Visualization and Statistical Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Visualization and Analysis for hybrid perovskite single crystal data\n",
    "    ## Author: Zhi Li\n",
    "    ## Version 1.1\n",
    "    ## 10-28-2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, fnmatch\n",
    "import matplotlib as mpl\n",
    "import math\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.font_manager import FontProperties\n",
    "from scipy.spatial import ConvexHull\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection\n",
    "from matplotlib.colors import Normalize\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy.spatial.distance import pdist, cdist, squareform\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn import tree\n",
    "from sklearn.externals.six import StringIO\n",
    "from IPython.display import Image  \n",
    "from sklearn.tree import export_graphviz\n",
    "import pydotplus\n",
    "import optunity\n",
    "import optunity.metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What amines we have tried?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['N,N-Dimethylethane- 1,2-diammonium iodide', 'Pyridinium Iodide', 'n-Butylammonium iodide', 'neo-Pentylammonium iodide', 'Pyrrolidinium Iodide', 'iso-Butylammonium iodide', '4-Fluoro-Phenylammonium iodide', 'Acetamidinium iodide', 'N-propylammonium Iodide', 'Piperidinium Iodide', 'n-Octylammonium Iodide', 'Ethane-1,2-diammonium iodide', 'Imidazolium Iodide', 'N,N-dimethylpropane- 1,3-diammonium iodide', 'Dimethylammonium iodide', 'Phenylammonium Iodide', '4-Trifluoromethyl-Phenylammonium iodide', '4-Fluoro-Benzylammonium iodide', 'Methylammonium iodide', 't-Butylammonium Iodide', '4-Fluoro-Phenethylammonium iodide', 'N,N-Diethylpropane-1,3-diammonium iodide', 'Di-isopropylammonium iodide', 'Benzylammonium Iodide', 'n-Dodecylammonium iodide', 'Formamidinium Iodide', '4-methoxy-phenethylammonium-iodide', '4-Methoxy-Phenylammonium iodide', 'Piperazine-1,4-diium iodide', '1,4-Benzene diammonium iodide', '4-Trifluoromethyl-Benzylammonium iodide', 'Propane-1,3-diammonium iodide', 'Phenethylammonium iodide', 'Guanidinium iodide', '2-Pyrrolidin-1-ium-1-ylethylammonium iodide', 'tert-Octylammonium iodide', 'iso-Pentylammonium iodide', 'Morpholinium Iodide', 'i-Propylammonium iodide', 'n-Hexylammonium iodide', 'Cyclohexylammonium iodide', 'Ethylammonium Iodide', 'Butane-1,4-diammonium Iodide', 'Diethylammonium iodide', 'Cyclohexylmethylammonium iodide']\n",
      "************************************************************************************************************************\n",
      "Number of amines: 45\n"
     ]
    }
   ],
   "source": [
    "file = \"0042.perovskitedata_RAPID.csv\" # data file, 26 amines\n",
    "df=pd.read_csv(file)\n",
    "Inchi = pd.read_csv(\"Organic Inchikey.csv\")\n",
    "Inchidict = dict(zip(Inchi['Chemical Name'], Inchi['InChI Key (ID)']))\n",
    "\n",
    "Amine_done = []\n",
    "for i in df['_rxn_organic_inchikey']:\n",
    "    if i not in Amine_done: \n",
    "        Amine_done.append(i)\n",
    "Amine_number = len(Amine_done)\n",
    "for i in range(Amine_number):\n",
    "    Amine_done[i] = dict(zip(Inchi['InChI Key (ID)'],Inchi['Chemical Name']))[Amine_done[i]]\n",
    "print (Amine_done)\n",
    "print ('*'*120)\n",
    "print ('Number of amines:', Amine_number)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function for basic data analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function for specific amine, crystal class\n",
    "def per3D(points, amine = None, category = None, \\\n",
    "          dim = ['_rxn_M_inorganic', '_rxn_M_organic', '_rxn_M_acid']):\n",
    "    if amine is not None: amine = Inchidict[amine]\n",
    "    if amine is None:\n",
    "        if category is None:\n",
    "            All_points = np.zeros((points.shape[0], 4))\n",
    "            for i in range(3):\n",
    "                All_points[:,i] = points[dim[i]]\n",
    "            All_points[:,3] = points['_out_crystalscore']\n",
    "        else:\n",
    "            All_points = np.zeros((points[points['_out_crystalscore'] == category].shape[0], 4))\n",
    "            for i in range(3):\n",
    "                All_points[:,i] = points[dim[i]][points['_out_crystalscore'] == category]\n",
    "            All_points[:,3] = points['_out_crystalscore'][points['_out_crystalscore'] == category]    \n",
    "    else:\n",
    "        if category is None:\n",
    "            All_points = np.zeros((points[points[\"_rxn_organic_inchikey\"] == amine].shape[0], 4))\n",
    "            for i in range(3):\n",
    "                All_points[:,i] = points[dim[i]][points[\"_rxn_organic_inchikey\"] == amine]\n",
    "            All_points[:,3] = points['_out_crystalscore'][points[\"_rxn_organic_inchikey\"] == amine]\n",
    "        else:\n",
    "            All_points = np.zeros((points[points[\"_rxn_organic_inchikey\"] == amine][points['_out_crystalscore'] == category].shape[0], 4))\n",
    "            for i in range(3):\n",
    "                All_points[:,i] = points[dim[i]][points[\"_rxn_organic_inchikey\"] == amine][points['_out_crystalscore'] == category]\n",
    "            All_points[:,3] = points['_out_crystalscore'][points[\"_rxn_organic_inchikey\"] == amine][points['_out_crystalscore'] == category]\n",
    "    \n",
    "    return All_points\n",
    "\n",
    "\n",
    "\n",
    "def plot3d2d (point, x_range = [0, 2], y_range = [0, 5], z_range = [0, 10.5], xy_loc = -3, xz_loc = 0.1, yz_loc = -0.5,\\\n",
    "              x_step = 0.5, y_step = 1, z_step = 2, elev = 45, azim = -70):\n",
    "    %matplotlib notebook\n",
    "    xy_plane = z_range[0] + xy_loc\n",
    "    xz_plane = y_range[1] + xz_loc\n",
    "    yz_plane = x_range[0] + yz_loc\n",
    "    # 3D plot\n",
    "    color_type = ['blue', 'green','orange','red']\n",
    "    color_type_2D = ['navy', 'darkgreen','orange','darkred']\n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111, projection='3d')\n",
    "    for i in range(1,5):\n",
    "        s = 5 if i == 4 else 5\n",
    "        ax.scatter(point[:,0][point[:,3]==i], point[:,1][point[:,3]==i], point[:,2][point[:,3]==i],\\\n",
    "                   c = color_type[i-1], s = s, alpha=0.5)   \n",
    "    # 2D projections plot\n",
    "    for i in range(1,5):\n",
    "        s = 3 if i == 4 else 3\n",
    "        arf = 0.2 if i == 4 else 0.1\n",
    "        ax.scatter(point[:,0][point[:,3]==i],point[:,2][point[:,3]==i], \\\n",
    "                   marker = 'o', c = color_type_2D[i-1], s = s, zdir = 'y', zs = xz_plane, alpha=arf)\n",
    "        ax.scatter(point[:,1][point[:,3]==i], point[:,2][point[:,3]==i], \\\n",
    "                   marker = 'o', c = color_type_2D[i-1], s = s, zdir = 'x', zs = yz_plane, alpha=arf)\n",
    "        ax.scatter(point[:,0][point[:,3]==i], point[:,1][point[:,3]==i], \\\n",
    "                   marker = 'o', c = color_type_2D[i-1], s = s, zdir='z', zs = xy_plane, alpha=arf)\n",
    "    # make 2D planes with meshgrid\n",
    "    # yz plane\n",
    "    yy, zz = np.meshgrid(np.arange(y_range[0],y_range[1]+y_step, y_step), np.arange(z_range[0],z_range[1]+z_step,z_step))\n",
    "    xx = np.ones((len(np.arange(z_range[0],z_range[1]+z_step,z_step)), len(np.arange(y_range[0],y_range[1]+y_step, y_step))))*yz_plane\n",
    "    ax.plot_surface(xx,yy,zz, color = \"silver\", alpha = 0.1)\n",
    "    ax.plot_wireframe(xx,yy,zz, color = \"black\", alpha = 0.1)\n",
    "    # xy plane\n",
    "    xx, yy = np.meshgrid(np.arange(x_range[0],x_range[1]+x_step, x_step), np.arange(y_range[0],y_range[1]+y_step, y_step))\n",
    "    zz = np.ones((len(np.arange(y_range[0],y_range[1]+y_step, y_step)), len(np.arange(x_range[0],x_range[1]+x_step, x_step))))*xy_plane\n",
    "    ax.plot_surface(xx,yy,zz, color = \"silver\", alpha = 0.1)\n",
    "    ax.plot_wireframe(xx,yy,zz, color = \"black\", alpha = 0.1)\n",
    "    # xz plane\n",
    "    xx, zz = np.meshgrid(np.arange(x_range[0],x_range[1]+x_step, x_step), np.arange(z_range[0],z_range[1]+z_step,z_step))\n",
    "    yy = np.ones((len(np.arange(z_range[0],z_range[1]+z_step, z_step)), len(np.arange(x_range[0],x_range[1]+x_step, x_step))))*xz_plane\n",
    "    ax.plot_surface(xx,yy,zz, color = \"silver\", alpha = 0.1)\n",
    "    ax.plot_wireframe(xx,yy,zz, color = \"black\", alpha = 0.1)\n",
    "    # set axis, limit.\n",
    "    ax.set_axis_off()\n",
    "    ax.view_init(elev=elev, azim=azim)\n",
    "    ax.set_xlim(yz_plane, x_range[1])\n",
    "    ax.set_ylim(y_range[0],xz_plane)\n",
    "    ax.set_zlim(xy_plane,z_range[1])\n",
    "    plt.savefig('Graphs/Outcome_plot_'+ amine_name + '.svg', format = \"svg\", transparent=True)\n",
    "\n",
    "\n",
    "    \n",
    "# Check if point is in convexhull\n",
    "def point_in_hull(point, hull, tolerance = 1e-12):\n",
    "    return all((np.dot(equ[:-1],point) + equ[-1] <= tolerance) for equ in hull.equations)\n",
    "\n",
    "\n",
    "# Generate meshgrid points of certain size and location\n",
    "def gridgen(n=20,x=3,y=4,z=10, plot = False):\n",
    "    a = np.linspace(0,x,n)\n",
    "    b = np.linspace(0,y,n)\n",
    "    c = np.linspace(0,z,n)\n",
    "    points = np.zeros((n*n*n,3))\n",
    "    xv,yv,zv = np.meshgrid(a,b,c)\n",
    "    if plot: \n",
    "        fig = plt.figure()\n",
    "        ax = fig.add_subplot(111, projection='3d')\n",
    "        ax.scatter(xv, yv, zv, c = 'coral', s = 5)\n",
    "    for i in range(n*n*n):\n",
    "        points[i] = [xv.flatten()[i], yv.flatten()[i], zv.flatten()[i]]\n",
    "    return points\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['N,N-Dimethylethane- 1,2-diammonium iodide', 'Pyridinium Iodide', 'n-Butylammonium iodide', 'neo-Pentylammonium iodide', 'Pyrrolidinium Iodide', 'iso-Butylammonium iodide', '4-Fluoro-Phenylammonium iodide', 'Acetamidinium iodide', 'N-propylammonium Iodide', 'Piperidinium Iodide', 'n-Octylammonium Iodide', 'Ethane-1,2-diammonium iodide', 'Imidazolium Iodide', 'N,N-dimethylpropane- 1,3-diammonium iodide', 'Dimethylammonium iodide', 'Phenylammonium Iodide', '4-Trifluoromethyl-Phenylammonium iodide', '4-Fluoro-Benzylammonium iodide', 'Methylammonium iodide', 't-Butylammonium Iodide', '4-Fluoro-Phenethylammonium iodide', 'N,N-Diethylpropane-1,3-diammonium iodide', 'Di-isopropylammonium iodide', 'Benzylammonium Iodide', 'n-Dodecylammonium iodide', 'Formamidinium Iodide', '4-methoxy-phenethylammonium-iodide', '4-Methoxy-Phenylammonium iodide', 'Piperazine-1,4-diium iodide', '1,4-Benzene diammonium iodide', '4-Trifluoromethyl-Benzylammonium iodide', 'Propane-1,3-diammonium iodide', 'Phenethylammonium iodide', 'Guanidinium iodide', '2-Pyrrolidin-1-ium-1-ylethylammonium iodide', 'tert-Octylammonium iodide', 'iso-Pentylammonium iodide', 'Morpholinium Iodide', 'i-Propylammonium iodide', 'n-Hexylammonium iodide', 'Cyclohexylammonium iodide', 'Ethylammonium Iodide', 'Butane-1,4-diammonium Iodide', 'Diethylammonium iodide', 'Cyclohexylmethylammonium iodide']\n"
     ]
    }
   ],
   "source": [
    "print (Amine_done)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
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       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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jMe99lKA+GU5kTgZj7mnqxhPAhIg43lfdVUiIAIiMBQESqUSDg4OwD8XFhYQi8WGYlwahDsClUoF+/v75kuzs7MmC5bfTZYTv4mrPxEYHAEJkMGx1ZlFQAREYOIJSICMxxQYBgFyVZYT25LCFMNMPawmAiJweQISIJdnqDOIgAiIgAh0ICAB0mVq1CtA9QRo1oFQAohMA0O6wGUaXlqy2Obm5pBIJEZmzl+0nLRm7HKbSviiW5fEychMAw10yAhIgAzZDdFwREAERGCcCFCAHB4emmB0uWBduLPFHaByCDSblgCJLwOR/oO7BzlvRlmAuLGcSJwMchbp3CLwgoAEiGaDCIiApwT4ApergqdIR/pkFB7b23sol0tYXV1WDIh9N5sNoLgJVHNAOAXU8kBiDYjODOX9toUkBzc/P28KEY5788NyQguKmghMIgEJkEm867pmERgAAb6sc7kcjo+PzeKEqToVcDwA0CN0SlbR3tg4wtOnW6hWK7h5cxUrKzPyo7fvYfkAKNMCUrNESGwZCA/nwr5VgMiShZeKMA7CciJxMkIPOw3VNQEJENfI9AUREIGLBPL5PLLZLJiqk8XK6K5x69YtXLt2TbAmmECpVMPDh7vY3t5HrVbG8vIi7txZRDSqXV8zLWgFqWYBNIBgHAgPb1wFLVlHR0dm2BIg3X/UspxM8ENPl+6YgASIY1Q6UARE4CIBCo2TkxMjPLhDyg/FCFN0cpGytrYmaBNMgALks892sLm5h3q9gtXVJdy+vYhYTAJk1KZFoVAw1k22xUWKyOioXcJQjNepOAkGg8ZS2Pqx/86+kE4B8bKcDMWt1iB6EJAA0RQRARFwTYDuBplMxggOihD+SXebdDoN/hs//O/19XXX59YXxocA58QHH2zie997ZgTIm29ex+uvr8oFawRvsQTI4G+a1+KkUyHGwV+JehCB3gQkQHoz0hEiIAKnBOw4D1o5aPWgWwbFRiqVMoKDO3QUJhQlU1NTxgKivPmTO33K5RoePNjBkyfbqNWquHlzRS5YIzod+JuntZNtaWkJkUhkRK9kNIfdrzhptaS0Wk4uihNatPSsHs25MaqjlgAZ1TuncYuAzwTsOA8KDtvywSBzCo3WxYgEiM83Zoi7KxarLTEgFaysLOD27SW5YA3xPTNDq5eBRg0IRYGgJTQkQIb3plGctAbBdwqIv+jW1fr/2iwa3vs7riOTABnXO6vrEgGPCLSL8+DuGYVHu1ScrQJkdXXVWEXUJpMAXbA+/HAT9+8/Rb1exRtvXMcbb1zCBYv1MurF07oZcSAYmkywg7xqBsWzNkm9CoSTQGzRCBFmuONvm215eRmKMxjkTfDu3L3ECa3Y/Ny8edOkV5Zlyzv2OlN3AhIgmiEiIAJtCXSL86DLVSdzPbNh8YU2PT2NlZUVUxNEbTIJ0AXrs8928fDhhhEgt26t4c6dJUSjfc4Jpqyt0A2ocZq2dkkixOnUYtV1NIFgtHu19eK2lRo4lAQapbPaJBIgTkGPznEUJ3Sro7Dk81rCcnTu3TiMVAJkHO6irkEEPCTQKc6Dma1o9ehl0eBChe4arAOiF5qHN2YET0UXLAqQw8MjVColLCzMmyxY8Xgf8QNcQJe2gFoRCESAAKzFMXfp1boTqGSA6rGV9tfUG1kAAh0skxQgtICA96gBJFZNcURuLPDDpo2F8ZlwvKd8ZtOarfs6Pvd1FK5EAmQU7pLGKAI+EXAa59FtOBIgPt2sEeim0Wji6dN9PH26jWq1jOvXV3D9+gKCQaoHl40xCUUKkByM+gjFgfjKUNfOcHmFQK0A1AvW9YWnrBiMy7ZG3RJupt5IyLIYxVeBSKr9mSnwKEAaVcsKEpsHguFzAkSulZe9KcPzfVo/mOGM8Xy6r8NzXyZhJBIgk3CXdY0i0IMA4zz4IqpUKmf1PLrFeXQ7HUUMRQgtIMqWo6mXzxewsbFjMqOtrS0hlbqExYKL6OqJtZMfmQIis93diUYJPwO/SztAjUIhCETngPhyZ0uF02trFW60HLHRctRJgPDfKVqadSsAPWCJRT4f+Ltm00LVKfzhP44uWHSZpQBRIPrw369xGqEEyDjdTV2LCLgk0G+cR7duuJvGxcrs7KwKlrm8H+N4ODOmHR4emkUOg1zbJS5wdd1cUJtYhj7cuFx15PPB1Zxl4eF1mQDwKJBY9+Y6GTdTObKC920XLJcB/K0CRAtVn+fGALtjcUluDjANr+o2DRC0Tv0SAQkQTQoRmEACl43z6IaMC02+1Obm5kw1dO6sqU0uAc8FyBWirNaqyJVzaDQbSEQTSEYvYc25eB0mxmXHcpVifEZ01nIxO7VAXPqyaWGhAKFbV6f4jy6dcKec1k02CZBL342hOcHREeOzKmcWkKEZmAYy9gQkQMb+FusCReA8AbuiMReGFAtMlcpd6Yv1PPrlJgHSL7nx/N5IChAu1BmPwSBsxpoEI+Z3spvZxVHhyAiQdCyNlekVxCIeCmzGXzAGhAIhnPbG+uHRtOKmAp8dbNop9wjqEJyG1kkWleU7gK51aiLgFwEJEL9Iqx8RuGICrXEeBwcH4Icpcm/fvm2qmHvVuODkrhotIJ643Hg1MJ3nSgiMpAAx6X6ZNapmBYPHF1FrBrB5vIlStWRER7laxtrsGqbiU1fC1e9OJUD8Ju5Pf3wP1Ov1syxY/vSqXkQAkADRLBCBMSfQGudBUzstFHSloBsWU+t6HShOocNdNcaAUIAkEokxJ6zL60Zg5ASICdretCwgwZglQhJraIZT2MnsWBaQRgPpeBorUyuIR+MTMQG4qcBnB+v/0AVLbTwI7O3tGeue/S4Yj6vSVYwCAQmQUbhLGqMI9EGALxXmeKfYoImdiweKEb5oaPlgUCkXE4zTYACiV00CxCuS43GekRMgzLDFYHBm22I2KoqQBNP9JsEYkGwpexYDkop1SGU7HrfOLEwrtYr5s5ArmAx5EiBjcnNPL2N3d9fcU74XFhcXx+vidDVDTUACZKhvjwYnAv0RsDNRUXBw0WBnOWG120gkYsQIdzT54qGVwstAcVpZaNZnGl6emy82tcklMHIChLeK1g/jglUHIunxSvfrYioe5Y9wUjhBE03UCjUkQgkwPbdiBVxAHPJDd3Z2THHZVCplNqPURMAvAhIgfpFWPyLgA4F29Txo7aDwaE1/asdpcEheCxBaW/b3902fPDdfbGqTS8AWIJwT9nzgIpafoW60hDAY3WW62qG+JheDo+Vj62QLxWoRQQSRz+YxHZ0GrT4SIC5ADvmh29vbxiLOOED+PtVEwC8CEiB+kVY/IjBAAgwiZJpMLvbsOA+6TfClQgFAS0draxUgDBa/dG2GlpPT6kK/YgoQntvLAPcBItSpB0TAFiCPHz82cUG2tY1zkgsfW4zYf/Lv+FG7WgJ0N6MAyVfyCAaCKGQKRoCkE2msrKxc7eDUu2cEtra2jFWcz2k+r9VEwC8CEiB+kVY/IjAAAt3iPJhWl6b1ds2O0+D3+dLxMlBcAmQAN3qET0kBQkH67NmzcwKk2yVRnFwUJvb/XxTTI4xm6IdO96vj4jGajSZqxRqSYSt+TAJk6G+d4wFubm6aGEBuGNFtVk0E/CIgAeIXafUjAh4T6BXn0a07O06DAoS70l7GadAaw8BGCiCKG/6pNrkEWmNAOBcoJChSWz+ch04bRXU7ccKFscSJU4rOj6MrFgvPnxyfmGQWZL+8vOz8BDpyaAkwmxtdsGiVpADhR00E/CIgAeIXafUjAh4RoHiguxX/5OKOHy6+uLhzasmw4zQ4JL50vIzT4EuNgY22SV8vNY9u/IiexkkQOufMRVHC/6eYdSNOQoE6wqEwwtEEwpHImVCRS9flJw+tWHxu0F2HqbvVRp8Af198VlOA0PqhzaLRv6ejdAUSIKN0tzTWiSbgNs6jGyzbTYqLOwoEL+M0JEAmepq+dPF092NWNGZe66cwJed9J3Fy1hktKNUMUMtafxVOAdEX/uytLl0X4046uSnqLp4nIAEyfjOCvytaqylAaAn38j0wfrR0RV4TkADxmqjOJwIeE+gW58EXRj+7u7abFM/NXS8vd754Tpr1OTa+1ORX7PGEGLHTXVaAdLpczjPbSlIrF1DLPUetnEet3kAjEAFiS0Ao1pPWRZeuVoEil64X+LhQJW/GC6heRM9pNRIH0KJFYckkJHxWe2kJHwkAGuSVEpAAuVL86lwEuhO4TJxHtzPbVopBCBD2y8wqfJnxpcaP2uQSGJQAOUe0XrGql9dLAAJGgNTCi6ghbNy4+o036ZSla+hTCA9gukmADADqFZ+SbrxMj00Bwng9L2MBr/jS1P0IEJAAGYGbpCFOHoGLcR5cxHGn1k2chxMBwmMoFLyO06AFhPEoFB9K7Th587f1ir0WIMYiWMqaCt2M95iKTyEUCALVY6DC6uUAIlNAdB64kH6a/9TOpcv+O6d3qlMKYQqTcXXpYqwAOdFdRwXrnM6U4T7O/m1SgNA90mkM4XBflUY3KgQkQEblTmmcE0GAL/hMJmP85Wka539zQXPjxo229Tz6hWK7Sdm1QiRA+iWp7/Ui0CpAvEj5TPGxn91HoVJAJBTB0tQS5lJzVtHARsUaTjDaVnygmgdqOWMlQWQaCMfPhs/fQqd4E1oMnbZBpBCm2MqVcmg0G0jGkkhGk06H49lxEiCeoRyaE9kJIig8KCrtGj1DM0ANZKwJSICM9e3VxY0KgXZxHjSNU3wwhmIQlYfpJsV+aQHxOk6DixXuqvG8qq47KrNwMOP0WoAc5Y9Mgby55ByOCkeYT81jdWa19+DpplXaeRGoHpkB4itAsHdFdjvepF0wvOMsXc06mKUrFIoiHEueSyXcLYUwz7+T2THXajYMYmmsTq8iGon2vmYPj6BVk0LM3i338NQ61RURoIsvMyrynjKuh/E9aiLgFwEJEL9Iqx8R6ECgU5wHFzt84XNxMoi8+1xQcEFju0p5eYPoL86XGQWI3DW8JDt65/JagLRaQKLhKBbTi5YFpFerFYDiFoAQ0KwDwRCQWAdCl1t0OUoh3KwBpQOgUQICYYDiJ5I+N+LWSvCtdU5o9dg82TQuZ7xe/rk2u2aEiJ9NAsRP2v70lc/njZWdAoSplZliWU0E/CIgAeIXafUjAhcI9IrzODo6MjU+aAUZROVhWinsHU2v4zQoQPgyYwyIBMhkT32vBUhrDAhdsBgD4ijuokERsAtUGScSAKKzQHwZYPzIgJptMakXj1DLbaBWD6JWK6AeSAGJFce9HhWPkKvmzHVOJ6exPreOVCLl7Lod99L9QNtiyg0Lr58XHg1Rp3FJIJfLIZvNGgHCTa5JTK7gEpkO95CABIiHMHUqEXBCoDXOgyKE8R62KxRT19qpP4+Pj0HrCBcdg3DBsn26B7GgYPwKX2a0gChlp5NZMb7HXFqANBsAPw5cpXpSpBtWPW8JENYKCfq041vJAKVtoBkAUEUzPItaZBG10wxdrbEn7eJNqvUqcuWcZbGMJJCIJsyltqsKb2fu8jqF8ObmpumTmZKU2a7nTBuJAyg+aAVh7Ac3ufpJ6T4SF6pBDiUBCZChvC0a1DgSaI3z4M4oxQX/5Au9XT0P+ubyGLa1tTXPkdhpNQfh0834Fb7MGNyuqsme37qROuGlBAjdpipHlsuUXVzQgcWiXq2isLuLRr2OxNwcolNTV8usUQfKB0C9YAkpZugKtw8kb+fSZQsUx/EmdDQLhc7FmbS6ePUDQwKkH2rD/R26X/EdQwHCTS5HlsThviSNboQISICM0M3SUEeXQD/1PPhy4O4UG18OXu9o0kphFxbz2k2Kla/ttMGDiF8Z3ZkweSPvW4Awq1VxG6geca/fslYwaPxC7MRFolykH378MbLPnqFRqSCxvIyFz30O0aT/maPOjc1k6apaLl99WnMcVYXvMcX6SSFMpnTBYhtE0orJ+1UMxxVzk4sWeAqQ9fX14RiURjExBCRAJuZW60KvgkCvOI9uY6IAoY8uFww0j6mYm/AAACAASURBVHu9O0UrBSvhMlbDazcpCZCrmG3D2Wf/AqRhFResZoFgAmiUgcQaEJ3ueqG1chm7776L8skJIuk0aoUCFj//eaRXHWTKGk6EPUflVQphPmM6FV9kELoESM9bMVIHMM6Q7ygKkEFY2UcKhgbrOwEJEN+Rq8NJIOA0zqMbC/rn8kMBQiuC1/65FAlcHFKAeO0mdXh4aC6NhRMHEUA/CXNoXK6xbwFCABUWFzy2LAfhNBBf7Bm3Qber3ffeQ/b5c0Z6IDY/j8W330Zifn5ckLq6Drp0dbKcOHXp4jn4m7bdKhmE3urS5bV11tUF6uC+CfCechOKbriDiDPse2D64kQQkACZiNusi/SLAF/otFrw4yTOo9u47AwlPIYCwesMJXz5cHE4iDS/3FmzixzqxebX7BvOfi4lQOi2VC9aQeihWE/xYROg9ePkyRM0GGO1tISp69c9d2EcTtruRmULk3YCpfVMFCB02WRjzBo3Flpba9rgVguK15sm7q5OR/ciwE0o3nsKEG0U9aKlf/eagASI10R1voklwDgPWiy4o8T0uVx4sRYGA7H7ya/O+A/66HJ3kS5S/Zyj282w0/wOQoAwgxdfbAyul2l/Yn8S5sIvJUAugc5sBpxmjoqH474X7rvE0K/8qxdduuimwxgQe7HK37WT1q4qvC1QvHYpdTIeHXOeAN1wKS6ZCVGxepodfhOQAPGbuPobOwKtcR5cbNm1O7hLyAd7v42Chgt5vsQZJO51ldpB1hmRAOn3ro/f965KgBzmDk318FqjZor2LU0tmUJ+au4JUHgwbTcbxQefa61V4W0LSrsUwp16a5dCmJYUuyp8YX/fZDLj8y+9vo7YzIz7gesbXQnQqkWxSauW1264Qi8CvQhIgPQipH8XgQ4EvIjz6AaX2UkoEvgCnp+fN4GCXrZB1hmh5YaWIC5WlF3Fy7s2eue6CgFSb9SxebyJfCWPeCSOcrWMtZk1TCe6B7CPHl1/RkyxwbTdbLTodrKAOKoK72DIjVIJmU8/Rek07mT25k2sfeELiF5iQ8dBtxN3CO8p3y8UIF4nIpk4mLpg1wQkQFwj0xcmnYAd58FFNq0dFArczeOuIK0eXvk989wUIGwM+qSfrpdtkHVGmMGLC0/yoAuWglS9vHOjda6rECD8je5kdnCYPzRzLxaOYWV6BalYarTgDcloWwUIi4syFa/b5iaFcPHwEIcffYRAJGJSKQfjcSy9/Tai6XTH+iZy6XJ7RwBmNuP7ioKSm1xqIuAnAQkQP2mrr5En0BrnQZcELuJpmbh7967nLlJcuDFQnIspCpDLuHO1Az/IOiMSICM/1T27gKsQIBx8qVLCcfEYtXrNCI/Z5KyEcJ93ldZMOwi9XwHSqet2KYRL+Tz2PvwQ2e1tBAMBpFZXMf/mmwiEQh2vwHbpapdGWBsg7bExroexhRQgfMeoiYCfBCRA/KStvkaWgB3nYQeY0zrBLFV82dEyMYhAa/bJLCV8Qc/OzhozuZdtkHVGWgWIKux6eddG71xXJUBIir8dfrQ7frl5w2cRA5bZBvEsOje604KNlVweub0D1BsNRBcWEIxGz8WdOE0hzHNfzMylFMIWcVa3Z2whLdW8r2oi4CcBCRA/aauvkSPQLc6DL8BBViqn2LFf+vS77sftoRvw1jojXhc65LnpmsZx89xeuaWN3ATSgK8sC5bQe0fANwHCdMvlA6CWt6rFR2Y7Vr5vdem66N7l5spbUwjbQfD2n27OM2rH2tXt7UyNtGypiYCfBCRA/KStvkaGQKd6Hq1xHoNcwBMU/a7tLCXdAj/7hTrIQoe0DlGc8aXG9I5e1zDp95r1Pf8JXKUFxP+rHc8e7XvIqxuEO+gZtWoOKO0AjRrQrAPRGSCxBgSCjsG2c+lqrXfi9ETtUgjbwmQcLGpMGMAYELoQ8/3Cj5oI+ElAAsRP2uprJAhw554uRBfredBM3ZoKd9CFAvnSZJYSvlDZ98XiX5eFOcjxS4Bc9u6Mz/cdCxC63nDRGQgBAdYwVxsWAv4JkCxQ3AYQBJoVIDIFxNeAYOfYDzeM+CxtTR/c+t9uXLp6pRB2M6arOtZOrUwBwo0ir98vV3Vd6nd0CEiAjM690kgHTIBuBhQe/JMxHr3qeQy6UCB3qOzc+3S/8nqHapDj57kpQvhiY355r4soDngq6PQeEnAkQBpVy/WmUQaCMSC24LjquYdD1ak6EOCzkAkx2JgtyeuMfGfd0vJR3rdcsChEo3OWFcSH5lUK4XZB8MPo0mVnNuO9ZPyH1y6+PtwydTHiBCRARvwGaviXJ9Aa50GrBzNdcTeMD2RmB+mUQWXQhQI5BprI+SfH4bUAGeT4mT6YGcIYgM788l4XUbz8XdcZ/CLgSICUDy3XG3Cnuw7EV4CY0oL6dY969eObAOFAGnVLiNIKEvY29Xiv6+z0725SCHc6h+3S1U6gXIVLlx3XQwFCtzqvk5z0y1rfmxwCEiCTc691pRcIOInz6AZt0IUC2TfTJNpiyOsgwUGM3xZzLHJICwjTEzMGRAJkcn9+jgRIaQ/IPQZCMaBeAtJ3gPjS5EIbsivns+L59nOUa2UsLixicWYR4VD4/CjrFYBB5KGoq5iNIbtUV8NpF29iu3X1WxX+okAZVAph+3dJAUKrltdp3l2B1METSUACZCJvuy7aaZxHN1KDLhTIvm0LCF8OXqdJbB3/ZSut22KOrld88fLlRne2mzdv4vr1655XcdcMHh0CjgQI/f6znwG1DBCeBqbuAonV0bnIMR/p4ckhHjx7gEKlYBarq/OrWJ5efnHVlROgesy8x0AoCcQXJ0aEdLr1tktXO+uJm3iTdhYT++8uM+1sqxbfLQN1q7vMIPXdsSYgATLWt1cXd5GA2ziPbgQHXSiQfTMGhC8y20zu5R31SkDxPBQb3Pljs3fs+OKl+5Vebl7etdE7l+3qQdHfMYMS/f7zT4HwFFDLAqmbQGzxai6Wi2jGIDAgPhgBwt7W37mai7pcr1sHW0aAJKIJxNIxzKZncW32mlVfhXEbxS2glgMQBvh38VUg4r5auttRmjov9TqC4QvWGLcn8vn4i6Kk9f+dDoXP2U7xJk5cumwLOAXIwsKCNomcgtdxnhGQAPEMpU40zAT6jfPodk2DLhTIvpkFiwt720zuJePLCiiOyy44yHFxMcBgS2ZT4QuQQau02si87+VdG71zORIglWOgtGstZln/Ib4MRK+oMFolA1QOgXoRCCUsIRRJjx54D0e8f7SPhxsPjQVkYXEBK7MrLywgVyRAKpkMjh89Qr1SQWJhAdO3biHYpVK6hzgGdqpOLl18f/HjtHVKIczns71BxBhAxunx3aI4PadkdZyXBCRAvKSpcw0dgcvGeXS7oEEXCmTfrAPChT5jKLhL5WXrV0BddLfiC40fBjFSfPC/bXEjAeLlHRvNc9kChJYyzoe2vuYMPKb7Vb1sxYHQDcuj1KuuqRV3gfKeVQSPbkV0BWNWrgludK3c2ttCqVrC8tIy5qfmz8eA+OyCxWfQ3p//OTJPniAQCiGcSGDx7beRWh1ftz2vUwjzd0krCDeIVKtpgn/cV3jpEiBXCF9dD5YABQJ34VvreTAdLLNJeREUPehCgaTDSugcP8fNXSovWz8Cqp27lV3IqrXYoC1uGDjPF5wyrHh550brXJwLjx49R6VSxtra0vCn+zQZuXZp07NSwTIjl0+pYIf1zjKhBK2dbB0Xqz4GoTfqdey8+y4KOzuIzc2hmslg4d49TN+4MawIBzquflII857yt3nt2jWsrKwYdy41EfCTgASIn7TVl28EuFvEh+uTJ09MPQ8KDu7Oe5npw67TMahCgYR1cHBgrAkUIKyn4WVzI6A6uVtRzLWrCWCLG/47BYhyzHt550brXPfvb+Ojj56gWi3jzp013Lu3bsUODGujS1HlCGhUjAtWPZRGrdlEKBh6OfPTsF6Dx+NyJEA87rPX6U4ePcLJkyeoF4uILy5i4c03EZ2a6vW1ifv3TimEmamQ7zCmSudnqH+TE3fXJuOCJUAm4z5P3FXywcoMUnRh4s7O2tpax3oe/cJpNurY3nqOZiCMdHrqRZ0OupOg0b6QGl1MagWrS/qVM8i1S6MFhwKK1gXuPHrZnFRap7jKZrOmNoqdVpIvql41UmxxQwHCwGPWMVGbPAK5XAXf/OZjfPrpc9TrVSwvz+ErX7mLubkrDuw2geYFoMmYkygQTrx8c7iJUa/iIH+AcqWMSDiChdQC4tHhqE3h52ziM4AftmHZLW82Gijs7aFerSI+MyPx4XJCUIDwuc5NuUG8H10OR4dPIAEJkAm86ZNwyVw4s4YGX5q2i5Cn131auXlr86kRIKmZa5hZWAGqudN0lHUgNAXE5pgWyuqa36FrB4Nc+XcMsmWwbaDzbjAL+lGAUER5LUB6WXDoH0x+FBN24GI7d6t2XCVAPJ1tI3syCpA/+qPP8P77j9BoVDE/P4cf+7FXcefO3EvXVG9YgbasL+FoN9ZkXasD4Zh7PoxZoKsVC95RfMSW2ma7OsofYSezg0goYtXASC+eTz/rvueR/MYwCpCRBDlEg6YAoXWd3gHr6+tDNDINZVIISIBMyp2ewOvc3Nw0xfDovuR1ET+Uj4DiDrb3T9Csl5CYXsfsyitAaRvg4oaigjur9B+301Fyx5XpKlnh16T4DAOJNSvotkOjAKEQoADhzqOXzRYgPCctGnaldbfuVu3GZFtX6PZGCwj/VJtMAn/yJ4/wr//1xwiHm1hamsP3f/9tXL8+fc4iWaqUcFg4RKVaMRYGWhpocejYTj4Gjr5rifqpV4GlH3IHl3VHKEAi01baXwaaR18WRRQg25ltxMNxkwFqaWppIgUI4z/4LGWTu467qTasR/PdQjdlbirRAqImAn4TkADxm7j6840AXbC4c8fFu9dF/CwBso2dgxwa9QLi6TXMrb5iCYxq3hIf3J2lwLBTeNL9qrQDVC1XBssCsto1249tJueOMF/8XjZaiexCh3SRokggL2a8sQtlOXG3ajcmW9zwvBQgtrjxcvw612gQ2N09wbe+9cAI6ZWVeVy/voSVlRaXvEYVu9k97OePEQ1FUWvWsDq9itlkhzS8lTzw/PdRPfkeAoEQwvE1YO3fAWbuOgdSPjgNNA+cBpoz7e/MS9+nINrP75vsT7SCLKQXkIx65D5GNzA+C5pVIBABIlMvrKXOr8SXI8dBgFSLRTQqFURSqZGrGzKIm2wnaGEMn9fvlkGMV+ccPwISION3T3VFpwRYxM/2W2YgtKeNYqK8j93tDdSaIcSnVjG/fA1GmDB1J+NAaPmgawctHXajODEFuwLW7mu4uz8587TTT5dtELtUdFOj2KDQoJsVLRe2uxVfTBQO/WRHkQDxdLaN9MlKpTIePHiO4+Mc5udnce3aPKLR098E639UM9jL7uOgXEU8tYJitWgEyFzqZYsEQTRLB8h+9s9RL2yjGUohHgohefurwMxbXTlxnp8UT4wlIxwAZkNNRIOnlbu5GdDBFbJWr6Far5og9GiYGwseNeMGdtBSb2RhaLNt8TnEjQn7OWQ/IzwiMfDT5Hd2kHn8GLVyGfH5ecy9/jrCUQ/v5cCvwPsOmGGRz2nGgHjt3uv9aHXGcSQgATKOd1XXZAiwiB8FCB+yXtfQMB00qtjb2UKtAUTjKasP7mrWS0CzYblWtYoPfof/ZoqtRYFQ7xcgdx7tFz93qbx+8T9//tyk16QAoZsaF2l0WaM1pF12K6dTy7au0AJC65PnLnBOB6LjrpxAayFCzoOzjGgU8bQY1ksolAs4Zl2C8AzikQSW0nOImiQNL6cGLRVzOH74e0D2YwRQQXDqVcze/jlEUt1rdeTKOexmdk0sBzPsLqSmsZxi7If1O6xndpF7/39CvZhFbPlVJN/5qie/t0qtYs5PC8q53y+rv9MiGlkAqgeWu+ZVVX/vMUtaBcioxQswWH3nu99F7vlzhJNJgO+De/cwNeFxD0zQwuc0U6R7nWHxyh86GsBIEJAAGYnbpEH2Q4APWC6uuavvdQ0Nezyu6nQwQL3CHc+KFfgaXexpAbFdH7hwYQyIo+BcB7AoyujTzTTF5EM/YLpK9cpu5eDUZ4fQusLzUYB47gLnZiA69koJtBYipAA5qwlTK1kxU/WqqblRaTZRC6URaVYRCdAyEbcKAF4Q6rRgbB08Rjj/EE3GgKRuYn3lnZ7WiZPCCbZOtpCKpVDMbWE63MTK9AoCdL2KzOLw//qvkfnwj1EtlpBYXsP8D/8ckm/91KXYsU9aXRrNBqbj08aqcyZCaAEx1d8rQDAGxJccWUAYrB8MWBZLv5rtCsr+RlmARNJpNKtVS4Bcu+YXvqHshxt0dgHZQb0fh/LCNaihISABMjS3QgPxmgBraPDFyaDqQe3wuKrTUdwxblsIp6wUoIwPYZasLs3OPsMXBc3k/bhDXTw9Xbp4XgoPjp9ihK5WN2/e9OT8dn+ML6F5n+KD4kZtMgl0FCC0EtIFyY6JYgwEXRerh0AgDjQrp8Hh52NBuADfz+6DFg0uxKcT05hPzfdckBcrRexl91AonSBePcJcPIqZxKwROs3gHHb+17+H/LPPkLr+KvLPP8HiD/00Zn7kV/uuyF6tVY3gyVfyZmzxUByrM6sv0vjy+qsZK5Ce6bjpktklIx6v+zB3iFLNikfhNXvqEtZletrJMHgdg3AFHfQvI7e9jcyjR5YL1twc5t54A5H45KVTbuVMF2U7xm8gHgKDvqk6/8gTkAAZ+VuoC+hEgEF2dB1gGluvM0jZfbIPpjJ0lCa3RJeLXSBA//fGqcvFHMCdYLsewYXdXlop7DgWiqjWauNu7zyLA9KiwvHajXwoEuyCgW7P2e14CRAvaY7uuToKEF4SF+F0S2SjxaO0Z1kJuwgQHsrFOAPDuSBORBKdxQetjSbmii6RSRQbAZTLGYQq+0iFgwgiZC3+E2s4/H9/HScf/BFqxYKJE1j4gZ9A8s2faGuFcXI36Hq1ebxpBEMoEDIxJGsza0hE29QccXBCWlOYEriBBpqNpsnItTi16OCblz9k1AUICVRyOTSqVdAKEop0r790eWLDfwY+n/neopus5zGSw3/5GuEQEJAAGYKboCEMhgBfmrSAMPvOoLJ82HU6uJPUU+TQ573C2gN0uTh1L6kXrV1g7oKGk5YPeEtaXsZ/UCRwoUUzOeMz3Dbb3cqOJbGDzvnioTWElhDmgvd6F4w7bIwjoduNXnBu79r4HG8LELorcs5R7FJI8/OSRY+WQfN7qHV0wXJMhuLG1N05Mi5eCE9Zop+Cg39H6wNjthhrEltA7XgTuff/Z9SzW4jOzCL91k9ZewUmNsNhEguOm7/vQBjNYARM45sp0AWrgnR8BotTy327UZqUwCfbSMVTyJVyxgJCi4ofzS6IOohsfH6MX328TIAusnyf2JkKxUgE/CYgAeI3cfXnGwGKD3648B6U20C3NLncpc2WsibQj3UEErGEtePLGiBc2dCHm0G4pUPLLYtihPUIWtyyKBDYBwUIBQKFgpvW6m5l+4zT4sEgcy7+XMWwuOn4NAkAx0sB4rW4cTkUHX6FBGwB8uzZMxMTxPlnN85JW4zYf0ZCQMhkx432dH9imtxCtWB+H+lY2lgZzhqtH8VNK8YkFLFEfmLdyk5nJ4vgwRT8ra5PJkXvDhBMWtaTJF0luwe4mz7ZH10s+TtmkonoPJrBKMp5BtoXTVB9MHF+g8HNbbFdyJglLBaKYT49b9zP/GgSIH5Q9q8Pu1Avn8/cEFCSEP/Yq6cXBCRANBvGlgAtB1y8041pEBmkCK5blqq9zB6OCkeoNWqYik8Zl4l45ILfsR0XwjoA3KU1BdFe1COg9YZWFi6waEVgsLiTRncrXj8Xf3bjbhdfNq3ncBXD4qTjlmMY5CgB4hLaGB7OOciEEMy4dlGAdLtcCmTO2YsCxU7EQBcnZrWyY0FYN4S/sbPg7E4WkF7Z5+zgeLpMMhg+tmqJkIsZ7S4OnimF8xtW7AotOfFlK7Ccv3Gm3WZdoOgCkFju+y6Xq2WTxYvV4gOZLJr1BuJL3iWn6DQw+zkxiIKofcPQF/smQKs4XbD4LuA7QXWa+kapL16CgATIJeDpq8NNgLET3LmjAPEyg1TrVXfKUkXrB/2/8+U8krEkuHtJ/++Xdizp/87aIVy0BBPWTmvLLi7jVyhA2BjI3Ss1Ll8svG67dkiruxUXfxcz57iKYXF5u7no5OKRu2vKsuIS3hgd3hoDQssbRSkTQ1z8OL1kChDOq3KjjP3cPuKxOOrNOpLxJK7NXjtfQf0sBuS03gezzzlpdN0qbFqig9bKxErbSunnTkUBkvkEqGWAKpNMrFqFRut5IJSwRAldufj3DlqlUDCpY+uVigmcTq+vn/1+N/+//xP7f/4dMMXs/Fufw7V/68cRDL2csthBN44OkQBxhGlkDqLbLV1kKUD4fObvUk0E/CYgAeI3cfXnGwEKDy7eKRIuG8DdadCdslRx4b9zsoPDwiGaaCIVSWF5etmIkZfaRbeslgMYME6RwPNRgLS6r1w8D13NeM18ubCZAN0Wd6t212AHl3JB53UxKrp3cceUu2uDykLm22RSR30T6BqEfnpWzm/O23bChKK6XWMQOrNh0SWJbSY5Y2IiKHDaWU14Hv4mHKWvtWt0hGeA2omzGh108Tr52HL7YgFSY9FcsywfNbplRawNBmb76tSMa1jRCIuDTx7h+PETNOt1xBcWsPDmm0guLiK/vYEH3/gt5DY2EAgGEV9cwN2f+hnM3H2jaxatvm8gYFw1eR8H8Zy4zLj03f4I8HdGCzUFCLMUMg5ETQT8JiAB4jdx9ecbAS7IuXinAOk3gLvXYLtlqaKLCDPX0AWLtQf68dfmS5+7j1yg8UVxVkOhZWA8htfIP7m44rG2b2+vmBFXQfS9YFz4d46bu9XcXfNa3Lgcig6/QgJOBEi34VE4tBMm/DsGY7MuiJln8SnEwu1dFOmmVaqXEItasRNTyakzkfJS3yaWg+mBj61/ovWil3CwT1I+tFyuGIjOtLrxRavGx2lgOsJdUr9SfDBJReUEjXoVO+8/RjFTRWJpGaWDAyy88w6mr19H7vkTfPp7v4Xy0QECxk2tibs/8Zcw8/o9E3fipMCp2+kgAeKW2HAfTxddWqhpUed75aw46HAPW6MbMwISIGN2Q3U5LwjQDclOxdtPALcTll5kqerWD18UfPmz0ZLQ+qLo5G7FBb/TF0q3IHon19/tGAmQyxIcj+9fVoB0otBqNeHvpFWk8N/sRvdHumoxfoIFAWkpWZ5aPrOG0Ep3ZjEJNBCuHyLcLCPI+I9w2hIRzFDnpJnaHtkXabX5/U4FAzlGUwOEbl5BK4jdBM2XGYGPwwePkdkuolZrIrm0hPm33kJ8dhaNSh5P/uB3cPS976FZr2L29jpu/Xs/iTCj9524ijm5jgvHcLFKxozJkTWzD4BD9hX7N0kBQst6u42tIRuyhjOGBCRAxvCm6pIsAoyfsIsRugngdsPvslmqevXFRRVf/lxQUYDYpvJ27lZ8iVB8uKmWzkB1O17E60xhFH9sHFPPFMW9QOjfR5bAoARINyCt7lwn+RNsHG4g0AyYWKxEMICV9AJCkYSVraq1UTww/iMUQ7BZRiQxh3D6OsLhEMIUKtGYN8U6KTxoZWEMGOuf0HJhZ8Wr5U3Qer0RQu6YifOCiM3OIrGwYGXvKm6jUdjFydNnLG6BqRvXEZ6+DtRP406cpgx2MaPorsNnES2qiudyAW5ID6VrL9+NFCDcnOsVWzikl6FhjTgBCZARv4EafmcC9kOWbkZOArj7YdmapWp6ZhrBUNBkqImE3dfraNc/F1J8+VOAcCFPn91+3a3anb9bFq9+eLR+h9w5boqmQdVhuewY9f3BE/BSgLC6OCuLc14lo0nEIr2zwvE7+/l9ZIoZRBolpJtVTIWjqCGCWnAONYTM4tpYTbj4pwCplYEga4QsWml7WTPE1BJJIxB9UcfkYqyJo/gSImcdEpMdKwQ0mR6YtUYWjPvVWV+MFYnMnhZrZJxLwBJMpW1rnKwlRDcxk0Y4AuPeFaW1xvsK37YAoQibiccRjEYRaUmnPPhZpB68JGC/txgjSAHiNLuil2PQuURAAkRzYGwJ2AsfuhnRejAIM7OdpYrxHo1IA81QE9FgBAvxKBKhsOVeQV/wTm4YPejTzYrZSvgnP62V0Gnp4OLeqbtVJwHCOBYunLzOFEYBwjFTOEmAjO3PrOeFeSVAOJd2s7s4Lhxbgjw+hZXpFUdin79PBq2HKgdINHII8jdpWwyic+YajNWkXEDt5AFq+X3UAhHUIiuoM6NVldXUA9bi3hQLbb/IP+fOdVpssW3BRRMrsm25djFLVuw0ZS8HwmKGFDsMWm/UgfKe1T+fIRw3gpbwoBWFIoWB8vw3Ht8rxXDPu9X+AD6DmJWruLGBBJ9DLDB6+zaSy71TCldKJWz/6Z+ims1i4a23MPvKK32OQl/zigCt3rR+0/JBi1avWEGv+tV5RKCVgASI5sPYErAD7figvexCvRMkO0sVF0WlQAkzUzMoF/ewEg1hnoUH7QVLS20PN8C56Hr06JHJbsXdKl4HxUI/7lbt+m3N4uW1AKHw46KOY/bavcsNQx17tQS8EiAUEZtHmyapA62MtXoNa7NrJsGD41bas4oFchHPdqHujrFAUBhQALBgaHgGzWYVtXIetXrQ9F0LL1rWE9tq4qDzlwouooZw/QjhQA0BY7lgdqw218HUvRwPrTMcDwUGU/vSasJ4EwbIOxUdFDNovCiC6mDc9iEUICfPn6Pw8CFm5+ZQKxSQvnEDK1/8Ys+sYvd/+7ex8Sd/glo+j6nbt/G5X/gFiRAX7AdxKF14af2mAGFMD2N71ETAbwISIH4TV3++EbBTDVKA0EowiFSD9k45IAAAIABJREFUdpaqMwGSnkG1sIXlaBNzs3etrDbxFSuQ1WWjuOFLYmNjw3zT3q2iNcerHatOaYRdDrXt4eROEUju6+vrXpxS5xhBAt0ECC0ZmUwFlUoNkUgIU1NRhEKn4uDCtbK2Di0gR3nWzQHS8TRWp1cRjVyI4+jGiIHe/E0yKxVdmC7U3QFreXDBz39rFC0XKFox6YLFBT8tDkyxe1qr52LqYDsYvlPq4HNDowWjUUUoEkM4mnwpdTCtKbCLIrK6OkUI+6doorXDTWMaYPu6Q0nLitNaNb7HuVi0LvPsGfKPH2N+cdFYM5wIkEo+jz/7tV/D8cOHSK+uori/jzd+5mdw58d/3M3odazHBOzsjXynMENhq2Xd4650OhHoSEACRJNjbAnY1V65iLfrYXh9sXaQOHdna6EaApEA4s0y5sMNxFn82OxYLgHRWcddc1FDYUA/XS7QmAWLO6j01fV6Id8tjbDjAXc4kNwpouiCRQuIY//4y3as7w8VgW4CJJutYH8/j3y+YgTI0lIK8/OdiwUyk1W2lDXZrGj5cGX9sKnY1oRA6GXXSJOCd9/U4jCLfAaH002KlgiqHlocelVEp52hQ+pg/rZbM3R1u1H8vXBnOtTIIdIsIcyq8Il5hOKz7n5Lp4HryD85y7CFqbtWdXeHjQKkUiyi9OwZ4o0GIvE4pm/fRmpxpiXFcPIlniyi+O1f/3Xsfuc7CEQiiE1P4/Wf/Vnc/LEfc9izDhsEAb5faAVh7Act30bsqomAzwQkQHwGru78I8AX/dbWllnM80FLy4HXrTVIPJVOIZaIIRwIItwoWD7arKJM9yum2ezROF47uxX/mx8uQuivSwHFD4PpvWyDTCM8VAIk8ylw/F3Lj3/+y0D6jpcYda4uBGxXSMZLsepyayzW0VER29s5zM7Gwf+m+FhdveKqzIzBsOt2OHVvcjEDOtU0uWg1MQUWGzC1S8zTg5mFg9Zz5GLwu/3/bTPgUYBkHwL5R9YoG2Ug/Qow9ZojMcWv8Dlq6guFw0hHIiYIPUrDU2XfKrJoZ/KKvvyM3b9/Hw//4A9QLRQw/+abeP2rX0XIfNllM0UaS6euZ3FXFhyXPY394Xw2873C96I2h8b+dg/tBUqADO2t0cC8ILC5uWniJ7iTyMWP180OEud56ebVr8ix3a24WLOLCdqiicHcXLTQXM50wl62QaYRbhUgDEJ3kx7Yy2vEyX3gwdeB3KeWAJl+A3j1l2F2ga+6ZT8DDr9trS7nvmiNbcxaqwC5WMsml3thAYlGw1hcTGJurrMFZMzQnLucVqvJfmYfB9kDU1w0Ho5jIb2AoINNDP7G2omTUGUXAYpwEwMSseJI0jcdx4/YAuTcJogdSM/A+OqJ5dbFbF5tGjdq6qUSoikX8ToXz8PMYYzRoUCMpE/dyMLjPCUGdm2Mz+M7h668XlvVBzZonXjsCEiAjN0t1QW1EuCLkwKEJmZWfPW6cVeQ7gl2ulknAqTZaKB8cmK+E06nkcvnTc0S2+JhVw+3d4pZB8TOwU83LC9baxphr2ul2G5kZHKlZv7P/gnw9F8A029Zgby5h8Ct/wC48wteonR/Li4IH/z3QPZjy7+fO9Kv/qfAzNvuzzXE3+gmQDjnc7kqymXGgAQxNRVDMEjfxcltDK7fPN5EoZJHNBQDY1+WppYQD8VfqgjvKNaEKJsNhMs7CDfzCMeSCKdWEU4uGbcuJxsD3Mhh4zPp7DlqB+zTXc384/W+Yt0c3WmKjuKWlX44QOtJHUisWUKEbnMUQCZIP3GprIOOxjIGB3FTi+LWtoCMwSXpEkaQgATICN40Ddk5AYoDO82s1+5L9ijs3UFaQHpZWSg+jh48QG5zEwXGeExNYebOHeM7TcuHHSzfuihgDIhdhdjrImB2GmFei9cChNzp4kUmVypAHvwG8PT3LNcrBhIfv2cJkFf+I+cTaRBHPvot4MlvA+nXLBe9zEfAzX8fuPufDKK3KztnNwFyZYMa4o7r9Rp29j9BtrCDUDCKUHwBK3M3Td2Ti61drAl50+Jw1rhAZ1V31hwxVdaZTphWpoD5PRirSSTa1nJin8MWIOeecfWa5dbFzGKsRZK4ZlWOp5WFLlleuq/xd0sBYuqxnNZDYXIPZg4r7gKVA0vEU4Aw5o7CpM92dP9dHH30LgKBIBa+9MOYvvNWn2ca3q+xSCznCa3qSpE+vPdp3EcmATLud3jCr48FtLgTzxe119YDG61tAaF7Qi8rSzmbxcaf/RkO9/fNmEKxmMmNP7W0ZNy32qVDZMVamsv5b0yZ6GWz0wjznF4Xa2wVIFeaaWX/m8CjfwZkT12wpl4H7v7HwPz3eYnS/bke/g+WAJn9gpUW9ujbwM2fBV79a+7PNchvcNHKgGwHLkDthtGPAKFlpFDgQrqJeDyMaHSMg2S5uGZsAxfWXLjX8shnHiGb20ez2UA8fQ2zC2+4CjwnP4qQan4PteKhZTkJJFALpE0oiWlczNdY34RBJdMvLdq5IULLMT9csFKocDOBz1GTUILzgqLAHjtjS+zK8sZFaskSJl411kJh/ROTHjkNmPotAaC4aV0L/44WElpG+kx7Xth6goff+E2zScRrnH/rHl79+V9BdMZ767lXWPo5D98pnB8UINwcUhOBqyAgAXIV1NWnbwTovsRYBD5svbYe2BdhFwrkw7yblYVj2N/awuZ3voPy8bHZiWRWmNs/+IOYW13tyIQvf1oq6NvNhbyXzRYgXLBw7BRRXjU7oJ6LlivNNc+d0b1/BRy9ay30F34AWPjBvotDesUHh98BHv4TIPOxdUq6YN35RWDx3/Csi0udiClpn/wOkH0AhFPA+k8Ciz/o+pT9CBAGpPNTrTaQTkdNdixfRAitBbZLEa/ZQcYr10Bav0DxUWIg92mhQ5OwImQW9vVgDI1qHpH4LJBYdy8AeS0lui21VFFPrKIeiFp1TbLPUavkUKvVUUMM9chC2/S+3Cjhc5TPCFpAmNXOFFwMNBCu7ZtaJmFaUZo5hKKsfTRtJeBIrvctBDoytWuZtKYhZiwKP6yNwnvGoo59VoM/+vBP8dk3/hmC0Rhq5TLC8Rhe/w9/Gembr13qNg/bl2lV533l897rd8qwXavGM7wEJECG995oZJckwBfm48eb2N8/MjuJd+6sd6wxcJmuaGXpFiRu+blb7kh86Oc2NlDY2UE8FsPynTuYu3u36+4m/XUpQPjS9/plYdcx4RhpvfGyWjwD3Cn+eF5V220zwyiMDr9lffjfc18CFn/InTDi4jX/2HI9YQC7lwvmT/87YOv/sNzWGiUrhuaN/8x1BjG3AqTRaGJzM2NiQ2j9YHzI2toUpqc93E1v94NnnAHdiRhPwJ11ioH4svuFv5uHyVmhwQbQrFmuUZF5a6efu/kmFfAcEOsj+cQ5ARK0zsUaIuyD9UVovaA1wRQ0jKIZX0WtGXopzoTPCD7j2OwCqGeXyDiQWtaas+UjBGo5hIMBhOMzCM+9gXBy/sy1a2BpuDl+U6m+btVv4f9zTGzhqRcFHvkbq2aBJl3Swta/XaiFUtzdwGff+E0cf/oxAqGQsYDcpQUkdbnMbJVsFrViEeFU6nKB+G7mVpdjbUHJ++m1Vd2jIeo0E0BAAmQCbvKkXmI2W8b3vvcUu7uHCATqeP31W11rDPTLqVuQOIUDF+EUKGx8CTPzSCLYQDjYRCQ1bVVC7tIoQBgsTgHitbmci0PuhrFdzFDULw/7exIglyXY4/u0nDz8p0DhueW6Q8vOK7/kvkhdu264eH3v71lua8zOVT4AyrtWfAp3uOt5IHkLmO69M+xWgFAM7+zkcHhYNG4/0WgQy8tpYwkZaKMYYExDrfyi6CDTNXsZy3DxAmidKO2cujE1rR18uhDZbll0e+Pf9en+BjtzlFmM0zqwYJ3LtrzQdYnigZmsmMWK/32h0XLLODc+w7hjTkuvnUrYxJrQ2sHFfWkXKD0HmhQ7cWDqjlU48bQZq0k43L7gYrcb6yYtshFdO+cFiF24kSLF1HhhIHvEut42wi7z6D6OP3wXCIWw8PkfQura7UtNu8LeHk4++wzlXA6xmRnMv/66+fMqG632/G3RojUo1+SrvD71PRoEJEBG4z5plH0QODgo4P79ZwgGy9jby+Du3etYX/e+Fki7IHG+oLPHeyhlD0xQZjOcQDg2Y9wXEixibBc7o490dPHFLl2b62TKRC7m+cLwOmDQLqTIRR8FiJfV4imaOHa6dvElx4wrah4S+Oi/Anb+HyB5w6pyzR3d137ZsqJctnGB+v7fBw6+CaTvvgg0ZvpWChEu1rlQZtD88le69uZWgPBkpVIVx8elMxcs1gkZ2A66PfpKDsh8YLlEMVIieQ2YvgeEByh8uHCnSDA79kFLCPQZv9D2JvD8rGliArRj5wUG3ZmMu9lpUHoHkUORwQUrG59f/NiNzw0jRqpV1LLPUCseoVoPol6voElXKAfB4LyvneqaBChuKH7rhVNr0ELXZ+ULyw4jXZqW2OI85SYPObPKPavb08JEyxLFyYAb66AcffIJEgsLKB0eYvFzn8Ps3atNAc64RQpCPu+9Tu0+YJw6/RgRkAAZo5upSzlPgBaQDz98imfPdtFoVPB93/caFhZeziRzWW6tQeJ0NTLuVrksGoU9BGpMD9lEamYBU/M3EYimgfKx5f7AlzN9v+nmwcwtHdrJyYkRIGwsGuVlay2keHFxcdl+7AxbFCB8yXHnVM0jAhQI3/3PYWqcMJjepER9Btz9a8D6X/Kmk4NvAY//RyvI12QXWgaK3K0vWgu37CdWZrF3/ouurl/9CBBeABe3dMcKhXoX8axkMigeHJgFdnJlBZF+YpkoqhjvQvckuvNEZy3x1WIBqRaLyG9tocG6PPPzSC4uesPaZKpidifuTgxXo8CwXbC6blJwDnKRT4tFOIV6ZA7VOvpPHcy8XY08wtUDRGIphANVhJOLCE9d75w6mKKqvAcwfomN95DB8HS1qmTNxk+zlkN+P4M60ogu3EDC49pKF+/e4ccfg59wMol6uYzFt9+2Mh962Bq0RDWbCIad1UWhRYtJTShABpUd0sPL06nGlIAEyJjeWF0WjO/4u+8+xrNnO2g2K/jCF+4aVw6vG4PEGczNFzV3+S13qwYCxW3EQk1Mz8wgXDsCovRHZjaVgLVgNK4QNYDpJOOd63vQhYvxI2y0gHi5E2wXUuRiz2sBYge4MwaEFhAJEI9nHmM0Nv/QWrQyXoDuQq/9KjB7z7uOco+tGBO679B//rOvW3OYYuToPaui9hf+PhDuLOz7FSBOL4Ki4ODDD5Hb3jYL06nr17Hwuc8hGHKZOYu77XTfqdhuSQz+Xjlzf2IK7f2PPkLmyRMjQFLLy1h4++0rd6dxyqnf4xwLEHZA8WbqccQ6itJ2qYNtl66XxkgXMcbl8FnJ+xOdN7VGgoGmJUhCEYTjU2dphLmrH+AzlWKSjfOS8R60eFTzxtXtZPMQJ892US01kFhcwtzrrxvrxKAa4z+YVYuV4GNTU5h97bX+BHKHAdLFK/PsGZr1OlKrq2b+93pHMK0yXYH5zO+VuXFQXHReEZAA0RwYWwKZDGNAnqNUyuPo6AQ3b67j+vUZRzuqbqDQBWt3exO1WgVLy+smzWU4FMJUpIxEqGi5V9DXmy9PuljTzYLpKhnYG6QL1nxXP3MKELuWCWNAnBQOczp+ryq5t+uvVYDQAuJlhi2n1zfWx9E15dE/tworcj6t/tvA2r/rLojdDaDCBvC9/wY4ed+at8zWxD4petrEDtinHrQAKfD3993vIhSPm2rb4Xgcy1/8IqLpPjYbuICmu49ZvKbP/S6ZFWn33XdRzmQQnZ5GNZvF4uc/j3SXDHZu8F7ZsbS+GIsBg9GTQPS8m6p9/zg+ZrRj3MAgmp062BYj5s9KCbXCHhp8flJI0D2Nc49z37it0X2MyQJeBOm/5M7VLCJcO0QQVhze9kcbyO0VkFpbQ35nB0v37mHm9os4DxZ+LFVLpvJ8POKN6x8Fq5VVK+5eGHeBXatUsPfee8Yqh2AQ8dlZLL3zTldRTM60gFCA0KLVq3bVIO61zikCJCABonkwtgRyuQo++WQTW1t7KBTyeOONG1hfn3VdaZmL9EKlgAZz8kfiiJ76hPNBzhoj288+QSGzb96Fq2u3kJy7ZnaWAtwJpIsVX+4mT/2U5b5CtwD60tPNgy/VLos33hz2wQ93tZgFi7t8XrV+Krk77dvOsMUXHAWIlxm2nI5h7I+jKxbdXhiETivFoButHhv/m5UpKv0qcOvnrPncpQ1agHCHef+DD5Df2zOj4A4wF5WhqLexG8YC8uGHLywgKyujbwExweO0+hxZcSK0GNAiawoVWu3SAoSWC1roTLatpPsUuc0GGrUKavUGakxwVcqilttArVozmz7GRY7xJp2SBdByV9pFkHF4gQoyG8fIbefNczSWSmHlnXcwtb5urpVV6Pdz+8iVmM0rjJnkDOZSrDcynK2SzxvxXc3lEIzF0KzVsPyFLyDZpV4U32eMAaG1ngKEHzURuAoCEiBXQV19+kKAD9r33nuGBw82Uankce/eHdy44f5lcpg7xFHhCLVGDVOxKSxNLZmXH0VBrVpCbv8RitljRGNRvPrqXUSmbp5/yXKHkX7JdAuw02o6DDQ9KZ5g/3AfxUIR04lprK+um4BNL5ubSu5u+rUzbPEFRwEyqJ1TN2PSsR4Q4EKV4tphyt9BCxBeUWF3F/ndXZM6lYvJQWUZqhQKKGxtoc4q0nNzSI16ETfGazDGhxYGilgWE2TQdkv2Km4k2JnyXKfqtrNjUeDQNkyrEgXOZTKLnRVALIKisB5MohZZssQJLQ2nHz7/LVVRNEkaGtUiqo0mGs0Eiocl1ItFM0+mb9xAOBIxz9VyvYyD3BYiwQYawQBSiUWsz11DOOTtM9eDX6E5Ba//8JNPkH3+HKjXkaBb4Oc+h3AX8W0nFaAA4f30MvGIV9el80wGAQmQybjPE3mVxWIVDx5sY3t7H4VCFmtry7h5c8FVQTPuiG0ebxoLSCwSQ7FURDqYRoRpHPkCqFdQOnqCQKCKeNSqKhtMXX95l4+7gHxxmvzzzoKxC+UCdjI7ODg5QCFXwGxiFm/eedOYzr1sbiq5u+nXzrA1NgKExc5yn1nuTqyJcZlFlBuQI36sHwLET0TFw0Nknz4FA38Z8D517VpPn3s/x9e2L8a10PrKYGymUbbnLgUCM/IZC8hphfELAqFVgLguVsrnnhE4tFRErDgOI3AuuMdxHD0sweeuy64/QrNzZKZttq1GvYZqftdYTMqVEvbyOWQrNTQDScymZpGMJl+6b8XiEQ4OH6BZL6CGANLpa1hdfh3xWNxYTBi4TaHipRX6snODYpgJGChGmBgh0iPZh/17ZEweBYg2hi57B/T9fglIgPRLTt8begKWANnB/v4hMpkTrKws4PbtJVcCxMRIUATkDlAqllAv17E0vYR4OH6WR71ZPkLueAeVWglzS2uIT11HLNpeZNRKJeS2ttCsVRCfjiMxN4dSM4QiX9ABIB1NIxK2xE2mmMHWyZbx1Nrd3zUvzLfvvI1E3Ltq5ezHaSV3tze8VYBw4TLSO225R8Bnvwnknxgr1kH8Bv5FaRq7pSxuz97GX3nzr2CWFavVXiIwbAKkXC2j3qwjGoq63tnmYo8+97nNTbNgphVk8d4943s/tI2WV9bo4J9c5DP9LEWGveBn5ihTib0BBFnJ/Pyzi7FczPTH5lqAmHoju1alcsa/0U2Q7qcMUjc7OCwiyGKGHBtrc8w5zwTGcfP7tKzQGncxjTBdr5i1rVlDvpTFbrmKenQJ5XoFqUgKS6klUxi21WrSrJwgc/QAhVoDoWYF6ak1JKZfzljVNXWwGyF1BZPGFpQUILyfco29gpugLg0BCRBNhLElwPiGZ88O8ezZFnK5DG7cWMHqah8uWMeH2NjfAB/cqVjKuEIxoJpxHtwNyzEOZPcpjgtHSM7OYSo1jaX0krGItDbuUB3cv4/M40dA9RCpxSTSt2/iJBTBcSOCYDBsrBzL08tG3DAQci+7h/3jfcsCkpzFqzde9byehl3JndfkZUpGO8UvOfG8rfUDRm7SffLfAht/ACSuoVI+xEcHn+B3i0m8hwUkwgn8hTt/Ab/6A79qAlfVzhMYJgGSLWVxmD80vv7JWBILqYWzmC4n940uWHvf+Q4quRzCiQTqlQqWP/95JJeXnXz9ao6h9YNpv5lKmQH2ptjh+ktVwDsNjum0memPzW06bT7zaoUsQgGrqKSJMaH1w7Z4cGwUKM2q1T2LA3ZJSX5ujLQoU9jQbYzuYyyy2JrG2KSmZnB2HPniAXaLRdRjK6g0qphJzGBtZu2lhB714hFquS0UKwXUqxVTlb4WnoMpuOiw9V1w0eH5Ww9jcHv55ASBYNC4k/HPXs0WlBQgSg7Si5b+fZAEJEAGSVfnvnICfHlubOyYauRLS+52e7hw4vcoPChm+KEJni5FrSllmSL34cZDs7C5tnYNlUbFvNwuBi9WSyWzeCmf7COeqqKeyyBx5xayTCiUXEO5GURt5wAz1TBiiSSmb91CIxrGcfbYjIPiZ2Hem3S2u7sB/PEfR5DP083gEN///RlMTcU8LUpFLk+fPsW1a9fMeUc62PGD/xLY+1fA/A9iO/MYGxv/N74ZfQN781/BB7sfYH1qHV/7N7+GheTg0nle+Y+pywCOikf49PBTE7j71uJbSEReDmLmb5Fz4CpdPrZPts3vlOMr18rmd8pAY6fN+Nx//DGyGxtoVqtInAai93J7cXr+gRzHhbqpDs4K4KFTC0jnukMXx9CvAGHWp2NWAD8+NmJt7u5dRFnEkAk5aHHhWNjo/sUEHcxqxRTPSYe1jug6ZlL0Rqx05qxN05oQ4Sz2Lo96M4iDagP5ZgShYMg8m6fiLwoqnl2zndShNV4vFDPP/nPZuVpiTfhvTprXVhOKD85Fxj+Z2Kdr1zDzyis93QHt+8kNJ7eC0sl16hgRcEpAAsQpKR03kgTs3VcW86MLkJPFD83ypphgPm9ePGzcveN3eY6LOdZZJPCzjc9MoPrC3ALC0TBWpleMxaK1cfGy9/77yDx5iGD9EMn5JNK3biATDuO4GUf5OIfgsz0kq0HTx/Tt2yalIgUQdyA5FtcuEG3uWiYTwD/+xzG8914YxSJTaxbxoz+awVe/WjL1Oi7b+KKmYGIldAavMi7m+vXroy1AmO72+f9iXD4yxX1852QX/3vzOqpzX8T9/ft4c/FNI0CYpGDS2rOTZ/j6u1/Hw6OHRoDcW76Hv/7lv37GYpgsIEaA5A6NmyOz2q3OrJrdcDeNblisvWD73EeTDoubuo1zcDOoXscyEJtpv1ltnYHgjAVx2Pg7PjpiEDnM84HBy07ayZMnOLx/3+zK0/WU9S8WX7tlWTxMBXbGfSSAYOA0PiUGxOZ7ZlU767u4C1T2gWASaJwWx6R7WWujCKGFJBBCIxBDpV41z3I7k2HH66B7F62ZDtypaB1pJ04GbTVh3Mfen/+5iUVqVKvGArLE9NM95qN9PylA3NxPJ/dcx4iAGwISIG5o6diRI2AX0aIAsQVEt4ugmGB2K748bKFBawd3bjsFHvKBzhiN48IxktNJzKRmMJ+ab+tfzrSJOe6eVjJITEdMJeV8I4hcPYji1jbKD54gvbCE8tEREouLWP7Sl1BvNo0PNgWI6yw0bS72W98K4etfj4Ox7GtrDXz723XcvFnC3/7bR7hxo38BwvHZwo0ijv/PcTN1MK0gI51vnru2rAqe+R7qCOEPMwX8zmEWuWoey6ll/OTrP4m//MZfHrnfhxcDpvj4/fu/b6xAxVrRZIv7q1/4q/iJ137CnH6YBEixUjQWkGqtikQ0gYX0gus4ENfMGHhdZpA3A7ET1i6/CwHguj+vvsAMWdUMivksjrJFU7/IzYL15NEj7H34oYmTKR0cmA2V5bfuWG5RgdM6SMYli6KhYS34KY4cLPqtiZUHKgcARQbjVljx3I4t8YrBJc7DZyDfI8VsFsWjIzRDIQRZDb1eP9vYsk9PgcZ00rRkMC7QZnDRatIaBE/LEje0qvm8VRhzaQmLX/xizyB0vuP4PuR7bXFx0fOkJpdApq9OGAEJkAm74ZN2uXbKQe7I23Eb7RhcdLfiMba7Va8dP5q0uUPIBff0zDRSyVRPM7gZg226P33hssAZdwy5u8qc7jO3bmH+9dfNAs5Og+mFC8u3vx3Cb/xGHNkswFptT57U8fbb+VMBstjXFKGVhi81jpWNL05y48uOY6ZwGvmKu7xfDJgNRlFCEN98/k2clE5wbfoavrz2ZWf3vC+6w/2lf/An/wB/+OAP8cPXfxiVegXv776PX/z8L+Ln7/380AkQDoiF5vhcYGpVL4t6drxLLJrHXX9GYXORzQBwh2m4r/TOM76itItCvoDjfAmILmJx7bbjBStjE5gilgvlSCpl3IPSS/NWSnIGiDMjIIPOGbvRb6P4oPsVYz9a4z/6PZ/H32OsEN2kSkdHiCSTmLlzB+m1tXMWk2I+j/2PPkJubw+BcNi4Uk3duNFzJKFgEIXNTZQPDqyigjduYP727Z5zmptE3GSjAOHmkNdp3XsOXAeIwCkBCRBNhbEmYBdd4gPXLrzUesGt7laWJmiaB7jtrnXR3aodLLvi9zkXqXrJ2qFjY9Cnw9S7peNj88IORiImsDUUiZiX1R5dPihwpqcvnU0qkwH+1t9K4d13wyiVGANSxV/8ixn8nb9jWSvcNPIjWwoNjo+8yI/jpOBjil9mWRkLAeIGzAQd+3sf/R6+8dE3jPWjWq8aQfZLX/wl/MiNHxlKAeL7rWEmJsYrMF0sLWmMVaCr0bC34rYJ8i7U4jjefwYklrG4dtexAOHl0eLLivGMATmrzULRQBcsY/FIvZy9ati5uBgf3dAOPvie7H0QAAAgAElEQVQAkelpY9VO37iB1S996dwZmBVx//33zaYTN6Gic3OYv3cPTbqutcSatOvWxKaUSua5yyrrbHz+vlQN/jR1MI/j85ruxXwf0j12mFIKu0CrQ8eAgATIGNxEXUJnAnxAs9BeOwHSzt3KtpK4eSjbFgr2RTejVCJ+PvUkdzu569nnDp2dTYrnZyapy2aTevw4iF/7tTju3w+BRXCPjmr4/Ofz+Bt/4wCvveY8OLWVH+8AX262m5u9s0wBQqYUIF5m2NKcHx4ChWoBv/vB7xrLRygQwldufgU//cZPn2UE88IFq9FoIp+vgn8mEiFEo8NZGK7tXWGmp8ohwE0JVhinqxBdj4a9VY6B0j7yuROcFOpAdB5La7eMZVjNGYHMs2c4/Ogj41LFJCSzd+6YuL7WxiDy/Q8/RI1Zumo1TF2/bqqZB0Mv4nT47O8Ua3JWcNHBkChM6DJMYcMA9NXV1Z4WEwen1SEi0BcBCZC+sOlLo0SAAoRmZ4oKLoRtdytaLuzm1N2q3XW/ZKFIhC0/Z1biNWlZm1bxLS4++mimFsnOjvkmF/iXzSb10Uch/KN/FEetxrz+TTx+XMXcXBW/8isHeOed3u4QvF66W7XyMy4A09Mv7Y5y3DT1U5jxhac2ngRM/E8lZzIMJSPnF9d2HNZlsmAdHjIQuohqtYF0OoLl5dToiBC67jGrknEVivb9HHA8cxhAbWIqWBuDxTf6bKZGRxb5XBYnOYqnZH8uO4wlYZFDjmcUYl/6xNX23VCp4PjBA2P9CHEj5pVXXqoZwyByxssU6XrL5+itWyY20Gm7WMukl9XEjnFcW1sDP06s/E7HouNEwA0BCRA3tHTsSBLgLjwFCBdJ3AHizj1bP+5W7QC8ZKFIJS0LiKku3ARis0B8uW8LCMdpVyuna9hlBcjJSQBf+1oCf/zHYTQaXKDU8SM/ksXf/bs7uHlzteM95jhsdyt71812V+tUZJA1RihOKEC8yLA1khNwwgd9WQFSrzewuUm3kSri8TDK5RpWV61K2vV60xQWTaejE0759PLp9lltqWrOrFCttWkoTmiJoTBhQLwDgcJnJ2Po2FzHDDD7Fq0/DMRvV6tjAu4as6XR+kF3Wn46NaYtptUjGPbGunfRasKNN/4WmVGRz20GoK+vr0/AHdAlDisBCZBhvTMal2cEuAvPD/1ebfcl7vr0427VblBtLRTMvW9iQJquYkA6XTStOHyh0AJy2WxSuRzwta8l8S//ZRi08nOB9+UvZ/E3/+Ye3n67fQwIrR20evAF5jQ7GK9FAsSzaTyyJ7qsAOG839nJgVYQzj2KkEgkiGKxhmq1jmQyiqWlJFKpCRchtFjQ8so4E6bbZXVwVh2PpKy5Q/HBWBRT9TxoBcI7iEXhpgM/bK5jBhj/wkxVgZhVbPBirY5RmdUUULRisTFuhWxHtDFhCp/ntEzTAqImAldFQALkqsirX98IUHw8fvzYuF7RBesy7lbtBu21heJsscCFBF0XglFsH+QpZc7iKXrBq9UaKBQq5jAu0MLhFxVynz4N4h/+w7gpQnjzZgNPntRQr9fwS7+0jx/90flzJnlad7j4oN+wXROFVqSLxRg7jYfB8zyeook7bkPfaLXKPrBcZabfHKq0nkPPrsMALytAeFpaPeiCRYsHhUY+X0YmU8HMTAwnJ2WsrU1hdtYKwh3mZqyIpaypxM5aJOnYy3WF+h4/BUZx87TIH2t11K0Ff+S0Ng0X0PnnVgYqWkGi08DUG0C4jXAz2aWsZ082b6UmZ+tbgAQTVj2OURQgRrjtAayszmZi+pZHNnieqdH5XKcA4f1UE4GrIiABclXk1a9vBJjClgth/nn79m2Tlclrv1cvLRQGTOnQeunRbzycxM5JE41gwrw0egVzM1B3dzePTIaFx4Dp/5+99wCv7CrPhd/Te9dRLzPSaHrx2GNjwAQTQnMSIAUwBicQAmn8F35Ibsq9IQkh3NzUn5IQnDg0g20SCIFcDFwDNsU2tsdTNL2qjOrR6b3u/3nX0tac0RxJ50hHGs3MXjx6ZEZn77322vvsvd71vcVNu0UH9Az8AsAgwr/7OyuoBWlvVzA+XkZPTwbvetcsdu1qmRclsmLEiYeaAq+KzFlFqnf8OObU3hCwBIP1C9wbvjliQ8Dkd4BiCvBsB7pe3zjXPj0KnH8QSF2UdDnvXmDLr8sVT62teATy+QIuXrwE/g4GffD53Cvel+q0Fg5nEAplRPXObjehpcUBl2vjV0DimThmU7MihZ1amYArUDuRe6UjROE4f6i7MDkBS8vl1XrSoRKngNwUUC5JC1zPLvm7uhGgEIhzH0Y7EnkTUhmpl2tYtEzQQxtiQcGiAD8AGDb+dbpiPDhurCyJTNqKHE9q+jZQ5kgjtwufyazakwHQqOthI8fRPquNwHIjoAGQ5UZI+/t1PwJc8SF9iCJYvkDXoqkaDdXxadXHyEzIiYTZK37PpEwo6R0CgCwm5i5Ex5EbO4hMJo8I+mBu2SK6QeDR2emE1XqZf8wwwq9/3YxYTA+rNY+XvjSMO+7IiBUxro6R880yPYEGJ32qhXGjDjgce/KNCVrW7GVH4HD640DsmJwgMMys+41A/680dhnOflqmnds6gVJa8uP73wF0vPqK/TBHIlfKiQlkvUCssY7cOJ/mvTMxEce5c2Pifuro8KOvrxUmU/1J3LVGgxW+RCIvKFi8r91u83VxLabj0wKAMAAxnAqLJHb+d9MaNWesbpCOxQlyNVWIf0ucllUQgg6u7Lu3XEnD4mc42eazR28VtKlE0YFUQVZQGwYg3Gi+msKsjuuQusT+E7RxcYNrOEaXrOSs0NWwadd6hTtSLd25ELemi0Ir7J+22c0zAhoAuXmu9U17phTdqQBkrUrOpHlxVameCkVdF4IVkMKsXDk02hFK6FDSWYSge6GYmy4qpUwC6SP/jkJoCMVSGbOVAaDnlTB5OsTKcHu7S4h1q9vsrA78MZtTsFpj4k8EUARqbKpIn+CB2pOVtLUCIOxbvpyHSW+CYeb7wNkHJMecnHPSUBybgJd8AXAsH+g1f17H/zcw/X0g8CKgkgMSJ4HNvwL0/vL8Rw5OHMTXT38dyUISfZ4+vHXPW0USutZqjwABwsWLEYyPT0Kvr8BisWFgoP2mFY1H01HMJGcEBctitCDoDsJj86zf7UNgwXwPTqpJwWKFRK3wEXATgOSo24jItHJUEM/bkC7KZ8dN65rEqpAIT2R2ieuyrmb9rlxDR1IrhepG5UIBDIakwD1eKIhFIQKQ64IW29CZax++nkZAAyDX09XS+rqiEaDoLhaLCR3DWlVAKLYm132pCkVDnefqpKoBMVgwG8uhWCoJ/Ur1SyMxeh6hn3wPxeQULBiGLRCA3u5FKp6G0nsPbN174HJZxM9ijS43LMvzN6lSapWjGSJ9gj82gphmgT+mjz96/FGcCZ8RVYg3BzuwO/wtubpL8T/Bg9ENbHk3sOODdTn9iE4OPwyM/YekvVUKshIy8GtAy53iz5cSl/D3T/89ToROiOOWKiXcvfluvO9F75vPvGjoGl+eHQAT3wTix6VTUNsrAP+tK9rVRtuIFKmRkSjOnx9DpVJEIODDwEDrFdW4jdbntewPq2eJTBTFQhJmgwluZzv0hjWuCvA7UZIaDlCLQW0H73EdK6KVOc2IATB5ZWAqzTMIQPg5gxXxnAnprKRg3bQAhCdPcMZWh3MYJ/wMGFRKJVi8XvFcXo9WyGSQGB4WmSI8JhPVuUAVOXkS2dlZYfObt9ng6esTi0qaM+F6XBXtGIuNgAZAtHvjhh8BVj8IQqhpIABZSJthkixfLaa5JNmVDAjL2gQgtSoUde+PtAlWPFjar7bOBMBKAiksBAcsm6dnZpCdmUHo0HeRu3QcOp0Ck34W7qANZq8PBs8WuPb+AsyBviWpKaRbkT7G/nNcKNIn8KBonLSr1TaOO1fjaNPbLPD3Ly/8Cx47+xjKSllw6fcENuOPHDF4Iz8GdAYZ9Ea+uf82YN+H69dwkGIx/CUgweAwE9B6F9D18/PX4qmxp/APz/4DPFaPqHocmzmGHncP/uwVfwa3ZeW6BgF6Ln1NVm94J3p2AoO/DbgHVzv8G2L7RCKLs2dHxf3b1uZHZ+f6TMY2xMkv7AS/47mQXE1nM7kBa7CuSe2Kzoc6DlY0inMCanG8uVBU6jNoF85Uct53Jh9ga5P3O59D7KvehFg8MW9dvm62rTw2gRP7cp1pLfi8i5w+jeTICGitaw8GEdi583ISfK0LyYoUrwHNL+oAOIvdC7MnTiB+4YJ45poIMHbuFM/10NAQdExWz2aR1ukQ3LcPXr9fy2Za0ZdK26hZI6ABkGaNpLafDTsC1DNwIswVfq7Cqynd7HB8dBSZSQoMFdjb20UI1Ep4/awg0GVrYYWi7kHhyzZPv/y8fOGarxRrspJAahQdpcojI7jwrW8hF56BuTQGT6cd9rZO5OMzcG8egKt3Oywdu2Hr3LXk4Tke/FHF5hyXrq4u8VJayRjUOlizAQirDn/03T/CqdlTuLXjVkSzUUymJvG7g3fhjuh3pM0oaVe0Gm15MbDrfzQWfsZVTk7WCAIXiM+PTh/FJ37yCURyEXQ4O3A+ch63dd6GP3n5n8BkWEU69NCfA6EfS+oXq16ZEVl56fq5um+fjfxBAnNSFHkPqzbS/J7wXm7WfbbY+XMixvwQVmIsFsO1r7yUcnOCZlYhFID3zVoKmvlcmQ9FpYChKhSVIIh/I9VKVA3tsuq3QKfB6rGanbQuAGTeLjgjJ+PMMqHzVLNaA5WMlRyyXCxi5tAhZMNhWP1+EULYsmcPXF1dtXdHd61iTN4PfOZQqL9gAWrhhgQ2BBTVuSLCrvqFF0TlhaCHFY+W3bthstsxe+wYyvk8WJlJm81onwMgXHDSmjYC12oENAByrUZeO+66jQCdnDgR5m8KoenKxFYg9WhoSLwo+KKzeDwI7t0Li7vx1exqgFC32JqrjAVa7ZbkKiSpDwQf/HeuUlovJ4ez/+FzQygnIpj90TMIHTkNs9cFU3kMvi6XeOHYWn1oe9HrYO/cLgEM6RQ1WqFQECJz/uYEkMCGEwxWPVhdaUblQz0sJy+ssrAC0gzPeb5kP/LDj+DHoz/GFv8WzGZmYTVa8Ru3vhsvLg8DoR8B5Qxg7QA2vw3w7mnafUb6zOeOfA5Pjz0tUr/bne14y+634M5uSdFacTvx18DU49KRiBz9choYeNdV4vcV7/8ab6ja8I6Pj4t7q1pPxO8if0olBXq9CU6nFVar+YpFgtV0Px7PifyQfJ55Iawe2mGzrQIsrqYz3FYImievzJRgVsdaOUNxMs8qBye4bPMVEKPsC532hLbBKIXpnPwuaHz2kL7KZ0UzvsNLDiEBWmYKyE9LnQUrmrQR5ve5GSnq66Dl4DNq9vhxxIeHBQXL1tKCwI4dtWlYrFARBIpsFsOcw1a7BIM1GkMNuV9Wv3W0Q+/thb31sgaNieqxixdRymTE8fzbt8PsdouqSIZVbqMRWYsFnq4uQbddbabUar8O2vY39whoAOTmvv43xdlzlZ8vUU66OcHmyitbPpHAzJEjKGYyYjXJaDYLAGL1LbClrGOUuH9O5FlFqFvrkJ2RFpWkGyh5+dvcIh2Y6LJivTwZOP+jxzD13LegZEMwTAwjOV1EydIJXSWP3pfsQtveLbAHvLB37iZJWfrU264UR1Mkr1Y81FNif7kaTXoMGy1+qWNpViP9jZUhApBmrZ4emjyEh44+hPHkOGxGm6hCvPvWd8PC1WRmePBlbu+R1JYmN1ZgSL1K5pPo8fRgk3fT6o8Qfh4YfghIjciJqGc3sPV36gqJW/3B134PKgAZGxsT9L6FhgYECfwhCHE6TfD77TCbjeJ7yh+1WsL/VhcP6u31xERC5IQwKT2VKjQlL4QTzGy2KBasGYpoMFzO2KmrX1zxVjUZ1CpRDL6WjUBDTHDnQvSqKU38Gxc/hLiaE/6rz2XdAIhKF+OEnEJ50iDpAmjvnKvMrM45TYK/Kjerajpak8efWoz0+LioOLAK4qhB/RWHFACE2S0MrTXSslBWxBYBIJnZWYSPHUMhnYbChZ3OTkGnUish1HtkZmZEtYMLauq7jPdsMcvrrMNsNDrvakgQojVtBK7VCGgA5FqNvHbcdRsBUoxYoSAAoYBbFVlzNSly5gzScynjzvZ2+LZtg36uQtJIB1WaAif0dWkdRGoxrXZTcqVPpAWbJQeYlQtzCxSDRbxMiuk0zn/3i0iMHoTDY4czeQLpmAnpXACwdmHX/fciuKUTyM0CelZQMnICXqUh4Aomz5/VCDauZtIFheJwAgSOD19SpF81E4Codr48TjMFrKPxUVyMXhRi8L1te4Wj0HXdKKDnD69f4PYbBnzwmlQHEfKe4/3Ff+N9x2yQ8fG4CBakS1uhUEZ7u3PRVHPetwtBiQpUal3/mZkUwmFqHCDS01tbnXC7V36vCH5/JCsAE/N2nE6LqKo0DEJYmWBrxqr+Gt/4anW37mfbSvuj0sWKDEwckVkknIx7BgF790r3enm7a5znwfcNn+ekT5mdzssVETW7RaVgWVsWpWClp6elnoNU3ExGAIzWW2+FsU69Hp//pEOyEsnqB5/LWtNG4FqNgAZArtXIa8ddtxHg5JsvUYIETrCrKUZcMcpFo6IvVq9X2BSupHGlX+VJ101TyIUl8CgXAbMTMPrkhIT6A4NZcHkjZ88idu4cQqd+AKU4DFerBQFjDiWDDzpbJyx9L0Pny34WZrMOSJ2WFRUCGYpJnf0owTif6cHzEuJEk0m8fCiYZ2P1QwUgrIBwlbpZba0ASLP6p+1n7UegGoBwwsNqmNo4iZ+aSiISyUBRKtDpKggEaDetFyBFBczL9ZLAhNWR6moJgUmlokOMDnJFUrDMIi1dDeRcbp+1/k6ANDGRFMnsRqOsFnR0OMW+V9WE9igJKAVJh6LV6wYBJ6oBBse37uruSgZDTRxnTglpYxwDs0PSUalNWYU4W3SnOtGc+xIVkPVLNE+MjQkqVCGZFMDBt3WroM6KRvAlNEEUoS9eUSN4CZ84IWjDBqNRuFx5BwbqHm31u8h3IPUf1d/FuneifVAbgSaNgAZAmjSQ2m427giQGsUJNqkEzaYYqWfNiTYrLWy1nLZqjg5fiKRiVBieZ50vu+cIZqamEBseRuzsWRgsFowffRYVTCPQrkfPJj+s/nYYnEFYum6HvXuPdH1Kj8n96axQDEakyi6k84rIJ2HjCibpL3zpVIt/qQXhJIPghC8lrlI3q1UDkBWFmDWpI9PTwLe/DcTjQGcn8NrXAiuMNmlSjxbfDcXtR6aPCGvf2zpuE1Sv67ktBUB4XplMAdFoDuUyKwpm+HzW+fuT96RaLeHv6p/lxqSSzsL41DMwJZMw9XQCd70URpttntpVbUax3L7UvzMAcXIyKehc/A5ZrQZRsakO+ax3X1d8juCDFUxWL0k9In2Q4usN0NYNgIiJOGlS01KbItwADYDZLympjTRSm8RDb8GCEvV1dP9iI+Vswd/nqUoAzE18DvJwM0ePghoNitFTExNo2bWrIfAwfw/m80LYziqIjYYhpG3V2Vh1pOMhq5B81q8036nOw2kf00ZgyRHQAIh2g9zwI8AVfr5ECUBUm9mmnnSlhER4HKlUAjqDGW1dW1ZE45Lv3wJCRw8jM34W2XAIqckw8pkKdD4f8koBvt4A9t21HQYlDti6oSNlxzL3gqYDVCGOQiGPeFZB0UCHE72YKKlJ5qr+pfr8+VKiixcbOcHNfClR+M8KFPfL1dNGOfwruk6cfFALwmBCxyak8i587GPAT34CMGPR7wde+Urg13999YuqK+rfEhudDJ0EbYbPR89DBx22tWzDbx34LfR5+5p9qHXb33IAhB1hJYQ/alVhuc5xosjqCO/dhcCEf6vkCzB+5guwHnwBpgwd0QIo3/0ypN74xvmLzntRpW9V601UYEKwwT6RulUN2JPJAuLxrFg3YMgnqyqrdvMi3Yi6B2Zx8L/V7/RyA7EOf+ezgYsUHKO6DTZW0y/SUzkG1EUIHYhvUUONmochpYluctTCscpRp4MW7xtmaLDyzOvp6OwUeRnNatGzZwXll8chZYoCcXePXFyoEFzncmKxqdrZqlnHVvfD68jrqeZVNbPa3ey+avu78UdAAyA3/jW+6c9QfeiSgsWJcDNX+MXg5iJIhi8imUxBZ7SgtWsbDLaVrV4mIiHMPPc9GMpxWExmxIYnUSjZkC0ZYAgG4dm8GVt298FA6hZX7xgWRucaWxsq5RKS0Wlkslkoeit0eoOoevCcl3rRcALHVTG+GPnZZpblCUBUh611ASCkMlz4DBA5JMMEnZtxPPdr+Jt/lBzy3l5gaAjge/9DHwLWKR+s7u/ggy88iH8/+e/YHtgugg5H4iO4b899uHf3vXXvY6N9sB4A0sw+83jpQ0PQ//3HoE/EkWrrgnPsIvSbupF47++g3NKy5OH4ncnlpH0vnYm8XhtaWxnQeXk1nba+grI/R8Nadf83cAVk3QGIOphcSGAFpBHqlaojEdkmc1WOOl3GmBQ+MzSEYiIB6jUoHqcpCfUazWjFXE4AHGr6SPel5TspvxSHR8+cEdQso90O38DA0pkhq+iMygbg+6DZer9VdEvb9CYdAQ2A3KQX/mY6bXUCRJ0GJ9fNXOEX45idRCp8CcmCSay8Bbt3wOho3IEpV8hhOjKO2JHvQh+ZgNnkgb+zB5bOnUimKsgWCrC3taE12AJjJSHda0hTMPuQyVeEzXC1yFylWy1HNeE2THInACFHv5nCRNV1i5oTrp7WqsA09V6c/j5w/jNAmbkGDiA/g3H8PD70hd8ETWA2b5YAZMsWCUA2mg3+p5//NL5y8iu4vfN2EbTI7BECkLfvfXtTh2k9d7beAITnlj98DMrf/h0q2QLynd1wXboIc1cbch/8AIrB4HzVhBUUlaI4P++tVED3rEgkB5PJAIeD9r0OofOorpioehNWUmpVQGSVRoHBoFu+QrKBNSBcnFAzjugiuKGbEJpPSXcpZp5QU0H9SB02x7lYDKEjR4SDlBrk17pvH8xNFmpz39X3C211w8ePQ2+xCPtc3+CgsO1di8ZqNJkABCBMQW+m5fpa9Ffb5409AhoAubGvr3Z2pDXNOX9Qj8AHbzMn2GKA81Gko5cQj0egM9rR0rEFJnvjFZBoOorJ2CW4EheRnTwBh8mKQO9tMLfdgunhcUSmp2G0WtG3Zw+s5CdXSiiVFcTnMj34YmOjuJyVDFVkvtxNwAkYnVHYCNCaOT7UxRCEqBkjqgPZcn1a8d+ZKn7hs4Brm9TUhH+Cku+l+Pj3/ieefRZIJIC2NuDVrwbuvbexxdUV96mBDX848kN8aehLgoLFti2wDe/c/04Runi9tkYBiKDCJAooFKTQm65VjbpMKZkMSn/7Meh/8ix0hRyMXg90r3g5yu95D7DA5Y73fzWNK5XKYmhoCpFIWtjsOhxm9PdTG7W40HwhMCE9K5EoolhUYLMZ4ffbGj6Hhdeb9EzSg5gtYfZ4RF4Rk605cTU10Tp74XGvKwAikuZn52yOScFyARa6SjGEcelGQxLSpNJTU5KC1dEB35Yt9Wks+Oyt4xi1ehC7cEHkhlh8PuTCYQFAWnbuXK67K/o7q9FciCMFi46Qi70jWJXhOIiA3tbWplWBVtRpbaMbdgQ0AHLDXlrtxNQR4ARjampKVAhULURTR0epIBMPIRYLQ2ewINDWU/fkv7ofsUwMoegwDNlxAWp8Jh18nl4kch2YOH4G4elpmGw2bNq/H8GtW8X58IVSLTIngGiUQlUNQFg1aaY3PPtH4EftzVIvvKZdj9lngHMPSr9/CvMZ8tj9BiSDv4onn7wsQn/Zy0ifadpRm7YjTr6fHHkSzDqhCP2OrjtE0OGqNQZN62HjO2oUgFBjMTubRiZTFACE1QdO4Otu+RAM41+DbvYkcD4EJbIZaN2D8mteQ5HTsrthbsiZM7PI5YpIJHJoabFi61avcOlSgcpyOwmHM4hGs6JiYjAY0dXlgd/vXJUAPnL6tKDw0AnJ5HJJnRn1BHY7vP39tYPulusoqV8ig0IvtRLVGSFz27I6yvPmZJXf4Q3fCEJYCSEgMFiXTRWvPh+CEFKxhG7O41kefJDyRb0KqbCsuJo8DQMRHo/aEP62OJ3wDAxcdsdq8mBzQYjPYwIQVrNqLQhRjxI6ehSJ0VGZNdLVhdZbbhGLX1rTRqCZI6ABkGaOpravDTkCnNRNTk6uHQAhC2uutM0X10Kr3yUHRQgu40KvUNYZEMmmUIqfhTUzAruhAos1gFjCh7GTs0I9nRwbQ+fOnbD39aJULgudBxtfKAQOKxF5c3wI0Pib4OW6BiAcz7GvAqGnpAbEtRXov3/DOAptyC/IGneqUQDCifvUVEqIu/nfBB/t7XXmFShlGM59EobZH0EhBUcpQfHcgtLgf5NuSnW0RCIvrIFzObpuVdDW5hAAQm2qAF4FI9VCeLUKOTOTFlkhTF/PZEoiK4TnozbSImvlmSz2/eWkcPrQIZEjQevWyMmTYqLr7OlBMZmEp78fwd0MIW2gMXWcieNFir0ZlOKT9t0LbGCvOwDSwBCs6qOsetCxiwCEjYYgtPU1Na4ZYcWhmEqJSX6zKV/V58hqNBeu+L5YjBLLgN7J555DmcG6JpOouLXffvs8KKJWhdb1BrNZVEcaceFa1XhrG99wI6ABkBvukmonVGsEJiYmBBVIzcBo5iiVKP5OJ5GIJ2AyMMm5gTC/fAzIjAMVahac4gVWTI2hPP08YLID+gpyBR9mxxRMXppCSa9Hy0A3Al1+kZxutHjgDnTDusrsDgI0Tp5YASFdqlmNwIzif9ofryvnmJMCWnqSflErT0FMHqakVoRhZ1wp1dqajECjAIQWt6yAUCV+JOAAACAASURBVATOcMKWFjt8vjorIPkZmE79pdD+KK7t0LGaSKrilt+B4r2lrvOjwJxhgwQOJhMXFGx12+yS7snzjURSCIVSyGbzYh8+nwUWy/IlN1K38nlqBGiZzbA4+1wVxYDwyZMiR4JgpELtSrkMW1sb0pcuiaTt1v37YW+kQlFMCf2a0JHxu8IwT+ol+P+rGumZPC9Wj/kdrqvx+8WqQKMi8rp2vkE+pIbJchxZbaUmj8+SOl23mnYWBJBl2jczzd61pN6F4INVEF7LxUxBWGGbPnhQLHaxqfcWKX8EJwxCzIZCohrPag1palrTRmAlI6ABkJWMmrbNdTcCXOEnAGGFgpPhlTbSldKFtHAoshqsMBqMmE3NIp6KI5VIwWPzoKutSzhtCW55pQSj3ijcqK5qfEnTLjZ1UdpvKgWULJsQO38apemnUVAS0AXaYWzZinTEjKnxWegtdrT3BGEzleGwO+DyMpCwAzDWOUFb5MTVCgg1MqRLNavRdUXNX2kImC3XAb7808OSauHokXab9TZuO/rvQOjHEoA4+4DN7wDsnfXuQftcAyOwEIDoLXocmjqEbCmLfm8/+n39V+yNQDiVKs5rQFwuS/3hgcUkjKc+Cn3yFCrOQeiyY4C5BaUt74VCXVCdTeaPVIRuY6XBhdksLYIVWCysdshgxYW2wQuDFgl8WPWheJ3i90CAyfFGScErlZCbmRG/LQ6HSMLOjo0hG40Kjj5D6eigxAljXY2gIz8jAxAFBcsn80cWaBn4bOCzTLVuXXbfzDcqROZMMsyy8lSHCHzZ/W7ED+QjsgLCfBFWPiyt8lz5bCcg4bOG4GStQiVFbsqU1LwoOnkNa1Sx1KGj/oOLQgQgDMxdjNrJoMPEyIikYHV3w9nRIXZBwfzMoUNCg5SLRIROpvPOO1dsO78RL6nWp/UbAQ2ArN9Ya0e6hiPAVTyu/rBxIrzSRqF4JB1BoVyAw+yA2WBGLBuDvqLHZGgSbqsbg92DMFvNCKfCyJfysBgt8Dv8sJgsVx6WK1epc1I0yYmwyYlE2oPYyZOoFM8hnZqE0RtAyrcJRoMHKBkERzvgdaMt6IXJzMDAilx1MzlWekpiO46POslYDUBb2Ak1ZZ2ghqunnMSsunGCM/IlIPQ0UMkD9m6g/x3CcreuFjkInP30XO6CGyjGgI7XAtveW9fma/ah8eeAJ98NFGclHebOjwH9P71mh1uvHVcDEIPVgEfOPYLD04fFd6PL1YU373wzDnQcaFp39FPfAsa/CV0+BL3FjUrgxSj33S9X4zdYE8F3c1kmhUIRo6NRpFI5mM06EMC0tjpAAFarsQoye+KEqID4+/uRm55G665dCO7YISq9demGqGEQlrW6msF8PG7DAISUUjpRiVYBzLQJb91gI9+k7gi9SXoOaFilhobggwCM48C/i8p2cG1ACN8hooplBMpFwGBa0vWL1Wg+k6nn6WQia4MtOT4unMJIGSM1iynsbbfdVt+91uCxtI/f+COgAZAb/xprZ8gU2pkZAUA4ya6bRrBg5DhZmIhNIJ6Lw2VxIZlLwqgzioqIQW9AdDYKr92L/s5+FHVFTCenYdKbBFhpc7ch4JyjL4gXVAzIh4FcCAD97s3iRZWIWxA9/gyKShxj4xPQO0wwdrbB4eqAvmyFw25Ge0cXHFaTpDgIl5fVv9xUnnfdq5x13lXVAITArynBV7PPAucekONn9koedvsrgR0frK9XE49JobqjV1ZOIi8A3l3Avo82LCCt74B1fCoTA/5tF6DnxE26maHcAryRfZMZJtdrqwYgx5PH8aUzXxJ0v4AtgDPRM3hJ10vw+y/+/aZNYuKxHLJTh2EoTMLsDMDV+2LojVfSijbiWFJ7MjwcBX/bbCa43aRzmmE2y+qJ+qPqTHgOXKWOnmPopgKdwQDvli3z4XYLgxZV2+DlbLkXjo1Kz+R3t67FCTVU0WCXk/MNFKq4LtedVYnshAR2rNDyNxdJBNVzcSe1FfVNTY5nFYsULD4PqUNZoONR981qNHOx1ApIo8ck7S927hwyoZAIU/QODopME61pI7CSEdAAyEpGTdvmuhsBWknS/YOUh9U4ucwkZgTliguGuWIOOkUnVnKVigJD3oAWVwuC/iAKugKmElOiSkKA0uZqE38TjS8lls2LOaBEAaNOlu4tfhQKwPSRHyBy6SQSmQjyRRNMTj+Cba1wtrfDaPPD3bIZTjtXRelzb5WrX6tsawVA+LJjCj11JQQgy4ZAEpzRruq55+QZHTgA3H33lcBg4tvA+X8GbD2Sb00A4dkB3PK/6nO8CT8HnCWACUkAwtXK9lcD2//bKkdxFZsfehA4+tuArgQoDkDHVVUDMPhh4CV/sIodX/tNqwHIwdhBPHz6YbQ72+G1eHFo+hB2BXfhT1/2pwLEr7aRNjU5mQR1JKRPMYOjvZ3ZP02e+K22owu2z+dLmJpKY3o6iWg0JxLWd+wI1tS+VIORXCaD6PnzyMTjMDkccPX2LpukrQrgq9PfpVtX7fFvGIAIcXvoSgqWuQGKZJPHdt13xwwSViUyk7K6SvotaWj2HlkJaaAtzAypuSnHW2hAWMVyXqXhqd4mEomIihsXmtrrperVOGi5WBS0K02A3sDF1D561QhoAES7KW6KEeAkmOVnPnzp/rHSVigVQLtcgo5ENiG0HRaDBel8GqaCCR6LBQ6HHSabA7OZKPLFvKBeBRwB2C2kTEG6zhCAVBSgFAPKJcDRhbLehUR4FOnZCyglphCbCCObUOAJbIbNaUcl0AJbey9cHn9TszrYJQI01WpzpRWiWmPK8WaSMp21CECWDYF8+mng858HzsscDAwMAPffD7zkJZd3Hz0MnP0nIHMJMLqBclJSqLb+Tn2XlRSu0S/POWXlAHuvpHBRS3Kt2tHPA4feA+gKQMUB6DOAYgS2fRS4s87KzrXq+zLHrQYg4UoYnz/1eZwKnxLaKIfJgddteR3u23VfU3pfDUCou6B+43oAIOl0QVQ/YrE8kklZAdm2rUX0vZ7GlWnWzarBiUrtWhi0WGt/2Qg1G2XYfD7YXC5B4VIBChcn2Lh4ULc+jCvzpEfqjKvWp9Vz/hvuM6xIZEYlFc3aJvUZVlLR6tPniCwc6ntmZwWgdPf2NiUdne9BLsIRgFCErjVtBK7lCGgA5FqOvnbsdRsBrvxQgEdRdDMevCJbJDqKXOggjOUY9AY38ko7bCYrnDYz3P42FHRWFAsJMdGyWLySn8sXslKBkpmCLj8JFBKiLJ8qmIVIXuHkuJxBIR1G4uQ4yokMTJ5NMHrbYOjrEwLTZbM6VIoXnbV0FoCrj8tUSQgS1LTj1VSIFl7QhgHIv/4r8OUvA7fdJnf1/PPAm98MvOtdl3fN87v0n8DMD6R2xtEH9P9q3S93sSPugw5JrEbZu2Ro4bVsrIY9sgdQLgK6sqx+oBP45aOA/fqmOKhBoPzuMeTydPI0Hr/4OFLFFHa07MAbBt8gKoXNarS/ZRVBurqZ0NLiWLGQvFl9Wm4/BE7nz4dx4UJM9JnVm95eD7q63Kvu+8KgRRWYqAL45KVL4A9tV61+v6BxmRh0OtcIQFgdoUU3nw3VoYt16UyWO/kb9e+FFJCflQ6HtOglFa1Oh6zM7KxwPcvHYuJZRYOB4N69qxZ78znP+4F0utUsxN2ol0w7r/UdAQ2ArO94a0e7RiNA7isrIHQAWU3pubr7mdnDyE3/GEo+DrPRgmShBXD1w+FwweOySdErRZ7UeBBYmDzIKgbEimWgGIWtGIGSjSNecsGYj8KAipg0Wcwm6JNTiJwNIRU3IZc2wL9rLyy7d8NgNKISi8FuMknKRWc7dALYVCX9EtSQAsHSPGkt1Ihw9W2JxpUx6jW48smAqmY1rsiyusIKCPnjy4YkPvQQ8MgjwOY5QfnFi8Bb3iKrIAsbNSDkV3OFcYF1aLP6v6r9pEeByW9LvQ9BUtfPSqHvYi12Cfjuu4DsJcDSBrzyAcB//VtcLgQgvAd4n/N/DFtci8YU9UpFgdlMB7pFUrAJQmdmoKOglqvBq7SyXu15xGI5DA/HhPsX80MoQG9tra8CspJj8xoU8nlMPP884hMTMDidwmbVPTg473rEz1RXQAggqxuBSXW1RAUnjepMVtL/62IbPoNFJcggv/t1pqUz8X726FEYnU4UEglRmQreeiuM5tVRCXktCRpZzWrmQtN1cS20Tm64EdAAyIa7JFqH1mIECD74Qw902g82oynhF5CaeAIZUxCW/AQSWSdMvj1idcnrdkmRODUapQSQm0HZ2opQOoFkPotKKYdoPApdagb6Sgk2mxcBpx8eCycfDsSnYwiP56GzdSEzE0PrrbeiFAggPjqKwvg4rLoyHG4DvJt74Ojolatr6iQ8H5UcZAoS+d9WvxRALtFYISIA4YSimStjnHzypceJCwHIwgnMVV26cAF44AHg7FlZpdi6FXjPe4D+K61aF273wuQLePzC40Jvs6t1F16/7fWwGpvguNXIjUJLTgI/WmHyWpz6/4DI8yKHQvxb+88AA++qexLSyKE38mevACAOqwShVYCxWCyDP6RMETCsS1MU6P/rv2D4wQ+YIgqlqwvlt70NSm/vuhy+1kEE7SZRQDYr9Ssej1XkoKxl4zHpasTUa73RCL3ZjMCuXbAFg4LORQ3X+Pi4+G8Kl5ddQJjrLAFILWCykqDUtTz/jbrvQiolKiDZmRnoLRZhLODbunXVRg10O+S1YRW9mVTbjTqOWr829ghoAGRjXx+td00aAdKvCEBIc2IFpCZ1gJaJ/KknPKuUQSZ0GImpp0SasGJwIl7pgdu7BTYT4At2A6W89NkvMajKioK1G7PxUcQzBSQTUYzHwzCXkjDoKnC7/NjWvQkBmvU4+pGLhhCdyCGX1cPqcsG7dSuiuRzCx48jOxOCv6sV2fHTaNuxFa39PdL73TKXb0KNCSfC/M1JOAWQ6t8WGU9WiEiR4cupGRQ19TAs9/Olx4kLAUhdKesMwDp8WO7illuAnqW1Gecj5/HJZz+Jk7MnxXX1W/0CgLxl91uadPfUsRta+458WTpzmTyAe1DmjOit0hYzdhRwbgL2/lljmSV1HLrmR1hxm/4ukDgjrUFbfwpw15+DsdLD1tpOAJDJSzBMfgOuwimYzFZUAi9Cpf11KBQVhEIZkTpuMhkQCNjWRTCuO34cxgcegG5sDApzgaJRKC97GUrvf/8NDRAZYshVeAqI1Zbj4syFC1AKBVgDAXg2bxZghE1QTaekpS6/w5y4LswyITipR2fCfSwUwKtp8DcMMBGuV5k5W2PnqlyvWPnIxmLiWtiDwWXNBer5zvJaqnS61djR13Ms7TPaCCw3AhoAWW6EtL/fECNAC15OsvmbK/xXvfBYKqd9pEIvdZuctC/myjNnfZhMjiM+8ywsSglZApCcDwG7H1aLEX6vZw4E0AsegLUFRVMQw6EQwpkcUqkphOLjSFfKcLq86PD4MOhrRZvTAwMzPQx25DJ5VPIlGBxulMsWnB86LoSJ8VgeJrMJVgfQvn0b+vo9MLs7r6RZEXxUChJMMSBrGaoLwVkmkxHjcs0BSIN33GNnH8ODhx5Et7sbHosHz008h9s6bsOHX/HhVa8Y1tUVJiEf/wuA4nhru7QF5v3DcDJqb+h+Ez8GuHdIALIWepNiYi753S+v9fj/Acb+QwpheQ949wBb3yuth9e5EYDETjwC8+RXYVYSotKhWDtR7r0PYcNtmJpKCdF1JlMQwXttbWtHO1JPXf/EEzA8+CAUGlL4fNANDUHp70fpT/4EqDOrhhQvVhBYrbgeGjMc0pOTAoC4urquCCykiJ0/Cyk+1QCE1cvFKpj8XC1gsjBocbFx4sJBtbakGphcNzoT1RKXoYB0NhTBjotb4l6Le4aOZqxMqQtC16IP2jG1EVBHQAMg2r1wU4wAKx8EILTipcaBL7grGt1KuHpNkTgncNQVLGYdyVWu7ISw4Y1FTyGfSwkhczEeE64+Zk8fAoZJuT97N5R8GKmSA2lDN8o6AzLZOGLxYcTzs8iYTEgpFnS6AtjSshkdnhYYiFjIGxaraTmUyiXMnp3ByLkp5AolJONl+Df1whe0wuC0o7PTD2egfVUTWxWAcIWyWRoZji8naFx14wuPDjq04212+97F7+FfXvgXkbnit/lxMnQSL9/8cvzhXX/Y7EPV3l96DDj+UZko7doi3bkI/ngP8b9ZASMFjhqQ7jc0t0+s2I1/QwryCXhcg8Dm+4HTnwBmfwz4b5eBaMwlGPg1oOue1R//5LPA1/4KyMWB7v3AOz4CmBbnpnMSmnzhr2Ce+SYU3x1SlxE7hHL3mxD2/LIAIAQl1D60tNjXVPcw/+IbGhIVEHBCzhyDcBjKXXeh9IEPXFEBIShKJguCus9AQAIlNv47NRtMLHfaDPCfOQr9+DgUpxOVu+7ih1c/zk3cQyGZRGhoCEy4JrXR0daGlr17YVpG96LS59iVpQDIYl1dKIBX0+DrBSbcbzUwqaZ1bThgUh0KSNolFx9Y/Wx29scq7ouJiQkRQshrWbej2SqOp22qjcBSI6ABEO3+uClGgNoP6hwIQCi+44tsvglHJDpSxUTlAUVWLYqA0SXFw3yBUM8hwIlOcvq5yp2PIZedQrGYh97iQyZVElx2k8mIoFsvHFAKZQXxRAZFUxvg2QqdUoFFiaKsxBHNxpAqVZAoVBB0edDt64LH1S0rFkLHMSXoOoXEJMKnL2BiuoCK3oJYQoF/2z5Y3XY4HAQMHlgdq1s1JkWNFRC2Zmlk1PHlqhupG3zhrcVLL5FP4B+f+0ccmTqCfDmPXk8v3rbnbbi96/aV39u8Jyhwp4ZnOaE0w9aOfRSIviAF/3S+YbWDtsDJMwBXRG3dQMuLlt9Xoz0OPw+c+2fp6MXKHe9TgpzMODDzJODbLyt7/KH+pPM1jR7hys8PnwQ+8XOAaQIwlIGcHWj/WeD3vrjofjnZTBz5JCxTX4fO3gmTUQddMY5Sz1uQb309wuHsHAVLLyhYVoZsrnWjBuRrX4PhRz+6rAG57z4oqvkBgEKhjOnplLDFZaMmg9UZitqZNUK3LQL2lh9+B8HnfgDT7AwUhwOVAwdQpm7pGovaq4cwF41i5sgRUeUgADFYLGjbtw9m99L5HNUAhPTJejUgy10+LkxUWwZXA5PqoMWl9lMdtFgNTNZdAM9nRSkjqVci/bywISsgHFc+iwlAeC1XuhjEe4mVeFQqcHR0CDCrNW0EVjICGgBZyahp21x3I8DJtWrFS/EdH8JXNL44OEkrZqVwmAnlpK44NgG+fYBBB+htc2Jvo7R/ZYWCK92sWOiMiMQyyOezMOi4ktuCZGQcmfiMBDDWDugZIugww4YY8oUMYtmY+LzewJV7J+wmq3RKsXcCSgmF6Cgq2RiMJgXJqWmMnrmEZDgNnTmI4K4DcPYwE8QmVmYbadl8Fsk8aQIQie42i00AM4I0tkU1Mo0cpOqzaw1AeCiCkOfGn0OulMNgYBBbA1tX2Fsub08AIw/L3xTy9/4S4Nm59P6iR4GRR+bS2T0SBARfuvI+1Lsl7YjPf0ZWPnjvhJ8FAi8C2l8BjDwKpIelBSiT3rf+P5ISUt0IuunWRVqYs395gPTA78oMFuYaVNyAPQRkgsBHTgP22iCYk9jQyCFYxj4HW2kcRpMZimsbSpvfJQAbqUylUnkuOHAd6UycOE5MQJfJQKExBcXxVS2bLQqgwZV29pGhhh0dLtHPiYkkMpkirOU8Ap/4G3gmLkJ/y16hKYHZjNJv/iaU/fvrvYpr/jkGx0VOnkSaeg69Hs7OTvi3bVvW1lXNcGEHmwlAljrhWlkm/Ld6gYmqM1kogl8znYn67uA7gdQrfpf4XWQo4Aaqfqh0OpoJEHwsZQhCoFouFETaeXXYIP9t+oUXEB8Zke+Pjg607t8P8war+K35F0o7QFNGQAMgTRlGbScbfQQosFbDCCm+40P4qkZAkRoGJr4LVDgZ5ySrDAQPAPY+CTQo9uaktEZThdx0k6ITlqAZKCXuBQ6XV6we6llBEdWTCCqKDiW9BUalDL2Sl5UXwfXoRzquQ+L8SZQzYVgdJTh7N2P0+FlERkah6Dxo7xuEb8sWeKtWbOu5BsVSEdOJacSzcfFxj82DNncbspmsEOhzskUNSDNXEUnBEs5gXq8Qom/oRhrTyb+dE5Cb5aqm7xZgx+8ClqWtjEEdBqsf5H7zZz3a9JPA+QclIGaqO6lWnffI6gsrMonTsorT8uKrndASZ4GLn5PVEvUzm962uPaJ5/Op9wEX/xkoWwDFBdimgKwf+PBpwFmbXqeuohdTU3Arl2B3OFFx75Ri/Q3cmM0RCqVEOCC/F16vRdDDWAEJhzOCgqXE4+h58GNwzIwDe/dCNzHB0okEILevogK3BuNSKhSQIwVLp4PN74ehDktX6jpooy2eFR7P8kGia9BvdZe8j1RwUq03qVcAr+pMarlzrarbgr4bAUyuObpl+/p9/xvouAom+e7js3ixahbpepHTp0EnLovHA//27fNUPf5t4tlnRWYMq2iVQgFtBw7AsYpw3wZOQfvoDTYCGgC5wS6odjq1R4CggACEIIEPX06IFzauchZil2CcfgzGAp1f9IDRAvhvBVwDsuLBJNtFHKUY8kTHJ74oVY91tdw9X3ERQsWQpHvpzXJSyIlr6px8eZH2Ze/CzNkQkmMjsDgU6LIT8GzuQyhaRujcMBy9e2BO5uAbHETLrl1LX3JBD0gBZSmIzikmTCQmpTCeTQd0ejpRzBeFQJ8v6Zoi/VXcWBwTJu9yArPhnVc4mTj2EVnJoGsUJ+ek421/vwQiG60xZ4YAJHpIVuNYset/p3TcWqrxvjj518D09yVPnRMoAqzB3wQCBxbf8uiPgc/eC9imAb0C5CyA82XAnzy26DYqAOF3kFS8Za2YN9AYU5eSyZREjxgQSKcuNj4rWAFRKgpcX3kYpu9/D7poFDCZUKFl9nvfK7Ul13nbSABksaFUdSYLRfD16kz4zFssz6QunQmf51x44MN0Xj+4McA1KxYi5Z5aGpcLkXhcPIv5DuR3sVabPXECs9RI2WyoFIsI7tsnFrvEfZ9LYub5p5AYvSTowO6+AfH36uDK6/yW17q/jiOgAZB1HGztUNduBOhnT4BAsTWpBAxiqm5c7eSqJicVpsQR+HTn4LDrAHuv0G6AwMFIClaLXC2uaqQGsHpAqpGqoyCNiStMV60yqdoO0mIqDNFrBQxOIH1hTnPA1HI9QmenkRw7C4utKGhhns2diGUtmB6OoJhS0NreDu+mTfBs2SLCCRdtFEbz5VjMiP6XTT7M5HKC/sXmtXnR6m4VFRACELZmAxDmgBCAEYBseO95jtfQh4H4ccA5AGTG5AR9xwekwHwjNlZtkmdl6KVz86IVuiu6Th3T0+8HJg8BpgHAZwF0cWDLu4GOVy19lk/8G/B/PwbQ/SuwDfitTwFu/6LbXGsAQl0Wv6MED3VNKBu9xpkM9N/5jqRfud0ov/KVQHd3o3vZkJ9Xn5viWeH1XvXc3JCdnuuUqjOp5c5VX78VGPU6GE0WGE2mK8TwV1SI+W6odlA0eZeuItZ38FV/ipbL4VOnJO0OgLmlBUpLC2x2u6hEL3wHqgecOXpU2L1T35GZnhYAI7B9u9Q+ZidQjE0gPR2ConfC3rcHFl/Lqvuq7eDmHAENgNyc1/2mO2t1JY9ia9XPvnoQEomccOPhBIXiU78jh/Z2B3RMEKdFr0JXE7Pk9PJBPCc2zJf0SGR1KJZKAoQwaZ0l7i1btlzttMUDqiGBBDEixbtVghquuAvxOxPTXcjEFaTO/VCI400OL5ybBpBEB8KTcaQnJmAvlQRHl2Vw38AAPAMDMBNU0RVJdWDhalwuLMXsDCrkKretFQWjB+m81Hs4LA6YjWbRdxWA1HQJW8Udc10BEJ7n1OPA2H9K4EZaRdvdQN+9y+sjVjFG674p3Z8e+TVAOQqUDIDHDAy+GLj19wHv7qZ2RwUgmQy/Gzb4fJ5VW9dSn8HvKfUYrEwsBixSqQKi0axwq+LnaPO7aDJ6HWfNSe2agJg6jr1eHymXK+JQHNvrGYAsNl68hrwnawGTeZ0JwTyr1Kx+Cu2fV2oC51q1AF64dIlEeCP0hnUK0qzjZmC+S+jwYZSZ/QKgzGva0wN3MCgq0bVYAPwcU9ijZ84gn0jA6vUisHMnbIGApHkKhz8aslCrpQiXxzWxFa/j/LSPXP8joAGQ6/8aamdQxwio/FcCEJaeF1Ym6GhDAMJVUk5ufD6rEJzWnGzkQqhkQkK4nS3poBCk6O0iyI+fZ4l7UR0FX2wEG3yYE8yYA7KyQuBAJxU+1OlmVCmiOHsc5cwUTCYdDPY2xJRupNJ5ISbVTU0JIMKQKmdPD9r270dg68DlfbPCQtBBkEOKAFfpaAspAM/V+gQK0Dk27P9VLmF1jO9SHyGHnC9pVkBUatoqd9nUzcuVMhRwtXNu8kB6EisKapo8MzSWc8Jqao/WYWePPgr8x2eAXVHAlgbiGWDrLwBv/5umB/Fxsjc8fAnT0wmYzRb4/ayEOVac8k0L3FAoK76nZjOds+zCoWphI01KdasyGg0sLKK93QWnc3HL4MVGnhXSSCQjQA+teL1e66pB1Dpc5YYPwedgIkHNCzUfNpjNiqCusnHVfLFJa8MH2qAbzAvgk5MoZWfAuTt1cwrd7bgYsUxbGLSo6k3WTAC/RH+o15g9dgyZ2VnpfObxQN/dDbffLwAI31OLNYKXUiYDk9MJi+qURuAh3CKjcjNqIUkhVp+byw2O9ndtBBaMgAZAtFviphgBcrnPnBkRq/wuF7Mzriwbk6YxO5sRkxqu/Pn9i7tLpWfPIRWdREXvgFJKQ2cNwuHrFOOoCrkFjUlXkRN/rpwxkVxtrFCoIXX6y5ajdKrhS0NnMMBiN0JHsTqp9AqiAgAAIABJREFUUwQRZhfi5QASsSRmjx+HKRxGYmICNp8PZqcTwT170LqjTwbPFVKS3kVXI2oBWK1hrghBCYXKNQIWSR0jPY0ApKZL2ArvEvL+h4eHxQuPP6yubJTG1c7vnP8OfjDyA5QqJdzacSveuP2NsFD3c6O3z34WeOQR4MB+wJQFnjsK/PxbgN/4jaafOQHI0NB5TE3F4fO5YTLZ0N7uhM93tQ5r0YPnadJQpBAD0ZhcLHC5zGKyzO8qgcXCxpV8AhDmeJjNBqHb4Oe4XaMtEsliZkZWDTk5Z/9rgZ5G97uRPp/PlzA5ySpuUXSLQM3nMyGRkHTNmwGAzF8PVVhOR6tyFmVzK0p65xXWwaygNCqAVzNNqoHJWlbUGD6ZotMbdS6BAIoWZtnYxDO+phHLcjck32ciaJGiErp8Ne9ZScpYKZcT2hO94XK1abkuaX+/fkdAAyDX77XTet7ACExNJXHixEUkkwl4vU7097fD4bhyIsIJC1c4SdGwWK4upfOFw6pHPjUDXSEGpVKExeaCO9gPk81zJY3J74axHJPCdYNJJmMvsYJGOhWdR3KhSRgMBTg72+FuCwDFiKyMmNxIlH1IFY2InDqFPC01L12CyelA5x23wrd1G9xtbiBySNK8SnHAsVlmT8wFKuYKOWFTa9Ab4LQ4r6jukDpGgT5fVIu6hDUw3nwxE+wR2HAFlS+7TZs2NTVlvYHu1Pzos+PP4jOHPoPh2LAYE5/VhzftehN+evNPywmYeXXZKqvtX1O2Z/UrclBSCD27pEaEjfkXX/gCMDoq/39XF/DWtwLULzS5qQBkcjKOlhbSr6xLAhDSplIpZm/o4HGb4Xj6h2ByOd2llG3bEHvt6zGd0aFYlFQhhhcGg7UFtdlHv4ryU8+g0NaJwtt/BS2dXhF62GibmUkhFMrA47EgHs+L6iiBz43UVNvhClmcFUWANr/fiFQqIU5z4ao5P0Nwx++61WqcD2m8IcaEWrBCpEr7F6w52V4YtKjSuuoVwIt5PClccz9rEbTIiT1bNp8X7y9WPrgQdEUW1jW+aKR78b0mnLfcbvh37IB5EZH8Ne6qdvgmjoAGQJo4mNquNuYIcKV7bCyBc+dGYDAUkcspGBzsFDSKehq352Razcng/9eXM3A5bXA4vYDJIdLKWf3IpDOSxuQywFSKSME6g+qs/qttUKsOTqHgzNARGBGHkg3D6vcjsGO3yBQRS64wIZGvIFVyI3L2HJTxcVSyGVgdQHD7JvgGt0BH1674SSA3AQghpAkI3Cp4ugQfoVRIaD+o+fDZffA5LlOxSB8jAGHjSudS5fnlxoxghi869SXMygopbww4JDVtvRsZVefOAdTYc56tduGRY4/goaMPYXfrblgMFvx47MfocHag1SGzMg50HsAv7/xlmAgg62mk1dHRjGO/Efz/s9PA2X+U9wQBCCtiTENnpglnmd/5DvDUU4KegTvuAO65h8T/es60oc/wPrh4cQxTU5KCFQh4BWhgIvrCxkrl1FR6DoAALePn0PGNR2EYHYHCTAKjEaV77sHs635RrNSbTHpRSVHdqar3Z/jQh2BkpYcBm3Snuu02FL/6VZHT0WhjpYUUrFxOUrBaWmxXLWA0us+N9nkCClZ5CP74DHO7LXA69fPPhYWr5jTtYGWI9DQu5rS22tcnRHK9Bm6h9q+B4y4MWqzWm9S7G1VnstA2eKUW6arOj892VugJeha2a6VxUp23SPliFaR1717h8qi1G3sENAByY19f7ezmRiAUSuP48QtIJJJwu63YsqUTdvvyExFOzDmZJjdYLZWzhE0rUZXXm86lEc1EkcqkUMqU4Hf60eI2wVym/aFOChkpNGeGyCItPT2N2aHD0BdnUMlnYAkE0bK9H0ajSQIJVJDMlpEsOhA6cRo2Wpq2eFAKX4R/6ya42snFNQGpS0D2IqCzAtYWwLcbsLYhlolhKj4Fu8UuQIjb6kant1PMPUm9KBTySKdrr3TWexOJxOtEQmhh2Pgyo/sV/50vUY7ZsgCEHYoelnkW5Bj7b79iMp8qpMR+WZ2oh7pQKlfwoU8ew/eeKKGYM2Nbrxe/95td2L9fh2+c/gY+f+TzcJgdsBlteH7ieaEDCTokTcxv8+O+Pffh1QOvXn4I2OfRr0jhKse9762AexVhiMsfcflPjH0NuPgFaa9LXRFT2RmQSKtdtXG8+UOBxBo1VYSeTmdhNlvh9y9ehaC+gzQgViEpHPf+8P+i/ZtfAQb6Bf1Kf/CgABKlP/5jcR8seg9MTcHy0pcCzLBwOKDL0kLbhuJHP4ryO9/Z8JnyWHTI42SblQGCkBuxsQqczfJZx+EyIZ+/vDBRDUAIViYmEkilikLcn04XRVWIFSKtLT4CqgBeTX6vDl1c66BFdRGN1Wg+h6t1KaV8HrHz55GnTa/PB+/AAAym9bvHhfPWiROwB4PIzs6i9ZZbRFCm1m7sEdAAyI19fbWzmxsBvljPnh2dK0Eb0d3dvuTY1JpMq0Jqi6EsLU/1RlT0dkwmpkSwX6lYQjqRRqurFV2t7bDq0jLIjtoLBtOpOhBSqri6xkkfcz/0BrBMHj1zGrnJ08hHxmCyWWFr74e7dxPM5OiX80gVzEgqPiTGRmFKRIkcYPeZ4N3cBStTnJntwVX47KicVNp7pKORwYwk/dsTMyiQwwsg4AigxRnE7CxXPAsoFkmlyIoJxEq43qwO8QWnvkQ5MVTdxlgBEaDB6RQp60u2S98AJv4PkJuRehWmife/E0VFwVdOfkWknVMwvr99P968683L6jX+9TvP4K//Po/wtAlmTxT6xCa89uV+/MP/7kCyFMGnnv8UToZOCg0I09SZEP+Kza8QXfzJpZ+IY7zr1nct3We6i534KyB2RIbrsQoSuB3Y+fvX1iGGSegXHwLcO2QlLvyMDClkpsk6tkZseNXwv3i8ICbBbScPIvifjwDlMhSKaEdHUX7Vq1BmzsZS7fnnYX3jG0X1Q6HuKJGArlhE8X3vQ/mP/3hNz57nwOcNqzKrcdxa007WuXNVG8aP00BCzTPi95n6GlaWCUZIR+vudjetKsTnIelNxhVUq+o8tQ33MTVocb5akoujlOP4sgC+vN6Cz9xaIYtqpYOLQ7yeBCB8DldXUiJnzgjrXTpmccxb9uyBt79/3cYoPTODKKnFySQsdN7asUOEZWrtxh4BDYDc2NdXO7uqEaAdLCfJfLEtlUfBUjV/FD75S1nodAocbj+cbh90BA/50Jy2w4KyyYvJTEZMXHVlHcKRMNpcbehq74KNLiMUm1OErgq/CTzyM0AheVkbwhVzVgwqFUTPnETs7DHo9DpUygZ4N/Ui0EMtQg7pTBlxOiHOhmCKzsJgMME7MAhna1VCNzUndNXiSjxBj6NHODhxwsAqSKaQEav8pF+VChBiXq4053J55PNJtLY60NLir9vvnyt4dM+i2JwvQB6HLzg6XqkvPlK76gIgnLgzgyNxCnAxBHBEuoRtfz8eD48LulQkG4EOOrgtbty7+1787NafXfIe/+C/fAVf+lcvOoNO2DxJnDtlwS1bg3j0H7bD44EAHUenj8IeOYjMzFP41uwljNu3Ip6LYzQxits7b8c7bnkH7ui6Y/HV9thx4NTfyX4Q9CXPSb3Prj8EHL3X7jvIqsy5B2XlQ/StG+h9E9D5Wqkrohub2SOB3hq2RgAIu0EdliqEdujLsHzhc9AfOSI1ID09KN9/P5Tl6Bnkkr/kJULjotProZAH7/cj/8ADwKvrqGitcDxYwVFpSVYrqVr2FWlOVnj4pm+2FAAZH08IAEKwRSeygQFfTVpddaeK2SzSk5NiwYXWrsLedUGja1NiZARKsQhbays8mzaJa3hTNS5w5aYEfZfvqyKcKBn9KFWUeSF8vToTNQGe15LbcIGJdNjq6mFoaEg4Zrk3bUJieFhUIAgC1rNRB1LKZmFyOISxitZu/BHQAMiNf421M5wbAdrBqtqEWnaw9Lzn3/lbhzKU1AgsShIejxdGV7egMgk9B60IudIt6DZ+xBQbYukYcvkc8uk8/A4/Av5A7Uk8Ham4vdEBFNMAhc4MupuzeY0PD4sXgTUQQDYUgqvTh7YttIB0IJOYxfSlMSRHx2Ct6GExK7B37UJg7x3QG3TSn53giPvl/ki9sUk9g9qqaSuc5BGA5PP0xC8IANLW5hQUmcVScqv3w6oHgZrqBMMVNdKsFm7LCghffKoOZNEbklWPoT8H6P5FnQJDAJmLsv39+MzwITx6/FEJBKDD05eexi/t+CX8xoGlXZv+8r8exj990grMboPRnkYyBbzqbgs+/zd7L7OOXvjvwMXPoVLKIFOp4AmlDb8ftYmqSJe7CztaduCte96Ku3rvqt11pqWf+GuZZm/rkk5knt2o7PojTOTTAnx1ujqF0H1dG6tgs08BoR9JIOzbD3S8RloMj3wJyDHnxA10vxEIvnjNutYoALmqIwS3x49DVyigwlXZ1ivv6UU7/s1vwvIHfyASyqkfKb3znSj/j/+xZufJHdPsggCE+hZOzOm6dT3TklR7bp5btXCZIHFiIgm6B7LSUyqVBQVrobHHFc+eSkU4+BFcVPg8aGsTGRPmOZtXLsAwg2Lm0CEUEgmYPR4hRA7s3g17y+Jhd9wXNXTlXE5MXu1tbcvSM+k4mKfmjbbpfv/Gc13iM5zvCZ1RfnepQ+N7okpbtlAAX03nqnWT893GRvpVZ6d0bVRbYnRUmKCQgmXx+dCyYwecCz6zpl8cbec35QhoAOSmvOw350kzCZ2r9XxQV9vB8kHOibQqMufo6AthuMrjsJvLEiyYXYBzLgmbE+UKqUx6wBoErAEh8s4X8kglUtDr9CJtXZ2Ik1/LFyozOyxOM3SsgNBelxwTARIua0Povx49fRrZaBQmux2e3k64g2aROp0tVDBxYRiJ82cQ6GiHPpeBwd2L4IGfglH1dC8kJA2LLy72ucrmd+FV58Q4GqXGJYdKhSBEWpuy71cluFdtTIoAx5FAjU3NPuF2tfzu+Vluw30ufPFd0ScCqDMfB6aflKJpgo/AAWD7B/GVc9/Fw8cehsPkEOMbzUUFPYoajaXaqdlT+LPPfQ8Hf9COct6K3m4D/uoD+3D7zjkqWOQw8MTrZDVAb0WlkkMWZvxufgC64EvhtXpxcOIg7hm8B++78321D8WJ/sQ3gclvS1BqCSDfcQ8+N3kRk+NPYEt5Ar32Fty2/T7Ye16/at/8c5FzoIMX80v2te/D3ra99X+hWSE78b+A8HOyulQIA+6dwM7fA2zL0ONqHYX5Naz4lFKy+sPvw4K2agCyyNmR+kNxOCfB1GVQNK3+GyfIdLJzmyrQnz0D9PaKCki9LZej3kM6QfGn3kYAwuBDi8UkKjkdHau36+U5qRUh6jLWk9a1GAAhuOLiBXND+Biz20nrcdR0D1THjtUPgotiOi2AAn/TPtwxR8uMj4yIZx+pQIpOJ3QIfK5Vf6bWdeB2sXPnxP44efYPDs7vs9bnqxPCaffKiTYFzxuqykLQwfcMq8LUEbKazQwnYUiydFsogFeBCd9/pGjx3beQCsttCOLU7A97a+uyIG65fmh/10ZguRHQAMhyI6T9/YYZAdrBqhNnuoCwLXRs4mTabrfDZUhBzxVtToKZw2HvAFxbJaefVQz+Gyf3fDHMBTHxQc8qCx/m6iSejh7hkyeRDYdFarm7txeeDp/cniCBVJ0Fjkn56DQK8TAMVhtsrb3QEeyUssjlCpgeH0Hy7AuwFDMw21vh6NuLwK69V78sOClm9gcbNSiLvLjYV9qZcpIYi4VF31nF4I/ahoYMOHTIKCZ3/f0JbNlCu965Xesl2FoqoExYF+fzYp81AQgpTOf/Wfaz7+1A5BkgPQww/Kv79cK9idSrBw4+AAIK9nEwMIj33PYetFpZiYrIlXwCxRqNNrvPDR9HIWvGT23fgx5f1UR7+EvAs78tAc9cIn2hUsanlUGc890tBOrLAhAek+PNPrMvllZ8c2IIjx15AK8snkAfEtBDgce7C5v2vF+e0wrb+ch5/NPz/4STsydRUSoY9A/iV2/5VZFhUlfLTADH/0ICJdcgwOoNz337/wv4GgAy4pwrwMgjwMyPZGWQAGbT267az1oBkFgsB5pL0ERBOlM5RDWOTk6cIBM4BIMEAI0Jo6XjVVYAG7udE7bajl1ivPMz0BUTUCyt4h6knkpSsOiWZRR9quXQVde1mjNyYD4R+8TGBQLuc71ACBdm1JXzhc5JBGm0JJb0SjpmLW3qwUoFq7uJsTEo5TIcra1o2bVrvgIydegQUmNjc3q4M3B2daFl925hyWpaIjQvdOyYEFC7enuRGh0V2xC8LNaykQhCR4+K47AfBEOt+/bBXPXMq/f6rOnnqNejhpAAhM+2VQb+8f3HdxSf1cuagazpiWk710ZAjoAGQLQ74aYZAWoRSAci6CAFS50Yy/mjIlaHqF0QQktO0DKTkqZCJyry50mvWWIFihMt6kyqJ/GkFJBfqzebUUqlBD2A/NpFHUZUjQhL8ALgMD/ELrI98qkwIuFJ5FJp2PUKrM5OmHybYbDZBGd2ntMrrK2YBSJL7jC6Zfr5En3nxG16elp8nJUKFYCcOGHAQw9ZcPo0c+BK6O3N4/Wvj2HPnpx4kRF8LGcLWQ1AFnKPMfafwDPvvBxuxVX5u78p7YMXtHQhLQEIFGwLbIOrMAMMP3RZsE6Hp5Y7G7ufaVH73Z+R1DWdSTiWFU1efNL6Gjwej6CslDHgG1iaglXjiJ89/FmcPfYJ3GfLIGlw4VxqFj/ltKG3/03A3j9trI9Vn3702KP44tAXRZ/MBjMOTx/GL27/xWWpaPO7IFA49hHpNEZKB3nmzkFgxwelXqiRFhsCTn9SUua4OkvKXOBOYPf/vCLsshqAuPRhuJQJQG9GxcsQxJXrTwg+CDYCARvC4azIFqEAnBN2iqIJBFaS16HSqOiSl8uVxH5rWXbrZ74L/dS3oSuloFhaUO65F4p7J2glTF0VARBDTVfTZDhgEoVCRXx9mWHCqgr1JevRlgIgKzl+IZNBemJCTPxJM62mVnGhJnr+PCclIEXK098P//btS4IP9iF24QKiZ86AlWY+B7mNi37bizTSjPhM5m/SvhzBIFr27YPJdmPluiw8fVZA+Jznc1tdgFvJNdS20UagWSOgAZBmjaS2nw0/AgQfBCGsUnCSXa1dIF2K/3bFJJ6TNSEiJxBYXhRXPYnn/jg5F/a6x44Jd5EKrXM7O9G2f//inGMBfKaE5oO0K0GjgkGsrBeySYSnh6EYvXC7rCiG00hEzTBYbHD19MDT1yevgXDCmpK/2eiAxNVp/l6kETRNTU2Jv6p9538/8ogJX/6yAf39aaGZOHnSite8JoV3vxt1J+lWA5CF7iv4xk4geUrS2YSNF8nmLwVe9YOl7yeuDp74S2D2GZm7UYzOUYl+d8m8lZo7pYPVqY8D5TRgsAub2rOd9+KZS8+gWCliV3DX0iL0Gjulxe/Qkb/D3eVzyOnMiFeMuNNlRcfmN8kJ+grbw0MPCwCyvWW7ACC0Dv6F7b+A37r9t+rfY/h5gA5ZpF8RAHS8Duh8Tf3bq5+c+SFw9lMSJLN6REDi6AP2fli69sw1FYBUIofhj30DltI0FL1JTNZL/b8h9VQraKT/EIQQJLBSwcoA72MCEE7c+W+BgKPh5PPp6RSYcWE0knqloK3tah2HLjMK49mPQ5c+B8UcFLTKiu8AStv+++rSoVPUlTmJNMSIkMZFW2KK29lY6SEAqRWUuoIhXHYTmnbwh22hdeuyGzf4AYITCqBJA6Iug9Vi0laXawxxTV66hGImI6oYru7uJTUdvEeoQ8nweUcKVlcXXDeB3kGtzrPCX01BXm58tb9rI7BWI6ABkLUaWW2/G24ESL8aGRkBV4L4AObKPR2bCBRqhTI1egLqJF51fOJ+WeYnPYDe5qyCECSQX7toI+gg91cFD5zcoSI0CqSEzF46LlbpzZUyYqcvIZmwQ9E5hWNJx+23wWThKv6cGH0RAEI+uUqdsFrNmJiwg9EdNtskvN6SAGLsO/M8vvhF4L/+y4m+vgIMBgUXLjjwi79Ywf33ywlRPY0TGFaduM+rJjH/0SXFlnpOWEkbS0kg8XPHl941Q/aO/bnUbri3ydwQUs62vQ/w10lHqj5C8jwQPSrTwj0N5ndUSlJ4Tg0LJ+CoIF1I4eHDD6J9/N/QWQ7Da7ahq/2lsPS/HWh7+ZLnRo3H4xceF85qA/4BoT+xzlk40zKYVDRSsFgJIgXr7Xvfjju7G6z8MCGd9xmzVuyLrxYv2VGO2emPS5ctgggCdp7b9g9eUW1TAYjl4j/AmXwKeu8O6IpxoaMq9/0KKm0/U89tdNVn1CRu0p1IcyI9iY3p3KyE8N+cTlPdXHaCCl3iOIolYLayFTmlBTabQTg8Laxk6KIHYTz/KSgE9dZ26DgGlhYUt/+BoOA13A4/BsuT74POFIFStqE08Dso3/MHYjf8rkqdFquTBFX2hne/0g2qAchViwcr3eky27EqsR56DFZMWFa6Wax+WZ1XKca1TFjW6HJqu9VGYNER0ACIdnPcNCPAlXjSjC5duiRK0F6vd0ntwkoGZnJyUqzCsopAOheb0Flks2JVzmhZho9O+hQnZ6RgsZGSVIoCqRGUckmEwhEoOhOKkTwSRw+ikLcgl7MguGMLNr/yRTCZdHOaD/1lDUgVBeuyeDRPV1M8/rgfw8Okrujh8STwhjdEsWOHFN0SgAwPm/HlL/swOmqFwWAE3U/vuy+PXbvKdQ8PJzG0gOR4XAVAHrsdiL5wufrBak/Ha4FXfGPp/VNMTQASPQTYuoHcJODYDOz4AODcXHffVv1B2tle+CwQOyoBCEMnme1isKDsuwVj5j5YEkMIWt0wenYAvluXpMJNpabw8Z98HIcmDwmNB0MRCUCqxfZD00NShK6Usa9t35XVGd4/dQhVV33e6g6mnwAmHpO2vgQym++/CtCoAMR2/m9hTx+CPninEK3rM8Mo9d2PSsfPNa07K90RAYRh+LPQpy9C0RlQcQ4i3/vrMDg75wGMWDlP5EXFxVqegH/m0zBkLkAxB6DLz6Liu21lFZBcCpYHdkPnCQkMrrAYmLAjf/cjwO5XzoMqitvZGPzH9Pf10IHwmUkaFtt6AZCVXkNtu6VHgO8+Lrrx3bSUDf2ajSMXaqg3I6NgvR0B1+yktB2vZgQ0ALKa0dO2va5GgC9SUrC4EtTd3S00H81upDFxokKeLQHOihof1PlZWQWhMJue8IUwyooOM9y/0YRyJIbk0HHkMgYkp1Jo29uPLa9+EYxWt8woIeWKNC62KhG6yimn8PzYMTu++lUX9HoT/H4dzp8v4sCBKO69d2JeA8IVs+lpD86cIVdfhz17yti+vX7wwcOrDmMEIAuFrKAA/YmfkwCCYks6jf3M92Wa+HKNTk4jX5b6DU76O14FdP380hNwjuX41yVdiOngbT8NtLxouSMt/vfxb0odCq8ZBeh0hKIxATVD/N13L9B1T937f3L4SSEyp/tWq6MVL0y+gB3BHfiLn/4LmGjFuVhLnJXnlR6VehoaJrgGJL2qig5Vd0ca+SArH/xhta6GUJbURPG9GP03eJNPwKLLQIcKFOcgSpt/HQqDEq9xM1z8V+gn/hOKc0BUZvT5EEo9b0Wl643zPSP4UEXvnMj1mJ6D5/9n7z3A5Lrqu//v9N2Z7b2prrSyZEnuBWwwNpheAyYUEwgkEEoCKW9JqCEvJPm/JAHiF0KLKUlMTaGY2GDT3JssS1bXSlptb7M7uzM7ff7P55wdabXaMjO7qzrnefZZ2Xvn3nvOvXPv+Z7ft4R/Oa0BqVdq1W8X1pdn7lXJQ78teRNSpEzyEl6aUbLiXUq+8bPmeWLdtaJmAunxOI1d9mKi7+UYUqrGWXfA0/Rby3GAHPfBwgnYGg1MsRU2AnwHqfQDQGrycIQr7GizPpXNz4I6y3MXzdgs85VlOU5xJ+fVCBQByHl1uYonu5QR4EU6OjpqxOeUoFcCgLDKxIovAITAp4IaOhA0HFQDMnHrsORwKi2vBgbIECmVK5FR+MhR9T+5V4mpmOo2Nqn5svWq3rB5GoA0m4yS2Q3aCpMoHIQefDCge+6p0po1GZWUpPT44wm1t0/qfe/rUVVV5WmBggX1RTITGEAIAGRmlsCJ/RESN/Bz6zBW+9wT/PecjgcVC/CCDgT602Kr/10/kLr/01K3oKpVXCJtfK9UeUlOhzttoyPfko7eJVVfZasgww9KNVdLtdfa5HEAUdV2q7eAmoNIfgE3m4eOP6QvPv5FYzXcVNZkQhJxuPrkzZ+cP0eEvuz7B2nkMSl8XOl4UGG5FfS1KVZ3g9Zf8zcmtPJsNQAIDjyDfV0qH79fZclOZZwlSlVslSq3yRFokdsLWHZqdDSqSCSpkhKXydAwE85MRo7gE3JO7DXOcemaa5XJWmJPVxhnhqoV0k/X4S/K1f8TpauvMbovZ+hZIyoHVGQbFQgE4VQf+DdC96bq6AwXrJPOcXmdQ9culfz4BcqUReUIe6XSuBR3K9H8p0q96mPGfa63N2SoZWhAWERAXI/t8HI09kdVB3Azm7JWCADBHYtHFjqV5ajS0O/x8SlDQYNmhyHAUq/3cozbmdpHPBw+EdC3FKF8b2+vMVjBYKTgxbFCO42uMTYgOUuthT2ukljQF9tFPQJFAHJRX/6Lq/PQgAAgvFQpQRu3q2VuCP2wOmTfBZe5cbACgLBShDCah7bLrUwqof7hSWVKalRWVqnwgQM6du+9cpVAj0qrrqNVbddfLacvIPlq5hWdw4/HLnTfPrfuuiugQ4eoaEDJSui664Z1++2TWrVq1aJhhLkOHeMO6OOlB/BbiXHP9VxM0vrww1LNtbZSED4irX+n1PaqnHdxyoa990iAEGyVuWZY8WJvW74uffv7AAAgAElEQVRh2h2q0dKyTDJ9rdR0i7WqnQcoTcYndcdjdxgK1lRySq3lrXrd5tfpxe0LpHePPint+5yhQaUnDmli8pgGUw6NyKNJd63CHR/Say5/d2H9W8ZPsQILOM+kkioZ+om8oScMTTDhbdFE3evVM1qio0fHNTWVUkWFXxs21Gvt2mqVTD4lb8/35QgflqBHlW9Wav27FXG2mhwKJuiBgC9vu92ZXcPRytX9fTmmegwdMBNoV3LN7ygDZW668Z1B4I4gHIcrRO9zuWMVMmSeL79CrsyDkjcpJZ3KTK1S7N2PWkE6Tk9jUQN60IExCUdcn08+yXznBPjASSwcTpjKCqAKgJVtGHfw/aUtmOEz/QHOkx9AJxWaufQz+YwPzypAH2Nv84ZcpvoDELsYGpbBZJzEJyaMXXFNR4d809TefPpPFQ16MM9etHhZenA++1jStgaA8E4L2Mq+v6UIQJY0oBfGh4sA5MK4jsVe5DACCKEBILxUKUEjQF/uhsCd0D2qKwUL/aAJQcGCSsXKNRNXLHkzafUNjiojhwEH0c5OHbv/fuOuhaCy4fLt2vjKl8vBZ3LwjAdwfO97Ef3iF25lMm6VlQ3qhS8c0nXXtamxsQAh7TyDeU4BkL2fkfp/LpVfIiXG7Muw/V2WvlVI41oBQLC1hWaAsBvKExkv0MjiQetmxor9xH4psFq69M8XdOoai46JSgi2w+uq1+mq5qsWXvGFxrb/c1L4mKZChxWN9GpIpUp5qnUgkdIT1S/Vn938N6okM+UsNr4XgPPU0CNyH71TjuigUk6/HKkJTVXepB3hV6qra1yBgFvhcMys8q9bV6WaoW8pMP4LJcq2y6WYPPEexVvfpD73rZqcTJoeMSElCK9ge9pMSs6Bn8k59rStstRer3TtDacBRSbCOFMhSgcILMcKv+lAMin3Tz4px+AOZQItSr76b6WykxROJpCYR6RSMpPwpWSLzLwFAHC4bDF+ACv61NKCtbYN+skHgAAWSEePRBLTVKnMounoACoAC785h8rKklPGNJu4DlDK0q9wAcMi+Vxo2fT2xOSksUPHTWsh5y6yUHD5wpBkUT2gpJF9+0xCOa5gJLeTHF+9YToQN48ByNIgs6YrgJClNlzHCNgl36pksWo/FE1DK45Zp0ECS13L//5dap+Knz+zI1AEIGd2vItHO4sjgKgaAIIOBHpUyQLhVoWeJlQTQveyibN57QfeQtb6Fz0EoAOx3gz73JkaE8f4uLoffFCZREIpAMhVV6n5qqsWPSSTGShR/DCp6emJanIS16CYWV1saakqvHozx9EBfkxkGHOqQoUAv3gqbgIBQ7GQ2iratKV+S2E0jNEdFjCEj5ksCkPBQrQOjclbITW9OP88DAL5cPKC0oUWBUck/h/X79CXLMhBWxA6IHkrLQABiCxXQ39y+J+loQcUGXpEoXCfphw+jfla9ZuYV4crn6OPveDjqvWfI5QHdDOHvyYF1irjKVNm5Aklyy/VPs97tf/AsMbGImaSvX59lVavrlJ5z9fkG71fscClcqSickePa6zmNTocv3HabrdEmYxDra1Vqqrym++ey5V7ennelyE2JBeUweS4Mr4mpRtfbOmD51EjqwS6G7oWQBVuX7Tqar8aGwMnvls8K/n+8miqqamXy+WQ1zu3NS46DaoVUKYAMFmtSiAwP1jA7pgKDI3tGxpw4Ds5MeVZRZ5LttJF4CHBkEvNV1muSzXR22sySKLBoLEABhxUrl075+6xCw4eOiSqGoAPtvPX1y94KqMHDmh03z65AwFDw6rbskVV69fnfPq4MJIQn3Y6FZyYOEGrnRk0m/POZmwYC4VMYj19IciRfmN/vGDD0p5nlXmvLW6vXMh5FT9zfo1AEYCcX9ereLZLGIF4HAoFE5wxU4JeKL270MMAcAAgTIDyDnuKh6xWgDBCd6ktUZOUPqOhMWE1C/BU5nEouH+XEqFRuUr9qmzfqtL65gVPnTGAgsZqdJZHnUw65Hb7NTk5Lp/PKb/fV3j1Zo6jA/yyoI/KU77AL5FK6J93/LPJ5YCi1FjWqNde8lq9aH1h9q3CPhaQgBsLv4cesKtzvBjRb1zyISsgX2qjgrX/s0r2P6SRoaRiSZ8igRu17qUflG+5KSSIO0cfV2TiqH6599+0Z7xHgymXun3rddP6F5nU+EV587FRK+in4paLCUCh4zP8qHToyxLHI4ckPmzE8sn296m7G9elmMnwaKgvkSf4Kzm6vivH2E5l0kmlPXVKlG3SZNPt6p+s09gYqeOW7lNXd3L1nL4iuAWM8Dv77yUDk2RY7sP/T85R6GNTyniqla6/Wam175iXVkdlAdMHJs04WC16HQod1/FxOR97TAIwtLcrs2XLvOfU348hh6VWQXlD+1FRUaKampJTAAbf24kJqxkrK6sx2ShQtLKWx7NPFUBjKViko3sNpWuhKlE29JHKB58l9HEmBYz9Z6s/gKCSEvc5Az44NwBF3yOPyOnzabK314TMrr5pbpttwAqTdhpgomzVKpU1NSkyMCCHy2Um8LMrCVQYRg8dshknTPQ7OszvXBpVcQOORkeNri5eVqaqtjZDhcVqfSmN8MeBHTvkq6pSdHhYFevWqeXaa5eyy+JnL8IRKAKQi/CiX6xdZtKNRoMJOA9gaEyFNoSBhAyyNFhaV6eSaV5ucHRU0ckROR0ZNTa1nnSiyuVApK6TKs3kF+pOSeOpE0F4vN1HNDU2phKfR82NfqUjvUpMTcjtb5C7otW6i8xhcchLHDvcrKMNp8NkjFJ8FhAsqXqzQP+WCkAQYv/jo/+osdiY2srbtG9kn7Gf/fhNH1epZwnpxVCjnvmYNNkpVV02nSUSlTo+sDRnrBljEQ8N6Nd3/VhDxwfUG2zWwcirde3zavW7v7u4Xj6XW2aubXonenXPoXsUjAZNtQgb37LFgjQJJ+zCUSxoK0GNN9uqDc5WpY2Fnopd8ey/zwI9KnkNN9n9HrvLhkhCycA8oP0d1jlsZht6WDryTXt9sKZ2+pSpe46x7k2WrlcsFtfYWFiJRNLYT6OJ4D7P/gDU+Xf2N7teKjBxjO+S+9AdptqV8a+RI7RHKm2dzv843bktHI5raChiRN4+n0s1Nf4laVXmvRChkNz/9E9y7NolRyymTFubUm94g9LPfe5pHwEcUKlgwg+ViSootCZAwOzGgsrQUMhoX7DhhQqF7gV63HxACjoV4w5NbDGwBVgZHSU4MmXOpb6+9KzQq6gCARQBiVR4pqbi07kr3gXdxsaOHDE6vFBXl6FgUaFYe+utphoyu0309Ghk9245fD4lQiH5qquN8H9qZMRsWtbSorrt20/LJSEVPhWNWq3fIs6NjDsJ7+l4XLHJSY0fPGjCFqdCIQNA2q68UtU1NUt693Gu40ePamjnTvMQw2K+ZuNGNV55av4S58G4UIUJNDWprHnhxbHCHzLFT56vI1AEIOfrlSued94jAP8cC14ASDb5PO+dEDSeSJh088meHsEBDjQ3q27rVuFQMjZwVJGJfjnTcTW1rJZ89bmDECZ/aAig7zicFkz4plfiMxmlJvrU+dhvNDk8LF+JU6s2tKm8LiBlHFZ0zsSxtPk08TkAABE4/c9Owug/ZfiZE4QlVW8WGEgqQuyblTcqIPlWnsi8AID4PX41lzdr9+BuM7H+xAs+YexqC25UKAAgTCIrt0uR45YasOkPpZrFqWy5HHf/funv/k4KhaSODmn3bqm1Vfrwh8lVyGUPZ2CbREh69tNScKcJ1TNalVRCqtho/xuBPoCkkNb9I6n7P6RItxGQG0cwxre0xf4/I0htm5vC1PkN6di3bXaKnNLoY9Kq35I2vue0M2Hixf2d/cnqTbL3/HIBE4IK3QfvsNWPwDo5xneb/BkTQOitMRNvwAaTfFbrCRFklZ/JPZPtujooTqevPvO57HezkGF2/uY3cn3ta2alO1NXJ+eePUpff72Sf/7ncyJdJv0jI1NKpRDwe9TQEJgzXZ3v7fDwuIaHp9TQ0GTAHgCkqcZnjuGYmlIaylGBSeKWDoq2JS2vl+rrmdd24No1MBAxuiMTw5SAjuowz0bMDdAWzZc8zyT76H33GUDh9vuNVqPxiitUWns63TEBBXjvXkPXcpeUyFNerqnBQTk9HkHPAmA0Xn65vEuoToS6u22afDSqDHqreNzQtyJjY0qUlxsAUltHwOYSFm6o4PBM37fPVFfcOD52dKh0hrUvoGPgqac0fuSI+U4APqgOFSKgL+T7UPzM+TECRQByflyn4lkuwwhkA9GYjPMALpQHG5uY0ODTT9uXhtdrVpt4uPLSGe/fr8h4v0mGbq7BUhO7wRzpPATZ4ZZEojfZHaRUZ6sZyagix3fp8JOPKZlMyJmcVPPqVappXy23ohboEAQ3owLCyi99hcNNs6uSCD0r53Sigm4BWGFVjsDA5WrQvqiucFwAiN+fH19+MDyof3j4H/R0/9MmC8PlcOmWdbfo/de+39jVLql1/5fU82Or4XAHpNprpI3vWzZO/759FoBwCdrbpT17JIb2L/6i4DlbYd2lf90/tACX+6T11Sera5NHpT1/czJMsOcnNtMEp7B01OpktvxPmy2Tb3vmE9LIo1LNNbaqh2Vy++9JLS9dfE9Hv20rJYAVwAuOZavfKK1/++Kfnd5i2YGJIyV/99flGntcjmi/GZ9MaavSza9RquVVCk66FeoPyvfUE/InInKsalNfa4fJ8GFCi35hdpI5FQg0DoABaEtzVSIW63D8J/fI+42vK9PYIE9DnZxPPaX09u1KfvzjkvPU7wjCbgDI2FjMgKSGBv+8E3++t5FI1ACpsrJqUyGoCThV8f27zDHERLelRak3v1mxTVtMJcPtdpxXLlVUP7A59vk8BoQAFKurS1Ra6lUymVpQSM9Ee2Tv3lMWo2ovvXTedPVkPK7ExISpZDi8Xo3s2aNIX5+hYJW1thqROYG1hTQWw6BFQQVjog84Ahy43G6lnE6leP6uXm2ewfnSYOc6H45H9YN34OzKDAyBvkcfNdQxFuYARE1XXWUqIcVWHIHsCBQBSPFeuGhGIGtFCBUp6wZSSOcBHkO7dtmXzvTqDi8duLmhwaMKB4+bKkZTS6scAAIqE0ttyaimener8/FHFY3G5Egl1bKhQ/WbNpiEcpWgF6k44SwyGQqp/8ABxaemDB3A39BgaGezqx4zTyvreAM1azkBCKvRaG+ge/HyK4T6tndor364/4canRpVe0273rDlDaopPT3nJO9hptqELW/4uNXbNDzPjuMytWhUuuMO6eGHCWSUyKZ8wQuk97zntHnhMh1xjt3gzkVOCP3MiuPp56YPWt1LYmK6AvK0tckkT8RdJrW+wgIR4rkv+VOp6tL8z5G0+sEHrDWxAddxacPv5+Y6RoXk4D9Z8b4IgdggbXi3VJa7CPe0E2aJOzZk9CRJd42SKVs5mVkxcSRD8g3/XM74kFLuKkWqblLKXXOCyuVITaps9GcqC/5U7uSIMp4aOTwVSta/UMf1avn/5Rsq3/O0nOFJudtaNHXLrQo+70WGIoa+IevmNBwZ1r7h/RobjalZTQp4ylUSKDci8HxsZplAjz1zQOXf+KrKOvcb6pOrqUHpl7/c0LBmt8HBSVP9ABAhKkf4XVk5tyNRlpbpcGDRW2f0HIAr11e/arUmNTVyHjum+HXXq+d33qdwJGHuF2yCZwOt/G+eM/MJBPkDA2FNTMTMmLBwwyIMDUF8ff3ClsdUAyKDgzaAFpvxPBZY4hiBDKM/cyrQ2JiTM9Z8o5JJRjX09BMKdfXI5a+Qw+1R9caNFowkkwrHMRsoLdgIJJ+rgdsXFC2oWoA0wBWLdLnqV/I5VnHb83cEigDk/L12xTMvYAQIY8L9KVsJyO6CMvzUVNK8gBBYLuayEh0fV4R053TaTO6zJffQeFCTY31ypBNqbGqTkzDAxcLxcukHXPZIv4498UuFhkfkLKnXuiueozLscnFzmq4EUOWBYjZ48KBCR44oHomovK5Oa664QlWrVi14pCwA4eUL33u52nIAkOy5pDPp06seTKojPTZvo7T1zNg7Alj6fmqF1DhaETg4yzAge87BoHTvvRJaUKofL3mJtAT5Uf6XJbRf2vN/7eSfyftcbly4g3V9x1ZIxvfYY5Cmjii9cqu05X/Y6lq+jZyUZ/9amjwiZZK2qrf6DVLTC6X65y3+3SBbBYtjQBD0Lao3hTZceI59Rxp5/GQI5frfOQVwkrWT3n+HNPArZRITSju8ilVerYnmd5hcniyVyzP2qMp6v6mUs0wpd608kb1K+FbrWPfNqv/29+WJx5RqaVVV3zG5Lt2i5Ec+IscMak3XeJfufOZOHR05pCsS3brKk9aWmq1K+K+Rv+M2lVXkrk/DSQpRecPgEem+X6jcmZD/ym1Kv/SlqLZPG62s8BtHKTQqcwm/sx9i4YAKJiL+rKmG87775Prnf1amuVmJQLmcT+/U1Np2HX33nyoYiqu7e8JUci67rNFY+p4PjSoUz38AFg5sVHKg0WGGMB/96pzqFyYUsUFNDfZo/FiPUmmfSprWq2rDBlOdwAqd9wKVjzOVxUR1JNzbK8AI78gSVl+KrTgCM0agCECKt8NFNQKEMQFAWOXPpsFmw7iwj2RFEOcWuNqLCSjnGjiqK/zwWV7YS3bdyR6EldupAY30HdDw4aOKJ1xq67hS5avWGT4xHOr+/qDGxsaNnWX86C7BB65Z0y5HKKKGy7arehH7Rl5Q2dCx5mUUDLLCjPifCghWvEt1YDll3JlUHv03O6nk30yw299pfeZnNyhArKqzuh9Yu/jkd75vBiv5VBSME1LKAg8m1BveU/g+5zoWGhX0KfSLCkKhycFM/gEgGBwgADd5JGun80hmAM34uLoGn9KOzrvVNLFDDW6X2uoulWfNG22C+2KNe3RslzSB8LXUfmbwN9LBL1h9DVbHNChVdc+R1r1Nqn/OYntd2t85p4FfWME7YvZIlz03KI5UVVa9Xlr75pPH4P7Y/WnrRlexWZo8bMXvm/9USf+GExqT9PBj8h79ijLJmNLeBrkjBxUv26KRvhcocOc3lSI4tLlRFV2dSjY3a+yDH5SztvaEK9e3939bP+78sV7sd+iK2H75UxE1lDSpruoSudrfImfLAsGTs0YE+tbAwKShcNnnTsA8w+Zr0KlGRsIaH48b/ceqVeWGbjRX43ubzTWqn7aMdRw8aATvqf0HFXO4lUpnNPacm3T45tepp4fqSsTst6Oj1oCQ+fa9tAtb/PQpI4ChxlSvWYxKxcJKpV3y1LTbTCjJmI9AxwWAcB1ZgCu24gic7REoApCzfQWKxz+jI0COBgCEFzWTYRqld1xhWOlCQFpa6jYrd1mqRD4nyL4BIDQe9KwcFtRwB2LiiSjaVaLo6KCi/fs1eOyoJkbHlE5EVVvfrqqNW1Wxfr2OHulX/8C4UtGwSlyTcod7lBgcUzzuUqCuTeuvvUrVqxdePeYFlXXJylZACBWLx9PT9ryFCUSpyiD+h/7FmBeqvZlzHJngkoGBSxIBV8mQ1PZaC0JmtvG9Nv8jq/WAgrT6thOVo7yukUke/7y9NqVtEkJkhNTbPm7NAJajMaHAqpYJPZUDAAOBiWVzZwwseEgqRAi6B39laVAAmaYXSWvedApgQmvz2Uc+a7Q27nRU60srdMOGV+q2y38vtx5BtaLCwCSfCT4VC8BZ708kZ6k0/qytPFRutr8Z/w057ju3Mzh9q6yTFi5cADCsrhueb4HYyCNS80ukzX9y8nNUXBDkU+HiPCcO2Wu6+c8sBYw2vk8isLDv58rEg8qkU0r7GhVvfIVi2ir3P94h144dIssvQ2DoDTdo8q1vVXraoQuKz9f3fl33d9+v91f7dFnqgB6PudRRuUlXlsaVWfV6Zda/K+ces/gAqKCKyzMMDclCzy62P348ZHQnbI8uBcAy14LLXACEE3M+8IBiP/ypIqMhOTs26viNL1PIWWL2SwOAUEnevr15ZVy/ch4duyE0K7QdWDaTSwK1qpAFpjwPe+Y2Z7GC+xu6JRmSnmrrXjddGc++lwAgLIwV/F46cz0qHukiGIEiALkILnKxiydHgByNLEBAj0Cj/N7XHdTYEKmuHjW01BhaQiEvKCoIUJn4LKXuglaaeJmY1FiS0H2KJ0o0sr9TU337FezvVGQirOrNl6skVSpHXbMCqxs00DuksdGIaipdSkxNqtQZ1kTIK48jo4y/SeuuvELVNQuLvwEgWXCGBgRuOVzxLCijKgRtI9/GhItxp/LBmC8rADn+73ZyTbI52SkInutvlLZ++ORpUqVgUjn8kF19Z2wxB8But2prvt2Rgs/Y5HFe9tCvmFgj1AaAzEPDyvsgUJc6v24nEIjjWZlve82cDlA57RswSxWAKgRUqtrrTrNr/vWxX+uLj3/RJKY3Bhr1VN9TuqTuEn3qhZ+S17UI+KTS8OynrN6japs9DvdvRYcdn0ivDX/kGjFWbE9lJQ9BeU79nL3Roa9I+z9vneEAH0zSytulykulxJitgMw8B84LoDpwv71PPFVSw41WOA/gNEGW09bA6YzkLZeaXyxVX2H7Dd3y6FFl7r5b6ZERpdraFHvxi5VAiDvt0sUp3nP0Hv2o80e6MnlQNzn7lHRXaE3ZGjW4PQrXvULhuletTI7J9PMOyhaTcWhGgJCWlrLTAgahZx092iMWEGpqytTWNqNalk4r8t/3K7x7vxLlVQpffb0q1zSZJHSCBdFRs89Nm+pP6CkKun7L8CFoc2g8bO4JAnlAV8AAkVwbYwU9a6FMk1z3tWLbcX+nbB8N1XFG0jjPdt5NaB9ZXMpqXFbsXIo7Lo5ADiNQBCA5DFJxkwtnBFjR42HMpJhUbhqOHcd37FFwYFS+gF9t2zaqurUwDQSOU7hJAUCYbBeS+q3oiMRKrKdMSk4qMiEN7OuVt9StgcPPKjQ8IIe/RuUNqxVorld5Y6lCo+OaDEXkdXpUXlWtTHRAU3GPSivrFXfWqHFVq3F2WajNpo+RlMxkAttNVg8BZYUIS2cCECogULGWrWUrIKzsM1GfqwKSzftgAmwmx8N2gtzxXrsanm+Db404GrCTnLBWtS0vk1a9TiY8IJGQfPkDtVNOo+v7Uuc37Sq8s8Su1kPzwo1qhdpDxx8yAARnMeyOdw7s1BVNV+iTN39S7sWSi5m4Y2kMLQ33rKzjFVUWxp2xCu21wIPcD+hNiNEBKEtpjDc/81Uan/oT6eh3rE6KqguWw1SRsFmmokFVaba2BbBGOOXUgK1+cI8AYGj7/9G6puE6R1WFyhtVlMs+lRP4zLpyhaNh/WDvD3Sw90HdmNirzV6HmgLNSvnXa7LprUp5ak+I3vPNMeEYWMmChRCkz25USvr7w2ZhgW2ZiPPdRiSfbThlAVK6uk4CkM2b15yorDh/9CM5775bqeM9SnhLlbz8crk/+AGlS0unBe4kp5fOm5q+lEue72ep+ACMwuGEEffTf3JMZiauz7dPxicYjJrFGOi5PAvzAS75nutKbQ+9lncT7yPotXkvriXD1jIbNzp3+ZxZUyt17sX9XrgjUAQgF+61LfZsjhFAVMnDmNXILKcZpw4SavFLj4VCqly7Vg3btxc0ftnQPT7MZLsgu0PyQJj8sPqdSSoaL9HIoX5FhoY0iZgwkZCrqkqNra0qqw3IlQqqvKLaAKlULCJvaamc6ahGJ9xKuOpVWlmr2vryUyYYMzuHRSIhWaFgUAmXS/7GRuOCBUccAMJLOOuWwws438bnob5RAUF3gx3vsrVcNCBQkPb+naUgmeTtMUvB2fRHNuuikEb1Y+hBOwGFflV7rfTIo9JPfypFItKmTdIb3ygV2lfSwqGWTZGf4bGrmWRgrPntQs42p8+QMn/HY3eYysdUYkqtFa0mcf6lG3KwzOUIXT+YtvrttzQQslU2fcACNHQoGAXgqoW1NBUD/2pp7Bk7hlSm0LnkatgAkPnVr6T77zdWsLrsMum3fkuanW+w66+kzn+2FDA0H1AbGUPE59Da3PlZQmvv39tcE0Ao1RSqPOiOAFOzaX85jHosGTOW2u6Jg0qlkkr4Nyrp8J/iysVucs0xgVozOZlUJJIyVts1NYHTKFDsiwUFNG8MNxPx2da/VIWZtI+ODptnZWmpTwAQI8iORuX+5Cfl3LtX6W3b5OjpMdct+Qd/oMzVV+fQ61M3IbiQUER+AxAKpUeh5QN4kSdCmODMhi5ldHTKVH0QyOM0NnubuU6cKhD6GmioAEHGCfByTldC5ugIVXneTelwWI21tSbBHHvcnBrPOiynWchhIQLwPZfGLqedFTcqjsDJESgCkOLdcFGNALaSABCcXbKuLuPHjhkA4vT5lAyHVbl+veq3FkDNkZQN3eMlDwApKPCJSTXuSmQwmDyQGoWHRjXe16f+kRGl/X55AgFD8Sor9arcG5WTFSomdqz0ussVjacViXuVllsVFd4FX7b42I93dhpqWqKkRDUbNmj1JZeY8LdgcEqshjIxwKpzMXew+W4mxP/Y7wJAsuL/ZbvxABgIMHF5ms8FC04/1Bm2Q4TMqjU6iFwnvIud7KFD1m+X4A+qH4g8X/Yy6V05cvmZUOM+hVCaSk7N1RYwUeFBAwJlaO2b7N9WsI1Fx/Rg14MKJ8JaW7VW17Rck/tqKZNynMFw2WKMCS+cz7qXa3b0X6XBX1sbYCY1q15rqzwzG9QzdBhUIEirh8JFe+YZ6ctflhh3qh9U1V73Oum22079PHQqfhhfKiCc18Z3WzpbIa3vXmnf52ylh+8arlzsk+t1+aetrfEytnxzTNBsDQxMGM2DKTYFvGptrZTP5z0hgIcWijkGE37aXFUSJupDQ5Pq7OxROp1SXV2FNm1aZSfekYgBII7Dh5XZvl2Ovj4DSgwAufbavHs/NBQ2VRMm+OSS1NdjF547PamHOjQAACAASURBVIoDZumi9Nvuw6+SkpPXAqoZ2/AbClauzlZ8Bn0gmhqb1u5RS0t5QfrAvAdmGT9AVX7k8GFN9fWpxu+Xv75e9du2yZOLZTDVzHCPrfDxXYV2yOLBcj07l7GfxV2dXyNQBCDn1/Uqnu0SR4BkXwAIq0HZrAvsAoMHDpwIbqpqbz8l1TWfQ2ZD95g4MNHON3TvxLHMhCkpOdxGvAo4gMOLRgOhOCud69atk8vlVSYZl88dlxMA4g4Y8DE0FFF4MqbY8KC8iQl5/aXyNDQrUFl+ikgVG+HeRx/V1NCQHNXVGjp6VDWbN2vdZZed0K/Ql7xL9rMGbUUBSK4XyFhVDlkXLO8yVmE4/s9+ZifEJEJjbkBI2+bN0qc/LUOIX6wxET/2PWmqZ3pCe6W08b2Wz819wDlfSC98QApOYlAN/aukyUMWZBkdzXRSOAJ8aGgmod4n1VxuncaoWvznf0pf/7q0YYP1NH70Uel5z7MR8zMb+0fMP3HYVhShtJElAkd+dksnLU0MMA9NDJ3QrJZKxnXwkQ+qqv/HZLPLU7VV1Vze2uulbR87Y9doPmASCkXU2ztpKiaE6DEZb2rym4WDU6hc6bS8uAEGAnJXV5/Qm8x07WMyjwaEz1VXl6mxcdpZjoroXXfJ+bOfyTE0JBHGesUVSr7//fCuFrvTT/s7IYCI6Kl8UAmhwpBvpZVsk+HhiAlUjESwFi5f0Aks15PMAjHS2gEhVEAWchjLdb9nervhwUH1PvWU4sPDaluzRqmpKTVccYUqVq9e/FSofJgKSNh+h0zobWEU5cUPVtziYhqBIgC5mK52sa9Gn0E5Gj7szKyLVCJhUlvdPp+xtS20ZTMv+Dxah3xD9/BMn+zrU5Jz8fvN5GBiEotNu1rJeTMhYL8eT4XhNbOqB60AfQYTDTjLeP0rPKbe3QeUjiIKdcnX2Kzajo4TNp1MUkJdXep//HGFBwaU9nrlbGxU9YYNat2wYc609ELHBQoW1SBAWdZ9rNB9nZOfe+gh6UtfogQm1dXZlfkbbpA+8pHFJ6VUA0gMH31cqthiqT286AEgBdrUhkI2e4T5Ie6pZI+Ul88xcsbeuc9qI5hwLzcwO22Sn7K0srHd0rFvW30LVYQQlaN6adtHT2oysA4euE8KtFvBOGAMqlPjTbZzd95pK010rLPTVpz+6I9O7yR9A/Awpgjg56JdAT4Q/Rtdz5Qdi3W3S9WXnbK/ew/fq//YfZe2TTykDk2ozhfQmubnqvqS9+ZmVbySN288rtRvHlDwYJfGvQFNbLtcgapSVVaS6J00RzaLCaOjKv3BD+RCLE9GxPXXK3LTTeY+ZaGBxQ1+qJRQMebZwUJK1rTD7CgalfPee+Xo7pbKypS65Rapra2g3lFlhSIFfQoAUV9fOm8y+3wHAHwAQtxul3keomnJF8TMt29ACHoZsgmpBM+1GLNQNSnfQQFAJRIZQyXLJ5ByoeMMDw2pf+dORXt71dTYKKfHY4IBy1tzyNXhGQFNEioWFT7A+zJX+vIdo+L2F8YIFAHIhXEdi73IcQSofgBAqCQAQJa6sj/7sNnMC170AJB8My9Cx48rePCgpsbGFHe5VLpqlcqam83EAU43EwMqIXj+x+NehfpHFR8bNcBj3bZ1qm1tUChELkBY48d7NHLgkPy1VQoPj6pxbZO8qzaorp7VzDJFg0EN796tqZERm8ZbVqbSjRtV1tJSuIB+nuuACxZ6GPQfp0xkcrxu5/xm6BC+8hXpySetJoFKyNveJl1xxeKnDuXu6Q/bSTjaCETy5FBsfI+lMeXZ0MB/4QvSAw9IABFkKDfeKL3vfbO02kwsen4k9d9nV/1Lm6S1t0uV0O9WoDGBYZIP+EA7gSaEgEGoHYwB1siX/InlmdN2fsS6TkFvQuyPmB3ReOvLbce++EVp9248VqW1a6V3vMNWnQppI09IB78oxcctvz181GaVbP3oKQDyMw99RoCQG1quVPXUEQ2HunTDltv1ksvfX8hRl+8zCPG/8Q3pl79UZnRUyYoqpW96gbzveoccLtd0RSRpgIjjq1+V86c/VdrtViYSUbqlReHbb1d8yxazXbZSkjWPMAnf0wnaWWCS/b0cOUdZehRicYTwhYi8qdag8YjFoHG5zGJMITbqhVwQ7Iyp4NCo4iwF+KDLAYxZ50GP6upKCxqP2f1A+xgZHjYApDoQMBSsmk2b5CzUJr6QgSp+pjgCs0agCECKt8RFNQI4YFEFAYBAwVqqHSEvzZm6iGzmBS9t7GbztZwd3b9f3WQI1NdrvKtL1Rs3Gk0GQIaqBxUQABTzjXAwob5nDyo6MGBYPu2Xb9Caa6+Qw+0x2o1g/4jCxzqVnBhTNOWWu75FNavbVBIPyu9OKRGNGuDBaliKlXsAzurVhhdMlQLHFPQfgLSZDjmF3DDkgACgqIBckACEQWEMd+60InRCH3OhN2QHE6pR7922EkFFBLeuSz5oBe45NBa4f/lL6cgR+PCWAQYQQQuPLAVmzP/6X3aefqJRFcCilsk21QdoFoQHXvrhkyAgh2PnvEn3j2xoJJQyCEysqvrIK2i1VRAcs2bSno78ixW1p8nEiVuROlUhaFQ0Ovr00xaA0NFcVnPnO1nCCnE28zVa56vgTmvXi7vVDDvTzz3yOd196G5tb9iuifiEhsJDevvlb9erN70652FYkQ27uqS//VsJPUZHh7R/vx2P//2/T61MADqpynGfXn21MqGQMkeOKPG2tyl+662nid+p6AJEeAbwMxOg0I/ZFZPZwITnB9UBwECuuotCxwcgw/OYYy3nwhJ9RpRPERpwM1MzQ//6+iYN7YtjQnlrbi4ruK/oYTD+QG8HqFnMeZDj0xZ7PvP85fx8Ho9qKivlLp0796XQsS9+rjgChYxAEYAUMmrFz5y3I4CWAgDC76UklfNSZZKPMJGXTnV1qXnxZVcNGSAAQy6Ws6x2sYKHS89w5wGNHDig+OSkvGVlqtu0SasuvfREcNRMm9/4eEyd9z2g6HhIPldKjWsbtOHlL5dvmmvDCzk2PqZ4KKRo0qGUw6NIz3GlRnqVSSblnd7OTC6cTvkaGpSBPiSpqqpakQjCzZgRnsJ9nu2Uk89NkAUgVECy9sf5fP6C35YKBJNtQAEVAUTy8wm45xgMJBE/+pEEI4aJUjBo552YQ+3da2lYzEVPwUSE9B24Q/JUWtoTeR0AgW1/uTJULFy9CCpEL0Ebedg6e61/h9V4zNa4wD3v+q5EiKQxDnjR3LbJVC0Q7BtHslU2B2Yx2+DZY4jQHYtdrHUR+lORabrVunjNaE/0PqFv7fyWjowdMdbEW+q36P3XvN/YFp/VBuXv//5fIq+tLubAASvMB3WuW3fqqf3DP1jNElW68XGrofn937eUwemWr/h9LmCSTjs0NhZTMkn2hk+NjRWqrMzReemsDuapB8cxjGc9z3yornV1OGhZXRfOWwAQfvOc5B0AAJkpgM+nK1RxACA0vg5UquerqHBOoVDcbIvRCNvNB7yoQLPYxjup+PzN54oUt13JESgCkJUc3eK+z7kRoPIBAKESspSkcl4U2DPalUGpoaHM5GxkLWf5TdViMQCCJz0vnJERrIGjqihzyzE5qlQ0qqr6ejVu2HBKmXymza8vk9Gxn96j8aNd8nicqlqzWutf+UqV1tZOr1Rin4tUVoLaNX7kiHoeftjY+cL/xSmV32xPP5zl5RpjRTRDOFlA4+OsXqYN3QtXGsShhdIayF9hdRQAgntXsS3fCAA4sovaV10l9fdLO3ZY6hUSCaofz3++nWOeooc3k+7PS5OHjdOayUapf6605c9XxucfgGUqIOlpi+m0tcRd/fqFBwPzAPIHMFmY3dBrAKJGHjeZOYZG1vxSG3KYb8NxrPenNswNi17oaCWn36vPDj6rPUN75HF5dF3rdSsHPghvNNqcRslbvXBvqL599rMSWiT+jY4N3h2aGO8sR6nDh62An6oJjm1Y50Jfm73dHEfMB5iMjobNM5IFGioELNIQADhTY7KcVK58L3cu27OIg0geahSUKIDGzAwRxoN3ATQsWnm5z9C/CrXpzS5sUdmgYoTgfS7nQRasMBtg8Yq2WOUFDR50uWwY7EJ9T0PTc7mWtYqUy1gXt7n4RqAIQC6+a35R9xj9RNYJi5UgaEGFtGypPOvcMrNUjuOTDfhipcyviQnLD+blNFtUODgY0sGDfWYegKCcVazVq2sNcJmLXz3T5tfv8Sj49NOK9GIta/M7mq++Wg5/uRGi8zLjxVRV4dHwMzs1um+f0ZcgOHezIrl9s1a/8FZVrG43y20zHbw47/Fxm5QMAPH7oRaUz2nZmcv4wUGmP/Qrm7+Sy+eK2yw+AgCQj37UspGyAISF7SuvlJqabPXj5pul0xw3oeNgK9t3j510lzRK637HUo9WolHlyWpA0H4guG//3ZwC/OY9HTQigChE5DhXje204YbbPlHYfskJIXCNKhSi9XTKjk9wh62q1N0g1d+wuLHAUsaP6wIQ6r/XZi9QnVr7ZkvLW6jhOPDjH0sDA/bCv/KV1hBhrkaJ7CjUO5+lbC1RCzAXMBkamlBPz7jJEGLCXFtrAchMjQmfoy1G5ZrdBQANFrk0nsGFVhwWu0x2QYmqedRUEFjooSpBJSTbeEaykETjPAoFHzPPhX0utB9beZkwFXiaz+cyz+f5aG68kzAVAIDMZwKCEQvvh+joqKXhdnSYKnyxFUdgpUagCEBWamSL+z0nRwAKEwAEHUXBSeWSARVWLEhGhlt1df4TYkFWm3hxud1exWLuEwJFeL3YQ1JF4O/QwPr7R43fPnQFXH7Wrm3UqlU2oX2uNhMkVFZUKNbbq3BvL9M5+RsajLBweGTKWFLywsS5BU/8WOdeDT3zjHHYSifj8pdLtRtXq/WG58lZWquJuF9TU3FNTASN1315eYWmpqDZJ8w+oE4slqSePd9Dh5x68km30CVs2ZLS5ZenNDJSBCAr+YX44Q8lfo4ft1l8UK8++MEcXVGpfODvz0Q332A+HLTQdsQGrJaj9dVzVg1OztaS1laXhr5lqW46iMehTlEhgX4FAClbZwHIUh29sO4lkZ5UdETzAJLyDhs4WHPlyl1OQhuxKKYyhSYl2ifVXmO1OTP0KCt3AsuzZ9yjcKYKhabkcmFLTo4Q9sBWDE/LJ2CRCTQVE56VIyMEKdqFHaihgIJCq7OL9Rb9x9gYFCwWlTymkrMcIGOx4y7092zlBdtiGiCMasl8FKze3l6z2IYmcb4cJvKweEek4nFlUinVbt5sskLmaljXh44eFSG2JdXVxs4XGm+xFUcgnxEoApB8Rqu47Xk/AlCYACDQsApOKp8eBVbheMnCB565AofeITI6qsm+IUWjHpXW16m0xoKKlpYyORxpQwFD4Gny58ajymR4sUFPOskvnvPBn0iIaoJ96VTIX1pqxOqTx4/L5fMp0NyssLtSo6NRQ5sCQBhRZGJCI/v2aezQITkUVfWqSpWvXq2KxnqNT3k0Eq7QRDihaHTc9KW+vlpVVeUnxKdUUnJpR444deedPh044DJahPXr03rDG2Jav37QACJegNkAyFz2V9wmtxFgrH/zG+tGS6UDV9XmlZYl4GrFRHn4YUurAkw0PN8mzC8VWOTWbUtR2vdZGwxI5cJXJzW/WFr39qVVKYYfsTbBA7+ytshUHyq3ShP7pbVvtRWJlWoGVH1ecvktpQx3NMDh1o8tDO5W6nyWsF8mytA4AQfOeEx68EFpdFSZxkalrr1WCZNXQoJ5ImdgAu2ICrTbjSUu4nav2tqqFAiUnNDKccpUEaBOZd21ZlYt8u0S++JnpUBOvufD9owtlRAalY/5wAfbUQHBq8HlKjEAhMWw2dWS4KFDGtixQ4HGRrNQVbVunZrnCZYc2rVLowcOKJ1ImMysum3bjFtjsRVHIJ8RKAKQfEaruO15PwJQmPC2B4DwIC4oqXyRUejr6dHQ7t0KDwwpnS5VqrRSVRs2qrapUqWlvDQAHJZ6kNVF8DJlVW0x95Z4LKbeI0cMR7emqUkBv9+sWk2w9M2LqLraWO1OqeREcm82FZjVqlgopHQsJI/G5SsPyJFJaSjk08B4QFU1pdq5s9PQDGprq1Rfz08gLy/6//ovj777XZ/Wrk3L58to506XXvayhH7rt/rM+QFAsgGQ5/3NdLF3ILRfIqsDh6qy9TbEDy3JpX8hBVadudEhbBAqGWCEqgoC/mxieiFnAZja9UmbCQIli355qmyGCIIv8kEQz69UC3dJe//eCuJ9tVabU3ed1ea4CqOMrtSp5rxfKh5f/aoFIPADoYa96EXSm998ClDkuYiTYBaQzAVMoJYODk4IcTiXo7zcc0J3MZPKFQ4nNTZG+rlDFRV+UwkuxOI35z6eoxsynl1dPRobY8GrxNCwqNiT6M54AaxYBJsYGFL48AG5YiFjUIIDY+Uptnm2g1yj3kce0WRPj7FsB6w0XnGFqnD+m9XCg4OG0uXyes0+jd07Bi1NTaZyciYbGVtUbaJjY/IEAqpct87kfhXb2RuBIgA5e2NfPPJZGAEoTFQQoGCZCsJpxPiln1Tv0aPq27lTzlRKFRU1CkfiKmvfoKjRWSTNKhp6kOrqCjMhXwx0ZM8Iju7w3r3qPnTICNMbNmxQY3u7hnbs0FQwKG9FhRKTk6rfvl3O8mol42ETZlXirzhVwAv4iY1KqUlDXQmGSzQUtI4uR492G872unWNymR8pnoC5SDXlgUg69YhokSXYAHI619vaWm8/GYGQOa637O6HZ7H991nRRbQDK6/Xnruc5e2wn5WO7RMB5/slPZ8xlKqsMqd6LQr9Nv/Smq+dZkOchZ2g+h954ctAIDWNfSgFBuSytqlxudLG983Z0r6sp4ptsA9P7HCeqMBeatUsWlZD7HsO6MM98gjUk+PdeAimR6HLdrBg9JnPmOqH2pvt9ZsuHORXI9IaZE2G5hMTiL8Jg8pZUAFiyZZOldWY9LfbxPWqQRTCWlpwYGvzGghskJ4fl/ojQoTifbDwzHV1dWYKggV7dWrK827CDctzAKoLHmSEVV4k6pprDKU3vneTdjFUwEhMJft6rZuNdkiMxv5UlRKIv39crjdhtplckd4D7S1KcD+nU55KyvlPwPGJBixDO/apdjEhFwej2q3bFHtJSuUeXSh31TL1L8iAFmmgSzu5vwYAR7GUKQIJEQknm9QYC69HBoY0MDu3YoODqoyEFAKkNHYpvHJlHnII8ZetQqtR3XO4IPjIh7v37FDI+PjSsfjqm1r09rnPEcTx44ZGlYmHldpQ4NqL9kkj3tKsWCPRLhXdatU2qBJk5qORsAtHzaSWI06nIrGcXqxgsbBwQHTRcalvNwGFuZjv9vZeZKCxbHWrUvrttvi2rBh6PwFIL/4hfTtb9uQDRqi3Xe+06q8L+aGQLvzTunQV6XIMcnhsbkeDS+UNv/xma2CLPd1oE+9/22rO9j74kK16rVSy8tPJrXnc0zoalQ2oKbhsDWXo9fs/bFIQFWHYESsgc/19u//Lv0U8Xy/CTXVdddJ732vFbrv2SP93d/JCMMAHgAQJp0AEOyAC2wLVUzQ6OEwCEix4YQBBQJoSNInKtBzid+z4KTAUzrrH0Ocj4sW7lmAr1QKx6x+jY1B18pWQErNs53+Az6wEqZCNDQUUWtrual8L9RYDKMCQn6Ur6rK0LZmt/GjRzXw1FMGoAQPH1ZsdNRUVZxerya7u+X2+w0gAbjUXnrpioMQANPgjh2qWLtWnFv1+vVquuaas369LuYTKAKQi/nqX4R952WEJzoaDOhX+QYF5jJkaEzCY2Ma7+83wU/e6mrFM24NDERUU1Mhh8NnXFRaWytyFjOSWr7v3l+o+6lnFVFateuatWrTRq1/7nPNKhLWuvBxKWv7/F6NH3hUkYF+ZdIplVbXKdF0uUIRl5JJqhAeYxuMdoXy+8AAdIaY4UpHIkGzmlhSUqqGhlrjyjWXDeRC43DwoFNPPOE2GpDNm1O68sqUxsfHzEQAYNM8mytMRWZwUEb1zt/OkbI4kQrwpiv/9Qty/vA/JfjQTKB27ZLe8hbprW/N5XY4t7eBYuRw5zYhnqsn8ZD02O9Lk0elqq2Sw2urBTVXSWVrJP9qa+2LgPt8akz8j33Paj5wxAJ40KdC2tSA1Pk1WyECgJB2v/7t55Wg/JRu455F0iXf28svtxWNiQnpE5+wAYgIl48ds24I2ADjiMCXCZtgKiQkZGaFSh/4wCxv6EIG+PTPWH1EQjhxRaMxI34HfPAMohUifj8fgEk4HDcgAn0iz3c0hX6/c1o36JLXawNtEa1n9Sw2e8RWQHBpXCh7JJ+rw4IZVOSpwUFjkkL2FFQsc23Gx0/QoMJZChf30Qq2cH+/hp991tDAoINh2FK1wsdcwe5cELsuApAL4jIWO5HrCLD6hUsVDlQkfS+W0zHXfqEq8RD1et1zAggyL6B5UW05GfrkMo5Y0WjaTPChNeEXn0vLpNPqvP/Xeva+RzTcPaTxqbBat6zTdbe9Qmu2bT1tF4nwuIaf+qUSY31yeX2KpUs0VXeFnGW1pvrB6hiWjdDAsnaOWO2iQRkY6J/ONCk3mR3wrLGYRLBIJaRQESYVJ/jcAJCWmSuelEl+8APpgQdsfgGc47e//QwoqOcfeeZVd99tk8UBIB3DD+r2gb9X5dZV9n9gewz4uO22XC7fubnNKSF/JVa43fC8/M+VKsiuv5RGH5fKNkpTPXalHwcqHJtKWqTWV9jqwfnYsPfFYWt2SGKufeFmOvw1qfu/bBUFu2PE5YQvNt2S617One1wOfinf7JBh/SN0EMCZlgB/8u/tNkiABASMQHrABC8oWlURvhioQPgGYBNcFXVGe1bLhqT2VSu86liAp2qv3/SLBzxb5yxqqu9RvdYUlJinB9n6x6zGhDMAgAtCNRzpQUvdPGM02N3t6IjI8YghUpJbGzMfGQKkxaeo7xHy8uN21Y5yakr2DifyMCA0UG6S0pU1toq5ynBSCt48OKu5xyBIgAp3hgX1QhkHUEKBSCI9ZiUM2GnkgCImFkhIOiwp6dH2P3yEEdwTZWFVSdWmKamoGDBUPDlXP2g3L3nv36qvQ/vUnldjbo7O1Xd0a4bb3+dmppPL30jNh/a8ZCiQ12aCkc1MuZWtGaTfE2tqq6BduZVYyMrY5TnrVUmrlm0WGzcCBQrKijBlxi3GV5MgJOGhoB5oRXSqDihvzkNgDz5pPSlL9nJCbxxBKovfan0/vcXcphl+QyLu1/5ip1LkeemiZBe7bpbby/5jtWAbNokve99Nmr8fG1HvmXtc9FuQDMq3yhtfK9UuTn/HpGo3vUdCUteqEbRIal8vaUajT0jVWyWtn9yacLw/M8q908wkc6k8k9PX+wIw49J/fdIffdJ8VGp9ZXWLWx8j7T+d6TVb1hsD8v/d7JYeu+Wwt2St8oK9v15UKD+7d+ku+7C3s5+F/btk974RhtkyJcGrRSTTLj+0Fv++I9tIuY53i4UYIItL89sm8zuNM9sv99hnB8BHgAQgMhyNOyJeaexKMU7JR/QkohENHb4sBLhsErr6owgvAgGluOqnF/7KAKQ8+t6Fc92GUYAS0IACCX1+TzR5zoMk3XCn0KhuKlisChKACFggtV9VvmZZLNv7H7xXe/o6JgzUDDfbhx/7Ant+fnDGukfU8wtrbn2Mm1/0Q2qq5s7MyTU3a2R3bt09NkjGgtLgeY2ZaoatXrrelP9mLnKxUuE0j3zsHA4aIXrJaS6l5j+kv9BEBccYahb+TZoD4AyXvIAMihYJ15WcMZxx1mzxgIQAMnWrdKnP134qnO+Jzhre/I07rzTMkugsj/2mHRdR1Afv/nXdtLFiu4SeOtLPL2lf5wL/cxHpNGnpZqrlUmEFB/r0kTDu1RxyctzCcQ+/RzIzAgfk8iwGLhPcgWk0hZp7GmpbIN0GQDkHNQxcN7H/93SxkrbpDW3LY/AnJR5Etqx0MWli/0jaC9psk5hBDAWUnFi5KEq3n+/RPBgba10yy0nxd4L3R2mGvNVqX8aEDl9Nl/kkg9Jnorc7qtvftMCEKhXfBeeeEJ6wxtsFWRyUvrJT2z1A9DBQsL5DNKnqVqLuXKdSxUTzgUQYgTlHoJffYrHo+bdxDO9rq6u4PDdmTdIJJIw2hHCcwlBZNFqPrMSOz7cLmRdFdYQsKM3MbqRYtWisEE8Bz9VBCDn4EUpntLKjgAULCoVTILnS4XNFYBQSchk4grDcZ5u/BuhOQ98HJ/yWRmar+fQsLqfekZjfcMKO6TGS9apsqbarGjN1Xjodz21W3sf2qV0eb0CqXE5Kup06S3XqDLgMhxcrHzxcJ8ZIIVAH+oY5+71BkygYTZxmOoHQYr5vEhIngeQZR2wWltbTwVkzO6//GVLy2DSwu8Xv9im6J2lBvXqa1+zbCswEfOpl79c+sM/LPyEMAF6FFfXlGWoXHHFWcNXthN7/j9p4H5lAu3q7gxqYNCl3/T+nuLVN5nF7Dk0pbl1Ph6czuV40lZWfPXTuRy/c5Y7PMfpx8elfZ+RRp602gyqE/U3Spv/ZOk5Jr33SIe/YsMZmej3/lhyltj9Y6m75rdPr7gwgecm4VkCFZEbZTb1C8oilYZf/co6SkFhwm3qPe9ZPM2ca/PMX0qRLqly23QgZEraRGJljoYKLBB8/eunUrBuv926wl1E7WxWTLL5H0zqocYu9jzmfUQFmmd6fX29cQHLt3FMS8e1wAbaFlQvAA6Ap6amRG1tp1e6CIvkc5wri15ZQxMW82ARGPeydNq4aSFOn8sWF7pWcP9+UTUpqakxAYlQqJa7Ea5I86BdKrYzMgJFAHJGhrl4kHNpBBChMymmzTeBn+98sxQsHsAp7DqVkNfrMA9SGmVuAAcP/SwFi1L4cjY0JggsmSADoNB1EB4I9Qrhn3mgC1VO7QAAIABJREFUe8s00BNU5459ioxNGnHhuu3rtXrLegWfedIEEjo9HtVdeqkar7rK2BLS2Hckwosmo/LyKhO0SHUEhyzK7FVVaFfmT9zN9pNVQ156VIJ48fGD5obzBZydaMzIcZh6+GGrAVm1Svrd37W/z1KLRi0A2bHDghCKM5zSHDb3OZ3h4cOWNo/xD93duFFizjZPxldO+1zyRmO7pM5varTnuPYf9Gl3z+V6cOA9Gg359ZKXLJEBF+mW+n5mHZwCq6Xml56b9Kux3dK+v5dRyHKeoQOWlrT1w5K/dWlDPPhr6eCX7T6oeCBmr75M2vQnUmnj6cAiEpG++EVbAWQi1Noqvf710s03n3oeoOG//mtpYEDassWKvslT+B//w5bsFmpcDwAI9sIGgByVXKU2OLJqu7Rzp4TAHOvc5zzHlv9mN2aSgCQWDvg3TnA33njugculXb2CP30mgAnaDuyF0abwTEZongUh2fDFZDJlNIrQhHkX8b7jGUwIbCHWw4CM/v4JRSKWcsU7hzwW6LncBizEIV6f2fh7Tw+MAei9jmnjlXIDXhDK8/cST0au4S7FgqNylZQYlyzseWc2whGDBw7IjaNkPKGyjZtVtnqt/H6PAUNLbVyz8c5Oo1fhnV22apUJYSy2lR+BIgBZ+TEuHuEcGwFW+Xkg8wA/KRLP/SQRZXd3D6m/Pyh4sH4/nuo1qq+3/Fr2TYWFxgP/lAl37ocxWyZjMU1gdzg1ZXI+yltbNTwyooGBkCYmUqqsrFZFhVf1dX5NHD4gvM5xw4qX1ihW2Sp/JqKuzgHV1pWrfesaYz+466e/0eRkTM50Qqs3tenS17zsRIot4OzgwWEFgzFVV9ealwYvN0szI9vDpZaWCiNWnK9lqx78nZwVqGiI/dHBzNl4gxGkyMSrrU2pkoChlrMQvHo1NLc8B20ZNgd4MLcDEwE85ik05XSk735X+pd/sfNDDL7QmLz2tVZGclZbpFuP/vyw/uNHPmUqLlNpeak5N/r7oQ/ZKsgFvRiYzTFBuxJYI00ekso7pG0ftYLxpTS0Fgf/SQo+bRPaoV+te+v8Tlq4Q33hC8R32xv+2Wct1Q9h90zAzvcEAEKlcPNmm69RXm4BCILwxVrX96y9MOnu7jKp9lqp433SLx+UsNElwwOHKo6Nhe4K5CQtdooX4t+XC5hkMg6NjGCzS9Ar+SduQwPOBixSbRgeRgOSMhN0wIkUMyCEBSAosIW8j7A0Bkxk6bhVVT6jIYSKBWW3pobn/KnvBKol3d2Yj1gNIcU8qiQAKCrrgIep3uNyDx1RoMxrKhxoQZqvueYU1kD/449rrLNTJbW1Gu4akHNVh0pa15jqC6BnqSAENkD/k08Kp0kW7wBALMp55wLgF+LNeRb7VAQgZ3Hwi4c+OyPAKj+r86zSw4nNp7GiD5+2q2tMXV3jhlrk8ZRo27ZVWr/e0qF42LMNqymUvAtZccqeU/DQIQUPHjzht4514KTDpe7uoJJJh5qa6s0Dvq7SpcjBZxWPREwJOTgyqUxju1zlNmyqwpNQarBLex/Zq92PHVTSxQvDodXNJbr29S9Sy+XbzPkeOdKjXbv6FA6n1NBQb14aeMKzD/pKgBUPfqo6gYDnxCoY4YWsik1OWv3LzKoHOptcx4AKAZP1hx6SWBRmLka1ACfP87VlAQiVDwAIi9yvec05AEBkF7NhwMHmgQHHvBecyAJgMGgp/AAnDIs4/wuqQbk6+m/SwC9t1gd0sZaXSW2vWp5uIsgffUpKTUnlG6SyBVZVoVRRJqOaQaAb5TfMDv7P/znVlpovCNv9+tf2AsERvOEGW7Lyem1VAlBChQR9CCBlJo0L17LhB6VIj+SplBqeLzlKpI99zB7z0kutIQSgB4RMlkexrdgIzAYm0F+z6e8cdLZdMJUNMjvC4Zi5rFCwmpoItC011CrMREh/b2goF/a6mKRkMlHFYlFjLAIluJCKPDRcNB/8ZhGKd4Ldd2ZeijGVDgxO0A+yHdVzKiVkTnFugKZg5xF5Bg+pst46ZFWsWaPma689hRaMWxbvwOj4hMYTXrnbNihQU2mq821t9H1paeZQvAaeeMIs9gFAPFjFX321fOeBecKK3ZhnaMdFAHKGBrp4mHNnBLAkzArGqVDk0qiWAFpwt6IdOxbUkSMh1dZWK5Nxa9WqCm3aVGscsagAkLTOhJ4KCxWAXBvcWFJ7DR81Mq6Jg/sUn5xU1fr1JryJxNlkRaW6u0c1OZlQdXWdqVLU15YodGCP2Ybmq6mVo65VkckpOeJRJYZ61dfZp6F4mQ7vPKxSJ/QxJviVuuwFW9VyaYdKm1t1/PiADhwYUCrlkMtVZlxU6BsPe14irLxh48s8B9oZVRHoAFLSTGB5KeVU9ZhnQAgb/3//TxoZoXpkGSGwQT76Uat5PR8bjqVZChYL3EzkcfGlX2e74ZSKsREL8ESx4PwFAKGAx2I7EgPkCCyI/+m7D6gm/aiENW31dqn6yvOfesOEPAjXLiiVNkmVZJkULpYt+HpiSfq5z0nPPGN3wZfpZS+zltSzGxfnnntOitDRTGUnS//931YIzheIi/eiF0mve93CfYJz+JGPWOCCuJwbAScrAAj6krPduBEJAaUas327BVoXeFsImEBpoorABJ9FIKoRNN5RY2NToloBToWC5XK5lUwCVjJqba1TR8fagjWJ6DmorJgFLbMItfj3hPcZQnX6A+Dgs9CYqYDw7vA6knKPHFNybNQIzMnlqJiDfhsdG9PkwKBGwg5NOcvMe5YFLwxVstWfQm+JdCqlkWefNUwD9JDY89Zt2XIKCCp038XPLTwCRQBSvEMuuhHAkhAAwko9JenFGqAD8JH1gwdYxOMu9fZaUR4P+jVrKtTaWmke7mwfDAbNv9GYUPrOpfGQxkJxZGhSI2g0JkZVGhuVMxU34jt/Y6NqOjoU83g0MWHF4XV1DabUzipQdHzcpNOmk0njuY7/+viRI4aWNdwXVHDKrUxNozqHXIrHM6rwJrVpa5OaK9NSWZ1qtmxRcGxsWgOSUm1tvZqbA2purjB2vVg79vefFNtT6h8ZmVQ6HdPo6ITWrq3TlVeuVmlpiXEXy7XqMXNsWNiFCs/iLcUp5mOsxv/VX53fbBCCoGeK0NF/nI157lz3IaAIoPfggxIOYMxld++2AGR1a0qXbEyppqxLf/aaL6nZv0di0o5t77rbraB6pRr8N36gGOUzWKDj0F5LM0J/UYWY+zxAr4iE7r3XWlGDUl/96oXdrajghI9KaNECq6TxqHWPg7/Il4YwQH5Dz1pMU/WNb9gUc45No+QID+9s8B9n3k9UZf71Xy01DOHx1VdLv/d7p1aFuN44gnGP8NDI515ZqXt3hfabBSbo9OLxhJzOjDEN4YdGhYQJPpN76FGRSEyJxJSpmGzYsFpXXtmxQmc29245XwAIC1hUTtAi0qAuI0Ln/znSSWOKggB9rqoDVQlSzHm3AYBS5XUqXbVOFRUlhhK2HCYvvDOphNBKa2uLTltn6C4pApAzNNDFw5w7IwA4oEIBUKAkPV+DogVQiVGa5SWHntTrNQF9TK4pI7MqxEMUC0KE4DSADcegIbrO1Xedh3RPT0ihoaAmOw8qNpVQfbVb7ui4Ktvbjf4DEJI9d7i8cwEoKhSDxwfV/cROTY0GlRnuVjzt0uBoQmlvqYL+NvkCAQXSIXkdaZOB4KmpV/s1WxWNTsjjSauy0q+mpkazupRd6eL8KMMPDIRN0u7ERFjDw2MGgHm9PrW0VOq669pVU1O47z85ZywEUzWAgsv8Ex0uc6ELeF5xTnw5AEl33GHByPGujPqPx9QR6FNLYEy3PPdXesvrfqbKtg7JVSIFn5LaXmP1AyvRQKKs5lMJZBJNyQhUmkvruVvq/YkUG5Y8VVLjzdZ16kK6gdIJ6ci/SCOPW7cxMld8t0r/8HWbSo4eBABC2fDP/sxSsRZqCK5+9CPp0CFL68KJAArY2Ww8c6GggYzhAaJ7QZT0B38gXX+9PTPuDwBKtnKEvdyb3zwd4HM2T/7MHnuuisnw8IS6u20l3uXyav36JrNIdiZbVu8BcKBag2aDBbN8GtoMNBqJyUlRrSiprlbDlVeptOrM9iWfcy5um9sIFAFIbuNU3OoCGgEm8Pyg1SCTYq6WdQ6h6kGDN0uIHj8zG2Vw5jUzV2EALFRZeClYl6rcbP3Y18DAhAZ7xxQ8dFCOyaDqKt2qWdWs2m3b5J0WhHLu0Lw4p9kAimMODoZ19NCg9j72rMaP9ykQG1W536sJT6XGVaGYq0ylPikdDhkDoPIqv/y1DVq7qVEOR1RVVR7V15fNCW76+kLavXtAQ0NBeTwZud04kQDKAtqyZbXWr7c0tKW03/zGBiajAUGEjgYkh0JVzoeEYcL8lv0juMZB9Hyld+Xc6Rkb0n+qG9zKLLRn+8587z/+wybA7390TMOHx1WjEbX4x/WWG76tW1/1pJybnm9tZQ0AebXUsQKBkVCB/vEf7WSYe57VXWhGuaj2Y6PS7k9JE/ukQLsUOWYF4Jv/TCpbW8hwnZufGXzAJqzjbIWYPA5n8cXS98dsqY1nDqAC7hwVkJXms1ONiQ7a1HjfMlUhuO5/8RfWDQJgwQo1+pR3v9tSy2iAJlz0pqmx5n4BgLziFefmdTuDZ8WC0dDQpHGhQruHLiRbgThTp8GCGnQr7Hdx0mptLTc03Xya0WgAQCIRo9GgStKERgOgXGzn9QgUAch5ffmKJ1/ICECnokKBU9XsnA5K2dmqRxZUQKHCxSlXShFhhOhMrPCuymgicm1QunhhTA4OS+PDCvhdtvIxQ6vC+QFAaFkAFQ+HjVDdWerX4HBMhw6N6tiBXo0PjqosE1FZuVtOf4Wm5FP/kQFFQhPyeD0qq6vRqs1rlM5Ym8TycoT5JeaFMRvccG4HDw5o375uUz6vq6s04se2tjrV11ebzyzXCw5aOl2Exr6c4IDC1Oc/bx1HmbPATMGRipyPi6GxUMyCcR/GTwHroMp8bSYIQUY08b3/1ugP7td4y2ZVBNK6NvQv8r0kJXUAwKHsbZDWvlWqXwEhC2naKONBndiPIQwCKX3qU4vz/8PHpWf/2orKoYmFu2zl45I/kaouvXAucfd/SYe/bsXtBDxSCcHRquLtdkIOyqyukG67TbpkhfudmJCOfFMa32sBSO3V0po3LT1LhatF5gnUMNAxDwWqMh/4wEnHL+6T73//pKAKO+/f/m3pXe+6cK71EnrCOwiTErQXuWg2lnCoOT+arZhzbIxK0GxUVeWX4QHoGNm7V4jReVBVtLWpuqNjWahXy93f4v7yG4EiAMlvvIpbXwAjgE0uAITfWZtcHtQAEiof2aoHFKfy8vK8AATDg4vJMHQBwWZYwH52kbHM0r5mc1wBUNngQ0DC1PCw8TFnhQjtR7p2lZ49MK7jx8cNhYoHf11dqXkBHd7VpWPPHpG3vEy+5JQqmyrVuKlDnmnPeJcrbjSehA6uXdt24gyho/X3D+vYsRFNTiIsTButxxVXrFUsVq89e1xmEgtFOxc30LN1G2E29KUv2YV15rfYzhJlgMZkOYHO2erfQsdFmAqjBcE5wIs5KoZLsFmg17NIftNNVnJh6E/oAhgUBouX/2uvk164xlD2jFibFO25aE2RXmnkEQmaUMXmaQ3G4oLVE+f++ONWCASVCE4/nDDKVAilF6NRpWLS3s9Iww9LDo+UjlnrWyog3guIsjH8iHToqzZhndT5VFhqfaW04felZFw68gNp4ml7/equl1peKTmXnpkw5/117LtS1/fxbLLXnHFe93ap6Zalfw0QwwOoqIqBmElXnxl6+L3vSd/5jr2BASn4Z7/pTTZDpdjO+ghAB0YUz2/eRbxXCgFCgBB0Inz/qYAsh+7jrA9O8QRUBCDFm+CiGwGABgCEiTw2uQAOqgoABxoPN3QbgIdCPNOpomD1C4BgH7NpW0sdcM47m+SOBmR4926T70FJOhkOq3rzZgVVpT17ho3Yr76+1FgEEyL14D1P68COg/KmY2ppLtemqzZp9ZWbRbaJw4HVbkzB4LihYG3atOaEqN6K8DOmKoHNo8PhU1NTjcLhGn372x4zPzALzZfYUOZzFYRALwKAMNlmbstcF3YHi+sz4xaWeo2W+nnAAm05zwnzJNxWkQYQso1ul+JClp0D8MB1FaZTSXLSViF27bIUKHQYiH/hxC3UpvqlA3dI48/ayWjZemntW+wkONfG9/DOO+3FoUwFTfJtb7MOSLk0ghCPfUci38NXK616g1RxgXkIYwRApgdACw1Iebud9JfUS/33WXth+k8rbbEZJGhhVqLt/7zU82Op9jlSJmldxaiOcczlaNnqBysjs78QlDRJDUV4T0Prwn260pSz5ejXRbQP3h2FAI+LaIguyq4WAchFedkv7k5TPcg6YUGvgjKVbQAOQEOuwvG5RpJqAWGHABAqKPwsZ6Nyww9AiQrO6J49xu2KpNh0LKbaSy9VuqJBnZ3oXKIqLy/R2rVVGh0K6Yf/+rC6Dx6XK5FQe0etXvHOW9Wyrtm4b8EXjkanFItNqaHBr3Xr2sxxZuZ6uFxoPvzGcx5R4Z13Og0Dggkt81Ro+295i6X1nIuNSTcid4AINCQWTrHD/du/zV3jvJL9Ygx//GNL46dxbtDZlwOIMI/7+7+3faeoAaWeQh0sJ46DAQDSgQ9+cHquD+UFZyYAARQoMioWa0xEoQahA/BUSGM7bRL65j9e7JOn/p2BIJQExIsP8DxarXl3SmepfqBXWaxqkt+ZnTtbm4n5oAUgWAg7p8W9h75iKxJQshB5jT4mrXmj1F4gLQnkev/91tqXsuEtt5wq8j7yLanrB/Z6cy5ySOveJrWeIV4j9+nhw/Y6Z9M+z52rVDyT4ggUR2CeESgCkOKtcdGNAPqJvr4+9fT0GHCQzelAq8F/FxLUNHMQqaiQKE4j/RtAU2hDSIitIha46CvQWUQiYQMMaFRwEqGQxg4fVnJqypSn4ccGJ1I6cGDUgARSz9vbqzVwfET//b3HFJlKKp6S2uo9uu2dz1fj2iZ1d4dMam04PKnycihbXiOeB5Blcz0Ym9nVHKoJBCijdc3OGQEgmBadqw2a+Cc+YYXYzKkxV7r1VkstP9tz1Z//XLrrLguOaC0tVoT/ghcsz2jCpPrWtyR0HrBz+M08FgBJBkhmMqwP3fC4Ll8fspkQi1U8Zp9WVpuAKxPi6NFHpaYXSVv+5/J0oLiXxUeA6gcVoJJGe3GhaaHJWPumxT87ewvAJ3Q4nKigwPBlwZbune88yVmMDllB/ARlUJdUtV1q/12rTSm24ggUR6A4AkUAUrwHiiNgR4AV/d7eXh09etRY6jKpBiTkmtex2DhS+ejv7zcVkOy+F/vMfH/HxhDbW0rYBP+RQOtwJNTfP2L+X2troyoq/EpGo5oYCyueccvl8ZhAqmPHcMtKGJvcjRtrlZiK6GfffUg93eOKJ6VNmxv0qttvlKfEp/37RzQ6Sq7HuEpKsCcu1ZYt7SpHK+LzzZvrgZ6A5HIoWDQYEOg/mdCea425GAADl60vfMGu/KOByGaNfPKTC8cunIn+oLmlokROCO2xx6ymlvnecjWAIswVqiCEEKL5phpSkg7r2tgD+lD1N1TmjtqqB45DrCrn2iYOSwe+IIWelXBGCqyxFKiWl+S6h+J2Sx0BNDiHvmQBAQ0x/sY/kErndvxb8HB8sT/zGQs+OjpsVQpUjDvVzKoUqe+TRywAgQ6WrcYstS/FzxdH4BwYAajMLARivkII41LT18+BLp0Tp1CsgJwTl6F4EmdyBLDJxaWqq6vLTKypIiy3qC0LQKgicIxC2+DgpIaGIiZwKRgkODGgcDiirq4B4RDc1tag1tYaIzTHccSmkrPwmTGJ6mVlHoXDSTVVSemhbu18ukdHjk/JX1ujlvYWtW9u1tRUUocOBZVIxNTd3WeqH5s2NeuS/5+9MwGT7CrL/9u1974v0z2TmQlJSDIJhESiLGEXxEAwEFAhBJS/qARE8A+KLCIoIothR4E/IEGECGFLQECIQIjIGib7JJPJbL3vXV378n9+5/Sdqa6p7q6qru7p5Zznqaenu2/de+53bvV87/m+933P3amdO3uX5bCQ1NMuBJeAHfVHP9pyKkoNjoVP7LmcV7q5Xm0MqXRQpaGqMDBg86gbbpBmZ21HCd0bzBt+RCBQ7VVq8z4UquDUYk/j+avBqeW1FoMOJ0SGqIy03vUjPePgR9V7brtFagQG9HPNNZVdevpOaexW247Ter7U82RrBIipC6acp7vMVNndbM6jkSOeudPOHcGAcEd194EELgCEBwViF2YxKPIBQPgwueEisEUjAHGeP1VwVwYH54zvFwPw0d/fbKSN3VhdBBwAWV383Ls3YQTgfKBShZ8GlY9KZHLLvV1asGjFgkuCF0i1g12XiYm4cVxvaAiora1eo6PTGh2dMH8Aw+Fm7dnTaaoj/JE0/dfGnyulYNBvQApGibmhB5UfP665dED3H4kp2dCjTKhRgQDutH6jcIVbLtyO887bob17u3TuubvU0VG7NgoSXV4I21B9eM5zbDfHWg7ypve+14IkABLxoLoAAf3nP7d5Fck+CT4E7NM9MHyG++1VlABLkPorpUBUdR8Qv0E/9NMxfvYz6QUvWL2kKX1enBcEyMJfdZVFgW5s/AgAGnGnvO02CS4Imyn0A/JQbnXZuI2/Om6GaxABNu/Y9JueTigUogU5aAyHASR8j8v8zp10ToTW4Orb65QOgGyv9XZ3uyCTi0oVyle0SMHTqPWAhI4aFgCkg6SrymHlgVPKZPIKhXzmj+GRIxM6fJgWL5LnLp1xBgDEL6ol09O2AtLebsvEvC8QqNPcgbs0TyJY36xf3jGqB+dalQ02KJNJqbfXr87ORqN6iqP7eecNaPfuXvX0AFBWZyro3Ta5J0RvEmskYOEbnH++3UhdRXhWjCrXe/e7rYUApoOQ5Fnu177W+rSRU1GJgee8UQYVojvvtIWCCy6oPj48Hxgu/vKXNlcEeAGylixA0E/3mc/YIDFovUJ9qlD2tNIgkcCygw7xBhUjFgKAgzu3UyqqNJqnHp+asmaE4W4pUL7fUEUXZsfg29+2fXpUP3BJX4O/mRXNyR3sIrBGEcDI9957x0xnALzLgYEm8//r7GzKdBbAw9yxw/7MjdVFwAGQ1cXPvXsTRgCVKioUABDAR7UyufwxIskrJS8IwAGAQHDvhLhZwzE3F9PRo8OGA9Lb26nubtviBVF9ft5KCUM+Z/A984yPjih2/Khwlb13yKd7x0Oajsbl9+dMC9e+fX3atatDZ501oKamiKmurNbRvPCWUckkD0Vedvduq7gEB+Ev/9IqvK7VAHMBfAA85NPk1lzvr/5qnaoKCzfGddlERnANwAO3FwBELAAGHijguFtusZUZ5kuuF1wQN6o0Rrfeak0HPYEgig5wSZZqkTMPM4gF+VsGpi4Yg6ymZYoFeMc7LIcATgkLwfiLv5D2rbFBXqUB22zHj9wiHb9ZQjI50iPtuVpqcZWlzbaMbr4bJwLZbE733z+hAwcmTDcBrc27d7fpzDPbzf+v/Ink/9ZwOGD+X6116/bGicT6zMQBkPWJs7vKBooArVFwNFCS8lzOK50eLVEQxPmDhcES7q6Ff4xo8cJXhJamLvp9yhyxWErJZM7IrlLBKPUHbimndf4g2r5V+4eTisjUVNI4q+eyWWWHH1JmelwHjqV0z3BGaV9ILS1NuuSSXXrsY8/S3r295l7WYrCJ+q532d14Nr7JR8lvAQJruZnKfxj4mKEiCvGaasvTnmYNoleTV1cSI3w3Pvxhy9+lAADwQO62qcm20V9xhXVip0qERDAu7QA1uL5I8AJYyOMRU3vc4yxwWzRAKyAXbog+fU4u63cC94U4cz7I9sgjU9RYt8GuOSYrIFAQFcGgBEYFZCOVnWoZEB72b33Lkp1QOcA8r8ZS3Mbh/Z5/kuYOWK8THOCpgmBG2HmxNX90w0XARaCiCKA6iXgLJr7JJGZMeT384d1Gxr54kAM4HkhF4T3lYAdAVhc/9+5NGAESdWR4qwUgVuUqakhpVAngX0AOb2oKn4gGJHfI7gAQSO7lDMAHvadULeBtdHQ0GPJ58SjltM6cmA+9qgCQ+vqAUcBKp3PGiXb06Jgi0eOamZrW4EhUKX+TQt071dLWoqc9bZ8e8Ygda76bg6cdxsUAAYpCJMMPf3g5kVndMSTfAB88L1gKKgDr2b7+5S9L111nr0lHElgBUIH0L6AAfz0UuFDngv8BXiU+UDAAG1CIUHX2jAJpv4fLbQZJ7ic+IUEWZtDXhhFbW5vxZ0NRC3NIlK/I/Yn5unu0fOMb0s0327mCPiH+QG5fLwS4usensndT4oIzgWwtPY1wJp7wBOlP/7Q2Zi7ebCZ+Kt33QcnfIPnD0tC3JFzgm8+yxP8zXyJ1XFzZ3Dfr0XywkYsj9g/HkLFPCrZK/rXZTNmsYXLzLi8C4+MxjY/Pm/+Habfavbu1ZLsVXBDXhlVeTJc6ygGQ1cXPvXuTRgAZXtzEAQhI8VYyaH0aHJw1KlMk+olE1vSE8sfKGxgdAkDw0cAssJyBytXw8JyR+UPNqq0NtY1TPURKOa0jEzg0FDUEOeZnW6jqzBwxGZwdG1Nq6IB8uZxJRjPBJnWfc4Ee9vCduvDCPlNSXo9BAo76FCGHErAdBgUAMAJAiNizQU430u/8jgVGtEb93d9JUDAAIJgj8sgAQKiWULWBC0L3EoDkz/5MeuQjFyIHuZsX5RTKPTiHY8Ty3OcawSJACIAH8APYA7ysZctbyfVkXlRAhoftzaDRvJ4IcD0eMu6REhbGjehS86CzyNw3aPINb7CVn1qN6IPSPddJ84ekzLx1nsd7pevx0txd0s4rrfTuVhmADD4gxJUPDB8IACw/B/AdJjrcAAAgAElEQVRRXmwYly6ISfv2SLvOl3b/vmtJ2yrrv473wWae17oMB6RWPMh1vIVNcykHQDbNUrmJ1jICVEAAIACEamRyab/iRYWBnlD8OQqT+KmpKeM3gqlhL1qvZQyqFxDg+Eo+A6jp6zvVRb2U0zrVE6oy6JTzAhh1dtYb9SwUrman55QZH1UwEVVXV7Nadj5MHQ87y1RY8AlxY+0i8Ld/K33603YD3ANgAAyAgNehQ1sUwOSDH7QtWLRqcQw/Y5Czo5DFJi8AhLYqM+iz+tKXrJW5p4lcYBwC+OB85Gq8Z72kj9cumut8ZhaCyg3lp6UMRZFWo8wFf4ZSFUFHWo1SGygQCTN6DXfurN3kWevBb0hHb5Qmb5dS41LPE6WGndLkz6Wdz5HOeUXtrnc6z0T8ARkoM/ABgDhFGY9nnuoa6m1dEems+6Tsg1LnLunMHVLnr0nn/9XakfNPZ0zctV0EtkAEHADZAovobqHyCEBC99zEq1GpsrskKVNtAHgUVxCQ+MVxHQDSRzJSxuCcOJIPDc2ZDeLeXgtAisu8pZzWmQdl42g0bd5LNYad9FnKDaJlJ6I6+dTol1rb2hRqaVnzlqsybnnDHEK3DPkj3BR4GXAtauUJgukh7ubkr+SzXOvii+0GOSDkmc88QdswG7p071DIQLXrF7+w/BWW0fNZ+fM/t21ZZtx0kz05PBCSUi5CBQTewTYbXqEFrxkKQgCuBTpMdZGAvU81A1DBCZ/1LNtOVTzoo2ORjZlKq100lAP43NNPB5Efd85qqz7wPcZ/LOXStr2q/SKLKEe+Lz10vYT5I27ktByFuqSWs6U9L5S6H1fdfW+0d6HARSkPEMiDT7xp4wPUffWrFoCc3yrt3C+NjUo950mP2CEFm6R9kMx2b7Q7cvNxEXARgOafJ+txw0Vgm0UAmVwACMl8rVWqCCUKWwAQxo4yTRwsN2XOGA5S+qWdiipIS8tiHkix03pzc7NowaIaQ16C7G4iMW9awCDZY4a4nJv5Nlv6U24XUED+SBs54ICCFepTFBJqMfAbQd2WfBZQAyfjFa8orxrBfMAY8DfIvQAri6oYTB4AQpmDAbLB1GS79LcVLND3v285L+AAhA0AIIv4MpUsJjJlyKchHwyPAzI9PWzoNxeXkbCSpxLF55xFAoCw0AAWfkayzG5ANSN2zDrL02KVy0hNZ0p7XyS1nCfd+Xf25w1nSLN3W/fxvqfZSkjXY7YOxwb+0Cc/aStIADw+qFQ//uZvLPfpn/9ZOvQL6YKHpO6ctGOf1M0uzPnSBW+UQtX7MFWzZO49LgIuAuVFwAGQ8uLkjtpiEUAml+oA7UyVqFSVEwbankZHpxSPzxtVqYGB8gjeFljguGoNkPi+r+9UAMIcaCHj98gI5/Nh44JO6xayuu3tkNCDxmARGWAASrVSw+Xc72Y/hg1V1KfI5RFm4nvazHFGr5AetGQo6B7hRV6K7G5NW6HYQyJBBn2SAG9FcvcKDxncGvJRwN5551m6CTk/QA+X+4oHpSiUAah+eCeEkEP/W/EJvQoIPXLEn5YhQAdSw6tdi2NflR78VynCjn6zNPVLqf+Z0q7nSnf9g5Ses8Tz2FF7i+e+VmrbYPLGxIM48mGqxj390KGTPA/a3TgHBCqcTBkAvh98X9KvpIEJaUerVN8l7fwdqfdJFS+9e4OLgIvA+kTAAZD1ibO7ygaLADK5VCkgdJerUlXOLVC1gMcxPDxhKiDI855//h7DNfEGeuKYHEESB6AU+ojQ1lXILensbCjpx4GMMAAEo8PZ2To9+OCkpqdnFY/HdM45PTrvvH7V10cMvyVQq16icgKwCY+BCA4AIVcEGKDWxVcAyFqaJG7CUG3YKdOy9qY32SrTRRdJo6NWbQ0ActllVUwbsg7KACgBkPCSQMM9oP8NqePCAQBE75gePibCTv1LXmKPX+04+mULQBr3SoFGafIn0o5nSGe/Qrr7nRJqWMEWKT0jtT1SOv91VpZ3oww+XOhgA+hooaK0SBmv0sGHkhIX8QUQljLIYR3mH5KSE1KkV2qsIem/0vm6410EXARWjIADICuGyB2wFSOATC4ABE+NclWqyokDAII2qlQKkvqMqWTs27dXDQ1WNxXwgSoVXA1apXAeB2QUDkAMRHLeW8rkkGPhsNA+RmvV8HBSd9xxxAAVvt+xo02XXLJHnZ2napeXcw9b/RjyFDgVYEJa+2lzet/7rP8eVRBAx1OfatVsV7uBvdVjuZr7g09MpxPKXquNM2v68Y9bw27WkIoI8sbgBfxUqhq3327b20AzJM88FJi2lJosE6DsQtslbVenmLVUNQPL76AFixarfE5q2iud8QKp7ynS7P3S4X+XkuNWdvaMq6R2Tx6tyuvV8m2ABUAcFQoWgfjgBUNlqBbgrJZzXelcrO9qH9KVruF+7yKwzSLgAMg2W3B3uzYCqFRBFI/H42WTxMuJHe1XtEONjU1rfj5qpHTPPXe3wmGrOYspIHK5+Hwg34uCVn9/c8Wu43BY8AMBQGUydTp6NGpyn5aWRl1wwW7t2dPh5ANLLBg5Eaq1UCbgBP/6rxvFWo2NWe84j4TOJu1aGiSW8yxthWPI24g1wlAQwh/7WEup+M53LLkeAMKGNrQVwOBqBqCSQsT999tuH8wdUWtd1WDnHnldyP2UxZZJQr1OOIonKJjVrPA4c7c09qMFEvo+qecyqc5nbwtiemrGtmfhB7IeIxOXhr4pRQ/b6+54utR4xqlXBnAAQGjBgj8DOYfggApRCNsM48AB6Wtfs/eAKsTznufKopth3dwcN0UEHADZFMvkJlnrCAA+eM3Pz5dNEi93DtEocrozmp+fVXNzRP39PYaLwaBCMjIyb+RxaaHq6Kg3PI9SjufLXe/o0aNm/viYDAwMKJnMK5cLqq2txShgwQFx49QIfOUr1gyRdn58OZDBveYa6UmuVXxNHhe6Zog3HiZwMvAvoSWKrhzUqvhYYKpIOz/iXbUY1W5W8z5Uc8k1ESKAB1TuprenxHvrrVYpllyVLixEsLbUIEiHPmOND6m81AWt8/rDXyOFOxbfKmDjHe+wpUXKigQWBYb/+3+r44KsdyABn//0T9asBzTJC27PK19ZvaLZet+Du56LwAaOgAMgG3hx3NTWLgK0X5HA4wWCTG6lAGClmVFZocrCeZH5pTWKAejAZBAgQssUHBGMjmjNghMSiSwPHGi7gjwPhwXwAbkcnkd7e7vjeqy0KLJcVjY0EdEBgNAdgqUAPhxu1DYC5KrwuBGSoh2KKhM5KWbtUCuQIaZTCVEjKiNvfvPqrk/r1YMP2nMAACoRnmKu2KkgaIX3Ct6BiFiVq2ZMjk0LGMUSKmfMhffTxrelBqaH+98izT0gtV0kJYakTEw651qp+zGn3ioqVf/2b3bxKXHRwlYVKec0RJFFxZiHB4kWMlQk4AOhduDIYadhQdwlt1oEHADZaivq7qesCJDEAxAAIBgF4texmgGwoKrBwIUcCVzOzwAcQBYvHBwPOIHvgX8HzqsAkba2egNKSg1Ajefr4RSuqlst5HCRamVnmvYfEuIXveikoE51Z3XvKhUBqgKACjaQEY5iAxw6BfK4tGV5tiVIDNMu9apXVR9HWudwm8eInMFGO8k/7V7lDCo07363lTum0wrhJc7xxjeWl2sCarGjeNjujJqCSf30rnr92qN9woRyS41swgIQ5H9bHyEhE8zfznNeKXUuITdGbyjVBPriaiUrtx5BBXCgTgEixcUeV3t6+t761tpxfNbjPtw1XAQ2aAQcANmgC+OmtbYRAHgAEEjoIaEXqlQtdeVsNqdoFPNB+tkDBmgwABPj4zHNzaXM962tYTU2+sz5+R0ABC+OUmNyMq4jR6aNGzntHs3NIfX3tywin3tVDwCI5+tBS5erelT+jNCW/rGPWbUk8iZ241/+8s2VF1V+16fvHbRfff3rVkSKeOPoDjDA2gEQAgiEj/wHf2ArItUOqhe0ddHSxeeICgS8kquuKu+MtF69970WFAFA4KzAO3/DG8qTTKb16hPvmlT0wKCa6+Y0kunU5b/fqmvf1lveBDbTUce+Jh2/SYoPWmWujkssAAksFtOo6paOHrVqVywgamNUSwoUBKs6Z7VvQskAA0RKeChVYCz57GeXXxar9rrufS4C2yQCDoBsk4V2t7k4AnA/JicnDQDBB4R2puUGQAL1qunphFGoAij09DQZpapEIm2I5RgBchwE846OsObnZ8z3tEhRsSgetF0dPjytI0dmTkjy7tzZYtzPPfWrRCJh1LoYrupRm6cYsjLcUvIadrlX5ZZdmylturOwqf2//2u5NAAINoZL8SWoMH3zm5YYTmsSLfSQzskv2WCGL0GeCWl7NYPqxw032NY6Bjnj858v/dEflXdWNrnf8x7bksfzwPx+4zek172uvFau9Mik/uXqH+i/93cqEwjrwvr79fJnDWvXO/506+2Wo8Y1zuIvkNAhxSMFvNoBSqXlCWTKgwESxO/j8stXe+bq3888aMXijwbyyks96NVfwb3TRWDbRsABkG279Nv7xvHoAICQ3OOE7pHEl4pKJpPT8eOzps0KgJFK4VLerObmsPkZBoKoWjGojnR2hjU3N22+b2lpMYaBxQMwMzjI+zKamIipvT2i887rNt4gruqxvZ/PjXz3JOcf/ag1/QOI0B6PkthTnnL6Zk1F5XOfszYR9jNouT3wMMod0BWo2ODpCAmdCkq5arFD3z+gj/353frV5C6poV6/EfmVXnHJ/6rpza8p/yTlTrSM46gsUUjAG5GuJ4Dfhu9++q//skQa+BX0SEIUonePPrZy1QDKiI07xEXARWBjRMABkI2xDm4W6xwB2pkAIBDRC0niS00jl8trZGROU1MJ06aBfG5vb5NRm6LKAZiYnU0uAI6ImpsDwm2d3wFASjmRz8wkjGQvLV2AkN7eBu3Y0SJX9Vjnh2ETXI7OFPgNCPGgYIrh9ukakMY/8hG7SY3lBe1LF19s88SaSc8uc3NcF44GY+9e23YFKAKAYN3BgPQOt6fS6hafRUAM76uEFvapf5rSjR88ru7MkBLhVuXnY7rmsQ/omf/vqsVEFP54cAFEKdaotYhLEAs8USgqoCB86aVWvKkSYv6iJSAwgIC1BAIoANAfycPtARAm7gDI6fqou+u6CKxpBBwAWdPwupNv1AhAEseMEJ5GKZJ4qXkDEvDxoAULANLSspgsTlWEQVsWFQzMAgEgzc1USppPOSWcEjggsVhaoZDPcEcwMHRcj4361JyeecF9/eQnbdJNgk8LEw7fp0vi9Yc/tBUQCN7IGNMxQxvV299eecJfaUTpRqQt3yObw+F52ctskk3ijdgSg3mtZa5cPO/rrsvrm9eP6zH+nyodz2j//MN09Yvr9HtvO//koUwOY0OY7kwYPgHIrcYD7QvUx1AEA4jx3IB3Xv1q+31FA6k4ykugThAZcmVPf3pl6KzcC6JQQAvW/v0WUVJ+uvLK6pzTy71myT/0Y9LsvVKdX2q70HqduOEi4CJQ8wg4AFLzkLoTboYIYOCHlC0VECoUpTgaq7kPgMfw8LABIFQ/uEapwe9p70qnU5qbmzWHOK7HaiK/9d77z/8s4V8CSZuWJ9rR8S4hf612cA4SU6hPnHcFCtSiyyA1i3M8eSJJPuqqz3iG9Id/uPqkH6Ws226zRQJMs8nPC4GERzb35kurEa1WtICdzgH/5EtfzCszO69ULKOeHQG95NomPeEJC7OigoCi0i23WBTJDe7bJ73mNTX3xKCFDAACzgFw8JUY4v+HD0tFg7YoQBMmggx4GWhWP/7xFZ2m7IOPHZNAuMQHVMt1KilFlX2hJQ6E1/LAx6XogxaAtJ4nnfUnp3qcrPY67v0uAi4CcgDEPQTbMgK4iNMiBQcEgFCKo1FOYKh6UO0IBv2nuJkPDQ0ZAMK5W5dowHZcj3KivL2PwQvtP//TkqLZGGb3nxzwBS+oLi7keIUVlYsuslWEStpzmAPkcioSABi4wqt1MidxftObpDvusAkzfF9UrAq5JVAE4GkUks2JQzV+G/AjkAhmkJijtFrtiEat3QXtaHRWsVaYZp/osgLx4R9BLx03Rm8UP6MvyruZai9e9D4qQUgCgx0AdLST0clEBaQEFW35q/7Lv1iDlF//dZleUYg/ID5cFrfiOPj/pCM3Sg07pVxSwvdk79XSzudsxbt19+QicFoj4ADIaQ2/u/jpikAmk9Ho6KgBIACEUhyNleaGmSAtVHh5WOJ5o2m/8oZXAUGCFyWs4lGK68E8eNXaGHGle3G/txHArgAeAbkWeSIE69M9brrJepeQs5JcsjEMYIALUs2gzR7fCpSnULGimoAM7lOfWs3ZavMez7Tw+usl1E8pGAJCADbYLnhVEOZNCxa7+oAxjvuzP5OuvrqyeeDCTmUJdS4GIArFLKou1Q7uARBFgeOU/QaIK3AZkNniIpSRIFtjflJxX9TKM6SAAAcEkMWfnt/8TduWVvH413+1iA90RjsWbVJY1leLfiuewDq/4b4PWInhzsdIubQ08ytpz4ukPS9c54m4y7kIbP0IOACy9dfY3WGJCGSzWcPRQIYXgFCKo7FU4CCkx2IpDQ9jIJhUc3PEqGJBSkfJyhucnwoHJoTwTLyxVNUDkLKSHLBbzLWLAB4hcBvgXABAyBNXm5TWYra0GeGlQe5KLz9tPbyq5Tj8wz9YhSR26UlUuV9autixP12D2P/pn1ppXxJl5oWEL21mH/jAyS4cQBjVDkAixwCeoCVcd115fh3e/VGtwDcEmgFxpB2NnJo4rNmgt4xeLW6CUgSVDyoJZTL3Pad3OpJweod8v+YDpEfZCaRGoB7+cOlP/sSqD9RqYMrjeX+cc46V7Fojgv6KUz72denIDVJqSkJuuGGXdOZLS7u8r3gyd4CLgIvAchFwAMQ9H9syArRG0SI1NzdnzP2W4miUCg6SuaheoWAF8Ojra5JUZ74WuphTYaHSAgBBaYvhqh4b93GjykBiSgJMYktSSgsQ3IaNMNhhZ1QLPLx7+OxnpS9/2Sb1JLX4q3GPNe4EqihkxPotb7EgC+AB14UcnQIBFQ5v4B2CYzltWnjD0foEKAM88P5y28BoUWJzn+O5HvxwDCkh96/p4EZpw0KUAlfGZcAH1SnWnDlSWaHyg1Sw157GmpXQtlg8faoWJPcY33jotdIyD4CJwHNhqjW1VD+AWwLChFBE6cvz/qhEP7mWCzZyzLZg5Q9JoYjU/Xip/5lSna+WV3HnchFwEeD/sjyZmBsuAtswAoODg8IRnarDUhyN4rBAGB8cnFUslhFVlMnJhKl6dHY2qKurwXBBvAHHBADiuZZTbSlWuHJVj43z4JGYI18KJ4INWHbjaQFa86R0nUMAb4N7pfLhVRAQGzpdm84WmFsn8u98R0LFiY4lWsw+/OHFksM4lKO2hfO4N19Pmviv/srm9OWMb31LeuMbJVqx+B+Q/YHf/V177tUCvHKuv9wxVLygXeB/x7jkEluRuxFqQoPthOJ7ZIavuGKFq33jGxZtUslgsQkQqG5gYLXTrM37WQhcJOkHZBG4aUpz8GXWcyF4CFD7QgoY9DvQK139YunMs2tzn+4sLgIuAqdEwAEQ91Bs2whQAQGA+P3+khyNUoGh/WpoaM5UQHArDwTqDPhobY2cQkJHZQuyOy1XgYWdTk/hajtwPfg//ciRk8ZuG4FPsdzDDuD49Kdt5YPch/liRkf//FYbJLDwXWjjKUFPOi23C1+BxJuvVGVoCWNDvHCQfONBQqscQAXDQColCEq99rXW2b6cgVM6FRPAGFUE2rnIewEgFRO1y7lgBccAwqjEUZWhCgKJnI4nxAOoUvG5QhWXZ/OlL13hxMhh0fqFoR8Bo5oBgei3fquCGa3hodwsAISHsLPTlsAe9zirRrCeAAQ0jgQwQI12Wdj79Dm+/vXrq8K1hqF2p3YR2GgRcABko62Im8+6RQCSOAAEwnchR2OlCcD/wETQ+oGE1dYWLkkapwKC1whVkP7+fsM1oRqyHaoeJEmoJKHeRJJHbkFCSW6xUQdz/t737O46iS452zOfWXaLfkW3RfXMA6ZOcGBx6ABHyymvUh155zvtOlE5gR/NcwVfp1w5YUy2yTe5Fu+nAwh/FfL1Ss0LK1r4Mg6m1Qp+CvcCVx3MANAClAGOeDZpy6ICsiKO+Lu/s7K2lFHo4+IFAEE3eSMMUBYLQU8dvXCQcuh7rFYRAXk22s2QdEP6q1zHzh/8wKJa2sv4Y8V89uyxD8TpRqQbYZ3cHFwE1iACDoCsQVDdKTdHBCCJwwFheByNcmdO5yIJK1WQUgOux5EjR0wFBIJ7T0+P+bpdFK7YraVXH34plQS+R1WKjc0lLFHKDf2aH1crrkWpiWKAifIabX+04wE+qI7x4me8+DdVOTeWjgBJOFUMEnRyTOwiKpERpsvmQx+SACJUGXhGL7/cttyd7oHoFK1nfGagRVAIIAdG/WznTgvOaE9DjApax7KDliLITfSacbDXgkXL00YZLOKPfmTLUMiRIflbTfXjxz8+afTIvcJXufbaxSW+HAH1n3r+u+6yDwRBB4Cg9sVDRV/fevqQbJQ1cfNwEViHCDgAsg5BdpfYmBGgQgEvg93orhoRK53ClV1rOKv4V5BHsMNM7z7A4w1vWJ3fwsZ8klaeFYCVZ21+ft6A0qmpKQNGfT7fKS/Oxs+LQQngxFVLVo51uUdQmWPjGyI7zyhqWhsh16T753Wvs9U4r/2KVjmwA14e/Ltsp3fQNL2FXlWAUlE5/A+C8tWvWjt12qMotQAOVjNyWWnke9L0nZIvIHU/TuqooRP8O95hF5R+PCo9lMeQTKOaEh+x6lbzR6VIl7TzSqml4H6IE1wZCPugU8pNSKKt9p5XEy/3XheBLR4BB0C2+AK721s6AnA02I2mRaq7KpH8xecuVrgiYdxOVY/CaMAveNe7bCcD+QvJHi1NbCie7haX9f5M8HwBOFKplKiAAHhpxUN9DTDC73kxABi8ioGJBzyojBRWSryKyXrf03a9HtUSclzoFPAy2CQvt+2rkphBhfjHf7SCWeyNAIzAACjgrvkgGYeXAT9joUJsSi5Yqa+mcjL0nQUQcNioBlqX8T+2X2sxIPVAYqf1anrakolMu9lvSvf+kzT2Q0l+KZeywOe8v5BCJ+XRTUkbVS7AFyWxFSXGajFpdw4Xge0bAQdAtu/ab/s7h58BACExpEWq2uGqHqUjRxIFqRjwQRKFgTI2AisNOiluucUqIdFFQWvMungerDSxKn5PxYPKBwCD5wwgAQcIAFI4qJB4QARQwgugwosBIGEAQPi3B1I8wOJVSwqrJt57qpj2pn8LJG1atFCUwuWcTfDVVjd4HjEv5LyYmLNngUABrVDVdAytFOT//m9rJkhnEr4fcD4W1LxXeuvqfk8CTjJP9YPgQUIBiKzWtf2e66Shb0odvy5l41L0gLT3GumMq1Y3X+/dtJrhVEn7FOP88+2cd9RLd/69lByXWs6VYketx8e5r5HaH1Gba7uzuAi4CFQcAQdAKg6Ze8NWicDk5KQBIFQuemF5VjFc1WP5oJE8AUDo01+xX10Srdj/8i+2Y4SkDlz43OdKz3lOFYtzGt8CKJ2enjY8Dw9Q4AeD3HMlwIDzeFWSwmqJp55eCEYKqyYeaClVLdnqbVxU3fDOwzODTW24xEjsVstr9h4j+M20FZKLY6VBm+HevdKb32xpA2sx4GXzYjN+LUBOyTlzQWRwYebTzkQlgQ8vyTxk9nIHbpEeCmQnoW+/NHiz1HqBlJmXkqPSmS+Rdtbow828kR2++25LmsHQEACVmpHufJs0e6/UdLYUOyJFeqVzX7u4Davc+3LHuQi4CNQkAg6A1CSM7iSbMQIkiLTGkCT20fNbwXBVjwqCVcGhtGFjEAfhFs8D2tfJI2jd2iyDNiueKyoa/BuwAPBABa1Wo1S1pNw2rlLVkq1Eev/CF6zPCapW5M08Q/jaFRoaVrMOHq+JohSgBrBMGxbCClXuX5Q/DUAAig4w7UnmK2HcF19loaq2rPEL/hxwQGhJIpn/tV+zVvXlXhe0xk4C8rZIjVHCee6jpM57pOiDUl1Aaj1fOudaqb6GrupLRfT4N6TjN0nJMSnYKvU8Qdp7tTMYLP8JdEe6CNQ8Ag6A1Dyk7oSbJQJUPwAhSPECQMrdGabqQVsNiSW+HtuZ61HrtWYDEy8OZEbZ9SV/oQVrtcljredZ6nzFRHMqFiT7SDyvR4LvtXF5FRcPpACWGctVS3j2S1VLKqnWrEWMaXuirZ8qGtxpcu+VKgEY9l1/veURg/nYEEfdarX8Cfgf73+/BTRU9uA2AY7/+I9X3961bOwo6XzmM1ahCUR18cVWc7hSQAvw4ANGVYKB2hTIrJTiGqUjKhgY+fBhxICEHYElBmq6tIzRvYV3yxNH/0OBf79eOuccC1roieOD/NKnSzN3WxJ656XrAz6YM/czc5cUH7K8j/ZHST6nNLcWn1l3TheBciPgAEi5kXLHbbkIACLYqQaA0IK1UrJFIodsbywWMwTi7eTrsV6LjwIQEqQkjfTvs9P8kpfYxHMjj1JEc1SuECEoNVKprBKJjJFxbmwMrZhUe+cgj/rhD/368Y99xg/iooty+s3fzGrB57Lktbw2rsJWLrglAJZC0jv/LuSYcDKP9F7ILeFn5YL11awZvHw8MciXaXuiyvDsZ1tvluUGxQIsHdiEJ0Zsvv/BH5Tvkr7cuaEX4G2DyBI8Zeay5lxlTE/I7un74sKw3gEgl11WWXg5x2c/q8MHM/qv8YsUbezR3sv36Rmvf2RZ7ZFLXQw+zAc+YD0EAWkAxcs7f6znPfCPNkgAJUAUfZSveEVlc3ZHuwi4CGzZCDgAsmWX1t3YShEATABA+AoJfbldalf1WCmatfs9ClDtDtoAACAASURBVEP4MwBAcLYmgdzIo1yiuXcPgI+xsXlFo1RIfOroqFd7e6SsW/z5z3367GeDOnQItSxagPJ63vMyeupTLVm9kgFoKq6WeKT35dS41su7hBan973PChohk0s1DErCW9+6sjccnUM8QwAQ/Gc2rZoqiPOv/9om8LRBUQpCGgt52WVcCAHwxIuCCaJQRuTvk5/U+PXf1PvS1+qXwzuUnoqq9+wW/farzzYCEdUORCPYNAAXAT5++UvpvJ2zenvLexQ5sN8uAuAJWVuqN264CLgIuAighZf32IwuHC4C2ywCVD4AIFRCkOFll7d4uKrHxnkoyGNILBlsrJ5urz6PaA44ReGKZH4pojl55NwcErx5xeNpzc2lFIn4lUhk1dgYVH9/85KmltxvMmkrFl/9akQ33BDQBRfkTNXjZz/z6fLLs3r5y9M1WSjuyQMmhV8rIb0Xc0yqrZYAINhZJ4kmsQWQsO7wo9dFDaomEa3BSehJvPlmi8ghWoOmqCSAzksMWtbgwOA9iNgaoA3+eNd/fV63fvhX+sjQ76g5mFRf9rh+0XiZzn3aTmGYXo5IRKnrUaECgNBpxfoAQJja219+VJH9P7FuipiYoEol+y2f3UWtdHxAqO7wIfd0h2sQOncKFwEXgY0bAQdANu7auJmtcQRopfKUsDo7O0+RRnVVjzVegApOT2sHbfAQgRnsatOatUxbegVnr/zQSonm09MJTUzEDOCoq8sbXi7Vj1wubyogfX1NS05iagrOUcIAkFtvbdHNNzeqqyuvUCivQ4d8uuKKjF76UusjslaDykgpNS6ut5J3SSmn91Jgv3jutONdd53085/bhJUddjgXJNOrldRdqzjV8ryo4KLkFc7M65IH/0OtR++0Wf4znrFs+9V732vle8n5KZjwogXtmRcN6X/eeJM+8r1z5a/LqX+gTreHHq1H/nq93va26v1MqFABFFknuDFeaxrKY4WDzzCy3HyG+dw+/enW/NEAqxtusGQfAAiI6eqrLfek0kHQ4MrgekoATvcuRaXzd8e7CGyjCDgAso0W293q4gigfgUAgYje0dFheB0MV/XYeE8Kgjz//u82P2Gw+0/byBVXrO9cqyWaDw9HNTkZV3t7vSYnY6bqEQoF5Pf71NYWUTh8khBLPvbd7/r1wAM+BYM5nX32jAYGkmbHeHY2oJtv7tDBgwHlcnXauzerl7wko7POyq9LIABOzINXrbxLPDNFvhbzsNhN//rXram1EVJ67vaofsD/BnDDAaeKAeC+9mUJtXYFV0yqMQTH0BuOOdwZKiEAED4rcw9N6IN/P6Nf3t+kWLBNO88MmZ/DD1/NGB62zu0eCR3J42KDxn/7N7uWABGecfjpppAzdIuVvqP3kjeBLp//fPuqZPzwhxbh4FsCeMElEiDjQEglUXTHugisWwQcAFm3ULsLbbQIUOEAgNCGhVIR7TOu6rHRVsnOB2NmNkkR42HQ9vGCF9hW+PUalRLNC+dFFQPeRzqdU319QN3dDWputoC3eNx0k1833RTQ0FAd8j0644y4rrpqVn19WYXDPgUCLbrvvpCpopx/fk4DA2sPPkgsv/a1gO69t86QruGcXHyxVdcqHst5l3jVklJu75wHAAIQ8fuD+va3w/qf/wkom/XpnHPq9OIXS62t67Xap/c6+I1QxcC4kwoGAAxTb4wPVxok+chZUwggl0eOmETf48GQ55OrAwQQeQCorEdFCbliACVUFojrgCvu6benPyeBTi66yO4s8OGuVDeZAFHG4QLwTejVhPiCfB4VleIBYkLODJk1AgTCc8NFwEVgXSPgAMi6httdbCNFgDYa3NABIC0tLab33SlcbaQVOjkXEioqIF6iRPJNBeTKK9dnvpUSzU9NyvOamUkqnQZE+NXaujTp/O//Pqif/cyvSy7BzJBELa/nPGdWj398Ui0tkbIJ6+VGhvZ72p3y+Tp1duZLJqOf+1xA//mffsXjdQviADn98R+ntXdv+eCnEu+SO+6I6POfb9LwsM90HTG3Zz0rq6uvzp2QC14PaeNyY1jr497+dulHPzpZxTh0SPrDP7QqYCsNOBbYeEBEp6j7hCfY3P50j3e9y1ZJAEKAIAYbCE+KfcPqJjMo9/DQP+95lrRe7uCEqBMAPAAcAAwQFv16IKzCQYXkQx86KbWHmyQ287D13XARcBFYtwg4ALJuoXYX2mgRoKd9bGxMI/yHJNqrI87XY6Mt0sJ8aCX55CdtzsAgx6CtZK0lUNnNp0oGWF2No3klYX33u4P60Y/8uvBCrl1n2lpe9KKknvSkrEKh2noXsAH8xS8GdPvt8FFsReV3fzdjvOe8Qdvb3/5tUPfc4zeyv+SHIyN1hnfylKdUrr5VGAvauEpxS771rXrdeGOL9u5NG77A/v1hXXxxSq95TfREm9ZG9S6pZK2XOpZOIkA3vGzWhUoIPoBL8M5rcck1P8evfmVxBiJeACNMyvFmadS81VtG6YuHDRdSkElPj5kTvHsKI0t1UvG2W3+QU/Lb/63zR/5bT91xt/yJeVvVeO1rrVtk4YDQ/6lPWft6uCI4vqMo9prXrHkM3AVcBFwETkbAARD3NGzbCLAje+TIER09elRtbW3yiOi0Y9EG4sbGigB944cP2znt3l09abbcu/KI5uPj40YpjR13ng2qZR5vYS124W+91acvfzmgI0d8JlHbty9rqg1rofz0ve/59fnPBzQ7iwcIMc3ryiszes5zTgILKiT/+I9B/fjHfp19dk4TE/bYP/iDtB772NJtWOXGeKnjbrmFZDWoZDKnSCSrkRGfnvzkqF74wpmKvEt8PuYd0oMP+tTQUKcnPtFK+m70QdL9ta/Z3Bgbjac8RfqN39jos155fnx+H3jAcukf9agCEQmQML/wjFsaGw3Q/fzn7Y8Bob/926fGgN995CNWIS2fTOqMxP26qv82/dYjh6zvSKnSD4QylMXoP4MrQivW054mvf71K9+AO8JFwEWgZhFwAKRmoXQn2mwRYHcbKd7R0VEjwQsAwTyuWtnQzXb/br6lI8CuPN4wc3NRRaMZTU4OGolcgEexehOchVIqT6t5hkj49+/36eBBAEhel16atT4OazBorfqP/wgYPgftbT/5SWlZX/xHkP8dHKQlKq9HPjKnP/xDW51Yi0FL/2c+E9D+/X7T8nXGGTldfXVaAwMre5d4Romszfe+16BvfSuiwUG/wuE6U1W69tqc+vsDZt3WAkDWMh48Cys5v9fyehvpXB//uDV9BJMAyKgCvepVluLhjVOxRF5PfUJaf/nXgaWJLfffb50qKadSXsK6nZavQodLEA3AhIvjgkp71nZdiI30ULi5bKkIOACypZbT3Uw1EaASQtLpqh7VRG9rvccjmh8+nNGNNwY1MgJfI6tnPzulPXuShidUzigEJZ4vRrnJLtK8mBUCYgrVscq5bqXHfOMbfn3hCwEDPij6zc3VmQrIC15w6n0++GCdkf2tr8+bVqy1Ah/ePQA8UAIj+dyzJ6e2ttJ3t5R3CZ4r739/h+66K6ILL0xpasqv2Vm/rr46pssus74pHum9Vt4llcbfHW8jEItZ/jjAE44IXVNvfKOVIaZSQisanbIvfzkCCCejdtNNtpiBdQjtmGV3U3HgrbdaZIM/CRUQr8cLB8ePfUy65x4LUJgQalpboQTlHjgXgQ0UAQdANtBiuKm4CLgInL4IeETzWCyjj360Qb/4BZwg2oB8uuiirP7sz9Jqa8uXNOojCV5pkOwCQgC6hdKzhdUSkubx8Zjm51Py++uMRO9yhPWVrrnS7+HWfOYz8DssB+Sss3K65pq0Seg2+4Dw//a3w2/xa9++pMbH60yr2e/+7owe+9iEAXisSeHLW4tyvEuoTmA7MTZmBZeQCa5kk5x4s9GOIhRGi3QEbbcBvwmQAecFVSxAJy1yKJ5R3UAQi4oHMaYVDc5IIQ7w+OTEkfd6fPJi3vlScQV/4OROuxegB4Uu3w2ft6pcGJqw4UDFBMULSDinYxAYJslcAEuQZyp50E7HnN01XQTKiIADIGUEyR3iIuAisHUjUOxofvRoTh//eLfi8YjOPjuvY8fqRLL5ylemtW/f8tKzhYRqzPs8B3GiB6jA0Zx2rqamkDEiZHitQICSZDKviYmk+RkJdHNzSDt2LO+SvtzKAGhmZnBqzxr531JghiTs0KE64ytCpWGtKxvr+SSh3HXzzQEdPUo1CV5yVn/0R3G1tKQWAUkPQAJGCoGJ929PPthKBPuNael3vxvSt78d0PR0ndrbLUehsItnufsEfHzuc1YOFxAI3/qqq6x1xXYZ8EGoXtDpBJcD0Eu14+BBy3l53OOkd75TOn5cRhSB+MIpL3ZsHxparKiL/2A5g3weee/bbrMgkDWAi/7c9Bek97/fuipyEL+88koNvv59Zq4eDiil7lvOdSs6Bi1lj+TChUFjL3yhq8ZUFER38EaNgAMgG3Vl3LxcBFwE1iwCAANARTpNa86USUYhnduft+qDH2zVffdh9AcA8am/P6dXvaoy2VnO5TmIR6NxDQ7OaGYmbpzQ29sjxgG9mCsSi6U0Ohozc5N86uxs0sBAm0IhWzWplFtCNWViIq5sFjJ3QD09jeZrNJoy16DCQ5tXIpExr2DQp8bG0JrFfb1PTKJ/220+Q0JnB/1xj8uqv/9U6eBi7xKApAcgC71L+Bm8sVSqXZ/4RJcOHfJr5868BgcDBqy+7nX4slh+yXJrRXcPOS47+Gy0U0mBL/2Wt9id/u0w3vc+63UC/xw6BiAOnx8AxcUX24oQVRCUdYnJk58s/fmf2+9p2eL3C0JZVYWLNbjuOlv9QNSC7+GZvPnyX6jt9S+3JRnQjt+vwUddro/seZfuPtxoAAjVLqo0l1xS4aWRAivklmAFv1w1gwBg0shDAgrDoRIk9upXV3hhd7iLwMaLgAMgG29N3IxcBFwE1jAC8XhaExMxTU+jqJRWY6PfABCSRtTQ+Pqd7/iN7wVtO5jfXXZZVlddlam682FuLqnBwahxQOff5DXd3fXKZi2p2kt24X9MTycEELHE94iplniD3fdivkIxMb4wdIODc8Z/pLU1rNnZpHp7m0w1hGtwLX7e1BTU9HRSsVjayPx2dtbXtO0LYBOP29hhvkhr2WYZhd4lKKFNT0+b9RocbNAXv3imMhmfdu3K6tgxgByGf1GdeaatknnrVNhu5/GAfvpT6YMftIk1rT8kv7290t/8jVWH3eoD8PvXf21b0OCA43kCsABU0EZFBQRQQpUEDjjSvbRY8XtAG8UJ2tYAAdVWIsACgCCeS+bA9ViDN7/4IfW89y/thCjLZLP6auLp+le9RL0PazY4AOlf3OPxOSx7cAGY9XwlAMgN4z9CqWepceON9EjaoHDhn/zElmkoBbnhIrDJI+AAyCZfQDd9FwEXgfIjQFXi8OFJHTo0ZJL/QCCvzs6wurraFymgkR8cOFCn0VGf4X3QerUat2iS8NHRec3NpUzrFUl+V9diCSmSXa+FKxZLmvlRLfEGO+peS1fxv0txFmgnwoF9cjKmVIrWKgBWxICPTCavQKBOmYytjMzOptTSEjJghcpMX19T+UFd5kjAjnffAKqOjoi6uwtMRmpylbU9CTGfmZlRnKwXb/p8XslkSJ/6VJduvz2g+nqqIrR3JfR//g+mpnUl+SW811NNm5wM6SMfiRhvlaYmn1KpOl12mfQXf7G038Xa3uX6n/3DH7YqV5DHARoQ0LHugGT+9KdL7343n0ELQB56yHZCeWIJgDQKFMTsDW9YvoiAkNUvfmGJ7HB1qDRxHs6H4zw5PQNp4Cc9Sbr2xbPyv/udlhVPWWZqSl+qv1qfSbxAZ50XNC2KFDFO4ADKbEyUhwACCyim1EBT+LOftc7rGC7+7GdWKhib+qUGvWkodoHUuA6llxe8wCI0N1wENnkEHADZ5Avopu8i4CJQfgRmZ+d0773HNTsbVyCQM4n4OefsVEdHbRLu5WZC5YVKAIl4OZWARCqhZCapulyd/HXI0aZNpcZTbfOSYZJaBhWNaBSlLgsu2toa5PcHjJdGXZ1fjY1UUyIaGYkaYMKAY0IbFqAknbY79wCjYnBUfoQXHwnvhSpMOMw8rAt8f3/zCf5Lteddr/dRmcKIkph7LVXIMTc0NBiAeuONAWMW2d6Of0pKe/emThhW8p7iNq5Cwvvdd4eF4SLKYwMDeT3/+Rnt2rVYpGC97vN0XAezcrqLABck/xQCrrjC5uaM//gPC1A4DrsOVNDGx6WdOy0uAB/QMvX3f7+0JxAbCf/+79aBnVYrgAvg5rnPtaAFEIOSFuelCgIe4NwGsTABUEp7u+679MX651sefkIYi0oMOOBpT87aC1DCwXmdchYcDYjixeOGGyy5nTdTLqMEc+WVllm/3KBiwvk98gmoazW7Iadjsd01XQRKRMABEPdYuAi4CGz5CBQSzUdGZjU+PqdgMKy+vk719jQq6F+QnfVHNkQsYsmYxufHlUgnFAlG1NnYqcbwycpBYWuQ18I1OTmvycm4ksmMqWpQyaCFywMqfCWJzmbrlEhAhqci0qCWlgZTAQEgwQFpb6+vGUAorPyQM3HuWlVX1nqhEomEqXx4BHWvRa9QrpucEBI5u/i4dRePQh5QIYAEmDBYC1TWmptRSDupyuXxTorb7bi2BzjX+v7X4/zwP2ipAoDQ7VRIhyBEKOXCw6YNsq/PAhZI6nQj8V7AxLXXLj1TKitUUjgHxQMEreBx0/5Vkj9CleGb37QXpuJ1zjkWULS1GfoFhHWuS6WGIoTvzv3Shz5kZbo4IYgGma43venUUtahQ7aagcyvlZyTXvISy7x3w0VgG0bAAZBtuOjull0EtlMEPEdzj2hOpSAQiCgcrld92KdgflrKzEl1WIG3SCG2QG1FgcoASTQJPe1LVC+qHbQ7eeRvuCDwLZYaE9EJDc8Oq7W+VTPxGfW19KmzaXlywNjYvI4dm1Jra0hjY3Pq6AiruTmwSInL28UvVOdiDnATiiWCVyJSlxsHqiDz82n5/STaoWXvu5xzcj5a2SxHJmzWptYDvgeyzN4Ih8OGH1Sr5H8p7xJvXYrVuLzKCfMp9i7xOCaVChTUOmZrfT6qGbfcYonrYAMKCXBAlpOMRuIXAAJQ5Hg6mqim0LYF8fyUAcIA5UA6wReEsguljmc/u/TtIWOGShWlFSYCOYQTv+1t9kLFAxBCz5dncAiSWe2g9Wt01KK07UAgWm283Ps3TAQcANkwS+Em4iLgIlDLCHiO5qgWsfvMq5Bobq6ViUmJIQmqRS4jBRuk+n4DRgAf8BcAIiS7cBdQr6pmkDxxLs7JvEicUaTypHiLzzkVm9LozKgE3slLPa09am+wwGipgdwuqlcWMAXV3d1gWr3S6YxyuZP8Eq96UnyeQl4Jv+P7QtK7l+iWa6hYTZxWeg9tXLSQAUKIKaCQispqgGHhNQEGqKKlUilz/6xVc3Oz4Qetx/BU0wqrJZ75pVcVWY13yXrcw1pfA/ABX4R8e6VOJHJzeB7YaFChovBAq1cpOV8zb7SRaZOihQpnToxInvWspdnmyJchZwYHpKXFynNBJOEC6+HVQTWF+QJAeEZhxjt+yFo/gu78NYqAAyA1CqQ7jYuAi8DGiYDnaE4iSQWExI4kkteineJsXIoPWfCRz0rBZql+hwEgyNcOD8+ZtqGpqbj6+poNebyaARl7aGjO8DNotcGfo7+/SfX1wZKny+aympyfNByQcCCsjsYO+X1LV0w4CQn57OxJgnkwaEEUErxNTeFF4InE2iO9Fya75RoqllLiWo8deNrEUBMjhlSUaBnDJ2W5alK568WzgsqV1x5Fot/e3m48P07nKFyrQqGCpbxLCqslrEmhCpe3brWq5JzOuJR7bbqiMDqESwJ/5HnPs6q2JQeytxDF6fEKhzX4QExfH/gTjZz1OKO6BUfklIrLD34gfeMbFnxwAcoycEEWPpOAIH9sTg2//JElqlMhwfFwtQCFXrB3vMNWVJgURBZaxgA/EFrccBHY4BFwAGSDL5CbnouAi0BlEfAczUnWvJ1s2me8RJLElR3zE7vmycmFFiyfFGyzIETkCikj1wtxPBLxq6urcZEkbiWzoopy5Mi0hoejxt+jr69BAwOtJoFebuTyOfnqlj9mqfcDeCCb0/rEdXp7Gxd5fABYSG4LqwfeDnxhouvtwK90v4VKXF6iW+tqCcCNCggtWORvVECoTPFvYkz1h/uptC2LKtkcZI6FQdIO+Kj1/FeKYSW/97xLSplfFnqXADa4D89UkWuUqmzVquWukntYz2OpfqxUMUHxyvA07rlHsaRf1429SP/je5xy4QZTEIH/jQUH/140AB+8aNlaIANRqYF3/qufp+Xff7sek/mBntP+Q/kH+iySKde1cqkgwTuh1Yuv555rDVS4KNrAABw3XAQ2eAQcANngC+Sm5yLgIlBeBIodzUnMIpGIWltbTd88Kk8AgEQC74+QqQicqEDkUhKJft1iPgHeGFQv2GFHLaraQeJ8+DAAZM4kgrQN7dnTvupN0KXmQzKO+hTcC5SncFXnmrRkMWhhQnKX4/AZIZFfaqy0A79cTLzkl4S+cCd+NdUS1oN1AXRQ2aEawn2MjcWMChjft7bWl9Uux71R9YBw7o3GxkahdLVZRyF49MCJV9Upp42reK02MghbkzUCiN5xh+59MKT3/OcFSvsjxoaDLivaviCwo7a70vjKV6yQVvTYlLIHH1JfZFrXXHqfnjD9NastDHhYTXUtmbQSYJjKwNCnDQuGPRUQCC9uuAhs8Ag4ALLBF8hNz0XARWDlCNBmNTY2JsjDABES387OTpFMMqh6AACoQjAaGsLatavFSMKuxyhsHQKMIJO7XOtQavyIcqm4wl27VReqjndC9WN6Om7uHZBBpQDOCdcHCGFMSJzCYSoyzRVXDQp34AsT3WKCe6n4etWSQrO+1SS6ACpbXbKtWXie9Pe3LGt66LXpFXIsqJQBWrfaYE0KKyWeclo5bVyed0khgOTfqwGRmyG+8MUhsKPShYIWAIS8HgCylNVH4X194ANW4vcxA0eU+ckvdPvcw/TCX7tPL8pebxWw3v52/hCtLhR33ml5K1RB4IBgTvKMZ6zunO7dLgLrFAEHQNYp0O4yLgIuArWPQCHRHMlUPBtIatnBLkxykZ196CEqAhnl87alCQAwMNBsqgJLkcFrNWN27b3WIc65HHk6eu8PNXvfj5WLxxXp2632R18pf2N1O/IAHwAHLUnePVIJoj2LdiV+RgyJhVfhmU/Oixeck+ZIs0KB8jkQxbKzXqLr7cAvF08S2lKys+Ukutzn0BBiAznDecHhnXtaipyOqSDPiweWuC4tV8u5ytfqWdhI52FdSnGBmONK1ZJi1TQPoGyk+6t0Lohf8aIARlfT9ddL3/++9RCBZoFJ4u/9Xnn0jU9/2nJPelviSu6/T8mxWV2947u64twDFihcc015J1rpJpgcKMnTKl7pePd7F4ENEgEHQDbIQrhpuAi4CFQWgWKiOa00JE1UPYqTVvgc7PrjkxGNooblV09PqzEg7OxsUn8/bVrVS+wumjntXNmk5AtI/pOkddqGmAetQ4CeUjyFfCqh4e9+XLEjBxRoalU+l1X3Y65Q41mPqSw4KxxNHKiQkIBTHUGRi/vHd2R0blRziTnDPUF5q7eld9W73V61pDDZ9Uz6CqdarMTF75biKxTfIvczN2dbsAB4tNkVD+6XKlmMfv2FUV9fb9r0ygE6NV2EDXoyr+WueK2K27gKeSWebPBSIHIzkN5xN//CF2wuTzHh8Y+3CrxwvCcmbNXj0kvLd6o/flz6+MclhLJ883M6P3+n/viR/6vW8wesWtVqqx8b9Plx03IRKDcCDoCUGyl3nIuAi8CGicBSRHN2sBe3miSUnZ9QLpvS5Exec8l6wx+AE4G6FdWBYLBOPT1Npi2reAe+4ragXFJKjFl5X39ICnVYb5EyBwBk5Luf0Pzhe+VvbDYyvN2/UXsAAgGdqgHcCXgwJO0MKh9DM0Om6pFMJxUOhtXf2q+Av/ZeG1yv1O57YbWkEJAU/pu5Y6TImuHw7u2+QzS28sGngslCV3OuzXGeq3mZy7OtDyv0LilUTtsK3iUISkHJ+PnPZfge8LnxFYTPvW9f9ctOcYLWLSxFzjvPYY7qI+neuRUj4ADIVlxVd08uAls0AisRzU+57cS4lBxXJpNWOutTTK1KZoIaGYEDYYnHLS0ho3BVqg3L638v5CosqxaUmpbiw1KgQcrMS6FW6yuC3C8yv76QfS0z5u+/TbP3/I+yybjqe/eq/deukK9hLbkqeSkTN+0gqVydRqPjmovPGX4I8r/dzd3r+jStlOhCnrfclrzhenR0YCppBQK8aknxesERokJGssyL42i5KnQ1X9eb3EIXW613STG3pGLQX4NYAhTe+laJqgWAgyoIXPRXvtIam7vhIuAiUPsIOABS+5i6M7oIuAisQQS8JJLdV/5tDf1a1FDUypDJZkwLERK29ZkpNdSlbRUiPSfV90mhtgUVKDwyMqqv9xnlTI+vUAmJOqusgoGgGusBMJxkTkqMWLCRz0nhLskfkVKTti0LYOL9bJkYpacGlUvHFWofUF2wVqTovJ0fc6M1jHnhckjFJjVlFcBC7UrUNSieiZsKQb2/0XBB1pojU87j4hkoHjkypcnJeWwazDpiuIixo1chKXZ7p1qGyhWJLsktXjBdXV3bju9RToxrdcxKymnLOb0Xe5d4AGUt27ionGFYCN/DPle2YoGgFNYeW2kgnoUdCZSRBcXgrXR77l42UQQcANlEi+Wm6iKwHSNQytHc28EuRRoemxvTZHRSmXxGLb6cusM+RTDxw+U83LOQeJeOZKn+dxLfYoM+I98an1Y0EVVeeTWFmtTVQlLrVzA/r2BdWoFQWIGGlUN+OQAAIABJREFUHtWlp6TEpBRssq1ZCyBo3daStjBGKioxlxyArEkKd0u5rDRzj5SLGwUpRXqkpj2mSoNKFi/rBh5eVqq37HsB/AB6iuSOy36/EPyZNyaRDNTEOjrCCodRvzrp9s6cWTOI5njB8D2JLeDDU0bjGSomUm91L4xK4rwWx25k7xLarhCUOnbMckCuuEJ69KPXIgqn75y0mH35yxiWWk7Li17kFHtP32q4KzsA4p4BFwEXgQ0bgVKO5iSQzc3Np5KG81nl8tLgzJDhMjSGGzWfiKq/qUXN4QYLPMyu/8IgEYcRXkYyXCw5G0vENDg5qFQ2ZRNhf0C9zb2GM2EGib3Pmr/5M9MKZGcUDIUUDIYUbB6QL9y2PjE3Jouz1iY9Pb9Q5QAIzVvH92xCmr7LgpJ8SqrfKbXtUzrrN6R9fES4B4wYkerFU8QbKE5lMlnhuF5WhSQTlWhRU07yN0vh9qpigKIYDu/weBoarIdJsak0KlfIMlMp4xkCgPDceGaUfI8gAOpogBiI+NyH5Y9wPwFTMfFe5e6+w6mpmZhBVdHZnG+q1rvEI70Xt9xV28ZFJYTqQH19CbPBzRlao+A1M4NRp/SRj0go96LyxX0+5jHS61+/OjuSTRoWN+0NEAEHQDbAIrgpuAi4CJwaAZSK2MFeytH8xDvYVSfRziXMzv1YMqvJ+JyyuayaIk3qaepRpNhLY5H7eWtFRHGum86mNTg9qGgsauYXUMDwJXx53ynVEgFSMtNSNmMBUKhNPj+yuIuTXE9VqGbPAuAiMSxzfaoO6ahV5qoLnqwG0RY294CUz0iZhNS4U2o527Q2DQ/PG0lbEmpI3cjaespdSPjiEk8CDzjp7GxY3keENYoP2RYwDB/hwQCACgFhjW6clitczb1WOs/VHBDhJbpzc3ENDk4b40KOw5QSEIKKFlitqSlowI03SnlhFFZLAB4oixEXgExHR/2KLvc1ut0texrPu6TY6b1S75JaGWBuxkD/4AfS179u+SzZrLULgVzf3y/dd5/U2Sm9+c0LvibDw9LBgxZ9XXCBQyWbccE32ZwdANlkC+am6yKw1SNQMdE8PSPFR2xY8lllQx2azYeUzyQU8eXVEG6UAk1S3cLuPYk5ybDZ9c9KwWbbFlVGJaQw9rRgzcZnLRelvsVI1jJKeiuk07b9iq16X/hEdcRMmYx3QZWplLdCubvvpzwXxQCE+/c3SD6f/Qovhvas5LiUmjHzyod7NDHr1/x8UnNztrpTXx86QdT3Kg20QOFrgncIqmK4rJN0LzkAOPHBBbI7IEhSsH2hKhU+uTareLiXcjUvVS2jtQzfkMbGoBEjCARyZh2mpgBdaUUiPiNMEAqdrPiUmprnNZNI5DQxkZDPh0Gfz/BSurpWaTK3ilhs5bd6pPfCqkmhmSRVET4zhS+PF7QVvUuWWmsI9e95j3TvvdbD5MgRCfVpAAhO7ocPS498pPSWt0j1D96l29/zXzr8YFZNDTk95unNarz2pZYQ44aLwBpFwAGQNQqsO62LgItA5REol2i+6MwQqI3yVJOUnpUi3VK4Q0qMSqlZm/SH2iy/gcwXRSoDQHILAKTeKlVVCECYA5UQRtBvVZiWGvnEpDLxcaVTSaXrIkr7Wo0EcCG3pJg87Z1rKWWnsqKbnLItWGaSLYZkfsoAiOFdUufXfMJnHMUJTTqdUTgcMOCCakBhm9PwweM6/Ku7FGlqUGDHw9S/s91UEZYdzCW90IJFr5wBhDlLzGfNqoi/d71SruZ4e+DxUWpQqYBLYj1hbAsWrV0oa4HPWJuenogh6RYmusVcIO/ctISNjcXU2BhQdDahtgafdp7RpfrW1hOVLuczUtYTW9VBK3mXeCCez1IhAd4zzuzv798yimh33y3dfrv00EPST39qAceOHRaI0IrV18czLXV3S1ddJT32sdK3X/YFfeU7DRr07VJDLqpLeo7qFf+4W/VPfWxV6+He5CJQTgQcACknSu4YFwEXgTWNQKVE80WTYaefXXzjvRGWwp2SfBZkkOTmaH0KWpDhAyig/MTxC+1AwdbSiXmt7ti0H7H7TwVk4fpUXAKNplpCi0mhr4K3m8vll1J28rgKhTwFduNLVksMCZ3KS5H8Lypd6Rkl5hOai0vZOqpEdQtmfj6TkDc3h9Tf37IIfCSnp3T/Vz6v0fsOKuePqOsRj9T5v/PcFasFJpysFesBaIQTAgBhfvW7LAhZGLlMRvGxMeWyWUU6OhRcxrStWldzjAtpmwJY9fQ0aH4+o5kZzBmtNDPeMMV+IsVcINaKNZwZHtfY8QklUhnVJeYVzsbV2Naolp071QDb1xDmbdtdYetdKa4C16c1DDAE58ZzqK/V47idzrOcpDNrhykln6WLLrroBD9oM8dn/37pU5+S7r8fnx9pasryPc4803qbPOpR0u//vpRIWFCCwlc6ldffPPG/9cuDzbrgrKQGJ8MKxuf0itdGdOmra2uAuplj6+Ze+wg4AFL7mLozugi4CFQQgYqI5kudlyTWkMpxH4/YHX3kcOEcMEwFhDYr34IiEsnwgjpUGTwET0Wpgts6eSiJPlwM2pwARhgUAkAKXNILz+v1vheb9BXKA69ULSnsey+lFGaul5xSLjaqkdGopuZ8piUq0twqvx+uRM5UBiB4t7YurmyM3/4TPXjTl+ULh5WYmlbLzl16+NUvU7ilAmI9gGz+uJSdtxyVxl1Wfctfb8wRJ++9V9HB48pnMmro7lbnvn0KRBbPo9DV3ANqkUhEbW1tK7qacw0qPVQuGK2tYcNjSSYz5nsqPgG/lJiYUD6XU7i9Xf5Qaf+W+MSERu+5R9NDI4rNRpVKzKupr1epaFQNfX3q2rdPPpzoSoxSzuHz81lNTiYMAMTnpLu70YGQqj54S78pGo1qfHzcVCD5rOzYscM8N5t9fOIT0he/KF14IRVM6bbbpI4OaWDAVjx+7/ekiy5afJfxmZTe/LT/0f0PSBc1HdRIvkezDX16xZs79fgX7zVckRtvtG7weKS8+MVOvnezPycbZf4OgGyUlXDzcBHYhhEoRTSndSZci95jlJ6ocpD0B1uU94U1HZtWLBVTwBdQe2O7cfxebuApMhWbUiqTUjgQVkdTh3yQqCsdzAWuivHgQAK3cgUoeBnxOKApK58vf4Jr4k1luWpJ8c47SVddckTpuXGz45mOTinY3KuMv1k9PdaU0apfneqAPnnn7Tr0za8oNTurXCqptoefq3Nf+EfyFwGE5QMbk+bYph2V6mmN80sNA0rkmzU+NKWJ/b+SPx1TW2+7MomEeh7xiBOVBM5L1WFqakqJRMq0TFH5gevhSeyutDzJZFZDQ7OGmEuVA0DS33+SZM/7pw4c0Nzx46YK09jTo87zzpMveGqr3fSDD2rizjvV0N+vibvuUi6VUuuZZyo1N6dQb686L7hAmYVKF/Mu9pkpdHjnuqOjkOjT6uhoVCyW08BAm7q7m5xvyUqLWubvAR+IFPCZ4O8MPkL8zdkKLXIf+5j0pS9JF19sSed33SX91m9JT32qbb0CjCwauZzy//oZfeqjCX3rvt2azTRKDfV61NO69Orr9iiRrDMqWf/7vxL+Ie3t0vOeZ13ji5Xnygy/O8xF4EQEHABxD4OLgIvAukegYqJ5DWaIOeHo7KgyuYwxKexq6lrR5Xtqfsq8hw4mEpSelh611VexUwrwgJ9Cfw2kd9MKVv6A6D0+HjM79IACdutpzSmlFOTJzhYCE/5dnPj6s1H5UhMaOzyu+WRYkZ696ujrPQFAlpodVYlj3/uGpg8eMFWQHZdepo4LirZVS7yZtipfofMZHB3EA4iFz698qFtDE35NTkQVP3iv0mPDamuvV0tfl6kiRMh+KNwkkxobm9TkpI1HY2NYZ57Zr0hkeTBZOCUAByT66WmrgkWlxwNeHJdGxveXv1Rybs5WPvJ5dT/iEQq2dRiFMAZVkmDQp7ljxzRxzz3KptPKp9OqI7FtaTHva9m9W41kfgWjuLLltXF5h0xNxY3PCXOEBN/ZWW98WJaSnK1apKD8x29LHMk6o6pHyx5yzIBwjEzxhtkqA6Bw/fW2BYuBmeLLXmYrIiUHpifvfKfmj0zoa7pCBw9k1doZ0G/93eN19pN36gtfkN70JltNQTELIvtZZ0mf/7y0e/dWiZq7j9MVAQdATlfk3XVdBLZpBKoimtcgVjPxGQ1PD6sh0mAMBFvrW9Xf1r/smcdnBw0AaW3s0nR8Rjtadxi53ZUHylZIPTHgnECIpwKSl0ItlhDvqXKtfDKTkOLLgeM36lQrqU55ruGF/BJ2371BMptLpzR94E7NDg4plfUr0rtLveedo8YmJGSDi7gKpXaH4YL4SOQaGpe9g3w2q+lDh5SYmlIgHDbVgRBJHy1zcEFol/PXK+tr1eDwvGKxjHyJOc0cPqLO9pA69wyoBdkeISc6J3awSdIBZJDMm5pajEQwsZmZSRpQAnm+lD9I4URpccLnxHqEhBZ5nGRTKY3u36/Y4KDpNwk3N6tz3wWaTYdOtG3BE+nt5T6ymjl82NxfqKFBzWecYdq2qJYElyDBFweskKtAVQc1rmg0btrhOjoiJ4jT5mnK508YK/L9qkQKynj2tsIhxJeKGZ8Hqh5UP9rb20XL3lYa/Hn5yU8sCZ0KBUaK8D6WHDDV3/lO60x4zjnSAw+ArK05yFlnGTDz1rfac4GjDx2y3JFPf9oq9brhIrCaCDgAsproufe6CLgIlB0Bj2iOQRxJJEkBCUB3d/cyiUDeEpdNpkWy4CX1ZV/2xIGJdELjUXb7503rFS1YrZE2k7CSYBea7Jk3pWc0Hx3UdHRScQUUauhTV1O3GjA1LBxwPKhwsJPPv094kkCIb7c/M6pbGeuBAfEaQvwSHJBSdwZhmh17PDlIMtitX1F1qvBE2YRyuawyOb/SGUt8n5+Y0Mj+/cqwc5/NKtDQYCoNocaTgIJKQDYWM4ChoUDRCYBSrtlbdHBQ43ffLZJ6pWJq271Dneefa93YkSQGoC2sK/cJuMB/BInc9raw5mNZpVIZpVJRUYxgrfAgicd96u3tMIaCABAG7Uu8l7WEOwEoqXbERkY0e/SoARMNPT0K9+00IBAc57WfFLZtpVNU1upM1WK17SmodEGQp+UOl3d8SXK5jFHkKgaShfwkr8rFM5LP+0xViJdHfN+O1RKPY8bfG8AHz24HwgYl2umqfVY27fsobXzgA9Ktt1qNXgAzslivfrWR4EWq95prrIIWrY6E7IlPlN7//hLtXJs2CG7ipysCDoCcrsi767oIbKMIFBLNIX8CQOi9pmefhLKUqlMwGFBdcmJBRrZOCrZZed1VjGQmKV7+Or/qgw0mycN8jsS+pSVyMqk3vhUY580rkUkJsd1gwy5F6ou4G0j6pjBBRGmrwVY1UOQiqSYLpNIRarWEeOMCzn00SZHeU1WplrkvSOHM1WvBam+vL3Ifx2hw1hLrAUIoe3lcFbgnXJt7Qqo43GXmmZyd1fgddyg6OWlASLCtTW3nnmt2/Ely+T38hvTcnFGhatm7V/UFTeQks4W+Cl7VpLhaMnv4sMbuukv1rc2KDx1UU0+zeh9xrgVnC8IAhbdOuxntR7SaAUaGh2c1PT2lUKjOeGs0NUUUDDYoGs2ZeNTXB83P8fZAChc/EmIFOKgIpJWIP21jABDaqZDmBYBQZWGgEIY7PG1YzJlr4gyPbwrzKVbQquSxhSDP+QAzgAoqLR6YWqntDod6256GS73PxCASsS1/rFexF0ahoWIlc9wMx1JtpfJh+UwRA0AAH9sRiC25XpOT0s03SyMjlql++eXWOGRh/PjHFqNw2BlnSK961TItXZvhoXBz3DARcABkwyyFm4iLwNaMwMjIlIaGxpXPswMppVIne7C9Oy5UdTqxo5tNyp8eV8BXZxKpYLhRwZZd8gdP9XbAFDCWiCngD6itoW1FcjnXjcVSOnJkdkHxyaf6+oC6eyMKh4LyU6VIAEDiC87d/oWqRVHLBiCFNiLkdT2TQZS3aLOi5QoAgrwsVRzjgYEea7OR4F1ugF3icesxQoLt7aiTBJdMbAEfyTHrZg4A4Zp4fpjqy+CCC3qhBLDtewcczOOA7POpqb9fzcjlUKPJ5TR+4IBpQ/K3tGhubEzNe/aojQbwUoPrLFSqAuEmBYK2x57kNoej/cGDSowNKRiIm3aqlp0AMGK6Y6EKUvq0DzwwomMHDyuQnFM8kdWefQ/TmefuMUk0VQKAGUk6LyR0aVUj8SZGcGTw94A/sRowYO8rbypw8ThSvScBCK1bjKGhOdOaFQoB3nKmRW411Zfjx2fNs+nN++yzOwToXG54ks7j41FDsEesIBZLGg4JnKHCz1qxoprXxlUo67zZk/T5+Xkjs8szCOeDzY6tQjZf7/8pqPpFoxLF0UIa13rPw11va0XAAZCttZ7ublwENkwESGKHhsZ05MiEZmbmTQtQT0+rzj57wPS2F3pg0BLkOYifSJRySeUTC0k1Pww2SOFu+QIklH75A36FQ2GlcilNxCeUzqSVV16djZ2GLG7aokiMlyB8Dw7O6eDByYWWnYAa2jJqaqfzIGiI5k2+9AJxHLO8ZimCv0hRCxjJPUDDSP+mbbUDSeBM3P4MTxKqDhUMwMf4OMmTJTsjEbuiqzYmf8yF61E1AoAY40WQzJCUnF4ge/ts1aEAAGWRt6mrO0VmdubQIY3fc4/hbWTm59Vx7rlqPvPME74l3pplsxnbdmZMH1mnZinUcbICIyxQYsrH5hX2zau5gzaYkAINHaozDvSnqop5rubHHxrWsV/dqfjwqFrbmnTWo/Zp5yUXLSazF8SWdqzYfErTE1OmYuELhtXW3qTe3uUB35LLc8I8Mb/wDLAzfGobIM8SAKiWAOTgwQnhsI4U7znndJm2u3KG165HGxqVmfb2kNraQifWjc/ZUoaKhecHgHitW4VfN7paVKE881Ylm5fzHLhjXAQ2egQcANnoK+Tm5yKwiSLA7i+70vSrz87OaGoqqiNHJk1PfjDYqLa2JtMag8xrqVHYXmLM+eKTyiSmTTeTSeSDzUqmk4JQjgs5XA5cyCeiE2qsb1Q6l1ZbU5t2t3UoqJjpW7ayt4tbtzwZ1tHRmDF9kz+j5u60WjuDQnoXANLX2iufMraVqtgrxKtokHTT2gSXwXP0ph0LYjXApwKehxcPdvbZUaeVhlhSmcEM8BSOSmEAMfUzYC0mBQA+XcoFms29BHIJ+XBDNxLAjaWBVMG5csQ9gSFfXrMPPWTkZIONjab6YcjjRSMXG1F6+qDhlmTqwkpn/coGO43s8SmDFrFMnPqSYomgAQhNTbTi2d58El2uS9sMbXvxiUkN3X6nGpqa1BQJqb4xop5HParkPLxrxaZGNHRkWPlEVGP3HFJaTeq/9FK19bSZKkLZ1RAAJaDOVED8tgnecHdOJS6jjEXLFGtG5QXAuNQzXs7HmXMdPjyl1tZ60yI4MNCyMghdODHkesuRyZxQ0aKKVjg88F/o8l5ogLncHAslnT1gUi4fqJx7X80xhWRzD3xsRbL5amLk3usisFEi4ADIRlkJNw8XgU0eAfrxR0ejmpiYVjabNLuuVvEqrbq6eoVCkD8jJpGijYXdWdujXsxnKApEnlabrNKZnNnFHZwc1LHJY5qLz6lOdepu7DYtFolUwiSwbZFWtfkTUioqfyAofzCsYPNOBSP069skFwBCPz9JmgFMdUn5W2KGd0AlpSnSZBSySnp+nDAWhFdBbhqUQl227arOb9SQTFtTLqfGHTuMk3clgwTy0KEpQzpnbh0dDTrvvO4VAEjMVj6UlQKtSvnqNRGbMmAtHAyrs562NJLoAqlavEk8oLRQpQFsTD3wgNLRqELNzYb34Sdm4bDqSpnpwYGZPyZFD0v5pBRok5p3KR/uVSaHoWFmkdO7t/MOR2FmJnWCbE6LEG1UPC8oXZ1QdgL8jY4qOzFh+vabdu5U94UXlvTjMDHOZ5WcPqpjB4/pgS/9p6buP2juue38C3XGc56vvl6/OtoxDolYc8rlPF0MABlacLCvk/xhWz1awrgS8AEA5z7gFK1mUMmhChaPZxWJIMXbUFFLFyA2nYaPwvNenm8NwK8QkJgNgEym7GpJOXyg1cRkpfc6svlKEXK/dxHYWBFwAGRjrYebjYvApo3A0NCM7r33qDHJSyQShgw8MIDaTL0SiazhMdCPD7dhZGTeOD0zurrqjWJRqQFI8Xr6rReCNDg1qIPjBw3gIGFtr29XX1Of5X3n8moMhqXk6AJ/I6C6upxJHPMB20Pv+SlEo1mT4EF2b21rUDYQ1Xx6XoG6gFobW5f2+zixM562PIYCVSvamUbvuEPzx4+b6zTs2GES5mIX75UW+cCBCcEDoFUNLsFZZ3UYPkPJwQ4995uKLoChTk1mpOGZYQM+UumU+lr7jOrXiUHFxBD8YydbxYItBnxM3n23gs3NBoR0nH++2h/2sKWnC/cEQ8F0zHJhaFNr3WfJ+IATkvVgy4n3A0CQmaUqFo0m5PfnjdJTdzcchbTo2/cGpGF8GlJ4N4yPG+DYMjCgxgUFI8DkqTwF23J2+LbbdOfnvq5kLKV0LqCmrg51P+23tefCPvV0h+260aIGWb/UgMeDiWU6an9LVcnfXJWBpIkDa0RMaE8rU8mNqkoqhVO3zyiC8W9AAhLDy6lsQcanHQzsxmdm1UT8nAX+xZLOxb4ypcLoVUu8Skkl6mkrfUYKf+9Je/MzRzavJHLuWBeB0xcBB0BOX+zdlV0EtkwEcDQ/eHBIgJBQiKQyq7PO6teOHaea9kHWReUHFSF4DnAcaMsqHgAVZFXxaqD9iEoAyRRu5vcN3afJ+KQBH03hJp3RdYZaIi0mQTO7uPNjSsMLSSWVyYeVL+AkFBLeATckc2bX2u9TTjkFA0E1NTSZaolpLSmU2fUmSbsTCTesE3+zpvMhJeFCzCeVvP+Q6vIW6DAwsPNM9FZccNPaNafB41FNzvlV39xsqiA7dixDakblKjZs1bVImENNmsxGNDw7YiSD46m4elt6F/uXwNlgdx8lKngOqHJFujR1//2auPtuU7VJTk1ZALIU8Zyb4b1z99n2L6oJDWdI8DqiD5r7MMplzQ9blLiTGFN9gqtAjJDW9fuRCU6ZteOFv0c5Hg2FPAWPQO3PJzV99y9052dv0PSxUSXTPoV6B3Tmc5+tXWe3qrWrx6qCQYAv5UgPh8eolkUtVoAvE+61IKTS4YHD9LxtyQt1VgViiNXsLDHKG1BBRaQUCOFZoX2Pz4yVlvYZpa5CR3uO8cj71VZqvM9ZYYWLtq5CieClQuVtAJTjNVNOuIvJ5qjrtbW1bQln83Lu3x3jIrBZI+AAyGZdOTdvF4ENEIFCR/PZ2ZhGR1HfCai7u0Pd3U2LEp8TuXsio7ExCyyCQYBFfcldWg+oeAZzABUSLzgbIzOjiudn1VAfVGtDq3E0hwuyaHjqRb6wsrl8yV1c73iSohM7usbowZLXffmUAvl5Bf15BULNCjb1KBAMq46qBy1MymsmldbY/LRSmZR8ubyCxyalyTnDHWnasUNdF1xwCsG75NIVtHbNzKY0HQ0r7ev4/+2d23NcV3bev77fu3EnAYh3ipIoibp5nPG4ypmJH+w8TVVcyUMe8qfl3Y7jKttJObFdZSfjydiei0YSJZGUSJEESVwbfb/fUt86OFCz2QAaIIgD8Hy7ikWK6O5z9m+fpva31/rWQjKTtAgRT8LHDkYxLOJTd0RAbBbNYAb5Wh7NbhPxcByz6VnEI0MbaIoWNke03iROF/JeOIdupYTC/ftO6d1MBjNvvolYjlGC4caKQ3fBSErlgXOqzxSsCE3wm0DtgeOXoCDKvAVk3SjKwKIurWYbpWoAdatkVbcTfg4KPm4emVLnFiUYPnkf51MwocfmfDu35ZZ0fvJ3/xuFL79Gvx/A/Aef4Pof/QFSEZYqbgOspMa0Ofp2RgcjFvR+IGhNBi3Fzqp1vRiBYhSPgooCuVOroVksWspaYm4OAXpGnhOHO9XRyOUQg6ldFBVMF6RgoIdluP/I8Efxtc+elS3iyNfx9cOvpainv4T3TVEyN7fPc7XzwYzqsamizeeAwX8P3NQtd924jntFS3i/7pxGK3G50ZP9LsnO5jz8oJjhM5PJZOyXhgiIwOknIAFy+tdIdygCp44Ac93r9SZqNZax7VoqFDcZiUQa0Sg7DdN0vveGhTnq/MX89L1Si5gHzwgIX8dUpKmpmJ0AU5jYpi8BzMzHkEkkrfzuYcdw9+ndzVL1KQale04lK57kR+eBbgkIhB0zemIegWhut5cCN0mVdgVb9S3MpeewXd/GTCiDZIPNCQfWwI4G7okGr2kNCymAQmg22uhFzyOWSh+cx289QJo7RnOmCyXQQchM6BRmL/IZOFGAXhPNdhjbVZrvA2Z4zyYDGLSa1pjQUscY6elR3ISc0r7D5nJ6SChkGO3ghp2j9ghorADBtEVjLCUrfdn5WXPLNuUsUlBs9NHqsRmhs3bcQNIwPLb8K8Ver41BIIBuIIlOp4tOu41mpYJup4pgwKnkxYIDgYjDm89jo1hEkJGAnLNm4UAH4eAAkVgSkXjW0rpeGDTr25xY1Yvd16acqmIjg2lO9DLxOYqiDWyuoJXfMmbshj519aojUvlZrIq2Iw7HfdZ+z8dwVIObdX6v2HhxOKox/H5GS4rFxk4KFnuSsNeO8wp+n9hB3rxOnb5VB2PH+HGDjSOL335r/WDYB2bq2rXJn+WRDxz1AvG/83keQrTN288ePG5J4+HDAH7l6B1zU7i61MuBkN1/pVIysSOz+UT/uuhFInDqCEiAnLol0Q2JwOkmwAjEo0cbKJXKO12aWWc/YpvHsRu6I06Hp7Xs60Cxw7QTbo65gep2nV4YLLO6tJQ2o+2xDHo71v8PusW7YIPgTiCFTuKoP779AAAgAElEQVQCuv0o+jQts4JTnGbz530D7Ky+XdtGu9e21K2FqQXzW7gpJpPf28BJ/WmVHF8JrxNbAPpNoEe/SXjHQ7DHJ1q6z5bjveBpPdPOzHOw/3Cb3jEaxUgHe1hkUjy9LzslhhnlMNHRc6qJ0Yg9PHhdXpPCidW2WPKX8+jVgPQVIPuuk760452p14tY2VxHrVZFLPMGcpkl5LK5PU6uB06aF/0qFDs0gsdmMQg5fpXGxhqC/RJSC1lEZ3LoBpPohGbR7TmpeO5wN7XD6Xf8mUVLKEjYtyTKBofOZjfICBgjS4zsMAVrxKzea9WxurJqXdjDsQyahRLCm98hMzeNZqlkwvP8Rx85xn1GQcgnwDVhoYLDi2VX7FBU8bvAqOF+g6Kdr2UDwuFULX5/GH3kd+YgAVJ+/Bj5r782YddvNjH91luYeeutsZfld9X6bsbDExnw6e1ipKbVapsnKJkMmheMJZ153/zOU9w1m06UNJdjD5aOeVvabTaqbOHKlSVkMixeEFVn84O+5Pq5CJxCAhIgp3BRdEsicFoJ8MTxq68eY329bOZuNhe8cmUe58/PHmvONU9GeVLLVBJWAWLlrGQyutuJmpEQpmSxQ/SkVX4OZMrN9pP/gW5lHYH4HELhPjD9IRCfQb/TQmcQQSeYRacX2PUquJ9Zb9WtLDAjDamYG/EYOBaCoaZ8rk9hz14K3KRzw8/Bja9FGFhetwGEufme29s4zUhFY815H1Of4mPEwhgITg+Llgk8emLOn0shF6eQyDuRDZ7iJ5ecCFA046RWjTNSW+RgzREtnAdFS/ICsBORoJemU1nB/QefYbteRDiSRi86g2uXbppo4+C6c2NMTw77X1jEhOlQzTyQWnb8ONEc6pUwtm7fRq9VQ7+8jtTiAhbev4FgNL7b3NBKOreb6NYL6HQa6PRD6CL+fTrQYIAAmXVrGFDchXNOr5mdVLBxPTDsh4MeetVVrK6so1rrIhxPoV0DIsVVBPsdDLpd5C5dwvwHHxz4yB3mBeTCOZHNRINllB8/RiOft6hM9vJl9IJRK9E7SQpW8cED5NnBfm4O9Y0Ni4AwnXB0uBEXfifT6ZgVFDjIW8J1pvDlc8QID9eapaZ5sOBER9hMsYR2u4t2u2XfdVb1KhZZvKKGXi+IW7euYW4ua+LjtJQBnmhd9CIREAEjIAGiB0EERGAiAsy1LhaLWFkpYHubp6hhxONpXLo0a6eyxzIYZcj/Cvln61grJ5Fb/hClpmOkZUdnbsJ46szhXP/wp8l73mdjFYVvfobK5iOnqfnMIgJLHyEcyWKKqWWxjJ1es0cG8+GZFz+cWuLmvlu+OwVDt8R/YK33xoAn30Nj4l4Ku2Zxt8GgYxYfO3jS3lh3fkQxQLEyJnVo9L3sMzHcw2J+No5Ib33H4xIGGk8d4cGKUUzB4q+9BqMGux3f2bfl+3nz+Slvr2Mjfx/lRgHpzDlEc3NYnl1GLpGzfhfcHFN0cm2nMwOEOxsYdKqII48Q0+yS5y0CUyu0sXn7NgIYmGBMTsVx7tY7CKY4Z4qZnZwjChgKKfZqsT4tC+gF4o4fiL1kKk/R67bR7bSdOcbPIRAI2kZ/XLTE1o0Rk+4W6rUO6o2AVV5LzpxHpFFFs7CNcDRqm/1Y9vk1P9L3g2l55u3Z6YOzR1PNcZ9dX19H/s4dtMtMJQtg6soVzL77rm34JzGh08/CogQsRsD+L7mrV5E6/3z0i59DAUt/insQwIIJ7IWy36BY2dxkD542GCRiv5Phal0UNRQo6XQElUrb0i/Z1fzx4zX72GQyjps3L+PCBa7Xy5U8PtK66E0iIAIvTUAC5KUR6gNE4PUmMGw0b7fZcK2KZpN+j8zOiWdq3ygET9UtTz4aPrgJXP6XwPrPUMiXsVGMAzMfA3OfWBfoly0nuu8qDXpoFh5jbSWPaimP9a1t1OPTmLu0iNx0xOmunpkHu4PXNzcRYEnYN954fkPG0/luBd1WA12rwFU3wVTv9FHsRawxXzwat6pd40awW0E42EEkGkMkOYdwNIXwoI6ApVU1nSpKFBR7CIBOtYJAt4RwdLBTcWlmrHF63LWZssO0F5Z4tY0kN+3tbcekznQuio9wAv1AwjazB51wD5vWuZmnWbjRaNila60qWoMmYskEUvGUeWfoU2HEi5tOphexT0gs1EGwk8eg30UmVreiBsH0Basi1ev0ULh7F/WtLYQiIWQW55C9+MZOutRQhMA61ZcdIcSUMvP17FRmY6SJnhuEMOg2LLLVicyhC3YNd6pxDZunvxck/R0vS9kiCfQEpWaWEY3FEQ4GEY3Hj3Qi3+92Tdjumr0pmugfYUSJCiRGL8q5icv4lldWsPXFF4jPzloZ49S5czj/ySeOV2bC0a5WrRxzKB5HfOrFinZMg2RFM0bQ6NOKRvf2p1B08PtADwufH/43nzv+efQggX/P54GpWjT4h8MsA0zPGQ3tPJCYxcWLCxM8hxNOVC8TARE4cQISICeOXBcUgbNDwK2vzxNj12jO3gzBYNQ2ENyw7tdZmqfaPM10OkSzOtb+YgWrf28+jF7qXWw/+RKt5IeIXf1jK8E7UQdrbtqsOhX3lUlnI77f4Maep8yBMBrlElafrNnG5/FWBzUMcOnyPKbmgpifnsJ0L2Y9Mtq1GgadDpJLS1i4dev7CleMVrTZW4N9H9hfI4FBOI3Nyjry3Qia/TAS4QSm49MIDoJW5Wl3g8vIAVOtmLpk/g9uNhccX3W/blW4ItEEwokZEyjDRu1Br4fi/fsmjBiVyb6xjNTS8tEfMgopDvbB4J/ZzT0UB/tLcD05WJlsXNRrOHJgH9Ht7nY1dzfwuVwOwUjQEaXhKELWSwX2nNCj4HoA+r0eYoEqQgF2Ig9g6cISErnvmzpyw87TffosnEpdYwb9I1wTq3zFLvAL33enZ5SIFbuYrsZNPu+DQoW9S0JpIBRFdxB+oZmilZrle7s1i3ANGFkZec7GlZoNMiWM9xsOP1eWuV0pYfNXP0er1kJq+TKyFy8iMTvr+EasGhdLQfccD9Ae1bjGTd0iGDsiLZJIWFTGjPHHPBjFoDeDYmSvviNud3Y2K+VBBKvZUViwaWe7VrfUsEg2Z5ETV9zy4KLV6qBaLSMY5AFG1KJgWfMLTVjY4Zjnqo8TARE4PgISIMfHUp8kAq8Fgbt3t/DoUQG9XhPXr6dMZDDywTzrwxrNXX8BfRwUITQ4c/O65yh8Bmz83Eklik1jMPtDBBZ+OBlXbpatIR9PjOFsJnli/EK364Gz6bRGc9xkc48XxSCcw8ZWC9/eL6DS6COY6qNUrWJhPoUry+cwFw5h8/PP7QSZpUnZ22Phww93mgyyAR5P26tOP476E9vI8jR9vVFDPZBCNJa0LuuLuUXziTzXS4E+hcoTdAch9NsNIJoEYuftNHxcCVOmvHRoxo+EkEYb9fv3Eej3zSxMYXTu3asIBlgyiL0nnA7tBw76TeiJoAiieLMeGc5pOTeQjE6wdDIHU2OYFudWOuv1e44Rv9tGLBwzE36nTdMwK145gsa61E9NmdF73HArnPH0m8bjer2NWrWFIJyO3ueWpo+Qcse1LltXejOwj5bdNRFSdIQIzeEUjhSw4YyTkhWbBXa6xNs9D/oYdCrWX6YzCKPTc7q9j0ZLKHgCPVaiGpivhC1iWFGqXSwimkhg+uJFzF6/jn6lgAf/7b9i8/PbGARDyF1/B8t/8EdY+OADp8clzfxMreM6MPI19nnee2UpQtjIMRSNInnu3ESldA98Tsa8gOKDc93Lj+WmVNG/Ql/HwkIaiV7FUry2nm6hHUwgeekK5i4uWbSTwptCb3t7eyd6Gh1rNudzSXM6G88HW07pa34vWQr5ucF/G/bren+USes9IiACL0VAAuSl8OnNIvB6EXj4sIi/+quv8fXXKxgMarh1ax4//vFV8NSakY/D5luzfwE3H9x4cINiFZb28Ys083nUvvmZlYhNLl5A4uqP0e10UH32DDzpZ4M8Ox0eu4NtAbUnO9k/AWfvTMM0T7SHBzfZjFYwtYkN4lKXnChIfAaD2HmrzsN73i5WUKs3kcnEsbgwjbmZGDpPvzNDbjAcRnp52Yy5u4MRDPMb9CxdyTauoQQ26xUUmlXbUGUTWSxkF17sWcLN/85pfG8QQAcZdEOZ3Z4KwxWduDFfXa9gbXsLCPSQRRPpUgGxWAKDdhvZuRwWby4jHgXC0RgCPPVn9aqDht0/PzPoCBZudneqaFEUcC25jx902wijgcXFJGKpjM2xUCtgo7yxa71IBpMI977358Ri7Mg9fajnh0blUrEBRjrS2QSmpsf07Bg7p4FTscyMPBN4k6z88RrQZRPIoiNOWTaY0TGmvJmnZGeQEV/Dil8UKNF5dFpd2/gGYjRKd8xP0qk+Q7eet7Q2vq5eAvL3vkEwFEKn0UBiehpz797A9i//Hg//7n+hW+tg0Oogs7SE6z/9L7jwox+BUQuLgvB+rBwwSxZPMJ+D1vllfk4mVlL4cJ4Ufp/4/DDCwbQqFo8IbD3G2udfohnNor66huyNt5G+fM36ljDisbKyZlGVVCqBmZnMC2ZzRlPW12vWoLH95DtEaptIJcPWe4deFxMhdiix7VRkYxUyCsqQ08+F/x7xuXYaNoYO9Wy+DEK9VwREwCEgAaInQQREYJfAL36xgr/+6zvI5Qa4c+eeCYY/+ZNbyOUydoLtVgZyqzmN7dkwxNNtfOZUuolY6sVe/gH2HWDOeuXpU9vQpbiRuHkT5YcPUXr82El7OnfO/m6swZcbDTbAo6jgZs26e597MQ3L9QUw9FFbcU6WudHmZpMlXgewVCOno3Qbi4tZ6z1CFrl0CK1SydJ+LCd+OJ+e6V9tnsIygpDY3bwzOlBtVdEf9JGIJJ5vCDj87FGEcIPHzb+d1H+fq28VnWic7rA0cQ13vn2Meq+AZoPN+1pYQgexehcBNmObTyMzy5KvabufcGIa4cwbFnnYd92MS8nxUTAlbMgvQSZbWzWUS02guY1soob5WUZXcrZB36qXsV5eRzaWxePVx5ZmNpOesU0eG8Ol0+N9L/t+9QZdDBpb5s8IRmJOWeFRMfnCB7CUMYVlBfXNbbRaIYQz87YptZK4ew32RGGkgb+bYT3jCEk+P65449+TUWdnA95topwPobpVwaDfNz9Q5sIFtAubCLQ2EMtmMAg6VZ3KxQDWv7qHZr1uAiQyN4vc5RlUb/8TnvzDP6FRaaFVbiB98TJu/If/jOlrl8zMHo5PWcqd+72zak/cVFulMZZbjjvpesOn+xRUfA3FynGe+jMyxggjy0RbT5PJPSmtZhf59U00mm3EEynMLkyh8fQRtm5/iVKlh3q9hdSVNzH/1nVkMkFsbuZRKrXR7QZNfLz55rL1Chke/E4+eVJGpN/E6i9/iWivgYXFKYQiYZz75BMk5+cdTtZbhyWZ+05Z6+R5ey5pgqd4oQBhLxT+27TXYAUuRlsYmZu4Cpn+vyICIrAvAQkQPSAiIAK7BL78cgN/8zf38N13m2g2i7h1axk//ekN8xwwlYa/+D9vN61mku7FPMXkSfBB/+Om4XXj00/R63Ts9JIn3+w7wFKibIZG0cGc//lbt16oxmMRDJ5i0zjNE2MKkNQ1J/1odAxHKrjp54abIoQpR0M9Gnhqy003Nx4UT/Sv7NU08dgeIW7yLIWsuyNiXvQ2UBR9+2gVjzfWkIhGEIq1cWF+BslOCN1+H5EYe3iQQ8057Y1wbs8biLmeo2KSHd+dpoNkwopR88+duDNFqlGjL2EViUgPwWjMSddKLKLaHWBtew3r+XVEgo5pP5PMOF3N2V+ERnDXT8LOc0yHGlfKdxgkxQBTkLgmXN8YoxEvNgR8jr15aVZRX9/C9jdsotdEeMqJVOWuvbn3Mtnzs+FETthzhV3jyYCiZ9ffMQDqq0DtoT1jLJy1eb+BRjOEQChsEYtQIoFupYxAr4j0bArT1y4a+0FkDsWHK2hsbqLRa6E1lUAo3kCwsInCP/8GxUeP0A8lMf/hD3D+o1sIouV0YI/MPLd2tm6DulUHi6CBSDiCcOYCAokFxyPC6ERnJ42OzzWZTZB+RwF1YKdzsuVm3ppysjgBPSlLB/usSL1dQLeWR7fVQiieRiR7Ht32wNLSSptFtANxpC5cQijOAgcdFIttFIsdXLgwbyJyeTlrpbiHBw8JmOLZrNRQ+OK3iLUKmJ3PIJrN4tzHH1uktFvbQmXjEfqBJFKxpjWfLK53UN7Io9gMI3L+onl/WHXtwoXc2H+jGCWhN4mHKUxHZZlht2nisX3v9UEi4EMCEiA+XHRNWQT2I8AoyDffbCOTCePjj89jdjb2nBGX73VFiCtKXGHimpBf2NyGwwemODDFauvLL1F58sROlHlqPXPzJkr376P06JH1V9gzAuIadgeBnW7g0b0Nu9w8Me9/N1KRG1sZiBtuGq8poFjd59hKDe8H302DIuNAFPVQ2jamjJwMdzPfLlTxbHsDXbQxk0thITtvFbY4uBadRhGdZh1d9t4YJJ5ryudefrjjNP/OmvIFOoiEAojEUvbLmvJRMLiDnhlGAXpMC+Lpu+Ozqdbb2MxvotPvmADJprM7Xc0DQPUBUGPkoOwImsyVHX8OywnvU5GJAoSiklEPejOsrPBQOtQ4jvYcrKL44CHyX91F+o03UHm6gdylZcx/+LGTgrOzIWfEjSLXUp2YembpZ9xc953rmAdmZHD+5XsWqeq0g9j4+glarSiC0QT4eRzhRAL9Vh3RZAgLt95DJEfju7M27Xod65V1VPtNxAct25hPh+MIVVoI5S4ilE2jU36KbiCBTqOAXjCBQYyVr4YGI328B4almA4WSiOcvYBwIoMISwQH+whHWbQBTtPIfZpR9jsdq+zWpMBnqd0rVxCKOWle9Dnxu8jfo7kcMufndtIES3w4HT6Mkh0kJPlhbtTRja6xnDIrq/F57XTM/1IoFNDtOp3Ny+UOmhQIkZilR9FvNNqxnd9Plo+mCb698RTB8gZikaBFTqevX7fv9PrTLeRXn6DfriObSyHRbaH0cBWNSh2l+gDxyzeQWL5kBwxvvJEdK0BYlIJCh69hE1Z2oWcKmYYIiMDLEZAAeTl+ercI+IqAa5x204Hc3/n3+4kS25hNkMLF9BT2L+DmKjE/b/0H2Hej+vTp9x6QuTF9MFwDOjeI3BBxc3PQaflpXLmhjVqh/BSFQQzdUAqZeAYLmYXdilG2Qez3zNROYTIsTsZNa3TdXOO0G8nie0b7XrifsxvlCrQR6ZcQGTQQCtFcPYV+bAFFpg+1nOpYHKlUyvxCNtjDovSZk9rE1B2Kvtw7zuY1vviiKXz45s0XM9zZnYbwg3wgTMHKo/rkAQrffodWoYhQLIjpa9cwdeUNIEFfS84iERZ1aLWs0d70cgaBbsGJnO2mn40RIIww1B87zSL7QHFlC9UiS5XFEUom0a3XwUgezTJMAZq7dcsROEPjWfEZSvUSIqEwAv0mzmXmkE7OOZEEXptpToxeBcIYRGfQi0zvpt+Zx6S+hX7pnvMaimlGbTKsbkUxN3AEViCMYCiIcGYJkfjUbrSL38FhH1f50SNs372LHksAAxZxdH1NhXv3ULh/H/1224zdM2+/jeRs5vsO8eZJcfwUBw6WE6Y/ildhZIepbTvm/lGzOdMEs9kp1Ot90OfBAgQUH3umbvb69jMKJR5cUAByjkybWlkpo1mrIhbpod0JIFHZQP3hN1YNbOWzO4hefgvZ629hepo+k/Hd5dmbhgKEEVzeD8UQjfIaIiACL0dAAuTl+OndIiACO+VWR5vyWbnSnRP50UjJXilc3HwcuauxlUZl0zZucpLHm/9+UqtsZWO30e3WnepZSCIczVhUg9WzkrGDNuCHu1Gu0bCY5H8PG96fi5Lw3riRjE0h2CmjH51FvRe3zR43tjy5ZspVPD6Uq09jd/EzJ5WKaVjcgE69tVPR6QABwqlwTSlEuKmedLPL99Gf8eQpOttPEQo2kb10xYzNFCCDcBbrn36K2tOnCMbjZgyff/syktORnfSzhBNtGTV899voN9bRrqwg2NpE1Hwpc2h1chjE5yz1p/L4MWrr65bOxCIFmeUXyyHXWjUU6qwy17P1nE3PIjjs1aCINi9QeI8KZgP0S/fRqa6i0yzbRrvRTqFVryOSm3MiGDTJ04dEf8hOmWNisShXiH01GF2IoPr4Mcp375p3hTymb9zA7Dvv2EO09utfo7a6ahGF2toa5t97D9lLlw73gLmvtgprO/4auy9H3LVbLTxhs8RaDclsFrOXL2Nufv7o/wYM3R0jJCwowSgJg0WMYKY6eTQe3kezVDJRlb56A5k3li21yh63ft/mymgWSzvzNUzB3NysmWGd0Zi5udRuNTYejjA9NByL7V0Keuee+DpGe/icvFCl62hU9S4RONMEJEDO9PLp5kXg9BKwVKAd47T7u7u5daMl3ISN+kqY8sNN0rBpevTk9vTO+mXvzCkR3O91sFYroNhq2eaUKVjnsud206xe9ir7vX/Y8O52d7cys/SmNJ2u4o1mB5VOFP1Q2ja1zql11sTHC4UKWmtOWWIKEG7qk0s7ESpWM5u8Kd6R5sxIBX1B9HWwMllsDv1+EOu//S3qa2uIZDIWBZl//32kFqZ3+m1Ex/oaes1tFLa/RqPdQKy5hnRqHsncNWeDz/4cO2lW3JTaRn8nlWncfXd7XStKwD4oBw2e7LeKResfkpiZcQQ2vTcUKv0mCnfuYOvrb9ClV+nK25h6510EoiFrrMh1G45y8d74eeFk0jbBrDpX/O47dCoVJKamMHf9OqYuXLD1rLD4w4MH6DYaiLF8cipl7+EGmr1KzNRP74w1q4wcTiAyK6vRwLO7d1H+7jv0ymVk5+Zw5Qc/wPQx9iqhaCgWG7s9SjLpCKqrqxapiqTT5iVj6ifLFVM0NvJ5S/ns1OtOBOu990yEOE0Ue1ZmmA0XTTxVq9i6fRvN7W1jM3X9+ljBydcyhZSpbmTPz2WVLooWDRHwMwEJED+vvuYuAidM4KgpXO7J7agoOagK1wlP71gvx40uT8rJLB1PI5fYo9nesV517w9jfn67uol8fg2VShu9QBy9AZBIJKzS1V4lmikmQ4GupRzZ+sWi1uX9xIZtkhkRiO4WGWBhA0YreNLNTuGzb7+9r2DgvVYqz7C1eRsh9DBorCMVz2FultEcVlBjtbWDxcTwnOld4AaZG1r2xhnXaJMb1vzXX1vH93AkYp6W4dLPTFn85i/+u4kQioRwMoXLf/zHmLpyZfdSblSr9PAu1m/fRqvZQezcsm2YuQlmM0BuuMPsdj4zY+tILjSM92s1cLvdrVTQLZUwqNdtoz73zjuYe/vqTpNHGubjTtRoTJUyV/Rwk87y1Rzlchm1Wg21x49RunMHizdvoru6aht+Nvc81KAA2mkm6hQ3mHyw4EX+q68s6oFgEK1CwQRecmHBusef++ijPZs3Fh88wMZvf2tChu/LXrmCxR/84IXvAX1GT37+c4smUbxR8PBzM2+8MfmN6pUi8BoSkAB5DRdVUxKBs0ZgNH2LJ+/uye1w+tZBVbheKoXrlEIb7S7u1W26ufpcK1dssLwumQ9HuIZTuNx7HfWXuGlbo9GSw/aZeRkWPPVmYQNLiYkeLB4qjRI28ncR6rfQ69SQTkzh3NQFx1C/j9F73D2yohIrK1GEhMMhzM4mXqjyxPfRD7XxxRfW4b5Tq5m3hOlS0VQcmcU5tEpVfPs//9ZO4bkJppfjwk9+gos/+Qkiye/T9fqNPO7/5Z9j+849RLPTiEyfx+If/ASJxcXnes3w+8WoSGllxdKFePqfu3zZIiFbX39tpv3ao0eYe/ttXPidm5g+F8WgG0a3lEcweQ6pi2/vljvmRru6tmZltdkgk5ynbtxAtdm0xqZM2Wusr6O7soIAf57JYO7mzV2Bxee+vrmJTrVqEQaKgheeD/pfmBbIIgUUgKz6RW/KhKO2sYH1X//aREFtu4B6fguRWAJhltvNZLD8+7+P7IULYz+t9PAhNj/7jHWw0a3VTNCd/+ST515LXhSQT372M4ti5a5dM18bG5iOS8+b8Lb1MhF4LQhIgLwWy6hJiMDrR+BlUrhGN7Y8hT/Jze3rthrNZtO6mrvFBsiTjQXHdTUfF+VyU+32EiTu33PdRtPvjuwJOuZFoOk/X82j3qwgHI5gJjmDZJyRnMOnkZVKTayt1ayjfLXasd9ZanZ0MCUof/u2Vc+iMGBEJMaePKEOpi7MIbW0hGef3sOzX922lDJGc3i6Pvfuu2Yad0f90Vf49i//ArXtupX4DWfnce2n//H5RpqMdHQ6ePrLX6L85An64TB6gwGm3nzThM3jf/xHbH3+uW3MKQYWP7qJ3FIahYdP0cpvI5JdwMz1dzH/9tvoNxqoPnpkkRkKvek330S33UZ4eRnJpSUTH3x2pnI5NNfWHJGRTJrHhFESejEYYSjev2+pTozuzL711nNRAxPmLBtdf7ZTKa3mCBCm+E04KHA2fvMbFJ49Q2lzk8WvEWw0EQuHkFlcwswnP8T09WtmhB81wTOyQ3FB8UfjO/0zyZECGeWVFWx+/rk1UmUhDVbxW/7Rj6yXkXwgEy6SXvbaEpAAeW2XVhMTgdePwLA/YThqclAVrnEpXNwASZQc/IxUKhVUWdlpZ7CrOc3mh01/GzW8c/3cQgX86NGywO713J4lw6LSK08Qn7N2r41QIHRg5bH9yLoRkFqtY74CVmAa7XNh7x8MbCPOjTLFSLtSwdTlRdSffmtegvPvX0e90MTa7Sfm5WDZam7+0xcv4tyHH34vQJ7cw5P/+/eora6hU2sjffVNXPvpf0Isk3nuNnliv+uPSaetAhbTokKZDL768z/H2m9+gz57keRyOP/JR8iez2LrzleIJHNos3H89Axm3nsPW5ZOq4QAABlISURBVJ9+avfDyEC/XjcR049EsMDUrevXTYDMzs7ums1pQmdlMqZ3UWww4sJCAdzAL/3u79omnxXFaIR3xQkrdIUGDcxfm0EknUG7XEBk6gKi5/bp9zKyKPys7Ttf47tf/guqlTpSmSRKzzYwe/EiWtUu+tlZzH74O5iZS9v6jP570WfRhnodQTaNHOPp4NpxHuxJUllZMUP/hR//GKGdVLSDv316hQi8vgQkQF7ftdXMRMA3BCZN4eKG1xUrhOOWBh7e3J6WE3evF48RKPZmYLqMKw6O3NV8j8mMGt6ZyuWu0UHzn6Ss80Gf4eXP2VCy1erZyTo9IHuVmeU9MvLBSAIN0vW1JwgHG8hdOI/p6xes0lWzGUfh3jfm52C6Evt5DHsM+u0WCl9/aptghKOYvvEeclevjZ0+N/2VR4+e88dQmLAqVuHbb+1eeHq//G//rZUeXv/iM9S2i+j2epbSxVQr8zysrCCcyaBZrSJ4/jwuvf8+3rh1CzmWPZ6e3t3MM5JgUYKnTy19i2b7XrNpHgyWCLa+HteumRBiJIUm8od/+7cWHem1Gsgtz2Lq8hJ6nT5iM8uYvnkLqXMjvVP2WehBv4cnt3+LrfU8erUGat99i0R6BrVqF/HlS8jc/MAiIHs1KtzvGeKa0ajOubhG9WF/zqt8/tj8lR4jPle8fw0ROG0EJEBO24rofkRABI6FgHviPixOJq3CNa6R4rHc1Bn5EIqOYrG4G6FgFIJRD0Y/TmKMCsrRak573YNbYnY0WnIS93wS12CUgJvaEOpIz6cRjO2UtA0l0CqVLF0pHI1aD53RwdN+RlCY4sTN8EEbZ/oimG5l/pjBwMQAU7MoDpj6xWgEf0bBUt/YsD9nLl7E9oMHePqv/4pev4/VBw8QXFjA+Y8/xvX338f03Nz3PWJ2bsB8GL/6lYkPmt/plaARnP1ZmH7GiMjS7/3ermmeIujun/6ppYvxHhmByF26iJl33kEjv21lhBc++OBQy9GqFpFfW0WrWkNnKw+0gWIdCJ+7iHBuxgTi8nIGkQi7Ox48ut2+NTGlwA53Gwi0albkYKyP5eCPO/QreH16jNgt3o2wsdeJhgicJgISIKdpNXQvIiACr5TAuBN3KzF7QCPF02CafqVghj6c1YlYpcgdTFXjibXXkaFRT5DbTHGUy16Gd85jWJic+fQ79kix/iGH96Ac5VliFIQn+RQyrJbFqlnjBlOjKFbyq6to9/s4/8EHmLtxAzMzM0gOGePd91JQsZoUDfcDAAk+a7GYiSmLGly79pwRvLG9jbt/9md2DRq6mf7EcrrppSXzktBfwbLKhx29dhNVCqxu30z/7WgOtXbAIgjcvFOETDL4b8n6ehVbWw0r38v3LS6md3uNTPIZ7mtYpYt9apiadphB8fP0adnunX1M2ANlbi5h5YgpSFKpg4suHOZ6eq0IHIWABMhRqOk9IiACrw0BbhhG/Ql7VeHaK4VruDzwYb0RpwUkOTDqQcO5O9jVfL8Su17f+zjDuyso3Xvbq8O70u9ezerRMP+YaUflMjIzM5i5ehVzCwvm+9hrMIrCFCxutrOXL5vwaJfLCLE08NTUC2/bvncPG6xAxapgly6ZBGOVMJbEZTf3ce85aLaFb74BfzHFi5EYGuKnrt9A7uoVq1Q26djtwN7sWsPCZrNj6VsUAZMOekuK337rlF9mg88333xhThRu7NHCKBWF2PBg5IPd2yk4eD+8DwqPRoOd5cPmZ8nlHAHJVK16vWMpccnki2b7Se9ZrxOBwxKQADksMb1eBETAFwTGiZJJuru7punRniWnGRo37fR7uClq3Iy80NX8NE9g5N4OMrzvNZXhtXOjJV4Z3s8Q7t1bpXDnc0RhyHS9UbP5fnNiZIWpV5NGpigSGCFg9SxLxWo0TLAcpboU7/fZP/8zyo8emY+mcO+epXxRzLBk7mh1q/3mwajH6moF+Xyd+mg3AnIYHwarZlFgsT8LS0UzCnTuk0922bBvCSNArUrFSiWzfDFT1VjUgOlX0WjI0q9Y5tltnMioCKMxrMC2sJDC4mLGIjSM1vDvnO983H7mrgGFCQsmsAN8Oj25gDqLz67u+eQJSICcPHNdUQRE4IwSYBrQOH/CpClcp7G7OztSuyV2uSzccDPlir+/TmPc2k1ieB+toOYKk7Ma6XpVa+o+R+RC8RGPx+05OiucuOHf/OILizxQDLGMMQ317O2RXlw8FLZWq4tSqWXRBaY7TZq+5V6EndNZHjjKMsXb22bEX/rhDy1CxMF7ZQlga5i4uWkiCfMXTfSwsEE6HcXCQtLEB39RjFAUURBRdJw/nzahsf1kHd998QC9dgfRhUVkFmatHDQjJuVyE/fu5e0zE4ko3nxzxkSLhggcFwEJkOMiqc8RARHwJYHRNCBXoLiNFN0eGG6q17gqXF6kcPE+6PWos7t1IGCn1uxqnsvlJj6FPusLPi79btTwvld5YNfw7q6dm9J11pkc5f7dUs1kwagHU/f4HJ2lwVLArKy19eWXls6VnJ1FenkZc++/j0jiZA3crXLZxBDFBXuMTF29ahXA3LF5+zbyX36JcDJpDSN5j7X4AgqFJjKZqEVCaJp3jecUQltbdUvBYjRjdjYJtOpY+Zdf4Zt//H9oFMqILpzDpX/3h7jxb96zCMqDBwXcvr1u3hVGSK5fn8EHH5zfjaicpbXVvZ5OAhIgp3NddFciIAJnnMBRU7iGN7bDaUDHiYP3xlQZpsxwcJOdzWbHmoSP87pn5bPIZ7R62nCHd1eU7Gd4Hza9T5pWdFb4uPfp+oZarZY1FrTmglNTZ/o5otmeVb3ow2D/juGO8ie5PqxYxnQwVhez6llDRnQKlO07d0woxXI5qwC2Vexic7NmEadwOGDRCtfn4d43hQiN6Xwemeb1+B/+AZvfPkJ5bdPM/Jd//Ad469//oRUYePiwiM8+W0MoFEC3O8DFizm8//7CxJXATpKVrnU2CUiAnM11012LgAicQQLDlZyGN7icCjdz/PnwLzda4lbhOo4ULm4WaTafpKv5GUT8ym7ZraA2Kkz49weN0Z4lbsf3g953mn9Okba9vW0FHJhy5VZLO6lSzaeZzUncG4VSt9UyscDULKZ95fMNM50z7YvNLffrLUMTO7vbP/vFL6ySGiubnf+dTyzVK5pKmXn+zp0ti5zQuH7t2qylbmmIwHERkAA5LpL6HBEQARE4AoFxlZwYmTjIV8JLHbYZn5sq457gH7Wr+RGm+dq+xS0HzDXjr9EO73tNfFyxAka/zkK0ZJzZnGV2Xzff0Fl8aOnx2E94DM+p9PixCZBWoWDNGxlJofHefQYpZtgwk/1PWCHrLDybZ3HN/HrPEiB+XXnNWwRE4FQTGN3Yul3CedPjIiWu52TUm8CTaW4c3K7m7qTT6bSV2NU4fgJupGs4WjLO8D7qLxk1vLtpXKfJyM0yzYygnVWz+fGv9tn+RFYSo9GdKV5MOTtsz5GzPXvdvZcEJEC8pK9ri4AIiMAhCIw243NP3PkRbgrXsOndFSWscsW/5wk1ox5zc3NmFNaJ5iHgv+RLhyNdrjAZZ3h3Bebw2owTlV40hqxWq2AU7SybzV9yGfV2ERCBYyIgAXJMIPUxIiACIuAFgUlSuOj7yOfzdmpNszl/Pwun7V7wPOlrDhcrcKNe4wzvo/d1nL6gg+Y8zmzOKlcUsRoiIAIicBQCEiBHoab3iIAIiMApJzDar6RWq8H1GBw2hcuL0/ZTjveV3p5reHcjXO7vRzG8M1rxMilcfFZoNufzJLP5K112fbgI+IqABIivlluTFQER8DOBo6ZwnWXD9Ou03uNKAzOCctAYt36TGMZlNj+IrH4uAiJwVAISIEclp/eJgAiIwGtAYNxp+yRVuMalcLmG99cAy5mZwqiodNO4RicwrmcJI1vDpZ2H1881m/N97Gp+1jqbn5kF1I2KgE8JSID4dOE1bREQARHYj8BoChdFiWtqH07hcqs7uelBbmlgt4kiN7VK4TrZZ23UF+SKEnf9eDejgsS9Q64VPUMcFB1Mu6LXg94hFS042XXU1UTgdSYgAfI6r67mJgIiIALHSMA1TI+mAvES+1XhOmoK0DHeuj4KsEpobr8St6zzsOGdkMrlMhqNBpaWlkyAyGyuR0cEROBVEJAAeRVU9ZkiIAIi4BMCwylcw834Dmqk6FZxGo6UKIXr5B8ad/0Y9djc3ARTr7gmi4uLYHNBdTY/+TXRFUXADwQkQPywypqjCIiACJwgAW5qR0/bD5vCNexNeJkqTic47TN7KUZBWOmK6+ZWupqdnVVn8zO7orpxETj9BCRATv8a6Q5FQARE4LUgME6UuFWc9isNrBSuV7f8o2ZzChBGPiT6Xh1zfbIIiAAgAaKnQAREQAREwDMCFB6jhnf+96QpXMOREqYOySg9+VK6nc3JjcIjmUya50MMJ2eoV4qACByNgATI0bjpXSIgAiIgAq+IwLgqTsMpXG7lLYqXvapwKYVr78Uh31KpZGbzaDRqpXhZ5SqdTr+iFdXHioAIiMDzBCRA9ESIgAiIgAicCQJHTeFiadlhs7tbKvhMTPqYb3K0szlZTE9PW8UrDREQARE4KQISICdFWtcRAREQARE4dgLDjfiGU7l4Ibc08LC/xE3tcqtw+SmFS2bzY3/89IEiIAJHJCABckRwepsIiIAIiMDpJDCawuWWBz7IV8LZuNGR1y2Fi2V2C4WC+TvcBoMym5/O51d3JQJ+ICAB4odV1hxFQAREQATM7D5qeJ+kCtdoCtdZ6+5eq9WswaDM5voSiIAInBYCEiCnZSV0HyIgAiIgAidOYDiFa7iRIm/koO7uFCanOYWL90/hUa/XZTY/8SdLFxQBEdiPgASIng8REAEREAERGCJw1BQupjeNEyVe9NSgsGLKFUUVS+zKbK5HXARE4DQRkAA5TauhexEBERABETi1BEbTt/bq7s7Nvxs94WROOoWL90nxwftwO5vT78FojYYIiIAInAYCEiCnYRV0DyIgAiIgAmeSwMukcA2XBnZ9JS/bBJBm82KxaCxlNj+Tj5RuWgR8QUACxBfLrEmKgAiIgAicFAFGP4b9JJNW4RqXwkVhMqkoGTabs8EgO5tPTU1N/P6T4qPriIAIiIAEiJ4BERABERABETgBApOmcO3V3X04YsK0ruHBzuY0m1OwUHyos/kJLKguIQIicGQCEiBHRqc3ioAIiIAIiMDLEXC7uw+LE/6Z46AqXBQkFCKNRsOiHBQeFCDqbP5ya6J3i4AIvHoCEiCvnrGuIAIiIAIiIAITExhO4RpO5RrXSJFipdlsmuig+JDZfGLMeqEIiICHBCRAPISvS4uACIiACIjAJAQoPtxoiStK3Cpc6XTaPCf0e4ymZk3y2XqNCIiACJw0AQmQkyau64mACIiACIjAMRGgKGH6lRe9Ro5pCvoYERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwISIF6R13VFQAREQAREQAREQAREwIcEJEB8uOiasgiIgAiIgAiIgAiIgAh4RUACxCvyuq4IiIAIiIAIiIAIiIAI+JCABIgPF11TFgEREAEREAEREAEREAGvCEiAeEVe1xUBERABERABERABERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwISIF6R13VFQAREQAREQAREQAREwIcEJEB8uOiasgiIgAiIgAiIgAiIgAh4RUACxCvyuq4IiIAIiIAIiIAIiIAI+JCABIgPF11TFgEREAEREAEREAEREAGvCEiAeEVe1xUBERABERABERABERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwISIF6R13VFQAREQAREQAREQAREwIcEJEB8uOiasgiIgAiIgAiIgAiIgAh4RUACxCvyuq4IiIAIiIAIiIAIiIAI+JCABIgPF11TFgEREAEREAEREAEREAGvCEiAeEVe1xUBERABERABERABERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwISIF6R13VFQAREQAREQAREQAREwIcEJEB8uOiasgiIgAiIgAiIgAiIgAh4RUACxCvyuq4IiIAIiIAIiIAIiIAI+JCABIgPF11TFgEREAEREAEREAEREAGvCEiAeEVe1xUBERABERABERABERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwISIF6R13VFQAREQAREQAREQAREwIcEJEB8uOiasgiIgAiIgAiIgAiIgAh4RUACxCvyuq4IiIAIiIAIiIAIiIAI+JCABIgPF11TFgEREAEREAEREAEREAGvCEiAeEVe1xUBERABERABERABERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwISIF6R13VFQAREQAREQAREQAREwIcEJEB8uOiasgiIgAiIgAiIgAiIgAh4RUACxCvyuq4IiIAIiIAIiIAIiIAI+JCABIgPF11TFgEREAEREAEREAEREAGvCEiAeEVe1xUBERABERABERABERABHxKQAPHhomvKIiACIiACIiACIiACIuAVAQkQr8jruiIgAiIgAiIgAiIgAiLgQwISID5cdE1ZBERABERABERABERABLwiIAHiFXldVwREQAREQAREQAREQAR8SEACxIeLrimLgAiIgAiIgAiIgAiIgFcEJEC8Iq/rioAIiIAIiIAIiIAIiIAPCUiA+HDRNWUREAEREAEREAEREAER8IqABIhX5HVdERABERABERABERABEfAhAQkQHy66piwCIiACIiACIiACIiACXhGQAPGKvK4rAiIgAiIgAiIgAiIgAj4kIAHiw0XXlEVABERABERABERABETAKwL/H71FCQo0h7tDAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{1.0: 93, 2.0: 20, 3.0: 107, 4.0: 71}"
      ]
     },
     "execution_count": 398,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amine_name = \"Dimethylammonium iodide\" # The ammonium you would like to plot\n",
    "\n",
    "# 3D plot\n",
    "point = per3D(df,amine = amine_name,category = None)\n",
    "plot3d2d(point=point, x_range = [0, 1], y_range = [0, 2], z_range = [0, 16], xy_loc = -3, xz_loc = 1.5, yz_loc = -0.3,\\\n",
    "         x_step = 0.5, y_step = 0.5, z_step = 4, elev = 27, azim = -64)\n",
    "point[:,3]\n",
    "unique, counts = np.unique(point[:,3], return_counts=True)\n",
    "dict(zip(unique, counts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(291,)"
      ]
     },
     "execution_count": 399,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(point[:,3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convexhull calcuation for different classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "volume of class 4 is 0.9243858059580934\n",
      "volume of class 1-4 is 8.013680787033385\n",
      "volume percentage for N,N-dimethylpropane- 1,3-diammonium iodide is 11.5 %\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:23: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n"
     ]
    }
   ],
   "source": [
    "# Calculate convexhull for class4 and total\n",
    "point_1 = per3D(df,amine = amine_name, category = 1)\n",
    "point_2 = per3D(df,amine = amine_name, category = 2)\n",
    "point_3 = per3D(df,amine = amine_name, category = 3)\n",
    "point_4 = per3D(df,amine = amine_name, category = 4)\n",
    "point_all = per3D(df,amine = amine_name)\n",
    "\n",
    "if np.shape(point_1[:,0:3])[0]>3:\n",
    "    hull_1 = ConvexHull(point_1[:,0:3])\n",
    "if np.shape(point_2[:,0:3])[0]>3:\n",
    "    hull_2 = ConvexHull(point_2[:,0:3])\n",
    "if np.shape(point_3[:,0:3])[0]>3:\n",
    "    hull_3 = ConvexHull(point_3[:,0:3])\n",
    "if np.shape(point_4[:,0:3])[0]>3:\n",
    "    hull_4 = ConvexHull(point_4[:,0:3])\n",
    "if np.shape(point_all[:,0:3])[0]>3:\n",
    "    hull_all = ConvexHull(point_all[:,0:3])\n",
    "\n",
    "vol_percentage = round((hull_4.volume/hull_all.volume)*100,1)\n",
    "print(\"volume of class 4 is\", hull_4.volume)\n",
    "print(\"volume of class 1-4 is\", hull_all.volume)\n",
    "print(\"volume percentage for \" + amine_name + \" is \" + str(vol_percentage) +\" %\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Meshgrid points in the convexhulls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Plotting Parameters\n",
    "xlim = [0,1.5]\n",
    "ylim = [0,2]\n",
    "zlim = [0,16]\n",
    "view = [-64,31]\n",
    "grid_n = 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate meshgrid point\n",
    "grid_points = gridgen(n=grid_n,x=xlim[1],y=ylim[1],z=zlim[1])\n",
    "\n",
    "# Search and plot meshgrid points in class4 hull and total hull (also find meshgrid point in other hulls)\n",
    "point_in_box_1 = []\n",
    "point_in_box_2 = []\n",
    "point_in_box_3 = []\n",
    "point_in_box_4 = []\n",
    "point_in_box_all = []\n",
    "point_in_box_non4 = []\n",
    "\n",
    "for j in grid_points:\n",
    "    if point_in_hull(j, hull_all):\n",
    "        point_in_box_all.append(list(j))\n",
    "        if point_in_hull(j, hull_4):\n",
    "            point_in_box_4.append(list(j))\n",
    "        else: \n",
    "            point_in_box_non4.append(list(j))\n",
    "            if point_in_hull(j, hull_3):\n",
    "                point_in_box_3.append(list(j))\n",
    "            elif point_in_hull(j, hull_2):\n",
    "                point_in_box_2.append(list(j))\n",
    "            elif point_in_hull(j, hull_1):\n",
    "                point_in_box_1.append(list(j))\n",
    "\n",
    "point_in_box_1 = np.array(point_in_box_1)\n",
    "point_in_box_2 = np.array(point_in_box_2)\n",
    "point_in_box_3 = np.array(point_in_box_3)\n",
    "point_in_box_4 = np.array(point_in_box_4)\n",
    "point_in_box_all = np.array(point_in_box_all)\n",
    "point_in_box_non4 = np.array(point_in_box_non4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot convexhull + grid points (4 + all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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f/2rj3rQ1XzFFVf0UYui4m7Ode6553qCQoF5EQGhVwi/J4KS0kABi3vdcMMN/T3mRUysuzvzhqjkFb8TSak6qkZMrCCf9DGIT6jIZX1Yql5TxwkBISAEhEBaCIiApLUemo0QEAJ9RICIBTUdKD8ttNBC7q1vfetccgF5IOpBX48pU6Z4UoHSVdk455xzfJdzIhxFBOSyyy7zKVrUgaQ0iH7ceOONnoDQQDFvgJdFTEKCQn8TG3w2r8liG2JC0f/111/vC/xZh2ydSZFksIrfU9phmosQEAJCIB8BERDtDCEgBMY9AnjTMaTtD7K4kAEjBFaMTRoScrlEPaoasqRgvf3tb3dLLbVUIQGZNWuWL1JHPSulYQQEGV6iG3UGWGYjJvybP0XExNS5ishOeH0ICBLH6667ric3eepcWVLCv3vVmdS5Px0rBISAEBAC/UNABKR/2OrMQkAIJIBA2FAQIxYDFQJiReF0M7///vvdggsu6KMeGLt1xsyZM+emahVFQP7whz/4PiEUsqc0IF433HCD7wNSl4AU3QfEhOhItpcJ/2fpV0RGiiImRvxCApIXieqVysXcjIxU6WWS0ppoLkJACAiBiYCACMhEWGXdoxCYgAhkox6ht5y+HBAO6j1QgSLqQQSjatQjhBMVLIumQEA4X1aG9/LLL/fpXtSUpDSMgKy//vqOwvN+DoigRUjowG7RE/4OiQlREggHRBFiSAoWKXF11qaol4kRk5CUKGLSz1XXuYWAEBAC+QiIgGhnCAEhMO4QyIt6mAELQYCA4KmnDoSoB0Zv00EjQqIppFcVEZArrrjCEx6ITkrjySef9HUW6623nu8VMhqDtcqLmITEhCL0vIgJqVz9ICZFqlwqfh+NHaJrCgEhMB4REAEZj6uqexICExQBi3pABDBsw6gHkKD6ROdvlJ2ISKy99tq1DNg8WEnnoo8G0Y0iAnLllVd6OV9qRVIaKRCQIjyITl133XUe12whPGvLINKUR0xIJ+s3MQlVuZhHneultAc0FyEgBITAaCAgAjIaqOuaQkAIREegLOqB8tVf/vIXTzyMgKBe1XYQTaEHCNGNIgJy1VVX+bSid7zjHW0vF/XzZuTPmDGjVRQo6qT+fjKaQF577bXu3e9+92vqciCZ2YiJpXNliYkVvRtJIc2sDlEoSuXiHA8++KBPE0NeOYyY5MkF17lmP7DUOYWAEBACqSEgApLaimg+QkAI1EKgLOrx6KOP+qgHXvSVV17ZG4wUhS+wwAI+/artoMs5CldEN4oICGpOpDjFIDxt5xt+fiwSkKL7Zx9ALLPF75AT1p4BOcjrY8La1CEJXIvifc7HmhpRsXOEkTd1f4+5Y3UuISAExgsCIiDjZSV1H0JgAiKAx5uaDv42hSszAl9++WXf7+Ohhx7yClSrrLLK3EJrisIxROlg3nbQ5Xzq1Kk+ulFEQPDkkxbEHFIaRVGGFOYYa25GTPKaLIbEJBstYX/0Iiakh1GbEu6hqsXvZXLBdchQCmulOQgBISAE6iIgAlIXMR0vBITAqCNQFvV4+OGH3S233OJJCcSAJoChUUdNBoRg+vTpre+FLucUs+MJLyIgGKtIz8aIuLSecHCCWEZ+zDnZufo9N/YGfV/CiImRFNbRIiZGTEKCAjEhAlJ1Tat2fxcx6cdO0jmFgBBIEQERkBRXRXMSAkKgEIFeUQ8MSqIeEJBFFlnEk4I8eVlqMvBeI/HadtBkkAJzoht41Im8ZGV4UZri/2JEXNrON/x8Wa+NmNeqe65+E5Ci+UAWWMNsKhf/NmJiKVYQEOp/LK0LYkLKVdUhYlIVKR0nBITAeENABGS8rajuRwiMUwR6RT34nUU9uH2Ix7Rp0wrz+qnJwIhcc801W6NFPcn888/voxtFBARvOddbbbXVWl8v5glEQKqjyR4j3c96mNx7771z+5fw/wzWGBKSV2fSL2KSVwBvqlxK5aq+vjpSCAiBbhEQAekWb11NCAiBBghY1CPM2TfjiqgH6VaPPPKIJx2kXJV19SYlinMhw9t2UE9Ceg7kooiA3Hjjjd5YjZHy1Xa+4eefeeYZd/XVV7t11lnHk6iUxmhFQKpiEAoL5EVMSOfi//OISZjWlY2W9bp+nYgJ3xmifPzJU+aqep86TggIASHQDwREQPqBqs4pBIRAFAQwuEh7wZC74IILfJqTyZ7yO2R1b7vtNu95tqhHlQuTEoXXGsO77QjrSYoIyE033eTJyeqrr972clE/nzIBMYWurAxvVABanAziRqSjl7QyeywvlcuICZcvipi0JSYQJEglfVRCVa6yOpMWkOijQkAICIHKCIiAVIZKBwoBIdAlAmGtBz+ff/75Ps2Jpn/IrSKtS2NBCswxAumKXXUQkaCXBMZt2xHWkxQRkJtvvtkTnhg1J23nG37+b3/7m2P+RIKQJU5ppCwRDE5teruwF/JUuYjm2aB2KS+Vi4hGlXHFFVe4KVOm+P40eepcWVIiYlIFVR0jBIRALAREQGIhqfMIASEQBQGLemDMh93MzzvvPN/HA88wUQ/+JiJCsXndASHA+F5vvfXqfvR1x+MJJ8WFepIiAgJZwriMUXPSesLBCURAmqMJASHCwJ6MNYj25UVMiogJqVw0uOTvLDEhNZCmm0RA8kaZZDB72khKr14mse5d5xECQmBiISACMrHWW3crBJJGAAMeIyyvrwcEhHQVDDSUh4h6oELUZEAIKMBef/31m3z8NZ+hxwfG3FprreVTxShSxnMdFgBTo0LEhWNSGsyVFDJFQOqvCrihfkYDyn4PvhN5ERMigTaoewojJn/60588OScCUmeUEZMwcoITgD+qMamDsI4VAkIABERAtA+EgBAYdQSKoh4YO/zu/vvv94XmeHkp5KaxYJuBVO8TTzzhNtxwwzan8Z+loB0DcbnllnPUemAUYpCFfSNIJ7Kak5SUiYyAQIwwplMaqadgkeK04IIL1jbwY2IMYbeISUhQILshMclrsliXvNclJkZKQoKS0t6PuQ46lxAQAvUREAGpj5k+IQSEQCQEMGqIdmDA5ylcYVQRrYAsYNAsvfTSUTzOt99+u1fN2mijjVrfCQQExSbSZMi5p0ien80gxMgP7y2b18+/yfcfDeMM4xVDWgSk/jZIgYAUzZr9dtlll3mCBPlgndmP/LFBzVS4Fy2dqytiEhKU0dj79VdcnxACQiAmAiIgMdHUuYSAEKiMgEU9IB/8HKZ28O8///nP7o477pjbbZq6DVKv6qaU5E2I86Kg9b73va/yfPMOxEtPDQgGH7UAFMgT6bD8eT7DvRBx4dgll1zyNTn+RkzwEucRE9Jq+mmcGQGhNgXylNJIPQJSVmMx2lhecsklfr8ts8wyc6fCfiM6kq0z4f9M4hcCkrcX+f86e7EoYmLnsH4qiEjkpXGFNSijjaWuLwSEQHwEREDiY6ozCgEh0AOBsqgHxhFkwwx2cuxJvcKgIvUqRtHvXXfd5dO6Nt5440ZrhSF35513OprR4UnmD+lc/D8ExMiUnZxjieLMmDFj7vXAgUgJhljWICQqxAiJCcXGZhhyvTrGYNFN4hHHkEadC295SiN1AkIDSvbjCiuskBJsc+dy0UUXuWWXXdYttdRSpfNjv4UpXPYzf+cRkzClq+5eNGJCjQpRyHXXXXeuA4KJho6IXsXvMfZ/KTA6QAgIgb4hIALSN2h1YiEgBLIIlEU97rvvPh/1wPOP5C4qPjYspYR+H23H3Xff7cnDpptuWvtUpFtR64HXGIUhCARqUhS0FxEQCA+SwVVUt8CIOhJISUhOMAaNmEDIsl5qCEpdL7UISO3ln/uBWbNm+SLvVAnI73//e7f88sv7KEjTwX7Li5iExCRvL7I3y4hJ9juRjZgwZ/u/On1MREyarrY+JwS6RUAEpFu8dTUhMCERKIt6YGgT9cC4p84Dwz4rK4rHGdlTiEnbcc899zhIyGabbVb5VBhjGE14binYXnXVVb0EKsXxeOs32GADTxBQwspGQLgW3t42qltgmGcMQlTK0meKeqRwPnClQeJCCy1UGYsuDkw9AgIBWXTRRb2Rn+K48MIL/feItMDYw4hJVpkrS5Lzit8trRBHA2tc1ounTvd3RUxir7TOJwT6h4AISP+w1ZmFgBD4uxeTOo+iWg8iEaQoUYiNUV+UCkTRLzK8q622WmtcibRQiL7FFltUOheSvUQ9MPbxeJPagrHDCBW1iggIpOWhhx7yJCX2qOKltrz+MI0LLzVrIgLSbEWIyFG/gPpZagOjHQJC+iKiCF2NPJJsJCWbVkiqIv/HHJsIMdQhJjgErM4kq8qliElXu0PXEQKvRUAERDtCCAiBviBQJeqBUY9xT6Es3lqMg6JB4zcMabz1bQcF7kQuttpqq56nwkAiegGBwHiH/BCFCQdNER999FGvqFVEQIi4PPjgg1Fkf6vee0hMwlSubMExhuDUqVN9upsRlKrdtqvOpclxqUdALr30Ui+KkCIBYe1JwaJXDiRptEeYVmj1To8//rgnwDb47udFTOoqxDUlJllVLhGT0d41uv54R0AEZLyvsO5PCIwCAlbUivcTozbM4eZ3GOSkM2FwEPWoosB0zTXX+PPE6Cb+wAMP+JSvLbfcsrCYm7qOG2+80ddhYGSSamNRjxBSUkmIbrz3ve8tJCBEeSh6f8973jMKq/HaS4YFx5A/sCAtJuy2nW1qZ/UmXRKTJ5980l1//fW+bobIV2oDAkJ0gWhYaoNaJIrQqZeaNm1aatPz8+H7R7oiJCmvyWIoXZ1HTNgTdUhCW2JiBKXONZMEXpMSAokgIAKSyEJoGkJgPCDASx7DwVSiTGnKXtoY9UQ9nnnmGW+4kc7UK+oRYkK/Dc5L1+62AwleyMXmm2/+uuuHBAnDG4LUq0kf6WMY8ShqFUVASPniT4y+I23vPfw8pINUIiI7pL7lGYLZpnbZNC4wqrqGdeaeOgHJk7mtc3/9PJaoFvOjXopC+RQH3z+eFzQWzQ5TiMuqw7E/LWoSNvu0Hib8DTHJcxQUYdCLmBD95JzU0ZgTpVedSYo4a05CIFUEREBSXRnNSwiMMQTChoK81DG4SV2i0Jvf8TMv9CpGfd6t4w3HY4psZ9vx8MMPe+86Klhh4zWiHRhGECSiHhCkMmOGe+JeN9lkk0ICQsoXUR+iJCmNkICQhpU3IH0Yflm5YJS6bJAmE6pyQVIw3NoQk9QJyMUXX+wlbsM+G6msLd8TIjSQZ6SCUxx8/9gfzLHq4LnCvWWJCf82YgJRKIqYlH2Xw3lwrSuvvNJHZ3kOmCKXHVNHmavq/ek4ITCREBABmUirrXsVAn1AIIx6YKzaixmjm0JvVG5ItyhLZSqbGsQAQzjspVH2maLfo0hFRAXSgEIU92DF8HhQq6aFcX6IFeQCMlMUASESBFFp2/iw6f0Wfa6NocpaZw1B1jhM5QLLrFxwVWIyFggIim38SW1UIZajPedrr73Wp/6tssoqracSEpNsFI9oEMOISZac8O8iYlLU66WoyaJdJ4yWKGLSenl1gnGKgAjIOF1Y3ZYQ6AKBbNQj7ABOVACFKF7GeMQx6hdYYIHG04LEEJloI2VrF6cnBzUlEAIMadLCkACuUgyfvQGrZyGdq4iAUIBOrUjTxoeNQSv5YBsCUnRqPNF5HuqQmOR5qLOGYOoEpE6jv36tX9F5TV6Z9Kawl07X8+h1vauvvtqTU2pA+jmKIiYhMQmJsu1N/oaA1KnzqUpMilS5wudnPzHRuYVACgiIgKSwCpqDEBhjCFjUA2MToztMR+BWKG7Gw4nRSfF2UQF3ndtGtQqjlI7jbQcKPBhApFkR+SiTAO51PT4PuUDSt4iAUHOCWhYEJKUi1i5rBbhWXioXBiIDXEJDkP8DWyJoGKqpjRiN/vp1Tyk3mLR7RtUOhwQyvKMx2Hd5NU+2H21O7D3SEy2SVzWCF95TE2KSjZyk9NwYjfXSNccfAiIg429NdUdCoK8I9Ip6EE1A3YqoAMYknthsnUXTyb0lvCUAACAASURBVIVyt03PYZ+zInT+TQrNSiut1LhegVQzIj0oaoFN6Fm166GSxTFEXOrkobe9z7LPd0lAiubCHMKIidWaZFNnsqlcdYuNy7Co+/uUCQh40jcHxbgqCnN17z3G8cyP5pfIb6c0wv1ICimEg+daXmphNpJXt+apiJgY2QgdO2H/ElPksr9Twk9zEQJVERABqYqUjhMCExyBsqgHfRtIk8KrSNEmaVfUWWB0E2FoO4gyQBza1FFwD9RjQGYgC6gEte0Uzfn++Mc/egLC+fMICEXvRHAoQq9rpLTFrdfniWBRTE0ePl29Uxr0VmE/oZYWptGE+GZJCf+uK8/a9J772Wm86Zzsc5A4CqjXWmutngpuba/T5vNF9RVtzhnzs9leKlVSC7NiDOxHSEpd+eo6xETd32Ouus7VJQIiIF2irWsJgTGKgHn2+ZuXY5irjHcQckDNB3K11HpAPizNCelZXsJtB5EVog0UjjcZRGMwaJ944glvbFOITo+JXhK7Va5jPUWsq3oeAeFakBSwqGuMVJlD02NSJiB5NSBG8LKKXKEKUijPigFossF1G9qVYfq73/2u807jZXOy31MrRYrhOuus87rGmVXP0e/jUu4kz71X/W5wXF4qV6gSF6uvTh4xIbLKoJYmjJiImPR7B+v8bREQAWmLoD4vBMYxAmVRD4xEjHpetqRSUMRt6QNEREizoGYDI7DtQG3KZH3rnIt7gCQQ9UByl6gHBgEGEIpabVNUwp4i3HseATFvPo0IQ9nfOvfRj2NTblhXpwg9K88aEpSwoV1exKQJMeF6RECoX6BIObVBDRYiC0hWx/ju9eP+Uu6jwv2aQAM9cookqnvhklWJM5KS7asT1pbYz3WeEUSZcWrwXDMHEfMyslJHLlh1Jv3Y6TpnEQIiINobQkAI5CLQK+qB14+oBxEJDHiiHtlCYYwg0ixQrWqjfmWTC4u9qy4ZxAiCRDSGVCsMRl7ueMwxgDDQyENvM6jvuOGGG3y/E7yOEBCLEtl5Ud1CaQsyhuxvKmO8EJAiPIsa2rH+RkxIicsjJpDUIoPMCMjKK6/sFl988VSWc+48UHRDBCLVAn4mmrKKGPMzJbHVV1+99TMi3CDWVyerFBcSE54ReXsyj5j0UhOr0/1dEZPkvsbjfkIiION+iXWDQqAeAmVRD1KYMOopyqR4myLuPEONrudEGTCC6LLddkB2qKPYaqutSk/FPRCZID0BAxPvYNiQDW8ktQ90VW/i3QwnYE0NSQ3DE5lHQCBA9DHZYIMNfPQllZHNc09lXsyDfQaxg8DGqCEK7439ATnNkwsGEwZraUXGYfd36xtDETppL4sttlhKsPm5WPSICF+M9Md+3GDKNTTcb9d1NBATSEgeMTEiAQHJEhMK5XGi8CyuOuoQk1AymH1FZJuaMUVLqqKt44oQEAHR3hACQmAuAmVRD152FF1DKIh69DJuzMgnDz1GL4Kw1qKXkhTECIJE1AHvNEZi1nOI8YkBSZFu207RpFfhbUZil+vkEZB+GtNttu9EJSBFmIXEJEzjYi9niQl1FtQSQUAgKKx9KkZZqvvNcE89gsQ8U6mjYd+FNSb2M38bkeB5SJQ5m84FWa6zJ8uIyTHHHOO+/e1ve5n1lNT82jwD9dnRQ0AEZPSw15WFQDIIWKoKLzU89FZkbi8vPPgY9RjXpDEtueSSpS+2mEY+QFmtBalOeYXc3IPJ3TLvXspO5HdTRLzGGmu0Vn+ypoYoXIGd9UYJX9B16hm63BQpG4IpGdHgFHqnIScQT/ZZL+80BuFopNylGnGzvZ1y6p/NEU8/9RWpRpEgJuxJUrAgH5ZaGhITnpN5qVxNicnBBx/sfvzjHzsaq9YhNl0+03StsYOACMjYWSvNVAj0BQGLepiBTyqRGU0QDoq3eeEQxcCor5rSYUY+OdTTpk1rPfcw1Slr1BH1ID0LtSmu9c53vrOn4cd9XXDBBS7G3DCUaaqGwhWpQnkEJFVjRgSk2bY0hST22fzzz/+6tJnQCLS0mTCNC6OwTqFx3VmmWnNk95FC/5kyTI0Ap5Y2mZ03kVxkz01O3IhJVpkrL4qXJSe96p647le+8hV3/vnn+3dCPwgIxP6www7zAgoQK575u+++uzvppJNylwuH00EHHeTOOuss/+znHUVd37HHHtvasVS2P/T79giIgLTHUGcQAmMSAYxPDCm8kby08JqGfTvw8CIdyzEU2/KCq/PS4bwzZ850qMjEKNS1VKdsXxFeUsyTAUGqQnZizo3oBj0XULiCnGFcgWcYATFVohSLglOVk00pApL9gpcZ0GYEks8fpnLhsbaISbbQ2AhKDJnmVGWfDUccBtSHNVWY6uKBm6pyXXjvdVIos1E89qaRFEsvzBNkgJTwXON5ts8++3hHD+SgHwOhEfr+kNZIeuyZZ55ZSEDuvPNO7/Sh788ee+zh308Qb4RPDj300OQaXPYDr7F+ThGQsb6Cmr8QaIAABrh56k2xCUMaTz4pBxR8ExGhQBujnod83cF5zz333CjN/rh2tq8IERZehhAQcvHxRlct8I45N5MbxlOKEZlHQFLJJ89bQxGQujvb+TVGRQ1xg0UWWaTyCbL5/FZwjCFoI0bPiFQbX9o99kthqvJCVDjQMMThkWq9Q9N9GN5+kSADe5L3BEIQ1H0stdRS/vnGs+y73/2uf94iQBITG4gpz3mkrXk/ESXMi4AwZ5w5lsqXqtR0hW02oQ8RAZnQy6+bn2gIZKMeoUY80p2XX365f+hzHFEPXgR1oh5ZPCEgnIcXVdthkQakbHk5UpPCPE2JqO48zznnHP8S5cXaZoRyw6Tj5BEQFMEgd6huxZAkbjPf7GdTVSNKOQJiPSIQYmgrYsB6VJFmhZhk07hIocFrnR04D0iTSdV4hnjRI2jNNdds3Ycn5nchPBdpp4huIC5R99nSrzllz0ud3axZs9z06dOjCH3kERP20W9/+1uPBc9cxEAgBwwcUzx/qaU7/vjjo952LwKC02TTTTd1Z5xxhtt22229oh1EaDTqraLe9AQ7mQjIBFtw3e7ERABDHe+rpVyBQtjNHIMKmVi8Tyhc8UKLIX1KChb5yYTV2w4jSBh8hNr5m+hM03med955vqC+LTnCI4gRQFd1jMS7777bG4WQEQxEXtIYXKRpkVbQtvN6WxxFQNoj2FUKkRGTbOf3sMs2+z/M5Yek8F0hRSVV49kkblMk5LY7UPuj8SniEqmOrokcAiA0nD3kkEN89JnUV/7m+3DKKadEhakXAfnSl77k06yof/na177mn7+QRKIihx9+uH8Wa6SPgAhI+mukGQqBVghY1IMHOj+HUQ9ObKkGRlBi9MawCeOpwsBffvnlW90DH77vvvvm9vUgckFdSRvPJMWUzKstObJ+JxAt5mg5/uYlhOgZCSGiRFobBmNZwWdrwCqegJc4OKBsltJIOQLSFQEpWg/2VlhkbASFeYXD9looz5oXMel63S0lMeVO7dQjQEKo7Up1dJnayXON9FyiakcffXTfIelFQD74wQ+6008/3T9LWZ+PfOQjPmWYgnS+Fzh7iE5qpI2ACEja66PZCYHGCJRFPULlKGoolltuOV/AF6M3hk0a4xajG69Z08GLiDQAQv+MGMpVnAcVrGWWWaY1ObIaEM4JjtwrRh7zthx/PNJEbSAjYcFnmFJjP3edRpA6AUlRhaifqS9Nvyd8zvYchjNF1DSoYw+GxMSaK4ZREysybnPtOp8dC53aiWRSzE8jzFRHl/LevE+IOO+yyy6+JqTfoxcBIRLD85s0LBxJNqjLojB9p512cqeddlq/p6jzt0RABKQlgPq4EEgRgV5Rj7BfBnMnmoByFLULRCxiGficm27jFOlSB9JkhP1HIEiklcRqbEjtA15/IhdNh8mdksLG/DhXngyvFd2S2oaxl1VH4t9hP4k8YhJDHSnvPi+66CIfBWpbC9MUw6LPpSyDmnoRNZE4/mCMMfhu53V9Z98yiCQSpTNSYvuP/4tZZGxr3aXh3HRf8qxhD+L1T3V0KbfM84lnBOlPpD31e/QiINttt51XyEKelyL1cOBU4vsJedRIGwERkLTXR7MTArUQKIt64LklZxfvaLZfRkxpWps0UpvUlEBy6gxePtZ1HS8u4XSMpFjdy5kL5yKNa6WVVqozNX9sOD/ujygIkSNSAvKK0Ms85kWyrVl1pCwxgcy0TalJlYCk3EyPdUGwAbLO/kxtVE0fMmKSrTHh/42Y5EVM2hKTlNfW1pKoK+mVODxSHV2qnfGMYq8fccQRbt999+07JL0IyN577+17ffzv//6v22qrrV4zFwjjtdde64xc932iukBjBERAGkOnDwqBtBAoi3qQI3vrrbd6j2Zel3CTpuV3seoBSOmiGBu50qoD7+hNN93kXyBh1/XYjQ2JzpAyxTXqDMgG84NUENkhwgOZQdGHwvg8AtK0ZiCrjmSGYliEHBqITTzX4ECdTtti/DoYVjk2ZSPVCAjqPxDQ1MY999zjm4eiGNdk8F3LRkzYe2FdUxExqVKXNRZ6bOCowZOOYyHV0aVSF2SMdNqTTz7Z7bbbbn2HpBcBOeGEE9yee+7p/uu//sv/HQ5ryGgpu32fqC7QGAERkMbQ6YNCIA0EqkQ9UCshXI/HH6O5qM4AZSgiAoSxYwykNlHpIfWobGBs33HHHT51BKOOqEfYdZ0XEvm+sRobXnrppV66EhnJKgMP4F133eWVcVCyYh6krBgxwhiFjOQRkNiyrWF9SZjOFabUZJWR+DdrkTUQRUCqrP5rj+lafajuDKlfwDtO/UyswXMmj5iARR4xCaN12X3Xpee+6f3jZOCZRJQr1UG/JshmF0pdOLB4d/z61792FIH3e/QiIDgncJjwjiDKblFg0rJIz/rEJz4RXRa43/c7Ec8vAjIRV133PG4QKIt64CEjlYAHNJGNsqZpFPZRD0A9Q4xBx1yujXHea4RRBQgQL5esoQwBgCARTTEvV5s5It0IkQCXsoH3D5livMAmK2y58RAOcINkWS1NthN6jIZhZXPk91kD0SImZiBmOx1jJKLtT8SrrRpYlfnVOSblCIjJyKYoqwzGEGUcDl3IkRoxyaZxQUww4BnsuzBiQkQQD3WqfUqYMw34+I6nrKaEMwRi0DTSVef7SEos6Wg86zbZZJM6H6117JFHHullpHmGHnDAAf7dsf322/tzvP/97/eOHwapYPvtt59Xwdp55519xO/73/++dwpdc8010aL4tSavg2shIAJSCy4dLATSQICXPi93+5OV1iV1AMOSIkrC5niuaDBYNmKoVoXXIBeXuRalMTB/ij3JWQ+jCnnztBSxGM0DOX+V9DCuiYeROfJi4+WXbSQY1s4stthic3uthMW71rHXCv7L1iHm77MGYmgomiIXc+W+slGTKnsm5lzDc4mANEc2hQJq9h1Ew1K5bN9Zh20jJuGes59TkKjm2cU8qjgomq9Uu092uc40UkV1yhqqtpt58aeJvhMFzxsnnnii22OPPeb+6ic/+Ynv+0G6HAR388039z1KYjnQ+nWPOu8cBERAtBOEwBhDwPp1kGZB5IDaA4sW8NJHghNvFcYjL886nZrbqlZlobz++uu9Vx69/+zAy0WaAwYJ0rV44Mvyx2OmiJEeRjGtedSy82NezA+MmRuRj7yCb4vM4CklxY1oA3/CYzkGcmdd21PYcuwViCpRKup02C8Yi9y3KXKRqodRaOk0/M2Lvl+KXGOFgKTc2R4MSWVk39KYLbXB3sJzz3OK71VYa2KEmP2VR0zYj2XPiFj3y/eCOVRN0Yx13Trn6bJQHoVEUq/YW21k1evcn44d3wiIgIzv9dXdjSMEslEP0izIpbb8XwxHoh4UcZOiRNSjrqHYVLWqCGbSlphXKGUZ1lLgdYcAYNhWGbGaB3ItmlVh0GRzvMGZ9BBe7vweYtFL6Sgs3gf3PALCMcj+siaQlJQGtTBEySwFi/XJa3IHWbFBTn+eIldMydaUIyBdNoBrsle6NEybzC9PpcsIcbb4nb1YREz62TsHBwW1aE1U8ppg0uQz1PYRZcIJ1e9B479dd93Vv3MQ79AQAm0REAFpi6A+LwQ6QMCiHqTy8KLG0MOLSKh64403dhQj4pnCi43BTHF1k0FaEi/1WHnPvCCffvrpuc28+JmoAkZGtpaiynxjdlbPq09BXcoK9uuQuHPPPdd7Sqml6EVAUNzC2E9pQDpJHStLW2DvhcZhtvu29ZLIEhOiTE281iIgzXcJanes1dprr938JH38JM+uhx56qFKRfEhMwvTBMFLHc68oYtL0NqgRw9Befvnlm56i75/DwQM+VUQ+2k7mlFNOcfvss493TvCd1hACbREQAWmLoD4vBPqIgEU9rLldWOuBFxHSQe0E6RY0icJbVzfqEU6/KCrQ9BYxhKhDoZswKWMYHhioRD1I+6k7YtaoZOtTMIjIJQZjCt3LCvbDuVtqGMXzeQSEY4mAkLoQo4C+Lm69jq9KQIrOQYE9RokZh/a39ZKALJO2lSUmZXn+KRMQiDSFrqQWVo3exVyzsnOlLiEbo0g+7J0TEuO8FMIsOalS25SNDJZhPhq/v+6667zTqY7MedN5Hn300e5b3/qWJ7YxI51N56PPjX0EREDG/hrqDsYpAnlRj7DWg/oKur3ijSpLE6oKEUYV14gV0qcWBZUWjE3y5vGy41Fs+gJr2rsj7/55eUMW8B5ClCAgeDypmymSKS7CcebMmT6iQwFlEQGBPHHvsXqsVF3TsuP65eml9if0WNvPoTJSWF9iPxv2RkBQ+Km7HmX33Pb31C9BYKmxYN6pDVIxIYBl6nOjNW+Kp0kV7UeNSjaF0MgJKYRFtU1GUELnTaoNOsM1oyAcRw6pnf0e3/nOd9xxxx3nU7CaPr/7PUedf2whIAIyttZLs50ACPSKenD7GHIYGBhBDCQRYxloZpTH6P6LIUCaE4aGpXURrWkz6vbu6HUtZDbBEkMZoxiFKlKRmqQLmXwxdRRFBCRVg6ZfBCQPe1NGyhKTMM/f0mko4id6RrSMfVPFa91mb9X5LBFHviupEpDUe1jgmKCOJsZzpuq6GTHJygWHtU04SoyMUCRv8tRtospV59fkuMsvv9yn23ZRFL7//vu7s846y0s8N3lGNrk/fWZ8IyACMr7XV3c3xhDgJWmN7KzWwx72/I60K14AFAFTS4AnMSYBySsabwIhL3mMIFJV8JZtttlmUbxmdXp39Jo3JIF6F7yjvMCJIIFp02G1KUR4ighIqg3/wAGlNCI4ozXY29TfhMYhe4cCWxtmHIapXBiLecpk/b4PIyCIK4TNMvt93arn77I2oOqcwuNSqlHB+RCKLlhjT/ajDZ4NeTUmo7H3Qhzbpk/WWbvPfvaznnQTedcQAjEQEAGJgaLOIQRaIlAW9SB9iagHRhlpPni8MIKIMKCCFasoMFs0Xve2uA9IEsSIOU2dOtXLbW6xxRZ1T5V7PB4/DIE2RfLW9BDPJ0Yt+LX16FHfQW0H6wIBgURmjZNLLrnEe1RjdZmPAujf+6GMNgHJuxca6UFiSSPK9pMIjUP2WTaVC1LQzzQRonoYYjT6i/Xdi7WenIe5sf/afE9izid7ri7Vm5rcB99hHAakTBJdDmtMssQkS4jZe10Rky6dGh//+Md9yi/X1BACMRAQAYmBos4hBFogUBb1oBEeUQ+MLIoNp0yZ4q+GIY1UJDnysQph8UySe0932bqDlzQGI6lhRpKo/8DY2HLLLVsb+cyHInlIQxPVl1D+l5QeDAU87htssEHdW33d8aRXkb6FCEARAUm1qLXLNI46QBsByasBAeO8wnfS6RgQSuu8HRqITRW5svMmNYwUvlQJSJfFyXXW1I5NPUUMwkt0gfQ/nCjhyO49IydhtM5IsUVNrH9OTFKMs4e6sq6ELXbccUcvcEIaloYQiIGACEgMFHUOIdAAgbKoBznSRD2IflgjvPAFxu9JScIIaltbYdNHVQvS8L73va/yHXEfyAHzWVIV8Lqin8948MEHPSkhAhLj5ZsnnVtlomBIWgqEw+R/mS9GbhOylb1mWBxfREC6TJeogokdMxYJSNH9EXnKK3xnTRjswdAoDAvf60TBjICg7tYmda/OOtU5NvUu3pA38C5qAlrnXvtxLNFRUhOJvtmzrOw67LE8meqQFGeJCfuvabSO1DEcH101N8WJhMrfqaeeWgaFfi8EKiEgAlIJJh0kBOIiUBb1MMlaSzfKIxi87EjrQQq0V6O8OjPnupAJ6kqqjLBbOC8nvHFhwSbKUhgbm266aZQi4qx0btkcIUdEkEgJA0sMHpofMiiEDRs5lp2r1+9ZBzylGANFBKTLYu8695Jqw7VeEZA698ceyCpymaFoilzWeTsrFVxU+J6yRDDYQNQxbBFWSHGkHqGBxBJtXWuttVo7dyDF2eaK/DsvWhfWmUBWejlt+DxRVRw+pFD2c/AdIhKJs+vYY4/t56V07gmEgAjIBFps3eroI8CDHAMVwwcSEvb1YHZho74yyVpykQnB85KM9QKydK/NN9+8J1jcB7UdGPHkSJMaltf88NFHH/VypTRLJHWq7SC3nRd6FfWckBxZBCnMzYaUEKGpE+0pmn/YQb6IgBBpgKSMZrF33vzHOwEpWjP2MN8hKzoOjcQyuVarI0pRIpj77VKetcl3GrlvDOxUCZJ1uu9nn5dstM72n/XPCdMIwxonSyO0KM3qq68ezQHV67tC2itpWIceemiTJddnhMDrEBAB0aYQAh0hUBb1oM4DAoCuOwa9eeqLpseLCvlXXkDTpk2Lchd0VKcOhJSpopQUXnykhpGGQlE13b2LZCrxFMcslCeNiuv36h+A8fjAAw+42267zZOjoh4pdaM9vQAmusF6sW5FBCRVQx9PLxE21jGlESsCUveewgZ32c7bdi4iI3z/EB5g3S2Vpqvi47J7SnVNbd6pE6TRVDkjspGXyhWmERLdwqHDM5hCeRxQseqb8vYWz1QcYihhffOb3yzbfvq9EKiEgAhIJZh0kBBojoB5WnmpkeKB8WKRD85K0TZ1EnjsrT6hSr0EhhIduDGwkeSNMXrVbISGvXXfzRZoZueAWhDGUKxCeauJIRUgb+DRpugd4xXjkAZdReSIruwQPtLD2g7yxa3XSREBSdUoTHVeo0VAivaCybVCSpgb5BojMCw+tsL3rMe6yve57R4MP58q2bU5pj6/1FLsLI0wJCZEy/m3jbC+KUzlokapTn1TEQGB5NCMcL/99ou5VXWuCYyACMgEXnzdev8RwGjBIOVlgZGK596KGvkdaUDI1uJFhUgQ/ag6eClBQKg7WGqppap+rOdxRTUbGPYY/7yYITsY9lUaw9l9U6xbFtGpcgO33HKLV//KU66ingPywcuWSMQiiyzS85QmF1yWblZlXhhUeCCpMWFd8WJmveGpen1TnVdqBCTcB8iRstc22mgj/9/ZNC5ISphKExqEVmcSwzAs2psp9Hbp9b1JfX6kjvK8Q6CiynOuyjMi9jEmBb3mmmv6Z062zsTqm3gO5SnCQZ6rEhOizosuuqg74YQTHHK8GkIgBgIiIDFQ1DmEQAaBbK0HBjyFymuvvbavA7Accv6fqAeytU28pOeff74PwVPjEGNkaza4D1SxSMviRYZhX6feBPUp6iNo2GbywW3mmScTjKEHMYE88ZJcZZVVKnWGt3Qz1F3aDqIIpHuRDldEQEhFwxCFMKY0UicgKRqBkF32HASkKMJmqTRZVa7QMMwqcvFv9lFVw7BoH6UqeGDzTVURzubHs4RnDfVhTZ7LXXy/e5EkntvZ3jlGUIicM3ieZ5srQo7z9h/X4j31P//zP74OpB+D78lhhx3mqA/iWcl3bPfdd3cnnXRSz8vRBNai2Dj0Uqux6wdW4+WcIiDjZSV1H0kgwIOfB7wVmjMpXmAYyTwo8ZATFUBpirx7oh5tenjQAI86jFgPXXKKMUgxrHhB4QXEE7344ot7w7muN9CUuigazytSr7toWeUqIjLWU4CCVnpxVDXeKKKP1aMEzDBEke0sIiCpFt6mSowsApIyAaGJZZ26j9AwDIkJ3xMzDPmO5RGTOt+91A38VJty2vOIVFRkuiEgVZ8ndZ9lbY9vQpJC4YVsxMT2nynCsQcREOH9xLN76623dueee260prLZ+ycijSONZzjCKmeeeWYpAYHkUxzPs5z7EQFpu6u6/bwISLd462rjGIFeClcYpTNnzvTeJcgJcrVEPdq+3ML+EzGgteaGNNSjPoL5EVEgstBkxFbq4gVDgTlGKQYCUQxejhC5uv0YYvYogVyAFekQKOhQ10M6XSilmWpvBhGQ+ju7ifHX6yo8O0hzyaZyURdmilykzOQRkzwChIFPDVSsyGh9hHp/gucWz79YqaOx58dzhecfBDPVwXOQ5yEKg21HuP9CYrL33nv7JrgM3l04oai/451gf8pSXavOjYiNpfjyjoRwl0VADjnkEPe9733PffSjH/V/i4BURTuN40RA0lgHzWIMI1AU9TBywcMUzz1eGnJx8e5gSMQYofxrjPNZBIRzoaxFVIEXT9OBh4rID5GBpiQmvLb1R8EYg9xQi0IEqAmRI7UMVa3NNtusMI2m6n1DLvAgkl4HMTJvItEv1hwvIpEvkyyOkWZTdW5lx6UamUk5D5+9g8pav1N02Edhx3czDiErNsLmdlZfwppi4NObJ8WBfDhRW0hSigNvPAY+4hmpDqLo/LE6pH7Mk+c37y6iEcccc4wnH6YwaDVOJ598stttt92iXr4KAeHeeT8deeSRHocDDzxQBCTqKvT/ZCIg/cdYVxjHCFjUgwcmP2f7emDQkyLEw5rf89JFzjDWoLeENStse04r4mauzDNGWhe4UKdCmJzQepuBMYa3nuJL0tdIZ2tD5Lhf+orEaJLIvCAYYIdXl5S1bI8JIiM2SHMwf/jNQQAAIABJREFUY5G/7eeieoI2uJV9VgSkDKHX/94ICN7nJuS3/hVf+4mw6DhM5QoVuSC51F3l9ZBoe/02n+c5SOooss+x1PvazCfvszg6EBpAPCPVgYofkbg8QY7Yc4aAEGWAfLBmPOeIjJDCirAKTqCYowoB+cAHPuBwUlDvBPkQAYm5At2cSwSkG5x1lXGGQJWoBx5SHth0Kad4G6UkPH6kX8Ua1B4Qqqb4uenAy0XBJS8zPPiEwWM1NzSpYO6/jbeTYnaiFfzNoE9J2+LQWE0SwY25McANlbM8FSzIDvsGHMxo5G+82WGaTUhI+JkIStt77bU3Uk0NSzkCQvoenuFNNtmk6deuL5+zrtt0Gkd1DnLEHgt7SOQpctVRRGo7cZ4JREBI52nrlGg7l6LPk8qDo6NXv6F+Xbvqebuc46mnnur+6Z/+yT9/29QsVr23MgICIYKAWLf6b33rWyIgVcFN6DgRkIQWQ1MZGwiURT0onsUzhDGAl89ShMh7Jl+WtKFYA+OR+WD4Nhlm5HEODALqKfBOxkqZYk4ULjaVCmZepEOQ1oThBH54/lCuaut5Zp3w/pPnTRpL3cH6QtzwhlN/ghFHioIVoUMawjkSCcP4IhoUDusvEeb/YzSaNzvsiBySk1gyriIgdVfeecdCrPz7+lcv/wRpjxZhyPaQCCMmoSKXReHCiEmb9MuiWWJc8ixsU1tWjkC7I3AeYWwjnpHq4NnDMwNlxX6P4447zn3lK1/xUd06ogtN59WLgOCwYe8gn37sscf6S4iANEV6dD8nAjK6+OvqYwiBsqgHBikvLryjGPJ4/UPDllAxqUM8PGONG264wRuq6667bq1ThsYzsrrMCYPWUqZIbyKNKMag+N6K7uucj9x3jHYK48ln5xykTfF/vHzavghDxS+iDHUG3lGiHuBFHjJRI4yBXgQERTFwh9xVGebNDqMlXMO82SajGaZymYxrlfPbMXjLrbFknc/1+9iUIyApExBLccLR0es7HCoiZRW5LCLHvsgjJm1SBYkOXnrppV44oo6kd7/3W3h+HEg8VxGVSHXUfZ60uY///M//dN///vf9c66f0VibYy8C8vWvf90dffTR3illjXBFQNqs7uh9VgRk9LDXlccQAmVRD4wlXlp4FHnxkyeb9dCTgoWRn/WAt4GhrDN43rnx/PM55kpkAiPF5sp9ErGAkMTK673gggs8gaBfSZURdlzHA4uhQhobo6hRYpXzZo8xxa86XdqJYOD5RiGHVCuIGiSTtacGhJzxoghIDKMmK+MaGo5mNIKZebFD47GIsImA1N89CEpQJ0ARemqD/XfRRRc1TnFijxcpctm9Eu3LEhNIfBWnAF50nDE8B2NIc/cDf5P2bpPa2o95hefE+cRzm2dQv8cBBxzgfvnLX/podNvIc5W5FhEQos3UUNKNfc8995x7KsjRD37wA2fvmph1llXmq2OaISAC0gw3fWqCIJCNemSLzPHmEfXgwRhGEvLgCaVaY8FHGB5PfhW1Fh7qVpfSS7qW7uqkb8RS0CHfG0JWpfYF4wRDHZJErQRkLvS2UhiKwUzxL0ZQm1G3S7vVoWD0cy9InNrLmKZ0REVYBwxAohe2V2yOHINh1zRdrte9mtEYRkv4GTxtQJSy0RKMRgwZDEeIXkoj5QhIyjKt/UpxyksVJCIX7jHruB3KBYdS1OwvIpuIZxAJhMSnOKjXSvE7EWLVZerk5z73Ob9mRH1Hk4CwLmURZPYezz6N9BEQAUl/jTTDUUIgbCgIEcnm9GMMYyxzXDaSkDdlHp4YpjHziglDExUo06sP1bgw6jHui14keJEwrmN5kar2KjEVLuZF+lqevnzbuo1wXVClwhNL2hSpcUWDtUfmEawxsPA4UuAbjrBDexEB6TJn2+aGMWoyriE5MQlN29OQPCJeFjlJQSZYBKTZg4+1pQ9I0Xeo2VmLP8UeC3tH2D7DOcOwGiYjvxj2RBFJb0KlK8XRpXHf9P4RIOE5hLOo32OvvfbyPZd4XnYxiiIgOI1I6c2O0047zXdpJwrCu+2DH/xgF9PUNVoiIALSEkB9fPwhgMGJEWl/8qIeeLMxmDGSqQGo0gSPsD4vZwzeWIM0EIzjIjWesAeJqXGV1TtQhB5TrYt8b64NTnkDgwk8IVL0CiH9q6j41eo2aETYRoKXebAWzA2lmyJPLN5d1o3rEhGiQWNemgmKSBBSNPkhpBhf2QhISoWtzM8MRQwL9jrzDrshZ9W4wLtN7n/dPW8EBEy7vG6VeXbRg6HKPPKOSaXGgnnkEZOsIlc2lSsF8otxTyPRmIIhTdez6HNEJKiBiCGXXja3D3/4w772jPTcfg56etDElecQaV9EO7bffnt/yfe///2F6WaqAennqvTv3CIg/cNWZx6DCPDg46VpxnAoTwkxgXTgyTbVKGQkq4ak66RLVYWOnFy8iRRlZwcpQRjPGAIYzvSnqDLXqhGLqnP8wx/+4F/meGSzg6JGy7eGoJThaXUbaN9zzjaDdcZTTEQqLxfdIjJECUhPsoLHvGsSHSENj5qAIgICScGDV1cwoM09Vvms5ZJzj9nc/6xMMEQ7VEnqp0xwygSE7x11IBDh1EbKNRY8N60GjedRSFJC8hvuMfuZgviuBvV6OE2qpI12NafsdXCekNraRbf7f/iHf/DOIaIM/RzUCkLu88aJJ57o9thjj9zfiYD0c1X6d24RkP5hqzOPIQQs6oGXBw8ML6AwNQdFFLz0eLl5EGMs161BCI3UWNBgBJEGFsrS4s3mWjzI8exjWJZFPcL5lEUs6s4dLMkDD4slwZk54n3vVY+SvZbVbZSlTVWZI8Y2xbrIWIbkIlQIK4vI2HUggSgjUZtSREC4XwhUar0FyOtm/xeJI1juf1aNKysTnK0vaSsTnDIBQYSA9U6RgLCvIf0UUJt4Q5XvQ1fH4BghHZXvsKkEsv+M/IZy1KQP5okrGCnhudaP6BipRnz3qwpndIVdeB2eXZAPiFy/B1FIUuZOOOGEfl9K559ACIiATKDF1q3mI5Ct9eBFiBGOpxoDnmgI0QuiBxCPadOmNYKSdCk8p3TejjXwumNAmiwtBi4RBbygRD1IG6oS9Qjn0yti0WTepDNgJFjxYDhHUhysT0qVc1MIftlll/VMm6pyHo7BgCbdjBer1ZuYvC4khLUOFcJ6nTdMhSsiIJAUUrlmzJhRdYqdHFdGQIom0UQmGJJS1ZNtNVYppmBBQJDbriL+0MkiBhdJvcibqCd7jihmmROH7xL3Y6lcRoJ5RtuA6OYpcrWRi+0yutBkf3TZTZ5r8Yzcdttt3fe+970m09VnhEAuAiIg2hgTFoEw6sGLznL2MUxRbiJlCCOIlAFSgyg0b9OYi4gEaTh08Y41TBWKInRT5qGgmqhH0461dJfFMIglF4z6FwMCctddd/lGgsyRiEjdOo6ytKk6uJL+QcM2PMUQkFBet27UiHvCKIVcFhEQ7p29FLMGqM79Fh0bU3LUZIKz0RLWLfRkZ6Ml7INsbU3KBIT1xjGBEZ3aAHvrEN1LXGG05s13gD1H9KgqGc3OlahcXn1JGJULVd8sYsL/VXHIdBldaLIOJrXcxiFW9bp8b3FmffKTn3QHHXRQ1Y/pOCFQioAISClEOmA8IoCRiAeXv7MKV/w/SlAYRHjuecgTjm87SNmg/wYEpI13LpyHqUKRioBXMCsP22TOV199tZ9frCZcpFswN7DGOKJoktSBJhhY2hRStm2bmFnTRVRkMCaJrjTFD/IBwSASVURAiJJgVNMrJKURk4AU3VcoExySkyIJVwgKvwPTFCMgrCU1QikSEPYxUUdSC7NqbSnsO3AjnRWnSZW+IXXmbFG5bMQkVH0zqeAwahKmC/I+wAGF0U2NRYrDhAZw4vSqTYsxd/DAAXfggQe6L3zhCzFOqXMIAY+ACIg2woRCoCjqYV4xDFxqKkgTwHuIodsm6hGCy4sXYxwveVPPX3g+jDoIDWlYvEyJWLQtzOb89NnAw4YB03aANyldSN4yxzwJ2zrXsLQpoiltSSH3iKSjyYQyt6Ye4zC6VURAUvWad9lRObvWoYQrxMTIiRmMHG9qXGHUZLSVklIlk+DFdw0nAuIKMZ4Hdb6fVY61lFYEG5o4IapcIzyGZxD7KWzaaT/zDGBAhKx3CX9DfHFG9JIrrzuPmMd3mWYH2YHkHHvssT4KoiEEYiEgAhILSZ0neQR6RT3C7ttEPXhhmTc81o1ZtIIXbxXZ3l7Xxcggj9pSW3pJydadP+eFiLUtluYliXedmg8MxhgeT4tOQbbwyjUdobwuhboQzTbeWNLfqBNCDKCIgKRaNzCaBKRo/TB6EFiA2EE0rQ7AlJIg8Fk1ri5lglNNpwNPhBpIe+T7WzfFsen3qc7nqJ1BkAHBhtEc2XTBsPjd0gWz+8xISgwHUpt77zLKRV0c6lSnnnqqQ45XQwjEQkAEJBaSOk+yCJRFPTBuiHpQIIzHi5QcihBj9sIAHB7k5GZTuNq0PgMDDE86HljOgUoLURUK5mMp3mCQQnCapgqFZA7iQRoIL/cYBbsWtaBGo2l6RCivS0SFFLu2SjKhGhn3n9cHJNXeEex9cIiVchfrQZCtAQmVksJoCd9fG/0oSM67n1QFBZgrhJ8oJmIHddTvYq1b2Xn4rvD8whGT4jAZYwQ8iNAYMcEpY8SEGrmsVHBeHVO/7g+lRpoldkEyEU4hOnzmmWc65Hg1hEAsBERAYiGp8ySJQFnUg5chheF4tCg6t3xa+kPwM4XnsUZbCVm8XkQU+Jsu5ZAPDF3ylWPURNh9tulXwssbg5ZoDwQOlStLVyGXv+3AAKAZFs0KUc+qM0j34d7wwJq8LsWmRLrw8LUZnJO1MYEBSyEKC15NJKCsa32beTT57FghIEX3NhoywSkTkDyZ2yb7ol+fSZWI2/0WpTeZIlc2lSusY6LIPUtMIIGxU81wltG/BydR22h62ToTEcd5xDsxhhOp7Hr6/cRBQARk4qz1hLrTKlEPPP28rDFkiXqEevKxpWgB3xSc6kYrePFZkTMvN7z/VqtgKUkoOTWVB85uDAgZUYK6hrJFFjC6IXMmbRv2yIixCSEgEBs8lFUHXmFepBA2SCXRE+Z5/vnneyLXtpmXySFvttlm3tjIIyCpen4pCMa7C4lNabRVwQrz/sPC9zDvP6vGVVUmONWeLqyfGadVZG5HY71TTUU0LExFrGoRP44NSEtW+Y1nDcNqzLLEpKoiV94addkjB9nzrbfe2kfaYykjjsa+0zXTQ0AEJL010YxaIlAW9cADh1FMehCGcl4XbFRkiIpg2McaeMqIVoR9J8rOzUsNzzrRE4xkvPWhN417Pe+88zwpaZqSlJ0D+e146zfZZJOy6fnfY+hhxFr3eKITYeF+KFFb6YQlB1E4bkpaZecDH5P+nTJlik8lCNNSkOGFyLRtOBYKDFBLkkdAUEFj34127nsWs1QJSD/UksK8/9CT3Usm2Lq9hzVCqXa1Z21N5hZvdSwBjbLvWZ3fp1zAz31YDQ2OoqapsvZczCt8h7AweI5bTUldgQUcHrfddptPY4sdXcmu5TnnnON23nln7wRrGymus0907PhHQARk/K/xhLlDjAse7ng4w74elgaDkYExT/4sOf/ILBZ10SW/lnPEUIKyBTDZ1yoF1NwLubcYrHjKIBgY0NnBcRAQvPpt6xjs3LxoMBLw5pcN1MJMxpVaCgrDszr7dh9I1MYYSCTzIiwjDbz8iXqQsgZhIW0tOzcIIcQNYtdmWD8WSJuJGHC+8HqkaWG4ViV2beZT57OkpfHdiLnX61y/6Nh+EJCia4UN78pkgjEWMVJxKJCDX6WvRAw8qp7DvONt+mxUvVaT41JOX+N++llDY/VhecTEBBZ4fmSJCf8OyWSX0dTTTjvN7bnnnj5bgMa8GkIgFgIiILGQ1HlGFQFIBwZ+Xl+P0JgnX5aoR1nBdiwlqBAUq1/g+tRHFI2QKGFoYxz3UmiKlUZk8wkVnYrmCNakoXAsESQIUlEuMsfgZUchKoaxRvfyXgIB4Mw1MfYhb73kdakBIXWNFLw2A6MP0opHEkOBCIj1l7HzmteSCEgMHNrMN/ysCEgxkiYTnE2vCftKhMaiebJHUybYiFuK/VNAOuXoEfOr06k91neQZwWENktMSO0KG3jaXuNYiBJpdkVOtFhzO+GEE9y//Mu/+PTV0Vb/inVPOk8aCIiApLEOmkVDBMqiHmEKUxVj3qaBwWwP+IZTy/0Y0QoiL3mhbO6F9DAMe4x5jPoqHicMcupY8PLHGGUNE8GFqAcvQQx3Ii+9DOqy89Wdcy/SgJoTc8OIYF7Mrxd5o7CShobUlLQZJrFM3QwKOXkEpOv+B1Xvh1QOokT0jUhpdBkBqXPffE8p3OfZsvjii89VScJxkIJMcKr7zDBOlfDa/Lqsryjbd9bAM5QI5ues8ls2YkKaaRtZ8XBeRxxxhPuP//gPnznQ73SvMjz0+/GFgAjI+FrPCXM3GAE8nAkL46WkKJuHoxnCYeE2D2OiDlWMeQOwaSF22QIU1RyEPTPK0sOy17j44ou9qlNbL76dFwMGhRVSsELvWlhPAd5EFqr0GSg6XxlWRb8vUigjDQphAfYA5K1Kp3QKLNkXpI+1GRT+UjeE1xnymEdAUjWoRUDqrzwOCr6zYdqayQRnoyVFMsEWLYmtkpRqpM1QTlV1LXz+QZK6qK+ov/PmfIL3E88c6gLDru84YGxYx/ew+J2IcF0S8W//9m/uJz/5icORlFLktil2+lw6CIiApLMWmklFBMKoR9i12x6OJldLLwse0EQG6nqDqIGgdoGu5TFH1nvPvZgUcK+i+F5ziGVE2zUsnYhUIbz5DDAlLQ3jygrAq77IwvqIGEWx2fuFgGJE84JEeQuyWfU6s2bN8n1K+EybEfZ44cVv6YAhRm1VndrMr9dnU02JSZWwgWWdwv08mWC+R6FKUtiF2zq/891rYvClWmtke9BqxmIKfMT8bqQqFhHeY9H+y6YMWuQkFMXI7jX+jdOkaK99+ctfdjjOIGVN9mPZ2vBdOOyww3zzzKuvvtorMO6+++7upJNOes1H+R1EiLlQp8i8ETz56le/WqlesWwe+n33CIiAdI+5rtgCASviMylNHsQ8wNZbbz0fEbEmfVm52rqXJBUKw8z6OtT9fNHxNDik/gSPO9KneOzxZOVJAVe9JpLBGC14/WMM0pd42OPNx2MGESMtDEyJemCw1xlhehLnaztCieQied2q17j88sv9fbXFjnlcccUVPicbwxEjkHzp+eeff+7L3dSJUisOFgGpulv+77gYXvx+yQR3WaBcHznnHRkMniUpjlT79YRY1SVxkN1sGhfvzVCSOkzjwmEHmaHWbt999/UOHiK8/Ri8X3AUImCCFDgND/MIyI477uhw4O2www5eSZL5n3jiif4devTRR7tPfepT/ZieztlHBERA+giuTt0fBHiY8uDEG8ODEYMZZSkeyjyUrElfVQ993ixj1y3YNTB48ZBDQvAoZRsgNkEstmSwGdOklxAJ4t916mey92DRAQzvKilbZRhg6OOxA0fmlyevW3YO+72dq62+vTWZxKhC9jdMu+Flzn2TzgYWpmiWSkFnqj0tUo6AYPTwHIrdPd6KkUNjkWdathjZoiSWXhPm/KduQBO1tude1e9pl8el3qcELOjJwXOljePEJKmzxIR/k4L7jW98wzubSO+l3u9rX/uajxQTdaiTzly2dqSN8Q5HjRDSw97IIyBEvnknWVSe8+LEI5KGc4fIfb8L8svuRb+vh4AISD28dHQCCJjULlNB0hEPCtEPXso8IK1JX5upWl8HJFOrpvNUuR4EBGMC44UHLsXPbQ1R1Jd4mcRqJEexIfOEwPGw5yVXphrW697tfEQHiAi0HcyNlyT7ACleCGdTshmLvBkBgRRzj0S4+NkalGFEmnSr3T/Y5hmSTe+lKa4iIPWRg4AQwVhjjTXqf7jBJ+rIBPO9YK/Rx6JNs7sG06z0EZ5X7H0M2RRH6n1KwIx0Jda2be1aHv68S6gjQqKcfU6NIe9YjH3rYcK7ixoZUqJijl4EpOg6n//8593hhx/ulQ/JJNAYOwiIgIydtdJM/46AERBesrzM8KBYn4dYxpulIaFqFCNtyB7qViSN18Y6hbddWLxhEBoMjrYDTxfeL6IeFHETGWjrVaJ+BO/VjBkzcnuZVJ2z1cuQdof3D9WmvN4oVc9nL3KIQhtPNpjh1WU/kkYACbZeNOF+JPph3YQxXs3zCDmx4lHmEhaNGkHpp6xrqn0ZUo6A1E2BqbMn6xybJxNM7ZupcVmzu7DRnXV770c+f5W5k97JHqd3UYojVUIeYnXllVd6R1ss4ZFe60AdJI6y448/3qfi8g7jD3vroIMOirqETQjIRz7yEfeLX/zCq3TFiLBHvSGdrCcCIiDaIGMOAYxtUq8IlZOKgwFIrUYs8gEgMb32GJfkjBMihsxgTFKzEmvwMsDIb3tODD7mycBAJtw9derU1tPE0Ea5CoLUNJIChtwnoXYwJOUkhmxsKGLQ5EYNM4w5I4GkJ4AfRmC4J3s1OMvWA5iSkuVoEyUzYhJGTeqKK+TdowhI/ZWnjgFC3DZ1r/6Vyz+BBx/lObzj7KOwt0SeTLCRE0sTLL9CuyO6NJ6bzDRVVbjwXhDPIDWqrBlrk/sPP8Mep9kmmQBHHXVU29OVfr4uASGNGWfetttu6375y1+Wnl8HpIWACEha66HZVEAADzh59kQ9METx2OOlaZvKFF7avPY8fJvmu/LwNi8uBiopB0RW8JSvv/76Fe602iE8hClk33DDDat9IHMUxi+YYrTwUgNXIhakl/DvtoPQPcWDTQmN6fIzD6ILzBNCEiPiQ0SC+69LZkLlLTAiDYzieO6Rxox5BARSS8SOPVXFUxc2JwsNybC+BDJmhMQMybppN3yXIHZtCWzbfZL9fMr9LFInICiuZZ8xTWSC2VNNpFt77QVSKPmO0GA1xRFDYKDf94VDh3SjvH5SMa/NnoHI7rrrru6QQw6Jeercc9UhILxHeWaZzDvy9RpjCwERkLG1Xpqtc3M7xpJrHyo2QUZiDTOaqauo0k8ie1284bzIMATotM1DnMgH3jUMahSmYo02PUvAz9JJmCMpRHjd6a5OQTWN1toOyALNEusSmqy8LgSO3HHmS1SFlK62o0nHe158kF7ui9QElGL4mZxp9gtRozwCwufI3YY4Ydg1HaxPtkgZgmJSm1b0npd2k3dNEZD6K8H641RIUcmJ9eR7XfX7EcoEhz1M8mSCwz3VVCa4K+99/VWd8wmeL0SKUoxu2T3xrCH60e+aBwgI1/jKV77i5W77PaoSEN7PW265pVfmOueccxyp0hpjDwERkLG3ZhN+xrwczNiKmSoVAsv5L7jgAh/ehUDUGRb1MO8RRr0NjANkMumxEWuQcoFsMGHyqoMHPfm8FO7hjaTQnHQ2BvM+99xzfbQB47rt4FoQGl7oIRa9zsu6Qg5CI99y1iF2saJIddLXwIW0P1KWIL/cj0UyjGRRSwJhzSMg5OaT/060JUYxfoifyVOHBqT9zO8YVvQepnJB2rmnPI9523Vv+/mUIyAxVIja4lP0+Vg1DGVpgdSGZeuV+HdZJBopcoqYkV5NcaS8tvZ8xqGD8yOGg6jXGkBOSZv9wQ9+4PbZZ5++L1cVAgIxfv/73+/7gfzqV7/y6VcaYxMBEZCxuW4TetYhAcHI4oXWpr4gD0yucd5559Uywnkwkg6F4USBuXnsw/Nj7EFCNt9882hriEIJRnHVc1KLgJeP2hmKGAldZwtSISC84JZeeunW8zQsITkYHr0Gx0Ko6OeCBGRet/W2KWfh9auSGbCCEFFIjuFE+khY38Ha80KEsJKSlUdASOvDY0eaVt1eKk0XATzxFloKl/0dFr1jSGJocF9dFL1XvZeUCQi1Q+DWRga1Kg51j+tnX5cqMsEQ3SwxCWWCUVXiuRLj2VIXmyrH91Nhqsr1y47BSAdD3i8xUmR7XQ+nCU6oH//4xz4Nq9+jjIDwe/qBnHHGGe6nP/2p+/CHP9zvKen8fURABKSP4OrU/UHAvL2cHcOQcDSe51iqUjZrCMhKK61UKc+WtCqMWQw+1F3w9OepzBBxoN6C8HEsFZqq52RukB+MexRU8ox7u3ciFoT4Y3gpLaJCilevPF3SijDyeen1ktfFwMJjHyONrQqZsUJzCAeYETHKjjDKQ8Qsj4Bg/FOAS5pWDKnoNt+uUIULyU2w5/6s6B3jOisRzL9jFL1XnXfqBCTVXhajUURtMsFhBI49xfOZwbPO6pWoN+I7AgGpW69Ude+0OQ4nARFKHDApDpwH1OjxLIohEtLrHmmoyvvsN7/5jfvABz7Qdzh6ERD22Ec/+lH385//3B133HFur7326vt8dIH+IiAC0l98dfY+IBASEDP8YtUrhNPFo81LspfSCIYcRixGHKk3eKUslSnv1jkOI5toRSxjrso58b5zXQwEiswhFr1Uwwjxk/vLsTHGzJkzfdQgr2iS9aTxI4YT3lPWspe8LtEeXozo0LcdvWpysoXmrG1RTxgMd+6RuUM+8wgIBhmNDyHLbeWD2953+HkIKcY+RcsYjGHBuzXBs+PNiAzTuPplRKZMQFLuZYGDg6hXrL5AbfZankww6ZU2QpngsL4kZu+luvPnO0raUapF8l0+R3i3IZrBuzBm2nB2TY488kivPAnJOOCAA3y94Pbbb+8PI92K5+rnPvc5993vftfXe+y5556vW1beqf2OCNXdSzq+NwIiINohYw6BkIDwM5EKvDSxVTAIc/NAK9Jax5NHDQHGJ94y0ovKohp47knf4GEednRtswh2zrymieBDihZ54RiNPMirpP+gWoWXMpbOPPU0kB7UosIRyusS6gfHsr4jTWpeivAFFwzdbBFjWGjO3iqjRtDWAAAgAElEQVRb2zBlj2PzCAjqVSgA8XJtqqzWZp8Ufbas83O2SNkIitVhZY1Ii5yU1QKU3UvKBIQ0HRwNKTbTS1nFie8JEWscGzyPsl24Q5ngkJBwbFcywakXyfezliz7nSRiu9lmm/natX4SWhxT1DHmjRNPPNHtscce3uHEe6lo4DSL4ZQqey7p9/EQEAGJh6XO1CEClsPOJYuM27bT4UVEqkzWyAg946TjUKxdtVkhcrmE+EkfiqXaBRHCIMo2TcTgpdaDmg8e8Hj0qkZdqKvh3mI1C+PlAMEIvYpZed2qKXQYzJAQXoxtR1YUoFehea9rWZoZe4X7tGaZYZQJrzRSvdSJNO2H0vZ+8z5fRkCKrkndS1hbgjHJHzMi8WJnJYIxIqv260mdgPSrE3XbNe66S3ud+faqXwhlgsNULr43NiB92dTA2DLBXUnc1sEtPLZXP6Gm5yz6HO/WD33oQ77GMFY0PPYcdb6xi4AIyNhduwk985CA4BUh7YV6jZiDUDwvvFCOEQKBUY/31yRYy6Ie4Zz6odrFC4m50geEl3OY0oQRSKFsXYMXQ5k8aMhVjBFGkzBCqONADYy0Na5RJxpkER2aT7YdEBnORx+ZskLzsmtRuA9hI3WNe+RPSPi6zN0um2v4e+6ftXjPe95T52O5x2aL3s3DHdYCQLyzEsF5kq4pE5CUu3mn3KOE5yYGPs+kqvLmJjtte8nISb9kgnmfEK2NHVFv/eX6+wmQWGaNN9hgg1rPzSbX//Wvf+123313X3NX1UHU5Dr6zMREQARkYq77mL9rXj4mL0pBHiktFDnHHEQVIBfk7IeytRjzGM1NIhgxGhxm75F0IQgDTZkw5EjBICpSNaUpD7M88tUGW4uoQBRNXpf0Loz1OgSOOVQtuq8yX4umsJ7g1qvQvOx8JlpA3VAeAWHPgkMd46vsmjF+H5OAFM0HPLISwfw7LHrPdnrnu0KKHGkVVaMmMfCocg6imJCoWBHCKtesekzKPUqMhOPUyRNzqHqPHMf3KdsPh3/n7alQlatXaiDvFKK1PJvKFPvqzDXmsZABnlVE0cvSVdteF/Wrfffd19cU9aptbHsdfX5iIiACMjHXfczfdUhAMJYJw8duCoYePNch9EzUg5+JsuTJ1lYFtG1X8LzrmBQx8ySPFoMeg7qNxwoPL9576hViDEgi88KoLJLXrXodCtZJMyEC0tYwhYAQjWFQ79Or0LxsfqYcRrpbHgEx72/btSmbR93fs2f4E0NVrM61s5KuRlBIHTTnAufDUCUaZ1ETiH9d0lpnXlWOTVkpKeU+Fv1OQ6yyp8J+OCEx4VliNSqmZFhlL3R9DAIcPLOoI+z39+Coo45yBx10kHcetH3Wdo2Trpc+AiIg6a+RZpiDgBX58qswUhETLDz1hLshHkRYMByt8VzT61i/iLpdwXtdz6IqMYxouw6F8ngS6VnRdmBQQkA4H4pi/GnzMjPVL2pA2ngArTM5a8LalhWal+FgtUikb+QRkC71+8vmGv5+tAhI0Ryt6B2iSRoW3z0825Zyk4JyEsW51IfFEmmos15lx6LQReplrPTJsuvV+b0pOHUtRV1VJhhyyzMfJxNN/vql8FYHs+yxRIBxnHTR/fvb3/62O/744x1S5P0mO20w0WfHJgIiIGNz3Sb8rEMCQsoBOebIBcYa1FVAbDAarSFfjAewybVWacpX5V54WRKdIbWBlyaeuxjzjIFpWIvCz0jP0jCy7eBliJc3T/WryrnDQnO8oeydGH1ZkKpkDSBYeQSEtSe/nFRBFMZSGV0aNHXuGaKJTLJ5eq3oPVsLEBa9Z9O4wgZ4da5ddixRV4hR7LqzsutW+X3KjfRGoxlnL8xCmWC8/MwPlSkbRIFNgSsVmeCmohFV9k72mP3339+dffbZvgg9xnulyRz0mfGLgAjI+F3bcX1nIQGp2s26CiAYiSgj8ZDHOMW4oUA51oglG5ytSaFDdyxSw72S4sTLmLqSJgNjkXOgdEUtCkY+nmvqadoOzomXl9qAunnJ2UJzjAvmGaMvC/KiRFFIhcsjIKmmd4wVApK3b/g+EWELSQmGZLboPSQm/My+aWNQpUxAUi6Qt6gjjggM+tSGSWUTPYJ8lMkEZ6WCq6oMtrlv3k/U+DV9Nte59mc/+1nv7CEiriEEYiMgAhIbUZ2vEwRM5pSLkQ+LV7xtSJqXI2lXvIRMLhaVJIzTmKNtl3GiM0Q9MLKskJsmeDF6obz6qnODg87ddtstDlKDslbdwcuR+WEc8iKntoIXGGu2zjrr1D3d644n6oORVVfKOK+jOSk+RHvapnMxSeudglc8j4BYgSsRNdI7UhkoYLHPU9PQz0ZA6uCV9WxbfQn/zyB1LxstqdNngn4u1Kak2Kwu5fqULiVk6+wXO5Z9QnodqafZfklZsmvkJJQJJmUrrCuBoMSWCeZ9x7sqRjS5DKOPfexjnuz06r9Rdg79XggUISACor0xJhEICUgopdrkZvBMW9SDYlciCfyNYUZ0JUZ6TjivvJ4YVeZt86RzNfnnFN1bTQoExDqcVzlX9pjhYef22WfI/fznQ3//1bB7+eUBN2nSgFtgAQq0R9wb31h8ZkjLfPMNu+HhZ/2fKVMmuSWWWNAtuOCQe/ObR9wzzzzoJk9+3q299gruLW8ZcQsu6NyKK84hO3UHxAgjwWSHyz7fq6N5ryaOZefN/h6pYQr/IRhckyhd1iNKmlZqCjvjkYDkrR0GJKmKeZ3erejd+kxkO71na5ZQnUNGNsXeCClHZ5Axh/Cvv/76taOXdb+PTY5vEqExmeBQ5S1bs0QqYDYKlyc9XWXOXXa632GHHXwmwBlnnFFlajpGCNRCQASkFlw6OBUEeOibN5MiWnLFUUWqm1ZBvi9RD14YZsCbsRHTOx7ihg4+xguGatVBOhTz5CWXnSfngNQgadvEILrqKuc+8YnJ7qGHBtz117/s/vu/h9xb3/qgW2yxW93kyRu7iy4actdeO+CefnrADQzMmfEyy4y4GTOG3WabDXsi8dhjT7tZs25zjz/+qps6dQU3zzzT3DPPDDjSqZ9+2rl77nnMPfXUbDc4uJi79dZB99JLzhMbCMgGGwy7z3xmtnvb26qhYb1UMGLKurqXdTS3Jo5N0rmysw2bNxYRENYJrzlpaakMir3J8abWIqXRJgJS5z4g9lk5V75n2aL30IC89dZbfWSvyfetztyaHJtydMaiozgPKJRPbeDcIOWI9KaqzWWL7qEfMsFcq8s+L7xTEdX42c9+ltpSaT7jAAERkHGwiBPxFkICYqpIdfL4MTqIJBA9IUxO1CNrzMY0TsM1osM616qiUoNn1hrvYQAR9cgzusNGf1X3A9koe+455O65Z9A98YRzp5zyijPV3f33f8otsMB97stfnu5PNzLi3KOPOve3v8FARtyf/+zc5ZcPuauvHnAPPvjS32s8htyKK87nKJn5wAecszprPnvyyX92M2fO69ZYY3H3j/84e+7vXn6Z6w66004bdM8+O+AjLXvuOdtttdVIYXQE0giGM2bM8IXteaNqR/Om6Vx51wz70RQREFIZlltuOU8WUxkTnYBUMSDDqIkVveOoIBIZdnvvV9F7nb2ScnSmyx4WdTCzY/vd5M9kgrPRklB6OpQJthoTnv3mGCOdlV4mVd4fTTCwzzBXmh3y54c//GGbU+mzQiAXAREQbYwxiUBIQKwoGQ9ulY7aRBOoUeBvjMEiWdi6qT5Vgaza5I+XEvMkb5reEnjOi4oc8b7TILFqM8aZMwfcl740yX3qU7PdKacMua9+9VW3zTYjc2+BqNLBB7/qdthhBbfFFiPu/vudu+uuAffEEwNunnlGHA78ZZd9zt1++42OiAQ4LrfcCu6GGwbdzJmD7sILB30EBGJDrel73/uI23bbP7pNN+3dbfuGG5w78sghd8stg25oyLnNNx/2c5w69f/Qtb4n5EDndXiv09Hc1pgu4G0llkNiWURAIIqsZUpdlq2vAKpiKY2uIiB17hmjjJx/K/TGi89+DOsA8jq9ty16rzNHiDANP/lOpjZS7m4PVqNFkPJkgtlXpAwyiOxbGhdRXX4mgt7PfcVex+G10047uUMPPTS1raT5jAMEREDGwSJOxFvggU2OPaOqEclnULei3gNjk6gHHsyiYZ52wvG9jquLf1nfklC+FgOHeeYZ2uF18XpaJKfXfJ5/3rldd53kXnzRuVNPfdX/vNVWGPnDr/mYNfu7+eZt3KqrjriFFnLu3nsH3NJLU88x4h566Ek3zzw3u2nT5rykkCS1ccMNA+5//mfQTZ7s3E47Dbs77xxwp5zyrP+b6A01IBCL//f/hudGQvLm/Oyzzp1wwqD77W+H/Hy59qc+9apba63nHYY8haJTQ2binBcjqNPR3NK58PJR99NmkPpi+6qIgJB+R/QDEpLKEAGpvxIQfoQEzMgPi95DRS5LE8VxYJGSMJWrTR+bolkzN9TYSJ1JbXTZRK/JvadGkNg/2WgJzywb/ZQJ5j3EHtpvv/3cN77xjSZw6jNCoCcCIiDaIGMSgZCAVCEKPMSJJuA94qFK7naZZCIRCAxdlJtQvIk1rMN6nooJ3nsMaNK/qBPAy1XFSEH5hrD86quvXjjN//7vQfftbw+5b35zttt+e0jHkIN/ffvbs1/3mbDZ3/e+N6+bd94Rt9hizi2xxMvuppvucw899LTbcMM3uo02WsHPD4Lwq18N+pSs6dNHPPEIi9bvuutud911D7vVVtvQ/eUvzl188YD7wx8G3XPPzakrede7ht0OOwy7Rc4+0b15wSG37Nd3fd2cLrnEuWOPneTuvnvEvfjiU+5DHxpyn/vcG32EpVehea91Yz9A3mKQTCJb5I1DyIoISIrGYYqRBtbM5pVaZIa5VVlHDDjrXWIpXPydl24TpnG1VU1KkeTadzBVwQObX6rpiOEzjAgXjhf+hGSXfZXXEydU5Sp754XX4VzUKhL9+Od//udYrz+dRwjMRUAERJthTCIQEpBeRMFqKCiy5cVONKGobiALRD+6lnONoh4b5r0n3E5+L4pKVQdRFQYdhrPjySed+8hHJnnlqR//+FVH7echhwy6P/5x0P3kJ3NkSbMjqw61//5DbmDgWTc4eK8bHBx26667mNt444Xcww8799OfDjkiK5Catdf+vzSu174073ezZj3mlllmbTdpEkQGid4R94Y3OEcR/Be/ONndd8tzbuCZp91z7o1uUfeYW2aV+dyWH1/cR2jIJrECeNbl9NMvdtdeu76bNest7sUXZ7uFF37M/cM/3OW22+5ttTqaWxf5XvUkVdcAZS4iVqussopDqQZjk6hKaFxCUlJLjxEBqbrC/3dcGyM/TLcJvdthuk1WMYk9xN6qIrKRYpqfIUfPGWrakNBOcaQ+PzBjfUnhzEZR2VekAmYFFYpkgq2+pIjw8l6lYeqPfvQjhxxv7MHeP+yww3zDX1Iaef/tvvvu7qSTTnrdpUi5hgjRlR0SSxR5zz33dF/84hdLHYmx563zxUNABCQeljpThwiYd5FLGlHA+x92mOZBTNSDkHVZDUXe1GN3LbdroKCDHKX12CCVDIOV8D/KOhiwdRViiqIqRx456H70oyF3+OGvuPe9b84MfvazQXfiiUNu5sw5KWx5wwrw6a3CXG699XZ3yCFvdMsuO+R23HFR96c/zedmzRpwSy3l3C67zHZhgIiicyMLdu4zznjEXXHFI+6DH5zuSK2CL6Gu9fjjAz6N65/3eNJtvscy7luzv+4WffUvbtHZD7h/d193Uwaecc8svJz7y9BSbtrU59x6q93rdtzuIff04ONutbXe7XOkb7/9TnfrrUu7Sy5Z2T366GT3pjfNicDsvvuwJ1u9Rlk9SZ0tzUuUPcMLnwgIaXPWJM9kXjkfL3zW2YgJ/65iWNaZS51jU0s7sbmnHAEpMgLr4J49ludAGCkxQ9K82kQ4s2lcEJWsV5uGmNS1pSR0YPfaZRfvJmuR+vy4p7pKelVlgo2Q4Hwi8kF9CZLhv/jFLxxyvLEHRJRsBBwyOM7OPPPMQgLy6U9/2h1zzDGeCKF+SL3diSee6Pj/o446KvbUdL6OEBAB6QhoXSYuAiEB4QV93nnn+agBaUv8jiLqO+64wz9E+f+yGoq82cXqWp49N/PCuEL6FdUVSBIvCQrIeRg3MUazURWKxnfZZbJbeeVh98MfIn87ZxakMX3hC5PdZZe94iMRRcPqaiB1RI8wqhde+B3uoIOW9bUde+0122266WuVqqiXpE7kr3+lJ4hzSy01p3aEcfbZj7pTT33OPfDAip50LLjgiPvSl151227rnBsedpNXWsmNvOMd7sjbt3BPD0xxX1/oaDdw443u9Hl2cv/6wufdsm/4i/viHge5y57eyF16x4bugb8u4R55YTm34MLDbscdX3S77bawW3TROTf54IPOHX30kLvkkkE3ezZRoWG3776z3Uorvf5uY6XZsVfwinM+ImzWSRnjMPR4s/akrPF/ocxrGCUxQwCDs4uRKgFJtTaFNYGALL300v5PP4cVvWc7vWeL3sOICc8TBCtSJCAoD7LfqLlKcaCKiKhJF13Gm9w/zw0IJk1neVe0GZYemO32Tr0HDi2eQ4i6YPBvsw21gKv651qsekicR7z/qFfCYcPzLi8Cwn6ePn26+8xnPuOOOOKIubdMWtgPfvAD31eGuWmMPQREQMbemmnGXhZ2Tn61DQgIHahJWzLlKMLU/F+VGooiUC+44ALvpYmpKMNLmD8UsRLyp76EB3sb3XkiKNa5/IADhtw55wy64457xU2fo6Lrx513UhQ+2V188Su+B0evYcXZzg24Bx54m7vllne6qVMn+2jHL3855Gs2UMcKxy23DPhC89mzR9zs2QNuySVHfIrWCScMuT//+VU3adIzbued3+ze/vZJ7m1vG/HF7RCVSVtv7Qb+9Cf3yq23ul+sdrC7ar73uMNf+LR79cAD3eSPf9zN3nZTd/Y5Q+7A5w9wy7zhXnfsF//JvfXtT7r7n1vZff+2P7jfXTi/e+wxrjvg3vrWEfe+9w27j3982K288pz5/fKXg+7HP0ZqeA7x2XVXSMuwJ2DU3PBCxwOH16/JCFW3WEMUtWx/Zr3TYY+GvPoAjIFsU7zQ6436TROC2uu+SH1g/xDtqpMj3gSrOp9JmYAgp8xzYbTUzEKvdigRbMIc7JEw/c8ISlektmidEQDB6CTlMcWBgwDVwXe/+90pTs8Lr+DoqJuiW/VmePbgcCItiijDb3/7W+9Q4T3FnmNAbI877ji31VZbVT1t6XG9CMj+++/vDj74YP/ODIUViFbxXv7a177m/v3f/730GjogPQREQNJbE82oIgKWM83hdJjGM4MRTsoQD+gYheMYpxAFiEysQdNEws/ouhPixohpa1Tefvvt7oor/uaOPno9t8kmw+7gg19bWE4dyMYbT3a/+c0rrkwcBy/+5Zff6M46awH3+OOLu623XtB96EMjbt555yCA+Nihhw65VVcddtttN8fI5/+uvHLAPfaYc3ffPUcFi54h06cP+6L3KVMecb/73S1u+vQN3XzzTfbqV296k3ND++/vhn74Q/cy7GiB+dwl0/dxP3llB3fCTse4kVeWd7N3+YSb570buoG1XnFuLefOOmZr961XDnRLvul+d9wX9nLzf+YS5968vJ8DfU3OPnvQnXLKgLv55kH3wgsDvngeIvKxj832hInoyFFHDbmrrhr0aWIzZkDSfu+22OIdPi2q7sBbCuFlLTHyWEdEC3hZQzCyBn1Zl+psfYAZl9mmeNmISRvDUgSk7qo7T1pTS3OyHhOIKuCIYS9CaENSaz0mLMrG35DabKf3+ohU+0TqBj7pseCFwl6KA2cHxICIQIz3W697hGRvt912Dkww/HnH8KzjD5EKojCxRi8CsuWWW/ooB8+p7OCZvcYaa7hzzjkn1lR0ng4REAHpEGxdKi4CGGWWooBXCOOtjnJUldnU7a/R65zMDw8gnhxGDOlXzjM87Nzuuz/ne3CcfvobXkcwCBStv/5k953vvOIWXXTA8e8pU0Z8/UaYhgWWl176mDv++Bfc8PAkt/7697mddlrpNVK3dDa/4w66ojv3m98MunXWGXH/+I/Dvq6EehO6pWPwb7vtbEd2yuqrj/geHnlNHQd/9Ss3affd3csXXeTcaiu5yRdt5m759Cvum88d5H71Hzu4ka8OulcuvsgN3H+hm7zdN52DZ3zZOXeuc/976pbum7P/1S2+0PPuqF+81S28/oq50N93n3M/+tGgJyZPPDHoGyouvPCI22ab2W6PPYbdzJkj7rjj/uacW8AtscQk94lPzPb9UCxlrWg9IRi8kPEMYuxBeHlRYyDgPS0iIBSqQ5QhnnVGWbQkNCyNnFSNloxW74Oy+085ApIiAQFP9h2GI+mcVg9XpccE5DlM46pT9F62juHvcb4g/ABJT3GgQIhja80110xxep4c4cQgYhsrFaroRs844wy3yy67OL6HOOH6OXoRENKrcCqa0Eo4D9aJqBCkSGPsISACMvbWTDP+OwK8KJBN5KXGixePUGzPVdjboQ3wvHRvvPFGX2SK1wZvzqabburzXtuMWbOc23ffyW6bbR5z733vVY5u8OGAnGyyyWT3yU/OdssuSwRgwBvhFGq//e0jbvnl50QOTj992J1++lNuypTH3Ic//KqbPn0ZH+rnAR+qcV133YCPcLzhDSPeqD/rrCH/85ZbDrvddpvtu5lDToiW0Oyba2DMU3SPVPDchn+33OLmmTHDvXrkkW54t93c0B8PdJNuO8Q9ccCCbufHT3MXHLW5c2c4Nzy0rLv7i//llr1iGzf0pZfdAI3PD3LODTr3ys8Xchecva77xsi/umlTX3ZH/XR+t+hGvSNV3OuZZw66k04a8M0OIWOzZ7/g1lgDUjKvu+aaAa8OBjHbbLNh9+lPv7YJItiyhnjkMAaQSSYlAW8z60v0iPSSIgICBqTG8Lm2I1a0RASk/krULQSuf4Vmn8CQoz4FIYuyiB6GW7a2hH9bqg3PpiwpySt6rzNTUv2oX8lT66tznn4dy3cYRwwRhhQHsuEY4ki4QxL7OX72s5+5vffe2z/v2jZpLZtnLwJCpJG9TOQnO6hPIQqNY09j7CEgAjL21kwz/nsNCOSAhw9FbBh+eIF79cFoAhwGIzUkhHmbDJMBJvWAhzg9IiBOvEQoQqdIvsnAcP7Yxya5Rx8dcKee+op7/vk/+zx+wtVhOtfOO09yM2YMuw9/eNhdey154c7/uffeOSQBY/v++190K6xwi1tllcfdu961ivec8kI4//zz/YvYih2R2v3mN4fceefN6VL+zncOu222odHgoFtvvTkkhB5ZqFzBq4h8cBwjbPg38NyAW3DV5dzLO3/EDRw1p6hw0h92dkN/+a0bPtC59zx8qbvsmA2de8G5kf0H3dmHn+Lescyzbtl7vugGvvCMc68698xhy7i/vOs4t+yya7lJe+3lLvz1M+5rA4e4hd867L57/Hxuic3ePvfavfBlfU4++SJ31VXreknfp54a8IcTJaFOhsJ6Up9pgrj33q+65Za730c6iC6ATdi8MBQCKCIg1kE7ZvpC9v7qRks4nrxvyGFbQtxkLxd9JuUICCmfRLF49qQ0WEuitniNm9Q0WRpXVo2L56sN6pzCFECea1WV3PiOQHyaPk/7jTXF16RNplrUTIoxc6RIvk3NYBUcjz32WF9fAWHsd22YIiBVVmT8HSMCMv7WdMLcEQY3BiAe+uuuu8577mJHQDgvD8cmKQO8tK0gPpQBNoUpZHibeLHOPHPAff3rk9znPz/bF1QzrHEgERB7Wey335CPdhxxxGxfDH799XOM63vuGXDnnjvollqK5n+3uxdeuNtHj3jpGiEyZbHll3+XO/30pXw3coxxlK0gHkRTcMBBMmg8iKzvKqvMISF5w5pFLr3kem7FD77HvfTGBd11R13slltuxBHdn3TN3m7o3pOc+zfnNnjgUnfZDzd0VJe8fPpb3EtLf9LN+6//6tyrz7qBp252kz6wr3v1zj+7O37zG7fi+uvPudxDD7nBj/yju/jyed1XBr/jFpwy4v7jqHncOz5UHmkgf5iUFSsoJkryq18NuJNPHnK33TanuP2llxA9oLniS27xxYfdTjvN6/beew4GNkjfwEOJV84ICLn1ISGEeGI4cL0uR17vCaJyoZADezHbt2Q0CUmqBAQjnQhIigQE5waN6nB00Kgu1siTcoWkWNF7tiO3EZTs/kk9wjBa38+q60QqK+8U3h11pdqrXsOOo0fHkUce6dNn+10jpBqQuqszPo4XARkf6zgh74KXn2nk81AmfSC2ugrn5UVbR5YRA8VSw3hJYNiHMsBVOrfnLSiRhY9+dJJPaaKBYGj8ktKFZ4yu0Vzz8MMH3axZg+4Xv/j/7F0HeBTV/j2zJT0hIYQQCCEk1ATpTXpvCvKnSBGxomJBQenSEUQpoqhge/pQsVOVLr333hJaSAIEQnrZNv/v3GXIZrOBtM1bce/3vYewszN37szO3HN/p5iDBm/fBj76SI1Tp8wajRYtUmE0noS7e5IQ2NNOVJko8zgLF6rx888pYrLcu7dG6DxosUvwQjBDahfBQ7NmstB6sM2fnz8I4Rhu3rwbLT/6EmVP7cPW7y8hMUWLihVlNGokwy3zKLRb2gAzdGgVsxM7F7cC4VJm+Hy4DfoEuv37zaWbuy25fXv4HzsGw759QPXqoj/Hjkm4/fdxtP7saRyIq4jxqg9QtqyMz79Ro2Ln/Cf8dFDjZDI/S1W64qxbdw6//RaCM2cqITVVC4r6WRmhcVaXLkZB1XJ3z3Eiyw+AENByUkbNiCM0AhBO9OkoQyCvBJkpvytb2pLiJnUX9LwdHYCQRmdvbnxBx0rZrjRFypZJ75ZULmvRuyWNi89FPp8IkEw3OVUAACAASURBVByxseLt4+NTaI1WaZ1LaRpGTJ48GcuXLxfPhuKapDxofO4HQFiFmT17ttMF60GD+A/83AlA/oEXzdll8wjwoaXwla3D/UpqjAq7X65AkmbAVaP8BPF8QVNfwapKQZ1MvvtOhQUL1Jg1yyBE0tbNMjhw7VpPfPyxGn//zYBDCT/9ZKZMMZzP19eES5dicONGFIKCXMVEgKvenFAToGzerBIAp3t3IyIjN6Fu3arCAYVi7qNHVYKaRH0EKwPVq8uCemXZ2EfqPuiQlZ1tdqFihSM7OwPXX30WNX//E1c/GYrs8K44l94bWhdJpKeT7pRx6S949x+ENlc2Y/vX/SDXeRemsBehnjoV3MA4ciTUFz6G+vw8yNm3YfzWC5rtmdBt3ITMR5riwAEJqakA7fHVG9fhkYWvYH9qbYyVPhSi+0+/VCG4a14gsnHjRlSrVk2cJ0FFVpaZQqbVyuKlR34xBZ+kXCm0B1ZJfvxRwtKlaqEloe4F4Llm4LXXXPHii3qoVDqxcmj58nZEiof1qqqSqGxJw+F/K65ziuNXSTpx2fq9EoCQuti+ffuS+jmXyH5KMouhRDpksROzg91eQXHy8/Mr6d0XaH+27h8+8wiOlGZLW0Kwa++J7oNOwNIm+0Hb/i8+V34TpO/ae6xGjhwJmmZQ72bvY90PgPD4vJ/zywHhM9VRAe3/4h75Jx3TCUD+SVfL2ddcI2AJQMhh58OZD+aSbJahgQ/aL1enSMPhw/p+Pu1K9oS1wNvW/m/eZNVDi6Ag0pyYpWG7FzduJOKvv07BZGqK+fO9MGqUUVQ76tSRMWCASVjecnWbFAiu6HOyXaZMdcyfz1BClUgM79/fiPbtTUJXQlvdCxcOoGVLfwFCrl0zVxh4fA8P4Pp1cyWFWR6WjZSv8ePV8PKi/a1Z7B4WBlQ/NA1uw2ZBGgfgLgY4K7+OhJB5qF/fhGvXLgkdQqvp0/HY5R+wNTY0Z7e3b8OldWsYlz0LTdRkQc1idUQcebkWWAlkLfsVBwK64+pVCeXKySIMkenszY9/Ce/p47FLboHRhtnw8TZh0RIJIT0i7+1fyXoJCAgTOSZ0+gKykZFxGirVdWG3yv89iIawdu1FfPGFF86erSTCFiWJdDUjNmzImXgpL3NHemEyl4H3BV3ZOAnMr1kndROUcGJpr2qJowIQxWmqJMLgHvRMKezniksSny3Mb3CkxvuHFCdq6rjooQBcZRGJ/24r6b04OU6FPX8KnamBK8ncp8L24X7b03WPFu5t2rQpyd3a3NeLL74oKvmk9NmrkeJFfSCfIVOmTBFAo0+fPuJwvXr1ugcsKIanJoVJ6HxOsU9MQn/55ZexePFie3XPuV87j4ATgNh5gJ27t98IWAIQlom5Um3tAlXco3MFnPumY9X9JmbUozDhl24ddKC5Hz/XlsDb1r7nzlVh2TI1Pv1Ujwfldh04kIYlS+KwfHkEKItg0B6F55xPkipBjQirOXfueGDTpiY4ccJDAInBg40YOtQcynfrlhlksIrAz/btO4P69d3Rs2cV4RbFakp8vNk1i5N7AhAl6VzpP79LJyna8hKcULwdmBWF1i9EAv0B6THzlgqIuF5nNS4km/NbCIoiR41C66OLsO3gWcCYAZNfQ8CzqjkvJPELoFOqAB+WzXCiE9TztiHxvU9wrNFzov/u7ma9isg8MZlEFUW9cCF2+3TB6LRp8PI04dMlQMhjdQSfPzi4MtLSqguHL50uEefOxcLfX4fevUMRElKwleQ9e6KxZo0RRmNtQVPbssVsSzxggB6ffJItuuyIHPiCAhBb96g9qyWODkAsrW6L+5wpqe9zUs9V69KwaS1Kn61tqC1F75Y0Lluid8uqSUFF74XtIyvTdLWjZs8RW2kmyQ8YMEAAA3tmbHCcr7C8bqMRYDz77LPiE74zP/jgA3z11VcCFJFdQIA0ZsyYYgUNO+I1/jf1yQlA/k1X+yE7V66c8cHEFhMTI6oP1i5QxT1lrjhx4t6lSxebZWhO3qgTYV84IaFj1IPK1Xzprl+/XlRJ+CC1bpcuAU8/rUXDhiZ89JExVyYFtQ40pCFNiiCBf1+7VsJXX8nYulXCe++loUYNL0ElorbCx0eH9eujsGSJH65dC0D58q54/nkZTz5pypN1wSoHbXbJ3OC+1607g7AwdwwYQH2IOWyQIIX75uKqLRdIVh62baNoG9i7V4VyPtl49/PKcIm8A7ye92qcdnsRVz36ipUu0tE03TugzcG52LXYLC6XJQ0MDT+FyaM7XJqEQHofgEvu/RhDn4HpWg9ohgxB5th3kfjyWFHRKVPG6nhZWVANfxWaX3/Bzgp9MDZxPDzcTXjl1eMI690Yt2+H4+TJOJhMMXB1DUCFClXRtKka+eUTcuwJtjZtUomqiSTdQlhYFNTqZli0SI3Vq1Oh0UgIC/PGpElZGDnScO9eKWm3tuLc57RIZmWG4vmiurJZH78w1RJOLLkibq0t4USDVTFHo2AVxuq2ONelKN+lsQB1DKR3Wjq0FWVf9vgOMyyoh6te3XZuj3JMPk8JQqxpgIro3RYNkPdRcYXZzFBh9YMgxBEbfw/8vZa01tHWufbo0UO8z3755RdHHApnnx6CEXACkIfgIv5bT8ESgLD6wElUSWRrWI6nLXcpZUWG9CwCFE6cCSYKY4tI3QFfwtYrbePGqbFtmwpff62HtVESqxAMASQIoFB8/34V0tOB1q1ljB8voWnT8xg0yB9Gox9u3GAquAHnzunh6anDK68wp8M334A9AgZWP+iURap2cLCMs2fPISJChd69qxXoFiNAYZWEWgwmjtNhePDCFijrkoKy887b3EdUwLsIbD7GPHGQTdC2CkDrc+uxa0krMwBhvUNSwVB3LjTvjIQUBKBT7l3xM2P114Hdu+HSvTuMzz0H40cf5TkeseqZMxISTt1Ew3nPIOD0duyu8Qzeufwq3FyM6Nv/MmL8qqJ27QpwcysvqjsMUrRkslArQ8BBoEYQ2LChjI4dqa0BTp68iEmT3BETE4IPP9QhKEgHLqQyIb5bNy8R8Fir1jGHsyG1BwCxdbELUi2hvbFCwyFVkSCExgqO1DgJ5kr5/WiW/6v+lmZORFHOkRQnVolJaSxKs7aYVpLeFRognyO2aFwPok+KZ40Du5spY1WaQY605aarJKsOzuYcAXuMgBOA2GNUnfsslRHgS0dZEbMUYRcGCDyoowxpo3MRV2EVfjw5q6TScIJE9yTatz6o6mF9HOYI0HVJeREfOQK8/LIWjz9uwuTJRpvdio4GVq1SicoCRdKdOxvRubOMZ57RoGtXPa5ePYuDB2shOdkF3t4ZePzxE+ja1ZjLXtfWjqnboF6E9KP4eFnoF8qXpwj7hLDWbdq0YI5NV6+SYkTbWuZ+AM2+fhURp37H/LevYHDEK6hsXHaPesV+6LQVkdb6ENzL+JmBUWYsXNuHo2XUznsAROmvrPYAEjIgzQLAKshdLYzJOwL6TnsB1d2yyNmzcGnZEqYuXWBYtizX6ZI+RpDF82X1Jv3QOXT6egjcL53G+lpPYWr0CLhqgOHDjSjXqR4qV5YFgDhxQhLZJ3QSY1Wlc2eTCC60Tkvv3j0b8fEGzJ7thYwMGZ6eetSta06CX7RIg4kT3fDJJ6dRp84th0paLs1sAVv334OqJZaTSsuU94JMKh/0+y7K544MQPhsOnz4MJo1a2b38LiijB25+1xVL0mNhSWwtaRxKaJ3PpsVYGtJ47IWvdtKkS/KOdrzO6WV1E4wRj3GE088gfnz59vzlJz7/hePgBOA/Isv/j/91C0BCIXVLO9ToFaS1AMlwZuiP9JTqDMhD5euSKQNFTUhlqV+ih2rV6+Jl19WizC/H37Qw1auWWYm8OuvKuFQRTcnajvoanXtmoSFC1UiPM/DQ4bJdBuDB2ejSpUrcHVNQu3a1XPZ6/J6s0rBqgkBDIXpbNw/qxakEdGxihN1ggg3t8PCZtY6NIzbUahOChL7Q7DCFhVlrqBQ91Hhz29Qde6bOPvLIVTrUR0fL8hGe59n0MD3T6hgQJpbUxz3+A/SpHChJ6lRQ4Zr1hm4dmuAlhd2YNunbaHR2MgU+Q8A6jrueg0Yar8LY8S7925lgov4w/EI7t4QWWERSFqxEeUrEN1wvICDByUBIui6FR1tRHZ2FGrGr0TjRZ/ALS0N+zqNw6i/e0GSTWjfVo+Mmg2FloWgg2PBKhSNAXju3A//x/9+7DEKa1MRERGFXr3qIj3dhBs3jGjQwCQS4dmeesoVa9ZosXjxQQwa9OB8ktL6ff6vAYhtUCwL7RUFtwTqChVHceLipNLaSYngpLgUnIKMeXHD/gpyjKJuw+cgF0xI0eGk29FaaWosSJWzTnrnfWQpere8h/h8ZxXdEStbynXkwhebvU0sCEBYoaf4e9q0aY52Gzn785CMgBOAPCQX8t94GpYAhC8WJgBz5a8k7SdJadizZ4+wYCXw4HEUy9birMCyrxcuhODjj8MxbBhzJPJOtlnx+P57tZj0UlTOGIyTJyWcOydj5Uo1oqNVwmXqp5/0aNzYBOZZcGLGiZhir2t5XxA4kMLF6gTF6aRZUaRN+hUn5qRt0cKWFC+CE7X6KLy8DELQqjQKvNmHuDgzAClfXha2u9SNEMQQgARcPoCnPm+HfW//iLLP9URQUJaoGH3zjR9q1zaif9+qOHXG7R4Q0uslREboEBHTFqpJh9A1ah3+M+tZVPS7bna6UrkBJoq4ZUgJAD64WwVRA/oGn8AUNuxe/0j9okVwyrVU9BxfH7KXF1K370fZCi64cAHYulUlBOJqdQaMxosICUlCaKgBKSkV4fbLfnRYNQomtRbbOk7F7G0toVGZ8PH8bNQc3EBcB1aK4uIoipTg7y+LMRw4UIuXXjKicuVY7NiRgJYt6yE9XYabm7kCogA0djIiQoO4OFccPJiOagVjttn9p+2ok1ZbGhBHqJbYK+yvJC50adHpitpXLrzQbEIJ/Szqfor6PU6sef1sJb3zMzaCWGaBWFK5COYKW+Uuah/v9z1Wt1i5odGJPRvHggtkM2bMwNtvv23PQzn3/S8eAScA+Rdf/H/6qStBWDwPxdqWk+UALlWXUKOok7QBZcWVE3u+nIrTqLHo2TMFWVmuWL3aNZfGgJWHtWtV2LKF4mWumhvF5xSaf/KJWkz8OekvX96E2FgVNm0yQKfLFOJmrmQTfFGAagscUbdAmpWPjyw0JNQ4cILMPyl8v3iRDlgS3N3N1KPk5KPIytKjVavG9+hG3O7YMZWYfBPEMJwwIkIWInUBbqIS8Pz06jjWYQR0k6bBaLyJCxei4OVlgo9PNjZtqo+mtRJRxWs/vP08kO7VHucv+6FRpc2oHd8dmA/0j/4F49+ZhYZVj4ph1tf/CFLqeWiiPzNTuL4AEAmYWqqAMnVgrD4CpipDxLYECKdOGhEWJkGfYUD9F5rDU3cHyXuO4tilMjh7Frhy5TZiYpLg4uIGP78g3LiRgPBwA55/viIqBZmgmjMHmg8+gBwUhMP9puPtJZHCeWvKu5m4E9boXvWIdC4GNi5erAejKs6cicHmzddQq1YLUb0JCNAjPJxUrRzfrjNnzqFdu/owmdQ4ejTNZsWrOPdWUb77TwIgts6PzwEKlrnazd+r8qe9qiWODECK42hWlHunsN+h4xxX1m2ZbxR2XyW5PasifH7yOcpATlZPCFJY7WKzFL1bVk1Ko+JmeZ40GGCFnyGY9my8x/ke/eKLLzBsWM4Cjz2P6dz3v28EnADk33fNH5oztgQgBbW2LczJc1LDkjyrIHwpsQqiJvepGO2331SYOVONgQPPo2vXpHv0JlYfWO3g6nqnTiZ06iRj9WoVvvzSbOVau7YJo0cbGfqNP/6QMH++Bjt36nHjRhxoAUyvfL5ESVcpV66a0CsQFFB/QLxEATbF0Kxu0HiLAIQVETplserBxT9+Roct6sFJ1dq+/SJSUrLQokWkCB1kVYQT+IMHVQIEERgRgFSrJotqRlKiCT1H1EBSUC1sHr0SSUlXERNzB97efqhXLxipqYfQInATguNmQSWZdS6ZUhC24k9EBJ9GlZghAoAMu7IEfZ77A93rrxfb6NpsgOzfAupTU6G+9BUQkwTpI0CmHkRlzgTR1/8YpqBu0G0bBq/0HZAlLeJd+mGffiG6ftQHbueO49tR+/DXMQ8kJpqg1fqga1cP4Qh28uR+sepJZyqeN8/pdrwOtRa9ifJrl0KuXx9H/28S3pxdGQYj8NarmUiq1gjTpmkwb54BffqYV065Yn/s2Cm0aNEFarUMrZZBhMwDyQEg5lyZFPTp0w7e3jKOHEnPY2VcjNurSF91VN1AcV2wWC2xRcGxJVgujLakNNPGC3tBrUMlC/t9e26viLwdMUGe5604iFF4rSwyKaJ366R3y3vImgrIaklx3xP5XYfSCkpkJY2Vqp9++gm043U25wjYYwScAMQeo+rcZ6mMgCUAUaxtWZouroUi98XJDx1HtFqtqK4QfFA8WdRG2tOgQQzaApYuNeDMmSMwGIzQ6ZoIYTkpTO3bG7FunRp//sksCrpamTB+vNGcZXG3HTsGPPecFlu2ZODSpVNg+CH7RQtgOsy4u1eCTlddaDQ4761QQRZCcoIQrtgzaI8hgQQM1F7Uq2emT1k29pXbHjlyDUZjKqpWjRAAhPviv5OCpXy/dm1ZrPLHxEio+UZ3+CZE49f3D+PchRjodAbUqVMBoaHlEBOjgmvGr+jn9fRdbyvzpJ3/n6WtBn2zn+CzszHkBcDYmPdR5/9O4unW3wuEoW/2PeSKPQGVFupz86A5ORH4DACZYc3uOmVpfSG7+EOVHpXrXKKzH8Pnp5aj328DUf/aWswb8CNq9G6F7OwyCAuThYvVoUMHxYSBWpdz5yScP28GYEajhJAyd9D8k2eh3bIRug5dsLr2aHyw2Fdcn+HPp6PN241EpYqNuRVcQaVlMxsnLwQflgCENppcaXVxaYb27b0EhWvv3nSblsZFvdcK+z3FOcnRhMvFBSC2xoG/bQZyWtu7WgqWH6Qt4fdJyyRgpaWsIzWaZlCoTM1aaQb4FWQMHF3kXdDfQUHuIRqhKKCWf/KeosakuDQue4j4bV076q/4zvvrr7/QvXv3glxe5zbOESj0CDgBSKGHzPkFRxoBhWbBPm3atEm4SnHlpqiN+zt58iS4kkiaAF2umJRdHGCzeLEKS5aoMXeuAR07yiIob+7ceERFadGrV3mR2v3jj2rxZ2ioLBLJvbwkoa0geFAa9Q3du2vx8883cePGMUETIPCoSOU4IDQwyclByMysjkqVZFH1oKNV3bom0PWSVQ/SpJKTzVUOujyFhOQdKVZhDh/mdjHIzExAQEBDAVbo+hQbK8HFhQDNTOFq3tysI0l/czJ8vvsUX0/Zg7jMNPj4uMLbuzoCA11FFYZVhdDs8WjpNs/mpcnufh7qS99A88r7eD92DFza6TDqsRwrXZNfE+hbroD6zHuCioVYAJ8CmGmugtyvHQ7+E1cT9aj9xS+otul37J7yJ+480loEFbIadOHCYWHBWb9+I1ElSojPROUqaqSkuYhrJapEGdHQDh0K05HjWO77LNSvPI+Fn7rCKKuwYFYa6r7QCHHx8ULr0qlTJ0HZsAVAaGJAmgxFwl9+qcGYMW6oVcuEbdsyxDX5XzRHtW4lAOF4tWt313HAjoNTmGoJFyWio6OFzqocb24HalyQYEW0bdu2dluFL+rpOrJ7GM+puGYM1qJ3pWqiZFVxkcPaIph/LwxQ3L59u7But7eGhpV/2vAS8DAfyNmcI2CPEXACEHuMqnOfpTYCnOQp4sGtW7eiUqVKDwy5yq9zfHlz9ZCrVJZOKMzsUITnhTkxAoanntIiPNyEJUuMYvK/bJlKOExdv87wN1e4ufmgdWsTBg0y4upVSdCaSHWipW2FCkDTpma7V1KjWrTQYsaM89Bqz4mV10ceeSRX9ghXZa9dK4+srOqiYsFGwMAqB2lSbAQldL2iCxZzOqwbheWnThGAqHD16k1otfGoVq2eADQUq7Mf7BfBkhJ2GLBjBTRPP42dHyzBOa9KCA4OgVYbiqNH1YIKxnMimArOeBeN5A9tA5AeFwH3itD+Xzt8dbYprtQNwMwnJ+VKPTdW+j9I6VegSjps3sfHAFoCciMJmQZfeGju2Nz3do8FCIp8TKSd69+bB68503Bg1FLENf8/URnKzDwBX99MNKldDtlbn4VP9j6RPxKn6oUTHksQ2cBXCMnpVlbx6l7MvPIMpPh4GMaNw7mqXTHiTRfoDCpMGRuLjEgdOnbqJCZ/ikW05aonJ65cpVZe6s8/b3bGiow0YvPmzHxzWgpz3xV2WycAsT1iBVnpflC1pLDXorjbMw+JwakEbcUxyShuP2x935G1M+yvop9p1apVibmpWYveFVBCeq/y3mJlRKmSKADFOpST/eP2fMfVqFFDvOfs2biYxSBCLqjwPeNszhGwxwg4AYg9RtW5z1IbAUsAwocmJ+asChSmcaLIVUO+vBmSxWqHpbiQwklWQx6U3mt5TOo8Vq5UYdEiPa5do6hcJfQT6emSsNCtXz8BPXqcRo8e5tUl6i/oIEVqEwEIrXUJIggeCAoefVSFQYNOoHbta+IFxFUwy4ktt1m+/ARiYrwBhAlwQMYYV/kpEi8oU4TOW6Rp0VL38uVEGAw38eSTNVGrlixE6qxk0HkrLU0SoKSRxxl4t26C46++iuvdu4uX1a1b5UQgIV+YdJxiGjhT3dOur0OHrEHQSFmQzP5WoulNbkjT1IFXw+FQTVyLVSe8sbFyI3z2XO7odFnlCkm4Yd1tVwF8CcjTgfSac+B1fmyunBEewQRXJHU4Cy8/M32O1Z/rc75HnYXDceaVuTjSfDiys8+jWmgsWqe9ClV6dK5bJ8WjPVQd/8L/9dEKwf6sWWbtiur336EZMUJ48BoWLMB5bQRef02FjGwJ82akoNHwptAT7VE0b6EBoZMa7zPaRSutaVMPUamqWdOEP/8sfRCSkpKCgwcPOlx6dmlWQArzvFAAG6mepBWRzsWJpWLvymeHku6u/EldQGkAAtIAz507J3KLikv3KcyYFGRbR6ausf+lSV+jhsRW0rul6N0ylJPAhKCEi0x8v9Ghyp5t7dq1Qvtx5coVu1db7Hkezn079gg4AYhjXx9n7x4wApYAhAI9PrQL45HOVS/y9jl54IOdegrrFze96+kIUhDnEYKMZ5/VivwHsjNY8TCZzJP1Hj2MeOMNk+D7k1oSExMjJgpsFIHToYrUJuoPlKoBhcodOxpRv/4F9OlzW/BybeWckDa1fHkUsrNVCAwMFxNt0q5IH7LFEiFgYTWD1RUlLoDzZVrpMgeE1KzDh2/i2rV4DBtWV2RZcJ8EJ6RysXrio7qDyG7VcK5Re8RNnIwWLWrCRatB9N5duHPtGnwqhSFRaobrN1RCRL9nzwV4puzDgOB3oJWT7l1ZAUVks2je9H1D7LlcHp/6DsGPr5udrZRmlLVQS/rcd8R8QO7iAd2URKhPTYHm7Jx7n5ugwoVy/4EcMkCcD4HfrZtZuLn/ZwQc2YJKc37FuSdGYVvn59G04h9okDrR5t3W++sz6NI3HC+8kNcqWbVgATQzZkAuVw4Jc+di86EkfPNlA6TrtJg9MRENhzeEZJFYSG41J4lcZVUar0XVqp7C2YwUvF9/zSrV372jAhD+PlgxKg0KVmEGnIBj//79wp6aeUDm3++DtSXWE0pOKpVw08Ic/37b2kM3U1J9I0hjVlPDhg3hywecg7W4uDih+/tfgjdrm2mlYqKI3jlkBLVcaFOqJvx7SYvef/75Z+F+RYMK5R53sMvl7M5DMAJOAPIQXMR/8ynwga08nLmKy1VGvuAe1MjLpSPR1atX4e/vLyhX+SWoc9WJk35uk1/jJHLkSDU2bTJnc1y8qBK0pyefNGd8WNOdOBElCOncufO9XRKEUHNAIECQYjRmYuDALHh6pmDy5ExRgZFltQAIdIckcOBCGCfurFysWHEFZcumo169SFHBoECcIXrWjVQq0sFIj+LcmJUSCslZNdm+3ZwHUqMGt0nApUtX8eKLDRAYaHZy4ja0EY67loSgzs2RpvbCirEbERnph4iaWQg8PwDqG2b3KrbL0mCc9PoKoVVV2LbtItLTDWjbshIC4qYgTL8oV9dkWYL8mRpXEividdfP8OeYx3N9bnCvDk3mhdzfuQjgBxfojiTjTlIS4g58Ac/0Y5ARhIv6p5AoNRZuU6SAVQ1OhnprV2hSzPa+uMjqiYSLLXoie3QEIpIZsZ637fLahcZdc7JQ8mxhMEA9ZgzUX34JYyUVNK9n41JsFbz09TdI1fth6ujreHTko1Cp1SJYjxNr8qstG697eLgXmjY1olw5Gd9+W3ogxJb7z4N+P6Xx+T8JgOQ3Hoqdq3XuhFItoZ7EUqysTCqLWi1x1DHj+DjqfaZcO0cFbwq4pUaF7ywCAi68saKkNFtJ78URvX/11Vci/4PHKYxGpTSeC85jPDwj4AQgD8+1/FeeiSUAOXr0qHhgNm3a9L5jwVUdclvpfEOROQV996MrcLVTsWm1teM1a4AXXtCSbCNAx5AhRrFafj9RMScK1Jt07drV5rFJ0xk3ToebN73w/fd0rPIXVKwzZ0iDIggw53nQyYmVDupNVq++gtTULDzySC3xOQXsihbEst8EJ3SyYtmBVRBWBpheTtoXXbaYNUIw5OKSioyMGLRtWxOAORAxO1tGfPxtdP/2BdS+eQCj+kXBpPFEYiIwvPkYPBa2IM8QLTkwByvOvo3Y2AxRPeHLcnSHkXim+Sd5h/NPICvZBZ2jNmLH5Lb3PpdVZXDddx4qJJo96UnhYh8JvuQ5QNaTkdgR+TZc/cJQtmx9nD3rjrJ+Mtw9JEEd4zg1U78FdfTnuY95AzBNqelEggAAIABJREFU1CC5Tm34vnXyrkOXeRMTAZHKHYaelwHtA7JfTDqoVjSFdv5Z4AgTBwG8CpyMbow3vliINJ07Xn36GEKeDEZGZqao0lkndx8/LqFDB0907qwXov9FiyzoZnb8dTvqxNBRJ9PFHa+iVkv4DHoQrYoLKgS5dMFytKZU2vh85r3vaI10I/7PEceOY2VdeVNE79ZW05aid2uNEv9O0PugtmDBAsybNw/MCCoqGH7QMaw/5+99+vTpwvRFoUPTTGHixImCduxsD98IOAHIw3dN/1VnxIetsprICT352fm5drBSwqoDefhcReIkkA/kBzWmz3LSYJkIbvkdb2+tEDNTI1C1qllvYUH7t7l7vkxu3rwpHLtyazlMQgx540Ym/v47FA0amDUE3B8rI5zAswrBdwgBAf/ku5yf37mTiexsEzw8PKHRAO7u5gqHdaPOhItnPHWVyuyWxW2VCT2BDsGJp2c2NBqG9FWEu7sKkmTAnTs30OXYJ+h3YhFe73oW2tBK4rvs14xHG6Kc9mQu4Tj3lOzRCTHV1uDUqShcupSNOrXC0CG7MTyMufUWIoiYx1YBrabtxK6pZpoS/9102we7/zME2kpRaNJ3M9SuZi2GaOcB/Arox5aHMfgbZKWvgkfqz9AgHSnaxtie/SUq1KiBxrdbQrpzMFf/eMgMfW1o34yDNtgL0rjYe65asqSBoel/YQruk3MsXSLUl5cCWfGQvcJhqjIUULtCurUbLts6mLe7ddehi6fXAri5YBnOH/LF1HF+SMpwxbAn96NCn/LionFSabkCvmJFACZPLoNu3QwICTFh5kxzEJo9my1KkT2PV9B9OyoAsRdlTZlQWoYpWmpLClItya/CVtAxt+d2jhp4qZyzLXqkPcejsPsuiE2wYk1vXXHjfaSI3kn7s7YIttYoEQgsW7ZMVGsfBHoLex62tmfuCBkGXEAcPny4eC/yXf3555+L45Mm7WjhlSVx3v/2fTgByL/9DviHn78lAKH4kkJCWytYfKmz6sEHs+JoVdCVHX6P5W7mJNhqNWtqRdWDwmxSfVhhICCggLx9eyZi5/0WwQeBDfnGCg+cD2E+aHlOtWpFYNSoEGGVO2GCUayIkzJFe1xOyKnroF6EGR5NmsiC4nX27DlcvJiAli1bCVBiKzOR4GPfPknkXZQtKwvwwEoNt4+PN1cK2HdqPSpXvo2UlH2Cg8+qEQFewPHjaDRpEnZPXoNdLh2EaD4wEEKk3ia9GTRpR/MAEGP5LjC0XiX41devJ6Ctzxq4XVqYZ1AEWUwHSC5Ay6k5AIT/bEjywukV9XHV1AvB3fxRv+ILub/PUMK+gKlMBagqXL8HprhRdronknYNQkCLjZA8r+QChzxmmmdz7FdNQPsRI5CWmo3lg4Zi4DNaSJV7Qfatm3OczFi4bG0PKYPqd3MT9sBt1kMXuxHeB60Cuy6ZgYicqIXuzZHQTZiAoz/twpRxvkjL9sK44ZcQNiQEaenp4r6kS5Bez5DJRjh+nMGXaWjSRI+3384WEwZ7USGcAKRwD0F7ARBbvVCqJdYp75a5JZbaEl5LUnWoMSqNiWNhRq64NreFOVZRtuWEl/brjz76aFG+bvfv8P1Ae1wusJFeVZhmLXpXqiaKjT3vFd5rS5YsQe3atUE9zJEjR4Q5S0Hfk4Xpj/W2n332GV577TWsWrUKPXv2vPfx77//jn79+oEVmbfeeqs4h3B+1wFHwAlAHPCiOLtU8BGwBCAUrLKE3qHD3ZXou+JQrgqSO8tqB12aCiuq48SbE3BL5yLLHvbpoxGVj379TPjlFzWmTjXA29sc5vf33yoBHPi+aNXKhBYtzGCBL5MDBw4IsMSXCQPquALn5+cnKjPUo3z+uUqIyH/+WYXu3U1o25ap3WYnKlY/qDWpVs1scUvQYC1stx5F0q2U79Pml9URUq8obdFqZUHvsqyCBAcn4caNPcIZjMAuWJLQ8MkBiH5uKva2HCW+c+2aJFLReV7uF+egYsKUe05UnNybiV4qwD0IsWWH4VRWc3Q2TYR051CeSgRkUkzMK/7WAEQ5lzM3BiJ+X2V06GVl53sawGpAHms+Yk72uPmbBvdXkBSnQTm/RTnUrbsULsP3fkiPDsDojPkYe/MdhGljYJg2ETJj5yuGQqZIxt8fmn2DoY5dnufmTAp+AweTG6ND6guQYLh3bNELSYNMw0K4vTMVUlYW4kePxsG6dVFLroi3XgZupbpixsgbaDGmKdLSDThyJBuXL+sxc2Z5GI0Er+lo2TIOPXpcFveJsnJJTRL/uzg8b+VEHFUc7KgVEEewLbbOnFBWvO2lLSn4Ezn/Le1hc1sS/VL2wXcEn/MPovCW5DELsy8uWjGjivqxgtCoCrJvRfTOZwAX8Eh3IkNAAbik/vJ9xP/x3cnwzfyYAAU5Xn7bvP/++xg/frx4JzKJXmnUXxJwERi99NJLxTmE87sOOAJOAOKAF8XZpYKPAF+4CueV4IMPUSWJmjaHrCiw9E/bWoq4i+IWcr/KCns6caIa27ersGOHHjdvAjNmaDBsmFFQspTGyf+uXRJ27WJAHeDtnQk/v4N44okwXLwYLVbAre11U1KAefMIaIxYulSFS5ckjBhhFJatFJJ7eMjCnUqh9FoK2816DTPwUT4n6KDVL+lirq4QVZAaNWQ8+qhZgE5hOgXobKSRpaTE4/TpaPH9lk0q4pEebZDdoi22vPyDcOpiZYf2way0BAbKuHzJhIaG11HV9M29884BIZLQbZxLfxo1TL8CXll5KhGKE1Z+AEQBR/tTh6CJ1/e5v28CJIYSPgUgPO/9o6sxEXvSJ8M9ZgkaqcZCjUwY4YHMWrNxWdMBzw8ti1Z1JMzp8yfU096E6kIGMAuQDQGQV1SAdC0FGB0L+Bry0OsS06sjxns6QkMuw/vyRKgEj4wwSI3Muh/DWIXp74D2yy+hnfQuTK6A/G5bmDq2w7XLbfDWKxrcSHbDqOdvQtWyGVzcVHB1lTFwoDvq1zcInc7AgbfRoUP8vQRvJWPEMtxMASWFdcVxApCCP2+4JSeprF46WnI8V7D5rOJEnzkRCihRxMpc5bblxFUQbUnhRsj21vaYQJdEv5R9MD+FvwXLCXBJ7r+4+yqtjBe+U5955hmhJerbt694h5IFwEUyVke4IFfSjcCDwI8BrXPnzhXvay6ojRo1StzH/NyHLy5ne6hGwAlAHqrL+e87GUsAQntTPizpLKVYKvLlypUb2hYWtdmqrFjua/Jktah0bN2qF9oLTubnzlUL690hQ/Jat/K7Fy6k4uuvKXosI1azWrf2w2OPuQpKFIEHJ/UMv3vvPTXeftsoQAOdrubP1+CVV4w23a0oQGXJvF69rrh8WSXcqqjzoBCdVC0FgPC/CUxYSeFn9eubgRIn+NRymEwyDhy4hr17E5CZyepOFQz99HF4mFJxbd0R7NxlduKqUMEML0gTI4WL2R8U4bvqLyHw6puopMpxw1L2L6eroPJSJuhKheTun4zN0Jj/O78KCPdDe10JprxUryPVoPo7CtLbea90WoOfsTumt6CMVQg0IO32bWTL/qgVoUbv3qwuRWP+hyHQ/t0CqpRTwBIAewFMBkwNm0Dffiu0mx+FlHw8z3F1MZWh3hIBOTYWepdYuNQDJG8fGNPDYXKrDbliRci0KysvQZs8EpqfkoF1ACoAxnE1kTF4KxL2xuG1Z4y4keyOYf1uIOLFpjh5Wo133nHH2LHZWLlSiwkTstGtm1FQJciV5ouZ1EJloknArTTLiaYCTPKbaPJ7tLBu0KCBqMA5SnPUCoiiZXA0AGJ+rlwQ1VVO5JRWlGoJ75+iLNbc795x5JR29psTa/6u+DtwxFaaLl29evUSVsnLl+dUfPmc4DUMCwuzy/B88cUXmDBhgrh/lUaGwB9//CFMWJzt4RsBJwB5+K7pv+qMLAEIaULkrfJhxYcYRWvM7igud16hcCmVFesBnjZNLSoBbdrI6N8/B3CsXasSVY933zXmsuFleZuOXVxJLV++POrWrYdz5zRYscIcVsjqAh2sOnWSRR7Ili2SsPJlo2B84UK12N/w4cZcInMCsIMHT8PfvxPi49XCJSs1VRLZEgQZBCQnTkgiHZ1Cc9q9sgISHJxzRlwtPXz4OPbvJwiqBEmKQe91/0HI3pU4u/kSEtI8hT6EAYMEHbT65b45see+2UgHa5n9GALlTbmGSojM73KjrClSRkMDJMdLKFvZnHJ+PwCS3w1ucg2CNDYeEuUhVXK2kq94Q5/xFg5V7YuLLrXg4ZaNkKzF8NecxoYdgfBp2AtegXfQpZ4WLju65XzxZwB/AXgH0L25Cxmxx+F7bnguChdP1ri9DZBaCcaMDNyOj0dZdzdo5TtAQjKkG2mQkpMh8cIRGCkO0XTZ/QrAfkAOd4G+9dNI7NYfe6LK47MPDLiV5o5net5A8IBmGDLUEz/+mIHJk90wb14WWrSwDWr5W1C0ApYiVGtajgJISOHiRJP3o6MCENJB6ITjSM2RxdSkEbF/+enVlHEkiOV1t7xP+N+2qiVKmKLi2lZUbYkj5Gzc7z7iKj/HhVlLjtj4HuIiU2m4dJHGzFys7777rtSGgmBn8eLFwhmSOk0uJn744YdCnL5+/foCGcaUWmedByqREXACkBIZRudO/lcjQHGdQkfh6h+rFawosOrByX1JNK48kXtLAGJLkLdggRotWxoxc6YGq1aZ06+VdukS8OGHGowebUDVqhR6k9Z0WghEudpGTq2SakuBOcMIAwJkHDxI5w8JzDnjn3PmGIUeRBGWMzDwv/9VY+xYwz0AwdWpHTtOwdOzHVxdNaLqQUoVqyoUqrMawjDBGzckUaUpU0YWGSCKYxe/z1VAZo2kpzfCrVvuqLJ5GrqtWogtCw9BE1FDgBdWdjifvnKFCefmpHX+nRQuUtA89SfxaGorqOUcn/oHXYekI/Wxs9xi1A95H8HyCrSYuhO777pgWX5Xdg2ElH2XJ2Zrp8QvOwGMyPnQEDQC8slqSF+1BRfPZyJ85CmUKR9zbwOjygs7XGeiZb2K0O59MvdeWan4EdDPG429DaYi89hstPFdADd1OrKkQGRkPQe/1z+G7OUFY2gokoLS4P/YRag8zTkexhuhMEZ3gKzxhkv9bwBtam4KVxogb3aB9IsOMt0AjCZk+wficmBTjL4yAnG6cmjXIgOL9zTC1m2ZGDrUHV99lYW6dW2DEOshsZxoWlZLrEXMBC4VK1YUeh9ONEuKY/6g636/z1kBcUQA4shialKwKJJv0qRJkYa+INUSWynvBamWlOYKflFOnotXvO/vl/dUlP2W1Hf4buMiW34ujyV1HD4zSIfq1KkTFi3KndVUUsew3g+rHExeJ7WR726lbdiwQQCSOXPmYMyYMfY6vHO//6MRcAKQ/9HAOw9bMiOguHtwUs/JPRs5vOVsxX8X8ZCcmLNi0bFjR5sTs2++UaFdOxOGDtVi506rpG6Yg/umTZMQHHwZ4eFnBOAgl3bLli3iYUu+NqsDBBUxMUzFhqgoJCUBDRrIwrXqyBGzny4rFwwN7NjRnLT+/vtqUYGgAP7mzQSsXXsGWu2jyMhwFdSolBRJCM0JFEgPs9U46SD/mRWUgIAKcHWtg1OntMjevR/Pfdkem178An7PPyXcskizCg42U7YoQK9X14DqocmA1ldIv9NSZfiurwGNKmeCrxzTqPYWeh0XKUvoQSxbVqwXTgVNRlbo6yiXuQLPvRZiE4CYPKpClUF7qdzN5FUDqrTzIlEd75ozOFDJvI2h1kQYIyeJ/1adeB/a81PzfD/JEAb3lrPhsm9AXnH8PjXwmYTtPV7FhjpD0LRJBXh5eCEp1VOAwqBAE1Tr10P68n2o+h6A5GrKBTL0Ffsgq9G38NjWEqqUE3koXPrgQTD9Vg4un38O/YsvwlSzJjR//QXVsWO4nSDjZSzBDrkVmmkOYM6RVujT1xO//JKB4jAhLBOXKaomP19xwuHgKFadltUSGiMUdfW7KD89RwUgihsR3ZLyCy8tyvmWxHfsoWMoSLWE42AdqMh7yPJ+4eo9dWqOVtFSxv3QoUPienLl3xFbQatbxe07rzffT9SBzJpFe0H7N94TdCDje9y6UfvBqs8aBm4520M1Ak4A8lBdzn/fyZDGRPoIaSbh4eFChMnVv5LkjFLUyZR1PiRtTTh+/10lQMH48Wp88YVBCMMtG1dMWd5fv54VmSqYMYP8aoCrO3zQMwiRjRoPVhFo58vGSgOF7KxcjB6txty55P9zOwmbNkm4elUS+2EFg7qRvn3vYNeu8/DxqYusLDchJKdDFnUe+eExTj5p7Ug7RvaFs/aTJ1Uw3U7E469Ww4baA5E8ehp69iwnUtrplHX9utlpqrnXLIRlvg/JlA3ZNQAGjxFQz14F1SsHbN6I18s8j53nQ9G3/FRIku0V/CuqQbhs6oPxU4NsApD87vAsTIS24kmo41YC+wAcugtC7npiGWuNhTFiCs7/9wU84vVjnt3IOglI1wC++jwi89tBw3F2TzCaT5mKMx1fRvzzz6Cq/jOUcUuAR8UIaB55RwQVymcWwO30eJtdTO0eB03cCrgfezWXSxgkNTJabhB2vqoDB+Depw/kwECk/7UWUcnlsX+vCnc2HkaVI6uw8mpjaH1cMXZ7e/Tr74nVqzNEBau4jdWQ3bt333Nfs6yUkJbDSh0bV7kt6TjKhLMgq99F6aOjTliLY4dalHEozHc4gSONyh5ORdb9eFC1hNRXS1DC+yo/m/TCnKO9tmXgLB0SGU7riM0e4NLWeRKAkL5MPca4ceNKZSiUMef727KxL1wEoa30unUsRzvbwzQCTgDyMF3Nf+G5cOLMCTQdpDgR+vvvv4WIkFSSkmrkVO/bt0/Y8PJhaN02bmSgnBkYMANk1ixzSB6rM5b2uqx2REd7YskSNSZPNuD48U1C0KeI+kiLunKFlQ/z/ipWNIcasn3xhUpoTJi3QRDCqgqBBwEIKycrV6qwciUf1ncwdKgbAgPdhE6kWTNZ5HRYt9RUGXv3XkN0dAzKl3dHx441UKaMpwBBx44A//d2DWSGVMfM1rPRvn15dO5cQeyC+sDbtyX431qIivFjcibTrDzIgKHcLGgSJ+RZ5ed3ozzHY/GOPhjU8TYqZXyNwOxfxT6t9SDnM1rgpXnvYc3ox+DlZhZWi3qJpIEk56a4Kec1f+ZI9Kt+G5VG3IQ6fh0wAZDfAqQK5u/yGN+eWYJQ9+1oF/pD7pccq1SSP9zlHPGj5QZnjU8is844hKboUKZrW6ChHqrXcwCUyScS+vbbgHMfw/XsdJu3XXqtv2Gq3hjZJz+C16V5cEMyWM3JemQejOU7Caerw4fV2L9HRtp/V0N1LQahTzVDkzcaoXp1k9D6zP9Qhe/fv4XBFTejx88D8Mwzbli/PuPePVLU+52/oV27dgnuuy3gTgBiDUooSFWCzQjKLSslnHRar34XpW+OCkAUO1k+D5QMn6Kcnz2+Qwolr2fDhorYyB5HyX+fD6qW8Ju2nLhK4n4p7plyIYv3P90SHbGRBszKpb1F8gSWHAfSr159laVk+7cnnngCq1evFs8hyxyW3377Df379xf2wDNn0ubQ2R6mEXACkIfpav4Lz0VxBOKpc8LPqoJCayqp4eDkiw9GCjttuQTt30/7Wgldu5rQqZMW27frhbiTwIh/8oXGZFeDQUJiorla8fHHGtSqdRBdungW6IVHd6o5c9SYNMkoQA5F75yUBgXJgopDQLJtWxY++SQRRmMQ/P01AqiQItSrF/NCzFkhbElJmVix4iKioowICCiP8PAKqFlTElWcY8eASi88Dt/r57Fh8TkcPnoCbdv6o23bu3ymu4OqXV8HUlpUHvAga/0g6e/kmeBD7YG9fn/j9w1qdO1aA2UMx9D0Tpt8L1HPuSsx/6lRqB5kTkvnuRgip0N7evI9QCH+/e4eMrQt8P7bPdA26SA6fHcW0qazkOgWaWEdfyGlDar5H4ekT8pz3FPaoYjU/9dmfwwbA6A6FQpTt25QBS2F9M5lSKEAWOy4mzRviJwGo8YPrscsxCd3+ycb/SF/UAGmqmG4NWQI9mldUKXKozh6zAenTqmEHoc6nYYNjWjSxCgAheaHH+D25pswtG+PrGXLQP7cmjUaeGqz8ebAFLzX5HeUn/ESRoxww5YtGfDwKPrdrgAQev0XlLrIiiNBiDUwUSyxldVvS2DC6klhQs0cFYCQKkKBLFdl6SzmSI394rWhtsyRGvvEIFJWg6nN43ORuiPr+8U6odte1TVbY8NnfFBQkN1cnop7Pfg+IaWNv1N7NlbFK1eujKVLl2LIkCH2PNS9fbMCy8BbAlGCHrIZeC/TGYsOltTnKFrJUumQ8yClMgJOAFIqw+w8iD1HQElz5TEIQFjOrVLFwgapmAcnpWHbtm35akuYp0EQ8vTTJrRsqcX330fhwoVzgq7FVWVyWJnJQf0EReFmBypg6dLL8Pf3wJQpAXloP7a6TLetXr2MiIkxJ61T+E0nqjp1ZNDl9fDhbKxeTQ1IDezc6YNhw0xCrMyMEiWdvWrVO9BoTuHmTS/UqBGKkBAfUXWhXp+OWx6zJiNs9SJ8OiYaZaqWRVbWXrRoUQ61a1tYL2ZkwGVNJUjqgonMCRL0LZbjbEoLrFp1DhUq1EdNj7/QGgPzvTJDPvsvXumwBK1q7bq3zYXIc5Civ0W1rNl5AI4ghWl88NH7E/HUk3MRUDEB0gQAowEEmAGM7BUOVboZ0CjNDGBUWO3+C7r7fA3tjbV5+iRrfaEP+wzSrgRofEdCyjYB1EOyGMZFOVovhwyGlHgQUtr5PKAsrdZc7E96BQd+uIibG0/AkJaGyp1rofnweoisp8pXm8ObxbNbN1F2yly5EqfdG+HwYRUa1E7HwPap+LHvMsQPehNTpphBSFHnwqxw7Ny5U0xsCgpAbF24B61+KzkU1tWS/CbxTgBS+AeXIzs5WWsYlPvFMuWdwCQ/O2kFnNirWrJjxw4x8WYGhSM2alQYPBoZGWnX7tEsgDqYlStXgna8pdV4706fPl3QnemYRuBBS31WPkryfV5a5+M8zoNHwAlAHjxGzi0cfAQ4gVLoIKRg8WHFFZSSaix7b968OZdjleW+aUn7++9qvPBCOoYMyURk5BUMGOAigJCygnf5stnNigGAFIPfuSNBrz8Enc4Px46FY8oUc9bH/drFi8BXX5lF56xoEIAIIXg9E3i6aWk6/PLLPlSpEoHy5cvhjz9Ugsb14osmGI0GnDx5Bjt3puPEiXDcuhUIDw9JhBDSLYtp5oG7lqPBnKdx5NNtOOnWSKzEGwzbUK1aBUFx41K9aulSqLdNgvRYQoFAk3I+2V1PI9noj3XrDiEitCIaxLWGypSaZ7Ju8qgCVcYVvPHtx2gXsQV9m+b40D+zJgGdupdB48DlCLv9GlxMt/L0wRgyBMaLf8BFkwFso7AGwPPmXhjLtYb61g6bQ/ynx/do1rQZ1HuHwC+LIpKcJkCKiz903U7DZUM9IOs6JDLBSI+mPOIDwGRoBZUX7bfytg3x7yKhwgQ0bWqEq2siLqxahUf374fbrl3QDx0K3bPPmpMf2fRJ0MSvhqRLhMknAsaATnCZMAEuS5YgdfhbmOUxExMn6rD8JwPmvXwNq0f8iS0N3sSiRVps2pSZy5a5oPe/AkBYOQxgumQJN0UrYF0tYcVSDK2LSx4KF2k6FKE7omjZkQP1uErOKpOlk1AJX84i766gDl2KnbS1RbC9qyVbt24V7w2CEEdspaVRoY6IOTI0SWFVwtmcI2CvEXACEHuNrHO/pTYClgBk+/btQv9RkkJChdpFe0aK86xbZibTzzPRseNuXL7sg+XLG2HNmrvcnLsbU1tx9KhKOFNRt8GKhCwfR+3aRgQG1hPp6a++ahT5H/drL76oRrdu1HqYAQhpWI88Ys7y4It748aNuShoO3dK+PFHA7p2PQAPj1QEB0ciKakiTp9WCcvchAQgMVFCcMY5zFrTENsGfAKP158VOR8Uv+t0uxBS2Q8RV69CPWkS5NZhULVYJeIArbUbJu8IqFJzu5jQGQsqV9xqdx1QG7B79060q3QGZc7bFmvLKg9IpgxM/nUqKpWNxcsdvxTDccN9IBqP+EFQ0Jg90uRaKNxks+uZZZPdgyFlXjP/kwISqAcJrmKmcB14Jvf24m8qnNf0xUWvofDXH0XTdLNjlnXTN1gEzZE3IcGs8RGB5zMAOQ74tdMHeLK/bZvIrIiZ0IebqVmkN3Alk3Q+r6wsaL/5BtoffhBUK/2LveEe/xpUmVfvHVpf+Slk1ftMCNQ9+vTBOPUHePdgZxFDP+Ed4MJXe7Bs8lH81/cN/PabFmvWFB6EEGBz9ddeAMTWWHLBgCvd1pNMpZrJSTQtUfnbJoVRWf0ubqbPfX9cBfyQQmpqLejM4wj9sey2I1vJFkcgz/uF94b1/VJS1RLunxNu5kbRjtoR2549e8QCATMy7Nmod2Tlgc+p/5WWyJ7n59y344yAE4A4zrVw9qSII2AJQMglpZNJSZepSe1iFcC6PM9VuVOnTuODD8rgnXcSxXHbt/fErl257XhJvTp1ShICbrVaFpx9o/EEgoJ04iFPMEGNB3UYAwfmn/Hw11+SCAJk9oZZAwIRJsiqCl+iDGxi+ZzOWvw7cxSOHbuMFSseweOP+6JaNVdcvCjBzU0WVC5/fxlNItNRo0NVXH30ScwJ/VRUVUjxqldPRjXDKjRZ+y0qBWjg/v67kLyPQHtwmM0rdbbKdvhdm4FA48Zcn5/0WIRrbsPg45OJ69e3oZX/DpSPnXvfq71w3RtIy/LChN6zoZfLYKXqMv6z1Ev066mB6eirDoMrEvPsQ3YtD2TfzAFHmwE5FjD1DsDVLlfhdvgZBOl+yfU9RaR+1XMA/CMHwnP//9nsmzGoJ9Txq3NP3tYrAAAgAElEQVR/VwaMH7lCdVoDeUlrqFU5Ti0ieNGgRnbWFBg6PwU5IEBkNBw8cADNGtaCpy9DWFREedD8/jvcbr8NqUpanmNn1l8MQ+XBYruZDdfj/RvPI+uzz2Do3x89u2tQZ/93+HB2Bj5MfxV796rx88/mDJKCNgWAEGCXVHZOQY9tvZ2S8M6JJif6rJpY2gOTgmJN4eK/laY9sJLo7YgAhDkKpCiV9POvqNfT8nv2EMiXVLWE+yHNls9OR9UakCZJy3bqCe3ZNm3ahD59+iAqKqpEmQT27LNz3//MEXACkH/mdXP22mIEOIFS6BwsU5PSUdIiTFvULrpjkbfKSdNff7XE/PnmnIQuXTT4738NQpehNE5GmfERH8/KBxewZSQlHYXRqBOhT0pbtUol9CTjxhmFvsO68bujRpnF6AQgpG3xT6WxAhIeXg2SFIR9+y4gNTUZ9esHoVGjqvjpJw3Wr5fwxBMmkObMnBE6rPYYUx/qMl5I2bBDgBI6MqlvxOHkrDX4+0wg4kIbIqhuFfToYULPer/B6+hTNu+/bd7HcTu7Khq4zoNr6m4YZA9ckoYg0b2n0L3o9dnITNuCPp4jUEa+knsiz7+pPSEZ08W//7BrEA5faoh5Q0ZDjzI4WPUm4uKAkSM1OPjZyyifwhjx3E12KQtWQFTJx3M+IA4cB+j7aXBgWTdET/0aXYLfRGDGT3mPL2lgaPgFNIeez50FIgNphvKISm2DBmV/y3tcjTeMmwdB/d13uPVuDQSEnRDbmFwDkaUdBfXW69Bs2ADakmX3rgRN6Ga4qNIhq92hqzEOunDadUnw+rMcJJPZ8tay6ao8j+y6H4l/mj7dBVOrfA2Pt0fC0LEjMpb+gAYNPfH2rfF4YXYVTLj8MmJiVPjmm4KDEEcCIJbnrWhAWrduLQTL1qvfSgCptd0rqyUUvNtLwKwAENpy2+sYNn9gBfhHR86yoKiYz2l7J40Xplqi2EoTtB04cKBUq4AFuJy5NiFAIvhQbNsL+/2Cbs9QwGeffVZkA9mDklnQfji3e/hHwAlAHv5r/NCfoSUA4QogX0Al7YNvSe3iS5SrQ6wu+Pr6CvHu7NnemDHDTM35/HOVcMWaOvUuVcfiCtylvQvQQFtFrvBa2g6SFrVrl4Tvv1fjlVeMaN1aFna6lu3LL1Vo2dKcQG7dCJSMxkAcO5aN1FQPhIaGoEYNTyFUJ6BZu1bCZ5+p8dhjJlSoIKPDF0+h/Klt0F+MJhmf4hSoP/wQMcsP4/Dj7+JqlQC4e6rh4lIDer2MS+eSMSayPvzc4nLpL3Q+zbDetBWSSgV/fyA2FkhPSoG36ioq1yiPNH0ZbN16FT2rzEJjNxs5HCpXGCoPgvbKt+KUNp7oiB93D8Y3L78AGWoka1tgj34hlvz8CJb1qwh3dUIeCpgxoCNUCVty0cNEFWI9kJDRB9uOhiP7YhwenWtEeIXcAEQZx2z4w0W+nUdboq81CZKLNzTH89KsTAFtoW+zHqrZs6F+7z3EL5gN/8G9YNAGwmAk5U4tdq8+9TvcoylIMTuSsW/8M6vGbOhrvgavdSFCA2JNbTPcaoqsnj9BLlcOX32lRZcuBoRo4+DZvbu4Xrd/Xo1a/ZvhF/VANJnUAc/vfFEAy6lTdYLyZ33/WN8zrOLx/uaqeUnaVxf3wUMAcvnyZUF1sm4PmmQqgndb4XjF7RcDT5nJQH58YVy9invcgnyfk2hWiEglcrRWWi5O+Z33g6ol/B4BCZ0OLdPeHQFkKhQxUotZBbFn++677/DGG2+A+UCOZjNtz/N27rv0R8AJQEp/zJ1HLOERsAQgrEiQF0wRXUk2WjQSbFDgzmMQOJCLywwPTnYmTVLfAyCsIHTvrsW2bXlT0S37xEkMQ81o58nGoL9jxyRRJZEkGT/9pELXrrJws7JsTEmfPVuNmTNzAxxOJMljjo72QHJyZbRpUwkmkwYJCWahOiv3zPFg2OGyZSp0PDof/Y5Ngf70KWHLpV6yBOrFi2Ec9gLiWtfCjavxSEgHrkuPQuvyCEJDZTGxzYw/idbSQJSRLohuRaW0wQ7T9yhTIRBZWZKodkRoPkd902iohEob2HenLzbcfgfPVX0NwerDuc5HRIh4VMWpkL0IPdcK3vIFHL9SB1P/mIbfR/a9NyHXS76Iqr4XlY43h49bXitdE6sfiv7D4giJ+nrQjknDpvd2IHvPITySPgaRvc7k7oOocgTAW5tg87Yx1ByD6wGT4L6vN/z1m+9tY3QpD2O7vyF7m3nZ50aPxiOffwrTm3UhPxYCXbkuMFZ5WiANtyMvQXvNqvLCk7+hhXFNK2CAARrvHRZBhYQiKuivvQjNF5tgaNkSG5uOg6FSCDq0vgVoy8B17Hhov/oKF56bikbfj8Ve7w5I+r+heOfYs4JeN2GCDpGR5hyR/JoCQByNfnI/AHK/SaZ1pYR/5+STjdVRa1BCwXthgAQdemgp64gApLSEykV5tjqiPkUBssx2oUsXwQe1JpbaElsp76VN+yvNRQLmf9B5iu+4wvwuinJPOL/z7x4BJwD5d1//h+Ls+XBWJhgUOtJrXpnUl9QJMqSKLys+lPlCYtWDWhOlTZ6sxvTpOYCAdrw7dujvO/HjC4+TGcVpJD6eVrqSqFQw75CUrYMHJeFWNWaMUYjXlTZ9uhpvvGEUDlZsSqI5X5yJicGQpEcE4KD9L4MNCUAUd0n+m37DFvgN6oX5nVajZ6cMVP9yvMi5MI4eCc254VBfz7GjvZjRHGcD16FcoJtIQddqAd8yJiRdj4e7hxb1mpbDtVgVqE9hUnpd/78wqtETXOeHBHNwIlf648qOh5y0FZVMe/IAEJ1XI2zW7IY+PQkNXD+AS9wyPLXoO2ye0DnXtnS5ki//DI0qB9wpGo5sbVW46C/loU8lqxogbuOTuBV9B8tC+2BBh3Zw1WTlqnJwH4mRX6Ps6ZcB2ZCnCqGvOw+nja/j5AkjGvsvhbvuDBLTy8M98imE1spJeoz9cyjCdv0CLATQG0AfQBf2OrIjZ8Ft/0Bob/yVF3y5VUJm0K/QrPsTWv0XUNUxgyAZnshq8DkMwb3JX4Nm5Uqk/rUIXl3OwcMzHbLKDboaY2C41RIe/ftjnVdf9E/4DGf9WyD1xTcwdN3TiIgwYvZsnbif7jdpd0T+e1EAiK1z5O+WVtqWwIS/Y0vBO1e8rYEJRfC2mgJA2rdvX6rak4I8yygg5iRauNY5WHNkehjvB1aPGjduLGzTH1QtYVXE+n7h3+1VLSlKVk9RL//s2bPxzTffgJW+0tRWFbW/zu/9c0fACUD+udfO2fO7I2AJQKwn9SUxSCxFswLCSgv5t5b2usr+LSsg/LcXXlDjySdNooKRXyOFizajHTt2FJswXPDoUbMGg9oOVi7Cwsx0nW+/NaenMz+Ejba+K1eqMWKEQVDBSAnz9vZBXJwWCQm0Uq0qKhEUqVeqJAsKFl2tRIuNhUtkJIxPPw3d4dOYnfkWqjzdAkPe8ofmzHRozszK0+XEwLdgrPs+jh+XBAgpU4YaFknY/FIET/YW+8y+qvY+A23sz7n2IaocnuHYcPsFdHObcA+UKCDliPYzbIt9UeyPLpiNo73Rbvrf2DXVXB1SmqwtA+iT8wCEa3J36OCLMGlZnr4bTGqsOf4SHv18Dc7PGYzWvnNsXpKk8GnwjZ6S57NsKRDnqh+FXiorAFZIZRO8M7dDl3gJFcKCUKFeB0ClAdKi4bo+0lzBOA9gFiC3BaTngPR2B6CJXwHXc+/l2b++Qk9kNclJZ5duXIZm6xqo1x+A+sBhGGlS0KUL5OZ+cD89WHC3WCHLoXC9B33Vl6Hu/SQW7W6Mj6RROFm5K049Ngqv7xiMwYMNePXV/KtxigC3du3aIojNUVpJAZD8zoe/Z1vVEsXSm6vc1pNMLj4QgNBStkOHDo4yVPf6wYUSZrnY2ympKCfuyPSwpKQkkL5LdzqCUVvtQbQ/fsde1RIuLPHaMgXdVhhuUa5Hft+ZMGEC1q1bJypCTgBSkiPr3Jf1CDgBiPOe+MePACdQikc8J/TR0dHo1KlTiZwXnXio1eAxSNXIr7JiDUAOHADmztXg55/pBWu7XblyRVA5unbtKjYgYKDDFSsfpDqxwFKzpixAx507wLRpGgwebETTpmZQM3KkjH799iM19Y6ggnl6VsOKFVHIynJFQECoSNiuXl0GQ5HvCdp1OriEhkJ2cUFyWAMkvj0N6oZ1BbDYsEGFed3bwyV5Z+4qAsGDbwPoO+7BtWsEP5JIXld0DJwIc7GY1OTwcBNMf/eAZzK1GDmNPU7KDkavb/ZiQNhSDGs3Ha6umTDIbjgmT0WU5i1ciFKJSXXt0Fj0Vkeg7dSNeQBIfmN5yjACS7a9hamPNkdZj5u5j323ApOwsj7KBFaFS/OcbBHLDTO0NeGuP5cX3EhPYL/rLwIcpacaUe3mM6gi5YjRTQFtRNCi6tZOaHc9kbNLugRPBPAIkPnjMtxx6wjX3b3hb9x9bxu9axVkt14P2f2u9adJD5fohVDf3g1Z7QZDUH/IV8pDvX49tK7/gapucp5zQ4IWutg3oRv2EuKXbsGMme64pgrBH8GvI/H1cRj06wC88ooe/fvbvhepaWIGgqMBEP4++D9bGpAS+XHb2AnHwtIeWMkuUQTvXOFmZYSLElyIUACKvVa+C3uedAGkjqckc5AK24f8tnfk6gyr5kePHhV6PIKIwrSiVEsIcgpj4WxdoSlM/wq7LfUfpBkTkDmbcwTsOQJOAGLP0XXuu1RGwBKAcNWUNCxO6ouzekNAQ41GbGyseKGTC0snnhYtWtg8J2sAwo1Iw7K247X8MhNnCW66dOlyj2tLEEKwodebaViWi3H87OOPKQiX0bjxTSxffhNGoxajR/sjIKCsyBb544+LCArKRkREbURHS6LyYSlW10ZEQLp4EemVqiO+SnPcCqiF7LBa8GkViXINQ5DxV0/U8s3ROLC/onpRthn07ZnsB1GhIUDi8QhGfH2Z6UB+vRF+qlV4NPU5aJE3JT213CB8uHMUQldtwIVa/XAxywe3UvzQuIkKHTrISEwEqG/pV6YdfPV70HLqzlwAxOQTCSntImDKzAMSNsRPxsbr7wpx/EsRg1BOzkvzQpYLMNULmJIIyWqOYbythWTUQwowAyvLluTaAasz1okAyJD0eShzkRHruZsxfDiMoc/BZXOOo5nYglKVMYCxViROf70bR47qUDZpLqpXSEVSdlVoqg9EjTp3qXyyCe4HBkJzI8fKl7vIipwDfdhwuB0YDO31NbkOLET2si9059+A5qefYGjYGHGdB2PQKxXwuHEFxlf9CRnTZqL13P6YNCkbXbrYMkZwApAHPagsMyjoDsQJoWXj4oRltYRCcOpNivMMelCfbH3OSi2rWFyQcLRWWjkWRTnvhIQE0KWLC0y8bsVtrJbQHVEBsIqLG8GtUmErTLWkIBWa4vZZ+T4dsKhN5KKEszlHwJ4j4AQg9hxd575LZQQsAQh5q3RbYQWkMCtMlh21tNflqjBdR0i54EuKlqC22owZaowdaxRUJKV17KjFr7/q74Vcc9J+5YokxOZcZNNqryMq6oigYOXHN7c+VlaWAR98kICNG13QpUsGjhypgg8+MCejk5a1atVlqFQ61KpVEykpkggpZBXkXjt4ENru3XExtRxS4YMAXx00MME94zY8jSmQPSRow7IhlwMkf5j/LAfo678FU6fpZqcsznll4NCeJCRev4OAKsG4fjMLR45cxVs1+sFPupRniExe1XC97nYsXXoJoQu+gcfXC1A55T3UUP8HGqTj/J1HMW/HYvj4uWFhW3PYozUAWRnzAVyMN9E9dG4OhUsGdLI3Fp7fj9jkcKFz6V9tLIJTF9i8TvJvEuAqQ+qZ++O9rhPR8OaPcCmTt+8GeGK3ywpUqNsa1WJ6QXVjQ64vCwzgXRvGOjOh3dP33meKNsXg1hSqN+Og07jjl/E7cSvxANqEX4Ah0wjvkLoIaWQ2TFDfWAeP/U9a7VsCJA3Sul2By6XFcD07Pe/Y3gwBPlbDVKWKOa0+Kgq6sBqoeeBHfK17Gh38jyFpwedo/X4ffPRRFpo3z21q4KghbP+LCkhBHlhMaGeV1doeWJlsKno0/qatQUlhBe8F6Y/lNqWVFVHYfnF7RwZHSrikva2VeW/YCuC0rLBZ0/5YLSEAYVWiZcuWdnemYgYI6YerV+fOPCrKNXd+xzkC9xsBJwBx3h//+BEgbUJ5gBMkUOxIYTcfooVp3A8nFvyfYq/LCQPbhQsXwIoFhae2GisTgwYZGVB9ry1YoEJmpoQJE4xiwkz9QFQUqwfmJfYyZRKRlbUPnTq1KVDZn0LzHTtO49QpN3h4hGLnznKiGtK5MzBggHlSuWpVFGJjDahVq7agbjE13JrSzL4cfG4x4n/aiTBcRKpneSR2HQj/155EyqVbqHllIqplfg/VbRnyLcAQ5QFNjAqCd8Xm6QGEmyCFpAHlAJ2fGzYkP4e4kF54qWp3m+NjqDkWhshp2DRmMUxHb+GREXdQVff/7F0HeBRV2z3bkk3vlZBCCCSB0HvvIKCiqFQrWLCgIp/9Q5RmQwUbVhA7ioI0aaG30CEJJBBCEpKQ3uu2/zl3Gdg0SCCJ+/vt+zwxmN2duXNnduY99z3nvJ9edXzih8rk/rgUshYhcZ3FNub+/gbm3vPm1e3lBr2HgzlPIqhwDtrgUyhQjoTMEMS5foszWT1QWiqDq6sOvZXT0MWhqtWvgGBqX8iy04A5ABYBsL421MPWs+EdOgJ+p8dDpq+6us3P6mV2qBgSBevYl6BIr1aFIABx6gAobCDLPVSjOlPsPg4VHZfBYdBQGDIyUDYfcHbOvrrzyuBnURE+D6oLn0IdU3uHeGpI9LaBsDk0Hsqc3Vc/q7fxR2nfLTCofSCPjoZy82Yo//4b8iNHkKl3QyjisFs2EO1Vccj44GsM+ngyli8vR/v210CIBYA05C4BSP1JmKxWD84l6VnVBe/8G4MVkeqCd1ZL6rsAcaOR0k6ZTn38MbfYs2cPWrZsWaOZqzmM8580FpCqJbV1eZeqJazKsKLC80qRPEFKUzlxsSLPCtqPP17TpZnDObKM4d83AxYA8u87p/9zR2QKQFi9INeYpXTepOsbvPmb2uuy4ZOpBSG1JRR6D2e2X0usWCFH//56BAdfe7GwELjjDhV27tSI3P3wYZmgV/n5QdCNCgpoD3oIo0f3uO5YpY7m3L/B4AqNpgOsrNRwdgY++ECOzEwZ/v5bC2tr4NSpWCQnF6FHj55CQ8K/VQ82IKS71oUDGbD59CPYF6ShhX0BFKWFSOxyN1rNmQSDHZCXegnb9juhRKvBkiWtjY5epaVQrHsEyvg1ApzIcgADTZtyAF2CNZR2FYAjBDARP27G32WBE2AYOheFT89A1h3j0d7r2Sr9OqQx7s98GL09lld1qDKQBqbAdtVBJOZ3FKJ3hVyPn39Mxvr1HvhsmS2s1TJculQOZdE6THG7X4i0TZlUeoMCuh5fQ3X4YYBOuGQ9mWClPao34dtlCvycSmG1peMVoXfVmSOAkmXvhSLjWqf3q1WOdm9BkfgNUJpUA4BkKDrjoPoNWCmVGPbyfVBdKDUCIHcjvY3jLO3+K2T6CtgcfaDKTo21KzmKRyYCVi6AXoPUfb9Dm3cOrSM8oWkxwfj3aiHLyYFi61Yc/ekcRu6cg6PoiraIR9rU5zAk6n2sWlUKU5YO+8c0R4+B+n4f+T5zrYBcD4DUdXykdEoJpiktR2qgyn4L0sq31OmdFJ2GUriaq1ldQ86j9F5zHhsXl3h/lRwJb+b4GvszptUSNr/ks41A9UbVkput/HP8fNaQZszq3ueff97Yh2TZnmUGqsyABYBYLoj/9zNgCkD4cGepn31AWMW4UfCGS0oFxeBcUWKXXlN7XenzfE9MTEyd2pI//5TD358NEKu6Xkk6EGo6mPSzm7evr7Efh15fgsrKAxg+vFut++S+aR9KYMSHj49PMOTy1oiNVQggQ42Iq6sBy5YpEBpqEH1IEhPjQDpBXcLdggIgJoZCdxmysoyMqtAdX6DTugXI7H4bojO94JZ4FOWtQlHxyKOw7+KIgwcv4eLFnnjtNR1a+hlgtc67VieqylbPojQrGc6X/gS4wJ8NAVIMWXLknfSHTX4+1JUFgFoJeaimCkCRAIvWUQ6FQl8DgCz4+0N8HjkTXbvqMX68Hq0ddqJt/nS4q1NQUmmP07qnsP3y7birzQqEa2p2Sedclo/NgG7nBNil7gRYWHmbjSGAAnknrLz8DoYMb4XWAc6w/sukjGVyAWlbToYy5acqVRvx0JYpUXl7GlSHptagZ/H1Qt9HkdXyJRQXZKPj2V7ApwCOsK05gJbGHVx2uR8VboPhf/5aF3YJnFS2mICKLl9dHQmB7ZdfWmH27Jpd02u73lcup42zGjFh4xBwahNiP16Pu5eMwLp1pcIljcH+MbRubeomZzf6Ppq+bq4ApLHGxfuWqT2wBEy40s3gAkh1CteNxMvk7VOAzkqDuQXHRncuP67AmFk01jltqsOSaH+suvH6uF61hM8xgljTZor1BbN8HkZERGDChAl49913m+pwLNu1zICYAQsAsVwI/+9nQCphSwk7V9rYCd3DlA9Vy1FSWEoROGlbfGBzBbiu1aMbaUsiI43r7RRTm8b99ysxbZoWgwZxRRdCGE5thlptgIdHKTIydqFnz+5wY/vwasFVL46PYwoP74DUVDckJhodqKgjoStThw4G4Z711VcKYYs7efJ5aDSJGDhwsAA5BD6kYEktSxISWCWRw8uLHbqNmhTqRMIMMagYPQFnygJx+dl5UEZug+rAHsgc7RDfdxBaPjodmzap0KuXFvdbOUJuqGnrmuP6KPYULUR3zcNoASNNqQLu2GtYiULboSjbcxSKfeuR27cNHvd6CPIcI0ip8kPRNistriZVFHfgwyNv4pLzKJwsD4NMk4CNz/aEUlZZpaN4jNXzCAl2gtWZubVe0+c6Z+FCggGhhU+h5fd/AF4GJA8aibPOX2DP4csYNMgNA/p5wGpdC8i012hYkt3tkQvj0a3V6lq3XTH0CNLSL8Mv9j6oUHr1PcUIwCmfXWjbwRVWSi3sN3pCZtACP7DdO4CXAIQDF2ynwq4iFl66ms4zpS4jUNbjpyri2LlzrUSn8/rGM89YYc0aFRKeXATXpYtwcH0SHn7CGVu3lopKGgFISEiIWSWH5poUsjs7E8K69GD1PSd1vc80wZRASV3iZalawgoKqyXmWMnicZorzU86B7Qy5z2eGgtzjBtdcwSzktDdFJyYVktMAYkEUKo/73ieAgMDMWvWLLz++uvNOhWc/7feegsbNmwQi2h8Jvbo0QNffPGFMIKxxL9vBiwA5N93Tv/njsgUgPCGu337dnTq1Ane3t51zoVkr8uHdvv27eHp6XndeaPzDW0J69KWHD1qrCqMG1dV4LtnD/DFF0r88INW6EDY64NOT6w8ODtXYPfuHejSpUuV/WdlaXHsWAIyM9PRtq0LOncOR3GxCtwHrXWJq9i0kMCie3ejxuPFFxWiQvHSSyVo1Soe48Z1QXKyUbZB8EGROle76wQgYQbhA6x5/hUUf/M7yu++D+cfno+UpavgvWM1igzOcBvZAbvDB+Mu95no5FPVZYqTF+e2HMdyJwshuK44HWlJhSgyBMLW3lqMPf7nE/BoU4xPHx0Pa+TVoCrlW/WHc+UegG6xuVWBSebxUCQlO8FblwZfuzQovHTXaF6kMhGweLtCFz4UysLfapzL5PK+WJUbiRYtjL1L8mMuofdrIxD57nYEtPPGn2tiMGCAM0b5fgnl2Zp9QvSF3pB9nwnZU1XPr7Sjo/7rcClHBxdVHjxyNsNOXga9XTCidTNRqvNAp056+HjrYLc9AvKyFOPHNgAGtkt5So7SF/dDfWw65EXRNSyQ8+RtscfmHSE+lVbEly0LwJtvVgrtkClNR150FtYxr0Jech56a29UtvkPdJ5G2uDQoTZITZUhyaUT4OaKHa9vxHPPqREZWYqoKPNbnSYAId2pqRL9m71Rko5Jyk5zjqt6gikBE8l+nIkkrw2KlXnf44IKE05z6WRtrlbP0jVA+hUXomjDa47B8fEZVJcLY21jro+2ROp1w2u6sLBQ9Blh9Xzx4sWYOXNms00FNZbcL+9ndOFilYzng85p7733nlgcscS/bwYsAOTfd07/J49I6mrMm+7mzZvRrl27WmkIfGCTbsUEgqCD4KM+tov0iY+KiqpTW0JL2n37ZHjwwZoJar9+KuzdW7NiwLFs27ZN0L6kBnDnzhVg8+YkUb0ICPBDRIQr2rc3Agl2SS8uvgZACES6dTOAWvu9e2VCC9K160W8+2459PpQjBplEA5cbBzYsqVB0LQ4zrNnWYUhfctYRaFQvUqxKDpaVEOiKjsic/YrSFcXw/NcHpx++wWt8mNxqc8AdJqyHt6OyVevNVrQHlV8jvhzcnh4GHA5pQDBebMQ4fY3IJMjXTYa0a+p4Da/NQZbc9m/ZpT02wtl1P2wrqzqRJWlCceXyVHw8uE8yjE54AGM8PpZ6E5MqyfUoghNSikgo//AFR2K3k2OqLynsSOzFwLvCId1qC86ap9B8Mpf2a8RxYOC8FPSGwjq1gdDNRMhyz9Wsw+KxyBUGmZBHn0PrLyNlQepMnK2bBgOKV/C4MFtxMr4ubMqBKgvw8c9H+nl7ZFRFioASIDsD9gcfbDKgRv2AvgSqFj4DhTdD0KVXrNHSZnPfUhtuaCKhuDrr1vj/vtjoVQaOzJzRdNFlYvAM+Mh1xUJmpgxZCjr8St0XqNEpax9ezv4uxdj7xlPlC9Zgk0eU/HWW2q88cZGtG1rXtSdG636/lM3OiZrtOeuqydQc43LtDGeBEiYtF098zKZ6F0kXR8SeK3P/a6xj1KzCD0AACAASURBVIH3Ogrk67PY09j7rs/26HJIkw+uuJtjNOb4aquWvP/++1ddr6gzYcNdOkny2dShQwdBy6L4vSmC1zEbQEoNURui3WyK8Vi22XwzYAEgzTfXlj014QxIAIS72Lp1q+AaU0huGtRR0Oud7w0NDRWrLPUVeXJ1iE2+uEJWm0YkMxP49VcFnnmmZp+FwYNVWLtWIzqFm4YpWOJYSAPYvDkTeXke6NXLD3q9DSoqgM6dDUI3Eh8vQ2IiwYgM9vYGBAUZroremQzPnq3ArFnJ2LOHOpAh2L1bKcZDuhbNvAhU0tONNsBarQE0yunSxdjosHoU5uux/8FvkL4lGoZOPkgYchsiIhwRoNcj7d1VaJOyAaUD3HA5uCN6TR0Ar45DEXtGhm+/VSAlWYe3R4xAqIvRrUnSMuSmhiCt7RS0L66dIhUXdAgXUmzRWzsRzogRn83SdcFB1c9Iyg4Ei1S9elWieOOdCHeMrDHmpOwABLgnGf9OFpQJQEk/0g9550vgI7sMB6tMKG10gANEtcUw32jle77NnwjLfgmyvKM1AIjeYwjSwzbiXNQFtI0eC8+AJFTqrRF5cRyOGp5Hzz5t0LevNeKPrUOb1FlwgLHKYTDIEefwDpy6Pw7XS/Ngfe69mpN9GjB8oELl4/dD1f9PyDV5V9+jt/JA6YBdMNhc4c0bdFAl/4DoPSfgF2SNQvdRyNG4C3DSOu8DBGmr9hDh3Ffad0BJvx1CwEoNUESEHZ5oF4mFR8ai+MwZrN7ljbffLsfvv6cjIMB8tAPmCkDMla4jJfm8t7H6wWvCVPAu2QMTgFTXlnDluSmrJaSV0SKYieyNqLFN+Jioc9Ps+UQKU7du3f6J3d9wn+xtRb0QqcVNEZIWkjod0qB4DfF5yXmRqmzLly8X1YnGDtIGaUVP29+xY8cKFzlei/8EUG7sY7Ns7/ozYAEglivkXzEDfMBJloW8iVJMK5VtTe11CR64osMHdEOCHGyu4HXvXrteg0Dh3XcV+O9/awKQd96hsJoAoWZ1hGCJnFtWWHjDLy0Nh1brj+BgmWjuR7G5aIDnL1o8ICMDApQQUDAhN22a9913cvj6ZiE9PRo2Nv2QmqrCtm1yDBqkF1QtUr/oiuXiYtSjkFbLrupKZdWZIECJjZUhJqYUsVtOoe3fqxFmnYiw1W8hyTZc6FgC3QpR9tGXSIhMwVFDN1R26IKwe9th1G16eCv2w/v0kFqn96z3YrS5/CJkBgrNjev0/K9G5oFvc89DL1Ojcyc9ynIv4eRJBew8fBARIRcVm+zsYgQqlqKv/s0aQnCNwRZf7HgaTw+pXTi51joXK35wwMI38xEW7XGN5kXpzhXNear3y/Ap3wJ5/jUdhgSeEt0+RIHXDMTHy6FSaRCzdA2sYw7D2tsdm3xexJT7DRg92gCrHV1gXxF79dglLy5a5Sryj9Sw2RUzIFOitMUW2I4cDe2do2CY6QF52SXobf1RGfz8tS7pBh3Uh6dClbHh2vblNijrtQY6t95QH7oPqsyqAIRvLJe5YLPtckHhYqUkI8MNU6eG4G+fB9DH9hTK9u/Hyy8n4ujRVti6taqGqSHfkcZ+r7kCENp0U59lbnoB0k9pdVtblYH3RknwLoESAhRp4YYJn2QPLOlKCFJuxVHJ9HpgUskFHK6o16Z3a+xrp6Hbo9aO80cKkjkGF84IIEktbsogFYogh88lVkB4fZAxwN5avN5pcNDY8eKLLwqaFZ/br776qrhOuDDIqsgHH3xgtrS4xp6H/8XtWQDI/+JZ/xcesykA4UobH3JsIshVLbpIsYLBmyf9zW9mpY83Ygp1+YCqSxBXWzd0TjVBxPjxKkRG1qRhkYJFgMTVHgKjggJXUemgUJ0hCc3peHWjIE3rySc1aNPmFLy8OqK01ArUtlN/QdE5u6IzCECoV2nRwki/YhCPqVTGPcTFAdu2ZaKkJAkqlR2ysyrxwPnfELFpKZKmvIRdg/6LrVvl4rjcXA0YVLYJig3r4K9JRPfJwbB+uQ9UJ2pfKdtr9SXyUi9jlOs8qBTG+aiEE/YpVmNv/ABBNSOtzFvzB8LLX4GjIgml8gBE5r+K03lheDjkv/DRVO3Qy+pPmbI1Xt68Ee8M7AK1srgKMIstugtby38V4x01MA290gNrnco8xxFwKdxSA9yUwg9rkCAqRXl5pShO+A33+r4MRysKVYCUE0H4MGkD2g32xDTHWspJFOO3fR2agIehjuwNpTZTfE6icF2yfwbqPgtgnX4R9n37Qte9MzSfPCz8eXWuva8CEGXKz7A58XiVsYsmiLZBKBl6Umg/rC58UuN1jVNPJLf94eqKOBPQXbvcsHRJF6QbfJDz4N2IGTsWmzZ1REKCJ377rfKmviM3uj4b+ro5AxBqyBrCx2/osd/M+2+mysCkuzZ7YGkxR9IImNK4bqb/BBdwDh48KO6fLrwBmVnwGcHgPdgc48SJE1AoFKKC1JTBHlrsdUUr++aio40bNw5r166Fu7u70FVNmjQJ7MvCSgyvG1Kfm/q4m3JOLduuewYsAMRydfwrZoAPUslTnw86cp9pw0vuLFd++WCpjy1vXZPB1SeuCnE7vuRD1RJz5ijw1ls1KyB8q2THK32MZW2Wt8kl58ojbYNJkSFPn+JxOlqxMuHjYxAgonrQqZNVAfbmoIsRf5eVATNmaOHuHofRo1uhuNhWAAtWOahP+e03OcaMYeVBBgcHgwAcTIK1WqMehP01lMpyrFlzDnwed+/uDFdXd2zdeg49ewYhcXcR0r/aCGdVKXp9cBfUbVoiK0smnLYoqo//8wxa/PUFJjl9DeXbmiqJPPdDVLCqfAdWrm6Ftj4FeGDUHqRnWCFPPRRB4b7CopiVl66+f2O0zR1g9UAGgxgjs/Fjzl+ik80aKC5fqwBIiXx2RTDW6GKx7pv9+OmpibBXZIgp2598J6Z9vQJhHewxY4YOMafK8KyfL2S6sqtTKlU50uUD4KO/1uRPeoNeZo1fUQi5/DI0ebsxwf5RKGXlVUCO5qAVzskXIbzHC7VeGxWhbyDb6wUkHD8P3+RHEOgYjUq9A6IrpiHR/r9o38Fo46yIXwebIVMhczUIq2CDtR3Kun4HndcIWMe8BqsLH9e6/aLbLkOmK4XtngGieiKFQa5Gad9N0DtfoW4Y9FCmrgJyDmPHXicsWDYeOy4Nws7PlqLMywvffReOnBw15syJr9GXorGa5dX3hmOuAMRcBctcJKEF+a1WGXgfZeJnWikhSKmt/4RULeE9jAlyXcHPM5Hk6nptFNb6XhNN9b7jx4+L+y+rR+YYBAakyYWHhzfp8FiFuOOOO0TVg66QzRGstNA4hjQsLshJwWoehen33nsvVq1a1RxDseyjmWfAAkCaecItu2uaGTAFIHzQ8YHHFcEb2evWdzRcEdyyZYuoqlCgV1vUVQHheydOVOK557To3h24eLEA0dFnoFSWwM5OITjRFM3XN0ilopCcjlp85tPdqm1bdmAG/vijDD//XIBXXnFAWZm9eJ0VBYKUCxeAN99U4qGHdPD0NCAtzUjzsrGhra8MHh7ZKC8/gcREdukLQ2GhPU6f1iMlJQv9+jng8cfV8PPVQ/H441D88gsSHpiDo8NfEtUVUrsuXJCJ7a79IgvT3Saj08CqyXx56Dz8enoSXn3VCytWWAnAxGoPaWQhIQYQVJFmNsp6DJxKrz2IrgIBrxHQeIyAdfTsGlP1U9R0fHzoc3E8t4/RoFObZJyMsUXX3q5w81CBNLizZ+X4YOJjuCP8mxqfjy4aBY3CC51tv6vyGsFPJZyxOCkK9vYpuDt0Lfyyl9Z6qgxPWMHwvgFy+2uVLlGhgBJJYXuhtW+H48fl2L//HGzkCgR6lUFv0xI2jk7o3FmHVi3zYb89AijKh4wN0dmAkb1K7OxEhUOVvBLWZ9k85FoIbCZXo3j0ZSH2l1VkwSr+HciLz8Gg9kZl8EzoHa9cWwYD1MenQZX6+9UNlGtt8Or7i/DW5UVI2LpZVA5feMEOWq0GTz8dI75Hps3ypIRT+n0zq+H1vc7NFYCQppKTkyMWDcwpSLGiaxBpOq5cUWjEMHVUMgUmBCpSSIJ302oJK7tc8GAF+siRI4LCymvH3IIJPsfP+7s5BisSrByxV09TBnUYU6ZMERUIyRilKffHbd9+++1Yv349VqxYgQcfrGrSQXoyr2tWHC3x75sBCwD5953T/8kjkgAIrQpZruYDk+X+G9nrNmSyuEpDYTtpXLXF9QDI9u0yUKMxeXISTpzIhLW1HTp3DoBOdxoeHsYKTX0jLk6G6GgZnJwMQg/C6gf7gRCIREWVYfbsMjz8sBouLvZCqM4+H5LOg0n+woUK4YpFtyrSiqysdNi3Lx16fQqsrDxw/Hgw0tIUcHY2YPhwLZTK3Rg2LBQ+Pia2xgcPIu3OmYhS9kbFi6/COdQbxcUyUUWhU9cff8jQCqtwh+unUKddhGOcFtaDn8TPQffjv3M8sGCBDcrL+V6ZAB6s/Pj5caxA+9TeQodh2smcibbeuRtOee+GW/w0+Ot/vjpdmYbeWF/8FxYvdYGVlUH08PjtP08gUPEnZNAhXdcf67K/hbOvH8aWucPe+lqPD2kj0ZX34XD2BDzke9+VDu3GygvB0bZLD2B38ZOYONEbbSq+gvLMglpPlabVG1BdYIfDqpGp74HjHpHw99fjXLwM9ueewmCf74UGRmdQ4qz6Ldh2eQZe2A3bA2OMH6Zc6I0rLl/vAKXDfoXesQNsd/W5KlKXxlfR+gVUhvHN1w9l2p81XbgApOX745enx+PBSRmwXrZMbOSRR9Ro2VKPN94oFwmAadLJf0ur4ZL9q2nS2Vj2rxYAcqMzWvX1f4LmxMowaa7VqyWS4J1VBV4b/M17M6k0BLk3Q4Nt2Gw07N1ctGJlprlW/Rs2OghdBKm/TaHBMB3Ljz/+iBkzZohzSkDWHPHEE0+IXh+bNm3CqFGjquySIJ/291JzzuYYj2UfzTcDFgDSfHNt2VMTzgBFjuxUTntdrsrygdfYIlGWp0m/qmsV6noApKSkDD16KDBpUjS8vLwRFOSD/HyFACBt2lQ2SPx44oQM587JEBxsrBrQ2apjRz2Ii/LyyvD+++egVIZg0iRbQeup7Tny6adyQcsaPLgUFy5cwvHjDrC1dYK/v42omHBb7Bnh66tFfv4WdO5clXpGPcXZMwbEvfQdio/Ew+W2Hgj/711if+y0TiE7qy9fzs/BYO1mjB9vgN/nc/FI2ny0C7mM4Z8/iLgMZ1RWGulgtAomAOnRoww4OAk+ZZtqXC3JqoextXAZHOwNCPfYiwsnTyLmgi163DFF9BqhTfHGjcDzncZiWLstVT6frQnFFvlB3ANvWCnKa2z7RPG92Ji9AJP7H0NA2qOQ6Ywg5Vj+WPyWNA+9+wZh4EA1bDJ+htWRh2t8Xu8QCoNzByhSalIFijTuiHROElUORfwStMj871VwI9HMyrqugEHtC9t9I6pum6ZZZ4HSDZ9A1/0ByAtjoD7xJOSFp1CmcYQ89DFoQl8GZEb6C0FJRoYMeXkyAUw9PPSCXsewOvMWrM+/X+u3sNVzyViZNRGddy2C/ooQd8IENXr10uH556tql260Gs4V79oEzQ2lcJkrAImPjxeGERTJmlMwaeRK+T9Nc+L1wfuxqQsXKyBSEtlY10djzj1pu9Qg0D3RHIN0JFbzWRFoyli2bJloQMhFh+YCid988w2mT5+Or776Svw2DbpDMvhct8S/bwYsAOTfd07/J4+IK1hcYaN9IB989MMnf7Qxw1TcXtt26wIgUkfzZ5/th+ef16FdO/urlCWN5gxCQorqbf9IvcWJExAAhPoOUpbYaJACc7pa8SG/fXsk1q4djGXLrGs9/NRUY0PCDRuKsHKlDXr2zMP06faIiLARGgza9XKbKSnUhhiQmbkNHTqEIiTE+DBgknv8uEy4YbFKkrUvHi5LF6KXaxzsNvyIPZdaiY7ttrYG6L9ajkjVSFi18sP99+sx48ESHLLuDvnFHESFTEbpY0/Do1ew6HtSWFgAufw4KgvLcJfds3CQXbHUBVCEIKyr2IPzKZ6C5tWxIxAZWYDjx7MxfHgQ3N3lYlxtfeMRcbF2oeYZrz+gTPwGIbYmLlJXqhyvbFgO3149MHlyMCrKSrBt7SFk5ZTDu1UI7OyDoVYr0K2rDq5RvSEvOFllXgkiNP02QJHyCxRJK6u+Ro2NXo2H1iZi9mv26JDaV4AH0+oOP6DxGoPyrt/CNrI75OXJV18XFK5v1JDtN6B085ar4AAGPVZ8Z42BA7WiyiUFwSgrZFlZcgFAfHz0aNdOL86nKmEp1LFVuxtLLlwrKzbiP492wVbFKLTK2CbKaqxKjR1rg3vv1eDhh9kd8vpBXZPpajhXxfn/EoVLEjSbuixdj8JlrgCkMXsy3GhOG/I65/vw4cPiXtJUPRsaMh7T92ZnZwszEGosqFWRhO+m14fUaNP0+qjeaPNm93+jz1E7Q8pRXdXtG32+qV/n4herHwQhTRl0o/rss8/Es7S5AAivjYCAAFEd43mQtESkZZGeNW3aNHz99ddNediWbf9DM2ABIP/QxFt227gzwA7ATHS48kqRKBvC0c2jMYP8atIJ6nLkqC5CNxWaszvxjz92gkYjR79+dJwyiARRLj8Ld/f8eq2mUjNx5oxMdEEnJVYul4nkk1UHLoyRLiSJ5c+f74OePZ0QHm7cD3UeDOpEoqJ0OHw4BZmZRfjxxwgsWGDAPffIRMXi5EljR3eGQmEUqsfHH0HLli3QuTMf0AaRmEZFGTUoXKAi5aqoQIdO385C/pbDSBj3HFL63AcldLCd/zpkC+ehsEyF5ctpYVuO/8zegXH+p6A7/iHkshIUprli8+U5SAsJRWgoO3u3g1xbhHDlFyjJSkZ2WQCs2j8OmZUzdu26BpASEwtx7lwmwsMD4eGhRNeuBrT3OQS7vbUDz1N232LH2eEYazsawW6nr14a0foX8PjnL+PiRTtMmqTH3f2/RnjBu3BWpkEHa8QZnkJewDx0DrkAW2o0aglNt69hUPvAau+YGi5afHuZpi3eOnMM/wnvAhdlXA0AovUYhrJefyAl+iz8EyfAHsZmjOWKFijv8TNslq2H1UcfofTnn1Hcd7gQ/0dFGUHG+PHXjA9iY+XgT2CgXpgD8H0REXpxncjK02G7szfkGqN7lyS+rwyage35tyM5OQSLn9Djlx7vIWTbB+I9PNfDhtng6ac1uPvuG4OQ6lPD76QphUui6lSncJkmnRKFywJAGnb3MmedBRNaWt3S5ci0Elb9+pCAiVQtYTLK68H0+uA9+HqC94bNmvHdtFhnEswfcwupizwX1+oyQGmsMf/3v/8VjlTsdVPfHlmNse8lS5bgueeeE9fHfffdJ8xZli5dKs499TlNDbwa4xgs22j4DFgASMPnzPIJM5wBJt5SwyQmLqRJjBhRjc5yi+Pm6iI573V5xbMCQhcsAgECIq74cbWPziV8cDAZvOceFd59VysqF9RflJdT6JtXgy5GbQcTSAIHyVyGXcyp/bCzMwjnKgIS6jtCQq4dmNTc0M+vPZYsCcCUKXqh/6CdL/sypqTkY/XqZFRW6hEfHwaZzAZarQxLlujEKjkb1RGAcP902eL/R0efhLs7aWNeotJCE7D9+400MFZA+HlWJfiTsDYGNu/Mh42zFRJvewL602fgOHuaACqPPqqEj08JHuk7H5PavHu1WzfhTkWeFfLf8kLl+Ok4Mng2bB2VonHj0aNGShHtgjm+3FwZ3N0NYv5Ony5GYWEc2rSJgEJhJdy+glrkw2pDIKCvEA5aItG+UuX4IuUIsrUdEHWgAq88vA1J8TnQ2LVHy46dceDABVhbFyEpOhcL+98NG1WpOI9Skl4aOBvKkMmw2tqldgDSdRn0gQ+hYNcT8MxeUet7tDuGIHukA7wr19Z4vSJ0LooDZuHIETnycjQI8YxFYaEe+fpwdOpqJY5Z9dVXsH75ZZyd/SmOt58i5uL0aTlefFEj5p5x5owcMTFy+PnpBT2Pbmqk5wUEGF83UrhmGKs4CltoAqeBDl37DkSJFeAN33tgx+JofLS0Av4PDRKf4XYGD7bFm2+WY9iwmr1sGvq1kihcEhiRfhOoMCSKDv/Nv1EfxQS0sXpSNHS81d9PhyCOmYJqcwp28mayRvtUc+smzSowm+kNHDiwXuCBAKS6roQaF8kemJWR6qCEFZSbTZqbq8JwM9dLc3aRJwjgc459P252Lm/mGPmZH374QfT94HVC/cnw4cOxaNEis61K3exxWj53bQYsAMRyNfwrZsAUgJAvytU2ApDGLCPTqpEPg7oSjwULFHj+eS3S0y+IKgxpENWbHtKOd/duWgYb+26QzkGHD1O6GOmuyclGcTaTcDpE0TiG9CgCkNatjQl4UpJMNCnk/5sG7YJlsnCsXOmPUaP0glLl6GiAo2MiUlPPISXFHzY2wVi2zAZPPKHHgQMyLF6sE/1BTINaDv4UFByBm5sH9PoAkczq9aRfQdCsCG6oRSFA4JioT3Fz1sF+4eu4sCsVhS1CIZs6Cc5dgvDyy0rMm5eBcdq2sFGwV0fVceu041Hwejz2pLXCpXYjoH7wHuRonYVDF4+BTl4EXO3aGQRI2r+/GGVlp9CpUxekpdmIv7NCk3X4FwRnTYMc1yoDaxPfQJzqNTHes2eBSQM3ILRiLpyUKShTtsLqxCdRYhuIieE/wienqkuWGKXSHpVjU6Ha3A6ysksmFCnCHCUuhB6DX3gIMo5+gYCkZ2v9Tum/c4FsXD7gaKhi4WtQ2KJ4+HloZfYCgJBGRV1MRoYcNjYGDBigu9qtvuCbtfCZ/QjOTpmD1CnPY8kSK7z+eiXatzcCg8xMzotc6Hd4rKGhenTrxspgtSHpNaIBojQQUh9YpSPN47G+CVCfPob58WPg6G0UotLsiCBk6dJy9Ox56yCktgnid8u0JwWdpkzFp6RrmSad/PetJJ03e+Mz167Z1KXwHkXhbnMJiOs7h3RVInAbNGjQTd+TeY+vzR5YWniSDBFqq6Zdb5wENezx1BwVhvrOl+n7mrOJI+lOPFekG1vCMgNNPQMWANLUM2zZfrPMAMvUEq2Dq210whoyZIho8NdYwW605CzXZb/50Uc6tGlzEnJ5pli1oaCxOgAaP16J11/XQmq4W50uxqoDk3gmkvb2RpcoJvgEGuxeThAiuUYRlDDprt6WJDIyEgUFbZGb6ydWyO+6qwyHDyfBwSETHh4B0OtbIDtbgY8+UmDlSq2oppDaNW1a1cSS+zp1Sobk5NNwcnIGBYHsS5KdLRNULoICVnUIPrp0MYhqyenTpIgZrXXLTp8D/vgLpefS8KfsLgQHVGLaW9boraidGlfa8imcUn2Ac1sTkfX1epQnZ8Pa1xXej4xEeWCoqASxo3tr/1xU7JsFRc4uVGiABO1k7Mx5Cy1aKmFvb6zcBDochj55Lc7G6tCy+2C8+vFotG6tx8iRBjgUb8F9HrcLEpKochhoOqXEXpul6NfiNBQJn9e4ZAwGGUrvKELK6dMIvHgH1MgS79EZVIiSf4VC10niHBVcikRI3GjxmqTzkHQW5R0+gc3JJ2q9HEv6bYPepQcuXpThwAGFsDTmeaFbWb9+OgFCOVYC0/Sfd2HIu3ch4/b78Gj5N3j5Fa0AhgyCQlr9pqeT7gaEhenQvbsRhEqRn2+sJHF7dELjnFV32RnpGY9Qwxl8mHGnoHkxcnOBkSNt8d135QgPbxoQYjo5iYmJQnzKiqOpoNm0JwWTzuqghMl3Yy48VD9hXKFlIkythTlFbm6uuO/17t1b9IwwpyClhlXpxqbFmgreJfDK39WraawImf6YPhcIbHbt2iUq1QTh5haSuUCXLl1uqZdVfY6L9CcGHaksYZmBpp4BCwBp6hm2bL9ZZsAUgHDllGVkVhUacyWQiQcf8v0o4qgW6enpWLo0H+HhRRgzpnWdPvzr18vw119yfPmlcXWedDH2FWC5mXH5MoSbE1esCTAoGGdlomdPo5aDwu/MTKP1rre3kVbFRNI0+DDNzQ1EeXkQfvmFDltnYW+vR9u2QaiocBK0KYKFN95QYutWjbDvnT1bgffeM9LHGGwKyB4dpFnFxSUgKEiJQYP8hbCcIIPNEZnjXLxo7EPC5JtYj2Jyrr5z+zwW6lTUSi1mzajEd9aPYUDmb5AvhWi0V33cUYYl2J/1BEjDpnPXib2lkK1bhyGxn8Hg5Iz4sc+i07O9EZY2RNj0isT+Cr3qdMlDOOv8BS5dMtLH+vQxCCeuRx5RYto0JuEGvPOOAm5uBvz62GDYFe+tsf9M9WC4tJ8M1ZFHq8wn95Nc2AnDPziKTp30mDAuC7ZFu5CbXQGDWy84tQgS1R+CMOXFRfC9VNWKl5/XBD0JnXt/2ByeVOv3YVXeVoyc2lOMPTJSIY6D/VUIjjjmzp314nooTzkEh5P3Q51yGZgDFIW74vLyA/Bu5SOqaqygcP5JueI5qKhglUwvrhUGQQT7oVCkzgoU/x4Wpsfp01VtPrWZuejXuhgdggvx5fFrzdmoP7r9dlv8/nup0B01ZRCAMHGt/n1j0ikJmU1pOqZJp2myKQGUxqJw8T7AfdFtypyC9z1SZ+j+x8qQOQU1edQVkILVHGFaTTMFJpIhAgGIaS8bVqIpkG9M2/bGOs7m1PbcdtttaNGiBX799dfGGr5lO5YZqHMGLADEcnH8K2bAFICQC03BeJ8+fRrVDYYreCxPk0YghanQPC4uDD16+KF377o7AjNJ7N9fhX37jNamfDDTPnjkyJGCc8vVaVZAmCgy4SwokAlaUefO1xJ2VkCYvHOFu3owEf7112MoLnbF5ctqxMeXQa22w/PPu6Cw0EoI2Jk47tghA3uTLFumE+5ZBEXUifTta0zcKUanNS4pQAcPEoAADzzQbvoJHQAAIABJREFUCllZ1GUQYBj7kBQWGulR1CgQNFDsTHBCkMT3EaQQRH3yiQIvvZQB9eXN8N23Cl1v3wy54hoFK+ZyT/yYuQ2VWmthA8xej7QJZkIeHKSDev1qKNavR8/2e+D1TGpVgHAFhBxpeRFHY33EuAna+Nndu4Hz5+WYPp1uUAZs2CDHf8Lao6VTXA0AkqvqCP2gAzDsvR8eZauv7qMSLtii3wKdQwf8/rscRw+WYMkDM9HHfz17/yENo3HJ+0NEdHGA3e7OsC47U9PlqsU9qAhfCLvIToCurIo+RWtwwDbHs1j9lzumT680VphKNfDxLEdmnqMAm7TwdbXJgN3O7oAm37j9HACvAPpAe5TsTYZBrsThw3JRReG1Q/2HWm1Anz56AWYYcXFyREfL0aKFXlRYWAmhSP3y5f2iISardqxq8TosX7UBD7zTFcOmOOG9z6+VUEi/mzDBFhs2lIprp6miLgBS1/6kpLO6dkDSDZhSuKTk82YoXPy+EgBxRdqcQnKaImBrzMpvYxxjUlIS+NPYzoQNGRuvA1auTAEJ/81zyeD9t7quhEC2sYBrQ8Zq+t7motZxfigCp4aIlriWsMxAU8+ABYA09Qxbtt8sMyAJW7kzlqzpm84baWN2BOYKHpOioUOHimOqLjQ/d85PJHXDhlXVNlSfgAEDVNiyRSMSdwIaitWHDRt29UHHqoIkBGciyS7n1D9UD66Oc3+mQCQ5GVi1iiu0FOVz5dsPhw55YvlyneieTotWOnAtWSLHwIGk9xgrK6Q3/fyzHB9/rBPggVUYo3YE2LXrHJydZRg9OlhQgM6dI83JCEBY4TBaAfPhLhOUIYIl6okPHTI6ZX38MZ2/0hAYeAEtWjjg5EktBoUXIiz/A2gvJyHrjB306+X41momLrp3x6AHfeEbaCUSYeYGrKxQsM8qS0T8TFgZvqj1mtqhPoT9ZzqLz/B4WAFg4v3ZZ0rMnq1Dx44GUaHK/30UWjseqbGN0+V3o7Dtz0hKMqCV4lfos0+iuNIV2paToFH5CU2FjVqP8Iwx8EZklc+XOw6AbNgmyNa3harymkZEepPGYzjKeq5G1vENaJnyMKzkxl4klZU22L+4B9w6DIHXh8/jkyU6jPF6Ft3dfoRcpkOeIQwJXt+iVZd2sLn8E2xOVKNwlQB4CdB5BaN07yEkpFiLCkpKCnlTRk3MyJE6QZ1jsPoRE61H2xYXodGrcTGzBTp00CMr64Dog2BvHyIqX6yQcA4d5r+O587NxOylnnjwwWsuWKdOyTFtmhpbt5bWem02xpe+oQCktn1yYaK6boAARdINSI3yTBsp3ojCRX0ZtSnmBkDqcppqjHNxq9tojHN5q2Oo6/O8j7PZHVf+ScciKOEzpDbgKlXWrmcf3djjbC5gyePt1KkT7rrrLixevLixD8OyPcsM1JgBCwCxXBT/ihkwBSBc0aKokAlCY5bUk5OTQQEq6VJ8oFYXmrM3Brn748dfnx//2msKQZF57DG98Fvnw4/caFPaREmJ0QWLVYXaZCxM7ClCpxaDIIE6EVYrdu3KwNatmfDzK0dERHukpdmLfh79+xtEt3Qml2wiOHOmEgsXalFeLoO1NQGDTFjcsk8Jk33a7PJ9rCQcO5YIX98KhIWFitV1gg2+RpYHKzEcn6enkX7F/2eiT/AQHU2KVgU+/pgA4AhGjGiJ0lInrF59HiNGBMHBwVHsR5eZA/+Yv+Gw/S/sKumKw+iO290PAL16wm/qABSWGrUdpFH5KnfDandVdzOh4TAosTAuDRqZs+jGzmAlKTzcKDrnv6dMyYKPzZ8Yqn0eckNllQpImd4VH8b/Bv82/QWgorUx9S88BlZO3N2NtKb2PofhElWTgsf9lfXfDW30Qjjk/V3jO5Xu9jIMEa8KfcbRPUfgqzwOFxcX5Fn1gz5dg16fPIJ23tnQf9IOquw1Vz8vOsCr3FA26CCUGX9DfeqZmt9XLaCbHwhZqQbn10Rh5zEXVFYajQtIwWIfEIIMRn7CMbifmQobg7GxV46yP0o7r8DZiwmiQ3VFRVsBUgIC9ALI5WVUovSxVzFXNhcrNthXEaBT7D5rlhqRkaW1Nru81RtLUyWttVG4CEoo9mVQP1JbI0VpJZwAhHqzutzwbvW4b/bzNLNgdYZVhn961b76MSQkJAizDValzS2k/ik0F2EFhEHgShBSvVpS3T7alOrHa6ax7YE5loY6iN3s/PJ7wQrok08+iblz597sZiyfs8xAvWfAAkDqPVWWN5rzDJgCEKkXBh2oGtM3nXx0CtGdnZ1F9aO60PzCBWDnTjkeeaRuAEL61MGDMrz4ogKffaaDg0MOEhKiGqRXoSMRKVLUCRA80AY3MJCUrlM4fboIaWlusLNTIySktQAxrKCsWKHAokU6oSlgnjVkiNEOmFUCitj5m71FTp6Ui14Y8fEQVCDqRTSaeHh5FcPOrosAGbTUJU2LNB1uj+CFWgLSxkjJoWaBWpWsrGysWqVBRYU1liyxRkSELeLiyvHbb7EICmoDtdpB0KWY6LIK4+KgRUT+HgRt+gIv7R0LF+RjqvxnlAW2waWBUxD69GAxVlnUY/As/r7K5Xj0+67YvPtOaPv0xeDX+8CmKBLOaYvhZJ2BIllb3PXWQvQaWooX+s5DG+WfVT7LY8iTheOT898jOLi9AFYEWARrPEbqUtlPZcAAAzw1f0O1f1ytX4WnVq2FzC0E8wYMg4sq7ep7Mg29cMhuPQJaWePiRTkyY/7EaI+34KVORJHWC2cUL8MhYgpCX7kLyvt31rrt8ojF0LkNgO2uXmATwqsWwwAKKnygGHcSNmPHATFnsHb+YTi0dhH0qwsXbQQtrksXPWQVmbDd0QMyTW4VipjWrT92yv8L1ysAhFa+7CPC80KKVo+yXfjssbP40e4x7D2qF5ofKbZsUWDePGvs2FEqKkSNGU0FQOoaI5NL04RTaqRoav3KhJOJKUFKx44dBdWpue1K6xo/dWhcILkVp6nGPH+m26LOjRqVugw8mmq/9dmuVAFhZ3uCiLrCFLiaXiessDF4HbB6Vl3wfqt6HD53qFHhIlVTXms8Pi8vLyxYsACzZs2qz9RZ3mOZgVuaAQsAuaXps3zYnGZA4vLyRrplyxaEhYXBn2KCRgraSFI0zgcKk4/q9C4m599/r8Bzz12zf62+a7pNkcL00ktK0TPE0bEQZWUHMGRIz3rrVSQdBhNl9saIj2fn93No3ToX7dqFIyqqQLhotWnTVlQmQkNJuVJg6lRScSB0IA8/rMTcuTpBqaITEhNtVju+/VaO22+nnoN/M1Y77OxioFYXQq3uLYAF3blojavXG0XSeXmkdRmrMLQEzs/XYtOmNNjapuKTT3ri1Vdl6NJFLl7Tasvxyy9H4OUVgZISAjkjeCGg4bOfVQ42+43ZnIrv5yUh4WQZhmn/hlamgj9SUBHYGmXDbkOP4cdhU7wblzMrUex6H5zD7kHMkkgUbdqHzm32Y+Csa4k8qzI5Je6YtWUPFo57Di1km2sAkNzyFnj//HqMHh0uur9zdZ9C/BYtDIKKxKoQGx26qRNh9Xe40UHrylakXiFJHWMw/yNvbP+7DDNv/w0dQlKFxW++80QoraxFFaI0LQYd0wdAITNWYKQeJaURn0LvPQz2W9vWerWmecyBQ6/ZQMJK2MU+e9ViuMLggjd3rcXTczuJiodiwgSoIzdD9pYeMj8gQzYYuW2/hF+IF5TJP8Dm5JO1bn+P24+wdW8LR8e2VylYBIW+vsZO6u7PTsPYtTNwynUAoqNLq1Tlfv1Via+/VmHz5rKrjlmN8ZVrbgBS25irU7gISqgxk0CJROGStAP8TQeqpnThqmtuJavbpk5Ub+bcmmv3eB6LJN5ndYbUqoaGRNuqXi3h3xkEqdVByY1ofqZjYOWd34WmFvCzAkjGAPUf06dPb+g0WN5vmYEGz4AFgDR4yiwfMNcZIC9bSgy2b9+OwMBA0dfgVsNUaM5t0ebSiZl/tWC1YdEiBebMqR2AUK9ByhE1FrTAffhhHezty1FZuR+jRnUSlJz6BFfnSSli1aK0NBWxsdlo1UqB++5rBXt7G5w4cRpZWeWiX4lIShXG6sby5Qq8/LIOixfLxRgGDTL202AVhTiNtKMdO+SIiwMmTaKmw1gJsLGJg0qVg86de4PNELlfdj/nD0EQj4s/7NHh71+AjRvjEBdnCyenlli50g1PPmnsMcLqiIuLBklJ29GuXUdkZvoIGhmBC+cuLc3YNI/JvtSDJC1Fh62/F6FHxR6MKv0TJ7TtoSgrxhBDJLLa9MJq17HwG9Qe3bo5CctiAqfhheGwUybUEJl/tfcFDB6oQWvd0hrTvCt+KObuWo6ff/YUlDZWqQj0OC/8TXBJJ7IQ5Q9QHan5cD6D55Du/Q5yc7Nw8GAaUlM7Yds2Bby9dZg4kXQdUuD0cD3/LGzTllcFQKR82IeidNBB2G0Ng6wi/Rq4uSKw/zphPfJthmLSJA3OHT0Hu7JDcHBQ4UL5UHz7kx8++KAcLk5a2O4bDsWSoxASlVcBtAW0DhEoG7ADquSVUJ+ufWXzgNtyWLlHoE2bNgK8EhjK5cbmkpwPWmzZtGqNdpUnoGjphdWry8X8strFnO2rr1RYt06Jv/4yNhNsjDAHAFLbcdBpiskluzOb2gNXp3CZghKurDc1LUpaKaf9uLmFufZO4TxlZWWJynZjivf5HKJTWvWKmrRIZkrzMwUnpl3ipXPYXN8Dak1Y1acDlmTHa27XkWU8/64ZsACQf9f5/J8+GlMAQitaerq3bVv7inJ9J8pUaE5AQy7z9dy12A193rzaAQhXu48ckQkdBZN8irQff7wMJSV7MWRIhHAhulEw6efno6MrERt7CXJ5AUJDPTBggA98fY0NG2gTSucU2nEypFX2V15RiKrHmDFKPPigTlQcKBYniCB4aNPGSO2aM0eOmTMp3jXqUPLyklBZmY9+/ToiMNDoxsVmiaTq+PkZBPWGVR1n51SUlsYiJ8cTQBi++cYGvXvrERYGUVVglUQu1yMnZzeGDw9BQUELsT9WWSQxPTutUz/CSgs1LQQoEj1Mm1uM9tk7kX/0AsL98pBRYIu0NAOsUQnXNu4IfbwfOk4Oh8dOL8i0BTWmMursMHyb8j3eHdobjvKLV1/XwBEr0v7E0u8i0LGjC775shS5u+ZDnbcZWp0CJ3PuxOHSF9GuvQKjtaFQlF+8SoGSNnLe6gXE2y6EwZCFvXuTYWfXGSdPliMmxoDMTM5DKT74oAj+SU/DOnN9jbHprdxQMjIRZUn74HLyHqhkVJcb40zCaJSN+VVUnb77Tolnhr6DUHwCa1ke8gztsXjPMsyaHw6b0sOw22s0SACbrdPIayaAbkBp740wqJxgu7v/lerNlS7x/D9rb+x0Wg5HZ/frfl/kp06hYsCdaG1zCa3DFXjhBY0Q+bMnCN3O3ntPhaNHFfjlF6OW4lajuRKvho5T6hJNiqdpmFK4JCcuUzGzafduCZw0JoWLPVOoSzN16WvosTXV+83VOYzH21waC+6rOs1PAiimgvfq1RICS4IDLnw1ZdBkhSJ09gAZNWpUU+7Ksm3LDIgZsAAQy4Xwr5kBUwDCzs7UarRr1+6mjo8PBN6QTYXm/Bs7xF7PXet6AMT4sKMtrNFm99VXlfjxxzKkpm5Dly6dbtgEi2CAPThOnChAUlIytFoVevTwxaBBDoKKJYXUXT08fMDVjuqursZVfIrkP/xQgRdf1InKA22BmeRTOM5md0z2P/hALqhaxl4SMmRkpKGkJAehoRGCRkWwQgBC8GBsUqdFbGwyHB1T4ebmB70+ENbWMsyapcScOVrhlEUaGN9rdNDai/79A5GX5ycaKxIEkepEoMIqDB24SAmj3oPzRTE4O7mr1TL88oscw4dUIqTgMNLWnYQ2LwtebZ2gza5EROJf6GodDd0CQOnGTutVT33Uhp5Y/dM4hN/lgx73nII2PwEJqb5w6/c0TiY4IikpHYUFHfFA0L3oG/BXlT4j5/UP4SC+xCS5IxSomWAn6Kcg1f9beHikY82aZKSl+aGgoBj+/irIZHQgU+HwYS8smDgHUzrUrMBo3QagrM96xMTIcXJvEvzxOxxsipGR3BKZH55DnzYZaLV9KeRJn8Pu/JtXQSVhRIXOEZe77IOn+hxsD9197aDJQvsWwINA6cu/QOc9GqrEZbCOfumahkTphNKev+NQglxQAAnYeT543jl/EnCUNpo9Yz6S/ziB0diEcXdpMGaMTlR2eK0wXn/dCpmZ7HNz6yCEAIS0IglI39QXuQk+xGZ/FBtHRETccOumYmZTe2BTF67aGineDNe/uag6NzzoWt7ACgOrRkxwzS3+aeqaRPOTwIh0nUiCd14LrJhwQc0UnDS24J3XNQ0M2JS0qcGOuV0DlvH8MzNgASD/zLxb9toEM8AbttRo6tChQ4LPS61GQ4Olc1rjsopgKjQnxWLnzp2iAVld1YobARCORaIwjR+vQmRkBXbv3iKSGdpAMggKmOCTBsPqAjUSBBDZ2TqsXZuKjIwsBAbaw86uNZyclEI3YaqdJGiKj0+Dk9NAQWtSKIxVChaDPv9cjr175XjtNepPDMLxiaJ0ggr2+mAw+Z83T4EnntCJRoT5+WkoKkqFr293QaXie41VGIITOsUkwtOzBAMHBiEjw0MksHyNrloTJhgF+fwcKyB03WIFxMenNUpKfGFlRfG6TNjE0hKYK+kEIKyAkN5DYT8pQXTakty+du+WC9oYheEZxzcj4txJZO67DKu2PvD3S4ZX/kG0nHwaMoVRo8JEuhR+WFV0CL/NS8fd+SvQruI4DrV/ED9qJ2LcJGukpRWipCQd08floW9J1WZpksZjs1U0euumwEF3skafj2O6N+Ex6CWUlydj585EJCS4oHNnH3h7OwnhORP0sLASJPz2Bvq4VrUR1kOOvXYfwuDcERcveiIlxQU6nTVyc9VivjqHlWHE11MRdHEX8JUcMBTV2P959Uvw7v8I7La1Awy6awDjGICPgMrnZqDyjXfEuZAXnIQi9wAgV0PrOQIGG1/RuJOJcIsWoaKylZNjBJescLBRodTXLjZWDo+xg7HFYyJmXXweM2ZU4IEHtMLuV4qZM63FuV682Nhf4WbDXAHI8ePHBZ2qPgCktmM37d4tJZv8bUrPqa2R4o0STnPotVHXua6ranSz10Zjfo69mFjZNrfKkdRsk2Pjv0nPkgTvPP7qgnd+f2+lokbr+jFjxgg6GpsyWsIyA009AxYA0tQzbNl+s82AKQA5evSo2G9DuxXTSYZ0ASYYpFiYCs25arlt2zYBanxMrYBMjnDOHIUQl9cn6ITFZN7Tc1MVwXxSktGBiYm5UQjMfg7FAhSdPm0FF5dAhIa6ISNDJkTmbNxnqp1k4hYVdQl2dgNE0k4LW26Tbk5//inDoUNyPPEEXY64b2Mn87CwqtuYP1+BSZN0AmhcuJCBwsJL8PfvJhJpggE2o8vMvIzz53Pg70/nrAA4O9uI5oPsxL1ggQKPP66FUmnsE8LqDcXuBEGJiZGorAyDvb2P2LcEyGh3y/ESvBD40IqY1CyK3jl2rsoTdBBwbdokw5dfKhAYGIvAQCcknpfBIfEweibvgK5cCedxfggL+hP6kssoTFRDs9Ud6RH34HSnyVj2gzPefiQWMZ/vw+XLOhjcvCDvGwGX0DyMiUjAAPmUWk/fNsNmOLpYoVv+KMhxLbnORzvstNoNb78SZGWdgDY/C92Vf8BefwHlMg/EGGbDJWwwQgILYP83TRHoYlU1kvzeRqqyP86c0eHUKVskJzsgP18NJycZevYsx+236+C38hs4dXhfND+sHqfKHkPQfe9DF78STnEzIYMR+FEqX6F/BtaPfgnNxImoWLpUnAuCW4IzupzxfBKAMOlVKNqJRoVubnpoNEaHMjYqZGWKwXObsCcD/WZ0x6NdDmFDTDD++qsUPXpU7X3z0ENqBAXp8cYblfX5KtT6HlYg+X00twoIAQiTwcZO0iR6jmmlxJTCZZpwmjZSlCaPBhlMptlMztyiqeasMY6TwI3VI3OcNx4f7/sErXzusIpkag8sXSuS4N20r43U26a+gveNGzdi4sSJYi6ob/onIjIy8mqfLTqn0RbYEv/eGbAAkH/vuf2fOzICBOlGzJs2Kxm0VqxPmArNWeomdau6IJAPgc2bN4vX6rpB16cCIo0nMRF4+mklZs3ajKCgIFFtYUgVAK4ql5ayd0curK1jEBDATr2dkZVlL6oMBBa0WJUqF9J2+QA5cCABzs6DhUUvk3ra3bLK8OGHRnenZ54hJcrYqK5z55pd1c+fh7Du7dRJj/Pnc1FQcAljxkQgIIDdtDU4fToJKlUWHB394enpi4gIIxhifxJSs/7zHx6XDrQdZgWHTlkEIL17G3D0aCSKitpCp2spqhycB/arINDi+1ixcHAwiGSXnyfgoJieVSEK1Jnssrv6nj0yLFlSAHt7DQIDC9C/vyNkMg/knMtBuwsb4HVoI3Z4T0Bu257obBUNxfYdcEs7jV8UU+Dd2ROygf1wOVkD9f6daHEpCh2c4mA7YwgGR1A4cS2kKsp6eRzU7oGoyDgF/7LPoS/LgtYuHDles3AythiOjgno1KYAndIfgTWKjBQuETLkdfgZCudgOO3uXuvl+Ev8Oxj61Axx7GvWUISvhbU17T3L4eKSjxYtsuDgUIGhBTNgp0ivQS+bv/kT3DbzIQEqMmKPIFi9SQC/LOVw+HbsCZ+Sc7AfMACVfQcg6rVVoqrEMIJCPWJjjwgLUr2+naiAtGpl7JSeliZHhw66qxUObp/GBbrPvkXwt29ibI9URMeqcOJEqVGsbhL33qtGv346PPssLaIbHuYKQNi3h054N0vvbMhMSBQu00oJqTq1OSxxdZwOXRRT3wyFqyHjauh7uSBEDUw4G/OYWZjrdSZN043Am2lFzZTGJZki8FqQ+tpIlTUC2OrPN4rPH330UXENkY7Z3EEKNUEWQTRBlgWANPcZaP79WQBI88+5ZY9NNAOmAKS6EPt6u6ze0Zy9Q+p6gG/dulWsyhAw1BYNASD8fN++KixYsFXQr0JCQsQmqXlg13IfHw1iYy8iI6MQffvaYdCgYMhkCuHKxJVp0pWYkFfXOly4kIrIyAtwc+svqgbUh1DfzqR+6lQV+vbV4847jSJzLnQxwWeYboc6lZdflgsKVUpKPoqKLmD69I5QKHLx++/JyM5Wo1s3P1RWOolKBbfPZxbBxuLFCqEVYUWDQIn7oHi+sNBoZXvkyF4UFAShrKylSHIJMiSqGY+dx0THKXaEp00wnZjooEURNnUrXI2nFub8+QLExychKsoXKpUr3nhDLuhj7Pbu7m6Ag40Gx3+/AM2xWLTUJSFwbCh6PtUVpct/wUufBuM+vwNw7eKHZTkTYOerRFDs72gXtxe9H9kN/75JVU7v9tTnURTytkjwSZHjD4FicbEGVlbUv+RixAhvRFQugn3q11U+y9nVOUSgoOcGuEaGAPqKGhWQVRm/Yd63d6FLFx3uvVcjKFCsNvEc0d2rQwcNHOyL4HRiCuwLd1fZfgWc8OCag3B2VaOkxFb0/AgIUKOyUoWSElZQrmg0srJg07UH8txbYe/bkZArOX5WlfTIzz98hdJhBCDUCzEICnkeCVSqh23//tDZ2KFj/m5xDo8dK61iw8s5GjvWBvfdp8FDD13rol7fr7+5JoZMpknvbA4AUttcSQmnaaWkNgqXqbbEWN1S1HfqG/19R44YAS6t0c0tSFmlyNsce5Rwrm527vg8rK4rYWIv0ZQJonldrFmzBgEBAcINbOHChaIhZ1M7ttV2DSxatAgfffQRJk+eLH5bAIi5fVMafzwWANL4c2rZ4j80A6YAJD4+XtA3ruedXl1oztUXlquvF+ywzupHXaXhhgKQsWOVmDr1ADp2tL/6cKZF7pEjxTh2LFkIvLt3b4GBA92q0KzqGiNXvXftysHu3SkICekAnU4BSkuY+BMMDB+uwhtvaBEZKceQIQZBb2Llgskik0zazpL2RbvgjRuNYKBlyxwcP34Rgwc7IjPzInJz/WBl1RoqlbHzHHUKTPi5DYIQ9jiJitKISghF76xysM8Hp5Zi9PXrT6K83BNeXr4CIBGE8O+kkR04YKT9EBTxsxTrU9/C7ZImxmQ4P9+Av/5KRUVFqhCmnzvXCjKZJ+Lj5ejeXQ9nZ+PsMIk2al8M0KVnouXx9eh96GPYDOmJgfsWYuwkG3idO4Cjf6Sgwt0DshA7dJvQF+5n9yEg9U24BqdCo3ZEvs9kTPt4tqAi0Z6YYy4qYq+QctFDIDCwDBMneqFHD3sY9twNm6yNNU6PXuWK/KHnkH3wPbTJf7vK60na25DQ4gd07GTA999b48SmPXh66Hto5ZuJfEMYkl3no01nXzghHnY7u4nKSnUK17yDGzDwHnts2WKL1asDEBRUCDs7vaCuDR6sQUSESmg8Lp8Hgsf1hMLGCoe/OYgLqbZo355dnw+LFeqgoHDs3KkQ1DteB5w7VjFMmwxSM1RYKIOyOB8te4Ygb9FHCH/7UYSG6rB+fVXxOa+JoUNt8OyzlRg3rn7URGlyzBmAmONqPs0nmESy95FkD8yqiOSwJFG4TO2BqRlojoiKihKmILR5Nrcw5x4lnCvqGUkFlhaobmX+CD5M7YGpc5wwYYK4bhgUu9Nkhc9C/tA0gFonApWmDNLgWB375JNPwH+/+eabFgDSlBNuJtu2ABAzORGWYdz6DJCWILnLMHmhFmLo0Cu2pNU2byo0Z68Q/tSnedju3btFs6bQ0NBaB0wAQg1I9apEXUf3ww9ybNx4Ga++mik45UwWKDo8cSIJSqU7wsLaitXs6v2xuBJPKhWTYS5sUizMxJtVhu3bCxETcx7DhrVHTo61SOCpE+Frd9+twuuva7FihbHUvhVzAAAgAElEQVS6wSRTrzfSnmiHSyDAisXx4zKhQ1mzRobRozPFQ8HLqwROTqzCtBAr66yoMDElAKGDFoHE1q0y7Nsnx08/aUUlh1oOjrVlS9K9CCQM+OGHM3B1tUXHjrQ1NtLDpOoJKy8ck52dUZzOvh48LgIrGugEBJQgMjIGp08r4Onpj/T0bKSmesLNzV0I9Q8cMHYkHjlSj8REIy2sb1+jaxcrNV3aVyIoZgO2vn0cyy6MQGgfJxzMC8ND/Y5DvnkDHEoroBs0BP6TeuPi8VxEfX4cPpdPobV/Jb5wfhGebZxEQ8fIyFxkZuYhIMAKISEt0LGjXDTsw4mXYJP4cZXTzePPRnsccFiMxEQVvDQpCLNZC2tFKXIUvRFreAb+AQp07aqFVdYmOBy/3+idfKUqpVF4onjATqiKz8L+sInLlclefvrsfoxe9CQyPNthzRqCPDlUKi0iIujtn4mAgCxxjvPzrBBUtA693lsBRYEGJ9+ZDau+LyI756RY1bexaS+cuHhNcQj8TYBCu2UG9TpxcXJBleO5Dzm9BmHzH0Hstnj0u91P9Dx5772qug9WRwYPtsW8eeUYMsSoTalPmCsAudkV6foc8628hyvGubm5VWinN9IMEIBUd+EiuGpsCtfBgwfh5ubWKEn0rcxRbZ9ltZzPg4bqBRt7HHVtj46O1BxKFN2m2C+dwN5++22sW7cOo0ePBh2x2LuFz1PSscgSaOxrwvQ47rzzTmRmZgoHLoIPCwBpirNsftu0ABDzOyeWEd3kDJgCEOogeAMdMWJEjRvn9YTmN9o1b5C8IdclQH37bQWeecbYY6Ou4Ao/GwMyqSaN6rbbKrBixVlhgUq3GK5K3QgUpaQYherZ2UYAQhtb9tBg7NhRhOPH2Q8gFAUFbAhoBCDffy9HeroM06dT6CwTPUnoUkxKE7dB5ylug8kmKWD8/zVrKtCyZQKCg3PQoQOb1HkJsMPkk6vkrKAQgBCMEIBQhD9/vhbOzjKhFdBq2WRQJihZpFWxseFPP52BXG6PDh38heCcwIAAiz8EMjwWvo+JLilXdGBiB3m1OhcKxQnhEFVR0Ql5eXY4cSIFdnZWGDTIUzRXpLiac0+nrNat9eK4qJO5dMnopEWAxe1xFX/uf8oxwu0I1HGn0KldGdK7BsMhsBfsDuyF6sAepAb3xWmvEXD0UaPzyZUYdPRDfKychR1OI9Hv3jy0a+8Bf38fAbLYMXzIEC0UmkxY7xwAK03qVQcunUGJbxI/hs4tGHl5auTk2ECns0NOjiOsrKwRHq5A//4qkB5vE9kd8uKzNSocf52fjW4TJ8D3SPcqFRCpGvL7728iYt2vsHryfkT1mSncxbKy5GCX8okTtbjzzjKUlRbCKfYpOOdvpFEW8B4gOw8kvzcQJ/1fEA46FRWtcf68I/z9rQVlJzdXLmhhPH8MumCdPSuHqytXUo1gcchH98Ap9yI2vXsYkyfb4p13yjF1alXKFSl4Q4bY4uOPywUlrD5hrgBEEuybG52oviv51ZvkSVQuyYWL5510qeqNFG+FwsX7ppeXV6M0hq3PtdOQ90RHR4v+HJ0phjPD4KIXKVL8acqYPXu2sJnnfBBs8HrgM5R9SOiO1VSxfv16EICwSkYQOHfuXAsAaarJNrPtWgCImZ0Qy3BufgZMAQhXdChEHz58+FXuM1dzuNrF1+oSmt9o77xJMlGry8+eNrfUV7CHRW3B1WB2+aaImok5+yw89VQlPvvsMDSaMjHW6u5btW2HndCZ+DK5JrWK1QIKxkmhIn1r8+Z4BAaGw93dRlQemNjffbcSixZpIRVvHn1UgbFj9SJhJ6AgmGGiyeT80iXD/7F3HtBVVekX33nvpSckkJAECB1C7016UVBEReydEXUcbKN/HR0ddZzRUUfHsc3Yx4rYG0pXkCJIbxJIqCEJgUBCenkt//U718s8YmgaMI45a7GM8N4t597c++2z9/62tm7NUW5uvnbuTNI116xUy5ZDtHVrtDlminn2TzGPT4HzQsL1wAMuzZiBSd0q+GEvYB9g8Mka4b+ffkqL42g1aNDGhA7CciD1oqAFAHXvXmXYHUCS1SbYr8WL81VVtVetWoUpLq6VQkJcZjV+1aosM9dnn91MNijDt0DbX/JMKMSRnXMsp5xiAS0bjAAEYYI6d/AoNH2tBuR/rFaOAhWdeo42xg5R7trdapU2R83CChR21nC1vKC9Grx8rz59p4lecf9GvztljcpOHae8khAT0DhwoM8Ar52b9iph798U7U9TqT9Wi/MmKD9ooPGI7N/P3HiVmek1AC8oyK0uXfI0YMBexcaGadT+8XJW/TBNfIvnYp33jyl69KL/07i2hzIsOxxXaFnVv6TUNI3959nKObOtYs5yyOVya69/sP6z4gE1TgrVTZd+qwZLRx5yO1U9LwUtl1Y+fr/2tu2vHTsitHJlvMrLXXI6XUpIcOi00zzq0iXUFKQbN4aZtsLcd8wfZvaencrVeXgrVd56q56O+pP+9rcQffppuZHDBQ7kdGPGROjNNyuM7+Rooy4DEObicCzo0c7rRP375s2bBZjo16/mRgdH2y8m4OqegUAJV6CROTBI8Wjb5d8pbPG5Hc47dyzbOFGf4T3BqB4seaL2d7zbRfaL/Co5Ofl4v3pcn7/++utN9hVs1ckaME94qXhPv/ii1Z68HoCcrNn/+fdTD0B+/mtQfwS1NAPoW+3wJuhcutXQ2x1pyfEYzY90OGyTFcTD0fVvv82KMUXvD027bDcnRwI8UAjT2Skjw69XXjmg/v2zdMEFXsOsHIsu2zaq20ZlPBY9e1oeDgLwPv98pTp37q3ExAam1S0r1cOGBWvhQqsjESDjhRcchn2gYEe+hF8AJiM11a3c3C3y+YrlcLTT8uWNdPbZ8zRwYH9lZsYYyRSAg1VtZD2wIEiyliyRkpODdNNNPmPQZh8AENgLBkUrbExREeEUeBK6Gp8Hki+YIEzn+FXockXbYBia7GyPNm3aI7e7wnS58noTzf7xiHDMr7+eZQyTo0cnGSYGFgb5FvIrAApMConzI0dWaexYi6WBOWL+AUy33OLS6af7tHGjT0OGbNCQ1lGqnLNCWxfnandiT51ycXM1ivVr0xvfqGfmF2p7TrzCbrpTLz3u0bPvJ2mM5mhAu/1K+O04Rac0MVIymB+Xy6uFC3NNh68uXcI1ahShmBYAmjPHYdgdPBqAvxYtytWy5QGFhBQoZeuFivRu/wEDsiv6t/J3u1uvvBIn98a3dHbvz5SU6FOGe7QyI39nvBpffRWi20fdr4iMJ2wFl7k+lbFDtSL6U637YpZu7FFDi+F3JP9sp1KfeFKl/X+jmTNpUFChykrulTJ17ZqlhIRicw1zc6PVomK+2kV+o6CgYB2IHKe4fr9R4+8WKOL881WybJmu+3sXzZnj1PLlZaZ5QOAAeI8fj0+lzHRUO9KoqwCERYiYmJgjpsbX0iPtuDbDajWAoTalRIESrkDTe2AXrkCmBK9ATRKuk7WKf1wT9v2Hj9Zl6sdss7a+wzuN7CnYtsO1fq+tfWH+hvWYM2dObW3yqNu599579dxzzwnPZjyrUPUA5Khz9r/0gXoA8r90NX/l5xIIQNBCUyiQIQAYsRPNj8VofqRpRCJFl5DDtfedPp0MhSqz2l7ToADDXwH4cDjKtHDhLpWXV2j+/NZavDj6mHS2FP7p6eRpBBkWheIdEAF7wM+sKi1YsOCQwETMwMOHB2vRIo8pwpE+Ufy//nqQLrrIYk6QaW3alKuZM/eY4+veva327IlWZqZbq1dn69prG6p1a1rdWl4TJFjsjw5YyJ/uuMOlBQs8pvglD4QUcwbdq2AgAEv8XFGxSSkpJWrVqo8BYwAVDOrIp5BIMX+Alm3bipSWlqWSknB17ZqkQYPCjWcEBok8ENiUTz7JMUnrPXs2Mdvv1QvJF7kWzI2E53XBAumddzCoV4mIBIIZy8o4f47TMlQ3bOhVly7rlZLSQc2ahauy1Ktvp2xT5epNCi3fp/xWbdR2ZDON8ayQ99NZ2t5koBY1maB35iXrd7HvaGT2VFU0baVGN12srQndtW5dtrKzaWiQqI4dQzR2rN8wQMwd7YOZewAQoAmgRAgjLFXQni8V9u15CpLvoISrwNNUHxS/qMbJPqWlNdSWLXHati1e69c3VGysX3fcUa4JE0L07BNleqh3k++DCA+9+4p6vSW3M1HxK8cc8g+2hCtj0RVq/sq72n7/y1rY7GIjKeOeQcZFG95mzcrM6njUpj8qofCDQ7axNeR8ZcXfpG6PPaYGa9Zo34oVOuucJJNTs359mbn2gYMWz5dcEqGZM8vMvXO4UVcBCKbghg0b1jlDNflFFJC9e/c+oW+CQAlXYHtgGBQGLG5gu1d+pnMYjTt+rnyJI01IXfX0cMwsqBEQyMIU3sMTOc4++2zj0/noo49O5G4ObhslAr6WW2+9Vddee+3Bv3/mmWf07LPP6quvvlKrVq1OqPflpJxo/U4OOwP1AKT+5vifmQFejPZLkBcj5j1W5/j5aJ6KY50EXvL0SR80aFCNX6G4RBI1ZkzNAATGYcMGWJB8ZWXtVqNGDnXs6NDdd7fSunVhRz0MitXU1CDTihcgQuHO6jcAwvadMAcEOvXo0Utud6JptZqaKr3/vlMffOA1naUACBSYc+c6TNJ1u3Y+RUdvVmZmloqLWyssrK0kl8khqajw6I03ijRpUog6dIg2EilW8mE5yP2giFy3TnrrLac+/NBrgAkJ7Byfy2UV3TAbsCEwQHv2bFVKSoGSk/uYbSDDgnkBLHAu2dlVmjVrj5zOnab7S2Zmilwup8miIC+E+UW2hZ9l+/bdatq0TM2btzMABJCBLIzz4ziQYCEHgwlh38zFFVdYIXubN1tBhx9/7NSQIZUqLc1Ujx5J6tDBug5ffulRenqhYoPydU7wMiV8t0T+bt3lHTlKzrIiVXwxX99ktdK7FRN0zlleTSx7Tl3nPqv1ji6a3fW3cg8+U82bo6e3vCcwY8Zrs36XPJtekyr3a+eBLlpffq169Qk2IAQp3eZFS9Sq/Gk1CN2nInXS8so/q22XBHXvXm46by1ezBz5jPwpN9elvXuj1KFDgXq2SdOTp46u8R4qb3KXKnvepaCl1yim4JNDGJLdEb9RWsxVavL110p5+BHlXDpGQWMsGdj+sLMU3v1aJcGiFX2nyAWDavSgrE7+QHnl0Rp68cXKGThQa66brMmTRxtg9/HHmQf9BHZ7z7VrHfrtb8P05Zc/zA+xTwAAsmfPnsP+rh31l+UEfaCuApCf28tgS7iqBynalwFmF+AWaHo/Frb3BF3Gg5utyx26WExaunSpkfwGhuKeiDlBLYAM7bXXXjsRm//BNjG6H813g+yPhY/68b85A/UA5H/zuv4qzyoQgJAKjCba9mvU1sMbo+fevXs1bNiwGucYaRQ5FBdeWLPGnRWtpUs3KS2tWPHxTUwnKLd7myZOTNKHH0YbORKDwhijOqv4FLD2SjHbpqAmG4PPwCh07+4/JIwQeQR5JTExvVVYmGhW+KdODTKteO+4A/OwBR7YdnCw9Morfg0f/p1atNir7t07qGHDZLN6TYghjENpKQnw29W6dVN17RplWAaYD9gLwgJhFF55xUo+79mTVW9kVVXGv5GRgc+BwhuWgRa67HeLIiIIEOxjCm6Oh0Ruttu4cbm++CJNGzY41LlzgiIikszPgBgADAZ5mAT8B+w/M3OHEhIoYrsYwAM4atUKAzssj8NIoFiYtf0nMD9IoK691q/g4CrT9hdwxlxHRu7TqadGKjw8Qrm5hcrJyVdQUKiSkhobk3hUqFuVC79V8JezVVTs1IF+p2q9r4uho+ZtStbp7TbovJuz1HDTAaW/nSVXSaGcg/sp84xJimkSbjpzxWq9QhedLoe36OD9k+MbrMXB09W9V4iRxNECmfNjbpkfmK1TT/UbQz5+mhkzHMrMdCgiwq+QEL+6di1Werpb77zp1Op7mpsU9Opd2HxPOVV43kPaPe46+Tc8pebOucrLd2jJrrNU3mqskpJ2mZXGlDm3KfSPX0lnSLrUOsTyFr9VRZdHFbLnc0WumVjjfV92yqfyNR4l/9q1ajBqlHa+9ZY2x6Tokku6qkePvbr9dmR3SO3CTQEaGhqlTZvi9fDDjfX11+U1tpiuqwCkrnZ02rBhg8l4gOWtK4NnEYAE6SpteDk+CsrqWRSBoOREdOE60nxQ4Ddu3LhOpm4zV7Y5G9nfiRq8O/v27aszzjhDMBAnY7CQx3uq+nj//ff1wQcfGBYE38u55557Mg6nfh8/wwzUA5CfYdLrd3liZoCHKBpo22jOXqCua9O8R4tcWtKOGjWqxpPAx/Dll1aBW33Q3QoJF2Z4jgsjPINC6/nnPXK5OuuRR3ymcKcL1a5dVkI47XGtAD6L/aCIhg3gcxiqMZ+3hbD4fjAPM2fOlsfTWz5fotHaX3utS/ff7zXSMLpN2RKpkpJ8ffCBT1ddtUvnndfeFIeBA6CSnu5XRsZKLVrUU7fcEmK8HAAUGAiKflrrPvigS2vWeAz4AiDBRgCQACMkrldVWXItZEZVVZuUkVEhp7O3OQ8kWxjaGzXKV0XFepWVhcjv766KikhTgMPUILnCZ4LUDCAFy8GxLV68Sx5PhbzeDsZIb3VrskAP8iZYDv7+9NOt42Hu2B/zCHsDKEICRuZJSspe3XBDsNavL1deXpG6dw9TTExzLVvmNIyLlQjOdQ3St1/ka8fcHUrIWKnWXcK0p12ypn/dRh2KNumpnq9rxYj/04rMRJVOW6DCfR4lt3Jo8AMjNKDxNXIVrPjBvbFajyq81y0H5WOY8Lm2nAPX7JJLfOacYa+++caSrcXFWS2Q8bwgn4Ndee/exzR5yF8OYTh2VfbV9nWna+hzj2l7h/7KuP4UdQifp2CnWxv39dajM+7VrXdEaGTPLEUsGKiqnVLQXyT1k6pusDJHDgxZJofngGKWgUx+OEpHLJc/2mpNHXLffQp+4w2Vbt+uVetCNH58uG66qVgTJ+5VUVGJ0tM9ysryyusl5DJac+e21iuvbFBsbNTB1XGKUH4vAPuHYxtPzFPk6FutqwUrzxa6F9U1MzXPOzwgmI3phGVLuKoHKVaXcAWCElbCf0oXriNd1ZPR5vbod1XNn6BIR75GNseJzOLgmtCFcdKkSfrb3/72Yw+3Vr5Xb0KvlWn8RWykHoD8Ii5T/UEeywxAV9NtBR00pj0kCbUNQGBWMMzR3remgdTn1Veduv32/4au2dke+FCQIFAgUGDZA0Czfv1mPf74WcYkToAexTUr9xitWQln5Z8iE18F4IQcBgppWuJSnFfX0s+ZM1dlZV3l8TQzYAAA8thjXlPAw4js3YufYLf8/r1q3DhODkcrXXfdoWeE3AsvBpr9des2KCenra65JsJ0nQJk0C6Xlfa337ZW6l9+2We8IZi8ASh8nxV9Fu7CwqzWvTAUPt8mrVuHN6Cf6ahVUODXN9/ky+/fo4SECJPvERoarKKiKiOZok1wu3Z4RCxGCACC9Iw5mjcvW5mZBO61MBIn2CKYEYBFnz4AIGu+2EbjxpbUi0Id/8zKlRZL0r+/X8uW0ba2TJMnbzVFfosWzRUT09DM96ZNXIcq9ezpMx3EkIytWuUwEq+ERvsVvmmBvKv3qVfYVn3d6jfaWJCsO6Of16wNTVXQuo86DolV68VT1WD9Up3+ykwFhfxQnrc79App4IuGkZo506F16zCpW+dJhy2uPdcOtih9ZZoi9n2kiJAyZVWeImeLs9SzlwW0tm6Rpj40RRf2m6rEuHLtqhis7VH3avioEIWWZKrRk4PlGnHgEICyL6iL7p3/jnolfKPfdZ5s3QTkkt0tCWB7l1R6ykfyxI1QxMrLFLJvtpFhMQAnlUnnqaT7iwpywFTxN0GK7NVXvi5d5H13iqZOdenOO0P12mt0vKHJgcMEOfp8Hvl8Zdq82ac5cxrokUeWyOv9r48AuRbFK+F1FF8UoceS1XMsz4qf8hlayqLHP1wY6U/Z9k/5LpIWinSC4+rSAFjwXOa4YBoON/hcoKeE1X8WlMx9FkS3vIgfZJYE8wvzE0ddNsjjZeS6Dhw48JB3xk885R98nXdU06ZNdd999+muu+6q7c0f1/bqAchxTdcv+sP1AOQXffnqDz5wBniI0lKRJGBeVtC7tC/EyFZbIysrywAbAEhNxRCsxIMPOvXAAxYAwbB+tGwP+qwjn3jwwbO0aJHXrMxTXPNupZ0s7WVZ7aY7FH/H/9Myl85WABC6XFUfM2YsMJkOXm+yYQ6eesqpV1/1GmnPli0VKixMMwV9+/bJOu20RuaYb7zRZ1gKVto5D9rE4uVgtT0tbZ26dk3Ujh1NjLyMlHMbgEycSIFpZUXQBYpinZV5GBy+T0cwO2fE6gS1WatXFyos7BTt2+fWpk27VVzs1pAh0SosTFJeXpAGDaoy5wdTwfHAlABGkpKsNr0cG0bunTuzlJbmU4sWLTV6tMVyLF5smfzZL8eJbIm6h3bEgwb5zTEicwJc4c147jmH8vMrtWZNiK69drPGjk1WZWWk1qyxwh47dfIpORnmw6HQUAtYNWhAd5r95jMNG4aoXbtYtQjdp0EZ7+mLGU5N8V2qi888oOKdBeq4dYYadYxX1FlDNS5xhByhxT+QSOXE3KKYkY+Yy4iBnuMGOHI9uNZ0OAOIOHK/VMjSi+Soqjx4yUuaTZaj3z/M/zNfAJipU50G9HHPDB/u17hxfgVXHVD4jBZS1Q8lWjtbPKXUnXE603Hlf28lpNd3SoqVMj6ZprCm/RUZ5lTI5r/KuZdOOQ55EseqvN1dqgpymZVtAOK2bU4Vbd6j4b/rr4y//0cJE0/VPfdE6L33QvTaa2UqKnKqZUvrGLZvd5igw4ULnZo+3aUPPig0RSh/8H+wqGAneVOEBpqbWSEHlNi+ktr6HT/adupqpkVd7ebEghAsA9IwTM7HM5Bw2a2B7XT36hKu6kGKdD08ntA8ukwBJmuTKT+eczzSZ0ko590wZMiQY+qO+GP3izSYa0NHqsmTv1+E+LEbq/9e/Qwc4wzUA5BjnKj6j/0yZoBVNLtgoX86XVdqc6WSoogVKRLWD7f6RhgfaejIRwArR8v2sLf5ySdjdeaZQTrjDL+RLuGfgOWgkLQN2sdyFWAh3n57rYKCEhQd3cwU23R9+uc/vZo7lxdajlq0CFKTJikqLw83xfmzz1KEW8U++0RaRco6RSJA4MCBUkVGulRSEmb8J6zEU+zzBykWDA3gCLkURTNMBGAHBoRt8MdqkYsno0IlJT45HGGGrSKJPSIiRFFRTrNfAA8ggcF+MLLTSYmuV/hAOEbaDiOzqqoqVV6eVyEhMWbbtoKMYy4vtwAJ3R1hYWATACG0hoWpAlwQlLhtW6FhQnbtwmDv1oMPBhsQCPOxZ4/V0YzvAabYB1ke+/Zt0+rVocrNTVazZiEaNYq2wNZxuqo8WvjKdr05K0kTYuappG1XdW1dqhFbXlWPXnMUPHLXwQ5XzLXPG6wV4V+q05i+5vuAKzp9cez8O2wOwC2xsVfhs9pK7jwFfc9B2F2sKgZ/IX/jkUbKNnu2w3QloyOb2x2kf//bo2HDquTLX6fohTU3T3B3+4e8bX6n4GVXKHjPpxZDwnVzS557wuX2Rmne00+bixARESWXK0YNGkQpMTFa0dFRBwu+rVthOLhvq9R4+tvq//H92r1olRLbROjcc6O1aZNDjz5aZq6Ty8V9aQEQGK7HHgvW2rVOTZ1aYa49ckd+h5CfBBafgJPS0tKDv+csNgBMAtvBnkhzc12V7CDVgVntTKJlHRqwGPhmMBzDAP/UYUttq98Tdgt2nrfVQcnh2DO2xXuCTBcYgLo2CM2lvfLw4cNPmASNc0YeTNDhlClTdPnlNbTqrmsTU388/xMzUA9A/icuY/1J2DMQCEBoXwjlX5uBYaxI8aLnhRAoowq8Avfd59Cll34n0tiRahwt28PeZlzcSD3ySKQ+/thrCmw8ABTgeEDwf1RXG7DajESI/1KcAyQo9JFAvf9+mlq0CFNycks98ACSMLdatFinFSvK5Ha3Mi9bj8dpin1UDvgKzj+/yvg7unWjw5QlZaJoZ9vTp6eqVy8KzxYmnwPZFwXylCkOpaQQcmi1xYVtYJGTblQwNevXOwzTQhFNjhYekLlzCYnMU3x8iRyOeAUFtTWr2AAbwIx1zkidrHMD3MCowLiwL0ANxwZIOHBgv777juT5JLN/mBY76ZwinO8DHjDrsz0ADLI2zjszk2MsM9tu1MilTZuCDasVFxek0aO96t0bj4LlQaE7FwxESMgBLV2aqbS0WIWENJXDEWLaANMIwNq2xVoAIvCfvPyCQyMTNmrMgfc1dkylNHSQira+q9YpcxQZXaoDZW20ZuoAORblqG8Pt0KefEh7W/UzSe4Y45l/pGVcE0dZhsLn1lxcurs8JG/728x1+/xzwJTD5LN8/bXDMEfTpuVry8YlGp53vmVSr/bIcDv+IO85D2jfXre8ax5RZOEcFRVLByLOUsKI29X8sjEK2rZNmz78XGuzo5WT45bbXa6GDSvVpEmJoqOt5Ozdu+O1e3esunal965LCb85V/GxHoV8/YnxfPTrFy2Pp0r/+IclraEVcUqKxbyxan3ffeEmff2FFyq0Y8eOw3pAMDEDQqpLdux8itDQ0B+AkuNdGT/cUxU5Eb8/mPbr0qir7WS5TnQOI5/kRBqpWcwIBCXVJVw1BSlyzwX6U+rS9eRYYNy3bNli8qyOh9U53vPIzMw0Hp1p06aJdrz1o34GTsYM1AOQkzHL9fs4aTPAKpjdYQWzKEURAKC2BitFvEzJF6lu2GYfvPRuvrlYl166wQAfGJiaXhx2kB+6fa/3gJYvX2Zo9tNPb6hvvrHCAo80KP5ZaW1gFSYAACAASURBVKbIZ5UbkIIECqCCtOijj7aofXsSq9vqqquCdP/9y5SQUKj27buqrKyJkRFRnOM3+ewzhy6/nNa0VvEOeKDIJ68E+Q/F4e7da9W5MyFjbfXYYw7ddpvffPfee1168kmvAQ2satPlCrkUXa22brW+z7niXxgwAB9Ihd54Y7MJE+zbt7H8/qbats1hwBX7BmxQlPp8FPDWeaGgI5gQRoVCnJa+sBMU+evW5Ss3t0RjxrQwwILvULTzuY0bLf9MfHyV8czwfebH8sEUafPmTO3eHSmvt5kWLQrXiBGb1LBhglasiFVGhsO06m3a1GeODQ/GqadmKDQ0VRUVTZWX10VOp8Nsk33C4vTt6zefw2fyxRcOw6rQBvjTT10af5Zb17WcI330qdblNVN5v8HasS9anvVb1KZJmfpd3FK9170hfT5Da2JHaMtZtyjo1OFm+1xXunghoYqYUXMaclm3f0ltrzbXZMkSQBxzZzFIs2dXaOnSKj399GqNDHtRYTmH5nj4vYkKui5PvvETtPHu17RmndNksXCPvf++y/z80ENeRV1+oYK+XqgZDy6Vu2U7VVb6VVVVrhYtChQRUWDAwKZNfu3cGaWwMK9huGIcPk1+aKSKH/iTHNdfr/LyUPXqFa4OHXx6441yRUf75XRaDRts5vL3v6cTWZWuv36j8vLyDAPC7xB/juQBqW5utsGJbW4G5FZnSmBPjtdXUldTvVesWGGeSbW54HK059Cx/DvXgWMjob2mZ+axbOPHfiZQwhVoeg/swgVwYaEIgzz3R20B1R97zIHfwx/In8N1XayNfbAN2svjMyE/6kTvq7aOuX47v/wZqAcgv/xrWH8GATMQCEB46VF0HK3X+PFMoJ0vcsopp5i2kvag+GG1Crr8nXe66ZlnLElITcM2aiMDoriNiSnRnj2LNGjQQF14YZzefNNrUsmPNFjNByDg1aDwZqWe4h3wACvyySfpptijpexTTzXQM89s0IgRnY03hsGqPsUpuSWvvmoBClbc2VaTJhYTwT74DB6T8nIATAOVlHTS7Nl4EixQwGr7rbf6jM+ETlF03KJgRgpE6CLgAbADoxMXl6/8/A06cMClrKwwtW7dxwAEjgUvBtvALE4Rz3lxfrAYdO3CEwG707q1dey00OXzGzeyzQOaPLmNYTUWLgwyBXOvXhZIoesV22IMHVplPDNz5+YJ1om8toyMFL3wQqjOO8+rBg02qHlzvwmFtIBcpDZsCFHHjnQZy9bevX41aRKtli0bGDaG/cHubN3qMEBpwAC/kWvBXC1b5jDApFkzv9q3l/7612CNHu3XxIlebfxqrzxffaP05cU6kNRBffr6dWnJq4rdtkb5F12rlRvD5Zk+X0F+n3IGT1DYZeN16linYVhCVk6SK+u9gxIuzqtcScrptVxJLeO+N6mnKyp3iiJcBdqS31apFf1VWtZcMz6L1zd3tFCQv/QgA2KZyR2q6DhNoWf/VqmVbTXtqnel+EZmvgGCXJtZs5y6+mqv2v3jZsVNf1sb/zVbB1L6meuHPwXmjFFaWqUlSyq1aZPH+J8aNSrQKZnvqM9TT2jOK6+oqnFj5eYm6pZbemjChGL94x9ec0/y+8MfCkP+e+mlDjVosEc33bS3RkkRoOFYQAnHRIEZyJTwM8dmztyB2d9ibwLByZE6LsGssrBQm96y43kGHe6zdTXP4mR1cjrWOeQew1vEfVBQUCAC8eyGB2zDBqqB98PP1QDhZIVxIpHD10i75Np8Xx7rNan/3K9zBuoByK/zuv/PnnUgAMGUSRcdVt5qa9gp4/RMj8dc8H1aLV4P9OoUJgCQhx6qOQeEz+PvQCYFS4D8yeHAE/GNRo/uofffb2w6SNkm9sMdN4U5rXRhDShMMXwTlIvpGBnS9OnrlZXlVlZWsBYv7qh58yx5UeCgeP7rXx2GUQA4UEQjkwIwUERTrNMRCj+G271ccXHhqqrqZsDFtGlWO+ALLvCrQwcrawPmArkQHgt8J4AijNQEC65YkSe/P1stW4YpJSVKWVlb1KnTMKWlkZpsMTfsC+8BAATQsWIF54UUyUouR/aFB2PZMvwrsAIEKeZp27YCjRrVVuHheAqYTwzr1jkgy5KsBPY+fTzav3+bUlO9ZsVz27YEY34+7TSvAS1NmuxXTMw+7d3r0euvt1a7doQllmj79hitXJmknj3L9dRTXoWHR+rVV11GJsV+ADJsAykWYA1gibeE/W/c6DDzgvn9+eeDTcviM87wGWmafF41yklVh42fqX/wajW7aKAqcou16oOdWpE8QeWxiSpYsVXJRZs1enCJ2r10q/IjElQ47w/qEDxFLodHud5eWlL1qjoO6GDAm2P/NwpZMl4OvxUkyDgQeapCTv1E6+ev1sDiETXeUpV9XpWv2YVKu/hBzZ4pFY4cL3/fPoZNGjOGrJEqvfiiy4DOyZn/p47TX9CW236njFNuUNserc31YDAfAEe6jAEUOSYATIvrzzbdE9a89Yk2bPBo4cIIffBBa11+earOPdcKKrT/wDKiff/734dp3Lgw3XST5esK/FPTSdgMic04HonZ4LlQXb5V3VdiH49diNqeLyQ7NLqoawCkruaTcD15FrNoYy+A1Nbz+Kdux5aHkR6PpLa6r4TnPYN7ypZwBfpLaqML15HOAfkVLCBzdyIHDVvOP/9847uqa9LCE3ne9dv+eWegHoD8vPNfv/dangEKC1sHTvcQXihQy7U17JRxkmnJ8agp28M2ode0TwpsCmgM0LADvN/27PGorGyxTj+9s6KiEjR2bLAWLDiyDAvwgA8CKRO4gpatGNXxWNC6ET04BducOSPUuXO4rrnmUEAEu4GE68knHTr/fL9hPuguhX8DjweMhV1M4yvIz09TbKxTXbq0M4zCSy85TAH+xz/6jDwIAAJw6tHDb86LtHeASlGRx5jei4oqNWhQpOLimqiiIl/SWp1zzjCtWxdsgAoeEUzvgB6KXQrYXbto7yvTjhc5FEZqjmvBAgvYdOkizZp1QOnpBRowoI0BT2SiIIeiCAaUAWZgnObMqVR5+R4lJpaoX79meuaZOFMsDx3qNR2uWrXyq7jYWlUH1GVm+jR9ulsxMXmG2ZGc2rYtUjk5kRo4cLcGDChTVlYj5eZGq2FDp4qKwozXAmYEv0h8vN+wA5iuOaexYy2G5J57go1E6txzfcYvwrVDpnZKs10atvbfcn72mb7pPEnTCoerbMseNQ/PVWT3NuqxY5pO2fSG0tqcrlkj/6bypq1VWuxRWWW4kX6ddprfdEwLm9NFQWU7f+DxqOz9svwx3RU+f0DNAGTA+/I1GWeA8fKXNijx5b+rqm1b7bnxPvUf7DIggpG5bK5aZl6msAVl0huS/xqnKm9/U1XJVlgY1wzwyZwBFrkn6EbWrUOlwlu0UNpFd2nliNsNsHnzTYfmznXqmWd2qUsXMkKKzMq0XfBhdr/zzr4677wSTZqEFynqIIhmFdtmS2xgcjhQYjMlR5Nw8dygILWLUBugBMp1KD4pCJHrUKjhNTmR2vzjeW7V1XwS5otOgOS5IG+qS4N7jmfl4eRhvE+qe434f/ue4HwCmZLalnDBqHM/1uYiWk3z/9FHH+nqq6/W/v37j7tTWV26nvXH8suagXoA8su6XvVHe5QZCAQgPLx5oA4dOrTW5o0Xz5w5c4xhD2lHTdke993n1IMP/jcHpPrOKfwJ7MMfgBIkJsan/Pz5GjKkkzG3Dh4crEWLPKY4rWkACCjQ0fuz4g9QQH5F+nhGxjZzTHQB4uX4pz8N1z//6VFkpOWngCVBWkOOx+uvB5nuQ4AWjgMpDWwI/4Z/g4RzOmPxb/n5240uPyWljSlGf/97lzETwzDwfcAAjA4ghgR1iv+tW4uVmblLbjdG9ebGxI63JCOjUEFBqzVmzEClp4eZfcFSAFyQbyFLow0xTA5F9dq1sAowRpYpm3PGOwMY2bKlmLJYw4d3Mh4UwBDyNQppGBqXy6+VKwuUmlqsxo0d6t07Qc88E6G+fX3G/EzxTwFPEcl5M/B9hIbu0Msvxyk8PEStWkVq+HDYIa+ysys1dWqw0tJCNGxYjlwuQgvD1LRpiXr2REserIULm2rVqmi53S516kQYpt8Y2skvYb4eecSpt95y6corWYW3pGUAp2HD/IoKrtTSJ1fo6/f2y+v2q2X3BmpQkqOUXfPU58KWSk/1avm8chWEJWl37zNU3qGnzhznN0GL8pYq4ouEGu8ZT7vfy9PlITnmnaaw4mWHfKbc2VL+M5YrKBhmKki7N6xWfMmnci3+WgUrwtXozoeVfG5vyX1A4XM6Sd4SqwvXCqnqWUkXOFXx7zRVhTcx7N7cuQ7DQlkdzwCOfnNf+OcvlGP8hZr92HIlDGhlAOB994WY679wYZ52714jGEwKe64HAKCwsFg33NBLEyaka9CgPQezIBo0aHCQMeFet8FI4H85SdtXEnjCgYDkaKCkescljolFB3sg1wmUb/Ezq/w/ByihPTCLInVtBftktZL9MQ95JFjIjgYMGGAYjmMZgRKuQMbE7sJVW14jjgVmnUUvGJoTOV5//XXdcsst5p12IjvInchzqN/2L28G6gHIL++a1R/xEWaAVUxACAP6Gl/GyJEja3XOZs+ebeh62ku2bdvW/AmUe8CAIKE6HIBgkRd2wPaANG3q1+bNsw2oQcJ1zTVOXXSRXyNGWKv3FOIU32yP4pvVfTwamJ0JFYQN6Ny5XKmp6w37QdthXiR79hTpjjuG6f77mRPa0VpdpAAZFPh//rNTf/6zzxidrawJv5FicXxkbLBvjtFKI0+Tw+FRaGhXLVlChyqH7r3Xa1gUAvkAHBwLBTbAqkGDXIWF7ZDfH6/k5ObmpQaAoSANDi5QSckqJScPVm4urXg5xypTrAMgkJdxfIAMDPBLl1qdsejyxR86TpGsji8kPb1QkZEblZLSX+npLgNgYFCYs2XL/Fq8OFc5OZXq2TNUycmJuvfeEE2Y4NXo0T55PH59+63TGLbJ90AKVlHhUXZ2rqqqONdErVgB44GnxG9AHp4IrgMM0uuvO43/o1s3twYPLlTPnqwe7ld2drlWroxXSYlLRUUNlJERK78/xBz3xIlBat/eZZLj337bqcsu8xrgx/H26mUFDyKtY/s5G/O1f8l2ddk9V6OHVahjy3JlTt+ozyMv0hZ/a4Vv3aQIT5H6nhqpU168TBn7d6nXliGkc/yAAano8Bf5O92h3F17FbHmGiVUzTe/E7vLumtn8ynqNqitOQbHrncVuvq3CtJ/AbTvXaf8LSfLd8eZCvvmzEN/l9IkPSx5Lz1dlc9/bLqpLV6MgR85FiZ+wJHfBDjC/u258P8U/O0SrX31W5WUOcw9fPvtdErz6o03vlW/fj1+INOpqPBr6NBQ3XnnXnXrlnswJySw4xWFfyAoAXxX95UcScJ1PKCEtq20LGV/gTKuQF9JdbP7iUzyti9IXTXHI03F5Iy5+WRnthztwV9b7Az3Vk1BitUlXNXbAx9tPk5Wuv2zzz6rhx9+2LCQx9uU4WhzXP/v9TNwuBmoByD198b/1AwEAhBSywEho0ePrrVz5GWKnpkXB6tSjdAuVRuPP+7U9df7DmZZ1LRz9PEwC3bb2MDQRLwPjzzi0t13+wzLQSEOywHzgD8DiZTNDmAcr6wsUEjIWoWHs9Lc3VDoaWlpWr26SI88MkjPPIPRF+YhSG3bWj6NKVOCDHjATM6gMxSdo+icZA+kVrAtrGrv3LmDWEXl5XXWRx859e67XtOBi+NjBR8QxLZyc9165ZUcpaVRcDaWx4O5F4Bk5W/wucTEA/ruuzUKDR2kmJgwA65IW4f5YKUcz4nV4ctutWsxI1huOCY+g2cElmPx4gLTrjUioodKSpzm7/Fz8OLfti1D2dkuRUY2UWxslN55x6krrvAYuVfHjshtnKZgBnwxPz165KuoaKvS0hIVG5ukFi2CDWODTAhQA5MBSIBJ4nvGxyGM707T/eumm7yaPNlnVuOXLXNr0SKfcnI8KiryKSSkVImJRSopCdH27XE6cIDuW8HauTNMkyZVqnt3p5k/5F8AEKRnsBFI7Lp3cuvqhp8q9p2XVVLo0/SEicrY7pejuFi+Vq2UlLFc43LfkKNbkpz3d1KjykNN6pVqpNw+yxTXvKlhHWB6cjIK5fV49ZdHk3T11X7dcYfX5IuEz2ov+d2H5IyYQJC/RqmqWawc12T+8HbOljz3hsk7+gx9c+tUc9wARyurRRo5kqR662uFB/xydu2l77pepK1X3qvo6Cw5HJt1881j1KIFsr6apYcc94gRoXr+eY/69bOM6iwA2KGFFE78bK9Co80P9JXYoYXHA0o43pp8JQTXsejAYkHgYN/V5VscI/u0k7xtYGIXorXpIair5ng7y4JWsnWtuLXZGVjy2rwW9n3BYpgdpGiD1eoSruoNEAJlfbAz/D+LUydyAD5gQTDk/xzs3Yk8t/pt190ZqAcgdffa1B/Zj5iBQABip5affvrpP/mhynYp6sn24CVKau7hAr/wR4wd61e1+uSIZzNv3jyzqkphw+jdO1j33OMzsiYYAlbdYQco1m0GJCqKY9ojKUMDBgCIuh+kz5FhPfccrWo76P/+z28KbJgKAAjbvOcepyZM8JswODoYYRb+3lN/8DgBSTAbtJP97rsslZWVaurUzpo2zWO0/VZnKyuLBGYiMTFPqampysoiGC5FMTHRhukBNFFAAigAOL16UZStUatWPRQaGmEM5/hiAFrIsFg9J3wQgIb0ipXzwYPpkGRtA6aGbljbtuEHKdayZXsUF9dWPXpYDMjMmUXKzNyrvn3LFR/fXs8+G6msLIfuvtutxESLDdq/32m2hbcEZmbHjgOKitqjdu3ClJjYXFVVDsN2wAK9+67TzNGYMT5jOIeFAgTi72AFH48HjBFABSP8889XKjiYVsgOE14I69ShA7kVbiUlFSkjo1LZ2W6tXRuiDRsaKjOzgTp2LNB11+1Wnz4OrV3bWKmp0QoJoW0ssrkgU8TT3ti7MV3fPrxQS+e7VdakjUq8IWqyZ5UGdtmlIdqo8lXp2nZZZ3Uc8Z3CQkq1191DK50vqvuwTkZ+x4A5wj9kdzh76qlgnX22T3dMXKiwRTWD9cqer8h521R5x3yjsCb/TWHHGeINaa7tMdPV7KwRKm7ZSV/dO0fhkQ4zT2S7cN/awZIwaps+26J+N4/Qf654U+UpsRoyJF6NG7fQ0KHhhpl69dWaQQi5L2PGhGrKlEoDaKsPCn2745UNSKp3vAoEJTAYAAJ7HKuvhCBCfk/t5OwjFdW2r6S64T3QQ3CkAvR4HoGY4zHGY5CvSyM7O9s8O2Gi61pxSwgsz6wTHfQXeD249gDT6oZ3m7kPlPUBkLg/ACAnErzdfffdRlrMdapr16gu3cv1x1K7M1APQGp3Puu39jPPAA93exX0WFLLj+VwKR6gwnlp0GMfEALzcTgA8u67yHKs9OpjHRQPGFs70FJK0oABwWY1ndV+AAgFP4U3BTqsxObNbm3cuF1+f6GGDElSr14tDnlxwApcfXWMxo+PU5MmFmMCM4Dxec0ah5Yvl848k85CMsUchXv1gTafIh9z+M6d2Xr++cZ6/XWXunWzCnBAEQTQli203d2vqqpdSkqKULduSNJCDDuCKRljNiHDsDWAjfDwEk2dukt79nSQ2x1sDPSwI+SEkATOtvkOWAyvC4NClkEhy7xieocB2bGjRKtWZatJk7bq3j1IpaUZJkclKipW48fH6447QlRRUaULLvCpbVsARNX3vhIrpyMhwa3du3dq+fJwxcU11JAhEaaFL+BqxQq2T5cwv77+2qlLL/UZwAVAotiFUVq61GlYi9atLSM/uRYvvhhiumCddprVnrhJE785fwAefhnaE2/Z4jDmepLDXa5KfflliFq3LlVcXIkBR34/np4yRUYGq6oqQoMG0T0LQBKpFSuc+vQDvypTv1NC6kLFBpWqf0+fBu79XDtCO2pm8SDlbSlQqTNGJd36a9DNPXXW2VXmOLkmMCB26j3zCEB64IFgDe22QX/sXrPWvGLgJ/InjlHqI6+qXdS9im1eaK5Hsdoqr8t7SmjfSf6CIvk791VRVbQ+/NMyhceEmN8DJGb2ILtl+XK3Wr/zJ/X45kNNfWStBg+LMezeggUOXXZZqP7wB49uvdWSUVYfzN1ZZ4Xp008rjFzwWAbPA36HA0EJq9AMu7tRdQkXRWCgn8QGJ2QyENrGc8Dugmdv51jN7oEegkBgYhegrMRXZ0qOxVdChgP+j+rMzLHM0Yn8DPNFdyUYkLo26go4ssFz9SDFQAkX94T9xwatR5NwHet833TTTcZvQshu/aifgZM1A/UA5GTNdP1+TsoMBAIQDOh0ODlSavmRDiow24MCoEePHmY1iiBCPCDInWoaM2dauRAUjcc6WFVt2LDhQVDzpz85zAo9bW4peDFjU8zBNCADW7Vqo6qqQtSvX1clJPw3j8Te37Jlu3X55Y30+ONhxhROhyiSvFn1vusup2680W+KeUAGxwoAAFCwms/PgB4KcLwIMDk33ECS+n699FIT4/OwukyRseHWsmV7TaeYgQOj1KBBM1OkA5wYFLsUvfwdUifatbZuXaKPPlqvRo26yeuNNlIuwARtbGFKiosptmUyNegYxflT3CclWf4OQBj7p5iNjy/Q4sVbVFBAU4BcRUUVq2PHJpLi9Ne/utS+vU+jRlngo7TUYVoGI6Oii9jixSVasWK36WAlJatp02BTCHP+gBaOHeakTRsLXEyfboEQq3GAlXUC6xEWRkhhlfkcvgf+belSh95+22WACsCRa0c7WzpCkQ9CfgqgknNCeta+vV9vvRVs/v+228r08suk0+NPgaXyqFu3PTrttF2KifErLa2ZVq+ONv/WvHmwWkcGaUTWu+q77AVtaTtGX+Z0Vn6OR8UNm6tkd7HO8HyusRdGyPP448oqizNzBxhFJgWI4prQvvl31zt194Ax6hy38JDb1h/dSRUjFknOcDPn6d/slevJe00b4Yg/3qeu41oflO5l7/Co0ehB8ucV6N83rtMpYyJN+2SbXVu1qkAzZuSocWOfLn3it9qd2EdBr/zrYJetf//bqb/9LVhvvuk2nb1qGunp0iWXhGrWLEz/x/obdujnYCZs+Zb9X4o/m5ng9zvQU8Lvf3p6usmPwWPVDCOVydM5NEQxcC/H4ysJZG8CQQmMDoNckurFZ2BXMD6DN6V9+/YHmZkfNzO1/62TFab3Y468LoMjzgdZHZJa3ju2lIv/2s0VuE+r3xc/pjPbVVddZTJRuIfqR/0MnKwZqAcgJ2um6/dzUmYgEIDwQKU3/uFSy490QKyaBmZ7sOJph5MBaqDDD9eZBH8AhmxkWMc6OE6KHBvUIDc588xg/fOfXsNe4NFo1syn9HRLBgZbQsJ7RUXwQaM6RR4yJor4OXP26/bbG+ill4JVUIA3osp0YaI97rPPOnXeeX6zIo4siwL4+3xCUwDDMAAyACCAh/nzg7RqVaXOOSdVEyf2MOdGHsS2bQQo7lBlpUPt2rVQjx7RhjlgcRmmga5Uq1dbLAj7wAeAjKikpFLvvrtJXbq0UVxczPdAxjp2ivsdO/CS8CfIAAXkT336WADsvwyGlaUSGVmkmTOzlJcXodhYv/r3T1J5ebgef9ylM8/0GLlZ//60bHUY6RHnxzaqqnZo/vwD2rOnqfz+JMOewAIhmUKiBVNDkY40DOAEeNu2zalTTvGZXI/Vqx3at8+SMVVWkv7uMywHnciQmVkp8BjonZo3DxalSs895zEACvnTjBlBBoAwzwBBZGAjR1bpgw9c2rgxSGee6TMACHAAa7V9O8DMK6+3XG53gcLCKuXxOFVYGGaySk4/vUBtmkquuRu04M0SbStpqsiGwXLt26sezfdrbMVnityZqj09x2jFFY+rPKmNaZWLxI22wcwt44F7ijUu7noNa/u56UxWEDJU7j4vKzrRSmDn+mAy37G9SmHvv62ey19Vjz+Pk//228y/4935bn2Vxj97hkI3bdAtI9bo+gcT1bmz3yQ6r127Q4WFzRUR0VahBft19h3dVfT8q4q5bOzBX5Xrrw/WjBkOzZ9fabq01TRoUnDddSHmM7a861h/1w73OZ4ddstVmzGh2LOZCb4HKLELQopCCsDj9ZUcT4iizd4EektgYhmB2RQUocguAUd1TYIFGwvTMGTIkJ96iWr9+/gEASG12SmxNg8SVqt1a4JR/yursyVcgcnu/FydQQtshMC75UgSrvPOO8/cy9OmTavNwz/stniHTpkyRUiPuT9o0oDMDCnYaaeddlKOoX4nP/8M1AOQn/8a1B9BLc6A3Y2ETfLSpjMMLRZhF4511JTtEfjdtWvXGpnX4XqzU0BSPF5yyZEBCIunFLsU56tWrTQAJzCFlna88+Z5DACprCw1MjBeNIAhXkjIaFhNx7DMNiiAWWHHtzB1apFefNGpV18N0/79GLFlUtKfeMKpESMsVgVDN/Iqimi+x7FQgJPl0aaNlTMyfbrMSv7vf58taYdOO22AWIHOyMhVdnaOkpJCjR6+tDTU+CEAPwAhZD0AD7p1cTwAAYpcvBupqR5NnbpJQ4cmKzo6TosXW9kbABaYhkaNrLa4FLMcG0U9TAhtdfHAIOlhxb6oyK+lS/coO7tCzZs7NWZMM9Mid84cunu55XT6tXs32R4WSMDv0aqVV/v371JpaaGaNElURUWS6ejVsiWBilUGFHBdYAeY940bLfkb54NEDAna5Mlec8zMHR4NmCp+psvVaadZnhAAxvLlTtMRDFYF2RvHBRsyYYLPAKxVqxwGZAHKOEe+T27JM89YHbLGjvUZeRrzCThq3Xq/0tI2af78Ftqxo4XpsuX1ksNSoquu2qWgoELl5pZrzZo4le8oU7sdaxSdJAZb5AAAIABJREFUvlUNm4XoFMcqxalAVc5gM48bGg5R+VkXKOncvua87CKea/bQQy6tXeXVffdVqNwN02edAwPGhOuCdAv5XvSWNer96BVK6hanyhkzlJZJeryV59Ltb1eq8bczddeob9Tp/GAlJGw1xVR8fFvl5TnM95t++qLiHr1H5Tt3EvRh/o78lPPPDzHeokWLKk1jgZoGOTR33hmsr7+uNIDxRAy6yvF7R/HWuHFjk6DO7yAdjxi2Xt/2lgBQAsP2YFqONUQxsCXw0Xwl1f0DgavidACrHqLIqvjPNZBfwdqSA1LXxslKGv8x5819AyOBLNdm3A63nUAGLdD0HtiZraYgRVvCRaMWwCug4GSMCy64QIArwg9ZyOOYX3vtNbPo99xzz2ny5Mkn4zDq9/Ezz0A9APmZL0D97mt3BgIBCA9fOtbwgCP5+miD7/KyrCnbI/C7PCQpQg4XcIikCBnWb397eACCH4JijjqGFfOSkjUKDvaKhHV7XHmlS5MmedWhw27TxpIiggBEihyG1YbWWtWHdaB4s43qSKb27MnXDTfEye0ONSv4FLH/+IdTf/2rz4ACCm2KPTJJKBgBILAbXbr4jWyL4vv221169FGSw3ertPQ7NW8+UrNmZRrDdlJSM5WVtVB0NFkhmMUppC2pF9uiSxTAA18HXg5YHEzw5eU+ffzxGmMQr6iINUwCxwa4AEgBVJBs0X2LOSI9nKIXRgH5FeeamurTli0lKikhs8OnSy4J04oV0Vq+3KHLL/cYM3N+PqvoVqFLOGFKCtKFNO3cGa7o6Obq0yfCAI0vv3SaTBP8GRTaHC/yKsAdCexIqwAjtOFFyvb554AdnwFoMDR79zoMm2CDFPa3ciUyMYcBIHS3AgRx/vPmOU37XhgBrhvghQIfZgUDO522mKvp0x2aOhUWx2tYku7dsxQf/53i4xOUkdFNS5dabY1DQ/GUOM3xcR916uRTTEyZ9uxBulOi/L1larPza41e+5oiywpU1CBJ23fFKj26lxy5B9TMmaNOV/ZS47/fSv9kcz/NmoUR3gqa5P5DOgYwYhiG4ztaCdOS2LqHe7QvVZcbx8iRlqbc1z/R+pgh5u8Zoz6/TS1n/kdPj3tBO5tP0P33hxq2DQBs2v46pNBhw8yFr/zqK9NBiw5qgL677w4x87pkSaWRINY0kLL9/e8WCIFBq83Bqj1ZQrGxsYaZDMxHQBoV6CnheWDr9QEPgR4O2+zOAoPtJantEEUWRJDrkCPEfuzVcXtVnGOv3hqYFe+TYTjmeYoc9kSnef+Ya3+yksZ/zLEBXinS8RqS7/Jjht2ZLRCUwPLxrIaFePXVVw3A4X7hHfnSSy+Ze+hE3xdIjnnXBQJjfn94vyFzzM3NrXMtm3/M/Nd/58gzUA9A6u+Q/7kZsHXTvHy//PJLUzzwUD3SAKyw0gn7UVO2R+B3jxZwSHEP+/CHP9QcRohMCfAAO0ABSbclCuOmTfMOeUkvWABgKNONNy5SkyZNDEUdaDpEIkWXKlgFVBkwIfgbAAGoHU4/fbX69eui+PgwUzBOmeLU6NF+UygzACBIezZtwrxtpVfT7peCHwkR4IPVftiQhg1zlJe3XgcOxGrnzkh1754slyvWFOoUlBSI9mo/pna2u26dwxTZFKrI0sBNSJFgODZuXKKmTdursDDJFPH4PTgeClCbgaE1L8UuqfFIhZDdA05mzy7Ttm256tyZDJCWmjevQEuXtlZYmEMdO/pN3glMA6CI9rjsb+/eYlVW5hi2ISqKoLtg46fhWmzYYAXnUfxjsKcoJs0bYMZ5cQ4ANa4VbMG6dU5jLKdFLp+x2BPrGgAyKK7z8iz5WmqqBU4GDfKra1cLYC1aFKQ33nAaGRcGd7YJA0UgIhItzvnbbx3m2r77rkunnLJPgwdv0fjxDdWqVWvjRcGwjTQLORjADYDAuQHaPv7YaWRcFPgwRZdd5jGgpGLtWu1/frrS5xWoJLqRwksOaK8jSQMrF6l/5TIVDR+upROf0OLNbVRWFqJduxz6+muHkY6dfbYFprkvOD6YH0Aq15ZrgsTP9dhjCvrb37Vi3L3adPbtKi4uVWVlus787lV1fe8NZT3+hv687gINHEgXM7+ZC76XGF6k8Nat5X7sMa3pd62ZU86FZgvXXRem7t19mj3bYhxqGlOnwvS5TNr94bJ3juchR3GG3wOpIyvPMI7H0oHIlksFekvsYs9uwxvoK4GlwHBeGyGKPOtoZMEzAnkmg/OwGZtAxqS6rySwCxer5Mdyrsczn8wlctj+/fsfz9dOymfp+lRYWFgnjw2WDQa/W7duhn2rrWFLuFasWKH33nvPdAHbvHmzuVcYNFcACPDn3HPPNRLmkzVuv/12/fOf/zS/e3WtmcLJmoNf037qAciv6Wr/Ss7VfsHyAqa1YKdOnY6oi0YeAKvByiFgpaZsj8CpO1rAIYX0Aw9YTENNA2kJGnZkUciOsrIohHeqefNsDRtmyRTszluTJ/fRzJl5phCqvipFgc4qPSwKIAa/gJ3lMWhQkO65Z5b69BmohIQGhgX44x+d+sc/rGPiGCn02DdtcincYCdSUqxWt1df7dTw4X5dcAEFNwX1Tkl7FRERpVat2ikoKPRgSCGsAdIpVDTgPIpeQAVmZyRGtF7lDyyH1Q2Lv1uk0aOby+1uqc2brdVwWBMYCYpwingMz7AjBQWwJsin/HK7d2vWrHJFRYXrwgsba/166S9/cWjwYL8uvhgAgvTLYYp0zg/2IC5un/LzK5SYGKZBgxqaUDy2z9zRPhfARQgixTRMBSvpzCn7pwjm/5H4wIBQB/DfJ55wadAgn5GZAXgAEFwDpFSAGuYU0ARjgPqFucSozjzjofj2W1gjWgY7tXOnQ0OH+vXUUx4zPxz3xx/jEfGqvDxH06cn68orK/THP4YahmrhQiv8kZ+5rqSsn3qq3xwbnmUkULAoHMO2bYT8WUAKiRftgJcu9Kty9UYFLVtmjrVf9EaNdX9Ktrmyc6P1edxFyhs5SP62bZSZ2VBffx2nTz4pVOfO4QbUwfwwbwyAAuAHMMHImZ+mDRc/ruKQWG27coLUsJnGjElWn+/eVchNN2nXbY/pofwbDVg+4wyfyYWBtYuZ+7FCr7lGKz9NV2puoplH5Hfs67HHQnT11T49/HDN7XnZ7/PPO81cTpt2eKByLI8/QMSGDRtMoGdKSoopgn7KajCr2IH+DRucBLbhrQ5KWBU+Hl8JxwcAWbp06SEA5HDnW1NgXnVfSfXWwD+l2xLFLed9OMnqsVyXE/UZim9W3vtgMqtjg2uCNxAgcLR30k85dO41JL3XXnut8cIgMeYPeVc333yzAAUna1x66aX68MMPDWA91mT6k3Vs9fup/RmoByC1P6f1W/yZZ4AXrN0l5KuvvjK6c9pTVh+B2R7Qz5i6A2UWhzsNTHNItY5klrvvPqcefLBmAMLKOIUVUiJYAYpsh2OH4uMzNGzYUJPeDsuClvxPfxqmadP8hwQEAh4o9mFQkHJR/MEOwC6w+EkhP2IESeUz1K/fAFVUNNSHHzpMUXfWWZbEiO5WHAMFKyDI9iJg0L7nHodphfv731Pwe/XNN3tUWQlFX6Z27borOTnYyKxgepDaUKBzHrAX/D1dj1gpR4qGJ4TjBUBQpFOMU9gXFCzRqFFJ8npbmTwN5oJWu7A5FKWE8cF8cF6AgPR0vwoKslVVla+4uCQ1apSo7GyM3S7167dT/fsXyemMUqdO5KFgzG+g9evJ99ip9PRQ7dpFIRli5hE2CJaFAh2wxf44b46f4+V8ML7DDMEAkLo+eLDPmPNhQpgvzhuWok8fulJZ2wBEwC4BDvgeDAlMAefMvMCCwE5xPsibkDsBhFh4RDpWUMA18xig9v77pdqypVDNmnlNV69XXonU+ef7TDthjPHMPdcMH9DIkT5NmGCxWlxXvCUAQMAO/w5Dg8Gd4/zwQ6dpLsA9AmuT6Nynvru/0NnrH5ErsZFyMr1aF9Rd5XkV8keEK3f4UOX17aSXX+6h229frY4duS6NtX9/rMLCwpWSQsK7xYAxNmyo0ptv5Crh84+VuHuLSi+8Qv1u6GNAStWsOQq/+GKlnv1/Srv8z0aKhi/p8su9hnkLmTBBldt265vnlpvfCSuAs0rTpjn1zDPBevrpSk2caDEx3FPV2Y6HH3aZ1spTp/44EELBR+HFAoYd6HkiHmWBJuLA9sCBcqnqIYo8C44ESlhEYWEEBsT2u9UUoni486kpMK96t6VAUMLPx/KsZH91uchn4QnQGei9OxHX/Mdsk3sDlgKpki27/THbOdp3uB9prPDkk08awBE47BDNo22jNv6ddx5g66yzztJHH31UG5us30Ydn4F6AFLHL1D94R3/DAQCEDS0yJdYzQwc1bM9jmelk64peDKOFHB4JADCqjUFOhIb2wMSHLxdRUXbzYuA/BJCzmBuHnnEWlq+6y5LssLgexTHVnFvrcDDGtgs/RdfBGnatCqdd94sxccPUF5eI9P5inR2shMACJigYWEADrAEbBPwUlpqZUK88IJXO3YUKzV1pzGxt28fK7d7h1q16qOwsFDTUYsCEaACCAoJQepk+ShY+ae4RrIE8LBkZhYI4Tu0qc3LW2zC5yorW6i42JLyUMRTkMJCIIFilRzp85Il5Vq/PlcREZXq3TtJffpE64svHHrtNYcuuYSCPd+Y9PFchIaWqlWrAsXHlyknJ0pZWQ1UWdlYbdrgnwlWYWGwYT6ysx2GlWEeACXIgmCPYGJsBiMjg6wOixnBI8O5wVoB4Ei737qVsELAhV/nnEOR7zcGecAU3gS7wxiZHjAHMEPDhlndxz77zGFa9WIyh3myuoRV6YUXXFq92qtu3bLVtGmo/P4EA0jOOKNKDz4YbOaSrl4AIaeTNPAgA4LouMZ5MGf4j9g388i1SEnx68IL/UaqhY9m0SJaAANinYZ94nujh5Zpgv8jxb73H63ObKzNlW3k8/rVqjxNg4OWKPOc3+iMFY/qiquyVFFRLo+n0pj8PR6XunenuxchjOGaMaNCq1ZFKS6uscK2Zyl27sca3f+Aesx+SFVOl9Kmrlb3G0crZ+TFWjLpBcMGUSjfd59HkcFuhbdsqQOTblHOtfeYa4HEDFZs5MgQrV7t1HvvVRgfDvc+0j+AXWAXrLvuousbEsjDsyU1PVFsszlFNUXQyV59DZRLBXpLAuVSgUb3wGR3FkT4wyIKzznm016AqX6udmtgW2Z1JLmV3RWsero7CzcM5qo6KMEAX50xqstFPrJbjvdwLdWP/+1Te9+ABSAJnSYqJ/J+5PoiUSYJfeLEibV3AsexJWRweCpzcnKMFLqudXI7jlOp/+hxzEA9ADmOyar/6C9jBljRsiUO1fM1DpftcTxntnv3bq1fv94wIIeTJtx//+ElWOwLEEIBzAo4ACAzc7NoCYkMDCYG0IQ8Cr39Pfe49NJLXlMAUyyi7+cPhSsr2azc43n4PkRd113n1LnnVsrv/0pBQf1NVyRb2kRRx2o/RbTtQ8G7IVnZEDfc4NKiRW4juVq3bpsiImIVHNxdu3Z5tXdvqpKTu6llyzCzb9gDClmKQcAPZmrM46zQ2/khFMSAEbIyyPmwwVJ6+gLl57dVWFhz0+UIVoA/EFX8P34KfCSbNx/Q+vV0rArSmDFJJrPjk08sedGTT1YYEABzwBywat6hg1d5ednKyytUw4b8W6T27iXHo0LNmpUoLy9GVVVRatsW8EW2Q5QyMoLldlsFOyv5eDYADcwRrBGdwWAbyOqg4Kcr2IgRPiPdgkHCbJ+ejmTNpyee8Bg5GucMywEQACgAzuhmhdcFELZihcVUUMvBtvCd9u0rlZu7UQsWhGjmzM4qKQlV//4+AzCuvNJvMi/+8IdgI8Ei24QBC8DcjxvnU/v2FjNAAjuMCscHAxMbG2S8P0jHALz4RJBosW+KeAAO99FXXznNPIbk7FSrrCWK3bpKTaKK1bl0pZo7dqukwKveYRvUdXC0egwKk99fqeJit3r1ylWTJjkqLi5XejrJ7lEKD7cCFCP9Xk384DdqXbZZFTNnan+Tbtr+5XYNunGg9qYMUdYLHxtg9NRTLsPwDNNChYw7W7lzv1VYzw7mGjBgiVJSwoyc7KGHKg2Q5ncHAMJ9Z3+Oz/7ud8GGpXr88WMDISwo4AVA5oLeHl9GXRm2XCoQlATKpXhewF6g2ycFnZVy2+zOsy4w3d167vwwm+h480qQLFXvwhXYFay62R22mEGOUl0bFPhI3mCO6trIy8szxTjdwwB2J2pQ9GNE//jjjzVhwoQTtZvDbpf7icU82J5Zs2aZ3K768euYgXoA8uu4zr+qswwEIIGhgUfK9jieCaJDBy8ukn0P92I4GgCx92clameYAoif6ZXPC5yVdwACfok//9mpv/zFZ/T2rLBj/EbnTzFPEYZWHh29nQw9bFiwvvqqQrNmfSmfr69efz1B997rN6vj1B8UbJjOYT2Q6DRsaEm3rr7apX/9q1wu1zrTiQTpWlJSe23e7NDmzeXavj1NAwemqEuXCNN2FiaB77J/BsUgRTZFN+CEopuWveRoAFhgSThmmIb16xcpN7elXK6WhuWAjWF1nnOwAIBfWVmZyswsUVRUYw0bFq+4uCD97ncu00HqP/+pMMXomjVOU0wjR2vc2KPw8HRt20aR1Vy9e5PZUGWAgNfrUWJiqaKiilRQUKH9+2nH69L+/WFq1gyTdrBatnRq0CCnSkpiNHVqhJEsUdBTj3Iuy5Y5TbH+5JNkxMD+OMx5w57g/3jvPYzlVoesm27yaPZsp/GAADDoLEZIITIuGBa8I1xjriUsVq9exYqNXa2gIBikPkpNjTIAlda9gMNHH3XrvPOs5Pq77nIZKdUFF3gPtgvGYzJsmPXvn3xieUwowumUhayNUEwM8gy8QxjgOQ7mHv8MIICBtGz2bMz1TmVt96jhrnW6qujfGh60SM7KMs0rH6jflP5LnSN2qsfYJIV1aqkePfYoJGSdWQ13uzspLQ3GC7DnVnh4gWGkBk59Tq1mz9bWK3+rpSNuV9kujyY+NlSeZi1VMf9rRTVw6M03nUZCNTntNsWv/lKbP1ytdilWa2YGeSrXXBNi7tm33qo4mF0DG1e9S9YVV4SoUye//vSnmhPV2R73GL93SB5hQGEPatuAfTzPlWP9LICDZhkcO8UbzyCYEhtcINeq7iuBragNs/vhjpH9VwcldlcwvsNCDUbqwPbAdq7SsZ73ifgcnaBgF2Cb69rgPQN7hC/jRIJimgQg86Jhy6mnnnpSpwHges4555g8EAAQ8qv68euZgXoA8uu51r+aMw0EIKtWrTIUO8U0q0m8vGEYfmxbQyYRucby5cvNi+Fw1PiRJFj2heDhywuGFw0rmLSqtFkVWyLFwtejj9K9yqcBA6wsD1bdkWDBMrACThGJrMpeJAOALFjg1qxZs5Wd3V9r18Zr6FAZ6Q8yJ1b6AR9kY/AznYjYx7BhperZc6mQWLASHBaWYJgWQFBBQbmysjbq3HPbqmvXGOMjwONBW1wbLFldmSyJEsfFcdor7az88/+ADEDUrl2LVVjYVB5PWwNQMObzXcDJwoVubd26R02aFCoxsYXCwmJVXl6lp592asIEryZNAkxg8HYYKRKF9O7d5TpwIEtJSZUKCWkrv5/kenwelmmawpyClA5deGUAd6tW+eTxVCgsrETZ2T6VlbnVunW+2rQpks8Xqq1bmyojo6GWLYtRXp7LHBuFLqwI80jnLEzetBoG1AE0MME/8AA5Hi4lJxOM6DPAi+/AoOC7yM62WCwYCMzcRUUlSk7eouHD3erbt6s2bQrXnDkWQMB/AstEpgjbeOklt5nvxx5zmRT2a67xKDkZfw37ArxICxYAIByGmaJT1YABfo0fb0m/2CYMCAARJoZ54ZiR8HEvwLgRAggDxXWEeeC8grekqcOC/8i5eaNWO/rqlbLLlKxdOjv8S7U+M1jxd16kjp07q7wc9gWJmxU+CVgk+R7Jo2/+fPlvfFJfxYzTjgvOVViYW7e9doVCQoO0Y9pHckYmavnyhpryVpjeWNFNu/qMl+cvfzGMnZWFI02ahISO+8qlv/yl0gBvOr8BtqqP8eNDDPNz000/BCE8I2AxKeTpcoXk8ZcyKPTxqvB7CqtAm2DARaBUCsaE/7flUoHZIDYI4O+Ox+zO/BxPiKLtK0Hbz34AIXZXMLYFUApsV8zPx+orqa1rxXOc+asu0a2t7f+U7cBMMHcsdJ1IYAwIGzVqlHmnncxGAdwf5IF8/vnnevvtt3XJJZf8lOmq/+4vcAbqAcgv8KLVH/KRZ4AHm/3i5UWNvpTVOMyZaH3Rqv+Uwct9yZIlRrMagyaqhnE0AGKHHdrFPpuAVRk5cqSRBFBkUjgDMvCLzJoVpCeesDwGFPcUiBSb/IzsyZagIGOaNMmlzz7z6s03l2r69N666KIw8xlWwmEEKDLZPh2XAARTptANq1LnnrtaiYmhOuOMDoqJCTf7pVhFh4/mf968zTrnnBbq3z/WSIwoBBkUmxwLBmxW0unOxM8YiPkcsh6bKeE4KRqXLVutgoKGCg9vY4pcpEGwJ5WVeZoxo0gxMUEaPz5BWVkRRtJF9sbNN1eahPB27TBCk1VhycZ4Uc+cWWGua9++jZWcTN6CjAkcpoFCH+aBghijOyvmMEeAKNgamCGyPPByREXBhlC4lerDD8P11VdxatfugMaP366KijDFxoaouDhGmZkNlJ0dpvx8p5FGnXuuXxddRJaHNR8wOpinv/jCqagov8aN82vSJJ8p9NknOR8oU4KD98rjyVNKSgOdc06SARM0KZg9m+R2S0bFNWZeAWhPP+0yrMbAgT4D7ubPd+ryy3268EKfKcTZ99dfW2wSjAtSNYAJHhAABkAPRsi+d7hWgJfRo635AdgCQLgmfB5pFuzK8OHf54CsrtTivy+XY+ECvVV0jhprv94KuVaNggrkvfhi7f7DY0rNbGAADqABcAs4BrhxTb6a7tbS2z5R7L6t0qXjVJTUVLd/MFZRBXv06UPPKzW3pQFshSvKde+08Zrzh3fV/8Z+iouLMAsJXM+zz6aZgF+pqU49/7zbnFtNg/2dfnqoJk706oor/tsQwi7geU4cS9e7n/KsqO3vIssBOPGMwDh9pGcZRT9yLbvzli3jAnwxWFUPNLvbIYo2k1JbIYqBLENg2nwgY2I/rzmv6h24avKV1Na80jkMZoYQvro2kAYiXwOAnMhB2OH48eMNo3aygBj3wWWXXWbaAJM9ct11153IU6zfdh2dgXoAUkcvTP1h/fgZsAEIfc15wSAPOFq2x/HsjVU8Qr9YLcI0fjwAhJc7hlE61gBeWMGkiKCwQAM7bNiwg0nKsBQUXBSDZHIsWOA5KJWx90mRRQFNoYiX5KWXHKa4vuACv156KU3btrXQZZchybDYBQpZCm8YFgDIzJl+vf56lS64IFWtWsWpeXMM+0GmaEQeBFPAyjsSphkzUnXmmc3Uu3ec6cJFNytWpSnwMTuzUk2xzN9TaLOyjtyHohaZFgCDhWakQO+8s0mlpVHq3r2F8W4QKJifn6N9+/LlcMSrZcsk0wHrP/9xGI/FffdVGi8DMi9YBFiTVav8ys3drh07KpWX10IdOzYw37GlRoAfCnKKYI6H/eCJoCMTbBFAjLngeAFLfAajPMDg5ZdJ7qZrmFeZmXhIytW6daGiogqVkeHRli1hxtDu8zlVVRUuvz9MISHBSkwMVtOmTrMiD0jEYE/Bv3atxWC88ILbMFZTpni1dm2BGjcuUO/ejZSQEGfAJcfONf34YysIEMkax8/xAjA4TjJmXnrJpYYNLeM84YaYuCdNYj6s76anO4zvhv3Tftc2ocOm8O+0KiYfJTfXYeRhl1ziN/tAgoWBHgADAAFEAJ7YN8PyipRr4cJshefv04YvI6U9+/We8wq5qtza6mujNSnnK/mui+Vr2dr4ZwCcSPAAPfPnW+yMY+m3/8/eeYBXWZ5v/M5Z2ZsQRhIgbFAUEHEgKipKq1ax1oHWra21WmcdWLfUveq2aq3/utGiFgUUFQQZsmTPEEZCQkISMs/K//q9ny+epgECBIr1vNfFBeSc833v975fvnPfz/3cz6PKz+eo44As/eyvv1DPm34p17TpGj9mgpbU0whtq9q98XcdP+9VPX/bWxowaKsBpnFxyZo9O1v33ttWWVmQW5dRhX72s+ZJCPM99thY3XhjwBQKQGWkzG5LAPyuPBP2xXtJFaOkLV4ViNPulMa1HbObNlGM7JjdlJSgTBCB390miqjQPOvwGTQ3mBMBIkuULDGxRInrbKqUoJ60hipAnw1KnKOQ728DTyAkBKV9b45x48bpvPPOM4GcPckM2JU5XnfddabqFn4Pyv82HXRmt/1sduW40ff+uFYgSkB+XPsVnW0LVgACglGc9Ca+NPkCQ1lorQGhIWq0ow7r9AG5/faQAXB28Dmil5ANygITdbNfoqg0kCUMh5ElFwGxEIqTT/Zq/PiAIRmR5AOfAik9EAHIBed96SVyxGN0ww3lOv/8WvXsmWM8EhjV+Z7F3E3qz/Lldbr3Xp9GjiTK1kb5+RnG+E7OPVFzoud4TQDu4XBI69fP0rBheYqJaW+IEeekihMpSFR54v2AVozNkA+M3WvWOIoI6Uqk8tAVHCD6xhsr5PO51L9/N02fDqDfKJ+vRj17tlXXrpnmOPfc4zYK0J13+pWe7pS9tT03SJv65ps1WrfOp8bGTsrOjjdAF8BN+V4IFxF90sdIM8KATcoRQBg1hOuHePBeovWkJ/XsSYoTnhKXLrqIyk4AcozwLpNyRRldyAuKzqRJYS1dGpTPV6eGhnqVlweVk7NFBxywWdXVcfrii3wtW5ahmBi3WYuBAzHKuzV2rEduN6kzdJMH9LdTr15eHXaY04Q8E9u7AAAgAElEQVQQBcUp8esUGiCFDCIEiTjkEMfTQSND1I9p09ymihSd2kMhlynRe+WVwW0mdHufcO2nnx4yRQpQvj74wFFf4uKcfUGtokwv9w/XS4Ux1gAymZzcaDqh0yyRMWdOiT77rEjhMP1gOisjw6PJkxo1d2KFJrhO0rKCOH1X112dtUbVqR1UeOYfdNjVA826Q2qoVAZhhrRuWrhZ+S/fpVNSvpRr0jh577tP7nff0+d3T1JB+gBTcezntwxUaWKOHjjy/3TWWatVXFyvJUu8mj+/jVasSFdlZYLCYX7XSnXGGahNScaEHTkg8EcfHavrrlunjIz5Jt2RFMPdAfCt9QzZleMA0AlY4BXbW14Va3Zv2kSReaI8kWra1FfC+u3MV8LrEBACNQSBIg3vOyIQXHPknCwpiSRK7HWk4b25vd/ZOtO8sVOnTubP/jZQPyivzHfC3hyvv/66rrzySpMeB7HbFwNVhwqV2xt8v+5t5WdfXGf0HDtegSgBid4h/3MrgJRMpJCylHwpEUVqTXMd6QITJ07cYYf1Rx4hPz+0TbGwqRN8sTppH22MhwKiAF5KSanWkiVTTMlFW8c/cmPuvtttjNBXXfVDpNf28gBgAbip1DRmjFvffhswTQBvuKFCo0ZVGR8F58CngEJAhadvv92gs8/O0qWXrtUBB3Q2jQVJk4GoAFipuAUQBqAHAnQhD2vVqsnq06eXioo6GDDP+wGyAHwAPBWinF4eTjUsUqQAvKQoca1E9qnUBIieOnW5tmzxKSUlQ1OnVig9PaThw7NVX5+kvLywbrzRox49gjruuJASE13m86tXu0y6UCBQrrVri5SaigrQRRUVsaaELXPGGI86AmAHzE+b5jLpXQBgCAYgH2CN8gGxYr78GxVh3jyXSWUiVYo0KcgXx6KPBtdKKhpKAEoOqWmkhrHmqCakmCUmkh62VRkZlWYPZs6MU1VVWMnJfm3enKhAIFbx8WFt3OjR6tWpcrm8pokg/UPOPz9kFCkGe4d53fYpgdydeGLY/AG44w+hlC5qDqrFjBkuLVrkMqlLQ4aETJoafUh4ncFeoWKw/xBaTOqkd3k8TtoVZX1pksixIDYQlOpqp2oZe3bMMWENGRLWypUrNXXqZm3ZkqejjupgyDNEDuIHEXr1VY/evPM7FT4zXsWTl6vRH1BueK16eNdo4eCLVH/9H5WQ4jaqlJ1Xt65hHTzmPHn+9bH8Dz+s2sWFSnnpSX1y1ViVDzhO+QnFOvzcXtr02Ku6a8EZplu8z8fvVbXuuSdRHTps1TffpCg+PqBf/GKVjjtuvQHLkSVr+f/cuat0wQXdNWZMsU477T+beu6vD0GeNSg2FIVAQdiX5Uk5dyQhsb4Sm6KFcttcE0VLSgi4MHfIA1WmmktX3ZUKXOwRqgjHi/S7kGZm58ReN63CtSMDN0C3e/fu+6UHCHM4qbp8J+zN8eyzz+pPf/qTSddrDVVpb841euz/rRWIEpD/rf2MXo0A9VtMqgXRwsLCQkNGhg8fvkcdjSMXtiUd1l980WUMsIBpIln8IQoI+SD9gxQm1AvbzTozk6pOX2no0INMTnLTQWrNqFFeTZz4Q2lRyEFkLw+Oec89Hs2eHdDjj1Oec4kyMmKVn9/ZNHoDgIfDVHBaqKuv7qQTTgjo2mvpJu42RmdIClFwUn4A56gclOhFySD1qaBgkrKze6m6OmcbAZk2Df8GaU7OjEkzAqSjjtAjhBQYFBXbPA8ChG+jpGSF6uq2Gi8HfTqOOSZbHTowdwnyds89DTr++LBmz3YbL4cpD+vD5L5Gy5YBQNqrf/8MZWQQzcdQ7ZSy9XoB2aQXOb1OMKo7DRobDUlhbqhIkA6Oiyfisce8hhRdcUXQKD9cP5F6p2FfjFEn6L8BEevf3ymHS68JfBqQBXwaVPF0vBqO0gLIBuwvXEhFqIB69KA3yRqFQnX6+uv2JoK/fn2SSktpMIevYasefrhObdsma+FCjyZNcoiT7Z/ikAQ8KnRSjzFdv1kPqpdBNLiuDz5w67nnUAFkFA/mjIrA/I46yunWzj5TTQqiBrngHHg8fvYzh6xArD7+2CFVHLesjC7zGN3nGuUuLq6vyso6mhQziCekE1JHhTZSt+hV8vjjfm0sCKjxm1nqOuEFHVLyiWKDNeY6v+xynp7Of1hxbVPMup54YsiQYtfYsYq99FLNOfA8Bbr30qHv3KoF1z6vZQPP0RGLXlLOwzepdtVqPf9GuumfQqUxCObNN3v14IN+3XUXPSmCOvHESp1+eqEBzoBUW46bawuHM3TDDYP04otbNGBA/D43PO/qw5loPx42gCGKTXPPhV095p6+P9LDEZnG1dTDgW+D4hq8n74qkA9bFtga3+3fzc1pV5oocm6i93bPm+49c2lKSmy3+S+++MIUIaAPxv42MKBzXVSo2pvjwQcf1HPPPWfUligB2ZsrHT120xWIEpDoPfE/twJ86dn8Yduzg5zS1iz7SMlC0qia67DOgr7zDqbmeoXDcw0hIsrGe22TLogDwBnghoJRXMyX6BQNH95zu3m4Rx7p1ddf/0BAqGgU2cuDiD3HfeutkG65xa2RI79RMJigfv36GoVk69ZKA2hee62T6us76qmnvMYkjumZOQCs8X4ApOlEDsBEySAtC0JSXDxXeXnZSkhob95DZB5ASxrWwIE/9DWxZVGZDxF1qjGR2sOxAPiFhQGtXfudcnPLlJPTQ3V1eUZpWLJEeuUVul7Xa8gQ1AyIkfP5kpKANm8uVFLSVoXDVLlKMU39SLmi6hKgG5JkKjZ5nfK2gGxK+tpeHoBtPBNUwsKTct11HqMcnHRSyIBwyAPpbqg5EENSs5wO7U4ZXogJKgLpYaRHcQ78LZAsPKw0WCRVC+KB94E1dapcBZWVtVIHHbRRAwb01vLlWfr885BKSvwKBPwmpWjp0hT5/TR8rNBhh5VJilcoFG8M9VlZserQwWWUCuYGmaPPB+VoMfWjoqBSQEYgfkOH+rRokVuHHRY0vhIqUQ0f3miULYjRuHGOCZ15M0cUDDxDEFCUn08+oTmgcx9s3uxXRsZi9ehRZshzQkKmuXaui/uDNefztgIbn736aq9++9uAIRbMt493hfqOHSP3P/+ppXWdtKyxu2o7dNPUAy9XaXK+Kb2M0nV4jxKtPO5qrSxJ10Hn9VbPl0dr/tl3K370Ner+66NNfl/955NN+WMINgSGa4JA3nFHQHfd5TVki74pqI81NVXasGGuXC6nTwYR+dWrA7r99sG6885ppit90+Z+ANOmjfT+Gw9IwD2/q8wFAM8899cR6eFg3jzvSCm1g1StpuscmeoT2atkZ6TEEhOOvbMULmvAjzS7RxrwUUto9kcFNHwgzGl/2Hu7bvuqgePo0aNNJSqCZPvT9e+v93t0Xq23AlEC0nprGT3SfrICkQTE9uyw1aVaa4pEzvjSglg0N95+u0pFRSvVr1+lMZpjHI0cgHMAMqZjwDBlZisrv9Cxx3Y3x21unHGGR6NHB9W/vwMc8X6QMgWB4PDPPefSaac5XccBwj7fbPOF0rVrfy1YUKwVK1aptDRL48b10dSpIRO9B0gCriEzgHgAK6DR9uWANGDWBoj7/QuUnd1GWVntjRcjI4PPOx3OAYLk9vNZovGAfcgHCgNAl0g5AD01Fa/LOsXF1enAA+vVr98QLV7smM1JgaK/R79+pGy5TAqUo2RU6KuvyoxnpG/fDkpJiTPXTwTcqWIVowMPdDrFs56QBFKjuD5SwADllMulLC5kAuLwj394TP8LKl95PKgcpJs4ZnmUAVQTjkG0HcUG4kT6D0XPWHPSy2gwyL9pKMh6DBvmmLUhlqQkQUKoplVbu96kbZ1+egcdcEC8Af/02uB6IRDMG8N4bGy9Xn01TqtXe9WmDf1YQkpICKh9+xodemiVhg2rl9udapr91dUlqKLCY4ghBGTUKKfKFdcLIXvzTbfefddjyOFppwV1//2h7+fuNCpkbuwt+44HhDK9qCWk9bHfqEPV1VUqLl6rXr0C+vnPexiABkHjdYoL0L/EGvwtPiZ17G9/c+nNN726+GK/2rZ1OrWzfqHqOn075nNtfn2iOpfN1dbGBFUl56j3H0doYe9f6ptv3OZePmTOS0pd8LWyDs3TsG8fUf0lv1HMHbcoPj9f/vvvV+jyy808uEbM9uwv5Ik9Q91hH+Pj63X44YsMCTrttG7mnmEAcOfNq9cFFyTrpZeWye2uMJHzSGBq04rs36Qa7UtgxjOL1CWi9pAPSNGPZdi5QzjorYGKE5nGZXuDQB6sKmHX2Xo4In0l9t927/4jghpDKfEf/uyMlEBCrUICSaKkuh2Rc7Jzg6S0ZuBqV/YRAsq5Ub/25rjmmmuMT8cS3r15ruixoysQuQJRAhK9H/7nViCSgLSkZ8fuLADVU0ipatrAinOTu/vJJ5WKicnSb3+b02yqB0CPFCwi/6QPkQGwceMEHXhgj38zRBJlBmARjZ4wwYleP/MMeeExxqMB0CfKj7mcLuYTJgRMo7rHH6fK0jxjjl63LlUrV9bK683Wa6/lmveQMgVQxRhMZSpUBsAolaxI18I8zvGJ5jNHCIjXO1vp6W3U2NjZEBV8FcuWOWWC6SkC2OW4gHGUAQA8g1SeYBDlo0QbNhSrbds4U0o3HC5XSgrRaKdy1623+o1HpGNHpzzuggX4F9Zp7twKFRd3UK9emaZMLVF3vJI2jQ1SAOkgLQqshlEcMkWk/rvv6EruMilWXNeTT3oNcbj8clQJq1A0GmLCcWNjHe8Faw55oloU19Ozp2MSR+kAvENuOF9ZmaOU4AFBRWFdGBMnxujLLyvk9RYpPz9OGRmd1b8/3dSd17/+moZ/TiNDVBvAv63EhQfjgQe8psJTp04B9e9fo8xMqgSFVFVFvxI6ywfMOaurk0xq3bnnhpWfn6SGBp8xkaNssaf0I4HExcfH6PHHA4aokWK1ZInLnJP7CgJDnxb+z4AQfv55qYqKStW1a5zOOitPiYke8xoKCnOnxC+kCbLLepPexfj8c67brYaGRkPyMLBTBpcUMO5liC2kt33datW88p7iZ09X//C3auurUPDii+W/f4ymzY7VnJcX6cT3fqPUeL9y61cqdMrJahx5mnwXXazvPlyqqvhsM1/S0J55hsabVAbz66GH3KqtpSdMreLifLruujgNGOBUOYsczOPyy3364osGc98CTG1Kkf2bnzEiI/gAa1uutrXTVWxTUgzn+NfoV/TfAr+780wk3RX/HdWL8Hw0N3eIXiQh4d+2NwhEorkming4dmZ2/zdQ00JSAhmi8AfrzB5HKiXMiWHn1LQ08N5sDGivBVIA+e2DZLsXx8UXX6zi4mJT2TE6oiuwL1cgSkD25WpHz7VPVsBWUOFkLenZsTuT4ouLKFlkdArJn2aHnNPtPlAlJR117rn/DnwizwWABewCAgHAU6d+ZspB2rQuyAXgnqgwEV48DOed59VHHwVMihSRekA0KVKYpG+5xaO77w6aCDARbb7AFi2q05o1lPvN0W23tdWFF4Z08skOYCSSDVAFxKFicHzSaUjXYhCpB4ORZoUfZOnSxUpMTFGXLjmmkhSkAxWG+ZGCAxCGCEEMMDmjRjDvqVPDqqhYJ7+/Qnl5WTruuHYKBJZpxoxaPfrooRo6NKgzzghp1iyXKVFLWppEo7gCk67l9+coKyvNRNLpOM58IUooK7ZKF4SEuQLmuQaUCdQZpxcIlZ2oqOXShRcGDSCHoHC9XD+KBYoRn4NkoEwxFxQczPcMuq5TzerwwyErdHKnBwepTDS5DBuFA0DsmNT9pmfKnDl4NnKUnZ1lPCisOfvMevF51BUIDPPg/LxOFB/vDJ4Xusi//bbXlMrFXM7e9usX0pNPhk1flKoqQH1IKSm1GjasUEOGFJlo+fz5eVq6NFNt2vjkdnv1t7/F67e/Derrr91mvj//eUDl5U6zQeYF+UC9cRSUoMaNK9CSJQ3KyMhWv35Zokk0CheD+w4TPO+F7DkVpsKm0zr3I+lhdFnHiwNxffFFj266KaDf/tZZR3w5EG/2Ba9Mt5w69ZvxsmL/fJ9iuOFiYlR92DBtfep5xXdIV+KZp8k1Y4ZCMR6tzT5UFZ5MpdVu1MxHPjdzcLrMN+rVV926+26vbr99qR59tKNOPbVWa9e2Mdf5yiv+bfOP/P1j/265xWtIiE0hi3ydKkxNSUlkBH975Wp353kCwMartmHDBlNdjAp5+1J12Z0528/wvCXoAgGhmhSq8K7MHQ+HBf92vSP9O4DwyLXm39bDsSu+kqZNFCEZM2bM0MCBA//DIG/nFElKIudkGztGlgemieKuXPfO1pzGgDsqX7yzz7f09TPPPNOks/3rX/9q6Uei74uuQKusQJSAtMoyRg+yP61AJAGBFFBqcUc9O3Zn7vTsIGpGMzAGESRydomMkTZRXZ1q1AoLvFpyjqZpXZAPotEALRQCIv2jR3v0/vsYyR31w1aYIpXnscfcRgl48EHKEK/T4sWLVVKSJK/3UD3/fIKpZER6EyAbQEllKZQGCBAEBhCMShA5APkAeID6nDnL1b69V0cc0cXk2qMwECgkFQqAjlLAMQDYqASA/JKSWk2YUKaUlDodcURbxcamm0pW69YV6LLLOhrT8HHH4e9I1apVCQbkezw1WrOmUB4PvobOqqujqhFmZ/pWkF7jEBAAMCk/EAjWyOkRQuqZA5QBuYDd556ji3lYI0eGDGDlvYBj8C6VtTIzw4b4AMYhIRAJp7IUyo5T2pdzQfZQQjgH60alKQA9Fbcw75NK1bVrlTZupPklhOhg1dSkmOOhjDjEypkz+8eeQnZqapxu5fSpYG40EqTkMMdjkFY1ZYrHpJHhAzn+ePbXabBIWhs+GQCTx9OgUMhvygJXVFAFrF6xsSHl5DRo3LjuOvnkrRo0iHsoyxjqqZbFdVEsgTK8/K5MnLhE06enKDOzozIyksy147WApDBQPyZOpMeIY0LHB4Q5Hj8OgzXjmpgb9wbkilLPF18cNL4M7if2hnuKa6U0MMSL48XMn6/iK8do3bwtqlOckjJj1fmpq9Vm02L5brhBjR6fKjLz5d+0RZN6/lb/7PNHs/a//jUkrEF33VWi11/P1bnn1un999N06aVBo/RA8t5/32/u86aD39GHHvJq8uQGQ4h2NppG8AHMkdHySEBqU4t2pmJEdmUn2r0/GqK3ty7cdzz3SL3CzE3hj9YYEDLr4Yg0u1NinQHYb+orgajsShNF1BcCRpRTt6XPd6Rq2TlFVuDi33ZOtrFj5D2wJ+l7+6pJ4kknnWT27c0332yNrYseI7oCLV6BKAFp8VJF3/hjWYFIAkIU8/PPPzdEoTUbG82dO9eAPo5L5JJSvzRxIvWALyLA11NPuXXzzT90YN7Z+iGBY5a1aV3WqE6qk6NExOizz2JMxBeTNkoDAJBeDaRTAbiJkB922HzTVIovaFSW998fat57xRVO9B5lAgDO+4laowhASgDRKBYWqPEaqVQYyEn7KShYbkrS/vKXPQx5wQdB5B/A//XXXB1NC520GHBCRUWpFiwoUUNDskaMoMpVrCnbu2FDWC+/7NYttyzR5s1BY8DftAnw4FK/flXfG94z1KNHuvLyKF/rEAzmhToDyenWzUnzgggQhWcOqAdcB/Omc/yf/+wz6WknnBDcVsmLtYMIkAaEkRtwz88gTxjPUTBYH34O2EYJAWhDOlgnKjmReoTvhLWFJELAMLenpJQqEJin+Hgat/VXUVHc95WiKD/caHppsL6oNtOmOSZujgOJQd1BhYBQLlpEup3bGMHxaXDdECf27oYbfKYyWEpKWL16oTw4pZ65JnwWXDsej3/+062SkrCCQd5Xo9NOW6tnn+0olyugLl0qVFiYqoULs8x8rrhiq845p0KrVi3Xhg0ZKigg59xnCCT3HASETu+WYFACmDXgnsQHQrUym1qGh4b7FgUHAgW5YO3oXg4BPvvskOljwp4mJNAHBf+Os5+kAHJPlW7wK/1fb6n6n1+qc3CFBvoWKnzJhfK/N14xmzcrJiFeMTXVGnffbK0IddXGjQGVlJSqXbtaLVzYTW3busz9N2uWW+PG1evDDz367DOXPv7Y/713yiHvEEOIOF6Sv/3No08/bWiWpOzs93Zn5WqblgXm99Km8ACySZXkOfVj68rOnJk7QJ657+0qXTzX8ZQ0baJoU+Ugek1JCWvfXBNFSANVpjChE5yC0NixK6WB7ZwilRLWI3JOTStw2Tnt7L7aF00Smf+QIUN02GGHmY7k0RFdgX25AlECsi9XO3qufbYC9guAqNWECRNMni/VTlpr0FCQLxoGEVAb/bMSPODyjjtIC2k5ASHixRcoc2UQSSZS7jT6c/o5AEJJtfroI6LgTo8OFIHf/Y6eGA0699zpkurMMdavr9c//hHUpEl99Oc/0yjP8Rk41bNc5liAW9KriKTb5n1UjUIJAWATrebcRP+/+mqVMjJCOvfc7uYYAGneQ7QbMsB7qIBF5/AtW9bI41mvlJQcud1dFA5juA7r9dfdBvx/8EG9NmygxK4TKS8trVVpabFiYyu1bl26ibwfcECZ6uqohJWhNm286tjRo759fRo4MF51dZ5taWgAZYzgktN9/Y03eM2lc88NGoCNakKknOsFMFNKFzUJoAyB4fMAUhQQwDCGahQffDBUycJLAUlhrSAhKBesO+uCQsXfHTqsV27uMnXr1lZt2/bSvHnklDud0PGIQBJRGSBI+Cjw83Bs5oTJHSWC9C6AuAXxrBM/h+AA8Lk2BmTzyiu9KihwmX0bNCis3/8+aFQKvEUoM6Q64dOASKEuuN0QSfqHMG8UDYzXfkP21q5NUteulbr22nkKBDL17bcQlVjFxmLcZr0bt3UaZ7+c5pcOKYQMsjasJ4P7gXuWdYWAYFKnshqvn3uuT/X1TqoZ97TjDYoxxItj2EaFeKIgVRDkpILvdOTjo5S4foU5/oqkg5VVXaCkmFqVJXfSwncmqrZ+gZKTk5SWNkCffRavMWM8prIZc8BH89139aa62uuve/Tww35DjthD9t32h/nLX5zSxx984G+VR4QtV9s0hcuWBSaFhz+8DhkhlbO5/j+tMpm9cBCeeTYIY8vs7oXTtOiQkalyPJNZU5sqx/MYAhDZr4T0LZ7fXAPPSdbdpnJxQquiRJ58V0gJn2NOTZUSyCbDNnZs2t29aWNMFHGaN7aWqtTcYnKt7N/IkSP18MMPt2i9o2+KrkBrrUCUgLTWSkaPs1+tAF8A9osEAtKjRw+TW91ag/xcDO5Es7ZXJvNPf9o1AsIx+XKkahYDAAvYsx4Q28tj6NB/L8dL07jDDyfNp1CXX75eAwYcLClRb7xRottvb2NKltKkDhAL0CNliUgz0V9A9fTpTjlXIv/09ACIk8oFiYKAQDAgF1OmrDZVmUaN6mFAN2VzUVJ4H5FyyE1GRq2mTSuQ212r007roIwMel5gSG/U00+7DfB8/XW/6bTNteHd2Ly5XsuXF5pu6506UQEs5Xs/R7XmzAkZxaRjx3IFg3XKyqpRt26VcrlStH59tlyuJIXDCVq2LEHl5W598YXbpBTh9cAHAonjGgHpgE4UDDrC29S1776japJjnMfryTUUFUGuHGN8eXmjvvuOUrj02kBNwEzvdClHMdmyhVSRDYqPr9Tw4ekaOjTbkA7WjSpXYA5UCUjAQQc5ndQhFSgU7AHHxUPC/kB+UDpYTwiQTbMD5PM5CCjEAgUCnwVFAr7+2qn6BMCnmlWPHmGjWJFeBpHi/FRII0UKfw4G/FdecZku6sOGBeVylSkjo1Rt2ybovfdylJdXo969i7R+vdcQDO6Lo48mdctGl1O0dGmS1qxxuo1zTtLWrGqGOZ9KVBi7bYUvS6yYE71sID3nnBMyyg+pfKSeoZJARFkTiAeEjevi2lGl3HXV8l5yiWI+Gq+ZOkS5WqeOKtJ3Bxyn6ufuU79+vU3Xee5tetM88ohP11wT1F//6tbll4eM94lKa48/7tWf/+w3RR8gIhj5Bw1y9uS++zwmZYv7c28MnkeAUAAyCiV9VQCj9jlFFD4SKPNvSEpr+gpa47oos0vqEvNFASbNaH8bKBxNmyhas7udK0VEqE5oVROup6nZPbJnSdNr3FVSEul1sZW4ICmRjR2t2R1yAkna2z1KODck56qrrtIdd9yxv21jdD7/4ysQJSD/4xv8U728SAJCChYdhDF27ungiw1vBf1FkPwp79s0cmXPcfvtNNRruQKCaZyBKdIOIvMAZAAeIJO/f/ELj8aMCRrAvGlTUJ98Uqjrr8/X6NF0fO+ovn1dxjg+ZEiMTj11oc4/HzXEAaKk6XA8fAgAdCcNyCkDC+8BsAIUAX34Imw0m3ls2rRGWVlVGjr0QJN6RLSbATlxUou2qKCATtRuHXdcZ3XqFG+qZK1dGzY+ALwLd94ZNH4OjNaQlvj4Uk2dukmbNqXpwAOzjccE8ApgRzkAZAPS8VBAxGJi6tStW7n8/kotWBAyJXWXLUvR1KkdlZ4e1O9+V2T8JJmZsUpNjdPWrR4FAk5EnYg36g4kjGu2ZmgIAkAUIM01QzAiy+wuXeo0NqRjOcSsstKpBEW381Bordq2bVD79l2MMgOJYE1ZN9LASLEiPQqPDSk/eFFQZCAwvAcCh/JE6hqKAKCbfUENYJ9IJXIqZDmEArWL1/DcgPsAEOzdsmUuFRQ4RCkry+mP0bWr09uD4w8d6qSWQRxpGDhrVkgffIAiFNY119TpnHOSTTodJPHRRz3mGAMH1ikpqVYDB5aqY8diA57Ly2O1fHmG6urwtsQqN9ergQO96t070ahcHBtSxPk5F+OUUxyFgzWHmD37rMfsK4UH2A/Su2wZX8gf6wI54WeUPo7sy8mezXrkawXe+qdOCn6kfBVo9a1Pq/1tF9HunUwAACAASURBVJp147MoSO++6zbr9/DDQaNyMDj/88+79fe/e/TMM36zhihQkDubgXPjjV7zueee+6Hfzp4+MyI/z37Rb2HNmjXG6wHAbM7szs8YPFuakpL/Zr8KvG6LFi0y5mgCJfuiGlRrrT/pVqg2pGRBPFBJIAKRqlTTwgK7Y3bflSaKkV6XyDQu6yth/1nryDSuPfGVNF1L7kcqro0ZM0bXXnttay119DjRFWjRCkQJSIuWKfqmH9sKRBIQTOg8ZPmy35PBlxU5z+Qhk+9MBPO4447b7iF3RkAASqRRoTrgVSgrm69gsEGHHnroDqf57rsufflljO6/v0Jvv71SX36ZrqlT8/Xkkw6QAqxfdJFHeXlVys5erqOPPkibN7tNNBmwBYkhVQdzLmCZOQCUAa+oLqTOALTJ8cfsDOAFwNfWLlNCQrni4w836S0AWqcUbVhVVRtUVFSu3NxkHXNMnvLz3VqypFGTJknPPuvVJZf4DfEASGNMpoLTkiUbVV1dqvLyHKWlZZkUIrsWzJXKXABO5sHcAIyk9ECOrP/igQc8plzvSSdt1YABZSot9WvjRnpa+E3/jMJCGtAlqXNnlw480Kcjj4xVUpJ3mxGcayBqDtkhmk+6EdF3CMKCBS4TjUcdAVATJWdt8cF8+eUmffZZudzuRPXunSO/32fmCCngM3RgnzfPqXgFkI78A8EDnEMOWG9SsH7+87Ax1vNvgDRpVgzM7JAU1oaStqgSkydTgcttiJo1TtPTBAJ1ww1eTZniNqWd8/LwiDgGcZtaBtl6991affzxFgWDHoVC2ZozJ1a33RbUBReEzDr8858u04wQFYiCAX/4Ax3GKbkb1Jdf1uvTTx0iGAzS4yGgQw4pVX7+VtOjZOHCDtq0KUU+X5wCgVjjYYGAYDaHTFlCO26c2zQURG3gXrODe81WNmMtISikbLH27PnHHwc1YUK5kpJq1Le9V4OeukZJY/6o3hcfalL7UNvYK9blwgt9uuGGoM4/3wkC2FTB8eNdeuEFj+67zy+aTNviAHYOl1/uNYTxgQdal4QQAQe803GaYAiK7PbUjciywDatiOcOI9LrYMsCt9RXsLvPv8gSwdbr1tpliHd3bi35HM9qVBvWCdXGej4iValIxSSyL0xzTRStarG3miiikhGQ4nvLeowsKWX/m6Zv7e7+Q8LwRr700ku65JJLWrKU0fdEV6DVViBKQFptKaMH2p9WgC8QG9maNm2aiSJab8WuzpMvG0zmmM150BP54wuN/5944om7RUBsQzfbywPQGw4vV0bGZh1OPtUOBiASQHr33RO1dm07Pf30wRo+HGWE6Lz05ZdOp+uLLtqkKVMK1KfPAGVkuE0KFt2yIwfHwqBOyo/TU4RULEcRQV0gzYhBpLiubqVqa6loNdhEielgvXy534DxuLit6tWrrbp0oTeKU072oYdi9PzzXj3xBM2/XFq40GVSjOLjG7Rp02oFg7Vq27aTKiszlZDgeDMclcPxkhC5hwhQDtflIrJPx3GnBwiR7Gee8RhwfeihIePJgACQ0oNC4XJhVq3TvHlUvapXcnKVMjOr1bkzpMyjzZuzjeE6Pj5OGzcmKRh0GXJE2V2un9QtyuTidbA9JJ2u6KRylamysloNDRlyuVINOAbEkkZE+hqkgjQj0p1INWOv+/YN6fjjHWWHUrX4PxwviaNqQSAwqfM66/6vfzmpYagiEEWi+CeeGDZzXLqUwgL0u3DUJ3wggHiIGQOgfsUVXn37rdsoN6wr5u+jjw5p8eKN+uCDzSosbK/0dG4Gt448MmQaB3LPjB7tNwSGe4F0ubfewszu0h//GNSll4YMMcFjkp2Nwd3pGH/UUVvVu3eZNm/eqtmzIRA+1dZ6VFPjUX5+QKecUqf27RPN72BjY7LmzPEZUgvR+OQTj6lAZUs/8zP8RNw/EHQIKcTKKU9crTffLFF9vUfZ2R0UDsea9cBDwn3BXtnqYrYM8JgxXs2e/UOZXdab1LivvqI6mlcvvNBgepQ0rYCFX6Vv37AhZq0xIBQAYEAuz6HdKYjBMy3SgM2/I30FkV4H1to29tvT+fMcpb/H+vXrTZlwUnb2t7SwHV0j6W4QP1KuMMvvrCoZz/umBJB9iySATX0l/N+a3a2fZE+aKLKv33zzjSFL1hsEAbEkyaolTb0ukUoJ/96eOm/Xq7SUXj9d9fbbb4tyvPtiQKgeeughQ3r4XsXjcumll+rGG2/c6d7si/lFz7HvViBKQPbdWkfPtA9XIJKAUDLXlsfd1SlwHL68SD0gjatnz57mIUm9froVDx8+3HzxNDd25AEBgJGOAtgmSkxVqdratWrXrlDDhg3Z7jRtCtioUV312mtr5Hb30fDhcXryyYABBaRavfOOW9OmOZWBvvhigQ49dIhJSbJpLvbgRIRRGFBAAHuAX1QA0oEAcoBwW4GLlKTa2o0KhcqVl3eAaSwYDBKl26T6eq9Gjmyj7Owk0yG7b9+gMZvTd4IeEFTQAlSjthx4YLkKC1erujpBI0Z0VG4un3Hy/q3RHpICiUGZAFQCxEk9suTj/PN9JprNsVF8AJQAZsrw8lmuE2I3axb+GSLiqDqQyKDi4hpUV+c3DRrLyjBtx8rv9ygtLWhS3Hw+r9q3x9zNOdzfp2+hjlCqt16hECpVlXy+g1Rb29YQPsAr5A4SwH4ShYc4AdBRkEi5IpXomGNI8XL6fADiIRD8H0JF1B7SxRwwjo8dSxlgp5cKpIprgnTiUeH4pDlxz7BnnPeYYxxfC2vMnkIoMYz/619urVjhMvuYnl6mNm02KikpUx5PW0P6UL5I1frVr8LGV/K732GIDmvQIMr6OmWW+f/48R6jWJx6atCsOeoN9wzkC4WD+4bBXo4fD0kKKiamQR07QkyLlZKy2QQENmxIUmlphny+RHm98aqpSdT//V+qqUAFOcZDgpLBPnI/oP6gOnk8G/Tpp4UqKmqnzp3zVFnpMevKmlGFi3XgnuA+g1Bzz7AepPlhPh83zklp4veOe5v7Aj/NY4/59OyzDTruuP/s13PqqT6deGJIv/tdy9Mom/vFBSyS+sP1t7Zhm+cBx480u0d6HQiYRKZwRVbgasmzkOPznCPgQnW+jrSW/5GMSNWGdDfmvyeqTSQBsEQgsgRzc2sNAdgdXwl7OmfOHFOhiz3b3rD7bz0lkY0d+Qzpek2rcEVW/Fq9erW5Jz/55JMdBtNac8uvvPJKPfvss7rooot0xBFHiADhK6+8In7+9NNPt+aposfaz1cgSkD28w2KTm/3VoAHM5EWhq3Wcgj5FrswKisrTcoVJISoJakHdpBGwXGHDRvWbKdz3rczAkIVJgAjBIS+CIHAOmVmrtLxxx/d7Cz5UmI+RL3Gjh2ifv0SDUB87jm3nn8+aADbTTd5NGNGwPgdbBf4ww47SuXliaZkb2ws6UQOcKSJIBFnlslJcaHylFNtyfaqAPAC2gDUHk+J4uPXq23b/iorK1IwWCCXK0upqZ1NhSrKxpaXh/XCC1517hzWddcFTSdxUqjq6ih9u1kuV6Hi4tKVn5+n/v1dBnxDNCAMAHmAJ2AZFQHSg7KBGkNfDBrgUdUI7wDvBVwCIoncs4Z8T7OeqAL8bT0UHJMUNxQS+m1gBUKhwEQ/f37QpG117FipQKDORJQhV/QgcbtjVVDQRomJXh1wQL0yM5cpMxNPx8FatizZRP9Zc+aPgoXPgvXj/0TYN2xwmfXmNUA7/hui+QB3jNq2+hivkVoG0ObfzJs0IYgVqVSQEPbElhimNDBEE/IDCIesnXdeeFtjQPwppIDxWchMYiJNHjdr1qx05ea6jHIAYKeBIPcPxz/jjLBReljLCy/0auVKly67LGiUB+YMwWBPLrjAZ+4ZCFWHDo55nPQxVCMG6gWd3CGEECeqb9G7BEJTXV2jKVP8WrvWr9TUCpWVNZhKXV5vWH/960F66KEVSk9PVHFxmsJhyqe6DeFKSFipsrLV8vnyFA73NIoMa4gqBwGJVPVILYSgcS+jHuXlkUpF75qQrrjCqYzFfQXx454n1e2JJ3x6/fUGkwIXOVAHhw+PNT1Mzj1390jI5s2bDYDHTA7Q2xeGbZ57AOOm5WqtIswcLCmxf0eCUrsGqAA84/idQDmgRPiPZUQ2R9ybqk0kAYhsomhTtCAATX0lLTG78/2yYsUK4wdkvyKbKLIHO+tXwv5HkhK+O+z3Ib6WTz/91NwjELPHHnvMEJCdKe+tsff8LpBB8Pvf/15PPPHEtkNec801euqpp4xKGNnctzXOGT3G/rsCUQKy/+5NdGZ7sAKRBISHHg9bap23ZPDlUVBQYLr78gXNA5MvkshBRBBlZejQof/xmn3fjjwgRMcB9RAPOooD1ny+QoVCy//DVwJBWLt2g1auXKyEhHgDZJYtS9JVV1F614myP/VUUFdf7dHf/hYwzQYZEKhp06YrI+Mo05AQTwVgnmJggFmqJVGOFzAG8AU4E8kHCGPYRQGxZminYlGRamrWqq4uQ42N5frZzzLVvn2+AXwA17q6sO67z6dLLgmYkrOkTgHQvd6gNm1apfLyGlOWl87g9H8ABHN+QCHgFtDK9UAmUAcwJONHwZeAHwNPw0knOQZr5kyKE40EAaMAYgAlJm7bywNyAtgE0HNclB1UFH4OwSIKzmuoL3hcunWjoSAeDL+pzLVxo18FBXhmatS+fbXy86vUpQuR/XStXdtWFRXJamggiu8x6wdJwGODZ4RKVSgdgGCCxuw3YB0wz0B1QnGwQJr94LoBvXRJd+4Np5wu14rKQDlb/v/JJ25DQLhnIGFcG0Zu0sAgexjBIS/t2mF4b9DGjZt0+OGlGjkyXy+8kGm6hltChsGdcsUnnOCkvDG4L0jxwiw+bFhITzzhqB4MSOtrr7mMkZv7CTJ48cUhMzcGfWrwp6Sn41dx7gvS5Dg+pBDSjcIB6SFVLhSqN31JSkurdeWV+brqqjlKTa1TVZVX8fEeZWY2KD6+2gAlUkU2bow3e8e9wjG4VyO7mKOgoMKQCse9QE8aFKJTTonVO+/QbJB7yUnp43MQUUjO1Vf79NhjgW0NFe3vMPt27LGxuvnmgCFauzJILyF1idQfQNXO0mF25di7+l5rdm5aFjgSlFo/CX+j8qL8MkgD2lEUflfnsrffz7XSHBEQ35rNEVs6b1uC2Xp3rFrSdK0j1xuCakkLBU5I78Uob3tCNXduW4XLkpEdkRKOTeDKpm7de++9pj8WFc0YfM/RkJG95vuFv2mKubN0tZauiX3fbbfdpvvvv18oLxBDOyjKkJ+fr1tvvVX33Xffrh42+v4f6QpECciPdOOi097xCkQSEBpOQRhouLSzgcwOYSE3FpMo5Xube7BTUYUcXSRk20W36bHvusutW28Nbeto3fR1wCIg22nKRn+JQi1btuTfpPCiopC++KJAGzeWqVOnDJ1wQmelpnoMQP35zz06/HCn0hGg65e/DOuGG34ASXzZTJw4XR7P4XK5kk2+PGk5AC8ix5yfaLZNI2J+VNYCpDMA5/gJeB+pUHPnbtSWLZvk8Xh17LE56tw5VXPmoN44pu1x47w6++ygUTUgHxAnr9ev1aurFQi4lJVFNNBnov1URSItigg+xmtIBVFrqlGhFJCrj4pw++1ecxzy/PFJADohDAB53kvKDQTs+6JB5tiAeYAjqUgAdKpgIV5BTDA2s1aQJogCygveFEAoXgnM2syd9LjVqznOJiUmliozEzAQqy5dyrRlS5UWLCAVKk3FxYnq0AEFBaUhQYMGeXTQQQnGgE0KGHMDvBOt79HDKfOL6oBSQBlYiBevUQoWIgFhwyNCOVjWgIg+JIxu45Sz5WcffeQy/hQ+B4EA2FN62KZB0c+CtWtsrFJFRbE8njhdeGFbHXSQ01qd63v0Ubc+/dRtFA7IAyoCkX5UIpt+BwnkPfQPeeONBqMcQao+/dRlUs24jg8+gMzE6O9/b1DPnjINFmnwiELF6wzM81ZdgECRHgbw5z2QJogb9zBkd8SIWF13XbX69ClRUdEqeTx0MHeZ6C33wcaNmcYz5PORWhKnPn1iNWCA1ygtkDcUDfac+4DzQ3LYd4oeXHxxrPGbOOlpTooc957tr3LCCbH6058CJqWLzzI/SBl7cswxsXrwwf8kKM09TyKj76Rt8gzZHz0TFpQ29ZVYAzbXlpaWZv5YsNyaFZh29izendeZO1F0gi+QPkzc+8OwZvdIozv/jqx2ZkkepIAiJ6juNoVrV83uTcnJ9tbg9ddf1/XXX28UCUgBihdV2hh4ZyJV/9ZYRzyT7A8pzU0HviiID2pMdPw0ViBKQH4a+/yTu0oAiy1liJSNZ+OYY47Z4TqQssTDkYf9zr68APd0qh08ePB2G4jRf4MKPES2WzKa+ko2barW2LGrDYjt1q2DkpOzTHoSEV1A4vDhHuN7ADQCwJ99NmR6PdhBxOvTT6fK5RosKdWkyfDcB7QCCCEWeDYA/thYbMlW0nZQB5w/DgnZsKFamzbVmNSkLl3aGlP71q0OIAZU4g+46KKgiUhDDPjMli2bVVW1RqtXd1RGRjsdfrhLNTWOWZzzA+yIWJMaxmeo/gQR4bVbbvFq4kSXWb+0tLCJtvfsGVYo5JjiISBEuQHTEAqUBMA0IBw1w4JojguA5pogVhAfBsSLn6G+MADCtqM5x506tV6TJpUoJoZKSW3l9aYZoMrnAbp8R3/+OWWAg0pMrFZq6laFQjWmX0lWVr3C4TiVlLRTZSXgLU4DB8aqb196azimesdT80OVK0AyQB3QO3VqjCkkAHFB1WFvaaSIWZrUOpSpqVMB5c7rEBGIExWjGIsWNerVV7do3TpM/gk65phMDRrkVJRiQGpQIgDnM2ZgKncbdQbTNeCd49Gl3CpKGM5feMFnfCannEIVKpdJd2Ou3Jvdu4f11lteo67hy4FccGz2Nzc3rCFDnD1hsHaQP3wa3HNUx+LckCwGxOzMMyFxhTrqqM0aMaKr8vLijQF448ZqTZ8eVGVlvWJjUU1c8npRX2qUnZ1gAgHFxRkqLqYKV6y5N1GP+H2BSDz0kMfs9xNPBIzCx1zw3Ng2FpZocI2kjbH+qGak8EHGUUJefNH/H6lakb/bkZ4J/GJ7s4lcS54pu/oenkGUGcc3QMqVTeVq2m08MoULdXhPvBW7OsftvZ97BADN3wBZiNP+PKzZ3SolgHJbVIB5s6aR6Vu2RwiqRFNfiU2v29Umim+++aYuv/xyk65nCRDkDQXpyCOPbPXl43uVFDRbcj7yBCgwEEgCgNHx01iBKAH5aezzT+4qIwkI8i5RneOPP77ZdeChTfQHokLFEVKukMR3NPiSo1MtObpEq5obL7/sMqAtP79ly88XEB4PfCXkjn/99QqtXZulPn26qF27BJP+QpScaDkdrR9/nHK8TnldPCBE/gGGKBoArKKioCZP/k6BAHnzySYdxpIMwB8AnCgwP0MhAGjhAwC0ETgkOlxdHTQKTEFBrdLSko0P5OKLBxhpfuZM6amnPAZwXnpp0ET0+Wx8fFiFhRtUW7tFycmUkWxnekzYXh6cm1Ql5goRwAvBoJoTgPahh7zGqzF8eMiARLwMgEOXy+nYjpIDGQBMooAQrUYFIOoNEEeBQcHgdf69fDkkyWXIGt4UQC9rMXeuy5ABADTX7nRMBywXa8GCRVq3Dv9HLyUkxBnlAqBsDe4cE7BOOhHr16uXkyKVm0uaA+b8gJYuDamhoUYNDaRl1alnzzq1aZOoLVva6Lvv2qixkbQLryF5kEMICClwq1c7HhCIIevJddOskDWDgDiVnBwFhTQ0lAmIF4Sgutqvd99drWnTYuX1YjRPMYoSKVqAfMgMn2XNbbM/iAnpd3/5i9ekoHFM7g2qcjmFA8LGY3LvvV5jjv/5z4OGKHIsCBXqCz4UyAxlgCkYcN55QUM6+DnXZAfrTQlp0qMA/pBR1pz155wTJ5ZpwYIijR3bx/QX+d3vHPXEliy2xAmSRFGB2Fgqm5UpFKoyIKq6OqCiogTV1cUpJSVe3bp51aWLQ04AyiecgBoU1MCBTu8RFDVbQ4JrReG59FKfjjuOqmFhk+YG2eX3AqJ94olxeuuteqNmNR2RABig9WPzTNjnZHOGbWvAjkzhshWYAMrNVYVq7fSdHT1FrdGf90A+mM+PZfD9Q8oVVca6d+9ujP7NNVHkemwX9abEhCIru2N2/+tf/6qbb77ZkLZ9kSJIGiVKB8bzpoNsgpKSEq0kKhYdP4kViBKQn8Q2//QuMpKAkItNPjPyb9NUCCJ7dJwlRYuHI39aEs0j0jlp0iRDVtqDiJsZ773nVB8CeLdkkPZFZIjjIX8nJ+eqrq63qqvdJlJLRSBANOlTt97qNt2d+/f3mYg154CAANR4L+VXU1LC+vbb75STk6uMjHRjPoesALysbwPuhCpCNB2QxechOYDtQKBK7767UmvWxGrIkA5GZZg3r0CjRvUxlaKovgVJufLKoPFyAIwHDarRqlUrDSkZNKiDunTJMCDfqWTlpLNwDYBOADReBsgAygZldZnbPfcEzGcAf8wLA7pDPBw/hQWkpNugmnA8wCvqCmlUbAeqCEoBQBuSgHqCyoGXBUAJWSEVhz+OT8UBw3FxVOjiCzBXHk8PbdniNkoAygfeGQapVZAbgOuaNahF9BhxqlzZZn+8B5M6cy4tDaiystYAZa+3QuvW1WvmzBStWJGm1NSg2rb1GMJL48jBg+NNDw08HMyNNYW8cY2AeVKfUDBIL2P98DKQ+gTxqqnZqilTFmrWrDR5vV3l8cSbOaBCnH66UyWLdQJks64cl7Qn9txW4KJb+J//7DSDhDjQ0BLl5a67gobgYAv49a9j1aZNWL/+dcjc39x3Fu9x/BdecOvFFz2mpPHttwfNfnFPQnYhVlTwguhADvkZxKtPn5BmzFitL7/EGEsp5xxdf73P3K8vvhgwaYMQBPYV9QTzOnOE3NuUQfamvt6voqKtqqigw3SFamu3mtx3RjjsVUFBe91/fx9df325OnWKU9++PnXr5hBg5sK+QUQfeYTCAyGdfHJ42z3Fe/DHnHZanD76qN7ci3bYghU8O35sABjgSpoq3gOef+TmtyRljGj1zoBypFLSkrKwLXlONn2PbTDI7xBrv7Pg0e6cY299JtKvgudie1XGbBf1yHQ5SFdkYYHmmijuiJRAfE477TRNnz5drOG+8PlEFZC9dSf9OI8bJSA/zn2LznonK8CD1+YyA+ZJrUIBiYzyoDJAPviypcoLZtGWDh7eVBLp27fvdtMsJk6kwg/54y0jIAAA5gOI4cuoQ4eOBohjwgYkk0YCKOTfb77pVAgCmH78MaVP3QZAAQTxNowYQX8MyqfOVfv2nZSW1sa833bqtiAUAkK3cpQHwDNRa9KdMjKK5PfPV1FRtin127OnT0VFFZozZ7UGD+6gW2/tYMzLgE9AMUSgpITytMslJSo3t4sGD441RAgC4CgFjhcDIkD6Eb4RIuH0msCQfdllIZ10Ej09HOO59WjwWp8+DoCmqhQEgnlzDXg4iMYDfBsbKdkaNn4GFCAa6UFC+DfnZC6ke7EGrBtKkW16FxdH07nFcruL1bFjD5WXdzYkirkwd0jekUc6pYD5DJF4cC3zh6BAnDg3QB7VBgWGayCdy+nq7fTpYH1DoUaNHx/UlCmkljWY7vIuV7VJ3+rYscaUjK6tzdSGDVlyuRLVuXOcjjjCo/h4p2oa5+b4kAhSnTj2IYdsUnU193KKVq0aoJUrY42pHpWG+UFAmDtpd3weTw/pacyN1DXmBsh3+sjE6L33PPrqK5chgWedFTbleiFZZ50VMiTgiSc8Jk2MPhmjRjlVyRiQws8+c5l0LLw1pHfRQR4SAQnFP+KQS4d48rkRI/wKheapqKhKgcABpjkiaYLcI//4B4Z26aWXnKaAXDNpe8wfgzlKBOoJZJD7H9IGaWJwj6AMxcQ4QHn16hrNmhXWd9+5NXVqlkaOXGFM7gMHBpWenmIA2Lp1GSoqSjRrfd99XrOGjz8e2JZCxnEXL5bOOy9WEyY0GBKH2ZmUFT5PQIIqQz+WQSCFZyO+A55l2wumtPR6mgJlR5WCDDrPQFSopp3d96SbOhFzUnZ+jJ3ZI9ee759d9as0LSxgyaBNPSbVKbKJIuts09L47B/+8AdT/vYXv/iF3n///RaRzpbeB9t7X9QDsqcr+L/1+SgB+d/az+jVfL8CkQTEKgtHH320KWnIa8i8pF3Z5lS7AxomTpxoJHPM6s0NoqkA81NP3Xn1HEgSX6TMjS8j0iAYfG8DCgHCgDKixnff7dZvfhPSAw+49cADoe8NzTJpWVSFGjQIE22MMSuXlNQqPd1tjLqkNY0Y4aQwUQkIIEjpXJQVwB6pXbGxIU2ZskFu9wYNG5ak1NQ+WrmSZnQoIvWaM2etxo7tolGjlpqStB5Poukx4vFs0Zo15OZnKT8/Rzk5Tg8RUqQAi8yfqDepU1waoJ5eIW+/7TYVrOguTpQcMoHawSB6z+cB9KQREfEGMAOWAc2QJpryAcIBz/wMlQCgi0LAdUHWALocG9ALCeM9zAciwdxqaupUUbFSHTps1XHH9VBjY4YB6RjE8cEUFLhMWhEpVk7VpUYDtL/9lp876gR+AY7NGkI6KS5gCRYgnqaNrAdkDQDPH86PVwaSgk+ia9d6+f1VWreuRvPn05WcUtIBxceH1Llznbp3R5lI0cKFWVqyJFnx8ZSmguBVKC9vjUaMcKlv3z6aMMFrjOwoWqSvUXEMYzVqAgPFC48MpA1CxHXZCtOs16RJMZo2jfLJThf6mTPdZo6XXBLUZ5+5zTUMHhwy9+bjj3vNcd96y2/+TwleTOj0FoGccTxI34QJbjOHY48NatUq+uagDJFiVq9Onb6Vz1dnwHswmGGqXFnShnry8MNes5/vvOM3wltSMgAAIABJREFUCgyElHuD+4kUNQonsPcQPq6L+8USEpQr2+mcFCrS7iDCTz+N2ubXGWdQbKJENTVVxu9QX0+PnyQ1NqYoNTVOb7yRo9xct556imIP7m2/5hDAK67w6W9/W6aNG1eYtBIA/L5MO9rTh31kyhhrT9WlvTFsVaimZYFtVSgUi6akpCXPY1KWUG5+jGtPSht+Fe45qk611trbwgJNlSnO98Ybb+jDDz9Ut27dDEmePXu2Ro8ebf40V4Z5b9wLVLkaM2ZMtArW3ljcH+ExowTkR7hp0SnvfAV4ENsKI0T3ZsyYYUx1KCC2SgrkoaXpBs2dcfLkyUb94IHe3CAaCxA8//ztE5Di4pDmzFmjTZuK1LVrkmprN5nmU9tTYyAjjzziNiCayC/gj3QqQBfqB9V9ALUANoC8379IXbqkad68jqJ/BCoBAVoUBSLT+CGIHPOZ6mpKtq5URUVQxx7bTgMGtDUpUkVFpEKFNW2aWx9/7NHTT1eYDuh8efr9W01KTFxcUPHxQXm9serZ06VevXwKBNK0ahUdmd2GPKFWoODgOTjnHLplS3/4Q9Cce/lyl6nohQoDaQM0QioA6gBHotmAYWu45jV8CzTjCwZjzDqQNgYRAIRiZua9EBjWhH/zOoAWtQKwihciFNqsoqLVqqjIMJW9DjvM932qGa+7zGchH8yZaD0ECgWG82K8J13HphNxbbzumNRjjFEdAI6whp+CufF/lBsIGCQIcuPzOWVqIVkA58heFVJAixfTpK9SHTuWmEj+t9/Ga+5cjPE0TuR8+CRc+uUv2yg9PUEbN7o0a5bje0ExQgUAiNsyu6RuAeRRNUihIx3OEhB8RuPGuQ1p4/isOSoX5Oq223ymRwreCMifY9oPGTP4e++5dccdqBROals47HhzuAcpX9u9u/TnP3v0xht0Xg+bvhzSVsXELFLXrhQvONhEx9lrwD3Ezymd7BBG0vPGjnXr0kupckRFNXxKDqFjbXkPe83vglVE+D9qF68xWG9IoVUU77zTq2ee8evoo53XAcSVlVtF8QdSuILBSjU0bNXTTx8ov9+t0aNXbKsGRTrR2LFVeuyxDnrnnUL17v3j6g7OfQQARv39b6SM2apQTStwNY3eR6ZwQVSYL5/F04dnhecvZv+WpIzt/Ftj37wD4keTQb6fMF5vr4pia86GVGN8F1SYmjJlilk/lCkGZISKW8wFVQT1fW8Nvnu537bXBwQPJAG46PhprECUgPw09vknd5WRBMRWrKIcJl9aRCmJ+GE435Px1VdfGdmcWvPNDSLNALPtdVJes6ZW//rXGhUXh5Wb21G9eiWprOxLHXnkQduV45980q0RI0J69lm3Hn2UKLmTksKlAPIhA3g9ALOTJ8dozJgyZWT4dPbZyYZsAMYAyKgjGIohBQCzhIR6tW+/Qf37V+rww7uqZ88EUyGroCBsItuvveYxHc2ffTZg0nqI8Kenb9GKFWu0YEEbk7ffvXuD6Z+RlrZF7dsXqbTUq1WrUpWZ6VJmZrzKytI0Y0a6liyJ0wMPBE1UnTUCcAOGBwygd4ST3w8ohlQAiClJW1uLkRu1wTEOAyQBmAB2fAyQKofckBLjdMRmPSBigGleQwUBiKNEUDr44483qqZmk3Jy0hUTky+20fbpAAjbcrgQEEAtigBqAWtoO45bhYb0Js4ByQCcQ4KYF0AaszZAmH4YDI6LesI+EI1nXalAhdcCsgJBAEhDLgD5EDLmbXttbNjg16uv1mnJkholJjaYnht5eXiYKuXzkaqVrPXrs1VdTRQ/3pi58/IcnwOkgEaF9FWhDDLnJrVq+HBn7jRnHDfOZUgd68zaY7CHRENI6PNx880YXmN0zjl0ycaALNO0kJLJpKXRLR31g2P36hXSL3/pXAcD1eWKKzyaORO1qFCXXbZFQ4f2NGlnkDPuS5Qh0uVQ+yBGpLUxl4cf9pimmxQ8QA3DpA8xRVlh/Vk31h1CzX3EHrFu7J0dnIN7h3u4vLxRjz7q06xZDds6u7Oflnzxe5STQwPFakO+IJV33DHPkECbUjRzZo7ef7+n3n67UGlpThrXnqQU7cnzqKWftamnED7AYEvUhpYee0/ex5oCziP7Z0BQmpaq5f8EPzp16mSCPy3x7O3JvFrzs8wb8sEA8NM9fV8N1vLMM880PsN33nnHlKUn5Rciav9gSqewyt4cv/nNb/T888+bTugEBb/++muTCnbFFVfoueee25unjh57P1uBKAHZzzYkOp3WWYFIAkJpQ8gCA8JAtKc1JGciSkSvOF5zAzD22GNOL5Cmg4pXH35If490DR2K4TlRpaUhbd06RSec0H1bClbk5wCyo0e7DSAjVQlPgvUxAFIBs05DvB+MufQBKS3toFmz8g24xWcR2Tl6/fqwJk9erylT6rViRQdVVaWZlB36knTrFtKwYUE98kisMjOdqlR8FjKwbl2Z6uqKTEpQMJinrl0dcI5iADikylB1da1mzqzXmjUBLVpEJ/M2xqtw+eULTbQ7KSlFMTGpCgRSVF6eoupqjwG5pNUAHEmhQkUgxYqfEw3n5/gASG8D3NPoD9BZXEyVKweIonCQwkMknjQzALRjqHY6vefn12nWrIWml0d8fDelpmaaiDrviawngEJDNB6Vg3WFMKFwoCQ45X+duUF+7NyYJ6oN80M94BpINWK/jj02bOYPAKaUrdNk0GkoiL+F1DnWl8+h4BCpZ+CF4byQTED1jBnlGjeuRJs2papdu2wdfLBHRx8NiHYqQS1a5NeyZQD0kDGpZ2f7DaHLykpSOJymiRMzVV6Okdyp/MW1n3lm2MyFBokoINxXXAtrwJphxkYBgqxC6r75BrM5tXNjdOedAaPkQGbZ+5dfJuUvbNadogD0/7QlgJcsgRhvVHFxhSZP7qmKikTdfntAv/pV2AB8yA8EAHUDwodPBXWIz7Mmr73m1jvvuHXBBUFDkrjP6JECjuO+YO1p7uk0eHQKFtgmiqwlFcdI8eL3hTF1qtt4hF5/HaUpxlwb6hqfhwRBHK01DAXnyy+lW275wqTG5eTkGNXkjTfiNX58lu6552tDiFvaabx1nnS7dhTK7JK2tD80R2zpzInec1/zh7QrS0j4vC1VG6mUAOr3R1JCoQKAPt89kI99aZaHdJ5++ulG+fjggw92WpK+pXuzO+9D5XrwwQf10ksvmf3k9+jSSy/VTTfdtE8qce3OnKOf2TsrECUge2ddo0fdD1aALy4iTsi6RNXwVVCFo7Xk+pkzZ5roIWpKcwOw+Kc/uXXPPT8QENJlKLlYWFio6uouCgR6qGtXl4mSEzGvrPxCw4blN2ts/7//c6pqYdp+7DH8AU60HzUCwE0kGrCEJ8H2VaDCSVJSstLSDjAADoAHkLz66pDatKnX22+v1tq1QfXt204+X7ZJycFMvXhxWA8+6NFnn/nMzyA3+flhXXppg0pL1xhS0aNHhvLysg3A5ny8DyWDClMAP8AeYHv0aK95/S9/8atTp2pTptYCis2ba7R+fbzKy+PkcsWrSxe3+vXzKS0tyVSJ2rTJY6LfHBclAv8HSgbEAMBLtJsofIcOYZNixfsAzETPiebzHqLvrAvgsGPHClVUzFVtrVcJCQdp69ZkA14By02LmaFkQIDYF44BiMe/YqslQba4VgAsQJx1IyJPJJ5eHkTT8Yt4vc7ecA48IlgJvvjCZcAue4GJnCg9x2cu3AuY522vDEsoIdULF67VJ59sUVlZB6Wnt1N5uct89owznHNzT9hmfB07BrRxY622bKlXXt5m+Xxl2rw5oK++6qiSkiSzrg0NCcrKooEkaW/x8vtdRlFjTSEbgHAIr21yyD1N+tjChc48IV8vvug1nozRowPGO/Pxxy4VFTlGdEzrNJGkiWJDA3noq423ZfDgdkpMzDJq0ZtvOqWcr7iCHh8OyUKpgDBCME46iQ71TvUv1oUqWs8/79Wf/tSgk092ChLYwV7hb0KBYV3z8n7w3vAeSA7qEoSQ+4FrIb3rppuC5v61ewrxclQ5x2/EoE/QvfdWaOrUHE2aFFRKSsK28z7xhFuffSY9//x6c2/bKH6kzyGy8zWAeV8qD5FpSwA+0pb2R5C+va8NSAfPcdQonresX9NO4zzrzW9iDL9vSf/mK7Hd3f9bX0tUWST9iHmhOu1LlQzSeeqpp5rS7uPHj9chhxzy31qG6HmjK/BvKxAlINEb4n92BQoKCkx1Gr7oUUF2VLFqdxbBNlPakWR9++0/EBDmYMlQ79695fHkGu8D4IuUEYBOSclnOuig/H8ztltA9sc/ekwaD9FhTMtOmVnH5EuuPcQjshEh1wRJqqpKUkxMXwOoGAD56dPrtHx5ubp0qdagQTnq2jXRpKQEg0StQwaEXn11nP7wh4CJJNObYuZMGu/5jVLBmg4eHKPzzguZCDqpYAA61AdUCKLTo0d7TMM8mgliWgbgA8R5v808WLAAkuJXIFCriop6JSRUKju7SG53SMuWpSkYTFLnzh4FgwC2BB15ZJyys92GeBHtZv3wqVg/DKCVqDVkBIAMIEZpgJC43VT2WqSkpHQ1NvZTcbHPAF2qfgHGIQDsAdcBlsEjAiBFoSDdh/UFkLIfKBy247YtIwwBYa0gKPg8pk930pAAu0Th8bXQywMCglGeNCw+S5Q/MtKOcuOoOk6XevwXQ4aQdrJIq1eXq7DwAFVXtzPeE4A2RMEpF/tDBS7KD3NePg85Ouggq64ENH58g6ZPB1TXqbbWr/bty9SnT7mSk+mNkaxgMF2FhW0UE5Og3NxYgVesisBaot5AsvCXxMbGGE8HqtXvf+8z9yTpZBAXiNDatW6TqgVwnz9/npYsocxwX0N2mDtpYKS9QZwuvNBn1vTkk4NmD1AiuN+51+3gPlu8mEpa0hNP+PTqqw3GA8KwFcIgFdxjkCJIiO3jwXtQriAgzI99gABBri66yKenn/ab//O7xL6hAtqKa1Soo0EfaZuLFw/UCy/EauLEBjNHO+65x6MVK1x67TX/9/NpNCWAIwkJ/470OURG7i0paa0AiZ0XQQ/KkKO64nsjdam1z7E7z8+WfoY1JG2JdQO8b88zwesQlKalam26HMpIpNl9X6XLUSWNAiMYzSFP+7JQAYrHKaecYpQ6/B98B0ZHdAX2lxWIEpD9ZSei82jVFaAEL1WqaAbGQ5emgbbGfWudiIgWOct0Q9/eQAG5++6Q+fKHDCG/Y7i1X6IAaduJHGIxZ86/G9sB0UTSJ0xwov1Ll7r00ktBA1wB16TrULyG1Bmi8wBcq34wJ0jS2rUJCgYBfQC9Rs2aVaL4+GXq0SNBEyYM1Lx5bh1xBAQmpNzckL7+2q1x47x6//0GQ278fsgOpUaLFQqlKD8/T7m5HhNNfvttj+m1gZ8BwDtqVNCk8lx7rVe9e4d13XVBQwAAjcyTawRQo1IwT5tKxWcB5VTvOvjgkOkuPmdOg5YsCaiqqk51dfXKyqpWly5blZYWb4Cy252m+vpUbdqUbKoXAVo5Ph4NCAdgGBBfUxM2HdnT0grUq1cHpab2MNdMBTBSkJgbqVyQC1KdIDOoN1RboooU0XebWsb6cmzHZO4Y/gHnKCFckwXqtlwsQNnjcUoKQ8wgYdYMDdiFAAGW7WvsGR4RKkmx37xeVoZfZrkOPLBI/fr10Zw57TRlCr4axxgP8MYHYf0rVPZascJRxVAoWFvS42ypXBQbQDj3HmpSt24BZWY6qtSWLdXfV+BClaMTc8j0yejd22Pu2ZUrM/TVV4lG1eHYEBzW7ZRTHP/O+PExxgsC2aWoAOuKMtDYGNCDD87V4MF9VFiIHwj1x6kOBlmEDHC93Oc33ug1//7Vr0Lmunide8pRu5y0Ogb3y4MPevXkkwGThsW6cj9xboikvZ9IA7Mme3y3pFpBdLhnuV/YcwoO3HOPVw8+6DeKl9PYEs8UqWErRTCDHg34vVAOUBLvv9+rSZMatvVAYU7XX+94WZ5+2ikb3HRYn0MkKSGSb9OKiIxHkhLuc1K6dpcw8By0RTd4DrazC9FaD8G9fBzWibQlQDtpS6Ru7sqAfDUlJax30/4ZkWveGum5do6RlbpI1d2XqhPfN5TY5R6iZDwFV6IjugL70wpECcj+tBvRubTqCpBzS6SeL28ICACCCGBrDaKKnIMOrtsbt9/u0rnnLtLatWtNuUi+hHYkv+NV4X2kSDCI8tN3gK7qeBQgGaNGOWCPNCRAJcAeFYC/nVK6P8wGxWXVKsqHHqTUVL9WrlyloqJ6HX10mg4/PM98DpBMtB7DMaAYgkBOvFPKNKiZM5dp8eKtRrHBLJ+b6wA8wDuReuYAmAOwv/KKxygK2dlhEyEHQOblhbVmjVPliqg9kWnAMnn9kCgAJQCdnwNYeQ2/A+oOn6OTOApFmzb0E6jclnpRVUXFolgVF8crEEhWTg7kjgZ4iaqsTNHixV6FQvUqLFyt0tKwjj8+W0OGZJpUHtQNlCeAKEAVdQNVBrCOgZ8UnEgFBK8H70FlACwDUvG18D7mjrcjEhsBQlEyaFwHmOW7/4eeKRAApxysrcgFOSTViYF6QsM+h0jWau3aInXoENT557dX586JZr9I4WL+KErsF+WBrdmac9vr45oA4JH1Frh+QDgki9cpemM9Gs7auEzENC6uxihe8fFVyssrUkNDtZYuTdfs2e2Uno4yFKvS0iQNGxajM87wGnDFXpICBWmmyAG+ppNPXqoOHeL11FPdTZraTTcFzLm5byiMAPmyRIr7kGsjde6rr6ie1qgxYwI6/nhHzeGe516jIAGkkKpbd9zh0w03BIyPhfuR3xlbcQzfDvcT62wH6hbeHPbFadjpvHLVVV7z/2OOCRkPCI08GxqWqrHR6VDdVDmYPNllyNInnzj9QOy47DKv+T/zbsmAlJAu2tR8zc8YVO5rmr4FEN8ZKUE5ALxDblqj6EZLrqU132PTllAuUD5aixjsrH8G3xnNpcvtbL0jr509hbRS7v2/UakL5XvkyJHGX4HyYcu6t+b+RI8VXYE9XYEoAdnTFYx+fr9dAaJ/NtI1depUY7wk9am1xrJly0wTsqFDhzZ7SFKurrqqSmedNd9ETvPy8nYKGqgIQpqHLYUIQKeaFdWDli1z6eyzwwbE2V4eADWAFGCfasC2UpKdENJ/SUm9QqFe+vbbQjU24kPIU79+qQYc098DEBcfH9Ztt8UZnwdRcXLvTz21UvPmLdSyZT7FxnZTSgqdu52KUoBdFAYi0gBIOl/TgI7GdHTIxuQ7ebL04YceA2gdP4EDhg85JGSMxQB6ovD4RFBaSA2j8hA+F0Ak1wZYJFKekuKU2iVdyQLGjRshMA0qKkKpqVVMzFZlZZUqI6NWxcUJWr++jZKTtyo2lvLD3XToock6+GCngR9+GOaOD4MUK/gewB0lA5UDggeYpkkj78dnwHUD5FEQAPAoDUTySdlh3SEhVgHhuKyPLWUL8YKAcBxIHilunNepXEa38h/OCwkgwj5/PpHaYqWkxGvo0HYaPNi1zYgOuWGNwmGqejkN9ywRBIRDYlDWGAccQP8NR3FCReCeQrUCbDuVpBwCA0iHWNErg3sC3wzvA8Q7a0LVq1pNmIBCFFBNDQC5XgcfXGpS+chvpyhBSUmmSkqSVVGxWV7ven3xRX/j57noIqePCA0Oe/bEG0LaGyWEnXsBVY97iH1hTtwT9LWhJwlr+9BDfkNsIKq8DnlEBSJ97fTTY3XGGUFddFFomzIFEWc/I4P+kE3uTfbU9oWBaDO4RwcNitWFFwbUvXtACxcWKC6uUqeemqsuXSKMJhG/7RCiyy7z6cMPG/6tMzplpkl7u/nm4G4/biwpscQENQDFlYEi0BwpsRF225md9wHe92W1pd2+4IgP0heJAA9pS5RljWwg2xrHb3qMyP4ZkeqUbWZL0Chyvfn39kggx1q+fLnx+eXn55s/u0Je9vT6KA9/9tlnm2DXxx9/3Go9RvZ0XtHPR1eg6QpECUj0nvifXYFIAvLNN9+YL4zWrDFOdIsvmWHDhv3HGtq837//vbeefJKGfqktWuem8wQo33aby4BXABVRcmuGBkyRi+9Eax2wFVnxhxNOmYJ6Ua3KykYlJSUag3unTrGGfMyfT2SckrTSvffG6uyzgybfHvPw+vWVGj++RsnJMTrqqEzl5flMtB2wjEqA0gI4fecdl15+2WNIEX4QwKCNpkMuUA4A1KQqoZhMn+42wDwUcnwvqCOHHRY2qS4QGcrskiYDsKMcL4oIXgmAMyoB57YVoWzfB8ArIBJAfsABIeXk0CujUN9+61dtbbwaG0Py+Ugvq1Z+PsA/RQkJVN1K09q1mFkxTDteDAQyzgHJ4PgAco4NuYOAMOx5mRNReKpVkSZ0xBFhQ0R4vzXJO+V7nWsH5LNHkCpUAvaONQD4c2zbMM/J116l2bMblJDQTgce2NYoKLyHY9s+LxyT/zNf0s7Ye45NGhPeGF7jHoH84BGhazj3CmlKpLrh2+BY+HWoWgXh4JoghOwtWJf0M+YFKWRwLZCr5cud93bpElbnzvTLcIzXxcU1JqVtyxZkOIco9O/vU1ZWgh56qKM+/zxebdqEjUkdjwXqzW9/GzImeu6T6dNdxk+EBwPFg1+bESPCxixOyhPnO+88pwIW9wbrwvxQRUaO9Jnfk2uuCRgywfVEqoGoVZAz1p25s9+siW3QyNp89JHjXbrxxtmqqXErL6+bjjoq7t8Ujqa/yCiUo0bF6Z136s19QkCA8zOfk08OmaahrTV4pjVN3yLQwbAVoQDLqAdWOdiX1Zb29DoB76jFK1asMFF7Akb7Mm0pcv7NKVPc49sjgTZdjiIjEChUbIJO+2ow348++kgXXHCBjjrqKI0dO9aQpuiIrsD+ugJRArK/7kx0Xnu8ApEEhK6vfJGRR9xaA4mdL8oTTjhh2yFRXFBGbMrVu+8O0H33/WCi3dm5maeNWvJeKjnR+wCQe+WVIZOCZXPmI48FeAO4E+WmlCt/l5cH9Y9/LDZVstq3b6PcXL7QUSxC+u47pxws/oxnnvGZ3g3k4/ftG9LixRtVW1usI46IU2NjLz37bKwBciNHBg1wtYD017/2GYB73XUBA1QxYEMiIhpGG6AH4ANUEtEG9JK+RboSQJiSr6RuEc0GQBPpHjEiaICrA+QcPwS9LgCXROz5GxKCQkG0HCAKkOe13r0DqqtboE2byhQM9pLbnWsIFapIWlq5amu3bgNwdXWknCUZIpKWFqe+fT2m/wlVw+bP95jjE2En4g5YJZWH64ToYLAGIAOUAb+AfK4dgggZZG2tusJ1o1BBzmw0HlM/0X0+C0lhTVk30mbI2V+/PqDGRtL1MozqAeGzKV6oLxzfKVXrEAjmxrpCGt5/n0pWLtNsEj8E9wUeDdLHiPzj/wDQo75AWEhvgxzZ46O28XlbipbPWV8R80V9oToYe0vfFUiXNWMvWFCjDz9cp5QUPDttTHnk9u1LlZlZqqoq+n9k67PPumjTpoTvFRm3Tj2VdD2XKfOMKgRBZc25Nu4H0vgssabE76OPegxhvfzyoEkfY/7sP9d+1llOd/irrgqa+5H7xJIQqzxxv1gyHal4sTaff16hv/wlYBSca67xKicHcu28f0eDtLiRI+P0zDP1Skx0FEvOe8MNPv3mNwGdc872m5Hu7Jmws9dJk7QqCV4zCIodTStCQb5RqvalEXpn87evRyoH+BXw7O1L5aCl8ySlrWkFLksC7TFQsfHbQAD2xXqzdnQ6p8cGpvN//OMfxjsUHdEV2J9XIEpA9ufdic5tj1aAL2ZbBhMvBF8chx566B4dM/LDGAwx+p144onmixLwyHkAAES/yBm/4w6PMaG3dJCzzbzphs646y63AajkwpOyQkTYpozYYwLuHUO0U1UIUJibW6XJkxdr0aI4JScHNXToIaasa/v2YQ0cGDQKyH33xRp14dprA99Hm/F9kFZGZaRcDR+eodRUPCgO4J0wAeO2U0Vr9my3yXHH/AtQBfwBSEkDAqQzR9usDyAPCAakolYAWMFIqAQcj9QsiBAgEzD9wQduQzo4JulXAMzTTw8ZkM2xICAcg/MyN5QARlJSrRoa5qqxsUE+38Hy+zPMMeiFQaScaLv1QjQ0hE2PkqVL/aqr43N1SkvbrLy8KoXDLhUWtjeG+y5dfAqHqSKWIPpzQe5sAQCi9QSfIR6AeQiBJSBcL9F2iCHAntQyq2DQfBEVBTXJ73dIGeqJtMWQj4YGn1yu/v/P3nmAWVVdb//ltunMDDBDh6FXKxZULAghYCW2oLFgjLFiLESNij1FI0ZNQc1nQTEaJYktCmJDjYgUFaQISGdgYGAK02+Z7/nt44bDZWbunWGk+L/7eeYZmHvvOfusve85613rfddSSUmasRl25bM44wwABJ8nK4GTThYGkGAj+WgTPv7YAXTsh5SUFhoxwskwMQBOzI0sD441trS9YTgX6wIA4docXZHTv4TB3AF9AC+Oz/n5PBQwsn7vvLNKGzbk6NhjuyglJWCuEeDVq1fIZEc++qhGCxcCfKr0ySettHEjTpJHQ4Zs1ZAhVZo3r43y8gBUfrVu7VyXpdwBEKCWQSF7+22v0eAATuhDAiXRKQ/cQlOmeI3G44YbQmavWG0M1Cu0MYBBAsNQ/HjNam/IZs6bt1Ll5Z00aVI/A9ouvjhi9p8dAG6rHwGUurU1AP3hw5NMhoZrZu+xtjffHDC9TsjkfF8DB5RgCIEPou44727xNfckytTyPu5V7opQVoC9L0EJgRvupewh6KroJg6kYe/92BjwYZsluu0dTeFqLloZ56Cx3/jx43XhhReKZoJ7s8zvgbROibnuXxZIAJD9az0Ss2lGC7gBCA83HsINCcYbe2qijQCOYcOGqaioyJRa5CFOlassvHBJ993n1c03h3ehgrjPQ5Urun0T6cexLyxcoOrlvGYJAAAgAElEQVTqCg0ePNjQYx5+mKZwLfTIIyHjrEcPItJE48mQQMXhM8XFW+XzLVBycqo2b+6ogoJC011940anl8fBB4d1ySXJhiZClSqOu379di1Zsl6BACL0rurTJ8U4nQidoSFBhyKTQfQZZw9dAeVVcRBxaIn2A4AcwOBoEnDAcGaZP9F5shw4xDh8OK/oIHCeceSI1DN/2zgOcAENaO5c6bXXfEb/ggOKM3/yyWHTMwKKDyJ6nEKPZ6tqaxcoKytJubmHadmyVAOAmDvOOnOiPCwUGRxKQARz4z0IhnFO0cH061eqYLBUc+YEtWwZXeDLTYWt7OwqHXRQWO3aOaU8w+FMLVmSofx833fN/hwqD1QowBfrQVQc2+CkuqPoXDdONPbn+plD9+6b1abNArVtm6Hc3EO0aFGSyewAEDgWGSGyIAA8QBhZAgv60GiwVrZhHudEzJ2f73Q7B7zgiNsoPo6y1VIAbC3tjL0FbQ7xuFP1y6lK1qdPxFCkiOgDKHDiAXOsIU4/Tnxm5gqtXLlSyckdFYn0U0EBhQ92VpmymR/mTvaHbATX1717qTnf009nGqA1btwcFRSk64svctWpU1BnnlmqI47wqXXrltq6NUMffeQ3FC/sgfYGIEImadw4QHbEUNsAZs8+6zMd3ymmwJowAEsAFLQ7tscJFKz27cOGs79u3Tp16JCnnJyeBmCNHp2k99+vNiCMwT6zTQxZM1tBy9qdPfvhhy10440BMx/6vkA1JBN11llJmjgxqCFDmh+EEGTh/rZ58+YGaT+8D1ASHb13l6mNdpL3hiPrrtRFnyaaxR5IA60OZYKhZqG3sfd+a293WWBsb+0NJTja3o0V2gPc/vjHP+ree+/Vtddeq0ceeWS/zG4dSOuZmOves0ACgOw9WyfOtJctwAPA1tyPJRhvytS2bNliytxSaYRsCA9OHqDuh/Zjj3k1ZkzY0EGiBw41mQWyEdB06FlQW7tCLVtu0nHHHadHHvEaJwvn+cc/rttxwWkDgJBB6NQprAUL1ik/n2hyio49trc++miL5szJ14ABlP6NGCf/kktSdNZZYV1/PVz6Wn3zzWrNm5evqqp26tYtT23a+EymgkgvdCOi+JMm+QxF6B//qDHlSQFOL73k1YIFHkOHgToDXQnHjQgzOhUi11YMbQEIrwEywGc4gmRliLTjHENDcndpx14401B+ACjQnAAgM2d69NprXpP5cBzBMvXvv1pnnhnSSSf11vr1CN+dJoA4zAAZABEOtRV7Qz0CgOBgU8UKhxunFnBE1oEMBtdeXAxtqULZ2SVKTi4yIBYnDvH31q2Uk22jQCBNXbsGNGhQsrKz01Vail0cgTrz5foAAUTFmS82oT8KTjBrsnx5obzeLRo1KqATT8wzzQXJclBNjD0BCMTJx26ARfaN40g7NB/qKrij9FZkz7WzZqwP2hoG68Z1AwAQoVOqF0eaYzNXurv/61+I9gFUzv5k7ai8xnoCXjg3c2MtnSIB3yglZc2OMteAOTQo7E0ybu7WA4AmwBd7ymnO6PS/YTzwgFcPPBBQy5Yh/fa3G7ViRa0+/TRFHTsW6fTTV6iwMEVLl3aQ15uqrCy/KipS1aFDQEOHOvsTm556asgI5hmUKqbT+Ycf7uzXAUgAvLG3AUA9egS1fv0C02SwQ4f+Ki/vaLJzgKvNmz3muJTaZdgeIuwXgCDAkDWF5sWw2SP2zR/+4Nepp4Y1alTYgHTG0KFJeuqpGgNGm2vYBn04tk1x3nFgidpH60rcZWqjywI31klu6Fpx2sn68pvADdmDA2lAvQJ8YC/ovdCtGhrW3tEgsL6GlQAUW8kx+rgc64477tCjjz6qCRMm6O67795nepkDac0Sc91/LJAAIPvPWiRm0swWcAMQGjJBT6hLMN7U09oMCJSG3r17m+aB0ZzlyZM9Ou44Rx8QPaDA2Eg4AMUR365Vbu4anXDCEN1+u9dkRuh6Xlf2wx7PaVxXrcWL16impkpHHtlWP/pRrnEQ167doFmzlqlt244qK8vUrbd2NJFYqlDhvMyZs1hffkmp1a6Gs0y0l2g59GGAzeOP+wxNa+xYuqUjKN7ZU4Hzk4F55BGfZs5ErF5rGg6SCcHpAuwwN6LkRI9xcMkSWKE2n8eBxSnEacaZhhpjNSTYB2eRzAlZBegsfJb3kHGZNy+s6uplmjUrWV99lafa2iQDHnBoyfLgKAJy+JulEAGSbCaBLADgD2faCpotXcdeG44yTjtzxzasAw/+5cvLtWBBjdavrzEVuNLSig19Kz09rKqqVlq3Lldt2yYZ8fXWrWlq27aFKe/LteHITp/u0dKlRMjz5fOVqXfvXJ16apYRqeP8MzeKA0DRcsTxlCF2VhwHH20QDjDaDDRBFpxYRxn7AHywK3bDUQb0AazQ3nBN7DlszPkAXvh+XO+rr9LJ3FKsnAj+mWc6OgzWG7ofdtu+HUH0EuXkFGrQoP6mfDSgiszDihUOwMrLI+O2E2SQQWBPMG/bA4W5Wb8TcHbrrT7NnevTwIEhjRtH8YCI/vvfiAoKQmrfnkZ+laZ6G8fv1atEgweXm8xUixYtdfvtXbVyZUAXXIDzHzE0q9/+1q933qk25wTYsafI6GVlQb9bqvbti3Tssf1M80X2qm3wCEB75RWfqQI2YULIvMbnyf7YdWTuNsOC7aGoYR8A8113+U0n+FtucSphEST48Y93itWbet+xn8P5xXkng0DkPd5CF7HOG12m1oITt5McDUqa0tUdIM/8Gcw/lvMea957+3VABOADKhXgo6maCzIirGU0KLEVuAB8tpM79oJG3LNnT91www169tlnNXHiRPPv/VEvs7fXJHG+A8sCCQByYK1XYraNsIAbgAA+yIKMGDGiEUeo/61kP+Drk2FpqMM6zhxRd8szdx8R58/2NaA8qyPU3qDMzGXasuVk48gDXBrijpMhWLq0ULNnrzFC3sMP760+fdJM5BxHAm4y3PBXXknXCy/k6aKLFqtDh2r17Ekvke3Kz09VdXUfdevWyjjX0KVwqnD6r7jCr969I7rpJkSu0JycjtrR2RxbchbHkpKpOMS/+lXIRMwBADizULM6dnQcUXejRJxIPodzhiOMHfg8zi7HRW/AZ3CkyQSgAyFT8uWXZXr77Q1KTg4qL6+bvN4MA5zI3BAJf+YZr+m1AbghE0KlrZNOwhl2HEboOGQIsLnXi7CefiUOwLADZ5JoNh27AXPQ0lkP3kMWAGeaueDMFxQAMsuUlVWktWvLjaNaWBhUUlJIlZV+Y+/DD3dKp1Kqdv58r2bMKFBFhU/9+7fToYcmm/kDrrhWQApCb/6NfoUoO+fFXrZRIa+xR9q1i2jkyIihUjGgeOEsMzeun2i/rcBFlJ7sENduRejsT14HAHJMsjfYDnBoAZutgsXxySh9+WW5lixZrVatgjr99B5q186J/PJZOqWzLzk+a0qndKqrMX/mbjvIA5DIwACebAaHebPu9Am55x6/uT7W7Yknagy98E9/8hua2GGHhdW3b4X69Nkmj8dpoogDV1Tk09KlWfr3v/uqqiqg66/fqi5dknXrra31+9/X6NtvnR4jLVtWKhhcZfYZZXb79k0xwIz5uJsYUh3s7LOT9Ne/Vpv9QUaI/eymYEX39gPkYTv2+QUXBEz2Ej0KA+A2enSy3nyzapeyvY29KRUXFxv6J9lWnPfGNuhr7PnqcpLdXd0b2zvDzp/PMf8DqVIXtoNyi/0BHYCP5swKcXzbsNINSj799FPdfPPNZunQ8ABahg8frosvvtjMAd3hvtTxNHZPJd6fsEACgCT2wA/WAjjgNoq0YcMGo9EAgOxJWUcn+r1cq1atMvXVoW4cccQRpuN6XeP99x2PFgF59LAlTy0Fiyh8cvJ6hUKL9dZbo4yTY7UfRItxPslM2I7WmzdH9O6767Vs2Ta1apWpwYO76JBDvAoEcNjDO3qgTJgAl92rceOq5POVa/36IqWmbjT8+/x8Gtu1VMeOVUpNTdPGja319ts5CgR8+sMfQgaQ4ATajto47/b89noAD4AI5ggDgejy9Ole48wOGkQJXKdZn1trYD+LM4szj3NqHWwrHKYEMa8BKoi8A2YAINjoyy+Xadu2tsrK6qNAwG/oU8zNXfgF++LEA0hmzvQa55NzkM0gqk/JXiLv/I1zALwsOGLugEPbBwMbsD446nwG8MHcyOgAZnidufF/1g0AsXYtHdir5PHQn2SrIpHiHUJgMltr1mTJ48lRTk66Bg0KqHPnNLM3OSfXDnjguqHhkcHB0eVv06dzbqcTOvOEKkTzPLvHAG1E+YnU835bJcs6+TjyROkBAGSHACpWx8C6ADYRoeNEkwWw4ITX+OwHHxRpwYKNys72Kze3u/r39xlgx3jvvRZmr3XtGvkuS+DREUdEjKCbrIEV0HNc6G/onrAbwJPBmmE7qHmsC2Dk0UcDZk9jg9tvrzH2mTbNZ6hSP/952AAURjAY0aef1mjZsmolJW3X8uW1evXVXPn9EZ1yyko9//xAnXnmFrPGlZWlysjwacCATjr2WK/RjTA37MI6s4ehpjE37HD66Un67LNqc/0AYdvEMFZjcdbvnHNokFmrO+90GhNStvfCC5MMtcvqSxpzE0aojeaDLAS0pb2h06hrfnV1dQeUuHtnMEd3tgSgQfCGe/G+nn9jbO5+L/NfsGCByThh/+YSk8czH4Jov/nNb0yTQ7QmzAXtFQMQetVVV+mhhx6K51CJ9yQssM8tkAAg+3wJEhP4vizgBiA8tElfQ8FqarQKnjJRL5p8QbmiTj1Nn3gIQV+qa+DEQpUZPbpuDQfOK0JqK0KvrV2nf/xji2prj9Ahh8j0b+B1orZE2omQo2cIBKr0738v16JFCJxzlJXVTtXVLUxjtw4dHPBRW9tCY8YkG30GgvEWLSIqKlql5cu3q3PnVvrJTzpq27aI5s2rMs38pk1L1sKFaRozZrFOPnmDebBGIq3k9VKmNk1duqSZcrVkQuxwHG2HxkSmgbmhWUFjQCQcvQagAOoW0eToTBDABccPBxCHE+qRpbWQgcCRRuvBa3RX9/u/UVnZWtPVvlu3viotpVO6A3yoEGbpWziIHJu5WX0NDfuI9mPPiRP9RqiN3XESe/WK6KqrQqZhH4NjEhEHWBARJ6KPfbkGnGWoSswNZxR6GM49DjJRfztwVhG7A3hw8D2eiOgRAC2uuLiDiopaqri4Rh5Pmdq1K1fHjhWGhrJlS67y81upXz8aQNJQ0WMcYbIvzBVQ++GHXuMo22pjVNGyWQayB1w7GhTAIkDE9gmxc+M9XBu9OMhoWbsBAABWrCv/BqCwNg7NqFazZq3WBx+UqnPnTA0YkGeE7oBLS2uDtkczQQsmI5EWGjo0YgTiDGxiNT1kxcgqcF22sht2t71AmDuAjp9f/Spg9hRggDlffrmTYVu1yqGLUQ0LEMb3jYwV1+ysGddWobvuStX27WFt3erT8cevM3NJS6OIQpmxbadOgL9MbdqUqe3bfeZ19oul5E2e7DWgGg1UU8ZFFwUMoIH+yJgzx6Orr/brgw+qY5b4tefD4adSF4J56G5kXve3iLftnRGtKbFd3QHY3Jtwlim1ixMfT1f3ptj8+/hMfn6+Fi9ebAJOaG72pv157pxzzjnmGTR16lSNHDnS0K5sNobnG5UXzz777O/j0hPHTFig2S2QACDNbtLEAfcXC7gBCI255syZY7qWN4WuYKNePHAOOeQQI5bk+O+88455EOEQ1zWg8HzySQuNHRtf9RsaWF1zTUQdO3bWY49FTDQaygxOOLQqnKvWrYsUiczTypUt5fP118EHp6mystbw4g85xOHM45ifdlqyLrkkpPPPD5vo7bx56+T3lykzs7sOOijTgAEczzfe8OiOO/ymmeC998Kzr9b27Q6thZ8tW8q0erXPUImSkz3q1curzp1TJWVq1apsVVQETJQeqg/OIpQaaDZQgXCSydw8/7zPZEJuvjm0o6Ef9qKyFg4v78FpxRHFkec4NlLPNaelVWnbtq/l8xWZMp3W3mRFABk4mjikaCUAaXyW8xNlJ9qOyBynFIEyTjyOKjZFH4FjCwhavNhr5u04n1wHfVccOhjZHTQtOKsAChxhovNw/VkXq02xewCwyOuAKEZ2dlA1NV+poqJI7dr106ZNnQz4wSldu5bMTbl69ixSdXWJFi8OavFiv1JTa0xJYJ8vzYDRvn0Bky1VUZGud9/1mUwA0XyyN6ylbWSILcmgIBgH/LkrZDEX/s6+JLtFZguABcUL20dXB8O+rO2hhwb17bdfa+XKYtXU9FdSUjuztvTrwFZWWA0YmD8fIOkI2ZnbySdHDDhk8DeyDARtncyTk4FhH5LN4btCxopiBjQsTEpqoWOOcXqY0PSSfQqdbskSGi06TQfPOAOxukfTpnlNVgi6G4CUDA/r52TNInr00Y3661/batu2NJ1zTpVGjkS3s1UtWhSbfU7WkAaKBQXZ8vsz1LZtsvr3D6hbt3QTtDj77IB++tOQzjsvvu9y9P3gyiv95vqfeMIBIQA1rmfmTMpGN3zXxLEn+k2lLrRmaAAOJM4/wRsyx+jmoC3Z7AlXXVdXdyhG+9v1Af5Yg33RIJEKZ6NHjzY6xtdff900GkyMhAUOdAskAMiBvoKJ+ddrAR5yCK0ZRI9mzZqlY445plFiTUAGHc9JcxP1opO6O4Myffp04xATeaprECl/8UWvrrsuvl4g771XpCeeKNN553XQOefgEDtCdRxJHN358wtUWrpGxxxDKdJDjOCWSC/zbNs2bErNrl/v1dixNEWrMc7bpk0FmjFjlUpKMkxn5zZtko3TSLR+7NiAESY//TS9P3bVQFiH0dE7hBQMVqqkpFIZGSVq23ajtm/HNllKSfEoNzdJFRWZys1N1gknJCsQSNql6zSOIZkR6DnoD847L2yoOSwPlCH0MDjDtpkh/7eR8srK7dq+fam6d6/UoEEH7Vg/KDgAB4CEpc1wXTicjsDfI6/XoUwBMsgEEaknqm/LwQJuABSIv9GeOCJzh7b13HNeI8Dn/wjBqRw2dqxDKbMdtZ2O2w69zHaAx25cI9cFdaiysspUGuvSpUQ//nFPSa3MmnJcsimAMITPgCPWGXCzaBHApFJVVZVKSSlRmzabVVOz3WwxHLPq6lYqKMhRUlKaevdO0qGHpsjv95jXAT4ADECTU83KoZdx3RZ8kVFzsgROaWQcfFiEADfmRkYLcITdMjKq5PV+oXC43IDtsrJck0Vi7QAWZL1srw7OD+1t9WpnLmSW3M2g2c/Q1wBuZDiwJeCNOZKVefddj1l3OzdACdmdY4+FFuVkpeiIDrCkYeV//+sztnvkkRrTlJDKVzQrhNp0+uk0KkR8X2P0WsXFpUpOPlQffZSrP/4xoD59wnrvvRoDVrhXFBdXaNasKn37bdjoo7ZurVF2NsCwRBkZZKMydNllh+vll7eoe/d0U52osePmm/2GSvjCC859iRLEjz7qZEKi+/vYYwOMoCwRBKEzOFX3DqTBvYnMHzRYgJMt1mEb+lmdAyAQzRrDdnV307cAJXtCn22qzdgbFDGBdrsvwB+g84wzzjCZjrfffluDaEiUGAkL/AAskAAgP4BFTFxC3RZwAxBKTX788cemwV9rN+G9AeMRtXMcl2L16tXLUAaio3LvvfeeeSjR+KuugZNGedEJE+IDINddF9SaNZs1ZUqWMjLSDLggA7JpU0hbtqzUpk2VOuKIbJ1xRifjXBL9Lywkgkx1qlq9/77PCHXfeKNaOTkRLVy4QrNnb1NSEn0V8tShg8eUV6W6FcCIJm6nnlp/RNdSkXBUiSZbKhIiYJ+v2mRWVq6sViRSrpISzllitCUpKcny+bKMo5ySkq727VPVubN/BzXn5Ze9mj3b6daNk4pjDACyFbK4ZuhYXu8mrVixUSkpGUYs3LWrf4eZcWbRKqAjsIJ3gAIgA9sAAGwpWpw7wAnZAEAGr6NdwdHm/7avhT04IIAsAo4yJXexw+ef+8yceQ3gAR2L0r9QvNwdtTmGpZZlZhYa8LptWyudemonHXJIwFCbEDMzN0sfIwtgARCf5+9cH/sHuwAWcURx1jZuLNOXXwa1YUPQlC/Fwc7LK1NOTopSU1tq5cpcVVWlq2fPpO86ijvUMcCdLdtMtgrABIgj22Crm7EOUMvIrji+4HZVVi5Sly6Ujz3UUMQcPY4zR8omk3Gyg+NxbWSceJ/tlWE1HraSFNkkAAhACXoXuh96tgAg0ESRHSK7ArCkCAMaE5s9Yc8j4n/qKa9+9rOwRo8OmY7j9Ny4++4aUyyAcsLvvOMzWaTDDpujjIwKde9+mNavzzIAgGPdeSelfOlgHtGDD2JLJzOGjQBjBA9CoWr16lUkyckGQjF78sn+evDBjw0AcTvI/Ju/cWyAE1mduqrX/fa3dIT36D//gX4nPfusVy++6NPbb+8OQqAuQbnh/gX4y7GGPEBu+uxZ9BJkoPv372+yBw0N9CPscbf4mmtncO+liIO7d8b33WWcZ8iSJUsMeOIZwL1+bw6yRoAP5kG2nWBXYiQs8EOxQAKA/FBWMnEddVrAco/5jV6Diivwp2ONwsJC8+DkoQflCsF5XWPmzJlG/0EFkvrGnXd64+qGjuN1333Qfr7W+PHdjHPDWLiwVB9+uNI4fAcfnKejjsoytBgeSjzg+b19u0e//nXA0Fuee65GrVtX6euvF+qrr9CC9FL79m2Mg4WD+Pjjfh1/PA2s6HzesCXcYmycSXQDZGKsGBsnDUeaY/P3jh0rFYnspG+VlJRq0yaqGQWUnJykvLyAundPMde2dm2mpk5N1tKlDjgYPtzpdo6jPHs2tJoNSkrKV3Z2B6Wlddbhhzs0KDuI1pMBsTQo5oYjTzQfx48KVzi8OML4PUTZyQLYgYPtUJGc7Asgwm4Nsgg40kTXKYXLMcgi4LRDM6Lh3KxZXgMOOT/HPfHEiH72s5ChoHHud9/dqHXrCpWdnaUePTrroIMcp59BtB8aEUAG8IMOwi3uh7pFloY5Aj6wj61zwJwBV44IPaL8fCo0FSk7e6uKikr15ZcBFRYmKyen2nRzz8hI0ZFHepWXl26q53zzjddcN2vL+d3UMubGOalmtXr1Vm3b9q0OPbSFBg1yMn98Btvk5+NkOyWCAU6WYmV7ZVAUAHoYmRbAhS1Vix6KY5N14XVsx+scA7BFZok1dZpW0sOkVsOGOU0QGawDGRTAGX/7f//PpzVrPJoypdoAynHjAoamePHFYR16aJE2b16kjz/uquzs9ho1ymMyY2hWWC++KzQsxAZUv6Ja1SmnhEzWh3W3+h/2k903fNduvhnKYI2uuWbNjupbVngdDKaqtLSNqcoGIBwwIEVt2iTtFrh47DGf3nzTq2nTHNDxpz/5DPj69793akxwvG2PCe5b9n4Q6961v7xue5RQbpfMcX2FOmLNl0qD+6KrO5kbMk/QnwBP9dFsY82/qa9zbsAHYnMy7d8n+Jk7d66mTJmi999/32R6uE+gMULwTqWteAaFEajS9cknn5i3DxkyRA8++KAGDhy428cb8954zp14z4FpgQQAOTDXLTHrOC1gAUg8eg0OiYMB5YqUe12Uq+jT/u9//zN6EB5Q9Y0JE7wGWMQad9/t1fr1QZ111js65pijzYMH3jH0hUAgS/36HaxWraDa7AQezBe9x5lnJhln8MIL6bq+XcHgQlMiNRg8XNXVGUYHQcSXTMbTT1eb3gzxjobK0XIM68jiEEZHfKHqfPVVjfLzq1RRAZ2oWDk5m5WeXqVly7JUWpqpnj1xiNvos8+yNHhwC11++XbNnLlM335LB+w8tWyZaXQKAAB3tJ1zAzComMQccILRgEC5AhTZHh90+6YDOo6+e+DskmWxPSl4nUg757CVpAAGRMShSdkSwIAtPoszzWvYFpoR0fPXX/d918+lUmlpZTryyBYaOTJzF60DIJDsihXXk7nC0bYCdgAA+hUcYYAmawY4whFmrgAAnHgrkMbpZ25QoRhr1uA4VWrTpirTRDEtbZuhcBGRh8KSnNzSCN3LynCSU3X44QHl5DhI1HHwEYIDnrapU6csDRnSQf36OZki9CMLFzpNBsk8kUlBP8La2PUAQHBNtms7AIPMFgOQYXu7sGaAAT5v+7eRkbCZJ+hoZG6gyNnBXuR1xP8MzsNxfvObgI45JmxK/vKdmDiRuYV12WUbNH58e6NfwulnbgBd1pk15dxPPukzNqZhI5k5RPM0NOS82NhdXwLgCGi68MKAHnigRied5AQCyEQVFpZq7tyQVqygwWe5qqrISlIquFLZ2QDBDAMibKbkued8euopp9EhVDTKDrOfJ0+u2SEstmVqm9pjIt7veHO/DyoV4AnwQOasuXqU2HlGdxm3DULdXd2je5U0ploV87bZ76Y0eNxTe3722WdGTA61d9q0afUWOdnT89jPI24nmMY5KekL4HvmmWdMtbW//e1vprpWQ4NMDewCAnXjxo0zb33ssccMe+Dzzz832SM7GvPe5rq+xHH2TwskAMj+uS6JWTWTBYjC2YdSLL0GTgRZD0rrcsPs3r17TCEkDwpE7UT46huxAAjRXBzmBx/0auTIKnXu/K55aCPY5IeHEBkWW0EGMMUP2RkcsVGjkjV0KFQURLT5mjt3m/r39+gnP+mhr7+mh4HPiHTPO49O4RHjrMbJQjMiaug0OM22kSCR+IYaI7rtYMvVEsHHUcTpo1JXu3ZlpvrWwoVkcLaruJhu1TXy+SKaO7ed6YZ9yikeZWZmKzMzTZ06EfHf1cLMDaoQc8NZxdEFhKAVwIGnChSgDCcZ+hhCbSv2JeqNnoD3kAFA7I+uwFKRWA8cXRxm5k1EHPqWzZDACsEuOOIAFsALNuHBjeNClmTVqsP0ySdkenD6nfecdlrYONVE38ko4fO/o7QAACAASURBVPATacchtoDCCsE5Hok3IvuAOzQiOOrWCee6GDjxABi3owydiag+gMXJGtHLZbuJ2K9eXamlS6kIFVIggHaoSr17e5WZ2VKRSLpmzqzQtm1VOuywdgqH2xkQhO0ASIAusj42iwD4IasD7Y1BNonMEeAJKhJN/MhuuJOOACwoXFwftRvcWSlb0hknn7ljM8CLXTfAC+AQW3F8MizsZ/bXL3/p1//+59G1164R1eRKSrro0087G3Bx++1BAyyY+yuveI2jT8aKhoVk3O6912861NOpfMIEv6HaXXttSJddtjNwgE3ZE2Rn2C8PPujXRx9BO3T2JRk5jsFg3WhSGYlA/dqqUKjY2N9q0iidi4M8e3YnPfVUe02fXqZWrZJ1441ouip0wQUzTWCD+8q+KrPb1FuwbdCHuBxntilFP5pybu6JfP+iG/rZru7Mw03fwv512ZY1oqIUGSjuw/Vlv5syx1if4VkFrfeCCy4wmfc333xzr3SHJ5BGOXm3rgkQyfWjPSIL1BCAA8AAlKCrdYYDKe4V64xmadSoUXrllVd2XHpj3hvLXonXD2wLJADIgb1+idnHsIAbgJBexpmvS68BRxnHMRblKvp0pK550EKRaAoAsaVmn33WY5y7CROqVVj4gVq39proIdE3KF48mNyUK+Y5b55Pv/xlQL/7XY2qq8MqLFypqqptkvJ0wgk5pv/DlVcG1KNHxFBSKJOLftU207PzxYnGmYbiBcjAaYQWQrQXAMFr/B8RNxRkt9g61ga0zQQ5Jk4//RVwtqmORLQbrQQONyWCa2pWIWE2+pFt29L16qtcA71ECtS2LT0nUtSzZ7KyshxHedEin5kbDqzTFdvREtgGj8wZRxCHkWg9DrzNMuC8IrbGgYYuhN6ATIkFZ5wXJxWnE0cZChdZCDfwAmRARbJi8pSUzVq0aKE8nlTV1h6mrVtTdmQwsBn2nzrVb6ofAZqwJ449Xdsp/8u6MHDQcZRtBaroDAhzZ25keMhqkN0BYNm5Of1PAKdOVTGcfxx2/g2Y4rpx3Fu1Cpnyy3Ri79x5iyKRbaZ5IoUFamqodOZTRUWWcnKSddxxZElSVVzsMQAA8GNBAVkEbG8HNmPd2X/t20fUu/fOXYLjzprjrAMwACDQ5uzcrfaHjBcgj2NA97PZKz7L+dlP2B0AaTNT69ZF9NxzG41DTyWs3/zGb/YDNrruuoCx2bhxQQMkATgcZ9kyj6EjUmBg4kSvXn7Zp7vuCpq1mjzZZ3rH3HYblbYQUjufgcqHHadO9Roa3VtvObQpN/CFHkdwgAwNlDz2aF0lagGEn32WqWefHagHHvjM7Nff/a6fud7HHkPTkxozCBLrO7g3X7f3USg83BObWvK8ueYcb1d3my1hvkT9bXf5vUl7Y39Q4Wrs2LE66aST9K9//Wufd4e/6aab9PDDD5tMvAUW0WsD6ENXOWbMGE2ePHmXly+55BL985//FJRm9DqNeW9z7YHEcfZfCyQAyP67NomZNYMFeJDYCNhHH31k9B9uvYatcALtipsoEcfGVLdBIMo5SD/XNxrSgODgE61//nmPoY+0b79VXu9C5eWFzTG5abuBB/8mE/LMMz79/e8+IzYPhUr1+uurtXmzTx07dlXHjun629/8RmAN3QpKEs4RDl9W1q7ZC5w4orpWdIyOg87bOMM45ziEVqBtBcOWbhPP8hAR5xpxWB1n2Mkk2IaBTjfvoL75ZrHKyzcbcGjF/hUVNFqs0QsveFVcHNERR2xSv34b1LZtuYqKkrVhQzvDr4drT4WvTp2SdfTRjpMN1YZrwvEDWOGA46jafhfMHUcZChbgg2pVdYEzWx44uvkin3W0CM51lZdvlNe7XAMGpKtTp4H66iun5CpZG4AAtgcAkS0BuCxZ4mg8/vc/r3HW6dniZDmIylMKudbMDTDCmhHhtxkgAJvjxDtaCjtvq+cBXDA35s4c6JsBDZtjOmJ655rdRQW6dduqDRu+lNfrVzjc12TkioqqFIkQmS9Sp07b5fV6TAS5srK1tm7Nktebrm7dkgwotWAE2+OoA544F9kTC5CwueP0OxXJEL+z39hPNotAVop1Y724doAC1DOr/bH7Cefe6Q3jZEh8vip98cWXhn6WljZAr77axlQwe/ZZxPMOOAL0XXWV33R5R1dC3xBsQubrv/+lgSd7pVYzZngN6OCcgKNbbgmYOV15JRkjp2IX3xvW8emnfaai20UXOZkS7AYlkO8egLZ79911S9iefQjwdUo8V+mDDyp1441Zuvvuj5WTE9J99x2uXr2KdcEFq3eL2kPH2t9K1HLtlBBftGiRyRhwH20M5Smee0lzvcd2dY/uVULAxw6yT/xYYMIz4fu0OXNCg3HNNdeYcrv8e3/oDn/++eebniNQqQCVdQ2qSx577LGaNGmSrrzyyl3ewt+uvvpqU4Fy8ODB5ne8722u9U4cZ/+1QAKA7L9rk5hZM1jADUA+/fRTw0VGXMdAH2IrtFAeEue3sQ8ZomWk/Cnv2xQAgvP/l784ZVPPP59SjyXq1q1EJ57Y2TjidYEPmrJBZXrllWpt3LjB1Kb3eFqqbduD9eKLaXrjDUTvTtQ21rBlV6nkhEMEdYboLc4yGgUceRwpHCUcLregONaxeZ7jiOKs08QPZ5HItptyg+3IPLFOZHvcQlX0Bl9+6VS5woGnlwhR8UsuKVFubpHmzoVGhIi3TCUlAbVvX2EoVFCJamuzjJMspSgjw+lV4daP4CiTcXKaQDpOIo5yvNQyC85yc0Nat26lFi2q1rHHZmrkyI7mWq2GA0e7rgwGdrEZCihAOMJoS/7zH49ee81nwAkOPBmEM8+MmI7f1snn2OwX1ouMEtF6dzdxS3sjK8F1WpoSoNJWByNDYrUvPl+B/P6v1b59plmD2lq/2QdkqPA52rYNqqLCKSzAeq1YUaNVq1hTaFsh9e3rUYcOqcZZCwYztWxZuqliBW2NPYNt2U8AJMAPWSuySRwfmhgAg33B4LoBKABmnPy6tD/sWYAf9oDGFg4jvP/SfL59+0HatIlIKz1gavXwwwFD+fvb35yCC9iGDNCrr3q1dKnH0LB+/euQOc6//kU2w2vOSwlnMovDhtV+l0WTLrssYK7ngguCRtPDmqG7GTkyyQQCqFZGhseuK8CRHzvc9DIALQDQqfoWMvehefOCeuyx4/TaayF17Fit009P1kknbdMppzhid6tnw7GP1jfs60wJnbnh9rdv397o4fZFudxY96OGXsfBhnZFNjs3N1cVFRXG5ra4AJmRaPoWAKGxz4u65sA9Hp0FAm6yH3//+9/3C/AGnQoK1mmnnWayMfUNXoNWRfbm9NNP3+Vt/O3MM880IAZ9SWPeuyfrmfjsgWGBBAA5MNYpMcsmWsANQBDDEcmCWwtVgIc+N3/+H29p3uhpcJMmvdxQY6iGNCA4JT/9qUdt225S376bdOih7eTxLNKAAV0MALF6Dyox4axdfHGSjjqqVvfdV2XE6XTmpTpLZWU/jRuXrKOOiujhh2NXt7LXUV/jOahB1mHDYXQLhsmouAdRaRw+GsMRyca5sp3Iob3glAE6oF050Wrn00RM6SqM88QaRHPFoacBQOiYjbaDKDROG92v58716KCDIuraNWKi1j5fuQElXq/TVA7+NnMuKkpVINBS2dlp6taNylAtTSQPXQaZB+aGwwlVBnAVfW31bTvAy+ef12jDhpWqraU3Sk8dc0zGjmpP6Hq4dkAFTjyRdFvFimMCejgGTjiZD5x0mxXiutFRkOH45huPPv0UEOcxDjfaC3q9DBwItcmhKQFwcOKxDQNwgkge4EilKuxAlgGnn8E5ASDFxTSMXK0WLdZo4MB2RveE44jzDxDg2MydbIQVibPWTpWqiOkwXlBQZTIkHTsWqLKyQsXFSVq5Et1OkmnkR5GBjh2TdMIJSQoEnMpi2B2qn5PdcYT/NrtjgSH70jrpbu2P1UvZ8sWZmZu1Zs1Cs3cGDDhMX3+dbMAT4IzsCQUC6Dr+0kuUpw4aTRBz4JqwA9Wn6FlCBgMdFRkMMhQvv+zR/Pk+TZlSpeHDd9LL5s6Vrr/eqQZ2zz1BI0Inm3XNNUmm+hyAlrkBPFgfWx0Mu2M3rp21tvQyBOqbN39h+l+QNSgubq1zzknW889Xmb4mw4cn6Ze/DGrMGCiKNTuag1qdA9kTBqAk2kHeG6CE+yed2aHocL9qShCnibf2ZvuYpY2RbYY2ZnUh9VHm3DqeaJs3NjvF/f2BBx7Q/fffr+uvv14TJ07cL8AbfbMIqnGPJkDUxd3MJ8ryzz//vC6++GJTqWvEiBG7vErp4B//+MfiPRdeeKH5He97m22BEwfaby2QACD77dIkJtYcFiCtTsUUhi1pSWqdaB1UARzfxlCuoufEcagRD2e3vgEAufdempvt/o6XXirVo4/W6uqrl+mgg/qZBmfz539oIok8zHlAlZd7TGM8BKp0Yh49ukLl5fNVXV2hrl376c478wzfHLrVd/q/uE1HlgJnFccLwTWOIc4yombmizMFzx4nHWfROqL2BDaqCzjCQbZdtXGwEeTiRONw2agwfPisrIixP04L14lQkchj9GA+OItkezgeziPFVDgeAGfaNI+hzhDhHjMmvEszPNZ98eIKk5nYtKlGoVCZMjKKlZe3XYGAR5s2tVNhYWv17euTz5eu0tJkIeOBXhPPyM/fqv/+d7VKS9PUtWs3de6cbMTW7og3tuMH8OXudM3cyXwBUHDCcbRxiAFA/LuhXhlUqHrsMUckzdpBCRo8uNZoG2yLAI6Jo4vNHZoSXdSdLJId1dU1mj9/obZvL1L//n13NLfjmFTYAoAwF746AEdAAv+vq/cK+wJQ3KJFUJs3b9ecOUGtXElfjQqFw1Xq2LFceXmAtAz5/ZnG7tXV6UpNTTYUpXhtDmCAEgjAABitXVuoSGSFBg9O0sEHDzQZGShcULsAlIAY5g+YxuZUruJzV10VNODEEcE7WYyHH/Zr+nSPaXpIXxFsFQ7X6pJLnAIP48eHzPoAwKCYcZ6nnvKbPQnNC8ojWSFE7fQu4ftAxsnSv7A7VdL4nll6GZXhPJ6vlJOD4P8wYx8Gmb9TT03SpElBDRoU0YknJmnChKBGjtw9o2lBibuZnwUl7g7jNmPSnB3GuTeRAS4oKDD9KerTCMTzfdpX72HulLu1z4K67kPRcyMTFU3figaCbmBSn82xH2Vu//KXv+iee+7RHXfcsV+AD8AwoGHOnDlGWH7iiSc2uDyNyWo05r37ak8kzrv3LJAAIHvP1okz7QMLuAEIKXaiXfwN5x7a1Z6m0KmZTsnehmql/+53Xt1wQ3hHhBsz8PDBCb/yytYaNqxCt9zS3kTeiLpRR53XaToGZezNN3P0+9+n6rbbapScXKr8/NXq06dKK1Ycpn/8I83w1Wmm1tSBw4qTb0XoCKbdzmpDx4XOQjSd6Dv9F8iaHHIINCgHgNgqU9C5cJYHDqzWunULDKe4d+/exmmpbw2caklOuVpoWJwDulI0kPvsM4/+9S+vEUJfeKFTPhXHEycRZ5XIP8J0gGjPnqXy+4s1f37QlJtNSys1gutIxGdoTDTvs6VS64pmsj4Ap0WLlqumpoNatuyrtDTvbuCjIZtxXdiGzAUOMBQ1Bo6yUz3JKbPLdWIzIvLoZmyZXYLeZDmgIpHB+fxzr2lsh/0BCVTZGjIEQOasI59zV6FCCAplie8BABxAbgc6CeYGECGbZfUrzI22NO7u8+g3OCeAFUfbrgvzIrvDPNPTQ8rOLlFVlUPhoi8MjnpBQarRlHTt6lPfvn61auWUp20oao+daDzp8URUXLxaS5fS9LKNzjyzg1JTHZCM3QBwjrbCKRzAuto+IlOmePXggz5dc03IVMUiU2Ivn8/fdptPr7/uNY7/1VeHTMZpzJgknXhiWB6PUyWNNYFOCECeN89r9h6gmO8BOpHBgyPm+jk2wMxiaze9rLS0TOXly9S3b42GDDl4N74/+3XEiCQ98EDQaMMAIWRwAEixhu0w7naSbYdxNyixTnJTQAmZZSLjRMrp8xBPb6VY897br69fv95UbaLIB7TcPaGNNWRz29Wd39CAjz76aGMzBN5kBB555BFdd911e/wsag77cR30HqFgy7///W9Dv4o1GqPraMx7Y5038fqBb4EEADnw1zBxBQ1YwAIQSuvOmzfPOPaDBg1qclOs6FPhjEIjImJUnyP91796dfbZ4R1lUm1347lzqYo0yHRsdmhLiFsjpvQukTkciKlTO2j69Dyde+5K9ehRqe3bg1q7tr0++CBPxx4rPfpofHQrosc4WDjnsZoPxruhiCrD6cfJJ0oeTQdCRI3TZcvktmpVqqqq+YaqBd0Ex9cpQ+vMjQCwdRRx0sl+wLnnNRxBMgxuGlP0PMkqTJniM1Hpiy8OGYcQ8AKg4hzoEnAgATFU+CJLsHkzFK4KpaejKylUVRXOskNrQQtRW9taqakZRuPQtm2qadKVn79JoVBfRSJdjNiYrBDXb7NGsewH0MPJt+WByV6h43CyQw49i7kRCUecjiaHDIZbAwrwAJzh9PO6tQtTf/xxr9E42DK9tgraT34S0bZthSbiC38dfnd0fwn2CZF6gCMONHPD9szN9uMAINGNnOtgzQB+bqoRQAG7AwKhT9kSxdiFDMqCBTRPrFQwWKmamgrl5GxRVhbV26jq5d2tu7gFJVwzup/589eptrZYmZnddOihWWZu1smHPuam/QGOLMBgv2Kzb7+V7r7bbzJTr7xSsyOrx/4lw8Kee/ddr95/32MojY88EtTo0VChQiZz8t57LUzVMvqOQE8EfM2e3cKU8uW6H3+85rvqZDv7o3Btll62bNkWrVnzrXr2TNHxx/evl+/PtUDBuvVWqF4RDRuWZLKchxwSa4ft/jqAwQ1I+LcFJdZBtsAbYAIoqc8h5/tBMIff7CE3gG38zPb+J7jP2sARARCKkuxpIKquq7Bd3a3dKdl+ww03mPs8wSYCIieccIKpHkUJXEDJnmTj99SSPCvRcrzxxht64YUXzLziGbEqW7300ksm8BdPFSz3e+M5d+I9B7YFEgDkwF6/xOxjWICbKhxlsg04Xdz8hw4d2mx2Q4OBloQMSH1VX6hwdfTRTgQbIETkkPHkkydq+HCfERi7xeY8+Hkg0tegpKRW1167Uf/731ZVVYX02ms9VVnp0fXXz1f//jUmQ2Idh7rq2uO845DhzFqHEIfRLQTfE2MAMhANEw0mau4WDdtKQYiBi4o2qaiICjkZBnywFrzfOtqRiMPXt03p0HvAmYfOwlxxeskC2IZ2Dc2Z91IljCgykWwi1mQCiIajhbB0KBxashAAMpxs+3eigFu2lOqLL2q0Zk1Q27dXKDW1wlSCysgISsrUpk2d5fenKy8vWYWFSaaak7vMbyybAo5WrnS0M1wfcwPAWHDoVAdzgBnOvZvChaNse23wPgTU7iwHmR8i8FB9cGI/+gjBNU0XoUVVGWBx/vmpOu+83Sl1zBvQSCUnqExU0KIqGgDLPQA6ACV0K+4KYczZ3QfEaTToCK4Zll7GPmFNyOSw5mQCcNTsD5Qi6yBbfQNgafHicuXnB9SpU0916JBhaE62gpadH0CDvcW83Nky6ILMzdKvoB5OneozGUQ0FoBSMnqAGUAL4OLddz36+GMnI7J8ORStsIYMiYisG0ANWhbZFMo0s+/Gj/eZKlr0eyE44Kbk8R1fuXKl+UG3BW0pVtSd7xUg5PLLQxoxIqyRI5M1dWqVevSItcNivx7tIGN7xNcMC0rczRMBJbbBINdCjw+cygNpuDUr9HmKp9dTc14fz4trr71Wa9asMVkjHHMCWASe2OcXXXSRnn766eY8ZVzH4vz0HqFk7pNPPqnLL7+8zs+xZ8j489yBPmsHAnM0IOgSO1GWz9UHhOCcW8TemPfGNfnEmw5YCyQAyAG7dImJx2MBbohUieJBQ3SVyFdDdKl4jul+Dw2a0JYAauqLXr3+OiJz6B4rDRiCb5yVdaiuvDJV06cH1aKFA0BsiV2qKJ12WpIpE3rNNVs0b95CTZnSU7NmddXYsRGdfXaFMjMdsbX9sSUkcdIsIOEhUVHRUosX08/BoaUQtcaJt3Sexl5v9PtxQqmyhLNP9gLH0p2lIMpnxfJEG6FdWaeLzAmUGZxsMgDw5pkbjjhceaLRUF2YNw47f29MCWDoQ3S/Jir9k5+ETb+HeipJ7mYGnEkAUFIS/UvK9Pnn65SXR2fzVG3bFjIZDIBVdnaVSkvpKB7Q0UczX6fbdaxIJn4eoIB1AXixHtGlfutbGwvOKHELeMFW2A1nmIHdAIW2lwYgJSXlGwWDa5SXl6fq6p568cWAcaJZP8TqJ5/slP+lLwd/o1oUegdoV+5GgLH2S6x1w66U4rX0MjRCAEuyW9HDTWvBUSsqKjJajvXr07R9e6qyspLVq1dA3bs7FbhiCYDZQ6wpGTFABuAHuz/wAEBfpgkhAAngYauXoU9B4E8paBp6skehY11xRciARfb9e+/5TJZn7FiaPUqXX+6I1NnflOi94w7Ku0aMo4moF+on6xBv1B0wNWpUktGmnHJKWGedlay33qoyVbeae3AfcetJ+DcFHRh2vtxHEZxzHwOAxAJRzT3Hph4PJ9uuwb7QrLB/yTCQgcQhxzFnAPr4G8+RrKwsUfp2b48bb7xRf/rTn4ze4xe/+MVup//Rj35kABPVzlh7+ns8++yzO97HM/aoo44yxVygkzHohM73luIv7tL3jXnv3rZD4nx71wIJALJ37Z042162ABFfboKUd42HLtXY6ZHR4AZLFaz66qS//z5NzFaqe/cVBghRbeiKK/ymAd2VVzp9Sni484MDd+65SbrrrhoddNAqzZhRoEmTBunII5M0cWLYOPnR+gx3XXs3KOG4cO03bMg1TeWys1NVWEgZ4iQdfngdivh6Lr6+iLL77bwnWptBtJTsECl6hOYdCBO7hnVWEQxzXTh/RLTh7NtIOpQZhpMd2bWnAn/HWSYaD0ix9K3oy8DZf+EFn3HKocLB0Y81AFWUu5UKtHEjYvM2Gjass444wmcAE5WPli+nDHClPJ5yQyHKyipQKESGhLlQ9SlLPl+msrPpDZKhpKSAeY35uulllmIVb3d65ma7kVu7ucGZuzCABPVmqVq33qSDD965BtiX7IvX6/S0oAHfjBmOjgSHt3PniI46KmxsbquXxUPdY26AShx41iQ6cxVNL3NnveyaQNNiHoAEAGhJidNfAkCdnT1QCxeGlZ9fbapuJSeXmN45LVvW7FIJqi4djwVugF3mBkUN0Ab4+eADj8aP92vMmJDJcNjqZexHdDkM7PTEEx7dc0/A0NFmzNiZiWAvP/mkzbqF9dBDfo0fH9SXX3pNwYCRI1fppJMWG62BO3Icax/a1zn36NGAXMoyh3TJJUmaMaN6x9ziPU5T3gco4d5J5oYoPfQhmynhnkWWxJ0p2R9BCYEQW3IdqhO6j705oNRSjhbdCRSn4447bm+ePua5KKIyc+bMet/3wQcfmEIr9QEQPoh9KSVMV3XGkCFDTIUvMt7RozHvjTn5xBsOWAskAMgBu3SJicdjAZxwW8vdlhRsiC4VzzHd70GEibCOkoU4SNGD16dO/Vbr1iXp6qtzTI35bdtqdfrpAc2YUWFKzPIQJ4qIA3jLLX698EKFSkoWasKErqqoyNSUKVRJ8jRqak71rHKtWFGu+fPDKi6Gc19uKgV17VpmHEt3pqQ+zjf6DYABTjx0Gzj1dVzmbnMD9BHVI1qK0LmujsKWEkNU2YIqou307GCgJaDfA84XlBgi+m6QQ5UjotjQjGyZ34aiwjjWCIYRbA8fHtaPfxypVw9TWBjR22+v0/LlZcrJaaVevTqoX7+dFZtwpNEK4KhiFyhGaFsAvIDANWvKtWhRSIWF9CkJmkpHNJekR0l5eWutWZOt1q1TlJ7uNU66O4MRa6FZEwAM4Mzpwu6AM9stnM8T0c/PL9fSpYvUsmWVBg062ERXGZT5hTpH9sFWLgPA4PAT7Kbs7/TpXi1c6DHXaAsLnH9+WCNG1G8zjs0+YW62dDNzi9buOOWRnVLN0fQysgbffOM0IAQcSevl9y9V165tTX+JpUu9pmobe4TjOLarUZs2xbtE7t1View+DwQytHFjtmliKTnaGq7b9odhf9CocMUKj558slpdu+5KfQPAMDf265//DK3Na8AKmg9E/gAngAyUN/Yu4GPSpFLV1s7TE0/00KpVHXTzzRGdd15sAFzfHjj//ICh69G5fdw4vz78sHqHNifWvmnq61aszb0L553vNA59dKaEQAOD+xkgxN2rhP/HU2GqqXNs6HPc/ym6wPcSzUpTS643dW6AN/pjYK+3337bVDxLjIQFEhaQEgAksQt+0BZwA5AtW6AzzTORnObqMouT//HHH5uu5e4HG1mJdevWmSorZWW5Kiw8WFdc4TU0q5tu8qpt27BuuAEBuaP3+OMffaak7EsvFepPf9qq117rrPHjK/WLX+wZxxoHFScdDUgwSK8Jp19GTU2JeSBbpyFaiOrQiNK0YIHHZGWItONsEw0nQ1FflSyuD36zLXNMYzuaeNU1cEDRKmzY4OhToG7hWMZTgYv3k6FgbkTbiZiTSUEQHItmxXkBezjZcPvPPTccVaLWaVC5Zk2VMjL6qlWrXKMzwPGLJwvgNLJz5oaTW1iIKLlcXbpslVRktBjLl6crM7NaGRl+FRW1Uf/+6IScClzxdJC2zfhseWQCurvqHTabEqkIuHG67H7n2pkbOg8ACxW2oH5RuQxxPgAEbQN/B/ABJNDQkC2hSR/N+zgGupMzzgjrnHPCuznA0JCgl4VCUNIiptRuvINzM7dOncJavHiNNm4s0bBhrXT00Z3M9wTNEBQu1hrAwDwpERytUamvZwaFCAoKDDtK5AAAIABJREFUCBRkqV27JPXpk6x27dJ3oW8xh6uuCph9QZNCO9hv0LgA4RRJmDzZp9mzvUb/gz3uuQftENQ8p0P9XXcBRGr0619/rQsv7K4WLdINaMCGNAodPnx3IAK4BFii/YD+Bl0smpp3+eV+AxyhFd55pwNC6vmKxWv2er6fOzUr8Yi1LShxAxPuj9wTLCiJzpR836CEgh9Qm/jN98CC8D0yTCM+DN2IzAf3V3piQEFNjIQFEhZwLJAAIImd8IO2AA8/2zgKDu7s2bNNari5xJM82EhPI8gkQshwelAsNk0CaeCUk9NXL7zg169+FVJFRVgnn5ys99+vVFJSC1PlaOzYgHFsL7lkg66/vqV69arQ00/jjKY2y9rgMNrO0mhG3S03rNNApsbStyy9orqajusdFAikq3PnJNO7ITk5SUceWXcWhOuGKoMuBo57vGWOySbgSNdHoarLCDiAiK1x9nb2fGhhStDGS2XiuNBjXnnFa6hfF10UUihUYooE2AaVTXFYcB6ZG5FynHicSqplUYGLSHlRUa3mzaObeLUqKirl85Wqdestat3a4dqTjXIAYKZSU1sqJyddgcDufVLqBnXoZ1ZrxYoVZj/aiLV9L3amchmZJQAVYAFwgc4BQMJewckHBLBnoBrZCl9u8DVrlvTPf/pNo0iOiY5k2LCIzj8/ZIT9ZCYArIBDOsxTpjaegbbm22+hQC3Rtm01ys3trpNOopmh83mAF9XOoE8BuFh7ske2QhfzR0xeVeXodwC1FphxH1i+vFwLFtQoP7/GVODKyCg1vWHS0gCyTilgftLTW+qOOzJMmd3Jk6uNEB9qGcDKdnFnTbHTP/7h0/33B3XffX6TBbv00qD8/lJt3rxCkycP1MiRAVVW+jRsWNgAZAD3PfegO2mhhx4KGloVgz0NuCLT4uwDp8IYezN63Hij31QqO+20kP76V7/ef59MWzwWju89BG7QbtHjqLGaFfcZuL8Q5HAXF+D/FpTYve7um9FcoIT7mO39tC8E82RdRo8ebQJTCLQbauYX36o0/C7s+tBDD5kg29y5c001xWitRn1HsNSq+l4nKGKZBLyHju2TJ0+u8+0E3qwQvTmuK3GMH64FEgDkh7u2iSszpVR3AhAic/BTBw8e3GyRMJzud9991/Bc0TjYHgvoH+B787eamlrRC+SOO2p0//0+E7m95x4ezE7DsVGjgpo1q9x0Uf7979dr2DBHML+vhq2Os3lzqT7/PKx16+hhghMRUOvWYdOvIjfXoVjwQ3SdSCeOO9QXnF6cX5xBKDzQUXACoeM0F/WaDAiRfDQHNMLDmUMvgIMXT2EeR8xMCWEH/OCEv/EGZWE36eyzt+n44/s1OUvGsaEJkXkiMo1jiXNP5sjODYE82QXOjcagffuwadxnHbVly2q0enXIRMLT04MicNq27U6b10VpwdkD+OJ4NFThBy0MFCwKEmBHwAFZBJs5Yn9ChWLeUNugl7mzUmR2KMOLk0+VMhxkjvPiiz69/bbHiP5xhmkQedhhaG6cCmHxiOyXLKnQ9OmrVFLiU48eeerdO9noNCzA4DvB9wZwZ0sQ2w7yvAYgoM8IwJQKXnl5TlbNDtuN3HZCLyoKq3v3EqWnF+2wPUEFBlqHrVtz9bvf9dfxx9fohhsiWrs2xYAfroU1ZW4ffeTR7bf79fbb1Sbrdd11taa08003rdeoUT00bFiqPv64WlOnevXWWx5TMYsCE8zvkUf8qqlpoUcfdfQc9Dnh72Q/2NvsaXcvEfc94a67/GafjRwZNtTCt96qaRYQ4tZLQHuL1m7t6X3JghJ3psSCEo7N3nZnSvh3Y++HHBvwgeMM+IguN72n1xDr8/T7QHDO95BmfjY4Fetze/K6BRFojCg1/+abb8YNQLh//+c//9nt9ICJ2267zVDIXn/99R2vWwACCIkuQnDWWWeZzGtiJCwQywIJABLLQonXD2gLuAEIoAChHTXXEaU3x+D4RLd4UOOwQHvBIYfny4PU9va4806fJkyo1vHHp2rmzGqtWSPT4OyYY8igRHTWWct01VUZpjzn/jSgSOHQlZRARUFsXaz09K3GWbOZJR7yADGun2gpD1toV9C+iBhDS2EQrYZzH102tanXS6TbakBwQnE2bbnXWMd0l2Qlal1YuEEpKavUsWOOPvmknyIRjy69NGSi3U0ZUJmg66DFsGV23c0AGzomlZWItnN9LVpUadu2SuXmblNu7mYDcN2UFgsCEb1THhNHIlZjOFu5DB0GWScAiBVax7pWsjkI4NFoAPxwxrERvThwygFWONF0ESd7QHdxwB3gpn//iKFsQT2qK1qPbuirrxaovDxTnTsPVFpaktkzVqMRa27oTwClzAlKFPsOkTvZHQv8oFGxZ2w3cnQwgFaoTnbYTtfuvhlPPdVNc+e21ZVXLla7dsnyejPUpUuy+vRJVXp6subP9+gXv6BZ4FIFg8tVXd1Lf/5zHwPMzjgjpGnTvKabOZknaGNvvukxVaxuvDFogN511yWpRQunfw2li9HGQMXCtgD++rIbDz/sFA/AprNmeTR1ak0sMzX4Ot9pIvfsM4IqzXWfjDUpMi7RmRJABHudUVempD6qIplurgHQAfiojwIaa05NeZ35EpCipC0gAKe9KVnUppybfVtYWGieIfZ+HG8GpL7z3X///ZowYYKp2gWwsMMCEIJV8VBGm3I9ic/88C2QACA//DX+P3+FNqLJzfK9994zXODmrIIyY8YME7GjuzfRJzIf3JRtbw8ervfeGzAR02XLvCb6ecstASUnh9S5c4FuvHGJDj/84DqF2vvD4uFE22i47WvAtZHtoKwwlCvbxd2WAwaEbd3aVhs2tFbfvlQNSlV+vv+7buNNc+rrsgXBauaGI+2OhMeyG5FyHOnc3KDWrFmhpUsp09taw4fnGr46zvmzzzolfH/2s9COErexjut+Hd+JDAaOeWMSWmQfcJRx8AkkQsmxkXDKubojx24dj3XUaAxnaUQ4bj5f83FzbDdyiiewF8jikAUhw4H9oV0BnpgzTjOZEzIQ9PqgpwZZgG++cWhbONroGAAlW7euM+WyKe2K49sUp8ZpVEhmx7EXc8XuOPC2cAJO/bJlTgUsXoPaRRbDZn9YM0CWU554557iHrJoUZl++ctWatWqUkOHrpFUo9atK9WjR7WystK1ciWZkIP10EMbddppHUxkeMUK6frrA/rqK4+OPz6sn/40bEAF4BJw//XX6MGgbYWM+P266/wmA/KLX3BvqFWvXs4cGZZexvVBL4NqSBboqae8pgEnXdK5vmefbRoIsT0+uE8SQKmrqEZj9v+evteCkuhMCX+3e91N3WLPAz7QbzF37vNN2UdNnTf3RLIIP//5zzVs2DBNnTq13sqITT1HvJ9rLgCCZoVKj9CJ3UDOAhAAK/tmf6x8Fq+tEu/bdxZIAJB9Z/vEmfeSBbhJ2j4bZCuIEDcXR5Wb70cffWSOTxYEsabjLDhdzW2JXUp3InqGJz9pks/oPK655lMdfHCaASw48AfSwEmhyhVRa8sRZ/7Yw9KIFi6sMQ5Wy5YVotFgMJhuujgPGJC8o0JOY6kVzWUjnL/Zs6u0du1KtWgRVKtWPXX00WnGUXYPwA0lfMnk4Czj5OH0QVPiGNCBWDqcxHgj9bGuAccZLQCRcpxRftOvoq4eKNCtrNgcUA3vvaio9LusVcA42V26kJlyBO78AEri7UERPVeyDNCYcHQBR9gHgAGFy0bpceABIIARHH96aViRNL4j4I/sGEDg0099WriwWlVVNcrK8un005N00UVho5Vp7CDbgN2o2sZcOBf6FeZm6V848VQBg7Jny/xCd7IOPnNbtw7g6BQ3QIPhzg4BWh99FPE5GY9KdepUro4dt6imZo2JOhcVBXTnncfpyiuX6IQTgjtsXlSUpSFDMtWmTcSAkEMPjexojMl6A3ahtAF2yeL88Y9+Uz3sySd3dmqH3hVNL0MQz3j5ZY+hc6GB4tofe8wpBx3vsJQlvo9kDfZXCo2t7ufOTjF3C0q4XrKB3IcBIQCUvXFv5X7/3HPPmSaDNNqbMmXKXs28RK9zcwAQaGSUC+aa/vznP+9yCgtAsC/2J9s0atQoPfjgg+rRHF0y4924ifcd0BZIAJADevkSk4/HAhaA8F6yFTjMNFPa00FVLaJt3Oxp0kTEzQ08bGNBnD0aiVGelIj9uHHLdPTR3+yRuHNP574nn+eBg96D66bKVX1lLcmc0NBu3Tp6NlQqNbVEublbFAoV7wBmllqBY4zDsLciaevWFWjatDWqrMxUXl4PdejgOHz1gQgAx6uveg3NhaZ9PXpEjCP9XY824+gSSW+ODvM4yRwbsTIZFDINABD33NhbUK5orEnWjT4rFsyhHVi0iM7eVUbkHghsV05OgZKSSsyyE5l3C675Nw5nvKAEmhXOMACDOQFA4gVfAA90CzRgpAHnqlVrlZW1QUOHdpLf38WAvfffd2hbgAYE2j/7WVADB8a3YwFIzA1gSAaDdYlVFc0emawXAAPAR2UrRN44+NDLAJ2sC8UFAF+Ak9tuCyg9Payrr/5MrVuX7ag2tnHjdp19dq7GjFmro49euYOquHFjlu6//0i1axdWaWmSbrutSuee691hd74vVNYiA0Y/EnQ6Eyf6ddRREd13H4DfoZehpeI39DLmZq9v2jSP0IWwV7huPhPPIMINZYnvIpmPvUlZimd+sd4D+KDoAtX3nIyfzzjFFpS4m7PajElzghK+i3/5y19066236rLLLtPjjz++VzMvddmnOQDIFVdcYbqiz5kzx9CW3YNrJQgFzQzA99lnnxmQgn0RwHelhnViJCwQwwIJAJLYIj94C3CjtA8jKlaR/aAZYFMHDxzKzNKYKycnx1CRcJ7JZCCwdHc1t05dVlaKoXVAu4K+kpLi+e4H0SUOHF21HVoFpUs7dCBCSvTaeR16Cz9E26Mb/jX1OpryOXqpIHTmQU9/j1jiTmgxCIYZUG6ImkfzvS2NyGob3AJU7LonEfvoa3Q77q1bt1WHDgPVooXHROrjAQ84oe+849FzzznUmTFjwgaEQIuxVa6aYte6PoMTDfDBwXQnyNhjZD2gvtVVoQhHlUpRiMP5PA4zAvguXWhKWLrLD8CQAXiJBiUNdRYn28B+JrPRmOpLlvrWpk21Vq78RqtWeXXyyR10wgm799ABTCCufv11r9FOMPr1c8omDx3qRPqb87tAZgT9ChW9AFTYDSefqm/W/uhHEPETSNi+vUIzZtCItJ0mTgzptNOcctOARsw6enSSzj47pF/8onyHzZ94IkPLl/t18cVfadKkQ1VQkK6LL96o0aNrdthfStI//0lmyKNTTw2b8z3xhM+I+n/605Ap5FAXvYxzf/KJR7/6ld9k5E44IaLx43eWEa5rj9kM2p5Q35prvzflOHyfAR8IsN2V9/g7eqjoTAnfHQZ7O1ro3hTgxb3st7/9rf7whz/opptuMhmA/aEz/J4CECiHZFTRk3CviWcQ3BsxYkTcwvd4jpl4zw/bAgkA8sNe38TVmW7ZOwHIJ598YiL2RIybMrgxE/0nagg/lkwKER+ibmQD3F3NLfjgYUgzKkCLx5OlpKSDtHZtstat8yg/32OimXDCibzSzwLnhegyjkw47FRKwvG1P9Hztk4Yv2neRuQYh4mOzzjV0HhwqDIzHZCDCBw9Cr+hn6SkOO/b+XvnZwE9OJm1tRGj96AqClVx+vbt2+jKNA3ZO7qxGY4DDgRjTyP29rzsAx6mCDX3rLSoozWg4RzOPuBlxIiQqfbUXAL7+mwFYCBazW9bbSz6vZTRJctADxJAAnQiaEhuobXbJtGgpKwMMWuKQqEkZWenqnv3gNq2zdhR8SzeTEld10B0f/bsSn3zzUoFAvQi6a5Bg5JN1D7W4HsA+Js82dGRsN9xtKE00ZivMRqgus4FWIZehq4F0Md3EBBHZst+xwB0ZFiWLy/S2rXL1a0bVZYG6NJLKVEt/fa3QQMO8HPJXFEdiyzF3XfvzEaMGhXQNddU6Kij4NaX6Z57crR8ebJOPfVbDR++zmQgrIZn9uy2mjOnpY49toUBF4j6jz8+YoBJNL3MXhNZHEp7812/4IKwLr/ccbqjBxkDvtNk0KCP7g+Oc6w94H6d+yp9ligVTEAJANLQ4P1QFN37nUyJBSXo1iwIt+CkIVDC52655RZNmjRJ9913n26//fa4s4iNuc6mvHdPAcjLL7+sn/70pwZQ/frXv457CmRECFKhGUmMhAViWSABQGJZKPH6AW8BNwChazk0H8BCY4etrmJ7RABk+PcXX3xhKrgARojYu+ks7t4YpKVxfJvrQY9zafs4wLsnSkx5VMrLUv4WATXZB4AN0XQ45kRu+RwN2dzABlvUFU3+rggNqhZjLqLOABx+ACY0qcPxcrI4DuefqDHAhh+iyQ64gZu9M5NjwRF/59/298734sSF6o3YA/iiI/Y4EPU5x4AZHHfoeKz9nlb3Qf+BwJgqSlB15s71GIfwsstC3xsIocgB4Jf9A90PJ6k+RxrNCsCW9bLVx+JtVrdwYUhff11lKFzBYIVattymDh0KTeYO6kq03aFgxAtK8vML9M47q1VZmaVu3XqqXTufob7FCx7QlnBttq8NtKWvvqI7usdke9iHP/pRRBdcAC2ysd9wykY75W/5jrB/ASDRFC6CCUuXfqO2bXfts/LMMx794Q9+oxUCJDAfqr79/veOsPyvf3VACHM/4YQk00DQ6k/Ky2t1ww1es4/OOmuzTjlltdn73Lv4Di5b1lazZnVVmzYELVK1ZEmKxo0L64or6gYX6GvOOy/ZfLduuimoc8/d2fSQexbAg+toTL+exlvz+/sEgR40aNBg96RUsBuUWLE7v93FNCwY4d7Bs4MMOutyzTXX6B//+IceffRRo5OI9zvw/Vll55H3FICceuqpprojAScAaryDSlmU/7UVEuP9XOJ9/zctkAAg/zfX/f/UVXMztlEushXQTeA6xzt4SJHi56FNSUWoRzi7tsoV0R74+O7+AbY/Bg9Izh+rNGq8c/m+3oezZMEMv8nE8HvTpgotWrReJSU0S+ykkpIkE+HF8eY90GSIsANs6HxN5Pe7IjVmqoAad4Ymev4W4NjfvBenmUyOA3B2zeBkZkaUklKjQKBKPh8OcvV3tDeHRpScTPTYr6ysgLKykpSWRgMtmsLBD/dowIDuyspyHDNLa7NgCPDTGEoPpXydrtfQ5pyqS8884zP2GDs2tFt37j1ZO/YY1DcALvsvFl2ELBpN+7AlIup4axwQ9UfnwPpSnpdrYgwcWC2fb2ezSncZZhuxdwMTQIl78F0h4k4WMDe3rTp3HiCPx2vK48bTH8Qeqz56mRVjo5uhMSA6Ers2gwfTIDF+HQnfBQAIl+Cml7kdd4IJRN3dTifgiCaPjz/OnpMuvzxkAAhVuH79a78JDLz4olOhiopgDz3k07Rpu1asIut5661+k+2gqeMvf1mm8vLtO4D4ggW1eueddqY3TH5+ptavz9TVVxfqJz9xGim67Y6YHlE/c3zggRqNGOEUxaBZKNSrPn36fO/N8fZkz9f3We6nAHEAOcGE5u6xwTq7i2lYYPL888/rn//8p8mgQ72latv1119vMgSNcdK/D5tEH3NPAAh7A5AFneqtt95q1HSpYEegDuCSGAkLxLJAAoDEslDi9QPeAm4AQhSc6NWRRx4Z13XZak/w7clw4HQQgXaX2OUBzw/vtR3FeT9ZETvc6X3rqDWnEDKui2nEm7i+9evXm4csTi8Plminsr7DAUK4dAtiEBSToXH/5nUcRBw1nF4cZqLZ9MCgQhHvdahoDqixwIbO8TuzMm6AQ4aGTt5ON2/74wAKh0Lj93u+y9w4oIGMjFO+1wEj6FNwiBEYE5m2GQMLSqLPa45c68zBTV+LRGo1e7bXaEOGDw+bTt2Am/pAT0MaCqs3wnmH+gZ1sLkyaHWtHw4w9DKyZ9CbyKKQ5aKXhrsaFPNy98uwtBbbLZm94qazQMsoKCgw3yGq5DQ1Wkz2A3oZQmzmivYGell9/VrYZ+hI3njDa66J9crLi5hCAlQ04xrjaVzp1t1AP7TV7tw2REOCbgMwTvGFv//dp0svDeu22xwdxh/+4NPMmR79979Ow8CrrvIbAb9bp0EGBgoY34vnnnOqbY0eHdZvfhMyn8HuaM6WLCnX888nafv2Gq1YEdC2bQGNHbtIRxxRtqPCHPYPBlvqtNNaGjs98USFUlK+MI77/h4Qqe/eQmSdjDNUKrKAlJzeGwO7o/mjxwflddGdMAd7j7fN/6666iqdcsope2NKDZ6jIQDCd5SAGff1uoDTxIkTNX78eAO2zjvvvN3OQzaZDHT084D3jxkzRojXEeInRsICsSyQACCxLJR4/YC3gBuAoAEgonXMMcfEvC6cKkvbwQF3uns7Tq4Vm+NIuR1CIow47TjviPhwuLhhW2DCMW02BqoWDwG3o7avytK6jcH84FbjNOJooXX5Pp3ehhbC6VK+K3hxZ2gsyKGq0s7MC85pUJs2Faq0NKxQKGCqLpWVkZ3wKhTyKxz2ffcDdYe/OUDHAhdLT4sGH7YaEs0LKePKj83YAGaiAQ30LBzl3r0jJiPiABEn6s/fAVgWxLgBjgNuIkZoTiWr1q1bmX3CfrPvj6axWfqaG+hE094cqlvDwnHK2H77rQMgeT/aESL5sXqZWOc4WlNi6SwAbtujpKkgHCBbF70sKuFS75ZCBP/SSx6TIdm40WNAJtkTNCT81FWIwDbn477BfYDod12DPUPlKujvZFGgIz72mN8AnylTqpWbKz39tNeU3H3nnWpz7uOOS9Izz1Srb18ZHRiV8gAg2Bog3Lu3NGWK11RgGzkyorvuovHbzrMD2Mm6rVpFYQIAWUTXXfeN2rffZAIijFAoRePHH6uyMpohztYZZ+Q1e9Yg5s20Gd5g+5SwnygVXB8FsRlOVech0P1RYpdMJP0+6PVBYGDevHk7fugBgnZiXw2qcQEweQ7dddddJtNvGwieccYZZv/ajun1NSnkPWQwyITUFXTimQhFa/To0SYgRwYUajN0NJ4Xs2fPNlUhEyNhgVgWSACQWBZKvH7AWwCH2jpBS5cuNbzh448/vt7rwpFC2MiDBs4vkTbAAn+3vT34N065O5LLA5KyvDgqREmpIBId6XVXZ7GgxHb85b2cz5aktT0b9qbzzzVAbwA0wa3e36gF8WzGuoTa2L2srEIFBdu1aVO5CgoqtWVLlcrLvaqsBIykqbY23fwOh5Pl8wVMdaz6HE2i3FYXg+NZWenoEsjc8BtqGuDCye44EW3eRz8UN9CxxwfQWG0NWgsc0HAYmllYLVsG1KoVmhfK3jpaG6L2NnPj/k0Wx6k05pyfLBI/RMBtcQP+bsGaBVTR12krcAGuOJcFHwAaC3Q4r20AWRfokSq1bBmalWr16NFREuVnnSpc7mpE0ZqSWM3jsC1ZMuxP1bh4tS22jC76HTqhA2ZYG+w9Y4bP6C8ADtiYzuLoSNLTy03EnflyH4jVnM82MmSNsRtzo3QzDQYvvDCsX/0qpDfe8Oj++/2aPr3aNLwcMyZJs2ZVG+0JAvIOHZyqW1TcAvjR/4X1euQRn156yWv0Jb//fXCX68YmlDAme4UeBi3MxImUXy42vXrWrCnQTTcdZ8r//u53nygvj33l9IWxP7FoffF8976v95BpmD9/vrnn7os+JTjjZ555phFXo3GIJ4D1fdmioeOi6QEU1TWeeeYZ0b+jIQDCXse+V155pRHX1zWwBRW/KM+LPQC6AI/TTz/dCPH3VF+3L+yWOOe+sUACgOwbuyfOuhct4AYgpM6J7gwdOrTOGfBeONLcWLmp2mpPbsoVH4wGH1RWIrtCBgOOPg/1eAegxt3tF2BSXwUoHKCGyqPGe8663oejgrATB5Br2NsRxj2Zu/2s+xpwGAF09Q13UzPrGNcFBi0gpBywBYM4mjh9NhuDw+6I/R3tjJt+ZrMp7nlEO/4AEKdiFcep0caN2xQM+pWc3MoAJI5vq6LhJNsfjs2/cXitfobzWA0Njiw/OML8tnQv9/kBFxQLwFQ4rmxdKqYRwec3Hdlx9LOzI+Y1QAdFDCy4sUAHsGX/vXVrhVas2KBw2K/WrTspHA7skqEKBkOGwsUPGQZ+8x1jkClJSgooEEgyEdiMjIBSU51sjKW61Udpcxc14N/urA2Hx0FHq0FzRAAIwIymgG6dLToSnPl33qGXSqX8/hY6+WQaJNZqwAAnU2H1Jbm5sTNDXBPrBAiBokU2hAp4117r1+uvV+vNN736/HOvqZRFFS4E66wXRSUGDHCyT+4xaZLX9AsZNCiiP/4xaACnHbZfzeuve7RwoVcdO9bo0ks/Mdd30EGHacSIlqa88IsvfqPk5G0GDLoF1+x1d3na/QGUcD/EMWYv4BzHSwVtjvsJx8BhJ3vAPXnatGnm3pgYCQskLLDnFkgAkD23YeII+7kFcDQtHYGHCULYH/3oR7vNmgcMDzoi6ET/yWBYypW7q7nVfHAAXrcN4Yj8wK1uDm0HTkF9PRsACG7qlhW8N3UZrMgecIbAEmFnc1xDU+fTlM+5Sx3T06Cp1xANBm2PEuYE+HA7Z3vaVdxeJ44xzjzAZcWKAn399Vr5fNnKyenxHfjYqaHBwawra8Ex0JxwDFsQwOprcLJtWWcAiK1kZs+Pc2wzNDi+ZDkAK5Zi5mhonKwJx0Zkz6gvewKggB/v9/tMDxeAAJWkLMAB2EAvAtjwg7aEymkpKXDLixUKOVkSp0Qq3120OxkKBDIVCLQ0//Z40gydzp3dsZoh529OduO7tg87thSgA9oS9uD6yCa1abO7ED4YLFNx8UaTferUqYMWLfJrwQKPqSrHMXNyIqZBIP1IKNMLgLNFDRoS1S9ciDg9SaecEtE55wRvvROBAAAgAElEQVT1s58la8qUKv3mNwFdfHHI0MGgYHEO+uYAPijnW9egHPGkST4NHBjRww/TdX3nu9gP//nPdv3tbyGtWtVKgwZ59eSTIfOeoUMDWr3ao6++on/RTsG1OwgSDUrcwGRvghICCmRkCSRAJ9rb9yWoqGQ+uGaqQu1J/6im3NcSn0lY4IdsgQQA+SGvbuLajAXcAARtBpkKKny4qU2klYn+Ixa3JU5jUa5wtPgM3GCEteg9miqujWepOB+OmVtPYssdWtGvG5jE87B2lwneU4FwPNfwfbzHrVlp7lLHzJfjR4NBHGxGYxv41Xf97FHbZ2VPdDc4njjfVvS/e4bGZmccWpgbSOyshObobsrLPaqpQU/jvNdmYBxg4lDGHP3LzsxKOFwhr3e7cnMRWLdUTg49NSIma2KrSpElocoWc4RKZedqCxNY0ODocaBPhs0aOL93NtbD9oEAoJBGkl5lZ++kqQFy6INhszetWkUM0ECzTCd322md6mXuEsAOGF+jJUu+VVZWe+Xl9VN1tccAFgAejQqhcAES5s2jzLVT2ABHvk+fiHr0iG+Hf/ihx2RiTjoprPfe82ro0LA++MCrSy8NfWcrevY48627ZPXOogZvvunRX/7iCNoffbTGADruczjP6NaCwYP1wAMBffEF9K2wJk0KmqaJy5Z5tHRp1S4ZFGZfXxWoukCJBSbfByixTRIJiqBL2Nv6OIJR6BzQ/AA+6io8EN9qx/cuaGYPPfSQ0ZNQrZHrr0+nUdcRoVdNnjy5zpOR9aeylXvwHLz55ptFbyzGkCFDTN8PgmiJkbDA3rBAAoDsDSsnzrFPLeAGINzUEdGdfPLJJqplRePwZhGNc/MlwxCLcoXQD70HnyfazkNyb49o0a8FJm6Ru+V3A0yI3rsf4jzwiC4CYuji3tzlLPeGPagIxDVwLXtTs0JGLRqUMBdGXb0yALb1DY7FXqJ8JaVRv29HpzHr4nT8rruimRvcVFXVasuWQhUVVSoQoDJRhgEwUJUcPYxDdwLkMNzgBTBjsy38hgbmON80dnR+oDp17EhPk5AyMspUUeFkSTZvLtPGjTWmTHRZWcBUfQoGM1RTk2p+qqr8Zg5Q4gAQVvQfbQObzSH7WVNTraQkSjU75ZrJ3pApgf7FtfBeShRDm2NZjzwyYq4PHclXX3lM9gIdCWVvKaWL+LyugdD/0kuTTAYD/QnNBT/80KsXX6zeQWVz09rq0vTYrA8AcflyGTshQqdiEw4nFFIbFKG4AOWA58/36JRTwkYwv3SpRytXojVqeFdEgxKboaoPlHDfiScAUt9ZcZjR6+2rJok45eeee64pwEEp2voKDzTmuxTrvVabYStqoTVpCgABhETrBhGio2O0AxYAlSDJFo8bN878+f+3dyZQW1X1/t9qaXZzOaZmjmRa5qpVKRLirDigiDlPmIpiDpgTOS5dGiCgXhRURFQQRwYHFAXRUhOHzJVZTuWQpNccyHtbdfu37pX+67O5v7fN4Xne55xnn+cML9+9Fgt43/Oc4bPPOc/vu3/TNddc4xPYf/GLX8jT02qy9PtcCEiA5IJRO6kyAb48zVNArgarSzvuuKP/YkaM8GXKF/XGG2/sLyP0fFi4VdjVnC9HVqv5kmVlrjvjsmgunDur86GXhNAK69BOSIwl0lLlyjw+/LxuI2zMlzXvphPXyj0Wck/2ykiGzSGArUEiIoR7CYOgboP8DZ4jRGB3fRnwoISNM5NlmcmhWRIitSSRn20RD4RSmXiwULJ/9YtZ4o1ZYQUa7dGU71O3wgr/61ZdlSZ//3BrrPE/XgBssMGKbqON8BJ8zm2++efc2msvadJoA0MabyYhP7wLMN4JOSNci5yPP/95Rf/vV17BYF9ynogR9kFH9yUekn+FfPF/eqj813+t6PfD+a622mLfpNLsQD5L6Bb9QegQ7xx5LuSZLHYHH/zpUt4bbgs8ON2VbOYZx2ingAYNT0lIbuSRpX/NiSeu7IUI4XYIwz/84f91u+9G96S9a8LQrWSBgWTIYitRwj7ffvttH9aKEEeQd9KrnLwujo+346ijjvIG+uzZs1sWHsjreeU54vuJ0N92+niYB4R3SatCDgcddJDPZ8FLZgsefK9R5nvvvfd2M2bMyOuytB8RaEpAAkQ3R48nEAoQDERKBvKiJecBjwAhVzQYTJbYTSaa86VAZSz6GSBWrCdI1QFimGAcWvgWVcAsJybMazADOezkXtVrI8QEYyttY74yriPslREKE1s1RoCYscBKK6usrQy0Mq6ju2NifCI+uMfSVInK6/xZ8Q97zVjSP39TWeqPf/yn++Mf/9d99NFi95e/LPYCZkluCCWXEQUr+SpnK664pIfP4sX/40XMqquS/L6SD4NaY43FPvkeDwyVqTbaaMn/V1hhSdgWuRn0H0lTbwLBMnPmSj7hnN4qCJKvfW2x2223T323dSpejRixsq+Exe8OO2xJKJZ5mULvTaNmmfSeYeGB++nf/u3z3ruLuDDvDV4lwtLwzFjuDfk+//7vn3W/+tWSvjiLFi3x4MUMEyVhUYdmVc9MnNg9z2cpYY4hXERIayPxMWvWLDdkyBAfojt9+vSlvAYxXLJ+NkaAsBCCJ4+8mUYVFPkuwGNPz45kyBYeF/p5IIS6K+CR9Xq0vQg0IiABovuixxMIBQgvX4t5JWmcVWe+rMPeHo1K7PI5wmQIsyHUh3Ctuo1kzgo9GcKcEr60GKyehaFb1mG5yJXIZmzDPisxuRJlzZ0ZaKzy4oEKw/04p6r2hmnECyOFZ4KqbCQIV8kT2Oh8mxV2+PRTvCwruRVXXMOtvDKhlKu5v/71C+5Pf1rF/cd/rOg++GBF7wUhb8VCnghN+1ffmaWPZuFkeDMQJyTYI2LWX/+fbsMNF7vNNnNuk03oSL6iu//+ldzvf7/EFUNTxM9+9p9uzhyavDm3cOHfW4ZG8TnrU8I7ivcZ7zXO7T//c4kXZtGiJd4bEui5Bhp+mrcJLxT/f/ppclKWzQfJ4zlJipJ/FRjAY0Vo26o+PJT3D4KWhR28N0UOznHKlClu2LBhvvkehnkn8lrSXlOMAIElHOGKN4O8DgSdDRbg+vbt68vsUm43HPzs5JNP9ot0ffr0SXu62k4E2iIgAdIWNn2obgSs3CeJhcTaE2fLl/WSxm5LGgtamFJY5YrrJG8EzwcGFqE+dQxX4kufXAmus1mojyW52+olq/YWusaXcRhCxL+LXq1nDjF4OS8Lk6nbfRiGyZAwb1V1CMUKc0qSYXOhIGy2slkki4ULF/rVaoxdwq5ahXwUeW5pj0XxCLw33McsKOBBYA4slycU4safd0B3Qpz8DyvJvHAhJVwp+0vTwxV88jtiwJLuCUkLm08ibgjjIk8GAfGVryx2L73kG840HdacD88HIrBVn5K0bDq9XShKeJ4R4+YZNFES9ijBqO7U+4ZzGTdunLvwwgvdiSee6K677rrCE96TvNsRIOeee673gH33u9/1pYqfffZZN378eC/uCDvmfcPAy0MIFuFl9O4IBz+j6hfd3mm6qCECnSQgAdJJutp3ZQgQNoX4sIR0jHBESOj5aNTV3CoTYaAQtlVHQ4ueJsT6Yrhy3ayMpRmtQojYT9g0kX93qlINRgoCinNCBBIyV7eBmOMauBa8aBtssEHTSwjD5kyYsMLN9XOfhrH1GJ2I4iI8VGG1LsIQCR0r4rh5zzUGL/1+8ALyTITGbVKIwx/xy2hUYABjrwwGiFSa8/HMldGcL485wWDmvWzeGwRemFOypBTzEk8J3sFkTkns+5j7+dJLL3Vjx471FaFGjRrVMGwpj2vNso92BEij/c+fP9+Hk4XJ7NOmTXODBw/2uS78LhyPPPKI23PPPR3bkAejIQKdJCAB0km62nclCPAlx4sVAxzj9cknnwwSTRd7oy6Z78EqKKvtGB8kQpKUWoaREQMwDFfC2LWmijH7TIZTYEzbaj37tU7uJkzyWK3HWLSu9Mxf1UN9GvENcyXaFVAYYsmE32YNK+Gfdy4PRhHPBJ6DqlXrSntPh0nOPBMsKjSKk0/uDwGSrHoWegeTXcU73SyPOUDMWvhbp4+Xlm+W7XjHIj5g28x7w3yZdzC893m3mShJNk9MK0p4ns4++2w3adIkN3LkSIcHoSrv+LwECIzwiPAOZSGKIQ9IlrtU23aSgARIJ+lq35Uh8OGHH/rVM4yNxx57zLujrepVUnxYN21WFlkdrUtYQwg7FFCdDleyjuKWaG2d3E3YJVfr0xrG7JdykYT75CWgyrghufeouY+xSKJ2Wg9UmnNt1bAyaRi3CiFqdkxCfQhX4r7imSij7HQaHt1tw/2EJxBDLDbJOfQOhsLEijtYX56Qf145BdYfg4ppzEVagzuWX56fJ9yNfhdwxHuTJeE5FCVhsntSlBh73j9JRswT+Q8kXF977bX+31URH3DOU4BQgpeSviaYlQOS552sfcUQkACJoafP1oYAXzisePHlRRI6hpQZxggM/mCckRxMDX0MLHqC5GU0FAmKHBdWqvlCZbW9DAEVrtabMLHmfRgDsA9zSpKGsSXMcy2E+ZBwXiUDIc18cq9R259qa/RYoddKEcZidyFE3M9ZV+uZP8QHQp2V6izGYhpORWwTem9ahb+1ez7MN++VpKckz14Z9CsiLLSs/hjtsgk/Bx88HzwLiI88BDniw3J4GokSQufIh+B9yCIAIUZ4xUk8P+KIIyr3bslTgCBSeY9SXYzRqgrWXXfd5ctR1/E5z+P+1D6KIyABUhxrHalEAhhlvNQxEnDl80K2ClBW/ckS0skvwEOCgVyn0AauzXqUcA0kB1fp/MPmfSZKLLY+NIwxFjC0ukuYL/FWSnXosDt7FTrMNzKMbbUe8ZcUJZYTQe4U3hsEI4ZbHQW5hfrwNwZokb1WeCZ5vyRFieU1WB5VyL+RSGU/eAN5LqgQRZ+PuglyHhzeu4hZvKCI2U7eT+aZ5X0PO8KtWAwwTwBhtTvvvLMPUeJPlcR1dwKE55Y+KXw/IUQZhKlx3yTf93h4KLc7dOhQN3HixK53Fwnm5IBQytw6pFsfEHJACNPSEIFOE5AA6TRh7b90ArxYefnyBcMXDf0WwrjvJ554wicGk8jLqg8GQ9I4C1fri1jFzgoNg4Y8CcIz6tSjJGkY01zQjDO+TBFSrYyzrKw6vT2iivh8DB+8HlUs2ZxcrbdcHlutxzAmBJHVUgx2vIFVErNp55A5YLUdY70qBmajsrQIlGYhRLyTMBR5tsm9sdDRtAyqsh2hiDR75JlGCBb9HmVVn3Ak8mf428LAEEQ8s5wXvytT2E2YMMF3I+deuPjii/09y7kyBg4c6EPurGN6mFjONQwYMMANGjTIV9ZD2BFqdccdd3jv8XPPPefWW2+9rluBCna9e/f2nn5KDzPohA4jOqFzn2mIQKcJSIB0mrD2XzqBxx9/3JcU5MuFwQoiQgT3P8l5iBNe3jfddJMPBwiNMwwzW603A8ESrU2U5JFoHQOJL1IMXv6uqsHb6vpgzqoeIXB8KfJlac0TQ+PMOrmH8d1pkohbHT+v33OuGANcT5GN+fI4fzOMMYAwcrifzCvI/mEfVj3jvu9U1bM8rgdjiufCVturLKBa5TXAg4pdhPJZ0nWV2Sfnj7wbFkhY/MEzW/Qzy/EpL4tHb86cOW677bbrOkUWmzg3mpvyPVDm4LsJL1ejccsttzi6nTcSIIjTs846yz3//PM+x4lrQnhQZveCCy7w5bKTgzBdKn8tWLDA/6pfv35u9OjRXuRoiEARBCRAiqCsY5ROAPGA+52VIF7S1EgnCZKfExNu8cjbbLON4w/VcfiCt9Uwc+eHjfusLKp1EzdBwt8ImSJW0mgGx6oiITOsKhIqU7fBqjvXwLUQWsKXcMiuO/ZhSVrjX1RJ2iRnC1eyamt1rNYVlgpGzCIEwx4liPGwHHCy6hnsizYuG93v7733nk84R8zWtU+J9fjAS4gXirnBo2OlmE0QVlWM27xgMBMC9eUvf9m/V4t4L4b3BIsaGOJ4OebOnevvBw0REIHyCUiAlD8HOoOCCeB+phETyeaUXuTLHVHCH4wWvuD5cmcFGy+JiRJCH0LjyhKtw+pPYTfxUJBYN/G8LjUsJ8rqFiEynWrUldc5N9oPxi2r1BgHXAMrpGlGsiQtc2BJ7gjHZCf3dqs/pTkX5oJ7iT8Y7BjudVqdtmtkLghXQhBy7zfrtYIgTJYDRpQwTIyH/NNWPUvDutU2oScNg5cKcFUQRK3OO/l75oIeH1wPYTi2sNCqP0yVBCHnzqKPrdhTeaxo8YFnA88Hzz9J52FH8Kxzou1FQATyJSABki9P7a3iBDCUSApmZZREO4xFG3xhYsjiGSEOFkFCB1mrHoJxbAmL9jf7Cb9UwwpEFr6Vdz4J+6OJ2kcffeR69erl/xT9xZ7HNHP+JDgTGpNHh3m4YBibIAy7WlsDuVAU5pEAixBiLvB+xJZ2zYNpu/uwvhLMBeID0ZBlIFqSoqSRILQQrk4IQoxzDE7CKomDp5BEHZ8LQuAI4+P+ZAGklSeNezAMV+S+byYIrT9Mp0VZWPKYKnbWhTvLPRW7Le/uAw44wCdqk3CNINUQARGoDgEJkOrMhc6kIAKshH3ve99LFa6EKCGmFkFiogSBgpHAwPg3MYKnBEM6DL9qlE8SdvfNmk+CYYHHAKGTxWNQENpUhwnL0+K96WSIjDWQC0VJXoKQ0BgMRQxt5oL4/DoOC1dq1BU85nrCqmdWBQpmjEYdxVsZ2t2dC8fiueC5ZC6qmPifhiWinNh8hAJCsF2vZplNKzk2CwtcS6dKHrdiSWGRQw891Id8kfPRKAei1T6y/p538xVXXOEXsBA/5GWEieLd7Y93yK233upmz57tw1HJXyIUdd9993Xnn3/+Mt5IckGmTp3acJcsmFllq6zXoO1FoEgCEiBF0taxak8A45nVPWrxmyjhy8bCiMglwauCKLHQLSqKhPkklnAaJrinySfhC40VXgQOQifrKnUV4IcegzLK05ogDMPmQkEYxtXjLWmWaI2hy5yzkoyhWMfcmzBEpqhwpVYdxcNqcxjhabxUhD1aR23mAiFVx0ESNCGgCFlEVN5hfFm8VLBvJ4+NYyDKeb5IZk4bUpnXfHFPP/TQQ27w4MF+kem+++7zYq6IYaFmeFx4/9P8L60AQbDBa4cddnCUweUeQMhMnjzZCxH+HV6HCRBESNKbRdWsOn43FDFHOka1CEiAVGs+dDY1JMCXnpVeNS8J4VvkmvA7jFgMo1CUsEKVJZ8EYcPqMXH5GCd5NO8qGrV10+ZvS3Au+hwaHS8UhGETM0v2Zf5Cw5htKIuKQYAQTGMkV+E6w3OwVWpKoxIiQ35TGeFK9uyExR34d9i8LylKwvKt1iQRY51cCQRk3UaYQ8R7gbyVoubCwhbDPiVhHluyP0x3oXN4Zclb4fNlCEE4Tp8+3Z144olu7733djTUK9IQ5zuAQhqI+ayNBPkcnvZkBaqbb77ZHX/88e7KK690Z555ZtetbQKE+Su6nHHdni+db3UJSIBUd250ZjUmwJchq+R4R8J8EsJdGCQrJ/NJWLlN5pOwqmZlFTGyrEeGNY+ren8Sm0JyDAgt4csS46TqXXbDRGvzlpAYbAPRQZiP8W9ntbis27vqoWM8O9a8z9iHXiqMSrgj4Hk2uJfIlaijEOQ+Q8zyXqhKDpFV2wpFSXehc+QN8XvEB4Y3c1G0R5B7hjLqP/rRj3xnc0rWthu+lsdzmVWANDsmc8C9ftxxx/nrs2EChLniWSm7FHwezLSP5Y+ABMjyN+e64pII8CVJmEWYT8KXNkYWgxK0YT4JXz4nnHCC23777d348eN9aIk17gtzGkyUZM0nKQID12zd2fPOMSji/O0YGBSEXCGkiCfH+G2U5B72yahi3wlrzMd1IQSLCk+JnatknwzyC8woRrQ3Cp3rdKJ17DXx3Fr5aXIVqpwk3V3oHIY+1wJvkv8Juyry3ufewENA474f/vCH/l2Zd/ha1rnOS4DgRccjRrXGUaNGLSNAEHo80yyA4PUZM2aMKn1lnSxtXxoBCZDS0OvAyzsBvjj54uZLJswnwVPAyhZfojST2nnnnX3jLHJKyCfhi948Je3mkxTBnmsjpp2qRFTBQWBV3ShsxCUMHSNhPoxrZ55CMci/LckdIywZPlTmqixGOwYvHgTER0zSdxH3T6NjcL/TU4JmbTwbxNtb9S3Y46Wy0DmMs1AQltUfptF1cN+QK8G5l5Erkcf8IQB5tmkgynPNn/DeT4ZvdcJDZR3Dr7rqKp+sfdlll1XiHZOXACGX5bbbbvM5ToR72kCQwJoFK94z9LVCeHHP43Uvo+pYHveU9rF8EZAAWb7mW1dbcQJ8qZ9yyimO2N++ffv6BES+UEh6Z1h1nDCfhJXTMHSrzP4khpfrwGNAcj2VcDAU6zg++eQTfx1pQ8eSVc8sjMW8VBY+FDaP6/RqLee0cOFCfw9ZJ+pOH7MTcx0WMECIk7eSHGVWf0p7zZY0jwghbwWRWsdB3gLPhr2TLE8tDN1K5vMkRUmMIGeuzzjjDB+aRAfvc845p7DcmVbzlYcAmTRpkhs6dKjP/cDD02rMnz/f9e/fP3Xie6v96fci0GkCEiCdJqz9i0BKAhjteDtY7bruuut88iEDAxJDmMT2MMmdqlgMq7piogSjhmT17vqTYBhgADHyziexClEcv05hPslpsvK0sGSVut0V3GT4ECv1YUfrTjaPY4UYDxuhf6yKEiJTVIJzyts+1WbWoZ37Fi9UlpLHGINJo7jdROtUJ9vNRsw7YZd1Tprn8nj3ULmJPkg8G80EbZjPExZ4sCIDhA4lRUmapGruB5LN6eXEu5J/V+m+jhUgVO+iWe4+++zj7rnnntSJ5nwH4JUiN0pDBKpOQAKk6jOk81uuCFx++eVut912c9tuu2231225Fc8991yXKMGwwcBhUNkozCfBaMNVH4ZupcknsRCWtEmOGLok1bKqi2FSZCx4XjcKRjthPngNqEpkYW957Z/9WEfrMHwrbB4XGmWwbCfJnRANQq7IWyGOvK69AeiRgCjnevLyGIQNQ80wJs+BgdBMGsV53MfW7JG55Dry2Gee92TafZHTxTPOwgfezaxhlby7mNNQFCaLDIT8CSsKRQni8eijj3aPPvqo751Bv48qiQ84xggQ+lQNHDjQe8ApKZwlVJISvJT/tcWltHOq7USgDAISIGVQ1zFFIGcClk9CzkXoJcEAxXDDqEKEhKKE1fC88knClfZOGe05I2u4u9BoR3iQZ1DUsD4NoShJrtSHOSXdGSZhbwyEICvVdRzWFZxQHYz2TpZVNUEeGsbJppWhYZwlfMg8BmuttZYX5mlW+as2X2G5YMLfWOTIy/BPegmZA0QJ7xVCrc477zyfQ0YJcpoMEvo1c+ZM7yHI6xzy5N2uAOHaSCbnXf3YY49lrhbIvYW3HJGoIQJVJyABUvUZ0vmJQJsELPyB1eOwFDCr+wyMWYy6MJ+EVc1G+STWpwHjODSK2QfJvXTuJQGYaj51XWnn/EkMZvWwKkZ7uFJvwsRWN1lBD5Os+TdGsRntGLl17Y3B/fnBBx/4MJ+y+q20yufBkxEKwuRKvT22JMyTf9Oux6DNxz/Xj8GCUD4MW4QAuWmdNvwRHzyThBONHDnSe/NIeMe4Z+EEMWLNXvmbe70qwq47AYKo5Tq4d8LcOLzZu+++u6NBK0KkWUNNmHCdSQ/a3Xff7Q477DCfNzJx4sRc5187E4FOEJAA6QRV7VMEKkoAQwKxkMwnoSEdg4R26vjbFztf6hiAzfJJ2BcGr42880mKwsh1UH0MTxF5K1VtaGeN+0IvSZjoy/kjUJgHwq5Yca9jwrkZ7fTLoWllVa4hDB8Ke5RgLDO4b0yUIEgQUYTyYbBjuHfaaO/E88K1vfzyyz7vo6wFBvKxCEsijG3s2LG+BDPFOfiDMMHg5z1UdkL/hAkT/HlYdS7en4RFMTh/FjasY3rYJZ37nW3x+hCGy30fDv6/xx57+B+xSDJgwAA3aNAgn9PFM//MM8+4O+64w3tsETLJz3fivtA+RSCWgARILEF9XgRqToAvS4wkvrgQJvwhn4ScBAwmQpHC0C1WHvnSu+GGG9ydd97pRowY4VcjiaHvrj9J1nySIrBabxZWdzHWCX3IElpTxDm2OoaFr7zxxhuOUrvWl4F5tR4Z4Up92nyeVsftxO/Dlfa6GO22Uh92c+fZ4VoYrFTTO8buf0RK1ryJTrBOs0/Cn6z/Dc9GGYYt3oL99tvPh2LNnTvXC9JwIEYIPcWAL3twzyImGg2aI9JAsJEAefzxx90uu+zS9PR32mknxzYMhOBZZ53l39PWpBbhAaMLLrjA32saIlAHAhIgdZglnaMIFEgAw4kVxVdeeWWpfBLCYfg54oMwAYz2HXfc0ZfARICERlWV+5MYyjBvhZh2y4kpEHUuh8IwY64wTKybNvwxgpNGMQdknpI9MsitKHt13hrzIaLw3hSZf5PLRPzfTnhGWKUmFn+DDTbwP7UeJUn+JkqqwD/JgFAhwje5j+hBUUYeEZ4XPAeIZpKzee9oiIAI9AwCEiA9Yx51FSLQUQIWesIqHHXpySNhJRJRwqBULaFbYT4Jq6VZ80mK6iROmBIhV4RLVL0LdXcTG5anZT7WX3/9pptj4IcJ1sl8nmTlrbBqWkdvLue89wyjnfj2ZLPHTh87z/1zHRjt5ElhtONVs2FFBmwOQv6EmCX5E0ZXlijEq4AXtMxeJeStEb5EThmeDxNzec6X9iUCIlAeAQmQ8tjryCJQKwKIjf33398b7dOnT3e77rqrD/kJ80mIyeZnDFawk/kkrGSW1Z/EYLOii7GLQYiR2CzZs+qTY9eBsOA6EIFZB6vcoZcEo9iS3K0cbRi+1W4vlO7OC9GB0c51WLlcrBcAACAASURBVM5R1uuowvZcB0Y7Yp3rwMvUahj/UBhi/DMIpUuWA85SkrXVsZv93q6D3/P8lpEP9bOf/cwnVONZnTNnzlJCrt3ravU5nqcrrrjCvfDCCz63BI9imKfR6vP8nnfk8OHD3VNPPeU379evnxszZoy/juTIsm2aY2sbEagbAQmQus2YzlcESiJAzX068tIkq1koBGFNxDgn80mo+0/oD6E1oShh1R5Dq9P9SQwZ4oikVSoYkWzO33UcljSPlwJjN8/rCMvRWk5PsnFcKEpiEsQJU0IMduI6ipxXOCGiEGix84EXJdk4MVn5LBQmeYpCjouIYp88p0UInnCeEG8IjsGDB7sddtjBN+FLI+TymGvLzbDGrvTTyCJA8ArTvwmv12mnneZP6ZprrvELNnhzCPG0kWXbPK5N+xCBKhKQAKnirOicRKCiBDCEshg8GBSs8hLLHfYn4f+seGPgsHofJrn36tUr93wSzoPkUL74v/jFL/oVyaqU7Mw61dbssaik+WTjOOvkbpWfkp3c0ya5W28MPDfcA3VL/g9FLeF8iAJEbd7X0aryWbvdxJP3HRWmEIN4PBBRWZ7zrPdwo+25TopanHTSST6hmqpOeQrrVueI8Pv44499JcB2+njQuZxQMRLiLX+JssWEeNLbY8aMGV2nkGXbVuet34tAXQlIgNR15nTeIlBTApagTqhD2J/k7bff9ldESJQJEsspWXfdddvOJ8EgppLO+++/X+tyqHCjnwQVyzBwaARXVjUlq/yU7OTOOYZJ7rZSj1EberlYbaZqV517Y3CvUh4Wg5PKQ+SuxHiDsjzO1uMn5B92E4d3spt4d+dGGW48gyYGixbnXA9V9c4++2x31FFHuZtuuil3IZeFb1YBQvgWSfqEjU2dOnWpQ+FFoUcH4oZ3UZZts5yzthWBuhGQAKnbjOl8RaAHEsAAwQhCkISihFAjBlWqTIzwtzXYS5tPwj4wyEiMN8OsaCMrZtowiIgZJ4SMssjwqNrAo4URHOaUEHrHgLVV3mIbVtvrUma3EWfuVwQzwpYkaUILy0oYt/MLu4mHPUr4uZVjDos8mKcKEUUVNZ6NZDW7Iu4xzo88iUsvvdSdeuqpbty4cYUJuWbXl1WA0Iejb9++7vrrr/cenHDws5NPPtn36ujTp4//O+22RfDXMUSgLAISIGWR13FFQAS6JcAq+1tvvbVUPolVGGKVfauttloqn4T/Y+iaIfj000/70C8awLFCbbH1GMqMsGkcOQ1pQ4eKnjZyMgiNwZivW4WoMMmaWHiEh4VuWZJ7aBQXHfbTzlxiMOP1wHC3ssdli49m1wHrZDlmkszNU0W4GM8Fng9EVLJIRDt8snyG87vwwgvd1Vdf7S666CJ3ySWXlObVC887qwCZNWuWI6xq9uzZPnwsHPyM4h0zZ850Bx54oMuybRaW2lYE6kZAAqRuM6bzFYHllIDlkxAqEuaTsHqLIWOJ5XhICDeZOHGiN9jnzZvXlUwb9iexlXprGmehQ2GCddn9GThHxAcGLvkFRSXk5n2LhSIKoQjrMNEaocIgJyjkjzipkqfKepUQTlPX8s1WjhnvDUUAECHGn+fGPFXmKezUM4CRf/rpp7spU6b46lOU966KkMsqQKZNm+YT53nX9O/ff6nHh/4le+65p2MbwsuybJv3c6j9iUCVCEiAVGk2dC4iIAKZCFjDPfJJqLyFMHnsscd84zeqzhDu881vfnOpnBKS0KvanyS8eIvLZ1Ua8UGlqDoOBB6eq2blaS2fIQzd4t/mKbF8BhMmGMhl5L5YYz67p7iP6jjgigeHLtoWzofBnay8RS8TBgKwUTngGLFAMYshQ4a4e++9102aNMkdd9xxlREfXHNWAZLFq5Fl2zreXzpnEUhLQAIkLSltVyoBVu3Gjh3rJk+e7KgsQhIuX2DnnHNOqnhh1VwvdfoKOTgGE4bMXXfd5ZNZt99+e9+jhD/U9We1l0HuQVh1C+M+ucqLsWlx9Pa3lUJllT4MG8p7lT6s2EXyPXH5RSU35z1RVi4YZuTtpC3raknuYdM+81Rh+CY7uYdJ7nlfA/vj3kJEldmYL4/rCj04lMCmCECzwbUmG1cme8SYMEEcpg2fIwQMTwBNTfEGHHzwwZUSH+0IkCx5HVm2zWPOtQ8RqCoBCZCqzozOaykCJPGRzHfsscf6BD7i+2+55Raf3Hfttdd2S0s115ePm4kQCOKs6VdCPHY4MLwIOQn7kxDaRGgQxj1hQWEXd8Jr+Hna/iR55ZNgeL/22ms+v6DOSdqwZ4Wd8DjKBeOFig2lYg4RIWHlJ4xZRic7iePxQHzgdbHiB3V8oljV556HH/PRjgcn7BFj4iQMn0t6SpIliTk2zybnwbO61157VU58tCNAWlW2YlEEMZ6mCla4bR3vM52zCKQlIAGSlpS2K40AMf/0CaC5E8mKNogfHj9+vPv1r3/tY/2bDdVcL23qCj0wCeskOtNArdXAy8BqLv0bwnwSQlP4HYICz0jYNJHKU2HoT975JBhynA+emrrmF8AdLswFf+ipQHJzp0KmwtAhEybJTuJhTknWMDaS5nm/kF+E+Mj6+Vb3YVG/516nwSCeHK6DpPM8BnMN71AUIkys0ANV2+h/wTER+VdddZXvx3P//fe7HXfcMY9T6Mg+ugvB4jllMYP7KvQgkWBODggLCFRGY1gfEHJACL2ykWXbjlygdioCFSAgAVKBSdApdE/gggsucCNHjvQGTdiBmzKYNK07//zz3YgRIxrupNXKVFifXfOwfBPAmMKQSvYnwYhgsGIc9ifh39T+zyOfhApXFuKD2MZrUMcR5heUVSEq7CRuhnGjVXoTJs08M9Yokb40zEmsB6es+UR0ID4wqhHUnS5kYI0rYb9gwQIfOosX2sK3uC/ock7XcP7gjamKsJswYYJfxOA+vvjii71w+v73v++nbuDAgf5crWN6skv666+/7nr37u3fCcOGDfOfoRM6ng8WOci3sZFl27LuGx1XBDpNQAKk04S1/2gCrB6xColBkBzUrudLgg60jYbibaPxL9c7wJgilCjsT4JAwUhhIIDDfBIMVVbLQ1FipWgxyBrlk7A9PydcBa8LYSx1HKEHp1V+QZHX12qVPmzaZ+WYCYHDSFx//fUd19IpD06nObAAg/jg/BEf5DoVPRAflKHl2EcccYR79913fV4W3j5EEaGG1oS06HNLHo9zwUPTaBDy+4Mf/KCpAOEzXNPw4cO98GL069fPjR492guX5MiybdlcdHwR6AQBCZBOUNU+cyVAeBUJjhh+ycGXKoYPYVqNhiqO5DoVy/3OMGZZHaUjuYkSEtwRyKy8s0qOwRrmk7Dy2SyfBO+KJccb3LzySYqcLMJw8ODwdx08ON017TNuxOtT7MJESUzVpyLnwo6FSGZOSPznPVmGl4H3Mp4DQr4IT8LAt8G9ghFOSeN99tmnDEQ6pgiIQIkEJEBKhK9DpyOAyx5PB4nnyUFCOuVK33jjjYY7U831dIy1VfsEMGYRH4iQMJ+EFXR+Z2V0Q1FC7DgV3B599FE3depU7/kgVCasvJXsTxJW3upUb4Z2KBDzHyZpc711HKzGYxATMgNr8hgsyR0PQljxiX8nPV1VumaMeu5HzpN7K5kMXsS5Pvvss77x3iabbOI91HiTNERABETACEiA6F6oPAF5QCo/RTrBBAGEByvQeEdMlPBvQnsYlNdFOBOaQljHNtts48g1yCOfpMjJwNDFaEcQ1TlJG/GBwY43irLHZiwn+2MgEJNJ7qEwKcPLkJzv999/37388ss+F4HQnzJKONOL5/DDD/fesAcffNDf2xoiIAIiEBKQANH9UHkCVc8BabdHCYnHlIydPXu2DyFj5ZUQhX333dcn1udVqabyE7ycnCCiBE8BhhkFFUjApUwtRi1j8803XyqfBOOR8Jks+SSd7E+SnCZi+an4U6ahm8etg/eKecEDlSZ8zPpjhJWfLMEaAZLs5F6k92HhwoU+dwUPm3Wcz4NR2n1wj/M+Q1TvtNNO7p577vEewE6Pdt/BllDe7PwIqbQCBmzDdeGxbDQIp7TqV52+Xu1fBHoCAQmQnjCLPfwaMMZHjRrVkSpYedRcb7dHCc0RMTKpCIPIYlWcPBeaLSJE+HddE5J7+C3Z1uUx34hLDF6MNLweGE4YjGE+CR4FDFoMV1bjwyR38kkIB2rUnyTsJG5lUDuRT4KRScgjxhs5EpxT3fIjbAIJsUJ8kNeDB6edClGW5B42TQxL0eIdCoUhx8jbKxGWPibk6atf/Wrhc8I53H777b43E549/p228WRbD1TwoXbfwcw/3diTAzHB985+++3nn1UbJkAQIcnCBFTLKiPJP5adPi8CZRGQACmLvI6bmgChERgHzfqA0NQKQz6P+uypT+r/NozpUUL4ChWWkhVSbr75Znf88ce7K6+80p155plZT0nbV5TAE0884Tu0UxiBniKNhhmz3NNhPglJ7wyL6Q/zSei1EQqANP1J2s0nwVAnvIeKdBi5GLt1FR94MBAfFLjg/UJOR14jLEVrwoSGhvCDF16BMHQLodhupS2OhScKjxReNBYvip4TzuG6667zFaAw0m+88cbCyhbHvIObzfdPfvITd9FFF/ln1crwsq0JEL5r6lqWOa97XPsRgVgCEiCxBPX5QgicdNJJ7oYbbvCd0Lfffntf5pCyiEOHDnUTJ07055BHffasFxPTo6TZsTBYCOM47rjj3E033ZT1lLR9hQlggGY1NDHuyE2gdGkoSqwsNeE2oZfEGs11l0/CPUYIIANDysKG7O9GuQwYXQgjPotnhsIQdR00yMPThDcCXkWESTH3yU7u/J/BPcG5hOFbaQoNsE88ax988IFvXllGCBDnQKlZjHaaw9JsMOs9HnMfdeIdvMUWWziaULJAhEC1YQIEDyUhewjJIq81hpM+KwJVIyABUrUZ0fk0JEAy6JgxY3x4Eit9fNEOGTLEr7jZSlQzAcIOO1VzPSY/pdlUE5JD9+hzzz3Xh55piECSAKKEMJHnnnuuS5TQ74FVdgYGVChKKOSAqGg3nwQDnWcIEUJVpTrnJ1EIgI7366yzjoNL3uFQWe5WQuWSoVsYtiYMkzk9YUgTn8U7jKHMdZQhCBEf5513nqOB3yWXXOK9BkUb5Hm/g6m2yCLXqaee6saPH7/UdJoAQSzyrOE123vvvf13E9UaNURABNITkABJz0pbisAyBGIqdDXDOXjwYHfbbbf58BCSYjVEoBUBBAkGKYZ16CUhPAXRwCou92ooSgihypJPgnihGzxd2q03RtHGZisO3f0eRjS8e/PNN/0CBiK/6FClNOdvSe6hMAmT3BElhGxRRY2KXHhwmJOiB4tCGOmUOh83bpzv/l0Gz7zfwXjVJ02a5D2O5GmFg0UhnieeIwQ9pYYRKQgSqtwRkqghAiKQjoAESDpO2koEGhKI6VHSaId88fEFSO4HOSAaItAuAQxuVtMRsmEpYDpTMxARGK/J/iShEUmRBrwfrK7j9SBkqC79SUJuYZ4Ez+xmm21WirHczlxanxkrMkB5Z/7YYBU+WXmr014dCikQIvrAAw/4fA88A2WIDxjk+Q7muijBTF4VoW1pxvz5813//v3dMccc46ZMmZLmI9pGBETAOScBottABCII5Ln6dt9997mDDjrIdwWmfKWSHCMmRh9tSABjlnLPyXwSVtMZGF50zWbll1AljMujjz7ah9iYUYunhfCTsOpW1nySIqeH88UTRNEH8iS4xroOqjYRasc8UmaX1XgrBxwmueMhCcO38sxV4ByOOOII9+STT3pPLe+sssQH85jnO3j69Onu0EMP9SFVNApNOxDx9F8hZ0RDBEQgHQEJkHSctJUINCSQV/zxI4884gYOHOjo7P7QQw8VVr5S0yoCxPHTP4J8EhMmhJZg3H7jG9/woV1h6BYJ6IR0tZtPgmFclLgOE+epNkcIWV0Hgg/xAXtEYrLELfOIODBBwt/8H7FiSe7tVj8zZnheEBzkA1Ehivdf2SOvdzDXMWDAADdv3jyfX0Vxh7SDSlk0XLRQubSf03YisDwTkABZnmdf1x5NIKZHiR2c8qwkMrKSRwfhPBt3tdugqxEYGoux6nnkkUf6lU+NnkeAkK2jjjrK4Y2jwEOvXr28KOEPISnE/RP7jjEfihLKvyJIwv4khLOExnDYG6MT/UmSs2HhZxiFhJoRplTXQaI5Fch4N1AEIKzM1N01mbcqbJoYequsFLAJk2ShgnDfVNoaNGiQN84JvSJRuwojj3cw10FVOXKDCKdiESjL4HmgUh1sNERABNIRkABJx0lbiUBDArE9Slh13n333X1MOkJkzTXXzJV0uw26kidBx3b2xYqqBEiuU1SpndF4DRFM7gceORvW14IV+DCfhIRuBvkhrMqH+STkjRTVnyQJkXAkcl84PueF4KnrIDwOjwOJ5hi6sd4jvELJyluIRQbCxsQIXjES9cmJ4N/cG3B9+OGHvaCryoh9B9t1kHNHn567777bHXLIIctcHu8+2CdLVLP9YYcdtlRJ+Kqw0XmIQJUJSIBUeXZ0brUg0G6Pknfeecd/kfOlfvnlly9TRhMDbo899mibQV4Nugi7oNv1GWec4UtuSoC0PSWV/yD9dTBCt91225bniiihn0Yyn4RcCwZd0i2fhJwS7nVW8PPuT5I8UbwFGKUkZ3PMRj1NWl5cRTYgD+eVV17x7wZC3zpVdYxqWiZKLLeHpGryhTg2hjeek2uuucZ7QfL00uaBut13cHhsxB0eDDwhje4ZPFCEaHH9VJDjOXnmmWfcHXfc4e91FpPKKIWcBz/tQwTKICABUgZ1HbNHEWi3R8njjz/udtlll6YsCHlim3ZHXg26TjnlFEelF0Jw+GKWAGl3Rnr+58hDoB+P5ZMgTvCaYLxiPLOiHooSckyostUsn8SMYYutJ+8h2Rsj9AgQJoTwxpNICetYb0GZMwZHKpaVUTIYcUnH+9mzZ/vcBjwghLQhVJhHEuARqaeddlolvCHtvoNtfvGWcV8iZK6//vqG044wOeuss7zgJtkcTxLCA88Q71r6ymiIgAikJyABkp6VthSBWhHIIznzhRdecL179/ZGCHkqGIoSILW6DUo9WQxZDDWM2bA/Cf8nPwFBgVAI80nIOwlX+q0Mbat8EvaHAOm0t6DTQLlehAceUljwp4wqUzTkI+Gc48+dO9eHgOGNCT1e9P/YcccdO41E+xcBEeiBBCRAeuCk6pJEAAKx5SlZze7Tp4+vBnP//fd7qBIgurdiCWBgE0+PuA3zSWgSyMB7YYLEckrWXXfdpvkkCBNCwcxLklfFp9jrbOfzPHM0k2SFnbDHjTfeuJ3dRH2G+Xn00Ud9qV28AiSck+OjIQIiIAJ5EpAAyZOm9iUCFSIQ26Br4sSJPu+DVU+S5CVAKjS5PexUMHpJtkaQhKKEHAQGhriJEf4mt4PEcpKnBw8e7MU21bsQL636k4QVn6qEMexXQmhaljKweV0H80AFNJoM7rrrrm7mzJm1TuDPi4v2IwIikD8BCZD8mWqPIlAJAjEeEFaUWYE99dRT3aWXXtp1PfKAVGJql4uTwBvw1ltvLZVPQqw+uQh4Obg/2YZKXJRiPfPMM33OR175JEVCDvuVEJJWRj4B4mPatGmOnK8DDzzQl9pOW+63SFY6lgiIQM8gIAHSM+ZRVyECyxCIyQEhuZTqLiTBU03IBtVf9t9/f3fFFVd4Iyk2NCOPPiWUjKVTN6VKMaLw/Pzwhz/0ZTE1eg4ByychyZyiCNyDVGjbZJNNvFDhPqVHRphPsummm7aVT2Jekjw7iDebCbw4Jqzw7MQ+U+3MOGx5hs4991x3/PHHO7yfRSXwx7wDfvCDH7ipU6c2vGQqWpHAHw4KadDf5qmnnvI/7tevn+96ToUxDREQgWIJSIAUy1tHE4HCCMQ06KLUpOV9NDvhsWPH+rr5MSO2Twmr3ldffbWv20/VMEvgJbl55MiRMaemz1aUAAnaiGsqMtGTgiRp8kms8tYvf/lLn8DNWHvttZfKJ0Gc0A29UX8SC90ip+Svf/1rrh3Em6HEm8O5Y4STb7HaaqsVTh0vEs/KqFGjfJUnDPJOlfttdHEx7wATIIiQ5DnTnfzzn/981yG5b6jcRTI9CywMygojYgn7Y3FFQwREoDgCEiDFsdaRRKBQAjENuqhvTw+C5Dj44IPdDjvs4IYNG+abom2xxRZtX1Nsn5I5c+a4fffd13tqDj/88LbPQx+sF4Gjjz7aV2KaN2+e934kByKUkqnJfBI6VTPwioReErwmGKrt9CeJySeh/w8lildaaSV/PqGnsagZQfjg9bjuuuvcZZdd5svJFllxK/YdYAKEELZWHhsqelHNiyR/yucy8JJ8/etf9xX+ZsyYURR2HUcERICiNv/kba0hAiLQIwnk0aArBJNnDkhsnxLKf9JfghVvXmOsWpexgtwjb5wKXxQVtPB+4N1IOzC0yRUJ+5PQWI79IADoaxF2ccco5eedyidh1Z2wqzKbJWK0k++BgMeLSL5XkeKDuYt9B5gAoQIa3qRmIXO8G7hf6FieDNmi4SLdzGmgWbUGi2nvb20nAnUkIAFSx1nTOYtASgKxDbqSh8lTgMTkqGBQrL766j7Xg1wUQilY4aYKEjHshJTQ4E5DBBoRQLBitJI3FPYnYXWc31FhC89I2DSRSlzt9CdJ5pNQ4IHjcv+ScF7GfYrwwnh/6KGH3M033+zwKhUtPpiXmHcAnzcBwsIDHiUEHd4MwsjIBbOBR7dv376+ySCLMuHgZ4SBsQ1lxzVEQASKISABUgxnHUUERCBBIKZKF6vXJOwiPohhv+iii3zC6Z133unuueceNUvU3ZaZAMKD/I9kfxLCdBjkjoT9Sfg3q+pZ8klWWWUVv1KPwUypXVbcizb8Ee94Amg0yPNCvlfR52CTE/MOYB+Ej+HJYS5g++yzz7rx48d7vnhGLURv1qxZvqkind3pXB4OfkZhDUoOU/1LQwREoBgCEiDFcNZRREAEEgRi+pRQxYZcFMaTTz7Z9W/+v9tuu7mf/vSnvvs2oTUaItAuAUQJTQHDfBIECiFUDBLgw3wSPBqswjfKJ3n99dd9jxJCuwgJY5C3gCcEL0lMPkna6/vzn//sDXGejXvvvdftvvvuaT/ake1i3gHNTogKaf3793eEVk2ZMsVvRnlh+sWQN8TvwvHII494Twzb0EtGQwREoBgCEiDFcNZRREAEEgRiVj8xArfZZhufUGwdtG33GB3HHnusT6wlREtDBPIigCDB4/a73/2uS5Sw0k7BB8rpIijwbIT5JFRX+vGPf+wNflbiCesiNDJsmIjnxTq5U8HNxIgJk1YJ1mmuj8R8VvoRVA8++KD73ve+l+ZjHd0m5h3Q3YnB//333/fXypAHpKPTqJ2LQFsEJEDawqYPiYAIxBKIif/GmKJT9HbbbefDLsJBpRviwEeMGOEb1GmIQCcJIEoQH4iQMJ8Ejwe/Iy+J/KQBAwb40CeEM+GCeeSTpL2uP/zhD27gwIGOBH6eDzw1VRgx74Duzp8SvIgsE3XKAanCbOscRGBpAhIguiNEQARKIRDTp4QTDktphhcwefJkd8IJJ7gbb7zRDRkyJOraYpqkceDbb7/dx6SbMbr55pu7E0880Z9Xkb0WoiDow5kJIDw+/PBDd+ihh/oQQYQyuSRW2nq99dZbJp8EoZIln4Q8h9BTkiwlbCdNYj2eD7qaE4JUpX4Xse+AZhNDiXBEn+XvtKqCRTPTRYsWqQpW5jtdHxCB9glIgLTPTp8UARGIIBDTp4TDEtZCtZsHHnjA9wNhIBiodkOI1htvvOFDtGJGTJM0PDAXXnihjy9n9RmjlFCQn/3sZ77hG528NXomAQxeVuGfeOIJh3F7wAEH+Pl/9913l8onoQ8I4VcMxGmYT4IRTThWlv4kCBKSy2m2R44URjVJ5iTQIz5MtFeFesw7AG8OoWkkn4eDkrp4moYOHeo7utsgwRwGr732WleHdOsDwjPKs6khAiJQHAEJkOJY60giIAIJAjF9SljhJJyFWO/TTz/dffnLX3bTp093P//5z311HDo7x4zYJmnrrruur8JDWI4ZkeQPkANASIwlMsecoz5bTQILFy70wpM8pF122aXhSSJIEMx4xyzJnXwSSvQSOkR53q233nopUbLlllt6z1l3/UkoTUvXbwblhNkPnb85DwQOIqVKo913AJXwCGtDYOHVwcNDqBV9TRBa9HzB02QDzr179/aVy2ikyqB8NyIN/rDVEAERKI6ABEhxrHUkERCBBIHYPiWIj/POO8/3M2AlmVVkGqrlkXwe2ySNakhU5CIWPRwYpogbS5DVTdEzCSAuqHiVZSBK6NGBcR3mk5D0zkA80J8kTHJHeCe9JJTXHTdunBc4CGH2h1eG7WiyePHFF7tDDjkky6l1bNt23wHkgeFJfP755/2zRDlehAdldnl2KdGdHIi74cOHuwULFvhf9evXz40ePdrhbdIQAREoloAESLG8dTQREIGaEIhNkCUs7OGHH/ahVsTgY1zOmDHDG0cTJkzIRSTVBKVOM4IA9w3ePgztUJRggDMoxhCGbhHmxQr/Hnvs4e83ckMQIoQemaeFUryIYw0REAERKIuABEhZ5HVcERCBShOILRGKgUiH6UcffbTrOonpJzle/QYqPfWVPzlECfkLhBmZKCGfhG7gDHpdkBtFWJKGCIiACFSRgARIFWdF5yQCIlA6gdgmaaxakyhPPP8+++zjQ0RuvfVW3ySREBlWoTVEIA8Clk9CaN/VV1/trr32Wp//oSECIiACVSUgAVLVmdF5iYAIlEogxgNCyAsJr4gYEuNtYCgSd05CLCvY5IloiEBdCbRbpvq///u/vRifPXu2z4ciEZyKdYQtUpp3jTXWWAoJifVTp05tiInniL4qgiVJ7wAAEFRJREFUGiIgAvUiIAFSr/nS2YqACBREICYHhFK7u+66q6MkaDLZ98orr3Rnn322j+mnipeGCNSVQLtlqn/729/6xG9KBfOckShP6Wx6+CBE+HdYrcsECCIk2T+HcsfkuWiIgAjUi4AESL3mS2crAiJQEIGYJmmEWB1xxBG+JOjhhx++1BlTdYcywZQM7dOnT/TVUN2IRHeMNsq4kntyzDHHuClTpqTeNwYh1YGeeuop/xm8NPRYoQyshgg0IhBTpvrjjz/2lauS1aduvvlmd/zxxztE+plnntl1WBMghDHS+0NDBESg/gQkQOo/h7oCERCBDhCIaZL2q1/9yvf72GuvvXwlLBuUHMXrQQjWRx99lEvnZXqKbLbZZl3VkCj7m0WA0DNi22239c3r6BfBoD8CfUpIcK5S5+wOTLN22SaB2DLVjQ77l7/8xa2++uruuOOOczfddNMyAoR8qr///e/+uUl6Qtq8DH1MBESgJAISICWB12FFQASqT6DdJmlcGfHsc+bMcTvttJPvio34uO222xzihD4Ml1xySS4A/vGPfzhWlOkHwTFoPJdFgJAMP3fuXPfqq692dcq2DtF77723L+WqIQJJAjEhis1oIsy/9rWvLdNI1Dwgq622mq/0Re4U9yZeOvKsNERABOpHQAKkfnOmMxYBESiIQLtN0jg9hAGdsEm2feutt3w1rK222sr3/xgyZEhHriCrACF8i87Qhx122DJJvogYclgQN6w4a4hASCCmSEMzkoMHD+4S6d/61re6NiNkkfAr+p2sssoq7tlnn3Xjx493CBLCDjfZZBNNjgiIQM0ISIDUbMJ0uiIgAiLQjEBWAUIeSt++fd3111/v8PaEg5+RZJxXropmrWcRiC1TnaQxadIkN3ToUJ/7QQ5IqzF//nzf7ySLt6/VPvV7ERCB4ghIgBTHWkcSAREQgY4SyCpAZs2a5fuRUA51v/32W+rc+Bkd3GfOnOkOPPDAjp63dl4/Anl6QO677z5/H9Iv55577kmdaI5H5P333/cJ7RoiIAL1IiABUq/50tmKgAiIQFMCWQXItGnTHGEv8+bN86vJ4XjkkUd8iVS2Ued23XRJAnnlgHCfDRw40HviHnroIfe5z30uNWxyqyi6QHijhgiIQL0ISIDUa750tiIgAiKQmwCRB0Q3U7sEYspU2zGfeOIJn0yON+Wxxx7LnGtEGd9PPvnEN/XUEAERqBcBCZB6zZfOVgREQARyEyBF5YDE9CrJ2jVbt0cxBGLKVHOGzz33nNt99919CWmEyJprrtnwxP/2t7/5kCySz8NBgQSKJ5A3MnHixGIuWkcRARHIjYAESG4otSMREAERKJdA1hCsVlWw7rrrLrdo0aLMK9NJCjG9SrJ2zS53Bpavo7dbpvqdd95x3/72t31J3csvv9ytt956S4Hj/3vssYf/2YsvvugGDBjgBg0a5HvSrLzyyr4wAk0+N9poIy9kkp9fvmZBVysC9SQgAVLPedNZi4AIiMAyBLoTIJQxffPNN32jty996UtdnyXBnByQ1157zW244Yb+59YHhDh/wrRiR0yvkqxds2PPVZ9PT6DdMtWPP/6422WXXZoeiN45bMP405/+5M466yz3/PPP+2Rz7mOEB0UTaIa4zjrrpD9hbSkCIlAZAhIglZkKnYgIiIAItEdgwoQJvnP54sWLfZNDVpdJ0GWQ4EusvHkhkmVLaf7Wu3dv3w9k2LBh/jN0QsfzQSf0Lbfcsr2TavKprF6aZgdv1jU715PVzkRABERABDpCQAKkI1i1UxEQAREojsCmm27qCGtpNG655RZHJ+lmAoTPvPTSS2748OFuwYIFfhf9+vVzo0eP9sIl75GXAGnWNTvv89X+REAEREAE8icgAZI/U+1RBERABESgCYG8BEizrtkCLwIiIAIiUH0CEiDVnyOdoQiIgAj0GAJ5CJCsXbN7DDxdiAiIgAj0EAISID1kInUZIiACIlAHArECpN2u2XVgU9Q5fvrpp27s2LFu8uTJvuAASd1Dhgxx55xzjltppZVangaVyQjZe+qpp/y2hOyNGTPGbb311st8Nsu2LQ+sDURABHoMAQmQHjOVuhAREAERqD6BGAES0zW7+mSKO8OTTz7ZXX/99e7YY4/1HciffvppR64QP7/22mu7PZHf//73btttt3VrrbWWO+200/y2FC2gCAJFCyiVayPLtsVdvY4kAiJQBQISIFWYBZ2DCIiACCwnBNoVILFds1vhjWmW2GjflJJ98skn3ZFHHuluu+22Vocv7Pe/+c1v3Le+9S0vHq6++uqu455++ulu/PjxjgaDdCZvNg466CA3d+5c9+qrr3rPCcPKNtPVfMaMGV0fzbJtYQB0IBEQgUoQkACpxDToJERABERg+SDQTq+StF2zYwjGNEtMHvfWW2/13gS6eFdNgNA7Y+TIke6tt97yXchtvP32265Xr17u/PPPdyNGjGiIslXjSrqT07flC1/4gsuybcy86bMiIAL1JCABUs9501mLgAiIQK0ItNurJEvX7BggMc0Sw+MSikTvlDPOOMOdd955lRMgNJfEy0GDv+Sgozg9ZPBwNBp0ICdki/AtuqCHg58hutimT58+/u+028bMmz4rAiJQTwISIPWcN521CIiACNSKQLu9SrJ0zc4LSLthYhz/lFNOcfPnz3ckX6+yyiqVEyCEV6288sruhRdeWAbXd77zHd9pnDCtRmPWrFmOsKrZs2f7TuTh4Gf777+/mzlzpjvwwANdlm3zmjftRwREoD4EJEDqM1c6UxEQAREQgQIItCtAMOrpKv/ggw868iFWWGGFygmQr3zlKw5PB4nnyYHH4sMPP3RvvPFGQ8rTpk1z9F+ZN2+e69+//1LbUCAA7wrbHHXUUf7vtNsWMKU6hAiIQMUISIBUbEJ0OiIgAiIgAuUSaEeALF682IcefelLX3L333+/v4AqChB5QMq9t3R0ERCBJQQkQHQniIAIiIAIiEBAoB0BMnHiRJ/38corr3Qld1dRgCgHRLe6CIhAFQhIgFRhFnQOIiACIiAClSGQVYB89NFHPvH81FNPdZdeemnXdVRRgFDlatSoUR2pgnXXXXe5RYsWpaqCFW5bmYnXiYiACBRGQAKkMNQ6kAiIgAiIQB0IZBUg9NS44447HAnzq666atcl0pSPxOwrrrjCrbPOOm6NNdYo/fKpgEWlq2Z9QF588UX3zW9+0yejv/nmm2711Vf3YWU2SDAnB+S1115zG264of+x9QHBu0LyeTvblg5GJyACIlAoAQmQQnHrYCIgAiIgAlUnkFWADBo0qCvvo9m1jR071p199tmVuHRK6N5www2+E/r222/vFixY4DuhDx061BFKxrC+KMccc4ybMmVK13m//vrrPtF+7bXXdsOGDfM/pxM6ng86oeMJspFl20qA0UmIgAgURkACpDDUOpAIiIAIiEAdCGRtlkjPi/fee2+ZSzv44IPdDjvs4A11vApbbLFFJS6f6xszZoybPHmye/fdd70nY8iQIW748OHuM5/5TLcChF++9NJLfluEC6Nfv35u9OjR/hqTI8u2lYCjkxABESiEgARIIZh1EBEQAREQgaoTaLdZYrPrqmIOSNXnQOcnAiKwfBCQAFk+5llXKQIiIAIi0IJAu80SJUB0a4mACIhANgISINl4aWsREAEREAEREAEREAEREIEIAhIgEfD0UREQAREQAREQAREQAREQgWwEJECy8dLWIiACIiACIiACIiACIiACEQQkQCLg6aMiIAIiIAIiIAIiIAIiIALZCEiAZOOlrUVABERABERABERABERABCIISIBEwNNHRUAEREAEREAEREAEREAEshGQAMnGS1uLgAiIgAiIgAiIgAiIgAhEEJAAiYCnj4qACIiACIiACIiACIiACGQjIAGSjZe2FgEREAEREAEREAEREAERiCAgARIBTx8VAREQAREQAREQAREQARHIRkACJBsvbS0CIiACIiACIiACIiACIhBBQAIkAp4+KgIiIAIiIAIiIAIiIAIikI2ABEg2XtpaBERABERABERABERABEQggoAESAQ8fVQEREAEREAEREAEREAERCAbAQmQbLy0tQiIgAiIgAiIgAiIgAiIQAQBCZAIePqoCIiACIiACIiACIiACIhANgISINl4aWsREAEREAEREAEREAEREIEIAhIgEfD0UREQAREQAREQAREQAREQgWwEJECy8dLWIiACIiACIiACIiACIiACEQQkQCLg6aMiIAIiIAIiIAIiIAIiIALZCEiAZOOlrUVABERABERABERABERABCIISIBEwNNHRUAEREAEREAEREAEREAEshGQAMnGS1uLgAiIgAiIgAiIgAiIgAhEEJAAiYCnj4qACIiACIiACIiACIiACGQjIAGSjZe2FgEREAEREAEREAEREAERiCAgARIBTx8VAREQAREQAREQAREQARHIRkACJBsvbS0CIiACIiACIiACIiACIhBBQAIkAp4+KgIiIAIiIAIiIAIiIAIikI2ABEg2XtpaBERABERABERABERABEQggoAESAQ8fVQEREAEREAEREAEREAERCAbAQmQbLy0tQiIgAiIgAiIgAiIgAiIQAQBCZAIePqoCIiACIiACIiACIiACIhANgISINl4aWsREAEREAEREAEREAEREIEIAhIgEfD0UREQAREQAREQAREQAREQgWwEJECy8dLWIiACIiACIiACIiACIiACEQQkQCLg6aMiIAIiIAIiIAIiIAIiIALZCEiAZOOlrUVABERABERABERABERABCIISIBEwNNHRUAEREAEREAEREAEREAEshGQAMnGS1uLgAiIgAiIgAiIgAiIgAhEEJAAiYCnj4qACIiACIiACIiACIiACGQjIAGSjZe2FgEREAEREAEREAEREAERiCAgARIBTx8VAREQAREQAREQAREQARHIRkACJBsvbS0CIiACIiACIiACIiACIhBBQAIkAp4+KgIiIAIiIAIiIAIiIAIikI2ABEg2XtpaBERABERABERABERABEQggoAESAQ8fVQEREAEREAEREAEREAERCAbAQmQbLy0tQiIgAiIgAiIgAiIgAiIQAQBCZAIePqoCIiACIiACIiACIiACIhANgISINl4aWsREAEREAEREAEREAEREIEIAhIgEfD0UREQAREQAREQAREQAREQgWwEJECy8dLWIiACIiACIiACIiACIiACEQQkQCLg6aMiIAIiIAIiIAIiIAIiIALZCEiAZOOlrUVABERABERABERABERABCIISIBEwNNHRUAEREAEREAEREAEREAEshGQAMnGS1uLgAiIgAiIgAiIgAiIgAhEEJAAiYCnj4qACIiACIiACIiACIiACGQjIAGSjZe2FgEREAEREAEREAEREAERiCAgARIBTx8VAREQAREQAREQAREQARHIRkACJBsvbS0CIiACIiACIiACIiACIhBBQAIkAp4+KgIiIAIiIAIiIAIiIAIikI2ABEg2XtpaBERABERABERABERABEQggoAESAQ8fVQEREAEREAEREAEREAERCAbgf8PHWNBHjnaKqYAAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "# Plot meshgrid points in envelope\n",
    "ax.scatter(point_in_box_4[:,0], point_in_box_4[:,1], point_in_box_4[:,2], c = 'orange', alpha = 1, s = 8)\n",
    "ax.scatter(point_in_box_non4[:,0], point_in_box_non4[:,1], point_in_box_non4[:,2], c = 'blue', alpha = 0.2, s = 5)\n",
    "\n",
    "# Plot the \"envelope\"\n",
    "n_facet_4 = np.shape(hull_4.simplices)[0]\n",
    "n_facet_all = np.shape(hull_all.simplices)[0]\n",
    "facets_4 = np.zeros((n_facet_4,3,3))\n",
    "facets_all = np.zeros((n_facet_all,3,3))\n",
    "\n",
    "for i in range(n_facet_4):\n",
    "    for j in range(3):\n",
    "        facets_4[i][j] = point_4[hull_4.simplices[i][j],0:3]\n",
    "        \n",
    "for i in range(n_facet_all):\n",
    "    for j in range(3):\n",
    "        facets_all[i][j] = point_all[hull_all.simplices[i][j],0:3] \n",
    "\n",
    "for i in range(n_facet_4):\n",
    "    x = [facets_4[i][0][0],facets_4[i][1][0],facets_4[i][2][0]]\n",
    "    y = [facets_4[i][0][1],facets_4[i][1][1],facets_4[i][2][1]]\n",
    "    z = [facets_4[i][0][2],facets_4[i][1][2],facets_4[i][2][2]]\n",
    "    verts = [list(zip(x, y, z))]\n",
    "    ax.add_collection3d(Line3DCollection(verts, colors='red', linewidths=0.5))\n",
    "\n",
    "for i in range(n_facet_all):\n",
    "    x = [facets_all[i][0][0],facets_all[i][1][0],facets_all[i][2][0]]\n",
    "    y = [facets_all[i][0][1],facets_all[i][1][1],facets_all[i][2][1]]\n",
    "    z = [facets_all[i][0][2],facets_all[i][1][2],facets_all[i][2][2]]\n",
    "    verts = [list(zip(x, y, z))]\n",
    "    ax.add_collection3d(Line3DCollection(verts, colors='blue', linewidths=0.3))\n",
    "\n",
    "\n",
    "ax.set_xlim(xlim[0],xlim[1])\n",
    "ax.set_ylim(ylim[0],ylim[1])\n",
    "ax.set_zlim(zlim[0],zlim[1])\n",
    "ax.view_init(azim = view[0],elev = view[1])\n",
    "plt.savefig('Graphs/Grid points+Envelope_' + amine_name + '.svg', format = 'svg', transparent = True, dpi = 1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the class 4 convexhull only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "n_facet_4 = np.shape(hull_4.simplices)[0]\n",
    "n_facet_all = np.shape(hull_all.simplices)[0]\n",
    "facets_4 = np.zeros((n_facet_4,3,3))\n",
    "facets_all = np.zeros((n_facet_all,3,3))\n",
    "\n",
    "for i in range(n_facet_4):\n",
    "    for j in range(3):\n",
    "        facets_4[i][j] = point_4[hull_4.simplices[i][j],0:3]\n",
    "\n",
    "for i in range(n_facet_4):\n",
    "    x = [facets_4[i][0][0],facets_4[i][1][0],facets_4[i][2][0]]\n",
    "    y = [facets_4[i][0][1],facets_4[i][1][1],facets_4[i][2][1]]\n",
    "    z = [facets_4[i][0][2],facets_4[i][1][2],facets_4[i][2][2]]\n",
    "    verts = [list(zip(x, y, z))]\n",
    "    ax.add_collection3d(Line3DCollection(verts, colors='red', linewidths=0.5))\n",
    "\n",
    "ax.set_xlim(xlim[0],xlim[1])\n",
    "ax.set_ylim(ylim[0],ylim[1])\n",
    "ax.set_zlim(zlim[0],zlim[1])\n",
    "ax.view_init(azim = view[0],elev = view[1])\n",
    "plt.savefig('Graphs/Class 4 envelop_'+ amine_name + '.svg', format = 'svg', transparent = True, dpi = 1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nearest Neighbors to find purity of Class 4 envelope"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Building distance matrix (# meshgrid point in class 4 convexhull X # all point)\n",
    "distance = cdist(point_in_box_4, point_all[:,0:3], 'euclidean') # Calculate the distance between meshgrid point and all class in class 4 convexhull\n",
    "distance_class_ = np.concatenate((distance, [point_all[:,3]]), axis = 0) # Add the last row as class of all points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {},
   "outputs": [],
   "source": [
    "k = 5 # number of neighbor is considering\n",
    "threshold = 2 # dont't know how to use this yet\n",
    "\n",
    "# Finding the k-nearest neighbors for meshgrid point\n",
    "vote_list = []\n",
    "for i in range(np.shape(point_in_box_4)[0]):\n",
    "    lst = np.zeros((np.shape(point_all)[0],2))\n",
    "    lst[:,0] = distance[i]\n",
    "    lst[:,1] = point_all[:,3]\n",
    "    lst = list(lst)\n",
    "    lst.sort(key=lambda tup: tup[0])\n",
    "    lst = np.array(lst[:k])\n",
    "    if all(list(lst[:,1]).count(4) >= list(lst[:,1]).count(j) for j in [1,2,3]):\n",
    "        vote_list.append(4) # if vote is 4\n",
    "    else:\n",
    "        vote_list.append(0) # if vote is other than 4, set as \"0\"\n",
    "\n",
    "point_in_box_4_vote = np.zeros((np.shape(point_in_box_4)[0],4))\n",
    "point_in_box_4_vote[:,0:3] = point_in_box_4 # coordiation of point in class 4 convexhull\n",
    "point_in_box_4_vote[:,3] = vote_list # vote of point in class 4 convexhull"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fill factor is  0.47\n",
      "Fuzzy edge factor is  0.53\n"
     ]
    }
   ],
   "source": [
    "# \"Fill Factor\" (predicted class 4 over all) and \"Fuzzy Edege Factor\" (predicted non-class 4 over all) calculation.\n",
    "class4_num = 0\n",
    "class123_num = 0\n",
    "for i in point_in_box_4_vote:\n",
    "    if i[3] == 4:\n",
    "        class4_num += 1\n",
    "    else:\n",
    "        class123_num += 1\n",
    "FF = round(class4_num/(np.shape(point_in_box_4)[0]),2)\n",
    "FEF = round(class123_num/(np.shape(point_in_box_4)[0]),2)\n",
    "print(\"Fill factor is \", FF)\n",
    "print(\"Fuzzy edge factor is \", FEF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot real class 4 and fake class 4\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "img = ax.scatter(point_in_box_4_vote[:,0][point_in_box_4_vote[:,3] == 4], \\\n",
    "                 point_in_box_4_vote[:,1][point_in_box_4_vote[:,3] == 4], \\\n",
    "                 point_in_box_4_vote[:,2][point_in_box_4_vote[:,3] == 4], \\\n",
    "                 c = \"red\", s = 8, alpha = 0.5)\n",
    "img = ax.scatter(point_in_box_4_vote[:,0][point_in_box_4_vote[:,3] == 0], \\\n",
    "                 point_in_box_4_vote[:,1][point_in_box_4_vote[:,3] == 0], \\\n",
    "                 point_in_box_4_vote[:,2][point_in_box_4_vote[:,3] == 0], \\\n",
    "                 c = \"gray\", s = 5, alpha = 0.5)\n",
    "\n",
    "ax.set_xlim(xlim[0],xlim[1])\n",
    "ax.set_ylim(ylim[0],ylim[1])\n",
    "ax.set_zlim(zlim[0],zlim[1])\n",
    "ax.view_init(azim = view[0],elev = view[1])\n",
    "\n",
    "# fig.colorbar(img)\n",
    "plt.savefig('Graphs/Patriots and Traitors in Envelope_'+ amine_name + '.svg', format = \"svg\", transparent=True, dpi = 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "hide_input": false,
  "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": "3.7.3"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "position": {
    "height": "144px",
    "left": "1166px",
    "right": "20px",
    "top": "119px",
    "width": "350px"
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
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   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}