY+1/t4jeuB4aMJZUIAAQQQQAABBFwLhDZHO/LIIw2pvgny6aefmje1GzVqJLo3iG6QXtmh506dOtV1k5D/VgKh9U8aFwEEEEAAAQQQCEHA9RyNAEgIvSjAOrgeGAGSUiUEEEAAAQQQQKBggdDmaPomtgYy9NiyZUtWPnq+nhvqm9hZIXh6Umj901NmioUAAggggAACCOQk4HqORgAkp+bi5LgEXA+MuOpJPggggAACCCCAQJIEQpuj9enTpywAkk87TJs2LZ/LuCYigdD6Z0RMJIsAAggggAACCMQq4HqORgAk1uYms2wFXA+MbMvJeQgggAACCCCAQJoEmKOlqbWTV1f6Z/LajBIjgAACCCCAQPgCrudoBEDC72OJrKHrgZFINAqNAAIIIIAAAghELMAcLWJgki9IgP5ZEB8XI4AAAggggAACkQi4nqMRAImkWStOdPr06dZz7N27t/U0XSfoemC4rj/5I4AAAggggAACPgowR/OxVShTRoD+SV9AAAEEEEAAAQT8E3A9RyMAEnOf2HqjRRtZ6+aLJSUlNpLyKg3XA8MrDAqDAAIIIIAAAgh4IsAczZOGoBjlCtA/6RgIIIAAAggggIB/Aq7naARAYu4TmQDIli1brOSsAZDS0lIrafmUiOuB4ZMFZUEAAQQQQAABBHwRSOoc7csvvywj3G233cr+vPXf52O8dVr5XM81dgWS2j/tKpAaAggggAACCCDgl4DrORoBkJj7QyYAUlxcLCeffLIcc8wxon9XyDF06NBCLvfyWtcDw0sUCoUAAggggAACCDgWSOocraioyMht//Z05u/zYQ31Tex8LHy5Jqn90xc/yoEAAggggAACCEQh4HqORgAkilatJM2GDRvK2rVryxZgzZs3l7PPPlsGDx4sXbp0ibk0/mbnemD4K0PJEEAAAQQQQAABdwJJnaNlHjja/u3pQh5ECvVNbHe9q/Cck9o/C685KSCAAAIIIIAAAv4KuJ6jEQCJuW9s2LBBXnjhBRk/frxMnjzZ7N+hiyc9OnfubAIhGhBp2bJlzCXzKzvXA8MvDUqDAAIIIIAAAgj4IZDUOdrYsWPLALd+e3rrv89HOMQ3sfNx8OWapPZPX/woBwIIIIAAAgggEIWA6zkaAZAoWjXLNFeuXClPPfWUCYa899575ioNhuiTaH369JEhQ4bIaaedJnXr1s0yxXBOcz0wwpGkJggggAACCCCAgD0B5mj2LEnJvgD9074pKSKAAAIIIIAAAoUKuJ6jEQAptAUtXb9w4UIZN26cCYgsW7asLBhSu3ZtOfXUU2XQoEHSr1+/srdFLGXrbTKuB4a3MBQMAQQQQAABBBBwKMAczSE+WVcpQP+skogTEEAAAQQQQACB2AVcz9EIgMTe5FVn+Prrr5tgyPPPPy9r1qwpC4bofiH6iazbbrut6kQSfobrgZFwPoqPAAIIIIAAAghEIsAcLRJWErUkQP+0BEkyCCCAAAIIIICARQHXczQCIBYb03ZSul/IxIkTzSeypkyZYvYLKS4ulvXr19vOyrv0XA8M70AoEAIIIIAAAggg4IEAczQPGoEiVChA/6RzIIAAAggggAAC/gm4nqMRAPGvT5SVaOPGjWbDdH0bRAMgmzZtIgDicXtRNAQQQAABBBBAIHQB14uXQnynT59eyOXlXtu7d2/raZJg9gKdOnXa5mRdLy1atMj8nX5WuHXr1tknxpkIIIAAAggggAACkQi4XkMQAImkWQtL9I033jBvfUyYMEHWrl1rEtuyZYvsuuuu5hNYo0ePLiyDBFztemAkgIgiIoAAAggggAACsQskeY5WvXp1q/vpVatWzbyhzeFOgACIO3tyRgABBBBAAAEEshVwvYYgAJJtS0V8nm6CrkGPJ598UrRTZIIederUMZugDxkyRI466ijRhVsaDtcDIw3G1BEBBBBAAAEEEMhVIMlztEwARB8ssnFoAKS0tNRGUqRhSSDJ/dMSAckggAACCCCAAALeCbieoxEAcdglVqxYIU8//bQJfMybN68s6KGLs759+5qgx2mnnSZ169Z1WEo3WbseGG5qTa4IIIAAAggggIDfAkmeo2UCILqn3sknnyzHHHNMwQ8XDR061O8GS1npktw/U9ZUVBcBBBBAAAEEUiTgeo5GACTmzrb9xub61FjmKbTOnTubT1ydc8450rJly5hL5ld2rgeGXxqUBgEEEEAAAQQQ8EMgyXO0hg0bln1eVt/eaN68uZx99tlm/t2lSxc/gClFQQJJ7p8FVZyLEUAAAQQQQAABjwVcz9EIgMTcORo0aCDr1q0zuWrgo0WLFnLWWWeZhVfXrl1jLo2/2bkeGP7KUDIEEEAAAQQQQMCdQJLnaPog0gsvvGDevp48ebLZv0MDIXpkHkTSgEjaH0Ry17sKzznJ/bPw2pMCAggggAACCCDgp4DrORoBkJj7xdav3p900knSr18/KSoqKqgU+qms0A7XAyM0T+qDAAIIIIAAAgjYEAhljrZy5Up56qmnTDDkvffeMzQaDNG5ep8+fVL9KVob/cRVGqH0T1d+5IsAAggggAACCEQh4HqORgAkilatJM1MAMRWtrpQ06fXQjtcD4zQPKkPAggggAACCCBgQyDEOdrChQtl3LhxJiCybNmysmBI7dq15dRTT5VBgwaZh5Yyb4vYcCSNaARC7J/RSJEqAggggAACCCAQn4DrORoBkPja2uSkARCbhy7EdB+R0A7XAyM0T+qDAAIIIIAAAgjYEAh9jvb666+bYMjzzz8va9asKQuG6H4h+sna2267zQYjaUQkEHr/jIiNZBFAAAEEEEAAgUgFXM/RCIBE2rw7Jv7GG29Yz/GII46wnqbrBF0PDNf1J38EEEAAAQQQQMBHgbTM0XS/kIkTJ5pPZE2ZMsW8cV1cXCzr16/3sVko0/8KpKV/0uAIIIAAAggggECSBFzP0QiAJKm3pKisrgdGiqipKgIIIIAAAgggkLVAWuZoGzduNBum69sgGgDZtGkTAZCse4m7E9PSP90JkzMCCCCAAAIIIJC7gOs5GgGQ3NuMK2IQcD0wYqgiWSCAAAIIIIAAAokTCH2Opm9r61sfEyZMkLVr15r22bJli+y6667mE1ijR49OXJulqcCh9880tSV1RQABBBBAAIFwBFzP0QiAhNOXgqqJ64ERFCaVQQABBBBAAAEELAmEOEfTTdA16PHkk0+K1i8T9KhTp47ZBH3IkCFy1FFHWd/Lz1KTkMxWAiH2TxoYAQQQQAABBBBIuoDrORoBkKT3oEDL73pgBMpKtRBAAAEEEEAAgYIEQpmjrVixQp5++mkT+Jg3b15Z0KN69erSt29fE/Q47bTTpG7dugV5cXG8AqH0z3jVyA0BBBBAAAEEEIhWwPUcjQBItO1L6nkKuB4YeRabyxBAAAEEEEAAgaAFkjxH235j89LSUvN5Kz06d+5sPnF1zjnnSMuWLYNuw5Arl+T+GXK7UDcEEEAAAQQQSLeA6zkaAZB09z9va+96YHgLQ8EQQAABBBBAAAGHAkmeozVo0EDWrVtn9DTw0aJFCznrrLNM4KNr164OVcnalkCS+6ctA9JBAAEEEEAAAQR8E3A9RyMA4luPoDxGwPXAoBkQQAABBBBAAAEEdhRI8hxNP29VrVo1KS4ulpNOOkn69esnRUVFBTWzfiqLwx+BJPdPfxQpCQIIIIAAAgggYFfA9RyNAIjd9iQ1SwKuB4alapAMAggggAACCCAQlECS52iZAIitBtFgSklJia3kSMeCQJL7p4XqkwQCCCCAAAIIIOClgOs5GgEQL7sFhXI9MGgBBBBAAAEEEEAAgR0FkjxH0wCIzUMDILqPCIc/Aknun/4oUhIEEEAAAQQQQMCugOs5GgEQu+1JapYEXA8MS9UgGQQQQAABBBBAICiBJM/R3njjDettccQRR1hPkwTzF0hy/8y/1lyJAAIIIIAAAgj4LeB6jkYAxO/+kdrSuR4YqYWn4ggggAACCCCAQCUCzNHoHj4L0D99bh3KhgACCCCAAAJpFXA9RyMAktae53m9XQ8Mz3koHgIIIIAAAggg4ESAOZoTdjLNUoD+mSUUpyGAAAIIIIAAAjEKuJ6jEQCJsbHJKnsB1wMj+5JyJgIIIIAAAgggkB4B5mjpaesk1pT+mcRWo8wIIIAAAgggELqA6zkaAZDQe1hC6+d6YCSUjWIjgAACCCCAAAKRCjBHi5SXxAsUoH8WCMjlCCCAAAIIIIBABAKu52gEQCJoVJIsXMD1wCi8BqSAAAIIIIAAAgiEJ8AcLbw2DalG9M+QWpO6IIAAAggggEAoAq7naARAQulJgdXD9cAIjJPqIIAAAggggAACVgSYo1lhJJGIBOifEcGSLAIIIIAAAgggUICA6zkaAZACGo9LoxNwPTCiqxkpI4AAAggggAACyRVgjpbctktDyemfaWhl6ogAAggggAACSRNwPUcjAJK0HpOS8roeGClhppoIIIAAAggggEBOAszRcuLi5JgF6J8xg5MdAggggAACCCCQhYDrORoBkCwaiVPiF3A9MOKvMTkigAACCCCAAAL+CzBH87+N0lxC+meaW5+6I4AAAggggICvAq7naARAfO0ZKS+X64GRcn6qjwACCCCAAAIIlCvAHI2O4bMA/dPn1qFsCCCAAAIIIJBWAddzNAIgae15ntfb9cDwnIfiIYAAAggggAACTgSYozlhJ9MsBeifWUJxGgIIIIAAAgggEKOA6zkaAZAYG5usshdwPTCyLylnIoAAAggggAAC6RFgjpaetk5iTemfSWw1yowAAggggAACoQu4nqMRAAm9hyW0fq4HRkLZKDYCCCCAAAIIIBCpAHO0SHlJvEAB+meBgFyOAAIIIIAAAghEIOB6jkYAJIJGJcnCBVwPjMJrQAoIIIAAAggggEB4AszRwmvTkGpE/wypNakLAggggAACCIQi4HqORgAklJ4UWD1cD4zAOKkOAggggAACCCBgRYA5mhVGEolIgP4ZESzJIoAAAggggAACBQi4nqMRACmg8bg0OgHXAyO6mpEyAggggAACCCCQXAHmaMltuzSUnP6ZhlamjggggAACCCCQNAHXczQCIEnrMSkpr+uBkRJmqokAAggggAACCOQkwBwtJy5OjlmA/hkzONkhgAACCCCAAAJZCLieoxEAyaKROCV+AdcDI/4akyMCCCCAAAIIIOC/AHM0/9sozSWkf6a59ak7AggggAACCPgq4HqORgDE156R8nK5Hhgp56f6CCCAAAIIIIBAuQLM0egYPgvQP31uHcqGAAIIIIAAAmkVcD1HIwCS1p7neb1dDwzPeSgeAggggAACCCDgRIA5mhN2Ms1SgP6ZJRSnIYAAAggggAACMQq4nqMRAImxsckqewHXAyP7knImAggggAACCCCQHgHmaOlp6yTWlP6ZxFajzAgggAACCCAQuoDrORoBkNB7WELr53pgJJSNYiOAAAIIIIAAApEKMEeLlJfECxSgfxYIyOUIIIAAAggggEAEAq7naARAImhUkixcwPXAKLwGpIAAAggggAACCIQnwBwtvDYNqUb0z5Bak7oggAACCCCAQCgCrudoBEBC6UmB1cP1wAiMk+oggAACCCCAAAJWBJijWWEkkYgE6J8RwZIsAggggAACCCBQgIDrORoBkAIaj0ujE3A9MKKrGSkjgAACCCCAAALJFWCOlty2S0PJ6Z9paGXqiAACCCCAAAJJE3A9RyMAkrQek5Lyuh4YKWGmmggggAACCCCAQE4CzNFy4uLkmAXonzGDkx0CCCCAAAIIIJCFgOs5GgGQLBqJU+IXcD0w4q8xOSKAAAIIIIAAAv4LMEfzv43SXEL6Z5pbn7ojgAACCCCAgK8CrudoBEB87RkpL5frgZFyfqqPAAIIIIAAAgiUK8AcjY7hswD90+fWoWwIIIAAAgggkFYB13M0AiBp7Xme19v1wPCch+IhgAACCCCAAAJOBJijOWFPZKaPP/64DBs2rNKyH3nkkTJ16lRr9aN/WqMkIQQQQAABBBBAwJqA6zkaARBrTUlCNgVcDwybdSEtBBBAAAEEEEAgFAHmaKG0ZPT1mD9/vkycOLHcjCZMmCAffvih3HbbbXLNNddYKwz90xolCSGAAAIIIIAAAtYEXM/RCIBYa0oSsingemDYrAtpIYAAAggggAACoQgwRwulJd3V4+eff5aWLVvKDz/8INqfmjdvbq0w9E9rlCSEAAIIIIAAAghYE3A9RyMAYq0pScimgOuBYbMupIUAAggggAACCIQiwBwtlJZ0V4+//OUvMnDgQDnllFPkb3/7m9WC0D+tcpIYAggggAACCCBgRcD1HI0AiJVmDCuRNWvWyCuvvCLvvPOOvPvuu/LVV1/JypUr5aeffpJGjRpJx44d5fjjj5df/epX0rRp00gq73pgRFIpEkUAAQQQQAABBBIuwBwtngZcsWKFzJkzx/xP5+T6v++++85kPnToUNH9NbI9vvzyS7n77rvl5ZdfFv1zrVq1pF27djJgwAC56KKLpE6dOtkmZeW8fv36yZQpU+Tvf/+79O/f30qamUTon1Y5SQwBBBBAAAEEELAi4HqORgDESjOGlchrr70mxxxzTJWVatasmTzxxBNy7LHHVnlurie4Hhi5lpfzEUAAAQQQQACBNAgwR4unlatVq1ZhRrkEQDTocc4555jPTZV37L333ubBp7Zt28ZSsaVLl5q8dt11V9E/FxUVWc2X/mmVk8QQQAABBBBAAAErAq7naARArDRjWIloAOS8886Tvn37Srdu3aRNmzZmkbJ582bznV7dtPD555+X0tJSqVmzpnkibf/997eK4HpgWK0MiSGAAAIIIIAAAoEIMEeLpyG3DoDoXHzfffeVyZMnm8yzDYC8//770qtXL1m/fr3Uq1dPRowYYeb3+lb3M888Iw899JBJb5999jHzeT0n6uPGG2+Um266Sf7whz/IqFGjrGdH/7ROSoIIIIAAAggggEDBAq7naARACm7C8BLQwEZVT2NNnDhRTj31VFP50047Tf76179ahXA9MKxWhsQQQAABBBBAAIFABJijxdOQI0eOlIMPPtj8TzcJ/+KLL2TPPfc0mWcbANFgx+uvvy477bSTTJ8+XXr27LlN4W+//Xa55pprzN9pUOKGG27YoXL6xnfm01vZ1HzatGnSp0+fck/Vh6m0DsuWLZPFixeX1SebdLM9h/6ZrRTnIYAAAggggAAC8Qm4nqMRAImvrYPLSZ9E+/jjj0UXRrpHiM3D9cCwWRfSQgABBBBAAAEEQhFgjuamJXMNgOgbHYcccogp7PDhw+X+++/foeAakOjcubMsXLhQGjduLMuXL5caNWpsc94ll1wia9euzbrS1157rXmjpLxj0qRJctxxx8lRRx0l+sZ5FAf9MwpV0kQAAQQQQAABBAoTcD1HIwBSWPul+uqDDjpI5s6da16Xz2VhlA2a64GRTRk5BwEEEEAAAQQQSJsAczQ3LZ5rAOS6666TW265xRR29uzZ0r1793ILPnr0aPNpLD30E1vZ7AOYr4Buuv7cc8/J008/LQMHDsw3mUqvo39GwkqiCCCAAAIIIIBAQQKu52gEQApqvvRerE+K7bfffmYfEA2E6FNmNg/XA8NmXUgLAQQQQAABBBAIRYA5mpuWzDUA0rt3b5kxY4bUrVtXvv/+e/MZrPKOWbNmmX1C9NBPYOmnsKI49DNaLVu2NA9Off3111KrVq0osjH7FeqeKXrop7Zat24dST4kigACCCCAAAIIIJC9gOs5GgGQ7Nsq9WfqBopfffWVvPTSS/KnP/3JvCavx/jx42XQoEFWfVwPDKuVITEEEEAAAQQQQCAQAeZobhoy1wDIzjvvLKtWrZIuXbrI/PnzKyz06tWrpUmTJubfzzjjDHn22WcjqeCf//xnueKKK+TSSy+VMWPGRJKHJkr/jIyWhBFAAAEEEEAAgbwFXM/RCIDk3XTpuPDxxx+XYcOGVVjZq6++2gRDqlWrlhOIdvzKDn1iK/M02pw5c2TXXXfNKX1ORgABBBBAAAEEELAv8M0335TtLfH555/LHnvsYT8TUtxBIJcAyIYNG6R27domjf79+8vf//73SkX1rYx169ZJjx49RN8IieLQN8c/+OAD+cc//mHeIs/3YA2RrxzXIYAAAggggAAC7gRcryEIgLhr+0TkXFEApGvXrmYzxYq+J1xV5XINmFSVHv+OAAIIIIAAAgggEK+APqRy8MEHx5tpSnPLJQCycuVK2WWXXYzUmWeeKc8880ylas2bN5cVK1aYDdEXLFhgXVj7ia4ZdFP2t99+u6D0WUMUxMfFCCCAAAIIIICAcwEXawgCIM6b3e8C6DeDM09a/fTTT7J48WLzavzf/vY32WuvvURfZz/hhBNyrgSLl5zJuAABBBBAAAEEEPBKwMXixSuAGAuTSwBE36TebbfdTOkGDx4s48aNq7Skeq5eo3P7zz77LMZa5Z4Va4jczbgCAQQQQAABBBDwScDFGoIAiE89IEFl0X0/hg4daj599cgjj8i5556bU+mren1dX93/+OOPRZ9I028YV7RxY06ZFnDy1q9qhfpJrtDqGFp9Kuq+Idcz5Lpl2jP0OoZeP23HNNQx9HrShrlNkEpKSkTfMNBDP2VUXFycWwKcnZdALgEQ394AyavCFVzEGsKmpp20QvsZGlp9WEOE+Tnt0Ptp6PULfW699c+dkNsy5LpF0Yau1xAEQOzM+1KZir5Sr2+D1K1b1zw11rhx42AdXG/WEwdsaHUMrT4V9YGQ6xly3TLtGXodQ6+ftmMa6hh6PWnDOGYZ5FGoQC4BEB/3ACm0/km9Pg0/X0KrY2j1YQ2xTFq3bp3UHyEVljv0fhp6/UKfW2/dcUNuy5DrFmIbEgAJ7ldhfBV66qmn5JxzzjEZPvnkk3L22WfHl3nMOaXhB1todQytPixeWLzE/GPPSnZpGIdpqGPoizTa0MpwJ5GIBXIJgGhR9A3qVatWSZcuXWT+/PkVlm716tXSpEkT8+9nnHGGebiJw55AGn6+hFbH0OrDGoI1hL2faPGllIZxmIY6soaIb8xEmVMofZUASJS9JPC0p0yZIv369TO1vOWWW2TEiBHB1jiUAV9ZA4VWx9Dqw+KFxUsSf8CmYRymoY4sXpI4+nYsc1r6ahittWMtcg2A9O7dW2bMmGHe1NY9/Sr6nOysWbOkV69eJsMbbrhBbrrpplAJndQrDeMutDqGVh/WEKwhnPzwKzDTNIzDNNSRNUSBA8GTy0PpqwRAPOlQSSzG448/LsOGDTNFv/vuu+WSSy5JYjWyKnMoA54ASFbNnaiTQu6bIdct08lCr2Po9Qt9Ur/1D8OQ2zLkuqWlDRP1izvPwuYaAPn9738vt956q8lt9uzZ0r1793JzHj16dNlDTJMmTSp7uCnPYnLZdgJp+PkSWh1Dqw8BEAIgSfzBnIZxmIY6hr5Wog2T9dOFAEiy2sur0vbv319eeeUVU6Zp06ZJnz59vCqfzcKk4QdbaHUMrT4sXli82PyZFldaaRiHaagji5e4Rky0+aSlr0ar6C71XAMgc+bMKQt6DB8+XO6///4dCr9582bp3LmzLFy4UBo1aiQrVqyQGjVquKtkgDmnYdyFVsfQ6sMagjVEEn+0pmEcpqGOrCGSOPp2LHMofZUASBj90Wot9M2OgQMHSnFxcYXp3nXXXXLllVeaf99jjz1k0aJFFb5ab7VwjhILZcBXxhdaHUOrD4sXFi+OfvwVlG0axmEa6sjipaBh4M3Faemr3oBbLkiuARDNPvMZLP381fTp06Vnz57blOr222+Xa665xvzdyJEj5cYbb7RcapJLw7gLrY6h1Yc1BGuIJP4kTsM4TEMdWUMkcfQRAAmj1ahFVgIa0Fi7dq388pe/lMMOO0z22msvqVevnvm7BQsWmA3P33zzTZNWzZo15eWXX5ajjz46q7STelIafjmFVsfQ6sPihcVLEn9+pmEcpqGOLF6SOPrCXbyE0RpV12LmzJny2WeflZ2oG5r/7ne/M/996KGHyvnnn79NIueee+4Oic6bN8+c+9NPP5m5vH4Wq2/fvua/n3nmGXnwwQfNNR06dJB3331X6tevX3XBOCMngTT8jgitjqHVhzUEa4icfmh5cnIaxmEa6sgawpMBVWAxQumrvAFSYEcI8XINgCxdurTKqrVu3VoeffRROeaYY6o8N+knhDLgK2uH0OoYWn1YvLB4SeLP0TSMwzTUkcVLEkcfAZCkt5oGNMaOHZt1NbZs2VLuuS+99JIMGjRI1qxZU+6/a/BDH2Zq165d1nlxYvYCafgdEVodQ6sPawjWENn/xPLnzDSMwzTUkTWEP2OqkJKE0lcJgBTSCwK9dvHixfLaa6+ZfT30m8DLly+X7777znwSq3nz5tK1a1c54YQTZMCAAVKnTp1AFagWAggggAACCCCAAAJuBGwFQLT0+mDTmDFjTKBDF7H6BrcGPM444wz57W9/y3zeTROTKwIIIIAAAggggEBMAgRAYoImGwQQQAABBBBAAAEEEEAAAQQT31jSAAAgAElEQVQQQAABBBBAAAEEEIhPgABIfNbkhAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAjEJEACJCZpsEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAID4BAiDxWZMTAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIxCRAACQmaLJBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACB+AQIgMRnTU4IIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQkwABkJigyQYBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTiEyAAEp81OSGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBMAgRAYoImGwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEIhPgABIfNbkhAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAjEJEACJCZpsEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAID4BAiDxWZMTAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIxCRAACQmaLJBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACB+AQIgMRnTU4IIIBApAKrVq2Sjz76yOTRu3fvSPMicbsCpaWl8t1338lOO+0kTZo0sZs4qSGAAAIIIIAAAgggUIEAa4jkdg3WEMltO0qOAALxChAAideb3AIVWL9+vejEUY/ddtst0Fr6WS2137hxozRu3LjcAn766afy/PPPy9KlS6VevXqy3377yUknnSSNGjXys0IFlOovf/mLnHXWWVK9enUpKSkpICV/LtV6vPvuu/LVV1+ZQrVs2VIOOuggqVGjhj+FzLMk2nfvv/9+efrpp+X9998XXcDoUbt2benVq5f85je/kVNPPTXP1KO9bNy4cbL33ntL9+7do83Ik9Q1OPX222+bnzUdOnSQTp067VCy//7v/5aHH35YPv74YxPI2nPPPeXEE0+UoUOHmv9O0jFjxgx54403TED1yy+/lLVr18pPP/0k9evXNz9rO3bsaNpe69egQYPEVG3lypXy4osvysyZM2XhwoWybNky+fHHH03ddNzp74g2bdrIvvvuK4ceeqj5XbHLLrskpn6FFpS5TKGCXI9A7gKMu9zNbF3BGuL/JFlD2OpV8aTDGiIeZxu5sIZgDWGjH/meRlLmMgRAfO9JlC8RAmPHjpXzzjtPqlWr5vWN5yeffFImTJggixcvNjfJ99lnHznzzDOzusn64YcfmuCBLzfXJ02aJH/4wx/kvffeM32kWbNmcvnll8vVV19ddnP83//93+Wmm26SzZs3b9OPGjZsKHfffbcMGjQoEf0r20JmFi/aDzM307O91rfz9Iartt2DDz4o69at26Z4derUkfPPP19GjhzpbSBrypQp8m//9m+iZX399dd3uAGuN8lPPvlk+eyzz0zdtmzZsk0dtQ316N+/vwmQ1K1b16sm0p8DWsb27dubG/w6lvTGcWiHBuCuuOIKE6ja+ueIBqgeffRRU389fve738mdd95ZbvU1WPDKK69477Np0ya577775E9/+pMsX758m7pk+memX2b+UYMG55xzjvzxj380P4N9Pb755hu5/vrrRQN3W/9s3H7cafm3rqP28yFDhsioUaNM8DX0IylzmdDbgfqlSyAp4441xL/6JWsI/8cnawjWED70UtYQ/2oF1hCsIXwYj5kyEADxqTUoS2IFdPEybNgwc+PExxvPP/zwg3mSVZ96Le/QJ+ozT3RX1AiZAIgPdRw/frzx1l+oW9/A0rLpjVhtD705qTfJKzr0xtYTTzwhAwcO9LLfaXvkeugT6v/1X/9l+uFjjz22w+V6I8+HQ5+MV38NYrVr126HIn399dfSr18/84R2eTcoMzcpNYD32muvya677upDtbYpw6WXXir33nuvnHLKKeYNpK0PfRLogAMOMG+1aP1q1apl3mrRAIL+/NAA5fz5880Nd21LDYLoU+s+Hdp+mXbI/P8RRxxhgiG//OUvvQvY5Gunb1Q9++yz5QaotB/PmTNH/v73v8u5555blkXz5s1Fgwn//Oc/y/7uwAMPNG+QFBUV5VuUSK9bsWKFeZtD37aqKCigb7FoX9U3JrY+tI/qZ9s0UHf00UdHWs58Ep87d66pmwZ1tq6bvrmiY06Di1ovfbtHg636VsiaNWvKstL66VsgL730khmnIR++z2VCtqdu6RXwfdyxhtixb7KGcDdeWUOwhnDX+3LLmTXEv7x0Hs0agjVEbqMnurMJgERnS8opEvB98fKLX/zC3GzOHPqk7s8//1x2k0d/MemTvBo0GDBgQLkt50sARG8a641vvVGln0E66qijzA2s//mf/5HVq1ebX7KvvvqquSGpNyAvu+wy86T9zjvvbG44681MfatAbzTrTTu92axPc/l2ZJ6wz7VcFT1l4dPbSZm6LViwwHxKZ/vj8MMPlzfffNP8ddOmTU2QSs/TuuknefRNFw0iaJ30pru2vW9Ht27dTBBD3xy44IILtineVVddJXfddZcpv/7bLbfcssO+H59//rlcdNFFZtzqeX/7299MENOXI9OGWrbMmxGZJ+f1rZfTTjvNPDmv4zOpx+TJk+W4444z/vozQoOue+21l/mZ8fjjj8v3339v3lLSG/8arBs8eLBpy1atWpkqf/DBB6KBMH0DSNPQgKsuhnw79Gdhz549TfBDD/30k9ZbAzl642v69Ony8ssvm38bPXq06Zf6yTYNqD/11FPmz3oUFxebN1369OnjTRX1d8D+++8vGlTV49hjjzW/G/TnRosWLSos57fffms+AabtnPndqW+A6M+sij636E2lCyiI73OZAqrGpQh4K+D7uGMNwRqCNUS8Pz5YQ7CGYA0R75grLzfWELm1ge9zmUxtCIDk1q6cjUC5Aj4PeL0hdcIJJ5gbcHpjS98QyHy/Xm/Q6qdL/vrXv5p66U1N/TSU3uDa/vAlAKKfPdLPkWjARm8sHnzwwaao+gSz1m/JkiWyxx57mKd49cZV3759d6iLBkH0prqa6FP6uteCb0fmBnNFb0DkWl4f3tzJlLmyAMgLL7xgPsmm5dW3QDTYsf0eA/p09hlnnCH6malMwOuYY47JlSTS8/Xmqu43oMG47cumN8j1BqsGCMp7UydTMH11+rDDDpN33nnHBD80COLLkWlDvUmsN4X1razZs2eXFS8TDNG6amBA/6eByyQdGqzQ/qfBUw0ObP2Jr//3//6feRtA947QNyIqah99q0AXshog8a0NM23x0EMPyfDhw83bKbqHib7Fs/2hwQ59E0nrqnud6NjMHM8995wJ5Om41D2wNEipQTAfjhtvvFFuvvlmEyzXz7ecfvrpORdL66ef+dJAkX5GS9MM9fB5LhOqOfVCwOdxxxqCNYSOUNYQ8f6cYg3xr094sYZgDRHvyNs2N9YQuen7PJfZuiYEQHJrV84OTODII4+0UiO9manf9PdpgpipmN7o1xv+evNR98vQp3S3PzQAonuY6DdTtQ66d8aIESO2Oc2XAIgGOfRG669+9SvzJsfWR+ZGntZBn/J95JFHKmxfvZmnN/L00yh60923I3ODWT+9ontJZPPUsX5iR9840Prr2zzbH+Xd2HRR78oCIJn+qjdStc9VtPeF3ojVQJ7eiNZ6lVdfF3XL5KnjTD+DpJ/f6dq1a1lRNCiiT9ZrG+nTPbrZcmWH3nzVfXr0M1+ZjeBd1iuTd3ltqPuZ6ORHbzR/8cUX5tSt91PQQICOS21jffvK90Pf9tB63H777XLllVfuUFzd80P3HNI6aoBA36Io79CfU7/+9a9NcCDj4lPd9fegBrIuvPBCEyCv6ND9QS655BLR/U+2/5yi/uzRN7c0SKBB9IsvvtiLKurY0wDdNddcI7feemveZbr22mvN3ij6Nok+OODbkYa5jG/mlAeBNIw71hDl93PWEO7GP2sI1hCsIdyNv+1zZg1RdVuwhqjaKM4zCIDEqU1e3gnk+5mh8iqiT+r7GABp27atLF26VB544IFK98TQAM7xxx9vbtBpPba/YeRLAEQ/36WfutJ9FfTTVlsfWnatr5a/vH/f+lz9tIkGffRtEX1rxLfjP//zP+X3v/+9eapagyB33HGHeQq5siMpm6BXtnjJ9Ff9lJAGfio79HM8aqRBBO2fPh2tW7cW3XhZn57Uz+5kDg0SdOjQwfRRfTtAv4la2TFv3jzzBkHNmjVlw4YN3lSxqs+Y6WeTdB+bCRMmbPOpPa2APo2vP2v0DRh9O60qA1eV1uCbmusn1vSTSdsfGjTQN8y0LTUgp2+llXfoGzzdu3c3wef169e7qk6F+WpwTd+g009+VfbJMt1DQ8/V+uqnserVq7dNmvoWiAad1WTq1Kle1FM/XaZto/1Rg+f5HvpJPg3w1K9f39TdtyMNcxnfzCkPAmkYd6whyu/nrCHcjX/WEKwhWEO4G3/b58waouq2YA1RtVGcZxAAiVObvLwTCPkzQxnszE083axXb6RWdmQ2n9ZPmOhNLv00lH4iSg9fAiB6I1ifMtYnjrffkFb3NdGbjFp2/WSNbjRd0TFr1ixzQ0xv4m294a1PnVRvoOuT1BMnTjR10huL+oR2+/btyy1mCAGQTH+dNm2a9O7du9LmyNyA1pucGhTz6dDNoLUO+obAbbfdVlY0vRmrn/TS9tS3V6rawD2zD4UGwfRNM1+OqgIgmXJqkEf7rwZDtC46dvXIvBmiT3Hpp6b0E1mZz9n5UkcNaOjPlBkzZpi3HrY/3nrrLfOJMq2LfgpLfzaVd+ibd/qzSjfa1vN8O7Rc+rm17d9W2r6ceo7WUev7ySefSLt27f5/e2cCq0dZ/f9zS4E2tIK4JSwFgsgFrWhJWYRQlR0CVFBsgIBsCiiL0hIJyN7wKypLqgRBqAVNa9lKkUgVBbQIVNBqxFZLqXYjRNAEWkrbW+4/Z/qfcnt7577LfZdnvucziblqZ953Pp/zPM88Z847z2yyi78M3pf5Sulppe222y57sjFKAURxycTU+gvng4HcADnEpm2BHCKtvkEOQQ5BDtG+PkkOsal7coj0f0QVJYegANK+cZFvTsBAvha//wp5IMsgpbzmna/F7jch/Wad/wq50uY3kv0X615A8Btd/ittX17IiyIjR45s+1Mu/lJsf/lw0ZIz1d6Y/etf/5otTZTaL+v7io+3zW984xvZEkh+s9KfzvEnH/y/99wUCiBekPKbxP7kgy8309/mL1/2Ipc/UeBtPKUtXy7Iix3+/oeehY58GTcvjHiBpL/N+5+/PNtfLJ3Sy96r7Wc92fwpA2fx94XkL872f/dxJqUXbObn7EtWeZ/zoqMvD9V7y5e28nP3Isc+++zTZyj9ReGnnXZaUoWBniea/3rLn9bx9+8UbT2fXvIbXb6UW88txaeV8iWw/Gkyf6qs3s2XhPT+6tfAnm233s9r9HER5jKNdsbnYWCgBiL0O3KIvlsJOcRAe0/9x/c3/ySH2NQrOUT97WygR5JDbGqQHIIcYqB9qlHHUwBplEk+p5QG/GaP31z2l435DZ16t5QLIPnj634Tzt8lUM3mv1L3opD/atZv7vmLY/0G0KhRo9peANlzzz3NL6L+boQTTzxxM5xqb8z6r7p9WRtPYP2F6alvHhNfQ9Lf8eEVen8/gd9k7/mCbYUCiN9E9ndj+AvufcmZ/rb8kVJ/SbUvz5PS5ksd7b333lnb8r/+AvP8F/P+YnR/fNufVvKCQF/t2Fn8nQMec++DHndfYiiVrdp+VnS+HmNfQmLatGnZUmEpLh+YXx98DPWbHT1f7O3x9ba6ZMmS7OmJc845J1tmsK/Nn2TytuovDvf3DqW2+VjvS7X5+XnbLNr8PSi33nqr+TKEXszqvXlR2llTelrp6quvtuuvvz4rknpbK+pr/cXEl1P0dfD96aUrr7zSrr322tRCmBWu1OcyyUnnhMIbiNDvyCH6bubkEO3r/v3NP8kh3osLOUT72qh/MznEpv7JIcgh2tsj3/t2CiCpRILzaIsB/0Wo39Dwm2/+ngxft7+eLeUCiF+AZ82aVfEFt725fe17v1nkN8Tczyc+8YnsZbLtvlHpN/z9l/Df+9737Jvf/OZm4fJlkXzbb7/9Ctfk93//8Y9/nDnxoo4/7VKWzZf+8hvhfgPZY3HyySfbLbfckhXxylYA8Xe4+BI1PTePn7/LxZde8yXY+tt8WSV/qXaK7wDx8/YlsPxFmf50ij+tc8opp2TFRH9Z9l133bXxHScHHHCAHX300dn44zdZFy1alC0b5csMebHLl0967rnnzJO+VLaBFkByjnfffTdbGssLQf6flLb8BfTez/wm0CWXXJL99XcG3XbbbVmcfELvT054IcRvjPuTBn6z3TdfWs//3Z+g88/wgqW/DD21zV9a70uQ+Tn6e5H85e7+rot88wKPv4PInzrz7eyzzzZ/+qX3lj/15E9d+BMxKWz//e9/s2uXLx/nfEcddVQ2Znjx2ws1RZsXeHwsmjJlis2ePTvrh/6kjF8DU3z5ZoS5TArtiXPAQE8DEfodOUTfbZ4con1jQT7/JIfY8J5EcghyiPb1RjNyiM3tk0N0bFzyup1ts+i7KYCkGBXOqWUGnnjiiexXr35jpNLyH/2dVMoFEP/Frt+E86Wj/CmX/OZcNZL9xpevz//ggw9mjlJ40bvfhPOXX/t5+UW33s0fC/bjzzjjjOwGZZk2j4v/sueGG27Ibq77Mkv+39///vdnS+20u0hVyWU1Lw71dwn4UxP9bV7A8iR07Nix2UvvU9x8jPG2+sYbb2x874Wfp7+3xJ8i8HdM5O/D6H3+3t+8QOfvVvACV0pbowogKTH1dS7+3h2/Ed47Rh4bH1N92acZM2ZkS5n5Pl448Cd+vI96kdL7p+/rhRO/eV70ovR2evAilC/L5sVVZ/D38HiRzpe48hd+e/Ht9ddfzzh8rJk3b57tuuuum51yvrTbBRdcYJMnT24n0ibf7S+h9/HEnxLrGUfvg1509CUzfClE74v+pJ2/m6fni86d258ye/TRR7PCeopbhLlMit45p9gGIvQ7coi+2zg5RPv6PjkEOUT7Wl9t30wOQQ5BDlFbn2nF3hRAWmGZ70jWgN/k8F+r+nbhhRdmhYJ6Nl8T3H+x7ZsvuZHS9s9//tM6OzuzGz/+q13/9W4tm98c8+VdfLka39p9c909+5MpfnPOl86pZ/NfZvuNr1WrVmVc/uvnMm6+FJj/otyfiPG4+NMU/g6Xdseokku/eVp00z8/1p+YmDt3bnbDta/Nn1DyGDqvF8QmTJhQ6Wvb9u9+89iXsvIleHq+BDt30NdLx/yGq99Uv+iiizZ710vbQHp8cZQCiI8VvvxR76WhvA17AdULBb75k1heRM/HSP+bx9WfNPCnXCq906adcfUnJHxZNi9u9GToyeF90Z+K6bnsXn7OvtSbH++bPy3iPyxIafPivxfPPWb+lFW+9TUO9eyP3s5PPfVUmzhxYt1PiLbCQ4S5TCs88h0YqMVAhH5HDrF5iyCHqKWXNH5fcogNTskhGt+2Gv2J5BDv5ULkEPWtMtPoNtnX50WYy/TkpgDSilbFd2CgzQb8KQe/AbTzzjvX/bTDpZdeuvFX9osXL24bkf9KN39nh78Ho55t+vTpG9fr93ej9HxBdT2f1+5jvIjjBQB/yiCfFPe8ydfu82vG9/uyNF748M1vuPqTEqlvPsHwX5H7L+r//ve/my/P40U4fxeIPzng/fPjH/949h4F/09KS171duvLCHny5UuAlL3/VNNufEknf4+Hjz8f+9jH7Mgjj8yeGsg3v2nuS0D502T+0vvBgwfbbrvtZscdd9zGJ/Cq+Z527uNFRV96zpeW86dX8s3j60tNeBHPX+pY5s0fS/clIX39do+TX0veeustc/a8H3ph1Z/iOfjgg7MnR3q/7L3M/Jw7BjCAgVoNkENsaowcotYWlN7+5BDtjQk5BDlEe1tgfd9ODlGft9SOogCSWkQ4HwxgAAN1GPCnDHw5KF9yx7fUnkSqA4lDMICBNhnwgoA/XeXLYRU9hdWmU+NrMYABDGAAAxhooAFyiAbK5KMwENwAOUTwBpA4PgWQxAPE6WEAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMFC7AQogtTvjCAxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABhI3QAEk8QBxeu0x4O9PWLhwYbY++MqVK7MXFw8dOtSGDRuWrdP/0Y9+NFvjvcybGqMaT1HbUuZUZsvjqc6ozudxjMAYibPM13HOHQMYSM9AhGuEGqMaDzkEuXt6I2PlM4rQDyMwkkNUbuvs0T4DFEDa555vTszAm2++aXfffXf2ou+5c+daV1dX4Rl68WP06NF24okn2tlnn23bbrttYjR9n44aoxpPUSNS5lRmy+OpzqjO53GMwBiJs9YL9l/+8hd75JFHssOuuuqqWg8vzf5ROEsTEE60NAYiXCPUGNV4yCHI3ct4fyJCP4zASA5RPF2JMrcuCycFkNJMrTnRZhq455577LLLLste+upbd3d3xa/r6OjI9tluu+1s0qRJds4551Q8pp07qDGq8RS1DWVOZbY8nuqM6nwexwiMkTjruQ5PnTrVzjzzTPPrvv96T3WLwqkaP7jaYyDCNUKNUY2HHILcPW8DZbo/EaEfRmAkh+h/7hFlbl0WTgog7Zkr860JGbjhhhvs6quv3lj0eN/73mcHHHCAdXZ2ZstdbbPNNrb11lvbmjVrbNWqVdmyWAsWLLDnnnsu+1Wwbz7ZuOaaa+w73/lOQmTvnYoaoxpPUaNR5lRmy+OpzqjO53GMwBiJs94LdFkm9fXy5cdF4RyoJ47HQJTrvOL1get6+fPbCDFUZ1TnUxw7I96vaMRsJ8rcuiycFEAa0ar5jNIaeP755+2ggw6yd99910aMGJE9yeHLWm255ZYVmdatW2cPPvigffvb37YlS5bYFltsYXPmzLH999+/4rGt3EGNUY2nqC0ocyqz5fFUZ1Tn8zhGYIzEOZDrblkm9QNh9GOjcA7UE8djIMrYqXYdVOMhhyB3790GynB/IkI/jMAY5To40BlPlLl1WTgpgAy0RXN8qQ2cfvrp9tOf/jR7qfmzzz5rH/jAB2rmef311+3AAw+0V155xU499VS79957a/6MZh6gxqjGUxR7ZU5ltjye6ozqfB7HCIzqnP7jhEZs999/v02YMCHZJbCicDYilnwGBhplIMI1Qo1RjYccgty9qA2kfH8iQj+MwEgOUd1sghyiOk+t2osCSKtM8z1JGthtt92ypzf85edf+cpX6j7HKVOmZC9D96dI/vWvf9X9Oc04UI1Rjaco5sqcymx5PNUZ1fk8jhEY1TkHDRqUFS0asfm7wVJ9B0gUzkbEkc/AQKMMRLhGqDGq8ZBDkLv3N56len8iQj+MwEgOUf1sghyielfN3pMCSLMN8/lJGxg6dKitXbvW5s6da/vuu2/d5/riiy/a6NGjs3eFrF69uu7PacaBaoxqPEUxV+ZUZsvjqc6ozudxjMCozumFgUZuKRdAInA2kpHPwsBADUS4RqgxqvGQQ5C79zeOpXp/IkI/jMBIDlHbLIIcojZfzdqbAkizzPK5pTCwww472GuvvWYzZ8604447ru5zfvTRR+2EE06wj3zkI/bqq6/W/TnNOFCNUY2nKObKnMpseTzVGdX5PI4RGNU5/X1e/o6v3XffPXvfV73byy+/bM8880yyT4BE4aw3fhyHgWYYiHCNUGNU4yGHIHfvb2xL9f5EhH4YgZEcorqZBTlEdZ5atRcFkFaZ5nuSNHDUUUfZr371Kzv00EOzv/UsleE3Vw4//HB76qmnsr+PP/54UqxqjGo8RY1FmVOZLY+nOqM6n8cxAqM65z777GN/+9vf7IADDsgKGPVuqb/YLwpnvfHjOAw0w0CEa4QaoxoPOQS5e1EbSPn+RIR+GIGRHKK6mQU5RHWeWrUXBZBWmeZ7kjQwffp0O+WUU7LCx/HHH28//OEPs1/9VrutWLHCvv71r9sjjzySfcbPfvYzGzduXLWHt2Q/NUY1nqJGoMypzJbHU51Rnc/jGIFRnfPcc8/N3vHlSxG89dZbVu+SWKknL1E4WzJp4kswUKWBCNcINUY1HnIIcve+2kDq9yci9MMIjOQQ1U0WyCGq89SqvSiAtMo035OsAV/66rHHHssKGFtssUX2FMeYMWOss7PTdtppJxs2bJhttdVW2btCVq5cacuWLbMFCxbY008/bU888YR1dXWZv9jo2GOPNX/UNMVNjVGNp6jNKHMqs+XxVGdU5/M4RmBU5rzzzjvtvPPOy67vvhb2pz71qbou0aknL1E46woeB2GgiQYiXCPUGNV4yCHI3ct4fyJCP4zASA5ReYJBDlHZUSv3oADSStt8V5IG1qxZY2eddZZNmzYtO79alsHywodv/tTHPffcY0OGDIGxBQYixMw1KnMqs+VdQJ1RnU+9D/YcqlVjOW/ePBs1alR2Xb/jjjvMn5SoZ0s9eYnCWU/sOAYDzTSgOnYqXx8ixEx9/hIhhuqM6nzqfVD5GpGzRZlbR+HM40oBpJmzYj67VAb8iY6bbrrJfvvb32Y3nitt/lSIvztk/Pjx9rnPfa7S7kn8uxqjGk9RI1HmVGbL46nOqM7ncYzAqMi5fv16mzhxYvaU5mc+85nsCc96tlWrVtnrr7+eHbrLLrvU8xFNPSYKZ1Ml8uEYGICBCNcINUY1HnIIcndvA2W7PxGhH0ZgJIconkCQQwxgctWEQymANEEqH1luAz5IzZ071+bPn29Lly7N1g1/5513sqc7hg8fni2Ltffee9vo0aOz5bHKuKkxqvEUtSllTmW2PJ7qjOp8HscIjJE4y3j95pwxgIF0DUS4RqgxqvGQQ5C7l/H+RIR+GLaEsqMAACAASURBVIGRHCLd+QlntsEABRBaAgYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAA3IGKIDIhRQgDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGKIDQBjBQpQFfY3v58uXZ3iNGjKjyqHLtpsaoxlPUmpQ5ldnyeKozqvN5HCMwqnMSw3LNVzhbDJTJQITxRY1RjYccgty9TGNmlBxJfW7ds80pj6nKbGoxpABSxisB59wWAy+99JKNHDnSBg0aZF1dXW05h2Z/qRqjGk9R/JU5ldnyeKozqvN5HCMwqnMSw2bPMPh8DMQ1EGF8UWNU4yGHIHcv4wgcoR9GYCSHKGPv2/ycFdoqBRCNtghFCwzkHb6joyP7ta/ipsaoxlMpeVFsmxFiqM6oztdzUq/YB3uOO8qxVGaLEkPFeRlMGgYijC9qjGo85BDk7mUcTSP0wwiM6rkSMSzP6EIBpDyx4kzbbCDCwKbGqMZD8kLy0uZhsK6vj9APIzCSvNTV/JM7KEpbTU48JxTaQIR+p8aoxkMOQQ5RxkE4Qj+MwEgOUcbet/k5K7RVCiAabRGKFhhQ6PCVNKkxqvGQvJC8VOrDKf57hH4YgZHkJcXeVfs5RWmrtZvhCAw0z0CEfqfGqMZDDkEO0bwRrnmfHKEfRmAkh2heH2nlJyu0VQogrWwxfFepDSh0+EoBUGNU4yF5IXmp1IdT/PcI/TACI8lLir2r9nOK0lZrN8MRGGiegQj9To1RjYccghyieSNc8z45Qj+MwEgO0bw+0spPVmirFEBa2WL4rlIbUOjwlQKgxqjGQ/JC8lKpD6f47xH6YQRGkpcUe1ft5xSlrdZuhiMw0DwDEfqdGqMaDzkEOUTzRrjmfXKEfhiBkRyieX2klZ+s0FYpgLSyxfBdpTag0OErBUCNUY2H5IXkpVIfTvHfI/TDCIwkLyn2rtrPKUpbrd0MR2CgeQYi9Ds1RjUecghyiOaNcM375Aj9MAIjOUTz+kgrP1mhrVIAaWWL4btKbaCrq8uWL1+eMeyyyy6lZik6eTVGNZ4ocevJGSGG6ozqfN5eIzCqcxJDyWkNUBhIwkCE8UWNUY2HHILcPYnBsMaTiNAPIzCSQ9TY8BPdXaGtUgBJtHFxWhjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDNRvgAJI/e44EgMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAgUQNUABJNDCcFgYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAA/UboABSvzuOxMBGAw8++KBNmDDBOjo6bNGiRZJm1BjVeIoanTKnMlseT3VGdT6PYwRGdU5iKDmtAQoDSRiIML6oMarxkEOQuycxGNZ4EhH6YQRGcogaG36iu5elrVIASbQBcVrlMjB16lQ788wzswLI+vXry3XyVZ6tGqMaT1EYlTmV2fJ4qjOq83kcIzCqcxLDKicK7IYBDNRsIML4osaoxkMOQe5e88CVwAER+mEERnKIBDpTA06hLG2VAkgDgs1HYKAsHX4gkVJjVOMheSF5GUj/btexEfphBEaSl3b1oMZ+b5S22lhrfBoGBmYgQr9TY1TjIYcghxjYKNaeoyP0wwiM5BDt6T+N/taytFUKII2OPJ8X0kBZOvxAgqPGqMZD8kLyMpD+3a5jI/TDCIwkL+3qQY393ihttbHW+DQMDMxAhH6nxqjGQw5BDjGwUaw9R0fohxEYySHa038a/a1laasUQBodeT6vVAauu+66hpzvvHnzbObMmUkugaXGqMZT1ACVOZXZ8niqM6rzeRwjMKpzEsPapjgpz2VqI2FvDDTfQITxRY1RjYccov5+nvL1Tr2dqvOpz6179jrlWCqzRYlhX1cICiD1Xzc5UsDAoEGDsqJFI7bu7u4kCyBqjGo8RW1PmVOZLY+nOqM6n8cxAqM6JzGsfXaT6lymdhKOwEBzDUQYX9QY1XjIIQbWx1O93qm3U3U+9bl1z16nHEtltigxpAAysGskRwsayAc2nwA1YkvxJehqjGo8lZIXxbYZIYbqjOp8PZMXxT7Y18RXkTNCO43UVhsxT+MzMNAoAxHGFzVGNR5yiIH3ZnL3gTus9RMi9MMIjOrzT2JYa8/esH+KY2pPEp4AqS+uHCViYNttt7WVK1faIYccYtdcc03dVI8//rhNmjQpyQ6vxqjGU9TolDmV2fJ4qjOq83kcIzCqcxLD2qY1Kc9laiNhbww030CE8UWNUY2HHILcvb+RLtVreoR+GIGRHKK6eUaq/TDKPYveUaIAUl27ZS9RA4ceeqg9+eSTtscee9g//vGPuilTfumPGqMaT1GjU+ZUZsvjqc6ozudxjMCozkkMa5vWpDyXqY2EvTHQfAMRxhc1RjUecghy9/5GulSv6RH6YQRGcojq5hmp9sMo9ywogFTXTtkriIHLL788e3LDH3F74403sl/81rOlPLCpMarxFLU3ZU5ltjye6ozqfB7HCIzqnMSwthlNynOZ2kjYGwPNNxBhfFFjVOMhhyB3L2MBJEI/jMBIDlHdPCP1uXWUtppHiydAqmu37CVq4KGHHrIvfvGL2dJVs2fPtsMOO6wu0pQHNjVGNZ6iBqfMqcyWx1OdUZ3P4xiBUZ2TGNY2pUl5LlMbCXtjoPkGIowvaoxqPOQQ5O5lLIBE6IcRGMkhqptnpD63jtJWKYBU117ZS9zAsmXLbMSIERnlxIkTs1/81rN58eT//u//skN9Sa2UNjVGNZ6itqLMqcyWx1OdUZ3P4xiBUZ2TGNY2G0l5LlMbCXtjoPkGIowvaoxqPOQQ5O79jXSpXtMj9MMIjOQQ1c0zUu2HUe5Z9I4ST4BU127ZS9jAkiVLrLu724YPH27bb7+9JKkaoxpPUaNT5lRmy+OpzqjO53GMwKjOSQwlpzVAYSAJAxHGFzVGNR5yCHL3JAbDGk8iQj+MwEgOUWPDT3T3KG3V9VMASbQRcloYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQzUb4ACSP3uOBIDGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgIFEDVAASTQwnBYGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAP1G6AAUr87jsQABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYCBRAxRAEg0Mp1UuA+vXr7fly5dnJz1ixIhynXyVZ6vGqMZTFEZlTmW2PJ7qjOp8HscIjOqcxLDKiQK7YQADNRuIML6oMarxkEOQu9c8cCVwQIR+GIGRHCKBztSAUyhLW6UA0oBg8xHlN/D222/bLbfcYg888IAtWrTIBg0aZJ2dnfblL3/Zzj//fBsyZEi/kC+99JKNHDkyO66rqytJIWqMajxFjUaZU5ktj6c6ozqfxzECozonMdSZyyQ5weKkQhuIML6oMarxkEOQu/fVBlK/PxGhH0ZgJIco/31C9Rj2HB8pgISesgPvBpYuXWqHH364LVy4MBPS3d2d/e3o6Mj+7rzzzjZ16lQbM2ZMobB8guHHePUztU2NUY2nqL0ocyqz5fFUZ1Tni3J9UOeM0E7VY5janIrzwUCU67zi2MI1ofz5bYQYqjOq8ymOndyv0LxPGKmtZvd4u/O7vcxlMRDQgBcrDjzwQHvhhRcy+q222so++clP2po1a2z+/Pkbn+bwJztuvPFGmzBhQp+WUi6AqDGq8RR1O2VOZbY8nuqM6nwexwiM6pzEUGcuE3CKCnLiBiKML2qMajzkEOTuZbw/EaEfRmAkh9iw6kuZ7xOqx7CvayQFkMQn15xecw1Mnz7dTjnllOxpjy996Ut2++232/bbb5996X/+8x+76aab7LbbbssKIb7PpZdemv1/vbeUCyBqjGo8RS1cmVOZLY+nOqM6n8cxAqM6JzHUmcs0dzbIp2OgdgMRxhc1RjUecghy9zLen4jQDyMwkkOU/z6hegwpgNQ+t+UIcQNjx461WbNm2X777WfPPvvsxmWvemI///zzWXFk2bJl2b+fe+65dscdd2xiJuUCiBqjGk9RF1PmVGbL46nOqM7ncYzAqM5JDN+7wpR9LiM+HQWvhAYijC9qjGo85BDk7mW8PxGhH0ZgJIcwU5hbR2mr+fWSJ0BKOOHmlBtnwN/vsWLFCrvvvvuyJ0GKttdee82OPfZY+9Of/pQVQcaNG2f33nuvbbHFFtkhKRdA1BjVeIranDKnMlseT3VGdT6PYwRGdU5iuOkVpsxzmcbN/PgkDDTGQITxRY1RjYccgty9jPcnIvTDCIzkEBtG4LLPraO0VQogjZn78iklNzB06FBbu3Zt9g6QT3/60/3SrFy50o4//nh76qmnsiLIcccdZ/fff79tueWWSRdA1BjVeIoanTKnMlseT3VGdT6PYwRGdU5iuPkVpqxzmZJPNzl9QQMRxhc1RjUecghy9zJe0yP0wwiM5BDvjcBl7IdR7ln0vk7yBIjghByk6g0MGzbMVq9ebXPmzMlehl5p85ej+3JYv/jFL7IiyGGHHWYzZ860V155xUaOHJn9f/7Sq5Q2NUY1nqK2osypzJbHU51Rnc/jGIFRnZMY9n2FKeNcJqV5FeeCAfWxU3UuwzWh/NeECDFUZ1Tni3J9UOeM0E7VY9jXFY8CCHP40AY6Oztt4cKFNmXKFDv99NOrcuEFjtNOO81+/vOfZwWPgw46yCZNmpT9TbEAosaoxlPU6JQ5ldnyeKozqvN5HCMwqnMSw+JpTdnmMlVN0NgJAy00EGF8UWNU4yGHIHfP20CZrukR+mEERnKIzUfgMvXDKPcsekeJAkgLJ8p8VXoG/F0eM2bMyIofP/nJT6o+we7ubvvqV79qd999d1b02HHHHTe+JD21J0DUGNV4ihqdMqcyWx5PdUZ1Po9jBEZ1TmLY/7SmTHOZqido7IiBFhmIML6oMarxkEOQu/dsA2W5pkfohxEYySH6HoHL0g+j3LOgANKiSTFfUw4Dd9xxh11wwQXZUievvvqqbbPNNjWd+Le+9S279dZbsyKID3YpPgGixqjGU9TglDmV2fJ4qjOq83kcIzCqcxLD6qY0ZZjLVEfCXhhonYEI44saoxoPOQS5e19tIPVreoR+GIGRHKL/+Ubq/TDKPQsKIK2bF/NNJTCwdOlS23XXXbMz9WWsxo8fX/NZX3PNNXbddddlx6VYAFFjVOMpanDKnMpseTzVGdX5PI4RGNU5iWH1U5rU5zLVk7AnBlpjIML4osaoxkMOQe5e1AZSvqZH6IcRGMkhKs81Uu6HUe5ZUACp3E7ZI5iBq6++2lasWGEf/OAH7cYbb6yLfvLkyfbQQw9lxz755JN1fUYzD1JjVOMpir0ypzJbHk91RnU+j2MERnVOYlj97CL1uUz1JOyJgdYYiDC+qDGq8ZBDkLsXtYGUr+kR+mEERnKIynONlPthlHsWPaPEO0Aqt1n2wAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgoGQGKICULGCcLgYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAA5UNUACp7Ig9MIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYKJkBCiAlCxin2xoD//73v23+/PnZS3BXrlxpq1evtqFDh9qwYcNs5513tr322st22WWX1pxMk75FjVGNpyjsypzKbHk81RnV+TyOERjVOYmhzlymSVMkPhYDdRuIML6oMarxkEOQu9c9gLXxwAj9MAIjOUT57xMqx5ACSBsHeb46LQOLFy+2W2+91WbOnGnLli2reHI77rijjR071i6++GLbfffdK+6fwg5qjGo8RW1EmVOZLY+nOqM6n8cxAqM6JzHs+wpTxrlMCvMpzgEDPQ1EGF/UGNV4yCHI3b0NlO2aHqEfRmAkh9h0BC5bP4xyz8I5KYAwf8eAmV111VU2adIk6+rqsu7u7qqddHR02ODBg+2yyy6z66+/vurj2rGjGqMaT1GbUOZUZsvjqc6ozudxjMCozkkM+591lGku0475E9+Jgf4MRBhf1BjVeMghyN17toGyXNMj9MMIjOQQfY/AZemHUe5Z5JwUQJjThzdw/vnn25133rmx8LHnnnvamDFjrLOzM1vuaptttrGtt97a1qxZY6tWrcqWxVqwYIH97ne/y/5mlcSODjvnnHPsRz/6UZI+1RjVeIoajTKnMlseT3VGdT6PYwRGdU5iqDOXSXKCxUmFNhBhfFFjVOMhhzAjdy/f/YkI/TACIzlE+e8Tqsew9zWSAkjoaTvws2fPtqOPPjorYOy77742efJk23///asW89xzz9lFF11kL7zwQvYZv/zlL+2II46o+vhW7KjGqMZT1AaUOZXZ8niqM6rzeRwjMKpzEsPqZhllmMtUR8JeGGidgQjjixqjGg85BLl7X20g9Wt6hH4YgZEcov/5Rur9MMo9CwogrZsX800lMHDSSSfZww8/bKNGjbLf//732YvOa93eeecdO+igg2zevHl2wgkn2EMPPVTrRzR1fzVGNZ6i4CtzKrPl8VRnVOfzOEZgVOckhtVPL1Kfy1RPwp4YaI2BCOOLGqMaDzkEuXtRG0j5mh6hH0ZgJIeoPNdIuR9GuWdBAaRyO2WPQAZ8iasVK1bYtGnT7OSTT66bfMaMGTZu3LjsxWO+RFZKmxqjGk9RW1HmVGbL46nOqM7ncYzAqM5JDGubjaQ8l6mNhL0x0HwDEcYXNUY1HnIIcvf+RrpUr+kR+mEERnKI6uYZqfbDKPcsKIBU107ZK4iBIUOG2Lp162zu3LnZElj1bi+++KKNHj06e1fI6tWr6/2YphynxqjGUxR0ZU5ltjye6ozqfB7HCIzqnMSwtmlFynOZ2kjYGwPNNxBhfFFjVOMhhyB372+kS/WaHqEfRmAkh6hunpFqP4xyz4ICSHXtlL2CGIhQnVdjVOPh11v8eotfb/H0XDsvucpjqjJbzzYThbOd/YTvxkBvAxH6nRqjGg85BDkEOQQ5RDuvzspjqjJb5ByCl6C3c8Tgu9tuIF+f0Z/+mDNnTvYER61b6mv7qTGq8RS1N2VOZbY8nuqM6nwexwiM6pzEsPoZTepzmepJ2BMDrTEQYXxRY1TjIYcgdy9qAylf0yP0wwiM5BCV5xop98Mo9yx6R4kCSOV2yx7CBh5//HE75phjrKOjI1vCavLkydnfajdfOuvCCy+0P/7xj9lnPPbYY3bUUUdVe3hL9lNjVOMpagTKnMpseTzVGdX5PI4RGNU5iWF104wyzGWqI2EvDLTOQITxRY1RjYccgty9rzaQ+jU9Qj+MwEgO0f98I/V+GOWeBQWQ1s2L+aaSGPja175md911V1bA8K2zs9PGjBmT/d1pp51s2LBhttVWW9natWtt5cqVtmzZMluwYIE9/fTT2V/furu77eyzz84+J8VNjVGNp6jNKHMqs+XxVGdU5/M4RmBU5ySGOnOZFOdXnFNsAxHGFzVGNR5yCHL3Mt6fiNAPIzCSQ5T/PqF6DCmAxJ6nQ19g4IorrrDvfve71tXVtbEQUo0sL3wMHjzYxo8fbxMnTqzp2Go+v5H7qDGq8RTFWplTmS2PpzqjOp/HMQKjOicx7H82Uaa5TCPnRXwWBhphIML4osaoxkMOseFHjNVsZbreqbdTdT71uXXP/qYcS2W2KDHsyckSWNVcKdknhIFFixbZzTffbLNmzbLly5dXZN5hhx3shBNOsEsuucT22GOPivunsIMaoxpPURtR5lRmy+OpzqjO53GMwKjOSQz7vsKUcS6TwnyKc8BATwMRxhc1RjUecghyd28DZbumR+iHERjJITYdgcvWD6Pcs3BOCiDM3zHQh4HFixfb/PnzbenSpfbWW2+Zv8BoyJAhNnz48GxZrL333tt22223UrtTY1TjKWpcypzKbHk81RnV+TyOERjVOYmhzlym1BMxTl7SQITxRY1RjYccgty9jINrhH4YgZEcovz3CZVjSAGkjFcHzhkDGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgIF+DVAAoYFgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjAgZ4ACiFxIAcIABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYIACCG0AAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABOQMUQORCClC9Bp555hl74IEHbNGiRTZo0CDr7Oy0k08+2UaNGlXxIxcuXGhHHnmkdXR0ZMenuqkxqvEUtRtlTmW2PJ7qjOp8HscIjOqcxFBnLpPqHIvzimsgwviixqjGQw5B7t67DZTh/kSEfhiBkRyieP5Thn4Y5Z6Fc1IAiTtXh/z/G1i3bp2deeaZNm3atD6dnHjiiXb77bfbhz70oUJnL730ko0cOTIrgKxfvz45t2qMajxFDUaZU5ktj6c6ozqfxzECozonMdwwIinMZZKbXHFC4Q1EGF/UGNV4yCE2N6BwvVNvp+p86nPrnr1OOZbKbFFi2PsKQQEk/NQdAWeccYbdd999hSK8qPHhD3/Y7r//fjv44IP73C/1AogaoxpPUeNT5lRmy+OpzqjO53GMwKjOSQw3jEgKcxlmrBhIzUCE8UWNUY2HHGJzAwrXO/V2qs6nPrfu2euUY6nMFiWGFEBSmzlzPm01MGfOHDvkkEOyGwN77LGHff/737fPfvaztnbtWnvqqads0qRJNnfu3OwchwwZYtOnT7fjjz9+s3NOuQCixqjGU9QBlDmV2fJ4qjOq83kcIzCqcxJDnblMWyeLfDkG+jAQYXxRY1TjIYcgdy/j/YkI/TACIzlE+e8Tqsewr2skT4AwpQ9twJe+mjp1qu200042b94823777Tfx0d3dbTfffLNdfvnl1tXVZYMHD7YpU6bYqaeeusl+KRdA1BjVeIo6oDKnMlseT3VGdT6PYwRGdU5iuGFEUpjLhJ6sAp+kgQjjixqjGg85BLl7Ge9PROiHERjJIcp/n1A9hhRAkpw+c1LtNLDnnnvayy+/nBU5Lr744sJTefrpp7P1s//3v/9lL0j/wQ9+YOedd97G/VMugKgxqvEUNTplTmW2PJ7qjOp8HscIjOqcxHDTK0yZ5zLtnCvy3Rjoy0CE8UWNUY2HHILcvYz3JyL0wwiM5BAbRuCyz62jtNX8eskTIMzpQxsYPny4vf322/bss8/afvvt168LL3IceeSRtmLFimzJLF8ea/z48dkxKRdA1BjVeIoanTKnMlseT3VGdT6PYwRGdU5iuPkVpqxzmdCTVeCTNBBhfFFjVOMhhyB3L+M1PUI/jMBIDvHeCFzGfhjlnkXv6yQFkCSn1JxUqwz4upnr1q3L3vOx7777VvzaxYsX22GHHWb+14sgV155pV177bVJF0DUGNV4ihqdMqcyWx5PdUZ1Po9jBEZ1TmLY9xWmjHOZihM0dsBAiw1EGF/UGNV4yCHI3b0NlO2aHqEfRmAkh9h0BC5bP4xyz4ICSIsnx3xd2gZGjBhhy5cvtwceeMC+8IUvVHWy/gTI4YcfbvPnz8+KIJdccomdddZZNnLkyOx/r1+/vqrPadVOaoxqPEXtQJlTmS2PpzqjOp/HMQKjOicxLJ5plG0u06o5E9+DgWoNRBhf1BjVeMghyN3zNlCma3qEfhiBkRxi8xG4TP0wyj0LCiDVzmrZL4SBY445xmbPnp29/8PfA1Lt9sYbb9gRRxxhf/7zn7Oix+c//3n7zW9+k2QBRI1RjaeozSlzKrPl8VRnVOfzOEZgVOckhv3Paso0l6l2fsZ+GGiVgQjjixqjGg85BLl7zzZQlmt6hH4YgZEcou8RuCz9MMo9CwogrZoV8z2lMHDjjTfaFVdcYTvuuKMtWbIkK2BUu7355pvZDbI//OEP2XHd3d1JFkDUGNV4itqbMqcyWx5PdUZ1Po9jBEZ1TmJYeUZTlrlMZRL2wEBrDUQYX9QY1XjIIcjde7eBMlzTI/TDCIzkEMVzjjL0wyj3LCiAtHZuzLclbsCf4PB3f3gBY8aMGXbSSSfVdMarV6+2sWPH2q9//evsuBSXwFJjVOMpanDKnMpseTzVGdX5PI4RGNU5iWF1U5oyzGWqI2EvDLTOQITxRY1RjYccgty9rzaQ+jU9Qj+MwEgO0f98I/V+GOWeBQWQ1s2L+aaSGBgzZoz5en177bWXzZo1q+az9peojxs3zh5++OEkCyAOpMaoxlPU6JQ5ldnyeKozqvMpjp2MNZrX+EhtteZJGgdgoIkGuA5WlptanhQhZurXhAgxVGdU51Pvgz1HfuVYKrNFiSEFkMrzNPbAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGCg5AY6uv3FBWwYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgQMgABRChYIKCAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMDABgMUQGgJGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMyBmgACIXUoAwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAAxigAEIbwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgQM4ABRC5kAKEAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABRDaAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAA3IGKIDIhRQgDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGKIDQBjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGJAzQAFELqQAYQADGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwQAGENoABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwICcAQogciEFCAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQogtAEMcqx17gAAAkRJREFUYAADGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAbkDFAAkQspQBjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDFAAoQ1gAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjAgZ4ACiFxIAcIABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYIACCG0AAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABOQMUQORCChAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMUQGgDGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMyBmgACIXUoAwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAAxigAEIbwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgQM4ABRC5kAKEAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABRDaAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGMIABDGAAA3IGKIDIhRQgDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwAAGKIDQBjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGJAzQAFELqQAYQADGMAABjCAAQxgAAMYwAAGMIABDGAAAxjAAAYwQAGENoABDGAAAxjAAAYwgAEMYAADGMAABjCAAQxgAAMYwICcAQogciEFCAMYwAAGMIABDGAAAxjAAAYwgAEMYAADGMAABjCAgf8HJVxB9DEcx7kAAAAASUVORK5CYII=\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8., 6.))\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.plot(tmins, Tmins, 'o')\n",
    "plt.ylabel(\"Min temp RuOx (K)\")\n",
    "plt.ylim(0.01, 0.03)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.plot(tmins, max_tank_pressure, 'o')\n",
    "plt.ylabel(\"Max tank pressure (bar)\")\n",
    "plt.ylim(0.9, 1.05)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.plot(tmins, T4ks, 'o')\n",
    "plt.ylim(3, 7)\n",
    "plt.ylabel(\"Min temp 4K plate (K)\")\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.subplot(2, 2, 4)\n",
    "plt.plot(tmins, min_dewar_pressure, 'o')\n",
    "plt.yscale('log')\n",
    "plt.ylabel(\"Min OVC pressure (bar)\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylim(1e-7, 1e-5)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}