flame_speed_with_sensitivity_analysis_176.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Flame Speed with Sensitivity Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example we simulate a freely-propagating, adiabatic, 1-D flame and\n",
    "* Calculate its laminar burning velocity\n",
    "* Perform a sensitivity analysis of its kinetics\n",
    "\n",
    "The figure below illustrates the setup, in a flame-fixed co-ordinate system. The reactants enter with density $\\rho_{u}$, temperature $T_{u}$ and speed $S_{u}$. The products exit the flame at speed $S_{b}$, density $\\rho_{b}$ and temperature $T_{b}$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"images/flameSpeed.png\" alt=\"Freely Propagating Flame\" style=\"width: 300px;\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Cantera Version: 2.5.0a2\n"
     ]
    }
   ],
   "source": [
    "from __future__ import print_function\n",
    "from __future__ import division\n",
    "\n",
    "import cantera as ct\n",
    "import numpy as np\n",
    "\n",
    "print(\"Running Cantera Version: \" + str(ct.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import plotting modules and define plotting preference\n",
    "%matplotlib notebook\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "plt.rcParams['axes.labelsize'] = 14\n",
    "plt.rcParams['xtick.labelsize'] = 12\n",
    "plt.rcParams['ytick.labelsize'] = 12\n",
    "plt.rcParams['legend.fontsize'] = 10\n",
    "plt.rcParams['figure.figsize'] = (8,6)\n",
    "\n",
    "# Get the best of both ggplot and seaborn\n",
    "plt.style.use('ggplot')\n",
    "plt.style.use('seaborn-deep')\n",
    "\n",
    "plt.rcParams['figure.autolayout'] = True\n",
    "\n",
    "# Import Pandas for DataFrames\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the reactant conditions, gas mixture and kinetic mechanism associated with the gas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Inlet Temperature in Kelvin and Inlet Pressure in Pascals\n",
    "#In this case we are setting the inlet T and P to room temperature conditions\n",
    "To = 300\n",
    "Po = 101325\n",
    "\n",
    "#Define the gas-mixutre and kinetics\n",
    "#In this case, we are choosing a GRI3.0 gas\n",
    "gas = ct.Solution('gri30.cti')\n",
    "\n",
    "# Create a stoichiometric CH4/Air premixed mixture \n",
    "gas.set_equivalence_ratio(1.0, 'CH4', {'O2':1.0, 'N2':3.76})\n",
    "gas.TP = To, Po"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define flame simulation conditions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Domain width in metres\n",
    "width = 0.014\n",
    "\n",
    "# Create the flame object\n",
    "flame = ct.FreeFlame(gas, width=width)\n",
    "\n",
    "# Define tolerances for the solver\n",
    "flame.set_refine_criteria(ratio=3, slope=0.1, curve=0.1)\n",
    "\n",
    "# Define logging level\n",
    "loglevel = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "************ Solving on 8 point grid with energy equation enabled ************\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.136e-05      5.452\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0003649      4.427\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.435e-05      6.061\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     3.468e-05       5.63\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.001333      4.122\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [9] point grid(s).\n",
      "Expanding domain to accomodate flame thickness. New width: 0.028 m\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 4 5 6 \n",
      "    to resolve C C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 N2O NCO NH NO NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "*********** Solving on 16 point grid with energy equation enabled ************\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.136e-05      5.751\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     4.055e-05       5.58\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.887e-05      5.947\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.055e-05       6.11\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001756      5.504\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     1.172e-05      6.764\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [16] point grid(s).\n",
      "Expanding domain to accomodate flame thickness. New width: 0.056 m\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 3 4 5 6 7 8 9 \n",
      "    to resolve C C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 N2O NCO NH NH2 NO NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "*********** Solving on 23 point grid with energy equation enabled ************\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     1.424e-05      6.312\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     3.604e-05      5.689\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     1.283e-05      6.137\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001096      5.738\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.601e-05       6.05\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     6.943e-06      6.869\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     7.909e-05      5.845\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     6.256e-06      6.571\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001069      5.566\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      7.61e-05      5.798\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     2.709e-05      5.646\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0006942      4.499\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [23] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "grid refinement disabled.\n",
      "\n",
      "******************** Solving with grid refinement enabled ********************\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [23] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 6 7 8 9 10 11 12 13 \n",
      "    to resolve C C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 N2O NCO NH NH2 NO NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001709      5.006\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [31] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 8 9 10 11 12 13 14 15 16 27 28 \n",
      "    to resolve C C2H C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 N2O NCO NH NH2 NH3 NO NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     7.594e-05      5.228\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [42] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 12 13 14 15 16 17 18 19 20 21 40 \n",
      "    to resolve C C2H C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 N2O NCO NH NH2 NH3 NO NO2 O O2 OH T point 40 u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [53] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 15 16 17 18 19 20 21 22 23 24 25 26 27 50 \n",
      "    to resolve C C2H C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 N2O NCO NO NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [67] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 \n",
      "    to resolve C C2H C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO CO2 H H2 H2O H2O2 HCCO HCCOH HCN HCNO HCO HNCO HO2 N N2 NO NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [85] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 \n",
      "    to resolve C C2H C2H2 C2H3 C2H4 C2H5 C2H6 C3H7 C3H8 CH CH2 CH2(S) CH2CHO CH2CO CH2O CH2OH CH3 CH3CHO CH3O CH3OH CH4 CO H H2 H2O H2O2 HCCO HCCOH HCN HCO HNCO HO2 N2 NO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [113] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 34 35 36 37 38 39 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 \n",
      "    to resolve C C2H2 C2H3 C2H4 C2H5 C2H6 C3H8 CH CH2 CH2(S) CH2CO CH2OH CH3 CH3CHO CH3O HCCO HCO \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [142] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "no new points needed in flame\n",
      "Flame Speed is: 38.22 cm/s\n"
     ]
    }
   ],
   "source": [
    "flame.solve(loglevel=loglevel, auto=True)\n",
    "Su0 = flame.u[0]\n",
    "print(\"Flame Speed is: {:.2f} cm/s\".format(Su0*100))\n",
    "\n",
    "# Note that the variable Su0 will also be used downsteam in the sensitivity analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot figures\n",
    "\n",
    "Check and see if all has gone well. Plot temperature and species fractions to see\n",
    "\n",
    "#### Temperature Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
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       "\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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": {
      "text/html": [
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.plot(flame.grid*100, flame.T, '-o')\n",
    "plt.xlabel('Distance (cm)')\n",
    "plt.ylabel('Temperature (K)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Major species' plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To plot species, we first have to identify the index of the species in the array\n",
    "For this, cut & paste the following lines and run in a new cell to get the index\n",
    "\n",
    "    for i, specie in enumerate(gas.species()):\n",
    "        print(str(i) + '. ' + str(specie))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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 â‰¥ 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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"
    },
    {
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fvrp8vDDD8fGDgEkNtSRDsQiOFK8dA6BbgmQf0wQCCRHgPxLjj0ju02A3HM7/nifLAHyL1n+jG4mAQQQM+OCVY4QSLMAonY/LPlkg7zy5mp5c+l6ybbbDFGSETlkn/5ywrBBsu/uffSxTbmSVgHk7bff1kdaKZFDCRY//OEP5ZprrpEePXrkna0ffPCBPuZq/vz5WuTI+Z3NZmXfffeVTZs2ybBhw/QxWoXK7Nmz5fzzz9fV1O6RUaNGFWoS2s8RQEJDmWhHLIITxc/gjhMg/xyfALifKAHyL1H8DO4wAXLP4eDjeuIEyL/EQ4ABBhJAADEwKJjkDoG0CiDLPquT//rLh/Lp2k0Fg7XLwJ5y2bf2lMFfajkCKo0CSG1trZx00kn6rg+1mLj//vtlxIgRBX1X8f3d734nF110UVvd999/X0444QT99QUXXCDjx48v2M+DDz4ot956q66n7g9RtsRVEEDiIh3tOCyCo+VL7xDojgD5x/yAQHIEyL/k2DOy2wTIPbfjj/fJEiD/kuXP6GYSQAAxMy5Y5QiBNAog//ioRh6cslS2NGY9R6mivESuHLG37L9Hv1QKIGrHxTPPPKP9HT16tN79EbQ8++yzeueIKrfddps+UqtQue6662Ty5Mm62htvvCE777xzoSah/RwBJDSUiXbEIjhR/AzuOAHyz/EJgPuJEiD/EsXP4A4TIPccDj6uJ06A/Es8BBhgIAEEEAODgknuEEibAKJ2ftz1h/d8iR+5aCoRZPR5Q2Wv3ar1t9JyB8hbb70lp512mrZ56NCh8uKLL0pZWVngSapEj9/85je6vRJDjjzyyIJ9qR0f7777rgwYMEAWLVpUsH6YFRBAwqSZXF8sgpNjz8gQIP+YAxBIjgD5lxx7RnabALnndvzxPlkC5F+y/BndTAIIIGbGBascIZAmAUTd+XHLY+94Ovaqq/DtskNPufXyQ/SdIGkRQK688kp57rnntEvqKKozzzyzqNmpjr2aOXOmZrB48WKpqmo5Gqyr0tDQoO8MUbyOPfZYeeqpp4oa329jBBC/xMyszyLYzLhglRsEyD834oyXZhIg/8yMC1bZT4Dcsz/GeGguAfLP3NhgWXIEEECSY8/IEJA0CSCLl9XKr/+4uOiojflfB8jQL/dLhQCybt06OeSQQ3Sc1C9LdfyUWkwUU1R/a9askerqarnlllsKdvXZZ5/po7JUUWLMz372s4JtwqyAABImzeT6YhGcHHtGhgD5xxyAQHIEyL/k2DOy2wTIPbfjj/fJEiD/kuXP6GYSQAAxMy5Y5QiBKASQbHOz1G1qCp3g4y9+KG9/UFN0v4fs3V8uPW1vaWpsLLqvXAdVPcukJJMJrb9cR2rnhxIdVLn44otl3LhxRY2xevVqOfTQQwP3MXHiRBk5cmTg9kEaIoAEoWZeGxbB5sUEi9whQP65E2s8NY8A+WdeTLDIDQLknhtxxkszCZB/ZsYFq5IlgACSLH9Gd5xAFALIhvpGGf3Am06RveuqQ6RPr/LQfb7xxhvl0Ucf1f3ef//9cvbZZxc1xowZM+Siiy4K3IdqP2TIkMDtgzREAAlCzbw2LILNiwkWuUOA/HMn1nhqHgHyz7yYYJEbBMg9N+KMl2YSIP/MjAtWJUsAASRZ/ozuOAEEkHAmQFQCyCWXXCIvvfSSNlJ93G+//YoyWO3guOOOO3Qfjz32mKjLzQuVs846Sx+9VVlZKUuWLJHS0tJum6gL1nNHZk2ZMkUOP/zwQkN0+3MEkKLwGdOYRbAxocAQBwmQfw4GHZeNIUD+GRMKDHGMALlnX8Cbampl47x5Uj38FPucK+BR2nwPM//S5rtzkzMCh22NOQJIBJOFLiHglQACiFdS3deLSgA544wzZOHChXrwBQsW6HtAiintL1RXosbOO+/cbXfq4nm146Ourk6GDRsmU6dO7bb++++/L8OHD9ciSX19vSCAFBMtu9qGuQi2iwzeQCB6AuRf9IwZAQJdESD/mBsQiIZAoRdkNudeId+jIZ5cr8rfmukvyYZZc6SkqkoGj7s1OWNiHjmtvoeRf2n1PeYpYtVwtsccAcSq6YozaSOAABJOxKISQE477TR56623tJHq4w477FCUwccee6x88MEHMnDgQHn77bcL9qXqqjaqXHDBBTJ+/Pgu26i5NGLECMlkMrLnnnvK5MmTEUAKEnanQhiLYHdo4SkEwiVA/oXLk94g4IcA+eeHFnWDEOBleP6X4Tbmnu0vBzvO//b+Nrfe31laXe2EAJJ234vJv7T7HuT3uOttXIk5AojrMx3/EyUQhQASxSXomxu2yk3/d5Fkm4vHVVKSkdv/96FSVpItvrPWHqK6BF3d16Hu3VBl+vTpsv/++we2edOmTbLvvvtKNpuV4447Tn7/+98X7Evt4Ljqqqt0PXWs1aWXXtplmwkTJsjdd98tL7zwgjzwwAPyxz/+EQGkIGF3KhSzCHaHEp5CIBoC5F80XOkVAl4IkH9eKFEnCAFehot09zLcptxz5eVgLg/y+Zv7me0CiC2+B8k/W3wP8vvc1TauxRwBxNWZjt9GEIhCAInKsYeeWyoLlqwvuvsjhg6Uq88eIo2tf0VSdIcRdnDXXXdpUUGVX/ziF3LZZZcFHk0deaXu81Dl6quvFnXBeqEybtw4ue+++3S1Z599Vo488si8Td577z351re+Jf/+7/8uP/zhD+UHP/gBAkghuI79PMgi2DFEuAuByAiQf5GhpWMIFCRA/hVEFEoFl3ZB8DJ825SxXQBx7eVgd/7mom6rAGKb736efbb5HspDzfJOXI05AojlExv3zCaQJgFk8bJa+fUfFxcNdMz/OkCGfrlfKgSQRYsWyamnnqp93nvvvWXatGlSUVFRkMGWLVvkH//4hxx66KFtddWl52PHjtVf33///XL22WcX7OfCCy+Uv/71r/pYKyVy9O7du1MbdUn5mWeeKeqjuiOkvLwcAaQgWfcq+FkEu0cHjyEQLQHyL1q+9A6B7giQf9HOD5d2QfAyvPNcslUAce3loBd/bRVAbPXdy7PPVt+jfeqlu3fXY44Aku75i/UpJ5AmAURdyH3LY+/Ip2s3Baa+yw495dbLD9Ev9NOwA0Q5qo6dUsdfqaLu2Ljnnnu6FEFUPNURVL/85S/1bpH2R1aNGTNGJk2apPt55ZVXZJ999inIUQkoq1evlj322EPmzp2bt77aoaJsev755+Wggw7SddgBUhCtcxW8LIKdg4LDEIiJAPkXE2iGgUAeAnHmH7sg7LwbwMsLI5v+Kt6Lv15ehseZe2H98gvL97DsibofP/56iXnU9obZv+2+d5d/tvse5jyxpS9i3hJJBBBbZjR+pJJAmgQQBXjZZ3Vy1x/eky2N/u/vqCgvkdHnDZW9dqvWsUqLALJ27VpRl6EvX75c27377rvrC8mVONG/f3+pq6uTVatWyfz58+Xll19uq6fu7zj88MPb5uUZZ5whCxculJ49e8rixYultLS02zm7Zs0aOeSQQ3Sd008/XR5++OFO9d955x39syuuuEJ++tOftv0cASSVvw4iNTqN/wiNFAidQyBGAuRfjLAZCgIdCMSRf+yCaIFukwig/PHzwsgG3/34m0szW3aAhO276b+Ig/jrJeZx+63+QFPU/6q0/9jcLPq7231Pf0O21tRKzV9fkY1zX5PmpiZfJpf27Su7/OTHrd22jt0ykP4v91Hb1eF7HW3UFrZvu50fzS1jePZtewZq/JJMRr+rUH2sW7dOmrNZ2VpfL/UL3pT6d/4hsnWrL99LqnrJDhde4KsNlZMnoGP+5tuy6R/v+o65Dc+1jhFAAEl+TmKBwwTSJoCoUP3joxp5cMpSXyKIEj+uHLG37L9HP31EkyppEUCUrWoXxrXXXtvlLoyOU/jggw+WyZMna7FDFXXxuboAXV2EroQTtVujUFFHX6kjsFRRu0dGjRrVqcnJJ58sDQ0NnY7mQgApRNe9n8fxAsg9qngMAW8EyD9vnKgFgSgIRJl/Lt0F4eWFqS0vS7z42nGuptn3IP7m/A8qgLS9uFYvqrNZ9Y8l/aK25XP1Yjgrzfpjs/5Zc3P777fUVfV0/bY6LXVb6rd+rvrMfd7x+9msZDfWS/2iRbJp8RLfLwczlZVSfcpJLf13+L/j9/LWUf7pl+At/2t/c18r33Iv0XMccr60G8vTOO3rNzTK1toa2bph47aX635/8ZZkpKy6v+R/gb/tpX7nF/itP2t9qd/iX7uX/DlBoN3320SMfEKAX7upDwEI+CKQ5udaV44igPiaAlSGQLgE0iiAKAJqJ8h//eVDT8dhqWOvLjt1Txn8pSoNL40CSC7q6hiqP//5z/L666/rXR9q94cSOQYNGqSPtDrqqKPkm9/8ZqfjrZYuXSrHH3+87kaJGnfeeWfBiaQuP1eXoKui7g856aSTOrXZddddC/ajKjzyyCNtd5l4atCukrpb5IsvvpDq6mopKyvz25z6hhCI8gWQIS5iBgSMJUD+GRsaDHOAQBT559JdEH5ejqf9ZYkfXzumTkffcy/d9Qv6repl/taWF/Nb1Qv6rS0v7nPf1x9bX9yrv8pW9fTPW+vpdu3bt/bX1m5ra78t328Zo4ux2n1/6+Yt0vjpSmlas6aIl+ElUta/f4tA0V50UC/ts1nJZETbo+3PCRzt/2rfgd9BuAgBCEAgjQTS/kzPxxwBJI0zEZutIZBWAUQFQC3slyzfIK+8uVrefH+9/mOdXCkpycihe1fL8YcMkn1366Pv/MiVNAsgpk280aNH5zVp3rx58uGHH8opp5wiAwcO1HeRHHjggYHMRwAJhM24RlG8ADLOSQyCgKEEyD9DA4NZkREw6S6MMPPPywtyW14YePG1kAgQxgRTQoA+pkaJAY1N0ry1SZqb1Ev+JhH9cav+uf5fvWTXn7f8fFu9Dt9r2iqif97y/a2b6qXhkxXStHp1cCFARDIVPVpFjdYdDWEAoA8IQAACEIBAAgRsWc+0R4cAksBEYkgI5AikWQBpH8VNW7bKFxsbZHPDVqnsUSrVvXtIz4r8d1wggEQ//zkCK3rGaRshzBdAafMdeyGQNAHyL+kIMH5cBEy8CyOM/PMjBqT1hYH6w6bmxkZp+nyd1MyYIRvnv67FBD8lU1khfY87djtRokWkyAkQOYGiRazoLFpsEzO04KHGzx1948cQ6kIAAhAwlUDuD0Pbf8xkRP+5aKef6W+2fb/tj0pVvZYG27Vpad76s0xG3wOyddNmyW7eXDyNkhIpGziw+H7oIVIC6o8GsvX10rxpU9HjpHU9053jCCBFTws6gEBwArYIIH4IIID4oRWsLgJIMG42twrjBZDNfPANAlESIP+ipEvfJhAw+S6MYvLPj/CRi0PYLwy0UNDYKM0NDZJtaGj9vLHd5w36Z80Nue+1fL7t65a2Hdvrr1v71T9vbDRhKmEDBLwT0C+BMyIlJS2nDZSU6K8z6mPb5+2+nynR91Y012+SbAgvBzNlZdLzgP1abMiosdWnrTZ18bW2T/9s20vqvF+XtJ6e0Np3pv3XOX/b+mj1v93XLePkxmjlksnoF+H1/3hXNi953/edJ7nAlFRVyY6XXLj9y/rWF/fbvaDP+0K/3Yv+PELAthf47f3f9lJft95OOGj3wl/a+ZwTAdqJAerekw1z5krd/7wR+Pddab9+stvNN7basC2Gmk17ESOvb9tOxPA+yYPXbP/sW754sax/cbpsmDUnuO/V1TJ43K3BDaJlrASCrF86Ghj2eiZWAF0MhgBiQhSwwVkCCCDOhj5SxxFAIsWbys6LeQGUSocxGgIGESD/DAqGQ6bEcQxVGu7CCJJ/xbw4KOldJTtefGGLQKGFCCUuKPEiJ0Q06hdQLT/PCRrbixu576s6aicExQECpaUtL+5zH9VL7lL1Ij/3/RLJlJSKlKgX/KUiperrlhf9mVL1/dav2/rJ/by0tZ+W9i19tnyebWqUho8+li3LPmm5PDxAKanqpef7duJDqxhRUloqA3fYQceCuUkAACAASURBVNu5dv36lku9c3bqOq1iRZuIoWxrERPaBA1VJydudBQ62h2x7Nf0YnI8N1aaXw4W43+a/Vaxc8X3fM8+V3z3+/vA5vrEfPvoIoDYPNvxzXgCCCDGh8h5A7kDxI4pEOQFkB2e4wUEkidA/iUfA5csiOMYKi//oDblJVnH/Nuq7n3YskW26r8Cr5es/rhZf960br1s+vs7suXjZYFfCLs01xL3Vf3FdVmZ/l8LB+pz/bFUpPX7LV+3fF9/L/d1Wcv3VTu1y6bhk+X6/8BCQO/estM1V+QRLPIJGR2EDiVkJFi85HNX5nWX52l49kXle4Lh9DV0EP9N+d3uy9E8lW33vbv8s933YueGje2JeUtUEUBsnN34lBoCCCCpCZWzhiKA2BH6NPwj1A7SeAGBzgTIP2ZFHATiOIbKzz+go3pJpl5W5wQL/bG+Xh9n0/Z/6/E2LcLGJn3kS6m626KuTho3bGw5C517JSKZkpnycul16CFagGgRHZQ4oXYrtHxs/31RX+e+n6uXV7RorVe+TbxoEztCFg78zO+OAKOa75EEqotOg/ifdgEkhyJs3+OMWxhj+fHfhrnenpmtvntZe9rqexg5YWsfrsccAcTWmY1fqSCAAJKKMDltJAKIHeH3sgi2w1O8gIB5BMg/82Jik0VxHEPl5x/MObZdvSTTxz/pHRctOzDUTozmTZtla9tujC7EjM2b9G4NtXvD9aLFhR49Wv4vL5eSHuVtn6vvlbR+v6VOuWTK1fda67R+LClv/ZmuXy7ZLQ2y8X9el7rX/+b8GfFhzvc0zlU//tsigAQRQmwTAhQDL7G30W8bffez9nQ57mn8HR2Gza7GHAEkjNlDHxAISAABJCA4msVGAAEkNtSRDuRnERypIXQOAQcJkH8OBj0Gl+P4x6uXMbpyVb2Yr9xn7047M6y/bDuTkbL+/duEBy1AtIoMSoho+7ydSOFLwCgvb7n7IaJSTMxtezHqh4VtvofxQjjNzz4vsbcx5l6EIJv9LjTv0+R7kPyL4w8qInp00W1AAq7FHAEk4EShGQTCIIAAEgZF+oiSAAJIlHTj6zvIIjg+6xgJAnYTIP/sjm9X3ql/VG6cN0+qh58SKgAvL+ZyA/p5WdOczUp2Y5001XwhDZ+ulI2vzZfN7y8NfCdCqE5H1VkmIyWVlVLSq6eU9OwlmfIy2bpxozStXRfYbz/Mo3IrjH79zLMg8y0MG+PqwwsLW+Kej2nQF2Q2PPuC+h7X3Ix6nDiOVozah6D9p933YvIv7b4HjbnL7VyJOQKIy7Mc3xMngACSeAgwoAABBBA7pkgxi2A7COAFBJIjQP4lxz6Jkdv/I7KkqkoGj7s1FDO8vITtOFDupWy2oUG21tRI0xc1svWLL2TrF+rzDh9rakS2bg3F1tg6KSmRkl69pKSnEjAqWz7mvtaiRk8p69VL+u+8k5RVVUnN5s2SaRM8ekqmoiLvboogrG0VAfywsFkEUPHlZXit1Ex/STbMmtN2TJptR2B19bvLlZeDXvwP87kW27OiiIGieqYXYZKnpmGsPdPquydAVMpLwPaYI4Aw8SGQIAEEkAThM7QnAgggnjAZXymMRbDxTmIgBAwlQP4ZGpiQzYrqBZmfF9CdXFICQc9KydbVh+xtON3p+yvaxIterTsxWoSLll0ZXX2uRI/KlnsvMplujSkm/4Kwt1UE8MLCVt87TrCocj2crIq+F68vyIrJvei9CDaCV9+D9W5+q6h2NprveYsAGsWuzqh8DzP/0uZ7VExd6tfWmCOAuDSL8dU4AgggxoUEgzoQQACxY0qEuQi2gwheQCA+AuRffKyTGCmqvwrf1u9saW5sSsK1osZUuyuqTzt1OyGjtPWoKS1eKHGjvLyoMbw0DiP/vLz8z9liuwgQ1Xz3EkvT6vAyvPsXwmHknmkxz9lj68tBU3ljl38CNueffxq0gEALAQQQZgIEEiSAAJIgfIb2RAABxBMm4yuxCDY+RBhoMQHyz87genkp7vVlePPWrfreicbVq2XLx8ukbuGb0vjpSpHm5vjhqXsxeleJSEayGzcGtsGr71E7GGb+hRnzqP2Oun/Xd0G058vL8PyzLczci3o+0z8EbCNA/tkWUfwJgwACSBgU6QMCAQkggAQER7PYCCCAxIY60oFYBEeKl84h0C0B8s+uCeLlJXjO4/YiQHNzs2ytrZXGz1a3/L96tTS1fmxc83ngS7f90FW7Msqq+4myq6uPpX36SKa0VHfrx9eOdtgogOR8ZBfEtmi7vgvCT/65Vpdnn2sRx1+TCJB/JkUDW0whgABiSiSww0kCCCBOhj1VTiOApCpcXRrLItiOOOJFOgmQf+mMW0erg4gBmcoK6XXgAdL42RoteDRv2RIrDHUh+KDvX9YmeKg7NYKUIL7bLIB0J4SY4neQOBfThl0QxdCzsy3PPjvjilfpIED+pSNOWBkvAQSQeHkzGgS2I4AAwoQwnQACiOkR8mYfi2BvnKgFgSgIkH9RUPXWZxgvZYO8/PdmXfS1wn4Z74dF2GMHpRVH/rELImh0aGczgThyz2Z++AaBYgiQf8XQo62tBBBAbI0sfqWCAAJIKsLktJEIIHaEn0WwHXHEi3QSIP/ij1sYL6T9vOwPy0O1Y6P8S4OkfNCglo9fGiTqe3VvLZKNc1+V5sZGX0NFJUJ4YRPV2L4AiEic+ReG4ObXP+pDwFQCceaeqQywCwJJESD/kiLPuCYTQAAxOTrYZj0BBBDrQ5x6BxFAUh9C7QCLYDviiBfpJED+xRe3MC5mbvz8c1n/7BSpW/hWJPdyZMrLpXzQjlKWEzpyYsegQVKqLx/PX7yIDh1bRi1CpOEuDPIvvvxjJAi0J0DuMR8gkBwB8i859oxsLgEEEHNjg2UOEEAAcSDIKXcRASTlAWw1n0WwHXHEi3QSIP+ij1vQF/HqYvKmzz+XLR9+pP+vX7xEmlauCs/gsjLpe+zXpfxLO7bt6lCiRKakJPAYfoSQqAWQnBNhCE+BgRRoSP5FRZZ+IdA9AXKPGQKB5AiQf8mxZ2RzCSCAmBsbLHOAAAKIA0FOuYsIICkPIAKIHQHEi1QT4B+h0YXPixjQXgTIbt4sWz76uE3w2PzhR5LduDEyA6MUIPz6HpmT7ToO4+ixsO0k/8ImSn8Q8EaA3PPGiVoQiIIA+RcFVfpMOwEEkLRHEPtTTQABJNXhc8J4BBA7wswi2I444kU6CZB/wePW1Z0KXl7+50Yt6dVTqg47TLZ8+KE0fLpSpLk5uEE+W0YpgORMCbr7xacrvqqbdBcG+ecrdFSGQGgEyL3QUNIRBHwTIP98I6OBAwQQQBwIMi6aSwABxNzYYFkLAQQQO2YCi2A74ogX6SRA/vmPW1c7CfwIH/5Hbdcik5Eeu+4iFXvuIeU7fUkaPlkhdX9bYMwl5Pl8M/kYqqJiUWRj8q9IgDSHQEAC5F5AcDSDQAgEyL8QINKFdQQQQKwLKQ6liQACSJqi5aatCCB2xJ1FsB1xxIt0EiD/vMetq5f4u9xwvdRMf0k2zJrjW4TwMnpJ795S+ZU9teCh///yYCmprNyuaRDxJY4dIB39M/EYKi8xiKoO+RcVWfqFQPcEyD1mCASSI0D+Jceekc0lgABibmywzAECCCDpDfLy5ctl6tSpMmPGDFmxYoWsWbNGGhoapH///jJ06FD52te+Juecc44MGjSooJMfffSRPPPMMzJ37lxZunSp1NbWSq9evUT9gj7qqKPk3HPPlSOPPLJgP1FUQACJgmr8fbIIjp85I0IgR4D8KzwXuhMXMhUVItlseMJHSYn02H03qdxzm+BRtsNAyWQyhQ1VOyNraj2LMUkIIDknTDqGyhPYiCqRfxGBpVsIFCBA7jFFIJAcAfIvOfaMbC4BBBBzY4NlDhBAAElfkJXQcfPNN8uUKVOkucA54uXl5XLppZfK9ddfL1VVVZ2cXbdundxyyy3ypz/9SbLZbLcwTjvtNLn77ruld+/esUJDAIkVd2SDsQiODC0dQ6AgAfKva0R+xISCoLuqkMlIr0OHSaXe3bGnFj9KevQI3F17gaHQrpQkBZCiHbSkA/LPkkDiRuoIkHupCxkGW0SA/LMomLgSGgEEkNBQ0hEE/BNIkwDyq4W/ldqGjf6d7NCiX0Uf+cmRV0pjY2PRfcXdwYIFC7SgsXbtWj30rrvuKt/+9rfliCOO0Ds96urqZNmyZTJ9+nT9f87HadOmyQEHHLCduYsWLdJ9rVq1Sn9/7733lpEjR8qhhx4qAwYMkA0bNsjChQvl0Ucf1TtMVBk2bJhMnjxZKjscyxElBwSQKOnG1zeL4PhYMxIEOhIg/zrPiViEj9ZhoxYhTLyEnCzcRoD8YzZAIBkC5F4y3BkVAooA+cc8gEBnAgggzAoIJEggTQLIzfPvkZqGDUXTqq7oK7d9bXTqBJC3335bH2mlRI7S0lL54Q9/KNdcc4306OKvSD/44AMZO3aszJ8/X5YsWSJqN0iuKPFDHWulRI6Kigq56aab5OKLL9YLlY6lvr5evve978ns2bP1jy6//HK9aySuggASF+lox2ERHC1feodAdwTIv2104hQ+cqNGLYDkxuEScjN/D5B/ZsYFq+wnQO7ZH2M8NJcA+WdubLAsOQIIIMmxZ2QICAJIOiaBupPjpJNO0jsx1GLi/vvvlxEjRhQ0XsX3d7/7nVx00UVtddevX6/7Ujs/lCjy+OOPy3HHHddtX+qoLFVHtVWCyWuvvabvB4mjIIDEQTn6MVgER8+YESDQFQHX808JA7WvvCLNjU2RXWLe3eyLSwDJJ4SUVFXJ4HG3khwJEnA9/xJEz9COEyD3HJ8AuJ8oAfIvUfwMbigBBBBDA4NZbhBAAElHnEeNGqUvKVdl9OjRevdH0HLVVVfp+0NUUTs51I4OL0XVfeihh3TV8ePHywUXXOClWdF1EECKRmhEByyCjQgDRjhKwNX8U8LH+uf/Wza+Ok9fYl5MKenTW8qqq6Vh5SqRpiZfXcUtgOSM4xJyX2GKrLKr+RcZUDqGgEcC5J5HUFSDQAQEyL8IoNJl6gkggKQ+hDiQZgIIIOZH76233hJ1AbkqQ4cOlRdffFHKysoCGa52bqhjtFRRd30899xzkslkPPWl7hG57LLLdF0lfigRJI6CABIH5ejHYBEcPWNGgEBXBFzLvzCFD8W0pHeVDL7zdsmUlEiQI7SSEkDICDMIuJZ/ZlDHCghwBwFzAAJJEuDZlyR9xjaVAAKIqZHBLicIIICYH+Yrr7xSCxWqPPjgg3LmmWcGNlodhTVjxgzdXh2Ndfzxx3vuS90bcuqpp+r6J598sr4cPY6CABIH5ejHYBEcPWNGgIDrAkhOnKidOdv3Lo3uZk8+AcOPEIIA4nZu8vxzO/54nxwBci859owMAfKPOQCBzgQQQJgVEEiQQBQCSLa5Weob60P36pcLHpbaxo1F99u3R28Ze9Q10tTYWHRfuQ56lfeSEo87KfwMqu7eOOSQQ/RdLeqX5RtvvJH3onIvfS5fvly++tWv6qp77bWXzJo1y0uztjrvvPOOnHLKKfrrE088UZ588klf7YNWRgAJSs6sdiyCzYoH1rhFwPb88yNGBIl8dwKGl7ERQIJQt6eN7flnT6TwxDYC5J5tEcWfNBEg/9IULWyNiwACSFykGQcCeQhEIYBsbKiT/zP/107x/sVXfyS9e1SF7rPa+aF2gKhy8cUXy7hx4wKP8cQTT8gNN9yg26s7RcaMGeOrrzlz5sh5552n26hjtO69915f7YNWRgAJSs6sdiyCzYoH1rhFwNb8axMfZs6WZp/3cviZAV4EjO6EEC/t/dhD3XQRsDX/0hUFrHWRALnnYtTx2RQC5J8pkcAOkwgggJgUDWxxjgACSDghj0oAufHGG9uOmrr//vvl7LPPDmxw+8vPlRjyjW98w1dfjzzyiNx00026zXXXXdcmpvjqJEBlBJAA0AxswiLYwKBgkjMEbMu/uISP3ATxI2DkE0L8tHdmUjrkqG3551DocDXlBMi9lAcQ81NNgPxLdfgwPiICCCARgY27W/WS8tVXX5W5c+fKJ598IjU1NVJVVSWDBg2So446Sk444QTp27dvqGapMT/66CP54IMPZOnSpfLPf/5TVqxYIdlsVo+j7je45pprPI25evVqufbaaz3VzVdJ/UX8d77znbztu/p+V4OppJg4cWJgW/w0RADxQ6vrulEJIJdccom89NJLemD1cb/99gtssLo7ZMGCBbr9vHnzZPfdd/fV1xVXXCHPP/+8bvP73/9ejjvuOP35ypUr9ffV3SIqD9esWSPV1dVy5JFHihJdDjvsMF/jdKyMAFIUPmMaswg2JhQY4iABW/KvWOGj6ojDpPfRX5VN774nG2bNkWaPR2EGETDaCyElVVUyeNytDs48XFYEbMk/ogmBtBEg99IWMey1iQD5Z1M08SUsAgggYZFMsB8lOkyYMEE+/PDDLq3o169fKC9DcwO88MIL8vjjj4t6OdpViVMA+f73v992P0JHexBAEpycMQ0dlQByxhlnyMKFC7UXSrxQvzCDlmOOOUY+/vhj3fy9996TPn36eO5q06ZNcvDBB0t9fb1UVlbK3//+d+nZs6duf/vtt4vanbLHHnvI0UcfLTvssIMWJV988UVpbm7WPxsxYoTnsTpWRAAJjM6ohiyCjQoHxjhGIO35V6zwocJd2rePDL7z9rbIe7m7I1c5iACSa6vG2ThvnlQPb7lDi+IegbTnn3sRw2NbCJB7tkQSP9JIgPxLY9SwOWoCCCBRE464/7Vr18rYsWNl/fr1eqRMJqP/Sn2nnXbSu0AWLVokDQ0N+melpaW67kEHHVS0VU8//bQ888wz3fbjRwDZuHGj/OEPf/Bs15IlS9oEn7KyMnnooYe6fKHcXgAZPnx4wTHUTplzzz23YL0wKkSxA4RL0MOITEsfp512mrz11lv6c/VRiQtBi9qF9f777+vm6kJztUvDa2l//FXHu0imTp0qAwcObLtgPdfn/Pnz9Z0haieYEm8qKiq8DrddPQSQQNiMa8Qi2LiQYJBDBNKaf2EIH7kwdyVieBFCihFAHJpmuNoFgbTmHwGFQNoJkHtpjyD2p5kA+Zfm6GF7VAQQQKIiG1O/N998s7z77rt6tB133FFfrPzlL3+5bfTa2lp9WbISQlTp3bu3Pt5JvRQtpuQEEPXida+99pK9995bf5w+fbo+3kcVPwKIX1t++tOf6iO3VFFHfI0ePbrLLtoLIMpuk0oUAkhU/t08/x6padhQdPfVFX3ltq+NlkaPR18UPWARHVx00UX6aClV1Nzef//9A/emRDV1TJ0qL7/8sgwdOtRTX3V1dfq4q1WrVmkRc9asWXq3h5dywQUXyMyZM0WJJMOGDfPSpFMdBJBA2IxrxCLYuJBgkEME0ph/W5Yvl1V3T5Bs/aZQIlVIxOAS81Aw00keAmnMPwIJARsIkHs2RBEf0kqA/Etr5LA7SgIIIFHSjbhv9Vfdd9xxhx5F7YJQnw8ePLjTqJs3b5brr79ePvvsM/0zdZGzejFaTFH3DJSXl3f6K3Z13I564apKVALI8uXL5Uc/+lGb+Ur0OeKII7p0BwGkmEhva+uiAHLXXXfJ3XffrSH84he/kMsuuywwzHHjxsl9992n2992221y6aWXeupLiX3quDlV1D056muvRe0WUWKLOg7rwAMP9Npsu3oIIIGwGdeIRbBxIcEghwikLf9yYkTtzNki3Rx16ieEhQSQXF9cYu6HKnW9EEhb/nnxiToQSAMBci8NUcJGWwmQf7ZGFr+KIYAAUgy9hNuqF6q5+wm++c1virokuasye/bstou91S6Q//zP/9R/TR52iUMAefLJJ2XKlCnadHVclTr+qjtfEEDCibKLAojaOXXqqadqgGqX07Rp0zwdJbVlyxb5xz/+IYceemgb/PZ97bvvvrovJSJ2Vx599FG58cYbdZUDDjhAX3beo0cPTwFVdwMde+yxou7/eeONNwLnOwKIJ9zGV2IRbHyIMNBiAmnJPy/HUQUNk1cBJNc/l5gHJU27jgTSkn9EDgK2ESD3bIso/qSJAPmXpmhha1wEEEDiIh3yOGpXx+WXX952jJD663T1UrWroo4bUheFq8uUVbnpppsC/0V4d65ELYBks1m5+uqrZd26ddoMdUdDob+kRwAJZ/K5KIAocmp+qeOvVFGXid9zzz1diiDqSLMXXnhBfvnLX+rdIh3n5iWXXCIvvfSS7kvdzzF+/Pi8woTK01/96lfywAMP6Lq77LKLPPvss7Lrrrt6CqbK9/PPP18fR6eOwDvnnHM8tctXCQEkMDqjGrIINiocGOMYAdPzL0rhIxdqvwJIrh2XmDuWLBG4a3r+ReAyXULACALknhFhwAhHCZB/jgYet7slgACS0gmiLmRWx+iooi43Vn8pXmhHhxJJ3n77bd1m5MiR+gVp2CVqAaS938p29aK50H0ICCDhRNlVAWTt2rVaaFNHr6my++676yPk1O6O/v37i7qjQ93PoS4dV8dN5eqpXUqHH374dvA///xz+da3viWffvqp/v5+++0nF154od7d0bNnT1m9erXu55lnntF9qjJkyBB9BNZuu+3mKZBKJBw1apRMnjxZvvvd7+ocKaYggBRDz5y2LILNiQWWuEfA1PyLQ/jIRTuoAOLebMHjsAmYmn9h+0l/EDCNALlnWkSwxyUC5J9L0cZXrwQQQLySMqyeutRYiR6q7LPPPm1iSHdmTpo0Sf785z/rKoUuDg/qbtQCyIQJE2TOnDnaPHXZu/oL+kKlvQDyH//xH7J06VL54osv9L0pffr0kT333FPvnvF6tFCh8fz8nEvQ/dBKrq4SJtT9G3PnzvVkxMEHH6wFCCVqdCwrV66UK6+8Uh9L1V1R81HtIFF33OTrJ1/b5uZmGT16tDz11FNa5FS7P9Tip5iCAFIMPXPasgg2JxZY4h4BE/NPX3J+z0TJ1tXHEhAEkFgwM0geAibmH4GCgAsEyD0XooyPphIg/0yNDHYlSQABJEn6RYz929/+Vt8hoMoxxxwjP/jBDwr2pi5CfuSRR3Q99dfkv/71rwu28VshSgGkvr5e/u3f/k0aGhq0WeqC5zPOOKOgie0FkK4qqxfMJ598sn5p3KtXr4J9hlUhTQLIrxb+VmobNhbter+KPvKTI69sO76t6A5j7EAJIEpEfP311/UODbX7Q82dQYMGaSFSCYvqPh71eaGijtVSu0T+9re/yZo1azSP6upqLcYdd9xxcu6554r6Be21qJ0fSvz4wx/+IGeffbYosbDQrjAvfSOAeKFkfh0WwebHCAvtJWBq/m1ZvkI+f2KSNCz7pGj4mYoKkWxWmhsb8/aFAFI0YjoISMDU/AvoDs0gkBoC5F5qQoWhFhIg/ywMKi4VTQABpGiEyXRw9913y2uvvaYHV0fqqPsGChV1tI66V0AV9aL14YcfLtTE98+jFEBmzJghDz74oLZJvdhVn6sLngsVLwJIro+dd95Z/8W917sW8o2tjkwqVBR/5YMSQNTLb69FvSRfv369jp/awZLGkrv4W/lCCYdAe/FD3VNy3333hSJ+KOtyAog67qvQpe3heEMvURBQi2Al1KmidjSpOUOBAATiIWBa/jXV1MgXL74ktbNmdylY+CWjBI7dxo6RL6a9JLUzO/erfr7HnS1Ht1IgECcB0/IvTt8ZCwJJEiD3kqTP2K4TIP9cnwH4n4/AjjvuGNp7smIIZ5rV2S0UzwTGjRsnCxcu1PXPOussfdZ/oaLqq3aqVFZW6nsFwi5RCiA333yzvPvuu9pkdbfCT37yE0/mKzZf/epX5bDDDpOvfOUrMmDAAC0e1NbW6uOw1KXUb775ZltfKiluv/12T+JKPgO8CC7qcuuBAwd6sr99pc2bN8s///lPffcEL6N947OygXqRrXaAqWOvlPihhMEwxbGc6LbXXnvp3xsUCEAAAhBIJ4GG9etlxeRnZdUL0yTbups2LE96DBwgR/7f/9Td6XH+359l1V9ebBun/c/DGpN+IAABCEAAAhCAAAQgAAEIpIkAAojPaN1yyy3y97//Xbf69re/Leedd17BHlR91U4VpQirF6Zhl6gEEPUXy9ddd53kdLIf/ehHcvTRR3syf+PGjdK7d+9u66rdJQ899FBb/yeeeKJcddVVnvrvWAkBJBA2GgUkoC45v+uuu6SqqkofEZfv2Cu1S+yggw4KNAICSCBsNIIABCBgDIEohY+ck/kEjvZCSFmf3m0CiTFgMAQCEIAABCAAAQhAAAIQgECMBBBAfMJ2bQfIH//4R1H/q6LEDHV8V5h/5a76VYKQurhaFSUQqb+kV0dN+S0cgdU9MY7A8jujuq+vdn/kcqOrmuq+Hy8iab72HIEVbryS6o1t0EmRZ1wItKwpkjiCLoqjrrqKZ3dHXCk7Nrw2X/qfegrTAQKxE0gq/2J3lAEhYBgBcs+wgGCOUwTIP6fCjbMeCXAElkdQplVz7Q4Qtfvjs88+02EYPny4XH755aGHRB0v9f3vf7/tkvVrr71WX0YdZUnTJehhcUAACYtkPP1wCXo8nKMehYvwoiZM/xDomkAS+bdl+XJZdc9EydbVhxIaLjkPBSOdJEAgifxLwE2GhIBxBMg940KCQQ4RIP8cCjaueibAJeieUZlV8be//a1MmzZNG3XMMcfoOwAKlRdffFEeeeQRXW233XYT9VfhYZcojsB677335KabbmozVd3Psffee4dtuu7v5z//ubzzzjv687PPPlsuuOCCSMbJdYoAEileOg+BAAJICBAN6IJFsAFBwARnCSSVf001tVIz/SXZMGtO0Zedqx0eu9xwfZf9qZ8PHnerszHGcXMJJJV/5hLBMgjEQ4Dci4czo0AgHwHyj3kBgc4EEEBSOiumTp0qjz76qLZ+n332kdtuu62gJ5MmTZI/SNHgiQAAIABJREFU//nPut5RRx0lo0ePLtjGb4UoBBB1FJW6o0OVqISbnJ/33nuvzJ07V3950kkn6TsVoiwIIFHSpe8wCCCAhEEx+T5YBCcfAyxwl0BS+ZcTQGpnzhZpaioqAO0FjnzCCgJIUXhpHCGBpPIvQpfoGgKpIEDupSJMGGkpAfLP0sDiVlEEEECKwpdc47feeqtN9KioqNBiSL7Lj9tb+Itf/ELefvtt/a2RI0fK+eefH7oDYQsgDQ0NWoSor285wuG73/2unHXWWaHbnetQXSj9xhtv6C9PP/10ueSSSyIbS3WMABIpXjoPgQACSAgQDeiCRbABQcAEZwnEnX9h7vzIBS2fwNF+nJKqKnaAODvDzXY87vwzmwbWQSA+AuRefKwZCQIdCZB/zAkIdCaAAJLSWaHuq1D3YDQ2NmoPlLix7777dumNqqfut9i0aZOuo46UOvDAA0P3PmwBRO3GULsyVMlkMvLAAw/IgAEDQrc71+HVV18tn3/+uf7ywgsvlBEjRkQ2luoYASRSvHQeAgEEkBAgGtAFi2ADgoAJzhKIK/+iED5yQetuh4cad+O8eVI9nEvOnZ3kBjseV/4ZjADTIJAIAXIvEewMCgFNgPxjIkCgMwEEkBTPinHjxsnChQu1B4WOa5ozZ45MmDBB162qqhJ1h0ihHSNB0IQtgKj7Pt58801tyrBhw+TGG28MYpanNosWLZJbb912fnWUd43kDEIA8RQaKiVIAAEkQfghDs0iOESYdAUBnwSizr8ohY+cqxxx5TPoVDeGQNT5Z4yjGAIBwwiQe4YFBHOcIkD+ORVunPVIAAHEIygTqy1YsEDuuOMObVpZWZnceeedsvvuu3cydcuWLXL99dfLqlWr9M+ivNw7TAFk/fr1ctVVV0k2m9V2jxo1Sr72ta/5CoXaKVNZWVmwzYYNG7S4kmO0yy676Evi1YMjyoIAEiVd+g6DAAJIGBST74NFcPIxwAJ3CUSVf2EKH5mKCpFstsvL0hFA3J2/afc8qvxLOxfsh0DUBMi9qAnTPwS6JkD+MTsg0JkAAkjKZ8XNN98s7777rvZixx13lJ/85CcyePDgNq/Ui311hFTu7o/evXvLxIkT9S6QjmX16tVy7bXXtn1b9X3AAQf4IhSmADJlyhR58skn9fi9evWShx9+WHr06OHLHnVM2PDhw+XrX/+6KFEjX1E7TNSOGOV/rowZM0aOOOIIX2MFqYwAEoQabeIkgAASJ+3oxmIRHB1beoZAIQJR5N+W5ctl1T0TJVvXckdasUUJHLvccL3UTH9JNsya00kIQQApljDtkyIQRf4l5QvjQiBNBMi9NEULW20jQP7ZFlH8CYMAAkgYFBPsY+3atTJ27FhRuyVUUfdk7L///qICW1tbK+pYJ7UDRBV15JWqe9BBB+W12K8AonaVdCzq/oy6ujr9bSWy7LDDDp3qjB8/3hOxH//4x/LJJ5/out/85jfliiuu8NSufaXvfOc7bV8OHDhQi0P9+vXTO2aUOLR06VJRDNsXdTm8uiQ+joIAEgdlxiiGAAJIMfTMacsi2JxYYIl7BKLKvzB3gLQXOPL1iwDi3ry1xeOo8s8WPvgBgagIkHtRkaVfCBQmQP4VZkQN9wgggFgQ8xUrVuhdHh999FGX3vTt21fUBd+HHXZYl3X8CiDtxQU/GJ9++umC1T/44AO54YYb2uqpuzmGDBlSsF3HCn5sVMKI2jFy9NFH+x4naAMEkKDkaBcXAQSQuEhHOw6L4Gj50jsEuiMQVf7lhIrambNFmpqKCkI+gaO9EFJSVSWDx227J62owWgMgRgJRJV/MbrAUBBIJQFyL5Vhw2hLCJB/lgQSN0IlgAASKs7kOlMvKefOnav/V7smampq9A6MQYMGyVFHHSUnnniiKBGku2KSAPJf//Vf8pe//EWbu9NOO7Vd4O6X8MqVK2Xx4sWyZMkS+fjjj/WuGLXzQ+2KUXeDVFdXy1577aUvWP+Xf/kXvTMkzoIAEidtxgpCAAEkCDXz2rAINi8mWOQOgbDzL8ydH7kodLfDQ423cd48qR5+ijtBw1NrCISdf9aAwREIREyA3IsYMN1DoBsC5B/TAwKdCSCAMCsgkCABBJAE4TO0JwIIIJ4wGV+JRbDxIcJAiwmElX9RCB9eBBCLQ4NrDhAIK/8cQIWLEAiVALkXKk46g4AvAuSfL1xUdoQAAogjgcZNMwkggJgZF6zaRgABxI7ZwCLYjjjiRToJhJF/YV963pEkd3ykc25hdWECYeRf4VGoAQEIdCRA7jEnIJAcAfIvOfaMbC4BBBBzY4NlDhBAAHEgyCl3EQEk5QFsNZ9FsB1xxIt0Eggr/9gBks74Y3WyBMLKv2S9YHQIpI8AuZe+mGGxPQTIP3tiiSfhEUAACY8lPUHANwEEEN/IaBAzAQSQmIFHNByL4IjA0i0EPBAIK//CvPS8o9nsAPEQSKqkkkBY+ZdK5zEaAgkSIPcShM/QzhMg/5yfAgDIQwABhGkBgQQJIIAkCJ+hPRFAAPGEyfhKLIKNDxEGWkyg2PyLYudHpqJCJJuV5sZGTR4BxOIJ6Lhrxeaf4/hwHwKBCZB7gdHREAJFEyD/ikZIBxYSQACxMKi4lB4CCCDpiZWrliKA2BF5FsF2xBEv0kkgaP5FIXzkCCrBY5cbrpea6S/JhllzpKSqSgaPuzWdgLEaAt0QCJp/QIUABIojQO4Vx4/WECiGAPlXDD3a2koAAcTWyOJXKggggKQiTE4biQBiR/hZBNsRR7xIJ4Eg+RfnpedKaNk4b55UDz8lnYCxGgIIIMwBCBhHIMizzzgnMAgCKSVA/qU0cJgdKQEEkEjx0jkEuieAAMIMMZ0AAojpEfJmH4tgb5yoBYEoCATNv6h3gLDjI4po06dpBILmn2l+YA8E0kaA3EtbxLDXJgLkn03RxJewCCCAhEWSfiAQgAACSABoCTV57LHHZOzYsXr0iRMnysiRIwtacvHFF8vLL78smUxG3nvvPendu3fBNn4rfPTRR/LMM8/I3LlzZenSpVJbWyu9evUS9cv9qKOOknPPPVeOPPJIv9221UcACYzOqIYsgo0KB8Y4RqDY/NuyfIV8/sQkaVj2SWjkuPMjNJR0ZDiBYvPPcPcwDwLGEiD3jA0NhjlAgPxzIMi46JsAAohvZDSAQHgEXBNA1F+zbvqf12XAaadKY+vFq+HRjLanMWPGyKRJk/QgM2bMkCFDhhQc8PDDD5dVq1bJHnvsoQWKMMu6devklltukT/96U+SzWa77fq0006Tu+++O5AAgwASZtSS64tFcHLsGRkCQfMvzB0gXHrOPHSVQND8c5UXfkMgLALkXlgk6QcC/gmQf/6Z0cJ+Aggg9scYDw0m4IoA0v4lTmnvKvnK+DtSJ4CcccYZsnDhQqmsrJQlS5ZIaWlptzNLCRQHHXSQrnP66afLww8/HNpMXLRokVx66aVaXFFl77331jtSDj30UBkwYIBs2LBB2/roo4/KihUrdJ1hw4bJ5MmTtf1+CgKIH1rm1mURbG5ssMx+An7zL0zhI0eXS8/tn2d4mJ+A3/yDIwQgEA4Bci8cjvQCgSAEyL8g1GhjOwEEENsjjH9GE7BdAMn3Eqesf3XqBBC1w2LfffeVTZs2aSFh6tSpBefV7Nmz5fzzz9f11O6RUaNGFWzjpYISP9SxVkrkqKiokJtuuknUUVtqkdOx1NfXy/e+9z1Rtqhy+eWX610jfgoCiB9a5tZlEWxubLDMfgJe8y8K4SNHt/2RV1x6bv+cw8NtBLzmH8wgAIFwCZB74fKkNwj4IUD++aFFXVcIIIC4Emn8NJKArQJIdy9x0iiAvP/++3LCCSfoOXTBBRfI+PHjC86nBx98UG699VZdT90fctJJJxVsU6jC+vXrdT9q50d5ebk8/vjjctxxx3XbTO1EUXVUWyWYvPbaa/p+EK8FAcQrKbPrsQg2Oz5YZzcBL/m3ZflyWXXPRMnW1UcCgzs/IsFKpykg4CX/UuAGJkIgdQTIvdSFDIMtIkD+WRRMXAmNAAJIaCjpCAL+CdgmgHj569U0CiDPPvusXHPNNTrAt912mz5+qlC57rrr9JFTqrzxxhuy8847F2pS8OdXXXWVTJkyRddTOznUjg4vRdV96KGHdFUl3igRx2tBAPFKyux6LILNjg/W2U3Aa/55eYYGJYUAEpQc7dJOwGv+pd1P7IeAaQTIPdMigj0uESD/XIo2vnolgADilRT1IBABAVsEED8vbdIogCjR4ze/+Y2eAUoMOfLIIwvOBrVT491339V3cqhjq4otaufGOeeco7tRd30899xzkslkPHU7bdo0ueyyy3RdrztYch0jgHhCbHwlFsHGhwgDLSbgN//8PFO7wsal5xZPKFzzRcBv/vnqnMoQgECXBMg9JgcEkiNA/iXHnpHNJYAAYm5ssMwBAmkXQIK8pEmjAKJEg5kzZ2rBYfHixVJVVdXt7GxoaNB3hjQ2Nsqxxx4rTz31VNGz+aKLLpIZM2bofn73u9/J8ccf77lPJcCceuqpuv7JJ5+sL0f3WhBAvJIyux6LYLPjg3V2EwiSf+r5uv75/5aNc18TaW72DYhLz30jo4GlBILkn6UocAsCsRIg92LFzWAQ2I4A+ceEgEBnAgggzAoIJEggCgGkOZuVbF1dpF5t3bBBal+ZJRtfmy/NTU2+xirt10++/B//R5oaG321665ySVWVZPJcAh7WAIcccoisWbNGqqurPV0i/tlnn+mjslS58sor5Wc/+1lRpixfvly++tWv6j722msvmTVrlq/+3nnnHTnllFN0mxNPPFGefPJJz+0RQDyjMroii2Cjw4NxlhPwk39B/rAgHz4uPbd8UuGeZwJ+8s9zp1SEAAQKEiD3CiKiAgQiI0D+RYaWjlNMAAEkxcHD9PQTiEIAUeLEsjFj0w/HhweDf3m7lPbp46OF96qrV6/WR04FLRMnTpSRI0cGba7bPfHEE3LDDTfoz0eNGiVjxozx1d+cOXPkvPPO023UMVr33nuv5/YIIJ5RGV2RRbDR4cE4ywl4yb+whI8cSu78sHxS4Z5nAl7yz3NnVIQABDwTIPc8o6IiBEInQP6FjpQOLSCAAGJBEHEhvQQQQMKJXZQCiDp2Sh0/FbSo9kOGDAnaXLdrf/m5EkO+8Y1v+OrvkUcekZtuukm3UZez58QUL50ggHihZH4dFsHmxwgL7SXQXf6FLXzkKCKA2Duf8MwfAZ5//nhRGwJhESD3wiJJPxDwT4D888+MFvYTQACxP8Z4aDABBJBwghOlAKJ2cNxxxx3a0Mcee0zU5eaFyllnnSVvvPGGVFZWypIlS6S0tFQ3WblypTz//PP6Lo+lS5e2HaulLlVXIsdhhx2Wt+szzzxTFixYoH82b9482X333QuZsN3Pr7jiCj2uKr///e/luOOO89weAcQzKqMrsgg2OjwYZzmBrvJvy/LlsuqeiZKtqw+dAAJI6EjpMKUEeP6lNHCYnXoC5F7qQ4gDKSZA/qU4eJgeGQEEkMjQ0jEEChNAACnMyEuNKAUQdYfHc889p81QosbOO+/crUnNzc16x0ddXZ0MGzZMpk6d2lb/9ttvl/vvv1/22GMPOfroo2WHHXaQDz74QF588UVR7dTPRowY0an/Y445Rj7++GP9/ffee0/6+Djua9OmTXLwwQdLfX29FmT+/ve/S8+ePb1g1XUQQDyjMroii2Cjw4NxlhNgB4jlAcY9ownw/DM6PBhnMQFyz+Lg4prxBMg/40OEgQkQQABJADpDQiBHIAoBJMpL0FsuP58tG+fNl+aAl5in7RL0Y489VosUAwcOlLfffrvg5FV1VRtVLrjgAhk/fnxbGyWGqH5yF5rnfjB//nx9R0dVVZXe6VFRUbHdOCeccIK8//77+nvqQnN1GbvX0v74q4svvljGjRvntamuhwDiC5exlVkEGxsaDHOAgBcBpHbmbPULtygaJX37Su8jD5cNs+ZISVWVDB53a1H90RgCNhDg+WdDFPEhjQTIvTRGDZttIUD+2RJJ/AiTAAJImDTpCwI+CUQhgPg0IVD1Ys4sL+tfLV8Zf4c0BhRQAhkcsJHaPbHvvvtKNpvVx0ap46MKlSlTpujjrFS57bbb5NJLLy3URP9ciSUzZ87UO0bUzpH25dxzz5VXX31Vf+vll1+WoUOHeupT7UJRdq9atUofwzVr1iy9+8RPQQDxQ8vcuiyCzY0NltlPIF/+FfMc7YpY7tgr1ffGefOkevgp9sPFQwgUIMDzjykCgWQIkHvJcGdUCCgC5B/zAAKdCSCAMCsgkCCBtAogOWRBXuCkSQBRR16p+zxUufrqq+XGG28sOFvUDov77rtP13v22WdF3e/hpajdGUrcUMdhHXjggds1ad+nH1Hlpz/9qTz++OO6r2uvvVbU134LAohfYmbWZxFsZlywyg0CHfNv07Jlkdz9wb0fbswnvPRHgOefP17UhkBYBMi9sEjSDwT8EyD//DOjhf0EEEDsjzEeGkwg7QJIDq0fISRNAoi69Hzs2LHaTXU/x9lnn11wNl144YXy17/+VTKZjL6vo3fv3gXbrFixQh+b1a9fP33PSO7S9FzDRYsWyamnnqq/VDtSpk2bJuXl5d32++ijj7YJNgcccIC+BL1Hjx4FbelYAQHENzIjG7AINjIsGOUIgXz5t2X5Cvn8iUnSsOyT0CgggISGko4sIsDzz6Jg4kqqCJB7qQoXxlpGgPyzLKC4EwoBBJBQMNIJBIIRsEUAyXnvRQhJkwAyZswYmTRpknbvlVdekX322adgoA899FBZvXq1Pmpq7ty5Beuro8DOP/98mTdvntx7771yzjnn5G1zySWXyEsvvaR/pu4LUXeLdBRK1M/UsV2/+tWv5IEHHtB1d9llF70TZddddy1oS74KCCCBsBnXiEWwcSHBIIcItM+/5YsXy/oXp+t7OoLepdUVOgQQhyYVrnomwPPPMyoqQiBUAuReqDjpDAK+CJB/vnBR2RECCCCOBBo3zSRgmwCSo9ydEJImAeSMM86QhQsXSs+ePWXx4sV5BYf2M2vNmjVyyCGH6G+dfvrp8vDDD3c78dTdIqNGjZLJkyfLd7/7XfnlL3/ZZf3PP/9cvvWtb8mnn36q6+y3336idpuo3R3KPiW6qMvUn3nmGX3nhypDhgzRR2DttttugRMAASQwOqMasgg2KhwY4xiBXP7VffiRvH3jTZKtq4uEAAJIJFjpNOUEeP6lPICYn1oC5F5qQ4fhFhAg/ywIIi6ETgABJHSkdAgB7wRsFUByBPIJIWkRQJQ4oY6bUjsq1K4OdYRUoaKOvlKihCpq94gSN7oqzc3NMnr0aHnqqadk5MiReveHWqh0V1auXClXXnmlPiaru6KOulKXrysblDhSTEEAKYaeOW1ZBJsTCyxxjwA7QNyLOR6bQ4DnnzmxwBK3CJB7bsUbb80iQP6ZFQ+sMYMAAogZccAKRwnYLoDkwtpeCCntXSVfGX+HqKOfTC5Lly6V448/XpuoRI0777yzoLnq8nN1Ybkq6v6Qk046KW8bJa4o8eMPf/iDvldkwoQJBXeXtO9o+vTpMmXKFPnb3/4mateJYlldXa0Fm+OOO07OPfdcUb/cwygIIGFQTL4PFsHJxwAL3CWQTwCpnTlbpKkpFCiZigqRbFZKqqpk8LhbQ+mTTiBgCwGef7ZEEj/SRoDcS1vEsNcmAuSfTdHEl7AIIICERZJ+IBCAgCsCSA6NEkI2/c/rMuC0U40XQAKE01OT9uLHiBEjRIkm+e7y8NRZDJUQQGKAHMMQLIJjgMwQEOiCgMq/ARUVsmLys7LyLy9GcvfHLjdcLxvnzZPq4acQBwhAoB0Bnn9MBwgkQ4DcS4Y7o0JAESD/mAcQ6EwAAYRZAYEECbgmgCjU5eXlmrjpO0CimBZK/Pjxj38sTz/9tKj7Re6//34pKyuLYqjQ+kQACQ1loh2xCE4UP4M7TqBxxaey6t6J0rRhYyQkuPsjEqx0agkBnn+WBBI3UkeA3EtdyDDYIgLkn0XBxJXQCCCAhIaSjiDgnwACiH9maW7xq1/9Sn79619LVVWVXH755XnFj+HDh8uBBx5ojJsIIMaEoihDWAQXhY/GECiKQNsOkP/3Z1k59YVIdoBw9FVRIaKxxQR4/lkcXFwzmgC5Z3R4MM5yAuSf5QHGvUAEEEACYaMRBMIhgAASDse09PKDH/xA/vjHP3ZrrhJIzjvvPGNcQgAxJhRFGcIiuCh8NIZAUQTaH4H16dQXuPujKJo0hoA/Ajz//PGiNgTCIkDuhUWSfiDgnwD5558ZLewngABif4zx0GACCCAGBwfTNAEEEDsmAotgO+KIF+kjoO6+qp3+smyYPUeyDQ2hOqCOvuLuj1CR0pmFBHj+WRhUXEoFAXIvFWHCSEsJkH+WBha3iiKAAFIUPhpDoDgCCCDF8aN19AQQQKJnHMcILILjoMwYENiewJbly2XVPRMlW1cfCRru/ogEK51aRoDnn2UBxZ3UECD3UhMqDLWQAPlnYVBxqWgCCCBFI6QDCAQngAASnB0t4yGAABIP56hHYREcNWH6h0BnAmr3x9rJz0r9/7weKp5MRYVINislVVXC3R+hoqUzCwnw/LMwqLiUCgLkXirChJGWEiD/LA0sbhVFAAGkKHw0hkBxBBBAiuNH6+gJIIBEzziOEVgEx0GZMSCwjUD9u4tl9W8elOamptCxcPRV6Ejp0GICPP8sDi6uGU2A3DM6PBhnOQHyz/IA414gAggggbDRCALhEEAACYcjvURHAAEkOrZx9swiOE7ajOU6AY6+cn0G4L9JBHj+mRQNbHGJALnnUrTx1TQC5J9pEcEeEwgggJgQBWxwlgACiLOhT43jCCCpCVW3hrIItiOOeJEOAlEdfZXznrs/0jEPsNIMAjz/zIgDVrhHgNxzL+Z4bA4B8s+cWGCJOQQQQMyJBZY4SAABxMGgp8xlBJCUBawLc1kE2xFHvDCfgDr66rP7HxDZujV0Y7n7I3SkdOgAAZ5/DgQZF40kQO4ZGRaMcoQA+edIoHHTFwEEEF+4qAyBcAkggITLk97CJ4AAEj7TJHpkEZwEdcZ0jcDGvy2QNY88KtLcHInr3P0RCVY6tZwAzz/LA4x7xhIg94wNDYY5QID8cyDIuOibAAKIb2Q0gEB4BIIKIP369ZPy8vLwDImxp5zdjY2NMY7KUEEJqDjV1NRIdXW1lJWVBe2GdgkTYBGccAAY3noCNbPmyrrfPxWpnxx9FSleOreUAM8/SwOLW8YTIPeMDxEGWkyA/LM4uLgWmAACSGB0NIRA8QT8CiCq/vr166Vv377So0eP4g1IoAcEkASgFzFkQ0OD1NbWSv/+/aW0tLSInmiaJAEWwUnSZ2zbCehLz++eINn6TZG6igASKV46t5QAzz9LA4tbxhMg94wPEQZaTID8szi4uBaYAAJIYHQ0hEDxBPwKIM3NzbJu3TqprKyUqqqq4g1IoAcEkASgFzFkXV2dbN68WQYMGCCZTKaInmiaJAEWwUnSZ2zbCSgBZOWv75XmTZsjdRUBJFK8dG4pAZ5/lgYWt4wnQO4ZHyIMtJgA+WdxcHEtMAEEkMDoaAiB4gn4FUDUiBs2bBB1LJH6i/w0vpBGACl+3sTVgxLc1I4jFbM+ffrENSzjRECARXAEUOkSAq0Eorz4PAe5pG9f6feN46V6+ClwhwAEfBDg+ecDFlUhECIBci9EmHQFAZ8EyD+fwKjuBAEEECfCjJOmEggigOTuZFBHYKmX0mkTQRBATJ2N29ulxA8ltqkjsNJ850w6aEdvJYvg6BkzgpsEOP7KzbjjdXoI8PxLT6yw1C4C5J5d8cSbdBEg/9IVL6yNhwACSDycGQUCeQkEEUBUR1u2bNEvp9WDraKiQv+FvhJC0iCG5C7SbmpqYlYYRkCJHup/JbKpOZbNZrXIpuYYJd0EWASnO35Yby6BOI6/YveHufHHMvMJ8PwzP0ZYaCcBcs/OuOJVOgiQf+mIE1bGSwABJF7ejAaB7QgEFUBUJ+oltbqbQf2FvnppnZaSu0hb+U4xk4AS0tQOI3XXTG7HjpmWYpVXAiyCvZKiHgT8EWgRQCZI86ZoLkBH/PAXD2pDoCMBnn/MCQgkQ4DcS4Y7o0JAESD/mAcQ6EwAAYRZAYEECRQjgOTMVuKH+kv9NIgg6sX6jjvuqE1fs2ZNKmxOcHokMrSKkVowpWE3USKAUjooi+CUBg6zU0Fgy/IV8vkTk6Rh2Seh28vF56EjpUPHCPD8cyzguGsMAXLPmFBgiIMEyD8Hg47LBQkggBRERAUIREcgDAEkOuvC75kHcfhM6RECXgiQe14oUQcC/gnoO0DumSjZunr/jQu0YPdH6Ejp0EECPP8cDDouG0GA3DMiDBjhKAHyz9HA43a3BBBAmCAQSJAAAkg2QfoMDQF3CLAIdifWeBovgaaaWln//H/LxlfniWTDfab1P/tMqR5+SrwOMRoELCPA88+ygOJOagiQe6kJFYZaSID8szCouFQ0AQSQohHSAQSCE0AACfdlUfBI0BICdhNgEWx3fPEuGQJR7v7ouf9Q2em6a5JxjFEhYBEBnn8WBRNXUkWA3EtVuDDWMgLkn2UBxZ1QCCCAhIKRTiAQjAACCAJIsJlDKwj4I8Ai2B8vakPAK4Go7v/Y84GJXk2gHgQg0A0Bnn9MDwgkQ4DcS4Y7o0JAESD/mAcQ6EwAAYRZAYEECSCAIIAkOP0Y2iECLIIdCjauxkYgqh0gmcpK2ePu8bH5wUAQsJkAzz+bo4tvJhMg90yODrbZToD8sz3C+BeEAAJIEGq0gUBIBBBAEEBCmkp0A4FuCbAIZoJAIBoC6g6QmukvyYZZc6S5sTGUQbj7IxSMdAIBTYDnHxMBAskQIPeS4c6oEODZxxyAQH4CCCDMDAgkSAABBAEkwenH0A4R4B8wmPgFAAAgAElEQVShDgUbV2MlkBNAamfOFmlqCmVsjr8KBSOdQAABhDkAgQQJsPZMED5DO0+A/HN+CgAgDwEEEKYFBBIkgACCAJLg9GNohwiwCHYo2LgaG4GojsBCAIkthAzkAAGefw4EGReNJEDuGRkWjHKEAPnnSKBx0xcBBBBfuKgMgXAJIIAggIQ7o+gNAvkJsAhmZkAgGgJhH4HF/R/RxIle3SXA88/d2ON5sgTIvWT5M7rbBMg/t+OP9/kJIIAwMyCQIAEEEASQBKcfQztEgEWwQ8HG1VgJhH0EVml1tQwed2usPjAYBGwmwPPP5ujim8kEyD2To4NtthMg/2yPMP4FIYAAEoQabSAQEgEEEASQkKYS3UCgWwIsgpkgEAifQBRHYHEBevhxoke3CfD8czv+eJ8cAXIvOfaMDAHyjzkAgc4EEECYFRBIkAACCAJIgtOPoR0iwCLYoWDjamwE1O6P9c//t2x8dZ5INpznGfd/xBY+BnKEAM8/RwKNm8YRIPeMCwkGOUSA/HMo2LjqmQACiGdUVIRA+AQQQMJ5YRR+ZOgRAnYRYBFsVzzxJnkCUez+UF4hgCQfWyywiwDPP7viiTfpIUDupSdWWGofAfLPvpjiUfEEEECKZ0gPEAhMAAEEASTw5KEhBHwQYBHsAxZVIeCRwJblK+TzJyZJw7JPPLYoXA0BpDAjakDADwGef35oURcC4REg98JjSU8Q8EuA/PNLjPouEEAAcSHK+GgsAQQQBBBjJyeGWUWARbBV4cQZAwiwA8SAIGACBDwQ4PnnARJVIBABAXIvAqh0CQGPBMg/j6Co5hQBBBCnwo2zphFAAEEAMW1OYo+dBFgE2xlXvEqWgLoDpGb6S7Jh1hxpbmws3phMRvb8zYTi+6EHCECgjQDPPyYDBJIhQO4lw51RIaAIkH/MAwh0JoAAwqyAQIIEEEAQQBKcfgztEAEWwQ4FG1djI5ATQGpnzhZpaip+XASQ4hnSAwQ6EOD5x5SAQDIEyL1kuDMqBBBAmAMQyE8AAYSZAYEECSCAIIAkOP0Y2iEC/CPUoWDjaiwEojgCK1NZKXvcPT4W+xkEAq4Q4PnnSqTx0zQC5J5pEcEelwiQfy5FG1+9EkAA8UqKehCIgAACCAJIBNOKLiHQiQCLYCYFBMInEPYl6KXV1TJ43K3hG0qPEHCYAM8/h4OP64kSIPcSxc/gjhMg/xyfALiflwACCBMDAgkSQABBAElw+jG0QwRYBDsUbFyNhUAUO0AQQGIJHYM4RoDnn2MBx11jCJB7xoQCQxwkQP45GHRcLkgAAaQgIipAIDoCCCAIINHNLnqGwDYCLIKZDRAIn0DYl6D3P/tMqR5+SviG0iMEHCbA88/h4ON6ogTIvUTxM7jjBMg/xycA7uclgADCxIBAggQQQBBAEpx+DO0QARbBDgUbV2MjEPYl6Hs+MDE22xkIAq4Q4PnnSqTx0zQC5J5pEcEelwiQfy5FG1+9EkAA8UqKehCIgAACCAJIBNOKLiHQiQCLYCYFBMIlEMURWAgg4caI3iCgCPD8Yx5AIBkC5F4y3BkVAjz7mAMQyE8AAYSZAYEECSCAIIAkOP0Y2iEC/CPUoWDjamwEwj4CCwEkttAxkEMEeP45FGxcNYoAuWdUODDGMQLkn2MBx11PBBBAPGGiEgSiIYAAggASzcyiVwhsT4BFMDMCAuET4Ais8JnSIwTCJsDzL2yi9AcBbwTIPW+cqAWBKAiQf1FQpc+0E0AASXsEsT/VBBBAEEBSPYExPjUEWASnJlQYmhICHIGVkkBhpvMEeP45PwUAkBABci8h8AwLAY5/ZA5AIC8BBBAmBgQSJIAAggCS4PRjaIcI8I9Qh4KNq7ER4Ais2FAzEAQCE+D5FxgdDSFQFAFyryh8NIZAUQTIv6Lw0dhSAggglgYWt9JBAAEEASQdMxUr006ARXDaI4j9JhPYsnyFfP7EJGlY9klRZnIHSFH4aAyBvAR4/jExIJAMAXIvGe6MCgFFgPxjHkCgMwEEEGYFBBIkgACCAJLg9GNohwiwCHYo2LgaGwF2gMSGmoEgEJgAz7/A6GgIgaIIkHtF4aMxBIoiQP4VhY/GlhJAALE0sLiVDgIIIAgg6ZipWJl2AiyC0x5B7DeNAHeAmBYR7IFAfgI8/5gZEEiGALmXDHdGhYAiQP4xDyDQmQACCLMCAgkSQABBAElw+jG0QwRYBDsUbFyNjQA7QGJDzUAQCEyA519gdDSEQFEEyL2i8NEYAkURIP+KwkdjSwkggFgaWNxKBwEEEASQdMxUrEw7ARbBaY8g9ptIICeA1M6cLdLUVLSJ3AFSNEI6gEAnAjz/mBQQSIYAuZcMd0aFgCJA/jEPINCZAAIIswICCRJAAEEASXD6MbRDBFgEOxRsXI2FAEdgxYKZQSBQNAGef0UjpAMIBCJA7gXCRiMIhEKA/AsFI51YRgABxLKA4k66CCCAIICka8ZibVoJsAhOa+Sw22QCHIFlcnSwDQItBHj+MRMgkAwBci8Z7owKAZ59zAEI5CeAAMLMgECCBBBAEEASnH4M7RAB/hHqULBxNXYCW5avkM+fmCQNyz4pamyOwCoKH40hkJcAzz8mBgSSIUDuJcOdUSGAAMIcgAACCHMAAsYRQABBADFuUmKQlQT4R6iVYcWphAmwAyThADA8BDwQ4PnnARJVIBABAXIvAqh0CQGPBMg/j6Co5hQBdoA4FW6cNY0AAggCiGlzEnvsJMAi2M644lVyBLgDJDn2jAwBPwR4/vmhRV0IhEeA3AuPJT1BwC8B8s8vMeq7QAABxIUo46OxBBBAEECMnZwYZhUBFsFWhRNnDCHADhBDAoEZEOiGAM8/pgcEkiFA7iXDnVEhoAiQf8wDCHQmgADCrIBAggQQQBBAEpx+DO0QARbBDgUbV2MloESQ9c//t2x8dZ5ItrhnGneAxBo6BnOEAM8/RwKNm8YRIPeMCwkGOUSA/HMo2LjqmQACiGdUVIRA+AQQQIp7WRR+ROgRAnYSYBFsZ1zxKjkCYe/+UJ4ggCQXT0a2lwDPP3tji2dmEyD3zI4P1tlNgPyzO754F4wAAkgwbrSCQCgEEEAQQEKZSHQCgQIEWAQzRSAQHoEo7v+QTEb2/M2E8IykJwhAQBPg+cdEgEAyBMi9ZLgzKgR49jEHIJCfAAIIMwMCCRJAAEEASXD6MbRDBPhHqEPBxtVYCIS+AwQBJJa4MYh7BHj+uRdzPDaDALlnRhywwk0C5J+bccfr7gkggDBDIJAgAQQQBJAEpx9DO0SARbBDwcbVWAmEJYRkKitlj7vHx2o7g0HABQI8/1yIMj6aSIDcMzEq2OQKAfLPlUjjpx8CCCB+aFEXAiETQABBAAl5StEdBPISYBHMxIBANARyAkjtzNkiTU2BBymtrpbB424N3J6GEIBAfgI8/5gZEEiGALmXDHdGhYAiQP4xDyDQmQACCLMCAgkSQABBAElw+jG0QwRYBDsUbFyNhUBYOz9yxiKAxBI2BnGQAM8/B4OOy0YQIPeMCANGOEqA/HM08LjdLQEEECYIBBIkgACCAJLg9GNohwiwCHYo2LgaOYEoLkFHAIk8bAzgKAGef44GHrcTJ0DuJR4CDHCYAPnncPBxvUsCCCBMDggkSAABBAEkwenH0A4RYBHsULBxNRYCYe8A6X/2mVI9/JRYbGcQCLhEgOefS9HGV5MIkHsmRQNbXCNA/rkWcfz1QgABxAsl6kAgIgIIIAggEU0tuoXAdgRYBDMhIBANgbCEkD0fmBiNgfQKAccJ8PxzfALgfmIEyL3E0DMwBLgDhDkAgTwEEECYFhBIkAACCAJIgtOPoR0iwD9CHQo2rsZKIKxL0BFAYg0bgzlEgOefQ8HGVaMIkHtGhQNjHCNA/jkWcNz1RAABxBMmKkEgGgIIIAgg0cwseoXA9gRYBDMjIBAugbB2fuSsQgAJNz70BoEcAZ5/zAUIJEOA3EuGO6NCQBEg/5gHEOhMAAGEWQGBBAkggCCAJDj9GNohAiyCHQo2rkZOIIpL0BFAIg8bAzhKgOefo4HH7cQJkHuJhwADHCZA/jkcfFzvkgACCJMDAgkSQABBAElw+jG0QwRYBDsUbFyNhQA7QGLBzCAQKJoAz7+iEdIBBAIRIPcCYaMRBEIhQP6FgpFOLCOAAGJZQHEnXQQQQBBA0jVjsTatBFgEpzVy2G06gbCEEHaAmB5p7EsrAZ5/aY0cdqedALmX9ghif5oJkH9pjh62R0UAASQqsvQLAQ8EEEAQQDxME6pAoGgCLIKLRkgHEMhLgEvQmRgQMJsAzz+z44N19hIg9+yNLZ6ZT4D8Mz9GWBg/AQSQ+JlHMmJTU5O8+uqrMnfuXPnkk0+kpqZGqqqqZNCgQXLUUUfJCSecIH379g11bDXmRx99JB988IEsXbpU/vnPf8qKFSskm215qX388cfLNddc43nMd955R37+8597rq8qfuMb35Arr7zSc5tFixbJzJkz5f3335d169ZJWVmZDBw4UIYNG6b72nXXXT33FUZFBBAEkDDmEX1AoBABFsGFCPFzCPgjENbOj9yo7ADxx5/aEPBKgOefV1LUg0C4BMi9cHnSGwT8ECD//NCirisEEEAsiLQSHSZMmCAffvhhl97069dPrrrqKjnssMNC8fiFF16Qxx9/XJQI0lUxSQCpr6+Xhx9+WItEXZXS0lL5zne+I//6r/8aCiMvnSCAIIB4mSfUgUCxBFgEF0uQ9hDYRoBL0JkNEEgPAZ5/6YkVltpFgNyzK554ky4C5F+64oW18RBAAImHc2SjrF27VsaOHSvr16/XY2QyGdlvv/1kp5120rtA1I6HhoYG/TP1gl/VPeigg4q25+mnn5Znnnmm236KEUD69++vd64UKkOGDJGvf/3r3VZTIs24ceM0i1zZfff/z96bQGlVnPn/Tw8IDSJ02I4aRFEgEVETkxCjRuN+nDmjHkzEuPzcUKMhigpqREQDsgSFhlYUUYMLf9FxGTyJCYg7btHI4hYZRQINtiyy2Q0NPd3/U1fenoZe3rq36r51b93PPcczkX6eqno+z/NYRX/n3tpPDjzwwIDNJ598Ihs3bqz/mRJBfvnLX+ab2srPEUAQQKwUEoNAIA8BDsGUCATsEuANELs8GQ0CcRFg/4uLLONCoGUC9B4VAgF3BOg/d+yZObkEEECSmxutlY0aNSr4Bb56unXrJjfccIPsv//+9b6bN2+WKVOm1P/yv0OHDlJWVhZ8HsvkyQkg6vNRBx10kPTu3Tv4vy+88IK8/fbbwdAmAki/fv3ktttuM1live8TTzwhTz/9dPDve+yxh1x11VVy9NFH1/9cCSSzZ8+W5557rv7P1NxqDXE/CCAIIHHXGONDQBHgEEwdQCAeAraEED6BFU9+GBUC7H/UAATcEKD33HBnVgjwdz9qAAJNE0AASXFlvP/++zJ+/PggAnWXhfrfPXv2bBTRtm3bZPjw4fLVV18FPzvzzDPl3HPPNYp87dq1gZhQUlKyyzj33HNPcMeGepIggKi3YIYMGSLV1dXBmi677DI5+eSTm4y9tLS0/hNZffv2lTFjxhgx0nFGAEEA0akTbCBgSoC/hJoSxB8CLROoLl8l6x6dJdtXrIyECgEkEjacIJCXAPtfXkQYQCAWAvReLFgZFAJaBOg/LUwYZYwAAkiKE64+67Rw4cIgghNPPFGuuOKKZqN5/fXXgzc/1KPeApkxY0bwSSzbT9IEEPVWx2OPPRaEuc8++4gSOdRnwpp61q1bF1zaXldXF/x4woQJ0qtXL9uIdhkPAQQBJNYCY3AI7CTAIZhSgEA8BHgDJB6ujAoBWwTY/2yRZBwIhCNA74XjhTUEbBKg/2zSZCxfCCCApDST6q2OSy+9VHbs2BFEoN5WUG8tNPcou8GDB8vWrVsDk1tvvVX69+9vPfqkCSAjR46UTz/9NIjz17/+dd4LzhXHJUuWBPZnnXWWDBo0yDqjhgMigCCAxFpgDA6BnQQ4BFMKELBLwJbwkVsVb4DYzQ+jQSBHgP2PWoCAGwL0nhvuzAoBRYD+ow4g0JgAAkhKq2Lx4sVyxx13BKtv27atzJw5M+8bHQ1/uT9w4EA555xzrEefJAFEXXB+wQUX1L/RkU8kUjCeeeaZ4D4Q9agL1kePHm2dEQLI3gGCiooKqa1FAIm1wBgcAjsJcAimFCBgj0B1eblUlJZJbWWVtUERQKyhZCAI7EKA/Y+CgIAbAvSeG+7MCgFFgP6jDiDQmAACSEqr4vnnnw9ED/X06dOnXgxpKZxZs2bJnDlzApMBAwbIsGHDrEdvSwBRl6orkWb58uVSWVkpxcXFwX0j6i0Xdcm7+g96vkf5qkvh1aM+e/Xoo49KmzZtWnRbtGiRjB07NrBRnwp76KGH8k1j9HPeAEEAMSognCGgSYBDsCYozCCgSYA3QDRBYQYBxwTY/xwngOkzS4Dey2zqCTwBBOi/BCSBJSSOAAJI4lKit6AHHnhA5s2bFxgfddRRMnTo0LyOc+fOlQcffDCw69Gjh0yaNCmvT1gDWwJIS/N2795dTj/99OAy8+bu81D+b775ZnDnh3o6deoU3HuS7ykvL5frrruu3kxx7tixYz63yD9HAEEAiVw8OEIgBAEOwSFgYQqBEARsCSG8ARICOqYQCEGA/S8ELEwhYJEAvWcRJkNBICQB+i8kMMwzQQABJKVpnjx5srz11lvB6k877TS5+OKL80byzjvvyF133RXYqbcp7r///rw+YQ0KIYDk1vTDH/5Qrr322uDtkKYeJRApAUM96q2RiRMn5g3nm2++kUsuuaTeTgko++67b16/hgbr16/Pa6/4q0volQCydu3avPa+GKiNWAlY6lmzZg2fwPIlscSReAL0XuJTxAJTTkB9FmvNw4/J9hUrI0Vy0PR7IvnhBAEItEyA/Y8KgYAbAvSeG+7MCgFFgP6jDiDQmEC3bt3yXh1RCG5FdXV1dYWYyJc5xo0bJwsXLgzCOeOMM+S8887LG5qyV37qUaLBI488ktcnrIGpAKIEh6OPPloOO+ww6dmzZ/3bF19//bV8+OGHoj79pd7SyD1HHHFE8Jmrpj6J9dxzz8ljjz0WmOp+JkzdG3L++efXjz9+/Hg58MADQ2E4++yz89rfe++90qVLl7x2GEAAAhCAAAQgkFwC2zdskFXP/LdU/G2e1G7fHnmhR895OrIvjhCAAAQgAAEIQAACEIAABCCQfAIIICFz9Ic//CEQBNRz1llnyaBBg/KOoOyVn3qUYJC77DuvYwgDEwFk27Zt0rp16+Cf5p6amprgM14vvvhivcmQIUPk2GOPbeTy1FNPyZNPPhn8+cEHHyy333573kjUpdwNL4dXvL7//e/n9WtogAASChfGEIAABCAAgdQRsCV85AJHAEldCbBgCEAAAhCAAAQgAAEIQAACoQgggITCJcGbHL69AaKLQIkUSpj4+OOPA5f99tuv/tNeDcdw9QYIn8BqPpO8iqlb5dhBwC4Bes8uT0bLNoHqleWyevJUqa2stAaCT2BZQ8lAENiFAPsfBQEBNwToPTfcmRUCigD9Rx1AoDEBPoGV0qrw8Q6QMKlo+DaL8ps2bZp07dp1lyFc3QESJg4uQecS9DD1gi0EohLgIryo5PCDQNMEbF1+nhudS9CpNAjEQ4D9Lx6ujAqBfATovXyE+DkE4iNA/8XHlpHTS4BL0FOaO3W5t/oFv3qOOuooGTp0aN5I5s6dG3w+Sj09evSQSZMm5fUJa2DyCawwc6lPYV1wwQXBJeLqGTFihBx++OG7DPHmm2+KulNEPZ06dZIZM2bknULdL3LdddfV2ynOHTt2zOsX1QABBAEkau3gB4EwBDgEh6GFLQT0CdgSQhBA9JljCYEwBNj/wtDCFgL2CNB79lgyEgTCEqD/whLDPgsEEEBSmmV1GfjMmTOD1ete8D1r1iyZM2dO4DNgwAAZNmyY9egLJYCohV9xxRWyYcOGIIarr75ajjnmmF3iWb58eXBBunqKiork0UcflTZt2rQY86JFi2Ts2LGBTYcOHeShhx6yzqjhgAggCCCxFhiDQ2AnAQ7BlAIE4iVQXb5K1j06S7avWBlpIgSQSNhwgkBeAux/eRFhAIFYCNB7sWBlUAhoEaD/tDBhlDECCCApTfjixYvljjvuCFbftm3bQAxp1apVi9GMGTNGlixZEtgMHDhwl8u+bWEopABy4YUXytatW4OlK6Hjxz/+8S5hbN++PXhLpK6uLvhzFX/fvn1bDPWZZ56pvxz+e9/7nowePdoWmibHQQBBAIm1wBgcAjsJcAimFCAQDwHeAImHK6NCwBYB9j9bJBkHAuEI0HvheGENAZsE6D+bNBnLFwIIICnN5LZt2+TSSy+VHTt2aP1yX9kNHjy4XjC49dZbpX///tajL5QAsmbNGhkyZEj9+tVbG717924Uz8iRI+XTTz8N/vzcc8+VM888s8WYlaikxCX1nHXWWTJo0CDrjBoOiACCABJrgTE4BHYS4BBMKUDALgFbwkduVbwBYjc/jAaBHAH2P2oBAm4I0HtuuDMrBBQB+o86gEBjAgggKa6KcePGycKFC4MITjrpJLn88subjWbBggUyderU4Od77rmnqLst8r0xEgVNoQSQ2bNni3pbQz3t2rULPlXVVDzPPfecPPbYY4HdvvvuW38nSFOxrV+/Xn77299Kbe23v5QfP368HHjggVEwaPsggCCAaBcLhhAwIMAh2AAerhDYjUB1eblUlJZJbWWVNTYIINZQMhAEdiHA/kdBQMANAXrPDXdmhYAiQP9RBxBoTAABJMVV8f777we/pFdP69atZcKECbLffvs1iqi6ulqGDx8uFRUVwc/UWxDqbYg4nqgCiFrjHnvsEfyHOt+zdOlSuf322+vffjnxxBOD+0CaejZt2hS8KaLGV4+yU/ZNPVOmTJE33ngj+JH6VJb6ZFbcDwIIAkjcNcb4EOAQTA1AwD4B3gCxz5QRIRAHAX4JFAdVxoRAfgL0Xn5GWEAgLgL0X1xkGTfNBBBA0pw9ERk1apR88sknQRTdunWTG2+8UXr27Fkf1ZYtW0T9Yj9394e62LusrCx4C2T3Z/fPSqmxDznkkFCEogogH330UfBWymmnnSZHHnmkdOzYsdG86jNeL730UvBGR07QUG9/TJo0Sbp06dLsOp944gl5+umng5+rS9CvuuoqOeqoo+rta2pqRNnkLohXP7jtttukX79+oWKPYowAggASpW7wgUBYAhyCwxLDHgJ6BGwJIbwBoscbKwiEJcD+F5YY9hCwQ4Des8ORUSAQhQD9F4UaPr4TQABJeYbVZ5tuvvlm2bBhQxBJUVFR8It7ldjNmzfLBx98UC8WqE9EKdtDDz20yajDCiDqrZLdn3Xr1kllZWXwx0pk6dq1ayObiRMnNvozJYCotzpyMajPVX33u98VJdioR8Wn3vzIja3+TL0xctNNNzUbT24SJXCoO0I+/PDD+nmVSNSrV6/gLRIlIOX4KYOzzz5bfvnLXxakMhBAEEAKUmhMknkCHIIzXwIAiJmAqRCCABJzghg+swTY/zKbegJ3TIDec5wAps80Afov0+kn+GYIIIB4UBqrVq0K3vJYvnx5s9GoNyrUmw9HHHFEszZhBRAlFER5nnzyyUZuDQUQnTGVeKHi2X///XXMpaqqSqZPny5vvfVWs/ZKIPrVr34lAwcO1BrThhECCAKIjTpiDAjkI8AhOB8hfg4BMwI5AWTzq6+L1NSEHgwBJDQyHCCgRYD9TwsTRhCwToDes46UASGgTYD+00aFYYYIIIB4kmz1loO6v0L9s3LlSlF3X6g3MLp37y4DBgyQ448/vsnPSjUM36UAoi4eVwLOp59+Gvzz5Zdfivp8l/pHiQTt27cPPvHVp0+fIJ7+/ftHypz6FNirr74avE2ycePG4OJ09fmsww8/XE444QTp0aNHpHGjOiGAIIBErR38IBCGAIfgMLSwhYA+AdM3P4KZioqk17Sp+pNiCQEIaBNg/9NGhSEErBKg96ziZDAIhCJA/4XChXFGCCCAZCTRhJlMAgggCCDJrExW5RsBDsG+ZZR4XBOwInzkgkAAcZ1O5veYAPufx8kltEQToPcSnR4W5zkB+s/zBBNeJAIIIJGw4QQBOwQQQBBA7FQSo0CgZQIcgqkQCNgjUF1eLhWlZVJbWWVnUAQQOxwZBQJNEGD/oywg4IYAveeGO7NCQBGg/6gDCDQmgABCVUDAIQEEEAQQh+XH1BkiwCE4Q8km1IIQ4A2QgmBmEggYE2D/M0bIABCIRIDei4QNJwhYIUD/WcHIIJ4RQADxLKGEky4CCCAIIOmqWFabVgIcgtOaOdaddAJWhBDeAEl6mllfigmw/6U4eSw91QTovVSnj8WnnAD9l/IEsvxYCCCAxIKVQSGgRwABBAFEr1KwgoAZAQ7BZvzwhkA+AiZCSFFxsRwweWK+Kfg5BCAQgQD7XwRouEDAAgF6zwJEhoBARAL0X0RwuHlNAAHE6/QSXNIJIIAggCS9RlmfHwQ4BPuRR6JINgElgmz481/kmwVvhlpoq5IS6TludCgfjCEAAT0C7H96nLCCgG0C9J5toowHAX0C9J8+KyyzQwABJDu5JtIEEkAAQQBJYFmyJA8JcAj2MKmElBgCJm9/qCAQQBKTShbiIQH2Pw+TSkipIEDvpSJNLNJTAvSfp4klLCMCCCBG+HCGgBkBBBAEELMKwhsCegQ4BOtxwgoCYQiYCh+5uRBAwlDHFgLhCLD/heOFNQRsEaD3bJFkHAiEJ0D/hWeGh/8EEED8zzERJpgAAggCSILLk6V5RIBDsEfJJBTnBGwJHwggzlPJAjJAgP0vA0kmxEQSoPcSmRYWlREC9F9GEk2YoQgggITChTEE7BJAAEEAsVtRjAaBpglwCKYyIGCHQHV5uVSUlkltZZWdAaPO8TIAACAASURBVPkEljWODASBpgiw/1EXEHBDgN5zw51ZIaAI0H/UAQQaE0AAoSog4JAAAggCiMPyY+oMEeAQnKFkE2rsBHgDJHbETAABawTY/6yhZCAIhCJA74XChTEErBKg/6ziZDBPCCCAeJJIwkgnAQQQBJB0Vi6rThsBDsFpyxjrTQMBW0LId878Tyk59ZQ0hMwaIZA6Aux/qUsZC/aEAL3nSSIJI5UE6L9Upo1Fx0wAASRmwAwPgZYIIIAggNAhECgEAQ7BhaDMHFklYCSEFBVJr2lTs4qOuCEQOwH2v9gRMwEEmiRA71EYEHBHgP5zx56Zk0sAASS5uWFlGSCAAIIAkoEyJ8QEEOAQnIAksARvCeQEkM2vvi5SUxMuTgSQcLywhkBIAux/IYFhDgFLBOg9SyAZBgIRCNB/EaDh4j0BBBDvU0yASSaAAIIAkuT6ZG3+EOAQ7E8uiSQ5BIze/GgQRq97y5ITFCuBgGcE2P88SyjhpIYAvZeaVLFQDwnQfx4mlZCMCSCAGCNkAAhEJ4AAggASvXrwhIA+AQ7B+qywhEA+AraEj9w8CCD5iPNzCEQnwP4XnR2eEDAhQO+Z0MMXAmYE6D8zfnj7SQABxM+8ElVKCCCAIICkpFRZZsoJcAhOeQJZfmIIVJeXS0VpmdRWVllbEwKINZQMBIFGBNj/KAoIuCFA77nhzqwQUAToP+oAAo0JIIBQFRBwSAABBAHEYfkxdYYIcAjOULIJNXYCvAESO2ImgIA1Aux/1lAyEARCEaD3QuHCGAJWCdB/VnEymCcEEEA8SSRhpJMAAggCSDorl1WnjQCH4LRljPWmgYAtIYQ3QNKQbdaYVgLsf2nNHOtOOwF6L+0ZZP1pJkD/pTl7rD0uAgggcZFlXAhoEEAAQQDRKBNMIGBMgEOwMUIGgECzBEyFEAQQigsC8RFg/4uPLSNDoCUC9B71AQF3BOg/d+yZObkEEECSmxtWlgECCCAIIBkoc0JMAAEOwQlIAkvwnkB1+SpZ9+gs2b5ipX6sRUXSa9pUfXssIQCBUATY/0LhwhgC1gjQe9ZQMhAEQhOg/0IjwyEDBBBAMpBkQkwuAQQQBJDkVicr84kAh2CfskksSSNg9AYIAkjS0sl6PCPA/udZQgknNQTovdSkioV6SID+8zCphGRMAAHEGCEDQCA6AQQQBJDo1YMnBPQJcAjWZ4UlBHQJGAkfuUkQQHRxYweBSATY/yJhwwkCxgToPWOEDACByATov8jocPSYAAKIx8kltOQTQABBAEl+lbJCHwhwCPYhi8SQFAJWhI8GwXAHSFIyyzp8JMD+52NWiSkNBOi9NGSJNfpKgP7zNbPEZUIAAcSEHr4QMCSAAIIAYlhCuENAiwCHYC1MGEEgL4Hq8nKpKC2T2sqqvLa6BggguqSwg0B4Aux/4ZnhAQEbBOg9GxQZAwLRCNB/0bjh5TcBBBC/80t0CSeAAIIAkvASZXmeEOAQ7EkiCSMRBHgDJBFpYBEQ0CLA/qeFCSMIWCdA71lHyoAQ0CZA/2mjwjBDBBBAMpRsQk0eAQQQBJDkVSUr8pEAh2Afs0pMrgnYEkJ4A8R1JpnfZwLsfz5nl9iSTIDeS3J2WJvvBOg/3zNMfFEIIIBEoYYPBCwRQABBALFUSgwDgRYJcAimQCAQHwEjIYRL0ONLDCNDQETY/ygDCLghQO+54c6sEFAE6D/qAAKNCSCAUBUQcEgAAQQBxGH5MXWGCHAIzlCyCdUZgZwQsvnFl/XXgACizwpLCEQgwP4XARouELBAgN6zAJEhIBCRAP0XERxuXhNAAPE6vQSXdAIIIAggSa9R1ucHAQ7BfuSRKJJNAAEk2flhddkkwP6XzbwTtXsC9J77HLCC7BKg/7KbeyJvngACCNUBAYcEEEAQQByWH1NniACH4Awlm1ALToBPYBUcORNCQJsA+582KgwhYJUAvWcVJ4NBIBQB+i8ULowzQgABJCOJJsxkEkAAQQBJZmWyKt8IcAj2LaPEkwQCRsJHgwC4BD0J2WQNvhJg//M1s8SVdAL0XtIzxPp8JkD/+ZxdYotKAAEkKjn8IGCBAAIIAoiFMmIICOQlwCE4LyIMIKBNwJbwkZsQAUQbPYYQCE2A/S80MhwgYIUAvWcFI4NAIBIB+i8SNpw8J4AA4nmCCS/ZBBBAEECSXaGszhcCHIJ9ySRxuCZQXV4uFaVlUltZZW0pCCDWUDIQBBoRYP+jKCDghgC954Y7s0JAEaD/qAMINCaAAEJVQMAhAQQQBBCH5cfUGSLAIThDySbU2AnwBkjsiJkAAtYIsP9ZQ8lAEAhFgN4LhQtjCFglQP9ZxclgnhBAAPEkkYSRTgIIIAgg6axcVp02AhyC05Yx1psGAlaEkKIi6TVtahrCZY0QSCUB9r9Upo1Fe0CA3vMgiYSQWgL0X2pTx8JjJIAAEiNchoZAPgIIIAgg+WqEn0PABgEOwTYoMgYEmiZgJIQggFBWEIiVAPtfrHgZHALNEqD3KA4IuCNA/7ljz8zJJYAAktzcsLIMEEAAQQDJQJkTYgIIcAhOQBJYgvcEqstXydo/PSI7Vq/WjxUBRJ8VlhCIQID9LwI0XCBggQC9ZwEiQ0AgIgH6LyI43LwmgADidXoJLukEEEAQQJJeo6zPDwIcgv3II1EkkwBvgCQzL6wKAooA+x91AAE3BOg9N9yZFQLsfdQABJomgABCZUDAIQEEEAQQh+XH1BkiwF9CM5RsQi0YASPhI7dK3gApWL6YKJsE2P+ymXeidk+A3nOfA1aQXQL0X3ZzT+TNE0AAoTog4JAAAggCiMPyY+oMEeAQnKFkE2rsBKwIHw1W2evestjXzAQQyCoB9r+sZp64XROg91xngPmzTID+y3L2ib05Aggg1AYEHBJAAEEAcVh+TJ0hAhyCM5RsQo2VQHV5uVSUlkltZZW1eRBArKFkIAg0IsD+R1FAwA0Bes8Nd2aFgCJA/1EHEGhMAAGEqoCAQwIIIAggDsuPqTNEgENwhpJNqLET4A2Q2BEzAQSsEWD/s4aSgSAQigC9FwoXxhCwSoD+s4qTwTwhgADiSSIJI50EEEAQQNJZuaw6bQQ4BKctY6w3DQRsCSG8AZKGbLPGtBJg/0tr5lh32gnQe2nPIOtPMwH6L83ZY+1xEUAAiYss40JAgwACCAKIRplgAgFjAhyCjREyAASaJWAkhHAJOpUFgVgJsP/FipfBIdAsAXqP4oCAOwL0nzv2zJxcAgggyc0NK8sAAQQQBJAMlDkhJoAAh+AEJIEleE9ACSFfP/2sVL77nn6sCCD6rLCEQAQC7H8RoOECAQsE6D0LEBkCAhEJ0H8RweHmNQEEEK/TS3BJJ4AAggCS9BplfX4Q4BDsRx6JItkEAgHkqWek8r1/6C8UAUSfFZYQiECA/S8CNFwgYIEAvWcBIkNAICIB+i8iONy8JoAA4nV6CS7pBBBAEECSXqOszw8CHIL9yCNRJJMAn8BKZl5YFQQUAfY/6gACbgjQe264MysE2PuoAQg0TQABhMqAgEMCCCAIIA7Lj6kzRIC/hGYo2YRaMAJGwkdulbwBUrB8MVE2CbD/ZTPvRO2eAL3nPgesILsE6L/s5p7ImyeAAEJ1QMAhAQQQBBCH5cfUGSLAIThDySbU2AlYET4QQGLPExNAQBFg/6MOIOCGAL3nhjuzQoC9jxqAQNMEEECoDAg4JIAAggDisPyYOkME+EtohpJNqLESqC4vl4rSMqmtrLI2T697y6yNxUAQgMCuBNj/qAgIuCFA77nhzqwQQAChBiCAAEINQCBxBBBAEEASV5QsyEsC/CXUy7QSlCMCVt8AEREEEEeJZNpMEGD/y0SaCTKBBOi9BCaFJWWGAP2XmVQTaAgCvAESAhamELBNAAEEAcR2TTEeBJoiwCGYuoCAfQJWhBDuALGfGEaEQAMC7H+UAwTcEKD33HBnVggoAvQfdQCBxgQQQKgKCDgkgACCAOKw/Jg6QwQ4BGco2YRacAJGQggCSMHzxYTZIsD+l618E21yCNB7yckFK8keAfovezkn4vwEEEDyM8ICArERQABBAImtuBgYAg0IcAimHCAQPwElhKyb9bhs/eBD/ckQQPRZYQmBCATY/yJAwwUCFgjQexYgMgQEIhKg/yKCw81rAgggXqeX4JJOAAEEASTpNcr6/CDAIdiPPBJF8gl8894/ZO2DM/UXigCizwpLCEQgwP4XARouELBAgN6zAJEhIBCRAP0XERxuXhNAAPE6vQSXdAIIIAggSa9R1ucHAQ7BfuSRKJJNIHgD5NFZsvWjj/UXigCizwpLCEQgwP4XARouELBAgN6zAJEhIBCRAP0XERxuXhNAAPE6vQSXdAIIIAggSa9R1ucHAQ7BfuSRKJJJgDtAkpkXVgUBRYD9jzqAgBsC9J4b7swKAfY+agACTRNAAKEyIOCQAAIIAojD8mPqDBHgL6EZSjahFoyAkfCRWyVvgBQsX0yUTQLsf9nMO1G7J0Dvuc8BK8guAfovu7kn8uYJIIBQHRBwSAABBAHEYfkxdYYIcAjOULIJNXYCVoQPBJDY88QEEFAE2P+oAwi4IUDvueHOrBBg76MGINA0AQQQKgMCDgkggCCAOCw/ps4QAf4SmqFkE2qsBKrLy6WitExqK6vszNO6tfQqm2xnLEaBAAQaEWD/oygg4IYAveeGO7NCAAGEGoAAAgg1AIHEEUAAQQBJXFGyIC8J8JdQL9NKUI4I8AaII/BMC4EIBNj/IkDDBQIWCNB7FiAyBAQiEqD/IoLDzWsCvAHidXoJLukEEEAQQJJeo6zPDwIcgv3II1Eki4AVIYQ7QJKVVFbjHQH2P+9SSkApIUDvpSRRLNNLAvSfl2klKEMCCCCGAHGHgAkBBBAEEJP6wRcCugQ4BOuSwg4C4QkYCSEIIOGB4wGBEATY/0LAwhQCFgnQexZhMhQEQhKg/0ICwzwTBBBAMpFmgkwqAQQQBJCk1ibr8osAh2C/8kk0ySSghJA1Mx6U6s+X6S8QAUSfFZYQiECA/S8CNFwgYIEAvWcBIkNAICIB+i8iONy8JoAA4nV6CS7pBBBAEECSXqOszw8CHIL9yCNRJJ/Axr/OlQ3P/Vl/oQgg+qywhEAEAux/EaDhAgELBOg9CxAZAgIRCdB/EcHh5jUBBBCv00twSSeAAIIAkvQaZX1+EOAQ7EceiSLZBII3QKbPkOovlusvFAFEnxWWEIhAgP0vAjRcIGCBAL1nASJDQCAiAfovIjjcvCaAAOJ1egku6QQQQBBAkl6jrM8PAhyC/cgjUSSTAHeAJDMvrAoCigD7H3UAATcE6D033JkVAux91AAEmiaAAEJlQMAhAQQQBBCH5cfUGSLAX0IzlGxCLRgBI+Ejt0reAClYvpgomwTY/7KZd6J2T4Dec58DVpBdAvRfdnNP5M0TQAChOiDgkAACCAKIw/Jj6gwR4BCcoWQTauwErAgfCCCx54kJIKAIsP9RBxBwQ4Dec8OdWSHA3kcNQKBpAgggVAYEHBJAAEEAcVh+TJ0hAvwlNEPJJtRYCVSXl0tFaZnUVlZZmaeouFgOmDzRylgMAgEINCbA/kdVQMANAXrPDXdmhQACCDUAAQQQagACiSOAAIIAkriiZEFeEuAvoV6mlaAcEbD5BkirkhLpOW60o0iYFgL+E2D/8z/HRJhMAvReMvPCqrJBgP7LRp6JMhwB3gAJxwtrCFglgACCAGK1oBgMAs0Q4BBMaUDAPgEbQggCiP28MCIEGhJg/6MeIOCGAL3nhjuzQkARoP+oAwg0JoAAQlVAwCEBBBAEEIflx9QZIsAhOEPJJtSCEzARQhBACp4uJswYAfa/jCWccBNDgN5LTCpYSAYJ0H8ZTDoh5yWAAJIXEQYQiI8AAggCSHzVxcgQ+D8CHIKpBgjET0AJIRVl98iOVau1J0MA0UaFIQQiEWD/i4QNJwgYE6D3jBEyAAQiE6D/IqPD0WMCCCAeJ5fQkk8AAQQBJPlVygp9IMAh2IcsEkMaCKz508NS+ff3tJeKAKKNCkMIRCLA/hcJG04QMCZA7xkjZAAIRCZA/0VGh6PHBBBAPE4uoSWfAAIIAkjyq5QV+kCAQ7APWSSGJBPIfQZr88uviNTWaS8VAUQbFYYQiESA/S8SNpwgYEyA3jNGyAAQiEyA/ouMDkePCSCAeJxcQks+AQQQBJDkVykr9IEAh2AfskgMSSRgcv+HigcBJIlZZU0+EWD/8ymbxJImAvRemrLFWn0jQP/5llHisUEAAcQGRcaAQEQCCCAIIBFLBzcIhCLAITgULowhkJeAqfCRmwABJC9qDCBgRID9zwgfzhCITIDei4wORwgYE6D/jBEygIcEEEA8TCohpYcAAggCSHqqlZWmmQCH4DRnj7UniYAt4QMBJElZZS0+E2D/8zm7xJZkAvRekrPD2nwnQP/5nmHii0IAASQKNXwgYIkAAggCiKVSYhgItEiAQzAFAgFzAtXl5VJRWia1lVXmg6kR2raV75x2ipSceoqd8RgFAhBoRID9j6KAgBsC9J4b7swKAUWA/qMOINCYAAIIVQEBhwQQQBBAHJYfU2eIAIfgDCWbUGMlYPUNkKIi6TVtaqzrZXAIZJ0A+1/WK4D4XRGg91yRZ14IIIBQAxBoigACCHUBAYcEEEAQQByWH1NniAB/Cc1Qsgm1IASsCCEIIAXJFZNkmwD7X7bzT/TuCNB77tgzMwToP2oAAo0JIIBQFRBwSAABBAHEYfkxdYYIcAjOULIJtaAEjIQQBJCC5orJskmA/S+beSdq9wToPfc5YAXZJUD/ZTf3RN48AQQQqgMCDgkggCCAOCw/ps4QAQ7BGUo2oTohkBNCNr/0ikhdnd4aEED0OGEFAQMC7H8G8HCFgAEBes8AHq4QMCRA/xkCxN1LAgggXqaVoNJCAAEEASQttco6002AQ3C688fq00Ng9cTJUr1smd6CEUD0OGEFAQMC7H8G8HCFgAEBes8AHq4QMCRA/xkCxN1LAgggXqaVoNJCAAEEASQttco6002AQ3C688fqk0+AN0CSnyNWmE0C7H/ZzDtRuydA77nPASvILgH6L7u5J/LmCSCAUB0QcEgAAQQBxGH5MXWGCHAIzlCyCbWgBLgDpKC4mQwCoQmw/4VGhgMErBCg96xgZBAIRCJA/0XChpPnBBBAPE8w4SWbAAIIAkiyK5TV+UKAQ7AvmSSOpBAwEj5yQfAJrKSkk3V4TID9z+PkElqiCdB7iU4Pi/OcAP3neYIJLxIBBJBI2HCCgB0CCCAIIHYqiVEg0DIBDsFUCATsELAifCCA2EkGo0BAgwD7nwYkTCAQAwF6LwaoDAkBTQL0nyYozDJFAAEkU+km2KQRQABBAElaTbIePwlwCPYzr0RVWALV5eVSUVomtZVVViYuKi6WAyZPtDIWg0AAAk0TYP+jMiDghgC954Y7s0JAEaD/qAMINCaAAEJVQMAhAQQQBBCH5cfUGSLAIThDySbUWAnYfAMEASTWVDE4BAIC7H8UAgTcEKD33HBnVgiw91EDEGiaAAIIlQEBhwQQQBBAHJYfU2eIAH8JzVCyCbUgBKwIIdwBUpBcMUm2CbD/ZTv/RO+OAL3njj0zQ4D+owYg0JgAAghVAQGHBBBAEEAclh9TZ4gAh+AMJZtQC0rASAhBAClorpgsmwTY/7KZd6J2T4Dec58DVpBdAvRfdnNP5M0TQAChOiDgkAACCAKIw/Jj6gwR4BCcoWQTqhMCOSFk80uviNTV6a0BAUSPE1YQMCDA/mcAD1cIGBCg9wzg4QoBQwL0nyFA3L0kgADiZVoJKi0EEEAQQNJSq6wz3QQ4BKc7f6w+PQTKbx8jOyq+0lswAogeJ6wgYECA/c8AHq4QMCBA7xnAwxUChgToP0OAuHtJAAHEy7QSVFoIIIAggKSlVllnuglwCE53/lh9egisHDVaatas0VswAogeJ6wgYECA/c8AHq4QMCBA7xnAwxUChgToP0OAuHtJAAHEy7QSVFoIIIAggKSlVllnuglwCE53/lh98gnUfwLrxZf1F4sAos8KSwhEJMD+FxEcbhAwJEDvGQLEHQIGBOg/A3i4eksAAcTb1BJYGggggCCApKFOWWP6CXAITn8OiSCZBLgEPZl5YVUQyBFg/6MWIOCGAL3nhjuzQkARoP+oAwg0JoAAQlVAwCEBBBAEEIflx9QZIsAhOEPJJtSCEDASPnIr5A2QguSKSbJNgP0v2/knencE6D137JkZAvQfNQABBBBqAAKJIoAAggCSqIJkMd4S4BDsbWoJrMAErAgfO9dcVFwsB0yeWOAImA4C2SLA/petfBNtcgjQe8nJBSvJHgH6L3s5J+L8BHgDJD8jLCAQGwEEEASQ2IqLgSHQgACHYMoBAuYEqsvLpaK0TGorq8wHE5FWJSXSc9xoK2MxCAQg0DQB9j8qAwJuCNB7brgzKwQUAfqPOoBAYwIIIFQFBBwSQABBAHFYfkydIQIcgjOUbEKNlQBvgMSKl8EhYJ0A+591pAwIAS0C9J4WJowgEAsB+i8WrAyacgIIIClPIMtPNwEEEASQdFcwq08LAQ7BackU60wLAStCCHeApCXdrDPFBNj/Upw8lp5qAvReqtPH4lNOgP5LeQJZfiwEEEBiwVr4QWtqauTNN9+UN954Q1auXCmbNm2SPffcU7p37y4DBgyQX/ziF9KxY0erC1NzLl++XJYtWyafffaZfP7557Jq1Sqprf32l9rHHXec/Pa3vw0158aNG2XJkiXy0Ucfyb/+9S9Zs2aNbN26Vdq2bSslJSXSu3dvOfLII+WII44IXuvTec4++2wds3ob1RRlZWWhfKIaI4AggEStHfwgEIYAh+AwtLCFgD4BIyEEAUQfNJYQiEiA/S8iONwgYEiA3jMEiDsEDAjQfwbwcPWWAAKIB6lVosPUqVPliy++aDaaTp06yZVXXhkIBzaev/3tb/LII4+IEkGae8IIIOvWrZN77rlHPv74Y6mrq8u7xP33319+97vfSc+ePfPaIoDkRVQwAzbigqFmIgjsQoDeoyAgEC+BnBCy+cWX9SdCANFnhSUEIhJg/4sIDjcIGBKg9wwB4g4BAwL0nwE8XL0lgACS8tSuX79ebr75ZtmwYUMQSVFRkRx88MGy9957B2+BfPDBB7J9+/bgZ61atQpsDz30UOOon3zySXnqqadaHCeMALJ06VK55ZZbdhmvW7duooQOJd5UV1cHb5h8+eWX9Tbt2rWTkSNHBm+FtPQ0FEBOPfXUvLGrN2V+9atf5bWzYcAbILwBYqOOGAMC+QhwCM5HiJ9DwA6B5dcOl7pt2/QGQwDR44QVBAwIsP8ZwMMVAgYE6D0DeLhCwJAA/WcIEHcvCSCApDyto0aNkk8++SSIQgkGN9xwQyAa5J7NmzfLlClTAiFEPR06dAg+76Q+j2Xy5ASQLl26yEEHHRSIEOr/vvDCC/L2228HQ0cRQL7zne/I8ccfH3yyS4k4uz/vvvuu3HfffbJly5b6mCdPnixt2rRpNpyGAohad5IeBBAEkCTVI2vxlwCHYH9zS2TJIvDFNdeL7Px/PMm7MgSQvIgwgIApAfY/U4L4QyAaAXovGje8IGCDAP1ngyJj+EYAASTFGX3//fdl/PjxQQStW7cO/ndTn4Tatm2bDB8+XL766qvA9swzz5Rzzz3XKPK1a9fKHnvsEdzL0fBRn7F69dVXgz8KI4CUl5fLokWL5JRTTmlRzFDjqvtG1NsiubtGLrvsMjn55JObjQcBxCjVVp3ZiK3iZDAIaBOg97RRYQiBSAT4BFYkbDhBIHYC7H+xI2YCCDRJgN6jMCDgjgD95449MyeXAAJIcnOTd2Xjxo2ThQsXBnYnnniiXHHFFc36vP766/UXe6u3QGbMmBF8Esv2E1UACbsO9dbHW2+9Fbj96Ec/khtvvLHZIRBAwtKNz56NOD62jAyBlgjQe9QHBOIhwCXo8XBlVAjYIsD+Z4sk40AgHAF6LxwvrCFgkwD9Z5MmY/lCAAEkpZlUb3VceumlsmPHjiCCMWPGSN++fZuNRtkNHjxYtm7dGtjceuut0r9/f+vRF0oAef7552XmzJnB+tVbL3feeWezsSCAWE9z5AHZiCOjwxECRgToPSN8OEOgEQEj4SM3Gp/AorIgEDsB9r/YETMBBJokQO9RGBBwR4D+c8eemZNLAAEkublpcWWLFy+WO+64I7Bp27ZtIAbke6NDiSRLliwJfAYOHCjnnHOO9egLJYD89a9/lT/96U/B+nv06CGTJk1qNhYEEOtpjjwgG3FkdDhCwIgAvWeED2cI1BOwInzsHK2ouFgOmDwRuhCAQIwE2P9ihMvQEGiBAL1HeUDAHQH6zx17Zk4uAQSQ5OamxZU1fAOiT58+9WJIS06zZs2SOXPmBCYDBgyQYcOGWY++UALI9OnT5cUXXwzWf/jhh8uIESOajaWhAHLbbbcFd4hs3LgxuDdlr732kl69egVvz7R0kbp1UDsH5BJ0LkGPq7YYFwINCXAIph4gYE6gurxcKkrLpLayynwwEWlVUiI9x422MhaDQAACTRNg/6MyIOCGAL3nhjuzQkARoP+oAwg0JoAAktKqeOCBB2TevHnB6o866igZOnRo3kjmzp0rDz74YGCX762JvIM1Y1AIAUR9/uvKK6+UysrKYBXnn3++nH766c0uuaEA0pxRu3btgovU1Zsx7du3jxp+aD8EEASQ0EWDAwQiEOAQHAEaLhBoggBvgFAWEEgXAfa/dOWL1fpDgN7zJ5dEkj4C9F/6csaK4yeAABI/41hmaHgJ+GmnnSYXX3xx3nneeecdueuuuwK7kpISuf/++/P6hDUohADyyCOPyJ///OdgacXFxcHl7p06dWp2qToCSM55n332kRtuuEG++93vhg293n79+vV5fRV/9ckyJYCsXbs2r70vBmojIS2YzgAAIABJREFU7t69exDOmjVrpLYWAcSX3BJHsgnQe8nOD6tLH4GaTZtk47z5svnV16Vu531soaMoKpKD7rs7tBsOEICAPgH2P31WWELAJgF6zyZNxoJAOAL0XzheWGeDQLdu3fJeHVEIEkV1dXV1hZjIlznGjRsnCxcuDMI544wz5LzzzssbmrJXfupRwoESEmw/cQsgH3zwQfC5r9wvztU9JuqtjZYexeanP/2pHHHEEXLggQdK586dg89fbd68Ofgc1vz582XRokX1Q6imGDt2bIuiSkvz6Qgu9957r3Tp0sU2fsaDAAQgAAEIQKCABLZv2CCrnp0jFX+dK7Xbt4eb+d+K5OhnnwrngzUEIAABCEAAAhCAAAQgAAEIpJIAAkjItP3hD3+QDz/8MPA666yzZNCgQXlHUPbKTz1KEZ49e3Zen7AGcQog6k2Jm266SbZs2RIs63vf+57cfvvtQSwtPd9884106NChRZuXXnpJ1L0iOR3u+OOPDz6zFeVBAIlCDR8IQAACEIBAegkoIaT8v56WL//yV/0gEED0WWEJAQhAAAIQgAAEIAABCEAg5QQQQEImMGtvgCgRY+TIkbJq1aqAlHqLY8yYMdK1a9eQ5Jo3V4LQM888ExgoUeW+++4LPhUW9uETWM0T41XMsNWEPQTsEKD37HBkFAi0RKB261b5YugwfUh8AkufFZYQiEiA/S8iONwgYEiA3jMEiDsEDAjQfwbwcPWWAJ/ASmlqs3QHiLr0XL25oj5XpZ699torePNDXeRu81HzDB48WLbv/ITFkCFD5Nhjj7U5RaOxuASdO0BiLTAGh8BOAlyERylAIH4C/1tZJSuG3ag/UVGR9Jo2Vd8eSwhAIDQB9r/QyHCAgBUC9J4VjAwCgUgE6L9I2HDynACXoKc0wQ888IDMmzcvWP1RRx0lQ4cOzRvJ3Llz5cEHHwzslHgwadKkvD5hDWx/AkuJEeptl48++ihYSrt27YI3QXr37h12aVr2SljJzXXmmWfKueeeq+UX1QgBBAEkau3gB4EwBDgEh6GFLQTCE6jZtFk2/uV52fL6G/rOCCD6rLCEQEQC7H8RweEGAUMC9J4hQNwhYECA/jOAh6u3BBBAUpra559/XmbOnBmsvk+fPsHF4PmeWbNmyZw5cwKzAQMGyLBhIT7TkG/wnT+3KYDU1NTIxIkT6y97b9Omjdx8883Sr18/zdWEN5syZYq88ca3v7w46aST5PLLLw8/SAgPBBAEkBDlgikEIhPgEBwZHY4QaJGAEj42vTBftry2QOp27AhHCwEkHC+sIRCBAPtfBGi4QMACAXrPAkSGgEBEAvRfRHC4eU0AASSl6V28eHG96NG2bdtADGnVqlWL0ag7M5YsWRLYDBw4UM455xzr0dsSQGpra6W0tFTefvvtYI0qtuHDh8sRRxxhfc0NB/zjH/8o7733XvBH//Ef/yEXXnhhrPMhgCCAxFpgDA6BnQQ4BFMKELBLwEj4yC0FAcRuUhgNAk0QYP+jLCDghgC954Y7s0JAEaD/qAMINCaAAJLSqlD3VVx66aWyY+f/t6ESN/r27dtsNMpO3W+xdevWwObWW2+V/v37W4/ehgCixA81zuuvvx6sT/3HW33i68gjj7S+3t0HvOqqq2TdunXBH59//vly+umnxzonAggCSKwFxuAQ2EmAQzClAAE7BKwIHzuXUlRcLAdMnmhnYYwCAQg0SYD9j8KAgBsC9J4b7swKgdzv0Pbee+8ARkVFhajfsfFAIOsEEEBSXAHqboyFCxcGEeT7XNOCBQtk6tRvL9rcc889Rd0hku+NkShobAgg999/v8yfPz+YvqioSJQocdxxx0VZTiifDz74QEaPHl3vM3bs2NjuGslNggDCRhyqSDGGQEQC/CU0IjjcINCAQHV5uVSUlkltZZUVLq1KSqTnuP87d1gZlEEgAIFdCLD/URAQcEOA3nPDnVkhoAjQf9QBBBoTQABJcVW8//77Mn78+CCC1q1by4QJE2S//fZrFFF1dXXw+Sil/Konzsu9TQWQhx9+WP7yl7/Ux6DeWjnllFMiZ0m9KVNcXJzXf8uWLTJixIh6Rvvuu29wSbzaOOJ8EEAQQOKsL8aGQI4Ah2BqAQJ2CNh8AwQBxE5OGAUCLRFg/6M+IOCGAL3nhjuzQgABhBqAQNMEEEBSXhmjRo2STz75JIiiW7ducuONN0rPnj3ro1K/2FcXe+fu/ujQoYOUlZUFb4Hs/qxZs0aGDBlS/8dq7EMOOSQUIRMB5Mknn5Snnnqqfj4bn6BSnwk79dRT5ZhjjhElajT1LFq0KHgjRsWfe2644Qb58Y9/HCr2KMYIIAggUeoGHwiEJcBfQsMSwx4CLROwIYTwCSyqDALxE2D/i58xM0CgKQL0HnUBAXcE6D937Jk5uQQQQJKbG62VrV+/Xm6++WbZsGFDYK8+GdWvXz9Rid28ebOozzqpN0DUoz55pWwPPfTQJscOK4Cot0p2f9T9GZWVlcEfK5Gla9eujWwmTmz8veuGb7Moh06dOoW680MJHU09Z599dv0fd+nSJRCH1NjqjRklDn322WeiGDZ81OXw6pL4QjwIIAgghagz5oAAh2BqAALxEDASQrgEPZ6kMCoEGhBg/6McIOCGAL3nhjuzQkARoP+oAwg0JoAA4kFVrFq1KnjLY/ny5c1G07Fjx+AujSOOOKJZm7ACSENxIQxG9abH7s8rr7wi06ZNCzPMLrZNjakMwqxRCSNKSCnEZeu5xSOAIIBELnocIRCCAIfgELAwhUAEAkoI2fDfc+Sbt/+u740Aos8KSwhEJMD+FxEcbhAwJEDvGQLEHQIGBOg/A3i4eksAAcST1NbU1Mgbb7wR/LNy5UrZtGlT8AZG9+7dZcCAAXL88ceLEkFaenwUQL788kv59NNPZenSpfKvf/0reCtGvfmh3opRd4OUlJTIQQcdJIcffrj87Gc/C94MKeSDAIIAUsh6Y67sEuAQnN3cE3nhCGxftVpWjRmnPyECiD4rLCEQkQD7X0RwuEHAkAC9ZwgQdwgYEKD/DODh6i0BBBBvU0tgaSCAAIIAkoY6ZY3pJ8AhOP05JILkE6heWS6rx07QXygCiD4rLCEQkQD7X0RwuEHAkAC9ZwgQdwgYEKD/DODh6i0BBBBvU0tgaSCAAIIAkoY6ZY3pJ8AhOP05JILkE6hesVJWj/uj/kIRQPRZYQmBiATY/yKCww0ChgToPUOAuEPAgAD9ZwAPV28JIIB4m1oCSwMBBBAEkDTUKWtMPwEOwenPIREkm4C6A+Trp56Ryvf+ob9QBBB9VlhCICIB9r+I4HCDgCEBes8QIO4QMCBA/xnAw9VbAggg3qaWwNJAAAEEASQNdcoa00+AQ3D6c0gEySSghI9NL8yXLa8tkLodO8ItEgEkHC+sIRCBAPtfBGi4QMACAXrPAkSGgEBEAvRfRHC4eU0AAcTr9BJc0gkggCCAJL1GWZ8fBDgE+5FHokgOASPhY2cYRcXFcsDkickJipVAwEMC7H8eJpWQUkGA3ktFmlikpwToP08TS1hGBBBAjPDhDAEzAgggCCBmFYQ3BPQIcAjW44QVBPIRsCF85OZoVVIiPceNzjclP4cABAwIsP8ZwMMVAgYE6D0DeLhCwJAA/WcIEHcvCSCAeJlWgkoLAQQQBJC01CrrTDcBDsHpzh+rTwaB6vJyqSgtk9rKKisLQgCxgpFBINAiAfY/CgQCbgjQe264MysEFAH6jzqAQGMCCCBUBQQcEkAAQQBxWH5MnSECHIIzlGxCjZWAzTdA+ARWrKlicAgEBNj/KAQIuCFA77nhzqwQYO+jBiDQNAEEECoDAg4JIIAggDgsP6bOEAH+EpqhZBNqQQhYEUK4BL0guWKSbBNg/8t2/oneHQF6zx17ZoYA/UcNQKAxAQQQqgICDgkggCCAOCw/ps4QAQ7BGUo2oRaUgJEQggBS0FwxWTYJsP9lM+9E7Z4Avec+B6wguwTov+zmnsibJ4AAQnVAwCEBBBAEEIflx9QZIsAhOEPJJlQnBJQQsv7xJ6Rq8RL9+RFA9FlhCYGIBNj/IoLDDQKGBOg9Q4C4Q8CAAP1nAA9XbwkggHibWgJLAwEEEASQNNQpa0w/AQ7B6c8hESSfQOXiD2TNfffrLxQBRJ8VlhCISID9LyI43CBgSIDeMwSIOwQMCNB/BvBw9ZYAAoi3qSWwNBBAAEEASUOdssb0E+AQnP4cEkHyCVQuWixrpj+gv1AEEH1WWEIgIgH2v4jgcIOAIQF6zxAg7hAwIED/GcDD1VsCCCDeppbA0kAAAQQBJA11yhrTT4BDcPpzSATJJqA+gbXusf9Ptn74kf5CEUD0WWEJgYgE2P8igsMNAoYE6D1DgLhDwIAA/WcAD1dvCSCAeJtaAksDAQQQBJA01ClrTD8BDsHpzyERJJMAl6AnMy+sCgI5Aux/1AIE3BCg99xwZ1YIKAL0H3UAgcYEEECoCgg4JIAAggDisPyYOkMEOARnKNmEWhACRsJHboW8AVKQXDFJtgmw/2U7/0TvjgC95449M0OA/qMGIIAAQg1AIFEEEEAQQBJVkCzGWwIcgr1NLYEVmIAV4WPnmouKi+WAyRMLHAHTQSBbBNj/spVvok0OAXovOblgJdkjQP9lL+dEnJ8Ab4DkZ4QFBGIjgACCABJbcTEwBBoQ4BBMOUDAnEB1eblUlJZJbWWV+WAi0qqkRHqOG21lLAaBAASaJsD+R2VAwA0Bes8Nd2aFgCJA/1EHEGhMAAGEqoCAQwIIIAggDsuPqTNEgENwhpJNqLESsPkGCAJIrKlicAgEBNj/KAQIuCFA77nhzqwQYO+jBiDQNAEEECoDAg4JIIAggDgsP6bOEAH+EpqhZBNqQQjYEEL4BFZBUsUkGSfA/pfxAiB8ZwToPWfomRgCiP/UAASaIIAAQllAwCEBBBAEEIflx9QZIsBfQjOUbEItKAEjIYRL0AuaKybLJgH2v2zmnajdE6D33OeAFWSXAP2X3dwTefMEEECoDgg4JIAAggDisPyYOkMEOARnKNmE6oSAEkLW/ulh2fbpUv35EUD0WWEJgYgE2P8igsMNAoYE6D1DgLhDwIAA/WcAD1dvCSCAeJtaAksDAQQQBJA01ClrTD8BDsHpzyERJJ/Appdfla+ffEp/oQgg+qywhEBEAux/EcHhBgFDAvSeIUDcIWBAgP4zgIertwQQQLxNLYGlgQACCAJIGuqUNaafAIfg9OeQCJJPYNNLr8jX//V0/UKL2raVuurq5heOAJL8pLLC1BNg/0t9CgkgpQTovZQmjmV7QYD+8yKNBGGZAAKIZaAMB4EwBBBAEEDC1Au2EIhKgENwVHL4QUCfwKb5L8nXTz+r74AAos8KSwhEJMD+FxEcbhAwJEDvGQLEHQIGBOg/A3i4eksAAcTb1BJYGggggCCApKFOWWP6CXAITn8OiSDZBNQdIGtmPCTVn3+uv1AEEH1WWEIgIgH2v4jgcIOAIQF6zxAg7hAwIED/GcDD1VsCCCDeppbA0kAAAQQBJA11yhrTT4BDcPpzSATJJKCEj00vzJctry2Quh07wi0SASQcL6whEIEA+18EaLhAwAIBes8CRIaAQEQC9F9EcLh5TQABxOv0ElzSCSCAIIAkvUZZnx8EOAT7kUeiSA4BI+FjZxhFxcVywOSJyQmKlUDAQwLsfx4mlZBSQYDeS0WaWKSnBOg/TxNLWEYEEECM8OEMATMCCCAIIGYVhDcE9AhwCNbjhBUE8hGwIXzk5mhVUiI9x43ONyU/hwAEDAiw/xnAwxUCBgToPQN4uELAkAD9ZwgQdy8JIIB4mVaCSgsBBBAEkLTUKutMNwEOwenOH6tPBoHq8nKpKC2T2soqKwtCALGCkUEg0CIB9j8KBAJuCNB7brgzKwQUAfqPOoBAYwIIIFQFBBwSQABBAHFYfkydIQIcgjOUbEKNlQBvgMSKl8EhYJ0A+591pAwIAS0C9J4WJowgEAsB+i8WrAyacgIIIClPIMtPNwEEEASQdFcwq08LAQ7BackU60wLARtCCG+ApCXbrDPNBNj/0pw91p5mAvRemrPH2tNOgP5LewZZfxwEEEDioMqYENAkgACCAKJZKphBwIgAh2AjfDhDoFkCJkIIAgiFBYH4CbD/xc+YGSDQFAF6j7qAgDsC9J879sycXAIIIMnNDSvLAAEEEASQDJQ5ISaAAIfgBCSBJXhNQAkhX02bLttXrNCOEwFEGxWGEIhMgP0vMjocIWBEgN4zwoczBIwI0H9G+HD2lAACiKeJJax0EEAAQQBJR6WyyrQT4BCc9gyy/jQQWP/UM7L5xZe1l4oAoo0KQwhEJsD+FxkdjhAwIkDvGeHDGQJGBOg/I3w4e0oAAcTTxBJWOggggCCApKNSWWXaCXAITnsGWX8aCKx/8inZ/PKr2ktFANFGhSEEIhNg/4uMDkcIGBGg94zw4QwBIwL0nxE+nD0lgADiaWIJKx0EEEAQQNJRqawy7QQ4BKc9g6w/DQTWPjJLvnnrbe2lIoBoo8IQApEJsP9FRocjBIwI0HtG+HCGgBEB+s8IH86eEkAA8TSxhJUOAgggCCDpqFRWmXYCHILTnkHWn2QCuYvQg7c/avX3NQSQJGeVtflCgP3Pl0wSR9oI0Htpyxjr9YkA/edTNonFFgEEEFskGQcCEQgggOj/oigCXlwgAIGdBDgEUwoQsE8gJ3xseW2B1O3YEXoCBJDQyHCAQGgC7H+hkeEAASsE6D0rGBkEApEI0H+RsOHkOQEEEM8TTHjJJoAAggCS7Apldb4Q4BDsSyaJIwkETIUPFcO/dewonU44TkpOPSUJIbEGCHhLgP3P29QSWMIJ0HsJTxDL85oA/ed1egkuIgEEkIjgcIOADQIIIAggNuqIMSCQjwCH4HyE+DkE8hOwIXzkZuHtj/y8sYCADQLsfzYoMgYEwhOg98IzwwMCtgjQf7ZIMo5PBBBAfMomsaSOAAIIAkjqipYFp5IAh+BUpo1FJ4hAdXm5VJSWSW1llZVVIYBYwcggEMhLgP0vLyIMIBALAXovFqwMCgEtAvSfFiaMMkYAASRjCSfcZBFAAEEASVZFshpfCXAI9jWzxFVIArwBUkjazAUBOwTY/+xwZBQIhCVA74Ulhj0E7BGg/+yxZCR/CCCA+JNLIkkhAQQQBJAUli1LTiEBDsEpTBpLTiwBG0JIUXGxHDB5YmJjZGEQ8IUA+58vmSSOtBGg99KWMdbrEwH6z6dsEostAgggtkgyDgQiEEAAQQCJUDa4QCA0AQ7BoZHhAIG8BIyEkKIi6TVtat45MIAABMwIsP+Z8cMbAlEJ0HtRyeEHAXMC9J85Q0bwjwACiH85JaIUEUAAQQBJUbmy1BQT4BCc4uSx9MQTyAkhm196RaSuTm+9CCB6nLCCgCEB9j9DgLhDICIBei8iONwgYIEA/WcBIkN4RwABJIaUbty4UdQ/HTt2lM6dO8cwA0P6QgABBAHEl1omjmQT4BCc7PywOj8IVJRNk60ff6IXDAKIHiesIGBIgP3PECDuEIhIgN6LCA43CFggQP9ZgMgQ3hFAANFM6aeffhpYFhcXy/7779+k17Jly2TGjBmi/m/uUbYXXXSR9OvXT3MmzLJEAAEEASRL9U6s7ghwCHbHnpmzQ+CradOl6oMP9QJGANHjhBUEDAmw/xkCxB0CEQnQexHB4QYBCwToPwsQGcI7AgggGilVgsbvf//7wPI///M/5fzzz2/ktWrVqsCmurq60c9atWolN954oxx++OEas2GSJQIIIAggWap3YnVHgEOwO/bMnB0CX5aWybZPl+oFjACixwkrCBgSYP8zBIg7BCISoPcigsMNAhYI0H8WIDKEdwQQQDRS+uyzz8rs2bMDyzvvvFP222+/Rl533HGHLFmypP7P27ZtK9u3b5e6nd+CVp/CKi0tFfXnPBDIEUAAQQChGyBQCAIcggtBmTmySoA7QLKaeeJOAwH2vzRkiTX6SIDe8zGrxJQWAvRfWjLFOgtJAAFEg3ZO3CgpKZHp06c38qioqJBrrrkm+PMOHTrIddddJ4cccohs2rQpED0+/vjj4GdXXHGFnHDCCRozYpIVAgggCCBZqXXidEuAQ7Bb/szuJ4Gc8LHltQVSt2NHuCB5AyQcL6whEJEA+19EcLhBwJAAvWcIEHcIGBCg/wzg4eotAQQQjdRef/31Ul5eLj/4wQ/qP4XV0O25556TWbNmBX904YUXyr//+7/X/3jNmjXyu9/9Lvj3n/zkJzJs2DCNGTHJCgEEEASQrNQ6cbolwCHYLX9m94uAkfCxE0VRcbEcMHmiX2CIBgIJJMD+l8CksKRMEKD3MpFmgkwoAfovoYlhWU4JIIBo4L/88suDtzmOO+44ueqqqxp5jBs3ThYtWiRFRUVy//33S8eOHXexueWWW+R//ud/pHv37lJWVqYxIyZZIYAAggCSlVonTrcEOAS75c/sfhCwIXzkSLQqKZGe40b7AYYoIJBgAux/CU4OS/OaAL3ndXoJLuEE6L+EJ4jlOSGAAKKB/dxzzxX1i+qTTz5ZBg8evIuHuuPjkksukaqqKjnggANkwoQJjUacMmWKvPnmm8H9H4888ojGjJhkhQACCAJIVmqdON0S4BDslj+zp59AdXm5VJSWSW1llZVgEECsYGQQCOQlwP6XFxEGEIiFAL0XC1YGhYAWAfpPCxNGGSOAAKKRcPVZq23btsnRRx8tV1999S4eK1askOHDhwd/dtppp8lFF13UaMQZM2bI/PnzRf1H6PHHH9eYEZOsEEAAQQDJSq0Tp1sCHILd8md2PwjwBogfeSSKbBFg/8tWvok2OQToveTkgpVkjwD9l72cE3F+Aggg+RkFF5yri873339/+eMf/7iLR8P7P6699lo58sgjG42oLkJ/6623pH379vKnP/1JY0ZMskIAAQQBJCu1TpxuCXAIdsuf2f0iYEMI4Q4Qv2qCaJJLgP0vublhZX4ToPf8zi/RJZsA/Zfs/LA6NwQQQDS45wQMZao+caU+daWe2tpaURekr169Oni7Y/r06Y3u/1B2N910k3zxxRfSo0cPueuuuzRmxCQrBBBAEECyUuvE6ZYAh2C3/JndTwJGQkhRkfSaNtVPMEQFgQQRYP9LUDJYSqYI0HuZSjfBJowA/ZewhLCcRBBAANFIwzvvvCOTJk0KLLt27Sq//vWvA6Fj3rx58u677wZ/fthhh8mIESMajbZ9+3a5+OKLpaamRn7605/KddddpzEjJlkhgACCAJKVWidOtwQ4BLvlz+x+E8gJIZtfekWkrk4vWAQQPU5YQcCQAPufIUDcIRCRAL0XERxuELBAgP6zAJEhvCOAAKKRUnXR+c033yzLli1r1nrUqFHSr1+/Rj//+9//Xv/Wx3nnnSenn366xoyYZIUAAggCSFZqnTjdEuAQ7JY/s2eDQPntY2RHxVd6wSKA6HHCCgKGBNj/DAHiDoGIBOi9iOBwg4AFAvSfBYgM4R0BBBDNlG7YsEHuuOMOWblyZSOPc889V84444wmR1J3hvzjH/8IfjZu3Dg58MADNWfELAsEEEAQQLJQ58TongCHYPc5YAX+EygfPVZ2rP5SL1AEED1OWEHAkAD7nyFA3CEQkQC9FxEcbhCwQID+swCRIbwjgAASIqXql9Xqc1j//Oc/paqqKvgc1s9+9rPgcvSmni1btgSXpqu7Qtq1aye33HJLiNkwzQIBBBAEkCzUOTG6J8Ah2H0OWIH/BFbe+gepWbtWL1AEED1OWEHAkAD7nyFA3CEQkQC9FxEcbhCwQID+swCRIbwjgADiXUoJKE0EEEAQQNJUr6w1vQQ4BKc3d6w8+QTq7wB58WX9xSKA6LPCEgIGBNj/DODhCgEDAvSeATxcIWBIgP4zBIi7lwQQQLxMK0GlhQACCAJIWmqVdaabAIfgdOeP1SeTQE742PLaAqnbsSPcIhFAwvHCGgIRCbD/RQSHGwQMCdB7hgBxh4ABAfrPAB6u3hJAAPE2tQSWBgIIIAggaahT1ph+AhyC059DIkgOASPhY2cYRcXFcsDkickJipVAwFMC7H+eJpawEk+A3kt8iligxwToP4+TS2iRCSCAREaHIwTMCSCAIICYVxEjQCA/AQ7B+RlhAYF8BGwIH7k5WpWUSM9xo/NNyc8hAAFDAux/hgBxh0BEAvReRHC4QcACAfrPAkSG8I4AAkiElK5YsUI+++wzWbt2bXAZuvoltu4zePBgXVPsMkAAAQQBJANlTogJIMAhOAFJYAmpJlBdXi4VpWVSW1llJQ4EECsYGQQCeQmw/+VFhAEEYiFA78WClUEhoEWA/tPChFHGCCCAhEj4e++9J48//riUl5eH8NrV9Iknnojsi6N/BBBAEED8q2oiSiIBDsFJzAprShsB3gBJW8ZYLwRE2P+oAgi4IUDvueHOrBBQBOg/6gACjQkggGhWxbPPPiuzZ8/WtG7eDAHEGKFXAyCAIIB4VdAEk1gCHIITmxoWlkICNoQQ7gBJYeJZcioJsP+lMm0s2gMC9J4HSSSE1BKg/1KbOhYeIwEEEA246nNXI0aMqLds3bq1HH744dKrVy/Za6+9pFWrVhqjfGty8skna9ti6D8BBBAEEP+rnAiTQIBDcBKywBp8I2AkhBQVSa9pU31DQjwQSBwB9r/EpYQFZYQAvZeRRBNmIgnQf4lMC4tyTAABRCMBU6dOlTfeeCOw/P73vy/XXHONdO7cWcMTEwi0TAABBAGEHoFAIQhwCC4EZebIKoGcELL5xZf1ESCA6LPCEgIGBNj/DODhCgEDAvSeATxcIWBIgP4zBIi7lwQQQDTSetVVV8n69eulXbt2cvfdd0uHDh00vDCBQH4CCCAIIPmrBAsImBPgEGzOkBEgkI/AF0OHiVRX5zP79ucIIHqcsIKAIQH2P0OAuEMgIgHLY3KEAAAgAElEQVR6LyI43CBggQD9ZwEiQ3hHAAFEI6XnnXee1NTUyE9+8hMZNmyYhgcmENAjgACCAKJXKVhBwIwAh2AzfnhDQIfA8qHDpA4BRAcVNhAoGAH2v4KhZiII7EKA3qMgIOCOAP3njj0zJ5cAAohGbi677DLZvHmznHTSSaL+Nw8EbBFAAEEAsVVLjAOBlghwCKY+IBA/gS9+d61ITY3eRLwBoscJKwgYEmD/MwSIOwQiEqD3IoLDDQIWCNB/FiAyhHcEEEA0Ujpy5EhZunQpb4BosMIkHAEEEASQcBWDNQSiEeAQHI0bXhDQIcAdIDqUsIGAGwLsf264MysE6D1qAALuCNB/7tgzc3IJIIBo5Ob555+Xhx9+OLj7Y/r06dK6dWsNL0wgkJ8AAggCSP4qwQIC5gQ4BJszZAQI7E4gJ3xseW2B1O3YEQ4Qb4CE44U1BCISYP+LCA43CBgSoPcMAeIOAQMC9J8BPFy9JYAAopHabdu2yY033igVFRVy1llnydlnn63hhQkE8hNAAEEAyV8lWEDAnACHYHOGjACBHAEj4WPnIEXFxXLA5IlAhQAEYibA/hczYIaHQDME6D1KAwLuCNB/7tgzc3IJIIBo5mbFihUyevTo4C6QQYMGyZlnninqPyo8EDAhgACCAGJSP/hCQJcAh2BdUthBoHkCNoSP3OitSkqk57jR4IYABGImwP4XM2CGhwACCDUAgcQRYO9LXEpYUAIIIIBoJOHNN98MrNatWydPPPGE1NTUSOfOnYM7QXr27Cnt27fXGOVbk6OOOkrbFkP/CSCAIID4X+VEmAQCHIKTkAXWkGYC1eXlUlFaJrWVVVbCQACxgpFBIJCXAPtfXkQYQCAWAvReLFgZFAJaBOg/LUwYZYwAAohGwtUbHzaeoqIimT17to2hGMMTAgggCCCelDJhJJwAh+CEJ4jlpYIAb4CkIk0sEgK7EGD/oyAg4IYAveeGO7NCQBGg/6gDCDQmgACiURW2BBA1lXqDhAcCOQIIIAggdAMECkGAQ3AhKDNHVgjYEEK4AyQr1UKcrgmw/7nOAPNnlQC9l9XME3cSCNB/ScgCa0gaAQQQjYyUlpZqWOmZDB06VM8Qq0wQQABBAMlEoROkcwIcgp2ngAV4SMBICCkqkl7TpnpIhZAgkCwC7H/JygeryQ4Bei87uSbS5BGg/5KXE1bkngACiPscsIIME0AAQQDJcPkTegEJcAguIGymyhwBJYRs/OvfZMurr+vHjgCizwpLCBgQYP8zgIcrBAwI0HsG8HCFgCEB+s8QIO5eEkAA8TKtBJUWAgggCCBpqVXWmW4CHILTnT9Wn3wC/1tVJSuuv1F/oQgg+qywhIABAfY/A3i4QsCAAL1nAA9XCBgSoP8MAeLuJQEEEC/TSlBpIYAAggCSllplnekmwCE43flj9ckn8L/fVMqK4TfpLxQBRJ8VlhAwIMD+ZwAPVwgYEKD3DODhCgFDAvSfIUDcvSSAAOJlWgkqLQQQQBBA0lKrrDPdBDgEpzt/rD75BP538xZZcePN+gtFANFnhSUEDAiw/xnAwxUCBgToPQN4uELAkAD9ZwgQdy8JIIAYpHXdunWybNky2bJli2zdulXatWsne+21lxx44IHStWtXg5FxzQoBBBAEkKzUOnG6JcAh2C1/ZvebgLoDZMOfn5dvFryhHygCiD4rLCFgQID9zwAerhAwIEDvGcDDFQKGBOg/Q4C4e0kAASRkWrdt2ybz5s2TF154QdasWdOsd/fu3eWUU06Rk08+WYqLi0POgnlWCCCAIIBkpdaJ0y0BDsFu+TO7nwSU8LHphfmy5bUFUrdjR7ggEUDC8cIaAhEJsP9FBIcbBAwJ0HuGAHGHgAEB+s8AHq7eEkAACZHazz//XKZMmSJfffWVttfee+8t11xzTfBWCA8EdieAAIIAQldAoBAEOAQXgjJzZIWAkfCxE1JRcbEcMHliVpARJwScEWD/c4aeiTNOgN7LeAEQvlMC9J9T/EyeUAIIIJqJWb58udx2223Bp64aPt26dRP1T9u2baW6ulrUZ7F2fzOkffv2cvvtt0vPnj01Z8MsKwQQQBBAslLrxOmWAIdgt/yZ3Q8CNoSPHIlWJSXSc9xoP8AQBQQSTID9L8HJYWleE6D3vE4vwSWcAP2X8ASxPCcEEEA0sNfW1sr1118vq1evDqyV2HH66afLCSecIJ07d240wsaNG+Wll16SOXPmiPpklnq++93vyp133inqP0Q8EMgRQABBAKEbIFAIAhyCC0GZOXwmUF1eLhWlZVJbWWUlTAQQKxgZBAJ5CbD/5UWEAQRiIUDvxYKVQSGgRYD+08KEUcYIIIBoJPy1116Te+65J7BUl5uPHDlS1Ket8j3qTZDRo0fXvxEyZMgQ+fnPf57PjZ9niAACCAJIhsqdUB0S4BDsED5Te0OAN0C8SSWBZIgA+1+Gkk2oiSJA7yUqHSwmYwTov4wlnHC1CCCAaGC666675O9//3tgOWbMGOnTp4+G17cmn332mYwYMSL43z/5yU9k2LBh2r4Y+k8AAQQBxP8qJ8IkEOAQnIQssAZfCNgQQrgDxJdqII6kE2D/S3qGWJ+vBOg9XzNLXGkgQP+lIUussdAEEEA0iP/2t78N7vY46KCDZOzYsRoeu5ooAUQJIertkdybJKEHwcFLAgggCCBeFjZBJY4Ah+DEpYQFeUDASAgpKpJe06Z6QIEQIJBsAux/yc4Pq/OXAL3nb26JLPkE6L/k54gVFp4AAogG8wsuuEC2b98uxx9/vPzmN7/R8NjV5L777pOXX35Z2rRpI48++mhofxz8JYAAggDib3UTWZIIcAhOUjZYi28ElBCy4dk58s07374trPUggGhhwggCpgTY/0wJ4g+BaATovWjc8IKADQL0nw2KjOEbAQQQjYxeeOGFwWXm6v4OdY9H2Ofuu++W119/XYqLi+Xhhx8O6469xwQQQBBAPC5vQksQAQ7BCUoGS/GSQPXKclk9doJ+bAgg+qywhIABAfY/A3i4QsCAAL1nAA9XCBgSoP8MAeLuJQEEEI20XnPNNVJRUSH77LOPlJaWanjsanLttdfK6tWrg4vTp0yZEtofB38JIIAggPhb3USWJAIcgpOUDdbiI4HqFStl9bg/6oeGAKLPCksIGBBg/zOAhysEDAjQewbwcIWAIQH6zxAg7l4SQADRSOu0adPk1VdfDSyvv/56GTBggIbXtybvvvuu3HnnncH/PvbYY0XdJ8IDgRwBBBAEELoBAoUgwCG4EJSZI8sEqpf/S1ZP+Pa8p/UggGhhwggCpgTY/0wJ4g+BaATovWjc8IKADQL0nw2KjOEbAQQQjYwuXLhQxo8fH1iqz1gpEeSwww7L6/nxxx/LxIkTpaqqKrC96aab5Ic//GFePwyyQwABBAEkO9VOpC4JcAh2SZ+5fSeg7gD5+r+elsp/vK8fKgKIPissIWBAgP3PAB6uEDAgQO8ZwMMVAoYE6D9DgLh7SQABRDOto0aNkn/+85/11j/72c+CS9H79u0r7dq1q/9zdVfI0qVL5ZVXXpE333xT6urqgp8dfPDBctttt2nOhllWCCCAIIBkpdaJ0y0BDsFu+TO7nwSU8LHphfmy5bUFUrdjR7ggEUDC8cIaAhEJsP9FBIcbBAwJ0HuGAHGHgAEB+s8AHq7eEkAA0Uztxo0bZcSIEbJu3bpdPIqKimTPPfeUtm3bSnV1tVRWVtaLHjnDbt26yZgxY6SkpERzNsyyQgABBAEkK7VOnG4JcAh2y5/Z/SJgJHzsRFFUXCwHTJ7oFxiigUACCbD/JTApLCkTBOi9TKSZIBNKgP5LaGJYllMCCCAh8H/99ddy9913y0cffaTt1b9//+Dej86dO2v7YJgdAgggCCDZqXYidUmAQ7BL+sztCwEbwkeORauSEuk5brQvaIgDAoklwP6X2NSwMM8J0HueJ5jwEk2A/kt0elicIwIIIBHAqztB5s+fL+qOj9z9Hg2Had++vfTr109OPvlk+cEPfhBhBlyyQgABBAEkK7VOnG4JcAh2y5/Z00+gurxcKkrLpLby23vdTB8EEFOC+ENAjwD7nx4nrCBgmwC9Z5so40FAnwD9p88Ky+wQQAAxzPVXX30lmzdvFnX3h7ogvWPHjqKg8kBAhwACCAKITp1gAwFTAhyCTQniDwER3gChCiCQPgLsf+nLGSv2gwC950ceiSKdBOi/dOaNVcdLAAEkXr4FG72mpia4dP2NN96QlStXyqZNm4K7Sbp37y4DBgyQX/ziF4E4Y/NRcy5fvlyWLVsmn332mXz++eeyatUqqa399pfaxx13XPD5ryiPujz+3Xfflddffz2YQ31+TAlM6j6VH/3oR8EF9F27dg09tFqnuqBefcZMjake9XmyQw45JGDUu3fv0GOaOCCAIICY1A++ENAlwCFYlxR2EMhPwIYQwhsg+TljAQEbBNj/bFBkDAiEJ0DvhWeGBwRsEaD/bJFkHJ8IIIB4kE0lOkydOlW++OKLZqPp1KmTXHnllXLEEUdYifhvf/ubPPLII6JEkOaeqAJI7q6VDz/8sNmxlRhyySWXBKKFzqPW+eijj4patxJXmnrUhfannXaanH/++dK6dWudYY1tEEAQQIyLiAEgoEGAQ7AGJEwgEJKAiRDCJeghYWMOgYgE2P8igsMNAoYE6D1DgLhDwIAA/WcAD1dvCSCApDy169evl5tvvlk2bNgQRKJ+iX/wwQfL3nvvHbwF8sEHH8j27duDn7Vq1SqwPfTQQ42jfvLJJ+Wpp55qcZwoAoi6U2XkyJHBWyy5R72V0aNHj+C+FfXmRmVlZf3P1Bsmap58j7q8/rXXXqs3U4Xfp0+f4N+XLl0qa9asqf+ZertEiUWFeBBAEEAKUWfMAQEOwdQABOIjoISQ9Y/PlqrFH+hPUlQkvaZN1bfHEgIQiESA/S8SNpwgYEyA3jNGyAAQiEyA/ouMDkePCSCApDy5o0aNkk8++SSIQn0e6oYbbpD999+/Pip1P8mUKVMCIUQ9HTp0kLKysuDzWCZPTgDp0qWLHHTQQcGno9T/feGFF+Ttt98Oho4igDQUKtRar7vuOunfv3/9UtVdK/fff78sWLAg+DP1psakSZMCwae556WXXpL77rsv+LESiP7f//t/wZsealNQj/pk1/PPPx+8IZJ7O0RXWDFhqHwRQBBATGsIfwjoEOAQrEMJGwhEJ1C5eImsuW+G/gAIIPqssISAAQH2PwN4uELAgAC9ZwAPVwgYEqD/DAHi7iUBBJCdaR03btwuCf79739f/++7/8ykEhqOazKO8n3//fdl/PjxwTBKCFD/u2fPno2GVaLB8OHDRV3Yrp4zzzxTzj33XKPp165dK3vssYeUlJTsMs4999wjr776avBnYQWQFStWBOvMiRDqbZUf/OAHjdapBAsl/Hz66afBz44++mi55pprmoxnx44dcvXVV4t6UyZf7LNmzZI5c+YEdkpMUsJR3J/CQgBBADFqRJwhoEmAQ7AmKMwgEJFA5cJFsub+B+u9/61dO6mrqZG6HTuaHhEBJCJp3CAQjgD7XzheWEPAFgF6zxZJxoFAeAL0X3hmePhPAAFkZ44HDRq0S7afeOKJ+n/f/WcmZdFwXJNxlK8SZhYuXBgMc+KJJ8oVV1zR7JDqMnH15od61JsVM2bMCD6JZfsxEUAeeOABmTdvXrCkww47TG655ZZml/fPf/5Tbr311uDn6j/u6q2Qpi55f+utt2Ty5MmBXfv27WX69OnStm3bJsetrq4OGKpPbaln2LBhwQXycT4IIAggcdYXY0MgR4BDMLUAgXgJVP5joax54KH6Sf6tfXupVZ8gbe6uNASQeBPC6BDYSYD9j1KAgBsC9J4b7swKgdzvyHJfSamoqAi+esIDgawTQADZWQFpE0DUWx2XXnqpqDcc1DNmzBjp27dvs/Ws7AYPHixbt24NbJR40PDTUrYaIaoAot76uOqqq+rf1FBvbRxzzDEtLku99fHll18GNr/5zW/khBNOaGSvLofPfS7rpJNOkssvv7zFMZVA8uKLLwY2xx57rAwZMsQWmibHQQBhI461wBgcAvwCiBqAQEEIfPPeP2TtgzP150IA0WeFJQQMCPBLWAN4uELAgAC9ZwAPVwgYEqD/DAHi7iUBBJCdaV20aNEuCW746aXdf2ZSCU190inKeIsXL5Y77rgjcFVvNMycOTPvGx1KJFmyZEngM3DgQDnnnHOiTN2iT1QBZPXq1TJ06ND6sZUQ8Z3vfKfFuRqKFUosUaLJ7o96oyN3QbyOqKLEEiWaqKdz5871d4dYB7VzQAQQBJC4aotxIdCQAIdg6gEC8RFQl6Cve3SWbP3oY/1JEED0WWEJAQMC7H8G8HCFgAEBes8AHq4QMCRA/xkCxN1LAgggKU2rurRbiR7q6dOnT70Y0lI4De+4UJ92Up94sv1EFUDeffddmThxYrAcda+I+qRVvkd9Lkt9Nks9vXr1kgkTJuzioj5lddFFF9X/WWlpqey7774tDrtq1Sq59tpr620UY/XprLgeBBAEkLhqi3Eh0JAAh2DqAQL2CSjhY9ML82XLawuav+ujmWmLiovlgMnfnnt4IACB+Aiw/8XHlpEh0BIBeo/6gIA7AvSfO/bMnFwCCCDJzU2LK2t4X8ZRRx21y9sTzTnOnTtXHnzw2ws6e/ToIZMmTbIefVQBRF0+rgQa9egKOg0vgVdvwTz66KO7xPPZZ5+Jukg99zz22GPSpk2bFmNW94BccMEF9TZjx46V3r17W+eUGxABBAEktuJiYAg0IMAhmHKAgD0CJsJHbhWtSkqk57jR9hbFSBCAQJME2P8oDAi4IUDvueHOrBBQBOg/6gACjQkggKS0KtTF3uqCb/WcdtppcvHFF+eN5J133pG77rorsNN9yyLvoLsZRBVAlDjx3HPPBaP9+Mc/lhtuuCHv1MuWLZObbrqp3k4JKHvssUf9v6sL4tVF8epp166dPPzww3nHVAYXXnhh/V0pSkAJ+9my9evX551H8VeX0CsBZO3atXntfTFQG3H37t2DcNasWcNlXL4kljgST4DeS3yKWGAKCNRs2iQb586Xza+9HvqNj93DUwLIARO+/ZQpDwQgEB8B9r/42DIyBFoiQO9RHxBwR4D+c8eemZNLoFu3bnmvjijE6ovq1C3YCX1yn0T6+c9/HtydEfZRv9h/+eWXpaioyNpbF+oX++oX/Oo544wz5Lzzzsu7rIaCQHFxsTzyyCN5fcIaRBVAorzRUl5eLtddd139EtXbLXvttVf9vyuBSAlF6unUqZPMmDFDK5zLLrtMNm3aFNiq8Y888kgtv5zR2Wefndf+3nvvlS5duuS1wwACEIAABCAAAfcEKr9YLh+OHCU1W76xspg2XTrLTx7SO5dYmZBBIAABCEAAAhCAAAQgAAEIQMApgUQLIIMGDQrgnHrqqXLJJZeEBqU+zfTnP/858HviiSdC+zfl8Ic//EE+/PDD4EdnnXWW5NbY0uDKXvmpRynCs2fPtrKWhoNEFUCUIKBEIvUce+yxMmTIkLxr++qrr+R3v/tdvd3uosJrr70md999d/BzJTaon+s8V155peTe4lDrUOsJ8yCAhKGFLQQgAAEIQCAdBLZv2CCrnp0jFX+dK7XbtxstGgHECB/OEIAABCAAAQhAAAIQgAAEUkcAASRkyngDRCSpb4DwCazmi5lXMUM2OuYQsESA3rMEkmEgICLBp7DmzZfNr0b/FJa6BP3AKd9+lpQHAhCIjwD7X3xsGRkCLRGg96gPCLgjQP+5Y8/MySXAJ7A0cmP6Boi6e+L5558P3rp4/PHHNWbMb8IdICJJvQMkf/b+z4JL0LkEPUy9YAuBqAS4CC8qOfwg0DwBo8vQi4qk17Sp4IUABGImwP4XM2CGh0AzBOg9SgMC7gjQf+7YM3NyCXAJukZuTAWQSZMmibqAvEOHDqLuqbDxRLkzY+7cufXz9+jRw9p9JA3jifoJrDlz5oi6xFw9ffr0kTvuyH8x6Pvvvy/jx48PfNq2bSvqU2MNn88++0zUJea5R1203qZNmxbxV1dXywUXXFBvM3bsWOndu7eNlDU5BgIIAkhsxcXAEGhAgEMw5QCB+AgoIWTtQzNl29L/0Z8EAUSfFZYQMCDA/mcAD1cIGBCg9wzg4QoBQwL0nyFA3L0kgACikVYTAWTFihVyyy23iPrFuvpFus4v9jWWFLxRMnPmzMBUVzBQAoMSGtQzYMAAGTZsmM5UoWyiCiDvvvuuTJw4MZirpKRE7r///rzzzps3T5QQpJ5evXrJhAkTdvGpqqqSiy66qP7PSktLZd99921x3FWrVknu0ntlqBi3b98+71qiGiCAIIBErR38IBCGAIfgMLSwhUB4AptefEm+fupZfUcEEH1WWELAgAD7nwE8XCFgQIDeM4CHKwQMCdB/hgBx95IAAshuaVV3a+z+LFq0KPijrl27inpzQuepqamRr7/+WlavXl1vri4r17kgW2f8xYsX14sp6u0H9Yv6Vq1ateg6ZswYWbJkSWAzcOBAOeecc3SmCmUTVQBRnIYOHVo/lxJAlBDS0jN9+nR58cUXA5NjjjlGrr766kbmV1xxhWzYsCH482uuuUaOPvroFsdcsGCBTJ367ScpOnfuLPfdd1+o+MMaI4AggIStGewhEIUAh+Ao1PCBgD6BTS+8KF8/89/1DuqOj7pt25ofAAFEHy6WEDAgwP5nAA9XCBgQoPcM4OEKAUMC9J8hQNy9JIAAsltac2972M62+mW+esOhY8eOVobetm2bXHrppbJjx45gPCVu9O3bt9mxld3gwYNl69atgc2tt94q/fv3t7KWhoNEFUDq6urkqquuktwF4jpihbL58ssvg+l/85vfyAknnNAoHiVmKFFDPSeddJJcfvnlLcashJf58+cHNscee6wMGTLEOqOGAyKAIIDEWmAMDoGdBDgEUwoQiJfAxrkvyIb/fk5/EgQQfVZYQsCAAPufATxcIWBAgN4zgIcrBAwJ0H+GAHH3kgACyG5ptS2AtG7dWn70ox/J+eefL927d7daROptlYULF2r9cr/hmw177rln8OmofG+MRFlsVAFEzdXwXpPDDz9cRowY0ewSli5dGnxaTD1FRUUyY8aMJsWlt956S9SF8epRcau3Rpq7B2T79u2i3hiprKwM7K+//nr56U9/GgWDtg8CCAKIdrFgCAEDAhyCDeDhCoE8BNQdIGtmPCjVny/TZ4UAos8KSwgYEGD/M4CHKwQMCNB7BvBwhYAhAfrPECDuXhJAANktrbnPXTX849xnsZSQccopp+QtBPUL+T322EP22msv2WeffUSJIHE8DS8BV3OoOzD222+/RlOp+0eGDx8uFRX/P3tnAl9VdfXtdTOREIaIgqiIiIgWqzWoIA44VmtH66vi0NfWeaqK4Gw/EakV66w4QKtFKwitb1uxVVG0zrbWRlQgggwyBpCQkYTM32+fcC834933nHPvGfZz+rOQ3LX3XutZe2WfnD/77I3WZ6effrqcd955qXBJnAgg6rwU5afaDaIuJXAccsghHfxsbm6WO++8U7788kvrs6OOOqrN67PiG6idL+rVWNGdJd29+mv27Nnyt7+1vr6if//+8sgjj6Qsd1EfEUAQQFJSiHQKgXYEuAlmSkDAfQJK+Kh4Y4FUvfu+tOzYkas9CgKINioMIeCEAOufE3q0hYB9AtSefXa0hIBTAtSfU4K0DyMBBBCNrDo5BF2je0cmkyZNkuLi4thD+5tvvlkGDx4c67Oqqsp6kB89+6NXr17y2GOPWbsh2l+bN29u88on1fdBBx2UlH9OBBA10LRp0+Tdd9+1xlQC0oQJE9r4oF79pXZ7vPfee5aNEn4efPBBGThwYJd+vvXWW7GzPNRC8POf/1y+973vWTtH1KUElddee02effbZmPhy9dVXy3HHHZdU7HaMEUAQQOzMG9pAIFkC3AQnSwx7CHRNwJHwsaNbdUbIkIfuAzMEIJBiAqx/KQZM9xDoggC1x9SAgHcEqD/v2DOyfwkggGjkRu0MUJc6Y+Pwww/XaJE+E7Wz4bbbbosd9K0e6o8YMUJUYisrK+WLL74QtQNEXeqVV8r24IMP7tTBZAUQtVuj/bVly5bYK6SUyKIOjm9/qbNQurpqamrk//2//ydr166Nmey///7W4fPqs0WLFsX6Vwbq3JDjjz8+IfB4YUUZK8FE9at2m3z11VeyadOmWB+qP9VvOi4EEASQdMwzxoAAN8HMAQg4J+CG8BH1IrOgQAbfM8W5U/QAAQh0S4D1jwkCAW8IUHvecGdUCCgC1B/zAAIdCSCAhGBWrF+/3trl8fXXX3cZjTp8XT3UHzlyZJc2yQogZ599ti16f/rTn7ptt3XrVmsniBI7urpyc3PlwgsvlBNOOEHLh8bGRnnuuedk/vz5sV0e7Rsq8UjtDPnf//3flL/6Kjo2AggCiNYExggCDglwE+wQIM2NJ1C3bp1sfPgxad5W4woLBBBXMNIJBBISYP1LiAgDCKSEALWXEqx0CgEtAtSfFiaMDCOAABKShKsH/B988IH1n9o9UVFRYb3mSh28PmrUKEsoUCJId5dfBBDlo9qZ8fHHH1uvulq1apWUl5eLEj3UjhJ1FsuJJ57Y6e6SROlcvny5qFdiLVmyRJTQoq5+/fpZu2ZUn8OGDUvUhaufI4AggLg6oegMAl0Q4CaYqQEB5wTYAeKcIT1AIN0EWP/STZzxINBKgNpjJkDAOwLUn3fsGdm/BBBANHPz4osvSn19vRQUFMj3v/99zVYir7zySuzhvTqAmwsC8QQQQBBAqAgIpIMAN8HpoMwYphBwQwhhB4gps4U4vSbA+ud1BhjfVALUnqmZJ24/EKD+/JAFfPAbAQQQjYyo3QKTJ0+2LM877zz5yU9+otGq1eSll16S6IAIPRkAACAASURBVBkiU6ZMsc4R4YJAlAACCAII1QCBdBDgJjgdlBnDNAJOhBAEENNmC/F6RYD1zyvyjGs6AWrP9BlA/F4SoP68pM/YfiWAAKKRGXV2xD/+8Q9RZ0Q89dRT1i4Q3ausrEyuvPJK65VOP/rRj+RnP/uZblPsDCCAAIIAYsA0J0QfEOAm2AdJwIXQElBCyKYnnpL6NWu1Y0QA0UaFIQQcEWD9c4SPxhCwTYDas42OhhBwTID6c4yQDkJIAAFEI6m/+tWv5KuvvpLBgwfLfffdp9GircmNN94oa9assXZ/qF0gXBCIEjBNAKlraJbMHn1ke32TVFeWSd/8bMnrkcmECDGB2romKauul7r6JumRkym79Moh5x7kO503wSbn3MvYgzx2It+T/TwvJ1Nq65tiP3fiv44vP/Uzqb2t3Z9RpX96USr/+Y52dSOAaKPCEAKOCKRz/XPkKI0hEDIC1F7IEko4gSJA/QUqXTibJgIIIBqgL774YqmurpajjjpKrrvuOo0WbU0efvhh+eijj6xDyH/3u98l3Z4G4SVgggCidj8tW1slby/cLAuXl0lzy858ZkREDt1/Fzn+OwNk+N69rV1WXMEnQM79l8NU3wSbnHMvYw/y2Il8/86wAtlvz96yYkO1fNbJ2tHd504qUK1CB+7TR04sHCAHDy3QXpe2zPmTVL3znvbQCCDaqDCEgCMCqV7/HDlHYwiEmAC1F+LkEprvCVB/vk8RDnpAAAFEA/q5554rzc3NcvLJJ8ull16q0aKtiRI9FixYIFlZWTJr1qyk29MgvATCLoCs2bRN/vDqKtlQWpswiXvumicXnravDN49P6EtBv4lQM79mZtU3gSbnHMvYw/y2Mn47mVF5WRH5PSjB8mJI3dPKIRsfvaPsu1fH2u7iwCijQpDCDgikMr1z5FjNIZAyAlQeyFPMOH5mgD15+v04JxHBBBANMBfeOGFUlNTI0cffbRce+21Gi3amjz66KPywQcfSG5urjz77LNJt6dBeAmEWQBZ8nWFPDVvuajXXulePbIz5IofD5MRQ/rqNsHORwTIuY+S0c6VVN0Em5xzL2MP8th2fPe6srIzRX567N6dCiHRg9Ct11816693CCBeZ5XxTSGQqvXPFH7ECQG7BKg9u+RoBwHnBKg/5wzpIXwEEEA0cqpee7Vx40YZNGiQPPDAAxot2ppMnDhR1q1bJwMGDJDHHnss6fY0CC+BsAog6l/33j/3y6TEj2iWlQhyw7gD2QkSsGlPzv2dsFTcBJuccy9jD/LY55+8j8xasNrW2uCHClNCyNkn7CPHHtJfmiqrpOKNBVL17vvS0tCQtHsIIEkjowEEbBFIxfpnyxEaQcAwAtSeYQknXF8RoP58lQ6c8QkBBBCNRCjR4v3337cs7733XhkyZIhGq1aTlStXyq233mr9ffTo0TJhwgTtthiGn0AYBRD1Xve7nl2s9dqrrjK85255cscFByV85Uj4Z0gwIiTn/s+T2zfBJufcy9iDPnZWZkQam+IOgvJ/6XTwML+xVo6tXiKHli8VaWy0FUFGnz7S98TjpODUU2y1pxEEIKBPwO31T39kLCFgNgFqz+z8E723BKg/b/kzuj8JIIBo5EW9vkq9xkpdw4YNk0mTJklOTk7ClvX19XLnnXfKihUrLNurrrpKjjvuuITtMDCHQBgFkKVrKuXBPy91nMQJZx8gB+zdx3E/dJB6AuQ89YydjuD2TbDJOfcy9jCM7XQue9VeCR+jyxZJYeUyyW5pcuQGuz8c4aMxBJIi4Pb6l9TgGEPAYALUnsHJJ3TPCVB/nqcAB3xIAAFEIynqAHT1GqzNmzdb1gceeKBcffXV1iuturqU7bRp02Tp0tYHwf3795dHHnlEMjMzNUbExBQCYRRApr+8XIqWlTlO4ZCB+XJC4c4ai0Qijvp01tr+0A7dtj+wiKMdNMnweuO/G2VVyTZHvqrGQ/fIl5MPHyjJjN1hUAeNI85Gdtbakd+J0UcyMmSXggLLsKy8XFrizyqwMUnnf1wiKzZUJx44gcWwvXrJ90bt4bifZDuwEXJsiFf/XSLL17sT+/eP3DMp11/51wZXxt5/r16SzNiK1z8+2iBfuRB3UgH7xHhA3VY5d/3rktdc74pHCCCuYKQTCGgR4CGQFiaMIOA6AWrPdaR0CAFtAtSfNioMDSKAAKKZ7EWLFsndd98tSgxRl/qBUlhYKAcddJAoiOqA8+3bt1siibL99NNP29iq12AdcsghmqNhZgqBsAkgtXVNMuHxImkO9htOTJl+xAkBCEAAApoErB0g5YulsGIpO0A0mWEGAT8Q4CGQH7KADyYSoPZMzDox+4UA9eeXTOCHnwgggCSRjXfeeUdmzJghjUm881nt+Lj00kvlhBNOSGIkTE0hEDYBZENprUyeuciU9BEnBCAAAQgYRsANISSSmytDHrrPMHKECwFvCPAQyBvujAoBao85AAHvCFB/3rFnZP8SQABJMjdfffWVPPPMM9bh5omuoUOHykUXXST7779/IlM+N5RA2ASQVSXVMnV2saHZJGwIQAACEDCFgCMhJBKRfZ9oPVuOCwIQSC0BHgKlli+9Q6ArAtQecwMC3hGg/rxjz8j+JYAAYjM3S5YskYULF4oSRCoqKqS2tlby8vKkb9++luChXo/1rW99y2bvNDOFQNgEELd3gAzslyvZWRkiDl6p1eKksc2J2OLIX5uDqmY2x3XCqKGxWbZUuPNefBXCbn1zJCszIyEEJ4wTdt6FgRNOdnPjIK0Sz0gdMZKZ1XoGVVNjkxN3pLGpWcqrG+xi7NCub362ZGU6OARFTX2bcz9Zvk1NLVJZ417svXtmSWaGXuxNzS1SVdPoGvdeecmNXV3r3tiuBeGDjqJCyOHlxZKhW1kIID7IHC6YQoCHQKZkmjj9RoDa81tG8MckAtSfSdkmVl0CCCC6pLCDQAoIhE0AcfMMkIyMiDx4VaHk9Wh9aMvlTwLk3J95ae+VmzfBJufcy9jDMnYwKiZ5L89av0D2q92g1xABRI8TVhBwgYCb658L7tAFBIwhQO0Zk2oC9SEB6s+HScElzwkggHieAhwwmUDYBBCVy+kvL5eiZWWO03rY8F3ksh8Nc9wPHaSeADlPPWOnI7h9E2xyzr2MPQxjO53Lfm1/5oa3ZFjNOj33EED0OGEFARcIuL3+ueASXUDACALUnhFpJkifEqD+fJoY3PKUAAKIp/gZ3HQCYRRAlq6plAf/vNRxaiecfYAcsHcfx/3QQeoJkPPUM3Y6gts3wSbn3MvYwzC207ns1/bnrH9dhtRu1HMPAUSPE1YQcIGA2+ufCy7RBQSMIEDtGZFmgvQpAerPp4nBLU8JIIB4ip/BTScQRgGkpaVF7np2sajzQOxee+6WJ3dccJBEInrvxrc7Du3cIUDO3eGYyl7cvgk2Oedexh70sdVZL41NDg5sSWWR2OzbOgOkbJEcXqHOANG8EEA0QWEGAecE3F7/nHtEDxAwgwC1Z0aeidKfBKg/f+YFr7wlgADigH9VVZWo/9QB6OqhhM41bBiv9NHhZIpNGAUQlbs1m7bJ/XO/lLqG5qRT2SM7Q24Yd6AM3j0/6bY08I4AOfeOvc7IqbgJNjnnXsYe5LHPP3kfmbVgta21QWeep9MmKnwUVi6T7Jam5IZGAEmOF9YQcEAgFeufA3doCgFjCFB7xqSaQH1IgPrzYVJwyXMCCCBJpmDlypXy2muvyRdffCFbt25NqrX61+xz5sxJqg3G4SYQVgFEZW3J1xXy1LzlST3oUuLHFT8eJiOG9A134kMaHTn3b2JTdRNscs69jD3IY9vx3U+V5Uj42BFIJDdXhjx0n5/CwhcIhJZAqta/0AIjMAi4RIDacwkk3UDABgHqzwY0moSeAAKIZorVDo8//vGP8sorr2jv9uis67lz52qOiJkJBMIsgKj8qX+p/IdXV2m9Dku99urC7+3Lzo+AT3xy7s8EpvIm2OScexl7kMdOxne/VJQbwkc0lsyCAhl8zxS/hIYfEAg1gVSuf6EGR3AQcEiA2nMIkOYQcECA+nMAj6ahJYAAopnaWbNmybx582LWAwYMkLq6OqmoqLC+p15ttX37diktLbVeiRW9cnNzZdCgQbGv7777bs0RMTOBQNgFEJVDJR4uW1clby/cLAu/KpPmuLfFZWREpHBYgRx36AAZPqg3Z36EZNKTc/8lMtU3wSbn3MvYgzx2It8P3a+v7LdXb1mxvloWLu+4dnT3udsVOKBuq5y7/nXJa653pWsEEFcw0gkEtAikev3TcgIjCBhIgNozMOmE7BsC1J9vUoEjPiKAAKKRjA0bNsiECROsB7m9evWSG2+8UQ488EB55plnZP78+VYP0Z0dyubrr7+2vv/2229bbU477TS54IILRP0Q4oJAPAETBJD4eNWZIFm5faW2rlG2VZVLn55Zktcjk0kRYgK1dU1SXl0v2+ubJDcnUwp65ZBzD/Kdzptgk3PuZexBHjuR78l+rn7WqJ850Z878V/Hl5967eLnKyvkb++tk0QnuVk7QMoXS2HF0uTP/GhX8wggHvwQZEhjCaRz/TMWMoFDoBMC1B7TAgLeEaD+vGPPyP4lgACikRv16qu///3vluXEiRNl1KhR1t87E0Diu1u0aJH89re/tXaKKBHkF7/4hcZomJhEwDQBhIXYpNlNrH4iQO35KRv44jcC22obZMITC7XcckMI4QwQLdQYQcAVAqx/rmCkEwgkTYDaSxoZDSDgGgHqzzWUdBQiAgggGsm89dZbRR1+3q9fP3nyySdjLRIJIMrwvffek2nTplltpkyZIsOHD9cYERNTCCCANJuSauKEgKcEuAn2FD+DB4DA1NmLZVVJjbanjoSQSET2feJR7bEwhAAE7BNg/bPPjpYQcEKA2nNCj7YQcEaA+nPGj9bhJIAAopHXSy65RKqqquSII46QG264oVMBRJ0RkpWV1WlvV199tWzZskVOPPFEufzyyzVGxMQUAgggCCCmzHXi9JYAN8He8md0/xN4e+EmeeHNNUk7GhVCjihfIhHd1ggguqSwg4BjAqx/jhHSAQRsEaD2bGGjEQRcIUD9uYKRTkJGAAFEI6HnnnuuNDc3y0knnSSXXXZZrEX8q7HUbpD8/PxOe3v00Uflgw8+kD333FMeeughjRExMYUAAggCiClznTi9JcBNsLf8Gd3/BNZvqZG7nl1s29GLV78k/Rsq9NojgOhxwgoCLhBg/XMBIl1AwAYBas8GNJpAwCUC1J9LIOkmVAQQQDTS+fOf/1y2b9/eQQD5v//7P/nTn/5k9XDffffJ4MGDO+3tiSeekHfeeUfy8vJk5syZGiNiYgoBBBAEEFPmOnF6S4CbYG/5M7r/CaiD1sdPK7Lt6EVr5smA+vJYe3Woepc7QhBAbHOmIQSSJcD6lywx7CHgDgFqzx2O9AIBOwSoPzvUaBN2AgggGhm+7rrrZOPGjTJ69GiZMGFCrMX7778vjz32mPX1lVdeKccff3ynvd1xxx2ydOlSycnJEbVrhAsCUQIIIAggVAME0kGAm+B0UGaMoBN4+MWlUry60lYYl6z+q+zWUKXXFgFEjxNWEHCBAOufCxDpAgI2CFB7NqDRBAIuEaD+XAJJN6EigACikU61u+OTTz6RIUOGyL333htrsWHDBrn++uutr0eMGCGTJk3q0NuqVatEHaLe0tIiAwcOlEceeURjRExMIYAAggBiylwnTm8JcBPsLX9GDwYBO+eAWGeAlC2SIyqKOQMkGGnGS8MIsP4ZlnDC9Q0Bas83qcARAwlQfwYmnZATEkAASYhI5O9//7u1c0Mdcv70009Lbm5urNWNN94oa9a0Hpp52mmnydlnny09e/a0vl6+fLm1Q0TtHlHXqaeeKhdddJHGiJiYQgABBAHElLlOnN4S4CbYW/6MHgwCyZwDEhU+CiuXSXZLU3IBsgMkOV5YQ8ABAdY/B/BoCgEHBKg9B/BoCgGHBKg/hwBpHkoCCCAaaV23bp1MnDjRslR/jho1Ktbq448/lgceeCD2tRJJ+vXrJ3V1dVJRsfMwTPX6q/vvv18UcC4IRAkggCCAUA0QSAcBboLTQZkxgk6grKpebpnxWbdhOBI+dvQcyc2VIQ/dF3Rc+A+BQBBg/QtEmnAyhASovRAmlZACQ4D6C0yqcDSNBBBANGGrV1+VlpbKd77zHTn//PPbtJo1a5bMmzevy56UKHLNNdfIkUceqTkaZqYQQABBADFlrhOntwS4CfaWP6MHg8CG0lqZPHNRp866IXxEO84sKJDB90wJBhS8hEDACbD+BTyBuB9YAtReYFOH4yEgQP2FIImE4DoBBBCXkKozQl5++WVZtmyZNDe3PtRVuz6UYHLmmWda54dwQaA9AQQQBBCqAgLpIMBNcDooM0bQCawqqZaps4s7hDGgbqucu/51yWuudyVEBBBXMNIJBLQIsP5pYcIIAq4ToPZcR0qHENAmQP1po8LQIAIIIC4nu6GhwXr1VSQSkYKCAsnMzHR5BLoLEwEEEASQMM1nYvEvAW6C/ZsbPPMPgYQ7QMoXS2HF0uTP/GgXIgKIf3KOJ+EnwPoX/hwToT8JUHv+zAtemUGA+jMjz0SZHAEEkOR4YQ0BVwkggCCAuDqh6AwCXRDgJpipAYHEBGrrmmTC40XS3NK1rfUqLIdCCGeAJM4FFhBwiwDrn1sk6QcCyRGg9pLjhTUE3CRA/blJk77CQgABRCOTv/rVryyr7Oxsuf3220Wd6cEFATcIIIAggLgxj+gDAokIcBOciBCfQ6CVwBN/+0o+W1GeEIcjISQSkX2feDThGBhAAALOCbD+OWdIDxCwQ4Das0ONNhBwhwD15w5HegkXAQQQjXyOGzfOsjr00EPl1ltv1WiBCQT0CCCAIIDozRSsIOCMADfBzvjR2hwCHy76Rp6d/7V2wFEh5IjyJRLRbYUAoksKOwg4JsD65xghHUDAFgFqzxY2GkHAFQLUnysY6SRkBBBANBJ68cUXS3V1tZx00kly2WWXabTABAJ6BBBAEED0ZgpWEHBGgJtgZ/xobQ6BlRuq5N4Xvkw64PErXpDclga9dgggepywgoALBFj/XIBIFxCwQYDaswGNJhBwiQD15xJIugkVAQQQjXTeeOONsmbNGhkzZoyMHz9eowUmENAjgACCAKI3U7CCgDMC3AQ740drcwh0dxB6dxSuX/GC9IgTQNQxIl3uCEEAMWdCEannBFj/PE8BDhhKgNozNPGE7QsC1J8v0oATPiOAAKKRkNmzZ8tLL70ku+22mzz++OMaLTCBgB4BBBAEEL2ZghUEnBHgJtgZP1qbQ0AdhH79tCLp5hz0TmFMWD5LcqRJDxQCiB4nrCDgAgHWPxcg0gUEbBCg9mxAowkEXCJA/bkEkm5CRQABRCOdJSUlcsMNN0hjY6NcffXVMnbsWI1WmEAgMQEEEASQxLMECwg4J8BNsHOG9GAOgZunL5Tyar3XWVlngJQtkiMqijkDxJwpQqQBIsD6F6Bk4WqoCFB7oUonwQSMAPUXsIThbloIIIBoYn711Vdl5syZkpOTI9dcc42MGjVKsyVmEOiaAAIIAgj1AYF0EOAmOB2UGSMMBKwdII8XSUuCLSBR4aOwcplkt2ju/IgCYgdIGKYKMQSEAOtfQBKFm6EjQO2FLqUEFCAC1F+AkoWraSOAAKKBuqKiwrJ69913Rb0Oq7m5WUaMGCFHHXWUDB06VPr06WMJIzpX3759dcywMYQAAggCiCFTnTA9JsBNsMcJYPjAEEh0Bogj4WMHhUhurgx56L7AMMFRCASZAOtfkLOH70EmQO0FOXv4HnQC1F/QM4j/qSCAAKJBddy4cRpWiU0ikYjMmTMnsSEWxhBAAEEAMWayE6inBLgJ9hQ/gweIwKqSapk6u7iDx24IH9FOMwsKZPA9UwJEBVchEFwCrH/BzR2eB5sAtRfs/OF9sAlQf8HOH96nhgACiAZXtwQQNdTcuXM1RsTEFAIIIAggpsx14vSWADfB3vJn9OAQ6GwHyIC6rXLu+tclr7nelUAQQFzBSCcQ0CLA+qeFCSMIuE6A2nMdKR1CQJsA9aeNCkODCCCAaCT70ksvFbV7w41rxowZbnRDHyEhgACCABKSqUwYPifATbDPE4R7viFQVlUvt8z4rIM/1g6Q8sVSWLE0+TM/2vWGAOKbdOOIAQRY/wxIMiH6kgC158u04JQhBKg/QxJNmEkRQABJChfGEHCXAAIIAoi7M4reINA5AW6CmRkQ0COgdQaIQyGEM0D0coEVBNwgwPrnBkX6gEDyBKi95JnRAgJuEaD+3CJJP2EigAASpmwSS+AIIIAggARu0uJwIAlwExzItOG0BwS6OgOkvSuOdoREIrLvE496EB1DQsA8Aqx/5uWciP1BgNrzRx7wwkwC1J+ZeSfq7gkggDBDIOAhAQQQBBAPpx9DG0SAm2CDkk2ojggk2gHSmRAypuxzObxiqf64CCD6rLCEgEMCrH8OAdIcAjYJUHs2wdEMAi4QoP5cgEgXoSOAABK6lBJQkAgggCCABGm+4mtwCXATHNzc4Xl6CdTWNcn104qkJYlhezTVy/Wr5ui3QADRZ4UlBBwSYP1zCJDmELBJgNqzCY5mEHCBAPXnAkS6CB0BBJC4lK5evdr6qk+fPrLLLruELtkE5D8CCCAIIP6blXgURgLcBIcxq8SUKgIPv7hUildXanffo6lOrl81t429ElAiXfWAAKLNFkMIOCXA+ueUIO0hYI8AtWePG60g4AYB6s8NivQRNgIIIHEZHTdunPXVqaeeKhdddFGXuS4rK5PKytZfjPfZZ5+wzQniSSMBBBAEkDRON4YymAA3wQYnn9CTJvD2wk3ywptrtNvlNW2X61b9SdteEED0WWEJAYcEWP8cAqQ5BGwSoPZsgqMZBFwgQP25AJEuQkcAAcSGAPLMM8/I/PnzJRKJyJw5SbzyIHTTh4CcEkAAQQBxOodoDwEdAtwE61DCBgKtBNZvqZG7nl2shUMdhn7M1oVSWPmVlr1lhACizwpLCDgkwPrnECDNIWCTALVnExzNIOACgWj93fL6PVK6rcxxj31yesnEwksc90MHqSfwwKe/l8r6ascDhTHnCCBx00J3B0hUAFFN585t+8oDx7OMDowigACCAGLUhCdYzwjwS6hn6Bk4gATKqurllhmfdeu5Ej5Gly2Swsplkt3SlFyUCCDJ8cIaAg4IsP45gEdTCDgg4NfaM/XhoKlxqylsYuzR+rti3q2ytbbcQSW3Nu2b01smjx7vuB86SD2BSf9+WCrqqxwPFMacI4AggDguDDqwTwABBAHE/uyhJQT0Cfj1l1D9CLCEQPoIbCitlckzF3U6oCPhY0ePkdxcGfLQfekLiJEgYDAB1j+Dk0/oXRJIxwNhv9aeqQ8HTY1bFYGJsSOAmLsAmDjfdbONAIIAojtXsEsBAQQQBJAUTCu6hEAHAn79JZRUQcCPBFaVVMvU2cVtXHND+Ih2mFlQIIPvmeLH0PEJAqEjwPoXupQSkAsE0vGAzK+1l47YXUiR612YGjcCCDtAXC8mn3docq0nSg0CCAJIojnC5ykkgACCAJLC6UXXEIgR8OsvoaQIAn4k0H4HyIC6rXLu+tclr7neFXcRQFzBSCcQ0CLA+qeFyVijdOyE8CPcdDwg82vtpSN2U3Pux7gRQBBA/DovU+WXqT/jdHgigCCA6MwTbFJEAAEEASRFU4tuIdCGgF9/CSVNEPAjgdq6Jhk/raiNa9YOkPLFUlixNPkzP9oFiQDix6zjU1gJsP4lzqypIoCpD0bTFbdfa8/Uh4Omxp2u+Z74J216LXgFVnp5+2k0k2s9UR4QQBBAEs0RPk8hAQQQBJAUTi+6hkCMgF9/CSVFEPAjgc4EkKifbgghCCB+zDo+hZUA61/izJr8sMTU2NMRt19rLx2xJ6669FuYGjcCCDtA0l9t3o5ocq0nIo8AggCSaI7weQoJIIAggKRwetE1BBBAmAMQsEGgu0PQ3RBCEEBsJIUmELBJwK8PYW2Gk5JmJj8sMTX2dMTt19pLR+wpKdRuOm1paZFmaRH1p/U/9XWL9Z3Y9+7973SpbKh27Fqv7J5y8YhxIrG+Zee40qK+3Tpu3OdtbON8Us7E+9zS2qv1/80t6s/o5zu+vyPO7tq19tfWpzfXfijbm+ocx56TkS1HDixs9XFHnJYvVkzRv8X9GY0hFlerX20s475u7aLV/yiJ9l+3H7vVcme7aGv1rZycHFnyzVfS2NzoOPbMSKbs03svx/3QQeoJrK5aL00tTY4H6pvTWyaPHu+4Hz91gAASl41x49QPcpFTTz1VLrrooi7z9Mwzz8j8+fOtz+fOneunfOJLwAgggCCABGzK4m5ACfj1l9CA4sTtkBPo7BD0rkJWO0KO3/JfObh6pTYVBBBtVBhCwDEB3fWP10BVOWYdxIclYXwYrpPIVMdtPeTNiMiAAf2lqaVZSjZulKamRuuhvHosbz2cb2mxPlOP7tXDbuuzuM/V91pamlttrAffOz5vZ9vWJq6fmAjQtv9/rv+X1DU5P9MrK5IlwwuGdC087HiI30aUsB6UtwoTVnw7HpxHGcREg3aCRnsxY2fb1j64IAABCLhNIIhreiIGCCCdCCDDhg2TwsLCLtkVFRXJihUrrM/POuusRIzbfH7mmWcmZY9xuAkggCCAhHuGE51fCOg+APKLv/gBAS8J6OwAifevf12ZXLz2ZW2XEUC0UWEIAccEdNe/VD8QdhxICjsg9vSLP9GH/+pf6aoH/M3NrX9Gv1Z/qofeTc1x37Ns2to1q68tm512O7/Xzjaur6JvFkmDC/8qPCIiPTJ77Higv1Og4KF8CguWriEAAQikgQACSOogR1qie8FSN0bCnqM7QBIaOjBgx4gDeCFsigCCABLCaU1IPiSg+wDIAW+ymgAAIABJREFUh67jEgTSTkCdAXL9tCLtf1O5e12pXLj2HzE/1crWFMns8rB0BJC0p5QBDSagu/4hAqRfBEjVtFSPFRpbmqwH/OrVL+o/9XclHuz8XuvfZy+bJzWNtY5dUa+H2St/9+4FjJio0WTtGuCCAAQgAAEI+JUAAkjqMoMAkjq29OxjAgggCCA+np64FiICug+AQhQyoUDAEYGbpy+U8uoGrT4Gbt8iv1j3Ssy2IZIpT+1zhowuXyyFFUs7CCEIIFpYMYKAKwR01z8EEHcEkDtGXdtGdGgVIJqkoSUqRrQTJlqaOtq3EypiIoaGbVTocGXy0AkEINApgR6ZORIRtf9HvelM/am+ioj6646/qb/E/h6xbDq37a6PaDv1Z+x/O/q1ere+v2OcHTaqv5j9js+Xlq2Sxhbn52CoM0BGDvj2jsijBHbGbY3dGniMT9RqJ48dVq1Idtrt8LVNS8tGb5yoZSvqiJWXPn36yIuLX5GaBucib15mD/nBkBOpiAAQ+MfXb0mtC2feIICkLtm+EEDuvPNO64dlKq9Jkyalsnv6DhgBBBAEkIBNWdwNKAHdB0ABDQ+3IeAqAWsHyONFOw60TNz1Htu3yM/jBJD6SJY8uN95VsNeTbVy85BvpPaDD6W5vvWd4wggiZliAQG3COiuf2EXQKK7ItTZB+q/euvPBuvPmV/+nyu7INzKGf2YSyDDeqidYT28zbD+zBD1vejf1bOazIj1nTgb6yvLRn3eWTvVn9VWMmRJ2XJXXv+Vm9lDThl8zI4H/+ohdatPrUJA65+Jvo76m7hNa2yxPtv3v2PM+PEscnH+3F/0O1cOQQ/iQ9Gw/3zv7CdGdO27Yt6tsrW23PEPlSDm3XHQAe3AxPmumyrOANElhR0EUkAAAQQBJAXTii4h0IGA7gMg0EEAAiLJngGyZ+03csH6V2Po6iLZ8tB+58a+vuuiQ+SgPQtk/V9fkpJXXpOM/HwZfM8UUEPAlwTCdhi47vrnpwcG6jyHVoEiKlY0SH3zzq+VcBETMZqVmNH69U5ho17qdthHP1P98dolX5Zcl06pf5apXq2VmZFpPfTPUH+PZOz4nvqz3ffUZxmZlgAQs2vzvZ3t/7XpU1cOAs/P6ikXjzirE4EiIlmZWbJ7/wHWZ1u2lErEOhc9KnC0FTbiH9ynOkt+qvVUxxrfv6lxKwYmxo4Aks7q8tdYJs533QwggOiSwg4CKSCAAIIAkoJpRZcQQABhDkDAAYFVJdUydXaxdg971W6W/13/Wsx+e0aOPDz0nNjXt/3sIBlTOMz6et3SpVL54UdScOop2v1jCIF0EgjbL87pFkB6ZfeU/z3gpzFBwhIl2okRlljRQbjYIWo017vyr9PTOWeCMpb61/PZGVmSZf2Xaf29bHulNIvz30fyMnPlJ0O/u0N4aBUiOhct2gkUGTsEjXgxI9Y2I2Vo01HnurWXsiC76Dgdsac7Jp3xTI0bAYQdIDr1ESYbk2s9UR4RQBIR4nMIpJAAAojzXzhSmB66hkBoCPj1l9DQACaQUBFIdgfI3rWb5Pz182MMajNy5JE4AWTyhQfLyG8PtT7fuHGjNDez9oVqwoQsmLD94pxo/WtuaZaaxu1y73+fkqqGbSHLpn/CUTsZoqKDJUBEsiQ7Q32vVZCICRORVmEiKlK02sZ/r2vbzvvYaa8EifZX2Oa7bsbTEXei2tP11W27dMTuts9u9Gdq3AggCCBu1E+Q+jC51hPlCQEkESE+h0AKCSCA8BAohdOLriEQI+DXX0JJEQT8SECdATLh8SJpbtHzbnDNRjlvw+sx422ZufLYvmfHvr7mjOFyytHfQgDRw4mVxwSC+ouzOuOivrlBtjXUyLbGWuvQV/VnbeN2ieRmSnVdtWyuKN3xeY3UNGyXmsYa63PNUvc4M+4Prw70zcnMkZqGGldej9UrO1+uOeSCDoKGEjFaD0r23xXU+e6UZDri9uu9Zzpid5qfVLQ3NW4EEASQVNSTn/s0udYT5QUBJBGhbj6vqamRrVu3yrZt20Q9yB4xYoSD3mhqIgEEEAQQE+c9MaefgF9/CU0/CUaEgB6B6S8vl6JlZVrG+9SUyLkb3ojZVmfmybR9z4p9fdgB/eTOy45FANGiiZEi4OU5HH74xbmpuck6lHvbDhFDiRrq6/jvqYf20c+j329qaQrlBFK7J3pk5lj/KdEi9vfM+L/nSI8dgkb0c8tetevk+9kZ2TFRwg859ypxpsaejrj9eu+Zjti9ms/djWtq3AggCCB+rMdU+mRyrSfiigCSiFC7z2tra+WNN96Q9957T9auXSvqXxupKxKJyJw5c9pYV1RUyMsvv2x9b/DgwTJ27NgkR8M87AQQQBBAwj7Hic8fBPz6S6g/6OAFBDoS+HxFmTz+t+VaaIbUbJBzNiyI2VZl5snjcQJIRkTkhV9/X3rmZnMGiBZRjLz85dXNse8cdZ1sb6qzhIpWkaJ1d0b069ZdGq1Cxk5xo8aVw5m9nEV9cnq1ihQZrQJETpxQ0fq9jsJFTKyICh3KZkd79eqoVF5u5nzy6PGpdNX1vk2NPR1x+/XeMx2xuz5RXejQ1LhNF0Buef0eKd2m9w96uptmal2bWHiJCzORLlJNwMt/RJPq2Jz2jwCSBMElS5bIo48+KmVlnf8AmTt3bofebrnlFlm1apXk5+fLjBkzJCsrK4kRMQ07AQQQBJCwz3Hi8wcBv/4S6g86eAGBjgTWb6mRu55drIVm6Lb1cnbJmzHbiqye8uSQM9u0fezykdLy3gIpeXW+ZOTny+B7pmj1jZGZBLx8UOXW2OrAafXSo2bDXjDVN6e3IAIEp27dmu9By3s64vbrvaepDwdNjVv9NDIxdr/WX3BWBzwNIwEEEM2sfvnllzJlyhRpbGyMtdhrr72s11+Vl5db3+tMAHnzzTct4UNdN998s4wcOVJzRMxMIIAAggBiwjwnRu8JcBPsfQ7wIFgEVpVUy9TZxVpO77dtnZxV8lacAJIvTw75H+vr/MZaGV22SEbVLBdpaLC+l1lQgACiRdZco3Q8nGxPV+1qVzs0phY9JdUNNYGGnyER6ZndU/Kz8iQ/u6f061UgvXrkS0aDSE/1vaw86Zmt/uwpPbNzrT8fXPi0VNRXOY47aA/CVcBezDfHoF3qwNTY0/FAmHtPlyYp3UDABgHqzwY0moSeAAKIRorr6+vl2muvje38UK+yOu+882SXXXaRZ555RubPn2/10pkAUl1dLZdccon1qqzTTjtNfvGLX2iMiIkpBBBAEEBMmevE6S0BboK95c/owSOwobRWJs9cpOX4sG1r5cySf8Zsy7J6yfODTrOEj8LKZZLd7lwCBBAtrEYbpeKhbFNLs1TWVcnWugopqyuXrdvVnxWxP9XfG5p3/kMvvyQgN7OH5GfnWcKFJV7EhItWIcP6bIfYEf1ctVGvJ1aX7vqXCuZ+YZjID2I3U/hKNC+cfq5be07HoT0EINCRAPXHrIBARwIIIBqz4rXXXpM//OEPluV3v/tdS9CIXokEEGU3YcIEWb9+vRx44IEyefJkjRExMYUAAggCiClznTi9JcBNsLf8GT14BGrrmuT6aUVaL+/Zv3qN/M/Gt2NBbs/IlsyW5g7CR9QAAcT/8yEd/zq6OwpuPZDOzsiSwb32tESPirpKT19HpQ7ybhUvdgoZO3dpqO/1jAkdMWEjK08yHZ5/obv+ucWcHSDBOgPE61r3/09D+x7q1p79EWgJAQh0RYD6Y25AAAHE1hy4++675fPPP5e8vDx56qmnJDc3NykB5IEHHpCPP/5YCgoKZPr06bZ8oFE4CSCAIICEc2YTld8IcBPst4zgTxAI3Dx9oZRXt762qrvrgOrV8tON7yQyi32OAKKNyjNDrx+GuzW+ZwDV69+y8uSKg8+PvYYqJyM7tisjnX7prn9uMQ+iAIIIkM4Zac5YurVnDhEihUD6CFB/6WPNSMEhwA4QjVxdfvnl1jkf6vwOdY5H/KWzA0SJHm+99Zbk5OTIH//4R40RMTGFAAIIAogpc504vSXATbC3/Bk9eASsHSCPF0lLS/e+qzM+Ttv8oQyrWa8dJAKINirPDL18GK5em3vHvx+SqoZtnsXvxsB+EQJ01z8vc+4Gb/qAgN8I6Nae3/zGHwiEgQD1F4YsEoPbBBBANIief/751uHnJ598slx66aVJCyBq18g///lPycrKklmzZmmMiIkpBBBAEEBMmevE6S0BboK95c/owSOQ6AyQ6OHmnZ3xkShaBJBEhLz/PB0Pw5tbWqyzODbWbJFNNd9IybZvZJP6e+0WqWuqTxkE9VqsXXr0tf7rlxv/Z4H069FXHv7sD6E6DFx3/UtHzlOWVDqGgA8J6NaeD13HJQgEngD1F/gUEkAKCCCAaEC96KKLZNu2bXLsscfKL3/5y6QFkHvuuUcWLlxoHZquxBAuCEQJIIAggFANEEgHAW6C00GZMcJEYFVJtUydXdwhJCfCR7QzBBD/zxQ3H4ZPGnWtlG4vt0QOJXZstP5sFTtSfei4eu3Uafscv1Po6NFX8rN7dvsqKjdjnzza+/MgdNc/XgPl/7rEw2AR0K29YEWFtxAIBgHqLxh5wsv0EkAA0eA9ceJEWbduney7774yderUpAQQtXNE7RqpqamRAw44QO666y6NETExhQACCAKIKXOdOL0lwE2wt/wZPXgE2u8AcUP4QAAJzjxwSwTIiGRIhkSksaXJk+DtvIbKrdjtjJ0KSKx/qaBKnxBITIDaS8wICwikigD1lyqy9BtkAgggGtn73e9+JwsWLLD+tdTDDz8sAwcOjLVKdAbIm2++KTNmzLDsf/rTn8o555yjMSImphBAAEEAMWWuE6e3BLgJ9pY/owePgHUGyLQiUUeADKjbKueuf13ymt15LRE7QPw/H9wSAbyO1I4I4VbsdsZOBS/Wv1RQpU8IJCZA7SVmhAUEUkWA+ksVWfoNMgEEEI3sLVq0SKZMmWJZHnLIIXLrrbeK+oGiru4EkDVr1sgdd9whtbW1lnhy//33y6BBgzRGxMQUAgggCCCmzHXi9JYAN8He8mf0YBK4f26xfLWu2nLe2gFSvlgKK5ZKtsN/zY8AojcfvHwlkVsigE6keVm5MrBnfxnYc7cdf/aX55e+JFUNrXPPyWVHhHArdjtjO4m1q7asf6mgSp8QSEyA2kvMCAsIpIoA9ZcqsvQbZAIIIJrZmzx5sixZssSyLiwstF5rteuuu3YqgKjXXqmdHy+88IIlfqhrzJgxMn689+/B1QwXszQRQABBAEnTVGMYwwlwE2z4BCB8WwTiBZBoB24IIQggeunw6kF8TUOt3P3J47KtsfUe3q0rPyvPEjh2j4od+Ur06C+9s/M7nMnhVewqVi/Hdot1fD+sf6mgSp8QSEyA2kvMCAsIpIoA9ZcqsvQbZAIIIJrZKy0tldtuu03Ky8utFuoHyvDhw6WyslI2bNhgfe8HP/iBlJSUWELJ9u3bYz0PGDDAOjskPz9fczTMTCGAAIIAYspcJ05vCXAT7C1/Rg8eAfUKrAmPF0mzegdWJ5cTIQQBRG8+pONBfEtLi3VA+arKtdZ/KyvXWgeUu3XlZfaQi0acLXv07C+9cvR/D0hH7F3F6OXOG7e4x/fD+pcKqvQJgcQEqL3EjLCAQKoIUH+pIku/QSaAAJJE9tRB6A888EBM8NBpql55dfPNN4sSQbgg0J4AAggCCFUBgXQQ4CY4HZQZI0wE2h+C3lVsSgj50cb3ZMj2jdrhI4DooUqFCNDU3CTrt22yhI6o6FFZ7/xVU11FZPc1UKmIXY96+KxY/8KXUyIKBgFqLxh5wstwEqD+wplXonJGAAEkSX719fUyb948mT9/vrX7o6urZ8+e1o6QH/7wh5Kbm5vkKJibQgABBAHElLlOnN4S4CbYW/6MHjwCq0qqZersYi3HDysvlu9u+Y+WrTJCANFD5ZYIoF49dfQeh8mqynWyumq91Dc36DngghUCiAsQHXbB+ucQIM0hYJMAtWcTHM0g4AIB6s8FiHQROgIIIDZTqh5cr1ixQpYtWyZlZWVSU1MjPXr0kIKCAhk2bJgceOCBkpWVZbN3mplCAAEEAcSUuU6c3hLgJthb/owePAK6O0BUZIeXL5GTt3wSC7IiK196Nm3v8rB0UwQQp69SUjszWqSLd5AFZEohgHifKNY/73OAB2YSoPbMzDtR+4MA9eePPOCFvwgggPgrH3hjGAEEEAQQw6Y84XpEgJtgj8AzbGAJqDNArp9WpPX4/YiyJXJS6U4BZGXPPeUfA46W0eWLpbBiaQchxBQBxK0dHOmYRPlZPWVo371l3z6t/80sflEq6qscD21XAHEqHkUd75PTSyYWXuI4jiB3wPoX5Ozhe5AJUHtBzh6+B50A9Rf0DOJ/KggggKSCKn1CQJMAAggCiOZUwQwCjghwE+wIH40NJXD/3GL5al3i8yFGlS2SE0uLYpRW9NxL/rznSdbX6oyQ7zUtkwM2FUtzfb31PQQQ7yfUgLxdLaFj6A7Bo39eP4lEIjHH3BJv7Aog3hMKjwesf+HJJZEEiwC1F6x84W24CFB/4con0bhDAAHEHY70AgFbBBBAEEBsTRwaQSBJAtwEJwkMcwiIiK4AcmTZF3J86acxZst7DpIX9zwx9vXwvXvLPT8vlPV/fUlKXnlNMvLzZfA9U0LP2C0RwQ1Q+/YZFBM8hvTZW3pl9+y2W7d8RwBxI3vO+mD9c8aP1hCwS4Das0uOdhBwToD6c86QHsJHAAEkfDklogARQABBAAnQdMXVABPgJjjAycN1TwioV2BNeLxImjWOoBiz9Qs5butOAWRZ/t7ylz1OiPmdERF54dffl5652bJu6VKp/PAjKTj1FE/iSuegbokITn22I0K45budsZ3GS/u2BFj/mBEQ8IYAtecNd0aFgCJA/TEPINCRAALIDibvvPNOWubHcccdl5ZxGCQYBBBAEECCMVPxMugEuAkOegbxP90EkjkE/aitn8vYrQtjLi7NHyx/3eP4Ni4/cdOJsvfuvWXjxo3S3GzG2ueWiOA093ZECLd8tzO203hpjwDCHICAHwhw7+mHLOCDqQSoP1MzT9zdEUAA2UFn3LhxKZ8p6t3Cc+bMSfk4DBAcAgggZjwECs6MxNOwEuAmOKyZJa5UEVhVUi1TZxdrdX9M6UI5puzzmO2X+fvI3/Zo+w9eHrhurAwfvAsCiBZRd43siBAcQu5uDrzsjfXPS/qMbTIBas/k7BO71wSoP68zwPh+JIAAkkYBRA01d+5cP84DfPKIAAIIAohHU49hDSPATbBhCSdcxwSS2QFybOlCOTpOACnutY+8NLCtAKJ2gOye0ygrXnpZ+p5ysmP/0tWBEyGgsr5aWkTjHWIpDsaOAJJil+g+jQRY/9IIm6EgEEeA2mM6QMA7AtSfd+wZ2b8EEEB25OaJJ55IS5auuuqqtIzDIMEggACCABKMmYqXQSfATXDQM4j/6SaQzBkgY0s/laPKvoi5uLjXEHl54NjY172bauXOEduk9I0FEunZM1AHoLv1Kqh05y9+PAQQL+l7Pzbrn/c5wAMzCVB7ZuadqP1BgPrzRx7wwl8EEED8lQ+8MYwAAggCiGFTnnA9IsBNsEfgGTbQBKa/vFyKlpUljOG4LUUypnxRzG5R76Hy992PkfzGWhldtkhGVi6TrJYm6/PMggIEkIRE3TVAAHGXZ9B6Y/0LWsbwNywEqL2wZJI4gkiA+gti1vA51QQQQFJNmP4h0A0BBBAEEAoEAukgwE1wOigzRtgILF1TKQ/+eWnCsI7f8l85snxxzK44f7BUZeVLYeUyyd4hfEQ/RABJiNN1AwQQ15EGqkPWv0ClC2dDRIDaC1EyCSVwBKi/wKUMh9NAAAEkDZAZAgJdEUAAQQChOiCQDgLcBKeDMmOEjUBLS4uMn1Yk2+u7X6tO3PKJjCpfEgu/WSKS0cXZF34TQBKd8eGXczyczC0EECf0gt+W9S/4OSSCYBKg9oKZN7wOBwHqLxx5JAp3CSCAuMuT3iCQFAEEEASQpCYMxhCwSYCbYJvgaGY0AXUOyPWPF0lLgnO8T930kRRWfaXFym8CSBjO+EgEHgEkEaFwf876F+78Ep1/CVB7/s0NnoWfAPUX/hwTYfIEEECSZxZrUV9fL19//bVUVVVJbW2t5OXlSe/evWXIkCGSk5PjoGeamkIAAQQBxJS5TpzeEuAm2Fv+jB5MAhtKa2XyzJ1ne7SPInrGx+EVX3a546N9GwSQ5OdCRCLSJ6dX8g13tFBtJxZeYrs9DYNNgPUv2PnD++ASoPaCmzs8Dz4B6i/4OSQC9wkggCTJtLm5Wd5//3154403ZPny5aK+bn+pHzbDhg2TU045RY4++mhRX3NBoDMCCCAIIFQGBNJBgJvgdFBmjLARWFVSLVNnF3cIKyp8dHbGRyIGCCCJCHX8nB0cyTOjxU4CrH/MBgh4Q4Da84Y7o0JAEaD+mAcQ6EgAASSJWbFx40Z55JFHZOXKldqthg4dKtddd50MHDhQuw2G5hBAAEEAMWe2E6mXBLgJ9pI+YweVQPsdIE6EjygDBJDkZwMCSPLMaIEAwhyAgNcEuPf0OgOMbzIB6s/k7BN7VwQQQDTnxqZNm+SOO+6Q8vLyNi169Oghu+66q+Tm5sr27dultLRU6urq2tgUFBTIlClTZMCAAZqjJW/W2NgoH374oXzwwQeydu1aqaiokPz8fGvMUaNGyfHHHy99+vRJvmONFirud999Vz766CMpKSmRyspKa6w99thDxowZI2PHjrX4dHdt3rxZfvnLX2qM1rnJmWeeKWeffXanH3b1/e6K4rHHHrPtSzINEUAQQJKZL9hCwC4BboLtkqOdyQTUGSATHi+SvIZaGV22SOzs+GjPL90CSBgOOUcAMbkKncfO+uecIT1AwA4Bas8ONdpAwB0C1J87HOklXAQQQDTzeeutt8Z2fqgfJieddJL1nzrvIxKJxHppaWmR1atXy1tvvSULFiwQ9YBbXWonyD333KM5WnJm69evl0cffVRWrVrVZcO+ffvKlVdeKSNHjkyu8wTWy5Yts8ZWAkZXl5pk1157rey///5d2jgVQC655BLrlWOdXQggrqbcUWcsxI7w0RgCtglQe7bR0dBwArNmfSSFH74oec31rpBItwAShkPOEUBcmXrGdsL6Z2zqCdxjAtSexwlgeKMJUH9Gp5/guyCAAKIxNf71r3/JQw89ZFmqnQ233HKL7LfffglbKkHiN7/5jbUjQl0TJkyQ0aNHJ2yXjIHacXLbbbdJWVmZ1UyJMd/61resV26pXSBffPGFqMPa1ZWZmWnZHnzwwckM0aWtEnrUrhh1AHy0/29/+9vWjhjl16JFi2ICkDogXu2CGTx4cKf9VVdXy9y5c7X9UsJLVPDJysqS6dOnWwfQd3bFCyCnnnpqwjFUjs8666yEdm4YsAOEHSBuzCP6gEAiAtwEJyLE5xDonMCXqytkxpzPZHT5YimsWCrZLa3/sMXuZaoA4uQgcw4xtzvbaKcIsP4xDyDgDQFqzxvujAoB1j7mAAQ6J4AAojEz1A4H9Wopdd1+++1yyCGHaLRqNVECxK9//Wvr70cddZR1Hoib16RJk6S4uPWAzv79+8tNN90k++yzT2wIJb6oc0uUH+rq1auXqNc7qddjObnUK7euv/56Ua8GU5caU42tfIhealfHfffdZ+2IUZd6JdaDDz5oCTFOL7UjZ8WKFVY36hVfN9xwQ5ddxgsgf/rTn5wO7Wp7BBAEEFcnFJ1BoAsC/BLK1ICAPQJKAHnoxWVWY+sMEIdCiKkCCLs47M0/WjknwPrnnCE9QMAOAWrPDjXaQMAdAtSfOxzpJVwEEEA08nnNNddYr3hSuxfUA/1kLyUMKBFAncfh5tkSRUVFMnXqVMsdtQtC/b2zHRbqjI4bb7wxJlacfvrpct555yUbRhv7+fPny9NPP936QCA/3xI2dtlllw59qp0paufLtm3brM8uu+wyOfnkkx2NvW7dOqvP6KX4Hn744V32iQDiCLerjVmIXcVJZxDQJkDtaaPCEAJtCEx/ebkULWvdZRu9nAghCCBMMAiklwDrX3p5MxoEogSoPeYCBLwjQP15x56R/UsAAUQjNxdccIF1sPlxxx0nV111lUaLtiZPPPGEvPPOO6IOTH/uueeSbt9VA3WmyKeffmp9rM4jufzyy7vs+7333ouJL2oXyO9+9ztHOzGUAKGECHWdc845csYZZ3Q59l/+8heZM2eO9bnaKWJHRIrv/Pnnn5d58+ZZ31Kvq1Kvv+puVwkCiGtTznFHLMSOEdIBBGwRoPZsYaOR4QSih6A3t3QOIiqEHF5eLBnShVG7pggghk8qwk87Ada/tCNnQAhYBKg9JgIEvCNA/XnHnpH9SwABRCM3UQFk7NixcvXVV2u0aGuSCgFE7eq4+OKLpaGhwRpMvWZr+PDhXfqm7NRB4dHzOtTZHeq8DjvXxo0brUPNo9dTTz0l/fr167KrrVu3yhVXXBH7XL1STJ1RYudqbm62RCjVp7q+//3vyy9+8Ytuu0IAsUM6NW1YiFPDlV4hkIgAtZeIEJ9DoCOBDaW1MnnmooRoztjwlgyvaf1HIYkutwWQBz79vVTWV3c5rPqsRVOcSeS7k895BZYTerR1QoD1zwk92kLAPgFqzz47WkLAKQHqzylB2oeRAAKIRlb9+Aqszz77TO6++27Le7WzZObMmQl3dCiR5PPPP7faqB0baueGnWvBggUyY8YMq6k610OdMZLoUmeflJSUWGZqp4rasWLnio9btf/tb38rQ4YM6bYrBBA7pFPThoU4NVzpFQKJCFB7iQjxOQQ6ElhVUi1TZ7ees9bddXrJ23LgtjUxkyaJSGYXooPbAsikfz8sFfVViVz0/HMEEM9TYKwDrH/Gpp7APSZA7XmcAIY3mgDdmxrIAAAgAElEQVT1Z3T6Cb4LAgggGlNDPeD/8MMPLctf/epXcvDBB2u0ajVZvHix3HXXXdbfx4wZI+PHj9du253hK6+8Yoke6tp///1jYkh3bWbNmiUvvfSSZZLo4PDu+lHjqvHVpQ5214np4YcfjjH84Q9/KGpXjZ1L7R55//33raa6r9OKF0DuvPNOWb58uZSXl1vnpvTu3Vv23Xdfa/dMTk6OHZccteEQdA5BdzSBaAwBTQLcBGuCwgwCcQS0d4CU/FOGb1sba/lRwUGWAFJYsVSyW5raMEUAYYpBIL0EWP/Sy5vRIBAlQO0xFyDgHQHqzzv2jOxfAgggGrn517/+JQ899JBlqc6cuP322xPuOlC2a9assYQJ9bBdXddff70ceeSRGiMmNvn9738vr7/+umWoK0LEH1w+aNAg6+ByO1f82SM/+clP5Pzzz0/YTfy5HYWFhXLrrbcmbNPeoKamxjpEvb6+3vpIiShKTEl0xQsgXdnm5eXJd7/7XWtnTM+ePRN16drnCCAIIK5NJjqCQDcEuAlmekAgeQJlVfVyy4zPEjb8n5K3ZP9tO1+B9Xa/QvlXv4Ols8PSnQog7V955ZdXXEUkIn1yenXJSn02sfCShCwxgIDbBFj/3CZKfxDQI0Dt6XHCCgKpIED9pYIqfQadAAKIZgZvvvlm+frrry1rtXNAPSw/4YQTrF0I7S8lfLz99tuiBIfGxkbrY7XLYOrUqZqjJTZTgsxHH31kGZ522mly4YUXJmz073//Wx544AHLrqCgIPYaq4QN2xncdttt1i4KdemKEH//+99jB8Dr7lhp79dbb70l6rwRdalDz9Xf+/btm9B9HQEk2ol6pddNN90ke+21V8J+uzIoLS1N2FbxVzEoAeSbb75JaB8WA7UQDxgwwApn8+bNos504YIABFJPgNpLPWNGCB+BDVtqZNIfvkgY2Jkb3pRhNetjdv/cdaT8e5ed56xFhZDR25ZLZn5P2efe1leY2rn+30cP+vKVV+oVV1PGTLATEm0gkFICrH8pxUvnEOiSALXH5ICAdwSoP+/YM7J/CfTv3z/h0RHp8D7S0tLSko6B7I6hzq9QB4dXVla26SI3N1d222036xyOuro62bJli6gDyuMvtWtkypQptg/+7sxnO7swPv30U1Ht1KX8fu6552zhmDBhgqxb1/ovHdXB6qecckrCftRuFbVrRV177713TIhJ2DDOYNKkSVJc3Pou7sMOO0yUKKVzqR0qo0ePlpEjR8rQoUOtA9uViKVyqYQcdabJwoULY12povjNb36jJa50Nr6O4PLkk0/KrrvuquM+NhCAAAQgAAEIeEBg2ZoymfjIuwlHPmvDAtmvZkPM7q1dD5OPdzmoQ7v7LvyO9PqySAadeUbCPrsyuGLerbK1tnVnsZ+ufnkF8tSPW+8xuSAAAQhAAAIQgAAEIAABCECgIwHfCyDKZfXQX50HonZ46F5qh4g6ANzJjoLOxlLniixatMj66H/+539k3LhxCV1S9tHzSJQiPGfOnIRtOjNQh8Jv2rTJ+uiKK66QE088MWE/8bs31Lajxx57LGGbeAO1W0CNG9XJlAij+zqx6upq6dWr69cyqHGUf9OnT4/1r3b3XHnllUn5GDVGALGFjUYQgAAEIAABXxFYs7FSrr7vnwl9Onv9GzK0tiRm9+Zuh8t/CkZ0aPfETSfK3rv3TthfvMEtr98j5dt3/uObstoKaenigPWkOnbZGAHEZaB0BwEIQAACEIAABCAAAQiEjkAgBBBFXb3S6r333rN2DaxcubLTV/gocUHtNFCvyTrmmGOs3QZuX6btAPnzn/8s6j91KTFjxowZrnNVgtBf/vIXawyVQ/WKLfWqqmQvXoHVNTG2YiY7m7CHgDsEqD13ONKLWQRq6xrl2kf/mzDoc9a/LkNqN8bsFux2hHxS8K027SIiMufu70t1ZVlSr3/0yyuvdM74uPGwyxKywgAC6SbA+pdu4owHgVYC1B4zAQLeEaD+vGPPyP4lwCuwHORGvepq9erV1quU1N/Va6XU667Urg/191Repp0BEr/r5NRTT5WLL77Ydbwqh+qVXtFD1n/5y1/K2LFjXR8nvkMOQecMkJROMDqHwA4CHITHVIBA8gRq65pk/LSihA3PXT9f9qlt3Rmrrtd3GyVFBQd2aPf8jUfJhtdelb6nnJywz6jBpH8/7IszP9QZH5NHj9f2G0MI+IUA659fMoEfphGg9kzLOPH6iQD156ds4ItfCHAIul8ykaQf6jwNda6Guo466igZPz7xL6XqUPann37aajNo0CB58MEHkxy11dzO7pPnn39e5s2bZ7UvLCyUW2+9VXvsL7/80jp/JXqp8zmGDRum3T4Zw8mTJ8vixYutJqeffrqcd955yTRP2hYBBAEk6UlDAwjYIMBNsA1oNDGewIbSWpk8s/V1o91d562bL4O37xRA5vcfJZ/23SmAWIegly2S0TXLJSM/XwbfMyVRl7HPEUC0UWEIgU4JsP4xMSDgDQFqzxvujAoBRYD6Yx5AoCMBBJCAzopXXnlFZs6caXm///77y913350wklmzZslLL71k2Y0aNUpuuOGGhG06M1DjqvHVpSu+PPzww/Lhhx9abX74wx/KBRdcoD22ehWVOqNDXU6EG50B1RkvH3zwgWV68skny2WXpfZ1DgggCCA68xIbCDglwE2wU4K0N5HAqpJqmTq7OGHo5697Vfbe/k3M7rX+R8rCvsMlKnwUVi6T7JYm6/PMggIEkIREMYCAewRY/9xjSU8QSIYAtZcMLWwh4C4B6s9dnvQWDgIIIAHN42effRYTPXr06GGJIZmZmd1G8+tf/1o+//xzy+aMM86Qc845x1b06vwTdQaHuvbcc09R4kaiSx0EX1LSekDo5ZdfLieddFKiJtbn6nVUSoSoqamxvj7//PPlJz/5iVZbO0a//e1v5ZNPPrGa/uAHP5Cf//zndrrRboMAggCiPVkwhIADAtwEO4BHU2MJ6O4A+dm6V2VQnACyYNfDpE9jjcQLH1GIiQSQBz79vVTWV8eYq7/74dBzXoFlbBkEPnDWv8CnkAACSoDaC2jicDsUBKi/UKSRIFwmgAASB/TFF190GW/H7s4880xXxlDnVahzMBoaGqz+lLgxfPjwLvtWdup8i9raWstGvVLq29/+ti1flJChBI3oNX36dNlll1267Gvr1q1yxRVXxD5/9NFHZeDAgVpjq90YaleGuiKRiDz55JPSr18/rbZ2jK666irZsmWL1fRnP/uZ/PjHP7bTjXYbBBAEEO3JgiEEHBDgJtgBPJoaS0D3DJAL1r4ie9a13juoq0kikiktnXJLJIB49cornUPOJxZeYuxcIPDgEmD9C27u8DzYBKi9YOcP74NNgPoLdv7wPjUEEEDiuI4bNy41lON6nTt3rmtjxJ/Fkeh1Te+//74o4UFd+fn5os4QSbRjpDtHJ0yYIOvWrbNM1DkZ6ryMrq6//vWv8sILL1gfDx48WO6//35tBuq8j4ULF1r23/nOd+T222/Xbpus4RdffCFTpux8L3cqzxqJ+oYAggCS7DzFHgJ2CHATbIcabUwnoCuAXLjmZdm9vkwLl18FEHZ4aKUPowASYP0LYNJwORQEqL1QpJEgAkqA+gto4nA7pQQQQOLwBk0AKSoqkqlTp1oRZGVlyb333it77713hwlTV1cnN954o2zcuNH6zI3DvV977TV55plnrP569+4tDzzwgBQUFHQYu7y8XJRYUl3d+jqHSy+9VL773e9qTeqysjK58sorpbm59SG52nVy9NFHa7WNGqmdMrm5uQnbVFVVWeJKlJF6tZc6JF4tHKm8EEAQQFI5v+gbAlEC3AQzFyCQPIFEr8CKnvFxREWxRDS7RwDRBIUZBFwiwPrnEki6gUCSBKi9JIFhDgEXCVB/LsKkq9AQQACJS2W8AKIO2+5MTHCa+fHjxzvtok37SZMmSXFx6wGd/fv3l5tvvtnaZRG91IN99Qqp6NkfvXr1kscee8zaBdL+2rx5s/zyl7+MfVv1fdBBB3Xqb2Njo1x//fWyadMm6/N9993XEll22223mP0333wj9913n3z99dfW9/bYYw9LVNDdeTJv3jx5/vnnrbY9e/a0zh3JyclJip96Tdipp54qxxxzjHVeSWeX2mGidsSo+KPXTTfdJIcffnhSY9kxRgBBALEzb2gDgWQJcBOcLDHsISDS1SHonR1ursurMwEk/twPr878YAeIbgaxCxoB1r+gZQx/w0KA2gtLJokjiASovyBmDZ9TTQABJI5w+x0gQ4YMkeOOO856eN6nT59U58JW/6WlpXLbbbeJ2i2hLnVOxogRI0QltrKyUtRrndQOEHUp4UHZHnzwwZ2OlYwAojpQwoY6S0Ttsoj2r/pWZ3QovxYtWiTqAb+68vLyrNdLxYsziQKeOHGirF271jJTh6arw9OTvc4+++xYk1133dUav2/fvtaOGSUOLV++3PI1/lKHw6tD4tNxIYAggKRjnjEGBLgJZg5AIHkC7XeAOBE+oqN3JoB4de5HPBEEkOTnBy2CQYD1Lxh5wsvwEaD2wpdTIgoOAeovOLnC0/QRQACJY/3cc8+JOnRbvbYp/lLCwaGHHipjx461dgWoh+d+utavX2/t8ojutOjMNyXgqAO+R44c2aXryQogqqNly5ZZZ4vE755oP4CaZNdcc023h7S3b7Ny5Uq55ZZbYt9W4skBBxyQNPZ4ASRRYyWMqB0jRx55ZCJT1z5HAEEAcW0y0REEuiHATTDTAwLJEyirqpdbZnwmbggf0dERQJLPAy0g4IQA658TerSFgH0C1J59drSEgFMC1J9TgrQPIwEEkHZZVedNqNdFvfvuu/Kf//xH6uvr21ioV0eNGTPG2hkyfPhw38wJ9UoqJd6o/9SuiYqKCus1VwMGDJBRo0bJCSeckHAXix0BRAFQO0Deeecd+eijj6SkpMTaWaHOBVGvvIqy0jmHIx7mH/7wB3n11Vetbw0cODB2gHuywJU/S5cutYSa1atXW7tilH9qV4zySZ1bst9++1kHrCtf0y1uIYAggCQ7p7GHgB0C3ATboUYb0wmoHSBPTn9Xzl3/uuQ1t70ftMsmXgCJvvrKi9deRSQifXJ6xcJQf59YeIndsGgHAd8SYP3zbWpwLOQEqL2QJ5jwfE2A+vN1enDOIwIIIN2Ar62ttR7qKzEkes5GvLl6MK92hRx77LGW0MAFgWQJIIAggCQ7Z7CHgB0C3ATboUYb0wlEzwCxdoCUL5bCiqWS3dL6ak+7V7wA4uWrr3jlld0M0i5oBFj/gpYx/A0LAWovLJkkjiASoP6CmDV8TjUBBBBNwupAb7XL4b333pONGze2aaXO3TjwwAOtXSHq9UnqvAsuCOgQQABBANGZJ9hAwCkBboKdEqS9iQQ6PQPEoRCCAGLiTCJmLwmw/nlJn7FNJkDtmZx9YveaAPXndQYY348EEEBsZEW9TkmJIR9++KHU1NS06SEnJ8c6J0SJIeq1Skoc4YJAVwQQQBBAqA4IpIMAN8HpoMwYYSNQW9ck46cVdQjLyY4QrwQQXnkVttlJPLoEWP90SWEHAXcJUHvu8qQ3CCRDgPpLhha2phBAAHGQaXXuxieffCJvv/22fPbZZ6LOD4m/7rnnHhk6dKiDEWgadgIIIAggYZ/jxOcPAtwE+yMPeBEsAl0JINEookLIEeVLRPefuygB5M9n7yPq3I90nv3BK6+CNffw1j0CrH/usaQnCCRDgNpLhha2EHCXAPXnLk96CwcBBBCX8qgO137++eetnSHRCwHEJbgh7gYBBAEkxNOb0HxEgJtgHyUDVwJDoP0rsLpy/JqVcyW/uU4rLiWAPH36rlJRX6Vl75YRAohbJOknaARY/4KWMfwNCwFqLyyZJI4gEqD+gpg1fE41AQQQh4QrKiqsc0HUQemrV69u0xsCiEO4BjRHAEEAMWCaE6IPCHAT7IMk4ELgCEQPQU/k+LUr50rPOAGkMZIhWS2dr2/pEkB45VWirPG5KQRY/0zJNHH6jQC157eM4I9JBKg/k7JNrLoEEEB0ScXZNTQ0yH/+8x9rt8fnn3/e4dVXu+yyixxzzDFyxhlnSM+ePW2MQBNTCCCAIICYMteJ01sC3AR7y5/Rg0lAdwfIdSvnSF5zfSzIFwceL4O3b5bCiqWS3dLUJvh0CSDs+AjmnMNr9wmw/rnPlB4hoEOA2tOhhA0EUkOA+ksNV3oNNgEEkCTyV1xcbIke//73vzs9/PyII46wDj8/+OCDRf3A4YJAIgIIIAggieYIn0PADQLcBLtBkT5MI6DOAJnweJE0t3Qf+fiVL0huc0PM6I97fU/W5w2Qzg5LRwAxbRYRr9cEWP+8zgDjm0qA2jM188TtBwLUnx+ygA9+I4AAkiAjGzdutF5vpV5ztXnz5g7WI0aMkLFjx8qYMWMkNzfXb/nFH58TQABBAPH5FMW9kBDgJjgkiSSMtBOY/vJyKVpW1u24E1bMlpyWxpjNs4NOk5Lc/rGvo0LIyKpiqeuRIU+fvpu0SAJVxWGk7ABxCJDmoSHA+heaVBJIwAhQewFLGO6GigD1F6p0EoxLBBBAOgFZU1MjH3zwgSV8LFu2rIPFHnvsYYke6r/ddtvNpVTQjYkEEEAQQEyc98ScfgLcBKefOSOGg8DnK8rk8b8t7zaYiStmtXnV1cxB35eNuR3vD/sduEAOWlshnxyUn3I4CCApR8wAASHA+heQROFm6AhQe6FLKQEFiAD1F6Bk4WraCCCAxKH+73//a73iSv3Z2LjzX/Ipk169elm7PJToMXz48LQliIHCTQABBAEk3DOc6PxCgJtgv2QCP4JGYP2WGrnr2cXdun3j8uclU3auZ3/Y+weyqceuHdrkHvpPieTUpQxB/MHnfXJ6ycTCS1I2Fh1DICgEWP+Ckin8DBsBai9sGSWeIBGg/oKULXxNFwEEkDjS48aNa8M9MzNTDj30UOtcj8MOO0yysrLSlRfGMYQAAggCiCFTnTA9JsBNsMcJYPjAElhVUi1TZxd36/9Ny/8oGXGvtHp67x/JNz126dAm1TtA2PUR2GmG4ykkwPqXQrh0DYFuCFB7TA8IeEeA+vOOPSP7lwACSBcCyKBBg+Too4+WPn36uJq9k08+2dX+6CzYBBBAEECCPYPxPigEuAkOSqbw028ENpTWyuSZi7p2q6VFblnxxzaf/37vH8uWHgWx71lngJQtkpFVX0ptj4g889PUvD4VAcRvswd//ECA9c8PWcAHEwlQeyZmnZj9QoD680sm8MNPBBBAuhBAUpWkuXPnpqpr+g0gAQQQBJAATltcDiABboIDmDRc9gWB2romGT+tqEtfIi3NcvOK59t8PmPwT2RrTl+JCh+FlctiZ4RU5WUggPgiszhhCgHWP1MyTZx+I0Dt+S0j+GMSAerPpGwTqy4BBBAEEN25gl0KCCCAIICkYFrRJQQ6EOAmmEkBAXsEEgkgGS1NctOKWW06f26v78mB1aslXviIGqRCAIme/cG5H/ZyTKtwE2D9C3d+ic6/BKg9/+YGz8JPgPoLf46JMHkCCCBxzO68806JRCLJU0yixaRJk5KwxjTsBBBAEEDCPseJzx8EuAn2Rx7wIngEEr0CK6u5UW5YObtNYI2RDMlq6Xx9S4UAwquvgjev8Dh9BFj/0seakSAQT4DaYz5AwDsC1J937BnZvwQQQPybGzwzgAACCAKIAdOcEH1AgJtgHyQBFwJJINEh6NnNDTJx5QvasSGAaKPCEAKuEGD9cwUjnUAgaQLUXtLIaAAB1whQf66hpKMQEUAACVEyCSV4BBBAEECCN2vxOIgEuAkOYtbw2Q8EutsBos74OGrr53JY5VJtV90UQHj1lTZ2DA0mwPpncPIJ3VMC1J6n+BnccALUn+ETgPA7JYAAwsSAgIcEEEAQQDycfgxtEAFugg1KNqG6SqCzM0A6O9xcd1A3BRBefaVLHTuTCbD+mZx9YveSALXnJX3GNp0A9Wf6DCD+zggggDAvIOAhAQQQBBAPpx9DG0SAm2CDkk2orhKIF0CcCB9RpxBAXE0PnUEgIQHWv4SIMIBASghQeynBSqcQ0CJA/WlhwsgwAggghiWccP1FAAEEAcRfMxJvwkqAm+CwZpa4Uk1AvQLr/t//R0aXLZLCymWS3dLkaEgEEEf4aAyBpAmw/iWNjAYQcIUAtecKRjqBgC0C1J8tbDQKOQEEkJAnmPD8TQABBAHE3zMU78JCgJvgsGSSONJNYNWnX0nt75+SvOZ6V4Z2QwDh7A9XUkEnhhBg/TMk0YTpOwLUnu9SgkMGEaD+DEo2oWoTQADRRoUhBNwngACCAOL+rKJHCHQkwE0wswIC9gjEdoCUL5bCiqW+2AHC2R/2ckkrMwmw/pmZd6L2ngC1530O8MBcAtSfubkn8q4JIIAwOyDgIQEEEAQQD6cfQxtEgJtgg5JNqK4SUGeAXD+tSFpExDoDxKEQ4sYOEAQQV1NMZyEnwPoX8gQTnm8JUHu+TQ2OGUCA+jMgyYSYNAEEkKSR0QAC7hFAAEEAcW820RMEuibATTCzAwL2Cdw8faGUVzfEOnAihCCA2M8DLSFghwDrnx1qtIGAcwLUnnOG9AABuwSoP7vkaBdmAgggYc4usfmeAAIIAojvJykOhoIAN8GhSCNBeEDA2gHyeJG0qC0g7S4lhBxXWiSHVK3Q9gwBRBsVhhBwhQDrnysY6QQCSROg9pJGRgMIuEaA+nMNJR2FiAACSIiSSSjBI4AAggASvFmLx0EkwE1wELOGz34goM4AmTxzUZeu7FpfLpeumaftqhMBhMPPtTFjCIEYAdY/JgMEvCFA7XnDnVEhoAhQf8wDCHQkgADCrICAhwQQQBBAPJx+DG0QAW6CDUo2obpKYFVJtUydXdxln/3ryuTitS/HPlcbRRojmV0elu5EAOHsD1dTS2eGEGD9MyTRhOk7AtSe71KCQwYRoP4MSjahahNAANFGhSEE3CeAAIIA4v6sokcIdCTATTCzAgL2CCTaATKgbqtctPbvsc6bJCJPDDmz9bD0qmLJbmr77iwEEHt5oBUE7BJg/bNLjnYQcEaA2nPGj9YQcEKA+nNCj7ZhJYAAEtbMElcgCCCAIIAEYqLiZOAJcBMc+BQSgEcErDNAphVJJ0eAWB7tvr1ULlz3j5h3jZEMuX+/n1lf9ztwgRy+vEwO/qpWsptaTRBAPEokwxpLgPXP2NQTuMcEqD2PE8DwRhOg/oxOP8F3QQABhKkBAQ8JIIAggHg4/RjaIALcBBuUbEJ1ncDN0xdKeXVDp/3usX2L/HzdK7HP6iNZ8uB+51lf5x76T4nk1EnP2iY5rLjGEkK252TIMz/dzZaPvALLFjYaGU6A9c/wCUD4nhGg9jxDz8AQ4AwQ5gAEOiGAAMK0gICHBBBAEEA8nH4MbRABfgk1KNmE6ioBawfI40XS0sUWkD1rv5EL1r8aG7Muki0P7XduGwEk+qESQkas3C6fHJRvy0cEEFvYaGQ4AdY/wycA4XtGgNrzDD0DQwABhDkAAQQQ5gAE/EUAAQQBxF8zEm/CSoBfQsOaWeJKNYFEZ4AMqt0kP1s/P+bG9owceXjoOZ0KIE59RQBxSpD2JhJg/TMx68TsBwLUnh+ygA+mEqD+TM08cXdHgB0gzA8IeEgAAQQBxMPpx9AGEeAm2KBkE6qrBFaVVMvU2cVd9rl37UY5f/3rsc9rMnrIo0PHSY+DPpRIz0qJRHY2dbIDJCIRGdRroEwsvMTV+OgMAmEnwPoX9gwTn18JUHt+zQx+mUCA+jMhy8SYLAEEkGSJYQ8BFwkggCCAuDid6AoCXRLgJpjJAQF7BBLtANmnpkTO3fBGrPNtmbny2L5nx87/UB9YZ4AsqZFDltdKrc0zQNj9YS9/tIIA6x9zAALeEKD2vOHOqBBQBKg/5gEEOhJAAGFWQMBDAgggCCAeTj+GNogAN8EGJZtQXSVgnQEyrUi6OAJEhtRskHM2LIiNWZWZJ4/ve5YlgOQ31cSEj6ymVpOqPHuHoCOAuJpWOjOIAOufQckmVF8RoPZ8lQ6cMYwA9WdYwglXiwACiBYmjCCQGgIIIAggqZlZ9AqBtgS4CWZGQMA+gZunL5Ty6oZOO9h323oZV/Jm7LPKrJ7y7KAfyNHZr8ohK6slKnxEDRBA7OeBlhCwQ4D1zw412kDAOQFqzzlDeoCAXQLUn11ytAszAQSQMGeX2HxPAAEEAcT3kxQHQ0GAm+BQpJEgPCBg7QB5vEhautgCst+2dXJWyVsxz+oiWZIhLZLdsmPLRzufEUA8SCJDGk2A9c/o9BO8hwSoPQ/hM7TxBKg/46cAADohgADCtICAhwQQQBBAPJx+DG0QAW6CDUo2obpKINEZIMO2rZUzS/6pPaYdAYQD0LXxYgiBDgRY/5gUEPCGALXnDXdGhYAiQP0xDyDQkQACCLMCAh4SQABBAPFw+jG0QQS4CTYo2YTqKoFVJdUydXZxp33mN9bK9zZ/JPvXrNMe044Awvkf2ngxhAACCHMAAj4hwL2nTxKBG0YSoP6MTDtBJyCAAMIUgYCHBBBAEEA8nH4MbRABboINSjahukqgsx0gSvgYXbZICiuXdfmqq66cQABxNT10BoGEBFj/EiLCAAIpIUDtpQQrnUJAiwD1p4UJI8MIIIAYlnDC9RcBBBAEEH/NSLwJKwFugsOaWeJKNQHrDJBpRaKOAHEifET9RABJdcboHwJtCbD+MSMg4A0Bas8b7owKAUWA+mMeQKAjAQQQZgUEPCSAAIIA4uH0Y2iDCHATbFCyCdV1AndO+1C+tW6hrR0f7Z1BAHE9PXQIgW4JsP4xQSDgDQFqzxvujAoBBBDmAAQ6J4AAwsyAgIcEEEAQQDycfgxtEAF+CTUo2YTqKoHKlWtk3QOPSF5zvSv9IoC4gpFOIIYO5nAAACAASURBVKBNgPVPGxWGEHCVALXnKk46g0BSBKi/pHBhbAgBBBBDEk2Y/iSAAIIA4s+ZiVdhI8BNcNgySjzpIqDOALn/9/+R0eWLpbBiadJnfrT3M1kBJCIRGdRroEwsvCRdITMOBEJFgPUvVOkkmAARoPYClCxcDR0B6i90KSUgFwgggLgAkS4gYJcAAggCiN25QzsIJEOAm+BkaGELgZ0EVpVUy9TZxdY3rDNAHAohyQogfXN6y+TR40kJBCBgkwDrn01wNIOAQwLUnkOANIeAAwLUnwN4NA0tAQSQ0KaWwIJAAAEEASQI8xQfg0+Am+Dg55AIvCGgdoBMnrmozeBOhBAEEG/yyKjmEmD9Mzf3RO4tAWrPW/6MbjYB6s/s/BN95wQQQJgZEPCQAAIIAoiH04+hDSLATbBBySZUVwnU1jXJhMeLpLmlY7dKCPnRpvdkSO1G7TERQLRRYQgBVwiw/rmCkU4gkDQBai9pZDSAgGsEqD/XUNJRiAgggIQomYQSPAIIIAggwZu1eBxEAtwEBzFr+OwXAtNfXi5Fy8o6dWdk+ZdyypaPtV1FANFGhSEEXCHA+ucKRjqBQNIEqL2kkdEAAq4RoP5cQ0lHISKAABKiZBJK8AgggCCABG/W4nEQCXATHMSs4bNfCCxdUykP/nlpp+4cXl4sJ2/5T+yzyrxMyatvkuymzr1HAPFLVvHDFAKsf6Zkmjj9RoDa81tG8MckAtSfSdkmVl0CCCC6pLCDQAoIIIAggKRgWtElBDoQ4CaYSQEB+wRaWlrkrmcXizoPpP11RNkSOan0k9i3V++eK68flS+HFdfIwV/VdhBCEEDs54GWELBDgPXPDjXaQMA5AWrPOUN6gIBdAtSfXXK0CzMBBJAwZ5fYfE8AAQQBxPeTFAdDQYCb4FCkkSA8JLBm0zb57ZxiaWhsexjIqLJFcmJpUcyzVQNzZd6Jfayve9Y2dRBCkhFAIhKRQb0GysTCSzyMnKEhEGwCrH/Bzh/eB5cAtRfc3OF58AlQf8HPIRG4TwABxH2m9AgBbQIIIAgg2pMFQwg4IMBNsAN4NIWAiKhdILf//nMpraxvw+PIsi/k+NJPY99buUeuvHxCqwASveKFkO05GfLMT3fTYto3p7dMHj1eyxYjCECgcwKsf8wMCHhDgNrzhjujQkARoP6YBxDoSAABhFkBAQ8JIIAggHg4/RjaIALcBBuUbEJNCYGuzgEZs/VzOW7rwtiYK/bMk78f37tTH5QQMmLldvnkoHwtHxFAtDBhBIFuCbD+MUEg4A0Bas8b7owKAQQQ5gAEOieAAMLMgICHBBBAEEA8nH4MbRABfgk1KNmEmhIC019eLkXLyjr0ffTWz+TYrZ/Fvv/VXnnyynEIIClJAp1CwAYB1j8b0GgCARcIUHsuQKQLCNgkQP3ZBEezUBNAAAl1egnO7wQQQBBA/D5H8S8cBLgJDkceicIbArV1TTLh8SJpbnv8h+XMMaUL5Ziyz2OOLdu7h7x6bN82jlqvwFpSI4csr5VaXoHlTRIZ1VgCrH/Gpp7APSZA7XmcAIY3mgD1Z3T6Cb4LAgggTA0IeEgAAQQBxMPpx9AGEeAm2KBkE6rrBDaU1srkmYs67ffY0k/l6LIvYp8tHdxDXjumVQCJFz6ymlpNkjkEnVdguZ5KOjSQAOufgUknZF8QoPZ8kQacMJQA9Wdo4gm7WwIIIEwQCHhIAAEEAcTD6cfQBhHgJtigZBOq6wRWlVTL1NnFnfZ73JYiGVO+Uxwp3qeHvD+yV2zHR1T4iDZGAHE9PXQIgW4JsP4xQSDgDQFqzxvujAoBRYD6Yx5AoCMBBBBmBQQ8JIAAggDi4fRjaIMIcBNsULL/P3tnAp5Vde39FQYhgqAyfKJiixWtimJoC2rFOre911qHil5q7e11olYr4lBFUXEqrYqRPLaglVKrFVurFa0TVGVuqxdRgxSkF4dAAhpCAiGEhLzfsw++MfBOZ9jn3eec/TvP0+f7SvZee63fWqv7JP+7zyZU7QTynQA54dP/laM3Lmtfs7ZXZ+nduF12FT4QQLSnBYMQcEWA/c8VJgZBQDsBek87UgxCwDUB+s81KgZaRAABxKJkE2r0CCCAIIBEryrxKIkEeAlOYlaJqVgE8t0BctKnb8rwje+5doUTIK5RMRACWgiw/2nBiBEIeCZA73lGxgQIaCNA/2lDiaEEEUAASVAyCSV+BBBAEEDiV7V4HEcCvATHMWv4HCUC055bJUtW1u3kUo/WJjl37d9kn20bXLuKAOIaFQMhoIUA+58WjBiBgGcC9J5nZEyAgDYC9J82lBhKEAEEkAQlk1DiRwABBAEkflWLx3EkwEtwHLOGz1EisOKjBpn8pxWOS0r4GFFXKWUNK6Vr6rPbzV0660UAGdhzgFxTdrFLywyDAASyEWD/oy4gYIYAvWeGO6tCQBGg/6gDCGQSQAChKiBgkAACCAKIwfJjaYsI8BJsUbIJNRQCqVRKfvnwG/LF/3vTl/CRdsqtAFIiJXL/yJtDiQWjELCJAPufTdkm1igRoPeilA18sY0A/WdbxonXDQEEEDeUGAOBkAgggCCAhFRamIXATgR4CaYgIOCfQGt9g9TPniMNc+eLtLb6NyQiCCCB8DEZAp4JsP95RsYECGghQO9pwYgRCPgiQP/5wsakhBNAAEl4ggkv2gQQQBBAol2heJcUArwEJyWTxFFsAs1VVVJTXiFtjVu0LI0AogUjRiDgmgD7n2tUDISAVgL0nlacGIOAJwL0nydcDLaEAAKIJYkmzGgSQABBAIlmZeJV0gjwEpy0jBJPMQmkT4BseG2+dGnjBEgx2bMWBIISYP8LSpD5EPBHgN7zx41ZENBBgP7TQREbSSOAAJK0jBJPrAgggCCAxKpgcTa2BHgJjm3qcDwiBNQl6NOeWCojNi6TsvoVni8/T4fh9gRI55JOct9xN0UketyAQHwJsP/FN3d4Hm8C9F6884f38SZA/8U7f3gfDgEEkHC4YhUCrggggCCAuCoUBkEgIAFeggMCZLr1BKY9t0qWrKxzOPRobfIthLgVQHrvtodMHDHWeu4AgEBQAux/QQkyHwL+CNB7/rgxCwI6CNB/OihiI2kEEECSllHiiRUBBBAEkFgVLM7GlgAvwbFNHY5HgEBT83YZ9+ASaUvt7IwSQkaveVn6tDS49hIBxDUqBkJACwH2Py0YMQIBzwToPc/ImAABbQToP20oMZQgAgggCUomocSPAAIIAkj8qhaP40iAl+A4Zg2fo0JgbW2TTJxRmdWdM6vnypcbP3TtKgKIa1QMhIAWAux/WjBiBAKeCdB7npExAQLaCNB/2lBiKEEEEEASlExCiR8BBBAEkPhVLR7HkQAvwXHMGj5HhcDq6s0y6Q/Ls7pzVvXrckjjR+0/W9u3i/Sra5Wu27N7jwASlazihy0E2P9syTRxRo0AvRe1jOCPTQToP5uyTaxuCSCAuCXFOAiEQAABBAEkhLLCJAQyCPASTFFAwD+BfCdAzql+VQY3VrUbX3RkD1n2pe7yleVb5Ij3mzKEEAQQ/3lgJgT8EGD/80ONORAIToDeC84QCxDwS4D+80uOeUkmgACS5OwSW+QJIIAggES+SHEwEQR4CU5EGgnCEIFcd4Aod7639m9y0JY17Z4tHNpD3jy8h/Pfd2/aniGEIIAYSiLLWkuA/c/a1BO4YQL0nuEEsLzVBOg/q9NP8DkIIIBQGhAwSAABBAHEYPmxtEUEeAm2KNmEGgqBac+tkiUr6zJsn7t2jnxpy9r2f59/VA9ZctgOAST9dBRCtu7WSaaf1begjwN7DpBryi4uOI4BEIBAfgLsf1QIBMwQoPfMcGdVCCgC9B91AIFMAgggVAUEDBJAAEEAMVh+LG0RAV6CLUo2oYZCYMVHDTL5TysybJ+3ZrYMaqpu//d5ZT3lrUN3zxinRJChK7ZIS9dO7SdEcjlaIiVy/8ibQ4kDoxCwjQD7n20ZJ96oEKD3opIJ/LCRAP1nY9aJuRABBJBChPg5BEIkgACCABJieWEaAu0EeAmmGCAQjEAqlZLbf7dM1H0gHZ/z17wiX2yqaf+nucN6ytIvfy6AOKc/3tsiR65qkiaXpz+UsfKRE4I5zGwIQMAhwP5HIUDADAF6zwx3VoUAex81AIHsBBBAqAwIGCSAAIIAYrD8WNoiAvwSalGyCTU0Ah+ta5RfPrFcWran2tcYXfWyHLB1Xft/f+0rPeWdQ3bfcf/HZ8JHl+07fuz2/g8EkNBSiGELCbD/WZh0Qo4EAXovEmnACUsJ0H+WJp6w8xJAAKFAIGCQAAIIAojB8mNpiwjwEmxRsgk1NALZBJDvV70kA7eub19zwVFK/Eg5Jz7Swkf6hwggoaUGwxDISYD9j+KAgBkC9J4Z7qwKAUWA/qMOIJBJAAGEqoCAQQIIIAggBsuPpS0iwEuwRckm1FAI5PoE1gVVL8r+Wz9pX3N7iUjnzw+I7OQLAkgoqcEoBPISYP+jQCBghgC9Z4Y7q0IAAYQagEB2AgggVAYEDBJAAEEAMVh+LG0RAX4JtSjZhBoKgVyXoP/3R8/LPts2uFoTAcQVJgZBQCsB9j+tODEGAdcE6D3XqBgIAe0E6D/tSDGYAAIIIAlIIiHElwACCAJIfKsXz+NEgJfgOGULX6NIYNpzq2TJyrp213q0NsmIukr5Wv1yKXHpMAKIS1AMg4BGAux/GmFiCgIeCNB7HmAxFAKaCdB/moFiLhEEEEASkUaCiCsBBBAEkLjWLn7HiwAvwfHKF95Gi0BT83YZ9+ASaUuJpIWPsoaV0jX12e3mLt11K4CUSIncP/Jml1YZBgEI5CPA/kd9QMAMAXrPDHdWhYAiQP9RBxDIJIAAQlVAwCABBBAEEIPlx9IWEeAl2KJkE6p2Amtrm+Te37zhnPjwI3ykHUIA0Z4aDEKgIAH2v4KIGACBUAjQe6FgxSgEXBGg/1xhYpBlBBBALEs44UaLAAIIAki0KhJvkkqAl+CkZpa4wibQWt8gHz/zgrT88++eT3zs6hsCSNjZwj4EMgmw/1EVEDBDgN4zw51VIaAI0H/UAQQyCSCAUBUQMEgAAQQBxGD5sbRFBHgJtijZhKqNQHNVldSUV0hb4xYtNpu7lsjUc/sVtMUnsAoiYgAEXBNg/3ONioEQ0EqA3tOKE2MQ8ESA/vOEi8GWEEAAsSTRhBlNAgggCCDRrEy8ShoBXoKTllHiKRYBdQKk9qXZUj93fuATIGrHqxjdv6DrCCAFETEAAq4JsP+5RsVACGglQO9pxYkxCHgiQP95wsVgSwgggFiSaMKMJgEEEASQaFYmXiWNAC/BScso8RSbwG+felt2/99FUla/wrcQggBS7KyxHgT4DAg1AAFTBHj3NEWedSHA3kcNQCAbAQQQ6gICBgkggCCAGCw/lraIAL+EWpRsQg2FwIqPGmTyn1ZIj9YmGbFxmS8hBAEklNRgFAJ5CbD/USAQMEOA3jPDnVUhoAjQf9QBBDIJIIBQFRAwSAABBAHEYPmxtEUEeAm2KNmEGgqBVColt/9umaytbXLsp4WQr218T0pcrogA4hIUwyCgkQD7n0aYmIKABwL0ngdYDIWAZgL0n2agmEsEAQSQRKSRIOJKAAEEASSutYvf8SLAS3C88oW30STw0bpGuffJf0lzy+d715X/flJ6pJpdOexWAOlc0knuO+4mVzYZBAEI5CfA/keFQMAMAXrPDHdWhYAiQP9RBxDIJIAAQlVAwCABBBAEEIPlx9IWEeAl2KJkE2qoBF78x1r5y4I1O06A1FXK1+qXaz8B0nu3PWTiiLGhxoFxCNhCgP3PlkwTZ9QI0HtRywj+2ESA/rMp28TqlgACiFtSjINACAQQQBBAQigrTEIggwAvwRQFBIITUCdAfvX4Eilb/66UNaz0fBm62xMgCCDBc4UFCKQJsP9RCxAwQ4DeM8OdVSGgCNB/1AEEMgkggFAVEDBIAAEEAcRg+bG0RQR4CbYo2YQaCoGWjfXyygNPyuB173kWPtIOIYCEkhqMQiAvAfY/CgQCZgjQe2a4syoEEECoAQhkJ4AAQmVAwCABBBAEEIPlx9IWEeCXUIuSTahaCbTWN0j97DlSP3e+lLS2BrLtVgAZ2HOAXFN2caC1mAwBCOwgwP5HJUDADAF6zwx3VoUAex81AAEEEGoAApEjgACCABK5osShRBLgl9BEppWgQibQXFUlNeUV0ta4RctKrZ1EHjy/f0Fb5SMnFBzDAAhAwB0B9j93nBgFAd0E6D3dRLEHAfcE6D/3rBhpDwFOgNiTayKNIAEEEASQCJYlLiWQAC/BCUwqIRWFgDoBUvvSbOcESNfU9kBruj0BggASCDOTIbATAfY/CgICZgjQe2a4syoEFAH6jzqAQCYBBBCqAgIGCSCAIIAYLD+WtogAL8EWJZtQtRNYW9sk9/7mDRmxcZmU1a/wLYQggGhPDQYhUJAA+19BRAyAQCgE6L1QsGIUAq4I0H+uMDHIMgIIIJYlnHCjRQABBAEkWhWJN0klwEtwUjNLXMUgsLp6s0z6w3JnqR6tTb6FEASQYmSLNSCwMwH2PyoCAmYI0HtmuLMqBBQB+o86gEAmAQQQqgICBgkggCCAGCw/lraIAC/BFiWbULUTUCdAJs6o3MmuI4TUVcrw+h3CiJsHAcQNJcZAQC8B9j+9PLEGAbcE6D23pBgHAf0E6D/9TLEYfwIIIPHPIRHEmAACCAJIjMsX12NEgJfgGCULVyNHoKl5u4x7cIm0pXZ2rSTVJj/792Ou/UUAcY2KgRDQRoD9TxtKDEHAEwF6zxMuBkNAKwH6TytOjCWEAAJIQhJJGPEkgACCABLPysXruBHgJThuGcPfqBGY9twqWbKyrt0tdQLkmLp35av1/3LtKgKIa1QMhIA2Aux/2lBiCAKeCNB7nnAxGAJaCdB/WnFiLCEEEEASkkjCiCcBBBAEkHhWLl7HjQAvwXHLGP5GjcCKjxpk8p9W7LgDpK5SyhpWer4MHQEkalnFHxsIsP/ZkGVijCIBei+KWcEnWwjQf7Zkmji9EEAA8UKLsRDQTAABBAFEc0lhDgJZCfASTGFAIBiBlo318soDT8rgde95Fj7SKyOABMsBsyHghwD7nx9qzIFAcAL0XnCGWICAXwL0n19yzEsyAQSQhGS3tbVVFi1aJAsXLpSPP/5Y6uvrpUePHtK/f38ZPny4nHDCCdKrV69Qot26davMmzdPFi9eLNXV1dLQ0OCsNWDAADnmmGPk+OOPl+7duxdce9myZTJx4sSC4zoOOOmkk2TMmDGu57z77rsyd+5cef/992XDhg3SpUsX6dOnjwwdOlSUrf3228+1LR0DEUAQQHTUETYgUIgAL8GFCPFzCGQn0FrfIPWz58imeQsk1dISCBMCSCB8TIaALwLsf76wMQkCgQnQe4ERYgACvgnQf77RMTHBBBBAEpDcNWvWyJQpU2T16tU5o+ndu7f8+Mc/lmHDhmmNeOXKlc7a69evz2lXFdlPf/pTGTx4cN61wxRAtmzZIg899JAjEuV6OnfuLKNGjZKzzjpLK6N8xhBAEECKVmwsZDUBXoKtTj/B+yTQXFUlNeUV0ta4xaeFnae1dhJ58Pz+BW2Vj5xQcAwDIAABdwTY/9xxYhQEdBOg93QTxR4E3BOg/9yzYqQ9BBBAYp7r2tpaGT9+vNTV7biYs6SkRA499FDZZ599nFMg6sTDtm3bnJ+pP/CrsUcccYSWqD/88EO55ZZbpKmpqd3+kCFDnBMVyq/KykpRf+BXT2lpqdxxxx1ywAEH5Fy7owCy1157OSdXCj2HHHKIHHfccXmHqdMxP//5zx0W6WfgwIFy4IEHOmyWL18uGzdubP+ZEkG+973vFVpay88RQBBAtBQSRiBQgAAvwZQIBPwRKPYJkBIpkftH3uzPWWZBAAIZBNj/KAoImCFA75nhzqoQUAToP+oAApkEEEBiXhW33nqr8wd89fTr10+uv/56+cIXvtAelfoc1QMPPND+x/+ePXtKRUWF83msII8SFa6++mpZt26dY0atqdZWPqQfdSrknnvuESWUqEd9Emvy5MmOEJPt6SiAHHbYYXLbbbcFcbF97pNPPil//vOfnf/etWtXufzyy+XrX/96+89VLDNnzpRZs2a1/5taW/kQ9oMAggASdo1hHwK8BFMDEAhOQAkhVc++KNv+vjjUO0AQQILnCgsQ6EiAPwJRDxAwQ4DeM8OdVSHA737UAASyE0AAiXFlLFmyRCZNmuREoO6yUP//bCcs1B0d1113XbtYceaZZ8ro0aMDRf7yyy/LI4884thQYooSNtSpjV0fdTJl3Lhx0tjY6Pzo0ksvlVNOOSXr2mEIIOoUzBVXXCHNzc3OmpdccomceuqpWdcvLy9v/0TWwQcfLHfeeWcgRm4mI4AggLipE8ZAICgBfgkNSpD5thNIpVJy+++WSf26DTJi4zIpq1/hWQhxcwcIAojtlUb8ugmw/+kmij0IuCNA77njxCgIhEGA/guDKjbjTgABJMYZVJ91euutt5wITj75ZLnssstyRjN//nzn5Id61CmQhx9+OOdJDDdIlKhRVVXlDD3//PPl7LPPzjnt6aefdk5YqEedFFGnQrI9YQgg6lTHY4895iynTqAokUN9Jizb8+mnn8pPfvITUX/kUM8vfvELGTRokBscvscggCCA+C4eJkLAAwFegj3AYigEshBY8VGDTP7Tivaf9GhtkpG1b8lRm1a55oUA4hoVAyGgjQD7nzaUGIKAJwL0nidcDIaAVgL0n1acGEsIAQSQmCZSneq46KKLpKWlxYlAnVZQpxZyPWrcxRdf3H5fh7q7Q93X4eepqalxLjVPP1OnTpW99947p6kNGzbImDFj2n+uLk1Xd5Ts+oQhgEyYMEFWrNjxB4v/+q//KnjBueL4zjvvOOPPOeccOe+88/wgcj0HAQQBxHWxMBACAQjwEhwAHlMhICLTnlslS1buuG8t/fRu2SQ//vAZ13zcCCCdSzrJfcfd5NomAyEAgfwE2P+oEAiYIUDvmeHOqhBQBOg/6gACmQQQQGJaFW+//bbcddddjvfdunWTGTNmFDzR0fGP++rEhjq54eeZM2eOPPTQQ85UdapC3TFS6LnqqqukurraGaZOqqgTK7s+ugUQdcH5D37wg/YTHYVEIuVPx9Mq6oJ1dXF7mA8CCAJImPWFbQikCfASTC1AwD+BpubtMu7BJdK244Co86gTIN+oXSJHbvq3a8NuBJDeu+0hE0eMdW2TgRCAQH4C7H9UCATMEKD3zHBnVQgoAvQfdQCBTAIIIDGtihdeeMERPdQzePDgdjEkXziPP/64PPvss86Q4cOHy7XXXusrerWuWl89xx57rIwdW/gX9Y73a5x++uly4YUXZqzdUQA56KCDnM9qffDBB879Id27d5c999zTOeWiPqOl/ge90KPmqovZ1aM+e/X73/9edtttt7zTli5dKnfffbczRn0qbPr06YWWCfRzBBAEkEAFxGQIuCTAS7BLUAyDQBYCa2ubZOKMSucnSvgYUVcpZQ0rQ7kDBAGEEoSAXgLsf3p5Yg0CbgnQe25JMQ4C+gnQf/qZYjH+BBBAYprD3/zmN/LKK6843rsVITpeXL7//vs7F5f7eTrePfLd735Xvv/97xc0o+7hUPdxqKesrExuvPHGjDkdBZB8Bvv37y9nnHGGc5l5rvs81PxFixY5d36op3fv3s69J4Ueda+Jut8k/SjOvXr1KjTN988RQBBAfBcPEyHggQAvwR5gMRQCuxBYXb1ZKh5d4lv4SJvjBAilBYHiE2D/Kz5zVoSAIkDvUQcQMEeA/jPHnpWjSwABJLq5yevZ/fffL4sXL3bGfPvb35Yf/ehHBSP5xz/+Iffdd58zTp2mSH/GquDEXQaMHz9eVq3acemnOsmhTnQUep5//nl59NFHnWG5Tqy4FUDSaykh5eqrr3ZOh2R7lECkBAz15Lt8vePczZs3y//8z/+0/5MSUPbdd99C4e3089ra2oLjFf/OnTuLEkA++eSTguOTMkBtxErAUs/69eulrQ0BJCm5JY5oE6D3op0fvIsugdb6eql69kXZumiR5xMfu0alvqA1ZfSOPTDXo06A3HHM5/+HGNElg2cQiAcB9r945Akvk0eA3kteTokoPgTov/jkCk+LR6Bfv34Fr44ohjclqVSqw5eVi7FkvNfwcwrjrbfeEjVPPUo0SAsSXkmoExLqpIR61MXqp512WkETHcWIgQMHtgsxHScqAUQJDl//+tflyCOPlAMOOKD99IW6SL2ystL59FZ6bTV32LBhzmeusn0SS504USdP1OP2M2Hq3pALLrig3a1JkybJgQceWDC+jgNGjRpVcPyvf/1r6dOnT8FxDIAABCAAAQhAwAyBxtUfSOWEW6V102YtDrg5AbJ36Z4y9Ywd72o8EIAABCAAAQhAAAIQgAAEIJAcAgggHnN5++23O4KAes455xw577zzClpQ49U89SjBYObMmQXnZBtw5ZVXyrp165wfjRkzRk466aSCdl599VWZOnWqM04dO6qoqMiYs3XrVunSpYvzn1xPa2urPPLII/K3v/2tfcgVV1whxx9/fMaUp556Sv74xz86/37ooYfKxIkTC/qpTiR0vBxe8fryl79ccF7HAQggnnAxGAIQgAAEIBBZAtvq6mTNM8/Kx8+/KJ23twby040AcuBeB8ik0zI/ExpoYSZDAAIQgAAEIAABCEAAAhCAgHECCCAeU5DEEyBuESiRQgkT7733njMl14kSUydA+ARW7kxyFNNtlTMOAnoJ0Ht6eWLNPgL/eq9K3vrds1JWv8L3p7DcCCBTvnGrfXCJGAIhEmD/CxEupiGQhwC9R3lAwBwB+s8ce1aOLgE+gRXd3OT1LIl3gHhJRcfTLGrer371K+nbt+9OJkzdAeIlDi5BgVYy5gAAIABJREFU5w4QL/XCWAj4JcBFeH7JMQ8COwioL7Xe/rtlUr9ug4zYuMyXEOJGACkfOQHkEICARgLsfxphYgoCHgjQex5gMRQCmgnQf5qBYi4RBLgEPaZpVJd7qz/wq+fYY4+VsWPHFozk5Zdfdj4fpZ79999fJk+eXHBOtgF+Tp+ouzjUiQz1qMvLb7wx2Ocd1KewfvCDHziXiKvnpptukqFDh+7k7qJFi5w7RdTTu3dvefjhhwvGq+4XUXecpB/FuVevXgXn+R2AAIIA4rd2mAcBLwR4CfZCi7EQyE7go3WNcu+T/5Lmljbp0dokp3zyTzm08UPXuBBAXKNiIAS0EWD/04YSQxDwRIDe84SLwRDQSoD+04oTYwkhgAAS00Sqy8BnzJjheO/2gu/HH39cnn32WWfO8OHD5dprr/UVvVpXra8et+KLEiKUIKGe008/XS688EJfa3ecdNlll0ldXZ3zTz/96U/luOOO28nmBx984FyQrp6SkhL5/e9/L7vttlvedZcuXSp33323M6Znz54yffr0wH7mM4AAggASaoFhHAKfEeAlmFKAgB4C731QL7/6y/uyW/MWOfWTf8iXGz9ybRgBxDUqBkJAGwH2P20oMQQBTwToPU+4GAwBrQToP604MZYQAgggMU3k22+/LXfddZfjfbdu3RwxpHPnznmjufPOO+Wdd95xxpx99tk7XfbtBcOcOXPkoYcecqbsu+++7acs8tm46qqrpLq62hmihIuTTz7Zy5JZx/7whz+UpqYm52dK6PjqV7+607ht27Y5p0TUZyvUo+I/+OCD86779NNPt18Of8ghh8gdd9wR2M98BhBAEEBCLTCMQ+AzArwEUwoQ0EPgw1U18s/pz8jQjd7vAkEA0ZMDrEDACwH2Py+0GAsBfQToPX0ssQQBrwToP6/EGG8DAQSQmGZ569atctFFF0lLS4urP+6rcRdffHG7YHDLLbfIkCFDfEWvhAwlaKSfadOmyV577ZXT1oYNG2TMmDHtP58yZYrss88+vtZOT1q/fr1cccUV7TbUqY2DDjoow+aECRNkxYoVzr+PHj1azjzzzLzrKlFJiUvqOeecc+S8884L5GehyQggCCCFaoSfQ0AHAV6CdVDEhs0EWusbpP6V2bLhtfnSJbXj85teHwQQr8QYD4HgBNj/gjPEAgT8EKD3/FBjDgT0EKD/9HDESrIIIIDEOJ8d7+I45ZRT5NJLL80ZzYIFC0QJD+rp0aOHqLstCp0YyYdG3ZOh7stQTyFh4ZlnnpEnnnjCGXvAAQfIvffeG5j6zJkzRZ3WUE9paanzqaps8ah7R9T9I+opdFqltrZWfvKTn0hb244/yk+aNEkOPPDAwL7mM4AAggASaoFhHAKfEeAlmFKAgD8CjvAxe45smrdAUp/9H534syRSSAApkRK5f+TNfs0zDwIQyEKA/Y+ygIAZAvSeGe6sCgFFgP6jDiCQSQABJMZVsWTJEueP9Orp0qWL/OIXv5CBAwdmRNTc3CzXXXed1NTUOD9TpyCUaBHkeemll9rvx9hjjz3kvvvukz333DPD5MaNG51LxTdv3uz87JJLLpFTTz01q49du3Z1/oe60LNy5UqZOHFi++kX9Tkt9VmtbE99fb1zUkQxUE++z2898MADsnDhQmec+lSW+mRW2A8CCAJI2DWGfQjwEkwNQMAfgeaqKqkpr5C2xi3+DOwyS32Qc8ro/jltIYBowYwRCOxEgD8CURAQMEOA3jPDnVUhwO9+1AAEshNAAIl5Zdx6662yfPlyJ4p+/frJz372M+eURfrZtGmTqD/sp+/+UBd7V1RUOKdAdn12/ayUsn344YdnJdTa2ipXX321rFu3zvn5oEGDHJGlb9++7eM/+eQTueeee0RdRq6eAQMGyOTJk7Oe1Fi2bJlzKuXb3/62HH300dKrV6+MddVnvF599VXnREda0FCnP5TNPn365Mzkk08+KX/+85+dn6tL0C+//HLn8vb0o2JRY9IXxKt/v+222+Swww4LvToQQBBAQi8yFoAA/1dA1AAEfBNInwBpmLdAJOQTIMrJ8pETfPvKRAhAIJMAf4SlKiBghgC9Z4Y7q0JAEaD/qAMIZBJAAIl5VajPNo0fP17q6uqcSEpKSpw/3KvENjQ0yLvvvtsuFqhPRKmxRxxxRNaovQggyoASNtRdIuo+EvUo+8r23nvvLcqvyspKUX/gV48SKtSF4h3FmY5OKAFEnepIx6A+V7XffvuJEmzUo+JTJz8aGxvbp6kTIzfccEPOeNIDlcCh7ghR/qQf5YcSbZSoogSkND/181GjRsn3vve9olQGAggCSFEKjUWsJ8BLsPUlAICABNZ8sF4WTPuzlNV7v/w8vXShT2CpcQggARPFdAjsQoD9j5KAgBkC9J4Z7qwKAUWA/qMOIJBJAAEkAVWxZs0a55RH+qRFtpDUiQp18mHYsGE5I/YqgChDSpRQd4uoubkeVWRXXnml81mpXE9HAcRNSpR4oeL5whe+4Ga4bNmyRdRl7YsXL845Xgk45557rpx99tmubOoYhACCAKKjjrABgUIEeAkuRIifQyA/gdXVm2XSH5ZLj9YmGbFxmS8hBAGEKoNA8Qmw/xWfOStCgD/AUgMQMEuAvc8sf1aPJgEEkGjmxbNX6pSDur9C/efjjz8WdfeF+sxV//79Zfjw4XLiiSdm/axUx4X8CCBqvjoBMnfuXEdcqK6uFvXZLXUviPrk1THHHCPf+MY3pHv37nljUhePKwFnxYoVzn/SdpQtJRLsvvvuzie+Bg8e7MQzZMgQz4zUBPUpMOWrEm7U/SRK9FCfzxo6dKicdNJJsv/++/uy63cSAggCiN/aYR4EvBDgJdgLLcZCIJPA2tommTjj85OkSgj5z3UL5MCmate4EEBco2IgBLQRYP/ThhJDEPBEgN7zhIvBENBKgP7TihNjCSGAAJKQRBJGPAkggCCAxLNy8TpuBHgJjlvG8DdqBJqat8u4B5dIm7rJ/LPnyIb35T/W5z5ZumsMCCBRyyr+2ECA/c+GLBNjFAnQe1HMCj7ZQoD+syXTxOmFAAKIF1qMhYBmAgggCCCaSwpzEMhKgJdgCgMCwQlMe26VLFm54841dQLkO+vmyxebalwbLiSAlEiJ3D/yZtf2GAgBCBQmwP5XmBEjIBAGAXovDKrYhIA7AvSfO06MsosAAohd+SbaiBFAAEEAiVhJ4k5CCfASnNDEElZRCaz4qEGmPbFURtRVSlnDSuma2u5pfQQQT7gYDAEtBNj/tGDECAQ8E6D3PCNjAgS0EaD/tKHEUIIIIIAkKJmEEj8CCCAIIPGrWjyOIwFeguOYNXyOEoHW+gapf2W2bHhtvnTxKHyk40AAiVJG8cUWAux/tmSaOKNGgN6LWkbwxyYC9J9N2SZWtwQQQNySYhwEQiCAAIIAEkJZYRICGQR4CaYoIOCPgCN8zJ4jm+YtkFRLiz8jn81S14dMGd0/pw0+gRUIL5MhkJUA+x+FAQEzBOg9M9xZFQKKAP1HHUAgkwACCFUBAYMEEEAQQAyWH0tbRICXYIuSTajaCDRXVUlNeYW0NW7RYpMTIFowYgQCngiw/3nCxWAIaCNA72lDiSEIeCZA/3lGxgQLCCCAWJBkQowuAQQQBJDoVieeJYkAL8FJyiaxFJOAzhMghQSQziWd5L7jbipmeKwFgcQTYP9LfIoJMKIE6L2IJga3rCBA/1mRZoL0SAABxCMwhkNAJwEEEAQQnfWELQjkIsBLMLUBgWAEdAghhQSQ3rvtIRNHjA3mKLMhAIGdCLD/URAQMEOA3jPDnVUhoAjQf9QBBDIJIIBQFRAwSAABBAHEYPmxtEUEeAm2KNmEGiqBD1fVyBu//YscWfcv6erxMnQEkFBTg3EIZCXA/kdhQMAMAXrPDHdWhQACCDUAgewEEECoDAgYJIAAggBisPxY2iIC/BJqUbIJNTQCqVRKbv/dMllb2yQ9Wpvk7OrXZL/mT12vhwDiGhUDIaCNAPufNpQYgoAnAvSeJ1wMhoBWAvSfVpwYSwgBBJCEJJIw4kkAAQQBJJ6Vi9dxI8BLcNwyhr9RJLDiowaZ/KcVjmtKADmn+lXZt7nWtasIIK5RMRAC2giw/2lDiSEIeCJA73nCxWAIaCVA/2nFibGEEEAASUgiCSOeBBBAEEDiWbl4HTcCvATHLWP4G0UC055bJSveWysj6iqlrGEln8CKYpLwCQK7EGD/oyQgYIYAvWeGO6tCQBGg/6gDCGQSQAChKiBgkAACCAKIwfJjaYsI8BJsUbIJNRQCmz+pkxcmPyFH1XsXPtIOcQIklNRgFAJ5CbD/USAQMEOA3jPDnVUhgABCDUAgOwEEECoDAgYJIIAggBgsP5a2iAC/hFqUbELVSqC1vkHqZ8+RhrnzRVpbA9lGAAmEj8kQ8EWA/c8XNiZBIDABei8wQgxAwDcB+s83OiYmmAACSIKTS2jRJ4AAggAS/SrFwyQQ4CU4CVkkhmITaK6qkpryCmlr3KJl6UICyMCeA+Sasou1rIURCEBgBwH2PyoBAmYI0HtmuLMqBNj7qAEIZCeAAEJlQMAgAQQQBBCD5cfSFhHgl1CLkk2oWgm0nwCZt0CkpSWQ7eYuJTJ1VL+cNspHTghkn8kQgEAmAfY/qgICZgjQe2a4syoEEECoAQgggFADEIgcAQQQBJDIFSUOJZIAv4QmMq0EVUQCO+4AmSlH1a/wfPl52s1NpZ1k+ll9EUCKmDeWggD7HzUAATME6D0z3FkVAggg1AAEEECoAQhEjgACCAJI5IoShxJJgF9CE5lWgioygamz3peVy6tlxMZlUuZDCEEAKXLCWA4CfAKLGoCAMQK8expDz8IQ4POP1AAEshDgE1iUBQQMEkAAQQAxWH4sbREBfgm1KNmEGhqB2W/WyFNzP3bs92htku9XvSR7t25yvR4CiGtUDISANgLsf9pQYggCngjQe55wMRgCWgnQf1pxYiwhBBBAEpJIwognAQQQBJB4Vi5ex40AL8Fxyxj+RpHAtFmrZMn7dY74MaKuUr5a/y/pJCnXriKAuEbFQAhoI8D+pw0lhiDgiQC95wkXgyGglQD9pxUnxhJCAAEkIYkkjHgSQABBAIln5eJ13AjwEhy3jOFv1Ag0NW+XCQ8slK9tqJSyhpW+7gFBAIlaVvHHBgLsfzZkmRijSIDei2JW8MkWAvSfLZkmTi8EEEC80GIsBDQTQABBANFcUpiDQFYCvARTGBDwT6C1vkHWznpJti5e5Ev4SK+MAOI/B8yEgF8C7H9+yTEPAsEI0HvB+DEbAkEI0H9B6DE3qQQQQJKaWeKKBQEEEASQWBQqTsaeAC/BsU8hARggoISP+tlzZNO8BZJqaQnsAQJIYIQYgIBnAux/npExAQJaCNB7WjBiBAK+CNB/vrAxKeEEEEASnmDCizYBBBAEkGhXKN4lhQAvwUnJJHEUi0BzVZXUlFdIW+MWLUuqm0I2l3aS6Wf1zWmvfOQELWthBAIQ+JwA+x/VAAEzBOg9M9xZFQKKAP1HHUAgkwACCFUBAYMEEEAQQAyWH0tbRICXYIuSTajaCOg8AaJ2u8VDe8ibh/dAANGWIQxBoDAB9r/CjBgBgTAI0HthUMUmBNwRoP/ccWKUXQQQQOzKN9FGjAACCAJIxEoSdxJKgJfghCaWsIpCIC2EbHhtvnRpa/W1ptrtKkb3zzuXEyC+0DIJAnkJsP9RIBAwQ4DeM8OdVSGgCNB/1AEEMgkggFAVEDBIAAEEAcRg+bG0RQR4CbYo2YQaGoGKR/9X+i//p5TVr/B8GToCSGhpwTAEEECoAQhEkADvnhFMCi5ZQ4D+sybVBOqBAAKIB1gMhYBuAgggCCC6awp7EMhGgJdg6gICwQg0NW+XcQ8ukbaUSI/WJhmxcZl8deN70smlWQQQl6AYBgHNBNj/NAPFHARcEqD3XIJiGARCIED/hQAVk7EngAAS+xQSQJwJIIAggMS5fvE9PgR4CY5PrvA0mgTW1jbJxBmVjnOOAFJXKV+rXy4lLt1FAHEJimEQ0EyA/U8zUMxBwCUBes8lKIZBIAQC9F8IUDEZewIIILFPIQHEmQACCAJInOsX3+NDgJfg+OQKT6NJYHX1Zql4dIkjfJQ1rOQTWNFME15BIIMA+x9FAQEzBOg9M9xZFQKKAP1HHUAgkwACCFUBAYMEEEAQQAyWH0tbRICXYIuSTajaCahL0NfOekm2Ll7kWfhIO5MSkSlcgq49NxiEQCEC7H+FCPFzCIRDgN4LhytWIeCGAP3nhhJjbCOAAGJbxok3UgQQQBBAIlWQOJNYArwEJza1BBYiASV81M+eI5vmLZBUS0uglRBAAuFjMgR8E2D/842OiRAIRIDeC4SPyRAIRID+C4SPyQklgACS0MQSVjwIIIAggMSjUvEy7gR4CY57BvG/2ASaq6qkprxC2hq3aFkaAUQLRoxAwDMB9j/PyJgAAS0E6D0tGDECAV8E6D9f2JiUcAIIIAlPMOFFmwACCAJItCsU75JCgJfgpGSSOIpJQOcJEC5BL2bmWAsCnxNg/6MaIGCGAL1nhjurQkARoP+oAwhkEkAAoSogYJAAAggCiMHyY2mLCPASbFGyCVU7gbQQUvfafOnc1urLPgKIL2xMgkBgAux/gRFiAAK+CNB7vrAxCQJaCNB/WjBiJGEEEEASllDCiRcBBBAEkHhVLN7GlQAvwXHNHH5HhUBT83aZ8MBC+VrdMimrX+H5MnQEkKhkEj9sI8D+Z1vGiTcqBOi9qGQCP2wkQP/ZmHViLkQAAaQQIX4OgRAJIIAggIRYXpiGQDsBXoIpBggEI7C2tkkmzqh0jPTbWif/sX6h7LNtg5S4NIsA4hIUwyCgmQD7n2agmIOASwL0nktQDINACATovxCgYjL2BBBAYp9CAogzAQQQBJA41y++x4cAL8HxyRWeRpPA6urNUvHoEhlRVyllDSs5ARLNNOEVBDIIsP9RFBAwQ4DeM8OdVSGgCNB/1AEEMgkggFAVEDBIAAEEAcRg+bG0RQR4CbYo2YSqnYC6A2TtrJdk6+JFnoWPtDOcANGeFgxCwBUB9j9XmBgEAe0E6D3tSDEIAdcE6D/XqBhoEQEEEIuSTajRI4AAggASvarEoyQS4CU4iVklprAJpC8/3zRvgaRaWgItlxKRKaP757VRPnJCoDWYDAEIZBJg/6MqIGCGAL1nhjurQkARoP+oAwhkEkAAoSogYJAAAggCiMHyY2mLCPASbFGyCVULgeaqKqkpr5C2xi1a7CGAaMGIEQh4JsD+5xkZEyCghQC9pwUjRiDgiwD95wsbkxJOAAEk4QkmvGgTQABBAIl2heJdUgjwEpyUTBJHMQlwAqSYtFkLAuEQYP8LhytWIVCIAL1XiBA/h0B4BOi/8NhiOb4EEEDimzs8TwABBBAEkASUMSHEgAAvwTFIEi5GlkBaCKmfu0BKWv19CqvQHSAlUiL3j7w5sgxwDAJxJcD+F9fM4XfcCdB7cc8g/seZAP0X5+zhe1gEEEDCIotdCLgggACCAOKiTBgCgcAEeAkOjBADEJDfPvW27P6/i6SsfoXny9ARQCggCJghwP5nhjurQoDeowYgYI4A/WeOPStHlwACSHRzg2cWEEAAQQCxoMwJMQIEeAmOQBJwIdYEmpq3y7gHl0hbSqRHa5OMqKuU4fXLXceEAOIaFQMhoJUA+59WnBiDgGsC9J5rVAyEgHYC9J92pBhMAAEEkAQkkRDiSwABBAEkvtWL53EiwEtwnLKFr1EksLa2SSbOqHRcUwLI0XXvytfq/+Xa1UICSOeSTnLfcTe5tsdACEDAHQH2P3ecGAUB3QToPd1EsQcB9wToP/esGGkPAQQQe3JNpBEkgACCABLBssSlBBLgJTiBSSWkohJYXb1ZKh5d4pz8KGtYqf0TWL1320Mmjhhb1JhYDAI2EGD/syHLxBhFAvReFLOCT7YQoP9syTRxeiGAAOKFFmMhoJkAAggCiOaSwhwEshLgJZjCgIB/AuoS9LWzXpKtixd5Fj7Sq6ZEZMro/jmdQADxnx9mQiAfAfY/6gMCZgjQe2a4syoEFAH6jzqAQCYBBBCqAgIGCSCAIIAYLD+WtogAL8EWJZtQtRFQwkf97Dmyad4CSbW0BLKLABIIH5Mh4JsA+59vdEyEQCAC9F4gfEyGQCAC9F8gfExOKAEEkIQmlrDiQQABBAEkHpWKl3EnwEtw3DOI/8Um0FxVJTXlFdLWuEXL0oUEkIE9B8g1ZRdrWQsjEIDA5wTY/6gGCJghQO+Z4c6qEFAE6D/qAAKZBBBAqAoIGCSAAIIAYrD8WNoiArwEW5RsQtVGQOcJkEKXoJePnKDNbwxBAAIIINQABEwT4N3TdAZY32YC9J/N2Sf2XAQQQKgNCBgkgACCAGKw/FjaIgK8BFuUbELVTkCHEIIAoj0tGISAKwLsf64wMQgC2gnQe9qRYhACrgnQf65RMdAiAgggFiWbUKNHAAEEASR6VYlHSSTAS3ASs0pMxSaw+ZM6+evkmVJWv8LzZegIIMXOFutBYAcB9j8qAQJmCNB7ZrizKgTY+6gBCGQngABCZUDAIAEEEAQQg+XH0hYR4JdQi5JNqKERWFvbJBNnVEq/rXXynXXzpX/LRtdrIYC4RsVACGglwP6nFSfGIOCaAL3nGhUDIaCdAP2nHSkGE0AAASQBSSSE+BJAAEEAiW/14nmcCPASHKds4WtUCax+v1r++cgzUtawkhMgUU0SfkFgFwLsf5QEBMwQoPfMcGdVCCgC9B91AIFMAgggVAUEDBJAAEEAMVh+LG0RAV6CLUo2oWonkL4DpGHufJHWVl/2UyIyZXT/nHO5BN0XViZBoCAB9r+CiBgAgVAI0HuhYMUoBFwRoP9cYWKQZQQQQCxLOOFGiwACCAJItCoSb5JKgJfgpGaWuMIkoOPy87R/CCBhZgrbEMhNgP2P6oCAGQL0nhnurAoBRYD+ow4gkEkAAYSqgIBBAgggCCAGy4+lLSLAS7BFySZULQSaq6qkprxC2hq3aLGHAKIFI0Yg4JkA+59nZEyAgBYC9J4WjBiBgC8C9J8vbExKOAEEkIQnmPCiTQABBAEk2hWKd0khwEtwUjJJHMUkwAmQYtJmLQiEQ4D9LxyuWIVAIQL0XiFC/BwC4RGg/8Jji+X4EkAAiW/u8DwBBBBAEEASUMaEEAMCvATHIEm4GFkCOoQQtdtVcAdIZHOMY8klwP6X3NwSWbQJ0HvRzg/eJZsA/Zfs/BKdPwIIIP64MQsCWggggCCAaCkkjECgAAFegikRCAQnsPmTOnlh8kw5qn6FdE1t92QQAcQTLgZDQBsB9j9tKDEEAU8E6D1PuBgMAa0E6D+tODGWEAIIIAlJJGHEkwACCAJIPCsXr+NGgJfguGUMf6NIYG1tk0ycUSn9ttbJmTWvS5/WTa7dRABxjYqBENBKgP1PK06MQcA1AXrPNSoGQkA7AfpPO1IMJoAAAkgCkkgI8SWAAIIAEt/qxfM4EeAlOE7ZwteoElj9frX885FnpKxhJSdAopok/ILALgTY/ygJCJghQO+Z4c6qEFAE6D/qAAKZBBBAqAoIGCSAAIIAYrD8WNoiArwEW5RsQtVOIH0HSMPc+SKtrb7scwLEFzYmQSAwAfa/wAgxAAFfBOg9X9iYBAEtBOg/LRgxkjACCCAJSyjhxIsAAggCSLwqFm/jSoCX4LhmDr9NEtBx+XnafwQQk5lkbZsJsP/ZnH1iN0mA3jNJn7VtJ0D/2V4BxJ+NAAIIdQEBgwQQQBBADJYfS1tEgJdgi5JNqFoINFdVSU15hbQ1btFiDwFEC0aMQMAzAfY/z8iYAAEtBOg9LRgxAgFfBOg/X9iYlHACCCAJTzDhRZsAAggCSLQrFO+SQoCX4KRkkjiKSYATIMWkzVoQCIcA+184XLEKgUIE6L1ChPg5BMIjQP+FxxbL8SWAABLf3OF5AggggCCAJKCMCSEGBHgJjkGScDGyBHQIIc1dSmTqqH45YywfOSGy8eMYBOJMgP0vztnD9zgToPfinD18jzsB+i/uGcT/MAgggIRBFZsQcEkAAQQBxGWpMAwCgQjwEhwIH5Mh4BDY/EmdvDB5phxVv0K6prZ7orKptJNMP6svAognagyGQHAC7H/BGWIBAn4I0Ht+qDEHAnoI0H96OGIlWQQQQJKVT6KJGQEEEASQmJUs7saUAC/BMU0cbkeKwNraJpk4o1J6tDbJf6xbKF9qWuvaPwQQ16gYCAGtBNj/tOLEGARcE6D3XKNiIAS0E6D/tCPFYAIIIIAkIImEEF8CCCAIIPGtXjyPEwFeguOULXyNKoHV1Ztl0h+WO+4N6/mSnLZ0vWtXm7uWyNRz+QSWa2AMhIAmAux/mkBiBgIeCdB7HoExHAIaCdB/GmFiKjEEEEASk0oCiSMBBBAEkDjWLT7HjwAvwfHLGR5Hj0D6BIjy7Ku9npNTltS1O7m5eyfp1tImXXN8GUvtdhWj++cMijtAopdvPEoGAfa/ZOSRKOJHgN6LX87wODkE6L/k5JJI9BFAANHHEksQ8EwAAQQBxHPRMAECPgjwEuwDGlMgsAuBpubtMu7BJdKWEhnec5actHRj+4iq/l3lxa/3kq8s3yJHvt8kXXYRQhBAKCcImCHA/meGO6tCgN6jBiBgjgD9Z449K0eXAAJIdHODZxYQQABBALGgzAkxAgR4CY5AEnAhEQSmznpf3np/oxzdY5ac8PbnAshH/6+rvHxsL/nKe58JILtsbwggiUg/QcSQAPtfDJOGy4kgQO8lIo0EEVMC9F9ME4fboRJAAAkVL8YhkJ8AAggCCD0CgWIQ4CW4GJRZwwYCs9+skafmfizHlj4rx79b3x5yfY9O0mNrW8bJj/QABBAbqoMYo0iA/S+KWcEnGwjQezZkmRijSoD+i2pm8MskAQQQk/QbCCUFAAAgAElEQVRZ23oCCCAIINY3AQCKQoCX4KJgZhELCEybtUqWvF8nx+3+tBz3zmbXETd3KZGpo7gE3TUwBkJAEwH2P00gMQMBjwToPY/AGA4BjQToP40wMZUYAgggiUklgcSRAAIIAkgc6xaf40eAl+D45QyPo0cgfQdIaUuTnLPpGdm3ttW1k5tKO8n0s/pmHV8iJXL/yJtd22IgBCDgngD7n3tWjISATgL0nk6a2IKANwL0nzdejLaDAAKIHXkmyogSQABBAIloaeJWwgjwEpywhBKOEQJrPlgvC6Y+JWUNK6Vrapdbzgt4hABiJGUsCgFh/6MIIGCGAL1nhjurQkARoP+oAwhkEkAAoSogYJAAAggCiMHyY2mLCPASbFGyCVU7gdb6BqmfPUca5s4XaXV/6qOjIwgg2tOCQQi4IsD+5woTgyCgnQC9px0pBiHgmgD95xoVAy0igABiUbIJNXoEEEAQQKJXlXiURAK8BCcxq8QUNoG08LFp3gJJtbQEWi6fANK5pJPcd9xNgewzGQIQyE6A/Y/KgIAZAvSeGe6sCgFFgP6jDiCQSQABhKqAgEECCCAIIAbLj6UtIsBLsEXJJlQtBJqrqqSmvELaGrdosZdPAOm92x4yccRYLetgBAIQ2JkA+x8VAQEzBOg9M9xZFQIIINQABLITQAChMiBgkAACCAKIwfJjaYsI8EuoRckmVG0EinUCBAFEW8owBIEMAux/FAUEzBCg98xwZ1UIIIBQAxBAAKEGIBA5AgggCCCRK0ocSiQBfglNZFoJqkgEdAghnAApUrJYBgK7EGD/oyQgYIYAvWeGO6tCAAGEGoAAAgg1AIHIEUAAQQCJXFHiUCIJ8EtoItNKUEUmoISQ+VOfkv0+fEe6prZ7Wh0BxBMuBkNAGwH2P20oMQQBTwToPU+4GAwBrQToP604MZYQAnwCKyGJJIx4EkAAQQCJZ+XiddwI8BIct4zhbxQJNDVvl3EPLpHSliYZveFp6dPgXgTJJ4AM7DlArim7OIoh4xMEYk+A/S/2KSSAmBKg92KaONxOBAH6LxFpJAjNBBBANAPFHAS8EEAAQQDxUi+MhYBfArwE+yXHPAh8TmBtbZNMnFHp/MOZLU/Klz9sdo0nnwBSPnKCazsMhAAEvBFg//PGi9EQ0EWA3tNFEjsQ8E6A/vPOjBnJJ4AAkvwcE2GECSCAIIBEuDxxLUEEeAlOUDIJxRiB1dWbZdIfljvrn938pBz88ecCSHWfLtJ3Y6t0zXEoBAHEWNpY2HIC7H+WFwDhGyNA7xlDz8IQEPqPIoBAJgEEEKoCAgYJIIAggBgsP5a2iAAvwRYlm1BDI9DxBMj3tj4pB1V9LoAsPqKHVB7UXUa82yhD/r1VOqV2dgMBJLS0YBgCeQmw/1EgEDBDgN4zw51VIaAI0H/UAQQQQKgBCESKAAIIAkikChJnEkuAl+DEppbAikggfQdIW0pk1JaZcuDabe2r//OwUumyXeTIVU3O/7vrgwBSxESxFAQ6EGD/oxwgYIYAvWeGO6tCAAGEGoBAdgKcAKEyIGCQAAIIAojB8mNpiwjwS6hFySbUUAlMnfW+vPX+Rjm/caZ8sfpzAWR7iUjnXU59pB1R/7y5tJNMP6tvVt+4AyTUlGHccgLsf5YXAOEbI0DvGUPPwhDgBAg1AIEsBBBAKAsIGCSAAIIAYrD8WNoiAvwSalGyCTVUArPfrJGn5n4sF2z8g+z/aaurtTZ3L5G3D9ld3jy8BwKIK2IMgoA+Aux/+lhiCQJeCNB7XmgxFgJ6CdB/enliLRkEEECSkUeiiCkBBBAEkJiWLm7HjAAvwTFLGO5GlsBv//S27P6/C+Vr9culxKWX+T5/pUxwAsQlSIZBwAcB9j8f0JgCAQ0E6D0NEDEBAZ8E6D+f4JiWaAIIIIlOL8FFnQACCAJI1GsU/5JBgJfgZOSRKMwRaK1vkNoXX5H6eQukayrLJR95XEMAMZc3VoYA+x81AAEzBOg9M9xZFQKKAP1HHUAgkwACCFUBAYMEEEAQQAyWH0tbRICXYIuSTahaCSjho372HNk0b4GkWlp82UYA8YWNSRDQQoD9TwtGjEDAMwF6zzMyJkBAGwH6TxtKDCWIAAJIgpJJKPEjgACCABK/qsXjOBLgJTiOWcNnkwR0CB9p/xFATGaStW0nwP5newUQvykC9J4p8qwLAU6AUAMQyEYAAYS6gIBBAgggCCAGy4+lLSLAL6EWJZtQAxNorqqSmvIKaWvcEtiWMoAAogUjRiDgiwD7ny9sTIJAYAL0XmCEGICAbwL0n290TEwwAQSQBCeX0KJPAAEEAST6VYqHSSDAS3ASskgMxSTACZBi0mYtCIRHgP0vPLZYhkA+AvQe9QEBcwToP3PsWTm6BBBAopsbPLOAAAIIAogFZU6IESDAS3AEkoALsSSgQwjhBEgsU4/TCSHA/peQRBJG7AjQe7FLGQ4niAD9l6BkEoo2Aggg2lBiCALeCSCAIIB4rxpmQMA7AV6CvTNjBgQ6EkgLIfVzF0hJq7fL0Ju7lsjUc/vlBFo+cgKwIQCBkAiw/4UEFrMQKECA3qNEIGCOAP1njj0rR5cAAkh0c4NnFhBAAEEAsaDMCTECBHgJjkAScCERBP61rErefuw5+drG96TEZURqp6sY3R8BxCUvhkFAJwH2P500sQUB9wToPfesGAkB3QToP91EsZcEAgggScgiMcSWAAIIAkhsixfHY0WAl+BYpQtnI0xg2nOrZMnKOvnpR4/K7tvcOYoA4o4ToyAQBgH2vzCoYhMChQnQe4UZMQICYRGg/8Iii904E0AAiXP28D32BBBAEEBiX8QEEAsCvATHIk04GXECTc3bZdyDS6QtJXLVR7+X0m2pdo9bO4l0ybGlIYBEPLG4l2gC7H+JTi/BRZgAvRfh5OBa4gnQf4lPMQH6IIAA4gMaUyCgiwACCAKIrlrCDgTyEeAlmPqAQHACa2ubZOKMSsfQ1R/+Xrq1dBBASkS6fP5fd1oMASQ4eyxAwC8B9j+/5JgHgWAE6L1g/JgNgSAE6L8g9JibVAIIIEnNLHHFggACCAJILAoVJ2NPgJfg2KeQACJAYHX1Zpn0h+WOJ9f836PS1eUWhgASgeThgrUE2P+sTT2BGyZA7xlOAMtbTYD+szr9BJ+DAAJIQkqjtbVVFi1aJAsXLpSPP/5Y6uvrpUePHtK/f38ZPny4nHDCCdKrV69Qot26davMmzdPFi9eLNXV1dLQ0OCsNWDAADnmmGPk+OOPl+7du7tae+PGjfLOO+/IsmXL5MMPP5T169dLU1OTdOvWTfbcc0856KCD5Oijj5Zhw4aJ+h91N8+oUaPcDGsfo5qioqLC0xy/gxFAXP71yC9g5kEAAg4BXoIpBAgEJ6BOgNz7mzdkRF2lfK1+OZegB0eKBQiEToD9L3TELACBrAToPQoDAuYI0H/m2LNydAkggEQ3N649W7NmjUyZMkVWr16dc07v3r3lxz/+sSMc6HxWrlzprK2EilyPKrKf/vSnMnjw4JxjPv30U3nwwQflvffek1QqxzckOsz+whe+IFdeeaUccMABBcNBACmIqGgD2IiLhpqFILATAXqPgoBAMAKt9Q1S++IrUj9vgXRNbfdkrLlLiUwd1S/nnPKREzzZYzAEIOCeAPufe1aMhIBOAvSeTprYgoA3AvSfN16MtoMAAkjM81xbWyvjx4+Xuro6J5KSkhI59NBDZZ999nFOgbz77ruybds252edO3d2xh5xxBFaolYnNG655RbnhEba/pAhQ6RPnz6i/KqsrBR1wkE9paWlcscdd+QULJSQcvPNN+/kV79+/UQJHUq8aW5uln//+9/OCZP0o2xOmDDBORWS7+kogHzzm98sGLs6vXLuuecWHKdjACdAOAGio46wAYFCBHgJLkSIn0MgOwElfNTPniOb5i2QVEuLL0ybSjvJ9LP65pyLAOILK5Mg4IoA+58rTAyCgHYC9J52pBiEgGsC9J9rVAy0iAACSMyTfeutt8ry5Tu+R60Eg+uvv94RDdKP+hzVAw884Agh6unZs6fzeSf1eawgj/rk1tVXXy3r1q1zzKg11drKh/SjToXcc889zqes1KM+iTV58mRHiNn1SQsge+21l5x44onOJ7uUiLPr88Ybb8jUqVNl06ZN7THff//9sttuu+UMp6MA8sc//jFI2NrnIoAggGgvKgxCIAsBXoIpCwh4I6BD+EiviADijT2jIaCTAPufTprYgoB7AvSee1aMhIBuAvSfbqLYSwIBBJAYZ3HJkiUyadIkJ4IuXbo4//9sn4RSd3Rcd9117WLFmWeeKaNHjw4U+csvvyyPPPKIY0OJKUrYUOLFro86mTJu3DhpbGx0fnTppZfKKaeckjGuqqpKli5dKqeddlpeMUNNXLVqlXNapK1txx/PL7nkEjn11FNzxoMAEijVWiezEWvFiTEIuCZA77lGxUAISHNVldSUV0hb4xYtNBBAtGDECAR8EWD/84WNSRAITIDeC4wQAxDwTYD+842OiQkmgAAS4+T+/Oc/l7feesuJ4OSTT5bLLrssZzTz589vv9hbnQJ5+OGHs57EcItDiRpKtFDP+eefL2effXbOqU8//bTMnDnT+bk6KaJOhQR91KkPdem6er7yla/Iz372s5wmEUCC0tY3n41YH0ssQcALAXrPCy3GQkCEEyBUAQSSQYD9Lxl5JIr4EaD34pczPE4OAfovObkkEn0EEED0sSyqJXWq46KLLpKWz75Hfeedd8rBBx+c0wc17uKLL26/r0Pd3aHu6/Dz1NTUOJeapx/1Saq99947p6kNGzbImDFj2n+uLk3P9nkrL7688MILMmPGDGeKOvVy77335pyOAOKFbLhj2YjD5Yt1COQiQO9RGxDwR0CHEMIJEH/smQUBHQTY/3RQxAYEvBOg97wzYwYEdBGg/3SRxE6SCCCAxDSbb7/9ttx1112O9926dXPEgGx3a3QMT4kk77zzjvNP6sSGOrnh55kzZ4489NBDzlR1r4e6Y6TQc9VVV7VfYK5OqqgTK0GeF198UX772986Jvbff3/nE1y5HgSQIKT1zmUj1ssTaxBwS4Dec0uKcRDITkAJIR//5UVp+cdi6Zra7glTc9cSmXru53ekdZxcIiVy/8ibPdljMAQg4J4A+597VoyEgE4C9J5OmtiCgDcC9J83Xoy2gwACSEzz3PEExODBg9vFkHzhPP744/Lss886Q4YPHy7XXnutr+iV2KLWV8+xxx4rY8eOLWinvLxcFi1a5Iw7/fTT5cILLyw4J9+AadOmyd/+9jdnyNChQ+Wmm27KObyjAHLbbbc5d4hs3LjRuTdljz32kEGDBjmnZ/JdpB7I2TyTuQSdS9DDqi3sQqAjAV6CqQcIBCewtrZJ7v3NG3JCp+fkiP/b6tqg2ukqRvfPOh4BxDVGBkLAFwH2P1/YmASBwATovcAIMQAB3wToP9/omJhgAgggMU3ub37zG3nllVcc792KEB0vLi90aiIflo53j3z3u9+V73//+wUpPvbYYzJr1ixnXFlZmdx4440F5+QaoD7/9eMf/7j9YvULLrhAzjjjjJz2OgoguQaVlpY6F6mrkzG77767b9+8TkQAQQDxWjOMh4AfArwE+6HGHAjsTKCpebuMe3CJ9DvkefnR8xtc40EAcY2KgRDQToD9TztSDELAFQF6zxUmBkEgFAL0XyhYMRpzAgggMU1gx0vAv/3tb8uPfvSjgpH84x//kPvuu88Zt+eee7Z/xqrgxF0GjB8/3jlFoR51kkOd6Cj0PP/88/Loo486w9yeWMllU9lR9tTTvXt353L33r1753TBjQCSnqw+6XX99dfLfvvtVyiknD+vra0tOFfxV58sUwLIJ598UnB8Ugaojbh//x3/V7Dr16+XtjYEkKTkljiiTYDei3Z+8C4+BKY++76sLXlUfvjXnQWQ1s4iXXJ8GSufANK5pJPcf/yE+ADAUwjEjAD7X8wShruJIUDvJSaVBBJDAvRfDJOGy6ET6NevX8GrI0J3QkRKUqlUqhgLJWUNP6cw3nrrLVHz1KOEg7Qg4ZXJuHHjpKqqypmmLlY/7bTTCppQp1XUqRX1DBw4sF2IKThxlwHvvvuu87mv9B/O1T0m6tRGvkedUBkxYoQMGzZMDjzwQOfCdvX5q4aGBkfIUXeaLF26tN2Eaoq77747r6iSbz03gsuvf/1r6dOnj9fwGQ8BCEAAAhCAgEEC76z6RH41Z7z84MVdBJBOIl1yaPr5BJC9S/eUqWfseDfjgQAEIAABCEAAAhCAAAQgAIHkEkAA8Zjb22+/XSorK51Z55xzjpx33nkFLajxap56lCI8c+bMgnOyDbjyyitl3bp1zo/GjBkjJ510UkE7r776qkydOtUZp44dqVMbXh91UuKGG26QTZs2OVMPOeQQmThxohNLvmfz5s3Ss2fPvGOUf+pekbQOd+KJJzqf2fLzIID4ocYcCEAAAhCAQPQJNDZtk+tmXC7ff6nOtbP5BJC9uveWad+d5NoWAyEAAQhAAAIQgAAEIAABCEAgngQQQDzmzbYTIErEmDBhgqxZs8YhpU5x3HnnndK3b1+P5HIPV4LQ008/7QxQoooSbNSnqrw+fAIrNzGOYnqtJsZDQA8Bek8PR6xAYM3qGln6xC/lyx82u4aRTwDZo0tPuevr17i2xUAIQMAbAfY/b7wYDQFdBOg9XSSxAwHvBOg/78yYkXwCfAIrpjm26Q4Qdem5OrmSvndkjz32cE5+qIvcdT5qHfVJr23btjlmr7jiCjn++ON1LpFhi0vQuQMk1ALDOAQ+I8BFeJQCBIIRaK1vkPrZc6Rh7nyR1lZPxpq7lMjUUf0y5qiPv/6/7v1l/PDLPNljMAQg4J4A+597VoyEgE4C9J5OmtiCgDcC9J83Xoy2gwCXoMc0z+o+DXWvhnqOPfZYGTt2bMFIXn75ZXnkkUeccUo8mDx5csE52Qb4OX3y2GOPyaxZsxxzZWVlcuONN7paW4kRar1ly5Y540tLS52TIAcddJCr+V4HKWElvdaZZ54po0eP9mrC03gEEAQQTwXDYAj4JMBLsE9wTLOeQFr42DRvgaRaWnzx2FTaSaaflXliVQkgNxx+rQzoU+rLLpMgAIHCBNj/CjNiBATCIEDvhUEVmxBwR4D+c8eJUXYRQACJab5feOEFmTFjhuP94MGDnYvBCz2PP/64PPvss86w4cOHy7XXXltoStafq3XV+upxK76Ul5fLokWLnDmnn366XHjhhQXXbm1tlXvuuUfU5e3q2W233WT8+PFy2GGHFZzrd8ADDzwgCxcudKafcsopcumll/o15WoeAggCiKtCYRAEAhLgJTggQKZbR0CH8JGGlk8AmTRivJR262wdXwKGQLEIsP8VizTrQGBnAvQeFQEBcwToP3PsWTm6BBBAopubvJ69/fbb7aJHt27dHDGkc+f8v0CrOzPeeecdx+7ZZ58t559/vq/o58yZIw899JAzd9999xUlbhR6rrrqKqmurnaGXXbZZXLyySfnndLW1ubY/fvf/+6MU7Fdd911MmzYsEJLBfr5L3/5S3nzzTcdG//5n/8pP/zhDwPZKzQZAQQBpFCN8HMI6CDAS7AOitiwhUBzVZXUlFdIW+MWLSHnEkAkJVJ+/AQta2AEAhDIToD9j8qAgBkC9J4Z7qwKAUWA/qMOIJBJAAEkplWh7qu46KKLpOWzzzEocePggw/OGY0ap+63aGpqcsbccsstMmTIEF/RKyFDCRrpZ9q0abLXXnvltLVhwwYZM2ZM+8+nTJki++yzT87xSvx48MEHZf78+c4Y9T/e6hNfRx99tC9/vUy6/PLL5dNPP3WmXHDBBXLGGWd4me55LAIIAojnomECBHwQ4CXYBzSmWE2gGCdAFODykQggVhcawYdOgP0vdMQsAIGsBOg9CgMC5gjQf+bYs3J0CSCARDc3BT3reBdHoc81LViwQJTwoJ4ePXqIukOk0ImRfA6MGzdOqqqqnCHqngx1X0au55lnnpEnnnjC+fEBBxwg9957b97Y1OkSdcpEPSUlJaJEiW984xsFeQQd8O6778odd9zRbubuu+8O7a6R9CIIIAggQeuW+RBwQ4CXYDeUGAOBTAI6hJDmriUy9dzMS9A5AULFQSB8Aux/4TNmBQhkI0DvURcQMEeA/jPHnpWjSwABJLq5KejZkiVLZNKkSc64Ll26yC9+8QsZOHBgxrzm5mbn81E1NTXOz3Rc7v3SSy/J9OnTHXt77LGH3HfffbLnnntmrL1x40ZRYsnmzZudn11yySVy6qmn5oztd7/7nfz1r39t/7k6tXLaaacVZJFrgDop071794LzN23aJDfddFM7I/VpL3VJvNo4wnwQQBBAwqwvbEMgTYCXYGoBAsEIpIWQhnkLRDxehq52uorR/TMcUJegcwdIsLwwGwKFCLD/FSLEzyEQDgF6LxyuWIWAGwL0nxtKjLGNAAJIzDN+6623yvLly50o+vXrJz/72c+cUxbpR/1hX13snb77o2fPnlJRUeGcAtn1Wb9+vVxxxRXt/6xsH3744VkJqQvKr776alm3bp3z80GDBjkiS9++fdvHf/LJJ84l5h988IHzbwMGDHBEhVwnT/74xz/KU0891T5fxyeo1GfCvvnNb8pxxx3n3FeS7Vm6dKlzIkbFn36uv/56+epXvxp6dSCAIICEXmQsAAG+A0sNQEAbgTUfrJeVj06SL1a3uLaZTwC54fBrZUCfUte2GAgBCHgjwB+BvPFiNAR0EaD3dJHEDgS8E6D/vDNjRvIJIIDEPMe1tbUyfvx4qaurcyJRn4w67LDDRCW2oaFB1Ged1AkQ9SjhQY094ogjskbtRQBRBpSwoe4SUacs0vaV7b333luUX5WVlaL+wK+e0tJS5/NSHcWZjk50PM2i/r13796e7vxQQke2Z9SoUe3/3KdPH2d9ZVudmFHi0KpVqxxfOz7qcnh1SXwxHgQQBJBi1BlrQICXYGoAAnoIrK7eLLNfultO/ecm1wbzCSBjB18tgwb0dG2LgRCAgDcC7H/eeDEaAroI0Hu6SGIHAt4J0H/emTEj+QQQQBKQ4zVr1jinPNInLbKF1KtXL+cujWHDhuWM2KsAogytXLnSuVuk4+mJXRdQRXbllVfmvaT99ddfl1/96le+s6FOj2R7OgoghYwrYUQJKcW4bD3tCwIIAkihuuTnENBBgJdgHRSxAQGRtbVN8uJfbpeT3tzxaU/1bOsi0rVVpCQHIE6AUDkQMEeA/c8ce1a2mwC9Z3f+id4sAfrPLH9WjyYBBJBo5sWzV+qTVAsXLnT+8/HHH0t9fb3zmav+/fvL8OHD5cQTTxQlguR7/Aggyp46ATJ37lxZvHixVFdXOycr1L0g6pNXxxxzjHOBeaF7OMISQJQ/K1ascISaDz/80DkVo/xTp2KUT+reki996UsydOhQx1d1MqSYDwIIAkgx64217CXAS7C9uSdyvQSamrfLzEdvlhOWfC6AFFqBO0AKEeLnEAiPAPtfeGyxDIF8BOg96gMC5gjQf+bYs3J0CSCARDc3eGYBAQQQBBALypwQI0CAl+AIJAEXEkFAXYa++L7bZP9Pgt8BIimR8uMnJIILQUAgqgTY/6KaGfxKOgF6L+kZJr4oE6D/opwdfDNFAAHEFHnWhYCIc0dK+iJ5G4CwEduQZWKMIgF6L4pZwac4EVDCR/3sObJp3gJJtbgXP1SMuU6AqJ+Vj0QAiVMd4Gv8CLD/xS9neJwMAvReMvJIFPEkQP/FM294HS4BBJBw+WIdAnkJIIBwAoQWgUAxCPASXAzKrJFEAkGEjzSP5i4lMnVUv0w8nABJYskQU8QIsP9FLCG4Yw0Bes+aVBNoBAnQfxFMCi4ZJ4AAYjwFOGAzAQQQBBCb65/Yi0eAl+DisWalZBDQIXykSWwq7STTz+qbASaVEpk0YryUduucDGhEAYEIEmD/i2BScMkKAvSeFWkmyIgSoP8imhjcMkoAAcQofha3nQACCAKI7T1A/MUhwEtwcTizSjIINFdVSU15hbQ1btESUD4B5IbDr5UBfUq1rIMRCEAgkwD7H1UBATME6D0z3FkVAooA/UcdQCCTAAIIVQEBgwQQQBBADJYfS1tEgJdgi5JNqFoIFOsEyNjBV8ugAT21+IwRCEAAAYQagEBUCPDuGZVM4IeNBOg/G7NOzIUIIIAUIsTPIRAiAQQQBJAQywvTEGgnwEswxQABfwR0CCGcAPHHnlkQ0EGA/U8HRWxAwDsBes87M2ZAQBcB+k8XSewkiQACSJKySSyxI4AAggASu6LF4VgS4CU4lmnD6QgRSAshG15/XbpsT3nyjDtAPOFiMAS0EmD/04oTYxBwTYDec42KgRDQToD+044UgwkggACSgCQSQnwJIIAggMS3evE8TgR4CY5TtvA1ygQmvXavnPJSlfRp2O7azVwCiKREyo+f4NoOAyEAAe8E2P+8M2MGBHQQoPd0UMQGBPwRoP/8cWNWsgkggCQ7v0QXcQIIIAggES9R3EsIAV6CE5JIwjBO4NZ/lMsxr1XJIR82u/YFAcQ1KgZCQDsB9j/tSDEIAVcE6D1XmBgEgVAI0H+hYMVozAkggMQ8gbgfbwIIIAgg8a5gvI8LAV6C45Ip/Iw6gVv+Xi4nzP5YBq3d5tpVPoHlGhUDIaCdAPufdqQYhIArAvSeK0wMgkAoBOi/ULBiNOYEEEBinkDcjzcBBBAEkHhXMN7HhQAvwXHJFH5GmYC6B2TWb++SoSu2SCcPjnIJugdYDIWAZgLsf5qBYg4CLgnQey5BMQwCIRCg/0KAisnYE0AAiX0KCSDOBBBAEEDiXL/4Hh8CvATHJ1d4Gj0C6QvQN81bIKmWFs8O5hNAxg6+WgYN6OnZJhMgAAF3BNj/3HFiFAR0E6D3dBPFHgTcE6D/3DXgUlwAACAASURBVLNipD0EEEDsyTWRRpAAAggCSATLEpcSSICX4AQmlZBCJxBU+FAOpkRkc2knmX5W3wx/UymRGw6/Vgb0KQ09FhaAgK0E2P9szTxxmyZA75nOAOvbTID+szn7xJ6LAAIItQEBgwQQQBBADJYfS1tEgJdgi5JNqIEJ6BA+0k5s7l4ibx+yu7x5eI+sAsikEeOltFvnwD5jAAIQyE6A/Y/KgIAZAvSeGe6sCgFFgP6jDiCQSQABhKqAgEECCCAIIAbLj6UtIsBLsEXJJtRABJqrqqSmvELaGrcEspOe3Ny1RKae2y+7rZRI+fETtKyDEQhAAAGEGoBAlAjw7hmlbOCLbQToP9syTrxuCCCAuKHEGAiERAABBAEkpNLCLAR2IsBLMAUBAfcEdJ4AUbtcxej+CCDu8TMSAloJsP9pxYkxCLgmQO+5RsVACGgnQP9pR4rBBBBAAElAEgkhvgQQQBBA4lu9eB4nArwExylb+BoVAjqEkHwCiLoDhE9gRSXb+JFUAux/Sc0scUWdAL0X9QzhX5IJ0H9Jzi6x+SWAAOKXHPMgoIEAAggCiIYywgQEChLgJbggIgZAICeBIEJIXgGkrURuGHINl6BTexAIkQD7X4hwMQ2BPAToPcoDAuYI0H/m2LNydAkggEQ3N3hmAQEEEAQQC8qcECNAgJfgCCQBF2JPQAkhz864U8r+1SQlLqPJK4Bs6yZjD7tcBg3o6dIawyAAAa8E2P+8EmM8BPQQoPf0cMQKBPwQoP/8UGNO0gkggCQ9w8QXaQIIIAggkS5QnEsMAV6CE5NKAjFMYOz8O+SSP6+X3ZvdOVJIALnhqCs5AeIOJaMg4IsA+58vbEyCQGAC9F5ghBiAgG8C9J9vdExMMAEEkAQnl9CiTwABBAEk+lWKh0kgwEtwErJIDKYJOCdAfnunlK3QdwJk0nHXSGm3zqZDY30IJJYA+19iU0tgESdA70U8QbiXaAL0X6LTS3A+CSCA+ATHNAjoIIAAggCio46wAYFCBHgJLkSIn0MgN4Ew7gBRF6CXbt9LJp14BeghAIEQCbD/hQgX0xDIQ4DeozwgYI4A/WeOPStHlwACSHRzg2cWEEAAQQCxoMwJMQIEeAmOQBJwIXYEgggf6WBzfQJLCSDf6XGJnPKVfWLHBYchECcC7H9xyha+JokAvZekbBJL3AjQf3HLGP4WgwACSDEoswYEchBAAEEAoTkgUAwCvAQXgzJrJIWADuHDjQByWP1/yWXfOSgp2IgDApEkwP4XybTglAUE6D0LkkyIkSVA/0U2NThmkAACiEH4LA0BBBAEELoAAsUgwEtwMSizRhIINFdVSU15hbQ1btESTmsnkQfP759hS50A2fbmt2TyT4ZxB4gW0hiBQHYC7H9UBgTMEKD3zHBnVQgoAvQfdQCBTAIIIFQFBAwSQABBADFYfixtEQFegi1KNqEGJlCsEyBb3/iW3PbfQ2RAn9LAPmMAAhBAAKEGIBAlArx7Rikb+GIbAfrPtowTrxsCCCBuKDEGAiERQABBAAmptDALgZ0I8BJMQUDAOwEdQki+O0CUAHLD6ENl0ICe3p1jBgQg4IoA+58rTAyCgHYC9J52pBiEgGsC9J9rVAy0iAACiEXJJtToEUAAQQCJXlXiURIJ8BKcxKwSU7EIBBFCCgkgnAApVhZZx1YC7H+2Zp64TROg90xngPVtJkD/2Zx9Ys9FAAGE2oCAQQIIIAggBsuPpS0iwEuwRckm1NAIKCHkxYfvkCH/3up6jXwCSPOb35L7uQPENUsGQsAPAfY/P9SYA4HgBOi94AyxAAG/BOg/v+SYl2QCCCBJzi6xRZ4AAggCSOSLFAcTQYCX4ESkkSAiQOC2v94qP3x+g2tP8gkgpcu/I5MuO8q1LQZCAALeCbD/eWfGDAjoIEDv6aCIDQj4I0D/+ePGrGQTQABJdn6JLuIEEEAQQCJeoriXEAK8BCckkYRhlIA6AfLK1Nvl0A+aXfvBCRDXqBgIgVAIsP+FghWjEChIgN4riIgBEAiNAP0XGloMx5gAAkiMk4fr8SeAAIIAEv8qJoI4EOAlOA5ZwseoEuAOkKhmBr8gUJgA+19hRoyAQBgE6L0wqGITAu4I0H/uODHKLgIIIHblm2gjRgABBAEkYiWJOwklwEtwQhNLWKESCCJ8pB1LiciU0f0z/EylRLa+8S25YfShMmhAz1DjwDgEbCbA/mdz9ondJAF6zyR91radAP1newUQfzYCCCDUBQQMEkAAQQAxWH4sbREBXoItSjahBiagQ/hwK4Dc9t9DZECf0sA+YwACEMhOgP2PyoCAGQL0nhnurAoBRYD+ow4gkEkAAYSqgIBBAgggCCAGy4+lLSLAS7BFySbUQASaq6qkprxC2hq3BLKTnswdIFowYgQCvgmw//lGx0QIBCJA7wXCx2QIBCJA/wXCx+SEEkAASWhiCSseBBBAEEDiUal4GXcCvATHPYP4X0wCOk+A5BNADqj+nlxz3qHFDI21IGAdAfY/61JOwBEhQO9FJBG4YSUB+s/KtBN0AQIIIJQIBAwSQABBADFYfixtEQFegi1KNqFqI6BDCMkvgJwr15z3ZW3+YggCEMgkwP5HVUDADAF6zwx3VoWAIkD/UQcQyCSAAEJVQMAgAQQQBBCD5cfSFhHgJdiiZBOqdgJpIaT29dek63Zv5vMJINve/JZM/skwKe3W2ZtRRkMAAq4JsP+5RsVACGglQO9pxYkxCHgiQP95wsVgSwgggFiSaMKMJgEEEASQaFYmXiWNAC/BScso8ZggcOesW+U7czdKry3u9658AsjWN74lXIJuIpOsaRMB9j+bsk2sUSJA70UpG/hiGwH6z7aME68bAgggbigxBgIhEUAAcf9HpJBSgFkIWEGAl2Ar0kyQIRFInwDZ8Ppr0kXjCRAlgNww+lAZNKBnSJ5jFgIQYP+jBiBghgC9Z4Y7q0JAEaD/qAMIZBJAAKEqIGCQAAIIAojB8mNpiwjwEmxRsglVG4Gw7wBRAsitPzxc9u27uzafMQQBCOxMgP2PioCAGQL0nhnurAoBBBBqAALZCSCAUBkQMEgAAQQBxGD5sbRFBPgl1KJkE2pgAjqEj7QThT6B9ZMzB8uRX9ozsM8YgAAEshNg/6MyIGCGAL1nhjurQgABhBqAAAIINQCByBFAAEEAiVxR4lAiCfBLaCLTSlAhEGiuqpKa8gppa9yixXohAeQrB+8ll37nIC1rYQQCEMgkwP5HVUDADAF6zwx3VoUAAgg1AAEEEGoAApEjgACCABK5osShRBLgl9BEppWgQiJQzBMgnUpEJv9kmJR26xxSNJiFgN0E2P/szj/RmyNA75ljz8oQoP+oAQhkEuATWFQFBAwSQABBADFYfixtEQFegi1KNqFqI6BDCGnuUiJTR/XL8CmVElF3gKjntv8eIgP6lGrzG0MQgMDnBNj/qAYImCFA75nhzqoQUAToP+oAAggg1AAEIkUAAQQBJFIFiTOJJcBLcGJTS2BFIJAWQmpff026bve24KbSTjL9rL6ZAkhbiWx985vOv98w+lAZNKCnN8OMhgAEXBFg/3OFiUEQ0E6A3tOOFIMQcE2A/nONioEWEeAEiEXJJtToEUAAQQCJXlXiURIJ8BKcxKwSUzEJKBHkrw/fIUf8e6uUeFg4pwCyrZtsXXqiY4kTIB6AMhQCHgmw/3kExnAIaCJA72kCiRkI+CBA//mAxpTEE0AASXyKCTDKBBBAEECiXJ/4lhwCvAQnJ5dEUlwCQT+DVUgAKSkRuZ87QIqbVFazigD7n1XpJtgIEaD3IpQMXLGOAP1nXcoJ2AUBBBAXkBgCgbAIIIAggIRVW9iFQEcCvARTDxDwRiCo8JFeLZsAou7/SG3pJc3LjpW9enaVSZcd5c05RkMAAq4JsP+5RsVACGglQO9pxYkxCHgiQP95wsVgSwgggFiSaMKMJgEEEASQaFYmXiWNAC/BScso8YRFQJfwUUgASV+AzgmQsDKJXQjsIMD+RyVAwAwBes8Md1aFAHsfNQCB7AQQQKgMCBgkgACCAGKw/FjaIgL8EmpRsgnVN4HmqiqpKa+QtsYtvm3sOjHXCZC0AKLGcweINtwYgkAGAfY/igICZgjQe2a4syoEEECoAQgggFADEIgcAQQQBJDIFSUOJZIAv4QmMq0EFQIBnSdAUiKyubSTTD+r706eqk9gdRRAbhh9qAwa0DOEaDAJAQiw/1EDEDBDgN4zw51VIYAAQg1AAAGEGoBA5AgggCCARK4ocSiRBPglNJFpJagQCegQQtQOt3hoD3nz8B55BRBOgISYSExbT4D9z/oSAIAhAvSeIfAsCwE+/0gNQCArAT6BRWFAwCABBBAEEIPlx9IWEeCXUIuSTahaCQQRQtQOVzG6f4Y/HU+AcAeI1nRhDAIZBNj/KAoImCFA75nhzqoQUAToP+oAApkEEECoCggYJIAAggBisPxY2iICvARblGxC1UogLYA0zJ0v0trqybYbAWSvnl1l0mVHebLLYAhAwD0B9j/3rBgJAZ0E6D2dNLEFAW8E6D9vvBhtBwEEEDvyTJQRJYAAggAS0dLErYQR4CU4YQklnNAJBDn5kXbOjQDCCZDQU8kClhNg/7O8AAjfGAF6zxh6FoYAJ0CoAQhkIYAAQllAwCABBBAEEIPlx9IWEeCXUIuSTaiBCOgQPrwIIGosd4AEShmTIZCXAPsfBQIBMwToPTPcWRUCigD9Rx1AIJMAAghVAQGDBBBAEEAMlh9LW0SAl2CLkk2ovgk0V1VJTXmFtDVu8W2j40Q3J0DU+BtGHyqDBvTUsiZGIACBnQmw/1EREDBDgN4zw51VIYAAQg1AIDsBBBAqAwIGCSCAIIAYLD+WtogAv4RalGxCDUSAEyCB8DEZApEjwP4XuZTgkCUE6D1LEk2YkSRA/0UyLThlmAACiOEEsLzdBBBAEEDs7gCiLxYBXoKLRZp1kkJAhxCSEpEpo/tnIEmlRLa+8a32fy+/YpiUduucFHTEAYFIEWD/i1Q6cMYiAvSeRckm1MgRoP8ilxIcigABBJAIJAEX7CWAAIIAYm/1E3kxCfASXEzarJUkAmkhpPb116Trdm+Ruf0EFgKIN66MhoAXAux/XmgxFgL6CNB7+lhiCQJeCdB/Xokx3gYCCCA2ZJkYI0sAAQQBJLLFiWOJIsBLcKLSSTAGCNz0ykQ5dulmOWz1VteruxVAuATdNVIGQsAzAfY/z8iYAAEtBOg9LRgxAgFfBOg/X9iYlHACCCAJTzDhRZsAAggCSLQrFO+SQoCX4KRkkjhMEbh6/p3Sv3abnP9ynWsX3AogXILuGikDIeCZAPufZ2RMgIAWAvSeFowYgYAvAvSfL2xMSjgBBJCEJ5jwok0AAQQBJNoVindJIcBLcFIySRymCCgBZN91zfK9v21sd0HtYCWf/SebXzkFkLYS2frmN9uncALEVFZZ1wYC7H82ZJkYo0iA3otiVvDJFgL0ny2ZJk4vBBBAvNBiLAQ0E0AAQQDRXFKYg0BWArwEUxgQCEZg7Pw75Atrm+XM1+tdG8opgGzrJluXnthuhztAXCNlIAQ8E2D/84yMCRDQQoDe04IRIxDwRYD+84WNSQkngACS8AQTXrQJIIAggES7QvEuKQR4CU5KJonj/7d3J1BSFWfDx58Z1mHfFQSUsAiyiGhQ0aAivlHffHGN+mI0rgiKO7ih4i5GQRSMuItGYxKzaIyKGiUIuGBcEBUQRdkEkZ0ZlgHmO0+Rbntmerm3+96uO13/OoeTSNet5VdVdE8/U1W2BK577SY58r2N8pPl2zw3gQCIZyoyIhCaAO9/odFSMAJpBVh7TBAE7Amw/uzZU3N0BQiARHdsaJkDAgRACIA4MM3pYgQE+BAcgUGgCTVSYPv6DbL+9TdkzbS3pPYOf13wGgDhCCx/ruRGwI8A739+tMiLQHACrL3gLCkJAb8CrD+/YuR3QYAAiAujTB8jK0AAhABIZCcnDSsoAT4EF9Rw0pk8CMQCHxunz5CK8vKsatxau0gmn9K62rMVVY7A4hL0rHh5CAFPArz/eWIiEwKBC7D2AielQAQ8C7D+PFOR0SEBAiAODTZdjZ4AARACINGblbSoEAX4EFyIo0qfwhAIIvARa9fGkmJ5/IRWlZpZUSFSUdZEtn42IP737AAJYyQpE4FdArz/MRMQsCPA2rPjTq0I8N7HHEAguQABEGYGAhYFCIAQALE4/ajaIQF+CHVosOlq1gJbly6VFRMmys7SsqzLSHwwVQBky+yjK5XPJeiBcFMIAkkFeP9jYiBgR4C1Z8edWhEgAMIcQIAACHMAgcgJEAAhABK5SUmDClKAH0ILcljpVAgC+dgBQgAkhIGjSARSCPD+x9RAwI4Aa8+OO7UiQACEOYAAARDmAAKREyAAQgAkcpOSBhWkAD+EFuSw0qkQBYIIhHjdAcIRWCEOJEU7L8D7n/NTAABLAqw9S/BUiwDHPzIHEEgqwBFYTAwELAoQACEAYnH6UbVDAvwQ6tBg09VABWKBkNXT3pI6O/wV7TUAwiXo/lzJjYAfAd7//GiRF4HgBFh7wVlSEgJ+BVh/fsXI74IAARAXRpk+RlaAAAgBkMhOThpWUAJ8CC6o4aQzFgSue+0mOfn1ddJ8k/coiNcACDtALAwoVTojwPufM0NNRyMmwNqL2IDQHKcEWH9ODTed9ShAAMQjFNkQCEOAAAgBkDDmFWUiUFWAD8HMCQRyE7js7VvlpNfXSPtV2z0X5DUAMnbovtK8cV3P5ZIRAQS8C/D+592KnAgEKcDaC1KTshDwJ8D68+dFbjcECIC4Mc70MqICBEAIgER0atKsAhPgQ3CBDSjdyauAHoP1whO3yX7zN0uRj5q9BkDYAeIDlawI+BTg/c8nGNkRCEiAtRcQJMUgkIUA6y8LNB4peAECIAU/xHQwygIEQAiARHl+0rbCEeBDcOGMJT3Jn0Ds/o+106ZJrR0Vviv2GgDhDhDftDyAgGcB3v88U5ERgUAFWHuBclIYAr4EWH++uMjsiAABEEcGmm5GU4AACAGQaM5MWlVoAnwILrQRpT9hCsQCHxunz5CK8vKsq/IaAGEHSNbEPIhARgHe/zISkQGBUARYe6GwUigCngRYf56YyOSYAAEQxwac7kZLgAAIAZBozUhaU6gCfAgu1JGlX0EKBBX40DbpfpFNJcXy+AmtKjWxokJky+yjK/0dd4AEOYqUhUBlAd7/mBEI2BFg7dlxp1YEVID1xzxAoLoAARBmBQIWBQiAEACxOP2o2iEBPgQ7NNh0NSuBrUuXyooJE2VnaVlWz1d9SN/d3tm3oXzQs2HGAMiY3/SUdq0aBFIvhSCAAAEQ5gACURDgs2cURoE2uCrA+nN15Ol3OgECIMwPBCwKEAAhAGJx+lG1QwJ8CHZosOlq1gJB7gDRd7eJQ9pUa0uyHSD/d2RHObzvblm3mwcRQCC1AO9/zA4E7Aiw9uy4UysCKsD6Yx4gUF2AAAizAgGLAgRACIBYnH5U7ZAAH4IdGmy6mrNAEIEQPwGQffZqIpeetHfO7aYABBCoLsD7H7MCATsCrD077tSKAAEQ5gACyQUIgDAzELAoQACEAIjF6UfVDgnwQ6hDg01XAxOIBUJWT3tL6uzwV6yfAEiRiNw7op+U1KvlrxJyI4BARgHe/zISkQGBUARYe6GwUigCngRYf56YyOSYAAEQxwac7kZLgAAIAZBozUhaU6gCfAgu1JGlX/kQuPXFG+XYGRukxUbvURA/ARDtw01n9ZK2LUvy0R3qQMApAd7/nBpuOhshAdZehAaDpjgnwPpzbsjpsAcBAiAekMiCQFgCBEAIgIQ1tygXgUQBPgQzHxDwLxDbAbJm2ltS23vsw1TkNwByzZAe0qltI/+N5AkEEEgrwPsfEwQBOwKsPTvu1IqACrD+mAcIVBcgAMKsQMCiAAEQAiAWpx9VOyTAh2CHBpuu5iyQ7ztAtMEEQHIeNgpAIKkA739MDATsCLD27LhTKwIEQJgDCCQXIADCzEDAogABEAIgFqcfVTskwA+hDg02Xc1aIIjAR6zylDtAdhbJlg9+Xq2NBECyHjYeRCCtAO9/TBAE7Aiw9uy4UysCBECYAwgQAGEOIBA5AQIgBEAiNylpUEEK8ENoQQ4rnQpQYOvSpbJiwkTZWVoWSKkpAyDb6smWj48gABKIMoUgkFmA97/MRuRAIAwB1l4YqpSJgDcB1p83J3K5JcAOELfGm95GTIAACAGQiE1JmlOgAnwILtCBpVuBCuRlB0iKAAiXoAc6lBSGQFyA9z8mAwJ2BFh7dtypFQEVYP0xDxCoLkAAhFmBgEUBAiAEQCxOP6p2SIAPwQ4NNl3NWSCIQMjW2kUy+ZTW1dpSkSIAMnbovtK8cd2c204BCCBQWYD3P2YEAnYEWHt23KkVAQIgzAEEkgsQAGFmIGBRgAAIARCL04+qHRLgh1CHBpuuBiKgQZC1L/1TNsycJcUV/ovcWFIsj5/QqtKDFRUiFWVNZOtnA6oVyA4Q/8Y8gYAXAd7/vCiRB4HgBVh7wZtSIgJeBVh/XqXI55IAARCXRpu+Rk6AAAgBkMhNShpUkAJ8CC7IYaVTIQgEsftDm5UqALJl9tFJW335r7pJ945NQ+gRRSLgtgDvf26PP723J8Das2dPzQiw/pgDCFQXIADCrEDAogABEAIgFqcfVTskwIdghwabrmYlEFTgI1a53wDIRcd3kT6dm2fVdh5CAIHUArz/MTsQsCPA2rPjTq0IqADrj3mAAAEQ5gACkRIgAEIAJFITksYUrAAfggt2aOlYAAJbly6VFRMmys7SsgBK21WE3wDI5b/aW7p3bBJY/RSEAAK7BHj/YyYgYEeAtWfHnVoR4L2POYBAcgF2gDAzELAoQACEAIjF6UfVDgnwQ6hDg01XsxKwvQPkmiE9pFPbRlm1nYcQQCC1AO9/zA4E7Aiw9uy4UysCBECYAwgQAGEOIBA5AQIgBEAiNylpUEEK8ENoQQ4rnQpBIKhAiN8dIARAQhhMikSAHSDMAQSsCfDZ0xo9FSPA7kfmAAJJBNgBwrRAwKIAARACIBanH1U7JMAPoQ4NNl0NREADIS8+ebv0+rJM6uzwV2SFiGwqKZbHT2hV6cGKChEuQfdnSW4EchXg/S9XQZ5HIDsB1l52bjyFQBACrL8gFCmj0AQIgBTaiNKfGiVAAIQASI2asDS2xgrwIbjGDh0Ntyhw3Ws3yYFzSqX3V1ukyEc7NtUvkk/2biAf9GzoOQDCJeg+gMmKgA8B3v98YJEVgQAFWHsBYlIUAj4FWH8+wcjuhAABECeGmU5GVYAACAGQqM5N2lVYAnwILqzxpDfhCsSOwVoz7S2p7XP3h7Ys2fFX+vfpdoBceHwX2bdz83A7RukIOCjA+5+Dg06XIyHA2ovEMNAIRwVYf44OPN1OK0AAhAmCgEUBAiAEQCxOP6p2SIAPwQ4NNl3NWiDM+z8yBkCO6yz7dmmRddt5EAEEkgvw/sfMQMCOAGvPjju1IqACrD/mAQLVBQiAMCsQsChAAIQAiMXpR9UOCfAh2KHBpqu+BYIKfMQqzmYHyC8HtJX/Pbi977bzAAIIpBfg/Y8ZgoAdAdaeHXdqRYAACHMAgeQCBECYGQhYFCAAQgDE4vSjaocE+CHUocGmq74Eti5dKismTJSdpWW+nkuXOWUAZGeRbPng50kfbduintx0dp/A2kBBCCCwS4D3P2YCAnYEWHt23KkVAd77mAMIEAAp6Dmwfft2mTVrlsycOVOWLFki69evl4YNG0qbNm2kf//+cvjhh0uTJk1CMdiyZYtMnz5d3nnnHfnuu+9kw4YNpq62bdvKwQcfLAMHDpT69ev7qruiokJmz54tb7/9tnzzzTeyZs0aU0br1q1l//33lyOOOEJatWrlq0zNvHDhQpk2bZp89tlnpkxNLVq0kJ49exqjLl26+C4zlwcIgBAAyWX+8CwCXgX4IdSrFPlcFAhyB0iFiGwqKZbHT6j8GUXv/6goayJbPxuQknjCiH5SUq+Wi0NAnxEITYD3v9BoKRiBtAKsPSYIAvYEWH/27Kk5ugLsAInu2Hhu2bJly+T++++XRYsWpXymadOmMnz4cOnXr5/ncr1kXLBggan7+++/T5ldJ9kll1wiXbt29VKkCUxMmjRJ5s6dmzK/BkPOOeccE7TwkjRA9PTTT8urr74qGlxJloqKiuSYY46RX//611K7dm0vxeachwAIAZCcJxEFIOBBgA/BHpDI4ryABkLWvvSybJg5U4qTf1TIaLSpfpF8sncD+aBnw0p5012AHst4zZAe0qlto4x1kAEBBLwL8P7n3YqcCAQpwNoLUpOyEPAnwPrz50VuNwQIgNTwcV69erVcd911snbtWtMT/RK/R48esvvuu5tdIJ9++qls27bNvFarVi2Tt3fv3oH0+ttvv5Ubb7xRNm/eHC+/V69e0rJlS9F2aQBDv+DXVFJSIrfeeqt07Ngxbd1lZWVyww03mF0ssaS7Mtq3by/6mu7cKC0tjb920UUXyWGHHZaxPxpQ0V0qsaQTPxaQ0SBOYgBHd5dosCgfiQBI8gCIfgm16d13pdnP/ycfw0AdERBgzMMdhCh+CHZ5zG32vSbXnantfl9PzB9E8ENXcTb3f8RW/6G9W0mfzs2S/mNQr04tqVenOP5avbq1pKRuLdm8bYds3bZDvPx380Z1K+0w2bx1h6zdtC3+fNCvp/tXLVPdmf5FzPX5TOWH2fZc6tZnXe57NnZBvP/ZNM+mz0E+Q99T/xsZpHOUygpqzINYe/l2Carv+W53rvW52m/b76m5jlu6572sP5fHPUz7KJft+pgTAIny7PTQtjFjxsgXX3xhcurxUFdddZXsueee8Sf1OKr77rvPBEI0NWrUSCZOnGiOx8ol6Y6Kyy+/XFauXGmKDeiMKQAAIABJREFU0Tq1bm1DLGlQ4e677xYNlGjSI7HGjx9vAjGpUmKgQtt6xRVXiAZVYkmP23r44YdlxowZ5q90p4aWqQGfVOnNN9+UyZMnm5c1QHTmmWeanR76pqBp586d8vLLL5sdIrHdIV4DK7kY6rOFGAAZ99GjsmHbppQ0sfGPBccSM5aUbZdec9fJ3vM3SHn92rLPPeNzJeb5PAhkGvN0TWDM8zBAIZyB7vKY2+x7Ta577zmrpNeXZbKlbrE8f2qnahN/U3mp7EyxQ7PB5h3S7/NS6bNws2yuWyxPnNBaKuTHLRr6+v6fl8Vfr3r8VNXXnzu6eTz/ljpFsmiPetLz6y1Z7/pI7EwuAZCw/zUoLhLZt0sz6dyusXy1fJN8snCt7EzY6RLE6327NpfD920j3To0Np+5EpN+xlqwZKNM+/h7+ThJ3eme1XJyfT4XX5t1u973XMZNn/XyJVCyOmyPea79zuV5+p79v1O5uNt8Nowxz3bt5dshjL7nuw/Z1Odqv22/p2YzVtk8k2r9uTzu2TgWwjOM+Y+jSACkBs/oDz/8UMaOHWt6oIEA/f/Jdlho0GDUqFHxYMXxxx8vQ4YMyannU6dOlccee8yUocEUDUI0b968Wpm6M0WDGLFdG0OHDpXBgwcnrXvx4sWmnbEghO5W6du3b7W8GrDQwM/8+fPNa4cccohceumlScssLy83x2/pjhRN6fr+zDPPyAsvvGDyaSBHA0dhH4VViAGQMe9NkPXbNvqaX4lfTtXetWlIShvUkl7jJvgqh8x2BBhzO+5+ag36h1CXx9xm3wuh7lQBgmTzOdl7Q+Lz2by+rZaI/vpD7L1Gv/+v/DW9n5VVPW+UAyC59czf0+1alsjZx3SSjrvt+oWbxStL5YlXFsny1bt2DadLVZ8N4vlMdaZ7Pde251K3633P1U6fz+b9z/aYB9HvbMug79n/O5Wtue3nwhrzbNZevi3C6nu+++G3Plf7bfs91e845ZI/2fpzedxzsazJzzLmlUePAEgNns133nmnfPTRR6YHRx55pFxwwQUpe6OXievOD026s+KRRx5JuxMjE4sGNZYuXWqynXbaaXLiiSemfOSvf/2rPPfcc+Z13Smiu0KSpUcffVRee+0181KfPn3k+uuvT1nmvHnzzPFbsR9sdFdIskve9WL2e++91+Rr0KCBPPTQQ1KvXr2k5W7dutUY6lFbmkaOHGkukA8zuR4ASfblVcybAEiYMy/Ysv18KcuYB2vvtbSgfwh1ecxt9r0Q6vYSAEn374Q+n7iDIxbIiK2FTK97XTPZ5iMA8qOcHtk17JddzF9MfnGhbC33fu9X7Nl99moqn3+zPqfnsx1Lfc5m3bbrt933XMYt8Vm/73+F0u9s/Oh79v9OZeMdhWfCHHO/ay/fHmH2Pd998VOfq/22/Z7qZ4yCyFt1/c39eq21z1JB9Icy/Au4vNZTaREA8T+PIvGE7uo499xzRXc4aLrtttukW7duKdum+c4777z4fR0aPEg8WspPp1asWGF2VcSSHi/VokWLlEXopebDhg2Lv66Xplc9skp3fVx44YXxnRpa/qGHHpq2Wbrr47vvvjN5tPxBgwZVy691xY7L0p0nugMlXdIAyb/+9S+TZeDAgTJixAg/NL7zuhoASfflVgyRAIjv6WTtAS9fyjLm1obHVBz0D6Euj7nNvhdC3ekCIF7+nai6g6Pqysr0etgrkQBIZeE6tXftrynf7v9WeQ2CnD54T3nmjW99BU9iLdDnR57aPb4Lxe/Y62/N3fPHeVbq1rbarN9m3X7HKVN+P+9/hdTvTC5VX6fv9ta637EKKn/YY+5n7QXVJ6/lhN13r+3Idz5X+237PTXf41z1Z7/3PvlK7v7D59Y+z9jov+t1urzW0409AZAaujI++eQTuf32203rdUfDk08+mXFHhwZJ5syZY57RHRu6cyOb9MYbb5h7ODTpvR56VFSmlBis0F0WumMlMS1fvlwuu+yy+F9pICLZkVqJzyQGKzRYkhiUieXTumIXxHsJqmiwRIMmmjSoE7s7JFP/sn3dtQCIly+3YpYEQLKdVfl/Lt2Xsox5/scjWY1B/xDq8pjb7Hsh1J0sQODn34lorKjUrUgZANlZJFs++HnUmx+59tWuVSTbd/gPnsQ60q5Vidx4Zs9q95Fk6qj+Ys4tUz7zdGRXqrKyrVvLs1m/zbozjUs2r3t9/yu0fvuxou/21rqfcQoybz7G3OvaC7JfXsrKR9+9tCPfeVztt+331HyPc6y+2PrTcR829nVZ/kPmI0jD+Dxjq/8u1+vyWs807gRAMglF9HW9tFuDHpq6du0aD4aka27iHRd6tJMe8ZRN0nq1fk0DBgyoFLhIVd6ECRNk1qxZ5uVf/OIX5iLyxDR79uz40VjNmjWLB1jStU+Py9JjszR16tRJ7rrrrkrZ9Sirs846K/532oZ27dql7fKyZcvM5e6xpH3Vo7PCSq4EQLL5cosASFizLvhyk30py5gH75xLiUH/EOrymNvseyHUnekOj1zmue1n9Wv6TSXFUvUSdm1XxbZ6suXjI2w30cn6rzhlb9m7QxNffZ+/eIOM//Ouu+ZySdnUrfXZrN9m3blYp3rW6/tfofXbjyV9t7fW/YxTkHnzMeZe116Q/fJSVj767qUd+c7jar9tv6fme5xj9cXW35yFq2T0g7u+h8slZft5Jpc6eTY7AZfXeiYxAiCZhCL6euJ9GV6DEIkXl7dv395cXJ5NSrx75LjjjpPTTz89YzG///3v5cUXXzT59ttvP7n22msrPaOXj2uARpPXgE7iJfC6C+bpp5+uVObChQtFL1KPJW1D3bp107ZV7wE544wz4nnuuOMO6dJl1/nVYaRCD4Bk8yV4zJkASBgzLpwyE7+UZczDMc611KB/CHV5zG32vRDqtn1HR65rKd3zm+oXySd7N5APeu66+DuWKipEKsqayNbPBoRZPWWnENi/W3MZ+v/8fZZ76B8L5cMFa3M2zaZurdRm/Tbrzhk8SQFe3/8Krd9+LOm7vbXuZ5yCzJuPMfe69oLsl5ey8tF3L+3Idx5X+237PTXf4xyrL7b+xk6ZLTPnLM+5Gdl+nsm5YgrwLeDyWs+ERQAkk1BEX9eLvfWCb03HHHOMnH322Rlb+t5778m4ceNMPq+7LJIVqkEFDS5o0p0cuqMjU3rppZfkqaeeMtmSBTgSAyQHHHCAXHXVVZmKlK+//lquueaaeD4NoNSpUyf+33pBvAZrNJWUlMiUKVMylqkZfvOb38TvStG+9u3b19NzsUyrV6/OmF/9a9WqJRoAWbVqVcb8NSnDDe+Ml/L162T/z8ukz8LNUvWCWq990atSt9Yv9pr9x3zZn5Thu65dJ5vnIeWxT9n1Rr/dqzBjXWunSLYu2s1tdbN9OkXLI2/nXzxgodQNyGRXUWHGu7gitzHf/t87AvxLVH8iXZOLMvXHcwN0vu/qd859r+W50kr/xgVR9w4/dcfsEvqc7TyMFZXt81mI5e0R7v/IG7XvihqV1PJ8DJYeHbBp8w7fdaR6wE/dWobN+m3WHRh4lYKKpMjcg6Vp586dUqH/gFdJhdhvr5703d5a9zpGQefL15h7WXtB9y1Tefnqe6Z25Pt1V/tt+z013+OcWJ+uv6KiIllfui2wZvj9PBNYxRTkWSDItV5cJDLh4v2lpF5tz/VHPWPr1q0zXh2Rjz4UVehIkTwLZLMLIzEgUL9+/XhAwnOl/814xRVXyNKlS81/6cXq//M//5OxiMTjqjp06BAPxMQezGZHi7ZB2xJLjz32mDRu3Dj+3xog0kCRpqZNm8ojjzySsZ2a4fzzz5f169ebvFr+QQcd5Om5WKZTTjklY/4HH3xQWrZsmTFfTcuwbe1amXL3SOk2b13WgY+a1mfaiwACCCCAgAoQAGEeIIAAAggggAACCCCAQCEI/O6qQdJhtx+/Yy2EPkWhDwRAfI7CLbfcInPnzjVPnXTSSXLqqadmLEHz63Oa9DehnnvuuYzPJMtw8cUXy8qVK81Lw4YNk0GDBmUs580334xfKK7bjiZOnFjpGQ0IvPXWW+bvBg4cKCNGjMhYprZB2xJLVYMK06dPl0mTJpmXNdigr3tJw4cPl9guDm2HtsdPcjUAUrroG5l7wxjZvnGTHy7yIoAAAgggUBACBEAKYhjpBAIIIIAAAggggAACzguMu3SgdOvY3HmHoAEIgPgUZQeImF0oUdwB4vIRWNvXr5d/TrlL9p63XuoEt6Pc5+ogOwIIIIAAAvkVSHsB+s4i2fLBz/PbIGpDAAEEEEAAAQQQQAABBLIUuOWcPtK2ZUmWT0fvMY7Ait6YeGoRd4BIZO8A8TSA/81UqJegmztAviiT3l9uzjoQsrlesdQ94yQ/nJXzFuXrhPkf6wm2yuDa76ukLDrx0rdvSUVpmez97VbpvHSr1NYLXLJIOuYlZ5+WxZMZeugLIIvqUz4SXMXVhsXnOBVLkTRp2tS0dMP69UnPQE/ejeR9+Pui16SidLN0/2aLdF6Sw5jXL5aG5/7a89n8nkYnI3vGDGmr+etXU8181753ybHvjYb+xlOXYpl21V0q3RflXnfjob/x5f7nr141dffQuhdnP+bltUT0PpZs/53wBZbHzFyAnkdsn1XpGcbDjusi9ep4u/hma/kOefCFhXq1Vc7Jb91aoc36bdadM3aKAvQM9BYtWphX16xZY+5YqZoKsd9ePem7vbXudYyCzpevMfey9oLuW6by8tX3TO3I9+uu9tv2e2q+xzmxPl1/DRo1kTueeF92Wvo8Y7P/rtYd6FovLpLxF+4nJfW8fX6uCeZcgl4TRilJG7O5M2Pq1Kmi92Roat++vYwfPz6r3mez+yTxkvP99ttPrr322kp1v/DCC6KXmGtKdkl6soZ++OGHMnbsWPNSvXr15Omnn66UTS9q10vMY0nbULdu3bR93rp1q5xxxhnxPHfccYd06dIlKycvDxVqAGT9to2m+w0278g6EFLaoJb0GjfBCyN5LAuMeW+CMOaWByFD9Xrs4e67725yrVixwlwEm0tyecxt9r0Q6tZjop47unnW7w25zNswn+X4qzB1cyt7/27NZej/8/dZ7qF/LJQPF6zNrWIRyaZurdRm/Tbrzhk8SQFe3/8Krd9+LOm7vbXuZ5yCzJuPMfe69oLsl5ey8tF3L+3Idx5X+237PTXf4xyrL7b+xk6ZLTPnLM+5Gdl+nsm5YgrwLeDyWs+ERQAkk1BEX3/55ZflySefNK3zGjDQAIMGGjT1799fRo4cmVXvtF6tX9OAAQPksssuy1jOhAkTZNasWSbfL37xCznzzDMrPTN79my5++67zd81a9ZMHn744YxlJl6s3qlTJ7nrrrsqPVNWViZnnXVW/O+0De3atUtb7rJly+Tyyy+P59G+NmjQIGNbss1Q6AGQmEs2gRACINnOqvw/l/ilLGOef38vNQb9Q6jLY26z74VQd2KgIJv3Bi/zPd950h5/VSGyZfbR+W4S9SUIXHHK3rJ3hya+TOYv3iDj/zzf1zPJMmdTt5Zjs36bdecMnqQAr+9/hdZvP5b03d5a9zNOQebNx5h7XXtB9stLWfnou5d25DuPq/22/Z6a73GO1Rdbf3MWrpLRD+76Hi6XlO3nmVzq5NnsBFxe65nECIBkEoro65988oncfvvtpnW6+0G/qK9VK/3WpNtuu03mzJljnjnxxBPltNOyOWpG5I033ogHKDSgoIGFTOnSSy+V7777zmS74IIL5Mgjj6z0yPLlyysFUjQAooGQdOmhhx6Sf/3rXybLoYceKpdcckm17FrX2rW7fqtH23DIIYekLXPGjBly//33mzy6XX7y5MmZupbT664EQGJIfr7sIgCS09TK68PJvpRlzPM6BBkrC/qHUJfH3GbfC6HuZDsl/Lw3ZJzsFjKkOv5Km1LB/R85jUjtWkWyfUf2Zze0a1UiN57Z09dxb2bcKirklimfyfLVm7Nuf7Z1267fdt+zBk/xoNf3v0Lrtx9H+m5vrfsZpyDz5mPMva69IPvlpax89N1LO/Kdx9V+235Pzfc4x+qLrT8d92FjX5flP9j5PGOr/y7X6/JazzTuBEAyCUX09S1btsi5554r5eXlpoUa3OjWrVvK1mq+8847TzZv3vUP34033ii9evXKqncayNBgQixpIKJ58+Ypy9LzdocNGxZ/XQMMsaNYYn+pi/TCCy+U2AXiXoIViUEVLX/QoEHV2qB1aVBD0+DBg2Xo0KFp+6yBFw3waBo4cKCMGDEiKyOvD7kWAIm5ePmyiwCI11lkP1+6L2UZc/vjoy0I+odQl8fcZt8Loe5UR0XpPPXy3rCt9q47ROrsSL62Mr0e5IqM1bWlbrE8fkKrakXrVQMVZU1k62cDgqy2RpVVp/auO3fKt/sPYtSrUyynD95TnnnjW9la7v/YPn1+5KndpeNuDbMyW7yyVO754zwrdWuDbdZvs+6sBivNQ37e/wqp334d6bu9te53rILKH/aY+1l7QfXJazlh991rO/Kdz9V+235Pzfc4V/3Z771PvpK7//C5tc8zNvrvep0ur/V0Y08ApAavjMS7ODJ9uZ+4s6Fhw4aid4hk2jGSjuaKK66QpUuXmixDhgyR448/PmX2v/3tb/KHP/zBvN6xY0e55557kuZNvNdk3333ldGjR6csc8GCBXL99deb1/WCp0ceeUSaNKl+vME777wjemG8Ju23BmtS3QOybds2szultLTU5L/yyivlwAMPDHWGuBoAiaGm+7KLAEioUy/Qwr18KcuYB0ruu7Cgfwh1ecxt9r0Q6k4XAPHy70SmO0Qyve578aR5IFbXPl9vkQ96Vv6S3dyzvLNYtvznf4KsskaVpQGIYb/cdffG5BcX+vrBO/bsPns1lc+/WZ/T87mg2axb222zfpt15zJmVZ/1+/5XKP3OxpC+Z//vVDbeUXgmzDH3u/by7RFm3/PdFz/1udpv2++pfsYoiLxV19/cr9da+ywVRH8ow7+Ay2s9lRYBEP/zKDJPJF4CXrt2bXMHRocOHaq1Ty/2HjVqlLn4VpMGKzRokUt69dVX5fHHHzdFNG7cWMaNG5f0yKp169aJBks2bdpk8p5//vly1FFHJa168eLFpp26G0STBjj69OlTLa9e3nvTTTfJvHnzzGvp7iHRnS96NFZsZ0m6o7+effZZ+fvf/27KbN26tdx3332irmEm1wMgMdtkgRACIGHOvGDL9vOlLGMerL3X0oL+IdTlMbfZ90Ko20sAJN2/E5nuEMn0etUdIlX/Wz+B7NqzIGJe2ylSp8rmg0w7P0R3fjge/NDjn84+ulN894X+JtoTryzydKRU1Wd1LHJ93uu/lcny2azb9b7nMm6xZ7N5/7M95kH0O9sy6Hv2/05la277ubDGPJu1l2+LsPqe7374rc/Vftt+T/U7TrnkT7b+XB73XCxr8rOMeeXRIwBSk2eziIwZM0a++OIL0wv90v7qq682uyxiaePGjeaL/NjdH40aNZKJEyea3RBV0/fff1/pyCctu2fPnkmFtm/fbi4LX7lypXldLyHX4EWrVj8eAbFq1Spzsfk333xj8rRt21bGjx+fdufJpEmTZPr06Sa/BlY0eJLYBj36S3d7vP322yaPBii0zKpHaiU2+s0334zf5aFvBL/5zW/k6KOPjp8HrQEVDehMmTIlHny56KKL5LDDDgt9dhRiAGTcR4/Khm27Al7JUmznkfa9aiop2y49P1sn3edtkPL6tWWfe8aHPgZUkLtApjFPVwNjnru/lxKC/iHU5TG32feaXHe3Oauk15dlsrVusTx/aqdq03ZTeans/O8vQFR9UYPk/b4old5fbhY9buqJE1pLhUYZ/psSg+jJjqOq+vpzRzeX/b8oi5eX+N9b6xTJgr3qV39twWapKN51/JbWoc8k2/lRq6hY2jXcTS7tfZY8+MKXMveb1O+HXtZukHmKi4ukb+em0nmPxvLVsk3y8cK1sjPhZKogXt+vSzM5rG8b6da+cbV7N/QXXBYs3SjTPv5ePv6yet3pnlWHXJ/PxdJm3a73PZdx02ezff+zPea59juX5+l79v9O5eJu89kwxjzbtZdvhzD6nu8+ZFOfq/22/Z6azVhl80yq9efyuGfjWAjPMOY/jiIBkBo+o3Vnw3XXXRe/6FuPg9pnn31EB3bDhg3y6aefiu4A0aRfPGve3r17J+21nwCIFqCBDb1LRIMSsfK1bL08XNs1d+5ciX3JXVJSIrfeemul4EyyRpSVlckNN9wgS5Ysib/ctWtXad++vehrWmbsiCrNoPeGHH744RlHMTGwopk1YKLl6j8GX375ZTyQo69peVpuPlIhBkDSuXn9ILx9/QbZ9O670uzn7h4dko/5F6U6GPNwR8Pr2gu3FZVLd3nMbfa9Jtedqe1+X6+aP/G/U73W6KCDfL8/fbOiVD76ulQWfLtWSsu2SIP6taV1s3rStFFdqV1cJHVqF5u/a1RSW+rWKTY7UGI7UWL/W7dOLdFjoWKpft1aon+2bNth/nj572aN6kpJvVrxMjZv3SHrNm2LPx/06+n+PclUd6Z/i3J9PlP5YbY9l7r1WZf7no1dEO9/Ns2z6XOQz9D31P9GBukcpbKCGvMg1l6+XYLqe77bnWt9rvbb9ntqruOW6/cuLo97mPZRLtv1MScAEuXZ6bFty5YtM7s8Yjstkj2m92Pol/r9+vVLWarfAIgWpHdx6EXj+myqpJPs4osvTntJe+Kzemm6Biw02JEq1a9fX84++2w54ogjPCnpjpWnnnpKpk6dGt/lUfVBDR7pzpAzzjgj9KOvYnUTAPF/qamnAScTAghUEqiJP4QyhAgUigDrr1BGkn7URAHWX00cNdpcCAKsvUIYRfpQUwVYfzV15Gh3mAIEQMLUzWPZ+gX/zJkzzR/dPbF+/XpzzFWbNm2kf//+JlCQ7JLwxCZmEwDR53UHyL///W/RC8e/++470WO39PgqPfLq4IMPNkdJacDCT9KdGe+//7456mrRokWid4loGXrE1v777y+DBg2qdNyW17IXLlwoeiTW559/Lhpo0aQ7VnTXjJbZpcuuyzrzlQiAEADJ11yjHrcF+BDs9vjTe7sCrD+7/tTutgDrz+3xp/f2BFh79uypGQHWH3MAgeoCBECYFQhYFCAAQgDE4vSjaocE+BDs0GDT1cgJsP4iNyQ0yCEB1p9Dg01XIyXA2ovUcNAYxwRYf44NON31JEAAxBMTmRAIR4AACAGQcGYWpSJQWYAPwcwIBOwJsP7s2VMzAqw/5gACdgRYe3bcqRUBFWD9MQ8QqC5AAIRZgYBFAQIgBEAsTj+qdkiAD8EODTZdjZwA6y9yQ0KDHBJg/Tk02HQ1UgKsvUgNB41xTID159iA011PAgRAPDGRCYFwBAiAEAAJZ2ZRKgKVBfgQzIxAwJ4A68+ePTUjwPpjDiBgR4C1Z8edWhFQAdYf8wCB6gIEQJgVCFgUIABCAMTi9KNqhwT4EOzQYNPVyAmw/iI3JDTIIQHWn0ODTVcjJcDai9Rw0BjHBFh/jg043fUkQADEExOZEAhHgAAIAZBwZhalIlBZgA/BzAgE7Amw/uzZUzMCrD/mAAJ2BFh7dtypFQEVYP0xDxCoLkAAhFmBgEUBAiAEQCxOP6p2SIAPwQ4NNl2NnADrL3JDQoMcEmD9OTTYdDVSAqy9SA0HjXFMgPXn2IDTXU8CBEA8MZEJgXAECIAQAAlnZlEqApUF+BDMjEDAngDrz549NSPA+mMOIGBHgLVnx51aEVAB1h/zAIHqAgRAmBUIWBQgAEIAxOL0o2qHBPgQ7NBg09XICbD+IjckNMghAdafQ4NNVyMlwNqL1HDQGMcEWH+ODTjd9SRAAMQTE5kQCEeAAAgBkHBmFqUiUFmAD8HMCATsCbD+7NlTMwKsP+YAAnYEWHt23KkVARVg/TEPEKguQACEWYGARQECIARALE4/qnZIgA/BDg02XY2cAOsvckNCgxwSYP05NNh0NVICrL1IDQeNcUyA9efYgNNdTwIEQDwxkQmBcAQIgBAACWdmUSoClQX4EMyMQMCeAOvPnj01I8D6Yw4gYEeAtWfHnVoRUAHWH/MAgeoCBECYFQhYFCAAQgDE4vSjaocE+BDs0GDT1cgJsP4iNyQ0yCEB1p9Dg01XIyXA2ovUcNAYxwRYf44NON31JEAAxBMTmRAIR4AACAGQcGYWpSJQWYAPwcwIBOwJsP7s2VMzAqw/5gACdgRYe3bcqRUBFWD9MQ8QqC5AAIRZgYBFAQIgBEAsTj+qdkiAD8EODTZdjZwA6y9yQ0KDHBJg/Tk02HQ1UgKsvUgNB41xTID159iA011PAgRAPDGRCYFwBAiAEAAJZ2ZRKgKVBfgQzIxAwJ4A68+ePTUjwPpjDiBgR4C1Z8edWhFQAdYf8wCB6gIEQJgVCFgUIABCAMTi9KNqhwT4EOzQYNPVyAmw/iI3JDTIIQHWn0ODTVcjJcDai9Rw0BjHBFh/jg043fUkQADEExOZEAhHgAAIAZBwZhalIlBZgA/BzAgE7Amw/uzZUzMCrD/mAAJ2BFh7dtypFQEVYP0xDxCoLkAAhFmBgEUBAiAEQCxOP6p2SIAPwQ4NNl2NnADrL3JDQoMcEmD9OTTYdDVSAqy9SA0HjXFMgPXn2IDTXU8CBEA8MZEJgXAECIAQAAlnZlEqApUF+BDMjEDAngDrz549NSPA+mMOIGBHgLVnx51aEVAB1h/zAIHqAgRAmBUIWBQgAEIAxOL0o2qHBPgQ7NBg09XICbD+IjckNMghAdafQ4NNVyMlwNqL1HDQGMcEWH+ODTjd9SRAAMQTE5kQCEeAAAgBkHBmFqUiUFmAD8HMCATsCbD+7NlTMwKsP+YAAnYEWHt23KkVARVg/TEPEKguQACEWYGARQECIARALE4/qnZIgA/BDg02XY175J57AAAgAElEQVScAOsvckNCgxwSYP05NNh0NVICrL1IDQeNcUyA9efYgNNdTwIEQDwxkQmBcAQIgBAACWdmUSoClQX4EMyMQMCeAOvPnj01I8D6Yw4gYEeAtWfHnVoRUAHWH/MAgeoCBECYFQhYFCAAQgDE4vSjaocE+BDs0GDT1cgJsP4iNyQ0yCEB1p9Dg01XIyXA2ovUcNAYxwRYf44NON31JEAAxBMTmRAIR4AACAGQcGYWpSJQWYAPwcwIBOwJsP7s2VMzAqw/5gACdgRYe3bcqRUBFWD9MQ8QqC5AAIRZgYBFAQIgBEAsTj+qdkiAD8EODTZdjZwA6y9yQ0KDHBJg/Tk02HQ1UgKsvUgNB41xTID159iA011PAgRAPDGRCYFwBAiAEAAJZ2ZRKgKVBfgQzIxAwJ4A68+ePTUjwPpjDiBgR4C1Z8edWhFQAdYf8wCB6gIEQJgVCFgUIABCAMTi9KNqhwT4EOzQYNPVyAmw/iI3JDTIIQHWn0ODTVcjJcDai9Rw0BjHBFh/jg043fUkQADEExOZEAhHgAAIAZBwZhalIlBZgA/BzAgE7Amw/uzZUzMCrD/mAAJ2BFh7dtypFQEVYP0xDxCoLkAAhFmBgEUBAiAEQCxOP6p2SIAPwQ4NNl2NnADrL3JDQoMcEmD9OTTYdDVSAqy9SA0HjXFMgPXn2IDTXU8CBEA8MZEJgXAECIAQAAlnZlEqApUF+BDMjEDAngDrz549NSPA+mMOIGBHgLVnx51aEVAB1h/zAIHqAgRAmBUIWBQgAEIAxOL0o2qHBPgQ7NBg09XICbD+IjckNMghAdafQ4NNVyMlwNqL1HDQGMcEWH+ODTjd9SRAAMQTE5kQCEegoqJCdu50KwhQq1Ytg6nBHxICCORPgLWXP2tqQqCqAOuPOYGAPQHWnz17anZbgLXn9vjTe7sCrD+7/tQePQENDBYVFVlvWFGFfhNMQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQKSIAASAENJl1BIJWA7vpYt26deblZs2YS+60ExBBAIFwB1l64vpSOQDoB1h/zAwF7Aqw/e/bU7LYAa8/t8af3dgVYf3b9qR2BdAIEQJgfCDggsHr1ahk+fLjp6YMPPigtW7Z0oNd0EQH7Aqw9+2NAC9wVYP25O/b03L4A68/+GNACNwVYe26OO72OhgDrLxrjQCsQSCZAAIR5gYADArwROzDIdDGSAqy9SA4LjXJEgPXnyEDTzUgKsP4iOSw0ygEB1p4Dg0wXIyvA+ovs0NAwBIQACJMAAQcEeCN2YJDpYiQFWHuRHBYa5YgA68+RgaabkRRg/UVyWGiUAwKsPQcGmS5GVoD1F9mhoWEIEABhDiDgggBvxC6MMn2MogBrL4qjQptcEWD9uTLS9DOKAqy/KI4KbXJBgLXnwijTx6gKsP6iOjK0CwEhAMIkQMAFAd6IXRhl+hhFAdZeFEeFNrkiwPpzZaTpZxQFWH9RHBXa5IIAa8+FUaaPURVg/UV1ZGgXAgRAmAMIOCHAG7ETw0wnIyjA2ovgoNAkZwRYf84MNR2NoADrL4KDQpOcEGDtOTHMdDKiAqy/iA4MzUJACIAwCRBwQoA3YieGmU5GUIC1F8FBoUnOCLD+nBlqOhpBAdZfBAeFJjkhwNpzYpjpZEQFWH8RHRiahQABEOYAAm4I8EbsxjjTy+gJsPaiNya0yB0B1p87Y01PoyfA+ovemNAiNwRYe26MM72MpgDrL5rjQqsQUIGiioqKCigQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgUISIABSSKNJXxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMAIEABhIiCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDBCRAAKbghpUMIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBAAIQ5gAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgUnQACk4IaUDiGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAABEOYAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIFJwAAZCCG1I6hAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgRAmAMIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQcAIEQApuSOkQAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIEABhDiCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDBCRAAKbghpUMI7BLYvn27zJo1S2bOnClLliyR9evXS8OGDaVNmzbSv39/Ofzww6VJkyZwIYBAgAI7d+406+2rr76K//n2229lx44dppZ99tlHbrrppgBrpCgEEIgJfP/99zJnzhz5/PPPzTr84YcfZMuWLVK/fn1p2bKldOvWTQ499FCzDkkIIBCMwKZNmyq95+m627Bhg/lTVFRkPnt27NjRrLvDDjtMWrRoEUzFlIIAAhkFnnzySXn55Zfj+Vq3bi0PPPBAxufIgAACmQWmTZsmv/vd7zJnTMhx6qmnykknneTrGTIjgEAwAgRAgnGkFAQiJbBs2TK5//77ZdGiRSnb1bRpUxk+fLj069cvUm2nMQjUVIH3339fJk6cKFu3bk3ZBQIgNXV0aXeUBfS97pFHHpGFCxd6ambPnj3loosuklatWnnKTyYEEEgtMHbsWPnwww89EdWuXVuOP/54Ofnkk6W4uNjTM2RCAIHsBPQ9cfTo0VJRUREvgABIdpY8hUAyAQIgzAsEapYAAZCaNV60FoGMAqtXr5brrrtO1q5da/Lqb9/16NFDdt99d7ML5NNPP5Vt27aZ12rVqmXy9u7dO2O5ZEAAgfQCXj4EEwBhFiEQvIDudLzvvvsqFdy2bVvp0KGD2elYWloqCxYsEH1/jKXmzZvLLbfcIrvttlvwDaJEBBwSSAyA6C/X7LHHHia4WK9ePfMLAStWrDA7RGI7IZVGd4JoEJKEAALhCOhJANdcc40sXry4UgUEQMLxplQ3BRJ/9tP3vl69emWE2H///aVv374Z85EBAQSCFyAAErwpJSJgVWDMmDHyxRdfmDboh9yrrrpK9txzz3ib9EgC/aJIAyGaGjVqZH5rXY8oICGAQPYCsQ/B+gVQ586dpUuXLuZ/P/nkk/jxAwRAsvflSQRSCcQCIBroHzRokAwcOLDaMTt6PJ2u0SeeeCK+S6tr165y2223mV8UICGAQHYCL774ojRo0ED69OljjllNltatW2fW3jvvvBN/+YorrpCDDjoou0p5CgEE0gr85S9/kT/+8Y8mjx79OGPGjPjPhhyBxeRBIBiBxAAIgf1gTCkFgTAFCICEqUvZCORZQI8g0N/E06THDOj/13OXqyY9E33UqFGycuVK85IeRzBkyJA8t5bqECgsAf2CR3/jruqxOn/605/k+eefN50lAFJYY05voiGgd37o/R8a+Mh0rI4eVXfPPffEG667IPlNvGiMI60obAE9hkd3XX322Wemoxowuf766wu70/QOAQsCehSy/gJceXm5CX7oWovdU8AOEAsDQpUFK0AApGCHlo4VqAABkAIdWLrlpsCdd94pH330ken8kUceKRdccEFKiLffftvs/NCku0D0/HQ9EouEAALBChAACdaT0hDIVUCDHrH7Qo4++mg555xzci2S5xFAwIPA9OnTZdKkSSZn48aN5bHHHvPwFFkQQMCrgAYab7zxRpk/f77Z3T9hwgTzsyEBEK+C5EPAuwABEO9W5EQgCgIEQKIwCrQBgQAEdFfHueeea37bR5Me69GtW7eUJWu+8847TzZv3mzy6IdlL+dWBtBUikDAKQECIE4NN52tAQJTpkyRf/7zn6alehbz1VdfXQNaTRMRqPkCH3/8sdxxxx2mI7pT+dlnn635naIHCERIYOrUqfHA4rBhw8yxkIlf0rIDJEKDRVNqvAABkBo/hHTAMQECII4NON0tXAG9Z+D22283HdSLJ5988smMOzo0SDJnzhzzzIknniinnXZa4QLRMwQsCRAAsQRPtQikEHjqqafkpZdeMq/ut99+cu2112KFAAJ5ENDAowYgNbVt29bcSUdCAIFgBFavXi16t47+cluPHj3kpptuMndcEQAJxpdSEKgqQACEOYFAzRIgAFKzxovWIpBS4OWXXzZBD016sWssGJKO7JlnnpEXXnjBZOnfv7+MHDkSYQQQCFiAAEjAoBSHQI4CicH/wYMHy9ChQ3MskccRQCCTwJo1a0SPn9P/1cT9c5nEeB0BfwJ696PeB6m7q377299K+/btTQEEQPw5khsBrwKJa+uAAw4wd+4sXbpUysrKpEGDBtKiRQvp3r17fC16LZd8CCAQjgABkHBcKRWBvAs8+uij8tprr5l6BwwYIJdddlnGNiRuk9YPyePHj8/4DBkQQMCfAAEQf17kRiBMgR9++EFGjBghO3fuNNXob8sedNBBYVZJ2Qg4K7Bt2zb5/vvvzR0EL774oqxfv95Y6O4PvbdOvyAiIYBA7gIzZ86M76g66aST5NRTT40XSgAkd19KQCCZQOLaSifUsWNHc9qGfkdDQgABewIEQOzZUzMCgQrce++98s4775gyjznmGDn77LMzlv/ee+/JuHHjTL5mzZrJww8/nPEZMiCAgD8BAiD+vMiNQJgC+p6n732aWrVqZb4wqlOnTphVUjYCzgjMmzfP3CmXLvXt21cuueQSadSokTMudBSBMAU2btxogvkaYNTg4j333FPpfY0ASJj6lO2ygNcASMzo8MMPlwsuuCDjMeUum9J3BMIUIAASpi5lI5BHAf1NOv0NO03HHXecnH766Rlr1/z6nKb69euLnotOQgCBYAUIgATrSWkIZCtQ9QdV/RJWjysgIYBAMALpAiANGzaUc889lzUXDDWlIBAXmDRpkkyfPt38twYge/XqVUmHAAiTBYFwBHRtPf/882ZnR+/evc1RV40bN5bt27eL7jj++OOPRY8p1/8fS0cddZScf/754TSIUhFAIK0AARAmCAIFInDLLbfI3LlzTW+qbn1O1UXNr89pKi4ulueee65ANOgGAtERIAASnbGgJe4KfPXVV+aLofLycoPg9ahId8XoOQL+BVauXCkvvfSSebCiokK2bNkiy5cvl0WLFsmOHTvM3/fs2dN8+dOuXTv/FfAEAghUEvjkk0/i9z4edthhctFFF1UTIgDCpEEgHIHS0lIpKSkx36OkSps3bza7jfV+nli6+eabpUePHuE0ilIRQCClAAEQJgcCBSLADpACGUi6UXACBEAKbkjpUA0T0DsIrr/+elm3bp1puZ7FrMF/7h+oYQNJc2usgF58rr9ko1/EatLdIGPGjJG99tqrxvaJhiNgW0ADjFdeeaWsWrXK/Na5HofcpEmTas0iAGJ7pKjfdQG9D2vUqFHy3XffGYp+/frJNddc4zoL/Ucg7wIEQPJOToUIhCPAHSDhuFIqArkKEADJVZDnEcheYO3atWbnh/5muqbddtvNBD+aN2+efaE8iQACWQk88cQT8sorr5hn99hjD3MPXbrfnM2qEh5CwBGBJ5980hyvo+nCCy8UvV8gWSIA4siEoJuRFnjzzTdl8uTJpo316tWTxx9/nDvoIj1iNK4QBQiAFOKo0icnBR599FF57bXXTN+9Hu0xdepUeeyxx8wzembl+PHjnbSj0wiEKUAAJExdykYgtYBeDHvTTTfJkiVLTCYNetx6663Spk0b2BBAwILA1q1bZejQoaJHgmi6+uqrZf/997fQEqpEoGYLfP3113Lttdeao+b0WDndUZUqEQCp2WNN6wtDQHdqJR5RN2HCBI6CLIyhpRc1SIAASA0aLJqKQDoB/Q0g/U0gTV27do2fB5vumWeeeUZeeOEFk6V///4ycuRIkBFAIGABAiABg1IcAh4EysrKTLBD7/7QpMeDaDCkQ4cOHp4mCwIIhCVwxx13mIthNR1//PEyZMiQsKqiXAQKViAxqKE7G5MdfRXr/IYNG+K7IGvXri2dOnWKu+i9kXocDwkBBMIV0IvRE9/vbrvtNunWrVu4lVI6AghUEiAAwoRAoEAEEi/B022VGgypVatW2t7pG++cOXNMnhNPPFFOO+20AtGgGwhER4AASHTGgpa4IaDnot9+++0yf/5802G9oFJ/O/YnP/mJGwD0EoEIC+hlsDNnzjQtPPLII+WCCy6IcGtpGgLRFEgMgOTSwnRHZ+VSLs8igEBlgU2bNsk555wT/8u7775b9txzT5gQQCCPAgRA8ohNVQiEKaBf+Jx77rlSXl5uqsn0WwWa77zzzosfQ6BnpPfq1SvMJlI2Ak4KEABxctjptCUBvWhy7NixMnfuXNMC/YWA0aNHS/fu3S21iGoRQCBR4Oabb5bPPvvM/NVxxx0np59+OkAIIOBTgACITzCyI2BZQD+X6h10saTHl6fbuWW5uVSPQEEKEAApyGGlU64K3HnnnfLRRx+Z7g8ePNics5wqzZgxQ+6//37zcsOGDUXfhDPtGHHVlX4jkIsAAZBc9HgWAe8CeryA/kZd7H2wTp065o6BPn36eC+EnAggEJqA3sszbNiw+C/r8NvnoVFTMAJxAe4AYTIgYF9g4sSJ8vbbb5uG7LHHHnLvvffabxQtQMAxAQIgjg043S1sgQ8//ND85qsmPeP1rrvuSnreuV5COWrUKFmxYoXJyxnMhT0v6J1dAQIgdv2p3Q2BnTt3il4o+e6775oOa0D/yiuvlAMOOMANAHqJgAUBPdKjUaNGnmrWy5r1+KtZs2aZ/BqgnDx5srmfh4QAAuEJEAAJz5aS3RXQ0zfq16/vCeD999+XcePGib4PatJjx/X4cRICCORXgABIfr2pDYHQBfSc8y+++MLU07p1a/Pbrx07dozXq799pz+Axu7+0B9c9TcSdBcICQEEghcgABK8KSUikCigP1A++OCDol/yaCoqKpJLLrlEDjnkEKAQQCBEgX/+85+iO4qPPvpo+elPfyoNGjRIWtu3334rv//970Xvq4sl7p4LcWAoGoEEAQIgTAcEghfQdfXaa6+Z9z/9ZZtk73+bN28WfZ/8y1/+Ijt27DCNaNmypdn94TV4EnzLKREBdwUIgLg79vS8QAVWr14t1113naxduzb+RdA+++wju+22m2zYsEE+/fRT0R0gmvQ3ZDVv7969C1SDbiGQXwE9hm7NmjWVKl23bp2sX7/e/J3eR7D77rtXa9S1114rLVq0yG9jqQ2BAhGYOnWqPPbYY/HetG3b1vOxV/rb56ecckqBSNANBPIroF/sTJkyJf6Zsl27dqJ/9JdqNBCpv3SzePHi+I7jWOsOPPBAueyyyzh6Nb/DRW2OChAAcXTg6XaoAonrSr9Tad++vejnT33/02CHfiezYMGC+Pcu2hh9Te/BSvzl1FAbSeEIIFBJgAAIEwKBAhRYtmyZ2eXxzTffpOydXrqlZy/369evAAXoEgJ2BC666CJZtWqV78onTZokbdq08f0cDyCAgEjiLiu/HrpT8oEHHvD7GPkRQEDE/Par3iHnNZWUlMivfvUrOfbYY6W4uNjrY+RDAIEcBAiA5IDHowikEEhcV16QevXqJcOHDzcndJAQQMCOAAEQO+7UikDoAnoZ7MyZM82fJUuWmN9A19860C9Z+/fvL0cccYRoEISEAALBCRAACc6SkhDwKkAAxKsU+RAIXmD58uVmd/GXX34pS5culR9++EFKS0tNRXokSLNmzWSvvfYyu40POuggjv0IfggoEYG0AgRAmCAIBC9QXl4uX331ldnloX9Wrlwpei+W7nzUo1n1/U93/Xft2tUcydq5c+fgG0GJCCDgS4AAiC8uMiOAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBNECAAUhNGiTYigAACCCCAAAIIIIAAAggggAACCCCAAAIIIICALwECIL64yIwAAggggAACCCCAAAIIIIAAAggggAACCCCAAAI1QYAASE0YJdqIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACvgQIgPjiIjMCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjUBAECIDVhlGgjAggggAACCCCAAAIIIIAAAggggAACCCCAAAII+BIgAOKLi8wIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQEwQIgNSEUaKNCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg4EuAAIgvLjIjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBATRAgAFITRok2IoAAAggggAACCCCAAAIIIIAAAggggAACCCCAgC8BAiC+uMiMAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACNUGAAEhNGCXaiAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAr4ECID44iIzAggggAACCCCAAAIIIIAAAggggAACCCCAAAII1AQBAiA1YZRoIwIIIIAAAggggAACCCCAAAIIIIAAAggggAACCPgSIADii4vMCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggUBMECIDUhFGijQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIOBLgACILy4yI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAQE0QIABSE0aJNiKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggIAvAQIgvrjIjAACCCCAAAIIIIAAAlUFvv/+exkxYoT569atW8sDDzwAEgJGYOHChTJ69GipqKiQs846S4499tiClSkvL5fLLrtMVq1aJX369JHrr7++YPtKxxBAAAEEEEAAgZoiQACkpowU7UQAAQQQQAABBBBAIAuBm266ST7//POkT9apU0caNGggJSUl0rRpU+nUqZP506tXLxPI8JoIgHiVciufBj00+KFBkDZt2siECROkdu3aBY0wffp0mTRpkunjyJEjpX///gXdXzqHAAIIIIAAAghEXYAASNRHiPYhgAACCCCAAAIIIJCDQLoASKpii4qKZN9995VjjjlG9ttvv4y15zMA8qc//Umef/5506aTTz5ZTjnllIztI4MdgRkzZsj9999vKh86dKgMHjzYTkPyWOvOnTvNLpAVK1ZI27Zt5d5775Xi4uI8toCqEEAAAQQQQAABBBIFCIAwHxBAAAEEEEAAAQQQKGCBxABI586dpUuXLvHe6m/ol5WVSWlpqSxdutQc3VM1DRw4UM455xyzUyRVIgBSwBMoy65pIODyyy+X7777Tpo1a2aORdMdRy6k119/XR555BHT1eHDh8sRRxzhQrfpIwIIIIAAAgggEEkBAiCRHBYahQACCCCAAAIIIIBAMAKJAZBMOybWrVsneoTPK6+8IqtXr443QI/FuuWWW6RevXrBNCqHUtgBkgNeHh999913Zfz48abGE088UU477bQ81m63qq1bt5odL5s3b5Y99tjDOOiuKhICCCCAAAIIIIBA/gUIgOTfnBoRQAABBBBAAAEEEMibgJ8ASKxRW7Zskd/97neiX2LH0oEHHihXXnll3tqdqiICINaHwFMDbrjhBpk/f7754n/ixInmDhCX0sMPPyxvvPGG6fJ1110nffv2dan79BUBBBBAAAEEEIiMAAGQyAwFDUEAAQQQQAABBBBAIHiBbAIg2go9Huuuu+6SDz/8MN6oMWPGSM+ePYNvpI8SCYD4wLKUdfny5eYeDE1du3aV22+/3VJL7FU7d+5cs2tK08EHH2yOAyMhgAACCCCAAAII5F+AAEj+zakRAQQQQAABBBBAAIG8CWQbANEGbtq0SS666CJzlI+m3r17i/5mf9Xk5w6QH374Qd566y3RL4j1i3K9f6R27drSuHFjadKkiXTo0EH69Olj/uh/x5Kfy9wPO+ww0+7EtG3bNvn4449NvYsWLTKXVGv/tG6tR4/56tevn+idJ/p36dJnn30mN998s8myzz77iLZNk5atv/W/cOFCWbt2rTkyTPujX4DrBeCZyk2sU48j+/e//y1z5swxThs2bDAvx4w0EKXlZtpZsX37dpk1a5Z88MEH8vXXX5tyNLil5WhwYsCAAfLTn/400COaEoNUQ4YMkeOPP97XfP/oo49k9uzZZgeJOur8U8vddttN9B4bHaf99ttPatWqVancVOPy/vvvy7Rp0+Sbb74RdS0pKZG9995bfvnLX0r37t0rlVFeXi4zZ8409uquc0TvMNl3333lhBNOkNatW3vqi96Bct5555nn9e6TRx991NRLQgABBBBAAAEEEMivAAGQ/HpTGwIIIIAAAggggAACeRXIJQCiDX388cfl1VdfNW3W44wee+wxadSoUaU+eA2A6OXQU6ZMEQ1GZEr6BfWtt94az5ZLAOTLL780ZenRXpmSfsE9cuRIExBJlap+0X799dcbp9iRR8me0/JGjx5dKaiTLJ9+cf7Xv/5VXnjhBdG7JNIlHY9x48ZJ+/btk2bTdk6ePFlWrlyZthwNhOjxZi1atMjE4+n1q6++2gSZNN1xxx3SpUsXT88tWbLEHL321VdfZcyvgZvYLpNY5qrjcs0115jL1997772k5amf3tVx5JFHmtf1wnbd9aSBj2Spfv365jirqkGTVI397W9/awJPmnRO9e/fP2O/yIAAAggggAACCCAQrAABkGA9KQ0BBBBAAAEEEEAAgUgJ5BoA+eKLL0SPvoqlUaNGmR0DiclLAER/C/+ee+6JP6a/Dd+tWzdp2bKlFBcXS1lZmfkCWr8E110LVQMgL7/8snldd1fEviDX3QDJvlzXL/R1J0cs6c4P/SJeU9OmTU3AQOvVXQUaZNAAgZa7Y8cOk0fbpl+E77777knHsuoX7boLQ3cY6BfqWne7du3MLgsNvCR+ma67Fq699tqU80ODH3phtlrFku4aUScNzOiOB93BoEAaOzkAABWGSURBVMEF3RmhSb9k32uvvaqV+c4778j9998f75PuQoiVo95quWDBgvjr6nHnnXea3Q65JN1hcv7555v+161bV5566ikzvpmSmmpfYruNNH+rVq3M+GrATYNX2mbdxaHjdMABB8hVV11Vqdiq46J90d0vatijRw9jqPNMd+rozgxNOma6Rtq2bSsaMFmzZo00bNjQ5Ne5ov+t+XVniCbdOTNhwoRqQcBk/fvHP/4hTz/9tHnpqKOOMi4kBBBAAAEEEEAAgfwKEADJrze1IYAAAggggAACCCCQV4FcAyAaIDjrrLPiX5TrcUZ6rFFi8hIA0cDJt99+ax47+uij5fTTTzcBiKpJv+jWI5D0uCbNUzVlcweIBiL0N/EPOeQQ6dixY1L/9evXmy+rp0+fbl5PddyXvpb4RbsGFvTLcQ3GjBgxQvbYY494+RoEeOWVV+TJJ5+M/52Ohx6blSw988wzZudHLKnTKaeckvTLdg3Y6M6c4447zhyzlZg0iKQ7FWI7SI499lg5+eSTq5WjgR/dITFv3jzzeKYAjZeJq3fGjB071mT9yU9+Ev//6Z7VY9F018jGjRtNNg0o6fFRyS4O18CFBnf0CLMzzjijUrGJ46JBDw2kaSDj4osvNsGUWNIgyN13323GUZMeJ6ZBL50jaq7zW3d7xNKyZcvMfR6xoNOvfvUr0T+Zkh5fdtttt5lsugNIg2okBBBAAAEEEEAAgfwKEADJrze1IYAAAggggAACCCCQV4FcAyDaWL1PY9WqVabdRxxxhAwfPrxSHzIFQDSoceaZZ5pndKeBHnOkv3mfTcomAOKnHt0FoQEYTbobI9nxUolftGs+3T2gX24nfmmeWKeW8+6775q/SrUTQHeK6EXZGjTRlM3dGbE69ct63bWg6bTTTpMTTzwxJYGOje5K0S/5NemF5bqLJdv097//XZ599lnz+KGHHiqXXHJJxqJ0p8qMGTNMPt2loW3IZidK1XHRYJSOi+5EqZo06KKBkdiuH3190KBBMmzYsKTt1fZpOzVpuffee2/Gfq1evTq+VnT3jga4vOyGyVgwGRBAAAEEEEAAAQQ8CxAA8UxFRgQQQAABBBBAAAEEap5AEAGQxN0beo+B3meQmDIFQPQYodgXy3pckx51lG0KOwCiRybpEUeazj77bDnmmGOqNbXqF+16f8aBBx6YsksaUNHAiqZUuyIeeeQR0TtSNGkAQncOZBMk0iOiYkdDaWBGv6jP9KW7Xvp93333mbp1B8Q555yT7fDIww8/HL8LRXenJNvFk1i4zg0NsMUCEbpzJdnODy8Nqjou6qBHZaVKerSbHvGmSXfyPPjggynvaNF7a3Q+6G4fHRfd1ZPpUnPtkwayYkEt3W3j9RJ1L/0lDwIIIIAAAggggEBmAQIgmY3IgQACCCCAAAIIIIBAjRUIIgByww03yPz5841BsqOhMgVA9CgiPUZLv0TWL+NvvPHGlMdAZYLONQCix0LpkViLFy8Wva9C75zQuzdiSb+Qnz17tvnPZLtd9O+rHoGlF7vrkUupkt7boZdta2rcuLG5SL5qStxlozsTfvazn2WiSPr63/72N/nDH/5gXtOdH7oDJFPS479i91PkelRT4sXfv/71r+WXv/xl2ur17hTdEaRJAzaxQEymNid7PXFcdNeHBinSjcujjz4qr732mimqT58+opfZp0tXXHGFLF261GTR+2xSHaeWWIYGk2L3jeS6uyYbE55BAAEEEEAAAQRcFyAA4voMoP8IIIAAAggggAACBS0QRAAk1x0gCpx4zJEeB3TQQQeZP3ofhgYFvKZsAyD6JfQf//hHc8dH4kXb6epNdtG25k/8on3PPfc090mkSxoAit2bon2PBShizyQGSPTvJk+eLC1atPBKUimfHvn0n//8x/xdr169Kt1JkqpA3aEQCwSkCtB4bcytt94qn376qcmuX/7rjpJ0KXHny5FHHikXXHCB16qq5fM7Ls8995z89a9/NeXoPSkapEuXEgOBesxY9+7dM7ZVdz5pUE2TBv50TEgIIIAAAggggAAC+RMgAJI/a2pCAAEEEEAAAQQQQCDvAkEEQBJ3JyS7JyHTDhDttO4y0LbE7pqIQehxQu3atTOXVetv4ffr1y/pnQ2x/NkEQPT+Ej3uSO998JP0cmx9rmpK/KJd233zzTdnLFYvM0/sQ+IDejm8Bpk06VFMeldEtumaa64xF8hnm3SHjgYGsk1+AyC6k+L999831eVy74k+73dc/M6lxLWk80LnR6akAZ3Y5ekEQDJp8ToCCCCAAAIIIBC8AAGQ4E0pEQEEEEAAAQQQQACByAjkGgDRS7L1N+Njx0QlO1bJSwBEQbSsf/zjH+aOiNiXwlWhGjZsKHp3hB6dlOzuCr9fWmv5ib+5r/c26E6Dfffd1xy51KRJExNwidWV+CW67k5Rv6rJS56qz6QLgMybN8/sDtCU6w4MvXR8xYoVOc0/Nc42+T0Cy2/AJF27/I6L37mUTQCEI7CynUk8hwACCCCAAAIIBCNAACQYR0pBAAEEEEAAAQQQQCCSArkGQD7//PNKQQDdYaC7NBKT1wBI7BkNpixatMhcQK1/NACwcePGSmXq8VO6K6LqReB+v7TWu0s0AKJJgx933HFH2mOhPvjgg/gl7fkKgAS5AyTxuDL9/z/96U/zOi8TL0HXIJbeA5IuhbUDJNXYJbbF71zyGwCpegm63nXSqlWrvI4HlSGAAAIIIIAAAq4LEABxfQbQfwQQQAABBBBAAIGCFsg1AJJ4UbQGIx5//HHRXRq5BECqgmtAZMGCBWZ3SOwCcs2jl07rPSG5fGn9/PPPS2xHg95Hob+Rny69+uqrpo+a8hUAqXoHyEMPPSTNmzfPal7qRduffPKJedbLJeRZVZLmob///e/y7LPPmhyHHnqo6I6UdCnxDpDBgwfHL4vPpl1R2wGiR65deOGFpit694sebZZsV1M2feUZBBBAAAEEEEAAAW8CBEC8OZELAQQQQAABBBBAAIEaKZBLAGTDhg0yYsQIc3SVpv3220+uvfbaag5+d4CkgtTLuHWHRuwL/IEDB5r6E9Of//xn0T+aTj75ZEk8WipZuYlfsJ9//vly1FFHpR3H8ePHy7vvvmvy5CsAonUl3rNy8cUXy89+9rOs5pte9P6Xv/zFPNu7d+/47pesCsvioY8++kjuvPNO8+RPfvITGTt2bNpSpk2bJrozQpMeSXbfffdlUeuuR6IWAJkzZ47cdtttpm2dOnUSvaCehAACCCCAAAIIIJBfAQIg+fWmNgQQQAABBBBAAAEE8iqQbQBEgxH65bV+oR1Lt9xyi3Tv3r1a+4MKgGjBr7zyijzxxBOmDr2nY/To0ZXqS9xhcMIJJ8j//d//pfVM3MFy5plnyi9+8YuU+desWSMafCgvLzd58hkASWxnt27dRO/GqHr8l5eJs3DhQrnuuutMVn3+7rvvlo4dO3p5NJA8GjTTQJPOH71bZcqUKWb3Q6qk5hr80eOiNGnb+/btm1VbohYA0R1NTz/9tOmLBt7UhYQAAggggAACCCCQXwECIPn1pjYEEEAAAQQQQAABBPIqkE0ARHd8PPjgg/LOO+/E25ruOKNMAZDNmzdLnTp1pHbt2hn7rl8Y6xfHmpLV+a9//Uv0iChNhx12mPnyPF1K/BI63b0QegyXXuD94YcfxovLZwBk+fLlcvnll5vAgaYhQ4bI8ccfn9ErWYabb77Z7IbQtOeee4r+d4MGDTKWtX37drPbp1GjRhnzpstw9dVXmzteNOmRXF27dk1b3v333y8zZswweVq3bm2eadasme82RC0Akngh/MiRI6V///6++8QDCCCAAAIIIIAAArkJEADJzY+nEUAAAQQQQAABBBCItICfAIjeRTF9+nSzC2P16tXxfukX2GPGjDG/0Z8sZQqA6BfTerSR3vFw8MEHS4cOHaoVowGImTNnyuTJk+M7MPT+CA2CJKYvv/wyvitEvySfMGFC2i/3ly1bZu4SiQUWdAfIaaedVqkv2m+9vFsvQK9Xr55s3brVVJnPAIjW9/vf/15efPHFeHf1zhI94itZQEJ3ekydOlX0ovGqnosXL5brr78+fnRZu3btzN0nffr0STp+K1askFmzZpnyhg4dKvvvv39OczrxcnHdoaM7ddIlvStDgyYbN2402dq0aSPnnXde0p0gpaWlJjCnba56wXqUAiA6n7UPmzZtMsE/3eFTUlKSkysPI4AAAggggAACCPgXIADi34wnEEAAAQQQQAABBBCoMQKJAZDOnTtLly5d4m3XoEBZWZn5s3TpUtFARtV0xBFHyNlnny3169dP2WcvARDdhRBLTZs2NXciaABDL4XWAITuGFi7dm08T48ePUzQpeql0frFst4Lol+aa9Iy9Iv9Jk2axJ/VPg4YMCD+35MmTTKBnVjSC8bVQp9ZtWqVfPHFF6K7H/QLav1SXe8N0ZTvAIgeA3XPPffIf/7zn3hbddfM3nvvbXZGJLPSXQZ77bVXtbHRMjQ4FAvmaIaWLVvG+6391eOqvv3220rBLg1E5BoA0d0sl112mWmTjoXe65Ipffrpp+a4rth9M5pf+6zjpAEg/fvvvvtOvvnmG3Nc1gEHHCBXXXVVpWKjFACZO3eu6JFxmg466CAThCMhgAACCCCAAAII5F+AAEj+zakRAQQQQAABBBBAAIG8CSQGQLxWqndH6D0M//u//5ty10BiWZkCILpr48Ybb4zf85CpHfqF8fDhw1P+xrweUzVu3Lj4TpGq5VU9GkuDABpYiF2unqx+DQ5ceumlpo2xYE2+AyDaLg3w6EXmL730Usr+xdqvARF12GOPPZKSarBAd9R8/fXXmcjN6xpwGDVqVNKAiqcCEjLpeM+bN8/8jQagdFdHpqTtfeCBB0xQJlNKdjxalAIgGkR7/fXXTTdyudckkwOvI4AAAggggAACCKQXIADCDEEAAQQQQAABBBBAoIAF0gVAdHeB7nrQ+yF0J4XuJNDfuO/Vq5e0atXKs0qmAIgWpEcB6W/565fi+kW3HmGkf6df+GsbdtttN3NXxMCBAyvtUknViCVLlsirr75qytPdILpDIHbMVbK7QbQevWfi3//+t6lfd73oDhD9Yv7AAw+Uww8/3Ow08PIlupc8VdutR1nFkh4RlSlpn6ZNm2bM1Ep3a+hl4rp7pn379tK7d2+zy6VFixaZijKBn9mzZ8v8+fNFLx3XvuvYa//1eCx11wvn9fL1bC5eT9aAd999V8aPH29eOvHEE82xY16SjqG29f333xcNnOnuIA1gxeaI7ijRHSra3qq7g/yOS+JRXSeffLI5bixdSlxLujupZ8+eSbNrey+44ALjrMEpdQjK1YsheRBAAAEEEEAAAQR+FCAAwmxAAAEEEEAAAQQQQAABBBAIVEADTnrskx6HpcE13dmhd2G4kN544w1zp4ymYcOGyaBBg1zoNn1EAAEEEEAAAQQiKUAAJJLDQqMQQAABBBBAAAEEEEAAgZotoJfa33fffaYTern64MGDa3aHPLReAz+XX365ua+kbdu2cu+991bbqeKhGLIggAACCCCAAAIIBCRAACQgSIpBAAEEEEAAAQQQQAABBBD4UUCPsxo9erQsXLjQHDWml7Lr0VuFnKZPn27uPNE0cuRI6d+/fyF3l74hgAACCCCAAAKRFyAAEvkhooEIIIAAAggggAACCCCAQM0U0OCHBkE0GHLWWWfJscceWzM74qHV27dvl0svvVRWrVpl7mi54YYbPDxFFgQQQAABBBBAAIEwBQiAhKlL2QgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGBFgACIFXYqRQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgTAFCICEqUvZCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYEWAAIgVdipFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBMAUIgISpS9kIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgRYAAiBV2KkUAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIEwBQiAhKlL2QgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGBFgACIFXYqRQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgTAFCICEqUvZCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYEWAAIgVdipFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBMAUIgISpS9kIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgRYAAiBV2KkUAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIEwBQiAhKlL2QgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGBFgACIFXYqRQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgTAFCICEqUvZCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYEWAAIgVdipFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBMAUIgISpS9kIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgRYAAiBV2KkUAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIEwBQiAhKlL2QgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGBFgACIFXYqRQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgTAFCICEqUvZCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYEWAAIgVdipFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBMAUIgISpS9kIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgRYAAiBV2KkUAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIEwBQiAhKlL2QgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGBFgACIFXYqRQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgTAFCICEqUvZCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYEWAAIgVdipFAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBMAUIgISpS9kIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgRYAAiBV2KkUAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIEwBQiAhKlL2QgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIGBFgACIFXYqRQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgTAFCICEqUvZCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggYEXg/wPUO3I4NU6jawAAAABJRU5ErkJggg==\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract concentration data\n",
    "X_CH4 = flame.X[13]\n",
    "X_CO2 = flame.X[15]\n",
    "X_H2O = flame.X[5]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(flame.grid*100, X_CH4, '-o', label=r'$CH_{4}$')\n",
    "plt.plot(flame.grid*100, X_CO2, '-s', label=r'$CO_{2}$')\n",
    "plt.plot(flame.grid*100, X_H2O, '-<', label=r'$H_{2}O$')\n",
    "\n",
    "plt.legend(loc=2)\n",
    "plt.xlabel('Distance (cm)')\n",
    "plt.ylabel('MoleFractions');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sensitivity Analysis\n",
    "\n",
    "See which reactions effect the flame speed the most"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a dataframe to store sensitivity-analysis data\n",
    "sensitivities = pd.DataFrame(data=[], index=gas.reaction_equations(range(gas.n_reactions)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute sensitivities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the value of the perturbation\n",
    "dk = 1e-2\n",
    "\n",
    "# Create an empty column to store the sensitivities data\n",
    "sensitivities[\"baseCase\"] = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "for m in range(gas.n_reactions):\n",
    "    gas.set_multiplier(1.0) # reset all multipliers                                                                     \n",
    "    gas.set_multiplier(1+dk, m) # perturb reaction m   \n",
    "    \n",
    "    # Always force loglevel=0 for this\n",
    "    # Make sure the grid is not refined, otherwise it won't strictly \n",
    "    # be a small perturbation analysis\n",
    "    flame.solve(loglevel=0, refine_grid=False)\n",
    "    \n",
    "    # The new flame speed\n",
    "    Su = flame.u[0]\n",
    "    \n",
    "    sensitivities[\"baseCase\"][m] = (Su-Su0)/(Su0*dk)\n",
    "\n",
    "# This step is essential, otherwise the mechanism will have been altered\n",
    "gas.set_multiplier(1.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>baseCase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2 O + M &lt;=&gt; O2 + M</th>\n",
       "      <td>0.00156775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H + O + M &lt;=&gt; OH + M</th>\n",
       "      <td>0.00110824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H2 + O &lt;=&gt; H + OH</th>\n",
       "      <td>0.0252473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HO2 + O &lt;=&gt; O2 + OH</th>\n",
       "      <td>0.00313172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H2O2 + O &lt;=&gt; HO2 + OH</th>\n",
       "      <td>0.000752237</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          baseCase\n",
       "2 O + M <=> O2 + M      0.00156775\n",
       "H + O + M <=> OH + M    0.00110824\n",
       "H2 + O <=> H + OH        0.0252473\n",
       "HO2 + O <=> O2 + OH     0.00313172\n",
       "H2O2 + O <=> HO2 + OH  0.000752237"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sensitivities.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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 â‰¥ 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reaction mechanisms can contains thousands of elementary steps. Choose a threshold\n",
    "# to see only the top few\n",
    "threshold = 0.03\n",
    "\n",
    "firstColumn = sensitivities.columns[0]\n",
    "\n",
    "# For plotting, collect only those steps that are above the threshold\n",
    "# Otherwise, the y-axis gets crowded and illegible\n",
    "sensitivitiesSubset = sensitivities[sensitivities[firstColumn].abs() > threshold]\n",
    "indicesMeetingThreshold = sensitivitiesSubset[firstColumn].abs().sort_values(ascending=False).index\n",
    "sensitivitiesSubset.loc[indicesMeetingThreshold].plot.barh(title=\"Sensitivities for GRI 3.0\",\n",
    "                                                          legend=None)\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "plt.rcParams.update({'axes.labelsize': 20})\n",
    "plt.xlabel(r'Sensitivity: $\\frac{\\partial\\:\\ln{S_{u}}}{\\partial\\:\\ln{k}}$');\n",
    "\n",
    "# Uncomment the following to save the plot. A higher than usual resolution (dpi) helps\n",
    "# plt.savefig('sensitivityPlot', dpi=300)"
   ]
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}