FlattenTheCurve.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python Dependencies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from ipywidgets import interact\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "plt.rcParams['figure.figsize'] = [6, 6]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Constants\n",
    "\n",
    "### $r_0$ = contagiousness ratio\n",
    "## $P$ = total population\n",
    "### $T$ = period of infectiousness in days\n",
    "\n",
    "# Functions\n",
    "\n",
    "### $G(t) =$ the number of \"sick\" or \"gestating\" people in the population\n",
    "### $R(t) =$ the number of \"recovered\" and dead people - i.e. those who were previously infected and are no longer contagious\n",
    "\n",
    "# Difference Equations\n",
    "\n",
    "## $\\frac{dR}{dt} = \\frac{r_0G(t)}{T}\\left(1-\\frac{R(t)}{P}\\right)$\n",
    "## $G(t) = R(t) - R(t-T)$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Integral Class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Integral:\n",
    "    def __init__(self, func, initial_condition=0):\n",
    "        self.func = func\n",
    "        self.initial_condition = initial_condition\n",
    "        self.lookup = {}\n",
    "        \n",
    "    def apply(self, t):\n",
    "        if t <= 0:\n",
    "            return self.initial_condition\n",
    "        if t not in self.lookup:\n",
    "            self.lookup[t] = self.apply(t-1) + self.func(t)\n",
    "        \n",
    "        return self.lookup[t]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DerivR:\n",
    "    def __init__(self, r0, T, P):\n",
    "        self._lookup = {}\n",
    "        self.R = Integral(self.apply).apply\n",
    "        self.G = lambda t: self.R(t) - self.R(t-T)\n",
    "        self.r0, self.T, self.P = r0, T, P\n",
    "        \n",
    "    def lookup(self, t):\n",
    "        \"\"\"\n",
    "        Lookup previously calculated\n",
    "        \"\"\"\n",
    "        if t <= 1:\n",
    "            return self.r0/self.T\n",
    "        return self._lookup[t]\n",
    "        \n",
    "    def apply(self, t):\n",
    "        if t not in self._lookup:\n",
    "            self._lookup[t] = (self.r0/self.T)*(self.R(t-1) - self.R(t-self.T-1))*(1-self.R(t-1)/self.P)\n",
    "\n",
    "        return self.lookup(t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_infection(r0, T, P, num_days):\n",
    "    deriv = DerivR(r0, T, P)\n",
    "    domain = np.linspace(0, num_days-1, num_days)\n",
    "    r = {x: deriv.R(x) for x in domain}\n",
    "    g = {x: deriv.G(x) for x in domain}\n",
    "    df = pd.DataFrame(data={\"Currently or Previously Infected\": r, \"Currently Infected\": g})\n",
    "    return df.plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_infection_scenarios(r0s, T, P, num_days):\n",
    "    data = {}\n",
    "    for r0 in r0s:\n",
    "        deriv = DerivR(r0, T, P)\n",
    "        domain = np.linspace(0, num_days-1, num_days)\n",
    "        r = {x: deriv.R(x) for x in domain}\n",
    "        g = {x: deriv.G(x) for x in domain}\n",
    "        data[f\"Previously Infected R_0={r0}\"] = r\n",
    "        data[f\"Infected R_0={r0}\"] = g\n",
    "    df = pd.DataFrame(data=data)\n",
    "    return df.plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def infection_slider(num_days=365, T=6.0, P=8_000_000, init_r0=1.3):\n",
    "    domain = np.linspace(0, num_days-1, num_days)\n",
    "    fig = plt.figure()\n",
    "    fig.suptitle(\"Corona Virus Simulation\")\n",
    "\n",
    "    ax = fig.add_subplot(1, 1, 1)\n",
    "    deriv = DerivR(3*init_r0, T, P)\n",
    "    r, = ax.plot(domain, np.array([deriv.R(x) for x in domain]))\n",
    "    g, = ax.plot(domain, np.array([deriv.G(x) for x in domain]))\n",
    "\n",
    "    def update(r0=init_r0):\n",
    "        deriv = DerivR(r0, T, P)\n",
    "        r.set_ydata(np.array([deriv.R(x) for x in domain]))\n",
    "        g.set_ydata(np.array([deriv.G(x) for x in domain]))\n",
    "        fig.canvas.draw_idle()\n",
    "\n",
    "    return interact(update)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot 3 Different Values of $R_0$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "\n",
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       "    var canvas_div = $('<div/>');\n",
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       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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       "        return fig.key_event(event, event['data']);\n",
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       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
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       "    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",
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       "\n",
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       "        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",
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       "\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",
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       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
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       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
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       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
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       "        return false;\n",
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       "\n",
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       "\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",
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       "\n",
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       "        return fig.toolbar_button_onmouseover(event['data']);\n",
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       "        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",
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       "\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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kAABAgQIECBAgAABAgQIEPhvAQMsd0XqAos7wCr9NFXpJ6NKr+effz423XTTheY8YMCA8m8X7NOnTzz66KPJdRdeeGEcf/zx5f8uPfuq9FHCr3/963HWWWeVn581ffr0uOWWW+JnP/tZ+ae8Sq/bb7+9/JFFLwIECBAgQIAAAQIECBAgQKC2AgZYtfUvZPTFHWCdeOKJccEFF8QGG2wQL7/88iLNLrvssvjRj35U/vjgxx9/nDzQ/eyzz47TTjstee8uu+wS9957b7Ro0aLReqXfVLj99tuXf4pro402Kj8ovvQTWV4ECBAgQIAAAQIECBAgQIBA7QQMsGpnX9jIizvA6tevXwwZMmSxvd55551YZZVVyu8rDcBKg7BPX88880z544gLen3729+Om2++ufyt0oPjSz+h5UWAAAECBAgQIECAAAECBAjUTsAAq3b2hY28uAOsrl27xujRoxfba+zYsbHWWmuV31d6wPsPfvCD8r936NAh3n333YWuN2jQoOT5WaV/P+KIIxY7tjcQIECAAAECBAgQIECAAAEClRMwwKqcpZWaKLC4A6wNN9wwXnnllejevXtce+21TYwS5Y8cfvqbCO+5557yA95Lr9JPXpV+Amthr8GDB5efj1V6lR7mXnoulhcBAgQIECBAgAABAgQIECBQOwEDrNrZFzby4g6wPv0NhOuuu2689tprS+Q2bty45KexSh8JLH00cGGvzw+7zj///DjhhBOWKKY3ESBAgAABAgQIECBAgAABApURMMCqjKNVFkNgcQdYpYeylx7OXnqY+ttvvx2rrbbaYkT77NI111wzxo8fH+3bt49p06Yt9OHsl156aRx77LHlN15//fUxcODAJYrnTQQIECBAgAABAgQIECBAgEBlBAywKuNolcUQWNwB1v333x+77bZbOULp43ylj/Utyev444+PCy+8sPzWf/7zn7HzzjsvcJnPPzS+NPDq0qXLkoTzHgIECBAgQIAAAQIECBAgQKBCAgZYFYK0TNMFFneAVVq5V69e8dRTT0WLFi3KPxW1//77LzTgCy+8EKUYe++9d6NrSsOo0nOxZs6cGZtuumkMHz68/NNYn3+VnrF18MEHl79UembWXXfd1fTCXEmAAAECBAgQIECAAAECBAhURcAAqyqsFv28QGlQ9PlnV7333ntx4oknli8pPd/qe9/7XiOwww477L8AX3/99ejZs2dMnTq1/L3ScGrAgAGx3nrrlYdapd8q+Oyzz8add94ZTzzxRPz0pz+NCy644L/WKT3T6qSTTip/vTTMOvnkk6P0TKzp06fHrbfeGldccUXMmzevPNgaOXJkeX0vAgQIECBAgAABAgQIECBAoLYCBli19S9E9NJA6uqrr25yrQ0NDQu89tVXX4199903Ro0a9aVrnXnmmfHLX/5ygdedcsopce6558bC4qyyyipx++23x9Zbb/2lcVxAgAABAgQIECBAgAABAgQIVF/AAKv6xoWPUKkBVgmy9NNRN954Y9xyyy0xYsSImDx5cvlrK620Uvknqvr27Rv77LNPbLHFFot0f/zxx8s/bTVs2LCYOHFitG3bNtZff/3o379/HHPMMbHccssVvm8ACBAgQIAAAQIECBAgQIBAVgQMsLLSCXkQIECAAAECBAgQIECAAAECBAgsUMAAy41BgAABAgQIECBAgAABAgQIECCQaQEDrEy3R3IECBAgQIAAAQIECBAgQIAAAQIGWO4BAgQIECBAgAABAgQIECBAgACBTAsYYGW6PZIjQIAAAQIECBAgQIAAAQIECBAwwHIPECBAgAABAgQIECBAgAABAgQIZFrAACvT7am/5GbOnBkvvPBCOfEOHTpEy5Yt668IGRMgQIAAAQIECBAgQIBA3QjMnTs3Jk+eXM530003jbZt29ZN7hJtuoABVtOtXNkEgREjRkTPnj2bcKVLCBAgQIAAAQIECBAgQIBAZQWeeuqp6NGjR2UXtVomBAywMtGG/CRhgJWfXqqEAAECBAgQIECAAAEC9SZggFVvHWt6vgZYTbdyZRME3nzzzVh77bXLV5Y2jo4dOzbhXS4hQIAAAQIECBAgQIAAAQJLJjBx4sTkk0Bjx46NtdZaa8kW8q5MCxhgZbo99Zfcv//97+jSpUs58QkTJkTnzp3rrwgZEyBAgAABAgQIECBAgEDdCDiH1k2rvlKiBlhfic+bvyhg43BPECBAgAABAgQIECBAgECaAs6haWrXLpYBVu3scxnZxpHLtiqKAAECBAgQIECAAAECmRVwDs1sayqamAFWRTktZuNwDxAgQIAAAQIECBAgQIBAmgLOoWlq1y6WAVbt7HMZ2caRy7YqigABAgQIECBAgAABApkVcA7NbGsqmpgBVkU5LWbjcA8QIECAAAECBAgQIECAQJoCzqFpatculgFW7exzGdnGkcu2KooAAQIECBAgQIAAAQKZFXAOzWxrKpqYAVZFOS1m43APECBAgAABAgQIECBAgECaAs6haWrXLpYBVu3sqxp59uzZ8be//S1uuummeP7552Pq1KnRqlWr6NSpU/Tp0yeOPPLI8t+Vftk4Ki1qPQIECBAgQIAAAQIECBBYlIBzaDHuDwOsHPZ53Lhxseeee8aLL764yOqOOeaYuPjii6NZs2YVU7BxVIzSQgQIECBAgAABAgQIECDQBAHn0CYg5eASA6wcNPHzJcyZMyc233zzZHjVrVu3OP7442ODDTaIGTNmxPDhw+N3v/tdfPTRR+W3nXPOOfGzn/2sYgo2jopRWogAAQIECBAgQIAAAQIEmiDgHNoEpBxcYoCVgyZ+voSbb745vv3tb5e/tPXWW8ewYcOiRYsWjap8+umny98rDbuWX375mDx5crRs2bIiEjaOijBahAABAgQIECBAgAABAgSaKOAc2kSoOr/MAKvOG/jF9Es/bXXhhReWv3zHHXfE3nvvvcAKv/Wtb8Vtt91W/l7pGVmbbrppRSRsHBVhtAgBAgQIECBAgAABAgQINFHAObSJUHV+mQFWnTfwi+n/6Ec/issuu6z85VGjRkXXrl0XWOGJJ54YF1xwQfl7I0eOjC233LIiEjaOijBahAABAgQIECBAgAABAgSaKOAc2kSoOr/MAKvOG/jF9C+99NI49thjy19uyk9glR7gPm3atGjfvn1FJGwcFWG0CAECBAgQIECAAAECBAg0UcA5tIlQdX6ZAVadN/CL6b/33nux7rrrxvTp02ObbbaJoUOH/tczsJ599tno3bt3zJ49Ow466KC49tprK6Zg46gYpYUIECBAgAABAgQIECBAoAkCzqFNQMrBJQZYOWjiF0so/eTVwIED4+OPPy7/RsLjjjsu1l9//fjwww/j0UcfLf8WwtJvJNxiiy3innvuiVVXXbXJCqWNYVGviRMnRs+ePcuXTJgwITp37tzktV1IgAABAgQIECBAgAABAgQWV8AAa3HF6vN6A6z67NuXZv3yyy+XB1VXXnllNDQ0NLq+NLA65ZRT4sgjj4x27dp96Vqfv6D0kcOmvgywmirlOgIECBAgQIAAAQIECBBYUgEDrCWVq6/3GWDVV7+alG3po4FnnHFGDBo0KCZPnrzA92y11VZx2mmnRf/+/Zu05qcXGWAtFpeLCRAgQIAAAQIECBAgQKDKAgZYVQbOyPIGWBlpRKXS+Oijj2L33XePYcOGlZ999dOf/jQOP/zwWGeddWLmzJnx5JNPxllnnRXDhw+P0jCq9JsIjz/++CaH9xHCJlO5kAABAgQIECBAgAABAgRSEDDASgE5AyEMsDLQhEqmcOKJJ5aHUqXXVVddFYceeuh/LT937tzYdddd4+GHH47mzZvHM888E927d69IGjaOijBahAABAgQIECBAgAABAgSaKOAc2kSoOr/MAKvOG/j59EvPulp55ZVj6tSp5Ye2v/LKKwutrvQw9759+5a/X3rI+4UXXlgRCRtHRRgtQoAAAQIECBAgQIAAAQJNFHAObSJUnV9mgFXnDfx8+pMmTYqOHTuWvzRgwIC44YYbFlpd6eOESy21VPn7X//61+Pee++tiISNoyKMFiFAgAABAgQIECBAgACBJgo4hzYRqs4vM8Cq8wZ+Pv333nsvOnToUP7SvvvuGzfffPNCq5sxY0a0b9++/P299tor7rzzzopI2DgqwmgRAgQIECBAgAABAgQIEGiigHNoE6Hq/DIDrDpv4OfTnz9/fqywwgoxffr0WH311WPcuHHRsmXLBVZ41113xd57713+3jHHHBOXXHJJRSRsHBVhtAgBAgQIECBAgAABAgQINFHAObSJUHV+mQFWnTfwi+kfeOCB8fe//7385TPOOCNOP/30/6rw/fffLz//avTo0eXvDR48uPxQ90q8bByVULQGAQIECBAgQIAAAQIECDRVwDm0qVL1fZ0BVn3377+yf/nll2PLLbeMjz/+uPy90k9ZlX4T4TrrrBOl51498cQTcdFFF8X48ePL399pp53igQceqJiCjaNilBYiQIAAAQIECBAgQIAAgSYIOIc2ASkHlxhg5aCJXyyhNJAaOHBglJ6JtajXjjvuWH5OVuljh5V62TgqJWkdAgQIECBAgAABAgQIEGiKgHNoU5Tq/xoDrPrv4QIrmDJlSlx55ZXl3y744osvxrRp08rPw1pttdWiR48eUfqoYf/+/aNZs2YVFbBxVJTTYgQIECBAgAABAgQIECDwJQLOocW4RQywitHn1Kq0caRGLRABAgQIECBAgAABAgQIRIRzaDFuAwOsYvQ5tSptHKlRC0SAAAECBAgQIECAAAECBliFuQcMsArT6nQKNcBKx1kUAgQIECBAgAABAgQIEPiPgHNoMe4EA6xi9Dm1Km0cqVELRIAAAQIECBAgQIAAAQIGWIW5BwywCtPqdAo1wErHWRQCBAgQIECAAAECBAgQ+I+Ac2gx7gQDrGL0ObUqbRypUQtEgAABAgQIECBAgAABAgZYhbkHDLAK0+p0CjXASsdZFAIECBAgQIAAAQIECBD4j4BzaDHuBAOsYvQ5tSptHKlRC0SAAAECBAgQIECAAAECBliFuQcMsArT6nQKNcBKx1mU6gk0NDREw/zSn4j5yb83RENDRJT+fMVXQyUWKeVQgVy+YineToAAAQIECBAgUCCBZs2bRdulW2WyYufQTLal4kkZYFWctNgL2jiK3f8sVj9n9rx4d+z0eO+tD2P6e5/EjCkzY9bHc2P2zLkx+5PSn3lRuqZhXkN5YGUwlMUuyokAAQIECBAgQKDWAit1XiYO+EXPWqexwPjOoZlsS8WTMsCqOGmxF7RxFLv/Wam+NJAaM+KdePmxifHO2Okxf74fV8pKb+RBgAABAgQIECBQnwIGWPXZtzxlbYCVp25moBYDrAw0ocAplAZVz94/Lp69f3z5p6y8CBAgQIAAAQIECBCojIABVmUcrbLkAgZYS27nnQsQMMByW9RK4KMPZsU///JivPXKtFqlIC4BAgQIECBAgACB3AoYYOW2tXVTmAFW3bSqPhI1wKqPPuUty6lvfxS3X/hMfDJjzgJLKz1wcqVOS8eKHZeO9isvFUst2ypaL9UyWrdtWf67VZsW0bx5syhd16x5/Offm/3nv5u3+PTfo/y1LL0ylk6WaORCgAABAgQIECBQYQEPca8wqOUWW8AAa7HJvGFRAgZY7o+0BUoPY7/pnJEx7Z2P/yv0Gl1XjK7bdorOG65QHlZ5ESBAgAABAgQIECCQPwHn0Pz1dEEVGWAVo8+pVWnjSI1aoIhoaGiI+698MV4b+W4jj2VWaBO7HNE1Vv/a8pwIECBAgAABAgQIEMi5gHNozhv8/8szwCpGn1Or0saRGrVAETHqkbdi6PWvNLLosMay0f/YzaLtMq0YESBAgAABAgQIECBQAAHn0AI0OSIMsIrR59SqtHGkRl34QKWPDl59ymMx+5PPfttgm3YtY/+f9yg/58qLAAECBAgQIECAAIFiCDiHFqPPBljF6HNqVdo4UqMufKAXhvw7HtuvmlIAACAASURBVLnh1UYOexy1aazdvUPhbQAQIECAAAECBAgQKJKAc2gxum2AVYw+p1aljSM16kIHapjfENef+WSjB7ev1W3l2PPoboV2UTwBAgQIECBAgACBIgo4hxaj6wZYxehzalXaOFKjLnSg8S9OiTsvfa6RQf/jNosuG65YaBfFEyBAgAABAgQIECiigHNoMbpugFWMPqdWpY0jNepCByoNr0pDrE9fK66+dBxwWs9o1qxZoV0UT4AAAQIECBAgQKCIAs6hxei6AVYx+pxalTaO1KgLG+iDyR/Htac90aj+HQ7aILpu26mwJgonQIAAAQIECBAgUGQB59BidN8Aqxh9Tq1KG0dq1IUN9PzDE2LYP8Yk9Zd+8+Ch52wTrdq0KKyJwgkQIECAAAECBAgUWcA5tBjdN8AqRp9Tq9LGkRp1YQPd98cX4vVnJyf1b9h7tdjpsI0L66FwAgQIECBAgAABAkUXcA4txh1ggFWMPqdWpY0jNepCBmpoaIi/nDg8Zn44J6l/x0M2io36dCykh6IJECBAgAABAgQIEIhwDi3GXWCAVYw+p1aljSM16kIGmvL2h3HDWU81qv3gs7eO9isvVUgPRRMgQIAAAQIECBAgYIBVlHvAAKsonU6pTgOslKALGuaFIf+OR254Nal+mRXbxCG/7uO3Dxb0flA2AQIECBAgQIAAgZKAc2gx7gMDrGL0ObUqbRypURcy0OA/j4rXnn43qX2DXqvFzod7/lUhbwZFEyBAgAABAgQIEPj/As6hxbgVDLCK0efUqrRxpEZduECl51/99aTh8cmMz55/1e/gDWPjbVYvnIWCCRAgQIAAAQIECBD4TMA5tBh3gwFWMfqcWpU2jtSoCxfo/UkfxfVnPNmo7u/8qncs16Fd4SwUTIAAAQIECBAgQICAAVbR7gEDrKJ1vMr1GmBVGbjAy4965K0Yev0ricDSy7eJQ8/x/KsC3xJKJ0CAAAECBAgQIFAWcA4txo1ggFWMPqdWpY0jNerCBXrgqtHxyhOTkrrX77lq7PLdroVzUDABAgQIECBAgAABAo0FnEOLcUcYYBWjz6lVaeNIjbpwgW4+d2S8M3Z6Unffb68X3XfqUjgHBRMgQIAAAQIECBAgYIBVxHvAAKuIXa9izQZYVcQt+NKDfvpIzPpobqKw5w+7xVqbrlxwFeUTIECAAAECBAgQIOAcWox7wACrGH1OrUobR2rUhQo086M5ceVPhzWq+aAze8fyq3qAe6FuBMUSIECAAAECBAgQWICAc2gxbgsDrGL0ObUqbRypURcq0KSxH8Qt5z6d1NysebP4/qXbR4sWzQvloFgCBAgQIECAAAECBP5bwDm0GHeFAVYx+pxalTaO1KgLFeiVJyfFA38dndS8XIel4ju/2rpQBoolQIAAAQIECBAgQGDBAs6hxbgzDLCK0efUqrRxpEZdqEBP3flGjLj7zaTmNbquFHsf071QBoolQIAAAQIECBAgQMAAq8j3gAFWkbtfhdoNsKqAasm4/8oXY8yIdxKJbv06x7YD1idDgAABAgQIECBAgACBcA4txk1ggFWMPqdWpY0jNepCBbrpnBHx7rgZSc3bDlgvuvXrUigDxRIgQIAAAQIECBAgsGAB59Bi3BkGWMXoc2pV2jhSoy5MoIaGhvJvIJz18dyk5r2O6R5rdl2pMAYKJUCAAAECBAgQIEBg4QLOocW4OwywitHn1Kq0caRGXZhAMz+cE1eeMKxRvd/5Ve9YrkO7whgolAABAgQIECBAgAABA6yi3wMGWEW/AypcvwFWhUEtF5Pe+CBuOe/pRKJ582bx/Uu3j+YtmtMhQIAAAQIECBAgQICAZ2AV5B4wwCpIo9Mq0wArLenixHnliYnxwFUvJQUvv2q7OOjM3sUBUCkBAgQIECBAgAABAosUcA4txg1igFWMPqdWpY0jNerCBHryjjdi5D1vJvWuuelKsdcPuxemfoUSIECAAAECBAgQILBoAefQYtwhBljF6HNqVdo4UqMuTKD7B42KMSPfTerttmPn2Hb/9QtTv0IJECBAgAABAgQIEDDAcg9EGGC5CyoqYIBVUU6LRcSNvxkRk8fPSCy2O2D92HSHzmwIECBAgAABAgQIECBQFnAOLcaNYIBVjD6nVqWNIzXqwgQadPwjMevjuUm9ex/bPdbYeKXC1K9QAgQIECBAgAABAgQWLeAcWow7xACrGH1OrUobR2rUhQg0d/a8+OOxQxvVeuAZvWKF1ZYuRP2KJECAAAECBAgQIEDgywWcQ7/cKA9XGGDloYsZqsHGkaFm5CCVGVNnxt9+/lijSo743bbRdulWOahOCQQIECBAgAABAgQIVELAObQSitlfwwAr+z2qqwxtHHXVrswn++646XHTOSOTPJs3bxY/uGyHaNasWeZzlyABAgQIECBAgAABAukIOIem41zrKAZYte5AzuLbOHLW0BqX8+YL78Xdlz2fZLH0cq3jsHP71jgr4QkQIECAAAECBAgQyJKAc2iWulG9XAywqmdbyJVtHIVse9WKfumxifHQ315K1l+5yzIx4NSeVYtnYQIECBAgQIAAAQIE6k/AObT+erYkGRtgLYma9yxUwMbh5qikwDODx8Xjt72eLNll4xWj/7GbVTKEtQgQIECAAAECBAgQqHMB59A6b2AT0zfAaiKUy5omYONompOrmibw6M1j4l8PTEguXr/XqrHL4V2b9mZXESBAgAABAgQIECBQCAHn0EK0OQywitHn1Kq0caRGXYhAD1w1Ol55YlJSa/edu0Tf/dYrRO2KJECAAAECBAgQIECgaQLOoU1zqverDLDqvYMZy9/GkbGG1Hk6d176rxj/4tSkiq33WTe22G3NOq9K+gQIECBAgAABAgQIVFLAObSSmtldywAru72py8xsHHXZtswmfeNvRsTk8TOS/HY8ZMPYqM/qmc1XYgQIECBAgAABAgQIpC/gHJq+eS0iGmDVQj3HMW0cOW5uDUq7+pRH48P3ZyWR9/xht1hr05VrkImQBAgQIECAAAECBAhkVcA5NKudqWxeBliV9Sz8ajaOwt8CFQNoaGiIPxwzJObPbUjW3O9nW8Wqa7WvWAwLESBAgAABAgQIECBQ/wLOofXfw6ZUYIDVFCXXNFnAxtFkKhd+icCsT+bGoJ880uiqg3+9dbRfaSl2BAgQIECAAAECBAgQSAScQ4txMxhgFaPPqVVp40iNOveBpr3zcVx3+hON6vyfS7aPVq1b5L52BRIgQIAAAQIECBAg0HQB59CmW9XzlQZY9dy9DOZu48hgU+o0pYmvTYtbL3gmyb5VmxbxPxdvX6fVSJsAAQIECBAgQIAAgWoJOIdWSzZb6xpgZasfdZ+NjaPuW5iZAt54dnLc+8cXknzar9w2Dj67T2bykwgBAgQIECBAgAABAtkQcA7NRh+qnYUBVrWFC7a+jaNgDa9iuaMeeSuGXv9KEmHVtdvHfidvVcWIliZAgAABAgQIECBAoB4FnEPrsWuLn7MB1uKbecciBGwcbo9KCYy4e2w8defYZLm1uq0cex7drVLLW4cAAQIECBAgQIAAgZwIOIfmpJFfUoYBVjH6nFqVNo7UqHMf6JEbXo0Xhvw7qXPjbTpGv4M3yn3dCiRAgAABAgQIECBAYPEEnEMXz6terzbAqtfOZTRvG0dGG1OHaQ3+86h47el3k8y3/Pqa0fub69ZhJVImQIAAAQIECBAgQKCaAs6h1dTNztoGWNnpRS4ysXHkoo2ZKOL23z8Tb706Lcml77fXi+47dclEbpIgQIAAAQIECBAgQCA7As6h2elFNTMxwKqmbgHXtnEUsOlVKvn6M5+M9yd+lKy+y3c3jvV7rlalaJYlQIAAAQIECBAgQKBeBZxD67Vzi5e3Adbiebn6SwRsHG6RSglcecKwmPnhnGS5/j/eLLpstGKllrcOAQIECBAgQIAAAQI5EXAOzUkjv6QMA6xi9Dm1Km0cqVHnOtD8efPjih8NiWj4rMwBv+gZK3deJtd1K44AAQIECBAgQIAAgcUXcA5dfLN6fIcBVj12LcM52zgy3Jw6Su3j6bPjrycNb5TxYeduE0sv16aOqpAqAQIECBAgQIAAAQJpCDiHpqFc+xgGWLXvQa4ysHHkqp01K2bKWx/GDb96qlH8oy7bIZq3aF6znAQmQIAAAQIECBAgQCCbAs6h2exLpbMywKq0aMHXs3EU/AaoUPkTXp4ad1z0r2S1tku3iiN+t22FVrcMAQIECBAgQIAAAQJ5EnAOzVM3F16LAVYx+pxalTaO1KhzHej1Z96N+/40KqlxuVWWiu+ctXWua1YcAQIECBAgQIAAAQJLJuAcumRu9fYuA6x661jG87VxZLxBdZLeS4+9HQ/97eUk2w5rLBv7/7xHnWQvTQIECBAgQIAAAQIE0hRwDk1Tu3axDLBqZ5/LyDaOXLY19aKee2hCDL9xTBK30wbLxzd/skXqeQhIgAABAgQIECBAgED2BZxDs9+jSmRogFUJRWskAjYON0MlBEbeMzaevGNsstTa3VeOPY7qVomlrUGAAAECBAgQIECAQM4EnENz1tCFlGOAVYw+p1aljSM16lwHeuyW1+LZf45Paly/16qxy+Fdc12z4ggQIECAAAECBAgQWDIB59Alc6u3dxlg1VvHMp6vjSPjDaqT9IZc/0q8+MhbSbabbN8pth+4QZ1kL00CBAgQIECAAAECBNIUcA5NU7t2sQywamefy8g2jly2NfWi7r/yxRgz4p0k7ha7rRlb77Nu6nkISIAAAQIECBAgQIBA9gWcQ7Pfo0pkaIBVCUVrJAI2DjdDJQTuvuy5ePOFKclSvb6xTmy1+1qVWNoaBAgQIECAAAECBAjkTMA5NGcNXUg5BljF6HNqVdo4UqPOdaDbfvdMvD1mWlLjtgPWj279Oue6ZsURIECAAAECBAgQILBkAs6hS+ZWb+8ywKq3jmU8XxtHxhtUJ+n949dPxXsTPkyy3emwjWLD3h3rJHtpEiBAgAABAgQIECCQpoBzaJratYtlgFU7+1xGtnHksq2pF3XtaY/HB5M/SeLu/v1NY53NO6Seh4AECBAgQIAAAQIECGRfwDk0+z2qRIYGWJVQzMgaO+ywQwwdOnSxsnn44Yej9L5KvWwclZIs9jp/OXFYfDJjToLQ/7jNosuGKxYbRfUECBAgQIAAAQIECCxQwDm0GDeGAVaO+ry4A6zmzZvH+PHjo1OnThVTsHFUjLLQC/3hmCExb878xGC/n20Vq67VvtAmiidAgAABAgQIECBAYMECzqHFuDMMsHLU57Fjx8ZHH320yIpGjx4dAwYMKF+zyy67xP33319RARtHRTkLudi8efPjDz8c0qj2A8/oFSustnQhPapZdENDQ3w89+OYNmtaTJs5Ld6f9X58MOuD+GTuJzFr3qyYOXfmf/6eNzNmzZ1V/vd5DfNifsP8Rf+J+eXrSut/8bXAr8UCrlvA1774pYYmvm9BMavpam0CBAgQIECAQB4F1mi/RpzZ58xMluYcmsm2VDwpA6yKk2Z7wZNPPjnOO++8cpLXXHNNfOc736lowjaOinIWcrGZH82JK386rFHth/12m1h6+TaF9KhE0aWB0xvT3oiXpr4U46aPa/SnNMDyIkCAAAECBAgQIPBlAhussEHc3P/mL7usJt93Dq0Je+pBDbBSJ69dwPnz58caa6wRb731ViyzzDLxzjvvRLt27SqakI2jopyFXGz6e5/ENb94vFHtR160XbRu27KQHkta9IzZM2LIhCHx4PgH4+l3ni7/lJUXAQIECBAgQIAAgSUVMMBaUjnvq5SAAValJOtgnX/+85+x6667ljM97LDD4q9//WvFszbAqjhp4Rac8taHccOvnvqs7mYRR1/eL5o1a1Y4iyUp+JWpr8RVL14Vg98cHHPmf/Yg/CVZy3sIECBAgAABAgQIfCpggOVeqLWAAVatO5Bi/IMPPjiuvfbacsSHHnoo+vXrV/HoBlgVJy3cghNfmxa3XvBMUnfrti3iyIu2L5zD4hY8fvr4+O1Tv41hbzX++GVT12nZvGUs32b58p92rdpF2xZto02LNtG2Zdto3aJ1+b9Lf5eua9GsRXmgWPq7ebPmn/2J5tGi+f//WjQvX1P654uvhQ0jF3Rt6b2LM7ysxBpNNXMdAQIECBAgQKBIAiu0WSG+vvbXM1myc2gm21LxpAywKk6azQU//PDDWG211coPeV9zzTWj9MD3xTkUNrUqG0dTpVy3MIFxo6bEXf/7XPLtZVZoE4eesw2whQiUfsrq6hevjj8894fyQ9YX9Vq13aqx/grrx5rt14y12q8Vay63ZnRaulOs0HaFWLrV0lXZEzSOAAECBAgQIECAQLUFnEOrLZyN9Q2wstGHqmdx9dVXlz82WHqdeuqpcfbZZy9RzNLGsKjXxIkTo2fPnuVLJkyYEJ07d16iON5UXIExI9+J+we9mACssFq7OPCM3sUFWUTlpedc/WTIT+LJiU8u8KpWzVtFn9X7xE5r7BS9OvaK1ZdZnSMBAgQIECBAgACB3AkYYOWupQssyACrGH2OnXbaqfyxwdLrlVdeifXXX3+JKl+cn9oywFoi4sK/afTwt+Pha19OHFZdu33sd/JWhXf5IsDEDyfG0Q8eHa9Ne+2/bFZsu2IM3HBgDNhgQPmnq7wIECBAgAABAgQI5FnAACvP3f2sNgOsAvS59D9z6WODpd9C2Lt373j88ca/4W1xCAywFkfLtUsi8K8HxsejN382lOmy0QrR/8ebL8lSuX3P5I8nx4H3HBiTPprUqMbS858O2uig+NHmPyp/JNCLAAECBAgQIECAQBEEDLCK0OUIA6wC9Pm3v/1tnHLKKeVKr7jiivjBD36wxFX7COES03ljEwWeumtsjLhrbHL1Opt3iN2/v2kT353/y2bOnRnfHfzdeOG9FxoVW/qpq4v7XRybrbJZ/hFUSIAAAQIECBAgQOBzAgZYxbgdDLAK0OeuXbvG6NGjo02bNlF6RtUKK1TvI0U2jgLcUFUucfjNY+K5ByYkUTbcerXY6dCNqxy1PpZvaGiIk4edHPeOvbdRwusst05cttNl0XlZz5yrj07KkgABAgQIECBAoJICzqGV1MzuWgZY2e1NRTIbOXJk9OjRo7zWvvvuGzfffHNF1l3YIjaOqvIWYvGHr3kpRj86Mam1W7/Ose2AJXtmW97A/vHyP+LsJxv/AoZOy3SK6/e8Pko/geVFgAABAgQIECBAoIgCzqHF6LoBVs77fOyxx8all15arvKOO+6Ivffeu6oV2ziqyluIxQcPGhWvjXw3qXXL3deM3t9YtxC1L6rI9z55L/rf1j9mzJmRXLZMq2Xi2j2ujXWX51P4GwQAAQIECBAgQKDAAs6hxWi+AVaO+zxnzpzo1KlTTJ48OTp06BBvv/12tGzZsqoV2ziqyluIxe+89LkY/+KUpNat91k3tthtzULUvqgiTx1+atzx+h2NLil9bHC7ztsV3gYAAQIECBAgQIBAsQWcQ4vRfwOsHPe59BNX3/jGN8oV/vjHP46LLrqo6tXaOKpOnPsAt57/dEx8/YOkzu0Hrh+bbF/sZzuNnDQyDh98eKPe77XOXnHOtufk/n5QIAECBAgQIECAAIEvE3AO/TKhfHzfACsffVxgFfvtt1/ccsst5e89/fTTscUWW1S9WhtH1YlzH+CGXz0VU976MKlz58M3jg16rZb7uhdWYOnB7QfcfUCMnjI6uaT00cE797kzVl5q5cK6KJwAAQIECBAgQIDApwLOocW4Fwywctrn999/Pzp27BizZs2KTTbZJF544YVUKrVxpMKc6yB/O/WxmDFlZlLjHkd3i7W7FXdQM2LSiPju4O826vkpPU+JAzc6MNf3geIIECBAgAABAgQINFXAObSpUvV9nQFWffdvodn/4Q9/iKOOOqr8/fPOOy9OPPHEVCq1caTCnOsgV/50WMz8aE5S4zd/snl02mCFXNe8qOKOeeiYGDJhSHJJl2W7xJ3fvDNaNG9RWBOFEyBAgAABAgQIEPi8gHNoMe4HA6yc9nmbbbaJxx57LFq0aBHjx4+P1VdfPZVKbRypMOc2SOnjcn/40ZCYP68hqXH/n/eIDmssm9uaF1XYuOnjYu/b9o6G+MzDT18V8lZQNAECBAgQIECAwCIEnEOLcXsYYBWjz6lVaeNIjTqXgebOmRd/PGZoo9oOOqt3LL9Ku1zW+2VF/fqJX8cNr9yQXLZs62Xjgf0eiHatiunxZV6+T4AAAQIECBAgUEwB59Bi9N0Aqxh9Tq1KG0dq1LkM9MmM2fGXE4c3qu3w8/pGu/atc1nvooqaPnt67HzTzvHJ3E+Syw7f5PA4fsvjC2ehYAIECBAgQIAAAQKLEnAOLcb9YYBVjD6nVqWNIzXqXAb6YPLHce1pTzSq7fuXbB8tWxfveU+3v3Z7nPboaYlFi2Yt4r5974vVli7ub2TM5U2vKAIECBAgQIAAga8s4Bz6lQnrYgEDrLpoU/0kaeOon15lMdPJ42fEjb8ZkaTWvHmz+MFlO0SzZs2ymG5Vc/rhgz+MR/79SBKjX5d+ccmOl1Q1psUJECBAgAABAgQI1KOAc2g9dm3xczbAWnwz71iEgI3D7fFVBN4e837c9rtnkyXatGsZ3/v9dl9lybp874ezP4zt/rFdzJn/2W9j/E3f38Te6+5dl/VImgABAgQIECBAgEA1BZxDq6mbnbUNsLLTi1xkYuPIRRtrVsSbz78Xd1/+fBJ/2RXbxiG/6VOzfGoV+O437o6fDftZEr5l85bxyIBHovQQdy8CBAgQIECAAAECBBoLOIcW444wwCpGn1Or0saRGnUuA7361KT4519GJ7Wt1GnpOOC0XrmsdVFFHffwcfHg+AeTS7bttG1cvvPlhXNQMAECBAgQIECAAIGmCDiHNkWp/q8xwKr/HmaqAhtHptpRd8mMeuStGHr9K0neq62zXOx70pZ1V8dXSfjjOR+XPz44a96sZJmz+pwV+6y3z1dZ1nsJECBAgAABAgQI5FbAOTS3rW1UmAFWMfqcWpU2jtSocxnomfvHxeO3vp7UtkbXFWPvYzbLZa0LK2rwm4PjhKEnJN8u/fbBIfsPieXbLl8oB8USIECAAAECBAgQaKqAc2hTper7OgOs+u5f5rK3cWSuJXWV0JN3vBEj73kzyflrW64Sux25SV3V8FWTPe3R0+L2125Pltm649bxp13/9FWX9X4CBAgQIECAAAECuRVwDs1taxsVZoBVjD6nVqWNIzXqXAYaduOr8fxD/05q22ibjrHjwRvlstaFFbXHrXvEhBkTkm+f3OPk+M7G3ymUgWIJECBAgAABAgQILI6Ac+jiaNXvtQZY9du7TGZu48hkW+omqYf+9lK89NjEJN/uO3aJvvuvVzf5f9VE3/343djppp0aLXPT3jfFhitu+FWX9n4CBAgQIECAAAECuRVwDs1taxsVZoBVjD6nVqWNIzXqXAa6f9CoGDPy3aS2Lb++ZvT+5rq5rHVBRd039r448ZETk28t22rZGHbAsGjRvEVhDBRKgAABAgQIECBAYHEFnEMXV6w+rzfAqs++ZTZrG0dmW1MXid1zxfMx9rn3klx79V8nttpjrbrIvRJJnv3E2fGPV/6RLLVtp23j8p0vr8TS1iBAgAABAgQIECCQWwHn0Ny2tlFhBljF6HNqVdo4UqPOZaA7LvlXTBg9Naltm/2+FpvtvEYua11QUd+641sx5v0xybeO2+K4OGLTIwpTv0IJECBAgAABAgQILImAc+iSqNXfewyw6q9nmc7YxpHp9mQ+uVsveDomvvZBkuf2A9ePTbbvnPm8K5HgB7M+iL439G201DW7XxObrbJZJZa3BgECBAgQIECAAIHcCjiH5ra1jQozwCpGn1Or0saRGnUuA934mxExefyMpLYdD9koNurTMZe1frGoh8c/HMc+fGzy5bYt2sZjAx+LVi1aFaJ+RRIgQIAAAQIECBBYUgHn0CWVq6/3GWDVV78yn62NI/MtynSC15/5ZLw/8aMkx12/1zXW22rVTOdcqeQuGHFBXD366mS5nqv1jCt3u7JSy1uHAAECBAgQIECAQG4FnENz29pGhRlgFaPPqVVp40iNOpeBrvnFYzH9vZlJbXsc3S3W7rZyLmv9YlEH3n1gvPDeC8mXj+p+VBy92dGFqF2RBAgQIECAAAECBL6KgHPoV9Grn/caYNVPr+oiUxtHXbQps0n+9aTh8fH02Ul+/X+8WXTZaMXM5lupxObOnxs9r+sZc+bPSZb80y5/iq1X37pSIaxDgAABAgQIECBAILcCzqG5bW2jwgywitHn1Kq0caRGnctAfz5uaMyeOS+p7VsnbBEdv7Z8Lmv9fFGvT3s9vvl/32xU57ABw2L5tvmvPffNVSABAgQIECBAgEDVBZxDq06ciQAGWJloQ36SsHHkp5e1qOSKHz4c8+c1JKH3/3mP6LDGsrVIJdWY9469N0565KQk5irtVokHv/1gqjkIRoAAAQIECBAgQKBeBZxD67Vzi5e3Adbiebn6SwRsHG6RJRWYP78hrjj64UZvH3h6r1ix49JLumTdvO/iZy6OQS8MSvLdttO2cfnOl9dN/hIlQIAAAQIECBAgUEsB59Ba6qcX2wArPetCRLJxFKLNVSly9sy58efjHmm09sG/3jrar7RUVeJladGjHzg6hr01LEnpiE2OiOO2PC5LKcqFAAECBAgQIECAQGYFnEMz25qKJmaAVVFOi9k43ANLKvDJjNnxlxOHN3r74ef1jXbtWy/pknXzvp1v2jne+fidJN9ztz039lhnj7rJX6IECBAgQIAAAQIEaingHFpL/fRiG2ClZ12ISDaOQrS5KkVOn/JJXHPq443WPvKi7aJ125ZViZeVRT+Y9UH0vaFvo3Ru639bfG2Fr2UlRXkQIECAAAECBAgQk/WFnAAAIABJREFUyLSAc2im21Ox5AywKkZpoZKAjcN9sKQC70/6KK4/48lGbz/qsh2ieYvmS7pkXbxvxKQR8d3B301ybdW8VTx50JNR+tuLAAECBAgQIECAAIEvF3AO/XKjPFxhgJWHLmaoBhtHhppRZ6lMHj8jbvzNiCTr5s2bxVGX96uzKhY/3eteui5++9RvkzduuOKGcdPeNy3+Qt5BgAABAgQIECBAoKACzqHFaLwBVjH6nFqVNo7UqHMXaOLrH8St5z+d1NW6bYs48qLtc1fnFws647Ez4pYxtyRf7r9u//h131/nvm4FEiBAgAABAgQIEKiUgHNopSSzvY4BVrb7U3fZ2TjqrmWZSXjCy1Pjjov+leSzVPvW8d3zGj8bKjPJVjCRgXcNjFFTRiUrnrDVCXFo10MrGMFSBAgQIECAAAECBPIt4Bya7/5+Wp0BVjH6nFqVNo7UqHMXaOzz78U9lz+f1LXsSm3jkF/3yV2dny9o3vx50fv63jFz3szky3/a5U+x9epb57puxREgQIAAAQIECBCopIBzaCU1s7uWAVZ2e1OXmdk46rJtmUh6zMh34v5BLya5rLBauzjwjN6ZyK1aSbz5wZux9+17N1p+yP5DYqWlVqpWSOsSIECAAAECBAgQyJ2Ac2juWrrAggywitHn1Kq0caRGnbtALz8+MR68+qWkrg5rLBv7/7xH7ur8fEFDJwyNHz30o+RLK7ZdMYYOGJrrmhVHgAABAgQIECBAoNICzqGVFs3megZY2exL3WZl46jb1tU88VGPvBVDr38lyaPjusvFt07csuZ5VTOBa0dfG+eOODcJ0b1D97h2j2urGdLaBAgQIECAAAECBHIn4Byau5YusCADrGL0ObUqbRypUecu0L8eGB+P3vxaUleXjVaI/j/ePHd1fr6gc548J65/+frkS3uts1ecs+05ua5ZcQQIECBAgAABAgQqLeAcWmnRbK5ngJXNvtRtVjaOum1dzRMfec+b8eQdbyR5rNVt5djz6G41z6uaCRz9wNEx7K1hSYijuh8VR292dDVDWpsAAQIECBAgQIBA7gScQ3PX0gUWZIBVjD6nVqWNIzXq3AV64v9ej6fvHZfU9bWtVondvrdJ7ur8fEF737Z3vDn9zeRLv+n7m9h73cYPdc81gOIIECBAgAABAgQIVEDAObQCiHWwhAFWHTSpnlK0cdRTt7KV6/Cbx8RzD0xIktpw69Vip0M3zlaSFcxm3vx50eO6HjFn/pxk1b/t/rfYfJV8f2yygoSWIkCAAAECBAgQIFAWcA4txo1ggFWMPqdWpY0jNercBSo9wL30IPdPX5ts1ym2P3CD3NX5aUETP5wYu96ya6P6Ht7/4Vh5qZVzW7PCCBAgQIAAAQIECFRDwDm0GqrZW9MAK3s9qeuMbBx13b6aJv/g1aPj5ccnJTlstnOX2Ga/9WqaUzWDPzXxqTji/iOSEEu1XCqePPDJaNasWTXDWpsAAQIECBAgQIBA7gScQ3PX0gUWZIBVjD6nVqWNIzXq3AUa/OdR8drT7yZ1bbXHWtGr/zq5q/PTgm4dc2uc/tjpSX3rrbBe3Nr/1tzWqzACBAgQIECAAAEC1RJwDq2WbLbWNcDKVj/qPhsbR923sGYF3H358/Hm8+8l8Xt9Y53Yave1apZPtQNf/MzFMeiFQUmYHbvsGBfveHG1w1qfAAECBAgQIECAQO4EnENz19IFFmSAVYw+p1aljSM16twF+r+Lno1/v/x+Utc2+30tNtt5jdzV+WlBJww9IQa/OTip79CND40TepyQ23oVRoAAAQIECBAgQKBaAs6h1ZLN1roGWNnqR91nY+Oo+xbWrIBbz386Jr7+QRK/9AD30oPc8/oacNeAGD1ldFLeL3r9IgZsOCCv5aqLAAECBAgQIECAQNUEnEOrRpuphQ2wMtWO+k/GxlH/PaxVBTf+ZkRMHj8jCb/TYRvFhr071iqdqsft8/c+MWP2Z/X+cec/Rp9OfaoeVwACBAgQIECAAAECeRNwDs1bRxdcjwFWMfqcWpU2jtSocxfo+jOeiPcnfZzUtduRm8TXtlwld3WWCvpg1gfR94a+jWq7Z597okv7LrmsV1EECBAgQIAAAQIEqingHFpN3eysbYCVnV7kIhMbRy7aWJMi/vbzx2LG1JlJ7D2P7hZrdVu5JrlUO+io90bFwLsHJmFaNGsRI74zIlo1b1Xt0NYnQIAAAQIECBAgkDsB59DctXSBBRlgFaPPqVVp40iNOneB/nLisPhkxpykrv7HbRZdNlwxd3WWCrp37L1x0iMnJbV1WqZT3LfvfbmsVVEECBAgQIAAAQIEqi3gHFpt4Wysb4CVjT7kJgsbR25amXohfzpuaMyZOS+J+60Tt4yO6y6Xeh5pBPzz83+OS569JAnVu2Pv+POuf04jtBgECBAgQIAAAQIEcifgHJq7li6wIAOsYvQ5tSptHKlR5y7QFUc/HPPnNyR17X9qj+jQZdnc1Vkq6MzHz4ybX705qW3f9faNM/qckctaFUWAAAECBAgQIECg2gLOodUWzsb6BljZ6ENusrBx5KaVqRYyb978+MMPhzSKeeAZvWKF1ZZONY+0gv3wwR/GI/9+JAl39GZHx1Hdj0orvDgECBAgQIAAAQIEciXgHJqrdi60GAOsYvQ5tSptHKlR5yrQ7E/mxp9/8tlAp1TcIb/pE8uu2DZXdX5azP537h8vTX0pqe3MPmfGt9b7Vi5rVRQBAgQIECBAgACBags4h1ZbOBvrG2Blow+5ycLGkZtWplrIx9Nnx19PGt4o5nfP7xtLLds61TzSCrb9P7aPqTOnJuGu2PmK6Nupb1rhxSFAgAABAgQIECCQKwHn0Fy1c6HFGGAVo8+pVWnjSI06V4Gmv/dJXPOLxxvVdORF20Xrti1zVWepmDnz5sQW127RqK5b+t8S66+wfu5qVRABAgQIECBAgACBNAScQ9NQrn0MA6za9yBXGdg4ctXO1IqZOvGj+PuZTzaKd9Tl/aJ582ap5ZBWoLc/fDt2u2W3RuGGHzA8lmuTz9+4mJarOAQIECBAgAABAsUVcA4tRu8NsIrR59SqtHGkRp2rQO+Omx43nTMyqal5y2Zx1P/2y1WNnxbzr3f/FQffe3BSW5sWbWLEQSOiWbP8Dety2UBFESBAgAABAgQIZE7AOTRzLalKQgZYVWEt7qI2juL2/qtU/vZr0+K2C55Jlmi9VMs48sLtvsqSmX3v4DcHxwlDT0jy67xM57h333szm6/ECBAgQIAAAQIECGRdwDk06x2qTH4GWJVxtMr/F7BxuBWWRGDC6KlxxyX/St7arn3rOPy8fD7U/NrR18a5I85Nat1ilS3i6t2vXhI27yFAgAABAgQIECBAICKcQ4txGxhgFaPPqVVp40iNOleBxj43Oe654oWkpvYrt42Dz+6Tqxo/Leb3I38ff33xr0ltu6+1e5y3/Xm5rFVRBAgQIECAAAECBNIQcA5NQ7n2MQywat+DXGVg48hVO1MrZszId+L+QS8m8VZcfekY+MteqcVPM9DJj5wc94y9Jwl56MaHxgk9PvtIYZq5iEWAAAECBAgQIEAgDwLOoXno4pfXYID15UauWAwBG8diYLk0EXjpsbfjob+9nPz3KmsuG98+pUcuhQ6/7/AY+c5nD6w/casT45Cuh+SyVkURIECAAAECBAgQSEPAOTQN5drHMMCqfQ9ylYGNI1ftTK2YF4b8Ox654dUkXsevLRffOmHL1OKnGWjPW/eM8TPGJyHP3/78+PpaX08zBbEIECBAgAABAgQI5ErAOTRX7VxoMQZYxehzalXaOFKjzlWgZ/85Ph675bWkpi4brxj9j90sVzWWimloaIie1/WMmfNmJrVd/fWrY4tVt8hdrQoiQIAAAQIECBAgkJaAc2ha0rWNY4BVW//cRbdx5K6lqRQ08p6x8eQdY5NYa3dfOfY4qlsqsdMM8sGsD6LvDY1/u+K937o3Oi/bOc00xCJAgAABAgQIECCQKwHn0Fy1c6HFGGAVo8+pVWnjSI06V4GeuP31ePq+cUlN6/VYNXY9omuuaiwV89r7r8U+d+zTqK6nv/N0tG7ROne1KogAAQIECBAgQIBAWgLOoWlJ1zaOAVZt/XMX3caRu5amUtDwG8fEcw9NSGJt1Kdj7HjIRqnETjPIY289Ft9/4PtJyBXarBCPHPBImimIRYAAAQIECBAgQCB3As6huWvpAgsywCpGn1Or0saRGnWuAg257uV4cdjbSU2bbt8pthu4Qa5qLBVz25jb4peP/TKpa4MVNoib+9+cuzoVRIAAAQIECBAgQCBNAefQNLVrF8sAq3b2uYxs48hlW6te1ANXjY5XnpiUxNlslzVim32/VvW4aQf443N/jP/91/8mYbfttG1cvvPlaachHgECBAgQIECAAIFcCTiH5qqdCy3GAKsYfU6tShtHatS5CnTfn0bF68+8m9S01R5rRa/+6+SqxlIxv3r8V3Hjqzcmde273r5xRp8zclengggQIECAAAECBAikKeAcmqZ27WIZYNXOPpeRbRy5bGvVi7r7sufizRemJHF6f3Od2PLra1U9btoBjnnwmBjy7yFJ2KO6HxVHb3Z02mmIR4AAAQIECBAgQCBXAs6huWrnQosxwCpGn1Or0saRGnWuAt1+4bPx1ivvJzX1/fZ60X2nLrmqsVTMgLsGxOgpo5O6Tt/69Nhv/f1yV6eCCBAgQIAAAQIECKQp4ByapnbtYhlg1c4+l5FtHLlsa9WLuuW8kTHpjelJnB0O2iC6btup6nHTDrDTjTvFu5989lHJy3a6LLbrvF3aaYhHgAABAgQIECBAIFcCzqG5audCizHAKkafU6vSxpEada4C/ePXT8V7Ez5Matr5sI1ig94dc1VjQ0NDbHHtFjF3/tykrr/v+ffYZOVNclWnYggQIECAAAECBAikLeAcmrZ4beIZYNXGPbdRbRy5bW1VC7vu9Cdi2jsfJzF2O3KT+NqWq1Q1ZtqLz5g9I/r8vU+jsPfte190WiZ/P2mWtq14BAgQIECAAAECxRZwDi1G/w2witHn1Kq0caRGnatAV//80fhw6qykpj1/2C3W2nTlXNU4fvr42PO2PRvV9OSBT0a7Vu1yVadiCBAgQIAAAQIECKQt4Byatnht4hlg1cY9t1FtHLltbVULu/KEYTHzwzlJjG/8ZPPovMEKVY2Z9uL/evdfcfC9Bydhl2q5VDx10FNppyEeAQIECBAgQIAAgdwJOIfmrqULLMgAqxh9Tq1KG0dq1LkK9KcfD405s+YlNe170pax2jrL5arGh8Y/FD9++MdJTasvvXoM3m9wrmpUDAECBAgQIECAAIFaCDiH1kI9/ZgGWOmb5zqijSPX7a1acVf88OGYP68hWX//n/eIDmssW7V4tVj4lldviTMePyMJ3XWlrnHDXjfUIhUxCRAgQIAAAQIECORKwDk0V+1caDEGWMXoc2pV2jhSo85NoIb5DXH50Q83queAX/aMlVZfJjc1lgoZ9MKguPiZi5Oa+nbqG1fsfEWualQMAQIECBAgQIAAgVoIOIfWQj39mAZY6ZvnOqKNI9ftrUpxc+fMiz8eM7TR2ged1TuWXyVfDzc/b8R5cc3oa5I6+6/bP37d99dVMbUoAQIECBAgQIAAgSIJOIcWo9sGWMXoc2pV2jhSo85NoFmfzI1BP3mkUT2H/KZPLLti29zUWCrklGGnxF1v3JXUdOjGh8YJPU7IVY2KIUCAAAECBAgQIFALAefQWqinH9MAK33zXEe0ceS6vVUp7uPps+OvJw1vtPbh5/WNdu1bVyVerRb9wT9/EI++/WgS/rgtjosjNj2iVumIS4AAAQIECBAgQCA3As6huWnlIgsxwCpGn1Or0saRGnVuAs2YOjP+9vPHGtXzvQu3izZLtcxNjaVC9r9z/3hp6ktJTWf1OSv2WW+fXNWoGAIECBAgQIAAAQK1EHAOrYV6+jENsNI3z3VEG0eu21uV4qa9+3Fc98snGq39/Uu3j5atWlQlXq0W3eXmXWLSR5OS8P+74//G9l22r1U64hIgQIAAAQIECBDIjYBzaG5auchCDLCK0efUqrRxpEadm0BT3/4o/n7Wk43qOfryftGsebPc1NjQ0BA9rusRs+bNSmq6bo/roluHbrmpUSEECBAgQIAAAQIEaiXgHFor+XTjGmCl6537aDaO3Le44gVOHj8jbvzNiGTd5i2axVGX9at4nFou+NGcj6L39b0bpXDPt+6JLst2qWVaYhMgQIAAAQIECBDIhYBzaC7a+KVFGGB9KZELFkfAxrE4Wq4tCUx644O45bynE4xWbVrE/1ycr4/WTZgxIfa4dY9GDX/iwCdi6VZLuwkIECBAgAABAgQIEPiKAs6hXxGwTt5ugFUnjVrSNMePHx9XXnll3H333TFu3LiYMWNGdOjQIdZaa63o169f7L///rHJJpss6fL/9T4bR8UoC7PQW6++H7f//tmk3jZLt4zv/W67XNX//OTn46B7Dkpqat28dYz8zsho1iw/H5PMVcMUQ4AAAQIECBAgUFcCzqF11a4lTtYAa4npsv/GSy+9NE455ZT46KOPFprsj3/847jooosqVoyNo2KUhVlo/OgpceclzyX1tluudRx+bt9c1T90wtD40UM/Smpatd2q8cC3H8hVjYohQIAAAQIECBAgUCsB59Bayacb1wArXe/Uop199tlx2mmnleOtv/76ceSRR0aPHj1iueWWiylTpsSzzz4bt912W/Tq1St+//vfVywvG0fFKAuz0Njn34t7Ln8+qXfZldrGIb/uk6v6bxtzW/zysV8mNW204kZx49435qpGxRAgQIAAAQIECBColYBzaK3k041rgJWudyrRHnzwwdh5553LsQ455JAYNGhQtGrVaoGxZ8+eHa1bt65YXjaOilEWZqHXnn43Bv95VFLv8qu2i4PObPzA83rH+Muov8SFT1+YlNFn9T7xx13+WO9lyZ8AAQIECBAgQIBAJgScQzPRhqonYYBVdeJ0A8yfPz823HDDGDNmTHTv3j1GjhwZLVu2TC0JG0dq1LkJ9MqTk+KBv45O6lmp0zJxwGk9c1NfqZDfjfxdXPXiVUlNe62zV5yz7Tm5qlExBAgQIECAAAECBGol4BxaK/l04xpgpetd9Wj33Xdf7L777uU4119/fQwcOLDqMT8fwMaRKncugo1+9O14+JqXk1pWWXPZ+PYpPXJR26dFnDr81Ljj9TuSmg7e+OA4qcdJuapRMQQIECBAgAABAgRqJeAcWiv5dOMaYKXrXfVoRxxxRPzlL38p/3azDz74IJZddtlyzKlTp5affbXSSivFiiuuWLU8bBxVo83twqOG/juG/v3VpL6OX1suvnXClrmq9+gHjo5hbw1LavrxFj+O7236vVzVqBgCBAgQIECAAAECtRJwDq2VfLpxDbDS9a56tK5du8bo0aNj7bXXjjfeeKP8U1jnnHNOjBr12TOGPn2o+zHHHBNt2rSpaE42jopyFmKx5x6cEMNvGpPU2nnDFeIbx22eq9oH3jUwRk357P/BM7Y+I/Zdf99c1agYAgQIECBAgAABArUScA6tlXy6cQ2w0vWuarTS869KD2sv/V36jYNbb711XHLJJQuN2adPn7j77rtj+eWXb3JepY1hUa+JEydGz57/eX7RhAkTonPnzk1e24XFFHhm8Lh4/LbXk+LX3GSl2OtH3XOFsdvNu8XbH72d1HRxv4tjxzV2zFWNiiFAgAABAgQIECBQKwEDrFrJpxvXACtd76pGe//995OPB7Zt2zZmzpwZHTt2jPPPPz/22GOPKH1txIgRcfLJJ8cTTzxRzmWfffaJW2+9tcl5lT6a2NSXAVZTpYp93Yi7x8ZTd45NENbZrEPs/oNNc4XS87qe8cncT5Kartn9mthslc1yVaNiCBAgQIAAAQIECNRKwACrVvLpxjXASte7qtE+/z9tKVC7du3imWeeiQ022KBR3E8++aT801nPPfdc+eulYVavXr2alJsBVpOYXLQYAk/c/no8fd+45B3rbbVK7Pq9TRZjhWxfWhpclQZYn3/dtc9dsWb7NbOduOwIECBAgAABAgQI1ImAAVadNOorpmmA9RUBs/T29957Lzp06JCkdOyxx8bFF1+8wBRLHx3ca6+9yt/7yU9+Er///e+bVIqPEDaJyUWLIfDozWPiXw9MSN6xYe/VYqfDNl6MFbJ96dsfvh273bJboyQfHfhotG/dPtuJy44AAQIECBAgQIBAnQgYYNVJo75imgZYXxEwS2+fNWtW+WOCn77uuuuu2HPPPReYYunjhaXfUDh37tzo27dvDBv22W9I+yo12Ti+il4x3/vIDa/GC0M+e7baxtuuHv0O2jA3GC9OeTEOuOuApJ6WzVrGMwc/U/5NoV4ECBAgQIAAAQIECHx1AefQr25YDysYYNVDlxYjx1VWWSUmT55cfkfpI4LdunVb6LtLz8eaNGlS+SOGL7/88mJEWfilNo6KMBZqkYevezlGD/vsAeeb9usc2w1YPzcGj7/9ePzPP/8nqWfFtivG0AFDc1OfQggQIECAAAECBAjUWsA5tNYdSCe+AVY6zqlF6devXwwZMqQcr/T8q80333yhsT8ddnXt2jVGjRpVkRxtHBVhLNQiD141Ol5+YlJS82a7rBHb7Pu13BgMfnNwnDD0hKSetdqvFXfuc2du6lMIAQIECBAgQIAAgVoLOIfWugPpxDfASsc5tSinn356nHXWWeV4N998c+y7774LjD19+vRYfvnlo6GhIXbdddcYPHhwRXK0cVSEsVCL3D9oVIwZ+W5S85a7rxm9v7FubgxuevWmOOvx//w/WXp169AtrtvjutzUpxACBAgQIECAAAECtRZwDq11B9KJb4CVjnNqUZ5//vno3r17Od5BBx0U11577QJjX3311XHYYYeVv/erX/0qfvGLX1QkRxtHRRgLtci9f3gh3vjXfz72Wnr13Hvt6LHn2rkxGPTCoLj4mc9+mULfTn3jip2vyE19CiFAgAABAgQIECBQawHn0Fp3IJ34BljpOKcaZY899oh77703mjdvHvfff3/stNNOjeKXnnvVo0ePKP1P3rp163jjjTeiU6dOFcnRxlERxkItctf/PhfjRk1Jat56n3Vji93WzI3B75/+ffx11F+TevZYe484d7tzc1OfQggQIECAAAECBAjUWsA5tNYdSCe+AVY6zqlGefXVV6NXr14xbdq08m8lPO6446I01FpqqaXiqaeeinPOOac8vCq9zj333DjppJMqlp+No2KUhVno/y56Nv798vtJvX2/vV5036lLbuo/47Ez4pYxtyT1HLDBAXFq71NzU59CCBAgQIAAAQIECNRawDm01h1IJ74BVjrOqUcZPnx47LfffvHOO+8sMHazZs3i1FNPLX98sJIvG0clNYux1q0XPB0TX/sgKXb7gevHJtt3zk3xxw85Pv457p9JPf/T7X/imM2PyU19CiFAgAABAgQIECBQawHn0Fp3IJ34BljpONckypQpU+LSSy+N22+/PcaOHRuzZ8+Ojh07xg477BDHHHPMIn9D4ZImbONYUrnivu+mc0bEu+NmJAD9/h975wElRZW98cvkYfIMQ845KIoioqKAmEBREUVkdTGuYf2b1xwR8+4iJtaIq2LOqKtiQtEVEFxUouTMMDNMYnJ3/89XWDU9Q3dPdVdVT1XXd8/xyDBV7937e9Wv+n3cd995/WXgUR1jBsjFn18sC3cs1OK5YegNMnXQ1JiJj4GQAAmQAAmQAAmQAAmQQEsT4Dq0pUcgOv1TwIoOZ9f0wonDNUNtWqCv37tIirZVaO0dd8FA6Xd4e9Pab+mGJs2dJCuLV2puTDtymkzoM6Gl3WL/JEACJEACJEACJEACJBAzBLgOjZmhDBkIBSx3jHPUouTEETXUMdPRnLt+lJJdlVo8J15ygPQ+tG3MxHfSOyfJtoptWjwzR8+UY7seGzPxMRASIAESIAESIAESIAESaGkCXIe29AhEp38KWNHh7JpeOHG4ZqhNC/Sl236Q8qJqrb1xVwyWHoPbmNZ+Szd05GtHSnltwxbJ2SfOlqHth7a0W+yfBEiABEiABEiABEiABGKGANehMTOUIQOhgOWOcY5alJw4ooY6ZjqafdMCqSyt1eIZf9VB0nVgXkzE5/V55eCXDhaf+LR43jn1Hemb0zcm4mMQJEACJEACJEACJEACJGAHAlyH2mEUrPeBApb1jF3VAycOVw23KcE+d/23UrO3Xmvr9OuGSKe+Oaa03dKNlNaUyojXRzRyY96Z86R9WuzU+GppxuyfBEiABEiABEiABEiABLgOdcczQAHLHeMctSg5cUQNdcx09PTV86W+xqPFM/HGQ6V9z6yYiG9L+RYZ9+64RrEsnLJQWie2jon4GAQJkAAJkAAJkAAJkAAJ2IEA16F2GAXrfaCAZT1jV/XAicNVw21KsLOu+Fq83oYtdpNuPUzyu2aY0nZLN7K8aLlM/miy5kZCXIIsPXeptGrVqqVdY/8kQAIkQAIkQAIkQAIkEDMEuA6NmaEMGQgFLHeMc9Si5MQRNdQx0ZHP65Onrvi6USzn3Hm45HZMi4n4ftj+g1w671ItltyUXJl/9vyYiI1BkAAJkAAJkAAJkAAJkIBdCHAdapeRsNYPCljW8nVd65w4XDfkhgKur/PI0//XWNA5997hkpUfG1vsPt34qfxt/t80Rt0zu8vcCXMNMePNJEACJEACJEACJEACJEACjQlwHeqOJ4ICljvGOWpRcuKIGuqY6Kimql6eu/bbRrFMfeBISc9JiYn43lz9ptz7471aLIPzB8uccXNiIjYGQQIkQAIkQAIkQAIkQAJ2IcB1qF1Gwlo/KGBZy9d1rXPicN2QGwq4sqxWZt+4oFEbFz4yQlIzkgy1a5ebn/v1OZm5dKb7pesYAAAgAElEQVTmzohOI2TWcbPs4h79IAESIAESIAESIAESIIGYIMB1aEwMY7NBUMBqFhEvCIcAJ45waPHa8uJqeenWHxqBuGTGMZKUmhATcP655J8y+7fZWizjeoyTh455KCZiYxAkQAIkQAIkQAIkQAIkYBcCXIfaZSSs9YMClrV8Xdc6Jw7XDbmhgEsKKmXOnT82auPSx0dKQmK8oXbtcvPdP9wt7/z+jubO5H6T5bbht9nFPfpBAiRAAiRAAiRAAiRAAjFBgOvQmBjGZoOggNUsIl4QDgFOHOHQ4rVF2yvk9WmLGoG44qnR0iquVUzAue6b62TepnlaLH8Z/Bf5vyH/FxOxMQgSIAESIAESIAESIAESsAsBrkPtMhLW+kEBy1q+rmudE4frhtxQwLs3l8ub9y/W2oiLbyWXPznaUJt2uvnizy+WhTsWai7dMPQGmTpoqp1cpC8kQAIkQAIkQAIkQAIk4HgCXIc6fgh1BUABSxcmXqSXACcOvaR4HQjsXF8q7zy8RIORmBwvf5k5MmbgTJo7SVYWr9TimXbkNJnQZ0LMxMdASIAESIAESIAESIAESMAOBLgOtcMoWO8DBSzrGbuqB04crhpuw8FuW71H3p/xs9ZOSlqiXPSPow23a5cGTnrnJNlWsU1z59HRj8qYrmPs4h79IAESIAESIAESIAESIIGYIMB1aEwMY7NBUMBqFhEvCIcAJ45waPHazcuLZO7jyzQQaVlJcv5DI2IGzJGvHSnlteVaPC+c+IIc1v6wmImPgZAACZAACZAACZAACZCAHQhwHWqHUbDeBwpY1jN2VQ+cOFw13IaD3bBst3wy61etncw2KXLe9CMNt2uHBjxejwx5eYj4xKe58/b4t6Vfbj87uEcfSIAESIAESIAESIAESCBmCHAdGjNDGTIQCljuGOeoRcmJI2qoY6KjtUsK5LNnf9NiyWnfWqbcPTwmYiutKZURrzfOJpt35jxpn9Y+JuJjECRAAiRAAiRAAiRAAiRgFwJch9plJKz1gwKWtXxd1zonDtcNuaGAVy/cKV/MXqG1kdc5XSbfPsxQm3a5eUvZFhn33rhG7iycslBaJ7a2i4v0gwRIgARIgARIgARIgARiggDXoTExjM0GQQGrWUS8IBwCnDjCocVrV3y/Xb5+eZUGom33TDnr5qExAWZ54XKZ/PFkLZaEuARZeu5SadWqVUzExyBIgARIgARIgARIgARIwC4EuA61y0hY6wcFLGv5uq51ThyuG3JDAf/6zVb59vU1WhsdemfJGTccaqhNu9z8w/Yf5NJ5l2ru5Kbkyvyz59vFPfpBAiRAAiRAAiRAAiRAAjFDgOvQmBnKkIFQwHLHOEctSk4cUUMdEx3974vN8v3ba7VYOvfPkdOuGRITsX268VP52/y/abF0z+wucyfMjYnYGAQJkAAJkAAJkAAJkAAJ2IkA16F2Gg3rfKGAZR1bV7bMicOVwx5x0Es/2yT/fW+ddn+3A/PklL8eFHF7drrxzdVvyr0/3qu5NDh/sMwZN8dOLtIXEiABEiABEiABEiABEogJAlyHxsQwNhsEBaxmEfGCcAhw4giHFq9d/PEGWTR3gwai55B8GXvpgTEB5rlfn5OZS2dqsYzoNEJmHTcrJmJjECRAAiRAAiRAAiRAAiRgJwJch9ppNKzzhQKWdWxd2TInDlcOe8RB//j+Olny6Sbt/j6HtZMTLhoUcXt2unHGkhnywm8vaC6N7TFWHj7mYTu5SF9IgARIgARIgARIgARIICYIcB0aE8PYbBAUsJpFxAvCIcCJIxxavPb7t3+X/32xRQPR/4j2MmbqwJgAM/3H6fLG6je0WCb1nSR3HHFHTMTGIEiABEiABEiABEiABEjATgS4DrXTaFjnCwUs69i6smVOHK4c9oiDxgmEOIlQtUFHd5RRf+ofcXt2uvHm726Wj9d/rLl04QEXyrWHXmsnF+kLCZAACZAACZAACZAACcQEAa5DY2IYmw2CAlaziHhBOAQ4cYRDi9d+/coqWbFguwbiwNGd5Ziz+8YEmCu/vFLmb52vxXLVkKvkksGXxERsDIIESIAESIAESIAESIAE7ESA61A7jYZ1vlDAso6tK1vmxOHKYY846C9eXCGrf9yp3X/w8V3lqIm9I27PTjee/+n5smTXEs2lW4bdIlMGTLGTi/SFBEiABEiABEiABEiABGKCANehMTGMzQZBAatZRLwgHAKcOMKhxWs/e+43WftTgQbi0LHdZPhpvWICzFlzz5JVxau0WO4bcZ+c2uvUmIiNQZAACZAACZAACZAACZCAnQhwHWqn0bDOFwpY1rF1ZcucOFw57BEH/cmsX2TDskLt/mHje8hhJ/eIuD073Tj2nbGytaKhvtfM0TPl2K7H2slF+kICJEACJEACJEACJEACMUGA69CYGMZmg6CA1SwiXhAOAU4c4dDitXMfXyablxdpII6Y0EsOObFbTIA5+vWjpaSmRIvl+ROel2EdhsVEbAyCBEiABEiABEiABEiABOxEgOtQO42Gdb5QwLKOrStb5sThymGPOOj3Z/ws21bv0e4fcVYfOWhMl4jbs8uNPp9PDnnlEKn31msuvX7K6zIob5BdXKQfJEACJEACJEACJEACJBAzBLgOjZmhDBkIBSx3jHPUouTEETXUMdHRu48skR3rSrVYRk7pJwcc08nxsdV4amToK0MbxfHRhI+kW2ZsZJc5foAYAAmQAAmQAAmQAAmQQEwR4Do0poYzaDAUsNwxzlGLkhNH1FDHREdvPbBYCjaVa7Ec++f+MuDIjo6PraiqSEa9OapRHN9M+kbyUvMcHxsDIAESIAESIAESIAESIAG7EeA61G4jYo0/FLCs4eraVjlxuHboIwr89XsXStG2vdq9x184UPoOax9RW3a6aXPZZjn5vZMbufTTuT9JcnyyndykLyRAAiRAAiRAAiRAAiQQEwS4Do2JYWw2CApYzSLiBeEQ4MQRDi1eO+euH6VkV6UG4qS/HCC9DmnreDDLi5bL5I8ma3EkxCXI0nOXSqtWrRwfGwMgARIgARIgARIgARIgAbsR4DrUbiNijT8UsKzh6tpWOXG4dugjCvylW3+Q8uJq7d6Trxgs3Qe3iagtO920aMciuejzizSXspOz5bvJ39nJRfpCAiRAAiRAAiRAAiRAAjFDgOvQmBnKkIFQwHLHOEctSk4cUUMdEx3NvmmBVJbWarGcetXB0mVgruNj+2rzV3L111drcXRK7ySfTvzU8XExABIgARIgARIgARIgARKwIwGuQ+04Kub7RAHLfKaubpETh6uHP+zgn7v+W6nZW6/dN+H6IdKxT07Y7djthrnr5sqtC27V3Oqf21/eGv+W3dykPyRAAiRAAiRAAiRAAiQQEwS4Do2JYWw2CApYzSLiBeEQ4MQRDi1e+/TV86W+xqOBmHjTodK+R5bjwby68lV5YNEDWhyHtjtUXjzpRcfHxQBIgARIgARIgARIgARIwI4EuA6146iY7xMFLPOZurpFThyuHv6wg591xdfi9fq0+ybddpjkd8kIux273fDsL8/KYz8/prk1svNIeWLME3Zzk/6QAAmQAAmQAAmQAAmQQEwQ4Do0Joax2SAoYDWLiBeEQ4ATRzi03H2tz+uTp674uhGEc+46XHI7pDkezIwlM+SF317Q4hjXY5w8dMxDjo+LAZAACZAACZAACZAACZCAHQlwHWrHUTHfJwpY5jN1dYucOFw9/GEFX1/rkaevmt/onnPvHS5Z+a3DaseOF0//cbq8sfoNzbWz+50ttw+/3Y6u0icSIAESIAESIAESIAEScDwBrkMdP4S6AqCApQsTL9JLgBOHXlK8rqayTp677rtGIKY+cKSk56Q4Hs5N394kn2z4RIvjwgMulGsPvdbxcTEAEiABEiABEiABEiABErAjAa5D7Tgq5vtEAct8pq5ukROHq4c/rOAry2pl9o0LGt1z4SMjJDUjKax27HjxlV9eKfO3NmSXXTXkKrlk8CV2dJU+kQAJkAAJkAAJkAAJkIDjCXAd6vgh1BUABSxdmHiRXgKcOPSS4nXlxdXy0q0/NAJxyYxjJCk1wfFwzv/0fFmya4kWxy3DbpEpA6Y4Pi4GQAIkQAIkQAIkQAIkQAJ2JMB1qB1HxXyfKGCZz9TVLXLicPXwhxV8ya5KmXPXj43uuezxURKfGBdWO3a8+Ky5Z8mq4lWaa/ePuF/G9xpvR1fpEwmQAAmQAAmQAAmQAAk4ngDXoY4fQl0BUMDShYkX6SXAiUMvKV5XtK1CXr93USMQV8waLa1atXI8nLHvjJWtFVu1OGaOninHdj3W8XExABIgARIgARIgARIgARKwIwGuQ+04Kub7RAHLfKaubpETh6uHP6zgCzaVyVsP/KTdE5fQSi5/YnRYbdj14qNfP1pKako0954/4XkZ1mGYXd2lXyRAAiRAAiRAAiRAAiTgaAJchzp6+HQ7TwFLNypeqIcAJw49lHgNCOxYVyrvPtJQJyoxJV7+8uhIx8Px+XxyyCuHSL23Xovl9VNel0F5gxwfGwMgARIgARIgARIgARIgATsS4DrUjqNivk8UsMxn6uoWOXG4evjDCn7r6j3ywYyftXtS0hPlor8fHVYbdry4xlMjQ18Z2si1jyd8LF0zu9rRXfpEAiRAAiRAAiRAAiRAAo4nwHWo44dQVwAUsHRh4kV6CXDi0EuK121eUSRzH1umgUjLTpbzHzzK8WCKqopk1JujGsXxzaRvJC81z/GxMQASIAESIAESIAESIAESsCMBrkPtOCrm+0QBy3ymrm6RE4erhz+s4Df+UigfP/WLdk9mmxQ5b/qRYbVhx4s3lW2SU947pZFrP537kyTHJ9vRXfpEAiRAAiRAAiRAAiRAAo4nwHWo44dQVwAUsHRh4kV6CXDi0EuK1637uUA+ffo3DUR2u9byp3uGOx7M8qLlMvmjyVocCXEJsvTcpTFxuqLjB4cBkAAJkAAJkAAJkAAJxCQBrkNjclj3C4oCljvGOWpRcuKIGmrHd/T74l3y+fPLtThyO6bJOXce7vi4Fu1YJBd9fpEWR05yjnw7+VvHx8UASIAESIAESIAESIAESMCuBLgOtevImOsXBSxzebq+NU4crn8EdANY9eMO+fLFldr1+V0zZNKth+m+364XfrX5K7n666s19zqnd5b/TPyPXd2lXyRAAiRAAiRAAiRAAiTgeAJchzp+CHUFQAFLFyZepJcAJw69pHjdigXb5etXVmkg2vXIlDNvanx6nxMpfbjuQ7ltwW2a6/1z+8tb499yYij0mQRIgARIgARIgARIgAQcQYDrUEcMk2EnKWAZRsgG/Alw4uDzoJfAr99slW9fX6Nd3rFPtky4/hC9t9v2uldXvioPLHpA8+/QdofKiye9aFt/6RgJkAAJkAAJkAAJkAAJOJ0A16FOH0F9/lPA0seJV+kkwIlDJyheJsu+3CIL3vpdI9G5f46cds0Qx5N59pdn5bGfH9PiGNV5lDw+5nHHx8UASIAESIAESIAESIAESMCuBLgOtevImOsXBSxzebq+NU4crn8EdANY+tkm+e9767Trux2QJ6dceZDu++164YwlM+SF317Q3Du558ny4NEP2tVd+kUCJEACJEACJEACJEACjifAdajjh1BXABSwdGHiRXoJcOLQS4rX/fTJRln44XoNRI+D2si4ywc7Hsz0H6fLG6vf0OI4u9/Zcvvw2x0fFwMgARIgARIgARIgARIgAbsS4DrUriNjrl8UsMzl6frWOHG4/hHQDWDh3PXy08cbtet7H9pWTrzkAN332/XCm769ST7Z8Inm3oUHXCjXHnqtXd2lXyRAAiRAAiRAAiRAAiTgeAJchzp+CHUFQAFLFyZepJcAJw69pHgdtg9iG6FqfQ9vJ8dfMMjxYK788kqZv3W+FsdVQ66SSwZf4vi4GAAJkAAJkAAJkAAJkAAJ2JUA16F2HRlz/aKAZS5P17fGicP1j4BuAAve/l2WfbFFu77/kR1kzJ8H6L7frhee/+n5smTXEs29Ww+/Vc7pf45d3aVfJEACJEACJEACJEACJOB4AlyHOn4IdQVAAUsXJl6klwAnDr2keN23r6+RX7/ZqoEYdHRHGfWn/o4Hc9bcs2RV8SotjvtH3C/je413fFwMgARIgARIgARIgARIgATsSoDrULuOjLl+UcAyl6frW+PE4fpHQDeAr+eskhXfbdeuP3B0Zznm7L6677frhWPfGStbKxqEuUdHPypjuo6xq7v0iwRIgARIgARIgARIgAQcT4DrUMcPoa4AKGDpwsSL9BLgxKGXFK/78t8rZNV/d2ogDj6uixx1Zh/Hgxn5xkgpri7W4nj2hGdleIfhjo+LAZAACZAACZAACZAACZCAXQlwHWrXkTHXLwpY5vJ0fWucOFz/COgG8Pnzy+X3xbu06w85qZsccXov3ffb9cJhc4ZJVX2V5t6ccXNkcP5gu7pLv0iABEiABEiABEiABEjA8QS4DnX8EOoKgAKWLky8SC8BThx6SfG6T5/5VdYt3a2BOOzk7jJsfE9Hg/F4PXLwywc3iuH9096XXtnOF+YcPTB0ngRIgARIgARIgARIIKYJcB0a08OrBUcByx3jHLUoOXFEDbXjO/pk1i+yYVmhFsfhp/WUoWO7OzquitoKOeK1IxrF8PnEz6VDegdHx0XnSYAESIAESIAESIAESMDOBLgOtfPomOcbBSzzWLIlEeHEwcdAL4G5jy+TzcuLtMuPPKO3DDmhq97bbXldQWWBjHmrccH2BZMXSFZyli39pVMkQAIkQAIkQAIkQAIkEAsEuA6NhVFsPgYKWM0z4hVhEODEEQYsl1/6waM/y9ZVezQKIyb1kYOO7eJoKhtKN8ip75/aKIal5y6VxPhER8dF50mABEiABEiABEiABEjAzgS4DrXz6JjnGwUs81iyJWZg8RkIg8C7f18iO9aWaneMPKevHDCycxgt2O/S5UXLZfJHkzXHEuMSZel5S+3nKD0iARIgARIgARIgARIggRgiQAErhgYzRCgUsNwxzlGLkhNH1FA7vqO3H/pJdm0o0+IYfV5/GXhUR0fHtXjnYrnwswu1GLKTs+W7yd85OiY6TwIkQAIkQAIkQAIkQAJ2J8B1qN1HyBz/KGCZw5Gt/EGAEwcfBb0E3rhvkRRuqdAuP+78AdJvuLOLnc/fMl+u/OpKLaaOaR3lszM/04uE15EACZAACZAACZAACZAACURAgOvQCKA58BYKWA4cNDu7zInDzqNjL99em7ZQirfv1Zw64eJB0mdoO3s5GaY3/9nwH7nx2xu1u3pn95b3TnsvzFZ4OQmQAAmQAAmQAAmQAAmQQDgEuA4Nh5Zzr6WA5dyxs6XnnDhsOSy2dOqVO/8rpQVVmm9jLz1Qeg7Jt6Wvep16e83bcs9/79EuH5w/WOaMm6P3dl5HAiRAAiRAAiRAAiRAAiQQAQGuQyOA5sBbKGA5cNDs7DInDjuPjr18e+nWH6S8uFpz6uS/DpbuB7axl5NhevPS8pfkkZ8e0e4a3mG4PHvCs2G2wstJgARIgARIgARIgARIgATCIcB1aDi0nHstBSznjp0tPTdr4qiurpaSkhKprKwUj8djy1jplDEC21bvkfo6r9ZIu+6ZkpKeaKzRFr57c/lm2VS2SfMiLyVPBuYNbGGv2D0JkAAJRE4gPj5ekpKSJDMzU9LT0yUuLi7yxngnCZAACZAACVhEwKx1qEXusVmTCFDAMgkkm9lHwOjE4fP5ZMeOHVJaWkqkMU6gYk+1+Br0K0nNTJKERGcvjMpqyqSirqEwfWpCquSk5MT4SDI8EiABtxBo1aqVdOrUSTIyMtwSMuMkARIgARJwCAGj61CHhOl6Nylguf4RMBeA0YmjsLBQdu/e3ciphIQEc51ka7YgUFtdL+JrcCUxOV5axbWyhW+ROlHjqZE6T512e2J8oiTHJ0faHO8jARIggRYngCxo/OOSahSxWnxI6AAJkAAJkEAAAkbXoYTqDAIUsJwxTo7x0sjEUVtbK+vWrdNibdu2rWRnZwu2L9Bij0DB5nIRv0VRTvs0gYjlZNtavlVKaxqyB/NS86R9Wnsnh0TfSYAEXE4A4hW28xcXF0tFxb4MU4hYffv25XZClz8bDJ8ESIAE7ETAyDrUTnHQl9AEKGDxCTGVgJGJA1+Od+3apfiTl5cnELBosUugYFNZo+ByOqRJYpKzBazNZZulvLZciyu/db60bc3nOHafYkZGAu4hACEL73hVxMJWQtTFopEACZAACZCAHQgYWYfawX/6oI8ABSx9nBxzFf5VVI+NHDlSvvnmGz2XhnWNkYljy5Yt2hfjHj16SEpKSlh982LnEMBCaDcysPwst2OaJCQ6W8DaWLpR9tbt1aJql9ZO2qQ6+2RF5zxV9JQESMBqAnv37pXNmzcr3aAOVufOna3uku2TAAmQAAmQgC4CRtahujrgRbYgQAHLFsNgnhNOFrCwfRDbCBFDv379lP/TYpOAz+uT3VuaCljpji/ivr5kvVTVV2mD1jG9I4u4x+YjzKhIwJUE8I8Pq1evVmpiJScnS8+ePV3JgUGTAAmQAAnYjwAFLPuNiRUeUcCygmoLtqmKPpdffrlcccUVQT1JS0sTZDmZbUYmjt9//13q6+sFRdv79Oljtmtsz0YEvF6fFDYRsPI6pUt8grNPIVxbslZq6ms00p0zOktWcpaNyNMVEiABEjBGgO9qY/x4NwmQAAmQgDUEjKxDrfGIrVpBgAKWFVRbsE1VwLrrrrvk7rvvjronRiYOfimO+nC1WIdej1cKt+4rBqxaXud0iY93toC1pniN1HkbTiHsmtlVMpJ43HyLPWjsmARIwHQCfFebjpQNkgAJkAAJmEDAyDrUhO7ZRJQIUMCKEuhodUMBK1qk2Y8RAp56rxRtayxgtemcLnEOF7BWFa8Sj9ejoeme1V3SEtOMoOK9JEACJGArAhSwbDUcdIYESIAESOAPAhSw3PEoUMCKsXGmgBVjAxqj4XjqvFK0vYmA1SVD4uKcXfdsRdEKpTaMaj2ze0pqQmqMjiLDIgEScCMBClhuHHXGTAIkQAL2J0ABy/5jZIaHFLDMoGijNihg2Wgw6EpQAvV1Hine3nBaHy7M75rh6ML9Xp9XVhatbBRz7+zekpyQzCeBBEiABGKGAAWsmBlKBkICJEACMUWAAlZMDWfQYChgxdg4qwLWwIEDlUyQjRs3Snx8vLRv316OPPJIOf/882X06NGWRW1k4uCXYsuGxXYN19d6pHhH9AWs7t27y6ZNm2Tq1Kny4osvmsql3lsvq4tXN2qzb05fSYxPNLWfUI3h864ezjB79mzl8x7rVlRUJA888IB8/PHHynxXXV2thDxjxgy55pprYj38iOPD83/BBRco92/YsEHw2aCRgB4CfFfrocRrSIAESIAEok3AyDo02r6yv8gJUMCKnJ0t71QFrFDOnX766criPSsr/NPRMDGEsh07dsiwYcOUS7Zs2SKdO3fWzYlfinWjMuXCb775JqiYmZqaKvn5+TJkyBCZNGmS8h9OhzTL6mo8smenn4DVSqRt10yzmg/ajpUCVq2nVn7f83ujvvvn9pf4uHjL41I7sIuApc5DI0eOFDxnVllpaakcdthhgrmjqVHACk3dDAFr1KhRMn/+/P06iouLU94vEFNHjBghf/nLX2TQoEFWPQZau//5z3/kmWeekcWLF8vu3buVOQzPB/ofO3as5f2H6mDt2rWKX4sWLVL++/nnn6Wqqkq5xUyxGUIu+sF/69evVzjgc5Keni49e/YUjBl49OvXL2IefFdHjI43kgAJkAAJWEiAApaFcG3UNAUsGw2GGa6kpaXJqaeeKmPGjJH+/fsrX1rxBRaLjH/961+CbAUYFpbz5s2TxMTwskP0CGRqHBSwzBhR69oIJWA17RWLwA8//FDJ5DPD6mrqZc/OSq0pPFfYQmi1WSlgVddXy7qSdY1CGJg3MKrbIt0mYN1///1y2223KcxvvPFGGT9+vGRnZys/d+jQQfLy8qx+pJpt3/9z9vXXXysCgh3MSgGraXzIAp4+fbrcfPPNloTu9XoVUeb5558P2v7FF18sTz/9tEBci7bh/Rtq3M0SsOrr63W90/HenzZtWsTjQQEr2k8Q+yMBEiABEtBDgAKWHkrOv4YClvPHsFEEJSUl2gKuaWi7du1S/hUa//ILmzlzplx11VVhEaCAFRYuW1/sv7C+/PLL5YorrtD8raiokJ9++kn+8Y9/KNuyYMis+/HHH00RZGqr66Vkl5+AFddK8rtYL2BZOSCVdZWyoXSD1kVcqzgZkDfAyi73a9ttAtaxxx4rEIWGDh2qZJzY0dwiYP36668a/traWiX75/3335c5c+Zof//mm2/KWWedZfow3XLLLfLggw8q7SJrFGJmr169ZN26dfLwww9r7zxcB9Ez2ub/DEBAGzBggOAfm5CJBTNTwGrTpo0ilh1++OFKxhWE3NatW8v27duVbMgXXnhByciCzZo1Sy677LKwcVDAChsZbyABEiABEogCAQpYUYBsgy4oYNlgEKLpAhYVyMyqq6uT3r17B9x6E8ofbiGM5mhZ25f/ouquu+6Su+++e78O9+zZowhX2P4CQxYWslyMWm1VvZQUNAhYcfGtpE1nZwtYFbUVsqlsk4YmIS5B+uVGvk0nEsZuE7CwDWrNmjUyZcqURkJJJOysusctApb/6Zv+LB9//HHtH0qwjfC3334zFTXGH+0i+whC5rfffivYAq1aZWWlknEMQR7boFeuXKm8+6JpEHw++OADZTvjoYceqmRG+2fAmSVgISaPx6PUvQxmqHcGHzC3Y4sltv2Huj5QOxSwovn0sC8SIAESIAG9BChg6SXl7OsoYDl7/CLy/uSTT5ZPPvlEuXfbtm3SsWPHiNoJdJORiYNfik0bBl0N6RGw0I/gShwAACAASURBVBD+xf6iiy5S2kSW1pNPPqmr/VAX1VTWSenuffVfYHHxcdKmc7rhdluygbKaMtlSvkVzISk+Sfrk9ImqS24TsKzcEmrWwLldwML2PtTC2rx5s4IUgolZW5HVOQmZRLD//ve/Mnz48P2GDpmjRxxxhKlzmNHnwyoBS49fyLrCdkoYBMVw65PxXa2HMq8hARIgARKINgEj69Bo+8r+IidAAStydo69829/+5v8/e9/V/zHFgb8q7BZZmTi4Jdis0ZBXzt6BSwscA488EClUYifH330kfLnpgvzY445RskqePnll2XFihVK7bU///nP+532t3TpUpn11L+UrV87du5QTsvs2KGjHH/CcXLttddK37599wsA24GQPYiTNL///vuQAUKU7dq1q2DhjGcdW4hU0yt4zJ07V/79738rWyYRBzIm4Ndpp50mV155pfJzUyupLpFb77xVZj2ybzG9ds9a6ZXdK6CvekSNJUuWyFNPPSXfffedIjQjswIZE23btlUW6SeeeKKSDee/rTeYgIWMyy5dugi2EeO+Tz/9NCRD/zF/6KGHlC1Z4VhzRdzV36uZf9j+989//lOJFbyxDQrbA2+99VZlu5W/6andFqx4vLqlbeHChVJQUCApKSlKNg44Yjt1Tk5Os2FC/H/11Vflhx9+UHhiXLBN65BDDlHawYEH2LLlPxahGg2WfYPPBz5PYLJz504le6hbt25y0kknKZ+T5v7hARk2GDvEjJM3MzIyZPDgwXLppZcq2/jMroEVLAMLsY8bN05QYN3sdw76xEEh2B6HzGJkVwUz/H716tXSqVMn5YCRcLbDN/tQRHBBSwpY/t8BkJmGjKxwjO/qcGjxWhIgARIggWgRMLIOjZaP7Mc4AQpYxhk6rgUsRh955BHTFxNo0MjEwS/F0X2U9ApYWPRh8QfD4lldiPrfj79DvawvvviiURBTp07VBCwISjfccIM8+uijimgVyLBIR4YXCjL72x133KEUgcaiE0IWhKhgBnEWCzTY//73PznooIO0S5sTsKqrq5XtaO+9917Q9iEc4KSvgw8+uNE1xVXFcvtdt2sC1vqS9dIjq0fAdpoTsHCCHliBWSgrLy9vJKaFysBSP/eowYNsGCzkg9l1110n8AHjgcV+uBkz4QhYEOSuvvpqZQtYU4MQhGcL4qhqkQhYEHPOPPNM+eqrr4LGDD+wzStQBg9uwgEYZ599tnz55Zchx0QVpCIVsPAMXnDBBfL6668H7Qf1k1577bWg23kh5Bx33HGKsBPI0D6Y4v8wbCsL9ZkK5oj/KYShBCycfAu2MNRgbPrZCQk0xC8xF0DchkGYw0ElwQy/xwmFMNyHrLCWtJYSsHDyIeZEvG8xF6BuJsTNcIzv6nBo8VoSIAESIIFoETCyDo2Wj+zHOAEKWMYZOq6FU045RVmAw/BBD7WQDTc4IxMHvxSHS9vY9XoFrLffflsrvHzhhRdqJ33534/Mjl9++UU5AfP8889XMkWQnVJWVqYs+mF//etflYwi2IijjpYzT5ss3bp2V+rVrFqzQp59cZYsX75c+T0Wu2hLtVWrVmmZOPfdd5+SmRPMkAmDRXKgejvNCVjwFYWmYVjkXX/99Uq/xcXFiqCARScW6rm5uUq8/p+dwqpCufOuOzUBa2PpRumW2S2gm6EELLSLQtTq1itkfGHBjz4hWEFQRHYOGCEzxz8bLJSAhVpBqBkFQyFrFLQOZMjWQlzIhEJGEeqehWt6BSyIRcgCRYYfRCz8HwtsCIg4ZAIMkE2HuSEpKUlxY+/evYrgAkM2GUQaZMZB4FQNAo8qUNTU1CiZe8j8Q60fCJTICMLvEStqJiH7CwIVMrDw7OD59TfUUYKvaqFyZKxAZD3ggAMkOTlZEfnQzhtvvCF4PvEZQNsYK2SX4XMDw3bcphmvyCBST07EswXm6vysZnShGDfEBrCCUAwBEjyQjYi6T/6Gzxz8gk8wPNMQkiHQ4RlArMi6gR9q4XurBSy1Vhn8wWdJT6abnmcO2aBqTT4Irtdcc03Q2/B7CLMw8MUz0JIWTQELzyK2biJrEFl5EPZhOJnx2WefDRsD39VhI+MNJEACJEACUSBgZB0aBffYhUkEKGCZBNIpzWChgmwanBKFf7lWi3Ob5b+RiYNfis0aBX3t6BGwkBVz9NFHK1vpYC+99JKcd955yp+bZsLcfvvtcu+99wbsfN68eXLCCScov3vuuedkytnnSXlRtXZtQlK8tM6JV7YoIksGAgKeTWQAqQbRACJEqELQ/kJXIJEmlICFRS3EXdiYMWOUOnGqaKL6gMWemh2GrWIQLFQrqCxQCuGrWwg3l22WLhldAvIIJWDdeeedCkeIMDhFrV27dgHbwEliyJyAsKFaczWwkHWDLWnYDglxJZBBPDrjjDOUX+HPyJ4J1/QKWGgXQgL6acoaQhCeKdi7774rEyZM2M+N5gRJ3HDbbbcpgh1EImQIBtouhS12qJGERX6ggvBqRhragxCLwuSBtqBhXkW2l/+YNZdt5x+U+nwlJiYqwiEyHpsa2sdnEmLvUUcdJQsWLGh0if/2sECfAYgZeM4///xz7T4rBSyM3cSJE7XPVdMszXCfLf/rkXGFE1Rhb731lpJlF8z8hXjch4wsf4PoiG3DRizY1tVAbVotYDWXAQjxF2J9ZmZm2CHzXR02Mt5AAiRAAiQQBQJG1qFRcI9dmESAApZJIO3QDOr2jB07ttGi398vZMTg98gwgOFf8tV/kTbLfyMTh54vxV6vT/ZU1prlriPayWmdJHFxrUz3NZSAhSwXZGlAkMF1MIhKED2QcQLzvx+CCOpeBTvNCoIQhCksZLGQrCqvlfLiBgErMTlectqnKTVsBg4cqLSPBfbxxx+vxY3MEWREwZpuDVQv8t9qiEV500yaUIKHWqcH4gGEI9SMCmTwCYtwiGvIhEH9I9jOvTtl2j3TNAFra/lW6ZQeeJteKFEDAhmEDGRhQbALx5oTsCBAIhsHBuEDAkhTQ+Yb5hJk7KD2lr+IqNcXvQIWalBBPEJfTQ3ZZqiFBVEINZ8w/k2tOQGroqJCqZEEsQ+iE7LZghkKgeOQAow/RCIIiDBssUJGGrKwIH6hflY4p7bpFbCQfdWnTx/l2cNzrtYpDOQvtlWqGUTIqsJ9MLDCdk/4j6xIfE4CCW2Yp5HVBTELZraABT+wTQ/CJDLjwA7bQTEHHH744Xofo2avw1Z4tT4bmAQS/NRG/JmBrTqXqL93i4CFzxS2aWMuDuc59h8MPe/qZgePF5AACZAACZCAyQSMrENNdoXNWUiAApaFcKPdNBZzWJDgiymyCfAztmcVFhYqYgNOHcKfYSNGjFAW4aoYYZavRiYOPV+Kiypq5NDpjessmeW7XdtZcvtxkpe+TzQy0/TUElL7g8Dw2WefNapd438/hKNp06YFdA9bmrBlCNvBULdn8uTJUllWKxV7/ASslHjJabdPMEChcjyn99xzjyAbSTVsFYOohHawaMVWmKaGgtwQAPB8I9OoqQUTPJBplpWVpSy0/QvVBwoIWQvqtkgU8z7nnHOUy7ZXbJfp06ZrAtb28u3SIX2fuNXUQokaKGwOlvhsYlvasGHDdA97cwIWtudBcIOgg5MlkQ3nbxC5IfiAR3MiSiin9ApYzW1RxFY4ZBphiyCKkesdT/U6/6y65k6/Qz/oDzZ//nyt7pZ/BhEydHAwQTimV8Dy7z/YaXpqvxCY1a2j/j7hPmyXhDX3DxT+W8nNELBCMcG23sceeyygYBoOy6bXIlNRnSNQmwyF/4MZxDMI6TDcp2b3qddDrIXwZ8T8t642147VGVjqFlb4gc8z4sPhDc8//7xyeAEy9YJtI27Odz3v6uba4O9JgARIgARIwGwCRtahZvvC9qwjQAHLOrZRb1ldnDfXMQQuLFzVuivNXR/O741MHHq+FFPACmc0Ql+rR8BCnSBsy0FB8aZZMv73h9q+AzEAxZ7DNWwNUmtmqfeiMDUWqhCykLnjn12CzBi1ADeyaXBUfFMLJmD514eCeARBLpihX7XgNWpxYasbDBlX9997vyZg7azYKe3SAm//CyVqYBsksmewAEX2E7JKIKpBlMP2yVCnpzUnYMFPZBmBD7YfooYWMmNU8y+AD0FFzYYLd+z0ClhNT4ls2o+65RHCRKDi6c1lYEEERRZhuIatodgiClOz+vDnSIp/6xWwIEQhCyhc8z8lEkXK1a1xED+x1TCY4TmHWAqzUsDC1lDUn8JzZ7aZmYFltm/NtWe1gBWsf9TYGz16tFKLDEX8UZctXNPzrg63TV5PAiRAAiRAAkYJGFmHGu2b90ePAAWs6LG2vCcIBfgP/wqPhRayWJD9gn+px4If/zKP7UPIzrLKjEwcer4UU8Ayb+T8F9YQi9QFJsQH/As9tpogKymY+d+PbD41u6Hp9RC3VDEgHO/9TzBU78MJb2pBbPSPmjOqXXXVVco2MWwBQ7ZNXl7eft0FEzxQ40v9XASqj+PfEIqCgw8MIhnEIBhqXj04/UFNwCrYWyD5rfMDhtycqPHOO+/IJZdcsl9GCMYEgha2GQYSJ/QIWNiWqNaBappRBIEMW0GxzUutexbOmKnX6hWwIKCEEpjUU+6C1RZqTsDyPzggnDjUkwRxDz4b6ul2yGBTx15ve82NtdqOvxijt21c58/wwQcf1LJqIISqRfsDtYeMXFXkNUPAUgvcoy9kMkEogXCFjEjYww8/rJ0OGk58oa41swaWWT7pbaelBCz4p26XxZ+RWavWJ9Tru553td62eB0JkAAJkAAJmEXAyDrULB/YjvUEKGBZz9hVPRiZOPR8KaaAZd7jpKeIe6je9C7McXqfus0Oi2YIqdhCWFXRUMssKSVeMnJTG3WHbYdNT8iEIIsC2dXV1YqIg/ZgHo9HuRZb4EJtS9MjYKFNtVB7oPiDCVg4dfDh+x7WBKzCykLJS91fREObethhmx8ygbDAxHZInArobxD4kD0RThF39X71pEYIRDjREOafwdYcg+aeQrsIWBBo1GcEwh3ETT3mfzJgtAQsf/EJNcjULL/m/EVmpJod6d8G6tWhNl0wM1vAQg2vpoY6ZsgchJiFbEKcgtf0FMbm4gv1ezNPIYy1LYShuGE7tjq3QihH5l44puddHU57vJYESIAESIAEzCBgZB1qRv9sIzoEKGBFh7NrejEycej5Uswi7uY9StESsPxPIHz55Zfl3HPPlYqSaqksbRCwklsnSlZ+YwErWKRnnXWWUgg+NzdX2QIHUQIF33GqFgyCmVqjqmkbVm4hXFeyTmY8OEOefOhJpdvCvYWS1zqwgOVfmwkCkp4tlihw/8EHHyhZZliAwh599FG5+uqrtTD1ZGDhYmzNRHYShCZkyGCrqCr2YEshMtgiOZ1MdcQuApZ6AiH82rJli1LfK1yL1hZC/xMuIVhC+AnX/EWpaG8hDCRgwf9ly5YJBFPUrkPWIPwyy5BpjNN0Ydg6qWbKBWofv1eFmkBbQWOtiHsoxtierJ76iewriOThmJ53dTjt8VoSIAESIAESMIOAkXWoGf2zjegQoIAVHc6u6cXIxMEvxdF9TKIlYCFzCFlTWOCqW+5QwB1ZWKqlpCVKZpt9AlZ9ba3U1VRLUkqqxAfImEEx7wkTJijXQtDBqXnIRsIJe6jrhCwsHF4QyMwo4u6/JdK/iPvve36X5558Th6+42Gl6/Xb1kuPjj0C+oGtVeoJoHoFLLUhCDEDBgwQFPJGNtv333+v9aFXwEJ2F4q5Y0scimDffPPNWnH38847T2FpxOwiYEHohOAJCyVshooVJ+mdccYZyiXY9qWe4qiXj38NuFBjjVM/1ewkZFLddNNNervQrkOGk3qyZHNF3JGpiAwmmBlbCIMJWGgfz9Qrr7yi9NXcaYHhBI0+IUpC0O3fv79yimkww2cG2yqReYTPUNNacm4SsPznCTzb2LIcjvFdHQ4tXksCJEACJBAtAkbWodHykf0YJ0AByzhDtuBHwMjEwS/F0X2UoiVgISoILajNhqyetWvXSkp8hlSV+wlY6YmSmZcqtVVVsmfnNvF5fdIqLk7yOnWRhKSkRmBqa2ulffv2Sp0d1NZCHSdsocJ2JZwQh5+DWaiaSePGjVMW18hMQFZSsGwdZHoh4wtbojZv3qwIP7DVxavls48+k6un7suIem/ue3L6KacHdAU1phYtWqT8LlwBC/eoWwCxRQxbxVTTK2DherBCRly3bt2UU9nU0/Ui8adpkHYRsEpKShTBAqdL4hlcsGBByCL4gQYLbeBZgGCI2mHYahkfH6/7w+q/NROnwKmZgk0bQIYSxgJzaM+ePZXTF8Ott4XtrXge8dk4+OCDBdsmAxX9x3Y59IHPEsxqAQvCEeqrIUYIbBgHs0w9lADtBTu90b/GHa5/8sl9WZItaS1ZA8u/3lpzdegCMeK7uiWfHPZNAiRAAiQQjICRdSipOocABSznjJUjPDUycfBLcXSHOJoC1ieffKKcpAfDyXKvzH5DkuMbTr9LTU+S9NwkKdi4QaqrquXVN9+UcyadJW3ad5D03P234aFGFbZcIdPqiSeekIsuukhpu7mCxKEELP9tfdhWg+yUpjWTUHNK7QviGWpUqbayaKXsLtgtYwaPUY6tP+6E4+TzTz/fT0BoWqy7qWCEDDNsKQx2SiiyR1CcG9lTEEMgiqgWjoCFrVxqEXwIgtiOie1Y+ByGOulQz1NqFwELviKTCQXEYdhu+c9//rNR3TD/eJC9h/pTF198caMwr7/+euU+2JVXXimPPfZYQEbYmgXxyP/EToicEKZgEE5CncbnX1wbmWMQGJOTkwMiRz04ZMrBH3/z99X/hEL1GjybyFqEWKua1QIW+lG3/uLPX331lXISnhmGE0RxWibq4A0dOlTZouifgYnPCeYcZLhBdMYhBX369DGja0NtRCJg+WeJBRKaMXdAHFdF9UAOgg/m4oqKCoXHb7/9FrLYf6A2+K42NPS8mQRIgARIwCICRtahFrnEZi0gQAHLAqhubtLIxMEvxdF9cqIpYCGya665RmbOnKkE2a5tO/nzlAtl2GHDJTc7VzytamXDxlUy/+uv5ZPP50lJaamsXfaz5LZtKzntO+4Hxn9bFoQeZMlgmyIyS0JlxzR3ah1EKWwRhCHLCdv8sDUJogS2oEHAwrYl1N9CYWq1EDL+bkXRCuW+Gy+9UT559xPlz6eccopSawq+QciAIIHtOsgGwnYvWNOFKMSrxYsXK4vMY489VtkuiNMg4QMW4aiBBRELhu1tp5/ekOUVjoCF+yGEQQBQDZlYt99+u+EH0U4CFrKSINQhEwp20EEHKSc8IkMpLS1N4YpsJ5ykCVHnwAMPVDj7GzK4hg8fLupJe8jEQk0lXIuMPcx7qFv12muvyfTp0wVCg7/hFFhcg1pjqFsG7upzimcDW19heI4mTpyojCsMgiL6GTZsmPIMQLRCNhM+ux9++KGSoYXTZv0N20MPOOAApT8YDlBAdh1ENYw1hDg8XxB71DijIWD9/PPPymcKhuf6yy+/NPycqQ3ccsstgm2XsCFDhiiiJdghkxIiHvqG4br777/ftH7DaQjbWSEaqYYstOeff175EaK4f80zCMo4bbSpNSdg4fd4BjF34FRYZL1hfsRnACwgzr755ptKJhxs2rRpghpv4Rrf1eES4/UkQAIkQALRIGBkHRoN/9iHOQQoYJnDka38QcDIxMEvxdF9jKItYGFxDoEE/yELJJShkPhvi36U7Ly8gAIW2kJWiyrkoC1k10AcCGXNCVg43XDKlCmagBCorY4dOwqytSCAqOb1eQUZWLDCgkKZOn6qbFq/KaArkydPVjJ8jjvuOOX3gQQsCHShDCcP3nPPPfuJTeEKWMhMUmstoc1NmzZFVOi8qa92ErDgG7aXYnH/7rvvNvshQ2YQMoSaGoQiiEvNFSGfPXv2fgKWf2ZV03abXo8sLjzLKEgeqq4U2oEghoLkTQ2CHJ4vZNUFMrCAqHfBBRcov46GgIV+IKwgGxMWbLtfswMU4AIIMhAlITAHM4hEKOLuf2pnJH1Feo869+i5H2OD+bmp6RGwQm2hVttDhhqEVrUOnx6f/K/huzpcYryeBEiABEggGgSMrEOj4R/7MIcABSxzOLKVPwgYmTj4pTi6j1G0BSw1OiyWZ/7zCZn/7deyafNGKSsvU7b8dGzfXg4YOFBGHn2UjDv+eElPT5ek1FTJ7Rj45Dj/rWFoGzWl1CLYwUg2J2Cp9yFTAVt8UDsHwgUydVBvCtlO2LIF3/yt3luv1MBSrbSkVN5/9n15/733lcwr3I+sGGx9/NOf/qQsTtUtVE0FLJwAiO2LuAbbnSBCwAdk20C0w3YoFMMfPHjwfmGGK2ChLwhysKbbEY08jXYTsNRYkPWCBT6ypVD4G9vLUJcN2TrIcoLAgu2jobL4kB2F4v14NnBAAWIFQ2Rl4fmAyBVo2x/EM5wS+L///U+Ki4s1ETeQ4AV/ke2FbbJ4DvAMIXsHzx1EK/Q1duxYJcMv2BZD9IHsI/iL+5HlhYwxCD3IyvLfwhYtAcu/yDxqzkEINtMgjkGkQoYZPjNt2rRR5gRksYFXS1o0BKyCggKFKURWbA3Ellj8HUQ7ZI0iIwvZb8jIC7XNsDlOfFc3R4i/JwESIAESaAkCRtahLeEv+4yMAAWsyLjxriAEjEwc/FLsnseqtKBSaqoasrB83kLxeT37AUhISpY2XbraHkytp1ZwCqG/DcgbIHGt4mzt+7x58xTBBoZ6XthCSSMBEiCBUAT4rubzQQIkQAIkYEcCRtahdoyHPgUmQAGLT4apBIxMHPxSbOpQ2LqxkoJKqfUTsLz1uwL6G5+QIPndetg6FjhXXV8t60rWNfJzYN5Aw8XQrQ4cmTio7ZWXl6fUDwuWzWO1H2yfBEjAOQT4rnbOWNFTEiABEnATASPrUDdxcnqsFLCcPoI289/IxMEvxTYbTAvdKdlVKbXVagaWT7z1BQF7axXXStr16G2hJ+Y0XVlXKRtKN2iNIfMKGVh2NhR1RoF61CO74YYbBKcj0kiABEigOQJ8VzdHiL8nARIgARJoCQJG1qEt4S/7jIwABazIuPGuIASMTBz8Uuyex2rPzr1SV/PHlkGfV7ye3UGDb9ejl7SKs/dWvIraCtlU1lC0PSEuQfrl9rPdgCLLCifqofA3aogtW7ZMqa0FMUuthWU7p+kQCZCArQjwXW2r4aAzJEACJEACfxAwsg4lROcQoIDlnLFyhKdGJg5+KXbEEJvipL+A5fPVi89TFLRdbCHEVkI7W1lNmWwp36K5mBSfJH1y+tjO5VGjRknTEw6ReYUMLBoJRJsACozjv3AtKSlJOVSB1jIE+K5uGe7slQRIgARIIDQBI+tQsnUOAQpYzhkrR3hqZOLgl2JHDLEpThbv2Cv1tfsysHy+OvF5ioO226ZLN0lISjKlX6saKakpkW3l27TmkxOSpXe2/bY+qgJW69atFQHgmmuukalTp1qFhe2SQEgCd999t9xzzz1hU8JpnDhxk9YyBPiubhnu7JUESIAESIACFp8BEQpYfApMJUABy1ScMdtY8fa9Ul+nCli14vPsCRprbqfOkpSSamsWxdXFsqNih+ZjamKq9MzqaWuf6RwJtDQBClgtPQKR9U8BKzJuvIsESIAESMBaAkbWodZ6xtbNJEABy0yabEuMTBz8UuyeB6hoe4V46rxKwD5ftfg8pUGDz27fUVLS0mwNp7CqUHbtbThJMS0xTbpndbe1z3SOBEiABCIhwHd1JNR4DwmQAAmQgNUEjKxDrfaN7ZtHgAKWeSzZkggFLD4FuggUbasQT/0fApa3SnzesqD3ZbVtJ6kZmbrabamLCioLZHdlQyH6jKQM6ZrZtaXcYb8kQAIkYBkBCliWoWXDJEACJEACBghQwDIAz0G3UsBy0GA5wVUjEwe/FDthhM3xsXBrhXg9qoBVKT5vedCGM9rkS1pWtjkdW9QKsq+QhaVaVnKWdM7obFFvbJYESIAEWo4A39Utx549kwAJkAAJBCdgZB1Krs4hQAHLOWPlCE+NTBz8UuyIITbFycIt5eL1+pS2fN4K8Xn3Bm03PSdX0nPzTOnXqkZQ/wp1sFTLScmRjukdreqO7ZIACZBAixHgu7rF0LNjEiABEiCBEASMrEMJ1jkEKGA5Z6wc4amRiYNfih0xxKY4uXtLufg0AQt/rgzabuusbMlsk29Kv1Y1sq1im5RUl2jN56XmSfu09lZ1x3ZJgARIoMUI8F3dYujZMQmQAAmQAAUs1z8DFLBc/wiYC4AClrk8Y7W13ZvLxef7IwPLUyY+X1XQUFMzMiSrrb3FoC3lW6SspqGOV5vWbaRd63axOnyMiwRIwMUEKGC5ePAZOgmQAAnYmICRdaiNw6JrTQhQwOIjYSoBIxMHvxSbOhS2bqxgU4PY4/OUiM9Xo/nbqlUrTdzCXya3TpOcDvbejrepbJNU1FZoMbRt3VbyW9s7a8zWDwidIwESsC0BvqttOzR0jARIgARcTcDIOtTV4BwWPAUshw2Y3d01MnHwS7HdR9cc/5B5hQws1XyePeLz1Wo/JyQmSn1dnfZzYkqK5HXqYk7nFrWyoXSDVNY1bIPE9kFsI6SRAAmQQKwR4Ls61kaU8ZAACZBAbBAwsg6NDQLuiIICljvGOWpRGpk4+KU4asPUoh01FbC8nmIRX4NgldS6tdRWNohBCUlJ0qZLtxb1ubnO15Wsk+r6au0yFHBHIXcaCZAACcQaAb6rY21EGQ8JkAAJxAYBI+vQ2CDgjigoYLljnKMWpZGJg1+KozZMLdoRTh/EKYSqeT2FIj6P9nNqZqZUlTVsMYyLj5e23Xu2qM/Ndb52z1qp8TRsg+yc0VmykrOau42/JwESIAHHEeC72nFDRodJgARIwBUEjKxDXQEoRoKkgBUjA2mX+IdQEgAAIABJREFUMIxMHPxSbJdRtNYPr8crhVsb6kV563eLiFfrND03TyqKi7SfUROrbY9egv/b1dYUr5E6b0MWWdfMrpKRlGFXd+kXCZAACURMgO/qiNHxRhIgARIgAQsJGFmHWugWmzaZAAUsk4G6vTkjEwe/FLvj6fHUe6Vom7+AVSAi+04khGW1bSelBbsawYCAFRcXZ1tAq4pXicfbkEXWPau7pCWm2dZfOkYCJEACkRLguzpScryPBEiABEjASgJG1qFW+sW2zSVAActcnq5vzcjEwS/F7nh89hewGotVuR07S/H2rY1g5HfrLvEJibYFtKJoRaOTE3tm9ZTUxFTb+kvHSIAESCBSAnxXR0qO95EACZAACVhJwMg61Eq/2La5BChgmcvT9a0ZmTj4pdgdj099nUeKt+/dF6zPK14PthA2GMSq3Zs2Nvq7vM5dJTE52ZaAUJQeApa/9c7uLckJ9vTXlhDpFAmQgGMI8F3tmKGioyRAAiTgKgJG1qGuAuXwYClgOXwA7ea+kYmDX4rtNprm+vPbb7/Jgw8+KPPnz5ddu3ZJXd2+mlHzPnxfDhg4UOsM2wULN20Qr7ehLlZux06SlNraXIdMag1bB7GF0N/65PSRpPgkU3o4//zz5d///rd069ZNNm5sLOyZ0gEbIQESIIEwCPBdHQYsXkoCJEACJBA1AkbWoVFzkh0ZJkAByzBCNuBPwMjEwS/F0X2WvvnmGxk9erTS6V133SV33323ZQ4sWbJEjj76aKmqqtqvj0YCViuRdj16S+GWTeL5Q+DCDdntO0hKWrpl/hlpuM5TJ2v2rGnURL/cfpIQl2CkWe1eMwSsYAXwExMTJScnR/r37y8nnHCCXHLJJdK2bVtT/A7WSH19vTz33HMyZ84cWbVqlVRUVEjHjh3luOOOk6uuukoGDRpkaf+hGodvv/76qyxatEgWL16s/H/FihXi8eyrb7Zhwwbp3r27Yf/Kysrkk08+Ufr46aefZNu2bbJ7927l85GdnS0DBw6UcePGyUUXXSR5eXmG+2MDJGAmAb6rzaTJtkiABEiABMwiYGQdapYPbMd6AhSwrGfsqh6MTBz8UhzdRyWaAhbEkXnz5klmZqbcN/1+6dNtoKSkpIrPVyfdu+RIyh/bA+Pi46Rt915StHWz1NXUaECy8ttJamampYAg4N1zzz1KH9gWqNdqPDWyds/aRpcPyBsgca3MKTpvpYDVNMbc3Fx57bXXFDHLCissLFSEGQg3gSw5OVmeeOIJufjii63ovtk2Mf6hhFyzBKwvvvhCjj/++Gb9adOmjbzyyity4oknNnstLyCBaBHguzpapNkPCZAACZBAOASMrEPD6YfXtiwBClgtyz/mejcycfBLcXQfh2gJWNgqmJ6eLrW1tXLDDTfIffc+ICW7Kv8QimrE5ynRAo9PTJT8rt2lePs2qa3adw0sI6+NpGXnWAooUgGrqr5K1pesb+TbwLyBEizrKdwgzBSwhg4dKrNnz9ZcKC8vl7Vr18pTTz0lP/74o/L3aWlpShZSjx49wnU15PXIYho1apQsWLBAue6MM85QMr4gmi1cuFCmT58uBQUFymmTH330kYwdO9bU/vU05v8MpKSkyMEHH6xkRq1bt0653UwB68ILL1QyIA899FDp0qWLdOjQQdk2izn07bfflnfffVfJ/EpKSlIywQ466CA9IfAaErCcAN/VliNmByRAAiRAAhEQMLIOjaA73tJCBChgtRD4WO3WyMTBL8XRfSqiJWDt2LFD2SIGe+aZZ2TqeRc0CFjeavF5S7XAE5KSpU2XrlKya4dUV1Rof5+WkysZudZupYpUwKqsq5QNpRs0X5F5hQwss8xMAWvkyJGCcW9qyDibNGmSIpzA/vrXvyqZUGbaCy+8oGyJg11xxRXy5JNPNmoeQhrEHGyv6927t6xcuVISEszZhqk3js8++0ypMzZs2DA58MADlf5V/mjDLAELwlR8fHxIt95//32ZMGGCcg3+D0GLRgJ2IMB3tR1GgT6QAAmQAAk0JWBkHUqaziFAAcs5Y+UIT41MHPxSHN0hjpaABUFAzeZB9s85Z58rpQV/ZGB5K8XnLdcCT0pJldxOnaVsd4FUljUIW60zsyQz39raTJEKWBW1FbKpbJMWA2pfoQaWWRYNAQu+IssIwhGsX79+Sn0qMw11nSBKIeNqy5Yt0rr1/kX5UeT/lltuUbp988035ayzzjLThYjaskLA0usIapOtXr1asJUQmWA0ErADAb6r7TAK9IEESIAESIACljufAQpY7hx3y6KmgGUZWtMbbk7A8v/9119/rWz/gqjw9NNPyy+//KIU3+7ataucdtppcvPNNyvChL/5C0LBnL/+quvkhqsu036d3DpNUnNy5YmZj8oHH3wgq39fKyWlpZKVmSkHHXywnHPOOTJ16tRmM3NqamqUk/vQxv/+9z9B7SVk06AA9xFHHKEII6jzhG1+L774olxwwQXN8g2UfYNMmmdnPyuvvfmarPxlpZTsKVG24A0aOEjZInf55ZdLampqyLYh6jz00EPy5ZdfKiJFfn6+UvD+2muvlcMOO0zLADJyCqG6nTFYBhYcRBZWRkaG7N27VxGX8H+zbM2aNYooBrvssstk1qxZAZveuXOnspUOhrF+9dVXzXIh4nZaUsDC+KPIO7bgYrsnjQTsQIAClh1GgT6QAAmQAAlQwHLnM0ABy53jblnUFLAsQ2t6w+EIWBBXkD2FgtKBDJk73333nbRv3177dSQC1u+bNst5F14kmzY1ZDQ17Q+L+rlz50q7du0C+gLBCuIRBKdQpgpSkQpYmzdvllNPPVWWLVsWtBtw+fjjj6Vv374Br4Eg+Oc//1kguDU1CG7/+te/FK4Q46wWsNA/TsArhWCYlSUlJQ21yYw+fP7bB1EkfvLkyUGbhNAFwQviaKjnwKhPeu9vKQELmVcHHHCA4GRE1C4LVvhebxy8jgTMIkAByyySbIcESIAESMBMAkbWoWb6wbasJUABy1q+rmvdyMTBL8XRfVzCEbCOPPJI+eGHH+T0009XBBeIKbt27VLqGEGggUGUgDihGgpy47/t27drp6ihUPdJx4+TipJ9gk1edoq0yUtT/rxh4yYZe8ZEKS0rU04rnDrlHBly0GDp2KGDlO+tlG9++K+S/YUF/eGHH64IO4mJiY2gIZsJ9YuQHQZD7SD41bNnT6UgNoSRzz//XN577z357bfflIwsCDV4blHIXM0MQhHzpgZhRe2vqKhIhgwZomyFw8l5E8+dKEOPHCodu3YUb7VXfv3hV5k5c6ZUVlYqfS9dulQRhfwNggS4Ih60gYwrnNCHP6Oo+f333y/oB1vvIJJZLWD51ypDwXAIgWYZivf/4x//UJr7+eefleLowQwZfR9++KGSHYesI2S0taRFU8DC87Jt2zZFoH344YeVzxgMwvGf/vSnlsTAvklAI8B3NR8GEiABEiABOxIwsg61Yzz0KTABClh8MkwlYGTi0PWl2OsVqSo21WfbN5aaKxIXZ7qb4QhY6Bzi02233dbID2w7O+mkkxRRCBlDEKuwBc7fmtbAOvvMKVJeVK1c4vOUis+378+nTposi5cuVYShD999VxI8dVoz6umEn376qZx88snKaW0oCI9T7PwNRcAhFuEkuzlz5gTN9IEwhG1y/tv7wqmBBTEB29sgKr3zn3ckJT9FcyM9KV26ZXZThBpsBcRWvFtvvVXuu+++Rr6q28Mgin3xxRdyzDHHNPo9hIzhw4cr4hrMagHrqquukscff1zp695775Xbb7/dtGcOIuIbb7yhtIdtkqjpFMyuvPJKrcA76nCpWw/V6yE6Gs3MuuuuuwTjrcesFrCaywDE9lyImWadaqknZl5DAqEI6HpXEyEJkAAJkAAJRJmAkXVolF1ldwYIUMAyAI+37k/AyMSh60vx3kKRR3q5C/3f1omkBV/wRwojHAELwhAyhgItonFyG0QsGGpOYVudv+0nYE2cIuXFqoBVIj5fjfy4eLFMOGdfhgnqa/Xt1VP27NiuNROXkCBtu/VQfj777LOVWlzIXvr++++1ayCinXjiicrP11xzjcyYMSMsNHoFLMSDrYHI6EKmzLBjh8nuyoYC2xlJGdI1s6vS90033aRk0uAURghSqoElMsVgEGxU4aipw4gT8cKsELCQ4YTPHfrHNkUIkn369FEywHJycsLiF+piiI6ffPKJcklVVZWkpDQIfk3vU5nh71H/Cc+ev7lFwEKWGkRaCJ00ErATAV3vajs5TF9IgARIgARcQcDIOtQVgGIkSApYMTKQdgnDyMSh60sxBSzThjocAQvbv6677rqAfaNAupp1BdEI4pG/NRWwJk2cIhV/CFhezx4RX61Me/AhmfXc89K3Tx9ZvWaN1FZVSfH2fZlHsLj4OGnbfZ9wiW2LEH2QuYQtV8j8gvlnEKFPCD7hmF4BS+0fGVxlZWWyu3q3FFUVaV1lJWdJ54zOys/YXnnKKacof0bWEOo6wR544AElKwu2ZMkSOeSQQwK6WldXJ23btlW2OZohYIXiAXES4iO2UkJwM9PGjBkjX331ldIkhD9kyAWzO++8U8kAg2Gb6IgRIxpdim2gtbW1htwDU/ynx6zOwFK3sMIXiHs4DRLCJba59urVSx599FHtGdLjL68hAasJ6HpXW+0E2ycBEiABEiCBJgSMrEMJ0zkEKGA5Z6wc4amRiUPXl2IKWKY9B+EIWBBiUJ8pkGE7X3x8vPKradOmyR133NHosv0ErDOmSMWefRlYXk+RiK9eJv7pPPlh4cKwY0ONIFWIwHa9BQsWRFz8W6+AhRMLse0rXENWk5p1NWXKFKVeWFJSkiLCqfwCtXnssccKToG0WsDq1KmTUmsJp02abWZmYJntW3PtWS1gBev/5ZdfVk7chLD4/PPPK6dR0kjADgR0vavt4Ch9IAESIAEScBUBI+tQV4FyeLAUsBw+gHZz38jEoetLMQUs04Y8HAELAkooYUPdWhiotlBTAeusCefI3j+KuHs9hSiEJSNPGidr1q4NOzb1JEHcOGDAAEHNJBR4//HHH8NuS6+A5S/GhNOJP0NsucTWS5zaiOLpoeycc86R119/3RQBC6fZ4TRJGLYL7ty5U8lyeuyxx5TTB1FAft68eUrtLjPNzBpYZvqlp62WErDgm7pdFoXsceplbm6uHpd5DQlYSkDXu9pSD9g4CZAACZAACexPwMg6lDydQ4AClnPGyhGeGpk4dH0pZhF3054DWwhY9QWQUmTECSfKuvUbZPCBB8qcV1+V+ro6KdnZUAMLQed26rLf1jP/kwGjJWCp4hMKkUOU2rl3p1TU7jv1EJaTkiN5qXn7jVOPHj20E/XUNjp06KAUvg9lZgpYI0eOFIx7U8OJjKgphppYXbp0UU5oxEmQZpmZpxDG2hbCUIxxUIB6+iAOJUDmHo0EWpqArnd1SzvJ/kmABEiABFxHwMg61HWwHBwwBSwHD54dXTcycfBLcXRHtKUErDNPP0cqS2uUYL31u5T/qycQ9urZU9auWyee+nrZvWlDIyBtu/eUuD+2KgYiFa0thOoJhMhWwgmDW/dubSRgtUtrJ21SQxfdV0WpaG8hDCZggecTTzwh//d//6egxQmEah0qM57KF154QS666CKlKWydREZWMIMoCZEK9cICnTYYa0XcQ/FFNtwJJ5ygXIKTCG+55RYzhoNtkIAhAnxXG8LHm0mABEiABCwiYGQdapFLbNYCAhSwLIDq5iaNTBz8UhzdJ6fFBKzTJktlGYpw+8SrZGCJ3Hr3PTL7lTlKvR9kJLXNz5eCjesbAcnv1l3iExKDQrr66quVrXCwSIq433PPPYJthDBsrwtmf//73+Vvf/ub8mtsVWzbv61U1lVql7dPax8wA8u/PYgRt912m/JXoYq419fXKzW+9uzZY8oWwlACFgrGQzzCtkxsWQNDZJmZYRCk0Dbssssuk1mzZgVsFlsakZUGg8iHDKSm5iYBC7XWUHMNhmdbFRjNGBO2QQKREuC7OlJyvI8ESIAESMBKAkbWoVb6xbbNJUABy1yerm/NyMTBL8XRfXxaSsCaeOpkqSqvFfF5xevZrQT9zXcL5JwLLlT+fPPNN8v9990nuzasawSkTZdukpCUFBTSF198Iccff7zye4hZOL0tHHvooYeUvmHV1dVKPahAtnr1aqXeFkQuZBJNnzVdquv3FaWHdUrvJNkp2SG7XrRokVKrC4bTE2fOnBnw+rfeeksmTZqk/M6MIu6hBCz08cwzz8ill16q9IdTEu+7775wEIa8duDAgbJy5UqljtOWLVsEpzg2tQcffFDLMsJJfGeddZZp/UfaUEvWwPKvt9ZcHbpI4+N9JBAuAb6rwyXG60mABEiABKJBwMg6NBr+sQ9zCFDAMocjW/mDgJGJg1+Ko/sYtbSA5fPViw+nEP5h4yaeKT8v+0U5kQ/1fkYOPaQRkLzOXSXxD1Hp119/VTKExo8f3+gaFClHRlNcXJzSRrCtakVFRYqAkpqaqt3/0ksvKae+wZYvXy4QXIKZWlwbv7/53pvl3MvO1S7tnNFZspKztJ+R0YRMLWQU+duhhx4qS5culcTERPnqq69kxIgRjX6P4u7Dhw9XinfDoiFg1dbWSs+ePWXbtm2SlZWlbOHD/80w/22Ef/3rX5Uti/62bt06OeSQQ6SsrEx69+6tiF0JCQlmdG2ojUgELP8ssUDZfMiswrOZkpIS1LcZM2bIddddp/we9dMwP4Y6rdJQkLyZBMIgwHd1GLB4KQmQAAmQQNQIGFmHRs1JdmSYAAUswwjZgD8BIxMHvxRH91lqKQHrjPFnS3VFnfh8deLzFGtBb9q8WcadOUmKi/f93QljjpVTx42Tnt27KbWvaiROflu+XObOnasIQtdff71gO5+/QfQYNmyYVFTsK6p+xhlnKEIBRBmPxyNr166Vzz//XN5++22lUDmEBtXwuz59+uzr+4QTlC1+2M6mnrCIa1VBBT4edthhsn79vm2OQ48YKuMnjZfe/XtL19yuUl1WLcuWLZNPP/1UEacmTJig9OlvCxcuVEQrbBOEkHHttdfKuHHjlMwv/A7bDAsLCxUhDW1FQ8CCf8hcgy+wadOmyR133GHKgwn+yAD7/vvvlfYmTpwol1xyieTk5Agy0lBzq6CgQBEfP/roIxk7dqwp/YbTCJ6bpuP03HPPaT4/8sgjjbZVHnzwwYL/mlpzAhZ+j4L5YIBnoFevXpKenq78HcRZiK8qJ9RJ+/jjj+W4444LJxReSwKWEeC72jK0bJgESIAESMAAASPrUAPd8tYoE6CAFWXgsd6dkYmDX4qj+3S0mIB1ytlSvRcCVq34PHu0oCFSldTWK4t6iEvNGWpW3XnnnftdhgwsCEbYphbKkBnlL2DhWv/Mqqb3Nr0e9Zqwve+7775rzlWljhEykJoaCpojwweZT00NYtlTTz2lCBn//ve/oyZgVVZWKn1BPMvLy1My3SCumGFoEyLd4sWLAzYH8Q6ZWRdffLEZ3YXdBmJFtpNeu+uuu7S6af736BGwAhWob9pv586dledG3Rqr1y9eRwJWEuC72kq6bJsESIAESCBSAkbWoZH2yfuiT4ACVvSZx3SPRiYOfimO7qPRUgLWhJPPlppKCFg14vOUaEHHJyZKftfuSqYU6h+9+vJLypbCouJi8Xo8ipjSr39/JWMFAhW2mwWzqqoqQebM+++/r4hhyJhClhPEiSOOOEIRqo499tj9bkchc2QgIQsHta6QEeP1epXrAgle+PtZr82Sj9/9WJb9tEyKCoqkvq5esrOzlWwu9HXqqafKMcccE9TXFStWCGo/ffnll4polJ+fL0cddZSyfQx1stQtbNHKwIKj/kXmH374Ya1ovRlPKDLOnn32WaVAOzLmcJJjx44dZcyYMUrtskGDBpnRTURtREvAwrOFrCqIk8j827Vrl2BbK7a0omg/srpOOeUURSANVCssouB4EwmYRIDvapNAshkSIAESIAFTCRhZh5rqCBuzlAAFLEvxuq9xIxMHvxS743kp3V0pNZX14vNVi89TqgWNAu0o1K7a7s0bxVNXp/2c3a6DpJiUCWQWaa/PKyuLVjZqrnd2b0lOCFwA3qx+2Q4JkAAJtBQBvqtbijz7JQESIAESCEXAyDqUZJ1DgAKWc8bKEZ4amTj4pdgRQ2zYyZKCSqmtqheft0p83jKtPRRoR6F21Qq3bJb62hrt56y27SQ1I9Nw/2Y24PF6ZFXxqkZN9s3pK4nxiWZ2w7ZIgARIwDYE+K62zVDQERIgARIgAT8CRtahBOkcAhSwnDNWjvDUyMTBL8WOGGLDTpbsqpTa6gACVkqK5HXqorVftG2L1FVXaz9n5reV1pnmnIhnOIg/Gqjz1MmaPWsaNdcvt58kxLX86Xlmxch2SIAESMCfAN/VfB5IgARIgATsSMDIOtSO8dCnwAQoYPHJMJWAkYmDX4pNHQrbNrZnV6XUKQJWpfi85ZqfSamtJbdjJ+3n4u1bpbaqSvs5o02+pGVl2yqumvoaWVuytpFPA/IGSFyrOFv5SWdIgARIwCwCfFebRZLtkAAJkAAJmEnAyDrUTD/YlrUEKGBZy9d1rRuZOPil2B2Py56de6WuxiM+717xeSu0oJNbp0lOh47az3t2bJOaysoGASsvT9Kyc20Fqaq+StaXrNd8aiWtZGCbgbby0QxnUMAexdbDtZycHOnUqUGUDPd+Xk8CJGA/AnxX229M6BEJkAAJkICIkXUo+TmHAAUs54yVIzw1MnHwS7Ejhtiwk8U79kp9LQSsCkXEUg0F2lGoXbWSnTukem+DwJWekyvpuXmG+zezgb11e2Vj6UatSWReIQMr1mzUqFEyf/78sMOaOnWqvPjii2HfxxtIgATsS4DvavuODT0jARIgATcTMLIOdTM3p8VOActpI2Zzf41MHPxSbPPBNcm9BgGrXNlGqFpqRoZktW3fIGDt2inVFQ1bDNOycyQjr41JXpjTTHltuWwu26w1htpXqIEVa0YBK9ZGlPGQQOQE+K6OnB3vJAESIAESsI6AkXWodV6xZbMJUMAym6jL2zMycfBLsTsenqLtFeKp8yr1r/wFLBRoR6F21UoLdklVecMpha2zsiWzTb6tIJXWlMrW8q2aT0nxSdInp4+tfKQzJEACJGAmAb6rzaTJtkiABEiABMwiYGQdapYPbMd6AhSwrGfsqh6MTBz8UuyOR6VoW4V46r3i85SJz9dQpL2pQFVWWCCVpaUalNTMTMnKb2crSCXVJbKtYpvmU0pCivTK7mUrH+kMCZAACZhJgO9qM2myLRIgARIgAbMIGFmHmuUD27GeAAUs6xm7qgcjEwe/FLvjUSncWiFeDwSsUvH5qrWgm24RLC8qlL0lexoErCZbDO1Aq7iqWHbs3aG50jqxtfTI6mEH1+gDCZAACVhCgO9qS7CyURIgARIgAYMEjKxDDXbN26NIgAJWFGG7oSsjEwe/FLvhCREp3FouXo9PfJ4S8flqtKCbFmmvKC6Sij3F2u9T0tIlu31DkXc70CqsKpRde3c1xJCULt0yu9nBNfpAAiRAApYQ4LvaEqxslARIgARIwCABI+tQg13z9igSoIAVRdhu6MrIxMEvxW54QkR2b0Htq/0FLBRoRxaWahCvIGKpltw6TXI6dLQVpILKAtlduVvzKTMpU7pkdrGVj3SGBEiABMwkwHe1mTTZFgmQAAmQgFkEjKxDzfKB7VhPgAKW9Yxd1YORiYNfit3xqOzeXC4+n0+8nj0ivlot6Iw2+ZKWla39vLe0RMoLG8ShpNRUye3Y2VaQdu7dKUVVDSJbVnKWdM6wl4+2AkZnSIAEHE+A72rHDyEDIAESIIGYJGBkHRqTQGI0KApYMTqwLRWWkYmDX4pbatSi22/B5nIRRcAqFvHVaZ3jBEKcRKhaZVmplO0u0H5OTEmRvE72ym7aXrFd9lQ31OnKScmRjun2yhKL7uiyNxIggVgnwHd1rI8w4yMBEiABZxIwsg51ZsTu9JoCljvH3bKojUwc/FJs2bDYquGCTWWKP15PkYivXvMtq207Sc3I1H6uKi+T0oKG+lIJycnSpnNXW8WyrXyblNSUaD7lpeZJ+7T2tvKRzpAACZCAmQT4rjaTJtsiARIgARIwi4CRdahZPrAd6wlQwLKesat6MDJx8Etx7D8q2DqILYT7BKxCEZ9HCzq7XQdJSU/Xfq6uKJeSXTu1nxMSk6RNV3sVSN9SvkXKavYJcrD81vnStnXb2B9IRkgCJOBaAnxXu3boGTgJkAAJ2JqAkXWorQOjc40IUMDiA2EqASMTB78UmzoUtmwMxdtRxF0RsOpR38qr+YkC7SjUrlrN3r2yZ+d27ef4hATJ79bDVnFtKtskFbUVmk8QryBi0UiABEggVgnwXR2rI8u4SIAESMDZBIysQ50dubu8p4DlrvG2PFojEwe/FFs+PC3egdfrk8JgAlbHTpKc2rpBwKqqlD3bt2k/x8XHS9vuPVs8Bn8HNpRukMq6Su2vsH0Q2whpJEACJBCrBPiujtWRZVwkQAIk4GwCRtahzo7cXd5TwHLXeFserZGJg1+KLR+eFu/A6/FK4dZ9GUveehRo92k+5XbqLEkpqdrPtdVVUrxtq/Zzq7g4adejV4vH4O/AupJ1Ul1frf0VCrijkDuNBEiABGKVAN/VsTqyjIsESIAEnE3AyDrU2ZG7y3sKWO4ab8ujNTJx8Eux5cPT4h146r1StE0VsBoKtMOxvM5dJTE5WfOxrqZGirZubuRzu569pVWrVi0eh+rA2j1rpcZTo/nTOaOzZCU3nKRoG0fpCAmQAAmYRIDvapNAshkSIAESIAFTCRhZh5rqCBuzlAAFLEvxuq9xIxMHvxTH/vPiqfNK0fbAAlabLt0kISlJg1BfWyuFWzY1EbB6SatWcbYBtaacXm0JAAAgAElEQVR4jdR56zR/umZ2lYykDNv4R0dIgARIwGwCfFebTZTtkQAJkAAJmEHAyDrUjP7ZRnQIUMCKDmfX9GJk4uCX4th/TOrrPFK8fa+ydXDfFsIGy+/aXeITE7W/8NTVye7NGxtdgxpYqIUVqXXv3l02bdokU6dOlRdffDHSZrT7VhWvEo+34STFbpndJD2p4SRFwx2E2cDGjRulR499he5nz54t559/fpgtOO/yoqIieeCBB+Tjjz8WxF9dvW9L54wZM+Saa65xXkBR8hjP/wUXXKD0tmHDBsFng0YCegjwXa2HEq8hARIgARKINgEj69Bo+8r+IidAAStydrwzAAEjEwe/FEf3kfrmm29k9OjRATtNTU2V/Px8GTJkiEyaNEn5LyEhwbCD9bUeKd6xV8TnFa8HpxA2WH73HhIf39CHx1MvuzduaHxNtx6C0wgjNbMFrJVFK8XrazhJsUdWD2md2FCIPlI/I73PLgKWus1z5MiRgufMKistLZXDDjtMMHc0NQpYoambIWCNGjVK5s+fv19HcXFxkpWVpYipI0aMkL/85S8yaNAgqx4Drd3//Oc/8swzz8jixYtl9+7dyhyG5wP9jx071vL+g3VQV1cnX375pXz22WeycOFCWbNmjeDZTUtLk549e8qYMWPk8ssvV/5s1CDkIn78t379eoUD+kpPT1fax5iBR79+/SLuiu/qiNHxRhIgARIgAQsJGFmHWugWmzaZAAUsk4G6vTkjEwe/FEf36QklYDX1BIvADz/8UNq3b2/Iyboaj+zZuVd8Po/4PIWN2mrbo5dg4aua1+uVgg3rGl3Tpmt3SfDL0grXGTMFLJ/PJyuKVjRyoVd2L0lJSAnXLdOud5uAdf/998ttt92m8Lvxxhtl/Pjxkp2drfzcoUMHyctr+RMh/T9nX3/9tSIg2MGsFLCaxhcfHy/Tp0+Xm2++2ZLQMVdAlHn++eeDtn/xxRfL008/3WiOscSZJo1CQBowYIAgUzCUJf0/e9cBXkW1dTfpvSeUEEJAFFAQBRGfYkEUQVRAseBTQLA89RdBfYpiw4YdUVCfiiCCotgVUQQrCCgiFgSlhwDpvd3c8n/rhJlMbm6ZuTO35e79fXyE3DPn7LPOuTNzFmvvHRVFTzzxBE2bNs1jt8xmM0WquD+izezZsz1eD35We7xEfCEjwAgwAoyAFxHQcw71olvctcEIMIFlMKCh3p2eGwe/FPt29ygP1vjf/xtvvFF2oKamhn7++Wd6+umnRVgWbPDgwbRhwwZdSdSbGs1UfriObDYz2SytD3T2CdpBEBXu3tkKlIycbhQR1ZLo3beItR4NoYMIIVRar9ReFBXeksfL1/6FGoE1bNgwAik0aNAgoTgJRAsVAuv333+X4TeZTEL98+GHH9LSpUvl37/zzjs0fvx4w5dp5syZNGfOHNEvVKMgM3v27Em7du0SpNCWLVvEZ2gH0tOXpnwmDhgwgC666CI6+eSTqWPHjkIZBdXY888/L4e+gmQDGeeJgcDKyMgQJCnGgOIKRG5cXBwdPHhQqCEXLlwoxoW9+OKLdMMNN2geip/VmiHjCxgBRoARYAR8gICec6gP3OMhDEKACSyDgORumhHQc+Pgl2Lf7iLlwfr++++nBx54oI0D5eXlgrjaubOZSIIKCyoXT83UYKaKQhBYTWSzlMndIOQMBJa9gcACkSVZetccioz2n8JJ6Z/ZaqYdZTtauXx02tEUGdaSx8tTnDy9LtQILIRBIRxrwoQJrYgST/HzxnWhQmApv6dKHEHO3HLLLeJXCCP8448/DIUZ649+Qd6AyPzuu+8IIdCS1dXVEUJZQcgjDPqvv/6io45qe68x1ClFZwUFBSLXGBRPQ4YMcTgMwgoRzl1fXy9CL/Pz8ykx0bNiEBaLhaB4c2bIdzZw4EDCvR0hlocOHXLZ3lE//Kz21m7hfhkBRoARYAT0IKDnHKpnXL7WtwgwgeVbvNv9aHpuHPxS7NvtoYbAgkf4H/spU6YI56DSmj9/vseOmurNVFHkgMAKC6OOeT3b9Fu4ZxfZrC05ptK6dKUoxeHUY0cMuNBkMdE/5a1zL/VO603hYZ4nmdfrVqgRWEaGhOrF3tn1oU5gIbwPubD2798vIAJhojcUWYk17klQEsF+/PFHhyQRlKOnnHKKIfcwb+2T22+/XSheYe+99x6NGzfOW0MJ1RWUXjAQilrzk/Gz2mtLwx0zAowAI8AI6EBAzzlUx7B8qY8RYALLx4C39+H03Dj4pdi3u0MtgYUDTr9+/YRz559/Pn366afiZ/uD+emnny4q+y1ZsoS2bdsmkgdfffXVrar9NdY10fdf/0hLli2kdT9+R4cKC4XCqkunTnTOiBE0ffp0Ovroo2UgivbuJqvFQkPOOpv25eeLwykOqa4Miodu3boRDs533HGHCCGSTC3h8cknn9DixYtFyCTmgQTI8AvhPzfffLP4d4O5gXZVtM7R9c7z7wilBcyZIsURdo7yIm3evJkWLFhA33//PWFOUFZAMZGVlSVwGDFihFDDSQnT0a8zAgtJpHNycqiwsFBct2rVKpcYKtf88ccfFyFZWsxdEnfpc0n5h/C/Z555RswVeCMMCuGBd999t8gfpDQ1uducJY+XQtqgeCkqKqKYmBihxgGOUAmlpqa6nebKlStp2bJltH79eoEn1gVhWieeeKLoBwUPELKlXAtXnTqrFonQSHyfgMnhw4eFeig3N5fOO+888T3p0qWLS1+hsMHaYc6ovAlFT//+/en6668XYXxG58Bytd9HjRolQuVgmzZtEonVjTCM2bVrVxEe17t3b6Gucmb4fMeOHZSdnS0UTsrvjRG+6O0DyddHjx4tusE9C/cubxn6fuqpp0T3UKZBkaXF+FmtBS1uywgwAowAI+ArBPScQ33lI4+jHwEmsPRjyD0oENBz4+CXYt9uJbUEFg59OPzBcHiWDqLK6/E7qAe++uqrVpOYOHGiTGCBUJo+bQY9P3+eU3IHh3QovKQcMMX795KlqYkef3YuzZ2/QBw6kVsHRJQzw8FMOvz9+uuvdPzxx8tN3RFYDQ0NIhztgw8+cNo/iAMcNo859hjaXblbbgffQGA9+OCD4nd6CCxU0IMiA5i5surqakGmSeZKgQUS6sknnxRJrKGGwUHemc2YMYPgA9YDh32tihktBBYIOSSuRgiYvYEIwt4COSqZJwQWyJxLLrmE1q5d63TO8OOjjz5yGuaFJNyXXXaZqCbnyiRCylMCC3sQIWdvv/2202FQve6tt95yGs4LImf48OGC2HFk6B+Y4m8YwspcfaecOaKsQuhqv48ZM0ZgC0M+KuSCMsJwL0CuKxiIuZdeeslpt/gcFQphuA6qsECy999/ny6++GLhEu6l+A56wxCmiHsinre4F1RUVGgOV+RntTdWhvtkBBgBRoAR0IuAnnOo3rH5et8hwASW77AOiZH03Dj4pdi3W0QtgbVixQo58fI111wjV/pSXg9lx2+//UYXXnghTZo0SShFoE6pqqoSh37YTTfdJBRFsCGDT6HLxl1I3XJyKC42hv76Zye99sYS+vPPP8XnOOyir5L8fWQ2meifXbvo9BEjxWePPPKIUOY4MyhhcEh2lG/HHYEFX5FoGoZD3m233SYUQGVlZYJQgGoFB/W0tDTasHkDmRJMshsIHXx73tu6CSzgiETUUugVFF848GNMEFYgFKHOAUZQ5qglsJArCDmjYEhkjYTWjgxqLZBbUEJBUYS8Z1pNLYEFJRkUOVD4gcTC3zhgg0B87rnnBAZQ0+HegCptsNraWkG4wKAmA0kDZRyq3EkGgkciKBobG+lf//oX/fLLLyLXDwhKKILwOeaKnElQf4GgggILewf7V2nIowRfpUTlUKyAZD3uuOMoOjpakHzoZ/ny5WJ/4juAvrFWUJfhewNDOK69+ggKIqlyIvYWMAdBCpMUXUjGDbIBWIHcAAEJPNatWyfyPikN3zn4BZ9g2NMgkkHQYQ9grlDdwA8p8b23CSwpVxn8wXdJjdJNzZ6DGlTKyQfC9dZbb3V6GT6XSCHgiz0QSIb9P2/ePOESVH4jRzbf74ww7EWEbkI1CFUeiH0YKjO+8sormofgZ7VmyPgCRoARYAQYAR8goOcc6gP3eAiDEGACyyAguZtmBPTcONS8FFttVqporAgpuFOiUyisQ5jhc1ZDYEEVM3ToUBFKB3vjjTfoqquuEj/bK2FmzZpFDz30kEM/V69eTeeee6747JnHn6cJ4y8lm7W5EhYsMjqa4jOyRIgiVDIgEJA4vvLwQWpqbBRtzr1oLP3+558uE0Fv375dDjlzRNK4IrCUITxnn322OERKpInkJw57kjps3CXjaPaLzeGCYg5hkbRs3jLdBNZ9990ncAQJgypqqFbmyFBJDGFhIDYkc5cDC6obhKQhHBLkiiMDeSTl38HPUM9oNbUEFvoFkYBx7LEGEYQ9BYM6ZezYsW3ccEdI4oJ77rlHEHYgiaAQdBQuhRA75EjCId9RQnhJkYb+QMQiMbmjEDRU34PaS7lmWnJgSfsrMjJSEIdQPNob+sd3EmTvqaeeSj/88EOrJsrwMEffAZAZCFX78ssv5eu8SWAplUX4XtmrNLXuLWV7KK5QQRX27rvvCpWdM1MS8bgOiiylgXRE2LAecxa66q5P7DuQfCCoESYMghLhrXrMnQIQ5C/I+qSkJM3DqHlWa+6UL2AEGAFGgBFgBHQioOccqnNovtyHCDCB5UOwQ2EoPTcONS/FZQ1ldMbyM0IBSnmO3172LaXFpBk+Z1cEFlQuUGmgMiHawUAqgfSA4gSmvB6ECPJeOat+hYMriKkxF42ll59bRDZrPdmsVfKcImNiKD07R+Sw6du3r/g9Dtgn9u1DTQ314t8vvbaQHnxsjvjZPjRQ6ujee+8VShyQCziU2ytpXBEeUp4ekAcgjpAzypGdc8454hCO8LrVW1ZTZqdM0SwqPIqWPrdUN4EFggxEBlRYUA1pMXcEFghIqHFgID5AgNgblG/IAQbFDnJvYZ5aTS2BhUM6yCOMZW84zCMXFkgh5HyCcsje3BFYNTU1IkcSyD6QTlCzOTMkAkdCcKw/SCIQiDCEWEGRBhUWyC/kz3JV5c2+f7UEFtRXvXr1EnsPyj8pR5EjfxFWKSmIoKrCdTBghXBP+A9VJL4njog23Keh6gKZBTOawIIfCNMDMYnvI7BDOCjuASeffLLW7eS0PUJipfxswMQR4SddrMQM2AJjpfmLwMK6Q0GI7xwMKqz/+7//042RMwIL3ymEaSNcUcs+Vjqk5lmtewLcASPACDACjAAjoBEBPedQjUNxcz8iwASWH8Fvj0PruXGoeSlmAsu4XaMml5A0GgiGL774olXuGuX1II6k5OX2HiKkCSFDCAdbvHAJnTfsQrJZ68hmrZaborIgKgzCoEAoKSkRRNDNU6eQqb5O/P5wYSENHHqG6AeHVoTC2BsScoMAOO2004TSyN6cER5QmqF8PQ7aykT1jtCGakEKi3zi5Sdo1LjmUKSYiBhaMneJbgILic2BJYhChKUNHjxY9aK7I7AQnoeE4yB0UFny1VdfbdU3wj5B+AAPdySKK6fUEljuQhQRCgelEQ74SEaudj2ldkpVnbvqdxgH48G+/fZbOe+WUkEEhQ4KE2gxtQSWcnxn1fSkcUEwS6GjSp9wHcIlYe7yKEGFJYUqGkFgucIEYb0gZhwRplqwtG8LpSIUizDkJkPif2cG8gxEOgzXSeo+qT3IWhB/ekwZuqq2H6XS8KyzzhLkuFJVqbYf+3ZSCCt+j+8z5ofiDa+99ppQd0Gp5yyM2N2Yap7V7vrgzxkBRoARYAQYAaMR0HMONdoX7s97CDCB5T1sQ7JnPTcONS/FTGAZt63UEFjIE4SwHCQUt1fJKK93Fb4DMsBRlT13M0Fo0CP3zaLG2lq56RVTptI3334n1FFQ7ijVJVDGIE8RDGoalIq3N2cEljI/FMgjEHLODONKCa+vvfVamnbPNNE0LjKOFj+7WDeBhTBIqGdwAIX6CaoSkGog5ZDXy1X1NHcEFvyEygj4IPwQObSgjJFMmQAfhIqkhnO3VvafqyWw7KtE2vcjhTyCmHCUPN2dAgskKFSEWg25rFBNECap+vCzJ8m/1RJYIKKgAtJqyiqRSFIuhcaB/ESooTPDPgdZCvMmgYXQUOSfwr4z2oxUYBntm5r+li5dKkKyocLCvRY5qrQWTFAzjrINcuyBKEMuMiTxR142rabmWa21T27PCDACjAAjwAjoRUDPOVTv2Hy97xBgAst3WIfESHpuHGpeipnAMm4bKQ/WIIukAybIB/wPPUJNoEpyZsrroRqQ1A327UFuSWSAFu8R6jb38ceooaZGvuyDlavoxltuEf/G+Mg5I9ktt9wiwsQQAga1TXp6epvhnBEeyPGFHEgwR/lxlB0hKbiUn+bSSZfSfU82K0ASohLo9Wde101goa/33nuPrr322jaKEKwJCC2EGToiJ9QQWAhLlPJA2SuKQJAhFBRhXlLeMy1rJrVVS2CBQHFFMElV7pzlFnJHYCkLB2iZh1RJENfguyFVt4OCTWtuIrUElpKM0eKrEsM5c+bIqhoQoVLSfkf9vfzyyzLJawSBJSW4x1hQMoEoAXEFRSTsiSeekKuDapmfq7ZG5sAyyie1/UD9hrxuIKpBWiGkV6qoqLYPT9tJ4bK4HspaKT+h2v7UPKvV9sXtGAFGgBFgBBgBoxDQcw41ygfux/sIMIHlfYxDagQ9Nw41L8WcxN247aQmibur0dQezFG974orrhBdzZv7AvXvM1CEEJKtObcVLDounhLTM1oNh7DDhMgIqq9uyZVlCQuno/oeSw0NDYLEwSEcZrFYRJ4ihMC5CktTQ2ChTylRu6P5OyOwkqKS6LVnXjOEwMK4CPODEggHTIRDoiqg0kDwQT2hJYm7dL1UqREEESoawpQKNncYuNuFgUJgQYUn7REQdyA31ZiyMqCvCCwl+YR8SJLKz52/UEZK6khlH8hXh9x0zsxoAgsqIntDHjMoB0FmQU0IhZF9FUZ383P1uZFVCH0ZQoh7J6oM4j6G+xz+DdWlrwyVO3G/hIEoh3JPi6l5Vmvpj9syAowAI8AIMAJGIKDnHGrE+NyHbxBgAss3OPt9lDvvvFP8D7hkOLR6EtblbiJ6bhz8UuwOXWM/9xWBpaxA+OpLC+mC8y4W+a8EiXXEYpOSKDmzbbW9quIiqqtqqVYYl5RMU268iVBRLC0tTYTAgZRAwndU1YKBMJNyVNkj5s0QwuToZFr47EI5LAukmrNcNsrcTGq/i0hw/9FHHwmVGQ6gsLlz59K0ac0hjDA1Ciy0W7BggaimB6IJChmEL0lkD0IKoWDzpDqZ5EegEFhSBUL4lZ+fL/J7aTVfhRAqK1yCsATxo9WUpJSvQwgdEVjwf+vWrQTCFLnroBqEX0YZQjol1RJCJyWlnKP+8blE1DgKBfVVEvdNmzYJtSoKDCCPGdSrRia2V4MtVF9S1U+or0CSazF+VmtBi9syAowAI8AI+AoBPedQX/nI4+hHgAks/RgGfA+oRIX/9UYiV8nUHpq1Tk7PjYNfirWira+9rwgsKIc6duwo8rxMmXwtPXr/U2SzVJFNocCKS06hpIzman5Kqy4pptrKCvlXsYlJ9PX6H0XoDQyEDqrmQY2ECnvI6wQVVmxsrENwjEjirgyJVCZxT41JpeWvLKcZM2aIsZGI3lEYIz5DaJXUTut3EURMnz59CIm8kbB73bp18lzVElhQdyGZO0LikAT7rrvukpO7IycPsNRjgUJggegcP368mIorYtPVXFFJb9y4caLJokWL5CqOavFR5oBztdao+impk6Ckwn86aDUonKRE6e6SuEOpCAUTzIgQQmcEFvrHnnrzzTfFWO6qBWqZM8YEKQlCt3fv3qKKqTPDdwZhlVAe4Ttkn0vOFwQWlGj4jyOEWCIUFVh44z+S3GGovE9gbyNkWYvxs1oLWtyWEWAEGAFGwFcI6DmH+spHHkc/Akxg6ccwoHvA/3ojsfVPP/0kwkyKioqEv1oPzWonqefGwS/FalE2pp2vCCx4C6IFFdKSEpPox2+2UHpKJNlsDfJE4lNS24QQ4sPqshKqVVQGi0lIoLjUdJEzBodA5NZCHifsbYQroUIc/u3MXOVMGjVqlDhQQpkAVZIztQ6UXlB8ISRq9ZbVlNmpmXhLj02nDas3yOQaKn5JqjB7f6C4gBLD0++iFAKIEDGEikmmlsBCe2C1ZMkSys3NFVXZpOp6RtwbAoXAqqioEIQFqktiDyLPkKsk+I72DfrAXgBhiNxhCLUMDw9X/SVUhma62hO4V2MtcA/t0aOHqL6oNd8WwltBTOK7MWDAAELYpKP5IlwOY5hMJjEPbxNYII6QXw1zBMGGdTDKpKIE6M9Z9UZljju0nz9/vlHDq+4HhSJQlAAEO1SjqKqJe44/TJlvzV0eOkf+8bPaH6vGYzICjAAjwAi4Q0DPOdRd3/x54CDABFbgrIVXPEGI0fTp08X/TkO18thjj3l8aFbjoJ4bB78Uq0HYuDa+JLBWrlwpKunBThl8Ki16+UVKSoyRJ5OQmkYJac1J13EIf/XVV2nKlClkrq+jmrJSuV10fDylduoiclQh5ApKqxdeeEG0hblLSOyKwFKG9SGsBuoU+5xJyDkljTV63Gia8/Ic2bfMuEyiGhKECdSOIK9AiNkTCPbJuu0JIxxsocpISUlxuNhQjyA5N9RTGAOkiGRaCCyEcklJ8EEIIhwT4Vj4HmoleewdDRQCC34pw6cRbvnMM884De0EuYD8U1OnTm01pdtuu01cB7v55ptp3rx5DjFCaBbII2XFzv379wtiCgbixFU1PmVybSjHQDBGR0c73AdVVVVCKQd/lKb0VVmhUGqDvQnVIvamZN4msDAO5gNFHGzt2rWiEp4RBmII1TIRsjto0CARoqhUYOJ7AuIICjeQzihS0KtXLyOGVt0H9gBCQvHdBfkJNSCqu2o1pUrMEdGMewfIcZCYzgz44F6MEEbg8ccff7hM9u+oH35Wa105bs8IMAKMACPgCwT0nEN94R+PYQwCTGAZg2NA9oKXZvyvN15UQVbghRdl5WFGqCwcTVrPjYNfin27jXxJYGFmt956Kz333HNiklmZmXT1FZfT4EEDKRVETWQUFRQWiWTl77//viABoKjqYG6i6tISGZiouDhK65xNyrAsED1QySBMEcoSV+oYd1XroOhCiCAMKieE+YH8hT84dILAQtgS8m+tXLeSEjISZN+y4rIIJNaECRPorbfeEr8fPXq0yDUF3/B9BCGBcB2ogRDu5ei7CPIKikkcMocNGybCBVENEj7gEI4cWDgIwxDeNmbMGNkHLQQWLgIRBgJAMiixZs2apXsjBhKBBUIURB2UULDjjz9eJK6GQik+Pl7gCrUTchGB1OnXr5/AWWlQcEHJKlXagxILOZXQFoo93Pewd7HuDz/8MIFoUFpOTo5og1xj+E8F4C7tU+wNhL7CsLcuvvhisa4wEIoYZ/DgwWIPgLSCmgnf3Y8//lgotBCqqjSEhx533HFiPBgKKEBdB1INaw0iDvsLZI80T18QWFu2bBHfKRj29Zo1a3TvM6mDmTNnEsIuYSeccIIgLYEdlJQg8TA2DO0effRRw8ZV01FpaamocIrnG+y///2vCKl0ZUjsLiVZV7ZzR2Dhc+xB3DuQZwvPf9wf8R0AFiBn33nnHaGEg82ePZuQ402r8bNaK2LcnhFgBBgBRsAXCOg5h/rCPx7DGASYwDIGx4DsRcpxgvxAyN2CcvVMYAXkUvnFKV8TWDicz5p5Hz3x9JxW+dgcTR7EAnJn2UyNVFXSUn0vKiaW0rK7ioM+VC0SkYM+oK4BOeDK3BFYqAoGAkoiEBz11aVLF4JaKyUvhWqbauUmneI7iTBCqHiQrFo6sNr3cfnllwuFz/Dhw8VH9mQyCCwQdK4MyeHxXbYnm7QSWCjsIOVaQp/79u3zKNG5va+BRGDBN5ChONyDHHVnUAZBIWRvIIpALrlLQv7666+3IbCUyir7fu3bQ8WFvYyE5K7ySqEfEGJISG5vIOSwv6Cqc2TAAqTe5MmTxce+ILAwDogVqDFhzsL93K2Po89ByICUBMHszKCcRBJ3Z4UVPBlXzTXK+6ya9mgjPbPt26shsFyFUEv9QaEGolXKw6fWL6kdE1haEeP2jAAjwAgwAr5AgAksX6Ds/zGYwPL/GnjFA/wvKyqxQSmCHDkZGRlMYHkF6eDt1NcEFpCqKqmnHdv/ocVLFtAPP66j/fkHqKq6mlD5DioVqCcQvodwV6hS6quqqLK4UAY5Mjqa0rt2E/+2r6yJnFJSEmxnq+KOwJKug1IBpC9y54C4AKGGfFNQOyFkC9XDdlfspnpzvTxUl4QuhETuMKh6oPwAYQLlFa6HKgahj1deeaVQ0EghVPYEFioAInwRbRDuBBICPkBtA9IO4VCoGNi/f/8209RKYGEsEHIw+3BEPTs70AgsaS7IvYQDPtRSSPyN8DJUW4RaByonECzYf65UfCA3ly1bJvYGSFbMFRhClYX9AZLLUdgf9gKqBKKoRllZmUziOiK84C/UXgiTxT7AHpKq1oG0wlgjR44UCj9nIYYYA3sQ/uJ6fJ+gGAPRA1UW9revCSxlknnkfwIRbKSBHANJBYUZvjN47uGeABUb8PKH+ZLAQo5LYAqSFaGBINPxO5B2eBeAIgvqNyjyXIUZusOJCSx3CPHnjAAjwAgwAv5AgAksf6Du+zGZwPI95l4fEeFUCDvCwRcHICmfCyuwvA49D+AGgcriemqsayKrpZTI1lIVMzmrI6HCoL3V11RTZWGLiiQiKooycprzCfnbdpbvpEZLo+xG18SulByd7G+3NI2/evVqQdjAli9fLpLiszECjAAj4AoBJrB4fzACjH8BgzUAACAASURBVAAjwAgEIgJMYAXiqhjvExNYxmPq9x6lBNeo9gSlgaSGMILAkvKqOJskFB1QMsAQ3uWskpuj6/ml2O9bx+sOVBbVUWO9mayWEiKbRR4vpWNnQoVBe2uoraGKw4fkX4dHRlJmt+5e91PNAH+X/01Nlia5abekbpQY1ZzLKFgMShzk9kpPTxf5w5ypeYJlPuwnI8AIeB8BflZ7H2MegRFgBBgBRkA7AkxgaccsGK9gAisYV82FzyCskNsEITBIXIuwJcmMILC0VCdjAqudbS4DplNRVEcmEFhmJJ5uIbBQWRAVBu2tsa6Wyg8dlH8dFhFOWbk9DPBEfxfby7aTxdoyh9ykXEqIakvC6R/JOz0gqTMS1KMq3e23306ojsjGCDACjIA7BJjAcocQf84IMAKMACPgDwSYwPIH6r4fkwks32PutRFNJpOosIUqVXfccQchQbPSmMDyGvTcsUoEKgrryNQAAguJ2ZsrYcFSu2RTdGxcm15M9fVUdrC5mhoMuVyy8nqqHM27zf4q/YustpY55CXnUVxk2zl41wttvUNlhYp6SPyNHGJbt24VubVAZkm5sLT1yK0ZAUYg1BBgAivUVpznywgwAoxAcCDABFZwrJNeL5nA0otgAF0vEVTdunUTyZ+ROFppRhBYHEIYQAsehK6UH66lpkYLWc1FRGSTZ4DKgqgwaG9NDQ1UWpAv/xoKwI49jvL7zFEdblvptlZ+9EzpSTERMX73zZUDjiocQnkFBRYbI+BrBJBgHH+0WlRUlCiqwOYfBJjA8g/uPCojwAgwAoyAawSYwAqNHcIEVjtZZ6iuoL6CCuujjz6iCy+8sM3MjCCw3MGl58bBL8Xu0A3+z1sIrJbKgpgVKguiwmAbAsvUSKX5+1v9GgSWllBWb6AG5RUUWErrldqLosKjvDGcYX1KBBaqPoIAuPXWW2nixImG9c8dMQJaEFA+k7Rch2qcqLjJ5h8E+FntH9x5VEaAEWAEGAEmsHgPEDGB1U52AcqEo3x4jx496JFHHnE4qxUrVtB7770nPrv33nupb9++4ucLLrigjVrLU1iYwPIUudC4ruxQLZlNUGC1JrBQWRAVBu3N3NREJftbH1QRQohQQn+a2WqmHWU7WrlwdNrRFBkW6U+3eGxGIKgQYAIrqJZLdpYJrOBcN/aaEWAEGIH2joCec2h7x6Y9zY8JrHaympMmTaLFixd7NJs9e/ZQ9+7GVHbTc+Pgl2KPli+oLio7WEvmJuTAah02hMqCqDBobxazmYr37Wn168zueRQeHuHXeZssJvqn/J9WPvRO603hYeF+9YsHZwQYAUbA2wjws9rbCHP/jAAjwAgwAp4goOcc6sl4fI1/EGACyz+4Gz4qE1iGQ8odegGB0oM1ZDGZyWpBEvcWy8zNo/CItqSU1WKhor27W7d1QnZ5wV2nXTaYG2hXxa5Wn/dN7+v30EZfYsBjMQKMQGgiwARWaK47z5oRYAQYgUBHgAmsQF8hY/xjAssYHIOiF86BFRTL1K6dLC2oIUtTE1ktJa3mmZXXg8IcqJdsVisV7mlNFDkLN/QlcPVN9bS7soVYQ04uEFhsjAAjwAi0dwSYwGrvK8zzYwQYAUYgOBFgAis4102r10xgaUUsiNszgRXEi9dOXC85UEMWs4lsltJWM3KWmB3V/gp372zV1lnCd19CVNtUS3srW3JzIXQQIYRsjAAjwAi0dwSYwGrvK8zzYwQYAUYgOBFgAis4102r10xgaUUsiNszgRXEi9dOXC/JryaLpakVgQX1EggsZ1a4ZyfZrDb547TsHIqKifErItWmatpf1VIdMSIsgo5JO8avPvHgjAAjwAj4AgEmsHyBMo/BCDACjAAjoBUBJrC0Ihac7ZnACs5188hrJrA8go0vMhCB4vxqslqgwCqTe+0QFkYd83o6HaVo7y6yWqwtBFaXrhQVG2ugV9q7qmyspAPVB+QLo8KjqFdqL+0d8RWMACPACAQZAkxgBdmCsbuMACPACIQIAkxghcZCM4EVGussZskEVggtdoBOtXh/NVmtjWSzlMsehoWHU1b3Hs4JrH27yWq2yJ+nds6m6Lg4v86woqGCCmoKZB9iImKoZ4pzEs6vzvLgjAAjwAgYiAATWAaCyV0xAowAI8AIGIYAE1iGQRnQHTGBFdDLE3zO6blx8Etx8K23Vo+L9lWRzQYCq0K+FNUHUYXQmRXv20MWs7mFwOrUhaLj47UObWj7svoyOlR7SO4zLjKO8pKdz8HQwbkzRoARYAT8iAA/q/0IPg/NCDACjAAj4BQBPedQhjV4EGACK3jWKig81XPj4JfioFhij51EQnYosGy2BrJZKuV+IqKiCJUFnVnJ/r1kbmqSP07p2JliEhI89sOIC0vqS6iwtlDuKiEqgXKTnM/BiDG5D0aAEWAEAgEBflYHwiqwD4wAI8AIMAL2COg5hzKawYMAE1jBs1ZB4ameGwe/FAfFEnvspExgWRvIZlUQWNHRlNG1m3MCK38fmU0m+fPkjp0oNiHRYz+MuLCoroiK64rlrhKjEqlbkvM5GDEm98EIMAKMQCAgwM/qQFgF9oERYAQYAUaACazQ3ANMYIXmuntt1kxgeQ3aoO/YarURqhDarPVks1bJ84mMiaH07Byn8ys9sJ+aGhtbCKysjhSbmORXPA7XHqbS+tIWn6KTqWtiV7/6xIMzAowAI+ALBJjA8gXKPAYjwAgwAoyAVgT0nEO1jsXt/YcAE1j+w75djqznxsEvxe1yS8iTQiXBkgM1ZLPWkc1aLf8eFQXTujgnf0oL8qmpoUFun5SZRXFJyX4F61DNISpraKmkmBqTSl0SuvjVJx6cEWAEGAFfIMDPal+gzGMwAowAI8AIaEVAzzlU61jc3n8IMIHlP+zb5ch6bhz8Utwut4Q8KYvZSqUFILBqyWatkX8fHRdPqZ2dkz9lBw+Qqb5ebp+YkUnxySl+BauguoAqGlsS0afHplOn+E5+9YkHZwQYAUbAFwjws9oXKPMYjAAjwAgwAloR0HMO1ToWt/cfAkxg+Q/7djmynhsHvxS3yy3hgMBqJrEki4lPoJROnZ1OvvxQATXW1bUQWOkZFJ+S6lew8qvzqaqxJQwyIy6DOsZ19KtPPDgjwAgwAr5AgJ/VvkCZx2AEGAFGgBHQioCec6jWsbi9/xBgAst/2LfLkfXcOPiluF1uCXlSv27ZSg/PfpR+3Pg9FZeUUNORyoLfrVlNQ4cNd05gHT5IjbUthFdCWjolpKb5Fax9VfuoxtSiIsuKy6LMuEyv+DRp0iRavHgx5ebm0t69e70yBnfKCDACjIBaBPhZrRYpbscIMAKMACPgSwT0nEN96SePpQ8BJrD04cdX2yGg58bBL8W+3U7ffPMNnXXWWWLQ+++/nx544AGvObB582YaOnQo1StCAaXBvlvzFQ0ddrbTsSsKD1FDTQtZBPIKJJY/bW/lXqptaiHVED6IMEJvmBEEVocOHRy6FhkZSampqdS7d28699xz6dprr6WsrCxvTEPu02w206uvvkpLly6l7du3U01NDXXp0oWGDx9Ot9xyCx177LFeHd9V55WVlfTpp5/SV199Rb/88osgDOvq6iglJYWOO+44Gj16NE2ZMkX8W49VVVXRypUr6aeffqKff/6ZCgoKqLi4WHw/0Hffvn1p1KhRYqz0dO/sKz3+87WhjQA/q0N7/Xn2jAAjwAgEKgJ6zqGBOif2qy0CTGDxrjAUAT03Dn4pNnQp3HbmSwIL5Mjq1aspMTGJ7rnjTjr+uGMoJiZG+Ni3Xz/K6trNqb+VRYepvrol6TvCBxPTM9zOT2sDEHgPPviguMxms7m8fHfFbqo3t+TlQgJ3JHL3hnmTwLL3Ny0tjd566y1BZnnDSkpKBDED4saRRUdH0wsvvEBTp071xvAu+/z8889p7Nix1KioeOnogk6dOtGyZctk8tcTR0GQnXPOOW4vzcjIoDfffJNGjBjhti03YAR8hQA/q32FNI/DCDACjAAjoAUBPedQLeNwW/8iwASWf/Fvd6PruXHwS7Fvt4OvCCyECiYkJJDJZKIbr/s/uu/O/5LN1kL+uCOkKosLqb6qJd9UXHIKJWUYH66nhcDaWbGTGs2N8oJ1TexKydHeqYxoJIE1aNAgev3112W/q6uraefOnbRgwQLasGGD+H18fDz9/vvvlJeXZ+iGtFgsdOaZZ9IPP/wg+h03bpxQfIE027hxIz388MNUVFREYWFhQgU1cuRIQ8d31xmIoquuukqMD3LpvPPOo+OPP14oonBfg2Js+fLlopu4uDhat24dDRgwwF23Dj8HgXXNNdcIEmzgwIGUk5NDnTt3JqvVKsZasWIFvf/++wTMoqKiaNOmTcIXNkYgEBDgZ3UgrAL7wAgwAowAI2CPgJ5zKKMZPAgwgRU8axUUnuq5cfBLsW+X2FcE1qFDh0SIGOypx56jf186lmy2Bnmy7kICq4qLqK6qUm4fl5RMSZnGh7lpIbD+Lv+bmixNsk85iTmUFJ3klQU0ksA644wzCOtub1CcXXrppYI4gd10001CCWWkLVy4UITEwW688UaaP39+q+5BpIHMQXjdUUcdRX/99RdFREQY6YLLvkBOff3113T33XdTt26OFYHPP/+8CHOEgXxau3atR/6BmAoPD3d57YcffigUYTD8DUKLjREIBAT4WR0Iq8A+MAKMACPACNgjoOccymgGDwJMYAXPWgWFp3puHPxS7Nsl9hWBhTxCkprnuScX0GXjziebrUW95C4pe3VJMdVWVsjgxCYmUXKW8RX/tBBY28u2k8VqkX3KTcqlhKgEryygLwgsOL5r1y5BHMGOOeYYkZ/KSENeJ5BSUFzl5+cLFZO9zZkzh2bOnCl+/c4779D48eONdMGQvk466SSRtwpKrcLCQkKYn7cMucl27NghxkCOLDZGIBAQ4Gd1IKwC+8AIMAKMACPABFZo7gEmsEJz3b02ayawvAat4R27I7CUn0OZgvAvkAovv/wy/fbbbyL5NpQqF110Ed11112CmFCakhBy5vxt/3czPTh7NiGMULKGhgaR5PuDDz6gP//8k8rKyigpMZH69j6GxoweTVdffTVlZHd1iQfyGKFy30cffUS//vorIfcS1Dzdu3enU045RRAjyPOE5OaLFi2iyZMnu8V3z5494nrYX6V/kdVmFSFen777KX3/+fe0dctWKi0tFeGSffr0ESFy//nPfyg2NtZl3yB1Hn/8cVqzZo0gKTIzM0XC++nTpxPIEl8RWFBhJSYmUm1trSCX8LdR9vfffwtSDHbDDTfQiy++6LDrw4cPi1A62BVXXCFyTQWa3XHHHfTUU08JtxDahzXylklkGfYUwj3ZGIFAQIAJrEBYBfaBEWAEGAFGwB4BPedQRjN4EGACK3jWKig81XPj4Jdi3y6xFgIL5ApyJyFPkCODcuf7778nJLiWTC2BNfuhhwh5rWBbt24VhNi+ffucgnHigAG0ctUq6tjRsQoLhBXIIxBOrkwipLQSWCB6tpVuo0MHDtHN/76Zdvy5w+kwwOWzzz6jo48+2mEbEIIg5BwlDgfh9tJLLwlcQcbl5uaKqniemFSF0FkIodQn8j2hEl9ycjJVVLSo3jwZU3mNMnwQSeIvv/xyp12C6ALhBXLU1T7Q65On1yOEEKGEMFTXPPHEEz3tyuV1UF6h8iGqNiJ3mbPE914ZnDtlBFwgwM9q3h6MACPACDACgYiAnnNoIM6HfXKMABNYvDMMRUDPjYNfig1dCredaSGw/vWvf9H69etpzJgxgnABmYLwKeQxAkEDAykBckIyJOTGn4MHD8pV1O66fRaNGHYaEZlFs4z0dOrRuw8hrxVyIOGgDgIlKSlJ5GEaPHgwpScnUcG+ffTlmjW05O3l4kB/8sknC2InMjKy1TyhZsI1UIfBkDsIfvXo0UOopUCMfPnll0Ld9ccffwhFFYga7FskMpeUQUhibm8gVjAelFc//vMjXTLsEjpccJiioqNoytQpNOzMYaI/jI0xnnvuOaqrqxNj//LLL4IUUhoICeCK+aD6HhRXqNCHn5HU/NFHHxWKLoTegdjzNoGlzFWGhOEgAo2y22+/nZ5++mnR3ZYtW1wmPweB+fHHHwt1HFRHSCofSAZsoEDEXoCyD3vVKMN+KSgooE8++YSeeOIJ8R2DgTi+8sorjRqG+2EEdCHAz2pd8PHFjAAjwAgwAl5CQM851EsucbdeQIAJLC+AGspd6rlxqHkptlmtZDFQGRIMaxWekkIdwsIMd1ULgYXBUSXunnvuaeUH1Eio1gbCBoohkFUIgVOafQ6sS8eNJLK1JEBHPivktTr11FMFSXbCCSeI/qTcQrUV5VRdWiK6XPvtd3TVtdeJam3/+9//RBU7pSEJOMgi5CdC1ThnSh8QQwiTU4b3qc2BZbaaacylY+iz9z6jLjldaOEHC2nYCcMoMqw1mQaiBqGACMVDYvBHHnmkla9SeBiIEFSlO/3001t9DiJjyJAhglyDeZvAUiqLHnroIZo1a5Zhew7rIFXwQ5ikq7xRN998s5zgHXm4pNBDyRmQhHqVWffffz9hvbUayNrRo0eLy/A3iCa95k4BiPBckJmSik7veHw9I6AXATXPar1j8PWMACPACDACjIBWBPScQ7WOxe39hwATWP7Dvl2OrOfGoeal2FxWRv/869R2iZ2zSfVav44i7PJLGQGAFgILxBAUQ44O0V988YUgsWDIOXXhhRe2cq8tgXUeka1ZgQVL6diJftryq0zgQN3Sr18/+fO6ygqqKmlJYP2f6TPow08+FeqldevWye1Aeo0YMUL8+9Zbb6Vnn31WE0xqCay/d/1NfY/pKxRdLyx9gc4890zqndabwsPaVpW78847hZIGVRhBSEkGLKEUg4GwkULS7B1GiOFll10mfu0NAgsKJ3zvMD7CFEFI9urVSyjAUlNb8pJpAtJB4/PPP59WrlwpPqmvr6eYmBinXUqYoQGSpWPvKc1fBBZysSFcEOQZKghiDUG26jVnBNaAAQMESevNHFt6fefrQxMBNc/q0ESGZ80IMAKMACPgTwT0nEP96TePrQ0BJrC04cWt3SCg58ah5qWYCSzjtqAWAgvhXzNmzHA4OMKoJNUVSCOQR0prS2CNILK1VPBL6dSZ7n3gQZEY21H1u7qqSqoqLpK7fOPt5XTnrHtFCBdCrqD8gikVRBgThI8WU0tgzZ03l6ZPm06xcbG0YfcGQWb0Te/rkNxTKnZAfCCvE+yxxx4TqiyYqzxKTU1NlJWVJcIcjSCwXOEBchLkI0IpQbgZaWeffTatXbtWdAniDwo5Z3bfffcRFGAwhImedhpCTlsMYaAmk0mXe8AUf9QafIbiatWqVeISTxVcjsaTQljxGcg9VIMEcYkw1549e9LcuXNl1Zdaf7kdI+BNBNQ8q705PvfNCDACjAAjwAg4QkDPOZQRDR4EmMAKnrUKCk/13DjUvBQzgWXcNtBCYIGIQX4mR4ZwPpA4sNmzZ9O9997bqlkbAmvsuURkldukdu5C550/muCPVkOOIImIQLjeDz/84HHyb7UE1lUTr6I333CczN6V/1A1SaqrCRMmiHxhUVFRgoST8HN0/bBhwwhVIL1NYGVnZ4tcS6g2abQZqcAy2jc1/V1//fVCDQUDkfXhhx+6XDM1fbprs2TJEpo4caIgRl977TVRjZKNEQgEBNQ8qwPBT/aBEWAEGAFGILQQ0HMODS2kgnu2TGAF9/oFnPd6bhxqXoqZwDJuybUQWCBQXBEbUmihI2WKOwIrrUs2nTDoJNq2bZvmyUmVBHFhnz59CDmTkOB9w4YNmvtSS2CdN+o8+uLzLzT3r8QQIZcIvUTVRiRPd2VXXHEFvf3224YQWEiSj2qSMIQLHj58WKic5s2bJ5LnI4H86tWrRe4uI83IHFhG+qWmr5kzZ9KcOXNEU+CCdVPmTlPTh6dtED4KNRYS2e/fv5/SvBBK7KlvfF3oIqDmWR266PDMGQFGgBFgBPyFgJ5zqL985nG1I8AElnbM+AoXCOi5cah5KeYk7sZtP/8RWOeAPpEnkpadQ/0HDKAdO3YQKrxBBaS0xro6qi5tyYEVFhFBaZ2zRROpMiB+9hWBNfzc4bRm9RpKTU8VCdwjwiKoe3J3twuTl5cnV9STCKzOnTuLxPeuzEgC64wzznCodENFRuQUQ06snJwcUaHRyOp6RlYh9GUI4eOPP05Iog5D/iuQkEbi4m7TLFu2TK4+iKIEUO6xMQL+RkDNs9rfPvL4jAAjwAgwAqGHgJ5zaOihFbwzZgIreNcuID3Xc+Pgl2LfLqn/CKzhrSaa3rUbnTlsmKhAiJw/O3futCOwaqn8UAvJEx4RQZm5eW3A8lUI4aWXX0rvLn+XoqKj6Kd9P1FsVCz1Su2lafEkUsrXIYTOCCw4/8ILL9D//d//iXmgAqGUh0rTxJw0XrhwIU2ZMkV8itBJZ9Uh8TlISZBUyBfmqNqgr5K4IxfYTTfdJHwGOfrdd9+5rJ5oBE72fUANd+65CLklUYkQajA2RsDfCPCz2t8rwOMzAowAI8AIOEJAzzmUEQ0eBJjACp61CgpP9dw4+KXYt0scKARWRk4u3TpjBs2fP1/k+4EiCaF1kjXW11H5wZYKfmHh4ZTVvUcbsKZNmyZC4WCeJHF/8MEHCWGEMITXObPZj82m++++X3y8bNUyGnzyYOqZ0lPT4oGMuOeee8Q1rpK4m81mkeOrvLzckBBCVwQWEsaDPEJYJkLWgGFGRoameTlrDEIKfcNuuOEGevHFFx02RUgjVGkwkHxQINmbLwgsKf8U9kGPHj1EmKXRie3VAKusUIi9LRGMaq7lNoyAtxDgZ7W3kOV+GQFGgBFgBPQgoOccqmdcvta3CDCB5Vu82/1oem4c/FLs2+3hHwJrPl06FiGELZbRrTut/fprGjFihPglQrZQpU8yU309lR08IP+7Q1gYdcxrSxh99dVXdM45zX2DzEL1Ni2mDBdraGgQ+aAc2catG+mUE04RJNfIsSNp/uvzKS+5rSLM1dibNm0SubpgqJ743HPPOWz+7rvv0qWXXio+MyKJuysCC2MgUTkSlsNQJfGRRx7RAqHLtn379qW//vpL5HHKz8+nuLi4Nu2Ra0pSGSH30/jx4w0bX21H77//vsAclQe7du0qyCuQZv4wZfJ7d3no/OEfjxmaCPCzOjTXnWfNCDACjECgI6DnHBroc2P/WhBgAot3g6EI6Llx8EuxoUvhtrNAIbAQDoiwQBA6IHZQkQ/KG4m4aWpooNKCfHk+UGkV1dYLhdAFF1zQap5IUg5FU1hYGCFnkLNQtdLSUkGgKJNxv/HGG6LqG+zPP/8kEC6OrKS+hP59xb/pi4+aE7nPemQWPXT3Q07xhqIJSeWhKFLawIED6ZdffqHIyEhau3YtnXbaaa0+R3L3IUOGiOTdMF8QWCaTSSiOCgoKKDk5WYTw4W8jTBlGiNA8hCwqbdeuXSLPVFVVFR111FGC7IqIiDBiaNV9fPnll2JPAQco3xA2KCnHVHdCJAgvKfzRkZoPyirszZiYGKfdPvvsszRjxgzxOfKn4f7oqlqlFv+4LSOgBwF+VutBj69lBBgBRoAR8BYCes6h3vKJ+zUeASawjMc0pHvUc+Pgl2Lfbp1AIbAQDoiwQBAYgwcPprKyMgEEiARUYcvLzRVJ3EtKS+mPP7fR6rVf0+Zff6XbbruNnnrqqVaggfRAHzU1NeL348aNE0QBSBkoapBfCyTFihUrRKJypbIGn/Xq1ZzLCnmHEOKHcDapwiLaglApqiuinQU76bJzL6MDe5uVYaeffjpdffXVdOyxxwrlFgiyrVu30qpVqwQ5NXbsWDGm0jZu3ChIK4QJgsiYPn06jRo1SlyPzxBmWFJSIog09OULAgv+QbkGX2CzZ8+me++915CNCfyhAFu3bp3o7+KLL6Zrr72WUlNTBXGJnFtFRUWCfPz0009p5MiRhoyrthOQjGeffTbV1dUJUhEkU//+/V1eDoVWSkpKmzbuCCx8joT5wAB7ALnfEhISxO9+//13Qb5KOCFP2meffUbDh7fOHad2XtyOETAaAX5WG40o98cIMAKMACNgBAJ6zqFGjM99+AYBJrB8g3PIjKLnxsEvxb7dJv4gsOY++QJdNrY5KbVkWXk9BWkBQ64kHOpBLrkz5Ky677772jSDAguEEcLUXBmUUfahYSDMELrmyKT2h2sPU2l9KZUUltBtU2+jzRs2u3OVJk+eTFAg2RsSmk+aNEkofuwNZBkSiYPIWLx4sc8ILBA4IMtAnqWnpwulG8gVIwx9gqT76aefHHYH8g7KrKlTpxoxnKY+kP8Me0qLvf7662L97E0NgeUoQb19PyDIsG+k0FgtvnFbRsBbCPCz2lvIcr+MACPACDACehDQcw7VMy5f61sEmMDyLd7tfjQ9Nw5+Kfbt9vAPgfU8XTa2OdeVZB17HCWrnPA7KHVAIr333nuC6CguLiaL2SyUOj3z8mjwoIF05aRJNGjQSU4Bq6+vp1dffZU+/PBDQYZB1QWVE0KxTjnlFKHsGjZsWJvrkcgcCiSopXbs2CEUMVarVbSTCKyDNQepvKFcvnbzN5vpyw+/pB9//JGQhBx9QJUDNRfGuvDCC4VCy5lt27aNkPtpzZo1gjTKzMykU089VYSPIawSBIkvCSz4qUwy/8QTT9Add9xh2OaE4uyVV14RYaJQzNXW1ooE6VA/IXcZVGz+MF8SWNhbUFWBnITyr7CwUKj2ENKK0MUBAwbQ6NGjRRito1xh/sCHx2QEJAT4Wc17gRFgBBgBRiAQEdBzDg3E+bBPjhFgAot3hqEI6Llx8EuxoUsRcJ1VFtdTQ2092Sylsm8IzwOB5cpAXhXv29OqSWb3PAoP921+JMmBguoCqmiskP1Jj02nTvEtVRMDDnh2iBFgBBgBP2N48gAAIABJREFUAxHgZ7WBYHJXjAAjwAgwAoYhoOccapgT3JHXEWACy+sQh9YAem4c/FLcvvdKZXHdEQKrOccVzFlFQSUSVouFivbubk1gHUn87g/E8qvzqaqxSh46My6TsuKy/OEKj8kIMAKMgM8R4Ge1zyHnARkBRoARYARUIKDnHKqie24SIAgwgRUgC9Fe3NBz4+CX4vayCxzPo6Kojhrr6shmaQm/Q/J2JHF3ZQjhK9qzq1WTjG7dKSIy0i+A7avaRzWm5iTxMJBXILHYGAFGgBEIBQT4WR0Kq8xzZAQYAUYg+BDQcw4NvtmGrsdMYIXu2ntl5npuHPxS7JUlCZhOKwrrqLG+NYEVHhFBmbl5Ln202WxUuHtnawIrJ5cioqL8Mrc9lXuorqlOHhvhgwgjZGMEGAFGIBQQ4Gd1KKwyz5ERYAQYgeBDQM85NPhmG7oeM4EVumvvlZnruXHwS7FXliRgOi0vrCNTfS3ZLC35o8IjIymzW3e3Ph7e9U+rNuldu1FkdLTb67zRYFfFLmowN8hdd0noQqkxqd4YKmD6RAJ7JFvXaki8n52drfUybs8IMAIBjAA/qwN4cdg1RoARYARCGAE959AQhi3ops4EVtAtWWA7rOfGwS/Fgb22er0rP1xLpgYQWJVyV1BRZeTkuu0aCiwosSRLy86hqJgYt9d5o8HO8p3UaGmUu+6a2JWSo5O9MVTA9HnmmWfSt99+q9mfiRMn0qJFizRfxxcwAoxA4CLAz+rAXRv2jBFgBBiBUEZAzzk0lHELtrkzgRVsKxbg/uq5cfBLcYAvrk73yg7VUhMILGsLgQUVFdRU7qxo7y6yWqwtBFaXrhQVG+vuMq98/nfZ39RkbZL77pbUjRKjEr0yVqB0ygRWoKwE+8EI+B8Bflb7fw3YA0aAEWAEGIG2COg5hzKewYMAE1jBs1ZB4ameGwe/FAfFEnvsZDOBVUM2a0sFv8iYGErPznHbJ6oQohqhZKmdsyk6Ls7tdd5osL1sO1msLb50T+pO8VHx3hiK+2QEGAFGIOAQ4Gd1wC0JO8QIMAKMACNARHrOoQxg8CDABFbwrFVQeKrnxsEvxUGxxB47WXqwhsyNILCq5T6gokrr0tVtn8X79pDFbG4hsDp1oeh4/5BG20q3tQpnzEvOo7hI/5BpboHjBowAI8AIGIwAP6sNBpS7YwQYAUaAETAEAT3nUEMc4E58ggATWD6BOXQG0XPj4Jfi9r1PSgtqyGyqJpu1Rp4oVFRQU7mzkv17ydzUEraX0rEzxSQkuLvM8M+RhwsEltJ6pvSkmAj/5OMyfILcISPACDACbhDgZzVvEUaAEWAEGIFAREDPOTQQ58M+OUaACSzeGYYioOfGwS/Fhi5FwHVWcqCGLE2tCayY+HhK6dTFra8l+fvIbDLJ7ZI7dqLYBN/nnULoIEIIldYrtRdFhUe5nQM3YAQYAUagPSDAz+r2sIo8B0aAEWAE2h8Ces6h7Q+N9jsjJrDa79r6ZWZ6bhz8UuyXJfPZoCUHqo8QWLXymFBRQU3lzkoP7KemxpbKf8lZHSk2McndZYZ/braaaUfZjlb9HpN2DEWERRg+FnfICDACjEAgIsDP6kBcFfaJEWAEGAFGQM85lNELHgSYwAqetQoKT/XcOPilOCiW2GMni/OryWquIpu1Tu4DJBTIKHdWWpBPTQ0NcrOkzCyKS0p2d5nhn5ssJvqn/J9W/fZO603hYeGGj8UdMgKMACMQiAjwszoQV4V9YgQYAUaAEdBzDmX0ggcBJrCCZ62CwlM9Nw5+KQ6KJfbYyeL91WS1tCawQEKBjHJnZQcPkKm+Xm6WmJFJ8ckp7i4z/PMGcwPtqtjVqt++6X2pQ4cOho/FHTICjAAjEIgI8LM6EFeFfWIEGAFGgBHQcw5l9IIHASawgmetgsJTPTcOfikOiiX22Mmi/VVkgwLL1kJExSWnUFJGpts+yw8VUGNdi3IrMT2D4lNS3V5ndIO6pjraU7lH7hbEFQgsNkaAEWAEQgUBflaHykrzPBkBRoARCC4E9JxDg2umoe0tE1ihvf6Gz17PjYNfig1fjoDpENX7oMCyWSrJZmsJBQQJBTLKnZUfPkiNtS25sxLS0ikhNc3dZYZ/Xmuqpb1Ve+V+ETqIEEI2RoARYARCBQF+VofKSvM8GQFGgBEILgT0nEODa6ah7S0TWKG9/obPXs+Ng1+KDV+OgOnQGYEFEgpklDurKDxEDTU1cjO117nrV+vn1aZq2l+1X74sMiySjk47Wms33J4RYAQYgaBFgJ/VQbt07DgjwAgwAu0aAT3n0HYNTDubHBNY7WxB/T0dPTcOfin29+p5b3yr1UYl+VBgVZDN1lJNUK2SqrLoMNVXV8sOqlVuGT2jysZKOlB9QO42Ojyajko9yuhhuD9GgBFgBAIWAX5WB+zSsGOMACPACIQ0AnrOoSENXJBNngmsIFuwQHdXz42DX4oDfXU9989qsVLJgRqyWcrJZjPJHanNZVVZVEj11VXydWpzZ3nuseMryxvK6WDNQfnDmIgY6pnS0+hhuD9GgBFgBAIWAX5WB+zSsGOMACPACIQ0AnrOoSENXJBNngmsIFuwQHdXz42DX4oDfXU9989itlJpQQ1ZLeVECgILCdxBRrmzquIiqquqbCGwVFYvdNev1s9L60vpcO3hFj8i4ygvOU9rN9yeEWAEGIGgRYCf1UG7dOw4I8AIMALtGgE959B2DUw7mxwTWO1sQf09HT03Dn4p9vfqeW/8FgKrjMjWJA+UlJlFcUnJbgeuLimm2soKuV1sYhIlZ3V0e53RDYrriqmorkjuNiEqgXKTco0ehvtjBBgBRiBgEeBndcAuDTvmBgHk4zRbbWSx2qjJYj3yd/O/zVYrmS3Nn0s/t/092ja3s9qI0B/+toq/bWSTf27+XevPj7S3tlyjqv2RMdAWZiP5hyP/PvL7I+M3t5F+1/oaqQ/R5sg/XLW1/0zqWfYFGBwZrcU/B2NLHRm0Q43sTsLBCNeM9Kt5jYzwStoDxvWVnRJLd40MzAJGes6hxiHEPXkbASawvI1wiPWv58bBL8Xtd7OYmyxUdrCWrJZSIptZnihIKJBR7qy6tIRqK8rlZjEJiZTSsZO7y9p83r17d9q3bx9NnDiRFi1apPl6kFcgsSRLik6inMQczf1464K9e/dSXl6zIuz111+nSZMmeWuogOm3tLSUHnvsMfrss88I829oaK5y+eyzz9Ktt94aMH4GmiPY/5MnTxZu7dmzh/DdYGME1CDAz2o1KHEbtQiAQGg0W6mm0Ux1jRaqNZmpzmSm2kZL679NFqprNFOtyUINTRZxDf6YzEd+brKSyYLfWaixSfrsyL+PtAUhxcYIMAL6EOjbOYlWThuqrxMvXa3nHOoll7hbLyDABJYXQA3lLvXcOPil2Lc755tvvqGzzjrL4aCxsbGUmZlJJ5xwAl166aXiT0REhMcOmk0WKjvUlsACCQUyyp3VlJVSTXmZ3CwmPoFSOnV2d1mbz/USWAgfRBihZCnRKZSdmK3ZD29dECgEVocOHcQUzzjjDMI+85ZVVlbSSSedRLh32BsTWK5RN4LAOvPMM+nbb79tM1BYWBglJycLMvW0006j6667jo499lhvbQO5388//5z+97//0U8//UTFxcXiHob9gfFHjhzp9fGdDQDS/Msvv6RNmzbR1q1bqbCwUPiHg3tGRoa4z44fP54uv/xyioyM1OUn1mP9+vVirL///ptKSkqovLyccE/v1q2bWI+pU6fSwIEDPR6Hn9UeQ9fuL0TBlrI6ExVXN1JJTaP4u7yuiSrrm6iyztT8d30TVRz5u/LIZ1A9sTECjEBwIMAEVnCsU3v2kgms9ry6fpgbE1h+AN3DIV0RWPZd4hD48ccfU6dO2lVP6Kup0ULlh0FglRDZLHL3IKFARrkzkFcgsSSLjo+n1E5d3F3W5nO9BBYSuCORu2SpManUJUG7H5odV3lBqBFYjz76KN1zzz0Cnf/+9790wQUXUEpKc061zp07U3p6ukrkvNdM+T37+uuvCaRPIJg3CSz7+YWHh9PDDz9Md911l1embrVaBUn12muvOe0fpM3LL79MINd8bbNmzaJHHnnE7bD9+vWjjz76SFZRur3AQYOuXbtSQUGBy0tBMN988800d+5cj/BgAsuTlQn+a+pNFiqoqKP88noqKK+ngxX1gqAqPkJU4efSWpMIx2NjBBiB9osAE1jtd22DZWZMYAXLSgWJn0xgBclCEQlljKTA+s9//kM33nij7HxNTQ39/PPP9PTTT4uwLNjgwYNpw4YNJKlrtMy0qdFM5YfryGpG+J1VvjS1czZFx8W57QrhgwgjlCwqLo7SOvte+XSg+gBVNrYkk0+PTadO8Z6Rem4n7UGDUCOwhg0bRiCFBg0aJFQ3gWihQmD9/vvvMvwmk4l2795NH374IS1dulT+/TvvvCOURkbbzJkzac6cOaJbqJlAZvbs2ZN27dpFTzzxBG3ZskV8hnYgPX1t9913n/gPAKifBgwYIMjVjh07UnV1tfAR4b5QTcF69OhBv/32G8XHx3vk5jHHHCMIsFNOOYV69eolxkpKSqLDhw8LVRZIPCjAYHfeeaeMm5bBmMDSglZwtUUY3+7iGtpVXEM7i2poT0ktHThCWIGcCiWLCOtAEeEdKCIs7MjfHSgcvwsLE3/jD8TGYR06UNiRv/F+JP2Mv1v/W9E+rPk6te0xDnTN0vtXs8YZv5D+av5Baif93Nyk5TPl78Un8vVH+nHZnzyqPJbUv9N+jnwgrmx9ue6tJM1Ld0dHcDOiHy9MU14jI/wzCrOspGi6+pTATDug5xxqBMbch28QYALLNziHzCh6bhz8UuzbbaI8WN9///30wAMPtHEAoScgrnbu3Ck+wyEMKhetZmowU0UhCCwkQG/539m0Ll0pKjbWbXd1lRVUVdKSewrX4FpfW35VPlWZquRhM+MyKSsuy9duOB0v1AgsHNYRJjVhwoRWREnALIgdUdyeFVjOEuE+//zzdMstt4glQRjhH3/8YejyYP3Rr9lsFkTmd999J8LlJKurqxOhrCDkEQb9119/0VFHHWWoD+46g2/uQrCRr+25554TXeFvCTN3fdt/7m4s5IzDPR0EI3wCsaVVqcjPaq2rEnjtTWYr/V1YTX8UVNJfh6poJ0irolo6XNWcQ9CfBs4jPiqC4qLCKT76yN/4d3S4/PuYyHCKjgij6Mgwio4Ipyj8LP4ofw478vtw0S4qvPnfIJ4iQUIJckr600xSNRNUEjllMOPiT1B5bEYgRBDQcw4NEYjaxTSZwGoXyxg4k9Bz4+CXYt+uoxoCCx4tXLiQpkyZIpyDSmv+/PmaHW2sN1NlkQMCKzuHomJi3PZXV1VJVcUt1f8iY2IoPdv3ydP3Ve2jGlON7G/H+I6UEZvh1n9fNQg1AktvSKgv1iVUFFjOCCyE90ERtH//fgH3oUOHPA5FdrReuCe9+OKL4qMff/yRhgwZ0qYZlKNQJOm5h3l7r4BIgloKdskll9C7777rtSGhVoMaDfbpp5/S+eefr2ksflZrgsvvjc0WK20/XE2/F1SKPyCtth+qFgnPvWUgodLioigzMZpS46IoJS6SkmMjKVn6Gz/HRlJKbJT4OzEmQpBVCdERFBMZ5pHS21tz4X4ZAUYgeBDQcw4Nnlmyp0xg8R4wFAE9Nw5+KTZ0Kdx2ppbAgmICuVlgOOjgwAOzP5iffvrporLfkiVLaNu2bSJJ8dVXXy1+14hErcX1ZDUX0m9//ElvLl9O6zdspMNFRSKRMfK2IBxs+vTpdPTRR7fxvUdeHu3Zu5dOOvFE+vidtykyOprSu3ZzOEfkf0GyYhyc77jjDhFCJJlawuOTTz6hxYsXi5BJzCMhIUH4NXTEUBo/aTzFJTSHPSJ8EGGEkkHF9uCDD4p/uirNrIbU2Lx5My1YsIC+//57kdPGYrGIpNRZWVnikD5ixAihhlOGdDojsJqamignJ0eEDuG6VatWudwfyjV//PHHRUiWFnOXxF36XFL+IfzvmWeeEXMF3khsjf1w9913U58+fVoNrSZ3m7Pk8VJI28aNG6moqIhiYmKEGgc4QvGSmprqdporV66kZcuWiZAv4Il1AfFw4oknin5Q8CAuLk6E3koVIV116qxaJNRa+O4AE5AbUMvk5ubSeeedJ74nXbq4zr0G9STWDnNGEvHExETq378/XX/99SKMz+gcWK72+6hRowgJ1mEIY0NOPSNMunccPHiQevfuLdRVzgyf79ixg7Kzsyk/Pz/gDsi1tbXiPgMbPXo04R7kLcN/QiAHFmzFihV08cUXaxqKn9Wa4PJ5Y1To++1AJW3aU0ob95TRL/vKReU+oywtPoq6psZSdkosdUyKESSV/Ceh+We0iQz3fb45o+bI/TACjEBwIqDnHBqcMw5Nr5nACs1199qs9dw4+KXYa8visGO1BBYOfTj8wXB4lg6iyuvxO+TL+uqrr1qNNXHiRHFQbqhtooqiWrr/oen0yqLFTskdHNJxuEJCZqXdded/6fEnnhSHzo1fr6G8Hj0oIyfX4byeeuopQVzBfv31Vzr++OPldu4IrIaGBhGO9sEHHzhdjKxOWbRg2QLq3a+3SOCORO6SGUVgoYLe7bffLkg4V4YcOtKhF+1cKbBAQj355JMiaTPUMDjIO7MZM2YQfMB64LCvNXm/FgILhNy0adNECJi9gQjC3gI5KpknBBbIHKha1q5d63xds7JEAm1HCh5chNCryy67jNasWeNyTSRCylMCC3tw8uTJ9PbbbzsdB/mR3nrrLafhvCByhg8fTiB2HBn6B6b4G7Znzx7Cd0OrKasQuiKwxowZI7CFIR8V8kAZYQiDQ64rGIi5l156yWm3+BwVCmG4Tg25aISPavtAAnokmofhu4/vqjcM9xTkPkSoJQxktdYKkfys9sbKeN4nvnvIVfXNjmL69u9i2rC7lBrNnqurkLspJy2OemYmUI+MeMrNiBeEVdeUWMpOjaW4KM8rEns+S76SEWAEGAH3COg5h7rvnVsECgJMYAXKSrQTP/TcOPil2LebQC2Bhf+hlxIvX3PNNXKlL+X1UHYg8fCFF15IkyZNEkoRqFOqqqrEoR8E1o3/uZFeX/KqmOSQk06iyy4eR/0HnUSJSUmitDwqYv3555/icxx20ZdkW3/ZTAMGDhL/vGvGdJox7RbK7Ob4wA0lDA7JjvLtuCOw4CsSTcNAfN12221CAVRWViYIBZBxOCwkpybT+9++TwOPHkjJ0cmyn0YQWMARiail0CsoJXDgT0tLE0mfQShCnQOMoMxRS2AhVxByRsGQyFoKIbLfdVBrgdyCEgqKIuQ902pqCSyQRVDkQOEHEgt/19fXCwIReYCAAdR0uDdERUUJN6BUAeECg5oMJM1FF10kqtxJBoJHIigaGxvpX//6F/3yyy+EanggKKEIwueYKw7yUH+BoIICC3sH+1dpyKMEX6VE5QMHDhQk63HHHUfR0dGC5EM/y5cvF9Xm8B1A31grqMvwvYEhHNdefQT1oVQ5EXsLmH/22WeivaToQmJvEI/ACkQxCEjgsW7dOpH3SWn4zsEv+ATDngaRDKIQewBzRT4o+CElvvc2gSXlKoM/+C6pUbqp2XNQg0o5+UC4Io+UM8PnIGZhwBd7wN8GYhVEJ1SrL7zwgtgzWFcQkFhzowwqQdwrsLdB8H/77beia5Ccq1ev1jwMP6s1Q2b4Baj09/PeMvr8j8O0Znsh5ZfVezRGt7Q46pedTL07JVLPrARBWuWmxxFyTLExAowAIxBsCOg5hwbbXEPZXyawQnn1vTB3PTcONS/FNqtNkCGhZDHxkdQB/yVqsKkhsKCKGTp0qAilg73xxht01VVXiZ/tlTAoFf/QQw859PLTj1fSBRc151l5+tFHaMKlzZXIMnPzKDyi+X9zoTxBiCJUMiAQkDheSnzcWFdLJw0+mX7/8086plcv+n71F+Jae9u+fbsccuaIpHFFYOFQi9Ad2Nlnn00IFZNIE2mch+c+TPdOv1f8c8RFI+jdd96lxKhE2Q0jCCxULAOOIGFQoQzVyhxZZWWlCAsDsSGZuxxYUN0gJA3hkCBXHBnIo3HjxomP8DPUM1pNLYGFfkEkYBx7rEEEYU/B3n//fRo7dmwbN9wRkrjgnnvuEYQdSCIoBEE+2RtC7JAjCfmZHCWElxRpuO6mm24iJCZ3VI0T1fdASijXTE24qOTPK6+8IoixyMhIQRxC8Whv6B/fSZC9p556Kv3www+tmkB9CJIC5ug7AJIE+/zLL7+Ur/MmgYW1k0LU8L2yV2lq3VvK9lBcoYIqDDmjoLJzZkoiHtdBkaU0kI4IG9ZjzkJX1Y4DxSHILOn7p8cXXOuqYiyIfoQpugtFdeSDmme1Xt/5+rYIgLTauKeUPv/9MK368zAVVzdqggnE1HHZyYKwwp/juiSLnFRsjAAjwAi0FwT0nEPbCwahMA8msEJhlX04Rz03DjUvxfXVJlp4R+sDmw+n55ehrnnyNIpNbFafGGmuCCyoXKDSACGDdjCQSiA9oDiBKa8HIYK8V1C4OLKzzjyLvvn2Gzp/xAh6df7zcpOs7j0oTHENlAd9+/YVn+OAfc4554ifG+vr6LGHHqIHH5sj/r32s0/prFFtEw/fe++9QomDgxsO5fZKGleEh5SnB+QBiCPkjLK37WXbafK4ybTh2w2CXNu+azv17NYcwgQzgsACgQEiAyosqIa0mDsCCwQk1DgwEB8gQOwNyjccbKHYQe4td9XTHPmnlsBCDiqQRxjL3qA2Qy4skELI+QTlkL25I7BqampEfjWQfSCdpLw/jnxGInAkBMf6gyQCgQirqKgQijSosEB+IX+Ws33uqF+1BBbUV7169RJ7D8o/iYRy1CfCKiUFEVRVuA4GrBDuCf+hikQIrSMSA/dpKHxAZsGMJrDgB8L0QEzi+wjsQM6AnD755JO1bGmXbRFmJ+VnAyaOCD+pAyVmwBYYK83fBNbll18u8vU5uu94Cpijtcc6QMWH8FHpXq61fzXPaq19cnvnCOwvraN3N+fTis0H6FCluiqBSKLep1MSDc5Lo5Pz0uikvDTKSGh+drMxAowAI9BeEdBzDm2vmLTHeTGB1R5X1Y9z0nPjUPNSzASWcYurJpeQNBoIhi+++KJV7hrl9SCOZs+e7dA5hDQhZAjhYC/OfYbGHFE5oXFWXs9WCiL8DonKS0pKRDJ0qJFgpvp62rZlMw0ceobo56brrqMXXn65zXhIyA0C4LTTThNKI3tzRnhAaZacnCwO2spE9fbXbyvdRp9/8Dndfu3t4qNFbyyiiVc1E0IwIwgsJDYHljhcIiwNJe/VmjsCC+F5SDgOQgeVJV99tTmkUzKEfYLwAR7uSBRXPqklsNyFKCIUDkojhAgiGbna9ZTaKVV17qrfYRyMB0OIlZR3S6kggkIHhQm0mFoCSzm+s2p60rjKhN9Kn3AdwiVhICmkkDlH/kKFJYUqGkFgucIEap958+Y5JEy1YGnfFkpF6R6B3GRI/O/MQJ5BAQbDdZK6T2oPshbEnx5Thq4660c5Du6NCBkGYQ2yGvcthJlKhKQeX3At8lvBEEKI7zZCj6E+A3F57bXXCsIMhK1WU/Os1tont2+NgMlspc//OETLf8qn9btKVcGTlRhNZxydSWcek0WnHpVOKXHG/8eXKke4ESPACDACfkJAzznUTy7zsB4gwASWB6DxJc4R0HPjUPNSzASWcbtPDYGFPEEIy0FSYXuVjPJ6V+E7IAOQ7FmrITQIVfhgTQ0NVFqQT5dePZG+X/8jZXfuTPkFBa3UJVDGSAm4oaa54YYb2gzpjMBS5ocCeQRCzt6gkAGBdTD/IJ174rni4//e9V96/LHH5aZGEFgIg4R6BodMqJ+gKgGphsMt8nq5CgtyR2DBUaiMgA/CD5EXB4oMyZQJ8EGoSGo4rWunlsCyrxJpP44U8ghiwlHydHcKLJCgWBOthlxWqCYIk1R9+NmT5N9qCSwQUVABaTVllUgkKZdC40B+ItTQmWGfgyyFeZPAQmgo8k9h3xltRiqwjPZNS38gmBCa+vLLLwuyH0STsviElr7ctUVuNIQ6Ys2hcIUyTYuiEP2reVa784M/d4xARZ2Jlm7cT4vX76UiFSGCyF01ql9nGt6nI/XpnBhw1TV5nRkBRoAR8CUCes6hvvSTx9KHABNY+vDjq+0Q0HPjUPNSzASWcVtOebAGWSQdMEE+ILQL4VtQJTkz5fXIayOpG+zbg9ySyAAt3ksVDHFNU2MjlR7YT2+veI+m3zVTdINDnpIYu+WWW0SYGBQFUNukp6e3Gc4Z4YEcX8iBBHOUHwe/t1gthBBCU6OJTux6omh77fXX0v9eaq5sBjOCwEI/7733nlBI2CtCsCYgtBBm6IicUENgQekh5YGyVxSBIEMoKMK8pLxnWtZMaquWwAKB4opgkqrcOcst5I7AAikgkaBa5iFVEsQ1+G5I1e2gYMN3Q4upJbCUZIyW/pUYzpkzR07ODyJUStrvqD+QJRLJawSBJSW4x1jYt1AWgbiCIhIGtY9UHVTL/Fy1NTIHllE+edoPwi6hIAXBhHvR+vXrPe3K7XXKcErsA/uqr+46UPOsdtcHf94agX2ltfTaD3vo3Z8PUH2TxSU8fTon0ej+nWnkcZ2oR2YCQ8kIMAKMACNwBAE951AGMXgQYAIreNYqKDzVc+NQ81LMSdyN2wZqkri7Gk3twRzV+6644ormQ+zDs+mkE5vJH+oQRhld2+aZksaEEgG5h2Bmk4lK8vdRdXUN9R9yCjU0NgqCB4oTGBQMaIswGVdhaWoILGcHuiZrE/1d9ncrAuu666+jl19qCWU0isDCnBDmByUQQjcRDomqgEoDwYdwIy1J3KXrpUqNIIhABMKUCjZPDrVK3wKFwAJBg7nAQNypDZeMDqABAAAgAElEQVRSVgb0FYGlJJ+Qgwx7VY1BGSmpI5V9IF8dctM5M6MJLCgU7Q15zKAcBJkFNSFIGfsqjGrm6KyNkVUIfRVC6Gq+Uv47tMGzVLr/6cHI0bW4X0KBCUIWKixlQn81Y6l5Vqvph9sQFVTU07yv/qEVvxwgJGl3ZsmxkTT2hGwaP6grHdvF+X8sMaaMACPACIQyAnrOoaGMW7DNnQmsYFuxAPdXz42DX4p9u7i+IrBQpv3cc5tD7p5/6km6ZMxF4mckb0cSdzVmaWqi4v17RdNrb76FPl21itLS0kQIHEgJHMBGjBghPgdhdtlllznsVk8Ioclion/K/2kVQjhz5kxR6U0yZVgWDolKcknpkDI3k72SzBkeSHD/0UcfCZXZwYMHRbO5c+fStGnT5EvUKLDQGKokqJNANEEhg1BRiexBSCEUbElJSWqWxmGbQCGwpAqEcBLKFhBTWs1XIYRSBUL4B8ISxI9WU5JSvg4hdERgwf+tW7cSCFPkroNqEH4ZZQjp7NmzuYgCQiclpZyj/vG5RHg7CgX1VRJ3V3NX7leQfZIq1Ci8lP2AHMN9xFVFUmfj8rNa/4qgguD8r3fSso37yWSxOu0QSdj/PSSXzu3bkWIiHRdJ0e8N98AIMAKMQPtAQM85tH0gEBqzYAIrNNbZZ7PUc+Pgl2KfLZMYyFcEFpRDHTt2JBxwr55wBT0++0ExfnhEBGXm5qmatMVspuJ9e0Tbz1evpmv+c5P4GYQOquZBjYQKe1AVQIUVGxvrsF89SdwbzA20q2IXffHRF3Tb1OYKZkuXLqUJEybIYyFkSkqcjUT0jsIY0VjZTi2BJQ0CIqZPnz6ERN5I2L1u3Tp5fLUEFtRdSOYOBQaSYN91111ycverrrpKYKnHAoXAWrFiBY0fP15MxRWx6WquqKQ3btw40WTRokVyFUe1+ChzwLlaa1T9lNRJUFLdeeedaoeQ24H0kCpLukviDqUiFEwwI0IInRFY6B976s0332z+/rqpFqhl0hgTpCSImN69exNIXmeG7wzCKkHc4Dtkn0suEAgspQ9QrfXr108LHKrbIlwR90r8DXJx8+bNqq9FQ35Wa4KrVeOGJgu9+M0u+t93u52GCoaHdaDz+3WmqUPzqH/XFM8H4ysZAUaAEQgxBPScQ0MMqqCeLhNYQb18gee8nhsHvxT7dj19RWBhVicPHkKbftpIiQkJtH7NV5SRnkbhkZGU2U1dmJTVYqGivbsFQDh0HX/KqVRRWSlyayGPE0KoEK6ECnH4tzNzlTNp1KhR4nCNpNNQJdmrdeqa6mhP5R66bvx1tP6b9SIkav/+/YL4kQyV8saOHSv+uWrVKlkVZu8Pckxt2rRJ/ForgYVrpBBAe/WEWgILfQCrJUuWUG5urqjKJlXX88Qf+/kFCoFVUVEhCAtUlwTZ98MPP2hOcow+sBdAGCJ3GEIttSS9VoZmutoTUChhLXAP7dGjh6i+qDXfVmNjo9iPyEE1YMAAETbpKOk/wuUwBr5LMG8TWCCOkF8NcwTBhnUwyqSiBOjPWfVGZY47tJ8/f75RwxvWD/YX1qSoqEgQ8KWlpU6JeL2DKvMSKnMNqu2Xn9VqkWrdbu32Qnrg4220v6zOYQcxkWH075NzafJpeZSd4vg/YTwbma9iBBgBRiA0ENBzDg0NhNrHLJnAah/rGDCz0HPj4Jdi3y6jLwmsFW9/QOOvaFaxDDnpJFr08ouUnpFBGTm5bSaNQ/irr75KU6ZMkQ/wOPgW7WlOBg27/Z5ZtHT5O+KA98ILL4i2MOSLksIVHaHpisBShvWhD6hTlDmTakw19OyLz9J9t94nuj5vzHn0+QeftxoGh08QJmazWZBXIMTsCQT7ZN32hBFIMOSmSklx/D/vUI8gOTfUUxgDpIhkWggshHIhOTqsU6dOIhwT4Vj4HrqqdKhmlwYKgQVfoWRCAnEYwi2feeYZp6GdUO8h/9TUqVNbTfO2224T18FuvvlmmjdvnkOMUDkS5JGyYidIThBTMBAnrqrxoTqk9DmUYyAYo6OjHUJeVVUllHLwR2lKX5UVCqU22JtQLWJvSuZtAgvjYD5QxMHWrl1LZ511lpqt5LYNKoiiWiZCdgcNGiRCFJUKTHxPUM0SCjeQzihS0KtXL7f9GtUASkyo8C6++GKnXTY0NAhl3zvvvCPaOFNBKnPsKQsNSB2jmAbucUgG78wwfxTcwPcdhuqeqPKpxfhZrQUtovyyOpr96TZava3Q4YWR4R1owuBudNNZR1FWkrYiEdo84daMACPACLRvBPScQ9s3Mu1rdkxgta/19Pts9Nw4+KXYt8vnSwKrqqSebr9jGr2y6BUxyazMTJp01b/p3FHnizA7qA927twpcv+8//77ggSAoiohobnCEkKFCnfvlAFav3ETXXzlv8W/QfRAJYMwRShLXKlj3FWtg6IL6gQYVE4IB0RoEvx5Y+kb9ObiN4UvyanJ9Mn3n9DQY4e2WTSEFL711lvi96NHjxa5puAbiAwQEqgwCDWQVGXMnsACefXTTz/R+eefLw6WCH1CNUj4gEM4cmCBxIIhvG3MmDGyD1oILFwEIgwEgGRQYs2aNUv3RgwkAguEKIg6KKFgxx9/vCgAAIVSfHy8wBVqJxz+QeogbAs4Kw0KriFDhpBUaQ9KLORUQlso9nDfw97Fuj/88MOEUDCl5eTkiDbINYa8ZcBd2qfYGwjnkvY5iA6sKwyEIsYZPHiw2AMgraBmwnf3448/FgQvCBKlITz0uOOOE+PBUEAB6jqQalhrEHHYXyB7pHn6gsDasmWL+E7BsK9BnBhlyEWHsEvYCSecIEhLYAclJUg8jA2zz1ln1Piu+pG+kyCVsLZYS5DcICaxdlBivvbaa4S8XDB8hvVRKjul/t0RWPgc+w8EFcjt/v37i/srSMt9+/aJXIG4B4Ewg11zzTVibK3Gz2p1iFmtNlq0fi898cV2amhqm+cqrAPRxSd2pVvO7kU5aXHqOuVWjAAjwAgwAk4R0HMOZViDBwEmsIJnrYLCUz03Dn4p9u0S+5LAqiyup/rqSnpm3mP07PwF4kDlykAsIHeWUklxeNc/8iUgkU4+62zKP3JIxwdQ14AccGXuCCwc7EBASQSCo76yOmXRgmUL6PgTjqejUtoqHaDiQbJq7GdHdvnllwuFz/Dhw8XHjggsKDZcGZLDP/jgg23IJq0EFpRJUq4l9IlDrieJzu19DSQCC76BDAWpBHLUnUEZBIWQvYFsAAHhLgm5I2WMUlll3699e6i4sJeRkNxVXin0A0JMIj6U/YKQw/6SVDb2YwILkHqTJ08WH/mCwMI4IGVXrlwpxnQW7udufRx9DoUmSElU5XRmUGkiibuzwgqejKvmGuV30l17JG1HrjCEEjoyNQQW7gvuDOQpyPnHHntMUzis1C8/q90hTHSosp5uf3crrdtZ6rDxSd1TafZFx1Gfzp4Xy3DvBbdgBBgBRiC0ENBzDg0tpIJ7tkxgBff6BZz3em4c/FLs2+X0LYFVRw01VWSzVtP+/Hx64623ad3GjbQ//wBBMYLKd1CpQD2B8D3kkZJUKRIqUGApD/RPLXiJnj4S1oU2UDJISbCdIemOwJKuQxgZEnYjdw6ICxBqPY7qQUNHDKUJUyZQXEIcxUbEUo8UxwdNqHqg/ABhAuUVrocq5rrrrqMrr7yyVQJ9ewILFQARvoj1QbgPSAj4ALUNQtEQDoWKgVBX2JtWAgtjdenSRXRjH46oZzcGGoElzQW5l5AjDWopJP5GeBmqLUKtA2UMCBbsP1cqPpCby5YtE3sDJCvmCgyhyoIaDiSXo7A/7AVUCfz111+prKxMJnEdEV7wF2ovVCbEPsAeqqmpEYpEkFYYa+TIkULh5yzEEGNgD8JfXI/vExRjIHqgysL+9jWBpUwyj5xzCNs10kCOgaSCggnfmYyMDHFPgIoNePnDQK5h3lA/4R4Fkhgkt6Qw7datm1DDIcQS30FX4bvuCCzcS6EixJ5B9Ud8vxHWDB9SU1OFmhT3DyjypOqNnmDCz2rXqH2y9SDd88HvVNXQ9j9qMhKiaObIPjTuxGzdodqerB1fwwgwAoxAe0ZAzzm0PePS3ubGBFZ7W1E/z0fPjYNfiv28eF4cvqKojhprK8lmrZFHiY6Lo9TO2apHLdq7i6yKcuNpXbpSlJNqg6o71dCwtL6UDtc2542BxUfGU/dkdUnoNQzj06arV6+Wc4YtX75cJMVnYwQYAUbAFQL8rHaMTm2jWRBXH/560GGDq4bk0u0jjqHk2EjeYIwAI8AIMAJeQEDPOdQL7nCXXkKACSwvARuq3eq5cfBLcfvdNRWFddRY15rAiolPoJROLRX83M0eVQhRjVAykF8gwXxlxXXFVFRXJA+XEJVAuUltk9D7yh8jxoES5+233xZ5cpA/zJmax4ix/p+984COquji+D+99wZJCKF3UIrAB9KbWGiCKCAoIEhRRLGiIiiKCgLSizRBmohU6SBFuvQeWgiQSnrZ+p15uO9lgSS7+95u3tu9c45Hsjtz597fvMzu/DNzh2wQASJgHwTos/rxcbyVmoO3lp7A5cSsx94sG+CJyT3r4X+VQ+3jAaAoiAARIAIyJSBmHSrTkMitJxAgAYseC0kJiJk46EuxpEMhK2MP7udAlccErBzeL09fPwRGlDHZz+RbN6AtlDsrqGwkPLx9TG4vtmJibiJScoWE2f4e/ijnV06s2VJrzxJcsyNFLB/ZBx98AHY7IhUiQASIQEkE6LPamND+q8kYseJfZOSpH0P3Ur1ITOhSGwHetOuqpOeK3icCRIAIiCUgZh0qtm9qbzsCJGDZjrVD9CRm4qAvxfb7iDwUsNKh1+XyQXr5+SMgPMLkoFNu34RGLSwQ2O4ttovLVoUdH2THCA0l0CMQUX6mH4G0lZ/F9cN2WbEb9Vjib5a8neXJYbm1mJhlyIUlBz/JByJABORLgD6rH44Ny8k4f/91fLf1EnR64/Hy83TF111ro8tTyvqMkO9TR54RASJABEomIGYdWrJ1qiEXAiRgyWUk7MQPMRMHfSm2k4fgCWGk3cuBOt9YwPL2D4B/WLjJQafE34JGpeLrB0SUgZevn8ntxVa8m30XD/If8GaCPYNR1tf0I5Bi+5eifatWrfDoDYds5xXbgUWFCNiaAEswzv4zt7i7u6Nq1armNqP6EhGgz2pArdXho7VnsO7fhMeoVo3wxbx+DREbarsdwhINLZkhAkSACCiagJh1qKIDdzDnScBysAG3drhiJg76Umzt0Sk9+2l3sx8KWPo83gnvgED4h4aZ7FTqndtQFxQIAlZ4BNguLluVO1l3kFGQwXcX4hWCMj6mH4G0lZ/F9WMQsNitj0wAGDVqFPr37y8H18gHByRQ+FY9c8Jnt3GyGzeplA4BR/+szlNp8fbyE9h7OfmxAehUqwx+7FUPvh6upTM41CsRIAJEwIEJiFmHOjA2xYVOApbihkzeDouZOBz9S7G8R1acd6kJ2dAUPIBen88b8gkMgl+I6UltUxPioc4X2rPdW2wXl63K7czbyFIJCXrDvMMQ7m36DjJb+Un9EAGlECABSykjZeynI39WszxXAxcfw/Fbwm5cRsfJCXi/fVUMa1UZzs5OyhxY8poIEAEioHACYtahCg/dodwnAcuhhtv6wYqZOBz5S7H1R6Z0e0hJyIb2EQHLNygYvsEhJjuWdvcOVHnCDi6/0DD4BASa3F5sxVuZt5CtyubNRPhEINTLdAFObP/UnggQASIgBwKO+lmdlJmP1385ikv3jW8a9HJzwc+vPo12NU3P6SiHcSQfiAARIAL2RkDMOtTeWNhzPCRg2fPolkJsYiYOR/1SXArDZPMuU+5kQatiO7CEI4BMvGIilqnlwb0EFOQKSeDZ7i22i8tW5UbGDeSqhf7L+pRFsJfp/tvKT+qHCBABImBNAo74WR2flos+C47gdprwGcAYB3i54ZcBjdCgvO0+i6w5tmSbCBABIqBkAmLWoUqO29F8JwHL0UbcyvGKmTgc8UuxlYdDNuaT47OgU6dBrxeSsJsrQD24fxcFOTl8TOYKYGJhxKXHIV8jHGGM8o1CoKftdoCJ9Z/aEwEiQASkIOBon9X3M/LRc+4hxKcJO4AZx3A/Dywb2BjVytjuMhEpxo9sEAEiQATslYCYdai9MrHHuEjAssdRLcWYxEwcjvaluBSHyeZdJ9/OglaTBhQSsFgCd5bI3dSSnngP+dnCET5zjyCa2k9R9a4+uAqVVhDgyvmVg7+H7ZLIi/Wf2hMBIkAEpCDgSJ/VqdkFeGXeYVxLEj57GMPyId74dWBjlAv2lgIp2SACRIAIEAEJCIhZh0rQPZmwEQESsGwE2lG6ETNxONKXYkd5HgxxJt3Ogk6TCujVfOjmJmHPSLqPvCwh94i5SeDFMr+cdhkanYY3E+MfAz93+su7WK7UnggQAWURcJTP6sx8NV6ddxjn72YaDVD1Mn5YOvAZhPt5KmvgyFsiQASIgJ0TELMOtXM0dhUeCVh2NZylH4yYicNRvhSX/ijZ1gO9Xg+2A0unZQKWIAAFhEfAy8/0HUwZSYnIyxIWEmz3FtvFZatyMfUidHod311sQCx83Hxs1T31QwSIABGQBQFH+KzOVWnw+sKjj902WDHMB6uHNEWor4csxoKcIAJEgAgQAYGAmHUocVQOARKwlDNWivBUzMThCF+KFTGIEjspCFgpgF7LWw+MKAtPX1+Te8tMTkJuZgZf39s/AGwXl63KhdQLYLEYSsXAivBy9bJV99QPESACREAWBOz9s1ql0WHgkmPYfzXFiHdUoBfWDG2KyECa92XxIJITRIAIEIFHCIhZhxJM5RAgAUs5Y6UIT8VMHPb+pVgRA2gFJ3U6PVJYEnftIwJWmUh4+pi+gykzJRm5Gem8h2z3FtvFZYvCdl6xHViFS+XAyvBwpb/C24I/9UEEiIB8CNjzZzX7I8X7a05j3ckEI+Bhfh5YM6QpYkNN/8ySz4iRJ0SACBABxyAgZh3qGITsI0oSsOxjHLkoMjMzsWXLFhw7dgzHjx9HQkICkpOTkZeXh8DAQNSsWROdO3fGwIEDERISYpXIxUwc9vyl2CqwFWJUp9Uh5U42dJpkAMIRvKCyUfDwNj0BblZqCnLSHxQSsPwQEF7GJhS0Oi0upV0y6qtKUBW4u7jbpH/qhAgQASIgFwL2/Fk9fddVTNlxxQh1oLcbVr3VlG4blMsDSH4QASJABIogIGYdSlCVQ4AELOWMVYme7ty5E+3bty+xXmhoKH799Vd07NixxLrmVhAzcdjzl2JzOdpTfa1Gh9QEJmAlARCO4AVHRsPdy/SjGNlpqch+kMajYccP2TFEWxS1Vo0rD4wXNdWCq8HV2dUW3VMfRIAIEAHZELDXz+o/TyXg3ZWnjDh7ubngt7ea4Klypt+YK5uBIkeIABEgAg5GQMw61MFQKTpcErAUPXzGzjMB680330Tr1q3RoEEDlCtXDmXLloVOpwP7hV67di3WrVsHrVYLd3d3HD16FPXq1ZOUgJiJw16/FEsKWIHGihKwQqLKwc3T9FucmHjFRCxD8fDxQVCZSJsQKdAW4NqDa0Z91QipAWcnZ5v0T50QASJABORCwB4/q88lZKDH7EMo0Ai7hJ2cgPn9GqJdTdscVZfL+JIfRIAIEAGlEhCzDlVqzI7oNwlYdjTqTJhycXEpNqL169ejW7duXB32fyZoSVnETBz2+KVYSrZKtaVRa5F2Nwc6TaJRCCHRMXDzMD2HFDs+yI4R8gKWtzfYMURblHxNPuLS44y6qhlSE05shUOFCBABIuBABOztszo1uwAvzTiIhPQ8o1H88sWaeKNZBQcaWQqVCBABIqBsAmLWocqO3LG8JwHLscabi7Z69eq4fPky2FFCliNLyiJm4rC3L8VSclWyLY1Ki7R7jwtYoeXKw9Xd9BxSORnpyEoRnld2/JAdQ7RFyVXn4kbGDb4rtvOK7cCiQgSIABFwNAL29Fmt1enRb+ERHIoTdvey8XytcQwmdqvjaENL8RIBIkAEFE1AzDpU0YE7mPMkYDnYgLNwGzVqxCV59/X1RVZWlqQExEwc9vSlWFKoCjemLtDiwX1DDiwhmLCYWLi4uZkcXW5mBjKTWR6th8Xd0wvBUbYRsLJV2biVeYvvm+W+YjmwqBABIkAEHI2APX1WT95+GT/vNj4e3rB8EFYMbgJ3Vzoi7mjPNsVLBIiAsgmIWYcqO3LH8p4ELMcab27nVe3ataHRaNCwYUPuxkIpi5iJw56+FEvJVOm21AUaPLiXjQsXD+LnOfNw+OhRJKemQq1Wc6H9+++/eOqpp0oMMy8zExnJwjFENw9PhESXK7GdFBUyCzIRnxXPm3JzcUPVoKpSmC7RxoABA7BkyRKUL18eN2/eLLE+VSACRIAIWJOAvXxW772chAGLjL8DlfH3xIaRzRDuZ3p+RmuyJttEgAgQASJgOgEx61DTe6GapU2ABKzSHgEb9J+bm4uEhARs3LgR33//PRITH4oA7CbCPn36SOqBmInDXr4USwrUisb27t3LJfxn5csvv8S4ceOs0psqX4N9Ow7gpV7PIT8//7E+TBawsjKRkSQIWK7uHggtF2MVnx81ml6QjoSsBP5lD1cPVA6sbJO+pRCwisrV5ebmhqCgIO5YcYcOHTB48GCEh4dbNS4mni9YsADLly/HpUuXkJ2djcjISLRr1w7vvPMOatWqZdX+izPOdqbu27ePE/YvXLjAHbFOS0vjLr1gPjZp0gRsPAy/N5Y6WlBQgC1btnAXabC+bt++jZSUFG5HrL+/P6pVq8bxeOuttxAdbZtdhpbGQu0cj4A9fFbfz8jHc9P+xoPch39IYcXV2QmrhjRFg/JBjjeoFDERIAJEwA4IiFmH2kH4DhMCCVh2OtSLFy/GG2+8UWR0H3/8MSZOnGh2Emo2MRRX7t27h2eeeYarEh8fb9biyx6+FCvpcbKZgJWnQYcO7bHvwF74+friszEfoF6d2oiqVAVOzs6oXLkyPE24jTA/OwvpifeFxYa7O1geLakKE/C++uorzpxerzcym5afhnvZ9/jXvFy9UDGwolRdF2vHmgLWox0HBwfjt99+48QsaxQm0nTu3LnInZ8eHh6YMWMGBg0aZI3uS7TZvHlzHDx4sMR6PXv2xNKlS016bp9k7Nq1a6hSpUqJ/fj4+GDmzJno379/iXWpAhGwFQGlf1brWN6rX47g4DXjvFdjn6+BQc/aZl631VhRP0SACBABRyJAApZjjDYJWHY6zkUJWOyo1rx587g8WJYUc25dIwHLEsK2a2MrASs7Ixch4UFQqVR4e9BAfPHxR1yQERUrmyWg5udkI/2+ICKx/Fksj5ZUpTgBKzUvFfdzBPHMx80HsQHS9V1cDFIKWOzY8KJFi/ju2I4fJqbMmjULhw8f5l5nosnZs2dRoYK0t2+xW1JbtWqFAwcOcP10796d2/HFRLMjR47g66+/RlJSEpydnbFp0yY899xzUg2tyXbatm0L5uf//vc/1KhRA2XLluX8YzuxTp8+jTlz5uDGjYfJ/F955RWsXLnSZNuFKzLmzZo143ZysbmYHQ9lfbEdcWy37ObNm7kdamzHIptzGQ8m/FEhAnIgoHQBa/7f1/HNlotGKNvXjMC8fg3M+kySw1iQD0SACBABIiAQIAHLMZ4GErDsdJzT09Nh2C2Vl5eHuLg4rF69Gn/88QcqVaqEqVOn4oUXXjA7ehKwzEYm2wa2ErBuxN1GxcoPd0r98PUE9O39CrdIYAKWOaUgNwcP7t3lm7i4uiKsvHQiS3ECVnJuMpJyhQTyfu5+iPG3zfFFKQWsli1bgo37o4XtOOvVqxfWrl3LvTV8+HBuJ5SU5ZdffsHAgQM5k8OGDeN2Fj0q6jRo0ACZmZncrryLFy/C1dVVShdKtMWONxbXJ5tL27Rpw4t9TNSqW7duiXYfraDT6bjfgeLmU3a8kO0IY7ninn76aZw8edLsfqgBEbAGASULWOfvZqDrzINQa4VdtmUDPLH13WcR6G36rbjW4Eo2iQARIAJEQBwBErDE8VNKaxKwlDJSEvm5bNky7jgKWzgtXLiQy+diTqEjhObQknddWwlYly9cRfVaDxOeT530HV7p0Z07OhhRoZJZgFR5uUi7K+ShcnZxQXisdMc9ihOwEnMSkZKXwvsb4BGAaD/b5CayhYDFAmMiNxOOWGE5mFh+KilLzZo1OVGK7WhiuzO9vb0fM//dd9/hk08+4V5ngjs7qie3wnZdvfrqq5xbTORjYp+1SqdOnbBt2zbOPNstx26OpUIESpuAUgUslUaHl2YcwKX7wu3LTk7A8kGN8b9KoaWNlfonAkSACBABkQRIwBIJUCHNScBSyEBJ6SY7+sIWh+yoEEsezBaUUhUxE4dSvxRLxc7WdkoSsAq/v2fPHu74F3tu5s6dizNnznDJt2NiYtClSxewnGqPPkeFBaGiYntS8nh2bIol+Wa7Bc+fP88l0Q4MDORuz3yhfTv06t6N2yVTnAjGkmSzm/v+/PNPnDp1ikuQzdrExsaiadOmnDDC8jwxIbekfHEG37ed2IaomCjux0DPQET5RnHHzdhlCGvWrOF2yKSmpnIiQ43q1dGtSxcMGzkSXl5exQ4tE3UmTZqEXbt2cUfVwsLC8Oyzz+K9997jjpfZSsBiu7D8/PyQk5PDiUvs/1KVK1eucKIYK0OHDsXs2bOfaPr+/fvcUTpWmEi0YsUKqVyQzA473mfYvfrjjz/i/fffl8z2o4bYc2rYFcee4ZCQEKv1RYaJgKkElPpZPX3XVUzZccUozKEtK+Hj56qbGjrVIwJEgAgQARkTELMOlXFY5NojBEjAcsBHgi0KDbcPsjwrr732mmQUxEwcSv1SLBk8GxsyR8Bi4grLncTEmicVtnNn//79KFOmDP+2JQIWO5LFBBuBPJ4AACAASURBVLFbt24VSeOpunWwdN5chIeFPfEYIhOsWH4lQ66iogyx95mgZYmAFewZDHWaGi+99BKXG6moUik2Fpv/+osXbx6txwTB119/HUxwe7QwwY3lXGJcmRjH8iTdvHnToqfEcFStqCOEBqNMKMzIyEBAQADYMWSpSuHjgyxJfO/evYs0zYQuJngxcbS450Aq38y1069fP/73gOWmev755801YVJ9JmYyFg8ePEBoaCgnblIhAnIgoMTP6quJWeg8fb/R0cHqZfywYURzuLs6ywEr+UAEiAARIAIiCYhZh4rsmprbkAAJWDaELZeuduzYwd8yxm4iNBzZkcI/MROHEr8US8GstGyYI2CxpNaHDh1C165dOcGFiSmJiYlcHiO2I4UVJkowccJQWEJu9t/1a7fQpdvDfGsfjX4Pndq1BctfFVQ2CuHh4dx/rLDE1izJOBNQ/P39uaNZ7EbLcuXKcTub1v/xB+YvWACWp6h+vXpYv3IFoqvVMMojxHYzsTZsdxgr3bp14/yqWLEit1uKCSPbt2/ndnedO3eOE7AM+eJYInPDziCWxLxwYQncQ2NCuSTbrDjnOqNj847cUTh2cx5LRs7EoZjISKRfuYIdBw9i1vLlyM3LQ8XYWJw8dYoThQqXY8eOccnCWTzMBttxxRJ1s3+zpObsd5PFzY7eMZHM2gIWu0E0MjKSc7FevXrczjWpygcffIDJkydz5v7991+wyySKKkzA3LBhAzeu7Ngc2ylamoXlq2LiEdsN+PPPP2P9+vWcO9WrV+eS3UuZp4sJmXfv3sXOnTu5XXnsWCcrLMH9Z599VpoYqG8iwBNQ2me1VqdHj9mHcCpeEOWdnYA/hzdHnWjjeZmGmQgQASJABJRLQMw6VLlRO57nJGA53pgb7TiZPn06Ro4cKRkFMROHKV+K9Tod8rKF/BWSOS5jQ16+ftxxOamLOQJWUYtoduyM5elhohBbyLPFNzsCV7hcPHsZNes+PKJhyIHl6u6O0HIPE7sbCruVjYlkLGE1s8d2nRQuGpUKq39dhn6D3wITFVhC+Pc//cxIwGJJwNlRPnaTHdtdWNROHyYMsWNyhY/3FZcD63bmbWSphOfui+FfYN3qdZyoxI5Xshv79FotVNevQ/ffbqpTFy+iff/+yMnLw6effopvvvnGKB52PPD48eOcKMYEixYtWhi9z26ja9KkCX8Zg7UFrHfeeYcTaFiZMGECxo4dK9kjx8Zh1apVnD0mBj06toU7GjFiBJ/gneXhMhw9NNRhoqPYnVlPOrr6aLDF9cMEUbb7it1UKLYU/j18ki0mGM+fPx/u7pRgWixrai8NAVM+q6XpSRorCw/cwIRNF4yMDWlZEZ88J/73VxoPyQoRIAJEgAhIQUDMOlSK/smGbQiQgGUbzrLqhR152bJlC+eTIbeRVA6KmThM+VKcm5mB2YP7SOWuIuy8PX85vP2l/yuxOQIWE4bYjqEn3ZrGkkwzEYsVlnOKHasrXC6cuYxa9YwFLDcPT4REl+OrsWNyBgGH5deqU6fOY2OjVauRfPsmhrzzLjZs2YpG9evj8LFjnFjFChO9OnbsyP171KhR+Omnn8wa3+IErJsZN5GjfpgTKuF2Ajo/05nb0bVx40Y+H5IqIQHaBw+M+hw7ZQqmLFrE7WxigpShMJZspxgrTLAxCEePOsyOGLKcdaxYQ8BiO5zY7x3rnx1TZIJklSpVuB1gQUFBZvErrnLhOYfd5Ofp6Vlk9Y8++gjff/899z4T+NizV7iUpoDFRFr2nDCxj+ULk6IUJWCxOOfNm4f27dtL0Q3ZIAKSETDls1qyzkQaup2ai45T/0aeWstbqhDqw9066OnmItI6NScCRIAIEAE5ERCzDpVTHORL8QRIwLKjJ4Tl8mE7HYpbHLJF/ejRo7mo2a4R9kXUxUW6L3FiJg5TvhSTgCXdA2uOgMWOfxmem0c9YMmlDbuu2PPFxKPC5YkClqcXQqKEW/zGjBkDlhC7uNvvtBoNkm/dwKJlv+LTr8ZzO5eys7Lg7uHBdVd4BxHLFcUEH3NKcQLW9YzryFPnceZ+W/gbvvn4G24HV2ZmJvf7o1OrUXD58mPdbf37b/T475Y6tmuI5XVi5dtvv+V2ZbFy4sQJ1K9f/4muqtVq7oglO+YohYBVHA8mTjLxkR2lNBwlNIdfcXXbtm2L3bt3c1WY8GcQHZ/U5osvvuB2gLHChM3mzZsbVWPHQFUqlSjXCh9dLcqQoR+224/t2Dt48CB3xJQ970xUZJykuBWQJcs35GtjRwjZxRrsCCW7MZb5yVgMHDhQVLzUmAhIScCUz2op+7PUFhPk+yw4gkNxqUYmVr3VBI0r0oUIlnKldkSACBABuRIQsw6Va0zk1+MESMCyo6eC/cWe7ajo0aMHt+irVKkSt8Bir7FcLexIFVuEscKOo7DcRe3atZOUgJiJw5QvxSRgSTdc5ghY7Flh+ZmeVNgC3yCCjh8/Hp9//rlRtfOnL6P2U8Y7sNy9vBEc+fBGP1Zat24N5o+55W5CAsr+l7eJ3dx34MABi5N/FydgxaXHIV+Tz7k3duRYrF/5MA+SOYXtajLsumIXJ7B8Yez3MDc3t1gRuU2bNtxOSWsLWFFRUVxycnbbpNRFyh1YUvtmjj2WUJ3t8mM76OrWrcvNp1KIWE/ygV2cwLgxUeurr74CE/aoEAE5EDDls1oOfq47eQejVxtfstGvSXlM6FpbDu6RD0SACBABIiAxATHrUIldIXNWJEAClhXh2tq0qUdroqOjwW4Fs8bRFDEThylfiknAku6pMkfAKumoqeFo4ZNyCz1JwPLw9kFQ2YcJw1mpVasWLlwwzlFiSqRXr1xB5SpVuKosHxHLmdS4cWMcPnzYlOZGdYoTsK4+uAqV9uGun7dffRv7d+43235hhuzIJTt6yW5tZMnTiyuvvvoqVq5cKYmAxZLks9skWWG7E+7fv8/tcmK58FjyfJZAnl3ywMRAKYuUObCk9MsSW+yiAJZYnxV2AQZLtm+tYjhOyXassSTyLHE8FSJQ2gRM+awubR+zCzRo8+NeJGUJN7xGBnhi23st4Of58DIOKkSACBABImBfBMSsQ+2LhH1HQwKWHY3v5cuXuV1VbFcAu9GN3RLHjr6wRNXsKAq7+euFF15Ar169uONP1ihiJg5TvhRTEnfpRs1WAta5U5dR52njHViePr4ILFOWD4YtzNnzy26/Y7uAnlSY4JJ657bRW41btILXf7fUWVPAupx2GRqdhut7SK8hOLjnIJeInIlSrKjv34c2q+jLBZxcXFCtTRt+t45BwCpbtiyX+L64IqWAxW5KfNJON3YjI7sRke3WZLc+sp/ZTZBSFSlvIbTVEcLiYq9atSp3/JrlC2P+WKuwSw3Y5QassEsADMdOrdUf2SUCphAw5bPaFDvWrDPpr0uYvffhLZ6GsuD1hmhXM8Ka3ZJtIkAEiAARKEUCYtahpeg2dW0mARKwzARG1YsnIGbiUMKXYnsaf5sJWP9eQp36D297MtxC6Onrh8CIMjxOww2E7NgrE1+fVJiAlXjd+L2Q6Bi4/ZcDy5pHCC+mXoROr+Pc+mjoR9j8+2ZutxLLX8SOTxbExUGX9zBHFiuuISHQpBrnXfGoVAnOXl7c+wZRytZHCIsSsJhPM2bM4G8kZTcQGvJQSfHMsx2fhjxO7OhkUbdDsr5YHjQmCrF8YU+6bdDUnabF+W3KLYTFtTc8r2z82BE/axU2JzKxjJW33noLc+fOtVZXZJcImExA7p/Vt1Jz0H7K31BpH87ZrLSsGobFbzR64kUkJgdOFYkAESACREDWBMSsQ2UdGDlnRIAELHogJCUgZuKQ+5diSUHJwJitBKyzJy+hbgNjAcvLzx8B4cJfwtlNfDNnzuQWF2xHEjta96TCBCwmZBkKu8mQ3WjIyrvvvssdhWPFkiTuLM8QO0bISuE+2M8XUi5Aj4f9Lpq5CJPHTeb+zY4qsrxW+RcvAjphseQeGwv13bvQF0o27hYRAdewMK4dO3b22Wefcf8uLom7RqPhdk+y3EtS5MAqTsBiCeOZeMQSivv4+HAM2S4zKQoTpJhtVoYOHcolQ39SYUca2a40VpjIt2LFiseqyUHAMvgQHBzM7XK1Vin8O8ouUWCXKVAhAqVNQO6f1YOXHseOC4k8JldnJ/w1qgUqh/uWNjrqnwgQASJABKxIQMw61IpukWmJCZCAJTFQRzcnZuKQ+5diextbWwlYZ05cQr2GxgKWt38A/MPCeaTbt2/nkmOz8vHHH3O39D2pJN6IAztGaijBUdFw93y4q2nnzp18XjcmZk2dOtWsIZs0aRLXNyv5+fncDitW2M4rtgPLUG5cu4GX/vcSJ3KxnUTLlyxBwSPHyDyqVYMmKRnaB2l8Oxf/ALjHlON+Pnr0KJerixV2e+K0adOe6OuaNWu4I7+sWFvAYn3MmzcPQ4YM4fpjx9XYsTWpCssbxfJHMdEnPj7+iceYv/vuOy6vFCurV69Gz549pepeMjssgbshGX9xgqAUHQ4fPpy77ZAVlrtswIABUpglG0RAFAE5f1bvv5qMfguPGsU3sHkFfP7Cw7x1VIgAESACRMB+CYhZh9ovFfuLjAQs+xvTUo1IzMQh5y/FpQrVSp3bTsC6iHoNHy4eDEcIvQMC4R/6cDeSoTBBhwk77Ege23ljEG4K10m6eR06rRYXL19G/J0E9O7XD+xGQ0NhScrZjiaW9JrdulnUUTW2a4blgWP54Qxl6dKl6N+/P/cjS5htSNTNcl+xHFiFy7hh47B2zVrupR8mTsTwF1/k33ZydoFHjerQpqVBfe8ebt65g6NnzqB3jx5gxwgNpUGDBjh58iTc3Nywe/du7ubQwoUld2/SpAlu336Y98sWApZKpULFihWRkJCAgIAA7ggf+78UpfAxQibMsCOLhUtcXBzq16+PzMxMVK5cmRO7XF1dpejaJBvs2WP9MR+KKowLu/yC+cbKwoUL8eabbz5Wnd3kuG/fPu51tqON7dgqXNgxSnarZ3FsmYDHbqvUarVcvevXr3PiHxUiUNoE5PpZrdbq0HnaflxNyuYRhfi4Y/cHrRDgRYnbS/u5of6JABEgAtYmIGYdam3fyL50BEjAko4lWQIgZuKQ65diex1YmwlYxy+iXiNjAcsnMAh+IcbH05iAwXa2pKU93LX04osv4pVXXuESZTNRKykpCQf27MK2Hbtw4tQpDB34JqZOnw52o6GhMGGB2cjOfriA6d69OydiMVGGCQEsvxbb7bV27VouUXlhYYG9x/pipUOHDtwRP3acjQlYNzNuIjImkhdUwhCGpo2bcqICK80bNMBrL72EmpUqwdPfH1leXvj36FH8tXEj9h49ipfatsVv06fDs9AtckeOHOFEK3ZM0NPTE++99x4narCdX+w9dswwJSWFE9JOnz5tEwGLxcJ2rjFfWBk/fjw+//xzSX4FGH+2Y4ldMsFKjx49MHjwYAQFBXHCJcu5xcaYiY+bNm3Cc889J0m/phpZvHgx3njjDS6ZPXv22KUXYf8d+WTCFUvYz3ZBsdsaWWnXrh13kyTz99FSkoDF3mdCa9euXdGiRQvueCUTqVhONXaZAXs+t2zZwpllx2pZvwZx1dR4qB4RsBYBuX5WLzp4A19tNL7N9rvuddD7mRhroSC7RIAIEAEiICMCYtahMgqDXCmBAAlY9IhISkDMxCHXL8WSApKRMZsJWMcuot4zxgKWb1AwfINDHqPBciUxYYOJSyWVMe++g/HffAN2o2HhwoSBbt26ccfUiitP2hnDBDO28+VJZduJbYiKieLeqhFSA0mJSdwusf3795fkKvp17Yq5EybAs2ZNOBUSPNhOHHYsjO18erSw3UDs+BgTfJYsWWIzASs3N5fri4lnISEhXC4sX19pcscwm0ykY8fwnlSYeMd2Zg0aNKhEplJXMAhYpthlY8ZythV1m6spApZhh1Zx/TFxj/FgO7GoEAG5EJDjZ3VGnhotvt8D9n9DqRXpjw0jmsPF2Uku6MgPIkAEiAARsCIBMetQK7pFpiUmQAKWxEAd3ZyYiUOOX4rteTxtJWCdPnYBTz1Ti0NpOELIxCsmYj2psJ06TET6/fffOaEjOTmZ2z3FxJSKseXRqH59PNe+PerWrsXdZMhuNHy05OXlYcGCBVi/fj0nhrFdXWyXU4UKFdC0aVNuZ1ebNm0ea8cSmbMdSGwHDNsJk5WVBd1/ObcKC1g1Q2ryt1mtX7AAq9avx5HTp5GYmgq1RoPAwEBUqVwZjapWxfOtWqF5w4ZcXx5VqsD5v9xahs4vXLgAlvtp165dnGjEdv2wW+5Y0m52rJKJJbYUsJhfhZPMf//99xgzZoxkvwpsx9n8+fO5Y6JsxxzbdRQZGYm2bdtyifhr1Xr4rNi6sGeG7c5jxznZ0U52mUBiYiLYM8F2R7FjjWxc+vXrh7p16xbrXkkCFjsWynaZHThwAJcuXeL6Yc85u9WQJc6vU6cOOnXqxAlXTMSiQgTkRECOn9U/bruMGXuMb6ldM7QpGsXSsVs5PTvkCxEgAkTAmgTErEOt6RfZlpYACVjS8nR4a2ImDjl+KXb4AZUAwIP7OVDlpkCvF3YZ+YWEwScw0GzrKfG3oVEV8O3YTYbsRkNrlhx1DneE0FCcnZy5HVissETuT7qB0OW/HUv5Fy5Cr9PybdnthIb3rOkz2SYCRIAIWIuA3D6rk7MK0PKHPchVCXNt5zplMKtPA2shILtEgAgQASIgQwJi1qEyDIdcKoIACVj0aEhKQMzEIbcvxZKCcWBjafdyoMpLAQoJWP6h4fC2IDl46p14qAvyBQErLAJe/tYVsLJV2biVeYvv09XZFdWCq3E/61SqJ95A6Oz2MGFwwbVr0OUL/rpFRcGVdtQ48G8DhU4ElE9Abp/VX208j0UHC/+RAdj+XktUDpfm6LPyR4wiIAJEgAg4BgEx61DHIGQfUZKAZR/jKJsoxEwccvtSLBuoCnck7W4OVPnJgF7ITRJgofCUlnAHqvw8noh/WDi8/aW5Ja8ozJkFmYjPEvJpubu4o0rQw2Tv2qwsqG4J4pbhBkKWeJsV9h6rYyiuYeFwiwhX+IiS+0SACDgyATl9Viek56H1D3uh0ur4IXm5QTR+7FnPkYeIYicCRIAIOCQBMetQhwSm0KBJwFLowMnVbTETh5y+FMuVrxL9Sk3IhrqACVga3v2A8DLw8ns8d1VJ8aXdvQNVniBg+YWGwSfA/KOIJfVT+P30/HQkZCfwL3m4eqByYGXuZ01KCtT37/PvOXt5w6NSRf5n9d270Px3qyJ70SUwCO7RDxPBUyECRIAIKJGAnD6rP/79DFYeE/7A4ObihN3vt0K5YG8loiWfiQARIAJEQAQBMetQEd1SUxsTIAHLxsDtvTsxE4ecvhTb+zjZMr6HAlYSoBfykwRGlIWnBTfbPbiXgILcXN59v5BQ+ARaN8l1Wn4a7mXf4/v0cvNCxYCHIpX63j1oUlP591wCA+EeHc3/rElOhjoxkf/Z2ccHHhUq2BK/JH2xGxtZsnVzC0tAHhVFgp253Kg+EZAzAbl8Vl9Pzkb7n/6GVqfncfVvWh5fdaktZ3zkGxEgAkSACFiJgJh1qJVcIrNWIEAClhWgOrJJMROHXL4UO/L4WSP2lDtZ0KjYDixBwAoqGwkPbx+zu3tw/y4KCgkpxd1maLbxIhqk5KUgMUcQoXzcfBAbEMvVVsXHQ5uRwbd0DQ2FW5ky/M/sPVbHUJzc3eFZtapUrtnMTuFb9czptH///li8eLE5TaguESACMicgl8/qkb/9i42n7/K0PN2c8feHrRHu5ylzguQeESACRIAIWIOAmHWoNfwhm9YhQAKWdbg6rFUxE4dcvhQ77OBZKfDk+CxoVUks5TnfQ1DZKHh4m3/EIz3xHvKzs3k7vkHBYCKWNUtSbhKSc5P5Lvzc/RDjH8P9XHD9OnSFdoS5lS0L1xDBH21uLlTXrwvuOTnBs2ZNGHJkWdNvKW2TgCUlTbJFBJRNQA6f1RfuZqLz9P1GIN9uVQkfdaqubLjkPREgAkSACFhMQMw61OJOqaHNCZCAZXPk9t2hmIlDDl+K7Xt0Sie65NtZ0KrZDibhmEdwZDTcvbzMdigj6T7yCiVFZ8cH2TFCa5b7OfeRmiccEwzwCEC038NjgvlXrkCvUvHdu5crB5dCtyvq1GoUXL5s5J5ntWpw+u+WQmv6TbaJABEgAtYgIIfP6iHLjmPbeWFnrJ+HK/Z/1BqB3u7WCJlsEgEiQASIgAIIiFmHKiA8cvE/AiRg0aMgKQExE4ccvhRLCoOMcQSSbmdB94iAFRJVDm6e5h/zyEhKRF5WJk/WOyAQ/qFhViXN8l+xPFiGEuQZhEjfSOj1euRfuADoBWHOvWJFuBTaWfakOh4VK8LZgt1nVg2SjBMBIkAETCRQ2p/VVxOzuNxXhcv77atiZNuHt8NSIQJEgAgQAcckIGYd6pjElBk1CVjKHDfZei1m4ijtL8Wyhapgx5iAw3Zg6TTCX8pZOCHRMXDz8DA7sszkJORmCjmnvP0D4B8WbrYdcxokZCUgvSCdbxLiFYIyPmWg12iQf+mSkSmPqlXh7G68A6CkXVrm+EJ1iQARIAKlTaC0P6tHrzqFdf8KN8P6e7ri4Mdt4OfpVtpoqH8iQASIABEoRQJi1qGl6DZ1bSYBErDMBEbViycgZuIo7S/FNLbSE3goYGVCp2E5sIQSWq48XB8RekzpPTMlGbkZgpjk5eePgPAIU5paXCc+Kx6ZBcKurzDvMIR7h0OXn4+Ca9eM7HL5rZydjV4ruHEDukKJ590iysA1zLrHHi0OlhoSASJABEogUJqf1fFpuWj1416jmwffaVMZoztUo3EjAkSACBABBycgZh3q4OgUFT4JWIoaLvk7K2biKM0vxfInq0wPdTo9UuIfF7DCYmLhYkEeqKzUFOSkP+BhePn5ISBcuPXPGpRuZd5CtkpIHB/hE4FQr1Bos7OhunmT79LJxQWeNWo85oLqzh1o0wXRzTU4BG6RZa3hKtkkAkSACFidQGl+Vn/x5zks/eeW8Bng5sLtvgr2odxXVh946oAIEAEiIHMCYtahMg+N3CtEgAQsehwkJSBm4ijNL8WSQiBjPAGdVvdQwNIKt/ixN8NiK8DFxdVsUtlpqch+IOSj8vT1RWCEdcWgGxk3kKvO5X0t61MWwV7B0Dx4AHWCcIzF2dMTHpUrPxaTOjERmmQhfhc/P7iXL2927NSACBABIiAHAqX1WZ2cVYDmk3ajQCPcaPtGs1h8+WItOWAhH4gAESACRKCUCYhZh5ay69S9GQRIwDIDFlUtmYCYiSMuLg4qlQpOTk6oxm5qc3IquUOqIWsCWo0OqXcyoNOmGPkZHlsRzi4uZvvOxCsmYhmKh48PgspEmm3HnAZx6XHI1+TzTaJ8oxDoGQh1cjI0iUJuL2dfX3jExj5mWpOWBvXdu/zrRQld5vhEdYkAESACpUGAHQu/fPkyd4mFh4cHKlasaDM3Jv11CbP3xvH9ubk4Yd+Y1ogMNP9GW5s5TR0RASJABIiAzQiIWYfazEnqSDQBErBEIyQDhQmImTji4+ORnf3wqFaFChXgacEtdTQa8iLABKyUOxnQPyJgRVSsBCcn41xRpnjOjg+yY4SG4uHtjaCyUaY0tbjO1QdXodKq+Pbl/MrB38OfE6WYOGUoLkFBcI963BdTjxpa7CA1JAJEgAjYiEBOTg5u377N9ebn54fo6Gib9JyRp0az73Yju0DD99erYTS+f7meTfqnTogAESACRED+BMSsQ+UfHXloIEACFj0LkhIQM3GkpaUh8b8dLSEhIQgPt+7tcpIGTsaeSECj1iI1gQlYwq4pVjGiYmWLdtjlZKQjK0U4jufu5YXgSOsuoC6nXYZGJyyayvuXh6+7L1S3b0ObKSR3dw0Lg1vE4wnlTU32To8QESACREDOBNiuK/YZb/hDU1RUFPz9/W3i8sw91/DDtst8X2yD9q7RLVExzNcm/VMnRIAIEAEiIH8CYtah8o+OPCQBi54BqxAQM3Gw44PsGKGhMAErMDAQLhYcNbNKcGTUbAIalRapd9Oh1wo7ldjRUCZgWVJyMzOQmSzcaOjm6YWQKOsKWBdTL0KnF3KuVAioAG83bxTExUGXl8eH4Va2LFxDQh4LS6/RIP/SJaPXPapVg7MFSewtYUZtiAARIAJiCDDhKjc3F+yPTAbxis3jVatWhfMjt66K6aeotnkqLZpN2o20HGEn7PN1ymJmn/rW6I5sEgEiQASIgEIJiFmHKjRkh3SbdmA55LBbL2ixE0dKSgqSCyW8Zp4yAYvyYVlvzKxpWa/TQ12ggV6v5rthfzl39/K2qFudRgO1SljEsMWTm5WPmha+gZA5zcQrZydn6HJyAL1eiMvTE06uT05Mr/vvaKyhsrO3N2CDhZ9FkKkRESACRKAQAa1Wy+W8MhT2ecx2X7EjhLYoyw7fwufrzxl1tWlkc9SOCrBF99QHESACRIAIKISA2HWoQsJ0eDdJwHL4R0BaAGInDvYl+d69e8jIyJDWMbJWKgRYDqycjFxAJ9zi5+TsDL+QUIv8UefnIy9LOLbn7OoK36Bgi2yZ0oh7HnPuGVUN9w6Hq5ML1PeMX3cNDYWT+5Ovclffvw/ohF1cLiEhcPbwMMUFqkMEiAARkA0BW4tXOp0e7X/ah7jkHJ5Bi6phWPrmM7JhQo4QASJABIiAPAiIXYfKIwryoiQCJGCVRIjeN4uAVBNHfn4+0tPTuWML7K+/VJRJoCBXjXtx96HXCLf1ubq7o1ytuhYFxJK4J90odAuVpyeia9S2yJYpjdQ6NQ7fO2xUtUnZJnDVAjn//GP0uk/jxnAqQpTKPX4culxBxPOsXh2ulOPNlCGgOkSACJQyAbYL2t3dnct35evra5Njg4aQ911JHWPjnQAAIABJREFURv9fjhoRWDbwGTxbJayUqVD3RIAIEAEiIDcCUq1D5RYX+WNMgAQseiIkJUATh6Q4FW/s9oVUrP9xLdQ5G/lY2K2Bb06da1FscSeOYP33E/i2AeERGPTzQotsmdIoPisendd1Nqp6tM9ROF27hRtduwmvOzmh+pnTcCoir9Wtfq8j99gxvn7Ep58g+PXXTXGB6hABIkAEHJbAgEVHsfeycHFHlXBfbH+vBaUVcNgnggInAkSACBRNgNahjvF0kIDlGONssyhp4rAZakV0dON0MjZOWw11zlbe37CYWLz+wwyL/L95+iR+n/gF35YdHxwyZ6lFtkxpxG4gfHnjy3xVJzjh9OunkbN/P+LfGsK/7hIaiqoH9hdp8s67o5C1bRv/fsjQIQgfNcoUF6gOESACRMAhCcQlZ6Pt5H1GsX/TrTb6NC7vkDwoaCJABIgAESieAK1DHeMJIQHLMcbZZlHSxGEz1Iro6NqJJGyesRKa3O28v2UqVUGfiT9Z5H/8+TNYPf5Tvq2nnz+GL1hhkS1TGp1KOoV+W/vxVb1dvXGkzxGkr12Le2M/51/3qFkDFdetK9Lk/fHj8WDFb/z7gb16oez4r0xxgeoQASJABBySwBd/nsPSf27xsQd4ueHwJ23h5e7ikDwoaCJABIgAESABi54BgAQsegokJUAClqQ4FW/s8uF7+GsuE7B28bFEVa+F3l9Nsii2u1cu4rfPx/Bt3b28MHLxGotsmdLo0N1DGLJD2GkV6hWKPb32IHnWLKRM/5k34duyJcrNnVOkyeSfZyBl5kyhfru2KDfDsl1opvhNdYgAESACSiaQkadG0293IVcl5MAc0rIiPnmuhpLDIt+JABEgAkTAigRoHWpFuDIyTQKWjAbDHlyhicMeRlG6GM7vT8DOhSugyROOgcTUeQo9x35tUSeJ16/h10+Eo3curq4YtXy9RbZMabTr1i6M2iv0F+MXg83dN+PeuHFIX7mKNxHYsyfKThhfpMm05cuROEGI2at+fcSuWG6KC1SHCBABIuBwBBbsv46vN1/k43ZxdsLfH7ZGVKCXw7GggIkAESACRMA0ArQONY2T0muRgKX0EZSZ/zRxyGxAStmdM3vuYM+SX6HJO8B7UrF+I3T76EuLPEu5fRNLxowwajt65UarJfTdGLcRnx4QjixWD66ONS+uQfyw4cjevZv3I3T4cISNNParsJOZW7ci4b3R/EvusbGo9JeQF8wiGNSICBABImCHBLQ6PVr+sAd3HuTx0XWuUwaz+jSww2gpJCJABIgAEZCKAK1DpSIpbzskYMl7fBTnHU0cihsyqzr87/bb2Ld8KbT5h/l+qjT+H14aLYhC5jjw4F4CfhklHOljbUct/wMurm7mmDG57qpLq/D1EWHnVP3w+ljy3BLceLkn8s+d4+2UGTcOQb1fKdJuzuEjuD1gAP++c0AAqh0RmJjsEFUkAkSACNg5gW3n72PIshNGUa4d2hQNY4PtPHIKjwgQASJABMQQoHWoGHrKaUsClnLGShGe0sShiGGymZPHt9zAgVVMwDrG91mjeSt0HvmBRT5kJidh/og3jdqOXLIG7p7WOVay+NxiTD4xme+vWWQzzGk/B9fatIX67l3+9eiZM+DXtm2RMeVfuYIbL3Uxer/62TNwcrOO8GYRXGpEBIgAEZABgd7z/sHh62m8J3WiArBhRDOr7bSVQcjkAhEgAkSACEhAgNahEkBUgAkSsBQwSEpykSYOJY2W9X09suE6/lm7GNqCk3xntVt3QMeh71jUeU76A8wZItwKyIwMW7ACXn7+FtkrqdGsU7Mw+/Rsvlr78u0xpdUUXHq6PvR5wvGW8iuWw7t+/SLNaVJScLX5s0bvV9n/N1zDwkpygd4nAkSACDgMgWtJWWg35W+jeKf0qofu9aMdhgEFSgSIABEgApYRoHWoZdyU1ooELKWNmMz9pYlD5gNkY/cO/n4Nx9b/Aq3qDN9zvQ7Po93Aty3yJC87C7MGvmrUdsjsJfANDrHIXkmNfjz2I5ZcWMJXe6nSS5jQYCwuP20sVlXcugUeFSoUaU6v0eBS7TpG71f48094Vqtakgv0PhEgAkTAYQiM33gBvxy8wccb6uuOgx+3gYeri8MwoECJABEgAkTAMgK0DrWMm9JakYCltBGTub80cch8gGzs3t+rruDkpoXQqs7zPTd4vitavT7IIk/U+fmY3v9lo7aDfl6IgPAIi+yV1Gj8P+Ox5soavlrvar3xYcwb3BHCwqXq4X/gEhhYrLkrjZtAm5HB14lZvAg+TZqU5AK9TwSIABFwCAL5ai0aT9yFjDw1H+/QlpXw8XPVHSJ+CpIIEAEiQATEEaB1qDh+SmlNApZSRkohftLEoZCBspGbe369hFN/zYdOfZnv8ZmuPfHsq/0t8kCr0WBqn65Gbd/4aQ6CI61zvOTj/R9j8/XNfH9v1n4TQz074GaPQiKaiwu4fFbOzsXGFPdcZ6huCDsLoqZMhn/nzhZxoEZEgAgQAXsjsO7kHYxefdoorH1jWqF8iI+9hUrxEAEiQASIgBUI0DrUClBlaJIELBkOipJdoolDyaMnve87F13A2V3zoFNf443/r2cfNH3Z+BigqT3r9XpMefUlQK/nm7z+wwyExcSaasKseu/ufhe743fzbYY/NRx9M2sjfvBg/jWXkBBUPXigRLs3+/RF3gnhZq2IsWMR3LdPie2oAhEgAkTAEQj0nHMIx24+4EN9tkoolg1s7AihU4xEgAgQASIgAQFah0oAUQEmSMBSwCApyUWaOJQ0Wtb3ddv8c7iwdy50GmHn0bOvDcAzXYyPAZrjybS+3aFRq/gmfSb+hDKVqphjwuS6g7cPxuF7h/n6YxqOQZfrQbg75kP+NY8qlVFx48YSbd4ZORJZO3by9UKHvY2wdyxLZl9iZ1SBCBABIqAgAlcSs9DhJ+Pk7bP61EfnOmUVFAW5SgSIABEgAqVJgNahpUnfdn2TgGU71g7RE00cDjHMJge5edYZXDk4BzrNbb5N6/6DUb9zF5NtPFrx5wG9oMrL5V/uPf4HRFWrYbG94hr22dIHZ5KFBPRfNv0Sbf7JQeK33/HNvBs1QvllS0vs/94XXyJ99Wq+XmDvV1B23LgS21EFIkAEiIC9Exi34TwWH7rJhxnq64F/PmkDN5fij2bbOxeKjwgQASJABEwnQOtQ01kpuSYJWEoePRn6ThOHDAelFF3aMP0Urh2eBb32Lu9Fu0HDUa/9cxZ7NWtwH+RlCsnQe34+ETG161psr7iG3f7shmvpwvHHSc9OQsMNV5A6Zy7fzK9jR0RPm1pi/0lTpxq369AB0dOnldiOKhABIkAE7JkAS97+zDc7kZmv4cMc1qoSPuxEydvtedwpNiJABIiA1ARoHSo1UXnaIwFLnuOiWK9o4lDs0FnF8T8mn8SNEzOh1yby9ju+PQq1W7WzuL+5b/dHdloq3777J1+hwlMNLLZXXMNOv3dCQnYCX+XnNj+j2vw9Fu2kSlu6DIkTJ/K2vBs2RPlfl1nFbzJKBIgAEVAKgd9P3MH7a4yTt/89pjViQryVEgL5SQSIABEgAjIgQOtQGQyCDVwgAcsGkB2pC5o4HGm0S4517aTjuH3qZ+h1guD0/DtjUL1Zy5IbF1FjwTuDkJF4n3+3y5jPUbmhdRL9tlzVEmn5aXxfCzssROTEX5G1Ywf/mqm5rDI2bcbdDz7g27lXqoRKmzdZzIEaEgEiQATsgUCP2Ydw4hYlb7eHsaQYiAARIAKlSYDWoaVJ33Z9k4BlO9YO0RNNHA4xzCYHufLro7h7fjr0unS+zUvvf4oqz/zPZBuPVlz03lCk3b3Dv/zCqI9RrWlzi+0V17DRr42Qr83nq6zovAJ+701C3vFCtwl+9hmC+/Utsf+cQ4dw+82BfD2XoCBU/edQie2oAhEgAkTAXglcvp+FjlONk7fP6VsfnWpT8nZ7HXOKiwgQASJgLQK0DrUWWXnZJQFLXuOheG9o4lD8EEoawIpxh3Hv0jRAn8Xb7f7xOFR4uqHF/Sz9cCSSbwm3GnYe8T5qPNvaYntFNdTqtHhq2VNGb6/vsh7o8y5UcXH865E//oiAF54vsf/8S5dwo2s3oZ6TE6qfOwsnF5cS21IFIkAEiIA9Eng0eXuYnwcOfUzJ2+1xrCkmIkAEiIC1CdA61NqE5WGfBCx5jIPdeEETh90MpSSBLP3sEJLjfgL0eby9np9/g5ja9Sy2v/yz0bh/7QrfvsPQd1CndQeL7RXVMFuVjaa/NTV6e3uP7chq3wPaB8Jxl5hfFsLnfyXvKFMnJuFaS+Ojk1UOHYRrcLDkvpNBIkAEiIDcCRRotGg8cRfSc9W8q8NbV8KYjpS8Xe5jR/4RASJABORIgNahchwV6X0iAUt6pg5tkSYOhx7+x4Jf9NEBpN2cAkDFv9d7/A+IqlbDYlArv/wQCZcu8O3bDRqGeu07W2yvqIZJuUlou6at0dv7e+7DvYbPAjod/3qFP9bBs0bJ8ehVKlyqayzcVdy0ER6VK0vuOxkkAkSACMidwF/n7mHoryeN3Nw3phXKh/jI3XXyjwgQASJABGRIgNahMhwUK7hEApYVoDqySZo4HHn0H499wei/kZEwGYCWf7Pvt1MRUdFy0WbNhM9w+5xwY1Xr/oNRv3MXycHfyryFF/54wcjused34UZz411UlffthVtEhEn9X270DHRZwnHKmKVL4PPMMya1pUpEgAgQAXsiMGjJMey8mMSH9ExsMFYPNd71ak/xUixEgAgQASJgXQK0DrUuX7lYJwFLLiNhJ37QxGEnAylRGHNG7EFOMhOwhNL/x5kILVfe4h7WffslbpwSkqg/+9oAPNPlZYvtFdXwYupF9NrUi3/b1ckVh5v/juudjfNdVTtzGs7u7ib1f61jR6hv3ebrRk2bBv+O0h9/NMkZqkQEiAARKCUCyVkFaPLtLmh1et6D73vURa9G5UrJI+qWCBABIkAElE6A1qFKH0HT/CcByzROVMtEAjRxmAjKAarp9XrMensH8h9MN4p24LT5CCxj+Q1Tf/74Na4dO8zbbNarL5r06C050ROJJzDgrwG8XT93P+ysMh23+vbjX3P28UG1E8dN7vtGz17IP3uWr19mwngE9expcnuqSASIABGwBwIL9l/H15sv8qF4ubng2Nh28PVwtYfwKAYiQASIABEoBQK0Di0F6KXQJQlYpQDdnrukicOeR9e82LRaHWa//RcKMmYZNXxr1mL4hYSaZ6xQ7Y1TJ+HKP/v5V5p0fwXNXhFEJYsNP9Jw/539GLZrGP9qhHcE1gV+hISR7/CvuUVHo/LOHSZ3eXvQYOQcOMDXD//gfYQMGmRye6pIBIgAEVA6AfbHjeem7cel+4Vup306ClNeMb71Velxkv9EgAgQASJgWwK0DrUt79LqjQSs0iJvp/3SxGGnA2tBWKp8Dea9sxUFGXONWr89fzm8/QMssPiwydYZk3Fh/x6+faOXeqBFnzcstldUw203t+GDfR/wb1cIqIAlBX1x/8sv+dc869ZFhdWrTO474f0PkLl5M18/ZPBghL8/2uT2VJEIEAEioHQC5xIy8MLPgpDP4lkxqDH+V9nyP2wonQn5TwSIABEgAuIJ0DpUPEMlWCABSwmjpCAfaeJQ0GBZ2dW8bBUWvrcFBZkLjHoauXg13L28Le59+9zpOLt7O9++/nMvofWAtyy2V1TD9dfW4/ODn/Nv1wqphRl3WiN56lT+NZ+WLRAz11igK86R++PH48GK3/gqgb16oez4ryT3nQwSASJABORKYNyG81h86CbvXlSgF/Z/2BrOzk5ydZn8IgJEgAgQAQUQoHWoAgZJAhdJwJIAIpkQCNDEQU+DgUD2g3ws+nAzVJmLjKCMWr4eLq6W5znZuXA2Tm8XdjHVa/8c2g0aLjn4FRdX4Nuj3/J2G0Y0xHf/VkXakqX8awFduyLyO6FOSU4kTZuG1Nlz+Gp+HTsiepogiJXUnt4nAkSACCiZgEqjQ+OJO/EgV82HMbJNZbzfoZqSwyLfiQARIAJEQAYEaB0qg0GwgQskYNkAsiN1QROHI4128bGmJ+Vi2acbocpaJlR0csLo3zbAycnyv7TvXTofJzb/ydus3bo9Og59V3LwC84uwLST03i7LaJb4NNtPsjcsJF/LfiNNxDx0Ycm9526aDGSJk3i63s3bYLyi4wFPpONUUUiQASIgMII/HXuPob+Ktwiy9zf+0ErxIb6KCwScpcIEAEiQATkRoDWoXIbEev4QwKWdbg6rFWaOBx26B8LPPVuNlZ8sQGqrBX8e67u7nh32TpRkP5esRjH/lzL26jRvBU6jxRyVYkyXqjx9JPTMf/sfP6VTrGdMHJZulES9rD3RyN08GCTu0xf9wfuffopX9+jZg1UXCeOh8mdU0UiQASIQCkTGLTkOHZeTOS9aBQbhDVD/1fKXlH3RIAIEAEiYA8EaB1qD6NYcgwkYJXMiGqYQYAmDjNg2XnVpFuZWDV+PVTZqwXBxscHI34xPen5kxAdXL0ch38X8khVbdIcL773seQ0Jx2dhF8v/srb7V6lOwZMPo/88+f518p+PQGBL79sct9Zu3bhzvARfH23qChU3rXT5PZUkQgQASKgVAIp2QVoMnEXNDo9H8KkHnXwSqMYpYZEfhMBIkAEiICMCNA6VEaDYUVXSMCyIlxHNE0ThyOO+pNjvheXgTUTf4c6W9hh5BMUjKFzhBxSltA68sdqHFgp2KjUsDG6jhGSrVti80ltxh0ah9+v/s6/1bdGX3T/eBs0d+/xr0XPmgm/Nm1M7jL3+HHc6tuPr+/s64tqx4+Z3J4qEgEiQASUSmDxwRsYt/EC776nmzOOfdYOfp5uSg2J/CYCRIAIEAEZEaB1qIwGw4qukIBlRbiOaJomDkcc9SfHfOdSGtZ9vxbqnA18hYCIMhg03fhWQnOJHdu4Dn//+gvfLPapBujxifQ3+X2470NsvbmV72dwncHoMHAx9Hl5/GvlV6yAd/2nTQ6h4OpVXH/xJaP61c+dhZOIpPYmd04ViQARIAKlSKDrzIM4FZ/Oe9DlqUhM6236/FmKrlPXRIAIEAEioAACtA5VwCBJ4CIJWBJAJBMCAZo46GkwELh5NgUbfloNdc4WHkpIdAwGTJ4lCtLJrRuxZ/Fc3ka5WnXR64uJomw+qfGIXSOw784+/q33ag1D077TjapW+msr3GNjTe5bnZiEay1bGtWv8s8huAYFmWyDKhIBIkAElEbgVmoOWv6w18jtRQMaoXX1cKWFQv4SASJABIiATAnQOlSmAyOxWyRgSQzU0c3RxOHoT4AQ//V/k7Fx+m/Q5G7nX4yoWAV9v/1JFKTTO7Zi54KZvI3IqjXw6oQfRNl8UuM3t72JY/eF432fV3gbdd762ahq1SOH4RIQYHLfuvx8XH7KeMdBxa1b4FGhgsk2qCIRIAJEQGkEpu+6iik7rvBuB/u448inbeHm4qy0UMhfIkAEiAARkCkBWofKdGAkdosELImBOro5mjgc/QkQ4r9y7D62zlwBTd5u/sWo6rXQ+6tJoiCd27sT22ZPlVQUe5JDvTf1xvlUIWH7pIihqDBqhlDVxQXc8T8nJ7PiuVTvKegLCvg2satWwqtePbNsUGUiQASIgFII6PV6tJ2yD9eTc3iX+zUpjwldayslBPKTCBABIkAEFECA1qEKGCQJXCQBSwKIZEIgQBMHPQ0GAhcP3cX2eb9Ck/c3D6V83afx8mcTREG6eGAvtvz8I28jNCYW/X8oJCyJsi40fvGPF3Ez8yb/wgz/txD+iXD80SUoCFX/OWR2b1dbtIQmKYlvV27eXPi2aGG2HWpABIgAEVACgXMJGXjh5wNGrv7+dlM0KB+sBPfJRyJABIgAEVAIAVqHKmSgRLpJApZIgNTcmABNHPREGAic+zsBuxYuhSb/IA9FihsDrxw5iI1TvuVtBpWNwptThZxYUo1Am9VtkJyXzJv7xXUgfCcI/bDcVywHlrmFJXFnydwNJfKH7xHw4ovmmqH6RIAIEAFFEPhm8wXM33+D9zU6yAv7P2xt9u5VRQRLThIBIkAEiECpEaB1aKmht2nHJGDZFLf9d0YTh/2PsakRnt4Vjz1LF0Obf4RvUq3ps3hh1EemmnhivbgTR7H++/H8e/5h4Rg8Q7iVUJTxQo0bL2+MXE0u/8py1etwmyz04/XUU4hd+ZvZ3d3s2xd5x0/w7SLGjkVw3z5m26EGRIAIEAG5E9Dq9Pjfd7uQmCkcmx7euhLGdKwud9fJPyJABIgAEVAYAVqHKmzALHSXBCwLwVGzJxOgiYOeDAOBE3/dxP4Vi6AtEMSaWi3bodOwUaIg3TpzCmu/Gcvb8AkMwtC5y0TZfLSxTq9DvaXGeanWpvWGbu6vfFXfli1Rbu4cs/uNHz4C2bt28e1CR45A2PDhZtuhBkSACBABuRM4FJeC1+YLf8Rg/m5/rwWqRvjJ3XXyjwgQASJABBRGgNahChswC90lActCcNSMBCx6BooncHTTDRxavQDagtN8xXrtO6PdoGGi0N25eA6rxn3M2/Dw8cGIX1aJsvlo4xx1DpqsaGL08vrbXaFavpZ/LaBLF0RO+s7sfu9+8iky/viDbxfc/3VEfPKJ2XaoAREgAkRA7gQ+WnsGq47H827WKOuPre8+K3e3yT8iQASIABFQIAESsBQ4aBa4TAKWBdCoSdEEaOKgp8NA4J8/4nBk3TxoVcJNfg2e74pWrw8SBen+tStY/tlo3oaruwfeXfa7KJuPNk7MSUS7te2MXt54viPyNmwWLTwlfjcJaYsXixbCJA2YjBEBIkAEJCZQoNGi4dc7kZWv4S1/8lx1DGlZSeKeyBwRIAJEgAgQAYDWoY7xFJCA5RjjbLMoaeKwGWrZd3RgzVUc+3MOdOrLvK+Nu72C5r37ifI9+dYNLP1wJG/DyckZ7/32p6QJga9nXEeX9V2M/Nx0uBly9+zjXwt79x2Evv222bGkzJmD5KnT+Ha+rVqh3JzZZtuhBkSACBABORP469x9DP1VOELu5AQc/KgNIgO95Ow2+UYEiAARIAIKJUDrUIUOnJluk4BlJjCqXjwBmjjoCTEQ2LfiMk5umQWdOo6H0qxXXzTp0VsUpLS7d7DovaFGNkYtXw8XV1dRdgs3PpdyDq9ufpV/ycPFA2u3VEPeyZP8axFffI7g114zu8+0FSuQOH4C386rfn3Erlhuth1qQASIABGQM4Fhy09gy9n7vIuNKwRj1ZCmcnaZfCMCRIAIEAEFE6B1qIIHzwzXScAyAxZVLZkATRwlM3KUGruWXsSZbTOg09ziQ27Z9000fLG7KASZyUmYP+JNIxsjl6yBu6d0f9U/cu8IBm0XjjoGewbjlyW+UF2/zvcbOflHBDz/vNmxZGzejLvvf8C3c69UCZU2bzLbDjUgAkSACMiVQHaBBg0m7ECBRse7OLFbHbzWOEauLpNfRIAIEAEioHACtA5V+ACa6D4JWCaComqmEaCJwzROjlBr+8LzOLd7OvSaBD7ctm++jac6mi/6FOaVk/4Ac4YYH0N8e/5yePsHSIZ11+1dGLVHuC0x2jca06ZkQZuayvdRbuEC+DZrZnaf2fsPIH7wYL6dS1goqu7fb7YdakAEiAARkCuB9f8mYNSqU7x7rs5OOD62HQK93eXqMvlFBIgAESACCidA61CFD6CJ7pOAZSIoqmYaAZo4TOPkCLW2zj2Li/umQq9N5MPtOPRd1G7dXlT4+dnZmDnQ+BjiW7MXwy84VJTdwo03xm3Epwc+5V+qFlgVEz67AmiEZMSxa9fCq3Yts/vMO3sWN3v24ts5ubmh2pnTkubwMtspakAEiAARkJDAoCXHsfOiMPe3rhaGRW88I2EPZIoIEAEiQASIgDEBWoc6xhNBApZjjLPNoqSJw2aoZd/RphmnceXgFOh1wq6l598Zg+rNWoryXa0qwPR+PYxsDJy+AIERZUTZLdx45aWV+ObIN/xLTfzrYfQnQjJi9kalnTvhHh1ldp+qW7cQ17GTUbtqJ0/A2dvbbFvUgAgQASIgNwIZeWo0+nonVFrh+ODknvXQo0G03Fwlf4gAESACRMCOCNA61I4Gs5hQSMByjHG2WZQ0cdgMtew7+nPqv4g78iP0ugze1y4fjEXlRk1E+a7X6TDl1ZeMbAyYPAsh0dLlVll4diGmnpzK99HZsyEGfHnYqM+qx4/BxdfX7Fi06em40sQ4kXHlvXvgVkY6Ac5sp6gBESACREAiAr+fuIP315zmrbm7OOPY2HYI8HKTqAcyQwSIABEgAkTgcQK0DnWMp4IELMcYZ5tFSROHzVDLvqN1P5zAjRPfA/oc3tcen3yF2KcaiPb9p9e6QqcVjvP1/W4aIipUEm3XYGD6yemYf3Y+b6+PUxN0mXhAsO/qiupnz1h07E+v1eJS7TqAXs/bq/DnenhWqyaZ/2SICBABIlBaBN5YdBR7Lifz3berEY4F/RuVljvULxEgAkSACDgIAVqHOsZAk4DlGONssyhp4rAZatl3tObbY7h9+jtAX8D7+sqX3yG6Zm3Rvk/v3xPq/DzezqsTfkBk1Rqi7RoMfHvkW6y4tIK3N0zVDK0m7+N/dgkJQdWDhQQtM3u+/Exj6DIz+VYxS5fA5xnKD2MmRqpOBIiAzAhk5KrR4Osd0OgEgX7qK0+h69PmH7eWWWjkDhEgAkSACMicAK1DZT5AErlHApZEIMnMQwI0cdCTYCDw2/gjuHt+IgAtD6XPN1NQpnJV0ZBmDnoN+VmCANTri4koV6uuaLsGA2MPjMWfcX/y9j7KbIYGMwUBy71SJVTavMni/q617wB1fDzfPurn6fBvLy65vcXOUEMiQASIgEQEVh+Lx4e/n+Gtubs648TYdvDzpOODEiEmM0SACBABIlAEAVqHOsajQQKWY4yzzaKkicMJ6kekAAAgAElEQVRmqGXf0bKxh5B0lQlYQun/wwyExsSK9n3u2/2RnSYkh5fqaKLBsdF7R2PHrR28nxMSm6HaL4KA5VW/PmJXLLc4jhs9Xkb++fN8+7JfT0Dgyy9bbI8aEgEiQATkQOD1X47i7yvC8cGOtSIwt19DObhGPhABIkAEiICdE6B1qJ0P8H/hkYDlGONssyhp4rAZatl3tPijvUi9+aORnwOnzUdgmbKifV/wziBkJN7n7UiRHL6wU0N2DMGhu4f4l6bcbIro3/bzP/u2bo1ys2dZHMftNwci55BgP3zMGIQMfNNie9SQCBABIlDaBNJyVGj0zU5oCx0fnP7q03ipXmRpu0b9EwEiQASIgAMQoHWoAwwyABKwHGOcbRYlTRw2Qy37jhaM3o6MhOlGfg6ZvQS+wSGifV/8/jCk3rnN23lh1Eeo1vRZ0XYNBvpu6YvTycItWrPON0Lohn94+wHduiHyW+PdZeZ0njB6NDK3bOWbhLz1FsJHv2eOCapLBIgAEZAVgd+O3sYn687yPnm6seOD7eHj4SorP8kZIkAEiAARsE8CtA61z3F9NCoSsBxjnG0WJU0cNkMt+47mjNyEnKQ5Rn4OW/gbvHz9RPu+7KN3kXQzjrfTadh7qNWyrWi7BgPd/uyGa+nXeHsLjz4Fv13H+Z+DBwxAxMcfWdzfvXHjkL5yFd8+8JVXUParcRbbo4ZEgAgQgdIm0GfBYRy8Jhzt7lynDGb1EX/rbGnHRf0TASJABIiAMgjQOlQZ4yTWSxKwxBKk9kYEaOKgB8JAYObbfyA/baERkHeW/Q43dw/RkFaMfR/3rl7m7bR/awTqtu0k2q7BQIe1HXAv5x5vb9nuGvA4IuwsCBs1CqFDh1jcX9KUn5A6bx7f3u+5Toj+6SeL7VFDIkAEiEBpEkjJLsAz3+xEodODmPlafTxfV/yR8dKMi/omAkSACBAB5RCgdahyxkqMpyRgiaFHbR8jQBMHPRSMgF6nx4wha6DKXGoEZPTKjXBychINafVXnyD+giAotR4wBPWfe1G0XYOBZr81Q6ZKuOXwtw2xcDkv7MgqM+5LBPXubXF/qQsXIukHIT+YT7NmiFm4wGJ71JAIEAEiUJoElh2+hc/Xn+Nd8HJzwcnP28PL3aU03aK+iQARIAJEwIEI0DrUMQabBCzHGGebRUkTh81Qy7ojjUqL2cNWQZW1gvfTxc0No379QxK/f5/4BW6ePsnbatH3TTR6sbsktvV6Peovqw+NXsPbW708AridwP8cNfUn+HeyfMfXgzVrcP/zL3h7nnXqoMKa1ZL4T0aIABEgArYm8OjxwRfqlsWM1+rb2g3qjwgQASJABByYAK1DHWPwScCys3E+fvw4tmzZggMHDuDChQtITk6Gm5sbIiMj0axZMwwcOBDNmze3WtQ0cVgNraIMF+SqMW/kb1BlC6KMh7cvRixaKUkc63/4GnHHD/O2mr3SD026vyKJ7XxNPhotb2Rka/VsHyA9g38tZtEv8Gna1OL+Mv/ahoRRo/j2buVjUHnbNovtUUMiQASIQGkReJCjQsNHbh+c1ac+Oteh44OlNSbULxEgAkTAEQnQOtQxRp0ELDsa5xYtWmD//v0lRvT6669j/vz5cHd3L7GuuRVo4jCXmH3Wz8kowMLRy6HOXscH6BMYjKFzjY8UWhr9xqmTcOUf4Vln4hUTsaQoqXmpaLW6FW/KSa/Hqu/1gE7Hv1Zh3e/wrFnT4u5y/vkHt994k2/vEhSEqv8cstgeNSQCRIAIlBaBNcfjMWbtGb57D1dn/PtFe3i70+2DpTUm1C8RIAJEwBEJ0DrUMUadBCw7GufKlSsjLi6O223Vs2dPPPvss4iJiYFWq8U///yDyZMnIyHh4TGoV199FStWCMe7pMJAE4dUJJVtJzM1D4vHLIM6ZwMfiH9YBAbPME7qbmmUW2dMxoX9e/jmDV/sjpZ9BUHIUrusXXxmPDr/0Zk34Z2vx+KftEYmK+/eBbfISIu7yTt/Hjd7vCy0d3FB9XNnJckPZrFT1JAIEAEiYAGBQUuOYefFJL5lh5oRmPd6QwssURMiQASIABEgApYToHWo5eyU1JIELCWNVgm+vvDCC2C7q3r06AEXl8cTp6akpHDHCK9cucJZ2rdvH9iuLSkLTRxS0lSurQf3c7Ds0yVQ52zhgwiJjsGAybMkCWr7vJ9xdpdw5O7pTi+izRuW3wpY2KlLaZfQc2NP/qUy6U6YPltt5He1E8fh7ONjcSyqO3cQ1669Ufuqx4/DxddymxY7Qw2JABEgAhYSyC7QoP6EHVBphB2qU3rVQ/f60RZapGZEgAgQASJABCwjQOtQy7gprRUJWEobMZH+btq0CS+++PC2tpEjR2L69OkiLRo3p4lDUpyKNZZyJwvLP18ETe52PoaIilXQ99ufJIlp1y9zcGrbJt5W3bad0P6tEZLYPpF4AgP+GsDbqpPshc8XZPE/O7m5odqZ06J2S2kzMnClcRMjf8Xu6pIkeDJCBIgAETCDwKYzdzFixb98C1dnJ5wY2x4B3m5mWKGqRIAIEAEiQATEE6B1qHiGSrBAApYSRklCH3NycuDr68tZ7Ny5MzZv3iyhdYAmDklxKtZY4o1MrPxqATR5u/kYoqrXQu+vJkkS075ff8HxjUJ+rVot26LTsPcksf33nb8xfNdw3laru4EYtiSF/9klLBRVTcg1V5wzep0Ol2rVBvR6vlqFP9fDs1o1SWIgI0SACBABWxAYseIkNp25x3f1bJVQLBvY2BZdUx9EgAgQASJABIwI0DrUMR4IErAcY5z5KNPS0hASEsL9zHZibdgg5CiSAgVNHFJQVL6Nu1cfYM0386HJ+5sPpnzdp/HyZxMkCe7AymU48scq3la1ps/ihVEfSWJ7642t+PDvD3lb3W+EofdKYYHmUaUyKm78P3tnAR3F2b3xJyGQBIJDILiTosWdFLdSrEix4m7F3d0dgia4u0MS3IJrIEhwgidAiKz8T5Z/Z9h+QHazs7Ozu8+e0/N92bn3uff+7p739L2deWe3ybHulCwFTXi4oJNllS+SlCxpsi4FSIAESEAOApExahQbdxifo8UzAic0KIAWpbLKEZ4xSIAESIAESIADLDv8DXCAZWdN3759Oxo2bKireuDAgZgyRZo7Yv7FyAGWnf2gflDu41tvsX2KN1SR4pv1chYvjfoDhksC6MzW9Ti9aa2glatEadTrL432lrtbMObMGEG7XVB61Nz+VPjbtXgxZFuzxuQ67lWpipj/f6lCrFim+fOQtGpVk3UpQAIkQAJyEPC7HYr2vheEUA4OwLmhVeCe1EWO8IxBAiRAAiRAAhxg2eFvgAMsO2q6RqNBmTJlcP78eV3VFy5cQLFixYwiEDug+tnnxYsXKPn/d5E8efIEmTLxIFejANuI8cNrb7BzxkKoI7/+1mI/Ut4lFbhrK46vXSloZ/u1GBoNEYdOpmD0vemL6RemCxJ9rmRA2f2Phb/dqlZB5vnzTQmh833QsCGibt0WdDwmTkSKhg1M1qUACZAACchBYMDmq9h8Ufx3ghLZUmJzl7JyhGYMEiABEiABEvgfAryRwj5+FBxg2UefdVXOmDED/fv31/3/2Luwtm7danT1DrH/idXADwdYBoKyQbN7F19hz5wFUEddFKrL71UVNbv1kaTaS/t3IcBniaCVOX8hNBk5URLtRVcWYeFV8W2JI85mRMGAR4J28kYNkWHCBJNjPWrTFhFnzwo67oMHIXUb8fB4kwNQgARIgATMRECl1qD4hCP4ECG+oXV4nV/QoUIOM0WkLAmQAAmQAAn8nAAHWPbxC+EAyz76jGPHjqFq1apQqVRwd3fH9evXdf9r7IcDLGOJ2af9nbMvsH/hfKijrgoAClerjaodukkC5Orh/TiybIGglSHPL/hr3DRJtKcFTsOqW6sErckBHshx9onwd6p27ZBu4ACTYz3t1RsfD4lvaUzTrSvS9uplsi4FSIAESMDcBE7fe4Pmy87phTkxsBIyp0ps7tDUJwESIAESIIHvEuAAyz5+GBxg2UGfb968iQoVKuD9+/dwcXHBwYMHUbFixXhVzkcI44XN7pxunXyOQ95zoI6+KdRerE59/Na6gyQsbh7zw4GFswQt9+w50WryHEm0R58eja3B4t2Jc/elQ/qrzwTttH37Ik2njibHej58OMK2iHFStmyJ9MOHmaxLARIgARIwN4GRO29g1RnxztQCGZNhT88K5g5LfRIgARIgARL4IQEOsOzjx8EBlo33+eHDhyhfvjyeP3+OBAkS6B4brFevntmq5sJhNrRWJXwt4Cn8ls+CJuaOkHepBk1RvlkrSeoIOnUMe+eKd1ylzpQFbWaIj/2ZEmTgsYHYH7JfkFiyORVS3Hsl/J1+zBikbNrElBA639Cp0/BuxQpBJ9kfdZFx6lSTdSlAAiRAAuYkoNFoUWayH0LDo4Qw/avnQY/Kuc0ZltokQAIkQAIk8FMC3Ifaxw+EAywb7nPs0Cr2zqsHDx4g9tE/Hx8ftG7d2qwVc+EwK16rEb98+DGO+s6AJua+kHO5pq1QumFTSWoIDjyDXdPFc6hSpPNA+7lLJdHu7tcdx58eF7R8fZLC9cV74e+Mc+YgWY3qJsd6s9gbr2fPFnTcvLyQ2XuxyboUIAESIAFzErj0+D0aLhTfMBsb60jfisjlntScYalNAiRAAiRAAhxg8TcADrBs9Efw5s0beHl54datW7oK58+fj+7du5u9Wg6wzI7YKgJc2BeCE2unQaMSHzHxatkOxes2lCT/h5cvYNvk0eLwJ3UadF7oI4l2mwNtcDFUPHx+3fyEcPr4RdDO4uODJKVLmRzr3bp1CB07TtBxLVIE2davM1mXAiRAAiRgTgKT9t2G9/EHQoicaZPAr99v5gxJbRIgARIgARKIkwD3oXEisgkDDrBsoo36RYSFhaFy5cq4dOmS7sLkyZMxaNAgWSrlwiELZsUHObfrAU5tnAKtSjw7qkq7rvi1Rh1Jcn984yo2jxPPi3JNlhzdlq6VRLvx7sYIehek03LQarFhikb3v/9+su/cAZe8eU2OFbZnL57//1tBY8US5cqJnHv2mKxLARIgARIwFwGtVovfph/Fo7cRQojulXJiQA1Pc4WkLgmQAAmQAAkYRID7UIMwWb0RB1hW30L9AiIiIlC9enWcOnVKd2HYsGEYP368bFVy4ZANtaIDnd56D2e3ToJWHSrkWaNLbxSoVE2SvJ/duY0NI8U3ASZydUVPn82SaNfeVhtPPn5962CSL1qsnK3W0811NAAJ06c3OdanEyfwpGMnQccpbVrkPiE+umhyAAqQAAmQgMQEbr8IR605J/RUd/coj4KZkksciXIkQAIkQAIkYBwB7kON42Wt1hxgWWvnvpN3dHQ06tati0OHDumu9u7dG7O/OWNHjlK5cMhBWfkxjm+4iws7J0CreSskW6fXAHiW85Ik+dAH97BmSB9BK4GTE/qs3SGJttdGL7yLfKfTSvdOi3ne+gOsvJcvwdHV1eRYX65eRUjTZoKOg7MzPK9eMVmXAiRAAiRgLgKzDt/FHL9gQT5jClecHFRJd84mPyRAAiRAAiRgSQLch1qSvnyxOcCSj7XZIzVq1Ajbtm3TxYl9hDB2ePWzf6lMlCgR8uTJI2leXDgkxWm1Yv6rbuPK/vHQasKEGur1H45cJUpLUtObJ4/g21//TLe+63fBwdHRZP0Sa0ogUh2p08n5XItJvuIAS8ohU9SDh3hQu7ZevnmvXoGjs7PJNVCABEiABMxBoObs4wh6+VGQblcuO0bWzWeOUNQkARIgARIgAaMIcB9qFC6rNeYAy2pb97+JG/tfQLNmzYqQkBBJCXDhkBSn1YodWnYD14+MA7SfhRoaDR2LbIWLSlLT+5fPsaK3+PhdrGjv1dvglCiRSfoqjQpFVhcRNH69r8HQTRrhbyd3d+Q+fsykGP86q96+RXC58npasY8Qxj5KyA8JkAAJKI3AwzefUWn6Ub20NnUug5LZUyktVeZDAiRAAiRghwS4D7WPpnOAZUN95gDLhppp5aXsXXgNQcfHANoooZKmoyYjU74CklQW/uY1lnZvq6fVY+VGOCdOYpJ+WFQYym8Qh0rlb2jQa7c4wHLOkwc5du00Kca/ztroaAQVKqynlWPvHjjnzCmJPkVIgARIQEoCi4/dx+T9X19wEftJ45YI54ZWRQJHPj4oJWdqkQAJkAAJxI8AB1jx42ZtXhxgWVvHFJ4vFw6FN0im9HbOvox7Z0YDEB+/azFhJtLnkuaR1YjwMCzq2EKvmi7eq5EkRUqTKnz+6TlqbK0haNQK1KDtEXGAlbhECWRdvcqkGN86BxUpCu2XL8JXWdetQ+Ki4h1gkgWiEAmQAAmYSKD+glO48uSDoPJXySyY1LCgiap0JwESIAESIAFpCHAfKg1HpatwgKX0DllZflw4rKxhZkp3y5QLeHQpdoAlfv6eNh9psmSTJGJURATmt22ip9VxwQokS+Nukv6dd3fw5+4/BY3GJzRofFIcYCWtVg2Z5s01Kca3zsFev0EVKr6pMbP3Yrh5SXPQvWRJUogESMDuCbwI+4Iyk/z1OPi2KwmvPHzk2e5/HARAAiRAAgohwH2oQhph5jQ4wDIzYHuT58Jhbx3/fr0bxp3CsxuT9C62n7MUKdJ7SAJIrYrB7BYN9LTazvJGqgwZTdK/GHoRbQ60ETQ6+SVA1fPiY5ApGv8Jj3HjTIrxrfODun8gKlh8o1eGaVORvG5dyfQpRAIkQAJSEPA9HYJRu24KUkldnHBxeDUkcjL9xRlS5EcNEiABEiABEuA+1D5+Axxg2UefZauSC4dsqBUdaPXwALwKnqGXY+dFvnBLlVqSvLVaLWY20x/0tJ42H2lNvMPr2JNj6OHfQ8hx4N5EKH4tQvg7dccOcO/XT5IaYkVCWrbElwsXBb10w4cjVUv9RyMlC0YhEiABEogngb+WnMWZB28F7wZFMmJW01/jqUY3EiABEiABEpCeAPeh0jNVoiIHWErsihXnxIXDipsnYeorBhzA+8fz9RS7L98AFzc3yaLMbtkA6pgYQa/FxFlInzO3Sfq77+/G0JNDBY3x25yR5474JkX3/v2QukMHk2J86/ykazd8CggQvkrbuxfSdO0qmT6FSIAESMBUAu8+R6P4+MPQaEWlxS2LoWaB9KZK058ESIAESIAEJCPAfahkKBUtxAGWottjfclx4bC+npkj4yW9d+HjyyV60r1Wb0XCRM6ShZvftimiIsThUtMxU5DJM79J+uuD1mPiuYmCxuy1zsjwWIyRftxYpGzc2KQY3zo/HzQYYTvFtxqmatMG6QYPkkyfQiRAAiRgKoFNgU8wcOs1QcYloSMuj6gO10QJTJWmPwmQAAmQAAlIRoD7UMlQKlqIAyxFt8f6kuPCYX09M0fGC7tuxpd3vnrSfTfshoODdK9bX9SpJSLCxDdi/Tl8PLIWNO2RlqXXlmLuZfGQ9qVLEyL5G/EtgRnnzUWyatUkQ/Zy4kS8X7Va0EvesCEyTJwgmT6FSIAESMBUAu18AuEf9EqQqZk/PRa3KmaqLP1JgARIgARIQFIC3IdKilOxYhxgKbY11pkYFw7r7JuUWceeTzW/43pEf1wnyCZwSog+a7dLGQZLurXFx7evBc0Gg0YhR9ESJsWYeXEmVt5YKWisnuMA5wjxMcUsq3yRpGRJk2J86/x63ny8WbBA+CpptarING+eZPoUIgESIAFTCHyMjEGxcUcQrRbfxjq76a+oX8S0F2aYkhN9SYAESIAESOB7BLgPtY/fBQdY9tFn2arkwiEbasUGUkWrsajrWkR/2iTk6Jw4CXqs3Chpziv6dML7F88FzT/6DkXuUmVNijH2zFhsvrtZp+Gg0WLjFLWeXvZdO+GSJ49JMb51frdqFUInim9rTFyyJLKu0r9zTbJgFCIBEiABIwnsuvocvdZfFrwSJnDAheHVkNw1oZFKNCcBEiABEiAB8xLgPtS8fJWizgGWUjphI3lw4bCRRppQRuSnGCzpvRoxn7YJKolTpEJX71UmqP6vq2//7njz5JFwoXavAfilnJdJMQYcG4ADIQd0Gm4RWqyYoz/AynXsGBKmczcpxrfOH3bswIvBQ4SvnD09kWOHtHeqSZYshUiABOyOQPe1l7D3+guhbq88aeHbTrq7UO0OKAsmARIgARIwGwHuQ82GVlHCHGApqh3WnwwXDuvvoakVfHwXiZX9VyHm8y5BKrl7enSYt8xUaT3/NUP+QeiDYOG7Gl16o0Al086n6nKkC049O6XT9HirxZwl+gOsvFevwNFZuoPoP/oH4Gm3bkINThk8kNvfX1JOFCMBEiCB+BCIjFGj6LjDiIgW18FJDQvir5JZ4iNHHxIgARIgARIwKwHuQ82KVzHiHGApphW2kQgXDtvooylVvH/5GauH+iLm8z5BJnWmLGgzY6Epsv/ju37kQDy/c0v4vmqHbihcrbZJMVrua4mrr6/qNHI/02LCKnHj5uDqCs/Ll0zS/69zxIULeNSylfC1o5sb8l4IlDQGxUiABEggPgQO3wpFx1UXBNfYd3AEDquKNG7SDfHjkxd9SIAESIAESOB7BLgPtY/fBQdY9tFn2arkwiEbasUGev34I9aNWglVxCEhx3Q5cqPlpFmS5rx53FA8viG+2v231h1RrE49k2LU31Ef98Pu6zSK3NNgyGbx4GInDw/kDpD27qjIu3fx8A/9nD1v3oBDAr6e3qRG0pkESMBkAv02XcXWS08FnZLZU2FT5zIm61KABEiABEiABMxBgPtQc1BVniYHWMrriVVnxIXDqtsnSfIv7odh07jlUH0Rhz0ZPfOj2Zgpkuj/K7Jt8mg8vCzeHVCheRuUrPenSTGqbK6CVxFfXxdf4boGPfeIAyxznE8VExqKe16/6eWc+8xpOKVMaVIddCYBEiABUwjEqDUoPv4Iwr6Ib2Ed+Xs+tCuf3RRZ+pIACZAACZCA2QhwH2o2tIoS5gBLUe2w/mS4cFh/D02t4Mntd9g2ZRlUX44LUlkLFcGfw8aZKq3nv3P6BNwLPCN8V7ZxC5T58y+TYpRcWxJfVF90GrXPa9DGTxxgJS5VCll9fUzS/6+z5ssX3ClSVO/rnIcOIlEWnjEjKWiKkQAJGEXgZPAbtFx+Ts/n1ODKyJjC1SgdGpMACZAACZCAXAS4D5WLtGXjcIBlWf42F50Lh8211OiCHl59jV0zl0IVeVrwzVm8NOoPGG601s8c9s6dhqBTxwSTkvUbo8Jff8c7hkqjQpHVRQT/JsfV+POUVvg7aY0ayDRndrz1v+eo1WoRVKgwECPe5ZBt82a4FiwgaRyKkQAJkIAxBIbvuI41Zx8LLoUyJceuHuWNkaAtCZAACZAACchKgPtQWXFbLBgHWBZDb5uBuXDYZl+NqSo4MBR753tDHXlecMtbtiJ+7z3QGJk4bQ8snI2bx44IdsXq1MdvrTvE6fcjg7CoMJTfIG7Q2h1Uo+YlcYCVokkTeIwdE2/9HzneLVce6rdvhcuZly+DW7lyksehIAmQAAkYQkCj0aLUJD+8/hglmA+okRfdK+UyxJ02JEACJEACJGARAtyHWgS77EE5wJIduW0H5MJh2/01pLpbp57jkPdiqKPEN/bl96qKmt36GOJusM3hpfNx7cgBwb5w9Tqo2r6rwf7/NXz68SlqbaslfN17hxrlbosDrNSdOsG97z/x1v+R4/1atRH98KFwOePsWUhWs6bkcShIAiRAAoYQuPjoHRotEh/PjvXx6+eFnGndDHGnDQmQAAmQAAlYhAD3oRbBLntQDrBkR27bAblw2HZ/Danu+tGn8Fu+AOro64L5rzXqoEq7+A+Xvhc3wGcJLu3fJVwqUKk6anTpZUiK37UJeheExrsbC9eGbVCj8ENxgOU+YABSt28Xb/0fOT5s2hSRV8W3KaYfMwYpmzaRPA4FSYAESMAQAhP23sLSE+JQPbe7Gw739TLElTYkQAIkQAIkYDEC3IdaDL2sgTnAkhW37QfjwmH7PY6rwkuHHuHY6nnQRAcJpiX+aISKLdrG5WrU9eNrVyJw11bB55fyv6F2z/5GaXxrHPgyEO0OigOqqT5aZHuhFkw8JoxHikaN4q3/I8fHHTvh84kTwuW0/foiTceOksehIAmQAAnERSD2XL6K0wLw5N3Xl1nEfnpWzoV+1fPG5crrJEACJEACJGBRAtyHWhS/bME5wJINtX0E4sJhH33+WZXn9zzEqQ2zoYm5L5iVbdICZRqZ9obA/8Y8tWktzm5dL3ydp1Q51O07JN4N8H/sj94BvQX/RYu1SP1eHGBlWrgASStXjrf+jxyf9euP8L17hcupO3aAe79+ksehIAmQAAnEReDm8zDUmXtSz2xPz/IokDF5XK68TgIkQAIkQAIWJcB9qEXxyxacAyzZUNtHIC4c9tHnn1V5ets9nNs6CxrVI8HMq1V7FP+9gaRwzm3fhJMbVgmaOYqVRIOBI+MdY9f9XRh2cpjgv3qGBs7RGuHvrOvWInHRovHW/5Hjy7Fj8X6dOIhL0bQpPMaMljwOBUmABEggLgIzD93BXP97glmmlK44MbASHBwc4nLldRIgARIgARKwKAHuQy2KX7bgHGDJhto+AnHhsI8+/6zK4xvu4sKu6dCqnwtmVTt0R+Fq4gHpUlC6sHsbjq1ZIQ6YChXBn8PGxVt67e21mHx+ss4/gVqL9VPFu69iv8uxby+cc+SIt/6PHF/Nmo233t7C5aS1aiLTrFmSx6EgCZAACcRFoPqsY7gb+kkw61A+O4b/ni8uN14nARIgARIgAYsT4D7U4i2QJQEOsGTBbD9BuHDYT69/VKn/6tu4sn8KtOo3gkmtHv2Qr0IlSeFcPrgH/isWC5qZfimApqO/DqDi8/G+6o35V+brXFN80mLJPP0BVu4zp+GUMqbsmW0AACAASURBVGV8pH/q83b5CryaNk2wSVK2LLKsWC55HAqSAAmQwM8I3H/9CVVmHNMz2dKlDIpnS0VwJEACJEACJKB4AtyHKr5FkiTIAZYkGCnyLwEuHPwtHFp+EzeOTIRWEybA+KPfUOQuWVZSONf8DuLwknmCZvpcedBiwsx4x5geOB2+t3x1/plfaTFj+TcDLAcHeN64DocECeKt/yPHD1u24MXwEcJll4IFkX3zJsnjUJAESIAEfkZg4dF7mHrgjmCSNqkzzg2pAkdHPj7IXw4JkAAJkIDyCXAfqvweSZEhB1hSUKSGQIALB38M+xZdw+1jEwDtZwFGo6Fjka2wtOdH3ToRgP3zZ4ibrazZ0XqqONAythOjT4/G1uCvbzXM90iD0evE868ckydH3nNnjZU0yD784CE86y0eHp8waxbkOnjQIF8akQAJkIBUBOrNP4mrT8X/8NCiVBZMaFBQKnnqkAAJkAAJkIBZCXAfala8ihHnAEsxrbCNRLhw2EYfTali15zLCD4dexZVtCDTbMxUZPSU9hyVO2dOYs9s8ZHBVBkyoe0s8ZFCY2vod7QfDj06pHMrFaRBv+3iAMucQ6XPZ8/icZu2QroJUqRAnrNnjE2f9iRAAiQQbwLPPnxBucn+ev6r25dEhdxp461JRxIgARIgARKQkwD3oXLStlwsDrAsx94mI3PhsMm2GlXU1qkXEHJxDACt4Ndqyly4Z5P2APR7F85h5zTx0PZkadOh4/z4nx3V+XBnnH5+Wpdz1csadDogDrBcCxdGto0bjOJgqHHkrVt42LCRaJ4gwdfHFfnWL0MR0o4ESMBEAitPPcSY3bcElWQuTrg4ohoSJnA0UZnuJEACJEACJCAPAe5D5eFs6SgcYFm6AzYWnwuHjTU0HuVsGHcaz25M1PNsN9sbKT0yxkPtxy4hVy9h68SRgkGSlKnQZfGqeMdovrc5rr+5rvNvcFqDv46JAyw3Ly9k9o7/3V0/Syr66TPcr1pVzyTPhQtI4JYk3rXQkQRIgASMIdDU+wzOPXwnuDQsmhEzm/xqjARtSYAESIAESMCiBLgPtSh+2YJzgCUbavsIxIXDPvr8syrXDPdHaLD+YeqdF6+CW0pp32T15NZ1bBozREjFJYkbuq+I/11SdbfXRUh4iE6vlZ8adc+Ld5Alr1cPGabE/w2HP+OlDg/H3ZKl9Exy+fshYYYM/DGRAAmQgNkJvP0UhRITjkAjLnlY0qoYqudPb/bYDEACJEACJEACUhHgPlQqksrW4QBL2f2xuuy4cFhdyyRPeMWAfXj/eKGebo+Vm+CcOLGksZ7fDcL6Ef0FTSdnZ/Re9fUQ9vh8Km2qhDdf3uhcu+1R47fr4m4u1d9/I92QwfGRjdNHq9EgKH8BQCvGy75jO1w8PeP0pQEJkAAJmEpgY+BjDNr69e7T2I9rwgS4PLIaXBJK/9ZVU3OlPwmQAAmQAAn8iAD3ofbx2+AAyz76LFuVXDhkQ63YQEt6b8fHl/pnUf2zficcHaXdDL0KeYDVg3oJHBwcHdF3/a54cymxpgQi1ZE6/0Gb1Ch2Xxwope3TB2m6dI63dlyOd0qVhiZMfPtXllW+SFKyZFxuvE4CJEACJhNou/I8Au68FnRqF0yPhS2KmaxLARIgARIgARKQkwD3oXLStlwsDrAsx94mI3PhsMm2GlXUwq7r8eXdWsHH0Skh/lm73SgNQ4zfPn0Cn35d9Uz/WbcTjgmMH5TFqGNQdE1RQWu8rwp5novS6UePRspmTQ1JK14296pWQ8zTp4JvpvnzkPQ/52LFS5hOJEACJPATAuGRMSg+7gii1eKZf3Oa/Yp6v0p7ZiGbQAIkQAIkQALmJsB9qLkJK0OfAyxl9MFmsuDCYTOtjFchWq0W8zqsQsynzYK/c2I39FgZ/7OpfpRI2KuXWNazg97lXr5bkNDFxejc30W+g9dGL8Fv9mIVMrwXZTLOno1kNWsYrWuoQ+xbCGPfRvjvx2PCBKRo1NBQd9qRAAmQQLwI7LzyDL03XBF8EyVwxMURVZHUJWG89OhEAiRAAiRAApYiwH2opcjLG5cDLHl523w0Lhw23+KfFqiKUWNhl5WI+bRDsEuSMjW6LPaVHMynd2/h3fVvPd1uy9bBNWkyo2M9Dn+MOtvrCH4rZqng9vVpQt0ni48PkpTWP2jd6CA/cXjUti0izpwVLNwHD0LqNm2kDEEtEiABEvgfAt3WXsS+6y+F7yvlTYuVbfn4Mn8qJEACJEAC1keA+1Dr61l8MuYAKz7U6PNDAlw47PvHEfk5Bkt6LkPM570CiBTpM6L9HG/JwXz5GI6FHZrr6XZe5Au3VKmNjnXz7U0029NM5+eg0WL9FDUcv1HJvnMnXPLmMVrXUIenvfvg48GDgnmabl2Rtpd4vpehOrQjARIgAUMJRMaoUWTsYXyJUQsuUxoVRNMSWQyVoB0JkAAJkAAJKIYA96GKaYVZE+EAy6x47U+cC4f99fzbij+9j8TyvkugijgkfJ02W060njJHcjAxkZGY+/eferod5i1DcnfjX/1+7sU5dDj09XHEpBFaLJ8jbuhiv8t17BgSpnOXvIZ/BV+MGIEPm7cI+ilbtED6EcPNFo/CJEACJHDgxkt0WXNRAOHoAAQOq4rUbs6EQwIkQAIkQAJWR4D7UKtrWbwS5gArXtjo9CMCXDjs+7fxITQCvoMWQfUlQACR8ZcCaDZ6suRgNGo1ZjWvp6fbZsYipM6U2ehYfo/80OdoH51fhrdazF6iP8DKe+0qHBMlMlrXUIfQadPwbvkKwTxZ3brIOG2qoe60IwESIAGjCfTZcBk7rohvqyidIxU2dCpjtA4dSIAESIAESEAJBLgPVUIXzJ8DB1jmZ2xXEbhw2FW7/6fY108+Yt2IBVB9OSlcy16kOBoOHm0WMLEDrNhB1r+flpNmI12OXEbH2h68HSNPj9T55X2qxbjVoqZD4sTwvCTepWC0uAEOb7yX4PWsWYKlm5cXMnsvNsCTJiRAAiRgPIEolVr39sGPUSrBeWy9/GhdJpvxYvQgARIgARIgAQUQ4D5UAU2QIQUOsGSAbE8huHDYU7f/t9YX98OwcexcqCPPCRfzlC6Puv8MNguYeW2aIPpLhKDdbMxUZPTMZ3SsVTdXYdqFaTq/YsEaDNoivlI+YYYMyOXvZ7SmMQ7v16/HyzFjBRfXIkWQbf06YyRoSwIkQAIGE/APCkU7nwt69ueGVkG6ZMa/xdXgoDQkARIgARIgATMS4D7UjHAVJM0BloKaYQupcOGwhS7Gv4YnQe+wdeIcqKPEO5bye1VFzW5fH8+T+rOoU0tEhH0QZBsNG4dshYoYHWb+5fnwvvb1oPlKVzXouk8cYLnky4fs27YarWmMQ9jevXjer7/gkihnTuTcu8cYCdqSAAmQgMEEBmy+is0Xnwr2xbOmxJauZQ32pyEJkAAJkAAJKI0A96FK64h58uEAyzxc7VaVC4fdtl5X+MNrb7Bz2gyoo68LIH6tUQdV2nU1C5hlPdsj7FWooF2v/3DkKlHa6FgTzk7AhjsbdH51z2rQKkAcYCUpWxZZViw3WtMYh08nTuJJx46Ci1PatMh94rgxErQlARIgAYMIxKg1KD7+CMK+xAj2w+v8gg4VchjkTyMSIAESIAESUCIB7kOV2BXpc+IAS3qmdq3IhcOu24/gC6HYM2caNNFBAogSfzRCxRZtzQLGp183vH36WNCu02sAPMt5GR1r4PGB2P9wv86veYAa9c9qBY1kdeog44zpRmsa4/Dl2jWENGkquDg4O8Pz6hVjJGhLAiRAAgYROBH8Gq2Wn9ezPTmoEjKlTGyQP41IgARIgARIQIkEuA9VYlekz4kDLOmZ2rUiFw67bj9un36OAwunQBNzXwBRtnELlPnzL7OAWTPkH4Q+CBa0q3fphYKVqhsdq8vhLjj1/JTOr/M+NapcFQdYKVu0QPoRw43WNMYh6uFDPKhVW88l79UrcHTm6+yN4UhbEiCBuAkM3X4d686Jg//CmZJjZ4/ycTvSggRIgARIgAQUTID7UAU3R8LUOMCSECalAC4c9v0ruH70KY4snQSN6pEAwqtlOxSv29AsYDaOHoynt28I2pXbdkaRmnWNjvXXnr9w4+1Xnf5b1Sh5VxxgpeneHWl79jBa0xgH1bt3CC5bTs8l1/FjSOjubowMbUmABEjgpwTUGi1KTTyCN5+iBbtBNT3R9becJEcCJEACJEACVk2A+1Crbp/ByXOAZTAqGhpCgAuHIZRs1+byoccI8BkPrfq5UGTVDt1RuFotsxS9ddIohFwRD4yPfVQx9pFFYz+1t9XGk49PdG6j16iQ7+v/1X3SDRuGVK1aGitplL02JgZBBQvp+eTYuwfOObmpNAokjUmABH5K4OyDt2i25KyezdH+vyFbmiQkRwIkQAIkQAJWTYD7UKtun8HJc4BlMCoaGkKAC4chlGzXJnDvQ5xYOxZa9WuhyFo9+iFfhUpmKXrn9Am4F3hG0C7zZ3OUbdzc6Fjl1pdDeHS4zm/GUhUyvxElMkyfjuS/1zFa01iHoKLFoI2IENyyrluHxEWNf6OisXFpTwIkYD8ERu28Ad8z4h2yv3gkw/7eFewHACslARIgARKwWQLch9psa/UK4wDLPvosW5VcOGRDrchAZ7bfw5lNo6HVfBDy+6PfUOQuaZ7Xs++bNx23Tx4VYsXnwHi1Ro0iq4tAi6+PDS6Zo0IKcY6EzMuWwa28/uN95oAfXKkyVC9eCNKZFi1E0krmGfyZI39qkgAJKJuARqNFmcl+CA2PEhLtWy0PelXJrezEmR0JkAAJkAAJGECA+1ADINmACQdYNtBEJZXAhUNJ3ZA/l+Mb7yJw+whA+1kI3mjoWGQrXNQsyRxaMg/X/Q4K2rHnX8Weg2XMJywqDOU3/P8Bxlot1k1Vw0kjKmTbsgWuBfIbIxkv2wf1GyAqSHx7o8fkSUhRv368tOhEAiRAAv8lcPHRezRadFrv68P/VETudEkJiwRIgARIgASsngD3oVbfQoMK4ADLIEw0MpQAFw5DSdmmnf/q27i8ZxgA8YDgZmOmIqNnPrMU7O/jjcv7dwvaBSpVR40uvYyK9Tj8Meps//qIoGukFr6z1Hr+OY8cQaJMGY3SjI/xozZtEXFWPJsm3ZDBSPX33/GRog8JkAAJ/A+B8XtuYdnJh8L3udzdcKSvF0mRAAmQAAmQgE0Q4D7UJtoYZxEcYMWJiAbGEODCYQwt27M9uOwGbhweAvz/43ixFbaaMhfu2XKYpdgT63xwfucWQduznBfq9BpgVKzrr6+j+b6v52ale6fFPG/9AVbeixfgmMT8Bxw/7d0HHw+Kd5Ol7toF7r17G1ULjUmABEjgewS0Wi3KTwnAsw9fhMs9K+dCv+p5CYwESIAESIAEbIIA96E20cY4i+AAK05ENDCGABcOY2jZnu2e+Rdx58QovcLazfZGSg/z3MF0Zut6nN60VoiXq0Rp1Os/3CiwJ5+dRNcjXXU+uZ9qMWG1OMBycHZG3iuX4eDgYJRmfIxfjBqNDxs3Cq4pm/+F9CNHxkeKPiRAAiSgR+Da0w/4Y/4pve/29iqP/BmSkxQJkAAJkAAJ2AQB7kNtoo1xFsEBVpyIaGAMAS4cxtCyPdvtM07jwfmJeoV1XuQLt1SpzVJs4O5tOL5mhaCdtVAR/DlsnFGx9j7Yi8EnBut8igVrMGiLeACWUwYP5Pb3N0ovvsavZs7C2yVLBPdktWsh48yZ8ZWjHwmQAAkIBKYcCMKio/fFtTJ1Yhzt/5ssw3m2gQRIgARIgATkIMB9qByULR+DAyzL98CmMuDCYVPtNLqYTRP88OTaLD2/His3wjmxeR7Bu3JwL/xWLBLixZ61FXvmljGfdbfXYdL5STqXylc06LJfHGC55M+P7FvFRxSN0TXW9u2KlXg1Vcw9SdmyyLJiubEytCcBEiABPQKxjw9Wmn4UIW/F16t29sqBIbV+ISkSIAESIAESsBkC3IfaTCt/WggHWPbRZ9mq5MIhG2pFBlo7ch9e3lmol9s/63bCMUECs+R74+gRHFw0W9BOlyMXWk4S/zYk6KKri7Dwytec65/WoPkxcYCVpEIFZFkq3hVliF58bT5s3YYXw2IPwP/6ccmXD9m3bY2vHP1IgARIQEfg9otw1JpzQo/Gzu7lUDhzChIiARIgARIgAZshwH2ozbTyp4VwgGUffZatSi4csqFWZCCfQdvwNkR8pM8xgRP+WbfDbLkGnT6OvXPEu5ZSZcyMtjPFO7IMCTzl/BSsub1GZ9r6iBq/B2oFt+T16iHDlMmGyJhs89HfH0+7dRd0EmbIgFz+fibrUoAESMC+Ccw8fBdz/YIFCBlTuOLkoEp8fNC+fxasngRIgARsjgD3oTbX0u8WxAGWffRZtiq5cMiGWpGBlv2zHmHPxUPVE7kmQU8f8WByqZO+f/EcdkwVz7xKljYdOs437rG7oSeGYveD3brUeu5So8JNcYCVqm1bpBs0UOq0v6sXcfEiHrVoKVyLffNh7BsQ+SEBEiABUwhUm3kMwa8+CRLtymXHyLr5TJGkLwmQAAmQAAkojgD3oYpriVkS4gDLLFjtV5QLh/32PrbyRd1WIuKt+Nhb4uSp0XWJr9mgPLp+BVvGi28dTJw8Bbou+Xo3laGf7n7dcfzpcZ350A1q/PpQHGCl7dcXaTp2NFTKJLuo+/fxoM7vehqe167CIVEik3TpTAIkYL8E7r36iKozv65v/362dCmD4tlS2S8UVk4CJEACJGCTBLgPtcm2/k9RHGDZR59lq5ILh2yoFRco9qDg+R28Ef1pj5BbcvcM6DDPfGdIPbtzGxtGDhDiJXRxRS/fzUaxabmvJa6+vqrzmbxChRyhorvHhAlI0aihUXrxNVa9eYPg8hX03HOfPAGnNGniK0k/EiABOycw6/BdzPnm8UH3pM44O6QKHB0d7JwMyycBEiABErA1AtyH2lpHv18PB1j20WfZquTCIRtqxQVSRauxoPNCqCIOCrmlyZwDf0+fa7ZcX4U8wOpBvQR9B0dHxB4a7+Bg+Oas7va6CAkP0Wksmq9C6o9iupkWLUTSSpXMlv+3wtqYGAQVLKQXK8ee3XDOlUuW+AxCAiRgWwRi/6NC1ZnHcP/1Z6GwNmWzYfQf+W2rUFZDAiRAAiRAAgC4D7WPnwEHWPbRZ9mq5MIhG2rFBYoIj8bSXvOg+hIg5OaRJx+ajxMPWZc66XfPn2HlP531ZPus3Y4ETgkNDuW10QvvIt8BWi3WTlMjoVp0zbZxA1wLFzZYy1TDO8WKQ/NZ3GxmXbsGiYsVM1WW/iRAAnZI4HtvH+Tjg3b4Q2DJJEACJGAnBLgPtY9Gc4BlH32WrUouHLKhVlygsNcR8BkwF6ovJ4XcshYqhj+HjTFbruFvXmNp97Z6+t1XbIBLEjeDYsbeoVBkdRGotWq4RmnhO/Ob6RWAnEcOI1GmTAZpSWF0r0pVxDx7JkhlWjAfSatUkUKaGiRAAnZGYPrBO5gfcE+o2iO5C04NqszHB+3sd8BySYAESMBeCHAfah+d5gDLPvosW5VcOGRDrbhAr598xNrhs6GOPCfklqd0OdT9Z4jZcv3yMRwLOzTX0++8eBXcUhp2QPGn6E8os76Mzj/dOy3meesPsGLfAhj7NkC5Pg8bNkLkrVvihlPGM7jkqpFxSIAEzE8gdjhfafpRhLyNEIJ1KJ8dw3/n2wfNT58RSIAESIAELEGA+1BLUJc/JgdY8jO36YhcOGy6vT8t7nnwe2waNxvqqIuCXX6vqqjZrY/ZoMRER2Fuq0Z6+u3nLEWK9B4GxXz26Rlqbq2ps839VIsJq8UBloOzM/JeuWzUeVoGBf2J0eN27fH59GnBwn3AAKRu385UWfqTAAnYGYEbz8Lw+zzxbtjY8nd0L4dfM6ewMxIslwRIgARIwF4IcB9qH53mAMs++ixblVw4ZEOtuEAh199gx9SZUEdfE3L7tUYdVGnX1Wy5xt5lMLNZXT391tPmI22WbAbFvPX2FpruaaqzLRaswaAtGsHPKYMHcvv7G6QjldGzvv0Qvm+fIJe6Uye49/1HKnnqkAAJ2AmBSftvw/vYA6HazKlccXxAJVkH8naCmmWSAAmQAAkohAD3oQpphJnT4ADLzIDtTZ4Lh711XKw3ODAUe+ZOhyb6tvBliT8aoWIL/TOqpCY0p1UjqKKjBNnmE2bAI1deg8KceX4GnQ530tlWvqJBl/3iAMslf35k37rFIB2pjF6OHYv369YLcimaNIHHWPOdISZV3tQhARJQDoHYwX6FqQF4+v6LkFQXr5wYXMtTOUkyExIgARIgARKQmAD3oRIDVagcB1gKbYy1psWFw1o7Z3reN088wyHvadDEiIcGl23cAmX+/Mt08Z8oLOjQHJEfwwWLJiMnInP+QgbFPBByAAOODdDZ1j+tQfNj4gArSYUKyLJ0iUE6Uhm9njsXbxYuEuSS1qiBTHNmSyVPHRIgATsgcPnxezRYKD6KHFvynp7lUSBjcjuoniWSAAmQAAnYKwHuQ+2j8xxg2UefZauSC4dsqBUX6MqRxwhYOQUa1SMhN6+W7VC8bkOz5urdrQ0+vX0jxGgweBRyFClhUMxNdzZh3NlxOtvWR9T4PVAr+CWvVw8Zpkw2SEcqo3e+vgidJMZMXKoUsvr6SCVPHRIgATsgMG7PLSw/+VCoNHuaJPDv58XHB+2g9yyRBEiABOyZAPeh9tF9DrDso8+yVcmFQzbUigt0fvcDnFw/GVr1cyG3qh26oXC12mbNdUWfznj/4pkQo27fIchTqpxBMZdeW4q5l+fqbHvuUqPCTXGAlaptW6QbNNAgHamMwnbuxPNBgwU5Z09P5NixXSp56pAACdg4AY1Gi7KT/fEyPFKotGflXOhX3bDHqm0cD8sjARIgARKwYQLch9pwc78pjQMs++izbFVy4ZANteICndwSjPPbJkKrfi3kVqt7X+SrWNmsua4a2BOvH4l3GxgTc3rgdPje8tXlN3SDGr8+FAdYafv1RZqOHc2a+3/FPx49iqddxEPvndKnR+6jAbLmwGAkQALWS+BCyDv8ufiMXgEH+1RE3vRJrbcoZk4CJEACJEACBhDgPtQASDZgwgGWDTRRSSVw4VBSN+TNJWBNEC7vHQ+t5oMQ+I++Q5G7VFmzJrJuRH+8uBskxKjaoTsKV6tlUMwRp0Zgx70dOtvJK1TIESq6eUyYgBSNzPv443+T/HLlCkKaiWeGObi6wvPyJYNqoREJkAAJjN51Ez6nQwQQud3dcLivF8GQAAmQAAmQgM0T4D7U5lusK5ADLPvos2xVcuGQDbXiAh1adgPXj4wFtBFCbo2GjUO2QkXMmuvmccPw+MZVIcZvrTuiWJ16BsXs5d8LAU++3uG0aL4KqT+KbpkWLUTSSpUM0pHKKOrhQzyopf/IZd6rV+Do7CxVCOqQAAnYKAGVWoPSk/zw5lO0UGGfqrnRp2oeG62YZZEACZAACZCASID7UPv4NXCAZR99lq1KLhyyoVZcoD0LruLO8ZEA1EJuzSfMgEcu8569sn3KGDy4FCjELN+sNUo1aGIQn7/3/41Lry4BWi3WTlMjoZg6sm3cANfChQ3SkcpI9f49gsvo37GW69gxJEznLlUI6pAACdgogWN3X+PvFef1qvPr54Wcad1stGKWRQIkQAIkQAIcYNnbb4ADLHvruJnr5QDLzIAVLL916jmEXPz6Rr9/P21nLUaqDJnMmvXu2VNw98wJIUapBk1Rvlkrg2LW3V4XIeEhcI3SwnfmN9MrADmPHEaiTObN/b9JatVqBBUoqBuo/fvJvnMnXPLyDgqDGkojErBjAn03XcG2S+ILLQpmTI7dPcvbMRGWTgIkQAIkYE8EuA+1j25zgGUffZatSi4csqFWXKB1Y47ixa3penl1XrwKbilTmTXXAwtn4+axI0KMYnXq47fWHQyKWXZ9WXyM/oh077SY560/wMp78QIckyQxSEdKozulSkMTFiZIZlnliyQlS0oZglokQAI2RuBLtBrFxx/G52hxHRte5xd0qJDDxiplOSRAAiRAAiTwfQLch9rHL4MDLPvos2xVcuGQDbXiAq0ctA/vQhbq5dVr1RYkdHYxa65Hli3E1cP7hBixB7jHHuQe1ydGHYOia4rqzHI/1WLCanHj5+DsjLxXLsPBwSEuGcmv36teAzGPHwu6GefOQbLq1SWPQ0ESIAHbIbD76nP0XH9ZKMjRATg7pArck5l3/bUdgqyEBEiABEjA2glwH2rtHTQsfw6wDONEKwMJcOEwEJQNmi3pvRkfX/oKlTk4JsA/63aYfQh0dPVyXNyzXYib36sKanb7J07CryJeocrmKjq7YsEaDNqiEXycMnggt79/nBrmMHjYpCkir10TpNOPG4uUjRubIxQ1SYAEbIRAB99AHLn9SqimfK40WNOhlI1UxzJIgARIgARIIG4C3IfGzcgWLDjAsoUuKqgGLhwKaobMqSzovAqRHzYJUZ0Tu6HHyg1mz+LUpjU4u1WMk6d0edT9Z3CccYPeBaHx7q+DocpXNOiyXxxgueTPj+xbt8SpYQ6Dxx074fMJ8UyvtP36Ik3HjuYIRU0SIAEbIPD+czRKTDgClUY8O2/an4XQuHhmG6iOJZAACZAACZCAYQS4DzWMk7VbcYBl7R1UWP5cOBTWEJnS0ag1mN9xGWI+7xIiJk2dDp0WLjd7Bue2b8LJDauEODmKlkCDQaPijHv62Wl0PtJZZ9fglAZ/HRcHWEkqVkCWJUvi1DCHwbMBAxG+e7cgnbpDe7j372+OUNQkARKwAQJrzj7C8B03hEqcnRxxYXhVJHVJaAPVsQQSIAESIAESMIwA96GGcbJ2Kw6wrL2DCsufC4fCGiJTOpGfY7CkhzdiIg6Ig5fM2dBm+nyzZ3Bp304E+C4V4mQpUAiN6acJtwAAIABJREFUR0yMM+6eB3sw5MQQnV27g2rUvCTevZC8UUNkmDAhTg1zGLycMBHvV68WpJM3bIgMEy2TiznqoyYJkIC0BBovPo3AkPeCaJ2CHljQ4uv5fvyQAAmQAAmQgL0Q4D7UPjrNAZZ99Fm2KrlwyIZaUYE+vovEir4LoPoSIOSVIW9+/DV2itnzvOZ3AIeXiIMyj9x50Xz8jDjjrrq5CtMuTNPZ9d2mRuk74gArdZfOcO/TJ04Ncxi8WbQIr+fMFaTdfvsNmRcvMkcoapIACVg5gafvI1B+irjuxpazpFUxVM+f3sorY/okQAIkQAIkYBwB7kON42Wt1hxgWWvnFJo3Fw6FNsbMab19/glrhsyFKvK0EClHsVJoMHCEmSMDt04EYP98cWCVNks2tJ4W951fsy/OxvIbXx9xHLtKBc9nYqrphg9HqpYtzJ779wK837ARL0ePFi65FC6E7Bs3WiQXBiUBElA2gQUB9zDt4B0hyeSuCRE4rCoSOTkqO3FmRwIkQAIkQAISE+A+VGKgCpXjAEuhjbHWtLhwWGvnTMv75YMwbBg9E+qoi4JQvgqVUKtHP9OEDfAOPncau2aKjwym9MiAdrPjPr9q1OlR2Ba8TRdh7iIV0n8Qg2WcMwfJalQ3ILr0JuGHD+NZz16CcMLMmZHr8CHpA1GRBEjAqglotVrUmH0cd0M/CXX8VTILJjUsaNV1MXkSIAESIAESiA8B7kPjQ836fDjAsr6eKTpjLhyKbo/Zknt86y22TZoOdfR1IcavNX5HlXZdzBbzX+GHVy5i2yTx0Ha3VKnReZFvnHF7+vXE0adHAa0Wq6er4awSXbKuW4vERS1zhkzExYt41KKlkIxj4sTIe0kcDMZZGA1IgATsgsCt5+GoPVd8Y2ls0Rs7lUapHKnton4WSQIkQAIkQALfEuA+1D5+Dxxg2UefZauSC4dsqBUV6P6lV9g1cwo0MeKjLKUaNEH5Zq3NnueTW9exaczXw9hjPy5J3NB9xYY447bY2wLX3lyDa5QWvjPVevY5Dx9CosyWeQV91MOHeFCrtl4+ea9chqOLS5w10YAESMB+CIzfcwvLTj4UCs6Q3AUnB1WGo6OD/UBgpSRAAiRAAiTw/wS4D7WPnwIHWPbRZ9mq5MIhG2pFBbp9+gUOLJgAjSpEyKtC8zYoWe9Ps+f58t5drB3WV4jjlDAReq/5+mjgzz41t9bEs0/P4PFWizlL9AdYeS9fgqOra1wSZrmuDgvD3VKl9bRz+fshYYYMZolHURIgAesjEKPWoMwkP7z5FC0k3/W3nBhU09P6imHGJEACJEACJCABAe5DJYBoBRIcYFlBk4xJ8dWrVzh//rzun8DAQN0/b9++1Un8/fff8PHxMUbOaFsuHEYjswmHawFPcGTpWGjVL4R6qnbojsLVapm9vjdPHsG3f3e9OH3X74KD488PMS61thQiVBH45bEWY9aKAyxHNzfkvRBo9rx/FCD2XJuggoUAlfhMY7YtW+BaIL/FcmJgEiABZRE4cisUHVZd0EvKr58XcqZ1U1aizIYESIAESIAEZCLAfahMoC0chgMsCzdA6vAODj9+dIADLKlpU+9fAhf2heD46lHQar4OS2M/dXoNgGc5L7ND+hD6Est7ddCL08t3CxL+5JG7L6ovKLm2pM6n7C0N+uzUCP6JsmVDzgP7zZ73zwIEV6gI1evXgknmJd5wq1jRojkxOAmQgHIIdF59AQdvhgoJFc2SAtu6lVNOgsyEBEiABEiABGQmwAGWzMAtFI4DLAuBN1fYbwdYWbJkgaenJw4d+voGMw6wzEWdume238PpjcMBrfg2rIaDRyN7keJmh/P5w3ss7txKL07XpWuROFnyH8Z+/uk5amytobte+7wGbfzEAVbiEiWQdfUqs+f9swAP6jdAVFCQYOIxeRJS1K9v0ZwYnARIQBkE3n6KQqmJflBptEJCExsURPNSWZSRILMgARIgARIgAQsQ4ADLAtAtEJIDLAtAN2fIUaNGoUSJErp/0qVLh5CQEGTPnp0DLHNCpzaOrb+DCztiD1IXz2NpNmYqMnrmMzudqIgIzG/bRC9OxwUrkCyN+w9j33hzA3/t/Ut3vUWAGvXOihvBZLVrIePMmWbP+2cBHrdrh8+nzwgm7gMGIHX7dhbNicFJgASUQWDlqYcYs/uWkIyzkyMCh1dFMpeEykiQWZAACZAACZCABQhwgGUB6BYIyQGWBaDLGZIDLDlp22+swytu4NrBwXoA/p42H2myZDM7FLVKhdkt9O9OajNzEVJn/PFbBI8/PY7ufl/Pzeq+Ww2vG+IAK9XfrZFuiPhWQ7MX8J0Az/r1R/jevcKV1B3aw71/f0ukwpgkQAIKI1B7zgncehEuZFXv1wyY06yIwrJkOiRAAiRAAiQgLwEOsOTlbaloHGBZirxMcTnAkgm0nYfZPfcc7p4ap0eh44KVSJYmrSxkZjWvB41aPIi95eQ5SJc95w9j77i3AyNOjdBdH7ZejcIh4gArbb++SNOxoyx5/yjIy4kT8X7VauFy8oYNkWHiBIvmxOAkQAKWJ3DzeRjqzD2pl8jq9iVRIbc8a63lCTADEiABEiABEvg+AQ6w7OOXwQGWjfeZAywbb7BCyts8OQCPL8/Qy6bHyk1wTpxYlgzntWmC6C8RQqy4Hl9ccWMFZl2cpbOftkyFrOJ56VDCeVNvFi/G69lzhHrcvLyQ2XuxLCwZhARIQLkExu6+hRWnHgoJeiR3wclBlZHA8ccvcFFuNcyMBEiABEiABKQjwAGWdCyVrMQBlpK7I0FuHGBJAJEScRJYO3IPXt75dsDigL7rd8LB0TFOXykMFnVqiYiwD4JUo2HjkK3Qjx+pmR44Hb63fHX2y2arkOyLmEXmZcvgVt6yb/N6v2kTXo4cJSTlUqgQsm/aKAUqapAACVgpgWiVBqUn+eHdZ/GswR6VcqF/jbxWWhHTJgESIAESIAHpCHCAJR1LJStxgKXk7kiQm9QDrNiF4WefFy9eoGTJkjqTJ0+eIFOmTBJUQQmlE/AZuAlvH4lv7nNK5IreqzfLlvaynu0R9kp8pXy9ASOQq3ipH8YfdnIYdt3fhQRqLdZPFR89jHXIvnMnXPLmkS337wX6eOQInvboKVxKmDEjcvkdsWhODE4CJGBZAgdvvkTn1Rf1kgjo/xuyp0li2cQYnQRIgARIgAQUQIADLAU0QYYUOMCSAbIlQ0g9wHJwMPwxBQ6wLNl5eWMv6eWLj6HiwMo1WSp0WyoOtMydjU+/bnj79LEQpk6vAfAs5/XDsF2OdMGpZ6eQKlyLxQv0B1i5z5yGU8qU5k75p/oRly7jUfPmgo1D4sTwvKS/cbVoggxOAiQgO4GOqy7g8C1xUF88a0ps6VpW9jwYkARIgARIgASUSIADLCV2RfqcOMCSnqmiFDnAUlQ7bDaZBZ0XIfKD+Na85OkyocNc+c5sWjPkH4Q+CBb4Vu/SCwUrVf8h7ya7m+D2u9vI8UKLyT7fDLCcnOB57apsjz7+KMHokBDcr1lL73Ley5fg6Opqs78hFkYCJPBjAq8+RqLsJH+oNOILJ6Y0KoimJbIQGwmQAAmQAAmQAAAOsOzjZ8ABlo33WeoBFh8htPEfTDzK02q1mNtuNlQRfoK3e7a8aDVF/1D3eEgb7LJx9GA8vX1DsK/crguK1Pj9h/7VtlTDy88vUSxYg0FbNIKdU/r0yH00wOC45jJUh4fjbkn9RyBjHyGMfZSQHxIgAfsjsCDgHqYdvCMU7pLQEYHDqiKpS0L7g8GKSYAESIAESOA7BDjAso+fBQdYNt5nqQdYceHiwhEXIdu7Hh2pwqIu06H6Ir7aPXP+ImgycpxsxW6dNAohV8RH7Cq2aIsSfzT6bvzYgVvxNcURrYlGlSsadN4vDrBcChRA9i3ynd31I0CxOQYVKgzExAgm2TZvgmvBgrIxZSASIAFlENBotKg4LQBP34tvm2hcLBOmNS6sjASZBQmQAAmQAAkogAD3oQpoggwpcIAlA2RLhuAAy5L07SP257AoLO01BerI80LBuUqWR71+g2UDsGvGRASfPy3EK/PnXyjbuMV343+M/oiy67+eG9PopAZNT4gDLLdKlZB50ULZ8v5ZoOCKXlC9eiWYZPZeDDevH5/rpYikmQQJkIDkBI7eeYU2KwP1dLd3K4siWSx7Vp/khVKQBEiABEiABEwgwAGWCfCsyJUDLCtqVnxS5QArPtToYwyBD6ER8BkwAeqoq4Jbwco1Ub1zD2NkTLI9sHA2bh4T39JXrE59/Na6w3c1H3x4gHo76+mutT+gRo3L4pkyKRo3hse4sSblIpXzgwYNEXX7tiDnMWkSUjSoL5U8dUiABKyEQKdVF3Dom8Pbf/FIhn29ysOYl6pYSalMkwRIgARIgATiTYADrHijsypHDrCsql3GJ8sBlvHM6GEcgdCQcKwbMRaa6CDBMfbxvdjH+OT6+Pt44/L+3UK4ApWqo0aXXt8Nf/bFWXQ81FF3rf9WNUreFQdYabp1Q9pePeVK+6dxHrdrj8+nxbvK3Af0R+r27RWRG5MgARKQh0BoeCTKTvaH+pvD28fVL4BWpbPKkwCjkAAJkAAJkICVEOAAy0oaZWKaHGCZCFDp7hxgKb1D1p/f45tvsXXSGGhiHgjFlG/WGqUaNJGtuFMbV+Psto1CvDyly6PuP99/hHHX/V0YdnKYznaijwq5Xohpph81Ein/+ku2vH8W6NmAgQjfLQ7lUrVvh3QDBigiNyZBAiQgD4G5fsGYefiuECxxogQ4N7QKD2+XBz+jkAAJkAAJWBEBDrCsqFkmpMoBlgnwrMGVAyxr6JJ153g38CX2zB4FreqZUEhcbwGUuuLAXVtxfO1KQTZb4aJoNPT7jwIuu74Mcy7N0dl6z1Uh5Wcxm0yLFiJppUpSpxcvvdBJk/DOd5Xgm7x+fWSYPCleWnQiARKwPgKxd11VmOKP52GRQvLNSmTG5EaFrK8YZkwCJEACJEACZibAAZaZAStEngMshTRCqjROnjyJe/fuCXJv3rzBgP+/a6NcuXLo0EH/XKA2bdpIFVqnw4VDUpxWIXYt4CmOLB0Brfq1kG+t7n2Rr2Jl2fK/eng/jixbIMTzyOOJ5uOmfzf+xHMTsT5oPRKotVg7VQ3Hb6yy79gOF09P2fL+WaA33kvwetYswSSJV0Vk8fZWRG5MggRIwPwE/INC0c7ngl6gXT3KoVCmFOYPzggkQAIkQAIkYGUEuA+1sobFM10OsOIJTqlusQMpX19fg9PTasXzfwx2+okhFw4pKFqXRuDehzixZhi0mnAh8XoDRiBX8VKyFRJ06hj2zp0mxEudKQvazPj+2wT7BPSB32M/pP2gxYJFar0c85w9gwQplLE5fL95M16OGCnk51KgALJv2SwbUwYiARKwLIEOvoE4clt8E2mBjMmwp2cFyybF6CRAAiRAAiSgUALchyq0MRKnxQGWxEAtLccBlqU7YH/xT2y6i/PbhgDaKKH4JqMmIXO+grLBeHA5ENsnjxHiuaVOg84Lfb4bv/ne5rj+5jo8n2gxdo04wHJwdUXeSxcV82avj35+eNpdfJOjUwYP5Pb3l40pA5EACViOwPMPX1B+ij++ObsdExsURPNSWSyXFCOTAAmQAAmQgIIJcICl4OZImBoHWBLCpBQfIbTH38ChFTdw/eAQAOLdfK2mzIV7thyy4XgadBMbRw0S4iVyTYyePpu+G7/q5qoIjQhFuZsa9N6lEX2yZ0fO/ftkyzmuQF+uXEFIM/FAeYdEiZD36hXFDNjiyp/XSYAE4k9g1uG7mOMXLAgkiT28fVhVuDk7xV+UniRAAiRAAiRgwwQ4wLLh5n5TGgdY9tFn2arkwiEbasUE2jUnEMGnxbufYhNrP3cZUqRLL1uOrx89xKqBPcV4Dg7ou24nHBy/PeEKUGvUKLamGNRaNeqd0aDFUXGAlaRsGWRZsUK2nOMKFPP8Oe5VrqJnpqRHHOPKn9dJgATiRyBKpUb5KQF4/VG8qzX2zqvYO7D4IQESIAESIAES+D4B7kPt45fBAZZ99Fm2KrlwyIZaMYE2jPPHsxsz9fLptmwdXJMmky3H8NevsLRHO714sXdgxd6J9e3ndcRrVN789XD5dgfVqHlJvGssecOGyDBxgmw5xxVIGx2NoEKF9cyy79oJlzx54nLldRIgASsmsO3SU/TddFWvgn29KiBfBvnWVCvGx9RJgARIgATslAD3ofbReA6w7KPPslXJhUM21IoJ5DNoN96G6L8dr8/aHUjgJN+jLpGfPmFB+2Z6TDot9EHS1Gn0vrv59iaa7flqN2CLGiWCxQFWmm7dkLbXN3dxKYDw3bLloH73Tsgk87JlcCtfTgGZMQUSIAFzEIh9sUrd+Sdx45n4UoxS2VNhY+cy5ghHTRIgARIgARKwGQLch9pMK39aCAdY9tFn2arkwiEbasUEWtxjPT6/Xivk45TIGb1Xb5U1P41ajVnN6+nFjH0LYezbCL/9BDwOQK+AXrqvJq9QIUeoeDX9uLFI2bixrHnHFexB/QaICgoSzDwmTkSKhg3icuN1EiABKyUQGPIOjRef0cveu1Ux1Mgv3yPZVoqOaZMACZAACdg5Ae5D7eMHwAGWffRZtiq5cMiGWhGBtBot5nVciphPu4R83FKlRedFK2XPb07rRlBFiWfG/DVuOjLk8dTLY2PQRow/N1733bLZKiT7Il7OvHQp3CqUlz3vnwV83KkTPh8/IZik7dMHabp0VlSOTIYESEA6At3WXsS+6y8FwcypXHG0fyUkcHSQLgiVSIAESIAESMAGCXAfaoNN/U5JHGDZR59lq5ILh2yoFREo8nMMvHsshCrisDhkyZoTrafOkT2/xV1a4/N78XG7RkPHIlvhonp5zLs8D0uuLUHCGC3WTlfrXcuxZzecc+WSPe+fBXw+fDjCtoh3s6Vs3hzpR45QVI5MhgRIQBoCT99HoOLUAGjEJ5sxvM4v6FBBvje6SlMJVUiABEiABEhAfgLch8rP3BIROcCyBHUbjsmFw4ab+53SPryKgO/AuVB9OSlczVqoGP4cpv9WQjmorPinC94/fyqE+r3PYOQto39H1YhTI7Dj3g6kf6fFXG/9AVaeCxeQwC2JHKkaHOP13Ll4s3CRYJ+0WlVkmjfPYH8akgAJWA+BSftuw/v4AyHhJIkS4MzQKkjmktB6imCmJEACJEACJGAhAtyHWgi8zGE5wJIZuK2H48Jh6x3Wry/0YTjWj5oBddRF4cIvFSqhdo9+soNYO/QfvLwfLMSt3rkXClaurpdH58Odcfr5aeQP0WDUeo1wzTFpUuQNPC97znEFfL9hA16OFoeBLoULIfvGjXG58ToJkICVEYiIVqH0RD+ER6qEzP8ukxVj6hWwskqYLgmQAAmQAAlYhgD3oZbhLndUDrDkJm7j8bhw2HiD/1PeoxtvsW3KFGiibwlXitWpj99ad5AdxOZxw/D4hvjq+dgcYnP59tNgZwPc+3APXtc06L5XHGA5586NHLvFc7xkT/4HAT/6++Npt+7CVScPD+QO8FdKesyDBEhAIgKrzz7CiB039NQC+v+G7GmUdVeoROVShgRIgARIgAQkJ8B9qORIFSnIAZYi22K9SXHhsN7exSfzO+deYt/c8dCoQgT38s1ao1SDJvGRM8ln5/QJuBcovr2rzJ/NUbZxcz3NcuvLITw6HA1PadDsuDjASlKxArIsWWJSfHM4f7l+AyHfvhnRyQme167CwdHRHOGoSQIkYAECGo0W1WYdw/3Xn4XolT3dsaJNCQtkw5AkQAIkQAIkYJ0EuA+1zr4ZmzUHWMYSo/1PCXDhsK8fyFX/J/BbNhpadahQeLVOPVGoSg3ZQRxYOBs3jx0R4v73TrBIVSRKrP26Iey4X41qV8STklM0aQKPsfKf2xUXpJjQV7jn5aVnlvvUSTilTh2XK6+TAAlYCYGAoFdo6xOol+2a9qVQPncaK6mAaZIACZAACZCA5QlwH2r5HsiRAQdYclC2oxhcOOyo2QDO736Ak+uGQ6sJFwr/o/8w5C5RRnYQ/j7euLx/txC3QKXqqNGll/D3k/AnqL29tu7vwRvVKPpAHGCl7d0Labp2lT3nuAJqVSoEFSoMaMS7xbJv3waXX36Jy5XXSYAErIRAk8VncD5EfINqnnRuONinIhwcHKykAqZJAiRAAiRAApYnwH2o5XsgRwYcYMlB2Y5icOGwo2YDOL7xLgK3DQIQIxTebMxUZPTMJzuIUxtX4+w28YDzPKXLo+4/g4U8Lry8gLYH2+r+nr5MhSyvxRQ9Jk5EioYNZM/ZkIDBFSpC9VpMNrP3Yrj9564sQ3RoQwIkoDwCgSHv0Hix+OhzbIZTGxVCkxKZlZcsMyIBEiABEiABBRPgPlTBzZEwNQ6wJIRJKYALh339Cg4suYKbfsP1im47azFSZcgkO4jAXVtxfO1KIW62wkXRaOhY4e99D/Zh0InYYRuwYpYKbpFiillWrkCSMvLfNWYIpIeN/kTkzZuCafpxY5Hy23OxDBGhDQmQgCIJtF15HgF3xAG1R3IXHBtQCYmceM6dIhvGpEiABEiABBRLgPtQxbZG0sQ4wJIUJ8W4cNjXb2Db9GN4GDhNr+huy9fD1S2p7CCuHTmAw0vnC3E98nii+bjpwt/Lri/DnEtz4BKlxaqZar38cuzfB+fs2WXP2ZCAT7p2w6eAAME0Tc8eSNtdfDOhIRq0IQESUB6Bm8/DUGfuSb3ERv6eD+3KK3MtUh5BZkQCJEACJEACIgHuQ+3j18ABln30WbYquXDIhloRgdaO2IWXd8W39zk4OOKfdTss8pa8oFPHsHeuOExLnSkL2sxYKHAafXo0tgZvRdZQLaat+GaA5eCAvFcuw9HZWRFM/5vEi1Gj8WGj+GhkiqZN4TFmtCJzZVIkQAKGE+ix7hL2XHshOKRKkggnB1VC4kROhovQkgRIgARIgARIQEeA+1D7+CFwgGUffZatSi4csqFWRKDlfdfiw7P1Qi7OiZOhx8p1FsntweVAbJ8svknQLXUadF7oI+TS8VBHnH1xFiXvaNB/m3goulP69Mh9VLzDySLJ/yTo6wUL8GaeeGeZW6VKyLxIHMwpLV/mQwIkEDeBh28+o8qMo9CI75JAv2p50LNK7ridaUECJEACJEACJPA/BLgPtY8fBQdY9tFn2arkwiEbakUEWthlMb683yPkkixtRnSc722R3J4G3cTGUV/PuIr9JHJNjJ4+m4S/a2+rjScfn6DuWQ1aBYgDrMQlSiDr6lUWydmQoO83bcLLkaMEU5f8+ZF96xZDXGlDAiSgUAKDt17DhsAnQnZuzk44NagykidOqNCMmRYJkAAJkAAJKJsA96HK7o9U2XGAJRVJ6ugIcOGwnx+CRqPFvPYzoIo4KhSdLucvaDlR/0wsuYi8fhyCVQN6iOEcHNB33U7d44xqjRrF1xaHSqNCxwNqVLss3vaQvFFDZJgwQa40jY7z8ehRPO3SVfBzSpsWuU8cN1qHDiRAAsog8DIsEhWm+iNGLa5Dnb1yYEitX5SRILMgARIgARIgASskwH2oFTYtHilzgBUPaHT5MQEuHPbz64j8FIPF3SdDHXlOKDpH0dJoMEj/rYRyEQl//QpLe7TTCxd7B1bsnVgvPr1A9a3VddeGr1ejUIi4cUzbpw/SdOksV5pGx4m8dQsPGzYS/Rwd4XntKhyceE6O0TDpQAIKIDB+zy0sO/lQyCT2jYOxZ1+5J3VRQHZMgQRIgARIgASskwD3odbZN2Oz5gDLWGK0/ykBLhz28wP5EBoBn/7joY6+JhRdsEpNVO/0zV1QMuKI/PQJC9o304vYaaEPkqZOg8CXgWh38Otwa/5CFdzDRLOMM2cgWe3aMmZqXCjVmzcILl9BzynXsWNImM7dOCFakwAJWJzA649RqDg1AF9ixBdJtCydBePrF7R4bkyABEiABEiABKyZAPeh1tw9w3PnAMtwVrQ0gAAXDgMg2YjJywdhWD9yNDQxwUJFpRs2RbmmrSxSoUatxqzm9fRix76FMPZthNuDt2Pk6ZFIoNZi7TQ1HL85ODnb5s1wLVjAIjkbElSr0SCoYCFALW54s23eBNeC3PAawo82JKAkAqN33YTP6RAhpQSODjja/zdkTpVYSWkyFxIgARIgARKwOgLch1pdy+KVMAdY8cJGpx8R4MJhP7+NkOtvsG3ycGhVT4WiK7XphKK1/rAYhDmtG0EVFSXE/2vcdGTI44n5l+fD+5o30v8fe+cB31T1xfFf96Ite5S9RRmCKFMFBBT3QFFEVEBBEcStKAJOFAcoCAg4gT9DcQAiQ1my994bChRKaelOk/w/54WkSUnapH15Wb/LJ5/Q5L57zvme927ePe/ecy8a8dWk/ECQVGywfh1C4uM9prMzgg926oS8xDOWqlXHjkXc7aYlkSwkQAK+QeD0pSx0HL0cufr8TSQeaVkNn3Zv5hsGUEsSIAESIAES8GICHId6sXNUVI0BLBVhsikmcQ+kc2D/ujNYMPZNGA3JFrPvHPQqGrXv4DEMEwf0RkbKRYv8h4a+h1rNWuCtVW9h/pH5aHbYgLdn5w8eg+Pj0XD9Oo/p66zg40/0RubGjZbqFV9/HeX6PO3s4axHAiTgBQTe+GUHZm3K33kwLCQIy17tgGplOPvKC9xDFUiABEiABHycAANYPu5AJ9VnAMtJUKzmHAF2HM5x8oda2/85iaWTXwGMmfkBo7ffR62mzT1m3ncvDUBKYv6MsLuHvImGbdrjib+ewLbz23D7ZgP6Ls4PYEU2bozav8zxmL7OCk588y2k/v67pXqZnj1R+d1hzh7OeiRAAh4mcOR8Orp8uRJ6Q/765afa1sKIe6/zsGYUTwIkQAIkQAL+QYDjUP/wY1FWMIBVFCF+7xIBdhwu4fLpyuv+OITVM14pMwczAAAgAElEQVQCkD8g6zVqLCrVrusxu6YPfQlnD+fn5OrafzCadOqKTrM74XzWefReqsfdG/P1jbuzG6p+8YXH9HVW8Pmvx+HC+PGW6qVuvRXVJ0109nDWIwES8DCBQf/binnbEy1aRIYFY+Xr3HnQw26heBIgARIgAT8iwHGoHzmzEFMYwAoMP2tmJTsOzVB7XNDiqZuxc/FwGz3Mu/55Srk577+NE7u2W8R36N0P191+B26cfqPy2Wu/6HHjwfwAVrn+/VHxpSGeUtdpuZd++x1n3nrLUj+8Xl3UnT/f6eNZkQRIwHME9p5JQ7exq2wUGHBrXbzZ7RrPKUXJJEACJEACJOBnBDgO9TOHOjCHAazA8LNmVrLj0Ay1xwX9+slSHNsyxkaPF3+ei9DwcI/p9ufnH+HghjUW+W2690Tlrq1x3++m3Qk/m5yHGhfy1avy4Qco/dBDHtPXWcEZGzbgRO8nLdWDoqLQcMtmBAUFOdsE65EACXiIQL8fN2Hp3nMW6bERoVj1RkeUjvZcX+khFBRLAiRAAiRAAm4jwHGo29B6VcMMYHmVO3xfGXYcvu9DZy348c1fcOHoD5bqIWERGDLtV2cPd0u9v78Zg90rllravuGu+xHcqQEG/jMQMBrx82d6ROTli67x04+Iuekmt+iiZqO6xEQc6nSbTZP116xGaNmyaophWyRAAioT2HoiBQ98kx9Ul+Zf7tIAg2+rr7IkNkcCJEACJEACgU2A49DA8D8DWIHhZ82sZMehGWqPC5rw/FRkJv9m0SOmdHkMmJQf0PKEgv/+MAlbF86ziG7csSsudqiAj9Z/hDKXjZg0Tm+jVr3lyxBWubInVHVJplGvx75m1wN5+dG3WrNnIappU5faYWUSIAHtCBiNRjw8cS02HU+xCC0bE67kvioVEaqdIpREAiRAAiRAAgFAgOPQAHAyAAawAsPPmlnJjkMz1B4VpNcZMO7Zr5GXucSiR/kadfHk6LEe1Wv1rJ+xbu4siw4NWrfH/vah+HHPj7jmpBHvTcsPYAWFh6Phtq0ICg72qM7OCj/UpSt0J09aqlf98gvEdevm7OGsRwIkoDGBP7cnYvD/ttpIffvORnjmljoaa0JxJEACJEACJOD/BDgO9X8fi4UMYAWGnzWzkh2HZqg9KijtQha+f2Us8rL/s+hRs0kLdH/nPY/qtXHeXKyc9p1Fh1rNWmBVmzT8c+IfdNhhwPMLDJbvwuvWRd0FvpMI/fhTTyNz3TqL/hVeeRnln3nGo7wpnARIwD6BrFw9bvt8ORJTsy0VqpeNwpKXbkVkWAixkQAJkAAJkAAJqEyA41CVgXppcwxgealjfFUtdhy+6jnX9D5zOBWzRo6GPmeb5cBrb+mEbgNfdq0hlWvvWPo3lkweZ2m1SoNrMOuGgziSegS9/tXj3vX5OxCWuu02VB+fX1dlVVRvLvHtt5H661xLu6Uf7YEqI0aoLocNkgAJlJzAmKUHMGbpQZuGJva6AXc09v4lyyW3ni2QAAmQAAmQgPYEOA7VnrknJDKA5QnqfiyTHYcfO9fKtEObkzDvyw9h0B22fNr6wR5o1+MJjwLYv3YV5o/5JD/IUyUB41psRJ4xD2/O0qPFkfwAVrkB/VFxyBCP6uuK8AsTJuD82K8sh8S0b48aUya70gTrkgAJaEAg8VIWOn2+HNm6/BmfbeuWw/R+rbhzqAb8KYIESIAESCAwCXAcGhh+ZwArMPysmZXsODRD7VFB2/85iX+mjoBRn781fJdnXkDTznd4VK+Tu3dg9ntDLTqERUdhcod9yt/jx+ehQlq+egmffYb4u+/yqL6uCE/9808kvv6G5ZDw2rVRd+FfrjTBuiRAAhoQkLxXkv/KXIKDgL9evBnXVI7TQDpFkAAJkAAJkEBgEuA4NDD8zgBWYPhZMyvZcWiG2qOC1sw9hLWzhwLGTIseD745ArWbt/SoXsmnTuCHV5630eGn248jIs+IH7+w3YGw9h+/I7JhQ4/q64rwzC1bcLzn45ZDgiIiTEnog4JcaYZ1SYAE3Ehg47GLys6D1qVX6xr44P4mbpTKpkmABEiABEiABDgODYxzgAGswPCzZlay49AMtUcFLZq8DbuWvmOjw5Ojx6F8jVoe1Svrchq+6dfTRofZHU+h6sU8fPiTVQArJAQNt25BcHi4R/V1Rbju3DkcurWDzSH1Vq5AWMWKrjTDuiRAAm4iYDAYcd/41dh5OtUiIS4yFMtf64iyMb7T17gJD5slARIgARIgAbcS4DjUrXi9pnEGsLzGFf6hCDsO//BjUVbM+XgJTmwba1Pthe9nISI6pqhD3fq90WDAmF4PwKDPD1bNa3cGTY9l47m/rHYg9MHld2Lb/mbXw6jTWRjW/N8MRDdv7lambJwESMA5Aj+tPYZ3/9htU3n4Pdfi6Xa1nWuAtUiABEiABEiABIpNgOPQYqPzqQMZwPIpd3m/suw4vN9Hamj43aszkXJymqWp0PBIvPjzL2o0XeI2Jg7ojYyUi5Z2lrQ8h9t2ZODujfkJ3GO7dEG1r/MTopdYqEYNHL79DuQeP26RljB6NOLvuVsj6RRDAiTgiIAkbu/yxQpk5OYHz+tVLIWFL96MsJBggiMBEiABEiABEnAzAY5D3QzYS5pnAMtLHOEvarDj8BdPFm7H+GfHIzt1oaVSXMWqeObrSV5h/E9vDMb5Y0csuvzX5AIeWZ2G64/mB7DKP/8cKgwe7BX6uqLEiT59kbFmjeWQCkNeRPkBA1xpgnVJgARUJmA0GtH3x034d1+STcsznmmFtnXLqyyNzZEACZAACZAACdgjwHFoYJwXDGAFhp81s5Idh2aoPSYoNzsPE/qPRl72aosO1Ro1Q48RH3pMJ2vBv370Lo5t32L5aFPDFAxceBHlLufXqvrF54i7806v0NcVJc4MH4FLs2ZZDom//34kjPrYlSZYlwRIQGUCsuOg7DxoXXq0rI5PujdVWRKbIwESIAESIAEScESA49DAODcYwAoMP2tmJTsOzVB7TFDK2Qz8+NqH0OfusOhwXYeuuOM575jRtHD8F9iz8l+Lbvurp+Kl+RdseNX+8w9ENmjgMYbFFXzxxx9x7uNRlsMjmzZF7dn5Aa3itsvjSIAEikcgJSMXnb9YgeSMXEsDFWIjsPSlWxEfHVa8RnkUCZAACZAACZCAywQ4DnUZmU8ewACWT7rNe5Vmx+G9vlFLs1P7LmLO+8NhyDtqabLtI4+jzUOPqSWiRO2smPYdNs2ba2njfOl0PLniXH6boaG4ZstmBPnQDoRm5dP/W42T/fpZbAmOjkaDzZsQFBRUImY8mARIoHgEXp69DXO3nLY5eMLjLdCtSZXiNcijSIAESIAESIAEikWA49BiYfO5gxjA8jmXebfC7Di82z9qaLd//VksGPsmjPr8WU23PzcEjTt0VqP5Erexcd5crJz2naWd7PAsPLgx0fJ3eL26qDt/fonleKIB3dmzONSho43oesv+RVgVDpY94Q/KDGwCKw+cR+/vNthA6HptJUx64gYGlQP71KD1JEACJEACHiDAcagHoHtAJANYHoDuzyLZcfizd022bVl0HMu+fxkw5liM7f7OB6jZ5HqvMF6WD8oyQnMxIgd3bT9l+Tv2jjtQbcyXXqGrq0pIsugDLW+EISPDcmj1KVNQqn07V5tifRIggRIQSMvWoduYVTh9KSu/b4kIxdJXbkWluMgStMxDSYAESIAESIAEikOA49DiUPO9YxjA8j2febXG7Di82j2qKLd82g5snjfUpq2nv5yEsglVVWm/pI0c27YZv3483NJMsCEPd+w8bvm7/AsvoMILA0sqxmPHH32kB7J35Ocfq/TWmyj75JMe04eCSSAQCbw0axt+22q7dPCjB5qgZ6sagYiDNpMACZAACZCAxwlwHOpxF2iiAANYmmAOHCHsOPzf179/sRSH14+xMXTwT78gLMI7Zh0kHTuCn9+wSihvNKLbjiMwZ4mq9s14xHbq5LOOSnxrKFJ/+82if+mHH0aV99/zWXuoOAn4GoF52xMxqMCug23qlMP0fq0QHMx8dL7mT+pLAiRAAiTgHwQ4DvUPPxZlBQNYRRHi9y4RYMfhEi6frDzt7Zk4d2iaRfewyBgM/tF7dsJLT7mISQN627C9bfcxROTplc/qrVyBsIoVfZK9KJ08dSqSRn9m0T+qRQvUmjHdZ+2h4iTgSwRkyWC3MSuRlp1nUTs2MhSLhtyChNJRvmQKdSUBEiABEiABvyLAcahfudOhMQxgBYafNbOSHYdmqD0maMLz45GZvNAiP75SDfT76huP6VNQsEGvx5c977P5uP3+k4jLzkVolSqov+xfr9G1OIpcXr4cpwY8Zzk0OD4eDdatZdLo4sDkMSTgAgGd3oBHv12HzcdTbI4a++j1uO9671hC7YI5rEoCJEACJEACfkWA41C/cicDWIHhTs9byY7D8z5wpwa52Xn4pv8o6LPXWcRUb3wDHhk20p1iXW77k973IDTHaDnupsOJKJ+ehdiuXVHtq7Eut+dNB+SePInDXbraqFT/v1UILV/em9SkLiTgdwQ++XsfJiw/bGPXPc0S8PVjzf3OVhpEAiRAAiRAAr5GgONQX/NY8fTlDKziceNRDgiw4/DvUyPpeBpmvPMh9Lm7LYY27XInuvR73msM1xl0eP+ZuxGfHmbRqdnxc6h6KR0VXnkZ5Z95xmt0LY4iRr0e+29oCWN2tuXwGj/8gJjWrYrTHI8hARJwgsCy/Ul4+vuNNjVrlI3G/MHtEReZ39c40ZRvVMnNBM7vA5L2ACnHgUsngPRzQPYlIDsNMOoBowEIjQTCSwFRpYHYBCC+KlCuPlChoekVGuEb9lJLEiABEiABnyfAcajPu9ApAxjAcgoTKzlLgB2Hs6R8s96BjWexYMx7MOSdsBhwc8+ncNN93b3GoL3JezF12CBUSc5PKn/N6QuocyEV/hLoOfLgg8jZs9fCvNK7w1C2Z0+v8QEVIQF/InAiORN3f73KJu9VWEgQfn2uLZpWK+0fpmalAIeXAcfXACfWAUm7TQGqkpSQcKByU6BGa6BOB6BmWyA8piQt8lgSIAESIAEScEiA49DAODkYwAoMP2tmJTsOzVB7RNCG+Ufx3/R3YDSkWuTfOehVNGrfwSP62BM658AcrPjmG9Q+kz9QqpOUgmvOpqDBxg0IKVXKa3QtriKnX3sdafPmWQ4v07MnKr87rLjN8TgSIAEHBLJy9XhwwhrsPZNmU2PY3deib/vavs3t8jlg91xg9+/AqQ0lD1gVRUMCWnU6Ak26Aw3vBCJ8vy8uymR+TwIkQAIkoB0BjkO1Y+1JSQxgeZK+H8pmx+GHTrUy6e9vt2H3PxIoyc8v9fhHX6Jy3fpeY/jwNcNx6o9luPZYnEWnqhfTcGNEHOrOn+81epZEkQsTJ+L8mPxcXtGtWqHmjz+UpEkeSwIkUICA0WjEkFnb8Me2RJtv7mpSBeN6NvfNjRNk+d+++cCO2cDRFe4PWjk6q0KjgIZ3AE0eBup3BUL8cBkmrygSIAESIAFNCXAcqilujwljAMtj6P1TMDsO//Sr2appw+bh3IFJNkYO+nEOwiO9Z/v4h/58CBEbz+KGA2UselZIy0Dn69sg4eOP/MJBaUuW4PSgwRZbQuLjUZ87EfqFb2mE9xAY9+9BfLb4gI1C9SqWwu8D26FURKj3KOqMJkn7gPUTgR2zAF2mM0cACALK1gHKNwDK1ATiEoCoMkBEnCngFBQM6LKA3HQg4wKQlgikHAPO7wdS85eZFyksripwY1+gxVNATLkiq7MCCZAACZAACdgjwHFoYJwXDGAFhp81s5Idh2aoNRcksxG+GTAR2ZcWWGRHx5fHc996z8yfrLwstJnRBnVORKHdzvyBUFxmNh56rI/f5InSnT6NQ7d1tjkH6i5ehPAaNTQ/LyiQBPyRwMKdZ/Dc9C02pknQ6o8X2qFuBR9Z+mYwAAcXmQJXR5YX7SZJyF6zHVCrvSlvVZVmxc9ZlZ0KnN4MnFhvmul1UpYo6gvXQeTLjKzWzwGVritaX9YgARIgARIgASsCHIcGxunAAFZg+FkzK9lxaIZac0EZqTmYPPhT6LPXW2RXv645Hnn3fc11cSRwa9JW9F7YGw1ORKLtrkqWapG5eejz3meIatLYa3QtiSISTDzY/mbok5MtzSSMHo34e+4uSbM8lgRIAMCmYxfRa+p6ZOvyk5gHBwFTnmyJTtfk9yteC0ufB+z6BVj5GZB8sHA1ZQfBa+4GGj8I1L4FCHPTbFoJaO1fCOz8BTj8b9HBrIZ3AR3eMAXRWEiABEiABEjACQIchzoByQ+qMIDlB070JhPYcXiTN9TV5fSBFMx+byQMukOWhm+4+wF0eKKvuoJK0NqUnVMwdstYdNwaippnqlpaCjYY8eK0uQiO8J8t3U8+9zzSly2z2FjmiSdQ+e2hJaDHQ0mABPadTcMjE9fa7DgoVN65qxH63VzHuwHpdaYlghK4SjnqWNfgUFPeKUmm3qAbEB6trV0ZycCe34HtM03J4wsrkuz91jeAhOu11ZHSSIAESIAEfI4Ax6E+57JiKcwAVrGw8SBHBNhx+O+5sXvVaSz65k0YDSkWI28f8CIad+ziNUb3W9QP68+ux7N/BSEXtsvpBk6diUg/2IHQDLtgIveoZs1Qa9ZMr/EFFSEBXyNw8mImHpqwBkmXc2xUf/TG6vj4wSbem7RdlgrunA0s+wi4dNwx9uhywA1Pm/JNST4rbyintwDrJwG7fgUMOscaySyxziOA8t6zYYg34KMOJEACJEAC+QQ4Dg2Ms4EBrMDws2ZWsuPQDLXmglbN3ocNv75mswNhzw8+R5X6DTXXxZ7A7LxstPtfO+QacjF2oh5ba9jOluj96deoUNPHt723Mjx99Wqc7NvP8klQeDgabtoIeWchARJwjcD5yznoPnENjifbJjjv3KgiJva6AaEhwa41qFXtoyuBxe8AZ7Y7llipsSmvVOPuQFikVpq5JufyOWDTd8CGSUBW/kMSm0aCQoCWfYAObwIx5V1rn7VJgARIgAT8ngDHoX7vYsVABrACw8+aWcmOQzPUmgv69dPFOLb5Kxu5L3w/GxHRGi8/cWD52sS1eHbJs6iYYsS4iXr826gmssPzdwq75+W30KBVO825uUugPi0NB25qZdN8rTmzEdWkibtEsl0S8EsCadk69Ji0DnvPpNnYd1Otsvip702IDAvxPrtlp78l7wIH/nasW0Jz4NY3gQa3A0FB3meDPY1yLgMbvgXWjAOyLtrXOTwWuPkloPXz7svZ5Ru0qCUJkAAJkIAVAY5DA+N0YAArMPysmZXsODRDrbmgKS9NRWribxa5kaXKYODUnzXXw5HALzd/ie92fYfbthrQ/28D1tdJQHJsfkLi9o/2RqsHHvEafdVQ5PCddyH3yBFLU5XeeQdlez2uRtNsgwQCgkBqpg5Pfr8B205esrG3UZU4zHy2NeKjwryLQ3oSsPxjYPOPjhOhV7vRFLiqd5vvBK4KUlYCWZOBNV87DmTFVQU6DQOa9gCCvXSGnHedPdSGBEiABPyaAMehfu1ei3EMYAWGnzWzkh2HZqg1FWTQG/B134+Ql7XOIrdK/abo+cFHmupRmLAe83tgT/IevPSbHm32GbGzanmcLB9vOeS6WzvjjueHeI2+aiiS+MabSP3jD0tT8ffdi4RPPlGjabZBAn5PIDk9B09M3YA9BWZe1SgbjV+ea4OKsV603C43E1g7Hlg9BshNt++bCtcAXd4zJWj3lRlXRZ1lsnvhf2OAdd8Aedn2a1duCnT7BKjZtqjW+D0JkAAJkIAfE+A41I+da2UaA1iB4WfNrGTHoRlqTQWlnM3AD6++A4Muf0v2Zl3uQed+/TXVw5Gw1JxU3DzzZsBowOSxesRlAUfLx2Nv1fw8KQkNGuGx90d7hb5qKXFxxgyce+99S3PhtWqh7t8L1Wqe7ZCA3xI4l5aNx6esx6Ek22BQ+VIR+PW5NqhZLsY7bDfoTbv1/fsBcDnRvk4xFYGOQ4HmTwAh+cumvcMAlbRIPWViICxgtN/otfebAnhlaqoklM2QAAmQAAn4EgGOQ33JW8XXlQGs4rPjkXYIsOPwz9Ni37oz+Gus7ECYbDGwy7OD0PS2273C4CXHl+Dl5S+j9lkjPvler+iUFBuNTXWqWPSLjI3DwCkzvEJftZTI2rUbx7p3t2muwbq1CCldWi0RbIcE/I7AqZRMJXhVMGF7pbgITO/XGvUqlvIOmw8vAxYPA87ttK9PaBTQdhDQbjAQEesdOrtbC0lWL0yOrrAvKSTCxKT9S0CEl/jR3UzYPgmQAAmQgEKA49DAOBEYwAoMP2tmJTsOzVBrKmjZtD3YMu9NAAaL3EffG42qDRtpqocjYSPXjsQvB37BIyv16L7a9HQ+IzwMKxrVsDnk+SkzEBUb5xU6q6GEMTcX+2+8CcacHEtzVb8ai7iuXdVonm2QgN8R2H/2Mp7+fgMSU22Xo1UrE4UZ/VqjRjkv2JTi3B5TgvZDSxzwDwKufxzo9DYQl+B3PirSIKMROLTUtPvi+X32q8dWAW4bzvxYRcJkBRIgARLwHwIch/qPLwuzhAGswPCzZlay49AMtaaCfn7nTyQd/NZG5sDvZiIyxvNPuPMMebhtzm24mJWML7/Vo+qVjask1LaoWT0YrZabPPb+Z0hocI2m7Nwt7ESfPshYs9YipvTD3VHl/fxlhe6Wz/ZJwFcILNuXhEH/24r0nDwbleuUj8G0fq2QUDp/0weP2HT5LLDsQ2DrNGU5tN1SpwPQ9QOgMncbhT4P2Py9iVlWin1eVW8A7hgFVL/JIy6lUBIgARIgAe0IcByqHWtPSmIAy5P0/VA2Ow7/c6ouR48JA8ZAl7nMYlxMmQoYMPF7rzB2TeIa9F/SHzWSjPhsqmn5oLms6dgKly5esPx9x/Mv4bpbb/MKvdVSIvn7H5Bklbg9tHJl1Fv2L4L8JYmzWqDYTsASMBqN+H71MXywYA8MBdInNawUi5/73eTZhO25Gabd9lZ/Begy7PupQiNT4MqXdxZ01xmYeRFY8Ylp10Kj7W+ARWSTh4HOI4H4qu7Sgu2SAAmQAAl4mADHoR52gEbiGcDSCHSgiGHH4X+ePn0gBbPfex8G3QGLcY3ad8Kdg172CmOHrxmOuQfnoscKPR5akz86DU2ogl2334ojWzZa9Gz1QA+0f/QJr9BbLSVyDh/Gkbvutmmu9p9/ILJBA7VEsB0S8FkCOr0Bw//cjRnrT1xlw/XVS+P7p25EmZhwz9gnM4i2TQeWfQSkn7WvQ6lKQMe3TUsG/TVBu1r0z+8H/n4LOPyP/RYlZ1j7IUDbwUC4FywVVctutkMCJEACJKAQ4Dg0ME4EBrACw8+aWcmOQzPUmgna/PcxLP/hdcCYaZHZdcBgNOno+TxLOr0OHWZ3QFpOKsZO0qOK1SqSsn36YG+Vstg8/zeL3g1at8c9L0kuL/8pMrvk8G2doUvM36Gs4muvolzfvv5jJC0hgWIQOJOahRdnbsOGo1fWFVu1cW+zBHzavSkiw0KK0XIJD5EcTvsWAP+8B1zYb7+xsGhToEUSkjMZufPAhe3BxcCioUDyIfvHxVUDuowEGj8EcKaq82xZkwRIgAS8nADHoV7uIJXUYwBLJZBsxkSAHYf/nQm/ff4vjmz4wsawPmO/RZnKnk8evPLUSgz8ZyBqnTXi0yu7D5oVrTVnNg6eO40lk8dZdK9QszZ6f/q13znpzPARuDRrlsWu6FatUPPHH/zOThpEAs4S+GfvObw6ZztSMnVXHfJylwYY1KmeZ5bZHlsNLB0BnNpg35SgYKB5L6DDUCAufxdVZ+1mvSsE8nKBjVOA5aOAnFT7WKq3Bu74GKjagthIgARIgAT8gADHoX7gRCdMYADLCUis4jwBdhzOs/KFmjK7Z+Lz3yDz4kKLuhEx8Rg4dZpnBn8FoL3939v48/CfePxfPe5bn798MKxqVdRdugSn9uzE7PeGWo4KDY/A4B/nICg42BfwO63j5X/+wamBL+TXDwtDg7VrEVIqxuk2WJEE/IFATp4eoxbuU3JeFSwRocH4/JFmuLupB4Lv53YDS0cCBxc5xlyvM9DlPaDSdf7gCu+wIeOCKcn75h8cJ8Zv1hPo+BZQ2nbXWu8wgFqQAAmQAAk4S4DjUGdJ+XY9BrB8239epz07Dq9zSYkUSruQhakvvQtD7l5LO7VbtMWDb+QHhUokoAQHp+emo/MvnZGbmY4J4/WIy8pvrFy/vqj46qtIv5iMSc89aSPlmfHfI658hRJI9r5D9ekZONCmDaDLn21SbdzXiO3c2fuUpUYk4CYCB85dxsuzt2HX6bSrJFQtHYVvHm+BZtVLu0m6g2YvHAJWjgZ2yAzJAhnkzYfIjoKSYFwStLO4h8DZXcCit4CjK+23HxIOtOwD3PwKUKqie3RgqyRAAiRAAm4lwHGoW/F6TeMMYHmNK/xDEXYc/uFHsxUHNp7FvC9eBgz5A8JOfQag+e22ScM9YfW0PdPwycZP0HG7Ac/9ZbvlfJ0F8xFRty5kBtnXTz4MXU62RcXu73yAmk2u94TKbpV5/KmnkblunUVG3J3dUPUL26WfblWAjZOAhwjIrKvxyw5jwvJD0OmvDhLdcV1lfPJQU8RHh2mnoSQUX/kZsOsXxzN/ytQCOg0DrnsQ8LNZodqBdkGSOffY4reBlKtn6CktSe6x1s+Z8o9FaRzsdMEUViUBEiABEriaAMehgXFWMIAVGH7WzEp2HJqh1kTQgm/+w74Vo2xkPTl6HMrXqKWJfEdC9AY97vrtLpy+fAqffqdHraT8mjHt2qHG1CmWD35+40UkHTts+bvjU/3Rots9HtXfHcIvTpuOcx98YGk6KCwM9VetREhpDsLcwZttegeBTccu4o1fd+Dw+YyrFAoPDcawu9GE70QAACAASURBVK9Fr1Y1tFvynLTXNONq11zHM65iKgC3vgG0eBII9dAOiN7hPs9okZcDrJtgCjDmXravQ2Q80G4I0Ko/EM6l2J5xFKWSAAmQgGsEOA51jZev1mYAy1c956V6s+PwUscUQy19ngETB05C9qUFlqNDI6Ix+IeZHs8h9c+JfzBk2RA0OmHEyOl6G+uqTZyA2A4dLJ8tHPc59qxaZvnbH3ciFOPyUlJw6JZbYbRaRlhp2Dso+/jjxfA+DyEB7yZwIT0HXyw5gBnrT9hVtF7FUvj6seZoVCVOG0PO7jQFrvb84VheeCmg3YtA6+e5s6A2XilcSvp5YNXnwKapgD7Xfl0JNrYZCLTsC0RqdC55AxvqQAIkQAI+SIDjUB90WjFUZgCrGNB4iGMC7Dj85+w4visZc0eNhEF3xGJUzaY3ovvbwz1u5NN/P41N5zbh1V/1uOmAVfL2mjVQd+FCmwDbzmWLsXjiVxado+Li8dyknz0ehHMHxFMvvYTLC/+2NB157bWoPfdXd4himyTgEQLZOj2m/ncUE5YfRnpO3lU6hAQHof8tdTD4tvqIDAtxr46yJO3wP8CaccCR/CD5VUIlcHXTs6ZASEx59+rE1l0ncOkEsOITYNsMx8s9ZUZWqwGmV3RZ12XwCBIgARIgAbcT4DjU7Yi9QgADWF7hBv9Rgh2H//hy8dRN2Ln4PQD5+aVuf24IGnfwbGLw7ee3o9dfvVA30YiPf7SdfVVp6FCU7f2EjRNSk85iyqB+Np/1Hj0OFTy8DNIdZ0r6qv9w8plnbJqu/dtcRDZq5A5xbJMENCNgMBjx5/ZEjF60H6cvWe3YYKVB02rxGPVgU1yb4OaZMrpsU26rteOBpD2OGUTEmZagyYwrBj00O1eKLej8AdOOhXt+d9xEWAxww5OmgGTZ2sUWxQNJgARIgATUJ8BxqPpMvbFFBrC80Ss+rBM7Dh92npXqBr0BE58fh6xLiy2fBoeE4fkp0xERHe0xIyUpe6+FvbAjaTtGTNfj2pP5qgTHxqLesn8RUqrUVfpNfqEv0s6fs3ze8aln0aLbvR6zw12CjXo9DnXugrwzZywiyjz+OCoPe8ddItkuCbiVQJ7egAU7z2D8skM4cC7drqzIsGC82rUhnmpbC6Ehwe7T5+JRYPP3wJafgayLjuXIbB0JWknwKqqM+/Rhy+4hkLgN+PcD4NASx+0HBQMN7zTNqqvRBggKco8ubJUESIAESMBpAhyHOo3KpysygOXT7vM+5dlxeJ9PiqPRyX0XMee9N2HUJ1oOr9OiDR544+3iNKfaMQuPLsTrK1/HDQcNeOMX250HK772Ksr17WtX1qKJY7FrWf5gpG7L1rj/Nf8M6pz/6itc+GaChUNQZCTqLl6EsIrcGl61E5ENuZ1Abp4Bv209pSwVPJac6VDegy2qKsGrhNJR7tFJn2cKZGycChxa6jgxu0iPLn9lmdmzgASxWHybwOktphxZ++YXbkeV64GWfYDGDzG3mW97nNqTAAn4OAGOQ33cgU6qzwCWk6BYzTkC7Dic4+TttRZNXoNdSz+yUfO+14ahXstWHlM9Oy8b9/5+L5LSEvHZFD2qWk2ACEtIQJ2FfyE4IsKufpLEXZK5m0tEdAyenzoDwcFuzpHjAVq5p07j8O23A/r85ZWcheUBR1BksQicv5yDWRtPYPr6EziTmu2wjdZ1yuKdu65F46puChSd223KibRjNpBhtc2pPY3KNzDNxGnaAwhzUyCtWDR5kCoEZGfJVV+Ylo0abR+c2LQfHgs0fRi44WmgSlNVRLMREiABEiAB5wlwHOo8K1+uyQCWL3vPC3Vnx+GFTnFRpaz0XEwZ/AVyM/6zHCm7D77w3XSEhIa52Jp61cdsHoOpu6ai5zI97l+Xn7hdJCR89hni777LobDLFy/g2+eesvm+18djUKlOPfUU9KKWEt95B6m/WCVvDwtDvb8XIqxqVS/SkqqQgImALA3efDwFP687jr92noFOb3t9W3NqUKkUXr/9GtzWqCKC1F62lXratIvgjpnAme1Fu6f2LUCbF4B6XYBgNy5dLFoT1tCCQMoxYP0k0xLS3MuFS6zSDGj6qGlWVmwlLbSjDBIgARIIeAIchwbGKcAAVmD4WTMr2XFohtptglb/uhfr5owAjBkWGY3ad8Gdg150m8yiGl6TuAYDlgzAtcf1GDbDAOuhYmTjxqg1e1aRuwp+N6Q/Us6ctoi65fGnceO9DxUl2ie/1yUm4vDtd8Co01n0j3/wQSR89KFP2kOl/ZOAJGP/Y9tp/LblNA4m2c9vZba8SdV4vNCpHro0qoTgYBXzDaUlAnv+BHb/BpxcVzToiHig+eOmJWPl6xddnzX8j0B2GrB1GrB+InDpeOH2Sa6sOh2Bpo+YcmZFunmDAf+jTYtIgARIwGkCHIc6jcqnKzKA5dPu8z7l2XF4n09c0SgnU4fJg79EzuWVNoc99v5oJDTwzE52F7IuoPuf3ZFz8QJGf6dHOesH32FhqD1rJiKvvbZIM5dOGY/tSxZa6lVr1Bg9Rowq8jhfrXD2w4+Q8vPP+eoHBaHmTz8i+sYbfdUk6u0HBC5m5GLJnrP4betprDtSSCL0K7beWKsMXuhUH7fUL6/OjCujEZDlgfsXAgcWAqc3O0e1akvghqdMM2rCPbeRhXPKspYmBAx64OBiYPMPpvfClheKQiHhQJ0OQKN7TMGsmPKaqEkhJEACJBAoBDgODQxPM4AVGH7WzEp2HJqhdougtb/txppZ7wLGHEv7CQ2b4rH3bPNhuUW4nUYzdZkYsHQA9pzagmH/06NBfk55pXbF119HuT5PO6XOgfWrMe+Lj23q9ho1FpVq13XqeF+rlHfhAg516QpjVpZF9dAqVVDnj98REsdZAL7mT1/W9+TFTCzecw6Ld5/FxmMXYXC8QlAxMzw0GPc2S0DvNjXRtFrpkpueeRE4tgo4ssIUaEi12r60sNZjE4BmPYBmPYEKDUquB1vwXwKpp0xLC7f8BFwu8ENlz2qZmSW7F9bvAtTrDFRqzJ0M/ffsoGUkQAIaEeA4VCPQHhbDAJaHHeBv4tlx+K5H01Ny8MOro5GTbruM5vGPvkTlutovlcnR52DQP4Ow4dQavDHHgOuP2o56Y9q2RfUpk4tcOmj2SJ5Oh8kDn0Zm6iWLk669uSO6vfCK7zqtCM2Tp0xB0mf5yeuletyddyLh88/Umc3it+RoWEkIZObmYf2Ri/jv0AX8d/AC9p8rIl/QFWHVy0ahV6uaeKRldZSJCS++CjnpwIm1wJHlwNGVwNmdhe8eaC1Jlgg2uts000pmy/jhRg/FB8sjiyQgs7KOrjAl/5elqbr8pfiFHhtbBah3G1C7A1CzLRDPfIVFsmYFEiABEihAgOPQwDglGMDyYz8fP34cX331FRYsWICTJ08iIiICdevWxSOPPIKBAwciOlr9ZRDsOHzzhDIYjJj94Xyc3jUFQP7udTWbtUL3ocM0NypDl4HXVryGTYdXYsgfBjQ/Yhu8Cq1UCbXmzEZYxYou6bbu15lYPXua5ZjgkBD0GzcVsWX9cymHUa/Hiaf7IHPDBhtO5QcPQoXnn3eJHSuTgCMCl7N12HriEjYdT8H6I8nYciKl0ETs1u3ERobi7qZV8EDzamhZs4zr+a1kSWDKUeDUZuD0JuDUJuDMNsCQ57zDIuJMS7oaP2gKWoXa383U+QZZkwQA5GaYlqpKMOvIMkCf6zyW0jWBmu1MwSx5la3DGVrO02NNEiCBACXAcWhgOJ4BLD/187x589CrVy+kpaXZtbBBgwZKYKtePXV3YWPH4Zsn1NrfdmLNrA8Bo1Ui5aBgPP3FNyibUE1To06kncDgfwcj/dghvDFHj2rJtuJDSpdGzenTEFHX9aV/mWmpmPz808jT5Q8kbrr/Ydz82JOa2qilMN2ZMzhy3/0wFOgLKr76Csr166elKpTlBwRy8vQ4eC4duxNTset0mrJ74L6zaUUuC7Q2PSosBLc2qID7rk9Ax2sqIjIsxDkyEqxKOw2c22MKUp3aaMphlVmgk3CmtfgaQMNuQMM7TIECBq2cocY6xSWQnQocXALs/dP0rst0raVSlYGqNwCyu2HC9ab32MqutcHaJEACJODnBDgO9XMHXzGPASw/9PPWrVvRrl07ZGVloVSpUnjrrbfQsWNH5e+ZM2di8uTJitUSxNq0aRNiY2NVo8COQzWUmjW0d+0J/D3uIxjyTtnIbH7H/ej0tHYBDoPRgDn752Dspi/Rbv1l9FxuQGT+JnqKbkHR0aj5w/eIatq02HyWTB6HHUv/thwfHhWFxz8ag7IJ/rtkI23RYpx+8epdJMv26YOKLw1BUFhYsXnyQP8kYDQakZyRi8NJ6dh39jJ2nU7F7sQ0HEy67PTsKmsyZWPC0blRRXS9tjLa1y9fdNAqKwU4fwA4twtI2mMKWiXtBiQQUJwSGgXUbAPUvgWo3xWoeC1ntBSHI48pOQFdlikf26ElpmBWUTsZOpIoQS1zQKvCNUCFhkDZukBYZMl1ZAskQAIk4IMEOA71QacVQ2UGsIoBzdsPueWWW7Bq1SqEhoZi5cqVaNOmjY3Ko0ePxuuvv658Nnz4cIwYMUI1k9hxqIZSk4Y2/7UbK6Z9AaP+nI28irUb4fEPR0GW2Lm7yEB5/dn1+HrzVwjasB09VhlQ78zVUkPKlkW1ceMQ3aJ5iVRKPn0SP7z8nE0b5arVQM8PP0d4ZFSJ2vbmgy9On45z739wlYpRzZoh4dNPEF6zpjerT93cRECW/52+lIVjFzJw+HwGjpyX93QcOZ+OtGwXluEV0C80OAjNa5RG+3oVlIDV9dVLIyQ4KL+WzKaSIFXKMeDiESD5MHDx8JX3I0BW0TsUFookOAyodqMpYCWvai05y8pN5xCbLQEBuQ6SD5kCWbLRwPE1QHZ+nkaXW5bk8LL8UIJZ5RuY3svUMn0Wl8Ccbi4D5QEkQAK+RIDjUF/yVvF1ZQCr+Oy88sgNGzagVatWim79+/fHxIkTr9LTYDCgcePG2Lt3L0qXLo2kpCSEqTQDgx2HV54WVymVfikbf0/4E8e3z7VdNig7gEWXRt8x4xAdr8LuX4XgkB0Gl55YirnbpiNu9S502Wo/cCVNRNSvj2oTJiC8mjqzpP6eMAa7ly+10a5B6/a4c9ArCAn139lIyT/8gKRRn1ztldBQlOnRA+X6P+tyXjHfOOMDU8uMnDycv5yD8+k5ynvipSwlWHU6JQunUkz/T80qMM2xmKjCQoLQpGo8WtYqi1Y14tC6ihExuReBjCTg8lkg9bRp9z/ZrU1eshTQ1WVUhekWXd4UpKraEqh2A1C9FRAeU0xreBgJeIiAwQCc32sKZB1fbXpPt33AVGzNJKgbXw0oXQMoU9P0LjttxlYCZDaXJJKPLsuZicUGzANJgAQ8TYDjUE97QBv5DGBpw1kzKUOHDsXHH3+syFu3bp0lmFVQgVGjRilLC6UsWrQIXbt2VUVHdhyqYHRbI6nnM7B6zj84sPZv6HNPXCUnJCwSPYZ/hCr11d8yXmZaJWYkYn3iOmzfvgSZ69eh8YFcND1qvGqpoLVipR/ujopvvImQUuoNRnXZ2Zgx7FVcOHHMhkGlOvVx1+BXUaaKOoEytzmyBA2nzJyJcx9+BKPOTuAiNBSxHTsg/v77EdO6NYJj1GNeApV5qGytYDAiLUunBJwuySszV/m/vFIydEjOMAWprANWmbn5GzIUF2IQDCiFbMQHpSMeGSh95b1uKR3qxuahVlQmqoWno4zxEkIyzgPpSVdyUtluvFBc+XaPC48FKl1rygkkLwlcyQyTIKsZXqoKZGMk4CECygytw6YNCs5sBxK3AWd3ALlW+SrVVE2CXKUqmfJryUv+H1MeiCoDRJU1BbiU/5cx/V927QwOVlMDtkUCJEACxSbAcWix0fnUgQxg+ZS7ilbWvHwwJiYGly5dUpYR2itr165F27Ztla/effddjBw5sujGnajBjsMJSBpWyUrPxoldx3Bo006c2rsT6cn7AaP9bb0jS5VHj5HvoXy1GiXSUGfQISkzCefSzuDsyX24cGAHMg8fRN6xEyiTlIU6Z40o7UT+WlnSVnnkSMS0Ns0oVLuknE3E9LdeQk6mLY+QsDDIbKwmnboiocE1fjkjK2vXbpx++WXoTlwdxDRzlrxYUS1aKPnGIq+7DuG1aiKsalWEqJgzT22fero92c0zV29Ajs4ASXaek2d6z1b+zv8sK1cPmR2lvK78X4JN6Tl5yMzNQ3qOHpk58i7f5yE1U1focj4JMoUjDxHIRQR0iAjSKe+R8n/5zPJ3LmKQjZigLMQg58p7tvJZdFC2EqiSd6WOErTKQBwyEBLkxmBUYU4LDgXK1TcFqyRnVaXrTK/46gxWefpkp3zPEZBZWrLcVglobQXO7QYuHDDNatS6yJLFyNJAZDwQUQqQ4LLyXsr274jYK59deZc8XZKXTjZPCLvybv13SDivca19SXkk4AcEOA71Ayc6YQIDWE5A8qUqFSpUwIULF9CsWTNs27bNoeopKSkoW7as8v3DDz+M2bNnq2Kmr3Qce9atQlaGKYpiNBqu2G6E0WAaqMm7zBiSl6mOEbgyhjMa8mc1mL+XLbgsdZXjDXKQcsyVJmCUf/K5fG9p07Z9pa5ZptQy178iWxKd63PllYc8XR70Ovm/Dnq9AXk5OuRmZUGXnQV9bhb0ukwY8iSXRtGzMKJKV0LDLs0RHBoMfZ4OBl0uDHqd8n+ZqWOQz+Slz4Ne2s/KhDErS3khOwdB2TkIztYhLD0bMek6xGUAcVlAcDHGvUGVKyLi0e4I63Qrgq4EYM0MLU6wOlttRORXtNSw+Cj/E8v/zhzYjzXTp8Ggt88oWJbWJSSgVLnyiClTBhHR0QiNiERYRDhCIyIQGh6BoOAgBAUFF3gPQpDyVNr0bn9eSOFwrtbbrLapNTmf7PEw1xIUQeaTtsDVrWDKzoZ+3t8w/LMCyCv6HLE0ER0NlC+LoNLxgPw/JhpBUZGm9/BwICwURlmGGRYCQ0goEBYGY2gwEBQMY5CEWq5oFSTvQTDIe5DJEgOknnwu/6Q+TC/lOpJrDDBcua7kUrVmoPytfGcwXdPKu1xCRhgMesh1K5/L33r5Ti//N0CuKaWu/F+5Rs31Te1IfdFMvldeRiP0Utegt7Qt7Zg+EwsUK0R7hMCAEOQhNEis0St/h155D1HejQgN0ivHmD7XX6krx+mVz0zfyd8GhEGHcOgRdiUgFQY9wqFDWJAL/lOlp1exEZk1JcuYzEubJDglS5uU5U1VADmHWEiABIomkJsBpBwHLh0Dko+a3i+dANLOAHlZRR/vVTWCgBAJboWb3uUVGg5IUFtmiUl+zqAw0+wvm8/ke/MrxNR/yN9BV97Nf8txQdKG/J6afp9sX0Gmv5V6Vi+ld5fvgkz5xGyOs/rc3Kby6291B2D575W65u8UPeQzq995y4xSe3Wv1FPqm7+/8n9rmeZ2la/MjVu9m483H+rgbqXIU6PYs1+LOWuW8hy4pLg8i/SwTYWQ0HDE1LvOtYM0qu0r41CNcPitGAaw/Mi12dnZiIoyJaG+6667MH/+/EKtkx0KMzIy0Lp1a8iMLGeKdAyFlTNnzuCmm25Sqpw8eRLVqlVzplnN63z56OMwGIu5m5Xm2rpPYIgxAo1OJ6F68oXi3raoopwxyIhSVXJQunYmYqtmK/eEWpVz2TFYcPoapORGayWSckiABEiABEiABEiABEjA5wjE5+ai32+LvVJvBrC80i2qK8UAlupIPdfg+fPnUbFiRUWBHj16YObMmYUqU6lSJSWBuyR037lzp1OKB7nw1IMBLKeQeqRShD4a1ZMvoe7ZUwixM2tJC6XyIg2IqZiDslWyleBVaKR5JpwW0m1l6AzBWJlUGztSKl+ZP6O9DpRIAiRAAiRAAiRAAiRAAt5MgAEsb/ZOYOjGAJYf+VkCRjVqmPIXPfHEE/jpp58KtU7qyjF169bFoUOHnCLhPwGsXjAYS7BVtVO0vKdSEMIRnReFcpczUP38ScRnOZGESiX1daFGZJU2Iig2D2VK6VAhJhfR5XIRVkrvdTmXM/PCsDu1IvakVsKFHCYwV+kUYDMkQAIkQAIkQAIkQAJ+QIABLD9woo+bwACWjzvQWn0tZmD5zxJCXwlgWa9nN/8/BEEwvyS/kryCEGwMRpg+CGF6AyJ1eYjKzUaprHSUSz2HSJ3O4RJB63lPhmBAHwLogwH5vyHYeOUdMF75TB9qhCEUMIYagTAjgkNNr9BQA8LDDIiLyEOZsDzEhechLNKAkEiD1wWqnLnss/WhOJMViws50UjVReKyLgI5+lDkGkKUV44hFDpDiCnPUsE8F84IYB0SIAESIAESIAESIAES8CECDGD5kLP8VFUGsPzIsVrkwCoKl6+sPd6zZiVycrJhnlFmSrhtSnIpCbmDlfydps+kTv738rmEi6Se/D/EkqAzWKln/tz0f1NGTkkAamonxJzcSeop7UBJMqrIUBq0Svhpyed5JRH4lfiV6Jdf8gNcwVZbWVvXyU8wfkWGHSeaWrGf/DE/76eD722Os61z1YrTIpeg5h/vsKqwKjRjl8kHjoopZ6njCqZzwpGt1ugL1pEk41eSgSsJv01J+yWxt/k8ulqnIhJuFtTT3nLPIpleLdVxgviirnB1v1f0ED5XkqOb/n9lQwRJrn6FXbGklmBprMf4lEDnYjHiQSRAAiRAAv5BwLTbSf7mLta/J+bPbX5jCtYtxq471uRK/PtVAvmelO3ps8cDtjOJu6edTvkMYPnZOVC+fHkkJydzF0I/8yvNIQESIAESIAESIAESIAESIAESsE/AVyZS0H8lI8AAVsn4ed3Rt9xyC1atWoWYmBhcunQJoaH2tyCXXQfbtm2r6P/uu+9i5MiRqtjCjkMVjGyEBEiABEiABEiABEiABEiABEjASQIchzoJyserMYDl4w4sqP7QoUPx8ccfKx+vW7cOrVq1smvhqFGj8NZbbynfLVq0CF27dlWFBDsOVTCyERIgARIgARIgARIgARIgARIgAScJcBzqJCgfr8YAlo87sKD6GzZssASt+vfvj4kTJ15loeTkady4Mfbu3YvSpUsjKSkJYWFhqpBgx6EKRjZCAiRAAiRAAiRAAiRAAiRAAiTgJAGOQ50E5ePVGMDycQfaU9+8jFCWD65cuRJt2rSxqTZ69Gi8/vrrymfDhw/HiBEjVKPAjkM1lGyIBEiABEiABEiABEiABEiABEjACQIchzoByQ+qMIDlB04saMLWrVvRrl07ZGVloVSpUpBlhR07dlT+njlzJr799lvlkAYNGmDTpk2IjY1VjQI7DtVQsiESIAESIAESIAESIAESIAESIAEnCHAc6gQkP6jCAJYfONGeCfPmzUOvXr2QlpZm10IJXi1YsAD16tVTlQA7DlVxsjESIAESIAESIAESIAESIAESIIEiCHAcGhinCANYfuzn48ePY+zYsUqgSi7o8PBwJWD18MMP44UXXkB0dLTq1rPjUB0pGyQBEiABEiABEiABEiABEiABEiiEAMehgXF6MIAVGH7WzEp2HJqhpiASIAESIAESIAESIAESIAESIAFAmbBRvXp1hcXJkydRrVo1cvFDAgxg+aFTPWkSOw5P0qdsEiABEiABEiABEiABEiABEgg8AhyHBobPGcAKDD9rZiU7Ds1QUxAJkAAJkAAJkAAJkAAJkAAJkABnYAXMOcAAVsC4WhtDGcDShjOlkAAJkAAJkAAJkAAJkAAJkAAJmAhwHBoYZwIDWIHhZ82sZMehGWoKIgESIAESIAESIAESIAESIAESYAArYM4BBrACxtXaGMoAljacKYUESIAESIAESIAESIAESIAESMBEgOPQwDgTGMAKDD9rZiU7Ds1QUxAJkAAJkAAJkAAJkAAJkAAJkAADWAFzDjCAFTCu1sZQBrC04UwpJEACJEACJEACJEACJEACJEACJgIchwbGmcAAVmD4WTMr2XFohpqCSIAESIAESIAESIAESIAESIAEGMAKmHOAAayAcbU2hjKApQ1nSiEBEiABEiABEiABEiABEiABEjAR4Dg0MM4EBrACw8+aWcmOQzPUFEQCJEACJEACJEACJEACJEACJMAAVsCcAwxgBYyrtTGUASxtOFMKCZAACZAACZAACZAACZAACZCAiQDHoYFxJjCAFRh+1sxKdhyaoaYgEiABEiABEiABEiABEiABEiABBrAC5hxgACtgXK2NoQxgacOZUkiABEiABEiABEiABEiABEiABEwEOA4NjDOBAazA8LNmVrLj0Aw1BZEACZAACZAACZAACZAACZAACTCAFTDnAANYAeNqbQxlAEsbzpRCAiRAAiRAAiRAAiRAAiRAAiRgIsBxaGCcCQxgBYafNbOSHYdmqCmIBEiABEiABEiABEiABEiABEiAAayAOQcYwAoYV2tjKANY2nCmFBIgARIgARIgARIgARIgARIgARMBjkMD40xgACsw/KyZlew4NENNQSRAAiRAAiRAAiRAAiRAAiRAAgxgBcw5wABWwLhaG0MZwNKGM6WQAAmQAAmQAAmQAAmQAAmQAAmYCHAcGhhnAgNYgeFnzaxkx6EZagoiARIgARIgARIgARIgARIgARJgACtgzgEGsALG1doYygCWNpwphQRIgARIgARIgARIgARIgARIwESA49DAOBMYwAoMP2tmJTsOzVBTEAmQAAmQAAmQAAmQAAmQAAmQAANYAXMOMIAVMK7WxlAGsLThTCkkQAIkQAIkQAIkQAIkQAIkQAImAhyHBsaZwABWYPhZMyvZcWiGmoJIgARIgARIgARIgARIgARIgAQYwAqYc4ABrIBxtTaGMoClDWdKIQESIAESIAESIAESIAESIAESMBHgODQwzgQGsALDz5pZyY5DM9QURAIkt/2s5gAAIABJREFUQAIkQAIkQAIkQAIkQAIkwABWwJwDDGAFjKu1MZQBLG04UwoJkAAJkAAJkAAJkAAJkAAJkICJAMehgXEmMIAVGH7WzEp2HJqhpiASIAESIAESIAESIAESIAESIAEGsALmHGAAK2BcrY2hx44dQ+3atRVhGzZsQJUqVbQRTCkkQAIkQAIkQAIkQAIkQAIkQAIBSeDMmTO46aabFNuPHj2KWrVqBSQHfzeaASx/97DG9m3cuNHScWgsmuJIgARIgARIgARIgARIgARIgAQCnIBMpLjxxhsDnIJ/ms8Aln/61WNWMYDlMfQUTAIkQAIkQAIkQAIkQAIkQAIBT4ABLP89BRjA8l/fesSy7Oxs7Ny5U5FdoUIFhIaGekSPooRaTzHlUseiaHn/9/Sn9/vIVQ3pU1eJeXd9+tO7/eOqdvSnq8S8uz796d3+cVU7+tNVYt5dn/503j95eXk4f/68ckCTJk0QGRnp/MGs6TMEGMDyGVdRUTUJMNm8mjQ93xb96XkfqK0Bfao2Uc+2R396lr/a0ulPtYl6tj3607P81ZZOf6pN1LPt0Z+e5U/p3keAASzv8wk10oAAfww0gKyhCPpTQ9gaiaJPNQKtkRj6UyPQGomhPzUCrZEY+lMj0BqJoT81Aq2RGPpTI9AU4zMEGMDyGVdRUTUJ8MdATZqeb4v+9LwP1NaAPlWbqGfboz89y19t6fSn2kQ92x796Vn+akunP9Um6tn26E/P8qd07yPAAJb3+YQaaUCAPwYaQNZQBP2pIWyNRNGnGoHWSAz9qRFojcTQnxqB1kgM/akRaI3E0J8agdZIDP2pEWiK8RkCDGD5jKuoqJoE+GOgJk3Pt0V/et4HamtAn6pN1LPt0Z+e5a+2dPpTbaKebY/+9Cx/taXTn2oT9Wx79Kdn+VO69xFgAMv7fEKNNCDAHwMNIGsogv7UELZGouhTjUBrJIb+1Ai0RmLoT41AaySG/tQItEZi6E+NQGskhv7UCDTF+AwBBrB8xlVUVE0C/DFQk6bn26I/Pe8DtTWgT9Um6tn26E/P8ldbOv2pNlHPtkd/epa/2tLpT7WJerY9+tOz/Cnd+wgwgOV9PqFGGhDgj4EGkDUUQX9qCFsjUfSpRqA1EkN/agRaIzH0p0agNRJDf2oEWiMx9KdGoDUSQ39qBJpifIYAA1g+4yoqSgIkQAIkQAIkQAIkQAIkQAIkQAIkQAKBSYABrMD0O60mARIgARIgARIgARIgARIgARIgARIgAZ8hwACWz7iKipIACZAACZAACZAACZAACZAACZAACZBAYBJgACsw/U6rSYAESIAESIAESIAESIAESIAESIAESMBnCDCA5TOuoqIkQAIkQAIkQAIkQAIkQAIkQAIkQAIkEJgEGMAKTL/TahIgARIgARIgARIgARIgARIgARIgARLwGQIMYPmMq6goCZAACZAACZAACZAACZAACZAACZAACQQmAQawAtPvtJoESIAESIAESIAESIAESIAESIAESIAEfIYAA1g+4yoqSgIkQAIkQAIkQAIkQAIkQAIkQAIkQAKBSYABrMD0O60mARIgARIgARIgARIgARIgARIgARIgAZ8hwACWz7iKiqpF4Pjx4/jqq6+wYMECnDx5EhEREahbty4eeeQRDBw4ENHR0WqJYjvFJBAUFOTUkbfeeiuWL19eaN2FCxfi22+/xcaNG3H+/HlUqFABN954I5599ll069bNKTms5JhAUlISNmzYoLyEsbySk5OVA5588kn88MMPLuFTw195eXmYMmUKpk+fjn379iE9PR0JCQno3LkzBg8ejOuuu84lnQKpshr+FJ8//fTTTmH7/vvv8dRTTxVaNzMzE+PGjcOcOXNw+PBh5OTkoHr16rjrrrsUf9asWdMpWYFYadOmTfjrr7/w33//Yc+ePUofGBYWplwP7dq1Q9++fdG+fXun0fD6dBqVWyqq4U9en25xTbEaTUtLU65P+d0U354+fVq5RrOyslC6dGlce+21uPPOO5XrtFy5ckXKWLNmDb755husWrUK586dU9po1qyZ0sc+9thjRR5vrvC///0P0jfv2LEDly5dQqVKlXDzzTcr98ht2rRxup1Aq6iGP+WetmPHjk6hGz58OEaMGFFoXd4POYWSlXyMAANYPuYwqlsyAvPmzUOvXr0gPzL2SoMGDZTAVr169UomiEeXiIAaASyDwaAEqaZOnepQl379+mHSpEkIDg4ukb6BfHBhvnIlgKWWvy5cuKDc8MuAwF6RgLUEQ8T3LFcTUMOfag6QDx06pPjz4MGDdt0VFxenBCrvvvtuurMAgVtuuUUZyBZVevfujcmTJyM8PNxhVV6fRVF0//dq+ZPXp/t95ayEpUuXokuXLkVWL1++PKZNm4bbb7/dYV0JZLz//vuQa9VekYD/L7/8gsjISIdtSOCse/fuSlDNXpF7pXfffRcSOGG5moAa/lQzgMX7IZ6l/kqAASx/9SztuorA1q1blSfO8gNdqlQpvPXWW8pTDvl75syZyg28FAliyZOw2NhYUvQQAfMg+rnnnsPzzz/vUIuYmBjUrl3b7vfi31GjRinfNW/eHK+//roy005mcHz66aeQ80GK1Pvoo488ZKnvi7UOeNSoUQPXXHMNFi9erBjmSgBLDX/p9Xp06NBBmW0i5cEHH8QzzzyDsmXLYv369fjggw8gM4zkJnz+/PmcgWfn9FPDn9YD5EWLFimzfRyVatWqKbME7JXLly+jZcuWOHDggPK1+PLRRx9FVFQUli1bho8//liZXSezZlevXo3rr7/e9y8oFS2QBzHS3wn/hx9+WJlBIdeoXCdr167F559/rsz4kCKzM2bMmOFQOq9PFR1TzKbU8ievz2I6wA2HScCjT58+yr3oDTfcoMwsrVKlihKEOnXqlBJwmjt3rnLNSoBZZjrLjKqCRR7EDRgwQPlY7nOGDh2KJk2aIDExEWPHjlX6S2euc+kH5H5Yiuj04osvKv3Hzp07lfsk6U+kiDx5QMhiS0ANf1oHsL777jtlxYCjUrFiRcjLXuH9EM9OfybAAJY/e5e22RAwP70MDQ3FypUrr5oGPXr0aCXIIcWZabnE6z4C5kF0cf0gA15ZJiZTp2UALP6WQa+5yJIkWX4ogUo5H/bu3ctZd8V0p/hIbrDkJcsMjh07ZgkqOhvAUstfcrMnSy2kSOBz/PjxNlbJbB4ZJMgMTBkMit/F/yz5BNTwp/UA+ejRo6hVq1axEMuTfplRIEWCzq+99ppNO7JcRq5juc6dWU5cLCV8+CCZlSazqx566CGEhIRcZYk8nZeHOuYA4YoVKyC/kwULr0/vOAnU8ievT+/wp2ghQQZ716a1hr///jseeOAB5SN5l4CWdbl48SLq1KmD1NRUJUC9efNmyIwtcxEZcpysQJAiwSx50FOw/Pvvv7jtttuUj++55x789ttvNrpJfyG/nydOnFAeOhw5cgRlypTxHpheoIka/rQOYDnylTOm8n7IGUqs46sEGMDyVc9Rb5cIyFOrVq1aKcf0798fEydOvOp4eeLVuHFjZVArP84yU0NyhbBoT6CkASwJXkyYMEFRXGYatG7d+ioj1q1bZwli2gt2aG+1f0gsTgBLLX9JvhC5fmXGleS3s5fPTmblyWwSKbNnz1ZmprA4JlAcf6oxQNbpdEq+OhmUNWrUCLt27bK71FdmHchsACnSzxf2tJp+vpqAzESUwaqUQYMGKfkhCxZen75z5jjjT16fvuNPs6Yys3n//v1KYEpyZFkXCe6/8cYbykeSu0pmqRYsMptLHiRIgEWWZEuqjIJFPpccd/JQRx48yOzYgkVmZ5lzadl7qOB7ZD2jcWH+VCuAxfshz/iWUrUhwACWNpwpxcMEZDq1LDeRIoELczCroFrWg1tZ+tK1a1cPax6Y4ksSwDIajcqNl0ydl5sECWg4KuabiKpVqyoBD2dzbwWmV5yz2tWAh1r+klkiDRs2VJSUoIY5gFlQ67NnzypLNKQUtWzKOYv9u5ar/hQaagyQZRmqOd+L9MvmAVpB2taBaC4Hdv1czMjIUJbUS7E3sOX16TpTTx5RlD95fXrSO8WXLYF5mTEu16osrbYubdu2VR7UST5ACW45ymV3xx13QO5rJQ+k1LNOkyFtSnAsNzcXUk8CWfaKfC8PFmQWsyRzl1mwLK4TKMyfagSweD/kuk94hG8RYADLt/xFbYtJwLx8UHImyY4qjpYNyU2A3AxIkeUrI0eOLKZEHlYSAiUJYMm0dskBIcXRbDuzbvK97FAoRY5zlE+rJLYE2rGuBjzU8pf1dHlHT6HNvpBAl9zgyXIL2ZWUxTEBV/2p1gDZevmgo1mUIkuWD8bHx0OWBUs/L8vgWJwnIMuPzLubyUysP//80+ZgXp/Os/SGmkX5k9enN3jJNR1k5pWsDjCnRLDeoEQCSjLTWGZWScD/77//dti4PMSVh7lSZLmg9U531ssHpd6bb77psB2RIw8Y5D5a+l2uVFDPn9KSGgEs3g+55hPW9j0CDGD5ns+ocTEIyBMjWb8vyS+3bdvmsIWUlBRl+ZEUWVokS4xYtCdgDmDJFGiZASCDaMkTUblyZSXAKFtCO9pm2HoJxZdffokhQ4Y4NEC+f/nll5XvZUq9zEBgKRkBVwMeavnr1VdfVZJSS5EE/YUl9L7vvvuUgbqcZ/LkWQLbLPYJuOrPggNkybUiAzDpf2WGgOQe69y5M2SDBpn56KjITli//vqr8rX0y44Svcv30q/Ldu/Sz8vSbxbnCUieG9nsQIrkgPzkk09sDub16TxLb6hZlD95fXqDl4rWQQJDssGC5K2SpXrnzp1TDpKdCB9//HFLA7K0WpK1S5GE62PGjHHYuPW5IfkhrTfIkZ15ZQmxFKl3//33O2xH5JiXGu/evRtyn8ZSOAFn/SmtWAew5H5Xln/KzHEJVMoyUPlNld9P2XDKUeH9EM9IfyfAAJa/e5j2ITs725LAW7YRlhvywopM0ZZp+JI3SZ78s2hPwJmlfHKDJUuVZPaFdZH8ZvLjLmXOnDnKltCOiuzwY86BJMfJjCyWkhFwNeChlr8k78esWbMU5WV5hHUS24IWvfDCC5YE7/v27bMsPSyZ5f55tKv+FArWSwgdUZGt3GWw5eiak/5Xdo6U4KLsNFhYkeTW5pwu0t/LEhmWoglI3kdZBiS5w6TIEiVJ0uyO/pTXZ9H+KGkNZ/zJ67OklN13fFH9psyKkp0Are+PZMZVt27dFKVkIyIJXDgqcn2bcwRKW+a0GlJf/jYHr2WGl2x+46h89tlnlg01RL55qbf7yPhmy8Xxp1hqHcByZLnspDxs2DBlwyl798vsb33znKHWzhNgAMt5VqzpowRkMGveZrZHjx6WLYIdmSM7qclTfJmyLVsHs2hPQAat9957r7IjjuSpkqCi+FGWB0nAIzk5WVFKdh5bsmSJzRR2690kJY+D5HNwVOR786wruSl75ZVXtDfWzyS6GvBQy18SnP7rr78UmllZWZAAiaMi+ZTkqbYUe4N2P3NJicxx1Z8iTG7cZfdAmdkjARLZGl6KLEeTWVUSOJaZlVIcbccuu4ju2bNH2dlSnj4XVqRfN8+WlZle5iVxJTI8AA6WGYvmAa/4yjzjzdp0Xp++cyI4409en97rT0cBD5lNLKkO7G1QIQ/pHnnkEcUoyfso+R8dFckHap4tJQ9xvv76a0vVgQMH4ptvvlH+lnpy3+WoiBzz7C3py2WXU5arCRTHn9KKBLB69uyp/H62b99e2WFSlmvK7o/yAP6nn36CbHIixVHeR94P8Yz0dwIMYPm7h2mfkpxbct1IeeKJJ5TOv7AideUYyaN06NAhEvQAAclT5mjJkEyllyeOskxMytixYzF48GCLljJwlvw5Uv755x906tTJoQXWeR/kuHfeeccD1vqXSFcDHmr5S4Kd4k8pkg9EnlA6Ktb5lVatWqXcJLLYJ+CqP6UV2TlQlgs6mkkpN+Fycy434bIs4vDhw8ryYOsi/a8EvCT4JTfuhZXevXvj559/VqpI321v9yz615aAPAyQpZySV0ce8MjDGvODHuuavD5948xx1p+8Pr3Xn3LfI8vFpMhDGOkXJTAvS/qkP5QZqzLb1LpIvyf9n5SpU6eiT58+Dg20zmfXt29fTJkyxVJX/pa8SVJErgRNHBXr/Eoiv1evXt4L1YOaFcefoq6sAJFE/I5yi8mMWdlgSn5n5TdW7oVlGb114f2QBx1P0ZoQYABLE8wU4kkCnIHlSfrukS03YvKEUAbAklPn4MGDFkFqzRhwj+b+36qrAQ+1/MUnju45t1z1p7NafPDBB8oSCCny/7ffftvmUM7Acpak6/Ukb83NN9+s5BaTmYqyM5kkwLdXeH26zlfrI1zxp7O68fp0lpT760mQ6Mknn1SCFRKkkhyg5sIZWO7nr7aEwvzprCzJhSYP5KX069cPkydPtjmU90POkmQ9XyXAAJaveo56O02AObCcRuVTFa1/oCXZaUJCgqK/WjmVfAqGFynrasBDLX8x54N7TgJX/emsFrJMW2ZdyVLCLl26KLtaWRfmwHKWpGv1jh49qsw4TExMVDbGkGWDsqmBo8Lr0zW+Wtd21Z/O6sfr01lS2tQzL5OW9AoyI9W82RBzYGnDX20pjvzprByZOStL5dPS0lC/fn1lV2XrwvshZ0mynq8SYADLVz1HvV0iIAmdJW8SdyF0CZtXV37ttdcgeaukyJRqc34ItXbN8mrjvVg5VwMeavmLu+6456Rw1Z+uaGHeHVbyssgsEuvCXQhdIelcXQlaycwrmcEqszkkR4t5+ZGjFnh9OsfWE7WK409X9OT16Qot99adMWOGZffB6dOnKzmSpHAXQvdyd1frjvzpijy555UcnrIMX5YdWhfeD7lCknV9kQADWL7oNersMgFZHiG5buTplaxLl4SI9orsOijb1kqRPDkjR450WRYP0IaAbPkuy1ukWAewrPM8yA5nMoPAUZHvJTmqFDmudu3a2ijvx1JcDXio5S/rvBz/+9//IE8gHZWGDRsqTywl393x48f92BslN81Vf7oiUXIuyRJvewEs6zxl0i/LjCx7RZ5ES748uYGXfl5yAbFcTUCS28umF5IYX8q4ceMgiZuLKrw+iyLkme+L609XtOX16Qot99aVzWok75EU2YlQkndLyc3NVQIYkvdRdgOUGVmOiuw6OHToUOVryRfZsWNHS1XrfKBST3YldFREjsyYlfvozMxMh7ma3EvEt1t35E9XrLrpppsgO0baC2DxfsgVkqzriwQYwPJFr1FnlwnIj7Z5y+B169ahVatWdtsYNWqU5cZA8oKYbxhcFsgD3E5AkpkuWLBAkSOJT6tWrar8X5YkSRJneTotebJkRx1HpVGjRti3b59yrCR/dpR02u3G+JEAVwMeavlLAlISmJIiOzHJTkn2iuxoV6VKFeWrxx57DPIklMUxAVf96SxLCVzJDoPif0kmLjf01kUGSObt2aVflp0j7RXpz2WnQymOdmRyVid/rSfJfmUziy1btigmFsazIANen953VpTEn85aw+vTWVLa1LPe0e6rr77CoEGDLILloasE+WXjDPGbJAC3V2RHZrmvjYiIUOrFxsZaql2+fBmyUkECYlJPdmi2V+R7mZknS9ek312zZo02APxMSmH+dMZUeXAj/pK+oGAeWDme90POUGQdXybAAJYve4+6O01AZuiYg1aOZuUYDAY0btxYCXjIE33JAeFoFxCnBbOiWwhI3g8JTsnNlL3dImWLZ3MAw9HsDeuBr9QfP368W3QNtEaLE/BQy18yk0euX8kPIgFJeTJZsFgHqWWHp4cffjjQXOSSvcXxpzMCPvzwQ8uun/Z2AJVrW2aAyA26BJpliaG9ALMEKydNmqSItJ6J6YwOgVBHZkjIg5jVq1cr5kqyfEnQ7Urh9ekKLffWVcOfzmjI69MZStrVsc75uWzZMnTo0MEi/NNPP7UE+B3NPpaHfLVq1VJmat15552Wh3/WFsjnEriSmVVyj2VvN9eZM2cqD36kiFxJ5cDiOoHC/OlMa7KM1Lz7Y8EdJc3H837IGZKs46sEGMDyVc9Rb5cJmJcRyo/zypUrLU/tzQ1Z77Y0fPhwjBgxwmUZPKDkBObNm4du3bo5XOZ57tw55XvZOljK559/jpdfftlGsDx9kh9vuVlr2bKl4u+oqChLHdmiWs4HyR8g54Msq5FEmCwlJ1CcgIda/rKeNi/Lo2SZlHWR7cFbtGihPD2Wp5YS7HK0nLjkJPyjBVf9KfVld7vmzZs7BCB5lR566CElAC3Xpewiap5BaX2Q9TJCe4MlCU7LdSxPo2V53PLly/0DukpWCN977rnHkiD/xRdfxJgxY1xundeny8jccoAa/uT16RbXFLtRmYkjy91lN1BH5csvv7Tc40iaA+kvZQMGc7l48SLq1KmjBPtr1qyJzZs3Kwm+zUXugx544AHIvZWUggEwcz3rZYT33nsv5s6dayNHlq3ecMMNShJ5ecgry4vLlClTbNv98cCS+lN+O7dv324ToCzISR7UyOxkSYciD3VkGaH4pWDh/ZA/nmG0yUyAASyeCwFDQAIe7dq1gwQvSpUqpeQCkBwA8rc8VTLnQmrQoIES2LCeXh0wkLzAUHlKqNPplAGuTFGXv2WQKzdPMkCV2Rbyfymym9bSpUuVKfEFiywnktk2UmQwLUuQZLaWBDE++eQTSwCMy45K5vT//vsPhw4dsjQivjE/lZXrTbZ4ti7WW4Bbf66Gv+RGXQIZ5tkmcg4988wzyk223PTJTB+ZWRkcHAwJokgglMWWQEn9Kdeo9Kty7UrwRDbOkJlUUmTA88svvygvWZomRWY+ygwfe0WWtUgA2rzD0rPPPqsM9qQ/kEGY5IJJT09X/palLNdffz3daUVAzn8ZhEqRJYQSvCpsmbQsPZLfP3uF16fnTy01/Mnr0/N+tNZA7m+knxPfyv2M3KPI/al8tnPnTshMG/PvmVyfkjZBllwXLHJfJLNRpUgbMtOySZMmSioFue6lv5RS1LJ5+V7uh6VIPz5kyBBlh2fRRWblyf2TFJEn/TGLLYGS+tP8wKhp06a4//77lcCUpDyQgKUEDuW+5eeff1Ye/kiRey15uGOv8H6IZ6c/E2AAy5+9S9uuIiBPoGTarczAsFfk5l1uEGR2BotnCMgNgDOJteWGb8qUKcqTQHtFloRK8EKeQjkqMvVaApcS0GApHgEJSP34449OH2wOXBQ8QC1/SQBNlkLIU0l7RYKdMjOrYGDNaQP8vGJJ/WkeIBeFSZZ3ysyCogZBEhwVf8qsA3tF8r7IIE9y4rHYEnA1p5/M3pABlDv7U16fxT9L1fAnr8/i83fHkc7e78hyPrmX6dKli0M1ZOWAPKRx9Bsr/eivv/5a6GwveaArO8D+9ddfduXIvdKwYcO4QsGBF0rqT+sZz4WdbxLQEj/ILOXC+gX2t+64atmmNxBgAMsbvEAdNCUgwZGxY8f+v727t4lrAYMA6g6ogAqogYgeSBE5HVECGd1QACIiJ3yaK/EC209vpUUW4zmWnKH1951hfzx7f46iKtcFyLdaKaxyLZyHh4ffXjfnjw44/o/lLmL5m9ODcsRG3oBTOOZbycvLy+MukXd3d7+cAvpfbPkglpIqhUYeKxe+zO2Hcy00R+Cc/8t2buHx8wRfkVdOKXt8fDwu0J7TBHOHunyLfHNz8yOnUV1dXZ2/+F/6COfmmSMHnp+fj+dvjmR9e3s7nnfJJEfCxT45pED8PDLr/yiTX47Uenp6Oo72y7fPeS3If8iSZ4oXf34V+IrCw/Pz+/xmfUWenp/fJ89M8vLycnwWzVFWeW3LJRLe39+Po0rz+pijSlPO397envTZNEei5rUyd93OY+ULvhwFe39//++1q04RyHtnTofL6Ww5VS033Li+vj4+I3/eNOOUx1n7mXPzzHvb5/tnjhp/fX093j8/Pj5+XFxcHDeqyfXP8v6ZsuyUPz4PnaLkZ9oEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgpMkQNAAAF9klEQVQQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCSiwxgK3LgECBAgQIECAAAECBAgQIECgTUCB1ZaYeQkQIECAAAECBAgQIECAAAECYwIKrLHArUuAAAECBAgQIECAAAECBAgQaBNQYLUlZl4CBAgQIECAAAECBAgQIECAwJiAAmsscOsSIECAAAECBAgQIECAAAECBNoEFFhtiZmXAAECBAgQIECAAAECBAgQIDAmoMAaC9y6BAgQIECAAAECBAgQIECAAIE2AQVWW2LmJUCAAAECBAgQIECAAAECBAiMCfwDs3hkS5/KstUAAAAASUVORK5CYII=\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb264476e10>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_infection_scenarios(np.linspace(1.3, 3.3, 3), 6, 8_000_000, 365)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulate with an $R_0$ Slider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "78955a5bf91c45abaf6cf6aad9667228",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=1.3, description='r0', max=3.9000000000000004, min=-1.3), Output()), _…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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