{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dependency of the Young's modulus to plastic strain in DP steels: a consequence of heterogeneity ?\n",
    "\n",
    "Authors : Ludovic Charleux, Laurent Tabourot, Emile Roux, Moustapha Issack Farah, Laurent Bizet\n",
    "\n",
    "DP980 steel tensile test simulation using a compartmentalized model.\n",
    "\n",
    "\n",
    "## Packages and various functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib nbagg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import compmod2 as cp2\n",
    "import argiope as ag\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import inspect, os, local_settings, scipy\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits import mplot3d as mpl3d\n",
    "import matplotlib.colors as colors\n",
    "import matplotlib as mpl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# USEFUL FUNCTIONS\n",
    "def create_dir(path):\n",
    "    try:\n",
    "        os.mkdir(path)\n",
    "    except:\n",
    "        pass\n",
    "# SETTINGS\n",
    "workdir   = \"_workdir/\"\n",
    "outputdir = \"outputs/\"\n",
    "\n",
    "label   = \"RVE\"\n",
    "create_dir(workdir)\n",
    "create_dir(workdir + outputdir)\n",
    "create_dir(workdir + \"reports/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model creation\n",
    "\n",
    "The mode relies on two dedicated packages:\n",
    "\n",
    "* **CompMod2**: compartmentalized model dedicated package.\n",
    "* **Argiope**: FEM data/model management package.\n",
    "\n",
    "Each parameter of the simulation can be tuned in this section and run into Abaqus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "shape = np.array([10, 10, 10]) # Number of elements in each direction for the RVE\n",
    "Ne = shape.prod()\n",
    "\n",
    "def element_map(mesh):\n",
    "    \"\"\"\n",
    "    Element type definition.\n",
    "    \"\"\"\n",
    "    mesh.elements.loc[:, (\"type\", \"solver\", \"\") ] = \"C3D8R\"\n",
    "    return mesh\n",
    "    \n",
    "def material_map(mesh):\n",
    "    \"\"\"\n",
    "    Material name definition\n",
    "    \"\"\"\n",
    "    mesh.elements.materials = [\"mat{0}\".format(i) for i in mesh.elements.index]\n",
    "    return mesh\n",
    "\n",
    "def make_dist(k1, k2, l1, l2, w1):\n",
    "    \"\"\"\n",
    "    Double Weibull distribution.\n",
    "    \"\"\"\n",
    "    w2 = 1. - w1\n",
    "    d1 = cp2.distributions.Weibull(k = k1, l = l1)\n",
    "    d2 = cp2.distributions.Weibull(k = k2, l = l2)\n",
    "    dist = cp2.distributions.CompositeDistribution(dists = [d1, d2], weights = [w1, w2])\n",
    "    return dist\n",
    "\n",
    "\n",
    "dist = make_dist(k1 = 1.64,    k2 = 3.17, \n",
    "                 l1 = 4.16e-3, l2 = 3.42e-2, \n",
    "                 w1 = 8.67e-1)\n",
    "\n",
    "# Distribution Discretization Procedure (DDP)\n",
    "xt, x = dist.discretize(Ne, xmax = 1.)\n",
    "\n",
    "# random compartment element mapping (CEM)\n",
    "RVE = np.arange(Ne) \n",
    "np.random.shuffle(RVE) # Random RVE\n",
    "x = x[RVE]\n",
    "\n",
    "\n",
    "# Generation of the material of each compartment\n",
    "E = 213.e3 # Young's modulus (MPa)\n",
    "nu = .3    # Poisson ratio\n",
    "materials = [ag.materials.ElasticPerfectlyPlastic(\n",
    "                                 label = \"mat{0}\".format(i+1), \n",
    "                                 young_modulus = E, \n",
    "                                 poisson_ratio = nu, \n",
    "                                 yield_stress = x[i] * E) # Spectification of the yield_stress for each compartment\n",
    "                                 for i in range(Ne)]\n",
    "\n",
    "# Definition of the laoding path aplly to the RVE\n",
    "disp_values = np.linspace(0., .1, 10)[1:] # 9 Loading-unloading-reloading cycles\n",
    "steps = []\n",
    "for i in range(len(disp_values)):\n",
    "    steps += [cp2.models.RVEStep(name = \"loading{0}\".format(i), \n",
    "                                cx = (\"disp\", disp_values[i]),\n",
    "                                field_output_frequency = 100),\n",
    "             cp2.models.RVEStep(name = \"unloading{0}\".format(i), \n",
    "                                cx = (\"force\", 0.),\n",
    "                                field_output_frequency = 100),\n",
    "             cp2.models.RVEStep(name = \"reloading{0}\".format(i), \n",
    "                                cx = (\"disp\", disp_values[i]),\n",
    "                                field_output_frequency = 100),]\n",
    "\n",
    "sample = cp2.models.RVESample(shape = shape,\n",
    "                              element_map = element_map,\n",
    "                              material_map = material_map)\n",
    "\n",
    "model  = cp2.models.RVETest(label = label,\n",
    "                           parts = {\"sample\":sample},\n",
    "                           steps = steps,\n",
    "                           materials = materials,\n",
    "                           solver = \"abaqus\", \n",
    "                           solver_path = local_settings.ABAQUS_PATH,\n",
    "                           workdir = workdir,\n",
    "                           verbose = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation Execusion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "if False: # If True, the simulation will be run in Abaqus. Check load_settings.py before running this cell.\n",
    "    model.write_input()\n",
    "    model.run_simulation()\n",
    "    model.postproc()\n",
    "    model.save(workdir + label + \".pckl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation post-processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All output data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">areas</th>\n",
       "      <th colspan=\"3\" halign=\"left\">dimensions</th>\n",
       "      <th colspan=\"3\" halign=\"left\">disp</th>\n",
       "      <th>energies</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"5\" halign=\"left\">strains</th>\n",
       "      <th colspan=\"3\" halign=\"left\">stress</th>\n",
       "      <th>time</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>A1</th>\n",
       "      <th>A2</th>\n",
       "      <th>A3</th>\n",
       "      <th>L1</th>\n",
       "      <th>L2</th>\n",
       "      <th>L3</th>\n",
       "      <th>U1</th>\n",
       "      <th>U2</th>\n",
       "      <th>U3</th>\n",
       "      <th>We</th>\n",
       "      <th>...</th>\n",
       "      <th>E22</th>\n",
       "      <th>E33</th>\n",
       "      <th>LE11</th>\n",
       "      <th>LE22</th>\n",
       "      <th>LE33</th>\n",
       "      <th>S11</th>\n",
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       "      <th>t</th>\n",
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       "    <tr>\n",
       "      <th>frame</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>0</th>\n",
       "      <td>0.999991</td>\n",
       "      <td>0.999991</td>\n",
       "      <td>0.999991</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.999991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.999935</td>\n",
       "      <td>1.000080</td>\n",
       "      <td>1.000080</td>\n",
       "      <td>1.000111</td>\n",
       "      <td>0.999967</td>\n",
       "      <td>0.999967</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>0.001312</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>-0.000033</td>\n",
       "      <td>23.638306</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.000046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.999873</td>\n",
       "      <td>1.000162</td>\n",
       "      <td>1.000162</td>\n",
       "      <td>1.000222</td>\n",
       "      <td>0.999933</td>\n",
       "      <td>0.999933</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>-0.000067</td>\n",
       "      <td>-0.000067</td>\n",
       "      <td>0.005231</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000067</td>\n",
       "      <td>-0.000067</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>-0.000067</td>\n",
       "      <td>-0.000067</td>\n",
       "      <td>47.157815</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.000095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.999793</td>\n",
       "      <td>1.000226</td>\n",
       "      <td>1.000226</td>\n",
       "      <td>1.000333</td>\n",
       "      <td>0.999900</td>\n",
       "      <td>0.999900</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>0.011713</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>70.501260</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1.000126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.999727</td>\n",
       "      <td>1.000305</td>\n",
       "      <td>1.000305</td>\n",
       "      <td>1.000444</td>\n",
       "      <td>0.999866</td>\n",
       "      <td>0.999866</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>-0.000134</td>\n",
       "      <td>-0.000134</td>\n",
       "      <td>0.020695</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000134</td>\n",
       "      <td>-0.000134</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>-0.000134</td>\n",
       "      <td>-0.000134</td>\n",
       "      <td>93.606420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1.000171</td>\n",
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       "<p>5 rows × 33 columns</p>\n",
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      ],
      "text/plain": [
       "          areas                     dimensions                          disp  \\\n",
       "             A1        A2        A3         L1        L2        L3        U1   \n",
       "frame                                                                          \n",
       "0      0.999991  0.999991  0.999991   1.000000  1.000000  1.000000  0.000000   \n",
       "1      0.999935  1.000080  1.000080   1.000111  0.999967  0.999967  0.000111   \n",
       "2      0.999873  1.000162  1.000162   1.000222  0.999933  0.999933  0.000222   \n",
       "3      0.999793  1.000226  1.000226   1.000333  0.999900  0.999900  0.000333   \n",
       "4      0.999727  1.000305  1.000305   1.000444  0.999866  0.999866  0.000444   \n",
       "\n",
       "                           energies    ...      strains                      \\\n",
       "             U2        U3        We    ...          E22       E33      LE11   \n",
       "frame                                  ...                                    \n",
       "0      0.000000  0.000000  0.000000    ...     0.000000  0.000000  0.000000   \n",
       "1     -0.000033 -0.000033  0.001312    ...    -0.000033 -0.000033  0.000111   \n",
       "2     -0.000067 -0.000067  0.005231    ...    -0.000067 -0.000067  0.000222   \n",
       "3     -0.000100 -0.000100  0.011713    ...    -0.000100 -0.000100  0.000333   \n",
       "4     -0.000134 -0.000134  0.020695    ...    -0.000134 -0.000134  0.000444   \n",
       "\n",
       "                              stress            time    volume  \n",
       "           LE22      LE33        S11  S22  S33     t         V  \n",
       "frame                                                           \n",
       "0      0.000000  0.000000   0.000000  0.0  0.0  0.00  0.999991  \n",
       "1     -0.000033 -0.000033  23.638306  0.0  0.0  0.01  1.000046  \n",
       "2     -0.000067 -0.000067  47.157815  0.0  0.0  0.02  1.000095  \n",
       "3     -0.000100 -0.000100  70.501260  0.0  0.0  0.03  1.000126  \n",
       "4     -0.000134 -0.000134  93.606420  0.0  0.0  0.04  1.000171  \n",
       "\n",
       "[5 rows x 33 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = ag.utils.load(workdir + label + \".pckl\")\n",
    "data = model.data[\"history\"]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### True strain vs. true stress curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"638.888905813665\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "for i in data.step.s.unique():\n",
    "    step = data[data.step.s == i]\n",
    "    color = \"rgb\"[i%3]\n",
    "    plt.plot(step.strains.LE11, step.stress.S11, \"-\" + color, \n",
    "             label = \"step {0}\".format(i))\n",
    "plt.xlabel(r\"Tensile True Strain, $\\varepsilon$\")\n",
    "plt.ylabel(r\"Tensile True Stress, $\\sigma$\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Moduli calculation\n",
    "base on the protocol described in : Chen, Z., Gandhi, U., Lee, J., Wagoner, R.H., 2016b. Variation and consistency of young’s\n",
    "15 modulus in steel. J. Mater. Process. Technol. 227, 227–243. (https://doi.org/10.1016/j.jmatprotec.2015.08.024)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epsmax</th>\n",
       "      <th>epsp</th>\n",
       "      <th>mic</th>\n",
       "      <th>E1wag</th>\n",
       "      <th>E2wag</th>\n",
       "      <th>E3wag</th>\n",
       "      <th>E4wag</th>\n",
       "      <th>Ecwag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.011050</td>\n",
       "      <td>0.006428</td>\n",
       "      <td>1.0</td>\n",
       "      <td>209090.338143</td>\n",
       "      <td>157098.837833</td>\n",
       "      <td>209313.102413</td>\n",
       "      <td>156177.948216</td>\n",
       "      <td>179912.149766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.021979</td>\n",
       "      <td>0.016629</td>\n",
       "      <td>1.0</td>\n",
       "      <td>208178.024244</td>\n",
       "      <td>144962.584673</td>\n",
       "      <td>208781.412172</td>\n",
       "      <td>143510.235925</td>\n",
       "      <td>171676.021204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.032790</td>\n",
       "      <td>0.027000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>207649.990947</td>\n",
       "      <td>137960.719408</td>\n",
       "      <td>208267.703926</td>\n",
       "      <td>136193.294097</td>\n",
       "      <td>166814.630150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.043485</td>\n",
       "      <td>0.037331</td>\n",
       "      <td>1.0</td>\n",
       "      <td>207266.591647</td>\n",
       "      <td>132680.462692</td>\n",
       "      <td>208033.880672</td>\n",
       "      <td>130698.949517</td>\n",
       "      <td>162958.952609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.054067</td>\n",
       "      <td>0.047586</td>\n",
       "      <td>1.0</td>\n",
       "      <td>206973.833463</td>\n",
       "      <td>128381.920661</td>\n",
       "      <td>207970.526822</td>\n",
       "      <td>126304.004381</td>\n",
       "      <td>159688.966127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.064539</td>\n",
       "      <td>0.057776</td>\n",
       "      <td>1.0</td>\n",
       "      <td>206803.623750</td>\n",
       "      <td>125055.502364</td>\n",
       "      <td>207622.096375</td>\n",
       "      <td>123169.620041</td>\n",
       "      <td>157097.918161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.074901</td>\n",
       "      <td>0.067881</td>\n",
       "      <td>1.0</td>\n",
       "      <td>206654.886057</td>\n",
       "      <td>122104.666257</td>\n",
       "      <td>207302.743406</td>\n",
       "      <td>119703.357614</td>\n",
       "      <td>154817.595903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.085158</td>\n",
       "      <td>0.077893</td>\n",
       "      <td>1.0</td>\n",
       "      <td>206524.706443</td>\n",
       "      <td>119377.042277</td>\n",
       "      <td>207092.278577</td>\n",
       "      <td>117499.145023</td>\n",
       "      <td>152742.003026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.095310</td>\n",
       "      <td>0.087811</td>\n",
       "      <td>1.0</td>\n",
       "      <td>206409.660893</td>\n",
       "      <td>116858.180686</td>\n",
       "      <td>206808.821996</td>\n",
       "      <td>114622.127271</td>\n",
       "      <td>150811.872560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      epsmax      epsp  mic          E1wag          E2wag          E3wag  \\\n",
       "7   0.011050  0.006428  1.0  209090.338143  157098.837833  209313.102413   \n",
       "8   0.021979  0.016629  1.0  208178.024244  144962.584673  208781.412172   \n",
       "9   0.032790  0.027000  1.0  207649.990947  137960.719408  208267.703926   \n",
       "10  0.043485  0.037331  1.0  207266.591647  132680.462692  208033.880672   \n",
       "11  0.054067  0.047586  1.0  206973.833463  128381.920661  207970.526822   \n",
       "12  0.064539  0.057776  1.0  206803.623750  125055.502364  207622.096375   \n",
       "13  0.074901  0.067881  1.0  206654.886057  122104.666257  207302.743406   \n",
       "14  0.085158  0.077893  1.0  206524.706443  119377.042277  207092.278577   \n",
       "15  0.095310  0.087811  1.0  206409.660893  116858.180686  206808.821996   \n",
       "\n",
       "            E4wag          Ecwag  \n",
       "7   156177.948216  179912.149766  \n",
       "8   143510.235925  171676.021204  \n",
       "9   136193.294097  166814.630150  \n",
       "10  130698.949517  162958.952609  \n",
       "11  126304.004381  159688.966127  \n",
       "12  123169.620041  157097.918161  \n",
       "13  119703.357614  154817.595903  \n",
       "14  117499.145023  152742.003026  \n",
       "15  114622.127271  150811.872560  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moduli"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def modulus(strain, stress, low, high, order = 1):\n",
    "    smax = stress.max()\n",
    "    loc = (stress <= high * smax) & (stress >= low * smax)\n",
    "    stress = stress[loc]\n",
    "    strain = strain[loc]\n",
    "    E = np.poly1d(np.polyfit(strain, stress, order)).deriv(1)(smax)\n",
    "    return E\n",
    "\n",
    "steps = data.step.s.unique()\n",
    "moduli = pd.DataFrame(columns = [\"epsmax\", \"epsp\", \"mic\",\n",
    "                              \"E1wag\", \"E2wag\", \"E3wag\", \"E4wag\", ])\n",
    "trash, nc = moduli.shape\n",
    "Ncycle = int(len(steps)/3)\n",
    "m=1\n",
    "for i in range(Ncycle):\n",
    "    U = data[data.step.s == 3*i+1]\n",
    "    R = data[data.step.s == 3*i+2]\n",
    "    Eu = U.strains.LE11.values\n",
    "    Su = U.stress.S11.values\n",
    "    Er = R.strains.LE11.values\n",
    "    Sr = R.stress.S11.values\n",
    "    moduli.loc[m*nc+i, \"mic\"] = m\n",
    "    moduli.loc[m*nc+i, \"epsmax\"] = Eu.max()\n",
    "    moduli.loc[m*nc+i, \"epsp\"]  = Eu.min()\n",
    "    moduli.loc[m*nc+i, \"E1wag\"] = modulus(Eu, Su, .7, 1.)\n",
    "    moduli.loc[m*nc+i, \"E2wag\"] = modulus(Eu, Su, 0., .4)\n",
    "    moduli.loc[m*nc+i, \"E3wag\"] = modulus(Er, Sr, 0., .3)\n",
    "    moduli.loc[m*nc+i, \"E4wag\"] = modulus(Er, Sr, .6, 1.)\n",
    "    moduli.loc[m*nc+i, \"Ecwag\"] = Su.max() / (Eu.max() - Eu.min()) \n",
    "\n",
    "moduli = moduli.applymap(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"638.888905813665\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "markers = \"osv<*\"\n",
    "colors = \"rgbmy\"\n",
    "mod = [\"E1wag\", \"E2wag\", \"E3wag\", \"E4wag\", \"Ecwag\"]\n",
    "fig = plt.figure()\n",
    "for i in range(len(mod)):\n",
    "    plt.plot(moduli.epsmax * 100., moduli[mod[i]].values / 1000., markers[i] + \"-\", label = mod[i])\n",
    "plt.grid()\n",
    "plt.title(\"Moduli: Wagoner protocol\")\n",
    "plt.legend(loc = \"best\")\n",
    "plt.xlabel(\"Log. (True) Strain, $LE_{11}$ [%]\")\n",
    "plt.ylabel(\"Moduli, $E$ [GPa]\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Deformed RVE state : 3D plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frame</th>\n",
       "      <th>frame_value</th>\n",
       "      <th>label</th>\n",
       "      <th>part</th>\n",
       "      <th>position</th>\n",
       "      <th>step_label</th>\n",
       "      <th>step_num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>EE</td>\n",
       "      <td>ISAMPLE</td>\n",
       "      <td>element</td>\n",
       "      <td>loading0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>LE</td>\n",
       "      <td>ISAMPLE</td>\n",
       "      <td>element</td>\n",
       "      <td>loading0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PE</td>\n",
       "      <td>ISAMPLE</td>\n",
       "      <td>element</td>\n",
       "      <td>loading0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>S</td>\n",
       "      <td>ISAMPLE</td>\n",
       "      <td>element</td>\n",
       "      <td>loading0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>U</td>\n",
       "      <td>ISAMPLE</td>\n",
       "      <td>node</td>\n",
       "      <td>loading0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  frame frame_value label     part position step_label step_num\n",
       "0     0           0    EE  ISAMPLE  element   loading0        0\n",
       "1     0           0    LE  ISAMPLE  element   loading0        0\n",
       "2     0           0    PE  ISAMPLE  element   loading0        0\n",
       "3     0           0     S  ISAMPLE  element   loading0        0\n",
       "4     0           0     U  ISAMPLE     node   loading0        0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "step_label = \"loading8\"\n",
    "frame = -1\n",
    "field_label = \"LE\"\n",
    "component_label = \"v11\"\n",
    "\n",
    "# FIELDS MANAGEMENT\n",
    "fdata = model.parts[\"sample\"].mesh.fields_metadata()\n",
    "fields = model.parts[\"sample\"].mesh.fields\n",
    "F_id = fdata[(fdata.step_label == step_label) & (fdata.label == field_label)].sort_values(\"frame\").index[frame]\n",
    "F = fields[F_id].data[component_label]\n",
    "fdata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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z6GO75zHZMqBWx2b5eWVkxhS41ORZa5G5eXlXKTv20vAIX5qaetDd17EjzaC3mst4sd7rKWnO5hA+mOunHxvMk5ThaAr/54qVapQp06dLD9olcP0unXr6Nevn0fiJyYmxmFV8pb4yThPJYaUAHKKISWMVF6h9GIoq7pk3toaWYkhJYLSF2oVMeStFck//TjET11t49GdEfGjjaD3Wov48R5r6ekOJaBEiTqSUh/u7kRzqfvPnDnjyL2jSk6o+lzZXer+NWvW0L9/f4/Fz8WLFx0ZovPDpbipMH5nNJkq0KoyTqcXQ1nVOfPW+EUMeYt0/u9HxE/+X6PcHKGIn9ykKc8qUAS0HHOpqCnl1KwcgpXwccUxWImf1atXM2DAAI/EjxIZFy5cyDfiJ+NmUMd6TjGkxqoYqSKtTjGUvkhrXm2kzMSQEmjKYiWWobxaFe/06xA/DbX1pTshlh9tBL3XWsSP91hLT3cQAU9z96gpOiux16xZkxo1arjsT6I+eFetWuWw/KQ/dnEmOVTPzu44RgkK5VDdunXrO4J0dkValSBSYiivj5+cYkjtB+clYuiO2F5uD9IhfjTWBNYdEfHjNvg8aiDiJ4/AS7f5k0D6EhXq3+7496hjnlOnTjlKVCinZhX95O61cuXKTMWP8gVSokb50GR1qeirc+fO3THiJ+M80hdpVUJO5TZSDJ1JF/O6SKsar4ghd3f0nXO/Q/xozBKhOyji505ZcRE/d8pKyThvO4GMuXvcET7Kn0Udcylx0rhxY49DvpXlR0V7KeuCsja8++F7fPXXLxhql8EWlwIxqdQNrsGEoWMYMWLETdFUd7r4ybjAKrw/fY4hZ5FWZ2h9XhdpzU4MOavWq+MyiSa77S/dXOnAIX7aaHuUbq+IH20EvddaxI/3WEtP+ZiA85hL/XZH9KgpqZISJ0+edCQsVBFdWo5qlM+PsvDMfHkWG4/spuL9Han+UE98il4vM2G32og/FEL4sgPEbj6FPsFMi1oNmTTqftq2beuw/LRpo/EdPJ+uU8YirWqt0pfiyOsirSKG8unGcXFYIn5cBFVAbhPxU0AWUqbhGQEtTs3KZ+X48eMOJ16VVTl9JXZPRqME1NjHJhOtN1Jz5gAqDmuFTq/P9lE2s4XYPecIX7yf+N3n0Cel0aVJW6beP5H27dt7Mow7pk3GumRq4BnFUF5PJqtjMrEM5fXK3Nq/Q/x00DYu3U6x/Ggj6L3WIn68x1p6ymcEtOTuUflsDh486IhUUkVJtSTzW7p0KbM+ehNTBX/qvngXJVvV9JiUJcVE9NZThP+1j+SjoRjiUulSqxHPvvw6detqTGLi8ahuf8P0RVqdofXq6NB5RJYfirSKZej27wMtPTjET2ctTwDdNhE/2gh6r7WIH++xlp7yEQFPc/eoD1mVRfns2bMO0RMc7HklRBXq3ah9HVJSzdR6dSzVJvW4UecrN1Cdmf4VlVdvYUo9K4su6jmf7EeR0pXoOXICEx6c5JFDdm6MyxvPyKlIqxJDrqQfuN1jzckypES1O7mlbvd4C/LzHeKnu7YZ6jaJ+NFG0HutRfx4j7X0lA8IaDnmUtFIKlOzOm5R0VzZRV7lNFXlr9KhT3P6vx5M0VK+7JgfxpntMZhsvgT1bEnNGQMIqOB+tJjq15Ji5ETXF7mvaBSvNzOj0/0zmpAEWB4Cyy4biEoLILhuE0ZMnMGwYcNyVXjlNH9v/12tu3JKT1+XTFWoT39Mltd1yXKyDDnzDIkYuj27R8TP7eGaX58q4ie/royMK9cJaMnd46zEXqFCBerXr69ZKIweP4RSPWPpNa32TfNMijZxcHk4uxdeJSbMjE+1YCpO7EP5Ac1d6jPu4EVCh7/J7DZG+gX/k5smM5g2OxyIhL8u6NgW7kOKoSiNOvRm4vQnbltx1FxfVA8fqMSQsy6ZEkT5sUhrdmJICSFnXTIRQx5uggzNHOKnt7Zn6daJ5UcbQe+1FvHjPdbSUx4RSJ+7x90SFaqtypqsykZkVondkym99e5r7IhYwLjZ2RcgtdnsXNwbc90qtCWSNN9AivVqRQ1lFSpX/JauL326HP2H81jU00zlIPdHlpIGm6/Cwgt6TsT7QtHSVG/WlTf/8x/Kli3r/gPvoBZ3QpFWEUO3d0M5xM/NlWXc7lC3SsSP29DyqIGInzwCL916h4CW3D0qtPrw4cOOfDvNmjVDhVJrvZYsXcKb3z7BzKWd0Buyj+TK2FdCpJGDy8LZsyiMWGUVqlWF4El9Kdu7CSfv+g/tLp1iTiczfgato4QL8TB8GYyuC3siDVxLC6BWk7aMf/QZunbtqr2DfP4EteYqis95TJYfi7RmJYZUXqH00WRiGXJtsznEzyDX7s3qLt1yET/aCHqvtYgf77GWnrxMQEvunqioKI4cOeLI21O7dm2Xjpxymt7p06cZ8VBv/rW2C0WK+eZ0e7Z/t1ltnN8Ty/pvQri89DwB2BhVAx5pBFU8sPqk72zdZXh2O/zaH+r+7XZkscGucJh3Vsf+GF98ipenz5iHeHDyQ476XAX9yqxIq0pt4PQZKlGiRK7sEa0cnVZO9dt5iRhyjaqIH9c4FZS7RPwUlJWUedwgoMWpWQkmFcmlEhcqa09Oldhdxa6cbdv1acz0P9tQrkbWJSpcfZ667+jqMFZM38XcMWaqloAVp/QsOGLgSoydcgE6xganMbYu+Pm4/tTPDsGf52HBQCh1Pa9ipldoEiy+AEsuGYi2BlK/TRcmPTbrji2t4Tqh63feCUVa1ThFDLm+sg7xM8z1+zO7U7dYLD/aCHqvtYgf77GWnrxAQEvuHhXFpUpUqG/KSvioaKDcuGJiYqjVvBc2vZVqjQy0GuBPh/uqUrpKoMeP//OFw8QvPcfCcWmUyvAY9aX/+DWYf1jPphM2Uo3QuCRMaQDtK2bd5YyNkJAG3/UCXzeOzsxW2HJVWYX0HIv3JaBsMIPum8b4iQ8SEJCNgvJ49vmvoYoETF+xXu0lZQ1KX7FeS+bv3JpxZmJIpVxQ1ju139XeL6zHZA7xM1Ibad1CET/aCHqvtYgf77GWnm4zAWfuHncLkqphhYeHc+zYMUcVdlWNPbc+qFRofJfBkzG2/BLKtoP4kxhiNmCIWoPBdIUA30RqNNfRcXRpWgyrhF9A9mYai9nK53030i0wgQ8GpZFDAmgHcWMabD0HC/bDsatgsEPPCjCtCZQPBHWkNXgJdA2GF9uoyvHaFupCAvx1HpZf9iHGVgT/qk2YMmUqAwcOJDDQc8GnbVTeba3EkDPZYvoirc6ki/mhSKvTMrRz505HPTrn2hTWYzKH+BmtbZ/o/hDxo42g91qL+PEea+npNhHQesylykpEREQ4cveoD6fcuv78cwnjnngPS5f5ULRq5o9NS4aYfRhi1qCL2YGPLZoSZcw076Gj470VqdmmzI12184k8l2/dbwzwMLIJtmHsWc3h2sJsPI4/HUQQmMhMglG1oQPuuTWzK8/R1mDBu+tTeK9b6G7egb96V34psYTpLfRtkFNRvTuzqBBgwqFz1D6Iq1KDKljs/Q5hpTwyC3B7e4qbtu2jVatWjkc+rM6JlOh9coipP5eUK15DvEz1l16N9+v+1XEjzaC3mst4sd7rKWn20BA+eioDxL14665Pjk52XHMpd70VRh7bia5e+2tD/jvD5uxdfkDfIu5N/OUUIjejiF8BcQfx9eQRPFicQRGh7N2moXa5dx7XFZ3H70K436AF/vDtrOwOwRK+MDEujCqNi5ZlbJ69juH/HgrpgUpLy6DEhnC5FMS4PxBOLEdw6kd+CTFEKSz0rJuTe7q2YkhQ4ZQunTp3JlkPn1KfirSumXLFkcduMwyXqcXQyrirVGjRo78SHkl1G7ncnpT/MyePZsffvjBEVShLKKLFi26aWrffvst7733HleuXKFcuXJ88sknDB8+/HZOv9A9W8RPoVvygjFhLbl7FIGrV69y4sQJR72rqlWr5uqb+fB7p7L6uD/2tp+D3g1v48yW5tICika8RJU+lbEabSTuPMPdwVG8199IoJ/na7n4MLy9Ev6YBFXTGbtOhsNPu2HTWbBbrguhiQ3Bx8WofJsNBm0syeYqQ0id8R34uBjVZky+LohO7sBwcjtcOY1vlJ1RI7rx6KMTHR+6BflyFml1HpWpuXqrSOumTZvo3LlzjvXpwsLC6NKli+OIuMCKn3Hadpnuf65ZfhYuXOj4srZ27VqHwEkvfr7++ms+/PBDfv75Z1q2bElkZCTqi1qtWrW0DU5a30RAxI9siDuOgJbcPcpCpESPyt+ijrlyM0xbHW206Dyc836DodHT2rheW0fg5Sep2LUCbd4ZhH+Z6/HrVlMaF347wPmvN1PJGMvnPSLp6OZ74gdrYPVJmD8JimXjjxwSA7/shVXHwW6F4VXhkaaQlVtSrBFarK5IxNAXMA56zPP5b54PH30K5p+AA+j1i/D1PUPZsj7ce29Hpk59kEqVKnn+/HzeMmORViWIlB+O03la/c4tZ3zV14YNG+jRI+e6cufPn3eUQVEJPwus+JmobXPofnBN/Dh7ee211xwFkp3iR/ktVq5c2WEVGjBggLbBSOtsCYj4kQ1yRxHQkrtHmevVG42KwlGWBC2V2DNC+/DD/+Pll7/Cai8K/r5QvjHUHAGVB7pn/YneR5HzD1OuZSBt3xtCYOWsfZDijl/l2H/WkXrwPBOqR/J6H3OOYe0P/wwqOuube8HHjYgu5Sf0xwH46zCYTNC3EsxsAcX/tj7tDod+u2qS+MRP2Bp08nxPLf8OvvkFzH8BGVMChAGrMRiW4OsbSo0aJZk8uQ/3338fyoG4oF63s0irej0py0/Pnj1zxKec9ydNmuT48lAQL8ex10PaZqb7Vpv4OX78uMP5XB2Lvf/++yjH+cGDBzv+rfJKyZV7BET85B5LedJtJKA+ANS3ImW5cTeaS91/+fJlzpw5Q4MGDRzfrHLrWrDgT6ZN+w9JSd2x26cBKgt0CnAYDFtBdwQMyVC0DNQcBLXuh4BMSkUknCbg1ERK1bXS7sNhFK9T3uUhWlJMnP1xDyE/bKO2LY4v+kTTvMrNzS0WGPw5dK8Dz/fTFtEVkwyLDl8XQ/HJUMxHx2YaYHxzPZTOJpY+pxn9/jH8ug7M84Gc0gyoJH5ngeUYDKsJCIiiadMqTJs2zGGdyE1hm9Owvf13Z5FW5xGZsmIqS5Azkkz9dtV/TX24bt++ne7dcy5nvnv3bmbNmsW+ffu8PWWv9Jdb4if9YF999VWUdSerK6PlZ+vWrY4M6n369OHXX391NLv33nsdEajffPONVzgUlk5E/BSWlb6D55nxmEudlbt6OSuxq1wm6pgrtywE6gNjzJhZREc3wG5/CsguSkxFZp3F4LcNnWEb6GPQ+fuRVr4jVBqAf+iblKiaTLuPhlGqaQbV4upE/74ven8Ix/6zFsvJy8yofY1nethIMkPPj+GZ3nBfGzcfmM3tCUbo9Gk5zph6oDf4YE+7CPpUqFoVU8eB0PUeKO6i4/L3r8Pi42D+GfDET8rqOCLT6ZZiN/yIb3AAHVs25YHBfbnrrrsKbISSWp70RVqVIFL5hpQTv/OYTPkOZSUGleP1nj17HL48OV0bN27kv//9L8pBuiBeDvGjvr9ouHRfarP8KMu08vNRvkC9e1+vsrpu3TrGjh3riEiVK/cIiPjJPZbypNtAQJnllS+Nu9YeNRT1jVhFc6loCVWJXflNaL1UiYphwx7h0qWS2GzPAZ5akaJA9wn+dbZgCPKjSJli1J/Qgpr3tcuVMgnm+BTOfLGJi19vIiAqloc723mpv7YIrvTsftqjZ/ri2qRW+hJrsV7//MmWBqlH8E9ZC8kbwRaJyVcPTVpA56HQegD4ZBA3nz0N62PB/C3gurC9dS3XQYUXoGcfmPwMhJyCveswHN6Cf1IclUsVZ1TXdjwwdqzDyb2gXu4UaVVfCtQHbqdOOR9VLl++nDlz5rB69eoCic4hfh7VNjXdbG3iRzm+q3+MAS8AACAASURBVEjHZcuW0avX9deViB9ta5JVaxE/t4erPFUjAS25e1Rb5ZSpqrGr8/MKFSpoHA2Ob13Dhz/M4cMpWK3PA/U1PVNf5AOKdtpD7T/fxFAsEOOpS0T/vJ7E9Xsx2K3UHFKPBo91xy/IswzJSSFRHBn8Ea0To5hR187yK7AtGmwG6NkEHusJ5T1wIUgxQ+8vynA4qRcplb8Dgwu+NpY4SN4Dpg2Qsh+Ih1LFoUVbOHsSjlUG88eAp9kVz0HpKdC0Msx6D8pkcvSm0l6HnoeDm9HvXoNv5BVK6G30atGIcSPvckQ7uWNR1LT4Xm7sLNLqPCZTvm/KAqosQipnjzoS7tChQ46jWrBgAX/99Rd//vlnjvfeiTc4xM8T2kau+8Q18eNMz/HWW285iif//vvvjv2n0g1MmTKFkJAQ5s2b53AsHzNmDNWrV5djL21Lc0trET+5DFQep52Altw9yoyvcmeoNxd1zKW1EruyOvXs1Zf9+0Kx2/8DdNY4QRuGMlMpeXdxqn8+E10m1qi08Bhi/thM/KIt2BMSqdSxMk2f6UPRKjknYLQYzRy4/zuK7TzBl01TaZXh1CnaBMtDYf4lCDNDzfLwUA/o2yDnaf11BMb+VgtjpY+wl9BQBEkJkaRNcG0qlK4DpiQwAgltwfIg0CTnwTjuSIKgh6BGFDz3EdRp6mK7v29LjIMj29HtXo3PuSMEGJNoUrMqI7p2YML48Zr3jnuD8d7d6Yu0qgK+KozaGVavfmdVpHXu3LkO/yAVgl0QL2+KH+Xr8/rrr9+EUfldqaNFtR6PPvqoQ2QqXy7lw6ZC38XhOXd3nYif3OUpT9NAQGvunujoaMe3KOXQXKdOHc3f5H/+ZS4fffYUox/SE3bJj50bLUSF+xEb1YLkpPuArm4e0yThG3wPFZ4bQIXHXCsiZE1KIX75TmL+t4a0sCjKNChH06e6UqZV9VtIH39zGSn/t4aX65m5t7IlxzIVVhvsjYHfLsLeWND5QP8WMKM7lExXhcJsgUHflWJHVGdSKv0PfP4u9e7pWke8ANYt0O8bKPO36kqNgdBNcHYJxJy9LobiWoJtSiZiyAZ+L0HwWpj+KnQf7OlIbm5nSUP/6UxKnVpEUNmikGijTYNWPDJhGm3bts2dPvLZU5Q1SIWwq7Iu6t/qx1nrK31dMmWV+Oqrr1DZ0FUCvoJ4OcSPxgwVug9cs/wURH532pxE/NxpK1ZAx6vlmEtZis6dO+dIFta0aVPKls0kmsoNbsrkPOGhftRuHMWz/w0iqNg/fihms52Du9JY8isc3GUlNiqQmMgOGFNVdrQW2fRyEf8ak6k2ZybFe7VyYzT/3Gq3WEjcfJjouWswHj9P0fKBNJ7SFr2fgUsPz2VMGROv1DPi76Fr07VUWHwZ/gqFyDSoUxU61IJXN9QgudzbpBXXmPs/5RhEToLGd0Orp0GfzUCVGLq8AU4ugdgLkGqHlLZgKwfBf8DIiXDv9Fv9hzwiC5jNBLw8gFoN0uj9aX8Mfj5YTBZCt1zg3B/HiD0aSQm/YozqOYJJD05yWEoKwqW+MKhjrxYt/tm7KkhA+cupHyWGlB/KL7/8gtFodFgifvrpJ83+czllOM4Ltg7x86y2nnXvivjRRtB7rUX8eI+19JQFAS25e9QbsnJqVt9MtVZiV+N44qkHOXhsMa//X1EaNM05O3FKso3dm9JY/AucOmomNq4s0dd6kGZ6AKj994w3EtDwbeosfQv/Wp46SN8MT4nF5J3HuNp7JkVNJpqW82FuxzQqqkj7XLjSbNB3dxF2laqJ3i8A4tKwGJth9r0firnpOa3SPofNuB72P2gulHQzK6OaT2oMvqtGUbbEaey6AFJNvqRUa0tan7HQ3s3xZORzfDfFPhpLt7e6UXdY1r5ciVfiubjsJBeXnCItykSTGo14+L4pLuXIyYUluS2PUL5s165dc7x2srrU0e/8+fMdodeq+K86Uu7WrZuj/EK9evU8Gld2GY49emAuNHKInxe0PUj3togfbQS911rEj/dYS08ZCGjJ3aMepd64VeI15QyoUr9ryTq7eMki3nh7KvdN1zFmchH0es+cb+NibGxdZ2Hp73DhNMSG6UnwhwYHv8e3TO5ZC6K/X07qo59wr9FIY5uVozo9q3188QvU8X5LoyMJoaeXCo1ve6AsofeOIeCtWQ6u9pRU0nYdQL90FeY9x7BFp2I11sJkvxdK3Q36LGptJO9Fd20ShrYTsTR90uMEQz7bn6VB9TWM+bmnYzzm5DSu7Arj+KKrXNkXQUqCHWPpuqR2HgF9x0KgC47YKqh+zouUPb2AIb+MJCi4uMvIbBYr13Zf4ez8o0TtC6OIzZ+WNZrz8vMv3VGRZEr4KOuPCgzI6XrppZccVtWpU6c6fFNULpoyZf4pvJtT+8z+njHPjSfPyK02jn3+iran6d4Q8aONoPdai/jxHmvpKR0BLbl7lIXm1KlTjhpDWiuxqzf/8ZP6U7bKFV76KIiSpbWEWt+8xD9+nMquz+LoXl3HH2d9iC5fBd2TD1BqbF+P/ZEsCUmEdn6cWqcvMc5sJGMsWCSw1DeAqwY742qn8UoTm8t1udTod0bBwAtV0X/xH3z6ZJ37xZ6WhmX/UXQr1mDevA9bZCKYKpFiHAll7gd9EH4RD4LPRcz9foLinoeW++x6hXoVFnPPvN5ZilKrxUb4kUhOL7/GufVXSIxOxhhUhZTG/bEPnAiVMvhIJSVQ5IXeNOxTmi5vdEdv0Lbup+YdJP7zP6hQXk/oFV+KBlaiR/dxjBs3QfMx7O184wgNDSUhIYGGDRvm2M3TTz/tSBL61FMqr1XuXCJ+coejPMV9AiJ+3GcmLTQS0JK7x5mXRIXoqkrsmVWidnV4kx4ay9GTK3htdiAt2ueUUdjVp16/749vU1j17wRW3GXH72/Xlovx8H8ni7DqioG4KtXwf3ESJQbkHGLs7Dl2zmJMj33IvakWcgrOMgGbfPzYazPTrCx81gGqZqwWkWFKr53y40Pfhvgt+hZDRdczTKvH2G02rMfPwKp1GH9fgTE8AewGbFXug4YToJTzCNA9jobdr1G31ALGLuznljVOieu4kATObbjKyZVXiLucQqqlCMm1umCtVJcS6z+l7+yBVOlazb0BZXH3is7v8ucvyVSuct1iGHLRzvrVNlav0BMR7kvZsrXo33cSY8feR2BgOm/yXOnd84cofx/l0+PK8dX06dMdyRCnTdOYCTDdcPOd+HnDc5aqpe4VsfxoI+i91iJ+vMe60PekxalZwVNVpVXtGxXJVa1aNY+PudRR2fThfWlliCUUCLfrKFXLh573F2H4uCIEBGizAiybl8Ifzyaw6i57lkVAj0XBJycC2RphILFubYq+OZ2g9pkfPVjiEonuPpU6Z68wKsWeY+GH9BtNFYE4CazXgT4AXm8DQzKWvrBB572lON1rAL6fv4UuYxJCN3aucfEaTK9+hO0bFRXmg277Zmyr16IPC4VUG9YizbBWvQeq980x46Lh4LvU9v+O+/8arNkyo6aQEpPKglGLKBoXjiHAnwRrAIEta1H/wbZUau+5CLq64xKmz75j7v8U7Vsvte9Pn4S1q2xsWKMnNsafKlUaM3TIVEaMGJGnpThUPizlw6NeUzldEyZMcIx33DiNpc/zs/h5OycK2f9d94KIH20EvddaxI/3WBfqntIfc6mzdXf8c1ReElVMMSYmxnHMpfKQeHIpi9PTUydwatVCvm1spebfX8BV2pljSbAsDtbF6ojVQ3AzXwZOCqTvcH+3jqg2LEtlzox4Vg+3UzRnf2lU33uuwYdH/DkQ709y25aU/PdUAupfP6aJ/XIBpidnc785jbqqSoaGKxpYAVwxwJg68FozuJACXU8EY33nBXzGDNXwdDC9/C6mHUexfvszuuK3+s/YExKw79uDz8bV2A4ewR6fBH6VSSs1BBqMhYB/fKIMhz6iht/XjFs0EIOPNjGqJmVMMPLHgHmM6ZHEGzONjjQAiUmweaeOP1YV4dgZHQmWAIq2qkX9SW2p2Nb1Y7qVPT7gl6/iqV3HNT8xq9XOkUN2Vi+3s32rgaSEAGrVasvoUdMdfjTeTLaowtzVa1HVjsrpUsn2Jk+ezKhRo3K61eW/5zvLz7suDz3TG3XPivjRRtB7rUX8eI91oe1JiRcVPqvEh3pjd0f4qGy0KppLJfhSTpmeFqzcvWsXT94zhMllE5lWNXu/W4vKfxMPS+Jhe4KOZF8d1dr4MvqxorTrmvXx2K6NRj6eGMfqoXaKe3CKpvLurL8Ms48YOGfxIyLFQHB0ElPNkIU7sUd7ygxsRcd6Hzv2in5Y6zXE2KY9+qaN8G3ZGH1D93IkqXU1Dn8QW5VapL35AToXa6/ZrVbsJ45j2LYB++bNEBEN1gAsqUUpbdjPxDV3U6KyB2moM1C5uPUyW6Yv4au3zfTooGqAZX4pMbRpByxYbuDERR8SlWWodV3qTmxPhTaZ11yLPBpG1Mtf8fv8zK0+riyQSp+wf4+dFUth4zqITgmiVYuODOk9kuHDh9/WumRnz551FEFVQQM5XUOHDuXZZ59l4MCBOd2a49+zy3CcY+PbdIPD4VnEz22im/8eK+In/61JgRmRlmMu1Vbl7VG1tFRdLpW40B3R5ISoPpin3TuSiF2r+baxjcoeVItItcLWGJgX7s+RFDAH6mk2wMB9jwdQr/F1887BXSbeGBnLurvslM6FcPMfj8FXxSpRpKieywcTMcSZaXDFSDcLaJcDMD8ogKSugbz4VWliwi2EXkzjwrE0Qs6YiQqzYjLqSDbpsajMh6VLYaxYg8TaTfBp2gCf1k3xqXY9ZN8WFUPygAfQPTQNy5jxmveu7c2X4fAB/Ns1x37mLGnhsegsZvSmVAKL6ilT2ZcqjYoS3Ko8VTtUomjZ7P1n1r+8FfOmg/z5lYlybqZ/SkiETTvhz9W+HDurJ8mmxFA96k5sR4XW18XQ6n6fMOe9KBo10W6dSkiw0aOnH9PndyUhwsSJ9ZGc3RFLSoyNUkHl6NyqL/eOHut4PeTWpQIHlA+SK7XOVKHN999/3xHmrvXKLsOx1md72t4hfj7wtPX1drqn88by06qVa7nDlK+kytItF4j4kV1wWwg4c/coq4+71h5lJVL5RJKSkhzJ1zytxL5p40aeGz+SmRVTGFfZ4yjrW/jEpcHaKD1/ROg5Z7ZiLuZHZISJA/dDRdcirHNk3m5dABOWdKdMletKKiY0lcMrrnHgr6vEXkyheGwaLULNqCLt7tRAVydnX5QNpN49JZj1aYkcnYjT0uxEhVm4dimNsAtmLp8xc+mchZgoG5FXrVw6WwyqVsL+rxno7hqJXoO/kO7159GFh2L4+stb/I6UQ7U9IhL7pcvYzl/EduoM9jNn0MXFoTOlojcbCQzSUybYhyr1A6jQtAz7/7uFAc0T+PA1G7lQ05b4hOtiaOFqX06c1ROb6kdCdCqLl0KDRtrEj3q99Ojuw7B321G/a7mb9of6IhB9KYVTW6M5tiaS6Ism7CYfGtRqxrB+oxkyZIjHjv/qOFkdIwcHB+e4Jzt27MgPP/xAmzZq1xW8yyF+PtE2L90TeSN+VBmfL7/8MtvBq330xBNPEB8fr22SBaS1iJ8CspD5ZRrpS1R4UoldvTBVlWmVT0SF1XpaiX3W05NZvfxnKlpgVgUY6F7wkss4N0bBhP0+NLPZOO5ro30tHZ/0sFNOQ0BPnBF6nijNs+sy/4Zts9m5fCSBA3+FcnxdJMZwExWvmegcb72RVjGzCaiKER8FF2XMy2UZM03DAIHFPyby7vQipKb+V0kzAgI2YtcfgkATtGuIddJE6N7dZf8V3RNT0QcFoH//PY8sfA5xFB7hEEeWNesJnDeHEhWK4m9K5eHh0TwxJfeSQSu2c3438MJP1agxczCRK/ZjPHuVYvZ4RvZNZNIUqFDRPTE0YTyU6dKAntPrurT3zKlWLuyLdaz/uZ1xpMbZKV2sHN1a9+eeMWNdcmBWHSnnf/Vaq1gxk2KwGUaivogsWbKERo0auTTGO+0mh/iZrW3UukfzRvy0b9+eXbt25Th4VcB327ZtOd5XGG4Q8VMYVtlLc8yYu8cdx+b0ldjVm6srb8aZTUv5Eowc2oZ29U7xxgw7J87Dt7/Bjv1QyQz/qgSdcq4P6hKxBWHwzBE/nrCYUVHkyqpyVA8b/HUEFof/drfT3XW/2Rt9Pr5dj/6JlnS4x7XGZqOVk1ui2Df/CpcOxKOLMVM75PoRmXOq4cA3NYry/HcVaNfTA4ekdETeeSSWP7+phsWiQmMyniMqj6JjBASsw244Q1oRO7oB7dE9NAl901uzCKt110+8B5/mDdG98KJL3LO7yfLV15RcMId7fhtE8SrFSY5I5uB3Jzi76ATFbMk8Mz6GcaNzDDTLdhyTXy7KmugGtJ47A0ORf7yxUq/GEr36IBGLd2MJi6JqmRTuHpjEfeN1BAZmLYY+/sDOlrOVmPi15/XDFMfIiymc3hrFyk/OcyWuJFWqVGPmyBGMHzcuS185VQuvUqVKlCt3s7UpIwD1fPVlZOfOnY5Iy4J4OcRP9saTHKetm5Y34ifHgckNtxAQ8SObIlcIaClRodLnq0rs6reK5vI0D4oKhb97aAtenBzPyD43T0tFVe0/Dl//AgePQx0rPF8Zmrie1PemB34eouOTU748ZjHf8vGvblRiY3URPdd87DzQxM6LHVz/wG20tijP7+qFr4dFuuIjTBxZdY19C64SfT4Ze7iJaJuN/1tdlQYtPXdIUms8vWcsR3d3JtX4pItFXVNAtx/fwI1guIKujA/WIT3QPfQQBFfGMGoQPncNRjf1YU37UI2NcQ9Qu1wcQ2f3wuBMrpTuqfGX4tn3xVFCVp+hYpFUXp0ey5B+rndrNkOHcaUx9+hO/ZdHZmuhUmIh6XQY0cv2ELn6EMTF0ahGMg+MNjJ4mO6GRWzjBhsvvVOcf63qnitRbd8+eZIdpypi+/wHiIvF9udCDOvWUtpmY3L/fjw2bdpNr68DBw44xExOmZrVfJRfkKqhp7V2nuvEvXtnQRQ/ypJ+5swZh0N7TgLXu7TzvjcRP3m/Bnf0CLQ4NauJq/B157fPunXrunxMkhGa8u95/qlh/PiWmSY5nByoz8mt++HbX+HoGWjlCy8GcyP0PacFee2sDwvO63nEYianaHZ11LRJp2Ovnw/NKlr4YoCd4Gz8gnZdhRf8KzPle8+tAM7xR4Yk896EM0RXaYG1YXPsm3dgiA6ndJEUendN5K4JgdSo75oVKCXJxj2NY4m69gAms2sV6TPnGIvesBudz1+UKncOfTE/knsOwzp8JPpOHTxaf9vlUHzuu5tuM5vRclzOmYrVuKJORrHn08OEbb9InbIp/PvJBDq3y3rlL4VCx0nlqPH6A1Qa2jqnLXLL31U5jLj9F4levIPY7afxTU2gWa0E9u838PzW3hQr49o6ZNWxMcnCy4OOENttNNYnn79FmNmjorAtWYx+2RKKJScxulMnZj32GJcuXaJ27do5FmpVr3MletSHqfIvKYiXQ/xoLFiveyj/WH4WLVrE448/TpUqVRwC6PXXX+eRRx4piEvn0ZxE/HiETRopAlpy96i26lukyjCrMjVr+Vby6SfvsHLhW/z+vhV3y2dZLLBmJ8xZCJcvgcq3/GJlKJ9FVNj0437sDdUxJc2EO14dzmSDG3zAJwhe7wkDM6nv2XeDH32+60z15p7lMlLrYjHb+L9pxzlyrjj2/76PvmnTmzasLfQq1s07sK9ci/7SRQKtCbRtkcJdY/W07anqmt08s5AzJia2SyUp8TmsVvc/+G9+tVgoXvY1ajY+yKxvqxFYzMDxnUns25DE2aMmEpIMGMtUIbbdAAyj7kZfM/sQbMvCvwj6+A1G/W8A5Rq6Gc719x6+tv8auz85RMyhUFrUiOedp400SaehVmyA8W8H0/K3mRRvkLNjsCvvDpd+2sb+FzbhU6UhfjHHqdM4jRHPV6NWG/fPZM/uiea/D13B8uaH0KV7jt3bExOxrV6FfuF8fK9do0+TJrzxr6cd9fGyupRVtnz58g7rrKd+eDkOLI9vcIif77UNQvdg3okfVaMtvQWvV69eqAKyJUuW5OrVq7Rs2dJREkiu6wRE/MhO8IiAltw9qhK7svaoS1WTVuGXnlzqqGPKg0MoYtnA5y/a8c3JDJNDJ0YTLN0MPyyCa1egtwFerAHF/37u6P0+RET78ECaEdfS2WXeYRSwzgeu+MDoZvBKZxz1t1R+oebbi/Pyzl6e4HC0WfXlReZ/lQQzZ2IfNcYl52F7QiLW3XuxLV8PRw/jlxxD3eomht1lpFhxA6+MM5CSohybtVak30DV+h8w7sXS9HugTKZjU87cV84YObItib3rkrh03kqSPYjkGo0x9xqE4a4h6IOum86sM58kOOogo+YOwC9IeyYku81OyKZL7P/mAIlnI+nWMJHSJa38fqIubec9gV+pHOqDuLhq+x78jrCjAZjG/gYBxUCZIs9vp8je2XD1MLUaWRj9YmXqtM+5aOii9y+wZJEB29c/oXPBaTnjEO0mE/aNG2D+7/iFXKRD7dq8OmOG44My/RUXF+fIs6UsP56knHARTZ7e5hA//9M2BN24vBM/6kvkrFmzGD/+esqJQYMG8eKLL9KuXTvWrFnjsAKpvE5yifiRPeABAa3HXJGRkY4IE+U/oMztnr6RKgHVrlVNpo+KZWbuZdu/QSQxGeat9OWnxXoSIiEpykwNo54x9qyT5LmLU9Xf2q2HXQaoXQGaVYarYxox8Kl67j6K83tj+fjREIyd+mB74WV0GupH2S0WrJu2YnvsMYqWLYLOZMeWFEjClebYLP2BnEsh3DyBGMpVfZLm3eKZObsaxUq6E5wPJqONMweS2bPJzKFtKcTGQPhVKBnsz/hVo3JF+GQEnpaaxtwuP1DEz4bZ5oOhejCVH+xN+f7NPDqaU883RsSzpc9nmBpPxNRlVua5F5QQurgL/72fYwg7SM36Zu5+thL1Ot9s1bJYbLw98giXKnTC+taH6LQqf2UFU0knd+/C/r+5sH0bHz07i4l/f5Aqy4HK76MKAXv6mnV7U3u5wZ0ufpQwVUkolUVdhb2bTCZHRm6VJFa9186ePZvu3XO2DHoZe551J5afPEN/53WsLC3qG6AqJqoyLbvzJqjaqoSF6s1TWXtKly7tMQD1rL7d69Gm1hX2nwLlgjBrEvR2vUaoy32fugAjnvGlW08bhw9BbLgv1a+Y6We24aGv9C19JwEf+wdxuURlipQqgg8qoZ+VspV1VKkL1ZsFOY5DKjcMuuWDNynOzLtjTxBqr4bu44/QV3MtQiwrADazGeujT+N/+hDN3r2bsj2v1xtLvRJN3LaTRK84QOKpCMwxFsyxlUmO7Ar0BDIPnfcrMpvqDZfz1OeVadQ+N9Izwnv/imVp+GgoVwXdtoX4myJp0D2I7s+0dER4ab1iL8by56j5DJ9Vh05jglHWKBVWvu33MM7uisOs96dkv7bUfKQvfiVdswZdXbKf/TNXYh79A/ZqLvpzKS/9i7vx2/sFPlf3Ub2umZGzKlK2WiCvjjiF+bEXsN01Rut0b7R3rP0rL2HftxddnTq8WK+uw5KgLvWBetddd3HhwgW3Xve5NjgvPMghfn7V1pFubN5ZfpwjV6HsKp+PqsOmxJCnWfG1kcj/rUX85P81yvMRps/ds2HDBjp16uTWUZWqxK6+fSjR1LRpU48TsjlBjB7eieGt9zN52PX/c+ICzJ4Pe05Ay0bw+gyo6L77xy2c35mj549NPvz4Uxq1al8/6EpIsLNkqQ+//WIg7KKdCtes9Euy4EkaofPALyXKE1GqJqauz2JrOPx6SJj60EuNg7gQiL2IX+wRbOEn8Uu9gsGWgt6Wgq/ehM5qJDosGZ8xw/B54jH0tWp4vFeUoLT++z18V/xFvX8Npur97bL9kLOa0kg4FEL8ukNEbjqJ6VoKlgQ/kkKbYjEr65CFyjVfoP+Dgdz/fCV8fLQcFP4zrZATKUy8rwS29zb/Ez6Xmgx7VqLb9DM+0Rep2tiPnk83IrhNJbd5HP3lKPs+3MZjv7SmUr3MxVrcNSP7loSzZ9E14qIt+DWoQbVHBlCmXeYWsT0PzSV0N1gn/A5FPPTlUnvi0j58lj5NkbRTEFgEa+OWmDr1RTdwMPqS/9RFc3fSau1tb76ObfMmDA9PQ3/3aGw/fMf7vgaH5UBdKhpzypQpjuSjBfVyiJ8/tM1ONzrvxY+agUr58e6776Kcnj/99FNUgkq5biYg4kd2RLYEMubu2bJlC23btnU5HF1ZelQlduVMqcIt3bEWZTawJ2aMpbx9EW9MvbWWknJeXrYDvl4EqmbmfUNg2hjXQ8yd/SWlwIAZ/jRsqeO9D034+mb+wW0y2Vm7Vs/c7+HSWRtFr9rpnQDZSRCVC2ijTs/K0lUxVWlNSq83oYL7SeP8fr0f+4kU0sx34x9wGJ3+BOgjwdcIfhb0lUthaV4XXYdWGLp2Rl89a4tQ2v9+xfB/s6l+X0fqPt0Hva97x1JObsawWOJ2nOL8R8uwRMQQWMROux4BjHikLNXq5U6E0JBm8STOWgbBtTPft1YLHNmKbuW36EOOU7YSdHuiJvWG18vxuGrJgyvQRUcy49fWBBR1jYElzcapLVFsmxdGyOEErEWCKDuqC9Un9cCWYmZ9ny9IrX0Pth7PaU8xfmgB5Y88S++l09H7Gog5dIWo7WeJ2HmR1OgU0kyQVrU2qW17oxs8FH2l7MWfQ/R88B62lcsxjJuA/oHxNzJrWz94nzn1ajNy5PXIPpXf5/nnn2fv3r0F9h3TIX4WapuebmTeiZ+tW7c6orlUsVr1JfPbb791fNGcMWOG49hLiaHimRQc1jbjO7e1iJ87d+1u+8gzy92jXmAqF48qNJrdpRyicneKLQAAIABJREFUT548iYpA0FKJPX0f77/7Cuf3vse3L9gdVbmzuyJjYc4SWLQZShWDNx6DtjcHPWXafM12eOIjP955z06fvq7796hK3Tu22/nxKzh2GAKioGMMNPm7lxRgnn8gh0pWwdp0NMZOT0Og+5E9yjnW/5u+6MIaYjQ+q2IWMplHmqrdDlzE3/8QOoMSRlEYrWbwB33lkuja1oLgsvgtW0KFrnVp/O/h+BbXlvVZDUT5tRwa8Cr3bFRhLxCy7jxn/zxKwvkYigdZ6TYwgCEPlSMwyDVxkX5y7z4awXLzVLj3edf2vrKWXDgKK39Cf3wzQQGpdJhYgdZTW+AT8E//xjgjv/b+jU6jKjL0uRqaBHrE+SR2/RnOpu8uYky1kxrUBFOvf0M9bb4Whl1fUuHKx/T8axq+QZkHCFiMacQdCSVq53mubDhHSowJc4oNS6VqmFt0RD9kGPra10Wj5fPZ2Bb8gf7uMRgmP4TO/+ZQe9trL/PXgP507aqONUFZfFVdr82qAG0Bve508VOvXj0++ugj+vTpw+rVq/nkk09Yu3atY7V+/PFHPvzwQ4cFXq7rBET8yE64hUB2Ts2qKJ7KwKzCJ7O6VE0uVaJC1eRSEQi5ceb8269zmT9nGoveda9Ok/r8O3AKPvsVjl+ELm3g1UeheIZcO8rPdPJrflxK0PH9XDNlynh+TKP4Kf+g/31rZ/sWCI/xI8pYEgZ9gLX5WNAbPNt1ZiP+sztC/D2YTA949gxUBmYljBZSsdFP+JfwxWTzo/z4XtSY2ltTbS4llvd2nEW/LwdToeWtIeFxF2K5sOwUF1acxhydRLWaOgbdX5wOg1SNsewTB1w4lsLU8UGY393mvinPSSryCqydh37XYvytsTQdVJIaXcuz9fmNTP66GfU7e+6Hln4xfnz6GCEnjYz+picRJ2I5vCiE0IOxpKT4kVC6J5a2j0CVW7NdZ7WgPhvfolLq7/SYPwWDv3shjbY0K/EnrxG+6xJhm8+TcD6apEvRWMdNwTD90Swd421PzWTbI9No2PB6zP+yZcv4/vvvWbVqlYf7Lv83c4ifxdrGqRuWd5afChUqOI4nVUqC0NBQh4/Wnj17bkxI5VTT4mupjUz+ay3iJ/+tSZ6PSJ0Xq+KimZWnUPVj6tSpk2lGWPWhr150qlK0+haikmtpPeZSMLZs3szrsway+mMrRTyLincwVaHsC9fD14vBrNMzY7SNsYPgchgMfcqfe8fpeHymKVfGrPr76gsbs+cEMez1JkQcT+DQyiji4/yILj0QY4fnoUxN19c6KQK/T7tjS3kOi6W36+0yvfMCFerfw1Pbe1O0tD9xV5PZMec8R5Zdwqzzp+JD/aj2YI8cBUnGRx+fMptaTQJp/kTnHMenkv5d2xfGuT+PEbbrMnqziWbtfBg5rSzV6t98RKZE1ciWMcQ+swaCs85Fk2On6W9IjIVZ/cFuxF9voX1PPaNfrk6pYM+P55LjzLwzYAd1h9ajzwutbtlHqfEmzm28ypFFF4k4lUiKuRjxFQZh6/AIlMk8n1HAiieo6L+Fbr9NRu/joWhON+9VQ74k/lQEll0ns8Vle2gSpz9470Y25/nz5zvqeqm8MQX1coif5dpmpxuUd+Ln448/5t///rfjvVc5pn/22Wfcfffd2iZUgFuL+CnAi+vp1Jw5fDITLurMP7NU6UowKWfIxMREl47FXB2bykz64D2tWPlRGmU89BXNrK/QCJi92Id5a+1EmQKY8WAys54DPz93UhdmPovwazZGjfGnXItK3PtJC/wC/vnQUpl4j64MY+fPoYSdTyPJtx7Rjf4FDYdmbdEIP47hixHYTB9jt7twdpct3HhKV+/H4+s7U7bWrZFRsZeT2PbNOY6tuoLF15/gaYOofF+XHIXQ1QU7SPxpBUMX3ueReDQlGLm0/gJnFx4l/mw0xYKsdO0fwJAp5fjilRhWWaaRNlId8+XCdWIXfDgdRj8MY6eqWHrYtBz9X9/jF3OBtt3sjHqpBmWquH4MeGRdOHOfOcXwT7pRq6triRCTIlI4vfYKRxaFEB2SipGyxFW6GzpNgaCyBC26n+q1LtDm8wfQ5WAZc4XKud/2cmXFSRKuJJL4x5bsxc/YMUT9Pu/GuqtjE+X389NPP7nS1R15j0P8aDRs6ZSeVubmPLpUEsOQkBBUtvxSpTw4Vs+jcedFtyJ+8oJ6Pu/T6euT2TBVLSBVCDF94VGVX0KdJSuTqjKT51YG2KioKFp3aUCr6kbee9hC41z60u+c133vF2W3T30azRrA5b9OErH+BMQn0LxuEg9PjKdXb6VH3BNDH7xvZ+4fQUz4ug212mV/jOIo5nogjh0/XebszniiE4KIq3I/1vYzIfDvtmfWoZ/7OLa073IhyaCFEsG9mPxHU2p1yr6QpWIUfTGRbd+d5cSqUKwBRak8YwiVRrW/hYnxWhyHB7/GmI2T8C+mrUyDc23iL8ZyeuEJtr2xB7O5FIbGjbD0Gg0971UK1bNXkDrbfHcyxIfCv7+HCpkkbVRCaOsyfJb/gF/UBVq0tzH6+eqUq551SPv/njnG+aOp3PdTX4qW8dxyFBuSwMkVlzi55CLRJyPQYaPGE4OpPbEjfhr9scxJRpZ3+5jBm2ayauT3JMzLXvzY7xlF9MIFNzirvDEqVcU333zjGfs7oJVD/KzTNlBd77wVP9pGX7hai/gpXOvt0myzEz8qM7NKoV65cmXHNxz1LUNFFyjRo0RRbl0qPL5t7yaM+bI5pgQzu787TeSpOJpVMvLc6DRaNfC8pxQjtHu2FIF3d6fRv/rdZKlQPhKRuy9y8dcjxO47j68pmR6tY5kxNZUmzbIWQpcv2xhzjz/Vu1Zh1H+b4eOBBSk+wsjhJVfZvTCMqKt2olOCMZ4Lx2ZVyUe0K7+gckMZ9Wl52tzrfi6giDPxbPv+HKfWhWEPKkblJ4YSPKwtaq/s6fAMA74ZRvnmFT1flHQt1TO3vrKVPZ+GYS/+FNaACWA+io91MZg2gSEee63qWPveA13uBh8XnKePbkP3f9Ox3zsDRk51LfLKbIIdq/BZNge/8HM0a2Nn9HNVqVD7usNYSoKZ/wzZQ62+NenzYmv0es/9xNKD2/yf3fifP8H4p0uzc3US29ekEhUJlC1NUL8O1J7QwW0xtHLA5zT9V28q96nP8v5fEvdr9o7LulEjiPxr0Y1hKWfZ2NhY1NFKQb3uZPEzYMAAVq5cmePSDB482OG/JZc4PMseyIRAduJHHW2pSC9l+VGZmlWm5RYtWrgc+u4KcHWE1q5XM/q/XYuGvf8RVDarjXPbItk95xTXjsXQsKyRWaPS6OjGSZDKCdT7nXI0+/A+KvXOWUGlJRoJW3+GkHn7SD5zhZKBJoZ2iWXqFCuVKl0XQ6//W8/CFUV56Pu2VG2i/Wwu7HQiHz94HGPj1vjWCCZp10n00XHYEozYU/yxxFbHFKNqbHUDsgj5zgC6SInJ9P5XEgNecq3wZ3brdO1EHFu/P8eZTddIjDJRpl5pBs8dSdFyriX8y+7Z+z7by7Y3z2HxG09awFOgy8TKY7eAaT8+1kVg2g6+iVC3NpZ+D0DHITcfH9ps6D+aCEkR2F75Hsp5KNDTzLBrDT5L5+AXdoZqlZOJOBnN6Dl9qN1da9mPf4icXhPCwbfX8NWaKjflRnJ80Tid5pEYOjN3F2Gbz9Ht2/scHa0Y+BWxP2/K9qWoHzGUiKVLb9zz1ltvOSy6b7/9tisv4TvyHof4yR5LjvPSdc8by09gYCDz5s3L8chNlb5QiWrlEvEjeyATAuqNVhUwzOxS4evKJ0iVqVACSDnXuXs0lBP0bgPb0XJ6SVqPzrqopcq6e3F3FFu+OEXU8WjqlDTy9AgzPbOpu/m/1TqeWVqFrr8/TFD1nOsmZTbOlGvxXF19gqtLD5JyLhzl5Fq2HMxa1klzZW5VkPSLhw5z6moxis1+A78Gt1p7rFGxmE+cx37oKGm7j5J2KQJbvBFbEtiTgkm51gJQDseqNtN1ceZX9E1ajdnGA9/lXgrsQ3+FsOD10wQ/0A2drw9Rm45jvhaLLs1MhUalqHdXA+oMruuyk+6J34+zbuZh0hiKuciroHdDSNnTwLgHH9tCMO3C7pOCtW59aNoW/aYfsY+biX3QBNesPTltTsAw7/9o/uGTtPODYzodCb4GrKUDKN6pIrWH1KD+4Br4pQuld+GRjltiQhKYP2I+36+rSPFS2Ts3pxdD21anEhUFurKlKdqvA3XSWYbMCSms6PoRg7b/C9+i148kVw76kqi5G7N93RqGDSZ8xT/ev6pGlIoieumll1ydzh13n0P8bNU2bF2XvBE/NWq4lqLB39/fkYJELhE/sgfcED/qDVeFTiofH5W7R70Z5vY1fOwASvdOoeeM+i4/Wo3r0v4Yds856RBEwUWMPHu3mYHpkppO+jSQDal16PLTZHwCPfQZSTei4/+3iaP/O0LJd57Gcvw0KUs2YgiPpFwZK51GlqTb+OoEuJHLZs2XF5j/eSwlX56G/6hBbjsN25JSSDt1AeuRk1j3HMZ06jL2hFRSQxPQmZOZPLcVDftX1ixUVWTYV+N2o6tWhSYfjMOv9M05A9LiU4jbe56IVYeI23ceS1wyRYoZqNoxmIZjm1Ch2c1HYyEbLrD8wV0YjZ0xB74LBs9E6U2bxZoK8YOhTBJ6gw3Kl8f2wNPQXmuUHBT5z+N0WfgF8wwWAtKdckXa4bANNvr7sd9qJ86gw1QygGKtylF1cHWajKhNYOmsQxXNRgtzOv3Mx7+WpkZ99/enUwztWJ3ExmVGImN8sZcvT9TFZDrMHkNwj7o3EK0e+hUR/7fsRoHYzF5ovkMGErbqn2OUp556ypHi4sknn3T5dXmn3egQPzu1jVrXIW/Ej7ZRF87W4vNTONc921lnZvlRx1sqh4TyxSlbtqyjwnNuX1Mfn0h0uWMMf0tZLzy7HOH2R+LY+sMFQnaEU94vlbBrdkre14PmrwxxW1RkHIUlxczqu78jrXZ9Sn3wHDr/fz6oHNmwT57HtHgDxtXbIDqa8hXtdB9dis73V83UGnDpcByfTT2NrXMXAt98Cn2g5w6z6cdqPneZ6JGzsNbqj6nhCNj5O4ZLuwj0S6LtUH96PVGXksGuW1fUUei8p/Zzck8KTT6ZQKk2rh23KSapl6OJ2XaKiBUHSb0QDiYTxSoEEHEgGZOpNWlBn4NPLh0dmc+hM98NwyZiH/TEdSQXD2NY9wX2s/ugSlVsE5+HJi7W10oHtcTjwxi+by2f21Jxxb0n0Q5HbbDFz5dd6Ijy0ZNUxIfAhqWpNKAqTUbVoXT16xF3c3rN49Fn/Ok2MHfWX3H/8Pl4Vv2ewMDzH920jdc/8DNXZ/0/e+cBHVXVReFvanohoYQSeu+9914FKdKrgDQBFRVUVMSGiNgoKipV6QrSew8ltNAJEBJCKult+vzrTghpM5OZBH8Rc9ZyqZl337v3vDtv9jtl7+VIy5iv/RJK79JunYg+efLJuEmTJpmETV955ZX8fTH/BaMKwc+/4CY9xSkWgp+n6Mzn5VQ5wU+GErvg7RGEhWlpaaa3wKdp73/yDqcjdjD8B+uaUvZc89bRCL7tdQttWh0UrkG4+EqoMbMBVcY0yxeZ38NDtzg5aween76BU/d05ltrZjQY0Fy7g3b3YVL2nsIxOZbSpaFFf28a9CnJ8glXCU70xnXpfBQV7S9CNndtAVIS3/iCpH230QxfDT45ImhJjyBgDxL/TciT7lOyvJFOk4rSYGB5i1GhS3/eZ+v8QHwndKH8xI4FbrvWxKewt/HnGHoMQ3bpFJKYWFB5o03qBa6jQZ4/nSpJ6gKkblvRz1gDpavmdo9oQb59FtnBpRhDrmGsUBXjy+9C5TyAvE5H0WGNmRJ2i9kGVV633ernaiPcMMBpuYzjUhmhUghSKlAWkzLvW3eadrQdkFq70J4tatZ+E0+SWkH7M/OzHXrslU2EDJ+PtHYG/3jmx8bAQLSTXsE5JY2I85lhEFErIjhjRozIL7lmgdz2fxlsAj8FVO+QNC6M/PxfbtZTuEgh+HkKTnweT6FWq02dPIJnJywszKTELrq8Hjx4YEp7Cebmp2XLfvqetUe+Y8LGNk+tY+bncZfx3+CAPvUdIOPHNAKZ436kirM4FtNR9ZVa1JjeFrmj9TSD8MPx8VuIDEml+PqFyIrmjz/DqNejuXyL5C9+xPvoIaRyKZqmjVGPHYFTz7YFTkmpLlwn4qUPMTQYgbHb23kzIYvW79AAOLsZ6Z2jOBFH3U5KOr9eiRJVPIgLTWb54FPIqlag9lcjURbJQYudjw0gfHmg2WekvfYdxsbt088gQMm9W8hO7UZ6ch9ERqNPcsOQ1hVcXwZ5HulVQyJyTW9oUh/diEUgt4EFWa+HG8eQHvwBwgMxVq+HccL7UDqHMltyIj4DavFJchRDjebr4PLhBtOQcAN0LOlN6Te74FW3FEEbzhN3IRhnQxI9+8DgKZ64uttPbHhiXxrfzk1gzbHiDGybSMcz87JN8dTr27jX8VWkLVs/+btJvPjXX9Cv+Q2mfEqtLd/gtyVT4nzQoEEmYdPnmTTPBH4u5fdupo+T1C8EPwXz4P9vdCH4+f/5+l91JQFwhESFiPQI4CME8oQJICQiQaLmp6AmfgjHvTaLDfv2UbaqnBYvuNN8RAWc3e2veciYS0xIMp+1ukjyox4YVIMsaF+Jo2ORORxBojiO0iOFCsMqUfedLjh4Zie2SwqOYc8La3AY1g/Pt0YUOG2mXrCUCiuXs2W0AXGpc8Gw7bqEk8EyInQuJLdogXzKSByb2e5fg15P3Oj3SLuaiHrEGvDKZxQpLQmuH0Ry5nccw07gbojEfVwvanw0KF+RMnP741ivb0hoPwF933GWt48AQ6FBSE/tRXp8N4RFgMoJXWJ7cH4ZFGUzx6b8gczhAwwTv8FYq0P+tqROCwH7kB78CWJDMdRtBhPmmtJzvsMa8rMmgdYS23XebJnEFgO8UbkULdeOxrtu9pRfSlg8YX9d5uH2i+geJVCzup6hk1yo1yLvlNiV02l8MDmOdad80KQZGfWihvZHxQtApp2bu4db1Ycg7dEzHXvGx6GbOhWjiw+89yP47WfYha0s/+rLJ4N69+7NO++8Q7du3WxZ3r/yGBP4uVKwqUvqFIKfgnnw/ze6EPz8/3z9r7mS6OY6ePAgZcuWJWcXgWAQFRIWDRs2LNB6du/Zw/D35pE6eAIMmWh685ef3Ins5F5kcRGU8DHQrKcrzUdWtBkMHVpyh81vx6BLmQ3YIR1BMnAUifw4Cpd4yg7wpcG8jgRtvcKVlVcovu4TlDVsq3Gx5BQB9NS9x9I75QJLBhgxp1SQqoFjd2DrNQlXouTEObgT37EryimjUFYyD2hSDpwmfvIiDB1momk24al0NDlvnEZX4wo+malm3Q45B/ylxEvckHVoTrkZvXH0yV9a6uL0tYTqa6Of8bn9eyf8AdIzB5Ae2QkPQzEmyzAkpCGtXAr9jHXgUnCKAdOkNCo4/xds+4ZS8efw1RvpGaelrxyq2sd3aXGNYxycON2sAu02jEPpZl2vRfBORZ68Q+iGM8QHhOLhqKJbHykDJ3ri5Jx9QvduqHljUASrTpTG3VPOg7saZkxX0mZn9iLlSwsOccWjM7KXhqA/dRL9nDkw6VNokw6G+O1bvi5pZNy4TIDaoUMHk2hmhtCp/Tfw2R/xXwE/s2fP5vPP8/EdfPZvoV0zLAQ/drnrv3NwSkqKWUFSwbosdGOaNLG/YFR4T4zvPHIst92LYZj7DRQx090j3vzv3kR2fCeSI7twTo6geAk9jXt70nxUbjAkOmUWtPMn7Go19KmviubuAtwoUdOxixIuS3F3NJJWrgqpA7rhNqYf8lL5627TxcYjbdePWbUeMSXvUqEnc49NgYO3YdMVKYGxClK9ixLbuy8urwxB6uZM7IA3UcU4ox76K7jlzdhsi1PcVg2hf9E/+fVzoXGWOSI+EbYflfH7XjnBUQp0VStTfFJvirW3rfD97tIDXN+TiH7hhoIDNIMB19H1qNzUhUfXHpGc6kx86znQdqgtS8z7GI0G39nF2bswAb0BTl6Vc8hfzoNQI6mJ4KWW0CJGRV+gjh1ZqVgDtC1eHK+p7ag7q22+oojJIbE83HaBsJ0BGOISqVtHz7Cpbnh4yZjZN5Tvd/lSvFQ66eP18yreX+hFq/XZi5SvLTnBheR6GEPDMPhfgkXbwDVT6kT6yRSOTR9uivhmWPPmzVm9ejWNGlnhksjbs8/0ESbwc6NgU5TUeHYiP+Z02ER6c/78+aao/n/dCsHPf30HWFi/4Pkxp1EjWF6FcKl4GNprs+d/wpIde9G++yU0yqw3yPM8j2tCOLwD6elDyOMiKFbcQJs+DhSt5MaPg+6g0UwCbZbe9jxPau4ADW7Kj6nudY4VPVTUKQZ342H/fTk7ghSEpElIdncjpVM7lCP749gk77qntFOXcB85nlUDVDS1TFtk02xD42DPLfj9koTTqT5oZQ44eBZF71gMtVM5DEWqQakaULoOFLFNXyrrhT2Xt2d0rVMsfkeI2lqekiiXORsAv+50wP+6lGRnLxxf7Ei5CR2RO+eOZETuC+DsB8fR/3Qw/9IUGdPRaHAdWZc2r9em5sj0rsDEkHgCfjhH0L77JLrWQjVwEfjmn8zRZ34tlg2/Tj8zWTRRJhUYAn7XZBz0V3DvvpGURPBUS2gSo6KPARpJc5db7dfDy+VL02LVMIoXdCM89oVerSXiaCBnZm7EkKJm1T5vKmRpkz99IIXFW8rTfFn2IuVbv5zG7529MHgaiILvHCab1ovobWufvPyI54AgMhXMwBkq7zZt2H/ZQSbwE1iwSUuqPDvgR8gNzZw5M9dzfM2aNdy5c6dgC30ORheCn+fgJv4dSxCq7iJVk9NELZBgdm7VKm/l7oyxZ86e5YVXXyehcz+Y+JZtcgTWFmXq2rkGYwfDIxmIeRq7A72eEPvZ6xO5dAMVPFYzt6WGEbV0Fn/8H6XC8TDY/kDJ9TgZsRJHkmrWxjjiRVxe6IBUkVlsq/p6BeV+/J6tI3WUyK0hau8UTceLpVb8sRjaVUuR16+JISYefVgU+vBoJMHBGIMeoL0fhj42EdRaVEl6JMJfSheMjt5oHcpi9KoMJWtAmbrgWcpUcFzix8ZM73iFd8br7J5XSBhsPChn22E50WmO0LQeZaa/gFu1UiQHhnNk4Cp0Kw6DR/4KxZ9MKDkR73H16PBpK8r1zM3ObaI5OB7M+e/OEnMvlcSqA9C/+AE42i5Q6v7rKF4tvZ6PJ2ht9oNwb9BDOHNdyv5zSgLvGUl+pMFF50jDODUhcgf8m1akw8bROBSxfS55TSD+ViR+Y36lZLvKRB+6yl9ns2vJ7dmYzLordWk4X8So0k1QNexo+RXxtfrB2+alKhwmdiR6/7YnY4RfBZmp4Pjy9c1nPVlei3kGPjeBn3sFm4ik4rMDflq3bs2WLVsoUaJEtkUNHjzYxAb9X7dC8PNf3wEW1m8J/CQnJ3PhwgUT50deJjiBuo8eh3+aHsOHS6BkmbyG2Pb5sf0w/W1ImwG6l4BoJA4/g3EHSIpgVI8CbA2zXKGC13v0q5jCJ231ONnQKJR1kiod+EfAXw8dORGsJ16mRFWuHAkJabQ0BJsKmxV2pEbyckDP9e5cHj0Dxfh0qQJbTLTcG2ITnoAkQ3Ao+vuh6IPD0UXHkXb9IW5KLYe+CqdR3sEsq5dMTYP9fhJW/iEhMMKBezHOpLUfCiOmQ/lMoj1b5p3tmJgovCc2ouvSrpRqk3c9lzZFw/W1l7m6+gopWneSOs6FlgOsXlZ29Fd6BExi+0KN1ciXLXM3BSsfQJtZHhgrlEOdqEamkFGhT1WqT2qN0tV6rY+1a4iXkpMTfyfhZgStfx6BcykPTvf4nM0nsoOfNUtSOC5pTY0p6V11AsTs7/cLYWfKwrgOMGSa2cu4jGlF+NFMgkMxTtBciHS36Ph8Xs0EfkIKtjpJ2WcH/AiZINGwUmjmPVAIfgp3hlkPWAI/guPnzJkztG//uE3Ziv+K1mtIst4IXfrBqGlQPJ+6ShnXUKlgzDAIkIFavLXmfBAbgdNIHb/DaLyPUSNIN0THl7kaoHhKF3mDRj73WdLeQJmnFZkxwshdoDOCVC4hPBnSdODtLqFBKQN9amNKf9kpFm/ywFcn5Hzm3A2XnzO7cAqyfcWPaFS7sei6TEJfvSXKFW9RIvYSq2aG0MH+rGa2qQh1lAojfHCYOwN9XCLJRy6gCYlCn6pDX7wsmrqdoftA8LEBED8Mpuj0lvRc3ZdiDexP5yUExXH+az+Cjzwg2as+msGLoVTl7K4Lvkq9FU3w+1GFU/5xyZNzhkZC01k+lP9oCL790tNzqaGxPPgjgLC/LqKNS8WrdglqT21JscZZutfyuKEPdl/j7Oxd1JjSlhoT0zmx4m9GcO+15azcnR38LH4/heAGvSj3opA6Af/393JzfSl0xkowsgj0G5v7aqnJFHu1O3cP7X7ymQA/AvQkJSXh6PgUnFOQTfs3jn3ewM/f6Krn4tSF4Oe5uI1PfxGWwI+oBTp+/DidOuUtFVCsVXuSftwBR3fDnq0Q+RBK+sKLo6BjL/sQwPaN8N7noJoL+h42LDgRJKuB9SiVMjTqkaI8VSSOcHdaSGWvA3zdQUebp0QsnDGh3XfhuwAJO/sZn0QPDKJ+Ow78o+FwMNyJg0StBCcXGTVL6OlezUi3mmBNdeNcCHQ9WQv3Q78heUw7YIMTLB5iAj5tx6LrOgl9tyw/guHBKH+ZQ5EQP5ZPuk+/zvZfRaTmqgzzRjJvNm69std2GbU60q7dI83vigkQaSPi0Kv06EpWQtuwO3QbkL0I/vZVir/bld6bB1OkSsGiDiICFno0iMvfnSb6nor4msMw9J8LOh2+V1pvAAAgAElEQVQV3i3B0aWp+D4FYfqDZ2HwtyVpvGEaHjXNbzBRrxN9LJD76/1Juv4QubOCyv1rUPXlFmZ5pzSJaRwYuAalhyOtl/XHsWgm51LYwVtIf1/PpyuypxXfnxSHfvzLFG1cjvvbr3L6jUuoip2AqI9hcnXoMjD3zQ28SqNf53L4d/HdSTfxnRc6foL762nr+Nm/u/6+ESbwE1aw80tMWWTxEvbsWmG3V/q9KQQ/z+4e/UdnJkKmouU9p2W0wXft2jXP+ZVo0ZaETX6Z3T3iV/HqBdizBS76pRewNGsPo6ZC0ex56ScnT0yA4YPhrg+ovwDyE6K5ioPjIvQ6f1wlQXStYmBVd3C0M8WV14KjUqDLZjg6GDxteEGOTIFLkXA0Wo5/iA6VEYTHKxSFVhWgb10o5QmJaeC7ojRuh39DXjJ/HWdZ524CPm3Gous2GX23MeaXFROBcuVc3G4e4suRQYx50fYHetPJxYgYMAbvSf3zcpnpc4NKTVrAHVJPXCblxGXUobHIjUbUbiVxCb3IwINjcfd9Sq3sGT/oSWpu/36Rq79eJjk8mfaVE3lvnIGGNezD5DkX+PFaR77zr0CLLVNxyKF7Zs0ZyUHRPNh6mYidF9ElpFK0kS+1p7fGq3YpAhYf4c6a8zT94gXKdM6dOrz58xkax+xi3FvZweHr/cIp9tNc1HGp7O21llTvayBVQsS78GZbaGWGs+fIdibc3s+izzLV22NjY6lTp46J3FQAhOfVTOAnqmCrkxR/dsBPYbeX9XtZCH4Kttef29GWwI94q9m7d6+J7CyvB2GZNh14tPIAOFogZ4t9lB4V2rEeeXwkxlJl0fcfD+26p/8CrVoGC34E7RdgsKNH3OxdeUgJRS06azVEOkGYBLRS8HCBFqVhSE1oXjL/P3wCxzX6TcZPnfU0LkD0IEUDV6LhbDSceogpbXYxwgNV1QoU+Wo6Tp0K1tGWDnzGoOs2xTLwyeq/hFgkv8zDOWAf8wbc4Y3R1guiX3jLnXO1+uMzv2AaUIn7zvBo9re41y2H+to9KnT0pdkHHVA+BVHajOXdP3iXY7P2UvP9vgg+nbjDV0m6FY4kOYVSLio6VEtmSGcjtW0oVRL3v8+HRbhetB6Nl49Aqsh/rYUuTUPUoZsELjtGvH8g5QY0ouVXfZA5mEfrZ+fsZkKri7TrnZ2Be2qXh/hu+oj9rb7mkcNxcHxcB/dwJnw0CBqYaVpY+QXLq3kwbFhmTZng9RJp7vDw8Dy/8//mB6J4nhliCrYCqfezA34Ku70KwU/BdvN/dLQl8CPcsX//fgTpWV7FdJU7dyd08UbwKpq3F8WvxxV/pLs3QMBZDDfCIUkKRlF7UNDclApvZXmGaBLJyYaTBIQCd1ASIwWDzEhpTwm9qmkYVgsq2MjnN3yfgsbFjbxW3/5uKUvO0Rmg0o9FCEmYAJQExVEkstvIihhweqk57q+NRF7O9hqYJ8Cn+1T0XUfnfU+yHpGShGT9YhyPb2BG13t8MlWVq25p2ldurDd0xXf5LPvOnePopGMXiZ21iKq7PkdR1AN9mpr49Qd59OtunJV6ms1ti2+7vIuerU3i8NRtxASn0HjVJBy8s4MGkR5LuhvNI7+7RB27TdrdSBMgKuuWSq9acQzuAlWy1NMnp0L96cVxHdWdaq92LNDaMwYHLjvMvRUnULg70ea7F0wRIEt2aMgafvgyihJlsoOjV9o/JEzqS0j4F1CkT+bwe6NhyZtQJXd1u/T9sfh/MJ3KlTNrokRbtJC1uHv3biH4yePuPkvgp7DbqxD8PJWH0X/tJCK9JQCQORPsz+KL5eDgYNUtdXv14/YHy6C0rZ1XmaeT1GuOMXUMSLaDNAaMFUEnalPy7jLLOakiDjXprb9PJRtwiWjujxVC4EgIkkCyQoLUUU71EjCgkoaB1cAjR0pr1TXYfl/B5p7W+XHs2UMaHZT/wYtwQdpoyMmJlAjSCyA/ilQeiaKSB85Te+M6ui9SCwWpBQI+WSeuVsHWZTjs/ZmxrYL5blYyoqHky7UOfHK1FeU2zi+Q8GnSkQtEzVpMzb2fo/DOneJMvRlCzJe/k3LpDuXblabFvI4oXa3vw6zTTwpN4K+Bv+M7uBmVZva0+cfcoDeQdDuC6NNBRB2+iSooEmliImVcU7kWJKHhqimU7FJwsV9dqorjLyzFpUJxGn33Epdnb6fqixUp2c6MUOvjhe3psoyd+0SHWvaU1NDGIdyLm4aqxMJsW8/x7kuoVn8JJXMXWsun9ODRzvXZansuX75sUnO/du2aPVv4X3es8J82oWDTVng8O5Gfwm6vQvBTsN38Hx1tDfwcOXKEpk2b4uxsnbOk1cAhnJ/2MVSx/0dBWq8zhuQdj70vUMs5UG4G42VAAVpRcyQiItbFNp0kL9BBeZCmQk47nyauHgHcUygINerROMpxdIBmpfW0K63nm8tSTg0x4PyUaohE+3z55d5Epr0GhmZ5zFqsKxTkfkik55A4JePYpgqus4bg1K6paewT4NPzVfSdReH3UzChh7VzFco/v6Oh932uGMpT6fD3SJX5d0LSIX+i5nxPzd2foPCyXttlUGuI33iE6BU7cZRpaDK7FRW6Ws9PXV15notL/Wm84mU869reYWXJW6lhcWxvvwJD55eQnN6P0pBE+V6VqP5GF7vqfTLOH7Y7gIA3N1Lvy2GU7J7+nQl4fwelG3hS/sX0jjFztqvtt+w5lvmJSE1/9Wo02zdJiK8koHx2cwzsg+rPteCWo47KYEA2tDFxZ49mG+Dn58e7775r4vl5nk2AH1VKwVbo6PLPgZ+ePXuya9eugi3gPzS6sObnP3Sz7VmqNfAjur0aNGiAq6t14NFj5BgOD3sN6tophfEoCmnHyRhS1lmY8kOQ7wLJTiAOtCJEPwXITr3vIJ1HdRbyohmyRnt8Ye7YNEC8B1+o4IBPRSfS4vW4GQ00V6QwqBK0LJ2/+iEBfHyXF+OR6g3Q50dKQJDz3QD5ESTyO0g8wSBNglFzoJ/w0dMz6R/L8P1zHo184lHpZYTEy0ly8UbTqTWe4/viUMH2dGXSwXNEzP6eOvs+Q17Eza5Jpt15SMyi9SSfu0nZlj60mN8JR4/MOjODTseOQb8j8fSk/tKxyJ0KIn+SPjVtipo/my9B+8E6qPpYhDYhFo5sQ7J7HbKECHyaFKf27C64V7eemhTg9PSoX9ElqWj26+hswOnGlwfw9DJSdZzlWq+dzRex93Q66DQYjHw0OpLD1zqhCglFVfVsLl863O6C+sDe7BvUaMTp7ZcocmYPNwVrZRY7dOgQixYt4tixLAjLrjv07zhYgJ9kVcEE3FwdDf9Yt5e7uzuJiYlPnC1eUM+ezbz/e/bsoXt3QQZbaMIDheCncB+Y9YA18HPq1Clq1aqFh4f1Dpzhk6awpcsIaJ43J1C2SRzfi3TKPgypn9hwdzTAcZQOAijdQiJxRq0SxIdFqSgfxXCdnqfIMfhkPsFCCrWOKwu2l6dk+fS0y6MwDVf9UrhwMJF7ASrSYsELI+2KpDC4KtS30NCWcVIhbOq7oiSxKSLik87NUjC7AW5LodpgiDoBhjjo2APGzAZn68DV4nVVKhx/eIMy/usY0FTD2y+kkRWrhMXA/gAZf/hJCEpwItHBE1Xblni83BenmubrdERxc+QHK6iz+yPknvmcl/jh12hJ+OM4D5dsx0WmosmsFriW9mDf2D+o8W5vSg8sIHnRY6cIMPVH0+9Qv/odNLKwtzVqOHMQdqxBFnIDz3KO1JrZGp+ugm4h0+ICQjgzeiWVX+1MpbEtcqWu7vxwHHlKLHVeN08tIdJxe5p9wR5/Z3Q6I7MHRnD60TiSyryE8si3aCquNwN+OqE+dDDz7wL4zBvHmIubuJGsZ/u97C1PO3bsMOl67d6dyf1TsH35bI5+3sBPkSJFEHJEGZYTHD2bd+H/N6tC8PP/8/W/6kribVRw/ZgzQXJYpUoVRDeBNZs5602W1+sCHXvbt/afv0KyUIlRO96+caajg1AqN+Ok/QhXmZ6yOhDvzPlpkLd08esSCGjsxsKdFShSzHKaR6Qfwu9ruHoyjbN7UwgLVKFO0OIj19DZS8vgalDlsQuTTcCnFPEpb4AhU1AyHw5IH+K4ErzDod1acH5MLqlJgAeb4f56MCZC514wYpZt8g9RoXh+NQ7fCD+m91Qzur0WWxqaohPg0BUpW845ERgpJV7mhqpFU9zGvYBLoxok7PYj+qNfqF1A4JPTT6qgcO4M/QhdfCqOHkqKtapMmUFN8W5WsUBcNeJ7saPdMpIHvgsdbGvlF/IhXD8PO9YivX4GJxcD1UbVJOlOFLEnA2n+2yu4lDPfFBCy4Syq60E0miekW3JbSlg854f/wLrdDszsHcEFw9uo6r+H8tLXaIJkUFII/WY3h1sdUB8+/OSPTgtn0P/4r6wtmUTHOw5suxedbcDGjRtN6RQhlfA8mwA/CbqCRQU95OY1Ef8ffssJbsTzWdAUZJibm5uJqLLQ0j1QCH4Kd4JZD1gDP/7+/pQrV45ixawriX/88cd8XLQG9LFTbXvOZNgoHvb5YNh7vJryjl4MVam4LYWbChBf+aIGaKI19U3l2844yYho4cYX28ubSArtNZGWeHBbzRW/VC4cTiYqSEVKpIoHDxxQqV8HY0Fb+uPBYwFUfQHqvgsSC2F8VSw82ATBG0Ghhi4vwEvTIWfB9OWT+CybQGVZCB+9lEb72oYCST/EJ8ORq1I2+zvhd0PPfVUxPDvVovSkbni0sk0h3hafB09djDQuhtorZ6KNSybe7xbxBy6YCAX1qWpcSnvg1aE25YY0xbGo7Wm2Pb1/JrbxKOhfgFb+oJswtRcOblL6XH0HqcxyqiVs5yViDgTQcrF5oBXtH0zkJ2tJi0rhuusX6Gqlz8tx91BUDh+Cc7Vc7nK81RbV4fQUltOS9+i0Zwl/lYo3/X+nQCV/Bj3KNmblypWm9IkQxHyeTYCfWKMFWg4bF+4lSfvH0l4C3ERFReHklL6GnOCnMPKT/SYWgh8bN/V/7TBr4OfixYuULFnSxPpqzb7//ntmqVxh6ES73Ccd2hfD2Q8A+wulMy5UydGDkarMyJUgDxSpqgtyOY9kUlyAJmoNoofG1iz/ARcZkh5FmP9bWeSKgpO9CR8vnBTFztVOGNSdQeGXPhtTxMtyd49lZx4F753Q+gcoZkedleoRBK+HkK3goIXu/cHJgbLbPqRJ8Vg+HaGnqg0qFPbc5MCHUGthHbSf/QX3b8DJv5Dcv4pMk4B3Ex+Kj+qMW9s6dkdphE9vdn2bYk3LUuWTEWa7uQw6PUnXHpB47AqxR66iiRLkfUbc6/hSun8Tineobva6R8b8Trh7W4zj59qz1OzHPgyCmQNg/BwcNiygr3/uyEzWAVFHbhC66hjtfh1u9pr3/wjgzPiVpLRci7GKkHJJN8eNbVGVNV+j43i7DapDx3Fc+QVNNi3gWJnM6ECXQAVbg7KT3Sxbtox79+6xfPny/K/7XzBSgJ9oY/7TrmKJxSTJ/xj4EdIjosNLvJjWrl3bREkionWNGzc2vagWgp9C8PMv+Br+81O0Bn4CAgJMWj+lS1svaF27di3j78TCBPt4X6QdW2MI3gzYSLKTy10Gqjp4Mkxtvrdd9EdFAhcdHQg1GpEYjNTRak3l0pao6f4s7ozvCy68+YMvUmnBgc/1cynM6hVPUkwbjAZRhJgBwR6CcicYE0A7hPSkXV5mAJfFUNITWv0EigI8wFMjcTvZFJ+icUh1RvpUS+bNflA8v7fCzNRF9Kf0nCqkfrYHSlfMfkRaClw5idPpzRjvBiDTJ+NatzRFh3fAo1MDq2BIl5hCYNfXKTu5O2VGd8jLadk+18QmE3/mNgkHL5B4OYSUGBWOvt6UbF2B8kObceW7E9x9WAbe+t6u82Y7+OgOWDYPFvwGZSsjH9mI/gEzrJ4v5uw97ny1j87rR+Q6Tmh6Hej/Mwke46HFR9k+d1zbGFVlf7PndrzdCuPkEdT69X3O+2aP8nQNVLAlB/gRxc6ikParr77K/9r/xpGCeVqlUpkiHQqFgrCwMFOtiwABeTVlZJ2WAD/hxoIxiZeUJPxj4EcAH0FHIISnM/4RNAVCj1E8qwVJpaVShr/x9jyzpy6M/Dyzt+afnZioVxGaPubs6tWrpreIsmWttwtv2LCB0Vv3wZer7Gp9kjZriuGRaLfNL8h4QH3HmvRT5ZbnMLceQe0RIJEQqFCilUAFrZaWBoOpiV7w/qwv7ULLSUUZ/54NZI153DadzsBbvcO5eNwbbeo4EZy2MCIOlHvAeB+0QoZA1E2Zi1HdB8/voOEsqFjwNnanK+Po3ekokz8pQXKCjlPb4zi6OY74hyrqFtcwq5uWxvkJSj1epaCO8plVgZg3foPaNhQgq1Lh2mkcT2+CwEvIdMm41vTBe1g7PLs3eQKGUm+HEjT4fWovmYBnyxoF/vIIosPkW2FEH77BjQ+2Y3AuDq4uUL4yNO8MnV4EVzsqyZbMg6tnYOH6J+NkY1ow4MIkq3NNuPaQq+/8Qfdt2WVIRMTn3Pu70bl7k1rvCDhm+dFWJ+K4oSOqqubBj+x6E6q4BnOtdHQuosrugXI2BWVvj58/f74JVHzyiS0NCAV2vc0nEC9oQmtMRKTEf0+ZMoX79+/z9ttvm2qUZs6cidCxcnERcd687d8Ofsyt0BQJvXmT8+fPIyL2zyqAzfvuPP0jCsHP0/fpc3FGa+Dnxo0bJnXnChWss+yKQsmJX36MRuqKcehkjH1HgSJvHhhp41YY4rJ0o9jt0WO0dupJ5zQBXewzlWgUl8m4IpeTIrS2PIw0ecGTt5eXRi63NUFm/prHt8fz4RAV6jQhzNrSRnCXCorDYLwEhsZgEADncVGm4D3yuppe1OxW3r6FmjlacetTWpZfxvuryuRKF+m0Bq6cSGL/ulhCrqRQVK7hldZqhrS1C9dS7V1fbg9YDB0G5G++gmRRFA2f2Yzx5nmk2kSU3g4Yw8NpvONdnCsUXPssY2IxJ29xduwGdF1mQ7PhoE6FkEtw9xjcOQWpcZhaCStVgzY9oU1vyCk6K2gWZvSHMhXhzS+zOUs6vj0Dz5pRVs/iGaH5df6VdfTel178L76X5z88wP2jIVTct4ibrV4nrc3F7L6MOIvDoS9QVxTR0yymT8YxZCq61COkVQ/B3HbuEShnYw7w884775hS3ILr51myDBK/Pn360K5dO2bNmsWkSZNMUSAhz/Hpp5+aAFC/fv1M4CgvUVYBfkKNBRPPLSOJ+cciP3ndm8jISEqUyKPlNK+TPEefF4Kf5+hmPs2lWAM/t2/fRiaTUalSJauXFLUCSx3uUPLlrtyZs5bIA7cx9B2Jcchky3pfIr5RvwOGpIK01a6hi3wSrXT5JzYUCxNJs3W1XWjay4ubp+NJTdLjXdqBhm2c6Trci6KlbOsMSU3WMblVNPeulsVoEOkL295EsztXB/LToD8IkorgnASV2kGjz0Cafx2pjGtI7q+nrnQmX+6sgExuPeIm9kbIzTQObYzj4r44pCkaBtRTM/MFcLfCe9ltkQ/7qr0Ow998elt156/IfvgBhWtZpPprlBxUmarzByJ3sUFZ1sIsxA/l+TG/EnnViHHMKvC0UtuWEg/3z8PdoxDkD6oEEAXMNepD847w46cwYgb0yZ22kkzqyqBT5mt5Mqamikrk1KAf6Xt0EjqVlsPDf0NVvAy+y97AqNVxtf5MNN2ygx/J5aUY76ZBqTeerFAeuxVp1FxcF41B8svvPNLlAEyPj+wVKGN9UGZ7tPjza6+9ZhI2nTHDeoru6d1U286UAX4E8Jk8eTJDhgyhZcuWTJ06leHDh5skeF5++WVGjBhhM/gJNhYMPJeTRD2T4EetVptIac2JVdvm7efvqELw8/zd06e2IvGFMWdC40d8iapWtZ7/mPfRR2yra6D44Ham04gflfufbSJs00UM7XpjGDcrN8usSLXV6w2a7QVYx+f04yMsc+LafuqNTd358Uw6c3BGp9bFYymcO5BEbIQWgxGq1HWgwwBPGrR3zfV2ufm7WL6fpUOnEfU7+S/gzpxxDHguhzL1IC0ONKmg9ALXWlCyC/i0A7ltoOzJOSNPUymyD98eqpivDrb4aC3H/4jj6IZHpERraF5Wz9svaKjhmznrmevc+TZlKMY3n17RrGz9YmSbd6CpsgNkTqBPQxG3DmP4ClxLpFFlQU98ejW0/WYDCQHB+L24Am2rKdDpVfLV2pYQCRe2w9b3YPArMC17Pc6TCc3oR/+dPZA7WwZq2mQVRzt/TdetI9jffxWuEwZS9OX0tve0q/e4NWIj+o5/ZVuj495RqOSzwKUuaKOQBY3BqaYa933fmORPUnuOIyj6OO5mMHOv21J+uxebbR8LaQshbDpxon2NC3Y5Ph8Hi2eQeAkToCwlJcUU1bhy5QofffQR9evXp169eoiOUxEZsjXyc89YkF5QqCgJf2bBj+gCE34otHQPFIKfwp1g0QOWwI/Iq4siuho1rNdWTHltOv59y+LVLTdT8cMfdhG0/Bg6Uffx6jwo+viN6/ol5AMWodP8lO87I2MyQ1lFpjRjvk/FhgbO/HTB8joT43RcP53CmQMp3LmcSnKsFq8SztRrq+DPZRAdWgujUXTh2AlIzE75PnhvgpFbodjjFmbxMIsPhohLEHoGIq+AKgn0enAuD0Wagm9v8LAQpUsKpvT1xnyzvxxeJQo+R43KwIWDCexZ+YiI26mULSKhhlca30f1wPi50GkrWOowwy2KZXOQHLmOptJmkJpJpabdxSl8AaSdonhnH6ouHoJjcevFrDdeXc2DgzGox/8ORe3Xo3tyy6KD4Ou+0O5l0NyB974zvwHnT6HLnBIUaWg5ZSlqj/bUnotEpqDUqvdxaZj5wvFo5V6Cf5JDs/eznd9hYzvUZQ6jjP4eSeJyXNfPwalTZuF82sR32H5qEy3NdPj3C5Ty040IU1o7w0aOHMmgQYNM0ZRn0UJDQ011PqIdf968eaaUlxBjFfU+H3zwgSlqJaKVObXPcq5FfP5vBj+nT582Ab6MVves6yuM/OTeuYXg51n8Nj8jcxIFz+KhkdMePHiA6LAQ7ZTWbMDLIwmb1gKP5pbBQ+SW49z7fBfaCrUxvDofzhzF4b27qNVz8u0FJ0kPRhiPFlgLXkxgQwMXfrpQ3ea56PVGgq6lMX9kGHcDREGsABTibVJ0H+XobLL5rOLAS1DiKIzZBe42vJ2KiFDUNQg9DeHnIDEM1MkgdwPnGuDTCYo1p/iFeizcVhLfqgXjNzG3lPAgFa/1e4jKowQ6lQEtrmhbD4feE3LzCdnhC+Vn45Fc1aAuv9Iyj1HG+Qw6ZLHbUUR9h4PrI8rNaYPv2HbZIhvJdyPw770Ubb1hqLq/WzCAFn4Llg6CaX+ICh3Y+jr8YCGK+eOnNG/zgLKDzRd+i+/ezYUHeLB0N+Uurssl+xH08mJiVbOhRONs3lOsbYhU54RjjzK4rJmfKxqZ+vlyvvhxES+bKf8YclfKZ2fuULRoZnH/wIEDTbU0L774oh136e89NCYmBk9PT1PkR0QzxI+78JcAbQLEPHz40FT7Izq+RLG2LSbGBRoLxulQRRL6j0V+hNC08IWIyDds2NAkQST+Lf4RnxWmvbLvgkLwY8u34j96jCXwI1pJo6OjTW8Z1qz9kL7oP+2PS428RSRjD1/m3ux1pD6Mxxg2CqNxZj5rY8Bd2YSxmmsUeQr37ffazvx8xf7uoZUfh7FirujQEuKit4FTjxvsxRu1SMgJMkMbIy2yI1D6HozeAY52dBjlXL8AsgIERVyGO3+B3y4Uzo407q5j4nw3ytWwLlRrqzuT43V88HIEQTEelP1q2pNohfpBFDG/HyLmrzNoEvVoa3fFOORN8LbOF5X1ug6zX4SIcqhLL7Y/JaWOwDHya0jchVcjN6p9O5iw1Se4v/Ee6pd/A58CtLGJST64CitGwqt/pkeOdBpY0B42iXtvxravorZsBzXn5GZAVz9K4szQn+iqus/xMAVed7flOsGNtrNIbXgyG1hTBG5Cd+Rtip1ZirKm+dhn2pY9jJ8+nc/L5n6xGXlPytsHL5tAQ4YJwcy5c+fStasQE/5nLSOCI6JQn332manj9PXXXze1tgu5HfEjLyIfgvBPpMVELZD4b1tMgJ8bxgJE/IAakmCbwI/gQBPkkSJN16NHD/7880/TFAVJoaixOnr0qIleQNRVimjWCy+8kOcSRBu7OF9Gm7vo7hK0JAIECj+FhIQU1vxk8WIh+MlzS/13D7AEfiIiIkxcGuKNwpo17N0Rj5WTcShte4v4nTm/YNh2HE2CK6okN1SqKuj0fcHQCrCtGLGIY1VeUYWS/5LXzFWtq+7Erzfsr9U5uCGWD4bWA2PfHC4S0gFCof4moAa9L+g7AhbEL5VboYIUhm20v5bH0s25cxDWz4K0H0WrEkiOI3VejVJ5i3rt0pgw35WKte0vytZoDHw5Ixz/S46UmvcyHl0tEy3qEpKJ33WamN8Pk/YgDk3Jeuhfmg1VLVRqGQw4TOsE2k6oS7xXsC+lAIHRG/GIn4ijpwLknqR41iW5Qneo3wuK2C7I+mQi9/zh1/Hw2g7wyhI9+LQtbLQgCHr6AOXOL6TZD8OyrSds1zVuvvEbG5s+pH05qLSuKF53038cs9rV+tNQd8wsXJZeW4ni5BIkijSKxuU+PmOs2u8ibYaMZUup7BLmGgM0uworT12iYsXMKKWo9/nmm29o3bp1wfz+FEcvWbLEVMgsAI9IeYnUl/jxT01NNf3Yi2eX4LUROoR5MdFnTEuAn6tG600ceS2htuSuTeBn69atpojcgQMHTHPPAD+CTFJ8Joq3S5Uqxc6dO03/fe7cOWrWtP85JCJBojtXtLpfunSpsNW9EPzktYULPxcesAR+RAw+/OkAACAASURBVNRH1P00aWKdRbh65xaU2T0XuavtKRVVaDSG199l/MZ0wcgHAXEc/ymYgD0Gkh85oteWQq/pBlpRRC0e0Lk7k7wdyjBNHZtvlqCsd39tFUdWXKtpN6Nz4OVUxjUshtFgrZVZDZKboPQHYyRolWAUIE9Ei2Tg+DPUrgN9vy9YKibrgo4tgqN/gWqlGY4hwYt0AqnLahTKG9RqnsbEj12o2tA6aaJ4wP78cRS7t0Ox1wbjPbQzEjtqewxaHUnHAohZu4+kKyFoXMqg6z4F2vRNX7dOh2RUK3Aei9HHOi+OLd9cRcQCSjosZtCv7ShVvyhp8WrCr8YSdjqcYL8oosI0pKmUaBxLkFKkEYbq3aBmZ1BagNO3T8LvM2HGX7k7wz5rBxsEZ5UZux2A15oZdH7M4aPX6Lj46gY8/C5xolc0zkrQGaDK+mJ4B4o0WqbpHsVzvf0naLs+jipd/gGJ32qMacdx8qyPd9xWi67Q3Q/Ft9MgzhbPJDgUeHBwIJxJhoCo+GypsmbNmiEIS/N62bHF90/7GFtqeWy95v8T/GTM6cMPPzSBkgzwY26uwu/Tpk1j3DjBC1ZoT8sDhZGfp+XJ5/A84k3KXHeAEMsLDAxEPBStWYW2jah6emGehYY5zxHWbjSzjgpiv9wWH5bKqVX3ObtFTUyQFJ26GAZDO4xpInoiBEHllHAsyWTRcvwU7PfKTnx9ripunva1k6tUBrq6GjHobW0PFimIMFBcBN0VcEgBd28YtApKPY2+NWDlULgr2tYES3FedRACCPkhU/6M0vkGNZqnMf4jV6o3yZ5C+GtFFCuX6fAc3p3i0/ojVeZ1Xus3RfyYpV4NImrdERKPX0WjU6ILjITSn0CxAhbcamIpGtGGOj2ldP+yFXKlZW02MY+4kGTCLsVw90wsoRdjSE0woEqToXarSFqJNlC3JyTHwNZ304GPe26tO9myfugXrgR3MxTZjyJwef9Fep2YRNLtCM4OXsJbpSJ5q3EmuaggKa++2QfvW9k5exIPnefOmwEY260A/0Vw8Qgki9SYFCfPulbBj1GlRlGrM0HFI57cjNfvg4MOTusd2B6cKWwq/CDS23v27KFatdw6YU/hK5avU2R0eonBIrIhmi/E3zK6ukQt0KNHj7LVLuV1IQF+LhsLlvqsJ7ltU+THVvAj0mAiBXn8+HGTTEWhPT0PFIKfp+fL5+5MlsCPKHYWNOqCU8OalevQmBqnFtrtl3vNxvD2sU4oHPIWDlWn6vDfeJ+Tv8QSflOCNs0Tl9TzdEZLcUM6f3LeZ7E8xY0VHfn4aBWKl7GxPifLqdor09Bp88lp47EYur8HN/dAzC0wGsC3CTSdACWsF5rnWo0ofv6+CyT0A11+BDlFe+xZFC6/IFdcoVrjNFr00LNlAyjbN6PUe6ORuT2deqGscw9dtNGUFvMa0JaEo9fQhCWh01RGrxgN3n3siobJIn+gpPR9+v/QinItbSgYt7AldGo9kTfieHAxloBtITzwCyP1g2BwNc/ULds2G32ndtBaEFvmMJ0Oxdgm1H6lAZHf7eZY5wgq5ThNigbq/FkKrxsbsw1+OG8dEadbQtwduHodUjI/d/Koh3e8dQV2ffVOhBUJMZ3z23Dwi4ffy0LLMBf2BoU/uZYAP1WqVDGlTcqUKVgxsN0PAhsHdO/e3VT3k7UmScg6iDqlbdu22fzyJcDPBaP99X1Zp9lQciPbrEW3mYjuWDJrkR9RxC3qgXx9fVm1apWN3ig8zFYPFIIfWz31HzzOEvhJTk42UaW3aWNdgbxs56bUPL7Abs8FD3qHYbNLUq6R/Wyr4s3v83pbad/dkWsn1ETd1WBMNaJATnGjBN80NSWMRlMxtC1N11vKOjBnX2XKVrO/gqijUyIa1Tt2r980wHUZTNkKHo/rTwSnz93DcG0LxAiJVqBcC2g6PrPt3dyVom/DD4NA/QkY2uZvLtlG6Sni0YpKpW6TbFSiatsK7/mTURZ/GuXl6RdKuxNK4KiFuLerR9l5I59Ek4x6PSkXAone4kfSiWto44xoNS0wFpmSznNkznTJeD1sR422qfRe0galc8EiUxmXEPtsUdNt6NUGot/MjKDknILkzDqMxjswSQj15jCtFkn/6vQrEcnmbilmWQASVNBgZxm8rq7PNvh2r/dICqkG9zSQ+ku2z5zc6+OdkIPdOcelNQ16Eel4m20x8HUYHK4IghC9Y5w3+24GPTlagB+hCxUcHGzSznoWTTA7Hzx40FT707ZtW1OdjGB3FqBIEK3aagL8nDXa+WKR4+RNJVefSuRHlByILjuxz0QNkDInc7itiyo8zqIHCsFP4eaw6AHBoGqOEVRw/Jw5c8ZEfGbNynZvQc3Dn9rt4dDv/qQZ/rR71f4CP3Gxr1puY+2REiiUmfVAIg117lAqfvvTuHYojUfBBqQqKUqdkWIGKGtUIzp/RXIiKyj600fJtB0Vqd7I/gLgzq4xqFLM/OjZ4hGnn+Hl76GkhY661BgIPAjXt0NcUHrLd4XW0HQieD2WHbnyJ2z6APSrAetSJLZMCe5RtnRn5o6MZ3wXPVodbD8jYekeJQ/UbujHDqHY5H55yghYupZ40D94YwmJZ25R+Ze3cKpuvUtQn5RK/OFLPNp0krQbYehS3dBq+4DPRFB4QvR6fPQz6PtNM6p2ycK4aNtirR61ZswxKrTyIeCPYO6+dNNyFOreOaRnFmFYkB28YDSieG8wJa/8RfBoIapi3mLToNGesngH/JYNkFyvPx7V7a6g+jbXQCf3BngnbLI6f1WLAexMCmDKPThdEZPUxW01vOFam9+OZHaniXsiRIwFiaDopHpWTUjpDB06lKZNmxIUFGRSM2/VStTP2W4C/PgZC5ZibiG5VGDwI4CP4FUSkR8RuXqW/W67d5+9IwvBz7N3T56ZGVkCP+LLKXLQnTp1sjpX314tqXXAfjFEVVgM+hlzmLDJOriydPFlffYx/2snfCvlnapKSzFw+mAKp/eouH40lcRHBmRqowkUlTDCA6mRGdsr07CDbe2yWefUvUgkyfHzbIwx5ViNbC2MngOVrPv4yajkKBBdXNe2QXwICNmFhGTgAGB7K7klnypky6lR7j02f6ClipnsR3Q8LN8rZ+tpOYmlyuP84TTcmtkOXpNOXSV4+rcUG92V4lP721UwnTFn0Uofu/MccZuPIb9wC1laCq2/bEnT8TVQONhXs2VtYwf8GcTZNXd5eXMnVo06wZX6f0ExCy3SyTHIVvRDv/J4tlPKl81hSNJy7t5I5lRvIaRi3qJSoNm+UngHZKa1Hrz1E3HrD6B9EGp2kJNbQ7wTs6fJch6Y0nE4vn5nOVwBvB675kAybGg+mK9+yCQYFZ1TIvIj/p2XNtY/9eASbe6bNm1ixYoVpm4vkY5fsGABRYrYF438f4If8WwV/wgGatGOLsCb8K+YgwA+Irq+Y8eObGSTBfFvx44dTWBQpAft9UtBrvssjy0EP8/y3fmH52YJ/Ii/Hzp0KE/eD9++ram1Z36+VhHWdjSzjpkves7rhGtfOcWIwWqadcx/HUpKkp7T+1NZ+u4j9EYJ7V7yZuQcHxycbEmWpc9wQLkoIkNmAfnh5vkTBr0E9bO3Qee19iefL2wL8SIteRxkqemiqMapIldm8ynSD9RRyrsL3RpfZNlMIw5540kuBsIXW2VcDnMkrX07is6biMLLvA8MGg33Rn+GIUVF+eVvoCxlOy2CRcAwbxXNPl3NWI2Rw0o4KZMQ5yTHuZ43FcfXpt6gSsgV+asES41VsaTzTl490gdHdyVb3zrPScknUMsCSDUakS5oimH9uSfTle34hQb73+Hcd5G0HiPnRC/L4Cc8CVr7laeI31rT+KhvN5O81w99nJpEP/P6XE5ujfBO3GDWPUbxo7vwR+KWr+ecIpy6Wb4iP8RCwvQFJm6cDBPNDXXr1iU+Pt7m2hk7N1iBDhfzGjt2rKldXNT4tGjRwtQaLp5RS5cupVYtC+lQM1cVwOOEMTcbvT0TbC05b1PkR9T6CP6erCY0ysTfRERdkDWKou0ME+Ky4p/8mjiv4Pnx9/dH1EMVWqG8ReEesOIBS+BH1AHs3buXbt26WXwginB5iTb1qLNnPsqi1mUFzE3hXvMxvH3UtqLnnOP3L75ONZeHDJqYH9CR/Wyz+z/kwyYpHLkFv1x2ptPIogya5o1CmTcIeqVFFNdOTwDyk3I5Dl2qQ/t8Fkx/3gqSfn+cyEsFySGQiSJYUeQqCPhE22xevC03qeDTiQUTkhmUjyCcWgN/+ElNEaEwgweGiSMpOq7nkwjCoy1HCP90HaXnDMdrYD4uYGbjJBy+iHO3t/hTqydrrEf0rl0BDjnAaZmEeCc5Tg2KUe2V2tTqVxG5OYlzM+f/us1f9F3YjArN0zmnDn59nV0Bw6F9uuq6OZN92Qb92vTIj+T8YUp/O4rgVaGmGp+24+Qc62EZ/DxIgPb+lSlyYiUJu/yIWrCa+oc/52rv+cTuPgxm2KycXBvjnZQjzQZodx5GPXsBE3QPuBSpYV+OCN4bERK6rtmdrZFBgAoRNRC8XnnJQ/wTD1PBNi9qfn755RdcXDJT06I13M/Pz1SobYuul+neSCQcNQqaifxbO8lZm8BP/q9gfaRY682bN00sz3L504t2/l3z/SfPWxj5+Se9/4xfW9T7CABkzvbt22dKe2V9O8l6nBhXuXxRivq4kCB3wuDmgkOlUji1rYtTo2o4Vy9jtS06+KV3GfqWD+Ub21/0fOtoBOF/XeTtLwteoDmz6wO+65FGLV8hbArztknZcMOR3pOK02ecF3IrCujzR4Wzd42I3Nj+9pnpwxvQVAN9F+dvl3zcBNL2mGlpFzDgPCg2gjEAJK6g7Q8I4dXMh6VCsZhaFT7jjw/UlC941ozwmPS02LazMhLLVCQ6RodTpdKUX/Y6cg/rPEK2OkATEUtclVHsSE41dflZM7GrA0RS0AHOSCXEOshxaVKCOlPrULNPObMpnm1zziF3VNDrg8y6kIsb7rL296bQ34J4qeg2/LoL+l/2QsgdPGZ34+HK+7g8jri0Hy/nSDfL4EcIrHe6XBXHr94i5JUvaHRqIVKlkluvLCH8RxE5yE00KnVpQqlkAXzTTRt4H82EOTR8GMjWCgm4K6DDKTicA5O/+EDG8psPTTIIGSYoLUQaRogZ/9tMgIDq1W2XphHg55AxUwMtP+vtKPH7R8GPmLMAgUlJSc9smjI/fv07xhSCn7/Dq8/JOa2BH9FdIbq9rHUhvFDTjb0vak3eEMAhIBp23ocjyW7cVjuhdnFGUdwDl0aVUbaoi2u9SihLepnewEKXbKep/gztp9sPHNQpWjYO28X32wr+qz21YyhrB6VSLguFi9AMfXOznN33lAx4zYduwzyRSnOTLa79PJzlc3oC9hVepm+fWKhxFkbkfoO3aXt91AjUIjKQl90FueCHOWRKcaFrhZfXAV5sfYtlU9NQPOWXx8RkaDZRQmdfKXdTZMTpZCQZZWhcXdFXKY+ucV3c29XFpVFVpHa8uRp0Oh6WGcqqyJh8QU2xSy8Bu2RwViYlyUWBR0sf6k6pTfXuvoSci2LHO+eZsl9ErjLv9Z3DD1nxmRfaEdk7rrJ6XbZ6HPrhY3Ba+Ao3Ft+kXBYC6Y4T5RzqYhn83ImFTn5leaRXUv/gJygfpw+DP99E0BzBbWWG+8izLWXifsGQkETSa59Q5OhxdpWOolaWsrVWJ+Bkjgxo1wcKtoTEZNswgoBvypQpJtmEZ9lEQbbg9RHRDvFCJvS8BIgzJ/JpaR3PC/gR/Gvr1q2jcuWnIe38LN/1gs2tEPwUzH/P9Whr4OfIkSMmkkNrD5ceNTw41F9t1UeCx2RvMOyLUHBO40Y0jhjcXdG5ueESG8KE31vjXc7+yMDStltZdSwfMgU5ZjuxRQg7JqgoaiaDptHC1N8VnIxQMmy2D+1f9MiWGji8JZa5g+qDMW9dntxOMkD5DTBhb/722LymoBHFzvZYLDCHCiU34u6uoHwxHRN76unexC5KHYsXTE6FVq/AklbQOoeaR0waBMbDlXgJ/vFybj0ykoADyVIHdMW80NeojKJFLdw71DdFjHLag+av8vbFQAZpMgkC7Vl5zmPFrhUVNTsdZfgbjYRKJUy5NxJ3n+x1ZGEBj1g2PYnUcbssXk56YBHsX8TRL8Jp3SD7YZ1ekXOws2XwczEcum9RUP70MpyrZK47cv1RbgwV3VdmOGQ82uLxUQeMy9exxPEeI0pm1/BK00P7k3AmRwNgu4dO7LgfmW2CQh5C1NIIxfRn0UQK/vDhw6xfv95UlyQKnkW9jCgYFq3uM2fOtCvttc+YVyrYuhe6Sk7845Ef0ea/Zs0aE2gVHEFZC9Vt0Qh7Fu/z3zGnQvDzd3j1OTmnNfAjur2EarCrq2Vg0qV6EY4NSMuXN+7EQb39xShS0QtFahxevk40GeRLtS6lcPXOu+V2ccudrD9V8OLZsQ3uc/JNDY5WCn1TVTBhnZKABCVj3i9Js25uJhAk1N1H1fXGaMgnLX2Z1TBZRGTyYR82B+2+fAzcyrtjpzBvaBr+t2HjYTgfCHoDtKkDU/pCmdxExnleR/io9RQJi5sZaWcHx6DBCA+T4VYcnEtw4EKMjIcpEpKQkypVYijjQ2KCmq5Xg/labR1o5zlJCwe85CAlWCZlesrEXEckhKXwde9LJM4UcSMzFnIRfh7D8LpXWfuJIIvMbl0my9nf0Tz4CYiCl/6SE1+tEjUOfp1tYPyxK1zpdwV9nKAxyGrJyOSNGV8tjKW+IvWRe053U2DiFTkHS2deV8hbNI9w48C9h9kGiAiv0PUSAONZsgxZi4zIlNDBElEfAdJEOn7Xrl0IgsGJEyfaBX52GwtWe9ZDcuQfBz8VKpintRDPJKEdVmjpHigEP4U7waIHRPGcIDo0Z+KNUHRSCGFBS9ahelFODRDt1vmzyrtLknxyN1JPd3R3g9EuX43rqUM4oqJMDVfqDSxH5bYlcHDOnZtZ0GQnm057I5PlTkfZM5tRdYK4+L4WiQ2niU+GMasU3E1zYOLnpand0pkurhr0WtHxlQ8r+QNM88vHQBEQaApaeyM/4lKHmTZoGN9NSs123dhE2OsPW4/Bg2go6QVDOsKgdnlHhTKAz1dNjbS3oN+an0UK6YcZJ6XcVUkwSOTEx8KYSDUD80cuYHYKS6TwQCnjjIcD4yPG5DpGMD4vbHmQRzMCs3+m1yHd9h6ykEMoyrhy6ZXDVDHTaNdtipy9HXKDn613ZLxz1oHBv7Xg5w8iqLLry2znTw18yOUu61EH78/ydyNShxcp77mby/U0uFpIWR6LhZ/uKljjk/ndnhstYw3FuHL7drbr/PXXXyZdLwEmniXLKGIWHV1//PEH+/fv59dffzX9+7fffuOLL74wRTxEMbQ9Bc87jDZSS1hwRm/JwX8c/DxL9+lZnksh+HmW784/PDdr4EeQHArae2usr22rl8CvfwJmymFsWtn4ow788eFSHHp1yHW85sxF+Gk1jgHnUMj1VGruTeNBZSnfxBuZXMrXnQ7w9SpHSpQpGKPvmLpBXHjfPAC0tIioeBi2Qk6siwsBp4qhV80ERLrEBgSV9aQ+38Or/jb5KudBks/aYkzekY+xAYzs2Z3Vb2RX/M56IhEluHIP/jgBRwNAdHU1rZ4eFcrJAaTSQKvJEhY2MdLxKQIfMZ9PL8nwS5Dx53ANMimEJ8JXpx3Yf0lDlWQjc1KgIIlPIVQwSylltcbA4EoejL1jXlvsi8a7iJyeyYpM+C34eSwOL7XA9aPXUbfrTdIy85GhHq/K2NFab5q/MOHbj88p2RzvyvSjHfgfe2cB3fT1vvFPmkoqtLRUcPcCw6FQ3B2Ge9Ehg+EbOhyGDDYYG7Zhw929BVpa3K24Q6lRqmnkf24KtGmTNEn3/zFG33N2OGuu35t8n+973/d5osPlzOkRTNHD2p4fRXQc58tNI/7exY9bI7GYRGfvJRTwiMEzOJ7Oeia/+oUFj1+omOSR1N/AMFs2FqyFVWwUD06IIPlk27Rpk0bXa+tWw4zRZhy0DFX5oO01e/ZsDdu8GKfgzBFp3ILzJyV/jki+MCbzSXhGMsFPhrbls6qcCX4+q+363w7WEPg5d+4c+fPnx81N/x1Iw3IF2F3vJU7p31LpnNiJp9AuW0eslswyOHExzoS9x1Gv24r1gzs4OklIDHvL97Ps8G5iOjNzys76ln3I2QmmgZ8P9R+HQMHRuVHZeCBJjEWtsgC5CgtLW7DIBko3VAli/QQZm/hPRKQmAyRJjl9Rf5v8cDNl9yUz66COEYHMptoLWtWuyM6J+sFP6hbfxcKxi7DlBDx8BVkdoE116FQH6nwnYVYFNQ0ygkJ0TGH2BfCPkLCzpxrLVJQ9Irj+2D1YfApC3kCbN9DdRG+Q8MU0tLZgtVyF2P1vq3jQNaitzsX8udp+ng94qInql+ybAdd34bj7FywL5UetUqGsUJvIv3VfN7QeacnqsgqcZJCohJ4HrXhVIic91yaJBsdEyJnx9TWK+goxWm07W3I0sbfeByJLj1LAtTsP5r3i+A1YvcWS1cV0X6eNeyijQkw8rR2hU4gtB7y6ETPiN5yHePPYX9tbKLwpghtmzZrU12umnqt/tvwHb46IbRFX8MuWLdN4gETKe48ePTSkgYUKFUKAo5QiqIZGIcDPLnXDDA20leTwJ/f8iLURnq9Vq1Zp+I+EJpuPjw+jR4/Wm52boUl/ppUzwc9nunH/i2GLe3XB5qzLLl68iLhnz55df0ZVm1pl+a30bQqYTvOj6VI8xNzOlMEmYKdJ01XFxxPRyAeXyIe4ZFHSoosdLbvZ4OBoOrFd/3IPCRpvHvgRg7YfWZHY6skEd5qJKOLh7TWIuAJRN7CIvQ+xL1HHRKFOVCOxloHaErV1OLRcCIUbg5Vp2mKSmfVQx+wwad2SCsupVzkfR2dpX3sZ25DwJNx7DrsCYPEWsJdCSTcJbfKqaVcYrP+B7LF5lyzwDbNkV095GuCTepxvomFZEOy+CrmiYPQ7KGjEZLrbSGmnVtNKrkKE+s5qW5B2WxvrrPlrrf08bumLdFU3LGuXxOGXZEkT5f1H5OrTmetLnuqs23mcJT8VVOBoAy23WpDrG08aj0kW10yIUTC58UWKnUqrUXW+4g9EXxAepafYO9QhZMF97GQQHg2Nf5JxtqRu2YxON2VMsopnWLgtJ1uNIqHPVI0LyHFAZZ6d1o4xE9dKjx49Mkkjy4jl/ceKCP6h69evU7p0aY2Cu9D3WrhwIa1atdKwPAu+mw/xQel1KsDPNrUOAdr0Kqb4vK3kwCcHPxMmTGDnzp2MHz+eggULauJ8Zs2aRYsWLZgxw3TGfROm/1kVzQQ/n9V2/W8Hawj8CPey8PoIAKTPen7dkNEuJ6kgRLPMtJwHcqO+chyJCWnPoqu3vX6gaK+KZKlcjOdzNqPYdZCc7tBtiB3VGgn2VOOuoAaWf0jAOPPBj8PIcsRUN8N7o1LAgXIgz47EOQyyuKIu2RY824Fd+txHkhkNUMcaVvbWtyU1v3LjxM8Zz5qq+y2sqAIik2v/Cwn+z+GtHHI5QIvcajoVATsjGKNTjvPny1IOh0jZ00uOKSTNApSdegC/noRnr6FJGPRX6Ra3XSWBS9ZSfkkQnEiwD1g3uizN51TTuWS/VNvJiwhX7Df9jGUpbV6ZhE176H9sCPOH6fbC+EyS0kGmZOxpSxr84UXpxtrR4EqFivE1zlA8cFmavi/VnMDbU/5Yy2pwbuJ5yqSQQqs42YbzxXQHgNe5YE18ggXn+85H0WbQx3YdB1ThWYC252fevHmazKn58+eb+Q3+31cTUhwi48tUE+Bns7qFqdW0yneQ7Pnk4Ed45IU3TGR6fTDB7iyoSYRAbaYlrUAm+Mk8CXpXwBD4EW9bItg55RcsdUPfDexNu3frqW+qokKKhhoedeTSn+uwKm+a2nJk5+GUGFYbxyrJD6O4x695Oe4vLK5fo0wFK3xGyShU0vCd3LcVHnJyrPngx3FEad55Czo9001yqDLq8G+FxDsQDRYHkLgGo2HIK9YIdcnOkK1Q2oYVciSzW6OOM48jqHo5D/zn6RfbNHYmdQbBOu8ksPPBRNbYtTA48FyC33OIiAcPOwlNcqroVhyNB0Sf/XLZgv0hluw1Efikbi8iFv48B1sugmsUjIqCD74WEbkzwMqCXYmqj9zJy22kXF5QnWoDtc+gSqVm57DTXNzwBNnLKzpJ5WIHT+Sw1194p+Ui1Ayr+zgJJ4IkfBvYCI9CafXjxHdwXNXTFDuzIs2yXGk4ibcnC7Kw83aG1NM+o3Xm2HAkV4JGsDSlyVVQNlDK7TGbUNfWvsbLMrAqz/1TBlDD1KlTNUBi2jTzZGqMPSvmlhNXPGKN9JGtmtKuAD8b1K1NqZKmbGfJzk8Oftzd3TUgJyUNiaAAyJcvH2/evMnQ/P5LlTPBz39pN//huRgCP7du3dJ8ucRbhj4TQYeel6bTyXiS1TRNrbwGI2sMx27CEJNmF/n1YDx/bI7DV7ovOcKPXSZ8+grso8Oo39qW9t/Y4eya9lrsu4oP8P1BPw9LeoNyGlGSKO8b6RXT+bk2+ElZRIznBLheQGKnhjwVUZfuAbneE/JEvUCyaBjq2LQPTGMGUrVsTgLnGx/zo6/NuoNgfQ3IbiDsSqSy3wqHgy8kHHsKoXHgIoOGOdT0LAHZbJNaX3TVgt0vLNnXW/6PXJ2JNoU36OwTWHAC7r+AumGwT2rB8kSV1tXYZDsrVDsbUaxBsmslMV7B2k7HuO/XEIX6Gk4RuoFmbN0ORP96Ok3KuQgSH/STLXv8VAzzq0OuEvqlWMZ5BVA0MO1eXms5lTJPbnN8VESaLRiySUbzV/E0SlLh+Gg+d2TsVtgRsV6bzFAUcBhYjRf+2rxSY8eOjNi+OAAAIABJREFU1Qibin8/tRl7fWXuOP8r4Kdjx44a8tmff/5Z450XgEdkvQkAJILBMy1pBTLBT+ZJMLgCCXq4U4KDgzVvWyKoUJ+tXLkSxdbBDNXz1mvM0kfLIfvNqjgeXW9M8Y9lIpv1pfTPnbErpkOCPEVLghn45W97iF+7F3fHd3QanIU6Leyxsk66FhtZ6QFHvjcf/DiPKEqk9x2Txv6hsH7wk7q5a+Dkh8QhCtwKoc5VDYnvVdSx2hlCxg6iYulcnFtoPkXBh37qDYaNNcDNBH1ZAUgE2eHBJ7D/kRUh8RYkKBQkoubqKBWyjCXv6V2C2yHQeBnkTpCwLVabFHCAvRWeNzriki8JoMSExbOy5WGenR+JUt4Dy6wtcQrTLSQqr9yIqFXa4PfSbeg20Z7gUtNR3djLyhtJrOb6bFylExQ9t0rr47eBt7jdYTqHeoZTQ8fLxc6LEo7tkbCoaDK30KY3VkxXZ+WZZU4i56fNPrMfVJ2Xp7Szvb777jvKli3L0KFDjT0+/6/lhGRFjhw5PlJsiNjDvHnzauJ9MmpiD9apdQe1G9t2N8m2T+75CQkJoXPnzhpuJvGCGhcXR506ddiwYQPCK5RpmeAn8wwYsQL6wI/Q+hFZFCKgUJ8J8dOgma2Z6a39MDGiW60iTocKYn/NNM6ayIY9+Wp5H2T5jA84koe+5eXUv7A4c5aiJSV06mfHhhGvODDKfPCTbUQhwqvdAQvTg60lh6ugDhMxGWmvQ/Sv4Uuw2YRU9QSJdUkUcb1BJWQQjI80LlsiD5cWR5m6TWnKC8/P1tpJnhxzTYChpvuscHdRc+uNFCuphKFe8bT/Kn1+IWP7/OsM/BoAfSrD6UMSFqQCPx3srWgR1UdzrRV6/y1/tTnGq2tLPwrDWjo3xyk07Ru1KiQUx1ateLQyKc5CyKKM/c2WtSdz8KrrKXDKieUSb1bcNpwKN7WKH3nPrP44HfnrCG7XH0XXKq+pn0VJSx1C5M/DoeNCGf4lkq4vn8RB/Tt2tFrnxaKfXUkYm9ZTZTfYm1cnD2gtmyAJFMKm/foJgd5Pa3fu3NEE8X7wRIlki7Zt22r0B0VWmqDd+OAdEtpWQt7ClOswAX5WqTtkaJI+ks2fHPx8mIAIBv+Q7WUoNjNDE/6MK2d6fj7jzftfDF1ke4kflNT28OFDRGBhiRLJmSmpy4ig6AEtqjClOpR1hdxZhHKy6aMuvt+NiEM7kOYxnigmsnZXym0agrWHSCE33aLOBxMy8Xdsrtymekkp3aspqVkCrE30PGQfU4jXFa+Apekp9+aBHzHXN3zdYRhzJsQzempWjhzMRoKyDIlxgqG4arpJ355F83L997emL1qqGl594WAjzKY6+NBcu0M2jGmUQOW88CAMfj8jw/eeGkeZhNE14mmi/wganIPQ7G3ztwVOViqWtwe/e7DtL5iRFOf80do4WtPubV8enX7Jep8zhN3dDSSz6Fo6N8UpNG1wufyQH61X9WfNxFjuP4UOP9hxM+dg4pvM+di2zeLyLA0uYnCc06v6kjsoKdVclajgTu0R7Bx5lxNB4BEJPjXTVhdf2Qo/2nCxRAKJKqh2yYYWR+ty+1QkG263h47D01SyHVyD1ye1yQy7deuGuEbp0kUI9H5aCw8P14xFgDEh3SBiDitVqqS51hF/F1lOWbIkvSgIVfcBAwZQqpTxsYIC/KxUZ2yefSTrPzn4Een+lStX1sxd/AaL1H/BcyRS30VWXKYlrUAm+Mk8CQZXQB/4EdkDUVFRBn9cxNXYsEFlKF0Ubl2FdxFgJ0kKgK3mARXdwDMbyNJxSowNsGD5oDlYdxfq48ZZZPX2VNg/Fksn00HHhx5CdwfSdO1M2ldQsPCwNdcfJZLNyZo2lVW0r5SIR9b0x5JvXEGelD4DNqa75c0HP4nUa+TDwc3JQctXr8OYH10IOueOPLESibHiTb6MTuLFYoXyc3tZ2jiS9GerXaJGHzjQBBxMzOhK3U/Hw9YMbyCnaqrA+ZuvYFGgjKDHarI7woQ6CVTXzeyfZuiXn0OPrVLG11PTsVTS1dCWqxC4Gr5PVbqJozWey+uw7/tgIh6JVHDt+BxLl8Y4vUlLKxA3fh5r3Bfy8JUNC7dl5XlHX/BIgdQSYsiyqiqLbpQ0uLQzq/mS83QS+HnUaw7f5jnFyF4KVqyHqJswQk92ds1pEvwKqvnmrjVve3nSeHwJlve7QlCN9VBY7L222Q6pxWs/bWJM4VkRQKN164wFApt6dvSV79mzpyaF/QPFhvA8i4f64sWLNckXkydP1lz1iKswQcwoQICxsUL/FfAj0tsFCa2I9xH6ZmXKlNHIEIlrsH+bTMk/dS7MaScT/Jizal9QHX3g5/nz54SFhWm+WPpMMK+uW16dxbO1NY2C78Gew+B/EkIegaUSHC2hnBtUyQ5l3SGnQ7KX6E4YVI9rjPXGJUavfESVNlQ6MRWpIVGudFp7PGsj45+upo+4NXpvQsJi8SHYc1mm+VGtUkRCT+94yhfQfQ1TbGwugksGgn1y2qmxk5AcqoI63NRrr6TWa9TpxvGdunXVTvrDD9M8uH7TjURFTRSxfYBkBeiC+Qpw/08hcpox8+4NR5qDrfE3bjo77HLEmsF15XqBjfByXHoOv5yWceVZIoXdVUyso+YrPbdJk49KOHrPgg0dleRJ4RhccV7C0w1qkpO/36+lpYSXLl8RHSKCgdNOxjJbI5xC0nJRxTTuStnwM1y3b0t0mzVpD8irW+QL6sSU44YzAmZ5+5HDfzWhf+wh39417F2UFI+1aS/cOA5T9YSp9F8jJf8zJVscsjLkbFNNnZm1T3B/+hOdh1U2pDYhfnu09qBJkyYajawGDRpk7DD8Q7XbtWunSbsXmUvCRAyLkNoRiRe1a9fWcNkIrh/x/wcOHDDomU49JAF+lqkFHab51l+y9pN7fhwdHTUvpsIz7+HhgYgBEp4fAYaE9yzTklYgE/xkngSDK6AP/Lx69YqXL19qxE31meCaOLi9IfOmpB/zExcHh/3g8FG4eQ3i3kmws4Bcdmq83eD7iOLYnttnMDA05TgiyzWh8sUFRpfXNYeHPWayqtApanvqnqEgYTx4GZYcs+FZGORxldDFK4Fm5dQ4vg/yrTDBnYuFT4Gj/tgovQu4pzxEf2dizE9Sa1W8u+O/L32iwl17YeLsnDx8KIBQE5Tx3cmXpw53V4RglUHQUs0H/FqBtenhTlpL0uOoJX1rKaipP7b+Y3mxJwGP4Y/zltx+rcbTAybVUVLYFaLiodkaKVXzS5hdX/FRUuJD5QUBFii3qzRs0B9sq7WUCZYORMbqF4S0yFoP5zBtj4mI93lX62sUTVZDQT1K4bcO4a0aSd+leg7Y+0HMruGLw8/jieg/leCt4R8zxw74waFNsLCb7hO0yh/G/C1helh7LN+zS071PsnjOboJFy0HVifcXzvgWQCKX3/9lerVq/8rfikFuBHXOh+Y5cU1jtAdE14f8ULWrFkzTXp+nz59EMHQhqg4dIGf39Vp9dtMmfhAyapPDn4EMDx69KiG/HHRokUcP35cA4SEt0wo32daJvjJPANGrIAQNhVcGqlN3LMLLomKFSvqbUUEPJ/xbc2McemDH32N3AqGvYdh7goHlB4eWDSpj8WQ3kizG5YWjyzXlCqXFhgxQ/1FntQfzsFWtylipAr5kzcwfy8EPLBCJlXRoKSSXZdduFToODh/ZfJYrPeXRf5WxGaYEvCc1E25cl0462e8yrnY4r/Wwexf8xL/9hVNvNTUKZlIhcJQNA/pMinrmlzVnhDQhjQgw9SF6HUUetaE2snOKaOaUCjh2H1Ydt6Sh2Fq4hJU/NEOauXXfR6nHLMg534VLd+3/gho7+TEc6diqJ5oBwKnHIA0W12yhggqxCQTkhbvGnRF9uQh777TDTQ0BU/9RrfaK6k/2HDMzyxvXyLeWnJj1UtcXZJ7PnkW1vwBK4TjLpU9DQMRWuRQMSf9dyUplSsSVUyqFsjrX8TMUphCgXTxUKSndxF667bWR+LaSGQJiYyvf4P5+/tTtWrVj1pdu3btQninRGq3MJENJmJchCSH8HJkzWrE3fT7iQnPz2K1jsU0YeLfSlZ+cvAjUtwnTpyoGfXq1asR3jIBhsTfAgPNFEo2YQ0+l6KZnp/PZac+0Tj1gR/xw3L37l2qVEnSINJlgmI9+FJnJo40H/yIduPjoW0b2DMFVh+Hmb7ZCXPOjXSgD5atGiCxShuF/LZiayqf/ylDq/akrA/XRr/GzgxtMhFMu/okTNhsxxtVYcjRBGXhwSZdf8kOliU+wjzwU6FsZ4JOmMfS3G+kFQ8K1UQVKyf29F1ULyOxlyaSzV5FxaJqqnpCmYLgkeJBrGuhq/QAIYdlTpB7yvb6HpPSubqSemY4zz60E/QYfgmSaq669Nmo/RZUPqaiFiBgY3NbG679sh/ptOkon+oX9rT0qIvTi2TwEzt+LsViz3P/8CveDbyn/wxuG8qE2Tco7KU7Hkxcq944+JLVQ66wdcY7albWburCNZg/B9YP0P77k1Bo8bMF3Z+q2NctP93XJjFTv7oTxfzBEYRP9U+uEPEGqyltqdkSwq69ZtusAx+9KqJ/4VkRSumGsjoz9CX7Byt/iO05e/YsgwcP1rAcm8L0/F8BP2JJxW+zyHQT8T/CRPyl8OKbEgD+D27Nv7KpTPDzr9yWf8+g9IGft2/fcuPGDapV0035L2awfv16Qh/3ZvTgjM1n6264cRR+7JHcTuhbGLVOxr6nHsRXqIjt9wOxLJZMaPi2chsqn52doY5flu7C7R8zFvhbfHxO7gw9D9eOYHVwCRK5BHJ3QJ7XB6wNZ6IlgR+hCK+fAE/fBL8q1YXzAcZ7flK2E3QWhm6rQMPftan+46PieXDgLiGHg5Ffe4JFdCxZrJXkd1Pj5ammQnEomQ9s34PFqgL8tMvQFmgqDzgu5WsvJQ2Lmd+W/wNYfkHK6vb6wc832yxoe1qF8NENs7Vi+7ezkFeqj3TIBJSvk1PNtUehxDJHA5yeJYGfRP/zSEaNo8eOBvzZJJCYvmf0DlqyojlLz9pgnSriX+h5nfrjHv5/vyDCvQrSB9cIO/QkTTu378PY8bAjBf/nB+Cz6KmKUGBx1/x0W5f0Hb248ylLt5ZHMSiJ/0lyIwDrBf3otbQkBWvk5OiUs3Qv9K1GF0uYABOFCxfWqKaL9PJ/oxkbzGzM2AX4WagWGZHm2zDJsk/u+TF/9F9WzUzw82Xtt8mzFRwags8ntQkejcuXL2v0YvTZ8uXLUb8bwpC+JnerVaH3YOheHurouTk6dgm+3ZmbxxbuWHVvi23PlkTX706lIMNq8OmNKrJsRy5NyBjfjceofIRMf5AcYCqPh/3zsQncDhInFPn6ocwp7obSkuHIDpYjPkLE/JgOfkoU7cbVc7oDntObt/i8SIs8dDxh3BVA2K033N9/h2i/YOSP3mBHIk4yJffuq9nTHIqn4yFKbzyDfSW0qKKmcQaYwn3vwd9XJaz4Wr8Xsut6CUMuqLluZcE4zwq8WX0WzvkhGb4S9btf9AwzFqt8rXF8sAtV5Fuia7ZliH8LIu5HsH7AGxK66xfllf5eh5W3kknn3jyK4eD0m9w5F8frKt+Q2GkCvHpIpSXenF0bkqb/py+g/1A48D5r/XEotPzZgsVPVQgn2WnBjJ0C/OyYfJ29Nj9CzTZYbptHllMr+e5ITeyyJp29a9vu4RxQmOlTksQvBbAQoEdkdjo7m0cZkd7e/ps+F+Bnvjp1uLtpIxwpWfLJwY+IfRJXXBcuXED8Tqc0IXKaaUkrkAl+Mk+CwRXQB34EVbpwL4uASH0mAiWdpGPon7EECqrXhQOT+RhErK+/eDlM3mLDsqu5iYtNoND8Prg0LIf0gyvCxL2WV2hHwNiMyTxkG1OM8OnacRQfhxEVisW2H1FfCcDKNh/yQkPBow5IkgSZMgJ+ChfswbVzMZioB/txaCUaudD88DfYZDHjzk/El8gVrCm7DHeZBJvXYXQpJKGvZ6JZnD/f+UHDitDMcEa4wd09fAd23ZLwW2v94KfVnxKG3VDjk9WJJ0dCQMSRHNsGI04Bk/S0H4FVka5kubWV6ObdaTUkO0WaFuHe/rtsmeOK+utFesdl/Wt5lt4tzC3fN+ybeYewSAdedfoVKierx1se/IvxsX2Z/F3auLuIt9CmB/iNAQF8ms+VsOSFWgN8hAnw82vn/HRfn+T5+fXrAK74BGK1eDAlcj+m25/aQcwvr4VyddILdqxJyvgSsX6COFAwBH+IqTHxK/RZFRfgZ47aNBmd1BMcI1n0ycGPYHMWBI9du3bF3l6b6uODV++z2pj/p8Fmgp//p4X9rzSrD/wI5ueAgAAN4Zg+E3wc+bP9SI+MkaZSozacmmfaimbtW5CovLWxeXcBa1dr3NpUwb19VWxypq+ILnpKjIzGsVlP9g9PP2PK0MicxpUjarIRqu7Pb8GmSdi8uIskazni8w1Hdqan2Z6fQgX6Eegbjrkv7H2/sySmXQcKNTM/0GZzrVWU3TgEq2wOBM/eT8zKkxSQxjHyqwTq51VjYSTh5ciTULsctDCcFGXwgOy7CUfvwYIP0cw6Sjf8A0KeWnNl3XkokkQGZ7F1CappgvDxGz3tv8S61ABs+tYl5+WDtP2rkabcuUWXOeJXD2oJz50OUyqQ/lSM7Dmiicj6FbGDVoBHCln291XsZ3bk7IjNlNQREy2XQ+02sL4ftJoDv72ClMVEaOsvKcDPjJp+PI1wo/WYHFTqnrZBeUwi6xoc5eyhpPMqQI/IlhL/Cnbr/7oJ8DNLLa6ZzbexkoWfHPyIVPfQ0NAvArCav1OZnp+MrN0XUVcf+BF/F4RZhvg/RMrpVwVm0iEphMAsE5mZPt1g52TTqjea6cbhkjshXzWIj4ZzS7B+sgkrm0ScqhUjR+9aOJQrpDcVPsL3CtV+mcqSbhkDPw6TqhEzIcC0wd84jmz3TOR3rmMjzYlKVZIEubjzEQ/HFBLpBlrNn2cIR/e/IF/a56lRYxFxP8M2fEX9lW2MKq+r0K7m6yn4UzeyeibHi0Q/fMPtYZuRnrtDbXcFo8slUMDJcBc/+EPV0tA6A+S0O6+BCHqe3Vx3X4IrqMovcK3lFOL7J3t5pMsno1wsxHv1oaZHWObvg717DAMDO3wECUeGn+Jc3BgoqYOB8F0ILO8IoY9g550kD5Mec/yuIm+3X9D7edlGIBHcUy9TMjUlFRfgZ2GnvPTY4E1ivJIfyx2gx+6WuBXRf4W13Hs3Fw5c09QXPF4iyysiIiJDlBFmH6D/ccX/Cvjx8vJi48aNH7mQ/sfL+Nl0l+n5+Wy26tMMVMT7CKCT2kQ8gEhlb9Sokd4fxrE/jKF2+V9pmezFN3kSf66H8MswykTv0brj0OPyDNR1xmn3KXK6g/djefVXbCyeYV/UHfcutXFuoH099mzRLoZc/5OhDczLmBKdhkZBviXNiB2hzQFj7CIUnefMlh1xHDukxPegNRfO2hIfK0Mut0Ot8kCeWIJEhXiDF+Kt2tdTOXP8wN5tdymdAW9JiUbZaRuYKpXI2MEDB3vuwK1PI9xr6o5Ufrr9PC8n7cYlMpxexRT0KJ6InQ75kPGnoWxxaJ+BbOuNl+DWa5ii4yyKlPie26X4PoSXh7XPunT2QJQbBLO4DgEtzVrcRCJrz7f3O5IlZ3Js1rb2+7lTchtkS0VLffckbPgWwjqC/QbYf13/iiqVZB1QhIiDD3WWOR4A/cbB2qegiwIpCFjwHvwErX/M5tEXGP/csEbXyvp7OLfjqqa/p0+fal5uhD6UIeFVE47Ev7qomOM09cgMjXGiZP4n9/zMmTOHdevWMWTIEA3JYUpr2dKA6zNDM//8KmeCn89vz/6nI9YHfsQgDh8+TL169fSKB44YPpAWtf6isf6bsXTn0qEXjKgHVU0Mdo2NB8cfGqHsqU3alqbD0LtIL8zDJioAyyyWuLWvgXvbqjyf/jfLXA7QKAMP3OPXoHngIOJ8fkt3nroKlFvswLHTaWM9RNnbN1Qc3qfk1DEZt2/IiI2xRS63B3Uu4hM8yeJwmB2bb+PtZVbXmkpl6jrS2G8w1g7mxf34fX8Eq8plyNtWPxeU6EcRm8CtH3cTvzGQ4jI5Y8rFUT1Hcor85CAoVsSCzuV0r4UxM1x7EZ6Gw7j62qVjEqD1Ogu8ukhZs8WBx2u0GXClY9qjPDRNcAnr6OY6lrYDcC8fi49/ilREYG2drTxtdT050F24lg7MgtPb4J2IULYD28lwMAlo6LQH16m+ojb+a8O0Po6MgkET4EmsPeEPEvF9pBuga8BPx7z02OjN/IbHUcqV9PHrZHC51n59gAOL/BBXJ0JItFOnTty7ZyBd35jF/0zKCPAzWZ1a3MS0wU+W/PTJwU+BAro1XsT8MgOek/czE/yYdra/uNKGwM+xY8c02V76giHbtWtC1dK+9O4COYwXV9da4/I1IWBWcvq0KRtgN6Ascd9cMr6KPBbO/Y71i23Yhdygw1fx/NhaTk4zs5UWH4ARiQtIbGxeHIH3Shm7jxkfa6FUqjgXqOb4QRUbVlvg5JRIkQJquneCRg1AZqK6ev/vLHnXvgOFmpoX93NhURBvrdwoMkB/UHzqzYm88Zy7wzZhfSOYpjktGVY2jj9vQN4CUnpU1J+mnt4mrzwHkTEwMsVQ3kRDqzXQe4ol5apIadKrKG9+0wYj0kGNUQasSyMGK5X9hW22ZbTbVxffUYfoekSbZvkvr8287Pw+0D0+ClZ2hUdSkKcASbIpcOiK3qFb7lzCDJvBjEmRfb1lN0xdIqHlbE++qpuN6aWDOPJUN6WBSLL/uUNeWi6swB8d/cnqYUOzZU2wc9Z/EA6ND2Jg+e9p2LChJsVdCIRevWoAoKW38J/R5wIcTFSn8hSbOP5pkpmfHPyYOOQvtngm+Plit964iRsCP35+fhqSQyEkqMuGfDeMVRfu4soLHJWvcXdKoGoFNU29Y6n4FTgYEb7iVRsCTQx2/jCWfMMK8uTrAMiS3bjJpiy1rSXUrkjO42vIo35N/1oJdKqcaBLh4ZA/pSz23AXlmpnef3Q4zQ9mZ8128zQm/I4q2HTIjUaD8rBr9kOeng3D3VlJ+7bQsgUYQ3x7OgiGbS5LwxXmiVoG77rNvcuxlP7R9KAvkWn0eG0gb2buJ/5VKPWLqRhTR0UxN90aaukt8O9BoFLA4PdKE/dDof0GmLHWiqreluzdoaD3zoEoRqZKafepDZe2p2g+DkvbIeSr95SvdzVFrVCxvtZf+AT21hrC8vKbeONzB55dhVU94I0IhE5FCGozFQ5f1jt0u4mtuTl9F/lyw6s30G80xDpm5dtt5bC2tiDkcRx/VTnHlteJOtvQgJ/2eclaJituOSx5djOa/K1LUbCGfs6eyxuDyXW5DBPHT9QkNAih0KAg4UP679t/DfyI0AQhQ5Qjh5EU9f/9LdaaYSb4+cI23NTpioeQIDrUZSdPnqR8+fIaxWBdtnbtWvoFRECb0UkfC46bc3uxv7wZl9dBZLV6Ry6PRBpUjaduNSWlSqCVmv3iFQweCDvGmzrqpPKD/pDxu8N68DQjaHdrM1i4GHLnh3dRWC+aSC6/NXi6xzOqUQI1S6bPXNzgJ2eOtjkG+fXrn+md2eUDDJe2YuIs88CPXK6iVSsZkw8k9x0VLmf3/CfcOfQKBxslzZuoadcOcuXUv75FGmWno5lxP6+vvsL/91tU/l37SsjU3QxqNp/6BW9z95KM8GdKHK2gfE4JLUvGUzkvGHMrt1BgYCn0qQrnnkLfXfDXERsKFEryrE0dp2Bhrp1QI0kA9KN1qQc3trz/34dYWPvQ4NdClP0meV3Xeq3AJ7CXVrXfS20kosRoOLwYokT6tA73odV0OKo/EzDLoPK83X2JZWvgt41SuiwrQ+maye08uPyOg3Uv8mdE2pg8MZizwE+tcvHsWRzTztbi0KIHxNm6ULV/Kb1b8OxiCMGzwtn85zYNs7NQSxfaUF+CCfAzTp0kC2GuzZRM++SeHyFqKjx2mzZt0siAxMTEIGRAhCdPgNlMS1qBTPCTeRIMroAh8CPeDAVdupOT7nQd4S6vOmklqoF/6O8j4hUEbMbt5gacY27jYhdH4TwKGtVScvsuuMfDUG2iYaN3LPAWeG/shar1n0bX+VhwSxNYvAxyiGDiFHbvFo5zh5L32Wnql5AzpJ6Sgnqu9IpOyMHdoRchqxmep50zWNxkCl16mQd+xIjr1rBg1qlKOucuj1dycOlzLm58jlQpp7a3ms5doHiqGy7P2o40O2le3I88OoGtPQ9RY1vGKL7Plh3J6fPxWFom5cYrFCqOHVKxa52U2+fBWqkmj6OCFp5KahWAfM5pgemck5DLHpzsYdIJ2BJog4tL8pVih+ZKjk56m/ZusH0tCN4Bkp1YO86j57n6uBTRpktYU2U5vc4ke34S4xJZWnwpUW/KQ5wIGNdzdWk5E46d1302E+U49StKOdfHOHq60XdlqTTp5ld9w7nW7AoL4nTHQgnwM6GCC9auVgw76M2FXS+4cCqO5vP0E5PGvU1gUzM/gg6cZ/fu3RqW9n37kqU7TP8ifT41BPj5Xp0xcPCTZPInBz8+Pj6aF1YBdIQ2m8jWEyLUgpNNxHFlWib4yTwDRqyAIfAj3OHFihXTy/4qssScandAOdHEH88Hl5EGbsAjcBFu0jgalIeBzaCgid5bkdhlP9KL+B6C7s1E21gXlv8NbgaAy8Ht5Fn9Azlin9C9WiLdq6k1D9cP5jI6HxHT7oOF6bLmWZa1YNOMw1StbnrdD/1Xq6Dmp9OVsbYxHDck9th/6xv8lz4mITKOCmXUdO0OlcrDN99ZEdOpAwWbGBbf1Le6a5tupfb+9xTEJm6BBujIFTyuP5IDJw3H+zy8r2LL2kTOH1MR/QayWoMCdwwOAAAgAElEQVR3fqhXAMrlgrmn4NZLeAxsO22juTZKaQ1rwvnFOmgNWnnB0xJ4lL9Gj9NNsLBMux9rvNbQK7Drx+ZubLzN8WHHefd6meEZS2fB8XM6y0i3L0K2cQqzDxeiQBndwrant4Xwrt019DlGBfjpaS1hmH9tClVy4f7ZcPbNeUS7rXry/d+PZGnVXVw6cl2TLi2SGrZs+eD5MmMDP6MqAvyMVIvgdvNtvmTiJwc/Qr394cOHmnAEQVIpdBiFCZHXTFX35L3N9PyYf86/iJri3lgI4umyc+fOITILXF11CzOKOo5VmyKfcsystXKd14TdqoM8i4elESCXQevq0L0uuKXDDfOhQ+chRYn0uWk6AFlXE1ZvhWyG1eM1/cTHY7VyNvkP/0ZBuyi+rZNI43LgNqUkkRNumDX3/AuKsHfnM3LmMpIJUEcvXVspaDH9KwqUNiK4KkX9K34RHF34iIjH77C1VhGatwTN1n6NpUxHHno6s1vdYBN1j4wyaw1EpUfrg6h6YwMTZpgW7Bwfr2LPNhVHdyh4ckvN69eQpwjsCLBJ40FRKNR4V7MleIV2phdREdC+AjUGl6TaBN0eNDHGdTXX0/Nkx49zXFv9LxKexxHyOB3wY/ETHAvUDmJSq7FeOhbF4d206R1Hrzm6ktiTujq46CkeQ4PRl7wuYFV/ZyvmhielN4c9jWV5t4v0OKGfN+LOvkfsGeTHvevP+fPPPzVXJatWrTJ7/z6niv8V8JMvXz6uX79OlixZPoIfwdlUqVKlzGyvFAcyE/x8Tt/OTzBWQ+Dn4sWLGu2f1FwSKYfpUrE+sTOEPIDp5vpTQ/ZLj1DpPSebQgWLH8G2WLB1hG71oG11sDeQxVR1SnbOVD4M2U1kyNtQB9ZsAycTNY1ePMF+7jDy3jnCvXceJPZdA0Wqmgy+isx2JvByPBbG0iDrWN45k+UkFihM/Z4musxStPXgyjuGeT/HIbcDDjksKNKqMEVbF8UpX1ajNvSvmuuof3KsUWV1FTrXeh5/THhAuYrGZ73pamdQjwTGTrMiT7607QTfVtF+aHGezksRfBwbDX0aY/HoNaNjtDO5Ure/vs4GuvsmAYqQ6yGcGbWDqOdKHl9PD/z8Cls3Qrb33kWFAuvp3eC2HRZqD4Yt2ot3O/1pklvG36f6zEc66RefC3FWILKcI99fbKAZm0KuYkZVP/pd1D2fwFnnefDLZaQJ1vg9eaqJ9xFcP0uWLDF7/z6nigL8DFNnTA9woWTsJ/f8iHgfITy9aNEijaq7uPIaNGiQxvMzf/78z2lL/l/Hmgl+/l+X9/Nv3BD4uXLlCm5ubuTMqT9i1qNCLd5OCwCp6dc37rPrcsDKl/I6nrNRcpj1CHzl4OEGvRtB04pglSpEZsEOGBW6CFXFb03bjPW1YP0ecNB95ZBuYyoVpWvZkNvdkcBoN+JdCyP38kFVqinItPV2dLVVdqEDx8+az2sj2jwXqOSXv1wYssxEkqQUA4oMkdM9tysKxS5Qi2uhZTjmX4csWwQe5bLh2aUkub3zIrXSvb8rq66iYZD5QaRnK4wk8Gw8Uqn5HjAxnQ5NEti4z0qnTMOuLQr6HRqCYuj7B4M8Afo3g8utsbBZy+i4VEHQqTZsY8NNdD74tabtPd2302+oJYu/fU7w2aWGj4lkBayYDYXLQGw0Vj+0RBneAJXrWGwft+aPa6Fky6kf2a/oe5O+K1+SkkVJ+Md+B/ZZQvuCcLp5YTrNT1YEnlrhOH0vaIMfpULF7h5HyHHgEd+9kzO/fEXWHTvO3LlzERp+8+aZmW6Z7pfk31VAgJ8h6jkZGtQiyZhPDn5EgHOvXr3Yvn27Rp9NKpXSunVrjQcvtdZXhib7mVfOBD+f+Qb+fw/fEPgRrlUR7Cz0f/RZ8TrNeNR/LbiY7n3wmFmLg7KTlE3niutJLEy6D1ctpBQvKGFIY4WGFFEigVfhkG9+S+Ttdpm2VH97w5bDINOdxp9uYw/v0mV0Kf6um5Qp9yQKZl21YcvL7CTY5ySxYlsSqnQGZ93AsdofMvaezJi3Q/zwNagnY6avGdlm7yf45FYMQ8oURq5cn3bK6iBssi3A3v0CWXJbUqxtUQq3KKLFdLyi/AoaXphsFkOwiPd50ngk+4+bduWla29a141n53HdQGLSGAWLC+0Hr/oimhoGt4Fz1UHZFolVf0ZEe2NprT/wfEf73TT6pQaWtlZsb7Ka5UHFGF7jNjf80wM/G2BefyhQCqvRzUlUjgXndprh2z2szuYIw2fv5zZXmLczlA8nSLDxjJNAw7wwwxOWP4YTfcvQZFhyvNYsLz96Bnb5uERxkQlsbLabDhdDGKpQsVEFL38Yx5gffmDKlCmah6X490swAX4GqTPmGVkiGfnJwE+zZs20gtOFvtejR480v8+GvPNfwt7qmmMm+PlSd96EeQsRU1128+ZNjXpw/vxC+0i3Nensg2+14VC0sgk9JhXNMb06B+1OU8bI+B5R52IkTHsl5YkavEpL+LaRgorzyhPjo18fSefA1lWDHX5gZXqci6a9XeuZtqcnE8qnfXDHyuH3KxKWPM7OCwt3VMVqIa/VB/KUTkJssVE02enK33vNz/T6MKcalSXMO2v62n+ofyvwLeNqViRemc4VjjoKpL/hmG8TttnekbOKByU7l+DQ0CPUPTEWS3vTWaIf/h2E192NTJisO5XblAPV1Due/f66wU+7pgqOT41O4lkY3gFOFwd5z6TmLafT7aQlubz0i6QdHHiUr3oU4YnfQ0pkeUqbb3Mwut5trhxPB/ywHXoXxeLQJlQOa8Gu/McpZXlUlg3h+mPpRMGpdS6w0y+SOEDkKD2UwUYvyPUeM00PhpBZVajSLjljcW6tE3Q90VnTT+i9SDa32MvcuxHUfe9YG6WW4HPcj3LlyvH999+TN29efvjhB1OW+rMtK8BPf/XCDI1/mWTYJwM/gpVbpLlnmnErkAl+jFunL7qUPvAj0iYFj0ShQvqDMsdPnMR8SUWo3t7kNcw5zYvDDkF4JksmmdTG3lewIMIS/0gPFBX7oyrdB5z0E7xpNb62Cuw5bR6jnkhu/mk0m1/Np206SVIiI23PfZhx05W7SlcSc5UmJkdZvs01makLMg5+alVSMfVEZWR2pl87ivU4uz+UqS0aojT1jVh9DFv3RVjIArDN606ORp7kaVUKJ8+cSIxUCD/XZiFLJwRTtkLGPGAioLl+5QT8LuoGP/VrSri4KBqrH3uQeMgR4lMwcks2Um/BaSp+V1Xv2Ts56TQenvacn3+aFUGFNNdf45re5vwBIWtiYA8lW8HBF/JeAOsUHkC1mqzPirHujWFV2snVzvNd4FtmS2B4CeiT6h1kyHVw3VKbwpWTU/MXNvan9c6veer3nCPfHGfrs2hShkG1lViy802oZg5Dhw7V8HgJjagvwTLBz5ewy8lzzAQ/X9Z+mzVbke0lrr9Sm9D8EX8vUkT/E16ky/ocfwVtTdfMyTmlEkedzlPCzLCbD+PNd9+NAkNrc/H328S+s0dVugvqUt3A1kAwswA/+8xntnUfWI8D7r6UN1HW4+ob6O9nQ7hlAh5uElyzS6ha04KKNaSULC1BJjMt9qVHWwUNx5WhSAXzFtH379f80qsDCQoz+U9cqsCcPXBuJ9aXtmAd/RhbVxnZ6xUjd8tSZC2dSy8Y+qfifV48VzOwt5Jdh9ICEblcTQ1vO56U6IxqdwSJkannGUixjn/QeqNgaNZt5xdf5PnJu+R2esuY5QU1hWb3uM/xtSLWSfcBsJBeRyWic9yHQ/Yx2g0nviZ7QjVWBOvWaBKFH9+IZmara1QIjWVDFbDTgbE6XYKal5vh5J4M+tb0Pk+cdRbe7XzA3jex2KbClU2tbTny6rVmPP369aN+/fr07dvXrN+Nz62SAD991IszNOyVkm8/medHJpNp4rR0/VZ/mJQAtJmWtAKZ4CfzJKS7AvrAj+CSEF6h4sX1B9SKq7GKPyxBNXh5uv2kLpB7cgWOOl+kmGmZ2mn6yf8yN83OJnHNKOLlXJrvz7UNz5Djhqq0DxRrA9Z22vXWVYW9gSaP+UOF/G0KcN77MdnMCBkKDoc5Z2FFfXgZAzvuwckIuJcAVg4S3LNLqFLDgoo1pXiWkWBnpx8QLZqbSJhjAZp8Y6THK9WM9/7+nKVDBqBQjTBvLVzLw+8XtFkH42PBfwPWFzdhHfMYmYsN2esW1XiGspbJrQFDGn6fxiM58A/E+5w/o2LpbyqWr0mLEG7dUNGyqRWR72qjjPhZxxyf4lJyFP1u6JfouLP1Jvv77mT9g7I4ulhr2lg66jHb5vcB0mYZSqQ3sbBbg7pUf1RPbcAtlWclJgiv4p0ZvyutR/VmQCRrxj/ieVh2YkMTiS8frHdfmpyX0OVla60g7987BKHY/5r9CWmvEt+qoaurO4fuJgmZdu3alS5dumjETb8EE+DHRy3Cxc23VZKBnwz8CC+80FrUZ2J+XwpbtzE7mAl+jFmlL7yMPvDz5MkT3r17h6enp94VEkG3dsUrw/hdkD3prdhYyzOpLMezXaFwRsFPZAGanUib7RUfHsuZGSe5tz8EuU1e1GX6QZHGILWCv72Srr3MtGINXbjVKlITwmOqiauwZtvhgB5JrdBY2PEAToTBfTlI7SRkdZdQuboFlWpaUKqsBQ4OSR3fuKZi6lwnRqwpaeowNOU3z37MqnETUKOtXWV0Y9krwWLdRH4f2xCyJ/7rsb6wGet3D5G5WCFzt6NF/hvMmJfW42h03+8L7tqq5MpFFZNmpo3fmjZBya+LC6B8u0dPswpsXNozLEz/ta0AP4Hj9rM2uOzHNjbPe8GK0ULTTVvUVWJxBwu7P1G2uoT08V8ohdip2yCtvqWRq+noM4Uuk5K+L+JN/uKBUDbPeMrrxKKEttgE2fLhtKA8kUX1C/fWPy+h1+uvP7Z9esVDtk27wbxnCTTVcZMYpIa19RqybOtWTZ02bdporrxatTJdm83UPfo3lBfgoLs6ndi2dAa6VtL/k4GfzJgf005RJvgxbb2+yNKCKl2AmNT2/PlzBHlWmTJlDK6LvUNhlA55wUkJpWtCwx6Q1zNdcaw8E8vg53aNgulnhuvtXwy7UEJRmh7+xuAYox6Hc3q8L0+C4lBk9YSoa7DvvFkp+qKjCo2zcL5ljNnnpe4mON7W+OqR8bDrPhwPhbtykNhJcMomoUIV2H7YjrkBFcziDPpr7AM2z14AkuSHqPGjAnJXgYVCYtMEE2DopzYUSDyBq4uE3t9Am/YqrK3NQJLAgjkqcuVU0aGbtudnwVw1K5YoeflokRAD0TtAS4cOjHynG4m+CHrB3s6baN3Pkc7j8n1s48jaEOb2EEnoyZsosQjGwm4lylYixscRy7sLUDyyAzfts2kbOpwxf/hSvlE2Aja8YscvLwmVVSWixVpwSI7fybqgPBEGwI/3eQsGvk7StbsXEMrmb8/h5SWhxdIYaugAP8tUIJu/gD59hMcKGjdurMn0EldfX4Jlgp8vYZeT55gJfr6s/TZrtvrAj1AMFgRaIjPEkOXO7UVo6E+AiD3wB8dD4BgLRcpDk15QpJLOwOI8Yz05mfMm+VPdSJkyCZEG39C1LPU2dDe6WujVF2yuuxmcs0OenNC8HdRpahLhYc0mtpxooTtLzpiBVFsPp/UT8RrTBO8SYM9D+OaGK+7uKkpVktF0SC7yeRqPJn8b8IC9S5eCpLFRfaYplL8GzDOD5HLt9wz1CaB4HTd2TLjJE/8XVKwEw0cnUrCwaQHQQwaoGDAYPEsn15s7S43veUfilTIu7xKq7fqj6qXWnRiVkMSSnNIe+z3Ff8AuStpE0nNvWdzyJMfWnD0QzuTWeVDI+ydVsbiL1HY5ylbnwSaJuMoyeB6KJ87gmgQ2Ppjd86Z0HHabE5sieOPagnfN/0h7LSvkChaUI6KoflX4ypekfPeiNaFPYlnY5CRbAl345btwfNbEUE7HEn6DBVOuXPtIXVGrVi1+++03vLy8zNv7z6yWAD9d1CszNOr1kj6fzPMjGJ2FJz7TjFuBTPBj3Dp90aX0gZ+QkBDE1VfFiilp1tIu1ddf92L//upA8rVAUqnLYL8LnAQZTxFo2hc8a4E06Q09x4hiBBUIJm8GwI/I+JpUsw5ecw3rGaUe9Zoi64i+J2j9FWC5EovsgVi5W5NYuTaqVt2giAFZ99AQWvfNw46GSRw/5liVv+Fwa3AyPUM8TXeyE14k/HEazh7FY/NossofU72lE/X75sTZIylGRZ/N6fgQ381rQFLTnGlA4dow28/0uu/BT/lWybFK1w695OCMW9iqYzXeoK87GOcNat9CwYYdFlhaJj3xZ01TE3Ddif6bajGjZgB3T/kaHJ+tXT/6Pq2CnUvyQXxw8AFnhu3jxrAw6i20ZvptbTqBW2feMbGFDVFvvgfJfaS2f6BsdQ5kyarslnd+QvHMA7L5JPevTkRypyyyek2IazA7Kf1ej6ULfq5Z8s3NZvxUx5efV9lT2NOa7zu9YcKWWN6L2Wu13MbCir2hYR//Jr7Xmzdv5quvkkkSTd/Iz6eGAD8d1BmT8tgs8flk4OfzWel/x0gzwc+/Yx/+1aPQB37ElZfI+KpSpYrB8WsyvnxE/EwPA+XuYZFlI9JsL1C550VZrzcFto7iVP4HH3lLzFmkefdg79DOeH5jGKClbntbna289hOZPyljZcTV325k2bagdn6LpFAhEtr2RF29vjYZ4vG9jF7VhjlVzSfna78bJlaCMkZIixlaF3HtZ3O6ForfUgAQlQrJjiXk8p2Ha5Z3NPRxo1p7d2xs06bD/9j4IWcPbQGJfm0rg/tSvD5MP2r61ukAPx8aiY2Ss3PCTR77v6BCRRgxxrA3qEUDBXuOJIGIaT+qOHcvG30FiSUwsbw/Ty8ZBme2tjNptlVOoaZJkvcPdt3k0tj9XBsWjcjaLz/HhgXB2uvzLDiO7xvG8OZJX6S2S1C2OgMybd4ey9uzULzIDS7JXklZyPckvPwT9aI36a6Z84JyhOvx/CjVUPGGFdKSWeneV0WjtkmBc6PahjB/ZxxuqTw/Ipmzsa09x1+81JQTcUalSpXi2LFjBrM50x3kZ1RAgJ+26nUZGvE2SbdM8JOhFfzfVc4EP/+7tf5sexLq7Epl2ge5UAi+detWum7x6OhoPDxaoVSKqy9j7AWWdhvIYuVLCVk01V2UNM6qpooz2JtIfdPrpg1hv/uQp37Sg8tY8x2wm1tLRZCv/lgQuIulbDlStxvg7oS6QQvkzTrCtlX8eetHepUytre05Ub7gXcOaKWfQsmoxp9HQ6FHrUmYsUN3+Xdvka0Zj8f1LeTNr6bZ4ByUruP8MT5oVLXH3AjcAxL9Qe16B6KOgzJt4cf9Ro1Vq5AB8JOy3PUjrzgw/Ra2qhh69VPTtpM6TWxQo5oKDp205Mdxaq4+z0av1cILCYkJSsaXOUtIsGHhXanFDqpMPECNybW5u+kK92Yd5sK3MRqnzMVHMCwoCxMPantH3oYmMrjifcLeZEHZMghs3dOsgdWt6SS+LAQuSaSDJDzA5lFzUFqT8LP+66wPDTkvKEt40Ss61zZcDmUDocWIrAyZmswSOqTJa1YfjkeWCvw8V8OA7Lk4eOuWpj0BfgR/l5CwMSRfY/rG/ntrZIKff+/e/H+MLBP8/H+s6n+sTX3gR9wvix9Hb++kt2hDljVrVeLjTePQsHUfTtyYzfD8OvanV5LjRQAuyncUsVPQzFlBzazJbLb6+q55Mxu5dvbGxfO9eGR6A33/+dXF/pwdUQZ5orEcJ0L3agNS9wNIlfdp4BTOqIoqquUEazP4BdfdhBdRMMY0h1Wa2fk/h8aSfsSMNCKL5UkwWf8aTrbXQZSuIqPJkFzM7hDGw+tHQaKfc0Y/+AmG6lNhhBlv00aCnw99x71LZOfEGzw58ZCKXhYMHQ6FilhoHuJ1vZRUq2nBrTB3fFYmx6+8vBPF3EZvCH+8IZ1TcZnizWdQrG0eni3y5ezgGI3HR9gSX7hergBthmlTCdwKiuLHdg+J9A4GO91nz+rmFBJflQCXDgJtYP2wFvK37bCxXkXC3DNgaZhd3PnnsoQXSwt+ohXwzS04b2XFrvva8ikDG7xim592LFqMGjpIIEu1SmzbmwQExboJ0COSGoSEzZdgAvy0Vqd3FgyvxE5J50zPz2dyWDLBz2eyUZ9ymPrAjxA9PHfuHCIwMj3Ll8+b16+nAcaT7cncRhL//UZwS0Vd+/wGVgEryXVnJ46xr8llmUgDFwX1nNQaNuiUGpjFbmTH+9xgZM6mBQ49873L0eaxxMbOSG9qaT63lvanifIAr6ytibKT4GYPTQtBh6IJFDDyOXI3Aib7w99NTO5eq8LGO9A730Tiek01raGgQ2Tf8j1vzoWApDYqRTPUSnG9WSjdLL2PHamPQZPd0PcX0/oWpU0EPyk7uHHsFUdnX8VaEcvX7SUsniunaMM8dF+qzdJ8Zf9Lfv06N8qE9LSrwrBxaEeFEhGcGhD7EfiIPjsth5abKuKWOznY+dy+MJb8EM6bdx7I6+r2zIi6FlcnogorC85tsXr7F5Ln65AnDENmPYP4afu0Mrt0LaDzz18RXkwoeiWbXzgMvS8lonBOxo+Pp3Yz7XM/oO4rtp9KBj/RauhiCaWrQ5Zyw5n4Y9JaiOxOZ2dnDY+XlbkSL6bv+ietIcBPC/XmDI1hj6RDJvjJ0Ar+7ypngp//3Vp/tj3pAz/ihzEgIIC6dQ1dDSVNu0uX/mzfXkEkgRu9DrZuo4kbvRY80rn7iYmEwL9xPbcax5A7uEpUVHFS0dojlh6hOWh5Z6TJwpqCA2hDHj/iYk0PgLSUfEc/9XYKv5+pXCisA8H2MqQyBSVdFHT1hDp5wU7Py72I1Wm8GQ4n6VyabfMvwNgav5PYaoB5bXSuDg9FqvNdpLJHIK6yyILEohBKeV3USgEoBCDSkT6kXgudHkP7Cab3nQHw86Gz+OhENgy9wMNzoUy9ljbgfd/cYLaMESl1hhY5BGvZeCxt7xDz86s086g5X8LEa0nXaMIOLH3Bhj8seDXkBrKfahBfXX+av+WlH1C89QKHWkiCvVAnzNTIYchs5hI/bjW4Gva2Of9chvBi1zT9xilh2F047exOueOjOdF4IQf8LdKo2H9T6yU7TosTCe/eA5/RA+FJBFD+F40auDDxYpMvXz7Nv0Lq4kswAX6aqLdlaKoHJG0/OfgR3rqJEydy4cKFNNlfDx48yND8/kuVM8HPf2k3/5/mIuJ9BABKbeJvvr6+NGjQIN2ed+7cSefOh1GrjSfLk7l+T/yolZCjWLrtaxUQ8UnXDmIXsBb7lwdxqeWJ19wG2GU3TSTsryybiIs2/cfQgh/ow9/o470WIaVnpRBqB672UD8ftC0BJVy0nSq1/oYTHU2beurSw09ZsLDzTqjRwryGeteHm4LgL7XO1H0gEEvZQ9RqceUnAFFBlIn1UCsEIBLQbx4McIYG/Uzv+x8AP6LTsKex/Nn/PKMPpM1WW9rzAoFrBKOvLmFeBTY2f6C2P4y87yCaBk5gX29t0ciERKj+i5RZ1700D7xVYx9xNCA/b/qc1FA3yH7yJr6Kv965214dTVxEbYhcD+FifatpykosfkU9Zi7kSZ0dqd3UB89PYAQMCJbiMv1rCg2oRcyzCK53XcCWE2m9rP28X7LrjJwoNXS2hLGDoWUlGLNeQs3+uz96cYUieIUKFTQ8XgIUfAkm5tlQvStDUz0safXJwU+dOnU0gtOCodveXpvW4kshrDRmEzPBjzGr9IWX0Qd+hGv88OHDNGrUKN0fyPj4eLJla4JSOdfo1ZRlG0v8iN8htxnBtu97KT7TlXmDwhi0PDsOlYtQ5af62LoaRxm92nkNMZF7jR5vcsGp9GY5xoxaQErB0XvPFpQyKJgV2peARgWSPD9BXczoPkWVDn4ObBl4AMqmH5elqyfLkV+jCBAsxekotGoqi7fKD4AoBmViBIhMwB5zwF0XwDAwt38I/ESHJbCghT8TT9dL09nsugHc9hUxLtqeDQuLs0htZqDq0ALliJ+w2rqYWcFDGJmK6ujCIxh7KQsjtpVhdre7XIluQGSH5Pgm2fw6xFfQn0Zve2UEca/c4M0WSExx9SZbDQOHQWHDe5Z1fhl8pNc4ZJ2N8n6jkb0/18ELjlJNcgKfYWnBft9qL1h3NlEDfCYOgabvHbFdf7Pgx5W3yJEjh2adHj9+rPleP3v2LN3vdsZO6L+n9n8F/AimZwFera0N01j8e1b+04wkE/x8mnX/rHrVB37EJA4dOqRhgJVK04/qdXauSlyc8UHPMpfxxA//FfIaZpA2tJjFZ7px6+9QTZFtx2HY6uxkrVmIyjMapxsHtNZ1Oe/CjpixV3Ppzq9pWI2MaUiwrJyxSPIKRVhK6FpITZfi4JnN+FCblP3UPObKqfEnoIB58hYWE7ujOiLW34zUNbtFUK8M3BYaaSqo1h7qdgcHA4KyHwb/D4EfeZyC2Q38meSvLTMhuplY9iRPr5xMsVzh2MgmQYEYEn7fCc5Jqen2kztxpsImPFPJoy32haul8nHpaBRXXIaT2EQImSabzeJmJBTdoGFz1mW2l4chv7kNZcJsbZJF2Ubo1RVKNdV/ZF7dxnJ5M7xGeFJ0tLbo6vF689m2V4FtatVSoGflF0iuJjJlGDRK4VhqOkfKBt+wj1dct2/f1uh63b1715hj+58oI8BPPbU5LzvJ0z8maf7JPT+ClFLQi4hry0zTvwKZ4CfzdKS7AsLDI7h+dNnRo0epWbOmUW8ZBQrU4OVLwZ1jXNSvjfMkEobNhfzl0x2jvgIpwc+HMqv3wfidHrg1Kk3FsXWwdkwOVk3Zzt+5/uDti4OAqW9Qv9KJeVQiY7pUS3LYU2ry/7F3HlBNn98b/ySEsEFFxYFbxL0H7r333ta9W/pNWgQAACAASURBVEdb69a6R7Vu66jVuvfee6CouHEPRHGAirIEQkj+501kBBJIwr8/F/ecnnrIO+/7hTzf+977PBXxX30DtV8Q7vYquhRUUysHWBtZ8u+2PyuP5l2BjNo3epNt5kDYKSqGjM/Vip3DIv0cYobPgLxlQamA/XPg0i4t+KnXG8o3A0sDvv1/Aj/iOmqix0l+v6ibl6ZSqRlZ5AKB905ogZnkH6S2u1DN+hOq6GaZO/T1IKR/0tydtsvAO8yeZzWWoSqXNERns7YnEbaDwVn/82txujWqpx9Rq3S1vbDaAZ0aQFkDd57nVyC78CfWtuG0v6WrCB8dFoVn7ensu5iUxfvRHQWDmrzj7w4K6iR6n6g73ZId5+IJDq9evarR9bp5Uzeh2uTn5yvqIMBPDfXBVK34lKThZwc/s2bNYt26dZrzc3Fx0dlPs2ZJmcpTteGvuHMa+PmKD+9/tfTkwI/I+RFvGtbW+gFEwjX26DGIjRtFBCJ5UsTYPnKniSiGToO8ZhLsAe7TMnHvU+Qnsb+WbJcwZXdGsjYrR5mxVbC006VT3lliFa9uCrp7UxXRl9OKqVQWX6qpsL+y2dP6elfsMmkrdgLvvOPa9AuEnPYlkySaZnnUtMkP2ZK5xct+MAcvVzwAq5TPR+9Sl4yGf0VUT5uPYopJ0k1BPeZvyJYo+yk4ELb9Do8vQlY3aPojuFfUDW39P4EfsV4BfiZ61dRZ+vuXEUyp9oR3jycjsZ2Mul5FmLBQr8xKhq4FeTfsvk5//yCoOVvGoz5nIL9++QfrfeOIfFMM8iTVKbF6soToG1NRfRgKibPD5PuhbTmopCt7gSICtvbDLtM78m0bxWOPXnTw/klnXX7bruBybidj58W/YCgUahaO/sDhPY6EBlnwfpFfkmOsMdWavecD435+7tw5Jk2axIULImr3fZgAP1XUR1K12XOSep8d/OTJoz9RXuwvLeE5/njTwE+qHvXvo3Ny4OfMmTOaxMjEiXX6PHPgwAFatRKlpEkV1vW1lztMRjF0gsEvF2O8nxz4ie0/Z4OMPw5lIke7cpT6rRIya20J1tHmG3m4R1QqmRr1+JemjKcG5jM8i/n/ymZHq2vdsM+ctEw/KkzB5SXXCdh8A6v34VTMrKJTbjVlXECaID810+G8vF0tkpPNtH9nIlkWgDom5aT2xDNIMk5APX4HOLsantzvJmybBEF+ULAyNB4E2dxSVeqeeLLfK59kgqcu+Ll/9g1zm9wiOpM7qqWbwcUAwA35QM7+xfD7xT9u2OfvoOE8OQ+C8hC99J7BvcnOLUd57QMU043OWL7ai6X/eKw9chO0UlzHadXb40x2BFrkh5pD4n8W+BDWdcF1VH0y9mqE8l0wz1uPoM2pT9phn1oeb7aEVYuCyZpTGxq8fj6SSQNCeaIYTVSWkWS5m5dX854lWXOlSXYcvqhldxYmcvmErteJEyIy9n3YtwJ+vo/TSv0u08BP6n34zY+QHPgRpe7FihVDJNmlZIIROkvWsiApCiqhki1Sgg1Xksjtp6L4aRS4V01paIOfGwN+RGdRWj5ljSVLTmagQM8yFP6xOpcnHuXa9FaoMbVSagsNGEHdVIKfhdnsaX+1C/YuKQuRPjzsy72FF4m+G0gemxg65lFRPwfkPluQoJVa1l6zbMdfWMy/QYweYc8Ux0s/GmaeBDutkGeK5r0HDswHZThI1AycakH5djlS7JZSg8lVTzHubHzOj7gKm9PYE5/QYrBYXGsmY9fP02RZA/b20QpGxgKf2/4nsXYcTOTCq4Y73zyE5PBe1OUWx7WRBl1GfuMHMtzfRmTfkQStEVdsicCh9BQ0doYGo7X9vNcj9ZxNgQNjsc6nbRt534+gX+fSdE+8ZIwqRsXhyjM47mVJeJiKSQM/cP5cdt5mOwvyjKB4g/uLktyb/lJnzcoYqDw1HccuxoOi3bt3a/JG9u1LXQ5MSmfzJX0uwE9FderA3gVJrc8e+fmSfPolryUN/HzJp/OFrE18WSgUWm6QxObl5YW7u7uGEC0lE4SI1TpvQp21LzyYACFPQF0GVIKDRfduWoxlYT2DmKE/Q6GkyaopzRX7eYGpmbi/QZvwbIwJEDRupQVrL6fHJn9WHm6vh1olriZMsb3U4UcaphL8LMjmTPsrbXHIkjL4Sbi6937BXJl7iQ9HHnI3PBO07IOieifInijCYMyWjmzCYtpBYiI7GNNat43zKPjTO06o1ugBBK3CnGZkifbCPpMdHh1dqdghC3bpTM290s44tcZpxpyKJ+I8tvQJnptf4Z+lLtGj/0l2WfL1c/nj5c/8WBuevYO6s+U8CBAVXAWxcqxF1MJkZCh8vbHaPJ0oj090CaG+WF1oRIYb/2LhnJ7wjj/yfpPgGEosfXEe6kmh0TjYOgDbdC/Jv2eCDt9O2LkbRK9YR5018ecScP4JYYv+pV0XC2b/Fokf81Fl+iF+f+F38AitzoXxur8PAR+g06qc7DruE9d248aNGl2vzZs3G31sX3tDAX7Kq0+nahuXJNU/C/gRUfVGjbQJ8nv27DG4h7Scn3jXpIGfVD3q30fn5MCPADTijjljRl3RRn2eWbt2LX1mB0POn7UfC6TxeiP4LkQSFYFM2oBopbhesdF+bjkbhg2GIoJkzzwzFfzEziKW1macBftPZEVOBmJi8hChElwxInlV3KknV912jOqS3jRTp+7aa0H2jLS/3BqHrMaV5uvz0D81NlKoUzGubnxOcLAcVb6SRNbpCUUrJqsYHjfWhUPIRq9CGaElvzPJMo2GeaKQ3wy7uI0aDn9Sc3RJzsy6xoP9ftg6yajS1ZXybbJgZYLI27RaZxh9Qsvz8/pBKIu7eNN4QU3WzIwm4vcdyS7ObmQbblTfjswCGs2Rc+e1+HLU6sRJbGugXppMQvBbP6z/6k5klZMQ+Rb5qZqkPz0XSzdtTkZYmwF82C4iN4kjY5eh9EMI8SXbz7XI3D9pkuqHnaew9zpBhZnN449q0CZUF68QGFaaoMxHQJbouvT9Kdo6NGXLwDCdPd96BhNOlGXN1viox8qVKzXJzv/8kzw4NONkv9guAvyUURvmZTJm4VckVYwGP4KMcNCgQZw9e1ZDJyDIYsVVY6ZMpqsZCxFaHx8teE3L+THmpERwWXyzpVmaB5LxQHLgR7CIurq6Jqkq0DfcmDHjmXOkHLjoYdRVhiF9OglZwF6UURlRqdoisTyNekhfKKZbymvKYZkLfsQcCzeBhQMM7APXfWD7ASn7TmfG97kdUVFOKFU5iFFUQh1d6hOpXyxdsyeVJJ1pnUrwszBbRtpebo1jchnNKTjj33pb6HwkvhLpmac/5xf78OS6AmWmPKhqd4SKjcHRQOTu9iXo9zsojcvT0llOlvEwR3Bbm2Ev7lLiZkc6rI3P1fn4PpJT067ge8Ifp8xyavTKQcmmLlhaJU+zMKPOWUYeq4pSEcPU6mdova4x0RFKVo14TeiM5KkMHHpW4FaHS0mAD0Rj5ViPqIWG5SuI+oj19KpEVjmL/GQNHDcMx7pqvFhbaLPeBO8dACQCKZJTYL+BglcWYO2m/9ovcMlOcql8KTxYG9FShEayp9wfBFv9A86JCIli3f9mE6Pzd2RqoiKy8VvhQkhlduyIr3RauHChhuNnyZIlZhze19nlfw1+WrQQV/9oKrPE39hYUkIRdUuz/94DaeDnv/fxVz9DcuDn+vXrZM6c2Sjl5+Zt+nD4dX9Il0LlUPh9ZE9HEfPWE2mRkqhqDUbtXhOsTY+AFJiagfsbBHe/6TZ4BjRpCQ10c2XjBnrkC9v3w65TLtx/ZEdEpBPKmCwoP7pQXL2GzqgxsiJd7+IWZ7Wn9eVOOGY3Xg8t8UBrG2yl06FPquGJPgwNCOf8/BvcPBZCpNoBVdm6qGu0g1zu8ZVXzx9D98EQrltVZJQ3s00EIdBpjimV5F1XjD5H9H+Rh7wM48TUK7zwekUGV1tq9XOlaN3MyCyTSjHMrH+W3w5XZe3QG1jndqHK0NIE+QazvM89gueeT3Z19m3dyRHylLuvBR9QQqLHYKyd2xE5N3lwJx1TEqnUGcfpTbDtpJs7FtLgB0IOi2TohGsOAIupWJXKRaHLgv9Hv70Ys4KSFeXkbKLlXzrVdS2+hwNRFTUsX2ARMJu/Ko+gd4Kq/7G7ZazzcaBu1dbMnTk3bjJRLi2ISWfPNp6U1Jxj/pL6CPBTUp266rbrEi3btzFWvHhxRo4cqeFTErZ+/XqmT58eF8ExZgxDbUSV3qlTpzRkhwnXM3du/BmnZvxvoW8a+PkWTvF/sAeh46XPbt26pcn3EdGflKyER0vu2y0BGyPZfl/8g0XZs5ovB4tr11Aq5aiylYcKrSCfB1jqlqbrm99tqhMPNujKEqS0ztjPWw2DSb9DUUM6FXoG8n8F63fA7EUWOFjLkIQqsVeoyRejIp9am9mUMh2kduAVrnY0Od8JpxwpJ5Mb2tP6JtvpsC9ljYwYpYpbG+9yfu1Lgt5IiclZBHWdzuBWAlq3g4+/Geu2+HY5JsOM5MFFcoO6LnVn0NlkiP4+dX73JJgTk7wJvPkGl7yW1BmcD/dqmZB+Knub3fAcjX4twM7pj+l1tLWmV1jgRxa3ucSHRclcy/new6JfHWICRM5OYobrl9hk60/E9GSuSZTRMLYYTgOb4DA2qbZacL1uhB4dlcAFESCbAMr5WGQdSbGXhqMufr2mU2tECdK5u/DqzGNODj6HItKGGFfDOSty/yEcbL+AWkU0IvL8tEmGp10BsnUoR96TjkydFC/i+/vvv2Nvb8/EiYKX6/swAX6Kqi+larM+kvJGg5/Vq1cjEsvF/wVA6dKlC0WKFGHmzJmpWoO4Ovv11181DN0HDx6kYcOGmuo9IW2xYcOGVI39LXVOAz/f0mn+h3sxBH7u3LmjKXM3hk00u1tN3uU/ITKZjVvpx8fIs49CMW+ttr1IxDl7EtZvgLsPwdIe8leFck0hV0mQJoUVblMz8cCEhOeEC6vWE3ZvgvRGFisl7Fu0jQMrPbWCrAHPFBzf+p6Lu8N57fMRiwgVTtGQP0ZNXtSIG3590pGrXG1p4NmZdDnNAz+Kjwp2dDlA2x2mq6O+uh7A6fl3eXItAsXtd6DqCyqR72QsdBOSWdNhakIGZeOOPbaVy7wCDL3U2KROr3zecHr6Zd4/ek+OYk7U7puL7RPvEvw6kl5nOmBtr02aVoRHM6/2cd4v118JJ719CcmYLsiCXYkK2qZnDQ+xzjOWyIkGrs1e3kW+qguqsPdkeamfO+ZtjS5Enh7zaWwVyGaAUuQANUWSoRUl3i0wuPfHTUfQantrUKnZ5bGQ4OaXsVjfnJic4mVBv8kft8H3t+1kSQc9Vlty36045Re35+GWGxS/kp2xY+MFaEeMGEHu3Ln57TczQK9JJ/blNBbgp5A6meo9I5Z6V6JLaDlhwgSDAFKwZ3fv3j2OS8nDw0PDmO/gYH6kVyzRzc0NkbNVvXp1zYvp+/fvNVV727dv/65yuFI6rjTwk5KH0j7XflkoFHrfaO7fv4+lpSV586ZcSZQxd03CipoWCZBHVkex2QDxmKgK2r8TNu+AZ/5gnQGK1oHSTbRiqBIJqQE/FbqC1zHzZCVKtbVjxp48OGXQf/H1/GEkxza/x3tXKG8eRWEZoSJDjJqCKsihBmfgHwF+znUmXS7zwI+o+jry61nabNHmFphjYYHh/FH/Echd4M5liHGDCAFIUo70kW86TDIf/GSYWYBfb5gGfhLu8dnFV5yZcRn/S69ovqI2hRoJsVWtCYbnORX2EfT3oyRukZ3dh8XiEcjH9ies+03U0bP0uO4GVkXmEzVil+5nKhVWh6fA5Z1EtdyFzb7mON/VB54gpE5nQo7HAg6RWJxBUDJqxpPYtqNEuOErikf1htL+SFc8h+3hvl9D1BWGYrGiCjE5DUeirO7XJnTmCTost+R1ZQ/KTNdew91bdxWPB26aaEGsCXbgsmXLMniwGble5jxoX0AfAX4KqJPJ4TJijQ8kJYyK/Aj6EPE3s127dnHgSETZBLnk+fOm/Y1MvCxBOxISoo12Z8iQQSNOK0wUpcT+24itfPNN0sDPN3/E/z8bNAR+Hj16pPllF28bKVm6nPWJLH4qpWY6n8uDyqPYa/htVqdxWBhsWw+7DsDbt+DgSr7gw1xdE4mj6elCVO0FZ81ku+89Wkbhdjmp1NB44PLo5kdObP7AtT0hhD5X8NbSlsojSlFuSBlkchMiLp+c8sL7NVf+uknjlSlfHRk6lBfer1g52g51m09XMD4HYccUeP0BYoRYqEi4TUrCqBmvwJ8wwXzGXKcZRRnuVQO5bWwiuUmPTlzjFbW30+e49roroc2psIe3K3QJIOW7V2KxcxF257egWrGBoJ9ElFKXSFA7xnksy28metCnqKT40bvnyP/uiDpTGaLrztfcLVmvLU7Gezv1LjykVidCTo5DKj2FSiVyozbFt7PoQdEPo5DZ6/fto5qDqTOvHoe7HSGik7emX0rgx/peZWrkuExE61oUHxEv9Hr770vUCSytA3R69+6tuTbp2bOneU7/Cnv9L8GPyMURVV3Pnz+PSxkQ/86ZMydv3rwxqnrWkIsLFCigyffJli2bhoD2jz/+0Mwl1N7F2Gmm9UAa+El7EozygCHw4+vri7gSK1gw5cQYh5xNiS5u2peh3L8UiiOeYIRwapKNvA3EtbE7GW1V5MwKo3tEUb6I8ZGcOgPg2G6j3JOk0dHTsPJKNobNTszhYvx43coG4etfhYwZTlKifW7KDS+LlYPxXDcPj/hy/8ALGs4znyfp3u4HbF5dFHXDSboLV0TC/hlwegdEpge1AFjFEpBWqqDQYhh7wPgNJ2ppP78G/TfkwTmfGfeOCcZaVmsH/U60Sgp+yu7k7aqncT+XLvsdm9tHsDmxXsOpoxw6gaD5osw8niMofpBjSGqdRf3DQg3IsfRcjuToQhSN1kJ2Uf2nuVvDdmcVMtzYqh/81OxIyKkuSKULUKmEunyCKKFkGvmOFsKhtn5pl4eV+iBXRvG+9glIp43CWSyvTEwuT/3+VoYivV6eWn8UpFBf3YKDm4vP0yK6Or16xctpiCRckYPSvn3K+WJmH/AX1lGAn3zqeK4jc5b3WFLUqMiPGFu8MLZp0wZxNSZMRH5E0rMAQamxP//8U3Nl2bJlS8144mpN2JgxY76rHK6UfJgGflLyUNrnGg8IYVMRqk1sfn5+hIWFaRL1kjMBntK7dSGmmGloQv6iFop/lkIOI5OkEy0iX50cPFr7Bp9HMGKBnNfvlLSqJWNQWwXpkwnKREZC29GwN8HLuCmPgnBVuR+cWHxMv86OMWMNqBPMdb9dYFUUSfB8MljPpWBdZ6pMqGgU6/OtzfcIuBtBzYnma6NdXnaN/WebQLUfDS854AGsHw2P74JSKGYK1mIrKLkdfhVyJuaZfGVnekyKJncVU7XVdOdbUnUrA8+2TbKI+ZV28/ovQbSphmkDkMe8JN22RXHtIlv0IWS3yLtJyrsiZTuq5v5Q7ycky7ogt3IiqtkGXW2wkFfYn25Jugvr9DrgQ7X2RHkFER0tEqoTg+RtuEy9T9bRCUgKE4xyt0BbonN3QVV7etxPLZZXIiaXniuTSH+k91sgs/pAv5f9kqzl2twzdLZtrCm1jjVRhj1kyBC+J1I8AX5yqVPBhg74SQoZDX5EvuSwYcPw9vbW/G0tVaoUc+bM0fzfXBPj3Lt3TwOsRDqCMAGmxN/oQoUKmTvsN9kvDfx8k8f6/78pQ+BHcIEEBQUhyjaTsxs3blCxzWpU7qbxhlg87UvM5BZQLT5Mb8ruYsFPbB8BSuZtgA2HILcL/NQJqpZOGg3yvgOr9sOSP02ZTbdt4Rb2/O2VT0NgZo4NbfaBi3e2gG0C8BK8nXSyEeQobUnt6ZVxzm+YWfvi0usoIi2pNKyEOdNr+pyceI7TLwZBOf3l8kkGvrQJdsyDDyGQPxP0Xwku+Y0PtyUccNt4OrS7QokOWlJBc0xcyS722MLgi0kjGIuq7+XF3LtIx3VG7uaI4/zxOlOEV2tP+Nn9eqe1lK4kptwVLF7cJrrOn+CmR/vszX0cb/fD8cjKJGOowsJ5U7Y10fcFeNEnjOqNQ8O/yXcgNiE6fohw73v4txlFxIB4LS7NpwsqgHsiaoEwb6SPeqLKO56s6WbR5lhSEOg97SR9s7Wjdev4q0Fx5TV58mRq1zbv986cs/rcfcTvqav6YaqW4S9xMxr8pGqiZDqLApTQ0FAdRvD/aq6vedw08PM1n97/cO2GwM+rV68ICAigZMmSya5GlFj2nBYAuUeatmr/5Vh2fEd07+Gm9fvUOm/tHDxep/+e+6EfjFsMvi+hWTXo1w4yfrph+WcPBCngZzPobWIXWqO7LQMX5iRnASOr2xLtcFSHd5y6vAHsqiTde7gnjup+ZMr3kbozKpNdKJomstPTL2KXJT2lehQ2y3ei066+x7luOxUK1zNtjFd3YGJbcMwFtkHglA4KVYDSjSFXKZAZkcdzbh21My+lzsTyps2doHXE+0jWtNxH/1NJK96W1NiDvzIvts09sPu1T5I5gsu2IuqKvmvaGCwkXZFkfYGyz2WQGzhf/8s4Bk7Ecdt8nbFVwaEEN+hO1JVAlNGGeIICkeceTGFf3aRnxYtA/Ov8hL0impd9X+iMK/urIso88Tw10vfb4PlUVGWOInm3n3JNN1BhQlK29IsTjzK8UK84eQQxaLVq1Vi6dCmiAul7sW8F/FSoUEFz3ZU/f3yC//dyhqbsMw38mOKt77itIfATGBioCauKxLrkbNSoMfx5pDRkjWcbNsqdYXexyj2ZqDnm0ewnB35i5xfRoBU7YOUuNGXAP3WGI15QqRa0FDc4ZtqU+RDunovmPVLWPdM3xaSebzh4ag3YJ/P2HfkQ28hupM/+glrjyuHWMHdcpOnwb2fIXtGVQi3Mj5ysbX2MxwUWQ54KpnlBqYDBbUAdqzMUCWwD231g+xQcbCBXMShbHwpU1i9+6nuVUg/60m6N+cK2gfeCODjqPD/sFPpx8RYVqmBJhU1EjJ+ETQf9wrXhRZsSflvoeCW0UGSSrqgsVKgadgKPgYb98vg4DtIVOK2YEtdGFfSB4PrdCfdugLXVASKjDOXAqZE6NqV48F9xfWPCI/CtOpCjY+/R9jdX/Hvr5obI/vJAmcdL0176Yiqqt4eh4gmQypA96EOrdTa4lE3KGH1+5EHGVxqqSYiNNfH7vG3bthQjuqY9FF92awF+sqoNk0Qas/pXkryfPfIzbdo0hJTQwIEDyZEjh04E6Hu6xkzpvNLAT0oeSvtc4wGlUklMTFKtKlE6+fjxY8qXT/7tvFmLRpy76geWmVE5VCbSviU4lgVpCgm8KhXy6JooNpmWKB17bHlq5+TJukCjT/HZaxg9D05eB/d80LA6lCkLRdwhc0bTbm98/aDPH05M2WZe3s/sHwPYsXclOBpRraV8i3VEHxydLlN5SDFKdC3E3kGnKNTajfz1zJtfOG1p3RMEVF0LWdyN9mFcwwENQGVINV3kj3mC5SZwuAF2EsjkCmUaQJEakDEnREeRb0NJeh8xH4E+Oe3P1XX3aLMiPuIhpC3+qbcd+9DXvNh6Etknra2EG1SrVIS7Nebjk4SVhv7IpF1QWv8OBEK1UKj6i2G/3N6Gfc7jpJuu1bKLCXynifh8vCauEOXILU+jiF5hsL/Eug0lIuZpPhfreVr/FxY3u0TL2jG4N8+Jf28/nb6ypRVQ5jmPhW9vkCqJKRpfiSa9VIUBL5vqvQo5N2wvsxqPR0QMNHOp1ZocvpMnT35X0QMBfjKrdX1q6kMfKMn12cFPmraXcaeWBn6M89N338oQ+Pnw4QN3796lYkV9eQvxbuvbvyP1e5yjdCVLju+OZNtaS25dtydC6YzKrjyR9q3BqQJYfBI1TeBxSUB51IeMLHdPdFK5a+fA18C1V3KH+vcuuL8NCqUHzyB4HA0RFmBrD1lcoFzpT6CoADgLehYDVraFNYsuplwJp6/74pEvWLdxGTi1NP75U0ViGTYUJ7u9yCyV1J5RHbcGKXMwGZrgz4rHCG69HxyTXquluKiB1SDGFJ6fpyD5FxzPgW0opHMms8ybHvsam030eGPTfd7cC6LORO3zKfS91jTYwcjOL4kKVzMiejR2PydNAlYFvuVjuX58fHZY00/KRSykw4m22wGyQkgV61B5PIFaunlCCX0iu7oE20r+OA7vSczLAIIb9OTjLSEQWwCZ7BBKpfBp0rnjxpB1pmS0lu3Xv/ccfrA5yB/DwwkLh0KtcuHfK75STbSxWFwWFOlRZayOOm88YaH4zPpGKfr46Y+6nh64iyWdZ8VFeQT4ERw0QigzS5YsKR7zt9JAgB/nGP9UbeedhetnBz+p2sB31DkN/HxHh52arRoCPyKxTiQzV6miJy8lwYS9+rahad+LlKmsK0khqhPOHI5i0woJN687Eq7IgMq2FJH2rcCpCsjskTwvi/rYWd1KGiM3k7t2FnzXfTCydXwzUe3VtA0c1ZPH6hcGh1/ChQ9aUBQt04Ki7FmhfFkQxRoiUpTOCUo3tGTuhUJY2+jjcE5+WasmvWblqlmoHbuavH7Bhm3/PieZs4UTrZYhs7cjU7Hs5KmdlezlXHDIZm9UIvas4gf52O8iWJqRtzSoCihTo5IdRk5XJ1xyWvMh2pbc1XJQtFcxMhdKBm0m8tTJqZdwymFP6W6FERIe65ruYkB9f/r1VXHtGrSfXZbIXaLaSteir98mst58It5sQC5di0S6iig78Qx+KhFU7ILSXtDAsP6W5dnfse9sj1XVsgQ36k3EHSFxoY3CWVsvIjJSkAoKegADJh1KoUcdCd7pRcEj/3B8qZasLjQMCrfOjX8v3/iOio9IFxRHlXsmZE3EaaR4h5N/Tbr56H+OjvfY8gkuhQAAIABJREFUyrqflsVFeQT4EaDn9evXCMK878W+FfAjrrv0CdIKwspFi+KrGb+XczW0zzTw870/AUbu3xD4CQ8P15RqCir15Kx7r+a0GnyVUh7J63EJMOR9TsH6ZWouXEjPR0UGotRvYfofUKuByQDIrbYLD9YFG7lL3WblG4NnHdCjlal3vEchcPAFXA4BXyXEWMKTEAtqd8pAt9EuBtmeDS1uw5wAFi+cgMoxmehAMjvLqcrC6ZsqjcaVUqnC63Q0h/fE4H3NjpBwC2T21jgXzESe2tlwreCCU07HJIBoeuFDRA29bpb/pMMqoPpoprDppxlrVrLk4FGlRtlk5y5YvsqGlyE2ZCmVhWJ9ipO9rEuchpe+RR7od5SiPYviWi4LG1vvoV0ZP0YM11I2CIBboZ4T771vJukadfAkIc3PYKWSo7Z4RJTNYd1nL/ogFNoPLQx/mcgOD8GhWxZCp/+N8rGgCojPt7GSjydKITiQkgPFi3Ee+BinC2d5uPU10k9Ng0OgSLu8vOgZT9Bosb0LWQJ38qJ4eFI3vD1FgXxjqL82KdP3+wdv2Nf0H85sO6HhhhEmrrcFM7Cgp5DJUiPNa9Zj89k6CfDjFJWogs7E1QRbZf3skZ+EDM8Jl+/s7JzG8JzAIWngx8SH+3ttLv4gCgCU2ITys6Bjr1UrgVS0Hid17dGYDsNuUbyc8SR9scO0qh/Fw+h8RAcrUBUvg7prfyiYPK9QbF/32i7cMxP8tBsGQ2yhsvk8hXS7JGeDQxdclQfIkzeSTr9kpKiHnVFRlx1/veXPGcNROg4z67Er6ujM/nOGv7wE0Lx6QcnBXUouest4/9EGCztr0rs5k7dGdk2E6K/mV4kekrxyuaHFWY4oS3Swln3YPFNRr7qcPQeS5pqdPgPzF1nx8KUN6QtkpFjPYuSp6YqFpS4T9qamu2ixviF7+h2jfm5fJo7TfYYr1rDixaUHSZanXLSKDz/+jcy6FQob3WotTePoE0jd1qNq87fBrVnt7QovTxD1TFxB6V4byi1HoYgWxIbJ2Wqs0v/BB89grBME3t4HQ7H2CcDP3YOUevgDdtJQzqWPSDKg7NkUagy/RaFuZXU+u7vqIj5Lz+OU0Yq/fvuHokWLYmVlpeGEEdde4sVGkD2mxkShhOCyiRXUFFxCgoTvSwRVAvzYh6eOATnMLtNnAz979miLCzp27MimTZt01iHyMhcuXMiTJ6lL6E7Ns/Cl9U0DP1/aiXyh6zEEfsQfN0GlXreunvuhBHvp1K0+3X67S5HSpoOfn/oouNd1EnbVShN67CKvp21C8TYaddW68EM3cM1l0GsFartw30zwc+g8HF4Kf+p+Z5h0Qj28rVhdfj/krQ1v7pLpUh+c1bdo1MWeRj2csXMwLFtxaF0QU0b3JibdOJPm1DRWvKR2sSKs2mqavwUgunM9hoO7ovH0tsPnli3RRVpA3VHgkJTsL7mFyUaWRvn+SgLWZ1O38YbWjbOwfktScs2EI928BXPmWXL1ni0OOdJRpFsR3BrnxdJGxj81t5IunxPlbB4wZ2ZS8N68pQVXtt5A6qgrJhnapDsRRwqDvYHIjtITeZ7FKNobUMkO9IF/m8J7cdWVWPolGgvpOGJUJww4JAgQrL/3+K3fPWYk0hYN+gDFO+TnRc+H8PE91is9eHf+AR0Gy9kb/QrkuteClj5N6XapNLYZtRovirAoTvbago11DO3+qcOOHscY3XyyBvgIsc2bN29y4sQJTSGDhTnM6gl2JdiLhXK5UBcXJhTGW7VqxfjxhnOlTH1K/r/aC/BjEyx8b75FOGX4bOAnNtH52bNnGpmMWBMA1sXFhdGjR9OkiW7Vo/k7/fp7poGfr/8M/yc7MAR+xJfl0aNHqVevXrLRjA5datNz7EMKlTDty1hsbuKwMM7VnYBDo8pxexXzBm88TMCCwyijJdC4FbTvABmEJGi8pebaS1y11GoOp5JSoxjtcx3wE9srRons4jRcXy+iQBElXUZkxq1E0kTvUzs/MLp/e9QuhvNKDC7k3XJ++2UUA4el7tqifPV05BxYj+uTzxPtXAIaToQM8X9Yk3OE5bgKRAeK6IYZwmqagX3o1qEEy/9OHvwkXINQBpg9x4Iz3naQ3oE3z8JoWjWCvxYp9C51+hQJc4vNx6Zj87jPo89eIrTrEJSBY8DaQCm70hsr12lEddmRdNxAH+Tb2kH6HCh8hKxGYtDoj7XVFiKjEtOHi32KSJIYcyoSiRc7lk6nRSKKpbdBUKKzGy97PED6byt2jd5J03rwy1RL5njthsy61XFWNzzo66fNAwq44s/pftuoNbIkxdtoKRC29zjKquEbNV+Y4gp7xYoV7N27F3t7ew1Y6devX4oFDYaeA1FqLSI9QsZB2NatW/nll18QzPBfmgnwI39n3hV57F4Uzk6fDfzErkGIpW7ZYj6z+pd2Lv/VetLAz3/l2W9sXAE2RJRHnx0+fFgT+UkuRN62Yw36T/KlQFEjyO0STTJ/YjC7Cv5Gug76ifZUCgVv520laOMpVDYOSNt2RSmylW3tcKudhftrPwiBd7Oscks4WAkcTcdsmvn0gp+EK3l5FZcrfclo+ZDmPR2p2zlDXHL0paOhDO3cGHUWPdcuKezGPrQVq9eepFwVMxf+aXyPmk5UOqnVHgo45oP3kH1EWedF3XQ6ZEuePNFyak2in4lyayMU4PXu5ziDB9fjj5nGg5+EwwQFQd06cOWqYWedOAk/bG+CZNViTSNRUv7Roym5fqjEnV+ygI0oa9djMT5YZxlJ5A/7dD/8BHwUvY5hfWgokZfEdbDuvalU4olKLa6nRifoK9TEhaK70N2apskFkkrb43d2L65ZE03xFkp1dedl8QlUDxrGqY0BmgarNknotXgKFEgwrjoGW5+S9HzSlWuzTuK35xY/7GyMfeZ4wdTtPY+ycsh6zVWXMFG9KXS9xO/1/v37KVy4cIrX2vpc9P79e03ukIgmxRLuiX8L4U1RJerk5GTW7+R/1elbAT8J/SP8LPQXhfaijU3SF6z/ypdfw7hp4OdrOKUvYI3JgZ9jx45pEp5jtWT0Lbd1h8oMnuZP/kKmg581C0JZZTWADP2SilMmnkv5IYR3U1YTfuQaqkzZyPLkLHfWRWJjRrGSGPunqVDnPTRLyg1n1Kn0umLFqrL7IF8K4aPoSKy9xpD17WqKlobOIzITEhRDv6a1UGeLJ7ozalIgqzIvRy6E4uiUupyNSg2c8TikK7Hw/vpTLvfbTlhYOtRNp0Fe/SzAln82JfqeiFoZl5+VdG+bmPh7Z0b+Yh74EeM1aQD7DFENAW/fQs32LgRfuKSZPmbh3zg8vEqGRmW42e4VStkyA+DnIVYZBhLV52j854G3kW9riwA+OGXDekt7Ii9WE6ehM4a19WoiI0UkRAAjUYk4GXgNCCLP+LYyWUOiH5xOMn/AGyjVOTchEZZ8uPyQ2JzkMxeg6chWhORPUL0Wdp+MYe2wc44keyF7ms4V69G1Hb2OsWzwv3EA5erVqxpdr+vXzUt0jx1dn0q5UBXPnDmzjpq5sc/0f91OgB/p67BUTaPKYv/ZIj+zZ8/WANhYmRLxd1mIm4rcLZHsfOjQoRTJaFO1+a+scxr4+coO7HMtNznwI8jQBM+PdcKszEQLbdHGg+FzXpGngOngZ8/6cP540QnnEfpFHg35ROH3mkiP1mSxjcY+HTSpBm3rgqsJlDVCEHXuWFiVPI2RwWMxGvwkHOHpGbLd6I886hl+zyqjzrkLpKa9teWXZ+K4d+qAj1hSpcaZ8divX5IkzDeQy323EPxSRkyd0VC4gQ4LpGxFF5TeA4D460rTnt9FzJv3E/37qE3rlqB18yawO1FwJvFgFarb8OryPVQfgoms1gqP67MJufgAn+YX+ahMWgav6a96Bjbd4cdPeTuBd5Fva42i55E4lXXrLR2IvCjYqROBH6vJn668dgIiZ0hEauKv3WLXZ21VnYi7SZPNXwVCmeZStv2tolICblG/51C1W2Ge570dt0XJi3+wevYjnTfXJ38t/deVO3sfZ+nA1RoxTGFnzpxh6tSpmkKG1Fhs5OfRo0fky5dPM5T4t5jnS4388EIwkafCslt/NvAjInTbt2+PEzAVCewNGjTQKLkLwdQLFy5oAFCaaT2QBn7SngSjPJAc+BF/LAUdvhDUM2RNW5XjtwVvyJXP9ByUs4cjGHmmCZmnDjJqrQkbKQs24FKbIMSt11/esOcJRFlACXfo1hQ8ihL35mxo8CpN4ZyZeT8/XLTiXw8jIj/6Jr+7Bzb9Bpa2YO0GmYaArUfKNNMqJWXTO7H9rLm5NtrFREaqqN3BlQq7kmExFu3ehuDdfzNvfT6iqjEcdcm2ILWADUPgdH3ACIZqvc7/nTWrJ9I+qRan0c9B42awb3fyLqvf0ILbJx+h7PUzORrkIWv7aoTdeYZPvR2EfDSQlKwKQGrfAdXAkxB4Fza3hT6H4oCPWKD11k5EegnUrKtKL7MYhTJGnI2QhBHKufpBqr1tGUJ9dFXGhQB9918suXRFzV1v3QRuUYzpXtOZJwXeav0T/QHJ+Qo0npqNyoMNa+/t7HucxX1X4e6uZfEW111C1+v48ZSq0VI+BpHzM2/evLhohJDMGD58OCIp90szjQCxn/6rfaPXmsvys4GfdOnSIQCn2IfwrwCcItImfh4REUGuXLkQckRplgZ+0p4BEzwgiM8E74c+O3funIYdNjlCtMYtSjF26Xtcc5sOfm5fVdB7VRWyLDJRFBX4WLQJF5sEkjERLjvzFJZcgQeh4JIJ2taBpjUgkx4ZrlodYH0JyBqfJmG053p5W7GqnJngx3MOHBEJmIKf5SFIV4PsLTjUhYz9QW4g8TjsFB3rtGbGctN9nXBjL54p6TzOndJrjAOdyo+RXBuylZenA4ip2Ad10Bs4kAdU3Yz2V8KGMstBbNu0hAYNzOqu6dShi4Rli9Ukl14ybIiEdZVnY7nsb8pe0CaXR754x41KSwgONVDmr/qA1KYpqg4rkGxrh7rHAR3goxlkfRe4Wk6H30cquY9KvQAQmmGGqxQhlMzOFQm4HF+aLBLwuw6XY/NCxe1wGRfOJI1SFKlpz528oUKjAosbTchQ9gO12zpSoqNhlvFd/U6woNeKuIjBrl27NInJsaXT5nsfTVXXvn37OHBAcBqhEU9t0aLFF1vt9TWDn0yZMuHv76+p2hPnN2nSJG7duqXxu3h5FSAoJCQkNcf5TfVNi/x8U8f5320mOfAjwqkioS59esMCnhWq5eXHiVFUa2BtFMdNwp288lfSYnQJsv0rciNMM0Xplpys/YJsyRDVvg2HRZfg0DOQWkHVktCuIZRy1/LaTV4OOXyguzZyb5L1vmzF3+X3Qr7kqQD0DrqtL9wqDSTUTRP5L0dAthcsrSD9D5C+HUjj0Z3Fm1+ZN28lzdqnLtn5preC4atLU3xRT5P2rFIquTV2N0/+uYw6qABqpWAyFom8prEFO6ZrzfbNO6iaPHl4smvrN0jCsB/VFExGYWTbNuj5iyPlz8/ENn82zXjKsAiuFJtEcHD8FZLORCJhOaYCEif0Ax8Rz9neE9X5EgnAjwCyIqlZlNWnxJ10l9JFm3Flj1a5XQCfTj/Jyf5BxTgPJfX3yrnomfRlpGILW7ycw7F4voD0bgewy+9EtQoRFG5u+OHd3f8E83os1yQ2azDb+vUa+grBFZNaE0USQ4cO1eH5EZGgL5Xnh8fm55dpfJVP+tkiP0K0tFSpUvTt25fu3btTsmRJRB6QsPv379O4cWPNtWOaaT2QBn7SngSjPJAc+Ll06ZImxCqS6gxZpUaVCJcFYhH8nlIelnTua4VbYePyfxQKFZXb5sF1t7giMM2UFdpxoPJT8hgprC6+ZA48hOU34FUk5M4GtTzg6GbYkTRXNMXF9LksZ2V5EfkxA/wsaQQBvQEt825S+6hNkrW8AVa5IdOPYFcN5+AKbD/+mDxuqYv8nDoUxYyzVSk8tUOK+9TX4OaIDTjIowh7ruDFqWAUwTaoonMT81GEcoRSffJZ5C5ZqrN7+xlKGr6xSXFdv42R0qi+iuoGzk4EM3v1hvP3nSlya1XceOJ5P5dvBBEf7uufI8YLibIj6p/PJo34fOoh3dELlWfRTxGeGJBMBLWIooly9pRkP47Qs21H/p4ZgdATbj9YjttHFdOrKglXQI1dcFlPSk69zlYcjbqItX9nyj+cxbPRf1OrDrjVMUxPsHvASeZ2W6ohORS2cuVKDdfPP/+IBOzvxzTXXvfNzy/TeMpd8tnAz4MHDzQAR/AzFSpUSCNMK5LLhY0bN44XL16walX8M/79nKz+naaBn+/9CTBy/8mBnytXriDu9mN/0fQN2axrc7KNzo1Lyaw8PviQOwtPIw1+T9W6ctr3sCJ7ruS/qMs2ykaOA6br0kRX7cLu0g9wz2jkRhM18w+G+Rdhw20bXKwlOEijySyPoZCDmrIZ1Lg7Qh57kBvgKkwV+JlVDsKFqrcxyc6+IF0FsgCyutxh4QYrSpS3RC43s8Yf2Lk+glUvGuI2oplZzrvYai5VJtcmQ5F4cczgR2+4+89Vnu95TfgLCTGKzKhiahEdKQCR0LmKd6RLlhKcOHKTT7myZq1h+iwJbvnUtEkkdyUG838BXbpJKGyt5lTOKuRfIyJU8eZZdBThL5NGfiSsQO64EJmzkvDOdwyuS7qzD6pzIuQk9LyEerso+e/+KcF5l8gKSmZPS1n8+8/06wRtBsgpGq1icmVtjk+UEqrtkXLxTNIoRb9RclZuz0G56+OwyeWC77AlNGpnQ86K2oiWPtsz6CTT2s6jRIkSGroKof/08uVLFi/Wlv9/L6YBP7dTCX6KfD7wE3tO7969S/IiKhLM5XI5trZm3N1/ow9AGvj5Rg/2v9hWVFSU3mFFSaxgEM2aNREhSYLW3fr/gKynLTmqxuc5iHvouxtv8mjVBayVYdRpbEmb7jY4Z06KJMrUyEDOUytN3lZUnZ5sc/eheCrFqZ1X5SJo1WMQjLfvXsG108hvnybL0wtYv32GgzoSB4mSbNYxlEqnopgDuDnA1LtyVlUwM/IztRQoDMsnGHJGumy1KVbDhrdPQrCzUVOqgoz6jaUUL2eJlZXxYOifhR/ZJWlFvsH6+ZVSOowzlcfT8nhfZNaGI3yKkEgebLqG7yZf3vlEEhORDlSlifrYnBy5enHupB8uJlTnJV7T0uUSJKjp31f3k6PHYfQoWNsOHgTCb46tcZumm5t0vuRowp75xHdUK5EyCKey9yl5+Geu1ZnAhyaGSYSku/qiOiuIBIVSuNA4++PTWHMAkb9mWNRUIhnGmc3LmLlUTjl1DOMrxUt8xKigwg4LvM/pyn6IZOjGXSRczd2QQsuFlhg8HjCPlgMzkrWYYXbuLV0PMbPbAk3RgnjJEddUgtQ0VpIipXP+Vj7/VsDPt3Ie//U+0sDPf+3hb2h8kfAs/jgmNpFUJ/J9XF0Nk9kN/WUYbxsGk6+RllU2samUMVxddBG/LVdwslXQvJMVTdrIcXDUVsJ41ElP1mOmA4GPTQaw2fUKZXULbkw+lZLrs3BjkhdkSS5JFXj1FK6fwub2aTL7XSTS7ylvnSsQ03wNpDOOGTlucZNLgdL0PWfK34ZZl92xS2epSXS8ui8Qr60vePMoWAOGSpTTgqGSFZIHQ3/+HsYF9+64dhD5OqbbuWoTaH3GAEOygeHEev2PPuTBGh/eH7tF/nxh5MwFdeuqqVwRcudKudgt4dCbtsDjRzDmE++fuNacOEXC5eOwv7caGytYeErCkvJ9yTlQtyrtQqmxhPp9Ej1VvUeqakXO4bnJN1HLVnyz7UzeFNsO9vqBhWRHX9SeIr9n96errtjo5r+AKIHXE476tHgLi8bU8jhDTWs1oyokjfCU2Srliqfuz3+ZbMHu3THYrZlB+hoi1wge9phNp/G5yJAnKaFgWOBH9v10GulrK07sOq3Jw/H09EQwBI8cOZJRo0aZfuhfcQ8N+LmRyshPic8f+fmKj+B/uvQ08PM/dffXPZkh8HPnzh1NmbsopTRkU6ZM4UbhuxTuaPhtN7av0B66NPscr/dfxyVjDO172zBpUWaynlpjsgPD2w5nrdM5KqeAWVIauOMuGzZ1OwClaqTUVOdzi+m9iDmUGSvnfVCwBlE1ZoLcyNDz75VBtdCk+UTjdK79GXfIjhxFdPWqxGcCXFw/FIjXlpcE3A/GzlpFsTIy6jeRanKxrK3jI0MThoXzoE5/sjYuZfIaRIfzNSbQ8pRp4CfhROeqzWB/izdERcO6i3DuBbyLkJDexYIKFaBeLSWlSqIj+pl4oQcPwfGT8MdMeP8eunaXUNpezcwEtDpj9ko58MNIMjeroNPdq8JEQh5ehZg7SBTtKb67HRnriQR0rT2ZuAHfp62huAHyzU294bKochLVXQmjokLnSiSj616zxU+uQCKtxOxad/g5Ya57gtWV3SrFOwH4WbjaghMHwNJCyvPVf2PtqgVk9ztOpef8wjqMzqoYFZ7zr3NnvS8LJy2hVk2tKPHFixc1wGf16tWa3JHvzTTg50oqwU+ZNPDztTw3aeDnazmpL2CdhsDPvXv3NPfJsfT4+pYqeEMOWB2j9ABR+mu8hQeGcXn6Se7veYaFe25s2tTFvkVNZBmMo8Z/13U062XHqKll7jfb5nrCz4X+gpb9TBpDNqUHyqPiy8UDpOuRZ9yKusowoov3Sj6E8TEIZncE1XST5hONLa0nMWL3a0rUS1mOXoChm0ffcmGTP69uBWFrFUPx8pbUa2rJ+jVqQnsOJlP1Qiav4ePzdzz6dRV1N5lX5i4mPN/wTzZW86dgotvUSAXsvgY778l4FAxyGzW5c6tpUFdF1aqQLUH7s+dg7Qbo1wcGDpQwq46aeonwd89/pdybNxeH4iI3J94uVZ3Eh2sjsZBPxOPmr1i76iaOBWw5h89yFTSamdQ/MUpYXBX8igOJfSAqvUQukQBFiU0B0vY4ZrxKcG/DCuNlN0nw9tJ+Ue8+ImX2nxLOjIuh3nRLos/vipOaudtqIgPXl0Vuo7169LvwkoPDPGlRvRVTxk2Layfy9oTgqND1EqXo36NpwM8nn5q9f4808GO27/7HHdPAz//Y4V/zdIbAj9DrERbLEKtvj4J3YuWz1XiMFuF+0+2C+1R21oxm9g0LNgc7E54uA9b1K2LVqTFWboavk94NmMKq8D00SCysbeISzj2FaoGDUf9qWiRGNrErypNCaDIW9CmR244nOp0f6kYLIId+aQgeH4O1Gz9VB5m4WNbRc/FxGgw0PdwlwNDtk++4sPE5t06+h5w5cBvVnMx1i5lEUeC39hySp08pN86MKrdP273QbhnLCj6gnBHA1ccf1l0Cz1cyPsaoSJ9eRbVqWiA0fyHYSCUc6K0mY9JgGA3nW6A4vQ6Zo25EzstjJIpQeyreGIM0VkMiwVGE3vTlao8DKDtrOWziTK1GsrYLrvIzPL/cFUgcRRHlxoI5enOig40CaTuKj7RBvdOLmy0NE9KV2STlipcKryvQdwh4TwO5HKpNssLiskim1tqdJmMZsqcyH99Fsm/IGSQvLFm9YK2mOjNWi0/k7AnAs2TJkjgBUlOfuG+hvQb8eKYy8lP5ywE/IkXh9evXyeZifgvnZu4e0sCPuZ77DvsJzg7x5ZjYnjx5ohE9jWWI1eeaEydO8PvJqdSYZfqXoVKh5FbxGRxuEM9oq1TBursw/2V6Xlqnw7JkQeQ9WmJbsRgSkZT8yQJ+/pMVrzbS3PTghc42IqPB/kADYuaKKwsTbHQX8BRffmUTdQoAu7GQ3QWazQOHROGN83PhsNB9Muct/AINfl1Kz1lGoIZktjK2rjcVZrXEe9553tz7QLaWZcnVry7y9IaZvGOHu/7jWgo2ykGuhuY7/kLv9fyR4Sq1ktdP1buDsEjYfAm23oJHL+HBZC1nkz6rNssKmzu6KtgPx23Bf9VhPG4tQJ5BPz+R4ALyKjeFqD66GliSnYPwKOhJsdoOLO8oziBRtjVBgIgWJdAFIxKJtB3l/3TBPqc97jNWsri2bkJzwrWX3WbJlnXRNOsu48xoJbFLLDPKCkefePBzu9FoPBo4cWvNI6b+PFNTzi5Yf0Xxwrp16zQvLAL0LFy4kA4dzKM0MOG34Ytu+q2An9DQUAYNGsTmzZs1eVxC22v37t1cu3ZNI3WRZloPpIGftCfBaA8YAj9+fn6aX7BYkjR9A/r4+NB7WT/qL29q9HyxDQNvBUCPFayqokvnn3Agz5cw+6Edl2LSo86ZHeuujbFpVJW3s9ex8P7ftNdSmKTKrDZVQrHU07QxRnSFi2LPhvJmvMBpPhRpBLVGizsr7fjbB8BNcT9jIDKU7CqCKN26LyO3pW7TP3tcou35gUikUm2u0JJL3N7gg03OzOT7tRnpy+heEyVc0rmGc6izsAFO+c3kGAAu/LqbCVFnaB6fZmOa74VKuxrKTpdxZbThZ8djhjVO9+KjME+m7eKFpx9qp3SUmtQgjvhQ3+Tni/9GRPf4ijDrE1Nwl6zjp71leHA2kHkNY4gKT0zOKdbyE+D1aUgBfFpTcaErhQZWwOun7cwJPEn9ZEg1y2ySobSHbQOUuCVI5i8+3hHna9q9iDf/q2V+pEuNusyaNDsu0iM+E7+v06dPZ8eOHQQEBODh4UHTpk01lV6xESGTnf2Vd9CAn9OpjPxU//yRH0FwKP5WC6BTvnx5jeTFq1evqFGjhobsMM3SwE/aM2CiBwyBH0GpLn7BihUznMz89u1b6g5rQLMt2koZU+zOxluUX76LsSUMvwknHM8/FP7wkbE7LCMBwdE0dAqif1k1pbKSRObClHXYrylO+KobpnSBnzuBt0iI1VbfGDQhXZH+ENQYCcXawF9N4XWPTxwxpk0pWrvXasHk46lgBxTpuFWv0uajIpWMAAAgAElEQVRs/ySTv/EJ4OyYY4S/iybHD9XI0aUqFja6bNIny0+g3fl+SGUGCJCM2NKV6cfp73uA7uYVm8XNUOUPGed+MQx+Sk+3JdP9jZr2T+cd5Pm+W6Q7tpbgPuMp3KcUTuW1mlf67JLHaELbaZ8Jq8uryOY7jbFe2sTp1w9CmF/9KYGv/9LTdbDIagIikFi0puKSXBTqq70aPVx7Pk/KPcTSgOuE8Hi1jbByGFRLhG/dx6Yj2w3tXl6vOUbh0wGsXZRUmT6W8VcUIrRv315DiOft7f1dRwY04Od4KsFP7c8PfrJkyYKvry82NjZkyJCBoCARaUQjbyH4ftJM64G0yE/ak2C0BwyBH/FWId4eBZ26IRORg+JtStF6f0ej54tteG7CCQZePkMn/VXyyY538jk08K+MlWtOMt89g33kezLIFBTPFEO1nGrKZIOcTsaVT2dalZ+3y2+ClTGkg5+WNbwVXOmSLKdL/AYUYPU7ZAyEt28haimQ8hWTPgfk9mjBrAupAz8/V71Ou7OJr2ziZxPXkV5TTvHkkC92RXLhPqY59vm1hEpnKk+iradpyeGJ93F7+QUan9jGr6nQ9hJjNl4sY2MPJYlSeuKmKzbNlmwPNvJ8+VGerruI46mNmuhH8LCZFGiQHef6hkNP1+tP4F31U1j6niKD509M8akQFzn5GKxgWnEvXj1LKhMhYQBqTiKxaE7lZW6494q/Fj3sMYvntfULf+54bMEELwkx1iruzNa9gv4YBSVmZMbVew3K4HDu1ByN76nLSaQkhMSB0NgSult9+vQxKZfL5F/er6iDBvwcTiX4qf/5wY+ouhWRdgcHhzjwI4gPy5Urh0hRSLM08JP2DJjoAaVSqSE/S2xCKfj58+cakrTkrEjz4rQ51MnEWeF4ly3MjbpDVTO4ekSKkpOXB2HrLiT41laC9xmsTuwg243D2H14hYNUQW4HNXVyx+CRQ61hhLZIlCNSeqMr10YegdzG57FIf22F6tIPgCmJKy+QW3dEonYmOjoXKlX1TzlD6Yz2XdbiLZh/w3zwI8Dq2Ea3aX6ol1Fz+h1/zJnJF4mRWJBvUB2e/3WElseM62togsc7b1Jq1RqmG6bDMWpto/fKKJdNSUsDj6f7tPTIx/fh8eIjOHpuiwMvoeMWkruoHJf2hpP0nw1dxsMnNUjns4jpd8oht45nKhfXThPdjuP/eEeSdVpJBoGFNRVWFsLth3jgowiOwKvGbB400k12jlRCvxOWBFjDnpXRVO5oyeXfdRXIn72B2uvz4np8MQ/6LGBqtQ60a60baRURgYYNGzJixAhNXojmCz/NNB74VsDP4MGDCQ4O1uRxiQpc8XI6cOBATeRnzhxBsJlmmvNW62OtS/NNmgf0eMAQ+BFXWuKNQtwvJwt+mhajzZHOJvv2cPVlbMvzinzGf/frzJHxiBvvdt5PObxz7yaSoztw9jqAQ8AT0ksjyW4bTY1c0VTNpWbJVUtWt9kFHrpkeMltyOKXFsRcFsKgxgMmMV6p4sW5ui+S+49h4WoZO465EBSSgeiYPKgiq4NKfJPrKV36tJiMbq1YcLsoMksDWb4pnMLbZx/5a8wr6q41LVIXEfSRIz8d4Y3XU9IXdSV/+xLkalQAKycTomWf1vbynC85Jy9ivmlLSLKzXVfhpEiO1/PoiUR294lWvMleCEeveOAjBgn7YyXZHYPJ3ldU6+m3V38d4OGIjfzxtCb2GZLKVUwteowntxODHzUWku5U/bca+broIrJXZx5hO3wpW+vHs6n7BEK3IzL69VPS75MvyrS05MpkXfBz9TG09SxD+tHdCRu2lqsHhHJ8vD179kwDfIYMGaL5Lw346J6pxh/7Uxn5afz5Iz8in6tHjx6afC7xEmNhYaGp5hP8TYKPLc20HkgDP2lPgtEeMAR+RL6P4PqpWLFismPlLJ9bc+3l6GocR0/sYPuKzOFSjVBsjdNBTbKGYkey4LP0EmRNXkhT7+JfPYOju0h3dg/Wd7x4nb4A/LQAihsnNW4xrCkxV0XejCl3diqqVy3BqfVJ5UR87sGC1ZbsOZmZD6HpiY7JjyqyBqhFQrV93BbS5enBtFOZyJjTSELFRJu/svc1npflVJhk+p1TwNWXSGeuYWrfj/yxwZI9N52JsrYjS013CrQvQvrCLkZ98X54+AZ575n80yN1X0iPA6HvGhuO/xqR5Ii9HkGrVTaont1IUs4evmIbmT/cJdev+kNPIadv8rDPPIqUtqTnJhGdS2qzyh3nvrcoa483K8lWJBbL6Rg5A2mCykTR4t70A/Q5f4AfimuTtWddhM1PYM96cP1UECh+XrqFJdem6oKfI9eg76v6hN56wfm/t2n09mJNiFrWr1+fAQMG8Msvvxjlf6P/MHwjDTXgZ3fqnjWaf37wE3scoqpPFKOI50DID6VZIrCbFvlJeySM9YC48hIAKLGFhIRoVKCrVEkeEDgWLo5lNidslB/IXMSZou3cyFEtZ7LaT2KuA/lmcLNppLHLTNJuiKeMRd02oqpverK1zmBjB4BzJTgv+HcioP90KJp8NZbFkMbEXBfJrflNWP8TOrZswob5hpN0YwfzvgmLVss5cNqZ4LD0RKsLoo6siU3G7YzZE02BihlMmDe+6a5Zj3ifqQCFeyQu0U95uGcnnpDp380s/kWozmtNPDZbjsDCQ874hdpim88Ft44lyFE3P5a2usnSsX0UYZG8rTWWnQNT94UktLDK/G7F9d91waQyBspNscCvdHWstyfVjYvYcgAnn7PknyS4enQtYO0JgueuZdJiW1bOiqTnLqFSn9T+rHoCn3PbEnzwlozW/aicNwBHr9nIHXQjYueaL+Z83ruIbB5BKJ6vFCxMxHMplOg9Wkm4OkPXL6tPSRl6qRBNi1di2WwhiKs1ce3RoEEDTTRASFakRXz0P8Mav2xP3bNG6y8H/KT8m/p9t0iL/Hzf52/S7g2BHxFmFQyx1QSrnAETfTNVrMHHjZe0LW5dRrZjEXZPLmHnCHnr5aFgi3xkKOCc5I/z0VxTudJS9y3XlIWf8YdG1r0JHy+UtVNhXRpBh/mQxQ3ePoOVfUGqhAHToZB+5mqLwQ2JuTUUMIVzZwdTfhvNmEFJOZVSWv15b1i4xprdR2zI6AYFqzpTuV1mCnikRyY3/gpsWb+bpG9Xk1y1k6m3NrCYhzvv4L5/M7OGGl7/fV+YucmG43cdUdtZk6tJYXK1LYVTXmedUR+X+oVDQ1L5hSQIA6ZY4TVWF/yM3mHFuZAYrtX8P/auAqyqrIsuGrHFTizsFruwu3N0jDFGx7HHcezW37G7u2tsFBVFUBExx1aMwW4xkHz83zrPR74HL+BR53wfn8i7555z9rnv3nX3Xnvt35B2IvcocvN3Og0b50MourBPpA9eTN8CizMuWHcsE14/C8FfPd9j6Cn1obHlzc7gkhOBFUOUobAxG4QT/a5h8XkTmBybDpvskTWETlebiWV2zzHaHZg3C6ijxpn65SvQuCtwbnrk+U7ZZ4HZp2zx8uaDMN4SRe5IbqaGz8SJEyXwieELlFzAj6Ojo8Z9pt6abEoLSPAjrwStLaAJ/Pj7+8PDwwP80qlrVIa+cuUKWg0ZCd/1boBVFG4EX2UPbkQq161I9e0FMuWyRMmuJWDXoACs0lnjfOHpcGumP/gh6TnV+SoI3BaB9Kz1qiMc2LQSMN4dsLAK/+Pb/4B1vQFLC+DXGYB9FD2f3vUAb1bwttN6RHPLKdizfAta6a4HGTbGyi3AwFNzEJKhNKy9lyB9gBfSZQxGaccMcGiTHXZl08PUTDPZdVbrSyj1vw6wLaq5GrimBd3aeAXVrh3F+N7aeev8/YH1B4FNp9PgdVBqpCuWA/m6VkKOWgXh7TAaJ4fpDgKjzq3BHCscGhwA6x9OJu/XQLt11qjVxgpbqs5CqlbRK9cHnPaAxeZtKLlugDhdaEgIHg9YAPvgW5i5TgnS/L4qMKDxcww921KtObb1uwiX1SNEtp+lySE0K7oE//T8hp67TOC3cwLSFQy3b0hgMPYXnYLKth/wzwbARkPE8t0HoGM/4FQEvTqGwuqOAzr8tgw9u5NgDyFmSOBDvgdT2qXHJ+avoLDPDgOBdueE9/wsXLgw0kLp+du8eTOo/zN9ehTErPVdKfkdKMFP8tvTeFuRJvDDFPgzZ86gfv360cb++vWr8ArlyJEDbYf8Ae+xa2Ln3vg8hMXO+bD59zhSWQUgo/dTHG0einzqhXa1Wm8Gl6Lw3XM7dtJzTGdrWgVgZXd17fVDYONAwMpMGQ4ryJpOAPo0AR78AUD7iu7Zc3bCiY1XUVKzvEysa3Y+AzRbPBQhteaHH6sIBu7vRZr/ViCt4g5ss4eiQlNblG2aDTmLpIn0cBxb6wIaHe4nwKeu7cpiD7R8dRJDuwTq2lUcf+kWsGCXJTyfpEHoiw/oXQNoUBwomxfQVzZo6HYTNCkZikallFya6v+zxJz95pg6zhyXlxyHeY7oddACPa/BZP5ClNkxEiHfA3C/4xQ0c3iNARMyhq2L+SLdq/hguKd6Je6jM29hzxgqfFdFGsu++DjxFVgpo9ceE3xa8xdsS4enMN6e6QSfje54dvRLjHZ7/gr4ZQjgPD78sKk7TfDKpgNmL1gv/sjU5ubNm6Nhw4aYNWtWihUu1OUCFOBnq4Hgp2vCgx91a2YJE4Y8jx7VUaFeFwMmsWMl+EliG5aQ02XmAIFO1Ma/nzhxQhAqIzZmgZELZG9vj9y5c6Nh1x5w6zQSKBFzSnykkygUyNIuE3KnDYX1Rz90LKBA94IKqEmsidE09idz4cGyC0D23PqbsGUdYIJrzP1f3gM2DQJsrJWeoGkjgIf0/Gg/rl3+Gvj3yBukDecv6zxn7ydAyUGdENAgusZM2MkCvwG3NyLDq3VIa+aD7PnMULFFFpRunA2zOvyLdh6DdB6XHS5Md8UvcMUvrbQTpdQ0CD12dYeaoH0PS7jsCcILbwXSmAEOdkDjkkDlAkAUbUWN8911CbjyGPhfB2D+CeB6KivMWWOBpo5meHb6qtp+Qf/egdmkqbBfOQj3Wk/AoN/80axrdATes9oTDDnfRu05vHY+wYrOhWBjdRuHu1+C4w/qV//9wPO5w5GtqjIc+vXpR5xuuRyZLP1xZ4dSlE5Te+QDDP4LODxGeYTTZWCOc0EcdvlX/J8JCFRrZhh63rx5EvhoeRUL8LPRQPDTI3GCH764ZsyYEeRnyqa0gAQ/8krQ2gKawA/ffo8fP44GDRqE3Wip+8OCpxQ+pMoo24Chw7G+bAugpm4ZRHYD8mLUmXqgqN7pebfgvekesoQEolehELTNH4pU4dIqGtfym7sFlvfaCTRU/5CK1QgMzf3UCvhLyzen53eAzYMAyskH/QaE0iumXa5+sWIVcNs55rf/2OZLjJq+WT18b34ytkPDP//2BiY3V8D24w4oAl6hwqDKKN6vMsyttDBwhFHcRjvjr2xn0Ta6I1D7uQC48wiY8Y855m8I9z7xGjzppMCRbUF4+G8IzEIA+2wmaF02FLUKA5rKjt15AfyxzwyrfwpBk5VmOHHbSlyrjlVD8d7jhtp5BXs/QdAvg2D+9RNmLTJDuRrq04T71PoPA93Ue35Y4mJxsweoles9jvb6GjbOqBMmuPHX78hZr4goQ+HccDEKzuiOZwPm4+Hu9zHa6Y43MHYK8M+fyrplHeamgcuF/2BtbS30XVq2bClkJ6jzklJLVeh0of04WICftQaCn94JD374whmx+fn5ibDX+fPnRX0v2ST4kdeAjhbQBH54Gnp+WDuGhfQonU/hQ4oeRtSV4FvoGEU2oA11b7Rv2XvmwcSLkZ+kXz/44+SUa3h55AnyWwWjv30wGuSOLkyoGsX1GVDXfBBCpyzSfuCIR167AKxcD/SOXiogxhPOrA3kyQ9cuw/4KoCQXEBQLUDBEgiRyb2q85QvWQqXnaKnues68TT1q+FbSx1rkf0YJKdLLhRvlAXXj7xCka4VUX5wBVik0k5r4PTAQ5hW8iKaaNYG1Gop244A1/0tMHJiBI6Vmp6XPYOxe1MIblwIhWlgKPJlNEGzEiGoax+KXD8iVEHBQNW/zURV9yGLzeFQzUKAjmpVLfDtwhW18wlycsHn38djr0tq5MqvPiONHfvX+w+/uqgHP08uvceSZu54M8RPhLtUbcIpwOO3fsjXsjR8dnvB+59bKLN9BC6WHYzn+97GaJ9rt4GZs4E1A4B6E8yxds8VUaWdBS1btWqFMmXKYPny5RL4aHWVhR+UXMAPAS/XopLw4z24fPnyAgyXLv0jHK+jbZLj4dLzkxx3NZ7WFBP4YRYB3zbv378v0uHp8bG0jPzAoOhWV4+HCO0/TqcZZvjZHhNdK8E6rfqH79uHn3Fy/GX4XniJshkUGFQkGOWzRqb3MIRida42grfHErbSNLPNiwEfE6AR09Z1aHObAjNWADl+cH4e3QF2r4PZydMw+RQEk+BsCFHUhQKUCaAWhwJ1K5WAyx7DQkacYfr6FfC55SUdJht+aB7X3Bjl1ViIpDnPuA6vXc9QoE0pVPqzGixSawYCPMPJnnuxoPY11FGfAKf1fMYuBAo2tELLDtqBLtWJH3krsGN9EC6eBgJ9FciWBmhYLBQrXRQoUs0SK3cq5//pYygatMmIAFe3aHPyW7oZ/ut3IqOJL5y8YiabDWz4H/ocjw5+3j7+iiWNT6GaxVfs7B55iBluwImfeyFPk+JwrjMPVS78DVNLc1yvMhSPtr+O0Uae14AlS4BPX03RdchGtGzdFuTWtW3bVoSYV69eLYTtZNPNAgL8rDTQ8/Nrwnp++H29c+eOuA4sLHT73uhmraR/tAQ/SX8PjbYCvkkwc0tdc3V1FTdcSqiXKFFC7Vsn3bFV5q6DYgJrVmnfUg9viOFzbZCzRDjRVFPvRx5v4DbhEvxvv0edbKYYVDooTBk6tVNJ+B36Vz/S85g+gH0XoKR6PReNq5nbDJi2FMilIdvr+X/A7tWwOHYc+OCPkABr1KzkhQPrgPQGELw5n0z1SuBjq/CK49pbHCh4LjeGnQ8PT/Km6rrgFs5tfIx8jYug0tjaGsnQxztux5o2t1FJc51brabSdTTQfVwqVKhs2IP83VsFdm8Kwqq5QfDysYG5uTLl/8a1EHSbWRqhO5WFQNlCFQr49p8GxcvXsD2wAF8rNoPrlZgfIkOa+aD7oRaRrvmXd32xvrUraj3+BspLdYpS13bueeBA66744H4PNg2rIlcnZfXWa9VG4PHWFzHax+0i0HMY0K5Db0yeuQgMa7Rv316I2VHFVwIfrS6vaAcJ8LPUQPAzMGHBDxdFTw+9gDLkGfN1IMGPft+TFNlLE/ghz+DChQvImzcvihYtqjGlljfpLB16IWTRfp3sZ/a/gejf+T5KNtWeNMwBru59Ao8pN2D17ita2ymw/GUOPN94Hsime5Ewyz4NEdhmOZBNR92bec2BKYuB3Pm1W/OTe8jwe2XkyhgMW+vvaNdIgU6tgWy6Z5wjc91CeN/6gXbjRjmq8PncGHJOPTfr7IrbcF/ljew1C6DyxLpIlSlyTrZzi03Y1usBSukiaq1mlvX6Awt32SB7Tu31iWJabMNqATh+PjyE5nQgGIPOdkHq2cq0KcXXb/jYZjAsHUohwwwl2ftT5Q5w84w5BDmu6zM4zqqHTLmVdvjvynts7eSOQz5+4Fn2jwXSREmaW+oJLMtRE5/vvERFl6lh075WcyQeb3qmcRnMVBsxHTjlkRPnLz3A9+/f0bFjR2TJkgVbtmyJVsRUr81PoZ0E+FloIPgZkvDgp3Llyti6dSsKFdJFWDXlbboEPylvz/VesTrww2rurCBMFyvjyfT8aGrsn7ZBawSvPKbbHHauRJtMm9FwSGHd+v04OjhYAbcld3Bmxm28z2oPRYW6CG3SFijlAGjpGrZoWwFBf3oA5jGHfKJNcH4LYPJCILf2IodZfymIFpeGI9g/EHcXueLrrjNIq/iKJjVD0K0DUCCfdmbIUisP3rXxBsx0nDOAwh65MeRszMR0z00PcGbRXWSplAeVJjeATRYlIfhogzU4MOw/FNI+u1/tgir1MMGhizYwi0GPSDtLAO/fhaJHhyAcPh1uiwVzFFiSdQpsurdFiM9zfGj1O9KN7Qub9uFZix9rdIX72ZjJ5zMGvEGhruVQuEZWPHB/jT09POD83A+ZTYEm5sC5CCnpqvmuuQwMPp0atW/OhXXW8HIv12qPwuMN6iu6v3kHdP/DFIVLdMSsOWtBfa0uXbogTZo02LFjhwxzaHsxaDguuYCfGTNmCIIzi5nSGxjRA0QyvGxKC0jwI68EnSwQEKB8CyaQefLkifghmY4kZ5IubW3Vk3h5PEMnmeq1QMBaF53GxM1LqHK6D3osjyIgqNtZsNzxKNat/ogHd0OxfG0mXLmfEd9TZ0NI5YZAo5ZA4RIaQ2IW7SojaLSnjiMCmNcMmLQQyKv9W1iGn4ugxdl+sEwbIcspOBjemy/iw+rjSPXtI6pUVKBvp1CUKqo5ile8dS7cqeQFpPlRFEqH2dtfyI3B7tpl5V3Z8xguf99E5jI5UXFKQ5xtvwbOUz4gl4HlhKr1NcFBj7gpxOh5LgQbVimwfGN4CGtgXwVODd8PxbuP8O0/Cba75sKyRGSA/d6xF9xd3sYYQlg+8QtQNC9s0qfCwX4X4fb2C9KZAt9CgdapAM/RkQ1P/lnHHYBn0UqouGNYpA+vOY7G43VPou2Ukyswbm4q/L3gAKpVqy7Cz926dRMhrt27d0fj1+mw1fLQHxYQ4GeugZ6fEQnv+cmfX72XmetjAWrZJPiR14AeFiD4IYi5ffu2SKsl8EmVKpUQMuRbRtas0cXiVMBHgJ8yDgjqPx5wbAXYaPlgCwxE4THFMdzJsPShBeX2wN0rGObm4crG/v4K7NmuwJqtmeH9Ki1CsuZBiGNrBNdoAeQKd7FYdKqFoJHRibGxmnB2A2DKMiCf9l4r67EdUfePnMhRW3Mfn8M38WqlEyxevULZosH4pY0CVSsAphEiRLV7ZYZb7lNAFt3JN/aeuTHYTTvwo7LBDScfHJ9yHSHP32H6QAUqlwIKMANPT8pOnd9NscdVv8KsUfdl3YpgBPqHoP/Q8LBXm6YhuNF6LL4t34GsZzbBNB1LUERuH9oMxf7l95E5u+Z0/z0rvsDpmCn8LvrC/b0vrH/sgacCWF3QBLt6hj9QWU/spz0mOPHMGtUeLIFlusjru1pvLJ6sCX9A8V1jyFQTPHlTHNt2uol0dmpt9ejRQ/zLJAIrq5iz4WK9RrU8YMmSJYJTdOPGDVEdfv9+3cLXWg6TYIcJ8BOlXprOk/kr4cBPs2bNcOTIEZ2nnFI7SM9PSt15PdfNOl4sVcE3TqbUMrWdjfoR2bNnF0rOEVtE4MObCyX3p85bgL1nL+BrOluENOsGOLaMFQjlHVgQo09rrh2mzXJWVNmK0xdi1qz58EGBTWsV2HUsK55/zoCg7AURULstzHZsQ/BwZ22GiXSM6eyGUExeAtjpQIA5thMVfdejzPQWWo332uMRni48glDvJyiaNxg924SgXjXglzGpsBVHgLzqy47EdPLCF3JjiJaen6jnWeWwHQ6F/fD4mRXefwCsLIA0NkDxAqGoXjoQpe0hQmKsCKKpsRBq09Gm2HY0bsDP4F/80W+IBUqWCUdidR0CcD9LDdgeXqHRs+P7+yzMbnsclepqBurLxn/AoQWfcDswAD+41GJZ883MkaNRMPpR1QBAQDDQfLMpXnTtgNcHPVHzYpSKpfweNZiAJ6uUPC3q+fT60xydu09Fv18Hi78R8PTu3VuI1R08eFCAIWM1Ai2GUE6ePIlnz54lT/Az3UDPz9iEAz/p0qWTIoY6fBkk+NHBWCn9UKqEMquLoa2oxGZmclHMkErOqkbgwz70+Ki0JyLakArQ0+YvwO4z5/ElrS1CmnYB6rYGUkeXNs7WuyAmeegPfjiHHU124ICzbm4InycKzJ8LbNmTFRZZskJhWwDBZdpCUbQekC52FrL5nEYInrgQyF9U+8vnux/yjKmAhi46ptWToHvvNR7OPYyQq3fx8eV3PLebgNDK4wFT3YQK853Ph5Hn9CsutqHJAWz86x2KR8B7rN/l7gmcOgdcvWWN129DYWEWitTWIbDPp0C10qEoUwQoYgeksgau3QX+PmKORevj5uHeofF37HRSChuy7d4ajPF/Aameqhc4VG3Wl9mb8Hv61WjXL3qmIa/vJaM/4+SmNxj7JhhdooC5zuYW2DAsCFnTAN8CgSbbLPFpSC9YFcuHl8sPw2F7dAXtq40n4fGye1iyCdh8IBM2bjuLfPmUHkhKSPTr109oaB0+fBg2mop/aX+l6XXkpEmTwHIJydLzI8GPXtdEUuwkwU9S3LUEnDMBS9q00cMDt27dEn9nxhcbwQZ/+ICgxye2ooo87/R5C7Dd9Sy+pbOFgkCoXhsgtXKsjN0LY6pHNZhZ6Jf58/LOJ9ybcxTL1+ren+uo2NIOdQ4Phe+917i35jxenHkJf39LKDLlDwdD6aOH/MznNEHwhHlAgWI67VrGngXQ9goLYurf3PpswofHIfj2OACKbNURWPJPIIN2xOt8FwphpHsdvQbf+pMLZnd6guqVYu9ODw81Bl3cgUv/WuL5ixCYmSjg+yUUuYqYYfF6qzjJ9mpRyw+H3JRepJfPFWjdSIHPqbLB2itmBWy/PcfQ3Gsyhs6KDHRDQkIxqccHZLj1Gd8+++N/z4AcUS6thhYWuDAuCL7fgYZbLRE49Xdk7VQbd35fiXwdKyJzrejXxKXGU1Am8C5yFWiFuQs2h4E1vkSQwOrj4wMnJ6dI4qGxWzluj0jW4GeygZ6fiQnn+aEXcPbs2WHihup2ffBgpQdRNkl4lteAjhYg0VKlHBqx6927dwX3wM7OLgz48Mx7tnUAACAASURBVHNtgA+P41utSpad3qM5i5dhm6s7PtukR0iTzkjntAR/bs0P23z6FbxyW3kPJQOuYMBg3cEP51e+UU7UcWaB0sjN98Fr3F/jgeeuL+HvZwGFbX4ElmgNlKwPpM8Gs7lNEDJuLlCwuE6WTtezBFqc6A5rW/3Wy8FOtlyGgvP6I3Wh7Hh15AoeTD6G7x9tEFikL0ILdwbMNXtV7DwL4Q83/cDPP8MuYFi5W2iun+NI2GnXQWD0vvww//QBGa380L2PKVq0N0eqVJor0WsycFBQKFrU+o5jHjZQKELRvFYg7Bf0xvGBp2DlGTNHIuDcZRRbOhILtoXvQ4C/AiNavoHj1y+YViEYtQ+a49Cb4EjDB4YCDWzMcfz3YDTYagnzpaNg27iiOOZizVGo4z4x2nQ/eD7A1W7LsHXeStSrF65oTuAzZMgQkVTAwpQMbyRkS9bgZ7yB4GdqwoEfUhBq1tTMi+S9mGK0siktID0/8krQyQLkHNATErWxjhdbgQIFwj7XVmSLKbvkDKVPn16E0yL2+/TpE2YtXIQNe3fBNvNXVPulMMq2y4s0trqFQ3b86o6hHZ+idj3dwl6qdZaukRn1z/6oJBmDxXy93+D+yvN46vwM/t8tEPjlIzBwEtCie2Q2cixWt5jSC469UyFPkxI67U/Egw9VmwMH1xlCOVjVgr/64/aYPXh24ClC0pUFKgwHspSMNobdxUL444x+4OfE39fRzPwa+naJDAh0WYgnU8FPVETNha3g/9kfl6aewCeXf2FfKAR9B5mjSg2lhL827cFdBSaPCsCWA6nwvwlBOPulHGrMb4ZNlTfHCn6Cvf9Duv49seOk0gP5+WMIBjd6hcHpv6B3UeWDstJeC5z8GLng73UFMDGHGd6YmsNmy2RkrKb08vi/eI9bXeei5unIKuePlh3H501ecN9zNKwWHo/nd2348OHixcDZ2Vl8RxK6JWvwM9pA8DMz4cCP5Pzo9s2Q4Ec3e6X4ozWBn4cPHwoyJtPdtfX20JhUIiXwYbiM3IaYHmiU8F+8dCH2uexEiKU/SrXKhQod7ZA+R+yk2NWND2LDqm/InVdPz0+N9KhzNvrbemwXhFPNFXj7OitMQ9/CpFItBHcfEV7qIqbObkdQ2nsuHBa0i20IjZ8frjUfldyik2pVHd6fu4t/Rzjj24tQhNr/DJToBlgqPRwFvApjuGttvca+uMUbBW95YsJgf736s9OrN0DDWcXQcNtPkc7x7tZrXB5/BKE+z1G3AdDzV3PktYt5T4/sCwZT3Tt0NUef3jZoc2WoOKc24Efx+QuC67XHMS8rvPQJwrCmT7G0UADq51FO62sg4LjPAi5fIoOf1SZmmG4eiqLn5iNtqXB176crj8HkwwfYj1aWwwgJCML1vqtROjQbti9fHwn4E/iMGjUKnp6eonYeq3Inhpaswc8fBoKfORL8JIZrVJs5SPCjjZXkMWEWUAd+GAZ79eoVyPshGTpbtmzInDlzrDL75PlQIJHeHmaK6dLoLVqzdjW2HdqA7yafUaxxdjh0yQ9bu+h8JJ53adWdcD0XClNT7bwFUedSsWpq1PIIV+LVdq4uLTfiaZaFQK5KwO09MLs2B0hjAUX7vght3Amw1JCmHByMHENLoKmb/jH6Q/WWoLLLlFinqggMxr0Zh/Bk430EWxcCKgxDgefdMPy0fuDnvusLBG89g6VT/GIdW9MBdC4W+zU/WhzWXAT3/p4beLDoJDKYfUHHn0zRprM50qSNvr/TxgSiRGkTzP+fKWodHYQ0OZTXiDbgh9f213JNsXJjCMa2f4UDDt9RIoKU1ZU3wEQnE2wNDn9ofmDIK8QE6U9Ng23NyF61K82noNKW/rDMkAZ+T9/jaufFGP3Tb/i1V59IpiDwGTdunEgwcHFx0aifpbeB9ejI0DR/pk2bJjxRu3btEmAtag0/PU6dKLqIF68kDH7IueTLpGzaWUCCH+3sJI/6YQHe/MhBULWIGV0ERkxlZzYKU3GZ/UXdH0rvq1LiVf2ePn0qBLeYLh+TKrQ2huectmzdgvV7VuBz4HsUrJ0FlbrlR/ai4WrT6+psh7Orfl4fzqFKdWtUOjEJ5ja6qSW7dtyCJzYzgbwRYvH+n2HiNg6mb88A9iUQ0vsvwD56teX0PQqi/dXh2pgg2jEBn/xwottuVDo8Uqf+n2/64PrQwzB58i+yF8+MYvWyoYhjZuQokQGmZtrZ793jz7g14jB2Lf2u09hRDy7SMy9aOPeN9RxUwvaacRqfjl+BXe4g9PrVDLXqmYUB3S5Ng2Cd2hSBDRqgVL/waqvagB8O/r5sc+T+4gO32t+RPUrG+8YHJrh/MhSjfmR6kevT1NwCd3NmQNX7ayIDmuAQeNUYBccLU/Dm5A14j9yJgyu2olSpyDpMBD6TJ0/GsWPHBEeD35/E0Ojx4bwittq1awuAlhyaAD/DDPT8zE84z09y2ANjrkGCH2NaOxmMFRH8xJTRRWK0Cgh9/PhRuOxVHiGqQvOzcuXKxXm6LufEFNzlWxbg7eeXyFs5Iyr9nB/uI4/hoIv+VY4bNbGE3ao/kTpPJp120a3XDjwKHg/k11AQ9ZkHzM6PA0w+A406IKR9PyCdErSl6l0FrQ60QOqcmkuGaJrM06O38ODEW5Sc11Gn+aoOPln9b+T+ZyZ8dzoj5IQHTF88BzOrsxdNj5KNMqNgjaxIl119uJHlRI403IDjWw17kNh3y4WWLv11mv+nxx9wZeIRBN19gnLlgIEjzPFb9yB8S5MTzU9G9q7EBn4U3/zgO3gWgk+fxocGL6EO9w7ytEDDa0GobUbVc6C7qTleT2iGe7uvodLlRZHm/vHsbbxYcRjpi+VG6ImHcNtzNNr1z5cJliegpg5BBb8zshnHAgL8DDLsmsViCX6Ms1uGjyLBj+E2TFFnULm+VcCHi4+N40OPEENcrAPGfymQSAn2nDlzxrvLnIJs81b+D08feKFeIxP83MdUhEC0JcuqNvenLmaw+HMwbMv9IHtouesXBu/B3XcjgEJNYu6hYM73PJg93oEQCkV2Hw6TMwfh2NYf+dtF9wrFNvyVKU4IzV8IeX6uEduhaj8/6TAddl7rI33GPff3uoXvu5xgee0SzP2/IU0GcxSqngUF6uRCnvK2sLBWkqsP1FuH41sMe5DYd86OlmcG6jV/dnp89D5uzDyBbz7v0eHuXzC3juy1iwn8+O0/ja/j5qLKsPJ4tOgsntZ6qnYeDZ0ssO1ZECxNgWkWljjWqizyDamLS3+fQeldf0Xqc3fwKvi630KrGvWxfNbCaOcj8GGq8rZt2wTw4fdDNuNZQNwTBhh2zWK5BD/G2zHDRpLgxzD7pbjeBDIReT/aZnTRE0RhNPID+DZLz8/79++FNhBDY/yJb7VacieWr5yAd+/vwqFaCLr1NkXR4tqFcoYNVOBlm1+Rs75uej1eo/bj1uP+QFElwVWr9uER4DYBeOeFzHkVcJjZFFmr2ME8lfYhtxPt1yPfqHbI4KB9TbGIc3NxmIo8bithSsXBGJrC7zs+/3MKJsdPwtT7AawtFbDNa4Pgm49xakco1FSM0MoEPKhwu8xodX6I1serO5CAYnO55eh+7bdoH2+svBnWUVLdQ16/w8dfxiND6Cc039MOljaWOFhiNp7WfaV2HtX2W+DYuyD8Y2aOGfY5UP3KGNxaeApfLDIh729Nw/oEvPqIS47jsGzsTLRv21Yt8FmwYIEoH3H69OlIYqEGGUB21toCEvxobapkcaAEP8liG423CJIdWc+revXqWleRZkkMVfkLVTYYZ0zuEAEQOUIEQ6lTpxYgiOCI9cLis1EvZdWaifjk+xDVaofgp16mKGSvGQjNnhaE8wW6Iv9PVXSa1tVJh3D9RjegRBed+omDP/0H7O4B8yz5YB1wBVbpQ2FbNicKdCiKbNXzx8g/2l91ESoeHgVLW/UE8Ngm4954AWwX/wnLwrqXZg/09kFg9bbIlVWBDFmAnzsArRtChM10aYVbZURLz2E6e+kijhH4JQC76m1Ht4s9ow29qfI6WHkeF38XxOaF2xCwdjsaLq6L3HXCQeOhYtPhU/+DGsACVNhtgQWfg9AzY3rU9JkGU3NznGq/GvmXDYFVVmW40v/pW9xsMwv7F6xFhfIV1AIf1s1auXKlAD4qRWddbCWPNdwCAvz0MdDzs0Z6fgzfCeOcQYIf49g5WYzCsMf06dOxd+9evHjxAi1atEDr1q1Rq1YtjUCIfB9mhhD0RCx9EdUgPPeHDx8EEOIPvUAEQQRDBEXx1TjuwYMHsG7DFHz95oNa9UPQpYcp7ApEBkI7NgVj89vGKDIi/G1emznd+NsZVzxaIrRUL20Oj3wMwc+xCUDjjcq/MwXqhRvMHm6Etf8lWKdjodicKNC+CLLVKACLNOGZY3vKLUDNK9P1Bg5Xe6+A6U8dkLrej8JUOs7eulgNXOnoh3d+wKyLgNsHIHtOoFcXoEkdQJtanMXbpkf9E4NgGWFdOk4Dn30+4WgPJ3Q6HTllnufZWHUzrD3ID3qIT73+Qr7SaVF3ectI6eYhAcE4UXE2HtZ5F23oZ1+BtgfM8UlhjvL3JyNVVqX44JHa81HuzGzxu9/j17jd7m84r9qO4sWjC10SdBH0LFq0SJCbqZMlW8JYQICfXgaCn/US/CTM7uk+qgQ/utssxffgDdvb2xt79uwRxMzHjx+DFYVbtWoFR0fHsCrTzOaiHD+zWZgCr20jIKG4ITlCBEIMlak8QgRCuvJ1dBl3166d2Lx1JvwDn6FeYwU6dTdF7jym8DgbgnH7K6PMnOgP0ZjOf3vxaVw6UQuKsnpwVwh+nP8CGm3XPMSLszDz3gDr7x6wTheIjCVzIX/74rg01RU1LkTOzNHWDjzu4bxD+JQ6F9L/qh9hGkVr4VbHr4ioQ/jsMzDjIuDx3gT5Cpujf9cg1K8O/KiNG2165TunQ8Ut/ZAuj/7Cfm//fYWz486izcH20c7PsJd/dUfA/RxabmuODIWjZ1X5v/8Gz/qLcLNGdPDj8hToeBSodnYUMjsotXyCvgXgWKOlqHB2Dr7df447HefCdfM+Af6jNn6P1q1bh7///lsAn8KFC+uyRfLYOLaAuK/8bCD42SzBTxxvS7ydToKfeDNtyjgxb+AEP/QGEQixzEXjxo0FQLl9+7ZQpVVXC0xb6/D8vr6+YUCIHCMVEOJ54xMIbd26BVt3/A/BIa9QqXoIDt4vhtp7o3NHYlrLvTVn4bmvHBQV9KjT5esDnBgP1P/h+dHGaC89YOa9FuafnJCuhB3sxzRFxqr2Otvp7akb8Dl2H+n/HqXNqNGOUZRtAK/G75FWg4zRg/fA1CtmuPnVBPZFTDDgpyDUrBRZBLvBgPTIOaUbspTWTQMq4mSeuT3Bv2v/RdONLSPN8ft7P2yrvhZF+lRHhT80k8I/P/mAu80Xwcsxsn5KiAJo7GSK502qofKyrmHnfn3WG9dXX0a+P9rgwc+LcHbnEeTJE50kL7hImzdj6tSpQseHWleyJawFJPhJWPsbe3QJfoxt8WQ8Hm/o9PZ07doV9+/fF+GqKlWqiNBYw4YNDQ5f8fzUD6I3iF4h/l8VGqPsf3wBIWa4rV23Bgs2LkFwagukKZIFeduVRfY69rHq/jza7oVzGwsgpNJY3XdeH/CjGuVUTWD+KpjPGoFU7x8h90/VYNe/DszTaselCvzsh8u91iDL3sjp2touQlG7HY6VfQw7LbL0r78Cpl0zx0N/oFQpEwzqFoQKpYGuf1ojpO9PyFM7v7bDRjvO++AdPHP3QZ3ZjcI+Cw4Ixk7HLfj6IQjd78ZMqH5/8yXe9VyNk1V9w/qLlHYX4MQzoMHrhZGugev/c8bHz+b4dvQaPP85rjZVndft9u3bMWHCBKHcXKKE/iVM9DaM7BjNAuL+0cVAz8923Tw/379/F55xZsHS2y2b8SwgwY/xbJ0iRurXr5/gA/HmTqCyb98+4RW6cuUK6tWrh5YtW6JJkyYGeYNoSEFQ/fo1zCNEgKLKGqOmUHwBIY7NrLVl61fh7I0LCE5lgiy1CyJPqzLIVCYXTEwjc4X+O3ANboszI6TaNN33n+Dn+DigwSbd+x6rAhzzUPZj6fTVs5HKeSvSFbZFkfEtkL5seMkFTSc/12AGsp1Yp/vYAALa9MXuLJdRPodu3c8/BWbeMMeLIODrdwXy/dECpfpU0Hs/r628iuCv31BxhNK7w+tmX6s9SN+iCp5uu4hOp3+OcYKvPJ4Ag9dhb5VvYceNuWKO18GhuPjeEhW950Xqf7zpUgT6+OHqsTORanRFPGj37t2ibMXx48dRurTuMga6WVQera0FxD2jvYHgZ49u4GfkyJHi3nj58mUJfrTdqDg6ToKfODKkPI3SAs+fPxdvuxEVnfnAYTYXxQfJE2KtIpKkyRFq2rSpwQrPHJcZZSqOUEBAgFDF5TwIhLRNx9dnDwm6Dhw4gLX/bIb3yycwz2aDXM1LIlfTkkidKwNenLyDU9MtEFxzju6n//wMcB6jH/g5XAk4ehawiCLsePMKLOf8CWu/l8jbsyby/FIT5jbqY1Pnak9CtjNbdJ83E9X6TcBGv8NoEJ3qovX5+h4E9iI3LK3NkLNqbpTqVRaZS2bTCQidn+KBDAVtULxrGTGuy6CT+GqRHiXndcG5xnPR5mAHmEco/Bp1cj7H7yH76PVYXU1Zu2vFfXMcfAosaRSMFpfzoJJbeLHbd15PcL77Ztw6fVlj5XW+DLBQKdWbKfIpW+KxgAA/bQwEP/u0Bz8EPD169MC8efPQsWNHCX6MfClI8GNkg6f04QiEmNVFwECPkLu7O6pVqyZCYyRNsySGoV4bPz+/sKwx/k4gRK8QSdfxCYS4t1zb6nVrsOf0IfgGfYVJWgs88ykKtN4OmOmoME3wc2w00HCz7peNcx1gw1YgmwahvMBAmCyZglRu/yBjqSwoPK4N0hbLHWmcs1XGIJvHTr324+2UVZh3dQV+NsCxsfISsLRxDxQc1Bivjl6FzzJnhLz9iOzlc6Dsbw6wLZE11rmdHHQCRdoXEqGzywuv4J7LC1Q+qCxs6tV1DWpPrIgM9lk12vfh3n9R4X8bMb0KcOipKWZcN8W5nsFY+68ZVpZvilJjldl/vvdfw6PjBngddtfo8Tl06BAGDRqEw4cPo1KlSrrvqewRrxYQ950WBoKfQ9qBH7408RqgthMTPHj/k2GveN3eaCeX4Me49pajRbEAv/AHDx4UZGlqnDg4OAiPENPoCVoMBUIsgKriCDFMxoKrBELaFF6Ni83i293YqXNw5cErfE+TH4rSvZSlLkyVSsgxts8vgGN/Ag318L64dgGm/QGULB/bKIDXWaRb8QesFb7I28cRWTvWhJmVBS7UmYAMe5fB3FYL4k7UfV1/AEO2T8aoqrEPr+mI7TeAaQ6dYT+6VaRDXh25gsfzjkPx0Rc5q+RB2YFlkLmE+jIQhzvvQY2ZdfHh9ge4Tb2A6ucnhAHgG8O3oVjD7MjbWDPZ+PZaTzRfvws1cwN93c3g1ScEdBS13mcJy4OTkDp3Rnx79hFnWqyE67ajGjV6qCvVv39/ca1XrWqAUfQ3p+wZiwXiCvxEHGbixIlgTbSobebMmSJjdu3atULNW4If41+eEvwY3+ZyRA0WIEfoyJEjwiNEIijDAgRC/GEIy1AgxHCYSkcotsKr8bFJJIGPn7EAp7zuwD9NAShK/wLkd9QMhAwBP+eGAb/VBxx10CX69g2WS0Yj9WUnZK6UD77e75D67zGwLltEZ3N8c/FEq0mDsaiuMlykT3N6AAwv0BrFpnXS2P3V4St4PP84FJ98kbNqXpQdUDoSENrTaDtqzKgNpx4HUP3SzEglLrznHoZt2gCU6KcZjFyb44pmew9h2xMzuPUMQaYfQo0VtqRC6Xvz4P/+K041XoqDS3ZEK1CqmjSv5T59+giAX7NmhAK3+hhF9ok3C4j7SxMDPT9HY/f8EPSQ/0jhV3q6JfiJty2N8cQS/CSM3eWosViAHB6+LRMIkR9BgTgVEKJYoqFASFPhVXqbLKLyZOJhtwiExk6fD9dLd+GftiAUFEGMCoQE+BkJNNyq+wyuLQLqWwHd+unelz3cj8Fmam+YZ0wNmxJ2sGhUG1a1HGCRS3OIKOJAgY+fo2Kn9tjRJEC/8QF4PAW6p2uMkgt6aHWOlwcv48mCE1D4+iIXgdBvZXDyt2Pwe/cdDsdHI1XOyEVpn20/h9A791B5SmON5/cc54TXS07BtWcoCv6QqnrvB9Q4lhkV3MfCpfFSbJiwBDVrqAc19GaS10GuW506dbRahzwoYSwg7in1DQQ/J2MHPyxhQi9gmjRpxEJZLujLly8CCPHlr3Jl/YRFE8ZqSXdUCX6S7t6lmJkzHZR6QXxzJl+CYnAqIGRnZ2cwEIpYeJWK1EybV2WOUWAxvlsYEPK6C/90BZUeIbs6gN87wGmEfuDnyTEguzvwlx5ZZj8WnKVzIYx3Lo/Pr77j3OYnuOv5DV/8zWFimwnWjpVhXrc6rEoWhImZWTQTKYKDkadsTZxopz/4ufMWaBpQG2XX6lbZnZN5efASHi84AT9vH1T45w9krBidef3W5SY+bj+BOmvUe5ao8ePUZBUWFnuLbhG4yfvvmmB82qr4+PAj/tdrDNq2jl6ri3Nwc3NDt27dsHPnTvGmL1vitoAAP44Ggp/TsYMf8hDJDVQ1Dw8P4Rm8deuWuO8Y456TuHfCOLOT4Mc4dpajxJEFGLqiKBzfpMmfyJs3r4iXEwwVKlTIYCBEIiLrjTFzzNiFV2kiikSOnb4Ablfu47t1ToR++wy0cALMdARhX54Cb8cCi3QQSIyyR7m65sMUj+geDb9Pgbiw7Qmun/yAl88UCLBOByuHUkjdrCZSVS4F09RKLaHMJarDrf13vXf+1Veg4qOKcNinh0Dkj1Hdas5ELffRaufw6doTvJiyFfX/iV565OXZRzjfaxvyfPmIs/0Aqwhc9V+OWeKgf3aM6TkM/Xur96ydP38eXbp0wZYtW9CoUbjGkN7GkB3j3QLGAj9RFyLDXvG+tWoHkOAnYewuR40DC9BjwxsHgRDT6MkLIggiGKJirqGhMXWFV1WiivFdeJXmuXnzJob9NRU3Hr2Fn2kmhORrCRRoBaTWQjyHdcCuNgc2H9HP0m9foeTs2hi2xyHW/sxWuen8Eh573+DRnSAEWqSCmV0e5Dl9Eq6dApFRO13FaOMEBgN2l0uh8rHwdPJYJxPlALeaM1DLXX1/v6fvcb/nAjR1GRCp16NNnng8/Sgu1vmCtkeBk30jn7TiKhPU7T0Kk/4cr3Y6Fy9eRIcOHbB+/Xo0b95c1ynL4xPIAuJ+UdNAz4977J6fBFqeHDaKBST4kZdEsrAAPTZMm6eAHNPoGbqioGKbNm2Egq6hKe6qwqv0CFGzyFiFV1WbQ4L28hWrsXb3Sbz9okBQZgeEFuoEZHMATDRUo/eoD+w8od/+rp2HLnn2on5//dSVX97xxcoaR5EjnSnMTIEa+UzQpVAQymZHpHpfsU0u98WScDiqhzr2jxOfrTkJNdyjZ9vw42C/AFx2nIA2nkqVZ8owXBtzCJaHL+FUrW+gXmWd/YBrBOfO3lvA6mel8c/xHwKSURZAwbq2bdti1apVAoTLlnQsIMBPVQPBj4cEP0llxyX4SSo7JeeptQXosWHYgR4hispZWVmJBxF/ypQpEydAKCEKr0Y0AEN/s5ZswtW7TxFgmRMhBdoDdk0Bqwhp6a61gf2uWtst4oFpBtTFqPmpkbO4/kVF1xTZi/NNAkQx+n0PgfWPzPHSD2Cd0k5FFWiaX4H01jFPL/eFEnBwHqfXGtjpouMkVDqtHvzw8wsOf6Kt11CEBAbDvetm1PB5gJWVwnlK1f4Bzv+gHH38DtTbYo1T/75Uy8u4fv26uMaWLl2K9u2jF1LVexGyo1EsIMBPRQPBzyUJfoyyWXEwiAQ/cWBEeYrEawF6bBiGUBVe5f9VHqGKFSsaDIToLSAQUqXQ08OkCo3FZ+HViBZ/+fIl5i5cgd3HPODrb47gnI4ILdgeuNwbcFLvoYhtx7J0LoAZF6rC1NQktkM1fr62yF6cU5Pt5fMZWHwTOPPWHBamQC07oEvhYJTKGt0rlOd8UVQ8MVHvOXg5ToJDDODHs8poNDnaG6darMYwq+cYXDwkbKyAEKDOAcDjB/jpsscU7cdtR5Nm0UNZDFHyupo/f77g+siW9CwgwU/S2zNDZizBjyHWk32TlAUIfBiWoEeImWMUQKSYIt/WWYDVTE3Wki4LjFp4lX1VWWPxWXg14hy5xp07d2HB2r249d9dhFatCXQbCJSqoH28SaFAgV8LYaxLNV2WH+3Y9UX2wj2WVHd6hfZ4A+vvmeBtsCnyZQQ6FVGgcf5QpLMCcrvbw+HUZL3nERv48ag2FhZfv2J9gTeoH6X4+n+fgf5ngaM9gSP3gBXPymOnk3u0udy+fVtcR7NmzUL37t31nqvsmLAWEOCnnIGen6vS85Owu6j96BL8aG8reWQysoAg6d68KThCBEJMcecDjBwhltuIWJtMn2UnZOHViPNl+G/0giW48eIVAstWRWjH3oB9LFXE3Z3heGM0us0prs/Sw/qss9uBs60VOp3jyWdg4Q3g/FszoaR8yyY7qrpOgmUmpSaKru1crUmo7qY+7PX56mNcbj8Xl6u9R0E1ItYXXgFL7wFLWwB1Nlnh+NVnsLH5oXL4YyL37t0TpOapU6eiV69eBpPsdV2fPD7uLCDATykDwc8NCX7ibkfi90wS/MSvfeXZk4AFCFTu3LkT5hFiVXqVR4gFWONC9JClNVShMWMWXo1oflYRH7t0Jbw/fEJQlboIbd8LyBdd/8Zi/C8Y2P0/lGqkRVZZDPu7pcgunGoSrPcVEKwAih01RaBtFpjaF0ChcR2Qxl63OXnVmQQHXbju5wAAIABJREFU1+jg56PHfXj3W4gCNh/gpqHM1j8PAc/PwGs/U9Qbuhbt2neMtBYq9bIe3dixY/Hrr79K4KP3TieOjgL8FDMQ/NyR4Cdx7Gbss5DgJ3YbySNSkAUIhPhQU4XGHj9+LB5wTKF3dHQU5GlDm6rwKjPHKOBozMKrnDu9Xv/s24fJazfi6Td/BNVuCrT5GcihLGya8acSmOJcAjbpddQWimKYrUV2wcUA8MPT1fAyg8uJEFzwBH6faosPltmQf2RrZK5bUiuwoQ78fDxzC96/L8Nl5w/o1xdYmx3IHNmhI1ay4Dpw7zvw2Lw4/nHxirQ6XhdNmzbFyJEjMXDgQK3mYuh1I/vHrwUE+ClkIPjxluAnfncp7s4uwU/c2VKeKZlZgECIDzkVWZoChE2aNBEcISr2xoXWT0IXXiUQ2rhpM2Zu24nXwaEIbtAGuY7PxhRPw0sxbC+yCyfiCPyoLq2XL4H+Y9Pi6n+ZkLtPQ+T+uRZMGR/T0KKCn/fHruHpX6tw6fhHsLrAiMHAz75A5ezRTzDUHTjw1Ayed16ElSLgUU+fPkXjxo0xePBgDB06VAKfZPK9l+AnmWyklsuQ4EdLQ8nDUrYFCIT40CM/iGDoxo0baNCggQBCDRs2ROrUqQ02kLrCq8wcYwV6QzlI2kyO9c6WrVyFldsWwSajAiUbZ4ND57zIbKcf32ZHkV04biD4qXrOBK5nor+NBwYCY6dbYtcpW2RwLIcCf7WCVeZ00ZYZEfy83X8Rr6esx6WTn2D9I8X+7xmAvRfQyT66hertB9qNnIeefX4N+/D58+dCsZm1mej1MVRIU5t9kccYxwJiL/Mb6Pl5LD0/xtktw0eR4MdwG8ozpDALEAiRF0QNIYKhy5cvC08QU53pGWKKu6FNVXiVoTGm0mfMmFGk0Bur8CpFIzdu2ojN+1bB1/8dCtWyReWf8iFXyfRaP/B3Ft0F58b6c35ow5pngZNuMVtzw2Zg9mpbmBTMj3yTOyNt0VxhHVTg5832s/gwfwsuHvdFxHJtGzcAvluBkeUjj+H2HJjyX2EcdL8W9sGrV68E8OnZsyfGjBmjtR0MvRZkf+NYQICfPAaCn6cS/BhntwwfRYIfw20oz5CCLUAgRMVnltcgT8jT0xMkSZMjRE5Ihgxq0oh0tFdCF15laIwFZVdsWYiX7/9DzjJpULW7HQpUyaxRB4h22V1sF441DtfN0XHZ4vA65wDnM9r1vOgFDBufHm/MsyLfX+1g26A0LjlORp7uNfFt9S54OH+GeZQI2dFjwJlpwPzq4WP4BQG1Dljg4OUnYftHEEpg27lzZ0ycOFECH+22JEkdJcBPDgPBz0sJfpLKpkvwk1R2Ss4z0VuAD3xWa2Z5DYbGWG6DafMMjZE0nSlTJoMfmvTIvHv3TmSOqQqvqjxCLLlhjMYq1PNXzsJ9n5uwLWCNKj/nQ7F62WBuGV7dPSggGIfK7sXhRsYDP6q1v3oNDB6ZCl5PbPHlQwCK5A6Au9NnUa4iavO8CKwZCmyKUL91wBkTlOm7AN179xGHE9xy/+jZmz59usF7aIw9kmPobgEJfnS3WVLuIcFPUt69BJg7vRDDhg3Dtm3bxOhdu3YVqrbG4KQkwHINGpLhKlaeZ2js9OnTcHBwEB4hptEzfGUoXyShC6/SOCSBz1n8P1y+fR6pc5ih8k95UKppTiiCQ3Gy2j7sb2gg+DkPOOtXoQPkBVWtAnhdglrgw/l7ewOjuwEHayu3+uwLYOKjgjh07l/xfwJM6viQ10URQ0NrxBl0QcnO8WoB8X3MbKDn5530/MTrJsXhySX4iUNjpoRT0eVPz8bRo0fFchkKYCHHCRMmpITl671GFiY9cuSI8AidOHEC5cqVE0CIP/TcGAqEohZeZSaaSl06LsjY2iycZTbmLZqNU55HAetApL3/Cv80AXIbQIGqYwD4UV6fwI9LVe0SPn4EOjcAXOsB34OBmgx3XVKGu1TClzVr1hQAXwIfba6CpHuM+A5mNBD8fJTgJ6lcARL8JJWdSiTzzJMnj3gQqAo3UiH5jz/+wH///ZdIZpj4p/Ht2zcBHgmEjh07huLFi4cBody5c8cJEOKDWyWqaGlpKYAQQRaBkKFASxsLU9RxzqyZ8DqxF4GfXqNkhmC0L6hArVyAlebM9Gin1oXzo25eLVoBhw5onjHLa9RxADzrA7+7maBYr9no1W8AfH19RZiL3rolS5ZI4KPNpifxY8T3Iq2B4OeLBD9J5TKQ4Cep7FQimCcfqOStPHjwAIUKFRIz4u/29vYiI4n1q2TTzQIUOXR2dhahMZKKCxcuHAaE7OzsDAYqiaHwKi3CjLh1i+fgjpcr0sIPjfMEo1UBoFAsfHBDwU+bdsC+vTHviWMVYK49MNY7Pw6fv4kvX74InlapUqWwYsWKZAt8GDY1tJ6dbld74j5agJ9UBoKf7xL8JO5dDp+dBD9JZacSwTypc5M3b15BAKX2DBt/p1eBn9FrIZv+FqDOj4uLi8gaI1eItuZDmKExgk1DPTaJofAqrUNhx61btuDwlqX48soHBdMECq9QvTxAmiii0oaCn46dgU0bEKbro2536tcE/F9aYN/FR6CXrF27dsLea9asSbbggMR58vQoqbBw4UKRwl+6dGn9L95k0FOCn2SwiTosQYIfHYyV0g9VeX5Y/qFgQWVNKP5Ob4X0/MTt1UFiuaurqwBCTKNnyIogiGCoaNGicQKEGJpiCjfDY3wYqkJj5LsYCrR0sQZJ06uXzMN1NydYB39BnRwhaFMwFCVtAXJ+jmuZ6q5uzB6/ALNmAtmzqZ9RaChQoybQvdss/NT9FxHOJYjfuHFjsgE+5INF5Cup/k/PD7lnZcuWxcyZM5EzZ86wfY/aR5f9TKrHimve3EDPT7D0/CSV/ZfgJ6nsVCKZJzk/CxYsEG/HbHw4Dx8+HD4+PolkhslvGgQmTJtXASGGF8lHYQX6EiVKxElYRlV4lWCI3gBmoxFwUVzRmERfrvWfvXuxb8NivHlyF+/MvmPpMqBWTYDPJl1b/9+A4UMBezUKzswG6/+bCUIUdbB06W506tRJeDS3bNmS7LIXKcrJUi2UXlABW2YdMoxNoMf28OFDkJhPQMRGT6ExQbCuexvXx4u1mhgIfkIl+InrfYmv80nwE1+WTabnZVYXuSlOTk5ihRTyozdCZnsZZ8P5tn7+/PkwIMQwDe3PnzJlysQJUEnowqsRLXn//n3MmDEEjx9fQKMGQejTOxQ5dCjsPuwP4KcugEOFyPvz7h3QpZsZ2rSZgp49B6BLly6CDL5jxw5YWFgYZzONOAqrzleoUAH9+vUTo5LQzReYadOmoUqVKvj555/x5MkT4QkkQNqwYYMRZ5c4hlICPQPBDyT4SRy7GfssJPiJ3UbyiAgWYDiGxRwj6vzQEyR1fox/mTA0cfHixbDCq/y/yiNUsWLFOAFCJGSrssboHaJnhB4hW1tbo4aFuLZt27Zg08ZJsEn9Dn17h6BpE0RTbI66C2PHAfUbAI4/dHz4+Z07QK8+lpg16yAqVaosHvz0bjFzkWAyubcrV64IoExAtG7dOuFBZOmOTZs24eTJkzh16hQ2b96cImwRca8l+EnuV37k9Unwk7L2W642mVqA4IAPNYbGmDlG0EIgRI8Q3+zjIqsnoQuvqraOCtfTpo3A1atHULGCP37/LRQ/kg+j7e606UCZ0kCLFsqPWM5i8tR02LXrkuA4sU4X18U6bVZWVsny6uC1wQc7f2bPni3C1uvXr0f16tWF+GaaNGnE7/R4TZ06FW5ubjh06BCMpRieWIwuwU9i2QnjzEOCH+PYWY4iLWA0C/Bhd/PmTeHJIBBSifXxDZ8hjbjw0kUsvMoQCrlBBBPGKryqMubx48cxe/bvMDV5hW7dQtCxPWBjE27qufOBHNmBLp0B/n7SpQD27bssPD29e/cW4R9m1iXXB726dHaum0CZpToYtmYjoGRa/7x58wT4KVmypNGu18QykAQ/iWUnjDMPCX6MY2c5irRAgliApNU7d+6EeYRIfCXRlR4hFmCNC34LQ6GUPGB4jLXNmC2mUpeOzzASQd6///4rPBrMPpw7dypOndqAwoX88PtABcqXA1asBGACXLpkAkurpliyZJfIbGPIh/wW8tdsIqKlBNml+B907ty5IrxVoEABMRi5P6zRNmPGDDBEeu7cOZHxxfR+Ep5TogaQBD/xfx0mphEk+ElMuyHnIi0QjxYgEKI0gSo0xuwfFuxkCr2jo2OchH2MVXhVBXxoLurTRMxIu3btGmbMGIR3724gXdog3L4NDBs+FQMGDBcP9YEDBwpFcpYbYcgnubcbN26gbt26uHr1aiQtrt9++w0XLlzA6NGjwRIeBMLkcqVE4MNrQIKf5P5NiLw+CX5S1n7L1UoLCAsQCBH8sMQGQ2PU2mGdNnqE6tWrB9YGM7RFLbxKoKHyCBlyfgIfPtC5hqjAJ+KcedysWTNQpkw5NG3aDPz/kCFDxFpZXiRdunSGLjFR9lcHXghuKGZYvnx5IWWg8sj98ssvIFgkyZkeu5TclOAn0EATWIrrUrbEbwEJfhL/HskZSgvEqwV4s6ZCN0EQwRCBRYMGDQQQYjXzuCiMqqnwKjPHdAk7qYAP/9UltZ/HjxgxQjzoyRNKCaVYmLGVNm1aUZ+sRo0aIkuT4C9qo0YX1cRTelOCHz8DzWAjwY+BFjRWdwl+jGXpJDZOShM4S2LbE2/T5b6TF8TsJ4Ih1uSiJ4iZY/QM8WFqaCMQ0VR4NaYwlIrITc+GrsDnr7/+EhwXpnKTnJ3c261bt9CtW7cwYHnp0iWhxE7OD4EOOVJUsu7QoUPYwzolCRqq23/l+n0NvDTSS/BjoAWN1V2CH2NZOgmNowI+5IbwgRcXb/5JaPlyqj8swOuARGaW1+C14OnpKUjS5AgxSyguwiRRC68yJV8VGiPQUj2QVcCHnCICH21T99lv/PjxIqWbddPIaUmOTV2oS/U9Jpg9cOCAECalF4gqzrdv38aUKVME2Vk2pQWU19p7A81hK8GPgRY0VncJfoxl6SQ2DomxLJ1AvQ+GPmRL2Rbgg5SZXHyIMjTGchtMm2dojKRplkkw1HMQU+FVhmZ0BT483+TJk8VDn+CHafjJsUWsw7Vo0SKR3Zc/f34RulSVqqCuz9KlS0EPEBsz9Ehwlh7e8CtCgp/k+O3QvCYJflLWfse6WtWNdM6cOYIUSpl71vOSN8lYTZeiDmAhW+rjMDRGYEEPAoEQ0+gJMuICCKkKr5KPxOuShTezZ88uPE6xnZ/XK1O3CdQ4P/ZL7q1Pnz44e/as2ANmceXIkQM9evQQ4JSlK5jqTkVwgp6UWLg0tv1XXlOvYjssls+zS8+PgRY0VncJfoxl6SQyjgrkMDukTp06GDt2bCQBOLrXeZMwZrHLJGK6FDtNhlGYNk6gQU4Nq4QzNMYfEppjAyqaDMdrkdwVKjCTr0IhPlXhVVVoTF3hVfYjeN+6dStcXV0FaErubfXq1Vi8eLEAPSSQs9YebUDvz+DBg4VoYaVKleDs7IwiRYrovSfJ2Y7K6/SpgUtUvijKlvgtIMFP4t8jo8+Qb9rMDqHgGW+ebPfu3RM3TdmkBWKywLdv34THkEDo2LFjKF68eBgQIsFWWyDEBwh5KSzTwdBNRI6PpsKrzOCiV4Mp3axZReDDMZN7o61YiZ7rJzF9+fLlItxHxWaWq+CLSv/+/cV3WWZ1ab4alNfmYwMvl/wS/BhoQWN1l+DHWJZOAuOoXOGUuGdpBD68WPCQPAK+UVIYrnnz5kIWP1euXJFWxL68CWtLRE0C5pBTNNACBC70NDA0RiVlem9UHiE7OzuNQCgm4BN1SqrCq48ePcJPP/0kwBZ/P3PmDIoWLWrgChJH9/fv3wsbMtzXvn17tXYjH+rLly9CZZsAaOXKlcJzSyHDZ8+eYdKkSULjRzYJfuQ1oLSABD/ySgizgCrkxZtm1apVxVsjs70IaGbNmgV7e3t07dpVFMr8888/RT8ZBpMXkDYWYOiK2VbMGiNXiB4IcoQIhgoVKhT2QFeV46AHiQ9rbcE0+xG0M9RF8jXDZSTqs1K5IYKK2qwtvo/hWpiSTm/sqlWrYhyOYUd6fUhIp6bR8OHDBfepcuXK8T3NJH9+pefnvoHrsJeeHwMtaKzuEvwYy9JJZBymxRL48M2RxFXecEmWJHeDjRWhmQHGhwq9PyRYMsxA3Ra+ef/888/R6kVFTMNl+IwPQirzStJlErko4niazDRiSIpAiGn0vLYIgkjUJYDhNde9e3etC7AS+DCbiQCdSsUqfhDBVqdOneJ49sY9Hb97FGds27atKD9Cz09M7fnz50LDh2CHdc/o8VEnbGjcVSSN0ZTg57aBky0uwY+BFjRWdwl+jGXpRD6OCogwHZZvzySwMq2ZWiAMI6g+5wOlV69eePDggbgZM3uEn/FfZoaRVMkHmDrVXr7Njxs3Tijs8m2Wbnq+nZJcLVvKtADDNfRSMMy6bds2UXKCXo6OHTsKqYXYiPUEPlQyppeS12ZyCXXxauCLyIABAwSA44uFqu3cuVPwoOiJVZeFyfIdBJcUNFTJVMhszdi/X0rwcz32A2M8oowEPwZa0FjdJfgxlqWTyDh86y5WrBiYPUIQwxstvTskkvr7+4siiFT9dXNzEytS6YXwd3p/mBZ//vx54dkhuNm+fbsIjfFNnvwM3sgpkMe3WZ6XGSnz588XuiSypUwL8MH8+++/48qVK5g4caIgTNMjxPpTDI3xR5OiM68vihieOHFCgKXk1Bge5AtDly5dxLIIFM3NzYVXh98h2kqbJoGPNlZSiRxK8KOdtZL+URL8JP09jNMVkFxJfZV8+fKJ1OLOnTuLhw+Jk6NGjRKaKSwVQPc7s8EYZmC1aGaSkAvEv5EQzVAG+6o8QEyHZm0h3rD5hs63UlVT3ZzlTTpOtzLJnIxhUHoE+aOquaXyJqoKr/L/JPJSq4aaQvQIMWxG7hk9iQTbybnxu8EfrpsvJvScMgQtW9xZQOn5uWzgCStIz4+BFjRWdwl+jGXpJDqOKvRFrw7frPv27StE0/h/aq0wTEb3O9/WmWJLdzw9OfydWSYMZ/CBxlAawRNBD71GBEN8sNGdz/BZxMYHHW9E2qZFJ1HTymlraQFeD/QKEeww64keROrWeHl5CeCTErKYIr4Y0GPK0CAz2vjdky1uLKC831ww8GRVJPgx0ILG6i7Bj7EsncTHYQiLb+iZM2cWKyFxmSCI6fDM1mEjT4OcDYIc8nh27dolakGxEfCQtEnRxGHDhgnQ9L///U+kQjM9maUT6NYnoFI16QlK4hdNPExfVeOLHh9mHpJgn9wbXxKWLVsmyMt8uWDxVxLE+V0ix05+T+LmClCCn7MGnqyGBD8GWtBY3SX4MZalk+g4mlLZ+fbNlNq5c+eGFT8lT4PCaswW45t5YGCg4PswXZkg6ddffxVgh6RUhjDoBWIYjCq9DKUxTbdfv35CxZcVqdXxgOSNPoleSHLaeluAoWiGkAl6+KLB7wxfHPgCwhcM6SHV27SROirteNrAkzlK8GOgBY3VXYIfY1k6mY5DQibd8I8fPxZ8oIEDB4pyAuQJEQiRQE0wM2PGDCGUyMrgDHmRo0HgRA4HeQz169cXoQ2+zTJFl2CJZNa6deuqtZxMk0+mF5RcViQLqK5zvkRs3LhRfC/4/SAJ+v79+yKcLFvcWECCn7ixY1I5iwQ/SWWnEtk86YHhjTmiCB1v0Pxhlg6zuajqO2jQINy8eVOIs1GHZeTIkeImTl4QU5sZ8uJNnIRpirGpUnr5psvCjOzD87GdO3dOCNgxG02fJgGTPlaTfRLaAhG9nfQC8bvDFweGofnCUbt27YSeYrIYXwl+Thi4lgbS82OgBY3VXYIfY1k6GY8TMRNFtUz+bceOHSKziyEwgh56dkqVKiW4P/QOUUOIYGbatGniJq6qIE9+ET1F1CvZt2+fIFczU4y1nnx8fITrnyU3KPdPQTd9mgRC+lhN9kkoC0QN9zLLkl5S1uxi5XYZDjZ8Z5Tgx8nAEzWV4MdACxqruwQ/xrJ0Ch+H2j/VqlUTmTpUjiaBk4RVeo5IjmbYiyRWliJgDTHe0Flag+RpKtQSRDEMRvDETDKm+5IkTQVcTU2lQUTANHv2bCHOmBIyg1L4pZaslx8RtFOFnZwf8ugYOo5NEDJZGyYOFqcEPwcNPFNLCX4MtKCxukvwYyxLp8BxGALjDVlFyFSRn8n7YbVtlsegUjQF7JhSr6ogz7daAhUCHtaAIvGZJTRU0v78O7lC9CZR4E4l/qbJxDy+Xbt2gnNEsjXT9XmuRo0apcBdkUtO6hZQXe9UR//7779F+Fg2wy0gwY/hNkxKZ5DgJyntVjKcK7WAGB6j8jPVof38/ATPh/otHh4egg9Ejg+9OKo3W3J/mA1GTxCFFSNWlOfxDJXxgUBQRe4RgRUVgFlGgc3JyUlkmDErTTZpgaRqAXpHWXpGdV0n1XUklnkrwc9eA6fTTnp+DLSgsbpL8GMsS8txtLLAp0+f0KdPH8HlIQiiPtAvv/wiyNP02hAcLV68WNRzIpE6amMWGb1K7EPlaZ6P3CHqDWkqByD5P1ptjTwoEVmAXlQKPtKjyZcCyfkxfHOU4GeHgSfqLMGPgRY0VncJfoxlaTmOWgtoAh7MZFEpPxMMvXnzRmibsN4RCdIkerIuWMSQFz1I1AkiQVqVhUYROOqhUA2YarhUxqXGEFOFWScpYtOkaSS3TlogMVtAFU5OzHNMCnNTgp8tBk61mwQ/BlrQWN0l+DGWpeU4Wlkg6hss/09SM6t2s54RydGbNm0SVecdHBxEyEtVCoNp8vyd2if8Owux/vHHH7h+/bpIk6e+EL1HJD8T/PCNmd4g8ovs7OyizU96hLTaMnmQtECysIAEP8liG7VehAQ/WptKHmhsCzCbiyErZomx0ctD7w9DYCQvq5oKMNHLQ3HFMWPGiI8ImghsKLRI8MRUeqbIExyRR0S+BNPm6VliiIw1yMgjYjZaxCZBkLF3Xo4nLWB8CyjBz3oDB+4lPT8GWtBY3SX4MZal5Tg6W+DVq1dCMfrhw4cCoFy+fFmAFGZ5MU0+KighsKECLgnNbEydJ9Bh0VVygVgPicKJ1BCivhA9QMyWYcX6nj17Cu9QixYtRFV71lNinTFyKiwsLHSeu+wgLSAtkLQsoAQ/qw2cdF8Jfgy0oLG6S/BjLEvLcfSyAMtnMMzFjC2Gprp3747KlSsLTk/UEBkzx5gFdufOHTRt2lTwgyiwyOrX1BeimjRJ1AQ07E+PEstnUEsobdq0Yn5UmSZYYhr+06dP8fbtW1GElTpEUVvELDN+pi5kxxuqJKPqtfVG68RMQhbbVaWME1hTRTkqJ8xoE5IDJYgFlOBnmYFj/ybBj4EWNFZ3CX6MZWk5js4W0AQmYjsRw1kvXrwQAnD02rAUAENeqpIaJUqUECEvR0dHrF27NgzYEDwVLlxYFFitXr26GGbChAkCAPEcFGDkDZIZZ+QLWVtbR5oKOUUkZquq3Mc2T/l54rAAeV8E1wS9bBTXpAo59162lGMBJfhZZOCCB0vwY6AFjdVdgh9jWVqOo7cFtM3CiiqqyAFV2WAMgbHAKjPEyOmhB4jaP+vWrRNCimwESEyRZ1YYPT0UQ2R4jLWTGHKjNhDDYeQc8f82NjYiXMYfAiEWcqWXiB4nCjOyACW1WHbu3CnOKVvitAD1pQiMVSKau3fvFkR5Ko3LlnIsIMFPytlrrlSCn5S13ylmtfQaiQtcvM0pG9PnWSSVf2PojAKJJFDTo8PGNHm2cePGibpJrq6uePnypSBCs6AklampCs00e3KR+DlDcgRQ9Byw3AD1hAiAVI39GVJLkyZNirF9UlooZREIcKk0rvLY8XeCVWpEce9lSxkWUN4r5hq42BFae35kuNVAUxvYXYIfAw0ouycNC0QNofHBRj4RuT2qxmrze/bswaFDh8L+Ru8Nw1nMGOvYsaMgWfOYiOCGJGqqSjPVnuEwcpPoWSLAipo5pg6UJQ0LJs9ZktdFzx9Dm5kzZxaL5O8ku/MzCmbKljIsoAQ/swxc7CitwY8MtxpoagO7S/BjoAFl9+RjAYbIfv31VxHuINBp2LChKKtBHhAbH4gESOSEqMJpKlDFFHl6fOgF4sOTniCGyAiUypUrF81I7McfWYwyYa8flefH29tbqIqz8XfuufT8JOzeGHt0JfiZZuCw47QGPzLcaqCpDewuwY+BBpTdk4cFVCCGWWEMZbF8BoEP+TwDBgwQ3h96cvi21rlzZ6hUdVXp9o0bNxahEqpPp0uXTvzL1HmGwuhZ4PkJqs6ePStqiqketBGtl1yzwpYsWSL4VDdu3BDAcf/+/YnqouFDaMGCBSILkI2Adfjw4fDx8UlU85STiV8LGBP8yHBr/O6lNmeX4EcbK8ljUqQFAgMDRWZXhgwZxPqXLVsmNISoHUQuCD8j6dnX1xdly5YVD1DqBNGbU6FCBVFKY8iQIYJTxMwhcoSYYs9U/Hr16olK9apQS0QDa0vwTiqbwhpUtAmz6JhRl9jAD/eGJHaVPhRlEiiWKbO9ksoVFjfzZLjaUJI77wu8H6gaX5YmTZoUbYIy3Bo3e2bIWST4McR6sm+ytIAm8MH0eZKh+TDnjZI3NT4kWVOMgon8l+ES8oRYP4weJBKgWVuMGkP8nICIjRpDBEasZs/GzDMKMWbLli1Z2pSLor2uXbuW6MAPPXxDhw6NpPNDICt1fpLtpZjgC5Ph1gTfApntlfBbIGeQ1CzAUBeVpKkXlC9fPjg7Owul6MmTJwtiNIUST58+Lfg/JMwSMFFDhunxfNDSC0KV6nfv3gkOEd3tPA/T6+kZojbRoEGDRB0ybRsBGzWGSL5OrC2xgp/Eai85r+RtARluTdj9lZ6fhLUKn9izAAAHyklEQVS/HD0JWSCqorNq6l++fBGlNEh6pjdn9erVIh2eWjEMi1EniB4g1hcjUZoAZ/DgwUJokQVa6Q0h8ClfvrxQm6bHiH+jN4gka23a/fv3MWLECJFST9VqepHoWldp12hzjvg+RoKf+LawPH9SsoAMtybsbknwk7D2l6MnMwsQtFAkj3pABDxsvXv3FgRpkn7Zbt++Lci19P5QVJEgiRXrGWopUqSI8OAwbEYARcJ1bC0iUZq1z9zc3IRHiURrZqBFTOeP7Vzx+bkEP/FpXXnupGYBGW5N2B2T4Cdh7S9HTwYWoEeIP5o4IiQ4s+YYM8IcHByEB4icIdaSsrKyEqnw1AiiN4j/ZyFXVqNnMVfWMtOnqjxDcAzLcczEIrAowU8yuNjlEqQFkokFJPhJJhspl5E4LECgQg6PSlla5ZWhOjQ9Ox8+fECzZs2E54ceGZKjGZoiP4h8ITZmHTG9nn2yZ/9/e3cPC2sWBnD8NEoNkruRKIhKCIWEREWtmUpELyJahYRGQiFBI74SUat1Eioh0SkkKkSiENEgQbf5n92RWTvjY9018zr/k9xi986dec/vvMWTc57zPH+82RiVZGo+z/ex05O/gl8ZGn89BUd9/OH6P/Ol5xp5T1TbdiiggALlEDD4KYe6v6nA3wIcedF1ngrRJEdTdXpmZiYcHh7GpOm3Rn5HiF2k6enpl10i6um0t7dXjDE7PuxEFQ7yoLj671BAAQXKIWDwUw51fzM5gVLJ0iQqX11dxavvHHlRXZidoLGxsZjvc3x8HGsGvVUAMZfLxYRp8oQozkfeD+018kX7XmOXepbkFsUJK6BAsgIGP8kuvROvRAGCH4IedoKoJzQ/Px9vkREAFY7CPCCKJXLTi9tiBFF0rudGWWFT11Jz/S/5RJXo5jMpoIACnxEw+PmMlp9V4DcLlNrR4Zo6OznsAHFbrNjgtghHStQZenp6Cqurqy95Q8U+z2cIlLiRRhXjwcHBfyVplwqGfmrrjd+8nH6dAgpkRMDgJyML5WOmIZAPPqgmTW+wfEXowtlzFZ6Ah1tj7Ajlj7s4InurLhABFblE5+fnsdo0bTdItH6vmGI+ifr09PTdz6axSs5SAQWyLmDwk/UV9PmTEzg4OIhHWzRYpfs83cepKUQz1s8kOvNv+MMtLAa3sLiBRcuOYoMkZbres2P0kSO15BbGCSugQGYEDH4ys1Q+aEoCn8nF4fiLbultbW1hcXGxaHI0u0UUWdzd3Y3d56lEza0yrttTaZagh4KIBEDb29uxMz1NSGnqWlgn6Pn5OSZmOxRQQIEsCxj8ZHn1fPYkBYrV8rm5uQkPDw+hsbGxqAmVpDlGm52dDTs7O7G5KAEWV+1pqcF4fHwMTU1NYX9/P+4mkXjd3NwcAyJqDrGrVF1d/fL95AHlgzR3gpJ8FZ20ApkVMPjJ7NL54Aq8L5BPVGZnqKurKyZIM6guvb6+HnuSkfzM5xjsCNEeg3pD5BsRLDFqamriTtHw8HC8SfZ6Z8qE6PfXwk8ooEDlCBj8VM5a+CQK/G8CW1tbL53i+/v7w8LCQuju7v5H7y+6zhPg7O3thbW1tTAwMBCfh/+myzw5RVynv76+DisrK/EIjfpC3EajQKNDAQUUyIqAwU9WVsrnVOCLAnd3d7F+0O3tbbz11dDQEIMgjtEIjtgFIoF6c3MzVp2mMzxjdHQ0cKxGwFNXVxd7jlFFenJyMv4//m5ubi709vZ+8Qn95woooMD3CBj8fI+zv6JAWQVeH1ORJE0SNAnP5P3QiZ5dHxqwDg0NhdbW1jAxMRGfuaWlJe78EPRUVVXFCtS1tbVxd4hBYUZ6dZEv5PFXWZfZH1dAgQ8KGPx8EMqPKfATBF43XmVONB29vLyMwQtjeXk5BjbUDWIHaGRkJB55dXZ2xr8/OjqKSdLc+pqamgo9PT0GPT/h5XAOCiQkYPCT0GI7VQU+IkARRK69j4+Px4apJycnsdUGN73oSv/r16+Y98NO0cXFRawsXV9f/5Gv9jMKKKBARQgY/FTEMvgQClSmAAUV7+/vY2Izgc/S0lLo6+sLFDwkACLPh8KH3BJzKKCAAlkRMPjJykr5nAp8k0CpAosEQVSD3tjYiInP1P2hZQbHZB0dHR59fdP6+DMKKPB1AYOfrxv6DQr8WIFSgRCFEs/OzkIul4vHYA4FFFAgSwIGP1laLZ9VgTIK5Cs6U+TQoYACCmRZwOAny6vnsytQJoHP9B4r0yP6swoooEBJAYMfXw4FFFBAAQUUSErA4Cep5XayCiiggAIKKGDw4zuggAIKKKCAAkkJGPwktdxOVgEFFFBAAQUMfnwHFFBAAQUUUCApAYOfpJbbySqggAIKKKCAwY/vgAIKKKCAAgokJWDwk9RyO1kFFFBAAQUUMPjxHVBAAQUUUECBpAQMfpJabiergAIKKKCAAgY/vgMKKKCAAgookJSAwU9Sy+1kFVBAAQUUUMDgx3dAAQUUUEABBZISMPhJarmdrAIKKKCAAgoY/PgOKKCAAgoooEBSAgY/SS23k1VAAQUUUEABgx/fAQUUUEABBRRISsDgJ6nldrIKKKCAAgooYPDjO6CAAgoooIACSQkY/CS13E5WAQUUUEABBQx+fAcUUEABBRRQICkBg5+kltvJKqCAAgoooMCfZVhPY7h9L/oAAAAASUVORK5CYII=\" width=\"638.888905813665\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PATCHES\n",
    "vertices, emap = model.get_Poly3DCollection(deformed = True, \n",
    "                                            step_label = step_label, \n",
    "                                            frame = frame, \n",
    "                                            displacement_factor = 1.)\n",
    "        \n",
    "collection = mpl3d.art3d.Poly3DCollection(vertices)\n",
    "collection.set_array(F.loc[emap] * 100)\n",
    "collection.set_linewidth(.5)\n",
    "collection.set_edgecolor(\"black\")\n",
    "collection.set_cmap(mpl.cm.jet)\n",
    "collection.set_clim(0., 20.)\n",
    "\n",
    "# FIGURE\n",
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(1, 1, 1, projection='3d', aspect = \"equal\")\n",
    "ax1.add_collection3d(collection)\n",
    "#ax1.axis(\"off\")\n",
    "ax1.set_xlabel(r'loading direction, $\\vec x$ axis')\n",
    "ax1.set_ylabel(r'$\\vec y$ axis')\n",
    "ax1.set_zlabel(r'$\\vec z$ axis')\n",
    "offset = .05\n",
    "ax1.set_xlim3d(-offset, 1. + offset)\n",
    "ax1.set_ylim3d(-offset, 1. + offset)\n",
    "ax1.set_zlim3d(-offset, 1. + offset)\n",
    "ax1.set_xticks([0, 1])\n",
    "ax1.set_yticks([0, 1])\n",
    "ax1.set_zticks([0, 1])\n",
    "cbar = plt.colorbar(collection)\n",
    "cbar.set_label(r\"True Strain Tensor, $LE_{11}$ [$\\%$]\")\n",
    "cbar.set_ticks(np.linspace(0., 20, 6))\n",
    "plt.savefig(\"model.pdf\")\n",
    "plt.show()"
   ]
  },
  {
   "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
