prml-figure-3.7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PRML §3.3 Bayes linear regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "from scipy.stats import multivariate_normal\n",
    "from scipy.linalg import inv\n",
    "\n",
    "# cosmetics (change as you like)\n",
    "%matplotlib nbagg\n",
    "plt.style.use('seaborn-talk')\n",
    "plt.style.use('seaborn-darkgrid')\n",
    "plt.rcParams['image.cmap'] = 'viridis'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Phi(x, M):\n",
    "    \"\"\"Calculate design matrix of polynomial function.\"\"\"\n",
    "    return x[:,None] ** np.tile(np.arange(M), (len(x), 1))    \n",
    "\n",
    "def linear(x, w0, w1):\n",
    "    \"\"\"Linear function y = w0 + w1*x.\"\"\"\n",
    "    return w0 + w1*x\n",
    "\n",
    "def gaussian(x, mu, beta):\n",
    "    \"\"\"1D Gaussian PDF N(x|mu,beta^-1).\"\"\"\n",
    "    return np.sqrt(beta/(2*np.pi)) * np.exp(-beta/2 * (x-mu)**2)\n",
    "\n",
    "def likelihood_2D(w0, w1, x, y, beta):\n",
    "    \"\"\"2D likelihood as a function of w0 and w1.\"\"\"\n",
    "    return gaussian(y, linear(x, w0, w1), beta)\n",
    "\n",
    "def posterior_2D(w0, w1, mn, Sn):\n",
    "    \"\"\"2D posterior distribution.\"\"\"\n",
    "    return multivariate_normal.pdf(np.dstack([w0, w1]), mn, Sn)\n",
    "\n",
    "def posterior_sample(mn, Sn, size=1):\n",
    "    \"\"\"Sample w0 and w1 from 2D posterior distribution.\"\"\"\n",
    "    return multivariate_normal.rvs(mn, Sn, size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create model and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_true = [-0.3, 0.5]\n",
    "M = 2 # i.e., len(w_true)\n",
    "N = 100 # number of samples\n",
    "\n",
    "alpha = 2\n",
    "beta = 25\n",
    "\n",
    "x_true = np.linspace(-1, 1, N)\n",
    "y_true = linear(x_true, *w_true)\n",
    "\n",
    "np.random.seed(2018)\n",
    "x = np.random.uniform(-1, 1, N)\n",
    "y = linear(x, *w_true) + np.random.normal(0, np.sqrt(1/beta), N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABwgAAAJYCAYAAAB2JbLWAAAAAXNSR0IArs4c6QAAQABJREFUeAHs3QmYHVWdP/xfekkn3dk6CUuIgCgkAqKgBpWRGUdFowhRhkWQUZy/r46v2wCKgvuooCMMg4qKD+8MyzAqAgqI4A7K3wUXGMBggrJIQiAQEkjSSSe9vHWqc5ssvdxec++tTz1Pc++tOlV1zufcMj797XPOhO5sCxsBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAoUQqCtEKzWSAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFcQEDoi0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgQAICwgJ1tqYSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQEBD6DhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAokICAsECdrakECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEBIS+AwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKJCAgLFBnayoBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAaHvAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIECCQgIC9TZmkqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBAQOg7QIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBAAgLCAnW2phIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAQEPoOECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiQgICwQJ2tqQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQEhL4DBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAokICAsUGdrKgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEBoe8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQIJCAgL1NmaSoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQEBA6DtAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoEACAsICdbamEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBAQ+g4QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKJCAgLBAna2pBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBASEvgMECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECiQgICxQZ2sqAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQGh7wABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBAgkICAvU2ZpKgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAQEDoO0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgQAICwgJ1tqYSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQEBD6DhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAokICAsECdrakECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEBIS+AwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKJCAgLFBnayoBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAaHvAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIECCQgIC9TZmkqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBAQOg7QIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBAAgLCAnW2phIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAQEPoOECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiQgICwQJ2tqQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQEhL4DBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAokICAsUGdrKgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEBoe8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQIJCAgL1NmaSoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQEBA6DtAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoEACAsICdbamEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBAQ+g4QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKJCAgLBAna2pBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBASEvgMECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECiQgICxQZ2sqAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQGh7wABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBAgkICAvU2ZpKgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAQEDoO0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgQAICwgJ1tqYSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQEBD6DhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAokICAsECdrakECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEBIS+AwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKJCAgLFBnayoBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAaHvAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIECCQgIC9TZmkqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBAQOg7QIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBAAgLCAnW2phIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAQEPoOECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiQgICwQJ2tqQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQEhL4DBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAokICAcoLPf8Y53xPz58+Ouu+4aoNTgh7q7u+Pqq6+Ok046KV74whfG8573vHj1q18dZ599dqxcuXLwCyhBgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYJQEBIT9QH7ta1+LW265pZ+j5e/u6uqKU089Nc4666z4/e9/H+3t7dHQ0BAPPvhgXHrppXHUUUfFHXfcUf4FlSRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwAgEB4XZ4abTfl770pTj//PO3OzK8j+edd17ceOON0djYGJ/+9KfjD3/4Q/5z1VVXxbx582LNmjXxrne9K38d3h2cRYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKB8AQHhVlaPPvpovP3tb48vf/nLW+0d/tt0vcsuuyy/wBlnnBHHH398TJw4Mf980EEH5SMIZ82aFU888URcdNFFw7+RMwkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUKSAg3AKVRgy+5jWviVtvvTUf7XfMMceUSdh/sSuvvDI2bdoU06ZNize96U07FJw5c2a8+c1vzvdfe+210dnZuUMZOwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMpoCAcItmWnNww4YNkUb2pek/3/CGN4zY+Ve/+lV+jUMPPbR35OD2Fz388MPzXatWrYo777xz+8M+EyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBhVAQHhFs7nPve5+bqD3/72t+M5z3nOqCDfe++9+XX23Xfffq+3zz779B5bunRp73tvCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECIyFQMNYXLQar3n11VeParXTaMSnnnoqv+acOXP6vfbUqVOjubk52traYuXKlf2Wc4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAaAgYQTgain1cY+3atb17J0+e3Pu+rzel4+vWrevrsH0ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIERk1AQDhqlNteqLOzs3dHY2Nj7/u+3kycODHfvfU5fZWzjwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBIBUwxOlLBfs5vamrqPbJ58+be93292bRpU757sCCxr3MH29fd3R2dnd2DFXOcQKEE6usnxIQJE8LzUahu19gyBTwfZUIpVkgBz0chu12jyxTwfJQJpVghBTwfhex2jS5TwPNRJpRihRTwfBSy2zW6TIHS81FmccX6ERAQ9gMz0t1TpkzpvcTGjRt73/f1Jq1XmLatz+mr3HD2pXBw9er1wznVOQRqVqC1tSUaGibk4bnno2a7WcOGKeD5GCac0woh4PkoRDdr5DAFPB/DhHNaIQQ8H4XoZo0cpoDnY5hwTiuEgOejEN2skcMUKD0fwzzdaVsETDE6Rl+FNG3orFmz8qs/8sgj/d4lrVXY1taWH99tt936LecAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdEQEBCOhmI/15g3b15+5L777uunRMTWx0rl+y3sAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIERCggIRwg40OkvfelL88O33XZb9LcO4a233pqXmTZtWhxwwAEDXc4xAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAiMWEBCOmLD/Cxx55JFRX18fTzzxRPzP//zPDgXT/iuuuCLff+KJJ2ZrolkScgckOwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEZVQEA4Qs4f/ehHsXDhwvwnvd96e8YznhEnn3xyvuvf/u3f4pJLLomNGzfmn+++++445ZRTYtWqVTFz5sz8/dbnek+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgLAQMWRuh6tq1a+P+++/Pr5Leb7+dfvrp+fGf//zncc4558S5554bTU1NsW7durzo1KlT4+KLL85Dwu3P9ZkAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAaAsYQTjaottdL4WBF110UZx99tmxYMGCmDx5crS3t8fcuXPjhBNOiGuvvTYOPPDA7c7ykQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDYCEzozraxubSrVoJAR0dXrF69vhKqog4EKkagtbUlW/OzLjwfFdMlKlJBAp6PCuoMVak4Ac9HxXWJClWQgOejgjpDVSpOwPNRcV2iQhUk4PmooM5QlYoT8HxUXJeoUAUJlJ6PCqpSVVbFCMKq7DaVJkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDA8AQHh8NycRYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAqBQSEVdltKk2AAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgeAICwuG5OYsAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAVQoICKuy21SaAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwPAEBITDc3MWAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoUEBBWZbepNAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHhCQgIh+fmLAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJVKSAgrMpuU2kCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECwxMQEA7PzVkECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqlJAQFiV3abSBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBIYnICAcnpuzCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSlgICwKrtNpQkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMT6BheKc5iwABAgQIECBAgAABAgQIECBAgAABAgQIECiawPe/f32cffanht3sW2/93bDPdeLIBH7729/Eqae+O7/INdfcELvuutvILpid3dHRES9/+Uvy67zvfafF8cefNOJrusD4CAgIx8fZXQgQIECAAAECBAgQIECAAAECBAgQIECAQNULNDU1xcyZs/psxxNPrMr3T5zYFFOmTOmzjJ0ECFSGgICwMvpBLQgQIECAAAECBAgQIECAAAECBAgQIECAQMULvPKVr47009f2spe9KN/9ylceER/5yCf7KmIfAQIVImANwgrpCNUgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMB4CAsLxUHYPAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhUiYIrRCukI1SBAgAABAgQIECBAgAABAgQIECBAgAABAkUReNe7/k/cddf/xvved1rstdcz46tf/WL89a8PxtSp0+Lww/8uPvjBs+Jf//Vj8cMf3hj77jsvLrnkf/qkGaxMe/vGuPbaa+JnP/tJPPDA/bFx44aYMaM1nvvc58Ub3vAP8cIXLujzugPtfOMbXxePPbYyPv/582P+/OfEZZf9Z/zyl7dGWoNx2rTpceihL4l/+qd3xu677x4dHR1xzTVXxve//7146KEHo6GhIZ7znAPjrW/9p3jBC3qmZN3+Xhs2bIjrr/9O3HzzT+O++/7SW+cDD3xuHHXUG+MlLzls+1N6Pz/11JPZ/b6dt/fhh5dHY2NjPO95z4+TT35bb5mB3vzhD7+L73znqrj77jtjzZrV0dQ0KfbZ51nx93//yjj66GNi0qRJA53uWBUJCAirqLNUlQABAgQIECBAgAABAgQIECBAgAABAgQI1JLA7bf/Pi688ILo7OyM5uaWPGSbNWv2qDQxBY5nnHFqLFv21/x6dXV10dIyJR5//LEsQPtx/vP61y/Kw8j6+voh33Pp0j/FZz7ziVi79qmYOLEpurq68mt///vXx29+88u46KJLs+Mfjzvu+ENMmDAhJk9ujvXr18fvf39btu/3ce65F8SCBS/Z5r5/+cuf48MfPj1WrFie70/1SuelOt9yy8/yn1e8omeNx6ampm3OTWHiBz/4/nj00Ufy/en45s0Rt9768zzAPOKI12xTfusPKcg877zPZcHkd3t3t7S0RApYU5CbflJwmELRvfbau7eMN9UrICCs3r5TcwIECBAgQIAAAQIECBAgQIAAAQIECBAgUNUCv/jFLTFv3vwsSPu32GOPuZFG+U2fPn3EbVq7dm2cfvr78qDtOc85IN75znfH859/SBbkTYwnn1wT1133nfjP//x6fO971+ajFt/97vcP+Z7p/Nmzd4lPfvKz+ajBFHJ++9vfzALP/4hVq1bFKaecmAV0m+L97/9AHHnk0VkA2pwHbWed9cFYvfqJuPjii7YJCNMIxNNOe3d+bmvrzOy80+Nv//bv8zqnY9/4xn/HN7/53/HTn/4oH4n48Y9/urfOKcj70IdOy8PBXXfdLQ89X/zil0YKRVO492//9tn4wQ9u7C2//ZuvfOWCPBycMmVKNrrx7Vl9j8pHQ6bg8He/uy0uuODcbATkX+MDH3hfPpozhbm26hYQEFZ3/6k9AQIECBAgQIAAAQIECBAgQIAAAQIECAxDYHNHd1z1f1fFnQ+0Rfvm7mFcYexOqaubkI846+7uzkalDa9uTY0T4nnPbI5j/2ZWNDZMGLvKjsKVzzzz43k4mC71zGfuMwpXjLjiikvzcPDZz94vvvKVi/OQrXTh6dNnxD/+49vyYPDcc8+JK6/8n/iHfzg+mxJ0TqlI2a/nnHNeNmXo/nn5NH3oiSeenE0nel3cf/99sW7d2ixQOzOfyrR0wYMOen6ccMJJ8bWvfTn+9KfFsWnTpt66XXLJxXk4mEb+ffGLX8un9iydN3PmrEghZprC9KKLvpxPvXr00W+Mgw9+QV7k6qu/nbc3BaD//u9f3sYx3fNLX/p6FvydkF+/dM3S64MPPpAHm2mU4xe+cEGk8qUttSlNabrvvl+Pt7zlhEjTll511bey9/9UKuK1SgUEhFXacapNgAABAgQIECBAgAABAgQIECBAgAABAsMXSOHgjb9/cvgXqIIzl696Mg8a3/S3syq2trNmzYr99ps/6vW78cbr82umkXApNOtrS6P6vvzl87M1/jZm03DeEsce+6a+ivW7L4WPpXBw60LPeta+eUCYpgdduPDIrQ/l70shaBpx+NRTT2WjEGdHCoPTyMC0vfa1r98mHMx3bvlPCiCvuuobedB3443f6w0Ib775J3mJl73s77YJB0vnzpgxI2vfiXm4WNpXek3XSfdPaz1uHQ6WjqfXVMe//duX5yMu09qIAsKtdarzvYCwOvtNrQkQIECAAAECBAgQIECAAAECBAgQIEBgBAL3PdI+grOr59S/rNhY0ZXdc8/RX89uxYqHe0fKpWlA//u/L+3XYHNapC/b0vp9Q92e9axn93lKmqYzbWktxUmTJu1Qpqnp6X1dXZ358WXLHoo1a9bk7xcsePEO55R2pBF9hxzyovjxj38Q99zzx3x3ChrTaMS09RfwpWMvfOGL0ssO291335nve/DB++Poo/tfp3DDhg15uQceuG+Ha9hRfQICwurrMzUmQIAAAQIECBAgQIAAAQIECBAgQIAAgREKPGv3pliyvLLDsxE2MT/92XOeDqNG43qjfY2WltFfy27Vqsd7q7lu3brsffoZeEtrFg51KwWB/Z3X2NjY36Ed9q9Zs7p33+zZu/a+7+vNLrv0HF+9uuecdG5XV1deNE1F2t+W1ibsayt5pbA0rXU42JamRU2jLvsKPwc71/HKERAQVk5fqAkBAgQIECBAgAABAgQIECBAgAABAgQIjJNAWpsvbbW+BuE/HDZznESHd5u6urrhnbjlrDR6bvuts7MnLEv7zz//whhoRN725w7lc3396EUsaYrPcrdSGJjWDExb6bXn/P6v0199S9d79atfGx//+Kd7LuO/NS8wet/emqfSQAIECBAgQIAAAQIECBAgQIAAAQIECBCoFYHGhglx4t/Nzn4qr0WtrS3R0FAXHR1dsXr1+sqr4DjVaEv+la2P93Tgt/2t29p29Enr7ZW2lSsfLb2t6NfW1qeD3MceS3V+br/1LbWptbU1LzNjRmuk9Q5TWPrYYyv7PW/16r5HB06fPiOWL18Wpev2ewEHakpgZNF8TVFoDAECBAgQIECAAAECBAgQIECAAAECBAgQIFApAo2NE/OqrF+/YwhYqmNfawfuuedeMWXK1LzIr371f0tFd3hNgdgxxxwZ/8//89b42c9+vMPx8dzxjGfsGdOnT89v+dvf/qbfW6dpQG+//ff58X33nZe/plGYz33u8/L3v//9b/s993//944+jx1wwIH5/sWL744nn+xZB7Gvgh/5yAfj5JOPj899zijDvnyqbZ+AsNp6TH0JECBAgAABAgQIECBAgAABAgQIECBAgEABBEpr7aUg75FHVuzQ4hT+PfroIzvsT4HZq171mnz/L35xc9xxxx92KJN2fP3rX8lHzS1d+qd4znMO6LPMeO1M04QeccTC/HY33XRD9BV8poNXXHFplNYrfOUrX91bvde85nX5+9/85lfxv/97e+/+0psNGzbEt751RenjNq9patG0pbUFv/a1C7c5VvqQgsdbbvlZPPDAfbH77nNKu71WsYCAsIo7T9UJECBAgAABAgQIECBAgAABAgQIECBAgECtChx22MvypqU18j75yY/EQw/9Nf/c3r4xrrvuO/GJT5wVjY2NfTb/lFPeHjNnzsqn3TzjjFPj+uu/G+m8tD3++GPx+c9/NlIQl7Y3vvHYmDNnj/z9zvzPW97yTzFr1uysnu3x/ve/K3784x/koV2q0+rVT8SFF14QF1/8tbyKr3zlEVHySTuOPPLo2H//AyNZfehDp8YPf3hjNkVtR1723nuX5Ndbtuyh/PP2/znggOdGKWC8/vrvxGc+84neQDaFhsnpIx85Iz9tzpy5udf21/C5+gSsQVh9fabGBAgQIECAAAECBAgQIECAAAECBAgQIECg5gVS4PWGN/xDfPe7V8fdd98ZJ554TLS0tEQaDZeCsL33fma89rWvz0a9fXkHi9mzZ8d5530xPvzh0/NRhp///Gfi3HPPicmTJ8e6det6y7/iFUfE+953eu/nnfkmBZrnnfelrM6n5QFdCkUbGhqyOjdndV6brcXYnVcvjTQ844yPbFPVtAbhOeecm+0/NdKIyH/914/lU4GmALU0ReuJJ/5jfOMbl29zXunDGWecFWn60p/+9Ed5IJhCwTRNa1rjMVmnLYWX//7vX8qmQn16jcfS+V6rT0BAWH19psYECBAgQIAAAQIECBAgQIAAAQIECBAgQKAQAh/4wJlxyCEvykYMXhNLltyTh1gpGEzBXgq8UqDV37bffvPj8suvzAPGNNXoAw/cnwdeM2bMiPnzD4jXve6oSCPxKmnbd9/94rLLvpXX+ec/75nSM4183H33PSKtFfj61x8dCxa8pM8qz569S3z1qxfH9753bR7ypRGXXV3dcfDBL4iTTnpLpGv3FxA2NU3KQsVzcpN0flqPMI1abGpqirlz94zDD/+7OO64N8W0aT3rJPZZATurSmBCljj3RM5VVW2VLVego6Mre4j7X8C13OsoR6CWBFpbW7K/vKnLhth7PmqpX7VldAQ8H6Pj6Cq1KeD5qM1+1arREfB8jI6jq9SmgOejNvtVq0ZHwPMxOo6uUpsCno/a7FetGh2B0vMxOlcr7lWsQVjcvtdyAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBAgoICAvY6ZpMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQXAEBYXH7XssJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKKCAgLGCnazIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBxBQSExe17LSdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiggICwgJ2uyQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAsUVEBAWt++1nAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoIACAsICdromEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFFdAQFjcvtdyAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBAgoICAvY6ZpMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQXAEBYXH7XssJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKKCAgLGCnazIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBxBQSExe17LSdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiggICwgJ2uyQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAsUVEBAWt++1nAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoIACAsICdromEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFFdAQFjcvtdyAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBAgoICAvY6ZpMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQXIGG4jZdywkQIECAAAECBAgQIECAAAECBAgQIECAAIHhCBx77FHxyCMr+jy1vr4+mpomxaxZs+KAAw6MV73qNfHSl76sz7KjsfO3v/1NpHu+4AUvGo3LuQaBQggICAvRzRpJgAABAgQIECBAgAABAgQIECBAgAABAgRGX6ChoSGmTZu+zYU7Ojpi/fp18dBDf81/fvCDG2PBghfHxz/+6WhtnblN2ZF+OPPMD8QvfnFznHXWJ0Z6KecTKJSAgLBQ3a2xBAgQIECAAAECBAgQIECAAAECBAgQIEBg9ASe+9znxZe//PUdLtjd3Z2Hg9///vXxjW9cHmmU32mnvSe+9KWvx5QpU3YoP9wdKRy0ESAwdAFrEA7dzBkECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAAAITJkyIvfbaO/75n98Tn/3sF6Kuri7uvXdpXHDBuQOc5RABAuMlICAcL2n3IUCAAAECBAgQIECAAAECBAgQIECAAIFCCjz88LK4+eYfxfe/f23+mj4XaXvZy/42jj32hLzJP/jB9+OBB+4vUvO1lUBFCphitCK7RaUIECBAgAABAgQIECBAgAABAgQIECBAoNoF2ts3xk03XR/Llz+0TVMWL74r5s7dMxYuPCqamiZtc6xWP7z5zW+Nq676VnR1dUUKCd/5zndv09SlS/8U11333bjzzttj5cqVsWFDW7S0TMlHIR522MvimGOO32Zq0ve85x1xxx1/6L3G2Wd/KtLPwQe/YJspT9N6iD/+8Q/i5z+/Of70p8Xx5JNrIpv9NKZPnx77739gvPa1R8bhh7+89zreECiKgICwKD2tnQQIECBAgAABAgQIECBAgAABAgQIECAwrgJ9hYOlCqTQMB1ftOi40q6afp01a3bMn/+cuOeexXHbbb/eJiD86le/FFdccWlv+ydPbo76+oZ46qkn4+6778x/brjhuvj61y/Jgr0Zeblp06bHzJmz4oknVuWfW1pa8rA17S9tjz/+eHzwg+/LpzZN+9K0pyl0bGtbH489tjL/+fnPfxbHHXdivP/9p5dO80qgEAICwkJ0s0YSIECAAAECBAgQIECAAAECBAgQIECAwHgKpGlEtx85uP390/EVK5bHnDlztz9Uk5/32efZeUB4//1/6W3fT37yo95w8IQTToqTTnpLpDAxbY88siIuu+w/s5GF38ksl8U3v3lFb7B49tlfyMu87GUvyl/f//4PxOted1T+vvSfz33uX/NwcOrUafHhD380Djvs8GhsbIw0qvDOO+/I10P8y1/+HN/+9jfijW88Nh+tWDrXK4FaF7AGYa33sPYRIECAAAECBAgQIECAAAECBAgQIECAwLgLLF16T1n3XLJkcVnlaqHQjBmteTM2bdqUj+JLH6666pv5vpe85LB473tP6w0H087dd58TZ5zxkXj2s/fNy9x11//mr+X8Z9myh+LXv/5lXvQDHzgz/u7vXpGHg2lHQ0NDvOAFL4ozz/xE76WGcu3ek7whUMUCRhBWceepOgECBAgQIECAAAECBAgQIECAAAECBAhUpkBbW1tZFUtr7RVlS8FcaVu/fn00N7fE6ad/OB8duNdee5cO7fCaRh6mkX7r16/b4Vh/O9L0oxdeeHE2CvHhLBz8+z6LlYLHdDDVx0agSAJPP41FarW2EiBAgAABAgQIECBAgAABAgQIECBAgACBMRRobm4u6+ppvb2ibFsHfCWffffdL9LP1ltaVzBNKfrAA/dnU5L+MX73u9vyw52dnVsXG/B9uv7zn39w/lMqmKYWTdOWPvTQX+O++/4cW48aHMq1S9fzSqCaBQSE1dx76k6AAAECBAgQIECAAAECBAgQIECAAAECFSkwb97+sXjxXYPWbf78AwYtUysF1qxZnTelqakpHz1YateqVY/H1VdfGbfd9ut48MH7Y8OGDaVD+WtdXc9qad3d3dvsL+fDH/7wu7jhhmvj7rvvysPBrYPA0nXTdYZz7XLurwyBShUQEFZqz6gXAQIECBAgQIAAAQIECBAgQIAAAQIECFStwB57PCPmzt0zGwn3UL9tSMfnzJnb7/FaO3DPPT3rLc6b95yYMGFC3rwU4J155um9U3xOmTI1Djro+ZGmHN1333n5CMArr/xG3HTTDUPm+I//OLd3jcN0v7Sm4TOfuU/svfc+MX/+c/J1CBctWjjk6zqBQC0ICAhroRe1gQABAgQIECBAgAABAgQIECBAgAABAgQqTmDhwqOyYOv6PkPCFA6m40XZ/vrXB+Lhh5fnzX3Riw7NX9vbN8YnP/mRPBzcb795ccYZH4n99z9wB5Jy13Pc+sRbbvlZbzh4/PEnxj/+49uitXXm1kWGtKbhNif6QKAGBASENdCJmkCAAAECBAgQIECAAAECBAgQIECAAAEClSfQ1DQpFi06LgvGlsXSpfdkU2e2RVpzME0rWqSRg6lnvvnNK/IOqq+vj9e9ricY/cMffh9pvcG0nXrqGX2Gg+nYfff9Jb1k04DmL2X95yc/+WFe7hnP2DPe977T+zyndN2eg0O4eJ9Xs5NAdQkICKurv9SWAAECBAgQIECAAAECBAgQIECAAAECBKpMIE03mn6Kut1668/j+uu/mzd/0aJjsnB0j/x9W9v6XpL+1gBM5y1b9te8XEdHR2/50pu0jmBXV1f201nalb+uX99z7f6um6719a9/pfecvq7de9AbAjUo0LOyZw02TJMIECBAgAABAgQIECBAgAABAgQIECBAgACBnSOQArelS/8UX/ziefGRj3wwG/3XHWka0Xe96329FTrggOdGCvjSdv75X4h7713ae2zZsofiggvOiy984ezefWlK0u23qVOn5rvuvvuubQ4ddNDz8s/Lly/L67B27dr8c6rXb3/766we/yduv/33veds3LjjtXsPekOgBgWMIKzBTtUkAgQIECBAgAABAgQIECBAgAABAgQIECAwHgJ3331nHH30a7a51aZN7ZHWDUwj+0rbi198WHziE5/OplidXNqVjyQ8+eRT4rLL/jP+/Oel8ba3nRSTJk3Kw8T29va8XEtLSyxY8OK4+eafxurVT0QKCdPUraXtoIOeH2mE4ve+d21W5if5Nf/rv/4njjvuTfHjH/8wHnjgvrjyym/kP1OmTM3qtb63Xvvvf0B2vfZ8CtNHHllRuqRXAoUQEBAWops1kgABAgQIECBAgAABAgQIECBAgAABAgQIjL5AGpFXWkewdPW0zmBLy5QsrJuTryv4yle+Ol7wgheVDm/z+o53/L+x777z4rvfvSobcbhkyzqNk2PvvfeJF7/4pXHMMcfFpk2b4pZbfhbpXr/4xS3xqlc9HUh+6EMfzQLDc7NRgb+JjRs3RJpaNJVL97/oov+M//7vS7Nzbs7WgVyeh4utrTPj2c/eN444YmH+c+ml/18eEP7617/M7r1hmwBzm4r6QKDGBCZkw3qtvFljnbp1czo6urK/qnh6Huetj3lPoKgCra0t0dBQl/0fBc9HUb8D2t2/gOejfxtHCHg+fAcI9C/g+ejfxhECng/fAQL9C3g++rdxhIDnw3eAQP8Cpeej/xKOlCNgDcJylJQhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUCMCAsIa6UjNIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCOgICwHCVlCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNSIgICwRjpSMwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUIyAgLEdJGQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQI1IiAgrJGO1AwCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC5QgICMtRUoYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAjQgICGukIzWDAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQDkCAsJylJQhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUCMCAsIa6UjNIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCOgICwHCVlCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNSIgICwRjpSMwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUI9BQTiFlCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgR0FHn54WSxdek+0tbVFc3NzzJu3f+yxxzN2LGgPAQIEKkhAQFhBnaEqBAgQIECAAAECBAgQIECAAAECBAgQIFAdAu3tG+Omm66P5csf2qbCixffFXPn7hkLFx4VTU2TtjnmAwECBCpFQEC4VU/cdtttcckll8Ttt98ea9eujZkzZ8aCBQvilFNOiYMOOmirkuW/Pfzww2PlypUDnrDPPvtk/5DcNGAZBwkQIECAAAECBAgQIECAAAECBAgQIECgcgT6CgdLtUuhYTq+aNFxpV1eCRAgUFECAsIt3XH55ZfHZz7zmfxTXV1dTJkyJR599NH43ve+FzfeeGN89KMfjZNOOmlInff444/3hoMpbEzX7WtLx2wECBAgQIAAAQIECBAgQIAAAQIECBAgUB0CaVrR7UcObl/zdHzFiuUxZ87c7Q/5TIAAgZ0uICDMuuCWW26Jz372s3lnnHzyyfHe9743ZsyYEY888kicc845+ei+T3/607HvvvvGoYceWnan/fGPf8zLNjY25veYOHFi2ecqSIAAAQIECBAgQIAAAQIECBAgQIAAAQKVKZDWHCxnW7JksYCwHChlCBAYd4G+h7SNezV23g27u7vjvPPOi/R6xBFHxMc+9rE8HEw12n333eP888+Pww47LLq6uuLzn//8kCpaCghTsCgcHBKdwgQIECBAgAABAgQIECBAgAABAgQIEKhYgba2trLqtmFDeeXKuphCBAgQGEWBwgeEad3BJUuW5KTveMc7dqBN04K++93vzvfffffdvWV3KNjHjsWLF+d7DzzwwD6O2kWAAAECBAgQIECAAAECBAgQIECAAAEC1SjQ3NxcVrUnTy6vXFkXU4gAAQKjKFD4gPBXv/pVzpmmFD3ooIP6pD3kkEOipaUlP3bzzTf3WaavnQLCvlTsI0CAAAECBAgQIECAAAECBAgQIECAQHULzJu3f1kNmD//gLLKKUSAAIHxFij8GoT33ntvbr7PPvvEhAkT+vSvr6+PvfbaK+65555YunRpn2W237lmzZpskdrl+e45c+bEhRdeGLfeemu+rmH665IDDjggjj/++FiwYMH2p/pMgAABAgQIECBAgAABAgQIECBAgAABAhUssMcez4i5c/fMfgf8UL+1TMfnzJnb73EHCBAgsDMFCh8QPvroo7n/HnvsMWA/pPUIU0C4cuXKAcuVDpZGD6bP73//+6O9vb10KH/985//HNddd12ccMIJ8YlPfCJSCGkjQIAAAQIECBAgQIAAAQIECBAgQIAAgeoQWLjwqLjppuv7DAlTOJiO2wgQIFCpAoUPCNeuXZv3zeTJkwfso0mTJuXH161bN2C50sE//vGPpbeRwsdTTz01XvziF0e6TwoPv/rVr8Ytt9wS3/rWtyJd+6yzzuot7w0BAgQIECBAgAABAgQIECBAgAABAgQIVLZAU9OkWLTouHj44WXZzHP3xIYNbdnvf5sjTStq5GBl953aESAQUfiAsLOzM/8eNDY2Dvh9mDhxYn68o6NjwHKlg62trfE3f/M3+bSlF1xwQUyZMqV0KNKahhdddFGcfvrpccMNN8Tll18exx13XOy33369ZUbrTX39hGht7Vk/cbSu6ToEql0gPRdp83xUe0+q/1gIeD7GQtU1a0XA81ErPakdYyHg+RgLVdesFQHPR630pHaMhYDnYyxUXXNnCLS2zo8DD5w/qrf2fIwqp4vVmEDp+aixZo17cwofEJZGBm7evHlA/E2bNuXHBwsSSxc59thjI/30t6X1Dj/84Q/HjTfeGF1dXXlQ+C//8i/9FR/2/nSfhoa+11Yc9kWdSKBGBDwfNdKRmjEmAp6PMWF10RoR8HzUSEdqxpgIeD7GhNVFa0TA81EjHakZYyLg+RgTVhetEQHPR410pGYQqECBwgeELS09o+s2btw4YPeUjk+dOnXAckM5uOuuu8aznvWsSOsR3nvvvUM5teyy3d3d0dnZXXZ5BQkUQSD9hUn6P1eejyL0tjYOVcDzMVQx5Ysk4PkoUm9r61AFPB9DFVO+SAKejyL1trYOVcDzMVQx5Ysk4PkoUm9r61AFSs/HUM9TfluBwgeEc+bMiTvuuCMeeeSRbWW2+1Q6vttuu213ZGQfS4FjKYAc2dV2PDuFg6tXr9/xgD0ECiyQpt1NI2s9HwX+Emh6vwKej35pHCCQT9vu3w9fBAJ9C/j3o28XewkkAc+H7wGB/gU8H/3bOELA8+E7QKB/gdLz0X8JR8oRqCunUC2XmTdvXt68+++/v99mpnUHH3zwwfx4OesEpulKv/nNb8ZXvvKV+OUvf9nvddOBxx57LD++yy67DFjOQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjIVD4gPClL31p7rhq1aq45557+jRNIwzb2tryYy95yUv6LLP1zrRO4XnnnRcXXHBB/Nd//dfWh7Z5f99998WyZcvyfS984Qu3OeYDAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbEQKHxAeMghh8Ree+2V21544YU7GHd1dUVpfyp70EEH7VCmrx2vetWr8t1pBGEKGLffOjs74+yzz853z5gxI4488sjti/hMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYNQFCh8QJtEPfehDOeyPfvSjOPPMMyONJkzbo48+Gqeddlo+TWh9fX38y7/8S76/9J9UfuHChflPer/19p73vCdaWloiTU+a3t94442xadOmvMif//zn+Od//uf4xS9+ERMmTIhPfvKT0dzcvPXp3hMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYE4GGMblqlV00jfZ773vfG1/60pfimmuuie985zsxderUWLt2bXR3d+ch3qc+9anYfnrRdLy0dmF6v/U2d+7cuOiii/JwMK0zmMLFFDJOnjw51q1blxdNU5F+7GMfi9e+9rVbn+o9AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgTETEBBuoU2j/A499NC49NJL8ylB16xZE62trZHWBnzb296Wvw61FxYsWBA33HBDXH755fGzn/0s/vrXv8bmzZvzKU0PO+yweOtb3xrPetazhnpZ5QkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMW2BCNkKue9hnO7HiBTo6umL16vUVX08VJDCeAq2tLdHQUJdNAez5GE9396oOAc9HdfSTWu4cAc/HznF31+oQ8HxURz+p5c4R8HzsHHd3rQ4Bz0d19JNa7hwBz8fOcXfX6hAoPR/VUdvKraU1CCu3b9SMAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwKgLCAhHndQFCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSugICwcvtGzQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMuoCAcNRJXZAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA5Qo0VG7V1IwAAQIECBAgQIAAAQIECBAgQIAAAQIECBRD4OGHl8XSpfdEW1tbzJgxLQ4++Pkxd+6exWi8VhIgMO4CAsJxJ3dDAgQIECBAgAABAgQIECBAgAABAgQIECDQI9DevjFuuun6WL78oW1I7rjj9th772fGq171umhqmrTNMR8IECAwUgFTjI5U0PkECBAgQIAAAQIECBAgQIAAAQIECBAgQGCYAn2Fg6VLPfjgA3l4WPrslQABAqMlICAcLUnXIUCAAAECBAgQIECAAAECBAgQIECAAAECQxBI04puP3Jw+9PT8RUrlm+/22cCBAiMSMAUoyPiczIBAgQIECBAgAABAgQIECBAgAABAgSKI7D1OnnNzc0xb97+sccezygOwCi3NK05WM62ZMnimDNnbjlFlSFAgEBZAgLCspgUIkCAAAECBAgQIECAAAECBAgQIECAQHEF+lsnb/Hiu2Lu3D1j4cKjrJM3jK9HW1tbWWdt2FBeubIuphABAgQyAVOM+hoQIECAAAECBAgQIECAAAECBAgQIECAwIACA62Tl6bATMdtQxdIozDL2SZPLq9cOddShgABAklAQOh7QIAAAQIECBAgQIAAAQIECBAgQIAAAQL9Clgnr1+aER9IU7SWs82ff0A5xZQhQIBA2QICwrKpFCRAgAABAgQIECBAgAABAgQIECBAgEDxBIayTl7xdEbW4rR+Y5qidaAtHbf+4EBCjhEgMBwBAeFw1JxDgAABAgQIECBAgAABAgQIECBAgACBgghYJ29sOzqt39hfSPjMZz4zX99xbGvg6gQIFFGgoYiN1mYCBAgQIECAAAECBAgQIECAAAECBAgQKE/AOnnlOQ23VFPTpFi06LhIU7mm0ZobNrTF9OnT4pBDDo40wnD16vXDvbTzCBAg0K+AgLBfGgcIECBAgAABAgQIECBAgAABAgQIECBAIK2Tt3jxXYNCWCdvUKIBC6QwMP2krbW1JRoa6qKjo2vAcxwkQIDAcAVMMTpcOecRIECAAAECBAgQIECAAAECBAgQIECgAALWyStAJ2siAQKFExAQFq7LNZgAAQIECBAgQIAAAQIECBAgQIAAAQJDExhonby0fl46biNAgACB6hEwxWj19JWaEiBAgAABAgQIECBAgAABAgQIECBAYKcI9LVO3uTJzZGmFZ0zZ+5OqZObEiBAgMDwBQSEw7dzJgECBAgQIECAAAECBAgQIECAAAECBAolsPU6eYVquMYSIECgxgRMMVpjHao5BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAYSEBAOpOMYAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRoTEBDWWIdqDgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGBBASEA+k4RoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDGBASENdahmkOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgIAEB4UA6jhEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoMQEBYY11qOYQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGEhAQDiQjmMECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEakygocbaozkECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIjFHj44WWxdOk90dbWFs3NzTFv3v6xxx7PGOFVnV4pAgLCSukJ9SBAgAABAgQIECBAgAABAgQIECBAgAABAgR2moBArIe+vX1j3HTT9bF8+UPb9MXixXfF3Ll7xsKFR0VT06RtjvlQfQICwurrMzUmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIERklAILYtZF/hYKlECg3T8UWLjivt8lqlAgLCKu041SZAgAABAgQIECBAgAABAgQIECBAgAABAgRGLlC0QGygkZLp2PYjB7cXTsdXrFgec+bM3f6Qz1UkICCsos5SVQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGD0BIoUiJUzUjKtOVjOtmTJYgFhOVAVXKauguumagQIECBAgAABAgQIECBAgAABAgQIECBAgACBMRMYSiA2ZpUYpwuXM1Kyra2trNps2FBeubIuptBOERAQ7hR2NyVAgAABAgQIECBAgAABAgQIECBAgAABAgR2tkBRArFyR0pGdJfVJZMnN5dVTqHKFRAQVm7fqBkBAgQIECBAgAABAgQIECBAgAABAgQIECAwhgLNzeUFXdUeiJU7UrK7vHww5s8/YAx7xaXHQ0BAOB7K7kGAAAECBAgQIECAAAECBAgQIECAAAECBAhUnMC8efuXVadqD8TKHSlZVzch5s7dc0CTdHzOnLkDlnGw8gUaKr+KakiAAAECBAgQIECAAAECBAgQIECAAAECBAhUm0Ca1jKNXEvhVBqpl8K4PfZ4RkU1I9UnBV7Llz/Ub71qIRAbykjJV7ziNdHfeoXJYuHCo/q1cqB6BASE1dNXakqAAAECBAgQIECAAAECBAgQIPbAKA0AAEAASURBVECAAAECBCpeoL19Y58B0+LFd+VhXAqYmpomld2OsQ4aU31qPRBL4WzyH2xLIyVT3yxadFyU3DdsaIs0xWo6ZuTgYILVc1xAWD19paYECBAgQIAAAQIECBAgQIAAAQIECBAgQKDiBfoL21LF00i9dDwFUINtox009ne/IgRiwxkpmc6ptBGf/fWh/UMXEBAO3cwZBAgQIECAAAECBAgQIECAAAECBAgQIECAQB8CadTZQNN1plPS8RUrlg86Gm20gsY+qtnnrloPxIowUrLPjrWzTwEBYZ8sdhIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJDFUhrDpazLVmyeMCAcDSDxnLqU4QyRRgpWYR+HK02CghHS9J1CBAgQIAAAQIECBAgQIAAAQIEBhUorWfU1tYWzc3NkdZEMn3ZoGwKECBAoGoE0v++l7Olde0G2kYraBzoHkU9VusjJYvar0Ntt4BwqGLKEyBAgAABAgQIECBAgAABAgQIDFlgvNaRGnLFnECAAAECoyqQ/vijnG3y5IHLjVbQWE5daqGMP8CphV4c3zYICMfX290IECBAgAABAgQIECBAgAABAoUUGO91pAqJrNEECi4gIKmML0AaGb548V2DVmb+/AMGLDNaQeOAN6mBg/4ApwY6cSc1QUC4k+DdlgABAgQIECBAgAABAgQIECBQFAHrSBWlp7WTwM4REJDsHPf+7pqmr5w7d89Yvvyh/orkx+fMmdvv8XRgtILGAW9SAwf9AU4NdOJOakLdTrqv2xIgQIAAAQIECBAgQIAAAQIECBREYCjrSBWERDMJEBhFgXICklG8nUuVIbBw4VF5CNhX0RQepuODbaWgcaBy6VqDBY0DnV/tx4byBzjV3lb1H30BIwhH39QVCRAgQIAAAQIECBAgQIAAAQIEthKwjtRWGN4SIDCqAkMJSIocJI0qehkXa2qaFIsWHRelaV83bGiLtOZgmlZ0KP2QgsT+AuByg8Yyqlu1RYbyBzhDca9aEBUfkoCAcEhcChMgQIAAAQIECBAgQIAAAQIECAxVwDpSQxVTngCBcgUEJOVK7ZxyaRRg+hnuNlpB43DvX855pRA0/TFM+vcuTY06kjaXc89SGX+AU5LwOhwBAeFw1JxDgAABAgQIECBAgAABAgQIECBQtoB1pMqmUpAAgSEKCEiGCFalxUcaNI5Fsyth7Ut/gDMWPVuca1qDsDh9raUECBAgQIAAAQIECBAgQIAAgZ0ikH6xm6aCG2gr+jpSA9k4RoBA/wICkv5tHBlbgf6mPk13Xb78oXxq1LGtQeSjFcu5R5ratdq3ru7uWL2uI5Ys3xB/uHdttTenIupvBGFFdINKECBAgAABAgQIECBAgAABAgRqW8A6UrXdv1pHYGcJGKG8s+SLfd9KWfuy9Ac4KZDsb6umP8DZsKkrHntyc/bTkb+u3PI+vT6e7dvc2d3bzBvPObj3vTfDExAQDs/NWQQIECBAgAABAgQIECBAgAABAkMQqIZ1pIbQHEUJEKgQgVoLSCqEVTUGEaiktS+r6Q9wurq644lsFODKNdsGgCkUTCHg2g1dg8g7PJoCAsLR1HQtAgQIECBAgAABAgQIECBAgACBAQUqcR2pASvsIAECFS9QTQFJxWPWaAXTiL8U6qU1K9O0tGnkafr3aLhbJa19WWl/gLN+Y2cW9vUEgD3B35YwcM3mWLW2IzplgMP92o36eQLCUSd1QQIECBAgQIAAAQIECBAgQIAAAQIECBAYL4FKC0jGq93uM7hAe/vGfC3A7afgXLz4rnxt3BQup+/PULdKXPtyvP4ApyOb5nPVU9kowHz6zzTyb9swsK1dAjjU79POKi8g3Fny7kuAAAECBAgQIECAAAECBAgQIECAAAECoyYwXgHJqFXYhcZc4Kabro/tw8HSTdP+dHzRouNKu8p+Hcnal6M9mrHsSpdZsLu7O5vqszNfB7B3DcBs9F9pNGCaIjQrMq7bpIkTYtfpjbFL9rPr9IbYe07LuN6/Vm8mIKzVntUuAgQIECBAgAABAgQIECBAgAABAgQIECBQUIEUxPUXDpZI0vEVK5bHnDlzS7vKek1h9Ny5ew54/XR86+uO1WjGsiq8XaFNm7visWwU4OP52n9PjwZ8LBsNmELB9s3jmwDWTYiYNa2hNwBMQWApDEyvUybVxYQJWaEtW2urgLBkMZJXAeFI9JxLgAABAgQIECBAgAABAgQIECBAgACBnSxQ6SOSdjKP2xdUIK05WM62ZMnibYK8cs5JZYa69uVYjWbsq75d2RC/J9entQDTyL8tawCW3mejAVdnx8Z7SyFfT/BXCgKz0YAzsvfTGmPm1IZoqH86ABzvuhX1fgLCova8dhMgQIAAAQIECBAgQIAAAQIECBAgUNUClTQiqaohVb4mBdra2spq14YN5ZXb/mJDWftyLEYzbtyUjQLcMgKw5/XpMDCFgpuztQLHc2uoj5idhX1pCtDSCMBdsvc9U4M2RHNTVsBWUQICworqDpUhQIAAAQIECBAgQIAAAQIECBAgQIBAeQLjOSKpvBopRaByBJqbm8uqzOTJ5ZXr72LlrH05nNGMXV3dkdb7W7mmZwTgY09t7n2fRgau3dDVX5XGbP/05vos/NtuBOCW6UBbW+qjLs0VaqsaAQFh1XSVihIgQIAAAQIECBAgQIAAAQIECBAgQKBHYCxGJLElUEsC8+btH4sX3zVok+bPP2DQMiMtUO5oxj89uDpuu/rhfFrQx7NAsHOcM8CJDRO2CQCfHgGY1gRsiKbGupFSOL+CBASEFdQZqkKAAAECBAgQIECAAAECBAgQIECAAIFyBIYzIqmc6ypDoFYE0si+uXP3jOXLH+q3Sen4nDlz+z0+0gMd2TSfq57qiI2dE8u61Ion6+P+VRvKKjucQml8X+uUNAowBX5PTwe664yeADCNEJwwwSjA4dhW4zkCwmrsNXUmQIAAAQIECBAgQIAAAQIECBAgQKDQAuWOSBru+mqFxtX4mhFYuPCo6G8q3hQOpuMj2bq7u/OpPrdfAzBNAZrWAVy1tiOyIjF1wqw4sGnwOz3euefghQYpMWnihC3r/j0dAJZGAs6a1hATG4wCHISwMIcFhIXpag0lQIAAAQIECBAgQIAAAQIECBAgQKBWBMZrfbVa8dKOYgo0NU2KRYuOizQlbxp1mwLztOZgmla03JGDmzq64vFsFOBja7I1ALPQL60F+Fi2LmBPCLg5Nm7OEsBBtrXds+LJztkxvf7xfkum46ncYFta5m/m1IYtIWD2mo/+ezoMnDKpzijAwRAdzwUEhL4IBAgQIECAAAECBAgQIECAAAECBAgQqDKBSlpfrcroVLeAAmm60fTT19aVDfF7cn1nNuKvZ9RfCv5KIwDTvtXrOvs6bcj7lm4+NObFbX2GhCkcTMdLW0sW8u2aTwNaCgJ7pgBN+1I42FBfzGlAS0Hv5s3tMXXqlDjqqJGNAC15F/VVQFjUntduAgQIECBAgAABAgQIECBAgAABAgSqVqAS1lerWjwVL5zAxk1deQCYjwDcKggshYKbs7UCx3rrjMa4Z/PfxNSOVbFLw0MxpXFzNGYjHKfM3i+en62D+KrppTCwIZqb6se6OlV1/fb2jX1OFSsgHFk3CghH5udsAgQIECBAgAABAgQIECBAgAABAgQI7BSBsV5fbac0yk0JDEOgq6s7nliXTf+ZTQFamvpzZTYNaB4AZtODPtU2OqMAh1K16c31UVr7b3Y28m/XUgA4Y+9obVkQdWmuUFtZAv2tI1nWyQr1KyAg7JfGAQIECBAgQIAAAQIECBAgQIAAAQIECFSuwGisr1a5rVMzAtsKrN+YpgF9OgB8+n1Htkbg5ujs2rb8WH9qzKb53HVGQxYCpvCvMWZvCQBTEJj2NTXWjXUVCnH9NK3o8uUPFaKt491IAeF4i7sfAQIECBAgQIAAAQIECBAgQIAAAQIERlFgoPXVRvE2LkVgTAU6smk+V63tGfWXjwJMIwCz4C+fFnTN5ljfPs4JYNba1in1W9YC7BkBmIK/FATulr1Ob6mPCROMAhzTL0V28aVL7xnrWxT2+gLCwna9hhMgQIAAAQIECBAgQIAAAQIECBAgQIAAgfER6O7ujnUbu2JlFvalqT+3Xw8whYNZkXHdJjWmUYCNscu07CcbDZhGApamBZ01rSEmNhgFOK4d0sfN2tra+thr12gICAhHQ9E1CBAgQIAAAQIECBAgQIAAAQIECBAgQIBAwQU2dXRl031uWfuvNB1oNhIwHxGYjQbcuGl8E8A0wG/W1K2CvzwM3DItaPZ+yqS63lGAaSrLpUtvj+UPt8Xq5uaYN2//SKNzbTtXoDnrC9vYCAgIx8bVVQkQIECAAAECBAgQIECAAAECBMoQ6PmF7D2RRgikXwL6hWwZaIoQIEBgJwmkUYBPru/sCfxKAWD22jMicHOsXtc57jVryUK+0si/0nqApVGAM7NwsCFbK3Cgrb19Y9x00/U7rHO3ePFdMXfunrFw4VGR1vu07RyB9P8LUl/YRl9AQDj6pq5IgAABAgQIECBAgAABAgQIECAwiIBfyA4C5DABAgR2ksDGTV154PdYNhKwtBZg/ppNC5pGB27qGN9RgPXZLJ+zsylAd83W/ttlywjAPBDc8r5lUv2IpPoKB0sXXL78oTw8XLTouNIur+MskEZxpqA29YVtdAUEhKPr6WoECBAgQIAAAQIECBAgQIAAAQJlCPiFbBlIihAgQGAMBLq6uuOJdWnU35YAMK0HmE0D+lg2BWja91Tb+I8CnNZc37v2X88owJ5pQWdnoeDMKQ1RVzfwKMDhMqVR7IMFT+n4ihXLY86cucO9jfNGKJBGcQ70/xtGePnCni4gLGzXazgBAgQIECBAgAABAgQIECBAYOcI+IXsznF3VwIEiiOwfmNnFvhlod+aLPzLAsCnw8CObBTg5ujsGl+LxmyazzTtZwr/8uk/s9F/+SjAaT37Jk3MhgnuhG3p0nvKuuuSJYsFhGVJjU2hNMVrGsVZmpa8o6M9pkyZMjY3K9BVBYQF6mxNJUCAAAECBAgQIECAAAECBAhUgoBfyFZCL6gDAQLVLNDRmY0CXFsaAVh6TWFgTyi4vn2cE8AMs3VKfR76pVF/KfwrrQuYXqe11EfdhLEZBTiSfkzr35azbdhQXrlyrqXM8AXSdKPpp7W1JRoadk6oPPzaV96ZAsLK6xM1IkCAAAECBAgQIECAAAECBAjUtIBfyNZ092ocAQKjINDd3R1Pru+I5Y9tjL8sW5evCbgyGw1YGgmYwsFsptBx3SY1plGAfYwAzEYDzs5GAk6swsCmubm5LMPJk8srV9bFFCJQIQICwgrpCNUgQIAAAQIECBAgQIAAAQIECBRFwC9ki9LT2kmAwEACmzq6YlU2Dej2U4A+lqYEzfZvGOdRgGmA36ypPaP/StOB7rplWtBdsxBwyqS6mFCBowAHMh7s2Lx5+8fixXcNVizmzz9g0DIKEKg2AQFhtfWY+hIgQIAAAQIECBAgQIAAAQIEqlzAL2SrvANVnwCBsgR6RgF29gaAKfjLpwDNXzfHmnWdMdJBgFMnPB6z65dF44T22NzdFI937hlru2f1W7+WprreNQDTaMDSNKDpfQoHG7K1Aou0pekq587dM5Yvf6jfZqfjc+bM7fe4AwSqVUBAWK09p94ECBAgQIAAAQIECBAgQIAAgSoV8AvZKu041SZAYAeB9s1dPdN/Zmv/5SMB12RrAD6VpgLtmQ50U8dII8AdbpnvqI/NMa/xtphe//g2BXZreDA21O0SnbMOj12zddrSSMA8BMxGAO6STQPaMql+m/I+RCxceFTcdNP1fYaEKRxMx20EalFAQFiLvapNBAgQIECAAAECBAgQIECAAIEKF/AL2QrvINUjQCAX6MoW+ntiXRb6ZQHg9iMA076n2jrHXWrq5LrYr/53MbFj23CwVJHJXY/F3Im/jUWvOq60y+sAAk1Nk2LRouPi4YeXxdKl98SGDW2R1hxM04oaOTgAnENVLyAgrPou1AACBAgQIECAAAECBAgQIECAQPUJ+IVs9fWZGhOoVYG29jQNaE8AmEK/npGAPdOBPp6NBuzsGt+WN2bTfO4+c2LMmdkUae2/aZMiGwmYpgNtyF+fePzh+O53Vw5YqTRl5ooVywVcAyptezCNbk8/NgJFERAQFqWntZMAAQIECBAgQIAAAQIECBAgUIECfiFbgZ2iSgRqTKCjMxsFuHZL8Nc7ErBnCtAUBq7fOM4JYObb2lIfu6RpP7dMAZqmAZ295f307NismVOioaEuOjq6YvXq9dv0SBrlVs62ZMliAWE5UMoQKKiAgLCgHa/ZBAgQIECAAAECBAgQIECAAAECBAgQqAWB7u7uWJeFfNtMAbomCwCf6hkVuCp7zWYKHddtUuOELaP+ng7+0gjA2VkQmNYCnNhYN+z6tLW1lXVumirTRoAAgf4EBIT9ydhPgAABAgQIECBAgAABAgQIECBAgAABAhUhsLmjO9J0n/n0n72jAEvrAm6OjZvGNwGcMCFi1tQ05WdDNvVnGgn49BSg6X1aJ3BCKjQGW3Nzc1lXTevo2QgQINCfgICwPxn7CRAgQIAAAQIECBAgQIAAAQIECBAgQGBcBNIowCfbOrNRgNlUoGn0Xzb159PrAm6O1es6Y3wjwIiWprp8GtB87b9pWQg4IwsEs9e0LmAKBxuytQJ3xjZv3v6xePFdg956/vwDBi2jAAECxRUQEG7V97fddltccsklcfvtt8fatWtj5syZsWDBgjjllFPioIMO2qpk+W/TP2zXXHNNXH311bFkyZLYvHlz7L777vHyl7883v72t8euu+5a/sWUJECAAAECBAgQIECAAAECBAgQIFBhAg8/vCzSmmhp2sM0simFF2ltSRuB7QXaN287DWgeBmZBYAoD0/tN2SjB8dzqs1k+Z6fgr3cU4NOjAdO+lkn141mdsu+Vnq+5c/eM5csf6vecdHzOnLn9HneAAAECE7IAa3z/V7dCzS+//PL4zGc+k9eurq4upkyZEk899VT+ub6+Pj760Y/GSSedNKTad3V1xWmnnRY33nhjfl5jY2NMnDgx1q/vWVR2xowZcdFFF8XBBx88pOsOpXBfi9gO5XxlCdSiQGtrS7+LPNdie7WJwFAEPB9D0VK2aAKej6L1uPYORcDzMRQtZYsm4PkoWo8Xq73t7Rvjppuu7zOkSOHEwoVHRVPTpH5RPB/90lTtga5sob/V67NRgNkIwDQVaBoB+Hj+2hMAphGC471Na67PA8CekX9PjwBMAeDMKQ1RV7dzRgEO5jDY8zHS52+w+ztOoJIFSs9HJdexGuomIMx66ZZbbol3vvOdkbLSk08+Od773vdGCu8eeeSROOecc7L/o3NT9g9FXVx66aVx6KGHlt2vX/jCF+Liiy+OFAx+/OMfjze84Q15QHjXXXfFWWedlf1l1dJ8lGIKENP9xmITEI6FqmtWu0DpHxDPR7X3pPqPhYDnYyxUXbNWBDwftdKT2jEWAp6PsVB1zVoR8HzUSk9qR18C11777T7DwVLZFBIuWnRc6eMOr56PHUiqYseG9q4t4V9P6JeCwJ4QMAsDszUCO8Y5A2zMpvlMYV/PGoA9owG3Xg9w0sRsmGAVbuU+H6URvBs2tEVaczBNK2rkYBV2uCoPSaD0fAzpJIV3EBjxFKNXXHFFvP71r4/p06fvcPFq2JFCwfPOOy8PB4844oj42Mc+1lvtNBXo+eefn48k/OUvfxmf//zn86lCewsM8ObRRx+Nyy67LC9xxhlnxPHHH99bOk1XmsLG5LZq1ap8FOGHPvSh3uPeECBAgAABAgQIECBAgAABAgQIEKhkgRRKDDS9Yap7Or5ixXJhRSV3ZB9168xGAT6xNlsHMI38W9OxZS3AFAL27Fu3sauPs8Z2V2tLNgowW/cvDwK3rAGY3u86vTGmZ8fqJlTmKMCxVem5eppudGdM6VsKJk0tPB697B4ExkZgxAHhpz/96fjc5z6Xr6m3aNGi/LWhYcSXHZvW9nHVtO5gWhswbe94xzt2KJFGDr773e+OFBDefffdedn58+fvUG77HVdeeWVs2rQppk2bFm9605u2P5yPHHzzm98cX/ziF+Paa6+ND3zgA5GmMrURIECAAAECBAgQIECAAAECBAgQqHSBtOZgOduSJYsFhOVAjWOZNGAihXxp3b80BWjP+n9Pv1/1VEdkGeG4bk2NE/Kwb+uRgLtmAeDsLADcZVpDTGyszlGA44o4Tjfrb2rTxYvvytdFHGxq4XGqptsQIFCGwKgkeZs3b44f//jH+U8aSZhGxh199NHxvOc9r4wq7Nwiv/rVr/IKpCk+08i+vrZDDjkkWlpa8rUDb7755myY9uABYem6aUrStO5gX9vhhx+eB4RpFOGdd94Z6T42AgQIECBAgAABAgQIECBAgAABApUukEYNlbOlaQ9t4y+wuaM7Hl+bTQGajQBMIwG3DQM7YsOm8R0FmAb4zZqapgHddg3ANAIwTQc6dXJdTCjwKMDx/4YM/479rTuarphGDafjA00tPPw7O5MAgdEWGHFAmEa/pZ8bbrgh0rSaa9asiTTtaPrZZ5998nX3UliYpuusxO3ee+/Nq5Xq2t8/Qmlk31577RX33HNPvm5gOe0oXXffffftt3i6Z2lL6xEKCEsaXgkQIECAAAECBAgQIECAAAECBCpZoLm5uazqpTXRbKMvkEYBPtnWmQV/WQC4JgsAs7X/et9ngeDqdZ0xzoMAo6WpricAzAK/PPib0TMF6C7ZlKCzslGADdlagbbqFjC1cHX3n9oT2F5gxAFhGk2X1tj74Ac/GL/+9a/juuuuix/+8If5aLv77rsvX8PvP/7jPyKNpHvDG94Qr3nNa7LFUidvX4+d9jmFmmnbY489BqxDCjhTQLhy5coBy6WDGzZsyNctTO/nzJmTXvrcpk6dGun/TKW/uCrnun1exE4CBAgQIECAAAECBAgQIECAAAEC4ywwb97+kaYUHGxra1sf3//+tfnvwNI5O2OttMHqWKnH2zenaUCfXgMwDwC3jAZM7zdlowTHc6vPZvmcnYV9pbX/tp4ONL1vmWT5pPHsj51xL1ML7wx19yQwdgIjDghLVUuj71760pfmP5/85Cfz6UbTyMK0dl9HR0ceHv7mN7+JT33qU/HqV786DwtT+Z29rV27Nq/CYKHlpEmT8nLr1q0btMqla6aCg103HU8BYTnXHfTGfRSoz/4yp7W1pY8jdhEorkB6LtLm+Sjud0DL+xfwfPRv4wgBz4fvAIH+BTwf/ds4QsDz4TtQqwKtrfPj9tufGQ8++MCATXzggft6j6dAce+9nxnHHntcpN+1Ff356MwW+nsimwb0kSc2xaOrN8Uj2c+j2fv0mn7WrOvotRuvN9Nb6mP31qbYrXVi7D4z+8leS+9nZeFgfZ1RgOPVF5X4fGze3F5W8zs62v1OuiwphYYrUHo+hnu+83oERi0g3Bq0qakpjjzyyPzniSeeyOYdvil++tOfxm233ZaPrkujDNPPbrvtls1HvCiOOeaY7P8c7L31JcbtfWdnZ36vxsbGAe9ZWkcwhZ2DbaVrpnLlXnfrcwa7/lCOp+C2ocE/3EMxU7Y4Ap6P4vS1lg5dwPMxdDNnFEfA81GcvtbSoQt4PoZu5oziCHg+itPXRWrpm950Qlx55ZVx//33l93sFChec81V8Za3vKX3nFp+PtZv7MwCwPY8BFyRwr8t7/MwMAsBOzrHdxRgY/Z7whT67f7/s3cnUJLdZeH3n66lq/fpnl4mPZ3JAjJjIglhkZ1XUHwdIqFlGUFQNkWOIOo5eEQ4B87xoHJAUMOiLwoK/79yiIloDMgIoqgoiIFEJulkJpDMkp5Jepnu6aWqq2t7f8+9dbure2q5XcutW/d+7zk9VX3vrXvv7/Or6umup57n2Z+wAoCTGgTU+xoINPf7EmQBbj0xfXLHT6+PwcEBVyoDAwPmPWmTcsqCAAK+FmhJgLB0xPv375fXvva18prXvEa+/vWvywc/+EE5e/astctjjz0mf/Znf2Z9Pfe5z5W3ve1t8vSnP7304S2/72QGZjKZqufa3Ny0ttcK+OlOGiB1lmYe1znmXm61HnnO41809nJ97ItAOwT0Eyb6yxWvj3boc06/C/D68PsMcX3tFOD10U59zu13AV4ffp8hrq+dAuVeH2fPnpETJ05Y7Vn6+/vlhhtulKuuuqqdl8m5EahLIBbrNu/7/bz1Xt+JE98zVbLWJW+y4r7//YeqHk8Dio88clquuebqjv/7XN930/5/j2vgTzP/SjIANStw1fQJ9HrZPxizs/62sgBNRmAxG3BkICaRKlmA2Wze68vlfBUEyv3/UWFXz1b/yI/cIN/97ndrnu/JT77BVBXkuVQTih3qFnBeH3UfgAdaAi0NEGq23b/927/Jl7/8ZfmP//iPrb58+qa8vjl/0003WZ8wunTpkvznf/6nfPOb35Q3vOEN8q53vcuz6dFfxHXZ2Nioek5nu/YNrLXoJyScxXmc8/3uW+1XqEvpY3bv08j3+kvK0tJ6I4fgsQgETkDL7mpmLa+PwE0tA2qCAK+PJiByiMAK8PoI7NQysCYI8PpoAiKHaIvA+fOPivZT0tYffX190or+aKWvj8ceWzRVlu6S2dlzO8Z77733yNTUITl69BbzoWO7xcmOHfgGAZ8LDA6OynOf+yLrKr/+9a+6utq77/6uHDp0le//Ptf3Mdc2tBdgxuoHOFfsAThX7A24uJIVExP1dEnEu2Rin90LcNy6jZvvY6Y3oFk3FJPueIXMrdymXLpkJ0F4esGcrC6B0v8//PL+rr7W9f+r3f+PlQ5Qtw8MjPKedCkK95su4Lw+mn7gkB2wJQHCu+++2yoh+k//9E87goJqq6VEf+Znfsb6mpycFM2w++pXvyqf+MQn5Ac/+IF85jOfkSuuuMIKFHoxF3oN9957r2g2Y7XF2a5lUWstWo50dHRUFhcXqx5XexXqHyG6uDlurfOyHQEEEEAAAQQQQAABBBBAAAEEaguk0xtlA3XaH62VgbpywUHnavXNVt0+PX3MWcUtAh0p4LzXVeviUyn7PbFa+3mxPZMtyILpBTi/nBUnADhvAoD2/aykNr3NhDJ5FTJqsgA12KdBv4lhOxjoBAUHe6NW8oUXNpwDgd0C+mGWSv+fOf+H7n4M3yOAgD8FmhYgPHXqlNx1113ypS99SS5cuGCNVj9ho4tm3b3kJS+Rl7/85fLUpz7VWuf8oyU7b775Znn2s59tbX/88cflc5/7nGcBwsOHD1sZjtVqpWsm5JkzZ6xLftKTnuRcetVbPa5mRD788MMV9yvdpvuzIIAAAggggAACCCCAAAIIIIBA6wUqvbGpZ25VoE7brVTLuHDOfeHCrExOTrUegTPsWcCLjNM9X5QPH6DZuG6W3l53+7k5Vq199D3KS6bUpwb9NBPQCfzNLZugoMkAXFrNisdJgKbXX2Qr688J/FnBQBMQHDWBwZhpj8KCgB8FNNNdP8zi/EzUYL++no8cuZ7/v/w4YVwTAlUEGg4Qag/BL37xi/LQQ3ZtcScoGIlE5HnPe54V9PvJn/xJ0ay6aov2KtQ+hH/3d3+3FWCstn+ztj3nOc+RW2+91cr2e+CBB+S666677NCaYeh8+kkDmW4WPa4GCL/97W9bWZLlehd+4xvfsA41NDQk119/vZvDsg8CCCCAAAIIIIAAAggggAACCDQgoG9otiNQp/3Z3CwnT87wBqsbKA/3aVfGqYdDbOqptFSvZuPWWjSY0MwlndEyoDsDgKXBwE2TJejlEjVVPjUL0M7+KykBqhmBphxof0/Uy8vhXAg0XeDgwStFv1gQQKBzBRoOEP7hH/7hVjNhZXjiE59olQ992ctetueymU6/voMHD3omqhmN2ghcP8mnZU4//vGP7zh3Pp+31utK3feGG27Ysb3SNz/90z9tBR4vXrxYNiNS1//1X/+19fCf+7mfM/XWG56KSpfCegQQQAABBBBAAAEEEEAAAQQQKApoz0E3S7MDdevr625OK34qu+jqgkOwUzsyTnezOpk6reyXufuc9X6vAQMtM1gtEK/b95opmzdZgEtrmgWovQBNFqApB7oVADRZgJfWc/Vect2PG+yN2CVAtfefCfrZmYBaEjQmIwMxiUbIAqwblwcigAACCLRcoClRKc2A0zKhWkL0xhtvrPuiNaio/Qmf8IQn1H2Meh74rne9S97+9rdbvRDf/e53y2/+5m9aPQS13OkHPvAB+a//+i+JRqPyG7/xGzsOr70TP/KRj1jr3vnOd4pmSjrLlVdeKT//8z8vn/3sZ+VDH/qQaGbla17zGunp6ZH77rtP3vOe91hZi5o5+cY3vtF5GLcIIIAAAggggAACCCCAAAIIINBCAadCUK1TNDtQ19/fX+uU1nYvyy66uqCQ79SujFOHvVOzF+vtUZZK58v0ANSSoFlZWMlI1uMYYNyU+Rwzgb/xoWIGoPYCNOU/nazA3m6TJsiCAAIIIIBAhwo0HCDU8pwvetGLapYQdeOjx2nH8uIXv1je8Y53yMc+9jH5whe+YJU51b6Jq6urVmCvy3QG/p3f+R2rT2Lp9el2p3eh3t+9aNBQt//7v/+7FWj88Ic/LIlEQtbW1qxd9Ryf+tSnRIOELAgggAACCCCAAAIIIIAAAggg0HqBdvVHu+GGG+Xee++pOcBml12seUJ2qCrQroxT56L8kL3oXMtebiv1KPuhJ10niYED8v3HNQtwRVbTK/K46QN4YTFtfa1t5PdymqbsO9wfLWYBmkDgrkzA4YGoRMz7giwIIIAAAggEUaDhAOFP/dRPBcLlV3/1V+WZz3ymlfGnPQeXl5dlZGREnv70p8ub3vQm63avA9Vg4Cc/+Ukr4Ki9FU+ePGlKhaRMmYUpef7zny9vfetbrft7PS77I4AAAggggAACCCCAwN4FOqk8295HxyMQQMCtQLv6o2l7k1aUXXQ7bvarT6BdGad6te3OXqxHTCtorZsg35xVBjRrbvtlIXOTzK2bgOD5jCzem5Zc/mw9h677MYl4l1X6UzMBrRKgJRmAmg3YHScLsG5cHogAAggg0NECDQcIO3r0uy5eA4T65XZ5xSteIfpVbYlEIvLKV77S+qq2H9sQQAABBBBAAAEEEECgNQKdWp6tNRocFQEEWtUfzY1svWUX3RybfVoj0K6MUx1Nu7MXK4lmsgVZWNUMwGIPQJMBqPc1KLhgegEmTZlQLxfN79s/qME/OwNQy3+OaRDQZANqL8DB3qhodTAWBBBAAAEEENgpQIBwpwffIYAAAggggAACCCCAQMAEOrU8W8CmgeEg4CuBdgXqKpVd1LKik5NTvjLiYmyBdmWc6tnblb2oWYAryZzV92/eBP2cbED7flaWVrNS8PgJ0peIbAUANfh3QHsBagDQfI2a72OmVyCLfwWo4uDfueHKEEAg3AIECMM9/4weAQQQQAABBBBAAIFAC3RiebZATwiDQ8AnAu0O1GkWo36x+F+gnRmnrcxeTGfydgbgisn+MxmAc042YLE06KbJEvRyiZoqn6OaBaiBvyEN/hXvW0HAmPT3RL28HM7VJAGqODQJksMggAACLRIgQNgiWA6LAAIIIIAAAggggAAC7Rfwa3m29stwBQggoAIE6ngeuBFoV8ZpI9mLeZMFuLymWYBa/nO7BKhTCvTSes7N0Ju6z2BvxMr6szP/7HKgT7hyUK4cT8hwX0xWVpJNPR8Ha78AVRzaPwdcAQIIIFBNgABhNR22IYAAAggggAACCCCAQEcLtKs8W0ejcfEIIIAAAjsE2pVx6iZ7cXRiSmbX9sm9dy9bgUAnE3DeZAZmPY4BxkySn539p6U/TQDQygbczgrsNWVCdy8jI/0Si0Ukm/W2b+Hu6+D75gtQxaH5phwRAQQQaLYAAcJmi3I8BBBAAAEEEEAAAQQQ8I1AK8uz+WaQXAgCCCCAgCcCXmec5vIFecZzXyLr//IlWV6cvWyMl3Jj8j9nnyK5s49ftq1VK/b1R62+f1YJUFP+c/s2LsMDUYl00QuwVfbtOm69/QOp4tCuGeO8CCCAgHsBAoTurdgTAQQQQAABBBBAAAEEOkygkfJsHTZULhcBBBBAoMMECqYM6PpG3ioDurCSlTnTC9ApAaplQRdXs5KzEuueIYNd18pY9JzEu9KSKSRkIXdIVgujTR9xd6zLDgAOm8w/KwC4HQQcG4pJIn55FmDTL6LMAesNUpU5FKtcCjTaP7CdVRx4vricZHZDAIHQCxAgDP1TAAAEEEAAAQQQQAABBIIr4KY829TUIZmcnAouAiNDAAEEEGibQDZXkAVT7tMp/alBQCsYWOwLmEy7K62pwcDVbOMBQc3v2z+owb+YjJkAoB0EtIOBEyYoONgblS4fZQE2GqRq28QH4MSN9g9sRxUHni8BeOIxBAQQ8FSAAKGn3JwMAQQQQAABBBBAAAEEvBY4evQWqfQmlwYHdTsLAggggAAC9QhoFuBKMrcVACzNANSg4JLJAizUc+AGHtPbHREN9jkZgNvBQBMUHIpLLOrfMqC7M7/m5h6XhYW5shqzs+es/9+np4+V3c7K+gV0HtS32qLbL1yYrfghq3ZUcaj0+56Og+dLtdlkGwIIhFWAAGFYZ55xI4AAAggggAACCCAQEoFEokf0zUPnTcdUKim9vX1y5Mj1Fd/UCgkNw0QAAQQQKBFw/p/Q0oia/aQBDs1ET2fy21l/JgPQygY0WYHzy6YsqMkE3Mx6GwKMmPielvscL8kA1PtOP8D+noivsgBLiCve3djYkDvvvL1mUGr3AWoFqXbvz/fuBJrRP9DrKg7NCGq602EvBBBAIDgCBAiDM5eMBAEEEEAAAQQ6QKDSG08dcOlcIgIdL6BvVOkXCwIIIIAAAqUCqY2UfOlLd8nc44+WrpaZmROyLuMys/GjkpP4jm2t/mbABPmsDMBhLQNqBwM1ADhuMgBHTXAwqlHCAC133LH34KAz/JMnZ/jAj4PRpNtm9Q9sVhUHN39DNSOo2SQ+DoMAAgh0jAABwo6ZKi4UAQQQQAABBDpZgH4YnTx7XDsCCCCAAAIIdLpAajMv88W+f5r1N1+SCTiy9nUZiiyUHWK/zMvh+Lflgczzym6vd2UsKlawrzTzz8oANAFBDQL2JiL1HrrjHnfmzBk5c+Z03detlQFYmivQrP6BjVZx2MvfUM0KajZXkqMhgAAC/hYgQOjv+eHqEEAAAQQQQCAgAvTDCMhEMgwEEEAAAQQQ8KVALl+Qi6bf344goOkBaAUDTUBwNZUve92DXYtydaJ8cNB5wL7oggxmF2W1MOqscnW7rz9a7APo9APcLgs6PBCVSFewsgBdoZTZ6Xvf+16Zte5XadnwTl/cZMh5OcZm9w+st4rDXv6GalZQ00tnzoUAAgi0W4AAYbtngPMjgAACCCCAQOAF6IcR+ClmgAgggAACCCDggcD6Rs7u/2cCfnMmA3DeBADnTS9Avb9ogoO58jHAqlc2Fj1XdbuzUfdbze4MEHbHuoplQO3Sn1YpUKskaNzqEZiIhycL0HGq53Z9fb2eh209RnsKd+qylww5L8fodf/AcmPb699QzQ5qlrsm1iGAAAJBEyBAGLQZZTwIIIAAAggg4DsB+mH4bkq4IAQQQAABBBDwoUA2V5AFDfhp4K9YDlRv7SzArCTTdUQAa4wz3pWusYe9+YqhnDzth/eL1Qdwn90XcKgvKl1kAbryq7ZTf39/tc1Vt01NHero/oN7yZCrCtGCjc3qH1jvpe31byg/BDXrHSuPQwABBNolQICwXfKcFwEEEEAAAQRCI0A/jNBMNQNFIBACfitzFghUBoEAApZAoVAwpT5NFuCyU/rTvl2wgoBZq0RowWOrQqTH1Rmvu2ZEXvjsEVf7stPeBG688Ub57ne/u7cHmb01OKhBrE5d9poh5/U4G+0f2Oj11vM3VLuDmo2OmccjgAACXgsQIPRanPMhgAACCCCAQOgE6IcRuilnwAh0pIBfy5x1JCYXjUCIBTYzeVP2084AdDIBrQxAExTUcqDpjLchwIhp8zc65PT+c27jVibghMkEvHSxW+6883TNGevkMpY1B9fmHa6++mq5+upr5MyZyvMwNjYhExMHJJVKivYc1PmYnJxq85U3dvq9Zsg1drb6H11v/8D6z2g/sp6/odod1Gx0zDweAQQQ8FqAAKHX4pwPAQQQQAABBEInQD+M0E05A0agIwX8XOasI0G5aAQCKpA3WYCX1rUXoN0D0O4FuF0WdNls83oZ6IkUewGawJ8TDByOWev2D8YkqlHCCsuAyULTTLTZ2cq9CDu9jGWFoftq9atedUw+//nPl50HJ1NQgz9BWurJkAvS+GuNpZG/odoV1Kw1JrYjgAACfhMgQOi3GeF6EEAAAQQQQCBwAvTDCNyUMiAEAifg9zJngQNnQAj4XCC1abIAy/QA1KDggukPmDG9Ar1cYlGRsSE7+DcxrP3/7AzA8eJtX8Ls0MBCWcIG8Jr00J6eHpmePiZOmesgZQpWIqonQ67SsYK4nr+hgjirjAkBBPwmQIDQbzPC9SCAAAIIIIBAIAV44ymQ08qgEAiMQKeUOQsMOANBoM0C+XxBLq6Z/n9a9tPq/2dnAzr3V1N5z69wX390O/BngoETJgNQA4AaDBweiEqkq3IWYKMXS1nCRgWb9/gwZX41kiHXPHF/H4m/ofw9P1wdAgh0vgABws6fQ0aAAAIIIIAAAh0gwBtPHTBJXCICIRagzFmIJ5+hB1ZgfUPLgNoBQDvwVwwGLmdkcTUrOY9jgN2xrq2+f3bgzwQATTbguGYG7otJIh5p+1yEKTjVdmwuQMiQq/0k4G+o2kbsgQACCDQiQICwET0eiwACCCCAAAII7FGAN572CMbuCCDgiQBlzjxh5iQINFUga8p8Lq6YLECrFOh2D0AnGJhMexsB1Py+EdPvb8IE+5zSn3YpUM0CjMlQX1S6WpgF2FRcDoaARwJkyLmD5m8od07shQACCOxVgADhXsXYHwEEEEAAAQQQQAABBBAImABlzgI2oQwnEAKFQkFWUyYLUMuArtglQOdM9p8TANQSoWYXT5fe7khJFqAJBmoGYLEP4NhgXOImS5AFAQTcC5Ah596KPRFAAAEEmi9AgLD5phwRAQQQQAABBBBAAAEEEOgoAcqcddR0cbEBEtjM5E3wzykDup0NOG9Kg2pmYDrjbQQwYuJ7Y0MxGbN6/233ANQSoJoN2N8TIQswQM8/huIfATLk/DMXXAkCCCAQJgEChGGabcaKAAIIIFBR4Pz5R+XUqQdEezBpmTXNpNA/0lgQQAABBBAIi0AzypydPXtGvvOde/j/NCxPGsZZUyBvUvwWNfvPfJ2fT8vpC2vFkqAmKGiyAZfWczWP0ewdBkyQT4N9Y8Wgn9UPcNgOAO43JUKjGiVkQQABBBBAAAEEEAi8AAHCwE8xA0QAAQQQqCaQTm/I8eN3yezsuR27zcyckKmpQ6JvlmrZFxYEEEAAAQSCLtBImbONjQ3527+9XU6fPr2Dif9Pd3DwTUAFNjZNFqDJ9pszWX/2rV0OVO9rJmDG9Ar0colFNQvQ7vtnl//UMqB2AFBv+xJmBxYEEEAAAQQQQACB0AsQIAz9UwAABBBAINwC5YKDjogGDXX79PQxZxW3CCCAAAIIBF6gnjJnd9xxu5w5c7qsDf+flmVhZQcJ5PMF0X5/Vi9ADfqZbEDnvpYBXU3lPR/Nvv6ojJtSoJoJ6GQAOsHAEbMtQhag53PCCRFAAAEEEEAAgU4TIEDYaTPG9SKAAAIINE1Ay4ruzhzcfXDdfuHCrExOTu3exPcIIIAAAgggYAT0/9NKwUEHiP9PHQlu/SqwvpGzsv004FeaDagZgAsmIJjzOAbYHesqyfrbmQGogcBEPOJXyo66LtoMdNR0cbEIIIAAAggg0GQBAoRNBuVwCCCAAAKdI6A9B90sJ0/OECB0A8U+CCCAAAKhFOD/01BOe8cNOmvKfC6umCzAYgBQA3/OfS0Nmkx7GwHULn8jpt/fhCn5aWf+lWQDmnVDfVHp6qIXYKueaLQZaJUsx0UAAQQQQACBThIgQNhJs8W1IoAAAgg0VSCZTLo6Xirlbj9XB2MnBBBAAAEEAibA/6cBm9AOHU6hUDClPkuzALUkqJ0NOG8Cg4urWTG7eLr0dHdZJUCnxnvk4GjCCgT2x/MyMRyXscG4xE2WIEt7BGgz0B53zooAAggggAAC/hIgQOiv+eBqEEAAAQQ8FOjr63N1tt5ed/u5Ohg7IYAAAgggEDAB/j8N2IT6eDibmbzp/5fdVQJUg4B2NmA6420EUNv8jZo+gFYPwK1MwPhWVuBAT8TKAhwZ6ZdYLCLZbF6WltZ9LByOS6PNQDjmmVEigAACCCCAQG0BAoS1jdgDAQQQQCCgAocPXyczMydqju7Iketr7sMOCCCAAAIIhFWA/0/DOvPNH3fepPhdWs8VS3/uzACcN9mAS2ab10u/CfJNmJ5/4yYAaN9u399vSoTGomQBej0njZ6PssiNCvJ4BBBAAAEEEAiKAAHCoMwk40AAAQQQ2LPAwYNXytTUIZmdPVfxsbp9cnKq4nY2IIAAAgggEHYB/f/06quvkTNnTlek4P/TijSh27CxabIATR9A7ftn39oZgHpfMwEzplegl0s0InYPQM0ENKU/dwYDY9KXiHp5OZzLAwHKInuAzCkQQCBUApqZrR++0J+vWllCPzymvx+yIICA/wUIEPp/jrhCBBBAAIEWChw9eotU6kGib2bqdhYEGhXgD6ZGBXk8Agj4XeBVrzomX/jCHfLII49cdqn8f3oZSaBX5PMFubimwT+77KcVBFy2g4FaHnQl6X0W4L6+qJUBaJcC3c4A1IDgSH9UIlorlCU0ApRFDs1UM1AEEGixQDq9Ufb9FK3U5Pz+l0j0tPgqODwCCDQiQICwET0eiwACCCDQ8QL6y+r09DFxAjipVFK056CWFSVzsOOnt+0D4A+mtk8BF4AAAh4J9PT0yOtf/3p5+OHT8p3vfFf4/9Qj+DadZn0jtyMAuB0MzMrCSkZyeW8vrDvWVT4AWCwNmoibNEEWBIoClEXmqYAAAgg0R6DSh6316FqpSbfr+y0sCCDgXwEChP6dG64MAQQQQMBDAS1/QQkMD8FDcir+YArJRDNMBBDYErjqqqtkcHB063vudKZA1pT5XDTZfvMm2DenpT9NBqB1WywDup72NgKo+X0jA5oFaEqAmqw/7Qc4PrR9XzMEu7rIAuzMZ5v3V62/82tmC20GvLfnjAggEBwB/ZB1tZ+jOlLdfuHCLB++Ds60M5IAChAgDOCkMiQEEEAAAQQQaL8AfzC1fw64AgQQQACB8gKFQkFWU04vwO0egHYQMCuLq1kxu3i69HR3Ffv/aR9AEwDUYKBmAA7HZGwwLnGTJciCQLMEaDPQLEmOgwACYRXQnoNulpMnZwgQuoFiHwTaJECAsE3wnBYBBBBAAAEEgi3AH0zBnl9GhwACCPhdYDObN+U+TRbgsmYB7swA1L6AGxlvI4Ca4Dc6GCsGAc2tlQm4HQwc6ImQBej3J1WAro82AwGaTIaCAAJtEUgmk67Oq2XnWRBAwL8CBAj9OzdcGQIIIIAAAgh0sAB/MHXw5HHpVQWcnq36HO/r6xPt5USJ5qpkbESgJQJ5k+J3aT1XLP1pAoEm6OdkAGpQcMls83rpN0E+K+uvNAPQ3Nd1+01wMBYlC9DrOeF81QVoM1Ddh60IIIBAJQH9O8DN0tvrbj83x2IfBBBovgABwuabckQEEEAAAQQQQMAKnLhh4A8mN0rs4weBdHpDyvXVnJk5YfVy0nJtmpHBggACtkAzgukbm04Z0F0BwGIvwIzpFejlEo2IjGnvPw0AmgxAKxg4ZN8fN7f9PVEvL4dzIYAAAggggECbBPRDgvp3QK3lyJHra+3CdgQQaKMAAcI24nNqBBBAAAEEEAiuAH8wXT63zXiz/PKjssYrgXLBQefcs7PnrODh9PQxZxW3CIRWYC/B9Hy+IBfXNPi3XQJ0btkOBs6b8qArSe+zAPf1RU3/P7sHoN0HsFgW1AQER/qjEomQBRjaJzcDRwABBBBAoCigGdhTU4dE/w6otOj2ycmpSptZjwACPhAgQOiDSeASEEAAAQQQQCB4AvzBtD2ne3mzfPtR3POTgAZ3q/3xr9eq2y9cmOVNAD9NHNfSFoFawfS//NwXZGXohVZQcGElI7m8t5fZHevaCgA65UCdWw0IJuImTZAFAQQQQAABBBCoIaAVRCr93qPBQd3OggAC/hYgQOjv+eHqEEAAAQQQQKCDBfiDyZ68Sn806lYyzzrjCX7q1AOuLvTkyRkChK6k2ClIAllT5nNx1c76O332XM1gej71mJxZflRWC6MtYxgZiBZ7ARbLgZrA34TJANQyoPtMFmBXF1mALcPnwAgggAACCIREQNsLaAURp1JMKpUUbaGhZUXJHAzJk4BhdrwAAcKOn0IGgAACCCCAAAJ+FeAPJrH+WCTzzK/PUPfXlUwmXe2sbwqwIOBHAeeNK30u9/X1iZaB1kxvN0uhUJDVlN0LcN70/psz5UDt24yVBajBQbOLtVwbu08OuPgreyx6Tlaz9QUIB7sW5ED8UemPZ6Q70Sv7Jn7IGouWBdVMwFETBOyOkQXoZm7ZBwEEEEAAAQQaF9Dfqdz+XtX42TgCAgg0U8DFny7NPB3HQgABBBBAAAEEwicQ5j+YyDwLxvNdAypuFv3EMAsCfhJwW+J4M5uXBdPzb37ZBP3M7ZwJBM6bXoDWrbm/kSlGAGsMLt6VrrGHvbnWfprgNzpY7P1X7Ae4vy8njz7wNbm4MGsfRNsTmpj82ukfyHrmkLzAlPFKJLpdnZ+dEEAAAQQQQAABBBBAAAEChDwHEEAAAQQQQAABBFomQOZZy2g9PbBmW83MnKh5Ti0nxIKAnwRqlTj+/z57hzwsz5elNY22Nb5kCglXB9H9+hMRGTdlPyeKAcDSPoAaHIxFd5YBvfPO27eDg7vOQrnmXSB8iwACCCCAAAIIIIAAAjUFCBDWJGIHBBBAAAEEEEAAgXoFyDyrV85fj9Ms2KmpQ1V7q+l2eo20d94aKaPZ3itvztnTGbsMqJYA1cy/xy7MSnL2XNWDx7Nzkk3PmX3qK/e5++ALuUOmxOiZ3asv+/4NL/tRecI1V122vtIKnVvKNVfSYT0CCCCAAAIIIIAAAgjUI0CAsB41HoMAAggggAACCCDgSoDMM1dMHbHTUVO+sFI2lgYHdTtLewTcltFsz9U176z5fEEurmVloRgALO0FqOsuJXdmAV4be7Dl/QD39UVlrNj7b9z0/5vYNy6P3v+wLC+erzhwfb3sJTioB6Jcc0VONiCAAAIIIIAAAggggECdAgQI64TjYQgggAACCCCAAAK1Bcg8q23UKXskEj0yPX1MnCy1VCop2nNQy4qSOdjeWawUuNWr6rTSk8l0zmT/7e4FmLHWLaxkJJd3b12rz59zpGr7xU2Zz4nhmGjwb3zIfJn7WgpUy4KOme97uiPOYbZu00/6maYH0ynXvMXLHQQQQAABBBBAAAEEEGiSAAHCJkFyGAQQQAABBBBAAIHyAmSelXfp1LUa9NUvFn8IdFrpyWyuIIurJgBoSoDOFzMBS++vb+whAlhjCtz2A4zEeuTIRI8dBNzKBrQDgfv6o9LVtbMXYI3TSiuC6ZRrrqXOdgQQQAABBBBAAAEEENirAAHCvYqxPwIIIIAAAggggMCeBFrxZvmeLoCdEQiwgN9KTxYKBVlNmSzAZQ0A2pl/pQFADQ6aXTxZ3PaEEgWKAABAAElEQVQDfNPPPMvKgrWzY/9XLp1OSqavTwYOXyfDA/UHw5sZTKdcsydPGU6CAAIIIIAAAggggECoBAgQhmq6GSwCCCCAAAIIINA+gWa+Wd6+UXBmBPwl0I7Sk5vZvCys7MwCXE7Oy+NLm/KY+Uqlm5cF6EZbE/xGB7UMqJ31Z/cC1O+n5N5vnpbHH3u04mG0H+D+/aNy5523W+VYS3ecmTkhTn9N/aBDOxf9+anXoiVjKy26nXK/lXRYjwACCCCAAAIIIIAAArsFCBDuFuF7BBBAAAEEEEAAAV8IOL3uNACi5fU0g4bSlr6YGi7CRwKtKD2pWYCX1rUXoF0GtDQTUNctreU8F+hPREz/P+0DWAwCFnsBal/AUbMuZnoFlluu/OmX1ewH2Ck9HFtdrpmfueWeQaxDAAEEEEAAAQQQQCC4AgQIgzu3jAwBBBBAAAEEEOhIgXR6o+wb+n7K5ulIWC46kAL1lp5MZ/JbJUCtQOCyyQhcscuCam/AzaxHdUCLsxKNiIyZYN92FqBmAMZlwnzpuv6eaF3zV6vEcSf1cKw1lrqAzIP4mVuvHI9DAAEEEEAAAQQQQKCzBQgQdvb8cfUIIIAAAggggEDgBDolmydw8AyoIwXclJ7sHz4o//lwr8zf8/hWVuBKcjsLcLBrQcaij0q8Ky3dhYQkcodkU0ab7jHYG5EJkwXoBP1KA4D7B2ISiZTPAmzGhVQqcey3Ho5uxlppLG4eW24ffuaWU2EdAggggAACCCCAAALBFyBAGPw5ZoQIIIAAAggggEDHCHRSNk/HoHKhgRVIprUMaFYmfujHZXHlK7KxeuGysV7Kjcn/PHaT5B5bumxbVDJyOP5t2Rdd2LHtQOyM6ONOZZ4pOYnv2Fbtm+5YlxwY6Zb9A1E7CLhVBtTOBuzpNmmCPlva0cPRTwT8zPXTbHAtCCCAAAIIIIAAAgh4K0CA0FtvzoYAAggggEBTBOgT1BRGDuJDgU7M5vEhI5cUEIFsriAXV7NbWX92T0C7L6DeX9/Il4z0mTLYtWgyAc9ZmYAZkwm4YDIBVwuVMwEPx79lgoMXS46xfVeDhoflW/JA5gXbK829ERP808y/7VKgmhEYkyddvU/G9nVLPl+QpaX1HY/x8zet6OHo5/HuvjZ+5u4W4XsEEEAgeAL87Ri8OWVECCCAQLMECBA2S5LjIIAAAggg4IEAfYI8QOYUbRUIezZPW/E5uecChUJB1kyQb94E+zQT0LpdNgHAFfv+ork18TbXiwYDV7OVA4KlB9JgYqXgoLOfbn/VjVm5+tCVMm5Kg44NxaQ7Vj4LcGQwbpUI1QBhJy319nDspDFWu1Z+5lbTYRsCCCDQ2QL87djZ88fVI4AAAl4IECD0QplzIIAAAggg0CQB+gQ1CZLD+FYg7Nk8vp0YLqxugUy2IAurJui37GQCbgcD501QMLVZmgVY92lcP7DLtPkbHYzJ1fIDMY0Gay6x9QfkKU84UnO/Tt3BTQ/HqalDMjk51alDrHrd/MytysNGBBBAoKMF+Nuxo6ePi0cAAQQ8ESBA6AkzJ0EAAQQQQKBxAfoENW7IEfwvEPZsHv/PEFe4W0CzAC8lcyb7zwQArey/YglQvW8yA5fWcuJ1Tl1/ImKVANVSoBNaDtTpBWjua3AwFu2S//N/viJrLgKEi4vzu4ccuO+PHr1FKr2JqsFB3R7UhZ+5QZ1ZxoUAAmEX4G/HsD8DGD8CCCDgToAAoTsn9kIAAQQQQKDtAvQJavsUcAEeCIQ9m8cDYk5Rh0A6o2VAiyVATdDPCgZat/b9TZMl6OUSNVU+x4bsPoDj5nbCBAC3goGmH2B/T7SJl2NSDgO+JBI9Mj19TJweTalUUnp7++TIkesDmznoTCk/cx0JbhFAAIFgCfC3Y7Dmk9EggAACrRIgQNgqWY6LAAIIIIBAkwXoE9RkUA7nW4EwZ/P4dlICfmHaN29p3WQBmqy/uWIA0O4LaAcANUPQ62WwN2Jn/2kWYDEA6AQD9w/ErH5/jVzT6Oi4rK2t1jzE6OhYzX2CsoMGy/QrbAs/c8M244wXAQTCIMDfjmGYZcaIAAIINC5AgLBxQ46AAAIIIICAJwL0CfKEmZP4QCDM2Tw+4A/sJSTTxTKgpRmAVknQrCysZCTrcQwwbsp8jptsv9LMP/u+va6n26QJtnB56lOfIWfOPFzzDE996o/W3IcdOluAn7mdPX9cPQIIIFBOgL8dy6mwDgEEEEBgtwABwt0ifI8AAggggIBPBegT5NOJ4bJaJhDWbJ6WgQb8wNlcQS6umj6AZTIAdd36Rt5zgZH+qOn/t10K9IBz32QF7jPbIl3tK9+pr6/JySm5cGG2ootu1y+WcAjwMzcc88woEUAgHAL87RiOeWaUCCCAQKMCBAgbFeTxCCCAAAIIeCSgb9xNTR2S2dlzFc+o23kztyIPGxBAoIMFCoWCrJkgn1360+4HWHp/cSUrplKop0si3lUsA7qdCTihWYEmEDg2GJPueGuzABsd7M03T8vx43eV/X9F/z/R0pMsCCCAAAIIINB5Avzt2HlzxhUjgAAC7RAgQNgOdc6JAAIIIIBAnQL0CaoTjochgEBHCGSyBVlYNX3/lp1MQO0J6AQDs5La9DYLUBP8Rk2gb3yoGAB0MgCHtC9gXLRPYFcbswAbnVRKSzYqyOMRQAABBBDwrwB/O/p3brgyBBBAwC8CBAj9MhNcBwIIIIAAAi4EeDPXBRK7IICAbwU0C/BS0u4FaGf/mWCgCQDOaS9AUwZ0aS0nHicBSl8iYrIAtzMAx4c1IGgCgKYM6KgJDMZMr8CgL5SWDPoMMz4EEEAAgTAK8LdjGGedMSOAAAJ7EyBAuDcv9kYAgQYEzp9/VE6dekCSyaRow2ytia9vSLEggMDeBXgzd+9mPAIBBLwRSGe0DKid9VeuH+CmyRL0comaKp9jJuA3vhUEtIOB4yYAqIHB/p6ol5fDuRBAAAEEEEAAAU8F+NvRU25OhgACCHSUAAHCjpouLhaBzhRIpzfK9reZmTlh9VPTshf6yTYWBBBAAAEEEPC/QN5kAS6bTD87+GdKgJpyoJr9N296AOq6S+s5zwehpT4140+DfhoIdO5PmGzAkYGYRCOdnQXIh6w8f0pxQgQQQAABBBBAAAEEEEAg8AIECAM/xQwQgfYLHD9+l8zOnit7Ibpet09PHyu7nZUIINA+Ad6Qbp89Z0ag3QKpdN4K9mnAb0FLgGoA0HxpP8CFlYxkPY4Bxk2Zz7GtwN92ANDJCuztNmmCAVz4kFUAJ5UhIYAAAggggAACCCCAAAI+ESBA6JOJ4DIQCKqABhgqBQedMev2CxdmZXJyylnFLQIItFFgY2NDPv/52+TMmdM7roKs3x0cfOMTAQLZ9U1ELl+Qi6t24M/JACwNBq5t5Os7cAOPGu6PWhmAW/0Ah4tlQU150OGBqES6OjsLsB4aPmRVjxqPQQABBBBAAAEEEEAAAQQQcCNAgNCNEvsggEDdAtpz0M1y8uQMAUI3UOyDgAcCt912eXDQOS1Zv44Et+0WILOq+gwUTBlQDfI5WX9WCdBiBqDeXzTlQE2M0NMlEe+ySn9uZQIOmUxAKwhoAoHmfnc8mFmA9SLzIat65XgcAggggECpAB+mKtXgPgIIIIAAAgiUChAgLNXgPgIINF0gmUy6OmYq5W4/VwdjJwQQqFvg7Nmzcvr06aqPJ+u3Kg8bPRDQN7q+8pUvSTK5XvZsYQlkZ7IFWVg1pT9ND0CnBOj8VjnQrKQ2vc0C1Py+/YNa/jNmZwKa4N+YBgFNX0DtBTjYG5WuEGYBln2SuljJh6xcILELAggggEBFAT5MVZGGDQgggAACCCBQFCBAyFMBAQRaKtDX1+fq+L297vZzdTB2QgCBugVOnPieq8eS9euKiZ2aLFDpja5ypwlCIFuzAFeSOavvn50JqH0As1tZgUumRKjHSYDSl4hsBQDHNfDnBAPN/VETDIyZXoEszRHgQ1bNceQoCCCAQFgFKFMd1pln3GEUIFM4jLPOmBFojgABwuY4chQEEKggcPjwdaJ9y2otR45cX2sXtiOAgAcC6+vlM7J2n5qs390ifO+FQLU3usqdvxMC2emMlgE1Qb8VzQTMbAUDnUzATZMl6OUSNVU+RzULsFj60wkAOsHA/p6ol5cT6nPxIatQT3/FwfMGYEUaNiCAQImA/qzQD0tVW4LwYapq42MbAmEQqPQBSn0fbmrqkBw9eoskEj1hoGCMCCBQpwABwjrheBgCCLgTOHjwSuuXkmp/nOgvLZOTU+4OyF4IINBSgf7+flfHJ+vXFRM7NVHAzRtdu0/nh0B23mQBLq9pFqBm/5kAoCkHagUDi6VAL63ndl92y78f7I3YJUBN1t+4yQDUEqBWANCUAR0ZiEk0QhZgyyfBxQn4kJULpBDtwhuAIZpshopAEwQoU90ERA6BQAcIVPsApb4Pp9unp491wEi4RAQQaJcAAcJ2yXNeBEIkoJ9YqvRLi/OJphBxMFQEfC1www03yr333lPzGsn6rUnEDk0WcPtGV+lpvQpkp9L5rQCgk/lnlwTNyoLJDMx6HAOMmzKfY1uBv2I/wGIwUAOBvd0mTZDF9wJ8yMr3U+TpBVb6XVovgjcAPZ0KToZARwhQprojpomLRKAhATcfoCRTuCFiHoxAKAQIEIZimhkkAu0V0HIG+oklpySSZnTom7YaYCBzsL1zw9kR2C1w1VVXyTXXXCOnT5/evWnre7J+tyi446GA2ze6Si+pWYHsXL4gF02/v7MXV60SoOcXNuTcXKpYEjQjaxv50tN6cn9ff9TK/NsuAbqdCTg8EJVIF1mAnkxEi0/Ch6xaDNwhh+cNwA6ZKC4TAR8JUKbaR5PBpSDQIgG3H6DshLYLLSLisAgg4EKAAKELJHZBAIHmCOgn4fWLBQEE/C3w6le/Wm677bayQUKyfv09d0G+OrdvdDkGewlkF0wZ0HUT5LPLgGa3sgHntDegKQu6uJIVEyP0dEnEu2R8yJT+NGU/t0qAmqxAzQAcG4pJIk4WoKcT0qaT8SGrNsH77LS8AeizCeFyEOgAAcpUd8AkcYkINCjg9gOUfmi70OBQeTgCCLRQgABhC3E5NAIIIIAAAp0o0NPTI6973S/I/fefFH1TkqzfTpzF4F2z2ze6dOTlAtnZXMEq9+kE/eaWtSegEwzMSmrT2yxAze/bP6jBPzvop4E/px/ghAkKDvZGpYsswOA9kescER+yqhMuIA/jDcCATCTDQMBDAcpUe4jNqRBok4DbD1B61XahTQycFgEEGhQgQNggIA9HAAEEEEAgqAK8IR3Ume3Mcbl5o6u3t1+e/Iz/VzKxMTl+T8pkAq5YGYAaFFwyJUI9TgKUvkRkK+inAcDtYGDMZAHGJWZ6BbIggAACtQR4A7CWENsRQKCcAGWqy6mwDoHgCLj9AGWz2i4ER46RIIBAqQABwlIN7iOAAAIIIIAAAgj4VuDHf+Kn5cvHvygLc49edo0r+TH5n6Vnyr9+VTMB5y7b3ooVUVPlc1SzAIdN9p+WAzXZgNb9YjCwvyfaitNyTAQQCJkAbwCGbMJDMFynN71mx2oAXJ/j+kEgluYKUKa6uZ4cDQG/Cbj5AOVe2i74bXxcDwIIeCNAgNAbZ86CAAIIIIAAAgggUEMgb3oBLq/lill/O0uAai/A5fWcOcLTZbDrGhmLnpN4V1oyhYQs5A7JamG0xtHr2zzYq1mAGvyLy1UH+mRqLCFj5n5vJGuVCI1GyAKsT5ZHIYCAWwHeAHQrxX5+F0inN+T48btkdvbcjkudmTmxVR5cg1oszRXQnyEEYJtrytEQ8IsAmcJ+mQmuA4HOFSBA2Llzx5UjgAACCCCAAAIdJ6C9/jTYt9X/z/QCdPoCLqxkJWN6BdZaNBi4mm1OQDBmkvzs7L9iCVCTDThhBQTt3oC93SZNsLiMjPRLLBaRbDYvS0vrzmpuEUAAgZYL8AZgy4k5gQcC5YKDzmk1aKjbp6ePOau4RQABBBCoIUCmcA0gNiOAQE0BAoQ1idgBAQQQQAABBBBAwK1ALl+Qi6bfnwYBncDfVjDQrFtNaQlQb5fh/mgxC9CUAC0J/un94YGoRLrIAvR2RjgbAgjsVYA3APcqxv5+E9CyorszB3dfo26/cGFWJiendm/iewQQQACBKgJkClfBYRMCCFQVIEBYlYeNCCCAAAIIIIAAAqUCBVMGdH0jb4J/GdGMvzmTAVgaAFw0wcGcxzHARLzLzgIcdgKAxX6AJgA4NhSTRHw7C7B0LNxHAAEEOk2ANwA7bca4Xkfg1KkHnLtVb0+enCFAWFWIjQgggAACCCCAQPMECBAWLf/5n/9ZPve5z8l9990nqVRKxsfH5XnPe568+c1vlmuvvbYu8Y2NDXna054muZz2y6m8PP/5z5dPf/rTlXdgCwIIIBACAf1Usb5xkEwmpa+vTw4fvo5eGSGYd4boT4GsKfO5sLKdAahBQCsYWCwNmkx7GwHU/L79gxr8i1n9/0qzAA+YoOBgb1S6yAL055OJq0IAAQQQQMAI6O/4bpZUyt1+bo7FPggggAACCCCAAALVBQgQGp8PfvCD8hd/8ReWVDQald7eXlP6Ylb+5m/+Rv7hH/5BPvKRj8iLX/zi6pJltj744INbwcGxsbEye9irhoeHK25jAwIIIBB0gXR6w+o3srvk0MzMCZmaOiTac0fLarEggEDzBDQLcCWZK8n8M5mAVvDPDgoumSzA2p0Am3c9eiTt9TdRzADUrL8J0wtw3GQAalBwdDAu8RhlQJsrztEQQAABBBDwTkA/AOhm6e11t5+bY7EPAggggAACCCCAQHWB0AcINWtQg4P6qfNf//Vfl9e//vXS398vjzzyiLzvfe+Tb3/72/LOd75T/v7v/37PmYT333+/pX/w4EH513/91+ozwVYEEEDAZwJeZfQdP35XxX4kGjTU7dPTx3ymw+Ug4H+BzUxe5rUEaDHrz+4JaMqBLtvrNrPehgAjJr6ngT876GdKf5rAnxMA1IzA/p4IWYD+f1pxhQgggAACCNQloNVB9AOAtZYjR66vtQvbEUAAAQQQQAABBJokEOoAoZYS/cQnPmFRvuENb5Bf+ZVf2WLVsqJ//ud/Lq985Svl+9//vvzRH/2RfPSjH93a7ubOzMyMtdv11/MLrhsv9kEAAX8IeJnRp0HI3ZmDuxV0+4ULs4HsReJVEHa3Kd8HQyBvsgCX1zQLULP+SvsAZq11y+vVS5y3QmGwN1LsBWhn/jkBQL3VEqFRjRKyIIAAAggggEDoBLR/plYHqfa7v26fnJwKnQ0DRgABBBBAAAEE2iUQ6gDhl7/8ZVlYWLA+rf6Wt7zlsjno6ekRXf+ud71L/uVf/kWWl5dlL+VAnQDhj/zIj1x2bFYggAACfhXwMqNPew66WU6enAnUmwVeBmHd+LKPfwVSmyYLUAOApgegZgPOm9u5S3YAUHsCZkyvQC+XWFTsAGCx9KcG/sZNJqBVDnQoLr2JiJeXw7kQQAABBBBAoIMEtHVApb81nNYCHTQcLhUBBBBAAAEEEOh4gVAHCL/5zW9aE/jDP/zDUqlH4Ate8AJrn0wmI9/4xjfkpS99qatJ39zclIceesjalwChKzJ2QgABHwh4ndGXTCZdjTqVcrefq4P5YKdKb4zopVFW1QcT5OEl5PIFuWj6/dlZgPbtvAkAOv0AV1N5D6/GPtW+/qjp+1cM/O24jcvwQFQipiw7S2sFyC5urS9HRwABBBBoj4D2FdfWAc7/c/o7vvYc1LKiZA62Z044KwIIIIAAAgiEWyDUAUIngPfEJz6x4rNgdHRUhoaGZGVlRU6dOlVxv90b9NgaVNRlZGREPvzhD8u3vvUtK2NxcHBQbrrpJnnd614nGpxkQQABBPwi4HVGX19fn6uh6xsHQVm8DsIGxa2Tx7G+kdvK+rMyATUDcMXOClw0wcGcxzHA7ljXVgBwqwTosJYENX0BTY/ARJwswHY938gubpc850UAAQQQ8FJAy43qFwsCCCCAAAIIIIBAewVCHSB8/PHHLf2DBw9WnYUrrrjCChDOzc1V3a90o1NetMt8yl4DgZpR6CwXLlywgo233367vOMd75C3v/3tziZuEUAAgZYLOJ/Y1ew9DdAdPnzd1h/oXmf06blnZk7UHLN+qjgoi9dB2KC4+XkcWVPmc9GU+3Sy/pwSoE5WYDLtbQRQ8/tGTL+/CVP60ykBOm7Kf2oZUF031Be1yqv72TSs19aq7OJqP/fDas24EWiWAK+vZklyHAQQQAABBBBAAAEEEPBaoOMDhB/72Mfk4x//+J7cbr31Vjl69Kisrq5aj+vt7a36eO1FqMva2lrV/Uo33n///da3hUJBrr/+eisI+LSnPU0ikYjce++9otegtx/96EdlYGBA3vCGN5Q+nPsIIIBA0wXcZKZ4ndGnnxzWfiNaVrPSotuDVHLI6yBsJVfWuxfQ/8tXUyYLcNnO/LNKgGpPQO0NaLIBL65lxezi6dLbHbF7/zklQE3wzwkGjg3GJW6yBFk6S6AV2cX6c//OO+8wFSx2fshNP5jh9HrScm8sCCCwdwE3v1fx+tq7K49AAAEEEEAAAQQQQAAB7wQ6PkDYCFUul7MeHo/Hqx6mu7vb2p7NZqvuV7pRsxKf9axniZYo/YM/+AOJxbapn/vc58oznvEMedOb3iR33323/PEf/7Hccsstsn///tJDNOV+NNplSpz2N+VYHASBoAjo60KXsL0+/uqvvlAxEKcBuq997R/lBS/4MVcZfc94xtOa9rPlNa95jfzt394up0+ftual9J9rrrlGXvnKY+J8UKN0W6feHx4ecnXp+/YNNc3Y1QmLO4X19ZHO5GVuaVMec74ubsrj5r5+6bqNTW+zAM3niUy2X7dcsb9bDozYX1eYW/1ebwd6yQLcy/O6Wfu28vXxX/9l966uda2PPHLKfPjscK3dZGNjQz796b8QDWKUW5yf+6973S+U28w6BPYs0MrXx54vxoMHuPm9iteXu4k4e/aMnDhxQtbX16W/v19uuOFGueqqq9w9uEP2Ctvro0Omhcv0iQCvD59MBJfhSwFeH76cFi7KJwLO68Mnl9Oxl7EdterQIWj5zptvvnlPV3/gwAFrf33DWTM5nF6BlQ7ilAd1AoWV9itd/8u//MuiX5UWPdZv/dZvyc/+7M9a1/C1r31Njh07Vmn3utdridMYWQR1+/HAYAuE6fVx5swZOXPmdNUJ1QDdi170ItGgXLlgnfPga6+9Vq699hrn24ZvBwb6rCxqvcbvfe97W28OPeUpTwncm0OKddNNTzEZ5PfUdHvqU28yP7/b1wsuaK+PfL4gF1czdgDQBP8eu5g2X5tyoXj/oukF6PWipT6v2J/YCvo59ydNEHDcBAf5ZdfrGXF/vla8PlKppKsL0P3c/Gz467/+vxWDg86J9Ge9Zi4G7Y14Z3zctkegFa+P9oyk8lnd/l7F66uyoW7RDzLcdtttl/3eqb8n6e+jr371qwP1ITEdcxheHzpOFgTqEeD1UY8ajwmLAK+PsMw040TAe4GODxBq1l29mXf66UQNEOofJtUWZ7uWAm3mcuONN1r9v/QaHnrI3afG93p+LYuWM72RWBBAYFtA33TXX67C9Pq4997/3Qaocu+ee+61MvaqZfS94hWvkmy2+dlUWu5Ov0qXVpyn9PjtuK9jvPrqa6oGbPVNMS2/2o7xd/LrI5XObQUAH1822X8a/NMMQHOr32ey3v5/GDM/aw6Y0p8HNAhYkgWoGYGaCdjfE634FNSfT1mPr7fixbBhS6CVr4/e3r6t81S7o/vV+tlw9uxZeeyxx6odZmub/tzXnzcsCDQq0MrXR6PX1uzH7+X3Kl5flfU///nbKv4+pB9g0OBhULIww/T6qDzjbEGgvACvj/IurEVABXh98DxAoLKA8/qovAdb3Ah0fIDQzSAr7TM5OSnz8/M130Bx3mBxMg8rHW+v6zVAoUFHN0HKvR7b2V+Dg0tL68633CKAgBHQsruaWduM14d+MvzUqQes17H27zt8+DpfvtG6vLziau4vXVqRlOm1dvPNr7CySnRsmq2ib0gfOXK91QtQt6dS/FxxBVphpxe/+GY5fvyusiVfNYD4Ez9xc9t+djfz9VFh+HWvtrIATb8/qxeg1f9P+wCavoDF+6up5geua13svv6ojA/FTDlQuwfgxHCs2AswLiNmWyTSVeYQedlMbZivMptY5WuBVr4+rrnmSa6yi6+99nDNnw/f+c53XTvqz31+V3TNxY5VBFr5+qhy2rZs2svvVby+yk+R/g7tprrFzMypQPSiDtPro/yMsxaBygK8PirbsAUBXh88BxCoLOC8PirvwRY3AqEOEB4+fNgqZ/fwww9XtFpYWJCVFfuN9Sc96UkV9yvdcOnSJfniF79o3mxZkhe+8IXy5Cc/uXTz1n0tbbq8vGx9Pz4+vrWeOwgg4H8B7elULsAzM3PCyoI7evQWSSR6fDMQDV66WUozWPQT73zq3Y3a3vfR58b09LGKQdi9HzE4j1jfyFlBvzkT9LMDf3YAUAOBCysZyXkcA+w2HyYY37cdANy+bwcCE/H2lYENzqwzEhXQn7f6AQHtDVhp0e2Tk1OVNm+t1w+fuV1Kf+67fQz7IRB2gXp+rwq72e7x64fQ3CwnT864+rnn5ljsgwACCCCAAAIIIIAAAjsFQh0gfM5zniN33HGHzMzMWMG8kZGRnTrmu2984xvWukgkIs961rMu215pxfvf/36rfKEGGCsFCL/1rW+J09/wGc94RqVDsR4BBHwoUC446Fymvrmr2zUA5JdFMxs1eFlr0SxBFu8EwhiEzZrM9sUVkwVYDABq4M+5P2fuJ9PeRgA1v29kwGQBmgzACVMOdDsAaN/fZ/oEasY/CwJeCOiHSyr9/6LBQd3uZnEbvNBj8XPfjSj7dKpAqyo98HtV488Itx9kcNuftfEr4ggIIIAAAggggAACCIRPINQBwh//8R+3Snyura3Jn/7pn8p73vOeHc8A7T34qU99ylp38803y+jo6I7tlb7Zt2+fPPOZz5T//u//lrvuukt+8Rd/UQ4d2tlXS4/94Q9/2DrEE5/4RHn2s59d6XCsRwABnwnom03VMjz0cnX7hQuzvvnEczMzU3w2HVyOzwS0d56W+nTKfloBwGU7G3DeBAYXV7PmAzTeXnRPd9d2CVCTDWgFA62SoDEZG4pL3GQJsiDgB4FmZRe7DV6Mj0/45v8pP/hzDcERaHWlB36vavy54vaDDGQ5N27NERBAAAEEEEAAAQQQqCQQ6gCh/lHya7/2a/L7v//78tnPflZ6enrkLW95iwwODoo2RX/ve98rDz30kOm91Stve9vbLjP8q7/6K9EvXT70oQ/JjTfeuLXPO9/5Tnnta18rGnz8pV/6JXnf+95nZSDGYjGrrKlmGD744IMSj8fld3/3d8lO2JLjDgL+F+jUkkjNykzx/wxxha0W2MyYAKAJ9mkQsDQD0LmfzngbAdQ2f6OmD6Ad+HNu7QxAXTfQE+H/2VY/KTh+UwUazS52E7xIJBLyspe9qqnXzcEQ8ItApUxcvb5mVXrg96rGZtvtBxnIcm7MmUcjgAACCCCAAAIIIFBNINQBQoX5hV/4BTl16pRVavSTn/yklTHY39+/1XdQA3i33nqraJbf7kV7DD7yyCPW6lQqtWPzU57yFCtD8N3vfrcVbHzzm99sBQP1eE45FT2PZhE+7WlP2/FYvkEAAX8LOK/hWlfpt5JIzcpMqTVutne+QD6vZUAz8tBsyg4AlmQAzpv7S+s5zwepQb4JzfozZUAnTBagZv5NDNu9AfcPxiSqUUIWBBDYEqgWvBgbmzBlsF/lq165WxfOnR0CrSqRueMkAfvGq0oP/F7V2BPHzQcZ3PZdbexKeDQCCCCAAAIIIIAAAuEVCH2AUHsL/t7v/Z688IUvlM9//vNy3333WVl/ExMTVtlPzSg8fPhwXc+Ql7zkJVb/Qc1O1F6G58+ft46jwcYf+7Efkze+8Y1y4MCBuo7NgxBAoH0CnV4SqdHMlPbJc+ZmCmxsOmVA7UxAuw+glgDNyePLm5LJepsFGIuKHfTbVQLU6gtogoG9iUgzh8+xEAi8AMGLzp7iVpfI7Gyd6lfvdaUHfq+qPh/Vtlb7IMNe+q5WOwfbEEAAAQQQQAABBBBAoLJAl+kV5O07gJWvhS0tEMhm87K0tN6CI3NIBNwL+O3T7yMj/RKLRaTe14eO5+///m9qArz85a+mt1NNJXZolYBmAV5c0+BfVuzgX0bmlreDgdon0OtlX1/UlAHdLgGqGYBaAlS/RvqjEiEL0Osp4Xx7FGj0/489no7dQyxw5523V+13rMGT6eljvhLyy+vjH//xTlPB5Qc1ba699onykpdM19yPHVov4PytoNU3tOeglhWdnJxq/Yk9PINfXh8eDplTIeBagNeHayp2DKEAr48QTjpDdi3gvD5cP4AdywqEPoOwrAorEUCgKQJB/fQ7JZGa8vTgIE0QWN/I7QgAbgcDs7JgSoTmPI4Bdse6rACgVQrUCvzZJUDtIGBMEnGyAJsw7RwCAQQCLuBVicygMnZ6pYegzku1cZGFWU2HbQgggAACCCCAAAIItE6AAGHrbDkyAqEXOH78roqffp+dPSe6vR2ffj979ozcf/99srq6ZnqDJkwZ4etE35jYy0JJpL1osW+9Atmc9gI0WX8m2GdlAZoMQCcbUIOB62lvI4Da5W9kQLMAtf+fZv6ZDECrF6B9XzMEu7roBVjvfPM4BBBAQAW8LpEZNHX9vW5m5kTNYWmWGgsCCCCAAAIIIIAAAgggEGYBAoRhnn3GjkALBfz46fdmZjTS26mFT54QHVqrfGupz/lLxQCgCfqV3l9czYrXhcC119/k/oQcGInLcK9mBJpgoGYDmnKgY4NxiZssQRYEEEAAgdYJJJNJVwfXcowslwtQ6eFyE9YggAACCCCAAAIIIIAAAuUECBCWU2EdAgg0LODHT7+3IqORkkgNP1UCf4DNjAkAmizABSsIuDMDUIOBGxlvWwFrm7/RIacP4HYPwIlib8BDk4MmszZad4/OwE8oA0QAAQRaLECJzMaBqfTQuCFHQAABBBBAAAEEEEAAgeALECAM/hwzQgTaIuC3T7/7MaOxLRPDSZsukDcpfpfWc1bpzwWTAaglQO0yoCYbcDkjS2ab18tAT8TK/NMSoE4/wAmTAaj39w/GJKpRwgoLJUIrwLAaAQQQ8EiAEpmNQ1PpoXFDjoAAAggggAACCCCAAALBFyBAGPw5ZoQItEXAb59+92NGY1smhpPWJbCx6ZQBtfsBzu/qBZgxvQK9XPZFF+TKnvPSG9uURE+vjB88LIeuvLIYDIxJXyLq5eVwLgR8L6AfEtH/B/TDK/r/Uz29Z30/SC4wMAKUyGzeVFLpoXmWHAkBBBBAAAEEEEAAAQSCJ0CAMHhzyogQ8IWA3z797reMRl9MEhexJZDPF+Timvb/21kC1MkEXEl6nwW4ry9qsgCdEqB29t9IX15O3vMVmXv8URG9JPOVS4s8dun7El05JDcevUUSBAe35pU7CDSz9yyaCHgpQIlML7U5FwIIIIAAAggggAACCCAQTgEChOGcd0aNQMsF/Pbpd79lNLZ8AjjBZQLrGzkrAKh9/5zAn3O7sJKRXP6yh7R0RTzaJVr2c9yU/bTLgDr37dtEPHLZ+e+883Y7OHjZFpHZ2XOifTanp4+V2coqBMIp0Ires+GUZNReC1Ai02txzocAAggggAACCCCAAAIIhE+AAGH45pwRI+CZgJ8+/e63jEbPJiFEJ8qaMp+Lq5oFWAwAmjKg8ybwN2eyArUX4Hra2wigdvkbGdAswHgxCFgMAA7r9zHRDMG99Pujj2aInswMtSkCvGaawshB2ixAicw2TwCnRwABBBBAAAEEEEAAAQQCLECAMMCTy9AQaLeAnz797reMxnbPTSeev1AoyGrK7gVoBwFLgoEmCKjBQbOLp0tPt8kC3BUA1OCfrhsdikl37PIswHovkD6a9crxuLAK8JoJ68wzbgQQQAABBBBAAAEEEEAAAQQQcCNAgNCNEvsggEBDAn759LufMhobAg3wgzezeVlYsTP+NPNPS4AulPQF3Mh4GwGMmDTA/YMm4KdZfybgZ91aJUHtbMCBnsiesgAbmTr6aDaix2PDKMBrJoyzzpgRcCegGcb6IQL9OaFl6LXShP6+yoIAAggggAACCCCAAAIIhEmAAGGYZpuxIhByASejcXV1Ue6//4Ssra1JLJaQI0eul8nJqZDreDP8vEnxu7Se2xH4c/oAahnQJbPN66XfBPl29gC0S4DqOg0OxkyvQD8s9NH0wyxwDZ0kwGumk2aLa0XAG4F0esPq16t9e0uXmZkTMjV1SPTDZPr7IgsCCCCAAAIIIIAAAgggEAYBAoRhmGXGiAACOwSuuuoqecITrpGsyVZbWlrfsY1vGhfY2LTLgFq9/5x+gNoH0NyfN7cZ0yvQyyVqqnyODcVNENBk/TmZgFoWtHi/vyfq5eXUfS76aNZNxwNDKsBrJqQTz7ARqCJw/Phdsjs46Oyu63X79PQxZxW3CCCAAAIIIIAAAggggECgBQgQBnp6GRwCCCDQfIF8viAX1zTgZ5cAtfoBLpvvV+wA4ErS+yzAfX1RGSv2/hsvKQGq/QD3D8QkorVCO3yhj2aHTyCX77kArxnPyTkhAr4W0LKilYKDzoXr9gsXZqks4YBwiwACCCCAAAIIIIAAAoEWIEAY6OllcAgggEB9Asm0lgF1egHagT+nFOiCCQTm8vUdt95HxU2Zz4lhu+/fuMkGHDf3tQSoZgVqdmBPt0kTDMFCH83OmmR6XLV/vnjNtH8OuAIE/CKgPQfdLCdPzhAgdAPFPggggAACCCCAAAIIINDxAgQIO34KGQACCCCwd4GsKfO5uLpd9tMO/mW2goLraY8jgGYIIwPRYi/AYjlQLQOqZUHN7XB/VLq6Oj8LcO8ztfMRTh9NJ/CUSiWlt7ePPpo7mdr+HT2u2j4FWxfAa2aLgjsIhF4gmUy6MtD/W1kQQAABBBBAAAEEEEAAgTAIECAMwywzRgQQCJ1AoVCQtY28zC1r9l8x8FfsAajBQA0Oml08XXrimgWoQT878KcZgBoA1NvRoZh0x8KRBdgMdC2dqF8s/hSgx5X/5oXXjP/mhCtCwGuBvr4+V6fUD96wIIAAAggggAACCCCAAAJhECBAGIZZZowIIBBIgc1sXhZW7DKg8+bWygI0vQCdbMCNjLcRQE3wGx20A35W4E+DgSbwZ/UENPcHeiJkAQbymcigSgXocVWqwX0EEEDAPwKHD18nMzMnal7QkSPX19yHHRBAAAEEEEAAAQQQQACBIAgQIAzCLDIGBBAIpIBmAV5a116A2z0A9f6C6Q2ot0trOc/H3Z+ImP5/2yVAnSxADQJqcDBmegWyIBBmAXpchXn2GTsCCPhZQDOJp6YOyezsuYqXqdsnJ6cqbmcDAggggAACCCCAAAIIIBAkAQKEQZpNxoIAAp4LOL3gtK+Nlq7ST6fvpfRjOpPfKgFqBQJLMgA1O3Az620WYNRU+Rwb2i796fQAtEqDmmzA/p6o58acEIFOEqDHVSfNFteKAAJhEzh69BapVAZag4O6nQUBBBBAAAEEEEAAAQQQCIsAAcKwzDTjRACBpgqk0xtl32DS0lXOG0yJRI/k8wW5uJbdyvqbM9l/dk9AOytwJel9FuBQX3Sr999WALDYD3D/QEwiEbIAm/pk4WChEqDHVaimm8EigECHCejvZtPTx8T5gFcqlRTtOahlRckc7LDJ5HIRQAABBBBAAAEEEECgYQEChA0TcgAEEAijQKVPn6uFlq76s/97h5yN/D+yuJqRrMcxwLgp87k78OdkAGop0J5ukybIggACLRGgx1VLWDkoAggg0FQBrfawl4oPTT05B0MAAQQQQAABBBBAAAEEfCJAgNAnE8FlIICAfwWyOZMFuGr3/Zs3GYCz5x+VlSr9a3Qk0c05SaYfk2xhtCUDGxmIit3/b2c5UF031B+VSBdZgC2B56AI1BCgx1UNIDYjgAACCCCAAAIIIIAAAggggAACCPhCgAChL6aBi0AAgXYKFAoFWdvIy9yylv00X6b3n33fDgpqcNBUCt1aro09IAdc/PQci56T1Wx9AcKeuGYBFoN/w/FiMDBmrRszvQC7Y2QBbk0IdxDwmQA9rnw2IVwOAggggAACCCCAAAIIIIAAAggggMBlAi7e4r7sMaxAAIGQCTh9WpLJpGh/LS2h12llmTazeVnUwJ8JAK6fSlkBwPOLaTm/sGGt29gsiQDWmN94V7rGHvZm3W+wa0HGoo+K3s8UErKQOySrJqtQE/xGBzXgF9vKBJww9zUoqOVAB3oiZh+yAF1BsxMCPhOgx5XPJoTLQQABBBBAAAEEEEAAAQQQQAABBBC4TIAA4WUkrEAAAUcgnd6Qcr32ZmZOyNTUIdEsGX0j3A+LZgFeWs9ZwT4tA6qZgHNbtxlZWmteI0AN9LlZBiPLsj/xnzt2PRA7I+MHrpSbX3KL9Pf17tjGNwggECwBelwFaz4ZDQIIIIAAAggggAACCCCAAAIIIBAkAQKEQZpNxoJAkwXKBQedU8yaHny6fXr6mLOq5bfpTH5H4E8DgZoRaJUFNfc3s+6zABu5WM0C1EBfrSXetVF2l/nHH5V//uoXPbUreyGsRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEAilAAHCUE47g0agtoCWFdUgYLVFt1+4MCuTk1PVdnO9LW8a/S2ZLMB50wvQDvw5mYAaBMzKpWTzsgDdXtRgb2S7BOhwsQTovoNy/7dPy5wJ9NW7NNuu3uvgcQgggAACCCCAAAIIIIAAAggggAACCCCAAALhEyBAGL45Z8QIuBI4deoBV/udPDmzpwBhMm0CgFuZf8UMQBMQnDf9ARdWMpL1OAYYj3ZZfQCt3n+m/5/2BLTv27c93ZGyDk+YeJnceecdsrAwV3a7m5V7tXNzTPZBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKCWAAHCWkJsRyCkAslk0tXIU6md+2VzBbm46pT+3JkBqFmB6xt5V8dt5k4jA1Er6KfBvwkTBLzm4IBMjSVkbCgukk1LpKtrz6fT3osTEwcaChDuttvzRfAABBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTqECBAWAcaD0EgDAJ9fX2uhjm3GpVPf2XOygqcNxmAiyYT0FQK9XTpiWsWYNwK/o0Vg4ATmgk4HJexwZh0x3dmAY6M9EssFpFsNi9LS5t1X6vbIGqlE/T2ujOu9HjWI4AAAggggAACCCCAAAIIIIAAAggggAACCCBQjwABwnrUeAwCARfIZAsyesWTRGZO1Bzpt2cnZPXR1Zr7NbKDJviNmkCfkwGowcDS+9onsKuOLMBGrkkf6zaIWuk8R45cX2kT6xFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQaJkAAcKW0XJgBPwrUCgU5FKy2AtQ+/+Z0p/aA3CueH9pLSeaBHhdfEz2RRcqDuRSbkxWC6MVt+9lQ18iYjIAnf5/270ANRCopUBjpleg35bDh6+TGRdB1HLXPTV1aE+9G8sdg3UIIIAAAggggAACCCCAAAIIIIAAAggggAACCNQjQICwHjUeg0AHCKQzebvspwn+ae+/+Us7+wFumizBWsupzDPlsHy7bJBQg4O63e0SNVU+NdCnAT+7HKhza6/r74m6PZRv9jt48ErRQN/s7Lk9XZM+5ujRW/b0GHZGAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKBZAgQImyXJcRAwAufPPyqnTj0g2ptOy09qhpkGkVqx5E0WoGb6Wdl/GgRcLgkAmmzAS+u5hk+bk7g8kHmeDGYXZSx6TuJdackUErKQO1Q2c1BLfU5Y5T9NP8BhEwAsBgQnTC/AkYGYRCP+ywJsFEkDfceP31U2SKiBwJtuero88sgPJJVKivYc1LKik5NTjZ6WxyOAAAIIIIAAAggggAACCCCAAAIIIIAAAgggULcAAcK66XggAtsC6fRG2SCRlp90ssUSiZ7tB7i8l0rnrey/0gxADQjOmWzAhZWMZBuPAbq6Ei0jupodlbgp86kZgE/Y1QPQKQ3a023SBEO26LxOTx/bCg6XCwReffUTQqbCcBFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQT8LECA0M+zw7V1jEClDDIdgJaf1O0aRNq9ZHMFubhqMv9MsG9HBmCxHOjaRn73Q1r+/Uh/VMZNxp8GAp1sQOf+PrMt0hW8LMBmoGqmaKuyRZtxfRwDAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAFHgAChI8EtAnUKaFnRWj3odPs///f3JdU1apUE1QxAzQRcNKVA87VbAdZ5ZeUfloh3FQN/O3sAal/A8aGYdMfDlwVYXoq1CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggEU4AAYTDnlVF5KPDggzOuzvYf//2/8kj2Jlf7NrKT5vftH9Tsv5iMmaDfAZMNOGYCf5oNqH0BB3uj0kUWYCPEPBYBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgY4WIEDY0dPHxXshUCgUZCWZs/r+2f3/Mib7L2tKguptRsbTCzISrX0l8a507Z1c7tGXiFgBQCvrTwN/Jhio9zUIOGqCgTHTK5AFAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEECgnQICwnArrQieQzuStoJ/2Apw3gT+nBOicCQBqMHAzW7kO6L5YwpVXpuBuPz1Y1FT5HDVZgFbQz2QAOgFAOwgYk/4eFxFJV1fFTq0U0PKzp049IMlkUvr6+uTw4evoU9hKcI6NAAIIIIAAAggggAACCCCAAAIIIIAAAggg4EqAAKErJnbqdIG8yQJcXtMsQDvrb27Z9ADUYKBmApp1l9ZzdQ9xIXdIDsTO1Hy87le6DPZqFqDp+2d92SVA7YBgTEYGYiZIGI4swCAG0dLpDTl+/K7LelPOzJyQqalDcvToLZJI9JQ+HbiPAAIIIIAAAggggAACCCCAAAIIIIAAAggggIBnAgQIPaPmRK0WSKXzWwFAJ/BnlwTNyoIJBmbrjwFWvfTVwqhcyo3JvuhCxf2ifVfILc86vBUM1EBgb7dJEwzxEuQgWrngoDPVs7PnrODh9PQxZxW3CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgh4KkCA0FNuTtaIQC5fkIurdsaflQGo2YArJhPQKgmakbWNfCOHr+uxI/1RGTclQEf6XySxi9+QzbULlx2HjLHLSKwVQQ2iaUakBgGrLbr9woVZmZycqrYb2xBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQaIkAAcKWsHLQegQKpgyoBvk06293BqCuWzTBQBMj9HRJxLuKZUCL/QCL5UCtsqBDMemOl2YB/pw45TJTqaT09vbJkSPXEwQqM2NBDqJpz0E3y8mTMy17bjjPQ3ofupkJ9kEAAQQQQAABBBBAAAEEEEAAAQQQQAABBMInQIAwfHPe1hFncwWr3Oec6f1nlf802X/bwcCspDa9zQLsMm3+9pt+fxP7igFAkw04bu47vQG1T2CX7uRyOXjwStEvluoCfgiiVb/C+rdqUM7NokHkZi9BLtvabCuOhwACCCCAAAIIIIAAAggggAACCCCAAAIIhFmAAGGYZ78FY9cswJVkzvQCtAOA28G/jLVuyZQI9TgJUPoSkR1Bv61goMkGHDVZgLGo+wBgC8hCech2BtFaDd7X1+fqFJph2uwlqGVbm+3E8RBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgbALECAM+zOgjvGnM3mTBWj3ArT7/5lg4IrJBFy2121mvQ0BRk2Vz9FBk/Wn2X9DxQxAKxNQv4/JQG+0jlHykFYKtDOI1spx6bEPH75OZmZO1DyNlp9t5hLksq3NdOJYCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAiIECHkWXCaQN1mAy2uaBajlP3eWANV1l9Zzlz2m1Su01Kf2/bNLfzolQO2yoPtNcDAaIQuwWXPgRf+6dgXRmmVU7ThaYnZq6pDMzp6ruJtun5ycqri9ng1BLttajwePQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKgsQICwsk2gt6TSeSvrb25XD0ArIGiyAbMexwDjpsznmNP7z2T9jZsMQCcYqIHB3m6TJsjSUgEv+9e1K4jWUsCSgx89eotUKvepwUHd3uwlyGVbm23F8RBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgbALECAM8DPgsYtpmZ3fkIdn16xMQKsvoAkIahbg2kbe85EP90eLWYB25p9dEtS+PzwQlUgXWYCeT0rJCSsFtHQXzYbT7dPTx0oe0djddgTRGrti949OJHosKycbM5VKivYc1LKizc4cdK4qyGVbnTFyiwACCCCAAAIIIIAAAggggAACCCCAAAIIINAcAQKEzXH05VHe9AcPeHpdiXiXlfVXmgloBQFNBqD2AuyOkwXo6YTs4WTt6F/XjiDaHkiasqtmSuqXF0uQy7Z64cc5EEAAAQQQQAABBBBAAAEEEEAAAQQQQACBMAkQIAzTbDc4Vs3v035/E6YU6NiufoATwzEZ7I1KF1mADSq35+Ht7F/nZRCtPbrenDXoZVu9UeQsCCCAAAIIIIAAAggggAACCCCAAAIIIIBAOAQIEIZjnl2PUnv9abBP+/+Nmaw/JwNQg4Kjg3GJxygD6hqzg3akf10HTVaVSw1y2dYqw2YTAggggAACCCCAAAIIIIAAAggggAACCCCAwB4FCBDuEazTd4+aKp+jJgtwvDQDcLgYDDTr+nsiZAF2+iTXcf30r6sDzYcPCUPZVh+yc0kIIIAAAggggAACCCCAAAIIIIAAAggggEDHCRAg7Lgpc3/BNz9z1Ar4DSbEKguqQUEtERqNkAXoXjEce9K/LljzTNnWYM0no0EAAQQQQAABBBBAAAEEEEAAAQQQQAABBJotQICw2aI+Ot47Xn5Istm8LC2t++iquBQ/CtC/zo+zwjUhgAACCCCAAAIIIIAAAggggAACCCCAAAIIINAaAVNwkgUBBBAQ0f51U1OHylLoet3OggACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAp0vQAZh588hI0CgKQL0r2sKIwdBAAEEEECg7QLnzz8qp049IMlkUrTPsJYS12oBLAgggAACCCCAAAIIIIAAAggggIAjQIDQkeAWAQQsAfrX8URAAAEEEECgMwXS6Q05fvwumZ09t2MAMzMnrCoBWg1APxDEggACCCCAAAIIIIAAAggggAACCFBilOcAAggggAACCCCAAAIBECgXHHSGpUFD3c6CAAIIIIAAAggggAACCCCAAAIIqAABQp4HCCCAAAIIIIAAAgh0uICWFd2dObh7SLr9woXZ3av5HgEEEEAAAQQQQAABBBBAAAEEQihAgDCEk86QEUAAAQQQQAABBIIloD0H3SwnT8642Y19EEAAAQQQQAABBBBAAAEEEEAg4AIECAM+wQwPAQQQQAABBBBAIPgCyWTS1SBTKXf7uToYOyGAAAIIIIAAAggggAACCCCAQMcKECDs2KnjwhFAAAEEEEAAAQQQsAX6+vpcUfT2utvP1cHYCQEEEEAAAQQQQAABBBBAAAEEOlYg1rFXzoUjEEIB7S+kJcQ0S0DfCDx8+Do5ePDKEEowZAQQQAABBBAoFdDfCWZmTpSuKnv/yJHry65nJQIIIIAAAggggAACCCCAAAIIhEuAAGG4/ccdHQAANw5JREFU5pvRdqhAOr0hx4/fJbOz53aMQN8InJo6JEeP3iKJRM+ObXyDAAIIIIAAAuER0A8M6e8Eu39XKBXQ7ZOTU6WruI8AAggggAACCCCAAAIIIIAAAiEVoMRoSCeeYXeWQLngoDMCfSNQt7MggAACCCCAQLgF9ANDGgQstzgfKCq3jXUIIIAAAggggAACCCCAAAIIIBA+ATIIwzfnHT/isJXZ1PFWywbQCdXtFy7MkhXQ8c9uBoAAAggggED9AlpNYHr6mDi/K6VSSdGeg1pWlMzB+l15JAIIIIAAAggggAACCCCAAAJBFCBAGMRZDeiYwlpmU3sOullOnpzhzT83UOyDAAIIIIBAwAW03Cg9igM+yQwPAQQQQAABBBBAAAEEEEAAgQYFKDHaICAP904grGU2k8mkK2TNEmBBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBGoJECCsJcR2XwjspcymLy64iRfR19fn6mhaQowFAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKglQICwlhDbfSGwlzKbvrjgJl7E4cPXuTqa9hdiQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRqCRAgrCXEdl8IhLnMpvYQmpo6VHUedPvk5FTVfdiIAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCKgAAUKeBx0hEPYym0eP3lIxSKjBQd3OggACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgi4EYi52Yl9EGi3gJbZnJk5UfMyglpmM5HokenpY6K9GLXcaiqVFO05qOMlc7Dm04IdEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoESAAGEJBnf9K+CU2ZydPVfxIsNQZlMd9IsFAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKhXgBKj9crxOM8FKLPpOTknRAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgQAKkEEYwEkN6pAosxnUmWVcCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggg4KUAAUIvtTlXUwQos9kURg6CAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACIRUgQBiSiT9//lE5deoBSSaT0tfXJ4cPX0cvu5DMPcNEAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBEoFCBCWagTw/sbGhtx55+0yO3tux+hmZk7I1NQh0b5+WrqTBQEEEEAAAQQQQECED1XxLEAAAQQQQAABBBBAAAEEEEAAgTAIECAM+CzfccflwUFnyBo0PH78LpmePuas4hYBBBBAAAEEEAilQDq9Yf1eVO1DVSL9obRh0AgggAACCCCAAAIIIIAAAgggEDyBSPCGxIgcgTNnzsiZM6edb8ve6ptgFy7Mlt3GSgQQQAABBBBAICwC+qGp3cFBZ+zOh6qc77lFAAEEEEAAAQQQQAABBBBAAAEEOl2ADMJOn8Eq1/+9732vytbtTSdPzsjk5NT2Cu4hgAACCCCAQOgEwlxaU8deKTjoPBF0+7lzZ+Xaa69xVnGLAAIIIIAAAggggAACCCCAAAIIdKwAAcKOnbraF76+vl57J7NHKpV0tR87IYAAAggggEDwBNyU1gx6v+JTpx5wNbH64atrr73G1b7shAACCCCAAAIIIIAAAggggAACCPhZgBKjZWYnk8mYvnzTcuTIEbl48WKZPdyv2tzclM985jPyyle+Um666Sbr66Uvfanceuutsra25v5AdezZ3++uT05vb18dR+chCCCAAAIIIBAEAUpriiST7j4slUy6+/BVEJ4XjAEBBBBAAAEEEEAAAQQQQAABBIItQIBw1/wWCgV5//vfLw8++OCuLXv/dmNjQ970pjfJBz7wAbnvvvskn89bB3nooYfkT/7kT+SWW26Rs2fP7v3ALh9x4403utrzyJHrXe3HTggggAACCCAQLAG3pTWD3q+4r8/dh6X6+tx9+CpYzxJGgwACCCCAAAIIIIAAAggggAACQRQgQFgyq5rt9973vlduu+22krX13/3t3/5tufvuu2VoaEg++tGPyj333CP33nuv/OVf/qUcPHhQzp8/L29961tFMxZbsVx99dVy9dXXVD301NT/396dwF89Jf4fP2mTKIW0KCrKIFNEpPlppkZflchkadLIFmYiy1iSRo/CNGGMfRkMiihLE8lMxtJEiNHY19CiRRhKUnT/933+zvW5937u8v3ez+d+7r3f13k86n7Wc87neT/n+7mfz/mcc9oy/mBWIVYigAACCCBQuQL5dq2p8YorOXTq9JO8Di/fl6/yioyNEEAAAQQQQAABBBBAAAEEEEAAgQgFqCD8AX/x4sVm6NChZsaMGYF8HWoxOGfOHBvXpEmTTL9+/UzdunXtfM+ePc0dd9xhGjRoYJTu9OnTA0nTL5IhQ44yqgT0C1peVXWY36patUytJ55+eq557LG/20/NExBAAAEEEKgNAvl2rVnp4xW3br1Txt9L7jzQ76a2bdu5WT4RQAABBBBAAAEEEEAAAQQQQACBshaoV9a5DyDz6gZUFXiqGPzuu++Mxu3r3bu3mT17dkGxT5061e6/6667mj59+qTF1b59e9vF6IMPPmj0b9iwYWnbBLFgyy23jI+neFS8teIyo1YCesCnMQfVrWirVm2CSKJs4/j22w3Gb9ylN998zT4kVOVpw4Zblu3xkXEEEEAAAQRyCeTbtWZtGK9Y132/3wUy5KWqXGcS6xFAAAEEEEAAAQQQQAABBBBAoNwEan0F4Zo1a8y0adPs99arVy8zfvx4s3DhwoIrCBcsWGDjPOiggzKeE0pPlYNvvPGGWb16tWnRokXGbQtdoTfj9Y/wo0Cmh4DaYvnypfYhoSpXCQgggAACCFSqgLrW1IsxuUJtGK9YLwXxUlWuM4H1CCCAAAIIIIAAAggggAACCCBQKQK1voKwTp065oADDjCnnHKKUYWdgioICwlr1641K1eutFGoBWGm0KFDh8Sqd999N9QKwkRCTFgBtahUJWC2oPUrViyv9S0tsxmxDgEEEECgvAVc15rZrolqPVebeh3gparyPqfJPQIIIIAAAggggAACCCCAAAII5CdQ68cgbNOmjbnrrrsSlYP5sWXfatWqVYkNWrVqlZhOndhxxx0Ti9SCkFA8AXW3mk94550389mMbRBAAAEEEChbAXWtqUpAv0DXmn4qLEMAAQQQQAABBBBAAAEEEEAAAQTKX6DsWxBed9115vrrr6/WN3HNNdeYqqqqau1TnY3VgtCFRo0aucm0T++6devWpa1nQXgC69evzytyjdlIQAABBBBAoJIF6Fqzkr9djg0BBBBAAAEEEEAAAQQQQAABBBDwFyj7CkL/w4p26ffff5/IQIMGDRLTqRPedd59UrcrZL5u3TqmWbPGhURRkftuu22TvI6radMm+OUlVV4bqVwoUD7K63sjt8URoHwUx7kUU2nWrLPZc8/OpZi1kskT5aNkvgoyUoIClI8S/FLIUskIUD5K5qsgIyUoQPkowS+FLJWMAOWjZL4KMlKCAq58lGDWyipLZV9BOGzYMNO/f/9qoXu79qzWjnlu3LBhw8SWGzduTEynTnjX1a9fP3V1IPMaY7Fevf9fGRJIhBUSSdeuPzWLFr2S82i6desa96v1PfHmdCrXDSgf5frNke9iCFA+iqFMGuUqQPko12+OfBdDgPJRDGXSKFcByke5fnPkuxgClI9iKJNGuQpQPsr1myPfCJS+QNlXEDZv3tzoXymFxo1/bLG3YcOGjFn75ptvEuu23nrrxDQT4QvsvPPO5pJLLgk/IVJAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBEpMgKZRIXwhLVu2NHqzQ2HlypUZU1i1alViXditGhMJMYEAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIFCrBaggDOHr32qrrUzbtm1tzIsXL86Ygnddp06dMm7HCgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQSCEqCCMCjJlHgOPPBAu+TZZ59NWfPj7Pz58+3MbrvtZrbbbrsfVzCFAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQEgCVBCGBDto0CAb89tvv22eeOKJtFQ++ugj88gjj9jlw4cPT1vPAgQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTCEKCCsADVqVOnmqqqKvvv1VdfTYqpe/fupm/fvnbZeeedZ2bOnGm+++47O79gwQJzwgknmI0bN5r27dubwYMHJ+3LDAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJhCdQLK+LaEO8XX3xhPvzwQ3uo33zzTdohX3rppWbFihXmjTfeMBdccIEZN26cqVevnlm/fr3dtmXLlub22283DRo0SNuXBQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgiEIUALwjBUf4izWbNm5r777jNjxowxXbp0MfXr1zebNm0yu+yyiznxxBNtq8I2bdqEmAOiRgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCBZoE4sHpIXMYcAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAApUqQAvCSv1mOS4EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEfASoIPRBYRECCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAClSpABWGlfrMcFwIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAI+AlQQ+qCwCAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFKFaCCsFK/WY4LAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAR8BKgh9UFiEAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQKUKUEFYqd8sx4UAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIICAjwAVhD4oLEIAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECgUgXqVeqBVeJxbdq0yQwZMsS8/fbbZsGCBaZ58+Y1PsyNGzeae++91zzyyCPmgw8+sPHstNNO5pe//KU56aSTzNZbb50x7lgsZh566CHz4IMPmnfeeccoXy1btjS9e/c2J598smnRokXGfVmBQJACTzzxhD2PX3/9dfPNN9+YHXbYwRx00EHmxBNPNO3bt69WUsuWLTN9+vSp1j6jRo0yZ5xxRtI+P/vZz8zq1auTlqXOKG+PP/546mLmEQhUIMjy4TK2YcMGs88++5jvv//eLfL97NWrl7n99tvT1nH9SCNhQUQCYZQPHcrSpUvN3XffbX+nLV++3Hz33Xf22tS9e3czfPhw06VLF98jLrRs+UbKQgSyCLz44ovmzjvvNK+88opZu3atva/Yb7/9zIgRIzKep1mis6sK/RsfVrnMlW/WI5AqEEb5WLNmjZkyZYqZN2+e+fjjj43ux3U/37VrVzN06FBz4IEHpmYjMc/9RYKCiYgFwigbhZ7fXDsiPilIPiEQZPno3LlzIt58JgYPHmwmTZqUtOmxxx5rf+clLUyZadCggXnttddSljKLQPgCI0eONM8884x54IEHanzvoVxy/xHMd1UnDhkLJipiCVNAX9Mll1xi7r//fptMIRWEegilSsCXXnrJxtWwYUOzxRZb2AoWLWjdurW56667TLt27ex673+bN28255xzjpkzZ45dXL9+faMLytdff23nt912W3PLLbfYGx3vfkwjELTAn/70J3PHHXfYaOvWrWsaNWpk1q1bZ+e33HJLc9VVV5m+ffvmneyKFStsBXyuHZSGypDC+PHj7Q2920c3/qqgVNANv8qVX9h5551txabfOpYhEIRA0OXD5WnRokXmmGOOsbPbb7+9W5z2ecABB9gy6F3B9cOrwXSUAmGVD/02GjNmTOL3lK5L+v3mrhm6Jpx99tlGN0OpoZCylRoX8wjkElAlxaWXXmo303mpFwO/+uorO6/fVBdffLH59a9/nSuapPWF/o0Pq1wmZZIZBPIQCKN8LFy40OjFwv/97382B7r/Vllbv359IkfHHXecLXt16tRJLNME9xdJHMxEKBBG2Sj0/ObaEeEJQdJJAkGXD/dcKSmRlBldQ9x15JRTTjG///3vE1vod5le7NWL9HpOW6+ef/sgXY+efPLJxH5MIFAMgZtvvtlcffXVNqlCKgi5/wjw21IFIaG0Bb799tvY2LFjY506dUr8++yzz2qc6dGjR9t44m+zx+KtmGLxt9ttXM8++2ysd+/edl1VVVUs/lZjWhqTJ0+26/fcc89YvLIyprwpvPrqq7GBAwfadfEHw7EvvvgibV8WIBCUwD333GPPtfhbVbEbb7wxFq+0s1EvXrw4Fr+5tuv23nvvmOaDDJ988kmsR48eNv4zzzwzFr8YJUX/9NNP23UqH65sJG3ADAJFEAizfEydOtWe47pWVDdw/aiuGNuHIRBW+Xjrrbdi+tuv32rxSvTYf//7X5v9eGvbWLznh1i8Zbtdp/WzZ89OO7RCylZaZCxAIIuAfqvo95POxQkTJiR+s8dflIrpt42W77777rEXXnghSyzpqwr5Gx9WuUzPJUsQyC4QRvlYtWpVbN9997Vlq1+/frHnnnsupmuDwpIlS2Lxl28T14dbb701LYPcX6SRsCACgTDKhg6jkPOba0cEJwJJ+gqEVT58E/thYbz3h9ghhxxirx/xloJpz5/ee++9xLVF1xoCAqUgoGeo1157beLc1H2H6hNqGrj/qKlc+n7+zVsCrIAkqsIE4hUctoXSjBkzCovoh73VFaNr/afm5/GbFPv2olb37NnTtshSi0ClO3369KQ04zc3ttssLTz//PPN0UcfbVsPal5dZqnV4XbbbWc+//xz24pQywkIBC2gN6BuuOEGG+3xxx9vTj/9dNO4cWM7r647//rXv5pdd93Vtthwb6QEkQd1pauWH/HKb9OhQwdz+eWXm9Q3fN944w2blNJXOSIgUGyBsMvHm2++aQ9pjz32qNahcf2oFhcbhyQQZvnQdUnXCXXXru514y+p2KNQ6yx1ERR/6Gv2339/u+yaa65JO8Kalq20iFiAQBaB+K2gbd2tTw0rMG7cOPtWuXbRcAH63aT7Ab2Nq1YZ+YZC/saHWS7zzT/bISCBsMqHejxRN77bbLONvZdWV6Kul5G2bdvaMjlo0CD7Jdx0000m/pJh0hfC/UUSBzMRCIRVNnQoNT2/uXZEcCKQpK9AmOXDN8EfFl500UXmo48+ss9g//KXv6Q9f3Jlq2nTpkbXGgICUQvofkHDkl1//fWBZIX7j0AYE5FQQZigKK0JdUel7gsPO+wwo0o9VYAMGDCg4EzG31C3cagCw2+8NVWwKE0FjTHoDaow1FgJTZo0MerLOjWoS8Vhw4bZxX//+99zjlGVuj/zCOQjoApudUWiyjl1o5Aa1L2oW66uElxXPqnbVXdeD381To+6ZrjiiisSlZLeeNwD3ngrEu9iphEomkDY5aOm5zjXj6KdAiSURSCs8qExOTV+goK64HUvrXizoq7k3G8n3cyvXLnSu9rUtGwlRcIMAjkENDaOxg9X8OvqVpUWv/vd7+x63X+4be2CLP8V8jc+rHKZJbusQsBXIKzy8dRTT9n0+vfvb1q0aOGbtruH1rAdqWNBcX3wJWNhEQXCKhs6hJqe31w7ingCkFRWgTDLR6aE1YDkH//4h10d7w3C7LjjjmmburJV3Rd70yJiAQIBCOglRDVQmj9/vtFQZUceeWTBsXL/UTBhUgRUECZxlM6MKkCmTZtm4t1/ml69ehlVuOmz0KCxCxWy9Wft0tEbJ6tXr04k6fbVG/CZWkdpgGmFeBeoJt5MOLEvEwgEJeDOw3j3VybTGGjuPFRrDl2ACg0ff/yxbRGieEaMGGH22msv3yjdjzAqCH15WFgEgTDLh14QiXdVYo+iuue4yxfXjyKcBCSRUcCdh0FfPzT2x+GHH27iXe9mHYNZ47y54MZ703whZcvFxycC+Qi4MqCxaNT7h1/o1q1bopI73mWW3yZpy1y8Nfkb7/YNulymZZIFCOQQcOdi0OVD99Z6MVfjM2cKal3oglobegP3F14NpqMQCKts6Fhqen67PHHtiOKMIE2vgDsXg752eNPwTn/55Ze25bmWHXrooaZv377e1YnpmpatRARMIBCggMYcVMtv3X9ozMEjjjii4Nhd2eP+o2BKG0G9YKIhlqAF1DpKNxFqCeUq7DS4eSFBNxvujXW1IMwU1H2iC++++27iTUf3YDjbvmqB6IL21UMGAgJBCrjzsGPHjhmjVVe3aumqB7A6DwsN6k5UD3D1ZpZ7sz41TrVUXL58uV3cqlUr2w2qKidV5rbaaiujN7fULe9+++2XuivzCAQmEGb5UNyqdFdo1qyZufLKK83zzz9vW/TqwVbXrl1tK3LdqKcGly+uH6kyzBdTwJ2HQV8/dP5PnDgx56G89NJLdhu10lJ3ji4UUrZcHHwikI+AKwP6vZ7aTbrbX61d27VrZ+Ljaub9G8rFW5O/8W7foMulOx4+EchXwJ2LQZcPdeWbK3jv83Uf4QL3F06CzygFwiobhZzfLk9cO6I8M0hbAu5cDPrakUlX3Ylq2Bs9Y7rwwgt9N1O3p/odp7DLLruYO++806g1+9KlS21jj/i4b/blRr9e5XwjZCECBQqokcVJJ51kK7V1DxIf67zAGH8se9x/FExpI6CCMBjHwGNp06aNHdMvyIjVP68L3hsPt8x9epunuxaEqul3b7tn21cPyXSh0tv0bl8XL58IBCHgzuPWrVtnjU4PX3XOFnoe6oGue4Ne4x3q/PYL7g0trRs9enTa+CHvv/++mTVrlu1+7pJLLkmM/ekXF8sQqKlAmOXDneP6QaeusFRp7sKKFSvsg2R1d3LGGWckVaRz/XBKfEYtEGb5yHVsn376qbnvvvvsZt27d7cvsbh9alq23P58IpCvQHXKgB4s5fMbqtC/8dXJUxC/6/K1YrvaJ1CdczHf8pGPosqQxlBX0Di23het3PVB67i/kAIhCoGwykYh53d18sS1I4qzpvakWZ1zsdBrx7Jly8z9999vcXU/7n3h0Cu+ZMkSO/atluklxtSxbT/88EPbRakqCPXSb6ZnXN44mUagEIHUIcwKiUv7cv9RqGD6/lQQppsEsuS6666r9sCb11xzjamqqgokfb9IvN2VNGrUyG8Tu8y7bt26dXZZvvtqY+2vCkK3r42A/xDwCBRSPty56D1PPVEnJjUWoUKh5+Ftt91m49GPr1/96ld22u8/Nwi01qny8uyzzzY9evSw5UE3PzfddJMdo0o/6JQ3DSpNQMBPoFTLhzvH9UaiWsSqNe0+++xj1Bpq0aJFRtcwfV577bVGXSkef/zx9vBcmdVMrnLL9cPvjGCZV6BUy4c3j6nTqkw/66yz7EsrqmA/88wzkzapadlKioQZBPIQcH+Pc/0trs5vKBenks8Vr9/feLd/rn2rk6c8KNgEgTSBKM5F/abSPYEe+iroJStvcNcHLeP+wivDdDEFwiobhZzfYeWpmK6kVRkCxTwX1RJQY5+rQu/EE0/MCOgtW02bNrX3IQcffLB9QXHx4sXmjjvusMNY/etf/zLnn39+tZ9dZ0yYFQgUScCVOyWX6x6C+4/8vhTGIMzPqSK20oXEhUxjCGq9d53bx31qvQYUzRbc/t59sm3POgSqI+DOq3zPQ43jWdPwwQcfJFoPqrtfd277xacuFzW2p7oEVp/aGoBX/dA3bNjQdrV7yy23mAEDBthdp0yZkuiKwi8uliFQU4Ewy4ceTKnSu3///uaee+4x//d//2crAnWD0rNnT6PzWi2jFNT1yeeff26nXZ40k2+59e5jI+E/BAIQcOdVvudhIdcPl90NGzaY3/72t8Z1L3rqqaemdTVd07Ll0uATgXwFwigDLk7lId+y5d3HTee7bxDlMl8vtqtdAsU+Fzdv3mzGjh1rHnvsMQs9cODAtDF5uL+oXedgqR5tWGWjkPM7rDyV6ndAvkpXoFjnorrkda2wjj32WNO8efOMKHqpSvfqGvJJz6b0ovv2229vn2eplfrkyZPtcFaKYO7cuWbevHkZ42IFAqUo4Mqd8pbvPYR3Hzed77614f6DFoQhnelq7q2HqNUJ3q49q7NfvtuqosIFb9dwbpn79K5zhcW7rxuDym2f+un2d/umrmcegULKh37sqIVqvudhtkq9XN/EtGnTjN7sVde5Rx11VNbNhwwZYvQvU1CrEfURP2fOHKMHArNnz7ZvcmXanuW1V6BUy8fIkSON/mUKKmt6A1FjbaqM6o1ElRuuH5nEWF4TgVItH37HovFB1DX1K6+8Ylcffvjhtou41G1rWrZS42EegVwCrhVevr+h8vktX+jf+GL+rsvlw/raLRBG+cgkqpdHzj33XPPEE0/YTfSilcY8Tw3cX6SKMB+FQFhlo5Dzm2tHFGcCafoJhFU+UtOaOXOmvcdW7z0jRoxIXZ00/4tf/MLoX7YwatQoM336dPPll1+aRx55xFYoZtuedQiUkgD3H8F/G1QQBm9qY9TbHNne6Agp2azRNm7cOLFeNyWZgvrydUHdxCm4T01n21fr3f7efbScgIATKKR86DxW5UOu89Ctr+l5qIrBf/7znzbLhxxySFIlhzuO6n62aNHCdOjQwWg8QjeYdXXjYPvKFyiH8pHpW9h7770T49C6c9xbBl25zLQ/149MMix3AuVSPvR3XpWDGgNE4ZhjjjHjx4+3XfK6Y6nOp1/Zqs7+bIuABNy9QK6/xW69XpDKFQr9G1+s33W5joP1CIRRPvxUNV6Vrg+uC7if//zntpt278Muv/0yLeP+IpMMy4MSKFbZ8MtvpvOba4efFsuiEChW+Xj88cft4e2///4miMYlqtjs2rWrHQbH3bdH4UeaCNREgPuPmqhl34cuRrP7VNRajaGmVkwKK1euzHhsbpBdbeAuPGoZst1229l9su2rfoBVeePd187wHwIBCbRq1crGlO081AZuvTuHq5u8Wny4sjBo0KDq7p5xe/ewzT18y7ghKxCogUCxykemrOka436suXOc60cmLZYXW6BY5ePf//63rRBU5aDKxOjRo82ECRNqXDkoJ7+yVWw/0it/gTDKQKF/48PIU/l/UxxBFALFOBdff/1129WbqxzUyyM33HBDwS8icn8RxRlTe9IsRtnIpul3fkedp2z5ZV3tEijGuajnUosWLbKwYTybci/p1q5vjqMtZwHuP4L/9qggDN60ZGPUOFFt27a1+dPAtJmCd12nTp0Sm7lp7/rEyh8mvOvc9qnbMI9AIQLuvPKea6nxrVmzxnz11Vd28W677Za6Oq/5J5980m63ww47GL2llS2oq6777rvP3Hjjjea5557Ltqn59NNPE/Fm3ZCVCNRAIKzyoa5HNO7g9ddfb/RwK1NQWdD4CAoqOy7kky9vmXbbu/35RCAIAXdeec+11HgLvX7MmDHDaJzBdevW2XE+rrzySjsGYWo6br7QsuXi4ROBfARcGfjwww8zbq4xNj7++GO7Pt/fUC7ebGXLu85tr0TctHd9auYKLZep8TGPgJ+AOxeDLh8uraefftocd9xx9l5AXcSpW3a9PFK3bl23SdIn9xdJHMxEKBBG2Sj0/HZ54toR4YlB0lbAnYthXTuUiJ5NqYcrdf3er1+/nPIPP/ywufnmm41rdZhpB/dsSi11CQiUm4Are9muA951bnsdp5v2rk89/tp2/0EFYeoZUOHzBx54oD3CZ599NuORzp8/367TQwHXalAL3L4vvvhixvHf3L5NmjQxe+yxR8Y0WIFATQXcefjmm28aje/kF9x5qJvvHj16+G2Sc5l7Q2ufffbJ2epDP9Suuuoq2z3Q3/72t4xx6+KzbNkyu37ffffNuB0rEKipQJjlY+LEiea6666zA51nyt/zzz9v3Di03bt3T2zm8sX1I0HCRAQC7jwM6/qhysFx48YZDXq+7bbbmrvuussMHDgw55EWUrZyRs4GCHgEXBn47LPPzFtvveVZ8+Okfv+43kAOOOCAH1dkmXLx1uRvvNs3rHKZJdusQiBJwJ2LQZcPJTJv3jxzxhln2KE41K2bfk+ddNJJSemnznB/kSrCfFQCYZSNQs9vlyeuHVGdFaTrBNy5GMa1w6Xhnk117tw50VuPW+f3qXuQq6++2lx77bV+q+0yvaT46quv2mmeTWVkYkUJC7iyx/1HMF8SFYTBOJZNLK45+ttvv50YFN2b+Y8++sgOUKtlw4cP964yAwYMsG84fv755+bee+9NWqcZLVcLE4WhQ4eaevUY4tJi8F+gAhpsWV0Y6gHsTTfdlBa3ujW87bbb7PL+/fsnVXKnbZxhwebNmxPjgvz0pz/NsFXy4r59+9oFakHofsB5t1B+L7/8crtID45VnggIBC0QVvlo2rRpoiWtBjFfunRpWtZV9tRaSqFjx47G+2CZ60caFwsiEAirfOhQXn75ZTvGoN7uVdfW06ZNM3rBJFcotGzlip/1CHgFunXrZtq1a2cXqVvD1KDfP265tu3SpUvqJr7zhfyND7Nc+maWhQhkEAirfKhF7llnnWVfoNI9jF4mdPcNGbKSWOy24/4iQcJEBAJhlY1Czm+uHRGcCCTpKxBW+fAm5iryqvts6oMPPsjYilD37epaVJX1Rx99tDc5phEoCwHuP4L9mqggDNazJGKbOnWqqaqqsv/chcRlTC063A+x8847z8ycOdOoKyGFBQsWmBNOOMHevLRv394MHjzY7WY/d9ppJ9stimYmT55s7rzzTuPGmFKXcyNGjDB6a6Z58+Z2OmlnZhAISEBd5Z555pk2Nr0Z9ec//9lo7EsFVXCfcsopRoMsN2rUyLdbt2zlw0byQzzu7fldd93VLc76OWrUKKMBqlWeND1nzpxES6r333/fnHbaaUbjUmkcqfHjxxsdBwGBoAXCLB/nnnuuffFDXSeefPLJRi3R3fVD1xq9VKKXT3STcemllybGvNUxcv0I+psmvpoIhFU+9ALIRRddZMtDw4YNbXfTHTp0yDuLhZStvBNhQwR+ELjgggvs1Ny5c82YMWPsb3ct0Pg255xzju0qXV0eqkLDG7S9u7/QtDcU8je+0HLpzQfTCBQqEEb5UMvyr7/+2v4uuuKKK/J6ecQdB/cXToLPqAXCKBuFnN9cO6I+I0jfKxBG+XDx65mr675UL+HmE/RstmXLlnZT3aNoOBz3fOuTTz4xyu/06dPt+rPPPtu0bt06n2jZBoGiC3D/UTzyOvE3nWPFS46UChF46KGH7I284lBlniri/IK6LNE4UQp33313WheL6pZRXZq4wdE1uKda+7kLhi4kaiHYpk2btOi//fZbW/mhblIU9CBYD8P0wFhBA0ir0mbPPfe08/yHQBgCesNdN9sPPPCAjV4PslQ558Yd1HmpN+APPvjgtORzlQ/t8MILL5jf/OY3dt/777/fdO3aNS0evwULFy605cONwaZ8qaLSlQ/lS/k+5phj/HZnGQKBCIRZPlTxrQfKbiBzndP6564fKod6G1Fv9aYGrh+pIsxHIRBG+dD4HqNHj7aHo/KgVoG5gq5F3haGhZStXGmxHoFUAd0n6BxU0ItL+v2ul610W6h5dXt71FFHJe3mvQ/54x//aI488sik9YX8jS+kXCZlghkEAhAIsny89tprZsiQITZXui9o1qxZzhyOHTvWqBcUF7i/cBJ8Ri0QZNlwx1LI+c21wynyWQoCYZQPHZeGqOnTp489RL0cn29PVHpJfeTIkWb58uV2X/d7zz0z03A8p59+euLle7sR/yFQJAHvM1c9183Uawn3H0X6QuLJ0Adk8axLJiXdmOgNElUCPvroo0bjomnMqF122cU+1NVFJNPNiyoDb7nlFqNBb/XvnXfesQ+KVZnYq1cvc+qpp/pWLJbMwZORihDQj5nLLrvM9O7d257LasGqSjgNrqxuDdWK0A06W5MDVne5LuihWb5hv/32M7NnzzZTpkwxTz31lFmyZIkdr1PdefXs2dMcf/zxpjqtSvJNl+0Q8AqEWT4OPfRQs9dee9kXQTTWp95AVNDbjKqQHxF/W1HdK/oFrh9+KiwrtkAY5UMPt1zYtGmT0YDmuYK284ZCypY3HqYRyEdArTb2339/+7dc3aLrxSb99tcYNOpNpCZj0RTyNz6McpmPA9sg4CcQZPnwXh/U2jyf64ProcfljfsLJ8Fn1AJBlg13LIWc31w7nCKfpSAQRvnQcdX02ZR6wpo1a5YdBkqtsNTdqF7yVWtB/QYcNmyY2XvvvUuBjjwgUGMB7j9qTJe2Iy0I00hYgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDlCmxRuYfGkSGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQKoAFYSpIswjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggUMECVBBW8JfLoSGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQKkAFYaoI8wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAghUsAAVhBX85XJoCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCKQKUEGYKsI8AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAhUsQAVhBX+5HBoCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACqQJUEKaKMI8AAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBABQtQQVjBXy6HhgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggECqABWEqSLMI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIFDBAlQQVvCXy6EhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkCpABWGqCPMIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIVLAAFYQV/OVyaAgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgikClBBmCrCPAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIVLEAFYQV/uRwaAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAqkCVBCmijCPAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQAULUEFYwV8uh4YAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAqgAVhKkizCOAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQwQJUEFbwl8uhIYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJAqQAVhqgjzCCCAAAIIIIAAAggggAACvgKffvqp6dGjh+ncubPZfffdzX/+8x/f7V5++WXzk5/8xG7Xr18/s379et/tWIgAAggggAACCCCAAAIIIBCNABWE0biTKgIIIIAAAggggAACCCBQdgI77LCD+cMf/mDzHYvFzLhx48zGjRuTjkOVgRdeeKHZvHmzqV+/vrnyyivNVlttlbQNMwgggAACCCCAAAIIIIAAAtEKUEEYrT+pI4AAAggggAACCCCAAAJlJTBgwABTVVVl8/z++++bW2+9NSn/kyZNMkuWLLHLRo0aZbp06ZK0nhkEEEAAAQQQQAABBBBAAIHoBerE3/qMRZ8NcoAAAggggAACCCCAAAIIIFAuAl988YUZOHCgWbNmjWnQoIGZOXOm6dixo3nmmWfMyJEj7WF0797dTJkyxWyxBe+llsv3Sj4RQAABBBBAAAEEEECg9ghwp1Z7vmuOFAEEEEAAAQQQQAABBBAIRKBZs2ZmwoQJNi51MTpx4kTz1VdfmYsvvtgu22abbczkyZOpHAxEm0gQQAABBBBAAAEEEEAAgeAFqCAM3pQYEUAAAQQQQAABBBBAAIGKF+jTp4854ogj7HEuWLDADB8+3KxevdrOa5zCNm3aVLwBB4gAAggggAACCCCAAAIIlKsAXYyW6zdHvhFAAAEEEEAAAQQQQACBiAXWrl1ruxpduXJlIifqevSqq65KzDOBAAIIIIAAAggggAACCCBQegK0ICy974QcIYAAAggggAACCCCAAAJlIaCuRC+88MJEXjXe4Pnnn5+YZwIBBBBAAAEEEEAAAQQQQKA0BaggLM3vhVwhgAACCCCAAAIIIIAAAmUhMGvWrEQ+N2/ebG699dbEPBMIIIAAAggggAACCCCAAAKlKUAFYWl+L+QKAQQQQAABBBBAAAEEECh5gYcfftg8+eSTNp9qTahwzz33mOeff95O8x8CCCCAAAIIIIAAAggggEBpClBBWJrfC7lCAAEEEEAAAQQQQAABBEpaQOMOXnbZZTaPbdq0MTNmzDCNGzc2sVjMXHTRRWbdunUlnX8yhwACCCCAAAIIIIAAAgjUZgEqCGvzt8+xI4AAAggggAACCCCAAAI1FBg7dqxZu3at3XvChAmmffv25txzz7Xzy5cvN5MmTaphzOyGAAIIIIAAAggggAACCCAQtgAVhGELEz8CCCCAAAIIIIAAAgggUGEC06ZNM/Pnz7dHdfjhh5tevXrZ6aFDh5pu3brZabUonDdvXoUdOYeDAAIIIIAAAggggAACCFSGQJ149y+xyjgUjgIBBBBAAAEEEEAAAQQQQCBsgaVLl5pBgwaZ9evXm+bNm5vHHnvMNGvWLJHse++9ZwYPHmw2bdpkdtxxR/Poo4+aJk2aJNYzgQACCCCAAAIIIIAAAgggEL0ALQij/w7IAQIIIIAAAggggAACCCBQFgKbN282Y8aMsZWDyrDGGvRWDmrZbrvtZkaOHKlJs2rVKjNx4kQ7zX8IIIAAAggggAACCCCAAAKlI0AFYel8F+QEAQQQQAABBBBAAAEEEChpgbvvvtssXLjQ5vHggw82hx12mG9+TzvtNNOxY0e7btasWWbu3Lm+27EQAQQQQAABBBBAAAEEEEAgGgG6GI3GnVQRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQiESAFoSRsJMoAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAtEIUEEYjTupIoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBCJABWEkbCTKAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALRCFBBGI07qSKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQiQAVhJGwkygCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC0QhQQRiNO6kigAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEIkAFYSRsJMoAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAtEIUEEYjTupIoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBCJABWEkbCTKAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALRCFBBGI07qSKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQiQAVhJGwkygCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC0QhQQRiNO6kigAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEIkAFYSRsJMoAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAtEIUEEYjTupIoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBCJABWEkbCTKAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALRCFBBGI07qSKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQiQAVhJGwkygCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC0QhQQRiNO6kigAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEIkAFYSRsJMoAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAtEIUEEYjTupIoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBCJABWEkbCTKAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALRCFBBGI07qSKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQiQAVhJGwkygCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC0QhQQRiNO6kigAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEIkAFYSRsJMoAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAtEIUEEYjTupIoAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBCJABWEkbCTKAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALRCFBBGI07qSKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQiQAVhJGwkygCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC0QhQQRiNO6kigAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEIkAFYSRsJMoAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAtEI/D9EC3/7J9UwCQAAAABJRU5ErkJggg==\" width=\"1800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1160c4d30>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(12, 4), dpi=150)\n",
    "fig.tight_layout(pad=3)\n",
    "\n",
    "ax.plot(x_true, y_true, label='True model')\n",
    "ax.plot(x, y, '.', c='gray', ms=10, label='Data')\n",
    "ax.set_xlim(-1, 1)\n",
    "ax.set_ylim(-1, 1)\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate posterior distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m0 = np.zeros(M)\n",
    "S0 = alpha**-1 * np.identity(M)\n",
    "w0, w1 = np.mgrid[-1:1:0.01, -1:1:0.01]\n",
    "\n",
    "fig, axes = plt.subplots(1, 3, figsize=(12, 4), dpi=150)\n",
    "fig.tight_layout(pad=2.75)\n",
    "\n",
    "artists = []\n",
    "\n",
    "for n in range(0, N+1):\n",
    "    # calculate mn and Sn\n",
    "    Phin = Phi(x[:n], M)\n",
    "    Sn = inv(inv(S0) + beta * Phin.T@Phin)\n",
    "    mn = Sn @ (inv(S0)@m0 + beta * Phin.T@y[:n])\n",
    "    \n",
    "    ax = axes[2]\n",
    "    ax.set_xlim(-1, 1)\n",
    "    ax.set_ylim(-1, 1)\n",
    "    ax.set_title('Data space')\n",
    "    ax.set_xlabel('$x$')\n",
    "    ax.set_ylabel('$y$')\n",
    "    im2 = []\n",
    "    im2 += ax.plot(x[:n], y[:n], '.', c='gray', ms=10)\n",
    "    im2+=[ax.text(-0.9, 0.8, f'# of data = {n}', fontsize=15)]\n",
    "    for i in range(6):\n",
    "        w_sampled = posterior_sample(mn, Sn)\n",
    "        im2 += ax.plot(x_true, linear(x_true, *w_sampled), lw=1)\n",
    "    \n",
    "    ax = axes[1]\n",
    "    ax.set_xlim(-1, 1)\n",
    "    ax.set_ylim(-1, 1)\n",
    "    ax.set_title('2D posterior distribution')\n",
    "    ax.set_xlabel('$w_{0}$')\n",
    "    ax.set_ylabel('$w_{1}$')\n",
    "    im1 = []\n",
    "    im1 += [ax.pcolormesh(w0, w1, posterior_2D(w0, w1, mn, Sn))]\n",
    "    im1 += [ax.scatter(*w_true, marker='+', c='white', lw=1)]\n",
    "\n",
    "    if n == 0:\n",
    "        artists.append(im1 + im2)\n",
    "        continue\n",
    "    \n",
    "    ax = axes[0]\n",
    "    ax.set_xlim(-1, 1)\n",
    "    ax.set_ylim(-1, 1)\n",
    "    ax.set_title(f'2D likelihood of a sample')\n",
    "    ax.set_xlabel('$w_{0}$')\n",
    "    ax.set_ylabel('$w_{1}$')\n",
    "    im0 = []\n",
    "    im0 += [ax.pcolormesh(w0, w1, likelihood_2D(w0, w1, x[n-1], y[n-1], beta))]\n",
    "    im0 += [ax.scatter(*w_true, marker='+', c='white', lw=1)]\n",
    "    \n",
    "    artists.append(im0 + im1 + im2)\n",
    "    \n",
    "ani = animation.ArtistAnimation(fig, artists, interval=250)\n",
    "ani.save(f'figure-3.7-alpha{alpha}.mp4')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}