{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibration of the pixel position for a Pilatus detector\n",
    "\n",
    "This tutorial summarizes the work done by Frederic Sulzman during his internship at ESRF during the summer 2015 entilted \"Calibration for geometric distortion in multi-\n",
    "modules pixel detectors\".\n",
    "\n",
    "The overall strategy is very similar to \"CCD calibration\" tutorial with some specificities due to the modular nature of the detector.\n",
    "\n",
    "0. Image preprocessing\n",
    "1. Peak picking\n",
    "2. Grid assignment\n",
    "3. Displacement fitting\n",
    "4. Reconstruction of the pixel position\n",
    "5. Saving into a detector definition file\n",
    "\n",
    "Each module being made by lithographic processes, the error within a module will be assumeed to be constant. We will use the name \"displacement of the module\" to describe the rigide movement of the module.\n",
    "\n",
    "This tutorial uses data from the Pilatus3 2M CdTe from the ID15 beam line of the ESRF. \n",
    "They provided not only the intersnip subject but also the couple of images uses to calibrate the detector.\n",
    "\n",
    "This detector contains 48 half-modules, each bound to a single CdTe monocrystal sensor and is designed for high energy X-ray radiation detection. \n",
    "Due to the construction procedure, these half-modules could show a misalignment within the detector\n",
    "plane. \n",
    "While the manufacturer (Dectris) garanties a precision within a pixel (172µm), the miss-alignment of certain modules can be seen while calibrating Debye-Scherrer ring using refereance sample. \n",
    "So the aim of this work is to provide a detector description with a better precision better than the original detector.\n",
    "\n",
    "This work will be performed on the image of a grid available:\n",
    "http://www.silx.org/pub/pyFAI/detector_calibration/Pilatus2MCdTe_ID15_grid_plus_sample_0004.cbf\n",
    "and the scattering of ceria (CeO2) at 72.1keV available here.\n",
    "http://www.silx.org/pub/pyFAI/detector_calibration/Pilatus2MCdTe_ID15_CeO2_72100eV_800mm_0000.cbf\n",
    "\n",
    "It is a good exercise to calibrate all rings of the later image using the *pyFAI-calib2* tool. \n",
    "A calibration close to perfection is needed to visualize the module miss-alignement we aim at correcting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pyFAI verison:  0.18.0\n"
     ]
    }
   ],
   "source": [
    "#many imports which will be used all along the notebook\n",
    "import time\n",
    "start_time = time.time()\n",
    "import os\n",
    "import pyFAI\n",
    "import fabio\n",
    "import glob\n",
    "import numpy\n",
    "from math import sin, cos, sqrt\n",
    "from scipy.ndimage import convolve, binary_dilation\n",
    "from scipy.spatial import distance_matrix\n",
    "from scipy.optimize import minimize\n",
    "from matplotlib.pyplot import subplots\n",
    "from pyFAI.ext.bilinear import Bilinear\n",
    "from pyFAI.ext.watershed import InverseWatershed\n",
    "from silx.resources import ExternalResources\n",
    "\n",
    "print(\"Using pyFAI verison: \", pyFAI.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Nota: Configure here your proxy if you are behind a firewall\n",
    "#os.environ[\"http_proxy\"] = \"http://proxy.comany.com:3128\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/detector_calibration_testdata_kieffer/Pilatus2MCdTe_ID15_CeO2_72100eV_800mm_0000.cbf\n",
      "/tmp/detector_calibration_testdata_kieffer/Pilatus2MCdTe_ID15_grid_plus_sample_0004.cbf\n"
     ]
    }
   ],
   "source": [
    "downloader = ExternalResources(\"detector_calibration\", \"http://www.silx.org/pub/pyFAI/detector_calibration/\")\n",
    "ring_file = downloader.getfile(\"Pilatus2MCdTe_ID15_CeO2_72100eV_800mm_0000.cbf\")\n",
    "print(ring_file)\n",
    "grid_file = downloader.getfile(\"Pilatus2MCdTe_ID15_grid_plus_sample_0004.cbf\")\n",
    "print(grid_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'rings')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rings = fabio.open(ring_file).data\n",
    "img = fabio.open(grid_file).data\n",
    "fig,ax = subplots(1,2, figsize=(10,5))\n",
    "ax[0].imshow(img.clip(0,1000), interpolation=\"bilinear\")\n",
    "ax[0].set_title(\"grid\")\n",
    "ax[1].imshow(numpy.arcsinh(rings), interpolation=\"bilinear\")\n",
    "ax[1].set_title(\"rings\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Image processing\n",
    "\n",
    "There are 3 pre-processing steps which are needed.\n",
    "\n",
    "1. Define for each module a unique identifier which will be used later on during the fitting procedure\n",
    "2. Define the proper mask: each module is the assembly of 4x2 sub-modules and there are (3) interpolated pixels between each sub-module, such \"unreliable pixels should be masked out as well\n",
    "3. Correct the grid image by the smoothed image to have a constant background.\n",
    "4. Convolve the raw image with a typical hole shape to allow a precise spotting of the hole center.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Detector Pilatus CdTe 2M\t PixelSize= 1.720e-04, 1.720e-04 m\n"
     ]
    }
   ],
   "source": [
    "# This is the default detector as definied in pyFAI according to the specification provided by Dectris:\n",
    "pilatus = pyFAI.detector_factory(\"Pilatus_2m_CdTe\")\n",
    "print(pilatus)\n",
    "\n",
    "mask1 = pilatus.mask\n",
    "module_size = pilatus.MODULE_SIZE\n",
    "module_gap = pilatus.MODULE_GAP\n",
    "submodule_size = (96,60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#1 + 2 Calculation of the module_id and the interpolated-mask:\n",
    "mid = numpy.zeros(pilatus.shape, dtype=int)\n",
    "mask2 = numpy.zeros(pilatus.shape, dtype=int)\n",
    "idx = 1\n",
    "for i in range(8):\n",
    "    y_start = i*(module_gap[0] + module_size[0])\n",
    "    y_stop = y_start + module_size[0]\n",
    "    for j in range(3):\n",
    "        x_start = j*(module_gap[1] + module_size[1])\n",
    "        x_stop = x_start + module_size[1]\n",
    "        mid[y_start:y_stop,x_start: x_start+module_size[1]//2] = idx\n",
    "        idx+=1\n",
    "        mid[y_start:y_stop,x_start+module_size[1]//2: x_stop] = idx\n",
    "        idx+=1\n",
    "        mask2[y_start+submodule_size[0]-1:y_start+submodule_size[0]+2,\n",
    "              x_start:x_stop] = 1\n",
    "        for k in range(1,8):\n",
    "            mask2[y_start:y_stop,\n",
    "              x_start+k*(submodule_size[1]+1)-1:x_start+k*(submodule_size[1]+1)+2] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Extra masking\n",
    "mask0 = img<0\n",
    "#Those pixel are miss-behaving... they are the hot pixels next to the beam-stop\n",
    "mask0[915:922,793:800] = 1\n",
    "mask0[817:820,747:750] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Nan masked image')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,ax = subplots(1,3, figsize=(10,4))\n",
    "ax[0].imshow(mid, interpolation=\"bilinear\")\n",
    "ax[0].set_title(\"Module Id\")\n",
    "\n",
    "ax[1].imshow(mask2+mask1+mask0, interpolation=\"bilinear\")\n",
    "ax[1].set_title(\"Combined mask\")\n",
    "\n",
    "nimg = img.astype(float)\n",
    "nimg[numpy.where(mask0+mask1+mask2)] = numpy.nan\n",
    "\n",
    "\n",
    "ax[2].imshow(nimg)#, interpolation=\"bilinear\")\n",
    "ax[2].set_title(\"Nan masked image\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The Nan-masked image contains now only valid values (and Nan elsewhere). We will make a large median filter to \n",
    "# build up a smooth image without gaps.\n",
    "#\n",
    "# This function is backported from future version of numpy ... it allows to expose a winbowed view \n",
    "# to perform the nanmedian-filter\n",
    "from numpy.lib.stride_tricks import as_strided\n",
    "def sliding_window_view(x, shape, subok=False, readonly=True):\n",
    "    \"\"\"\n",
    "    Creates sliding window views of the N dimensional array with the given window\n",
    "    shape. Window slides across each dimension of `x` and extract subsets of `x`\n",
    "    at any window position.\n",
    "    Parameters\n",
    "    ----------\n",
    "    x : array_like\n",
    "        Array to create sliding window views of.\n",
    "    shape : sequence of int\n",
    "        The shape of the window. Must have same length as the number of input array dimensions.\n",
    "    subok : bool, optional\n",
    "        If True, then sub-classes will be passed-through, otherwise the returned\n",
    "        array will be forced to be a base-class array (default).\n",
    "    readonly : bool, optional\n",
    "        If set to True, the returned array will always be readonly view.\n",
    "        Otherwise it will return writable copies(see Notes).\n",
    "    Returns\n",
    "    -------\n",
    "    view : ndarray\n",
    "        Sliding window views (or copies) of `x`. view.shape = x.shape - shape + 1\n",
    "    See also\n",
    "    --------\n",
    "    as_strided: Create a view into the array with the given shape and strides.\n",
    "    broadcast_to: broadcast an array to a given shape.\n",
    "    Notes\n",
    "    -----\n",
    "    ``sliding_window_view`` create sliding window views of the N dimensions array\n",
    "    with the given window shape and its implementation based on ``as_strided``.\n",
    "    Please note that if readonly set to True, views are returned, not copies\n",
    "    of array. In this case, write operations could be unpredictable, so the returned\n",
    "    views are readonly. Bear in mind that returned copies (readonly=False) will\n",
    "    take more memory than the original array, due to overlapping windows.\n",
    "    For some cases there may be more efficient approaches to calculate transformations\n",
    "    across multi-dimensional arrays, for instance `scipy.signal.fftconvolve`, where combining\n",
    "    the iterating step with the calculation itself while storing partial results can result\n",
    "    in significant speedups.\n",
    "    Examples\n",
    "    --------\n",
    "    >>> i, j = np.ogrid[:3,:4]\n",
    "    >>> x = 10*i + j\n",
    "    >>> shape = (2,2)\n",
    "    >>> np.lib.stride_tricks.sliding_window_view(x, shape)\n",
    "    array([[[[ 0,  1],\n",
    "             [10, 11]],\n",
    "            [[ 1,  2],\n",
    "             [11, 12]],\n",
    "            [[ 2,  3],\n",
    "             [12, 13]]],\n",
    "           [[[10, 11],\n",
    "             [20, 21]],\n",
    "            [[11, 12],\n",
    "             [21, 22]],\n",
    "            [[12, 13],\n",
    "             [22, 23]]]])\n",
    "    \"\"\"\n",
    "    np = numpy\n",
    "    # first convert input to array, possibly keeping subclass\n",
    "    x = np.array(x, copy=False, subok=subok)\n",
    "\n",
    "    try:\n",
    "        shape = np.array(shape, np.int)\n",
    "    except:\n",
    "        raise TypeError('`shape` must be a sequence of integer')\n",
    "    else:\n",
    "        if shape.ndim > 1:\n",
    "            raise ValueError('`shape` must be one-dimensional sequence of integer')\n",
    "        if len(x.shape) != len(shape):\n",
    "            raise ValueError(\"`shape` length doesn't match with input array dimensions\")\n",
    "        if np.any(shape <= 0):\n",
    "            raise ValueError('`shape` cannot contain non-positive value')\n",
    "\n",
    "    o = np.array(x.shape) - shape  + 1 # output shape\n",
    "    if np.any(o <= 0):\n",
    "        raise ValueError('window shape cannot larger than input array shape')\n",
    "\n",
    "    if type(readonly) != bool:\n",
    "        raise TypeError('readonly must be a boolean')\n",
    "\n",
    "    strides = x.strides\n",
    "    view_strides = strides\n",
    "\n",
    "    view_shape = np.concatenate((o, shape), axis=0)\n",
    "    view_strides = np.concatenate((view_strides, strides), axis=0)\n",
    "    view = as_strided(x, view_shape, view_strides, subok=subok, writeable=not readonly)\n",
    "\n",
    "    if not readonly:\n",
    "        return view.copy()\n",
    "    else:\n",
    "        return view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1679, 1475)\n",
      "(1697, 1485)\n",
      "(1679, 1475)\n"
     ]
    },
    {
     "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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 24.9 s, sys: 4.06 s, total: 29 s\n",
      "Wall time: 29 s\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "#Calculate a background image using a large median filter ... takes a while\n",
    "shape = (19,11)\n",
    "print(nimg.shape)\n",
    "padded = numpy.pad(nimg, tuple((i//2,) for i in shape), mode=\"edge\")\n",
    "print(padded.shape)\n",
    "background = numpy.nanmedian(sliding_window_view(padded,shape), axis = (-2,-1))\n",
    "print(background.shape)\n",
    "fig,ax = subplots()\n",
    "ax.imshow(background)\n",
    "ax.set_title(\"Background image\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 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=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0 17.728813559322035\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram of intensities in normalized image')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,ax = subplots(1,2, figsize=(9,5))\n",
    "\n",
    "normalized = (nimg/background)\n",
    "\n",
    "low = numpy.nanmin(normalized)\n",
    "high = numpy.nanmax(normalized)\n",
    "print(low, high)\n",
    "normalized[numpy.isnan(normalized)] = 0\n",
    "normalized /= high\n",
    "\n",
    "ax[0].imshow(normalized)\n",
    "ax[0].set_title(\"Normalized image\")\n",
    "\n",
    "ax[1].hist(normalized.ravel(), 100, range=(0,1))\n",
    "ax[1].set_title(\"Histogram of intensities in normalized image\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For a precise measurement of the peak position, one trick is to convolve the image with a pattern which looks like a hole of the grid.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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,iVBORw0KGgoAAAANSUhEUgAAAwAAAAJACAYAAAA6rgFWAAAgAElEQVR4nOydeZRU1bX/K8vOU1eSt96w3nuat9brBNFoNDEmosEkEpVoNIkZFMUMJkYTEzWODY2IIigoIiAIQjMIMimTIDI0My3zPMs8y9CMzdgNDX1+f+Rn3e/dfb5Vu2+VVYW1v2vVH7KOp2/dOnVrf87Z+7tjzmQymUwmk8lkMuWNYtm+AJPJZDKZTCaTyZQ5GQCYTCaTyWQymUx5JAMAk8lkMplMJpMpj2QAYDKZTCaTyWQy5ZEMAEwmk8lkMplMpjySAYDJZDKZTCaTyZRHMgAwmUwmk8lkMpnySAYAJpPJZDKZTCZTHskAwGQymUwmk8lkyiMZAJhMJpPJZDKZTHkkAwCTyWQymUwmkymPZABgMplMJpPJZDLlkQwATCaTyWQymUymPJIBgMlkMplMJpPJlEcyADCZTCaTyWQymfJIBgAmk8lkMplMJlMeyQDAZDKZTCaTyWTKIxkAmEwmk8lkMplMeSQDAJPJZDKZTCaTKY9kAGAymUwmk8lkMuWRDABMJpPJZDKZTKY8kgGAyWQymUwmk8mURzIAMJlMJpPJZDKZ8kgGACaTyWQymUwmUx7JAMBkMplMJpPJZMojGQCYTCaTyWQymUx5JAMAk8lkMplMJpMpj2QAYDKZTCaTyWQy5ZEMAEwmk8lkMplMpjySAYDJZDKZTCaTyZRHMgAwmUwmk8lkMpnySAYAJpPJZDKZTCZTHskAwGQymUwmk8lkyiMZAJhMJpPJZDKZTHkkAwCTyWQymUwmkymPZABgMplMJpPJZDLlkQwATCaTyWQymUymPJIBgMlkMplMJpPJlEcyADCZTCaTyWQymfJIBgAmk8lkMplMJlMeyQDAZDKZTCaTyWTKIxkAmEwmk8lkMplMeSQDAJPJZDKZTCaTKY9kAGAymUwmk8lkMuWRDABMJpPJZDKZTKY8kgGAyWQymUwmk8mURzIAMJlMJpPJZDKZ8kgGACaTyWQymUwmUx7JAMBkMplMJpPJZMojGQCYTCaTyWQymUx5JAMAk8lkMplMJpMpj2QAYDKZTCaTyWQy5ZEMAEwmk8lkMplMpjySAYDJZDKZTCaTyZRHMgAwmUwmk8lkMpnySAYAJpPJZDKZTCZTHskAwGQymUwmk8lkyiMZAJhMJpPJZDKZTHkkAwCTyWQymUwmkymPZABgMplMJpPJZDLlkQwATCaTyWQymUymPJIBgMlkMplMJpPJlEcyADCZTCaTyWQymfJIBgAmk8lkMplMJlMeyQDAZDKZTCaTyWTKIxkAmEwmk8lkMplMeSQDAJPJZDKZTCaTKY+UdwBQVVXlmjdv7i6++GJ3wQUXuOuuu85Nnjw56f/XunVrF4vFar3OP//8yNdy+PBhN2bMGLdkyRK3evVqe9nLXvayl73sZS971eG1ZMkSN2bMGHf48OHI8Vg+Ku8AoGnTpq6goMAVFRW5kpIS17BhQ1dQUOBmzZqV8P/7FAB69uzpBg0aFH8NHTo08rWMGTPGCxX2spe97GUve9nLXvbSv8aMGRM5HstH5RUALFiwwMViMdexY8f4v1VWVrpLLrnENWzYMOH/+ykA7N+/P23Xs2TJkviizTZB28te9rKXvexlL3uda69PN1OXLFmStvgsH5RXANCsWTN33nnnuSNHjoT+vX379i4Wi7kdO3bQ//dTANi3b587cuSIq6mpSfl6Vq9e7WKxmFu9enXKc5lMJpPJZDLlmyyWiqa8AoDGjRu7K664ota/T5061cViMTd27Fj6/34KAF/+8pddLBZzX/rSl9zvfvc7t3fv3sjXY4vWZDKZTCaTKbosloqmvAKAK6+80t188821/n3NmjUuFou5Xr160f/3jTfecI899pgbMmSIGzlypHviiSdcQUGBu/TSS2udKPhUXl5Oj61s0ZpMJpPJZDLVXQYA0ZRXAFCvXj13++231/r3zZs3u1gs5rp06VKn+YYMGeJisZh75ZVXko5lLkK2aE0mk8lkMpmiyQAgmvIKAFI5AWC66KKL3C233JJ0nJ0AmEwmk8lkMqVXBgDRlFcAkEoNAFODBg3cNddcE+l6bNGaTCaTyWQyRZfFUtGUVwBQVFTkdQFq165dUhcgn2pqatx//dd/uVtvvTXS9eTqoq08fcY16TnX3dd7njt95my2L8dkMplMJpPJq1yNpXJdeQUA8+fPr9UHoKqqytWvX99df/318X/bvn27W7t2bej/3bdvX635evTo4WKxmOvcuXOk68nVRdvno82usHicKywe54YtrBsUmUwmk8lkMmVKuRpL5bryCgCcc65JkyauoKDANWvWzJWUlLgbbrjBFRQUuLKysviYRo0auVgsfGsuvPBC96c//cl16tTJ9ejRw913333uC1/4gvvOd77jTpw4EelacnXRthv/cRwAes7clO3LyXlVnj7j+s7a4hZvO5jtSzGZTCaTKa+Uq7FUrivvAKCystIVFRW5iy66yJ1//vmuQYMGrrS0NDTGBwAPPfSQ++Y3v+m+8pWvuC9+8Yuufv36rri42B09ejTyteTqojUAqJvwfp09m3qDOJPJZDKZTDrlaiyV68o7AMgl5eqifXncmnhA28sAIKk+vVeFxeNyqmZi6sd73Z3dZ7vp68qzfSkmk8lkMn0mytVYKtdlAJBF5eqifenDAABKyjgArN971L09e4s7Unk6g1eXXIu3HXStP1jtdh6Klpr1qY5VVbsuU9a7svW16z9QCABV1WdS+pvpFF6XyWQymUyfR+VqLJXrMgDIonJ10SIA9C7bTMd9OuaxoUszeHXJ9el13dq5LPngBOo6dUN8rpOneGCPgXbl6cwAwISVu1336RvdqWp+4mAAYDKZTKbPu3I1lsp1GQBkUbm6aNvWEQAyFWDW1NS4xdsOukPHTyUcl67ruqXTzPg8y3ccVv29E6eqU/qbGu2pqIz/vf6zt6iuy2QymUymz6NyNZbKdRkAZFG5umjbjA0AoM9HuQMAIxbvdIXF49yNr01POE5zXf1nb3HXt5vqpq3dS8c8OmRJfJ535m5V/b2jSdKhkqUIVZw47YpHrnDDFnH71dkb98f/3j295qquy2QymUymz6NyNZbKdRkAZFG5umhfHLs6JwGg3rPjVYG25ro0Y7pMWR8f8/i7PM0J56o4ya+ry5T1rn7L8W54guD+iXeXJk0nmrJmb3zMH99eoLquXNLZszVu1ScVrjqHCqZNJpPJdG4qV2OpXJcBQBaVq4s2VwGgYfup8b+3ZtcROi5dAPDGlKAG4OGBi1VzHT7B05M0f/PyVhPjY45V+dOJxi7fFR/zt0G668olvVa61hUWj3MtRq3I9qWYTCaT6RxXrsZSuS4DgCwqVxdt6w8CAOg7K3dyzO/uOSf+96as8afunDlb85mcAGgB4CCpT6ip0V3X11sEY44TABi6YHt8zFPvLVNd15kc6k+Qq2BiMplMpnNPuRpL5boMALKoXF20CAD9cggAHnpnUfzvjVi80zvm5KkznwkA/HXgItVc+49VecdUnDhd5+tiJwD9Zm2Jj3l62HLVXMlqEzIpAwCTyWQypUu5GkvlugwAsqhcXbQIAG9nyGXmg+W73B/6LXDr9vDOys8MX540NenwiVN1DrRZLnrnyXUHgPKjld4x6/YcrfN1saC9z0eb42MSWbBqU5MyLQMAk8lkMqVLuRpL5boMALKoXF20L4xZlfEUoE/n+d5Lk+kYBJOOpeu8Y/YeqaxzoM2sOzsBAPzlHR0A7D3iB4Cy9fviY65qXaqaizVYQwDQgokBgMlkMpk+j8rVWCrXZQCQReXqon0eACBRJ+DPAgASzYUA8Nzold4xOw6eqDMAsOAYAeAhJQDsrjjpHTNs0Y74mFs6zVTNxRyFepcFAMBcgM6KWohkvRMyqXQDwL6jVa6mJndqHEwmn/ZUVLoVOw/bWjWZ0qxcjaVyXQYAWVSuLtpWowMA6DFjIx2XTQBoPsLvILOxvO6pNuVk177TpHXxMQ8O0AHAJ4f9ANBr5qb4mCZK7/6KE34AKCkL5rq3xD9XVXW4FoIVJ2dD6Vw3/Wf/sx6izdg1abgyk+mzUeXpM3Eb47L1+7J9OSbT50q5GkvlugwAsqhcXbQIAN2mbqDj0hXIaR1yMDWp2Qh/8euaXUfqDAA7Dp7wjgkDwMKU5nprRhC0Ny2Zp5qL7dqHYKKnHwCOVVWH5jpAipOzIbyuVHdDLZ3IdC5o9a6K+Dr96RsfpTxfTU0N7RNiMuWbcjWWynUZAGRRubponxu9Mv5j1XnyejouXcGX3K1mel4BAKs+qVDNhWM2lh/zjnkdAODP/XUAsP2AHwB6zNhYZwBgu/Y9FacJh46Hi6GZO1GmVX3mbOi6TlWn1gzMAMB0Lmhj+bH4Or3p9RkpzVVTU+Oa9Jzrrnyh1G3Yy00TtNp56ITrOnWD23bgeMpzmUzZUK7GUrkuA4AsKlcXbcv3AwBgxbbOpS/4OlKps8jEk4mi4ekDANZUrGNpAAB/Unbc3brf/yMaBQDYrj2eJjAA2H+sKjTXvqO5AQCVp8Owl8ietHjkCveDV6e5Tfv8gOacbg1WnznrXpmwNqGlbbq1u+Kke3ncGrdk+6GM/U1T7gprk254ZVpKc23dfzw+151vzkr52j5tsHhNW27AYDLlsnI1lsp1GQBkUdlatBUnTydMvXgWAOCVCWu9Y7RpOxqVH9U59+DJRDoBYNmOw94xCACs2FbOtZkEq92n1x0A2K49wsQ9BAD2HQ0DALMnzbRknwb2HhEKf9l9Np1P81kPnr8tPmbVJxUpvweNbutSZicTprh2HgoAIJHTmUZY53RziqcJztkpmunclwFANBkAZFHZWLQjF+90hcXjXPFIfxGtc861GBUE2i+P8xdXSpeZVKR17sGTiWfSCAALthz0jnmtdG18zP39dACwsdx/JI8AcF9vHQCwXXucK9cAoHT1Htdp0jp38pQ/P1kCwC5SNI3Xnyhg0nzWT723LD6GNZBLtyyoMqHwGXfVC9wGWKMNewMASOQo5pxzJ05VJ+0CbmvVdK7LACCaDACyqGwsWs3DHgGAuaucSSMAaJ178GSCdcBdubPuADBrw37vGASAPygBYD3JyX1z2oY6nwCwoB3nYi5A8lSFOR1pteqTCvf4u0vd0gQpLUdh1/61Uv/J0YlT4eJk5pq06/DJ+Jjr2k2hf7Ou63nQvG10XDplQZUJhQBwacsJdFxNTY1bubMiYcreegCAxgkAYGP5UXd5q4nujq4fubMJIMDWqulclwFANBkAZFG5CwAr4mNeHOu/ttOimDMVaXftMZBjALBi5+E6A8DUj/d6x3SYGADA7/vOV821do+/niASAJCgvdvU5HOVi4ZorEGZVpp7uv1A8jzn48KdaOchf9H0FshzTpQzjXOxIAftY1kH6XTLgioTatuB46o1MWNduSss/mc+/mnSoXztnsDp7CedOQD8svvs+Dh2Mumcbq2Wrd/nbutS5sYs+4SOMZmyJQOAaDIAyKJyFQCKRwYA0PoD/7Wdqk4fACzdfqjO1/XUsGXeMVEAoHT1Hu+YVyMAACsoxqBdmwLEgvauEQBgT8VnDwB4kvODV3UAwGxTMcj5YQcdADBbxFcmBJ9j9+m8r4VW2w+ccBNX7XHVJECT1/V51ZyN+12LUSvoZ5hPSmZni4W7idbEDa9Mi49hjmIf7w6+G7d2LqNzff//F/cmmss53VpN53o+UnnaDVu0I+VNCa1Onjrj7uk11z04YFHCkxDTuSsDgGgyAMiizmUAkG4uqWiJEgCaj0gOAMt3hAGA/TDjmImrkgPA7/roAIAVmXaNAAAsaH9jSvK59goAYB2KtdJ8Pnjvb3xtuneM7E/AApNlMNePO85QXRfrnNxlStDR+fVJ3NVKIyx+T+QqlA8A8On7S9XWMpe1/1gVtQn+VFv2H3c/7DCN1iV9OkazJhq8PCUpHGOvk9u6cAC4qnVpfFwii89MA8AD/Re6wuJx7vp2U1OeSyPcfBm/cndG/qYpszIAiCYDgCwqVwEAA20GALKYMxVpAaDZiOUBALznB4BlAgDYjo8GAHDn+Ld9dEH7yp1+ANAE7XIuFrRjQKsFAFZsq5Xm85mzcX/SoF0CAAtM5m0+EB+TqNAR52I1E9g3gRW1a4UnGJc8O151XZ9Xpes91tTUuKLhy90f315Ai8c/Cy3aetBNXLWHbhJUnj7jrmk72RUWj0to5/rrHkGqDWvet3nfMdX9+k6bSfExDDy0TcW+1mJc0rmcyzwAZPq7gbVjAzNUA2TKrAwAoskAIIvKVQDAQPuFMau8Y2QxZypavE0HAEXD6w4AzAEjDAD+XSEEAG3QvpxYikYBABa0d56cHAD2VIQBgBXbaqX5fCav2Rsfw3aFj4qeD6xvwsz1++Jj2C6ntKJl9QR9PtocH9P2w9QAAIs5r305teLkc13peo+zARw7pXhCo9XuiqDIfPq6cu8Y3Ji4M4EV7fdeCnbtGYRuUgLAlS8Eu/ard/k3E7Bm6vYEAIB/b90efw2A1s0Nx5xrzfvQPnrg3K0Z+ZumzMoAIJoMALKocxkA5E5uKtICwDMAAE8SAJD1BCxPG8dMIMfC7Sd8HB+jLdxlLjmaXXs5FwvaOwEAsOvCACdTADB66SfxMWzXXjZ920IAoHT1nviYO7r6gxzpRMVgolcaTwAQMBPlXxsA6DVmWbBuHhu6NE1Xp/+bjw5Z4h2D3XsbkZQ258IAwNx7cK5E9+vS5ybEx7BTBwQA9t1wLvz5MJjQnuTimFSbCqbzu3H4xCk3YM7WhClO2EF+wJytKf9NU+7JACCa8g4AqqqqXPPmzd3FF1/sLrjgAnfddde5yZPr3pilcePGLhaLuUcffTTyteQqAOBO+/MEAORObipavO2gaq6nhwXX9cS7/kBBphMxJw0VAIwPAIDZbcq5Fm/z/2jjrr02nYjtaHeaFDQo0wIAm0srzefz3sLt8THsBEACAGuc9sHyXfExvyDdTiUAMJjAvgntx3+c+I0mETYVYz0YnDMAqIvGwmf9yGB/MJ5uDZkfrNXmI/w9UbBw9zttJtG5NCcA6N2f6H5h2s7cTQe8Y9Do4GfddADATiYPHT9VZwBIteg7nd+N3/ed7wqLE1urogvY27Mz1w3clDkZAERT3gFA06ZNXUFBgSsqKnIlJSWuYcOGrqCgwM2apW+pPmrUKPelL33pcwsAuNPearQfACpOpg8AFm3VAcBTw4KGTloAYMfVOIYVhiEAaIO9RVv9TcU6KdJ2ZEoL+6HFDsUMTNBHP9UfbW3Ph6ELgqCKuQDJdcNyk0ct2Rkfw9IvqoUVLYMJLMBmna21wu8Gq49xzgCgLhq/cnd8nocHLk7T1SUWpoUxq2Nt4S4CAKvbWa8EgEtbBicAM0hqEhbb/7wb/93Cv8c2JuRGgWYudtKmVTq/G5q5XhwbAEDfBIX7pnNXBgDRlFcAsGDBAheLxVzHjh3j/1ZZWekuueQS17BhQ9UclZWV7mtf+5pr27btOQ8ArPgNg5znRq/0jqk4kQUAgI6ujxMAkOlEVdX+okINALQDAGiiBADWVVgDANJalTnkYIOyTACAtt4Dd1X1AODPTR6+aEd8DDsBkL0oNhEAwHufKgA8CWuwXYLTBAMAvSauCgDgL+8sStPVJRam5HUs9dcdyMJdZiiAAMC+Z+v26ADgKqgBYPbEmIbGvhvOhT+f+Zv9pwlayNF8z7TKNAC0GbsmPiZTfUBMmZUBQDTlFQA0a9bMnXfeee7IkbBXe/v27V0sFnM7duxIOkebNm3c//3f/7mTJ0+e8wDA8uMx1YYBgDw6TuaDnUgLBQCwuZ5UAUB4LuYNj2PGrVAAQE8dAMwjP7SatB0ZaLO8VmxQxk4mPhEAkMgHPJlk2g4TpsdQABDguIF0TsZ0IpbmIIGJnSYgMLWfkFoKEK7BRPUEBgB6Yb3HgwMWpunqEgu/2z1m+HtDyMJdlk6IAMB2x7GvRaL79d3/7zpUWDzOfbB8l3cM1jndmQAA6j07Pj5uzkZ/t3PsKaAFgERNxTTKNAC0/TAAgN5lBgCfRxkARFNeAUDjxo3dFVdcUevfp06d6mKxmBs7dmzC/3/79u3uwgsvdO+++65zzp3zAMB2xzHVpuX7fgA4KACAue1oJAGA7bQ98e7S+Jh/kGJBCQDMVhDHfLjC/0P78rjgh+Out+bQ68e55mzy/9C+Pil52o7cHWfBxKsKANh56ERorkRFcsmkTfcaNC8AANa86/CJ8LpZTwAA04mY00ltAPDPhcXcqRYB4xp8KYGjkAGAXlPAPeqB/pkBAE13aFm4y9IJv/fSZFiDfgjVBtoNoXnX8EX+DSmtOxGmE5Wt3+cdo23CiGOYo5BWmQYAfI6XlG1K+W+ack8GANGUVwBw5ZVXuptvvrnWv69Zs8bFYjHXq1evhP//3Xff7W644Yb4f9cFAMrLy93q1atDrzFjxmQVAFhwjADwLAGA/ceqQnMl6oqaTAu2HFTN9bgCAGQ60YlT1d5xGgB4CXaOfqMEgNlkp02Tt39A3FNW1Ir2pCw1SQJAKnm72nSvgXO3xsf8qIPfNUUCAAsmECaYDWhVddjBhJ0m4OeYqg0orkE2l6zl+LxK8x43lh91P+82y705bQMdM21tAAB/fHvBZ3GptfQCOMNwAAin7bANEwQAtp6xeVei+/XDDkEn4KELtnvHYJrjr3pwALi81cT4uGlr93rHzN10QHVdOIZ1O9cq0wCAtVw9ZxoAfB5lABBNeQUA9erVc7fffnutf9+8ebOLxWKuS5cu9P+dPn26+8IXvuAWLgx2qOoCAK1bt3axWMz7yhYAHK30d07FXPsWo/wAUH407DOfijf0/M3hHyF21P6PoUHwxewC5WnC8arkADCWHLVj4Phr8kMrgz2204YAwHbty0XzLlbUijvaLDUJ/eozBQDvKABApo6t3eMPJnCun3T2W4rKbtTsNAF3e1nBp1YIAG3G+gFAequnkh6Xy9KsiVs6zUw6Zvq68viY3/flHbfTqVajAwBgu8LSuYelEyIAaLz7tQAwZD4DgOAZx55LzoXrCSaRegK891oAYN3Otco0AOCGCUv3Mp3bMgCIprwCgKgnANXV1e6qq65y999/f+jfz/UTgIoTfgB4UgMAIlhlP44aSQBgO22PAQAw724JAMcUAMBybTF3lO20SYcc5tyBeehs1146crBiu/aK2gQJAOw0QSO5a880YE4QtN9IfNMlAHy82w8A/WdviY9hPQUkALDdVwz2Ejn3aIQQymBCuhOxlLZzWVEaSLGTvTJo+va7PpkBgJbQHZYFhdK5RwMAK3b67TajAMDg+f6utXjKmehk8tsvBl2FmdEBFmBrP0f2HrXS/L2amho39eO91FWtLnNhzVT36QYAn0cZAERTXgFA1BqAfv36uS9+8Ytuzpw5buvWrfFXLBZz999/v9u6das7caLuRZbZrgE4SNrWhwHA75EtO82mAgDzBACwuR4dsiQpAMh0InbKUVcA+CXJtZVONNPX+gEAf4QYAEjnHpZPjAWMd/f0BwASANhpgkZar/C3IWhnjZNk7QjbMe07K5jrZtJTQDYxYqcJLUYFwR7ra6EVQiiDCVmbwALfQ8dPue7TN9J7UBdVnDjtuk/fmHJwppVc90w4hsH4rA1BJ+BETfLSKVwTLD1JOvew5xIW7rLmXSt3pg8A8BmXqDZJU1CMDdESeenjtbNmh1pp7gP+JiRyMNPMhZsv3abyVDTTuSsDgGjKKwAoKiryugC1a9cuoQtQovSdT1+jR4+u8/VkGwBY0xosdCwe6QcAuVvNcu01kgDAahMeAQB4RAkARxQAMGbZJ94xaB/Hiu1kHvrUj/25tli4y3btawOAf0cbi9oYAGw/EAaAVKz7tADQD4L2H3ec4R0j6xxYOkHvssCnnTUV0wIAdrZmrlZaIYSyLtnyZIKdaOFcqQobzaVSj6OVfI9Ml0FnW/Y9m7MxAIBE/TbSqRajVsT/Zpcp671jpHMPey5hoL2Q7Fhj8y4tAAya5wcAPDFl33/nnLv25cCd6P2lO71j0G738lYT6Vx47Yu3Jd6VTybNfcDPh90H7VxowNDVAOBzKQOAaMorAJg/f36tPgBVVVWufv367vrrr4//2/bt293atYFf+Nq1a93o0aNrvWKxmLvjjjvc6NGj3e7d/iPWRMr0opX56nsq/ADwuAIApM0k293TSBaisbz9vw9enBQAZDpRxcnoAIANZJjdngxCJ6+JDgDynrKiVjyZYDuAEgDYaYJGcteeqW8aAaDXzE3xMSwFSNqmsnQiTVG7Vhi0s9MEuSY0VrSp1glc8XxQ8Mm6vqZT2t4Q32pdmnQcbgAksttNp7DbeadJ/j4A0rlHAwCsey8279ICwEAS+Grv1/fBUWgYcRQaBgBwxfM6AGCQo5XmPmCdU6K0Hc1caMHMYE+rU9Vn3QP9F7q/DlyUkvOdKb0yAIimvAIA55xr0qSJKygocM2aNXMlJSXuhhtucAUFBa6sLHAaadSokYvFkt+ac80GVObtfnLY37USAaD5CD8ASJcZlmqj0ZxN+0NzMZj42yAAgMF+AJCnCYdP+NOc6goArOHO8apwIMSa92AhGtu1k/eUFbXiyQTLAd524LgAgOjWfTJoZ8LuqjcRAJDuUSt3+gGgx4yN8TGsCFjee+ZOguuZpbRphadQrEu2DI41TlSpfH+cc+7n3WbF52KOL+nUUWVvCNyFZuNk3U4mhKecHSb6m8NJ5x72OSIAzNrgdwFbFgUA5m71jsENk0QnJj94NbmjUBQAYL1OtNLch+7Tg+9/ot4dmrnwdKzz5NQAAGuT2KmKKfMyAIimvAOAyspKV1RU5C666CJ3/vnnuwYNGrjS0tLQmM8rAMiCVZZbiYWOzUYs946ROeZsp10jCQAsbefhgXUHgEOkzgHHjF7qBwB0j7RYJWMAACAASURBVPl5Nz8AyEBo4ir/SRDuaLFdewkArKgVwUQLAOw0QSMtAGjSdiQAsJz1N6dtiI9hNqDHBACwXHrctWfrWatHBgdzsXQieV0suMdGTan0aXDOuaYl8+JzMaBNp7TOUBoAkL07MiEEORZgrt4VzttnJ5MIAMwEQOu3rwEAfF4yS2HnnLvxtelJ5xq2sO4AwJqKaaW5D9hUMBG0a+Z6Y0rwLGGnPVph/VUvsxTNGRkARFPeAUAuKdOLVrqTMGcYLHQsGu4PmGSKCdtp1whzgBPBxF8HLoqP+fvgxd4xMp2IFTrXFQBYN1rZJIu5baBzDwMACVUspx2vi9kAbt2fPgCQQTtTSVmQtsMAYN/R8FwsXaXr1OBH+6ekEZiEL5ZOhMHeM2Q9a4UAwJrkyc7JbD1jB1lWPKrVQ+8E3w0W7KVT2rQwdKJh45Yog+N06i9wv1hDN+ncw04mrwEAYDVA6N2vBYB3GADA85J1FXfOuR93nBEfN2COfy7suK0FAHbKoZXmPmBxMkv31M6Fz5KOpQYAn0cZAESTAUAWlelFK507WF447pgyAJABJttp10gCAIMJ/NH+2yA/AMjThAPHqrzjcAw7ysVA+46u/iBUWmSypmIIAGzXXgIAy2nXAMAW8fmwdCKNtACAefsMAGT/COYogsf27N6rAQCC9qeGLUv8ZpMI61CYRa7cHWfr+SedA498Vjvi3D8D0V4zN9GTMefCvTsyYXUoQY7VMHyj1YSkaycbAPBA/4Xxv8fsXKMAAEsB1J5yIACwoF3rmoQA0H/2Fu+YdxfUHQBmkl4nWmnuwwfLd6UNAPA08bVSf7qXc//czJm/+UDC3H4DgNyUAUA0GQBkUZletNKekAWFjyp2TDfvO6YKtDWaLQCAwcRDEQBgvwIARi3xAwB2C72d7ELLnVDWVAx/OFjQLgGA5bTjdbH+BBIAWDqRRjLYY+oJAMCsOyUAsJ1vLNxjACB32lk9AQLAk++lBgBYh8JSE6RrEvtu3FsyNz7mvYX+HG3nnOram48IXFNemcCDHI2qz5x109eVU5cw55zbK/qAsF4Ht7/xUdK1o90dT6d+33d+/O+xYm5p3clSuRAA2Amg7FDOhADAgvaPNgR9E37bRwcAb6cRAJjVsVaa+5DOEwCsJ3iV1Hs459yd3We7wmLeGdo5A4BclQFANBkAZFGZXrTSspLtMGPKxNPD/ACwSQDAvqPRAQB3tBIFTA8OCADg4YEEAARMsOuqKwCwNBS5O84AAK07GQDItCqW0/68AgAkoLF0Io1k0M6EhbvMuUc2kFu8zQ8A6N3N4EumX7F6Aty1f/xdfwdprRAAmEOWhEK2BvG6EnUo1dx7tDpN1Oxsd8VJ1/L9lbRjtXNBysRVrUvpGGlZy6xHsQnbE+TeZ6MGAOGLpXJJ6052AnONwm9fW+isAQBt47RGUAPAAGCoEgC+1iK4dpbmpFWmAQCfS6kWFBsA5KYMAKLJACCLyvSild7dqaRMbCwPN8lJtFuYTBIA2K79gwOCY3sGAPI0gV0Xjhm52A8AGGizQlQZHLMA4CVFV2FZuMs+HwyqWIMyCQAM9jTSAgDutOkBwG8piK5JFABEqg2rJ8Cg/bGhqQEAFqIzhywJheVH/GsQ03baj/cHJrJuhwltLRMBwKe7nInm0vw9eVp1qtoPAM+NDhpusROMbADAXW/Nif89BnLSulMDACydUPYnYUIAYEH7TACA3/fVAUC/Wf65hszXAQAWrE8iaU5aae7D6KUBALCmj9q58GSyHfmeaefCjRwDgNyRAUA0GQBkUdkGABYwaQBgw94wAOwlQY5GeKSdKGj/M+Tt/nXgIu+YWgBArquuAHBrZz8AyFQI5sDykqKrsAQAltKCQRVrUCZPaFg6kUYyaGdCAGhMAEDer0XEUxxrJtjpiwSAZQoASLSbqBEWojNHIQlMrN8GAsDL4/yFqDLNiekZAADWoCxK914muVZZr4Nn3w/WKjsB0KbHpFN3vhnYprI6J2ndyYu5AwAYQZ4lsj8J0486JA/aZ6wrj4/5Q78FdC5MAeqbIgDUbxkAAHM600pzH95fujNtAIC1Sex7pp3LACA3ZQAQTQYAWVSmF61sUMQCJkxNeIrs2q3bEwaA3RX+ngIa1QIAErQ/oAAAeZrAgi8cw360caededHLjsgMANoqAEAWVrOUFgyqGABsLA8DAEsn0kgG7UzdwG2DAcCeivBcrKkQAhM7fZEF2KygGHftmXuUVliIzgJHeb9Yv40nAQCYE428X0xPDwsAgOW0465qqgAgT5iYR36LUcFaZelXMj0m1aZoGt3RNahNYM84ad1ZcSI5AAwnDbekOxkTngCwoH06AMD9SgBgee1ot5kIAC5tGRRzj1vBAaDth2vcrZ3L3FbiMOecbn2NWpI+AEB7YvY9085lKUC5KQOAaDIAyKIyvWhlgyLNjik7tl+7J9wkZxcJcjTCnNZEQfuf3l4QH/OXd/wAIGGCgQmOYT/auNPOAlrZvZcBADbvYkG7LNxlJzQYVLEOxdkAALTbY8AkA9r5pKkQ9jpgACCLbRkA4K49Sx3TCgGA1cdIKGT9NrAZVVsSmMiTHCbsdswAAAs+UwUAmQLIHHJajAqKk/9B0q8kAGSiwyoWJ7Prku5EzM0J7VxZx11pTsCkAYBpa/fGx/zxbQ4AmALEAGDQPB0AXPZcAACszglPmFnfFOd062vk4vQBADYobDPWAODzKAOAaDIAyKIyvWhl51QWMGkAQHbJ3HnIH+RoNHO9Lmj/IwDAQ0oAYGBSVwBgOe0yF5r1FMCAVgsADNAwqOIAEA7QWD2BRtpdaGy4w1KmZHDMuoqi1SkDAFlsyxyFEADYutEKnahYepwskN1+wP/dwA7FLDCRTjRMmE7EOhR/uGKXai7NGHkCyPLji0cGa5XVX8j8eFZQnE79FACANRWU7kQaAGBuTtKcgAkBgAXtUz8OAOBPaQSAy1txALi81cT4OLbJgb8vWkchphFpBIB+s4LuvYnqYwwAzl0ZAESTAUAWlelFKzuUsoAJUyZY3q7sksl2OTWSAMBSJu7vlxwA5GkCmwvHsF27lpBqw2wtpXMPKwIMAQAJ2mVaBQM0DKp+kQEAkEE7U5cpgXe/FgDmbvIDAKZfsblkh2LmKIS79g8OWJjk3SYWOlGx1BHZ0Zk13MOO28yLXps7julErEMx5o6nCgByA4Clx6A7EQMA+R5ZQXE6hQDA0sJkcTKzJ8Zux+8u8AOArE1iwhoAFrRPWRMAwAP9+XpGAOhd5p9roBIAvvl8AADMNQ0BINFcmvswfFHQoThVAOg/OwAAVh+jncsAIDdlABBNBgBZVKYXrWycxAIm3DFlebuySQ7b5dRIBibsNOEPAAAPDvADgIQJNlddAYA1tpLFkJqmYixol+keDNDQ850dtcsibVZQrJEWADpB8y62ay93x+ds8ncVxToHPQD46wlw1z5RwKQRAgA7HZOnQpv2+RvuYcdttjOpTR3BdCJmazlPCROaMfL7zzpuozsRC+QkAFRV+wuK06nbupTF/x7rKSKLk9l7RAAYSgBA1iYxaU4AJgMAJAJaFQDM3Rofk2jX/soXSuPjWM0Upph+o9UEOhfeB1bvMQwAIJFzV10BgJ2OaecyAMhNGQBEkwFAFpXpRSsdRTQAwPJjpUd2oqKvZJIAwE4TsHmPFgDYXCEAWOgHAAxCb+o4wztGFu6y3bEoAMA+H9xVZQCwXgAAKyjWSAbtTNi8iwXtsmZizkY/AGCaE6snkHabzFEIg/ZEOdMaoRUtOx2TULix3N+ETQUAyp1jTCd6NgMAIL//zLoX3YmYA5O8LuYolE4hALC6EFmbwACgAQDAkPl+AJCpiUwIACxon7R6T9LnoHNhACgp8werCACJdu2vah0AAHteosnEZc/pAIA1kBu2MH0AgClA7HRMO5cBQG7KACCaDACyqEwvWtk4ie2YYsoEAwDpkc3SHDSaLgCAnSaEAcC/86WFCRzD8nax2PbHSgBglqLYVIwF7bJwl30+uKv6s25+i0wJAKygWCMZtDO9DgDAgnY512wCAAg5rABbdihmjkIIAIlsEzVCK1r23dB2YcaO2yw1QZs6gjDBAEDrRKMZI7//zLoXi5NZrr28rpOnPnsAuLVzcgCQtQmsQSECwOD527xj5MYEE6YAsaC9FAAgUU0LAgALVt9RAsC3X5wUH8dOORAALlUCAKv3eG9hULCeKgD0BQBg3w3tXAYAuSkDgGgyAMiiMg4Awjed7ZhiygR7+EqLPJbmoNH0teGgnZ0m/LbPvKQAoIWJugJAo9eme8fIYE8DACxol3n77PN5RgEAskiTFRRrJIN2djLRsTQ5AMj8+I82+DvSoq0lAwDpt79gCwOAIGhP1DhJIwQA9t3QNmHDjtvMuUebOoIw0WLUZw8A0iOf9QHB4mQtADBL0XQKAYBZCsvUJHbKgQAwaJ4fALT1F3gCwALMiat2x8cwNzTnwgDQk8w1YI4OAK5uEwAAgxxMAdICAKv3QMeqVAEAXYBYepx2LgOA3JQBQDQZAGRRmV600jddAwAsb1da5LE0B40kALDThPt6BwDwZ5LLLQGAwQSOYYV7mIZyIwEAGeyx/NjnIwAA29HG4PiOrp89AMignaX3dJgYdO9lQbucq2y9HwAwcNR2FWaWohi0/7bPPMU75sJeFOy7IU9yNB23WW6yFgAeCQGAv7Ottp4gCgAwty0sTmbFtvK6jhNL0XTqJ51nJg2iZWrSvqN+ALiuXQAAAwkAyOcSy33XAMCElQEAMHhxzrkb0wgA2O144Nyt3jEhAGipAwBW7zHUAMBUBxkARJMBQBaV6UUrfdM1KRMsyJEOGRv2RgcA9LUuLOanCU1LAgBgxZxamMAx7EgbAeBHHfwAIPP2maUoutqwoF0W7rIdbQyO2VyyTwNzFNJIFrUyAHhVAQByrpkEADCnnTkwSQBglqIIAE1LUgMA7EXBctrl58gAABvusdxkbe44wkTxSAIAynQizRh5AsiK7bE4mRXbyus6SixF06nGnQIAYGk08mRCBQAkOJbPJdbrAFOAWNA+HgAgUV8LBIC3ZvjnwgLZRACAzc76z/b3J0AXoPotx9O58D6weg/sUMxS7eRcTNgILNUaAOsEnJsyAIgmA4AsKtOLVvqma1ImWJAjHTJYnrNGEgA2lvsB4N6SuXUGgM0EJjQAgHabP+wwzTtGCwDYU+D2N3R5+2xHG3dV2Vwf7w4DAHMU0kgG7Sy955UJAQBo+ybMWFfuHYcpLQwAZIMyZimKu/ZNes1N/oYTKAQAJKVFnr4wAMB+G2xnUtraMiFMMADQ1hNoxsgTQFZrg1anLFiVAMB6CqRTtygAQJ5MsDoHBIB3CADIZ9xpkvuOAMCC9nErAgBI1NkaU4B6zNjoHfO2EgDQ6Yg1KEMAuORZHQCwdC/sUJwqAPSauSk+JlUXIAOA3JQBQDQZAGRRmV600jaRBZghACBBjiyQY3nOGmFjm8JifppwT68AAFgDHO1pAo5hzh1ot/mDV/0AINM9mKVoFABgO9q4q/pTJQCwvH2NtADQHo7HWdAu55pOAAB3tJkFq2xQxixFMWi/u+ecpO83kbAZHQu+5L1nFqwaAJDFoyx1BOdqPsIPANp0Is0Y2SRr2wH/SdtjCgCQYFJxMrMAwJx0JJiUkzoHBIABc7Z6x8hnHNv5RgBgQfvY5UFDN/Z8di4MAN2npwYAWOfA7Emxz0w9JQCwDtLYoCxVAOiZRgCwFKDclAFANBkAZFGZXrTSNlGTM82CHFkgt2ZXdADAxjaFxfw0oYkCAOQPLTtNqCsA3PAKA4Bw0M4s8rCnAAva5c4xC2gfVwCAbNTEHIU0ks3OGAC0UwCAnGv6Wj8AYDM6ZsEq+xMwS1EEgN+8lRoAYDM6FtDKJnnMghXfI3MnkQDAUkdwrmYjlnvHfJYAwFLt8CSH5avL62Idd9Opm1+fAQDgP02UYMIA4Pp2U+NjWHrMZPGMY05HGgD4AAEgQZOsGxUAgBaZWgBg9qTYZ0YLACzdCwFAWwPA4PitGXYC8HmXAUA0GQBkUZletNI2ke0wP6AAAFkgl0qnWQkAa/f4YaJJzwAAmJ97bQDwwwSOYa4WaEXJAEDmezNHoWcVACDz9llAi2kVrOGWBABW8K2RFgDwx5Ht2su5pn681zsOrWgZANRqKkbuF+7a/6rH7KTvN5GwGR0LaGWTLGbBiv02mHOPdI9hrik4V9FwPwBo6wl0ABA+AWSgjSc5rNhWAgDruJtO3QQAwAwF5HUxpyMEgLcJAKB3f2ExL3RGAGBB+5hln8THJOqSqwGAvhEAgNmTIgB8vYVufbHTnoERAID1FOgxY2NSAKipqTEAOIdlABBNBgBZVKYXrbRN1ORMs8I9WSCXSqdZuTvGThPu7jknKQBImGDpRDiGWfchAHy//VTvGC0AoKUoC9olADCP/McUACB3oVnBt0aysRUDgJc+BAAgQbuca8oaPwCgExXrwSABgN0v3LW/s3v6AIAFtCt36gAAIYc590j3GJY6gnM9QwBA1hOwHVNNICRrgNj3DGsTWK69BBPmt59O3dQxOQDI69pTkRwA+pH8+FIBACz1RQMA7y/dqQqOEQDenLbBOwYBIFH33msVAICNJr+mBAB22oMNyrQAwE7Huk8PAIDZ7WoBwFKAclMGANFkAJBFZRwAjtQ9Z5qlOUgASKXTrASA1bv8MHHXWwEA3E8aOsm51qcAANhw6/p2fgCQefvcUjQ5AMjc8Vkb/J8PplWwueQudCoAIJudMQBoMzY5AMi5JhMAQCcq1oNB9idg9wuDdtaFWStsRscCWtkki1mwIuSwwl1Z1M6KJh9SAIA2nUgTCMkuuSxtD2sT2P2SYML89tMpBABmKCCvSwMArEB24qowALDUFwQAFrSPWhIAQKL8eA0AoEWmFgBY4CsbTTLhGHbagw3KtDUArKnYm9M2xMewhntnz9oJwLksA4BoMgDIojK9aKVrCgMATJlgaQ7SISMVn3l5PM7SiX4DAMA6ukoAYOlEOIZ5d2PDrevaTfGOkXn7GktRbdoOa5KFnu/MklMCAHN80kgLAC+OXR0fo+2cPGn1Hu84LERnAKBtKoYAwHowaBXuRu3/bkiLTGbBipDDCnclALCdY7xfTw/TAQALmKIAADMBwNoEdr9koM3sNtOpHwMAsHoieb92V/h7HXy/fQAArEAWm3cVFnOnIw0AjFgcAMDj7+oAoNvU5ACgdQFi9qRRAICd9mB/Ai0AMGelblOTA8AZA4BzWgYA0WQAkEVletHWck1R5ExTABAFcqnYTMrjcZZO9Oses5MCgIQJFpiEAIBY9yEANHjZDwAybUdjKcqCdgkArEkW5lVrAYAVfGskux0zAGj9QQAA2s7JpQoAYE3YpKMQu18YtLP6C63CAODfOZYFsuy7gQDACnelqxXLmcbC/aeGLfOOkfUELGDSBELSBYyd2mFqErtfMtBmxbbpFDrksHRCeb9Ys7OGAACsQBabdyX6HBEAWNA+fNGO+JgnlADQVQEA2hMAZk8qO80z4RgGe9ifQAsArKlYVwUAVJ85q7p2SwHKTRkARFPeAUBVVZVr3ry5u/jii90FF1zgrrvuOjd58uSk/9/777/vbr31VnfxxRe7f/mXf3H/+7//6+666y63ahV3FUimTC9a6ZqiyZlmec7SISMVm0kJACxn+lcAAL/vO181F6sn0AAAdty9VgkAGkchFkDLvH3WJAvTKthcEgBYwbdGWgB4AbodawFg4io/AGBAy5qwaZuKYdDOTl+0+l2fYC6WOiILZDkABO+RFe7KonaWM411O0+95wcAWU/AAiZNICRdwBi0Y2oSy7WXgTYrtk2nblQAgLxfnygAgOXHo3e/FgBY0D5s4Y6kn7V8j29M8c+FTbK0AMDciaIAAOut8HYEAGD1MW9MSQ4Ap5UAYCcAuSkDgGjKOwBo2rSpKygocEVFRa6kpMQ1bNjQFRQUuFmzEucGt2nTxt17773u1VdfdX379nUvv/yyq1evnrvwwgvd8uX+H+9kyvSilUWTmpxplrcrHTJScZmR+bEsneiX3esOAGxnEsew5j0IAN97yQ8AMm+fOQppAEAG7axJFqZVsLlkISor+NZos2h2xrr8Pg8AwHbt5VwTVu72jnsgAgCw+5VOAPhtn6AbNUsdkekxDI4RcljevixqZykTWLfzJAOAtbqCYk0gJF3AGLTjKQcDJgkALNc+ncLgmNUTyfvFAOCGV6YlDQo/XLErNFfFiegA8O6CoEsuO+2RczEAKCkLLDK1AMCKkw+fOKVaOziGwR7ak6YKAF2mrE8KAKeqDQDOZRkARFNeAcCCBQtcLBZzHTt2jP9bZWWlu+SSS1zDhg3rPN/evXtdQUGBe/jhhyNdT6YXbZSiSa1zRypFphIA2I7pnQoAkHOxegINADw1LOi4+72X/KdEMm1HYynKAmgJAKxJFlo+srlW7AwXorJ6D41kt2P2N1uNDgCABe1yrvEEADCgZV2Ya/UUIPcLd+1ZypRWCABs51jujrMeDAg5LG9fAgBLmfijAgBkOhHzoo8CAKzOASGHdu9WptqkUxgcs3RCeb92HvJ3O0YAYPnx2LyrsJif5GiC9qEAAGzdyLm6TFnvHYNdchMBwPdeSg4Ah47XHQBYXQW6EyWqc9Cs506TAwBo/YH/t1YLAJYClJsyAIimvAKAZs2aufPOO88dORJOC2nfvr2LxWJuxw5/Eyemmpoa96//+q/u3nvvjXQ9mV602qJJTaGjBIBUikxlgRzbMb3zzVkKAAjPpQEA1r3zqfcCAPhuWz8AyLQdjaPQLVoAIE2yMK9aDQAk3UsjGbSzUwfsdqwFgHEr/ACAAS3rwiwtRdn9wqA9VQC4r3cwF9s5lg5Z7HQMIYft5MqidrZjiml7LC9cBrTMUQjHMKtQ+R7ZdxYhh52YaHfa06kfdgiCdvYskelXOw4mBwCWH/+BAADmfqMJ2gfPDzzyEwEAnnJ0npybAMBgD2sTGABI607WW6HTpHXxMewEoKr6jOra7QQgN2UAEE15BQCNGzd2V1xxRa1/nzp1qovFYm7s2LFJ5zh8+LDbt2+fW7lypfvzn//sYrGY6927d6TryfSijVI0yQr3pHNHKkWmskCOBUy/AAD4XR8dALDcZBzDunciAFyjBACNoxADAJm2M21tco98Npe0omT1HhptLNedAGCzM7ZrL+f6cMUu7zgNAEhHIXa/EAAYvGjVtCSYi+0cywJ5djqG75HlcsuidrZjiqd2LGCSAS0LmDQAIF3A2HtEyKG59gIA2E57OvWDV5MDgDx90QAAy4/H5l2FxePcQQUAsKAdu+Sy1DHtXD0jAABzJzqoAAAZtLPPWgMA0rqTOWS9DgDA+gBUnjYAOJdlABBNeQUAV155pbv55ptr/fuaNWtcLBZzvXr1SjrHN77xDReLxVwsFnNf/vKXXatWrdzZs343DVR5eblbvXp16DVmzJisAoCmaJIV7knnjnQCAAsmftbto/iY3/aZp5qL9SfQAMCTAADfaTPJO0bu2msA4GbSJVcCAOuSi3nVbK70AkDY6pQBAPY6YEG7BICxy/0AgDvarAuzBAB2v3DXnl27VggALHCUBfJsPeN7ZGk7sqaFBUz4nWU50zKgZV70OIZ1V5WQw77/CDnsxESeTLBAO53SAIA8fdEAgKZ7b2Exr+XAkwkWtGOXXFY8LufqROZ6a0YAAIlsQBEAmDuRBgBk0M7uKRYnMwCQ1p1sPXcsDQCAdQI2ADi3ZQAQTXkFAPXq1XO33357rX/fvHmzi8VirkuXLknnmDt3ristLXVvvfWWa9CggXvmmWfc6dP+Bw+qdevWcXCQr0wtWpkzzQAAc6a1zh2puMyMF0E7Cybu6JocAORcrKAYx7ytAICrtQCgKChmQbtM22FdctE9hs21TAAAq/fQSA8AQaEzB4DwXB8QAPiDAgCkoxADAAza2YmJVveWzI3PxU6htOlxmrQdCQAsYNIAgAxomRc9jmHNwiTksCJz/BwZAMiTie0HPnsAwKCdfY7y9IVdlwYARi+tOwCwoB275CYCAIScTpPWeccgAGhPAFhx8oFjVUmDaBm0s3uKxclaAGDr+bXStUkB4OQpA4C6aun2Q671B6szAuzJZAAQTXkFAOk4AUAdOnTI/c///I975plnko7NhRMAmTPNXFMwZUJbuJeKy4wM2hlM3P5GAAD39dYBACtOxDH9SPfOJ95dGh/z7Rf9ACB37TUFxTcpd+1Zl1wsrGRzyWZUrN5Dow17dQCAvQ5Y0C7nGrPsE+84DGjZXNJRiAETBu0MmLS6p1cwF4NQ7emYJm1HFrVv3X/cOw6/s48pAYA50UQBAFZjgp8jS5mSAMDeYzqFQTv7HCV8bTvgvy6cS9O9t7CYdzvWBO3YJZf1j5BzvU7m6jFjoxIAJicFgP0RAIB91libwL4b0rufrecOEwMAeG70Su8YLQBYEXCgT+8Dc3zLpAwAoimvACAdNQBS9913n7vooosiXU+mF61MmWCuKRqrQ5m3m4rLjPTIZnP9VAEAci7mKKQBgMcBAL7VutQ7Rg0AcJpwE+mSKwGANcnCvGotALB6D43WKwEAnY60ADB6aXIAaNh+qneMLChmwIQAwO6XVk0AANgalHDMgFazay9rWjbvO+Ydh2lOjw5Z4h0jd7SZEw2OYd2CpQ0wO2HC96jNtd+SAQBA734GABK+NADA0mNGLg4DAHNzwrlY0I5dchMBgGau7tPrDgDMnUgDADJoZ+sZaxPY6Zj07mfr+ZUJAQC0fN8PACdOVasAwE4AAmnuV6ZkABBNeQUARUVFXhegdu3aRXIBcs65X/3qV+7CCy+MdD2ZXrQyZYIBAAYT2sK9VFxmpEc2m+u2LmXxMU1L/D/alyhWjAAAIABJREFUci7mToJj+ioA4CoCADJtR+MoxABApu2wJlmYV83mWiIAgKV7aSQBgKXRoNMRAwA51/tLd3rHYeD4fQIAsp5gEgEm3LVn90srBAC2BuV3QwMAbNde1rRsLD/qHYdpTo8QAJA72syJRgMAMs2JnTDhZoI2154FhekUAgADOQlfbLcad9rZ7vgIAQCsAdZnBQAdS9MHAMydaN/R5AAgg/ZN5LPG1CQGANK6k63n9hOCXftnCQAcrzIAqKsMAM595RUAzJ8/v1YfgKqqKle/fn13/fXXx/9t+/btbu3ataH/t7y8drC8detW95WvfMX96Ec/inQ9mV60MmWC2SZiMMEAQBbupVJkKoN2Nlc0APDnX2sA4B9DAwC48gU/AMhde01B8Y9JECp37Seu8ltkYu44m0sCAEv30mjdHh0AYKEz27WXADBqiR8AsA5FCwDsxASDdna/tGrSM5jr3pK53jESAFh6HL5HtmsvAWD9Xj8A4CnHI4P9c8kdbZaHjmNOEwCQLmDshAk3E7QAsLH8sweA7wMAsGeJvPfsZAIBgO2OD1+0IzRXObFz1QTt/aFLbiIAQMh5rXStd0wUAGDFyRoAkEE7+6wxNYkBgLTuZM5K7ccnB4BjSgCwFKBABgDnvvIKAJxzrkmTJq6goMA1a9bMlZSUuBtuuMEVFBS4srLAH7xRo0YuFgvfmv/+7/929913n+vQoYPr3bu3a9asmfuP//gPd8EFF7g5c+ZEupZML1qZMsFsExEAtIV7qRSZyiY5bK5bOwcAwIIvORezFMUxfT7a7B2DAPDN5/0OGXLXnhUUYz1BI5IzKQGAdcn9gwIAFm8Lz8VOezRauyfc7IylAGGdAwMACRMjF/sBAHeOr2/HACA8FzsxQQBg916ru3vOic91Ty//GpRwzFLa8D2yXXtZ0/Lx7iPecXjKoQUAloceBQDYCRM+S7TFtuyUI526vl1yAJD3XgMAbHd8mAAA1s9BE7S/DQDQfMQK+h4RcjpM9M/15rQNKgD4btsAAFhxcvnRyqRBoQza2WeNYMIAQDr3sPWMQXuLUX4AOFp5WhXQpvMEoKamxnUsXedeK11L7XZzWQYA577yDgAqKytdUVGRu+iii9z555/vGjRo4EpLw7u7PgBo3bq1u/baa92///u/u4KCAvfVr37VNW3a1K1c6X+gaJTpRSt3TJlrCu4mssI9mbebSpGpbJLD5vpJ55lJgy8JAMyCUQMAjwEAXJEiADyuAAC5a8+65GLqCJtr8baDnxkAsBMATHNiu/ZyrhEEAHDn+Lp2U7xjZD0BOzHBXft0AkCTnv41KOGYpbSFAIAE7bKmZfUuf18LhJy/D17sHSNTWlgaCo45Ve0HAFnozE6Y8FmiLbbdQE45nPtn0JeOYOm6doGrDdtMkPeepSZpnHuGLdQBgCZo7zdLBwAIOakCwDUaADiSHABk0M4+6ygAwOoqMGhvMcp/v44IAGBrLJ0AgOuePbuc++eGwhPvLqU1KNmSAcC5r7wDgFxS5gEgHDAxAMDdRAYA8tg+nQDA0gkad0oOAHIuZsGoAYBHhyyJj2Ee2XLXXlNQzFwT5K4965IbCQBIupdGH+/WAQCmObFdewkAwxb5625w55gBgEwnYicmGLSn6lhx11vBXHf39J/8SThmKW0IOSxolyltrLEdQs7fBvnnkiktLA0Fx1RVn/GOkTbADDA1RdMSANbt8QeFi7cddJe3mkjfX12EAMCeJfLes3x1jXPPuwu2h+baUxEdAPoCABSP1AHAq2SublN1APCdNpOSvscoAMBS2qIAAAPath+uSXq/JACw/hfpTAHqMmV9cE8JVDkXfB9T3bxItwwAzn0ZAGRRmV60cseU2SYiALC8XXlsn4rLjGySw9IJbgEAaEJ+tOVcrAATx/QuSw4A7MdR7tpr6gl+1EEHAKxLLuaOs4B20dYwALB0L43W7NIBAKY5MQCQMDFsYXIAaPCyHwBkOhE7MUEAYPdeq98AANz1lh8AJBwzAMD3qAWA5aSvBb7Hhwf655IpLSwI1QCAdDpigIlgwlJtZGrS2j3+NCdMj2EnE1o1eDkAAPYskaeJLF9dU7g7VAAA6+isCdqxS24iAEDIeWWCf66uSgC4GgCAvce9CgCQdpsM9vBkggGAnIsBbZuxAQCwE5OKk2EAYPa36TwB6Dy5bgCQC4E2KpeuywAgmgwAsqhML1q5Y8psE5tEAIBUXGZk0M7SCW5+fUadAYAVYOKYkjL/g/wRAIDLnvP/OMqgnQHAYyoACAftrEsupo5oAYCd9mikBQCEHLZrLwHgvYXbveMwdeRaJQCwExPctf9hB787kVYIAL8hACC/G6ymBd8j29WWQSjra4Hv8a8DF3nHyJQWFoTimMrTOgBggIlgwgEgfF1rdvkB4KrWpfExrIBZq2sVACBPEzUAwAp3h8wPA8Cuw/57rwnaEQBYSotzYcjRAAB7xjnn3LdfnJT0Pe6pqDsAMNjDkwkGANK6kwHti2NXJweAE2EAYO5XuQoAn9YTtP1wDT29cO6f92zR1oMUcOoiA4BzXwYAWVSmF60MmJhtIu7ascI9eWyfisuMDNpZOsFNCAAk/1rOxQow6woAlyoBQJNOxIJQGbSzLrmYOsJgYqGYi532aLR6V7jXAQMAhBy2ay9h4t0FfgDAUygGADKdiJ2YYNDOOhRr9eses+Nz/brHbO8Y+d1g6XH4HtmuvQxCWV8LvC4tALAgVAUAwumIASbee5ZrLwGA1TngCUCqzcKws632WcIKVhEAWOHu4PnbQnN9kgIA9C7TAQBCTvsJH3vHvDFFBwDfAvhi71EDADJoZ0XtXRUAIK07GdC2/iAAAOaadPjEqdBcrPg9nSlACADMWck5XaCNQM6MFZwLgJyd4tRFBgDnvgwAsqhML1oZMKUCAPLYPpUi09FLBQCQdIKbOiYHADkXK8DEMexB/shgAICWDADCgXY6AYB1ycWdYzbXgi3hudhpj0arPtEBAL5HBgASJoYSAMBTqO+9pDtNYACAwTHrT6DVr2CuXxEAkN8Nlh6H75EF7TIIZX0t8Lr+8o5/LplOtPPQCe84DQBIpyMGmHjvWa69rE1Y9YkfALAGiNVCaIUAwGo55L1nBasNFXn7g+ZtU937BoqgXQsA+B7bj/fPhXnoiVKA8PSFvcfdFSeTBoUyaGenPQgmDACkdScDWgSAouF+ADh0PAwALMUsnScAndIIACVlQd+Elz5ck9JcWhkAnPsyAMiiMr1oZcDEfNPx2J53yQz/aKdSZCqDdpZO8GMAAPajLedi+dcaAPj74MXxMfVbjveOkUE7AwA8TWC70HLXngEA7hxrAYDBnkYSAG4m3XTxPbJdewkAQ+YTAOiJADDZO0aeJrCUqc8KAO7szgAg/N1g6XEIACxorw0A/qL2X3YPrushMpdMJ9pxMDkAnDzlBwDpdMQAE+8XS7WRtQksuMe5Uuk74lzY157VcshnCQMALNxlefsDlQAQ2rUnQTsGe1oAaKcAgEQnAFe9kB4AkEE7O+3B62IAIK072anK82NWxcc8QwDgoAAAVvuCANAzjQDA7GOd0wXa2DmZfdbaubQyADj3ZQCQRWV60cqAifmmYz4xc+6Qu3apFJm+vzTcJZOlEzR6bXrSH205F8u/xjHsQY4AcMmzfgCQQTsrKMbTBBaEyqB99FI/AGDgyGBi/uYDGQcAvF9s117ONWjeNu84BIDvttUBAEuZwsCR9SfQCgPtO9+c5R0jvxsUAOA9sqBdAgDra3EnXNeDA/xzyXSi7QfSBwBsfeH90gLAip3+Qmd0v0pkm6gR+tprnyXMsQYBgKXtvDN3a2guBl8IACyQ6zUTAYDbUCPksLkwDSURAFwJAMAgZ9fh5AAgg3Z22oPX9eR7y7xjpHMPu6etRgcA8PQwHQCwky8EgB4zNnrHaJVOAMDOyezkSDuXVgYA574MALKoTC9aufvKfkQRALRNctIJACyd4EYFAIxaEp6L5V/jmLdm+AHgb4OCgLaeEgBYPQEGx1oAeH+pP5cTA0ctALDTHo1W7tSlAOH90gLAQAIAeArFAECuZ3ZigkEo60+gFQbavyAAIL8brD4G3yML2uUuNOtrceebs+oMAMxXHMecOFXtHSOtThkA4HWxtD1Zm8CcjnB9MftYrdDXnhVzy2cJc6xB5x4WfA2YowMAza59TyUAIOS8PM6fFtJJCQDffH5ifByDnE8UACCDdgYAeF3sBEALAM+NXpkUAA4cC3cx1gBA9+kpAsCkdWkDALRNZYCmnUsrA4BzXwYAWVSmF60MvhgA/EYBAPJHOxWXGflDy9IJsOGO9keb5V/XFQC+3sL/kJNBeyoAIIP2UUv8AICBI5trnpiLnfZoJAGAnQA8PBABwB+01wKAuVu94xBCryEAIOfKCABAQPvzbn4AkN8NVh+D7/HBAQu9YyQcs74WvwgBgH8ueZrACmk1ACCtThlg4nWxtD1Zm8Ccjp4Zvjw+hrltaYUAwIq5Ry4O33vmWIOFuyxtpz907y0s5qcvuGvPgnbc7X32fQ4A+B5ZXjgG2szowDnnrgAAYJCjAQBpt8nSvTA4fpwAgJyL3dOW7wcA8NQw/2nCfgEA7OTrswKAN6ZsoOM0gTa6JrEibe1cWhkAnPsyAMiisg0ArHES5kxru2Sm4jIjf2jZbiI23GEAIOdiu684hh3lYkD7NQIAMmhn9QQIEywNRQbtrEsuBo4MAOZukgAQPWVixc5wt2MGAH95Z1F8DNu1lzDxDgEAhNDvtJnkHSPXM0uZwl171p9AKwSAn3X7yDumFgCQ+hh8j3/urwOA+aSvxc+7zUo6lwQA1tkWxxyv8gOAtDplgInXxU7tJAAwpyMs5kxUNKkRNrZixdwjIgAA27V/WwAAO335riJo7zEj2O1NBAD4HtsyAIAglBkdOOfc5a0AAMh73HnoRHIAEHabLN3rdbiufwwlACDmYvf0WQQAkk6072gYABj4IgB0m8qDdo1eTyMAYNF0IocfAwATygAgi8r0opXBF2ucpHHukD/aqbjMyKCd7Sai3R7btZM/2mz3FcewnZy/DlyU9CEng3ZWT4AwoQWA4STN4TcRAIDBnkbLd+gA4KEIADBgzlbvOFyDDADkXCxlCoN21p9AK9zRvqOrHwDkd4MBAL7HB0jQLk+0WGO7n3X7KOlcMp2IdbbFMcfUAOBfX3d0Da6LAYAsTmZOR+jn3mYsdzrR6GoFAAxftCN0XcyyEp172K59v1lhAGCnLwgALGjHdI+WCQDgagUAYBDKjA6cc+4brSbEx6UCANJuk6V7dSxNDgByri3knrYYtSI+htUTlB8NW5gy8EUA6JpGAEg0lybQzkZTsXTOlaoMAKLJACCLyvSilTu5rHHSrxQAIH+0UykylUE7202MBAAk+MIxWgCoqandPEUG7SydCOdiaSgyaGd5zr9WFLXO2bQ/NBeDPY20APDggOA9srQduQb7z/ancuB7vFoJACxlCoN2Zk+qFe5o//QNPwDI7warj8H3+Ke3F3jHSDhmje0w0GZzSQBgvvY4hgGA7HXAAPP2N4LrYqd2sjaBFTpr7By1wsZWvyRuTsMEADDLSizcZbv2fQUAsGD1ms8IABgwYaCdCAAuey4AAHbKseNg3QFgGQGA10rXxsc8RgBAWneyE63ikQEAsHoCCQBs3SMAJMrb1yidAJDOegKt0jlXqjIAiCYDgCwq04tWBnIMADTOHfJHO5Ui09oA4L8u9NvW7tqx4AvHMADAlJbC4nHeDosyaE8FAGTQPmyhHwA0rjZyLvZZa7RMDQAL42PYrr0EgH4klxvf47df1M3FGuAgADB7Uq0QAG7rUuYdI78brD4G3+MfSdAuvxussd1P30gOADKdiNla4pijlae9Y2SvAwaYeF0M2uX9YoXOL4CdI9sV1goBgNm5DluoAwAs3GVBO3bvLSzmAPAdRdCuBQB8jy+O9f/GIAAwpzPnnLsUAICdcmgAQAbtrN6jw8QAAB4dssQ7Rjr3sBOt5iMUAHAkDABs3SMApJqGhvc+VQDAuRKlJqUzaE/nXKnKACCaDACyqEwvWhnIscZJIQBQdslMpchUBu1sNxHt9rS7diz4wjFaAPC1T5eBNqsnwLlYHrqc672Ffo/8OxVFrXM2fnYAcBMBgAf6JwcACaGsmBPXIAMAORermcCgnbkTaYWpNgwA5HeD1cfge7y/nxIAiP/9bV3K4mMYTMh0ImZrqQmEZK8Dtr7wuhi0y/vF6hzQzpHtCmuFnW2Znet7C7eHrot51iMAsEAbm3cVFvPdagQANteb04J870QAgO+RzYU77czpzDnnLm0ZAAA75dAAgAzaGQC8CgDwCAEA6dyzsdx/T5uNCIrHWUHxXiUAvPRhAACJUm00SmfQjsD05jQDAJNOBgBZVKYX7dLth0JfWtY4CQNMbZfMRABQcfK06/PRZmqjJ4N2tpuIdntaAGDBF45hD8yHBABUe9rDy0CbwQTOxfLQ5Vzvki65mNPOAGC2mIvBnkZy3TAA+NPbC+JjWNqOhAnWOA3X4Ldal6rmYjUTGLQzdyKtMNXm1s46AGD1Mfge/0AAQMIx62uBgTaDCa2rDY45ogQAtr5u7Vx3AGB1DujmwnaFtbpKAQDvLggDALOsROee1h/4n+XYvKuwmO9WY9oOmwsdX54bzQEA3yObCwPHRABQv+X4+Dh2yrH9QHIAkEE7K/h+ZQIAwGAdALATrSJwj2InR3sqwgDA1n1bAIBExbYaIXylCgB4vxK5E6UzaE/nXKnKACCaDACyqEwv2iVaAFBY99UGAL7DjA44Psmgne0motuG9tieBV84hj18Mae9sHicO50CAOBcDABk0D6UAACmtLDTBDkX+6w1kuuGpQD9EQCA7dqrAQDe41UEACSYsJoJBABWnKwVAsBPOvv7IchcewoA8B5/33e+d4z8brC+FhhoM5iQpwmsqFUTCMlmZ2x9/aTzzPgYBu3yWcLqHNDNhe0Ka4WdbVk/h6FKAMDCXRZoY/OuwmK+W41pO2yurloAeKFuAMCsjp1z7pJn0wMA0m6TFXy3n/BxfMzfBy9WzcVOtJ4eFgAAOzmSXYwrTvrXfZuxAQB0LE0fAKS6a99+fHC/EnUoTmfQns65UpUBQDQZAGRRmV60i7eFAybWORUDE+bcIYOcRC4zyR4UMmhnu4notsEAQB7bs+JkHKMFgFPVtQFABtoaAGCFqHKuIfP9AIApLQwmZm0Iz8U+a40kALATgPv7JQcAGbSzzsnpBAAM2lMFACxqbUwaoslce7YGf6EBAPHdYH0tMNBmc0kAYCktmkBINjtj66txp+C62HdWPktYmhO6ubCgUCsMjlk/hyHzdQCAhbsvjFnlHdOzFgD4g1UNAKDlY6vR/r8n3yO7Lky1YVbHzjlXDwCA1SZsO3A86bNe2m0u3uav98CAln3Wci52wvzUsGXxMezkSHYxrjjhX/dYiJ7Ib1+jdAIApiaxXjTaubRK51ypygAgmgwAsqjMA0C4aRVrnISBCXPukEFOIpeZZA8KGeSw3UR029Dm7bLUJBzDCrCwqLWweJyrqq7dHEYG2uxBjnOxQlQ51+D5/i65uKOtBQD2WWskwZEBwO/7zo+PYWk7MmhnP1a4Bq96wT+XBBNWNI1BO3Mn0gqLWtlJiMy1ZwXyCHK/66MDgJkEADDQZgAg04lYQKsJhGSvA7a+bn59RtLvrASA2QQAsJjzb4NSA4ArFQAweP620HWxplUIAM+TQBubdxUW83QVzNtnQXuXKYHlYyIAuFIBAJg6kiiQ+3qLYAyrJ9i6PzkASLcd5vjUDgCAfdZyLpbS9tR7dQeAwydOecchACTquKtROvP28WSCnapq59IqnXOlKgOAaDIAyKIyvWgXbdUBAAYmzLlDBjmJikyTPShk0M52E7HYTpu3y1KTcAxrwiIBwNce/qMN+0Jj2IP8z/2TA4Cca9A8PwDgjjY7TZBzpQYA4XWjAQC2ay+DdnZcjWvwSgIAEkxY0TQCACtO1gpz7dl9kLn2miZZv+3j77gtvxussd0tCgCQ6USpAIDsdcDW100AACzVRm4msDoHLOZ8eGBqAPBN6GzLGroNmhcGANa0Cgt3WUCOzj2FxRwAMG+fwQR6vrMx8j2ycVoA+BoAADuZUAGAKLZljk8IAOyzlnMxl6YnAQBY6pjsYnzouB8A0InqlQnpA4BU8/YRTBJ1ydbMVVNT4176cI17Zvhyb9prXebKlAwAoskAIIvK9KJdmEYAkEFOoiLTZA8KGbRzAAh22lgwIediqUk4hgEABu2FxToAYOlE6JDDnGjkXAMJAGBAywCgbH14LtYlVyMtAPyuT3IAkEE7s03FUw4OAOHrYkXTuGvPipO1CgFAxxneMdq+Fvge7+vtBwC5nlljO9xp154msIAWx7CdUAkAbH3d1DE5AMjNBJbm9AwUc/514CLvGK2ugOCYNXQbqAQALNxlOfkSAFi+ejoBAN8jAxPMtU8UyOEYBgBbIgDAgi1+AEC7TfZZS+celtL2xLtL42NYQbFsYnaQAAA6UbWf4O+HoNWraQQABJO3SW8V7Vz428EaNWrnypQMAKLJACCLyvSiXbAlHDCxH20MTJhzhwxyEhWZJntQyCCHgQkW27Fje1m4x1KTcAxrnPKAAICTp2oDgAy0WTpRGAD8aShyroFzt3rHYUDLThPSCQDy5IgBwH2958XHsLQdCQDMNhVPOb75/ETVdbGiaQzaWW2CVjjXj9UAkLxLbtMSPwDI9cwa2+FOOztNkADAurDiGAYAstkZ68Lc6LXpSb+zEgBYmhPmcj/0TvoA4HbS0G3g3K2q+4UAwGw50bqzsJjnq2PePgvaO03WpQBd3koBAOPDAOBrduicDgA27zuW9Fkvg3Zm+Yo57X8hn7V07mEnWv8YGgAAqyeQFqYHjlV5xz03OihEZw3RtEonACCYpBq0D5gTrPtE60szV6ZkABBNBgBZVKYX7XzRtZb9aGNgwpw70gkAMshhAHCNAgBk4Z4vNammpiY0RgsAJ07V7g45UwkAaJHJAEDO9Q4BAAxC2WmCnIt91hrJkyMGAE1LNAAQnov98OEavEIJAKxoGu8Xq03QCt12Gr023TtG29cCT3LuLfH325DfDdbY7sew085OE2Q6EfNgxzEsFUI272Lr60YAAJZqI08TWZoT5nI/OCA1AMDgmAHAOwIAWNdaLNx9lgAAWncWFvN8dczbZ6cJ2PU1UYD2jVYTks4lAcDX7FA+L1k9gQYAZNDOLF/bphEAHgMAYPUEEgD2EwBAJyrWEE0rDQDIe8+EFrns5Ng5XdCOTetYwbd2rkzJACCaDACyqEwv2nkCAEYt8f9oY2DCAEAGOYlcZpI9KGSQw3arMdeWBRMSAHypSfKhyjo6YtBeWDzOHfe0h5+xrjw0hqUToUUmc6KRQTvbycEgVAsA7LPWqBYAkJ3ve0vmxsdo03bYDx+uQQYA8rpY0TQCAEtN0grv/Y86+AFA29fipwoAkOuZNbbDnXZtOhHzYMcxLBVCWney9fWjDsF1sVQbuZnATjkwlePBAQu9Y7TC4PinBABwJ7SwmAMTFu62GOUPtLsKAGAWrJi3z4L21wEAEtmA4ntkJxPtFABw9mz4ecnSjjYpAEDabTLLVyxqZac9ci6WovXokCXxMQwApIXpvqN+AGgxKgi0WUM0rTTe/fLeM+F1sdox53RBO6arsToHLZhkSgYA0WQAkEVletHO3VR3AKB++yLISVRkmuxBIYMctpt4tQIApHOH72RCPlRZR0cJAMcUAMBOE9AikwGAnKs/yeVEy0d2miDnGkm65GokU8cYANzTKwAAbdoOK5rG4PjyVv655HWxHz4M2tnJhFZ473/YYZp3jEy10XTJvaeXHwDkemaN7XCnXZtOxDzYcYwWANj6+mGHafExWgBgpxyYyvHn/qkBwGXPBcEx6+jcf/aW0HUxALgqBAArvGPQurOwmBesIgCwoB07yCYCAHyP7GQCc+0Li/3dzs+I5yU7ddAAgHTbmbPJX/D94tjV8THstEfOxVK0HgEAYAXFEgDKj1Z6x6EVbaLdcY00ACDvPVPxyOC62EmoczoAQJcp9tuova5MyQAgmgwAsqhML9o5m8LWkOxHG4Mv5rYjg5xUAEAGOQxMcKeNBRPSucN3MqEFgD8KAPC1h58uAm12moAAwKwo5Vz9iJsDWj4yAJBzjUgBAGTqGAOAJj2TA4DctWcpUxgcf6PVBNV1saNvDNrZyYRWeO9/8KofAGSqjQYAmhAAkOuZNRXDnXbtaQKzYMQxLBdaAgBbXze8EgAAS7WRp4kMcjCV44EMAMDbAgDYiQkCQPFIPwBgUFVYzAEAaxNY0I7+8QwSnHPu0ggA4Ot2Xn3mbGgMg46N5ckBQLrtsJ4P6GrDTnvkXCxF65HBAQCwgmLZw6D8iB8A0IqW2aFqpUkBkveeCR2ymBuaczoA0PQn0F5XpmQAEE15BwBVVVWuefPm7uKLL3YXXHCBu+6669zkycm9wUeNGuXuuece9/Wvf91deOGF7rLLLnNPP/20O3zY/9DRKOMAIBpNsR9tDEyYc4cMchIVmSZ7UEgAYGByVQQA8IGJ3L3oRFq6Y9BeWOzvijp9rQ4A/gBzMStKGbQzOze0fGSnCXKu4aRJlkZaALi755z4GG3aDkuZigQApGbiswKAG17xA4BMtWEOWSEA6KkDANZUDHfa2WmCBABmwYhjGABI7362vhAAWKqNPE1kkIM7uX9829/tWKtLFQDQb1YYANiJCRbuNh/hBwAs3C0s5o41WJvA0onQPjIhALSckHQuLLYtLPZ3Oz9VHQ722N/cWH406bNeuu2wng8IAOy0R87FTmiwEz2rJ5AWpnsJAGCgzYqhtdKcAMh7z4TdjhkAaNN2EAp7EZu1WpfwAAAgAElEQVTm0wYAnwvlHQA0bdrUFRQUuKKiIldSUuIaNmzoCgoK3KxZ/kD3U/3nf/6n+9a3vuWef/5516dPH/f444+7f/mXf3GXX365O3nyZKRryfSilZ1m2Y+2BgBkkJOoyDTZg0IGOQxM8IeWOneIuXxgIgHgdSUA+DzRp63dGxrDThPQI58CgIAJ1tAFLR8pAIi5WJdcjWTtCAOAu94KAECbtsNSpnANXvacHwDkdbGiaQza2cmEVrcoAECm2rACeUxNurunv+GeXM+sqdgPXk0OABK0mQMLjmHFkNK7n62vhu2nxsewQFsCAIOcvw8OArn7+6UIABAc39rZf119lQCAhbvNRiz3jsHC3cJiXrCqAQDcOWY7+845V7/leJjLDyZtFQBQVX0mNCYVAJDFtqznA9pastMeORf7fB4eGKwbVk8gLUz3VPgBoAisaFkxtFYIAMwNTd57JiyQZ3bI2rQdhC9mKaq9rkzJACCa8goAFixY4GKxmOvYsWP83yorK90ll1ziGjZsmPD/nTFjRq1/e+edd1wsFnN9+vSJdD2ZXrSyO6wGAJjbjgSAREWmyR4UEgDYdeEPLdtNlNZ9PjCRx5cMAP4gAMBniVgLAMhcCADMi17OxQAALR9pOlEaAUDWjjAA+HWP2fExWgBgJyYYHF9KAEBeFwMADNrZyYRWCF8N20/1jpE77axAHk8m7iIdt+V6Zj0FcKddm07EHFhwDCuGrAUApAvz9e0UACDSCdl7xJ3cP6QIABgc/6TzTO8YdEP5Z4DpPzHBvP2i4X4AeF0JAFi4y4L2KADAUpMkAJyqrg0AlafDwR77mxv21h0APtrgt3x9PhIA+D+fvw5cFB/DAEA6GO2u8G/q4U57oh4MGmEPBgYA8t4zYbMzVgOg3bVHpyNWV6W9rkzJACCa8goAmjVr5s477zx35Eg4/7J9+/YuFou5HTvqFiQdPXrUxWIx9/TTT0e6nkwvWukNz4JCDL5Ysa3c5UwFAOQuJ7su/KHVAoDvuiQAdCzVAYDPEnHqx3UHAOZFLwGgdxkBALB8ZKcJci4WoGmkBYBfAQBo03bYiQkGxwwAZE0Lc01CAGBgohUCwPXt/AAgd9oZAODJxG/UAOCvJwgBAEknkt8z5sCCYxgASO9+lnZwXbugezcDAJlOyN4jBnKs27FWGBw37qQDAFYzgc+lp4f5AQALdwuLx7mVO/0AgLUJLGjHnWN2SuCcc5c8mxwA0G2nsHicq6qu3evk5KlwsMf+ZhQAYE3f0Nf+TyTdS87FPp+/vBOsG1ZQLAFg12E/AGAvikQWrBohALCGiNpA+3FwyGJuaNp0Imy4x3435JrItgwAoimvAKBx48buiiuuqPXvU6dOdbFYzI0dO7ZO823YsMHFYjHXvn37SNeT6UUrrSHZlxsBgOXay13ORC4zyR4UMshh14UFciyYkN7dvuvSAgAG7YXFfkeUKWvCgTY7TcAuuQwAJEyUlPl/FH6sAAA5FzsW1kgG2gwAftk9AABt2g4DJgyOL21JAECktDHXJAzaGZhohacv17XzW7Bq6lCcC4MJ67gt1zPrKYCpNtp0IlaAiWOYG4r07mfrq8HLAQCwVBsJAOw9PgSBHOt2rBUGxwwAepfpAACfS08NW+Ydg4WVhcXcshIBgNUTYOCYCADqwXtkc6HbTmGxv9v5iVPVoTHsZGK9AgCk2w5r+oYNt1i9h5yL1bQ8FAIA/2mCdDD6hAEA7LQnqr/QSAMA8t4zoUNWqrv2CBNsY097XZmSAUA05RUAXHnlle7mm2+u9e9r1qxxsVjM9erVq07zPfjgg+68885zGzb4CxlR5eXlbvXq1aHXmDFjMrpoZWEo27XD3VcGAHKXM5HLTLIHhQQAdl2YH8sAQHp3+65LHoW+Vur3OpYA4CuInCwAgMHEb/sETbJYMyoJE6wACz3fWTqRBADWJVcjGWizDrh3RgAAdr8wOK7fcrzquli+Kgbt7Lq0wtOXBqQLswy0NQDAOm7L9cx6CmCqjTadiBVg4hgGANK6k62vawEAWKqNTCdkrkkPDggCOdbtWCsMjm8hAFBStkkVYOJz6an3/ACAhbuFxRwALtUAwHgEAP8Y55z7eovg77HaBA0AHKsKB3vsNGHdnuQAIN12WNM3bGzF6j3kXKymBdcNKyiWDkY7D53wjsNeFInSrzTCz5EBwPGqugMAc0PTAgAW2zMAkGsi2zIAiKa8AoB69eq522+/vda/b9682cViMdelSxf1XEOGDHGxWMw1b95cNb5169YuFot5XxkDgLU6AMDdV1Zsq83bdy45AMhdTrabiPmxWgDwXZcEgA4TdQDgK4jUAsB9vaFLrhIAehIAQMtHBgByrkTe0MmkBYBfvDkrPkabt8/gSwMAsqid2aZi0M6uSys8fbmWAYBYz8whC08mWMM96UXPgmNMtWEAIL9nLP8axzA7RAkAbH1976WgezfbaZfphMw16c/QmZs1O9MKg+ObSWfrXjPDALBgS3IAeJIAAKbtFBZzz3osTmZBezslAHxNAQBY8FlY7AeAo5WnQ2NSAQDptjOdAADmobN6DzkXq2nBdcPqCWQB846DfgDA3fFEpy8aIQCwZ7020EYAYLVQ2l17BAB2si/XRLZlABBNeQUA6ToB+Oijj9wFF1zgbrvtNlddXbs5lE+5cAKgTQtBAKC59sq8fefqDgBsNzFK8x7fdclcSAYAmLZTWOzPh560eo8qoNUAgIQJtiuElo8snUgCQKLukMkkA22WAvTzbgAAJG1HAgC79xgcX/KsHwBkUTuzTQ0BALkurRAAWBdmTSG6c+GTCdZwT65nFhxjqg2rJ5Bw7Mu/llaBDACkdz/LO/5u27oDAHNNwsZ8rNmZc/+sdRq+aIerqand1OpTIQDcRACgpwAAtsOMGxNPvLvUOwbTPQqLuWc9AgArKEabRhaMOxd+7rK5JACcPFUbACpOhoM9djKxds+RpM966bbDuj5jZ1sGAHIuVtPygAIAZP0CAwDsRZHo3mvUTgEAR5SBNgIAq4XSwgQCANvYk2si2zIAiKa8AoB01AAsX77c/du//Zu79tpr3bFjx1K6nkwvWhkUskD7Fg0AKPP2nUsOADIwYbuJeDzO8oll8x7fKYcEgFeVAOBLhygVAMAC2qYlAADEi17CBHOGQMtHlk4kYYIdC2skA212AvCzbkEDOZq3L+oJ2L3H4LgeAYCPNoRrWphrEgbt7DRBK0y/Yk3YJNBSAIDrYg335HpmwTGm2rB6Avk98+VfyyZ5zA9dWncywLwGAICl2sh6IpYyhY35mNUpdodlxdfOhXfHGQD0mLExdF0MAHBj4nEGAOPDAMA867E4+RkStKN3vxYA2FwSAE6cqr2hVXEiHOyx0wQNAMhiW9b1GTvusoJvORfrKozgyAqKZf3C9gN+AHgUgmMGQlq1U6QAaQNtBBNWC6XdtcfGaWxjT66JbMsAIJryCgCKioq8LkDt2rVTuQBt2rTJXXTRRe6yyy5z+/b5j8/rokwvWhlgMgDA3Ve2067N23cuOQDIXU62m4i7YyyfWAZMvlMO6WH8ygR/EIp5+4XF/t3Qiat0AHBvSdAlVwsArDkMOr4wAJBzsWNhjbQAcEfXAAC0efvs3mNwzABAuloxAMCgPVUAuBHmYhasMtBmebQIJqzfhmxGxYLa770UAACrJ5DfM1/6hfQKZ37o0rqTAebVbSbFx7BUG1lPxAAAXbmY1SmecibqFox/j51odZ8eBgCWYoIbE/8Y6geAdgIAWFdhLE5mQTtadyYKQvHvMXci9NsvLPYDwKHjp0Jj2GnCx7uTA4Astp36sR8AikcmBwA5F6tpQXBkBcUSALYdOO4dh7vj7D5ohWuCPeu1gTYCAKuF0sJECADIxt7hE6dUc2VKBgDRlFcAMH/+/Fp9AKqqqlz9+vXd9ddfH/+37du3u7Vrw4HJnj17XL169dxXv/pVt3Xr1rRcT6YXrdytZjvtGgCQu5zpBAC2m6jx7pYBkw9ytACAaTuFxf7dUAkAbEf7nl4BALButPLz0QAASyeSAMCOhTWSO+0MAH76RgAALG1HAkD7CR97x2Fw/PUW/nUjAYDZpiIAsOvSCgGAOTDJ9czyaPG6WL8N2YyKBceYasPqCSQc+9IvpENWqgDw7RcDAGA77RIA2IkJ1uQwq9MoAMDW85vTNoTGsRQTBIDHCABg2k5hMW9ahcXJLGjXAIBM5WJzPS8A4HhVbQA4KACAgcmaXckBQBbbTiFdn5uPCACAOT5JAGBNxbChIysolvULW/f7AQCb0bH7oBWuiTen+Y1EtIE2AgBLhdTCBAIASxOWayLbMgCIprwCAOeca9KkiSsoKHDNmjVzJSUl7oYbbnAFBQWurCwIdBs1auRisfCtufrqq+NFv4MGDQq9Jk/27wQmU6YX7cRVu0NfWrbTjukXLNVG7nImspnEcb68XBmYsGBCY90nAyYf5Eg3BBaESgDwBUPynjKYQABg3WglTLAfBbR8ZAAgYYLtCmmkBQBsIMcCbVlP0G58cgD4GgEAaWvLbFMxaGenCVppCrDlemYOWQgArN+GFgCuUQCAhGPf7qsskGcNkaR150BywvSt1kHzPgYA0lCAnZhgSh6zOsX+Fyzdw7nwM6nRa9O9Y7pNVQIAnEw+OmSJd8xLH0oA8BcUIwAwS1H07mfpODKVi82FfvuFxePcMQ8A7D9WFRqTTgCYTACg2YjAi545Psm5WFE7giOrJ5DpS1sIAGAzOgZVWiEAdJvqf9ZrA20EAHYSKk9ymBAAWJbAAbEmsi0DgGjKOwCorKx0RUVF7qKLLnLnn3++a9CggSstDQdRPgBgDj6xWMw1atQo0rVketFOWBkOVtlOO6ZfMACQu5yJbCZx3NmzCgAgwUS9CADggxwtAGDePguG5D1lczWJAADsR+H7CADK0wS2K6SR3GnXAAALtCUAvDxujXccBscMAGYIW1tmm4pBOztN0EpTgC0DbQYACCbMblc2o2KOQphqwwqK5XfDt/sq62MYAEjrTpZidhUCAFk30lCAnZggkLNCZ3Q6Y+kecnecAcAbU8IAwHLM8WTyEQIAsuEWAwAsTmZBO1p3MgCQqVzMnlQDAPuOhoM9Fviu3lWRNCiUbjuTVvu7PiMAMMcnORdrKqYBAJm+tHmfv77v4YGLk95TrRAK35jif9ZrA22sTWAAoJ0LAYBlCcg1kW0ZAERT3gFALinTi3bciroDgDbXPpHNJI6rPlO71bwMmFgwgT+OrKBQBky+91gLAMgutAQAX3fI8VoA6BkAwBUUAMJzsR8F9HxnACBhgv0oaCR32hkAYP8IFmjLeoKXPvQDAAbH7AdG9rXQAACDCa0QAFj9hQy0mZMGXhez25XrmaXH4E47KyiW1+ULvmR6HOuIKp17WIrZlS8E18XWjQQAdr/w+8gKnXFNsHQPuTt+IwGALlPWh8axxml4MvnIYD8ASL991lQMi5NZgImFuywPXQsA2HCrsHicO1p5utaY8iOV4bkImKz6JDkASLedUgIARcOTA4Cci/UUwJMjVk8gTy82EQDArsLM8lUrBIAuU/wd0eXpCxMCAEuF1M6FaU4sRig/WqmaK1MyAIgmA4AsKtOL9sMVu0JfWpZqg+kXbKddBu0snWjxtoOhcac9ACADExZM4BgtAPjeowQAloaChbuFxf7ukLUAgMx1d8858TGXt/IDgDxNYD8K6PnO6gkkTLAfBY20AID2sQwAZDpRWwIAGByzHxjZ10Jjm5rqjxU6MLH0K7kGmZMGXhdz25LdaFl6DO60s4JieV2+4Et+N1hHVOncw5xHvgldctlOey1HMXK/MI2OFTojALDdXhkc/6iD/7o6Tw4DACsyRQD4++DF3jHSbYc1FUMAYAGmBgBkLQebCxtuFRaPc0c8ALBXAgCZSwMAsth24io/ADwDAMAsX+VcrKcAmjkwAJCnFxvL/QCAXYWZ5atWWMvRabL/Wa/daUcAYBsh2qAdAYDFCHJNZFsGANFkAJBFZXrRfrBcAADZacf0CxZoSwBgOwU4prB4nDtVnRwAWDCBY5ijSC0A8LzHk6d0AIABR2Gx3xtanqqwuaIAQGfyo4CWjzydKDwXy4/XSKbaMABA+1i20y4BoM1YPwBognYJABrb1FR/rLAAm8FXLQAgThp4XazYXgIAS4/BnXYtAPiCr6gAwGpMrlAAgDQUYPcLT9FYnQOuVRbsyeCYAUCnSetC4xgAYGri3wbpAIA1FcMxLMBE5x6Wjy9rOdhcEgAqTtYGgN0VJ0NjGExoAEAW205c5W9s9/SwAADuLfEXfMu5WE8BTB1jBcW1AeCodxx2FWaOT1rhqdDrk/wNJOXpC+ttgQDAegrIuZhCAEBihD0VBgCfBxkAZFGZXrRjln0S+tKyVBsNAMigne0U4JjC4nGuqrp2oxkZmPiCCZm3ywoKZcDkO02QAMDy0DUAIE9VGADc9VYAAN9o5ffIl6cJbFcILR8ZAEiYYD8KGslUGxbIoXsUAwBZT/DiWP/alwDg++HDgs/CYp1rUqIfUY1wLnbv5RpkDlk4FwOAkrJwMypWT4CBNnMUktc1YWXt4Et+N3Ye8vuhS+ce1oUZm2SxVBttJ3CEaJbmhKdVWgD4YYdp3nGvCwBgLjOYmvjwQD8ASLtN1lMAx7Cg/XkFAMhaDtaf4FkFAGBvhUTXpQEAWWzrW4POOffUsGXxMazng5yL9RTAk1wGAPLaN+z1AwB2FWaOT1ohFLIO8nKn/Yynhs65sD0pOwnVBu0IAOw0Xq6JbMsAIJoMALKoTC/a0Ut1AID51+qddiUA+FrNy7l8wYTM29UCgO80QbZEZwDQRACArznMWHGqwub6DQDAZc/5AUCeJnQiu0LfeylwfGH1BBIA2I+CRloAwNoR9qMgAaD1B/61L3ftfcXjsrM1K5qWAOCbSyuci917GbRrAIAV2/cS3WhZfvzlrQIAYI5C8rsx3hN8ye8GAwDp3MOKzLFJFttpl45izFAAv0PslKNMAQD/j70rj4+quv4PiYJoXWrdWu1YwLYKLlVRwSq44U61StWqpRX1J1rrBj5ABDWCLAoCIgREEBBFRAOGHYkQlhAIa4CwLwmEQCAbIQkkc35/xDdz3nnnzNxMZt6Qmfv9fO7no8PNzcud+94737N8D/WO39KfJwAD52y2zZNUZjABeP7LlewcKrcp9RTAcySjHRfuSgSA1nJIa+GOux4zBYrKnAQgV5EArM8JTgBosS13BgEAXv/GTwCkng+UAEiSotiRIykKUQKwRSAAuKuwpPikCnwmpP4x1GjnaugA7ARAioSqGu1Y6UiKxtMzURenSjigCUBo0AQginD70H6/Osd200rsHudfS4a2SqoNgJMAcK3m6VqcMUHzdiVFEWp8cdEEauRIhaiUAHDNYSgBkNZ6ZMQS3xxVAiCFhbHmu2SE0miC5B1XAU21kQhAOwUCQOsJeidvYOepGO20s7VUNB1OAoAlWKVULmq0Sx5tFQIwkqwl5cdjQ1tSFKL3xo/rnE3FjlbY7w0u6gXgLNyVisyxRr7kaVdtBPgwuoekKAdOMZO8vdQ73uZD/roGzFYjADhv/zmBANBiW44A0CinlGKCCYCkyENTuaS1KAEoLKt0zNl7uMw2RyIT63IKg97/tNg2ZR1PAF5TIACUTEiSovg5LhUUU/KSnccTANxVWCr4VgU+E5J8NDXauRRaADsBkJ71qkY7JgBSZC/niP1MSJEJt6AJQGjQBCCKcPvQfrfKTgAkdq9CAKg3UYom4Dkek+80SdfijAkatpcIADW+uAcYNXKkQlScc+wx+eYwtK5ChQBcLhAAmk4khYWx5rtkhFIyIfUUUAFNtZEIQFsF5R5aT/COIgHgXjCUAEhF09hor+vLCkuwSqlc9AxKHm18XZLaloMACPnxWIteUhSi1zWD6SpcGm4C0LP2BECqJ/rbp/57SIpyYIIpeXupd1wiAB/OshMASWYSz+k8nicANNee6ylAo5xSigk2HFUJgLRW92nrbPOOHA1OACQyoUIAaK49R0IBAF792q9rLzV9o2RCkhTFz3GpoJhe++a8YnYebiomFXyrAqdfSepx1GjnUmgB7ARAetbT71FyhGACIEX26FpSZMItaAIQGjQBiCLcPrRTCQGQCvdw/rWqp11Fucdj8p0mVQgADdtLhajUyOEeYKoEAOcce0y+OQytq5DWeliBANBowsA5vFfoWqT5LhmhlABI6TEqUCUAVLqT8zBRAtDrB54AUKOde8HMIwRAqplQWUsVmABIkRxqtEsSuXgtSW3rs1S1dCKsRS8RAHpd0xkCUFJu7xYqEgCSty+pTGGFHCnVRrURYIfhaUH/Rhytkry9qgSg36xNtnk/KxEAvvswzbXnegrQKKdktGMyIUlyUgIgpauY3wUnALsLjipd19q94SMA/0MEQGr6RteSJEXxc1wqKKYEYNN+ngA8gwiAVPCtCky+pNox6mnnUmgB7Nr90rNe1WjHBEAi9nsK7GtJkQm3oAlAaNAEIIpw+9BOWbnXdtNKBADnX0uGNiUAKso9HpNvNEPX4h46NGwvXRc1cri1qJdTUqKhBIBrDkMJgLQW9l5e3lONAEh5odcoEAAaTZDSY1RAc+0lAkALdzkPE60nePuH9exaKkb7XNLsTEqZupmsxUnRqgL3YJC+R2q0SwQAryUV249I3WZbS0onwko0kqQovTe4rsLFhABwdS8AzsJdSWUKX5dkaKv2AXlwWFrQvxFHhSQCQI3j1v0WsPP6zrQTAElnHs95dhxPAGiqDddTgBIAyWjvoUAAaDG3KgE4zBCAXYeOKq2lQgBorj0XhQIAeAV1tn1UaPpG15IUhXDtiEQA6LVv3McTANxU7IUJfLRHFW9N9e+9VDtGjXYuhRbATgCGCgSAEjnpOYgJgETs6ZmQiIlb0AQgNGgCEEW4TgAy7ARAyu/DBEAy9qinXSITeI7H5HWmKQHgHjrUayddFzW+VAiApESDlXs8Jt8cRpUAdEAEoHlPvksuTSfqLxCAq9/1EwDJC00JgJQeowKaaiOpuagU7lIC0PN7ngCoGO2027EUMcGGtsesm7cK92CQvkdqtEs57Xgtqdj+04X2taR0IlyIKikK0XuD6ypcdEyNANDCXUl7HF+XKgGQookPDFsc9G/EZ0JK96AE4GaBAHyQYu/eyxEAmrcvdR+mqTacpChNc5S6CmMyIWny0zonaS1shHrMFCgorXDM2XGw1DZHIgBrQiAAXBQKwC5rKXV9pmtJikI4/VJSFKLXnrWviJ2Hm4pJBd+qwM3OpMgx9bRzEXQAOwGQnD07idEupRPhbscSsadrScTELWgCEBo0AYgi3D60X5PunVJ+H86/lgxt6k2UyASe4zF5mTlKJriHDn1pS0YoNXI4MhEqAeCaw1BlJWktnL4gGY6UTEiFYbjrq0QAaDRBSo9RgSoBUMnbpwXF3afxBEDFaKfdjiXCRNeSXnwqwEZ7sx7890iNdimnvRXq5yDV2tC1pGgCniMZx5SYcE3FisrsBIArfAdwEgBJZhbPkTztqn1A7vskOAHA6leSt5d6xyUCgDu1eky+0RTN25eaj1FPOycpStMcpSJTTCYkAkDTHKW1uk1da5t3iCEA2wkBkMjE6j1HbPM40GJbLgoFYDdopa7PdC1JUQinX0oFxfTaN+TyBAA3FZMKvlWBex1I7w3qteci6AD2/ZL6x1AiJ3ntMQGQiD09ExIxcQuaAIQGTQCiCLcP7eQQCICqoa1MABiZOUomuIeOKgGgRg63Fs1zlqQo/+4gAE5lCKqsJK2F0xckw5ESAKkwrCVq+iTVE9BogiQpqgKaay+RQpW0HVpP0H3aOnYtbGh7TDUCIBEmulZdwtXYaG+qSACknHYbARBS2uhaXDSBeqElRSG6FtdUrLCs0jaHK3wHcBbuSjKzeI5EAFRkgAEA7hmyyDdHKprGkS/J2KME4Ka+/HW9N4MQAKbRFE3bkaRHqaFdFwKAyYTUlCucBGBbfonSWioEgObaSwQAp6GoEgBJUQinX0oFxZmKBOCJJD8BkOo9VIF7HUjvDZpqw0XQAeza/ZKzZ1u+3WjnBDkA7ARAuq/pWiXCdbkFTQBCgyYAUYTbh5Z275QKfDABkLS7qaEtkQk8x2PyMnOUAHDeRPrSlq6LGjncWqoEAIeOPSbfHGZaphoBwN5LyXB0EAChMKxFCARAUhRSAc21l8gXTdtRIQDmdzwBwMaxx+S99rTbsbRfdK26EADchfkPQrOz4T9ttf0+SSIXryXVtNC1uGgC9UKrEgCuqdiRo2oEgBbucoYCJSaSp11FBhjATgCkoml87iVjj6bH3Nh3PjsPd2r1mGoEQFIewukeHpOXFKV1TpLKDE7bkQgAfcZJa9HrOljiJABbD5QorUWNaA40155LQwMAeGGCv+PuwwIBoGRCqifA6ZdSQfGq3fZrX5/DEwDcVEyq91AFljqV5JBpqg0XQQewG+2Ss4cSOSmagPde6ilAz4R0XW5BE4DQoAlAFOH2oaXNeyQCgD25knQfNSaktfAcj8mrTNBoAmdM0Je2KgHg1qKFjqoEgGsOo0oAsPEiEQCaTiQpQ1yJur5KhaiUTEgFxSpQJQA01YbL26cFxW9NVSMAnNFOm51JhXQ3kLXqkq+K15K6HQ9boEYAcEdnKariWIshADR3XPKO03uD6ylwmBAATvkKwJm3zxkKlJhInnZKAKRnyd2Df/bNkYqm8T0k9cig3vFWH/AEAHdq9Zh8p1m691LdwZvE0OYkRWmdk6QygwmA1JSL1nJIa9Hryi8pd8zJzitRWkuFANBc++9X852tn/vSb4T+7VOeAFAyIdUTPITSL1UJwNq9hew83FTsP3UkAFjpSFJDo6k2nAMNwG60S2IIW4jRLkUT8FpSTwG6FleLpnoAACAASURBVBfZdxOaAIQGTQCiCLcPLdXulir8b44gAeCKzCgB4IwJ+tJWvS5uLUoAJO/Lw4QAcM1haG8Faa32g/0EQPIcUwIg9RS4AhEA1XoCKT9eBbTYViIAKmk7lAB0m8rrmFOjnSMAtNmZVEgXTgKAjXbJyBlKjHZJ1QZ3dJb2VIVMUM+x5B2n0QSup0BBaYVtjioB4AwFahxLnnYqAyw9l+782E8ApKJpej9yoDVAEgHoTbr3LtjkJAA0bUcqMsX53h6TlxRVJQA4bUciADSV6/8mqBGAA8VOAkA77krXRY1oDjRNiKtDAQDoPN7fcbeDQAAomZDSiXD6paQotGr3YdtamXuOsPNwTwGp4FsV/0VKR5IYAk214RxoAHbCJIkh0O9R8tpjAiD1FKBrSdflFjQBCA2aAEQRbh9aKt2nQgAk7W5qaEtr4Tkek88xpelEnDFBX9oSAaBGDrcW9Y6pEgCuOQztrSA1troLGS+S55jWE0gG7Z971Z4ASPUEKqC59pKxSg1tjgDQguKu3/IEgBraHAGgvQ6kQjq6lpT7qgJstHtMvtfBJ/PtZ1BStcEdnaXzrEImqOEoeccpmeAkRQ8RAsBJ3wI4C3e5+4wax6oEQFIeuR11mpZqJqjUMff90GfJDQIBwB13PWYKzGc6zdK/UfIw43xvj8krCtE6J8lox2k7UldeSuSktSgx2Vd4zDGHNtyS1qJGNAdKALg6FAB7x90Ow/muz3QtiQBg9ShJUWjlLvu1r9p9mJ2HpaH/JRR8qwI375JqoWjaDudAAwDoPN5vtEvRXto5WSWaIPUUoGdCui63oAlAaNAEIIpw+9BS5Q7pRYtTOSTpPmpoS2vhOR6TzzGlZIIzJmhOq0RMQiEAktGOi8c8Jq8N/S0xOKS17vjIb7xIBICmE0mSon/q5e+uKhUU02iClB+vAlUCQA1tLm+fFhS/KRIAu6HNee2p1KmUfkXXqotiBTbaPSYvdTpk/hbbHEnVBnd0lu4zFTJBDUeJAFAywUmKHixRIwA0bYfzFNLIhORppzLAkqIQ7jQt1UxQpTOuDoU+S65P5K8Ld9z1mDwBoH+jZGC+/o2dAHCKQvR7lHTm31QgAPR7lNaixIRr/EYbbklrqRAAmibE1aEA2DvuSgSAriWlE90/1E8ApILiDEIAVuzkCQBWhpMKvlWBC3elSChNteEcaAAAz47zR0ykaC/9HrmeDwB2AiBJilIJVu697iY0AQgNmgBEEW4fWlq4J0l84VQOyTCh3kRuLVoE6DH5HFNKADhjghrtqtfFrkWkDqX8yw6EAHDa0JQASGth76X0cqQEQPJo//Ht2hMAKT9eBbTYViYAduOY89pTAiA1MqKGNkcAaKGzFMmh1yUVv6mAXhcndTp4Xu0JgKSQo0ImaH2MlB5DCQAnKZpfUm6bw/W+AHASAM5TSA1aydNOZYAl5ZFbB/gJgFQzMSndnubIkVCaAnh94jx2Ldq9dx5DAGj0RSpYfS0EAiDpzGOv/StCV9784nKltSgB4Po+UGNPWot60TnQNKFvmToUAHvDrYcEAkDXktKJsACD9P2s2Gm/9uU7Cth5uC6srgQAF+5KjhBaf8G9PwEA/oMIgKSGRr9HiUw8j9KJpP4xtAA7n0kdcxOaAIQGTQCiCLcPLc3blTxtmABIhgk1JjgCQBUypAcFJQCcMUGNdokA0OtSWUuVAHDScDTlQOpsexvyXkovR5q/LHm0L0cEQCoopulEUj2BCmixrUQA/vJ+cAJAC4olHXNqaHNpO5TkSN8jXasuknX0b+Q8zJQASE3yrkUdnaX0GEoAuLVofYzUU4BGEzhFIWo4cr0vAJwEgOs+Sg1aydNOCYCkPKIiTzyBpDlyxJE6EyQCQLv3zs3KC/o3SvnquODTY/KKQlTpTMVolwjA/qJjtrUkzXoameBqPqjcprQW9aJzoFECrhAdwN5w68FhagRASifCAgwSAUjfUWBbi+vUDGBPC31qTN0IADa0pecgzbWXDO1OKGVKivY6jHaBTODrknoK0PSrvCJNAOojNAGIItw+tPSlLREArMAiGSbUmODWovmx0oOCEgDOmKBFbaoEgAth0rUkox037/KYAgHIUCMAfx1gb5LFgdYTSASgec+ZvjlSQTElAFI6kQpUCQA2aD2mGgGQZAypoc2l7dCIiVRIR9eS1C9UQP9GTunoY0IAJF37a9BaknFMyQS3Fk1pkfLjKZngFIUOKBIAmrfP3WfUoJX+RioDLCmPqKiT0f4EXLSHEoDr3pcIgL15lwoBkLzVr0y2EwBOUYhGclSM9v8KBCC3UI0A0MgEF/Ghajt1IQA0SsAVogMAPDnar7f/wLDF7BxKJqR0IkwAJEUhSgC4Pg0A9rTQJ0fzik+qwHn7UjE3zduXDG2cMiWpx1GjnSv4BrAXFEuSopR8cbUjbkITgNCgCUAUEW0CIIXacTGnFLanxgS3Fg2Pe8wU2F/kfFDQvH3OmKD65Ko501wIU5UAPEQIAKcN/U2GPedYMkJpl1yuOJESACmlpVmP4ARANZ1IBVRtR5JgvYYYx5z3lSoKSS8+amhzBICmX0ldheladdGspmtxKSYfz822zZF07a9+17/WXwQjlJIJbi1q0Er58ZRMcAXFeUWUADiVrwCcefvcfUYNWsnTTlXAJOURXJsk1QDR4mTuu6YRQGnvsdymx0yBOQoEQDJW/0sIAKcoRCM5nceHTgD2Hi5TWosSAK7XCVXbkdaiaTQcKEn4JoPvbI319u8fyu+pg0wI0QSswCZFaJYTAsCpNAHYnUKS5KsqcN6+9D3SvH3u/QlgT5mS0j0pYZLIBFZgkiRF6feYqwlAvYQmAFGE24eWvrSlUDsmAJJ3jBIAbi36cvSYvKeA5u1zxgTVJ5dSkygB4EKYlExIRjslAOtynNrQlAD0ENaiXXI5AqBaUNwUEQCpoFg1nUgFVG1HIgDYoPWYPAGgBcVSESMlE5wnl0ZfJCUNBwGog2Y1vS4uyvERIQCSRC7u6Hz1u3PZOZRMcGtRg1YiAJRMcAXFNHVEIgA0bYe7z6jajvQsoQRAUh7BzyXJAUAjE5w8IXUASASAdsmdvcFJAGiU475PeGP1ZaT44jH5gmInAeB15rHR/vJXfFfe3QVHldZ6laQmcUpntNhWWkuFANA5nBIVgF1uU9pTaoRK0QTcP0IqKF623U4AuBoNAPs74fEkXvJVFVjp6CXhe6R5+5KhjQmAlO5J917y2mNiIjWQpBETrnjcTWgCEBo0AYgi3D609KUthdqxmss17/GGCfUmcmtRD6D0AKMEgDMmqKydatEk1xadEgDJaMf60R6Tbw5DVUektWiTLE49htYTSDntf+jun6NKACQyoQJVAtCyzxzbPC5vnxIAKYeZkgkub5/uvdRUjBrtkvydCuh1cQRg0Bw1AoD7ObTsM4edo0IA6HmWCmQpAeAKiveR1BHOIwzgfJZw9xlNTZIMbSoDLCmP4GJuiQDQdCKu0JHu17XCM45q5M/esN8xhz7j7hnCd2F+iRAArqCYEiYVo10iALSDrLQWrU3glM5ouofUAZcahSpzOCUqALvajkQAqEErRROwBLOUorV0+yHbWlyEBsAuKdpR6PmgCpy2I/VWoAQg5whvaP9zjD9lSkr3pCRHWgsTE0lSlO4XVzzuJjQBCA2aAEQRbh9a6mmTCYD/RXuVZJgoEAD6QvOYvKeA5u1zxgTVJ79ZIACUmHA5jDSaoEoA1jAEYDIxQqU0FKqRz6nHqBYUX9bdvqccaDqRRCZUQOU2RQLQW4UA2MmEZMCoEACq+CL1FKBrhZMAcFGOgXM22+ZIBAAXc18pdK2l0QSu3wY9z1KNBiUTXD0BzR3nul8DOA1t7j6jajuSoU1rgCTlERXVJLoWVzRJCYDk5KAa+SoEQOrC/NIkOwHg6gkoYZIMbWy0S55j2kFWWovWJnB1TjTVRuqAS9NoVOZwSlQAdrWdewUCQMmEFE3AEswiAdhmN2g5ggZglxTtOLJuBAB77aWCb1qALXnacc2ElO65hPyN0lqYmEiSonStXULDQLegCUBoiDsCUFFRAW+99RZcfPHF0LhxY7jxxhth3jzeM4WRnZ0Nr732GrRu3RoaNWoEhmHArl276nQtbh9alYZbAHYC0KK3mmeSy9ulBoD00HEQAMaYoLrWN/VVIwBcDiM1mCSjHXt7PGYKrGa6Q36VTgkA74WmUpRc8ShNaZFSk+iecqAEQFpLBZQASAWYLQgB4PL2KQGQDJirSDSBK9ylna3fmKJGAOrStZJeF0dyBsy2EwCpSR6u5fhTr1nsHBpN4PptUHIsETRKJrh6Apo7LhEA6kzg7jOamqRKACTlERzJke5/mgLI5UzT+19Kv6IKObPWOwkATduRejC8OHGVbZ4KAZAMbWy0S/fPVqIfr7KWx+SjnDTV5t9CB9xQCMCkdGchOoC92FaKqqiSidsRAZAUhSgB4NK9AOySolLTN1VgpSOproIWYEuedlwzIaV7Ltpy0LbW7gLeaH8GEQBJUpSuJfULcQuaAISGuCMATzzxBCQkJEDXrl0hKSkJWrduDQkJCZCWxj8YLIwbNw5OOeUUaNmyJVx77bX1kgCo6O0D2D1tf+6l5plU0duXHmD0pc0ZE1SfXDIAaGSCy2Gk6USS0Y69PR6Tbw9PCYD5Hb+WikSmaj0B3VMOtJ5AWksFM9aqEYArUUqLx+Tz9qmi0EuTeAOGphNxxZy0sZ3UU4Aa7VIDHBXQ6+L+xv6EAEhN8nAk5/KePAGg0QRObpfeG9L3o5KaRAlAdh5PAKgzgbvPaK695GmnzyVJeQTvvaRORveLS3Og979EAGiB7EyGANAopyTBijXfPSZfUEwdJpKhjQuKpfuH6serrOUxeScH9bRLa9EUE5U5nBQtgL3YViIAdC2JTOAeLFKRNvVoc2QPwK4oJDV9UwX22ksEjRZgS572f4wKTgAWZufb1uIkXwHskQlJUjSVrCWphbkFTQBCQ1wRgBUrVoBhGDBo0CDfZ+Xl5dCsWTNo3bp1wJ89fPgwlJTUvAwHDRpULwkAVduRiu2wwfTHt9U8k9xaNNTuMXmvA83b54wJqk8uGQA0MjFwjtODESoBWLXb+XKkaSgSAVApaqUEgItMcM3VuIJimk4k/Y0qoA23JAWWP/cKTgCoolCXSXzuK00n4ggAbWwnSYpSo70ubevpWlxq0oezghMA+j1K/RyoQcvJ7dJ7Q5UAcJGJPQVqBIAa7dw9S+9/ydCmzyVJeQRHmKSuwh+kbLStxTkcaMRESnOk+fEqBEAqwMbdVT0m72Gmak6SoY0LiiUCQOUjVdaqecY5O+BST3snRQLAPZdo7jgnRQtgT79sP1iNAEhkoh0iAJKiUNpW+3X9uG4fOw8TAKmrsCqw117aUyrdKRntuGhaqvdasMnehFHy2uPIhCQp+tNm+1pSrZBb0AQgNMQVAejWrRs0bNgQiovthU79+vUDwzBg715eRYCivhIAlSZZAHZPbvOevGFCjQlOu58a2h6T92BQAsAZ7VSfXJUAcDmM9Lokox2He6WX40SShiIVolIvNKdEQ4taOaO9mmmupkIApL9RBaoE4E+9ZtnmccYxJQBS8RtNJ+L2i0o+SopC1GiXOmCqgBITLjWp36xNtjmc1/4E6ZEhFXPTdCJObpdKd0rfDyUTHDGh6jGcKgyAkwBw9yxNtZEMbUoAuLUA7EXTkjxx7+QNQQ0mSgCkAmyaHpOyzkkAaNqOVH+Bmyt5TL6egBIAySjEBcUSgabFo9JalACs2Ol8xlGj/V9j+bXoPK7OiabaTGCkaAHsz14prUqVTLRFTRilguLFW+0pLdPX8gQAS4pKTcVU0RF57aWuwlS6U+rM/dhIf9G0VO9Fu7BLXnscmZAkReeTtaRUQbegCUBoiCsCcNddd8EVV1zh+HzBggVgGAbMmDFDaZ36SgBoqg1ntAOodZqlxgSn3EHz9j0m73Wgefuc8gA1ciQPIL0uLoeRGgCScYy9PR4zBVbucr4caR56t6l8Hjo1HDkvNC0o5sgENRw9pqAoROoJpOtSQfIae8ddSYHlj2/bCQBnHFNFof+boEYAuMJdKvkoaWnTvT9YEjoBcBATJjLRb6adAHBee65HBkfkaDoRJ7dLlXuk74eSCe66dhH1mE371QgAd8+qetqpCpikPILPl9y9167dzxk59LnUUqhzoukxnFeYpu1I5Os5QgC4FBOaMikZ2ioEgBaPqqzlMVNg+Y4CxxxqtD8jEQAyj+uSTVNtuF4UAPZnr6RqRX+ftNZtCgRg4WZ7SssPq3PZeVhRSOopoApstP9zDN9TgKZfSUb735FqkiQeQRXYJK89jky8L0iK0n4ukqPALWgCEBriigC0aNEC7rjjDsfnGzduBMMwYNSoUUrrhEIA8vPzISsryzaSk5NdPbTU0Jbk9rDOvMdU80xyyh00NcFj8h4Mel2c157qk0sEgHpf+81yhjCpYSJ57e9ED3uPmQIZdSAAV5D8eK4NOyUA3Fpcd2UVAvCmoJCjAlUCcHnP2hMASf2C1hNwBIBKUUoFkdRo5/ZeFfS6uMhEX0IAOK89J5HLGUw0nYgr3KfKPdL3Q8kEd11UPlIiANRrz92zDkNbIAA0Mikpj+DzJfUUeH2KPW+f80zSmgmJAFDjmCMA1Gsv7T3u+uox+XQiWjMhGdpYUUiKoNHiUZEAEHWipducHXBpeozkraYGeeUJ53mma3G9KADsnnZpTymZkNbCXdglRSHqHZ+WyXcVxu8EqaeAKrDRLjUVo3sqGe1YNUkSfKDRVym9D9cTSJKiVMyBk491E5oAhIa4IgBNmzaF++67z/H5jh07wDAMGDJkiNI6oRCAPn36gGEY7HDr0NICWY4AcDnmnIFJjQlOuYN67T0m78Gg18V57amXU0oBeP9Hew4wV8REDRPJaMe5ox4zBdIZ79iEZfZCVEmKkqbHcOoktKCYW6vyhJMAcKF2Wk8gKeSogBIASYKxeU87ceS841RR6DmBAFDCxCn30EJUKR+aGu2cNKQqVIgJJQCc156mjnhMvquwCgGghbvS90PvWW6tHUQ+UnqxU689d89SQ1tSFKMEgCPtAHbVJKmnAE1p4QgMdUxI10WN4xlMWgglAJI8MW6u5DHVCMBTY3hDu8skf0GxRABo7rgKmfCYKZC21UkAaHqMRACoQc6dZ7oW14sCwO5pl5w9lExIa93S308ApIJiKk7wrdBVWEVSVBUPI6Nd6ilA1XakVBusmiQJPlAxB4nc43oCqaCYOnI4+Vg3oQlAaIgrAhDvEQCq3MN57bkUExXPJKfdT412j8l3FqV5+5wBQL2c1yeq5QBzRUyqBAB7jjwmHx7/khAAydN+OUmP4eRQaUExtxaXOsJ9P5QAvC4UyKrgh9VqBKAZiRxx3nH6EpLk72hBMafcQ9NQJGOIGu0H6kAAVK6LFqJyBIBTyOKUoWhEi1PbooW70vejQiaofrwqAeDuWVq3IymK0dRESXkEqyZJkqK02JYzTCgBkHowUOnO5DXOtBD6PUq1Sf8hBICrJ6C1Sf8QjEJ8XVIKHc0dl4x2TCY8Zgr8vOWgY87PW9QIADXIufNMDdovBKMdG9oS2aNkQlqrzYfBCQB9LkldhVUUhVTRARntkqQoTU2SUm3wWlJKK3XkZO3jjXacmiQRALpf63M0AaiPiCsCEO81ALRwl/Palx93GpicJ4caJhwByDlS5liLC2E6CABjANC1JALQ4/v1tnlcERP1TEpe+9b97N17l213EgAqRSkRAOod54qhKQHgvPbc98MRAFpQLCnkqOD71faeApKBSVPH1AgAL39HIyacoU2N0BcmqEUT6kIA6PfI1XIkkigUZ2jTAlmPyfdNoPUEXOE+LdyVvND0nuXW2pZvJwCSkeDw2jP3LI0ASoIClABwpJ1GJiVFIdzF1GOmwLocp649JSZXCASASndOXeVMC6FeeykySa+LSyei+yWpzODrkggA1e6XjHZKchZuznfMoZKPUmSCEgCuSR4lAFwzOgC7oS2ljtG1uL4WAHYCICkK0Wec1KFYRVFIFQ8hqVPpu6apSZLXHq8lvYOmZdr/Rslrj1OTeguKQpRMcP0j3IQmAKEhrghA165dWRWgvn37xoUKEM3b54x2rnsv9yB3EABGuo+mJnhMPu+QRiY4A4CuJRUBdptq796ZyBQxUQIgPTBbke69S7c7w+OUAEipNtQ45lKhqKIQp2vPEQCuqRitJ5AUclRAX46SgUk7FHPpMVRRSOpQSgkAZ2hT9SgpnYh67fOKQiMAXHocpyhE09A4AsAVyHM1EzSdiCvcp3n7kheakglurW35dv14iQCoGO20bkdSOqLfI3fPUvUrrqDY6/U66nY4XXtqaEsEgCr3cI2mqNSp9FzqRAgAl05En3FS0yoc5ZBILy0eVSUACzY5O+BSL7RUsEo98lyTPBpNkIx2rNwjRY4oAZA6bmNHjkQAaN8UqaeAiqKQKnCjyb8JBcU01166H7FsqvSsp3+j5LXH9QSSohB9J3D3mZvQBCA0xBUBSE9Pd/QBqKiogObNm8NNN93k+2zPnj2weTNfiAZQfwkAzQHmCACXmqDimeS0u6ln0mPyIUwVAkDTHKQXLe3eyakY0BQAiQBcR5p3cQVy44gWvdSMiu4DR4RoQTGXtnOsMjQC8IqgkKMC6jmSmrDR6+Ly9ikBkBrgUEUhztCmtSNSNIESAK7+QgVcehynKPTeDDsB4NJ2qBfaY6rVE3B1OzRtR7o3VNaiHWQlLyE12rlIG03b85h8vQr9Hrl7lha/c15hGuH0mLx0LyUmkoFJlXu4HHNKAKTUpH+NtRMATmaSfo9SugomJhIBoBKZkteeRjm4DsVU8/3J0WoEgOsDQqMJktGO0y+lyBElE9JaN/X1E4C7B/OSovR5KcmT3jpgYdDvRxVY6lSqJ6A1U9L9iHvWSMpQNC1U8trjegJJUYh2mud65LgJTQBCQ1wRAACAjh07QkJCAnTr1g2SkpKgTZs2kJCQAIsW+W/mtm3bgmHYt6aoqAgSExMhMTER7r33XjAMA958801ITEyE4cOHh3Qtbh9aFa89p92v4pnkGgFRz6TH5EOY9MXNGROUTEgqIFS6790Zzr2lBEDy2l/9rr151xKGANBmVBwB4DzHnCeHEgAubYdTj+HUNmhB8cuCQo4KviMPe8nDTK+LIwA0dCzpk9OaCY4A0HOjGk3YVxgaAeDIF6co9O6MLNscjgBw9TFclIPWE3B1OzRtR0qPofcslwK4JUQCwHntuRRAlXRC7p6ltS+ccg/9XR6T17WnBOBPvfhmh53H2/P2ub4JNJVL2vtnCAHg6gk259mbd0ldhTExkVS0aEGu5LV3Nihz1iZQzXeJAFCPPNcHhHajlYx2nLbjMXmJXEomuMZ2AAA39vVHcu8SegrQZ6+KolBdCcC9iABI6UT0eSl57TGZkOqq6DtB8trjLsySohDtM8MRbTehCUBoiDsCUF5eDl27doWLLroIGjVqBK1atYI5c+wvE44A7Nq1S1Tx8Xg8IV2L6wRAwWvPSXdynklqmHDNe6hHy2PyRYVUu58zJqg+uUQAaEibK2Ki3leJAFD5SE4hYyxpRsV57auY5l3cg5wqCr3KhHKPMilaKgRAkshUgQoB4EgOl7dPX2iSPCGVFOU87TSlTep2SqMJuSESAKr57jF5RaE+0+0EgMu159LjuL+R1hNwRjv12ktFrfSe5SKA2XlqBIBK93Jee+5v5KKJtHCfu2dp6hv3N9Lf5TH5uh1KvqRu51S5hyNy1GEi5as//Xm6bR5HAKh2v9TRWYUAUG+8ZLRTAsCpE9E8dEmyknrkORUwmk4kGe20/oqrc6Jkgmu4B2BP5ZSailFHjlSbgImJFE1QBe51IMmT0mcvV9NC15KeqZTkSF57XE/AdaMHcNaYcRLZbkITgNAQdwTgZILbh5YaAJzXnvNMcoYcNUy45j00n1gyKCgB4IwJGk2QlCGo3rYKAZDSdqjnePFWp0IGJQCc157T7ue8L1RRiMvlVJWPpAXFUlhYBTTcy8nycSSH82hTAiDJE9JiW87TTlVtpBcfJQA5R5wKTCrgomNcPQElAFyuPSW0HpMvTqb1BJzRTr32lwsGLV2LcwBQL7TkcaRpO5xeOEcAOKOQ1u1w9ywlvlbefmFZJUxYtouNNnhMPmpHU5MkAkCVe7i9p2dCkhR9akxwApBJpDulWhv8jJPqXqh3XCIAtM6Bq02gTZ8eT+LViRwEgBEBoOlEXFQFwJ624zF5RSFKJrjGdgAANyACcIcQVRmz2N5UUCUyIUUTVHH3YH+9ilSbQPu5rBHSdjABkKI9tF6Na2wJYK9N4LrRAzjfL5xEtpvQBCA0aAIQRbh9aKnRzhEAmmvvMXnPJDUmuOY91DDxmDwBoJ5czpig+uRSri0ttuNUDGgRoCSRSY3QRYxE3ueEAHBee066k3v4UgLA5e1zXmju5UgLiiW1EBXQ4jFO6YTLj+cIAK0nkIoTVQgATWmR1lKRYOXw+jdr4P6hi33nn8vb5+oJqEcb59qnbT0E0zJz2OgYl5rkIAAKRvsfhGLbt3+wK2Rx9/+m/YoEgNTtcGk7XA0QdyZo2t47yRsgY9dh+HThNl/EgCO+WEcdGy3B7llKFiTCRJ8lKl3FpYLif45ZbpvHdZqlhbtSLQdOTZIIADWOJa89rXPgiAntICvJk1LSwaUALthkJwAqXnuPyacTUTLBNbYDALg+MTgB+CzV3lRQIiY4MiFFE1SBC9YlMqGatoPJRMeR/PdDnVVcehyAvZ5AkhSl0QQu0uYmNAEIDZoARBFuH1panMil7VBD22OqeSY5AkANE8mgoASAMyaowSQRAOppe0eBAEgNpKiqDaeRTT1HHAHglHu4ngLUQ/NfhgDQ+RcB9gAAIABJREFUxkMekycA9LqkYkEVqBAALspBjfaF2fmOqIpktNOeAlyqDSW0UqEjTSdSIQA4FcaKxHBeZs5of4cQACtvHxMIqqIjXRe9Zzmv/cZ9zvuMa973xhS7p/3/JqyC/3292mb00bWklANKADivPRfl4L5HGrXr9YN//6wcZO7cq4yF2flQWFYJpRUnYHNeMSzcnA+jF9nvjct78gSAFu5yjgmq5iTVEzw52k4AOMOXymhySkcA9tQkKd+bGtqS0U4JwPernVKntEmW1LSKEgAuckzrCSQCgI12j6lGJrh+GwB2MQeproJ2tpaiCTgyIa0lgZKY21GvA2ktmhYqpe3gxmmSohB9J0hee1ybIPXISVpkJ0ycQIab0AQgNGgCEEW4fWhpceKA2ZvhyNFKWwoJzSf2mLyXkxomnHeMM0w4g4KqE3HGBC10vEYgAI8nLbPN42TMaBEgp0TDpbSkZjs1sulDlUvb4fL2udQEqijEFe5yKk2c3B7VyJc8hSqgBV8cAeCiHLsL7L0OOAPtH6OWwYy1+xwN4qhsKkdC6XmWQt80mrCnIDgBwI2UrLxurqidqyfABqzHrCkMPVFVbUuRoApT1qB55vRv5Lz2G3KLHOuMWbwD5mblQcq6/TBk/hY2csSdx6x99rUkpRCq3MXds6r7RUn7W1PX2f4fwKm3rzomr9jj6ANBB1aZqThR5TtrNG+fU0ShksISmXgiyU4AmvZwKttQr73HTIEOw9Mchi3+d4kAzCVpO5JRSMkX1+tgJiUAgoeZ5uTTwn2v1+uoJ5AM7b+Q+4OLAFJiwsnt0rXaDlzIzqE1LdJauKD49kGp7BwOFunE6YC4p0A7YS3qtZeKbXHjNKmgmBrtktcepxNxPXK45w1XH+cmNAEIDZoARBFuH1qam/zsuAxo3nMmtB24EFKz82Hv4TKHQesx+Zxp2nCLdgJduDkfepI5kkFBc7mtF3f58SqfJ5PWE0gE4FHUxER6aVMCwIXHOYN2oQIB4NJ2uPQFLppACQBXuMsZQlyKFt1TyVBQAc1D9ZjOSA4X5cAF39Sw5Ab2Wv+BRF84AkDPM/0et+WXOOpePGYKzN94AP4zLgOuT5zHqp4AODupjlm8w/EC9Zh+YlVV7YVN+4sd5w+PpUiZhZIS+0v+COQWHnNITHpMPmqHZftCHbf0ryk4pS93iQBQBaY+07NgW34JnKiqhuNV1fBNxh5HDr3HrCGFny7cBv83YZXPqPs72bOOo+wk3uv1svUXKgPro0vDIgBerxc6fLoELutec69TAsB5QykBaPaLYV9d7YUh87fA52k7wev1OhwTHrOG2Iz6eTvcP3QxbNpf7Mi1p3sA4KwT8Ji8cUzTdmiO+d7DZZCybr9DnWjKSmcvHCpF6TH5/H5KYPBzafC8LXB94nwHoZXSdq55z67AxkXa6HOJK9IGALgWrSU1kKTnWVoLpyZJRjsH+r0DANyGegrcOoAnJjRaJRXb4miCVJxM05wkr337wX4C8MaUteD1emHXoaM+CV8u3Q6n2nm9Xth7uIxVbooUNAEIDZoARBFuH1qam6w6mvWYCZ2+WGG7obl5Vk4hp/9tjfdmbIRFWw5CxYkq33pU8g2PB4YthqpqLxuZeP7LlfB52k44WFLhU4noQIwhTsaMFjpz3jFObpPrkkkf0JgAlB+vgqpqL5u+sHBzPvy0+YCtsJgqUXCFu5xRuOvQUUjfUQAfpGz0ed3od/305+lsQzeMkvLjkLWvCKav3Weby5FCj2lX5uAiE7jOIZgX1mPW5Oe2+fAnWzjbGn95fx78tNnepIim2uA0B0ryAg0Oq3Y7Da1AP//mt2uV56uMy7qn2ELx1vggZSO8OHEVtOwzB8Ys3sHW7IQyLGUnSgCkokNauG+NV79e7SgQlMbH87Y40su4cVPfBUqGfF1GbuExm/rJE0nLHXn7XHofNcit+gtM9rBxZg3LEFW9vqMVJxyROGtYCjI7Dx2F579cCZNX7HGQl1v6/+TTgX9l8mrxmfs10wGXdu/2mHxEkRIATEykv6vNhz/Bll+6w+cWHvM1SLyqj12BjUbt6LPSY/JqW/R3SwXfVIrWqtvZuK8Y3p2RBTsO1lwXTk26beBCOHy0kk3BxKDywW9MWQtTMvbaJEU9Jv8coka7lLcfKJpQXH7ckc7mMWWvPX7+vvr1at/z/5XJqx2Rf2tYUSr8PuRSeSMFTQBCgyYAUYRbh3ZdTqEjBB3KsF6AVCqQPsQ4j5H08KeFr9y4g3mBcoOLOHAyZpzS0a5D/nSVvKJyh8qJx0xxGKAAzrDqrQMWwsLN+b4Xym0DF7K5458u3Ob7b8uzSMO9L05cBV6vF4rLj8ORo5Ww69BRRxGtx0yxNXh5+vN0WL3niK2bIx6PjFjCqgYdq6yyqeX87+vVsGZvoaMQEg9c0M0pvvy85SB4vV7WgAh1rNp9GI5XVcPirQcd6QtWakL58SroONLpcZUG15yqNgSAKhtFclypQKRCGZaqFpWixATA6/XC3Kw8yM4rEQmAtZbK78RdVU+2wT0vX5xoJ+Rc3YvHrHkGSqQZD+5elgatuaKD64Icyug7cxM8PGKJr26Fk/e1BpXmpEW5G3KLoOJEFasGh0fL3nMgr6gcmvecCX/oXtMlvSWRYN64rxh+WJ0L9wxZ5Og3YI0/95rtcyodPloJs9bvhxU7DzvmvTsjC3KOlEFhWSV0n7YOktfkOuqJPkjZCGWVJ3xEyfLQX5/In+0VOw/D9oPO7u45R8ocjQitQdfacqAEvkrfA31nboInkpbDW1PXsc3tOo5a5th7ei9ZKkaFZZUOMmgNHIU+UFwOvZM3QOKPG23EpDbRxddIE07rXnADmgCEBk0Aogg3CUBdXwzWyNxzxNFREI+DJRWsdyaa499frLA9MDkC4DFr0ivoi4COpz9Pd6iWhGPQpkPWoJ6wcAwuvE0L+FTH9LX7WLUXj1njRcPqFOEYbT78yZEeYI1HP1sKpUy9RbDBKZ/UhgDEwrht4EKorvY6eoVg1ZGUdfujcm3RGBzRogXrUqTT6/U6iqQjPQKlD4U6qFecG1gGlxKAUAcXncDKNIGGVTclGb11GbRgmhuZRKXn9SlOozgcA5Pshdn50FJ4T1DRBTxmrN0HP6zOdXSDDudwC5oAhAZNAKIItw5tqAV0sTRw8VWgFKV4GV+l20P94Xp519dBC93jjQB4TN7LjA2acHiY6/Og3Ye5YkiPWZMfT3sbxOrogVIsqSpPtAbtR+DmoGprtJ7lZBq0+D4SQ0VwIRzQBCA0aAIQRbh1aAOFcesymvWYqZTbHY1BU1ewzrImADUD13TUJh0hVgeW2ItHAsANTAAeFtLK3B40PcTNgdM8qGxnuIYbhlko47GRzgL3Tqj7NpX4jMdBhRtoHUk8Dq5TfbihCUBo0AQginDz0N5AGqsEG7R5EjfuHvxzWBRIrPE6k0MYysg5Uga5hcfg1gH+vMg2H/7k2wupa2io4+nP0x1qGifLuPrduQ5FHWtg3XmVnGXVcUt/uagbnx2394IrxsTj4RH+YvBYJgCBFIjowKSIqvV4zBQxHcsafx3wk1iPQgeVm5SGak1QoDEnKy+kNJ2+M/1qZ7i2hVM8CnUs3R4ZYuExa2o6Qv1Z2vTQY9rVxaJFAGh/i7qMuqYOYUIE4Oy0TMfgeVvCenae/3KlQ9K0rkO1pkcabvQI0AQgNGgCEEW4eWiPVVbB7YNS4c6Pf4Zdh44G9dzTXGA6Lu85C1bsPMy+FDxmCoxN22krKg02/jlmOeQXl0P3aetthgaWJPOYKXBzvwUOSUmsBkO7elqa4jf1XeD7DBMArOssPsC2H4Lqaq9DAaHvzE3w3aocqKr2whKk+tF92jp4cFgaawhzkqdYd9ljpohKC3TgQmJp3Nyv5u/m1IOwSg/uG0C/N6opHmx0n+YsxqaDKxqm44p3ZodcKHr/0MXQvOdM+G5VDrw4cRW8PmVNwMJVj5kCrVB/g3ARAKrSQxsOXdY9xdao7LVv1jga0KmODsODK+XM3pAHszeo5/JjAkAVtjxmStAGXQDODrcSIag8Ua1UvB1IajXYeCJpOSzYVFPMHwrptYorAQAmr/DXQnFND+l47suVQQvGLWWWcJw9j5kCE5fv9hWbPjJiCXi9XsczVXUUlFbAU2PSbTnjWA2Iavxb4z5GzUp14D3mRtMeMx2F69a495PFkJ1XAm//sB7Sth7yKer0+H49FB07DjsPHbUpP3nMmqaKfaZn2XLq84vL4VBpTW1bbuExWw3ZQ8PTbN2gm/ecCcdRvZlV29V+8CLHe2vLgRLwer2QX1IOXSatgusT58GrX69m7+Nnx2UoEd95G2vONu3U6zFrmk+++e1a27tKZUipbtYIFuV4/0dnA71wQxOA0KAJQBQRjUNrpX2s2VujDDQnK89RBJS+o4D1xmXtq1F9KS4/7pN4211wFC5/exZc+c5s+HrFHpi4fDekrNsPXm+NLrpkYGPZsl4/bHDkCh6vqoaMXYeh/HgV/LzlIDz9eToMmL3Z57W2DPvxS3cBQM3Lp8OnSxzNuqx+BVj/GRuf367cC1XVXvB6vbC74Ci8k7wB1uwt9HmzOo5a5tOnr672wpYDJWJIM23rIZiTlWf7DL/wb/8o1dEB1jKwMnYd9l0n1hbHxg5uMPV4Uo0SBN3XsWk7bSpNWBN6d8FRuPpdv8cWdyPGXqOqaq+vGNpqrkVJCh4391tgSw+hBOanzQcchX0AwMp94tFv5ibYll8KV787F54akw6Hj1bCP0Ytg39/sSKowbVpf7FD7SiYUY9lV1fucqqHWANLrHb6YgXkHCmDJdsOwbTMHFv/gP6zNzt04suPV9k8vCt2HoatB0rglcmrYen2GuOPplrcOmAhrNh5OKAWfrtBqTaPNEcirM6yVdVeeCd5A/SduYlt1mc/n36SSPW/cXqQlPMO4OwBsWx7gU1l562p62DT/mLffZ+dVwJbDpRACyHVJ1heNUdU8PVYoApkf+o1i9Xrx+OH1f6CcWxk0e+ZjgeG+ZszcU4Aj2lvDrZoy0HoPD7DFq1ZveeI7/lNDVc8Bs3Jtnld84vLIW3rId/9sOvQUegyaRXMWr8/YARnzOId8NjIpfCH7vZicHwWcBNF6ii47v158NDwNDh8tBIWbDoAKev2Q3H5cRi/dBcs3npQFDjwer0wYdkuX1fiTfuL4ZuMPbbz8PG8LbAhtwg27itmU1xzC4/ZDHGAmndfzhGnPv3avYUw4Jd7FaO0wtlg0benJeWQvCbX1+141M9+NTj8c1YqaodPl0B1tRf+OWY53NR3Adtbx8KJqmr4Kn0PPDN2BXSbutYnM+r1em3P7zGLd/iUd67qMwe+WLLT97dxymsYQ+ZvgdsHpcK8jQdg8LwtsHCzvUv7de/Pgy+W7PQJJHA9UKzB9VrBg+sZEW5oAhAaNAGIIk62Q4uVcqqrvT6Pab+ZmwLm8R0sqWDbvgMAvIIUc+4futj2UN5TUAZHAzxka3O9Eiyj+VrUOIwSAAm4V0GowJKotw9KdXjtcUOtjfuKIf+Xhlf7i475uuNOSt8N32TUFO0WllXClJV7fXr/FhG64p3ZvmZZ1dVeuH/oYmjaY6bNyw8ANlk83I3Y+q6bokZGq/cc8b3MOAIwZP4WmJaZA7sLjtrC/z+stns5LZjf1Vyr1Uk4kCeqdb8FUFhWc6ZOVFWz34P1tz88Yomj+670gqWShLh76WvfrPHNo17rmev3w2vfrIHZG/ZDQWkFtB24EJ5IWs5KiO4uOApTV+XAscoqmyoR19iNAzZCLXlOC9J+lR+vsp3rv3+21BFlsYxsjGD9EjABsPoSXJ8433dOLUwXpF4BnDU3AP5zeH3ifLE/hUQqJi7fDVf1mQMt+8xh05IkgtCMdN/F3uVnx2VAfkk5LN9R4DO67xmyCJ4dlwETEFGYlunvlIsb93ERtqfGpEOP79dDmw9/gs15/r3/Kt3u1V6YnQ+vf7PG0Q3b+n4mLN/tcJBI0R4ruqGKvKJyWLa9gI0KBYJFsp4Z6095wQSAayhGUXmiGqqrvbBxXzFc8c5suLznLJscM0VVtRc6j18J9w9d7DAqqQSlG3nnGDgSjq/NSil6BKUX1uWdknOkDBZsOuB791WcqIJVuw87/l7aJZmKPnCwrsvr9TrIE0DNWTzEOCFwhGBS+m7YcbAU3v5hPTwwbLFNJSqSONlsqfoCTQCiiHg4tP/72k8AuEY6kYbVLbZlH7+CBzaMpq7KCfDTdQd+sd4+KNXmKfKY9m65ocDr9TqMMYAaT2pBqbNDMPaCYx1oS/KPplBZwATg9W/WQJ/pWY6XxLyNByBzzxHb78BGdUn5cZiyci/koq6eVKe7d/IGVk+bw7HKKpiTlQdHjlZC5Ylqm9fbIg8cqJFz+y/RqP+iJm40D5uiNi/xMYt3QJdJqwJeEwYuAr3hA3vnUnxNHYanwY1958OEZbt8//76lDXQsvccX8MgnB4neeKsHOTW/RY4Xu6YQFp1G1QPH6CGMI5I3QZTV+X4olyfLqxpDnSUSLNayNpXxHZ4tnCwpAKSFm131BnNycqDkvLjUFpxgs2xphGAPtOzYNCcbF+TKQtFZcfhyndmw2XdU3yNngBqCAs+ozhlEBu2OIWouPy4L2pmNUWSkF/sjxZYUdXaAhOA2welQuUJniTXBl6vF17+KhMu6+5PJZFgRSatCCEA2KRIcY8QFRyrrBKdSCqgjfiqGWIeSeBoEn7uWpEuq0eJW6DpWNPX7gvb2thp8tDwNACoceYs214Q5Ccjh3iwpSIBTQCiiHg4tK8iAoCNQbdgvZSvfGe27zM3CQB+EN8+KNWRd2x1wXQLa1ERIG5sZu3TFWifMDABCEZaqqu98OTomlA3ldekoB6lD2dtrv0f9Qu25ZdC634L4PUpgc+ZZRQPmpMNAP5UJJwCRBVe3ATu2mnVcFhYueswPDUmne1KbQFHJQrLKuGNKWthUvrugL/T6/WyDZsyEAGwiqhfVohkYLJDUzRqC4vEc+eWNoPzmDVqNQs2HYDLutf0AAmEvKJy2BnA62zNsdaejDrljkRkvqyyJlIWKG0EY3NesSOtpjbAJIfrdh5p/OOXKAvuvo0JQKjEJlRY0UCPWZP+5jZw92tMaq2alieSlgf46fCDdmWeuX5/WNfffrAUhi3Y6pqHPxjiwZaKBDQBiCLi4dDi0OzrUSAAlmcbt4DHhZnfRZgA4Afx7YNSbWkDHjPF4ZWMNHA+Nq5X4CIlGLUhABZUvHC0R4VllIcKFS9odbUXth4o8V2f9bc9jwoaqZa4m3gWqYLc0v+n4D8QRny3KscWgcAE4LZfCrJDieRZ6701dV2tf7YvESTAkSuOAFipTgWlFWHxBB8s8ZPUCcv9RAqn83HdtSMJTAB6J29w9XcD+OUtH/1sqe+z2Rvyav2MCBd6oC7wzXvODP4DYQZujomjR1bBO20iF2nQbsmzN+QF/6F6jHiwpSIBTQCiiHg4tLgTYjDPbCRg5bbj/F83CQB+EN8+KNWhzhAo5zUSwAXC2Ctk5dDTnHMLoRAAFZSU21VkBs/bEra1VWEVND6LChoXks7IbgKntdw2cKGrvxvAHv2wUokAwFfI/caUtbVeMzuvBMam7YTi8toXBH5E5DpxgSsnaxlu4Pz+cUt2+j7HBf1up5zgtKh3Z7j//rBkj//2qT+3Hac7uk0AcKrbn3rxaYyRxHer/H1UcL2GlapF5UEjDZrCOD9ISld9RzzYUpGAJgBRRDwcWqzRHIrhUFd8jNRtLO/w7oKjvs9wUV8ksBQVurYblOqQtcNa/G5gW36p73fjvFBLupPmnFuIFAE4Vlll2w/csdktWN7Uf6GCRtrV1E10meRX5br9o1RXfzeAvTgbE4Cb+i4I2YtfF1Dp1PQd9lzjSBOAYkRSsQyoRUyikXKCCUCiCzKLFFbdyIPD0nyfYQLAFZxHEjhNrEVvPooZSWC1N1zDdP/QGudC5/EZAX46/KC1VQuz5ZTBWEA82FKRgCYAUUQ8HFpcnPXmt+4TgKFI397KjXaTAGA1mXaDUmHKyr22B3OwHPlwY9ch/m/v+sv3RHPOLUSKABwnUqZW4aibsJRknhrjD9NTSUM38V+knIVlXN0CJq3Y2L4+sUbSt4fLOedUghD3JgCIPAEoq/QXMY/6ebvv8/6za6KL0Ug5wbK7/WZtCv4DYcZzv0Sp7v3EL2+KlWfcJgBWDZPHrGl+6Daw2huu67Kemy9MWBngp8OPzD12yeNFKG0uFhEPtlQkoAlAFBEPh7YrIgBdo0AAuDxdbARbWtORAtaFbzcoFaZl5tgezFR7OtKQFE2sLsxSznmkCEB1tb1AFBtYbsGSjXw8yV/QSGUR3QSum8EGllvABAD3irj2F834d1zOOR+/1K7Xv3Zvoe3fe36/PqLfVcUJf5QKE1SrNiEaKSeYAAyYHXrhfKh4ceIqB0HFBADLnroBq9bLY9Zo2LsNqf7BEhh4aZKaBHC4sC7HnhrnRjfeaCIebKlIQBOAKCIeDi1WZ+g21X0CMIpR6nCTAOAc5XaDUh2dQOsifRcKJEUTq19DWyHnPFIEAMDuwcUpFm7hydHOgsaUddEjADhqhhtIuQWcP4wJgNW4qc90d59XX5O0Oaowg2U1I+GNr0IkFaeoWQ3vWkYh5QR3U/5obt0K50OBFaW6fVCq7zPcPDI7z111swGz/c3VWglpjJEE7oOyLsdPUDmJYTdAm+8t3xE9iU43EA+2VCSgCUAUEQ+H1mr+5DHdzx0GcGp1AwDsdJEA4CYp7QalOgxLN7okYkiKJi9NygSPmQJ3fsynnGACEO7wPt4PXGTpFqxmPbigkTa2chP4numArsktYAKAtb2vfGc2eEz3c86/X22PmlHjEndIllSs6gIsY/oxKlK3Ck+vec/9lBMcAYhG4bwVpbp1gN9hgJ9tbhOAj1GheGshjTGSwKIBuEP2rQNqlLPclsDecsAu6UsbQsYa4sGWigQ0AYgi4uHQdp/mN2bM79wnALRbJ4CdAPywOjeiv3/T/mLf72o7cKEtVOwxU5R1w8MFrGjyBTK2X5hQk9N7z5BF7M+5RQBwUyu38O8vahRNcEGj1M3YDeCUlr+jqIRbWLbdX7eCCcAf354FHtP9nHNKmmmjONxtOVJKY8161HQHHjjHn25jSU9en+h+ygluBDYsCoXzVpSqzYf+lEH8Pbnd3wQrMuFrcgtYOQtL51rKWW7Xv20/WGq7Z+rSc6I+IB5sqUhAE4AoIh4OraUuEy0CgGU3D5bUdGh0kwBgT0zbgQsd6jLlx93VDy8RFE0s7fn7h/IpJ24RAJWW9eEGV9CIZf3cJgC9kaRhx1HudhAFAFiOCteXbvfnDnNGsBuYT7qa7i5wSudOXL4b3piyFoqORSaixpEfK73xxr7up5w8OMxPAKJROG9FqfDfLhXCugGsFOV27wwAO2nG98yNfedH5d2Hpa49pj0tKRYRD7ZUJBB3BKCiogLeeustuPjii6Fx48Zw4403wrx5ah6c3Nxc6NixI5x99tnwq1/9Cjp06AA7doSesxwPhxZ7M7tPc58AYNlNq2vhDuQdSV4TWQKAZTfbDlwIqURf/nhVdUR/PwWW3RyJCm6t7rMdhqexP9d+sDsEYErG3uA/EGZwBY1UrclNWLnlHtP9DqIAhAD8UjwopcG4gcVb7U2NcKMlt8ClP1kSx9HwON/3yWL2PnYLPZnoByYAW10mAJ+l+mu9/jrA/e8jY5df7GHxVr/izvWJ88Bjut+tObfwmO2ecbszs9uIB1sqEog7AvDEE09AQkICdO3aFZKSkqB169aQkJAAaWm84WOhtLQULr/8crjgggtgwIABMHjwYLj00kvhkksugYKC0Aps4uHQvv0DJgDut6yfkuE35HKO1Gjuu0kA8O9qO3ChLVTsMd1vIFR5wi+7Ofwnf+qA1f31kRF8zrlbBCDSjdk4vPxVTf0D1tynhaduAne+dbuDKIBdutYiAFIhrBugmuYHit1VzgLgC6D/93VNIWw0mrXhiFw0Cud7M/UPM1DdzLZ8dwkAloqNBgFYjWQ3seb+Nb8oZ7ndrfkAKoz3mO7XZLiNeLClIoG4IgArVqwAwzBg0KBBvs/Ky8uhWbNm0Lp164A/O2DAADAMAzIy/A09Nm/eDA0bNoQePXqEdD3xcGitDrMe0339cAC+Q+P2KBIAHCp227AEsMtuDpnv9+Q+nlQjhSmlnLhFACL9fXB4lTHkJqXvjtr31B8pmrjdQRTATgCW/EIAJClMN0C7/R4qrXD19wMA/OX9Gk9urx/8htxLDHF0C5a8pMdMgbFp7hfOv/+jUwFpehQJwOdp/lqvaBCA9Tl+sYd5qOtuy941xPG9Ge4WzuPC+Gh8H24jHmypSCCuCEC3bt2gYcOGUFxsN2D69esHhmHA3r1y+kGrVq2gVatWjs/bt28PzZo1C+l64uHQ4nxmt8OgAPYOjTt+KR6MFgFoNyjVFiqOBgEAAPhD95rfjeUDHxtZ0wzrydF8yolbBODHdfuC/0CYwaVyTFi2K2rf00dI0cTtDqIAdo+7RQCk1DE3gAvpPab7ylkAADd8MN8Rxfy/CTWpY+0H84XzkcQdH6X69mP80l2u//5+v0Sp/txrtu8zOwEoDfDT4QfuFYGVidzCxn3+Mzp7w37f51f8kjr2QYq7BKCo7Ljtntl5yFk3E0uIB1sqEogrAnDXXXfBFVdc4fh8wYIFYBgGzJgxg/256upqaNSoEXTp0sXxb7169QLDMKCkpPYMOx4OLW7R/vYP7hMAnJf6eNIy6Dw+A55IWu77bPrayBqcNAJAOzRGA5f3nOW7ns7jM6Dz+AxfioOUcuIWAZi1fn/wHwgzrGLOy9+e5dsP/Pe6/T0Nmb/F93uf+9LdDqIA9nzmh0csgc7jM6B9v214AAAgAElEQVTTL0pJHtP9lJMdRNHEbeUsAICb+y0Aj1kjMWmdEasz8n1RaNbWbpCfAExEcr5uwdLdv6x7im8/Hhjmr0ugSk2RBhZ7iAYB2IrEHh4clubbk8t+cbZ8OMvdwvmjSBnLY/qj37GKeLClIoG4IgAtWrSAO+64w/H5xo0bwTAMGDVqFPtzhw4dAsMw4P3333f824gRI8AwDMjODtyMJT8/H7KysmwjOTk55g8tbtDSd6b7LesXkqJbOnC4NhI4hEKxb3671qHPHA1YHV258eLEVezPYDnX/UXhLcK0jCuPGZ2W9bjoVhpuAveuePVrdxsIAdh7V3ADN5BzA7h3hcdMgcoT7hbOAwDciVJu6Og40n2lpkc/W+r7/ZHuZcIBd1jnxj6XC7Vxr4hoSOfuI0W3dOB6KzeAa708ZnTS5tyEJgChIa4IQNOmTeG+++5zfL5jxw4wDAOGDBnC/tzevXvBMAwYMGCA49/Gjh0LhmHAmjWB9af79OkDhmGwI5YP7e6Co/DvL1bAv8au8KXguInKE9XwxpS1cP/QxY7x2jdrXJHhTFq0HV6alAmFZZXg9Xoh8ceN0OHTJVEpeAUA+HblXugwPM2xH48nLRP1oouOHYeXv8qEEanhz/9esOkAPDJiCbz57VrXVZEAalLC/jV2hWM/rJdnpssa2vkl5fD8lyvhydHLYUOu++odXq8XeidvYO+ZLpNWQWGZu92rAQCGLtgKDw1Pi0qjOACA2Rvy4OERSxz78ehnS22qL24hfUcBdBy1DF7+KhNKyt1PidpfdAw6j89gz8igOe53Ji4pr3k+dRy5DNKj1PX2o7nZ7H50Hp8RdqeJCsYt2QkPDU9zvWg/GtAEIDTEFQHQEQANDQ0NDQ0NjdiBJgChIa4IgK4B0NDQ0NDQ0NCIHWhbKjTEFQHo2rUrqwLUt2/foCpAN9xwA6sCdPfdd0PTpk1Duh59aDU0NDQ0NDQ0Qoe2pUJDXBGA9PR0Rx+AiooKaN68Odx0002+z/bs2QObN9ur9vv37w+GYcDKlX5VjuzsbGjYsCGYphnS9ehDq6GhoaGhoaEROrQtFRriigAAAHTs2BESEhKgW7dukJSUBG3atIGEhARYtMiv5dy2bVswDPvWlJSUQLNmzeCCCy6AgQMHwpAhQ+DSSy+F3/72t3DwYGhFYPrQamhoaGhoaGiEDm1LhYa4IwDl5eXQtWtXuOiii6BRo0bQqlUrmDNnjm0ORwAAAHJycuCxxx6Ds846C84880x48MEHYdu20FVR9KHV0NDQ0NDQ0Agd2pYKDXFHAE4m6EOroaGhoaGhoRE6tC0VGjQBiCIyMzPBMAxITk52SITqoYceeuihhx566BF4WJLqmZmZ0Tbr6hU0AYgirEOrhx566KGHHnrooUfoIzk5OdpmXb2CJgBRRGFhISQnJ0NmZqZrDFlHG/Qe6v2rv0Pvod7DaA+9f3oPoz3o/mVmZkJycjIUFhZG26yrV9AEIE6QlaVz5OoKvYd1g96/ukPvYd2h97Bu0PtXd+g9rBv0/oUHmgDECfQNU3foPawb9P7VHXoP6w69h3WD3r+6Q+9h3aD3LzzQBCBOoG+YukPvYd2g96/u0HtYd+g9rBv0/tUdeg/rBr1/4YEmAHECfcPUHXoP6wa9f3WH3sO6Q+9h3aD3r+7Qe1g36P0LDzQBiBPk5+dDnz59ID8/P9qXUm+h97Bu0PtXd+g9rDv0HtYNev/qDr2HdYPev/BAEwANDQ0NDQ0NDQ2NOIImABoaGhoaGhoaGhpxBE0ANDQ0NDQ0NDQ0NOIImgBoaGhoaGhoaGhoxBE0AdDQ0NDQ0NDQ0NCII2gCEOOoqKiAt956Cy6++GJo3Lgx3HjjjTBv3rxoX1ZUkZGRAS+//DJceeWV0KRJE7j00kuhY8eOsGXLFtu8Tp06gWEYjvGnP/3JsWZ1dTUMGDAALrvsMmjUqBFcddVVMHnyZLf+JNeRmprK7o1hGLB8+XLb3KVLl8Itt9wCp59+Olx44YXwyiuvQGlpqWPNeDur0vmyRm5uLgAAtG3blv33e+65x7FmrO5haWkp9O7dG+655x4499xzwTAMGDduHDt306ZNcM8998AZZ5wB5557Ljz99NNw8OBBx7za3LOqa57MUNnD6upqGDduHDz00ENwySWXQJMmTaBFixaQmJgI5eXljjWls/vhhx865ubm5kLHjh3h7LPPhl/96lfQoUMH2LFjR6T+3IhA9RxG6t1R38+h6v4Fei7eddddvnm7du0S53399deOdev7/oUbmgDEOJ544glISEiArl27QlJSErRu3RoSEhIgLS0t2pcWNTz66KNw0UUXwSuvvAJjxoyBxMREuPDCC+GMM86ADRs2+OZ16tQJGjVqBBMnTrSNGTNmONbs3r07GIYBzz//PIwePRoeeOAB8SEUC7AIwP/+9z/H/hw6dMg3b82aNdC4cWP4y1/+AiNHjoS3334bGjVqBPfee69jzXg7q8uWLXPs3YQJE6BJkyZw5ZVX+ua1bdsWLrnkEsfcn376ybFmrO6h9aL//e9/D+3atRMNh5ycHPjNb34DzZo1g6FDh0Lfvn3h3HPPhWuuuQYqKyttc1Xv2dqseTJDZQ9LS0vBMAy4+eab4YMPPoDRo0fDf/7zHzjllFOgXbt24PV6bfMNw4C7777bcTapPntpaSlcfvnlcMEFF8CAAQNg8ODBcOmll8Ill1wCBQUFkf7TwwbVcxiJd0csnEPV/aP7NnHiRHj11VfBMAwYOHCgY70nn3zSMX/37t22NWNh/8INTQBiGCtWrADDMGDQoEG+z8rLy6FZs2bQunXrKF5ZdLF06VLHDb9161Zo1KgRPPXUU77POnXqBGeccUbQ9XJzc+HUU0+Fl19+2feZ1+uFW2+9FS655BKoqqoK38WfJLAIwNSpUwPOu+++++Diiy+G4uJi32djxowBwzBg7ty5vs/0Wa1BWloaGIYBffv29X3Wtm1baNGiRdCfjeU9rKiogLy8PAAAWLlypWg4dOnSBU4//XTYs2eP77P58+eDYRiQlJTk+6w296zqmic7VPawsrISli5d6vjZ9957DwzDgPnz59s+NwzDtocSBgwYAIZhQEZGhu+zzZs3Q8OGDaFHjx4h/DXRgeo5jMS7IxbOoer+cejcuTM0aNAAcnJyfJ9ZBAA/8yTEwv6FG5oAxDC6desGDRs2tBlfAAD9+vUDwzBg7969UbqykxPXXXcdXHfddb7/tx7iVVVVjj3EGDFiBBiGARs3brR9PnnyZDAMo957XzlgAlBSUgInTpxwzCkuLoaEhATo1q2b7fPKyko488wzoXPnzr7P9FmtQZcuXaBBgwawa9cu32cWAThx4gSbOmUhXvYwkOFwwQUXQMeOHR2f//GPf4Q777zT9/+1uWdV16xPqK3xtX79ejAMA4YNG2b73CIAx44dY1OELLRq1QpatWrl+Lx9+/bQrFmzWl37yQIVAhDOd0esncPanMGKigo455xzoF27drbPMQE4evRoQE9+rO1fOKAJQAzjrrvugiuuuMLx+YIFC8AwDDYcGa/wer3wu9/9Dtq3b+/7rFOnTtCgQQNo0qQJGIYB5557Lrz00ksOI+y5556DM844wxEe3759O/vSjAVYBODMM88EwzCgYcOG0K5dO1i5cqVvzpIlS8AwDJgyZYrj5//617/ayJY+qwDHjx+H8847D2655Rbb523btoVTTz0VTjvtNDAMAy688ELo1asXHD9+3DYvXvZQMhxyc3PBMAwYMGCA42eefvpp+PWvf+37f9V7tjZr1ifUlgDMmzcPDMNw5KYbhgFnnHEGNGjQAAzDgCuuuAK++uor25zq6mpo1KgRdOnSxbFur169wDAMKCkpCflviRaCEYBwvjti8RzW5gx+//33YBgGjBkzxva5RQCs91CDBg3ghhtusEWXAWJz/8IBTQBiGC1atIA77rjD8fnGjRvBMAwYNWpUFK7q5MTEiRPBMAwYO3as77Pu3buDaZowZcoU+Prrr32FXbfccovN4/3AAw9A06ZNHWuWlZWBYRjQvXt3V/4GN7F06VJ49NFHYezYsTB9+nT48MMP4bzzzoPGjRvD6tWrAQBg6tSpYBgGLF682PHzHTt2hIsuusj3//qsAvz4449gGAZ89tlnts+fffZZePfdd2HatGkwYcIE6NChAxiGAf/4xz9s8+JlDyXDwfp8woQJjp/p1q0bGIYBFRUVAKB+z9ZmzfqE2hKAu+66C8466ywoLCy0fd6mTRv45JNPYPr06TBy5Eho2bKl4wwfOnQIDMOA999/37Gu5QHPzs6u098TDQTaw3C/O2LxHNbmDD766KPQqFEjx/nbs2cPtG/fHkaOHAkzZsyATz75BH7/+9/DKaecAikpKY7fFUv7Fw5oAhDDaNq0Kdx3332Oz3fs2AGGYcCQIUOicFUnHzZv3gxnnXUWtG7dOmi+ft++fR0FWnfccQfrea2urgbDMODVV18N+zWfjNi2bRucfvrpPnWaCRMmgGEYsGLFCsfcZ555Bs4++2zf/+uzCvDkk0/CqaeeqlQU+fzzz4Nh2BWX4mUPJcNh8eLFYsTpnXfeAcMwfAaE6j1bmzXrE2pjfFnPPEpMOVRWVkLLli3hnHPOgWPHjgEAwN69e0Xv69ixY8EwDFizZk2t/4Zoo7Ykqi7vjlg8h6r7V1xcDI0bN4ZHHnlEad3Dhw/DhRdeaFNcisX9Cwc0AYhhxItHsC7Iy8uDpk2bwqWXXgr79u0LOv/YsWNwyimn2PLX4zECIOGJJ56A0047DaqqqnQEoBYoLS2FJk2awIMPPqg0Pzs7GwzDgMTERN9n8bKHOgJQd6gaX9988w00aNDA9rwLhlGjRtny1+MxAsChLu+OWDyHqvv3xRdfgGEY8N133ymvbSkrWQXDsbh/4YAmADGMeMkJDhVFRUVw7bXXwq9//WtHEVYgnH/++TZvxHPPPQdNmjSJqxoACdbDtLi4WNcA1AJWCpqqbKxlILz++uu+z+JlD8NVA6Byz8Zq7rCK8TVv3jw47bTT4MEHH2SL/CXMnDkTDMOA6dOnA0B81gBICPXdEYvnUHX/7rzzTjj77LNrZaBbxHLdunUAEJv7Fw5oAhDD6Nq1K6sKYoUiY0UVJBSUl5fDrbfeCk2aNIFly5Yp/1xJSQk0aNAAXnjhBd9nn376KRiGU8nhq6++Ej3gsYpHH30UGjduDNXV1VBUVBRQBejZZ5/1fRbvZ/Xee++FM888E8rKypTmb9iwAQzDgH79+vk+i5c9DGQ4nH/++aLSB46O1OaeVV2zPiGY8ZWeng5nnHEGtGnTxpfKo4rhw4eDYRi25+oNN9zAqgDdfffdrAe8PqC2BKCu745YO4cq+7d//3445ZRTbO8KFbz55ptgGAbs37/f91ms7V84oAlADCM9PR0Mw66RW1FRAc2bN4ebbropilcWXVRVVUGHDh0gISEBZs6cyc4pLy9nvVKWh/v777/3fZaTkyNqOf/ud7+LyT4AXPfEtWvXwqmnngodOnTwfXbvvffCxRdfbNvLzz//HAzDgNmzZ/s+i+ezevDgQUhISIBnnnnG8W/FxcUOz5fX64XHH38cDMOAzMxM3+fxsoeBDIcXX3wRTj/9dBvZsSIgI0eO9H1Wm3tWdc36hEB7uGnTJjjvvPOgRYsWcOTIEXEN7hlQUlICzZo1g9/85jc2Scb+/fuDYRg2lbDs7Gxo2LAhmKZZtz8mSpD2MFLvjlg7hyoEYPDgwWAYBtv0EIA/g7m5uXDuuefC1Vdfbfs81vYvHNAEIMbRsWNHnxc2KSkJ2rRpAwkJCbBo0aJoX1rUYHUUfOihh9iOgwA18mLnnHMOdOnSBYYOHQpDhw6F+++/HwzDgHvvvReqq6tta1oP9xdeeAHGjBnj6+ZIJfFiBbfffjvcf//9vm6hr732GjRp0gTOPvts2LRpk29eZmYmNGrUyNYJuHHjxja5VQvxelYtj+mcOXMc/5aamgoXXXQRvP766zBixAj46KOP4JZbbvGdNYpY3sPhw4dDYmIidOnSBQzDgL///e+QmJgIiYmJUFRUBAA1BafnnXceNGvWDIYNGwb9+vWDc889F6666ioHkVK9Z2uz5smOYHtYUlICl156KZxyyinQv39/x7MRe/X79OkD11xzDfTq1QtGjx4N7733Hng8HmjQoAFMmjTJ9nstYnDBBRfAwIEDYciQIXDppZfCb3/7W9aIO5kRbA8j9e6IlXOoch9buP766+G3v/2tY88s/Pvf/4Zbb70V3n33XRg9ejT07NkTzjvvPDjttNMgNTXVNjdW9i+c0AQgxlFeXg5du3aFiy66CBo1agStWrViDY14Qtu2bcEwDHEAABQWFsLTTz8NzZs3hyZNmkCjRo2gRYsW0K9fP4f+OkBNnmu/fv3A4/HAaaedBi1atHC8BGMJQ4cOhRtvvBF+/etfQ0JCAlx88cXw9NNPw7Zt2xxz09LSoE2bNtC4cWM4//zz4eWXX2Y9ZPF6Vm+++Wa44IIL2EjRzp07oWPHjnDZZZdB48aNoUmTJnD99dfDqFGjHHnDALG9hx6PR7xnceO0rKwsaN++PTRp0gTOOecceOqpp+DAgQOO9Wpzz6quebIj2B5auurS6NSpk2+tefPmwd133w0XXXQRnHrqqXDOOedA+/btRW9tTk4OPPbYY3DWWWfBmWeeCQ8++CD7vDjZEWwPI/nuiIVzqHofW0IHb7zxhrjW5MmT4bbbboPzzz8fEhIS4De/+Q088sgjtsgoRizsXzihCYCGhoaGhoaGhoZGHEETAA0NDQ0NDQ0NDY04giYAGhoaGhoaGhoaGnEETQA0NDQ0NDQ0NDQ04giaAGhoaGhoaGhoaGjEETQB0NDQ0NDQ0NDQ0IgjaAKgoaGhoaGhoaGhEUfQBEBDQ0NDQ0NDQ0MjjqAJgIaGhoaGhoaGhkYcQRMADQ0NDQ0NDQ0NjTiCJgAaGhoaGhoaGhoacQRNADQ0NDQ0NDQ0NDTiCJoAaGhoaGhoaGhoaMQRNAHQ0NDQ0NDQ0NDQiCNoAhBFFBYWQnJyMmRmZkJWVpYeeuihhx566KGHHrUYmZmZkJycDIWFhdE26+oVNAGIIpKTk8EwDD300EMPPfTQQw896jCSk5OjbdbVK2gCEEVkZmb6Dm20GbQeeuihhx566KFHfRuWMzUzMzPaZl29giYAUURWVhYYhgFZWVnRvhQNDQ0NDQ0NjXoHbUuFBk0Aogh9aDU0NDQ0NDQ0Qoe2pUKDJgBRhD60GhoaGhoaGhqhQ9tSoUETgChCH1oNDQ0NDQ0NjdChbanQoAlAFKEPrYaGhoaGhoZG6NC2VGjQBCCK0IdWI5KorvZG+xI0NDQ0NDQiCm1LhQZNAKIIfWg1CssqofP4lTB43pawrruv8Bjc1HcBPP15Oni9mgiEC3sKyqDDp0vg4zB/XxoaGhoaoUHbUqFBE4AoIlYPbVHZcTheVR3ty6gXePuH9eAxU8BjpsDew2VhW/ffX6zwrbs5rzhs68Y7HhmxxLevlSf0GdfQUEH58SqoOFEV7cvQiFHEqi0VaWgCEEXE4qHdcqAE/vj2LLh78M9QFaUUlLLKEzB/4wEoKT8e9rXLj4f3JfbgsDSfQbl6z5GwrXvHR6m+dbceKAnbuvGOP749y7evxyq1QaOhEQxHjlbCte/NhZv6LoCyyhPRvhyNGEQs2lJuQBOAKCIWD+3jSct8BtKavYVRuYbXvlkDHjMFOn2xIqzrfpW+B5r1mAmfLtwWtjUf/Wypb7+W7ygI27o39V0QkchCvOPPvWb79rU4AgQz3qHrVmIPH6Rs9N0zX6XvifblaMQgYtGWcgOaAEQRsXhoO45cFhGDFgCUc9mt3+8xU5TW/HblXliYnR/WdVXx5OjlvjXnZOUFnFtWeQJ+2nwAjlYE96Lha805oglAuHDFO34CcPhoZVjXjrbx6/V6oxa1AwAYtmArtOw9B+YGuQ806he6T/OnOU5K3x3ty9GIQcSiLeUGNAGIIurToV2YnQ+3DlgIk1cE9uA8/Xm672Hf4dMlYfv92w+WQqsP5sNjI5cGzb2ujaH+7cq9vrkHSyrCtq4qcK7+lIy9AedakY0uk1YFnLfz0FHbteoIQPjQovcc377mF5eHbd0tB0rgL+/Pg5cmZYZtzdqgqtoLD49YAq37LYBDpYHvg0ghEveXRvTx5rdr/c+4lYGfcZHC0m2H4KO52VB0TEftYhH1yZY6maAJQBRRnw6t6su58/iMiLzIcWrRkm2HlK81WNTgdpQrvz6nSHndcOH5L1f61hy9aEdYfv/uAk0AIoWWffwEILfwWNjWvXXAQt+6wfKkF2bnww+rc8MaMfhp8wHf7+8+bX3Y1q0NNAGITfzv69W+7/WH1blRuQbr97/69eqo/H6NyKI+2VInEzQBiCKifWi7T1sHd3yUqmQgqr6cX5qUWasXeW7hMaVc6nuGLPKtGSwHH//+YMYUnrstv1Scd7TiRMQjACN/3q58rYGwp6AsJgmA1+uF579cCR2Gp0FRWXQ8eVchArC74GjY1lU9s/nF5dC0x0zwmCkwdMHWsP3+5DW5vt//38nRMZI0AVCH1+uFTfuLI6KscyLMCm5dJq3yfa8p6/aHdW1V6LMV24i2LVVfoQlAFBHNQ3vkaKXvgfjoZ0uDzld9gL7+S5qKytwNuUXwh+4p0LrfgqDqOjgCEEwzH//+QF7aihNVhADIajnpOwoi8hJ5IslfA/BZqjoBCLRfNAKwpyA2CEDWviLf3/TaN2vCtu7+omPwzzHL4dlxGUGVfa55b64SYawt8PcVqMZjQ65/Dy7rHr5ziFPhXp8Svr1VxfGqam2k1QITlu0Cj5kCT3+eHtZ1e36/Hlr0ngNLtweOstYGncf7o5zB6pwiAa/Xq89WjEMTgNCgCUAUEc1DW1R23PdAbNl7TtD5qg9Q87t1ynPfmOLPDf1x3b6Ac/8xyk8AgjVhwr9/5yHZS3uwpEKZAIxfuss376o+wffrs9Tt8PyXK4PmU//tU7+u/IhU9chGXpGcf77rUGwSgC0HSmr1HagC1628ODFwfcVf3p/nmxuu/grV1XYDpVSRAITTmJmUvtu3Zvdp68K2rirw80gbacFR271SEVDAhnI4769OKMq5cHNwsYVw44QmlzEPTQBCgyYAUURUCcAx/wtXxZOo+gDtnbxBeW7/2Zt98z6amx1wbscQCcD2g7KXNr+k3DY3kF7+mMU7fPNu7rcg4O/POeJPwfkgZWPAufd+sjgkArAvQGSDFgGHM1UlEvB6vbB6z5GgRbWYAITzRd6850zlda9P9BOAYDUjqsjOs/9dgfpXrM+JDAEYt2Snb813kjcEnDtx+W6495PFsGp3+PpW5BYe00ZaLVCbvVq2vQCue38eDJoT+BlbWFYZke/gn2P8Uc60reGLLKiCRno1Yg+aAIQGTQCiiJMlAqDyUFSd22/mJuW5Y9P8Rkef6YH3AMuLfhyELKga9QeK7QRgS5gIwOwN+31z/zlmecC5mADUprYhUF7/joOltrm7AkRBTgbM3pDn8zoGyj+mhnIweL1e2F1wNKj380ok7RmcAMz3zcsMU+O2dTmFygRg7d7CWu2BKkYv8p/v938MTFoj8fu3RojcxSoi8ezelu9/blz97tyg6/685SBk7DocdB5+di8NIuBQXe2FtXsLlRouFpRWwLAFW2HT/sCRuGOVmgDEOjQBCA2aAEQR9YUA0BSFQPhobrbyXGxU9w7idXxspL9hVqBoAQ33ZufJRn1ekToBwAZSMAKAvandpq4NODdUAhAorQe/yOsDAcBe9UBRgM15xbV6kb83o6YB0ZD5gSNGOK8/2LqtPvATgBU7gxs/KqAEIFBR/JpaEoDEHzfCfyevDmpQfbpwm2/N/rM3B5wbCWMK/11/fHtW2NaNVUSCACxHdU7tBqUGnLtq92Hf3EBplgD2NMdgCm7DFmwFj6lW22BFhYOdl9IICThonDzQBCA0aAIQRUTz0NYm3EsVcALJDw795QGusu6on7f75vX6ITABwB1zA4Wy6bUG8g7tI2kHgchC0iL/td7UNzAB+BxFNl4PUqyKCcDwnwKruuBrDfTS3ZZfojz3ZMDlb8/yXeuRAM21Nu2vHQEIxagPNhd3WA7mzVQF9eoH0ipfveeI8rWu2Ok30oIVmA+et8U3tzYpduECNiivfGd22NaNVUTiPpibleeb12F4WsC576BUz3FLdgace/9Q/zMuWApQJP4unO6qCUBsQhOA0KAJQBRxsqgABXsolpTbH6CBvIk4rSfYutjr2PP7wNrjf0cEYOAc2UN5mPxdWfvkPG2ad6xKAG7sOz/gteLIRrDGTpgADAsi64ivNZACDU2n2BGgDuJkAL7WggBF0xv3RYYA3NL/J+W5rfv5CcDPWw4GnGupCwWL7FCvfiCJ08xaEICpq3KUiegAVI9TGyIaLqzcpQlAbYC/g2D9IFS/LysVT4UAfJCy0Tc3aVFgcnn34J99cxdvDXzPROL+rs27TqN+QhOA0KAJQBRxMhGAQC+RYkIAAuUoY+93MCUJHC0I1nzokRH+MPKAACkK+SSvf0OuTAD2Hrbr5QdSdcHRimAEAJOFzuMzAs7FBCCYrju+1kC1DbRYtj4RgEDdmLEMaDgNhNsHpSrPbfOhnyws2HQg4NwnR/uLHwORZkoACsvkKMiq3eoE4Kv0Pb555neBlX1qY9BFwpjKqAUBOFhSAX1nboLlOwrC9vvrG/B3EK7O6JgAPBSEAAya40/1DOa4wPdXMNIcifv7UGlFRM6sxskDTQBCgyYAUUQ0Dy31lAfyKNN6gUBeWuz9DkYAPkZpB//P3rtHW1WX+//7DDknHecyzvecMc7Rzhhn5a0yNTNvYal56WKlWWZqppVWlpWlgksRRUVQVMBLiQjeECQ1/wgAACAASURBVC+IiCIgAoKIICCiqIgihog38MJFERTl+f1xfu31fN57f16f+Vmt3drEfMbwjxizvdfcc645n9dzeb/PHMkJyhEFAUAXe598eWX0WAUAGhca5ABgr4sYAPyxxw3hWVYPAFdMKg4ABCu6LEtKSLlxx5yltmuvCTZ81ksN+5n+s9IOQI4E5roPiy/+eZO51LFf6VcDgPufZk3zbc+q/UyS9tSxHhqD8pXy1GfNUfbx6l03JEY6OiKZ8j4bOydkib2s5OYa/hrkmB1SePGCb1/1MB7rizcpdSHfYZv6HMuAdgQAaFGojL+/KAGgvigBoInRzJv2LamKLHg1nlBqt4A06D0A7JIAAF9FSpkP+UUyWlJUAJgHSi1qmNUoAPCjTSmTtXoBgEabdFm2UYZVH2Usg+eE/5lvNAgAcl7637lqeuFj9790SutxKe8K/zOpqq9jPQQAczIAwHeteieUfc4a9VTrsbc8ynDXEffAoxkAkPv7/zjlBesz7ln7KDEqsymF/xuknNSL/r3GP1UDgG9dyQDg762U1LEHgCkNAoAcc6/XVpUSs3/vUQJAfVECQBOjMwEAjcpot4AkKHMA4OLxtbnj3942D4/1AHDx+DgAqLIPaZWrYRZB0DVTiwPA1Q/WqmPfuYpb6R4AUmo1Ra+XzsoXAYAiRkFL3wo7Jo0K/zNfWxX3N8jRwFcpVIrDri4OAAc4ABg97xU81v9MGm1SAHgbAMAv9qY+q78PqWtmZnbGnTVTvttnLy18Xo2KmYtrAJAyJvS/P5XU+7/XHXP4vDalKHq/6LEU4xwAfPMKBoAbXHcppeAWAEDCCKzoZ81RpvO+LKlj31u/wX48dJZ1u/PJQs/EMjpHlABQX5QA0MRo5k2rc5FkaqTHUkLp5TJTAODnjlMOrIc7AOg7/tnocVrteQx0qjVJpKr6n6bWqvp7JgDAt8e/MXAaHusBYACor+gLj0abdFaeHI7NzO6au8x2v3CijZjzMh6XM36SE/5nvgIGZyqXSaFSqBQ5HQA/z3znY/z3Kgo2OtdPI3Z+VCb1Wfs7SV66t8zM/nDHE63H3tYEAJix+M26AIBGq8zMhj1aczhOCQ1sSuH/BikDvXoAIPXcynGO9gDw4ELemyn6WXO6kTmFCy9j3SiVrzI6PkoAqC9KAGhidCYAoIRyxZri40J+ATYFAOePeab12NSy7OGuStt3XHEAIK32xXUCwB69GQC8pGLqRernz0l+8YMNob8BjTbpqEwKAIq+HP2IwI4N1Gr3v5+6SzkmWDmuwd++6uHCx3oASFWUi56Xl8CsVMfamwAAj2YAQN/xNVO+1IL5qbfPaz321ll/ewB45AUHAInnRpD8ruHkN6dSvSmF/xsQNOuxFGPn177fXx/Az607H3u59diUwpTfm5m0oDEAoH4vFOqMTuG/B3fPW4bHltF5ogSA+mKzA4D169fbmWeeadtss41tueWWtvfee9vEiROzf84hhxxiLS0t9pvf/Kbuz9LMm1aTekooc5R1AgBIVPK8lvTx18/GYw8rCACq7T9zcVwpRKvEdF5+rj8FAL7ymgUAYHCmbpZzX4qDjQIAKQaZFX/p3jxzSetx+178IB6bE0UT5RwTrBzTMK9Tnjr2qw4AcirlpMSkAEDjQr5SnvqsfZwrd8o9+ze3Pt56bGrBuyMAYPqi4gDwmZ413wgyxDPLczjelMJfg9TfoOj1um/+q63HfW3AQ3jsqMdrErOn3MpSxx4AJmYAACnTfZgBADndwNNH1EbhRiQ6fBs3brTR815J7jWU0fFRAkB9sdkBwDHHHGNdunSxbt262eDBg61r167WpUsXmz6dZ7V9jBo1yv75n/95kwaA5WuKz8rrXD0lyn45LAUAZ99dWzw8ZvCjeKwf0+gDAKDa/tTGVb38RgGAX27OAQByOFYpVups6Kw8ORybFU8QfBckdV454X//S2/FTctyTLByPAP8AmzqWL8EnJMo0zXQ0Sqqas94oT4AoL0ZM7NThtcAoBlLwA8vWlEYAL7gnJtJDcss3N2hwoHZ/yXAvxz2GN6DnSX8NSCVr5xlWQ8Ah/RnAPAeEyfd9Bge6wHggWdYOct/VpI31Y4ohe8Gfuqs1LNgfuHv9wRnnNbZ3db/3qMEgPpiswKA2bNnW0tLi1122WWt/7Zu3TrbfvvtrWvXroV+xrp16+xTn/qUXXjhhX9nABBPKHWshvYFBmUAwJkjaw/blFqOH9Mg1QkFAHKe1DGR4gDAHaNLnKlSqpX+9QE1ACA5PVViIg10HZVpFAD4v0FqSTAn/O8n1+IcE6wcxaDe99V2Ub73p0fwWA8Aw2YuwWP976fxMlX2IQB4JAMA/I5NSgXoV7fMrZ1XEwBg2vM1AEjJB3sztsehc2kWLkKTgaBZ7bxSPh+dIfw1IAPDnGXZMU/WAOCgy6fisX4E6MQbeXzTA8CEDAB4/4O4d8b6DcVlfr2D+LYJAOg5utaVvmnGEjz2FNc1u/dJVgQro2OjBID6YrMCgO7du9sWW2xhq1eHVaO+fftaS0uLvfwyt/zMzC644AL73//9X3v//fc3bQCQsZ45sCyrSfX8ZfF9AQ8AKTk/rzxy+B858fJjGpTMqOLDNDCe0TERAhufSHzxQgYAP3udAgDvkkkAoMBGnQ0dlaEEIUcv/yq33HxoBwEAVTNzTLByFIMudABwRAIA9utXA4BUguB/P+3YtAEAWOr0ozI5YJOaf//lsMfqAptGxdTnlrf+zM+f/wAee+DltTGsRxKLmn4fh3ZszDrmvDoq/GelwkXOsuy9DgAOvGwqHjtiTg0AUh0A/51JeWf4z0rypjnPLV8M2O7scXjsBWNq35khD7+Ix548rAbN4556DY8to2OjBID6YrMCgEMOOcR22mmnNv8+efJka2lpsTFjxuD/f+nSpbbVVlvZ7bffbma2SQOA6uXPgoqyGmYRAPiWewoAvPJIKqE81Knl0Cyvflaaz/SVodR5+eQ3BQB+9CI1S3tI/xoAUIVSuzAPL4qDjY7K0JhEjl7+wEm1ZCplFJQT/veTwpTOylPk7AvkAIBXNMkxzKIOm0p7kheCH5XJOa+U0/bPb64BwM0ZAJCSSlz7wQabs+Rt2/ARu9VOyQAAr5yVcmPOcazNBYBmykQWhcucWXkPAF9NAMDts2su0z+/mQHAd83GJxJl/1nJDyMHALx62PYJAPDFm2umsiP2STfNaT02NdpURsdGCQD1xWYFADvvvLMddNBBbf59wYIF1tLSYtdeey3+/3/wgx/Yvvvu2/q/cwBg+fLl9swzzwT/3XPPPZ0GAGhZVpNqeuH4OfEUAPz2tpriQmrm1L/0LxhTHABIdk7lMosCwO4JAPCV19R5HewAgLTa9bwegs6GjsoQAOSY5Hjn5pS/QU74308LyzkypDnjQr7q991EJ2rfi2sAMHR6cQCgkS2V9iSjvYeerw8Aut35JB7rk5mczgYtapqZ/ezG//u5f5zyAh43ZWFxAPDdwJSqjE/o/jSVP0MOAFz+wHO2+4UTmyYVWRQuc2bl73nildbj9r90Ch5766waAPwiAwBSlXL/WWkZXkURKHxBJAUAHhhTylnekTolb1pGx0YJAPXFZgUA2223nR166KFt/v3FF1+0lpYWGzhwYPT/O2XKFPuHf/gHmzOnNu+YAwC9evWylpaWdv9rxk2ri730IlPH3CcAAPyceAoAfj281kJNtZz9smwOAFCCoHPiBDZXZgCAlzdNAcBBbpyBHI71GpChjo7KkMOxqiZReI3sjuoA0LhSjgtuTrfAX6/UKJoHgOum8YiA//20i6IAQJ4BflQmB2x+fzsb7f0lUa9Ux9qNGZ2NVGW/6Gd9cOEbhQHA7wOlKq8exgdP44puDgDkHNsR4X8/wWXOrLwHgP36MQDc4vwVfjmsOACMnV8cAOh7sPaDDXU9C3bowQDgu5wkymBmdtyQWa3H0qhpGR0fJQDUF5sVANTbAdiwYYPtsssudsIJJwT/vil3ABQAKEFRHeWiAPC5c+/Hz/ALN3aQajl7ADh/TPzvpaYvlCDonDgBwBWTigNAr3trCeXBGQBASi3qWkyjD1opJ98G3e+guHRCbbm5owCAuhU5Lrg5sOCvVwoA/ALqtQ8VTyhpFE21/V8FXfcpGQDgweaU4SzV6KuZOaNNpNSix1JMWlADgN0uYADwimCpmXJ/ba/P6NikojMBAD27c0ZlRs+rAcBX+rHM7zAnCXzyMDZx9ABw33xelvWflSSB31tfHAD8c2PHHuxf4t9fKeWsowfPbD22NA1rbpQAUF9sVgBQ7w7A9ddfb//4j/9oM2bMsCVLlrT+19LSYieccIItWbLE1q5lLeb2opk3bc5MuTrmkmdADgCc6KqOKQDwajm97i0OAJQgqLMsgY0HgC8kEhTvb5BS0/ALjeRwrBBGYKPJb6MAwKsbfevKjgEA+qw5Lrg5hlkBAFzNo01fcgCQmhH2v5/0z2cuzgCAhcUBwJ9Xakzj+OtrAJCTKK/fEFdqyTFrmpgBAN4TJDVTfs7omsRrI5ebOxMA0LM7Z1TGA0DK5+PmOgFgTEItx39WktZ8NwMA/PcrZWDofSNSyllHXjOj9ViSZS6j46MEgPpiswKAbt26tasC1KdPH1QBovGdv/w3evTo7M/TzJtWRz9oplyNVEh6z6vlpADAVx0PSMycFgUAHZWhmVNdFCWw8a3hVILSw/kbJAHAGUuRTrkCwP1Px89LK+UkQamqSRR93XJzRwEAKZrkJPU5hlnnOWA7LAEAvgOQmmsveh8qAJCz6+Rn3yh8Xh4AUlKNPx5aG2fI2W1Y92EcAFatDb0raGn2Aaepnvp+eVfw1EiJ13VvpMNxZwIAGj/JGZW5e15N279r38l47I3OYflXtzAAHOAA4J4nXsFj/WclQYA14otC4aVzP50AgBzn6O/+8ZHWY8lHp4yOjxIA6ovNCgBmzZrVxgdg/fr1tsMOO9g+++zT+m9Lly61hQtr7b+FCxfa6NGj2/zX0tJi3/rWt2z06NH22mv5MmCdCQBoREENs+hh55dlUwDgk47U0pmXy6QHs47KUMtZ1XIIALycYCpB8cZSByYA4KsFAUC7MJRQaqWckuocAPC68h0lA0pSrJooU+To5fuOTWq52e8AXP1gcVUZSnwUVpa9E+8m+lGZHLD5WQIAfjTk0dZjU/KH/vev/WBD9Di9t2hh2JsqpTpsPvFKVZS91PCIOSzzvKkCABVvckZlvLvvlxIAcP30WqL86+EdAwA0DqjGiBTeY+IzPRkAhrndhrPvZuUsv4tC744yOj5KAKgvNisAMDM76qijrEuXLta9e3cbPHiw7bvvvtalSxebNq2m137AAQdYS0v6T7Mpy4Dq6AepGKhhVlEA2CkBAMcMriUdqaUzL5d5bgYAkEGLLstSZ8MDQGpJsXpXreqYAgD/ciSH48UCAJT4aKWcAECXpim8qkyjjMDUqZSUmHKq+jlymTkA4GVAr5hUHADumrssepy6+9Ls88Q6AeCnN8zGY/13MQcA3l0fBwD12fgIAOD+p19rPS61Y3PEn2oAkEoof3/7vELXQM8rFZ0JAKZC8UYr5dSF8QCwTx8GgCEP10ZlTrmV90v8M270vOIAQM+tVe8XBwC/N5MCgOGzagCQUs7ye2kpQ7oyOjZKAKgvNjsAWLdunXXr1s223npr+8QnPmF77bWXTZgQqtVsDgCg1TlSy9EXOcnOXZkBAEcNqi1RpQDg4IIAoKMylCCoUgyBjZfATDmVdh9Zqzqm1I38fCw5HCsA5FSUGwUAfqm0UQCgRkW0h6GJMkWOXKZ3/0wtN3tX0wEZxlJ3zImPn+QAgB+VyQGbFAD88NradzFH3YjMmvT7RYpB458qDgDfcwCQSih/49xac6rPqehMAEDdW62UUxfmrrk1ANjrInZD9rPyv8kAgLvnFYcwEmXQ8TIKPzaXAgCvbnTaiCfwWP9OSo0ATXluue3Xb4rdNpvH0MqoL0oAqC82OwDoTNGZAICWFBe8GgLAY+Aa7JdlUwDwg0G1JaqU6oRXy+k5ujgA0AtHl2URAJwE5i4JADh9RA0AUsvN3iWTls50D4POSxNKGqvJAQBfUf7GQHY4LhqqU06VtJyxnpxlWb8omtpt8ADQPyET6H8/vfj1vJa+FQeACRkA4MHmJwkA8DCeI5e56v04AOguCgHAuAwA+L5bvhz1OCeUv7qlJjWcAwBUKdeuVTOiKABopZy6MCMdAOyZAIBrneP7b29jiVkPAKnrFT6P4++ZlWs/KHwNPDR/tie/k7y60ekjuAPgxzfps5o1Hxj/3qMEgPqiBIAmRjNvWk38JoCqjBpmzSkIAKmHrQeAL1/CAODVcs4ZHZ/N1Fn5kdD21wSFHuIeAFL+Bqc5h+McACCH4xeWryl8XppQEgCoahKFTygbBQAqU0jXYPqi4gCQsyzrl7ZTuw1+BOiyCcUBgBZQ9bxeeiuufuJHZXLA5oTrGQC8ognJm2ryu3Jt3K1Vd1E+BAAYO784APjnBn0PzEKH45zxE6qUa9eqGREAAHiCaKJMEHbnYy+3HrdHbwYA7/j+uwQA+EQ5db2Kvmfeea84APjvTKoodXMGAPhiAH1WsxIAOjpKAKgvSgBoYnQmACBVGTXMooedV8tJAYBPOpIA4F4iPWA5S0dlRjwWX/zTWXnqbHgTrNRys587Tqkb+ZcIGZwpANB5aUJJc/U5AOAT5UYBgMr50TXImevPmZU/OwMA/BIwGbeZhS/94bNeih6XAwB+VCbneh2fAAA/VjMIAOBjSX7ffq84AJBnwJgnX2097osJAPDdCvoemJn91CmN5YyfUKU8x123o8L/ftrf0kSZIMwDQOoaeMf3FAD4Z/edietV9D3zdgYAeLhMPbtvmlEcALwiWEoGtNn3y997lABQX5QA0MToTABAqjKql08PO78smwIA38pP6U77KhKpMygA0Oy1qspQ8ukt4lNVpN/eVgOAlLqRryiTwZkqMd0OIyWaKNMsrcqmUnh1o68PaAwA6IgC3VvTMub6dVSGKrr+vFK7DR4AyLfBrDgA6PUi/fNxdQLAj4fOwmO9sg75G2j1+81310ePVcAmz4B7HQDs0TsBAG5fgb7fZqG/QQ4AUKKco63fUeF/P5kCaqJMEDbCAUBKicn7vZyacJn2AJACtqLPghwA8PdWqnvrZUDPSCwB73nRpNZjZ4Ebs1kJAB0dJQDUFyUANDGaedNq5ZfkMp8UvXx62Pll2dTCla86pgDAz5GeNSoOADorT7PXOitPFScPACmwOcUtHqYAwCeU5G+gSkyUUOoCbKMA4MyRNXWjrw1gh+OioRXKR+He8uf1qbOKt/1TCZ0HgFRnw18vUm0yC1/6tzwav14KNn8GAPDVzNT1OjsDALy2/p+mxv0N1Nxr+Zp10WMVsAkA7nmiZkKVAgC/sJxaqjxuSE1qOGf+nBLlHBOqjggdwyIBh7feXV/4GoyYUwOAlNSxV3v7fQ4AZEix0ntGz4vC31upDoCXN00BwO4XTiz03DIrAaCjowSA+qIEgCZGZwIAkstUvfyiAJAyXckBgP0LA0CYKFPipbPyVHG6dELNBTcFNr8eXls8TKkbFQWA514Pz2sYnNfU58IFWFLWUdlUim5OU71RALBiTfgin7H4zeix/rxSAKCJMhlWebOoFAD4tn/KKbTo9VIAeHFF3ADpvvmvFr5eHmxSAPCdq2oAQAZnHyoArI4DgKpR0TXIAQAvWUogrMfmyIBSopwjQdkRkQMA+v2ia+ABICV17He9TruD1XI8AKQ6Nv6zUlL9Zp0AkOreDnUAkJIB3aXXhNZjZy4uAaCZUQJAfVECQBOjmTetVn5JIeNxAQB6MPtl2ZTtutfzTjlP+mXZs0bNjx6nADBs5pLosTp6QQDQ7/6Fhc/r5GE1AEipG/mEMgcAbpoRP68pAgBkUqOqSRRe3eiQ/o0BgDdWrwsB4IU4AEzJAAA/U16psmGV921IAcCX3PWinQ0zAQC4D7VjsxgA4N4ncwCgdl7HDWEA+NaVNVMjAoD1G8Lxl9dXAQC8UBwAvAttagH12OtqST2BlVnYLchZQKXPmjN+0hGhexik4LZ8zbrC53XHnKWtx6WUzvyoZ0ou0wMAjS6ahdeAkmoFG4rR82oAkOreen+DJACcVwMAKlyYlQDQ0VECQH1RAkATo5k3rVZ+SSFD9bzpweyXZXfswYmynztOOU96AKjeFQcAnZWnRFkrr9TZCAAgcV5eeSQFAD6hJIdj9WK44ZE/R49VCcxGAYBXNzq4QQCgjtTTFwEAuPPaNgEAvupXqY61NaBX70ebUrsNXyoIbGbFAUA7Ni8sjwOAnheFB5sfDXkUj/3mFTUAIIdjVW16deX70WO1w/b+B/Hk05tQpQDAuxbfDH9XszzFoKKfNSf5/Pjjjdbj7qfsvHueRmnRnNA9jAdAwW25ADad1+2zHQAkZuV9oSfZAXAKbqSGZVYcABRsKDxcprq33t+g+8gMAIDChVkJAB0dJQDUFyUANDE6EwDQfKzq5VO1w8/K79BjHH6GwzMAwKvlnDkyDgA6K0+JsiZeBACXOABInddJN81pPTalbuQTSjI4e/a1EADIrfXBhaECDmnrq2wqhVc3ahQA6DL6tOdXRI/155UCAF/1q1TH2qq1cQDwxm2p0aZ9+hS7XmbhS58S1c4AAN7V9KrJxQFg2TtxzwIFAOrCeBOqFAD4uX76fpuFXcYcBZr3wOFYu1YU/nqRe3dO6B4GSTi/vmpd4WvgASA1K+8LPX/IAIDUyFbR94yCDYWHy9RY6uBpNXnTJAC4EaBHSgBoapQAUF+UANDEaOZNq5XfHL38ogCw/dnFASBlPe/VcujBrAAwdDpUyiXxotGmi8cvLHxeP7uxBgCp3QafUJLBmQIAmTVNEglMMjjLAQCvbnTQ5VPx2KKhIPoQAIDX9t8ucQ38S79SZbnKnN2GvfvUlD/Ij8IsfOnnjGy9sHxN9FgFGwrf2Tj2OgaArw2ouZpeCQCgCjjkWqzyppR85phQ/XhoDQDo+20WPmNyFGjeBQDQrhWFH5Xpn3COLhq6h3H/03EAeG1V+FkJbG5zAJAalfE7UcklYAcAtJNlJgAASXUOhPlnQap76w3OcgCAOpdmJQB0dJQAUF+UANDE6EwAkKOXTw9m/2JIJWleeWTvPvzS98uy9GDWWfnrphWvlFPL2QNA6rxOcNKDKQAomlCqGzNptasGPgGAyqZSeHWjAxsEAPr7ydXUg03qGnhN80p1rK1YE5erPOPO4rsN/nqRHK1Z+NK/MWNka9EbcQDw4wyp6+U7G8cMZgA4uH8NAK6YFAeA90QBh1yLdceGkk8vQblXAgC8tCd1wszC5eYcBRoaGctxz/ZqOf0SvhFFIwcAFFYIbG6dVQOA1KiM74gmZUAdAKR2Nvxnpaq6djYofHcpVbzxBmfUaTYLAeDhRfHChVkJAB0dJQDUFyUANDGaedNq5ZfUGVTNgx7MflY+NaZxmAOA1EvfAwAtZ+msPLmaqlssAUDf8c+2HpdaQPUVyhQA7OW0pMngTN2YSarxAdHAJ3ddlU2l8OpGjQIA3dkgUyMPNqkXuVc0qVRZrtIDQGq0yV8v2kUxqx8AngcA8MlM6nr5zsbRg2fisT5JGzgpXqlWCUzyLNAdG0o+/fVKPQt+4sy9qBNmZnao223IAYBV78cBIEc5yyeUfROysUVDjcjIxHHZOyGsENgMn/VS63GpURn/PEwagXkASOxs+M9KVXXtbFD47lKqcOANzlLfbw8ANLpoVgJAR0cJAPVFCQBNjGbetFp5JXUGVfOgB7MHgFSinAMAXi2H9JkVAMjUSCvlNNrUd9yzhR/ifkY5pW60Z50AQEotaoLVKADw6kYHXjYVjy0a2rEhSUMPNikA8PPMlSrLVXp1oxQA+OuVGhHwv59m1bUT9dzrcQAYmQEAHmx+eC0DgDfaGwCjKmvWhRKYJFmq6kaUfHoFmtSzwLv7UifMLNxtyJGgpJ2RnK6ZXyq9MCEbWzRUiWk8mDhqt2J1QQBIKZ31cc/D3yYA4CAHADQKZ1YcAHLGsHw3MFWU8gZnOQBAo4tmJQB0dJQAUF+UANDE6EwAQOoMOstLD2bfGk497Hx7PjX365dlyaJdZ+UpUdZKOY025QCAlylMAcAevYuNlDz9SnEAuP/p8LzI4VhlUym8utFXGwQACmwkaejBJrWI7ccZUgBw2oiaulFqt8Ffr5RRkP/918OsunaiFr6+OnqsjjaRsowHmxQAeJUtmlVfLQBAC8u63EzJpwe2FAD4HRvqhJmZHeJGm3IkKFeuje+M6J4RhXeWJZWvnNBFbHJxVwAgsLnl0RoApL5fve9bUBcAUCfMLLwGNFbzSgYA+PGyVFHq6gdrI1skN20WAsBUGF00KwGgo6MEgPqiBIAmRjNvWq385jiV0oPZz8qnHnbfvqrWnk8pf/hlWdKd1ll5kjTURJkAoI8AACVeXns8pW60R++J7oVTHADovMY/FZpgkcNxDgB4daNGAYACGyma+OuVSlB8MlOpjrU3CACcvGlqtMkDQEr/3P9+WlbNAYARAgAff1wMAI5KAIAfsev/wHPR41atDQGA9hV0uZkAwANbah/I34cEwmZh8plyDfaflZbG9Z6lGObuw9TOSNHIAQA1fCSw8Z811WG7YEwNAH5z6+N4rN8vSak2+c9KYzU62kTPY/3OUPidjRwAoN0lPa8yGh8lANQXJQA0MZoLAMUNs7SVTw9mPxuaejB786EUAPjlS9KdVgCghcb7nw4TZdptuGjsguBYSryOGlQDgJS6UQgA8RfOU8uKA8C4DADQGXwKX3k94FJ2OC4aer1ontlfr5Sax80zlwQ/lwyr/uABIAE2/nql5A+LAoCqNj37WhwA/KhMpTrWPvzo4+ixEKvnGQAAIABJREFUvrNx1CAGAN9huxwAYOXa0ASL9hUUAGiu3o+fpAGg1okiyVKzcLSJAEDddd96N740rjBO4TsbqZGxoqFKTGPnx78zuq/wDoCNB4DUqMz5Y55pPfaUDACgTphZ+J2hsRrtbNDzWPeBKK6sFwAWlgDQzCgBoL4oAaCJ0ZkAIEemMAcA6MEcAsBE/Lx++ZIAQGflaZ5ZE2UabVIA2ACJ15HX1MyHUgDwxQtrCSXNnCoAUOIzdn54XuRwnDPO4Jcv928QAOj1omqm72ykAOBGN3pRqY6111bFDau8v0EKAPz1Si0/+t9PajW6i7Lg1TgA6G7D+g1xYyff2fjBoBn4WT1gXzYhDgDviAsudSt0ubno+EnqO+NH0QjwzcLRJhpzVHddUo2av2xl4e+M39lIGWYVDQWA++bH/QVU7Y06G8MEmil63esAYHhxAEjJtvrfT2M1CgAfwXtGoZli4KSabCt1ZM3MdnUAQOIFel5lND5KAKgvSgBoYjTzptXKb86SIlVmdFaeHsxeoeOLFzIA+OVLqrxqdY7GGTRRJgDwM6+VKldevflQqpq5u0soSXZOkw7Sar9v/qvBsWRwlgMAXt2oUQCg14uqmR7YUkuK10+vDwBSo03+eqVGH+oFgGdeXRU99jYBgHUfxgHgDxkA4AH70glxucq3BQAIVvS5UXT8JAUAv3AAQIBvFo42kQmVuuuSatTjS98p/J3xvg2pWfmisfaDUImJDMZU7Y06G9o1ozj3nqdbj/v18Ll4rN/DSMm2FgUAHW2igoxCM4X3bUiNbH3+/AdajyXxAj2vMhofJQDUFyUANDE6EwDkLCnSg1ln5enB/M06AYCMZzShpHGGMU+GiTLtNlwoAPDBhvh5efOh1ELjFy6ovURoRODJl0MAoMqnnhcBgKrwUHh1o/36dQwAUDLjgS0FAEMefjH4ua+ujAPAqQ4AUqNNHgBSlU//+8mPQpfRn34lDgC63EzmWh5sjryGAcB/v0iv/s131xf+rPrcIADwyWdqb8YDAAG+WTjaRHtO6q5LS+OPiTM6hf8uphLloqFeDPfCd0Z3vd4EALhpRnEAOGf0U63H/eqW4gBA3wOz8DtDc/UvvfVecCwVZBSaKfpPLN4B8ABA4gV6XjQWW0Z9UQJAfVECQBOjmTetVn5zKpT0YNZRGXowe4m+3RMA4JcvyXhGE0oaZ7j3rwAAGr3IkTfdrU4AIK32e54I3WLJ4TgHALy60Vf6sb9B0dDrdc8Tr0SP9Z2NlE65l1+sVMfaKwAAv3MOx6nOhgc2Snx0ppwSH5VtpaTaz8pXqqyt7wHg+wkA8N+vSwAAVqwJAeCpZfHPqrsNNH/uk88UAPgRIPp+m4WdDQIANdeinZFZYoxI4fdWfnHzY3hs0VAvBgaA8PtNo005AHD23TUAOHlYcQBI+TYE7xmYq9fdhkYBwOUP1JzsUzsAHgAeAPECPS/qipdRX5QAUF+UANDEaOZNm+OYqwlKDgBQpdwDwBcueAA/r1++pNlrTShpnEETZdpt8KoXlSqPXuTIm/qXCBmcPfFXAAAZnKkMJ8XRg2vLzY0CAN1tGD0vDgC+mpoCgEEPLQ5+7rJ34o61v80AAA9slNDpTDklPjkAMEzUjUhb33c2vvenR/C8/Pfr4vHx78zyNaED6/xlK6PHauGA5s/9zkYKAPwScMpd158XudCquRaNjKkvCoVXrvrZjXPw2KKhXgwEzdrppdEm3ZuhOGvU/LoAgIwZzcJEmebqdbeB3jPaNaO4bEINAFI+AP7ZTeplel70WcuoL0oAqC9KAGhidCYAoAezymVSZUZn5alSngMAfvmSZmk1oaQEwc/nVqq82+BVLyrVsfb+B/HzypE39YtkpCs/T+aOafZZz4sAIEfS8Cgnb/rlSxoDALrbcPe8ZdFj780AAO/omQKA39z6eOtxqdEmDwAn3RQHAJ0pz/l+UVVdFzVJWtN3NlIA4L9ffcfHHWuXrw4B4ImXiwMAzZ/fkAUANTUqghWzsGNDSmcKANQxenhRqIpG4TsAPx46C48tGjkAoM95Gm26IQMAqnfVAOCXw7iz4QGAjNu0azb52TgA6G4DvWe0a0Zx6YSajDXtZJmFAHD/08UBgIpHf4miY0IPPb/CBkx8HjuBm0OUAFBflADQxGjmTZvjmKu68lSZ0VEZeth9fUANAHZLAMDuBQFAE0oCgLvnha6qOQBAs9c58qYeAMjgTAGAzJr0vMjhOAcAvLpRowBAR5vumhsHAN/Z+ExPBgDv6FmpjrWX344DwCkOAFKdDf/SPxEqujpSQomPytFSVV0XNUla03c2jsgBgHFxAHh9VQgAjy99J3qs7jbQ/PlQt7SdMs/zAECf1Sy8XjcDAKi7LgGjyiJT+GfnMYMfxWOLhpqxUddMn/Pkh5EDAN1H1jwmUqNNXxtQAwAyblNoJgBQI0t6z6gnCIV3sk/JtoYAEBcvMAsBgN4dZv/3vfnCBQ8k9yX83so5oxvjMbGpRgkA9UUJAE2MZt60mvjRg1nlMunBnAMA/sXw+fMZAHwlj9RXFABonvmuuWGiTMvNXvauUh1r70HFxasbpeRNvZY0GUup8ggtP456XAAA/A1Uh5/ie07daN+LGwMAOtp052MvR4/NAQBv6NNIAPDA9tMbZkeP04pyDgA8CVV1ndMmaU3f2fjuHxkAPGD3gaT6tVWhA+vcl+ISszraRADgl7ZT99aJzo/iorEL8NhdzqtdLwIANdei+0Udjin8szOlxFQ0Vr0fAgB1zfQ5T7sNqpxFccadNQD4eQYAkHGbLmKTso4uN9N7RsfmKLyRZQ4AjAf5YrMQAGhsT4+l8PdsqiP69x4lANQXJQA0MToTANCDWWUlCQB0Vp5GZfyLYddeE/Dz+tELMp7RijKNCIwUAKDdBgUAarnmqBv5BIV0wue+VBwA9LwaBQDf/WPHA8CIOXEA8KNNn+15P/7cKyaFALD0LQCA4bVEOdXZ8MB2wvVxANCKck6HjcZqdE67KAAcngAAD9iUVL+6MgSAx8BkTkebaAE1BwC8Id2F9zEA7HTu/a3HkteJAgDdL+qLQuGVq1JdmKKhbswEAPr9pt2GoRkA4E3maBTOrDgAaNeMlHV0uZneMzn+Bt7HhnayzMJ3EvmXmIVJPXXt9FiKEgBqUQJAfVECQBOjmTetvhjIWErVcqgykzMq42dDUwDgqy0kv6gJJc0zq0V8DgBQFScHAHZ2AED+BgoAJG96p5wXORyrERfF4U7dqFEAoKNNd8yJmzX50aYUAHg5v0p1rL301nvRY389fG7h8/IAQDPdmlDmdNjmwViNVmlJWtN3Ng6/ejqel09mekNS/YoAAJnMaWeDFlC9alPqGvzUGdKdP4afnZ8+Z3zrsTeC14maa9H9ogZnFH5xPbWHUTTUjXnU43EAUFEEksPNAQDvMXHSTbzc7Ec9ycFcu2akrKPLzfSeyQIAJ2NNO1lm4XeG/EvMwqSe1LD0WAp/z5YAUAJAPbHZAcD69evtzDPPtG222ca23HJL23vvvW3iRE7SzMzuvvtu+/rXv27bbLON/dM//ZP9z//8jx155JH29NNP1/1ZOhMAkK68qspQZSZnVMY7RO6SAAA/ekF62m0AAMYZ1CKelpvPc8Y3lSpXcXLkTT/nKpQMAKH2OMkfKtiQwVkOAPjl5tScdtHQ0abbZscBwI827XQuA4CX80sldL+6JQMAHLD9aEh8plsTyhwAoLl6TdIomfCdjRQAeMCmqro6sJLErHY2aAH1WqfalAMAve7lZ+cOPca1Hktmh2quteTN+P2iBmcU9/4NAID2ZhQAaLlZvTMovMIU7cKYhQBAhSYFAFLWURlres/kGJx5FTvayTILAYDcmM3CpJ6W4fVYCu8HUQJACQD1xGYHAMccc4x16dLFunXrZoMHD7auXbtaly5dbPp0fkFecMEFdvTRR9sll1xiQ4cOtYsuusi2224722qrrezJJ/lBEYtm3rSa+OWoyjQKAA66fGoNAM5jAPCVV9Jf14oyzTOrQyQtN5+rAACjFznqRn5EgQzO1HyI5E0VbAgANEGg8LsNKaWWoqGdDXJr9TsbKQDwah6phO7kYcUBwHdsaKlTE0oafVBHagIATdJIWtN3Ng5LAIAH7AvGFAcAWjBXAKAF1EEZAPATBwDn3sMFmO3OrgEAmR3q9XpxxbvRY3MAwBdPGjUC9I64MY8EAFBVNFpuzgEAv2Cekjf1AEAO5jo2RwCg6kY0kpnjb+BV7GgnyywEADIwNAuTeuqE6bEU75YA0BolANQXmxUAzJ4921paWuyyyy5r/bd169bZ9ttvb127ds3+eW+88YZ16dLFTj755Lo+TzNvWk38cpZKqTWbMyufBQDnFQMArSjTPLMaxOQAAI1e+BdeCgA+27MGAGRwNkcAgNSN7pgTnhcZnOUAgAebxgFAeF5k1uR3Gz6XCQB/BgD45bCarnyqs+EB4IfXzowep2ZNOTs2c18qDgBUTfSdje9cxQDgAZvGapa+FQIAjZdpZ4MA4JqpxQHghOtrAJBSP/G/nwBA3XUXAwCowzFFRwDA2wIAtDivO1G03KzmeRR+vyQFAP65Qf4lOjZH0pqqbkQjmTn+Bl7EgnayzEIAIDM2s/A+pO+BHkvh1aBKACgBoJ7YrACge/futsUWW9jq1auDf+/bt6+1tLTYyy/HH6TtxcaNG+3f/u3f7Oijj67r83QmAKCZclXLocqMjsrQg/lABwA7ZwAAGc/kAIDqQ9Nyc8/R4XnR6IVfekvJm3oAIIOzHABQsCGDsxwA8GCzT5/GAIB2Nkir3e82pADAy/lVqlzR/YVzlk2BjR/ZOgoAQLXaafa5LQDE5+o1SSNlHd/Z+PZVD+N5eQCgsRp1YKXuknY2SIHG+zakFrGPdwBw9t3FAWAoAIAC2wvL10SPVYdjCt89bRQAvPVu6MZMAKAjkbTcnAMAfryM1LDMQgCgTnNbAIjP1auIBflh5Mib+h22HAAgLwaz8D6kPQw1EKTwy+AlAJQAUE9sVgBwyCGH2E477dTm3ydPnmwtLS02ZsyY5M9YuXKlrVixwp566ik78cQTraWlxa677rq6Pk9nAgAaKdGlUqrMKADQg/nAy2oAkErofOWVjGd0pIQWGlUfmpabzxn9VHAsjV745eaUvOlnetaWFMnfYPafw0SZ5E3V+ZIAQEcEKPx57d2H/Q2KhgIAKbX43YYUMF5SJwCkwMaPbB01KA4AqtVOADBGluxJWedacTgmZZ0sADivGACoAyvdWwo2pEDjfRtSUqweAM4axWZN/vcPeTiuq67AtuiNOACowRmFX1xvFAC8KQAwAgBARyJpF2bwtMWFz8uPl/0kAQC+cED+Jbo3Q9KausNGO1k5AOA72LSTZVY/ANAYlkIQhR8FKwGgBIB6YrMCgJ133tkOOuigNv++YMECa2lpsWuvvTb5Mz7zmc9YS0uLtbS02L/8y79Yz5497eOP09bey5cvt2eeeSb475577mnaTauJHyWUOlNOANBmVh4ezDkA4CuvZDyjIyW00KjqEDkAQJXXgzMAwKuUkL/BrBffCn4/yZtqZ4MMznIA4OAOAADtbNCipr8PUwDg9bwrVR7p+HkGAPiODem6q1RjjsrWHACAQRkA4EebvnUlA4AH7PNgrl4dWMk7Q8GGKp9XP1iTbU0BwI+Hzmo9NuXWWhQAFNieBwBQgzMKPz7ZYQAA0rlaEKFdGIVLCj9eRnK4ZmFHlEZNdQ+DpDV1h43eMzn+Bh4AaCfLLAQAMmMzC+9D6sIoBFH4TlAJACUA1BObFQBst912duihh7b59xdffNFaWlps4MCByZ8xc+ZMmzBhgl1zzTW211572RlnnGEffsi6vmZmvXr1agUH/a8zAADJZepMObVmdVSGlmW/6gAgtdTpK69kPKMAQAuNqg5By8097g4BgBIvv9uQkjfd0QEA+RsoAND10s4GJWlqnEbhz2uvixoDANrZoDltfx+mdka8nnelOtZeWB4HgJNuqiXKKbDxAHDkNXEAUKUWWn5UACBpTT8rX6nyQqHvbBx6BQOAB2xarFUHVlLO0vMiAPDGbTkAkNJqLwoAaq618PXV0WPV4IzC7600CgBWrAkBgKRz9XlIuzA5AOC7S8cnAMB3DmnUVPcwCAC0g03vmRx5U1/Aop0ss9A7g7wYzML7kCBMIYjizRIAWqMEgPpiswKARnQAfLzzzjv23//933bGGWckj+1sHQBN/HKWZak1q5VyWpY94NIprceldN194kXGMzpSQguNuhxGAHC2AAAlXlkA0MMBAPgbPKoAAOpG6nxJAKBLghs3bowe63c29mwQACjY0Jy2V21KAsA4BYB4Rfekm2rGUimw8SNb3wcAUKWWHJldAgA/K1+psrSm72x8MwEAHrB7jo4DgBow0d6MAgBJUF6ZAQDHDakBQEqq0f/+66YBAEjH5tnX4gCgBmcUfnyyUQCwfM264PffDtK5+jykUTjtLlH47hL5YZiFnUMaNdU9DNLWVwCg90yOupEvYNFOllkIACTFahbeh9SNVAii8PdBCQAlANQTmxUANGIHQOPYY4+1rbfeuq7P08ybVgGAZuV1pIQqMwoAtCy7fwYA+MSLAEBHSmieWWdDSd2oDQBA4uUT5ZS/gdcpJwCYuTgDAKSzQQZnCgAffQwAcFnjAUDBhqq0t2UAQJ8MADjxxuIA4Ee2SNddlVpyAGAWaOv7WflKlRVFfGfjGwOn4Xl5wCZlHTVgorE5PS+afR44qWbctl+/KfhZfzTk0dZjU4ua/vcPnhZ3Y1YAeObVVdFj1eCMYkRHAMDq4gCgz0NKPrW7ROG7SykA8AUREi/QPQzS1tcONr1ncgDAv79oJ8vMbPcLJ7YeS1KsZuF9SM8ihSCKN1aXAPCXKAGgvtisAKBbt27tqgD16dOnLhUgM7MjjjjCttpqq7o+TzNvWk38aFZeR0oIAHRUhpZlPQB8pic/wHziRc6TOQCgrWFSNzprVHhelHj5RDmVqG7vdMrJ4EwBgPwNVPeaxjRUJWTDR/F9Fj+ytUfvxgCAnhcBgF9uToGVN/SpVHmp82cOAFJg40e2KKHTOW2SP9REmcy1/Kx8pcrKOjkA4AG7ByjrqAETQbOeF0lQDphYHwCk5rT977/2oTgA6MjW06/EAUD9DSj83kqjAOANAQAyz9MOG43C5QDAzzMAwBdEaNdM9zBIW18LWPSeyQEA//7KAQBSYjIL78PnXo8/ixSCKF5bVXPlLgGgBIB6YrMCgFmzZrXxAVi/fr3tsMMOts8++7T+29KlS23hwvBBtXx52yRqyZIl9q//+q+233771fV5mnnTauJHs/JaUabWrFbKSad8v35TCj/AfOJFzpM6U04LjfpiYACYHxxLiiZfrRMAyN9gxuI3g99PI1s62pQDAB8CAPiRrT16p92zi4QCAI1p+E5UCgC8oU+lykudHgBSYOPvw+/+MZ7Q6Zx2jtHezMVxAPCz8qn70I825QAASWuqARMJAuh5EQD0zwCAY6+rAUBqTKMoAOjIFgGA+hvQ2JzfW2kUALy+KgSAW2fFAUA7bFR91vEyCg+Xxw0pDgAkXqB7GKStrwUses/kyJv6Qg+JMpiFAEBKTGbhfbjg1fh4mUIQxSsrSwD4S5QAUF9sVgBgZnbUUUdZly5drHv37jZ48GDbd999rUuXLjZtWu0FecABB1hLS/in+a//+i879thjrV+/fnbddddZ9+7d7T/+4z9syy23tBkz4rPAFJ0JAGhWXpdlqTWrlXJSy/lKvwdbj9sxBQBuVp6MZ7TiRQCgLwZKZhQAaKHRJ8optRrvVEr+BjNeCAGARrZ0tIkMzlQmcP2Gj6LH7t8BAKBgQ2MavhOV2q24UACAqm4/dc6yqfPy9+HhAAA6p03yh14qslJld90rBQDoPvSjTV8fwADgO2xnjYoDgOqv0z6QnhcCwAPPtR6X2gE4ZnANAGhx3ixMvAYBAOjI1vxlK6PHqr/BxzA25/dWOgoAyD1bAZs6YTpeRuHh8kdD4o7YZmFHlMQLdAyLAEDfX/SeyZE39c/51L0VAAAoMZmF9yHBpUIQhXflLgGgBIB6YrMDgHXr1lm3bt1s6623tk984hO211572YQJYTLRHgD06tXL9txzT/t//+//WZcuXeyTn/ykHXPMMfbUU2xEQ9HMm1YTPxqV0ZGSHAAgtZwvX1IcAPysPBnPKACQoom+GEjdqHpXCAC00OgT5ZS86bZn1X4m+Rs8kgEAKntHi5pqnLbuwzgA+I7NFy9sEADIeVGVdlgGAFwwpjgA/CQDAPx9ePjVcXddHdPIAgBw171iUnEA8J2Nrw14CM9rxwAA4tKaqr9O3UB1ECf5w8sm1AAgZQR29OCZtSQN9mbMwsTrmqnxe0vNtZ58OQ4A6m9AezN+bK1RAOBHP1IAoN8v6oTlAICHy2OvYwDwHVEaXdQxLNLW1/cXvWdy1I38cz51b3kAICUmswwAWFsCQD1RAkB9sdkBQGeKZt60mvgRAOhICc1maqWc1HICAOjBDzA/KkMAoC1vUjTRFwMBwJkjw/OihUafKKcA4FMOAMjfQAGAdjZ0t6FRAOA7Nrs3CAD0vChJ86NoKX8F7+hZqbKs4wnOWCoFNh4ADgMA0Cot6Z9rokwA4GflK1UGUd/ZSAKA62xU74oDgOqvUzFAHcTJhOrSCTXfhn0vLg4AtDdjFiZef5r6QvQ43dl4AgBA/Q1ob8aPrTUKAF5dGQLALY/GAUC/XwTCOQDg4fKYwQwAviNKo4s6hkUAoM8tes/kqBt1H/lk4XvLAwAtYpuF9+FTy+IAoH8Dipfeeq8EgP8/SgCoL0oAaGJsKgCgIyXUmtVKOanl7HtxLaHcocc4/Lx+VIacJxUASNFEXww0zqAAQOMMPlFO+Rv4n0n+BtMXhS9y2tnQ3QZSalGjoLUfbIge64GtUQCg50VJ2s0ZAOANfSpVlnX0zrKp8/Ig+p2r4gCgVVrSP9dE+REAgP4CAASiHgAO6c8A4MGGzLVUfpGeBXpepH/e7/7iAPDDa2sAQHszZsUBQHc2Hl/6TvRYlTclAPBja40CgFcEAIYBAOj3i0BYF8wp/L119OC4I7ZZ2BGlzqWOYZG5lj636D2Ts9zc7c4aAKTurS86AKBFbLPwPqTxMv0bUHhX7hIASgCoJ0oAaGI086bVByjNyutICVVmFABILadeACDnSZ15JUUTfTGQupGvDFWqPM7gASAlb1oUAB5etCI4lnY2dLchBwDeWx8HAH+9vnABJ+BFQxOUP06JJ2l+FG23xO9XAKDFO28slTovfx9++6q4tr4maZdNKA4A0xcBALhZ+UqVQdSPNh2cAAAPNt1HxrX1VX6RkrSRGQBwSQYAHOUAgPZmzMLvF91bCgBzX4oDgKob0eL8sA4AgGXvrA1+/7CZS6LHTns+fG4QCOuCOS03+3vrh9cyAPiOKHUudQyLzLXU4IzeMzkAcEadAECL2GbhfUjjZfo3oPCmfCkVvb/3KAGgvigBoInRmQCAZuV1pIQAQCvlJFPYte/k1uO2P5sBwM/Kk/OkLpWSoomqXhAA+MpQpcrjDL5STgCwcePG4GeSv4ECAHVsdLeBDM70RfpuQQBIJeBFQ8+LkjQ/ipYLAKTrngMA/j781pVxANAkjQBAE+WHF62IHnt5BgD40aaDLp+K5+XBhtx1VX6RkjRvglWpsgutd27u2ncyftajBtUAgMbmzIoDgC5tP7YkbsamAPDBBgAA17Ui1aic0HvrZgCAhwQACIQVAGi52d9bRyUAwBdEqHOZAwBqcEbvmRx1o9NGPNF6XAouPQDQHoZZeB/Og+6SjqJReFO+Ih0Aup6bepQAUF+UANDEaC4AhA9QmpXXkRICAK2Uk0yhB4DtEgDgZ+VJd1oBgBRNdOaVFhoVAKia6RNlqsy0BYC4upFW8ggAdLeBtNr1Rbp63YfRY/31ahQA6Hld/WDcMMuPoqUS9fPueTr4uUUBIHVeHgAOBXddv6BXqbIDqibK056PA4Bflq1UuRN1fJ0AcAYAgMovjno8nqSNkPMiF1rv3PylDACgrplZmHjRvaXmWnMAAFTelJSzbu4AANB7iwBg6nPLC38PVGGKlpuPzwAAXxCh55Ymv3Rvqd8LAUDObsNpd9QAgEQZzEIAoD0Ms/A+pPEy7URReFO+FAC8tup926fPZDt68My/SxAoAaC+KAGgidHMm1YTP5qVVwCgtr8myqRS8qUMAPA/EwHgheIAoDOvtNB4hpwXVTM9ANCD+eOPQwAgfwOt5NGLVHcbcgBg1ftxAPDXKzWDXzT0vK6aHE/S/ChaCgDOFQAg5Y3jhswqfF4eRL8JALD0rTBJIwdUBYCHAAD8rHylyp0oDzYHJgDAg83pI+IAoPKLd4EDqjfBqlTZhdY7N+/ThwHgB4NmtB5LXTOz4gCgqk2z/xwHAFVtosV5P7bWUQBw04wl0WOnCADQ90AVpmi3wd9bRw1iAPDPQ3puafJL95b6vVChKQcA/uAAINVd8gBAexhm4X1I42XaiaLwnhwpAPDnRU7jm2qUAFBflADQxOhMAECz8jpSQq1ZBQBSKdmnTy2h3PYsftgVBQBVvSBJQ215EwCcPiI8L6pm+ko5PZg/EgAgfwNNlGlnQ1veZHCmlbRVa+MA4K9XowBAK5RXAgB4EE0t6/YcXRwAvLNs6rz8zyRzLa/QUamyA6pWygkALhEAoE5UAACXTcXz8mBz2ognosepeMBISNK8CValyi603rl57z5sxnbkNR4A4t8Zs/B6EVyqahO5MatqEwGA71o1agdA4fLGR/4cPfbBhW8Ex5ICzcBJ4YJ5UQD4wSD2wfEAQM8tTX7p3lK5Zyo05Sw3n3r7vNbjUt2lAACgC2OmABCHS+1EUXhPjhQAeNlWKghtqlEatM84AAAgAElEQVQCQH1RAkATo5k3rSZ+NCuvIyUEAFopJ5USn1B+CgBAR2XIeVIBgCQNteVN8qYKAJTM+Eo5+Rts+Ojj4GeSvKkmyrSzoRUvMjjT++Cd9z6IHuuvV0qHv2hohfKKSY0BgHNGh34UlPh4Z9nUeRUFgCVOoSMJAFIpn/pc3Ln54vH1AcBXEwDgf+Zpd8QBQHeH7gQH1BwA8MZte13EAPB9BwDUNdPzIrhU1SZyY9al7fc/iAOA71o1CgAULm8AAJj8bAgApECjAEDLzb5rduQ1DAC+IELPLU1+6d5StTcqNOUAwO9uqwFAqrvkAYDGsMzC+5D2S7QTReEleVNLwL+59fHWY2mEd1ONEgDqixIAmhjNvGm1hUqjMjpSQrOZmijTkuLefSYVAgAdlSHnSVWVIUlDbXkTAPjlsP9LZuJ62j5RJn+DDwUASN5UE2Xa2cgBAL0P3gYA8Ndrlw4CgIGT4oZZXt0opdff4+7iAOCdZVPn5X8mueu+6BQ6KtWxdvH44gAwBQDAL8tWqjyK5pO0Ay6dUvi8/oAAEN4vIyBJ8y64qe+MN27bMwMAqGum50Vwqdr65MWgS9sknTv0bwAA10+PA8CkBSEAkAKNekzQcrPvmn0/AQC+IELPLU1+CQBU7Y0KTdrppfhtAAB8b3kAoDEss/A+pP0SBVEKL8mb6gD43byUZ8GmGCUA1BclADQxOhcAxBNllVGj2UxNlAkA9rpoUqGHnY7KkPOkqsqQpKFWvEjT3C+HVapjbRE4avpEmQDggw0ZALCwOABoxYsMzvQ+eOvduKOmv14NAwA5rwHgmOtH0VKOvWcLAFDl0xtL7XJe/Ly0E0XmWosFAPqOjzugaqV8ykIAgHEhANAomk/SCAD0vH5/+7zosTo6OGJOPEm7TQCAvjPeuC0FAN/70yOtx1LXTM8rBwDIi0F3Nkg613etGrUDoN0lAoAHnnk9OJYMztRjgpabfdfsewmw8QBAu2Y6hkVwqWIP9J7RTi+Fr5SnAGCP3jUAoDEssxAAaL9E70MKL8mbAgAvikAdo001SgCoL0oAaGI086bVGUoaldGZ8hwAIJWSPQsCgI7KkPOkAgBJGmrFi1qjCgDPFwQA8jdYv+Gj4GeSv4EmyvQi1YoXGZzpfbBiTRwA/PWiRDkndEa5PwCAH0VLAcBZo0IAoMpnUQDQThQBwAvLiwOAVsofXBiXbfWz8pUqL9b6JG1/AAA9r1MBABQY75gTrybeOis8L/rOeNnWPXozABzhAIC+M3pe1F1S3wbyYtCdDZLO7QgA+LMAwFAAgAkCACRBqQBAuw2+a5bqbPiOKI2aavWb4FLFHggAtNNL/ganDK8BQGq8zANAKqn2v5+WcPU+pPCKXCkA8J1DksPdVKMEgPqiBIAmRmcCABqV0ZESWs7SRJlUShQAYg9mHZUh50mVlSRJQ33hEQD8Qc7rudfjyYyvlJO/gQIA+RtookxL2/rCIwDQWdrla+Jyenv0rp3XzgkA2LhxI8oI/iV0Rrk/OOYOCgCAk8SzRoV+FFT59M6ydF6aUJK7rpfoq1THWt9xxQFg8rNxAOh9XwgANFfvk7T9+hUHgN/dFgcAfW7QOMHwWS8Fx9J3xlcoU3D33T/WAIC+M9o5pO6SauuTFKuObK0B6Vw/ttYoANDxsiEPvxg99v6nQwAgCUo1mSMA8NCcAgBfEKFRU61+E1zqrhcVmrTTSzKYvx4+t/W41HiZfx4ShJmFAEAL5nofUsxzC/mpHQD/TiBX8k01SgCoL0oAaGI086bVxI9GZRQAaDZTE2VaUvQPUAIAHZUhAFC1HAQAeeERAPzeqUNUquyouWdBAFj3YQgApG6kiTJV0vSFRwZnbQAAHDV9xYsS5Q0ffWyHXT3dvnzJg7ZybXynwKztjDK9nPwoWgoA1JGaAMA7y37u3LhxmyaU5K77vABAHwAAHZUh5+YL2wBAPKn2APCVfnF3XT2v3wIA6P1yGwDALY8WBwAv25ra7zjcAQB9Z7RzSN0lldYkJSYd2SIA8F2rRu0A6HgZAcD4p14LjiUJSjWZo+VmD80psPEFERo11eo3waXuelGhKQcAfnVLDQBovMwsfH/RNTALAYAWzPU+pPAL+SkA8OOTvcGNeVONEgDqixIAmhjNvGl1iYpGZXSmnGYzFQBoSdEnlPRgVgAg63kFANI01xce+RsoAJCjpn8xkL9BRwGAjjaRwZneB2So45feKFEe55IO0v02M5soAECOuX4ULTUnro7UNPrgjaV2gvPShJLMtbxGd6U61i4aG3/p6qgMAYBflq1Uea7eV2kJAPS8fnPr49Fj9X4hB1QFgIWvx78zXrY1pfBUFAC0c0jdJU28SIlJOzZknjfobwAA102LJ5/j2gBAfP5cn4e03Oyh+fAEAPiCCI2aavWbAEBHPanQpM9D6kz+cthjrcfRTpZZ/QAwY3F8vCwHAPw+TmoEyPtR0P7YpholANQXJQA0MToTAFClXGfKCQA0UaYlRZ9Q0oNZR2XIeVLlMknTXF1VCQBOlfMiR00PNuRv8P4H4XmRvKlWyqmVrqNNOQBAhjq7u+tFibJfkqS/v1lbACDHXN+JSgGAOlLT6IM3lsoBADLX8hrdKQDQUZmJAAB+Vj4FAL5K++VL4gCgifIpAAA6e00OqMMEAKhr5mVbUyZvh189vdB3RgsHBACqrU+L2NqxIfM837Vq1AiQ7pcQAIydHwIASVDq8xABwEHz4VdPx8/rE2UaNdXkl7pLOupJhSZ9HpK/wS9urgEA7ZfoedE1MAsBgBbM9T6k8Ps4JQCUAFBPlADQxGjmTasqClQpVxUFWs7SRJmWFIsCgFbKyXlSZSVJ0/zSCaGmOvkbeH3oSpWNpfx5EQCs/WBD8DNJ3lQTZWql62gTGZzpfUCGOl+44IFsAKD7yqytSgk55noASGnFqyEdjT54Y6nP9oyflybKZK614NUQAKjtrgBARj0KALRY66u0+14cBwBNlE8ZHgcAnb0mB9RhM5cEx1LXzKs2pQDgMAcA9J3RwgGNl6m0Ji1ia8eGzPN816pxABB2lwZPWxw99r75rwbHkgSlPg9J3chD82FJAKg9D6nTrABw66w4AGinlwpN+jwkf4Of1wkAdA3MQgCgBXNVeKLw+zgpAPCGdCUAlPGXKAGgidFUAJAXOVVqdamUlrM0UaYlxd0FAGKVGQUAcp5UACBN837iqkr+BjkA4M+L/A3eW18/AFArXSt55G+g9wHpae/mAIAS5RwAUJUSMszyo2j5ABBPfDwA0CytJspkruVNeirVsXYhAICOypBzs1+WrVR5rt5XaQkANFH+9fC50WN19pocUG/OAACv2rRbAgC+c1UNAEgSWJ8bNF6mAEBjWApstOfiobVRAKAL5tc+FE8+730yBACSoNTnIakb+e/Md65iAPAFEeo0a/Wbxsu000uFJh1tIn+Dk26qOebSgrlZCAB0DcxCAHh4UXy/RBWeKHz3NrUD4A3pSgAo4y9RAkATo1MBACTKukRFs5ltASCeoPiKcqUar8zoqAw5T6pcJmmaX5IBAL+V8yJdeQWbWCgAUDKjlXJqpWslLwcASE7v8+fXrhe9cHIAQFVKyDDLj6Lt3YcBQB2pCQC+XxAANFEmbX1v0lOpjrULxsQBQEdlyLjtXAEAmqv3ANC17+TocZoo/+qWOADo7DU5oPqxg0qVx+a8atPnzy8OACQIoOdF42VaeaUxLAU2cs/uCADQBfNBkHze88QrwbEkQakAQMvN/jvz7asexs/rn4f0PFAIo/EyLfQQAGhBhPwNTryxBgC0X2IW7jbQNVA/ClKYUoUnCv/sTgHA0EwAePnttXhfd7YoAaC+KAGgidHMm1Zb+VQp1yUqAgBNlGlGebeCAKCjMgQAKpdJmuYXjw9feORv4A1iKlXWlVewicW7AgDkb6CVcgIAfZGTwZneBwQAu/aa0AEAEM4ok17+lRkAoI7UNPvsjaWola4AQNr63qQnHwDiOxt+WbZS5bl6P6aRAwAnD4sDgI5ekAPqjW7soFLlrplXbdo1YTL37asebj2WBAG0cEAAoJVXGsNSACD3bN+1ahQA6IJ5DgCQBKUWRGi52X9nvnUlA4B/HlKnOQsApNBDnWYFAJI3/VmdAHDN1Pg1UJldUpjSBW8K341LjQB5P4oUAPxlfHGXXhPwb9WZogSA+qIEgCZGZwIAqpTrEhUtZ2miTDPKCgCx1qxWysl6PgcAvDlKpcr+BnpeJCup5xWLNes+DI6jaqYCAMm26ouc5E31PiA5vV0cANALZ0QGAKhMIenl+1G0ffrEE1qztoZ0NPvsjaV2hPPSRJm09ecvWxkce/6Y+HdcZ+UJAHqIwzGN1fgxjS9lAMAvhz0WPVZHL8gB9YYMAPBL2ymX6W9dWQMAEgTQwgHtl2jllbowCmzknu2htaMAgJLPu+ctC44lCUotiNBy8xEZAOCfh9Rp1i4M7Zfoc546zdoRpaT2JzfMbj2OFszNQgD409S4uZaKB5DClC54U/hF6BQAeD+KFAAcN2RW67HUrehMUQJAfVECQBOjmTetzvJSoqxLVLScdYokyjSj7EdKKtV4a1Yr5WQ9r3KZZGrUd1xxANDzIllJPa+Yv8FqAQCqZuqoDC3T6YucAEDvA5LT2+W8GgBQouwBgGZ+zdoCAOnl+1G0JACIHC3NPntjqR17FAcAktb0Lp2VKsuh6qw8GbedLQBAYzV+TIP+Xlop/8XNcQDQ0QtyQFUAeGpZ/LP6nY2Uy/ShVzgAAEEALRzQfolWXgnCFNjeBADw0NooAFj4erhgTsnnqMdDACAJyjYAAMvN/jtz6BUMAP55SIUm7cLQfok+56nTrB1RAoATrq8BAO1kmYUAQO66Kh4wBQEghDtyLX4oAwC8D0AKALyDOC0sd6YoAaC+KAGgidHMm1ZneSlR1iWqHACgGWU/UlKpxgFAK+Wkp60vBjI16iMAQAZn3iK+UmVZST2v2EN81fvheVE1U0dlKLFWsCEA0PuA5PR27gAAUJ1yksv0o2gpAFA/CgKAwwsCgCbKJK3pXTor1TwAIOM2vyxbqTIA+DENGpnSSvnPAQC08no9OKD6xcNKlQHA72ykXKY9AJAggBYOaL9EK690DfR6rVgTBwAPrY0CAJWYpeTzrrkCACBBqR1RWm7235lvZgAAFZq0C0P7JSqLTJ1m7YiSwdnxHQAAOjpIErO64E2mZR7GUzsA3pAuBQDeP4SAsTNFCQD1RQkATYzOBACUKOsMJakzaKJMM8qaKMcqM1oppxepvhjI1OiisaGpUg4A0FLpLnJesYf4qrUCAFDN1Eo5jdYo2JC/gd4HtEz3uXPvL5Qo5wCA6pSTXGb/DABQPwpafvS68jv0iBu3KQCQss7jGQCgy7Lk2+CXZStVHqs5oiAAaKX8pJviAKCAPRQAYKgAAC3O+52NFAB80wEA7QNp4YABYE3ha6DXa/mauHmeh9ZGAYBKzFLy6fdxKlWu6GrhAAHAfWe+MXAafl7/nKdCk3ZhaL9EVdGo06ydDfI3+PHQ2vgLiTKYhQBw9YOLosdp55AkZnXBm0zLPIynAMD7UaQAwMsH085IZ4oSAOqLEgCaGM28adVIhRJlnaGk5axfD58bHEszypooxwBAK+XkPKkvBjI16n1fCABkcKbnRUulflSGHuIr134QHEfVzBwAULAhAND7gJbpdnIAQIlyDgCoTjnJZfpRtBQAqB8Fvch8MrM9ODdrpZwAYO5LIQCcd0/8pavLsuTb4JdlK9XiAECyqVopP+mmOdFjFbDJAdUvHlaqvDjvR7bIZdrM7BsDp7UeS/tACgC0YK4AQNdAr9fy1XEA8NCacswtGioxSwAwQgCAJCgVAEgF5rAMAPDPeSo0aReGAEBV0ajTrABA/gZ+/p1EGcxCALhqchwAtHAw+dk4AOh4F5mW+e9iagTI+1GkAMCLB1DntDNFCQD1RQkATYxm3rSq5kGJss5Q0nKWJso0oqCJcqw1+1cBAJgaXagAAAZnv7olPC9aKt25AwBAR2VITUPBhgzO2gJAvJL22Z4FAWBOcQAYIzrlpJbjR9FSKkAqR0vLjz6Z2Q4AQCvlpKzz2JK3g2PPzQAAkm1Vh2Maq/Fz2uScrInyiTfGAUC/X+SAqgBAi/N+ZItM5sxCAKBxQO0c0oK5jl6QcpbuNiAAuHs25ZhbNBQAqPrsv4uVKi91aueQ1I28FOvXByQAwD0PqdCkEEYL5goA1GnW0SbyN/jRkNr8O4kymIUAcCUAgBYOSGJWx7vItMz/DVIA4OVoUwDgRwep0NWZogSA+qIEgCZGpwIASJR1hpIAQBNlqlBqohwFABmVoRepvhjI1OiCMfUDAFVG9LxiVZx33gsBgMYZdFSG1DQUbMjfQO8DmqX1AECVcp900LKyWVujIlLL8aNoKQBQOVoCAJ/M5AAAKevMEQCgl64mlAQAanBGYzV+TnuP3sUB4GcAAKpGRQ6oXnmkUuXFeT+yRSZzZiEA0FiNFg5owVxHL2hvRncb3gAA8PdsyjG3aKjHBFWf75gTuhaTBKV2DkndyEuxfm3AQ/h5/fOQ3jMKYbRgrvchdZq1s0H+Bn4BlkQZzMz2cgBwxaT4NdAOG0nM6ngXmZb5v0FqBMjL0aYAwBcOyEG9M0UJAPVFCQBNjGbetCrnR4mytlBJneHkYfUDQGw2Uyvl9CLVFwOZGp0/5pngWHI41vOimXI/K1+pxqs4bwsA0DiDAgD5Nuh5EQDofUCztJ/pOb5QovzXAADNyvtRtJQTsMq20jKbT2a2BedmfZHTGNLsPxcHAE0oqfqsBmc0VuNHmwgAtFL+0xviDqiqRkUOqDkA4Ee2UsnM1wfUAIC6gVo4IABQaU0CAN1teH1VHAD8PZsyzCoaCgBUfb5tdggAJEGpnUNSN/JSrCkA8M9Des8ohNGCud6H1GnWzgYBgF+AJVEGsxAABk56PnqcAjY5fWt3h0zLvDBE6jvjTRRTAOCfG9S160xRAkB9sdkBwPr16+3MM8+0bbbZxrbcckvbe++9beLEicn/36hRo+yHP/yhbbvttrbVVlvZpz/9aTv99NNt5cr6vyCdCQAoUdYWKqkz/HLYY8GxNKKgiXJsNlMr5WQ9nwMAve4NE2UyONPzooryTgUB4K131wfHkbypzsoTAOh5kcGZ3gc0S/vpcxoPAGpURADgR9FSAKBqVKR+4pOZTwEA6IucuhCPvvhWcOw5o5+KHqsAQMmnGpzRC/qwAADizzitlP8EASAEUTKh8tKDlSorZ/mOTWqc4WsDHmo9lrqBWjgghSmdvaaxOR1tem3V+9Fj/T2b0ssvGmoyR9XnW2eFAEASlAoApG7klZgO6c8A4J+H9DxWCKMFc70PqdCknQ0yOPvhtfUBQP+JcQDQ7xd5TCjckWSpHwtNAcCVGQDgO6JUYOhMUQJAfbHZAcAxxxxjXbp0sW7dutngwYOta9eu1qVLF5s+nduz//mf/2m77rqrnXvuuTZkyBA79dRT7Z/+6Z/ss5/9rL3/fvwFQNHMm1b1vMn9UysotJyliTKNKGiiHAMArZRTJU0rQ3Refw0AUEXZj8pUqvE27psCADTPrLPypKet50X+Bnof0Cztjg4AqFL+1wAALcv6UTSaaTdrq9r0CACAT2YIALRSThAyc3EIAD3ujgOAVpQJANTgjKrqHgC+eCEAgFTKT7g+DgC6jE4mVF56sFLlcQLfsSGJWTOzQ/rXAIC6gVo4IIUpnb2mrpkCwKsr489/f8+m9PKLhprMEQAMnxWalpECjY4OkrqRV2I6OAEA/nlIz2OFMAIAvQ9zAIAMzrwCDqmymYU7AP0feC56nH6/yGNCAYAkS31RKAUAXo42BQC+IFJ2AP6+Y7MCgNmzZ1tLS4tddtllrf+2bt0623777a1r1674/506dWqbf7v55putpaXFhgwZUtfnaSoAiJU6uX/qA5QA4Bc3h4kyVRA0UY4tZ2mlnAHgtcLndd49TwfHksOxnhdVlP2oTKUaB4AVa8LzonlmBQDS09bzygEAaqXv2KN2XpQo+7njFACMnhcCAC3L+lG0jgKASrU4ANBnmLE4NFgjANCEklSb1N+AAMBX8nYHANBK+fEAADqKRiZUg9oAQHxv5pQMADjYAQB1A7VwQApTOntN3xkdbXoFAMDfsym9/KKhAEDjJ+paTAo0uhNFy81+D+Ogy6fi5/XPQ3oeK4SRwpSKIhAAaGeDDM68Ag6JMpiZ7dG7BgCXAwAoiJLRn3Z3SLLUj0+mAMDL0aYAwMMdde06U5QAUF9sVgDQvXt322KLLWz16rDK2bdvX2tpabGXX44vgbYXa9assZaWFjv99NPr+jydCQDI/VMfoKTO8HNJlClBUQCIzWZqpZxa6QoAdF7nSqJMBmd6XpRQ+lGZSjU+x7l8zbrgOJpn1ll50tPW8yJ/A70P6EW6Q49xrccVBYDuIxkA7p4XGhXRy8mPotFMu1lbNSrSP/9mQQDQVj59hkdeCAHg7AwAoPET9TegF7TfbfjCBQ9Ej9ME5cdDZ0WP1VE0kqD02uOVagIAHLCRx4RZCABUDNDCQQ4A0HdGR5uWvbM2eqy/Z1NymUVDXaYHwPiJuhaTAk29AHBgAgD885Cex3oNCAAURGnUVDsb5G9wpHPPJlEGM7M9ek9sPfayCXEAUBAlkzm9tiRZ6runKQDwcrQ0jmgWXlv6znamKAGgvtisAOCQQw6xnXbaqc2/T5482VpaWmzMmDFZP2/RokXW0tJiffv2revzNPOmVUdPcv/UByipM5x0U5goU4KilfIYAGilnFrp2hqm8+o5ujgA6HmRnvaOAgCxOc4cANBRGdLTPmd06BbbKADY/uxxwbGxuH12cQAY9XgIAPRy8qNoKQBQ1Sa6Xv6FV6mCc/NaBYB4VX36ohAAzhrVGABQfwMaq/GtfAIATVCOGxIHAO1EEQB47fFKlSUF/fUiiVkzs4Mun1roWaCFA5KY1eVL8gTR0aaX3wYAcPdsSi6zaDwhSSLNn6trMSnQqHgAqRv5RewDL5uKn9c/D8lkTq8BScwqiNKoqYIN+Rt83wEAiTKYmX3xwhoAXDohbjKn9yGZzOm1JclS3z1NAYCXUKZihFk4Ykdy12b/V3Db9+IH8fvyt4gSAOqLzQoAdt55ZzvooIPa/PuCBQuspaXFrr322qyfd9JJJ9kWW2xhixbFZzD/EsuXL7dnnnkm+O+ee+5p2k2rjp70YNYHKKkzaKJMFQStlMeWszRRpla6tobpvDRRJodjPS/S0/ajMpUqAMBqAQCYZ84BgB53h+dFD2cFQXqRblcHAJw5cn70OLO2AECjMr4TRcm3WVvVJrpe9QIAzdWrw/JZo+J/Bx0poflz9Teg75cfbdotAwDIAVU7UaRBrwBAyYS/XiQxa2Z2oAMAehZo4YAkZnX2mhTBdLSJAMCPT6bUcorGPHGZpvlz9ZigBVTdHSJ1I7+I/dUUAPTwABCXmNVrQBKzCqI0aqpgQ/4G3jyPRBnMQgDod38cAPQ+JJM5vbakWOSfnSkA8HK0VIwwC79fpHZnZoXeB3+LKAGgvtisAGC77bazQw89tM2/v/jii9bS0mIDBw4s/LNuvfVWa2lpsTPPPLPQ8b169bKWlpZ2/+scABB/MOsDlAFgTnAsVf20Uh5bztJEmVrpbQEgfl6aKDMAhOdFetpFAeANOS9aaFQAIEOdsxUAwN9A7wN6kW571tjg2FjkAMBdc0MAoOqU70RR8m3WdmmbrpevZlaqY+3jgsZtNFev/go5AECqTSpvSt8vDwCfPz8OADoqQw6oeh+SBr03H6pU2TvDXy9SmDIzO/CyWoJCzwItHJDClCafJAigo01L34oDgIfWlFpO0Xg8AwDUY4IWUBUASN3IV4kPuHQKfl7/PCSTuRwAUBClZdUcAPAa+CTKYGa2uwOASwAA9P1FPh96bUmxaOTc4gDg5WjpWWRm9lX3/SIHdbMSADb12KwAoFEdgIcffti23HJL+8Y3vmEbNsRbdD46Wwdgkjh60oNZXwykznDijWGiTC/9ogCgiTK99HU2lABAE+VbwOBMz4v0tP2sfKUaV3J4fVV4XrTQqMuy5Nx81qj6AYBepJ8SAIhVym/LAICRAgBUnfIv8hQA6NI2AYCvZlaqcedmnZWnsRqVV63eFf876Ew5LaCqvClV1f1uw669JkSP0xEFMkDS+5A06BUAqJrorxcpTJllAMDq4gCgy5c0DqidjZfeei96rIfWlFpO0dAkkRZQVWKW5s/1OU/qRgdnAIB/HpLJnAIAeUwoiNKumZ4XGZwdngEAX7jggdZjLx4fBwB9f5HPx9yXwmtLikUjHqupraUAwKtRpZ7J+186pfVYUrszKwFgU4/NCgAasQPw5JNP2r//+7/bnnvuae++++5f9XmaedMqANCDWR+gtJyliTK99LVSHlNnyAEAnQ0lsNFEmRyO9bxIT1tn5WMA8Nqq94PjaKFRl2XJUfOsUfODY2mcQe8D2tnwx1WqxQCAEl8zszvdS6xS5eqUvw+p+m7WdmmbgM1XMyvVuHOzjsrQWI2qK9FLV2fKaWdD1Y0IsP1oEwGAjiiQ/KHehyRB6d1HU88CP2KXAgBfoaS5en1uEACosg51AxVsCAD8+GRKLadoaJJIC6gqMUvz56oeRupGfg9j/wQA+OchmcwphJHHhAIAPbf0/UUGZ94Ei1TZzMx2cwDQd3zcZE6f8yTzO/el0ECQFpa92EIKALwaVWov6yv9Hmw9lsQuzEoA2NRjswKAbt26tasC1KdPn0IqQIsXL7att97aPv3pT9uKFfGKYtFo5k07URI/ejDri4EA4GeSKJNhllbKYw87rZTTS18BgMCmeleYKBMA6HmRnrbOysek3F5dGb4YSN1IEy9y1DxzZHheNM6gAEBLpf64Sraxd/AAACAASURBVDU+KpMDACMEAOh4fx+mAEB3NgjY6gUAGqvR3Qp66SoA0M6GqhsVBYBdAAB0VIbkD3VngxRovPtopcrjBH7EjhSmzMwOcBVKmqvX5wZ5TKj6CnUDFQCWvBkHAN+1Si3LFg1NEmkBVRfMafxE1cNI3cjPie/XjwHAPw/JY0IhjDwmtBNFzy19f5HBmZfOJVEGM7PPn+8AAFym9TlPMr+PLQmvLS0s+1HLFAB4NaqUNPO+F9cAgMQTzEoA2NRjswKAWbNmtfEBWL9+ve2www62zz77tP7b0qVLbeHC8KH6+uuv23bbbWef/OQnbcmSJQ35PM28aR8Qx1xy/9QXAwHAT2+YHRxLevkKALGHnVZQ6KWvy2EENpooDwOHYz0v0tPWWfmYlNsr8mIgRRNNvAgAuo8M3WIJABQEY0ulGzduDI6rVOOjMlkAMCcEAKqUe9UmGr8xa7uzMWVhHAAOFgAo6txMAKCjVQQAulRKI1uqbkRVdb/bsMt5AABSKSf1Ex3ZIgWaKwUAqBigHTYKP6JAc/UKAOQxoQBAzwLtbPwZAMBXn1PLskVDk0QCAN0vofETfc7TcrMfw/pKvwfx8/rnIXlM6DUgjwktiNAyvJ4XGZx56VwSZTAz27XXhNZj+wAALHtnbfD7SeVrjlxb2lfwLs8pAPAKaqePYAD4Ut/JrcfS6KRZCQCbemxWAGBmdtRRR1mXLl2se/fuNnjwYNt3332tS5cuNm1arap8wAEHWEtL+KfZbbfdWpd+b7nlluC/iRO5GhmLzgQAVJlRuUySZ/uJJMrUQtRRmRgAaKJML31dDiOw0UT55gwAmAR62jor3wgA0GXZX90SB4Bud4bnRQZneh/EZso//vhvAwCUKPul7RQAtBnZAgDw4wyVanHnZhqr0c4KVd10qZQAQJebqarudxt2BgDQURlSP9GRLVpAvWJSmCjTPLF22Cg8ANBYjRYOyGNC5RfpWaCdjRdXxEdBPQCkZuWLhiaJpECj+yU0fqLPeQIAP4b15UsYAPzzkDwm9BoQAGhBhJbh9bzI38BL55Iog5nZLg4AyGX65bdDACCVr1kvhg7itK9wizN5SwGAV6M6bcQTeOzefWoGZ9Q5NSsBYFOPzQ4A1q1bZ926dbOtt97aPvGJT9hee+1lEyaEL8f2ACCm4NPS0mIHHHBAXZ+lmTftBEn8qDKjcpmkzqAAQC1EHZWJVTv0AUrLdAoABDaaKNNLX8+LDHU0UY5pOWtliCQNFQBOHhYHgDPkvGihUQEgNlLyUTsAEBuV8ZWpFAD4OdZUouyXtmn+3ixvZOvAggCgs/I0VqN/1zMyAIB2NnS5marqHgA+d+790eMUAGj2WUe2aAE1BwD0+xXbLzEz269fDQDIhEpHLwgAVH6RzA61s7EYAMBXn1Oz8kVj9p9DACAFGu0uUfVZn/MEAH4Ma9+LGQD8zyQA0GtAHhPaiaJleAUA8jfwi/MkymBmtst5NQAgk7mlb4XPeVL5elQAgPYVvMlbCgC8GtVpdzAA7HlRDQDouWlWAsCmHpsdAHSmaOZNe//Trxd+MKtcJgHACdeHL3LSX9dRmVi1Qx+gVPXT5TACG02Ub5qxpPB5kaGOJsoxLWcFG1pu1hfeL4fF/Q1OH1EcABQEYyMlGz76uM15xUZlPACkJOf8HGsqUfbLzSkAyBnZ8uMMlWrcubkNAEBVXf+u1HZXVRka2dLlZkqq/W4DAYCOytDss3ZsaAF14KTnw88K3UD9fsX2S8zCJUWaq9cOG5nMqbIOmR0q2LywPA4APvlMzcoXDQUAUqBRuKTqswIAyZvuXycAkMmcXgMCAAVR2oXR8yIA8HszOQBAHhMvvfVe8PtJ5Wvm4hAAaF/hphnFAcAvo//+9riHjFnocEydbrMSADb1KAGgibGpAIDKZZI82/HyIif1laIAsOTN8AHaKADQRJmqfpqgkKGOJsqNAAAdvfgFOByfNuKJ4FhSNNFENVZR/rBOADh68Eys5t4mAECJst/ZoPl7s7YVZXqRfVUAoKhzM43V6PeLzkuXSmlkS5ebKan2uw07AQDoqAyNPiiw0fz5gIkhANA4oD43YuNlZmZfvqQGADRXrx02MplTZR3yOlGweWH5muixPvlMjcoUDR0TIQUahUtKPrXQQ+pGvgtDAKC7Q2Qyp9eATOYURAkA9LzI4MwDAKmymZnt7ACAFKb0/UUqXzMWhw7itK/gTd5SAOCX0U9NAID3N6BCl1kJAJt6lADQxGguAIR6+VSZUblMkmf78dBZwbE0Q6iz8rF255/lAUptfwUAAhtNlAkANEGJGeq0tywbM3PRzgapG2nFiwDgD3eE50WKJpqoxirKH2xoCwCxURkPAKmXox5L86l+ZyMFAApsDQEAGZWhqvp4MaSj81IAoI6NLjdTUu13Gz7bM/5ZdVSGEh8FNpo/7y8AMH1R/LPqc6MoANBcvQI2mcypsg4JHSjYLHojDgA++UxVyouGjokQAOi9RcmnFnpI3ch3Ybr2nRw9TneHyGROrwGZzCmI0i6MnhcZnPmxOVJlMzP73Ln3tx5LC+Yvrng3+P2k8jXjhRAAqFvhPR5SAOB3UX4HLvJmIQBQocusBIBNPUoAaGJ0JgD40ZD4g1l15UmeTV/kNEOoCWWs3blYHqDU9ld5OAQASZSp7a/nNT5iqNPesmzMzEVbw6RupADwcwCA398+LziWASC8D2IV5fYAIDYqo0k9vRyGz3opOI7mU/3IFi3gmrUFANrZ8PPMlWpxAKCqujpS03lpkkYdG91tIADwuw2UIOioDCU+em1p/rz/A88Fx9I+0HFDwu9XrLtkFsoU0lx9DgCosg4BgILN8wAAZ3cAAOiYCElQqmIRLZhroYfUjTyEfQkAQHeHjh4c95jQa0AAoPch7cLoeZHBmR+bI1EGM7OdHADQeJm+v+gaPCIAQN0KL/GaAgAvhUou8mYhAMTec3+JIs/4v0WUAFBflADQxGjmTasVSmrNql5+DgBQ5VWTxBgAvLB8TXActf0VAKizoZVyavvrecUcNdtblo0BgLaGablZW94n3RQHgFMFAMjfQAEgVqVdv+GjNucVAwBN6unloMf+ARJlP7KVAgDt2FAre38BgJhxmy7LUlVdHanpvDRJIwDQ3QaqqhcFgJxldL1eNH9+eQYA/GjIo4XuLbMQAGiuXjts5DKtyScpnSnYPPd6HAB88kmV8pzQMRGSoFTFIlow10SZ1I38NdinT/y8dHeIXKZV3Yhcpr0CTqXKo3B6XmRw5sfm6HtgZvbZnjUAILjU9xddg+mLwmtL3Qov8ZoCAL+MTi7yZqHDMRnHmZUAsKlHCQBNjGbetFqhpNas6uWTPJtW8nLUcmLzjs+/ET5Aqe2v+tDU2dBKeQ4AxB6M7S3LxhyOFQBotEnVck66KW5w9rvbBABA3UhBMJakrfuwLQDEKuU5AKAvclpQ8x0bUuAxa3u9JgAA+HnmSjVu3KbLsvTSVUO6HAAgYMtR2fLLzZ8+J/5Zc3ZRhsn1ovETBQASBDj2uhAAYveWmVlXp1NOc/XaYaOFdE0+ac9Jz2vh66ujx/riCVXKc0IB4KKxcQUaVSyi/RLt9JK6kQeAvftMih6nz8OjAAB0uZlcpr0CTqXKIKznRQZnfmyOvgdmZp/pWXOyp3trkby/aMn/4UUrgmOpW+ENBFMA4JfRyUXeLHQ4vm9+3DfCLHyH0+J+R0cJAPVFCQBNjM4EANSaVb18UmdQAIglXu3Nysf0mRe+vjo4jtr+qg9NnQ2tlA8FANDzijlqtrcsG3M41t0G6mzkAMBv/woAiCVpHQUAmlDSgpoHNlLgMWsLADTL6ueZK9W4b4Muy1JSrXK0BDZapSU52hyVLb/bsGMGANAuiiZeNH5y2YQwUSZToWMGhwAQgzCz0KiIxmoUsEmSVpNP2nPS83r2tTgA+OIJVcpzQufESYNeF5Zpv0Q7vQQAHsL2uigOADo6SC7Tutw8cFLcZO5muQ/pe6DnVdTgLAUAnz6nBgB0bz33+prC1+Ch50MAoG7FoAwA8Lso5CFjFgIAGceZhQBAXbuOjhIA6osSAJoYzbxpdUSBWrOql08AoK38WOLV3qx8DAAWvFo/AFBnQyvlOQAQezC2NysfAwBdDqPz0qW3E2+MA8Aptz5eOKFUEIypNr3/QQcBgLzIaUHt1AwA0OtFAODnmSvV4gBASbUuoxPYaJU2Zxmdkmq/27Bjj+IAQLsomnhR9fnSCQsL3VtmZj+8dmZwbMw7w6w4AChgU5KmySd1OfW8CAB88YQS5ZzQOXECAF1Ypn0gTZRJ3tRfgz3hvLRwcCS4TOty8wBwmfYKOKl7SzvYRQ3OUgCwowMAMjDUAhaN+E19bnlwLHUrvMJTCgD8Lgp5yJiFAEDGcWYhABC0d3SUAFBflADQxGjmTasjCtSaVb18AgBt5ceWiNqblY8pHjzz6qrgOLKeV8MsAgCtlNPin4JN7MHY3qx8zOH4heXvFj4vVV/5GQHA8BAAyN9AQTCm2rT2gw1tzis2K58DAJpQ/hYAwF8vkuA0aw9E47OsfpyBkk9Vy6GkWgGAwEYBIGcUjRKf/QsCgM7K0y6KJl6UfPa7P0yUSRHsKAGAmHKWmdk+fWrJJ83VK2CfOTIOAJp80jNOAWDBq3EA8MUTSpRzQufEyYRKF5apG6iJMsmb+mtA56WFg+8DAOhyMwGAV8BJ3VvawS5qcEadMLMQAMi/RAtYBGFTBADos3rxgBQA+D0I8pAxCwGAjOPMQgCg72xHRwkA9UUJAE2MTgUAg+IAoHr5pM+srfycZdmY4sHTr4QAQFU/Ncyi0abfSKWcAEDBJgcAYg7HOhtK56UA8NMb4v4Gvx4+Nzg2CwAWtv8ifW99WwCIVXx0rr9SjQOAN7OpVFmhwnc2UgBQFETNwnGGSjXu26BqOTv0GBf9mbqLQgCgxlJ0H2pngxIfDwD0WXVWnnZRbhAAoOTzkhwAGBQCQGxvxsxs7z41p1Kaq1f1FarSavJJAKBg88yrq6LH+uLJHr0bAwA6J37BmPg10H0F6gZqokzypv4a0Hnpc+N7f4qbzOk16A8A4BVwKlVWm9PzIoMzvw9EnTAzsx171ACAZH61gEU7PlMWLi/8Wf3oIAkSmIXdHVKQMwsBgFyLzUIAiL3n/hZRAkB9UQJAE6OZN+0YmVGm2UyVyyR5NgWA2BJRe8uyMQCYv2xlcBxV/RQAaLRJR2VyAGD0vPYBoL1Z+diDUWdD6bxU9u4nAAC/uiUEABopURCMOea++zcCAFKo8J0N0uA3Kw6iZmE1s1ItDgDbnx1PqnUUjTobOqdNCjTa2YgBm1mYzNBnbbOMDrsoWnml5PPi8QsLf9YfDJpROJnY66Ja8klz9dph6wZVWl2spWecgs3Tr8QBwBdP9ug9MXpcTigAkAut7ivQs0BHPUne1F8DOq/V6z4MfuYRAAB6Dfo/EHeZVgAgtTk9LzI48/tAh0AnzMxshx7jWo+lJX8tYFEX5sGFbxT+rL5wkOoA+O4OKciZhQBAvhFmIQCQaVlHRwkA9UUJAE2MzgQANJupcpn0cjx6cFjJy1mWjUmePfFyCAD00lfHXBpt0lEZSrw0oRz1ePuVkfYAIOZw/Oxrqwufl47VEACcPCwEAPI3UACIvUjXyIu8Uo3PyucAgI6UkEKFB5sUAOh9SACwp0tmKtV4K1vlMreDpFpH0aizoQBACjQKopRU+2SGPqvOypPK1lABAEo+FQCoSvv9a0IAiJkCmoXJJynQ/DUAQBKUel4EAL548sULGwMA02RRlIz2dFyJngWaKJO8qf/O0HmtWhs+Nw7/IwCA7DZcDgAweNri4FiS+dURVjI48/tANApnZrb92TUAoB2fp5aFAEBdmMnPvlH4s/rnRgoAfBeE9sfMQgAgzwKzEABIsrSjowSA+qIEgCZGM29aVSmh2UyVy6SXoy7zxUZl2gOAmOTZ40tDi3iaOVXDLBpt0lGZwdPiiZcmlLHWaHvLsrFkRitDtCSoAHDC9XEA+MXNjxV+6SsIxmRbtZJXqcZn5XMAQEdKfj08vqD2y2G18yITLrO29yHpWe/Re2JwbMy3QZdltz0rfl4KogQAuqhJC6h6H1JS7ZMZ+qw5y+haeaXks+/4Z4NjY90lM7Pv/emR4FiqJvrkk54Fqr9Oc9qafJICjZ7XU8viAOCfnV+4gN2ri4YqxdA10G4FCR1ookzypnv0rl2D3QEA3nnvg+BnHn719Oixutx82YQ4AHgFnEqVl/x1hJUMzvw+UAoAtnMAQB2+J6WARSOZkxa8Ufiz+v0OUiQzC68t7Y+ZhQBAkqVmIQDQvkJHRwkA9UUJAE2MZt60uqRIs5kql0n6zLrMFxuVaU8tJyZ5NvelEACo5awAQKNNOiqTAwAjIwDQ3rJsDAC0MkSztJpUHw8A8HMBAFoqVRCMybauer9jAEBHSkiizoNNCgD0PiQ9a+98WanG588VAD4FSbXehzTapIuaNH+uYENJtU9mcgCAltG9+VAq+ew7rjgAHCEAEBMEMAuTT/rO6I7N6SPiAKDJJy2g6nnNX7YyeqxfXN+tQQCgSjF0DbRbQWOOmiiTupGHZgKbt95dH/zMwwAAdLmZAMAr4FSqvONz2oiwg00GZ34f6CDYhTEz2/asYt9v7WDTGNYDz7xe+LP6/Q5a8jcLry3tj5mFAECSpWYhABCsdHSUAFBflADQxOhMAECzmSqXSdUxTbxiKgLtLcvGAEBdOqnipI65NNqkozI0eqGJV2w2sr1l2ZjDsVaGqJWuevk/Hhp3OD7pphAAqOqnABCrpGkrv1KNz8rrZ61U48mnjpSQRJ0/r9TSmy6VxkbRzMIXXqVaHADovPQ+pNEmBQAasdPvF80+ewAgWNFlWTLX0tGL8+55OnpsH0mU6bN+948hANA4gU8+qRigBoK0qKnJJy2g6nk9+XIcAPye0efPbwwAqFIMXQPtVtCYY70AQGCzYk0IAN+5Kg4Auttw6YS4y7RXwKlUucOnO2yUVHt5U1qGNzP7lAMA6lxqB5s6shMEAMiLwY930ZK/WQhB1D02C5+HpFhkFgIAqUZ1dJQAUF+UANDE6EwA8F2YzVS5TASAQcVGZdqblY9pHqtJD71I1TCLRpv8SEmlyuY/mniNiABAe8uysXGGefJioEqa6uUzAMwJjiUA0PsgJpe5cu0Hbc4rNiuvn5USZQUAkqg78cbaeaUAQJdKCQB27TUhODbm26BymXRe6ttACUJ/UWrBDpt8v8hpW+VNY6Gz8qRGda2MXpwLyedFYxcU/qyHXz290LPALEw+CZp1yZ4AQJNPmj/X83oCAMB3GXdNuFcXDVWKoWug3QrqcmqlnORNv+i6ZvQ8fmN16J797asejh6ruw397o8DgLpnU4dPAYCSaq9uRMvwZmHyS4UL7WBTR/b+p0MAIC8GP95FOz5m4R4fdY/NzD5/fg0AaGHZLPwb0NJ4R0cJAPVFCQBNjGbetKPnhYkfLWepXCa1xzXxio3KtAcAsRlC1ejeBV6kOQCgs/I5AHDHnPZbo+0ty8YAQF8M9CLNAQCfKFeq3PZXAIgty+osb6XaGADQmfJfgETdz9x5pZbe9D4kR8udzwsBIObboHKZlepY27hxY7vHqmwrAYBKNeZ8v2j5UeVNY6Gz8iStec3UEAB6jo4nn73vW1D4sx4mAEDzxD75pG6gGjCdBkotmnzS+Ime17yl70SP9UUGem7lhAIAXQOFFXrGaaJM8qa7FwQANc/71pVxANDdhksAANQ7g77fKmJBSbVfMCdndrMw+aXnlnawqSBz/9OhLDNJsfruDnX4zMJdFHp3mIUFEdpXMAv/BtQx6ugoAaC+KAGgidGpAABmM1Uuk9rjmqDEKuU5AKAKHaQBr5VX2m3QWflrpgIASOU1thzVLgBE5pn1xUAJghpmHTck/hD/6Q2hW2wOAMRa6W+3AwCxZdm/BgBIo/on7rxSAHCkqMqQo+VO594fHBuToFS5zEp1rH38cfsAoLKttNugAEDyh6qWE9vZMAvHGega6Kw8qVHp7PU5o5+KHnuhJMr0Wb9zVQgAJH/ok0/qmqnKFkk1avJJ4yd6Xo8DAPixtZR3RdFQqcgcCKNnnAIAqRt9wY2JUGdDpXO/eUUcAHS34eLx8Wugyln0/VYRCxpV8QvmpIZlFia/JK05R57z9DweL87sVFXX7g6F3+Ojd4dZCAA0rmQW/g3ofunoKAGgvigBoInRzJtWjYpoOUvlMgkANPGKyYi1p5YTAwBd0KMFUK280m6DzsqT+oqCzW0RAGhPLSe20KijTZQgqF7+j4bEHY5/8lcAQKyVrst8lWpjAECXSulFevz1tfNKqV5ookwJwmd6jg+OzQGAjyIAoIvQNCKgWu2UfKpaDiXV6m8Q61borDypUensdY+7GwMA377q4eBYWij0ySfNn6sD6+9BqjGn+nzBmOIA4LtxKenaoqFSkTkQRgvmWimnhM7Pie8Czy3dm/nGwLi7ru42EADo3gw51qqIBVXV/YI5qWFt3BgaWZK05izpYNMexjgBAJJi1e5O7PttFu7x0bvDLAQAGlcyCwGA1LA6OkoAqC9KAGhidCYAoOUslcvMqVDGKuXtqeXEXA91QY+SPwUA2m3QWfkcAIipI7SnlhMDAB1tIrBRADj2uvhD/ITrQwCgF452gmKt9DfbA4DIsqx2KyrVOADoUulJN8VfpD8eWnPB3TEBAJooEwDseE4IADHfBtXLr1TH2oaPPm73WF2Ept0G1Wqn5FPVckj+0M8zV6rxboXOypO0pgLAWaPiyacmyvRZD70iBACa0y5afVYHVgKAnOrz+WOeCY6d+1IcADyMp5SrioZKRRKE6WclF3etlFNC5+fE6bx0bwYBQEab+o5/Nnqsds3IsVZFLKiq7sfLCAA+Fid7UtbR5zztYagzO0mxKtzFihFm4RgvvTvMQgCg4pFZCAC0C9PRUQJAfVECQBOjmTetOpXScpbKZdKCnKp5xBLlHADQ+VySPNPRC9pt0Fl5qo5pZ2P4rPbVEdpTy4k5HOtoE421qGEWPcSPzwAABcFYoqxqHpVqfFk2BwB0qZQqaccNKQ4AmijH5GjNQkfPSjUu26pymZXqWPswBgDyN8gBAEp89PsVW9o2awsAsQRBZ+VJWecqmb0+a9T86LGafNJn/aYAAI1pBNVnAAD12SCzpjbJ57j4Neh1rwLA29Fj/XcxtbheNCYKAJwNAKCflRSmtFJO8qY+SaSCjELz1wfEAUBHm+gaaNeMHGsVAKiq7sfL9usXB4CPBABIWUef86Q2p8aMNFev36/Ys8gsHOM9enDcG8csvLb07jALAYBAuKOjBID6ogSAJkYzb1p1KqXlLJXLpAU5neWNJcrtyWXG5n61Orc9KB60AQAYbfpZBgBoZ2NYRB6tPbWcGABoZ4OSWjXMOmZwHAB8pbxS5YpTUQBYvmZdm/PqCAAgkxrvgpvSvdZEmUYEvJ53pZoHAB9saP+lqx0bWhLsJ2ZNfSDxOVzOi/TP9xKH41i3QgGAlHV0+fL/a+/b46Oqru9vIYqA1Wq/RW2l0xLAKtZaK1JoLRbxQUX7UFpbtVW0VevPqi04yFMJIA8FRRECIoqiICKIvJ8GBJLwDgmBYAgkIAQC5EFISDKzfn/Emdy77zk7M5OTDMns9fmcz0cmN+OdOyf3nrXP2mt5P9ETALr45M71jglJIS/S7NVnTn5CCcDTTFgTrapz3wH9XJtz9ATATlpr61sJFXUhAJzDFCUAnL3ptbZFInc/phazt43Xh2tRaRP3HdC/GV2vGeB2sePmln13icvDqCRBllxjLQ2Z4xqxqS0z58REv9vyyirtsXYZ75+nhE4AOLICOAkA93dQ3xACEBmEAEQR5xIB6MU0Z1G7TI4A0K183UJZZZepiz2n1TnO8YAm5nK9DbRZNiwCoLFHU7nl6DzN6c4G5+VMCQBXxbEvOmq7idOdIN1CWUUAdG454RAAmujJbaXfnxg6AaAL5Xlb9QSAnqsut4EuZriHLt2x4ZqbaVprwucZ2mOpW47OtQlwNjR6vHoCQJtlucba11Y6CcDzc0MnANy5UgLAVT7tCxSub4YG7XFprdR/fcQi/XcwdMEux7GpzMLHTlpr61sJFTQsipNhDSHnylk400o5SwBszlnc/Zg6THHpupSEcd8BDTjTubIBbhc7TlZjJ5dcHgZNsucIAC30cI3YtCeLc2Ki87CsQk8A7Lv4fcIgANy5As57Z3J2AXtsfUIIQGQQAhBFRHPSziUEgHNnoHaZXJMifZDrFsoqtxwdAaCVIY9X3/BEmy85AkCbZTl9LNWUv6f5XCq3nMOagDO6s8F5OdPEXK6K87dpmxzHhkMAdAvl/CI3AdA1y9Lqt8erXyBQW8l/MATAHsZWW/AN9ZXXaYRpM5/Hq7dtpX75Hq+eAFDCxjU3UwLw0kL9wofusHEBSPaGRo9XLxGgzbKcrSN1X+k/V5+uSxcoHAG4bfwXIS987NVnrrF2Z54zaO8pJq2Vuq8MZ0gYXVSn7NcTAPucrY20hgpKVjgZ1uD5znPlDBxopZzTdFPr3FAbzLl0XbqzwREA6oCjM2UA3C52oZJLLg+DJtlzjbU0Y4LrNaMEgGvEpt/tmbN6AmDfxb9vst4aG3BeA64oBjgJwIavjrPH1ieEAEQGIQBRRDQn7cebnUmlXHMWtcvkAlp6vup8kOt8hFUEQOf8QStDHq++oZESAK65mTbLcgSAasp1n0vllqMjAHRn48dMJY0GZnFVHHvV0ePlt5zpTpBuoUwDfTxePQGg1W+PV/+5qK0kp6W1W7HWRgBopVz3uaiW1+PV27bSaqbHq6+60e+LIwC0mjnsM/39gLrlcAFIdj2zx6uXK9FmWa6xlrqv9Ps4dALAkRV63+AWPnYCZdsfZQAAIABJREFUwDWg0qRtjgBQ7TVHwujCi6t8hjNnQwUNi+JkWIPmpzmO5QwcKAHg8g2uIda5oe4ucem6lABwO2E0jVknNQXcLnacrObaCAkAJ8mkDlPcopqaMnCN2AM/dX63p8srtcfad/HvZbJxACcB4J6JgJMAfLlPCEBjgxCAKKKxEABql8m5lPx23FrHsTM0PsIqu0xdRDvd8vZ4meZLQgC45mbaLMs1yFECoPtcKgJwSEMAVDsbOlC/fI4A2KUyHi+/jUt3gnTNdEcK3QRA55ZDdyu4z0VdZbiUSrsTE6c7BtyVcl0gHd3K93jNEAD6fXHuRvZAH4+XT3b93euhEwC7nMHj1e9WUK08p6unqcX/YwgArZRz53orIQBcA6pdfsI11m4nBODfDAGglVeOhNFF9SaGANilgxzBDwc0LIqTYdFFIiffpFIZzt6UZmfo/g4oueTSdel9ntuFofkGOqkp4CYA3O6SfWeDIwDllU4ba25Hlu70cgSA9mRxfwcD5jm/22JNMCPgLOJx4ZiAkwC8zjwTAScBSNp7jD22PiEEIDLEHAEoLy/H888/jyuuuAIXXHABbrrpJqxYoW96C2DPnj149tln0bVrV7Ro0QKWZSEnJ6dO5xLNSTuHEADOnYHaZXIE4Ddj1ziO1fkIq+wyddZ/tOLFLWao+wrX3EybZbmbHW0q1X0ulV1m3km1uxGteHm8+q10FwGYrH/g/CXRGVoWDgHQNdPRRE+PV98sS6vfHm/oBIDT0toXU7URAFop1xEbVSCdrmeDBmZ5vPptd/p9ce5GlABwvu60x2ZhGAnHoRIATldP7Rf/O0dPAGilnDvXHq84Cwdc9dn+uThdvYsAfKAnAHThxREAuqje+JWeANDCAefVHirCIQB0kcjJN6lUhnN1+clgJwEoPauuPtO5xaXrUmkTtwtDLWZ1kkzAbWPN7S7Zdza6MonY9L7B3Y9pvgFXVaeSTE6G5f1kp+NYXS4L4Czicdk4gHMXhOsZAZwEYM2efPbY+oQQgMgQcwTg/vvvR1xcHPr164fExER07doVcXFxWL9eLxUBgBkzZqBZs2a49tprcf311zc5AsC5M1C7TM4j+1ejVzuO1cWeh0MAqD7X49VXnCgB4JqbabMsRwBoU6nuc6nsMnUEgD7wPF69VSNdUHI6zj5TnASA05zSnSBdcNvhU6ETAHquHq8ZAmBfTHH9EoC7Uq4jNqpAOt33RfXM3MKH5htw7kZUz8y5utAeG11uA+BepOn+ZmizLCerofaLz83Rp+vSSjlHAOjOIbf4tAe3cc5Z2w6edLznkx/ow9goER7K7MK8QAgAp32mvSg6qUw4oPdDrg9jwDznIpEr3rgJgL63gYbn6arPtA+D89anhZ4XF+qfi7TBXCfJBNw21hwBsO9s/DIMAsDJaqi9KfecoZJM7u/g+bnO71bnygY4i3hcNg7g3GHjJGOAkwCszjzKHlufEAIQGWKKAKSkpMCyLIwbNy74WllZGeLj49G1a1f2d0+cOIHi4mr7sHHjxjV+ApDqXPj1ZNwZqF0m51PedZQzfVQXJKLyy9+XryYANByFW3hRBxquuZk2y3IWeZQA6D6Xyi1Hl3BMK3ker17aRBNzuQeOXXfs8fJbzpQA6Nw0DikIgM4tJxwC8MZqp6sMF1Nv34WpjQDQSrmOAKjsaHXN6CoCoNPdhmNvSvXMXFMnJQBswNlA5yItVALAyWqo/eJzs/UEgFbKObJyCyEAnKWgPbeBa6zdGgYBoPfDwfP1BIBW1Tcw2mcqReOcWkIFTYvl+jBolZgr3lCpDPcddCThebpQQLoLw3nr0/shRwBof8k7Gkkm4Lax5giAndh0GaknALRw8Eemqk6lntxzht6PuQbzfh/vcByrc2UDnM9wLhsHcO6CcJIxwEkAVmQIAWhsiCkC0L9/fzRv3hxFRc4moFGjRsGyLOTm6r2E7WgKBGB2qtMvn7Nno3aZHAGg3uM6D3qVX74u/Gch8Ub2ePUVJ+pAw/U20GZZbruTVvK0BEDRLKsjAPRB7vHqZRqUAHA6TppazBEAuhOkc9PIO1nqOledWw49V49XTwBosBTnpmH/DmrTU7sIgGZnQ9WMriOiNDHX412EEg0BCMfelBIATtJx+/jQCUC7F5wBZzq5Eq3ScrIa6lj0LEMAaKWcO9fuRDqoW/hQ1yausXbLAScBeHymngDQBHFOhkWr6hwBoPNQV7gIB7QgwvVh9J/rXCRy4VpUKsPZm4aank2/A85bn+5scDIs2l+i25EF3DbWXGOtndjcNFKfiE2DLLmqOpV6cs8Zej/mdpf+O2dHSN8B4HyGc854gHPnkCOMgJMAcEnf9Q0hAJEhpghAz549cfXVV7teX7VqFSzLwsKFC0N6n6ZIADh7NmqXyT1EfpHgdB7RWVCq/PJ1BICGo3i8er1jOASANstyN2bqKqNLSFS55egIAHUe8Xj1FUIqKeEIAE0tZgkAqXzqkptzT4ROAGj12+PVL9ZpsBSXcHx3GASAJsvqdjZUUjSdTzgNzPJ49USUuhtx9qYjFjn1zNyCjtpl6hKOVfamOgJA3XK4qjp1LOLSdcMhALR3SNdYS12buF6QLQdOOI7lGrGpe9hARoZFq+qc+wndsSliGjVDBb1vcH0YtErMWWtSqQxXfaa7S7p7weYc53fAeevTgkg4jdi6ggzgJgBcY62d2HQeoScAdOeQC5ykzc3jGStWej9el6VvrH1u9nbHsbodWcD5DOec8QAnCeLmC73HcEF/9Q0hAJEhpghAp06d0KNHD9frGRkZsCwLU6ZMCel9IiEA+fn5SE9Pd4wFCxZEbdJ+RCpenD0btcvkEhrtSYoer74BVUUAso6qCQB16PB49XpHakHJEQDaLMvdmCkB0BEblVvOwQI1AVB9Ll2FkC6quS1nGlrGNZ3RB47OTk9JADRuObT67fHqF+s0WIqz07M39nLhQ4B74fWRZmdDNQ91EgFqacgt6GhvA2dvSh1NOF09dcvRBbep7E11c4vKNLiqOm1Y5tJ1qVRGR1YA4NdjnL1DusondV/hpGB08cmRMCod5MK1qPZ6fZaeAFDCxum0QwW9b3AE4H+EAHDWmuEQALsMy+PVp52n7Hd+B5yzDt3ZCKcPg0s7pzk2XMCZndhwBIAGWXKLatrbwGUx0MIc11j7DElu1t2PAafjHWeMATivASfDovcYzuWrviEEIDLEFAFo164devXq5Xo9OzsblmVhwoQJIb1PJARg2LBhsCxLOaIxaemWN2fPRt1yuKqA3UHA49U3oKoCs/ZqCAB16PB49dudNICJczf6M2mW5W7MVMur89ZXueUcKFBryqnns8erl5RQAsA5OVDnEW5ngz5wdHZ6BwvcBOCo5oFDw708Xr37CQ2W4hKO7XIKUwRAZduqWyCoCIBuJ6ouBICT1VC3HF1wG10oe7z6fgXaLMstqqlciUvXpZVyjgBQ8wDdoppWXrmdoFRCALj+Enrf4PowqKyGq9JSwqZrnA8HtGGZI4zPzXFWiTlnHaqV5/IN4om8TGd1vCm7wHEc56xDdzY4O1wqw+KyTmiODeesY/9cNwzXuwNSAsAtqmlvA9dYSwtzKxldPU1u1t2PAecznDPGAJzXgPsOqIUyt8NX3xACEBliigDIDkANKAHg7NnCIQA0IEYnP1EtvHQEgDojeLz67U76IOfcjahbDkcAqK2kbmcjHAJALd88Xn1FmVbVOc0ptSzlGrlcBEBjp3eg4LTrXHUPHCp/8Xj17kaUAHB+2lTWw4Fq5XW9DSrXJp37CU3M9Xj1zY+0uZnLNxhOCAAnq/ltiARA5W6kI5e0WZZbVFO5EheuRTXKut0KAOj2spMA6DzFVZItHWj1mSOXtHGd68OgshrO/5y6G3GLtFBB791cIzaViXAVXSqV4fINaH+Jbpdzw77jjuM4Zx3a68UtPukuDGd1THNsOItZ++fiAvFo7xBnNkGlTa8wBIB+t5yunga36eyLAecznDtXAPjxgJr35HbCaJGBI/j1DSEAkSGmCID0ANRgVrLzRtOdsWejdpncNjK1h9PJT1R++XuOqAkAdUbwePXbnTSEinM3om45XGWGEgDdzobKLlPnKkMredyCklbVOQJAHYu4pm1acdL5aeccdxMA3bY/rX57vHp3o/EkWZYLOKNVfQ5UeqHrbVA1besqnzTUyOPVSzpobwNnb0o9zbmqOl1Q6hKOaYXS49X3K9BGTe7a0t0KLlyLVih1ZAVwE4C1GumDqnCgQzKpPnPOWbTHhrPWpLKaLxgCQJubdang4YDKlbgdo2cJAeB09TTvhcs3sC8SPV59ivv6LCcB4Jx1aK8X58REd2G4Pif6ubiAM/vn4uxwKRHlpKZU2sQVZGgvCpeeTW1bdbswgNPxjjtXwNnYy/0dUCtU3b2oISAEIDLEFAHo16+f0gVo5MiRMecCRAkA589M7TK5hEbaHKbzPFYRAF3zJXVG8Hj11Q4aQsW5G1G3HI4AUDcP3QNHZZepeziqPpfOyo1W1TkrN+pYxH1ftOKkSzjeryAAuu+AVr89Xr270auUADCBOnRRz6EnkV7oehtUPRs6VxcaasR9X7S3IRwCwC2qqV2mLuFYZbMbDgHQSbbobgUXrkVdZbgFwi+JffCaTDUBUBE23blS+Qn3N0MJNmetSXc2dGQFcPc26AwBwgHdreB2YahOnNPV02R0zoHmR4QA6JyzkvYecxzHOevQ3gbOiYmSMK7PiebYcATAfhzXC0N3DrmdZrqzwYWx0QIWJ6uhf1/c3LI73nGyWNrYy8nL6C6jzmq5ISAEIDLEFAFITk525QCUl5ejffv26NKlS/C1gwcPIjNT/0faFAjAB8nOSgPnz0ztMjkdKa0M6fTnKumFjgBQmYrHq692UALAuRtRtxxua5ZqeXUPHJVdpo4AqD6XrrfBRQAY1wnasMw99CkB0PlpZx8rcZ2rjgBQa0+PV+9u9CpJluUCzuiinktVpd/X+5reBhVh01V0VQTghIYAUGkTRwBeXJjuOPaJ9/V2ldQtR5dwrOqx0cnLqFuOx7sIPo1ki54r561Ptdc6JyYA6DLSSQBW7VZrn1Xfl+5cN37lJAB3TdRLH+iuFddYS3X1XKMm3dnQ7QaGA0pW/jVzs/ZYugvDVdXpfZ6zN6XfgU6+uZak4HKNtZQAcE5M9DvgwrUoAeDCtejn0t1j6E4vV2iiOxtjmDA2KvXkds1oz4ZOhgU4+904skIbezk5Iu3H4f6+6xtCACJDTBEAAOjTpw/i4uLQv39/JCYmolu3boiLi0NSUg0r7t69OyzLeWkKCwuRkJCAhIQE3HnnnbAsC//73/+QkJCAN954I6JzieakpVuNnD8ztcvUaTNV1oM6Zx1VYNbur9UEgC5SPV59tYNWxzgCQN1yuK1ZuvCaqHngqNxysjUJx6rPpettoAsUzsuZypW4ZFm6EzRd46f9lYIA6OQMVP7i8eotKF8hBICTadAGWI4A0GN1BED1fekSLVUEQEfY6M4G14BKU025Bd3NY5zzUFd1U/196RqWqVuOx6tPrKXnypEVmh+iazAHgJtGOvNDlqertc+qZnRdf8mGr5zyE076QOdsOI21ut0KwL2zoauUhwN6rlzIHNWJc1V1uiPK2ZvS7yDjsPrevSbTSQBuZAgANUXg7ltU2sQZHdAgS12Pj+r5pZMuUkkk56JHiQ2Xxky/W66qTt2NdL1mgNMYgiMrZyudjb3cbiTtg9DJLBsCQgAiQ8wRgLKyMvTr1w+XX345WrRogc6dO2PZMmezj4oA5OTkaF18PB5PROdyLhEAzp+Z2mXqGuRU1oM6WY1qK1/3EKG7FdzNjhIA7sb8x0mhN8vSB7mu4qRaUH6lIQCqz6XrbaAEgLOd+93rTgLAyRkoAdD5ae/LdxMA3S4Mlb94vHoHmnHLnASAyzeg+ndd5RdwN8vqFp8qx6JlmsUnTcz1ePWuLnRngws4o5aGj72nJwBUUqILOFNJm3T9JdQth1v4UALAhWvR3iEurIkGCOqaH1VEVEdWaAMqt/ChvSicrp421uoII+AmNrpKeTigc4sjl08RnTi3qKbmATonJtVCWWedu5KEYP0iQe+sQ93euHOl0ibOwIESUV3CcTjWuVkkFZwz0aDEhuvJovdDnXkB4N5h0+00A86iEFcUo7p+7u+b9kFwBL++IQQgMsQcATiXEM1JO5MQAM6fmdplPqPZFqTVA49XL6tREYD0w+qHCD1X7mbnIgDMjZnaZXI3ZhpwpotzV1UodQRA9blCbazlCADtV+AWM5SE6AmAOwVXRwCo/MXj1evP6QOPyzeg+neWAJBjde5G9Dw93kVYrAm0UREA3Y4N3dngCADVlHOBVdQuU7ftrpKi6cgKdcvxePU9GzSBldutoPcNzqrxFwnOhbIuVGjvUfc81JGVLwkB4IwO6Pelu8cB7uqzTq6k+ly6Ikc4oGFsXOP8vz9wEgDO1YUWDnQEwKdYKOusc2kIFmetSQkA14BKpU2cfJMGWeoSjiur3M8v3a4ZNQTg5hZ1e+OCNEcRm11uUU2bm3XPGcDZP8UVxaiu/9F39X/fp0qdMkOdgURDQAhAZBACEEVElQAQJwmOAFC7TN22v8p6UNfwpErM1REA6nrB3eymJjkJAFeZoRUvTitP8w10W84qu0zdtr/qc+lkNbSxltMzU7tMrkmQEgBdwrGKAOSdVMuwaDWVe5COXeZczHD5BlSGpZN+AG6yoHs40fP0eBfhsx3qQJudeadcx+oSUOnn4hKOqZsHJ+mgmnIdAVARUd3com45Hq++Z2PwfCcB+CezW0EldpxOmxJsnfuJyopVR1YoAeDucWOWhp5wTGU1nFf7DcOdnystT32PC6C8sgpzt+RpHdEAdyM29zdDG0W9n+jtTal1ri7fQFUp1+nqaQjWzxkCQBfKXMgc3dngdm9pkKUu4Iz62nu8etJMszO4HjpqY80FadIdNp0pA+CWNu3L188Z+/2QeyZSXT8XnkcduXT9Yw0BIQCRQQhAFHEuEQAuoIXaZT6suSmorAd1DU8qiYJuG/ndDe6Fsu5mRwkAV5mhdpn/Y6Qy1N5Ut+WsJgDqc6WZBR6vflFNG2u54Blql8lt41IpmC7hmG55c+dKJQoer94uky68OHtTKn+prPJh28GTykZcar8YDgHQNd7tyFUQAI1ki34uLuGY+pRzD92uRIqmCzhTNW3rGlCpW47H6+zZKC6rwJQvvsKO3FMYND90uRJ1o+KqtHShvDAMEqZrxA7HgpImHHNWrFR7zRGAn5FkdBpCdbbSuXth/zvX9bjQXRiuGEDTfbmqOt010+UbqCrluqr6EuKBf/1Ly7X/f7pQ5qrPdGeDa6ylPWw6m19VeF6oCcechJbaWHM5OlQOqNuRBdw7G5y8zF444J6JVNfPmRfQRmjuXOsbQgAigxCAKCKak5ZWn7mAFtocpqtmqkJ6Xl5SdwKgWijrKmTUz5uzN6ULFM7SkAbf6HobVH75OgJAHYs8Xn1zMyUAXJojreRxkhIqQ9LJNFTSC925UjkFt0gbTRbKnFUjlb8EmutuGbfWtViiBODdDTnK96Tn6fHqG++2KwiALtiJfi4uhIoG7XEPXdqLEtAIU62yasdGt0BQEQB7z8ZA26JkIFmgcHOLStE46cPPCQHQ2R/S0DKP170b6PP5UVnlw7ospwUlpz8PJ+CMVpRXMATgp2Tn0N6A+tmOw+gwcIlj8Wp3UdPpz2kKLufqQsO9uH4gSlZ0bliqSrkuNIym+/6MIQA0F4XrbaDERvecAdz3eR0BoPp37h4Xzu4StXvmcnSovamuIAO4bVu5XaMbbT023G4FfYZzhQvaF6bbPW4ICAGIDEIAoohziQBw1TFql6lr1DypsB7U6epVibk6AqBaKOscg6YQGzXuZkftMnWVV9WWt66aqfLLz9IsvGi/gserb26m7hBcmiP1y/+7JoW2rKLKRQB0iZp7jqgJwI7cU44q2dGiMteOkcer30qnembO3pTKX+yDNhlTuZBuK131XqrGO+pnHhhHCsvg8/mRdbTY0ZNAj+MIAL1e3MKH2mXOSj6IN9fsw48HVFfgNmUXoLC0AplH3FIZ1d+X3+/HgHlprmPtqcH212kAU19GrkRtW7kUWrr41KUGq/oV7PKTM2ercMu4tfjV6NWu6jO3+FRlMegq8NQUQedYBACdhjoJgF1+Yn89ALvU8OvCMzh5+iwGzEtz7ErRRSIn6aC7FTp7U9V80eUbqHq9dJah1AKTS9elhgRcPxC1wOTIJbUE1pEVFQHQSU2puxFXQKN2z1wuC+1t4ALOaOFA90wEnH9fnBMT1fVzuSy0J4rr8alvCAGIDEIAoohoTloqq+ECWqiWVyc/UXn76/SOqsRcnT5WtVDW9QtQAsDZm/ae6CQAumY61YNBpzlVSS90lVe6W+Hx6pubqbOOnQAcLykPLlZo6qTH625AtTtz0IXXc7O3Ky07VQuEgI1p5xErceZsleuhSK/Bwh2HXV70VHrB2ZvS6je3AKF2me98uR9L0r7Gb8aucViCqt7L3jBc5fMrnZ0C4+vCM8FG5r9N2xRcMNDjuKZtSkQDO2wVVT6MWrwbU5Oyg98vdZVROUn96a0NytRilU77Cw2xsX9P9tdpRZnrV6B9GC98moZtB08iv7gMz83e7uijue5F5zykoWGBz0+tPT3e6ibcsooqlJRXOu4VdIHUaah78Xm6vBLJ2QUuadM1Q5biZy8tV1o2UvOAZelHUOXzu+Q8AHD1kKXOeWoL17K/HoBd4pV5pMghpwuEzv2HOOBw1WfqFKOzN6W7vB6vPt9AJZXRyYWoBea1DAGgRgdckYMSm/5zd+CjlIM4WlSGL/Yew/ubDgQJOb1v6BKOVT1suqr6MtLczD0/ado6l8ZMiQ3XN0NdtnTPRMA5DzsOWqI9juaHcCSM9g5xZKW+IQQgMggBiCIaetKm5pzAnM25qPL5XYmDXEALtctU2ekdKDitXHTotjtVgT47805hX34JHp+5xWEDqFoop+UVIvdEqatKR4NU7ASgrKIKh0+dwZzUXJw4fdbll6/T0qqkTbrmZpVNYYAAvLcxB79/88ugEwg9V90iDXATgICnuX17WSW98XjdxEZ1jH10HLQEy9KPwOfzw+fzI2nvMdcuUGDhEVxYEGcU3ej38Q7szDuF0+WV2P11kcsl5Y4JSUjLK8TKjOpF3Rurs3DjiJV4Zfke1+KXDrsbC+0XeOfL/Y5m9oB3u+p9fjJ4afB9qNSADkpk419YrCUMQxbscszXY8Xl+DDloOsaeLzVJMDeQDkn1Z0a7fEucvVwcN9HYPGZfawkmF9Am0QDI/tYCfp9vAOvLt+DDoNq+l+otErXDwS4JVuqEVg0UKnMjwdUz6+5W/KCsqMbR6xULlQnrd2Hbi+vxtVDljq04bRSTxc+uw4VuqrDqlF4pgIvL8nEra9+gfTDhS5p05zNufjV6NXoMnKVy2q14yBn75B9J8r+emBe2HfvXl2+x+HM88T7W+Dz+V3f2Y0jVqKwtALJ2QWOxnjagOvxVpPDAfPSXFaYtG/I462WYdmryoWlFej12jrl9xogCznHT2NnXk2fA61+X/sNCfP5/FizJ9+xe0hlWJxWnfbNBIa9qBOwyKVzS9fcTBtgPV71rtnitK9djfuBqvqinV+7doTozoauD8Pv97ukcJy9KQ1u23LgJPrP3RH8napv7t8A0H6gU8Kqapz3+fw4Thp773ljPVZnHsXrq7JchSGV25uud6e+IQQgMggBiCIactIW2Zp7HpiW7FrY3DhiJY4UlqGwtALFZRXILyrD8M8zXM1WgRFofkzLK3Q51NjH8M8zUFHlw9lKH3JPlGLaumzkF5e5dLQe7yJXtezk6bPKRbLHuyj4ABg0Pw2JSV9h+OcZSj9zj7fa0YM2T/5t2ibXcQGN8ILth/DvWVuD1Xh6UwyMnXmncKDgNOZszg1eD5VffkAbGfh3h28WIrTi5fFWV5J6vvoF7nxtXbBps/RspfJmS51TdOOPk77EsvQjmLgqS7l9rxvL04+4pBGmhopQeLyLXA/rcMY1Q5Yi80gRVmQcDWnxuWaPfsciYIFY23uoej6GkiZN+6C9JNygTZmqQRscaxsB6d9PBi/F/uOnXa4jgUHtCHXj7jfW490NOdh28CReX5WF/3y0LUguqFxJN2jKtalBbRLjX1gcvB9uzjnhSi0PZfx3zg5XyJz933NSc+Hz+ZF3shT9iFQnMF5ekum6pwQkbLTYQndf31yzz7X4/dlLy4O/F2h2zy8qq3Wu2cmKigAExuzUg1qiGBhPzdrqaEq9dugyFwELjAXbDwWlh78Zuya4UKWyPY9XbwdL031VI/6FxS4Zmse7CJ/vdC5SS89WYthn6a7mao+3muA+/E5K0O5X1YPi8Va7G9l301ZmHMWaPfmorPK5nmGdR6wMFoPum7whuHNE5VIeb/V98v1NB4JZE5VVPlRU+VBWUeWSl9kLJBmHi/DAtGRcPWSpy/DD462WZGYfK0HfGanoM2UjEj7PwDVDlrq+Z/t99LnZ2zFkwS7MSj6ozIIIjBOnz6KsokrrJFYfEAIQGYQARBENOWl3f+2WcNRl0MqWblz/jcTEXoGgW9jn0qCLhsfe28xKQOxjefoR7QOCVuNUqbKq0e/jHfhRBAsVGdEbqor+uTqoraeJceurXygdk86F8eaafdqiRijj58NXsL0or6/KchUyQhneT3Yiv6jMFVqlGtfU8v5peYXwfrIzpP/viwvTtfeshhzc7t7s1INYnFZdWe8+dg0emZGqLCCFM8orq+D3+0O63oFx9xvrXbJRE2NJ2tcu1zDVyDl+2kUIIx3Zx0pcvWLhDLpbYx/2HUMum8AkhABEBiEAUURDTtpz4SbfkCNUghI4tkMYx3PgwTImAAAgAElEQVRDtzUtQ4aMpjHiw9jFCWc8+HaydtdAhvmh6i2TYX5MWlv/vQFCACKDEIAooiEnLdegGep4d0OOS3d4ro6H30lxhXfpxnUvLne5m8iIvUH7Bhp60GC6hh7hyolkmB/UBcbUoHKRc3mszjwa9XMIZ0T7vnGuD52jl0kIAYgMQgCiiIactDRmPTBUoU2qcX/iJpRVVGHLAbXO3j7+34fbtBpvOvJOlroalHSj/9wdrgRI3Vi1+yiW7jqCXySsQPexa1xezPYxeP4uV7Kjbug003T8d070CUV9VSrPlWFq1yYwaMKrbtCGbBNj2GfpyrC1hhp9Z6QqG/NV44u9x7S2qHUdofQ9NJbxUcpBXBvmwptKEE2MZelHXI3L0Ri1SZc83mr5mN/vr5M8hY6fvbQcMzcdCKlnKtRnUWDs/rpImQ9S1/HnKer+ibqOUM0aTA4aflcfEAIQGYQARBENOWntTaQPTU9B97FrMOWLr9hmHvsIQGX1GRjvbsjBrkOFqPL5sTPvFG599Yug5Vn2sRKlYwkA5J0sxeFTZ/Dykkz8bdomh02lfeSeKEVllS9oUVhUVoHcE6XIOX4aE1buxcGCUiza+TVmpx4Mumr4/f7gf/t8flf677DP0oOe50cKy7ApuwAZh4tQUl6JE6fPOsJpCkrKUfFNwNBba9XNyYExaH6ay/6NG//+YGvEVbo7JiThxYXpeOL9LXhuznbcMSEJo5dmorC0IuwFiMerX4Q9/E4Knpq1VUsaQyVRqkGtMD3eRZi+fj8qqnxKdw6PN/yHtW78450UPPbe5pAXwGl5ha6mcvvgNOK6cbyk3NGo39DjqVlb4fP5ld+DfQSaIWliKDeWp7vdaOiYk5qLvUeLcbAgtH6bcEY0emgC7mOFZyqUCemBkXG4yNGkabcunfHlfjzz0TYMWbBLOddV7miqUVZRVev3er3NDnjmpgN4th4WivZ7UdLeY0qHrUD6L/ec0Y07X1sX/H/cPGYN7piQhFnJNZkee44UK40XAmPYZ+k4UliGzTkngsWA6ev3Y8+RYny8ORfL04/gb9M24fqXlmPLgZMOR691Wce0O3hzt+S5/l6oXfPVQ5ZiZcZRZB0tDppPcMW5v09PwY8GqO+bdH75/X48N2c7ek9cj/yiMuw6VIjHZ27BpLX7XMTwN2PXoKyiShkOyM117ufUGas+IAQgMggBiCIaatLO3ZIXfAj+ImGFwyoOcDqdJO09ht++stbhD08T/j7dlodxy/a40ml1CaoB+P1+V2VcBXrz/83YNdogqXBBHzpcemIAPp87ECi/uCbJuP3AxS5f6mGfpcPv9wdJi9/vx1fHSlBeWW1t2XnESjzyjZPFvd8Eq9ldae5P3KRtDAs0gv16zGqcKlUn7AaQd9K5oHpzzT5MXJWFt9Z+pa2y0Qav2akHXd7Zr62stue885sHSMAOUvcQoL7ZNJ1TFTTGBWt5vDULuz6TN1Zb3KbmunIgVGPbwZMoPVuJ9zbmOEKBQiHDgQVF7olSzNmc6yKr09Zlw+fzB3MIHntvs7YhdtSS3Ri/Ym/Qccjv9wevZ2CoXEw8Xp5k2KuHVw1ewpKVwHjom7C4Kp/f5XITGLePT3LMgWnrsh1NiemHC/HMR9tcDaihOE/Z03RVYV+hDJqA7fFWu30VaFy8VONfMzcj4fMMZSNvqDtqt776hStB9rfkms7dkhckU3abyMB3Ry0w6TVcuuuIYzf2nje/RNbRYmzKLsCeI8VBEh/ICKDZBfbx/NydyD1Riklr9+HrwjPB/2cg34Ibqh3Rw6fOBG1Jp6/fjw6DlmDGl/sdWQ+ZR6rtRTOPFDmeCYHkW5q9cs2Qpfjd6+vw7OztqPzGVY5a8Kru0yqoCOF/5+xw3Et9Pj8OnTqjDIPTBcTRYKz7Jm8IZjcANUnHgaA/u+ROF+JVWeVT/k1WVPmQX1yGiiqfcrd54Kdp2vO0Y8aXTjvw92wZKHuPFmPaumxMW5eN9gMXY8LKvUjNOYFPt+U58jjsLoBDF+xyzAmdXbZpCAGIDEIAooiGmrS5J0rRYdAS/HjAIkeiZACBcJ+AJ7fvm1CbXYcK8d7GHGUwFABMTXI2UaneW4XAjY/asQVA0whpkFVdQCVE+/IjcymoqKp5IE9NynbZp3Fx73bknSwNejLbqy73Td6AM2erkPC5czEeSDP1+/0hP/CS9h7DiEUZwQVHALoK08yNOXhxYTo6DV2GN1brg2iA6gf16syjKDxTXeVR6cj/9NYGx8P6V6OrFyXztx3CjwcswoB5aQCcidM0rZPbvn95ifMhozvu0XdTa21Io77l9jE71Z0QDDhTmrcdrMlx+LrwTJBsq97PvjgI4HR5ZXChGaiG0s9+zZCl2Jmnlx1MXJUVJAif7TiME6fPIuNwkcNpZVn6EcdD/Pdv1gT+6BpRdcFMWUeLXX7p9t8DECSzOolLIJdB9fv2BUWgUv38XLfLTWABa38tkO69cMdhvLrCbaVLR7Jt3i3Yfgh/nboJ2w6eRGWVz1Xh1dkf5xeXgWLsshoy/wcSrmTPeAgs1H/7ylrXe9j/H6szj8Lv9+PRdzejxytrXQWSsooqzEo+GMwcUeUnBEZxmbpCS4OxHpiWjHYvLMbUpGxcNXgJer22zhVEZw/RC6Ciqtrm0u5xbydIPp8fz3y0DY+9tzloHVlZ5SQ8t413Z88ACH4nYxSBbTrQ3RSaiRApMg47nfZUqcvZ3xSBAKCkvBKbc064CnIqUHJrX9wXlJRj+OcZSNp7DKk5J/Dmmn2OJG8ONAn+g+QDyuNoboDf78fYZZl4fu5OVFT5kJxdgIGfpuHQqTMoPVuJWckHG8wBCBACECmEAEQRDTlp527JCz4MKMoqqrAj91RINyI7aJjYgu2HQvq9iiqfq0JmB90uDVQnTeAZYkF6oECdvBsKdh0qxJzNuaio8rma9+iiNBSUVVQFF3v2h5LdT/0XCfrAtnBBtew/HlCdB0HTesPBseJy18Lo1eV7UOXzB5Nh7amhdnJ56NQZDJi3UxnUs/vrIjw0PUW55U1Tme0/Cxw/JcSYevvODh26uXLmbBX+/cFWbeo14E6d9ngXaa/zvvwSvL1+f/AhnnP8NN75cn8w0XTNnnz4/f7ggp5mWry19iscKy5Hyv4TjoVCyv4T6DBoSTC91/53FvAZB6odw7qPXeNadOiC8lQIkMtA6NHZSh827DuOkvJKpcSPfud2K9XDp86gw8AliH9hMb4uPIMDBafh87l3a5L2HnN9fwESFYA9mfbaocvw+qosh/97jiaJG4Crrym/uAwfphzE5pwTDnOEwILXjpLySgz8NA3eT3a6CirzttbIDAOSjJ6KsEX7//sLTfKuDtST/+Yxa3DXxHXaxX8ABSXlGLpgF1ZnHoXP5w9WyUvPVqKyyufqrbJLbijs8svadnTpbpyOfBaeqcD6rOPKa67DVYOdvUN20l4X7CU9PN5Pdhp5XwAOqU47W55FXfEhkakGwtMaG4QARAYhAFFEY5+075GAkcWa0JZwQStPgQWLCdDt0ryTeiISDmhzFV2Uhor8ojIXUbOHsXQZucrE6QJwB5HlF5UZC2+xS1QCyZRFZRXYl1+75IqDSuJD0zIDC6rnZm9HeWUVTigq7TqcOH3W9f4BElMX7Mt3S5xKz4ZWpQug9Gwlsm1VtYMFpViS9jWWpDn1xFSyR9/DTgr2HCnGqt1HlXIB6sZyzxvrQz5Xv9+PzCNFqNQszGiwXSClOIBdhwrR45W1eG1l9Q7UgYLTrsX5zE0H0GHQElw7rHqnyu/3u+Q+T7y/xXVeuw4VOnTJpWcr8ezs7cEdUB1oY6adwOWdLMVfp24KmWjaYSclgWTiQNK3HY7rte+44p30eGBasuP3w1kwc6DmEtwCcl9+MW4YvgL/mrlZe4wddslV74mhz73aQPui0vLcab+RgKbAD/w0zcj7AnBIJjuQROu6gBK4T7bUv2NPfaCxr6WiBSEAUURjn7R0+3cZiUCPFFTv+th7oT0wQgG1+7RH0dcFVDYxnolwDxfdbQmZAU2vCdDFdEDGYwJ2AjBhpblroSIAr69yy5SOl5SHpIGlKDzjbm7VSeDCBQ2gotvqkYJa/L7z5X4j7/sFcfr5I5Gu1AV0lyhlf2QyDLqQLSx1fn//78NtJk4XgHsRbWpe2BtCAw2Vv3vdXfGuy/WiwVmR/G2oQNNra1tAhipbBJyVertEra6w97d5vHr9fbigqeBDF+wy8r6AMyH66iFLjb2vfffJ4w19F/9cQ2NfS0ULQgCiiMY+aaleetXuo7X/Ugig2/u0ilcXDJiX5nhvU83F9H1r086HA3sD2G9Ic2BdQINw6iL9obATgEAV1wRUzie1VW7DAXUcUul4IwWViYUrudOBWnKqdNiRYMO+4473vW/yBiPvC8DlorXVkAyDygefm73dyPsC7kW0qSq6vUE+IOu6W7HbYv9/bzkQ3vXqO6Om98KkhGQx2X0yuYC0u6IFjBJMgPbUZB2t265kADQxfniIfWChoM/kmt2na4ctM/a+9t0nj1ffl3euo7GvpaIFIQBRRGOftHaLTI93Edbuya/9l0KE3anhqVlbjb3v4Pm7HOdcm4tOpO/71trwpQA62LXYqubASEEdIGrTA4cDOwFQVegjhYoATI5AdqEDdR95fq45HS+ViZmqwtKFOqfDDgfJxArwz1M2GnlfwG0gsDPPjFc4lQ/2+9gcgbMvok1+f6t210itAtVpVcW7LtfL7lJmUkJC3b1MLiDtlfq/JJqbe/ZmeI93UdB2s66gDeijmJ6gcGE3V7j+GyMIE6B2pEt3mdnFb2g09rVUtCAEIIpo7JN2/jZn9eDLMHWpHDoMrNn+feYjc9v41LYuVLeEcN932jq9Djtc/O71mgYwnRtGJKAOECYJgN160uRuCF04ery85j1cUPeRFwzqeO0ysXiDVVi6UDfVyLflgDPX4a9TzblxvU0MBHQGBeGivNJJAAIOUyYQcEszXUVfa7P/DdiP/klR8a7L9bLbH19jUEJC+0SWGOoDA5yV+oB1pglQC13OkCIc0Ab0cJyJaoM9H+LGEeaMIJbuchK4lRlmdvEbGo19LRUtCAGIIhr7pF1I9J/UurEu+MngGh9ukzIMaqtpqumVeueb0mEDzgawXho3jEhAg8pMkSEAQccaj9esREdFAKavN3etqfvIEIM63gHzaqwrOxqswtKFuqlGPppf8ODb5hZh725wGgjsNSTDoATO5Pdn7+Ew+f2tz6rZwQk0vvaZ7K541+V62e2Pf2pQQkL7RJYb6gMDnJX6vxt0gvuNrafK4612mTIBaiBAzQnqgoffqZGf/XKUOSMI6si1xuAufkOisa+logUhAFFEY5+01H3ElJ8y4HRqMCnDGLV4t+OcTel4X17iDO0ypcMGnA1gKm1wpPiYOECYJAB261KTBID2LXi8zvAaE2hncx95caG5v81B82v6RExWYelC3ZQOe9chZ7BRwFPfBGgqeLYhz3BK4F5aaE6H/R+bhXCnoeYW0arUVZXkpS7Xy25//PPhK0ydOr4k8jO7nWxdYa/U9zXoBEdD2VS5DZGANqCblD4++m7N7lMgR8UE7OGTHq/bjrexoLGvpaIFIQBRRGOftMuJ/nN7rhkdL+DUf5qUYdB0XVM6Xpqa+WGKGR02APSx2Q/SEKG6gFr4na4nAmCyH0JFAN7fpA6viRQdBtXIz0YsMreAtMvETDby0YW6KR02TWc2uQiju08HC8zIMADgx7b+IZM67Ofm1PRwXPeiOR325hx38rFK8mL/ebiyFbv9cWeDEhJKXsLNJ+Bgr9SHah0aCmgCejg2wRxKiIGAycLH4zNrJFw0JbouWJfl3MGhdryNBY19LRUtCAGIIhr7pKX6T5oGWhfY9Z8mt/Ht6bcmdbzU13zOZnOBKvaQIZNOLNTCr74IgMkmXRUB+Mgg2QIQ1GF7vJEFuunw0sIamZjJRr7MI84E0qW7zOiw9+U7fc1N2vFS/3FTMgzA2T80dpm5789uIfyLBHNV9G0HT7rmtCr80P7zrwvDu1725OSuBiUkWw44yYvJPjC7+9m/PzBnBGEP1fJ4zdkfUwOBxCRz9z27hKuHQSMIexq4x7sIqQZ38RsSjX0tFS0IAYgiGvukpfpPU37KgFP/aVKGYU+/7TDQnI6X+pp/us1coIq9AcykGwaVcIUbTMXB/v2ZfBCqCIBJsgUA1w6rkZ9FGuimwkib/MxkojMNGTPVyHeg4LTjfU3a8VL/8fwiMzIMwOkfbzKP44VPayRcJgP50vIKXXP6YYXcynG9wpSt2M/912PMSUi2E/mZyT4wu/vZ0wbzHGiauKn7XgXpP3nbYG+SXcJ1+3h3SFykSNnvJHCm7HgbGo19LRUtxBwBKC8vx/PPP48rrrgCF1xwAW666SasWBFaNefQoUPo06cPLr74Ynz729/GPffcg+zsyB1IGvukpfrPuqa82mHXf5qUYdjTb00SAOpr/tkOc3Z4j9jsB026YVAJl6lgI8BJAEy69FD3GI93EeZtNZteaZefmVxAjrbJz0wuIPeTACJTjXx5J52+5v82aMdL/cdNyTAAoKNNwmXSgWrIghqrX5M67N1fF7nm9KPvuuVW9p+fDPN62c/9lnFrDZ25W35msg/M7n5mMs/hD7aeKo/XXCAfza95d0OOkfcFnBIuk0YQ1EDAlB1vQ6Oxr6WihZgjAPfffz/i4uLQr18/JCYmomvXroiLi8P69XxzZUlJCTp06IA2bdpgzJgxGD9+PNq2bYsrr7wSBQWRVT0a+6Sl+k9TfsqAU/9pUoZhX6ibJAC0Mr3YoB3eYzYPb5ONmFTCVV8EwKQl6nQFATCdXnm9jQBMNNjI94pNfmYy0ZkGEJlq5DtS6LQ1NFmFpf7jJlOo7T0cJuVnLy5MD76vSR121tFi15z+p0JuZf95uJa99nPv+ao5K2FKXrYZrCDb3c9M5jncN3mD45zDSSeuDfb3/SDZXG+SXcJ1j0EjCGogkH7YnIy3IdHY11LRQkwRgJSUFFiWhXHjxgVfKysrQ3x8PLp27cr+7pgxY2BZFlJTayozmZmZaN68OV544YWIzqexT1ravGbKTxlwOjWYlGHYbSRNBuK8Q0K1TNrh2T28VZXBSEElXKYsUQGg84gaAmByK1xFAEynV9oJwKS15hr57H0iJmUYNIDIVCPf8ZJyx/s+a7AKu3SXkwCY7D9pP7DGxckk+bRLuG41uIjOPlbimtMquVVdyLrdpviOCeYkJJS8pOWZW0D+6a2ahbrJPIe/JNaYKvxowCJj7ws4v6PZqeZ6k+wSrj8aNIKgOzim7HgbGo19LRUtxBQB6N+/P5o3b46iIqdWfdSoUbAsC7m5ei1x586d0blzZ9frt99+O+Lj4yM6n8Y+aWnzmslGvp6v1jg1mJRh2BeQJr28Z250+pqbtMOzN4CZdMOgCbL1RQBM+vRTouXxmmt6DcAuATLZv2DvE7l5jLkKMg0gStlvRoZxqtTpa24yj2MF8R83JcMAnDauMwzmcdglXCYX0XQHx+NVp5/bfx6ufbHdpviuieYkJFR+ZirQDXC6nw2eb84Iwt5T1X6gOSMIwPkdzTWUxwEAQ20SLlVGRKSgBgJfGbLjbWg09rVUtBBTBKBnz564+uqrXa+vWrUKlmVh4cKFyt/z+Xxo0aIFnnzySdfPBg8eDMuyUFwcPnNu7JOWNq+Z8lMGnFZtJmUY79kW6lcNNkcAPiS2hkkG7fCenV1jP2jSDYMmyNYXATAZiqYiACZ3WwAnATC5e2GXn5kkADSAaMsBMzIMamtoMo9jTabTf7zKoAzDbgNq0iLW7iDWe6I5GcbhU2dcc/o/ivRz+8/DtS+22xT//k1zFWRKXkxWkO3uZ8M+M/eM/IctVOsng83lcQDO78ikNNHuIHZ/orlEbmogcKDAnIy3IdHY11LRQkwRgE6dOqFHjx6u1zMyMmBZFqZMmaL8vePHj8OyLAwfPtz1s0mTJsGyLOzZw8tU8vPzkZ6e7hgLFixo1JM247CzemCykc9OAEzKMD5IrgkgMkkAqK3hBoN2eP/7uKYBzKQOm1r4mazC3mgjACab4WYoCIDJ3RbASQBMnrtdfmaSABSecQYQ7TCUx0FtDU3KMJKI/MwkfmQjACZlGHYHMZM67PyiMtecVjW91uV6jV9RIz/701vmrIQpeTFZQX5oes1CPeFzc0YQj75bY6pwrcFAN8D5HZmUJtrlZyYTuekOTt5JczLehoQQgMgQUwSgXbt26NWrl+v17OxsWJaFCRMmKH8vNzcXlmVhzJgxrp9Nnz4dlmVh+3ZeHzts2DBYlqUcjXXSUpcQk02kdp2mySre5ztrvO9N+ilTRx2TmQgJn9dUf0xuhdPqT6WhVGQA6D2xpoHPpEvPJ1uc9pEer1nnEQC4Y0KN/eD8beaqeHNSa0iiSR1veaVzoZ5jqBm/yufHTwbXZCKMWmIuVIs2H5qE3UBg6S5zu0PvbqjZPTS5CCspr0S8Tbakq3jbpSvhwi59fMRgoBslnybtXJ/+sMb60uQusN1Rx2QzPgBc92JN8cBkqq7dvc6kGxft8zlVaq6I15AQAhAZYooAyA6AeSQmfYWHpqdgTqpZL/btuafwz/c2Y8C8NKMOIWUVVRi6YBcefTcVG78y51ldXlmFYZ+l48G3k/Hqir3GEoaB6m32Zz7ahqc/3GZscRfAG6uz8ND0FKMLXQBIzTmBR9/djEHz04w2eJaUV2LQ/DQ8+HYyHnw7GaOXZhp18QCqvbEffXczBs/fZTQbobisAgM/TcNj7202JtMJ4JMteXhoeorR3TKg2q7zoekpeHb2dhwy2OPj9/sxbtke/H16CpYYdMwCqu2J+85IxbDP0o3uap0qPQvvJzvxr5mbjdslfphyMDinn/5wmzIZOb+oDN5PdkbU83LydPW5Pz5zi9HiBFC9q/rg28lGe32A6iTqJz/Ygv99vMOovHRffjH+PWsrHn4nBat2m909XJOZj0dmpGLEogyjBZVjxeX438c78OQHW4zm7QDVu6oPvp1sPFG9ISEEIDLEFAGQHgCBQCAQCASCpgNZS0WGmCIA/fr1U7oAjRw5slYXoBtvvFHpAnTbbbehXbt2EZ2PTFqBQCAQCASCyCFrqcgQUwQgOTnZlQNQXl6O9u3bo0uXLsHXDh48iMxMZ/jU6NGjYVkWNm+usWHcs2cPmjdvDq/XG9H5yKQVCAQCgUAgiByylooMMUUAAKBPnz6Ii4tD//79kZiYiG7duiEuLg5JSTW+zt27d4dlOS9NcXEx4uPj0aZNG4wdOxYTJkxA27Zt8f3vfx/HjkXW7COTViAQCAQCgSByyFoqMsQcASgrK0O/fv1w+eWXo0WLFujcuTOWLXNagakIAADk5eXhvvvuw0UXXYQLL7wQvXv3xr59kTfdyaQVCAQCgUAgiByylooMMUcAziXIpBUIBAKBQCCIHLKWigxCAKIImbQCgUAgEAgEkUPWUpFBCEAUsXXrVliWhQULFrgyAmTIkCFDhgwZMmTwI5CptHWruZC0WIAQgCgiMGllyJAhQ4YMGTJkRD4WLFgQ7WVdo4IQgCji1KlTWLBgAbZu3dpgDFl2G+QayXWSa3SuDLlOco3kOsk1quvYunUrFixYgFOnzCZ0N3UIAYgRpKeLRq42yDUKDXKdaodco9Ag16l2yDUKDXKdaodcI4EdQgBiBPKHXzvkGoUGuU61Q65RaJDrVDvkGoUGuU61Q66RwA4hADEC+cOvHXKNQoNcp9oh1yg0yHWqHXKNQoNcp9oh10hghxCAGIH84dcOuUahQa5T7ZBrFBrkOtUOuUahQa5T7ZBrJLBDCECMID8/H8OGDUN+fn60T+WchVyj0CDXqXbINQoNcp1qh1yj0CDXqXbINRLYIQRAIBAIBAKBQCCIIQgBEAgEAoFAIBAIYghCAAQCgUAgEAgEghiCEACBQCAQCAQCgSCGIARAIBAIBAKBQCCIIQgBaOIoLy/H888/jyuuuAIXXHABbrrpJqxYsSLap1XvSE1NxVNPPYVrrrkGrVq1Qtu2bdGnTx/s3bvXdezu3btxxx13oHXr1rjkkkvw4IMP4tixY67jfD4fxowZgx/96Edo0aIFfvrTn+LDDz9siI/TYBgxYgQsy0KnTp1cP9uwYQN+9atfoWXLlrjsssvw9NNPo6SkxHVcU51zW7duxd13341LLrkELVu2RKdOnfD66687jonla5SVlYW//OUv+MEPfoCWLVviqquuwksvvYTS0lLHcbFyjUpKSjB06FDccccduOSSS2BZFmbMmKE8tj7uQaG+ZzQRyjXy+XyYMWMG7r77blx55ZVo1aoVOnXqhISEBJSVlSnf9+2338ZPfvITtGjRAu3bt8fEiROVxx06dAh9+vTBxRdfjG9/+9u45557kJ2dbfpj1hnhzKUAKioqcPXVV8OyLIwbN87186Y2lwThQwhAE8f999+PuLg49OvXD4mJiejatSvi4uKwfv36aJ9aveLee+/F5ZdfjqeffhrTpk1DQkICLrvsMrRu3Rq7du0KHpeXl4f/+7//Q3x8PF5//XWMHDkSl1xyCX72s5/h7NmzjvccMGAALMvCP//5T0ydOhV33XUXLMvCRx991NAfr16Ql5eHVq1aoXXr1i4CsH37dlxwwQX4+c9/jsmTJ2PQoEFo0aIF7rzzTtf7NMU5t3z5cpx//vno0qULxo8fj6lTp8Lr9aJ///7BY2L5GuXm5uI73/kOPB4PXn75ZSQmJuLhhx+GZVm45557gsfF0jXKycmBZVn44Q9/iFtuuUW7aKuPe1A47xlNhHKNSkpKYFkWfvnLX2LEiBGYOnUqHnnkETRr1gy33HIL/H6/4/gpU6bAsizce++9mDp1Kh566CFYloXRo0e73rdDhw5o06YNxoGXRnYAAAymSURBVIwZg/Hjx6Nt27a48sorUVBQUN8fPSyEOpfsePXVV9G6dWstAWhqc0kQPoQANGGkpKS4/vjLysoQHx+Prl27RvHM6h8bNmxw3ZyysrLQokULPPDAA8HXnnzySbRs2RIHDx4MvrZy5UpYloXExMTga4cOHcJ5552Hp556Kvia3+/HzTffjCuvvBJVVVX1+GkaBn/5y1/Qo0cPdO/e3UUAevXqhSuuuAJFRUXB16ZNmwbLsrB8+fLga01xzhUVFeGyyy7DH//4R/h8Pu1xsXyNRo4cqQwY+vvf/w7LsnDy5EkAsXWNysvLceTIEQDA5s2btYu2+rgHhfqe0UYo1+js2bPYsGGD63dfeuklWJaFlStXBl87c+YMvvvd7+Kuu+5yHPvAAw+gdevWwXkIAGPGjIFlWUhNTQ2+lpmZiebNm+OFF14w8fGMIdS5FEB+fj4uvvhiDB8+XEkAmuJcEoQPIQBNGP3790fz5s0dD1sAGDVqFCzLQm5ubpTOLHq44YYbcMMNNwT/3aZNG/Tp08d1XMeOHXHrrbcG/z1p0iRYloWMjAzHcR9++CEsy2o0VUkdkpKS0Lx5c6SlpbkIQFFREeLi4hzVbqD6wXzhhRfi0UcfDb7WFOfc5MmTYVkWdu/eDQA4ffq0iwjE+jXyer2wLAvHjx93vd6sWTOcPn06pq8Rt2irj3tQqO95LiGUha0daWlpsCzLIe9ZvHgxLMvC4sWLHcdu3LgRlmXh/fffD77WuXNndO7c2fW+t99+O+Lj4yP7EA2AUK7TI488gptuugn79+9XEoCmPpcEoUEIQBNGz549cfXVV7teX7VqFSzLwsKFC6NwVtGD3+/HD37wA9x+++0AqqsglmVhzJgxrmMffPBBXHrppcF/P/bYY2jdurVru/mrr75yPYQaG6qqqnDdddfh8ccfBwAXAfjyyy9hWRbmzJnj+t1f//rXDkLVFOfcvffei4suuggrV65Ex44dYVkWWrdujSeeeCKoQY71a7R06dKg3Gf79u3Izc3F7NmzcdFFF+HZZ58FENvXSLdoq497UDjveS4hXAKwYsUKWJbl0K0Hepho0u3Zs2fRrFkz/Pe//wVQrX9v0aIFnnzySdf7Dh48GJZlobi4OPIPU4+o7TqlpKSgWbNm2LhxY1A6RAlAU59LgtAgBKAJo1OnTujRo4fr9YyMDFiWhSlTpkThrKKH999/H5ZlYfr06QBqbqQzZ850Hdu/f39YloXy8nIAwF133YV27dq5jistLYVlWRgwYED9nnw94s0338TFF18cbOqiBGDu3LmwLAvr1q1z/W6fPn1w+eWXB//dFOfcddddh1atWqFVq1Z4+umnMW/ePDz99NOwLAv3338/ALlGAJCQkICWLVvCsqzgGDRoUPDnsXyNdIu2+rgHhfOe5xLCJQA9e/bERRddhFOnTgVfe+qpp9C8eXPl8d/73veCf6/Hjx+HZVkYPny467hAdXzPnj3hf4gGAHed/H4/brrpJvz1r38FAC0BaOpzSRAahAA0YbRr1w69evVyvZ6dnQ3LsjBhwoQonFV0kJmZiYsuughdu3YN6hvXrVunrUgOGTIElmUFHy49evRQViR9Ph8sy8IzzzxTvx+gnlBQUIBLL70Ur7zySvA1SgBmzpwJy7KQkpLi+v2HHnoIF198cfDfTXHOtWvXDpZl4YknnnC8/vjjj8OyLGRlZcX8NQKqCfYdd9yBqVOnYt68eejbty++9a1v4Y033gAQ2/NIt2irj3tQOO95LiEcAhDoOXnrrbccr/ft2xctW7ZU/k7btm3x+9//HkB107qusj19+nRYloXt27eH/yEaANx1euedd9CyZcugRE5HAJr6XBKEBiEATRhNrYoWKY4cOYJ27dqhbdu2OHz4cPB12QEAnnjiCbRv397RMC07AE506tQJlmUhKSnJ8XpSUhIsy8J7770X89foo48+QsuWLZGXl+d4/eGHH0arVq1QUFAQ09dIdgBqR6gEYPbs2fjWt77l6BkJIJZ3AAJmBUOHDg2+JjsAAg5CAJowmpqONhIUFhbi+uuvx6WXXupqeApXf9uqVasm1QOQlZWFZs2aYeLEicjJyQmOLl26oGPHjsjJycGJEydiWrsNALfddptyQZCZmQnLsvDaa6/F/DW6+eab0a1bN9frn376KSyr2qkllq+RqR6AUO5BjVW3HQoBWLFiBc4//3z07t0blZWVrp/Hcg/AkCFDcMkllyAjIyN4L1+/fj0sy8LAgQORk5MTLPQ09bkkCA1CAJow+vXrp3TSCGyfNjYnjXBRVlaGm2++Ga1atcLGjRuVx3zve9/TOhzYK5BvvvkmLMvtmjBr1ixtVfNcx9q1ax16bdV45plnUFhYyLq39O3bN/haU5xzAb/s1atXO15fvXo1LMvCrFmzYv4adezYEV26dHG9PmfOHFiWhaVLl8b0NeIWt/VxDwr1Pc8l1EYAkpOT0bp1a3Tr1g1nzpxRHrNo0SJYltsFaMOGDa5K9o033qh0AbrtttuU1fFzBbrr9I9//KPW+3lA1tTU55IgNAgBaMJITk52bf+Vl5ejffv2yod1U0JVVRXuuecexMXFuR4GdjzxxBMOzSRQU2WcPHly8LW8vDytb/IPfvCDRpkDcPz4ccyfP981OnXqhB/+8IeYP38+0tLSAAB33nknrrjiCkdV7O233w4u7gJoinNu27ZtsCwLf/vb3xyv//Wvf0VcXFxQVhbL16h37944//zzXUnbf/jDH9CsWbOYv0bc4rY+7kGhvue5BO4a7d69G9/97nfRqVMnh5c/xZkzZ3DppZeid+/ejtcffPBBtGrVCidOnAi+Nnr0aFiWhc2bNwdf27NnD5o3bw6v11v3D1RP0F2nrVu3uu7liYmJsCwLDz/8MObPn4/CwkIATX8uCUKDEIAmjj59+gSrbomJiejWrRvi4uJceuamhmeeeQaWZeHuu+/G+++/7xoB5Obm4rvf/S7i4+MxceJEjBo1Cpdccgl++tOfurSNAc3jv/71L0ybNi2YnDhr1qyG/nj1ClUQ2NatW9GiRQtHgusFF1wQtFS1oynOub59+8KyLPz5z3/GpEmT0KdPH1iW5QgMiuVrFMiRaNOmDYYPH45JkyahV69esCwLjz32WPC4WLtGb7zxBhISEvDkk0/Csiz86U9/QkJCAhISEoKLsfq4B4XzntFGbdeouLgYbdu2RbNmzTB69GjXvZzu7gY0/Pfddx+mTZsWDKMbOXKk47ji4mLEx8ejTZs2GDt2LCZMmIC2bdvi+9//ftAR7VxCKHOJQtcDADTNuSQID0IAmjjKysrQr18/XH755WjRogU6d+6MZcuWRfu06h3du3dnt0LtSE9Px+23345WrVrhO9/5Dh544AEcPXrU9Z4+nw+jRo2Cx+PB+eefj06dOuGDDz5oqI/UYFARAABYv349unXrhgsuuADf+9738NRTTyl1sk1xzlVUVODFF1+Ex+PBeeedh/bt2yudaGL5GqWkpKBXr164/PLLcd5556Fjx44YOXKkS6sdS9fI4/Fo70E5OTnB4+rjHhTqe0YbtV2jwCJWN/7xj3+43nPq1Km46qqrcP755yM+Ph4TJkxw6d2B6kr4fffdh4suuggXXnghevfujX379jXApw4foc4lOzgC0BTnkiA8CAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGIIQAIFAIBAIBAKBIIYgBEAgEAgEAoFAIIghCAEQCAQCgUAgEAhiCEIABAKBQCAQCASCGML/B8vRcEyyJcRTAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff81c79e710>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#print the profile of the normalized image: the center is difficult to measure due to the small size of the hole.\n",
    "fig,ax = subplots(2)\n",
    "ax[0].plot(normalized[:,545])\n",
    "ax[1].plot(normalized[536,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19.63857792789662\n"
     ]
    },
    {
     "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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Convolution kernel')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Definition of the convolution kernel\n",
    "ksize = 5\n",
    "y,x = numpy.ogrid[-(ksize-1)//2:ksize//2+1,-(ksize-1)//2:ksize//2+1]\n",
    "d = numpy.sqrt(y*y+x*x)\n",
    "\n",
    "#Fade out curve definition\n",
    "fadeout = lambda x: 1/(1+numpy.exp(5*(x-2.5)))\n",
    "\n",
    "kernel = fadeout(d)\n",
    "mini=kernel.sum()\n",
    "print(mini)\n",
    "\n",
    "fig,ax = subplots(1,3)\n",
    "ax[0].imshow(d)\n",
    "ax[0].set_title(\"Distance array\")\n",
    "\n",
    "ax[1].plot(numpy.linspace(0,5,100),fadeout(numpy.linspace(0,5,100)))\n",
    "ax[1].set_title(\"fade-out curve\")\n",
    "\n",
    "ax[2].imshow(kernel)\n",
    "ax[2].set_title(\"Convolution kernel\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1679, 1475)\n"
     ]
    },
    {
     "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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(array([1065]), array([338]))"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_smooth = convolve(normalized, kernel, mode=\"constant\", cval=0)/mini\n",
    "print(my_smooth.shape)\n",
    "fig,ax = subplots(1,2)\n",
    "ax[0].imshow(normalized.clip(0,1))\n",
    "ax[0].set_ylim(1050,1100)\n",
    "ax[0].set_xlim(300,350)\n",
    "ax[1].imshow(my_smooth.clip(0,1))\n",
    "ax[1].set_ylim(1050,1100)\n",
    "ax[1].set_xlim(300,350)\n",
    "numpy.where(my_smooth == my_smooth.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "335009\n",
      "782371\n"
     ]
    },
    {
     "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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7ff81c647e80>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#mask out all pixels too close to any masked position\n",
    "\n",
    "all_masks = numpy.logical_or(numpy.logical_or(mask0,mask1),mask2)\n",
    "print(all_masks.sum())\n",
    "big_mask = binary_dilation(all_masks, iterations=ksize//2+1+1)\n",
    "print(big_mask.sum())\n",
    "smooth2 = my_smooth.copy()\n",
    "smooth2[big_mask] = 0\n",
    "fig,ax = subplots()\n",
    "ax.imshow(smooth2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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,iVBORw0KGgoAAAANSUhEUgAAAwAAAAJACAYAAAA6rgFWAAAgAElEQVR4nOx9a7SVdbn9KhlqY5wPZ4zzxTo13uMl07S0vIVmpllmpnUsO3Y6p1PZxWPlMQOXF7wiKOLdShBNBLTQSMQtICCIioKCooAogoCIiIJcFLnz/D/0d6/nnWvOtX+sd7kW7P3MMfjieP3td6397rWe+TxzzqdkgUAgEAgEAoFAoMug1OobCAQCgUAgEAgEAs1DEIBAIBAIBAKBQKALIQhAIBAIBAKBQCDQhRAEIBAIBAKBQCAQ6EIIAhAIBAKBQCAQCHQhBAEIBAKBQCAQCAS6EIIABAKBQCAQCAQCXQhBAAKBQCAQCAQCgS6EIACBQCAQCAQCgUAXQhCAQCAQCAQCgUCgCyEIQCAQCAQCgUAg0IUQBCAQCAQCgUAgEOhCCAIQCAQCgUAgEAh0IQQBCAQCgUAgEAgEuhCCAAQCgUAgEAgEAl0IQQACgUAgEAgEAoEuhCAAgUAgEAgEAoFAF0IQgEAgEAgEAoFAoAshCEAgEAgEAoFAINCFEAQgEAgEAoFAIBDoQggCEAgEAoFAIBAIdCEEAQgEAoFAIBAIBLoQggAEAoFAIBAIBAJdCEEAAoFAIBAIBAKBLoQgAIFAIBAIBAKBQBdCEIBAIBAIBAKBQKALIQhAIBAIBAKBQCDQhRAEIBAIBAKBQCAQ6EIIAhAIBAKBQCAQCHQhBAEIBAKBQCAQCAS6EIIABAKBQCAQCAQCXQhBAAKBQCAQCAQCgS6EIACBQCAQCAQCgUAXQhCAQCAQCAQCgUCgCyEIQCAQCAQCgUAg0IUQBCAQCAQCgUAgEOhCCAIQCAQCgUAgEAh0IQQBCAQCgUAgEAgEuhCCAAQCgUAgEAgEAl0IQQACgUAgEAgEAoEuhCAAgUAgEAgEAoFAF0IQgEAgEAgEAoFAoAshCEAgEAgEAoFAINCFEAQgEAgEAoFAIBDoQggCEAgEAoFAIBAIdCEEAQgEAoFAIBAIBLoQggAEAoFAIBAIBAJdCEEAAoFAIBAIBAKBLoQgAIFAIBAIBAKBQBdCEIBAIBAIBAKBQKALIQhAIBAIBAKBQCDQhRAEIBAIBAKBQCAQ6EIIAhAIBAKBQCAQCHQhBAEIBAKBQCAQCAS6EIIABAKBQCAQCAQCXQhBAAKBQCAQCAQCgS6EIACBQCAQCAQCgUAXQhCAQCAQCAQCgUCgCyEIQCAQCAQCgUAg0IUQBCAQCAQCgUAgEOhCCAIQCAQCgUAgEAh0IQQBCAQCgUAgEAgEuhCCAAQCgUAgEAgEAl0IQQACgUAgEAgEAoEuhCAAgUAgEAgEAoFAF0IQgEAgEAgEAoFAoAshCEAgEAgEAoFAINCFEASghVi1apWNHDnSZsyYYbNnz45/8S/+xb/4F//iX/yLf9vxb8aMGTZy5EhbtWpVq8u6nQpBAFqIkSNHWqlUin/xL/7Fv/gX/+Jf/It/Bf6NHDmy1WXdToUgAC3EjBkz2h/aVjPo+Bf/4l/8i3/xL/7Fv53t3wfN1BkzZrS6rNupEASghZg9e7aVSiWbPXt2q28lEAgEAoFAYKdD1FL1IQhACxEPbSAQCAQCgUD9iFqqPgQBaCHioQ0EAoFAIBCoH1FL1YcgAC1EPLSBQCAQCAQC9SNqqfoQBKCFiIc2EAgEAoFAoH5ELVUfggC0EPHQBgKBQCAQCNSPqKXqQxCAFiIe2u3HbZMX2A3jX7Zt27Z96D9r27Zt9vO7nrFv3/y4rX5/04f+8wKBQCAQCGwfopaqD0EAWoh4aLcPU+a/bVm5zbJymz30whtN/XmXPhC/o0AgEAgEdjRELVUfggC0EPHQbh/+MPGV9oL8qtFz5XWLVrxng6cstNXrinXtx815s/3n/ezOp2teu2XrNtu69cOfSgQCgUAgEKggaqn6EASghYiHdvtwzdi57QX5zRPmyes+02u0ZeU2O2Nw7aK9I0x8aXn7z/vvO6bJ66a88rZ9ptfowj8vEAgEAoHA9iFqqfoQBKCFiIe2glsfnW9HXvWIPbVghbzm0gdmtxfkgx5bIK/74Jqs3Fbonh6b91b7OT+87amkn7dpy9ZCPzMQCAQCgUA6opaqD0EAWoh4aCtIKdrPu+/59mvunrq40Fkp8B6A0wY8mfTzNmzeUuhnpuK9DZtt6ar3m/KzAoFAIBDYURG1VH0IAtBCxENbQUrR/pt7nm2/ZsSMJYXOSoEnAP/+xyeSft77Gz98ArBx81Y78qpHbM/z22zW66s/9J8XCAQCgcCOiqil6kOnIQAbNmyw8847zz7+8Y/b7rvvbocffriNGzeuw/9vxIgR9oMf/MD23HNP+9jHPmb77ruvnXvuubZq1aqqa7Mss1KpVPXvV7/6VV33HA9tBSlF+6+GTG+/5m/TP3wCMPnligTolFseT/p5723YXOhnpuDJ+Svaf95/3T71Q/95gUAgEAjsqIhaqj50GgJw+umnW7du3axHjx42cOBA6969u3Xr1s0ef1wXbmZm//Iv/2Kf+9zn7OKLL7ZBgwbZ2Wefbbvuuqvtt99+9v77eYlFlmV28MEH29ChQ3P/pk3TBtFaiIe2gpSi/X+HVQjA8GdeK3RWCibOrZiAT7zxsaSft2b9h78v4OHZy5LTiQKBQCAQ6MyIWqo+dAoCMG3aNCuVSta/f//2/7Z+/Xrbe++9rXv37jX/30mTJlX9t7vuustKpZINGjQo99+zLLOTTjqpIfdsFg+tR0rRftawGe3X3DPtw/cA+EL769c/mvTzVq3bWOhnpuDvzy5p/3ln/+VZed1bazfYPdMW29vvbvjQ72l78N6GzfbQC2/UfK+2bdtmv793ph151SP2yvK1hX/m1AUr7MU31hQ+JxAIBAI7FqKWqg+dggD07NnTdtllF1uzJv8F37dvXyuVSvbaa7pbzLB27VorlUp27rnn5v77BwRg48aN9t577xW+7539oZ2+aKVdPWaurXyveNGbUrT/+u4KARjy1KJCZ6Vg9AtvtJ9z3LWTkn5eI96LjjDkyYXtP++Cv78grzvlD09YVm6zk2vIl1qBs/7/7/G7NXwVi1a81/4azxo2o9DPe2HJ6vazXlu5rtBZgUAgENixsLPXUq1CpyAAxx9/vO2///5V/33ChAlWKpVs1KhR23XevHnzrFQqWd++fXP/Pcsy+9jHPma77LKLlUoly7LMbrzxxrrve2d/aPe96B95+9/705TCZ6UU7b91JuDBUxbSa7Zt29YwAvDAzKXt5xx/XdoE4K21utu+actWW9sAidCtj85v/3l9Hnox6b52JKTc10OOfP24xg6GTVu22pPzV9Q0X18/7uX2s/rWeL8CgUAgsPNhZ6+lWoVOQQAOOOAAO+6446r++5w5c6xUKtmAAQO267wzzjjDdtllF5s3L79s6uSTT7Z+/frZyJEj7Y477rCjjz7aSqWSnXfeeR2euXz5cps9e3bu38iRI3fYh3bbtm22bVvtzbaNLDBTzjr7LxUCcPvjr9JrNm/Z2rD7GjGjIrU54YbJSfe+fM16es2mLVvtq/0n2X69xtiiFcWmR3+clLYReWcmAPc+81r7Nb8b/py87oPdEP/zZ00S/O/xt/doyVSg62Dem2vtyKsesfNHPN/qWwkEAgURBKA+dAoCsNdee9mJJ55Y9d8XLFhgpVLJbrjhhuSz7r777uSiftu2bXbCCSdYt27dbMkSnUpjZnbppZfSBKEd8aFdt3GzfeP6yfatmx6rmWvfbAJwzl+fa7/mtsl8Edj6TVsadl/DXRH6zUQT8BureTb/E69UIkV/OeSZQvflJwC1OtqdhgD8VROAlLO8ZyIIQMDM7EeDprY/Eyt2MI9MIBDYPgQBqA+dggA0agLw2GOP2e67724nnHCCbd6cFuc4duxYK5VKNnTo0JrX7UwTAF9gDm2C1j71rN85AvCnSfPpNe9u2Nyw+7p76uL2c066OY0ALHmHa8wfmftm+zW1utUpGNAFJECefJ1TkAD8bXoQgEAe37zxsfZnYuZr1ZHPH2DUzKV20s2P2ROvvN3EuwsEAtuDIAD1oVMQgEZ4AGbOnGn//M//bIceeqi9++67yT/7A5Jx0003bdc9m+24D23f0S+2fzn+cdIr8rpmE4Bzh89sv+YPE/l9rV63qWH35c22tYy0/ucpk+m4ORUCUDS680+TKgSg94Nzku5ry9bacq5mwt/XVnFff326Qr7+r0bS0fZOE4oSgG3bttltkxfY8Ke3L1ggsGPhjMFPtz8To194Q17XyM+49Zu22NQFK2zTlq2FzwoEAhXsqLXUjo5OQQB69OhBU4D69OmTlAI0f/5822OPPWzfffe1t956a7t+9oMPPmilUsnuueee7b7vHfWhvWr03B2SAPz+3goBuHH8PHrNinc3NOy+7nj81fZzvvOHtE3AC9/m+v4xsyqRoj+/S0uAtm7dZvPeXCsLYzOzP0yseAAuH5VGAJqxn8DMbMorb9vtj7+aLB1bt5FP2vz0pVbUadI04ekKAfhNQQLQ9nzFnPzCktjCvLPCJ4rd/+zr8rpGfsZ9kH5V62+20aj1ORIIdBbsqLXUjo5OQQCmTp1atQdgw4YNts8++9gRRxzR/t8WL15sc+fmTZPLli2zvfbayz7xiU/YwoUL5c9YuXKlbdmSL2o2bdpkRx11lO266662bNmy7b7vHfWh9QRAddrNPjwCoMzHngBc9/BL9Jo316xPOisFt01e0H7OqTWSjvzPW/AWnx75VJtfDZkuz7pk5CzLym12rXh9Zma3PDKv/axLH9DPjr+vZuwn8PKrAY9yiRbel0pNGvrUoqSufcoz+JdpFTJRlABc8PcX2s8a8uTCQmcFWoffuESxETM+/K3ijT4rBUveWWdH9JlgP/nztEKfgx9g3ptra6acBQKtwo5aS+3o6BQEwMzstNNOs27dulnPnj1t4MCBduSRR1q3bt1s8uRKessxxxxjpVL+JR900EHtpl/c8Dtu3Lj26+68807be++9rVwu24ABA6xv37524IEH0rjQVOyoD+3VY5pLADC6U3WtvATomrE8/eb1Ve8nnZUCn7Zz2q1Pyuv8z1NLq3ykaK1c+5T39KYJFQJwychZSWc1Yz/By2+ubf95qXsTXl/FTdNeflWUAAybWiETv7672E6BD1KHsnKbDXqMG9EDOz48Abi3CVvFt25tXDxxKn58x7QOP5dSMWPxO5aV2+wLV4yz9Zv0dC8QaAV21FpqR0enIQDr16+3Hj162B577GG77babHXbYYTZ27NjcNYwAqGSeUqlkxxxzTPt106dPt5NPPtn+9V//1XbddVf7p3/6J/vyl79s9957b9333IqHdtGK9+ycvz5nE19aLq/xBOCWR7jUxqxxX45b4Mtxs9DIehNw39Hc/Lp4xbqks1Jwsyu0fzAgjQC8tIx/0XpTa60udMp7esP4Sq59r/vTCEAztgF/UCRk5TY7JVEypTwTg6cs3O73S3U5hzzVOALQ96E0f4yZRaG0A8MTgFp+jkZ9xr3dQGliKr5+/aMdfi6Zmc16fbX9/dklNT8rv33z4+1nPVfDNB0ItAJBAOpDpyEAOyNa8dAeedUjHX4JNZsAbILs/o2b+RfR/7k9AFe2cR3t/LfeTTorBTeO334C8OIba+g1d7mOdlFT63VusdWFNTYB+7OWr+X7CRqJyS+/1f7z/nPQU0n3tXgFJwB/fqLiv6hVtPuzlLnSv/dFCcC1D7/UftYN41+W14187nXb64KHapq0A62DJwD3TFtMr9m4uXE7RZbCZFJhy9ZtNmbWGzZ3Gf8c2R4c23+SmwBwaeKGzZXYZLVbxczs6H4TOzwrEGgVggDUhyAALUQrHtqUL6F+jgDcPIETgEZu3PVfQlm5TXZO/Sbgy0bx98zLUGqdlQLfaU8lALNe58bQgZMryT2pufbq3n0RWv6bXmTkz3pTLChrJLxB9hc1jM7+vpRp+vbHt58AvLeBG4rvTCQTKfD+i35jdr4lbIF/wH+WDJvKo44bmSi25J11SWf5SWGt7dYp8EX7fOFNemttZTLxxSvG0WvMzD5/2cNBAAI7LIIA1IcgAC3EjkoArhnbMQFATWsRkxku71JffD65Q2nf5yxdk3TWmvWb7IbxL9uU+Trf23faT0skACoZxkd3pqbaqILW/35+f+/MpLPUgrJGwqftpOr2lWl60GMVA/ZZiQTgHeFz8GlOtc5KgSdyqRGsgR0PngAoM/cbq9O69il4bWUaATjmmokd/m2kwk97X36TS4C8NOnAS8fSa8zyz7M6KxBoFYIA1IcgAC3EzkAAVNzmZpDtFNHar9uYX96lCt+zhlUIgJK+zHp9ddJZve6f1SF58Z3279+algKk9LE+ujO1oF0roju9REstyUJfhTLbNhKpaTv+vlQ30RfaqaZpNeVIJRMp8GTi4kQDtsLmLVut530z7ZKRsxqS0tJsLF6xzoY8uVBGue7I8ARg8JSF9Br0ExXBohXvJZ31VSfbUV37VBx25fj2s+Ys5ZKi5S41bb9eY+RZ/t6VzDEQaBWCANSHIAAtxI5KAHwMqErbQX1sEa09bu9Vhe+ZQ6e3X6OkLy8sWZ101p7nb1+nPTUGdPqid+g1XjryyyFp8pjV7/N794vaVKGNUxVltm0kfHZ/atE+T3QT/cTkf4fp2NSU15gjEwUJgCcTRQmAf7/Gz3mz0H21Aqf84QnLyrX9Htu2bbPrHn7JLhs1u+YyuvFz3rQzBj/dtOLSE4A7hPZ94dtpRXsKFoA3SSFFt5+KL14xrv2s55fwxoT3Juxz4UPyLH/vSuYYCLQKQQDqQxCAFmJHJQCXj5rTfo0y22KBWURrv/r9vNZWFb6/HPJM+zU97+PSl5mvrUo668BLxrZfs1R0x32n/bt/TEu1eWbhSnqNj+48Y7DeBOzPUtn9fVwSjSqOkVQps20j4dN2au068Pel0kn8xOTMoWlnvSr8BLc+2jgC4M9K3cGgsLNHiqa8xsfnvd1+zfCEuM1aXehG4mwXKKDe+9Si3cw6nIC+sjyRAFxbIQBFpTZetz9jMW9MpEqT/DWKTAQCrUIQgPoQBKCF2FEJgJfHKLPt+xvzBKCIDGDVuo1Jhe/P76oQAKV9f9ZFUdY66/A+HY/H/SQkNdZy6oIV9BpvKE4lACq7v/eDFYKmzLb4niqzbSPh03bUfaF5XHV8/cREEQA8S0km/D6HWpOJFHhiov42zNL+zi4b1fkJgJ+YFH2/GglPAAZO5kvrUov2l5attYMuf7jmhu95EE6gcJwjALOXFuu0f/biMe1nPS0aE68mTjn8NYpMBAKtQhCA+hAEoIXYUQmA33aqupypsp0UrHwvX6yqwveMwU+3X3PucE4Api96J+ks32l7cj4v2n3m+8m3PC7v3/88dZY3FP/szjQCoLZu+gmNIhOYO17UUJgCn7ZzxmBeDKE3QRU5fmKipgloRFfLjnL+i4IEwBO5K4QJODUhK5UAjJq51M4cOt2WvPPhT3G2Bymv0b/3andH6lmNhCcAf5rECUBq0f6BFCor67jdl5alnfW16yrZ/UXz9ve9aHSHn0uvLE+7L3+NmnIGAq1CEID6EASghdhRCcD5I55vv0bpnNesB9nOuvoJABaramnVT++sEAAVpTl90cqks75102Pt1zw8exm95sq2SqF90s2P0Wuw2HviFZ4q5A3FP/nzNHqNGWT3C1Orl478+A5+1vK163NnNSO6zxtkfypIDkrHlJ7YF9rKM4FGdOUn8GSiKAHwv0dFAFK3vl7hJjm3TdYE4INrDuk9Xl6zactW+/ldz9jP73qmkCF/e5DyGj3xvW6c3pvQSgKgtp2nFu0+bnPRCj5pw3QyheMdAVBd+1R4AvDYvLfoNXOXpd2Xv0ZNOQOBViEIQH0IAtBCtJoAbBWmvPPuqxCAi+7naTuYka0iGFOAxarqov3Pnyur7dUyracXrkw665s3VgjAmFlv0Gt8gXbijZwAYLGnvmi9oVgV7Wb538+y1fzeLx5ZkWj9tzjrzTX591QVx42El3v8jyA5KB1TemJfOCppBRrRlZ/Ak4miBMDLwpSkBYmJgpdyKRmKWVpxPNT5L0bMWJL+ggog5b78+6UK7dSzGgm/VFBFHb/4xvYX7Uq3j+lkCn57r2ompGK/XhUJkNr8nnpf/ppa0cmBQCsQBKA+BAFoIVpNANTm1B73zmy/5gIRt/kOyHZUpz0Fy1bni1UV5/jfd1QIgMqZn7pgRdJZ37h+cvs1o1/gBMBLNE64YTK9Bou9SeKL1huK/+v2qfQas/zvR5mTL7r/hQ7PwvdUFceNxG2TF3R4X++BdEzJHHynXUmmcJqg/ASeTNRKFEqBnwopeRwutks5a8CjxQiAJxO1zmok/H2pGFMvV6slc2olAVBRx7OXphXHJ91caSbMFM8zppMp+M8lVbSn4gAXdKBSpjA0QcFf8/i8IACBHQtBAOpDEIAWotkPLcpVVHLPucMrBOD8ETxucwXIdlSnPQU+ii4r66VV/3X71PZr1EbXJ+evSDrLa23bnucEwEttvnE9JwDYhX5kLv+i9dGdPxqURgCU5tt7NFQEI76nzYhXHOASctR9rQXpmDIU+m3UqdME5SfwZKJWBGsKPCnsdT+XxyExUWgkAfDG/Tuf4LGWZmYPPr/Uzhj8dOGMebwvFfF5oXtW7xILt/CsZsBLgJQ0KbU7fuqfprRfM0V07VML7RNuqBAAJU1MxYGXVgjAmFn8LPRMKfhrHn2ZTzkDgVYhCEB9CALQQjT7ocVutcq//91fn2u/RsVt+hXyWVnLVVKw5J18FJ1aWvWfg55qv0bFOU555e2ks3ze9qiZS+k1lzipzfHXPUqvwWJPddp8dOcPb9O56f4slWvvPRqnD+Rn4XtaNFEkBT5tR90XRr5OX8R1zl46kjpNUH4CL7+qldSSAl9oq2V0uNhOSe38M3FrQQLQ874Kab9n2uIOzzryqkfkNanw96Wmif6+1MZdPKsZ8HsArn34JXrN80vyRbuacvzwtsrn0jjx9z9jcVqh7QmAakykwseAPvg8/4yb9urKpPvy10ycW2wyEQg0GkEA6kMQgBai2Q8tdqtVRr4fj6u4TdSYK7lKCjCLWhW+pw+sfNEqKYfPHa911leuqRj3Rj73Or3GF3vHXTuJXoNd6LGia+clGv8x8El6jVn+i1YZCr1H4wcD+Fn4njZjeY9PfDlN3BfGkyqjo09gSp0mKD+BJxO1EphScP6ISkf7/BGcAOB9qeLYv8Y/Tiqmj/d/s7U8AI0stP1Zapron1W1cKvR95WCX99d2SrebwxfdoiRwspc/RPnTbr/Wf5ZguEECt6b9Pdni3k5Dr68QgDUZ9yU+W8n3Ze/ZmdcWhfo3AgCUB+CALQQzX5osVutjLt+PP674Txt543VeYlJkU2zi1a8lztLLa36j4FPtl+joiEnv/xW0llHXf1Ih1/aXr5wbP9J9BqMQ1WGYq+FVsWxWdpiK+/ROO1Wfha+p0WX98xZusZ63jfTXliiicTNLm3ne2JzMka+qkQRL49RhAmnCcpP4AvtWglMKfDvvdpGjfelimN/XzeML5aQ47dkq2Iv9axU+LPUHhBPmFTSEUoTVae9kfjfYZX366rRnACgPEZtO/fxxPeKZWcYTqDgCcBfn9aTnBQc0ruyCfhv0zmZeGzeW0n35a9RTY4dGc14pgKtQxCA+hAEoIVo9kOL3WqVM/8bNx4/R8Rtvg4ac9WtTgEuo1FLq04bUCEAatHUo0AA1Fnd+05ov0Z1TH3xcsw1E+k1GIea4if4/q28ODbLf9Gq6E7v0VBn4XtaNFP8kN6VxWkKN46vEIB/F5uT0Tui8sl9ApMiOThNUH4CTyZUalIqUuRxeF9Kaudfo+pCp+4U8BG5rZgAqD0gnkSrKccmkCYqyVQj8ashFQLQ5yG+n+AZKNoVkfPvvSraMZxAwROAu6cWIwCHXln5mx3+NCcmE19annRfe55fueYhEZqwo+LdDZvt69c/at/705SaEbnrN22xMbPeKBRoEWgNggDUhyAALUSzH1rUTKuEnLPcePxsEbeJEhPVrU4BbtxUS6u+f2vFbKe03PiFps46zH053ie6Y+W/VeQLR/fjBADjUFP8BKeK7rhZvqhS0Z2+CFVnLXgr/54W3d6ZUiRc79J2FAFA74gyTXqzrXqNOE1QfgJfaNdKYEpBijwO72uNKI59nOuVbXynAC5OU/ARucNFF9rswyMASk7oZXQqbhMnk0oy1Uj8wm0V7y32OaA+/v2NnAD49175L1KlNj4FaOhTi7b/hTn4befDpvKzxs95M+m+9rrgoQ4/41KxZv0mu2/6ErnnxOwfxHfi3OU2fVHtz61Zr6+2/7p9qpy8muVjgGvJqj5IV1M7XwI7LoIA1IcgAC1Esx9a7FYrg6wfj/9GxG0uXpEnAEUWTeHGTXWWT9tQG3AfmZv/QlNpJ348rsb2Xr/85X7cNIlxqEp+4Yu974ri2CxfVKnoTl+EqrOQVKniOBX+LCX3uM6l7aj7Wg7eERUp6Ccm3/kDPwsXyCk/gScTtQzYKfDmUbWMDknOqnVcaufN3KoIRd+Ows9cF1p1jlMXlKUAJxNKTuiJ7/UibQdldBs280K7kThjcIUAqH0OT0HXXk1yfDyxKrSfeCWNAPh0slqpSSn4kptyqrPGzFqWdF97OwJQS2KWgg/Il/pMNTN7zqUmqSku3peC/yzZkaJoA41DEID6EASghWj2Q4vdaqXb9+NxlbazECQmRRZN4cZNddZ3//hE+zVq0yx2tF5Zzs/yBjk1Hvd6b5WagpIW5Sfw2f2niILWLP8lpKI7fRGqzkJSVXSrqD9LRb72H/tSh/eF+wlUpKAnTCff8ji9BhfIKT+BL0JrGbBT4M2jahkdkpwVQlLgE3JUEZoaKfpz19FWxV7qfoIUYKKYkk34CcA1Y7nMCT+XVKe9kfCyHbXPAbv2Subk48+i/9oAACAASURBVIlV0lGq1t4TgFpxrinwMkd1Vtvzb2w3ASi6aC7l5/mpXdEFcj5t60+TiqVtBXZMBAGoD0EAWohmP7TYrVayHT8eP3MoN9uixGTusvpz5nHjpup8n/KHCgFQ2fAPz853tNRmzs+5jOy/iLG919p37zuBXoPdXjVi9tn9qqA1y38JqehOX4Sqs5BUPSWK41T4s5R0zC87U/eF+wnUsiOvHf/2zfwsTKJSfgJfhCo/QSrOGlZ579UyOiQ5ijD93hFMVYSmRor+ckjlb/Z2kbaDEsAiwMmEknP432Pf0Vxrj5Mc1WlvJLxsR+1zwK69kjn9aFCFAAyespBeg94kBb9VuFZqUgo8AVBnjXzu9aT72ufCCgFQE9NUpPw8v9laSe1Sz/KNiZuEDC31rMCOiSAA9SEIQAvR7IcWu9WqO+7H42px0ivL8wXmnKX1EwDcuKk63yff8nj7NcrMiSNtRUz8khwlmfBa+yP6cAKA3V6VtuHlHrU0pv4sFd3pi1B1FpKqKfOLbe/0Z6nlan7Zmbov3E+gFqd5A/a3buJnYRKV8hP4IlSlE6XCp+2oZXRokFc7Mn43vPJ8XTySF6Eoj1EmRi/bU0vFsNNeBDiZUK/R/x6VzAmJnOq0NxJetqP2OWDXXkm5/B4AVWhPnJtmtvUEoJZcJQWeAKizRsxYknRfn75wdPs1RdOJUn6eJybq7yz1LB9O0H8s3/mQelZgx0QQgPoQBKCFaPZDi91q1Wn3emJltn0ZJCZFcuZx46bqfJ90cyUhQ5k5x8zKj7QVMfEEQJntvNb+sCvH02uw25viJzjxRl7Qoq5aRXf6IlSdhaTqCVEcp8KfpbwjftSu7gvN4ypT3BuwvynOwkJb+Ql8EVrLf5EC32k/axgvTPA1qo3O5ziCedH9vAjFSFGlj/fGfSWZwL//IsDJhHom/O9RTTnw97h63YdPALxsR207x679SuFz8PHEqtCe8GJemqhiKT0BGDhZy1VS4D0AKoJ1+DOvbTcBKJpOlPLzPDEpSgD+NKmyobyvSHxKPev9jVvs5Fset1P/NEXGwgaajyAA9aHTEIANGzbYeeedZx//+Mdt9913t8MPP9zGjRvX4f83YsQI+8EPfmB77rmnfexjH7N9993Xzj33XFu1ihdfDzzwgH3hC1+w3XbbzT71qU/ZJZdcYps31zeybvZDi502VWj7xTbKbDt3Wb7DXCRnfuZr+Y2bikyc6CLyfjSIE4CHXngj6SxPAJRu1+9DOKQ3JwAoaUnxE5xww2R6DSa+PCuSe3wRqopjJFWPzeNa+1T4s5R3xC87U68R9xM8LDLFvT5enYXThMnCT+DJVy3/RQq81l7tokCDvNpF4b0cF4guNEaKKn28j+69cTyXOeDEpAhwMqGeCf/cK5KD75cyFDcSvmt/3n2cAGCimPI5+HhiVWiPA2/SFiHl+vr1FQJQazt0CjwBUFOhvz69OI0AXFQhAEMKphOl/Lz7plcIgPKhpZ416LEF7dcoEpp61oBHK2Si6CQk0DgEAagPnYYAnH766datWzfr0aOHDRw40Lp3727dunWzxx/Xemszs3/5l3+xz33uc3bxxRfboEGD7Oyzz7Zdd93V9ttvP3v//XxXa/To0faRj3zEjj32WLvtttvst7/9rX30ox+1M888s657bvZDiwWAKtp/7Mbjymw7Z2meAKhiNQW4cVPd1wk3VCLyVJrLg88vzZ2lFld5AqB0u76o+uIVnExiEZriJ/jG9bygxTx0FYHnJVqqOH5hSZ4AKLNtKlIKWr/sTL1G3E8wZhYnAF4f//XrH6XXYKd9kvAT+CJU+QlS4Zc+qV0UaJBXXhvv5VBdaJTtvSv08f5ZvfZhLnPA96sIcDKhklr8c68Wp6GfSJmmGwnftVcac+zaKy+HjydWRftY8Cap7rEnALXMrynwBECZX++ZlkYA9nUEQH1epiLl5w1/ujKZKEoA7nj81fZrlNwr9Sw/5SxK0AKNQxCA+tApCMC0adOsVCpZ//792//b+vXrbe+997bu3bvX/H8nTZpU9d/uuusuK5VKNmjQoNx//+xnP2sHHXRQruN/0UUX2Uc+8hGbO5cnXNRCsx9aHLWr5VB+PK7MtthhLhIziRs31X35jGyV5vLAzDwBmCnO8gRAJWR4WcXBlz9Mr8GiKsVPcPx1vKBFXfUzIrnHS7RUcYxTFWW2TUVKsefj9tRrnA/F3mixVMjr478mzsJpwsS5/DX6IlT5CVLh02POGMwJAL5GFWvrvRyqC41JR8qI6p9VtdkWC+0iwMmE2rfhn3tVaKOcUBXajYTv2qs4V+zaK/P791w8sVp2htJEtVTME4BbHtGG1RR4AqDIxLCpi5Keic/0qhAAZTJPhf95ytT+F0dMlNQOz1K4bXJlAhAEoHMiCEB96BQEoGfPnrbLLrvYmjV5vXffvn2tVCrZa69tX2rB2rVrrVQq2bnnntv+3+bMmWOlUsn++Mc/5q5dunSplUol692793bfd7MfWixW1XIon2qhzLbYYS4SM4kbN9V9eX3saQM4AcBUCzWZ8ClAyrjnjZWfv4wTACxCU/wEx107iV6Dm5qnvcrfUy/RUsUxTlWU2TYVKcWej9tUrxH3E6jNyV4ff6w4C6cJE17kr9EXoWpikgqfHvMzMR1Dg7xKovJejh6iOEbZnpLH+GdVmW2x0C6C1EAB/9yfO5y/RjSsq0K7kfBdexXnil17ZX7/dxdPrIp2jNtUSUeeANRKrEmBJwDqvoY8lUYA9us1pv0aJXNKRQoR8sTkf4dxqR2epXwV3gOgEp/Qf6XO6psYKRpoLoIA1IdOQQCOP/5423///av++4QJE6xUKtmoUaO267x58+ZZqVSyvn37tv+3YcOGWalUsmnTqgviT37yk3bqqadu9303+6FFra3q2nt9rNLaY4dZZbCnADduqvs67tpJFQIg4hz//uwSOKtjAqCMe34fwoGXjqXXYBGq/ARe731s/0n0GoxpVNGdXqKlimOcqiizbSryxR4nAD5uU71G3E+gtop6/8VXxVnYaR8nXqMvQpU0KRU+PeYnYjqGhbZKtfJeDlUco8dE6dD9WUrnjMbwIkgNFPDP/Tmi0473pQrtRsIX7WrZIXbtldH5Oy6eWBXto2AyqaRcvsmhFqelwhMAdV93PblwuwlAUXOy/3kq8WmIu69UAqA2SN88oZICdIlI28K9FiptKwjAjokgAPWhUxCAAw44wI477riq//5B137AgAHbdd4ZZ5xhu+yyi82bV/nQ7N+/v5wmHHbYYfalL32p5pnLly+32bNn5/6NHDmyqQ8tFquqa3/6wAoBUFr7GdBhLpIz/+T8FUn3dWz/CgFQcY5/m54nAEpG4wmA6mj5ouqASzgBwCJULWHyeu9jrplIr8FNzSq600u0VHGMUxVltk2FP0stavO7DtRrxP0Eaquof7++Is7CTvtY8Rq9Pl5NTFLh3/sfi+kYdrSVEd17OZQMBT0mSh7jzcmqyEHSrrqcKcDJhErb8r/Hs0WnHeWEKjWpkfBFu9KYY6CAMjr7/SQ3jOdFO04m14jC1y8Cu054OVLhCYC6rzufeDV3XwpeAlRU+uJ/nvJ7DJ5SIQBqFw2epQzy1497uf0aRY5xr4VK2/IEQMm9As1HEID60CkIwF577WUnnnhi1X9fsGCBlUolu+GGG5LPuvvuu61UKtl5552X++9XXHGFlUolW768Wmd89NFH20EHHVTz3EsvvdRKpRL916yHFotV1bX/gdPHKq399EX5ArNIzvwUWLij7uuYaya2X/PvIs7xPiAASkbjCYBKyPBF1f4Xj6HXYBEq/QRO7310P17QYk67iu70Ei1VHONURZltU+HPUrsV/K4D9RqxOFabk/379eV+fAszdtrVa/T6eDUxScV/DqqQYxVFix1tZUT3Xg5VHOPUTuXte3Oykjng36xKokkBBgookuOlSarT/vySPDFRhXYjcYrbKaIKTAwUUOZ3f5Yq2u9/Nk8AVNTpsW7KWSuzPgVH9KkQgOvENMEbZFMJQNHC1/88Ne3x96V+PyjbUaTqmrGVBYWKHKP/at1GPqEJArBjIghAfegUBKBRE4DHHnvMdt99dzvhhBOqoj07wwQAi1W1OfW0WysEQGntn4YOc5Gc+cfnvZ10X0f3qxCA74g4R8y1VpMJTwDUKNcXVZ/pNZpeg0Wo8hN4vfdRV/OCFjc1q1hLL9FShfbUBfmpijLbpsKfpbq9Pm5TvUYsjkfM4IvT/Pt15FX8LIyiVa/RF6FqMpEKPx37z0F8OoYdbWVE914OVRxjopCSofizVKQoksIiOeY4mVDJXV5Gpzrt6FdRJvNG4ts3V4p2tewQAwXUffmzVNGOk0nl5fiqm3JePWb7gyU8DrtyfPtZKhnKR2SmEoCi6UT+5y1awd9Tf1+KAGBsstrT4It2FUWL8kslTfLLDoMA7DgIAlAfOgUBaIQHYObMmfbP//zPduihh9q771ZrnDuDBwCLVbU51adafP9WLrXBArNIzvxkWLij7uuoqx9pv+aUW3icI+Zaq8nE5y97uMMPcp/48umLOAHAIlT5CbycSBW0b4OxUsVa+ghDVWijrEqZbVPhz1LdXh+3qV4jFsf3ic3J/v3q3pdvYcYoWvUafRGqCFMq/HTs9IGcAGBHWxnRvZdDFcc4tVPdcX+WihR9Cv5mlQEzBRgooF7jL9wUTWm50a+iTOaNhN8potKcULaj7utbN1XOUkX7vdCYUF6Or7gpZ9/RemlVCg7pXSEA14zl9+UTclIJQFFzsv9588V7OnByxbir9m1gbLKSx13h9pMocrwW5Jdq6/NVoyvThCAAOw6CANSHTkEAevToQVOA+vTpk5QCNH/+fNtjjz1s3333tbfe4oXsBw+YSgG64oortvu+m/3QYrGqNqd6g9ypQmuPBWaRnPlJsHBH3deRV1UIwMmCAGCutZpMeAKgOlo+8WWfCx+i12ARqvwEXk70JVHQYuSjirX0EYaq0EZZlTLbpsKfpSQtPm5TvUYsjoeLzckp7xeSCfUafRGqCFMq/HTsB2I6hh1tZWr3fgJVHOPUTnWh/VkqUnTK/PwzoWQOKcD0K/Uavc9BFXLoV1Em80bC7xRRaU4YKKDu65uOTKii3efa1ypWv9yv8hnXp8bW2hR88YpxHRITv9gqlQAoP0EKULaj/EQ+uUc9Nxs252U7S8V0zKeTqV0UKL9UBM0TgKKTkM1bttov7nrGfn7XM9J03GjMXbbG/jDxFfn6dlYEAagPnYIATJ06tWoPwIYNG2yfffaxI444ov2/LV68uCqvf9myZbbXXnvZJz7xCVu4cGHNn7PffvvZQQcdZFu2VDpnvXr1so985CP24ovb/2Hd7IcW5RdKYuINct8VWnssMIvkzE+cuzzpvryp7aSbeZ475lqrycRBl1cIwM2io+UTX/a6gBMALEKVn8DLiQ7vw7cKL1udJwAq1tJHGKriGGVVymybCn+WkrT4uE31Gp8DI6rappnyfmEUrXqN/iw1TUiFn46pJCrsaCtTu/cTqCIHTdOqY+rPUpGi+EyoJJoU4E4B9Rq9z+HnYnEaSpNUbGoj4XeKqF0nKNtRxao/SxXtf4HGhIo69U2OK0ScayoOdp9xipj4QrsWAfCLwJSfIAUo21F+oj9MfKX9GiXRwthk5dG40IUTqL8NlF8uF78fLwEq8j6Y5afVtbYKv7V2gz08e5k0Jm8PPvh5Sr64syIIQH3oFATAzOy0006zbt26Wc+ePW3gwIF25JFHWrdu3Wzy5Ers3zHHHGOlUv4lH3TQQe2m36FDh+b+jRuX3/764IMP2kc+8hE77rjj7LbbbrOzzz7bPvrRj9ovfvGLuu652Q8tFqtKYuJNbacIrT0WE0Vy5sfDwh11X4f3qYy0T7yREwDMtVaTCU8AbhzPCYDvqv7b+fzLEYtQ5SfwcqJDr+QFLUY+qljLU10RqopjlFUps20q/FlK7uHjNtVrxPSoe8Tm5JT3C1Nt1Gv0Zx3RpxgBSJmOYUdbmdq9n0BtFUbTtMrb92epSFF8JtRSsRTgPgfltfFTtDMG8047SpNUUdhI+LhNtesEZTsq6tSfpYp2bEwo82t31+S4bFSx7wU/5VTExBfatQjApy+sEADlJ0gBpu0oP5GP7lQEAHX7ihx7b5L620D5pZomeDmRWriXimsffqn9rFpTlQ+M4Ve2FSOEZmnLznZGBAGoD52GAKxfv9569Ohhe+yxh+2222522GGH2dix+ehGRgBUMk+pVLJjjjmm6ufcf//9dvDBB9tuu+1mn/zkJ61Xr162aVN9X6TNfmhRfqEkJt7U9u2budTmUSgmiuTMPwwLd9R9HepMbWqh0xDItVaTCU8AVN62T9tRH5hYhKbIiQ7pPY5eg8ZKFWv5XVeEquIYZVXKbJuCrdC1U7sVfNymeo3YHR82lS9OS3m/UGqjXqM/S71fqUiZjqE/RpnavZ9A6dCRtKsiNGWzLT4TSuecglQ/kZ+i/VRIbVCapIrCRsKn7ahdJ+gnUvsc/H4SVbRjY0KZuX2TQ0VWpsJvO1fE5JZH5uXuS2GvCx5qv0b5CVKAaTvKT3TD+Ep0pyIAGJus/jZ+77xJahcFyi+V18bvOik6ofHpRGoKbdbYoj0IQMCj0xCAnRHNfmhRfqEkJt7U9q2beKd9IhQTRXLmx8xalnRfh/SuaFrVQiefH52V9WTCd8dUdJ9P28nKPDcdO9qKAPhC6AtX8IIWIx/HzOKmVp87ropjlFUps20K0Gyndiv4uE31GrE7PkRsTvbTF3UWkgn1Gv17r96vVKRMx9Afo4pj7ydQOnQk7ao49rIwFSn6yNz8pE1lsKcA/URKaud/j0pq8wTICVVR2Ej4tB216wT9RLOX8vvy+0lUzCQu3FIFpm9yqDjXVBxwSYUAKGJy04Q8AVC7If7t/Mo1RdKJULaj5ITXuex+JR1D3b4iaF6aqP42UH6pvDY+6rjohCbVT5BStG/dus1+99fn7Myh0+VCtNSzUnHnE69a974T5MS+mQgCUB+CALQQzX5osVhVEhNvavumkNpgMVEkZ340LNxR9/UFZ2r7+vV8odOfYbGNmkz47piK7vNpO1mZ56Zjtrrq5PhC6KDLH6bXYOSjSrU52RWhXxTFMf5+lNk2Bdi1U7sVfNymeo2o91aL0/z0RZ2FZEK9Rv/eHyzOSoWfjikjOvpjlKnd+wnUVmEk7ao49rIwFSmKUru31tZPANBPpKR23pugpDaPzctPE1WkaCPh03aUmRtlO+q99/tJVNGOC7eUXt03OS4UiTWp2P/iyvZeNU3wS7LUZxwad4ukE70Lsh0lJ+w/tiKPUeQYdfvq9+Olib8WaVuvg/xSGb69nEiRvVSk7hRIKdr9zoqhoqmSelYqGnlWUQQBqA9BAFqIZj+0WDApiYlPyFBSGywmiuTMtz3/RtJ9edmO2uh6Oyy2UZOJA113TI20vawiK/NV87gPQfkJfEH7uUv5VmE0VqpUm5NurhA0VdDi76eWyawjoNZW6b193KZ6jaj3/rNYnOanL+osJBPqNfqzPn9ZMQLgp2PKiI7+GGVq91IuVRzjlEN1TFM226LUThlRU4DSJCXb894EJbVBOeFz4jU2Ej5tR5m5UbajiIk/SxXt+LmkOsy+yXH+iGIEwCf3XCyK1eucDj0r890QKAEskk6Esh2VHnX1mEp3XE2OULev0sl+66SJKm0LY22VEd1HHaudAqm4sq3iJ1DhEWZphbb3ctSa0KQW7fPferfDSVwQgJ0fQQBaiGY/tNXbYXnR/vXrK6Y21WnHYqJIzjwu3FH35Zd3qY2uuNhGTSY+67pj6gPTSzSyMl8Pj3pv5SfwReiBl/CCFiMfVaqNzzBXBS3+fpTZNgWr389/aavdCj5uU71G1HvfLhan+emLOgvfe/UaU85KhZ+OKSM6FrTSbO+KdrVVGEn7DNEx9dIkVeSMmZUn2sqImgL0vqhJm/c5KKkNytWUx6SR8Gk7ysyNsh1FTPxZagcDfi6pnQK+yaHiXFPxaZfco4pV32nPynw3BEoAexfQvqNsR00TfdqO+ttA3b4ix7920kSVtoWxtkpq97vhz7nfdTECcPmoCgFQ8dFmaYW2J3LqOwiJnMKbayrvqwodSL2vZiEIQH0IAtBCNPuhxe7rQ6Jr71MtVKcddftFcuZx4Y66L9+1/2r/SfQav0AmK+vJhB+Pq5G2l2ioL0fUeys/gS9CP3vxGHoNGitVqo2f0BwouuP4+1Fm2xSshFG7krT4zHf1GlHvrRan+emLOgvfe/UaU85KRcp0DP0xyofipVwqlg9JjvJfeGmSKnIeAqndkne4DCUFaMBWkzbvTfiPgbzTPuHFN5NeYyPhI4WVmRtlO4p8+eQeVbTj55KSmPgmh4qsTMU+F1aMu2oBVj/Xac/Kbfb+xurPOMzbL6J9x88SNU303XH1t4G6fSUn8tJE5Sd4FeSXappwjvMTqJ0Cqbj0gdkdfg6mFu2eMCk/Af4eFTxZrWVEDwKw8yMIQAvR7IcWu68PPs+Ldp9qoTrtqNsvkjOPC3fUfXlT21eu4RtdcbGNmkz48bgaafvIx6zMFyeh3lv5CXwRul8vXoRi5KNKtfG54weIjjb+fpTZNgVvrc2P2pWkxWe+q9eIeu+Bk/no2xeO6ix879Vr9Gd9phff6JyKlOkY+i9Ud9xLudRWYSQ5qmPqp0KqyPE64aysjagpQO+Lmtp5b8JpQms/DuRqKja1kfBpO2qr+B0g21FylSP6VAjA70XRfit8LqmdAr7J8bvhPLEmFT65R00mvBE1K7fZe2Q3BHqAiqQToWxHGeR93KbyaGBssvr9eGmiiqLFWFs1TTjb+QmKEjS/oEx9DmJsqkIKmUD/hYKfJtTadRAEYOdHEIAWotkPLXZfHxBde59qcYwotLGYKJIzjwt31H35rv3R/fh94WIbNZnw43E10va66qzMFyeh3rufkBP5InTfi3gRisZKlWrjJzT7i442+ioGT1lIr0sBdtqUpMXHbarXiPKYW4X21ReO6ix875Wh2J/1aXFWKr6WMB1D/4XqjvuiXRU5+DerIkX9ZEIVOThpUzr0FKD3RRFt73P4/q1cajMW5GrqNTYSPm1HeTlQtqOWnR3mzlJFO+btq8hKL01UkZWp8Mk9ajLhjahZuc3WrK+OtF63MV84Kj9BClC2o9KjfEGrnhuMTVa/Hy9NVGZ7nL6qaYKXExUlaD5S9JZHuHcM33uFC9yysyHicxBN0woXO2Jyh5BomgUB6AwIAtBCNPuhxUVAqmvvUy1UoY26/SI587hwR92X79ofdfUj9Br8olVn+cU2l4/iBMDrqtWXI76nyk+QK0Iv5EUoGitVqo2f0KiONhI0ZbZNAX7RKsOnj9tUrxHlMSr9wpMvdRa+93eK1+jP2ltsdE7FsQnTMSxolQ/FF+3KiIoTkydEx9RPJlTe/v3P5gmA0qGnAKVJirR7n4PS2qM3QXWFG4kvOrOt8nLcNjlPANRk4pDeFQKginbM21eRlfv1qhAAFVmZAkzuUd1qL7XJym22el31Z9xaMO4WMb9iM0GlR/ki9N+FRAtjk9Xvx28C/7Ew22OsrfKhnDWsQgD+r8DvxyxPAFSnHf1XCn7XgZqELl+zPuksL3NS30Gbt6RNJpqFIAD1IQhAC9HshxYXAf39WV60H92vQgBUoY3dxCI588Offi3pvnzX/sir+H3hF62aTOztxuNqpH0yEAD25YjvqfIT+E6oKkLRWPkXYWr1ExrVHUeCpsy2KcAvWrWnwcdtqteI8hilV/XkS52F773qVvmz9hQbnVPh8+OVDwULWuVD8UX790RxjK9Rya/8ZEKlpoyYkZ+01TL4dQSUEyqi7f+GviP2JqA3QXWFG4mDndlWeTlQtqMmEz6557cighXz9tVOgX3dZ5yKrEwBasfVBlwvtcnKbfbOe9XL4bAIVX6CFKBsRzUTLrq/0tFW+zYwNlmFE/hN4MpQjNNXNU3wciIVt5uKC13XXjWOVoBkSsETAPU5iI0cBS9zUt9BuM+h1QgCUB+CALQQzX5oMW3jb6JoP+rqSqqFKrRRt18kZx4X7qj78qa2L/WdQK/BL1o1mdgrgQB4jbb6csT3VPkJfCdUFaForLx7Kv/w9RMa1R1HgqZ0oSnAeFK1p8FnvqvXiIZPtTfBm1rVWfjeq9foz8rKetlRCr6SMB3DglbJY3zRrrqc+BrVZms/mVCRojhpU1GHKUBpkvo787GpSmuP0yrVFW4k/CJA5eX446T8NFFNJnxyjyra/WbbrKxNpv4z7qxh9RMATO5R26EvGzU7dx1bDrdqXV46ovwEKcAiVPljzh9RKY7VNvr58LmkpmNemqiSqHD6qqYJXk6k4nZT4V+j2ir8ZmLXvud9FQKg/ARodFbwEwC1UwDTnFqNIAD1IQhAC9HshxaLr3tF0e5j7VShjbr9IjnzuHBHkQlftB/eZzy9Br9o1WTC62OVptVrtNWXI76nyk+A0wQGzHxXH75+QqO640jQ1JdCCjCeVO1p8Jnv6jWi4VPtTfCFozoL33sVpYdnbSXLjlLhM9/VdGwUTF+UD8UX7ao7jn4CNX3xpFDl7eOkTclQUoDyK/VZ4mNTVSGH0ypFchoJvwjwOCHlQjmhSr/yyT0qgvU6WLilTKb+M+7MofysFGDii5KreK19Vm6z5Wurd0NgF7pIPClOE5U/xi/cUhIt/FxSkyMvTVRJVDh9VdMen3RW5Pdjln+N6jsICZP67PIbitVUdR74HNRZPupUySrRy9FqBAGoD0EAWohmP7RYfKmi3UfkqUIbu4lqVJgCXLij7ssX7Yddye8Lv2gVmfDXKE2r12hnZb45Fd9T5SfAaQLrQqOxUpm5/IRGdceRoCmzbQpQH6sSX34Ai9PYa0R9vMqsaHOfmwAAIABJREFU/uaNHb9f+N6rZTp4FlvolgpPjtV0DKcvSh7j5URqqzC+X6pg8qRQdTn/ApM2JUNJAUqT1N+s/xv61k28kMP3S5GcRsKbbY8VUq6bYZqo5Fc+uUdFsGLevjKZ+s+4X4g0pxRgco+SJnmtfVbmy+EwBaxI+g3KdtRniV+4pSRaaNxVkyO/hFF5bXD6qqYJXk5U5PdjlpftqAVy+H6pzy5vAr5hPP9MRZmTOuvc4ZX7UlPVVDlRsxAEoD4EAWghmv3QYja8WpzkI/IOFYU2dhOVXCUFuHCH3Rea2g7pLQgAbLZkhQmepTStPm4zK7fZcvLliAWakhPhNGEL6b6gsVIl9/giVH34IkGrtWq+I+B4XO1p8ElH6jWiPl7tTUDyxc7C9/5PkzgBwN8jW+iWCp/5rqZjaLZN8dqoJBp8v5Sh2JNC1eXESZuSoaQAvRzqs8T7HL4pOrnoTVASs0bCm21VpDBOE1X6lScTqijEvH1mMsXPpTMG119gYnqMkiZ5rX1W5svh0Dyq/AQpQDmhksf5LrSSaGFssvIT+CWMymuDsbZqmuDlRCptKxW/+2vHS8VwysF20Zjl5URqs/3zS1YlneWJiWoc4e+xiKyyEQgCUB+CALQQzX5oMRteLU7yEXmH9B5Hr0HdvpKrpAAX7rD7QlPbF6/g94WdNlaYbIGzlKbVx21m5TZbtrqaAGCBdokY5WJBy7ovaKxUyT1+QqM+fJGgqbFwCvCLQ+1pOBUWp7HXiPp4tTfBF47qLHzvFcnB3yNbdpQKn/mupmNY0KZ4bZTMAeNcFfnyxETl7eOkTclQUoDSJPX3730O37ied3Lvg2mVkpg1Et5s++V+fJKD00RVYHoyoYpCzNtny87wM+5nIs0pBZj5rvwEvnOcldvs9VXVBACTe4rEk2JBq+RxXoeuJFrY0VaTI7+EUS19m/ZqngCoaYIPOlBpW6n4P2e2VbIqnL6yXTRmeTlRX+FDwymHOsv7CVQ8KU5fWIOmmQgCUB+CALQQzX5osZhQcWGH9K6kWhx8+cP0GuwmKrlKCnDhDrsvjB1T94WdNkYm8Cz14fs1KByXki9HLGh73c8JQEoXGo2VKrnHT2jUh+9fn84TNGW2TcEM+OJQkY/fhcVp7DWi4VPtTcD3np2F770iOT42NSvzZUep8JnvajqG05cUr42SOaT6CTwxUbnpOGlTm21TgNMXtYPBJ1YdL/YmDIf3S6UmNRI+BlhJua6FaaIqMH06mSoKMW+fLXTDzyWV5pSCNRDdqfTqXjuelflyuNchuadIPCkWjkoe99t7KsWxkmi9sCRPANTkyC9hVIlCT8H0VZE9LydSkaKp+M09HS8Vw+nrWhJFbZbv2qtNzegxU2d5MqEkmjh9KTJVbQSCANSHIAAtRLMfWiwm1Je2j7X7/GW80MZuYpFFU7hwh90XbkRU94WdNkYm8Cz14XssFI5L3qn+csSCVvkJsKBl41fMfFemVj+hycpttpl0x3FCo8y2KUBvgopWPQUWp7HXiIbPq0ZzAuALR3UWvveK5OBZbJ9DKnzmu5pC4fRl+NOcAPhJjuqOp/oJ/DOhEoX+/ETaZtsU4PRFTau8OVl1cpGsKllII+HNtkrKdc3Y/GeJKjB9co8qCntD3OZTJGUGP5dUmlMKMKXll0O4nMh3e7Nymy1aUb0c7rWVeb13kfhL7Gir9Kiz3MIttYwSjbtqcvQ9N5lURnTcKq7InpcTqUjRVPidAmqpGHbtV62rTqIzy8uJVBMKP8dZrLVZ3n+hJrRITIpMVRuBIAD1IQhAC9HshxaLCeXw97F2B146ll6D3cQii6YGTp7f4X2hqe1z4r6w08bIBCZk/F4QgK9C4ci6Y1jQKj8Bkgk2fkVjpTK1+glNVm6zjZurCQBOaFQnJwXYHVNf2ph0xF4jPoNqXO0LR/UFg++9IjlfgbPUF18K/AIpNYVCs60yyPtJjuqOY5qTeu/9M6EShW6HSRvrQqcCp4lqWuV9DqqTi2RVTZgaiZRAAWwmqALTkwlVFF4+Kk8AWGY9fsYVKTBx6+vPhTfBd46zcpu9SrZDY3JPkfjL1G3n/zuskrevJFpYHKvJ0b+7yaSS2uFWcUX2fNCBMtun4syhldeoUprQm8CS6Mzy2f3lv/GJNn6OrySx1mZ5/4Xaa4Oy0HcLTFUbgSAA9SEIQAvR7IcWiwm1MMRnZB9wCS+0UbdfZNEULtxh94WLRw4U94WbLVPIhOq+YOHIumNY0Co/AZIJ9oGJme/K1OonNFmZd8dxQqPMtilAaZL60sakI/Ya8Rm8so2nJvnCMStz2Q6abRXJ8dGdtb74UuAXSKkpFJIvZZD30wTVHUd9vJIT+ftSefs4aWNd6FTgNFFNq7zMSXVy8f1SUw6zf8jRHn35rUKmw9RAAWwmqMQaTyZUBCvGbbKUGfyMK1JgYnSn8ib4Yi8rt9l8sh0a8+NV1GkKqradi+nYL4dU4jaVRAuLYzU58pvAldTuUYi1VWTvtFsrBOAHwmuTCr9TQKU0oTeBxbSamf3aTUx63scbWugxY6l2ZnlvgtpPgORr9fv1N1UagSAA9SEIQAvR7IcWoyFVxJfPyN7/4jH0GtTtF1k0hQt32Fnvgants+K+cNTOyAQmZChTGxaOC0l3DAta5SdAMsFkKJhrrzTtfkKTlXl3HCc0apSbAsx8V9GqGLfJXiMaZNUXjDfIZmWuV8WzFMnB1KS3RRctBZ4cq+kYki9lkPXTBNUdR328Kpj8fSmZwwAg2mqxVQqQ+Kq0EG9OVovT8P1SqUled1zEwIxm2y8IKRc2E5gBG8nE6QN50X4JxG2ylBn8jFNpTinA6E7lTfBm26zcZvPIcjhcuKWiTlOAnWOVHuXz9pVECyUtyh/jN4GrRKGJMH1V0wQvJ1KRoqk4Y3AlUlRNVbBrz4IozPITE5XShFMOFvlqlicTKtUO/QRsSWYzEQSgPgQBaCGa/dCiOVF17Q5wudaf6cU3zWI3sciiKVy4w+5rLZja9uvFCQCO2lPIhDK1YRG6gHTHkFQpPwGSCSZDeRiMlSqBwS8eysq8O44TGmW2TQFOJlIy39VrxI62Mqxh0c46THiWIjndITVJddFS4Mmxmo4h+VIGed+1V91xlBOpgsln0au8/T9NyhMAtdgqBUh8FVn1MifVycX3S02YvM65SOgAbsk9SEi5roBmAku/wkQx1RXGuE2WMoPGXZXmlAKM7lSGYi8dycpt9tKyagKAyT1F8u+xc6yS6H7m8vZV2hYWx2py5CeTXxNSO2y+qGmCDzo4VUSKpuInLlJUmbTRm8BSmszMfjWkQgDU1meccrBQC7M8mVD7CZB8qWlCsxAEoD4EAWghmv3QojlRacz3d7nWn76IEwDU7RdZNHUTLNxh97X6/fyX477ivnDUnkImlKkNi9BXllcTACRVqvuCZ7GOCe5puEmYWn2xl5V5dxwNn8psmwJcuJWS+a5eI3a0VYcJo06Z+Q3PUiTHJ+RkZd1FS4Enx4qEIvlSXhvftVc657unpsXt+ix6lbePRFtFHaYAia8iq96c3F10cvH9UhMm35lUU4IUoAdITXLws4R5E5BMqAQmjNtk247RuKsy61OA0Z3KUOyTaLIy3w6NyT1F9hNg51gROZ+3r9K2UNKingm/g0VN2rD5IqcJTk6kvDap+LHbUKxM2hgMwXxoZmY/d3Ii1dDCKYc6y8uv1EQbyZeaJjQLQQDqQ6chABs2bLDzzjvPPv7xj9vuu+9uhx9+uI0bx0e7Hi+99JKdc8451r17d9ttt92sVCrZwoUL6bVZllmpVKr696tf/aque272Q4tmO6Ux/0yvSqzd3hc8RK9B3X6RRVO4cIfd16p1eVObIiY4amdkAjttavyKRSgbjyOpUt0X7EIzMxfuaVAbHX2xl5V5dxwNn8psmwIkJqprh0lH7DVi4otKrMCoU6bbx+64IjmYmqQ6Xynw5FiRUHzvldfGEznVHUd5jEru8n+zKlEIN9uyIjQVSL6UAdvLnI7owwkAvl9qwuS71YokpAA9QGqSg58lrMOMZEJ1hTFu85G51SZTNO6qNKcULIXoTmUo9mk7WZlvh8bIxyL7CZ6BzrEix//timOVtoXeJLVvw08m1dI3/IxT04Rv31yRE6nt3anwOwUUqcKuPZOhmuUnJmrpG045mKfNLC+/Uv44nEwU+UxtBIIA1IdOQwBOP/1069atm/Xo0cMGDhxo3bt3t27dutnjj9f+I73zzjvtox/9qB144IF28MEHd0gADj74YBs6dGju37Rp9cW1NfuhRbOdGtv7XOs9z+ebZlG3X2TRFC7cYWethC/HfS7kxKTX/fkvbUYmsNOmTG1YhLLxOJIq5SfALjQbmWKspdK0+8VDWZlLbVCipcy2KUjdH4FJR+w14vulRsxYtDPdPnbHFcnB1CTV+UqBL7Q/fWGaPE75YzyRU93xwVPS0rb836xKFLpxfJ4AqKjDFCCRu04YsL3MSaXt4PulTNNeAqRIaArQA6QmOfhZwjrMSCbUoimfrZ6VecoMGneLdJiXvJNP7vnPQdyb4OUeWZlvh8bkniL7CXDbuSLHPm9fpW2hN0kZ5P1kUk3acKeImiZ866bKNEFJ7VLhI0WVRwPll8ykbZafmKilbzjlYJJWM7OfOjKhvs/QT1DkM7URCAJQHzoFAZg2bZqVSiXr379/+39bv3697b333ta9e/ea/+/KlStt7dp/FHb9+/fvkACcdNJJDbvvZj+02E1UY3ufa52VOQFAOUGRRVO4cIfd19vw5biXmExcCKN2Riaw06b0l1iEsvE4kio1fj0MzlpORqYYa6k07X6LaVbmUhuUaCmzbQrQ8Km60BjdyV4jvl/nj+AE4IuQdMR0+0PheVYkB1OTFq+o/8vKF9pqOobvvfLaeDKhuuMo5VJkYm8XRakSha4Hoq2iDlOA5Es9q96votJ28P1SMicfWak6xylACaCa5OBnCeswI5lQCUwYt8lSZtC4qzrMGzdvtT9MfEWmEplVZ/crc7LXjmdlbq7G5J4i+wmenJ8nAOp5Pn1gpThWkc8Ym6wmR34yqSZt2HxR0wQfdKCkdqnwG4oVqcKN22wKbZafJiiTNk45XlnOz/LTF5VOhJMJNU1oFoIA1IdOQQB69uxpu+yyi61Zky/Q+vbta6VSyV57LW1cnEoANm7caO+9V/yBb/ZDi2Y7pTH3udZZuY1G7qGcoMiiKVy4w+5r+dq8pvXfxGTi/BH5L21GJnCaoPSXPqYxK/PxOJIq5SfAs5gOHWMtlabdbzHNylxqgxItZbZNARo+VfGF0Z3sNeL7pTKrD4akI6YxHQLPsyI5mJrEss5T4cmxmo6h2VZ5bTyZSO2OK7P9ni6KUumckWiPmcWjDlOA5Es9q17mpNJ28FlVBNN30RWpSgH6idQ0EWU7rMP8LgQKqAQmjNtkxTsad0+6mReYnjAp8+WiFe/lzlLmZB9FmZXb7FmyHRoXbhXZT4DSEfW34fP2VeTzI3PTvEl+MqkShbDJoSRmfqO7ktqlwkeKqvcUu/Zzl1U3oczM/nNQhTCpnQ845WATbbP89EXJY3EyoaYJzUIQgPrQKQjA8ccfb/vvv3/Vf58wYYKVSiUbNWpU0jkpBOBjH/uY7bLLLlYqlSzLMrvxxhvrvu9mP7RotlMac59rnZXbbMvWagKAcoIii6auHjO3w/t6E74cs7IiAPkvbUYmcJqgPjCxCz3r9WoCgKRKfWDiWUwzibGWStO+NxA0VgSgREuZbVOARmc1tsfUJPYa8f1SmdXeIJuV2+yN1dVn4fOsSA6mJqkxegpSyDFOx5TXxv8eVXf8tsl5AsDM9hhFqRKFkGirqMMU4O9RLQzyMieVtoPPqiKY/m+7iOQQ/USKyKFsh0WwIplQi6YwbpNFiqJxV53ldejPL+FxqJjdryIrvd47K/Pt0Jjco+REKUBTq/rb+P6tlbhNFfmM3XElC/M7WBTRxiaHmiYc76YJKlEoFae6SFG1PwI3brMmlFl+mqB2PuDuDnWWn76o6XjqZKJZCAJQHzoFATjggAPsuOOOq/rvc+bMsVKpZAMGDEg6pyMCcPLJJ1u/fv1s5MiRdscdd9jRRx9tpVLJzjvvvA7PXr58uc2ePTv3b+TIkU19aNFsx3S7WExk5TbbtKV60yzKCYosmsKFO+y+8MtRFV/4pc3IBI7a1QcmdqHZly0WocpPgGcteadahoKxlkrTvicQNCa1wSL04pHcbJsC1HursT0mHbHXiO+X2sJ8IBTtLP4Od1EoknMApCYV+bJCcryVkONbHsmTY1Ws+t+jMjpid5ydhbn2SueMRJvFWqYCf49KfuVlTkrKgc+qIphekqOaFylArX1W5gSgB8h22EZnJBNq0RTGbbL3Ho276iwfa6kIAGb3q0Qhbx7Nym329MJqAoDJPUpOlAKUjqi/Db+9V0VRj4XuuEoU8pNJRbQx1UpNE45z0wQ1aUuFX1Cm3lP0XzGPhpnZaW5i8hMhJ8IpR8pZajqeOploFoIA1IdOQQD22msvO/HEE6v++4IFC6xUKtkNN9yQdE5HBACxbds2O+GEE6xbt262ZEntWLpLL72UJgg186FFOcG1pGjHYiIrt9mGzdWLplBOUGTRFC7cYfeFX45ZmU8m8EubkQkctSsDFnahnyP6WCxClf4Sz2KmKUwUUkUVvg9MaoNF6EX3c619CtC4q2QomJrEXiO+XyplAot2dhY+z4rk7A+pSWr03REYOd5MyDHG2jIZGp6ljI7YHWdeG4yiVDpnJNos1jIV2Ey4fBR/Vr3MSUk5UE6oCKYnAEU+b7ABkJU5kTt3eP6zhJmTUU6oZCG/hrQd9t6jcVctrfJGVLUQDbP7VaKQz6LPym02lWyHxuSeIhtwMYpSyVB9cawS37A7PnjKQnqdn0wqGRqmWikfip8mqElbKvyCMrXzAbv27DvILL+gTHk0cMqRcpZKJ0qdTDQLQQDqQ6cgAM2aADCMHTvWSqWSDR06tOZ1O8IEAM1214ytlphshmIiK7fZ+k3VBADlBEUWTeHCHXZf+OWYlflkAr+0GZlAOZEyYGEXegbRx2IRqpbk4FnMNIWxlkzTzopQJrXBIvQCkbaTAjTuqp0PmJrEXiMWjiplAot2ZtzF51mRHN+FzsptNmdpfd0qRo43bu54Osb8MXjW5y/jBACJHOt8YxSlShRCon3/szzqMAX43Kvpi5c5KSkHygkVwfQSoCKxttgAyMqcyKFshxWFKCdUspCzhuUJAIuZXLxiXdJZPteeFexm1dn9KlHIZ9Fn5TZ7cn71eZjcU2QDLkZRqknOya44VmZ71LSrhCw/mVR/ZzjlVNMEv9FdTdpS4Sc5an8Edu2nL6r+DjLLLyhTfgKcMKecpZpjqZOJZiEIQH3oFASgWR4Ahg9Ixk033ZT8/3yAZj+0KCe4mhTt2E3MynzTLMoJiiyaumzU7A7vC1MtsjKfTPwOvrQZmXhjdX6aoDom2IVm+ljUaKuOCZ7FjKiYrMKKKtw8mpW5PAZ3KyizbQrQuKt2PqDRmb1GLBxVahIW7Sz/Gp9nRXI+DalJzMuRglRyfB1Mx5g/Bv/OVHcciRyT2r2/MU8AVKIQEu0RM+pfpoXkS01fvMxJxW1iDLAimD3vq5D7IqZ2JidknyUo22FFIYYTHCsSmM4cmk/bYTGTC0G3ryQmngBMErsc5i7LZ/erdCKfHpOV2+yJV6q3Q2NyT5EFZbhUUElHfXGsPBrYHb9dSMf8ZFItfcPP3pRpgpq0pcInCqkJDfrCmETLLD9N+OFtXE6EUw51lidfPxbfjZhYp6YJzUIQgPrQKQhAjx49aApQnz59GpoCxPDggw9aqVSye+65Z3tu2cya/9CinIAZ97CbmJX5ptm+o/NygiIdOdy4ye4LUy1U8fV/8KXNyMTriUtycOEW+8AcAEWo8hNgR5sZUbHQvoQUVYygMXkMFlXKbJsCNHwq3S4andlrxMJRpSZh0c5SJvB5Pn8EJzkYa6t00x1h4+bq9/79jdXPYP+xeQLAihz8O1PdcZwmMEL7HiTRKKMj/p2p3PQUYNIR2+eA0yol5cD3Sz1ffrpXRNKGf//qswS35LKiEMmEkoX47apZmcdMLgDdvjrLF44qyWnO0jwBUOlEPj0mK7fZY/Oqt0Njck+RBWWo22fPM77GrMwJAHbHVTKUj2BWf2eYaqV8KH6aoIh2KvyCslPEhAa79k+JiY8nTEqihRNmdZaXmKnvxurJBCcTzUIQgPrQKQjA1KlTq/YAbNiwwfbZZx874ogj2v/b4sWLbe5c3amuRQBWrlxpW7bkvyQ2bdpkRx11lO266662bNn2R+o1+6FFOUEfUrTjYpuszDfN9gE9MTsrFRfDxk12FqZaqOILu3aMTKCcSCUw4MItNm7HQkiNTDG7n2UwY6HNtuQygsbkMejRUGbbFKDhU+18QKMze43YtVepSZh09MryagKA5lG1th5N0/V2q9jfxrsJ0zGmV8euveyOw++RTdpws/UhvbnOGTfbslSbVOB7z/Y5oMxJxW3i+6X2k3hJjvpdp4BNE9mUE7fkMokJepOO7seL9p9D3CYjX68sfzfpLF8cq421mN2vllb5xJes3GaPvlxNADC5RxWrKcBt56xBY5aP28zK3KOBmnYVKeonk+rvDD97lQ/FTxMOFUQ7FT5RSO18QF/YFDKhMcs/E0qihVJOdZYnJirxCScT014NArAzolMQADOz0047zbp162Y9e/a0gQMH2pFHHmndunWzyZMrpqxjjjnGSqX8S169erX17t3bevfubd/85jetVCrZ73//e+vdu7fdcsst7dfdeeedtvfee1u5XLYBAwZY37597cADD7RSqWR9+/at656b/dCinKA30ZjjYpus3Gar1lUvmuoNcgJ2Vipw4Q47C1Mt1Jc2du0YmcACQI1MsWhn+lgshJSfALP7XyZJNLj0iXVVWRHK5DHo0VBm2xSgcVftfECjM3uN2LVXqUlYtLPkHnyeewiSg++X0r52BPa3sSZhOsb8Mdi1V8uo8PfIJm242VoZHXGzrUo6SQEad1lBjtMqtbwP3y9lDP2t+9v+nfCOpAC19lmZTzlRtsMkJthMOOpqLgvBtB1GvuaBbl9JTHyBxpKJzMyeX5LP7ldLq3zeflZus4lEUoTJPapYTQFqx9Xk2BfHWZl7NDC5R0WK+smkmkLhZ2/KNEER7VT4/QSKoGEAA5vQmOUJ06lCooUTZnWW35z8HwM5mcBoaPbd2EwEAagPnYYArF+/3nr06GF77LGH7bbbbnbYYYfZ2LF5vR8jAAsXLpTpPFmWtV83ffp0O/nkk+1f//Vfbdddd7V/+qd/si9/+ct277331n3PzX5oURfOkjtwsU1WbrOVZNPs5aPmdHhWKnB5FzsLUy3UlzZ27RiZwAJAfchh0c46JjhVUX4C7Giz2DQ0yLKuKitCmTymH3RVldk2BajbVzsf0OjMXiMSJpWahK+RkQl8ns8dXk0AmGn6GaF97Qjsb2P1uo6nY6xrj9toP30hL0yuGp3/PbLnGZNoVN4+Em2Vm54CNO6yCRNOq9TyPjQnq+fLJ+ko6VgKUGuvfo8o22FdYWwmKAM2pu2wwv2lZWuTzvISDbUz4TlY3qUiRf0yqqzcZhNerN4Ojck9akFZClC3rxpHvjjOytyjgUWoko75yaQyFONnr/Kh+GmCSu5Khd+crn4/2LVXng9PmL4rJFqDpyxMOstHnappApqmmXekmQgCUB86DQHYGdHshxZ14cxkinKCrNxmb5NNs6gnLrJoqvy35zs8C1MtsjKXJv3vsHzXjpEJLABUBBsW7Y/Pq/6Qwy600kxiR5sl0WChzYy7rAhl8hgsHJXZNgWo21fGPTQ6s9eInWOWmsSKdkYm8HlmUw5mmlbJKR2B/W28Q8gxTsdSuvaqMMHoTmZ+xSQalbePS/JU0kkKqt57QjDZtIrt7sBmgnq+/N/2WcO4dCwFbJrIfo8o22HpROhNUrpwTNthkaIvvrEm6Sy/CExJVWbA8i4VKeojH7Nym42bU00AcOOuWlCWAtSOq8aRL46zMvdoYBGqpIl+EaAyFGOYgwo6+IKbJqi/s1T4/QQqPha3nTOCZpYnTMrwjZPcR+bys/x7rwzfOJmYTKRjzUQQgPoQBKCFaPZDi7pwZjLFwiQrt9nytdU586jbZ2elwqd7qLMw1SIr867dr4bkCQAjE2i2UxFsuPWVfchhF1ppJvHeWRINGoqZcZcVoUweg4VjkY4p6vZVBjt6JthrxM4xS01iRTsjE/g8sykHM03XO65mfxsrCDnGVCu2z+Gd99K20SKZYH8bGGupEoVwSZ5KOkkBvvf/RwgmypyyMt/dgc0EZQz1HXm1oCgFbJrImhxnDM7LdlhXGL1JyoCNaTssUnT20rxuX2nMT3EZ+Ur3Pn1RPrtfRYr6hVtZuc3Gzq72smFyj+pWpwB1+6px5IvjrNxm6zZWyz2xCFXSxAOhMcFIKH72qmnCQW6acID4O0uFNxSr3w/6rx4mvx+zfNGuJjTYYGJkz8zsy/0q96WmCWianjiXTxOahSAA9SEIQAvR7IcWZSHMZIqFSVbmi6Yuuv+FDs9Kxe9heRc7C1MtsjLv2v0CunasYErdkolbX5lBDjuhbKMj62iz3GQ0FDNJCytCmTwGZRXKbJsC1O2rnQ/omWCvEVNtfkZM06xoZ2QCn2c25WBd6HrH1exvg5FjLGhZlxO79lmZEwDsjrP0G0yi2V8kneCSPJV0kgJ87xnBRJlTVua7O7CZoIyhZwyu/G2ruN0UsGki+z3+FHT7rCuMxl2lC8e0nbvI9AWNu+osn9OuCtWnYXmXiif1C7eycpuNmfVG1TWY3KO61SlA3b763sCt4kzuiUWoko5hmhszFKcs3DPLTxOUoTiEq5mnAAAgAElEQVQV3lCsfj/YtWe/H7N80a4mNDjJVQlS/r1X0wQ0TY8XZKJZCAJQH4IAtBDNfmhRFsJy01eQwoQtmroA9MTMsJoKzO5nZ+GXY1bm3Vcc27MvmJQtmaxoZwY57IQyPwHraLMNnqiPZ7IKVoQyeQxmviuzbQrwvtTOB/RMsNeIhImtrWdJR4xM4PPMilBM28nK2vzWEdjfxptrOp6OsS4n5sdnZd6ZRDLBfCEYa/mZXtxP8Lvh+b8zJR9JAb73TJLDyCrTcqM3gSV3meULcvbcpIJNE1mTA2U7rNhG464yYGPaDtPuo3FXacx91151vXF511fFTgGfH5+V26zt+eoCE7e+Hi+61SnALHr1vdEdtoozuSfKY9jSR7PqnSKMhOJnnFpQ5mWOyrifCr84UUW+Ytee/X7M8kW7mtBgg+mhF/hZR/SpvPdqmoCmaTY5aiaCANSHIAAtRLMfWpSFsNz0t9ZWFzlL3qmOmUQ9MStMUoHZ/eysF5ZUE4C31nY8tmdfMPilzbZksq2vTDOJKS3MT8A62s+SrcKoj2eyClaEMnkMylCU2TYFeF8q8hU9E+w1ImFii2ZY0c7IBD7PbMrBZCjK/NYR2N/GG6uryTEWtGwKxZZRsaQTJBPMF4JGVJV0gptt1cbdFKDRmT1fjKwyLTd+ljDJlFm+IFdemxSg1CYr8yYHynZYVxiNu2rTLKbtsOnLs6DbV2d5AqD8Eri86yuiwPR+gqzcZqNmLq26BpN7jhPdarN/TAu6951gf32apxOhbl/t7sCt4iyJDk2tSjqGO0UYCa1auCemCX6fi4q1TYU3FKutwihNeoD8fszyRbsiaEhy2O/azOxQl3Sk0qPQND1akIlmIQhAfQgC0EI0+6FFWQiL7kM9cVbmi6ZQT1xk0+xvIbqTnTUTUi2ycpstJ91XHNszMoFf2mzMyba+sjEnZpgzPwHraLMoStTH/5Z0tFkRyuQx2DlmZttU4H2p5A40OrPXiISJFXKsaGdkAvXxbMrBZCj16lXZ3wbbwoypVmwKhfnxWbnNNm6uJgBIJljUKRpRVWGCOzJU0sn6TVts1uur6UTiA+B7z54vJnNiWm70AF0hni9fkCuvTQrYNJF9xv1oUJ4AsG47GnfVpllM22HTl+mL3kk6y0uAlBwPl3epAtMnCmVlvlcAk3vUhmKzvNeJAXX7akEhbhVn016UxyjpGC4CZPtjUJqYMk1Qvp1UeEOxinzFrv39z/K9Dz6eVBE0bOSoHRI+NlVNE9A0/eDznEw0C0EA6kMQgBai2Q8tykJYMcE6k4tWVOfMo564yKbZX0N0JzsLu2NZmcsv/gfi9hiZQAkA25LJuvbMgIUZ5iyDmenQWRQlymN+TTrarAhl8hhc+lREM41fjiq5A++LbU5GwsQKOVa0MzKB+njWhV79fvVZ9epV2d8GKxwx1YpNodgyKt4dzxMAlnSERlSVt49/Z0o//oHWvpZECN97tgGbyZzY4jS/4Tcr86Qjs7yOXm07TQFKbbIyX6b3w9vysh2mMcdpgjKGngppOyxn/hnQ7auttV62o6Zxj8/LEwBVYOLGXVZgYnKPmiaYdUwAULevFhTiVnE27UV5jNopgGEO7BnEhXuKWKHMsRZJ7gh+b8qXROQrdu3ZBmkzs0N6V94vJffCwIoRM/hZ/r7UNAGDIRSZaBaCANSHIAAtRLMfWuwKM5PpG6urO5OvkkVTqCcusmn2rGEzOjwLu2NZmcsv/ht0u4xMoKGYLWFhXXtmmkIpBEtNYNn9bHMiymOYrpoVoUweg0ufmNk2FfjlyDTtTDLF4jaRMDHTNCvaGWFKmXIwGYpK0ugIrGvPCkfsaLMpFFtGxTqTOGljsjA0oqriC//O1Mbdjs4xq37vmSafPatMy40eIJUo9h8DK110ldxl9g/y/vKba2Vxhhn56jMOZTtMboPSRGUM/S6k7bD0nmmvrkw6y8t2FBmfDMu71E4Bv1QsK/MC8/5n8wRATRPMOn52ULevFrodBFvFWbMHTa1KOoa/a7a8DyeTyueEMkdmKE6F35ui0qNQmjScbJA2y+86UBukscHEtlGb5VOTlDkZiYkiE81CEID6EASghWj2Q4tdYfbhi4bCrNxm88miKdQTF9k0ixs32VnYHcvKXH6Bul1GJlACwHSOrGvPdI4ohTiF+AlYdv9TpDjGL6Ezh1Z3tFkRyuQxKB0pYprsP7bj+FgmmWJxm0iYWCd31brqop0RppQpB/NMqCSNjoBbX7MyLxyxo82mUNi1z8p8szVO2pjRGT0tWZl3JvHvjElakMgpoDeBLcBjzyrTcqM0SSXDeBmNiic0q3w2qQkHayawzziU7bD4W5QmKmPoKZC2w7bWPgXGXXWWl+0osjQJlnepnQJ+62tW5kUhJveoaYJZxwQAdftqPwkuFWTNHuxCM+kYC3NgzyBOJtU0AZPhmKE4FT6d6JDenADg9FVtfvbpRGobNX6OK5+G9zkoczIuwFRkolkIAlAfggC0EM1+aLErzLqJTJrAcubxS7vIplmM7mRnYXcsK3P5BcbtMTKBBIDpHFnXniUwoNn2ZOInYNn9U+ZXR1FisgrraLMidAYhACgdYWbbVOCXIyvQNm6uJgBsczISJrZpEjfbZmVOmDCKlk05mGdCpV90BPa3wQpH7GizKRRbRsWiDnHSxqZCLNWG5e3j3xmTtCD5UkCCybwc7P1iW8VRmqSSYbyMhv2dmVUXfAysmcA+43BJFpOFoDRR+S9OhrQdRk6mzH876Swv21Hv1cS5eQKgOsxfuy5PAIY/XV3I4cZdNU0wyxMARkJRt6/2k+BSQdbswehOJh1jCWzsGcRAAeZzYmSCyfZS4f0EKj0Kp69qe7d/v9TvBz/H2TI6s3ycs5omoC9MkYlmIQhAfQgC0EI0+6HFL21mMmXShJeWVX85/gaMu0U2zfp8b3UWdseycppul5EJ1ACzXGvWtWepCSiFYLFpLA6RZdHjlxDraLOiavqi6u446tCLpKagbIcVHWxiwjYno3ac7WBg5lFGmDCKlk05mGeiXsMamm2zcpu9srz6bwNTrZjUjnXtmTwGz2I+B7Yjg3Um8e+MGR1xMqGABPOHt1VLudhnCVu4hdu7VTKMz6xnsj2zagkjA2smsChdXJLFZCE4TVD+CzTbMvnVE2DcVWd94/qKbIcFOZiZTXgxv7xLdZj9BtmszDvMw5/OEwA1TTDLEwCWtoO6fbXRGZcKsmYPdqHZNIR5uZifABsTTFrFZI7M1J4Kn050kIh8xamw2t7t36/D+/DfNX6ODyHL6Mzypmk17UE5kSITzUIQgPoQBKCFaPZDi1/azGS6kEgTXnyj+svxLOjaFdk0+zNI7mFnYXcsK3NzstcJZ2VOJnBsz4xOzIjKjE4ohWCFCdOhsyx6TGliHW1WhDKzLerQfzSofgKAsh2maWfRnWxzMhImtoOBmUcZYcL4SDblYJ6Weg1rTLbDlrBhqhWT2mESVVbm0gQ8i02FWKoNK77w74zFJqKmXQG9CUzKxT5L2MIt3N6tilpvflXpJLjki4E1E1iULsp2mCwEpwn/JpJh0Gx7E4kUfWzeW0lnHe+69oxcmlVv7/2i6DD7DbJZmXeY/wLJPWqaYJYnAOx5xvQYFU+MSwXZZz3q49lkkjUmmJ8AGxPM58TIBJvapcL7CVTiE06F2f4IszyZUBuk8ftFbQL3MidlTkY5kSITzUIQgPoQBKCFaPZDi1/arPuygEgTZi+tTpnBrl2RTbM/geQedhZ2x7Iy11+fBsY9RiZwbM9i05gRlSVkoAyF+QmYDp1tFcYvIdbRZkUoM9uidpx1aFOB3TGmaWcTE5a3j7p9toOBmUcZYcLnmU05mKdFRel1BCbbYZ1jJMdMase69kyagGextB2WasOkCZiQxTraaJBVwOeLmXLZ+8WKL1zepwIFTrq5UkR/TaSTIBliwIjMrMyjdFG2w0ymbJrApC9otmWLph4F46466zjXtWfPlln19l61VOzofnkCwAq5YVPzyT1qmoASGSbbQd3+z0U8MUZ3LiBSO9THs8kka0wwPwE2Ji4m0wQWDMGmdqnwhbZKfMKp8O1ie7d/vxTZw+8XtosCf4eK7OEmcEVMmoUgAPUhCEAL0eyHFr+0mcmUJYqwL0fs2hXZNIsbN9lZGGuXlbn++vu35nW7jEzg2J7lWjMjKks6QBkK60yyjjbbKoxfQsxYyYoqZrZFIyrbUJwK/OJgmnbmc2B5+zgxYTsYmHmUEabf39vxlINJplSUXkfADdJZOY0cM6kd69ozaQKexUghi8hlhmJMyGIdbfzbUEBvAou/Ze8XW7iFkwkVKOC76CqLfsbiju+ffZY8v6Q6ScsTjqzMTaa4cCsrc/8Fmm3ZoqmJYNxVZx3bv0IA2BTXrHp77+dEh/moqx/JXXcXkZgMgehOVWCiD4jJdlC3zwitWfVOkVeWV3/Woz6eTSbZThG22BI/ly66P03m+A4h7SnAQlslPmHzhcXHmuXfLyUnwu8XFvOLYQ6K7KGcSBGTZiEIQH0IAtBCNPuhxaLwl0Oquy9Mm8y+HLFrV2TTLCb3sLMw1u4fXwrV8gvM22ZkYvqifNeOJR0wI+p9pHBEGcrXr6/uTL5JdOhsqzB+CbGONiuqmNkWjahsQ3Eq8IuDdWiZz2HCi9WvEScmbAcDMzozwoRFaKoOvd7ECpSXZOU0csyKNNa1Z4vtfjkk/3fGSCFLtWHSBPw7Y0ZHlLQoYAoYm+QwmRMrvnAyoQIFvPZdmRNR3sPAPktYktaJINthJlM2TWAL3Y4DrT3zX6BuPytzL8dXnGxHfe4+9EKeABwo9hMceVWeAPyZdHLvguhONU3AbvtCMqFF3b5KJ8P3gZm0UYbCpGNMysmICfrjLiDTBEYmmKclBWhOVtu7MWSCLe9DMqHIHn6/sLNwyqHMySgnUsSkWQgCUB+CALQQzX5osShk41f2pf0cyZk/Y3C+a1dk0ywm97CzMNYuK3P9NeZtsy/Ip6HIYcUEM6KyDGaUoTBpAtOhs2VUWByzJVmsCGVmWzSP1spN7wgp8bHM5zCOvEacmDDPBOvaM8KERSibcjAder2JFSxtJ4UcM6kdy6JftrpjeQybcuDznJW5NAEN8szoODWhgDar9iawVB7ckquKLyQmbGJilk+sUeZE1NEzsM8StmgOZTtMF86mCUx+5bv2WZn7L1C3r876cr9K0a4W/D34fH57r5KYfKnvhNx1rJP75yfyyT2qwEQZIJPtoG6fEVpmtmVSO0y1YYstWWOCERP0xzGZIyMTjLSnAKclewvDNzZfWHoUkgm1jA5JDjsLSdznL+NkD6fCaqt4sxAEoD4EAWghmv3QYlHIxq/sS5vFTP4UxvZKy5mC0wc+BfdVfRbG2mVlnk70HTDuMTKBul222IbJdljhiLIqtjiF6dDZMiosjllBy4pQpo/HAo1JNFKREh/LfA5jyWvEiQnzTDCjMyNMGEXLphxMMnWPyNLuCEy3n0KOmdQOpSpZOU0ewxanYdGelbkBEw3yrKBFs70CRncyIsdkTszM+aNBeQKgZC2+iFZJNNhFZ3hkbnWhzYz0KNthunA2TWAL3dBsy/wXqNtXZ/muveqgPzAzTwCUxOTwPuNz1zFZyO0Q3ammCeibYhNa3EbLppzMbMtM2ihDYYZo1phgxAQbOUzmyMgE8xOkAOVEewrDN3723kzM40gm1O8aSQ47C0mc+l2nEJNmIghAfQgC0EI0+6HF6M6fkpQZXG2flfkWVhzbKy1nCnDjJku/YeNxlk50Chj3GJlAmQDrJrL4SFY4oqyKrWFnHW22VRijO1lBy4pQpo/HAq3W4qSOgMSEdWhZ3j5buIVftMwzwYzObJqAr5FNOZhkamidiRWsoE0hx0xqx7LomTwGDfLsmWAJWcxQjAZ5VtCi2V5tOsWtwozIYaJQVubGfWwAqGhIL31R2mTUvjOMJ512ZqTHjHymC2fThHeJ/wLNtsx/gfeelbmXo7vr2qt435HP5bf3qqVih16ZJwADJ1d3cjG6U00TsNhmDRrU7TPZHjPbMqkdylCYdIw1JhgxQT8RkzkyMsGMzilge2aY4Rs/e5l5HMmE+l3jZy87C0mO+l2jnIilWjUTQQDqQxCAFqLZDy0mivwP6R6xIodtYUVDISMTqcCNm6yrxcbjzID57ZvzBICRCTTuscUpLImGReShrOorxE/AdOhsqzBGd7KClv1+mD4eCzRmtk0Fdu1Zh5b5HNjCLZyYMM8E69qzaQK+RjblYJIplaXdEVhBy3YwVJPjjqdQWZnLY/DvjD0TLCGLGYpxsRVLTcGONosTNav2ObBdGkzmxMycSEyUrt1LX5Q2GQtfVlQ9TDrtbM8EZuQzXTibJqwh/gvU2rNEIdTtq7N8155NhMzM/v5sfnvvpy/kReEhvcflrmMbigdOzif3qA4zyiZZgwZ1+yw+liX3MKndFWCQZZHPrDHBiAn6iZgRnZEJ9jebAiYnYoZv/Oy9jnhH0JugFsghyWFnofftM734c4NyIrZUsJkIAlAfggC0EM1+aDFRhOkvmTmRbWFF3S4jE6nAwoTlubPxOOsK4cIdRibQuMfkBCyJhkXkoayK+QmYDp1tFcYPaFbQMgLA9PH4u2Zm21SkxMcynwNbuIUTE+aZYF17Nk04c2j+NbIpB5NM1RtZh/sjsjInx/i3kUJCszKXx+BZbG8Ck6EwbTIutmKpKZhEwzrQZtVbhdnvkcmcUjbuKj+RL6KVDv2+6fnCdzMx0Y6ZVf1ZwvZMoGyHLShj0wQmv+oOWnuWKIS6/azcZqvXVRMA37VX5n58H5TG/AtX5AkAk3L8aVKeAKgOM05N2eczxkeyTeDMbMukdmiQZZHPrDHBiAl+jjOZI5OFMj9BCpiciBm+sSnEvCNIJpScCEkOOwsJkyKOSEyYqb2ZCAJQH4IAtBDNfmixa8fGx6zIYd0xNBQyMpEKNO6y+2LjcdYVwoU7jEygcY9lHbMkGtY5Rq39UVdXy4nYbgW2VRinCSxZhRE0po/H37XanJqClPhY5nN4IOE1Ms8EM6KzaQIWoaeQ94tJplj+dQpY3CYjx6hpTyGhWZnLY/DvjL1GJkNhhmL0x7DUFOxos2LWrNrnwGI5MW0rK/PuKxITJSc8ok+liFZGx7un5pdWMRMt67SzpXUo22HvF5smMPmVv/eszBOFULeflXnMpO/as03aZtXbe1VReNDlD+euYxuK/zAxH92pikJsArDPZ9TtsyYHixRmJm0MJ2CRz6wxwYgJfo4zmSMjEyyKOgUsZY49q9gw6Tu6WjrGyAQDkhzmQ8HXqLZRY1Oo35jqs5qJIAD1odMQgA0bNth5551nH//4x2333Xe3ww8/3MaN42Nij5deesnOOecc6969u+22225WKpVs4cKF8voHHnjAvvCFL9huu+1mn/rUp+ySSy6xzZvrWwfe7IcWCyaWMsOKHNYdQ0Oh0qKmADdusqQT9qU9k3SFMLmDERNMCmF6YqbbZ5sTUYfO/ARstwLbRosf0Ey2w2QVzFCMv2um0U5FSnwse79SXiPzTDAjOpsmnDE4/xrZlINNTJjRMQUsbjOFHDMSis+gKibQH8NeI5OhMEMxLrZiqSkotWObe82qfQ4sSpfJnKhvB/7+lZzQd76VNGHwlHxkJYtDZZ12trQOM/LZ+8WmCSwa8jDQ2jMDNsqX1Fm+a88mQmbV23uzMi8KP3fp2Nw1TMuN0Z1qmoBNE9a1x63irMnBdrAwHxoaZFMbEy8sqSYAKI9lMkc2FWZ+ghSwlDlm+MaGCZOOMTLBvDvoAexDfCj4GtU2apxWM2LSTAQBqA+dhgCcfvrp1q1bN+vRo4cN/H/sfXl4FeX9/QDRIFh3ES30KouKYLEqKliLUkFQxFal1a9aq1Z/olWrghcQRUGWgAKCyCZiQVSKCyBL2GUn7MgSZA9hMawhQBZI7vn9cfPOfecz5yaTm2RGb+Y8zzyPDjeTuZN3Zj7L+ZwzYgSaNm2KhIQELFpUNPVhzJgxqFy5Mho1aoQbbrihyARg+vTpqFSpEu666y6MHDkSL730EipXroznn38+pnN2e9HKqh3jj7Igh6nMSN4uSyacQgYmbDCMvbSZdreuFR4I8sREOm4yYxumRMM0siUPnVmnM28F5kYrq1As2GO0CjZQLINjNmzrFE7kY9mcw7dr7L4JUrmHzUywQXTWTZAKOazLwTombNDRCdjgLkuOZdDuZA1GCybkfEwbksgxGgobKJbGVoznLKl20YYcpXkfU9KSw/aBoLO5nWh0whu1wDcaz3nkAuvAKqugs0o7o9FJ3j5TmZlOChOMfnVTT2sCwAawJW8/EOQJ2O/fiVTtWUcIsLv3BoJ8HqLR29YEgHG5B822JgDRugnyGcCq9tLYihU5WEDLhrTlgKzTwgRLTCRlkvnHsK4w62g5AROZYMPj8nnJpHvZnAOjvsl3FaOhsevF1o18JzBPETfhJwCxIS4SgJSUFBiGgf79+5v7cnJyULduXTRt2rTInz1y5AiyssI3cf/+/YtMAK677jo0btzYUvF/8803UalSJaSmlrwF5vailVU7NoDFghymMiMdd6MNozmBDEyY/CV7abMXjFTuYImJpEywgUKmRMM0siUP/ZZe9m4Co7QwV2FZhWLBHqNVMH68DI7ZsK1TOJGPZXMOzHFXVqFY4Miq9qybIBVyWJLDOiZs0NEJWEWbJsciaGcdLaeyttLYjn1HNh+TdtieAEhjK6aaIgNaNpcA2GcTWOeL0ZwY/UKeV7Ruok5XiRaESroKC6BZpZ3R6CRth/lfTF1vTwAY/Upy7Zmi0Ner7AnAzySZaKRV7aPN9owV5l2BIB8yve6tGZbPsMHQAbN+sh2LQT4zWdVe8vbvG2x/xrGAlrmdSx46K0ywQg5T7pKGe2wQnQXHTJ7UCRg1iXl3yA4z6xwxahIb3pfvKnYs9hxnyYRMTBilzU34CUBsiIsEoFOnTqhSpQqOH7fejL1794ZhGNizx5nzZ1EJwKZNm2AYBoYOHWrZv2/fPhiGgZ49e5b4vN1etFKdhA1gMU3xean29rgMTFgy4RQyAGCDbeylzV4w0nCHJSYy+GLW6Yy2w6gj8sVxM5knYJQW5iosq1As2GOmT4wfL4NjNqTpFLIzwSgaTLmHOe7KJIcFjqxqz7oJUiGHJTmsYxKrZjWraDPqiBxqZR0tp7K2cj6GfUc2H8OGEyU9jvGcZactGsVBmvexzhczyXJC22MJE2CnqzCagwxWGRXqm9X2QJupTEnaDhsMZYUJ1jWRXHumKDRh5R7bsdj5N9Sq9tFme8YI865AkA+ZXtvNmgD0T7YnAFK6M9q1l89MVrWX+vGMmsgCWuZ2Lgdk2bA9K+Sw94bsmLJBdBYcs4TWCRg1ic3byKp9t+/snSNGTWJ0IkkLZV0o9hxnyYQs5LxNjuUm/AQgNsRFAnD33XejQYMGtv1z5syBYRiYMmWKo+MUlQB8/vnnMAwDKSn29nStWrXw4IMPlvi83V60MmBiA2RMU3zOZnt1TAYmLJlwChkAMKlD1h5nCixSuYMlJjL4YooijLbDqCPSqfWmnvZuAqO0MFdhmUwwaUWWoDF+vEz22LCtU8gqFKNoMOWeCSvs31EmOSxwZFV71k2QVWiW5LCOCTPAcQJ2b7DkWA61so4WGx5lwYT0tWhB/o6sCs3MjqSxFeM5y4A2WoVTavezQXpGc2K0PXleLGECrIFvIMgDWqkywzohUiEnEORdNEnbYQkTK0wwaUiZvDBFoa9W2Hn7jMrVQKvaR6P2SfOuQJAHcle/Od3yGTbMKaU7A0FeFZaSu2w+RurHs/Nn1XHWaZOzSWzYngW0LDGRHVPW5WRiDiyhdQLWTThM5j2kmANLHNmxmHqXpAAzGWD23mPDyTIxYR0tN+EnALEhLhKAhg0bokWLFrb9qmo/fPhwR8cpKgFQ/8a6CU2aNMFtt91W5LEzMjKwceNGyzZp0iRXF61UJ2EDZKxqx0yY5OBeNDUKJ5ABAFOGYO1x9iDXtcIDQZ6YSM40cztk8pHM7lw+VNk8AaO0MFdhmUzcTQJaJh/J+PEy2WPDtk4hg3ZG0WB6+18S4zT5QmOUKVa1Z90EWYVmSjSMtjNodmwJANPbZ8mxvDfYGmTDo2w4UfLj2d9xCqlCM719SY9jPOfv1lgDWqbkAthngFjiKyVFA0FO22sh9PajdRNltZoFJpJjzgarWaWdyfLeKGg7LGFihQmWdEiuPVMU+oIM7rJkQg/ao1H75CxEtOtVr+s0y2fYMGdfkVQFglORd8aeAMhOJ5uPkfrx7BnHuPaMhvofwUNnw/YsoGV0IlkwYV1O1hVmCa0TsG4Co6vJd0Lwa/u6YfNXzD9CUoBZEsreeyyZkM9xJinsJvwEIDbERQJQp04dtGnTxrZ/x44dMAwDAwcOdHScohKAHj16wDAMZGTYK3533HEHGjduXOSxu3fvDsMw6ObWopXqJEyBgVXtWHtcBibR1CicQAYmTM/9f+SlzSpMcnCPJSay+srcDlnVfuh8O3VEPlRvIHQiRmlhrsI2aUVS7WW8asaPl9VxNmzrFPJhz+Yq2Itj/PLikxxGmWJVe9ZNkFVo9h0ZbeeDGE1rmHIPS47lUDtbg0zVigUTkh7HfCZYFZrp7Ut6HOM5y0SbGZ0B9hkgtu4ZzYnRL+4U5xWtm1hfVKtZYCKlIdlcBau0syRa0nZYwsQKE0zOtYHg2jNFoXHL7IO7jMpVv2vkOrCOEAAM/2G77Vin8uzXq04XawLAlGGkdGcgyJMJWehg0qqdv7EmAOwZxyrazOxQUhNZYYLNX7HERBZMWJeTFTmi3R/FgXUm2LyHfCewdcNoToxOJAf3O020H4u991gyIZ/jLKF1E34CEBviIgHwOwDOIKU7mYgV/NYAACAASURBVAIDG05k7XFpuMWSCaeQjptM2ULqWkd7kN8mDHdYYiKHJpmkIKvaM+64rBz9/h17IMQoLcxVWPL2WbWXdWjYQLFM9tiwrVNI7iir0DK9fWacJlvtrHLMqvasmyCr0MyDgdF2YjWtYXr7LDmWQ+1sDTJVKxZMSHocm5lgVejUA3bqjqTHsaFJmWizailgnwFi6565dzPantTbj9ZNrCuCVRaYyMFQpjokvQICQZ5ES9oOS5hYYYJ1Ha7pZk1emKLQf8ngLqNy6deBdb0AYOj8bbZjMZWZKztbP8PUXKR0ZyDIOeay0MGC9uDX1r8Pe8ax6jjrtMl5IlaYYPNXjE4ku+MsmWBFDraenYBRJtm8h3wnMOUu1plgXhSyKMTWICtWsWRCJibsWG7CTwBiQ1wkAP4MgDPIgIkpMDBJQTZkKg23WDLhFLICeD85FtO1ZhUmObjHEhM5NFmfOFsyQzTGHZeVo0ZknoBJq7LgWFZoWEWbub6ygWIpRckCR6eQA3KsQ8MSpv8S4zSZMDEFJla1Z90EWYVm35HRdmI1rWF6+yw5lvcGW4Osas+CCUmPYzMTjNPOuPsy0GY8Z1kdZ8ESYDcVYzQ6pk7EEgqpt8/WF2APVpnEp+SFM442q7SzJFrSdthgKCtMsO6L7F4wBaZPyeAuo3Lp1yFaZ09q9weC9oQpFArZPsNkJnsIWlUgyLsv0kOGSatKU0HW0WLVcdZpk6o2TPCBVbTZ4L7sJrJBdHasaAlycWCdCUb3ku8XNojOOhMHs+zzBJIyydYg8wFiswkyMWHHchN+AhAb4iIB6NixI1UB6tWrV5mpAKkFFk0FqEePHiU+b7cXrQyYmMwkG05kQ6ayMhlNjs4JZGDCEhNWtWMVJt0lMxDkiYmUOmTGNuxByLjjsnLEHEqZtCoLjmWFhlW0WRWa0WPk37opCRydIla9feabIL8jU2BiVftxJGGSVehbe9m/I6PtMAdMJ2AVbcYdl/cGW4OSax8tmJD0ODZsyzjtbKBY0uPY0KTkobNgCbAPJzcgNDqmkc+6dk1F1451AFmwyoIcqU7CuipMIpMl0VIikyVMjLfPaEeSa/8yCeRGLbTz9n8SyYS8DuwZAdi1+wNBeyW3oMB+TZk0pJTuDAS5wZqk7rGgXSZo3DjRHtAyrxNJQ2GdyR/T7UE7S0xkwYQNorMiB1vPTsA6pmx2RD4v/00G0VmXg9GJJAOADbUz+iW7z2Riwo7lJvwEIDbERQKwfPlymw9Abm4u6tWrh1tvvdXcl5aWVqRef3E+ANdeey0aN26M/PxI+7Nbt26oVKkSNm8uuROe24tWqpMwBQYmKcj4sbIyGU2OzglkYMISE1a1Y23hGwRvlyUmUjWFuR2yByEzyZFUGxYIMUrLGBIcywoNezkyihabJ5B/axYcO4Ws2rPBPUZzYrKp8jsyBSZWtR9LEiZZhWbzBCxhYjxnJ2CDu1Mc3BtsDTLuOAsmJG+fuVaz7hgbKJb0ODY0Ke8zpnIE2GlOV5MuGlMnYh2FW3rNLvZ65ZNglQU5cl5lGREKkG7BgSBPoiVthw2GMsMtJud6lehesECO8fYllUsG7dE6ex8Q7X5ZyT2TX2D7DJOGlNKdgSDXrJfPORa0SwMpVphg1fHppAstCxNMPY51cpnngyyYsGSCFTmidciKA0sm2OyIfL+88Ll9EJ0da3+mnU4k/UleIEPt7F3F7jNZ+GLHchN+AhAb4iIBAID27dsjISEBnTp1wogRI9CsWTMkJCRgwYJIkNu8eXMYhvUrZ2ZmomfPnujZsydat24NwzDw+uuvo2fPnhgyZIjls99//z0qVaqEFi1aYOTIkXj55ZdRuXJlPPvsszGds9uLVgZMTGaSvbSZa62sTDI9Z6eQgQlLTFjVbibhX+sumYEgT0yYaop0O2R6+8wkR1ZV2DwBo7SMJqZisg3N6B5ssJJVx+XfmlWOncLJQDFT7mGyqfI7MuoIq9p/tmSX7XOyCs0UmFjCFKtrJRvcZdxxeW+wNci444zS9ifB22eUKdYdY26nkh7HeM6Sh86CJcA+nFy/q33dM4181lGQcpvseuWdsQerTG9fDuUv2mpPqkYTiUw2YyJpOyxhGksKE6z7Ij/DAibG25dULhm0R0vsmXSnVJnJPZNv+wyTc5TSnYEg54VLhTIWtEsDKaYCxqrjrNMmCxNMPY51ctncjuwmskF0dqxoHbLiwJIJNjsiOxNsDoUdi8nHSn+S58fZj8VU5thsgnyOs2O5CT8BiA1xkwDk5OSgY8eOqFmzJhITE9GkSRMkJ1uDC5YA7Nq1K6o6TyAQsP2e7777DjfccAMSExNRq1YtdOvWDadP26shTuD2opUBE6vkspc248fKwd1oetROIAMTlpiwATnGv5a8XZaYsO8oda1Z0M5McuRcBZsnYJQWVh2Xx2IvR0ZDYXQiqUTDKsdOIatQLDFhHRPmuCu/I1NgYkpULGGSSlROlWgYz9kJ2OAuS45l1Z6tQcYdZ5Q2KWvLhm1ZEMrkNqWsJRualAZSLMkG7DSnOoRGx+YcGP1Cnhe7Xjmn7cGqE8oEu6aMasOG8iVtx0nCFAjauy+MvsQUhRhvXyYTMmhnXS/A7ocQCNodik/lnbF9hunMS+nOQJDzwmXnjlFHpacIey6xijbrQsu/NZsdYfNX7L0hCyZsEJ0di61nJ2DJBJsdkVV7NrjPii/s3pDePWymhYlMsNkEmZiw83ITfgIQG+ImAfg1wu1FKwMmJiHHuMmMHysVRaLpUTuBDABYYsKcLVlVSMrtscSEBSZS1o4F7Wx4VLaOWSWUUVpGLrAnALJCw16ObLCSce2lShOrjjuFfNizY7GOCVNNkt/x2m72BIDpx7OESX5HRidiMy2M5+wEbN2w5FjeGyyhZdxxVm2X9DjWMWFB6AoityllLZlBmTSQYsESYKc5BYJ2Gh1z3GUJhTwvdr1O5tqDVUaZkAkm46GPWGCn2rChfCmRyRIm1k2Q3RdGX2KVXMbblz4MMhFiKloAl+6UVeGsnNO2zzCdeSndGQhyzXopUMCCdjm4y54lrKLNOm2STshmR9hzib03ZHGMKXexWS62vpyAHYspd8nOBHM7Zsdi8rHyO7KZFlZ8YcmEfO+x83ITfgIQG/wEwEO4vWhlwMQk2Bg3mbnWysFdFrQ7hQwAWGLCXrTsBSN5uywxYUmO1MhmlRA2PCof0FeReQJGaRlOTMVkFYq9HNmMBguOZYWWVcedQgbtLAhlHZMPiWqSrEIx7jir2jM6kfyObACbDaIynrMTMLlNZlAm7w3mUMy444yaIOlxbMaEqcewgWLZHWtPeM7SQIopgAF2865AcCoKCqw0OqeOu42E3CZ7lhwnweq2DHvFVK4vRkP5eL49AWAUM/kZpjLDugmrhZ8Doy+x6ivj7UtvCFm1j3ZfvzfVrtwjA7ljp/Jsn2Ha8FK6MxDkvHCZuLPumBzcZSIAbJ6IJdqSfslmR5hzOpvbkTMtLJlgx2L3rBOw5yVT7pLvBOZPwI7F6ESyAMhEABhlkiXacsaMnZeb8BOA2OAnAB7C7UUrAybG5WbcZOZaK6X7ohnSOIEMAJi2NXvRsqqQbpITCPLgi1UmpaoFk9vsTYZHZcARCNrnCVhVhdFjJG2HvdwZD50Fx7JCy6gjTiG/o1OaExuallUo1jFhNCdmwtZqgHU9s+CYzXt0JTQHJ2ABLRselVV7ZnbEZlpYsCrpcSxhklX7QJAPFMvuGKM5yEFUFiwBduneQNBOo2M0J1Z9lWo77FmSecqeADC1HRnIsSIBo9rILhqj7bCEaRgZ3JXKQ4y+xKqv/ZLttB1J5ZKJEOt6AcC7U+wJgAzkDp/ItX3mdWI0JaU7A0E+fyET969J51gO7jqVTWZdaFmFZrMjjNPO3htSupdJUTMTRnbPOgHrCrPZEfm8ZDQ0dixGJ5JzO0+QmRYmA86kaKXbOTsvN+EnALHBTwA8hNuLVgZMTEGCuWQylRlbkBPFkMYJZADQnCQmzNqeVYVk254FX6zLkXnKmgAwGsp7U+3ccfmAZoEQOxajx8gHNHu5Mx46SyZkhZa9aJ2CfUeZ5LCXEDPckgEak2BlNKchc+3dhLvFsC0LjhltJ1bbehbQsuFRKWvJEm2mRMM405IexxImdm/8QAaK5VAroznIQVQWLAH22YRAcCpyz1hpdEydyEnXjnUmj5y0V6uZyZdMfNkzYuBse6VddtEYbYepzHw0zz64K/0csvPsCQCrmPaZbk8ApHPyUXEdWNcL4Mo9smOSkZVj+8yrRM9dSncGgpwWIul2rDsmvU7Y+TPaDutCyyo0mx1hzyW2JmRxjElRs6IQu2edgBWFmGeFfF4yGho7L5Ycy+/IjsWevVKKFrAXq9ix3ISfAMQGPwHwEG4vWhkwMQUJpijCBuSkdB8L2p1CBgDMHIZJ5LEXjDQLYsEE63JI50Rm+sTUYyStigVC7FgsoJUJGqPasAFmlkzICm20QMEJ2HfMO2NNchjNic1MyEobo0wxmtPA2fZugkxy6nW1JxMs2YvVtp7x9plB2a29rAkAS7QZpY0F21LVig3bsnuDyXdKJ11Gc5DV8W/X2IMlwJ7kBIJ2d1hGc2K0EJmYsITpYJa9Wi358YB93bMOzfsz7Qo5cibnNJHIZAkT4+1L6VE2v8Aqpsxxd7k4lrwOrOsFAN2+syv3yKBwf2a27TPMaEpKdwaCnBYi71vWOZbykWwGiFFtWKItq9CM7unUOFG+G1kywegx0RLk4sDeCZLuBdifl2xuh50XoxPJ5Jgdi1Em2WyCfCcw2VQ34ScAscFPADyE24tWBkxsyJQpijANdmm4xYJ2p5C0HWZuw3i78gXD2vYsmGCVXGl2wmgoTD1GBu2BoH2egLVVGT9eykcyhRxW0WbHkvKR0QIFJ5CVo0DQTpliFa3e0+2UKXa9JJgULZNglcEeSybY37ojoTk4AfOiYBKskrbDEm1GaWPBdkPB22fXi8lHsoFi+RlGc/hwjjWgZTQO9h0Dwak4Idxh2bOEBV8yMfljkv3+//m4vVrNAibZmWTFi75EIWeYmMlhtB2WMDHe/hJBv2LzC2yegDnuylkOGbSzrhfAlXtkUJh+9JTtM8zQ6RUh3RkI8vkLed+y5FjKRzqlE7JjSU476/ayQJslhfLdyMQj2DshWoJcHJg4gez2APZnL+tCsfNidCL5HZnUKaNMsk6bk/NyE34CEBv8BMBDuL1opTwh45gzagIbkJOVyWiGNE4gTXLYsVirXb4UmLENCyYYzUkOtbFWKFOPYcOQx0VwzB72rKItA1pWHWODqIxrL2c0mD+BUzDFF6kDzmhOzHBLJjmBoJ1OxJIc1k2QSU4gaA+O9aq9CjRfnRCbbT1T23GSHLNEmynRsOBYdscCQfuwLbs3pAkTc31lnOkBIqBl1AvATk1i655dLxZ8ya4du//3HbNXq1nAdLNITNizS1Xa9d8rZ0wYbYclTIy3L70H2PwCC74YbUcmE3uOWIN21vUCgM7f2Ad3ZVC4+/BJ22deJP4E0l05EORVYdmdZMmxlLVk50+NAMmxJGWSFaHYs5d1E+Szl3UTWHU8WoJcHNix2OC+7EywLhTrmLLumHxeMt8E9uxlpoLyOc7Oy034CUBs8BMAD+H2opUPAMYLZ9QEJjMpK5OxOs2yqj3TmWeDe/KlwNQ2WDDBqBzS7IQ9oN8m6jFS8jEQtAfHzEH2AxK0S/UYVh1jlBbGtZcUDcYddwrp+RAI2jsmTLmnB6FMsWPli4CWfUfWTWA8dBkc61Xoa7uFZ03+Q3jOTsDUdpij8x9EcMwSbTY8yigTsjoeCE7FaTFjIqv2gaBdvYfdG4zm8IGgx7BzAuwFALbu2fWS80RO738Z+AaC3OVXnhdTyFIDsjr1SFLyGG2HJUxMblMaurFhWxYwMdqOdJrddeik5d8ZJQwAOk208/alPOmOgydsn2H+BC8I7f5AkFeYpboa8yeRvH3WtWO0HXYsJzNtTDSBdYXks5cNorPqeLQEuTiwYzFXYfm8ZF0o1jFl3TH5TniAHIsJZDBTQfneY+flJvwEIDb4CYCHcHvRyoCJ0UIYNeETYsJ0teDtRtOjLg5s2I4ZYLEgR1b3WNueWc2zOQdpdsIeqt2+sycAstIeCE7FIWGSw5IJFrRL+gKrjrH5BVYdlzMabNjWKViSI63mWRuadUzYsWRAyzo0bP5CXi92LN0/4vpCtSlGc3ACdm8wgzIZhLJE20lHSw+OdVMq6VnBhlrlsC27N5jevqxoM+oFEBnc1+l70hyKqRPJqjC7/5lrNatWy+o4YFc6ktQeIFJp12VRJY2OaeSzhInJbUrzMUZfake6CV0IbUcOc2/LsAftDGxwVyoKbf05y/YZ5k8gtfsDQT6wKhN3VjiSvP1A0N4BZN1ElmjLKjRbN2xminXt5HOczbQx+WjWTXACdiw2tyM7E0zqlFXtpRIVYO+OsY4We79IWVvA/uxl5+Um/AQgNvgJgIdwe9HKm5ZVmBk1gVXRZGUyVplJVplk+vcsyJHBF6vasc4E43LvPmwdamMvDiYfKXXaA0E7nYglE/2Siw/aWXWPcdpZdfymntZjsUqbU7BKu0yYGGWK6e2zY8mAlv193pliv0fYtZfH0oNQRc1hNAcncHpvyCCUUbmcdLT04FhXypIzJrJqHwjah21PkHuD6e33FoOojMYBRAoAeidQmkMxdSKZtLP7n1GmdorKdyBor7QD9ucSG7Z/87twoK13aiSNjtF2WML0zpSNts9Jd1jWvWhDkgmmty+TidQDx22fkV0vAPgPGdyV5nDsWMyf4JnPVtg+x5ym5bOJ3RtS1YadP+smsiKUpLSy9waraDNamKyOs24CkwFm3QQnYMdiJnmyM8HWDfuOTowAWUeLFV8Y1U4KHbDk2E34CUBs8BMAD+H2opUPORZgsmFbqTPP2vbFqcwM+2E72g5eZOOOssokk79kw3byBcOG7VhViGmw7xDGKU7lI1VVRZcflRrZrN3bl1TtZdAeCNqDdiatyORJJQ2FHcsp1LrRq9BSBYTxUFnCxKr2Uj2GuT6zZEImTOxYetCuvgejOTgBuzeYo7Mcamf0K6YeIwOT3DORe+MG7eUth237J9sTADlPkJltvzfY0KTUj2fUCyASaOvnJRNfpk4kk3Z2/7NAjlW+ZcWUzTmw+RjFj2/y3mxzDkAOmUu5zUCQJ0xvTbLTdqQ7LEteWDLB9PbnbLYea8PeTNtnpOwwALxEePuSY86O9cxn9gTgCSHdGQjapU4BO7WSmR0yQQHZtXNqdigprey9wQomrGsnA1r23mDBMesmOAE7FjPdk+9sNpzMqvZsnkDSdtmxmHKXVKIC7HNObD27CT8BiA1+AuAh3F608iEXCNrbr4yaINvobNg2mhoFYH0xy4cOq9ozalISUe6QLxhWtWPVRDacKFUtWFUl+LVdPlIF2nrVV1bHWTLBqvY3vGvnVcvqGHtAM3UiWe1hf2unUIG2XoWWRjOMa9v5G/v1YmvwpAhodaqNCqZZMiFb2oGgPTjWFXJUwMBoDk7A7g0W5MihVtZ9kcO2LDDR7w1ddScz2zpsy1Rt5LAtC2iZRK7koTPqhV4A0P+eco6GqRPJQI7d/8wd9idCV5EurCyZ6J9sp9qpQLtp7zlm4i47coy3zxImprYjz4tRbRjH/NUJ9qq9TCbWEZdcKTsMAC8S3r40h1ufbj/WU2PsBmVSuScQnIol2+30K9m5c+LdEQjau3as+8ruM0nbYe8NRvdkyYR8lrC5HfbsZd0EJ2BdTiYpKgNtloSyohDrjknaLht0ZsUx9reWNEdmuOkm/AQgNvgJgIdwe9GygElWjxjXXipk6C9a9QKNNowGAIfEy1SHXplUDyjGfe9ZKJF3VRHKHcwsiFUTWYVZamSzFm2niXb5SMUr14N3WR1nyj1MIUcdq6iXOzt3xrWX7sqBoH3Y1ilUZ0LvKmzeb+3kMIMydr3YGpSSovqArPoeLPliSjQyONapNooz/C9Cc3ACJ/eGTtvRu0IykWNa9DIw0e8NnTp1VHhWsEFUOWzLdPSZaoqkobBqqV4A0CkKMvF1kjCxrh2bmdi8305XkSZMjLfPEm2la//HpLlmgtlnujUBYNeLJUyMtjNjg7WSu2lf5NzVM45xzJncpkwmmEuu7HoBQIfP7bx9GRSuTrMfixmUPfRx2HFXH5qWSkeAvbDChA6YCIA8f1Z8YU7gkgLIKK2s2MOc0+WzhHW0mUIeuz+cgB2LKQrJdwJLQlkyITtHgF1tjyWh7P3CXMWleWdpjEDLAn4CEBv8BMBDuL1oWcAkqy+sMikrOTqfWH8QsApz7pl8S6tZzgrolUm9qiCPpVrt+u+TBlj6S1tVYVk1kamTSI1s1jp+nejHq8q/XgmV3QSmasOGWuVDNRC0B8c6pUUFL2w4mR1LttqdQiU3ejtaSsOxLsdrE+zXq6RBu0o+mHY/65jI4FifHVGmOs98Zq9yOgG7N+Qa1JNj/W8grz2Tj5TBsZ7Q6nKzcsicDaLKeQI2iMr8NmQVmlVL9e+oD2LKORonCZPetVO0IjYzwegq0tGVVe2ZEpWixzTvN88MyHuLhJyZZLGE6XVC25m63poA6JV29Yxj155V7acLWkjKTrtLrux6AcBzY1faPicpUyuJ4+4To+0JgHIC15/P87fYB1blc5XRHJl0rzx/Ro9hXifSi4J12piqHRsMlwUT1tFmQ+3s/nACdiymuCVlgFniyJIcuW7YsD1LaNl5sb+1E/M+N+EnALHBTwA8hNuLttHb9qqwfPiyyqR8+B47FQlM9BaldIddvuMwru02wxKoyZeo3h3QH+gyYFK8XT2AlOeVoQU5KjBnbWH2kJOydnpbVXHfmUumehDqLzY558A4moy2o4IRJVcZCNqVVfTgWFWHuhB6DNOPl8meU6jfoyv4SJk51jFhcpuMmiTlI/VAW80MvEqOpQISnXIjr5daz1d2nmoaB/2TVDmdgN0bg2ZHV4/R7w157RltRyYTGVmR9aw7gmYIrj2Tj5TUhL1ER58pZEnNd1Yt1Wk7+nnJzheb2xks7lk9yVHPJ9ZNZHQVqcByINOe5DDp3hc+DwfaLd6fbz4nZEKuS2SqyikL2tmwraRyrNodCbRVoYBJnbKqvUwmlhCNfOm/AADPfGZPAKQ53DLiuMscitXfWC9ysAqzVMlyqtwlCwDMQI6JJkh6TCBo77SxwX3mnC4DWpZMsGMxapITsGOxgfs6DkzynLiKM3ocS2jZ4D4bTpbdBHZvuAk/AYgNfgLgIdxetKpirD/sMk9ZH76qMqnf4NK0Sg/a9Qe6bOUySotsFepBu04nkEonqjKp/z454KdX7VTl+KrO9m4Ck3OUsnY631MFmow7rh7QulmWdE5k3QRG21GJhk61kXKbelCl6DSMHmP+rbWBVBYoOIEaHtN1t6XKhN6GVp9ncptqTRQVtOtrUCUdL5PkS1Xt9O8olWjU7Ei9rtPMSuY/SJXTCdSx6nSZZv6tZJVT72jpHGWZaCu1HV21RgbH+nrW5RPlmlCcdr3jIFVTdCUadf+z+Zj/N9YahH483x7g6NQk/by2ZVgH6dV31J838lmid+30AoCkJq4l3Hc5gMmGbVlyrL5jqwELzKRDJuQ6bUd9hiVMqpugD8hLbXg90FbrmV17VbXXg74pQs6VaeTLBBoAHv9kue3aSzoRSyYeHWl3KFZdHl2SUh4LsAe1LPliyl3y/FlAy5IJ1gGURSg2hyLvM32mRX8uScokOxa7P5yAHUvO27CqPVMnYkH7/8QaZCpg7FjMn0RKCrNhe5bQugk/AYgNfgLgIdxctPpDTn9wyuCrz/RwkFO/6/SIQoYItPVKm05NkAGmfEgEgvZhIT3I0QfEZFVIVSbv6j/fPC+ppa9b2+vJhHwpsAem1DrWq1Aq6ZD8WP2a6rb00oWRDWmxl6P6XnqSs0tUVfW/j3qZMnqMCiL0ZEKqtDiF6ibcPyTyHeVgmJ5UqUDuBSK3qZIDvctxINN6XorTXv/N6SZnmB3rOq3LE/VYhUHoNd2m4y+FJkSsyukE5nl1nW4GhVKeVK/a6/QYmWgr2o5+HWRwrAftuoNq+lEr117dG3oALdWJ9OBYrYlGhOcsJR9ZtVSv2uvn9ZMYDFedCf15I9V2dGqS3kWTBQDGfZf0C0YTYnMoqjreZtBCMyGVCbnOj1dD8ExSWHUT9M6WTEwWbY0E2koFhw2ZqvPShzVlJXdeql0jXz7DgQhvX6+SS1qInkyoROHhYXZ3WPV30bs9TLFGqmSx5IvNAMnz19Wj1LOH0RxZgUkWoRgNTb7P9Oq4TgWSXbvB5Fjs/nACdix5z7KqPfPIYUG7lCdlIgAsaGdzOzKZ0NXJ1MZUk9yEnwDEBj8B8BBuLlr9YaIHmJJO0EsLmFQQWVSgfe+HkZfCEcG/lg+JQNAuF6YfSw+iJc9ZVcdaDVhgVk2lAZYeMOlyczIxYfKEUutYH9JSicnfhi+1fEYfhnyw8IUbCNqTCaZEIV9oelVFT4RkUKVkGhu+nRyhx0yw02PUz+vDo5Ki4RSqwv7wsMh3lK6VOjVJVQqfH2fvmKiAVw9MJHe8R+HA93VvzTA7K06PJRMm/Vjqb/R/o+xVTidQQfs13aabgYxUOtKpNrrmuQxy9L+j6rZJxRo9aH9s1HLzv+Ww7b/+u9Jy3QNBe2VSl9FUnQlmDiclH2W1FLB27fTzktQ3xY9v1mduVLUdvQCg37OyKryC8NXld1y63U5pYdSxf34a/o73D1lkJidSZlavjqvrejMJctRzSX+mykBON7Z6oLBjwgadnxoTTr50qqacc2CGe9KVGwDaFAbrOm1PdhP081JJ4X2D7XruavZHd/GVVWHAHjyywgSTJ5ZdOzYDxBI59VzSu2jyOlYS7wAAIABJREFUWa97ZESje+kdLb1DIeev2AwQm01wAnYsOR/DBuSZ1CkL2qUJm16YUBsL2pk8sZwnYspdsRqBlhX8BCA2+AmAh3Bz0eoPE52uIqX79IApGs1Bt6N/SAt8ZTIhHxLqJa8j7XAkaNcDTFnJVS/ttoMXmdUqqfChn5cekMsXDKuYSK1jfaBN0Ryke6eeVD06MiKVVxQ9Rm1S1vK0lky00yrtcjZBNzFSwb2cTdA7E3rVTlKTnEIFb3qwJwcKlRb9VZ0jgRwzFVJ/O71DIxWY3i4c+L6+e7J5LKbcoyqleuArr5dyfb2+e7JZrf77iKW2YzmBfm+o85dzDrpjrb6eZfdFP6/GUYLQbRkR+UgVHAaC9iRHBe16Mi4rk1sORI6lB9qSaiMlH+WMAwDs05Ic/bzk+nphfIRrr4I1ec/qBYAHNDqRvF6Mry7PbTYJjl/4PNI5OnoyDwUFIZMe85ehi82ZInk/zk2NHEtdVxbkqKq9/kyVSdNMzSTv7yPCa5DNJqnz0oftJS+cuYqzzp4K/PWiiuwm6IZb6lnClGFUEK4/475dY1eskdV2NjOl6JQ6bU+ev05zVN9D0gn1Z6/e+ZJFKEXbq9tlmvk5SZnUg2O9+CIFBdQzTqdoMZ8JJ2DeHTKZ0Km2qtvBKK0saJezO/o9qxImtp5Vh1nfbOpkRG6bdbTchJ8AxAY/AfAQbi5anWurv2hlNVHxiW/pNTvqy1GvJupBoTTA0nmxapNOhvqwnXoBsvNSv+fBj5eYlV9pgLXd4bEY/3LJtuiUFvXik7rJeiVEJSiB4FQsE8mErq2sqr3SVEx/oakgIRC0O252mhj++9zaa475cvy3eDnqnQmdosEcHYuDnkw8rQV7Up9cBccN3pphVh+Z2o56+ehBqKRMdSnUVr+xxyyziv600CcPhULmsfSESSZyOg3lb8PD16L98JIlAGqwUAXtjbonmwGfnAvR7w19Dcp7Q/0db35vdtS/o+7UqnPztwvTuvbqe2l/axkc65x2PTn+YOYWTFi5xwwq9IQ+EORSjnqnTT8vqQylkoP7Bi+Mes/qBQA9+ZD3LOOrq26CksrVlajU71PrRt3zwa/Xm/fzw8OWaJ0c6/2o+1qo68qCHL2bEK3LoR9LfZ5JVqp1rCeOsirMtOhlEQeIKOTo11TvJuw7lm15Lqn7kfHCVdCu3/+SFgLYq9p68qWgKIC6KZW8N9SAfP2u083zem6stQCgv8/0Z4ks9ugdbeUcLJ3A9fX8F63LIQtaigJ49ZvTo9JQnUKnE+r3og69O6a7Hst5IuYELpX79MKE6jCxLpRS22tQhNqerral3md6Z2JbRpZNJKK84ScAscFPADyEm4tWr7TplRxJC1Ev7TaDFpocZp1+EQqFLJrvOmc47XDkpc0qdioY0KFXOXXlCunMq1dvG0YZ3NPP67UJEXk+aVrFWqaK0hIKhZB2+JSlDa0oFlKBQa+E6IGQ0k0OhUI4cjLPoq2sHvgvjF+NEQu2Y/gP27H94ImoyYTk2iut8D8mzY3w48WLVudo6hVaZg6jY92eY2g7eBH+/cUa80WqD6LpKiXTf9xvqUR11YJ2qbZz9GQeZmzYj4NZueaLU3/RKlfRY6fysHn/cTM4vqXXbNvgbn5ByOyCmIGGJp8o1UmUetRNPWeb6/6hj+0852gY9sN21H9zOt6etMFMTBq/O9M8LzkXouvVq3Wj7rOsnNOYvG6fpSLcetBCs8P0l6GLsSbtKPrOSMWuQyctnHbd2XXrz1k4nnParJzq18gMJgoD94KCEFbuOmLpeulrQm1Kg1xPpqIFODo1ST+vtWKQXgWfDw9bYt6zV785Hf/670qs2n0E+QUhs9sjz2vD3kx8MHMLxi8PK/0s3Goffu01bTMmrkpH3S7T0Gd6qiU4VjSnR0cus9Ef1Ln8bfhSk99/Y49ZmLHhgDkvpEv3Pll4P0oJYyBStX/go8XmTIqUHtUTk+fHhe8hpXSkq9aoKvzLX64xiycvf7kGE1elm0kOk/dVMyE5p/OxeNshy3PpWW0N9vx+Ex4ZscyyT20q8WO+KSqZ0u8zqcAE2FWyiura6ZQp6SmiqHbXvTUj6n2mF470golMhhTVrtHbyeZzSR4rWtKuX9f8gpDpRXPdWzPMTuab3/1omzGTSDt8Cm0HL8JtveeYHUr1jLup52yzkCE77XrQrifmsjv+zpSNlnUdCNqTCd1dWZ/bk+eu3pt6F0o/1uq0oxZVKzUzUa/rNBQUhCzD+rF6JMQCPwGIDXGTAOTm5uKNN97A5ZdfjqpVq+KWW27BrFnOeGl79+5F+/btcf755+M3v/kN2rVrhx077Pq+hmHQrU+fPjGds5uLVn9g6oH29d2T8cL41Zj2434LVeWJ0Slm0P2XoYvx3Zq9GDR7q6U6JV8K2w+eQMrOI1SCTm33DFyAUCiEbRkncOhEruXBpB9ry4EspB0+hTGLd6LbdxvMl9ATo1PMdujjnyzHvmPZdKhXV5KQJj96cK+2EQu240x+gflgVtt1b80wg8hAMKzwMXX9fkvFT72o9ZfI4RO5tmqqfEjrm96VUYOFgWC4mjh+eRr2HDmFvDMFJue4xfvzzXb1nf3n48uUNHSfvBFvTdpg4erqAZp8KUjoL9JAMNz61Y+lJ1X69ux/V5oa5s36zDUD2idGp6CgIGShpqhNJibHTuXZZGqb9Zlr+f3TftxPgxc98Bg0eytSdh5B/+QtNs1x1UX669DFjl2R9Qqd2m7sMcusuitKWygUsiWWL31hN3aS2/+NWmYGmPr2p37zLGuio6Y332vaZvwxaS7qdpmGVbuPmupMz41daa7J/slbsD79mOUY+t9V7lPDn20GWf9Wcs5GOt/qOvhq9iXvTIGlYv/4J8ttA5sN3pphSVjUfcqu0ZYDWfiBqN+ojoz8/6s6T6X3ntz+MTrFEujox9GvkUp82dC0nlT+gXRMtxzIslSoddnQpr3noMX78zH8h+2WZ9g7Uzba/DJaD1qIzOzTVN437fAp5BeEzA6XvnUkPgVs04sOzfvNw6eLd2L5jsPIL4h02vS/tRx0Buxu7U9+moItB7KwbMdh2zNa/9t/t2YvZm36Ge2HL7WoFtXrOo3S9k7nF1iKWHphQnWOdh8+abkfG78709INmbnxACas2IMXxq+2eCbohZyUnUcwZd0+XP3mdJMGFQiGqTP6bEWjt5OpiZd6LkjzM10coN1Hi813QudvfsSGvZnYlnECS7cfNgUMAkFrIvfQx0uwfMdhjF+ehqfGrDCTKd3Y7p0pG81kSLpo6wWU96ZuwhsT12PxtkP4aN4289ndcsAPltmKP3/wg+X9rDZdGOLdKZts7syyW1le8BOA2BA3CcAjjzyChIQEdOzYESNGjEDTpk2RkJCARYsWFflzJ06cQP369VGjRg0kJSVhwIABqF27NmrVqoXDh610AsMw0LJlS4wbN86yxbro3Fy0emWSuVeyF4eUBGSbqrCUxSZfIGx75rOVtiBFbrf0mo35W6xqGXqnQ+eqMpqSvrUZtNCktxS1ObmmV3aeSmXw5PbGxOKP1XrQQgv9KtrWd0aqJVH5+4ilePWrtTaKBQDbw1vf6nSZRvnHcrvr/fmWKhoLsALBqZYZi7HLdluUUvRjOVk3zGhNbq0GLLBU5K/tNgP3DFyAR0cuw8PDlpiVZgl2rDuS5tmC1+K+Y7TtlS/XUE8Adc31a8Q+88ekuSbd4+Uv19AAUd+e+WwFNW27qnOYPiGTJj15ZoOEOo3kzv7zLUGD/h3Z8Ke+PflpClW4UZveNVGbfA6o6nj74UuLLEKobdTCHVSXXt9u6jnbTCyuI7x9VRD5+4il5lp/9au12Hssmyb7jH4ot8FztlrmWtimKyu99MUaap4VCE7FhBV7qPeG3HppwWZR10tXKJIdWOZIHW1jnhps058l0f5W+v2zfMdhs1Kvb60HLaQ+C3Jz8uyV5xUIhnn1jGKZnWdXzNG3F8avthVeivuO0bZ2QxbZ1pycD7j3w4WYscF+L8mNFQ7YVtx7jw3hlwf8BCA2xEUCkJKSAsMw0L9/f3NfTk4O6tati6ZNmxb5s0lJSTAMAytWRDjGqampqFKlCrp06WL5rGEYePHFF8vsvN1ctHpFfPqP+2krWd827M0s8oUcCIYrqtEeJvW7TrdRNYraunz7oy1oZ9vr/1tHjbzU9tqEdTiec9oWrOjW9bo7bHEP1vembsKq3Uep5rT+8F9MOMpyu757cpFBttqW7ThcbGLSasACOlwst5W7jtCgg8mQFhUozEvNsKi/RNte+mINVT2S21ZRlWpHXjjvTd1ke9GqTVXgG3VPRsbxHEtgwrYlhRWuaP/OHKOXbOd/06fGrKAqHrbfuf0Q1qQdjdr1uSNpHlbtPoITuWfw2oR1Ft6tvt31/nyEQiFLZ4htH83bZqk2y+3KzmFaAwumo229NIdcvYsYCIarghlZOTZTIH1r1mcuth88YTM00rfX/7cO+QUhyvNXm+w8FLX1/H6TzdAsEAybNqkg8tn/rkTumXybm6zcvkhJs/DIJdSMylNjVlgGgdl23+CFyDmdH/XvrLZN+47T81dbg7dmUPdXuQW/Xo/cM/k2aVe11dWG+4u6N9R2IDPH0lG4srNVdpM5Ukfb5qb+XOS6CQTDlW7mmK1vHf+3zvKeYgWHZn3mYsWuI1idVvRzPBAMd7F09S62df7mR0wg5o6N351pK6wcIfKb+vVftfuoZUaEbTf1nI2TuWeKvf//MTrF9rzU77vr3pqBnNP52HPkVLHX/oGPFltmiqJta/ccK7Kodf+QoguwZQU/AYgNcZEAdOrUCVWqVMHx41YuYe/evWEYBvbssQ8sKTRp0gRNmjSx7W/VqhXq1q1r2acSgOzsbOTkxKaprsPNRdtFe4FuP3gCuw6dxB+T5uKOpHm2yopOFWEuo1+kpOHoyTyEQiEcyMwxq443vDsTv39nJt787kfsOXKKmo+oreHbyXh+3Cq8O2UTtmWEOfq6HJu+PTxsiRkQL91+GKFQCDM3HkCT92aj9aCF+HpVOpZuP2xTk9CDcl0DW1eZCIVCFjrKi+NX43ghV3velgwLR3fnoZP4MiUNny7eiUVbD2Helgy8OH61yTv/elU6+idvMasn//5ijSWovr3vXIv6TSAYHtLbsDcTU9fvR/fJGzFhRXitrtp9FL2mbcbjnyxH43dn4rq3ZlgetP2SU5FfEMKwH7bjll6z0WniOvRLTkWf6amYsGIP/jZ8KbpP3mhSXWTQ9wfB9dWHavvOSMXqtKN487sf0S851eQfA+GX/I09ZmHg7J+QkZWDBT8dNAPcJu/Nxs5DJ3Ei94wl6FU8a/US2nPklGXwjm1/6DELx07lYcn2Q2jaew5u7zsX9w9ZhKvfnI7v1uxFKBRC+tFTpgSiMopTmwqyGr6dbFJTDmTmFBmkSeMfndal/92+XpWOUChEg40+01Nxz8AFuGfgAlNHPBQK4efjOTidX4DT+QU25R0dLDjX78d+yak0Oby22wzsz8y2VWGTZqTa9MwPZOaYfx/mDq5roeuSiRv3WXX21T3FhhDV31oNLOousmvSjlooFWp2aN+xbEtg8u2aSGeHnWe07X8r99iofMqxNTP7tEV2VnVpru+ejPXpxyyB9T9GpyAUCll8KSQUnaPD56vodVCds1mbfjZlJT+csxW/f2cmBs7+CZ8s2oknRqeg5/eb8M6UjSYf/mBWLtoV0gy/TEnDoNlb8ad+83Bn//mYtHavZd5J3+4ZGDY30zs36UdP4dUJazH8h+04lXfGpNzknsnHpLV7kXE8x1ZMaPH+fFzVOUJZVMPU2Xn5lnWvP3OjdYPbfbQY/ZO3YOO+TDz5aQpeGL8a+QUhjF60E79/ZyYe/HgJHh25DF+kpCG/IIRjp/Lw1Yo07D58EvkFIQsVRm3dJ280n0spO+0Sservp8+lAeGAfMFPBzE39WcM/2E7vluzF29+9yNe/986LN0e7vjnF4QsRaIXxq/G3NSf0eXbH9Fp4jqTWpOVcxqn8wss9Capv6+r73y1Ig17j2Vjyrp9NmrMN6vT8dSYFej4v3Xo8Pkqc17hzv7zLapyoVAIG/ZmYsKKPfhk0U4Lnah/8hYczMo16Zhy0+cjlmw7hFe+XIOh87fh61XpthjgP1+tRdrhU2ZhbvI6+3q7pddsnM4vwP7MbHT+5kfz/fSnfvPMROROYfxZXvATgNgQFwnA3XffjQYNGtj2z5kzB4ZhYMqUKfTnCgoKkJiYiA4dOtj+rVu3bjAMA1lZkQFSwzBQvXp1VKpUCYZhoEGDBhg/fnzM5+3motW5pwwLfjqIqzqHqyW6+sGZ/AJ8v34fVqcdxd5j2TaZRSA8vCmVCdTP6g8MqaLDcDL3jEW7Xg087T580qYyUhz0weevVkQoHqr9rOzeT+cXYE3aUZv5UFlA50i2GbTQwh0NBLlUZlFYuesIPl++G6eLCCKjYYr2EJeDcLoKUUnNbQ5m5WLmxgMW87bxy9PQrM9cU40m43gOJqzcYwZfx3NOR61Cbcs44Zijr3Ai9wz6TE9Fx/+tM+X7ck7n24JfhXlbMjBm8U4L91maz72lDahmnjqNY6fyLBW+PUdOoX/yFizZfgjr04+ZgX0oFCrx+SuwroOU9Ms9Ex5K1GlISpc953Q+kjcesEmFShw5mYd1e47hZO4Z28t92Y7D1OhMH/6TA+XDf9iOBz5ajOk/7seJ3DOYuCrdMhQ8ae1eXNk5opo0f0sG2g1ZZDOUGrN4Jx76eIkpKaqGZvVNSpXKbX36McvfLhCMDOZLhEIhLNtx2JSPDIVCmLByD5JmpJpeBLqUpITuxXE6vwBjl+4y9/3z05SozxQn6yMUClmSbx2satzkvdk4nnM6prV3+EQumvWZi/pvTreomJ3JL8Cmfcctw6L6etEFFnRp2+y8fAyes5U6BpcUoVAIC7cexLId4eKPvKeZAVxZUE8WbzuERVsPFXs9T+VFCl3Sm0JXppMyrGWBjKwcvPzlGvT4fpOlGyMpZMw/gGHxtkPoPnkjfX4s33EYWw5k4Ux+AZbtOGwbRgYiA9OdvwkXHN3yB/ATgNgQFwlAw4YN0aJFC9v+TZs2wTAMDB8+nP7coUOHYBgGevToYfu3oUOHwjAMbNkSqb41a9YMgwYNwuTJkzFs2DA0atQIhmHg448/LvYcMzIysHHjRss2adIk1xatknC790O70YvCwazcqC+cWKFzgkvSDtxx8AT2Z9rl7UoC3ftA1zJWbWX2Qi9r6InXc2NXWuTcAsEw/cFN/N+ocPD0oFDC0TWnP1uyy5VzmUi4+/W7To85eI4FOndaOuzqCkJugQUzsqqoIzsvv8iOglPkF4TwRUqameAr6UfdIVef01DKTSWB0uEvCdh8x/wtGXjh89WYsGIPPluyy8ahzs7Ltw0US2OxkkDnq8u1qYZ1pevtqbwz5bqOJfVy5a4jpf59J3PPUFdhCX0gW+e965K7bkL3f1GbNPsqT4RCIZNqI5V89Pt5ZhkkQ05xv1DzYvKu5QnVtbmadM3KA34CEBviIgGoU6cO2rRpY9u/Y8cOGIaBgQMH0p/bs2cPDMNAUlKS7d9Gjx4NwzCwdm30SkJeXh4aNWqECy64ANnZRQer3bt3j6oi5MaiVcNqj4yIzQU1VuizBiXVXy8tCgpCpuykTqPQdabLGxv2ZuKabtPRrM9cbP05y1RsURvj4pcnVEX17g+s3Rj9JToxiqJFeeBtUallXPzyhF5JlU62qpXuVhsb4MFMeVQOi4PiSuuO1brRVkm7cbFC0o4CwXCHSIfevQoEw109fQ5Fdfpiha4aJjtv0aQ/yxvSEZh5AZQX1qQdNX/v3NSI7K6imbrtCqt7AqgtVofeWKHulze/syaCRXXNyhOq0KO21oOiF/7KA4M1oY3iZFLLAn4CEBviIgFwqwPAMHz4cBiGUazakNcdAF0q0E3ocnZPjE4p/gfKGMwzQDd0cQOn8s6YVVpZmek9bXMxP122UCoXt/SyVrV1lShJyyhPSN60PK/yhq4vLx2cn9RMntwCG7SWpmtu4KaedklLnUKm5nbKG3oXT23SIwSIeHso/4MVuyKB12sTStdlG7Eg4qGgUx1DoZBJY+ufHJshVKzQXXzleZU3otFalCJMk/fcvYeZ0s6Yxe5p0AMwZ4ReFu7HetdMPl/KE1LBT8n8ugXd+0a6M5cH/AQgNsRFAuDWDADDtGnTYBgGJk+eXOLzdnPRqsEttykn+sBYSfnuZQE1bKi36JWqx7Xd7LJ+5Q3po1CcNn9ZQ3ez1RGtqlfe0A2qAsHwAJmbWLU78r3nb8mw/JvSkn90pHtdM93ESW3KpM5NRBxy15v7dOUTSZcqL+hGdGrTh3h16DMcoVAI3b7bgFe/WovjOafp553isyWRwWCdIpN3JjLjJJ1XyxvzhGJaSalVpYHuUKsbgimFoNt6z3HtXIBwp1euEeZUXJ5QXif/FLNVeqeGzc+VF1750qoi9fgny1373YCVWulGd8pPAGJDXCQAHTt2pCpAvXr1KlYF6Oabb6YqQC1btkSdOnWK/d1DhgyBYRhYurTk9BY3Fy1r6bsBnfP+0hdriv+BMoYaKNaHwnRHR7chtftLOnBbWij6U72u1vkH3bl5SZSByfLAGKGV72RQvCyhU0xmbLBydJXO/DOfrYjy02UPSWdxu3KooFR73pgYSQB0hRwnXPGygpQsZh4W5YkvU3gwo6uW6TNGbmCBMEZzE8dORaQtP9Uq7UqJy22+OQCLgVggOBVTCofi3YLuB6FjsgddMwA2fX7mylye0L1G3DAD8xOA2BAXCcDy5cttPgC5ubmoV68ebr31VnNfWloaUlOtQzp9+/aFYRhYuTJyg2zZsgVVqlRBMBg09x08aK/CZWVloW7durjkkkuQl1fyNpebi1ZJdfZymXKiU4CeGuNeIKWg3HKfH7fK3Kfbw7uNp8dYNbndDhx0EzSdz6x7MKza7V7AqQdXgaC7dBugaJUOZUT2wvjVrp1PKBSZW1GbW3x7HaxjOFzr1px0kXKiy8i6VVHUocuR6uooP2t0raIGtcsD0jjPTehJ6tD5kQKGqjrfkeRuFw+AzWnabdqckr184KPFlv1edM0A2Fyy/+1y8S1ZkzNWil7lCT8BiA1xkQAAQPv27ZGQkIBOnTphxIgRaNasGRISErBgwQLzM82bN4dhWL+yCuJr1KiBfv36YeDAgahduzauuOIKS9DfvXt3NG7cGN26dcPIkSPx7rvvIhAIoFKlSvj8889jOme3Fm0oFGmRKo6sW9AfQv/wYAZAce512Utdrs5tSDfKccvcDRx0zeosjRqhq4q42ar+bo3VldZtrupeodOtQ8k5lpZDXlJIN9+ffnavcqigDOtenRDpnOmuotIzoTzRQjhCS7+P8sbU9ZFB8S0HIn+L3YdPmvu/dnFwHrDLxboJPUnVKYzKvMzNoXkFaejmNm1OuYzfM3CBZb9XXTPpB9LRZeqvrhTlRkHJTwBiQ9wkADk5OejYsSNq1qyJxMRENGnSBMnJ1gCPJQAAkJ6ejocffhjnnXcezj33XLRt2xbbtlmpGbNmzULLli1Rs2ZNnHXWWbjgggvQqlUrzJ0be7vTrUWrV2ykTnF5Q38ILdf0pd2CcozVW7NKI9xtuTrAKgsaCLqruAMAYzXDn4ysSCClt2ylykp5YsYGq56521zVw0XIn6ruVVch8VjekI7M0szIDaihxle0oUYlrckMscoT0iVamb+5BV39aH16xNsg9YA3g/NAWJPdqwQAgGm0997UiLiCcqpt8f58189HGiy6TZtTyU9zMcPkVddMOpW7Tf3V12c0D46yhJ8AxIa4SQB+jXBr0R7V7MjdVkfQH0LRhvfKE8osqZ3Wmn3zu7Bc3Y093JWrA+zcTLe5qrr2vh5YFqWHX56Qw4xu8u2BsPa5+t3KLVZBcc91BSk3oLvmelHxBiJGQvrcjuqc/f4ddxPnR0daJQ3drKQC0ZWi9MH5eakZRRyh7LFyl9X91m2o5FiXvVTKM27P8QCwOXy7TZtTA9C39rIOQHvVNRs6f5vleuiJmhtYn37M/N2zXaBj+QlAbPATAA/h1qKVduRuwsvKHRB5KbUaEGnNRvSq3ZWrA+y6925zVaPRGXSlk0MuBlhLt1srmW7y7QGryszA2VZ6nDKxSxLmPuWNPwm36MxTpVOxiQVs/iGahGx545nPrHMzpTH1igXRqpn62l2y3b3BecCqXuVFAsDocdFoMG5AyitvdZk2p0zQpI+JV12z0Yus4grvu6w299PPWa4WufwEIDb4CYCHcGvRlrcdeVHQH0Kn8txrgSooyo0+mKYcXt3WqwYiEqRqc9McBgDmpkboDGv3ROgM0bTOyxt6FVUGFG6hXtdwoN9neiTQP5MfkXh021RImsXlnC5bd24nUMPzHT6PDM+/FIXmUN5QhmxqK62sZ0mxdk+kmqlL5M5LjXSv1qQd9eycvEgA1FzGC59HEkQnbvPlhfbDrG7QbitFqef6Nd2sgb5X82a6EV4g6L7a3J4jp8zf7YYkq58AxAY/AfAQbi1a3Y482UU7csCaALipVa3Q+Ztwtf9mLdhXlUzZrnUD7wvjq5Sd7nJV9eHBpdsjMxnR1IHKGzqPOhC0+jW4hUaFZnHdJ0fuwxMaNWjEAnfnZtqJamYo5P59w4wDn/WowqvoFWpzk0sNWE3ypmtcf91FevP+40UcoezxY7rVIdlt3Dc4LJGrK7t5YZynoFR41KbPN7kB3dBQv18V5dPtrtk3q9Mt18NttbmMrIhC1tilu8r99/kJQGzwEwAP4daiXbvnmKks4nbFWVc08QLvTAlXYHTJTxVQNHXZsAYAhszdankwr9Oq8G4gGm85qdAfoE6XaUX8dNlj16GTluvhNt8eiJjF6aZXh4opcOnSAAAgAElEQVQYDi5vqMH1QNA9t2qJ1oUeCLp+uAqy/jJ0cRE/WfaQtDm3OyI7onRQ9SBLlwd1A3pRx+17Fojo3j8yImKSF00K0w0o+pFXXSLlRC3X58tfetM105PTQNB9tbm8MwWYtelnLNx6EPszfSOwXyr8BMBDuL1oQ6GQ61X4FbuO4MYes1wfQlJQgW1d7SX52oRwAuCFYY0uwxkIWnn4biCaconyRnDbHO1AZo7levR1mW8PRMzi/qOZxaUfjbSw3Z6beaJwcN0L6oCCcjZ9WqvwqqDPTWdkwC5peMbFDhVgXQsTVkToDJ8vjyhquT2orXclJO3EDbBg//9GhYe1H/zYXSlfIKLCo7a8M+6uEZ1zr8+oeNU106mebtFwvISfAMQGPwHwEBVl0XpBYVAYTKgtrxbOBfwxyf0EQNeFDgTdV0aKpl2uBqPdVkbSXUUDwakYNNtdvj3AzeK2akNsk11WanpWq2Z6MacCRIYq/6n5ZzDahxsYONsqaej28+RgVqQbpNMZRi2MJPNuD2rrQ5ZeJIkssP37iHDnqv2wpUX8ZPlAp4nV6TLN9TWic+4PZEaSQa+6Iku2WX0i3FabcxsVJZYqa/gJgIfwF235Q39JK+Mr5Vj5J5fbsoBVblO+LNxAhuZeqreFX52w1pOuiO5REQhOxbAf3OXbA0DbwfZgVx+ynLPZXaWml7RqpheuqkBEe/8JzbyPDX66AX1APRB0n0p4POe0+bt1LrVO+8g94y4taVtGJAHwQs2MUVvUIK7uueIWlLSzF11MwEoH26nRwdQ10alSbmDVbqtMrNtqc27Dj6Vig58AeAh/0ZY/xhHjq5c8dKyUzrduSxpGC2ZeKFRauctlEx/dpToQdN+nAuB8Zn1Y2m2JR72aefcH7muqA8Bfh4YTAN2YzStn5LGia+Y29CRVV1Ppnxwe/Lyqs/tdCX0uwQsqIxtuffDj8H30f6PcDXYBoOf3m8zr4YW/y/QoA+GquOB210yfEQkE3XdGdht+LBUb/ATAQ/iLtvzxNTG+etGjYBewvigCwanIznO3cnhak7ccrMlbKq311oPcl/DTr8cXKe7y7QE+3DpnM5dLdQNKUzwQnIq2g91XVAGAhz628/2Z+ZMb+N/KPZ4mAHqS+sGsiFdEj8Kgs4EHFWc9AXB7wBTg8pYPfGRPGt2CSsa8SoiiScL+mcjpuoFtGScs94zbzshuw4+lYoOfAHgIf9GWP3Q1BDVwqyzr/+xBdVUOZ3khjcoMrh4b5Y3CC2BNAL5dk178D5QxnvlspS35mbJun3lOP7lsKvTe1Eg18yEPBiqBiBKRTudoUOiM7PZAv25e50UCAAD13wyrmfWevtnc19WjuRkA2HIgQgHywnm3b6G4Qv2ukQFkNTfypEalcwu6upoXs13ROoa39w13zV6dsLaIny576IPrgaD7zshuw4+lYoOfAHgIf9GWP/TKjKrkPj/OO8t6OZzlBZTu/TtTIutOVXzd5qoC1gRAVyZyC6ojpFPCJqyIVJ3dNhXSvSIeG+V+NRWwD3SGQiFc2Tl8Tm67isqk2Quwe8aruRnA6gNw32D3u3a6b4hSZWLKUW5Bn/XyIgGIJq98U89w16yry/4muoxxIOi+M7Lb8GOp2OAnAB7CX7TlD2Z89dxY7yzr5XCWF7j5PbvuvVJ4+acH1Tv9eszfklH8D5QxXi/k3N+m+UKMWRyR9Tt8ItfV89GHS73gUwMRSUfVgYjGg3cD+j3s1T2jAjndqK7D5+FCQgsPqIS6Ud10D5JmXc5YOYffMzBsHqd7R7iFsdqs1+193U8AopnFXVfYNevxvbtdM319eFHEcBt+LBUb/ATAQ/iLtvxhqcwUBpfKNMYLvvumfcc9D2buSJqHQHAqXvlyjbmPSWG6Ba9b1UpB5IZ3Z5r7hs7nxj5uQJcU9IoCJOciMk9FhsdHL3J3UFtXZPLqnlED0DqV46kxKzyrwANhKdD5WzI8kVnWA+6DWeEEueWA8DPk/411/xkyWaPsedGR2akZGioaYygUQp1CumX/ZHe7ZgUFVnEFt43R3IYfS8UGPwHwEP6iLX/oxleqMqMGXr14cR85med5MNNqQLhS99zYSKVOmWHpSYFb0K9H+lH3K1VKQeTabpFhTkXDudIDhZcZGw6Y18MLSUUA+EehGVm7Qv1y3bDN7UFtne/u1T3DhjkfGWHtklQkTNTEFVR12SuZWABYuv2wpwmAfn+MXx6+P/LORAQX3O6aAdbnqpdePG7Aj6Vig58AeAh/0ZY/dOOrb1aHKzOqcnf/EPcVVqTspRdgGu+KFhT8en0RP1k+0K+H26pIQERBRA/2vXJGBoBZmyKcdy8UVQDgn5+GEwClQqRXOL9bs9fVc0k7fMr7e6ZwwPUf2j3zFyKVWlGgD2arIfk7+4cTgH9/4X4RQTfu84ICpBsaqg5ZZjaXXHYLXt8zbsKPpWKDnwB4CH/Rlj9046vPl4eNr5781FrddBt3Fb4oe7rMC1Vgjp2NuoeHHLtPdn8tKndkXVPcTegKIsrQqfM3YZ1zL0yW9KR1wso9rv9+INIlu/fDcJdMp67N2OAu51yaxXkBVe1/eFik2u8l591r6IPZ6wrFFRS18D9fuat4AwAnNc67bnDoFvQ1OnR+uNr/M3n3uIm3Jm3wrCPjNvxYKjb4CYCH8Bdt+YMZXz1RSG/wQvISAPZnZmPS2r04lXfGk98vq7sAUL+rXebQLZzJL8CczT9j77Fs1383YFUQycwOc2WV06lXTryT1u7FsB+2eyITC0TmZNSg/KrdkVkaLwa1vU4AVELURpsbat5vnmcVb6+hD2Yv2xEWV/DKKE5h1e4j+DIlzVQlchMWr4hClSzWfXYT2Xn5mJv6M7LinP8P+LFUrPATAA/hL9ryh258NWRu2PhKad4/WAG5u0BEvUT5IORrA2MDNKOjigJ9oDHjeNgtWgbAFQ3/b2x4jbQaEP7+unzt8sKAz02MWbwTv39nJiatdZd+pPBv4h5+a685CASnotNEbwJeL8HEFW7rXXGvBwBc0y1cROk1LVxEYfNnPsoHfiwVG/wEwEP4i9YdKCWGfslh46tHR9rb+RUJUr88Oy/Svv54/naPz8596E6zyi1aJYl/9ahL5DVkkqg7I69Pd9cZWcHLQcbg12FKWJP3IpSw378zE4HgVLw9aYNn5+UVWHDbhMgLVyQ0fje8Ht4qXA/RvAF8lD38WCo2+AmAh/AXrTtoWGjio7SYTQ78cG8UVryGdDA9etI+wFaR8P16u+vvXwsHPL0y4vIayhztrkKNe/0axbupEIMaCm/4drK5z3QHnuY+bc5rMHqLV6ZXvxTIDoiuTKQ8aHyUD/xYKjb4CYCH8BetO7ipZ7gypUx82g8PJwBeSSx6DSV72aBQ4WZ/Zrb5olISdhUJszfZBxor8oAnALxUSHlp3i88A6F3SeLdVIhBysIWVHDaHBNXuEFUwCsapAoSc6H3UT7wY6nYEDcJQG5uLt544w1cfvnlqFq1Km655RbMmjXL0c/u3bsX7du3x/nnn4/f/OY3aNeuHXbs4LJdn3zyCa699lokJiaiXr16GDx4cMzn7C9ad6A07l8tVKd4eNgSBIJT8ehIb1xWvYYMZrZlRCT0vOJYe4nF2+xu0UrR5GUPfBF+CfjPV2stQ9CfLdllXiO3nZF/Cfh4/nbz+2fn5VucVof9UPFoc0xc4XoPlcR+CWgzKOym/sxnKwAAU9bZO4s+ygd+LBUb4iYBeOSRR5CQkICOHTtixIgRaNq0KRISErBoUdFa7ydOnED9+vVRo0YNJCUlYcCAAahduzZq1aqFw4etbbvhw4fDMAw89NBDGDlyJJ544gkYhoG+ffvGdM7+onUHyqFSudw++PGSCk3v+Gie1eVW56rOTf3Z69NzHT+mZ5rff+bGAwAiXaOKymeWcyKD50SkUvPOuK+y4jWUVG0gOBWHTuRW+K4ZE1e47q0ZFqplRcPfhluppbqj9/5MbxTOKgr8WCo2xEUCkJKSAsMw0L9/f3NfTk4O6tati6ZNmxb5s0lJSTAMAytWrDD3paamokqVKujSpYu5Lzs7GxdffDHuu+8+y88/9thjqF69Oo4ePVri8/YXrTtQJj5Pfho28anIBj4AMHrRTvPFdOxUHhb8dND8/xW7jnh9eq5jl2ZyNXFVmM+sgpl3p1TMYKbj/9YhEJyKpr3nAAB6TduMQHAqrn5zusdn5g1059u0w6cs7sTfr9/n9el5grpCXEGq4FQ0SOWw4T9EukYncr2RfK4o8GOp2BAXCUCnTp1QpUoVHD9+3LK/d+/eMAwDe/ZEN9Np0qQJmjRpYtvfqlUr1K1b1/z/adOmwTAMTJs2zfK5pUuXwjAMjBs3rsTn7S9ad6AqM38rrMwoJ1zd1bMi4YsUa2Vq2o8RV8/N+48Xf4A4wxFtCPrTxTsRCoVwZefw/79fqOld0fDGxLDqjTJn89IY7ZeA6eIeWbnriPn/C3466PXpeYJGheIKKklWXiJ9pqd6fGbeQHbNlMP4VZrDuI/ygR9LxYa4SADuvvtuNGjQwLZ/zpw5MAwDU6ZMoT9XUFCAxMREdOjQwfZv3bp1g2EYyMoKc/fee+89GIaBjAyrnFdeXh4qV66M1157rcTn7S9ad6Ccf6/vnoxnPlthut7+89OKmQB8t2avGbw8OnKZyV0NBKci/WjFG/DU6Qwt3p+Pp8asMP9fuXpWNHT+JqwUVb/rdDzz2QpT8/4uTQe/IuEHrUv28LAleKCwiFCRBzwVTa5Zn7mmUZreEaho6D55IwLBqajXdRqe+WyFOUd0fffk4n/YR6ngx1KxIS4SgIYNG6JFixa2/Zs2bYJhGBg+fDj9uUOHDsEwDPTo0cP2b0OHDoVhGNiyJVwBfPHFF1GlShV6nEsvvRSPPPJIkeeYkZGBjRs3WrZJkyb5i9YFKFdXuVUEi3SGeVsy6PW4qvPUCuEayaA03eVWEfndQEQpSm4V1TtDnxORW0VURQKAP3/wA70eH82rmEnzkLlb6fWoqEmzm/ATgNgQFwlAnTp10KZNG9v+HTt2wDAMDBw4kP7cnj17YBgGkpKSbP82evRoGIaBtWvDyjFPP/00zjnnHHqc2rVr44EHHijyHLt37w7DMOjmL9ryxY/pmXh05DLc++FCc/v7iKUVtnJ3Or8Ar01YZ7ke9w1eiJELuPJVRcDEVeloN2SR5Zp0+HwVMk9VzIRox8ET+MfoFMv1eHjYEizedsjrU/MEoVAI3SdvtFyPez9ciP7JFZMiBgDJGw/gr0MXW67HM5+tqLADrwcyc/DMZyss1+MvQxdjxoYDXp9a3MNPAGJDXCQAfgfAhw8fPnz48OGj4sFPAGJDXCQA/gyADx8+fPjw4cNHxYMfS8WGuEgAOnbsSFWAevXqVawK0M0330xVgFq2bIk6deqY/z916lSqArRkyRIYhoGxY8eW+Lz9RevDhw8fPnz48BE7/FgqNsRFArB8+XKbD0Bubi7q1auHW2+91dyXlpaG1FSrQkHfvn1hGAZWrlxp7tuyZQuqVKmCYDBo7svOzsZFF12Etm3bWn7+8ccfR7Vq1XDkSMn10/1F68OHDx8+fPjwETv8WCo2xEUCAADt27dHQkICOnXqhBEjRqBZs2ZISEjAggULzM80b94chmH9yllZWahbty5q1KiBfv36YeDAgahduzauuOIKHDxo1XdWcwEPP/wwRo0ahX/84x8wDAO9evWK6Zz9RevDhw8fPnz48BE7/FgqNsRNApCTk4OOHTuiZs2aSExMRJMmTZCcbNXfZQkAAKSnp+Phhx/Geeedh3PPPRdt27bFtm1cymzkyJG45pprcPbZZ6Nu3boYOHBgzCYf/qL14cOHDx8+fPiIHX4sFRviJgH4NcJftD58+PDhw4cPH7HDj6Vig58AeIjVq1fDMAxMmjTJJhHqb/7mb/7mb/7mb/7mb0VvSlJ99eqKae4ZK/wEwEOoRetv/uZv/uZv/uZv/uZvsW+TJk3yOqz7VcFPADzEsWPHMGnSJKxevdq1DNnvNvjX0L9+v97Nv4b+NfR686+ffw293uT1W716NSZNmoRjx455Hdb9quAnABUEGzf6HLnSwr+GpYN//UoP/xqWHv41LB3861d6+NewdPCvX9nATwAqCPwbpvTwr2Hp4F+/0sO/hqWHfw1LB//6lR7+NSwd/OtXNvATgAoC/4YpPfxrWDr416/08K9h6eFfw9LBv36lh38NSwf/+pUN/ASggsC/YUoP/xqWDv71Kz38a1h6+NewdPCvX+nhX8PSwb9+ZQM/AaggyMjIQPfu3ZGRkeH1qfxq4V/D0sG/fqWHfw1LD/8alg7+9Ss9/GtYOvjXr2zgJwA+fPjw4cOHDx8+fFQg+AmADx8+fPjw4cOHDx8VCH4C4MOHDx8+fPjw4cNHBYKfAPjw4cOHDx8+fPjwUYHgJwA+fPjw4cOHDx8+fFQg+AlAnCM3NxdvvPEGLr/8clStWhW33HILZs2a5fVpeYoVK1bgxRdfxHXXXYdq1aqhdu3aaN++PX766SfL55588kkYhmHbrrnmGtsxCwoKkJSUhCuvvBKJiYm4/vrr8cUXX7j1lVzH/Pnz6bUxDAPLli2zfHbJkiW4/fbbcc455+Cyyy7DSy+9hBMnTtiOWdHWarT1pba9e/cCAJo3b07//Z577rEdM16v4YkTJ/D222/jnnvuwYUXXgjDMDBmzBj62c2bN+Oee+5B9erVceGFF+Lxxx/HwYMHbZ8ryT3r9Ji/ZDi5hgUFBRgzZgzuv/9+1KpVC9WqVUPDhg3Rs2dP5OTk2I4Zbe326dPH9tm9e/eiffv2OP/88/Gb3/wG7dq1w44dO8rr65YLnK7D8np3/NrXodPrV9Rz8e677zY/t2vXrqif+/LLL23H/bVfv7KGnwDEOR555BEkJCSgY8eOGDFiBJo2bYqEhAQsWrTI61PzDA899BBq1qyJl156CaNGjULPnj1x2WWXoXr16tiwYYP5uSeffBKJiYkYN26cZZsyZYrtmJ07d4ZhGHj22WcxcuRI3HfffVEfQvEAlQC8/PLLtutz6NAh83Nr165F1apV8Yc//AHDhg3Dm2++icTERLRu3dp2zIq2VpcuXWq7dmPHjkW1atVw3XXXmZ9r3rw5atWqZfvs3LlzbceM12uoXvS/+93vcOedd0YNHNLT03HJJZegbt26+PDDD9GrVy9ceOGFaNy4MfLy8iyfdXrPluSYv2Q4uYYnTpyAYRi47bbb8N5772HkyJF46qmnULlyZdx5550IhUKWzxuGgZYtW9rWptRnP3HiBOrXr48aNWogKSkJAwYMQO3atVGrVi0cPny4vL96mcHpOiyPd0c8rEOn109et3HjxuGVV16BYRjo16+f7XiPPvqo7fO7d++2HDMerl9Zw08A4hgpKSkwDAP9+/c39+Xk5KBu3bpo2rSph2fmLZYsWWK74bdu3YrExEQ89thj5r4nn3wS1atXL/Z4e/fuxVlnnYUXX3zR3BcKhXDHHXegVq1ayM/PL7uT/4VAJQATJ04s8nNt2rTB5ZdfjuPHj5v7Ro0aBcMwMHPmTHOfv1bDWLRoEQzDQK9evcx9zZs3R8OGDYv92Xi+hrm5uThw4AAAYOXKlVEDhw4dOuCcc85BWlqauW/27NkwDAMjRoww95XknnV6zF86nFzDvLw8LFmyxPaz7777LgzDwOzZsy37DcOwXMNoSEpKgmEYWLFihbkvNTUVVapUQZcuXWL4Nt7A6Tosj3dHPKxDp9eP4ZlnnkGlSpWQnp5u7lMJgP7Mi4Z4uH5lDT8BiGN06tQJVapUsQRfANC7d28YhoE9e/Z4dGa/TNx444248cYbzf9XD/H8/HzbNdQxdOhQGIaBTZs2WfZ/8cUXMAzjV199ZdATgKysLJw5c8b2mePHjyMhIQGdOnWy7M/Ly8O5556LZ555xtznr9UwOnTogEqVKmHXrl3mPpUAnDlzhlKnFCrKNSwqcKhRowbat29v23/11Vfjz3/+s/n/JblnnR7z14SSBl8//vgjDMPA4MGDLftVApCdnU0pQgpNmjRBkyZNbPtbtWqFunXrlujcfylwkgCU5bsj3tZhSdZgbm4uLrjgAtx5552W/XoCcPLkySIr+fF2/coCfgIQx7j77rvRoEED2/45c+bAMAzajqyoCIVC+O1vf4tWrVqZ+5588klUqlQJ1apVg2EYuPDCC/HCCy/YgrB//etfqF69uq09vn37dvrSjAeoBODcc8+FYRioUqUK7rzzTqxcudL8zOLFi2EYBiZMmGD7+T/+8Y+WZMtfq8Dp06dx8cUX4/bbb7fsb968Oc466yycffbZMAwDl112Gbp164bTp09bPldRrmG0wGHv3r0wDANJSUm2n3n88cdx0UUXmf/v9J4tyTF/TShpAjBr1iwYhmHjphuGgerVq6NSpUowDAMNGjTA+PHjLZ8pKChAYmIiOnToYDtut27dYBgGsrKyYv4uXqG4BKAs3x3xuA5Lsga//fZbGIaBUaNGWfarBEC9hypVqoSbb77Z0l0G4vP6lQX8BCCO0bBhQ7Ro0cK2f9OmTTAMA8OHD/fgrH6ZGDduHAzDwOjRo819nTt3RjAYxIQJE/Dll1+ag1233367peJ93333oU6dOrZjnjp1CoZhoHPnzq58BzexZMkSPPTQQxg9ejQmT56MPn364OKLL0bVqlWxZs0aAMDEiRNhGAYWLlxo+/n27dujZs2a5v/7axX4/vvvYRgGPv74Y8v+p59+Gu+88w6++eYbjB07Fu3atYNhGPjb3/5m+VxFuYbRAge1f+zYsbaf6dSpEwzDQG5uLgDn92xJjvlrQkkTgLvvvhvnnXcejh07ZtnfrFkzDBo0CJMnT8awYcPQqFEj2xo+dOgQDMNAjx49bMdVFfAtW7aU6vt4gaKuYVm/O+JxHZZkDT700ENITEy0rb+0tDS0atUKw4YNw5QpUzBo0CD87ne/Q+XKlTF16lTb74qn61cW8BOAOEadOnXQpk0b2/4dO3bAMAwMHDjQg7P65SE1NRXnnXcemjZtWixfv1evXrYBrRYtWtDKa0FBAQzDwCuvvFLm5/xLxLZt23DOOeeY6jRjx46FYRhISUmxffaJJ57A+eefb/6/v1aBRx99FGeddZajochnn30WhmFVXKoo1zBa4LBw4cKoHae33noLhmGYAYTTe7Ykx/w1oSTBl3rmycSUIS8vD40aNcIFF1yA7OxsAMCePXuiVl9Hjx4NwzCwdu3aEn8Hr1HSJKo07454XIdOr9/x48dRtWpV/PWvf3V03CNHjuCyyy6zKC7F4/UrC/gJQByjolQES4MDBw6gTp06qF27Nvbt21fs57Ozs1G5cmULf70idgCi4ZFHHsHZZ5+N/Px8vwNQApw4cQLVqlVD27ZtHX1+y5YtMAwDPXv2NPdVlGvodwBKD6fB11dffYVKlSpZnnfFYfjw4Rb+ekXsADCU5t0Rj+vQ6fX79NNPYRgGvv76a8fHVspKamA4Hq9fWcBPAOIYFYUTHCsyMzNxww034KKLLrINYRWFSy+91FKN+Ne//oVq1apVqBmAaFAP0+PHj/szACWAoqA5lY1VAcKrr75q7qso17CsZgCc3LPxyh12EnzNmjULZ599Ntq2bUuH/KNh2rRpMAwDkydPBlAxZwCiIdZ3RzyuQ6fX789//jPOP//8EgXoKrFcv349gPi8fmUBPwGIY3Ts2JGqgqhWZLyogsSCnJwc3HHHHahWrRqWLl3q+OeysrJQqVIlPPfcc+a+jz76CIZhV3IYP3581Ap4vOKhhx5C1apVUVBQgMzMzCJVgJ5++mlzX0Vfq61bt8a5556LU6dOOfr8hg0bYBgGevfube6rKNewqMDh0ksvjar0oXdHSnLPOj3mrwnFBV/Lly9H9erV0axZM5PK4xRDhgyBYRiW5+rNN99MVYBatmxJK+C/BpQ0ASjtuyPe1qGT67d//35UrlzZ8q5wgtdffx2GYWD//v3mvni7fmUBPwGIYyxfvhyGYdXIzc3NRb169XDrrbd6eGbeIj8/H+3atUNCQgKmTZtGP5OTk0OrUqrC/e2335r70tPTo2o5//a3v41LHwDmnrhu3TqcddZZaNeunbmvdevWuPzyyy3X8pNPPoFhGJgxY4a5ryKv1YMHDyIhIQFPPPGE7d+OHz9uq3yFQiH8/e9/h2EYWL16tbm/olzDogKH559/Huecc44l2VEdkGHDhpn7SnLPOj3mrwlFXcPNmzfj4osvRsOGDXH06NGox2DPgKysLNStWxeXXHKJRZKxb9++MAzDohK2ZcsWVKlSBcFgsHRfxiNEu4bl9e6It3XoJAEYMGAADMOgpocAX4N79+7FhRdeiN///veW/fF2/coCfgIQ52jfvr1ZhR0xYgSaNWuGhIQELFiwwOtT8wzKUfD++++njoNAWF7sggsuQIcOHfDhhx/iww8/xL333gvDMNC6dWsUFBRYjqke7s899xxGjRplujlKSbx4wV133YV7773XdAv9z3/+g2rVquH888/H5s2bzc+tXr0aiYmJFifgqlWrWuRWFSrqWlUV0+TkZNu/zZ8/HzVr1sSrr76KoUOH4v3338ftt99urjWJeL6GQ4YMQc+ePdGhQwcYhoEHH3wQPXv2RM+ePZGZmQkgPHB68cUXo27duhg8eDB69+6NCy+8ENdff70tkXJ6z5bkmL90FHcNs7KyULt2bVSuXBl9+/a1PRv1qn737t3RuHFjdOvWDSNHjsS7776LQCCASpUq4fPPP7f8XpUY1KhRA/369cPAgQNRu3ZtXHHFFTSI+yWjuGtYXu+OeFmHTu5jhZtuuglXXHGF7Zop/POf/8Qdd9yBd955ByNHjkTXrl1x8cUX4+yzz8b8+fMtn42X61eW8BOAOEdOTg46duyImjVrIowM5RcAACAASURBVDExEU2aNKGBRkVC8+bNYRhG1A0Ajh07hscffxz16tVDtWrVkJiYiIYNG6J37942/XUgzHPt3bs3AoEAzj77bDRs2ND2EownfPjhh7jllltw0UUXISEhAZdffjkef/xxbNu2zfbZRYsWoVmzZqhatSouvfRSvPjii7RCVlHX6m233YYaNWrQTtHOnTvRvn17XHnllahatSqqVauGm266CcOHD7fxhoH4voaBQCDqPasbp23cuBGtWrVCtWrVcMEFF+Cxxx7Dzz//bDteSe5Zp8f8paO4a6h01aNtTz75pHmsWbNmoWXLlqhZsybOOussXHDBBWjVqlXUam16ejoefvhhnHfeeTj33HPRtm1b+rz4paO4a1ie7454WIdO72MldPDaa69FPdYXX3yBP/3pT7j00kuRkJCASy655P+z961RVpRX2kfpJbpWfmSt/NFcVkVQ4gWDRtGgMQTiRB1Hk5jBmJkvk5kQozHRqAEKFbwhHRERxRsXFQS8gBIQW0BAEBAFBBQBUS4CIrat3O832d+PDH12Pefdz1t15rRFt+9eiz9Ydp+i6lTtZ+/nIr/85S8Tm1FdTeHfr5IVAECoUKFChQoVKlSoUF+hCgAgVKhQoUKFChUqVKivUAUAECpUqFChQoUKFSrUV6gCAAgVKlSoUKFChQoV6itUAQCEChUqVKhQoUKFCvUVqgAAQoUKFSpUqFChQoX6ClUAAKFChQoVKlSoUKFCfYUqAIBQoUKFChUqVKhQob5CFQBAqFChQoUKFSpUqFBfoQoAIFSoUKFChQoVKlSor1AFABAqVKhQoUKFChUq1FeoAgAIFSpUqFChQoUKFeorVAEAhAoVKlSoUKFChQr1FaoAAEKFChUqVKhQoUKF+gpVAAA51ubNm2XcuHGyYMECWbJkSfgT/oQ/4U/4E/6EP+FP+JPhz4IFC2TcuHGyefPmvNu6RlUBAORY48aNk0KhEP6EP+FP+BP+hD/hT/gT/vwf/owbNy7vtq5RVQAAOdaCBQvqb9q8EXT4E/6EP+FP+BP+hD/hT2P7c2iYumDBgrzbukZVAQDkWEuWLJFCoSBLlizJ+6OEChUqVKhQoUI1ugq9VHkVAECOFW7aUKFChQoVKlSo8iv0UuVVAAA5VrhpQ4UKFSpUqFChyq/QS5VXAQDkWOGmDRUqVKhQoUKFKr9CL1VeBQCQY4WbNlSoUKFChQoVqvwKvVR5FQBAjhVu2lANWV98cTDvjxAqVKhQoUI1aIVeqrwKACDHakw37YEvDsrCtZtk7/4vvMfOXvG5PDp9pezed4Aed/DgQXli1ofyt9HvyIbte7w/N0tDu/+A/3M2thr91kfS9u4p8o+F67zHPj1nrZx62yR5du7aL+GThQoVKlSoUPlUY+qlDqdqMgBgz5490q1bNznuuOPk6KOPlrPPPlsmT57s/f/GjBkjV1xxhRx//PFyzDHHSKtWreSmm25yJspFUeQMn7j66qvL+syN6abtM3GZRHGNXP/sQnrc3v1fSBTXSBTXSPWE9+ixk5d+Wn/skJmr6LG1W3ZLu+qp8pvBb8rBgxwIPDN3rbS6dYIMnsF/5qHavHNvquMaqj7Zskt27t3vPe7Qv1UU11T02FDp6+DBg/L2R5tl445875lQoUKFCvXPaky91OFUTQYAXHnllVJVVSVdunSRQYMGSbt27aSqqkpmzZpF/79vfOMbctppp0nPnj1lyJAhcv3118tRRx0lJ510kuzatStxbBRFcvrpp8uIESMSf+bOnVvWZ25MN23ahnLLrn31x53ScyI9dsSba+qP7T7mXXrsX55ZWH/sgrWbKvJZRUQGz1glUVwj973yvvfY5Z9uk1eW1KbaRDw8bYX8fug8+Wwb32wsWrdZvtu9Rn587zTv1kKflw8wBADQMDVxca1EcY2cdfeUQLEKFSpUqMOgGlMvdThVkwAAc+fOlUKhIH379q3/u927d0vLli2lXbt29P+dPn16yd899dRTUigUZMiQIYm/j6JILrnkkop8ZpHGddOmbSg37dhbf1yrWyfQY7MAgE4D36g/9o2VG1J/1q2796U+ltXufQfqjxv11kf02I827qw/9q6XltJjL35gZv2x732yNfVnrd2yO/WxoSpX37/jlfp/17AFCBUqVKj8qzH1UodTNQkA0LVrV2nWrJls3ZpsoKqrq6VQKMhHH/GGDWvbtm1SKBTkpptuSvz9IQCwd+9e2bFjx//5czemmzZtQ1m3bXf9cS1vfpkeO/yN1QoALKLH/vtjs+uPfXNVegDw4ef8OqU9r3Wbik19u+qp9Njx76yvP/Z3T/Lt0IX9Z9Qfu3R9egDw8eZdqY+tZA18baXc8NzbXmDVmOrgwYNy9fD5cmH/GV4tyo/vnVb/77qibvuX9AlDhQoVKpRVjamXOpyqSQCACy64QE4++eSSv586daoUCgUZP358pp+3fPlyKRQKUl1dnfj7KIrkmGOOkWbNmkmhUJAoiuSBBx4o+3M3lpv24MGDqRvKjzfvSn3ssNlFABC/wAHArx4tAoC5H26kx+rfv/Iz3qSl/ay1W4rA5gd3cW3JoBkr64+9czzfAGgAsGT9ltSf9aONO1MfW6la9dn2+p/ZLwVlqrHUgrWbUt+Hlz38eur7MFSoUKFCNXw1ll7qcKsmAQBOPfVU6dixY8nfL126VAqFggwcODDTz+vcubM0a9ZMli9fnvj7Sy+9VPr06SPjxo2TJ554Qs4//3wpFArSrVs378+sq6uTJUuWJP6MGzcu15v24MGDsqJuuxzwcJl37T2QuqFcs2FH6mOffP3D+uO6Pc8br8sVAJiTYQOwom5b6mNZaVqPT9twSFcQxTVyd016APDuuvQAYM0Ge7OhhdiVBAB6s9F52FsV+7l51/T36+rP67dP8I3Nfz85t/7YCe9+UrHPMO7tj+Wyh2Z57+1QoUKFCpWsAADKqyYBAFq0aCEXX3xxyd+vWrVKCoWC9O/fP/XPevrpp1M39QcPHpQLL7xQqqqqZN06bs14++23Ox2E8rxpH562IlXzvW33vtQN5Yq6bamPHTKz2Cj7PsMvHylOXmcu/4weq3//B5/aACDLZuPDz4vAxkdt0gAgiwZg/pr0m41VZLOxeefe1OeVpR6dXtxs3DG+6TxoX11WdKPyUba0GP25eZWzWG0oylaoUKFCNfUKAKC8ahIAoFIbgJkzZ8rRRx8tF154oezf77dlFBGZNGmSFAoFGTFiBD3ucNwApG06tuxMDwDe+2Rr6mN1o9z1+Xfosb9QAGDqe5/SY/XvZ8La7Xv2p/6syz9ND2yyUID+9cEiAJi98nN6bHKzYQOALDSsLHXICjaKa+ShV5f7/4dGUlOUHe3vh86jx16nAMAzFcxYCAAgVKhQocqrAADKqyYBACqhAXjnnXfk61//upx11lmyfXt6cd8hkPHggw9m+swi+d+0uunYs98O7dLOPr4GZdG6zamPHfhasVHuMpoDAM299lEv9O9nvPrPtu1J/VmXrk8PbB57Lf2k/JIBRQAw7f06emzazYamKzUGALB73wF5fcXnsi+n8LZJS2pTU5s0ABg5Zw09du2GnXLRAzO9NDCRAABChQoVqtzKu5dqrNUkAECXLl2cLkC9e/dO5QK0cuVKOfbYY6VVq1by2WecXoL10ksvSaFQkGeeeSbz5877ptVNx2rilrNhe/pGef6aTamPfWT6ivQA4KFZ9ceOe/tjeqz+/Ys/tgFA3dbdqT9rFmCjz+v2F9MDgImLa+mx+vcvq7U3G1l0GFnq3klFADBgauUAwKGm+m+ee6ChasK7n9Sf1x+HpwcAw9/kAOBSdc8ygC0SAECoUKFClVt591KNtZoEAJgzZ05JDsCePXvkhBNOkHPOOaf+79auXSvLli1L/L+1tbXSokUL+eY3vymrV682f8fGjRvlwIHkS3zfvn1y3nnnyVFHHSW1tbx5c1XeN61uOpgFZZZJ+ZurNqQ+9pAGIU3zp5up0R4ffv37F60rTXQ+VNrZp5LARp+XDwD824DygA3bbGi9QiUbyr6T3q//mQ9WEADoz7prL2+Us9T8NRvlumcWUhAoIvLSoqK4+U8j59NjtQZg2OzV9Fh9XiG4LVSoUKEapvLupRprNQkAICLSqVMnqaqqkq5du8qgQYPk3HPPlaqqKpkxY0b9Me3bt5dCIXnKbdq0qRf9YsLv5MlFu8ehQ4dKy5YtJY5jGThwoFRXV0vr1q2ddqFpK++bNu2k/NMMk/JZyz9PfeyAqcvrj7tpFAcAulH2US/0719IUoPXZ+DKz8kAbB5U59Vz3GJ67GVlAhvmGLRS2XVWsqG875UiAOg/5YOK/Vz9WTdVKFzriy+KAu//GPImPXbc2x/XH/vnpxfQYzUAePL1D+mx+ry2VSiQTkRk9ec75LHXVkrdNh4GFypUqFBfhcq7l2qs1WQAwO7du6VLly5y7LHHSvPmzaVt27YyadKkxDEuAGA58xQKBWnfvn39cfPnz5dLL71UvvWtb8lRRx0lX/va1+RHP/qRjB49uuzPnPdNm3ZS/smWZKN88KBtGzptWV3qZqb/lA9SAwBNlcnSeM1fYwOALFz511ekBzb6vHqM9QAApW0Y4aGU6N//zkf29crixJSl9AagkjkA+rN+7gniSltZru2otz6qP+76ZxfSYzUF6PFZ6e/DzTs5sMlyvU68dUIqsJK12Pc61OFVe/YfkElLagMIDBVK8u+lGms1GQDQGCvvm1Y3HW+ThhJdZVhuwCtKUOlrZvpNLjbKNz73Nj1WbwAGvrYy9Xm9tdq21ly7IX2TqL3is5zXLf94lx6rAUCWhnIB2Wy8X9swAECLgPtMXOb/H1KW/qx1WyvT0KyoS78FGfHmmvrjbvDchxoADJ6xih6rf78vYTjtZ92zP30mR5Z6d90WObv3FC9lLdThUb1eWipRXCNn956S90cJFSr3yruXaqwVAECOlfdNW+6knAkaX1aCSl+DoiklvsmrtgH1OdDo38+ClVYDV55NQLVVZJbz8ibLKgrQYxmADcsMQCvWLzxBb2mresJ79T+zesJ7FfmZIsnz+mTLror8zA8y2LY+PqsYSOfbRGkAkAWI+oBN2s+a5byyVIe+01MB/FCHRzXEPSDyT8vneas3VuyZESrUl1F591KNtQIAyLHyvmnTTsrRVYYJGjWf2vdy0hNlH53hVyoJ+P7JnH+uf/8bK20AsAq48vuJDeXExemBjXbL8bkb6RyAR6avSH1ecz+0r9eS9VtSA7Ys1fvlIgBIY22ZtvRnXbdpZ0V+5rLa9LatWdyotAbg0enpAYAP2KT9rIs/3pL62CzV6n9pRVFcORpWqIarLPfA4o+3yOOzPkwlsD8EBId6aJaNsXbvq5zBQKjDq/LupRprBQCQY+V906ZtKNFVZisRND4/f13ql9PfJxQbZZ/7yuUKAPj45/r3z15hh2shV569IMa/s76s87pxFKeU6CTgh6elBwAM2GCT6HOgSVt3/S/tIIr9AWdZSn/WjzZWBgAgCGKlNRu+RGoNALJcL3ZeWrDs+6zvfJTejlZEZO6HG2Xi4lovv/+c3lPrf+b7tXbGREPVwYMH5eFpK6Tf5A+CFiFFZbkHTr/zFYli/3Yr689NW/sPfCE3Pve2dB/zbm7X9i/PLJSTekyk77lQjbfy7qUaawUAkGPlfdOmbSiRT82cWp6Zuzb1S6RaTZR9/uuaAtR3UnoAMGu5DQCQTrF9j90o/2NhemCjz8tHbdIAwOetnxbYYGbBll3cgSZt3TF+Sf3PvM3jbpSl9GdleRRZKsukvJ+ibPnsaDUAyHK91mywz2vv/i8Sx7JN1MK16e1otXZnuidk7sL+M4r3lieRWkTkwBcHUzVz+w98ISs/2+49dt7qjfW//4X567w/96teWRr1tMdmAaJZ6glFsXvtg2w5O5WogweL59X6tkn+/yFUo6u8e6nGWgEA5Fh537RpG8rl0Ch/ts2mCGhBpe8lcndNcaL8h6c4ANBi2Xs8AlT9+9kLB2kiW3bajbJ2ivlu9/Tn5aM2aQDgs9bUn3Xmcvu83oYpsU+AmrZuG7e4/mfeOpaLm7OU/qwrP0ufws0qy6RcU7b+6gFsGgA8MCU9AGDntXPv/sSxjKoxf83G1OeVxd7014PeqD+2ZhFP2p6/ZqOc0nOiVzAtIvLnpxdIFPspJS+ozeF1z/BrECp5b/n4+mnvF7wPK1WH7oEorpGxC3nWSUPUvgNfNMh5hTp8Ku9eqrFWAAA5Vt43bdqGEl1lPiWCxuFvrE79sL1zfLFR/v3QefRYHQTmE6Dq3z+NTD6Xrk8CAMZ9fnpOcbPR8uaX6e/XVJlrRnBqkwYA/TJoGxiwwdCySjnr9BhbBADdxzQMAFj+aWXoJ1km5fcoLcq1nkZZNzNZrhc7r6279yWO3UE2UXpS7juvMQuKTbUP2PznkDn1x2YJpPNV2mO1y5YvtyFU8t+1UinTG3fsbZBG+T+GvFn/M32bqIao7XsaBtiEOnwq716qsVYAADlW3jdt2oYSG+WPN9uCxmGz0wOA218sUkp+9+RceqzOAej9cnoA8OqyT83jkCbCgM1TCticeMsE+vs1VeYqz2ZDUy/uy6BtmLbMfpG+BU0iu15Z6pZ/vFv/M7s+7+cTpy39WZfV2onUWSrLpFy7G/moaNeOXFDW9XrvE/u8sPFiGpssSduj1dbKp0XRAGDMAk7B0b/fR+1J+1lnryzmbFzYfwY9VkTk8+17UjlG7dy7X56es1ZW1H35uoaGLP3vyqiLeCwrtHuuVF2khhyvk03zoWIUOF13jF8i7e+d5k36bihgE+rwqbx7qcZaAQDkWHnftImGkkxmsFFeu8EWND75+oepH7aaUvL/Hp9Dj9UvkV4vcQGq/v1TltoAALnyrFHWVpGtbuUAQJ9X52F8s/Gz+4sAwOetn/a85n6YbH4r5azTfcyi+p+ZRlCYtvRnXbq+MgAgy6Rcuxv5rtc1I+bXH3vvpPTXizUpdduSSduMiqYbZd95PTevuLXyuRtpAPC8h4Ovf7+vWUv7WXXQ3g+rp9Jjt+zcJ6f0nCgtb37ZC271d7Eplf53ZSFzmv/u+zfIkiC+a+8BufzR2fK7J+d6bWPPu+fV+p/p0wBMXFwrJ/WY6AXXIunvLQyyDNX0Ku9eqrFWAAA5Vt43rX4oTn3PbijfXZcEAKsIn1k3yr6H7a1jixNl39pfT8rvGM//vfTvn7Sk1jwOufJMqDlk5qr6407qMZH+fk2V8W02Luj3Wv2xf5+QvqF8hZwXTokr5azT7fkiAEjD/05baRvlLJVlUt5LUbb+6wl+va566q2yrhdLbl4Pk9eNRGQ/a3l6ADByTlGP48uj0ABg1LyPUp+Xz1ox7Wed8cFnqQGAFpX6gssasvGrlL1uOaXPi6UB78/Af88inH/stZX1x734znp6rAYAbCMr0jCCZbSxDtX0Ku9eqrFWAAA5Vt43rX4oTiYTZWyUGZ9ZN8q+h+3NilLy60Fv0GP/5f5io5zlpT9xsS1oXAA8cSbUHDSj+ML7Xg++AdBUGd9mo8N9xQCm6gzUJnZeOCVmwCZL/W30O/U/s5JCzbSNcpbKMinXWhQfEO087K2yrhdLbsagPaZF0Y2y77y0HseXSK0BwDNz16Y+L5/FbNrPOk1pAHwAQDefvjwK/fvTUkvS1O0vLpFWt06gg5OGLH1e68kWJEtytKbNnXAL1znprZkvwPBHfYoAgA0uRNLfL1mEvdrtzWfgsHX3Prns4dfl6uHzgx1tI6q8e6nGWgEA5Fh537T6Acom5dgoMz7zQPVy9j2YNaWk02McAPxUTcp7eiwo9e9/+V27UUaeOOMJ66bDBwC6j0m/2fiJSmDN0syw89J0iiiukQ8rZK1546i363/mtSO5WDZLpW2Us1SWSbnWolw5iF+v/xk6r6zrNY8E7WEgHZvo6kbZd15DFR3P953RAGDknDWpz2sb0StkmdK+uqyYtO0DAAOmLq8/Ngttjn3WrJX2vBqq9O9nAH/3vvQAQH9nfFvOfpOL2Rk+Mfz5fabVH8sGFyLp/12zABu92WjhMXDQjmCMFnuo3lq9sWK6pVDlV969VGOtAAByrLxvWv0AnZChUWY0jUenpwcAXZ8vTpQvf3Q2PVZPyn0WlPr3v7TIXk8jV/4DstnQabE+ABC/UAQ2VwzkwObH9xZfjr5wLf1Zx5O1+8zlySlxpaw1//ps0QLz6uHc3ShL6c/KEqmzVJZJeU/FE/ddr989Obes6/XmKjtnA212a7fYAEA3yr7zejwDVUYDgOFvrE59Xox/nqX5nLw0PQC4T+U2ZLHOrZQbFv7cPEr/fja42JHBAWeKugY+v3w9EPGZMrRXzzj2PBZJ/++6a2/DbDa6qC3ns55NmP65zBo7VMNX3r1UY60AAHKsvG9a/QBl3t/YKL+7zgYAD09bkfrBrCklP3/4dXqsnpT7LCj172eWhsgTZ5McfV4+AKCBzb8/xoGNXo9noTax85oOU+JKWWtepzzwfbkNWUp/1koldWaZlGstim8T9dsn5pZ1vZj7yXufJF22GKVDN8q+89LbuLs8wnkNAIbNXp36vFjGxDawN2U1cXFtagCgXZsemZ4+jdlHhTvwxUF5Y+UGCmpcPzeP0r+fbWTLvQY+AKBd0XwDGf3srpTFbBZrz9lqI3qix8BBbwMfn8WzK7QhgA/YhGrYyruXaqwVAECOlfdNqx+gbKKMjTLjaT/06vLUD2ZNKbn0oVn0WD0p9wka9e9nwTPIE2cONJp24HMBumlUEQD84hEObM79exEA+NJ19Wf9x0LbqWXasmTz+35tZQDAtcoD/388uQ1ZSn9WlkidpbJMyrUW5VeeTZRulLNcrxnE/QRF9sy1adKS2tTnpe9Z35RWn9cTnsZH/35GV9qwfU/qzzrh3U9SAwBtsztk5qrUn5U1yiLFjcklA2bS47I46zRU6d+/aJ39PN6yMwkAGK/9ZXUNTunJKUDaYcpnMdtBAQBfyrP+rMxdCLMzWOlhgG9400dlgjz0Kg/609tAnxZk8869MuLNNRWzZA6VrLx7qcZaAQDkWHnftPoByiYz2CgznvaDU9MDgBueKwKAf32Qv3T1pNznQa9/P/M0R648ozY9MCU9ALhRnddlHmDTrnpq/bFZqE3MqnHqe8nm19f4pK0/jSxOvHxuOVlKf9Y0PuFpKsukXGtRfIDtN4PfLOt6MT4xphYzm13dKPvOq++kIlUmCwDI0lQzulLtlt2pP+tLi9anBgB6Y/OUh6504i0T6o+dv4brS9J+1sMhWVb//vlr7K0ZeuCzplpfA58G4Jm5RQDwp5GcDqjpm1kcplgi9uad6b399WbjZA+w0Zten8tXp4HF9OzZK/lz67/+d3N4Zq8p9LhQ5VXevVRjrQAAcqy8b1r9AGUTZRRUshdO/ykfJI5lEydNKfGF/+hJuc+DPm2jjDxxNkm7X4nefGtkzZX3TRPP6V0EADd7nFr0Zx31lv0ixeZ3yfrKWGtePbwIAHzuRllKf1Y2Kc9SWSbl2t70Mg8V7Qr10s9yvVhuA6YWryai7ZpF6QGAdmrxWedqADBoBnd10b+fbSvWbtiZ+rOOe/vj1ABAU+x8dKVTek6sP9YHLtN+1iy8+oYq/fuZvuRz2MLsI05I+hr4nnHD3yxazPoAQEcFALI4TLE8jCzhXi++UwQ2vs2Gtpj1Ced1Ov0ccg1E8qeMNfXKu5dqrBUAQI6V902rH0psNYuNMnM00e4QUVwjX5CJ058VpeRf7n+NflY9Kb+ReNCj8wibOCFX/m1CbeqnhIctPU4SWYBN27un1B/bfYxNbULaAROoYfNbKW/9PygP/N8M5m45aQvPK43zRprKMinXWhQfFa3TY2+kul4i6V225q9Jb0ermxnfeel8gx5jeTPzH0OKm41Hp6cHAGxbsaIufbDU2IXpAYDesPm2FW3ufCUVCBNJ36RtOgySZfXvn7ncBs11W5NbGJZdoK+BTyyrHaZ8jmA662T4m+kdppho+7Nt6ell+rx8mw0NAHxUU31esysELkOVV3n3Uo21AgDIsfK+aRONMpkoY6PMph3aoSOK+cTp2pFFANDxvun0s57du9go//VZ24Meg29Yo4xceUZt0nSK4z1e0hrY+ADAmb2K59XtefuFg8CGWTVOXJxsftlmI0t1Hla0wOzkcctJWwfgvHxBQWkry6Rca1F8G5vLH51df2wWKhqzbX1rdXo7Wj2l9Z2XzjfwgRUNAB6ell5Yyyxml67fmvqzvjB/XVkAYKDHg/602yfVHztxcXoPeja4+HRrempTQ5X+/SxdF1NwGa1mzILiNfA943Tey7VPcwCgM1yGvp5eX8ICDLNcA31evs3G4BnF8/J9Z/RW2re5zPt+aeqVdy/VWCsAgBwr75tWP5Sem2c3yiioZEJN7aMcxXzipCklP+k7nX7Ws9SknIVQoT/003Ps80KuPKM2aXGY7yGuufK+zcYP7ppcf+zfRtsNJQIbNknD5pdtNrLUfyvRm08sm7b27k+eFwuky1JZJuVai3LxAxwA/OKR11NdL9xsMJH9HBDZMzta3cz4zks7mrDPKpKkAA2YaosfEYgysILaBlaj3vqo/rh2HgCgRfY+sNL6tiIAYFbHIsnnIRtcYHCbr158Zz11WctaWbZmH0PK9I49dnDbaHUNfOelHab+4gkF/Nn9xRT3LPoStglDYMOopvq8fNtbbWPto/jpd1KlEo5DlVd591KNtQIAyLHyvmnTNspTgFPO1p33QKO8e58NAK5SlJIf3zuNftYzexUbZTZxQu/xEaRRfgWoMozapK0HfS8cDWx8mw1NUWBuGtgoM+7zeGh+KxWu9V/KAtMnlk1beL18U9q0lWVSfv2z6Slblz38eqrrhZsN5kb1xsokAGCi7efnpwcAOt+Ap14hmwAAIABJREFUbc1EkgDggSk2AEAgyhymcLPBSrvK+DYA2qudfVYRkVMVAMjiQc+eWys/S09t0g5PlbK4RRDGHGgQrGwlYWij5qUHAFos60sFv7B/EQBk0Zew78G6TcnzYinP+rx8ScDaOcuXnq3pm1kSjkPCcOUr716qsVYAADlW3jdtuY3yrOU2AKh+Odko79xrT5w6DysCgB/1eZV+1jPUpJyJzlCgx1xCtDtEFHNqU284L/bC0cCmg2ezoSkKNxBtAzbKT5JVOja/bLORpf7f48Um0SeWTVs79yavF6PKZKksk/K/KM2Gb2PzbwOKwj/WVKNTDNPYzAY3KibaztKk3aLsTX00DU0BYsmuuGFj1rm42WCNz9Nz0gMArdm475X36bEn9SiKgF8kWxiR5POQTcoxt4GV5pT7XKPSFt5bbGu2ZsOOxLFMWKudfXznpV3RrveASw0AsuQ2MLtpFJgzwPZshvPSZg++66VpqVm2S2wrfqgCSMhWefdSjbUCAMix8r5p9UOJpX8ip5xxTu+uWZo4dhuZOP3P0CKn/Ny/cwCgJ+UshRaDbxjnFIWizMpNCyqjuEb27rcBgAY27T2bDU1RYJM0TL5kq3QteotivtnIUrpJ9Ill0xYG+jCqTJbKMinX+QY/7ccBwL8+ODPV9cJGmYnR0WWLibazNDPdxxQBwB+H8+C2Xw8qipv7TrKbarwP2WfFzQazoNSuMj4KkNYA3DORWzW2urVoA8q2MCLgQLPLfm5loTbpZ0ylsjPw3mIC81Wwrdi4ww45GzlnTerz0qYIvg3AxQ8UvzOMXiaSPhV89edJYMMGTVnOS2u9fBsA7eCWBVyye0vknwO3H9w12UuXClWsvHupxlpNBgDs2bNHunXrJscdd5wcffTRcvbZZ8vkyZO9/9+YMWPkiiuukOOPP16OOeYYadWqldx0002yebN7+vDiiy/KGWecIc2bN5fvfOc7ctttt8n+/fbDh1XeN23aRvllaJQZ5/QuaJTZw04Hqfhe+npSfhVJod2yKwkAWKgRcuWZTaAWVEYxnzj9XgGb8/twAKBtCv9MprS42Rg8w3454PTbZ1GXtq4cVAQAPrFs2sLr5UsKTVs4KWeiTp3o2cFD2dLTTHa9sFFm9ofossUmn1mamfiFor3p7z3Np/Y070OaarwPmb4EczYYr14ny/qeBdpm9+4annB8ogIAWUKoNpFGOQu1SeunfFknaQu3gWz6vKJuW+LYz0lyswZhvvPSmijfdkmD5vvJdkkkeQ3YcwtpWGzQlOW8/j6heF4+EbB2pmM22nhezN0Ijw2VrvLupRprNRkAcOWVV0pVVZV06dJFBg0aJO3atZOqqiqZNYtPKr/xjW/IaaedJj179pQhQ4bI9ddfL0cddZScdNJJsmtXMrVvwoQJcsQRR0iHDh1k8ODBct1118mRRx4p11xzTVmfOe+bNm2jrANiopgLnnRKZxTXyOad9ov0t4pTfk5v/tLXk/LOw+xmBi362BQFhaLMTk8LKqOYu2loYHPePXyzoSkKzE4PNxuPEfcTnH5XKl1XN4kXecSyaQsDfXwv0rSFk3LWfP5xeHFj4xOja0FjFioac21Cl62FRLORpZnRXPn/fpIHt/1KuRtVT7BDwzCBlYVrzVyeBDYMND+pbCV9AEBTtnz5Bi1vfrn+2NHE6QyFtZ9tsxtlpGyx0pkcPn1J2kLaHBMYf/BpEgCw5OZhs1enPi9N9bxmBM8BuEhtANh2Ca8B28gisGHUJg0ufeelN9g+ly/tAsTuLZH07kZZU6aHv7Farhkxn17Xr0Ll3Us11moSAGDu3LlSKBSkb9++9X+3e/duadmypbRr147+v9OnTy/5u6eeekoKhYIMGTIk8fennHKKtGnTJjHxv/XWW+WII46QZcv4KtpVed60KCRjjTJyypmfNjbKbOWshYdt7+YJiXpSzlbpGyD4honO8LwYtek2JaiM4hrZTjjCGtj4qE2aosCoTTgpZ+4nOP2uVLruvz9WbBIr1cxgoA8LbstSOClnzafON/BtbH6qvL+zUNEYxQ5dtphmI0uTpt1yfutJbtbuRiw1eMvO5HkxehkCGwaata2kDwBo+2BfWNPx3Yu/nzmdoWibJRy/BhsbVlpnVKnvDN5bjDaHegV2XhqE+c5Lb3rZRlYkCZoZZQuvAdOavV+bBADsPZPlvPQAyxc4qQFAloCz5cTlC7c7rLQxBBuKfRUqAIDyqkkAgK5du0qzZs1k69akIK26uloKhYJ89BFH51jbtm2TQqEgN910U/3fLV26VAqFgjzyyCOJY9evXy+FQkF69eqV+XPnedOimwdrlJFTzhwPekKjzCZpvxlcpJT4ItL1pPx3ZJpZty3pD80m5f9YmJyUM2pTj7HJ82JuGlos6xM0nnhLEQCwFylOyh961ebS4vSbbTay1C9Vk+gTy6YtDPRhXPkshZNyLkYvUrZ8G5sOKtWUUtGgUWauTeiyxZrqLM2Mtjf1JTdrd6O7XrJpNQjYWAot5mwwYa32X/cBAO2y1X0M52l/VwEA5nSGLlsfb95lHjsNgA0rTZ+sFADIQptb/PGWxLHryXlpEOY7Lz3o8TWfOjCLgUsUNzNvfcyYYO+Zx2el/87o9xcLnBQR+VGfIgDIEnDGdDNZUqY1EGzlyTdo6hUAQHnVJADABRdcICeffHLJ30+dOlUKhYKMHz8+089bvny5FAoFqa6urv+7kSNHSqFQkLlzS5vPb3/723L55Zdn/tx53rQoJGONMnLKmVXjrWPfTRzL+I5aeHjGXVyvobm8rJnBgBjmOvECUGUYtUk7qkQxXzlrsezZvTmw0RSFzsPshhIbrweJmE47qkQx32xkqZ+rJtEnlk1bmFTqm6SlLZyUV0qM/pO+09X1Sk9FY65N6LLFuM/YpDFtg7Y39SU3a3cjRqtBwMa2S5izwUDzY8pX3gcAtMtWljA25nSGk1eWcIznxUpb8v7s/soAgCy0OW1DGsWcfqJBmO+89HPeRy/ToPnO8Ta4xGvABjIIbNhmIwuwuVk9533uRj++d1r9sVkCzpjGByl2rD5X2+7v9QgAIACA7NUkAMCpp54qHTt2LPn7Q1P7gQMHZvp5nTt3lmbNmsny5cUmq2/fvuY2oW3btvLDH/6Q/sy6ujpZsmRJ4s+4ceNyu2lRpMgaZeSUM9HZzdAoswez5pS3ufMV+nlPuKXYKP/nEBsArIfgGzYpHwXBN4zapB1VopivnLVY1rfZ0BQFJtREalP/KbaYbgRMv9mLNEtd+lCxSfSJZdMWBvowrnyWwkk5A2w638C3sTm/T/Gln4WK9jjR2KAdLeM+Y5PGtA2aK//rQTy5WQs1byO0GgRsbEqLwIZdA+0r7wMAemPjm9Lq388sgZFXv4qEUOF5MctGTTOsFADAe4uJm98GxyIGbHS4l6/57D6mKDD30cvaq0aZ3Vv4TmL5BovWJc+LbWyynFfX54u0OSbyx/PKEnDGND4I7ljpkLc0AIC5cDX2CgCgvGoSAKBFixZy8cUXl/z9qlWrpFAoSP/+/VP/rKeffloKhYJ069Yt8fd33XWXFAoFqasrbabOP/98adOmDf25t99+uxQKBeefPG5aXDXSRhk45SxQR78YopivnLXw8LTbJ9HP20JNytk0EwNi2KRchw9FMbfT044qUczdNDSw+YFns6F/JqM24eSVebUPB9GbL6UybV0yoNgk+uxN0xYmlTKufJbCqR8DbJqy5dvYnHfPq2VdL+bahHa0bKr+GDQzTNugufKdBnIAoN2NmP85AjYGLhHYsGvw0KtFX3kfANCJ1D4LSv372RYGefUs4RjPi2WC6O1ppQAA3ltMgLpg7abEsR9+vsM89pHpKxLHstICcx+9TINmZq2J7yRGNV0I58U2Gzrd13deN44q0uaYKYOISAe1DWQbdJHkfcg0PgjuWGmLVx8AWLdpp5zZa4r88pHX6dCgsVYAAOVVkwAAldoAzJw5U44++mi58MILS6w9m9oGAFeNrFFGTjnzPNYTFN+DWXPKW9/GAYDm8rJpJiZfskk5Bt9MXGxvNvC8mOuCFsueTjYb6PjAJmk4eWUBSEh/YZuNLKX9vH1i2bSF18u3Sj948GCqSRZOyhlHWIvRz/KI0bX1XxYq2kDSIKAdLdNsYJPGtA3a3vRXj86m5/Uv9xd52jeTJg0BNru30D6YgWYdLOUDAFpk72vS9O9nWxjUbCyrtQPO8LxYJshotWWslG4GnwVM3IyWpSvJZkNvYbyNstKX+OhlWizLNBv4TmJU0/lrkgBgNQE2Wc5L0+aYyF8kSW1ipgwobmaJ0KhhY6UF3if1mEiPvXdS0d7Ul1nQGCsAgPKqSQCASmgA3nnnHfn6178uZ511lmzfXvqQbGoaAHzhMX9m5JQz0ZlO6YxivnLWnPJTetoPMGyUOz1mAwAMiGGTcnSKYSm0eF6fEm3D5Wqz8f07bACAQmzWUNZuSb4Y7p1ku2k8AaI3X0x92tJTYp9YNm1hUilr0g58cVB++cjr0q56Km3oRUon5UyLosXovo2NDv9hVDSclD863QYAaEc7nUzVsZlh2gbNlf/lIzy5WbsbxS/Y/ucI2NjWDO2DGWjupxJYfTQsvbHxWVDq38+2MKixYUJNPC+2hdFbxkoBAHwWMN0MpjEzB5oHpy5PHMuoTdcpetkVnu2SBs3s3sJ3Ensez8sAbAbAebHSoYB/8LgbdVQAgA2aUNvAbJnx2rLS9C4fANDPDUbDaqwVAEB51SQAQJcuXZwuQL17907lArRy5Uo59thjpVWrVvLZZ+7p26EbzHIBuuuuuzJ/7jxvWnzh9SMTZXRUYaIzvUKNYj6Z0Zxy9gBDy1I2zcTkS+Y7jVQZRm3SE68o5tQmbanYmlCb0HmETdJQ2/D3CTYAQPoLm6SJ/NNVZNzbH9PMBpHklNgnlk1beL0Yl1bbSvrcX3BSzrQoWozONjYiImfdPSXV9UJqE5sQoh3ttGU2AMAmjQXt6UTqyx7mAEDTGZiwFgE20wPhebFrcJ9KlvXRsDRg81lQ6t/PaBpIq1m0zhZq4nkxdyM9PKkUAMB7i+lmMI35/VobAPSf8kHiWLZp0/Syf3+Mb5fO7l38zrB7C99JzN40C7DR2yVfU60dpnzheXoDwDaymHbOKH54bVnpf4OTyQBNJDnsYiBM5J8Dt8lLP6Uhf4dbBQBQXjUJADBnzpySHIA9e/bICSecIOecc079361du7bEr7+2tlZatGgh3/zmN2X16tX095x00knSpk0bOXCgOPHp0aOHHHHEEfLee7a9mVV53rSfA9eQNcoYpMJEZzdAo8zEdJpTzmzMcFLOppkYEMNSTZEqw1ajOn00imtk3SZ7s6EtFU8l1CacDDFqE1IvqomdHtJfWJMmUuRU+yZ5euLlC25LWyvqkgCA2dFqqoxvPY+TciYS1JoNtrERETmz1+T6Y9m/F07KBxCKHdrRMloNNmkMtGl3o0sf4oGI2tGE+Z9jAisDzWgfzECzTpb1CeevUNeLOWeJJAEAMzpAWs0CItTE82LuRnp4ckGFnLPw3mIWlJjG/N4nNrVJb2GimAvMdaPs2y5p0MzuLXwnsU3z7JXpz+t+OC+22dCg2edupEXALN8AqU1MOI/Xln1WnSDONugiyXe4DwDo8LoNhLZ3OFUAAOVVkwAAIiKdOnWSqqoq6dq1qwwaNEjOPfdcqaqqkhkzisKr9u3bS6GQPOU2bdrUi35HjBiR+DN5cpIO8NJLL8kRRxwhHTt2lMGDB8v1118vRx55pFx11VVlfeY8b1p84bEH2FBwVGGis+uhUWZiOs0pP+GWl83jcFL+czLNxORLNilHpxj2wtEr7yjm2gZtqcgmM+h6wYSa+GK4u8a200PXC5YUKpI+el5PiX3BbWkLrxeb0mpLRZbCK1I6KWfXS4vR2cZGROSMu4oAgFHRkNr0wBQbAKAdLaNs9VOT8ijmwlqdSP2vD/LkZu1pzpx1EGCz7wzaBzPQXD2hmCzro2F1eqwIAJgTk0jy3mZGB0jZYlkMeL2Yu5EeMlQKAKzdkHwWsIwJTGNm1Ka+k5L3FqM2aXqZb7v0A/WdYfcWvpPYpnnW8s9Tn9d98J1h1rlaYO5zN9LfGfY8RmcfJpzHDRsTmOtGnQ2aRJLvum7PcwCgbaxZGNvhVAEAlFdNBgDs3r1bunTpIscee6w0b95c2rZtK5MmJb8ULgBgOfMUCgVp3759ye8ZO3asnH766dK8eXP59re/LT169JB9++wXAKs8b1p84VVPsCfKGKTCwpr+Ao3yB2Q1qznlLW62AQBOytk0c1ltMiCGTcrxvNgL58+KGxrFNbJmg01t0paKbLOBrhdslY4NJQtrQtcLtkoXSQ8A9MTLN6VNW3i90lJlrvVY9OGknGlRtBjd9yL9/h2v1B/LqGgfwoucaWxGgx0to2xhk8a0EFose9EDHABooSbzP8cEVvadwfNi16D3y0UA4LME1hob5sQkkry3GQjDDRvjaeN5MRCm9TiVys7Ae4u5G2Ea87vr7EZZb2GimCc3ayvWfxvAt0tt7ix+Z/5K7i3kv7NU8BmQxswoW1oAG8V8s6EtgZnGRyT5nckSnsdc2XDDxkCY1qL4nluaFurLztAbUZZJcjhVAADlVZMBAI2x8rxpkWvIEhqRU85EZ9dCo8zcNDSn/Lvd7eYTJ+WXDLCbmSXrkwExvciDGaky7IWjOa9RzKlNF6nNxom32AAArQfZKh1f+iysCekvbEorkh4A6ImXb0qbtvB6sSmtpl78xWP/iJNyZn+oxeg+MV3r2yfVH/sLcr3wRc44wmhHy8SP90CTxsTN2t3Il0L7QyXUZP7n2nnE951B+2CmB7rrpaX1x/ksgfX1YsJ51A4xEIZTdcbTxuvFQJh+dlYKAOC9xYTzry5LhpYxXrfewkQx1zZoetnFHnB5mvrOMNtW1DmxQROmMTNv/b9PSH5n9uy3m2otMPe5G2lDgCzheZMJxW85bETZNdD5PD4AMGhGcSjUZTQHAFrDxixLD6cKAKC8CgAgx8rzpkVKCZtg6IdHFHPR2Z9Gzk8cu2S9PXHSziNRbPMdUUTFXjiYEMmSJ5EqM4pQm7SlYhTXyIo6GwDozUZLstnYsisJABi1CV/6t79o3zPaUz2K+ZRWRFJdA5HkxMsnlk1beL2YHa2evPpSOnFSzlxCLlNidLaxERE5pefE+mMZ9QFf5My1Ce1oGa8emzQmrNViWR/9pK3iaTNrTbxe7DuD58Wuwe0vLkndzGjzADalRe0QA2FIvWDp2XhezBFMP2MqBQCQhsXcjaYsTQIApm3QW5go5g5Tml7mA5en3lYEAGxzh++kZ8mgCdOYWaNaDefFpuqa/uLTRGltQ5bwPLbhw40oE/lre26fCFibIvgAgKawvkWocIdTBQBQXgUAkGPledMipYRNMNBSkYnOtDgsijk3U7soRLHNzUQRFXvhvAPJl6xRRqoM89P+4/C3Escy1wm92TiebDaQG3oZoTbhS7/HWPuFg64XTLQtkgQAbOKk7fx8U9q0hdeL2elp1yZfAixOypkWRb/w2MZGROSkHkUAwKhoSJVhGhu0o2Vi9LtrliaOZeJmLZbt6Elu1uJmJrDGBFb2ncHzYtfgtnGL64/zbWG0ecCVg+wp7Z79yc0hMwRAgM1oGpi0zcTNuvHyXYO0hboZljExCVKLWUPX66XkvcW0DXpS7nM3OlmBZqbdwS0MGzRNBmDDqCr4nWHPOJ3i7nM30toG9jxGui3b8OFGlNHL9PfL953RQyEfANADLJZKfjhVAADlVQAAOVaeNy3aL7JGGSklT5G0Vi0Oi2LOzdSc8ii2BU/oD81eOJgQySYzeF6M2vQHOC9GbeoIwMYq5IYyahO+9FmiJrpeMNG2SBIAsImyXnn7gtvSFl4vZkerN1E3juIAACflzP5QazbYxkZEpNWtE+qPZcJapMowLQra7I5daFO27oImjYmbtVj2J32n0/PS4mZmrfk2ALan59jfGTwvpge6dey79cf5tjCaYsemtKgdYoYAuLFhNA10RWPiZt14VQoA4L3FMiYwZZqFUN0xfkni2E2k+dT0Mt956e8MA5dIc2Sp4JjGzDQbd45PfmfYZkPz333uRlrbwMLzkG7LNFnvrksCAJadoQciPgCgh0J/8wAAPZhjm7DDqQIAKK8CAMix8rxp0X6RTTCQUsLSWrU4LIo551RHxEexnai5CRpltkqfvyYZEHPrWPvBjAExbOKE57V0vQ0AtFtOFNu0GrS9Y9QmXA0zH3zkvzMurUgSADChpl55+2zn0hZeL2ZHq19izE5QpHTqx2wC9cSLbWxERE645eX6Y5mwFqkyzCUEG8oxC+yNjabK+K6Xdjf68b08uVmLmzsPs511MIF1BNkGos0uuwbdxxQBAHMEExH52f3F68WcmFBkz3RO+P1iqeDoisaugb5nKwUAcErMhPOYMs0aZby3mAWknpT7wOWJtxQBAAvXwi0Me88gsJlNNBt4XoxWo1PcGSVTJKkH6j4mfXge02QhwP5ki71d0vfh93pw0KwtXn3DE/1e9qXIL1i7Sf5n6DyqmfkyKgCA8ioAgBwrz5s2y0QZLRWfIKIzLQ6L4hqZv8bmnJ53z6uJYy1u5gZolDuQFykmRLLJDFJlGLUJz4tRm3CzYQXqIDeUUZuWrk82KMzLGV0vGJcWU5aZWFbTRHwTp7SF14vRNDSth7mJiJROypkWRTeUUcwBQIubX051vXCSxzQ2WWx2NVUmirmwVov5fMnNrRVPm/mf4/Vi20C02WXXoNvzi+qPY45gIknt0OXEiQlF9uwa4PeLWeeiexj7zujGq4OnUU5bCC5ZxgSmTLNGucfY5L3Fps+aXnZ+Hw4u9XeGgUukObL3DKYxz1xuT6rxO8M2G9oRzJedofVAzFkH6bYM4CPAZhs+7TDl25ppTZTv2ampnoyuJCLy3e7pnpsNXQEAlFcBAORYed60uEZmEwy0VGRprVocFsWcc6ofNFFcIzv3urmZ6KLQnkwzMSGSnRdSZVgzg+fF7PRws2HZzqHt3c/utxtKfOmzFw7y3xlNAzMWmFBT00RO9Lxw0hZeL2ZHq2k914zgOQA49WPX6wIQozOfcH0cE9aitoFpbLLY7GqqjO966UA6X3Kzbmb+i/if4/ViU1p0D2PXoMvodxLHstIUBebEhNRBdg3w+8VoGnhezBBAN16+LUzawnuL2ZtiajHzdb/lH8l7i4mb9aTcd2/pn8lyG1A3w94zeF6MqoLfGbbZ0A5TvuyM7/UobjYYrQbptgzgI8BmAF/fhz4AoJ2QfA5q+r1cKQe5hq4AAMqrAAByrDxvWlwjs3AQpJQw1wntPR7FnHOqOeVRXCPbDXEWTsrZxAkTItl5YUAM89PG82LUprSbDbS9Y9QmnCgzCgzy3xlNA6ekTKipaSI+mkbawuvFaBrapcQXAIVTv3fI9ULNhqVFwW0Jo3Rk0aJgQ8k2NjdDk5ZW3PzDap7crJsZZq2J14tZUKLNLrsGN45KJogzEKY3bEw4j9RBdg2wqWaND7qHMUMADcZ9W5i0hfcWszfFMDbWKGsaVhRz+onOYmD3Fn5nGLjEoRQTN2MaMwvXwu8Ms23VDlO+7AxNbWK0GqTbMoD/JgBsBi71fegDAPrZ6QtR1O+vLPox5iDX0BUAQHkVAECOledNiw0lcwZAS0WW1qrdIaK4Rt4k7gzaejCKa2SrIc7CSTl7kb6+ItmgsMkMUmVYM4Pnxez0cLNhBepg+BCjNmGDwlxwkP/OxHSoQ2BiWc159dE00hZeL5bboF1KfCmdOPVj1ws1G5YWBW0lGaUDtQ1MY5PFZjd+YVHiWCas1eJmX3LziUqo+R9DbGcdTGBlU1pslJlX+18hQZwloOo8ChZChfc20wMtgKaaWeeiexgzBNAWlD4QlraQJsLsTTG0jDXKmoYVxdxhStPL2L2F3xkGLnEL88h0W9uAacxT37O56t3HJM+LbTa0wxTbyIokqU2MVoN0W2Y2MRueh+x5rB2mfABAUyKZyF9E5McKYLPtsUgSADDXqIauAADKqwAAcqw8b9qShpJMMDAhkj2YtY9yFHPOqeaUswcIuiiwlTMmRLLzQqoMa2a0p3oUc99p3GxYtnMoDmNiOpz6sRcO8t+HzV5tHotbCCbU1H7eLLgtS+H1YrkN2s3Dl9KJUz92vVCzYW1skC7FKB24ymcamyw2u12ffyf19dJuOb7k5paqmfn1IFtYi9dr0Ax7GKAbFN81uA4SxFlYk86jYML5um3JwQHTA70F14sFnKF7GNM2aNDqA2FpCz8ry5jAMDZmb4o0LMY/19kZZ/ayQwHxO8O+tziUYuLmUQBsmGsTfmfYZkN/Z3y5DfpnsoAzFJizjezM5cnvF7u39H3oo2RqSuTvPdtTPRBh7w6R5L8BC8ds6AoAoLwKACDHyvOmxYnXDWSijEmK7MGs3SGimHNONac8im1xFjbK5/S2J2nTISGSnRcGxLBm5teD3kgcO49oG3CzYdnOoTiMUZtw6sdeOGjnx6hN+G/LxM3azzuKK7PyxevF7Gj1S4z5v4uUTsrZ9dIT5Si2NzZoK/mjPjYQzaJFwUaZaVFuGpVsZtKKm8/wJDdrMV8nYq2JCazMghIbZXYNMEGchTXp1GImxP4UqINMOD/3w2RTzQLO0D2MaRv0d5E1ylkK7y2WMYGhZczVBWlYazbY/HNNL2OhgPidYd9bHEqxUEBMY2bhWn8DYMM2G9oRjG34MGWaBZwh3ZZ9v/F5yGhz2pzDBwC0wJvRsESSIntG9xVJAgC2jWzoCgCgvAoAIMfK86ZFigJLVsWESOY6od0horhGZhDOqfZRjmJbnIUBMWyS9uqyT1OfF1JlGLWpE5wXozad2SsJACzbOfS9ZtQmnPr9mbxwUABuhPl5AAAgAElEQVTLqE0IQlgzo/28o9h2N8pSeL16Ep625vWzJlWkdOrHrpeeKEexrUXZuTdpK8k2UVm0KNgoM8B243PJJo0BNi1ubkOaNORp/4o46+D1YsMAdA9jYU2YtM3CmjTAZpkguN1iwvk3ViabaqbDQFMEpgfS9yy7BlkKPyvLmMDQsleW2I3yDXBvMXeji9Wk/Pt32OeF3xmW24BDKaZteHpOEgBMIG41CGzYZkOHODKziX1AbWK8eqQ2se83fr8YbU6bWPgCDPVGlNGwRJIgiH2/RZIAgG0jG7oCACivAgDIsfK8aXHixRpKTIhkrhM6fCiKa2Q64ZxqTnkU27Zz2CgzOsMUSIhk54VUGUZt0q4XUcwTEn8Am43NO92bDfS9Zg0lXq9rR9rnhXZ+jNqEDhVs4qRFb1FsuxtlKbxejKetz8uX0omTcna9ULNhaVG2g68843SjtoFpbLBRZoDteuDKs+ul3XJYcvMBmGYyZx1MYGXDAGyU2TXApG3rGogkqYOMpoEaGyacx+vFuM/9wD2M6Uu0FqV1hdKzkSfOMiaGQ8YEm5TjvcUcpnSTyEIB0WSA5TbgUIppGxDYvLTIdm1CfQnbbGhDALbhw83GH4fbvHrcbLDnMX6/GG1Om1j4Agz1RtS3PdXgjoEwkSQAYMOIhq4AAMqrAAByrDxvWpwisYYSkxTZQ0G7Q0Qx55xqTnkU2+IsbJQZneGVJbWpzwsn5WzagefFgk9ws2HFuaPvNaM2oTsES9REOz/mpoGfgTUzmicexZynnbYmwfViAWd6iuVL6cRJObteqNmwtChbdiWbmbN720AUubys+cRGma3d/wJceTYh/Ini8p5KmjTkaV9GApAwgZUNA7BRZteg87C3Ul0DkSR1kNE0cHPI6ICobWA6DDRFYFbH2lmnUuF5eG9lyZhgk/I/Aw2LuRvpSfnJ5LzQipXlNuCQg2kbMDzvRWLbivoSttnQ/Hc2kMHNBgs4Q/0Wo5ri94u56KGJBSut72AgTCQJ7lgwo0gSALBhRENXAADlVQAAOVaeNy1OkZivOjbK/chkRrtDRDHnnCKn3BJnLQcXBbZKn7j4k9TnhVaRjHOK58WCZ06DzYZlO4fuEIzahJQS5uSAdn6Mp43e22zipHniUcx52mkLrxfjaWs3D9akipROMxkVDTUblhZl886kreRZ5Hq9Bg0laz6xUWaA7dqRC+B62QBA51GwJg2nmcxZBxNY+5FhADbK7Bpg0J4FmkWSdrSMprEaNoeMDojcayZ+RPMARm3Szjo+p5a0hfcWyzd4AjImWMAZ3lvMgUbzxNl5oRUr2y7hkOPvE2wAgCFzYxfatq0IbJi1pnbAYRs+3Gzw9OwksGFU05fh+8Woi6jNY9a5eiDiG55ocMf0JSJJAMCeRQ1dAQCUVwEA5Fh53rQ4RWINZU9olNlkRocPRTHnnGrv8Si2xVnYpDI6Az5A2XkhVab/FLuZwfOi1CbYbNQZmw30vWbUJqQodB5mnxfa+bHNBn4Ga+KEPPEo5jzttFWzKHm9GE9bnxdrUkVKJ+XseqEblaVFwUTqH5BN1LRlyYaSNZ+YR8EAG3LlmbBW+3mzJg2nmSwACRNYGU0D3cPYNcCgvc9JWJP+fjHhPG4OGR0QudeMp405G4zapAWolcrOQCF2lowJFnB29fDkvcU43Zpexs4LrVgZcMehFMsEwfA8lq77p5HJ82KbDW0IwAYyuA3Mkp7NnsfjMyQ3ozaPUTL1QMQ3PNE0KBbMKJIEAOxZ1NAVAEB5FQBAjpXnTYtTJNZQoqc6mwroIJUo5pxT5JRb4ixsUhnnFB+g7LzQKpJNM/G8pi2zm5lTYLNRu8UNANAdgjWUCNiYlRva+T30qr3ZQIGaNXFC14sott2NshReL0aV0eflS+nEaSa7XuhGZWlRMJGauZ9MfS/ZULL0TVzlswbhqqeSVBk2fdbiZiYSxGkmc9bBBFY2DMBGmV0DzNmwQLNIcnPIaBpIb2NCTeReM542mgcwapOevB5fIetcBCssYwKzGBhVBu8t5jClrXPZeaEVKwPumDHBMkEwZI7ZtiKwYZsN/Z1hrk242WDOOrjZYLqZLMnNqGFjG1m9BblkAH92auog05eIJAHAGyvtZ1FDVwAA5VUAADlWnjctTihZsio2ymwqoINUorhGXiacU+SUr93gBgDYpDI6Az5AWaOMATFsmonnxYJnTuqRBADrjc0GnhejNiFgYxMnFMAyatOidUmBmjVxQteLKLbdjbIUXi8WcKbPizWpIqWTckZFQ82GpUXBRGrmfoINJdOi4CqfNQjIlWcvXa1tYMFtOM1kzjqYwMpoGjihZNcA80OYV7veHLYjNA3cHDLdDHKvmQ4DGy9GbUIqWiWsc/HeYhkTGFrGEo7x3mKOYJpexs4LQxwZcEcdBqM2YXYGS9f9AwCbpevtzYa2mGUAHzcbWdKz2aY5S3IzUnN37rU3snoL4nt26mvLcllEkgCAAeGGrgAAyqsAAHKsPG9anFD+jjSU6KnOVrPaQSCKuTvD8cApX22IszAg5ns97GnmPxYmH6CsUUaqDJtm4nkxatOJYJe5bpMb2GDzzahNuPZnSbho58deOChQsyZOe/YneeJRbLsbZSm8XizgTE9TWZMqUjrNZNcLNRtW8/nJlqStJNtEYUPJtCiYR8GEtciVZy9drW1gwW04zWTOOpjAyiwo0T2MXQPMD2Fe7XpzyITYuDlkQk3UNjCeNjZeLF0X+eeVsM4tFc6nt5hlCcd4bzFRJ1rnWueFVqwXkeC2LNQmzM5gtq2dhyXPi7nVnN27+J1hAB83G1nSs5mGriS5mWzNUMPGNrLaZesCT8CZvrYsl0UkCQAYWGnoCgCgvAoAIMfK86ZFtxzWUKKnOlvNageBKLZXzi5OuWU7hzZqLPQEGxR2XkiVYdQmPC9GbTrhluRmw6I2vQ3nxRpK3NiwiRNOHRm1CQVq1jQThaJRzIWaaet5uF4s4Ezb+XW8bzr9uTjNZNcLNRtW84mJ1MzVBRtKZhOIlBJ2vZArz8ToqG2wprSobWDOOpjAyp4FGEg3cbG9DcScDebV3kJtDpkQGzdsbBuI2gZmCYyNF9sGIv+8Eta5KJxnGRMYWvYCocrgvcUcptA6d+9+93lh0ODP7renz0htYpbAD72aPK+Rc2zXJgQ2bLOhM1zY8xg3G1nSs9mgCQPO2L2F1FzmnKVBUAfPs1NvQRi9DO2DGVhp6AoAoLwKACDHyvOmxZcIi2jHJEW2FtTpo1Fsr5xdnPIVdW5uJgbEMNEZTlBYo4wBMYzahOfF7PRaALXJ8p3G82LUJtzYsIkTCmAZtQmt96xpJgpFo9h2N8pS2FCyRE1t58eaVJHSlz6joqFmw2o+sZlhmygUNzMtClJK2PVCrjybuqG2wZrS4jSTOetgg8KeBTgpZ9fgV2Czy7za9XFMN4ObQ7YNRCoa081g4zWZUJsw36ASzll4b7GMCbSYHU0SjvHeYq4uaJ1rnRcGDbLpM1KbbibUJszOYLat//VEEtiw4Dad4cKexzgMyJKezWhzGHDGtmbo9maZF4iI/LcCd0w4L5LcHLJrgEMh9j1o6AoAoLwKACDHyvOmRbec3wy2G0pslNlaUKePRrHtzrDfwSm3osRxSs1EZ9igsEYZqTJM8ITnxez00C7T8p3G82INJb4cWZjLtUA7YBMnzIOwchtQKBrFXKiZtp6dm7xeTKip6RQ/Jk2qSOk0k1HR0I3K0qJgM8M2UShuZtNnnJT3IZuo/xySbNLY1A21Ddb0GaeZLAAJGxT2LECXLXYNfgk2u6uMbSBuDhlPGzdsbBuIVDRGw0JNFNsu4SaK8bTTVhbhfD9wmGJceby3mKvLWWCda50XhjiyzR1Sm5gl8P1gnctsWxHYsKwT/Z1hz2McBrBgQtxsMArtcAg4Y1szpLBa5gUiIr9VIIgJ50WSIIhdA3wnsO9BQ1cAAOVVkwEAe/bskW7duslxxx0nRx99tJx99tkyebI9HTpU77//vtxwww3Srl07ad68uRQKBVm9erXz2CiKpFAolPy5+uqry/rMed60+BJhK0xMUuxJuJnaQiyKbXcGF6d8Wa1bnIU2alFsA4BnoKFkjTJSZVigTgc4ryzUJst3Gs+LNZT4cryCTJxQAMuoTWgvak1xUCgaxba7UZbChpIJNbWzz3n38JcYvvSZ+BE1GxZgw9RktonCiTKbPuOknE0IkSvPKAKYtG1NaZGnzRoETGBlzwIMpGPXAG12rW0gDg6YbgY3bGzLiVQ0FnaImii22cBNVCWcs/DeYhkTmMXAuPK/GZy8t5jDFNLLrPNaUZf8zvyEbO5wK802G2idy2xbEdiwrBOtB2LOWTgMYN76OLxhtLlhs5MBZ+zeQgorex7rfwMmnBdJgiB2DVA7xIZiDV0BAJRXTQYAXHnllVJVVSVdunSRQYMGSbt27aSqqkpmzeJ+4UOHDpUjjzxSWrduLaeffroXAJx++ukyYsSIxJ+5c+2XO6s8b1p8ibB0QExSZNxMbSEWxTUyylg5uzjlljsD2qhFsc1nxgaFrWZRoMdcJ/C8rGYGeZFRbPtOz4HzYg0lvhzZ9ULaAaM2IT91krFyxhCsKLbdjbIUTryYUFMDG99LDF/6LCgINRuWFgWbGbaJwokyswnESTkT1l4BXHm2dsek7V173QAAp5ksAAkTWNmzACkK7Br824Ckza61DcTBAeNpvwUAm205kYrGaFioiWLe+kg/qYRzFjoxsYwJDC17eo4NAPDeYg5Tp8N2yeKfY4gj29whtenGUTawQevcx2fZAABBM0vX1d8Z5pyFw4CfE299HN5kCW5j9xZu5plw/teDiteWCedFkoMDdg3QFplZzDZ0BQBQXjUJADB37lwpFArSt2/f+r/bvXu3tGzZUtq1a0f/340bN8q2bf982fTt29cLAC655JKKfe48b1psUH5FItqxUWa8QJ2kGMU18tw89wvHxSm33BnQRi2KbT7zcGhQ2GoWveIZnQHPy3LTcNllWr7TSL9hDSVSti4n1wtt79jKGfmp1soZhaJRzIWaaQsbSpaoqYGN7yWGL30WFISaDWv6jM1MFNvXC8XoTIuCk3I2Ifz3x5JceQuwiZTa0W43gttwmskCkDCBtfsY+1mAFAV2Df71waTLlhVChYMDxtNGfQvbmiEVjdHm0GaXbTZwE2WlTGcpvLdYxgQ6TI0gXPlOjyUBAAuh0mnMUWwbAiyrTToxMXoZbqXZZgOtc5ltKwIblq6rMyaYcxYOAy59KH16dpbgNnZv4WaePY/1tWWBkyJJTRRzZfsUbJGZw1RDVwAA5VWTAABdu3aVZs2aydatyZdGdXW1FAoF+egjm/eoKy0A2Lt3r+zYYYvU0laeNy2+RNgKExtlZjunkxSj2J44bd9TCgAsdwakqUSx7ToxFBoU1igjVYbRGfC8LDcNF7XJamZc52UVupT8glyv3wPtgFGbkJ9qrXFx2hPFNlc+S+H1YnkUGtgw9xeR0pc+Ez+iZsOaPmMzE8X2JgonykyLgpNyJqy9HMSyTIzeCqhNWw2aBvK0WYOACayMI4wUBXYN0GXLCqHaAc8NxtNGgM2GASPnJDdRjIaF2iHW+CCthiUcpy00OmAZE+gwNfyN1eaxeG8xhyl0zrIMAZauT35nGL0Mt9LMEQwzJgYS29YSYEOSm1EPZH2/P4BhAAvXws0G25phcBu7t9DswbLRFkle2zOIcF4k+W/ArgFSB1kYW0NXAADlVZMAABdccIGcfPLJJX8/depUKRQKMn78+FQ/Jw0AOOaYY6RZs2ZSKBQkiiJ54IEHyv7ced602KCweHBMUmS2c+gPbU2cXJxyy50BaSpRbPOZcYXKGmX0imcPZjyvLNQmq5nBdF/2wnkRpmPsev03CGDZyhn5qdbKGUOwfC+ctIUNJcuj0FZ2zP1FpHRSbokfXZoNS4uCzUwU18h+Q1iLYnSmRUFOOdtE/Ry48ox3i0nbFk0Dp5msQcAEVsYRRooCE6D+y/1Jkb01DNgKwkOmm5kNAJsNA3BzyGhYqB1ijQ8C0UoI50fNSz67WcbEneOTAICJZX8BQmzmMIXOWVZ4HlqxMnoZbqWZIxhmTDDbVgQ2LF0XvzPW9xszJi4m+Qb47GZbM8w3YPcWmj1Y1EWR5HOD5RuIJP8N2DVA6qC17f8yKgCA8qpJAIBTTz1VOnbsWPL3S5culUKhIAMHDkz1c3wA4NJLL5U+ffrIuHHj5IknnpDzzz9fCoWCdOvWzfuz6+rqZMmSJYk/48aNy+2mxZU3W2Fio8xe+ugPbU2cXJxyy51hOtBUotjmM+MK9TJyXujQwR7MeF6VoDZhui974eB0jF0v5B2zhhIDq6yVM4ZgRbHt1JKl8HoxqowGNiw1WaT0pW+JH12aDQuwYTMTxfYmCsXoTIuCnHK2ibrsoSRXnnGEkdpk0TSQ2sT+bTGBlTnQ4KT8GSJA/Sm4bFnDAHxutCQ8bQTYjKeN4ktGw8LJKwM2CEQrIZzHe4tlTKDAnIllUYjNAs7Spp1jhguj7uFWmgEbdM56eJoNABDYsORmTKffs9/9nlmyPvksYOm6+OxmAzTMN2D3Fm6wrc2lSFJjw3QzIsnnBrsGq2FzyLIYGroCACivmgQAaNGihVx88cUlf79q1SopFArSv3//VD/HBwCwDh48KBdeeKFUVVXJunV8/XX77bc7HYTyumnRfYVFtGOjzF766A9tTZw27igFAJY7A9JUotjmMw+akWxQ/m2A3SgjVYbRGfC8rGbGZZe5aJ27mUH+PWsocTrGVs7IO2YNJWoLrJUz+l5Hsc2Vz1K48mZOLRrYtCbuLyKlk3Lr5eTSbFiADZObo9jeRCGlhNFPMGeDbaIuGZDkyjOOMFKbLPoJUpvYvy1OKBlPGyflrEHoACJ7axiAzw2mm0GAzUAzbg4ZDQspkQzYoL0pE2qmLby3WMZETwgtY2JZFGIzhyl0zrL455g0zqh7uJXOAmwenGrbtiKwmU6ADX5nrO83ZkywZPIxC5LP7r+RAdoDU5IAgLk24WDOopqKJJPsmW5GJJmzcRUxZVgJQmhGL2voCgCgvGoSAODL2gC4atKkSVIoFGTEiBH0uMNtA4DuKyyiHRtl9tJvC/7QTxgvHBen3PKdnrK0FABYfGacUDJgg17xXZ+3H8x4XlmoTVaipgvYWC8cnI6x6/UfQ5K8Y9ZQovDO0jbgujeK+cQpbT06PXm9mFOLBjaneqZYOCm3goJcmg0LsGEzE8W2/zlSShj95EaYlLNNlH6RR7EN2FzUJot+gtNM9m+LE0rmQIPmASysCUX2bxnPAtdzw6LNIcBmoBk3UWxrhpNXBmyw+ayEcB6f3SxjAgXmQ2baYlkUYjOHKXTOsoLbMOuEUfeQNseADTpn9Z9i27YisLGyTlzfmR3GoAkzJli+AVrMMmedfpBvwO4tTYmMYntwIZLU2LQitDkM6GSmDLg5ZNulhq4AAMqrJgEAviwNgKsOgYwHH3ww9f9zqPK8adF9ha0wsVFmL30dpc5eOC5OueU7/QrYqEWxzWd+eFpyQska5d8CVYZNZvC8slCbrERNF7CxqE0o/GPXCx1wmGsTrqctbcPaDaUAwOLKZym8XsypRVt7ntSDT7FwUv6Ucb1cmg2LfjJ/TSkAsDZRSClhWhR082CbKBTLWoDNRW2y6CdIbWL/tjihZA40OCln/HMU2VtWjeg8EsU18oXhCIbp2exZgJuoHmPtrRna7LLJJzafldDN4LObZUygwHzQDFssi/cWc5g6PmXYIWadsOA23EozQwAMY+tHchsQ2EwxgI3rO2MNmjBjgiWTo2aDOetgbgO7t1DrZQ0uRJJBlsxuGjei7N7CzSEDlw1dAQCUV00CAHTp0sXpAtS7d++KugC56qWXXpJCoSDPPPNMlo8sIvnetGjnxyLasVFmL32dIhjFtj0bpo9Gse07jR74UWzb6eGE8mf3240yUmXYZAbPKwu1yZpmuoCN1VDiS4StnDuB8JC5NuF62tI2oFNMFNu5DVlqwNTk9WL5BtpRhYk/RUon5dZ0yqXZsOgn6CvPGgT8fjEtCuZssE0UimUtwLZ3fym1yaKfIE+b/dtiAitzoEHzADYhRJG99SxwaVGshGMUuLNnAW6ibiGgGSmRQ8l5YfNZCd0M3lssYwKtWB8jbjk/uz8JAFgKLV4DK+wQM1yYABUzXJghQPcxyfPqO8nObbgIngWvGMDGRQe0Bk34LGD5Bqi3Y+9PzG1goBm1XtamWSQZZMloczgQYenZuDlkTkwNXQEAlFdNAgDMmTOnJAdgz549csIJJ8g555xT/3dr166VZctsezcGADZu3CgHDiSns/v27ZPzzjtPjjrqKKmtzR6DnedNi+4rbIWJjTJzBmgDATHWQ8HFKbd8p5GnHsU2n/lBaCgZsEGLPkZtwuAbq5n53OGXb00zUYDLGkp8ifyUnBcKD5noDDcLlm0r8j2jmK+c01b/KcmGkuVR6DAbJv4UKZ1mWtxnl2bD0qJgcFsU18jmnW4gipQSpkVBqgzT2GDStgXYXJsNi36C00w2IcQEViYSRI4ymxCixuZ141mwblPpJsoSauL3iz0LcBPFQDNSIhmvHu/DSuhm8NnNhPOoL2FuOReAENtymEKaSBTbdEDMcGECVNxssPNC4XwfknaeFti46ICWcB6fBSzfADUbDDRjboNFoRUpfS+zhGOk2Fm0ORyIME0WaqLYvdXQFQBAedUkAICISKdOnaSqqkq6du0qgwYNknPPPVeqqqpkxozi1Kd9+/ZSKCRPecuWLdKrVy/p1auXXHTRRVIoFORvf/ub9OrVSx566KH644YOHSotW7aUOI5l4MCBUl1dLa1bt5ZCoSDV1dVlfeY8b1q082MrTOSU/2mk/dLXUersoeDilFu+0+iBH8U1UrfNTWfACSUDNrqhjGJObcLgmyzUJit4BgNiotieOOF6vAM5L3TAYa5NyLu1tA0r6kpDsNjKOW0h55XlUejNBgvpESmdlFvXy6XZsAAb+sqzBgG/X0yLglSZGwkQRbGsJUDdtbe0mbFyG5CnzSaEmMDKRII4KWdhTaixsZ4FLiqaRZvD7xf7zuDggIFmpESy88L70AoFzFIILlnGBFqxMrecDgAuLYep/Y5JuSVAnbU8CQBOIQJUzARh54VhbCztHIHNy0Z2hus7Y+Ub4LOA5RugZuPq4fb7E+1NGWjGARZLOD7vnuSGzQrSxIEIsy9GTdQAIsRu6AoAoLxqMgBg9+7d0qVLFzn22GOlefPm0rZtW5k0KTltcAGA1atXm+48URTVHzd//ny59NJL5Vvf+pYcddRR8rWvfU1+9KMfyejRo8v+zHnetCiWZStMbJTZAwwDYqwXjutFbvlOI089im3f6X4woWTABqkyfyabDTyvLNQmK3gGA2JYQ4nr8Z+Q80LbOzZRRmBhcU7fry0FABZXPksh55XlG+Bmw5piiZROyq1NlEuzYQE2V3CbtYlCTjnTbCBVhnGEcZJnATZX0J7F08bE3Ci2AQAmsDKh5v/ApJxRBM7slaTYWU4tLiqaJdTEwUF78ozDwQHTAyElkp0X3oeVoM3hvcWaNNSXsCbtJwAuLYcpF70srdUx05egE9OvB9l0QBTOs7RzBDYvLXIDGwyZY+8ZfBawfAPUA/2BgGa0N2WaDcyYsGhzIqU21pbb3JadSQDANFk4OGBC7IauAADKqyYDABpj5XnTop0fW2Fio8ymfhgQY71wXC9yy3d67MJSAPDJFjefGSeUDNj8CiblbDWL52W99DEdMYptOgMGxLCGEl1lzu9jnxc64LCJMk6nLD4zBt9Esc2Vz1J9gPPKrBpxs2FNsURKJ+WPTndfL5dmwwJsruA2y1kHOeWMf45UGcYRRrGsBdgwMCuK7aAg5GlHsS2sxQRW5kCDk3JGEUCK3bRl7meBi4pm0ebw+8W+M0htYnogpF6w88KmuhK0Oby3WMYE6ksemGIDgPP7JMHl2IVuAOCil6W1Omb6EtxssPNCi1mWdp4W2Li+M9Z7BsMpWb4BajbYd+Y2sG21nlsipQnHLODs7N7JDZvlNofPQ2ZfjIOD+16xdRgNXQEAlFcBAORYed60KJZlK0ycvLKpHwbEWC8c14vcsmdDoWoU18i6TW46A4qoGLBBj27GZ8bzsh7MLo6yRWdwbTYsahNOkc67xz4vdB5hE2Xk3VqcUxR8RTHnnKat6gnJhpJZNeJmw5piiZROyq1NlEuzYQE2VyCd5ayDnHLGP0eqDNPYoFjWEgm6NhvLLZ62Y7NhCWuRosCEmtgoM/oJUuwspxa0HoximzaHgwP2jMPBAfvOIPXioVfTN9WVoM3hvcWaNEyLvZ+45SBNxHKYcgnnLQEqOjExfQlmuDA9EIaxsbRzfBZYwAan3+w9g8+CM3vZAACBDXPWuXVs0t2IfWdwIMKSm3HDZtkXo80uo2QiDYrpMBq6AgAorwIAyLHyvGmR88pWmPigYfZsrSAgxrJnc3HKrZc+ClWj2BY0ooiKvfQxLIoFz+B5WQ9ml7bBojNguBdrKHGKxM4LnUfYRBl/rsU5xeCbKOac07SFE2Vm1Yie6tYUS6R0Um5touq2lVK2LMA2bVkpALASUNHdiGlRUFTKgOgPYZVvATbXZsPin7s2G5awFikKzCVE27ZGMQ9rQoqdZUGJ1oNRbNPmcHDAnnFIbWLfGaREsqk6Ajbm1JK2cHjDMiYws6AfmdLiZx1tOExlEc6jE1MLIt7HzQazzkXdDMttSAtsXN8ZSzeDGS4s3wD1QOw7g7atjLKF7y9rayZSumHbZmzN0GaXUTKRBlVNaFgNXQEAlFcBAORYed60yHllK0x80LCp34m3JBtlay34gWOSZ9mzoQVmFNvBM3fXJCeU7KWPVBnGzcTzsrBXIU4AACAASURBVB7MGI/OHswY7sUaSnT+YOeFziNsoozTKYtzilaRUWxz5bPUXTBRZlz5S+F6WVMskdJmxmrSXJoNC7DhNDOKbSCKfvlMs4F+3gyIoljWAmyuzYbFP0eedhTbwlqkKDCXEJyUM47wyUCxs5xalq4vBQAWbQ4HB+wZh0CUfWeQEsmm6gjYKrE1w3uLNcqYWcDsMtGJadQ8NwDIIpx3OZ1ZhZsNZp2LuhmW25AW2Li+M1ZuAwKbNiTfAPV27DuDtq3sO4PPQ2uAJlJqzmFtzZDCytzL8LnRi9CwGroCACivAgDIsfK8aVEsy1aY2CizCUbLm5MJkfdOcq8FXZzyiYvdAOAZsMCMYttPGxtK9tLHsCiWeojnZTWUqxzUpqnvpd9sWCtnbNTZeaHtHXNtwrW75RPuSsG1uPJZCifKLN8Ar5c1xRIpbbysTZRLs2EBNldugzUhRHcjpkVBP28GRDGQzhKju9yoLP65a7NhCWsxgZUlN6NIkYU1fa9HEmBbFpQYWhbFNm0OBwfsGYfPDbaFQe0Q4z4jYKvE1gyHN6xRRnoZo2ngZ33WcJja5JiUZ3E6s8T7uNlgzSfqZlhuAz4LLGDj+s5YuplJ8Cw47Xbb3hT1dky0jbatbGODz0MW3HYqbNisrRlusC8mG1l8brAtTENXAADlVQAAOVaeNy1yXtkKEznlzJ8ZEyLvMV44Lk65Zc+GPspRbAfP3P5isqE86277pY9hUYzahOdlU5tKAcBkYzLj2mxYE2Vs1Nl5oe0dc23CtbtFbXKl4Fpc+SyFE2WWb4CBPtYUS6RU9GY1aS7NhgXYXNNMa0KIolKmRUGuPBMJngGBdJYY3bXZeHedGwC4EqktYS0msDKXEBQpsukzbtheNCwoXZsoizaHgwP2jEMgyrYwqB1iTTVyryuxNcPhDWuU0Ynp7xPYZ01+Z0bOcTtMbXBMyq0MF5eFsyXex80Gaz47D0ueF8ttQGBjWee6vjOWbgaBDcs3QGDDxM3obpQl4GyC8f4UKdWwWfamazbsSBzHNrL43Og5zt7CNHQFAFBeBQCQY+V50yLnlUW0Y6Ns+TMfPFgaEGPxAl2TPMueDZ1q2IMZG0r20keqDEvUxN9vNZQukaI1mcFwryi2G0pcI7PzQts75tqEa3dL0DjPkYJrceWzFE6UmW0rXi9riiVS2sxYmyiXZsMCbK5AOmtCiACbaTYwZ4OJBDFoz3KgcQXtWbatrs2GBa7iF5IUBZbcjNoh1ii3gA2b5dSCoWVRbNPmcHDAaBr43GBGB6hFYR70yL22GuUshfcWy5hAJybG00ZwOdywmEWhKHsWuIwOLPE+bjZY84m0OZbbkBbYuLaBy2rdtDkENieTfAPU2zFxM7obWQM0kdJNr/X+FCkF2Ja9KW6wmXkBbkFuJluYhq4AAMqrAAByrDxvWhTLshUmNl7WCtOVEHl3jZsX6JrkWVM/dMCJYlvQiC4KDNhgSI+12XABG6uhdPnlW3xm9OCPYpvahGtkdl5oe8eaGZxOWdQmVwquxZXPUrfARJl5teP12mBwv0VEfgDNjDX5xIlXFNuAzTXNtJJd0Y2KaTauHJQEAAyItr49Xc6GC9hYtq0TF6fPo8AEVtbMoGsTmz5/FzZsYxa4hZroPR7F9tYMrXNbk2ccPjfYFga518yDHrnXlQDNeG+xRhm3S+yzIrh8yrCYRaEoexa4LJwt8T5uzVjzibQ5ltuAzwIL2Li+M5ZuBi1mv9fDtjdFYMM0G5gKzgDbT2HTa4FmkVKAbYFmNOdg4Xm4BYlfsEFYQ1cAAOVVAAA5Vp43Ldr5sRUmThqstb8rIdLyZ3Zxyq0HGDrVsAczUhQYsMEHqCXOOuAANtZkxiVStKhNGO4VxTa1CSf137/DBgBoe8eaGZxOWYJGVwouc51IW93HJCfKzKsdr5e1xhYpbWasF6krj8ICbK5p5gfGJgoBNtNsIFeeUeyQy2uJ0V1Be2+tdvPPXZsN698WE1hZM4PaIav5dAHs5w2nFldomaXDwMHBqeQZh+4rzOgAudfMgx6vVyVAM1rnsowJdGJiQk0El1YmyCdbSiflloWzy+jAEpjjZoM5ZyGwYbkN+CywrHNd3xlLN4PA5sRbbACAlC2m2fjTyKS42RqgiZRuei3QLFK6wbZAMw6w2EAGByIMhDV0BQBQXgUAkGPledPeOT4JAFhEO3LKLd9pV0Kk5c/s4pT/Y6H7AYYOOOzBjBQFBmzwAWoJGvc5gE0WatN4Y7OBE8oothtKtJVk00y0wGSUkv5TktMpi9rkSsG1uPJZCl0vGFUGr5cVwiVSOnm1XqQuzYYlQHVNM9/7xA1E0Y2KaTaQK29R7ERKubyWS4gL2FgC1PGOQDrr3xY5yswmELVDVvPpGhxYQk0XELUSjjFZlqXQ4nODgTDkXjPxI16vSoBmdCxik3LcLt05Pj1YedywmHXpZizanMvoYLshMMfNBnPOQtocy23AZ8GTBrBxfWfeMWhzCGxaEntTBDZMs4GuTex6tYdBj+Vu5NrMWy56OMBiAxkciLDAyYauAADKqwAAcqw8b1oUy7IVJjZelu+0KyHyNkMY5OKUW/7M6KMcxbagESkKDNjgA9SKnt+zv/S8rIbS5ZdvbTaGOjYbFucUBXJsmom2d4xSgm41FrXJ5RVvvfSzFLpetCNUGaQ2WSmdIqXNjPUidWk2LMDmCqRbst59H6KrDNNsoKuMdR+KpM/ZcAXtvbHSLUB1bTasf1vkKLNmBvMorGGAa3BgCTVdQNTSYaBzFkuh7QL3IbNqREokEz+eCNeLWTWmLby3GE0DLUsZWEErVsti1kWVsRzcnptXSnO0BOa4NWPNJ2YxXEdyGzBjwgI2ru+MlduAwOa73W17UwQ2XNycBADseuGg57l57u+M6/tlUU1xgMUGMvg8ZNegoSsAgPIqAIAcK8+btieI3tjLERsva+2/a29po2z5M7s45aOMCcZAEMBGsT2ZwYaSARtM6bTcGVzAxlr7u7QNVvIkTiij2KY24aSeTTPR9o5NM5F3a1GbXF7x1ks/S904KjlRPqe3DQCQ2vSxwWMVKW1mrBepS7NhATbXNNPaRCHAZpoN5Mozl5ATbklyebOI0S0BqiuQzvq3RY4yE6Bio2xdA9f3yxJquoCoZQiAzlkshRbvQ2bViFoUZkGJ9sHMqjFtoWMRm5Rjirs1kBEpBZdWJogr68SiObosnC2BOW7NWPOJW7M/k9wGfBZY1rmu74yV2+ACNpa9KQIbptlA1yYGLnHQ8/QcNwBwfb8s7RK+v5h2CZ+H1460r0FDVwAA5VUAADlWnjctii/ZyxEbL2vtv2NPaUS89XJ0rfKtCQZaVUaxLWhEigIDNpgQaVGbXOdlTTNd2gaLm4kTyii2G0qc1Lci54UWmGyaietpi9rk8opntnNp668wUWZUGZx4WTxWkdJmxmp8XHkUFmBz2bZaQBRdZZhmA11lrPtQpFTMZznruIDNrOVuAPC8g6dt/dtiAitrZlA7ZDUzru/XcEOAOv390vvQMgRA56zjyZQW70Nmb9oRNqLdx9gAAMXNlfjOILhkGRNoWcoCs9ApxsoEcWWdWFszl87JEpgjLZVtA3FrxrJOMGPCss51fWcs2pzLwOELw94UgU0WcTMDlxjcZombXd8v6zuDLlttyfMYQRCzm27oCgCgvAoAIMfK86ZF8SV7OWLjdakhYnJFxFsvx9mOVb619kcBbBTbkxl8kTNg0w4m5b80Nhuu87IaSpdLiSVodFGbFq1zN5Q4qWeiM7S9Y9NMXE9b1CZXCq7Flc9S1z2TvF5n9rKpMjjxssSfIqXNzK1j3fehK4/CAmyuaaZFEUBXGaZFQVcZ6z4UKRXzWc46LjH6ax+4HWhcwMayo8UEViZARdG21cy4vl+WUPPVZaX3obU1Q+esKLantH+B+5CBsA6wEbUsKF3iZmbVmLbQOpdlTGCKO2soEVxaDlMu3Yy1NXvKoXOykpsR2DDhPG7NWPOJNKxHp7sBgGsYYNHmXMBm3wG3vSkCG0bZQnFzlnwD6zuz1fH9sr4zSM1lz2MEQcxtrqErAIDyKgCAHCvPmxbFl1FsAwBsvC4Z4F77uyLirZeja5Vvrf1RABvFNTLPcDTBFzkDNjhB+bmx2XCdlzVJc2kbslCbLK92nNQz0Rna3rFpJjqKWFz5yY6wKGvql6WuBUrJGYQrj4DNalJFSpsZy6PaJdq2xHSuQLr5a9wAAF1lmBYFXWWs+/D/mrMxzXCgceVRWBzhP0ACK5tmonbIGgZs2Vn6/XrC4Gm7QsusrRla3EaxPaXF+9DSOYmUbkQt9xOXuNmyOs5SuL1lVBkEl1m2FVYmyAcOqoxl4ODSOVnJzUhLzZJOz9KzkYZlARvXd8aizbmAzZ79bncjBDbMWec3g5PiZp5vkHzOW9oGV3Kz9Z15E6i5jLqIJhYsSLOhKwCA8ioAgBwrz5sWufJRbE/HkFNuiZg27yx90HQxXo4uTrm1wkQBbBTbiZr4Io9iGwDgBMWyZ3OdlzVJc2kbKkFtwkk9AzYYPsTCmtBRxOJpY+hLFHPf6bSFtncsrAmpTVaTKlLazFiTNJdmw3Kgcbk2WUAUATbTbGDQnrVhczWUlrOOS4xuuTa5k7bdFAFMYGXTTNQOWc3MRkeDYglQXfehZQiAFrdRbE9prxmRvA8tECZSuhG13E9c5gEWvSxLIbhkPG0UYlte7S5w+aBhMbustnRSbm05XQ5uVggVbs2ypNN3HpY+xd2yznV9Z6zcBpc1tWVvisCGbWzQEphZa+Jz3tI2fO5IbrY2zbiZZzbaCO5+S8wmGroCACivAgDIsfK8aVH0FsU1st94OWLjZfF+XRHxN41yP8CmObi8VvAM8t+juEZmr3RPZvBFHsX21A8nKJajiatBsRpKl7YhC7XJ8mrHSX0U2wAAbe9YWBPmQVjUJgx9iWJ76pel0PaO2ZueBYDNykxwNTNdn3ffhy7NxrPG9XIF0s0xgCi6yjAtCoplrQ2by83D2ti87QA2lmuTK2nbsqPFBFYmQEWRvTUMcDUolgDVdR9aWzMMYIpiO4TqKthsMK923IhaFpQuUwTL6SxLoWUpo8qgZan1PXBlnViZIC7anAWaXTonK4QKM1zYMABBs2V17HoWWGGHru+MldvgAjY7DHtTBDZsY4OibWatic95S7NR5whus6iLuJlnbnP4b8C0Zg1dAQCUVwEA5Fh53rTIlY9iO6IdG69/ud+99ndFxFsPMBen3AqeQf57FNfI68ZqFhvKKLaBzRlAlbEcTVwNijXNdGkbRhibDRdFwRKd4aQ+im1gg7Z3jFOO/FSLK1+zqLTxqkQzg5QS9sJBapPl/uJqZqxJmiuPwnLTcE39LI4wAmymRUFXGWvD5nLzsDY2KOaLYtu1yQVsrHyD34JIkVk1osjeGga4GhSLp+1KY7a2ZhjAFMX2lBY3GxYIEyndiP7FsD/c7hBfWnTALIXgklFlUIhtfQ9cWSf9DIcpF1XGGnK4aI7rNrm1OyUZLhnS6S2rY5cHvmWd6/rOWLkNLv3WNsPeNMvGBkXbLN8An/MWtckV3GZp6FBkzzaX+G/A7IsbugIAKK8CAMix8rxpUXwZxfZ0DBuvnxq8X9eL/HrjAebilFscxj5Af4liezWLDWUU28AGEyIvMhqvum2l52VNM13aBsvRxEVRsKhNOKmPYhvYnAK2d4zOgPxUiyvvCouyuPJZ6vdge3cy4crj9bKcLFyTcguIvuXQbFiAzTXNtIAoAuwWRLOBYllrw7Zzb2lDaTnruM7LcqBx2dFa+QYoUjzvHnuaiZqNG4xr4GpQrGbmRcd9aG3NUDcTxXYIFdovWs8CkdKNqGV/6NIOWXTALIVpzIwqg/eWlZjrApd9J7kBgIs2Z31nXDRHy2EqS4YLgmbL6thFm7Osc13fGSu3AR2moti2N0U6IHPWQUcwC1yKlNqbWtQmV3CbNWhCkT3bXOK/AaOaNnQFAFBeBQCQY+V507q48jv3ul+OyDW0eL+1W0obZesB5uLyWrzfv08ofZFbq1lsKKPYBja4QrUar08dwMaaZrq0DZY7A3r7R7FNbcJJfRTbwAbTRxmdAe0qLY6wKyzKWvtnKaSUMHvT1nC9rCm1q5mxJmkuzYZFRXNN/SwgimJ0FhSEYllrw+Zyy7E2NnM/LG1mLNcmF7CxePUoUmRWjSiyt4YBH28uBQBWM+NKY7aaGdTNRHGNbNnlbtLQfpHZm+JG1HKgcYkvre1SlkKrYybUxHvLAmEuupJlMeuizVnfGRfN0RLvI7Bh02e0YrXSs106DCvs0PWdsXIbXA5Tmwx709KNTXptA/PWR6tjKxV8zYYdJZ/V2lziYI5tLvHask1zQ1cAAOVVAAA5Vp43rYsrb03Hvn9HEgBYvN/1jhf5tUZAi4vLa/F+MUgliu3VLDaUUWwDG0yLtRxNXBNK60Xq0jZY0fMubYPl1Y6T+ii2gQ3a3rG0VrQUtDjCrrAoa+2fpZBSwuxNcbNhTaldk3IrpXL2ylLKlkVFc039LGtN9MuPYltkj2JZa8PmmihbGxt084hi24EGA7Oi2ObVYwIrC25Dkb01DHAly1rNzAuOzAKrmXE9NzbvdDdpuNlg7ka4EbUcaFzUQcvoIEthGjPLmMC0cwuEuehK1RPcDlMu2pz1jHNtOS3xfpYMF7RitayOXcMAyzrX9Z2xtmYu+qZlb4p0QAbYUNtwzQjb3hRDAS3Kliu3wdpcTlycHMwxswm8tlY+0JdRAQCUVwEA5Fh53rQurrw1HcPJqxU841o1Wg8wF6fcEjG56C+Wowk2lFFsczNxhdrR2Gy4JpTWi9TlU25Rm/pOKuUozzAaSpzUR7HNZ8YXA0trRUtBiyPsarws29YshY0XszfFzYZlZedqZiwgOmt5KQCwLChdUz8LiKJffhTXyAFDs4G2kh0MgO2aKFtidJcWxXJtyuJGhQmsjM6AIntrmulKlrV42q40ZsuqEQOYorhGNhhNGm42rGeBSOlG1HKgcVEirW1glsLtEsuYQCG2BcJc4LK3YTHrsjq2treuLacl3kfaHHsW4HfGSs92DQMs61zXd8bamrmc6Sx70xsA2DBnHdQ2XEXsTdOGAq6oK7Vttd4zLzsGc9bgAkX2TDfT0BUAQHnVZADAnj17pFu3bnLcccfJ0UcfLWeffbZMnmyv2g7V+++/LzfccIO0a9dOmjdvLoVCQVavXm0e/+KLL8oZZ5whzZs3l+985zty2223yf797gmzr/K8aTsPKwUA1nQMJ6+WjZlrkvfH4e4HmItT/sh0N+/XRX+xHE2woYxiG9hgQqTVeLnOy3qRunzKrZeji6JgUZtwUh/F9sYGXwyMz4wCNYsrP8rReFVimomNF5s44WbDsrJzNTNWUqiLsmVdL9fUzwKiLi2KZUGJYlnLJ9zlsmVtbFzAxgo4y+JGdTkksDI6A4rsrWGAa0Jp8c8xfTSKbRqW67lhNWm42WDuRrgRtRxoXJtDa1KepZC+ybjy6FhkAWEXuLQsZl20OcuC0iXEthymstDm0qa4u2hzVtih6ztjbc1cDlO1W9z3FurtmNHBBaDZYPam+PutjY0r4djKBHG9l63BBZpzsPdMQ1cAAOVVkwEAV155pVRVVUmXLl1k0KBB0q5dO6mqqpJZs2z6g4jI0KFD5cgjj5TWrVvL6aefTgHAhAkT5IgjjpAOHTrI4MGD5brrrpMjjzxSrrnmmrI+c543rYsrb0W04+TVsjFzTfKs9biLU24J/1z0F8vRBBvKKLaBDabFWo3X2g2lAMB6kbq0DVmoTa8uczeUOKmP4hrZamw28DjGZ0bnDYsr72q8LN5vlsLGK4rtiRMG+lg0FVdug8XTnraslLJlNTMuOoMFRLNoUbBJswC2S4xubWxcwMbyancF7Vm8ekxgZcFt2Chb00zXhNKaZmL6aBTbNCzXc8PyoMfNhrXlFCl1X7H8z10bUQtcZinMzmBceXQssoCwi65kWcy6aHPW9ta15VxW69buuHRp1rMAvzMW/9w1DLDOy/WdsXIbXM50lr3pn+G82PVCzYYVruVyN7KAjcu21RpcuN7LltYMzTks7dKXUQEAlFdNAgDMnTtXCoWC9O3bt/7vdu/eLS1btpR27drR/3fjxo2ybds/JxJ9+/alAOCUU06RNm3aJCb+t956qxxxxBGybJn7hcUqz5v2dw6u/Gfb3OtxFBtZNmYrHZM8a4Lh4pRbwj8MUolim5vpaiittT82lJal4YcOYGNNMycuLl2hWpaGLoqC5TqBk/oodrtOuHyv2YMZnTeszcYzjrRYiyufpbDximLb3hTDvSyaimtSbgFR18ZmoNHMuOgMFhB1fb8syhY2aRbAdonRLVcXF7CxRNsuOoPFq8cEVsY/R+pg52Hua+CaUFrTTFdmgUXDcj03rCYNNxvM3Qg3opb/uWtwYA0DshTSNxlXHh2LLCDsoitZFrOvO6gy1vDGteVcut4NAFy6NGv6nDbF3TUMsM7Lpd+ytmYuZzrL3hQBGzM6QM2GZW/qsm21gI0r4OwVQ9w8ZkHpe9kaXGA2DaPNNXQFAFBeNQkA0LVrV2nWrJls3Zp8sFRXV0uhUJCPPkrnVsIAwNKlS6VQKMgjjzyS+Pv169dLoVCQXr16Zf7ced60Lq58nTEdw0m5FTyz3BERb63HXZxyS/iHQSpRbHMzOw0sbSgtYIMJkdZL3wVsLGqTi0NpvRxdFAXrwYyT+ih2u064PPDZgxkToa3Nhist1tI2ZKlfQeMVxW57UxewsbysXXkUFhB1bWwsKpqLzmABUdf3ywoKwibNctZxieytjY3LZtcKOHMG7Rm8+ksGJEWKzKsdRfa/N6aZ731SmixrTTOfcqQxW9NM13PDsqD8OdgvMncjpA7+ZrBbgOoaHFjDgCyF9DLm1HJmr+S9ZW1hXHQly2J2hmNSbg1vXAGGlnbHpUtLm01jOZ25hgFW2KErm8ayOnY5063d4L63UA/ErhemTFv2plkyQVwBZxMXu59bLo2N9dzCAZa1Qf8yKgCA8qpJAIALLrhATj755JK/nzp1qhQKBRk/fnyqn8MAwMiRI6VQKMjcuaUN7be//W25/PLLM3/uPG/a/xxSypW3OIzIKT/LEP65JnnWBMP1oLGEf5gQGcU2N9PVULqAjauhtCavLoqCNVF2BRU99Kr75eimNrkfzDipj2L3ZsPlgc/4zOhQYVEEhjsar0rQGTD4JoprZM/+0omTy897nsFTd03KrVW6y43Kul4uOoMFRF3fL0uMjs2MBbBdlBLL3QjdPKLYtqB0nZfFq0eXEsY/R+rg74xhgCtY6i6Df+4KY7NoWK6tmdWkXQqbDeZuhFqUKwwB6oq60sGBNQzIUhhaxjImUIdhbWFc95ZlMYthUVFsD29cW05Lu+PSzVjTZxSYWwJUF23OOi8XaLZyG1zBjJa9KZ4X0zkhtcmyN3XZtvYY6wY2Ltcm67nlonpaVNM7xiffXxZ18cuoAADKqyYBAE499VTp2LFjyd8fmtoPHDgw1c9hAODQf3NtE9q2bSs//OEP6c+uq6uTJUv+P3tfHh5VebZ/hCgC1rVSbOUbSxCluNWKCK0/lQrKJ2Jbpdpq3duKfFZrwQFFEUKQKIKCCAFxYRFxRUzYwhYQZN8Ewiq77BDCkoQkc//+CO+Z57zneWYyw5tMmbz3db3XpcMwzDnnnXOe5X7ue5VnjR8/PmGb9oFMP1d+h9Ae16kX0uDf6p3+Sp5UweBuNJJBC1f9lhRNuIDyx3z/cXEcSinwWsd0NqSKMmdU9LZQHeMGe7OFirJeqQ8E+c4GVxmKxGfWFSqkzgbnFmuCzqAb30gPfS6xmS+YpnHVTCkR5RK2t3L468XRGaRElPt9SUZBejAjJdgcpaST0LHhOlHS0DZHZ5CG0XWVkkh8Zp06KHHlV2z3VyilaibnWSDRsLj7xg9CkKZ3NqRrAPhVtqQBVO6+IVXKYwEndSxBN8+TujDc3pIkZjl6mSRByXU5pdkdbm6mot40kns2dy+QjovrBkpJcy9GmW6jIG+qJ2yBoDzboFObJHddTulMOi5OtUm6b3EzNtIMna5MF6lrVtmwCUB8SIoEoGHDhmjbtq3v9U2bNsFxHAwYMKBCnxMpAejVqxccx8GePf4H480334xrr7024mf36NEDjuOwKxGb9s8MVYZrj3OVcmnwj6vkSfxYjlMuGbRw1e8vl/LcTC6g5BIbrqL8mzT+oc9RFCRqEzdEJVXHuM7GNyv4G7NeqQ8E+YFGrjIUic+sa4pLnQ2u8ioN/sUCvfIqPfS5xEbiqXPVTCkR5a6X1Ini6AxSIspR0SSjID2YkRJsbshe6thwiag0tM0dl8Sr11VKIvGZ9Rkb6V7AURQkmgZnxibRsHQDpkBQlqC8U+tsRFI30qmD0gAqd9+Q7gWxgFM6k+Zm9DkM6b7F0ZUkU0Bubka6d3NdzsVb+NkdLrGRumb6gLkkdMDdCyTpXK4bKDkcc8e1YQ+vbsQdlzTboHcDJXlTbrj5hc/445q30a/aJA03czM20gydTrGLJAlc2bAJQHxIigTAdgBix31D/FSZLfv91TGOUy4N/nEW8ZJBC8cp7ysof3DV788FRRMuoOQSG84hMpbERqooc0NUUkDJVSilyoxeqQ8E+c7GUaYyFKkyo0vvSRVCrvJqgs7wv2/P9n0uJ2/KHZfEU+dkW6XgkxtGlyQoOTqDlIhyVDTpQaoHM5JRECeXKQ11co65kgRlLMPougNrJD6z3jmU7gUcRUGiaXBmbFLSrDvLBoJZWC9IULbp7+1sRDJr0j9TGkDl7htSpTwW/HW4v7vEzc0A/jkM6b7F0ZUkidkpTKVcMtfiBrEliVlubkbqmulKTJLQAdfZkI6L86aRkmbOl2XtLn5v6S7Tin5OiwAAIABJREFUgaA826CbzN37Lt9d4mRbJUUwbmhben5ynV5phk6n2EVKmisbNgGID0mRANgZgNihq14Egnx7nFMbkIxnljAW8RI/luOUS8ofyiGSBhTjhOEsLqDkEhuuoiwlNhxFQaoof8YMN0vUJq6zIVVm9Ep9IMh3Ng4zutcStQnwS+9JFUKu8ipx5WOBXnkNBHnfBu64JNdkrlIuBZ/c9ZKCGa7tL0lr6nKZgaCsQa8HM9I+5GZRpKFObshemtngjksaRtddiyX+OUexk6qZHEWh6xd8AsB5FsSSNEsSlL/XOhvSNeA6oncLA6jcfUOqlMcCrnsrceX1OQzpvsXRlaSAklM6k0zDuEFsSWKW62xIXbOKmjhySfPz4/jj4rpmUtLMHdeaH/m9xR2XdL10ytYfhO4SN9wsebhwQ9vScPOIOf5OrySd+8Jn3gLWtRGS5sqGTQDiQ1IkAJ07d2ZVgNLT042pAKkNJqkA9erVK+bvnchNq6teBII8h5GrlEu830XMg7zDEP6hz1UapIeIcoikakTScBYXUHKJDecQKSU2S5nERhrO4gyzpIc+V6GUZOf0Sn0gyHc28o/5A2WJ2gT4JeqkCuFQpvIqzTbEAr3yGgjynFNOzk9ys+Qe+lIiOm6h/3pJ+1AfegsE5URUl8uM9CDVgxlpH8Yyi8LtQ2lmI5ZhdN2BNRDk+edc4eBPQjWTM5aS6CecZ0EsSbMkQanrr0vXgKMOSk7b3H1D6nLGAq57K3Hl9YFlqRPG0ZUkiVluvkQa2uYGsSXqHufhsk/omlXUxJFLmp8TAmWODigpnXHHtWonr27EdWyk66VTttoL3SVuuFlyp+fkTaXnJ9fplaRz9edXJEWwyoZNAOJDUiQA8+fP9/kAFBUVoVGjRmjevLn72tatWyPq9UfzAbjyyitx7bXXorQ0nL13794dZ5xxBtas4YOGSEjkpuWoMlx7nKuUS7rTC37wJwBSC5PjlEsPERX80kDpY0HSUB9SDAR53i/nENlEUDRZvMV/XFJFmRtulirKXIVSqihzJjmcognXGo5k1qRL1EkVwsEz/ZVXE3xmnVMeCPKGdAeY45IGVbmHvjSoyc2iSPuQa/tLD1J9qDQQ5ClbgD9Ik5R1uCBNUjfijkuSN+WOS1IJ0R1YA0F+oJG7b0hUGc5YqrNQfeY8C2JJmiUJSl1/XboG3DC6xD/n7ht9hOQyFnDdJUmpRR9YliRLObqSJDHLucW+OoF/hnE0R4m6x3U2KipNLUlQcsp0ktcJR9+UTAG541q5nd9bnDeNNNuge0y0G8h3l3bl+xMASRCAm9mQhpu5Qo8knas/v6TnZ1XAJgDxISkSAADo0KEDUlJS0KVLF2RmZqJly5ZISUlBbm745nzLLbfAcbyHnJ+fj7S0NKSlpeHOO++E4zj4z3/+g7S0NAwaNMjz3m+++QZnnHEGWrVqhWHDhuFf//oXatSogb///e9xfedEblqOKsNxGCn3Wg31pQptfzpspN4rtTC5SoP0EFHBL62OjJ7PD2dxASWX2NAhKvWQlAYaucRGqihzgZf00FcW8fQhLZk16ZX6QJDvbFBHTzWsGMms6e+aRJ3U2eCoFyb4zHrlNRDkOaectr80qMpVyqXq8yhm6E1SoOFUm6QHqS6XGQjKKlv6sKzUYeMcPSVpTe64JAUajs4wQaDVtNBMywJBfqCRm9mQgpk56/0JgETT4DwLJDrD06P9SfNyQYFG11+/ojt/L+ASG4l/zt030oTkMhZw3SVJqUUfWJYKFxxdSZKY5Srl0tA2N4gtUfe4zoaUNOvS1JIEJadM9/RoPlDm6ICS0AF3XNLe4gQBpNkGvbMhqRvtYDxBJEEATt1IUgTj7vMchRYIP7/UiiQIUNmwCUB8SJoEoLCwEJ07d0b9+vVRq1YtNGvWDJMne1tSXAKwefNmUZ0nEAj4/p2vvvoK1113HWrVqoVLL70U3bt3x4kT/I85GhK5ablKOcdhpJVyxSe9TNAxpsNG6r1SC5NyytXNXAq8VPBLNa1HCsNZKqCkDwgusaGUEvVdpYFGTkVBojZxgZf00FeJDeXpSmZNeqU+EOQpW7Q1rCrLEp0BAJ740JsASLJzHPXCBJ9Z55QHgnzVj9P2lwyguEq5lIhyxlKSARKn2iSphHC/L6mSpr9P6rBxjp5Sx4Y7rv7CMDpHZ5DUjXSZwkCQH2jkVEqkYIbjKEs0Dc6zQEqaud/MUsE9Wtdfv/xF/hpw1MHfv8knANx9QypyxAKuuyRRZfT3SYULjq4kmQJyA+bS0DanXjZLoO5xnY2KSlNLHi7cb0aSOubogJLQAXdckjM5JwjAdTkBf2dD6i5xQgfScXHqRh/O3cy+923mPr9JkDfVu9JSYbAqYBOA+JA0CcDpiERuWlUpp9Vnrj1OH+RXkwo8JztHH+SqWi8NyNFWo9ILl4xMlEMklUiTbmCKo0wrKRzvl1JK1HeVDFpoYqNu0FJFmRtulh76KrGhnQ2poqxX6gNBXnaOBsqqnRypNatrVEuDmpR6oc6BNLQdC27O8HPKOUM6zgVXMoDiKuWSUyiloqlK/IuCnrYaeqO/GSkR5TpRnFEQNywrJaKcypbE6eaG+WLx2ZDUjXSZwkCQH2jkKFtt+vPBDMdRlqrPnBeDRAfUk9tAUHaPvknrbEjBDKe/LvHPOfUVqcgRC7jkkkua2UFsoXDB0ZWeGsVXlLkBc2lom6M5zhCoexVVcOMGsW8SlM44iVlpbmYs072VhA6445L2FudNIynr6J0NqbvEybZKx8V5nYwQZhu4Dpskb/rUKG+CLRUGqwI2AYgPNgFIIBK5aVWlnPLqOQ4jrZRTibITjOwcfZCrar3k0PjuzHACoKTqpMBLOSlS+oGkzqAqeTSo5hIbSimhx8XxmWeRxEadL6mizA03S+1xldjQzoZUUeaCmXUMtYkGykpeMlJr9jHNfEea2aAPBnUOTNAZOE45N3TGVbwmC0o1XNVPop9QKprqxEg64Wrojf5mPhD2IUdt4mZROE65pKzDqWxJnG6OYicNoHJ0BmkWRZcpDAT5gUaOsiVVyqet8XOUJT4z51kg0Rk4/XVJgaaZlthIwQzX2ZCM9rjOhlTkiAWt+/uTS+43ww1iS79vjq4keYJwLu6SBr1OEwkEszA9j0/cOdoclzRz0tSS0hknMSspnXEmWJIpIHdc0t7ivGkkQQD9fZK60XqG5hiLN42kCPb6ZH+CLcmbckUpyY+ismETgPhgE4AEIpGbVlXKaVWf4zBSuTHa/ueqfvRBrh6odwptf8o1VEZIkvKHqlLTarF0A1OVPBqocNbze0il/Mb08MOf4zNT50t1viRqUywVZRXU039f0p3mXDI5SUNqfPObtPLPjaTV/ogWJEmmRv2mlFMvftk1nFyZoDOopI629Lmq35b9R33HLynV0Eq54kBLSi2ZuRt911bSCVdqVFS3X6qkqaFS2i3gHqSUU07b/xy4Kq1E6eCG+SR1I47OIKkb6aZlgSDv28ANKd4qVMqnMkOKEp+Z8yyQkjBOfvE7wT1ad2MOBPliAKdGJRntcZ0Nya01FnDJZUW9TqTfN0dXkgbMOaEDSTK0EyNeIHXuuM4GR3PkkmZJ6YxLbCTaHGeCJXm4cKIM0t7i5u24hI3r2EjdJY7mKDltc8PNQ4XZBi7BlpSzuGcSVxisCtgEID7YBCCBSOSmVZVX+uDjOIy0kkcH5biqH32Qq0q8xGGknHIVAEsPEVXJu43wxSV1BkVRoMkKZz1PAxTK/+X4zFRFQZ0vidr0HqFeKBqSlNio6jv996VgRq/USzdmWilXyZBEbQL85juSUouqDKV2y3aDQIkrHwvUdaLBL6duxLW8swUHWFopV58r7UPaiVLXVhpAVcEMpcFIiaj6rdBuAScTSCklVAGECz65YEaidFDVJpWISupG/2JkdqVZlKs1mcJAkPdt4IYUb87gK+WTvvcPKUoGZz0n+BMA6RpwspKSAg2X2HDFAI7aJPHPuc6GdC+IBbpiUSDIV8o5V3Dp983RlaSAkgodqARX0qDnxAukzp3uxRAI8vQTbhD7ekHpjEtspK4ZNzcj0ea445q7kd9bFZ0H4jo2UneJU22S6IBcx0ZSBEtjPEEk5Sy9eBQIyv4GlQ2bAMQHmwAkEInctCo4pNxXjsNIK+U0AOdk5+iDXHUYJA7jgJwwpUQlI9Lgn3JSpK1vqYKhKv80WeESGxqg0EFU7gZGVRTU+ZIqynS4WVXKpcRGHRd9oEsVZe5my92YaaWcngMuoAT8VVIpsXltYnkCcPmLE93Ogolqpgqm6SA0F8xwTqWSAyytlKsAXNqHtBOlrq0kf6g4r5SKJmnrq6SOGvtwFDtKKaHv5ZxdvyN6+aqzIVE6aIKtEguJf66qmdQ1VlLZUu+h6jKcAg11YFXdHSlQprry6nMl+onyLKDJiqTUotRXqMrS7PX8ACqX2HDVTI7a1Dyd559zjrlSdykWqPsl7S5xlXJuXkGaheHoSpIiGK2Uq70ladBzg9gThcRd3YdTowg4cIPYknMzTWzU3pLmnDhp6gyBNqfom3RJ6kZcYsMVObjERuoucUPbsUhTS7MNnCcI10EH+A7bUaYbWBWwCUB8sAlAApHITasCL0qr4TiMtFJOA3DuoU8f5K1Otqkl3q9S8/hl13BiIekzqxsN5Yi+O5N/6Ct6Bm2Tc9bztFJOBzY5OgNVUVBBtURtotQLVVGWqmPquOgDQqpm6pX6QJCnbFETLHoOuGom4DepkWY2+mSXt4av6D7R7dhIvN9YoOYfaADGBTOctKfkAEsr5Sqovk3g0lLVC/VbkPahmkWhZlhS8Kk6G5RbzinQUN8G2lngOlFzmWF0idJBE2xV3ZaUWlSQ5lHZEnj1KqGiATinaEL3oRrylwJlylFWieDjAv3k5ZOeBTRZkYIZ5XZOuzCSAo3uxhwI8sWAPYwa1Q29efoJ55grdZdigUpA6XFx80DcvII0C0PpSuraSvQyGiirPSPNbKjfDE1WJIlZrmvGdTk5D5erBRMqOr+lOrJS0szNzUhCB9xMlmRMyHVsKmpOKSXNrOmmcL1imW3gpI4l5SzO4IzrBlYFbAIQH2wCkEAkctOqSnkrEiRyHEZaKadcxv2M7Bw1iFFtT4nD6FaUX5roBuAS71fdaKhKhCTPpgID2nadzxwXrVBS92DuBkZVFFSyUhFKiQoCJUUTdVz0u0oVZa7asniL/8ZMK+XUZZcLKAHggUzvTVxKbBT3usnLk9zqttTZiAUq8FddhUCQ923gOK+SVCWtlKsAXGql9yfDzeq3IOmEKxoWTRilVroK5im9i0tEaUWZvpcLPqlevqq8ShXdN6eE5TLVd5GUWtSMDaXNSSpbKpindKU9Bf6BRmrGdhW5xhyoqoxK4KWBxhdPSrHSZEUypFPDl3RmQ/KO0N2YA0Ge5vhjfvh+qBRbJPpJ1gp/AiB1OWOB2tO0Y8RJONP5LXoP50DpSuoeWpFAWe0Z6TejeOJ0v0gKUyqxodeLVaZj3M4lqWNufkuiQQ2JYW6G479Le4vr2FTUnFJKmuk97rIo3UBOmU6abeAkgSV1I87g7KAgb1rZsAlAfLAJQAKRyE2rbrI0+OQ4jLRSfg9RM+Bk52glr93A8mBdcmhUXMMmL09yv8Pfhba/ClKpnJpkauT6D5BkgeP9Uk45fS93A6PHpbogtwudDUopURUt6eGobqDqXAWCckWZq7ZwiQ1Vh6AJm8TN1N03pcRGca+bvjLZrZSbCGZU4EXVgLjhZo7zKgUSNFBW31WqpNHhZnVtJf65omzRTpRUfVbdH0ov464XlW2llUIu+KTVTFXVlwK6jEnhmQ1FbZLoJ4peRruBksqWqg5Tzjxn1pS3K5ywqeROcqSmFAUV3Er8865flEuW3tA7x6V0vDGZ52krvXzaWckRBlBVYkNlGDm3VloQUX/nWoF+8jXjmCsVA2KB2lu0u8QFypx3hpTgU7qSSq6kQJkWOdSekX4zan6L7hdpwFx1FmkxgKOf0K6ZCqolqWPv/FaOe7/lMGg6kTo+eW2luRn1m6H7ZYow26CSJNq1Yjs2TGIjdZcotUntQ+l6fcBQm6TfTJfP/IpgkrpRhyH+BECSN61s2AQgPtgEIIFI5KZVLW9aVec4jLRSTp0auYc+VRtQpi7S4J/iGl7dY7L7oJba/ipIpY6KUgtTBSj0vVzbfyOhKFCjFs5Q58ul4eNSQbUkz0YfIoqCIz0c1Q2UGuBIFWW9Uh8IZuFbJrGhgRdN2DhqE/0OaklceXW9ruox2Q1qJapMLFDXi9LLOK48J+35uSBVSekMqgsiyQSqQLnRi9luIirxzx8cPt93vaTqswp4aBeGS0RpQBmNikarmSpYkhI2peZx+UsT3eTq3+NOnYqmAh7aLeAGGqkXg+psSDSN0fPDnHL1XaWBRuXFcGN6jrt3XpvI87TV9aSdFSlIU4EkrVRzxQBaEFEBnXRcnGGWZK4VC1TlnybNHB2QKoKpJe0XSldS17YigbLaM9JvRlEX6X6RfBtUYkOvF0c/oW7nquAjOTfTuTT1uZIhHe0GquejNDejfjO0c5S1gp9toAmwei/XseEGzH+TxifNM9f6OxsVEaZQS5IE5hTBpMF5zt9AkjetbNgEID7YBCCBSOSmVTfOP5HglwuUN5NKOQ1Ctx/0P/Sp2oBKFqQhppe+CrfyVav+YaHqpz6L/vuSq6kKUChnnqv6UYoCbWVynQ1qEa++q0RtooZZKgB54kP+4ajOPU1WpIqySoIo93omY6izeudh3zUIBGVupu5SKSU2inpxfa+p7kNfomyNX7YDj3+wkOW56lDta9qF4Ya2OUOfT4VKIlWjUp8r0TRUoNz4pYluciclomqfdBg6L2r1WT2UaXeH4wjTgJJS0bghezqMrroF0vVSlK0ru09y3ysNaqrfFXWY5TpRVH+dCgJwTqErtoevl0oYmwo0DeqdoZJmSanlPyc9C1r0mRbVj0IlVLQLI0nHqvsGDdK4ewEdsldJnnRclNqkfrfSbyYWKEoVnfHh6ICccpaU4NP5LVXVl7oFNFBW3TDpN6MCZdpdkszzVGJDr1c0YQp1LiTnZnpc6nMlQzqldNawW7b7XSSlM1UMoJ0NiZKo3kOToGjeNOr+Ig03U8qW6nBVRJhCLWm2QSmC0cU9ZwDe30Bybq5s2AQgPtgEIIFI5KZVLU5KLeEMWmig/DAJqjkVA2qlroKKFoJDo2rlN+ud4wbCUtWP/rm6MXLybNQhkpqUcA/9tbvCx0X59Vxngx6XCpglahN9OKqASuIzqwo9vQZvC9QmVamnbWQusaFUGZowSdxMvYojJTaqNdw8fZqb2EjW8+qzJNqNAtW9plQkjirDGfqMW8gnAHRoW33uNa/yD1I626C6YY8I10slVH8Z9p3bdpcepKqSTM8vxxGWqGjckD3llKtrIM02UMqWChSlQU11XLQbxFHsqEoJpZdxdAaqUqK6IFKVlnLKVRIkDTT++6QD62/7TneDP6lKexsJ+NTnS1Va9edUFY0LZuj1ogpWHKhcpkoIpd9MLFCJD6VvLmTmSzizKEmUgc5vqQRfShaUgEPDbtlRfzNKipV2lyR6maq6024gRz+hXTNFg5Kkjrm5NClpVkIHjV+a6CaC0uC8urfSoF4yz1PHRZMgjtpEKVvq/iJ1l2gxIJrkNqVsqdU7i0+aOX8DiTZHixtqcXFBVcAmAPHBJgAJRCI3rap40WGmSd/72+O0okwl3biqH33g0dYvB1XJa/nadLcCfn8m/9BXgfJD7813JeJen+xvYZYQHWXq1MipTtChUqqxz3U26HGpG//vMvjgVg1fXtY1TMGR+Mzq4Um7FRKlRCUetELJJTa08koTG47aBMBDE4oUUD53MvD6XcZ0N/iTrOfp50UCNSqiMqcctWkho3ohadVT7rVKWqUqrQqUr3plsmefcVDUn4fem+8mYj0n8A9SRSlRlULpQUqHtmk3hlPWobMo6rtISdYrJ9Vyrnl1ihtQPTWKrz7T47osQoJNhxRpd4nzN6AqJSpQkKq0dPhSJfuSupEyY/t/r8+IGqSpgIt2Nrh7AU1EafWZk6Ol1EE1tHq54LRNdeUVZUvqBsYCFRzShHHeRn/STO/daj9Kalh0b6mqvvReSi+L9ptRXTM6NyN5uKiuNE0uOWEK2oWh14tTOqM0LHW/lQzpaNKsaDvS4Lx6ZlFFMInapI6LJkGcNw11cVcJozTbQIsBKtGtiNSxKvxJ961YZFs55+aKdH0rAzYBiA82AUggErVpaaWcZvycrCJ1VVVBYCDIG7SMIvrQKrFoJgwxqQf5zRkz3CrRfUN4FQP1oHt4xAL3BsZxGGlASYeZvljir8zQSjnVdOYqGPS4VFAtBV60OqYCOklPWwUmNAF5UzCeUZVkWnHighlKlaHJHUdnAOAJIiIdlzLBuq3fzKhVP/p5kXCU6JQrjf1AMAszmJYzVb1Qa8x8/oFLZ1HUA62xEKSp2YZrXp3iBp/S9VLH/ej7CyKaodGA0tuJ8ifYtBNFqWjcMB2l2KmukTTbQCl2qqou8bTpcUXqbFCOMk0uOf45vV7qvEpVWsopV58rydH+38nE/tY3ZhJ1I16OVlVGaReGo2lQAyZaVefUqGhVXSUYktM27WyoQFFy140FKpinSRiXNNNigOpIScEv/c2ooF4qBigBh1+9PCnqb+ZektCpz5cknNW9nc7YcPxz2pWmycLxYr/QAaVhqe8qFW+UxOy1PadElTpW5552KyRqk7pe9LtylC1KB1T/fmo3fm/RhC1aZ+NNOtsQpWum5E2pL4tEbaLHrhYXF1QFbAIQH2wCkEAkatNSLq+qxAeC/FAlreQp2k4gyBu00IqXCqol6T8aUKqH/h+Eqp+qID72wUJXy7kPI89GdZTVzTwQ5KkilFJCExuugkE5yipYl6hNfclQqaoSSXraKjB74sNFUTnl6qFM28icCg49LprYcNQmwN/GlYbO1GfdMSDXUzHWodvZRwJVvaDDZ1OZSvlcxql0lKBVT1Vl1LWVHqRK9/rXvaa6FBjperUl1ytS8EmpMs8STi1HP6FVWhpUcwkb7UQp6U7peik5v9+k5bjXWOJp032o6AqvTvDfkyhFge4tjqdNrxelonGGdNSzQCVMUjXz6dFL3GBHVeA7C3K0KoiiiRVXDKCJKA1UOQ16mrApapWU2NDKqwrSpG5gLFBdGkod5Oa36L1AJaxSUE+TS3XfkooBVMBB/Wak7q3ae3RvSwpuqitN6YCccRv9zVDaGjfnNI4clyo0ybTU8G8m2t5S+4TePyUTR3W9aGLDUbYovSxaZ4MmbO2jdDZox0btg+5f8bMNSrWJdpolapNKaulcGhcXVAVsAhAfbAKQQCRq0xaXhCte1PiDo1TQB/mrE1ZFfDhSgxjVWZCk/1RltnX/We5NR1IxCAdeC13+K8dhpBSF9JN8TilQnLsxfFxU+5jTZx5BVBRUgCJRm6hhVrTOhuIm/2PkIrdKJDlPqps8bSNzcnrzNoYrrzSx4ahNADxVqUBQ1tNWiU+7gXM8XHgduptlmWBABnh1ytWQcSDIt5yp6oVaUsWNdmzoteWCz25fhh/6KlCMdr3+OXJxRC+Ew2Qf0qSZ67DRThTt2OzK9ycAVM9bJdDSbINSy2mePi3qkD2lCEWi1VBVGbq3OJoGdZal9C7O4ZiaAtIKPwd631Ayu5IcrVKVocEnF8wcjKGzQYNPOlsQLbFRlXApUK4oaIL9KDmv3HwJ7cKozqFU/aZJszoH0bpL1/eaGh6MH8IfF73Hqc/nNOhpV5peAy6xoV1peg44miNNmtU+lLrSnU8Ww27qM839fUvKWeo3RWl7nDs9LbbRRJT7zVAFN9qZ5TobdC5N3Y+la0sV3NRvQqI2qXNP3c4lapPaU9SPgqMDVgVsAhAfbAKQQCRq0x4vDgdpaggyEMzCR0xARQMvVd0OBHmpRtryVpVPSSNbtRrbvjXb898cqDyjqlBy+syHjoUf5NQI6QNm6IweV69vwueAG2ikx6VmC6TEphdpj0frbFA1ncujDJWqShPlXXIUGCqBSYNqaTjrTo3HKfG06bFQNRwduvvoseISVk8d8FaU08g14FrOVM5PLcmsiupe06SVCz6pqozi60v8c9cobMwSt/rFKetQmULFKw4E+Y4NpWxR/i03gErl/FSw8iuBI/z8uPCMTbQhezokrB7qnGcArVB2I3uLkw+m+5DSoIpK/MEMrVDS781BJUlt35odVY5WBSaqWxII8t1A6nbecXT4GnDGbTRho8kzV6WlXgzR9lZFQelKNKjmumax+GFQt1h1jqXuUvDzsICD6kJIJlRKgeqZj5e6Ff5o81uUEsklNrQrrTpCgSDf5aTFALUPpeOic07R9paib9IZH86cktJS6awXR22i9wKaBOUf898/6fVS30G6trSzoRIbyZFaFa2owhQXFwBhF3eaLHBxQVXAJgDxwSYACUSiNi2tlNNAmdP+ppKKb08Lc3W5ISYqN6YCq6sEFQNVjWk/aI4b+EjybLTyqoajOIoCDbxo+507Lqqi0I+cA66zMZQMKaqbqTScRdvjj0TpbKjhrU5jlrjUJsl5UgUbdGiXuzFTPW/aBZGGsyjnWS2uak+9GNRD/0/MQ59K2amAp9GL2ewDj1aU6TXgqGiU86qWpCZCEzaatHJmaJRSoh7Q7QVDHSqnqZI3zuSNqpSo6nYgyMuWUprG/5HBdU5bn+5DRXGTZhtoMBNtyF4Fh8+OXRqxqr6O8N9pwsYFadSAqROZM+IMzmjSTIMVDipAuffdua7MpzTcrIoFNKjnqpnU66QzoURyg7XUj4LKIJ5gkksqxaqCWmm2oaKgHTa6X7j5EpqEqf0q0V9GkkBZzeNIxRsq4BCtyEGpNO58CXOkmELOAAAgAElEQVSPo8dFE2FucJ52b+n12rLff4+jtFTVlZaOy6WlvjEzqieIKgbQ2SVOwIHSUlWhKxDkqU20Y0MTG85pm3YDVcImdaVpUh3N7VxRqmhyK3mCqLkS2pXmfBuqAjYBiA82AUggErVpKfd68MxwoMwNZ1Ed5czccADCDTFRNQ+lQhKtovzHwd+6N2ZpiIlWylVV7xVm+JLqQ9NqKWeuReXhaLLA6TPTc6Qe6pd15dv+ilJ1Xc8pbuVR0mem1bFfRdE0p/KI9Bh1UNULSkHgqE0AP8jFBcqK8/rg8PkRA2Ua/NLFPXSpxwS9BhwVjVIUIh0/4JW9o0krZ66lKATtBs7x/DcH11Drk2UR3at/iOG4FvwQrmbSOQiuY0OHZRXVrKEw26ACk9vfnOVy8CWaBqUz0S6HDlr9poUDzlyLdmzocXHdIJo0U/UiDnT+JFqQpgYZ6RwGRwekg73quwSCvG8DrdLSIVzuN0OPhV6PUwGdV1CBXSDIz5fQ4o3qHEpBIr23q6BaogNSAQelstVeKHJcf7JK/OKXK13lLK57SwNlquA2mdlblF5Grxc3gErpm2ofSsdF6WWR5pyAcGLzn0+XR+xs0I4oDeo5bX3q9E2pgxx9k9Jt1d6SXIPpvB0VnuCg7vOU2iS50ytFPmomys0DVQVsAhAfbAKQQCRq01LuNb1Bchr0tPJKqw7cEBMNdpSpSiDIV8cojUSZj0ja+ipQ/r+Pl7ptR26IicqoUXdR7riouRe9mXK8Xxp40aCae+hTTjkdnOVAq63XRhnOUsEObQ1znNOxhPNKOzIctQmAp3qjFtdypkoxdB5AB2c+pJYOquZB9+FIJkijg9j0+DgMJEE/DWw4bX3a2VAJm0RFu4lUMxUli/N4oIOidG+Nnu8/LjqzQWk1XDBDPSaosgeXiNIkjSbbHNSwbPDzFRGDaqrtT5OsbGZmgxYOaDDDXQNqMker5hyoolGkawCEXaYpFY6rZtLEhnZspq3xV5+XkHNAh5u5zoY67ht657j3OGkIt6LwzpeEj4ubL6F+GKpzKPHf6d5SHRnpGtCAMlpng8rlXvOqXLyhx0UTG07qmJpg0ecM172l3UBFXZK6t/T3H21+i96vI3U2qHLWv8ncDLe3aFeadm83MpLb9N6u9pZkdvjkR+HnEDXV5KBmD6INbVPKVjQPl6qATQDig00AEohEbdo9BeFK+ajvtrgVDE6Bhqoo0P/m2uM08KLdAE6dgQ6SqsqM5BqsqkjdvlwZUZ+ZyqiNW7QtoqY5TRBo0My50FJ3X/pA4YIZNXx5Y3qOSz2QzHcoH5PSMDioSj0dFOU4px9oAaf6b856HoCH66kWp0BDK97qgcI5hdLgly6uE0SH3uiwHkftofQXtbgECICnOk0pANyQIJU0/ftHkRM2qvzzxwgVQkoToZ0LjrJFedqKCx8I8kZBKthJ7Zbt+a1xCbaq4P1l2Hceuh0HNRj44pcrI0q80m4FTci4mQ0qv0hnbPYz14D+ZqgbKwfKzY6mQa+UtV6bGA4SuWIApWHRbh9Hq1m8JXwOaJDEdTYo9YIa6UXDxJU/ou1bs1k5XEpzpPMt3HwJLd6oIE2iVilKV5OXJ7nnS+re0kq5orVIrsEqCXttYp5nn+mgg9g0EeYSG0pzpEUnrnhDCzYquZR8G2g34/Eoic3lJOi/iiQ5OmhXml4v7jdDrxctOnH3bpqAq46NRG3iigH3CDRH6oaunp+cNLWX2hR+JnHUpqqATQDig00AEohEbdof88OV8o8XbI0orUmDSEqb4XSn6c2WDl9xiibUJEs9HG9i+KmhUMh9iPSZuMbTDdBBKSVfLt3uefjooJVZeuPlBv9otZUOX3HHRR/6iqMruetSTeZorsGqUk/5sRznlD4YKB2IozYB8BjZqMXxzyk1hAYAOmjwSxc3C0Irr/QaZOb6A3uahKkl6YlTKVZ6vXYziQ2ll6mETaKiXU8UciJJvNIgkZqScTKBtO1PgxkuwU4nClP0OnMqIXcS5Sx1vaRElFZmaeKg41uiCEaLAdzMBv190ePiroEqALR8bbrnHsIN1tIh5UjVTKqWMyBnXcQhe9qFoV1OzmeDJkE0GeeKAVTRiPoyRAPd40B5wUbN8Ei0OU4QgCZhKvCTqsSqW/GbtByPKhMHKtqgupzc/Ba9Bv2nrouorU9nh+g8EKf0RX9TtODBdaV7kcSGHhfXNaOzTXQ2SEeptrciSWvSrjS9XpyAAf1N0X3IJTa0AKA6XNK8He1yRityUJd39Zvhnp9UcIN2+CSn7cqGTQDig00AEohEbVo6fDlu0baIg7X0Bks5pRw/VgVeDbtle4JProVJtf1VK5vjMNLhsHdmbHATB07RhLqqjl+2IyKvnnYo6HFxLUz64KDHxQ3WquHLmzNmeP5bB1XzeCtnfcTBWsCr1HJZBM8A2sqfQlrKekV58ZaD2HbgmMtrp1rOHP2EdiieJhQAilAo5Ak66OICH0opoe1vrrNBh3kjvQ/wDl9SuTyOS0u7MIoiIFVJVaDc4+tVrvIGd72odC7dWxz9ZHpe+M9pVX16np8ioCqIV/WY7OlEHWaqz3S+JDxYW34NQqEQ9h8pcoMgys1WtBaO+kCHSmkx4JOF/uCTzl5QzXKu8qk437e8PsNTgecodjRZUd+Vuwb09zVo+nofdXDVznz0yV6D5dsOeZIw+l2/WLIdoVAIM9bucauwdFCTUjq4pFkFx637z/K4zCoUlZSi6xcr0KZ/rocTTvd4r29W47Ku5feerBU/ehLsr7U5Jh20+6SqtNcJVWJ6Deg9RAkClJSWuQpOVNxA73KWloXw4dzNeH1ynqfT/M6MDRGlNakSE33mcPQTeo+hQTMnNKCKSzem53jogFxXmib1kdSoqIhGZu7GiJ4gtCtNO81v5fiPiwb99DnDJTbqXnBl90lu9+aK7nxng84zRKOiqWv03CfL3OcnN7NBFdxogYyjOVYFbAIQH2wCkEAkatNSK/XPF293W7MvfLbCVxmhXENKV5iyahdKSsvc9x8vLnUrDc3Tp3kCumfHLsXuw4WYvX4vRs/fggNHiz2UEjU4e2X3SQh+vgK/SZuK4OcrUFYW8jxERs7b7HJO9cHaktIyD/0ka8WPHjfD58ct9zykaYBCVSWUoklpWch9+NGKMh1unJ63Gzmrd2PR5gNutZJW/biHyIY9RzBn/T7Pg2HkvM3uINfv35yFuRv3IWf1bg+1Q1Efnvl4qRusP/fJMuTtOozPF29Hn+w1mLtxn6fNTQM29RApKS1zKzt0qcAqECzvFqiH/Zb9Rz0BbedPl3t03dUDfcv+o57AgVufL96OsrIQvt+Rj+935Hs+hwZh/aeuw9TVu/Hh3M2Yu2Eftuw/6j7wGpPvPmg6byhEda9pQJe98kd8vng71u8uwIy1e9yWvwoMFf3kl13Dgc+u/ELsOVzo+R30+ma157vfnzkPad+sxls563FTn2ke2UtaNec6FnQWhe6tb1bsRCgU8vweqWkZrbAfPOqvPtOghLpTl50M0NTvMhQKeTqA6pw07JaN60+6CCsVEhr0Ux42N1ibRnjkuonbn4fOw2eLt+Nw4QmPJHGrfjM9iU3GpDz8Ji0Hwc9XYNL3P2L+pv2eSj4d7h09fwv+PW4ZBk1fjxOlZR6KwpBZG91Et9OYJe4AtfpN00FSet8at3CbSye7rGt5AEePhVKbqLrQws0HPCpJdw2c7bmHbNhTgLxdhz2/l8tfnIidJ6Vfpd/Pbf1mev79eRv3u7+H3lmrUVoWcjsReiJOlZC6frECC34IB5W0Un/HgFxPdXnj3iNYu6sAN/WZhiYvT8J3m/Z7Zkqocg4QHnzW1/DZmzzdxuGzN+HQsWIUl5RhxfZDnsRmwvKdbvDJ0WpoIJ21IkwHUklU/rETmPT9j1i3u8DT/aJBNS1yFJ4o9aggPTh8vsfrYPO+oxj53RZMXb0bpWUhz/Nz5Hdb3KC5Vb+ZyDn5HgV6XPS7BoLlz1OquEb3IS0McN12NdR96xszPcWssQu24kRpGY4WlWDG2j04Xlzqdjmf+HChR8J156HjuDE9B+0HzXFnWNQzM+2b1e6cQ9NXJmP7wWN4e9p69JywGl8v3+k5B7Tbf1nX8k7nkFkbcZQRXags2AQgPiRNAlBUVIQXXngBl1xyCc4++2zceOONmDo1ersVAHbs2IEOHTrgvPPOw09+8hO0b98emzb5q3WO47Drtddei+s7V/Wm3X240K3eqjV+2Q63ra6Cptv6zXSpAOpGHAhmYeeh4271ueVr011ZsS37j6LZyYAjECyvDNFkIdJ6evQSz42PrsEzN3iG8r5ausOjKPL8uOWYt3G/R2ZQLcoT1Vef7DUerjEd1FI3cvrQVXKdv3p5kidQ1Vdm7ka3dfz7N2e53OZAsHxY7W8jFrjnj65vVux0b8z6avzSRI8kGw16Iq2re0z2DNkGguXVvbaa7r9aKkCiN/LGTKLwwmcr3KqayTV34z53FiXSuo6Yzrw9bT1KTyaJczfsQ6cxS9xrFQiWB8qcfCi3MibleQaR9x8p8vBw6Ro5b7M7BxFt6ZSo7JU/4sf84+j25Up8u2GfZ5BUv16BYDlXVw1wqz1yY3qOJ2D519ileGPyWpSUluHtaeuR9s1ql//ec8JqjyKWLvva65vVrppHxqQ8j6yhWuMWbvMldzRp/k1aDl6dsAob9x7BuzM3ej6jWe8cj3woXTem53goWq36zfTMbERaA3LWsbQwtajPx0fzNntMuyItmrBRmc1AsDxJpvKmlNIRCJbfS574cKF77tX689B5nvMn7fOvl+/0GGJxi3bCvt+R79Jq6NK9PRq/NNFzL1LrmY+X4pH3F7gBbCBYLhNKr0mk1WHIPE9FmfPqUGvkd1s899VIa8EPB8LdgpNytKVlIaRnr8Gf3p3riicEglmeIkcgmOV2vvT1x8HfepIn1UHeuPeIu//VeuT9BZ4ELtL6fPF2zz1HXcfM3I3uvJpaG/Yc8TwnA8HyYlnz9Gk+Q0bqdRAIlrs+z1m/DwePFnu8B/4w+Ft8s2Kn73tx9+5nxy4Vn7VTVu3yzGENnrnBpahGW7QwQBc37F1ZsAlAfEiaBOCBBx5ASkoKOnfujMzMTLRo0QIpKSmYM4cffFM4cuQILr/8ctSrVw8ZGRno378/GjRogEsvvRT793vpII7joHXr1hg1apRnxbvpqnLT7j9S5AvyAsFyyot009RXWVnIo2Wslh68PvHhIizUbmDS+vcny8RA6+kxS1yH3ECwnHZE1REirRlr97gGSNxSOupKEUJRcCKtP7071zMwqK+G3bLdCmqb/rmeYbZIa8nWgx6qSqT13CfLPA9saXUYOk+s9nPr2bFL3apxpJWevcb3cDKxlm496NKMIi06tNxvylpWxlStZr1zPGo0kdaGPUc8lIr+U9d5Okj0/BeVlHpmMSLtB0pFCQTLA6xeTHBxVY/JHnWuSKvla9M9VVC19IBUnSNa+Yy0Bk1f70ks1Bo6a6NLoaHnqyKfeVu/mb4Emy6avL88/nuRQqavD+duZt2h1aIV73GLtrk0iGhr/e4C9rqrRZ1nuWugr2t7TkHuur0eapO0xszf6qGXRFtb9x9zO4OR1qTvd3kM6SKtHl+v8sywRFodhsxzaVCqixQIlnfQqF9JIFheaOI8R7i1ed9RNyB+9P0F7J5Ui85kRFoPj1jgmZ8IBMtda7mCTN9JeR4hAWn9smt5h4R2kwNB72yIWs1656CsLOR2FiKtOwbkIv/4CU9XNhD0F5UCwXIxDGnuiq5GL2Zj/qb9nk6mft3p/3+ycKtHcjrSWrzloKuQpq+qUgWyCUB8SIoEYMGCBXAcB2+88Yb7WmFhIVJTU9GiRYuIfzcjIwOO42DhwrAubl5eHmrWrIlu3bp53us4Djp16mTse1flpqVVQLXGLdyGUCgkBuB0KZvxQ8eKfTd3JZmmVmbuRhQUnsC1Pae4A4vp2WvQc8Jq9JuyFu0GzkGz3uWuhPM27sehY8VuVafnhHBFUv/copJSrNtdwCYyal3fayoe+2AhjhWXYPfhQoxftgNHikp8lWBFJVJ29/uOFOGNyWvRpn+uOxOhr/5T16GktAz/GLkI17w6BTf0zkGXz5a7HOpAMKyJ3Pat2Wz1uf2gObhjQC5a9ZuJ63pOQb8paxEKhVBaFvK0yPUqolrPj1uO3HV78e9PluGJDxfiup5T8PSYJXh9cp4b7D8/brlLC+Ee/Jd1zfK9/tJXK1mt/UCwnG51zzvf4uERCzzzHMUlZdh/pAhj5m91aQHPfLzUZwYWCIal6tT6w+Bv8cSHi/CHwd/iHyMXobQshNx1e10Xzi6fLUf/qevw5EeLcGX3Sfhl1/KkhrbG9W6WvjqOXuzRDOfWkx8twncnH1J0YI9qdqtFOfxUsefp0Uvc634t6VAoXrZeSeYSuI6jF3voMJHW/3t9Bj5d5E8YueR80eYD2JVf6Evubuid4wt+FvxwAIUnSvGvsUs9e5pKLQaC5Z2XktKyClUIn/xoEUKhkNt5Grdwm0c9h5pphUIhHC484Tk///5kma96f9sbM3HoWDFCoZAnsKbV8fZEm/ybFTt9QVmfiWtwrLjEE5Bd9cpkHCsu8QV/78zYwCandL5DX23fmu3SkQCvHCVd1B02M3ejzxwv+PkKTFm1iw0qDx4tjtgRpIPc0SrazdOn4Ysl21F4ohTHiks81evUbtno/OlyfLJwq2dWqPtX33skO/V/d+nWg/jft2fj6TFLcKSoxEO9irSOFZe4Ve573vk24v3+4NFiz3dt+dp0dP1ihWtopZb67ar/b9Y7xzNw3jx9GobM2oh+U9biWHEJVmw/hKt6TMaV3SfhlfHf443Ja90k8o+Dv8VH8za7zsOhUMhDiaNdvUCwvNugKJihUAj7jhTh0LFivDfnBzfZbPRiNjqOXoxPF21zZ3p25Rd6OkdXvTLZ80x8/IOF2HnoOEKhELp8thy/ScvBld0n4dqeU9zf75+HzsMTHy5yRQUKCk+wnZh7tWJZ7rq9mL9pvyexe3jEAizfdsjTYfrHyPLf93tzfsAtr89A30l5niRFclI2DZsAxIekSAC6dOmCmjVr4vBhr1xWnz594DgOtm3zO3AqNGvWDM2aNfO93qZNG6SmpnpeUwnA8ePHUVjoV7OIFVW5aakU3pBZG7Fe04UvKwvhaFGJ+xAuPFGK4bM3ocOQeWjVb6aHh1hWFvIMcNIb9Mrt+S5vOf/YCVb2LxrUQ5E+dKk0ZGlZCD/mH8fcDfvw5pS1mPT9LlbVQQcdAlO8SE7JBoD7eRv2HMGQWRsxdsFWdigR8HKj1blQGvkb95ZXllVwFQlrdxVgQM46/LDvKApPlHq472pxChoKBYUnWNfIvQVFOF5cilnr9p6s8B3Exr3eCq5q167bXeA+VHYeOs4qzEhQx3eEmBUFgmHZvXW7C/DOjA2syVUklJV5ufAqOdITxPbvfIu8XYcxa91e5KzejZLSMpwoLUPw8xW4e9AcvDNjA+Zu2IfUbtm4/MWJrOSrohjRwHTsgq2+ocGDR4vxj5GL3I4AxbhF29Dty5UurzYUCnkqb2oAXq0+E9egqKQUoVAITQjlrtc3q/HBtz94jHYCwfJElEsu9QorlUndf6QIPb5ehR5fr3KvKa2g3z1ojs8BWp2Lbl+udM/5M+SB/sO+oxgyayOmrdmNxz5YiN+kTcVtb8zEyu35+OfIxWjVb6bLtS48UeoGTFT9SSkrUQGAY8UlWPDDAd/Q9uHCE8g/fsIne3roWLH7XpUsUFrjtDW7sXjLAdzzzre4Y0Au1u7y3vvmbtiHR99f4A5eF54oxasTVuGvw79Dn+w1KCktYyu3y7Ydcqlgb05dhw17CvDqhFWsMRrtmr0zYwMmrvwRI+dtRuGJUo/cIqVLfbMirELEVcFDoRAKCsv57ou3HMD4ZTtw6FgxWvefhTsG5HpmnrjOaf+p6/Dthn2YsmqXb45kV34hVu30K4cVlZTioffm47Z+M/Fj/nGWDsiJCADlv4Nl2w65++DQsWKs312Aw4UncO+7c9Hk5Umu5KTqDN3y+gwPDXXDniNuAUo5QBcUnnA/kyL/2AmMW7TNM0SrJDObp0/zVL1LGCndwhOlPh47NzysoKhA9HnI6f3r3/GbFTtZgQIFOmSrfuN/G8GrxVUEB44W49NF2zydA0pNenbsUvd8qDkkXWhgzvp9mLVuL+saT2lsnJpYZcAmAPEhKRKA22+/HU2aNPG9Pm3aNDiOgwkTJrB/r6ysDLVq1ULHjh19f9a9e3c4joOCgvDNzHEc1K1bF2eccQYcx0GTJk0wZsyYuL93VW5aXQnkVHGYaVVLxjGxQq+YBoK81GCsoAGPqpZLRi+xgM4FqIeVpLMcK3SeM+d/EA/ocHUgyA/bxYsSjfZytSBPFy9Uh4gGvMsYqTwJP+w7KiYhqnJMK+YTGaOrWEG7K3SOQR/wm7B8Jzp/utynllNaVl45XLzlQPlw/OFC/C5juociRwMlTm6TgxqY5IysVEeKVqk5JaNYQavcaumKUvGCoy1w6jCxghtwX7m9PEDWE0AJm/YeYZXDlI58j69XYTlxGqbBI3UgDgRlTwcJtGNl8j5CJSDV4iRRY4UaeKedKKWcU1YWwq78wgoVfXTQ4XRFX+KUfuKB3hkPBHkFn1hBu/eq6/bcJ34lpXjA0d2iFaoqAtVhl0wVTcMmAPEhKRKApk2bolWrVr7XV69eDcdxMHToUPbv7du3D47joFevXr4/Gzx4MBzHwdq1YanFli1b4q233sLXX3+NIUOG4KqrroLjOHj33Xejfsc9e/Zg1apVnjV+/Pgq27SK0mDqQVtWFvLRVCpiclMRvMhw56eujlxJqQho10KtJz7kLdFP9XPvFeQ8Y4XugPvSV2Ye3FReNRAsVxExCRqYKpqVKSgaAh2A3MwEVvGADthJQXo80BVATDzES0rLUHiilB0EjaVzI0F1HijP3EQirneIAsHyjosJcMPZXKcnVnAUHslbI1a0OMmf/s+nyzGfyIzSxCUUCnkq1pw+fiToMrqcH0I80O/Vl3Xl/RtiBcfB/4AxCIwVVOFIUdFMBalUVUwtyYE9FnzGzMWYGrClnbJAsHx42ARMJ1fRYBOA+JAUCUDDhg3Rtm1b3+ubNm2C4zgYMGAA+/e2bdsGx3GQkZHh+7MRI0bAcRwsWyY/pIuLi3HVVVfh/PPPx/Hj/hYkRY8ePUQVoarYtNEcAOMB5TsHgjKdJlZwmu9Uti5ebNrrH1zkNKljhU6nCQTL+eomoA9w9vja3F6hA8KmAgKFq0jlTtKcjhdK4YImGfnH5NZ8LOBUcFSl91TAzSKYupa3v+kdhG70YnZc1VEdimJFFUU4ekusCIX8xQPJzTdW/OdTPyVFcsGOBeOYmQsTnwuEXb7/OXKxp0u5eAufuMST3OlzHJKHRqx4WZP9vOZV3mcgVnAza5zbcaygKlMqsb0/08y9mlOj48wiYwX1c1GLc+eNB7oTfDPGiyceuFLMr5jt/kqwCUB8SIoEoKo6AByGDh0Kx3Giqg0lugOgqnmnwh3UoQ8z/mGwmeSCG0pevfPUH7bUlt1kJYX7XFPcR33Q0CRVh1JRMib53R5PBZRCw7mEngq4trWJqiMAltPM0TZixRKmS8QZucWDP2oKN5LZU6x4jBk8nbP+1LshADx0pUCwfJjQBDiZwy37T/36cbLC+ixBvFDzJg+PWOCR0jRxz1Pop1XU32NcqeOBfr5/29dMxfdjRmGJM8eLFXR4Xt1HTO097t5xxIAWPnWqVmtY7qlT8QD45EclF/RYQQesufkK07AJQHxIigSgqmYAOGRnZ8NxHHz99dcxf++q3LRqQOnp0UuMfaauJmAq6OXa7SYoHtzcAmdzHis46T5TFc3Z672V4/Rsc5X6FkS6rZ+hipIC7S6Yonco6MGjqbY1wKsmVZRPHwnrGS18U1VYnbZkqu3OKSEt3nLqnTgArvmgWs+ONaMWonPdA8Es7DFw/XQzs0AwyyekEC+UgWKHofOiOo3Hize1GQZTjq26pK2pLvCXS/20FxNdYE4z30QXGOBN0EwUJvT5j0CQN9+LB7pUthKvOFXQZ3gB41RuGjYBiA9JkQB07tyZVQFKT0+PqgJ0ww03sCpArVu3RsOGDaP+24MGDYLjOJg3L/Y2YlVu2psIz9QU7hrorR489sGp8+kBeJwF1TLRStU12QNB3pLdxOc+8r6ZTouuuW8iYVGgBjb9p64z9rkAPBKTsQ4sRgOlFwWC5dKbpkCN59SKpPxRUVDnZ7VGGKrC6vKfpqp41HRPLVO8d717GPxcVreKBbTyqJauYBIPVmz3B2FUEvdUoFyl7x40x1P55pRt4oV+XkzMcgB+dSFTv3Wu42KCipfDSLe++KWZuSpd5vRyQ4UJ6nBv+vrpxYMOQ8zQoegznFOmMw2bAMSHpEgA5s+f7/MBKCoqQqNGjdC8eXP3ta1btyIvzxtA9e3bF47jYNGicBtw7dq1qFmzJoLBoPva3r17ff9uQUEBUlNT8dOf/hTFxbErH1TlplV0j+5fmXPn07WDTXUXODMgUxxv3fWRSiWeCigfPRAs12g2ASqZGAiWa7KbAtVXf3vaqSdCFHRw9H/fNqsEofs03NTHzPA5ANZMq6IqL5GwjzH5GjN/q4Fv7FfNMlXF44bxTQW9v9fmFkzNQwydtdH3nXXZ0HjAuTSbqtCruZPW/Wfh/W/D3HcTajoKullVtgFlK8ArLx0IluvOmwBn8ibJi8aCb5lOTto3ZmiVulKUKfWzrfv9xQNT1++JD700P1MUYfoMj1X2OR7YBCA+JEUCAAAdOnRASkoKunTpgszMTLRs2RIpKSnIzQ3zj2+55RY4jveQVRBfr149vP766xgwYAAaNGiAn//8556gv2gjsRYAACAASURBVEePHrj22mvRvXt3DBs2DD179kQgEMAZZ5yB0aNHx/Wdq3LTKkMPkxQSaugTCJYbUJkA595qIggD/NXjj2JU0xA/VwtK//6RGV6pPmD8psFKPe3gmKKjKNAHgGkpOH34/LY3Zhr77BHa8OEvu2YZGag9yijfmBhqBPzcY1NVPM6xeOchM1VpvXvY19AMCh3yDATLB6JNgJMuNRXYPHdSMeV3GdM9xmYm5BgV9MTWBJ8eADI0wQZTnU+qhqRWJK38ioJzcjdFfxyiJZ+m1M90yeZAMAsz8vYY+Wx9cNnUPAR9huftMjfLIsEmAPEhaRKAwsJCdO7cGfXr10etWrXQrFkzTJ7szcC5BAAAtm/fjvvuuw/nnnsuzjnnHLRr1w4bNngDoqlTp6J169aoX78+zjzzTJx//vlo06YNpk+Pn29bVZu2rCxszGEygNQl90y1Uqnbq8kgDIDPEXXcIpkeFguaaZ/bcfRiI59L3WkDQTOUJQU6PDrEUCdEgT4A7jScAPy6l5c/bjLB0IcPf/WyGW+LUvIbVGvS92aqeDr32FQVj6NDHThqpip935C5lbKvdbWeqwxVYQ8cLfadC2q0dSoIe7TkeOQvTd3zAK8JYiBoxhsB8A8XK3OuUwVHuYrHVFLH6p2HfZ9rqvihSzbfYkj9jJsxU86+pwpdNcvULM6MvHAHZ6kBGd5osAlAfEiaBOB0RFVt2uPFYc33d2eaC/R06oGpVurcjd42bRNDQRgAj7twIJiFCct3Rv9LFYAyTVKr0xgzdKiDWuBhslJ/f2bYNMmUqoTCDNLCv2OAWRUgfYD0T4Y8FwC/7Or1vcwY5wHewehAMAsz15qp4umDr6aqeBwdyoS/AODvHmbmmrkvUVfuQNCcrCG9h6plYrgYCA+eX/XKZJdTb8pUUUHvbJnwRgD8tJd/GzKo4obmObO6WMFJQZuaxaFmfybve9yMWSzGh5GgDNfU6vqFmVkcqlw0d6OZZDMSbAIQH2wCkEBU1aal1asP52429rk69cCUrKFurGUyCKO890DQjMEYAI8rrclKih54mEzgaBBmShZQ4TvSwjedAOhdnAeHm1FcAoDJmua2SSOba171UpfmbzJTxdMHPE3tPU6Nq8yQ3KrePYzV2EqCPuRpyoMiFPJ3cExx9BWNJrVbthuQ/drgPQ8ARmrUKFMSo/psQTdDXWBuaN7E3vsx/7jvcz9eYGYWZ/wyb/HApOeOPrtmSoK2d5aX5vfqBDOxCFUuMkU3iwSbAMQHmwAkEFW1aXcQGsm4hWYoL4CfemCqOr3mR2+b1mQQ1l6zazela67bwJuSlivTqCOmKqWAdwDMhMsmxXLyADDtA6A73z7xoZmKN+A37Pr9m2ZkDQG/6+aK7WaqePrgq6kq3uj5XjUuk3Krz2jdQ1NUvDnrvd1Dk8mn7j9x1IDGO+B1p3127FLj9zzAT23bZGiYW+8SmfIp2VtQVCl779AxP5Xrq6U7jHy2btj1QKYZWWzAP7tmav5Ed1w25QdDlYuyVpihOkaCTQDig00AEoiq2rQb9oTbnl8borwAfuqBqSry5n1HKy0Io7SXQNCcrrn+uZ0Nyq1WxjkGgI6jw663piqwCnm7wkmcKW1whZv6eAPp//vYTMUb8Muu3jXQ3HwBVUYKBM3pyOuDr6aCMF2Ny6Tcqt49NEXFW7zFe/1MmRMCwPXa7ElxiRmDI9ppeXhEuSTobYakXBU+1WYjTEmM6oOvplTKjmhD86b2XuEJP5VrsgF3a8BfPHjU0EA04O96mpLW1BO4gYbU4Khy0WeGJEsjwSYA8cEmAAlEVW1aKiVpivIC+PmfpsxldmvOuqZkDQHg0ZOa22qt2mlG11z/XJNyq/RzTVbq/zU2XIU1JUmpQCtAtxtM4AC/hnyXz8wlW7rs6n1DzM0X3PmWV/nG1BCpPvhqKgjT1bhMyq3q3cMcQ/elVTu918+UOSHg33emhnRHEs309icd201L5+qzLQcNDXNT2dJAMAuDppsJIEs03rupvRcKhTweJYFgFnLX+SW+48FCrXhgSggCAH6X4d17psy13tNmQ4bPNjMLRpWLRhoyLYsEmwDEB5sAJBBVtWlX7zyMO9+ajVvfmGnETVFBr/58scRMpp9/3Kt6YDIIo1XvQNBcK1z/3N5ZZqqwAHD5ixMr5WZKFSDGGuLBKuwhSdxLX5nhBSv8tq/3YfjKeHPJli67asrRGfCqLgWCWdhbcOqqJoB/8NVUEKarcd1qUG5VN00yRcXThzxN+XEAwO3Eu+DyF83RoT4jnRYV6N1rcLAd8Dvgmhrm1qlFpgJIwHvfMyn1q1O5Fm4280zUiwemaKAA0Lq/1zfDhLcFAIyZ771+phyGC0+UYuS8zfh00TZj3iGRYBOA+GATgATidN+0uuyZKXOSohJvm9ZkEKa7m5rSNdc/901D2tIA8KuXww8sk5X6bsToqTKqNJm5G/HMx0uNOOlS6EpOfSaa87bQhwRN+TkAwF+Hf+f57COGOOT64KupIExX4zIp56p3D01R8fTr97QhNS4AuPtkdT4QNCcPCwBZK8KdFsX1NnnPA4BJ33v56aaGub9c6qWJmeoCA17DP5NSv7qMsCl3a0q1DQTNDUQDcDtDgaA5bwsA+GKJ9/qZchiuapzusVSiYBOABOJ037S67Jkpc5JQKIRfdq2cIEx3NzXVCtc/d/BMc3Kd1Pjqk4XmEoAeX69yP9e0ClBl4hZNcnVAjjlvC31I8BmD8wW662aJoSreXM3d1FQQpqtx/dEgn/7dmd7uoSkqnn79TM7i/HloeM7nOoPzENPWeBO4QDALTxq853H/hilM1GhiprrAgHfY36TUr07l2rDHTIVaN4vrZUgWG/DuPVMOw4D/+pkq4lU1TvdYKlGwCUACcbpvWl32zKTeL616/8uQrCEApGnupqbcNvXPfd8gV5+ajJkcqEonNAyT8qKVjdu0YdqhBk3M9CHBFz4zo6gDeF03TVJIlmiBuimHYV2NyySf/gONO26Kiqdfv5cN0sMeIXM+pvwFAH8CFwiaHWwHgFnagKopUL+PQDALEw0GkNRbxaTU7239vPePHYa6wPuPeJWLTMliA3CHwwNBcw7DgNewy2QRr6pxusdSiYJNABKI033T6rJnJh3/qNmTySBMd640Ncinf65JTj2tWJkK7gCv06tJh+HKRivtAf6RQQUjvfvU42tzv83OZObCZBVPD9RNOQzralwm+fR699AUFU8f8uyTbY4e9tSo8JyPSZlOPYELBM0OtgP+JMMUqOFTIJiFGYbM7QCvt4pJqd//fds7jG/K3fpYsVe5yNQsDgD8c2R475lyGAb818+Uw3BV43SPpRIFmwAkEKf7pp293ltVyttlxlwG8Aa9JoMwKnv2y67mHoS6nJopbWnAW/E2KeNKTXxMVqsqG3QYMxA0pyGvQLtPJucLXibKNyareHqgbspheFe+V43LJJ9e7x6aouIBQGPiuNx/qjl6GJ3zMTmUunqnN4ELBM0OtgPAgh+8CjWmoNPEvjNkbgd4vVVMdkTufXeu5zubGojWPVtMDkQ/90l475n0ttCvnymH4arG6R5LJQo2AUggTvdNq8uebd531Nhn/54Eea9NNCNrCAAjiOyZyQRghCanNul7M9rSgNe92KSpCuVhm6yUVjZ0N2dTGvIKdEjQ5HwBVb4xWcXTZXNNOQznH/OqcT0/zlxVWndcNkXFA4AruocTAJP0MDrnY9Lc7gctgTOdeAL+LoMpUL8P0wHkA5nhoXmTHRHqgB4ImhuIBrySzSYHort+Ed57Jr0t9OtnymG4qnG6x1KJgk0AEojTfdPqsme7D5sxJwGAtkQz3SQ9RZetq6zPnWVIWxoA7hoYPhem6B2A14DIZJelskGpAYGgOQ15BUo/MxlAUuUbkwGkLptrymFY59OblHPVOemmqHiANwEwSQ/rnRWe8zFpEKd3WkwnngCwcrv3Xm0KevfJZAD5+AfhoXmTHZEnPlzkfu4V3c3N4gDeBMCkok7PCeG9Z3IWZ8t+7/Uz5TBc1TjdY6lEwSYACcTpvmn1m4dJuUcqezYs11wrVa88moJutGPSb+Evw8KVsCmGXCsBYMOegkr5vpWNtpqh1rcbzA2fA17XzQ/nbjb2udQ3w6S5XalGPTD1ENf59Ca9LZZvO1Qpv0MAuObVsGqWSXrYm2TOx2QVVlcuCgSzMMRg4gn450RMQe8+bT9oLoCkPiUmOyL/93HYANGkmhPgTQBMKurQeS2TszgFhd7iwf4jZrxJqhqneyyVKNgEIIE43TetPvRksopHB7VM8t51zqMp6DrbK7ebkTUEvA8sk0PAADBn/T6jSUVVgHZEAsEsLN5ibvgc8CYA36wwt/fGki5R+0HmEgDAG3gcKzbjLwB4TZP6GfS20ANHk2j6Slg/3mQnblhuuGN2zzvmEgC902I68QS8yb5JBariEq9jb3GJGWlbwDs0P8KgTHGXz8Kfa3KYG/D+Dk0ZjAHAyHlhzx2TErGhkLd4YPIZXpU43WOpRMEmAAlEMmzaynqIU5qHyRvpjkPHK+U765SGDXvMtcKpXr/JwbLTFdSQKRDMwuqd5obPAeA64rtgik4DeJVYWvefZexzgcr7HdJg+p0Z5rwtSkrLKu07UxWnbQfMVaS/Jo7L7Q0mAHqnJRDMwriFZgfbaQJQmUGvSTxDCh8mz8crZBi/Vb+Zxj4X8J6LH/PNKFsBXrdvk4pIQOVdv6pEMsRSiYBNABKIZNi0lXXzCH6+wv3cLfvNDRfTilXPCeYoDfM3eeXUTAYeVDHF5BDw6Yr2RB0kEMzCDwaHzwHgUaL3bkoiEPDypU228YGqSQBMVmGB8HfuMGSe0c8dND2sblVqcMCTSibebbiDQzstgaDZricAbN0fNqnq+oW5WQ6g8vZeZm6YMmeyCESH8U3OcgBek0KTe28m8Vsw6TAM2ASgOsMmAAlEMmza1yfn4bKu5lvW+48U4f7MeUbdFBWm5+3G65PzcKTIHFVixXYvp3mfQS5lKBRCj69XoesXK4w+VE5X/GGwNwHYlW9u+BwAth04hjvfmm00QQTKr+M/Ri5Cs945xpOW7JU/4ppXpyAz1yx3nCYAY+ab87YAyjsiL3650pgRk0LhiVK8/+0PRn1JAK/Tq2nfDKo8FQianfVR6DspD09+tMjofQ8opz/e+sZMjF9mTvoYKL+OncYsQdo3q41SU+gwvkmHYaB82PqW12fgTYN0OQA4UVqGuwbOxm/ScoyKbQDlxasnP1pknEpZlUiGWCoRsAlAApEsm7ag0Nzw7+mK9bsLPA/wo4YfshZh/EnT8T50zFyVvipQWTzbyvhcmgCYnj85HfHRvM146auVRmVLAa/vSSCYhdnrzc0uWHhBh/HvG2I2AahMhEIhlJSam7FIJiRLLFXVsAlAAmE3bfJg24Fjnge4rdRXHu4b4k0ATAdjFmFQUzSTErQWXtymuVsvMkh5sfDiw7mbT8sEwEKGjaXig00AEgi7aZMH+44UJQWX8nRAh6Hz3PN8WdfTV7nidABNAGYYchi28IOqngWCWfh+hzkVMQsvPlm41SYASQYbS8UHmwAkEHbTJg+OFpXYBKCKcH9mOAFo8vKkRH+dpAalAH1nyGHYwo97NVrbxr1HEv2VkhZUVMH0ALpFYmBjqfiQNAlAUVERXnjhBVxyySU4++yzceONN2Lq1KkV+rs7duxAhw4dcN555+EnP/kJ2rdvj02beLnF9957D1deeSVq1aqFRo0aYeDAgXF/Z7tpkwe6GZNF5YEao13fq2K/cYv4QKUYTUrbWnjx4PD5nvuH6cFoizCoos4Ln61I9NexMAAbS8WHpEkAHnjgAaSkpKBz587IzMxEixYtkJKSgjlzIsu1HTlyBJdffjnq1auHjIwM9O/fHw0aNMCll16K/fu9Fa+hQ4fCcRzce++9GDZsGP72t7/BcRz07ds3ru9sN21yoePoxQgEs9BpzJJEf5WkBg2Wbnl9RqK/TlJj+bZDeCDzO+MSoBZe/HPkYk8CYFJ+1sKLwhOl+Pe4ZbhjQK6lWiUJbCwVH5IiAViwYAEcx8Ebb7zhvlZYWIjU1FS0aNEi4t/NyMiA4zhYuDCsy52Xl4eaNWuiW7du7mvHjx/HRRddhLvuusvz9x988EHUrVsXBw/GLqFlN21yIRQKYcv+o1apoZLx0HvhBMC0HruFRSJA3WkDwSwcL7aD7RYWFYWNpeJDUiQAXbp0Qc2aNXH4sNcRtE+fPnAcB9u2yS6CzZo1Q7NmzXyvt2nTBqmpqe7/Z2dnw3EcZGdne943b948OI6DUaNGxfy97aa1sIgdD48IG3U9OHx+or+OhcUpo3fWak8CUGZVxCwsKgwbS8WHpEgAbr/9djRp0sT3+rRp0+A4DiZMmMD+vbKyMtSqVQsdO3b0/Vn37t3hOA4KCsp5r71794bjONizx6uEUVxcjBo1auD555+P+XvbTWthETuoU2/H0YsT/XUsLE4Z1L34l13tDJGFRSywsVR8SIoEoGnTpmjVqpXv9dWrV8NxHAwdOpT9e/v27YPjOOjVq5fvzwYPHgzHcbB2bbmjX6dOnVCzZk32cy6++GI88MADEb/jnj17sGrVKs8aP3683bQWFjHi8Q8WusFS8HM7xGdx+uOjeZs9HQALC4uKwyYA8SEpEoCGDRuibdu2vtc3bdoEx3EwYMAA9u9t27YNjuMgIyPD92cjRoyA4zhYtmwZAODxxx9H7dq12c9p0KAB7rnnnojfsUePHnAch11201pYVBzPfbLMDZTenLI20V/HwuKUMXnVLndP39RnWqK/joXFaQWbAMSHpEgAbAfAwqL6YN3uAjw9egn+PW4Zdh8uTPTXsbA4ZZwoLcOrE1bhsQ8WInfd3kR/HQuL0wo2AYgPSZEA2BkACwsLCwsLC4vqBxtLxYekSAA6d+7MqgClp6dHVQG64YYbWBWg1q1bo2HDhu7/Z2VlsSpAc+fOheM4GDlyZMzf225aCwsLCwsLC4v4YWOp+JAUCcD8+fN9PgBFRUVo1KgRmjdv7r62detW5OXlef5u37594TgOFi1a5L62du1a1KxZE8Fg0H3t+PHjuPDCC9GuXTvP33/ooYdQp04dHDhwIObvbTethYWFhYWFhUX8sLFUfEiKBAAAOnTogJSUFHTp0gWZmZlo2bIlUlJSkJub677nlltugeN4D7mgoACpqamoV68eXn/9dQwYMAANGjTAz3/+c+zd6+ViqrmA++67D8OHD8fDDz8Mx3GQnp4e13e2m9bCwsLCwsLCIn7YWCo+JE0CUFhYiM6dO6N+/fqoVasWmjVrhsmTJ3vewyUAALB9+3bcd999OPfcc3HOOeegXbt22LBhA/vvDBs2DFdccQXOOusspKamYsCAAQiF4jNtsZvWwsLCwsLCwiJ+2FgqPiRNAnA6wm5aCwsLCwsLC4v4YWOp+GATgATCbloLCwsLCwsLi/hhY6n4YBOABGLJkiVwHAfjx4/3eQTYZZdddtlll1122RV5KU+lJUuWJDqsO61gE4AEQm1au+yyyy677LLLLrviX+PHj090WHdawSYACcShQ4cwfvx4LFmypMoyZNttsOfInid7jv5blj1P9hzZ82TP0amuJUuWYPz48Th06FCiw7rTCjYBqCZYtcpy5KLBnqOKwZ6n6LDnqGKw5yk67DmqGOx5ig57jiwobAJQTWB/+NFhz1HFYM9TdNhzVDHY8xQd9hxVDPY8RYc9RxYUNgGoJrA//Oiw56hisOcpOuw5qhjseYoOe44qBnueosOeIwsKmwBUE9gffnTYc1Qx2PMUHfYcVQz2PEWHPUcVgz1P0WHPkQWFTQCqCfbs2YMePXpgz549if4q/7Ww56hisOcpOuw5qhjseYoOe44qBnueosOeIwsKmwBYWFhYWFhYWFhYVCPYBMDCwsLCwsLCwsKiGsEmABYWFhYWFhYWFhbVCDYBsLCwsLCwsLCwsKhGsAmAhYWFhYWFhYWFRTWCTQCSHEVFRXjhhRdwySWX4Oyzz8aNN96IqVOnJvprVToWLlyITp064Ve/+hXq1KmDBg0aoEOHDli3bp3vvWvWrMEdd9yBunXr4oILLsBDDz2EvXv3+t5XVlaGjIwMXHbZZahVqxauvvpqfPzxx1VxOFWG3r17w3EcNG3a1Pdnc+fOxW9/+1vUrl0bP/vZz/DMM8/gyJEjvvcl655bsmQJ7r77blxwwQWoXbs2mjZtirffftvznup8jtavX4/7778fv/jFL1C7dm1cccUV6NmzJ44dO+Z5X3U5R0eOHMErr7yCO+64AxdccAEcx8EHH3zAvrcy7kEV/cxEoiLnqKysDB988AHuvvtuXHrppahTpw6aNm2KtLQ0FBYWsp/73nvv4corr0StWrXQqFEjDBw4kH3fjh070KFDB5x33nn4yU9+gvbt22PTpk2mD/OUEcteUjhx4gSaNGkCx3Hwxhtv+P482faSReywCUCS44EHHkBKSgo6d+6MzMxMtGjRAikpKZgzZ06iv1ql4t5770X9+vXxzDPPYPjw4UhLS8PPfvYz1K1bF99//737vu3bt+OnP/0pUlNT8fbbbyM9PR0XXHABrr32WhQXF3s+s2vXrnAcB3//+98xbNgw3HXXXXAcB2PHjq3qw6sUbN++HXXq1EHdunV9CcCyZctw9tln49e//jWGDBmCl156CbVq1cKdd97p+5xk3HNTpkzBWWedhebNm6N///4YNmwYgsEgunTp4r6nOp+jbdu24fzzz0cgEMBrr72GzMxMPProo3AcB+3bt3ffV53O0ebNm+E4Dv7nf/4Ht956qxi0VcY9KJbPTCQqco6OHDkCx3Fw0003oXfv3hg2bBgee+wx1KhRA7feeitCoZDn/UOHDoXjOLj33nsxbNgw/O1vf4PjOOjbt6/vcy+//HLUq1cPGRkZ6N+/Pxo0aIBLL70U+/fvr+xDjwkV3UsUb775JurWrSsmAMm2lyxih00AkhgLFizw/fgLCwuRmpqKFi1aJPCbVT7mzp3ruzmtX78etWrVwoMPPui+1rFjR9SuXRtbt251X8vJyYHjOMjMzHRf27FjB84880x06tTJfS0UCuHmm2/GpZdeitLS0ko8mqrB/fffj1atWuGWW27xJQBt27bFJZdcgsOHD7uvDR8+HI7jYMqUKe5rybjnDh8+jJ/97Gf44x//iLKyMvF91fkcpaenswZDDz/8MBzHwcGDBwFUr3NUVFSEXbt2AQAWLVokBm2VcQ+q6GcmGhU5R8XFxZg7d67v7/bs2ROO4yAnJ8d97fjx47joootw1113ed774IMPom7duu4+BICMjAw4joOFCxe6r+Xl5aFmzZro1q2bicMzhoruJYU9e/bgvPPOQ69evdgEIBn3kkXssAlAEqNLly6oWbOm52ELAH369IHjONi2bVuCvlnicP311+P66693/79evXro0KGD732NGzfG73//e/f/Bw8eDMdxsHr1as/7Pv74YziOc9pUJSXk5uaiZs2aWLlypS8BOHz4MFJSUjzVbqD8wXzOOefgiSeecF9Lxj03ZMgQOI6DNWvWAACOHj3qSwSq+zkKBoNwHAf79u3zvV6jRg0cPXq0Wp+jSEFbZdyDKvqZ/02oSGBLsXLlSjiO46H3ZGdnw3EcZGdne947b948OI6DUaNGua81a9YMzZo1831umzZtkJqaGt9BVAEqcp4ee+wx3Hjjjfjhhx/YBCDZ95JFxWATgCTG7bffjiZNmvhenzZtGhzHwYQJExLwrRKHUCiEX/ziF2jTpg2A8iqI4zjIyMjwvfehhx7ChRde6P7/k08+ibp16/razRs3bvQ9hE43lJaW4pprrsE///lPAPAlAN9++y0cx8G4ceN8f/d3v/udJ6FKxj1377334txzz0VOTg4aN24Mx3FQt25dPPXUUy4Hubqfo0mTJrl0n2XLlmHbtm345JNPcO655+K5554DUL3PkRS0VcY9KJbP/G9CrAnA1KlT4TiOh7euZph0p9vi4mLUqFEDzz//PIBy/nutWrXQsWNH3+d2794djuOgoKAg/oOpREQ7TwsWLECNGjUwb948lzqkJwDJvpcsKgabACQxmjZtilatWvleX716NRzHwdChQxPwrRKHUaNGwXEcjBgxAkD4Rjpy5Ejfe7t06QLHcVBUVAQAuOuuu9CwYUPf+44dOwbHcdC1a9fK/fKViHfeeQfnnXeeO9SlJwCfffYZHMfB7NmzfX+3Q4cOqF+/vvv/ybjnrrnmGtSpUwd16tTBM888gy+++ALPPPMMHMfBAw88AMCeIwBIS0tD7dq14TiOu1566SX3z6vzOZKCtsq4B8Xymf9NiDUBuP3223Huuefi0KFD7mudOnVCzZo12fdffPHF7u913759cBwHvXr18r1PVcfXrl0b+0FUASKdp1AohBtvvBF/+ctfAEBMAJJ9L1lUDDYBSGI0bNgQbdu29b2+adMmOI6DAQMGJOBbJQZ5eXk499xz0aJFC5ffOHv2bLEi+fLLL8NxHPfh0qpVK7YiWVZWBsdx8Oyzz1buAVQS9u/fjwsvvBD9+vVzX9MTgJEjR8JxHCxYsMD39//2t7/hvPPOc/8/Gfdcw4YN4TgOnnrqKc/r//znP+E4DtavX1/tzxFQnmDfcccdGDZsGL744gs8/vjjOOOMMzBo0CAA1XsfSUFbZdyDYvnM/ybEkgComZN3333X8/rjjz+O2rVrs3+nQYMGuOeeewCUD61Lle0RI0bAcRwsW7Ys9oOoAkQ6T++//z5q167tUuSkBCDZ95JFxWATgCRGslXR4sWuXbvQsGFDNGjQADt37nRftx0A4KmnnkKjRo08A9O2A+BF06ZN4TgOcnNzPa/n5ubCcRx89NFH1f4cjR07FrVr18b27ds9rz/66KOoU6cO9u/fQeUDhAAABqhJREFUX63Pke0AREdFE4BPPvkEZ5xxhmdmRKE6dwCUWMErr7zivmY7ABaRYBOAJEay8WjjQX5+Pq677jpceOGFvoGnWPm3derUSaoZgPXr16NGjRoYOHAgNm/e7K7mzZujcePG2Lx5Mw4cOFCtudsA0Lp1azYgyMvLg+M4eOutt6r9Obr55pvRsmVL3+tffvklHKdcqaU6nyNTMwAVuQedrrztiiQAU6dOxVlnnYV27dqhpKTE9+fVeQbg5ZdfxgUXXIDVq1e79/I5c+bAcRy8+OKL2Lx5s1voSfa9ZFEx2AQgidG5c2dWSUO1T083JY1YUVhYiJtvvhl16tTBvHnz2PdcfPHFosIBrUC+8847cBy/asKYMWPEquZ/O2bOnOnha3Pr2WefRX5+fkT1lscff9x9LRn3nNLLnj59uuf16dOnw3EcjBkzptqfo8aNG6N58+a+18eNGwfHcTBp0qRqfY4iBbeVcQ+q6Gf+NyFaAjB//nzUrVsXLVu2xPHjx9n3ZGVlwXH8KkBz5871VbJvuOEGVgWodevWbHX8vwXSeXrkkUei3s8VrSnZ95JFxWATgCTG/Pnzfe2/oqIiNGrUiH1YJxNKS0vRvn17pKSk+B4GFE899ZSHMwmEq4xDhgxxX9u+fbuom/yLX/zitPQB2LdvH7766ivfatq0Kf7nf/4HX331FVauXAkAuPPOO3HJJZd4qmLvvfeeG9wpJOOeW7p0KRzHwV//+lfP63/5y1+QkpLi0sqq8zlq164dzjrrLJ/T9h/+8AfUqFGj2p+jSMFtZdyDKvqZ/02IdI7WrFmDiy66CE2bNvVo+es4fvw4LrzwQrRr187z+kMPPYQ6dergwIED7mt9+/aF4zhYtGiR+9ratWtRs2ZNBIPBUz+gSoJ0npYsWeK7l2dmZsJxHDz66KP46quvkJ+fDyD595JFxWATgCRHhw4d3KpbZmYmWrZsiZSUFB+fOdnw7LPPwnEc3H333Rg1apRvKWzbtg0XXXQRUlNTMXDgQPTp0wcXXHABrr76ah+3UXEe//GPf2D48OGuc+KYMWOq+vAqFZwR2JIlS1CrVi2Pg+vZZ5/tSqpSJOOee/zxx+E4Dv785z9j8ODB6NChAxzH8RgGVedzpHwk6tWrh169emHw4MFo27YtHMfBk08+6b6vup2jQYMGIS0tDR07doTjOPjTn/6EtLQ0pKWlucFYZdyDYvnMRCPaOSooKECDBg1Qo0YN9O3b13cv17u7isN/3333Yfjw4a4ZXXp6uud9BQUFSE1NRb169fD6669jwIABaNCgAX7+85+7imj/TajIXtIhzQAAybmXLGKDTQCSHIWFhejcuTPq16+PWrVqoVmzZpg8eXKiv1al45ZbbonYCqVYtWoV2rRpgzp16uD888/Hgw8+iN27d/s+s6ysDH369EEgEMBZZ52Fpk2bYvTo0VV1SFUGLgEAgDlz5qBly5Y4++yzcfHFF6NTp04sTzYZ99yJEyfw6quvIhAI4Mwzz0SjRo1YJZrqfI4WLFiAtm3bon79+jjzzDPRuHFjpKen+7ja1ekcBQIB8R60efNm932VcQ+q6GcmGtHOkQpipfXII4/4PnPYsGG44oorcNZZZyE1NRUDBgzw8d2B8kr4fffdh3PPPRfnnHMO2rVrhw0bNlTBUceOiu4likgJQDLuJYvYYBMACwsLCwsLCwsLi2oEmwBYWFhYWFhYWFhYVCPYBMDCwsLCwsLCwsKiGsEmABYWFhYWFhYWFhbVCDYBsLCwsLCwsLCwsKhGsAmAhYWFhYWFhYWFRTWCTQAsLCwsLCwsLCwsqhFsAmBhYWFhYWFhYWFRjWATAAsLCwsLCwsLC4tqBJsAWFhYWFhYWFhYWFQj2ATAwsLCwsLCwsLCohrBJgAWFhYWFhYWFhYW1Qg2AbCwsLCwsLCwsLCoRrAJgIWFhYWFhYWFhUU1gk0ALCwsLCwsLCwsLKoRbAJgYWFhYWFhYWFhUY1gEwALCwsLCwsLCwuLagSbAFhYWFhYWFhYWFhUI9gEwMLCwsLCwsLCwqIawSYAFhYWFhYWFhYWFtUINgGwsLCwsLCwsLCwqEawCYCFhYWFhYWFhYVFNYJNACwsLCwsLCwsLCyqEWwCYGFhYWFhYWFhYVGNYBMACwsLCwsLCwuL/99+HQgAAAAACPK3HuSyiBEBAACAEQEAAIARAQAAgBEBAACAEQEAAIARAQAAgBEBAACAEQEAAIARAQAAgBEBAACAEQEAAIARAQAAgBEBAACAkQCPX1Vdq1lSWwAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff81c62ca58>]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Display the profile of the smoothed image: the center is easy to measure thanks to the smoothness of the signal\n",
    "fig,ax = subplots(2)\n",
    "ax[0].plot(my_smooth[:,545])\n",
    "ax[1].plot(my_smooth[536,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Peak picking\n",
    "\n",
    "We use the watershed module from *pyFAI* to retrieve all peak positions.\n",
    "Those regions are sieved out respectively for:\n",
    "\n",
    "* their size, it should be larger than the kernel itself\n",
    "* the peaks too close to masked regions are removed\n",
    "* the intensity of the peak\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of region segmented: 82126\n",
      "Number of large enough regions : 41333\n"
     ]
    }
   ],
   "source": [
    "iw = InverseWatershed(my_smooth)\n",
    "iw.init()\n",
    "iw.merge_singleton()\n",
    "all_regions = set(iw.regions.values())\n",
    "\n",
    "regions = [i for i in all_regions if i.size>mini]\n",
    "\n",
    "print(\"Number of region segmented: %s\"%len(all_regions))\n",
    "print(\"Number of large enough regions : %s\"%len(regions))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of peaks not on masked areea : 30001\n"
     ]
    }
   ],
   "source": [
    "#Remove peaks on masked region\n",
    "sieved_region = [i for i in regions if not big_mask[(i.index//nimg.shape[-1], i.index%nimg.shape[-1])]]\n",
    "print(\"Number of peaks not on masked areea : %s\"%len(sieved_region))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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,iVBORw0KGgoAAAANSUhEUgAAAwAAAAJACAYAAAA6rgFWAAAgAElEQVR4nO3dfayfdXnA/7v0wOkDU8qTILC6ljERSdEIrihRq1KQaTJdFxO6LJnAYEQxrkUWQTI76jqTKSCDwggbUAiabQV/bgxZjGU6kXWarKBTCKHFYHGmPExblPb6/eGP8/N4TrE99Hyu7319X6/k/qN373P3HO7rW653H77tAgAAGBpd9icAAAC0IwAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICING2bdti/fr1sXHjxti0aZPD4XA4HA6HYy+OjRs3xvr162Pbtm3Za12vCIBE69evj67rHA6Hw+FwOBwv4Vi/fn32WtcrAiDRxo0bx4Y2u6AdDofD4XA4+na88IupGzduzF7rekUAJNq0aVN0XRebNm3K/lQAAHrHLjU1AiCRoQUAmDq71NQIgESGFgBg6uxSUyMAEhlaAICps0tNjQBIZGgBAKbOLjU1AiCRoQUAmDq71NQIgESGFgBg6uxSUyMAEhlaAICps0tNjQBIZGgBAKbOLjU1AiCRoQUAmDq71NQIgESGFgBg6uxSUyMAEhlaAICps0tNjQBIZGgBAKbOLjU1AiCRoQUAmDq71NQIgESGFgBg6uxSUyMAEhlaAICps0tNjQBIZGgBAKbOLjU1AiCRoQUAmDq71NQIgESGFgBg6uxSUyMAElUZ2vkf/X8mHAAA063KLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtXaQATAN77xjbjwwgvjNa95TcyZMyeOOeaYWLZsWfzP//zPhGsfeuihWLp0acydOzfmzZsXy5cvjyeffHLCdTt37ow1a9bEq171qhgdHY0TTzwxbrvttkl//Om4556oMrQCAADIUGWXam0gAuB973tfHHHEEfHBD34wbrjhhli1alW84hWviLlz58Z///d/j123ZcuWOPTQQ2PhwoVx5ZVXxhVXXBHz5s2LRYsWxXPPPTfunpdcckl0XRfnnntuXH/99XHWWWdF13Vx++23j7tuOu65p6oMrQAAADJU2aVaG4gA+OpXvzph2f7ud78bo6OjcfbZZ4+du+CCC2L27Nnx2GOPjZ370pe+FF3Xxdq1a8fOPf7447H//vvHhRdeOHZu165dcdppp8XRRx8dzz///LTec09VGVoBAABkqLJLtTYQAbA7r3/96+P1r3/92LcPP/zwWLZs2YTrjjvuuHj7298+9u1rrrkmuq6LBx98cNx1t912W3RdF/fdd9+03nNPVRlaAQAAZKiyS7U2sAGwa9euOOqoo+L000+PiJ//CnzXdbFmzZoJ1y5fvjwOPvjgsW+fc845MXfu3Ni1a9e46x5++OHoui6uuuqqabvn3qgytAIAAMhQZZdqbWAD4JZbbomu6+LGG2+MiIgHHngguq6Lm2++ecK1K1eujK7rYseOHRERcdZZZ8WCBQsmXPfjH/84uq6LSy65ZNruuTtbt26NTZs2jTvWr19fYmgFAACQQQBMzUAGwLe//e142cteFosXLx77s/UbNmyIruvijjvumHD9ZZddFl3XxbZt2yIiYsmSJXH88cdPuG7nzp3RdV1cdNFF03bP3bn88suj67pJj74PrQAAADIIgKkZuAB44oknYsGCBXHMMcfE97///bHzfgdgcAkAACCDAJiagQqAp556Kk466aQ4+OCDJ/xl27398/pz5szZ538HYE/uuTeqDK0AAAAyVNmlWhuYANi+fXucdtppMWfOnPja17426TWHHXbYbt+xZ8mSJWPf/uxnPzvpO/asW7cuuq6LDRs2TOs991SVoRUAAECGKrtUawMRAM8//3y85z3viZGRkfjiF7+42+vOP//8mD17dmzevHns3L333htd18W11147dm7Lli27fc/+o446atx79k/HPfdUlaEVAABAhiq7VGsDEQAXXXRRdF0X7373u+OWW26ZcLxg8+bNccghh8TChQvjqquuitWrV8e8efPixBNPHPuz+i944c/wn3feeXHDDTeM/au969atG3fddNxzT1UZWgEAAGSosku1NhAB8Ja3vGW375DTdeM/xU2bNsXpp58ec+bMiYMOOijOPvvs+MEPfjDhnjt37ozVq1fH/Pnz44ADDogTTjghbr311kl//Om4556oMrQCAADIUGWXam0gAmBYVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7U2MAHw7LPPxsc//vFYunRpzJs3L7qui5tuumnCdX/4h38YXddNOH7rt35rwrU7d+6MNWvWxKte9aoYHR2NE088MW677bZJf/yHHnooli5dGnPnzo158+bF8uXL48knn3xJ9/xVqgytAAAAMlTZpVobmAB49NFHo+u6+PVf//V461vf+qIBMDo6Grfccsu446677ppw7SWXXBJd18W5554b119/fZx11lnRdV3cfvvt467bsmVLHHroobFw4cK48sor44orroh58+bFokWL4rnnnpvSPfdElaEVAABAhiq7VGsDEwA7duyIJ554IiIiHnjggRcNgLlz5/7K+z3++OOx//77x4UXXjh2bteuXXHaaafF0UcfHc8///zY+QsuuCBmz54djz322Ni5L33pS9F1Xaxdu3ZK99wTVYZWAAAAGarsUq0NTAD8oj0JgOeffz6efvrp3d7jmmuuia7r4sEHHxx3/rbbbouu6+K+++4bO3f44YfHsmXLJtzjuOOOi7e//e1TuueeqDK0AgAAyFBll2qtlwEwY8aMmDNnTnRdF/PmzYs/+ZM/iWeffXbcdeecc07MnTs3du3aNe78ww8/HF3XxVVXXRURP/9V/a7rYs2aNRN+rOXLl8fBBx+81/fcU1WGVgAAABmq7FKt9S4ALrnkkvjoRz8ad9xxR9x+++1jfyn4TW96U/zsZz8bu+6ss86KBQsWTPj4H//4x9F1XVxyySXjfqybb755wrUrV66Mrutix44de3XPyWzdujU2bdo07li/fn2JoRUAAEAGATA1vQuAyVxxxRUT/iLukiVL4vjjj59w7c6dO6PrurjooosiImLDhg3RdV3ccccdE6697LLLouu62LZt217dczKXX375pO9eVGFoBQAAkEEATE2JAPjJT34S++23X3zgAx8YO+d3ANoRAABABgEwNSUCICLisMMOi9/93d8d+/Y555wTc+bM2ed/B2BP7rmnqgytAAAAMlTZpVorEQDPPPNMzJgxI84777yxc5/97GcnfceedevWRdd1sWHDhrFzhx122G7fBWjJkiVTuueeqDK0AgAAyFBll2qtVwGwffv2eOaZZyZc/8If1fnHf/zHsXNbtmzZ7Xv2H3XUUePes//888+P2bNnx+bNm8fO3XvvvdF1XVx77bVTuueeqDK0AgAAyFBll2ptoALg6quvjlWrVsUFF1wQXdfFe9/73li1alWsWrUqnnrqqXj00UfjoIMOigsuuCCuvPLKuPLKK+Nd73pXdF0XZ5xxRuzcuXPc/V4Ig/POOy9uuOGGsX+1d926deOu27x5cxxyyCGxcOHCuOqqq2L16tUxb968OPHEE8f+/P/e3nNPVBlaAQAAZKiyS7U2UAEwf/783b5TzqOPPhrbtm2L5cuXx7HHHhtz5syJ0dHROOGEE2L16tXx05/+dML9du7cGatXr4758+fHAQccECeccELceuutk/7YmzZtitNPPz3mzJkTBx10UJx99tnxgx/84CXd81epMrQCAADIUGWXam2gAmDYVBlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7UmABJVGVoBAABkqLJLtSYAElUZWgEAAGSosku1JgASVRlaAQAAZKiyS7U2MAHw7LPPxsc//vFYunRpzJs3L7qui5tuumnSax966KFYunRpzJ07N+bNmxfLly+PJ598csJ1O3fujDVr1sSrXvWqGB0djRNPPDFuu+22Zvf8VaoMrQAAADJU2aVaG5gAePTRR6Pruvj1X//1eOtb37rbANiyZUsceuihsXDhwrjyyivjiiuuiHnz5sWiRYviueeeG3ftJZdcEl3XxbnnnhvXX399nHXWWdF1Xdx+++3Tfs89UWVoBQAAkKHKLtXawATAjh074oknnoiIiAceeGC3AXDBBRfE7Nmz47HHHhs796UvfSm6rou1a9eOnXv88cdj//33jwsvvHDs3K5du+K0006Lo48+Op5//vlpveeeqDK0AgAAyFBll2ptYALgF71YABx++OGxbNmyCeePO+64ePvb3z727WuuuSa6rosHH3xw3HW33XZbdF0X991337Tec09UGVoBAABkqLJLtdarAHj88cej67pYs2bNhI9Zvnx5HHzwwWPfPuecc2Lu3Lmxa9eucdc9/PDD0XVdXHXVVdN2zz1VZWgFAACQocou1VqvAuCF8zfffPOEj1m5cmV0XRc7duyIiIizzjorFixYMOG6H//4x9F1XVxyySXTds/JbN26NTZt2jTuWL9+fYmhFQAAQAYBMDW9CoANGzZE13Vxxx13TPiYyy67LLqui23btkVExJIlS+L444+fcN3OnTuj67q46KKLpu2ek7n88suj67pJj74PrQAAADIIgKnpVQD4HYDBJAAAgAwCYGp6FQB7++f158yZs8//DsCe3HNPVRlaAQAAZKiyS7XWqwCIiDjssMN2+449S5YsGfv2Zz/72UnfsWfdunXRdV1s2LBhWu+5J6oMrQAAADJU2aVa610AnH/++TF79uzYvHnz2Ll77703uq6La6+9duzcli1bdvue/UcdddS49+yfjnvuiSpDKwAAgAxVdqnWBioArr766li1alVccMEF0XVdvPe9741Vq1bFqlWr4qmnnoqIiM2bN8chhxwSCxcujKuuuipWr14d8+bNixNPPHHsz+q/4IU/w3/eeefFDTfcMPav9q5bt27cddNxzz1RZWgFAACQocou1dpABcD8+fN3+045jz766Nh1mzZtitNPPz3mzJkTBx10UJx99tnxgx/8YML9du7cGatXr4758+fHAQccECeccELceuutk/7Y03HPX6XK0AoAACBDlV2qtYEKgGFTZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1ZoASFRlaAUAAJChyi7VmgBIVGVoBQAAkKHKLtWaAEhUZWgFAACQocou1VrvAuDLX/5ydF036fEf//Ef46796le/Gm9605ti9uzZ8YpXvCI++MEPxrPPPjvhnjt27IiLL744jjzyyJg1a1accsopcc8990z64+/pPfdElaEVAABAhiq7VGu9DYAPfehDccstt4w7fvjDH45d981vfjNmzZoVr3vd6+Laa6+Nj33sYzE6OhpnnHHGhHu+//3vj5GRkVixYkWsXbs2Fi9eHCMjI3HfffeNu25v7rknqgytAAAAMlTZpVrrbQB8/vOff9HrzjzzzDjyyCPj6aefHjt3ww03RNd18a//+q9j5+6///7oui4+9alPjZ3bvn17LFy4MBYvXjyle+6pKkMrAACADNxyZ7oAABPrSURBVFV2qdZ6HQDPPPNM/OxnP5twzdNPPx0jIyOxcuXKceefe+65OPDAA+MDH/jA2LmVK1fGzJkzxy31ERGrV6+Oruti8+bNe33PPVVlaAUAAJChyi7VWm8D4MADD4yu62LmzJnx1re+NR544IGxa/793/89uq6LO+64Y8LHv/nNb47Xv/71Y99+xzveEccff/yE6+69997oui7uuuuuvb7nnqoytAIAAMhQZZdqrXcB8NWvfjXe9773xY033hh33nlnfPKTn4xDDjkkZs2aFf/1X/8VERGf//zno+u62LBhw4SPX7ZsWRxxxBFj3z7hhBNiyZIlE6578MEHo+u6uO666/b6npPZunVrbNq0adyxfv36EkMrAACADAJganoXAJP53ve+F7Nnz46lS5dGRMTNN98cXdfF/fffP+HaP/iDP4iXv/zlY99esGBBnHnmmROue+SRR6Lruvj0pz+91/eczOWXX77bdy/q+9AKAAAggwCYmhIBEPHzd/I54IAD4vnnn/c7AI0JAAAggwCYmjIBsHLlyui6Lp5++ml/B6AxAQAAZKiyS7VWJgDe9773xaxZs2Lnzp3x1FNPveg79vzRH/3R2LkVK1ZM+i5AV1xxxbh3Adqbe+6pKkMrAACADFV2qdZ6FwBPPvnkhHPf+ta3Yv/994/3vOc9Y+fOOOOMOPLII+OZZ54ZO/e3f/u30XVd/Mu//MvYua9//esT/h2AHTt2xLHHHhtvfOMbx/04e3rPPVVlaAUAAJChyi7VWu8C4G1ve1u8613vir/4i7+I66+/Pj784Q/HnDlz4uUvf3k89NBDY9dt3LgxRkdHx/2rvbNmzYrTTz99wj2XLVs29qv7a9eujVNPPTVGRkbiK1/5yrjr9uaee6LK0AoAACBDlV2qtd4FwJVXXhmnnHJKHHzwwTEyMhJHHnlkLF++PL73ve9NuPa+++6LU089NWbNmhWHHXZYXHjhheN+9f4F27dvjxUrVsQRRxwRo6OjcfLJJ8fdd9896Y+/p/fcE1WGVgAAABmq7FKt9S4AKqkytAIAAMhQZZdqTQAkqjK0AgAAyFBll2pNACSqMrQCAADIUGWXak0AJKoytAIAAMhQZZdqTQAkqjK0AgAAyFBll2pNACSqMrQCAADIUGWXak0AJKoytAIAAMhQZZdqTQAkqjK0AgAAyFBll2pNACSqMrQCAADIUGWXak0AJKoytAIAAMhQZZdqTQAkqjK0AgAAyFBll2pNACSqMrQCAADIUGWXak0AJOrb0E626O/uAACYbn3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrR7EwDCAACYbn3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IAJOrb0AoAAGCQ9G2XGhQCIFHfhlYAAACDpG+71KAQAIn6NrQCAAAYJH3bpQaFAEjUt6EVAADAIOnbLjUoBECivg2tAAAABknfdqlBIQAS9W1oBQAAMEj6tksNCgGQqG9DKwAAgEHSt11qUAiARH0bWgEAAAySvu1Sg0IA7KUdO3bExRdfHEceeWTMmjUrTjnllLjnnnumdK++Da0AAAAGSd92qUEhAPbS+9///hgZGYkVK1bE2rVrY/HixTEyMhL33XffXt+rb0MrAACAQdK3XWpQCIC9cP/990fXdfGpT31q7Nz27dtj4cKFsXjx4r2+X9+GVgAAwHj74v+N/l85dX3bpQaFANgLK1eujJkzZ8bTTz897vzq1auj67rYvHnzXt2vb0M7HT/J+YkOgEEzXf+/8//Qfa9vu9SgEAB74R3veEccf/zxE87fe++90XVd3HXXXXt1v74NrZ+8AOir7EV9kI8+69suNSgEwF444YQTYsmSJRPOP/jgg9F1XVx33XW7/ditW7fGpk2bxh2f+9znouu6WL9+/YTvyz6O/KNrBvLI/u/icDgcjhc/sv8/4Riu/9+uX78+uq6LjRs3TucKWI4A2AsLFiyIM888c8L5Rx55JLqui09/+tO7/djLL788uq5zOBwOh8PhcOzjY/369dO5ApYjAPbCvv4dgK997Wvxd3/3d7Fx48bUah7E34FweI7DdniONQ7PscbhOfbn2LhxY6xfvz62bds2nStgOQJgL+zrvwOQbdMmf26uAs+xBs+xBs+xBs+R6gTAXlixYsWk7wJ0xRVXRNft/bsAZfMTXA2eYw2eYw2eYw2eI9UJgL3w9a9/Pbpu/L8DsGPHjjj22GPjjW98Y+JnNjV+gqvBc6zBc6zBc6zBc6Q6AbCXli1bFiMjI7Fy5cpYu3ZtnHrqqTEyMhJf+cpXsj+1veYnuBo8xxo8xxo8xxo8R6oTAHtp+/btsWLFijjiiCNidHQ0Tj755Lj77ruzP60p2bp1a1x++eWxdevW7E+Fl8BzrMFzrMFzrMFzpDoBAAAAQ0QAAADAEBEAAAAwRAQAAAAMEQEAAABDRAD03I4dO+Liiy+OI488MmbNmhWnnHJK3HPPPXv0sY8//ngsW7YsXv7yl8ev/dqvxXve85545JFHJlzXdd2kxyc/+cl9/eUMrak+x+985zvx4Q9/OBYvXhyjo6PRdV08+uiju73+zjvvjNe97nUxOjoaxxxzTHz84x+Pn/3sZ/vwKxluLZ7j/PnzJ309/vEf//E+/mqG11Sf4z/8wz/E7//+78dv/MZvxOzZs+O4446Lj3zkI7Ft27ZJr/d6nD4tnqHXIn0mAHru/e9/f4yMjMSKFSti7dq1sXjx4hgZGYn77rvvRT/u2Wefjd/8zd+Mww8/PNasWRN//dd/Hcccc0wcffTR8b//+7/jru26Lt75znfGLbfcMu7w/sj7zlSf40033RT77bdfvPa1r42TTjrpRRfHf/7nf44ZM2bE2972trj++uvjgx/8YOy3335x/vnnT8NXNJxaPMf58+fHSSedNOH1eP/990/DVzScpvocDznkkDjxxBPjsssuixtuuCE+9KEPxQEHHBCvfvWr4yc/+cm4a70ep1eLZ+i1SJ8JgB67//77J/zLxNu3b4+FCxfG4sWLX/Rj16xZE13XxTe+8Y2xc9/+9rdj5syZ8Wd/9mfjru26Li688MJ9+8kz5qU8xx/96EfxzDPPRETEpz71qRddHF/zmtfEokWLxv0K48c+9rGYMWNGfPvb337pX8iQa/Uc58+fH2edddY++7wZ76U8xy9/+csTzv393/99dF0XN9xww7jzXo/Tp9Uz9FqkzwRAj61cuTJmzpwZTz/99Ljzq1evjq7rYvPmzbv92JNPPjlOPvnkCedPP/30WLhw4bhzLwTAT37yk9i+ffu++eQZ81Ke4y96scXxwQcfjK7r4pprrhl3/vvf/350XRerVq2a8ufPz7V4jhH//9Lx3HPPxf/93/+91E+bX7KvnuMLnnnmmei6Lj7ykY+MnfN6nF4tnmGE1yL9JgB67B3veEccf/zxE87fe++90XVd3HXXXZN+3M6dO2N0dDQuuOCCCd936aWXRtd1Y78aGfHzAJg7d27MmDEjuq6L448/PtatW7fvvpAhN9Xn+MtebHG89dZbo+u6SX9r+uijj473vve9e/15M16L5xjx86Vj9uzZMXPmzOi6LubPnx+f+cxnXsqnzi/YV8/xBd/97nej67pYvXr12Dmvx+nV4hlGeC3SbwKgx0444YRYsmTJhPMv/OrSddddN+nH/fCHP4yu6+ITn/jEhO+75pprouu6+M53vjN27tRTT43PfOYzceedd8a1114br33ta6Pruvibv/mbfffFDLGpPsdf9mKL4wvfN9mvfJ188snx27/923v9eTNei+cYEfHud7871qxZE+vXr48bb7wxTjvttOi6Li6++OKX8unz/9lXz/EFH/jAB2LmzJnx3e9+d+yc1+P0avEMI7wW6TcB0GMLFiyIM888c8L5Rx55JLqui09/+tOTftzmzZuj67pYs2bNhO+78cYbo+u6+OY3v7nbH/e5556L1772tXHQQQdN+EtR7L2pPsdf9mKL4yc+8Ynoui62bt064ftOO+20WLRo0V5/3ozX4jlOZteuXbF06dIYGRmJLVu27M2nzCT21XOMiFi3bt2kC6HX4/Rq8Qwn47VInwiAHmv1OwCTue6666Lrul/5jgr8an4HoIZWvwMwmbvvvju6rotbbrlljz+Gye2r57hhw4aYNWtWLF26dMJbe3o9Tq8Wz3B3vBbpCwHQY63+DsBkvvjFL0bXdXHnnXdO7ZNnjL8DUEOrvwMwmRcWmyuvvHKPP4bJ7Yvn+K1vfSsOOuigeMMb3hDPPvvshO/3epxeLZ7h7ngt0hcCoMdWrFgx6TsdXHHFFb/ynQ7e8IY3TPouQO985ztjwYIFv/LHvvrqq6Pruvja1762958447yU5/iLXmxx3LRp04u+68hkvxvE3mnxHHfnC1/4QnRdF7fddtvefMpM4qU+x4cffjiOOOKIOO644+LJJ5+c9Bqvx+nV4hnujtcifSEAeuzrX//6hPc63rFjRxx77LHxxje+cezcY489NuF9pf/yL/8yuq6LBx54YOzcd77znZg5c2Z89KMfHTs32U9+zzzzTCxcuDAOPfTQeO655/bllzSUXspz/EW/anF89atfHYsWLYrnn39+7Nyll14aM2bMiIceeuilfyFDrsVz/NGPfjTu+UVE/PSnP403velNccABB8QTTzzx0r+QIfdSnuMTTzwRCxYsiFe+8pW/MuC8HqdPi2fotUjfCYCeW7ZsWYyMjMTKlStj7dq1ceqpp8bIyEh85StfGbvmLW95S3Td+Ef9whJ/+OGHx1/91V/Fpz/96TjmmGPila985bil//LLL49FixbFpZdeGtdff338+Z//ecyfPz9mzJgRt956a7Ovs7qpPsennnoqVq1aFatWrYozzjgjuq6LP/3TP41Vq1bF1VdfPe7aL3zhCzFjxoxYsmRJXH/99fGhD30o9ttvvzj33HObfI3DYLqf40033RQLFy6Mj370o3HdddfF6tWrx96V65ffopCpm+pzXLRo0dhfGP3lfx32nnvuGXet1+P0mu5n6LVI3wmAntu+fXusWLEijjjiiBgdHY2TTz457r777nHXTPaTXETEli1b4vd+7/fiZS97WRx44IHxO7/zO/G9731v3DX33HNPvPOd74wjjjgi9t9//zjooIPi9NNPj3/7t3+b1q9r2Ez1OT766KPRdd2kx/z58yf8OP/0T/8UJ510UoyOjsbRRx8dl156afz0pz+dzi9tqEz3c/zP//zPePe73x1HHXVUHHDAAXHggQfGm9/85vjc5z7X4ssbGlN9jrt7hl3XxVve8pYJP47X4/SZ7mfotUjfCQAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIaIAAAAgCEiAAAAYIgIAAAAGCICAAAAhogAAACAISIAAABgiAgAAAAYIgIAAACGiAAAAIAhIgAAAGCICAAAABgiAgAAAIbI/wtj8dt7bV6+XwAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(array([1.0000e+00, 0.0000e+00, 1.0000e+01, 3.9940e+03, 2.2274e+04,\n",
       "        1.4800e+03, 1.1700e+02, 3.4000e+01, 8.0000e+00, 2.0000e+00,\n",
       "        2.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 1.0000e+00,\n",
       "        1.0000e+00, 0.0000e+00, 0.0000e+00, 1.0000e+00, 0.0000e+00,\n",
       "        1.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 1.0000e+00,\n",
       "        0.0000e+00, 1.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        1.0000e+00, 2.0000e+00, 2.0000e+00, 1.0000e+00, 0.0000e+00,\n",
       "        1.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 0.0000e+00, 0.0000e+00, 1.0000e+00, 0.0000e+00,\n",
       "        1.0000e+00, 3.0000e+00, 1.0000e+00, 2.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 2.0000e+00, 1.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 1.0000e+00, 0.0000e+00, 0.0000e+00, 2.0000e+00,\n",
       "        0.0000e+00, 0.0000e+00, 2.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        2.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 1.0000e+00, 1.0000e+00, 3.0000e+00, 3.0000e+00,\n",
       "        7.0000e+00, 1.0000e+01, 1.0000e+01, 2.1000e+01, 1.9000e+01,\n",
       "        2.9000e+01, 3.5000e+01, 5.7000e+01, 7.3000e+01, 9.9000e+01,\n",
       "        1.1800e+02, 1.5900e+02, 1.9400e+02, 1.9500e+02, 1.9700e+02,\n",
       "        1.9500e+02, 1.6300e+02, 1.6200e+02, 1.0200e+02, 8.1000e+01,\n",
       "        6.6000e+01, 3.9000e+01, 7.0000e+00, 1.0000e+00, 1.0000e+00]),\n",
       " array([0.04771975, 0.05009548, 0.05247121, 0.05484694, 0.05722266,\n",
       "        0.05959839, 0.06197412, 0.06434985, 0.06672558, 0.06910131,\n",
       "        0.07147704, 0.07385276, 0.07622849, 0.07860422, 0.08097995,\n",
       "        0.08335568, 0.08573141, 0.08810713, 0.09048286, 0.09285859,\n",
       "        0.09523432, 0.09761005, 0.09998578, 0.1023615 , 0.10473723,\n",
       "        0.10711296, 0.10948869, 0.11186442, 0.11424015, 0.11661588,\n",
       "        0.1189916 , 0.12136733, 0.12374306, 0.12611879, 0.12849452,\n",
       "        0.13087025, 0.13324597, 0.1356217 , 0.13799743, 0.14037316,\n",
       "        0.14274889, 0.14512462, 0.14750035, 0.14987607, 0.1522518 ,\n",
       "        0.15462753, 0.15700326, 0.15937899, 0.16175472, 0.16413044,\n",
       "        0.16650617, 0.1688819 , 0.17125763, 0.17363336, 0.17600909,\n",
       "        0.17838482, 0.18076054, 0.18313627, 0.185512  , 0.18788773,\n",
       "        0.19026346, 0.19263919, 0.19501491, 0.19739064, 0.19976637,\n",
       "        0.2021421 , 0.20451783, 0.20689356, 0.20926929, 0.21164501,\n",
       "        0.21402074, 0.21639647, 0.2187722 , 0.22114793, 0.22352366,\n",
       "        0.22589938, 0.22827511, 0.23065084, 0.23302657, 0.2354023 ,\n",
       "        0.23777803, 0.24015376, 0.24252948, 0.24490521, 0.24728094,\n",
       "        0.24965667, 0.2520324 , 0.25440813, 0.25678385, 0.25915958,\n",
       "        0.26153531, 0.26391104, 0.26628677, 0.2686625 , 0.27103822,\n",
       "        0.27341395, 0.27578968, 0.27816541, 0.28054114, 0.28291687,\n",
       "        0.2852926 ]),\n",
       " <a list of 100 Patch objects>)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Histogram of peak height:\n",
    "s = numpy.array([i.maxi for i in sieved_region])\n",
    "\n",
    "fig, ax = subplots()\n",
    "ax.hist(s, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of remaining peaks with I>0.1: 2075\n"
     ]
    }
   ],
   "source": [
    "#sieve-out for peak intensity\n",
    "int_mini = 0.1\n",
    "peaks = [(i.index//nimg.shape[-1], i.index%nimg.shape[-1]) for i in sieved_region if (i.maxi)>int_mini]\n",
    "print(\"Number of remaining peaks with I>%s: %s\"%(int_mini, len(peaks)))\n",
    "\n",
    "peaks_raw = numpy.array(peaks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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,iVBORw0KGgoAAAANSUhEUgAAAwAAAAJACAYAAAA6rgFWAAAgAElEQVR4nOx9eVwV57n/y2ETNcEVAVEE1EMEZFFAOGznwOGggiKCS4wxiY1LbNXgBoogAiKL3bI3bZPc9Kb31/trk16XNF2Su7RJkzZtFhOTfpouN02sbW+b301bkxjz/f3xzvPODGdmjhqNVp7v53M+wDzzvjNzmHnnWb+PAIPBYDAYDAaDwRg2EJf7BBgMBoPBYDAYDMYnBzYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGAwGg8FgMBiMYQQ2ABgMBoPBYDAYjGEENgAYDAaDwWAwGIxhBDYAGIyrCB0dHRBC4Kmnnrrcp3LB+PWvfw0hBNasWXO5T+Wiory8HEKc35L7wAMPQAiBBx544NKc1MfAn/70J4wdOxYbN268rOexZs0aCCHw61//+rKex5WCC3l+ruT77JPEE088gaKiIsTGxkIIgcWLFwO4sGf3k0BycjKSk5NN2w4dOoSIiAicOHHi8pwU4x8GV94dzbjqIIQI+fk4CuuVrgAIIVBeXv6JHIsNgCsXVkrEU089BSEEOjo6LMdcyYrZpk2bMGLECLz11luX9Tyu9Of/kwYbABeGX//61xgxYgTi4+Nx++23o6OjA1//+tcB/GMZAH//+9+RkJCAhQsXXp6TYvzD4Mq7oxlXHUjJ7+josP18nJf3la4AsAFwfrhaDYDf/va3QV65UAbAO++8gxMnTuCdd975BM7w3PHb3/4WERERuPXWWy/3qVzxz/8nDTYALgz3338/hBD453/+5yCZ1bN7JcDKAACAvr4+CCHwox/96JM/KcY/DNgAYFxykAFwqXClKwBsAJwfrlYDwAqhDIArFbt3775iFIwr/fn/pMEGwIWhs7PzH27ttDMA3nrrLbhcLqxateqTPynGPwzYAGBccpyPAfCrX/0KsbGxGDt2LH7zm9+YZH/961+Rnp4Ol8ulFmm7lCLjokjh2/fffx+dnZ2YOXMmoqKi1AvynXfeQX9/P7xeLyZPnozIyEhMmDABdXV1ePrpp23P9cSJE7j55puRnJyMqKgoTJw4ESUlJbj77rsB6C9Vq89Qhe/HP/4xli5dikmTJiEyMhJJSUlYt26dbXrFT3/6UwQCAYwePRrXXHMNKisr8fTTT5+3AUDK0xtvvIFDhw7B7XYjOjoakydPxtatW/H//t//sxz35ptvYtOmTUhJSUFUVBTGjRuHuro6PPfcc0H7vvXWW+js7ERxcbG6voSEBKxcuRKvvPJK0P52CszZs2exefNmCCGwZMkS/P3vf3e8NuM8J06cwOLFizF27FiMHDkSHo8HTzzxhOW49957D729vcjMzERMTAyuueYalJSU4P/8n/9juf+3v/1t+Hw+xMfHIyoqCgkJCSgrK8Ndd91l2m9oGgF9904pcU6K2U9/+lM0NDRg4sSJiIqKwtSpU7Fx40a8/fbbQfsaleR7770XmZmZiI6ORlxcHG699dbzijB89NFHSEhIwJQpUyzlxnvqi1/8IrKysjBixIggI/g73/kO5s+fj/HjxyMqKgqpqanYvn07/vKXv1jO+73vfQ8lJSUYOXIkxo4di8WLF+PEiRMX1QAgY/3kyZNYu3YtEhMT4XK51Pf/+uuvY9euXZgzZw4mTJigvvdbb70Vb775pmmu1157DUIIXH/99abtv/rVr9T/+T//8z9Nsp07d0IIgR/84AcXfA0Xct/b3WdOzgun7/1817PzxcW8x8gId3oOQ6Xv/fznP8eCBQsQGxuLmJgYlJWV2RrHZ86cwV133YXCwkJcc801iImJQU5ODu644w6cPXs2aP+PPvoId9xxB2bNmoXo6GgkJiZi06ZNeOedd2wNAACoqKhAdHS07RrOYLABwLjkON8IwL/+679CCIHi4mKcOXNGbb/xxhshhMC+ffvUto6ODmRnZ0MIgS1btqiUos997nNqH1q8a2trMWnSJNx0003YuXMnBgcHAQDPPPMMIiMjUVlZiXXr1mHXrl1YuXIlRo0ahYiICDz++ONB53jkyBHExMTA5XJhwYIFaGlpwYYNG1BUVIRp06YBAH7+858rhTw5OdmU8mRU0L/yla8gPDwcI0eOxIoVK7Bjxw7U19fD5XIhISEBv/3tb03H/tGPfoSYmBiEh4ejqakJra2tmD9/PqKiolBTU3NBBsCiRYswZswYrFu3Djt37lTf6Zw5c3D69GnTmOeffx7jx49HWFgYampqsG3bNqxZswaxsbGIiorC0aNHTft//etfR0xMDBYsWIDbbrsNO3fuxJIlSxAZGYlRo0bhhRdeMO1vZQCcPn0aDQ0NEEJg06ZNli/KoaB5ysrKMGbMGJSWlqKlpQVr1qzBiBEj4HK58C//8i+mMe+//766X9LT07F9+3bcdtttiIuLgxACra2tpv3vu+8+CCEQHx+PW2+9Fa2trVi7di3y8/Mxd+5c075DlYhHH31Uff/l5eWWKXF2itnhw4cRFRWFyMhIrFy5Ei0tLfD7/RBCIDExEb/61a9M+9NxmpqacO2112LVqlVobm5Gbm4uhBDwer0hv0/Cyy+/DCEEVqxYYSmnY9XW1iI2NhbXX389du3ahd27d6t99u3bByEExo0bhxtvvBHbt29HdXU1hBCYNWtWkNLyr//6r3C5XBgxYgTWrFmDlpYWlJSUYMyYMSgrK7NUROk8zserLYRAVlYWkpOTkZGRgU9/+tPYvHkzjh07BgDo7e1FbGws6uvr8ZnPfAbbtm1DTU0NwsLCEB8fj9/97nem+SZPnoz4+HjTNko1sXIEzJkzByNGjAh65s4HF3LfX0wD4HzXM1KkzydKejHvsV//+tfo6OhQz+eaNWuCnkMnA2DhwoWIiYmBz+fDtm3b0NTUpO7V1157zTTmgw8+QCAQgBACbrcb69evx5YtWzB79mwIIXDDDTcEXSs5PRISEvCZz3wGzc3NSEtLw9y5c5GQkGBrAOzZswdCCBw+fPicv1fG8AIbAIxLjlA1AL29vUFjNm7cCCEEWlpaAAAPPvigUlSGKn+hPIC0eGdlZeGPf/xjkPydd96x3P7mm28iISEB6enppu1//OMfce211yIyMhL//u//bjlu6PXbvdxef/11REZGIi0tLUh5+P73vw+Xy4X6+nq17aOPPoLb7YYQAo899php/89//vNBnqtQoO9u/PjxpojL2bNnlcK9f/9+tf3MmTNIS0tDdHR00LW/9dZbSExMRHx8PN577z21/dSpU/jf//3foGO/8MILGDVqFGpqakzbhxoA//M//wOPx4OwsDAcPHjwnK7LOI8QAtu3bzfJfvKTnyAiIgJjxowxKZsHDhyAEALz5883GZ+nTp1CcnJyUNpLXl4eoqKicOrUqaDjD72nLlYR8Lvvvotx48bB5XIFeZAPHjwIIQT8fr9pO/2fp0yZYlLAzpw5g9LSUggh8Oyzz1qew1Dcc889EEIoA3oo6FhWhggAPPnkkxBCoKioKMjbT9e7devWoOuNiIjAT37yE9P+W7duVf/ji2UACCGwevVq0/+f8Lvf/c50bxOeeOIJuFwubNiwwbR99erVEELg+PHjatuKFSswYcIE5OTkoKSkRG3/85//DJfLBZ/Pd87na4ULue8vlgFwvusZ8PEMgIt1jwHO6ZNOz67V93bvvfdCCBHEkEXH+PSnP40PP/xQbf/www9xyy23BK3rP/rRjyCEQFpaGv7nf/5HbT99+jTmzZunnEtWeOyxxyCEwI4dOyzlDAYbAIxLDrvwKn1iY2ODxpw+fRrZ2dkICwvDHXfcgVGjRmHixIkh0xusQIv3UIX5XPCZz3wGQgiT0jQ4OAghBDZv3nxOczi93EiBOXLkiKW8vr4e4eHhSoH+4Q9/qLx7Q/Hhhx8iLS3tggwAo5JPeOONN+ByuVREA9BfKkMVCwIZIUOjAHaoq6tDdHQ0PvjgA7XNaAD85je/QXp6OiIjI/G1r33tnOYcOk9sbKylAULX/uCDD6pt06dPR1hYmGXB35e//GUIIXDzzTerbXl5eRg5ciT+/Oc/hzyfi2UAfO1rX4MQAitXrgza/8yZM5g2bVrQPUvXev/99weN+epXvwohBO64446Q1wAAra2tEMK6WNJ4rM9//vOW8vr6+iCl2IicnBxMnDhR/U3Xe+ONNwbt+8477yjKxqHP/9tvv33eBdRCCFuDLhSysrKQkpJi2kaOiy984QtqW1xcHJYtW4bt27cjMjISf/3rXwEA3/zmNyGEQE9Pz3kf24gLue8vlgFwvusZAPztb3/DiRMngiIDTrjY9xhw4QaAx+MJ2v+DDz5AREQE5syZo7adPXsW48aNQ3x8vKVx+Ze//AVhYWFoampS2z71qU9BCIGvfvWrQfvT8e0MgB//+McQQmD58uWWcgaDDQDGJQcp+ueL1157DaNHj4YQAmFhYZapOMC5GwBWxgPhhz/8IZqampCUlISoqKggI8VYC9DY2AghhO35DIXTS7SwsFB5aayiI8XFxRBC4Kc//SkA4Itf/CKEENi7d6/jd3G+BsB//Md/WMrJ601etF27dkEImUpidb7XX3+9pXf4yJEjqK2tRXx8PCIiIoK+X+P/hhSYefPmISEhAddeey2+//3vn9P1GEHz2KW3kNKzZcsWAMD//u//QgiByZMnW+5Puds5OTlq26FDhyCETAHaunUrHn30UfzhD3+wHH+xDIDm5mZbZR7QU+WMBi/9n3/+858H7f+9733P1gi0wrp16yCEUGkxQ0HHsqufobxwu4jgrFmzIITAn/70J9P1fuUrX7Gcj77Xi1UDMHPmTFv5Rx99hIcffhiVlZWYMGECwsPDTfdxVFSUaf///u//hhAyxQ7Q06fuu+8+HDt2zPQ9btq0CUIIPPPMMx/rGs73vjdu+7gGwPmuZxeKi32PARduABi/RyMmT56M1NRU9feJEycghMCMGTNsz2vkyJHIzMxUY/Ly8iCErHUYijNnziA8PNzWAPjFL34BIQQqKyst5QwGGwCMS44LNQA++ugj9cLIyMiwzfs+VwPgo48+spR/61vfgsvlwsiRI7F48WI0Nzdj7969prxQ40uhqqoKQgi89NJL53QdTi/R6dOnh4yQCCFUuk1XVxeEELjzzjst5yMF/XwNgKG5qgR6oVN6EHmkQn2MdRoUFRg7dqzyfLa3t6PDUL9h/N+RAjNu3DilcJ+Lh30oaB67XPXHH38cQgjcdNNNAGTqlhAiKHefcPr0aQghTBERAHjooYdQWFgIl8uljNWKioqgdJWLZQCsXbvW0ctK94DRw+v0jJwvE9GWLVsghMC3vvUtSzkdyyo1A4ClAWj1oXsu1PUuX778ohoAVtE1Anm4ExISsGrVKuzcuVMpb2QsD8WMGTMQGxuLDz/8UD0Lv/zlL/HXv/4VkZGR2LZtGwAgPT0d1157rSk15EJwvvc9cPEMgPNdzy4UF/seAy7cALB7boYW6FL0NtTHuL5QRJeiREMxadIkWwPgxRdfhBCyToLBsAIbAIxLjgs1ACgfe8KECRBCoLu723K/czUA7JCRkYERI0bg1VdfDZKRt9P4UriYEYA5c+ZACHHOTA2XOwKwbds2CCHw7W9/+5zmP3PmDMaMGYP4+HjLCAwV5VkZAGvWrFH3QG5urslbdy640AhAUlKS5f4UAcjOzraU/+Uvf8HRo0fxqU99Ci6XC+PGjTNFAy52BODLX/6y5RiKADz66KNq28U0AHp6eiCEfQQi1PM4fvx4jB079pyOBXzyEQC7Z/XUqVNwuVzIzMy0TK2ZOXOm5Tqzfv16CCE9+3V1dSaFzePxIDs7G2+99dZFU9YuZgQgLCzMMsUFABYvXhz0vZ/venahuNj3GHDpDQCK/ixZsuScz+njRACoDuKWW2455+MxhhfYAGBcclyIAfCjH/0IERERcLvd+P3vfw+3243w8HD813/9V9C+VDz1y1/+0nKuUAZAdHQ08vLygrafPXtWhYqNL4XzrQFwuVymYj8jKOxv590cistdA0AMTXY1AENx8uRJCCHQ0NAQJHv33XeVcWdnAADA5z73OQghkJmZid///vfndFzjPOeTC52WloawsDD84he/CNr/K1/5CoQw1wDYge7J//t//6/aZnUf/ud//ieEEGhra7Ocx0oxe/jhhyGENWPImTNnkJKSAiGsawAuhgFw+PBhCCGU53ooQilnCxcuhBD2+dlDcaE1ABcCJwPgmWeegRACzc3NQbI333xTeZ2H4hvf+AaEkFGx2NhYk0LW3t6OsLAwfPazn4UQwsRedqG4mDUA48aNw9SpU4Pm+PDDD5VzwPi9n+96dqG42PcYcOkNAHKGJCQkmGqenPBxagDuvvtuCCHwxS9+8ZyOxRh+YAOAcclxvgbAn//8Z0ydOhXR0dEqZ/mFF15AdHQ0pkyZYmJDAIAdO3ZACIEnn3zScr5QBoDb7cY111xj4qj+6KOPsHfvXnXuxpeCkQXIynM+lAVo4sSJtov0iRMnEBkZiRkzZuD1118Pkr///vsmppfLwQLU2dmptn/wwQdIS0tDTEyMbaHv008/jb/97W9qnpEjRyI5ORnvvvuuaR5SkkMZAIBkngkLC4Pb7T5nLvFzYUOJjY01eSvJu7148WJTKsYf//hHVVxrNEKffPJJy9Sy2tpaCGHOk7e6D1955RVb5RZwZgEKDw8PyhcfGBiAEAJVVVWm7RfTAHjnnXcQHh5u6xkOpZx9//vfhxCSocXqf/nXv/7VdF3vvvsuxo4de94sQBdaBGxnAJAxW1BQYLo33n33XUW/a7XO/PGPf0RYWJiikjUWT//7v/87hBBK9uKLLwaNp3vA+Dw44ULuezsDgK5raO8Aotgc+r2f73oGfLwi4It1jwGX3gAAoN4pGzZssOxj8vbbb5t6o5DD50JYgCgS+PLLL1vKGQw2ABiXHPSisCt86tAaqRCIwWGo5+LOO++EEAJ1dXWm7d/5znfUIrlz5050dXWZGE1CGQBE2RYXF4eNGzdi8+bNmDNnDmJiYlBXV2f5Ujhy5Iji1F64cCFaW1uxadMmlJaWBuWIr1ixQoX329vb0dXVZTIcHn74YURGRiIiIgK1tbVobm7GZz7zGSxevBjjxo2D2+02zffDH/7wkvUBWL9+fcg+AC+++CLi4+MhhOzVcNttt2H79u1Yvnw5UlNTIYTAyZMn1f4tLS0QQua2btmyBRs3bkR6ejri4uLg9XrPyQAApJLicrmQlpZ2TsrChfChv//++ygpKYEQsu5kx44d2LRpk1LQdu7cado/NjYWkydPxtKlS7Ft2zY0NzcjPz9ffXdGT5/Vffjhhx9i8uTJiIqKwtq1a7F//350dXUpY8xOMXvssccQGRmJqKgorFq1Cq2trSqdKj4+Pihl4GIaAIBM3YqKirKszQilnAGSrjQsLAwjR45EY2MjduzYgY0bN2LBggUYNWoUAoGAaf9Psg+AEx0lPcuZmZlobm7G2rVrMXXqVMycORM5OTm26ww9T0Ofjffffx8jR46EEAITJ060NCYp8rR27dpzuoYLue/t7rPvf//7CAsLU9/77bffjsLCQsTFxaGiosLyez/f9ezj0IBezHvskzAAPvjgAyxatAhCSLKB1atXo6WlBbfccgtKS0vhcrmCaLGJie58+gCcPXsWiYmJQd81g2EEGwCMSw568Tl96MVDOe7EmjEUS5YsgRACn/3sZ03bDx06hPT0dMXgY9UJ2AkPPPAAsrOzMXLkSIwfPx719fV46aWXHF8Kx48fx+rVq5GYmIjIyEjExcWhrKwM9913n2m/U6dOYeXKlYiLi1OFokNfGi+99BLWrFmDqVOnIioqCmPHjkVGRgbWrVtn2RXU2Al49OjRF6UT8ODgoOoEnJiYiC1bttjm8p46dQq7du1CRkYGYmJiMGrUKEyfPh1Lly7Fww8/bKK5O3PmDA4dOoTrrrsOI0aMwKRJk3DDDTfgN7/5jeWL3M4AAIBHHnkEERERSE5OtsyLNcI4z6uvvqqMnJiYGBQXF+M73/mO5bjTp0+jp6dH1YaMHj0aHo8HjzzySNC+99xzD+rr65GSkoKYmBiMHTsWOTk56OvrC0q/sLsPn3vuOfh8Plx77bUICwsz/f+cOgE/99xzqK+vx4QJExAZGYkpU6Zgw4YNlh7Pi20AEB0sdb0+12MZ8V//9V9oampCQkKC6r6dnZ2N22+/PcjTDwDf/e534fF4EBMTgzFjxmDRokWOnYAvhQHwt7/9Dbt371a9MJKSknDbbbfhT3/6k+M6Q3UMs2bNCpKR4bZs2TLLsRTl+N73vndO13Ah973Tffbtb38bc+bMQXR0NMaNG4fly5fbPruE81nPLpUBAJzfPfZJGACAjOL+0z/9E3w+H8aOHYvIyEgkJibC4/Ggp6cH//3f/x20/x133KHebwkJCbjtttscOwE/8cQTEOLipJQxrl6wAcBgDGOc64v0HxFOhgTj4+HDDz/Eddddh+zsbFt2LcbFQW5uLgoKCi73aTD+gdDQ0IDx48efV/obY/iBDQAGYxiDDQDGheLo0aMQwlzozLi4eOedd+ByuUyMTgyGE372s5+pBpoMhhPYAGAwhjHYAGB8HHzhC1847w7NDAbj0uHYsWPo7u627DbMYBjBBgCDMYzBBgCDwWAwGMMPbAAwrhq899572LlzJxISEjBixAgUFBTgu9/97uU+LQaDwWAwGIwrCmwAMK4arFixAhEREdi+fTvuu+8+FBUVISIiwrJ5GIPBYDAYDMZwBRsAjKsCzz77LIQQGBgYUNtOnz6NtLQ0FBUVXcYzYzAYDAaDwbiywAYA46rAjh07EB4eHsRbf+DAAQghgriVGQwGg8FgMIYr2ABgXBWoqqrCddddF7SdWsL/27/922U4KwaDwWAwGIwrD2wAMK4KZGRkwOfzBW1/5ZVXIITAvffeazv21KlTOH78uOnz9NNP48EHH8Tzzz8fJOMPf/jDH/4Mr8/zzz+Pxx57DH/5y18u5auMwfjEwAYA46pAamoq5s+fH7T9jTfeCNkSnVrA84c//OEPf/jj9Hnssccu5auMwfjEwAYA46rAxY4AfOMb34AQAplheyDE8aBPQfhd8MSvRoHrTmu56054Jq1ykIceXxB+l/3cSWtQ4HKQp6x1kN8FT/ItjufmOHbqzfbnFn4XPJNvhCdxNTypn4In9VMonrFebku+BZ6UtXK83fzh8tw807R9p90Cz9SbUexeD0/KWhTPWI+CiLvtx6aslZ8pN8EzfZ0cl3YritM3yPOZdovjuRfPWI9i93oUp29A0XUbMU/4MU/44Zm+Tn6ndseOuBvF7vX2c5PcYfxXR6divui3lI8f85jj2KLMTQ7ye1B03Ubn8RnOcsexoebOvM1RPi/L6dzvxleucfherv2W41hP2q3O/7P0DShO34B5WZtQdN1Ged/Q/ZZ2q/yZ+il1HxS718t7Urs/7e9F+f+m/Yuu26ieB0/qp+TfIe5FT+qnHOWOY6fc5PyMOR3bpY23nf9u5/Vh8o3O55Yc4tiJqzFlxD9byqdEPozxI75hKasW/VgWvwjVY29FtPiJtv1lCHEc0eInqB57KzxJa+zl166FZ+JKVI9bZykvvnYphBB4/vnnL+WrjMH4xMAGAOOqwMWuATh+/DiEEJgmHoMQH0EIGD4fIT3sOGrStsMtjlvLxcuomboV7rAQcofxtmPDjqMmpfkcjv2K87k7yEMe20meth2BGTsQSG8xf9y75GfGDsdjB9y7EJi5E9XZbchfPYjArFYEMnbLbVltzmNn7pT7z9iB6uw25K47hOrcdlRntSEwqxX+/H2O4/1zO1Cd3Ybq3HZ4fQdQFdaIqrBGVGfJbaHO23HuEMd+Y0QcssSLlvLRMSed587rcJRXFXY6jy9wln+c6/q4x35j5KQL/l5C/c/8+ftQnbMX1Tl7Ecjcg2d+k4yAexeqs9sQyNwD/9wOBDL36PdBdhv8BZ3w53WgOmdvyP8JzVOTth1nT06X9+HMnfIen9XqfO7Zzve60zMYSG9xkL+s3asO40OcW6jnP6Tcbu3SnqPUsNcs5amuExgd9balbLZ4AU+NTofPdXiITH584YdRM3UrfBFHbORHHOXSYSJw/Pjxi/XaYjAuK8TlPgEG42Jg+/btlixAPT09EOL8WYDIAJCeLoeXRbjDy2TKFvjCHV5Gqdsc5SHndnqRpW5zHB9Ib3EcbyuLCDE28qhuAGjKPin0gRk7EJjVKs/NaX73LgTSW1Cd1YaalGap0JMRkLkHvoijtmOrs9vU2EB6i1Tms9ukgpfegsDMnbbjvZFHlbFAihspfgoewucAACAASURBVIHMPajO2QtvpMNYB7kvhNwbdRRPjsnACvGIpXzSuJecj53dBu+IY7Zz+ws64Y2yH++f2+F4bk4y/9wOeKPsj11V2Okol+Ptz+3J2Fm230t87IuO34t/bofz/5vuD8M9Up3brv725++DP3+ffh/M3Al//j5pTOY5fGfa3JWeLgRmtcq58jrkfZy5B4GM3ajObgv5HNje65FHHZ+DQHqL/b2oPSdOx3Z8RsOP2K8tdN4O8pq07c5rW9p21IZ901Je6/om4kf/zFK2QjyCN6ImODtdzsVxYiNPEY+CDQDG1QRxuU+AwbgY+PGPfwwhzH0A3nvvPUyfPh2FhYXnPR8ZANWxn0KM+Jt6CQgBxIi/oTG+DTVp29E0dpelvGnMDtSkbkPTxN3W8onSo900vtVaPnaX7djG+DbUTNmCxoS99nO7d6Exvs1aHrcbgRk70BS3x3Z8U5zNsRPbUTPtdtuxjfFtyrsZmLlTKt0zdiAwY4c0DGbuRE3qNjQmtluPT9AU9VmtuifWvUsqTZpC35jUYT02qUMqVrntwcp/xm5lSNiOn9KJ6qw2qahl7jF7fnPbEcjcg8bU/fZjc9vRmGwjT+5EZXEXGpM7beXr09fjOZEXJA8Pex8F2fehMa3LcuzStG74SruxNK3beu60LlSWdDueu7+g03b+xtT99see0YOqov32153WhapC+7kb3D3w5+9D4zT7c1ufuRHPhVl/L/Nm3W0/lo5td27T9qv/d3V2m1L2ydD053XICEFuu8kQ9M/tUEq97dyJ7SqyQPej0big+7ExweY5SNonn+Gkfdbyye32ssR2Ofdk+2esJqXZ/hmc3I7AjB228qa43c7P/8yd9mtXwl65fjitbSnNuH/kYkv5/TGLUZw4gGjx9yDZC2I2nhrltneqRJyD02ba7bZy6QxiA4Bx9YANAMZVg6amJkRERGDHjh247777UFxcjIiICPzHf/zHec9FBoBn0io0jWuBL/ww0sNehi/8CJom7kZN2nbUJH4aNUmb0TRxN3zhR5AedlzKx+5CTUqz3CdtO5rGt+ryiCNoGiuV4JopW6Q8bjd8EQZ53B4pS2lG09idUia0Y49vVfOSEm+ST9yNmqlblffdNHf4YTROlgo8eeQbE9uDjk2K+1KxznzemmERmKEZN3RsTd44uV0q+GnbVcpPTeo21KRuU+k/NSnN0sOesxeN8W3wRR41z5/eogwFMgKUETFzp0oFapzSaT52kqa0z2qV3n/NYx/I2C2NAlLsNUWsMbEdXu3Y3sijaEzap4/TfgbSW5TiR0qiVHY7zWOT98M/VyqL/rkdaEzeD2+UJo+S8sriLnUOjWnd5vGp+1FVKI2PDe5bcX/sUtSGfwuprteQdu1zKMy8F1WFnfCV9aDB3aOPjTqKxrRuqajO7YA/rwNL07pNxyYF218glfwGdw+8UcekPPoYGtw98JV2y/PLbUdj6n5dHnUUjWld6tqCZd3yvHPbUVnSbT636GNoTOuWnu8Cee5LZ/TAG03jj6ExuRNVhTKdxp/XIeVR5mvzlXbDP7cDt+bchvuvaZDfS/hrmH7Nsyhy3wl/gZzDdF2RR9GY3Km+k+rsNu3cDXNrBltgVqs8v9JupexXZ7WZ/p/V2W26AaB57tV9lbPXfD9EHZXPAXn6tZ+UVmZMRwtk7tGMRv1eVveidgx/XgcaJ7er50TKtUhCeotprHwOZHSiJqVZPt9BcvkM1KRuk0bCkOe/MaFdN9STNqMxYa9JvlSsk+M1JV6ui8fhFY+hKW43aqbdLp95JTesPfFt6lk2rXviZe3Ye1XEcGP8Kjwn8rBCPILZ4gWsEI/gOZGHjUk3SuMlvg1N4utK9oKYjffCIrAxfpW9U2Zcixpra5w4OFaqx97KBgDjqgIbAIyrBqdPn8b27dsRHx+P6Oho5Ofn4zvf+c4FzaUMgMk3IhC3Ub7UEjapl1vNlC3yRZa0Wf6d0qz/PnWr/GiKek3qNv1n4qflz6TN8icZCsaf025HTcIm+RLWDIGa1G3y75RmqUjTvnSsxE+r8yAFXR1XGxOYuVPuS+dKRsi02+V+9FP7VIU1SmPC4L2nuWlbzbTbdaVdU9JrUpp1JUlLu6lJ267yrJU3NGev8sobfw/M2KGUJmUEGLyylN6jFCyKGFCUgNJ/NK89KWuBmTuVAlZV2KnPT2M17251brv6qQwA7W9KDyKl1Z+/Tyl3dEx/nh6J8OfvQ6WnSynplR6pUFcVdupKpkFBp091Vpv+d/4+qaAWyCiCP38fqoo0o4O2FUiF1l/QqbaTcuyr6NG303mUdKvz98/tgK+sB5WeLvgqeqRCXyyjBpWeLqWkV3q61N9VRful4lzRo66Lro2uu6pov+k7ICOmqtCg+Gsy47Ho2P6CTjWvr7RbfWf0v/Pn79ONH/oeDf+XSk+X2q+qsFMq1Np3rc5N2z+QuUel69D3Z6wNoPugqmi/MmCrs9p0Y0E7B7U9u03VD1Rn6R5/NT63XaUFkcHpz+uQUS96FrSxFMWi49FHpdhpRq8ytindjmoNjL8b0vHUc5zSLM+PttEzQ+uNwQCvCmvU55yxQz7/tLbQ2mGYT60JdF7anEYHCTlSlExbSzZMuxlPjU7HG1ET8dQot1L+af3aGL8KT41y443ICVKeeINaU5XThRwjcXtMa3fTRHKMvAxf+GHdeNHW0Ka43ebxE3fDM+UmNgAYVxXYAGAwLKAMgMTV2svkMNziuP6y0F5SNWnb5cvERXI9QkAvv8bEdvjCj6jxjfFtyqAoju/H9JhnkOp6DbWub+L+mMXYOHm18qTJF9GQucnLNnWr9KKHH4E77BXtRbdbGipJm2UEYJzM13dr0QlKXaqZdrv0EMa3afJXpBdOS/GpSdsuIwARR/Vjj281KRj6WG3uRC3VIWO3qeBXpQRpylVgloxiNCa0m4892ZAqYfDCkzJinKdpXAu8UUfhDntFedmVl1+rFyDlUClNWjoGeV29kdp4zYtPSjwp3f65HSYDgLY3TjGMjToqU0lI0S3uknLxmHZdR9Ews0fJ/fn7ZARAnfsxNE7brxTT9bPW40tjtAhA+OuYfs2zKMi+T829VIse0LGXpPdKZVxTeM1zy2NXerqUMr10iHyJ+4AyEqqK9qNxmvTyq3NL61YGQ8PMHtN5LzVEAKqKZJqQN+oY3K5XVARAGSnq3PS5l8zqhdd7QBkLpPyTUVPp6VLGz5JZvfBGG85Li5pUerrk9zLDfG6UclWdsxeVJd1D5FpkI0+eW2BWq4pumO4nreC3OmevKRKkjD5NgW9M6zLfS2ldujGgKfoqAmC4B9V4w73oo+hFnsHLn7RPf04iZYShJm07Ahm70ZjUEfwMac9ITUozGie363OTl50iAO5d5vHhMgKgnt9ZrfozLvQIADkzKAKg5tbWFnr+KEJIY9W6pynpprnDD8voA8mTNuvrg6Do5G617hVN/SymxzwdvG6SATB2l7Yuams2rcnatZOCr+bWIqfkbKHoBF1b0/hWeCbfyAYA46oCGwAMhgVUDcDYW23z5GumbrXNlW8a1xKyBqBo6mcRLt4Lkj0n8rAh+Wb7HH0tTcdpbsc8fS3UbpvnP6UTTeNaHMfahcmNqTSBzD162g55AzXPve34xHY9ZULL/6dUHkqdsM19Tu40K/qaJ7U6u83kdbXNGdfSRpSnf0gEwDFXXVMo7XL86zN6ZT66TR5+w8werM/YYJvrXjj7PttjN2hKfKNNDcDSGT3wlfXY5+HP7IHXewAN7h7bPP2GmdYyMgLsxi7V0oDqM3ptz50UfWPEw5/XoQyTUPUDDe4DttdVndtu+700pmlpT7b3w35lJBjZoJQRkNVmX1eRul+/l7RIFBkTxpQg25qQJO1+s5NP6XSsZSHl3vYZc++yn1s94/Y1BLbrXtwe57WF1p6xOx3rE5xqBIonD9qvm1PXOJ6bU/0BpVfapRBVX3sL2ABgXE1gA4DBsEBoFqDDjgVjvvDDCMzY4VhwFj/Kns3iqVFuRxYOObcdg5DGtGE7/nBIJh5HBiH3Lmf2EkPevakQV0v1cTy3iCP6vlltKFw5qKf2aCkbodhNVOpEbjtK6vpNhZ3VWW22jDM+jbmFFDdfabfJ8xvI3OPMhpPnwIYTGYLtJuoofjAhy54FaPzL53BsO/kxVHq67OXRx+DP3wdvtD1Tj5OsorLXXh59DFVF+x2v25gGZEwB8noPwFfa7Ti2Omev47EdvxdiZrJlKDomvfRDI0GGyJIjsxIVF2tREF9pt4oGUCqT7b0YcQSBWa2ObFuhGYSs5d7IowjM2OH4HIVi8nFkEHJiKIsIsTaFZAk6HHrddCryTWk+B2Y2LgJmDA+Iy30CDMaViJB9AMTLqJl2uwNX9svOfPniZYyOfMtSNlu8gDeiJjpzaaduc+TSDsXzH4qL3/HYjtd9XFF9Ut6zKnqcsUMpQCG5/LUIgjGPn4yHULzvKrc6V2diofzqUJz1gYzdUjnTcsRJ8aOc+VA9BJzkvrIee7nLme9+1OjfO85dWdzlOHelx0FO5+Zyuh/sZV7fAcdjh7ruypJuWYNQIot+3W2fVTn/lSXdztcd4rqqivZf+PemzW9iAdLuD6odcLwXDcp+ZUk3Nv50lUyBo0LimTtDjr/Q3gyBzD2Oz/C5PINO4516DDj2NzmHfhnO38vLjn0AnNfNl53XTaHJbcYzDSjjaoO43CfAYFyJCBkBCOXpChkBOIz4kc9bys4pAuDkoQs/HCICoHnCnCIAIfoAOHoPSYGnAltKA9Ly+53OzRt51JQiQePIEKjOlYwodmPJ2FApRFoxLkUPqnPbnbnbtcgBeXlNqR/5+5w92U5c+1FHNW+2vbc5ZATAYWxlcdc5eOHt5b6yHsfxFbY9BrS5bSMEx6Q330FO9Q2+MslIRJ+qwk54vQec53a67qhjcrzD/8TJC099Ifx5HUEGABmW9s/BUVXMrQqJCztVNIpy/G3v5Sh5bKfnxOnYgYzdzs/wzJ3OUbjcdsc+A44e/BBrS2DGDnjFY9byEF54X8QR53VzdLpz5DNU9IFpQBnDCOJynwCDcSUiVB+Apom7Za7qmB3W8rG7FNWdXY1AUfLnHGoAbrLn8Q81d4g+AI0Je2UNgcN4pxx9WcBrIx9SCGhS/qmIN3OPPQc51RBojZaoCFix7GS1OeZFK5YYg+ffX9CpCjqrCjvtj60VX5KiZir+1NKCGqfYHDtNstbY5ZMvnSGZeOy4+qkG4FmbGoD8ufdj6QzrPPsls3pRWdJtm2dfnyELhZek28u9vgO28iXuA1jikGcvKUCt5fUZvfCVdqM+86DtuZPiX1W0Xyn/lSXdshNzYaftdS2dIcc59SioLO6yva6laZL+1K5GoGFmT1AkiO4tf4GMTtj2TkiW+1EhMtU10N/UD8C2hiCtWxb52vUZSOpw5Pkn+lCnOhs7eVPcHrl+2NzrTXG7ndeWWa32PUq0uW3z8Mfuknn6NjVIqnYq7H3LdXNj4g3269r4Vkmc4HBuNVO32h6baUAZVxvYAGAwLKBYgJLWBFHCNSa0KxadmqlbFUsQ8VlTAXDN1K1aMW4wzz8VxBYnDmD6iKeR6jqB2rBv4v4RiySdnUa/Z+LaJwYhYrOYulWns6Njx+0xUekRS1B62Ms6175GrUkFcZLDnMZrbBmZe4L6ADQm7DV58o385MQgZOzYW53VZqYA1eg9qT6gcbLOQe6NlGw6lDJkYk3RfldFldltinlF59rvlIWWGnuPkQ6yqmi/qkMgGsaGmUP49KfpLDTEalNVqBd/EsVlZUm3xpRDYyWLD/UI8M/t0OUuOfeSWb2SylKjwJRsOjqffsNMud1X2o11mRvxpbGNkgUo4jWkxT6H/Nwvwes9gMqSbixxH9C59KOPoT6jV+XLkxHgjT4mjx0tmXbK/ZJtp6pov5RHmeWkaJf7exXbDl1bg/uA9LL7Dug8/i4pq888CK/vACqq5Pzq2Nq5LUnXlPuyHlRUDplbO3ev94Cco7JX1QH4KvR0ILvrosJmGkMMRTT30rRuVFT1KmMiqE8A/b9LunVWKPU/O4bG5P1K2TfVgsztUN+l6vswbX/Q3MQUZCwqN9KLVnq65LOgFeOa+kJMlnSuqk/AZCNXv6GHQeYeNCYM6WeR3Kk34MvYPYTHX441UowG9QGY0qlobgMzdgw5ttYHwMAQ5B36/BOVqHtXUJ8QWveIqnjo2kXOBcUyFLdHX7vCjyjHRcC9C8VJhyQLUJhh3Zy82twfxTC2aeJunVLZSPNJDGZJHYrWtCalWev9YujtMq4FnsTVbAAwriqwAcBgWMBIA1ozZYvkqiau/ClbEIi/zcS9T9vV31O3yr+Je5q2Eae/e5feN4DG0b5Jm819AYiLX3t5kfKuOLbTtkvaz0zZQCzg3qX6FBD3NtFxKgrQjN06t7/G021s2EWc3zUpzXpTLk2BJypQxW9OXn7i05+5U2feofx/javfP7dDjTVxmhPdJ/UH0PKkVTdVbT5iXxnK9mMszqRUH2ripFKANL52RTdpKOZU2zUueprfyP+uaCUNfPfEM19ZLDn0FR++Fm0gRZb4+2kfIx++4tIv7lIKqyqI9XSZPOK+0m5d8dX293o1BVpTnklprqjqha+iB2U1B+V1aR52r0+TV0oFuazmIMr9UlmvKtoPr/eANBo05b6yuAsVVTKKUFEp5yyt7VPjfWXaMbU0Hq/vgFL6KyrlvOX+XtO109y+ih5UVPXK37V51H7GaID3gG4glMqeAXTdvooevXDYd0D/WzsW1RfQtRHrEN0/xu+c2J6MvQ6MqWCq/4LGWlRZIv+3lcVd+r1HhqZG/UoRA9WLgYxSbT/VO0FjQFIKODW2y9b7BNDvQz+U8qboQ7Xu2VRzoMYa63JovHsX/AWdeuROo8qkOgXVB0Trh6DWA1oTZrXq61fqNp1mVOs7QrS/tE7UpDTL9WnmTr1vCvUvIeeFe5feS4W4/7W5qS8I7af6BxgoRmk+tV4Z1k+iOTaNo3WV1mjDWk/rNxsAjKsNbAAwGBYwNgJTnNDEhx+nv8R0PmwDpzR169WadCmufiOfviYrThww81lTBEB78Sku7bBXzDz+2suwMaFd57vWog9K4daoQof2CaDogzp3I494gu6FowiAkUNcNc+auVNyiBv5z6d0ykLfLEP+vtFgyNU5ygMZu9E4bb86NnV+pWJfUs6poy/xzROdInls1bEpeqB571XahaGhU1XRfmUcDOXTV1z+BVrTK2pMRZ7fgiGc88RJT97oCt0j3eA+YOKkb3AfUMqn4rQ3yMmT7vUewC3zNqs+ACnhryN1zE+Qn/9lpcguzukzHXvJrF5lYFRU6V524uKvz+hFSV2/UsbrMw8Gj6+QCnnZ/D7pSTfw7ddnHlTyJem9prEkK5vfp889Qpc3uA+o45rOjY6dLreXBw6ioqoXi2cfRMUI87lVerpQ7u9VEQB1bC2tiYyNBi0yYhqrGSREFWrsQUD0o1VF+7UeBV3B/RNKupVxp2pBcttRUdmrp5XN7RjS30Dex9W57XoTNa1mgIxA+qk6/Rp7EGhefHp+7PoMkBIsewQcNY/VImiBzD3mHgKGTsF6j4EOy+ef6ngoAkBy6gQcmNVq5sqPPCp7CBDT19StKrqguPTjDNTAtDZF6Fz9jfFtugMivcW87kYcldFLLepq1QdgQ/LNat1VfQCMa7ah4WHT+Fb92BQ5JSePRkOq+q9okVM2ABhXG9gAYDAscC59AAIzd6JpfKt9jUCIPgDFSYdsc1kd+wBQDwKHuSl8b5vrqjUws8vjt82T18LwtjnASdKDSYaAqbupodup7fxp3So9wZ+/T08JMtCI2ubhT9uv5/4beOWVp15LC7LN207drzzvpBiS4uer6HHk2l/i1hVR2zz94i5bvvwl6b1YW7DZtg9Afv6XbWsAFs8+KNODZl1Yjn/dnH5UlnRjcZZ1nn595kHH+oJQxy4PHLStAViU0wev74Dt/IuzDjp+Z77SbtvvpT7zIHxlPbbHbnDLugy7+Run7VdeeWMEQHVxntthPzZN74xMdSiUMmTsM2Gbp681IrOtEUjqcOiHsd+5X4bWsM/2GdQUcdv1IanD/vmnue16EGgpSo49TLRGXHbrT6jaKdsaAK2+wK6/Qahjcw0A42oDGwAMhgUUC1C4DQsQce07cPE7c/WfA591KBYgO7lLYyByYupJb7lgFqDqnL3OLB+UlpDVhsqSbqT1HjJ19/XP7XBmAZrVKr2uWg4+pdlQOo8j9zp1btVSds6enK6Kev15HSFZYSgKoMYaPL+VxV2hmXhCMe04yJ1YgCbGv+I4trK4C147pp7oYzJP344tZ8QxmfLjNN5JFqIPQCiGoopKh2OPOObcg8DpuqJDMxD5Khz+J1r/BF9Zj6kWhAqWKz1dDr0ZjsmoVXabSj86e3K6nlakRbicGKn8+fsc5U59IZwYirxav4tQfQCc5KFYfkL1CXFiGArFIhR/zc8tZSvEI3hq5EzHNTdUbxZmAWIMJ4jLfQIMxpWIkH0Awo5LvmsHzunAjB2OnNMXzmdNPP8fg6s/ZB8Ah7EZu0P2ATDlLefsNTP7ZO5x5j+nfSknmgooNe+pIxe/puhTygV5bKnYM+T4gk6ZyqPllBsjABWVvY589v6CTkd5VWGnPde+6zh+OSretg/A6FG/dxxbVnMwtNzh3Ly+A47jnWQVVb3O8kpneXnA+dwdewyUOvQJCNWDICzE/yzsuKIjNRoAVIdQVeg8lhR/UvY9S/pVnQGls12qPgDVWSF4/tNbPtZ4x7lD8PyH6uXhvK4eD71uOvVHmXa7s9yhT0CKeAxsADCuJojLfQIMxpWIc+4E7OSlT2+x90ZFHEH8qFB81jZesvAjzlzZ4c5dRL2RRz9WBCAwqzWk9zCQ3iKNACru1dJ3SPFxHK9FCagYk1IniKHHyetKBoBiANIKaanwUnL123uUycPrz+uQaT8G9pfKEgce/2it266DN9rrPeDoZf9B3GzbCMCEya86zl02v8/Zwx846Dy+xlnudN6lC5yPHWpuxwiA07GjZFSlIsZaXjFC+14c/mcyImR/7lTkrCJBGisQRQGc7iV/gV5ITEaosRjYMZoVFSICEOUQAdC6EDt1EQ5k7gnZB+CCIwCOncKPhuwkXpO0+cIjAKPczp1+neYO13q7cASAMUwgLvcJMBhXIlQNwLh1zvmiY3fZ59mnNDtw+e+UNQA2uawbJ6+2rwGIc64BaIxvk0V4dnm4k9tRk7rNPgc4sd322I1JktXEiYOcGHuoCJjy+KmoN5C5x57fXOPip8JfMgYUFWhehy2XfmOaRtVpoJMkphYyBCo9Xbac9o1pssi33N+rutOqCIBWaOvEpV9R2WsrX5x10DEPf1FOH9YWbMazYXOCawBc7yO37Kv2efI5ffB6D2BRTp9tjUDZ/D7UFgzY5tKXLuhD3Zx+23Ovy7eW1WfKuRdn2+T45/ahbH4f6vJs5s7pQ3ngoO34xbMPOtYXlM3vw+LZdjn+srDZrrZhSbqkIbWt29AoUP0FhgiAxvjj9R1QBd92efhenz6ejICqwk41ttLTZZvj3+CWzFBOfQJs+2GkSQPWKQ/f8RnWenHYzp/YbptHTyQFtjUCkyVVqO34hL1y3XSYvyj58x+rD4BjDwKHPgD+8evBBgDjagIbAAyGBRQLUPxqcx8A4vnXOP6paY3ku9a59ImtgorpFN91+GFpPGhjiyf1YfrIH8s+AK5v4v4RddiQfJOi9ySWDsWlPVFn8ZFc23qPAW/kUZ0rW6Pna0wI5vkm6jxLeUK7ogxdKtbBF3HULNPYRyz5yxPaTXSFRN9JzD7U0Zc+8tq0+SOPojGpQ1F6EnUi0Rsqfn6tQFfxtmtc+kvTpFeWFH7FtqIZBBQNII55YrtRfPczexQ7i9d7QDccNMWP6COtuPQVn71Gn0lMO+mu4/COOIa6Of2KBrOiUmO0GaHLF88+iNIFkknn5uLNuG98ExZGPIrUiNeQOu6nyC39Kioqe/W5R+jHXjz7IMpqDipazsXZB01zL8rpQ0ldP0oX9KG4YQCLcvtQockrYqS8dKFUwj1L+rEot898bjl9KF0g56jL60dFjHlsyaJ+JVc8/5q8Lk+yD3l9B+Sx8/pMXP71mQclQ1FVLzxL+qUhM+TYFZW9KF3YJ8/L8J3WZx5EeeCgziCUdVCdmzf6GBbl9qHcLw0br/eA+X+iMRQR7aiph4HL0P+AjMCi/SZDkChPK0u6Ze8Et4zs0L1IBeHU20AxRGnMUlTPQoaqZAEy9JVI61KpQpXF0mA13usN7gOKlaoxdX9wHwD3Lr1fxpTOYLkWnfPP7TCtL4pFSGP6GtonwBt5FEvFOtnXI0vObV479qr+JYGM3UE9BJripNOEWMZMPQpo/aC1i3qYRBi4+uPbFINQ0bTPY3rMM/q6OXIxNsavUvMT+5np3JI2287dNL5VpyJVzG6H9T4C3AeAcRWCDQAGwwLKAJh6s+SxppcDcfoTP/SULYo6TnFNT9ki6S8TP23qA0B82ooiVKPzrJm6VefbJi5r6hVAv9Pc2u9Gjv/qrDaVdqMalGm81gH3Lr05T+YeRQ9KNKBG7v/qrDadAtC9S3J+p7convFAeoviGae8fmL3MW4LpLcoHnRqZqSYT7IN7D6aR9+okJDST/n7/oJO3YDQKECpQFixq5B3tWi/4nNXqRuFnVKhz99nomVU3PzaHIoysqBT57c3NICqqOpVzbrK/Tq/PeV5l83vQ0VVr0x3IR59rclVSV2/4uf3VfTov5f1KAW2bL5UVElZL6uREQNPfT9KF/YpOs3ygDQWyv2S3tOzpF8fM1//eOrltqLGAZTWSuW/ZJFUtktrNcV9odzPU9+P0lppBJTVSEOgeOmAnL++HyWL5E+awbeW0wAAIABJREFUu3RBH3yl3fK4C+UxvN4DKF0oz7tsfh+KmgZQulA3HuYtG0DZfHnckjo5Z2ltn/q93C+/u7Ia+X2ULpCGCZ0nUY2WLuhT51K8VM5JPQVoLH13ZTUHVZ8B2kYGBfULKF3Ypxtn2v+BlHxfmdxmZIMi7z3da75SGWmi+4X+v9SrgHoS0P1K9wv1ZKCoAN2TlPKmqGwNfSuoEN3Y4Zr2o2fNZIDT82cwwo2N8tQzm22g7c3QGwVS0X51ls7qVRXWqPfrMPbvIKdEeotce+i4mXtUD4GatO2Sv1+jBTauY9SbRP1O6yH1O8nYrRwqqg+K1l9A9RxI2ixltE7SXIZ+KWoNnna7vr5qdM6m/Wmt19bpQHoLPElr2ABgXFVgA4DBsIAxAhDURMbQTMbUwGvqVtQkbNIVeXp5aLz5yvtFY6gZjdGAIIXcwNVPBoLRcKAXnWq2YzQKqBEPHdfQXEe9PMl40Dr0Ko5+8vBn7FY5zyqVh1709Ld7l6nRFjUAI4WevJD0M5Cx29SASXUFNnZMpaZdlP+vNeoyKveqLoAaK2kKPHlFVZ52md6Yi5QrUvyJl58UM2o+VbqgT0UJyv29euqH9rfXqymWGi8/KbzU3Iq4/qmRVtl8qRSXLuyTSra/F8UNA0rJLw8cREVlr1LUSQknRZ0U3uKGAaX0ltRpCvoiqQiXLuyDZ0m/MgpKF8j9SMEuXjqglP2ymoNyLu28ycAobhhQxy5uGEDx0gF4lvQrpb5w5aCcSzuP0to+tU9Ro7weuqaSRfr5ldTpyjqdIx2PDBKas6KqV10LGQultX3KYKFIB52T0RgiA6R0YZ/qW+D1HlDfT+nCPtU4jAyB8sBB9T80Ni6rqJI/ybgwGoJe3wGULuhTLEDU9I0MBooaKBYrMhQ0WemCPt14NUSp/Pn7VOTKV9qt39dkMBgMCKX8D3kOqnPbVWMy1RRP6zdAHbBVcb4WZQtk7DY9i9SlWzXZM/T9oOaA6rnNlamENEatW9R8kCKN6S0qqqiaglEvgsw9JoVbNRWkuciJYWhQqJoXGpp/KUeHwRFjcpoY1lRqIqaaJRqbLNK8RqeMtn56Jq5kA4BxVYENAAbDAsZGYMpbRB57eunQy4heKPQCIeWfulJqLeiVQk9RA/I8DX15kYFAL6H0Fj1yYIgMkMeNXpgqOmDovGv0+FdntekvZnqpawq/8uRrL2vy9qnuoVpnUZXWY+z2S2Ope6/GuW/s5KuUC0rtMXTnpf0rPV2KhtPorSRlSnXipa6tGmOPf26HUshUClBeh+oGS1SOqgutpqSTB9fYOZe8wWU1UjFXEQCt4yzJSHkk77PXp3vAKyoNXmjNY04eelIsK6qk0u+p71cpIjS2dIFmCGhKsGdJvzIiyFtPirVSfo2e9ho9tYb2LWrSPPB1/aoxWHGDruSTol3cMICixgGToVHUOICiJkNEoE734hcv1WVFTfJ6yOAgA4OU/7KagyhqGsC8ZXLOkkXSoKBjFjUOqIiGuk5N8S9cMai+Xzp2WY00AEpr+8zfsxZJKF3Yh8riLvU7pQyRAaP+X1W6sk8/qTOy13sA5YGDQf0gqgo75Xz+XtN9ZzQwjcaAsdswGY+qOFhLBaIUNKXUU+dozTCg5mL0vFQVdqqom1HhJ4WelH7VUM8QFaBnWXUDNij+ah0w7qMxeykDgDryajKKQCpPu7YWGBVu5TygfYzjta69qjuwYX2tmbpVrYHGyIHy6JNjhdZbQ6SB1lvqjl4z7fZgY8VgtKgOwmSQ0No8dSs8KWvZAGBcVWADgMGwgDIAkm9RivXyp2/VXxBDw8UpzZj2zz36y4oiBprHv6qwE8VLB/RUHYMxEXDvwl0nyvVUH1L0Dd4xo1yF5w0KvpJrL9WatO36Czi9BU1Pr1PdPYcq/Pe8VqaH/7UXP0UA/HM7cPbkdJOST6kDVKx79uR0U3Oj6tx2VcRburAP2RsPKWWFlBtS6u95rUxvrGRgSyFv/dmT0/WUC60A09hV9+zJ6XoqhqbMU6pNyaJ+nD05XSlylLZD3uF5ywcx51irihaQ95eUQmMfgHK/5hmu0hX4syenqxQSpbRS6kqdPDYpq0avdkmdVG5pvGeJnhJDSjSNLW6QCnZRk1SUS2tlys3Zk9NRuGJQKtNNuhI+b5lUsM+enI6CVYMore3DvOWDKFwxiILrB1HcMIDClYM4e3I65i2X42meect02bSv9aBg1aD08Gvze+r7lbxw5SCKGgfUHPOWSaOB5EVNUkbGRP4NgyhZ1I/8GzS5ZgB46vtNxgDJPfWaQbFEfi+eJVL+wdupSH5IGk/0PZIhUrqwT40tqetXBhYZIWU1B6Vc+77VeC2VqXRBn7pfihoH9EhAjW4AlM3XozRk0NH9dPbkdJT7e1X0h1LAKA3t7Mnp6j4sDxxU6UHUxZmOTQZBVdF+lQ7k+e4OpA4cUvsb05Cox4DR829MLSK5MiyIJUuLQgQy90j5XH07GfJk8H/wdqo0KjQDgNJ/qnP2YtrXZKqU0VGgPP/pLfjdm/FK0aZ5jVHEU79LMEUI1LqmHeff3shUSr2KUGpGRNETO5F854BuMNDaqxkFd50o19c9WrdpbU7dhnteKzNFYtX6q0VVm3/epP72TLmJDQDGVQU2ABgMCygDYOJKU8pOzdSt6uVAqUAqPceQr2/K3ydjgfJTKSpAL5yUZlVnUJO2XSrbWpGuMWXH5J0ypPXQMajQVnn3yWtG2yhUb8z1pZctRRK0l2VN6jYZAaCoAe1PBgIVGhq8hqouwJAWRLnFpJT453bo/QDcu0zpC/S7UfEhTyd5WakokwwIr0+mXqj9DIWWlSXdkv7SZyj41BQyonGkvO2Kyl7pcdUMATIClAGgzUNzqpxyzWAgjzd5mo2558rDTsW2WtoNebtprpJFUulVqT+a0mtKf9GMBFKePfX9SkkuXjqg8v7nLRtQx6Q5ySNfsqhfKudNmre/Qfe+U349RQw89f0oXDGoDIzS2j5lNFBaUFHjgErrGZqiRNGDwhWDSmmn66YIBBlJtK10oZ4yRFELusbSWr2+gWoH6Drp2sr9Wq0ERUq0qAFFCcgYUP8zSscy1CEYC4yNqWB0r1RUyWMow7K0W9ULqALgkm6VVkSGKaUfqYiUViugogNaKlp1bru8P8v0iANFEfx5+jOi0uA0zz89PxQVoG2k7BsL61WHbG1sVWGnniZEa4N7l3xWNeW7KqxRrSUqEkC/05pFKT8kp5oCWp+M6UEUQaWaJUMUUjkkKDWS5qK/h+T4D1XwA7Na9ZRNQwTVWLeltlFKpxaVtVrzPfFcBMy4usAGAINhAWUATLkJNQmb9BfE0BcG5edP3arXBtCHXjTGojcKcRtePuolR54oKnbTXpSUZ6tC4LTdUPRGKUpqHL0UyYgwvkBpDgr/a545lQ6kRReqwhqVl59C9RRZUM2MjAqCltNLaT9kIBi9jio9yKCY+Eq79SJdUu4NKT2UBqT2M3hAVbFlWY8pT7+qaL9K1yDlyli86yuViryvtBultX3mCIKWAuL1HTDlflPKB3mGfRU9Umk0FN1SIa9RsSXlVeW1L9Rz+ZWSb1BQS2v7lMI/b7n03NO4whWDStGlD3m0qVbA6Pkmhb1kkYwOUMrNvGUDyF8tPfylC/qUt532od/L5veZUoLmLR/UFfdF/Zh74yH5d73ZqKBC4sKVg8hfPagMhuKlujFQ3DAQNB+NLbh+EPOWD6qIyrzl8lwLVwyqa6VojLFQuTygp/tQOhXtQwo+MR7Rd0xpP6qQeb5eL0CefmMxONUMeH0HdE+/VvhtTC0jY6HSIz38Xq80GKlImAwDSv/xVfSoYuCKyl4VOSj39yqDmD6monaqBzAa01qOvyoYNvTHoAJ9f0GnqVlfYOZOVX+jDHuNDYjmUXVBWkqh0cgPSjEkQ8GYImRMHxqSoqiiAOS4oPQeLbVSeffJIUIpP1r9lUrjSdpsTsc0KvpkaBgcKsooIGIG+p1SkbT92QBgXG1gA4DBsIApBYi8RUmbzd6hlGbJnEPMO1TYSyk+5IUyeJLIo69ealSYZsh3NRbsmgwDUuINyr6p2JdyVg0eNGLwIGNA5b8avG9UN0CMPPR3VVijydNvZBkxKvqkyCuvoqb8G9MMSMmw9F5qCj5161X51Jr3M5CxWynoxn1JkScPP7GukKeeogUVVb16HrbmbaXiXNqXlDny+lJe/9AaAPL+kqFAnmNK+1Eee40xh5RjzxI9DUix8NTqLD2UV2/MmS9qGlD0nZ76flOazrzlg2p/yp8nb3zBqkGl5Bc3DMjUH23OecsHTXn985YNKOU6f/Wg8tyT51+lBy0fVCk9+asHTak/FJGYu+YQ5i3Tj1e4clBX8rV5yQCg74NSf5QB0KTPR9+PSgXSWIEo0kD7kQFVskg3EFRBcp0eJSmbL40hzxJZd1FS12+qtRhaP0AF4UYDoNLTpf7nyqDU7otyf6+6N1UxONUdaEYD1ZhQjwpfWY+qAfHn71O9A5RRoFHbGo1kpfBTszytSLg6u00ZCKrGxtCJW3XTpvQ9Q3duem7Jm68ieVl6yk51bruKAFTn7DV77Id47/1zO8zGAKXvGItxDc4NU6EvrYdUz0QpP+ToMDpPDKw+xD5kjASoaKyRBMHoqKGILdVn0dy0DhO70KxWeKbdwgYA46oCGwAMhgVMRcCJnzZ7iwzhZxNzBBkIlCJkpPk0euqH0G+qF5MxWmBU6g30nkYPPtUbmJR/rYDXWORrZPSgAl4VDaDwPL3stU8gvUV5+2g+NUeWufiXlHljbYBKO9BYfGhO6rJrNAIol9lf0KlSIKoKO1WhJClCFB0wUWmWdqvCYmMhJqVaGNMnaFxJXb9S1lTBp+bNJ68sefaNKUDEK0853JSeon5qDDiUfkI/i5cOKJYdyuMnRZ9SdYhNhxR5Uq499dIbTh7z0gV9Kp+/dGEf5t54SO6zSnrYPUv6kXfLIRQ1DahxpFST4m40SgquH0TBKj1Xn+oFKDJByrfy3DfpRsjcGw+pXP/iBj0tqLhBO9ayAcy5Sd9HjdeMB8+SfnXO5PEvXjqgcvgLVwwq40QZEQYjyes7YC5ebhrQU4+038sDB9X3T9EVYkhS6VMG5iHF2lRrplM1RYK06FDpAllkTIXCZESSQUBRAjJKjV5/6ithpIQlQ5Xuc3oeiIKWngtjUzuV8kYRNs37r7oOz+1QufrGAntlFGjROVWMqxX7qsgeGfwGZjDaz2hEKO++weuv0g1JqR9CPmCiHbZIWSTnhnJyEB0oOVdIsacopyH3X6VUDmVb09Zo5VChtdRwDOWwMa7tKc1cA8C46sAGAINhAZ0G9AY0xe2BL/wI3GHHVSMvoydKNgo7DLfQms7Et5m4+6mRGMmbxrcqpX9j0o24P2Yxal3fRKrrNUyPeQZFyZ9X6TbULMdNzXCS9unGxKxWNCbt0+VWzbqm7dfkr8AbeVQ2KTPUAujjX5HjkzqUArBUrIMv8qga25jYrlP3Ze7B0hk9prkbk/ebvIvkbSQGH0pPqCrsxAb3Otx/TQNqw7+F1PDXkRb7HIrSvmjK+1dFklpTJPJ0UgdWb/QxeeyoY7IJFXlPPV16rrWWblG6oE/lZJcu6JNNp2j8iGNYnH1QRgYMDDrG4k+i1yz398oGVTHH4Ha9Ihti5fapItSKql7Uzek3yevmmHPb6/L7URHzuJLX5us0nasWNOPu+GWojfgWUiJfx7RJzyNj4UNKca4tGEDFSG3syMexoFhn7SlqHMDsqgcxIfFVxIz9AyZMfhVZ1Q+h4PpBWYRb14/M+Q9hXPIJjIz9A8Yln0BmzUNKgc9fPYgc3wOYkPQqYsb8AeOnvIpZtQ8pr3/64ocwfuoJjLzmDxg/9YQ6r8KVUrnPnP8Qxk+Rxx4/9QSyqh9SxcIF1w9idtWDcvy1f8DExFfleM3oKVw5iNn+B+X42D9gQtKryPE9gMIVUvHPXKAdO1ae12z/g1JmMDYoAkIpUBRdoVQq+t9S0TGlEKn+BoY+BqUL+lREqLTWbAhShIe8/nnFX8HEhFcx8ppTiJt4HLmlXzXTwWoGQqWnS68P0QyEispeFGTfh0kTjmPU6FOYGP8KCjPvVTUrBTlfQtzE4xg98veYNO5lFOR8Saf/zN+Heel3Y9K4lzF65O8RN/E45mXcg8riLknZWbQfRTPvxKSxL2njX0JB9n2mFJ95s+6W8hEnMWncyyjMvFdn7kpvQdG0zyM+9kWMjnob8bEvolBsU9HAorQvSln0ScTHvoii5M/pxr5hjTHSHBvTh0x0x4aUH6WQu3eZaJWH1gsY03OMRbwmqlBDmqXy8A9hclOpnUNlFH3VDA3P1JvZAGBcVWADgMGwABkA/gkbrNvGa91+bdvKj29FIP42NCbstW1pvzHxBjwn8oLk4eI9FKV+AY2T263HJrYjkN6CxgQbebz0yjUmd9qOr87Z6zh/4xSbsVMkhaft3MnmPGRVnGgoQlyfuRHPhVlcd9j7mJd5r+6111KAFPWi5hldmtZteewGd4+iciRmFfK2GnP/l7gPWI6n7rLE9FLUNKAUP0oJWZzTZzm2Lk96pRflWcsXFkolvy6/31K+wDOA6xc241nXnODvxfU+sqofxIKSAeuxxVIJnu1/EOGu94PGZiyURkBWtbM8Y+FDlvLMwEO2stn+B5G/ehBZ1dbyHO8DyL9hENctspZnVT+E4oYBW3lm4CFkzrc/NtUVLJxnNowW5/Sh4PpBlcq0sHBAGWXeEcewcN6Aqgso9/diUV6fySiry9OZgUoX9pnvA82oKA8cRI73geBzC3sf+XPv1ylFqXZEqylQPSnKepCf+yWEh1mMz7sfBTlfgsv1gUkWJU6rLsWFs++zHDsv4x7453agIMdaXuS+E/78fSiaeae1fNrnUZ3bjqLpFnLxHoqm34mi1C9Yj03+nKIcbUzaB6/mQPBFHJFdiA0RBtmF3CCf0mlSvKlbL8mb4nYrZZy6qyunS6JMT6IcfuqQ7g57RXbyjdtj4bQxOGUmGgqRqVMwnbvWKZj7ADCuNrABwGBYgAyAAtdd2kvO/PGFH0ZN6jb4Io7Yy9O2wxduI484gqeuvQ4rxCOW8vhRP7OfO+IIArNaHeRH5bEjjl7g+CO2Y72RR+Gf2wFvpINciwAYO+0Sw4g/rwNPjsmwv+4xL6lcZ0qLUF15tdxmb/Qx62NHHzMV6VION3lgKbe/IsZm/IhjKo2HUkCMil954KDt2IqYYyip64d3hL28dEEfKkY+biN/HE9MzbH9XsYln7AfO/JxFK4cxNTJP7OUT038GQpWDSI5wVqeHP8zzF1zyFY+dfLPMDXRee5Q8mQbeXLiz5C/ehDTJj1vLU/4mb0s/mdKubc0uopkutLCImt5XZ5MJ6otsJYvyutTvQaMNKBkAJTN70PKBOtzS5n4vKo1oXoSVVg8X+8/kDr+p5bjU8f8BHETj1vKmsTXsT5zI1LH/MRSnnbNc/DP7UBa7HOW8unXPIuqov2Yfs2ztvLq3HZH+fSYZ6xlo3+MQOYeewfC5HapYCfaOB8SZGNCW+dEQrutU6Upbo9S3m2PPXOnrdOmMWEvalKabcf7x68HGwCMqwnicp8Ag3ElggyAaeLb6iWgfz5CethxBGbsgDvsuK28Jm27o/xX0RORJV60lF8T9RbcYa9YjxUvI5DeYi8PO47ArFZHuT+vw1HuJKvO2es8t5ZiQEWOxQ0DKke/qrATb4ycZHvdo2NO6t18K3okN7rmMS2rkWkUtsd2HTdxt6s+ABU9Kj2n3N/rON7YKMrYB4CKVN0u67Fu13GU1vY5yuctG3CU/2JMgu33MvLaU85zLx9ESuTrlvKUqNcx56ZD9vLI1zFv+SCmOcinRdnL8m9wHltwvb08NfJ1zLn5kKPc7rxTI19H4cpBVMTYG0bFDQOOhlNR44CjUUeFyHQfUPoQpQylRNicW8RrpoZu5QHZg4Duz3K/pAl1Gj965O8tZbPFC/jBxNlICbcZG/4a/HkdSHWQVxV2ItVlL6/ObUeq6zVrues1R1nAvQs+GweBL+Ko5nywd05Ix4q93NapQk6XUE4ZB8dHzbTbbeXSGcQGAOPqgbjcJ8BgXIlQEYBwmwhAxJGQHv6a1G0OL6sjeGp0eogIgIMHf8YO5wiBe5etl94XcQSBjN2OXny7F7g38qj0wjvIA+5dKuefPlSEW1nSjSfHZ9pe96QJx1VxI+1PnVNVka5DBICUKyrMJaYer++A6rpb4eSlX6hTcZYs6tcjABpTj52yWD7qcSl3UDZLFjnLv5vkEAGYZh8BKB/1OAquH8TCyG9ZyhdGPqrJH7WWRz2KglUO8shHHcfOvfGQ/bGjHkX+6kEsjLKf2/HcIh+1HxvxKPJvGLQ3jMKPo3ClvTzddRwF1zuMdx1XRdvKEDRQjZbW9qE2wua6Ix5VtQU0pqKyV+9avFDWENiNrw3/FuImvWIpWyEewS9HxaM23H6sv6ATtS4H+dwOx/HVue2O451kgcw95+CcsHeMBGbuvGDnRKixNVO2wC0uzGmTIh4FGwCMqwnicp8Ag3ElggyA6rG32oeb3bvQNK7FNlRNeax2efobkm+2rgEIex9FyZ+3z7Onue3C7BRGt5MnyWZcTXF7rOWp++3rC5Jlka7t3Mkau4+m9CuGHuLvL+7C2sLNtjUA+XPvlwaAxq5ibLREBkF9Rq/lsZe4DyiGH+J8r6jqVcoW5Xzb5ekvzj5oooj01PebFD/Pkn4szj5onW4yTxbi1pQNWsqrqwYx56ZDmF9qnW4yv3QAKxZvs60ByFj4EALlNnNXSFageyYts5TfOXUZ8lcP4u5Ea/ldk5dhzk2HcFeStfzuxGWOsrk3HsLdCSHmnmwjT5Ryu3O7O3GZvSxhGfJvGHQ0jIoaB1A+yi7t6hg8S/rtIwhkEBoMAGrSRnSv98RZn9u9E5sUPayRVrRkUb/qFVFR1Yv7xjVajv/S2Ebkln0VUeJ0kOwFMRs/iJuNL41Zajn2/tilqCrstJdf2wB//j57+TUNqM5tx/2x9vL7Ry2xlv1/9t40uK3sOheFRM1jzy21pJbECSBmQJxAEPPEeQSpeSYlapZIcRTneQBwn+22E7vLubfbcadS78X2e2kSzrXdqXIquXE7r+PEarfl2K8qdnKV+E/yJxW7KvJ6P9Ze+xxI2Jtt9XtRF+9ZVSiQWNgHBwcHB2v41vftaIaoZVhaQIjp+6XFi6hlWApvlFbwZUWXj1M4kfhL178BWgKg2VoyLQHQTLMsxlmAXj/PB84MjImn7eWhTJafl3GgzMCZeEY4j3VVbg8bdnsXDLofcqYekra/8tppeHNLA2MB+gjyN/85VLy2xFks4vvHHtv2aIaKb/zgBAQ2Liv+/eMZ9J/x/WMQZH5k6plQBMBMQ2zQTu2f5FSfrbpLENiU6YuZ7yGe3z6Cr03+TcvQop/lir+cvYcF/ySyRcO5F8tuwpeea2UsQD+G3Bf+CkrtX+KDw0R/GHJPce59ElHyh+eg0TYPgc0rYFh/HwKbV6DRMs/pPImakyu+1izwW9A7A+6mRWi0Ip7fsP4+Z/Lx1CBMiGAfFS0K9IMoOd3Ni5yJx7D+PjLxVOIQ7pHzyINfV0IDqeiv9ihUmYRJ96n8NRVLnFLzeH0PfH5fO9Ru+jrkbnwAr+/7AIoa3gJHRxKKzyYh5kuAbweu9e3A13ZeTILzQpIPER/TvQNW3Q/gmO4d+N76I3C0qQeOnE/C0aaerP5jjT3gvJCE1hMCf0MPtMez+47X90DxmaTYX4f++NHs/vY47pts32XbdnQkocYtGI6uXALnhaRwBqDBsQBlxxPCpK2uFGlEy9szzwO1ZsMF180n923dETjnuYVBfmiOd5+oM+WpWeAibRdLMRl+fH1H8XUIVeLAepvuD7jvBzor/Pv6DdDhvA4XS27A955Y64QO53UIemfgkvXqE9t+X+eEy+YrEKqYgsuGy/C+7jH/OidcNl6GsGsSLhuz+HUOuGy4DF15HVl8Tugq7MQZgP3j2QsEh3COR1q8KOyTzgi0vSLA8O9jhRHJ/ABdr4UzAIfuCP3RFzq1BECzNWVaAqCZZlmMJwD7zyrCX0QbR2qUJGajlponLQA1rR1LFNQ8/VWv31Z8Kq0ATo2nVsmkx9XaAGqlX6LmJFEvw0AGDV8GzzcT9KH/o7Zh5XHbMOcJJ85vzhfOaAe5aBAp+jKRIKr6c4GvUoXFhyr/FNiHKqYUhh92HymdUHjNK3Hgl3jUPbWMwpOx+hCNIqnBclVeJrpEjxOMJ+id4YkABWI0yMnVekk1lwXqFa14Uw8Be6vmuWgV8du72hAiQjSdpScTUHw2CUfOJaH8KP5dcjqh8O23LeFjp1S8/ReTXDHXeTEJR84nwdGB98Vnk+C8mATHpSTn96ftl55MgOMSe35nEkpPJKC9tQfSuXZ48PxeHCpu7AFHJ663X07CscYe+OYh9K8UOKC9pQfKjiXA0Ymv1R7vgZUCB/z4xb3wzcN2aG/uAefFJFivpeBoUw+k8+3w45f2QvqwHU7WdMORc7ivjs4kHGvogZVCXJvOy3xt21VMQNJ5dnjwwl5I59qhPd4DxWdxrfNiEo7Xs31n/uN1PWDvwvd5rEF5X988jD46Vs4LSYgGEjzp8m1LQ61rCRyXklB8Bo91lTeRkZTVVDL6UUYzqvYHtqxAjVuhE62sX8yYBaHPnMTVzvpuw7f22+Dvdu2Fb++xwdnAbaSFZVSifGaAqTL7w3MZqtIXym/Cd16xwk+37YHvvGyF8xU3uYCdPzQHHc7r8O1XrfDT7Xvg23ttcMl8hesQcN+2V+E7r1ih034Vwq5JpMR1T0Gn/Rp852X0v/eCmftJU+Cy8TJ85yUL/HTrq/Cdlyxw2XwFZ3gYne9l42X4091G+Nlpe3GMAAAgAElEQVSWV+G9581wSRdGbYBi5ttlhJ9tfgXe222ErsJOfj2IGQYgvn8sszhxcEKhB7YNQ/yAunixjAxjdD0q6IX43lHFv3EZO5eMBYjokfm2GTMaXafje0eeKMpwmk8W5HM/YwlSK70TAxGtb3tlCNx7TmkJgGZryrQEQDPNshhPAA6c4z8mnDLulXuKOJhhAH8scv5Yoat7cZArYlYduqOis2Nc/ntHeQB/5bVT8Oa2JkUHYNv/AFfhGxig6/uV116ncPGH18V5FV9NtRegH0lS82RV+qCaii93MkO8J35gglPxBTYuQ/zQJCYBjlHeAeC+vOmMQD+eO5nx2i2FM5y/nAJ4CuxJuZQUTjttV+HN3S1Qt/5rcDjnAeQ9930ocb7JE4RAcJZX/dUDwMTow3UA1n+IHQDrPA+KqMpKCQBxu7ubFzkMo8k8n8nVT7SP7FbZgNV+PvxJwX7NgipY/BD8W9PQ4FjIELHiXP05H4JvexqqvNgdKD2BQX+tC2EpRFlZ7UHBLOeFJJyMoQ5A7cavw+GND+DAgQ/A0PQWFJ/FAL3aw9aybUfDiYyEIRpMKP6d6Ld3JcFyMwW2K0mI+bGDUJjzIfh2pCESTYDtipJ0RMO4vpBtP+bDxMR2JQnhWAK8O5W1oaoED+6dF1l3QuWPBnFdyekEWG+kcNs7lH0Px9Bvu4pJQDSQ6Y/6MTFxdLL9ZsfMtz0N0RC+b0qc+GdCa4P4eOlJxe9T0YRWeTEZKzmF97WuTBrRKq8iTFZ6MsHPA5oJKDuO69xNi0ghui2doQtBiWZlwyIXiQv6Z/h5SaxAnpoFRkGaeS6HKqehsn4Riku/DLkv/hUcznkAdRu+Bl98sQ06iq/zhLfZMAeBLcraFv2soi7smcbvCX2HN61As0Fh1Qr6Z6A1bzrDH89FiF/QMw2XTV3w5i6m1bH+x5D33PehTNfDh/njr41mXnsOTvBrR8Q5xhMAvPYsc42RqA11BCjAV/zjingYYwp6XKOErqsZ11TqfJrv8WLN4xSi8b0jigo70YBm6KeM8AQgVtALbc/3KTSjTPvFvf+slgBotqZMSwA00yyLKToAl4Vc+VV5d6HtxcHsMwIvD2HwL2pl7xuFrtwLwhmAiteW5DoApiFhG73tlXtyHYD9WMkX+8cgfnBSOB8QKZ2AFv1MVn9LIQYfFPhHSsYhEJjlQUUgOAsdjmvwvXVZsO7rfg0lji9xRV8STcqg8QzNibn4SxByoVblJWVdGsSsaEGIjog2kgJ9UqmlwK/0JAaTIsrJGheKXYngKNUehKNE/WIc/+nInewzADm/BkPTWxCOZl8bqmIBdiC7PxzDQD0azu6PRBJgvZ6CaFDsD8cE+x3CtaFqybavpSBUJZ6NsHclhRoH1Z4liEQEa4MJPKaC/a5xY/AugvjUVGLiVVMh1lcoPZF4ohNUcgqFx1xxMcVoXQmDjLEOgrd6gXeaXPElrkAsOpcbrfPgrPjyE1z7W3X/Bt9b54SLJTfEszAGTJxbBHoXzQbUxIgL9DTiedNw1ntbqFFSbvodiOcKrg/7RiFqGYb4IYF//zgvTGT1H5zAwoTk2iWDB1UduiOeX9o/LoUAtb08hPAjjQZUs/9FTEsANNMsi30cFqBYQa+U5SdmGIBgzh8L10tZgHb+QDoIFzMMyIfZTEMSKj7UAZCxBAU2CZh2Ni5jUC8a8tu0gtj/knGE3jAxpKBnmg/2fudly6osQISXfvQwH7sG7ikOo5Bx7XurEALkrUYcv/fbPeCLzXNFWneTmMnHvzUN5UcT/Pb6f53PoH90xcWUkr7taSg5lRAPnG5LQ/HZJPh2iNev5ItZgJ7L/0i8dkcaHJeS4NuZ3e/dmQbnxaRw37w702C+nRL6fdvT4BVs27czDebulPC1fTvSYL8s3jffjjRYb6Sk7036vjvkx9TRmZR+ZsVnxMfFvy0NJacTGYlg+VFUPabhYBmrk7sJxeGoE3X0Lzqhsh5VoSkxEA8gp6UsQN9+1Splwwq7JsX+TSuYjG8SfYeX4b3njOLv6At/K167cXlVhrGIc+wTaJy8K75u5bwr12bZ8C7ECvukNKHSIeAcjQZUs7Vlume9A5pp9mk0RQfgGyCnjJNQ0q2iE/D/bHrp6XQA1t2HmGlI7l9FJyBqGX5qqr3VNARo+DfknkJBLwZHIFVfqQ7Atn/Cqj9T9P2jn9q5mBKpr8poHX2xeUwCGG//6/9tDvH57YjRX40W0lu9wHHhzuWhDAhQ2TE5ZWTx2aSUkrL4bBL0OWL/T54X6wBsfe6fpWvtXfJt27uSUPgJ/DKf7ar8tR2d8m2bb6ee+rWLz8i37ej4GJ+JxO/oSGYoQtOcR3n7kvRcIt0HCvbL25fg0cN8hJHVLvDugOxc3Lbzl1l9Vt0P4Kc79kj1LEKV01J/0D8j/Q7/bKvkO7rl4ao6INJrj01+7cFrl/i6+UloQFfbtmy9RgOq2Voz3bPeAc00+zTax+oA6PulHYDVKOn+dLtergPwtFR6Oe9C1D6yehVO4pdVByPFY2L/5hUO9yH+fqr8R0rGwR+ag2+/apV2AAKBWQgEZzO40+l/T92CtIJPKqt8SJNBf9zNi7wiK1tfdhwDvNITWOmlwI+GSWUVX1kHwLc9Dc4Lkmr1jjQOzj5lB8B2Vb5te1dSWMX37kyDqUdehRd2AHZglV3aAej6BB2A7WnpWken/H2XnE4I/f5taXC1yYXCaDCbzoOy4wg7KjuGSYCMYtQVZ4ln+xJXl6bgf9Vu1LY0vLz3R1l9x3TvwHdekXQANq3gjIHEHykZl3zHV+A7L0m6dC/8raQDuIwifjIdEcuwXKNkVZXyVTqfkuuiTOhrtdfWaEA1W2ume9Y7oJlmn0bjOgAvXBLT1en7hVz6bS/gsJqQa3/PMHQdPCfWAXg9BfH9Y9nXHphAjL+Iam//mByHexDZNoQzBocmxfjg10ZxAFiw7dY8JfAPBJHDP1w2wQcPidXke9l0ANajDgBX861e4BSgJOblqVmABkd23HRt+RIP8ivrsepa0Yo47sp6ZG+paJXgtkuRYaeiFYdDS088Cf0QYfyrvAkppWTUj1j5iADHHw0lON1lthmAgmNvQzQkx/iLZgTCsQRYbqbEWPow7luwMbs/0JiAgMAXiSbAdjUJwQbxa5tvp8DXkt0frE2AsTclnDEIx8TzBzGfMpycdTaiGucPRLMRVV4M7kWzEdFAAkpOJcDRkczoBFW0IO1ryWnxTEita4nPCZQdS/CKf0Urdg5oJqC+ZDHr+gb7AtgD/xVy1mebATgCF8pvQpM5uyZFi36WzQAI5nT0MxByTwn98UOT0Gm7mv07qvsVuPRvSOYHpvDaIrp2MSphIU5/7whe24Q0oaNibRXGEiRce2CCMwSJrslVuT1CmtHoC5dASwA0W0umJQCaaZbFOAvQntPIGJFBGTekMEocuKXw/KtZfkgHIO+uyv9DTilH9J5dB8/Bm9ubFRag7X8JrrzPKSw9+5RtE9MGp8rT90N8z/ATVHlRyzBEHaMQdk0+QbXXUjjD6T5pEJj8yCKELD+cBWijwvMfz5vmbD5R2zC0FM5AYNOKSgdghot4ERtQpHSCV/RJAyDonYELrpvwxRfiULfha5C74ceQ++JfwZHyL4OnBmE+nhqslgYCyGriiyGTDwl8NdpxFoB4/Cn491bNZ9JzMuy+K45V2MqGRT4YqqaFjPmQsrPsOAZ9R84nM9hfiGrTdhV554mL378tDTE/Pt/ehbSTkQix2dwH3/Y0BqLXU+C8kOTDtty/Iw3RAAboxr4UxI/2wBuvt0PNpq/D4U0P4MD+DyDv5NtguZkC67UUZ+LR59wH7640BGsxAC8aSIHpbgqCtcq2vTvTEGhMgLEvBeZuXO9rSYB3l2p9PQ4QG/tTYL6N6/n2d6YhWJMAUw/z1Tzma0Rf0WAKjL2Y3Ki3HQ2j33ITt6/eNjEQme+gz3IrBeFo5nEJNuC+WW5lvm/fDty2sR+ZjSy3UhANqdbuxM/Eei0FtqtJPoScccz9KMxm70IGI4VdCWlEq7wJ/nk6OpMZw+DFZ/A8KTuGt2rPEvi34lr/1hWo9mCQX9GKCaUrzmhDW3Do2N2McwAkJkYsQKQr0eBAelpPzQI4PL8Hh1/+vyF3w4+hdsPX4XdfaoPz7lsQCCBErtE2z78Hgc0r0GRW2LL8oTlkCSK9jE0r0GSa4wJ7YdckNJnZ+nW4Pn5Qge51FXYqLEA5P4a83e9Dma4HWX6KxyDOGIT4tePABNcBiTpGOUsQvzYxEUFiAorvH39MZ4RREDMa5PjeUa5hwqk+if1MdV0khiGiZabCDPev/2MkRijo5ZTMT9CI7htVKJmz0Ii2vTIE7sMXtQRAszVlWgKgmWZZjCcABy8gZz9xRB/uRi7+3B6oOnAL/z5wS+H9P3QHH2N80sT1TwlBrLAPqvbfxB8q4vFX/XAR13+ssA9/7AwD+INpH1G4/onbv7CPB+P0o0y6AJFilggwHn9KGuh5tM1I8RiEXcjsQ2tC7ikIuyYhvC6OlJ/OMYTysGHcqGOU4/yD/hmIlIzj8xnGP1QxxQW8SA/AH5rjwby3eoFDhPyhOahoWeLVfk6VWLPAcfyVDYs4E8CCe1JidTcr3P3E009MK5UNWPGn++IzSahoYawuLZgQFJ9BisryoxgMUmBHsI+S06oEgHj3O5Cu096FtJllx1iVuFPhs3d0sMCSBfzmOymwX06C7QpSeVpvpMDRidSclptKkErBpqMzCebbGLBbr2GAbOrBYNd6HbdlvoPbdXTi9qzXUmC9gdsy30mBfhi3be7GAN10F32mu7jOfBsfKxpMgWEIn2fqwSTE2IdBd9EAe6wXn2PsY9u9hY+Zu/E1THfxubYrSX6fu5TkzzF3p0A/iuvpWJjv4OPGPvb+r+O+0HFxdCR5AG/uxtejZMDRmQRjXwqPdWeSv3fLTby3Xse/7V24XesN3EfrtRTXDiD6UdtV/JyOnE9yKtYj51EzofRkgt+rE4Aj5/FcOXIuyfUdKGHkAX7rEocJOS8qmhFlx9iQebsyG0CaE9ShIirbQHAW3M2LiqI1g7VVtKCWAKe7ZQJ2vggyYFGnjL5f3qp55P5n9Loht3If9GLSTh06YuCKOkYxkWePEb1neF0cIs4xru1B+h50XSBtkVDFFL9mUcAftQxzTZKoZZj76HpE1MUkYpihT8Kud3QtIyrjqG1YuY6SfgoL9LmOCl1fWdGErs90HefFHNJ5ybvL9ViqDnfz7WkJgGZrzbQEQDPNshhPAPadeYJTuu3lIR7gY6VqJIPnv+2Veyg68/rt7HzWe4bxR8Y4CF2HzsOb2xqhbv3XmA7AX4Ir9zP4A2QYgPj+cWXbG5exRc6SgKhlmG1bxfOfN8V/6EhxM4Or+9AkBD3TmBjYECaUyeU9iYlB6QTvAHCO8IOT/Ac/XDaBOgCcQ3wZWlmHgHjISQWV+PxJyTfon4EL5Tfhiy+2Qd2Gr8HhDQ/gMOsABIKz4KljOP5aDPS9VfNchIvYV+qdi5z/3L91BeqPLHK4hZrfvew4BvzE2+6Ko6+mIpP3vaZyiWP/S05jN8B5IZkxA1B2HCvWxElPXPnRQIILdhGkhPPZ71Cq7PYuDDijYYVP37sT1zs6MWlQKvgf8io7BeCWWwqXPq0N1mOVnVfp6zK5+v1NCQze+zHg9jep/KxDYBjC7ZvupiDQiFX8wpwPwbsL/dZrGJx745m+UHUCLLcw4Db2p8DfnLltf3MCigYxADf2KR0A2vdQFfopyVDvu3cndghMPfi+A42Z+gXhGFbozXdw3yLRzLWkMeDowM+Ejiutr/IibMpyKwVHziF8iusnbMvUbrBdVc0AHMPPuvQE3vOOj0qbgShfafi89ASeV+XtCB2ioL/8KDJTZehKbEtDXekSn19xNy1CXcnSE+c6CdmRIrZ+3YcQ2IIdAILLhSqnocG+AIFNik5Ak2lOGcj3zkCjRbV+M+oEkBhgp51pdeQoWh0ZOgBqHZBNrLuoKjBQd5H88YOoCs41Sg5NKtdF1n2MGQYwyLcMq66rigYKJQDx/WOqa+pyRtc187r5IdduiRkGFB2Bvaprcg7TCVBpt/BugEoE0n3ogpYAaLamTEsANPtPt/fffx+uXbsGRqMRtm3bBgcOHIC2tjZ48ODBE8/90Y9+BLFYDLZv3w7PP/88nDp1Cn75y18+8bxHjx7BwsICHDp0CDZv3gwWiwXeeeedp95HRQegKzvGn7WU257vF2LlkZNagDfdOwJdh86LZwAO/hcxRv/gJEKLRHzYuZMY/Iu4/FmrXsi1LZsByEOV3maDgIPciIE+wX0CgVlO6UldgPPuW8IZAEfl73H8vqdugQt3uZsQNuEPzUG9MztuusaFAf6Rc0mobEC1XqL/JMhGefuSFKdffBYDt9ITDFfPAj+q7ItmAIK12DWIiXj+wxhIB2vFWHcRFt3bjoGwaAYgGmY4/Lrsfn9TAszd4tcO1uL2g/Xi9aIZAMLwi3QAKIGRzQBYbqWEMwTB2oRwvwKNGOQHa8QaBLarSeHsA80QxHxinQFHBwb56kSQFIYdHeK1JCTGA/9TCQ4fIgiQK74kPJ8anNgFaHAKNC+ci1B/JPv3oNGGEDrRjEA8D7tz4hmBWei0XxXqAJRZvwjxvCnh9SFqHxH7cyflOgB7sWsg9B+YEF8X941y6JBofoDgQ6JrOnUEeBeBQTWrDneDe98Z0BIAzdaSaQmAZv/p1traCnv27IEbN27Am2++CVNTU/Dqq6/C9u3b4Yc//CF/3i9+8Qt46aWXIC8vDz7zmc/AzMwMPP/882Cz2eDXv/51xjYHBgZAp9NBZ2cnfOlLX4La2lrQ6XTwB3/wB0+1jx+HBajqcLeUUaLqwC2hP7BxWc4CtPMHYqaMjctSPuvARtQJkDJ1OEalTD+yteGyCbFOADGQBLDyb7uShMOpBEIUGI7/O6+IWYBefvVD8MXmwRdByMOjh/mcS50q+ELWlq1pHnC5mxfB3pWERw/zofQEMreUnMb71Zh8CN7z6GF+BgRIyvKzGif9TjkfvneXmO3GuysNxr6UmMVnF2PSka3vT4F3l5gFqHBMsn5nGry7xe/L2LvKvl1PCdd7d6bBdFeyfmdaut/m23L2otX89i7xZ+bfloYj5xAuROeBowMTAOeFpJzVaXsayo4luIBcRSvSgNKcSfHZVViltqbB3SzTrFgRsvz4t6yALzInXPtxdAKkLEAv3Zd8/5dx7kdyfZCyiBFLkMC/KguQjB2NtFtk1+zD3QoEiMEpq3J7IGYaAveBc6AlAJqtJdM96x3Q7H89+/M///MnAvif/OQnsHnzZjh58iR/7MqVK7B161b4+7//e/7Yt771LdDpdPDFL36RP/YP//APsHHjRrh27Rp/7De/+Q14PB7Yv38//Md//MdvvY8fRwcgVtgHet1qnNJPpwOwY/P/lPNZGwel216Nqz9SLPfLfEHPtJS/PBDEqr8vMseHfqkLEAjOwk937hG+7+07/5kPAFfWo1oqzQIQxlnGvV5yWuFpLz6rYLspGCs+I+d9t1/G5xJOnAI/++Xkqnz3q3HpW68/Jd/9hvtgvSFZu+E+WG7J/aYeud985+m5+I398m0be+X+osGnf+2iAflaU09K+plJj1vOfZxDUCcADKplu4rQItm2Cf/vvIjJAsHLSk5jZ8DVtiQ9lytaxX7D+vtSnz88J/VLdQDW35drdWxdRQdglWvLav7VdAKk10XzPfm27SOrXld55d84CIc+k+BwIPfr50FLADRbS6Z71jugmWZkTqcTnE4n//+VV16Btra2J55XWFgIoVCI///5z38edDodfPjhhxnPe+edd0Cn08Gf/dmf/db7wjsA61fpAEiUflfjs/7TXUXiDsBzfwvBDeIqWNQxuirPv6zKFnZNSqv8Uo7xgIRjfPMKH+Yl+k6CAlXWLzIlYHEH4KX9P+LDjuXtSOeppvCsbJBzp9NgLlVZi8/gcGbJaYQAlZyWV/FtV3AAlCq9PAHowoRAyocv6wAQV7+kUi6sgu9maruCbXt3pcF8R1Lh352GogF5lV0/LFm/S9wB8O5CDQFZld7YJ9920aB8vcxnuiup8DN9A9lnZrkp99sv45yAGgpm6knxjpJUhZhBhYj9JyMROJVYVVdC1u0KbF4RKmIHtuB31C/xB/0z8g6A5DuKHYDVuosSJXHnmLy7WdAr0QkQdyc/VoU/767cn9uDg8Us6FfPBbhfOw1aAqDZWjLds94BzTQDwIr9vn37IBqNAgBW9XU6HSwsLDzx3FOnTsELL7zA/+/o6IDt27fDb37zm4zn/fSnPwWdTgef/exnf+v94ToAz3eKMf6M4lPkx2E0AR/2nmHoyusQzwAUviHm+T8wATHTkHgG4NAkH7LLPkPAKEAF/hb9jBQfHHJPCfHFjdZ53gGg4N9bhZhkGuw9670N31uXhe9+/a/BGv5v4G7Cyj8N9LqbccCXIEA1ldlx0zWVS1zIq+Q0MrKUnMYB25JTymMiLH2VF4d1HZeSTwR+1ms4RCvCk4eqGc5egEf3tSDOXoilr0sIMfredqQJ9TeJsfCGITHO3nssgYFyq8Afx/UirH04Jp4B8LWwtaL3VY9+b5vYb7or1yAQrm3EYy6aPwhVs9kGwWwEaRREg2JtBsutFBSfVRJB640Ur+pbb4jPhyovdpuIDcp2BbtRjkt4X3Iak1TRuVzrwiHhmgrxuS7UIChDJqEGe/b5gUYbfg9F3+Em0xxcLL2Z/Tuq+xWUmX939RkAEYY/l+kAiK5NrzEcv2T+SagDsG8UB4RF10VGIyrVATh0BzH/jOCh6tAdiBkGMAHQOgCarTHTEgDNPhX2la98BXQ6HXz5y18GAIDvf//7oNPp4O23337iub29vaDT6eBXv/oVAADU1tZCbm7uE8/7t3/7N9DpdDAwMCB97X/+53+G+/fvZ9y+8Y1vgE6ng3JdBNlwdN8Ag+6HENB9A1p1l3hAEF4X/0T+S7owvKmLQp3uf4dc3YeQp3sPynQ9/59s+5P6P+m2ZbfV3vdqt0/y2p90/af5mK/VfXvWx+VZnovP6ris5WvT03xm5bqIlgBotqZMSwA0e+b20Ucfwa5du8DlcnG8/ne/+13Q6XTwh3/4h088f2RkBHQ6HfzLv/wLAAAEg0EoKip64nmPHj0CnU4Ht27dkr7+2NgY6HS6rLdyXeS3+jHXbtpNu2k37bb2bloCoNlaMy0B0OyZ2sOHDyE3NxcOHDgA//iP/8gf/zR1AJ71D492027aTbtpt2d70xIAzdaaaQmAZs/M/vVf/xXsdju88MILTwzw/rYzANu2bfv/ZQZASwC0m3bTbtpNu2kJgGZrzbQEQLNnYv/+7/8OHo8Htm3bBn/xF3+R9Tkvv/yykAUoGAzy/9944w3IxgL01a9+FXQ6HXz3u9/9rfePKwG/fp4zQfzB3x3BwTAmI8/p4kxDECvsg+SPworcvGkIYuZ7XFQmUjoBuYtJ3BaTsCfFzJi+Hx49zMfn0xrDAKr1stujh/mo0GnBdTHTEERtwxB14ODbo4f5uE3nGEScYxAz34NIKQp+RZxj8OhhPqr4Fo9BpHgMlUA90xB1jMKjh/kQ9ExDqGIKwq5JVPL1zkB4XRxCFVPcH/QrdJ7q/x89zAdP7QLn7/eH5vjAr7k7hf4ahdbTFUdGH08N8vyXH8WBSFLrLT+K6r2uNuROLzue4MwpdH/kPLL9PHqYzxlWHB04vEtMPsY+fG3bFfTbL7PnXUIF2YOfw+3TwK/llqKoa7mZytABMPYzxdtevLfcQj+ts95ANVz9MKre6kfRbxhKgX5EUdo19eDfRYOKv2gwBYXjKSgaSHFVXvXawvEU5E8nQT+KPv0w+osG0F80gK9n7GfbHmDr76WgYCoJhWMpMN9RXvv4/+iARw/zIW8uCUWD+Pr500kw9iv7dfidGa6ya7qL75te59HDfDB3s/29h76CqSS+xx7060dwaFo/gv78mSToh1P8fDAM4Vr9SAry5vDzMN1NweEkfqbGXra2D+/pfT56mA+v/948FI4r6wsncD8N99BvvYavSceraJAdt1HVvt3GbRcN4PEsGlT2zdTD3nNfCmxXk2DuVobBTT2o6Gy9gecIKSHT+WC+nQLrNRwkP3IOzzXLTfz/0cN8sHfh46UncCCdBtWdF5Nc84KG1UlDgKhDC6aSnM3KU7cAxWeSOBwfX4IvP6hQlLJrFziVri8yB57aBf4dJJVgb9U8H9QPBGfh0cN88FbNQ6hyGsX7YvPgD81ByD0FQc80XHj/LITcUxBeF4dIyTgE/TMQqpyGSMk4RJxjUHoyAaFKFAkMuafwWsOuP/zaxVSCI068BsUMAxAzDfFrH6n8Rkon8DpoHISoYxRuf9DOr3uR4jG8PjKl86h9BKw3UnjdNQ0pAl7sGlxyKsFZfWL6frxeGwb49ftwUqH5jBX0QtXhbhwCZloABz+b4JoA2hCwZmvNtARAs/90+4//+A9oaGiADRs2wPLysvB5XV1dsHXrVvj5z3/OH/v2t78NOp0Ofud3foc/9otf/EKoA7Bv375PpAPgPnghQw2yKu8u/jiZhvBHp7APfzQKepXg33yP/9BU5d3lAX+ssA9/6BzIdBG1DON22A9azIxy9VEHk7y3j+A22Y9jpHiMPxa1DUPYhYwa4bIJ/CFmP8bhsgn8IS0Zh5B7CiIl4xC1j+APMvOHKqYgEJyFSPEY/mBXYgIQCMwqycC6OP7vnUFawRDj9GeCXp4aDPo9tQsQCMyCp24B/GEU8KqsX+TiXe6mRfBWL6C6by1SfLriS1B2LAGVDQrDT0XLEqdHdMUxEHLFlzICoeKzSc7nX3qSBVHnk5xxhRh/HJ1JsF5DBhd7FwZxjg4Mxsy3Mdiz3PQVg2QAACAASURBVEwpvkvI7W7sY8+7hQEgBX62q0j/aOzH4NLYj8GuqQf/NwwpwaqxNwW5SxjwFkzijftHWdDcrwTnhntK4F44js8rHFcSCv1oCnIX2XPZ8/JnklA0wJ4zouyD4R4G85Q8qP+m5CJ/NqkEviyJyJ9N8v0wDOHr8wRkQgmY6fUNQ6qEp1fZD/X71A+rEqJhZb1hCI9J4ViKH9PcRdwneo+GIXzdwgkMxuk40nNMParAniURBZMpntBQcE83/SgG5sY+TIYst/B5+hE8D0x3lde13FSeYxhKZbBBGXtRF4D85tu4HXsXBvvWGyk4cg7PKfNtfA5Rhtqu4HNsV5iOABMTc1xSEgLnBTxfy44pNLbEGkQiYuVH8eaK43emvB2/I2qqXPoOeqvx+0ZK2p66Bc7ORcm6p2YBgv4ZTBrY30HPNASCs1y92xeZ49eEoGcag//iMR70R0rxmhJxjkHQPwOR0gkIl02gzzmmBP90c47xpCBqw+tgpHhMue6xYkjEyYod9hG8BpaMK8UT9XOJv5+uo3R9pmswXb9ZgB8zDPBiDF23q/LuQsw0BFV5d3lCEHUg21usoFdLADRbc6YlAJr9p9utW7dAp9NBfX09fOUrX3niRvbzn/8cXnzxRcjLy4PPfvazMDs7C88//zxYLBaO/yejuYBLly7Bm2++yZWAv/rVrz7VPvIE4PBF5YdCJRFflduDwT9LCOh/3hUo7MMAnxIDqjoZBjCgtw3zH7iofYQ/HikZV37ATEPcz38kWXWffhCpShYz38MfZFbFj9pH8Ae4bIJX5NR/h9xTGf6waxJ/2N1TvOoXXheHkBuTAqoK+mLzEPRMc6EvbzUG/ZX1i5zu01OLQYYrrgQjvtg8eOoWwN20yAMXV9sSCiLFkSfdFV/iwX95+xIPfCpaUdSLKvkUKBWfwYBeTa9ouYkBl/NiEkx3MQhzdCodAOsNrOpabmKgZ72hBHmmu5gIUKXf1KOiAVVV+Cnoo4q3YUh5vrFfSQ7U3QCqgFOQScF2wVSSB/AUQOtHlcDd2JuC3AUMzinw1o+o1k8+VuUeUYJ0Yx+uL5xQnsuThXvKfpnuKpVwwxAmR9QNyJ/BxMdwL8XvaXvUjaDOAwX4dEyoAk/BPFXVTXdZcjDCAnnWSaCki44hvR9jLx4P8x18vHCMJSZjynPM3Zn7pe6mGPtYl2AAX9tyM7P6T++bjpflJjt+vUqFn84Dc7eSHBj7U7y6b+zDc8l6gyUI3SnejaLz7XERMev1FFeeLjnF1KpPJXhHq7x9CYrPJDkdbukJ7IBRx6zklNIxq2xYhLLjCXA3L4K7eVF5HkuyvVXzUNmwCO6mRZ6QqxMATy129UiszxeZ40m/t3qBFwHC6+Lgi8xhghCYxU4Au36EXZN4Pamcxg5i2URGxT9SMs67nlHHKE8MQpXTSoWfihWs2KEO+vnjDqRYpmsoD/rN9zBotwzzayO/bjMqTwryMzoBhgHlWs0SAKr6V+X2YEJwuBvc+89qCYBma8q0BECz/3Tz+XxC1h2dLvOUvH//PkSjUdi2bRs899xzcPLkSfinf/qnJ7b56NEjmJ2dhYMHD8KmTZvAZDLB7//+7z/1PvIE4NAFpT2cd5dXjnj1nlrPqvby41LyPDEgaBBtg1WvorZhfqMuAO8asGSAfix50M9+5CLOMZ40qKE/MdMQD/I5HKhkHILeGfxhdYxCqGKKQ3kCwVkO/wkEZ/F/qvaxJCDoncEqf2iOJwOVDYu8UuipQdVeT+0CD/C91Qso7MX+dzcvYkWScfsXn0lC+VGs7nvqFrDaz6qhjg4MhIrPMGGuTkWgq/gsVvjVwZP1GgZZ1htKkGm5hc+xdyU5VMN6gwXrfQq8xdif4lVbCp7VCQBVlU13lcCPAvSiAaUiXTSoBJrqoJwCdf0orjF3ZwbKFJAa7j1Z/c+fTSqBLYPrEGSH4Cu0lrZZOKbAimj72RIWCoJ5R6EvszNQMInbMd9RfOZuFoSzIJ7gO7RvRQMKLIfDeEZxjbFP1fkYUqA9xn6lCm++rXwuhRNKMmAYwmSIEiBjr6rz8dgtfzoJeQtJvg/6ESXYz59JKgnKPdX7us3u76gShccSQUpOzN0pDjWi84Y0AmxXk1xB2HRXdc8eJyia9Rp2m46cxzVlx/A8PnJeEQ3jCtZnkzwRLj2R4PAf6gRQZ6CiVfU9a1nicDvqxLnaGEyobgETg2rsFIQqp8FTi8k8wX9IwdsXmePXhfC6OE8GfBEU/At6Z3jhIFQxhWupmFA5zTuPVKCggJ4nCOxGcEd1dZ86nrwQYh9RugLsGhy1jyiwSfU1VFWE4c+hhIC6AKq/ifufOr5U6KnKuwtVeXfBfeiClgBotqZMSwA00yyLZUCAWCUoZr6HbWSq9jNID1WeeNXocHdmokA/RGookLozwCpYUccox7Xy/y1KckDYf/rxo6CeMP2RkvGMalogOIuPVUxhpY51ByIl47z6HwjO8op/qBKTAV7VYx0AbxUGBL7IHIcQZAT+tZgUUCegsmER/KE5Hnz4YvNYiSRFX5YMENa/+AxWO8uPJsBxCZVTi89ioO/owGDfeQHvS04nMAnowOoqJQbWGxj8E1THeh0DOR6I9WDgRcGa6S761UG/5aYStBcN4v8U+FFV2dyNQWLhOAay1usqqMy4EpDSdghOY76Nway6Kk6BuO1qkgfTfCaAVbmLBnFN0QD7mz1PP8qCY5aoEGSnYCrJ95GeT0G1uupt7mZdAFUCYb2Bx4S6DZTIPB5sE+ynaCClzAn0qLY7pCRVlIjkz2LCQjAdOmb6UdxngvfwY3cv8zgVjivdAJ5MjSjbpfdeOMa6FwNKd6JoMKXMO6iSM+oMqGFHtG/GXny8aBDfI58BuKscB8stdv6wc4g6AZabSnJlvaZ0BqzXlQ4BzavQjYJ+R6ciGFZyOsHhQxwCxyBBBIvj3yf2XcuABh1NQHn7ElfV9tQgHKiyfhGT9aZF3pmrbFjksz/upkX+PQ8EERJInQBKAMKuSX698FbN8w4AzQb4InMI8WHVfio2cDgQg/8QRChcNsGD8ZB7KqMgkgERUhdB1F1QC85SUVJQdbibz0nx6yxdcwmi+VhRJyMR0PejCBhd+/X94N6jKQFrtrZMSwA00yyLqROA+N4RCG54F/Tr7kNww7sQ3zOstIoNAxDfO6r4c96F+L5R5UfGOAjxAxMQ3LgM+nUf4vr9Y7wDUG7+Xcjf+T3IXf9jqFv/NXhzRzN05V3kwX1L4QwE2NrApmVU+XWM8h/E+P5xxb9xGVrzpnmVLVQxBfHcSQhsovUrEM+bUgb1KqehRT8Lgc0r6N+8Ai36GY4BbtVdQt969DVaEP5D+OEG+wL4tzL/lhWody5yKBAFJwRLcLUh/ri8HYMRV3wJalxL4N+WBv36D8G3PQ1VXgxqyo8mwH45yTHQjg5F0Zfw/lXeBPi2p0Gf8yH4dqQhWINdA8JZ2y9jcO64hME/BfuE2Q/WJMC7Kw2FOR+Cd2caAo2JjAFdgsLwBEAFwfE3Za4N1ic4DMXYn4JgA/Nv+BC8u9LgPZbgAWPefBLX72Trd7H1LFAP1inb9jyfBl8LDn/mT2MA629KgHe3sjbQmOBVaGM/qvnyfdudBm88AQWTrCMykoJgrcrP1hdMJXkyEWhU7dtOfH1jLx4T/r7Ur92nVOgz1u5KQ7AukQHJ8bWo9n0n7hs/1neYX7V9X2uCJz7eY5nH3Hs0kdEJ4O+bjnkc940Sjoxt705zZWaauWi82AN/bHbAj1/eC8t6B7Se6MFuwXQyYxaEBn/VcKam8z2wbMC1KwUOaD7XwyFEamiQuRvX2q6yjtQ11jG4kuTJ65FzShJAw+7FZ5IcAnfkXJLPv5Qdw4Sg5BQG+gT3KTvOAn9KDFoQikfzApUNi0r1n91TN88fxkSeDxPXLfDZAG/VPITXxXl3IOif4TMCBP0JVU7zriJ1FCMl43g9K53gs0YESaRZgYhzjBcnopZhXgihGQEqgFChg4ogBA3isB52zeUdUSJpeLwjSzBLBuNUV/ozijms+xvT94P7oNYB0GxtmZYAaKZZFqMEIPLS5ayy8W2v3IOqvLsQ3yuQnd8/DjF9v1iW/uAkuPI+Cznrfv2E732dE7ryOiCeO5l9bd4UStofnMjuPzQJoYopaNHPZPW36LGq16yfzepvNsxBk3k+q6/euQhB/4zQ3+BUgobydoQiUKBCUISK1iWodS1lXR/1YwJQejLBmVSKz6oCoPNJCFUnsq4N1iR44G/vSvIOAA38En47WCtYX5/gFWyqEFPgpx/FALryhGBtbQJMdzEIzub3HsNg19ue3R9oTIjXtidAP4rJgWitflT8vvxN+Noiv7cdA3XhcWlIgL8puy9UvcraxgRYr4vft7cdA/Fgvfi4irYdaMTX9sYlx2U4Bf7m7H5fK65vvNgDf5lzBI7p3gGL7m/gmO4d+F7OEWi82MPhUHwG4I4C97J3JaHlZA98L8va+LEennDSvMnjA+i2q0kw9qYgGsTEiZLZcBTP49KTmADUuJcykt0a1xLvCFR5EzyJ9m9LQ23ZEmcKou8Z+QNbVqC2HKFA7mYM/OtKFb9/6wo0mXHAn2YE6ksWMwoErbpLvPPXZJrL8DXrcSYgEJiFUCVeX7h/0zLE8xAmRJX8ZsOcqjiBfpoB4Pj/0gkF8kgsZ8Vj4Mr7XGbhZGsjdBV28lmq+L5RVdFlGeIHJ/h8QEzfD/GDExlFnbZX7vEkIGoZVoo+OsXvPnBOSwA0W1OmJQCaaZbFKAEoXf95Fjhk3oIb3oVYQS8ENy6L/YYBCIj8G5dhz86/zuo7pnsH/nS3Ubo2Ujoh9Ac2LUPEOQaBzStCf6hiSuzfvAKBLdl9/q0rCPfZKvYT1IdoPR0dyF7C2X5al8C/NZ11vW97GnHRbNDXeiPFcf8Ek/DtEKzdkeZML45LyhCt9ZpCZ1k0kALvruzrvbvSHM9PEBN1AmDqWX2t0L87DfoR+XrvTrHP3J0C726x33Q3JV5Pry3w+3am8b2J1u9cZd/uSN7XzjQG6ZL3bbm5ynGRbLtoQH5cVnttw1AKPne4PWuC8Nm8doRU3c7sBFG3xXwnBZ/Ny772c4facV6gj0F/ritQIZohsd6QJE61CHWLBrP7o/6E0FdTiTCfGkGS3WDHJL3BsZDVX1uGsL0m01z2AoFxTuwzzEHYNSksPrQWYOcgflBQ3MjFDifNB6jZz4gi1JX3OXHh5OA5iB8QFEZeG4VYQS/E945k9+9BuJCoqBN94RJoCYBma8l0z3oHNNPs02iUABzS/Z/8R0C5/QYM6+5DTN8P+nUfCv1Ry7DUv2PLw6w+q+4H8LMtr0jXRkrG5X7nmNQfqpgS+9ffB/16sc9TtyD069ff5xVGV3wJbFeS0PrnlxEK1LTImUuE63Puw5FzCoTn0cN8Tpdo78J7fY54rfk2Yv0tNxEfTpzzPBi7loJCyXrC+RPnvHoGwNgvWbvhPs4GSPyGIblf5iuYSkr95m75tosG5O/b2Cv3y3ymHvlrm2+v4r/z9Mclf0Z+XPQj8vdlGEpBzZavP+bDW83mr/M5DD4MToPaYwgPqtksXmvuZsPEjEmI9A1IH8HRmRQnZTswMZIlu77t4iS6+ExS6PdvXYHy9iVhEh/YsoJwIJF/04q0eBB2TUr9EecYBDYJ/BuXFZgPY0UjjROaGXj1hb/NupYKJ8EN72b1BzcsQ8wwIPQHNi5DVW6P0I/FIC0B0GztmO5Z74Bmmn0ajXcAcgQdgJx3IVbYJ/mxeRdi+n7pj9Ge5/5G+EP23nMmcYV/4zJE7SNi/+YV7BCIfmQ3r+CQsMQv6wBUtCBsIKt/WxrczYsKVeFpxCOrh3/LjiWkwYvtSpKLLRE22nEJg//VgiLLTWXYt2gQ/zb2KtALw5Ck0r0rzZl8aEBWzf+uH5ZXm/Wj8m2v1kGQ+aQV+l1psF0VB5PenWkw35ZX+E13xcfVuzMt9Rnuid+XbwceU9l7M3enwCfrPki6KkWD8uOy2uedu5CEQ5t/AtkShEObH/BhZ94JGlZYiwxDKelaczfCfNRJpbFf0SSQJm0598F2RZLsrr8vTYTLjiekSXpFqzgJXy3JlxYI1t2HoH9GWnwIl03ICyc2RfSLkgFiBYqUTsCOrf+Uda1V9wP42eaXP0Fh5IcQK+wT+g/rvgFaAqDZWjLds94BzTT7NNpqMwDxPchQ0fbKPeGMQMwwAPH9Y9nXH5gAV+Eb4lZ2YSe05k0LZwAipRPQbMzeho/nKQO+2fyNFmT3aLRkx/E3meaEvkY7DgzWOxezwwfKFfYRUjwtPZHgzCU0wFjlzQ5fqPLic6zXFcEl21XGmtKFcwDhmHgGoGgQgysSeuJDprcVykZfqxgrTxSSVPGnwK9wDKu5wQYBlr0twYd4s/rjiEcXYd1D1XKsu+1qUuinQV0ZDt9yUw43ka0PVYvhJuEYDtsKt13DMP6C4xaqSvAh3t92BiBYi8fU1yKeXSgcE/sDjQkw3EvBvsMfPBbs4W3/4Q8gfxYpPNWJIGlCGIZSsC8v+9p9uR/woXFiAKJuQtGgohUg6wCY70iS3e3yDkB5+5K0A1DRuiRN8n0RMcxPViAIbF5BmlAh/JB1CDaJixuR4ieVzDn7j/neqoUTYdFl4zLETEPyoo1xEII5gg5AjtYB0Gxtme5Z74Bmmn0ajbMA5XbgQNjGZaxubWAsPyo+6fhryAKk9tPQWsw4yAfO0L+MA8KM5tOV9znI3/GXyjDbzha4bLjMf/CIBciw7j4ENiILEFHnRYrHIH5oEgKbVtDPWIJIyTfoneGDdoZ19yGweQWaTHOcuSPonYFmIw7yGdajv9E6zyn/WnWXILAFff6tK9BgX+BqohUtS1Bbhp0Aw/r7OIDoQtx/2XFk5Ck7hsw9rjZMBsqOK8wlxWeTEA0Rk8998G1PQzSEiYL1miLWRQqrtqvsdoUNToYT4NuRBv2G++DdiYOT5juMn/8e4rMLJxRqSvNtJjzFuOaJDUefcx8ZZ1oSnL9eTcGpZn+hJIAYZfQ5+Nr+pgRX8S0aVJh89Dn3kYmnLcFpMjmL0M7M9Xy/GjJ9gUZMaqiCHKzPfN+hagxyico0VMX8bH2wNsHVi21XMImg7ft2pCFUleBDqdbrKYhElPW+HWmIhlHB1nojBZFo5rbDsQQPiPXDKYgGMteGY5i4WK9jwBwNJsBHr80+MxJeM99OQTimHDffTmQRIhagQKOylrM23U1xmI36fdExJcVl/SgOAqs/71BVgmsD5J1+G9bnZCbi63N+Dbnn3uYsRxlQsF6FUvX1q28J1xaOMbjPKN7MdxRxOBKLC0fFiZX5jjhxigYSwrXVHvweipLsuhJkBxIN4tc7Ucuj0Soe9G+wZ58faDLP8wFh0fxAqHIamg3Z/S2FSFccqpx+QiuAmIFc+ZLCycFzEN8/LpwBqMq7KyZmWKWoE3mlS0sANFtTpiUAmmmWxdQJAKeXYxzRUdsw55VWy8dHLcOKAA0TsOG80/p+XtmKmYYyVYBJyp64/5loDVHnxcz3UN3XMYqUeozvP+yaRGq9iimFa9uv0Hj6wyjUQ3R7ITcmBb7YPFf3pef7YvNc/bP8aAJ8MaT889QhG0hlPVJ8+iJzXOzL3bzIaQcJ4+9qW+L0ncVnkxnQH+oIlJzCJMB5MVPBl6gRHZ1IhWjsZ9zqLOAiCsaiwRSHBRG/PRd0GlF43omXXy36RQO+BVPKkDAJbqkpK4mjXi0Eph9mYla9mSJgpCJbNJiCQ59JcMEp4uMnfn/ipC8aYFSSPfheMwTI+hWlWeLZt9xivPM3lfdObDRELUnHwXwHA3LLTWUtsR8RKxKx0di7kvyY2i8nOSzFep0dK5aU2K4iDavtCj6HNBOI0562Qaq3auYle1eSv1eCxJhvp/isBnHlW27hsbLeYPt8B4e/Sb+BFHotN/EY2S8nM/j8id5VrXlA+68fVeg+iZ6TkgMSP8s7/TbsKvoINr/yS9hV9BEcuPYW1xQwDCnnQcGkoi9ASsb5J96GXQZl7f6bbykwMpXKc9GgSsNgGI8FMUepE8pwLMF1GWxXWaKsTsqCCZ4kV3uWFN/2NET9mEQTjajCEoRJek0FdujcTUgLWuPCWQCe5DsWOAWou2kRGpwL3E8sQEH/DHhqMEGgAkFgMzIIkXBYIDgLjTbmX3cfAluQJYgKD0HPNLTosVOAxYsV3rnkwmFMMIxoREkELFKK3VPOApTD6JPzOzn3fzx3MrMoc3BCuXab70F8/3imf+9Ihm5L/MBEpv+1UXC/fl5LADRbU6YlAJpplsV4AvD6eYjvH2OUcR/yHwOuIGkaUukEKFz9xDEdtQyzDgCjpNu4DPF9ozwZ6Dp4Ht7c3gx1678GuTkPIG/X+1Bu/AJnwmgteEwHIG+K/zgimwZi/YmKj35EQxVT4A/PZfL8b1Lx/DO6vmb9LAS2oN+/BQMAogFs1V3iPP/+rSvQ4FSCfnfTItQfWcygEKz2KIG+q20JnBdQ5beyYRGKz+Jgb8kp7Aq0tfXAGwfaoXbT1+HQxgdw4PUPQN/6FufwJ/gPBUHWGywgvo2BYagag6JClQ4AKbRSpZ4CLfqfeN0NQ4/xwjO+e8M91gEYV57LoR8qpd7H1wbrE1A4oSQQT/DZtyQyAj+qVqv57q03MBBVc+3z99WnKNOGo5nvOxpO8Aq6veux47IT1xPlpOWWUuGnfY9EE1ysytD4Fuw/9AEc2vQAajd9Hd440A7trT3g6ET4VTT42GuHEnzg2tGZ5F0Z7g/gth2XGIwmprxv3440xHzsta9jQB+sU+3brjQEG5TjEqrGDoD6fREXv+UmHnOfatvBBqUjpB9JPam90JDgSZl+hHVtVH7SKKCEQa0ETEmfqYcxQ8UztROInpTOQdIiMPYpomPqhEW9b/SZm7vZMPutxz7znSwBuJ6CktMJiPmwi1aYg1oa0QB2346cSz5BE+rblsbuwDFFWbjas/QEjai7Cb/jlfWLUF+ymHENIBrQQGAWGhwL4N+i6IA02uYhVKnohDRa5zNoQuN5TCWYFSjieVPKtWvTMrToZ3jAH7XhdVO59q1Aa940L4KUG74Aebvfh9z1D6Bu/R/Bm9uboSv3AmcLih+cVK7ZG7HrGnWM8mJLfN8ovyYHmJ8LghkGoGJ/Evbs/GvYsel/wp4dfw2uwjfAvf+slgBotqZMSwA00yyL8RmAl7uyt4v3j2E7ec+wwD/OK00if1d+J7yvcz7hz1n3a3DlvyHUAWgtmIFI6QTE86ayt9EZz7+oDd9kmkMdAEEbvtE6L5wvaHAsQPnRBNSVZocP1LgUHnLnBYQBlZxKcAGjklMJONaI3OlPvO+cX0Nh21uYALBKsuWWIqJkuovBpEgHwN+swD6oUksY7qLBFBx8YwkKJ8SwCn9TAvKnUU2WAjU19EM/Kub59zcleAAvwtGb74g56UNVYkgH6RtEQ2K/45J4RiDMgnwZpWT+8bchJ+dJWMX31h+Bo409EPML1obxfYWqsvsjEfzsRXMb0TDChET+cCwhXWvsF792sBZhPqLPJMgCdZHGga8F9RXUCQB1EkjBWHY+UOfJfOcxBWjWrTJ3i2cfIhH8zCKScyISye6L+RLgvIgJWdbvaOUSlJxKCCFAtWUoFib6jjfa5qHRJpgRss2Dp2ZBSAPKrz2C+STSAmgtyL4+fmgSyg1fkM5OCfVTGDRTNpcVK+wD18H/DXJ0v3rimmzb0wdaAqDZWjItAdBMsyymsAB9gf0QPDlQJmPiCW5YhphxUMrk895uIxzTvZPV/+oLPxQPym1aZiw+Iv/qVHyyIT//1hUpRaCrTUwh6NuehrLjGIAcOYfDuzT8W3Ycg5pvHrIL3/dzuR8hvOEKKt8+epgPph4F9rIa241+WOFd1w+n4OBbc6jiO6jAMaRc/gy6UTiBycPjQ8Cytcb+Vdhu7siZeIQDnzuRGUm21t4l10dwXhTTQvq2p2F3wUdZfcd078A3D9ula8235cOqUu2G7WlwXJLTYYpe28v0C4QMRbvYcZPoCEg/M+ZXJ4L6USWAX+3zJmgZdQLyFpJcUdp8m3WLJJ+p9bp8SHi1Yyr7zEpPJqRMXhWtEqavrXIaUG/VvHRIOOSWa5CE3FPSIWEZDeh7z5kk2izLEDPfk2u3mIYgf9tfZvUf2PoOaAmAZmvJdM96BzTT7NNoH0sHoLAP9OvuC/1R+4iUku5nW14Bi+5vsvp3bHko5ekPueU8/lIqPqL5k/hlFIJlx+QUg6RSSsw/lAwUn0Fs/4MX9grf95YXf4mDoddS4LyI94TdJziIjPfd2JvicJyCyZQCCxpP8UFcKW/8qDKgWTieSf8o5crfcB9Md+W0jqv5ZT7HJQnffc59cF6U6yM4OpJS7YUtL/4yq8+q+wE8eGGvdK3zonzbR87J993RId932VrrjVX0DVY5X1Y7Hwi6pe4EkaCc9PPcgK/NYUbDmMzmzyY5rKhoUL7vlltPf77YuySfyfr7UHxW7pd9x1fTCQl65deeoGdafm2rlPjX3ZfTgK6in4LXZMk12zIMuet/nNW/f93/BVoCoNlaMt2z3gHNNPs02qo6ABvehahlGIIbxNWmqry7Qn9g4zK895xJWAnf89zfSiv8yPMv8H8MMR5PzYLYv2VlVZ5/kd+3PY04/w7k7Sc8svMCYpKPnEtCOk/SAcj/CId+GWUncfcT7rpoUM5XTyJLhiGE8eTNJTnWumASEwhZ1bZwnA2SdmeBAA3L167G1S/TMPDuTEurwY4OeUV3tYrvauufPyzpAByySz9vV5uYcpI6QsJq9bY0OC/I903WAXB0JKXHzXJL3iEw9kqq8LvTfJhbPQxO3aXV9A2oe6DG/9MwsLE3tapuhPXa03cApB2h7Wk4ci4p/443iYXAj7fSnwAAIABJREFUZB1C/5YVnC+S0YT6JTShG5chVDkt1ijZtAyvPv+0HQBG8ylRWI8V9ELd+j/KftzW/RfQEgDN1pLpnvUOaKbZp9EoAYg+3ymklIuZhiC+T0Apt38M/Qezy9K3FsxAV16HcAag3PAFoQ5Ai34WQpXTQqxrsxFpPEUzAI2WefBWL0CjgMqv0Sbh+XcxCsHy7PjgKq/C++/oRAiQo1NJBCw3U9DW1gPfWy+ZAWDMMVQ9Nd1F6I964FOE2S6cYIq9YynIn0nyod+iQQWHLVrvbUvwRMMwhMEaBX5U9fW2CzDZ9XI+/FB1Asy3JTj8YEKI8Q/HsKMiw3yXnhRz9UeDmHiJaCFrKpdAH38LctZnnwE41tAjxosz6tcad3Z/NID7HhXMEFR5cShcuO8ByfsKIDORCOseDSEOX4ijr8XPRDQDEKxJcPpYdQJAg8PG/hR4j4rPRcL7F0wqg+UFU0lMMhksLSiYIQg24KCvaN/CMbmWhqNTPDNS48Y5nWqPgAa0BNm8ZDMCIhrQ+pJF8IfmhBSiTaY5Tj8svLZVTAlnCFoKZ8Cl/7x8BuCgYHYqb1pOA3pwAmLGQXhzW1NW//gmP2gJgGZrybQEQDPNslgGC9BroxDMYZRwOe8io4R9hNODxg9OcJ2AwMZliL82yunmYuZ7EN83yrn8kZJuklOAXjJfgTd3tUBdztcgd/1HkPfc96HU9kWk+qyYgta8aRXP/wq0FCKDRtA/AyH31GM6ACs4AOydgUBwFjw1C9DgWMjk+WfBfyA4C4HgLDSZ5zO4/mtdOADoqXtMB2BbGuqPLEJ5OwZ8pSdxiNC/DSkI/duQ1cV+mTGQnMLhTvtlpPu0XVHEvByXktByugfeeL0dajZ9HQ5vegD7D30AeWfeRvw+G/rVj+AsgKlHgV0UDWBwH2zM5Nonvnwa/DUMKff6EYQFkSiYsY8xt+xWeOGDtSx5YJVZ/TAOb6rZX0w9Chc/55xna2lI2Xotk4uf+OyJAtR8G5OEDFrHEAZ7zosKiw/ROlZ5E5wa9cg5xsSj0k6I+THhKjmNXZeaiqUMf03lEjg6EH515FwS6ksW0b+e+SuWOFzLEn0LDu75AA5vfAC1G78OX3itHU7GulHN+WhCxRiDn3e1Z4nTupaexCTg8W2XnkhwWlhOZ8n81R5kjDpyHvetpjJz36MBZYA8HM08LuEYbpc6TdGQSmOANAhIUfoa009QfWbRIDIMOS4hDSuxDOk34Hpfi6KfUDimSgAGVNz+bKaE6zpsuA+e55AVigTlTD1spmRcoaYlGBHR23rjT+pKEH2tufsxjYNdCgMSsUKpdR2i4QRn0bJdeYxClGltOC4pcznqY85pQtsxyS9vX0Kmr63sM9+ahlbdJXDFl8DdvJipA7JVpSFSNa9cW1TXniYT0oMG/TNcC4BfuzavQGvBDKcIDbmnkAHtMY2TkBtZ0Fz6z0PezvchN0fRT+nK7+RqwWrtFWT5GUOGH7omM4Yh7t+HBZ2oYxS68i7C+zonHNO9A1bdD+CY7h14X+eE9j0NWgKg2ZoyLQHQTLMsxhOA/EsQK+hFWk/G6x91jOKPib6f6wGouf0jxWOcszpmGICYcVBRtLQpkvYR5xjEjIP4o0bc184xCLvwhy7oQa7/sGuSJwSRknEIuacgXDYB4bIJhfffi7SelBwEArNc8MsfnoPKhkXk/w/OQmXDInirF8BTwzi/6xbA1Yb0f+6mRXDFUewrvC7OOfxLTyDXf0Ur8vyXnlREvSgIdHQkeSB65DxW8Qn+Q3SP1hspTjtZehIrldYbKh57xllP3O6cNaU3xWkfjf2pjCoq0TUSd7/pLt7nzyYzK64DSleBOPb5gPCwUvmn/VArwFpu4X4TH33hGL4fY5/Che/oSHLqSefFJPdZr6eg+AzTOriMHRHz7RQP7ClRsl5LQfFZDNxKTiF1aMlppPEsPpPkg9SlJ1FpmQJ3glc5LiHtKn0m5e1LfB6DEgBXXKFnLT3JgvOzSahsWETWpuMY7FMAWHYc/65owc+95BSeA662Jb6N8qMJ/L99ie9X+VHlfCk7jq/vii9lzIcUn8XksPQkMkY5OnG/af8cnQxGxnjtKQkiWlLaBulGlJxSKFEdHUlOjUrnHSWiNCRuu4LnqLEfffYu/Pz0Iwrlq7kbP+PHO0F0bhYNKn/rh5VAXy0qR/AzgqWRLgAlGFxHYoDpU7Bzks436oJZbqqExNg5SjS5xl5830SZSwxazouYJNEx4JC8i3hsSa+DqHuPnEfmLlccv/P0GbvalqCidQnC6+JQdgw/V3ez6jpSs8D/DgRnwRfBLmTQi4WKipYl8NQsgD88x/VHiE6UAn661oXcUzxJoOscaZkEPSgQFvRM82shiYSRaFjMfI+Lh1FQH7UxYUbTEL9FLcMQK+jFYo5piOsARG3D0PX6WXjvORP8bNPL8Kc7DNB16Dy4D1/UEgDN1pRpCYBmmmUxngDkdULbK/dUOgDIGV2Vdxd5/h2jEN87wvmqgxuXIX4QRWtihgFU683gs2ZqvmUT+EOjvwRv7mYdgJwHkLf7fSg3/y4Kd1UiXZ7ClZ3J8x8pHsOqmopru8mMQb4/jJW4Bjt2APTrFT/9YHtqEAakcPmnob4EBYLcTYtMByCTI9wVVwK6mD8BPuIYZ9VqUnZ1XlACX0eHkgAQv397vAc+d5jpAGx6AAcOfAAFR9/mjClFg0rwxMW5KPjpzeTL9+7CDgAFRSS+lTeX5MGcmoqxcEKgAzCkYLtpW2odANtVVi2uelKDgIJNUrRVc7OTsJO9i1Wrg1QJZ9ztQQx6S08gVEbtq/YsYUDPkiVesWX+mkqWkLFKe8yn4n3fjl0ZCqhLTid41Zb8tS4lcHdeSKq6OviZ11QucYG3upKljPOhrgQTAU/dAsLCyjLX1pcs8mCy+Gwyg3Petw27F5UN2FV6nJOe9p0SimgQ3xcd05gvwROB4jPJJ/jwwzGs8BefVXHpb1e49MOxhMIu1Y3nU8ZnWpfIGD6n88B2Ncmx/cRU5WvBbpL6XLJeU/D+heOqRGAqCXkLSU5Va7qbAm9b5rkcbEzwZMLcnYJgzWO6ES2KzkA4pugfkPKzvUuh0Q3HHntftQmeCDkvJhWdAPaZ1ZYjRSglmqTeTXoe4XVxFBFrXQJP7QLXBPHUYXDvD89hIaFZEQ3kBQnm91bNcz0AuvfF5iHoRdFCKnDQNZCKH1HbMN6zAgoviFRM8Y5q1D7CdQS46KK+H/UF6DkqlfaofQQLOEzAkWsBmO/hc8in7wf3wQtaAqDZmjItAdBMsyzGdQBeEugAHJyEmL4f4ntFeFKE+Qh1APKmoEsv1gEotX8RWgqz42CbDXMQdk2KMf62efDF5qHJnB2H22zAjkCDMzuOt8G+ALVl2fG/FJDWlQh0ACoxYKMgw3YVbxSsWa+loOW0WAfg9atv8aosMaXYriR59dRyS4zh9zdlBvEEASocRwrGgikM2GRYev0ogyDdwYqqOgEwDInx5JEIBl4if9SPkKiYT4zDF/HdV3kx4RJhtmN+DNZEmHAK8kWYboLyiD7zWteS0FfvxCC/plKsC1HZsCj017qwkyCaKan2LAnfN6neCucPwpgkiD7vUDUmCaIZgnAMPzPrdeU8IPpO63UF/pN1nuSoci7mzyS5jkTBFOpS0Lko0hHwxhFWJpxPaEgINSUiEabNINDLiIbwfBLNVtS4MLErPoPdgMr6Rd4RCq+Lgyu+xDsCFPy7mzHoJ8VwT61SZAj6Z8BbNQ+e2gXehaQiRdAzDZ66BQhVYNDvD83xDkDQMw2BAM47hSqnMxIEKoBEbcPKfSl2AMgXKZ1QKv8ssI9ahpXOACvS0D11cfm9cRCTgoJeqDrcDe7cDi0B0GxNmZYAaKZZFvv4LEDvCv0yxonAxmV473mzWAfgxR9KmTBCFVNi/+YV/KEVMHEQz7fQL2P52JYGR+cqjDMMqmG9hgFQ3jxWvimYWjY4hO97h+UjMN9mMJ4RpE409jE11QHGvCJhTimYSvJuQf50Eh49zOfiYDTAKWNusdzCwN9yE1+bAj/rjZSUUca3AznnZcel+MzTsd34dsjX+relV9VmKG8X+/3bmF/CCuPfKuaEr2xYFO/b1hUoOy7nnC85LfdL155KSI/bkfPyY267ItdPsF7DLgCHAPUoMDLzbbmGgOGeClbWj0J0eQtJyJ9J8u6AlEWo9+l0I7y7kA1LygK0ynEhiFfJaewslR1LcFggBfsU1KuDe4IRBgKz4KnDxzx1C7xD4IvgELC3ah78YQz26bFQJUKBgl6ENXLoI+t4EuSRAv2YaQiDfBbURx2osB61YDIQMw4q1XzHKH9uzDjIIUBR+wgG+wyqyYN+SgD0/TwpcB/SOgCarS3TPesd0EyzT6N9LB0Afb+UczpSPPb0OgBbJToA61bhyl5/H/yhOSlXt6duQcoDLuV1Py/nbSfYj+Umwl5sV5IZGP8HL0l0AF76JeKhBxGqQwO5xv4UD+Rl3Ouk1Gq4p1RcqRtgvs1w2ZJ9V9OIqqEfxt7Uqpzzzotyvvvis5Ljtv6+nMe/U87bXtG6JOd1Py7XbnA3LUo/c9m5tBpnfGW9ZNvr70NFi3zfZb6SUwnpMV1N/8DetYp+wqVkhhIwzW4Y7jGtCMm5aBhS5gNMPZhQqhmmVtMoMPWkoHDD0+kAmG+vcq5eWOU7fDaTwvftn5RB+dEEhwBVNmBXwN2kQLi8VQgvrGxY5Pe+2Dw8epiP8wAM6kMEBYEAEhY8epiPs0tsFoCq/VT5f/QwH0IVWPUPBGaxC1A5DZHSCSg+m4TC/2MCkwWao2L3UfsI3P1BHGcACBrEIEBU5f/Jz/cokCAG+1EnBemfFfGEwL3/LGgJgGZrybQEQDPNshjvAGyQKAFbhsVKv6uq9S7Dey+IOwCvvHJfyuMfCM5Kefx9kTnwSyr8lQ0Snu9tH6MaLama0qAsDfISnIYGcWUdgJ3Gj3gAnreQhNylJGf20Y8y7vTdEt72UabiO4NYa9Nd7EDQQKZ0PdMB4FVe1fCn9RrixT9JB8B5Qc69LuXSP/bJquiuNnmF/6l537el8VySbLuyXu4vPfH0HQCZoi0p3koVki9IFJZZJV3NBmW9oQyRSzUlduP3gDpXNAOQN5eEvDmkpy2YlK8vmJKoGO9Or/raMg0B6bnMdAL4gHVHkjNNhdfFofhskg99lx1LcNagynqEA1W0KExilCxU1uNMQGUD3lOyoE4IaB4gEJjl0J9AAGlBQ5XTnOyAgn8+BFyKQ8I0E0A+Dg9S4f55h8CJ95QcxIyDGYkBwYqilmGeDFQUXAYtAdBsLZnuWe+AZpp9Go3PALx6NTuG/8AEUoCKMP4Hsd0cP5SdkzqeNw2XTV3w/rrsMwBl5t8VYvybDfhDKcL4E9WniMu/wYEt+QZH9hmAWteSlGPceSEp5HWv9iyB5WaKw30cnUkOozB3YyLQcjq7DsD6nF/D4fNvc7pNYvAhOFDhGAZUQtw04/GnBIISDgr8iQY02CDmhS8awOSF6EfVLECOSxLcdOUSOC4lhVh3PjtRKsDKu8U4+xoXMq7UCDD89SWLUH40ITwfal1YoRW9dr0T2VxE3O5NpjnhvEijfQF8ETHve6NdGRAW7Xtlw6LwXKxxiWcXqrxssFnil+kjxPzIXhUNiOc2+GA3JQDXFaE4c7d4foAGdYlhililCqaS/H/9iBjj729CGlKRP1SVgGC9eHahaBCH1WWzDaJ9r/YoDFNlxxUIkHoGgFjACCrkqVuAyvpFHvx7qxAO5KnBz5/YgdRBPw0B+2LzvBugrvLT/+EyrPDT/5HiMYUZiLGr0ZAwsa9FLcMQKRmHcNkEVvZZIB+1j3BWIBoO5nMAxsFMtiA1BMgwoEGANFtzpiUAmmmWxTgLUG4HxPeOcE7p4IZ3ucgXtYzVnNPBDe9C/MAE/wGKmYaQy590ADYuQzx3kmNYL5uvqFiAfow6APYvIeWdd+YJHYBGyzxvlwe9M9Boe5Jrm6prnlpMAvxbFZ7/+hLWsmf0no32BfBvXeHc7jVuhQe8VXfpCc555wXGvc4YRNR89sGaBGf7ISy99UaK03zSveVWCprP9cAbB5gOwOYH8FrBB5B7/m0leB9SqD4J1lM4wYL7e5gEqLnRfa0JrhNAvP/6YTZIPKBALooGGbOKmsufcfUThaLpLsN4d2fSPxJVZzRI7EcK97r1RorTUnImHXZMq7yMTpEx9dSWZ+on1JXi51F6gmkrbCVudfRxWs6jCf556nPQ32BfyBjGbHAuZHzejdZ5KD2RAE8NPo8+b9p+fQlitr3ViOWuK1kC/xZ2PmxZgQb7Ag/a6kqX+Lnm37oCjbZ5Xun1VqF4nFpTotG+wPfLFUdO+Wx+dxNWiPl7I90JxkhVfjSBAlOqY8p97FylY06aFbUuRkfKqFDVGgY+pllBn8eR88kMTQvf9jSEqhKcScdyU5UI3sTz2NTDzofrCtMO5+mvR4YhU0+KD7QTaw+nnR1lcDZipGI6At5daQg2IAuQ4d5jfrb9QCMOCBt72Xm8S1nra0VGqsJx3O/Hz/NwTKHetV5PKYxUzB+JMC2P88iuRCxMRAUcXheHilblMRoGpvPXU7cA5UcTSPtZi8khJQGV9excq1L0AoL+GTy/IjgfQImBmt6Y6EBpNoDPBDDaUEoEovaRjCHgsGsSA37GABQpHlMYgUrGIWYY4NAhmgHgMwKFfZy+OVbYhzMA2hCwZmvMtARAM82ymJoGNL53BIJE87kBhcC4HoAKN0otZDXNXLhsgguBqWlA6fnx3EmVbwXiuZOc4zronXmMBnQZmvWschae40w/aprPZv0sDt7VYiu+tgyHfdVUntSqd7UtwYnabvjvB+zwk+f2wp+8boezgdvgbl6EsuMJuKQLw58ctMPf7d4L3zxkh+N1PVByCoMm29UknKjthnSeHX7ywl5I59khfrSHB0zWGwr9pv1ykicClpsYjLce74FlvQN+/PJeeNfkgPrLPWDsS2VAeGhQ0tjLsPusG0AJAhdT6k1lVFuLBpQ15m42O9CHyYe5GwMzYx/j4b+EtKQkCGW9jtul/VYPf1qvpVD1lottIZ0lMQDR0OSZ4B1I59nh73bvgT85iMet7HiCY6VPRe/ANw/Z4e92of9M8A7XXzgTugN/cgCP+X8/YIczoTucd99TtwBng7fhW6/Z4Kc798C39tngfMVNcDfj0KW3eoHDLQhqQZVZNS7bU6MMZVa0LGHwFZvnA5veatXQZmweKusxaPPFlIDfU6cEbZX1mEDQeVdZv8g53/lwaDMqxAaCszg4Wq1oUNB6Yo+paF3i+0xY84qWJS5ARdoC3uoFzk5TfCaJQSjTJSDqSld8iWsokI6CK65oFZScYkJmTL2aROzslxH2YrmVeR44LzAtgWvKOWPsYxoX19i5wzpdprvKuUQsQNSZIt0Jyy3lnM6fYQPso8pzqRtGMzG5DNZWNKjMIajPf1NPiovW0WsTDM9yE59ru6rM59i7EOZD3TrSlSDtBdIHcLUh3Ce8Lp7xf8mpBKcNrmhFClFPHSaN/y97bx7c1nnd/YM7JZGSbIsUJUviJhIkCJIASAAESOyruC8gRVmmdlHUvlArRYriJm4AkqauN8VJrD/cdjqx8jYW2aSxPWnat5ETu24iRXZe581MO30du+1Mlz8cderf+f1x7nnuhXifS9eZqT3sPTMYkjh8Li4u7r14znnO+XzpM6MVATpv6BwgHQDnjlmW+fe6McvvdU4l6KGw/gAJItTrwMCA6v7JF6wcZuU9tHpA5TwB83VcARDu1dQ8HNJeEmv/BXRowDSKGNDSixAwjaolQKqtOFMDANVUkzERA3pEvoRHMolnAYCwjEwNaAETagDwSoB45UPtFcLknlMC1KnFAIBX8tGux+X3FrN8CVBTHX4x7/WcgbvJNdCreQUqNX8LvZpX4G5yDewOnYO+wFl4S2Nc4uuJDELlqTh0dw8uHZtSA5270c8mQmfFLGjlKZyMtBwdhE9S0uBdTRUb3530R4g+PCs2SZLaKmVOqSm4bCgOzp2PsNNbo7B9Cpnv2hGhQXNUFFEidWESR/KHRLa6KxtVZ3UXRK0CEpSSTvxs3fMQ9PFLo6y7orC78Zz8MW08B9beKPQFzsr693rPwB6vvG+P7yzYIvNw0HxyqT+pBg6aTzLiSrt+RmT1Zwq6D82zbBLWVjkjBoSU4RdILvsaTsPzOd3QnPoqFKa+D4Ub3oZa60vg8WI9dlvVjJChx2CzzYDjvI5JcIVmlvqrZsQgonVuiSZFWyUGF24/BhGtxlk23r1qAYNVQbSOVkZIr6LJOs/KTeyd85JVFzHQpcy0vWs+UT9B0Dew7hL1FxobRA0D0rQwDKBAW+0eMQCoPirUxfeLAmQJuhDZuBJWeRrPQdIK0J+Js/IhCgD0Z/D68DZJdATWLeJ1cEYIgq/Fwdss8Ut0AKiESKpn4W2KYmAgiOEFPbQCIPgFlWJjP67kPaoTEPRFWSBQs1/Q+pDoTnRp+lnQxFayhM9kh0P4PISAtdkyn/B5thpxxYdWBdqqxHPRk7EAHWXiKoCvYRLPVamGSQXSgrzOKajTPw/F696CwpT3oTnlVbi5thOOVAwwElCkeAI86UJiJe0ORIonxIm/9hJEtlwXEy9pdxDbLPQHhCqGIJI/nujfOqY2Aau24kwNAFRTTcaWxYCm3REbxYSa0YBJQNGZRCSdUhOwIuazfkKxCdi5Y5brd69aAHuXMvbR3jkPz+b1yE5mn93cA89ulvf9wZM9UH0sBs9sk/c/s7WHqa/qLoqqvqRUWn4lDq/pjPCupmrJ+PSkTyC//xYr9SmeRQILle5QptPZw6+LptIJUuul1QAKSKqPxcDbxKn59kaZimrNflzloIkfZYiVUJyWp6LwfG637Lafy+2Bup55eHYj55jn9XB9L2zoBkfjLLzwhPy2n9/QrRgwtpiQxsKr8W8zzMJByym4K9ePkvwQzKabfM2JShRw4vUAtFfghE7J79wxC23V8v4WM78/gEqQeP0JLTVY7sbrhWmy4YoBr4eAyoSMh2IJzeCGI6J6M0/3wbcjys55Vgp0Qcz8l47h37x+Fnd7FEomYvx+l518HQBvU5QJ0sn5A0EsIeL5g158z7zeiCbbvKKeRV0Pv4eoxYSBKO98atdj0NhWKX8+dGqnwGJ4EVKSHi7xvaUxwYC2X6HvCkXEIvkc/5O4ohvJG5Y/bhuPghoAqLaSTA0AVFNNxj4LBpQ40rTkTEg5FgBYxhRRnoqYT/uEIlrRFZr5nfzW3ig0pb0qO5ltSrsNTWm35X3pt8EwEIOmdHl/Y8ZtNukvvxyHb39ggBv3drDyHN2lOLyXs0mRAlQ6hhP+knFEJxbPxNjEXpG8snaR9Q5UH4tBwe9FmY4A0Vsqzivz0Y39WMf/qA6AtRfFk5SQlJbdUWhK5R/ThtY5vj/1tqLP0TwLzcv4eboOnkxlXQhPxgL8YGMVn0i18b6i5oQzPKMYjC5HrPJ4FPwZCgSiVQvgaJpVDHRtEWX60XIaBaYDmOWXrgQZ+7E0xtivTIWiUqDKU6KuhHZEFLirGFTg/K9bVNasyF5UpBdVnlKgAGUvQwHKWgTjIWWilRJ5yRZRSD4In5nSubjc+bDxiZ/L+no1r8AbT+i556o37Q4Ejdf45La0OxA0jHD9SIRTAwDVVo5pvugdUE21L6MthwH1pN3BOtHaUawblTSXMUGa6uFlVgA4vowF8NvGl580KUz4HI2zihObup1RKEx7H+Qms4Vp70MBz5f+PhgGYop+qv8vG5JMds6LCqp3tEauDkBG7sdQfUxU/i29LikJEur7lfjm1MBbfllQE74YZ3XcRCNS4p9XHRd6A4QyCJr4ERKRK4i1zDEtSn0PbJF5KEzl+5V8zvCMot/juaGoC+FonFX0/2rNRu5nsmbNbxSDSWf4dwhGk+7hviuMV9SzaOTrWZQl3wNbRFljwPKUgj6CoHlh2R1l54HxMP5tPBRT1nUQWPxUe68/G4eCr0QZiar6GPaeLKcjoKh5ofDa5VeWuU6UNAyE963kVzqmdT38Y850IRTORcXzIekeZK3+jayvSvMufLB6o2JiJVg9rOyv5PsLNd8BNQBQbSWZ5oveAdVU+zLashjQLdeZtLxUht6fFMH6f0GJsrN0it8DUDzBLYvw1U9Ah46DAdUhQYNXNtFqwkbKpjr50oYmK/YAFOS8/ciXHD62bnkHtm1+h+sz90Vh61Z5/5Zt72DpwzmxUdcwEMPJuKDG23p4ELqT/kh2/NqyB4zaUzKBrHTdRbGJVzFrunaRNV9SvXXFYJw1OFLzplJm07IbM/2mg9gMKi0BsuyOcjGfhNosyJU/pgW5b4OjeRYKN/xU3p/zNhRukB9buOFtDACekB9b9PhPsYlSIWvqCkwr+l/PqeSvAOTcU1wBcPsUtp1+Rzmjm6m8guDJXFD02TuVS92cOxRWCFYtCArKCvoJkfmEQJAaiE0HsARISS+j6iRO/Gv3xlizue6i2LCrP6us9KsdUV7tUroOyi/z9S5Iq0NRH+Egf4VASbOCNCeUlKGxPFHe78lYAK9zSqE8cgFyc+7J+no1r8Abj+sVky5BwwjfL6wA8NTdLSnqCoBqK8s0X/QOqKbal9EYBWh7P0S2jIoYz9TXkPFvvIYkIKH5VyorH7CMJawCSDGgRAHy28bB1zApYj4J46mfYY1uvvoJrKEmzGem0AgnIPLcvmnW1CnFPjoaZxmHmxoryd9UN8+a+PThlyElObGWNiX5IWgjL4M28jKkaH6b6Et5CNrOl6HqeBz9KYljk1MeQnHfLZb5144IvHNCHo7i3+WXsXkxPemThPFJqf8B247dgrKrIjWFiCZSeg+vLtrTFsUVgItiw3H1MWwMNgykd3qEAAAgAElEQVQgiaj6WIxb+7zDIfLNiYNOEz97F/osT0WhsT4ROdloQwRiQ+scGLzflD2mpvpvgHPHLBid35D1m81fB5P9Je5YR+MsmI1La59Tkh+C2fgi1lXzmsKFOnteMNqhvQGHDcflewCSHkJN3UvQVSI/tqtkCpzhGYgUyddVdwrUqo4yXkM7kmCUasI7tDe4/QfO8Ay/B8A8B/Ud/B6BZgtShXjN8vS5WneJgSCdF6aDSBTiagh4o6yRvPK0SMCqPI3BKBGyvJxz2duGPQRczYq2KNfnacNGX9514m1CP09jIBDAXhilhveQgg6ItTfK1X1oNiN1qo3Xj1KJmgC85Ed7xTSYa2/K9wAkmeBw9THoKp6UT7rkjyOYgZN4iRRPIplty6j8cckdUAMA1VaUqQGAaqrJmBQDytjQAh+a0HFMYl6g/oT0V/F/yi5DqOwyY/0Hq4fB655iEvVe5xQTsCE1S6Z62TDJ/nb7p8HtwweRVhxNiFd07sCfXvcUU9gkKgoJ7tg75xkBhjG7OxGxWNeDf1cGX4b1xQ9g1fqP4PH8B1De+jLU7omBuS8KVs0gPFb4AFY99jGsL34AZW0vg/4cUnT0Z+NQ0nsL1mofQOaGj2Gd9oE4+b8orgBQIyTRTyoGRRZ6wcFbsLb8AaRv/BjWlj+AbcdeFhGfAsWHSD6U/ac6fm+TwD9PuYfklTYkCFWdwEm+6QAKeRkGMOtvOhBjeNLqoyjoJdU42OHAVZHavZj5Nx6KMeyhPynCePOW3VGwdyGb3roLJ/2Oplmw7hLFkAyub8KGLb+ANdkfQc6mX4DB+U3EcgpITZP9JcjZ/AtYk4V+s/nr7LM1m25C7sb7sCbrI8jNvQ+1lpcYGcXtmwaL4QXI2fwLyFr9G8jNuQdm89dRKdU+wcThpLoQHbppdk65/dPQoZMElOl3cALuRbXVQ7Un4MX1XaImxbqfQK3lJRRhEibxngxBkyJjATq1Iq/dZ58Q/cnkvwFu/zRjuLdVzSQEux1luNLldWIwmxDsCpQgUoZ9VO+iQzfNCEP2znlGGKJAua1KVJj1eG5As3meBcpEKCI2fUPL3CP6CYvQYpoDa28Uxa265hMCQXMfknLMT+NqUdiZeC6F3Hj+UDN5zT7EbVYMxplIHiE4K09hMy6dy6QjUHVCLGXzNiIFiPzOHmwQ1l1Yeh142qJMfVh/Jg7OSOK23R0YJNNKmVQHwJW1yBqIDQO4349eJ12afqjdg2VQTAdECIRDbgyOLE/hNdIo1WZYtQAtNXNg2S0e0xZzokZJq2mWCYNRo7B4rmLyg+55tZaXoHj9T6Ao5T2kAK3rgiMVA0wULJI/lph0EbRXAubr2AhcMM60Wzxpd1DbRSL6FXny2iPaL9ehvvCgGgCotqJMDQBUU03GWABQeBCRcOkSHYCtWN5DkvGRLddF5Fz6AkSKJ1lvQMAyBp3aKYlfRNKhT8r5FzL8Avfa7UeFVU+G4M9E8SW3D3F4j6ITPZkL0GJCTnt9xxzTAWAoPkFAiRjo9s552OEQ8YhuQSDJ2huFmn0x6NL0M8wfCX0Z+2MMbxj0iwhBEtOiDD9xy0mIi8oeSsYxAGg/MAhfK+qBxozbUJDxS3iy6B0o3H+L1f1XDIp6APpz4koAlQd52xLxhaRuqrsQZyJHugtxhmqsPoZBTe1e5PUHvdj8WZpyn4l1UfaflE+lmd+Gljmo3RsDR9PsI/hDxBs6mkTUZsJnkoGfSUMr4i7d/mmcrGaKn1m7Hhn7bv806j7Q5y1Msj2eG+AKTCdM8MnfVYIrRbSi1Llk/A1kqNsnIGC+Dl0lUwn+VgMy2H31E3DYcIyJ0hWmvA/F638CZvPXmerqo+dqpBi36/Hia1BwQdvu0GJAS5N4mtDR+A4dnutu37S42pUuGS/BQtbYXoKcTb+ANWvEwIiCYldgGkz13xADp433wej8BgbPwjEnsTFH4yzTQajvmBO1E4Qgub4Df6/bGWV6A3U7owm9IEQGMh6KsSZhJpr1NF47tXux5Mx0AAMB+r1iMM5IU/ozcdaXUnFeEM87J+oHlF+WrKAJBKzSUTGwJiQuEbIoOKayOdaHc1Ey/nqcqV0zRO5x9NfsF4KS06Iads1+fB+GASxj8idF8L0fjrFjYYvMMz2A2r24MmLtxefJTwkHUg12NGKwTDoBbh9+1qQnQZ+b1zmFfwsaEkwE0T3FEiV0/nqdU0wbgM531pNlGmWJGkZqE5I3pCxMui6hkgssEAgarzFRsPriw2oAoNqKMjUAUE01GWM9AHnH5ZeLN+EXA5fzn4/Zfh6SrlPLL3voEMoieMvgbQYU0eEto5N6K69evbF+HkwHYlz8YdAb5S7/B/1RxTIaT1uUKaWWXY0nKPtSZr/18CDcTalZMj455SEUHLwFFedx4k9KwMT1p5Igbwu/dEF/Blcoqo5jiUXVSQwCDANYtmE8FIMdDs5xseOEz7oLJ3h1PWLml4S6eDjLVuOsYmlDqwk/E17fRodumlsmQ9nsTi2/DMdXPwGdnFKZDt00BGpHFcpwpqC/6hi8pZEvAbIYXoAIp6yiqxgnXErlRaRozfP7Gib5/S5l0/KlT0kPocb2Eng8N8BS/QLX79yBK2GtJjHoIhVjW2SeCZy1GhP9zWYsZbF34QRVSgEiVWcSzGu0iwGha80iBL24MmDsjzF1aApEqQyt+ij2EFSewjIfpkmRtQj+YJSJ1pUNJfqda0XWf/llUSWYNARcnaiIXTqKk3pnT6JeBmkIUFO+tykKrmwxiA8Eokw8rPpoTKJyLOoAVJ2IIybUR6sDuN9hJx4XEsR7VJuhxYzHiwKwFvNc4mdShZl/UqVuNcyiKrUkIKRVUrPpJhSt/wkUCToAL67vgsOGY7i6KpT5SAUWu4onUfVXmPhHto4lijMWCwGDaRRCuisJAo3e1NcgsumaKgSm2oozNQBQTTUZW04HwJN2Byk/HGScdxn/chQgRcpPBlJ+eH736kUUWPqc+EPXGn6Tnyt7EapOxMGl0IBITcBSJV6alGhH4nCnzMhtOF2nfcCQn9phsWmSMpbVR5XxhaYDwmT/QIyV+1DNdu1e/Lkcy5/UZM19YuaXVlR4DaWezAVlFGfGApZnfZ5m14wF1IVQaIz0OiYV/X7buGJz5Os5ChjQnHuKY72OSYUm4AVcJVBoIsamT972F6Bo/U9kfYUbfgpe5xQUPS7fHF244adM/IwXKCv5W2rmWGldwkrQnhjUd2B/QbOFE0T7MAigDLrpIP5eeRonz9QX4NvBr/GvPqqgAxCJgquTryFQNhTn+r1NUdCOKLx2cxR0l/j+kCsKQU4PQKMNVwF4x6XRhmWJLTXyfRctpjnW28RLflirXljSK8N6AAzHuP0qy/YA5I+hCBhHoDH4eD+oAYBqK8k0X/QOqKbal9E+kw6A8ZoiUi5QO/r5dACWQ+El3wO3f1oZj9jExyMuh+rTpigjBg0DCojA1HtQeVosNyj4KtYrU6lC2dU4vLdhExc5mbnhYywjuoJBw6cfbme1/+WXcdKktG+k+Gvsx9KhTz/cDqYDWM9Mqq9K4627cOJWtzOaoANgi8xDffvc8rhLhc/U655SPh8Utu11Ko8NmK8r+03K5+KvVvExoFmrPlRGJxpGFP1+27ii3+uYVPQXpnDwpynvgc8+oYhHVQpO3KsEAhEvkF61wPpoWAAglArRyoBSEG3tjbLA03goBp9+uB2qTsbB3BeFylOIpuUGs9mLGOwqBNpKFCDtNWWCkHZYmUBkGIjxdQSUEgRrFsH8tIK2wqpFqO9QSE6sWl6zQokC9HpulWKwiuKMnG2n3YFgJT9pg8kgNQBQbeWY5oveAdVU+zLaZ9EBUBSVSb8DfusY35/xGTK+CtliR+MyeEMFASTXGsyUu3j+rEXuxMSZrSwy5MxehIrzmL0vGcc6Z6o7ptrl13T8FYC12gdIABpGDChl/Uk4qWKQv/rgWoP4Q8MRzLiaDuKknyZgxkMxRBQqrIzYurExtL4dJ3o08XM0zUJ9+5ziCoArpIyz9DqnFDPlSmOXU5VWXCGg80nhXH3jcT33M9n4xM8VVasD5uuKq1kBy5ji+/YnRRRXAJpT5AXQmlNfBbd/mu9PeRWDLoXAyuNV1k+gvgFpIEjnR0MrPyDUJmMwae6LMqSs8TCegzX7cAWg+pgya193QTnYVQrCdReVNQSW0wFYTkdASf/A3Bfl+5fRXvgsIoZr1nwk6/ssOgA++8TnDmZVHQDVVpppvugdUE21L6OxHoANR+SXi4vGUTaes1zcVYKNjzzZ+Xb9DLcuur0CyS28evO2akR9tho59eZGbHDk1fg32ufB2M+vhfeHsElWzufbgTX+vDp8d3sUtMNx2H4jBqWjYuNu+WWs4dcOx6GzT74HIEXoAdCOxJlgEjVIEkGo+miMW5rgD0VZbXX1UZx0mfuwKbNmHzYnWnYjxpNXEmLui0J9O1JKpPQXoi+1mORLF4hQwvtMOnTY0MhDWnaVTHFr/DtLp8BvG+fjDYvGFf0dZdMQsIwplEaMwRHdEW4PQF3Fc9zzOFI0DgHLGNffVTwJIf1Vbv9Bl9BIzMOIRvLH4ebaTlnfi491gc8+AS8+FpH1v/BENwY+Chl+t39auayrcRacO2YTSoBsEVwVsHUrqwyb+3A1ia0E7BH7UIyH8ZxUUqWuPM1n9TvXLiqqBFecV14BUFIZdmUtgvFwjOt3r+YnCFxr8H0rrRAoJS88mQtQ3z6nvAKw8b6sT9QB4Aerv5MSsLoCoNoKM80XvQOqqfZlNAoA7NojiUi5tDvQVTwpEiRMo6xhrCzpHngFP9EngsZrAkVIxCd2lE0zMgpRX6ToQ1cIWdiOxln0Szj/LWaRXFLfPgctNXMCcUb0N7TOseyj2Ih3j9FurLuQdGPuw8kwwwCuWQRfGCf4VSfj0KXpB1e2gBDMRgpQ5WnM4leeRo64M1tEDHracPJPgl8l45j9JwVf7TV8XjsSh/b9g/C1QqIAvQ9bt7wDRXtvQfXRGOguYnZUOyLQUU7FWVOv7iJm+APBRHxh2IkT/aoTiDC09iKxiHCG9R1zrAzI2oscc/cq8bi0GmZZlr9uZxTqeuYTMr/OHSK5hKE2k/CYt+uxedHtx8DtUZxlu36G4QuR1DOVcD50luK54LeOiZhOwddVgpoQfts4+K04ifekE94QKUEByxgELGPgdUzittLFc5Um6PSQnque9DsQyR8DXwM28g5o++Fmdic0JwsY0Oy3oK7iOSSnVA9DpGA84TqI5GPgwc7zrYnoxa6SKUYQ8tvG8bXTE9GMXsck6mYYRvBcl0E39uuPwltJJujVvAJVmnehV/MKvJVkgiP6o+BrmIQjMv67SSY4bDiOJC1OPXl7xTRDjMrWowvXkjM8IwaCzQJBqB2vP16te5MNiUKW3VFWelbXM88ag6uPYkAadnKC2SBea1wdgNYoNwh3RlBxmDfW2Y20Lm8zv5GfEKP/1QRB0I/XIU8nIOzEe08jJznRakIKEK9HoK16BmpsL3F1AI7ojnCDzQ7tDbxfc4LVTu0UQ4TK+QN5x9UAQLUVZWoAoJpqMiYNAIKVw4ztH9JfZZP/UMUQ/m28xvjSARMi5QIWRNH5rUgD8jVgUOB1IO8/UDuKkzbnFOOwk7iXKzANjuZZpgHg9uHfrtAMm4Q6GmdZJtLai1lr664om5jUt8+x7GN9O05+qcGVJiTGQ4jHNPYLKrkn4mzSXHUyDv6kCBiOxFjTYtmQmM0nvr/+HP5ePBtjjbulY2IPwPbJGMvol47F2e+kDEzYQhL5qj4WY0JepCdAIkpVx3Fyrz8TZ7QfYz+SVIz9Qnb1cIyVXZgOYsmPtTfKsJ72LhFHSJN8QqLau1Anoa4H6/2lEz+3bxqPu/C50OfmdU+B248Zdo8X6U2EcPU6JhGD6RQn8R6v+Nl7PDdQB6IBsbG+esQZBkyIkPVbx5iqdKB2FIKVwzjhNoxgY60QNNAEnIKAgPk6OwdJeyJoGEFNCsMIE6gLmK/j9gQ162D1MNs3Gh80jOC5XT0Mwcph8fw24f4SVpGuA9pHhl2ka0NAL/ptGJAEq8VtkY5B0DCCfzdMQtB4DbzOKfb+DxuOwesbKuGD1RvhjSf0cER3BMXyBAzkYcNxwZ8Hbzyhh0OmE+z68tknZJnyHi9qIHidUwxxKg3EHc2z7FpkAUCj8FyTiBNN1BBYgCargL/sxp/mp/HcMz8tXHu78dqjpvQEHYGsRQgEcSWLAlqRxIOBuC8cZZhbqQ6AMxs5/0Tc0g7Hob5vHv2p98C5bpGJ5ZUNCThdGp8qBPmCv2IQA+5HA+0uTT8Y+/G6C3qiCcmDkEtc6ajZFxPpSCkYZO9wCPoZvXi9NZsTdQJaTUhscgWmob5DCLQzRW2HVsMs00aptbwERY//FIpS32MUoIOWU6g54Zhk6GX6vImURef3kkB56xi77nBldxS8aWKgHSkah/qt+9QAQLUVZWoAoNoXbpOTk6DRaKCiomKJ76/+6q+gvr4eVq1aBRs3boSTJ0/Cv//7vy/5v9/+9rdw8eJF2LRpE2RmZoLFYoHvf//7n3ufmA5AwQH2ZaBNui+IxuCEKKS7gplPCTIOxZWmcCIkTKIixRMJOgAdZeLkI4H7nimIJ/kwM+kMz0Bb1YzI8V+FTHl7F9Yh2zvnkZoh8TfVzbOJrbkvCs2WeRHVt3oRmmzzrCbZ8lRU8iWOKL+gB1cAjIdQB0DK2ve2YfMiUX5cnRLEYDbiCYnaox0WJ/9lV0WqDwUQHfsH4Zl8UQdgS8E7TEis8lScTfIrT+FrkXgSTTCCfpw00b6F3GLG33RAqLnuF+v/iU9e14OTsgRE4apFVFBuQioMCXolZH6bZhmPnCYm2mRBu0E/w3j3vnpREEuq7eBrQAwhy4Sn3cHxaXi++K1j4KufgEjxZKJmRAFm/ilAaK+YTsQX5ouTbb91LPFcpImNZQwn77WjuJqVLvq7iifZZJwy/Anbrh1lAUNk65h4HUgUrYmlTitl7LWLxkW2uv7qUn/+OAsMbMVfg+J1AtYx+VW4md0Jhw3HWCCQcFxolU14Xbdv+pFrDK8jCiw8XkTqSjUGOgX8qDM8Awdsp+DFxyKi/sG6t6DWighR5w6c8NN54ArgBNS5AwNwe+c8GLwo/LY6+yPYsOUXUBn8FpvoEgef9ARq9+IKgHUXnp/WXVEo7XkZ1hc9gMzHPobHCh+ArgXVts19Udi+6xas3/4AMh//GNaVPoDi3bfYNai7EIeivbdgXekDyNiA/qL9t/A6E0ro8vtvQbbuAaTnfgzZugeQ338L9Gcw+NZei0PhAfRn5KC/uO8W0yrQn0PF73WlwutrH4BVM8gC79Ie9K167GN4rOgBlOy8hRQuIWmg7XiZCQk+se0B6EMvs/tOXc88GJx03D6GDZt/ASb7S6zHwhWagWrft1D7IesjyMm7DzV1iH31uqfA6PgG5ObegzVZH8HGDffAbLqJonSC5oXXMckE7Hz1E2KQLIgvkoaL9BE0XhPv68KqF40L6a5A/XaVAqTayjI1AFDtC7W///u/h9WrV8OaNWuWBAB/8zd/A5mZmWA0GuG5556Dq1evQkZGBoTD4SXb6e3thdTUVDh//jy88MILYLPZIDU1FX70ox99rv1iPQAbj3FrlwPm6/zl5NIpVrLBW47m1YO362fA65zi1pNTyQkXpWfGFQAu59+HDYm8ZXpfmI/587RFoWIwztUBoPKC8stCZl+SbSwZx4lHaz+/B6C47xab/Jdfxol/xXlhJeB4nGVMZXsbGlCl1dwnrHQIqwB1PRgUmfswK8sr22irRgY5TfAaWkT+OwkS8Tj/JODG49nThFSJh8/HExK+kNMDkI8BAreOvngCgpXDfM2KYuUafL9tXEHvAlckltXDUNg3m/YZ+ZIOjQkGtP389100joEJ57hReRTvOussnYJ+/VG4myTT+5D8EMy1N1lpFwsABOExKhczOr6xBEmZkvwQqn3fAvPTONGlib+te54FAHU7sVSmoull2fHarpehrO1lSEr5jwRfetIn4G3Fa7C47xakpCSOJS0N/bk45A/w/eVX4pB/+BYkP+JPSXkIBYdQi6Non4xf81vQdr0s+9opKQ+hpPcWGA/FoLxN/n3pGzEI0DfK+43Ob0B9xxyY6uWPq8n+Ehid34Dk5EeOi+YTpizta5jExAoFfGlCqZskEKBSukeTOrQaFsmX6AAISsGqEJhqK83UAEC1L9R27twJXq8XXC7XkgBgx44dsGnTJvjXf/1X9tzNmzdBo9HA9773Pfbc3bt3QaPRwPz8PHvuk08+geLiYrDZbJ9rv5bVAUi/A6GyywpklQVsOFOivvCa1TIXsOlUoXnRFZpRbEBUpABlLULtXmWevhIFSHdBgQK0dpFN9Klxt/yKpKn3fBy+q1fQASh9AIYjWPqgPyeW+kjLfhQ5/gLDn9RZHc1Cv4RQj23rnuePX7UIjqZZ8HhugNs/ndD86fZPo/aCArnJ655SPB8UaTnpC3wfEaeU/ArNi0yzQmG8N/V33LaCX5FglHYH8tb/TNbHmjoVtq2ob5BGhCL+Z/bGE3z6UW7ufZaNTugFacJVAVdgGgo3vC07tjDnbZb5t0WwDI0UuGv34opU7Z4YbHvyHdnxW7e+A+uLH8j6upP+CDp3D8LWbfJjtxS8A+VX4rClUN7/ZOE7oB2Jw5NFfH/1sRh3/Jb8d2DrFnnftiffAeNh/vvKz3sHrLuikJ/H99s756Fgo/xxLch5G3Ly5JuAuzV/CAfNJ7kBX2QLKgPzmu0jRcrBbGDLCVADANVWkmm+6B1Q7X+u/fCHP4SUlBT42c9+tiQA+Nd//VdITU2FCxcuJIx5+PAhZGVlwcGDB9lzFy5cgJSUlIRAAQDgxo0boNFo4O/+7u/+y/v2mXQAluGf++oVkHPJyjoAy3H+bREFjn/yPajZF1Pk/BsPxRRRfooIwfPKiMDiaeT+l45imUHFeaz/L7+CZQvvL6MDUDYUZ2rCn364HYyHsUeh+hjW+CvtNwUAlt1Yd11+Jc7UYOt2RsHRzNdHoOPe0DIHHu8NKL89mtAD4HVM8sd+Bp79cjz834Xzv9y5uJxmxe+y7eU0BoLVw4r+rMwPZX1Vmnfhg1XKWEe/dUzxOlruGvzVagX9g9W/Yc36dB5QCYorhCsDShoEDS1zDBlq75yHTz/czs5NW/c81O6JQWGa/PjCtPch87GPucdlYbsBCjJ+KT82433YfiOm6NcOxxX9paNxKEjn+NPf549Nfx+qj8agIJ3/vpZ73/Xtc4rHdU0WHwP6+oZKfpCedkc5SE+7AyH9VW7AiEhoNQBQbeWY5oveAdX+Z9p//ud/QlVVFRw5cgQAYEkA8Jd/+Zeg0Wjgj//4j5eMbWhoAJPJxP72+/1QXl6+5P9+8IMfgEajgT/90z/9L+/fsjoA6cqiMctmfDMUVgAyluP8I6/evUqZZ6+E4qvZpyD0k628AqA/o4AYzF5k6M7S6xgElF3FiX/ZVVwFUNIBWFf6AGuQT8RZL4LhCNb21+7FQEBpBYCEmqTNlyTmxJp4eSsrmQvg8SJ9iTL+rARIaPZV1G5oUFDjzRBWhBREiBQz2SZlHQDF1ai0OxCqGFJWpV4Gjai0QqC0bW/qa8qvnXYH8tb/rayvV/MKvLG+QvkaU9RHWFAWfspYgNdzKhX1D6jZ+9FAsKEFaVzNqfIaBE2pt9nqATWXO3fMguWpqKgzEZmHprTb8uPTbsNjhfIrAL2aV+C9nE3QlC4/tjHjNuguxaFRwV82FIfGjGXG8/zpt/mvnX4bDEdi/PeVfhusu6KK77uuZ17xuObm8jGgH6zJUw5WLQoB4zLBrKoDoNpKM80XvQOq/c+0Z555BtatWwcff/wxACwNAP7kT/4ENBoN/MVf/MWSsd3d3ZCXl8f+rqioAK/Xu+T/7t+/DxqNBp5//nnFffnoo4/g3r17CY/vfAdv9oG849za5qBhhFt/3KG9objc3K6fgfYK+XrxNgPWofN6AJotWFLQaJevZQ87sdGOixgMRaH6WAwCAQXMn4+DH2yLQvllbADm9QhQ02/pKOoBlA0h0YdKgtoOKvQA7L4FVcdF8g+V/VieEsp69sYg5OL0ANSLhB97Fx4jW2SeYVMdzbgSwEUMViFlyeO9wZp+pQGAr34C2vXyyMiuEiTSKLH6A7WjfH+BUp39GPabcOv0kQTE06SI5I9BqOwyRLaMcv2RrfzXDhpGlLddehEiT17jj68c5qIVI1vHwFaq0ANQfIjfGyE0GXM1CgrG8bhxewRuwOHqY/I9AEkPwWJ4kVG7Hu0BcIYR1ft8Trfstp/L7QFneIYJhtk759mk396FiFBH8yx3/LN5PaBrfhnSkz5Z4ntXUwULJUZ4ZluP7NjfL+gB3cU4/H6BvP9rxT2gvRaHZ7Zy/EU9oD8Xh68V8bfPG/sHT/ZA7Z4YPLtZ3v9sXg+Yn47Cs3l8v71rHp7P5RyXjT1gbPgGpGvkj8vrGyo/v2jdMuKO6gqAaivN1ABAtf92+6d/+id4/PHHIRqNsuceDQBu3boFGo0G7t69u2R8X18frFu3jv1dVFQEO3bsWPJ/v/rVr0Cj0cBXvvIVxf0ZHR0FjUYj+7CXPKIDIOGTB2pHwWefSETKpS9ApHgC6Sjm6yK5RcJ9b6ucwYmF9wYKSGVKmPEV2GBI2MkW8xzzu1ctQEsN1rLXt8+Bo2lWRO0l3wPX6kVotGGzK7H+g16R1e/KWoSgO8qwntVHE1F+zuxF8AejoD+LE/UuTX8CYtDVGWVlPGVD8joAhPbUXcKyH4b7FHoBCDHY2SfoAKTfhsL092HrtnegtPtlqDoZZ7SfqhO4ElC7BzP/pF1Qsx+DAClisLF+nqE869txclW3Mwr1HZippcmYM2kXdz0AACAASURBVDwDDa2Jx5VY/UReolUAX8NkQg+A1zEpUn4YYvAOdJZOiRSghkmk6UgRgwKxxm8bFxsMpf4towwvG9lyXTxXhObFoGGE4Tsf1aSI5I9BSHsJkbTCJN+b+hqWJKW+BpEtSDcJlVxgJB7yEyWIEJ7U+Jiw7ZILDHe7ZOyTSEcJVQxBSHspYd+8qaI/WDksvre0xPdNPlvx12B79l0oSn4PKUBrO2Gg9DCESi9CqGJo6TErGGd41ID5OkSevLYE28goLtXDjCJE4zu0NxhZ6YjuCLy4vguaU1D/oOjxn4LZ/HXwOqcYkYvOA1/DJMO/ugLTcKj2BNxdokFQA3s9Z7BZuFE49zpwZYqUput2Yqna7sZzcDe5JnF8cg30dA2C+Wlsxu9O+iPme1dTBZ+kpEFP5yB0d2MgnTA2pQa6nhpk19ij/h+n1EDLwCDoz8Wh5cgg/FhmfKR3EHSX4tCxd+n4tzRGiOwcxG3L7HekdxCqTsZx32T8O9sGwbI7Crt3yL/vPv9ZqG+fg72eM0v9STWwz3Ear9+aOejWPHJcktPggO0UVwegs3SKIV8VA22eDsAmVQdAtZVlagCg2n+7DQwMwPbt2+Hhw4fsuS/rCoC9bAB55sJEhTByfit+WRDP3VeP6DlC0VHtsCs0A37rGE4kvDdY7bDbP83UZe1dmKV2+6fB3ikiPi1PRaGhdY7VDdftjLJJhLkPs9vko6ZC42GhXGaPyPevPoasfNOBGGbXT2BG3ngohhN6gbevu4SoTv1ZzLz7kyJswm4YiDG+eOko/n/ZVXGiX35Z5PyTFgAFAOWX8TUoECANAcMA7qvxMOoOEPaTOONVx8USINPBGKudtjwlNFPuiYG9ExstCS1oeUos+SE1X9JNoJIMagx2hhHf6fHcYFhWKvGQrf2WfL4B83Wm80AiXSSKFahF7r6vfkI8V2pFfQgph584+sTqlzL5iYEfNIyA2z/NOPyE7QxWDiPbX+Dvh7SX2Hka0l2BkO4K6gRUDov/K30NCRaR8IehiqHEn9pLECq7jOP1V9l2Q/qr6BMCF/KzfReIKiHdFfZaobLLCQEB21bZ5QRhPfo/hmcUAiCmSUDvQdA+YNvXX8XjS5hH83XchmmUHUdCsQYsYyIm0o76C/Q5+uonGEKUSr9YACBQZkjfwbljFg6aT8LruVXwQVYe/GBTNey3nwKve4qdY44myQqUUA5k7cVzuL59DvZ6z8D3txrgl+s2wfe3GOCppnOIyRQE7Z5qOgd/VmiA9x/bBIvFBti94xxTvI70DsLCdgO898QmWCgxQufTg3iNH8frLtI7CK+VG+G9JzbB4nYDtB4eZJhe3cU4tB4ehDtlRnhvwya4ozVC28FBds1rh+PQ+fQg3NHi+DtaI/Rr/FA2hNd/555BWCjBsYvFBujsG4TqYxioV52MQ08H7tv7j22CPyswwO7Gc1CzDxGhlqeisDt0Dr6Xj+/7e/kG2Os9w65te9c87PWcge9vMcD/ycqDP99cDXs9Z6ChdY5RmPY5TuNxX5MHr+dWwaHaEywIxyB9gQWEHQKFy28bB1/9xBIdgK7iSXadoliYGOwSBcheckQNAFRbUaYGAKr9t9ovf/lLSE5Ohq997Wvw61//mj2sViuUlpbCr3/9a/jnf/7nL00PQJ0mwL781Yf6UB/qQ338z3zUaQJqAKDaijI1AFDtv9XefPNNbrkNPU6fPg3/8i//okgBOnDgAHvu/PnzshSgqakp+F0pQGoAoD7Uh/pQH+pDDQBUW2mmBgCq/bfaP/7jP8Lt27eXPCoqKmDbtm1w+/Zt+NnPfgYAAOFwGDZt2gT/9m//xsZ//etfB41GA4uLi+y5H//4x/CoDsBvf/tb2L59O1it1s+1n2oAoD7Uh/pQH+qDHmoAoNpKMzUAUO1LYXJCYG+//TZkZGQkKAFnZmZCMBhcMr67u5utGLzwwgtgt9shNTUVfvjDH36u/VEDAPWhPtSH+lAf9FADANVWmqkBgGpfCpMLAAAAfvSjH4HdbofMzEzIycmB48ePJ6wIkH3yySdw/vx5yMvLg4yMDDCbzfBnf/Znn3t/KACwa49gY5hlDAImpP4ELGPga5hkP/3WMSTENCAlhh6u0AxrECZ6iKN5ljWcEpeemlKpYdXeOQ+2iIgNrOuZZ82/1l3Y7GqLzEPtXmyiteyOgulgDGr24e+Wp6LIzhcexkMCQ/8YPqhBUHcBcZvU9Ft5Og7bJ2NQcR6f9ydFsEn4Uhy2T8VAdwGbfOk57bU4lExgczA1/5YNiZQg3UVsJqw8JSA9z2IDcuXpOGv6NfbHoGZ/jCE+a/Zj43LNfnyYn8aGQOlxsO6KMtqPvWueHQ9H0yzYIvOo/NuOjb+E9XTumGWfhcd7AzweJP143VPYGNggafAlwlP9BPvyD1gQtUmfd9B4jf1NDaOBWiTuBMzXWaMpNbwGjddY82qgFqk/rLmcfEIjK2ug1V9l/8dIPyUXxMbZymFGyaH/DWkvsebcUMkFfJRdZpQgasylv0OlF/GhvSRumx5CA3C4aBDCxechXDSIY2g7FUPYPKy9hNvQXYFw8fmEbQWrh3Ec7b9km7R/4aJBNjZoGBFfo3oYtyccE/betJdw20aRMsT+puOluwKh0ousYTpgGUtomKZrWtoQTc/77BMQrB5ObBAWzgO3bxrPE4EQRI3h7LwSGv29jklw+6aZojSdb45GvNYbWuegrmeePVfXM88ahGv3YvOv5SmkeZn7okxJ2HAErwlrL/5esw+vF2qg15/F5nq6vnQX8Xm6Num6113A63j7pIDpvYS6HboL+D/U8F9+BZv5y64iwcufFIGSceE+IGnu110QAALn8Hn9ObzODQN4vyEtD4ISGI4IaF/h+q/dE2P0Mmrkr+/AY2TdFWXXfN1O9DG0aofQ2N+EtCVH4yw4dyDC1+vERn6P5wZet7ZxJuTGrnfnFLs30zUfNF5jDeHUZB4wjUL99n41AFBtRZkaAKimmoxRAGArPyqSVyxjjDLCJoT1koBAIMPQlwyRZOiLiBREHU34JUV4SkcTTgKIBkSs8LoepP3QxLeuB+kh9q55hsOkCYLpAH6JGo7gF27NPiT/VJ6Og/EwTur1Z3ACrj8jcvbLLwvEEOGLntF6hC97mhzQz4pBYbIwihMG7bAo9KW7KAYQ5ZdxG9oR/P/qY4lf/lUnke9Pk4Kq44j7NB1A4o+5Lwo1+2KMblS7J8boRw2tc1DfMccCqLqeeUZZIfyno2kW6SsC+cfjxc/BGZ4BV2hGJLk4hADOKX5WbGJgTwwAvI5JRn0KmDBIYOQf06g4eReQnUSjYfQaYSJBk1uaaAeN13CiSxNvYXIeMF9PwGyGSi7gOGECzsg6FABIJvjMJ5B72GSaCD4UGJRcYJPyUMkFRhNiQYH2EoS3nhYJQ9WSoINem4hBuisQKrkA/qQIvkbpRZzsF57D3+k1pYGK9pJ4LMhH74WCB3oPlRKy0CPkoVDpRTy2wiQ/VDEkXrfm6+LvQpDGKEFEDKLgja5vCgKF84TOA48HaTJEgvK6pxjpia5vrwPPK2d4Bty+aTYhdTTNMg0BZ3iG3QPq2+eYXgAFr7ZuDGpt3fNg2Y2idrbIPKOB1ezDa4cIWVUnMZim66vyVJyhdJmKdn8MJ+dnBQqQQOPSDuP1XHlavGa1w2LQUDaE13rFoHhP0A4LAYZwryByED0qT+P2DUcE5PAx/Kk/i/tVuxevdRLrs+6KsvdZuxcDG0qEWHfhe3c0zjKsry0yj8c2PIP3AYGo5grNMI0GV2BaxPcK17qvfkIMCuwTeL0LQb/fikkev3UMA3qiUgnnkq3iqBoAqLaiTA0AVFNNxhICAAENR5g4X72AfxQeAcsYuALT7Ivf473BMIGuwDT7oqLsoDOMKFBHszAB6JhjkwVCBTa0zIG1N8oy/iQexAKCyDxmyfeJE2TKotOXaOUpnPzrzwmZ91PCl/7ZONTsRz9l6gkHWnEef9cO45c9TRYI/VcyLqj7Cpn+ylM4rmQcA4HyKziBKB0Ts4nlV4Tsv4AgpWCg6gTuh+kgrlJQZrN2L05W6DlCotb1iFlBW/c8mwx4PDfYsWxomWOIVUfjLJuAed2YsXU04v8HLGNsks8+NwH1SUjXgPl64gqABFVJwR5l8WnCT4hPNpEl9KbwHENaCln+oGEkgePPsvvCJDVUcoG9Lpv8E0KzYohNstlYCgZoQk0T7YohcTItQXiGSi6w7D3bhvRRcgEDB2HyHi4aFCfztN+lFxODC/qbXp9WFmi1gQIa6XakqxJCAMD+l7Yr7A9bxRCOBQVQQcMI+3+GVRWOWcB8nQUQlPGn1bxHA3tCglKQJw0EabWHPnsKHplgmG0cJ52S7DIhgN1+1PagTLU0OLB3iStXDS1zTMDOshuvifp21P+o2RdjGgJ0vZj7oizorzqOgUDl6TjDcVaejrOgmxIB+nP4e+UpnMRXnRTvBboLYqBfNoS/68/i7/6kCOjPCFofFyVjLkrE+4SVvqoTeM0bBoT92YP3otq9eK+ipIXxMP6k+1l9+xxD/Jr7JJl/ISlCwb2jeZZpftDxp1VXtkrjn8bPR/gspD/dvmmWvPE6hJU8ye8BC97fg4YR8FvHwKZXdQBUW1mmBgCqqSZjLADQH4e6smchb/3PIGvVb2DjhntQV/asyH63joHF8CLkbrwPWat/A7m598FS/YLIlHdPgbn2JuTk3YfV2R9Dbu59MLi+yb78a60vQc6mX8CarI8gZ+N9MHi/CQ0tmAm07I6CoxmzXVQOYO0VsmR7sNxH3/gyPJ7/ADIf/xgeL3gAZW0vg+lAjGXcKMtOkwDKzpdfEb/09efEST+p9ZZdxS977QhOCEpHxQm+9H+kpQX6M6I2AJUYVJ4WM4L05U8lAdVHcZJPgQtN+E0HcWWjZl+MlT/U7cQAoK5nnmVMie1v6xZ0FISSC4/nBguwHE2zrOSHMn5+K2bx/dYxMcMrPCedyPmtY2IAUCtmkGn1R5pRDljGEjLzbJJfPZyQjZYy+6UZ/2D1ME5uhcx9uPg8m5jThDdQO5q4SiAp02Hb018VS4PIR/9H46g0SDrBpv/RXmIT/nDRoJi9lyvxkZYjCVl3+puVC1HWXxLcsGBAUjrESnzovUhWCWgST5l/lvUXgoJA7aj4OrSPpD8gWTEImEZZ6RYr7yDdBmlpEK0SSD43dh4I4n50HrBkgG2cBY+++glw+6fB1zAJrsA0BpTuKSZCR0kAWgWgv+l8pVVBWgmwd4raAdZdeH3U7RTL/mr34E/jYbyGqo7H2e/6M7gCQIE6C/Ivi9ctJQfKr+A1zO4FQ2K5EN0H/EkR0F5L3I7uEvopWCgbElYHLqCPVgAqzseZTgmtSNTsx0SAuS+KYn/CfY2y/lQKRZondA9gQUDTLNi6UfeDrn/pSoArIAZfFBxIr3XpSg99nkyXg7QyhMDerlV1AFRbWaYGAKqpJmMUAFSWjkJK0sMEVciUpIdQp3sWvI5JMJtuQkryUr/ZdBOVfvUzS2Trk5P/A2otL4HB+c2lY5MfQmXwW2DtxS+9xoZ5cK9aBG3yfXCvXoSwEwMA04EYlLe+vHR8ykMob30ZDAMxqBiMg7cRlX5LU+6DM3sR3O1RtiLgC6OSL/k8bVHQjmBdP1MCXif41+JYqgvWDsfB1RkF51rR72mLMsXf6mOY7dOfw0lB1UlRfMzcF4WQKwquNfi+XGvwfZkOiIEAZTstT0WZoJe9c54pIDfZxOPiyUQFZRL8YqsCQskFBWI06QrUjkJXyRR4MhZAm3QflWMLxlkvAMvmm0bZxI9NBMzXmeKtNum+qJgrEa8KGq9BSHspQdxLmlWPbEbVWm3SfaaYS5PVhG2n34HIlusJE+dI3jB4U18DLSn9br6WEABENl8T/PdFvyT7HtlyHbwpwviU76JarzAJt+V/Fbav/rGgxvttuLmqDY5u2cOCgoTXTnkNIptG2EQ+XDQIkU0jia+96RrL2ocqhhL2jVSIWUlR6UWIbFp6XB5VONaSMFP+eEIwEHnykfe95TrrUwjpriz5zLqKJ8WJv2EE/ekL4r4VjbNJYaBWPA+kInDUH9ChmxbHZixAV4mYcWYBgFCGQpNRjxdLVFyBaWjXz4A7c4Gdyy2mOSYi1mQVz3PX6kVoqpuH2j0xqOvBXoGwU7iOUvA6CrnwOiKBvaBXvP5dWYvgbY1irb/QG+BpS7yGvc14D9BdjIO3VXLvEK5/6gsqHRWVwNnYpigLGAwDMXC3J957AgFUCjccwQAgEMR9L6V9d+NqhvlpLAdqtM2ze4R79SI0WedZeWRb9Yx4X1yFx8zRiAGBvWseWg2z4F4lfCaZCygMJqzMOnfM4t/S6794ggX/AcsYdBVPip9pOqp5qyVAqq00UwMA1VSTMQoAtq7+Q2GCnfgoXv8T8NvGoejxn8r6Czf8FA6aT0K35o9k/TmbfwGFOW/L+vLz3ob69jkIuaLykvQBXAHYuvUd2fFbt70DVSfj4G2SH+9uj4K3Wd7naYtCxXn+WG8jfsm72+X9rs4oW1WoPIUTf+pHMB3EoCDolR8bdkYTGp3rdooNkLYIlvzUt89Bq2lWdny7HsuoKNNH2UCaePlt4+AMz0Bn6ZTs+M7SqYRyr0dXAAKmUYgUjMuOjWy5zvpEKDvNVGypL8B8HSJPXpMd3517leuLbMH+Aq5/0wiESi5AZBPHv/kahLee5vq7c6+CbVscUjS/XeJ7S2OCo1v2QHfuVc5rYwDRnTsk788TAhvevm0agXDhOejOkR/fnTsEkS2j3OMSrByGyNYxeb8QQHA/s61jENJegkg+x58/jtl/23hCKVjAfB2CxmvgdUxCpEh+bEfZNAaUgpqwKzC9RHHauWMW2vUzsuNbTbPQbJ7n+ixPRSHslL+OGuuxPHCHQ368tykK5VfiEAhwrvHWKLg65X1dmn4ov4KBA2/bZUMK/kZs/PWH5P1BdxSMh2Pce19j/Ty0mOZkfc1mLJ1sq5Q/ph06POYdumn5z7sIy754n2lgk1oCpNrKMjUAUE01GaMAYEvya+xLQHz8f1CU8h4EakehMOV9eX/qe/B6bhVUav5W1r967UdQmCo/tjDtfewJWL34iA8f7tWLYH46CgVpnPHp70Pl6Tg4s+XHO7MXwbmW41u7CLpL/LGO9YtQNhQHF2/baxdBd1EsAfj0w+2MUEJZSVcW/31ZduOknxoeP/1wOyuFsPZGob5jDtyrFmTHezIWwBXCIMBXPwEV/2sEvv9/tQmNfr76CfBkcManL0CwchjLAAwj8OmH28UVAMMINgCn3ZEd6029k0D2Cemvwqcfbmc1+fScN/U1+fEpryls+zUIVQzxx6begVDJBQX/axAqvQjeFP5r52X/jayvV/MKvJlVprjfobLLyq+9nF97SdHP83nS7uD7UhgbLhpU9Acrh7nH3ZN2RywZogBACA6DhhEMLNP556K0pjxQOwqffrgd3L5p8FvHWMkK71x0r1rgnufuVYtgi2B2XM7vWrMIpgMxcHHuH66sRag+GuPfAxTuDx7Nd6D8isK9Ze0iVAzy/a7sRag6qeBfvQg1+2Pc9+Zevci9L3oyF7AUkHd/SF9AMAPv+s9YwGs8Xf58sKQ+C2oAoNpKMs0XvQOqqfZlNAoAXMlflf0yaE55FXz2CWhOeZXr/yArD3o1r8j6czb9AppS5cc2pd0Ga28UtMn3QW6Cr02+B8b+GDSl3ZYfn34bqo/GoDSFMz7lHt+Xeg9r/hX8ZUMK/pR7oD+LJQIV5wUyiUAhMR3Eh1ZhLDUxU70v1fjburH8x+2b5h6XsuR7rMHaZ0csIzX/Us23r34CtEmc8Un3GAnE65zC5j9J82ewelhxbEK9PiE+hcZUCgCUxmuT7iluW/G1Sy8qjg8Xn1fw/xyy0v9B1leleRd+lZ4DWo3CtosGlf3F55X3XXtJcd9/p+OyjD9oGFH0P9oDQIGg3zYOgdpRxbGsoVRoBLbsjmJtulCi5vHc4I9Pvqd4nlueUrg/pNyDmn3K11nFoPI1zvOVaX6OJUBKY0eV7w+Vp+LL3gOU3pvScalvn1P0K94/ku4p3h8KNd8BNQBQbSWZ5oveAdVU+zIaBQDXswOyy8Evru8Cr3MKXlzfJe9/LAKv51TCu5qqJf50zSdQ7f0WPLexR3bsc7k9YH46ys10uVYvQu2eGPzBZvnxz2ztgcpT8c+V4XOuXYTS63FwrlPI8J1XXl2oOin0AJzBn0QEqdmHAYBSds/RjOSThpY5UfNAIP6QXgI3w5e5gDQm9xTW+9pF5B/RPoLGa/ysbdodxoynlQDpxG/ZbDGx+4m5L0F2Ug2/N5Wf5VfMZBefXz7D/ztk2T//CsB3IVx47ndbAVhm9WK5DL7itnVXFFcQgoYRxZUXKuGSrgBQOVigdpR/PqTfYT0ChAsmOo3Hi3oUjsZZ8GTys9E8n3vVgnAd8DP8xn7+SpszexEqT8X5/rWL3Ovbo/kOlA0p3FvW4goh7/7hyl6EytP813ZlCasXn2MFwL1qAelKCiuEbj9/1cWTvoA4YM79QV0BUG2lmeaL3gHVVPsyGgUAXdpeeCvJBL2aV6BK8y70al6BtzQmOFB3CryOSThkPA53H/HfTaqB/fZTcNB6Cj5JToN3NVXM3635Q2g1Ifpzr+cM3E2qSRybXAN9gbNgfjoKIbd8HWyTdR5MB2Owq2UQ7iYvHd+1axAqT8e5df7eJn6Nr6ctCtpr/B4A1iPQwq/xrTopiIwJmM+qE7gSULsXA4CgR35si3mOIQ+JAuIMz0DdzqhISmmchTYDvwfA655KJLBImO3E8o8UT8rXABeMi8x4ocGUBQACEYRbb54/JmIopSQbCgCoSVehXp1bZ5+HqwrcOvst14Um2hHu+HDhOYhsuc6t47cVfHVJszv1AAxs28uv0c9BDGhks0L/QcFZ7r51515lDca8HgGl3odw8Xn+cREaoLnHJR81HLj9CUKPQLByOGEliGkHmEYhUjzB7Sfx1U+I+hISoUASnHP7pqFTK9+P0l4xzT3Pmy3YCNtkk6/xb7Rjs6xSD5HuIgICZK/hlii4O/g9AAQA4N4/hvk9AO52vD8EfZweAB9Sf3j7HnJFodki/75barARuK2a0wNQhjhmJb+vfgI6yuR7BAJbT6oBgGorytQAQDXVZIwCAKvxBBypGIA3HtfDB1l58MYTejhSdoSh/rzOKThkPA4/2FgF/ycrD17PrYKD1lPg8dwAZ3gGDlpPwQ82VsEHa/LgzzdXwwHbKUb4cPunYa/3DHwv3wC/XLcJ/nxzNex1nUHevyCQ02SbB/fqRdCm3APXmkVobJiHmn0xhsjsbRuExWIDvP/4JlgoMULXU4NQdVwU5vK2IqlDm3oPnGsXwR/CCX7ZUBx8OwRfCvqckSiUjiHST39WoACtFcc6I1GG/aMggI3Pxm2XDYns7+pjyPo29ovlP4YjGAgE3bjCoU3G99Vkw+bfhtY5qNsZZYrIDS1zjPxD2E9XYBraK6bBnbkAZcn3wJOBFCBC/tHEi8TYCM9Ijb1e5xS0V0yDJ/0OlCXdY7QdIgAR4lNa+80QlMKE0pOGY72pdyBSPMEQllL0JBP6qpSIcGkvMSJNGZF8iJYjofiUSSg/4aJBhuTszhlK9G9BYbHw1tM4yd8kjNf8HLwp34XuXBGnGS48B91PXBHG/xy8qa9Bd84QQ47at8Rg+6r/DUXJD5ACtBopQOGCsxDedgZJPCnia3fnSnQESi4k7luK8L4kSr9s3yTvW4oV7c4dWuKn7Ys+cb9JQyBcfF72uDGNAe0liGy5nnjMhcZqwn1G8seZ35N2ByIF4+LnKTkPSOQtWD2MvQBEbmLn0gJ0aG+wcjMqQ5MKA1IgSoq0EYE4U5Z0jxGtSCSw1YirBGXJ98C9agGabIjAJD2MFtMcu46IlEPlczX7YhD0I4lHm3IPXFmLEAhGkdN/EulcRPohv7clytR8PW2J9wdXF1KASiZioL0mUMAk17+7Xby3lA2JlDDye1sx8CA1cCIU0WuHXFEwDMSYUFhjg0ABEu59OxzzrEeoxYwrgfS+W8xzDLHq9mHw5JHcH9qqMXngaEbBsPYKXAkoS8Zj3qG9IdKa6iceuT8sQKf2BtRVqk3Aqq0sUwMA1VSTMQoA6iqPJyLhMhbE7J6gAtpZKkFKCl/ghKE8bDgOz+d2Q3Pqq1CY+j4UbngbjA3fQH51ZB6aLcIEX8DZNdnwC9wWmQdjfwwa6xNReGEn8r/1Z+JgfjqKX/ACBtCZvQi+HVGmvKu7FAd/8BFUX0uUcbvpC7w05T441y2CqxMRgcT0pwCA/N42/AKvPI1f8N6mpRhRxvg+hLX/FYNC8++hGFMuNvZLAwAB8WebZ+qndTuj4GgUFZEdzaKir6MRv8DN5q9D7sb7sGbNR5Cbex9qrS+B142M/4D5OngduALgt40jm71BFPexaf8ANj7xc8hajboO1qoXRKSkICxFgl3S0g9iy9fpn4e8te9CVsaHkLf2XbAV/Z5Y5lMxBLb8r0Deur+FrIz/x/xSISv7lhjkZb0DWZkfQl7WO2DL/wrj2NsKvgp5a96BrPR/gLysd8C+eZ6p6QYrh3Hba9+FrPT/B3nZfwO2/K+ySXS4+DyEC8+JGgIkAiYR/ApWDiey+YnnLwQw4eLzCdsJF5+H8LYzorgXTehp+7orGJxsO8MY/BSwSCf/TNhLdwWDFWEf2fYlysBMRVgILEhTgG278FyivgGVXZE+AekLkEox+UgEjYIzqRaBpFSL4VtJs0F3JWEliKk+C/9DPR5SoUCGEKWSIaEEjRqDiQZEASrhQf22cfA6p8DROItCglLhQOGe4WhEChDphdi7UCeEHsZDMUbQkipqk/he1UnUBiCxPcL0GgZQQ6DqpIACFkQB9IaGLgAAIABJREFUS8bxeteOoA4APU+if4QGLr8iqoPrLiEJTHcBt0caA1UnJWKAQnlg9THs+yFtANoX2ndrL1LPpErIUp2AhlYMhqy7oqxMkJTBSTFcqgju8dxgn4XfNs6IYT77RIL6c8B8HXs9hJ+qEJhqK83UAEA11WSMAoDAtlPyy8VarDHnYfzaqmbgUO0JuJtkWuIn1n8rZ4m/xTwHpgMxaLTLL3UH3Zil84Xll8n9IUR18pbh/aHoshhP3lhXp1A+wCsBasIlftMBnEzU7hVWAQ6LSp88PGGLeY6x/kkdlcSR6DnnjlmoqXtJVnvBYniREX/8tnHWqElcf69zCqz65yE56T8SxmZoPoFI8YQ4WRN4/wmZX0HQy1b0e7K6ELbir+EEvvj35f1Fvwfh4vPc8fbN82DTPsMdGyq7DLb8ryxBdaYkPQT7k1E20X1UJ6A79ypm8AvOCuUyVxN1BPJE0bCjT/bBzdVt0Jz8bShKfg+2r/rfYM+bYxP/7tyrgobAfVEHoOQCbrtocMm2u3OGEoTEZPdNCBSYDoB032iFoOSCrMZAuGhQzPAnaAgIqwdll8G5YxbHbx1LGN+de1UURtNeekRH4A6uIAjlP6GKIXElSJjskyJ00HiNrR4s0RgQ0K9MZdh8nWFqqTndVz8BbZUzYgIhYwFxtoJWQFuVqBHgXrUArQac1JIwWIt5jgXSLiGQrm/HFUTjIcRp4grifXBlL0LQH2XXov5MHFn8ElY/YTwrzguc/7WJGiK0AqC7FAd3R6KGgDMSxQbf4ThDhTIdkWxRR0R/DlcYvU3ieFqdMBwRxAEP4X0CVwjusxUA0wEMCBob5hMSCLQCQKuEzZZ5YYUAj2mzeZ6ptTvDM9CuF455MuoAtFcIeiFCqVZn6RR40u9IdAImwWo8oQYAqq0oUwMA1VSTMQoALGnPgVxD2GdByv1gYxWXArThyV/wm/xWL4K5L6qI+as+xm/yc2Uvgu6CcqOeUgNg6fVlmvyuKjcBU8afFElJ9dd0MIYYT4UmvoaWOWT+t4ulP1J1T1/9BBQ9Ia+9ULT+J0ztlzKxAcsYy/wHTKOwccM92bHdmj+EgdLD2AAsrAYELGOJAYDuCmxf82PZ8dvX/BhCZZf5/qy7EDSM8P3Zd2H76r+W963+awhpL/H9WXeFHgF+D0G44Cx0P36Z6z+auwve0sgEq5rfgm1bnNsDQKU23Nd+UtAg4NT4d+dikMCt888bVugBuMYCB65fe4m/70KQwNUB2HKdiZhJV4LYapHxGkTy5Xs6OrSimnTANMoUgqWrUb76CejQ3uCO5/a6CCVCLTXyPPzGehQL4wXaQW8Uqo7HuX5PW5Qb4Hdp+kF3ka8D4m7HHgCujkhrFKpO8P1BP64icnsE3CgQxusBaGid49b4t1Vj4MVL2tDKbifnMwlsUQMA1VaWab7oHVBNtS+jUQBQoPlf7EtAfCAyzuNVxvh9kJ2nqAOghLqz7FbG/FWdVEDpEaoz9b+O+dOm3gPdJWWM33KYP8MATviNh2Pw6YfbwXQAlX1r9wgYUAVMn6MRa/1J/ffTD7ez2n5XaAZcgWlF7QVqtPRbx6DwlSmoWbjCGnsDtaOQlfkb2bFVmnfhzXU6sbSk9OISHYCg8RoUJb8n/9rJDyBYOazgfw9CuiuK45V84aJBRb8i5z/1NQhvOaWoA/DmqlJusJq35h3FseGCs5+fxf8Zxiu+dvF58KZ8lztWiQL0WehIoYqhhFIwokEFjdcUmfFEGCIl4aDxGnz64XZW9++rF8pPFHQElDQCHM182o179SLU7YwqU4IU9Dic2coUoNJRZUpYyYSCxgDpBHD8rjWLYDjCpwC51ihQgFYvKtKR3JmoE6JEXvI6+UkdlQKk2kozzRe9A6qp9mW0ZVcAlvmycK9agD/fXM1fAdi8zArA0worANnKmD9X1iKK9Sh8CSsJ+WyfiikKfenP8IXAXGtw32r2xdjEnxr3LLujiDflfUELKwCOplmwd86zxl+PB5VTqW5aSXuB1Fcpw+qrx98pE7vxiZ/Lju3VvAK/ytzIyD30eLT0ozn52/KvnfwqhMouK/rDBWf5/qRvK4z9NoQLzyn7l2Hth4sGFf3/Nz2HG6xmp/+DMue/4KyifznO/++kA1By4TNoDCj4yy4rbp+IPwk0KEHZOViprAvht46JKtAWUV8iYBnDQMCurEmhFCjbO+cVdUKsu5R1REwHPp9OSJnm56AdUdYB0F5TTj4spyNiOKKsYcDzlSXfA1uEf1zKku9BfYeyToDfOqbqAKj2P8Y0X/QOqKbal9FYD8DWE/LLxVqclLZXyCPj2iumYX/9abibVCPbA2BwfRNajfJL/GEnZssDAf4yuekAEj7k/L4w1uE7u+X9zgh/id8ZUV7Cd0aWWcL3YHmBuQ/reWv3YINf7R5s6rN38vGFzWax5p8af6n8h5r3PJ4b8OJjEdnxL67vYhlWUmylxj5qxLQV/z5kaD5ZMvZdTRW8sV6HEz6B+CPlvxMR5ubqNtnXvrmqDYKVw3Bzdbu8f3U7jl/D8a9qg5uZrZyxbRAuPg83V3FeO7NlWZ2A8NbTiln4N9do+SsAmT9RzMKHSi4o+L+rrFGQ8l1cAeBl8VNeU8zwL6uPsJxCsu4KeJdRYJYGgkzrQXgo6QDQeUfoUPqdGoED5uufewXA7ZtWTCBYe6N8JeA1i6jHobQCoKAErB1RTi7oLi7jV1Aad2UtQtWJuOIKgJJGQF3PPLgV9BMczcraC17HJH8FIO05UAMA1VaSab7oHVBNtS+jSTGgkeIJERknNIz5rWMM69dRJkHKCcg5Infsc5yG53O6oSn1NhSlvQ8FG9+Gau+3oK4HyR0M85l8D9yrFqHZgo1ulqeiULMfaTkMlbcGUZvGfqRnUK2sFMXnbRY4/JewEc8fSkT5eZuioD+DiFDnzijDfDrWCRhQgQJUdUKgAGVLEIECxk93Cf1BbzTB7w/ivhkP4wqAYSDGmvZq92DjYd1OXAlorJ8XMX6rFlgTX337HDh3zIIrMA2ORkQhEt2HUIoHraeW6Ce8pTHBIeNxCNSOMnIH8f9DFUPY1CuQfSIF49Ct+UM29l1NFfw2KRUGig9h46dAAZJmfkO6KxDSX4WB/H3wlmapLsRA/n4I6a7AQMF+Wf/RzX0QrByGgaID8v4n+7hjB4oOQKjkAhx9sk9+bE4vNuHyWP1CIzCvB6A7Z4htW64HwL55nlvj3517FcJbTkH3Y5eUX5s3XmgU7n7iirz/CYXehiexSVipxh/RqHx9BGog5vU3BCuHE3QAKDgkFChXW6FYDDz91jFWQuZ1TLK+FK9zCiIF8v0HndopLo++rWoGGlrnuD0ALWbEDPMCbcJp8noAQu4o+IPKOgA8nQBXVxTKr/D97nZECfN6CLzNiCkNejkJBm+U6yP9A+5xMeFx6dDxkza+hkluX4a/4LQaAKi2okwNAFRTTcYoALCVH2VoPinCz+ueAr9tHFwB5M97nVPg3CFmr4k5TZNYIlTYu/BLihj31l2I7qvdi6g+exfSPcx9mOUnLrbhCD5q9iG2T3cJefuE1iu/HIfKU0jXqBjEh3YYEX3bJ2NQMhFDVN9l/B/tNfSXjuLvZVdFfnf5ZfT5kyK43dP4OpWnkOBRcV5Aex4WUH7H42wfq06i+JfxMD7ofdXuiYGtW8D2tcyxn/YuPBaE93Q0zSZgDxk/XVD2JX56v/4ovJ5bBR9k5cHrGyrhSNkR/JwcIsKPMf0J6ynUbgcNI3BEfxTeWF8Bv8rIgTfW6eCI7ghT7iWcZ6j0YkLmN2AahVDpRRgoPghvrtXBrzJy4Y31FTCQv1/k2ZddhoGiA/BmVhn8Kj0H3lyjhYGC/SLqUncFjm7ugzezBf9aHRzd3MeQl0c3PiWOzSqDo0/2ITpTIO0M5O+DN9do0Z9dxsYSIrP78ctLWP0MuVl4Dnn6KSKrv/sJAeNZfB6ObtkDN1e1QXPSt6Eo+QFsX/3XiBndehpZ/DlD4E35rjg2Z0gkDBWcFTUGNAKr/7FLIrJTaMaV+iN5wyJqlChC0n0TRMZIKAx9P0df7hAbi5P4kUc0BEYYlpRpECQcF0FHQEC7RrZcB69UJyBfbAaXngdUChYuPo8IUP1VJAylSTQlisaZHkSwehgDUoEY5KtH2hRRqrzOKegqwVLCsiRMIHQKTPqAZQw6tDcSkwtV2Afj8dwAV2AaWgXePQXSbdUzYO7DgNvyVBTCzmiCTsAOByYejIfx3pKgE7AGSTzGfrzHeFvEBAERgvxJESgdizNSWIJOSA8mCErGMfngbUYKEPndHVF2v9GfFSlC0gRC5SnxfhMIRhM0UILeKPYWHYpByJ34vkhHhO4rTVZMMJB+QlslIkAdTbPg8d6ADt0jOiICeYn0QxJ0ADIWoKtkCiw1p9QAQLUVZWoAoJpqMsZ6AMyn8EtYgoTrKJsGr3uK1ae3GWZFpByJzgg86j7/WXgutweaUl+FwrT3oSDnbTB4volM7+555PyvFlF3VP5Tsx+/6IjzXypg/LxN+OVNXO1AMJHF723FEhzdJfyipS9xxvJvxgxc2VAcnL2PaAS0RqHsKrK9y6+IKwC07YDwBV11Mg7GQzHwB0UNAlfWIgQ9WONv7MfJh+kglv1Ye6Ng7xL0Dbrnoa5nHlpNswzj58lAvKGjCR/2rnkmhETsbp99Aty+aQhYxsDtm2aTJimmjzKzAdMoajRIGjCDxmuM4DKw/TDczO6E5uRXEXe5+sdg0z6TMGmjhzQAoOdEZKQgBJY3zBjybLIqxVluRloN8fMjm0bAm/Jd9NNEt+wyy+IzHGWKBNMp8PppAq+VTuALz7FJOG77NdBq7iWMDxecFYXEkr/L/GwSv/U0HN3cBzczWzEASJJgQDefEEXEaNupiQFAAqqTtv24KFAWLhqE7scuJu67QAAKF58H27Y4ipAlvYciZJmtMLBtL4S3nUkIDqQIUdIICBcNihhQzT3wpnwX33fJBQxA9FdZAEDHtTt3iOkIDBQdwMCH8Kerfwy2gq/icRc0BhJKgISAhjQCpIhRT5oQABivMfQnTf6ZHoCQSPBbxyRCYHR/uQOdWixj87qnhHuPiAhtq5xBjYvQzJJ7D62kkV6AvXMeGm2JuMyQC9n6hOQN+kQMqCtrEYK+KGPz0+oiXf/+EAYAlGAgoS+6f7jbMfuvvSYEAK2J9xdCDNP9JeHelI1CY3R/MQzEGKKU7i8hF6JNa/bFYHfjORRQXL8JvpdvgKeDZ8Hai8mUup1R2B06B9/faoAPslGAcY/3LBNQc4VmYL9dEGjMzoPXc6pgn+M0OHfM4j3GfB0OGY/D67lV8KvVG+H1DZVwqPaEKgSm2oozNQBQTTUZowDAXyCvA9CuR8VJrg5A5YxiD4Cu+WUuzo6+pLnL4D6sr1dC7WlH4uCM8Ov4nT0cX08USsYxe8frP9Cfw9Ii3r6Tkmft3hibiNg7UeirbmeU2/vQZpjFL2H/NJv8UwkQlfRQdo6H8SP0ItVd+23jWAJEk//Sw/KlLkkPwaZ9Bid3wqRPSn8JlVwQMsWj3HKUkPYS/P/svXlwXNd1/9lYSYAEd4IAiH1rEPsOdgNo9N6NHSAaFLhJFClRBBfsO0CCIIi9G3HGSbwozs9SVVy/VMaRx1zajuNROV7lWLIzokTJ87OnJhPHE/8VJ5my9avynPnj3HPfe0Df2/pRNZYKfqfqFcG+fV+/9/q92/fcc87n25soSUfJHAZfihhZKepLar2yNBma3ItSXWgS/dQpQJL0IVIBDp0CNAPe9CHpuZmPrW3TP4gz/D8steqieN8swiBM8Um5zR2u0Nf8Fk+7Cnk/5HyaC4RpUsEKpnhKjy8tNAbUl7HAtSTIKSVNAHfFbS5Y15O3JEghuifEUXYVIRJXpiNi6kWV4JDPsA2VgoU1RM1yDKjx1qZw/KAFBtHYY+3CFB97h0CjxO1HlWDJsZ13D8MbkZgCWGL4R+gzfAneiKyCM+2j0Ni2Bs/Zhra3R1TBc5YhsDpW4LmmIZ5CqG6/XDcAjS1r8ELF9W3tPzRUQk9Bn+4A6LajTHcAdNMthPEIQLSYAmTxrooL9eKDUgrQ4fQn0kK3mvN+KedfRuKx7AuvAyBs2y8v0rMkBKF4ZFN8bHtQw6DujJ+nNNGqXGPrGtSd8QvxhbZdj8DSvMbTGyjCQiqpdgvWAgi1F2IegtN0lyMaKQLAV2Ar5+H1hBPiYtf9/8iLPN1luIKsdgDCIiPDISfDFKRKUZnZo3LMZ/pQeBSnpNBWWgQsw4BGPwBv1ogc1Zk1Ii3kTUr4Sci2PsOX4PW9BU//2R/imr++v1B83gk/5kJj/D4gleK8cXCX3xLu2xbzkN9DnuJZTqGiFDRX9Tx4imbEGNFdj+QFwvZl6dhj6t0QY0LjglD1vAS1mSDWCbEZvoLRQ8n4IdUR2R9EB0GEAU3A8Uc2vvxZyumQzsGfHTsNtef88Jljods/m9gLjS1r8NkjvSHbP3/QB1bHCnz+QE/I9jt7nKA7ALrtJDN83Aegm26fRAurAxD5GOyN96RIuf99n0QHYL9cB6D8qhzTVzIoR+lJUXthdADCYfqqnpcfW+05P5h8G1D9XAD+t//zOJx8Bh2A+q71sBg+ixcjKw7zIjS5VuB3v8zF9B8nKnXabBLthYjHnP7jqrkDeYuIIaXVWlflPPwsLlH4nezd9S84acufAE/BFLz+fyg6ADQR/CjISUR1CpCThrflqM2sESmu0ps1Iu+fNihuN7wNP489IsaARv+ztK83fUj+2Tlj0va9sf8Ssq3U8BP4WexR6TXz5E/IEaR549L2n+8S40/3xv6CpyhpUsFKlFoR2fdNNQJUS/C7X+YqysCV83IMaORjaZvVuSJtb2xZk2JAK14Q63GEw4AWD4UZWxbkGFDjXHgMqKy9Nfa1La/j1hrzGtSc90NrjKA9+jUwn9qAtujQGOHW6L8Bu3VJiBluivwU6A6AbjvJDB/3Aeim2yfRwkYAdj/CYjwhqi8I30iVRADS3v3ISr+yCED+QpgIgETIp3hEjukrvyoX6jH1bkDVxQCPBJCqr/nUBioBSyIAjvpFaGxZQwfAg85AY9saFvfWL2JBsGhlNOYh5lizAsqt+dee4ll4fZ8kArDvJzyvm5wGmvhRMal0hT9/AuzRYqRkOGSlbIXem3JDjuKUCYFFhVkJj3oAr+8tEF+XvT9++hX+qPDRiaQ9b4Zs4xEAyXFLEaQf4ppLIx97f7wNA0pFw2ExoDEP8b0lc3jvsXvKaboLrtoFrjQtxoiKMaC2XQwDKhMKaxXjLq3xQTCf2pCjNp82ArAvGD5CIBmbmhKYholk/MmMDS0EmBXzPtT1+SErRiAUGPM+NLasQVa0WEiwybMqFBpMjbwPugOg204yw8d9ALrp9kk0cgAcmYOh89XLVqGxdQ1OGUPn8LbVbMAF57CwBuBExyvQUh+6BsDtQNqFCMVn68Q8fIdXjOLLn8ciX1Gev0gjgDB+ohx/KkL2WMWYvpOnUcX35GlGPGKkn4aOdWhsWxPmJneWr0GTZ5XjVZs8q1zYy96IbH+bfVl4zU8Zl/hKP0//YZunaAYxnjmXxTnfuX+ikIBYyg+f+LG0D1HOd+/RGTlS8jirARC09ybOivPsWbFs78EJaY6/L2nu6WoIjs5Af8p5eQ2ApC8WJ4vrC6h4WVgDcNwPUYbfbmsjfKoUIZozJkWQegqmxDUER2fgavpz4vsh/0/Q8dviAHgzh3mqmLAmJOW2UktSogiHERaUCoRF/U/lL4EvOzQitKt4VVoL01GxBnV9fmivCf2ctZg2oOr5ALSeDD3+uFzyGoCC2U1hu7XbD7n3AkLMp+U06ow0nRKPL0VjYp0Rp9sPaWlvbZmc45ae8hbU9fkh/Xjo9oykt6DJswqZiaEdzqwjb4LVsQLZh34Usj0t4b+C7gDotpNMdwB00y2E8QhA1QB0Fa9qUHwdFWuc5GF1rkBHxRpHztl2PYIW8wZHXD5rZxSgmNeQAnTsTShxvwJ1ZxDz6WlSUHfW+CB4rEjRKbuGSE17iwrTtzcI9nY/FI4jArRojKH41Jx/RvIpmEEc31ZUn7ULWf9UJGzZz/rux74nppHxTxQgNSLQ3qpg+qqeD3ACEbU3N25AzXmk/tR3rUPtWRT+MvcoTgCp+269Zl3FWPBr8a6CqxoVU222ZaShWJZwVZ8JKdktS5ycwtGLmVj8q8Z+uirnFdXWMiW3/2rG84wCxKgve34ApoxPYYEncxQ8BVPgKZzWRgDyJ1hR6W0tcjL1DtJoGOpzK3LSl3JbQVayCak96j7iMInEkz2qRWVuRW2yVBTsuwXjySg75GDYoxhqM/K+BpdJWgC8PYq1pw2CN3sU+o+dRQpQJMOAxn0PzCkbW0g897ehNL0pN8CbNrjlvO5D70FGPsobx/bEEOfNMKGmjE8xCtATpADFdUL/8QsKQejw9JZ9TyrnraInaa4bnXfOmOo7e1uLR80bh6sZF+Hl+C7lvOO/D+aUDfAUzfDIz7Yi4DKMFHnyJ8CXfRdsaoRo6h2871TkKcLIUiSKXndVz6POSKwWI+qsQwf2VP6Squ0RnMpfwnqYRhx7uopXNbjL9qp1jh5ubF2D9pp1ld5GEFpMG6jKzepyPE1E8sJn2GNF/ZGq5xFC0KTWGOlgFKAx1fixT2lvOoUFwEWjiBIOOfbM49hUOM4oQuqxq82PiONxRglq0Y4vbhsWEJ/ofAWiorRF41GRH0Bh+ytQdTEAxc2vQFTk9vZS5xfB4l2Fisa/2FZ0HhXxAVTXfQEszWtQZfrC9v4RH0DxiTu6A6DbjjLdAdBNtxDGHYDaQbDZlzl2z9FwjyMq7dYlzpW2NOPElsSsmjyrfNW7ybPKef91fX6o70ZKR/WzAXQELiPys/ylAJT1Iz2n/KUAlAwiX794GNF4RaM48Sfe/4kpxH0WjWFbwSz+cBrnsC3/zqaC9ZzCH1bjHIqA0fuMt7D/iWncF+FDK64EwBnhg7JryAQnNF/hJNMeuLHJj7PiBeT81/Xh+dG50iTD1LvB+f5cI6F1jU9kLM1rXOnX6ljhLH+LdxUc9ehoEQFIzVHnlBU2sdIw/4m+UnNHwXtW3OYTe0/hNP6fJv35E5rcbkJ6aoqAGTaSMJBqhr27BEWlaCLuzRpR8JukEWCcVJj9WSN8Us//T7z+9CFlYk2OA8OA0oTXmz4E3tQBjrr0Zo3g32yiT2hPmtzzPux4vakD3CHxpg1iW9aI8i/THeDHSZPt1AHFIaF9Ego0sR88SdeUtuTrymdnjaCegLqd9sU+n64X/5ddM2/mML6Xrhd9JjsHb9YIv7Z0fela8euj0kLgx8KiOvz7Yf3590z7yxpRHEGGciU6EBX5eopnefqYp2CKR53IgSCFaVclFqVTbQA5qJS65i6bA1ftgqJpYcZ0NnKEbTZE4pIGiaN+kY9NVgdqklgdK9DQgcJ6ja1I1qrvWoea8/g8khYJjUW15/xceJA0PIi3X/U8jkPFIzhuOCN8UDzMxhA2/hjncKwpGlV0ROhf2kg7IHcJx5D8eexD2ND8Bdxn8TAuMBRO4t+lNzah4sUAFA9t8kWR0uubYPS9AofTn0DcwV/BwawnUNT6CtRcQAyxybcBhW2vwJHUdyHuwL/CoYwnUOb4IliaEY9q8m1AqfOLcCT1XdiT8K9wNPldqDr5BWjoWOcph9W1X4DEo49hb/z/DceOPIaaypehruKm7gDotqNMdwB00y2EkQNQVT/MRGEYi3s3KgHb7MtIpYnwQXvluorFHeSrcHV9iKz7syQlApCR/BYUN7/Cc+Rb6jcUlj4T4im/qo0AEEubdAAKZnAyfmJKUfpVs7jz7uLEPnc5wFfpSAfA4vNDzmoAjLfYvvdr+xaP4AS/aEyJAHCNgVZMTSJxMo/Vrzl2txN/fBs61vnK/8ln/NDYtgYnT29onKTOklUmYPQOV1ema9rkUVjnNBkiZrqrdgGcdQvgy1jQsNN7cu5xdCdNsFyV84r4F03ui2fhSnH/9ghAzqeV9B/jJE7eVBM//nrhNPhS5xXOP7H2jZPgKZ5lq823tCz/5Ns4cWTpI5z1b1CtpJNQF1vh38baZ5NtEtviPPtDU8qkVr1vWgk/OKlMtlNu8JVwhYc/yyf9VzMuKhEA0gE47ueTdM7iV3P+2WTamzYIvQcnt2sM0MSdjo33Z9EH1m5O2YDcXd9V6QC0Q3/KeXQA0oe29FVFTUgfQX1No1QiY6kDuEqfNMe0F95BnYDkW/id5Y2jABqPALyHEYDUgEZ/QXMfFM1wZWhvzphKF4LpAKTi/Ufvoftqa1SAnFNfBtYCKDoAuNDgMC+y+1zRu+hmbaQo3JNzj+thWOMeIUrXuwqNLWscBWqNC/KxqbVOwfKaezaguVGrE9DciErk1c8GwNGsaJBYEoJg6/RrHABbp6IhQOMHiQ8WzGyCvVM7Nlme8eNEfxKdAkuvVkfA1okRgOKRTch+/lVIzXwLMnf9FFpjX4NPZ56GnjOjUNYfUBTSt4w9dWcUDZUWMxtX6bxNKgHGjnUegTRG4pjeWYpCYIQgpqgv6S/4su9CXcUN3QHQbUeZ7gDoplsIU3QAQtcAdLB89c6y0DoAzY0bcNEyCG9EinUA3DZxnmvlpYCUhV04iT+wIfNsexmLW1ADYO0S1wDYOzHFSFQD4GjGiIVLUJ/QYtqA+i6McJh8G5rV//rudXBG+ITXjHKbaYLT5FoBZ90CpgAx4SRX7YIwN9qXeVdZiWUOgKt6nk+8PEUzcDXnBXHOd+an+Kqzmv3OKUCF01LePaUHCdsLpqTt4n3P8jSXkO2Hp/kkOWT7wUmeoiOsAUg8I60BENYXHJoCT9I1qU6AN3NYWgNgSt8U1wAknZMet/S6HJwEb8oN6Wdfzbjmuvg3AAAgAElEQVQovB/MqQGMRKiEwGj1n0/+U++EvheTbyuRJxYdcpffQiIQKw52V9wGX4ZIR+CusK3biFEAoU5A8SpYmteguyB0jQBNhkU1AG47KgiLagCKR8Q5+tZuXKAQ6QQ0nmX1SSIdgQ4/5J55FSKjtutCvBFVBb6+UaE+CgmFeZpCt7dX4cJEe1Xo2oiOShynOgX6CvacIdAdAN12kukOgG66hTCeAhQj1gFobF2TUoC+nl4uJIwcyHkC1ngx6aLiSkBMytgbhMIJCat/XxAKZjelpB9hG3H+RRSOPUGouiimAFnjg2Dy4Wq/qXcDfvnPyVDftQ4N7euc7S+jANlsLBXIicjP3/0yF9N+SFW1dkHITrfHPMRca5Ya1NiyBq7qeUzDYCuyr++TcN/3vqWkhWSPQsafbmhSP8Ky9tMG5ZSggikpsUZK2pFy/O+DN/m6nMSTOSzdf3gdAMm+c8bkxya7blH3ISleQgGKy/9oFCDZeYejAO15i6cDaRzB/AmeCibVAaC8fyYCVnPej1Eqpijtqp6XUIAeimlXsY/AaborpgTFMj0NEQUo7hHU9fnBGid+xkVjk83wFSgeklN+ZBSgxgNBdABE48/+IOw78UR4PzzKqxCPi3uCUHkpIDx2a3wQGtvk18VmXxaOT/hboDsAuu0cM3zcB6Cbbp9E4zoAEWIdAEuznLUt0wGIO/jRdACKRuUs7sKJp9QBiHoMJQNyTnf1sxKGeORjDLO3r4PJtwEVV1AN2OLFVUlHwz0pv9zeeA9s9mWe+//l/1YOdgvSfRz1mPscjsVPyr+NrWs8BcNdgSuy4XQAPMZJjBYYJ6Hs/qziALB8cymLP2dMzoUvmZMy6aWsfZkOgOFt8KYOyPtnjz61DsDe6P9LctxvgzflxkfQCXgb9sb8ImQb1wGQcf4LpyXX/G3wZg4//XnH/oLfT+oIgLqgO9z3TdECd8kc/O6XuTwdzV2Gjqqsv/Q5sS5J2222ZaneRmObfOwySnQApGNL1IfQAbgl77/r6K+E98N7R5PlGiRn/dLzqusTtxdEPoYm14qwPSviK6A7ALrtJDN83Aegm26fROMRgFixDkBji3w1SaYEfChTrgRc/lJAvMIfZpXNsi8IuUsBeQRAEj0ovSGPAJS/JF9lq+9CAlJDB6YC8WJoUvcVXDNbLOoAUKEjpQMRNpHyosUrow+VQmC2qVWA3RW3wyoBq3P1NSu/BVOM8/+UEQC+Ui5ul0YA0gblq/CpAx8hgvAAXo/PF1+XuB/J9505LFX6lWoYhNMB2GOUHrfHOCk5tvvy7yxc5GPvj7djQFmRsDdzWKoLQREAXlxOhcKs6JeK0EW6ERgBEGsMSBWxSVFbohNw8hl5BEA0NtkMX4HiYXn0URadbDwQfuzaZxRHAB4WVIjHpr1BqH4uAE2Sscnk2xCPXbsfSSMEegRAt51mho/7AHTT7ZNo5ADYc4ZC5oN2lq9BY9sadBWHzmdvMW/As47h0DUAUR9AifuL0NwYOgfX6WE5/h1iHYCCGSzCE7Xn39mEph5xnq6or8Prh9Kbm0INApcLiSFttaGPvb0GWf+155A40ti6Bg3t67wwUZab3F2wwvGqVPBLRb9EQvEUz4IvU1wDQAWWtOpK6RZEZ7ma8bw055tTgVgBp9oB8OaMgS9FwPlPviXn/DPkpah/76EpuQ5A+pCkfRa8qQNCHj4dm7D/oSnoTzonrgE4uiJm7R8Nc2xHZ+R5+IenwZy4GkYHQFIbIat9IA0CgX5C76Ep6D9+QXw/pGxwapIGB8ucQU/htLA2wpd8G8k/eePgrrit9CueBY9xEgvVC6eFuhK+zLvithxE4nYLagA6y1bBZl+GDkEue3sNOuitptDPcEv9hlCjpMdwBccHkU5IG9YQCeuTWCGwqAbA2uWH3LPiGoBTz46CyyWuAag74xfWALRQ7UOdYOyqwkUKUQ2AM3MAdAdAt51kugOgm24hjByAmroh6Cxf0+gAdJaucsReQ/s6dJSvqVjbj6D1JP7Q1Hetw7nmke0UoJZXOCbT7dBy/t02P5ReV7B7jmYVKzshCJbTyPnPu7vJf2g5i5uRNIijzSlA+xUWt63TzxF8TT0Kp7tpbxCcbj+U3kAMX8WLAa0OQEIQnB4kFNWewyLl1pNEEEENgxaTwvo396Dqr6UZi6WbPMj4b3Ih7aeraEVzTbsL8HWrcwVcNXeQ+sMQiK7aBaSesNx+d8kc6gAw9rot5iH4Mha44JKr5o6CWWSRAI9xktNYrhqvwMt7uqAt8m+Q+77nB2BK31SQkISSVEcACqc5ntOXouL8Mxa/J2+cYyM5k54x64k4Q/vkPPwIRsNhzoE3fYiTdjSs/LRBJPFwGg7j4Uc/QNZ+5jAiQzlpR8XLJ4pQ2iBShg5Pgz1yC4uf9e1PPAMvx7YzChDTATiyzEk/vQfGtX2JAkQaAwfG2Xmp2tlxe7NGGInngfbY0gbBmzoA5tQA0wF4F9oiiAJ0gWNUNfoH0SrCkPq8Qn12zpiGYETX3Jdym9d19B+/AC/HdW7TAVDjUNU1AN7sUf5d8vOK1uo+EGqWJvw8AsCiUfR/T9EM+DIWeH9bzEPw5dzjNCuiXZFGQFfRCneOHfWLcMq4hM8R0wnoLkCSDSGKO8uQtkU6AW21mI5Hz2mraUMzdjU34jNcew4LgblGwN4geJqQAlR6cxMqXgiAvVWrA2Dt8kPhhIIT5u3RTEegHccewoY2ndrS3onwgsKJTci8TBSg96El9jX4dNZp6L44CkWjiCh2O7XjZnMjipvVnkVSmcvFjp3GJjMSyUiNvNWEYxfXT6hc53jixhYUK6TrRjoltZU6BlS3nWW6A6CbbiGMHIDq+mHEwzmwKLXJtcInsibfBjS2oRNAPxx1fYr4lakXf5Tq+nA1vOY8blUXAxy1V3k5ABVXAlBzHgXAyq8qHO7CyU3O4C4eUdjaRaMKf/vENP5gFk4oAjoFM8jVzl0OgPE2+/+dTQ2izziH+z4xhcjP4iHcb/nVAJReR+6/M8KHWgSXkPdfew45/zUX0AGoO4MrbvVd63jePTi5OHkaGeOkgdDQsQ5W5wo6Aq4VsDSvYTGvfRnsjZjiY3XgNXaa7oLNtgyumjtcAMxRv4jOACsCJuY/raJSfj8JeFHutbv8Fi/WJBKLp2CKM/o5851N3jnXnekCePInNCu/fCLO0j/UBcOe/AmFd0854vkTCgtfNVHmOgF545xnz/8OxeAn3j7x71Nu4GspN5TXSX8g+bryfxWCk/9LG9uHJ7FfeV/ydXxdzedXc//ZRN6TN45/k8YAHQddH+ZQcERo8nXNZ3vyJ5T9pg4oE3n1Rtcr5QZ4k68rmgr0mfQeej9pKbD98e+DOSAkRsavA+kvpA1q9QZIc0Gt16DWg8ifQERs9qjC+SdELDmQKkoQj0aVzXFMLVGANClBrEjdabqLE3yVmjV3ZMtvcf0LKoznlKz6RY14HukC2Oz4r8W7ik55F0boiIdv6mWo3pY1PkE++QziNGlcqrqIYxJpg5ReRyHA0ptsoYIx+0kzpHgYx5vCiU0u7EWaI7lLAchbDKAjcIvplNxWxqXCCUXHhMa00ps4PpE+QNm1AJTewM+pvIzHQeNo3RnUM6i8jJjlmgt+rk9Cjg2dZ+1ZP+omOFc4urjJg7VKXFOBOVNWxwrU1g7qDoBuO8p0B0A33UIYOQB1FTf5ajXpAHSWYyqLpXkN6rvXobNslTOlrXGPoLWORQC61xWl30jkVbc0bEDdGcTVVV5irO29jGe9F1fZaRWer6IlqFj8nX4+6S+YQdSnmuVvOe2H3KUA1wEgNU7qb+3yc8EwWoEjjQGXG4+rZADFdnoMVzSsbWKE11zASUELXz1EhnhL/QafQJh6Me+frpPNjs4TKfl2lmg5293GZS7y5apFRV+KAPAc/rI5cDTcQ3ximoqdHvMQfBl3uRCTJs+6/BZ4c8bQWWATtf7jF7Zx303pm4qYl2qCqKEA0WryoSkNc54wnXy1mtoj3lFUZ1lNAaXLaPrTSjop2kbd17LyyfnIHmVKvqw98j5PwSHnoPfgpJa1f3BCmRhnj/LoA//sgxN80o+r6Kq+tIrOHAGKHhi3Ri4oOqHRCbiv2bdyblvamVNhPu7fogPQAf3HzuLkP7GfHbeqLykgM7E0vm+KEKiO3ZM3rvSPeIddV+U76086h/oHEXQ/qCJC7Hvf6ggSDtSbPcojAPR9a3QA2PtclfO8oJg7qmUKCpTuZXvMQ/Cl4T3vNN1Fzn+scp+fMi6jSJgVC+PVOgC22EfQWYIaGvbGe2B1rODYtFsZu9pr1vkiRkMHi16qdADaanCSXHfGD611Cku/aS+qBDsjfKgGPrAJbhsqBdPY4/SgjggtWmwduyw+HJtOTG9C7r0Ajj+qsYvSh05Mb0Ln5VH4dMZpaNn1GmTu+imkZr4Fxp5X+CKFXaVBQNGJmguIKK4959eMu9Z41AEgITSTb4NHAGjM7ixHYUISdVRru9h24XWtOaljQHXbWaY7ALrpFsLC1QB0VCAzWpQL31a7AS1mQY5tA9JxRDoA9lY/lL8UAHubmJUtqxGw9KEgj8Un3r+1S9xWenNTzNq2+rmAkLAGoHWNp0A1tq7xjVbVThmXQvY9lb/EV/rVwl+umjuYEsGUfYV5+BkLnL3OlX7ZRItWea9mXxLrAKRvKivHW1OACqbAmz4k5uEnznIhL2EeP0vREeWrC/d9eJo7HqJcdm/KDXE7m2gL8/gPTUFv4qyg76S8foA5GL0HxuU1ApLzNqcGBDUAFdCfch56D0+Lz1tybL6kOe70iK5rf8p5eQ1A+hC4y+Y0jiBXdTZOyusPKLKQM4YTf6YlwaMBFbfBlzovyPO/J9a7yLgLrup58OXcC11LU4gTWZHeRmcJrnKL2ttqN6Q6AKXXN8HeLh4/TkxLagD6wmiUdPuh8/Io/CBqe+1UZNQHkHvmVXA0h+7rdmKE1WMV1AA0bEDVxYCw9qGrWHGKQp6brgOg2w4z3QHQTbcQxmsARBQgRtqwiihA8UEhT7ppTxCqnhez9Jv2BpG0ISFlFE6GaZ8IowMg0RioeCEATXvFJI2qixIKUNwjjvw0n9qA3/0yFyzeVUxLsCPjX8wvR7oJT3NouMd1ANwlczz1xy5gp9tjHoKncBodhep5yF0KgNW5gquwrChYSgGKf5OnB3mzR2Hh7TZt6kcYoow3fUhOw8kelRJrpPtOG5T2RQqQhBKUPQr2SEF75P0PoSEg4fyn3JBy/sMRiqQ6AHuM4uOOui+nG9E1l5Cb5BSgtzAdSOUIUlEwbVLdB3VBedEMXPrhcxxRS/oCQh2AmIfC+9wW+xBxuSIa1q5H+LyJaFu78RmVkbxkOgCVl8TjgyUhCCUDcp0A6di0PwgPCyqE38m+gifCz+Zjl0Sj5OQzfikFCHUAQrfrFCDddpoZPu4D0E23T6JxHQCDWAegybMqZ2lLOP8VL4bh/I+F4fxPylnaxjkJiztKrgNQ/VxAyAE3Rj6GmvNylnZjG4bTyRGg/H6rAwsYhX0jHmOef+U8pgPV4oo+CSkRDlSqA8BWWikK4CmaUXK08yfg57vEOgAJxH2nTYV/pAmfWAeAWP1ifro3dUDK8pfx6j1543LWvkyDwBCehy/dd/L1j6Qx4Em6Jm2X6gBEH5brH2SNyI9Ndt4Rb8PPY8Q6AAmxv+AO4TYhMFazIdOF4IXhhZiu5C6ZU+5HJgj2VDoAEY/BVT0fVk9D1m51iHn3srGrwPA2VFyRj12l1+U6AAWz8rHtvcRk4Xey+8ivpJ9dcUU+dp18Rq4TUN+1rusA6PYHY4aP+wB00+2TaFwHIDp0BMAah7x70Sq/bBWNr1RJeNblVyU6APuCcGJasoqWEF4HQLaKVvW8eIW/aU8Qi+VEq2xxQTD1Yg1EYwvm/lNerc2GRb8yBVOO/ayex2hA3QLPm6ZaANmqKZ/0GyexDiBvXCn0zRuXRwD2/YSrvFKxqwb/WDj99Dx8HiGQRABk+5au8N8PEyEI018WAYi8L49sRH2I9jCRj6Td/xCyjUcAZJGRzGF5uzT6cD+sErA3Zwy8qQPaSBAjAcl0AOzRD7ijQAXCvC6AxMHK5sQ6ArGPpPe5u+J2+AiA6DljEQChhkmYCEDJoEQHICEIRWMfQilYEgG4XyyJAJyQRwDCqpT3SnQA4oOYqqgrAev2B2KGj/sAdNPtk2jkANiMw0LWtvnUBrRXrguZ06IaAKfbDxUvIspOyNKe3BTm6Vu75DoAFh+ytkU6APYWv7C+wOXCQj63II+Wiunaa0Kfd0c50kRs9mVobMHVf7t1idNI7I33oEeQu9yTt4ST/8p5niNNuf9qkoovQ8BHT8OIAc/TZulAfBJWNANX05+T1wCw9xKxRoN/zBoR55MfnODFqNIaAFGu/aEpca47w2UK2w9gsaowDz9xFmsERDz8g5OSGoAJ8CRdE+7blzDG9i3WCfAk9kvbzUeWxToAxy+Ir+nBSSxOFl7zWel34ku+Bf0pF+CHhort94Pht2BO2QhNg2LOoKdgSrzvpDmFCsSKgdVRKSoKF+lG+FLnwZch0buouSPUw+g2LoPdioX2IccupmEiqgFor1oX1jb1GK5A+UsBYY2QrdMPJYNinYCGczh2iWoIbJ1+6H5OXAOQeflVYe2T2+aHsmsB4djltSANqK1GXL9k6t0Qjm323GHQHQDddpLpDoBuH5u9+eab0N7eDgcPHoS4uDgoKiqCP/7jP9a857vf/S7U19dDXFwcHDt2DG7evAn/8R//sW1fv/3tb2FiYgKSk5Nh9+7dUFtbC3/7t3/71MfGawBODkFX0QpY4xQmdEfFGtcBaGxDYoSah08/NCefYSztvdjWtAfbqp4PQMkg4uzcdi1r2+1EjnXRKKL07B1+aFRx/Im1nXd3E/Ln0UlQs7QbzyBrO28xAPkLqnamE9B0Cn+ASwbxR1jN+Xe5kMJReQkxegoF6DGnAFVdRMpGQ8c6Z4gXRD4G6+5H0Fm2yjF6NpvKAbAgRs/qxBQgq3MFTuVr+eWn8pcw95/l73PUYSVGAjj2M38C3OW3wJdzD+xqHYDjt5XCX2KvF0wpEQD6v3ESrmY8r6IAKdx3DeN968QvfYhP3jj3nfHwfUlzCuWHiV5x3j1RgAjdyUk8W3j4DJWJFB+VRgCRchg2kyg/vP3QFLYxDOc2zv8BFbIzfWg7L594+tmjqjYVaUeFDdWw+KPu8wk4vUerQaAiDDGk6TaNgoOTHONpPrbGKEBPmA5AB/QnnuGIUtQYUH02E0cjkg/XVtiqn8A2rs1A5504i7UeWSOof7C7Q7kf4r4HpvRNDaqV3weEcFVhQrm+AekAJCPW05s1ohT/MiE5EqfjGgEFU+A7fnubjgChbbfqAPhyFnlKnKt2gVGC2HO06xGcMi6B3bqEuhm1C+DLvos8e9beWb4GdusS1+boLF3VapjUIR6zvgudAGu88vy3NGyAM8IHFS8EoPo5nGjT+GFhOiFl/Uj5OTG9CfaW7WNP3l2G+5xUaZhEPwbLfiSYFY4j4azz8ij8TzlEAXofNQEuvwrG24ww1K7VR/E0IUa54gpijD1WPzSpjr29BlHFtWdDaJjEIR3JfGoDkc5MB8Cq1gEoWoHaGl0ITLedZboDoNvHYl//+tchNjYW6urqYHNzEz7/+c/D5OQkjI+P8/f8+Mc/ht27d0NFRQV85jOfgdnZWdi1axd4vd5t++vr64Po6GgYGxuDz33uc2AymSA6Ohq+/e1vP9XxqR0ADRKOYUDru9c567+1To2UC0JbLRJwas/5obmRfkTf0TgAFVeQrU1CX/kqDGjhJHKv1WI5alTeiWlk9xdOKBP8/GiGAfUhZcM4hw6CBgO6Lwj2FkVsx96qoPQsCeh8FI9sopjOtYAGA0piOuYehaXdXrkO1rigcl1KUezL6lTY2hbvqsIkty1Dk2cV7NYl6MlbUvCGzAFwV9zGyT+b4LgrcFLPhb3KsBDYUzAFvtR53t8e/QB8aQsKX50m+zTxp7QLJsh0NeN5eH1vAfw89ii8nnACrmZfUvK6aXLHePWaiR/j3PcfvwCvJ5yAn8cegdf3GBFXScz49CHoT7kAr+8xws9jWPvxCwojP20Q+o/2wetx+fDzmMPwenw+9CedQwcgawT3vTsP9723ACfBKu69J+maogfAEJqc3598XWH3E/pTzclX8/pVTgNn9qcOKNjO5OsaoS3O62fH4km6pvD+aR+kV0D7Ju0A4v2T7gAdE72XPpdeU+9XrSFA70+5gfshHQD6LEKxqr5DrhvANBW43oL6nKk9c1ijAUAr+N70IeU+oPMgZ5HwsKQfwNCgdL9xvYGsESV1iBxUpjlB9yz/t/yWomBdPMvVrckxdpff4vUxhBKltDlHwz3UzWhA4TybfRkc5kU+4bfZl/kzSs+jpVkRwKrvXoeGdtzq+vxc1Zt0SpwRPqh6PsC3iiuoWVIygHjOwnEcu0qvM0Gwcfz3xDSOR5z3z3RM8u7iVjSKm3EOtQFIn6TixQAUzCqaAAUzmxw1WnpzE/VSxlGYrPwq6pWUX8Vjo4WMmgt+qH4OXzP5mCBYzwacPI3OjqUZF3TquxCR2tCOzgCplze2IcpY1wHQbaeZ7gDo9nu3X//613Ds2DHo7u6G3/3ud8L3NTc3Q3JyMvz617/mr7388stgMBjg61//On/tjTfeAIPBABsbG/y13/zmN5CTkwMmk+mpjpEcAOuJ0ClA7VX4IyGSjfdaxKFmtx0VdUVhcnsrhtFFGE+LD1fKmk4J2k/7uUaAaP+iFCBSIhalJ7WaML+/tS70uXWWM+Y/m1g0eVYR/+lBPrnDvAi+nMXQqQ0ZqPrrNN3l4kekmkpIT0/RDPjSBClAGQuc+KNxAqgYM2+cY0D7DF+CEsM/Qp/hSzzVxFM4reH/qyd+nrxx8Kbc4ClE2/onnUPngGElt7ZfzbiI7cfOwg8NFdv7p1yA/sQzIfoiCpMmrBodgKj7uMJPk2Na6Vbz8mklnE2wt+kMHJ7mTsU2jQH1vrNHeXRCs+/0Ie54hNQoIOeE4Tq36QywYzOnbEDu7u+hDgBFAI48wyMIvYkzqEGg1k5QOTK9R7e0kwIyc1g0GgeRKn2FrBHoP3ZWpQT8HuTu/h4iQGmCr04FK5jiSFhP8SzTGJjF8454ByNCybcUpWAm/kYRALofeTpQ4TT40hbATjoA0ahqTc7rNo2AzLvcKXBVzmMkjTvSD6HbuIyOQP0iWJ0riARV6QR0FWFKXkPHOqYJaTRMgtBRuQYnT+MkmbPyaQHAhBGAyks4mSY1Xr54wZTES2/gZN7pUekAsOhl/h0UADsxxRYn1BomvYqSsMW3ZWHjtJ+LihVOsuiCauHE3orjVsWLOPFXIqvv8KgsiTKaezZUEQDUAWivWucT/8a2NeioXOPXxbbrEXSUr+k6ALrtONMdAN1+7/aZz2Ax1bvvvgsAAP/5n/+5zRH49a9/DdHR0ZqIAADABx98AHv37oXLly/z18bHxyEqKkrjKAAALC8vg8FggH/6p3/6Hz7GcBjQcAVlTXskRcB7glDxorgImBf5Ctob9wch/4680E5aiJcgwYDuCSLmT1jk+whqz/nFBYS7H6Hqr0tRT3Y03ANHwz3EgdYviosXYx5i6o95USP+5aqc5/UA7pI5MQY0+oEyySqe5UWX7pI5vqr7clxnSOfh5fguZcWXUI9ZI8rKb9ogeAqmxP13t4M35Qa8vLtD0N4B3qwReHl3u7D/y7tEbR3gTb4uzeH3pg6I6xOIxS/qnzgjzqM/PM0FyEI6XfvHw2gQsGOTaBiYUzbkOgAyzn/ydXntROoA+PYLaiMOTcHVjItiHYDjfu548ftApfSM4mei+oLbGnVgIgBR+g85lSLtB1/qHfCl3gndlnMP3CVzwlqYnrwlTP8R1Np0lONqv6hGoL1yXajz0WO4AtXPijVMHM04URfl4VtOY5TR8oy4vkm0sGFvxfRGpzt0u9Pj545JqPYWE676y7RbGtvWoKNC1wHQ7Q/DdAdAt9+79fT0wL59++Ab3/gG5Ofng8FggD179sDVq1fhN7/5DQAAfOc73wGDwQB/9Vd/ta1/Q0MDVFZW8v87nU44ceLEtvf93d/9HRgMBvjqV7/6P3yMHAMaERoDGg4ZZ4x8LMbRRT2G4mE5Cq9gRt6ePy9H7eXek6P6wmJAJedlPrUhxYA2eVahyYW5/7/7ZS5X2LTZsDhRhifk6T7lt8BRvwi/+2WuQvRhNCAZHtGbM8aLhXP+6yLUnPdjX0ZvaYv88pZ+uLVFfFmJFLBUjZtv9WkxoGmD0BYh6B/5ZXl7xJfBmzks7S/dd8oNOeVHxsOPug/e5OsSnv4DOQUojA6AJ+nah9BHeEoKUFy+9Li9WSPifUeG0QkIRwHa+2OedqWJBFFaVNaInPpEjkLOGHgKpuC/vH9SGz0omJJShKS0q6IZcXvsQ3CYJY72LkYBElCCrHGPhCQcm+ErUtIO1wEIt7gh0TAR9t0v1z9p2huE0pubYkrQniBUPyfXMDH3iBd1amN1CpBuO8sMH/cB6PaHZ6WlpRAfHw/x8fFw8+ZN+PKXvww3b94Eg8EAfX19AADw13/912AwGODv//7vt/Xv7e2FpKQk/v+ioiKw2+3b3vfOO++AwWCAz372s9Lj+dd//Vd4/PixZvvKV5D5XCsSAtv9COq714WiMU17g2Khrz1BKL0u/qGy7AtC0agYlde4n2E+JSv8BTPyH0rZj2TlpYDwvKzxQajr84snCLsfYa6xbZk7AXYLFiXyvORY8cSGr/oz0S93CeY4kz4AohPFEQCe+sMmWJSXTfn/2RHvQSjnITvyibLyT4WrLBXIGeHDnPPMYXn/1AFxe8QTef+IJ/K+6UNy3n249tSBp9cBSE8L+94AACAASURBVBv8aJ8dpr9UByDmyEfatydvXMrqD6sDwHL+NSlAqvoCqSaFcZKv+HMyFasRIKdUdmxSHYBKiQ5AxGO5xkDkY2hyrQjbw+kAVD0vYe1HPYayfsniw4dZ3JAtnIzI9U9KBuXtdWfkOgAynQBdB0C3nWaGj/sAdPvDs+zsbDAYDHD16lXN6y+99BIYDAb46U9/Cq+++ioYDAZ44403tvW/cOEC7N+/X7O/5ubmbe/72c9+BgaDAf7oj/5Iejzz8/NgMBhCbs7MgdBh9Mo1LAAWyMq7bX4hBtTe6ofi4U1wCULZ9jbMhZXl+OcuBcDaHbq96ZQf8hYDwjC72+kHR7MgTN6ApB9RiL+tBkkZojB5dyGm/1i8WHBI6T+Ohns8HUhYA5DJcv/ZRoqpzjqsDaB0Hl+KAJ14/Dau4NOEX0VfoVSM3N3f2/LDjltu3Pe3FwKrJn6U8pEb+x1B/++BN20QcuO+H7o9/vvgzR6F3F3fDd2+67uQGyc6tu+FWW2+HyZCEE4pOIwScPL18DoBopXsyPthV8qT4n4Uso3rAMjOS6pBgKvwUh2AuHy5MnT2qFYPInVAkyYm1QEgJ5TuQxIDY7UBTxsBsEejoyzWEAivFGx1rjx1BMDUK9YBadqLq/SyxQ2pyrkkPdGSEEYBPSEIZdfEKsVNe4JQe1aiBByPGidCHQA9AqDbDjPDx30Auv3hWVFRERgMBvjWt76lef1b3/oWGAwGeOWVVz4xEYAK6winABUwzGdbzQZYmtfAfAppP0qxnIIBrT3nh5OnN7AYba8K82nFQjnCgHqsDGfHMJ62Tj+nXeTPb4K1W4vKs7cj479gVkUJ2q+0Eya0YAbfY+1i7ezznR4sMK54IcApQNTmtSAir/acH0y9G9BjuKLBm7bVoriXyYe5su01ynWx7UIKUGMLYgZttmXuADjrFsBuWeJKvo76RfBl3tXgDXty7il5/izX31U5jxGAkjntqn7hNPiS5nh/ezSiOGmVn0/6C6bAXTLHJ3Ge4tmQ+eZRER+AKeNTSgSATfI0Ez9GjgnZ3/BbMCeuYnviauj2oyuIu0wNhG5P2ZDvO21QnMPPCmLD5fHLcuGl+gZpg2KO/yGc2Arz8ElHQKJhYD66ItYBSDon2fekvLbh4CQvPhbVEPSnPhu6BoB9J9tqQYj2w2hCMh0ATkwiMhA5pwwN6s0eFesAJN8St6XhcySqH+jJWwJHwz04lb8Usr2rGJ3zrqKV0IsbFWtCFn7YGgCvH0pvinUAiFJmOS1o7/ODpVdQH9AtXxhx23FsE9UftJhwcUO0MNNq2oDGViwADtVuy9d1AHTbWaY7ALr93s3lcoHBYID33ntP8/qTJ0/AYDDApz71qU9MDUBV/TA0tiLNxuJdhcY2BQF68hnEYZpP4d9VFwNQdTGAyLwXEEFH3OmyawyZdy2ApAyGsCu9gYi70ptIxshfQMfgxPQm5KwEOM4z9x7i7oy3NyF3KQD5d/A1wuYZ55CukXcX/y2YxX+LRhHBVziJ+LziIcT1FY0hraPyEnKzSwY3ofrZANSdwWOv714HZ4QPiSCnEf9p8uHflma8BlYHIvMaW9c4+tPqYKx/B/5t8SL9x27FVCBH/SJHfDrMi5rUHnfJnIJAZDx/WvnnCr+sPsBTNMOdAXqvN31ImWARAUidc80mYObjfkja+xYkxP4Ckva8CebUAM/p9maP8v5bJ37kBJgOL0HSHur/FvYnpGb2KJhTNrA95p9x/8fW8BiYmJj52Bokxf0IEqL/GZLifoTOAUs9Mh9bU/rG/QjMR5Y57tKTdG0L7/4+n4ATipPrBFA7sfzZ+XGePmf1Y5GuJ+nadk7/4WkFy8mKaUPqF9BnMwqQWifAk3SNXxci9fD+BxQkp/nIMuTGfV+lA9AO/Uf7OIVom8bA0Rll36kDSPmJVmkv0HVJH0IxMNJX2KpBwLCtXAcg4gnkxqEuBPXV3AeEDWXIUK5voOL49ybO8PQzPvGnyX8IRWBfyhYdgNR5XshOFKCCiMdIAcpY4Pe2q3oeCULRD9AJj3kIvuy74KpdAEf9IjhNd7U6ArseQWcJq8+xopPQWbKqLG7EPeJOfn33OrTXKCx8a3wQWhkFiMY0T5NfoxPgcvv5eEJOQFOCogPgdGMRb/GwivSjWvywd6BzQCKHXEOALXwUj2xyHQGiAKk1CIpGcUyruhgAt8Ov0TDxWvxQcwEXZWouqPDMqnMz96DIYUMHO3fSftn9CDoq16C28qbuAOi2o0x3AHT7vdvU1BQYDAb45je/qXn9m9/8JhgMBvjLv/xL+Ld/+zcpBejSpUv8tbGxsZAUoKWlJfioFKAK6wg0dCAf2tK8Bg3tqBZ58hk/1J1BPnZdn/bvmgsYAai6iII5lZcDUHoTfxTLryKnuuIKTsLLrqHoV/EI24Zx0p6/oHCzjbfx7/wFnNQbb+PrOWsByL0XgJxVtq0EwHgbnYGiUfyxLJxAB6B4BH90ST+geARZ3cUjm5yfXf0srv5XP4tOjDPCxyf+pHlAkQ+a+De2rfHJvtWxwvP+6f+U/uOqXUBxosp5cJrugtN0Fxz1izjZJ+Rn7YKG3OMuYbUAxPYnuk/RjKKoqp6wM/46rf7TJN5TPKvkYFNNAK3iqqk/xJQnbr6qBoAjJ9MGcSJP7HnizydfV6IHxKMnnj69ThNxFpHgn0W8e6o/2MreV7P22THyyW/OGNcQ4EhO4vfTv0zIS7OfrRoB9Flqbj+10/8zh3H/6UPK+0g3gJwQ2hcdE+0nfQg8if24JV1Tjpf60/tSbiiaCmr+v1ojgM4t5cZ2/QD1e0kjQSVWxr8zOjf1/0kPgJ2bJ3+CI1DVgnDcMaDPyRzGPH+VQBg5B7RPj3FSm55G9yF7jd8T5DCQPgC73+k5USNAyWnW/F1zh6tpO+vQEXBVz6NT0HAPnXDzItgtqM5NtC6rYwWZ961rUN+Fz3ZD+zo0tmGqo/nUBjR04KJA9XO4UHDy9AZHgtadQXVzvqBxfZMvLJTe3OQLDvl3cPw6McXGtHnltYIZZdGD9AJOTONiRtGYoitAYxhpBxSP4HtpQaN4eBNKBnBsrXgBx7WKF3HMrX4ON3PPBlQ/i3/XXMCxu75rnesE1HfjuTd0rEOTBxd+qk06BUi3nWW6A6Db793eeustMBgMcPbsWc3rZ86cgejoaPjFL34BAABerxeSk5Ph3//93/l7/vzP/xwMBgMEg0H+2g9+8APYqgPw29/+FnJzc6Guru6pjpFHABqGFZGcrnW+Im7qxYlxfRdGA2jl3NyzARVXcCJdMoirURUvBvgPYukNXIUvGsV/i4fwx7BgVvnRM95iKUDshzFvMcBX+I1zOPEvmMUfR+PtTchZDXBHoXASt/z5Tb6aVjSKP8SFE/h5JYPoaJBDUjKA/Oyq51kE4wI6Ac4IHxfNMZ/a4IxsEsdpbF3j0QC7FRVIrc4VcNQvQpMLyT9WB1ttrF8Eh3mRq/tysS9a7S+a4cW+JABGqUB8Vb9oBpWA1Q4BiX0xeg+fgNH/qWiTTc7cJXPKxH/LpEszEWTsdo0DQFx5muST06CaXHryJ5SJML1ODgFNwLdOYmkyrVKu1YhosYm0J7FfmdCm3OBiXFxcK+UGHkNiv9a5oGNUMfu9aYN47mrRLxLdos+n46RjpEm5et/qCT5x7+lz1PtSOwm0T9pSB/C7OvqSViBM9TfVZGgm7errSdco6ZqG/8+Pka4/OXt0ben7VO+XtvQh7ihqHAD6bLXzuCV1jIvJqdWlVUXB3EFgr5NitUbIjjkLFBlzVc9z59ddcVuDyqWoGE32XdXoADjrFrgTTn+rnQG1s06CV5ZmjOhZmlEToO6MH0w+xQGoOY+Rz4oXcMyofhbHt7J+ZPBXvBCAE1M4Ma+4EsBxbgTHG5rUc4EwFvXMX8C23CUcy3LvBbhIGDkHtABSNMqEwSaUfRQPYVojRR9ozKUJfsWLuPBSe05ZrDH1ohBY3Rk/j36aevE8yeFpaF/nDlF1vZ4CpNvOMt0B0O1jsUuXLoHBYIDTp0/Dn/7pn0Jvby8YDAaYnp7m73nzzTdh165dGiXg3bt3g9vt3ra/3t5eHjH43Oc+B2azGaKjo7fVGXxYIwfgpMHFf/z1Td/0Td/07Q9zO2lw6Q6AbjvKdAdAt4/F/vt//+9w584dyMjIgJiYGMjNzQ1J6/n2t78NZrMZdu/eDUePHoXr169rIgJkv/nNb2BsbAySkpJg165dUFNTA1/72tee+vh0B0Df9E3f9E3faNMdAN12mukOgG66hTDdAdA3fdM3fdM32nQHQLedZroDoJtuIUx3APRN3/RN3/SNNt0B0G2nme4A6KZbCCMHoLZ2EBpbkIhh8a5CfRcWhlFx7MnTWBx78jTSI2ou+KH6OSz8rbyEW/WzASyQu4yFaJWXkApUOL4J5S8hDYiK5AonGeFiTKFfUIGv8Ta+VjiuKp67oxQRF41i8VxZP5IwjHMM+clIGaU3kI5B9Iuq5xX6T+WlAC+IO/kMEj6cET4sguvGc25sWQOLFzGCDe3rnPevpos4Gu7xol+bfRnsliVwVc+D1bGCRYo1d5SCxZo7nPxDhb+cfkJFwOW3FA2A4lmleFVN4GHFt56iGV6Y6TFOKpQgVhjszRrhWFB1kS4nAhHNh+g2avyjuiCWikipuJbIN+r25OvYT00WIpoOkW9UxB5evEpFtltpNlsLWqlQVlXAS0XB/Ji2EnbURbtqgs4W2pDn6EvKa+pi4Mxh5TPUxbpUFJ06AJ4jV5Rjp4JjogslX1foQLQvalMfF6MccdKRuthXXYRM56cmEqmvH11r+r7U12Lr+dF3uLW4m/3N7wN2nXixNxU/q+lRhAil705VcE7Fvt6sEf43FbdzghUVtW9F3hbPctqPp3BaQwGiAmFX7QLX03DVLvDn02FGLKjdgsX6VKDvql0Au3UJi/Zty9DkWYUmzyoifjvwmbfZlznwwBnhU/DHDJtJZJ2a834knL2A41zZNRznKl7AMe7ENI5lhCQunMTXTkzhOJc/j2NW7lKAj3XZ64g8zr+DbTTWlQxif+MtHA+NtxSoAVGASgaxGLh4SFWg/CJuRGyrej7Ax+/6biS8NbZh8bPJh7Szk6dRH6CmTqcA6bazTHcAdNMthJEDUGkZ5ng8cw+j/pzCHwdTL251ZxD5Wdfn5z+EFS/ihL/qIv4gll1TfhTL+gP8x6lolP0oTuAP1okp5Ycx7y7+6BVOqlB47MeOEKHqjfoVjis/tqU3EYdXMrjJf5zL+nGrPefnTO/ac36F9a9yAIh41NCO513fjY6Q3bKkkH6cK5wwQjQgh3kR7NYljvukyQfhCV2V85xsQjQTTj9hk3c++cmfULjpjKDC1VQJp6giAXGHgCZYaiQjTYxpYkaTQWqnySZr4xM/mljSe8iBoL6qiSfHXNIElCanNEnfOrGnySm9xhwUTveh/upjVaM/1U7FVkQmvWcr+pLIPjRJJ5xl0jVloq5GlNL+1H3UE3D6TPZ+7iioJ96EQKXJM72uJgapnB81558fP32m2oFRH1sox0DthKmvA6FD6TtSo1AZAYiuP78PVHoP/B4i7KeKKsU/S32/EOIzbxzvaxWKlpxVd5lK0I60K+hZYEQg7iTT88D0MtRIXYd5EZx1CxyvywX5GIrXZlvG/1uXUDWYPceO+kVO81LjQBs61jkFqLFtDer6/AoK+YKf08MqLyFuk7CbJQMKeaxwAscz0jw5MY1jGi12kDNQOMGcgVuK1knhJO7HeIs5C3fwX+Mc9isZwH7lVxUSUMnAJtdjKX8Jx77KS2zxgx1vzQWFcER6LnVn/Nz5sXjRIWpsWYPKJp0CpNvOMt0B0E23EKbGgHYVr4I17hEYI98Ba3wQ2qsQ/WnuwR8Or4WJzkS+A017gtBSv8FXop7pGoU/ST8NrbGvQWbsTyEt9S3I63sVKl7AdnsLqvHmR70DloQgNJ1SlIDz7m6CvR2VfPOj3wHL/iBYfCimk7uM3H9bJ2uPegcs+1BJuHiYrYxNbnK1X9q/2+6Hysv4Y1jU+gqkH38LsmLeh9aY1+DPkk/Dc/YhzsHuMVwB6248b9vuR9B6cgNstmX8YWxeg+7CFbDtegTGiHfAtusRdBeiBoDNtsyjAQ7zIrhqF8Bpuosr/jV3wGFehJ6ce2CLfYh9Yx6CLwXFvDj7nFZGiZFOqESGQfQl3wJ7NPa3Rz8A3/HbimOQPqRM/NUrryr0IgpqPQCj4TEKSx2e1qI72cRRvfLryRvnqrb2qPtg5IJXE0rftEHWTvtmYl2qiW3vwUmwR97n7b7943yyqekbeR9FpZhT4025wYXA+L4PTiqT0dQB6D04of3sozMaZj2JdWna2cSXn5dhi5AXmxz3HhjXHnfCqIIjJUEsdf8D48qEOm1wW7tv/zh3nsxJ65Ab+x3IjniPCYF1oBAYcz40fSPvcwEzb/J18CT2c6EvbP+qIoDGojHYX/V9M/Vkb/oQ9CeegZd3t0NbxJchO+I9yN31XRRvU2kebHMEVVELzXcWjSJlGiQsOw4N+5+cU34vP8B7OUr5zj3GSTClb0Ju3PcgO/I9aIv8Mry8txuuGq/gin/xLPgy7oItZstzUDwLTtNdcFfc5orbxoh3wBb7EE7l44TfVYvq3F1Fqmc49hGOdQ6MBjxnGYLPHe6Ftui/gazo9yHz2JtQZxjlaNDWug2wxinjnteCOE2KKDq8pDSOY4+91Q8lAwyFPIyKvnxs2odjn/EWRgAKJ5VFDYoI5N9RcKBNp1AITD1u5t5j+NHhTXB4lfamvUFwO/3cMak574cS9ytwMOsJxB38FRxOfwKlri9CXR+Oe7Vn/VDq/CIcTXoH4hN+BUeOvwsVlr+AykbdAdBtZ5nuAOimWwgjB8BaMBxSFr6tBh2A5sbQsvIt5g042zoCb0RWbWuPivoAcs++CvbW0JL19nZUxLScDt1u8fmhYAaVNEP2Zz+0ts7Q7S6XHwrbXoGoqA+2tb0RWQXP2YegrSb0eXUVobpvZ9lqyPbuAmSKu2rucPa/qxZ55E4TqpT6MhZC9vWlzitpD2wFlFY81alBvjRB/+Tb3Fngq7GUrqHitfuSb4XszyfyKmVdmvjRJLz36EzovmxC2Zs4G7qdqer2HpwQtvcenBQcF6rW9h6aEh83m/wL+zM13ZDtR2fEn31gHCfgB8aFfUmBWHhsydfFx354GsyJqxBl+O22th8aKqE/5bz4mh5C51D62WmD4mM/MA79iWfgh4bK7c+o4bdgSt/kDgp3AGi1nzlFvuTboe/FlNuKngTpI5AjS/dn/gT4kuZC9z9+G8wpGxAVsf0Z/aGhEq7mXAZfzmLovjn30DnIvBuy/ZQRU/N6cu6FbO8sWYVLJwfgjYgQY5fht1DifgXaK9dD9nXbcFXdawk99jSd8kPhhHhssnX6+eJHwYwiGGacw0UP4xxO/kP1dXhRLdjeHrrdbcUIhbFn+9gXFfkBlLq+CFUXA1Dq/CJERW5vP1GxCLoDoNtOMt0B0E23EMZrAGI/w34ItJs1Lgi1Z/1gjQ+GbG/aE4SvZZZDn+FLIdv35z8BS0LovpZ9QTDObYJlv7g9ZzUgbS8a3RTuv2lvEA5lPgnZ1mf4Enw9vVx4XrZdj6CxdQ1sux4J2+2N93iuMU9BIEXS6nmwxT4M2dce85Dn/XMl4NoFJfWBpfnYox6E7h/9ACMGbNJFK67erBHMu2bpGsL+Ufe1AlHqCABbYbdHC/pG3gdv5jDYo+6L951yQ9ou7Svd9wPwpg3K+6cNgj1S8tmSNk/SNfm+Uwc+Qv8HkLTnTeG9+Hpcfvjzeur2B/B6XJ7wGU2Kf5NHZrgjSCJfzEkU7jv6Ac/zJ8eTFKjVStDC+yn6ASQl/Fh4Xf7XA4Vgjw79HNliHoKncBrsMYL22EfgaLgnfA5tux7BN1LKhNflcNq7wuffGh+EiisB4fhh2RfExY19gvaEIKb23FJUgPMWA5C3iLUAufcCYfsKx709Qah+LgBpaW+FbM9IegtOPuOHjKTQ7ccP/BXoDoBuO8kMH/cB6KbbJ9HIAciM+F+AVoGU7f+FgsjH0Ni6BsbId0K2G6Mew08PJkOJ4R9Dtu8+8ivIjxL3zV0OSNtPTG9K20sG5e1xB38Vsq3U8BP46YFk4XkVRD4Gu3VJ2u6qXcBJv3kR8/5V0QCn6S4YIwR9Ix6jWm/ZHOZCF89Czl/d1RQ/erNG5P1pgsVyo6mwUp1GZDQ8Dt3f8LaSN581AmX9AW3qR9qguG/EY/BmDsv3LetveBuMEZK+qQPyfeeMyduzRuSfLWnzJF2T71t2bBFvgzd9SNp/b8wvhPfiz2KOyD873DVPuSFt/3n0YeEzujf2Fzy9SuMI0sQ+5Yb4O4t4WylQZyv+L/zDBe5QkLKxuP9j2BsruS6xR6XPgbvitrTdUb8obo98DP9tb5LwusTv/1fpuFd5KQBGydhTPCwZm6If8/TFE9OY7vO7X+ZC7r0AFI8w8IFs3BuQt1c9H4DMmPdDtmfFvA91Z/yQJWhPjboPugOg204yw8d9ALrp9kk0cgBqBBGApj1BOPlMmAhAljgCsO+EJAKQEATjrY8QAUgIYoqQZCXsYPbTRQCscY/A0iyJAMQ+BEfDPXBX3OYpP456LEik4l/Rqqct5qFSHEmFv8ZJnitNxb6yCIB6gkYFljyth6UDhY0AsIJdzcSPRQZkK93e9CH5Kr00AvBAfFyR4aMH3qwReXv6kHT/sjbP0Zfk+06+Lr8uqQPS/km7fii8F6URgMivgiexX9IePnrx+h6jNAKw1QHQ3Feyax79QKndoAgA1aJQSlDWiDwCEC+JjCQUgE24wv8QPMWz4hX+mIdIAhI+w4/gm4mlwutyNOVdsMaF7tu0JwjlVwPQtFccfSy9sSlst+wPQv4dLPjNXQpA7lKAAw9OTGMdgGzcOzElH/cqLwegNea1kO2t0a/BydMbwnZL1KdAdwB020lm+LgPQDfdPolGDoCldDR0DUAt4j9bTaFz5d1WP5xpHw1ZAxAZ9QHknnkVrN3iPNkTU5tg7RLk+HewGoBecXvJ4CbYBXm2bqcfTnS+si3PlWoALjiHob0mdI5vV/Eq2K1L0FkSugbglHGJT/jtjfc46tNdNofEn5I58GWEzk32pS3ge8rmFPRn4TQ6A/kTHLnoSwmdd03Fl5SfzalAVASbOYx5/KJ8dCrWJQpQ9qjiALD+wjz6AzgpFOXh+/aP80JYUX9ZfYEnsR96D0+Lz1taIzApzYX3JYyFz+EX5dGzYlxfwpj4uiRfF9cnHJoC83G/uAbgaN+HqLuQtMtqHw5OSGsAzCkbGqQrvw9UhCHhNT86oyBFiRbEyEJq2pUvdV74LIStARA8B74MdLp9x0O3dxesgMO8CD5BDcAp4zK8UHEd3ogIfV3K7f8FOirXQvb1WJEs5rYKxqZONjZ1hG63dvkh7y6SzAonN6H0ujLxLxrFOgDRuGlvRQCCyyWofXL7oea8H/4s5XTI9s8cOw3VzwbgM8dCt9/Zp+sA6LazTHcAdNMthKkxoB0Va2CNewQFkY/BGvcIWk2Iy6x+LgAnT2MhsDU+CMaox2CNRxoGoehOPTsKn844DS2xr0HWrvchLf0tyHr+VY7ptDOKjzHqMaf4GOewLXcpgLSLfVvabynoT8tppF2o20tvbHLuttuptDfFB8HlRlJH7Vk/FHtfgYwkFQUo5TQ8ax/m6L8ewxWw7cbztu1CQkiTawUszWtgty7BKSOuIvL2IsSBumoXwF1+C+yN98BdfotHAtwVt3ErmQNfxgLYYh5CQcRjsMc8BF8qm/gz/j+l/aiRh2rkoi9pDuzRD7A/kVdoksUcBl4HQDhHWo1NG0TyShTrTzQdNR6UOQuaCAAr6kSSzgMoMLytJe0wpGTvgXGwR91n7Yw4w9CVnsR+TuLh/Q8qOeVI8bmvHNeBcYU6w4pted/I++BLGFOQo8nXwZcwBvZI1WeraDk0EVd/ti9hjLcT5Ye37R8HT2I/MvkT+7f17T08DZ6jL6FuQMqN7e0HxjUYUd9+1f4j2f6PXAFvyg0wp2xA7q7vQnbkE6QA7WqH/mNneUSm9+iM9rxYUTVd923tBycUHGjOWOhrzhy9/mNnkQIU+WXIjniCFKCUDQ0SdNt9QEXlqQN4L6rvJXZsvFaANCi26FFQTYAv+bbmXvYl3+L3uSnjjyB3zw/wuhAFKPsSOsdFM+BLvQP26IdK37QFjgJ1l82BL2eRP2e2GKQA2ezLvDC/27gMttiH/BnuLlhBLKhtGS7XDcDnDvdCa/RrkB39HmQdQQpQQ/s6mHwb0Hpyg9HRcNyjRZHKS0gZ81j90MTGRUtCENwOPyKJB3Bssreoxq79QbC3+ZH6cy8AxlubfBwsmEEHgOoACsc3wd62fVwsGtvkmie2TiIQPYamhCA4PfjZxUOb0NeJCzN9hi9BqeEn0Gf4ErwRWQXn3cNQc94P55pHQrZ3VpzXHQDddpTpDoBuuoUwcgAqHCNQ360w8M2nGPufcbArLwfg5DNM/OsFxMwR779kUBGnqbykvK4WwimcVARujHMK57pwYhNyVvCHMP8Ovq9oDHNg8xa1WLzCSUTfkZAY6QUUzOAKWtXFANclqH4W+dd1ZxSGd+05PzS2roGpF4V9GlvWoMmziszvljVo6FgHq3MFmjyrYGnGNrt1CRpb0BGwW3Aj1jhhPx3mRc76J5EiV/U8L/J1Vc5raT8FUwr1hzCJ+ROc/sPTgIpnlQLfnDFlokW8+NQBTg7iAk9qeotaBIzlYvM0IWLCs9xtTQ1AzphGvIsXDLP3a5j+xJWnaAK9l9rUGgJbdAg8eSp8plqrgD6ftAYoVWmrwBfpBBDjnrj5jOHvSezHSTu9hybp5CioOfz0GakDfKLPG4ZsmAAAIABJREFUNQ3YfjxHX1LeT2jOg5exT2K/omdAyFA6Fnat+bHQ8bDvzHP0Ja0ompr7rxYSU2sK0PWl60IRIVVhN0d5qr8H6pdyAz9X/X1uKQLmuf30+eze4KlBarE2mvAT758iABTVonQ1IgMRJpRE7IpmFM0LVTSMi+aVzfFnwV2CUTbS2OC1M+W3eBE+OeOuynlEgTINAEc9Ynudprtgb7wHTa4VaHKtgNWJWh9NnlVoaEcdAIt3lY+FjS1rUHUxwIXCqp/DxYXq51BbRD3ukShhySBqkxhvMaGuETbGTShCiPkLCvknbxHHzPwF3GhxRKN/MsXGVKanwp0BJgJGwmCl1zeh8nIAzrSPwteyyuGnB5Lha1nlcLp7VNEB6PPDc01D8I2UMvjp/mT429RyeNY+DBX2Ed0B0G1Hme4A6KZbCFPrAHRUrik6AHGPoKVhgytF1vX5oaVhA3UAot6BpvgguG0YAai54IfT3aPw6UxFByA14y3IOf8qlN5gEYBWXMkinrW1C3UA8u6yfFcfa1frANxBVeCiMdZ/v9Lf3orpQcXD+KPosSos7qY9eGyk+tvSsKHRN2irxfMx9aLyZY/hiua8u41sItCxDjb7MnSWrGoY4t0FK8rkgjH/KRrgqrmDExNamcy4y9nntpiH4Etb4IJHPBJQppB/PHnjijAYXzV9iCz+6AfITmfEHz7pVuVfcwXh7FFcbY77HmRHsNXm3e3Qn3JBmbyrhLa2FgErrP0tLH41538rT//ojGbivI3VT6vZ21j8bKWbfa4n6dp21v7haTw/NtHvPTihsPojcaWbVHWdET5cCVe1U2qSJ7GfRy543wPjGlVginyoWfw0wfck9vMVfg2Ln02oPUnXeHRCozOQ2A/e5OtgPrbGdABUEYCkc8o112gvqFb4mUPQe2gK7yc6rwTVRJzhWXk7XVcmQNafdA5e3qXSAYj7PpiT1tHRSuzfrghNziBzJigCwPfNUrL4hJ7E6RgCVON0shQme5SiA+DLWMAJf/EsmDI+Bbnx31d0APYoEQB3+S3wZSrPkT36AfhS7+Ckn6kBq3UA7DEPoScPxfmcdZgmhHocipYHYX4dDffghcob8LlDPq4DkH3oR1BnGIXGNowQttVsgG23Mn60nmTjhw+jAG67wvlv2oMRgMIJJtI1yFj9+xQdAGuXnwt75d9h0U0a29jYZ7yFE31rl0oHYF+Qp0UWzLAIgUr/RK0DUNaPiyFuh1a7pblxA0XBmLgjj+qyc+ssX4MKh+4A6LazTHcAdNMthHEdgBOhdQDcdpxIC2sAbH7oOSuuAci8/Co4PQLOfx9O8hvPCNpPoxiYsEagFdOARO2eJnGObqtpAxrb1qD1pEAHoHgVbPZl6CpaEeYP0yqjsw7FhtSpP67aBfBlC2oAMhY4uYev9LPVfm/WCHcOROz03kNTSl+W/qOZrOWMgTk1IMw3v3qwd9tqs1oIzJs6IM4nZxN1aR4+m0SLjl2Y488cDN9+eR6+VAdAwvL37R8X1wCw+gPhZzOxL+mxsQm6qN18dEVcA5B4Rq5/kD4k1nU4PC2/Loenw9cAMCdyWw0Ac7qEx5Y4g44XW9nnkSqKfKQNgsc4KbyffCm3wZT5KXENQPYl8KXeET5H7rI5sV5G5l2WwrcsfMZfqL4h1AGoaPwL6KgQ1wCcPL0h1AFwudAJEGmg2DqxXcT6bzjrF2oIWLv8UDyEjkWodqfbzx2TUO0tDRtQe84v1HaxGXUhMN12lukOgG66hTBOAdr1WfZDoN2s8UGofjYATXsExImEIARzw1CARDzrfUHIn5ewsvfLKUFNCUEoHJfTMISUn/ggNLbJOf+O+kU5BYjhPp2mu1B71o8r/yq0p4heYo9+wDGglPqQ8cqKkjrB0h+E5JSoB0p6jzo1iKIA2aOQFPejkH37DF+C1/cYueKvN2sEz0MVAUCijJwgFJ7lL+7//xvvPvI+eI5cEZN6IiWfHflVxvn/qvCzPQcvy69L8nXpsSXt/gfxdxKXJycrhbmmSCAS3y+vx+fLKUDM8dNEgsgBCKMx4E0f0qSVOesWtHUp2aPSe1lKAdpjFFOAYh6Cu2xOQgl6BM66hafWATiSKtYBaNoThJrzfuG4aEkIQvGQeGyy7AtC4aR87JONezKNgaa9QVQgFhCIrPFBqLkgJrvV7PoM6A6AbjvJDB/3Aeim2yfRPowOgPnUhpR3/f6hp9QBiH6MhW/R4n0XzMh516U35e1CjnfkY6jvWpdy/h0N9+SMccr9r8R8ZHIIPIXT4Kq5I+eXl9/ilBQSA6OCR1rZl/LyabWfcr1zxhQBptQBOXM+9giu2FI+unrll+XqPzUP/8PoAMj6Jl//aJ8dpv2jfLbnyJWPxOL/SDoAYa5puPP+eYxYByAh5he8JkJTA0ATe5m2QsRjXtNBdQj5dzaViEDWCHiKZsLoAPyL5F6V6wB4Cqel7dLnMJwOwD65DkDV8wFpe8UVicZJ9GNEf4rGvujH0rbC8Y+gExD5GGrP+oVjembEV0B3AHTbSWb4uA9AN90+iaZEAARKwPFBqD0n0QHYG4RgjiQCUCCJADAWtpB3vT8IhROSFf6EIJQMbkLT00QA4h5BY8saWOPESsD2xntShjip+bpqMa/fUzyLf7N/pRGA4lml8JeKfKkIkv0rY6fTRN+TP8GLfLn4Ut64XHV2dx6f2G2jALH/y1aT5avN4ZWCZavkUiXfyPCr7NL2MErAUs5/5H1k8YsiBJHh+n9VHgHYnfchrvnT6yOEUwLmq/d0HxDWkzkB0ggA3UtMhI4UqnmaWfaoVNMiad9PxNdlr0QHIOYhuCrFittKuzjKJ9MBOHL8XbDuFkQA4oNQdVEcGbXQ2CRq3xcE4+0wEQDRCn9CEApm5RGAihfFGgXWuCBUXhKrGOsRAN12mhk+7gPQTbdPopED0FQcWgeg1bQBdWf8wlxXj9UPvmfENQA5F14Fe7tYByDvLhYAh8x17UZcnihP1unBGgBHs0AHwOEHj6AGoKMSqT/tlQIdgCKkAfWIGOL5SxgBqLgNjvpFjiSkaICrel6cm5x8W2H/q4S/OAWIEVJEuc+cvU7pP0x8iZN1skbAnLQuzjc/dlah5jCKy1YhMDFTfjIsF96TNy7NR+9NnBWfV/J1cZ794Wlpnr4vgeEqE0Lfy70HxsX7PjQVRgdgAjyHXgTfntC1MqQDINMJMB1eEnwnFdCfdE782aR/IPpOjs7I6zYSZ+BqxkVxDUDi6vZIUPaoEgHIkegn0L1I9CGWWsYpQiyFSPidJ86CKfdPJDoAL4AvQ/AcZSyAp3Ba3J6KBfmiWpyuohW4dHJAqANQZfoCtNaFzpNvaUCSmCiP3t6GY5OoBsDh9UPBrLh+ydLnF46LhAIV7dve6oeKF7AAOOSxm7AQWFTXZT2h1wDotrNMdwB00y2EcQyofQR51/FBzrtuNW2AuQcdgPKXAuC1MKJE1GOkXVgV/F3P2VH401SmAxD7PqRmvgU5z74K+fOI87ScVvGsGemCkHfGWyj2ZdkXBGM08q5JJIzwd3YV79qSEAR7C1KEyvoRuedo1h6bpwnxnyef8UOLGelFBey82qvWob5rHRpb18BmX0YdABXnnxjhdssSMsQLVpAhHvEYKUDGZcSAViNikATAaOWfCEDu8lvgS7mt1QFIW1CKdyndh5wB+j/725s9ivzzKJUOwKEpJeefVH8Jy0jsdraZMv5oCwWoA/qP9invYwQgTe63Kp0DaTkPFOY8UX6ISEOs/oi3OaGIJoHe7NHtTPpDUwrFZ2sbUYAYqrP34KSKpf9VJPUcucIxnL79Kg2CyPs4+Sf8JukEaHj4k5zz70sYBXvkV/m+fQmj4DlyheM+sX2LBgHDdWL/sS39xzja05N0TaszwPp7Dr0I3rRBMB1eQh2AiHehLeJ/hpd3t8PVw6c55nPreVHxsXLNJ7Q6AEdnOPbUmzXC6UkFEaz9AGoceDOHFR2ACKYDEPsdMB9bU1ChWzGgbPWesKFcB8DAvu+DE4oCNSv6pYk/ITs55tY4ySlABUQ4SpzhzoI5NaDVAYjvQgoQd4bnleco+iEWADNalrtkjlOASAfAl7OoeR578pYUHQBG8rLZlsHqXIEXy6/B5w8iBSg7+j1OAbI0r0F91zq0V62DNV4ZP1rMG1D1POI/a877oaV+QzsuOv1QNIoozqJRhdRDY1fTKT9HIRtvb4K1Wzv2WXr9iAQdZxSg/axtP/YtmEEyWunN0ONi6XXEgpbe2AS3VaUTsCcIbrsfqi4GoOY8Ogkt5g1F+4URjiqsOgVIt51lugOgm24hTC0E1l65joI2hLtjq/8153HzWtiPiQFFZxxehpy7hsi5vL5XYX/+E9h9+Few78QTyOt7FQrHEdOZceVVSCh+ArGJ2JbxEjoHJH6TeflV2HcC2xMKn0DOs69C3mIA8u4iJzvnWWzfdfRXsD//CeRceJVztotGkXld8YKiAVDXh0qdNef9UOb4IhxJeRfi9/0KjqS+C1WmL4DJtwEN7etgaV4DZ4QPeeCeVbDZlsHRcA8c9Ytgty6B1bGiwQnaLUvgql3gr7srbmPRY/GsQgFidQHkFHBWOaE/SfyLkYAIB8pTKFg+P+X5a1b51YXCW9MtiP9OeFBalSVhsYIpZWWX+O1b+O/qXG6eBkKpIMSdJ749TQ5JHIxY/6oJK6E5Nbx+ij6odQbob2L104RaxdkngTHeJ+UGeA69yEW2SMyLM/pJByB9CCfgmcMapj8X/2LMfs/ByxzX6Um6hn22/q3CgXLRM9oX9VXtV/N+0hmg49x6HQjBSmx/ctJUnH51Wg7Xccif0F5LIvCQxoJK1ZfjTmm1nr4btu9QOFjO/Kf9smgBP0b1988cUq5fwY6POwQFU1zpWu3IcqeY9AFYdIzrZZBjrGrzFM3w91DxvbtsDrUAGJ2LInKk20GOvc2+jM+6GZ9zR/0i2GzLYPGuQmMbjgn2/4+9Nw2KK7vyfTNJRgFCSAIlCEnMiZhBDAJBQibkIEYJMhGaZ0YNiFmIQUxiysy+bbef7Vb37Wt1PA/RrklT9miFu8p+rrItu8OqkqveK8cLD7deuzs6enbVvVFvvQ9r733OgbN31q2K56rAZ0VkALlyZx7g5Mm19lrr969egOqGFahuXGFfD3YgGpnqi9Dv86/6oOSMF/VIzuPXgj68NuZf8UmaKCMSwpNe/9KWkPVvmsbv05a9kL7ghaxbSi2AjHm8zzSJ63MH8NqaPYJIUXpffj/eSs56obAbkaAHznmhqEvSR6GI5LITqJFCscgVrjUortEqAJptLtMSAM00UzGGAc0eVC0HO824i85rAaKY0LrDHgjV/0bh1wf/D0g9dw9SLtyDIIOyxB9k+AD29dyD9AUv7Lus7k89j/6U8xv9BsMHkNF5Dwp68QPWXqfUAWioQsGe3MNfAUPQurVBH0Ch+U/g0JFVMDuXWQXAFPQmWMKREV5bv8QSgTbTHQVDvC0Tk4C6ynnk/pdggEG55LaSGRakuPbNgSXkkcQvT5iS2P8yMSRH9k0WtMsFlNxxE5IOgOEBuIyTLBBiwbesFYgFgKlD0BvXCXfDW4jy609R+VW+40sD+fUtQGSXfwOLn7T/OBP6WVuIgvMfNyElFpRZv349CXTXc/qZEjAJMOlOOF3rihlhwbgzoZ+sv6/UAaC7+LEXlRoGVAeA6hMoXvs+KvUSkS5HXDe4tgzI1pIKAfUb+1iFQP7cNNjH6sPQhtemSULFtjmZDsA34W5wI/RsbZPEx+SBNhUdo+Jlewc2ai/EjioEvxT/syBSWSHJXO/OY3g+0ApA+HfxfCA6AYpEkAb4NNlIurbu/0128GlyauxTzqLIAn96frp33CQs/43rK42rpALwU2gKehHuRh6BnrRLUgWAqAgzPY3EaUlcr2ASXEm32fvMEvII2tNQrI8m76gD8Ii9h49mofCX1bwIF0uvYgXA8CKkGN6GlB3rKgClqwodkcaDGPSXnfDAgfPyyihh8ddhdTL3BtEwafFAjYzlX9MuVTczZ1HNV66BUtPuAdM0KgWbOzxQvU3SCKg9ihUAqpJuaZU9d7QfbDYUbcy9gcKMco2C2i14bAfOeaHkLFYBHLUehQ5AU9mapgOg2aYzLQHQTDMVY0PA4eoY0JpIHHYTDQG7OofArf+6qj8m8znsTnmq6tud+hTSF72QmMbxpz2F/Td9kMRZn7T3KeTe8IHNzul1rVyDvYnqa5PjfwhVzatczv+RHGwD4vnb0xZQ7bdgkrUD2fMm2VCwPY/PJ3fHSzuXdDffmXyD7dA7sm+ydg71GYIpVgFg60kbBk0eepPOiLnvsuBfMfxJgj1+n/0wimlxZwSQAc+dAdg+LtYYSLzCf+0tA6wFR9VPAnFev7orepjbw++KHsIef978QCxSk4Tr47r5MwCxo1ARu8CfAYg/rlT8lQmqScJsnD58kjyJ9BV6jSf550PcEksa2XlAd/XJ/dzXjp+QlIBpYkmrAqSiRdt/eDMEAXUAEqfV/+apc5gccPU2MPjn+dvTFsQ6AFX/FZoPqM8Iteu6sP2H00dfd9gDBX1esNfzWf5ZE4IZALcHao/y15omfVydgLrD2AbEnQGoXIOSs9j+oz4DoCUAmm0u0xIAzTRTsUAYUFPQMyg/7hHi7vxphVyUXlj8ryE57B1VX3L425Ax74Xk8Le5/sxZH3d9SujbkHdNzLtOCVF/7tTgn+IMgEgHoHKeTxAhjHG6y9j6aq+kDEzaf6wiChAV8iI6AF94XqMI5h2mMSEFiLV/ZI1DZfsaSxrozu2TqCw+9SXyqaK/e9/n15RCYCmDAlrORyDSCHUCHorXJl0Tk3iMfWIKkIjlH0AHwBHXLVyLGgM8//2AFCExBShdapNK6IfiC17pZ9ImFJgCxCczPQlP558PET9g7UDrE0F2Pohem6pRk+A///6k1LJG5lGEFKDoH/H/LtH7A+oA8N4nltBAOgGP4K93CShAiW+BhUMBqo3wQ8lZwcZItB8K+rxcQpl5K2H5c/zV2/xQve1jaghE+6Gwh08BqolCbReNAqTZ74rpPu0D0Eyzz6IFxIBGPBYKgZmj/fD2jgShEFhj6EuqvoawlyBjzgcNYXz//nGBP/QlKL4gYG0bnkFj8IuqaxuDX4LqxhWhDkBt3RLfr3/G2n1o0M/6/bNvgq1kRswvJ/3OztQh1tdMd01pW49oPdtdpUEW6eGmFYCfhewUcN9/KQk9kZ5zRetHINZ+IC68iFmvf/aJWPqO7ZfF/vjej60D4DD2fSIdgEDro4J/qeqjOgB0yJkG3vK5AefeAfFrx3V/fB2A4F9iAC8/D+gMCTmvhP8z2YyAXBHYmTLIzs+PrQMQFh/wfSTUASibFfr/r0i+DkBklEAH4CNsjBRd9gr1U4QaJ8HPhNe1nGGxDkDugNhfdpJ/7JoOgGabzXSf9gFoptln0QJhQBsOrUHZCcEMQL0HHqcXwo91+Rv8ofrfQPLFe/C59A7VtZ9P7oDsUR/X/7nUDjBN++DzyZz1+zogd0BQAYjww5fi3aprv7irI6AScG3dklAJ2FZ6m6E/7YVTrCXIVjIDjqxxgQ7AI9z5z5mQhiMzR9mgIx30FSoBy2g/jMRCNACcacPwJEKg/Br5Q2nwlvT0s8CP7DoLue+iXXpybB+bxb93QKwDkHglcIVAwOIX+cQ7/A/EFQKmI8D3C9WZwzNY2w8deJYPHQdUSA6gzvwk0iQ8H2igvmEYnAT2AVWpabBPW39oWxtJUoUVAIFmxbe2ZQt3+B3ZN4U7/EIl4NDH8Ddx/ApAXIK4AlB6mq8EXBPlh/yr/GuTmar5cjRQqrfxlYDNW/2QNSHWASjoE1cADpwXVADCvwRaAqDZZjLdp30Ammn2WTSaAOQ7hqDh0BrURiAGtGaLHxoqsFe07AQOljlqZajNKD/UOzyQPeoDd8cQ/CY4BH6sww/TfN2Pwa3/OtS0I6/66PkheN1wgPk6dV+F7xkOQHPPEGTd8sHhwSH4nor/yPkhyJjzwdGzG9e/bjgA7o4hKOwW8K4r1+BM3Q14PWjdWv0BOGe+DtVNK3Akd1l1bWv+MljNi9BmWuQyyGnfv61khlUCKMvfXjAJroQpTg//NBvyZQO/pFfauXeABWOuBPXeZ3f8hESNoa0X9EZIOr1xnWLuO6HD0ABz/RAwt+c7dhQHaXnzCcZJ7EcXMOu5vm0jwtd2xYxgn/6WAX4fPhnS5T1/oNkGvn9Q7CeDvlyW/7YR4QxAz7Z2nAEgg79s959WABL6+XMV8bcC/k/wfCjinw/rK0F0PoTcuP8T46QCQ0sF6lhSSs5Lvg7ABFTs9XE1K3qSz3PfB659SN/i6WW40uZxBmCf+gxAm2kRLhXzZwAOVPwxtBaoXx+aS1ehsm0Nmko5OgANHijo5V+bLK04A8DTSKk65eH2+FubyVqODkC9wwO5A3x/Q+UaFF/wQsMh9WM35w1pCYBmm8q0BEAzzVSMJgAFtiEoPYU4uMp2JOiUdyJGs/iCF4oveOHAeUTIFXV5If+qDwq7ES9X0Is6AI8zi+CncQnwyFQEbaeHIHcASRSmaUwCHuQVwvO4BHiQWwSN14YQcbfghczbPmjuGYJHpiJ4y4j+lstDsP8mki5yhnxw9NwQPMrC5/enF0LbySHI7/dB0WUv5A76kHYhY3E3VCGr++AxD5x0DsJf7CuEd2IS4C+TCuFc1XVUAa5b2qgDIKMAWasXwFq9AEez5ToAyBin5B9bCWIG6QCwvWgaE4DCKXBkjYMraQaswY8Yx9+VdFvq/5ehDhmmk5B9qLAXY69THQAqvEQRnUTBlSEiiRCTM+ka9CaehrsRrUgBCnqOFKDENWnnn4g8OdOGNwiBSRSfh0qOP8VKMkrQOp0AGdKSEmvYeiJoRYeMLfpXZJz+UYnjv+c6Ye2vY+kThCUO+sp4+DIWv2NnF0kCBpXrKYnH2Kfg+Fv0Mh0AghPd+NqI46TIUVfMiEwHgBCIZOhPfO37ivUUMVoRuwDpIa8SHYAX4G5oM/TEupVIUjkKlA4CyzUGFPoGo6xP32HsI3/zh6gDEHSfDVY7UwahN/64pANAzwcqAkbOiQ1KwDTB3HMdz8XgdecDfRzVo6DUIDoDQOdSUgbBHX8L1xMKkCthCitgpjHUrNjyfxAdgBfh7pYj0Jt4imlkuJJmwBoiex/tmwNH1jirvrmS55hOgCX0EbhS55R6HGnzivfw0Wx8j1ssd6A7txfuxrRBk+FFSDX8lFGAqhtXoKp5FVrzlgklTNIRkaM07Rblxojd6oG86z4ovuCFvGs+sNd7wBxNWP1b/WBt9UDuIOKPs8eIBgph/Vdv84O5wwMpPg9kzhAdgGhJI6D2qAcyZyWEKNMQIM9d5/RAYY+X6QTYbEodAEct+g+cw+u5o8ZDCEfPoDbCDy3FKxoGVLNNZ1oCoJlmKkYTgML6IahqWYVDR1fh4DEPlJxBoZuSs4iMK7rkRVEZGe7OZkPcXWG3FzrahuBzqR3QGPoSJIe+A7tTn0LyJdQByBlCNV/zVhnO7gii7vbf9EHqipcJgVG/2Y3PbZpCvrW1VfLXRPvB2oSUjcJuRN7VO8gHXRDBgFauQWXbGhw85oHG8jUF6q75AOI/q1pWUe1XjgENewxHcpeRDV45TzCgixIGNPQx7v4T/CfljNvzJtnNkTWOiYACXyhLAEjrjz1vUsKAEv6/gtuffRMq9v0XMEY+haiw/w7GyKdSAE+DM/p4yv6nARlhvVcmroEx8ocQFfrfwRj5Q8Q+UrEuyt2XC4HJeP40AdiAnEy8ghhQEmwyLCQV8yLBJBV+UqwnglU0yJZjPqlglWNnF1TuvAPG8O9DlOEXYAz/PpJqZIFwRewcGMPeQH/o61CxbY5hQJ0J/VCxdRb9wb8EY9gbUBGLfoYYpa+tvw+uyBtSy01cN1TsWARjyPcgykDWbp2VmP47u6AidkF67fDv43MTXKfD2IfHHvq6zL/Agnt23MG/BGPED5S/F/295b/XjkVJpyC+F/+fET/A9Vt+iOcDneeQ6zfQBEKuLUC/l6FiGXZUbQhYrj2w5zpU7loB45YfSscev4zPQcXhKJY2oV+qCtDXkyNCabJLkgXW/kbmB5huQM4EG4h3ZIxI6FzSPmfPm1SgQGmywNrxiB6HrQzfr/XliO6tL5+VtD6q8WvdoXl8v1ctgNm5DPV6F5gPr4D58ApUtqNmSHXDClS48ZpS4UI13dJTiAMtP45V0pKzqEVS1EWum12YBOQM+yDvuoQGZVoAt32QMYeM/8xZvJ9qA2TMeyFzBr83Tfkg/Y4XTJPSY7ImMMjPv4oaAvvHUQcgdwB9VBOg6JIXNVN6UbSRaqYcOI+3ChfBmp7EzZ9is5YAaLa5TEsANNNMxZgScO0gHOxYgwr3GhOFoe0/BzvWuJL39loPdLiwRWe9P8jwAeztuwfWFjEKr/p4gDI5T/K+GXezeGX2xoo1rtx9SxGqAPNK/G2mO0wDQLW9IHkO+/1JgEEHgukQsCP3Frj2qWNAXQmoYOrIvSUppdKWILprmnwDKvb93gY8okH3PlQmeSXyyvqdWhLkUQ2BMN1/Kv8n+g+g0riqENNSCECRXWdeqwvFPnJbOohasKiFiNfK4opB9dmK2LkNLSEG3fsYSMd1i/2xF6Fix6KqvzJuSdzis7OL/9wkCVBr48HXnsMAPW6J66+InYMgnfL/Gab7T4YQ5T135c47LADf4Kf/T5p0yTUODJIOgMPYB71JZ+Bu2DolYOOqFOjLZwBkO//OpGtQmbimfmy7VqRKEsWB0iSEYmnJOU0rACbdM0kTg7S+MdVqqgOw5Qj0JJ8Hh2kMbCUz4EqUdACswY/AlTAlvdeyb4Jr36zM/5C1/1Ayl0IHIPQxvr+rFiQdgG3t0BTyxlkAAAAgAElEQVT8IqQEvy0pATuXobphBVqKVhQ6AC3FK1DeidXSQ0dWobGCbDCQjZHD1WuQf9XHhArtVtzFp5sb9Q5sjcyY90LKhXuQlPwUkkPfgYawl+BzGR3Q3DsEacteyB71gdml3BixtHrANOVjCusW2caIeStuyuQOkmRjYKM+yuHqNSi67FWIO9JjryVtn7kNw1oCoNmmMi0B0EwzFZNXAA524MAvTQLKTqAIWMlZPgWoJtoP/rRCPgUo6zkXdWeO8UPGvFc47JY7yEfl1UT5ofgC/9hqt/ihNoIzxBv+GKobBEPAoQQDyvOHyIaAZehPWzHOA4iGeC0hjySVVKp+SmcBsm8yX3rEd1XXp0d8l7UI0edgCQGdATCeBLfua6rr2dCnDPVIAz+6Uy0cOE28IkRO4tDnxxgCJkO86aGvqf/eIa+CM6Ff6Hfs7IL0EI4/+FUhxhPXvsp/7u2XBf7X8NgFfmPI91R9bt3XoHfXCUgP5/y/Q8lzh31H3R/+XWyrMk6qJ13bx6E38XRgHYDEKxuVgMmN+9ph35ESz/U7/SSpEOkAuIyTULnbw9cBSLvE1wHYjcrb3BmAPaje3Z6hPsfTnrYAF0uvwut69b9LacldaCla4c4AVLjWuCx9m80D+VewMqnmr2nzQOrZjQKHEbr/gO8ZDkDTlSGoOsHRCDjmgfRFL3dGgCYYvI0TuwXVf3lgB00HQLPNZrpP+wA00+yzaPIEoLJtDQ4dXYUP30tnPa6lp7C0LcLZvb0jQagDIELdmaZ8kBn88XF3B84LMKBBz4SYT7NzWeivq1oIiBi0Fc+AvWga/vGXiazvnw4BC/GFubckekrmKKy9acdqQO4tRlBJ1f9UdX1q0HMFeSV9wQtVzatSD3byDXgSlSXGgMqUZlO+uqjUARBhPD8CqtOZfIOPfQyE4ozv5f/e+ufgiOuGVP3zj+0PhPHkr30LHDu7xH7ha78FUYZfqPrydT+GJ2Hp4t8rvpfvD3oegLz0EJ5EZATUAVC0gtHqEjkfhOci0SpwZI6CM2UQ2r/TrVCpdqYMCjUtjFFiHQARQciRe4urt2EJfQT2omk+BSjsMfxNXB737xIf/yaXAlQT6YfyTo9QILGwh68DUBPth62m59zf+0FukVAHQEQBMkf7hfooNZFIMNIoQJr9rpju0z4AzTT7LNr6FqCyk7jzTwP/oi6vUAegJsoPj7KKuB+i0dnPuR9U1dv8YJr28T/oov1gmvTxxXSi/ZDfLxYC433I1UY8BvNhcQXAYrkjxIDaCyal3X/ZDAC9j48BfbihAkB7/lklIGMEmoJeUF3fFPSC1G5Be/ZpKxBpvfhZ6E5+wBf1FAM72QCxAgMaACn5iUSpgh4IqwfOhH5o0n9T/ffWv0D8nL+L/pvgiOsWrhchSB3xvYK13wTHzi6xX7j+BTCGvaHq69R9Fd4N3iH4vV4AZ9I1vp+cD2IdAL4uRFTor1gbkKICIBsuF702TVjZOUVa0FgrUPINoS5EVMivVH35uh/Du+EBdAByJsRJerFAjyPoGbwbsYv/d4n8f4QbBBXuNbEOQJd44yRs56+5v/fzXQnijZPJADoAN8R+0bFpOgCabTbTfdoHoJlmn0WTVwBoy8/BjjUcciNJQPEFL3cGoM7pAVcnfwYg6fpXhHL3pikcEFbt8W/0QNYtH3eGwF6Lw8r2es4MwME1aODMALTmLUONY5mLAT2atQR1lfNwlDcDkDqHLUCk7cdeOMUGEh1Z4wRPOKO+Num2svWHDC+yth5CAbq75Yjq+rvhzUz512Hsk1p/qHJr0jV4EpGpqs0QpvtPHN6ka0jApqAA7bnOxVm6EqZJjz8HSbnjphBJKUJxurchvehuaJP67x3SCI7tl/n+0CZw7OyCu8GNHH8zFxHqikYhLO5zBzeCI66b/9zBjfjaIRx/SBNURM9smMmI0P0H/FiXD0/C0oTHjcfWzPfvHRAmXYF0ADYMg8sIUc60YbgbznntiFbpsTIiEPueaFNwE8aPoATMrR6EPAJ74ZRQKViUiFvCHsPf7ORXAIQ6AFsCVwBEmxPmGD9EZ/MrAPcLC/mtk1v9kDnDb42krZPCCsApvoaBVgHQbLOZ7tM+AM00+ywa0wFwDkN5JyYAtP+/7ISHkS5KznrBaVbi7mx27HPNHfCB69gQ/MHeDmgIfQlSQt+GpOSnkHb6HuQOIOmHUoAozq6mDTF3mbeRAkSH2ajf7EaNgawJpFtYGyWUXk2kH+x1mJwU9uCNEYqC0N94kFCAOtagqWxNwvhFPIaWQqR7mJ3LCgqQHANaV7UANTZEgbZlLqKfYUAXcLe/YBKHFItlw79kuNeeNwmOnAlw7Ztbhz6clmgmpjFEgKYMYhJAtQBI0NWz7xy8oStWaBi8oSuGnn3nGWaRKQFT/CKpDPQmnoL39cFKbQbd1yRST+IVBdJTQQEiZBh37OgGDKjD2MeIMwp/EMF80l1jMgisWB87ytqO3NtGFBhPqgHgTOiH3p3H4A1d0brfuwhxmTu7oDf+uIq/mPl7trapr9/ahpjOLQMyTKcSA9oT6+K8tgscMRegJ9at7icc/54dHfz1xj5wRd4At+5rzPdjXT68rzNAb1wnY/WvX9sb14lDvETbYcPvvaNDyOp3x46KdSF23tkgCOfIGJGQpMk3oNd4UvW1e5POSAQq2vZD51LocHraMH8+If4WVCZ5A+gACPQ0cm9xOf+ufXNgz5sEV6q6/6jpDlwu7IM3ODMAJeV/DC2F6jMATWVrUN24IpwBKL4g1gFIvsifAWjuG4KadjEcgbdxUnsEZwB4GyP2Wrye8469JlfTAdBsc5mWAGimmYrRBCCvYRgOHV2FCjeKxJSdxESg+AKy/w+cw0pAURci5Ar68DFFl72wfxwxdJQ9vX8ccXe5gySAvylh60xTeNs/jvdnj/gY6k6Owcua8LEEIGsCedn0OWnSkX/FBwfOefHreWxVKjmD+L2DxxDNV9mG1YxDR1bBfBi53lXN+H2NYxks1jtQr3eBxXoHrLWLYLHcYahAs3MZ6g7Ng61sFqzmRUXPv630NtRVzmOwXzglIQepLkDhlJQk5EzgYLBpDBMEmfAXu2WNM6SnI3OU7aj2Jp6CJ5EmeDc0Dp5EmqBn71l8HB3QpPx1SvWRqbD2xnXCk4hMeDd4BzyJNEFv4mkpWaA6ACRYV+z80koC9dNdXYqWpDoCVE2Y3rd3gGE+NyQZBN/pMPYhjpOgKR1x3RLrXiaC1bvzGDyJyIB3DdvhSUgqBrmJV5DFv/0y9MS64Ul4OvpD0zBI3tkl+be2wZNwsj4sHXqij0isfYILdcReRG0Aoh1Af+7Z1g5PwtLx7xaejsH79su4hr12htIve66eWDc8CUsjr50miXwlXWMJypNQmX9HB/vb9OzowN87eAc8CUuH3p3H2PE5Uwahd9cJyR+RCb07j+HfjqA/VbUXyP+oN/G0pAOgfw7p4d+VUJ7k/6d6HpBWsd5dJ+DJlkw8F7dk4rlIBn0ZHpYmgJQKJBtM36ADQETEHFnjULHvv2zQAejZd469D1wJ00odgD2z+D4iFTfXnlnpuUMeIaUrb5JRgFz75iQdgJBHWOGrWoD68lnoyu2Fu1uJDkDwTxkFqLppBWpsS3AkV6YDEOGH1sIVqHCtQVXLKlS2r0HDoTW2MVK7BXUA8vt9DAO6Xgeg3u6B/eM+yLrlg5Tz92B3ylNICXsbKUCpHdDcNwSZM3hNNXdIGgHmrYhPzpiTrouWVkknoCbaD9YWFAEr6MNrtPy1ayL9YG2Q0KUHzmMSULPFz363prI1KLBpCYBmm8u0BEAzzVRMXgFoKltjuLuaSD/Yaz1QdEkSAXPUIFIuk+Du6h0oeJN3zQdu9xB8fh/RAQh7B3anPIV9l1EHIH3Bi4I2BFdXHYMVANM0YV6veCWdgGDE2ZldHpYE5N4gFYCtytcuuow6AJS2IWf92y3I6q5sQ4Qpw/hFPIbWfNz5NzuR9890APSSDgDl/NeXz6KIEPWHPkIdABJY0MCfJgGOnAnUACC7+66k22ANfiThCWnQQ9GftO+f3OfcO4AB/J7r4MgaV6ITadCUMyEF8jSYp4kADebSholQ1wOJ00+DQblyMAn0NwR+yTeQl294gBoGciEvMndAg032/NvHpedPHSIVAOIPkolW7bkOruihDToA8qSAVgjoWlf0ICYLROxLwfInQmCOuG6WALgib4A16L7k3zLAVI+pUBd77pgRDOCpkJdiLYqQ2beex/Vx3RufmxwbFfuiQmOSX6owSEJgz6FJ/024G9yIlQuSCLG/ufxvRgXOdnaRqovcPyYpBideYeJsDAMaN8ESQ6Uuw0OpYkP0CxTnAUXEys4XXK88HxwZI0wXgs2gJF6RkgKaJLLXf4DvBfL6VP1awnySAD9xGqtk5D3i2o0JAHsfJUxLmht5k+DaNwsW4reE4HvUXjQN9RVSFWD9e9havQC2slnozulBDKjhRUg1SBhQuinQUryiuH40leJ1pfw4tiAerpZ0RmoiMQEovoABeH4/EeOKRtSmORqDcCpwmHr2HuxOewrJYQQDmt4BLZeHIH3BC+mLXjB3rtNHcXlg/03UDjBNK/VRzNGYIOQO4EZJ7g0fuDqH4HF6IbyzPQH8qSigSI+t+IIXTtkH4S/2FsL/GWOEv0wqhFP2QSiwawmAZpvLtARAM81UjCYAtdmDquVgp9nDRMB4ffoiHYB9Xfe4ODpLK7YB8XQArI0eyB7jzwDYbKhKbLPzdQC4MwAFGPy35qnPALSnISPclbbAaS8gKsBUDKxkhokR2YummQqwetvDBAtsKCaRElTY14wRbuuDO3ZMEWgzRWAa/KcM8nvw4yek3XpZkKegACVdE/f4pw6Be/u4up+oBfNe3xUzAq7IG8IZAJ6f8vL5ffxDLADn9fkLdQC2X+bPPkQPYWLBe+1IDKRF/optGzUGsNUFW4Rc0ervQZrccP8n5O/GbQHaNsI/H2LHpCBd1gLEgve0YXxuDsbTHX9LSgqpQjUdApYNpnPPh4QpQYsPttXxNCekFiCO3kYiwYTy/Pvm4FLJFW5rVHHlH0MrpwWopXgFDh1dhZZidb+9DpMAHmrT2uSBtNP3wMBrAeod4s5O1R7xQMa8l6+P0ogtQO6OIXg96AB06r4Kebq/g07dV+H1oAPg7sAkoLNF3d9Qe1ZLADTbVKYlAJpppmI0AcDBL/WBsQPnxBQgkQ5AdPZzIed//00xBWj/uFgHoKiLj9qrjXjM1QGojXgMFquI8vMY6ivmwBIq0AGQtQPRvn97wSSbB7AGiylAjqxxBTedJQKkl1qEP2RDl7QFgw5skl100dAla82RqcfKA7+AOgApgwKazkPx64soQEFIARKy+uN7waoP4Oet198XaBDcB0dct+C1H4ifm63n/94iCtCT0DThazsTr4gJRqLXNjzkD9IaHkoBvLwVjLbvkFYeIblJTgCicwC0AkC+ijCgIp/DNCb02wsm+RjQECR1iYaAv7VDMASc+Bb3+lAb/hiHgDnXl5ooPxRd8vKHgKP9sHU/fwj4laJCPuYzxg+mKcEQcLQfskd98Af7OlQThP/N2AHFF73whSR1/9QOB2gJgGabyXSf9gFoptln0WgCkKx/hX0ISDdExpWc+fg6AKG7BDoAhmcod8/TAQh+hjMCgvX5V338YwugA1BXOS9ECNZXzH1kHYDUry1g+w8dBs4cFa5lmgGkj/neO+WYBORMsN5+Lktf/xPWVuHcOwAFvV5cJxvgDcTxZ1WAlEHY+yfLyp3fpGtCbKMzZfAT6QQIWfxx3WL/9sti/86uj//agZ7b2PeJjj3K8EtVX77ux/Bu8A7x3zSh//+3vzmrJskF4Ugb2kfShaADwCT4P/D4ppQEkNkO4bFxz3NyrgneR47smwHfZyL/u1v4GNDI6L/nYz4/Cgb0kuC6GfwRMKACfZSsCfF1saDXC42hL63z4a0x5CXI7/dBY4i63xz8+6AlAJptJtN92gegmWafRWMVgDBOBYAK2gh2sh5n8HUAYjIESsDRqAPA3ena6oecIb4OQE20H4ouB1AC5mD6LOGPobpRoAMQ9hjqqhb4FYDQR9j2UziFVYDiGRzwpXjPzFHxziYZ9HVkjkoVAKIH4Ey6JlQSthoeKndZyfe0iiAWhXqg1A9Yz38niYVovSO+V7wjnHhFXAEQKQHH94r9ol16fYBdfP198dqdXeIKgLFPXAHYflm43hj6uqqvU/dVeBKeHlAhObA6s6ACIFpLZy+MfUoaFJkdEOs+PJSqVvR8kvf/kyqA+Ng+fgXAkTMhFgIrmORW4iyhj+BbO3IFQmDP+BWAiMdwsGMtoBCY6NonqgA8yCsSVgDSFwIoqA/4IDnsHVBLEFJC34ayEx5IDnlb1b87+CFoCYBmm8l0n/YBaPa7ae+88w4cO3YMdu/eDREREWAymWB2dhb+4z/+Q/G473znO3Do0CGIiIiAXbt2wdWrV+Hf/u3fNjzf+++/D6Ojo5CQkADh4eFQVlYGf/mXf/mxj4/NAOSq9x87apAGxOtlrTssngFIuXAPao9ydAA6PJC65gWzi9PrepRI2jdzcHZ1Hijs9kI9bwagfA0ay/kzALV1S9BaoD4D0GZaBHvBJLTxdADSFtgMAOv9L5iUUKBkcJHXm8xoP2R4l4mBkUFeR8aIoO96QpoXkCcClNaTMiju0SdtPozYsl4IbM91cO+4yX/tPdf5x0Z6ynm99O7YUX6ffMwIG+AV9/hzeuXpes4MgHvbCLi2DKivjbgO9q3nwRV2ld+HLzy2QTw2wbFXxC4IZwC4f7NtIzj7wNNPIMPZov+5cAaAEqXkLUCyeRLn3gH++RA3IbUKkYoBG0Yn57EzbViI8hSd5zgLw3kfJd3GAd9Ejn/PLNgLJvmY0LR5uFzYB69zMKBF1f8VjuQsqc8AFK1A6WkPNB7kY0CLLnnBwZudagqMAeVeN10IUOBhQOsdHsi/6oOklKegliDsSXoKxRe8sDdR3Z+w489ASwA020ymJQCa/dbt5z//OWzbtg327dsHS0tL8OUvfxnOnTsHOp0OWlpa2ON+9KMfQXh4OBQVFcEXv/hFuHXrFoSFhYHT6dzwnJ2dnRAcHAzDw8Pw5S9/GSoqKiA4OBheffXVj3WMTAnYOgiNFZRmgTi7w9VrUHqaIO0I7UKuA1Dv8DAcp6uT6ACEvQTJYagDkHruHuQOIsLT2qzE2VlaEWe3/6YP0he9YG1S6gDUHsUPuewxRIVaG5BARF/bXuuBgl4v5A74oOgSDtvRY6/Z4ofm0lUoOeuFyvY1aClCikcW0QFoLF+D2volqK1bAquZUIBCiQ5A6GNFcG8rvQ3tGYsKhKAreQ4JI+WzjADEEgFKAcoclVGAHkr4woRpTBKokBel/9ABSpn4ksM0xugoFJ3ojr8lte+QYN+RMSLhOCl2M/kGowAhEvKhFKzJ+P90h5YFfhQtauxDyk/QA4UOAHsNMiisQE4SETA6lOzeNqLwu6KH2G4zpd0wDYHYUSTpxPdKfjmrf8sA8ztiLzIKkILlv/0yw4giZUjO+scA3hHXDa7QK2DVo8+ivw+u0CtgCz0B9sgzYI84BS5DD1h0r6Bf9wq4wq+DI+YCknhiLzIKkOK5KYKUBOoW/X32u7kib+Cxx3XLKEBvQZP+Bbgb0oSY0J1dbMBZ+r3wb+Yw9iECNeaC8vc2PJAGwhP68X++fVymvfBQMTCOvnWIUDq8u14IjFSiWBKQdA1cCVPScwcT6hNNFOS4WBr8Z44qqgCUUCSdyxPssS7jpPJ9kjjNEgtH1ji4EqfBIseA7ptFClDmKNHbkDCglpBH0E61Ogilq810B9/jenyPt2cQrG/ZLFwsvYoUoOAXIdXwU0iNRQpQXdUCVDetQGuhdP2whD+G5gOI/6Q6Iy3FK3jtIRjQhoo1KOj1opL6ZS/UO5TXrtojSE/LHfRB8kVCAQonGNA0QgFa9ELmbR+jp5mCnzEKkGnKB6ZJvHYy/RTDMyQMEfHEgj4vpJ/YOGRsMHwApvavQN51H+xv/QoYgtb5gz6AjMpFLQHQbFOZlgBo9lu3xUX1C+mZM2dAp9PBP/3TPwEAwOHDhyEhIQH+5V/+hT3m7t27oNPp4C/+4i/Yfa+//jrodDpYW1tj9/3mN7+BtLQ0qKio+FjHSBOA3AYUAqtwrUHJWeTplx9HYbDiC17UAbiIXOuCPi9kj/jw+14v5A4i0k5+o4F/1i38oDJN4i17DMW/6M8ZcygEtv8mrjNN+hgeNO+6lADkDPkgvx+1BoouI8KusMcLedd9UNiN7P+yEx4oO4mM6/JOVDSualmFgx1rUN20AtWNyP6vblqB2volMB9eAWv1AtTrXdjuY7kD1uoF1AGoQKXfuqoFqDs0D3WV86gJQJICOuxrK72N7T9Uzdc0hr68Scb9Z4EKZf6Tth/G/c+ZkNp4aDsQfQwN8GmCQHutCaHFkTGiFF6iARdlsdPgkAZytPWHBIzOhH4l/50Of9KhTtofTvvBZQqvihtRFGa8//heBd/fmXRNcT9j8dPgln6VBfHOhH6G3mQaApTHT5OB+F5wxFxg+FAahFNsJn0++9bz4Nh+GewRp8AecQps4SfBFnoCbCGd+JV8X284BvWGY9J9oSfw5/CTYI86i89Dmf/y16G39ccmfyz9meoO0MdQbQL6e9LnoT6aGJFBXfY9/X+Q+1kgTpM0eh8NzJOu4XlFqz8kkXRkjLDzYQMOlg72rsPGKp6XJpL0HJAjQRP6paSWnLeOrHEmfseUr7PGpcR474A0EE8SYUfuLXBkjEgiejIhPdZ+R2Zw7HmTmITnTKiietl7mLTvWSx38D1+aB4sljtMG8RauwjmwytgsdzB60bDClQ3rLDA/+Ax6VpTehq/HjiHyOQD5/D6RK+RRZcQV5w7iNdDqpGSeRuvgfS6mHkbdVIyb/sgbRmTgKwJvEZmzOF9dF3mDFk76mPaAPtv4oZM9ghePzM678HW/c8hfMevISbzOWR03oOCXqLh0uWF/S1fgW1pzyF8+69he/JzyLf9NyiqHdQSAM02lWkJgGa/dRsbGwOdTgf/8A//sOH+oKAg+Pd//3f4l3/5FwgODoaRkRHFYz744AOIioqCixcvsvtGRkbAYDAoEgUAgDt37oBOp4Of//zn/8vHKNcBaDy4pmDpN5avwYFzGFwXXfZCnXOdDoAdqwPZo1gB+Hwy0QEIRR2AtJP3ULDmlg9q2lGQJtPwJlMCTl/wgmkadQDMLiXPuqbNg8JfAxj0W1sllnZNlB/s9VgBOHCeKAFblToAzQdQ1KzCLVUATEHI+W8pJCJgljtSBUCmA9BmuoO7g0QLwLVvFiyhcsb4HNjKZhkByJ43yZR/Hdk3mTgR45cHP2Tsc1fCNFMLpu0RrO2HqgCTAMthGkMdADl7XbZryjCNcnEvGoztuY4c/mAZE55y+Nf3aK8XgCLPi5z/ddx4wptnFQAZy5+1k9A2otixDax/GvgqOP8GZO2zgJ/gNtez+FkgTdp85DoAVEmYBuXy9Rb9fXCFX2cBvcvQBxbdy+jTvQzt+h4p6A/phHZ9j8LvMvRIiUL4SaYkrOD800B/+2WiM7Du2BL6sXqw/veKINUF8nsr/qZB9/F/tndAqozIf295VWXvAEOFStoMpCpDKj5UmXmDRgDZ+VckAHJMLNndZxx/nawaRedJ6LlHzi1HxogU3JOheIVGQbCsIrXnOvro+4TqZZAKAuphrPPvxkqavXAKbGWzKPQVsu49WnobH5M3qfSHPoI20yLYimfAWrsIrmSkfaEP3//1eheKBdqWoDV/WaED0Fy8iqKJLhQZbCpb26BBUtQlBf/2OloBwGuftREV1HOG8dpobVFe+8wdHsic9UHGPNFPiUF9lOoYVEhnScEq8UdLa+UaA1m3JAV1es1uOLQGRZcxGTl4zIPaLpHk2CPwuqklAJptNtMSAM1+6+b3+1m7z49+9CP4+c9/Dl//+tdh69atMDAwAAAAr732Guh0OvjGN76xYX1VVRUUFxezn+vr62H//v0bHvfXf/3XoNPp4P79+//Lx0gTgOoC9b7sxoo1Ic+63u6BtjP8GYDU8/e4PGuzC8vVvF5Wez2K3vB410yjwKrubyle4fboHsldhsq2NTiapd7j22ZCRWCeDkB72oK0q1ggKf7a83AewJF7S8jitxdOsSoADZBoqwRNBHg6Aq6EaWlHle64ypVX04b5/eCxY9KOsSzAWy8Axe1HJ20+3J5wEuxyefoxI8Jed9r+w50BIAG2qn/LgNhv6AGXoUf9/6nHIJ/np0kA10+Exvgs/0Hh30SoXxAzQpIa9ed2x46hgBlv9iF2lH8uxslE5eTngVwJOOka/3yKm8CKAk0q6flIh9NpMspj+Rsn+T3+CVNCPYyAnP+0BVQBTpvnvoe5729dF9TWLUFz8aqqv7l4FQ4e80DDIfXri73eA8UXvWC38Fn9uYM+4bXR7Bbro/Bmp+oduDHDu27WHcYZAd51syZXEwLTbHOZlgBo9qnY/Pw8REREgE6nY7dbt24x/5/9GQ5c/e3f/u2GtW63G4xGI/s5JycHrFbrhse9+eaboNPp4Etf+pLwWP7+7/8enj17pri9/PLL8FF0AHi0C3O0Hx5n8ilAW/c/F/OsJ318mkV0AApQpB8OnOfTMEQUoNqIx1juD+dTgGzFM1wKkDXkEesxZjfa+kMGgnn8cTnHn/H/c2+xwJ9WBkT0Ezb0S3utaXsGaesIyG2nrSIpgxsVYIWc/49ApNk78LEpQKgDwPHr74Mj9qKY5b+zi+u36F4Bi+5lju9lqDccE/ptIZ1g0b3CPXZHzAUhJUhIGApAEEICUSBKEP9/LqLwsPYd+RBw2rDUviU8nx5KrUfrElhaRXBkjgpJP0IKkF7gv0sAACAASURBVIiGRWhaXMpPyCNs8QnlUYAe8ylfupfx+iCgAB06ssqnAEX6Ib/fx6Wn1UT5IXeQT0Cr3uYPrAMguG7mXec/d02UWNsFiXBaAqDZ5jHdp30Amv1u2p/+6Z+Cw+GAP/zDP4QXXngBLly4AHq9Hj7/+c8DAMC9e/dAp9PB66+/vmHt6dOnISYmhv2cmpoKhw8f3vC4d999F3Q6Hfze7/2e8FhmZmZAnojIb59IB2B7AB0AAec/a8In9OcOiHnXZSc93GPLCqADUGNbEjLC66oWxIxx0gJkK5kBa7U0dEgTACG/nAT8tNc5xeNlA400eBLy0amQV+IVqK+Yk3ZcCV1IyKuP75XaRox9YJr0KTGgIh0BfWDmfCBm/Sdi8X9Cv8hXH+T+RP5PpEEQSGMggP9j6wDon0kzGvG9SgoQTRQD6UrIZ0LShiH3lSkpGcgaF+sA6J8Jz3NH1rjYbxoTv0dF78OgZ3yf7idgsdwRrq1qXhXqABT2ePnXrkDXtuBnQp9pWnDdNDyD/H7xdbOwm39NTw7CTSEtAdBss5ju0z4AzX737Gtf+xpERETAL37xC8X9586dgy1btsA//uM/fvYrAFv8UHxRrAT8KItfAYjOFSsBZ8x7+Ttd0bhLxlX63eKH0lMevg5AxGOojeDrANTWLQmVgG2lt/m7hyGP2K4/HShkw4lZ44Q/zt81ZUPBORNs8JcRVEggJdx1pRUA+TAm3bENwOF3GPvY8DAdwFXw34VMeaIEzH3++wHXC6sLwh1+ogMgUgIW6ABYdC+LKwBB7o9fIQhYnQhQ+Ui88vErAIYHAdWfhecSHcJe3wJEd/UDKT/Tnn/5kLqcCpQyKHx94Q5/oApAzgTXbwl5JH4Phz4SVgCstYvcCmHtFj9Utol1AIq6xPopOcMBKgC862aMH7ImBDv80X5sERJUTkX6KfhZoCUAmm0e033aB6DZ755VV1dDZWXlhvtffPFF0Ol08Fd/9VefmRkAM2cGoKFqDXtZOTxrm80Drs4h+B5nBiDt9D2wtqqvtbR6sAWok9Pr2uyBgj4vt5f1cDXOJ/B6WZtLV6GleEXV15q3DLX1S9Cap64D4Eqdg7rKeWgzLXL9bAC4QOr7p1oAOHjI6U1OmmG7/VQDwJE5isE3FQcT6QDETUiBFg2yZPhF594BwQzAqLRbS4ZuFS1AgbjvVAeA01PuikEkKbefPXpQ4BvGXnYeq5/gNrk6ApE3cAYg4jq3z1/U419vOAbtum7u2vogN9fvih5kQ768Y+PONgTQL6CzD+7YMfHcBafP3r1tJOD/c0MCIA/kRboPZD2jQ5F2ICpIxxCkgnkY7rmUMIWITx7nP2kG32c8vY0knNHh9fm7UuegLVP9/d2u64LqhhU4kqt+fWgpXoEK9xp3xshR44HCHi80VKn7rQ2I87Rwro3Vxz1QfZyvn5K+wNdPsTYS/RTOdZNqFPDmF8x52gyAZpvLtARAs9+6ZWZmQnl5+Yb7v/GNb4BOpwO/3w///M//LKQAXbhwgd03PDysSgGiuNFPQgHKOzwMTaVKHQB7LWLuSs4g1s5ulfGso1EHIGcYkXNtp4fgcymoA5AS+jbsTnsK+7rvwf6bSKwwu5BGQTn/VadwADhtyQtpK16oaZPxrqP9YG1G2kX2KN426ABYPYxOVHzRCw2VRKOAHHtT2RqYDyP6s7l0VaED0Jq/DBbrHdQCqF9iFKCsIFT+dCXPIfKTcMLb0xbQryf+tHnG/ac0IEfOBM4AFE1jNYD09rsSpiS+ecgjHOCl9B7S769QBc4al9COcnY6Za/H35KEl9KQjMNEmOgwJ127nglPiTCkdchh7JPaiOSBH00C1nP+afJA1F7d8RPIpNc/Iyz/MSkI3DvAiDWSDgBROd7Au78vUYAoD1/B2n/AhmwpQhOfW8bij7yhwHG6Qq+ARU9Z/kjyqQ9yY5BPKD/U167rQvxnkBuD/A3+brZW8pPn1r8CrpArEt6TDPNa5ToAJLGRfu91x739srR2HeffFTPC6ELOPdc3/E3d20YYIciZ0M/ISxu0G4i4mzX44UYfPSfkehBy9CcdLCckHoWOAJ1loWhROotCvydD5o7MUXAlTCvOR5cRB+ediVeUGgFUL4PgQp2pQ7hWoacxxSptjowRcCXdlnQCiFZHffksq9K50haY3xLyiCX4tuIZOJKzpHj/H81egnq9Cw4e80CNYxk5/zIdgJbCFTh0BLUADnas4fWFapBE4rWJEsryr/jAXqu8btpsuLGxf5yQetZroBxBjZSMORwSrt4m+cwuD2TOICo0fWHddZMQhvKuEXTysA/qDq+7btYhqrToEl7T5foptUQ/Jd85rCUAmm0q0xIAzX7r1tTUBKGhofD2228r7j9y5AgEBQXBr371KwAAcDqdkJCQAP/6r//KHvNHf/RHLEmg9r3vfQ/W6wC8//77kJ6erppofBSjCUCBfQjKTiD3/+AxogdwBhGgxReQsV/UhR9o+f0+KOhFBn/+VYlrnTuA32eP4YePaRq5/lm38PvMGR8k/z7ufGXdwsdkziDjmjKsKd86eww/5HKGfZB7w8eEc/Ku4WsW9hC+dhcmASVn8QONsrkr3PjhTD+kq1pWoap5FWpsS1DdsAJm5zLUHZoHa+0iMr+rF6C+Yg6s5kWmBWAvmob6ijmJI16E1BFb2Szu+BP2ONMFoNUAgidkiQBBflJuuXzo15E5iuxzqggs0wFQtAStb/mRqa9SvQAFipFy++ljaVJB0J8OYx9+v57/ToNBKuglFw6TiY+tHzqWc+XZ65C+cob3jO+Vkg+CzaRaAXIRMMbL334Zf6Zsf8rOpz/T79fx/hnrnzD86w3HkPFPAnwW7Mu+Mg0A8hiFJgBdS35WfC/TCGC6AJThTzUL5Kx/WaJAv1KNBFXdA7kOANFzoDMc1Mf+7nIeP72P/r3jujfs6jPEp6x9jJ4HjgxEtrJzYP25sG7wl2Fl5aJgVG+CrqOaFvR8pDd6PLSKQHUtUofYTAyrlmWOon4AxYuS9xDT4iA/U50Oiue1ld6WxPvKZlHXo0r2Pi+fBWv1Anv/1+tdUNW8ygQDq1pW2TXE7FyGCjdeW+j1pewkXjephsqBc14o78Rr5sFjiDTOv4rXzsJuLwbpY+R6OYK3jHkv00BJX/CCaVLSAsgeI9fQ23jtpPdlTUjaAqZJfJ7cAaKbchWvnfT1qDBZ8QW8dhZ24/elp1EzhWobFNi1CoBmm8u0BECz37p9+9vfBoPBAPHx8TA3Nwdf+MIX4PDhw6DT6eDSpUvscT/84Q8hLCxMoQQcHh4Odrt9w3O63W5WMfjyl78MlZWVEBwcDN/+9rc/1jEyHQDHEFS41+DQkVUoP44JQOkpFNYqOYMfFgV9XjBN+eDAOSJqcwPFwPKu44dO9igJ2Mn3uTfwA8k05cPdrgnpRjUATJM+yJz1MbZ15gx+zR6TnifvOq6nr1l6GjF2xRdlCQoRACs74YHK9jUmzlPhXkMBn8YVqGpZheom1AA4dGQVauuWwOxcRiGwQ/NQW7fEgoK6qgUm8mUrnsFEgOzus0SAigyVzDARI9YGRESLGBaU7mZSYSPaIkFJQORGKwGMoU4DIUpWodx1WfDkyByVgjF58C5X/KWsdrnQF7kphj/lisI0YKQ4RxrU0QBQrhZLXpcF9VQQjNxYmwnREWDBPGH7s4pEQr/ko4E9FQcjSYEj9qLEzqeJgCzApsG/IqiXBfeK79USApoAyP3yZGDdV3vkGRQJizyjFAWTi3/JNAxYokB/J/rYnV3s/8H+BnLBsJgLyoSA/l/lYm9UvIuKsFHdBvn5QB+7nvUvTwTp4+RJH23vkQuJydvPZCrW9Dxh5zI9Z8n5SytdDIVrGpPmYGTJsLwy5sgal6pmORPSDA29ZY2zVjzWnkeFv4pn2MC+vXCKJfv0vV1fMYfvffL+r9e7wGpexEph3RITEaxqWQXz4RWobEcNALrJUN6JCUD5caliWnIGr0uF3ZImQM4Qbp6YpvFaSTc2cobxukc3R9KWvJB+B5OAzNvI/KeBf9YtSfiLqqnT62feNXyu/KuoBpx7A6+Z+Vd80kbJeayayo+x7IQHqlpWofSUR6sAaLbpTEsANPtU7PXXX4fDhw+D0WiEkJAQyMzMhMXFRfif//N/Kh736quvQmVlJYSHh0NcXBz09/crKgLUfvOb38Dw8DAYjUYICwuD0tJS+PM///OPfXw0ASgtH5B20GXBdPlxDwu4C3rxA6SwB3eUDpyXgv+869KHWPYoqQjcIJL143jLvO2D9EUvpC15IXtUKmOnL3ghY96LFYFZ0vYzRtSER3DXjO7+013//H7yoXZJ2m2jH2b0w7m6YYV9pe1A1Q0rYK1dRJVP5zLb7WNqoFULeF857hLaymahrmpBifssnJJ2JGnAT4MQutsvC1JogEN3I5kCMFH7VagCZ9+UkgAaSNHdfhr005/lu+50F5f2Xcvvozv+8qoADdrWJwB093a9qixdS4NLuSItfRxdIw9AaSBJA1HyPQ3q2e4/3Q2nO9skKGZtQXQ3Xb7DHteNAXTsRRYY0wqAIlDXu1QTgPW7/qoJgeGYtF6WBLDnJ4mGPeosHoeseqHY/ZcfZ8wFpXJwzAVpLU0adnaxv/F6ZWRFJUCWOCkqMvR/oLbbT9qwFArPZJ2iEkTPBfn38moDubFqkkyhmu72OzJGpGRxXQWJBvxUB4NVw+Tnv2wmxmEaw8ebxqTdfyq6RzU4TGMSiYtUAOoq59n3LBkom0V6V+0iqn6XzEBd1QLU1i+xa0KNDXf/a+uXwFq7CFXNq3gNIclAZRtumBzsWINDR1eZEnnRJRJgn8fNifx+HxPfKupC5fTcQbz+mabwGpc1IamgZ8xhwJ97g6gCz+J96YtexSYKVQ3OmsDHyDdO8q5jFaDoEl6riy7jdZMG/vn9Pig7SZSLz2EVoOQMqVY0aAmAZpvLtARAM81UjLUA2bACkDvogw/fS4fSUx4ovkDK2URtt/iCFz58Lx32fnlVIXNf0OuF/Kv4Qfbhe+mQMyR9qNEeflrq/vC9dNg/juVu+YdZzhB+yH34XjrkX8UPsOwxvOX3Y8tP9ij6C3vwg6zkjFTOLj3tgQ/fS4eMOZ+i9ae6YYUlAB++l45l/tpFTATMi2A1L7Ldvg/fS8fe/9LbuCNIeoTpzx++ly6JflHiDwn6//d3SrENIfsmzgSQVgTavnD/3VzW/uDIvolfZe0+7d/pZthEtpYGUZmjkPz7Hmn3PvEK+kkwljnjw+BofWJAdn73/smyMmiju7MkcNv7xVVlAiB7jHPPdVxP7mPBnqzFJG3Zq9gdpm0pjrhubLMyLyqSAvmutmnaJw0ky1tjyPfZoz5FpYD5yOtkj8j8pFpgjzwDtpBOcMT3gi385IZde7Zzv/X8ht1/+c6/Y/vlDW0/8udwGPtYEmCPOAX2reel48u9hZjVdTv8NEEovuBVJjY0ASC/l2kK/y6KdiCaNCVegX1fWJMSKloBoNWAlEEoPeXZMOdBq0Bsd12mGk0DfUUlSL5OVm3I/OastPtPH0cCe4dpDKr/aliaS5Gds869A1BfPgspX1uQkgBSIaAVsqwJn5Q47B2Qdvmzb4IjYwR6f3ASg36aKJD7qfL2h++lgyP7Ju72k5u9YBJbf0pmIH3Ry1p+6I5/ffksa/2xWO+wawJt/6lxLEONYxne+bkRKtvI5kIjbi5UuNdY2+SH76WzDZPCHum6mX8Fd+M/fC+d7fjnX8Hb/nHcKMkZwvbI/eN4zcucxa8Z89J1Tx7kszbLKR/z0xbMrAm8ftJNEvraRV14PPT6WXraA6WnMPDPnPWxiq9WAdBss5mWAGimmYrRBOCgzsY+/LWbdtNu2k27/W7eDupsWgKg2aYyLQHQTDMV0xIA7abdtJt20270piUAmm020xIAzTRTMS0B0G7aTbtpN+1Gb1oCoNlmMy0B0EwzFdMSAO2m3bSbdtNu9KYlAJptNtMSAM00UzGaAGS3jkBjBRHTMryJgjZ1OAhc1IUYUGsLispkGt4Ec7QfLK0ehvS0tqIgTabhTTDH+MHc6YG0ZcKyXvFC7VHiD34Tqrf5ofq4B9KWcPgsxeeBQ6dR8CYzWFpvmkIs6P5xHz5/tPTa1kYctMvv94Grcwj+YG8HNIa8BMkhb0Ny/A8h1/EV1DE440WBs4jHYAp6E2rDH0NLMZI8KOGjXdel8Lfmo0pwXdUC1DiW4WgWCgWZ9G+CJfQxtJkW2ZAwvdlKCE6QDBvaCybBVjwDrn1zYAl9hGtDHoFrz6xykJhShMhXxYBx1ji442+BNURa744juENKGqJaAhQtSigpKJ6EImQm/TNJuIkSgKiAEyGx0A9/NhS6dwB6d5+GJ5Em+FnITngSaYLe3acVTPfeXSfgSUQG/CxkB/p3nZCGfI190Bt/HNcHb4cn4RnQs62dkW1644/Dk7A0+FnwDngSng4929olZGjSNejZ0QFPwjPgZ4bt8CQ0Df2yYeCeWDc8CU1Df0gq+nd2MRxnd/Bh+JZ+L7yri4Fv6fZAl97Ghnu79Db4lm6P0qd3bRjypUPBivtUdAFsoScQARpzQUKWyilAcvwn/Xlnl8T9J9Qjhkilj5NThMgwsHPPdcVaVQqTmiYD/V6O75Q/nnD42XlA6FHML9cPoOePnBAl16vYc12BsJXTpxzZN3Gol+I/5ecxQd0q6D4ZI7iGIkDJQLA9T0Ls2vPwPUPvo6QuivC1Fc8wfC+lelHKF8X9Wix3wFY2C2bnMlQ3rUC9HilAdYfmGQXIYr0D1Q0STvjQUUkMrMKNw8F0sJZeMykpjV6r8q7hwG/OEGH4y5HJY4SYdhOve1QnxTSNQ8GUGJQ9go/Lu47PsX8cH5M9JtNLuU40U2S6LXQIuOSsNJhcfBFBClS/oPS0B3IbtSFgzTaXaQmAZpqpGE0AKsuGubLxJWe84KhRl5W3Wz1Q71D3WVo9YJrG4F1Vct7tgZwhH1/y3uWB/Cuohqnmb6hag87WIXg96MAGvyHoA8h1fAUaK9Tl7luKVqDGtgStecuq/vY0DAzaTIuqflfqHFP+tZXNSmhQQihx5N4CV8KU+lrjpJIERAN4ikEkQborcVp1vTv+lsRUlwVfjLmeMgiuBM7a7eNMyZchRpOuscDPkTmKwX/iKXhDVwSduq9Cnu7voFP3VXhDVwy98cfBuec6378T6Ti9cZ0q/iLo3XUCenceU/X17OgAx84u6Il1wxu6YlW/M+ka9GxrV/dHHwH71vPQE9ao+vxdQXboDnao+/Q2Fui367rBonsZTLpnREW4T5EUUKVgyd8DtvCTLOh3RQ+DRf8KmHTPmMox1SioiJ2D9JBXIVX3HJr034S7wY3QE+tmBCOqIoxrH4ArekhKquK60W94wPzu2DHmdyZeYUrC9LWZ2i8J9lHd+SH6DWS9jAglTwQZKYiu3XFTem3DA1SWlmNE5djQNBkJKPkGVCauQXrEdyFV/1No0r8AdyNaoTfxFDsXFcmqTAmYJgiuxGnifxOswY/AlTQjoXZzJsC1b1aRKLv2zTIBMEzEZ8FC/aGP8f1dNgv15bOoEhxKEvywx9Cat8wSAPPhFTiSu4wbAEFvohJwMeoAVLYhbaypTLZxEuWHw9VrKFTYh0lAQ8Ua2zipiUalYMr+T754D5KSn0Jy2DvQEPYSfC6lA5q7h1AHYMEL5k7Zxkq0H2raPAq9FGujzL/VD/Z6FB3Lu4YBfr3do3zteqQUUfxneaekXUBpRnmHtQRAs81lWgKgmWYqxnQAwr5IgkXlrSbKDyVnvVAT5Vf1m6P9fF+MH0zTPjBv5fvTF7xgjuE/d84Qf31NlB8emTCYU/Pv3P0W1G5RX2sJfwy1dbizr+oPfQR1h+bBEvqI63fkTDCuOMV/sl3JQgxo1NZagx8iKpTuasqSBoZoTB3irzc8VCry0mCN7uzuuQ5WA2/tAyWekaxhgR/BiN4Na1ZNIO6Gt4AzdQjuhvL8zeBMusZfH9LI94U2gyO+F+4GN3LWNoFj+2W4G9Kk7g9uAPvW83BX71T36+xwV2fn+mhwr5oQ6rqFflfoFQzgI2+o+2NGoCJ2AQy69zf43tAVQU+sG1zRQ+prSRLg3jbC8aMgmzt2VD3p23ETnKlD4I6bUPfHTbAkgJ0HVDmaoGTd28c5yeiEFOzTxJKeh0ToqzLJCwb9Byq/dzH07D0L7nj146JJgCvptrp/N/HzEu09s2AvmgZX2ry6P3mO62vXdUHdoXk4mr2kvoFQjJWAxnL1DQZ7PVYB7PXqmxfWRg+kH78HQYaNf5fvBR+AxmtDYD7G2Rjp8EDmjA/MnfyNl+wRTA7U/E4z4j5LT6FyMdVQKb6ASUBOywhoCYBmm8m0BEAzzVSMJgDJ+lfYh4R0+3/BZHgGpac8kGl4k+vn+oKf4W6VwG+a8kFmMP+5cwcF6w3P4J3YBMjT/Z2qf0vM34MpSH1tVtAzMB9e4fv1z8BWehtMer6fVgDsBZPIH6diRKQtQbSWtTWQIKn3ByelqgDZ+RStZ20YiVfA+q0bCpEwh7EPTLpn6mt1P5G47ES4ae+fLCtaPxzGPmjSv7BuLd6a9C+Ac++A2L/nOjTpv8n1i3zOhH6B/5vg2NnF9+u+Cbbwk9Ck4/n/DJp0f8ZdW284Bhbdy6p+i+4VsV//Cjh2doE16L6q3xr0AIxhb6j6OnVfhSfhGWANesBd69h+WfDc90nSx1lveAjOpGtiP0koFa1gVAsiZVCcjNLWIKLSe/jbV9k57Nw7AMbIp/zfOyqLn6wGPwSHaYz72paQR2AvmgZrMD9Jt+dNgjWE77eEcjYAdC+DxXqHu0FQG/EYqptWuBsMNVF+OHBOvHESk/mc+3e5X1DI3xjZ6oesW4KNlWg/5F/1cV+7JsoPhT2SAjDVUKEJQb5jCLQEQLPNZLpP+wA00+yzaAErAJF+KLok/iAzR/N3+DNnBB9UW/2QMeeD6m18f/aoj/v8NVF+8KcV8isASeIKgPnwCljCeRWAx9j3K6gA1B2ax2C/aFqqApB+fkf2TWEFgAb+dA7AkTEiKZ9mjGDgwt3FfygJhZG+f5YAkO9FwZ4jvlfa/Sc95CzwI73aqfqfgloCkap/Ds491yFV/1zdH/QcnHsHBOvf4q/VvwWOuG6xP+YCpOo4ft1bYAs9Aam6tzj+N4W+esMxYeJUH+QW+h3bLwv9UYZfqPrydT+Gd4N3iJ87vlec1CVeEa/PHBWvJy087DyQ7f47k2+ASR8goaQK0+R7KnrnTB2CqJBf8X/vkJ3859Y/w+MW+J2pQ+IkvXBK6Of6dD8Ba/UC3x/0DKpaVsEk2JwoOyHeOAnf8Wvu3+UtY4JwYyRz5pNtnJSdwDYgpvZORMAq3GtQWK8lAJptLtN92gegmWafRaMJQHWBevuBvRZ3iJxm9XKyzebhlpotrViqtjap+2uP4KCvuYNT6j7mYX2uvPmDjjb+DEB+/X+D5uJV1bVHcpfBYr0DR3LVZwCOZi2BtXoBXKlz6u0D+0jfPw3gSduPrfQ2/pwzwe3DdxknpSFI2vdPg38yD+BMHQKXcZK7ngVntP2CBFs0COO2bMTioCUL2PYOgDOhXwr89g6AM/kGpIe+ti5wwFt6xHfBkTEi9DsT+vn+kNcgPew7XJ8jvpe/NvhVcMRehPTgb6v60/RPoN5wDNL0T9T9um9Bmu5bXJ+4AvCy0G8Nuh9gl/4BGCN+oOrr1H0VnoSmCSoA98GZ0M9/bsMD9HOTvge4iy9IKGkyyM4DuvuffAOrTLxjMzzEgWE6aExbfzJGWFJqjP4R//eONAmP25F7S9xKlzcp8D8CW/EMWIQVAI5P9zKYncvCCsChI6vCCkDpaY9w4yQ6W1ABKCzkb4zEBK4AFHV5hRsnB855oegyVgGKL0iDwKWnNCVgzTaf6T7tA9BMs8+i0QQgt3EYmg+skmG2Z1AT6QdHrQeKLyLJoqjLC/UOj+SP9kO9wwN515FoUdOGlB6T4RmYt/rB2ozBvWnShx9Wx3BYjfrNLg9kzOEgW8a8F9fL/NZGHBDOHkOChbUVP0zpa1NCUclZL3S4huALSUgBSgl5G/YmPoU8+1egwo2DepQClBX0DGojHkNz8SrU1uGAn8VyB9p1XWAJQz+l/FjNizhAWHob2jOwEpClfwaW0EfQlokUIDlpxF4wKSUE2TdZRYAOH2bR4cbd0ywwcmSOMgKKM2WQVQFYEpA2DC4jBjhZ+mdgNTzE4D/5BpsVYJUDch9txXCmDOJAqOEh7mYGPwRXwpQ0NEyTAEKHYYEf6QWvjF/e0K9u0H8AlYlr4Ey6BpW7PRv9uvclv9p63ftQGbcElXFLqr6K2AVwGPugYseiuj9qGhxx3VARManqPxg8CraQTjgYPKrqLw8agXL9MNdXbzjG7/E39IEtpJPvjx4iQ7qcPv5AMwBb2/g9/jEj4Ijv5frd20ZwRiD+Fr/HP/EKPyncPr6xAkDaw+j55I4d4z837f9XoUs5MkZwBkD19y6G3sTT/EQ5cRocmaP8Hv/EaUy0OcPybAYgaUbdnzYvnAGoblyB1gL1DYLm4lU42LEGjQf5MwD5/T6w13I2TuweSD/BmQEwHICm/iEwu/lwhMzbPjC7OPMFzR7IGfaBhQNfsNfhpg4N/osuIwGo7ASpANi0CoBmm8u0BEAzzVSMJgD5zmEoPYWl4APnvYwSUXraA0WXcGeooA+TgcIexMgVX/RC7iCi7LImJLRd5owPMuYQW2ea8kHmbUwEMuYQcZc1geg706SPYULTF7xgmia+MZI4TODjKdWi5KwX8q8i3SL/CiYGB85hckKPu+yEB8o7PUjoILeDHWtQ1bIKVS2rUOFag+omHOAzO5fBYrkD9XoX1FXOg8VyBwd/yde6QwQTWDKDqM/S21BfeaAgLwAAIABJREFUPsuQgvKvNAlw5EzggC9BFTpMY0gqyRpn+EPW+y/HeWaNK0lANEinbRV0aHddqw/7nswOsP7+PdelNg45ypHeUgZx55b4FC1AZEi40rgKxsgfQnTIr8AY+RSDe1plSLoGlbtWwBj5FKJDfgnGiB9A5a4VfO6EfnAm9KM//PsQHfxLMIZ/Hyp2LDK0ZeXOO2AM/z5EBf8CjGFvQMXWWQmfaeyDim1zYAx9HaIMPwdjyPfQH9fNMJ8HQ2/CrqDvQJTu/4ZdutdY8E9pPQeDx2GXnvj1r0G5fpj5yoNGYJfuNeL7DpTrhlQpP1m6n4BF9zIOAMswoC5DD1h0r6Bffx9c0YNI+SHHTkk8WbqfEArQEDhiL4JjZxdUbJuD9JDXIFX/FtJwQpqgZ2sbQ3+6oodkax+w4F5J8ZH55SQeEuSzpM/wAAeE6f987wC44yZwPUXDUkoQ2elXVADkVQC6lh4bxcrSJJImlvI1svsqUn8fKUBBzxkFqGffOdYq5I6/hcetf4aUn4QplhQ7TGPg2j2tTKT3zOIcTfZN9Cfdlvwhj8C1bw7seZNgK5tFClDavJTEhz2GNtMdRghqzVtmaxnmV+8Ci+UOWKx3oDV/GSzhZIMg7DE0l65CeaeHXUsay9egdou0cdJQsQZFl7xQdAlJQI4aD9TQzZFoP9Q5PZB3Da9pe/soBehtaAh7CT6/rwNaLw1B1i0fG/Q1x/jBFIwbI7VHPJA5S/DIN8nGC/VH+6Hejps2OUNIGap3SBszNVF+FvwXdmPgX3TJC+XHcRag5Az+nNugVQA021ymJQCaaaZiNAEosA9BQxX9IHsTarf4wV6LrP0D5xFn1yjH2UXhh03edUwA6g7jhxzF0dFdKNO0j7X5mKMJ538rcv5TV7yQMe+F9EUv+mOk9bVHCCpvCLnWFpkOQE0UovQKe/ADi1UmgvC4nWYPQ/RVuNagsULSAbAQzn9V8ypYqxegtm6JVQAoBvBIzpIU/BMUKMMEhjwCV+oc2EpvY+9/6W3k/tNkoGhaovlkjYMraUaGL8RdeEb9yZnAoD/7pqJlQt4/7Y6bkLH8HyJ1JekathDJd/7pPIAs6HLHjsmQjw8lHQDZADBt39iQACRdI8HkA2l97KjEh08dQixk0DosJKXHJPRvQFa6ogcZ69+9TYmrZL6dXRhER96Q/Pr74NoyALbwk2ALPSFDdb7CUJzt+h6J2R/kVkF59nAxnu164tO7wBZ6Qh3zSZ7bFnoCXMH9Ssxn5A0F898VPQzWoPtKDChBhFZsm4P00NcgVU8woKFN0BPrYvoI7thR2doHjPBDNQI2/t2GlAnCthElJjRugu3O9xpPwt3wFmjSvwCp+ueQHvYdTOpokrgOA8rQsvRcjMWBXMX5RCtOtAogqzCxtXsHWCVrw1ry3K6E6Q3vEzoP40wblmFCZe8jogngyJkAV9LtDRhQW8kMa81z7ZuV9DhCH4EreQ7qDs1DffksWGsXoa4Sef91lZj41+tdTCekqWwNasOJTkjEY2gtXIHqhhUoP46bDU6zB6+bQW8qKqcFvdhaY3J9BbalP4fwHb+GmIznkHbmHmSPIqM/a8IHqefvwVbTcwiL+zVE5z6HlAv3IP2OF9KWvZDiQa2U7FG8FmbO4uZI5izqAWRNED0Beq28IT12/zhqABR2YyJSdBmPqaAPW38OnMedf/kMwMGONSiwaxUAzTaXaQmAZpqpGE0AarMHVcvFh6vXoPiiAGfX7AGbneNrIrg6Xo+/ywOmSR9Un1D317SjjgC3lF3v4R5XQ+UaHDq6Cs0H1GcAmktXobZ+iYv5ozMAbaY7XIQgDfZtpbdx9z9jBFuBCAlIqANAAnja6kNFktguauqQuKWDBv504DJ1CFnuZGiTh1Z0bx9X7AhvaP0ggZx7x03uazsyR7lISVfMCAb4nHYTV8wIuGJ4OMshcMRc4LfRBPcL23Ta9T0BUZ5CzKfouYnfFXqF24YjbAGKHoKKrbP8FqAdHYK/yzAL/rn/E8Hf3B07Cr3Gk/CGrnjjrIzufaiMX2bnxAYKEAnquedDrOz8pec0bU8jaFreeewyTgrxpK7dAVqAkm5jkr1nltviYyuegbZMdS2PNtMdsFYvQH3FHFirF8BqRrGv2rolrAAIZoQaK3D3n3d9sdfjkG368XtgWNfmYzB8AGln7uF8U4sHQvW/Ufj1wf8Ddt/4CqSuygQUicBi9XEPE0fMuoUaKXKdAGujB/bfxMA//6oP6u3KjZN6O1YfCrsxCbDXepiGQe0WPzSVrWk6AJptOtMSAM00UzFGAQr/EvkQ2jgwVnzBCzWRnIEyEQUoAMXHvJVQggS4u9xBMQWIN2RXu8UP5cc9fApQGMH4iShA1Qt8TGDIIzbway+aZlUAivd0ZI1zhw+twQ9ZsC9v+VEETmnDYvQiHQCWtwiR9htHxoh4IFS2808DPPkMgHPvgFhHIG2Y//xBD8jQKH8YVrQWUZrqfovuZbCFdIoHdYPcQpTnxx3yteheAVvoCbDoXwlw7HxUpzH8+6o+xICmCwZtHyDGUzAE7DD28f+uwQ/hSaSJS8syRj5l7TYbdADI+SEcIE4dks4pej7S+0TDx8EETyo4z/FcDoQBFfgLp4RDwLaSGWwTKptlSt51lfMsAaiN4AwBb/FDeSf/+kKvm3uS1BGou1OewpELQ+DWf13VH5X3XAhXyB3E9h+ev6AXldvV/HVO9PPADtUFWgVAs81luk/7ADTT7LNoH0UHoOSsV4i7E3H+0+94xToAk2KcnWlSjLMTHVdl+5pQB6C2fkmoAxAIIVhfPosVgJIZ+PC9dJwDILv/jtxbYo4/aZGwF0yCI2scbv7dUTYPQFsohNhGGac968UZSRSM9OcHRD7SVp4912HvH64od36Tb/DX63+C6MUAxybyC3GVO7vEKM5AqM4A/k+C+bRHnPpEqM4owy9VfR8JAxpI2yHA3/xnITu4ehnRob9iLP/1iSDt5w94LpKZE0fGCNieXGcDwQH1LFIGBefaM7Je4A/wPrMXiPU4rNULYCuegbqqBfjwvXSorV8CixXngszOZe71wRT0DCpc/OuLyfAMii96ITn0HVV/Stjb8DC7iPs/Cd31a/7GSIwf2yp5AokfQQeg5Ax/U6ck4kugJQCabSbTfdoHoJlmn0WTdAA4FYAtRAeAVwGI8gs5/yJcXfU2P+QMiysApmkf1HzMCkCFa01YARDqAIQ9BlvpbT4mMOQRY/7biskMQOEUC+hFO5MUX8h0AGgLD6UAkSFh4c4pHRKm7ReyGQIUfRLs4BOxL2fSNdZyJBcCQ6SkuPrA9dMKgGCXX4S7tEee4e6yB97hD4Dq1N8XP7feJRb6ir0oqADcx114gZiXWAgsXVg1ccT3BqzqiCoI/x97bx4UV37eezeL2BFCEgxi0MbSjdhBLGLrDbpPSwgt0EhoH0kjBNpA7CAEArHT3ddxnPgmSq4zU/H4zc11MjOS4K2bvFa9TuKU7diZZBjP3LpxXLGdO4n/SapSyWtXXeV5/3h+z++cA+f3Y6yJrybkPFVdQP/6LE13n37Wz/dZnFVcAYj9M+NWMBouzrgj3nfkE1BSruuHy9eoTG+khyFblwmBubc8BSVnQJzhZ59RsZbHMjTUYQuQyzULDXXT0FA3jW1BYX6sAIowoHErcOi0vAJQ0hmEpqjfN1w/Ev378FHKLuFrklD84Ytz/iNXoeS6JPESsQrlF8VJnX1hb4MZAJi2mczysk/ANNM+i8Z1AEqNe5d9dqT/iHrtPZ4ANApmAJwnsIdfVIp2tOB6/Rnj9UZFLmnfqEhmAKqR/CPC9B0vWYC65kU4XmTc49tim4GGumk4KZoB2DuF/f7FY3wGQDt0qOSPgv9VYzxhW+ooPoa1+/Ah3vxRVQlY0vvMBzu15BU2EExYT+m2ROohJy2zTy8Ate+uuN88mfq6BTMGyYPYr548KOxnF84HRN3CIduIG8brEZ18wFe0TkO6huvxd8Eff1c4XyA9dvxdNp9gPCvjTxoAZWcH+BP7hf+X6uQp4QxA187T4hmA+LvS/2lbMg7binrp27YPy2cAXg1wR5/eBzRf4su4g/MFomMThUhD/aFWNvpd+F5JGcUZANH7gZGApDMAtiHxDABhQgWoT/++KSR81U1z+pfLNQtuu0oBEs0INVcsQl3zIjRVG19fGnxI1vnCnlOG61/Yewqe5JXCe5aidetRYf8f7L75hjwxMiZvjSy8I18vvyQWd8R2UDMAMG3zmBkAmGaagXEMqNIHR2oZBSh8FZxxK3wAuOwq8vZ9dpXFb09cAfeRAJR2BHXDZraIVbAnrYCbiYBZHyChwu7X4+wcLejc28ZCkD2rUoD4emuA40LX6gw4EhClV9qB5+VtJAoQrh2uX4KqMwGOAD1So+oAuGKQ4uFsnAOHMg/2wwt6HYDoZeT8V02Cp+IBGwTW6AAwxKBScA88lYgE9VROcgQotf8otiHwFo+Bf/ckuCM1+MJdiA3VEk68hWO64Ukt4lPFNr7PKED31PWMO+ocAAUE1Lqxv1dFRhLyMXmQzwrwCgBrHdK1frB2jrbtwxrso4bcwvYhxEIyqgzScFRkJQ0IKynX9ajMsHe5A+6JOst5+zoUJ5F6iOTDKD+0TpQfT8w58CZcAn/0bXCHvavuP7EPlNQu8MaeR8IQW3OFvQv+6NvgjT2PiNGtl8Ef2w0u3bb9nE6kpFwHf1wPuMM160kDSPlJuc4Hgfl6+GMMHnZ2IAY0eZpRgL6HFKAtTdCZ3AbKzg4kJ+kQoo/xvNNu8JkNoiPRa+JP7Edl5/RbGJgx8hN/zQjzmdkHXa9egEcxzSoFKPZPoSYjqM6PaClAVJEiKtS+u0h9on2HP8YBYKoiaYfKtQEp05vgeFLN54ACXSV3GPyvjjO9C1WzgrC2St4IpwDx7fdOqmjdvBHw753inzP6jBKZq6FuWqfH4Yp6Cv4szPZ7KifB2TDHM//OhjmOBnbXT4PDMwfHi+fV60c06ojUHVuEQ6eRpHOkbkl3/fHZA4jYvBaE1jMoVNhueQuKLO9Bu+Ut+GbEQWg92wctF/vgXyK3wHuWIr7eFvZ/gf1UALJnguA8IQYv2O4jIlQ4I9ATggaf8brixOBElDyxF5kzAKZtLjMDANNMMzAKAEo8fVDTusT5/4SJO3RKDQLKriAOtKQzCEU3Q4gAvYvEieIbQcgbxPuKbiGjOnMhCLn3mB7AeAhZ//dDkD0ThPx+JFlkzyIGNGsuCDlTiLYjPQDbOAYPhd2oDZA3gNsUduMxy64i0q7kOt4OnQ5A+SUmaEO8/+ZFqDyHuD76cq8/ugAOBVGgdt88Iv8acY2QgA110zgQyJyExuop8JRNcAEwunH+P5sFUGxD2N6TO8zJQKQN4C3RIEAZ+pPrBLBhYF1VgFoqNO1BXDHYNsQdfY4N3dOjowhpnTcl7QZiHVO7VHY7OW+azC/hJnkgoNUOSL+lDneyzDAfJtYMjPK/qdKQfovjPwmVqSRdASX5KniizoI39ryK2dSw/Pnv4W38J2E++WMYFpTvJ+Yc37eSch28Wy/jMYnTn3SFO+P8lnxV3Sb5KngTLqlrzOnnDn7aDc70J7QnOf7kiCupXaqmQcp1fGxqF388b8FKv4X3MedftB96HLVnKaldKqaTAjktj1/7erE2HF9mn247PrSrff207wMm6OXL7FNxnTQ3Qi0+dKPj0/FonYIA0rzIRQLVOoQt6VjQ+17zeMU2pN4Ir0uBds4A1wFQrIPq567kPg7lE6aXBeje4jForJ7imh+NVZPQWIUBAH3u3c4ZPgPgUObBoaBWiEOZh/ojC1B7chGq25ag9sQi1xupakcBrcqzDK15KcgFFMuuBKH9eB+sZJXARzt2wbK1FPztfRzbefxqHzzJK4WPUnbB0wOlcPK1Ps75t40xfPJWTIzUb0M8cu4oXgdt91UKEE/KHFcTJ0W3Q+B1awQU41dAcQT4tbzsahCOVC+BQ5P0OVKzBAXNJgXItM1lZgBgmmkGpq0ANB1a4jxr+jKouICs/6ozAfC6A1wnwJGwAt5GpEkU3QzpcXVbV6DhMPsiGkDnnZR+CWfnaA3w4CB7Jqhf37oC9jaGs7uNX2buJhVnZ2cqxAV3Q1DaEQSPR0XZOeIxA1d5DrNcNS2oA+DScLxPFMxDfdMC1J5AFOhaHYAW2yxvC2isngJ/1rSqAxC9DP69GAyQFgDRf7QCYN5SzHD601W+uWvLU65uSvx/ynBq2f/cecrsQ356hKoD4N81riIXyZnTOmGagEGvA4AZWyXthuocam46AShqA2LiTOr2g7qgoS11VKMT8FhVlGUCYzqdgPB3EZXJHGt/XI+O4++PuKFz6I1Y/drgANfZ9mHvgD/6Nnfgaf+cpx+mYfFvv6bn9GuFvJhTj6x9Dcc/rkd15JOvGnD++3SBAFU+dOu8AjAF2Vv+SNUB2NIEXSntPFjQc/5RCIwHDaQToOX8bx/mQYJvT49+nbQbWEDQlX4eHkUdZRWAjyA76o9V8bb0W/pZEFL0ZQGGYh1k+zbQlaBMv7YKQMEre492pV9ADYLwr0Jm+EeoQfBqgAcFXCcg7ANV8ZqCXeug5nPEhL4y2MA9E9nz78YMv1arQ7ENYeBergqBoQ7AMmJ+najo3WKbVdeil6E1B1uAHB5UCz9WtqDTAWg6hE5/XfMiVJ4N8MqplV1/FEeAc/cLu0PgbSAnnGmkHMPqZ9EtdPLzhlS+f9Y8inhlz6AOgL19zXXxFFZWbeN4XbS36a+L7qYAJkmY0FjD4YBOu+VwvSpSdvByEBRngAUAeO5H6pZMITDTNp2ZAYBpphkYBQCOAuMZgMP1S1B0MwSKQ9CH7w1AoyIoJbcFIHs2CO5mwfop/LISlbLdTQHIeRgUzgB4GwPg8RivNW0wA3CsZAHsvnk4VrYgXHe5ZsU6AHunuMqop3wCFOsgZh0LMdOo2IbAv8t4BsC/a1yX6Vdyh1WHiwUH0t7ntLH11QHN376sfnE/ODltFCwwZ19XAdh3V9zzvX0YfLtuSvrRh3jLh/EMQK+QpU9tPhtx/v0Rxuv+mG7m4AtY/EkDUk4/tfeIzptal4Tbp3aJ15MGoDp5Wq4DIDi3tm3YiiNcZ4GXiNXvTxqArlfOimcA0pf4e0cXAGiUosU6AINqwEpDw1Q5YBWCrtQzxscO+xlU7wmJZwRSsZVOqCPAggB/xgPBZxRb9ETrJ23iz3erpQPqmxaEOgDHShfAfngBjtQYX18URwCKboWE1yf3UUyAFNxVs/m5o/gz5yEKgNUJ9FHsflQDtreJr5tFt8UtQN6GAJRdCcKRWuNzN1uATNtsZgYApplmYJwCFPVFMBwYi2c6AALahT1xRUjpsW9dgbwhOeUnezoI9dvkFCEZzk50bGfsCtS0SChAMctY3hdQPlxRy0gHkegANNQ85K0GBe/gLACnAhWOSXUAeKDA+qD3/uoSVgWoxUHCP3dHPlGz/1n94Gyc07ffyCg9EY/VzD9rGXIo8+sUYKWUn313pUQaGQ3HFSZj8b+zIecf1yUknqQrUha/lLSTch3cYZL1tBvSfT//OBvaX/2vwu2lOgBxVvn/fNdNqQ6AlNQT8QSexeaIKUAx38Z2nNQu/fuA2n82okqxihCvaFE1iwUVzxJyxcdO/HM5BShnQE7TKh0Ht4QCpOSPiilB0ctiQpDlbWwLFFGAYpfh0Cnx9cWRsAKlHUGxBkoiXttI0Cu/PwRZc9gymXsPZ6eE18UkpKMJ6WuJSFcTXjfj5dou5hCwaZvNLC/7BEwz7bNon0QHoOzKC+oARKxC1nxQjLOLXAXbfYkOQOQq5I6+oA5A+CpUngtIdQDqjyxI193103LGeOk4VgHKJ2DsL4+jQ583gq1BG2gIKHkj3NFXcodh6QMvbwuivmYx//x9nnFVcodhz28sgG9Pj+p47bsr35ZmA1jAsP+tGZX+wtpJPg1z3re7+4VZ/J4t7fL1mHNyXn7K9RfXINh+7VNpFDz/OBsKo/9SuJ4Q+Sl0ADbQGNjoNfvrLTvFOgCRP+aZfl0rGFGmZLoS9F6kPv6cATj8/97mrTu+zD6pBkFC1N/KOf/WQennyFM5ueFnVLgevipes7wPbvuMdNvaE4tSHYDSDjmKs+AuZvzzBkKw59cW4fnH2ZDfh6092dNy/RTrhPy6WHhHsh6OmFDRuZsYUNM2m1le9gmYZtpn0TbUAaBskSiblCjRAUhcgdxRSaYqCSsAwgpBolxJ2JEo1wGoaV0SK3nGbqADEEU6AJIKQN00H/7lWgBsIFjJG5FnNml4seCe2vpD2f/cYWTpy/jp5JzRYDAN/bJBXSkznoY5adhXO/zJHEHp9jIl4AhSAhar+b6wGm/YO+CNvyjJ0r8LyvZrG1QAxBoESmqXlOO/oRpvynVphWFDHQDh//SJPMNP5ybJ0kuVgBO+u04RWskZ4EGikjMgVymm4JMGxPf0cD0LxTYkP/anrQBIKm2uKFQKFmb5o5fFFUDL22A/vCBVApZVGB0JK1DYLc7C27euoLM/gP3/2dNBaAzzg/UBZv+l10XSV5FcNw+MSK6b8QwDalYATPsPYpaXfQKmmfZZNAoA6srEMwBlV4NC1r+7KQDuo2Ic3YERsWS9owVxd/WCXldHCw4SC3F4RwLgbTBeO1yPg3oiTjcNAjcfXDTuD85DRdAW24xxf3HmFA4Al45jG1DJfWzrYUrA3tJx8O+V8MlJ9XffXd76oyWvKLnDwt7lttRR/WOtg3xQkzKxMia8rv+fDWzqWj/29Ih7vtnQqXD/2wbkvfQRncIefhr0Fc0A+KNvM9a+gMXPhm1lvfTSbdmAr+F6XI+U808zAEL9g9huqN4xI5gBKIPO5DapxgAiPiVzGRl3xK9J6ih0pbSLZwBeWVinBKxYB1VS0J4e8fNOH1epQ/S+IqwoDR+/ekE8A7D3P4k1K1JHpZ8Df/o4eMomwJ8xYfx+ykKVX3/mlPFnPHdOqBHQaukAZ+McHK00vn40VS9BddsSHBFcX9xNSNsRoTbdxwJgfcBagEZxALigF4OBrDmkotlPiWenrA/ks1MFd0PgPiKeASi5jgPAhvsvNmcATNtcZgYApplmYBQAFHv64Ggl41lHrIIjbgWOViwh0u4K4+27A3zdnrgCjV4cdCu6zShAieqai+Hockexp1WnA5C0AvVnkGaRPRtEHYA2/bpu+9EQuJsD4Ehk64kr4PEGIL8PKUCNXvW8HPEqvaimFfUAfPYA53g741bgaCUOCNcfWQCXe3adDsDJvDmO/PRUTiJDPHpZZYjvnQJPxQO+7i1FwSFCDdLvSt4Ip5MQv7wtZRQFv7L6OT2I40CpBUiDS0QdAMZeJ346wygqtiGeoeUVAcra2oYYt13l9JOwEtcOoDYgrQIsEVx2dzMCkcqkJ+eeiDHIdl+/riRdQd5+BJJ6OMvfch0RnuFt6zj//giV8uPZ0g7+iBvqtmHv4oAv4Td3djBevoa1Tzx8htMkko/K8u/lWM91nP7EXsSApnbhIG9cj4bFzzj/KddBSb6qsvpJJyDiMR8gJsyp/tzehbbkQY4Trd42Bdlb/phRgL4Kj2KakQLE8J9ETtJqJ3DkKtd2eMKPrROF23eXk5l02g2cxHMeSTxaHYD0JR0uVhcArEHK8vcTvZdJY4C212gA8IoAI1Z17rkEj+KO47HDP4Ts2G9ATUaQVwlUnQCNDgC1w1kHwZ/xQK8DsBvnbQj9qdUJIAqQt3CM43r9+3CeBz/DSPJyO2fAUzkJJwrm1c939DKcyJ/jFKBq/5JOB8AZswxHqlWdkar2gKpDokFtFvTgtanoFgohOhJUjRPnyQDk92OrT8Fd5vg/wOHf7Nkg5DxEAlDWfBAcrSoGlOhotvsYMOSOqnQ1ui66jyJYoeg2oph1GFBGbjt4OahqqDiJ7LYKzlikABV7zQDAtM1lZgBgmmkGxjGgvn7k57fhl1vl2QAcfC0IVe34s+xKkHOuSfyr+EYQCnrwyya/nyE7B9hQWx9+sR0YwS+3rLkgHBhRB93yBhFllzUXBOskI2Ew/r91An/mDeH2hd3q/YXdeNzSjiAU9DLeNdMEKLvCgpWLqGVQdSYAh06jJkB1G97qjywgz/sEagDUNy1w0R8S/nE2IiLQXY9iQQ1101wbgH56C8dw6DdvRG3/YUhQXgVgmEKqDHhL7qts84J7XMSIAgIt91zrPPE2H2KlawOA9Fv8dyWXISGz+lUWu5bLTqhQjUNJFYN1QmA0ZEwsf2oxogCBKDGkMZB+izP0vbHnwRt7XsfzJ7ynId9f+7gt7eCJOYdc/4RLenb+zg7V0SZNAbqPOdCcwU83wneym463T3z/1C4MLujx2v2u1Qyg+5OuqOdC99Px2XEI3ans7MA2Ga0eQMp1VQ9Ay9Cn+3bdVF8nNqBLAm2+3d0qv5+y7VrtBu1rmNXPAzauE8FIPTxwpNdVGwjSEC+RgEgDQqszQO8zFnCu06FgAmEU0Pr29+LjaD6Afmo1AJgitmIbAt++u6pIHvtMkGaGt+Q+NFZN4meMIXh5NY7N5nhLx1HLo/Yh0roqJ8HlnsWWvYoH/LPdWD2Fn31lHlxu1AJpDPND/REk/dh98+BsmINDpzBxUN2GAoM1rUtQ7V+Csivqtab8EmqSlL6uaqaQXgq1/BwYUXVOrBMhyJnCnweGsQKQuRiEfZ8LQOZSEFuCWFUgcxF1VGz38dpIegD5fez3Edx/QS/+LO3AYxd34XmUXkOnv/wi/l15LgAlnXju1W1LUH4Rfy/ymRhQ0zaXmQGAaaYZmFYH4NDpAFScR4Y+OdAVFzAYKH09CMVdeDt4Gb/gim7jl0vRbWRak4hXQS/+tI2pjr1tDDNcOVMq6s46iV9cFARkzwbxS5D1wdruqyXygl780itoLwnPAAAgAElEQVS6jXzrotvq74XdISi/FOQiPJVnUfir8mwADp1a4l/Yh07hFzY5/rUnNUJgDagM7GyYwyCgYQ7c9hnwlE3w4IDEwAj/yZ2L8gne9kNVAG/hGN6vqQZwoS9y8snpZ/MANETJ24Pob3L6Wc8/fyzbB28H0oo3kdNPXHbKzmpFozQCTtzx095Pzj0FA5Tp1eAhKTPu3XpZ5/iToi//qWH464IA+p2JfHHHX+t8k8OsEcTijjo5+uTIk3gXcflJVEsr7EWOPu1DK9a11pmnGz2GflIAQOfA9udLv6Vz/HXnq3H8ydHXiX6lXEenn35n/19t4MaDhbVCYBTMEQ6WXmOtOJg2SKDHkIov25+uAkDHYT39uoCQggNtUMBUf7nYF7uPY2o1egF8YJ0UsImApa2GWQfVQJnE8kgEjP30lE2oKN68ER6Ik5NPwn30OfZUPECV78pJcNtnuDAYqQGTOjgJgdUfQTFBUhWnBAldS2pPLEL5pSBUXAhw8S+6VlJigoQTi25h8iK/P8SFwHLv4bVxfwCvgZQEyVoIgm0sBPVnA1C/bQWskaifYj+FaGTbOAYG7ia9ToDreADyhnD/ZVeD0KioOgFUAai4EIDyixgANPhIRR01Do7ULEGRYlYATNtcZgYApplmYNoWoKp2zGJVncFM/8HL+OVVdpU51iwwIGXgwjv4JXNgGCsAeUOY6SrsDnFHPvcey94/wC+13Hss6/UwyCkYmUtBpFpMhLgK5oERTQVhQm0Fyu/H+4pvBFFMhwUBJLxTdpV98V5BFeOqdvzCq/Yv8b/rj2BWT1sBsPtQ8dNdPw1u5ww6BLUPwW2fwfvtTCG49iFmFzUZf8o2ktOvrQLwAEDjtCi5w7w64MvsU6sA5LyTM7+/V68RkDeio61olVa14mFKzoBeGZYyseSIkRNJDqG2AqBR7dXRgqhyQJlocnKZ2q4n5pzeydeo9moDgLWKv54t7VzB1xt/EZ1kllXnDu6eHlUVl1UCuGLxrpuq4i5l5LUZfq3DrQ0OtNUA2p6OTU69JqPPnX9Nm5HusRSAaKoOusfR/5T+vxpxLy62xf63umw/Of1UGSBxLnLO6b1ArxEFABSg0ZrmPv7eoN81gQB/H1BgsL9XfS9Qhn93Nzr4VIXQin5RNj93mL9HdSJ3FACw9zKp+RLSVim4p27PgmNv4RjP+tONPkdKwT2u9EuBgLcYq3PewjFU8i6f4J9RUgb2VE7yzzcFAw4Pzv2QErD98AI4G1EMrP4oJgxqWpfg0GlMkvCEyVn8u+JCgCdGCrtVpXRKWJCiOSVFiP9PmX9SRM9cDHJxRJEOgG08BK7j4vmC/D4UATOcAXDLdQCcBb1mAGDapjIzADDNNAPTBgCHTi3B84+zIXMhyMvBpdeC/FZ0OwTPP86GgrvoYNMXGy9vD+H6gWEsaxf0MAeetfgcGMF162QIMhfQ6c9aCELWAva+Zs0H4fnH2TgENx9EhcwJtcz9/ONsyH/nPhTewX0X9IR4ib3oJq6XdgShum2JZ7kqzuMsAD23ynMB3gpU14xzABQAPP84G50A1yy2A1BAUD+NrQFfu6tmEJkSsKccKwHPP87mjomn4oHq8OcOg7fkPjz7QTY6M4z97ymfULOc+aPw6x/VqUEAc6bIcWqsQtQoz6CuYa3v/cISHxzmzhyRWbL6Ye8bc7pAQUnt0lUC9n9lWl8B0FYP9vdCYXeIO5g6hzf5KnjjL4I34RLP9Gtbe3gFgLX/rKsCRJ0F366b4N16GTPq5ERrWn5KOoNqBp5l071bL3NHuuJCQM2yb7+md7Az7uiChbWZfE/5hN7xp4x+0hXwpd+C6rYl3vevJF1RAxAWMNQdW8RjUOZeUzngDjo7HwpmeCBA56Q919Qutd1nrWNPQRvLurvcs7rXiY5B9yn5o7yNiO+DXls6N41qs2EAoA0q6Ph7eqDifEBtEdIO/bL3rcs1y/G2NAugo1yxahavbpGznzsMdt88fo5oe6oCsPXS14NqEM2oW97Sce78l18KgmIb0mlyeMqwLaihBh1+Cubd9dP8s+62z3Dn3+HBGYDaE4tQ37QA9U0LvEWm/ugCb5GsbluCynNq28+B4RCUXsPESX4/JiwK77DrYz9De06q7T90o6qobQyroXlD+FNIT9u6ggKKEkpQQa9cB6D8okkBMu0/jpkBgGmmGRgFAIWH+6H2xCIvcVdcwGx/+UX8Qqu4EOC99yWdrM/1WpB/uRXeQSc8v09t2+F9rqydx3Yf/85cwgxXzkPMeFE7UPZMEHJHWXvQhFouPzCCzn5hN2srGmFZ/y4stxf0hniPK30B03MovxTkX9j1TQtQcSEAdc2LmNVj8wAUALjtM2olwDnDnQVt6wC1/TTUTXPHwlPxQK0GUEtCxQN1KLjgHh/49WX1cxEwb8l93eCvkjeCzhw5RKwVwltyX+2l1mT5edtE3oguu6rDMWoz+Brqj66tJ6tfHwBQmwdljJmDqc34e+Mv8qy/1vnXOvu6+zXBAFUAvLHnda05WieX/00OsbafntpnUq7zjDl/jDYrv6btR1cFoMw8BR2aliCeuc8Z0M8YaOYMfOm3MDPNnH4KBHQtQ5oKBM/ar8nq66ox9DcjQ3GxNmq50TjzNa1LvAefz32QM767GwMEyvxTpUc7M0CPp4BxLQWIqkXaitSeHlCsg+BQ5vXrrG2MglJPGbbE6dSpWfDJ1/b0qEPs1kGuaVF2JYifh4J7aisQ9f/nDEDWfJC32JHzrw22s//rlK4tiGYFPJWTar+/5nPtts9AQ+1DqG9agOIbQX4doApA/dEFnCNqW4KL37wMVe0BqD2xyCuLNa1L/Dr0/ONsXhWlimThnRBn+z//OBsOjODftjGG+5xlM1AjIaj8v4cwSGAtkFL9lHG5DkB+X0iq3VJyXaztsi/c1AEwbXOZGQCYZpqBUQBQ4unDAMCPJW7KnpddDfIZABquLbsS5L3/+X0hOHgZ224o65U3iPMA5LzbxjRS9+PsS4+xrq0PMAOWPR2EzIUg/z17Blt8KJCgfeYNYi8ttRoV38Av2dJrGJyUvo7BCpXkK8+qX9iVZwNI/2FZvbrmRag9uci/7F3uWQwA3LM6Z4Gyh7xloHwCB4HJ4S9H5d+Gmod8MNFTNqEOJxIelPr9SQNgTd8zbxXS0n20Dr+GrMJbK9gMgK4liOYDqDeclFrJaaM+f3LQdt3UD3+y1g7emkKOcsp13q7DnXtq9THI8OvWtDMBMefAE3OOU30o2OBOusbh52vaAV9q62EzAeuGbo16+7WDwdoAgBx6ytAnX1UHddnzXpvd1+1z7U9tEKDdBwsqKABY2w6kmwegYIH+B3QfteBQ8KYNCui11yI46TGaas66dc08gS+zb/0sCLX2UDBJMyfa4JJmTzRzIjrELRvo5RWo/FH1fUkBJtPO4J8N1t7jLRzD93/BPfx8sAF6aqHjGhwUUNN9rNXHWzzGK3Xe0nHewuepnMQqABv2p+Ffl3uWBwD1RxEW4PDMQf1RTBZUtWOLJLUUVp7Fa2XRTRVOUHIdr40Fvez61I3XwoIe9ZqYN6S2AeWO4vUxeyaI18QJVgGQcP5tYxJ9la0rUHRLrgNQ1R4QVggqor9oBgCmbSozAwDTTDMw3gLkxRagynP45Ual7Wr/Enf8+XDb7RD2ut7CL7SSziB38Avuql9uRl9yRL6gn/RlRySM3FFGxWBtQxQM2MZU8kXeAH6Z0hxAQS+eT2kHBi1Ft0OcYkQDwOUXkWhU3bbES/vVbUt84K+ueRGHgBtx+JdIQC73LHf8G2oeIj2k5iEPCsiZ8BaOcQVgHRGIKgA0HMxagMhZ4b9TuwORgVgLhK5PmoYsaSiTBJc07UDarL3O+dOSYWhegFo7tPQXyjqzXnNyaCnr742/qJJ6jPr61/T8r60GUMuQbsCWnFuWDacBWE7CoZYacoSpOqENEij7r3XOKdtv1MOvfYx2sJcChOSr6wZ6+TlQZp+CI23fv6ZfX9fyQ61CdM6aIIA/b+2cg7bPn7L02mFubXuOFgFLf2tuFFDy94/Wqaff17YAaZSitYGFEXJWi//Uvre4vsWa/n/dOrUGUasQq3IpBffUKgAbnqfPCbXaaWcB+OePYXhpTofagBpqcFifPs/U7uN24iCwyzULLtcs1B9d4GCA2hOYIKDef0oiVFwIcKhA2dUgT45QwqSwW4UTFN3SXLeG8G/bGLY+auebrA9Uks/+UACyFoJg94v1UQ6MiGcAGg4jnrlRMV732TFBcrjeeAbA1AEwbbOZGQCYZpqB8QpAIw4B155c5JlzqgRUnsVZgOq2JSi6hdn28ots4JZluopuqcO4NBBsfYDOetZ8kJMrKCAg9cvsGez3p8HfA8OYCcuZUpGiFExQT23eAKsC9DCaBkOQHryMAUrZFQxYqv1LUHFexfNVnA9wlF/tiUU+B9AY5ofak4vgds6AQ5nnOECHMo/3eeZ4xpCy/I1VkzzLSCQRnoEkLKh2YJHafCjzzzKcnG7Chh856Sd3WO3jZ8PA1C+tG/olZ4ycLK1Tp6HCKDkDepSjxuH27enRC4FpB0+1Wf+Yc4YUHxndhwcJMefW9drzthciC2naY7TDs+uGaddk77mzTs9nd/d6GhA539pgQFNN0AUPbF1XjdAGC9qB4+SrutkIHsAQeYiqFZqWH107EQU01Juv7ffX9vavbR8ilKeG0kRDwr70W1wcjs8I5A6rgQW9/lqcKHtf8PcBVZYYplPruHPROXrvZfap6No18yfagXaiA/GWHnq/s+2V3OH1xCxWRaM2t7VULSJt8bY7Gvxln8GGWgzaSdfD7ZyBhrpp/pMH/QwD6vAgDawxzM+rhFQprD25yJHCdccWofJcAOqPLkD5JQwCDl5Wq6OFd9g1qhevTbmjKpufqpo5Uyrxh9oeMxdwCNj6AAMFR4uqj1KftAJ2fwCyp3FOIOchBgn2RFUnwN2MImB5A3gtblT0OgAeT4AjnSvPBkBxEAUIdQCaqk0KkGmbz8wAwDTTDIwCgDLHXWguWwRnLEPCxa3AkVoscZdc1wiBEVIuHoXASq9h+dvbqOLm7ImIm6Osf+69ELiPanB1DGdHFYGsuSDUnccvOr7uD+Aw8AJWF9zH9bg754kAFPRiQNBwmIR48Ly8DUjnqDqjZrqccYS6W4FjZQu8ClB7YhFVP2OXwRb+ARcCo1Ygt3MG/FkPwRW9DLawD8AV9RRas6ZBKbjHCSKEBF3n+OeNoIjYlqdgC/tAFTBiuEIld5gzz3VoUKbCqlgHoXrv5yAt8T1IiPpfkBb3Haje+znVySfHihx/1vLBW300jpcuY6xt/1jb+qEdlk2+qjr/a+g9skBAVxnQtvusJeKQ06/NWmuGVHXOvsZp59uRk61l7a/J/OsIQJr+f57dX4vqXDNArAs0KMtP/yMNwUfbuqOrSmgDgzXnrgtatPdr2Ps6IhAFb/S6aXGu2gCC/o/UrkOBgFb8TUv1ofYw7ftA2y5Ex9ToUWipU9oAQrvG24DImddUA6gtSKdrQYO/FAAQLYuCZxr8LRzjlQHtDICn4oEalFdhz7/LNcs/m43VU+j8M32PxqpJPg/g8KgVPx0GlLUB1TUv8qRI1Rk2H3UpCIdOo0Nd0olBQH5fiLcAFd3GlkXO52fggvw+tQpKM1J0raQh4f0hzPLn92sqow+xRSh7FueeqBpKpDXbGFYdSjrZ8W/ijeakyq7gXELFBZVgVNOK1d6aFiZu1roEJY1mAGDa5jIzADDNNAOjAMBe3GdYDj5St4QkFoFsvMcTAHeTWJLedj8kLGXb25BpLcTdncYvQfspsaS9u1mMuit9PQiKw3j9WBkO+B0vnjdcP5mLrUAtthnDdX/WQz4YTFUBGnCk4WD/3injbTMm1g36aln/RE+p3vufIMLyU932EZafQnXW57lTpWvnIaefZVVJRdgWtoqqsNsG1BYOjfCUbviTObzehEvgj7oFLsvbYLOscrVerZOPSr/r1ykA8EfeBFfYO2CzrKqqtszJ9Sf247lZVlHRdtuALruNSr6P1fXkIZ2T3ZY8CO7wdzXrg7rgRbce/i744++qSr+J/bp9c6VfFgz4E3s122oUjlk2H7dX10kJmJx3f9IAuCMeq9tvH+YBQc3OWb0ScHQzdKWe4Rl/UvLFc3sCbTtGdEhXUszl6xqlX9+um+w1f6z/v7BgAJWAm5ka70eQHf0nqASsqTBoKUA8y89u/P1kYUrAqaO6IJI78TSrQlUE2xBuG8nei2sUrX37e7nSLw+U08fVz4VtaP16xoSutc6fMQGuKAy0XVuegj9rmgcE3pL74M+aBlcUC+KZ2m9DzUOw++bhZO4cBvgsAXCiACsAdccw64+JkWU1MVKDc1IVF1BvpKl6iWXZP+BZdgIVlHQyFr82eXEygNn/e0whfU1ihKoC1klVQZ22dbQGdEKK7ub1iZeiWyE+k+BtwAoAJW28bkQ8E9KZVNK1z63EYwYApm0uMwMA00wzMAoAEP1mPDBWcUE8MOZIWBEOm9kTVyBvSDyMZt+6Arb7IajfJlhPWoHsGckw3NYVIcrOGbsC5ZeCwvN2xi5DfdMCOGOXDddd0cuYQYwRr3NhMM2QITn/3sIxcG15arztlqdqS8PatiDW4qPkDkN27J8abp8d+w2dABg5Sr79vZyv7t913zD4aNsxomZpNUEAOX7erZfBE3UW/JE3jYOXiE5oDG+D1rBO4bon5hz4o28bHz95EPxJA4I1VJNtSx4yXt82AEraDWhLHjQ+dtIAc/B7jdcT+4X79if2g5J2A/zxd+XH3j4s3n5nB/gT+4XbV++YWRfQxVr+Gb5lKYOulHbx894xgkHPjhHj9e3YLtaWMir8v3altMO3LGXr1iMsP4WatEVeHdK1glFr2f5e8b5ZAMJbkbQtaKyC0JZ6z3jbVFTAFq37906Ckj8K/vRxwTqKfPn3GQfaLVYc4Betn7TNwknbrOFaq6UDalqW4HjJguH64XpUAPa6BcmPo8jiFyVHXMcDYG8TJD7aA5C5GBSuu5sxSHC0imcAyq4EwesyXlecOKtwpEagA3DA1AEwbXOZGQCY9m9m//RP/wTj4+OgKAokJyeDxWKBL33pS4aP/d73vgeKokB8fDwkJyfD+fPn4Sc/+cm6xz1//hwWFhZg3759EB0dDYWFhfDWW299qn1+EqMAYF/YO/xLQL0hMq7yXABs4WKknAxHV9ArwdVFrn5q3J1sreqM+Lxzw1eh7tiidN3lmgVbmHjdbZ/hVYDnH2erSFDWAiTcNmyVM9FJ4Osr//OgfhjSNgSZ4R8Zbp8Z9qGO8nL8j7rUfmrW3uGOeLxmO7y5Ix6r/eEsa1zQG+KOH2XvXZa3Dbd3Wd6Wr4e9A96tl8Ed/q7w+LJz82XcAXe4ZH3XTfF6OFsX7T/8sWTbd0HZfk26vtGxlbQb4I54Ijz3tLjvGK61W96CZ7E50ueN+5b8X3Z3S479BJ7F26Dd8pbhelrcd9YpAXNCD2sRku1b1xK0vxf2/MaCjkrljhRsG/kEfJl94n1HPsVWO8H2ri1PwVs6Dq4oQaAd9RQJP1HiIN4VLVizvA31R8UJAmfcCpRdFbP07YkrUHRTzOK3b12RJjay5iWJj6QVsE5IKECJTAdAcG6O+BWoOhMAZ5xJATLtP4ZZXvYJmLZ57Ac/+AFYLBbYs2cPOJ1OEAUAP/rRj2Dnzp2QlZUFv/RLvwQzMzOQnJwMxcXF8LOf/Uz32OHhYbBYLHDt2jX49V//dWhqagKLxQJf+cpXXnifn8R4BSD6i8Ivi/KL4kz6J6oAiL6oklgFQPJFmHtP/kUnzPDHrUDp6+IvaGfcCjg8c8IvQVf0Ms4BiByEqKeqAFHlpE4LgDCgIsfDHfkEhxkJD0q0EzboS0HB0fCvGm5/NPyr6nAw0YK0KMasfrCFrYJh8GF5Xx3wZeQbb+x5XQDg2dIONot4+8aI09J1JeW6dH2jcxNuG/Y++HbdlO5bur3lffl5p3bJ973BsZW0G9L1hIgfGa4VWd6D72/Z+eLPK2wVfOm3pNv/deQOKLT8heF6YtTfcuedBwBaAbDMPvlrQkO/9HjN0LBiHRS/3mGr4Nt3V7ruLR2XBtINNQ+l656yCem6cM3yPjgb5qSJj4OvBcXrkatQdHOD5IdkLWs+KE+M3JcnRko6g+L18FWoPCtOjuwPM3UATNtcZnnZJ2Da5rGf/vSn8PHHHwMAwLe//W0QBQBdXV0QGxsLf/M3f8Pv+4M/+AOwWCzwa7/2a/y+H//4x7Blyxa4efMmv+9f//Vfob6+HjIyMuB//+///XPv85MaBQDOAuO2icP1S3DwchCO1BmXi6UzAM0BKLwjxtU5WgKQPSsudTtaAphFE5S63cfFx/bZscdVhLprqlqC2pOLcCJ/znD9RME8uOun4WSu8XqLbQYZ45UoDMapIwwN6i25D/5MwQzArnE+JKzkDKgDwZqqgG9/LzyKO264/aOYY+tFlmhIkw1vyjLRpKbrjT0P3viL2NfPHD/q8X/RCgDPlIuOHy6rADyRZ/AjHoMv/ZY8C59yXV4BEK69u3HlJO3Gi1cfIh5DWuyfGa61W96CZzE5G1dGNlwXv+bSCkD8d/l7ic+CWAd1mhHS9xP1+5PGgTaY3aACIMvwuyOfgJI3Iq8AbNBq11g9Ja4QbFABsB9eELYAOuNW4OBr8gpA4Z0XrABs1PqYtAJ5AxLOf4K8+sB1AERKwGYFwLRNZpaXfQKmbU6TBQCpqanQ1ta27n6r1QoNDQ3871/5lV8Bi8UCH3zwge5xb731FlgsFvijP/qjn3ufn9QoACht6IXmCqIArYIzdhmaqpc45aK6bQm8Tj1SrlFBdeCS60Fo9Kpr9sQVcB8NQN4gYvAODIfAeQKH3WyRq2BPWgHX8QBH4mXPBsHRquLu7FuRApQ3iFSMvAE27LZVXXcdxwHjopu4tg51d1VVLfbZA4wCpH9edt881B1TKUC54avgil6G48XzqAjKqCAn8nFIMDdsFVxRy9BinVHxgqQLUDwGnvIJFA4ruc9VSP1Z0+De8hRyw1bBHfkU/LsnVYpJzgDHf5IAEu/ptw1BV/p5+JalDNotb0GR5T1ot7wF37KUQefeyyphRTtwqWHCC/uqE/uR7hN/kav2agMAqgBIe/yjzoI/4oawx1/ar548tGE/uayXHWcAxL3ySsp18CcaD7T7E/uFPfr+xD4cohXNFyT24XyBaH5h+zAoqV3S+YXq5CnBDEApdL1yVnjsthQctvWnjYlnADLuCOcT2naMSGcAqvd9jgeUuhkAGirP6he/Jqlr8LXU+kNkIDaMLtzWNiR8Xv50xH+K5ln8e6fAUz4hHrbfjRodLYI+/xbrDBwvMoYAtFo6oPJcAJoPLgoTDBUXAuAVwBHcxwNQ0COeAXA3B4RwBOeJAGTPBIWJE9dxnAEQwRE8XtRC8XjFMwAHXwvCkWqBDkCROQRs2uYyMwAw7RdiogDgxz/+MVgsFlhYWFi3zfnz52H79u3879dffx3i4+PhX//1X3WP+6u/+iuwWCzw+c9//ufe5yc1rRJwTcsSF86qOoOaAFVnkKFf08pEbxhGrvgG4j9LOlX2NWkAkAhOwV10/g8MI8c/bwDZ1ySAYxtH7nXWHOLtckfR4c95iL9nLqEeAImMkaBYfj86/gW97NYTgspzASjtQP522RX1nMovqgrBNS3o+NcdQ553TQuKgjWG+cHZgOhPZ+McNFZPQf2RBXC5UBnYfngB3M4ZVT20HlWCHZ65dQEAkUk8FQ+4qBdxy0mtlGNCSeSIxL9sQ1gBIEdqdzd0vXoBniUegO9HpcCzxAPQueeSjumv5AyoyEfCP+7vBcU6CG3JQ+COeAy5lveRhBPXg0JcsefXIz3XBAAUBLgsb0Ou5X1wWd6G1rBOjvX0br0M/vi74A5/l+2fkXoYsUZJ7WLEGnb8CEbDYYjPtuRBzdoT3JaIM+m3OM2Gb5syqkNYEsmHrycP6gS1/EkD6no4rhOyEwlEmm23Dag40PRb4E/sU59XhOZ5sf3juT/h6/7Efp06MRKINMcmwtHubqhJX4Ls6D9RKUAxx6Ar7dwayo/m3IgCxBz0df8X7VB3xh1o2zGiO7e2lFE+jNuVfgEeRTMKUNiHkB3zDaQAabQidC1A1Mqz6yYeO/Ue7jsMXzP/rvvqYwjvqdWt0GgBEAUol4hUbACYsJ/+jAl9oJw5herYJfdBsQ6CP32cb++Kegr+XePgKZ/gehz+vVPgYtsTqpcwn56KB0j6iWJBfPQytNiYIJhrFo4XzYMrZhls4avgilmG4yULXAeg9sQiHK1c4okRR/wKNB1a4kjQg6/hsC1iiDEB4W4KQN4Q4j7zBlGQS8fqZ8mPAyMhsLdpEh9JSPmxjaFGim1csx6B2zpaAmAbR4JQ0e0QOE+yfVPipRnpZ0W3Q1Dawc5tTXKk9FoQDp1agooLAThSu6QmRxgFqNRpDgGbtrnMDABM+4WYKACg+99888112wwMDIDFYoGf/vSnAADQ1NQEmZmZ6x73z//8z2CxWGB4ePjn3qeR/f3f/z2srq7qbm+/jf2epc5eaD64qPLy41AU5uBl5F2XXwoi7i5eowOg4JdN6euICSXcnD0Rv2jyBvFL8MDIetydoyXAvyBzHgbBfoqtR+J6/RlUw7SNodPv0ugAOBLxS7agBwOQBl9Ah+HzOgM8CCjpRFKHMw7XnXEr0FyBAYDdNw/1RxawAhDDMIAxqAPgbJzjgmAt1hkdQrA1Z0YVAqt4AA21D7k6sKd8gmf/iVDi5joAT8Gf8YCrAyu2IVXxlG4kDMY46eR02cI+QKcrbUwNEFjvNWesE0ee9WK37RhRcZdh74I/ppsr8jZGnOaqvUYtQI0Rp3kAgJjPd8Af0YkBxJinHw4AACAASURBVNbLiMtci7tMGUVuPWtF0iEpCQO6vxcz7WtxllonO+MO1OychbTYP4OEyB9DWtx3oOaVBVUNN/0Wd5S1KE/fnp41qM7HOpQntajUpM5DWsy3ISHiR5AW822oSZnTaQlU75iBtOhv4bGjvwU1O2dVXn/GHahOnsbtt/wtnturAVU/YNdNqEmZg7S476jnvnOWi4DVvLIAafHfxW1j/wyqd8yo/HwWIPD1uO+gg76nhwcXNanz+n2/GtApOvPt2Xp18rQ6zKvVHdBy+wnjmXFHDQBIX4DUhffdxX3HfQc1KeK/q74mtH/K+muVf/f3gmIbgup9n4O0pL/AbRO+C9XZX1CrXXkjUJ31eUjb+h4kRH8MaYl/DtVZv8wFvhCJ+zlI2/YXkBD9MbyS/JdQnflL6tB94RhUZ38B0hL/HBJi/w5e2bkKhwr+s14ErGoSxb9q0OknjYCGummcBWqcg9qTi+BsnIP6IxgAVPuXUAH4DOI+yy8Gof7oAlRcCPBrYtlVvB18Lcj5+4XdmNwouY4Jkfx+ldlPCQ3rAyaIOMH+ngjBvs+hyBdx/fMGmXr6GPt9TH08iYmR8jolXkquBzkCtKQTbwdfC/LrYflFRICWXwxywcfKs8j/rz2xCIdOLUGxiQE1bZOZGQCY9gsxUQDw9a9/HSwWC/zO7/zOum3u378PFosF/uEf/gEAANxuNxw4cGDd454/fw4WiwW6u7t/7n0a2cTEBFgsFsOb84DxDEBTNWa7mgTlYq87AA0+sQ5A3lAI3MckOgBTIag7L1g/FYD8fvEMgfOEeAaA9AsaFeP15opFqD+6AEcrjZ/XiXwMAE7mGc8A+Peiqqi3dBwaq6cQCaqtBlROQmvWtHgGoFgjcERVAsqastYeIf5w17hOkIlXD4juk9knbEVptVzXZ/7D29ZVAMj5Nzx29G3k7EtwmL6MO9I2Hinukjn/RvoHNelLGFiIWmWSBzG42GbcpuNPGoCa1Hnjfe+cBSW1S3js6h0zuJ4yJ15PuS7ePnkaqnfMQHjYz3Rr0ZZ/4ToBNRlB8fPe3Q01rywYrzOMZ036kvDcfPt7oeuVs6gDEK7RAXhlQRWR0wqBkSO/uxsU66DxvsN+xgMUErHjlQDC0loHoXpPCCLWPO+IsJ9BtfUL6r6N1rM+j8GD9QuG64fyfhW8xej8i9YpSD9pm1XF/KJZG1/dNDgb5niLHwoFLkNzGVYFSRzrSI0qJOiIXwGvC7PolBzx2TVChGsrAJr2RWukqgNgG0cHvu6cPjHiPhbgCum2caYErE2ctOJcVe4oVj/dxzWc/wRVnLH0dQw+PB713JxxK3C4Hp9TddsSFBx+A/amfxf2b/kf0LTl9+BXd52CC413TSVg0zadmQGAab8Q2ywVABEFyBmHFCBnrHigTDjolrgC+X1yClDuaEg+7DYo1xEQDsLFr0Bxl4QCFLsCNa1LwuflilkGl2tWSgFqqJvGNgTm/FMbkKdyEucBIo2HD2n4kYaAlfxRbB0qHOOCYIp1UDwcGfFEJ9TE5wCoVWRPjxDD6bK8jU4/u62tAFD7j8vyjuDYGyMnfem3pAOr4ueF+86O/hPD9eyoPwZfVv+LY0TDH4v3Hf0noGy/Jj22knZDur1v103Ijv2G8XrMN4RDwG2Wr0BXSrv83HIGxPuO/Qb49vSIt4/7U+jaeVqsA/BqYH0LEFUGmFOfHSfRpKBAgVp+aDtWGRBuG/enoOSPip9XwjdxPeGbxuuJ3wRv8RhkJX7LcD0r6VvgqXgALVZjMb8TBfNwokA8A1DdtiRMEHjd6Gj77ILkxEmmA3DUeL3+TADqzonXch4GhTMCjpYA5A2IEyM0m9UomAHw2QNQoLwBEeE/W7f2zfCD0HzoApgBgGmbySwv+wRM25z2bzUDEBcX91JnAGQ6AAcvS3B3Eatgk+Do8vs+pQ7A2IvrABTdDonPLXwVak/KdQDc9dPi9bBVVAGum4aGuml4/nE2NFYh/UfJHwVPuRw/SPMCSv4oKLnD8N//2qYLAHyZfVJEIe/733cXuv7sHO//V9JugLL92oYYT61ir5JyfV0LkBRJKUNOhq2Cb0/Pi6E4GRYyM0yufyA9t93d0vXMsA+F+1ZSu6Trvl03xeuWD8C3u1u6fcKWvzVcK7K8B8/irOLnHf4hKDkD8vW0G9JjyylA3+EtO7oAgILK/b0bnpvW4Q9+r1HXoibUswj/EJT8Ucn6R+AtHBOvR3wE3tJxyIz4H8L1xqpJcRC/AQXo0KklISbY8Ql0AAq7JcmPrStS/PFGAoj5fXIKUOEdsQ6AM24Ftu/90HCt3fIWPNppAzMAMG0zmeVln4Bpm9NkFKCUlBQhscftdvO/v/CFL4ARBejLX/4yWCwW+PrXv/5z7/OT2kY6AM64Faj2L4lFZRLFarz2RJbBl3wJ5g3JlYBt45L1REkFIGEFyq7IKgDLUHtiUfgF74xZBpd7VqwEHIXrHANaPsF7jT3lE9hrLMIPMnwhDQUrucP6CgBrpxDjEZ/q0Yusr15JvoqEn62XhRl8l+VtfQtQxGmkAa2tAIRJKgAyJGX4Y0Q/SioEUgzo/l6x/kHYVzesLvj290orAEfDRPv+b6Ck3YCjYf9NfOxdNyXbb7yeFv9dw7V2y1vw/aid4m3Dvwq+zD75sXd3S7f/6y07xToAW36Mjr42ACAKEGszk+17bQDAVar394JScE+uZ5E7LF33Fo/B0fDfM16P+D3wVDwQr4f/nlwnIHxVHOBb3oealiVp4qPsSlCcYIhcxR7/F9QByJ6R6wDkjsoTI6WvS5I24asQm/QTw7Uiy3uwHL8TzADAtM1klpd9AqZtTpMFAJ2dnRAbGws//OEP+X1/+Id/CBaLBb74xS/y+370ox8JdQBeffVVnQ7AJ93nJzWuA5AnngE4dGpJyNNXHAFhn737COLqRDMC9tOI8qy9IJCkP4H9sM4TglJ4awA8HuO1hsM4qOd1G68frUQKkGi24XjRPDg8c8IWgZN5c3yosKHmIR84bKib5urA/r2Txr3oaSgUpuSN8J9cB4B6p/NGhDMAbSmjaqtFxh1QUq7r0J4bYTy1/f98KJg5ft6tl0FJvipEaRKNR9jHnzwEvj09QgyoP2lAOh/gy+yDR9HNhuuPtjThvkW4S0KQSvb/KEqw76ij4Nt1Ex7FiNabcV22/e5u8bnHNEPNqwGItvzLurX3LEXwLN4Gj2KOCbf17e+FR7EiXYhm8O3pkZ77s9gcuRLwmiFgai8jp1587GN6HK2WBsQIQMJt446DYhuCR3EnBOsnQMkfhUfxJ43XE1ugsWoSHm1tEa9XT71wBaC6TVIBiF+B0o4gOATr9kTG6pckP2RrOQ+D4sTHVhRQFG3vSFiBkk65COKO3d8zXGu3vAW//opZATBtc5kZAJj2b2q//Mu/DA8fPoSuri6wWCzQ0tICDx8+hIcPH8I//uM/AgDAD3/4Q9ixYwdkZWXB5z//eZidnYXk5GQoLCxc16tPPfwdHR3w6NEjrgT85S9/Wfe4n2efn8S4DoCzF5qqlzgP3xm3AooTh8WqziAp4nD9kg53pzgDnDzRqOhxc46WABT0IhHDOsEG4TQ4O+cJFAGzPghhuduvx+HVnwlA1jziQbNngzgMR+uMAmQbRwJGw2EVw2dPXAFvQ4CTMDgKL16DumM6AIdO4c+1OgDHShfAocxDfdMCOBvVIUFab7HNgLt+WnX+2SwA/e0pm8Dsfuk4+PdO6vCE/r2T2PrDhn9peFexDan6APmjGAzYhsC/676KT4x8gqQdKzq6vt3dOjVfT8w5XXZ/HcZTMwDs2dLOZwC0SsDK9mtIs2GO9lpUJ3cM9/SoKM+wVRVJSSjSPT3Qtk2D4ox4gg76nh4dxYfjKlNHOVGmK/WMof5BV9o5MUZ0+7A6zLq7mxGI9DhMZfs1tu/S9ftOPYPY1bRzhuudyW14bq+cNd5+52nwpd9i2xuce0o7x2G2Wb7C196zFMFPLRHQ9cpZ6Eq/YLBtKXSlX8BzM1xn587Pbf32nXsucU0JwxkAIg1pdAAoECXMp/DY6RdUFeqsfvX9TLecAejcc8lYz2LfZVDyR6Ez+5rxuvUaeEvuQ6etw3D9en4neMonDLf/ZlgZdNo6wG2fEQ7ynyiYh+YKY85/q6UDalqWhKz8w/VL2GcvSn4cC0DBXfEMgKM1AM6TYrhBzlRowxkAUWLE2xhA+lmj8XpT1RLkNwlmAMLMGQDTNp+ZAYBp/6a2d+9eEBF1fvCDH/DHra6ugtfrhbi4ONi2bRucO3cO/u7v/m7d/p4/fw6zs7Owd+9eiIqKgvz8fPjt3/5tw2N/0n1+EqMAoMjXD3XNiMGrPbGImgB+JADVnlyEivMBOHhZRceVX0TOftmVIBT0hODgZdQBKLqNaDrC0hX0IhIvbwBv2dNBRNqNIwovdzQEWXOM9z+OwUDOQwwMrA8QEZo1zwKF6SDXAqB95A3hzwPDSN0ou4rnUdyFOLyKCzisV3YF2dfll4JQdQYZ3jWt+Bwbw/xQ3bYE9sMLUNe8CHXHFqH+yAI4G5AE1FA3DfbD+HdD3TRm/msfgts+o8v+ExGooRaRoDQT4C25D97CMfy7FAlAnPpDrHOmH+AtZHoCeSNqgED6AFoyy84OUFK7dI6/1rnXoT416M+1j/PGngfv1stq6wfj6FNLCG8FoWMz3jw5+RxByRSI+fAow14qaTfwfNNuqPsihVl6LN0y+xDjuacHul45C8+is1H/IM4KXa+c5edBpCTfvrv4eAo66FwIh8o0BXwZd/j5+NJvQVdKOzyLs8L3I3fAs1grOucZd/jz7kxug2fxNvj+lp3wLDoLnXt6vru7oSv1DG6/ZSc8i7dB545T6gB2xh3oyrgIz2KteO7xNgxc9t3F/0H6LVyPycHt46zQlX6e/0+70s/jvqN24rmlndOhOLteOauem3bfTHW3K/2Cem5xVujKuMj/3107T8OjKKYDEP4hZMf+KQ4A0/9ud7caANiwkqNYB/n7oHPPJfXYibnQufeyDieq5AyAkjvMBcR4EJHVD51ZV+FZQi58PyZV1bMg9G3eCHTuvQzPkvLg+9Ep8LVtedBpvcY/E0reCHRmX4OvJeXB92NS4WtJedCZdRU/S4UYaF/Puw7/z85C+Ku4V+Br2/LhWskNcNtnEPVZ8xBOFMzrgvjjRaj54XbOwPHCeXDGrWDiI3YZmiuQAlR5NgAV55GVTwkERwKy8g++FoSK8zhs22rp0LP4m5Dlf2AE0Z0Nh5mIIUt+2NuxsmkbQzEvbeLD3o7OP2mj1F7QbJuEGgK2cUyqHBgOgfuIJvGSuALeRqYDcBO1UbxuvUbBEVbRPXg5CAWKhgIU+fvwxVdOwXnvXShz3DUDANM2lZkBgGmmGRgFAGWOu7wCQDi8pqolKL+IKsDll4LQdIi+CD/gFYKyq/hFSErAhKPzulHsJm8IHXbnSQ3OLhG/yKyT6ORbJzW4O4bKc7QEIPeeysp2nsQvSmskbm9vC3BxMEcLiuFYNRi+oluoEVB5NqCi8BjG70gdfglSANBq6VD1D2JRCKj+KN6cjXNwvJAJBYV9oCoB100j/79WFQYjLnlD3TR4KlHx1581DS6mA+CKesrVSTnvP2cAtyubUPumc4dx3TYE/l0ogGQLU3n3yvZr4E24BN74i3qnnpCe7OaP0HL83wZ/xA18LAsISNBLOwRMQk6+rH5oS9Vw/Em8iZz73d1MB0DD8teITulY/ST+tH0Yn1/ajTUc/zU6ALu78diRTzjnn++bOcpUAVC3H+TH9e3p0WsU0Pa0b60+QYSqX0DBhE5DgITASF9hnQbBE0Sf7rrJneh1+2dtUb7MPqhJmYPsmG9AZthHKAQW3YxOfFa/RshLs23qqBpc7e7mQl/8eW8bwMCCgikKrLQcf6qspJ+HRzHHmBDYRygE9sqCipPVUIB4O5qG5+9/VfNeZNUorj7N2tYoWKDAgSoCVAmjbf2vjuPjWDXMnzbGPyfuyCfgz3jAtTK8xWOa7T8A95an4N+HKsAUdJ+0zaqfsy1PoTVnBtzOGWisngK3fQZaCAMajhjQEwWo8WH3zcPxYhICw+vasVLUAag8h4kC0j8hzKfPHuB8/YOvBcHbEABHonptaziMTnzeADL73cf1KE/7KVzPmQqBvV1/3bO343UvezYIeUNMP0Wzb0dLAJMg9zDR4nXr191HsPWx+AbeOKKUrn21S7yqW6C8AXt3EQb09+E/p7TBJXsPlJg6AKZtMjMDANNMMzAKAOyFxj3fh+vRST5SK8DhOQPgbRDj6IpuhoSsfpK8F0na15/BbFf9GeN11/GAUGPAfQSDE9EMgOIIQMWFABytEMwAsCDgeMmC8QyAbZarjFI7EGX3PWXYDuTfO2XcB79vCrObpeOoAcDIQRwJyjL//l0CHYAtt1QnPuqsrqVH6/wbzwDcAG/seWz1Ycq4uuFPJhIl6uFv2z6MjqqoD5852sL1HSNijj9zKGXbkvMv3H5/r3g+YfuwRENgSKohQBoF0ued2SddN9IIiLX8M7b5pLSLZxfo2KLXhIIbjaIvtVpRENCV0i5vAWLVEp0OALX2SHQd/Lvuc+wnF6VjLW2KbQj1LHbdN9424wFX+RWtewvHxLM0mVPgqZyEFtuscRtPDrbqiVqATuZhe5+sBUiof+JibTZO8bWNBAyFLUCCFp76syiCKFp3H8cEh6i9qOEwViYUwbkdqV2CQu9vCVuAjpedBzMAMG0zmRkAmGaagW1IAYpdhuq2JSHr3xEvoQAlrUDptaCU42+dkOsAyIbdpBSgxBUouhkSnrczbkWK+XNFL2PbT6x4gLCh5iF4KiehsXoKak8uYraxHrGgjVWYsTTcdstTnRAYzQsoucM4FMwcJxFJx2V5Z10bDwUC1NcvpACFvYvZbnL+1+IfWaZbTPHZgAIU8Rh8u27KdQBk20o1BhjlR7R95BP5erjs2BvoF4Q/BiXthvzc9/RI958W9x3DtXbLW/As3ibXR5A9r4jH+hYtEuSiFq6sfjkGNOG7vM1I1wJE+8vsE78mkU/Ugd+sfnW2hVUPlJwBCc3qiVzvIvIJKLnD8s9R6biYthW1DO76afGgb8yymPK1EQY0YQUOvhYUa6BsXcEWH8G1q37bivS6lzUnwYAmrmDlU3RNTliBkuvic3PEr8COPRIMaIo5BGza5jLLyz4B00z7LNqGOgDhG+sAyHB0hd1yFJ6U8x+5iv2uL4LSi1iF0g4Jpi98FSrOB6Q6AHXNEp2AsFXEhLpmwV0/Dbm/hwJgjVUYEHjK5DoA3tJxrgHgKZ+AzK9Mq44TaxeR8ey1rTzehEu6SoBnS7uclU+tIaxVJOd3J/X89w04/r79vRKW//ug5Ay8mA4AO7cNjx0mWZfpBIStyve966Z0XUm5/uL6CJb3pToA34/aKd93Vr/0f67rxU+7AdaJkK63/6+37BBjQKP+Fnv3tTMAeSO6eQvp/4Xes6zvf3b1sDrMbh0Uv15hq/hekXxOlPxRuZ5G5aQU8+lyzUo/4zIMqEwnhFCb0mvX/Q2uXRLMZ85Dyb4jViG/X44BLb4hufZFrELsNgkGNHYHmAGAaZvJLC/7BEwz7bNoFABURol1AKraA1IcnkwHoOi2HIWXuSDJdJFSsKwCINjWkbACxTfkWbBqv7wCUNe8KK8A1E3jIDAbAvZUTnIEqLd0XJi5dDMdAE/ZBCjWQawGWAfBWzimZm3Tb0nVfHnGn7H7tcJeGyr5kojY/l6uI8ADAOY0yjK+G2X4UYlYkoUXrUU8kSv5bphlp0y5RINAlG0Op8qGJAsve1507rIKgEAJuN3yFjyLtUq3VVK75OrL2qCOhqE1r/GzOKu8ApBxBxTroI4CRGhaX2afPEvPKgB86HffXT7E7tvfK982fxTcks+JtAIQtUEFIHoZB4F/ERjQBKY0LqluyjCgG1UApJXRrUzoS1IBkImUbVQB+A1TCMy0TWaWl30Cppn2WTQKADwWv7AXtjHMD62WDuG6bG2jbT/t+ss8NlfPFdw+zbaf9WP/e33NXuaxqyx9whmADkvjL/S92GFphG9ZSg1nAKosfS/1vfgf9f3wWX0v+i2HwAwATNtMZgYApplmYBQAHLJ4oNXSsYYb37Hui1y0/mm2/bTrL/PYn8T5edFtP+vH/vf6mr3MY1dZ+iDL8jXItHwARy2/C48sXuiwNP4feS92WBrhkcULRy2/C5mWDyDL8rVP5Pz/n3gv/kd9P3wW34uHLB4zADBtU5kZAJhmmoFpA4Cfxzk0b+bNvJk387b5bmYAYNpmMzMAMM00AzOqABA3XpRNMlr/NNt+2vWXeeyNbp9m28/6sT+rr8nLfj+8zHP79/pe/EWuq5nu70mrLv8eX+9fxLmZAYBpm83MAMA00wyMAgCX7a5hv2hTFaoBH64X8LDdKLRlyKtuCkB+n1gHwHUcRW1Ekvf2tgDkPAyCo0XM2hZxthsVZGU3+IzXffYAHHwtKOR8N1csQrV/CZqqjNdP5KOKqMs1Cw7PHKqK1jOV4JqH0FA3Da05M8b88t2TOKCZfgu8Wy+DN/4iEn2izqKqL/u9NUzE8u/kj/HGngcl6Qqq2O66iYOY6beEbPW2lFE+2EmIx7XDn779vdCWes94+21IhREy61PvyVn5u7vFrH3SARDte/swCpRJ9i/VCNjTI9429R40hvnFGgJ07jJWf2afdF14bqn4vP1JL/h/SR5UlYr39PDXl1SYN9InIP0AX6baDsR1AJj6slCTgr2XlZwBvDGErbdwDH/PHRZu25Y6CkrBPfBnTBj3qmdNg6d8QqgD0GKdAbd9BvxZ04brx0sWoKLiN4S8+6uVd6C5bFHYJ195NgA+u/H1w+uWX1/sbWLOv70tAJlLQag7L1j3B2Df5wLC66L7SADyBlEF2PDcXKh+LtJuaapaguaDxs/7WNkClNlNJWDTNpeZAYBpphkYpwBtEVOAalrFNAxnnJgC5IiX0yrsW1cgv09Ou8gdDUH9thegACUyCodIJyB+BcovikkZpH8gowA5PHPgUFBR9PnH2eCpnEQyEFMgdUUZb+uOeAxKynXEd8acg8aI06AkX+UIT7q5LG8bH9vyDjr/CZdA2dkBzoY5xDjuu8udMCnFhynGknBTzlRI5/gp1kE5cUZGdol4sjFJR8biz+p/cc6/VGOAOP9iClBjmF9+7rLtN9IRiHjyKQhCG+kAaChA5MzT3+y24fuBBQr8fZBxBwOJjDvy5x35hAcLFDySvgW9v4SUn8gn4CmfkHP+S+5LOP9PoaH2oZTyk5L2geFau+Ut+O8ZJeCMFVDALG9Lrw/2RHZtE1GAkuSUn5yHEvrZ1hWwTooJQo6EFSjofXEKkDNuRXw9j12GMocZAJi2uczysk/ANNM+i7aRDkBu+CpUnRHz8m0Rq1LedMl1Oc/6wEhIysO2Tr64DkDhHTkru/ySXCfg0Gm5ToCzcQ7svnlwNsyBw4MVgMbqKWioRVVgIZ/c8j6Kd1G2n4l5kZIv4Tw3YtIraTdU54tlXkmFVXZsxTqoijft7kbtAm3md3+vlL2+EatfyunPuLPxuoyHL9MoCNtAY2ADbQW5vsHqhjz8T6NBoFgHX1yDgGkv+Pbd5cJf5ReDqhqwTEOAPW/SnuDvA011CFn+kvcDO6ZScA98mX1Q17yIAYB1cEOOv/RzErYK3sIx+XrJfakOQHzC3xuuFVneg/+5dZdUB6D8klz/pOjWC16bIlchZ+pTXPc2uraFr0LlWck1W6Z/EL4KB2vNAMC0zWWWl30Cppn2WbRPogRce3LxhXQAHAkrUNohV8uUcv6TViC/X5zFl2XZHIkrcGBEXgHYKEtW0yKpAMQsg8s1C84GbP9xuWehsWoSGmqx/cdTJslsWt7GLH/MOZ2gF1UDVJa/cQXAHf4Ynfc9PdzhV6yDXI3Vl9UvzdBrdQAU2xD49vSojh/brzTTLeXhb6D0u9G+pRx/UgoWVwg+jUJxY5hfrkGwAed/oyy9lPO/kcqw7HlHPNE5/75dN9W/991lFR3JsVnwoOQM6CtB1NKTNyJXAs4dxoqBRjeAC4nlj26o9Ctad0U9hYa6afHniKlxiyptruhlSE0VVwD+IL1YrANieVuq9OtIQDVe2bVLWgGYCkG9pAKQNSdWUHckrkDBXXkFoPJsQF4BEFQ+nLHLUHGoB8wAwLTNZJaXfQKmmfZZNAoAnIIZgGMlC1B/ZEHYK++zB+BInfFaoxKAks6gsFfVdTwARTdDwj5+R2sArJMh4QxA/ZkAOFrF8wcHRkLgPmq87vEEoOxqUDjb0FyxCJXnAnC8aF44A+BQ5sHZOAfOhjnwVE6Cs2EOGmoeohBYyX3w7zbuXfZH3NC3+2h7/zVBgT/CeAagLXlQdfzJScvF/njKvLbtGBH3fGfcQcefOfu6zC8Tk2pLFfWbD+G6qB9924B4fiAZgw3httRnL+pX3zECvt3d4l751HvgT+wXb5txR97Dv79XPAOQPCSfAWD/V+G5J0tek+RB+bltH954/iDjDt5otoNl8CkgFL4m7H+u5AzoBeGo/3+D7f27xlVn3zqoC0iVvBHs8X9VMD+wdxK8xWPgz3ggXPdUToJ/75Rxn37ODDRWTcJJ26zh+sm8OTh46DeFMwAX3XfhaKXx57/V0gElnUHwNgquL8cCUNgdAnez4NrVIpkB8AcgezYI9lOC9dMByFoIimcAmgJQ3BWERq94PqH09aBwfqG5bBGaK4xnAI6XLJgBgGmbzswAwDTTDIwCgFJnLzSXLYIrZhnbW2KX4XjxPFT7l6DavwS1JxfhaAXOAtjCV8EZtwJH6pag5HoQDl4OguLEjJMtYhUcCSs4JHc7BIV3QlD6ehDcTQGwJ+K6PXEF3E0ByB0NQe5oCGxjIXCeCIB9fdaYpAAAIABJREFU6wrYIlcxe9YWgLyhENjGQ1DQi4PC9iR13XkCt8+Z0mwbsQr2rSvgPIlr+f14a1QC4EhQz01x4hdkSWcQDr4WhFZLh/55VS9BTcsS1LQuQe2JRWguwwpIbvgquGKW4UQB9v2T8+9Q5nnbj7fkPnhLx9ExT7sB/ujb4Ap7h3O41zn/mgpAY8RprvBLQ77+6NvgDnsXci3vgzviCTpczOFXcgbQySLHy8qGQff3suHL++COfAK5Ye+DO/IJDl3S4/NG1OFN25C+BYj1kreljoI74gk/dlvKqOpcZvVD27YBzfpjdZ0NnbojnkBu2Coemw3wUltKWzJmpfm2LLCg+YS2lFHNOts+/RauM2eZr0c+AX9iP3da27YPgzv8sf686Hll3FnzvB5zB7sxzI/npjv2Y/AnsXYp1le/dr0teRD3nX4Lt1+7f3LQ2RDyumOTInNWP9v3E83rfZ8P4vr294I/aUA9dvi70JaMQaCu/5+1dtH/kv9PUzEbT/8zCnp4O9i+u/oAILNPbe/JGcBz026fek+tImX2qVUD9t70Fo/h73kj6rZh74Nry1PwvzoOSv4oeAvHMAhIH2frq7i+bwq8xWPgqURV7dasaXBFPcX1qGVozcJZGxq+b7HNgisar12uaPyMuuunwdk4B6X1/wX2pXwHMiM/gqYtvw+/trMNXrN3Q00rXtvWXddql6AxzA+l14JQ+noQvK4AODTXLq87AAW9ISi4G8Jh3OOaa9dWvDblTIUgezoI9jb1ulW/bQUcLQHImg+CdTIE2bNBqD+jua5tXQH7qQBYH4TAOonXRvcR9brpSFjBAeCBEJRdDULRrRB4G9Rzc8SvwOH6Jai4gMmNQ6cR3kDPzRG/Akcr8LpW3baE17XYZXzescvQXLEI9U0LUFl22wwATNtUZgYApplmYLwF6FAPHKz+TUh55QOIT/h72Pnq96DE8SX+ZVF7YhFKHF+CHbu/BzHJP4Ht+z6EvOY3oPJcACrPBcDW+gYk7/8QYrb/BJJyPoTcE29A8Y0glFzHL9Gc029CUs6HELPjJ5Bk/RCyzr0JRbdCkDeEX3b7r7wJiXkfQnTKTyAx70PY2/kmZM8EIWs+CLmjIdh98w1IKGbrBR/C3g5cz5kKwe7bb0BiwYcQ9QquZV56Ew6M4JfzgZEQWE+9wY+9LftDsJ18A4puhqDsShDKLwWhytIH2/d9CDHJP4Edez6EQu9vwaHTAahqD0BN6xKU2v8L7Hz1exCX9BPY+er3oLzqN3n/v9s+wzP/3uIx3lKjpFwHb/xF8G+5pUPt+SNu8Gy/tt2HZ/7Z7974i6Ds7IDq5GlIi/sOJET9L0hL+HOozvwltec/b0RXBaBBTMU2pPub38+cM3LWeJ+3tvWDVQB49pgcSBosJWdUs70u+6xd29PDHV9Op1m7PXPKufO67y62sFBWOuMO/s0qFZx2Q8fcdxedZ3oMnev+Xr4fnSNM55N+C39qtmsM8+NcBe2TjkPO9Z4etbWGtsu4g9tozlFJu4GOcdoN3A8bpOXPV7s/NnzL79OePw3i0j5oG5Ztp7addc+d9rfrpvo/ZYEhfx21+9Dsa90MAL2/6KYJNinDrwtIC+7xz4GSOwxKPpJ+lNxhXCu5D56yCfAWj/GAmY7RWDUJnooH4CmfAE/5BAbTJffBXT8NnooHoBTcwwpb9RQ01E1jy13dNHf0Xa5ZDMwb5sB+eAEcnjmob1qA2pPo2Np981B/dAHqmpHwVd+0ADWtS3DwtSBUnQlAxYUAVJ0JQPmlIDSG+aH8UlB3DSvtCEJ+HzrmxTfwdwoEckdDkDcQ4o6/dRJ/t42HwHY/BDkPg3g9WwiCbTwEWQtBODASguyZIN/ONhaCgh68JubeC0Fht5rEoPvzBkNQcj0IBb0hKLoZ4kFK6euYzKg4H4Dyi0E4dGoJDp0OQHUb/qxpWYJDp5ag8lwAak8s8ltVewDqm7DKW9e8CPVHFqCs3pwBMG1zmRkAmGaagVEAkF8wta5UHhH+MyixfwnqmhehxP0lw/X8pjcg9/gb69cifga2k29AyfUg2FrWr4dH/Aysp96AA8Mh2Hv9TQiPWL++99qbkPMwCHs7BOtdb8Lu229AeKTxtoXdIci89CZERKw/twPH3oCyq0HIaX8TIiw/Xfe8it2/BTUtS1Dk+S3j/4vrS+Byz3LnxFtyHx2glOugbL8Gni3twhYef+RN3bAv9f57Y8+DN+ESeLdeBuX/Z+/Ng+I6z7zRhmYRYpG1IYSQhNgaNVuz0yxN743YBY2EdmsXAq1ISOxCgNi6Oxk78SRWnMwkVa75qq63sYBMNt/66iaf7djOYhTLk3FyayYzmmTWSupm4jvlPPeP533ecw6c95B4vim7uOep6hLqp9+z9HLOs/ye3y/pIlQmToMxbNm+wz4E664QBk0UfJn7cf9ZfRhoMTgQVVVNYQ+xSr59hCcAFHStSABkwX/Hxlts/RJWqxMHMXikDsDGW+A0vqr0s0CzMnEaMmK+B2lhj6Ax/AW4H90EXTuOSR2Azf241rAkVfgpmdh1Vdq2YYlX8XmlW1al5/7N/Tw4p+4C3/bWAQyGWVC/wr/xFtRt717WAXigXE/Hxrf/QNo30XCyQHzFsVP3gtGE8rXhr3JaVUoclOcldV18plu478394AwXvG8pl6U5EPocWVeibs91XBshO6/EQb6WkjNOB8u6S7xLlNUH/h0jsu8DHhslnBcyzsL99a3QGP4CpIU/gozY16EyeQ6/o+Z+8G8fAUfkvPRdZPAfT8koeIpGwb/7Lvc7orHC7ykbw6SgaBT8aciqZQp7CI6oBU4B6rQhFW9rzpTkX7cALZYZqPVNg23fDFhsX4E9W96GPRHvQ0PEi/DFzR1wzH0Nyg8FoOLAHDSVzrIq+UNeRacOAMEEa+MWIcv4EGrjF8HtC0De5RDk9GLQT93NLONDZCbrRIhP5jjCeGqeWISsCPRVHZ/jiUHmeBBsB2VrExbB5keKTypeyLddG4f7zr0agvwe7AJ4ndTdxGP3OjCRKT0WAKt/Duqr5/i52dcvQlPxLNhdU/y8HesW0Mc6vnb3FJSW6xAg3daW6QmAbrqpGCUAKRv+B6gNhaVufRuqm2YhNfFtdX/i27A7+R1V386Ud6DsSAB2pqj7U3a/A7lXQ7AjTd2/Y887kDkehOQMgT/tHUjOUvclZ7wD2YMhSEkVH1tBVxB27VD370p+B6wdc8LzTtv0Fjic93ilsm7nFfBtOgvehJMyGs9XVNc6DK/wij+H+1DVf+NpDNhSr0FG7Ouq6zNiX5egPKzK6s0bwmprDgZlwvmD7SMc783hInLoB6sYa/H8+zJvavDpD0Bl8tyKxCXG8P/Am4Yi6NpxTHs+gQXYIqw7Bcmi9SKNAf+Gmzz4F+Hw3WF+bRx+ymXxsScOas8vJA6K9Q8SB1c9L825jMQBBYyH/ysbAvYnDQm37TP3C4eAKRn0bx8WfJ+G4ULqSXjTULTCbwz7EKy7P6uJ8ffmacwApE+gP019BmB/9hTTARhXx7PnT0OxVTADEL76DEDxSQyw1fyufQjFcfvU/dWHA+LZpcMIAxJi/Ftw9km0bbcXExDRfEKdDbsADRViHYBmy4z6e1Ywrc8A6LbmTE8AdNNNxSgB2GF8wG8E0uP3kBbxCGoaZ2BP5Puq/j2R72v6LBeCkBr11+r+6PchezAEqdHq/tR174NpRNsv8u2Jfh/29ofE+456H8qOBCA1SnzsVv+c8NzSjI8w6GYQjOrmWaT2ZJSennVHNKkXqfJPfP5lhwO8uk5V/bTwR+r7Dn9Pqvqb+6Hpf3Zj4M+gP5rMK8YHvJpMweLVdw4ohcBSr2nzvmsy9TyApLgfqPo6Dc/Da3HZ/zW+ey1Oe+Or2se9vVv8voT/AfteRcPAl9Wn8b5rHJvxVW39A8bys9pnQhAlqtjzDsAqzEp8fkQ2DM6x/Cyh1GLyeS3BDJ2G51X92zb9WJPlx1M2psHzv6DNphW1gB0AkQ7AugVI3KbBArSjAGo1WIAs54Ninn/GxPNxWYA02c8SFiFrVIP9LF5bX6U2dhHKOwOa2i2aLEB6B0C3NWaGT/oAdNPt02iUANSGf1b1htAQ8RKUdwagMeJFdX/kS9AQ+ZKqrz7qJSg7HICGKLE/92oI6qMF/uiXIHtQ2y/0Rb0E2QMhzX0XngsKj70h8iWoOBgQ+hvDX8BgfdNZVPKV4fdpsFcs5PWyVPHfcIrTNpKCqtcyDL7s29AYrv6eN4a/gNAKqvgT5zp1BDJvavO277kuDQIzPD4P/BhE6L/Chx8X+feqvnzDD+GDqC0fXycgbBWufcMqOgCraQys5l9NR0BLo0Dr2MLehbqdV7S3vQqXPx/EpXkPVtWnOQXxe7qkCgWTP7eaPsLPorZAnuFHqv74qL//+Dz+YUvgLh/T9LsqxzV1ANbH/0r4XfzrDdo6AJYLGjohxiXYe/vj6wBk3NPQR4lYAtOwtg5A0SltfRUtDZPVdAB0JWDd1poZPukD0E23T6NRAnAnwaPaEv5CYgfY9s3AFzd3qPqf2XYAnkk+oO5LPgCWC0H4fIq6/6n0A5BzIwRPp4r9aXNBeCpd7P+TTIEv7QCY+0Lwud3q/s+nHICCi0H4/A7BsScdAGvHHPxporr/fkQDV/JdTuPpjTkKbuNB8QxAZA+q+G49j8OxROGZ1YfDkZZh8OUOwv24/er7TmgDn+kWdiDM/cg6xCr/lAxoVotpiJgeWX2KDsBqFV/tSvcDSIpVh011Gp6H19ZnafL4a3L1R1AlXEuDQENjYJW1dTuvaOsAJPdo6ytoVemNr2pvezWe//Qb2p+pbEiZD3qzwWpf5k3N95TPhSxPAGQsUcIqfuQ8vBa/V9wB2PhjcEYIKviR8+ApGhX7eYdAzPPvtE+CY524A6ClBPz1VIumDkB+t4bS7ypK45odgIRFMA1pKKDHo06AUAdgFX0V+/pVOgAxi0J9E3vMApSVXQE9AdBtLZnhkz4A3XT7NBolAC2FR+GNsGLoNDwP+YYfQqfheXgjrBhOl12G6uZZOOG8utIfXgxHvdfhcMN1eCN8pe9gay8UngnCAX/vSr+xGJrP9kLOjRC0nFb3t5zuBdNwCPaf6IXXjSv9DZd7oflcL7weofS9biyGtuO9sPd2CJrPqmw7vBj8nb1Q0IXH9qahcIX/SP11KD8UgGPuayvO+01DIZyPql8p5CXvAqw7Au7wDmg3nAeH4WVGA/oK+KN6OM6fBnE9JaPgzRsCt/UuePNwMNJdPgYX0s/Am4aiZfsuggtZZ/kQsDdvCDxFo1LAxoYy/SmjYsy36RYPDCngV9CAsgFi1eQleYRRSgp45Tf34/DyssHqP3gGYM91MVae6QAIsfBbB8QY/8TV5wvqdl3V4OpHViXNY9fSONjcL9YYIP0D0dqNfXwAWDgDkH1bGvwl5h9ZUiDC8BM1bF36DfCZ+xWdIGL18WVqaDskDsIF0znxDED60+BPVcfw+3ffBW/hCPh3q8+rtGVNgqdkVIjx329GGt795ilVf2PpHBRWf1k4A3DEdx18dnUcfbvhHOT3iHH4rn0ByBoNgbNZrGFi6xTrAGjx/NtbkQLZ2SDg+bcjzafo2Osr57DzKtBuaS6agXqBr8UyA0W1egdAt7VlegKgm24qRglAWellOF1+Gb6VVAA/jUuCbyYXwHHXNaTT801DTcMMHHdeg7/aZYGfJmyHbyYXwAnHVahunoWq/bNwZN91+PoeC7y/cTt8PdUCh5p6obwTb1QFF4NwsLUXFtMt8GjzdljILIT2Q71QcDHItQDaD/fCA3MhvJe4HR7kFELryV70DYYgbSYITRd74dVcye/v7IW9/SFInw5C/ZVemN9bCO9t2w7zpkJoOd0L6VNIs5c9EIK2Y70wn1UIj7aiv+1YL+ReRSq/0mMBOGdww2K6Bf56w3ZYTLPAkX3XkR6vEakDz2efh9diTfCBcRO8FrkHzkfsU3L3s4DfE3WYzwEoBL5YUuDbeJpTM/IAvnCEJwBeyzB2AApwoNdbMATnzefhtQQzfBCdCK8lmOGC6ZxEs8gYVrx5Q1JHgLoAnLd9nnPx+5NHJCpQqu6yh5z/nV7TkTgocfkv1wFI6wV/0pDMz/j2GZ99ZfIcZKz/X5AW/h40hr0A99c1IwsQo59ErvxXpW2TDoCcy1/G809DuBTQEtPOCh0BNqgr1xDwx/cqqDBxrey8iN2I0XUu5+InoS4KslH/QLbvxAGJxjP1GnL1Ryzj+mc0nVxDIEymrSAb2FVw7RsZVz/Reqb1oraD/H1hiQcF/nzAm2hVyUfnFSGdtz95RKLzXCYERmxSvkwcnvaZbuH3IULSdvCnjPIE8sLuJ+F+/H5oDH8R0sLfg4z4N8Ca/jT/Hvt3joEjUvZd3D7CB+g9JcTyI/H8t2VNgqtynNN+tmVNSjz/UfMoxOeZAlf1BNhdU6jNwTRMHOsWoLmQ0X12II1v6ra3IS3yfWiIfAn+dNsBOO66hhTAhwLgq5U0TOzrkeffHeaHwnNBKOhCIcNaORd/E+qMmPuQyae2faWGSdosXn+qDyv1S2z+AKc+zhwPgq2T8fwzHQBnC/r39iPNp8er1DBx1QWg4CJqAJQdDkB91ZxCf6W+Eqk+yzuRArTeKtM4kHH9V7bhILA9RtJ92W+egppGXQhMt7VnegKgm24qRglAke0atBRMgyMaaeFITId4tKubmBBYzAKnlKuvkrilG6xKurl9NViFyu8JSWI6Mio91z5U0sy9zsR0miS/LWERHC0BHsBn3UG1YNsGRqe3AcW+cq+HcFjuAN6As4zoq21jVHq3kFtbTrVXG7cIHm8Acq8hjV9BFwqB4U0U/Q0VqHtgd02BN28IaR/D/lLJ5U/BvSzAJ/Eu/lh3BPzGi+AwvILUixEo7CQPfNzlYygiRvzolBAwnnT/7jGJPjFyHoM2YgBiwRWH8pj7wZd9m/On+1NGJdrGiAfgTxqSBpdJtEmN/jGrj6v9ytd3JA5KWHMK0pf72foVVJqJA1ypWC70Jaf55EF0Wq+SJpREq4h/P/3GMipPScwLBcwGZXSXsgCcBcUkYCanAeWaA3TetO1wllyQHsByv/FV8CcN8WOTzl3l3NJ6oSv5KLwWa4KfRW6B1+KyoSvpiILnvyv5GLy2Pgt+FrkZXlufhUkT0YRm3oSuxENs/WZ4LdaE63deUQ52y8S7FBoDJO4lS7Tq0np5QqhIAOSKvux70rXjGLwWvxd+FrUFXovfi52ozJvgyxmAC6ZlNKBxb4A17U+4VsWFrLPw2gYzfLAuEdemn8bveeEIuMvH4Hz2efjOxlz4YF0ifGdjLpzLvwieMsbzb5+Ec7ld8O3EfPggZht8e0senC69JInxuZHv3+G8xzntaxqwcGH1z0F18yxUtqGeCemaVDfPQsWBOSg/FICiU0Eo70Q9k+InMegnGlC6RuRdQcpPc1+IFy2y7iA/f/Yg4/sfYrz+fSHYEwwg9/+9IBYjbuNaogc1DeOavf0h2HsbaT2zB0OQfwm3Y+5D/n/zrRCn/cy/hMdSeA73QcWVwrNYyCg7IukYlB1GJqCyI0h1WtM4g6KOHXNgd2HyVN2M1/Va3zTUeqa4noLF06snALqtKdMTAN10UzFKAJwZ19TbxRasgjcVqUvHN1hRSVPNt68GRXa8DgHdXT2qBYva6M7mAOy9HdKky3O2qPscLVils7eKW/j53SEhzV9b1iRCYeKvq0MEwi4oRbxUkgF/9CV16ILpHrgqx8Fpn0RRo8pxcNomkRe9aBQ8ZYz7XETluWMEk4W8IWkOgGYH2GCwEMKzfVip3MqEwhQKsHuug3+7+nrixNeC4QgpJxMHuX6A0M8CeOG+Uy6LqTa3DmhCk3xJF8XwIjovLZrP1SBAyT3i/W+6DV0pxzmkK8/wIw7p6ko8BHU7r0BX0hF1f/JRqNt1VXs9C+4pYOdCXkyJty6tV6nrsCyho9kRRQJAELHMmwo4mnzfF9JOwYXdGjSg6U/Dudwu9bWmc+DLHYQLGWdV/edzu8BVNQ5nCrvhjbBl/rAingQ4nPeguXBGxmm/CE2lGPTXNM5AgfPPIHXb27AnEnUAvpDYAUf2XYfSowEoOyxTy6UCgQc7ALnXMfB21iuLE7XteF2ioN92gHH9UwGiPYBiX1NBqG1T+pxNATANSUlEbZtSB6C2DTsAOTewOCKpmEsaBPk92B0oORHk3YsspgNQX8WEG/fPQvmhgKwDgFz/zUUzUNU6C7Z9M6gJECPTTijAgo/FrScAuq0t0xMA3XRTMQ4BivpTWD4QZjDgIF1Nw4xw0A4p5dR9tesXoeh0EGpjNYbZzgbFg3QJi2Du06bL0xq0yx4QD9rVxrFjEwzSOcNfBd+ms9pc/lTplwX93tjjKOS18bRwaNMRtQCesjFw2hDmQAqoXsswuCrHMQEoGdUcxCW4EAX83oIhhQqraLCShj4V1V3TLSX/u8bQpzPiAdSl9a4yiKsxzJrWq73tVag2V6MgFfrCVxu0XY0G9A9Yv71b89juRzaqD3WvawJfVh/cj2kR+JvBl3kT7kc3CddzyA+JgLEHQXzECSF2lOr2XAdf9m0lFIy+HzkDcH+94Nji9sNrCeIh4KQnfgz34wXD7PFt4M0bgvsJbar+Zze2g6tyHO5vaFf3P9EOtn0zwhmApuJZsNhWChjSDMAx9zVhcaLdcA7yu8U4fHsrJgEif83hANg6xGtzboSgtl1c+DDfRPiPmt/jwU5FnU3dv68GOxv1leIZAJEOQGvuNJSVXgY9AdBtLZnhkz4A3XT7NBolAKlhr/AbgfRAWrjq5tmPRSlnMi5B2ZGAJl1d7lVtujvT0CpUexFiX/ZASOxnVHpaNICrcflzzH/UYfAlXQTfhlPI7pN0UZuKM3wJXNWoIOwux0Tgo8cZHPJA8CBN+kSq/mf1wUePMzDwZ7ztdek3NNcS3SjBhr7xM9OKDoAWbWRdWq+m/2NTiNK2Py4VZ9i72hSjq9B0atJdGt6FuuSe1SlMNdY3hr2w7Hl8NIa9AHW7rmr7U69BY9j/oe4Pf0HJ2pM7CLufCkgKwWm9mgxClAQq6GBJG4ANB4spaV+En0VvFdKAxkX/g3it8UXwFI1Co1Hsd9omNf1215RmcWJL8k9UfZ2G5+HreyzC4oTD8DKY+8Rc+7aERcjp1WDy2bCoqRGQMSEufNTGMY0BkT92EYqf1CisxC4i1EfEcBS9ICzaONYt6AmAbmvODJ/0Aeim26fReAcgUtwBqG6aFVf5YxeFNxpeZdfoAOR3a1f49/Z//A6A+aZGByB+EYpPBsU3QlbhX7UDwIZ9fRtOgW/LOU7r6S4fEwsURc2Ds2YCXFXj4KyZwL+rJ3AegHUA3Na7YoGkyHlJ/dfcj12AzJvYFSgcAW/ekHaVPf0GfyynAaUgUrx+HukuNegwtcSwNGk+V6XSfMAoLcXnplmhX6VzsZpgVl1yjzaVZ8plze2nhQmE3cLeg7q0XrHwW9h7ULfnuuZ6uRIwJYHyeQ5NXQg1CBBpS7DvlpYonZYQWFLCD8VrjY/AlzsIaUax2J6rchz2iPwRj8DumtLktF9VB0BQXMg2vLsqz3/OjY9fnMgc19YB0Ny2cQnyu0OaRRlrx5zm+yL0hS3pNKC6rTkzfNIHoJtun0bjMwDpV4UzADX1M9BcqN4ybi6cEc4A1NmQBUjUZve6A5DTK26jO1oCYBrW9tsOCGj42gKcZUNElVfTMCOmKIzsAU9kJ/gje9T9bBDYG3cCfBtPY9U/+zZ4Su/gMJ1rClryp4Vtdrf1Lgb/bA7AUyYF/76cAXBVjUN75qT6vtMnOFuQt3BEEgQjcbBVIB8U+Msx48sDPxGO3799BNloBNvv2HRbkwpTewZgYPUZgJ1XxDMAiYPifRNNp2gt0YCKaEI33tKk6vRvH9Y+9o19kBH93WUBFz4yYr4HdSmXxf5134O6tF7IiPmeuj/6u5ICMOH2ZRoPdek3tHUdVNiguKhc7iDU7bkOGfFvCI99tRmAjLjXVdemx78JnqJRSHvi++r+J74PrqpxSBf492x5a1V44uad4g7AYpp2B0BT6Ze4/AX+mie0lYBNIxrbjl9EiJCG0q9WYcW+fhGsfnEHwB6zAHaRdkK0rgOg29ozwyd9ALrp9mk03gEovgwt+dMS1V70AjRbJArQqtZZaM2ZUtDGNZYiq0Zl2xw0lM+BPYbRza1fhAarxBBUfBLxqpyuLnYRvK4A5F0OQd5lHHhzNjAqPeMS2OIXwd4aQHjQKLJj2PfLqPbYsFzWnRCYhpHlp+YJma89wFk6TENs2zIav8ayOXDWTIA3bwjqtndDu+EcOAyvSFz9LLgnik+/8SI4wuT+C+CNOSrBfXIHkY7QjewatrppZBFyT0FrzhQ4oqT3tDVnCpME+yTOAFSNIxyoDOcAnLZJ8JTewUfZGPhT5fSI8+DffRex/pZhPivgtQzjILBlGHUBSu+AL3cQ/LvHlLSNu8cwSaDqrukWZ+bhgR8JimX1McpJOV3mgKQym35DSSsZMc+Ti7qUy4wi9FW+745Nt6UqdXIP+JNHJKpNRmcpH06mgVVOh0ksP2y4dTnVJ99+ymVGMfqAUW3KWIAYvInYizhNJzEM0bYVNKCv8uSA4DScylNOAyoT3pKoPpcUFKWVW6dW6CMYwz6EyqRZqEu9BpU7Aiv9ht9B5Q6E81h3hdTX7whIcB1W8V9OCypMXHZIrFKKYfDUa4oZEWvG58AY9uGKfVszPsdZfu7HLqMBNX0efNm3hWvLCr4IdvcUlFmeVfdbngWnfRJKS7+00h/+IRRXPAe1vmkhnr25aAYKXH8mnAE44O8VkgC0G85Bzg2xDoC9FVnKHAISgppDAahtE2D8G7A4IfQzmlHRvj1eZC7y1ar7Gyqm9VjUAAAgAElEQVRwCLhF433RZwB0+/+T6QmAbrqpGE8Ayq6Aq3IcbHXTnPvf7poCh+Me1DTO8H9r6pFOrqYRebbpUdk+B+WdSDlHgX/5oQCn1ys9GkBebUZbV3guCPndISh+Mgjmm0h1l9MrPcw3kQIvYzLI6fKy7iAzRvYg/t80hI+sMXxd1p0QpM0GIW02yDUEskYlmr3SowFwOO5hgJx0EXxbz6NgV5hfSOPpjTmKOH/6O+4EeBNOcj5/r2UYnPZJsNVNQ61vGirb8eZb3TyLz++bAadtEiuVDqQtdNZMgMNxDzsAtklw1rAEgCUBnhJkAqIKPyUE7nKEBhF1ojdvSKEcLO8AKB6mWxKvOwvuKZAn7QAK/DxFowp6SB60p99QBNE+cz+ntqTn5VSUPhNWzPlQKgsoiZOe01BSsEqvo21SsM8q25zTPvUa+nZe4bSbfJ/0uu3dEt3lrqvSOqYDwI+B7cdnkmg+ifeeHwv9m9wjraXt0/nJRbfo9cS/T88n90DdzitQuW0GkuLegfjIX0DS+rehMnkOX5PcA77Mm1CZEoSk2LchPurvISn2bQzuKTHacx0qk+cgKf6HEBf195C0/m2w7v6s9BmkXJY+g51XFEw+dek3lAkdJV1ECcu+K8sF4XzZtzk1bUX2M5C04UcQt+4xbNv0Y6jIfkbSr6B/CYZWOCJR21qGoSL3C7Bt448hbt1jSHriR1CR+wXwZd9Grv+qcajIfgYSty5B3Pp/hMTEh1BadB88JaO8K1ZS/hwkbnsIcbHMX/olTLh901DTiF1I+/pFVpxAPnxrxxxUHAxAvvvPYPf2d5AFKPIleCbpABxs7eXXJa9bybXvbEIWIKL9dLQoef7t+wOQcS8IWWOMBahD8tcwrv/McdQBqDmkLFzY9wc4AxANEVNxwha/CM6GAFguIP1o/qUQuPbJNAhikQWo+GQQik4h9ee+GqYDEI7+BqtEdVrZPgcNFXO8aOOIRhagmkakSW22zIBdpp3Qko90oBUFPXoCoNuaMj0B0E03FaMEoCKvG1xV41JgyoJah/MeTwpqGmc45zZxSJcexaC/unkWKg4iO0XFgTnOQ13eibzUlvMs8D+DSQBxWBdcDELODaS1y+kNQe41DPKJp998E6v8udfxpmkaDkHGBPJqm4bQnzGJN8zsAUwa9t7GR9Yovr7wDN4sHc57GOgkXQTfxtOSYm+YXyHoRQG/nOufnvNtOIXBVc4AeAtHwO5CPu2qVnxUN89CTT1LoNxTvDNgq8Obq8Nxj7+vdvcUnwNwVY3zYIhYgdzlmBTIA35P6R2O8/cWDHHlYE/RqJQEmPsxyWHBGwV3FKgRNSSHichYgDg7UFYf3w8P8Gn7cpEoxjzDYScEJ2FdAnkQTn4K/OlvUibmfPUs8OaBb3KP9PwyhVtKVngCQMmE/LXy5IGC48ybuF0m0MX3ITsu+et58sMCeZ4AMPEwLlIm0zJQJAT0vDyhkHUNFEkDHT89x9h85Ew//L2XcfrzwV16L9JvKOYBqLvCkzgm+MaTAHknKHcQvwPy7wubN6Fkjw+eM6iQPBEgVitaQ8+5rXfBVcXmXMqxg+WqGueJLyXFDuc9cFVLczK2umlw2ieh1if9dqqb8LdGD9s+FLiy+ud48YGuRXRtKjwThJITQSg5HgTLhSC/7hSewefyL+G1yB3mh7zLeE3Ju4yJQNYoFiFybuDfGRPI8Z85zpKBYfaaUaQAzZgIKp7LGsOiRPYg0xFg16fsAdxm3hU8lrzLuP+cG1gYKTqFx1p4BjUKqJhR/GRQcY2tqcfzLz8UgKpW1Dmw+uegumkWhQ3ZddtWh8UdW900f18djntQ68GEqqRKVwLWbW2ZngDoppuKyYXA7K4pjl+3u6fAtm+GB6819TMY7C6r+le24w2HxGYqDsxByXG8MVk7sCtQeiwABV0Y9BedwptYyfEgV9okvu28y3jDy70q8WDTDZEqZtQBoOp+9gDeWLPGQhwSZL6JyUHuNbx5VrXOgqtqHIPQreexih97nAf47jC/FPRTsC8P/mOP45AvwX0Yb7/dPQWV7XM8AapqlUR1KBGg52rqZ/h763DizdZpx0CHw4HYILCn9A6Kg1EVlbEDeYpGuViYt3BEmgOgymsBSxCIIYh1BOTKwd7CEUwMWAJBCYMiAaBH9m1OC+oz9/NgnUOHZJhzEqriAmOy1xHFJA+iKcCVdwdIoZgq99QloM4DBdUplxU89ysCdnngTckDBcoUuMsDb2LKob/lAb88YCbdhKSL0n4oGdh1VUpmCIojgzMpEhEZPSfBpfj5be/G7dBxypMbpkLMH/SeEXxHXvFnQTkP8unzou6A7DMlrD/5Fd8D9t3gAnOsI0VickRD6ykaBU/JKCaeTNWavqe+nAHezaJOl3zQ3WmfREpcWRJMiTMpATttk4prEU+ofQi1s9VNQ3UTS8L3I/9/2eGAMgk4gsq4ZUcwWC45IV1/Ci6i0BcF/xSA772NQTkF6aYR/DttJgimIcmXMRmEzLsY9GfeDfGEYO9tFP4yjeC1ae/tEGTexe3k9EpdTBL7okJI1iju33IBE5Lcq/h8wUVMWIpOB6H4JIp8lRxH0S+q+Nc0zkBl+xx/jsS/qptmefBP7x0lAvLrkMNxD8qKLukJgG5ryvQEQDfdVEwOAar1TPEqkNM2yWFANfVMZbNRqrLVelgFjs0HVLbjzabiwBy/8dDfpUcDvIqV341Bef4lSd0y9xpTwhzAm535Jj7yrrDqWC/e/CgJMN+SFDmzRiWYED3yu0NQfDIIlW1z4HDcw+AmsQt8G09zGI+8qu8O80sc/rHH0R/ZCd6EkxLO33SLVyOrWmeh6BTegOk8yw5jsFHZNscDkZqGGV5hs+2b4d0V6gZQ4F/rw9e4y8cQosSqolwjoERSCKbZAG/eEO8MkCgYr/jnDkpqw1SJZfSQFMwRv7vXMqwM/GSwETm1qAIKRMG/TBWYV+wpqJe/TqY4LMeoy7sIPCCWBcMU7Mu7BjxYp21Q94B88ko/g9XUpV5DX8plCSef3CNV4VknwJfVJ21fVslX7J+ep2q/rEqvwM1n9SlfI6vyKyBNckVegkgR/IagWmxbPAmQJxiUnBCjE1XmaVss2fKZ+xVdGBIHo8+WOjaKYXCZsjQlC1x/gpJLWaJJ/5KQnacIla69BUMSvI0J3RGczVM0ykXxHI57HBLncN4DV9U41NQj1JBgiQ7nPd6NpGsR/Z/Ufum6U3EwwOEwJceDPPAvOi11JItPYkXdcgGTAYL9uMP8HEZoGsLrSu51qepP3UbTCBYfTCMSDNE0jMlA2myQV/73BFEAjKCMNJ9E3UpzH14LzTelbgBV/AnuQ53MkuN43MVPBnmiU3YYrz3lndjtoPO3duCMVmUbkh4QFNG2b0ZR/Xc473HIp54A6LbWTE8AdNNNxSgBKC/sAadtEgq6guC043Cq3Y2dAIK52PbNwEePM5ChwjPFbyiV7XO8I/DR4wyw+ucUN6SyI5gAlB8KwEePM6CgC5OBkhN4EzbfxKpbfk8I9r40yiFA/IbYizfImm/egL39eBM232JVuSGptf7R4wzI7wlB2ZEA2N1TGKhk3gTfprMI39lyDiv/cpiPbAaAXkfCXr6t56Fuz3Vwl4+Bbd8M5HeHoOJggD/KDwWwvc7Oq6p1FrserAVf0yjhbT96nMGTJn7jZUGO0446AE7bJIdIuMvHoNaDA8M1jTNYKS0ZVSQE3sIR8JSNwTd+ZgKH855U3WeKwj5zP3iKRuHxL7ZLKsFU/WfYf2/hCPy//5AmBX7mfiloZ9COuYdeRdWYEoW6tF6wu6ZwIDF3UJo1kCUCZV+/pQjYFXCcPdeh660j+LcMriKH/zz5xpNS94Aq4lQhT78Btm/18uCbV+lZstLwP3v44K4isGeJRunibSlJkMN3WDW97OtsNoC6AhRQp1wGh/MeVPxVn1J4Sza3sPvpOT4Hwd8Pdg6+rD6wf1uZ9HCID0sIzr91VEo86Ngosdp1Ffb/XxeUCYQs+XBVT8Cu56Y5zMubN6SA/FR94ya4rXelz5k+u+VsULKEkgJ8b94Q6k4Q5r9wBLtVLOnwlIzCP/8iGZNTFuBT0uqqHOe/f0/RKPc7bZPgtE+C3TWFv4OaCbDtmwFXNVLk0nWounmW/87s7ikMauvx91XTOAPPvV8JHz3O4BVwCpZLj2HV/6PHGViIOI8FCMt5TAZyr2HA/dHjDA75cYf5+fwQwQ8/epzBSQlMQwzyI+s8fvQ4AzImgtgRGA8qrk8fPc5A/z28dpmGpO6m+VaIX1dzbkjECPndISg8hwnAR48zoPAcBv2lR/Hcip/E47d2SNdd+bWYEiC6LlNX0rYPIVN29xTUNOK16S8/yOXQRGvuRT0B0G1NmZ4A6KabiskTAGoJU3WaOgEcL7pvBmo9eOMl/G1l2xy24JtneRWu4gC7+TA8KuFULefxZlx2JMDnAYpOYVeA5O0tFzA5yLuMN17qBORex5tszg28oRImN+dGiLfjC88EobppFryFSFXp23BKMbwrh/hQIsAhQAwS5I05inz+KZeRT98+yQP+wjN4A65sRyhBxcEAr85Rhc3agXAg/h41zEDVfuwI2N34vtY0zICrahxqPVOcOcjhvMexz077JK+KEiuQu3yMzwR4ysY47MeXO8ghFp6iUV6dpS6BL/MmBnFZfZwdiJIEXuWXQ4BoiFgG61mB75cxzsgZZPhr5FAeVqGmxEIB/Vnul+PcCcpD/0+9hpSUVG0nKJB8mFgG1VlRKackgYJ86mbIkxP5wPD2biV0hwJ42dCzHI/POxW0LzlWn/bHkh85Hl+B5af9LD9GWQLCkwaZjsPy8+fwLdY14HAfSu5kMxwcBsQ4/xWJICWTJaN83sRnusU7TlT9l1f2aWjdXT7Gh4BdleN8kJ2+2+5yhLVRYuu0T3JKXILKOWsmEKqyb4ZXqGsaMHit9WBnsuxwgHchKSkvPSZh//n15hxWzS0XsOJf0IWJQN4VVoG/yYJ9Vnhwh/lhbz+bMZpASE/udRbQj7IO5CBLAu4ocf7pM0HeFaDnc69JM0tZdzChkBc49vZL8wZ5l/F6Zr6J3dLCs3isBV14/Sk6FeQdDepuENypvDMg4fzdEmSTChFW/xy/nttdU7zLK4cB6SxAuq010xMA3XRTMTkNKLXg5TcG+b8cCtQgMQBRF4ACfqo8lXciPMbqn4OSE0F+M6Y2dtEpvJEVncZg33KBdQMYvKfgYhCxr5dYRayXzQTcYB2BW3iDLLiIWN7yzgDY9s2AtwCpPTmch7H48Ad7To7vpxkAb+xx8G09z4Pl6iYcpKOB5dKjWEksPIPBRMnxIFj9CHEiOlQ5FtfagclRTaM0FKxgWXLLbryMEtThuKcYDKbZAHoQdtpVNc6x1p6SUQn2w/D+HApUNMqhPlw4jA34ylmBFIEfGwDlASKrJPOglmYD6N9lQali4JcNyXLdAXl3gZILggVRAC8PuOlv+SDs8iRhe7e0lroJbN8KiJB8HmA5c5BsmLYuuQchMfQ6wvrLh4aXB+kyliR+3vJ9yaFElLzIkgUOhZIF9BzLL0842HvLNRzo/JbNXixX8uUQHUoIKNGjZDBnQAkFIz8NflMXQM4mRcO9FPzLGIHkbFZ8sJ1B2Ij6lsNP6EHzMDTs67jHrzvyGSRb3TTOHLGEmyA/Va2zvPtYfBJ/o6XHUIuEZo6o8JDfjUF5QVeQww5pyDf3GiYAVPk332I4/esY1GcPIJY/6w7+S9AfngSMSth/mh2QV/0JZkQJRd5lrPQTE1p+dwgKz+K1sfAcdivo2EuPIXMRzTSUH8K/yzsRBkSQxIoDc/yaSF1cwv1TEkVJFb3frmqEJ+o6ALqtNdMTAN10UzGeAJRe5pAUu2sKB+/qpJuwnOOeqnKV7XMS+0b7HGeZIEYcakETFpUYg4pPYkWr+CSrbjE4UMFFieWCht8KLqI/5wbemOlGvPc2Jg00gOspGcWgadNZ8CacVAzzehNOIqZfRunJh3yjDmPAk9iF1c3SO7yzUXosgAkGq/zn97Ab8ymGJWZzAKXHAoqkp9YzhewbrBJHOOWq1lmsvrGbcnXTLB8IpgDH7priswAECeL4aRZM0dCkpwRhFG7rXamSTxAhWXWWD2/KWVlY0EcBqyIBYIOhXssw/s0CRwr+l9OL8mBUzkXPqvo8YJVj1UlkSoZTV3QOWEDPoTkyGk+OrZez+agN7FLgzeg9FQkFwYgY1IfDhGiNvFuwPPGgqrsctkPDu8sZemi7cpai5R0HSiYIq88C8eWCXpTMKLD9dCyyhIk+J8XnwBID+TA4Zwmi7gAL7ul7QPMfcsE5gmlRwklD5TSQ7qocl2BqDP+vGPitmVB0sgj+5nBi8E+dAFe1VPknRi2qaMtZf4iOuOIAg72wAkRlOxYdrP45DJxlwXNBFxYc8i+FOCFBzg1Wjb+Flfjc6wwCdEeiGk6fCYK5DwP39GmE+WRMYOCfMRlUsP8Qzp9TFQ9LyUXeZbyO7e1n8J+bEgsQdSToupffHcLiCRtcJqy/5UKQD//S7BHNXcmr/VWts0jreRATgeXQH4cTZ5KoA+lwIPOSngDottZMTwB0003F5DSgNARM0BOH8x4fwCMmILoZUzJANxZKAAgeU92EsBe6adEsQOEZDKhpMLigK8hnAgj/mn8pxDsDdJPMuRHirBxUga9sn8MKd1Yf4vsJ5hN1mOP4CdazvOrPn084iQFP4QgGEwcDCBFg9KT0b+FZDCLyexh2+BS23wu6pG5A+aEAwn1aZzn7SNX+WQ4LIsYSwixzWlV2M+bUoJXj/OZMlVEKnKj6T5ShntI7HFLB5wJYgEYYazlTC6d4pECedQ4U9I+E5Tf388SCXssHb3ddlRSIKTmgpEAON6FAk4JRVu1XwGbkVXBiGiKdARnNqKJLIKe2pK4EVdApsCb8/jLmHT6nQLh+qtbLgn4FbSftkxINShzob7MkJKaAMcnYelZQeMqSoeXD0fLqvuJ9oqSDoD7UASD8/3KBN/p8qJLPBr85dEsGByJ4j2IGgKg9C6QBcwr26XtDGH9KKqnKz+FqNLhOWhYsEaAOgNM+yXH+zpoJjv93OO9B1f5Z/ruga46cdKCmEZMAorykSjgNyZYfkhh/CEpDg7WEvycMft4Vxs7DIIWUAHDOfjZ7xGcARthg7zAmBKZhfD5zHPH/mXeRLYhey2mKb0rXs9xrjP6YDf3md+O1xXKBFUgY3IcoSgneVHI8yLsAlAQQ2w8lQ9YOvB5TccHhvMeLNXb3FH9faxpmJMghKziUF+pDwLqtLdMTAN10UzE5BGi/eQoc0QtgCn8IjihUAq5qlarUrbnT4FiHfnsMisrY9iHGnYR4yFdvneMQoIqDAaizBbi/NnYR9tXMcdiP5XwQvE4S43kItXGL4HUGOP1d3uUQeN1MUIdtvzVninP6e+NOSAF+ZKdy0DfqMPgje8AR9gqYDEvgCHsF/BHdKObFoB7thnNgj1mALLZv174AwgMuot6Ax4sqxlnGh1Abj8fG2TjYTbr4ZFDRfq84iDfm+ipSSH4I9phFaMmb5gwm1U2zPAEgyIOreoJ3YJw1E9CeOYmfSdhDcEQvgH/3XayWslkAwldzPQDWFfCU3gH/7jFwRM3j2sh58O+WZgV4EsDgPgr6Rxb4+1PugDPiAZjCHqJwVCKjEWUJgn/7iMLvTx7hnQB/yh1wGmW+lFGFcJZ/+wjzS6JU8qDYnzTEts1UiJ+4KbH27LqKar/yY9vYJ6neks/A1m4dUHQAOjbeAqfxVeZ/Ff0yIS9SAjYZJBVj3m1IvcYVkPmxbe7nyUBlShAyYr4HaWGPoDH8Bbgf0wJdycd4kiSdN3tfto8o4EH+nWPStiMegH/7sMLPj43et8QBJTUrMfMQHEhG5enfIX1ejqh58O/AYJ4zMslnQeQCcmyb/t1j4Iicl4497S6H/5zPuQD3N7RBo/FFSDO+D+kJb0J5/hc5/Mefdlf6HkfNQ1vWJIe62V3s2kLXHiZYRUJfdvcUNJXOgl127WkqneVduuqmWWgsI0Es/J157Rj8lx7Fa0/tevz92uIXweMJcNKB/EshcHvx2pJlfAi2hEVw1qMQWOZdDOpt/gDYNjD/hkWwHQjw+aOs0RDYDrD1EczfEUBWoIkg2FuV27a3BiD/EhsAvhICrxOFwOja4/HgvELeZSyCeB0Bfl61sYtQXz3HiypW/xw0lsmuu+sXoakICzY1DTNgsX0F9mx9G/ZEvA+NxhfhC1s64HTZZc701pLPrufs2rLfhEmBPgOg21ozPQHQ7X+b/eY3v4GRkRHw+XywceNGMBgM8JWvfEXxmo8++gi+8pWvQFNTE6SkpMD69eshJycHxsfH4T/+4z9Ut/ulL30JsrOzITo6GjIyMuCpp55Sfd0vfvEL6OjogA0bNkB8fDw0NzfDBx988LHOhRIAV+oVVWn4/WaEpWjJyjeWzqlL0luxOldfqe6vsyFW11WnLmnvdWK7W+T3x19XxfTLK/7+qB7VtR0bb4G7fAyai9TPy+PFG7HXob5vXy0TFjqHFbvikwyzezbIW/GNZern3ZI/zRMA6gaQYJinbIy341tzplTXt2dO8uoqh1QwzDXpFPjTx9Xfs3RJX8CXO8jhHQrsd84AdCQOqq9nQb5/x4j6+5o4IPZtxqCyI3FAfds7RqAu5TJ0bFX3dyQiZaV/+7C6f+uAeO0mnDnwJw0J19al9YrPO2mIJxei9ZWJ02AM+3CF701DEVzYdeLjb5sF+Vrr5RoAapSg/pRR8efJkgRv3pACAkT4fp+5H/wpd9TXp92F8+bz8KahaIXfGPYhlOd+AfzpE8Jri9M+Kfyet+bi76RZcO1psWDHrqloVnj98NrVf7+uugDk9IbAWa/ubzecg6yxENS2qfspCbD51f321oDQ52wJwN5+VAFWPW4XJi++WnV/vRW7Hy0F0+rXZMsMFNZ8GYzhK7+Lb4QVw+nSS9Caq762NWcKKvK6QU8AdFtLpicAuv1vs5///OdgMBhg165dYLfbQS0B+M1vfgMGgwEqKipgYmICnn32WTh58iSEh4eD3W6H3//+94rXf+ELXwCDwQDt7e3w7LPPwrFjx8BgMMD09PSK7WZmZkJiYiLMzMxAKBSCnTt3QkpKCvzzP//zH30uvAMQ8afsZqB8OKIXEKcbvaDuX7cg9NXGLmIbOnZR6C9+Mij2xy2C5UIQ7OvV/Y6wV1SFu+T4fofhFeF5VbbNCfdti1+EnN4Q2OLFx0bMIkWnglD29Vscp1t6FDG5DsPLqmvtMYsci1vrQwYly/kgtucZQ4fTPgmOKMF7HrWA8B/G9e9w3MNZgHKJa90ROS9YO8+DPa9lmMM4ltOAitY7Ix6Az3QLnBEPhH6nUezzZfWB0/iq0F+X1qu5bZ/pluZ64b6ND6Buz3Vtf/oN8b6Nr2r7Ix5AUuzbqr5Ow/PwWvxezX37zP2rv2+CfTsi5xUDv0TxyuFcGmudEQ94MiiHAHHBLwb1EX4fIufhOxtzodPwvKp/2+Z3Nb+Ltrpp4fXDvm4BYXIxAn/MIs7cCH7D9vWLmr/vvCvi37fD8DKYb4XAtkGwPoFdHxIE/g2LYh9bWxsnvi7md4eE1z17zCLOE2n4tyT/RPhd/Na2fHCsE19bKrMvgJ4A6LaWzPBJH4Bua8d+97vfwePHjwEA4Pvf/z6oJQAffvghfPe7312xdmxsDAwGA3zzm9/kz/32t7+FzZs3Q0NDg+K1R44cgdjYWPjXf/1X/tzMzAwYDAZ48803+XPvvfceGI1G6O/v/6PPhRKAVMMrQJUg6fF7yA5fArtrCkxhD4V+U7jYV7V/Vug3hS9B6bEAmIxiv7VjTrxvw7tcuEvB+CMT+jIZltS3bVyCvCshyBLt27gEude0/ZYLrOp/JghF8wNg9TNVZEZHqPW+yGcqaupnYO9Loxz7XFM/A07bpOZ7TkPBDuc9yJgIckVVGhoWrg1bUlT+vXlDMP5uAw/8iH1Ga703b0jTbwpTf8+zw5bAZ7ol/Eyyw5agLv2Gtn/P9Y+977pdV7WPzdyvvW+t9YZ3IS7y71V9+YYfwgdRWzW37cu8qb3v1Gvan6lsDsPhuAcZ94LSXED2bc3zllN6yjtBNEzuLRzR3PcH6xIhz/AjVX/c+n/U/B67rXc1/dXN2tcPq39O7Dcuia8txiUw3xL/vrMN7yLHv2h9xBL6IzT8WteWq9rXlqLTQc3rYmW7+Lyzw5dgffwvhd/Fv4lL0vw8Kwp6QE8AdFtLZvikD0C3tWmiBEBkP/7xj8FgMCjgPfPz82AwGGB+fl7x2u9973tgMBjga1/7Gn+utLQUSktLV2zX6/VCenr6H338f0gHwFU9Ia4YRYs7APaYVSp46xeh9FhAWKVzRC+AL2dAWPF1GF6Rqv409EuDvywxcIb/pepaW8IimIY1KngJi2DuE/tr4xa5GiepGxdcZDR9xxCjK67Qse6Db5ozJ9X6prnAEamdCrsuUQucLcVTNKqkWWQiYeLuwTzXC+CBnwz7TfMBmhXjvCFwanQINCvZmTe1K/xafiPrEGjtW6uCn3pNe99alXLat0YVPynuB6o+7ABka257tfd8tSo+H7wmlieifGUDz5qfJ4P7rJgBYEJxntI74ip+5Dx8Z7NGB2DTu+CIEqxdt4AzRsLrB+uUaXQAyo6Irx+1seIOQG0c/r5rNToApiHt60PWqLiDYEsQdwBq4xfBfFO7A2C5EBT67TGLUHI8qPG+LMDW1ToAomtL9AKUW/QEQLe1ZYZP+gB0W5v2xyYA3/jGN8BgMMDzzz/Pn5uYmACDwQC//OUvFa/98MMPITw8HK5fvw4AOFcQHR0NXV1dK7Y7NDQEBoMBfv3rX/9Rx08JgGfXZSFO11U9IZwBaCqeFVdNP2cAACAASURBVGJ0G9ggsMhPOHoRTtefNAS+LeeEOH5/VM9Kjv+4E+CNOwG+jaehbns3+HePqa6tbQuAuU+MAXa24BBybbsYp0vMIvk9IVToZIPBJBImmn1oLprhugEO5z0uplZTj7MA1U2z4LRPQku+Ok53v3mKD1+6y8e4WJin9A5XB/bvvqv+nrFBYOJ1J1Gn5UPAIhy/P+UODrMK/aNiX9IQrk0W+LcPgy/7NnRsuq05fyCcIdg+rDE/MMgHfEVr69JvCGcE/DtGtNcnDYF1VwiMht+t8L1pKIKuHcegY+Mt8XlrzDb4t49ozi/4t49IMwBU9SctABrgFW17N2OKYsO+PBEkZh/6Pglw/P60u3A+54JwBqC08Fkh3ny/eQocjnvC60OzBedjmgvV/V4n/t7qq9R/Z25vQPz7bsBBfxEOv91wDrIHNGYA/AHImAwK/bVtAXA2i+cPzDdDwtkmjwevi1ozAGWHA9BQoX7eTUWzYLF9RTADUARnSnrEcxc5U2DN1WcAdFtbpicAuv232B+bALjdbkhISIB/+7d/4891d3eD0WhUff3WrVuhs7MTAAD+6Z/+CQwGA9y9e3fF6z7/+c+DwWCAR48eCff9y1/+EpaWlhSPl19+GYgGtM10DxzRC5AdvgSOaGTasbswAXDaJjlLEPfnTnMtgJa8abDHLICJ+ZqKkaqvqhV5qSWWoCWwr1+EhnK8iVW2IWNOY+kcONYtQLaMFca36Szi+yM7wW+8CA7DK5BteBcchlfAH9kj0X0ySk9PZCcG/5vOIl7bNgm2fTPIAhK/CKaIJWT5aAiAaYgpgPaFoN1wDmwbJL+9NQDZg5L4mLOFGIqWoDZuEZzNeAPP70F/wUWJYrD4SeTnLjqNf9dbiZ1kCWpjFzEpYqJFChXlBokWtNbDWIBsk9BUOrviPSeGIBILczjuIRsQo2QkbYD95ilwRM1DdtgSsgClj0t0ooyrneBAchpQr2UYvIUjnPWFPhP/7jHUSmDQEP+OEXDK/TvHeOW5I3EQnBHkm4eOjYzak1FY+lNGwRnxAP1GZMPhNJYs2OV+YrthzDY0rOs0vsrXdyQOcipQ3PcDyDa8C07jq5hIEqMNSyCcRmnblJi4w/zgy7wprZd/F0mgK/XaimPzJyNHfl1yD1TuCEDG+v8FaeHvcRagC6knOaUnMQgpzosYfLL6OLOS/Ng4HajpFvi3D6/Y93LdAM7qwwJ4gvcQC1B22BI4I5EFSEH3aRmWZgDY/72WYc4yRaxS2WFLyCKUxjQqikbhXP5FePaJdsYC9AjSNr0F5flf5MxWy68dLXlIJ+yqRh76ljxiGFviLD81jdgds3bMQb2V2LTw+lFfhQl06VEpCaiNZb/R2EXwupFAoPAMBtK2ePTZ4vH3u7df0hUhlh/6/de2IwtQ1ihSfNoOKv22gwFOEWoakliA+Pq2AGTexW07G9ha2nc9Fg7ye5DO2NkgHVtt3CJ4vIxc4CzSl/rsAeX1oxwphaubUPSsqRRnAbLZ+9ZYOsepmkvKn4M9W96CtIhHyAK0tQNOVl7mgmttJpwzyg5fAkcUsgC5qsb1BEC3NWd6AqDbf4v9MQnA5OQkGAwGeOaZZxTPnzp1CmJiYlTX7Ny5E1paWgAA4G//9m/BYDDAzMzMitc999xzYDAY4Ac/+IFw/6Ojo2AwGFQf1txuOG8+D9/emg9/E5sE396SB6dLL/Eg01U5DqdLL6E/Pgm+nZgPZ4p6OI79hOMqfGsb+r65vQCerLnCOfGt/jk46r0O30wpgL9+Yjv81W4LHPVe5zfwqtZZaM2ZAmfkPFIvhv8lBvgyOA+H+UQdRoy/jN//QnQDfMe4Gz4I3wivrcuEC+lnwO6a4sF429FeeGAuhEeJ2+HV3EJo6uqF7MEQZI2h6A4lAJwGsDHABYHMN0PQfrgX5k2F8GjrdlhMs0D7oV7Iv4Qqolyl84wkaka0oOWHAnDUex2+nmqBn27A8z7muYbKyUzAjLi7SR/A7p7iswC1HkzASCnV7sLkgAsoOe4hPIPUg5masKsSlVbd5WOcZ91djsG7q2qcB4U0B+CqHJcCPxYschpIOZyE+OSJPpQ4/+XiYFSBlj1fl9ar1AugYFyuaEt894xGlFewcwclTv0911G8jFFyynnvaRucd1+uOpwzsFJzgCULdSmXOb/+CmVdUr6VaxfIgnEuukVCX3TOy7dDA7qk0kuJDDtWropM/uzbXD2Yr6f3SSagxtWKZUJq/EFc/yT6Zu6Xhn3ps1vmkycAvJtUhLSyrspx/l3x5g1J4nQMguYpQhEvd/mYpPRbI3vYsUtFyS0xXxEffa0PBQarm6RrBiXJ/NHOFG4PSWq4pUcxYKZh/JIT+DssuIhBds4N/I0XnUbu//weiZM/95rE6W8aRtrOzHHk+neH+TnN595+TARIzIsKBxkTQdgTDKDq77D0PL3O3CcJfpHuQH43XlfyLuO/+T1M2+ScpI9CeinFTzK18Y45LvQlpxguO4ydRqt/jiuyc7VfpjNCAmpEMEDBP6mP0xyRs2aCf876DIBua830BEC3/xb7QxOAv/iLv4CwsDA4ffr0Ct+noQPQbuqENw1F0Gl4HvIMP4JOw/PwZlgRnMvtAmfNBJy1XIQ3wooV/jfCiuFk1RV4subKSl94MZysvAwVB+bguPMavBG+cu2T1VfA4bgnpqw0XpTw/IzWU/6vN+YonI+qhzcNhSv2fWB/L+T3hKDtaC+8bly2b2MxtJ7sBdNwCOyt6m12R0sAMseDsP9kL7yhst5/sBeDjEvsBn4Wb9Zy5dGDLb0rzzu8GI7su84hQDUNM7wTUt08C9XNTBuAdQS49kLYQ3CsQ350eQJAPOo8+GcJgNt6FzUESAcgagHaTKgfQLhuOX3o8g6Az9yv4H13REq88QQtWaEDkHKHB/bLNQQIxlKXfgOryckjnKvfETmPGgMFQ1wIjCrdco0BCtx9uYNYhSc+fcbFTwG05JO6C1w9d8916bhJJyBxgKvn1qVeA/+OESXfPYMmkYgYbv9VSYNg6wAX9JJz7eO+hyX1Y1lnQ+Lxl4JxX86Acj1V+ElMzdwvW/8QnBGsis86CHymQwb/IaiYL/s2+HfKePwj58GfLKlD82CfEgBGMUvCX56iUfCn3pW+D9EL4E+9y4fRz1q64X4C0wEIfwRpm9+CMssXubAXdRdpbXMRClDVNKDqdotlRqEx0lgqqftyHZEYpY4IsW5ZLgSxy0c6IrHY5aPfp7MeO4CkA+D2Ik9/7nVMBBwtSq7+mkPYAciYDEL6TBCqjwag5gnG85+AOgCmYSZO2I8wIXkBwe1DilDzTeweynn+va4AWM4HUeOkBzVGuD92Eeor57CA8GSQwwjlOgCNZfh+VBxEocGGcqX+SnPRDO8oFlZ/GdKe+D7sMb4PjRHYAThT2M27i+3pEzJthgVoz0QhMJ0FSLe1ZnoCoNt/i/0hCcA3vvENiIqKgsbGRvjP//zPFf5PwwzAnXiPaiD87EY/2F1T8OwT7QJ/O3xxc4eq74ubO6CmcQa+sFXdfz++DQcrwzWGfCM7FTAfjvVneP/7EfWq2356zwEw94XgqbQDqv6n0g9A1p3Vh/yeSldf/3TqAYQBdaOYUOFZSbWz6DQmA59PUV/7zPYDULUfIQ4VB7C6V9mOFb5aH3KfV7XOirm6c6cRmsWq/gSzoIfTNinEbLdlTfKgzl2OQmKKDgDjfhfi9FPuIFRFMFvhTxkVc8ZvH+HBvxDjzwJsTb8GVl7Ilc9w8mIs/Bi4w/xinYDEQc35hY6tYu2Ejs39XNxMeF5acxcsCRDOH7AkgHdkZErOVMn37xR8XpTUmftxpkSWANB8iNcyDP400UzJXVYcEMwAlH4J9mer4833Z09BdfOscNalqRS7ASKdEV8tQu28bgHOvz4gxPg7WhDm52wRzwBkTATB1qnurz4cgKyxENj3i7fvEGzb4w1AQZf4uL2uAIcPit6XynbxbFVL/jQUW59T1aSgGQDRWn/6hK4DoNuaMz0B0O2/xVZLAF5//XWIjY2FyspK+O1vf6v6mgcPHoAaC9B3v/tdMBgM8NWvfpU/V1JSosoC5PF4IC0t7Y8+fkoAasM/qxoINxpfBFfVODRGvKjuj3hR6GuIeAns7iloEK0NewF8iV1i+kPDuzzg90R2gjfhJHhjj4NvwynE+m85B43hL6huuz76JcgeDEF99EtCf8ZkUEzjZ1wC05DG+qiXEEPch5XAjx5nQPFJSdm46HQQGiLV1zZEvgQVB1EEraoVg5yPHmdATQMG/gQPEjEv2WMWOIOQw3EPCl4d5EkAdQTEDELzGBRahrGyWzYG6f/jrnL4M/u2Ju+7FmONI2pem60m+/bqPP+rseF8LBag1Vl+VmPaWU0H4L+075yB1ZmXVnlfCatPXRIa5F1124UjfD3/HjChOZoHETL5RC/AdzaJWYASE5c0NURqGmbAHiNmu7H654RsWqQjIvTHL4pZejZo8/hzFiANHQAtljBbgsa+4xch/1JIk72o8Iz4vIhFTOhftwBbkx6q+lZlAYpagPJCHQKk29oywyd9ALqtTdNKAH7yk5/A5s2bIScnR8Hlv9x++9vfwqZNm6CxsVHx/NGjR2H9+vXwL//yL/y56elpMBgM8P3vf58/9+jRIzAajXDr1q0/+vgpAdgR/gDUAuE04yPwlI3BHuP76v6IR7AnQuCLfB9qGmbEfsNPwBtzVCzWZXhlpcpv7HFk+EnrBV/uoPC4UqPfB/OtEKRG/7XQvyoN6E3x+j1R7yOO95qE7y06FYSCLoQA5XeHIDVK/dj2RL7Psf9V+2c5lrniYADKOwMY3DfOaPJ81/qmOQTIVif9TQPCWjzfBAvxlODQcMWBOQUNqKdkVHt96Z1VuPg1+Oozb2pz8Wf1aa833fr4OgDpN7S3ndX3BxybyP/uH3De2jz+q2k3aGozEJafQXlqfdOS2rNleNW1K2ZBGPsPJRWaOgAx24Q6ALFxv9T8Htc0iL/nfwjPf96VkKZfi8d/721tHQDTiAbPv3EJ9vZrc/lr+fIvaawNZzoAGu/LajoAsXEaOgCxq+gA6B0A3daYGT7pA9BtbdnTTz8N4+Pj0NXVBQaDAdra2mB8fBzGx8fh3//93+HXv/417Ny5E8LDw2F6ehq+9rWvKR7f+973FNsjDL/f74f79+/D8ePHwWAwwOTkpOJ1v/71ryE9PR0SExNhdnYWPvOZz8DOnTshOTkZfvWrX/3R50EJQEr8Xyy7GeAjbdNb4LRNQvoT31f179nyFqRtekt97ea3oKZhRrg2Pfz/BE/UYfAbLwpnABQJQMJJ8CVdBG/eEB+a3Znyjuq2d+x5B/b2h2DHHrE/YzIopPm0tyKTR4pgfUrqO5B7HQcMc68iFKjwHA4fFp7BocTdyeprdye9g8N9foT+lB3GwJ9Yk2goWKi9sG6BD07aXagmXNk2J8GAKsfFOgDRC1wrgCcBMuw3BYNavO++nAFNpWCtCv2qfPd/AGf9x1Uh1lz7h1TpV9Ew+K90DzTfl8h58Jluab7n3oIh8GXexGo+UbyyTo+Wkq8jch47QSWjCiEwb+EIisqV3sFhXY0OwLcT84UdgK1JDzW/x5qdrvWLUH5Im+e/oEvMl18bp63Gq8Xz7zC8DFljGh2ADdrrbRrdh9q4Rci7LNYBsK9fhKJTGh2A9YvYARDoADiiFyBxm7gD8O1EbR0AfQhYt7Vmhk/6AHRbW7Z7924QMer8/Oc/h5///OdCv8FggBMnTqzY5rPPPgsmkwmioqIgPT0dPvOZz8Dvf//7Fa/7u7/7O/D7/ZCQkABxcXHQ2NgIP/3pTz/WeVACkJcxsgIzSjzeTtsklFm+qOovrngOiitW4k2NYR9CWcEXwVM0Ctbdn1nBj240/A4qIm6D23gQvDFHwW+8oKT5NF6QAv+Yo+Dbcg7q0nrBXT4GNfUzUN4ZgMKzQcjs/CqEG5X7Djd+CKlnvgo5N0JC/+6zX+UMIO2Gc0oav3bk+N57OwS7LorXWy4EIe8KDgLm3MAOQN5lpAUt6AqCyf/nK7i4jeEfQk7Dn/Nqf8WBOV79r2qdxXM7FICaxhloKp0VcnUTewrpBzhtk4jnrxoHZ82EcLB6f/YUr/K7rXfBaUPmluXDn+0i3vedqCMgnhEY1eTS9+YNiXn8dzAsvGjbjItfCyuv5atL6xXPADAcvcjfkTiA64UaBiPg3y7et9eirVGAQ9WCY9uJVJuiuQsaoObsTMsYmrx5Q+IZgN1j/PuggACVjPIOgNZMyX7zFJwp7FafAQj/EAptX4amIvXvcUsBdrpEePT6yjkofhIHfFWx8g68BnhdYq5/ERe/swkHdUUkAO2Gc5A1KtYBcDbgILCogOBsCAjXet3suAX6J147igmKzptmAEQ6AM2WGSgtua86A/BmWBGcLbioOSNk3YtFLT0B0G2tmJ4A6KabilECUGk6DxU5fwrbtixB3PrHsG3Tj8Fq+pxEL1k9ARXZz0DitocQt/4fITHxIRRXPIe0fvZJKCl7DrYmPYTYOPRZTZ/jVIfehJNgXTcI28K/B3Fh/zdsC/suVET0ce5+ovv0RB1W/O2NOYqc/mm94LUMg901BeWHcPDPciGI8BsW5G/IfA/WbfkVJOx9D9KPfRX29iMPt2k4BKlnvgrx5vcgOvFXEG9+D3af/yqYhpEGNHsAKf+I19t8E7m9s+6EIPMu0gSmnpbWJ2S/B7vP4vbzu5HJw9yHXYC9t0OcHpS0Afa2/DnE5b8HMU/8Ejbveg/MTX+OVH+HA1B+SKL8q2pF5o6q/bNQ3hmAqv3IgNJQPsf50R3rFqClQKL1q2nEGYCq1lmkCnXe4//KmVeywxCH3ZY1yWldnTUTSCHqRApRzgLEuOPd5WPgT7vLdQAckfM4KFsuCYkRq4zkv8tVhpHnX+ZLucM1B7wFQ0ou/ch5HNLNGeAMNgrOemLLIcpPc/8yvvx55MtnFJj+pCGlfkHKHYkWVMakw/07Rjj1aV1a78r1LDGh/fuThpT6BzKufmI/4se1QynShexH85L+AePx9xaO4LCu7LwdkfPg3zkm0Yiy91y+/fbMScTpM2pO+mz4PACjA/VahsGfPKL8vNLuSkxQbFiYvgdu610UiGMK0+7yMUw8oyQu//3mKfCUIe3nudwu+OKWDmiMeBFhgVvehtLSL4GtDuk9mxnLT3b4EtjXIctPZdsc2PbhIHyzZUbSCYlBlp/yQwEoOYFUvvWVc5IWR+wiBv9nJCVut49pfZBWR0MAKUCvh6DmEOPpNy5xmt/sQfx9p08Fwdkk4/nfgDz/pANgGg6BrVPG878BCwSmYYnm094q6YTY4nHfe/tDYDkfRAYi2XG7fRj8F55DmlKvM6DQL6ivnoPCs3hexU+ivoH0vixAQ8UcJxCobp6FpuJZ/r46oheguRCLAbW+aSiq+jKkbXoL0oyoA/DsRj+cLr+MXcKqcc4ShroOC/z3a83REwDd1pbpCYBuuqkYJQDW3IvQloXCMEgLNw/+dOSP95SNgbNmAoVjZFR++7OnuBLt/uwpyccoBn2JXeDbcg5hPhHd4Ah7BWkfSchLxu2PHYCXJf+6K+Dbcg58WX3gKb0DLfnTnO6uNhYFcwhy42yWqPRI6Cf3KiYHeZdD4NqnpOmztwYge4AF/CQEFs9o/jagP202CBkTQdjbv4wmMB795pshXv2nYWDSBKDOQMFFFPqpjZNo/rzOANcJKH4SOb6LT6J6cMlxNhTMgv/yzgA0ls0xgTWk+WvJR55vuws1Aqr2z4Jt34xCVIn0AVpzZJ9JFAaLTtskeEpGOZXochpQb8EQf85q+jwkPfFjiIt+DNu2LEFF9jMSfKhkFKxZn4Ntm34MceseQ9ITP4IK8zNcY8C6+zOQtOFHEBf9GJI2/AisqZ/ljDLegiGoyH4G/VH/AElP/AisGZ/jdJO+rD6wpn4Wtm3EfSfFvQPW3Z9VsNxY05+GpIQfQlz0P0BSwg/BmvpZiftexolP2HgK/n3Zt8G6+7OQFM/Wxv8ArOlPgS/7NhcCs6b9CSTF/wCPLY75Tbf4sXOufca8o6YBwKk7ieNfdix8UJcx9XDtBfaQazQQTafiXNhgry9ngGszELMTF+6yDKNoW+kdPgfAYT7lY4p9ecqQDUrRCWJzItRVItpYdznyxvPrAqOUdDiQX95WNy3B09xTfJ6FOP7t7inkp983wyFwxO1PcLiKg/hbKDoVhMp26fdRfFIKnIlqN+8K/sbNfRjsk3ZH9gAm5LlXMYjP6cXXmIbwsbcfn88eZNeBW1gQyLwb4joAlABkjuO1wDQSgj2hAH/93tu4PveqtI3ca7ht8008xtyreF3I7w6B5QImKyXHJbawotP4NymIlx7DR/GT+P/KtjmoacT3inQAyg8FoLppFt/T5ll+DSAtBdIEIFKAWt80OO2TnC7Y7poCZ80EOBz3OPe/s2aC0wdbcy/qCYBua8r0BEA33VSMEgDP9m4BLdw4eEpGoS1rUh2OkjsN/t0CikCm1uuPEGw7ohvhPyJ/yig4bZPQXKgOEfA6A+L2f3MAcnrFNH+OFuQCF/lt/gDsvS2GANgOSIEABR/5PZI4WP6lELi96mt9dlbZPIKdgMJzGACUHwrwm7zVPwdNxQLoRP40F2AjGJDdNQV29xQPvkQUom2mST4nQOrBTtvkCvYXq+nzqrCuCvMz4LUMgzXjc6p+6+7PgjX9KfW12c9gcpD2J4K1nwFfzgBY059W96c/DXV7rkNF9jPq/ozPKdR05RoE3sIRnjiork39LPhyBzX2/RSn10Q133lJZyCJBfCZN7nCsUK/gFXv69Jv4LHJufipu8AEy1ZoL6Tc4RV+r2UY/CmjXNvBGYFVfF/2bUm1l6g7KalgswC+nAHwp49LuhBMGdpVPaEQ+qLvgatyXEoA2GyJX84bz5TCKek8YbsKz25sh8aIF2FPxPuwZ+vbUFT1ZU5r25I/zRNZxzpU+q1uRsEva8ccNJbNQa0swffaMQkoPYa/j301cwqef48HK+k0gO9sliXa8ajGa76Jv01ngzKBr23DCn7WKAb3ch7/mieQ5590ALJGkeqTFxA2LIKjBSv85j5MApyNyu07WgI88Hd7lfoEXjt2LkqP4W/f68AOQJbxIdjXL0KdLcCTgfJDAWiwSjz/jnUL0FQ0CxUHMTFwOO+hEjDTT3BEsw6hC7uyRVVfhrTNb6EOgPFFePaJdjhT0sMphFEpXPo827IQRlhWfFlPAHRbU6YnALrppmKUAJRFPMOCnmVDYVEL4LbeFQ8BRs6LfYZXwLPuiAbLz8voDxP4oxe0aQDjFoWDdLZ4RvMnouJjPP/CIb4Ni7C3X9tv7sPKX9Yd7DZkD2D1b+9tDEpEa2vjFvmcQMlxJvpzYA6KTgex8s8SAa0hwJp6JvhTj1AgUgGt9WFyoDXkR+rAlATYXVMS9INVdjPi31Bdn77hTfAWjgj9GXGvQ0acYG38m+DLvi30Z8S+Dr7cQciIfV3sz76t6dfUGMjqg4z1grVxr0Nd+g3tfZtuibH0SQh7Eu47R6wTQPAooX7CzjHtfafc4V0DgmBRl4GoXkVJeptpEtV8qycUMwAkKGd3TbHgX32mpDV3Gk5VXIY3worVZwCqxTMAjaUY/DeUq2PZvQ7Gh1+t7vd4A5DfHRJy/dv8AbAdFCfwWXfEPP7thnOQeVdjBqAlgDSgfnW/a18A3D4xz7/lfBC8TnV/nQ2Df5EOQLMFf/PC2Yr8aSgt/ZJQB+B06SVhgaA9fQLKii6BngDotpbM8EkfgG66fRqNEoBUwyv8RiA9kBbOVTX+8agXDe+CZ90RTZ5/Lb8pfAkqDmjTAJo0aP4sF4KaNIBZoxpUfBFLkD6tvd40hBCArDuoA5B/CZOAvCuYEGjRAFouYOufBoA/epwB5Z0BsHZIrEBaNH+V7XMcWvHR4wyw7ZsBu3uKDxILP6/wJXDaJdVgT8kofPQ4Q5EAuMs1aF+Nj8BbOAJpGn6hL/w98FqGIS38kcD/CLx5Q9r+Am2/JotP9m3Ntav6V9MgWIVpR6idwJiVtPya66PmOZTIWzjCYTa8c1AwJGYBiprnA7/yWRCq/Lutd3GuRINV6lvbNFiAkn8i5vlfvwjWjjkxy8/6RSg7osECFL+omWjbErRZgDLHg1AjYPlxGF6GzLur6ADc0igwaLEAxS5CyQltlp/yQwGh3xG9gHAqwfvqiF6AxMQlVV+n4Xn4zuZcTZ0QfQhYt7Vmhk/6AHTT7dNoq3cA5pFWUhT4hP2luIJveAXcxoPgMLys7g97BXyJXeA0qisBEx2eFg3gqmI7Gv6Me0FtmsDhkDBAsMUvgmmEYYfv4MPch4+sUcQFa3UAik4FOfSn5ATCfwgWQDhgsUDSAlb+GQyoaj+KiVW2zUGtB2cDhNSL0Qs8qHPaEb9d65lSQIBcVePQaBSItxlfBE/pHaEAW2P4i9AYLlgb/iL4cge1/eZ+Df8L4C0c0VyvyaVv7tc47hfAWzCkeV6eIm19hNW49jWPLWfgv6YDYBlWaDt4ipDelf7WWuuqGgeHE3UkeAJAlLJsYFwrofybuKSPpQNgCl+CkuMafPfGJSg5ERQn+UZtLn9ThLYOQPqUOMHPNryLZABa+15FB0DruMsOixN8k3EJyg9pFwBs+7R1QjR1AGK2aX4f9BkA3daaGT7pA9BNt0+j8RmAnT2CGQAcBBZBAPzrr2ry+HsiO8X++F6oS+4RUjc2WJEGUNQK97oD4PEIWvT1ATDfCoGzSd1f245MIFoYf9NwSAghIBzw3tshyJgMIhRoFAf9zLdwHkAETfA6caCx6DQOA+dex3U0HFx2GP0NgvOutyJ0orJtDqqbMPi3u6b4sKCtbhpaBNSK+81TPPCnIU55AkCV3/sb2lXXlcHf/QAAIABJREFU309oA0/ZGNyPb1P3x7eJfQlt4DP3w/24/cK13rwhsT9uP/hyB+F+bKvQr8WVr7lv2nZMi7o/pmVVDQOxb35VdeXVOgSe0jtCqJ0zch6hW/Kgv/QOsgIxvQctCF+tb1oaBGbfA4KJOe044CuqGNtjFuBb2wvESsDbHgr56nmlW5Do1sYtQvFJMc+/LX4Rcq+L+fRtG7Q7ALufCggr/LwDoLE+95q4A6AFT1ytwm+PWYCKgxr+dQvIAKZRxU/cqtUByBN3dKLmdSEw3dacGT7pA9BNt0+jSSxA3Urax6h5xAczOkFvHqNuNL6KXP1hr/AhXwzyV/L4u40HOaWnP7IHHGHo///Ye/Pgts7zfPSQlEiRErVZqy2JFEECIAiSAEiAK/aN4r6AFLUvXETtC7Vy30mQANrYjhPHtR15Gre9vbXcXy0iaRPn3mSmEzu1mzSUbWWpp2nvT3H+uG2n00ncqfLeP97zfgeQ8B06TjP28J535gxBvPgOzvJ9B+/6PK7k/wXtG68xRBKXdQqb1wjuLgPh8KpasEnQcigEfocEl+fIiILfjk2Apq5HoPbWRcG9D43/wguIxkFNegymr1FCAdIMPc4DYNsfAtUsGvV5k2GsJc6MgQFsRZIw2od2APkECq7i9+muIXpI0XlEIHr02AynECmo6DwighReiDB0kNKjWBZUdkCqA3ZkRBE+MSMKdeVY+lPZhsY/kYdVNyISSHXDPFQ3zIPTNQNNRXNxEIHN+jmG2uIpE0s+xGwAGX52/xx4Kiag23QO3k4yQafwKhQJP4BO4VV4W0AMcU/ZOJzSn4a3hcf1faou6FN1c3Td4Csc4uvVPeAvGIA+VVdifW4P+PWDsvvnYvGLdfTcfWedAL/mBpzedZT/3bpb/Dr97Am+LmucQaMm1D+FCD5cDoOsCdTzmu2zxhlyk7d0lCE5EcGX18J34FvVWA7mKRsHl2M6zhF0OSRuiUZTYoeyyRAUeQD4PQD1lsSObF05NrzzHF2fB2FyfR4+WZ92IMLF+re1h8DJafK3HghB7lQYXPX8HgDd9QjYOvggA+pxPo+Axx8CLwcEoLYKoT55vQ21FVgGyLsudWW45nngCM16fg8AreEW7Sx3rlVq+xQHQJEVJYoDoIgiCYQcgHLBK9WBK5uyJQWgV/DAm8Ju+KmwAd4UdkOv4PnE+t9l7O+qbxN6wSm8Ljqjr0Ob0Ps/+t1y+1/uu3/ferntdxm73PhewQMvCD6oF/4ccoR7oBLehDKh/3NxXf7/+t1lQj+ohDchR7gH9cKfwwuC7xOtk3LBqzgAiqwoURwARRRJIIoDoGzKpmzKpmy0KQ6AIitNFAdAEUUSiOIAKJuyKZuyKRttigOgyEoTxQFQRJEEojgAyqZsyqZsykab4gAostJEcQAUUSSBkANQtbcLanL6oeh8BPybusCXfhi8qzvjtzWHwL+pC5t7V3eCJ2U/e03Nvr7CIfBv7oGaXRcYMZG7GtFEbPuC8PBBLpTvD4G1LggV7QtgrcW/5ftDkPt/TEDR2QhUtmJzYMmJMJTvF2ExDyNWPiHlFJ2LMCx9/aUIlB4LIxb/OWy+JVbewosIyam/glj9BVdF7P5RRPDRDkTAkxQA7SDqtQMRyJ0JM6ZQzTBCfe55CfH21aMI9akZQZ16DFGAHj7IRTjQ0QjCC46jXjOC3//wQS4U9EegoB/3V3Qe+QKKzuJ7Dx/kIhJQF8KDlhzHczOdDDOOAdNJJAwr60SegPL9SBj28EFuHIEYcQFYa4NQ3oF6u3+OvW/3zzHWYGt9MI4HgBiFHR5ECyrvWIAX71eC1zyGDcRWhIZ0V0+B1zIO/+//8xTYaubA7p2VuAUsyCVAHANETuU1j4G7egoZZ0XCsYcPcpGt1jLOxvkLBhh6zcMHuayxlZBu/AUD4C0dharmeTj61glkvNUPIgKO2AhLY31GkQVYZMT1GUeQIKtwiH23p2KCjfeUjbMxDx/kgs8wDH7tTTwH4wjD1d/zIs4HX+FQ3H4JiYeO2105iWtCdwt8xdJfdt6lyNzrLR1l14X0cdfSMg5O1wx4S/EY6brS/54yRPFx2aZh3/99HrSDEYYC5LJNM+Qnp2sGHj7IBadrBpyuGXavH20Gt9YHEf3HOcPI5qobcP48fJALlkPSGrbVzEFlG67hsk5cpyXHEc3KfDgE5R0LUHo0zPguHj7IRRSsk9I8Lz4TZuuk+HSYNfHHrl/dddTn38TX2kFxHQ7hOs7+A9x/7nQYm/gHI6Caw33lTeDYrFdmQBUMQ95kGHKnkOlXPY77ofWvv4LPBN01fJ1/KwL6y9LzQ3c9wtay/jIeZ9F5kQvkbASMvXg+hlNhMPZgY7/hFK5jgvi1HAyB6aTU8H/y7WOQ/YchbOxvRQCEsgMhRvb38EEuYv+7Z8G2D+8HsYDTPSXIVqdzhhH9UbP/wwe5bA3T5wgJzPDGAHzrH9U4Bw3DUKk5pTgAiqwoURwARRRJIMwB2NIJ/g0n0fBfcwiN+fTDEpIPOQGpB1Ef4xT40g+DL/0w+DecBP+WXqhRXQVfIRps7uopsHvR2CSoSodbIqyqCCCaTUVgAaob8UevqnkeqlrmwVofhLJO6QezrBNRQQj9x9iNBkTB1QgYexBZp/ACvi46G0Gj4goaEbrrIkLPdTT8NSPij/dF/LFXj6LxnjeJxn/+zQjkTiESkGYYjQxyGPImw5B/KwI5C2HIm0AjQz2KBkn+LTQMNMMRth/ddfwuGl9wFY0aOsbCixEwdoeZA2A6Kb0uPYqGlOEUGhHmIyEoPYbcAeYjInHYITSyKtsQPaSqZR4q2tGIsBwKsWtM7MEOzyzYaubAVjPHjEPmAIiGv907i6zCdUH2nsuGqDAOzyxCiFoRK544BZzOGQYtyox9wzC4rFMMmpKYab3mMfBUTKCDWDmJ/4tOA0OxMQwjvn0swo1xBNxVk8h2WzwkGdjkAMRs9B4Rnvn1g+DX3WLY+L5CkTnXMMx0nqQA+15fscSm6zOOSI5G6SjuR9yHzzAMfs2NuOMmp+DRjc6bzp0di/gdnooJCb6T8PxFR4LOi64TGf7ktLB7JDrcdH9cVpHQyzUjGYDi/bLVoDPocM/GMULb/XNg2xcEu3eWOQA0H6qa5+PmU2XbAnM2KwIIUUtrtbxjAcyHcQ6WdYbA2C3B3JYcx7ledFY0os9FmNNL61R/CR15/WXR4L6CDrTuBq5JzZBkwKtHRT6OG+jEq0cjoApKaF7qUfFzY5Jzrh6T2Lx11/C17rroANyQuD3yb6G+8IJ4PJfw+Aqu4ho29ogOu7hmjb1hBvVrPhyC0qPI9UHOUFknXhPLQTTyKwII60vPx1iIX2tdEGw1yPDtcOO6dDmm2TPVVjOHzlvFBLuXhOpE999lRThnml/u6inJYaa1J86vqpxuxQFQZEWJ4gAookgCIQegcm0zGv+ige9J2c8cAXIAYp0BFvlfcwh8a4+i4f/kOfBrbiB0oBh9okijrWYOHO5ZcFdP4Q+ZZ5ZBV1a0i9CWregEVDXPM0OiugGNWTIqis5FoKJ9AX9oj+EPrbEHI27GbjE7IBrWxm6E2qT/C/pFqM4bERbJy5vAH3v9JQnOM/+mGP0XDQwGCTqBxobuhoj9L0Yg94bwtXYA31ePSc4DEYSRE6G/LDkjRWfxr/4SZjMKruJ3m7rQATCcEs+rV4qSlh5Dw6n4NBoRppNhZmhVBHCrapmH8g7MolS2Slt1Axr/zHhrmMfovX9OivzWodFHkWEyAF1WdORcjmlmXDLHwDHNDA67f06KMDqmmZHrrpYMEE/FBBocMRmBWAx7X6Fo2BcPgadiAg1qUU+f9RlHmKHt1w9KxjxF+0sxU+DXDzJngbIM5EhQpoBlCbQ30QGIMdbpOJiRbhjGLAVlBUTD3WsZZ0y8ZFj5Cofi9u81id9Hjov4HXR+FOl3V04yo5/IuFhmwzzGMjDuqknmWJGzTfeDOWlilJdeu6unmLFPhiNlg2LnAUHM2mrmMAotZgBoLlUEFsC2D+FoK9twrlEmz3IwBCXHcZ6aj4SYUVx8Bo374tNoFJPhXHxacnjpNUXf9ZdFh5kM/2uSwZ5/Ew177SCuzfybkuNN2Tm2LmcwK6eaFSP/MYZ/3iRmCciB1w6KDgBF+sVnRv5N/N/Qh4EFU1eYOeZFZ6X/jb14DnT+VS3zyO9xKMQydeSsVzfOYyZP5PWoaMfrWhFAUr/YtUhrk6B83VWTLOtj96NDT1k4MvrJ0SMn21uKGVlyRNm8JCfbPKZkABRZcaI4AIookkAYD8Cq2vjofmzUP9bgj4n8e1MPgn9zD/i3nQZ/3jU0ikpHpTISt2QgOtz4Y0YGJxmfDvcsGvqN+H91wzxzAso7JMx7yyH8kSw7EBNN24/RcNNJ0dA4iQZ/4YUI/iifi8RtrCToMhrdhRfwrycpwBwCyg5oB0XjYgCNAvUYGv85QcwQ5E2iQZE7E8b3RiJxZT/qcdw324e437xJNG7yJqTSAspM6K/g54rOS+VNLLoolgXRRhmQsk68HuQElB3AsovKNnxd1okGGUUYKbNirQ2ye2GtD0oOQC2WFrgc06xcyO7HEh8qK3B4ZjHiWDYOdj8ake6qSfbXXSm+rp6KN2JFI5dFwEtH4w1bEXOeItxUZsQyBaLhEsd4S8a8aAiT0U/ReYrYP5pNIG4Lf8EAyxZQdJQ5FTFOBjkYsQ4Ei/7rboHPMAxO1wyLxtN+aAwZ92Rw0XHR8ZDeUzEhZUrMYyxy67WMS46WbRo8FRNo/ImlHHT9KepL5Tt0P4jZl71fPcVKgBJlgihDZK0NMoO0uhHXJhmrZOxT+U9lKzoDFPEuOYHrtOS4VApjPoLR/6Lz0hrVX0IOjKLzEeYQ5N9CB7noHDrv6jHM1lHmTn9FctiJhE89jtm4vAk09DUjmAGg0jzNCOrzb+Fn6T3iA9HdkAIAnqQAe49KfShjqLuBx2boE53zXinoUHxacgCI18PYE2YOADnmJcfDUNU8z8r5KgILYK0LsqwKOenWesy4kOHv8GAJEJXxOTwYVLHVzDFnwOGelYjdyuL/slI7Wn9EGieuEcUBUGQliuIAKKJIAmEOQGodi/Cz2n7xdZxDIDoJvnXHwLf+BNTsvgh+9XU0gowjcT9CVDJCkeHYTABFj631QWb8k95aH2RRbFZOIBoalkNiaUFMb4CxG39czUdCrJym+AyWA5lOopFh7MWonf4SGtwFV0WisBv4Y190XirX0Yzg+/orYkR/XCoVYCUH4l/dNYz2q4L4OYpGUolC7hSWM1BWQHcjwuqMi86LxsUlNHQKL0bijpFKmCgjYOzFDICpS4wuHg4xx6f0KOqYQ3BQuj6UYaFsSlWzVFpQ2bYQ5wBUN86zqL/TOcMchFiDkiKO5Nix+nIx0uiunpKM1JgoZdxr0bhnZT2UISADWozOu6unmMFOJS3MgbDEG9Xe0lHWI0BGOWUA/AUDzAByV05KUXfaj+iIeJICUmkPHYcYdSeD32cYlj4vZjP8BQOSsyBmCpgTQIZWTG8Ei96bpPIeMuipbju2jIf6AchBIueKiPTIgLf75+L6NFzWKfYeRYPJ6He6Ztj/1KND86CqWSKWK98fYpm6sgMhqXRPjF6XHcD1Sa/J2LUcwtfGnjBUti0wY774TFia+5dxHRSfCbOSH6rvp4i//opYgndL6smhtagdFKP4E2JW4Ja0HinCT04ArUXVLP6lTGD+LXxNJURUFljQj8dCRj/rRbiB7xVelEqXqCyv5LhUAkSGPq3HivYFVqpHZXm2mjlm/Fc1zzODv7oR1yeV7DldM+i81wUxiyO+R866wzPLovzkSNPaoGxb3HwWs7SxTjI5phV6hQlYkZUligOgiCIJJDYD0JbUB07hddAIS+AU/hLakvpYtL981U1QJX0bcoT3oV74P+GFtAbo23MM6/0NwxBQTYEz9S5oku6BM/UutOhmpYijawZaNDPgTFsETfI9cKYtIkuta4b9yDXr58CRHgVN8j1wpEehrmKB1cwedV2G53Z2QP2q12Dv6vuQteMd0NfchooANgrX2EIii/A9sK8VWYK7MR1vOhkGnwvZeNUp9xgbb0G/WNN7UWICVqfcA1tmlDGMaobR0HA2IROwOuUe2DZEwXogJDkEw1J9sXZAcghy5tEAsXWEwLZBGmsLhFidceFFNILyJiKMGVh/RWp+LLwYAR9jQL4HTuF18DnQsKdSCYqulndgFNZ8OMSM/33WBXZdHOmLUFeBxj+VVpV1hlhZQWwGwFqP2YFmPTIJ0z1rNAVZ9LGk/EVQbfw+7E25D/Upr8FXNgWgy3we3JWTYPfPQatmBpyp0thWNToELitGnltpPiTdA2fqIjQXzDJmYk/ZuDifFqX5pJmRsgdl49CWNy2NX30XAirR4DEMQyBrIl6XPSH1GSQFIKCaBOdqaa4GciakCHxSIH4ui+O9lnFWKhFQTcbM9UVoU02xLEWLblbad9oisgAbR7APwjKOx7ZaGtuqmWaOia94CFq0s3HrqLlglhlwnooJaC6Yla5L2iK0aGdZcy851mQguqsmJQPRPQtNhiC7Lo70RWgqnGOlI4/Ng/ogy75Z69DgbyiZl9ZoRhQazOikVzXPs+h26TE09qk8r/QYrkNagxpxDfpc6Ljqr2BmjhizaQ3aAiHmCKtHI2Brj1mD66PgbAoxx5yxda+PgnqVtM5ypzALkNXzCjypehey19yHutQ78HROBzR19WO5zwCy+bI1mon79iQFmJPu8Uvfbc+MgqsuhFH+U9ibsM+6IJ3bWnx2lR5FR/2w7zI8t70D6lbfYc+uQt9XoaoFo/wN5nlwpC+y516DGZ2A8o4FcHhmH1uDzQVSZtXpFNcR6deI60ycLy7bNAR2j8fN9RbtLMtKlWufg9zMtyAnGdfwC5mt0Ks/rTABK7LiRHEAFFEkgZAD4E3uSEwNn9IH5atuQorw64S08t3GsxBQTSYc26rBiHBzQWLa+aZCLC1pMiSmtK83L8AR72V4K7nkMX1K8sdQ6LsNtdULCcd6/Fhj7HOFEurd+0KguxYBV11ivb01xAz4RHpHC+pz5jHamDuDPQbqcYwqagciYD3AGSs6GNoBCcmEnAIqRSo6j45HovFeX4jVTBedi7BmSlZicTwMtVWJr0ujCXstYrMAZZ2huNKPqhY0TBKNb9bPganqJUhJ+vgx3VtJJdBlPg9NxXMJx7boZpnRknDfohPQqplOPBezsTymLS+xvkU3C4HsicRjVVg+1KaaSqhvU2EvQqua892qKfHYEh97IGucuw7a8tD5CWSNc/ftqZjgn7cKo/m8Y2vWJ2gKdc3ERYmb9YnvSbN+jjX82mqkHgDq0alqwbr/uvLE82mfdQGM3VJpj6lLquun7JTPk3gee3whKDofAVc9X1/QHwFXQ2K9LYBOgL01sd56MARPXbwNySmPz9XvpZRAU1c/2AKJx7YJvaAZjoCLswZd9XhuXl9i/T7rAhzyX+E+u/S1t6HekviaNphxXfLuWYsWG4FbtImfq61qzLDx5nogZwLK9V9OuIbfFkzQkdUGigOgyEoSxQFQRJEEQg6ARXha/DGI35zCX8L25L9NqOsUXoU3NxaAM20xod6xZhGjkBy9c80ilgSlc8anR+GvdxmgU3g1oX5z9vvgSI8m1NnXRsHUFQb72sR6W2YUis5GwJ7J0a+PQv6tCNjWc/QboghBKNYZ506HWVkC9QHIjdVdi+8XoD6BgqsSRKh9Hf/cCHGEYFCNPegElB3A6L8jI/FYR3qUlQWV7w+BtT4I5sOSA0A1//x7sgjbtt3jzodv7igG5xrO/U69i1mh1LuJ9WmL2DjOmy+py+u5+159F5FwePrUu+A1jf4O+kX+caUtgrd0FJyp/OPG68K/bp6KCdn9x9b0U/8NIcrYvbP8NZq+yDIAlW0LbB5Qoyo1+HLX2boo6zchZKrSo1LJmrGbvwbtmVHQX5GZ55lR0F2PgG0Df42qR+XX2bqi97lz9a8KDdyxTuF10F+WX4NF52T066Lw9Wz+s+uJ3e9xr6lzzSI27PPWUdoi9tnw5sPqu6iXWQvbN/0D97q8uD4XFAdAkZUkwmd9AIoo8nkUcgCyhdeBIkHS9hvQCj+CdSn/nFBXJPwAfrZmG2iS7iUem7QETucMX5+8BE7XDGiS+fqfrN8BhcIPE+ozNnzEHatJWQJTVxjUKXx94YWIrL7gqox+1RKDClXNIsY3axwWo/rqVfyx2kERxWRCwiinmuiCfrGxUebYCDGl5Dh+dywsaumxsOx1ofKf8g5EIonlAaDmQ7l7kpH5S+58+EnmTtmxy80Hr3lMdj65Kydl9XI6n3FEVu8tHQWNsCSv/zTfnbz8cbur5PUux7SsnhBjbDXIT5A7E2Z1/Q73LH8+JC8h2s8+zAzRPCCUGmr4lRtvPoxIP5aDITafCBbT2BMGjdwa65ef5+rRT6CXWWep2/lz9f1tO7n71go/Av3lZdbgSZlzS16CH2/cyX12rc3kP7u0yUtg2yezBpebD8lL4LWMy86XdWt+wb0u0dTNoDgAiqwkET7rA1BEkc+jSBmAZx75McDNlfIG7Fj7bkJdp/AqvLlJLx8Vdc7IZgBko81rFuGvd/OjaFt2vceNdNvXRsF0MiwbodNfioBNJgNQ0C8fXSRkIIYIJNb+E6cAN3K5IcrQhQhytOCqRBKmv4RZAN6x2ddGGY+AsVvkEejFDIDpJDoActelvAObqWPhCFnzZws2dsplALbufI87H2QzAGmL2AMgE8l22ab5kXAaL6OXm4vuKqz95431lI2DU3idM56iqvwovZxONmJL583NbNzFch6ZTBshAFFzNpX0EEoT75440hcZeVxsBoAa8C0HcZ7IzaeyA9jwS1CYhIRj6sLsFC/LZs+MQsFVmTWYGQXtoPw6yr8ZAetG/hrO1PMzAHc1Ru6+ncLrYOiTf37IPl/WRuEbe5Z5dnHWmHPNouz9dqYtYsmXTCZMdq4ukwF4aV0OKA6AIitJhM/6ABRR5PMoUg9AZ8J60fZtg1CheZZT822CU/rT/FpTFSK48GpZmwqx9KCR0wPQZAhCl+UCvJXE7wGosSWuwfV50HDxejl19F4k1+LV8Hq9Yv0xpz7Z2YSNwKpZ7AHIm5BQfghFiNc/YG8Nwd4Qop7k35SIxAhZiMqBbPv5382YkHuwEdFwKszYgo3dYe51qbdgg6L5cIiROMU6APQerz65qWgOjLaXICU5cQ/AyfIL3PvZXIAR6qYiTj16AcIXtugS1zY36xHqsIVTh9+qmebW6LdqkB2Vt++ACpF0eP0qrZpp2R6CVg1/bJMhCO5Kfm9DiwbRlnjn1axHI57XK9OsRxhP2z5EzyKyKCJxs+2TWWNF2IdjOYjoPjQPCNWHELfqKhLPB78dM0lFZ7EMjSL/hRel/3l9No5mbGbn1fDbW0NYSsep07d1hCB3OsxdJ/a2EGT1vcLtAWg92g8ezvpvE3oRIczPeb64sRGYt85qqxC8gNcDYLS+BA0l/D4b274gNJgS61s0iN7EnatqRISS6wEwm17g9gC05+4HxQFQZCWJ4gAookgCiYUBDaRfBFfy/wJt0o/AlfIGBHYMMaKjCtUziBiR8gFDjDhV0Mfg5AKqSXCtvotlP2mLEFBNMtIkT9k4GjFpi0zfVDzHGGcdnlloKhT1yUvgXLMIzfo5Vo5youoifCkOSeNdMLheZuzAEgrQEjgyouB3oOFCeOS1VQsiks4S2NdGwedG45/q5tuEXhHFY4mhfBBMYP6tCLhrEGFEs2oJbOtjUIKGECY0b1LcJrCpN3cmzOBDbZ3SWOtGRCehDEH+Lcwe5E6FGZJQ3oSIRX4Lm4GdTeL4lCWwbRARSMQmS/W4RHBG/ABEtlRyQkReycTrYl8bhX1WxGgnNlK6RhXt8ZFf4g8ghBJt8hI40heh0YhIMZWtC2C0vQTZ296BnFUfQN2qO/D85gAct11kkKFNhiA414j3M3URGkzzrE7d5Zhm6Cba5CWGbsIi2LZpbBiOmS/UUE5Qos36OXCm3sXxq+8yNByXAw1xNpdSESnHWzrKIDUJSQf1d6FVPc1Qc1zWKQhkT6Be/O62vGkG0emumpTmsjg+kDPBcPgJ3YjOq1WDUJ7EkkzoRaRv0c6y2n1yQKRjW2TGIJHnNRXNxY1vKp5jqE0EE0n8Dda6ICOAs9YGoal4DhwZUXY/aysxyk9QsBWBmHmwX0L1IbI5v11cZ+I6qq1eYJCXxFth7EX43aKziO5TfAbRclwiklbsGiLGbO1gzDxftQS2zCjYW0O4PsQ1ZW+N0W+IMgc8bwLXYOw6s63H8QQHuufMK7Br77uQnXYfatPuwDPZHdB6tJ8xdLvqxHUirn+fR0IBKrwYAb8jJD0fxOcL8RyYToahtlp8vsSss5LjWBJ1zHkJvrytnT27sre9A0brS4xErcE8L62DNYu4blwzSL5H6yQtfj7QOnJXT0GrZlpaJ4RIVSYxSRNilTYJ10kgS0KzKtd/GVTr34ac5A+gPvk1eCGzBfpyexQeAEVWnCgOgCKKJJBYJuDKLTOwY+07sC71f8OOjT+ECs0XGX50hepp2L75H2DdmgewY+MPobzgSwwP3VMxAeUFX4IdG38I6zJ+Aduf+BGYS19gWObuykkwm16AbdvuwbqMX8C2bfeg1PIiM3ys9UEwVb4IW3fcg4z1v4StO98DU9VLcUQ4xa6vwhO734OMDb+EJ/a8D8WurzIjpaDuNmzOeh/SRV1+020o349GfunRMOj9t2HT3vchbcsvYUPe+6Btvo1kYSKSTpnQDxvU78OaJ34JGzTvg+rwK4yZlxB9is6joUE45bprEg557nRME/AIZgJyp8IMZpA1+oqfJcNff0XkFBDJh7QDIopQPzoAxWfCjCRBuHgyAAAgAElEQVRMOyByF1zEY9Fdx+PPvynChl5ALHJjt4hD3o2lQIQMRKzIVK9degwbhqnMg0V+xdIgahKOZWOmMhEihyIyMcoaVLXMS7wBMQzQRAZnrQ0yNmFioY2FrySyMZd1irEWE5eEu3qK6eOgLkViMiIfI+x8p2uGMaYy9tRYZlTiJBDhORm0ojiOCLcIg5+NEbH1iVGXOA8YC2/Ma4K5ZURN1RI7K/EpuKy4H7peDg+eI11bIl1zumbwmtdLxr3DPcvuBV2/yrYFcDpnGJEXYf4Tm3YsKzRh0tP9frQHgIxc8xF0qInkq/g0vl96TCr3of4TgrYlbP+icxLRXeEFae3QfC+4Gomb47lTuJaIj4PYuAmSVzOE0J/ErE1rTTOCTjUR7+WIPAA0jkj+iG2bCPiIj0B3Dd+jdUfs4PScKDqLWTZiIac1RfCn5sMh1oBvOSiR8hHeP1sjzfMMhcu2T2LdJn4U274gWOuCEl+KG+8/8aoQ0zZB6hLzL5HJEbtvLHs0Y9YmRmoR0tavvclYs4l1268fVBwARVacKA6AIookEHIADJsvPwb1mZL0MZRrn4MK1TOQnPxfcbo04VdYFmEZTwgpl5L0MZTpv4zGv/mPEupLLS+CyzYNpZYXH9cnfwxG20uIlW2ah9SkX8Xpk1P+C/Q1t8Fgf/mxcpSU5I9B03obSo6HQV97G1JSEuhbbkPRuQioO24/dt7JKR+D6sgraLBcwzIghkEuRidjjRD6S5F9cgxUwXA8D8D6KNjbQqgfkMYRwVH+TSmjQAYSRUbpu121GDnVX0ECIoIOLTofYchARWfjI7BF5yJgPoI12sSeTJCNtMU2AVe2ovFSV7YQg1GOEePSY2HGDBuHC58ehXrzAnPY6i0LEu9DTEanumEeXI5paDIEwRGDb95UKDGb2r2zLIpPePktWsk5sO0LSvjnSTHj3fgZxkEg6lo0EkOu1zKOUXc6tlTkECBHwpMUkDgGxGNv0cwwFmJPxYQ0Xtx/q2b6sewD+26RD4OchjbVVBwfRotuljlF7qpJaCqei+NPoPMiY76peI7dE2caXldrreSMVTUjdCcjmCJeh31BqLfE3M+MKNRWiBmh/cgHUd4hOQCMaO5wiDmSPncoDu/e5wqxeWfokwi+is7h/NNfljJUrrqYebw+Cq6mEBJ9iZujRVwnj+D4587geqg+HALrRtRbN0Sx/GcGG+5Vs2GWIWB8G50h1meTdeoVeDL3XchO+zFmALI6oOVEP3PyXbWP8ITUoENcfBodG+IoYOftCDHSvZLjYYmrQ1wn+6wLjN38qOsyfGlbB9SJHCZ7t74DBtvLjO23qXgubr40Fc4xB9nunX2MP6W5YJY5tbHZrNh1wki/LOPxnBcipwWRg2GmK0aXhfwBVbm9igOgyIoSxQFQRJEEQg7A7rQ/hkRNYbnr3oLtm3+UUNcu/An06k9DbuZbCfWqjd8Hd9UkqDZ+P6E+e+s74HJMQ87mv0uo37v1HTjmugTtwp8m1G998j3I3v5O4n1vfwfK94dgz5OJG5h373oXjD1h2L07sX5X9rugvxIBVyMHB7wxxCL86nGRFfh6DHPwKBo1vNrlvAnJYcidCoNmOMLYS7WDaLjwxrsa0bihyD+xFpecEMsvzuNGjcL6S5E41CBCCio9hmVQpcfCcfCPFe0LsM+auOa73ozMzDxc+KbiOW69eYNJKkVJpG80oKHKq9Mn8ji5WnuejjgGeP0oVKrTJvRyxztdM9BUyBmvnuaeF5E38XofWsUeAF6NP5FDyV1Xyg5UtmIGgKLO1Y04lne/aisWwHxEiu7TPCBIT2MPOotyPQBFZzFKrr8sEdlpB3HuFZ3nc224mkKgGUYiLl4PgHaAvw4czcgDwOsRcDWFIK8zcQ/AWykl0HqoH1y1/B6AovMRbo/APitmznjXpbZiAY7ZL3F7AIq8X+Xi+FPPB+9+t2ixV4bPG4HOamDXWOJzU03x+TKyJ5QMgCIrThQHQBFFEgg5ALuS/or9EEjbbyAn+QNYt+ZBQl2R8AP41tYiyEm5n3hsygfgrpyEvTJ6l2Oar1/1AXxzZzEXSi9940ewdxVn7Or7YD4cguzVifV7U++D4VQYslM5+rT7slj8tvVRjF5ex+j9wwe5jJVUdx3fl+UQGI6w0oWcIEJ5xpYHyaKjrI9C4UV0HorORhgEKTGnFlyNMEfAcAr3rbsRYWVBVLNdfBoju7EwoOYjIVkUIUf6IlS2LvD1axa5+OaO9EWsZZfhfZBFjUpbxFIZGVQpubG2fcFPv+80xMuX5SCQQT9yuOVRXeTO25G+/HlTvX9FAMt6CNnHcgj7OXjX3L42yu65+Ui8A0DvmY+E+Hwa66PMySy8iNF/7SCW1egv4WvuOlgfBc2QzDzfsDzOf8FV+f1n6uRRgHjr2ym8DoUX+MfmyIhC6TE+x4EjIwp/s6uYiwK09UkZFKA0REeTm2uyaFipdxHRSobTgouGtfqu4gAosuJE+KwPQBFFPo9CDoA96Q8S/iDUJ78GOzb+kPsj+tP07VCf8lrisSmvgbd0VFbvdM1A/arE+rpVd+CnmTtkf0TrVt9JPHb1HSg9GoY63r5T74CxOwx1qYnH16beAcMpGR4BkQcg/6ZY8vPaKMsE5M4gN8ByY3OCYcgRWYQd37oC6jHMIOhuiFkFmfFFZ6X+Av//dQGNrQGx/OI8ll+UHMeMwI0ftDK24KLzCBlafEbqE4h1AExd6BTIYZRXtMvjwn9qfPP/Af2nxtL/BPu21gVlx8uNlcPi1yYvga1mTlZv98qPL+9YYDX9Dx/kQtmBELL4ikRecver7AA2tcY2g1sOYg9N8WksBVqOT4Oi/UXnRId0AB0C7aA8lr4s38WqpWXX0XJ8GWlb+DwAHzwhzwNQckKGTyN5CUqOy+t/Fx6A5e63p0we599nGP7UfBmKA6DIShPhsz4ARRT5PAo5AGPproQp4RfWt0KF5ouQJvzqMd0PhCJ4c5MeXljfmnjshlbwWsbhK5vaEuq/srENXNYpeH5Le0L9l7e2wzd3FMMPhKLH9KnCr8DgfBm+vDXx2Od2dEBF+wI8t7Mjsf7JDjCcCsNzTybWf3F3B+gvL8MTcFUi7dIOYCmOekzqB+BFJq0bkeE0Z15CENIMRxgKkO467oOLby7io+ffkvoH9Jfw+6mB2NgbZlHY4tPYnGnok2q1TV3oHFBDJxl+hlNhKN/Pj/hS5FMuQ8DNAKxBzHk5jgE5ZmjnGvkoviNdPgMgi7WfJmKvy0TxZTMAafzvdogRerkIflXLvDxWf/vy162qBRt7y/eH2GtrbRDKDoRk8eqJP8J0UpoHppNYHqYdiCzLp1F0LsIa5in7pR6NMEhcboQ+EzNhyzL9ymQItAPLZAAK+BmAxTwjd99O4XUoPi0zzzOiyJcho/+bJ/kZgC1Pvic/F90yczH1LngtcozYd8FnGOZmCFyr73KzA67Vd5UeAEVWnAif9QEoosjnUcgB6NjZDG8LJugUXoUi4QfQKbwKbwsmOKU9hQ1jWePQLvwJ0/1AKIJfJ62CU9pT0KfpgbeTHhmbZIJu0znwmsfgVEHfY/q3kkzQZbkATucMnCy/AG8l0HeXnoNj9kvwq+TV8AOhiOnbhT/Fuui6IBxzXYK3kkoeGVsCh2quQNmBEBysuwJvJT+iTy6B9vZ+MHaHobOxH94WjI/pA/v7oehchMsj4KoLMTST/FuS8U5IJupRmdrkhpD0+UHJEVCPSU3EeZN8fHNXfYiVG2kH0OkghJOCfgktSH9FRDe5hMY/lQV5kgIsC1ByAiP+rATocAhMJxFCNNF319gQEaaWU/vcYJ7n9g80GhCnnlfrXm9ZkO0RYHX4nFr6RkOQq2sqwmbZRiOnrprq8Dnf3aLBuvpGE6cOv2Rels/CWs8/tkZTkDX48q5LVQv/u+vKMPJPiD7EyFt6FJGeSo6HobaSX8Nfchwdw9geAGMvNo8Xn8amct588PhCONcuRxisJjFh0//L1fjb2/g1/pph/jpyNCMPAK9HwNkUgj1nOD0AySXQ3tHPXd9tQi9YDobA5+Tj/JceDUODOTFWf4N5Ho54L3M5TAy2l2V5AAgKl9uvYpuGgGoycR1/zgR4TaMQ2DWaWP/UCF+XNa5kABRZcaI4AIookkDIAajK7YU+TQ+8uUEHP1uzHb69Xgd9mh4GHefX3YK+3B54c6MOfrZmG3xrSyF0G88yfZ+qC761pRB+mr4d3tyshz5ND7grJ8FrHgOXdQp6DGdQn7EdvrWtCHqLziBUnXkMXI5p6DKfh29tK4Kfrt0B39xZDF3m8whluC8IJyovwDd3FMNPMnfCN3cUw1HXZYZdbq0LwqGaK/CNPQb4yfqd8Ne7DHDMdYlB8VkOhuCQH/U/3rQTvp5tgIN1V1gzrPlICHoFD0T3GuD+pp2wmGeE/c39DAGk8AI2AsbxBDSFMNp5Q8oAULSdUH20gzEoPhskfHJnk8gDMCY1D+dOhUEzhPujvgAiFnM0x4wX0VHyb6LxT4RjmqEIgydlGOxnwqwEQ39JMtCMvfg+wTUWn8ZMAcsA9OF1MfYgugnDfV8XhRpbiGUILIdCUFu1wPSODMQ/p/rzuoqFOG6Gugp8n7ZGU5DhmzvSF6GuHGvWqxuwafVRDoJm/RxUtkooQ02GIDjSRUz7NYtQV4Zwi7aaOYacEsspQft2OtGBcKyJx+In3HVrLTbbxnEU6BGZhSA48bvj92+tD4LLNo3nJY51iLju1jp0fJzOGYasRGMbzNjAy5CVTPNxWP0NJfMMFrKqZT5uvCNduq5VLYjeROg0xPdAnA5lB0Kwz7ogzeO1eD+JC4OyQjQPis9gr4j+Es4l/ZX4dWDLRD4N3XXsMyHODP1lkd16TIL61F8R10Fm/DwmBzZvIsLQsmidVB9EB5syCXE8AetFlJ9BiTTP0RzDl5GJ+y/oxzmuCdyGXdnvwt7U+1CXiihAzSf6sYxuMALemPNyZEg8ANQvU2MLMR4RQk+y1gdZkzWtA7qn9ZYF1pB9vPoiPL85AHWrXoOcVR/A3if+DszmPwK7H1GxHuWNaDIEwV2FiFRO10w83wWh/FjG2bMzkDMRj/OvmmLcLV7TKARUU+Bc/QgPQOko6naPg2vVG5LuKRxTlXVScQAUWVGiOACKKJJAGBFY/mkIZE0wyDhXyhsQ2D0Ofv0g8gBovohEYIw0phX6NL3gKxwCv+5WPKScCK1IWNW+wiH8oYqFTlQjHjththPhDUEvNhXPgd2PhltX2QX40rYOqF/1GuxddR/2bkEyHYKVrCtfQEhIEd6wrhwxzWMNHzRG7zECo1gHgBGBiXqfM8Rq6IvPhMHnkWACbZlR8PgxMll4EY0T7SAaOVQCkX9TIvqydcZAiIoERZQ1oOj93jCiAqmCmDkgTgHtAEY/GYzohihUH0YY0fybCH+oHo8w3HTdddwvlWN4fPHwpe596LjoL4nQoSJUqP5SJC7ya+zB6K+6/TZszn4f0jf+EjbtRX4Fy0E0LvX+27AxB3Ubc9+HQt9tRn5kORgCfY3IzbDxl7Bl13ug34djyQEodiOvQ/oG1BucLzOs+aqWeTDYX4YtT74HGZkfwZZd74Gp8kWw1gbZPTdVvghP7H4P1q77CLY++R4YbC+jg1AbBIPtZdi6E3VbnnwPSi0vgrUODTZrbRCM1S/B1p24721bl6Ck/EWw7Qsy5BxrPeKz2/3SHLR7ZxncJjkDBElqq5mTYDhb8LPVDSLOu3+Ofaa8A6EhCaOfMPwrAmgwlu8XITnr0WEg7gXiaig7gNjzla1Y5mM+gp+nvg3zEczelHWig2Y5iM29loMhlumhccZe7P8ovIAIUY+WABWfCTN4WYrwE44/zV/qO6FNPSpF//MmRGhbsUQtZz4cB5OrGRHn7xiOoVI4QtCiv+RQ667jZ1RzYeZ0M6KwmO+mY9MMYfYrFp2o4KrYI3NOOh9ydEqPSaRl1AtReiyMTNmHQowLwXw4xBzR0mNhvKcNEg8G4f0zzH/xr7Ueib8Yvr+I/U8cFXb/HOOxIN4IxkshvucpGwd39RQj+XJXTzF4WnqPMP59xUPg1w9KXADGEYb37yvGZ7bPMIzP98Ih9hl/wQBU7e1SHABFVpQoDoAiiiQQcgC82/oSp4R3j0NF7rNc2vie4jNcyvlWDf5w8VLVy0EzNhXNQVfZBW4a3VT1EjcFX1uJDkBtVeLShxob/pjzylU8fjS2fA5+CZD+ChoW+bcirCSnoB9f624gfwCvhCdvMgw5C2jwqMRGYIIEJdIwZxO/9CFvAr+38CIaV8SoSuRKvLGuBoRtJCeh8EIkLgNg6kLHKL+Jz5+Q33QbklLieSFSk34FPicaqfra2wm5GXT1t5FIyvXVhHq9/zZUN8xDoS+x3lj9Eljrg4m5H5KQN8JU9VLisdaXoKoZHQee3uGehYrAAmLvx/AfNJqCzIirCCwwluNYfXXjvJT5oLFiZoJw+e3e2XhnNX0R6s1oIJZ1YsS+rnyB8SM4MqLQYJ5nJF5VLfPgt8djztdbFljdPxG8lR4NswyY6STeT8rYMDz7dRjpNpwSDV+xNyS2F8RwCh0E6i9x1cU7lK5GxOrXXcN5ROhVlAUglmvNCDL5WjdKYx0t6MiSA8scXZEHwHogxPpi9FciYNsv4vyLemdTiDXB665hGVHssTlaMDuhvxSBvP2vwO4970J26o+hNvUOPLunAwKd/Wj894iM2WvxujgyMEBAfRDmw7FM4xggqCtDh4wM/XrzI/fUImW6TlRegC9vaWfBi+yt70BJxYtg9yLBFwt8JEm8EERK53JMSzwAMYETrwVJ6rymUQysUNCGIvyWGCbgrPE4HoA2FQZk/PpBCDw1Aq5VMUGbrAnwGYahStWjOACKrChRHABFFEkg5ABYUr4IiZrCnKvvwo71P0io6xRehTc3FvAh5VLvIkMrF65OhLOTaYb75vaiTwWl58iIQnmHDFxlehRMXWFuw6p9XRRKjvObH22ZUYazr7uORor+slgWJNbiyzUn5k2GWbNwjhj5z7+FCEK502hUyTVHqubCLOq5NxTGiOuQlJHgNk5mYgOy7obYN9CPf8nwo8zA7j18/oTN2YkbK9uT/hQO1l2BLA73QtaOd6GifQGyt/G5GywHQ5C1I/H47G3vgN0/Jzt+7xOJOSWyt74D1vognzdi6ztIOsdxKOvKMXrPc1YbjUF+PXgJNuTyar7rLZix4mHK11VgaQ9PX2MLseg/QXeWHkXj1XAKS9l4tew+d4gZ/8WnJQdAd01sHhcdAJ5DaQuEQDOCn4llu6Yslmo2zK3ht7eiI2zrkNfzegScYimeq4HvpOceeOUxR5Z6AA7U94Of4+C3Cb2yvRN1FQus/IfXA3DUxe8BMFa/xOWsaNVg5L8tTwbn3zIOrWqOfvc4+AzDEMjiYP2rprgcAYHsCaUJWJEVJ8JnfQCKKPJ5FHIAsoW/ZD8E0oawcHI8AD/N2C4LKectHZXVe8rGZeHufrpux6eC0tMkL0Flmwz8YcoSWA6FZPUlx8OgkYEYJNhD3TUJi7/gqth8e10e3jC2/l81h1CcqjnRKRhDR0BuvGYYSyt0N/C7iRU1bwKPQW4sHWPBVXQ6YmFAqV8gO+3HCcfvTb0Pa57gQytG9xr43Aur70NF+wLsleFmsBwM8fWr70NVyzyf+2HVB7I6W82crL66cZ7rMDrXiPwHMkg8cs5mZZuMM5oRharmeVln1nxEHnHGfBgJ3Ax9OJ+M3djgXXgR+R94qE72dVGpHyQmA6C7jnNbM4zzhOuMipwW2kGcz3kTEfjwn3dgOc/o8mhYudNhWZQg9ai8IyyHAmTPjMKGPD4KUFRlkOUBkA0gZIj3VGY+yKEAbZVDAUpdBHe1TGAk9S54zWOyPABe0yifB2C1PA9AVU43KA6AIitJhM/6ABRR5PMonygDsIHPA/DmE/rlMwAyek+ZDJxd2iJ8a5tMBmDHPT50YkZU1qCzr41CWScf7tK+LgqlR+XhD2Progv6xXIgEY1Hd0M+A6Ael2qnc2fCjBmYDHv1mLzhoxnB8gfmLIjRV0IXkssAUO124UWJOCy2CdjQJ8+PsDGXb1Td37RTlpuhfH8I6lZzuBlW38FIt4y+rFN+PJf3YfUdsNYH+ZwT4rHJ8h8EPh3/geYTjJX7bk3yEphOymDOpyyx3g1jN6L2lBwXEZ6O4f2Uw8rXX5IyWMwRvCKSehG87SoZZ3QkHgY3bzLMytLyJuSd0eV4AGS/O0XU/w48ANz7LfxI/povc8+0yUvwk/UywYt18jwATteMbODEXTmp8AAoosgnFOGzPgBFFPk8CusB2MLpAXhyBCpUT3N7AE7pTvFTzdlYU8rrEWjRYq0rD+6uRTMDPYaz8FaSiQulx4NebDDPQ1Uzv6TD58KGVJ6e4BF5MIHUUKu7gY2SBf34mjUc9mPNNK+GXz0uNUPmTmEPQM5CmBn0mhE+/KH1IJZd5N/CsXtDYYa4Qu/zyiIczSFsqrwmZSp01yXDr+gcHvszWYn5EZ7J6gB1x21ITUrMCxFVGeCLPG6FXR1QejQMX3yKw82wswPMh0NcbobndnSA+UiIz+2wowO+tD2x7stb28FyKMTVf2lbBzb7yvAfWOuDshFhuQxAWSc/gm9fG0Wcf5l9lxyXj+ITalXxGdxKj2HtP9Xy8xxC+7ooGv9inX9cBuDsJygpE9l8c6eR/E53A+dV9hewP0A1G5Z1ZHXX5Jl+tQMyjnCmqOed2zIZgEW1kXtNncLrsgzIjvTluBui8M0d/AzAtu33ZJmAHe5Z2dJJ+dLKu+AtHZWN8rtWvZFQ51p1V0EBUmTFifBZH4AiinwehcGA5nRDYPc4g4xzrXoDAlnjiBZROAQV6mdBlfk25KTEogD1SM1m2TFwdKl3oVU9zZAnPGXj0KZC6nqm10xjs5sN/1IzXCz0om1fEJyuGegyn4cvb2mHulV3sMxjCzbSEQxovXkBHOki5GR6lBn/hKRSb3kckpIaI0uOhxEFaG08PKL5CDZVGnslFCAGA1oXQoOrF+ERWTT9egwGvwjLaQvEwBduiDLsc/U4RktVwTA2AU+JWQCxKZjQgawHsHlSs2oJrBuxOTJ3Ogx7wyHIWcBIa+4UIqhQ7XXehJgFCITAGgsh2hFizoV6DD9DBl9s7bfuWgSauvvhrZRH+BNSSqD5ZD/oL0XA5wlBe9KfxvFC/CplNQQ6+yHQmWBscgm0HcSx7R39ibkZOvqh5EQY9jcl1h+o74eyAyE40MDRN/TDIX9i3of9Tf1gORTi6jub+sHUhXOBV2dPiFKJ9Pus/Bp+vwPr83lja2w4D2tsiZ02rxfr9Hn16l5fSGKAviI5oPrLknPq3iePtU9ZLJoH1NiuHRCbdDmcFLbOEKhmseyIWLA1wxHI/sMQzk2ZsVXHFuT33YGNwi5eQ3sdNvry9O6aEKiOcHoAUnBO8PgN2oReMB8Jce9JvQVBBnj3vKFkXuQ34QMYNBVyOCe02Ajcok0cGAmoJsFdOcnnAdiNjcCBbE5gJmucH7TJmlBKgBRZcaI4AIookkCYA5B1Evzamwwazq8fBL/6OkLKiagR7LXuFvgLBuLwpv36QfDrbiH2f+ko+HW3EJbONMpg6gjKjuBBvZZxBgVKkHbu6ilEwLBNg8s6hZtN+p8g9JxOJG6qaEfox6qWeQa9WNWMcI/VjegAVDeiQ1DescAgF8s6sWa67ABifpd1Il665SBCJJYcx6ZIYso1dmMpRdF5hBZkcIKXIoxlt+hshEVTyRAjrgDdDQmznGAMc6fDDD1FM4zR/BzR+CcnIXc6prxHdBgoe8AaiMdjIBXFxsvcacwoaAfws4QQpAqK2OuT2DOgGYp3BLQDEkxo69F+eENnhA+27IS7WiO0HOtnGY6i8xFob++Huxoj3N+8ExbVRmg72M8w5Tub+mExD8cu5hlhf1M/u57mwyHY39wP0RwDfPDETvjGHgPsb0ZiNtNJvNYH6vvh69nIzRBVGeBQ7RUw9oRZrfuhWpHbYQOOP1h3BcyH8R4eqr0CX89G3df34ljz4RCDdTzqvgzf2I37/sZuHFvescDgH2urF0SkHXQYG0rmoXx/iGHqS7Cy6DDWVSwwuMjaCokbIdaZNHYjKRfjThDH+lwhBq1q6MOMUyzmvN8uNvKKeP2xmPQ0vugsQnkWn0HISyLwMvbGzNfz6AQQVr49E8cSm7TuBjp+NA8I0Uc9KpW5xWHtE5b/hJR1yglKpWw58+hoaoZFUrtAPI5/1RHMguXfwvGuxkdw/jsQLpeyaq46kScgBfUev6gXYUldtSLPgMgD4GpEp8jUFYa8zldgV5bIA7D6Djz3ZAccaJDmqs8Zf83rLTgPCNmp3hIzH0Rkp4oAwn9a65C4LpbTolk/x6Bej9suwlc2tkF9CvIA5Gz+OygtexFcjmlm5DtTxcBH6l1o0c2Cp2IC3JUIo9yqnpYCJ2mLCK9cJiH9BLInJJz/1LsQyJ5gOP++wqE4HgCXiPXvMwyDv2AAAlkSD4Br9V0I7MLntgIDqshKE8UBUOR/TP7jP/4DRkZGwO/3w6ZNm0AQBHj55Zdlx/zXf/0X5OfngyAIsLCw8Jj+4cOHEAwGITs7G9LS0qCwsBBeffXVhPt67733wO/3w9q1a2HTpk1w+PBh+OUvf/mpzoU5AHu7ILBzRIKUW/UGBHaOgF97E/wFA1CheRZyM74HOcn3MQOwrgVOFfSBzzCMiBPZE3Fwc4EsNPS9plHwWsahLW9a4gkQCWvcVZPgNY0yKFBnqgh3l7rI2DCdrhnoMZxhP6J7U+5Dzua/g5KKFxFLe18QmvUSbKNzzSI0GhCvvaoZyZEaTPMSNGNGFGorJcKkisACtAm9cTB/NTaRRbUT//qcIYknYF0UfGJE19iDRsL6Xt0AACAASURBVD9BaZpOopNgOIXGk6EvjIbLeokHwFUXYlFZhmE+JhlgBAeqv4TGehz8ocgjoB6TDH8qs8ibDDMngBwEW3sMh8B6NNhyp8Ks70A9huPzb8WUfoiOimYYYUwJWtGeGQVXA0KfFl6MgOqwBK1Yl3oHns3qgLaD/XhNziO5EhpkIreCJ8TIyYrOiuRLa8V9r42Cx4eGLsFYSkbZPUa+VHoUszZlB0Lgd4TErM89cKQjCVnpMSSzYkayeL/9DhxjPoxZnX3WBaa3x8wH82HEy4+F2rSLBGc0/kB9Pzy3owPqVt+BvavvQ9aOd0DXcBuqWuYZg3Lsd++zomNQ0Y5/fS4JUtKRgXPN1IVOpuVgKA6Skgx8guksPRaOu2420YgnuE7DKYm9l/DvGZ7/OSwLe5QXgvD8Cy/G94KQYZ5/Cx2+vAmE8ozltHDVh5jDSc3rqlk0/AkFiPD9ieiLzcVOiQ1bNRvGubo+Xq+7IZWoOVriv9vjDzHSO8MpXGexXB3ufXjdis5FQNt0G3ZlvQvZIhHYc092wIH6fjbXDtT3w1/vMsCPN4oO474r4EkKME6L2kqJR8SRLpG3VTfMM+K42OdPs17C+j9ReQGe3xxAGNCU+5DzxN9BSfmLDPe/uWA2HuZTg/CfLusUuCsnoaf4DLy5sQB+lrEd3txYAD3FZ1hWFZF+xqXn5mrkX6FgjK94CE5pT8Gbm/Tws/Rt8OYGJHcknoA+VRd8ez0SO357gw761D0IA5qtlAApsrJEcQAU+R+TDz/8EARBgD179oDD4fhEDkA4HIa1a9dyHYCbN2+CIAjQ09MDX/nKV6Curg4EQYA/+ZM/ifvcP//zP8OWLVtApVLBF77wBZienoZNmzZBcXExfPzxx7/1ubAegK18HoBy7XPcHoA+dQ83ndyWJ2JV81LRqinwlo5CqyYxnF2rZhp6DGfhbU4PgKnyRWg0Je4BqK1A3PQGEwfWsQLx02urE6fwySj02/llF4Y+jGgXnUVDRH9JJB4S/3r8/NIFim5S7b7uhsQMTM2UjmY+PCJFVolQicqA1OPoHHB7AFrQaKOMAkVhYyO/RefR4OId+96Tr0Ayp6yi7UA/tyTD50Lnh1cK43MiMy3vmvucGEnnlsJ4+bwPdRULjNWVV4ZjORTilgD5HFL5UKK5WOT5Kve8aqsWwNgt/93mIyHwufnXTXY+NYrcDv1oyBt7ROP/dJg5Bbx+FPe+EHP4tIPSPIhlp86bDMtyUjBHNBhm85KagTXDfAhRwvLn9bq46pHNl8en4d6HbMHuGs742hBoWh7npEgXEAa0o7UfDvukkrBC4YdYEpZUAr2CBywHQ1BXzinxMWFGkdeD1GgKQpf5fOISoKSPwWJ4Hlo0M4mfe2p0AE7pT8PbSaa4Y3tbMEGv/jTi+OfwnquT4DMMQ1/OSXhbeHx8X24P9OX2JNapuhQHQJEVJ4oDoMj/mPz617+GBw8eAADA97///WUdgI8++gg2bNgAExMTCR2Af/mXf4HVq1fD2bNn2Xu/+c1vwGq1wq5du+C///u/2funT5+G9PR0+Kd/+if23t/8zd+AIAjw/PPP/9bnwlCAVj0n/pA83hS2I1OGB2CDTrbZzK8flNW7q+R5AuRQgLZtW5KF4bPWBmWhFaua+ShB1HjJG08oQcZeNLbI8C86h1HXovORZTkEtIMSbjo1BBNEpxy8oW1DFGE/BzCCmv2HIca+SlkAOejF2AyAehy/N7YESD0m3/S5XrtMY6UMclLhBf51sa+LQskJGeSltVEwnZRphl0blW3iNZ2UR3UyHwnJfvfXsw3cubgx533Z7y49Jn/cy51X0Tn5+VR4ATNR2oEIGHslttzCixHZRlmai7rrmDWieUBs07pr6BzIzUXNsMhMPRdmTMBUDpR/S2YuimPl9l3QL9/kW3hRZj6tjcKmHP5c/Xq2gdtw/oLgA8tB+SZgu3+O/3xZswjf2lrIf3ZtXZJt4nXZpuGF9a2Jj219q/jc5D9XfYZheCGTMz6zBV7IbEmsy2hWmoAVWXEifNYHoMjKlE/iAJw4cQIsFgv84z/+IyRyAL74xS+CIAhw7969uPdfffVVEAQBvvvd77L3tm3bBu3t7Y99h1qtBrfb/Vsf/+/KA/CzNduWx/n/HfQ/XSsHpfcLWSg9a31QHtaxXR6aseyAPE9A0bkIlJxAw//hg1zsBTiFWQFZLP6UJdAMRRhrqnYQxxdcjckGjC7DIzAmQYg+fJDLIq75t8QIrMzY3Kkw60XImwzH8QBQRkAO9jFtKx9a8f1tO+UhJy/LX5fCC/J6Y488pKUcb4OxW57Xwdgts+/kJfjxpp3cuZix4SPZfZcelf9uU5f8eRVeiMiOpzIg7QDOJeo/WZaTImWJzblYRzBHjObn3xTnohwMqOi8akbws7GcFsvBgC7HWVF0Vv7Yl9Ov2cyfqz/eyIesrRf+XHb9a5OXoLphXp7DJJP/7Fq3Vv7Z5a6ahPqUxJC19SmvLcuv4iscgvpkzvjk16A++S84ur9QmoAVWXEifNYHoMjKlOUcgLfeeguSk5Phb//2b1np0KMOQHd3N6xduxZ+85vfxL3/05/+FARBgKeffhoAMFMgCAIEg8HHvufw4cOwefPm3/r4PxEPwLrEzKydwqvwbZkMgGv1XfAkBWR5AOQJbZbLANzjcgg40hfBVjMnyxOwXIZADnrRkREFY49EtmTqwrrrkuPYxCoXmbStx4it7hoaWPk3MfpaeEGCFdVdl4c/1N3AyOzecAiy/wAzAJqhmJprGQ4CKvfQDEnQoawEaEL8bpnxmXp+VPWu1igbbZaN2K6LQsHViGwk3NgjE8XP5GcA7GuR+VlOX3JcHi5TNgOgel82Em3slYfxLDq7zHXpl9FnxnBS3JD6SbSD0uvloDip94M5APNhto/lyLjUY1LNP3ECUHOwXDaKIETlsk36y/IZAFOXfFZn017+XP3GHj5pXY5wD4nAOEzhjnTMIPKeL841i/CtLTIZgG33+BH81EXwlI1DTjLn2FI+AF/hEHe8a9Ub4Csckh2fk/xBYl3yB0oJkCIrToTP+gAUWZki5wD85je/AYvFAgcOHAAA4DoAdXV1kJOT89j4//zP/wRBEODmzZtx3/XKK6889tlr166BIAjw61//mnusH330ESwtLcVtr7/+OgiCAN4dZxPXkz41AhU5X+D3AGh6+XB0qilEquD0CLSqp8FrGefXwmqmobfoTOIegKSPodTyIrRyxhISB7dG1xiEylY+dGNtNSJ98GrK/XZECzJ14UaNl8ZuLAmSq2Un2Mbi0xi1zb8lwjZekpou9Vf4ddv21hBD8YnlASA8dvUYv67atj/EIEDzJqXSI5YBGEOjTa7mO7s7cQ/A96gHoFG+94F3Xh4/NrTyat29Xqx193n4em4dvQObQnn6GhveT6+PX4ff0Ybwpo/NxZSPIW//K9zj8rlCCJ3KgZz0eUKsYZxX6150nn/dXI3YzJs3ISJMiaVluutovOff4tfR21uxhp/mQmwPACH6qIJhsLdyvrsB55NmSGoo1wyLDcQ38S9vLrnq8bt5/SbOJqzx5+m9PrwuvOvu8YVAX3s7MQxocgkc8V6GrJ2Jgxsq4U0o6wxBQ0niHqIW3SxUN8xDE+f50qyfE2FAEz+7LMXPQ4DDjxJQTYGnYgJyM99KfGzr3wa/7hYEdo8nHp81Dr7iIchdl3h87trvyeoUIjBFVpooDoAivxeRcwBeeuklSE9Ph5///OcAwHcAXC4X5OfnPzb+4cOHIAgCXLx4EQAAvvOd74AgCPBnf/Znj312eHgYBEGAf/3Xf+Ue6+joKAiCkHCreuooBHaNSrBwq96AwK4x8Kuvgz/vGlSonoHctd+DnOQPoD75L+CFzBY4pT0Ffv0gGvm7xsC1KoZDIHsCEYR0tyS0CoKrE1GAPBUTDNIOeQLuinB4CHfntYyDy4GNwF/ZFGBQeqr1b4PZ/EfgciBK0GMcAgWIDlTZtgAu2zQ0GoLgXCPq1yxCgwnRgZzOGXC4ZxEFKD2KMH4ZUagrR1jH8g5Ef2E8AiJMYG3lApScQFhHQp4hqFDzERFG9AT2B7j3xcMT+jzY+EicAbobkgNQdFYsC7qE/xdcjYFeFOERHc0hZuBRuY5qFpGDdNclqFH1aASqDz4CrdgZYtFaajimPoDYEiD1WAyHwYaY8YEQ+56c46/Ak7nvQnbafahNuwNP53RAQ18/ixg7m8TzFsc6m9D4Z85Ng3Rd7Oui4K5BI7bgKkayCdWF4C693hBzmHTX0Jhm+nV4XQma1W9/ROdCxBjTSczQeHzxeq8Xm4updIuhPsXs23AK73Ogsx++uEtEAUq9D7t3vwuqw68gTGeXiNLzyL6LzknQsbFwlfZ1EpqN/hKel6spXu9owetCc8YWiJ9PdF2JVTpvMiw1lw9K72sHxX3HzAd7a4jV6etuxPcAqMclRmrNMN7TqiMLcfOBGoAJzYdQe4jcju63ZjgGglQc62pAjH8qUXI0x5+XoxnXibEHHZNYPaFKUcN66TGRq+MReFRjL95TTcttyNoRAwO6E2FAzYdDUFD3eJNwSvLHUCb0Q1ULcok0mjBTSDCfjYYg2P3IU2KrmUMknzXxMKAO9yxymJRdkJ5dKQgDWq59DtxViOUfz4+CKEDe0lFwV06CxfCVxwIvKUkfQ4X6WfAVDyHAQlYsdwuir/kMw+A1j0FF7rOJx2f9YcKgTkrSx1CR8wUlA6DIihPFAVDk9yI8B+Df//3fYfv27TAyMsLe+zxnAKr2nGD4/v68a/haexP86uuI/V8wgDwBhUMMY5r4Afz6QeQEKBxi5F8+wzAb5yscQi4A8a9fP8g+47WMIxyoZRzclZMM959+IN2Vk4w/wGWbBnflJDg8yCDsrp4Chwfh9ux+jPi7rFMMYs9aG2Sb3T8H1togwveJvADWWswCeJICUNG+ALaaOahuQHSPytYFqGpGHHDzYYSArGqeh5LjCMdoOYQQocZuNPyKzkag5DgamOUdCwjbeDTMkIJKjqPxauxGI1N3Hev/Cy9KpE35N9GAJWxzasDUXxZRWmKMPDIKc2dE9J/RCDPO1aORuAZfKvEgQ041h9FditSqZsOS4Sfuhwy7/JtSeQdFevNviYZeTI04RYDzJsMMVjL/lhQF1l2Tshy6a9goTX0IBf0xzMTXpFIWuj6GU2E2hlCXdNelfRReiLASmOLTaGhTGRbxOBT04/2he2XsRYQc+kvjtAMSnKapS4R07UcD3tgrwpieQ2eNMPaN3bgxVmjRiTF2I1Rs8WkcV3gRzy+WtIscA3L89JdENulLUo8IXe+i8xHmAOkvSf0i+ktSOVfeZBjn1hXpvqjHpJKg/Jt4b7UDEQYJS5wTsZkgggClfWqGsLFXNYfXIzbST2U/NHdUcxIhXe403jvaF83N/Js4PvZ89JclWFzNSIShaxGngbFX4tog3oPSY5LO2C2tTVp/JccRzre8A9dxRWABTCcR8pW4G4pdX4Un9rwPGes/gq0734Ni91fBkxSA8o4FsNYFweGZhfL9IfaMcXjQuLd7kbDL7p1luP4OzyyWFrpnJR4T8ZnmNY+BuwqfcV7zGHgt4/gsNY6wQIi7clLSmcegTP9l2L75H2DdmgewY+MPoVz7HPgLBpAHQHQCfIZh9tdnGAa/5gY+ZzU3oCL3WRyf9r9hx8Z/gArV0+AzjoCveAgqcp+FHRt+iLrMH0DlrjD41dcVHgBFVpwoDoAivxfhOQDDw8OwadMmuHfvHnz44Yfw4Ycfwne/+10QBAEGBgbgww8/ZLCd3d3dkJGR8Zn2AFTtOgaBp0bAteoNiQcgawIzALpbUK59LiYDQEzAvWj0Fw+xSBTDo86eYM6C1zwGgZwJxgPgEvGq2Q+YcQR5Amh86l0I5EyAy4E/mj3FZ+CF9a3xPADlSKbjckxjBC41HofbVjMH1Y3zYPfPQVMhZggIx7tZP4cswrWYJaAMQCx2e0X7ApTvD0H5/hhypxh96TE09IkPoOS4iOV+CKPJlBEgXHfC0vc7QlBwFSObhRfEiHgMihCRbBVexNfOphh89JjIqHo8woiQcqeRQIyQXPImxNrrznhsdSr3UI+K8I4iY3BsBoAIxjTDIpPwRnH8hijY25CFWD0ageyuV2Cn+l3ITkMegKdVHdBwup8ZonHHLUZ8qdFUd10kdsqM50fQX0ajt6BfxH2POW9XA0JCkmEdi/tuXxcFV22IGcOO5hDYM2N0dSFGhqW/EgGfO36se5/I7NyDjhBlF0jv8YcYwlPr0X54dg9mALJTfwy7d78LeZ2vMMOfMh+MO6EeI9GGPnT83PukY6PzJn6Egn4pA8DOuy7EHAPN8OPXjTIAdN3Vo5KjSO8xNl/C4l+F+7Z1Ipws3fP8m/ElQOQgkOPnaI6ZD5mYnaBysoYz/fDM3g6oS70D2Wk/xuxQ1ytYqjbw+Hk5mpHFt/AizsU4zol1qC8+jffM2BMGdw1et1h+BPMRvHamrhjuBpE3wucJMabvgrrbkL3tHdi7+j7UrXoNvrytHY54L4O1HoMBdRXxOP9NhiB4kgJQ1TIP1vogZgDWLMbxAFCQwe6dhRbNDMPyd6xZhBYdOgjuaoTyjH12qTZ8H8p1zyHpYeUkI+oi/pM21RR4TYjz7y0dhUDWRDw3S9a4FFgxjsQ9d4noi3R+3S0IPEncLkvx3C66W5jxTXkjnvcl7xpU5iklQIqsLFEcAEV+L8JzAI4dO8Ytt6Ht7//+7wEA4Nlnn4VEKEBf+9rXQBAE+M53vsPe27p1KxcFyOVy/dbHz3gAtp9OXE+6K3EqWeoB6IFAFqcWdRdGpXi1qm2qKfAVD0GrOjEPQCBnAvpU3dw6WrP5j6AtL/HYNtUUI9pJpK83YwkQr8a3wTwPlkMhaDAn1tdWYnlQ2QEkcjIfQXKwkhNhZpjw8Oo9fvwswTTm35Qi4xTpLujn13w7m0Is6lp4USoFolIP7YB8XTURNeUEw7A3HIpjAqaoLa/m2xYIQVYPvweg5UQ/2Pbz683JOeD1FxRclT/v/JsRLseBqz7E14mGtHuffP8BjwfA4wtB69HEPQDJKR+DJnBbtrdBf5n/3a4m1Nvb+HrdjQiXX8FVh4Z87kwYcmfCbG7kTkvZIV5PiPVAiGVp1GPxvSC50xjxJyKvhPOhPQSNPf3wPc51yTnxCv+8GkJQeFH+fhZejICH05dRY8N1xONf8NsTl/ikC/8JbyWVwInKC9weoDahF6ob56HenFjfJJYBNevnEuuL56DbdI7bv2Qpfh5adImfTQHRCeDyp4g1/oFdY4n1O0fAr7nB7zF4agQCT45wxg4rGQBFVpwoDoAivxfhOQDvvPMO3LlzJ257/vnnQRAEOH78ONy5cwf+7d/+DQCQ3IvHA/DUU0/F8QD09fXF9RUAAHzzm98EQRDgS1/60m99/J8IBSjz7xPqOoVX4c2NOnCteiOh3rXqLviMI7I8AJ6KCVk8azkkje1P/IiLAuRMW8Q6XB5K0JplcLzTF6F8f2hZPUUZs55ZAPMRjEqWHkNHQA71xdAnloVcwMixZkgshRBhQYvOy2O3U3Q3/1YEsp5bYNF1auqVQ23RjEhswerxCOx5IRiXAcibkBm/IQqZBXxklb/SG2Vx3bWD8rjv6lF51BjdNXk9V5cZRUx6GZQf/eUIOIXXueMXc/koQJm698G+DNa+HNqNZmgZtJxh+XtK5UCq2TCL6mtGpJ6A5cYSmy/Ng+w/CMWh+8gd2xv5RtnrIndP9FcistfN2M1H+XFkiOhKMvon9vDn6l/vNnDXt1N4HZyuGb4+bRHsXv7zxZm2CN/aKoNgtnVJBgXoLnhNo/L8KrpbfPS1VW+AX3tTVs97ZjtX34VKbR8oDoAiK0mEz/oAFFlZ8swzz8Dk5CScPn0aBEGA1tZWmJychMnJSWbYPyq8HgAAqYa/t7cXXnjhBcYE/LWvfS3ucz//+c/hiSeeAJVKBU8//TTMzMzApk2boLCwULb+nycSD8DrwMOUXpcmwwOQtlUWj9pfMCCPV20ckdX/LH07H0s7/YHsWKdrhq9PXgKHe1aWB2A5nO/yDmwWNh8JwcMHuWDsweh/6VEsJ5HjECg+EwbTSXQCiEeAmFwLrkaWxTenhlnddRyrGYow8qb8m/LY6trBmH6AYDwPAEV95canbpPhAdguwwOwCo/7U+PCpyzhccvxI8jo9JeW5yDQCEtc/Qdb+TwAadt+uSzWvpz+k2D1y2LxixF84oUgh5BKgZabD8T4G5sJ0gxLdf5y4z/Y9umvS+FF+fM2nJLnTzAfCfH1yUuQsYE/V3+yfid/fQs/AmudPI+I3Tsr+3yR4zBZ7tnlKxySf67qbsnrtTdl9XK6qj0nQHEAFFlJInzWB6DIypKsrCzglfZ8+OGHCcfIOQAPHz6EmZkZyMrKgtTUVCgoKIA//uM/TrifpaUl8Pl8kJGRARs3boRDhw7BL37xi091HstlAFyr3oAd6/gZgG9namWjSb7iIXDJRLK8lnHZDMCbGwuWwdLmcwi4q6f4+jSRKZjHE5C+CLZ9MjwB6YtQ2bYAZZ0h3A6EWMNh6dGwLIuofW1Uah4VewGKz4SxufFkmDWB8iKj9swog3nUDqLhV9CP9e35N5fHXifSMN0NbOzM/kIorgk4bzL86TMARYblI/zLRKN54wkP/9NmANSjyzDiXv7dIt1yePR5E/LfvVzmYzluB8L7JxjYvAmJ40E7EAHrRnkmX4r0x5YAaQcjn4gX4q6Wf13W578vm3Ux9MlzL8hF+O1ro2A5FJJl85bNAOySzwDY/XweEWfaIrisU/IZABkOk+2b/0GWCdhrHpOJ4N8Fv/amTOb1DfkMweq74FrFzw5UqXpAcQAUWUkifNYHoIgin0dhPQA7OTwAO+V5AE7pTvHxqHeNYQMwr0cga4I1CPNqYU8V9HHraMu1z3HraFs0MwgRyukBaNbPgd07y63hbSiZB2tdEBqNiXG+6yoWpAzA4RBDFiFkIMuhENT8f+y9eXBb13n3D5ISSUmUZEkWRUmUuIAiYBLcCZIAiH0V9wWktVGLtVFeJFGURIqruG8A4ziOG1fNm9jzi/3LH3YyY4t827TWTDpvEjuJotRybOet01+nTdzkn7aTtrHf1nl+fzznOfdCxDlMk3bs4XvPDIYkHpx7gct7L86zfb6O+LXLQRc2pZafxgxAxUmkm1BDcdlZpJq4WgS10azhtegSlgoRUcU4oPQRiOrRHY9GFLzjiEL54SVArJZc1APgbItA1gVxD0D9xV6wHxHX8BsHFqX9BcaBReHndoQRHSmsRw9HpO/bOLAo1BjwNEY4djWe3RuKQNsxcQ9A9pkXpZ+r4NqiUB/B2Y4NzqJ9u1oiHK0q6hHIH1MW/6QHQVH8A+OIhBW9N/1MlPcM8AzARFRxIoaxoTzue2uNQOPj4uOiP/aiWNeB6WGI7EEXXk8i/YSDdsy+ibQ6GqoWoMT7VWEPwOnqi9BUHv/6btedA69tApqL4t8f2vIRQSzSMGkpnJFqmFSbviS+L+5DIpCwB2DfGAQLByQ6AAhgCO8eFtb5C++5e0e0DIA21tzQHABtaCPO4BSg7MegY+dArA7AvjEI6a9CoAydgBgKUFordOef5bjQcObNWM5/7jji6hgydIUOQOZN8FnGwV8+CkHTIIT1Eyt0AvyVo+CvGoOzpU9wkkZu0nug3/oW1BQ8x3UC2gxTqCGQgDoAbflT4Dg4h1hRB7OnLHF7S2EsOrRdd07REUhdgqZybPCztc5DbROK/SAlCDnfDVWICCVKEEcKHkHcoCW8ABUnMQtAFCBD0n1wMoJQ2Tl0EMzHsF+gtBtxk6YrSLghkTDTlcUYZj3RcEw9ixz1WHh1MQazaLqyyDnwROIxJCk6AFT/bxxkNeKMBBRDf5nCOnJ3s0oHYKvCjc+bjkLekRdhr/4uZKe+D3XJ34Bn8jqh/mIvV4B1hBXuu/0hpNXo56Kgn0G6zIP6Bo7OSAyW8kFmveNQhCMtjQMqjYIkfG+exgh3gmI0CLYiUcYwpGgu8PemYumT85Q3FVXms+Pmao1wNGvrqV54JqcT6pK/Adkp78Ne/V3IOfUi5+g721Xve+syeJpUnP8+heJD2/Y0x3L+7Ydjj7mrJcLr842Di5zkw/8n7agETWhY0njQz+DPvMkoLw9ztq3UAcidi3Lu/4MZAHImCq8yNeAO1XvfuswdtpLHo9B6ohee0XdCXco3ICflfcjMuQv6oy9C0UXscwn4iOKDx9x7EM/jsnNIv1IoP8jx99ShU004z4ArEqvFYVvg/TfmroiK5HMfXBuWoc6yAPa6ObC1zEOJ96uQnf5DyF33HtSv+wb80a5OOOG8DLVN81DbiI2+xPl3py5Bc8ksKpi7p8FxcC6uzogaN9xagBQysrcZpsDtngZ/1RicKXsiRgcgb/ObUFXyPHhtE+CzjON9ke5dybe5eGKgbGTlfZHR0Qi9TE4A3bPxvor325D+KgTzr6/Udslg6Ob86xDOGIqxdaQPQvDANa0JWBtrbmgOgDa0EWeoHYDu7FNwJ80IP0vZCXfSjNCd+xiEcnv5F0a3/gzc2fwIfJCaDm9sLYDu3MdQH6BwALr1Z+CNhwpw7pYC6M46yZ2DQMkQdBvOwhtbC+BnyTtxbtYpvsD3V47C+cJueGNHEfwsJR3eeKgQzhvPI0K0chTOG8/DGztMuN8dJjhvusA1BDz2SThb+ji8saMIPti4C/5iZxGcN54HjwMjdB7HFJypfBL+4mG0f2tPCZy0XwK3GzME9oY5OKfzwV+kF8Nfb8qAP99VzO32hjmw189xUTD6aWudB0sH/s0Fww5FwNKB+NDyx3Dxb21DPQDChZKNtALKzmK2oLQbo/5VR5FEU3EyyvnwRZcWFaXh81HeJpv3fQAAIABJREFUI8CbiBk+0jigMPUJD0q1/tQQSot/YrgfGGd8+IFYAai8KVykUx35gYkodxpIbOzAOPYPFFxHhyB/FMuJCBtJQmUFfYsxYlG00CYUqXEQ5z/Sv8ijzoYRXDBzxeJxfJ2phzHpR9h7uab0QdA2C68qc0irgLCp9N7pQceIRNcKri/yRmjSOCg7G+XHl44h9V9QvwVtj3CcpOhc0KeIvan1GGixTT0b9D+gOnxCeRLrn/4m0a68SaT90GI/bwqPiX42Cvq5KEe7Up8HRfEPjOP/iDQCqAzMdEXBs9J5QPvmn2tEOcaGIeVYkmNE2gz8c6rY/mSn40kaCoT4rDiJ5zrpaJiPRbgzXHEK/646is515QnG+mfXV82j6HxXH0bGP12PNZ0LYG+Yw+c7Fvh1bG1H593Wihk+W8s8OA4yrRD/DNjr58DtmUYHwDONTkBoFnVE6uc4etjtnsYSIA+KCfos4wrfv3IUXL4Z8FeNga8a2f4+yzg6BeabECy4AT4LwyQz3r/XOgG+6jGun+KvRHwyZ/sztGegBLHLQdOgosNScEO516oW/zG2ghuo78KeD5QMQSi7B5Gghj4IFtzAe72hTxMC08aaG5oDoA1txBnkAHRmtsJbunI4pHsJinQ/hkO6lxDzmX0KI1GZN6FD9zK33dMVw0cJ66A77yx0688I5wbKRqBbf3qlPaGcL/LPmS7EnX++4DycL+yGjxLXwT1dMbd36F6GcC6WD50rfhzeTIid+ybbtts9DafNT8FbK+wVcMp2CRyhWThlvQhv6cpW2B+zXERRH+YE2Frmwdq+wPUDahsxemhtw8i/rWWeOwLmLlywVB2NwEE7qQgjn7zegirC5Y9hCVDlCXQCSEeAGoMrTrHIp0/FpGfR6rJzUd4zQAsxYsWTtkDRJcZW3xrLnKcF7CM3FPZ7/uhibOkHW/A7OmJZ/LVHMcpe0LcITeeUiG926k9hd/5dyLrwIm53bOW+nW1IlaFot6dJxaRnkezc+ShfCLtaVs4nR0Y/+wDTfmusxoGzLXauqyXCm1kf6V9pd3SqMgCq7IR636YruPBtOtsLz+Sxz53yU8jMvgtZ3S9CwXV0iBydbO46hdNPC+NH+lkGQL1vltlQl+o8uG/DML4v/UyUZxj4/DCWg1ENP4mx0bFSI2L5e1NpCFC2iBwWOg8IJ0sORP7YSk0Kd3OEO6DthzEzUp+M+giZ2XdB3/UiFD+J2yZFbOL8BzxY/lPyODq2SqaMcfw9EV4WV3k8CnW1C2hnWhx1VnQGLB242A85IjEs/7raBahtRCG/Mvv/gJyHfwg5696HhnWvwh+ld0KXvwcsYXTYMcPHdERSlqC5GDMAzuAseFxTMToi7hTUEfHYUcnc45hCln+yomHSapwBvxkznOcLuzEDkPgq5Ca9D/qHvg/Vpi/xwIea848ZgAnuAASKhngGgOur7FYchEDJ0Ertlr0jXLslUDQEHemDKh0BzBAEDX0Q0l+FjvRB8Kg1BnYPQ9DYr2UAtLHmhuYAaEMbcQY5ADdT3HFrQm9taAZrZhRSdL9ZYbunK4Y7mx+BW5ta4s/d3ApBYz/cSmuNb9/UAv7yUbi1uS2u/Y+3tcMb201wT1e8wp6i+w2YK2/BrS3x597a2g5u9zQ8vz0s2HYYvNYJof35hzv44t8SxkVGbSOWBDkOooIwCQnVdC5wZWFb6zzPEtQJGONBVwSqjqBgWOVxXACRI1B5ArMBpd1R8PsFXPmA4gSUPB7lCriGEaYw2yNmqzvbI1zNt+gSLjz1s0rt9yM3cOEoqjd3dEag/qKY+5595kUhc97ZhrXstUfj22uPYYmRtEdgUGy3H4mAo0PyuSWfy9WCOgGi/gJPcwQanhJ87nUfQ9ZZ8ed2hJG1L7J76uW9D872CC//Ef1P9Cz7kjuHztuBiSjv9TAOijUEXK0RXv+vxoDm31ScEnKaRPNbTsU/LklJH0PekRch4I0/N+DGYx7wiTn/VUcjEHTGt9db8DprLBdoddgWoMQj7gE4ZbsEzaXiHgB7wxy0GsU9Rj7LuLDHqC1/avUeAFEdPvVOCWv8mQ6AqEdgNysfEvQYdKQPQjhjSNgfoDkA2lhrQ3MAtKGNOIMcAGfC59iXQeyjIfEVyNhyL67tkO4l+CBlJzQkviKY+yoEioagIfFV4bb95aPQkCSwJ70KH6SmS1nasrke+6TU7vZMC+31616F2kZc1Ls907wfwBmcxcV/HS7+qbTgkw/zwNqGEcWqI9i8KKKTODctQ+VxXOxXHo9yjGjFKSyFKH8MMwEyilDxkxh5LT2P2EfTFaUH4JF+OXOeSlEKr+IcNQa0sJfpAEioL6+ZJDScQgn3nRGIZISh1TQMCq/KdQRWJQxJ7Plji2AX2O1bl+H1AvHnTiuRfO6ty5A3LSErkQ6A5LjoZyUUoM3LSvPvdFRBf95c5Iq+q+2beknoPKDyLCqhEpKZNi/DUr74uGzLFesjONOWwXxMTsuqPBEFp4TyY+6SUIA2LMPDmT+JayMdACHFh+kAyCg//spRsT15Cd7YYZJTgCR0NJl+iofR1UT0NM86ZpfqAEgoQFlaCZA21tbQfdpvQBva+CwOcgAyE16DeFzo3MR3IS35F3Ftxbp7cCfNCLmJ7wnnBg9ck9jfg6BpUGp/Y4dJzNLe+A+Qm/R+/LlJ74HHNQU5Ivu698DlnZHancFZFBNzTysL/jrMCtQ2zWPUn5UHUYbA2obNibYWsYaAIfE+VB+OKJoBZ6LcaSg/rZQCyfjn5CwUXcSFGvUEkPOwGg+fE4OuL8ZgQKkkRMp9l/DwkzN+JeXVS3n46+7L9510Hxe2ku1LbTfl+zaMyLct5d3vlPDu191flcW/Gmt/1c89ynoxxpguxLDSGyHVXki6z/szTFcUB8AwhH9TOZls/vs7xMcl9WG5DoD5mITjn3QfbK3y68jSsSBl9W/cItEBSMuQ6gBIdUQS7oPHMfXfpmHirxyVc/5Ng3+QjoBUB0DrAdDGGhu6T/sNaEMbn8VBDsC+lP/ngS8DfORt+A5kbI6fAejQvQwXMo9DXtqb8eemvQnB/OuQt+l78e2bvgdB06Bwvn7LW3DedAE6dC/Hte/a/jbot7wVf+5D3wdf9RjoH/p+XHvu9h+At3ZSaM95+AfgsU+CyzsDjtAseBxIFqrpXMCGwAYkBTkOYomQvWEOG4NZFsDeINYQcG5ahppOzBSYu1BDwHwMy4IqTkZ53fNqOgIVp7Chkur/i59iegKXF4VzHZsxA1B0UWliLbqoqv1mjZ2yDIKMh59W9K40kp27IOa+2x9almsQsCi9bPurqunKVIpX4eXLMgBbjPLPbRz8AyL8W5d/J20HogBR7T5vOJaoLzvT8HwgZWnuCF5jzbtPYXZAyOpfRSH5obx3pedxxUnxee7auCzNpLk2LuN1JskA7NwjzgD8RXqxmPOv+6ac8598GzMAEjVfaQZgx9vCKLx7/W0IlA7//krA629DKOeKVCdAaEt6XcOAamPNDd2n/Qa0oY3P4iAHoCTjOiTpPmJfBKxWVfcRWDOjYN2zAIkP6ACk6P4NwntGIFA6DJbsp1foBCQlfAyW3M9DsOAGWPTPxLdnPQ2BkiGoNn0pvl3/DATKRiCcNb6iByEx4f9AtelLYDE8G3euufwW+MtHoark+fh285+A2z0N1cXPr/zcCR9DZfWXkQzCGgHtdVjqY6+bA0cI8aG1jfNgb8B+gJpOXPw7QrPg9kxDbeM81At6AOqsC9g78ChG/SuPR3nTb/WhCNcVENU+B9zYP8BpKk8wCsu1RSh+EsuCRP0Dnnps3KQGYGr25CVAVxeldfaexgi0Cmq+E5M+Bv1RMQ/f1hXheNK4NfyHI7zBN26PwBHsERDV+dsPR8B+WFAnfyjC8aGiOn3DyCK0684J6/BlvQ+7+14Q6h94muX6Ba4WbMaV2fMmo+LeivYIpxSpHQDTZYWUJOoJ8dRHeNmYYTjWEaTmYNNlbOqON98fiED74V54MzF+D4Ch9QVhjX/QGYGSx6NCvYyAC8k/wuvIgk339dViHYBSz1fEOgDmp4Q1/u26c+CtnZTW+PvNN6HNMBXfbphGDRNd/B4Ai+FZcY1/7jjW+It0AjJHIVhwA8K7R4Q9BEFDH3SkD8bvAdg5IOkBGAFb5gnQHABtrKWhOQDa0EacocaAWvTPQMbmH0Fa8s8hY/OPwJoZRXTcgWtg3RuBjK0/hrTUX0DGlntg0X8BggeuIZLuwDWoMT4HGZvvQVrKLyBj64/Bkv8sIkILbkCgZAgsuZ+HjC3MvuUe1Bif47ZAyRBYsj4HGQ/9GNJSP4SMh36MnH/zTUSBlo9CTcFzzP4L2LX9r6Cm8I8gUDYCXusE1Ji+BLu2/xWkpX4Iu3a8DdXFz4PPMg5e6wR4ayfBXH4Ldj18H9I2/QOk73oHagqeA7d7Gry2CXQCdL2QvlOxm8tvIebPNQVO/wxmAQ7OcS64MzgLLt8MogQbVOVALCtQ2zjPdQKayogwghoC9RZEEVYdZRoCXREFDfqokhGoOoq/B52MjpJ4n9NRqMyn/DTTD+hZ5JmAsnOKY+D3K9x2ZxrTELiMZR3FTy3yvoGYyG+fgqskWg6x24nEYxxYhMbzvfCFbIX7vjf3LmSdZRSgmyuZ845whDeUiuzE+CexMM67ZyQfUjDmOgMqHr4jjEz7/FFk8dsfUtk6IjGKyTHb3oqc//xRdHz0c9EV+3Z04ns/MBGFhidUFKDU92FP3l3Y9+QLHIH6oHaCuznCUazGARTUitn2IWzgzR9lCs7hWLuznekjMEctRj+B0Y9IAIyaf6nsp+C6Uttf0PeA/gE7psYBPHdKu6MxPQAVJ6Ncu6DkAjabe+pVmhaM1W/qwaxTZ2svPLsP9RFykt+HffvvQn7nC1BxCs/tgDt2bsDLyt/OYS/MQfsCP8+dm5Yh4FYUte0Nc1BnU3H+GU2LqFzWdoXkY2TXWWMFXoNO/wyYzX8COQ//gOkAvArPbw/D6aqLvLTvQc5/m2EKfAlh8NgnwVs7CW2GacWevARh/SRHe3ptE2hXaZiQc+CrHoPzhd1wa2s76gAkog6AxfCsQvnZNxbL+c8aR0IQ108Z53bO8Tf283unWl+FtFtIJyBQOhyrA5D0OjYIG/pQB2D3cKxGQNYYhHJ7NSVgbay5oTkA2tBGnKF2AIgHrWZCBw19EMrthZD+KnKjC24or2P6AHwhXzaCDgN9QRUNoRNg6ENbwQ2uG0COAzGt1aJhvmqkXASKhpD3z/QAgoUDyMYuGwF/1Rji8FQMbZ9lnH8p02uI100Pby0+XN4Z8LimcC4T/XH6Z8BrmwCnf4bzvZ3BWd4L4HFNgSOEPHB7PUb+HQfxd3sDEoBo8W9rmQdHaJZnBqxtGPXnnPJHcaFPzPKqo8gxrz6Ez1OPQNlZVhJ0ApuFK08gl57UgitO4uKstBv/Lu1GzYDC3kWuL2C6oizySs9HedbA1MNKPHpVDsB1xYkwXVY478TJL35KWVyarijaAwV9CuefUJ5qbQDi5RtGFjmSk/j0hNjUz0YVnYAxXBBTZNowFMvLp+ZWUjQm/GXBNXwfhiEFYamfjcYw/Ol90PYLrqsEs0gvYRT3R5QkEk0jzKlhZJGLfxkHlEyKfiYKuXNRnl2h5lz1Z9XPKBx/arblEfxJRfSLBLzoWND7Ioxr4VWFu28YZrX6Y0ppV8E1RRjOOKA4A4ZhpgUxpNiJ289pUP2Kk0gOI/3/6UFaFSUXmGDXCYVMRedaxSk8b83HIpz5X3k8yrNf1PtCInpUGkevqXk0wq814vdb2xSuv60Frzm3B53z2qZ5zNjVY6aOl+qxzBw573SNuz3T4K2dBKd/hvP9Xb4Zfk/w1iq4T69tgnP9vbWTeM+pRo6/xzWFv5czbZOqMc7q91eOxnD9/ZUYwfeXjyLnnwl/8QfdS0nwi2mp8Hsqu+fy+ymx/AsHuI5AoGiI37+DB66hNgDDfwYPXMN5dK+m+zmza03A2lhrQ3MAtKGNOIMcgBqdn3/5aw/toT20h/b4v/NRo/NrDoA21tTQHABtaCPO0BwA7aE9tIf20B700BwAbay1oTkA2tBGnKE5ANpDe2gP7aE96KE5ANpYa0NzALShjThDcwC0h/bQHtpDe9BDcwC0sdaG5gBoQxtxBm8C3ncSG31zruBPagLOv84fodxe5XlGBwrmX1d+N/Yr28i5gnNyrmATWm4v30Yw/7rSHMwa1gJF2BQcLLihNKax/QRKh3EO7Zea1goHlEbhylFs/GUNw9RczJvvmC1QOgy+hDBUHo/GfOl5a7FJ2Fc9xhv8/OabMU3GhAR1hLCR0F43xylBbg82ETuDs+CtnVQoQkwrwF43h82HQRU+tB1JJtWHIkg0qcdGYmp+rG1C9WFLB2sapgbhQ6xh+HAELB0LUH4am30rj0e5pkDlcWzCLD+tYEarjuLrK05hIzA1H6uPA4mRlZ9GgbLyx7CpmPZRdhYbPIufQuSo6bLSXEzKxLT9wqtIiCk7hw/TFaZX8CQ2rBJlpvipRTAfQ0RoyeNRRE9eUbQKSNSKaEfUYFvYi88V9qoak3tY0+qTuH9CXBZeVakfDzIba3otO4ufr/gpbGil/VPjcv5NfBRdVNSW86aiUHBdeR+GEQWbWfwUe10P/qSmXdMVpdm24Bo+ciJRKLqoNNwahnE/pp7Y5msS9SroU34vusg+9zVF/8E4gL8XXcSf9D8qflJBxpaej3LyVNkZbN4t7cbf6TxQ/4/LT0f5Nkw9+P+m84Maxkm7ovI4brvsnHLumY+hvkXFyShYOvB8rzqK57IlrJzbNZ14Paixuvb6Od7cawkvoCo3awam551+vBYdB+fA45jiOh2O0CySu1gDsNs9rTT/s+udGv+91glsCLZNYLNvQpg3+aqhAtS867MgqtNvvolNu+weRHQff/koJ5wFSoeVBl5G5/FXjeF9joEUaE6w4Aa+vnBgRbMv3SP5/dLYz0lraoADf9C9mzUIB439eC/O7oGgaZDDHej+TL9rOgDaWGtDcwC0oY04gzsAmSf4wp8W8GpngChAoeweZSGf8Ti+JrtHWfQTaYIcA0MffvGwv8khCBr78XdjP6cGcUcju0f50qIvONOg4hzQFyebQ4ShQOkwfsEyigb/yZwETuQw34yhc/gSwpze4bVOKNQO9kXPaR9VY+DyzoC/agypH5ZxvtjnZCH7JAqHuaZQSMw3wx0AW+s8/h2a5Y6A0z8DthZ8nggkpDbsDCJxqObRCH/O2rbAHQBzFyISqw9FkI7CnImqI0gLqjiFiy9zV4TTWCxhXGSVn0aHoPwxXNTTwq/oIi74iO5Ci+Lip/B59QK29Dw6B6Yr+Dstqk09ygKbCEElF5S5JY8j1pKcBHqQoFnhVZz3IK2HKDbGQUbJGUYqDi2SiUBEjoZhiNFw2MKfCD4FfQoNiLCkRMo5MBHl+MxHbij7zR9TFuDkGNDnzB9TnBTD8CLn8BNtp+gSIwBdxkU7aTAU9KGtsHeR41mNg4pzpHaYCnuV54ufVFF9ritO1iM3cPv0/yrsxYU5LdhJL4Ie5ChUHsdzoeTxaIwjSM4gaUtUHUVsKJF8ys7g+VV2JgqWMDqTpGNReQIX++auCD8nq44ojm5N5wLYWnFRT5QsWvATUtdxEOladJ2QLofLN4PXCbtGapuQuMWpXf6Z2MU/Q/66vOise20T4AjNclQnOfmE9qR7gtc6wYk+gbIRjiX22ibwfkGYYgo+qIIN6kU63Yd81WN4H6L7FBF9WLAjUKIgPmPuccwWKBlSCGp0TzUNcsKPOlDDF/8UnGEBl5D+qnIvVwVj1Pd+TQlYG2ttaA6ANrQRZ3AHYOdhXMTn9vIvh9D+yzziH8rugVDmRSXKn92Dv1Nkf/9l5cuFMgUFN2IzCgU3OJKOHnzhT0g6Y7/y5WkajI36sy8xiqJRVI0W9L6EMF/4kyNAiNGYL97SYfzyZl/Y5ADEOAUs8kdf+D7LOJ/jqx7jSFGPawoX/g5c8HtcU/w5n2UcMwKEFmWoUUIWqh0BWvDYWuZxYeOf4ahDx0FcBNU2zfMMASEQyQGghX3NoxGOVKQIa9nZKFjbcDFGi7KKk7igs7YvxGRDii7iIpIWiBWnYqO9ZWdxIVlyAf+mn/ufn+eRcOMALu7LzkS5snDRRQVLWdi7yLfBefW9SvTc1KNEuTlm9LqCAS3sjdUwoIU2OQH0+gMTUUSIDjMH5DqiPPPHFnn0nt6f2jkwjCjbKLzKHIkbCvqTFt95k1GOOzUMMYTnSOw2Sx5XsJ75o8p2DUPKceAZg8u4j6JL+Hpa0FNWg46jYRjn0f/KdBk/HzkNpOxMmZuii4scEVt2Fp2DsrMM2cleU9qNDiKdBxTBL7mA50DZGXw9x3ayCH7liShXr6bsFDkPPMrfoZybdA7TuU14z6oj6MQSOremcyFm8U+ZNo9rCp1lDzrLHscUV+sm59nlneGONl2btJj32Cc50lON9vRXjfHrm9DAvuoxnk0kxLC/clS5f6juIRQw4M4Aw4D6y0f5Ip9eQ/ejGGxn2Qj+XTbC74HcGVA5AiH91ZiACb+HGvpwm+q5dN8kJ+DANdwWYUEJBXrgGr9/B/OvaxkAbay5oTkA2tBGnMEdgIwu6EgfBM+618GgQ2GYjp0DENp3Cb8csnsgvHsE7Qn3wZP0GoR3D3OHIZwxBJ6k19C2jgnO0JeL/qpq7jsoSJOBnGoqFQrvUezu9bchvBe/EOnLL5wxpOx7/W0UvGFfYMTXprR5oHQYF//s9/C+MfCsu61sO3ucR+N81WPQrjsH7mRmT1bsjoNz4KsegzbDFLiTl9CesgQthTMYNWSaAm7PNM8GxOgMOKagtWAG3KnK3FYjPu/0z2CJD1vYOw7OxUQwqfynqXQOXKlLYEh8B1wblqCpbI5HPC0dGDG1dCzwiCqVD5U/FoXGinkmQvYOuDYuQ51lISYyW3VEWcTFlACxsh/vQRRvyk96B5ybUYSs7Aza/IEIODejzbF5GXzBCI8+F15dhIAXRcjyk95BEbL6CF+4F1xfBO9Bxe7YvAx+fwQKr2Kk2TiAyrPq7XvqcH7xk4uQffpFyMy+C9kpP4X65G/AF7I6ofl0L194e5pR8IrmkuCVYQQX3p762H17GrD8yNSD2yeRsvx1yr7J+Wg+owigZSf/FPbtvwv64y9yB8TRodr3lmXwhiJY/sNKlVytsXZPQwQZ+8zZ8dQ/8LmbI9wpUou7qY8rlTtRNqbiZJRnC0oex8V74dVFOPDoi/BQ3ruQuv1X8JD+XTCEX0BmPyvbMvUoOgBlZ9ABqDjFVKpPRMFU9wJsz34XUrf9CrblvAvFvq8qKtYnomAKvQA79r8LG7b+CrZnvQum4AtQ07kAljBqYFB2gJ6ztcyDyzuD0f/2BX7O8yxA/Rxn/NvrMYumzo65fDOKA87K7agcjy/8mZPutWGJj8cxxaP65LB7bSzSr1q8+xLCuGBnz1Nkn7P+2WvV5YfqTCPdgyggQfN5ppIFL+i1PCOgEvnif9MinmVEafEeyu1VAiWk3WLsVzKoFFihwInacaBM7AM6AcH865oOgDbW3NAcAG1oI84gByCw9YxQNj6U3QMdOweE9o70+Lbw7mGcK5KkT8c6VKGk/W6MaIX3jcW3Z43HfqGyCBivlzX2QzhLMDcTnYZw9rjQ7q8ag7B+Mr49d5yXFngcU+BxTHERMlpctBqm485tNM/H1CNb2xf4Nqjm2RGahaayubjzm0uV0ojaxnneQ1B9OMJrpestC3Hn1ltUQkudCzyCq174lZ2NQsAbiTs/4IuAPxDf5qmPQGl3FIKu+HZ/ABfSAU98u7s5AqXno+C7Hv9/5mmIgL7rRUhM+niF7c2kCmg62wueRvG2jQO4wI5nd4Rxoe5uFs9v6+qFN5MqVtgTkz6GrLMvCrftacJt+0THrQkX+Z6G+HbvQVRw9tTFt/uC6Jjx0p4Likp08RMY/Te0vwBJDxy3pMSPobD+BS7kVXFKOQ+qjkSg5AJG8StPRKEo8AIkJa6cXxR4AaqORqC+egGSE34TY09I+j9Q7P8q1HTi+cid0Q1L0GBmwnhtGOlvKp+LsTcXz3IhL3vdHLQUMkc68R1wpS5BY/k8z6B5XFPQXDoH7hS0k5Pus4yDxzWFc1OYE568BC2mWV7u57FPQrt+MiYA0K6fRAegCkv/wvqJ2OBEliIA5q8aQzVfNt+z7nUI545zga9zpgtwK61VUQJOexMs2U/zqD8GJ1SBjcybPEuJgZNhJXCy7nUIZ97EbCxbsKsDJxh4GVayr/qrqsDJO1wJmLIIMUEVlcqwVgKkjbU2NAdAG9qIM8gBqEr6Ivvyjn14kl6D0L5L4El6Lb593evgSXpdaAvtvwyedWJ78MA1sX39bQjpr8rnUzqdmukohc4icLK5gZIh8Ky/HdfuXn8bAqXD4E4W2722CSwhYuUBlAXwV2H5kDtlKf7clCWMRrqmwHFwjpcHuT3TvM7Z3jAnnO9KXQJb6zxXQaUMgCW8gOVE9biYijt34zL2D7BIrC8hzH/6EsJQcRIXg85Ny3HnOzctgzMtvs2xeRnnCuzOtGUouSC2OzYvQ8G1RXBsFszfvAxb89+NazukewluG8vAsUWw7S3LYOpZFNs3L0PxU4vgFOzbsXkZbhvL4JDupbj2h/TvSueaeiSfK211e/ETi9LjWtqtNFmXncFyIFKRLj8dhX2Zd+PO3b/nLleZLn9McQCqD0V4n0jV0Qjs3xt/ftbuu3As0AMdCf9vXPuO/e8KndFG8zw4gxJHtwQX+C2m2bj2FhMu/kX21oIZaCmciWtrM2B2oM0wFdferjsHgaIhaJcEAPyVo+IAQ9YYnC84D2/pylfYkxI+Bkvu58WBjd0Y0AhnjooDJ/qrEN4fWSW5AAAgAElEQVQbP3DSkY73QmFgJWMIwruHhXNte4+D5gBoYy0N3af9BrShjc/iIAcgW/dN/kWgPH4LxoT7EDxwDQwJ7wjsb4Mh4b54rrFfMvc+BE2DcnvhwKrzA2UjEDT0wScf5mH0izUOB4qGpHP9laNyu/mm3M6agf2Vo/DJh3lYP1yLNcYu34x4buJ9sNchscTtwUbFTz7MQypJcJbbDIni+URBsbXMwycf5nFnoLYRI6OyuTWPRvjCrupoBD75MI8v/GjBKJpvSLoPhiSxzXR5EfIl9uIn/gD7uvuQuv1XcW3Funvw3sO7pe+tsFe+70f6F6XzP9BthSLdj+PaU9J/Jf9cT8n3bepZxb7KcS07hzX6pd1ReOZdNxQ/sYi1+2exBCh7/ftx5+Ykv499Ho9FofqQ0gNQ2o01/VVHImBtW4Acwfzc9e/Dn+4vFR6XjVt/KXZGNyxhvb7QvoyZslSBI52MjrQ7WeJoS5xwf9UYuEUBAN035fbk1QMEd7YWCB3GjK0/lgQnbkPQNCjc96qBk3WvQzD/utQus9kyT4DmAGhjLQ3dp/0GtKGNz+LgGYBEUQbgdYzCi6L8SfIvk6CxX5ohCBr65PNNg6tunzfPEV6U9Q4ESoYkX6K3wV8+Ks4AJN8Gf+WoZPFxm5cYeK2xDYWBshHwuKakiw9es8waGp3BWd6g6DffBHudOANAGQSqlbZ0YD21rWWek4NkGQA1cpEaLnkPwAkkukgzACJb2ioZgM3LUHZOnF1wbF6GksflGYKtB8QZgNcLyqRR8uIn5FH2snNRod2xeRluPyLOAGzLfVce4b8sj+AXXpW/t/LHosIMg3PjMiI9zyn0JtMVpfG3+IlFqF//jbhz65O/AeYuLAlTl4JZOrA5vPoQNvbWr381/vz134D/vSVDeFwe3vsTqTNqr5+T2p1BiTPLnHCZoy1z4H3Vkrm6t1cNTkj3nXAfPkhNFzpGaSm/kAc28q9L7aGcK/LAS/51if1taUDHtqcLNAdAG2tp6D7tN6ANbXwWB+8B2HY2fkp4ez+E9l0S1vl37ByAdt25+KnmvVhv2rHjhjjVzepYRfZA0ZC8R6BwgJM1iIoRKBpCXrf5pqQHAIkcwh6AbOwvCOsn4pcIHJjipCCq/ScHwGcZB49jSlg+0FI4g1oDrGSIqCXUwOh240NUvtBimuWlPlxPoA1rqikT0Fz6O/QPsMbM6sORmNpvc1cE6qzxyzYC3ggctAtsHiwj8YYEPQD+CJSdiwp7CLwHsUfAFxT3Hxw49OKKWvYNun+FNxMroK2rV1yHX4817TJ78ZPiOn13cwTCh+L3ACQlfQz64+IeAH8AP7fouAR8iOAUHRd/AGv8Re+NjnvZGYb8fExpzK04iZH853Z3xp373O5O3hT+YCmYuQt7S6qOiud/aWcHfGtvCdzTFa+wJyf8BkodXxE6o+7UpVUdXY9rCtySDIDHNSXOACQvSWyrRPB138QAgiTCHygdFmcI1t+GNx4qlGYApBH+ghvywMcqgZPVSieFtqTXtR4Abay5ofu034A2tPFZHJwCtKcLOtIHwLPudTCyprCO9EEkAGVehFDOFaQEJTF70mvQkY7iMqHMi9islvSaMnensiAPGvqYnc1dfxvrVAlrVzjAG9Jw269DRzpSLohUEc4ai3lv4cxRRdyGNbxxogbDjTpCs7iI3z0C7uTbYEy4z5v4SHQnaBpECtB6Zk9WmvyotyCcNR5jbzNMIdmDscAJEUoiYupG4LZ8XKAYE+4rBKGqMbC2L4DTrxCBiCZEaEMimDSXzoFr4zIYE3F+c+kcR4m63dO8B8BeN6ew05noWO2xCLg2LIEx8T4nCFFTZfUh1BAg/jot/Mxd2PRZeTwKdbWYCTAk3QfnpmU4aF/gGgNBZwScaWhzbVyGgCuiiEKdjkLAjQQhw/r74ExbhoA3wokxxU8tQr1lgc93bEE7NbCWXGDzNyv79gWwwbjsXBTyDr8I+zLvQk7y+1Cf/A14dl8ntHX1QtGlRb5Q5nPTliHgi3BspqkHG335vhnBiJCnxU+hA0J2ZxraKbLe0dkLz+7rhLrkb0BO8vuwb/9dyO94ATGnjG6k/ly+AO6bavIf3HbAhXSjootYsuOpj8Qcc1+Qibp143FRH3fnpmUIuJXPVnpecQAqTyiCbuWno3C4oRfeTKyAQ7qXoFh3Dw7pXsK/m3uh6giiOtWOYOUJ3Aax+4+GrsSdf8J5Gbp8PfCbpPVwT1fM7R26l6GxHBvSRTX+1MjbXBS/hr+5BBn+shp/j30S2gTN9uGsMWjLF9T4H8BMm9CuO4eQgFxBgCBrDIMTogDCvjHozjsr7gHIf1ZYhx/eze47IjsjqMnq+KmBWBS0EQZdMoa0EiBtrLmhOQDa0EacwR2AvccVVcj9l5Hfzxb+of2XuYIkV/bdd0kRC6Pf919W5jK8ZzD/OoT2XeI/+fMMOafWB+CaAEw/IGjo42g7rj9AmgIkCEZOgFpARyWeQ+zrGHEcJrLjtU5AsHBA0QFg5A5C8HlrJ/lzakEgLh7EFEJJVMhvvgluzzRum+FAPfZJThMhaojbMw3+ylHe+Mu1AUKzXKSIRMVcXmSbu93TXPWUSD8uL4qMWdsWkJjChMLsDSg6Zq9TbNa2Ba6WSnOs7UrjsLr5kxZ/pNpa82iE14SXn0bxJ0vHAhcbI6Gn0vNYc24+FlFUYJnmQPVhtJu70FEgrjyVrlCpStm5KMeSmrsiUHQJyTYVJ3EBXHkcf5KabfGTqExLKsElj6PgWNlZfE3peYbEZOrAFCkv7FVKZUoeR0xm2VlFUIuX1LBtlnZHuWNE+yNePu2r6ii+35ILDIvJsKJlZ6OctFN5At9P+Wn8nWr0icJj6lkES8cClJ1RhNxIfZkITaTeS8e/6ij7v3RF+Dy10i/Rno7UX4E/zSqFnz60G/5ndikcqb8CtY3zvIFcrQpNpT81j+L5UNs4D8e9PfCtPSXw06274Vt7S+Ck4xJmnhrn4YTnMnxrTwn87y274c8yS6HL18PPP1vLPDSXzIIrFZ1RdyqSeEit1+WbgRbTLLhTFEe5sWKeC+P5q8Y4yYfsbYYpLrZH2TZ3yhJ3lNsM0+A33wSPfRLnJqsc+PwpzvIPlI1AOGssNkCQO841RYIFNzjlh9v1Ewqf3zQYG5xgCGN/JQYouvWnYylAG78LltzPc7VeDHzcVubuHlGUf8tGYgMj62/j4t80yO95HTswU2DUvY2BkT0jisaKCq9MgRWObtZffSCgw7DP+qtg23dScwC0saaG5gBoQxtxhloJuGPnAGP5v8O/EEgm3ro3Ankp/wtyE96DhoRX4FZqE1zYcwzFwQ5cw+yBSgegY1sf5/wrOgEqDYGMoRj5eco+qHUE+KLd0Acd2/tX2IOGPvwS3fsACm/vCNcBCJoGIZyBvQDcvmdEERFTKQFzhrcqk+CvGsMFAp9/G1qNM7zUhyuDkqiYSjXYa5tgGYDbXAegzTDNMwU+C6JEaSFDzgGJHnlrJ/nCyJCICMPmklnwOKZQbdg+idx01cKeFk21jfPQXDzL0Yru1CUIeCJQ28jKhJqUn46Dc3zhV9OJpURVRyLQYF4A18ZlMCShjkC9ZYELO9VRBD/xHXBuWob6mgW+CDV3RaDOxuYye9DF1GCPIvIy4KNIN9oDXozCm7vwZ8AdAbfum2DQYaScymhKu6OgP/4i7N97F7JZBuCL+zqhM9wLpssYBffUKSx9ZxpG4cvOoLNQdJHtO02xU/ah/DQu+gOeWBa/9yCW2Ji7ItB2vBe+kNUJ9esVHYADj74IZWejHNUZ87k86DyRMBrtm+yE8CQ1X18AOf903Dx1EV6WVXU0gpmTTcr/JOBRMitU9lN5Ap0ycgAI+Rp0Rfj/hHQhaOFv6cD/u7oHoLaJZZdY1qjBvBLlaW1fAEvHAhz39sCXdnZAw7pXIWf9+5C964dQ6vwK70tpLpmNwXRSJsteP8edXyqDI/Vsfp47pqDVMK2gPFOWoLVgJqbsrrVgRoXyxOuM1HvD+klFx2M9Yj65eBfDgXqtE5zX762d5ErAgbIRCOeOx+qIZI3FqPdaDF+EjLQfQVrKL2DX9r8Cy/5FdB4Yn9+i/wJkbP0xpKV8CBlbfwwWw7NcRNGi/wJkbLkHacm/gIxNd8Gif0Zh9hv6wJL1OchIuwtp638OGQ/9GKx7FhQF4QPXwJL1NGRsuovz034E1syoogWQfx2sexYgY9MPud2S9TmuA8ADMiTYyAI8Wg+ANtba0BwAbWgjzuA9AFsei58S3jMC1j0LkKT7aIXtLV05XNjbJa7x34uL9HDGkDiVbewX1/hnjUGw4IZYZyBzVGzbhwI+wm3vHeGCO76EsEITYj/95aPoPIhQffuwRIgvHoqG8Cd7zl81Bu0H4pcXtBmmleyA+SZ3ALimAItqihCFbYZpzkC3tWI2wOlHETEqI2o1xu8faKyY55kEygyoMwA1nVjmE3LErzcPuiT9AR7mHNSK7ZXH5RoDFScldhfrAUiM3wPQ0dkr7B/w1GGUPOgUb7vyeBQCAg0DXyACHZ1YRhOvB8DY8oLwmPkDGMUX6R+EHGgX9RCEHHhcvAfF9upDipNg7opwgo+tFfs86qvj/0+CTpxT24jnEZ0H1jZ0DqxtqEQt05Xo8vfAmwlxjkvCx1Bu+x/QXCIo8SHWfx06Ax77JDhCs9wJJpEvUYlQqwHL4IQlQNnjwmswnDXGhbzUaryk9OtLCGMJUOZN6XxL3rOQlPDxis9t0T+DpY17RiBFF6uPkJjwMVj0XwBLvmBu1tPoOOxfjG/PfhqChj6wZkZX3JeTdB/h/APXxPOzPof6K+qgDAVVjP1aBkAba25oDoA2tBFnrK4D8DpkbPxhXNsh3UtwZ5NBTPlZf5vh6gTNbkmIsxM12v0uzWyyJj1ZI517/W0IlAyBMzjLv+wp9e6vHMXsQPmoePuMEsRVPkuH+YLea0OnQIwQXFIyCFVjSAByTCnZABf+LmyOTF5CZCjTD7C1znMNAXs91v8L57LGS1JZpYZgtQNQfQgjxfHmuzYuC23OTctgPiae69y0DOYuiZ10AiSUoW25YgrQsr5UTMpJW4aqoxExiYe9NxnBaDm3VNjUuT3rXSnlp/y0/HOZj0WEdtfGZag+LLdXHscyKyq7KjuLP22t81BxKir9f5JSr7U91gGgRvPapnlpI++39pYIj8vO3T8RN/GyJl+PCwXwPA5srKfSN67gK7kOvNYJaaOvtAmY+njKmeIvKfwyB0B2/VOjbl7am3HteZvfhO68s9ChezmuPWPLPcjb9L34czd8B4KGPsjb+F2B/bu4b4k9lNsLeRvEdrE444DmAGhjzQ3dp/0GtKGNz+JYVQdA9zakrf95XFux7h58kLoLDLrfF0dHGgMSu6FPisOTovRWmUuKm5QByP7aFK/tDZQO/24aBKXD4KseQx0AVgJEGQTZXK91QukTcE3BJx/mcQ0Bn2UcPPZJKd7Q45jiEdJPPswDl4/1CnimfycNAYq6OoOzMToAtBAU6gAk3pdqBFSekGgIJK5iT7oPlcejUt69TAfgp9t2S+dWnIpKOf/mrojU/v6O3UKs44Ztv5LOrTwh2XfifTAfk+w78b5cm4FpO1QfQgfgkw/zUOuBlQ7VPBqRz+1cgJpHIzEOgL1hjhOlrG3y8+GvN2eIdQC2/FJ6LpIgntszDR77JD+XPa4p3gwvw4B6bRO/9/2B+nnoev3kwzzuCPgSwhAokeuIBEqGIDfxvbj23MR34Y2HCqUYUNncoLFfbi8ckNvzr0NugtguQzPb9p8CzQHQxloamgOgDW3EGavqAKz7AzIASasrAa8W4Q/lXPm9MgCedbchWDggzj6sv817CGjRQwt6v/kmby6WYf4CJUO8zthfOcrr+L1W7AmQ4Ql9lnHwWrF+mQTBqC/AY5+Uz09ZArdbaRqmZmCqoXb65RkAKh+y181hVJxlQXwJYR4Nloo3SSL8q0Wqqw/LMwSVJ6Lg2iC279gvzgAs5ZVK9Qsqj8sj4bLMh3PTMvzPHHEG4KHcd6X7lkX4uV2SQajplGszkLKzuQvLeSgbUPNoRHrMXRuXweWd4c3j6gyAtR3Lf2ytkgxAyhL8+W5JBmDXO+DWfVM412OfxMwXi/q7vDP4f2BN8B77pPQ68tZOis/19belGUJq6qdrmJcAUVlg4YAcA1o0BA2Jr8S1NyS+Cj9L3inGgG65Bw2J8bUVGhJfhaChT7LtV+T2hFcglNsrnS/TCLDlnAbNAdDGWhq6T/sNaEMbn8Wh9ACcFiLjrHsjK2pJqQege/8J6NjeL5yLtAmBhkD6IOJFd4o1BoIHrgmRdR3pElTevjGcK6rh3z0CFSejvAk4UDoMQWM/j/wHykYQ8yfCAGaPYxNh5Sj4LOPoOLDyAXIAwlnx57brcaFPdCG3e5pHI6ksSNYD0FKIDZAeFyJEqRSIawh4xBoCTWVz4AzOcvKQM4h12LwE6FF0CEToxgbzAjSa5+PaDtrReRDVi9fZWF35KXGPQNXRCAQFdfiN5nkoaHxB2APQ2dor7k/w4bZFdfgBTwQqTkWFGgdBVwSO1F+J3wOQ+DEUNLwg3HfQidsW9QjU1aIYm8geckSk9oYqbOS1tc5D1dEIp/pYwgtga8UofoM5/ntrNM9zlKy6FIyi/5YwOgLNxYI6/tI5OGW7FL8HIJH1AAg0KdoM07HnrXuai+pRP4vsOgjrqVdG0AOgnxRiOlsZJSho7Fd6f1g/QNA0iCVAlaPi+0cmlgneSmuNa7+1qQXe2FoQVx8hRfcbsGQ9Dbc2NMefu7kVgvnXxfYNzRDafxlubRTYU5sgaOiDW5sE721DszRoY8s9ozkA2lhTQ3MAtKGNOEONAe3Y3o8sf93byPnfqbD4rbvmIC/1O5Cb+C40JL4Ct1Ib4cLeLiT5ZF5U5ia8zTUCQvqrSJrI7kHCUAznfxAJQwxZ15E+AB7G2vesex1RewwJ+iDOzk24vAPXsImYUXr4XEb5CRr6IFA0xPZ9O3YuW+yH9Fd5uj9QNMR7APzl+AUfKBlimD/V/H1jCi2oZAipP5WjvKTHVz3GNQJaTLMqBOES8sfZa/3lo7wEiLIB1D/gtU6A2zMN4dxxZT5RhJgCMUX8PXZFVIyrCrtw4aRGI7aYMOpPpUP2eqQG2euVyC85BzWdC9BUrmgQuDYsQX3NAtjr58DUswgH7UT5QR2ABjP2DhDJp84aa280Y2kRUWPqLUQYQvtBOy5iaQFbZ10Axxac79y0DPXVSBmqOhKBwvoXYN++u5Cz/n2oX/cNeG5PJzza3AvljyH9pt6yAE7VvussCxy7WX0Ihcwe1DCoPhzh5Bz1Z3NuWuZNtpXHo3As0APP7UEKUE7y+7B/710oaHgBzMew5OagXdFOcG3EuRWnMBJfeRwbgelzEx2JCEPmLmy+Vh+3egsuzCtP4Dbqa9j2VZ/NfCzCF+o1ndi4W3UkgpkcH0bUba3z0Gie5+eDa8MSNJrnOe3HGZwFW4viANQ2znM6T23jPNhaUVzOtWGZozybS2Z55umk/RI8v6MDcZfr3oOcnT+Eyqovc7Xr5qLZmHOxuWiWn+t+800lc+VWGuTpd07TIgwoQ3mSo40oT9V1wrQ66LpEClDs9eurHoOgaZBfp5QJIMdfTQYLZ47G3l+yxjlA4LzxPLylK4/RR3hLVw7d2aeg23AOPkpYt0IfoSMdlcqFc7NOQrDgBlxIPyzcdvDANejOOhXXfmFvFwTzr0P3/hPx7RlHIbxXFFQZ0EqAtLHmhuYAaEMbcYZaCEzN9Q8a+xWu/+4nFE2A3F58bt8lfOivKq8jrCcT+Apl9yh2NpewotRwS7oAxPcP6a9yJF3Q0KfoAzBnIXjgGj6I53/gGl/I8+3or3LONqH6Qvqr/GewcIB/gQeN/ZjuN/Yjuzv/Oj5v6MMFQuUoR4YGSoa4LkDQ2A/+qjHUEaAFP1swqMsJuH5AyRBf7FDkn2hBVAJBegG+6jFweWeQEOSYUpwC5mDQAslbOwle6wRHgrrd0+C1TWD01D3Nm4s9DsVZIEyoy4v1/46DczGlH/Y6rP3megFMZZiEy2gxSGUmljBy3u0Nc1DzaARsLfN8kV99GOvKaeFta8GFLGkPmI/hgr/6MC76S7ujGMU+EuHsetIiqDgZ5Q6AuYstqlntOi3eq47iIrz6MP5ua8EINuFHK04iR7/6EBKBiHNfciHKyTnmLoYrPYL7IO5/5XGF2195PMrfO+2z5lH8vexMlIupVR2NgPlYhLP6zcdwsV/TiYv2yhNK4676/dQ2zuM2GL6TaDx8gc/+JzWdWLZj6cBIPx0P6gew189hJqBDaeglDQj6P1nbF3i9v71uLsYBqG2c5zoUJBrnsU+CrQWdA1KudvrxNeQ8qvGdjhBmmNTidRTZpwZg6gHgDjQrgyPH1m++ya8VwnRSwzBH8LKFvL9cKcWjazJoGuQNvzGNv0wMkK5rav6nskACAfBSvyokf/H7AHt0552FO1sL4IPknXBn8yPQnXeWozq788/CnS2PwAcpzJZ1UtFCKbgB3frTcGfzI/BB8sNwZ7MRF/+sNDFYcAO6s0/BnS0F8EFKOpt/KiZw0p1/Fu5sNrLtG7lzQPu4sLcL7qQx+yYDdGedUtDMJM7INAQ6tuM9X8OAamOtDc0B0IY24owYHQAWxTfo7oMn8TXo2NaHi/j9l1EHYMN3FB2Ajc1wYdcR/mXUseOGMlcV4Q8euIYZgvRBhdXPdABIdCx44Bp+GalY/h3pg5yFfWFvF9xKbYKGxFcUMZ39i4pK8O5h8Ky/reDsmMYAieWs0AnYjWI5XttEjBKwWkcgaBrkUX6KAMZwwE2D4HExRWAWhaQsgnpx0M6ij3zb2Vj6Q84AiYPR35QRIDxom2FaxTdHDQJa+NOCn6sHs8i+x4E/STyJ2Oktplm+yLI3zIHLO8NLftQLv5pHUSW4qWwuhvveVMbqwX0zUF8Ty4RvNM8ri80mjDa7NijM+YYqtkh9FFGhMfM3LkOdFR2GsnMoOlVXq+gIcGZ9By56TaEXIHvXD1kG4FV4blcnnHBfhopTUbC2LyhzGWufsguExlSi7GzbtgVeL2/pWIixOzfhvitPRKG2aR4ON/bCcxlMB2D9+7B/z114pPkFqDyBTkHAxXQA2LabSnFxXX04Ata2BVV2IZbFX/MoOghq/QTKnFg6Frgj01Su+p+kLkGdbYHrOZDDZW3H/4EjNMt7OmobsTRL+Z8tQ2PF/Ar+vroZ3NYyDx7XFDgO4uK+xTQL7lQVy794ljuXp2xKBiAn6X3I3f4DqCp9nhOt+LnI5rYasPmXMlcx5+r627w8yOOaAn/VGLQaYzn/vASPXT9thmnlGk1eQrEvpvPRrp+MvX4zb3KRL3/VGGbZ1Nd/1hh3AAJFQxDeN8Z1ADzrbkM4axwX+Ex0MJx5U7m/sPtDoIip9arvPUwkjNj7eN8bYfsm9fUBzvhXZz4NaiEvEkNk5ZEx901WdhnSX4XQnie5kJhBR6jPYe5gPHhPppJLTQlYG2ttaA6ANrQRZ/AegO3n4qeEt/eDddecWAdg5yFxjT8rIRLW8JNdoBPQsXMAunMfg7d05Svri3UfgWX/oljSPov1AGSOCnsAgsZ+sUZB1jibL+CAZ45yYhCp/JITQIrEovrjcNY4j2aSaBhlDDz2Sf5cY3n8WvtWwzTPDBAxhbbndmNEtrUgfg9Aa8EMLxEiwTG3Z1rJANQjIlRUt91UOifsAWioQtVh0dzGcoz6N1SJewSqjmCZi6hWvtj3VWEPwOGGXmGdfH0NLrLrbOI6/drGeXGdvnUBjgbFPQAl3q8K33eDGZ0bUW9Egxkdm8aK+Me1zrYAFSejwuNeb1ngLP/qwxHuxFk60BmgEpy4/5OKeX4OqEvB7HVY2kPng6gnpKlsDs6WPiHsATCb/0TYj9JiQsVrWQ2/2z0NbfmCHoBsvI6EdfqSHoDwPnTiRfZ23Tks/xH08VAQQGjfNya+N+0e5ov/uPYMdB7EqM5B+X0zfRCdB1F/VMaQcN8dOwe0DIA21tzQHABtaCPOWJUClPQ6ZGz4QVzbId1LcGdjvqSh7DUIZff8/pSfpNfhziaDmKSx+UfSbQdKh6U6AEHToJgSxDjfYpY/6gBY2xewTEAtKsQeormedbEEIXUJEH9USjQI1t+OKZGgKCyVAfmqx8RzU5Z49sDlw6ivugTI6ce/hez21CUxIYhIOkKC0DLWjEuINFVHJfM3yilAf7q/dPX3Jtm3tX1BOv9Ps8QUoB37xRQg4vTL9m1rnRfP37CEJB8Jmclej9kZKvNxHJzjUXxb6zy4JCx+a9sCL9FRnwfO4Czy+V1TUqrUX6QXC4/Lrofv/w4cf/E15nFNSSlAgbIR6TUquwaDhQPiubpvYjmR4P7gXi+f71kv2/frEDT2S+9dSDCT2POvS1Gewfzr0vnSJmBNB0Aba2zoPu03oA1tfBbHH6wDkLxTjJTTvQ2hnCtilrbubQjl9kpZ2z9L3illaUs5/QU35HZj/x+kI0D1wv7yUej4zjleAkQ1/6vqALAmRl/1GDzxw8NIBmJlB77qMel8Kjvy1iI7nWNEq7GcSKYhQDXYPss4uN3TMToAjtAs1DbNS9ntMpuMOW9MvA+Og3NSu6VDzJw3Jt6HjVskOgAP7Za/t045z776sJyXL+Pdb3hIzLs3JN4HS1i+b3OXfN+2Vvn/xNKxwGv7P/kwj9f82xvmVv1/2hvmuDK0uhTM1jLP0ZwyFv8Hm3aJr9FN/yA9j1fTu/BZxldl8f/eOgClw9J702rbXk0nRKpvYhqUzsX7omS+9N719qr6KjKbLesx0BwAbaylofu034A2tPFZHKtnAF6DjE2r6QC8Fn/u7xDhR6VgSQZgs/H3zgCE9Ff/sFJDkiYAACAASURBVCicaVAa4eMNvaz5N2ga5GVAfvNNuYZA0RCnjqjxn/TTb765ahSfGh+9NkVPwFc9Jo/YJt9GhCgrIaLsgZr/bm+Yk0Z8RdkB14ZlXDSKItWpS9hYKskQ4HxxpHznnp8Iz8U/21cKThHH/3eI8DtCs+IofeoS/Ol+eQZAFqGv6VwQf64NqMYrPW5N85LjvsSVnakhm3oAahuxoVv23qjG3+OaUhzBg3OcNGWvl5wPKfIMQHr6O1I1Xp9lXJoB8FWPSRW1/eWj0mtcdv0GSoakGQBZdsGzitK4Z93tP0z/ZDV7bu/q91VJhkA2VysB0sZaG7pP+w1oQxufxcF7ALadFWLhrHsWhDoAF/YcE9eibuvDBmAR5z8dxbZkPQQXMo8LewCsexaE2yYUqKiONpyBRCBhHe5ubAQW9gBkjcfoBVA/AFcSLkJ8aNz64gPY5KtWEqa6f3IAAqXD4vrkA1O8cZgW/EQQIhGxsH4yPns9f4pjRNWNw7TwI6qLqG67tWBGWOveWIGLT1EPQHMRLkhltey2VjGzvqlsDkrdXxH2ABwL9Ajr6AlDWieqw69Cx0fW33DCcVnYA1Bu/bKwZ6OhChtxRZ+rnjU4i/bdVI6NxKLP1mBeiCnZcfpneAmQI4ToV9H/s7kUX++tnQSnXzkPqLeEHIMWU/wegtaCGXjMchHeTIhzjSZ8DObyW8IafkJ5tgvO1Xb9JPjNN8VaHFmovxHWTwivE9E1GN47wht4RT0AwYIb4vlMB0DYY7BnRDw3AwlBYo0SDCYI710MYiCr8Q8W3BDfl3fckNyTB7UMgDbW3NAcAG38l41f//rXMDIyAsFgELZt2wY6nQ6+8pWvxH3tJ598As899xyUlJRAamoqbN++HdxuN9y7d2/F6+bm5iA7OxtSUlKgqKgIXnrppbjb/MlPfgLBYBA2bdoE27Ztg2PHjsGvfvWr3+uzxOgAbOtT6QAwLBzDcVr3LDAK0LtIAUptggsZRxHxmXlRQcoR53/nAMfNcR0AQs4xSlAouweJGAeuoQ4A6QQwWkUouweCB67BhT2MApTwCuQmvgt5G74LlqzPqXB2I7Fz94zE4EjDueMx9o70AY75DBr7oV13jmkY3EdSR+44J3EEykZQcEitQaCiBJETwLdn6MNsAEOHqjUK3CpCiL9yFDUH2KKfMgFEEaLofpthSpmfjAQSQh8SGpHEk1y+GSwtsiEyFDUEiJ2OZBQiCHlrmQKrA5/jDgDDNDoOznEyi5rdTgJNzSWz4NpATPllaC1ARCgJk7UaZ8CdusSZ8U2lcxw5aulY4IQhsjeaWb06i2Cr7a4Ny1Bfw+g2jfNgCqopQN+AL6V3wEnHJY7BrLMuMALRfU4gIrErS3gBGqpUnH9G6rF0oMaBMzgL9dULsfuuRhSptX0BjtZd4RSg3PXvQ1bGXTAdfIELZ9VZlH27U5egsXye4zhrm+ahsXw+RluhsWKeY1HtdXNQX73AjxuRlwjJSQ6KYsfjYm+Y4zQfWvTTwp3jXkOM4pOiHPOWQiz7oSZgj105Dzz2SYz8exitp3oMWf7JyvnQWqA4DmdLH4c/fqid6wDkbv8BWAxfRFytdQJaC2Zi9SyYI0plcG35U7F6GUzky2ubwOvoQZZ/5k1O0fJVj0FYP6Gw+uk6Y9m4mGswWUXpKRwAf/lojMaIh+mE+BLCmOErGoLw3pFYHYB9Y3h9k1igSieE318YgpjoZsp9jd0rGMI4vHckRv+E09Pyr0Mo58rKexsjnIVyriDlZ8+Ior9CFCDCNOf2rtRf2daH+OXcXrznJsXeF0M5VzQHQBtrbmgOgDb+y8bf/M3fgE6ng/3794PL5ZI6ACdOnIB169bBY489Brdu3YKnn34aTpw4AX/2Z38W87r+/n7Q6XRw9uxZ+OM//mOor68HnU4HL7/8cszr/u7v/g4efvhh0Ov18PnPfx6mpqZg27ZtUFJSAh9//PF/+rNwB2D/Kf6FgChPJgTGWP7WvRHI2/hdxIAmvgK3NragENgDC3yOm2MR9lBuLwTzr4Ml9/OQsflHkJb8C8jY/COw7llQ7IY+sGQ9DRmb7kJayi8gY/M9sGR9Dnn97MvQkvW52PmZUY4JtWQ/DRmb76Ft64/BkvU0J/EE86+DZf8iZGy5x7b9I7Dkfp5/QQcNfagDwLQB+E9icZNCKGvyDZoGlVIfxgmnpl0qB/Kbb8awwuk1/HfWNMx1AhjKkPoB6LX0O+FBvdYJbP51TSk6ADbmBNgmYh4exxTXEfDYJ/lPIgfR4p847zzyywSZiP5ir8PFJQk+1TYp1BiKOFMzMS1iabFrbV/gmgL2hjmuGWBrmQdrG77GXjfHG1i5A8D+ppp2wlzyv1vnuSNBmgM1nfiwtc5zLn71IaYncDzKF+g1nWwxzzj61YdQMIu2bz6GHH1rO5J77PVzMRhO0iywtuM+iL9P75deW9ukaCNQWRUhUunzW9uUecT5Jy0A9fP2hjmu9EvMflvLPG/gtjeg40LH3OVTFv3E53ccVP6Xah0I4vnXNs1jA7nqPCCnkua4PQp2loTqCPNJ5ySp+DqDs7xRnfj/Xpty/hKOljJXpHVBvSle2wRmw9g1wa8XQn+ynzxjxq5P0gKIuR4fvOYqR3m2LlA6zDU+SC+AlIDJkac+H+7gs9eQSOGDmT/Cg654ztCHr1cFH+j+RwELrnOitrF7KDkNfDvs/hbK7Y19LeGXSTeFvY72zZ9n97gYzZbsHq0ESBtrbmgOgDb+y8ZHH30EH374IQAAfP/73xc6AF//+tdBp9PBq6++Kt3e3//938P69evhiSee4M/99re/BbvdDpmZmfAf//Ef/PkLFy7Ahg0b4G//9m/5c9/61rdAp9PB888//5/+LLwEaOsZYRmPdc+CGAOacVScTt5xA0K7nwDr3siK+UkJH4N1zwIEC26AJevpFSVGSQkfgyXraR6pStH9W4w9MeFjsGbMgyXrc/Hn7l+EUM4VsOR+Pr5d/wX+hetLCCsOg7Efv7BVX6AUheOc8MybMc4Jif4QEjRYOMAzA+GsMaZRoGgI+CtVPQMkUFQ0xBf69LzPMh7LMGfRSzVy1GcZ50JkfIHDIqPh7PGVGgK2Cb7457oBqsgv1xSwT2LUltjsqZgBoGZjiiYbEpBH31owo4iIMRQo576zDIAzqCxIm9R2UimuVwSp1AJStMi1N+AilhbS9HD5ZrgSruOgEiUnjYK6WsSTEiMfMwQKS7+pbI47IjWdCzwDoNY/IIeFePf1616FnPXvQ3b6D6HY91XO2m+sUOkfbMDsgroZt8G8wD+3a8MSquv6ZrjIWmPFfKy9CCP01JzdXBzL4qcoPiFdKQvjdk9ztr+9YS5GjVetC+EIzfKMkdc6oWQAWP2/x6X0iqAmxQMsf7ZgP1P+JM8A5CS9D7kPfR8qLF/mKteYAVhSzuNcLEOjzBcpXvPrRK8S+CofxSi+6lxu10/ya8hfPornesx1Nh5TivegDgB37B/Q+UDO/xh3AHD++AM6IsN4r2DbCGcM8Wvcs+52DGufz9Vh5qIjfVARSiQF9KRY/ZOQ/io6ADlXFI5/wjuxmVVSWGeZU9IJ6Nhxg4syYtb2u4p2S2oj125RZyeUfaMGgaYErI21NjQHQBv/LUPmAFRXV0NVVRUAYInPv/zLv8Tdxhe/+EXQ6XTwzjvvxDz/0ksvgU6ng7/8y7/kz6Wnp0NHR8eKbeTn54PX6/1Pv3+lCfhZUDeD0cOT9BpkbL4X18abgGXNavsuQd6G78S15234LoRyrkDexu/Gt2/8LlzY0wUdupfj2jM23RVve9P3IFhwA/LS3hRum8p8fAlhJeLPFDoDpYzVLajjbTXOcGeBqwNTat/QhwsHEQd831iseBghRKkxmDkFwhpi/SRf8FP/AJVSUERVVBfdlj8VIz7Gm4dVkV+vdQJaBWz2lsIZaNfF14xoLsEFvog531wyC7ZWXMQKewjqsOzE2rbAVYcdB+d4WQsp2TqDszxCTpmF2iZxnXyjGVWIRXX6jeWY2RDZm8rnoMvfI+Tdl3q+Ak3lYv0DKv+Ju23mHMl4+Y6Dc+LeiFKliddxcA489knu2JEjIKrhb8vH8h63ezqmFMzlm+GKuyQqF3e+YQrOlj4u7QEQnYvhrHFpjT8t8oXzs8f5Al20fWH/ABPkC++Nf422686xOnxBjxHTARFe4xniHqDwnhHsARBpkFB/kqhHYO8I6gAI3nt4z4g8aLOnCzp23BD0AAxoQmDaWHNDcwC08d8yRA7AP//zP0NCQgI88cQTcOPGDUhLSwOdTgc5OTnw9a9/Pea1Z86cgU2bNsFvf/vbmOf/+q//GnQ6HTzzzDMAgJkCnU4Hc3NzK97HsWPHYPv27f/p978qBjThvhwDuv5hKVIutP8y5Ca8F9eem/guhPZdgtxEsf3OZqMUAyqe+x6Ecq5Itx3SX4Vg4QDPAPgs40r6nqX1pZQgyhYUDkDB9UWMRlaN8Qj+ahQgKkUIlAxBbeM8j+BTZFHGN/dVj0HQ2I8OAKtX9lnGeU20jL1ODgM5EOZjEb7w89omwHFQTn0RagSkLIEjNCvdt8s3IyXSOIOzPIpNUXWXd4aXv1BdOpUoURmNyzsDlg4JSYdtW0ziWY1QtAR/nlEipN3s3PMTKWvfGZyVayt4Z6THvLZxXmh3bVjiUX63R9F3cLuneU+HbNvqMh11DwBpS3gcU+JzMWUJ3thuEusA7Hh71fNYRgGSXkfJeB3JWP9CHZDk2xDMvy6lAMl0QDxJr8s1TtbLKUCBIswaiLYdNA1KWf2r0dOk5LbNRul7s+09DpoDoI21NHSf9hvQxtocIgfg7t27oNPpYMeOHbBr1y547rnn4Gtf+xpUVVVBQkICLC8v89fW19dDbm7uim3/67/+K+h0Oujv74/Z14svvrjitdeuXQOdTgcfffSR8L3+8pe/hPv378c8vvnNb8IflAFIM4oxoEwIrCHxlbj2hsRXIHjgGjQkiO0/S35YigGVbrtwQG439isOAIv8UylQoGgIQtk9q+oMUKOw1zqhRP+ZHsBq/HJ/+Sg4Ds5BoGgIHKFZzAKUYL2wv3xUrgNAddDlo1D85CLWSZcOo4CYe1o6l8qGqHwj9+XY5k9ncFbKZpdy/kOzcuZ8nVwHwBmc5TXtvoQwVB3B2ndnELMHVOZD9fWmnkVez26vl2/b3iC2GxLvg7d2UjpfxrvflPZL6TFzBuXHxdom1z+QsvjZ9ikD8Nb/t5+XW3lrcXEvm0slPmoMqMcxxaP/HteU9LN9sFGiA7BRrgPgr5Sf51JW/+8wXzpXdo3p3oZg/vU/TAdAJ+H4G/rknP8D136H+eL3npb8i7i2Yt09+CBlp3TbmhCYNtba0H3ab0Aba3OIHIBvf/vboNPpQKfTwfe+9z3+/K9//Wt4+OGHwWaz8ec8Hg888sgjK7b9ySefgE6ng0uXLsVs88EMAgDA8PAw6HQ6+Md//Efhex0dHeXv6cFHYHv8so6OnQNg3TkjxoDuOiJGce4ehlDOFbiV3BjXfiu1Ee0bmgX2JrizyQD3dMUr7Cm6fwPrngXx3I3NEMruEds3tfCmN19CWIn8UyMdawiWZgBUzkKglNX9Fg7w52SRS8owUNMiaQLwJkVjvzSDQPN4DwBlAFjDsZStTk2WqvIhngFgzZnSDIBMI8Atjja7NqwS6U7FDAJvLPYiztLjmELOPWtAdgZnOeqSXlfbNM8i/JJtr8LDl0XZ3SlL8Oe7xLz7nXt+Ip0ry6q4UpekWRvXhqVVo/i02Of8ftao7a2dlKvppizxBl6fZVw5D1h5mL9yFDMEEpb/Gzt+/wzAqtdJwQ1xpHzd66jWK7lOVsvCSTMAhj4p51/K6k+SsPbXvS7f9moc//W3UQdAkiHI2HQ3ru2Q7iW4s0Gi3r7uda0ESBtrbug+7TegjbU5RA4APZ+Tk7NizqlTp2D9+vXw7//+7wDw2cgA2PYefwDV+Rp0bLuOdIj9l8GaGVUwoImsoSz9MBIo9FfZ3NdicHOhfZcgtPsJuLDnGLylK4dDupegWHcPDulegrd05dCddRJC+qtwYW9XfPv+E9CddRI+SlgH93TF3N6hexkb7Q5c4zoBcbedcwW6s07Gt+tPIw5PfxV8CWFOwaDGXrIJWdt7RxQqByN68B4AYz/4q8bEGgKZozH0kEDJEMcK+ssRDxooHRbP1yP5J1A0xFGKaueBmo9FddUkPMb1B8w3+cLPb74JXuuElPsu0higptJWo0BDwIgNq6IegOYSpZnVcXCON7/Sc9TQSgJXTv8M7wcgp0CkQdBiQpKN7HPJauVbCmfgpP2SsAegsurLYv2DYmzkFdlbjbjvNkN8Xn6LCRt1ZceVmrupAdjtnuaEHNnnJjSsxz4Zcx74qsdQH4I5i6L31q6fhPMF5+NrdSR8DDWFfyQ8X8L7kHIlZOmzXhdhHX8mOsrC+Vlj4jr5LGzWl+oA5F8Xz8/ATJ3wGt09Iu4P2DvCmnDj2zvSB1fVR8EGYLHGiTUzKg7aZB6X9AAMak3A2lhzQ3MAtPHfMkQOwM9//nPQ6XRQU1OzYk5fXx/odDr4p3/6JwDAHoCNGzd+qj0Atr3HIZh+ARfCmRchtPsJjvhU8/rpd+L/kwNA3OnQnifxse8Svo5F2S9kHoc7G/Lhg/UPw500I1zYc4xvO5h/HS7sOgJ3Nhngg+SdcGeTAe1s+91ZJ+FOmhE+SH5YsdFcQx/aVXO79Wf4Qpx0BPj8NCM6B4TOM/ZzDGho3yXFASAqkIoCFMPqpqZhYz9v4A0WDijZALa4D+8diWGEh/eNKdF/piDsLx/lJJ+giVFAGG40vHt4BYOcY0Ypa6BCj/qrxiBQMoQ6ACo2ujuZkVXYa2l/hBFVl374q8bA6Z/hZBVis7caGS/egcJQ7uTbChPeOMMJQtiEPKlw/pOXkCDD0KFu9/QKJj2ReFzeGb6Q9TimYp5zhGYVdGk9NrsSotTpV5j2rQWxGgTNxYp+geMgNim7UmP1DewNGDl3+pGWQ6x+dwqSejyOKbA3zMFxTw98aWcH593n7PwhVNR8mWciiG6knkvvzRGaxeOgsjeVznHnxumfUY5LgnJcCdXpcU0hBSgl9rhSs67HNYWZAs80R2dSM7DXOgHtB6aUbSffhhbTLD9vPPZJ7AlRZwDIuSwdxsZwo4rlT/tm6M7zpgtwayvTAUh6D/QPfR+qi5/nGNtw1vgKFj/H45aNIIlHzflnDb6BIkRuImtfxepndnK8w5k3VdcZbj9oGsRFfva4YiNCEHPyg/nXmQ6A6hrbO6KUBbKF+oMaJer+n470wRWsf8JxxugAJDE8MrvnreD001z9VX6PVfRR3lbuPcZ+fM3+yyuCNpR1jQnaJLKgzcZmuJB+mMMPFO0WRfcleOCa1gOgjTU3NAdAG/8tQ0YBysjIgH379q14vqurC1JTU+GTTz4BAIBnn30W4lGAvva1r4FOp4Nvf/vb/LmdO3cKKUAej+c//f65A5BxjAuBEcufhGG4EFjK//r/2zv36CqqLP+fvJMb3iHJzftxA0GSkBCTQG5AyDvayAhJprUB0wIBAioPQV7hEW4SoO3RRsdRiIzz01anp5cubMXusWVYo4OtKOpvAKXHB79Reik6a1RYCtjG7++Pc/apqtxblYAihOzPWndxU6fOqapDVd2zz9n7uw1Juai/QUv8z1CXugy17sVSro7qUhIxNciuS75dtW2Sq4s1BtzmpDSWY6cukwP4uJvQFX0DpgU/icygY8iKellKiI5ahbqUpfpH1FI3fbk8duoy/UNnlK83ZuBVHgAyVrQ+du56rbVNP/DZNIBI3GjVAVcDCXIjIhnR2px1euBC0ot64KKkQmtH32kEDqvBDiUJq8lvRUOKISNKgxetGKTUh3Q8AK0AqBgEi7RiuFG3dswaPUgktyFzEHDVhDZUTmrHxNwHET/yCAZFfYL4kUdQPH6XnCkuaUNxUZcui4s7ipL8nRZZ0ZL8nbo81n0UxeN3yQHlJLkCUZK/E/ExhxEdfRJxcUdRXPyQzEirZrKLix9CXOwRREefRPzIIyiasFu6tHh9KLjmYcTFH0V09EmMTHobhWX/KI0CFQh79cTdsnzQScTFH8XVpbulC065DJAt9O5GrPsoXINl+fjJ/2hRGbp64m7EJryN6EEnEZso26cBfHlFp1E++CTi4o6g0Gu0XzBFnptryKeIi5fXpdV4qraiuKhLX1dcvOyXqZVbtatOUclufW1xcUdRVLJbz9BPqd6qczmYtffLKzql0Va7TSbmqt1mJIRT2vs6cVzxZq3PT24+5AZmVgGi4F/KT0ErSxQ3Ul2iDEjVZtWENm2U6pUlZWDW5LfqGBVyK7LkxqDAdzJolUqVVsVS/5oNZ1opM2v3k+scrabpSQBlpFP9Os9KQxd/1Cqdybsmr1Ub9totUMl90qDbLBFcl3mHlgOmAX9dxgpDb19p82st/h65APR5qIkV/U6gPCSjVlnOl95P2kCghGCpy7SsqKU8Zamsl7pMxyvVJd9uedeZc7XUJd4qZUDds9kAYK4o2ABgLgpOBsDSpUshhLAk/frss88wZMgQXHfddXrbRx99ZJsHICkpyZIHYNGiRYiKisKHH36ot73wwgsQQuCBBx447/PXeQCGzAu8JDxijdTat5OUi/+Z7XJyg7tVz1LZtV07+k6HtPTrsCi1KbB7gTiL0swd9nWVXrbdMjnNdtVl3iF/7FXynJp8lRRIGQFOMn+0AkE/2Lqu+rG3dQ9IazMGHhQ30CMxkeOxkzfL/ANqwEWz/qQeNPGnv7R3m/D49ACrduxamYzJbACoAfqE3AcD5k8oKtmN3Gv/T+CyCbtRXbwZJQU7A5YXF3WhYnI7JowLXF5UInXjS/Jt6hd2obioC8HB31jKwsUZzBgrYwOKix/yrxt8Ts/Sj5/8jwgJ9i8vLn4IVRPaUFSyO2D51RN3Y/J12zEjuxPh4oylPDj4GxR6d9tfd/FDKC/vRNGE3Y7lJQW7Ah67qGQ3Kr0+TKndhhlqBYEMyhnZRoKtykmG/Gd1SZteraHEW1LHnwxCubpARhkN9s0uQJRPglZ16lU2Xm1Qenw6G3VD2hZL2w0en76Pa8ZLdxiLzr/K1EsDfcrWbc4DoIPilSFt1fk3svmSHKelflqbHrQ3JG+yGtHuVm0g1OS36my82aZsu/qdMPpOq16+0vLXK6LKTbAilPIAPKvdg2SG8/XWyQnlvqPbJp1/UwJFcj+sHbVKTaw8a5ybaXVBZ1AP6ZEnQA38vcl/h6zoV6yTNomzpeGQvhyNMWutkzJx8ri8AsBcabABwPyg3HffffD5fGhpaYEQAjNnzoTP54PP59OuPZ988gkSEhIwePBgbNq0CXfffTdGjx6NqKgovPXWW5b2yId/wYIF6Orq0pmAH3vsMct+H374IWJiYuDxeHDvvfeis7MTw4cPR15enqP/vx295wF4Fm6Xg6RcdLazClDqMofyZ2Uwm0Mw3P5BY+xVgAa9ad92qJLpcwiUox/iqqAG1IzfqGfRzDNujjkOMlbImUXzTKIpHsApeJEG7HoWUMUP0KBHBm7a1A+TwZHmTMHaiMhZJ5WA7IKAw/YaCchUzgBz8CclJMsc8XrA+p6hB+EZ9lrAsswRrzvWzRz+OsrLO5E53KZ8xOsor+hEmjvw/ZYZ8zriYo8ELGsUT2Be8W3IjLFvu2JqBzJsyjNiXkfF5Hbba8sYeQjzim+zzUkRF3fEvs+GvYaplVvhGWrfb+UVnci0Pfbr0j3IRoufYgB0dugeGXYrpnbYasrXe9r1DL9ZBUivGKgVAFs/+2SHskyl82+n458iDVf7fBc+53JlBNjG6SRvRkPyJkcj2jEGQLn/2cYf5KyzjxFIsM8x0Bi7Tq962oknyBwENpMXNLnhMHHiTbzLPgYgUa72Bqwbs5YzATNXHOJSnwBzZZGWlgY7RZ3jx4/r/d5//33MmDEDQ4YMQVRUFCoqKnDw4EG/9rq7u9HZ2Ym0tDSEh4cjJycHv/71rwMe+8iRI6ipqYHL5cKwYcMwa9YsfPLJJxd0Hb3mARCHnfMARDhIyonDqEtZ6ig5V+dZ6Shn90FojK3E4OCwv9hL6YnDvcp40vJ3VVADavJbMeapTTqmgXx0HWUAyY1g7FrsfT9Hz8qTa5GjzN+YNdoNqSavFXvfz9GzoTSYd5RHpNnV/FZ0f5yl4wnIL9qxrnK1IHeL7o+zDAOgYAOqS9qQGfLngPUzQ445llWXtCHDrjz0GCrLfBdeHnIM0YNO2t6LL7jzHetOqd2GjFCHY3t99tcWegz74sY5yl06Hbvimg7H6y4v73SsXznJQYkn4jnttlVxTQdePJ4pffPJ1afM52gQVpb5dPC3OQaAjADHvBJOSjtK5cfeEFZKPA7nVpPvVF/p6dtp/TucW0Wo0tq3q6vyADip5fQ2QeA4eeA0OaEmF+wnRp7pJQ9AH5I3BttPypS52QBgrizEpT4Bhrkc6XUFIPgZZ0m53lYAMlY4/tBJuTv7+vsHO6wADH6z9x9ZJ6k95aerl/uVy4DZd9hRyo/8cil/ALkDKd9dJwlBrR5EKwbKl7g2e7XOBuwoA6p8/WvHrpW+z+rYNfmtzknEwvbqwEtaPagsMwZ+5Lc9LfipgPWnhTyFaSH2ZZVlPsfyiqkdmBbqUD653bF+fMxh23vx3cFu52Nf43zs3s79vUFu23sxLu6Ic794HdoOfQqVk5yvu2pCm6NRVzlJqviUl3eitOEuHVhOPve9ae2TMWhWg6ou3ixdwkq3XLjWfonzefd2bo5698oQvtBzczSUdR6AC9fydzz2qFXOCRQ9K3svd5hYccwDED7SOQ8AGwDMFYa41CfAMJcjvcYAxK5zTiuffLO9XF3cehkA7CBX5yRn1xi3TkuIks0wHAAAIABJREFUBooB8CbeZX/sEXIwb9t2jNT5JwOgLmOF9tutS12mg/ScYghIIlUH/JEsqKpr6x6QtFEHHeoZf1MGYh3Ea1c/ebOxn5L/rPOslH7NKn+Bk9tEdfFmXc9PBlQFd3YNnhmw/q7hDdg1vCFgWdfQmagq3WJfd1g9qkvasGtYvW3blZPabcu7htajpGCnnw9+lPgKb4lx2Bc3zvbcdg2rx9Sqrc7H9vpsy3eOaMC+uHEBc1KEizOYkPugQ9v1qJjcjp0jbM5teD0qJ7Wja4h9n1dcY+8SVh7+nGHMTWrXyeBoW1XpFse8EOQuVFOwwWIIUnB5zfiNjrP0TsZm7Zg1zpl+e1shcDCEK1T7zrPwDisADnV7zwPwrHJvvIBjhzyLupSljjP4jisAob24ToY+C3dUYHc0PWnjMDHCicCYKw1xqU+AYS5HtApQ/CyllvOMkQcgdp1W2vEm3mWVlIucLlWAlKJEY4yc8R4jDqNc7JEBZZl3aDlQnSdAHDaC1UhS1LMSjSPWGOWk5KPqtrhnoStyulQBCn4HWREHtApQbfZqGWgXYkjtmduuHbvWv1ypG5FKkUXxY/SdRplyEaJAPbOUH6l50AqAWdGDBud1mXdYZQBVEJ8e8JsUSmoKNmgZUZIXvaZum0X+0BL8qNSHKia3G8GSKgiYFE8a0rZYj50kVxZoYFebu14rqujgz9ItqC7ahIU5i/zzJwQVojl/MRbktgQsWzBuMSq9PizIbcGrQf65FxbmtqDS68P88UtwMED5/PFLUF7eieb8xXg16GpL+atBhZhfeCsqrunAzOwONIondNlbYhzOBIdiftGtAY/9atDV8twmtaO5IMCxg+SxK72+gOVUf8G4xTgT7J+TYqYKxJ1fdKvfeR8MKsT8oltRNaENzQWLA7RtPrb/dR8Usr687k5nP/4Smd25unCTnrmn/8/6UYF1/BvS2vQg3ywDWlW6RWerJlnXwH767bbnRapTDWk2MQIUA2AXI5C8WQbT2xnCnnZpKNsF2yc5a/HX5LWiwd1qHwOQvdoxySG9e+wmP+zaJqlOWy3+WKkO5hQDIMvtJz9KU++2jQFYlNqExhFrbNsui5/FBgBzRcEGAMMEwGwA1GWskDJx6cullj/p+5PMHEnIkf5/8u2yPPFWud0sSUf1aB/6JCwx8gmkL5f5BpSmNSlrmKXstGyeGmyb/fPNdXQAb8YKS1Kvnt+1HB61rYKAa7NXG4m8aCBPs/lKJo+UO+oyVhjSn5Q0TEn+0fmR3KbOKUD7k2xhzjrp7kMShKQ8ZMomrF2KaGA/3pR8jAwHlQdA5yFQqwDVhVZZUJJj1HKJqs3q4s0yoZgp+JOMggW5Lfi3Ebl4zxWPfxuWg0XZC7S844Jxi7F/6Fi8FxWPfxuRKwf3atBZXbxZ1o3Jk+UxuWguWKyDSsvLO9FcsES2reovGLdYyloqNZrmgiWy/iA39sWOw7zi26SqjVK0aS5Ygn2x4/CeKx77RuZhYc4iGThd3om5pbdj38g8vOdyY19sHuYV36b94Ssmt2N+0a2qrhv7RspyLYc5SZa/4M7He1Hx2Bebh+aCJVrusjl/se6TF+LleVWWSQnNyjIf5heqtqPdeCF+HBaOXYiKazp0cK4uV+dNbZeXS8We+ePVdbtkvzQXLDZm8tVAXOvpR0gtfnLzqSnYoFV9yCCoLparRZVeH2aO7jDp+O/FzNEdWgaW5Dh1LMj4jdIIIMNggkzYVS72aD39ek+7NjgbUtq0ln45ydXmtepVpoakjX55AMhdrSa/1ZpzImyvzJdBz0/2apVPo4chnWvI+VqM9NBnpfGgnu+AdelZowmEHjr/ZmWwhoSNJq19kxKPev5Jicc8wVCbvVqvbvqVkWxo9mqTzv8ROelCEsbqXWbJAxAiz838LrYcW6kM0bsu4KRN4hy9ytkzRwGtavIKAHOlwQYAwwTAnAisMXYdKoKVln/wM2iMWauTennjthl5AFQm4EVpP9cGg84hYJqFrx19pxz0J9+OxmGr/PMEpC7Tev30QynLnzHk7LJXyzwAkddjWtCTyAw+hqzoV+BN+qU2AGh1gdpucLfK46ofUYuUnnkFIGWpkQiMjAxTEDD58hsygGpwolx4tAFAiXkouZga7Ndl3iHlCcNMEoEJG3WOAK3+Q9rfuev1MSmQmJIQaXlDykCsjAQaRNWOvtNYPchZh+rizTJplCWHQJvhJqTkGSvLfBYDgFYPqos3y8RRZulGT7seVM4c3WGcV/hzqB/VoTMSV01oU0mjDLlKyupaVboFFZPb5WDUJGc5M7tD69aTcoxZVnJmttKkL2nDhHE74RlyEBkhf8a0kKewc0QDmvMX6xwGDR6f0Xa40XbFNVI3n5KY6WOrbLhVE6RxckPOVsuxb8jZqg2fBrMUpjpv0tmvKt2i6j7n33bpFpSXd6rcDKZzG92hB8kVk9t7XPdeNGRu0WWVXp81t4OSyyRDj/T8q4ukQag1+JVRNjO7x/9nmtxOg3+zC1Cl16fvo+pCyi7d49jqfiKlnoAyncrVzZzPggb4ZAhXlvn0ahRJ49bktxq5OsasQYO71biXQ5/Vib7Ija4hebNVLjOtTT+jZABkk/GRtNHQvx+1ysgjotpujFtnuAWaDAhZrmRATZMRhhSnSepTTYK0JM7B/uhsfBA2Evtdo9GSOEfHGdWlL8ei1Cbsd43GB5TkMPlm+V5TExwtsTdi/+Ax+CA0RiVQnGMkWFTvsJ6JGmnVVr+TlFyxrpN4q/G3KtcTKunLOQaAueJgA4BhAqBjAIbOD7wkPHy1cwxA3E2OknK1o++0Lx9Ofvb2MQQt7ln2eQDSf2UfX5C40fHYDe5W/YNozvrZ0wXINsdBomkQQa5Aana+pmCDnt2zcwGoKdhgBA+bkwSpQT1pm9vFRphXAGryWjGleqvRZu56W9lHcqug/Wg1wDzzWzN+o63LyA05Wx1lGyu9PluXD5pxtnP5uCFHatg7ubqUFOwK7NoQVIjmgiW2500Gyg252wKfW3anNnoCl3fYusHMzFZt28l0qoy59m40UvPeKXdD5aR21Dscn1YBtAGgkm+Re4+tVGf6FsMFyGQA0Ow9Je+yrZ/mVLZFrw7Y1TUn1DMn96ou3KSfDdv6aibf/jlZby8DquravT/qxQJpwNtJeapkgrbtu1vRknyzdpXLE/9Xu3QtSrtFZygPVN4S/zPUjr4Ti9JuCVyeNEdPNgRMoKgG/3oFQE/ayBUAWt211KVJl/TlLAPKXHGwAcAwAeiTCpBTHoBBY5xVgBJvddDip3IHFSDX6AvPA9CLAhG5AZEBoLN5mmITnHIYaDcCyuZJmT/HrJHBjQ7H1i5CFAeQ36pdjGh2zlGBiOqQ9Ci5Dam/bQMrw/bqLMO1Y9boDKsWGdDCTY6Bnb0Fo9rKVYbtle4utrKRz0klGzvJyfC9iB8ZOA/AjeJx7BuZ5xhwKqU0HYJhCx3yJ4Q7yV0+5yy1GS5lOp3KK70++34Lf85ZBjT8Ob0CoHNDkFuPyvzrGIhL8SfmIODizTrIvGb8Ruf7waGst7p6tWvMGjnopwR3yoh2lLtUOS2cpD4dnyGHtsvFHqVQ5pBHpJdA3a6ovwkczB59A+oy70BX5PTA5VF/I8tdNwQud92gE3nZ+fE7Ttq4ZznGLrABwFxpiEt9AgxzOdKnPAChJwKWjRNv4f0wJ0m5w1LuzqHcWc7uMD6IiHXOA+CUg8ApD4CQx9YGwKhVSH14mwzoVfEMUgbQWUaQfPl/9XalIeWpVhF6yyFQ51mpl+cP/r9UY1sfjq1jBsasQffHWXoWlbIROx5bufhQ3MDJEwl+KwAXS/axclL79yof5PrE9l58L9p9USUpbcuCe2+7tz6tLuxFDrOXvBDkplNdtAndH2dp1xyS8+xNSrO6sMdKkNrWl/vp+8h0avc3FQD/sboXtX9/LzktLpoUpzgs277QHCZBhzEt+Mke2+VnWvCTqEtd5lhek9fqWO5oGIX2krxx8FWOCkRlyU1gA4C5khCX+gQY5nKk1xWAsL3OknKu0X3IA+CQCdgxW28vKwDRb/SaqdcxD4AarOsVAAq+owBnz0rnGUByAaKZfOWTTEHHjvkP1OymDhymnAAUG9DLDzwNnGryWo0ZU3LtccpBEPKM9LFWvv4UgGwe+PU64+s0i160yXb1Qc8If49ZeMcVgLhxjrPsNQUbnI9dvNkxqZVTmZTatF+5kNmZnRN5Oa18OEp5qn6lwF9y/yEFIKe8EBVhe7XvvSUIWAX30n1lm5U69FnnFYA853wWtBKlV7SUa5t5RcvpOagZv/HCknGF7XVsu1zs6VVitC7zDsdnPDP4GAIZB5nB76Au+XZkBtmX145a5VjeW54Ax+SNYSMdDR82AJgrDXGpT4BhLkeMPABzbX1lnZaTF6Xf4piSnoLs7GIE6hKWOGr1tyTNccwDYCe11xi3vncZv7FrjTwAFExHA3rlitObDCDNUmpXHEoolrECDQkbHP2HSUJUD96VQUJqPQ0JNhKGpGJiGvBbcgnkrLM/tgpQrC7aZIk3sAz8xm909Nt2igGoLt7skINgiwomtW+7akIbZmbb+/GXZt9vK2/YnL/Ytu0bcrehuqTNXnIybQsqy3y25fWjnGMAqos3Y4adHKZHJumy9fFXuRls5TJVoK9dDEBDWpuR3K1I+tGTklNt7np53XZymMoPn+4Hug9oIE6++Lb3Q0qb/Xmntcl70enYdA/mrjeUdZSBSi5utnKaaW2y3OZeb0jY4PAMbZDvJocYABmEb9O2ijGyPbfEjciKernHAFt+slx/Ql3mHchy/SlwecQB1I5Zg6xIm/pRL6uJE/uJFccVgKjRjoZLmXs22ABgriTYAGCYAGgVoMQ5Sk3HkLtrjFkrZ8KTb7fPA0BydDFr/XIIkEqPVglSeQIqQmXbWq0iY4U1D0DIM1rJp3bUKrQkzTHyAAS9g6yoP8Ebv10Gs6UuM2T6lJReg7vVkAPNvMOagyD0WaniQbP9npWWGIC6lKWGAlD2aouKkEVGkDL/kmKJOS8AzeqPWiXVSUjGL2yvVkciVyMdBKxcicwyoNUlbf55BNLaDIlSFTBZm73acJlQBkGl14eG5E1aWlHW3WLxuabBlzkPgPb7zjOUXbR0Y6ahDW8pC9uLhuTNWo2GjABDcvI5PUilGemGzC3WttO3aLek6pI2qRJkbl/p1WsVoKEHkRl8DNOCn0LXkJk6x0B14SarpGT4XiNIVrnJzMjutMhh1nvatexlxTUdWqmHymdkd+oA24a0HnKV6VKlpya/VRsY5roNHikPWlOwQZYrFR/ql3pPu+GqQ/XDevSbkmalgFrztdWP6jDun7FrpeynSQa2duxaneytIU0q8VikNun+VbKw2gDIXq1XBkjNxyzlqe8ntXJlkfkklR/lTiZzAbSZ7mN1bGXs1mXeYcmmrZPj0T2ucgFYnsHkzRYlLPmcmM4tcaOhIJRoyIDqHCWelVK+N+DzrWRAVX6PnjKhjbHrjHghUzCtru+W1+RN+qXfxElI0Dl4E+9CXcaKwOXiLErT7pHlyX8XsNybeJfOnWIbAxC/3WbSZrxM3mg3KRO7jmVAmSsONgAYJgDaAIi9ydDmT7xV/sDFtWgZTz1Dnr5cu8do+TiSkEtZav2evhy17sWyPXMbGSuk/r9JqpMMDfO+loBcyjFgkg41y99pFx5S8FHnask5QO1Sxl/VDkn+mX/UtX+++rt2zBpdro0FqmMaeNP5kQ44bdeuDjTAocDhjBVy9pNkBSkZWfpyax4BMjBM+uNkLJDbDuUk0O3TyoAp5wAdr3bMGj0YN7sAVZVKI4EGblppyJRDgHIP0GwzrWKY8w6YB3814zfqoNKqCW36fPW+SmmGMtKS37rWoadyJVmpB/OqLklV6iBYk3qNuU5lmc+ij0/XYTmm6TsN6ivLfEZgrdpG5ZVlUvmI3G0oj0F1ibxOOrdKr08bT9VFm7TsKCVlM18DGQN07dUlbVbpV+pPku9UBhvtS8fQ/wc0iDcniqP7RLmt9XQF0/kqlFGqVXloxYrK1SBdGwvqPjG3SxK1llwVZLQqA5aOVedZaRgAdI+bcnSQTKiWrDW50vX86OfVFB+jnx+1WmZx4yNjXLWv3QEpjwjJ/Kpjarlg9XxpKU4lX1yXsQLexLvgjn4Dg8L/Anf0IZSm3m282zwrUZr+K7gHvYHBYX+BO/oNQ95YvV9KU++GO+p1DA47AffgN2UCRPUuqktfbp20CTUlQcy8A9747T0mba5HS+JsWT9lqTExQjkIRsiVSzYAmCsNNgAYJgDaAHDPNgbINAB1LzYGzpTUi5KB0ew+bc+8Q+cM0H/TPmrAXxvXYuxHhoPalwbD+seWEpKlL9erBDrpmCnxmP5hNiUAIw1urYs9+k69WlCXfLtOhEN1q4IajL+VcUM/4NrgUIpBOkMwHUsZCdpwoMRjNEg3zbab8wzo/WhgT0aN6dh6gEUrCjnrjHgBGtCnLjMGL2pQRapANPijcp1IzCQ5WudZaZ35VXEFWmNdDXjp7+qSNjmIzGs1kkjRIFMZCnT86sJNWtdffygDcbFM1KQHu8oHvWKyHBjTIFcbHWRIqFUEGjDrgbjXZxgD9Clp04pHlMhLnz8Nlmmg3GMfrUuv3GC0gWMyfGryWy3bago2aIOADAzqD2140PkXGUG7dB3VxZsNI6XQMM4sBoEpj4P5/8J8jpbM0CYjxBynYkkwp9zAKCleVVCDHuiapWUtA3sy/MjwpPvcvKJFA3bTzL6uS/EuFARMhgWthNG/ZASrHBk6xsaUf0O74JmyaGtXPJMRT4Y5taeTAZLhTgN3yg6eYwymLYkBTc+8+aPfPZQMkfT6aUKCJkDM+9H7yfyeMyUp1EkV6f1H7w56r5pyluh3FE2UKDEBS4JG08ooba/NXm28HzNWsAsQc8XBBgDDBODQoUMQQmD8kDqUpfwcZclNKEucI78nzkFZ7E0oS7oZZe7ZKHOrv+Nnye/u2fI77Z96i/xurpc+V/6b3CTrJM5BWdpc+a97jixLuln+ndxkHJ/aTLpZtkXbkpvk9pSfG+3Rh84l6Wbju3u2cWw6VtLNlnOdKKqNY6X83KibMc84Hp0jtZM+1yjLnC/LUm8x+k2f42xZnnQzyjzNclvaXFk/Y56sQ9/T58qy5CaUZS2Qf6feIuunzTXap308zbJe5nyUJTfBm71QfqcPtU3nl/JzlHma4R21UJbR94x5mCiqMVFUyzayFsiy7IW63DtmkdF+1gKUXtWij+PNXogJBbfKfUbJ+t5RC+EdswiluUvgHbMIZSk/R2nuYnizF6I0dzFKc1pkGR0va4HcltOC0tzF8vjqmN7shSjNadHtyzaWoPSqFr3dXK/0KrUv1R+10NK2bi9bnmNZxjzdFvWJbkN9L71K7m/5nrtYXyNdf+lVLfr6vKNMx85dbGxXxzWfE20vzWnRfVrmacaEgltlf9LxVP9OzFui/y/M/TIxb4m+ZtpWljlfXqepn/X/kTpOWeZ8y32gr3OUKs9aIO+1jHnGeXqajXsxYx7K0ubK9tLn6vbLMufLv+kYdD9nLTD2TzPd/7Svuj/1vlkL5HdPs9F+trw3y9yzjWeJnhU6Fj0D9N6h7/R8ppme47S5+pwnimpZRs871afnm77TuyG5yXiv0XXQO5H2cav3l3u20WbqLUbd5CbjmU9T7wJ6f9F+9O4yv5PoOPo9O9t4/yaa3nuxN8lziJ8lP+Z9qb2kmzE+YQaEEDh06NCl/nlimB8ENgAYJgD/9E//BCEEf/jDH/7whz/6s2fPnkv988QwPwhsADBMAF5++WUIIfAv//IvOHLkyID97NmzR//oXepz4X649B/uB+6HgdoPhw4dwp49e/D5559f6p8nhvlBYAOAYQJw5IiMAThyZGD7e3I/SLgfJNwPEu4HCfcDw/Rf2ABgmADwD5uE+0HC/SDhfpBwP0i4Hxim/8IGAMMEgH/YJNwPEu4HCfeDhPtBwv3AMP0XNgAYJgD8wybhfpBwP0i4HyTcDxLuB4bpv7ABwDABOHnyJDZt2oSTJ09e6lO5pHA/SLgfJNwPEu4HCfcDw/Rf2ABgGIZhGIZhmAEEGwAMwzAMwzAMM4BgA4BhGIZhGIZhBhBsADAMwzAMwzDMAIINAIZhGIZhGIYZQLABwDAmzp49izvvvBMJCQmIjIxESUkJnn/++Ut9Wt+bgwcPYsmSJRg7dixcLhdSUlLQ2NiIP//5z5b9mpqaIITw+2RnZ/u12d3dje3btyM9PR0RERHIy8vD448//mNd0gWxf//+gNcnhMCf/vQny74HDhxAWVkZoqKiEB8fj9tuuw2nT5/2a7O/3jN2/9f0OXHiBABgypQpActra2v92rzc++L06dPYuHEjamtrMXz4cAgh8PDDDwfc9+2330ZtbS2io6MxfPhwzJ49G59++qnffufzHPS1zYtNX/qhu7sbDz/8MK6//nokJyfD5XIhJycHPp8PZ86c8WvT7j7aunWr374nTpxAY2Mjhg4disGDB2P69Ol4//33L9blMgwTADYAGMbEjTfeiNDQUKxcuRI7d+5EaWkpQkND8dJLL13qU/te1NfXw+1247bbbkNXVxd8Ph/i4+MRHR2Nw4cP6/2ampoQERGBRx991PL53e9+59fmmjVrIIRAc3Mzdu3ahZ/85CcQQuCJJ574MS/tvCAD4Pbbb/e7xs8++0zv9+abbyIyMhLjx4/HAw88gPXr1yMiIgJ1dXV+bfbXe+bll1/264NHHnkELpcLY8eO1ftNmTIFycnJfvvu27fPr83LvS+OHz8OIQRSU1MxdepUWwPgo48+wsiRI+HxeLBjxw50dHRg+PDhyM/Px7lz5yz79vU5OJ82LzZ96YfTp09DCIGJEyeivb0du3btwi233ILg4GBMnToV3333nWV/IQSqq6v97pOeOQJOnz6NUaNGIS4uDtu3b8fdd9+NlJQUJCcn43/+538u9qUzDKNgA4BhFK+++iqEELjrrrv0tjNnzsDj8aC0tPQSntn358CBA36DjP/6r/9CREQEZs2apbc1NTUhOjq61/ZOnDiBsLAwLFmyRG/77rvvMHnyZCQnJ+Pbb7/94U7+B4QMgN/+9reO+1177bVISEjAl19+qbd1dXVBCIF//dd/1duutHvmpZdeghACHR0detuUKVOQk5PTa93+0Bdnz57Fxx9/DAB47bXXbA2AlpYWREVF4b//+7/1tj/+8Y8QQmDnzp162/k8B31t88egL/1w7tw5HDhwwK9uW1sbhBD44x//aNkuhLD0gx3bt2+HEAIHDx7U29555x2EhIRg7dq1F3A1DMNcCGwAMIxi1apVCAkJsQz6AKCzsxNCCHz44YeX6MwuHoWFhSgsLNR/kwHw7bff+vWDmfvvvx9CCBw9etSy/fHHH4cQ4rKZ8e2J2QA4deoU/vrXv/rt8+WXXyI0NBSrVq2ybD937hwGDRqEefPm6W1X2j3T0tKCoKAgHD9+XG8jA+Cvf/1rQBcoor/1hZMBEBcXh8bGRr/to0ePRmVlpf77fJ6Dvrb5Y+PUD4H4z//8TwghcO+991q2kwHw9ddfB3QRIoqLi1FcXOy3vaamBh6P57zOnWGYC4cNAIZRVFVV4aqrrvLb/sILL0AIEdANpj/z3XffISkpCTU1NXpbU1MTgoKC4HK5IITA8OHDsXjxYr+B3/z58xEdHe3nBvDee+8FHBxcLpABMGjQIAghEBISgqlTp+K1117T+/zHf/wHhBD4zW9+41d/0qRJFoPpSrpnvvnmG8TExKCsrMyyfcqUKQgLC0N4eDiEEIiPj0drayu++eYby379rS/sBr4nTpyAEALbt2/3qzN79myMGDFC/93X5+B82vyxOV8D4Pnnn4cQwi/OQQiB6OhoBAUFQQiBq666Co899phln+7ubkRERKClpcWv3dbWVgghcOrUqQu+FoZh+g4bAAyjyMnJQUVFhd/2o0ePQgiBBx988BKc1cXj0UcfhRACu3fv1tvWrFmD1atX4ze/+Q2eeOIJHShaVlZmmS3/yU9+gszMTL82v/rqKwghsGbNmh/lGs6XAwcOoL6+Hrt378bTTz+NrVu3IiYmBpGRkXjjjTcAAL/97W8hhMCLL77oV7+xsRFut1v/fSXdM8888wyEEPiHf/gHy/a5c+di8+bNePLJJ/HII49g+vTpEELgb//2by379be+sBv40vZHHnnEr86qVasghMDZs2cB9P05OJ82f2zO1wCoqqrCkCFD8Pnnn1u2e71e/OpXv8LTTz+NBx54ALm5uX7302effQYhBLZs2eLXLq2mHDt27HtdD8MwfYMNAIZRZGZm4tprr/Xb/v7770MIgXvuuecSnNXF4Z133sGQIUNQWlraq79+R0eHX1BjRUVFwNne7u5uCCGwdOnSH/ycLxbvvvsuoqKitKrNI488AiEEXn31Vb9958yZg6FDh+q/r6R75qabbkJYWFifAjGbm5v9lJP6W1/YDXxffPFF2xWgDRs2QAihB799fQ7Op80fm/MxAOhd0NNIDMS5c+eQm5uLYcOG4euvvwYAfPjhh7YrIbt374YQAm+++eZ5XwPDMOcPGwAMo+hvM5gXyscff4zMzEykpKTgL3/5S6/7f/311wgODrb4vvfXFQA7brzxRoSHh+Pbb78dkCsAp0+fhsvlwrRp0/q0/7FjxyCEgM/n09v6W1/wCoCkrwbAP//zPyMoKMjyHuiNBx980BILwSsADHP5wAYAwyj6mw/zhfDFF1+goKAAI0aM8AtcdCI2NhYzZszQf8+fPx8ul6vfxQDYQYOwL7/8ckDGAJA7WF8lXGmAu3z5cr2tv/XFDxUD0JfnoL/HADz//PMIDw/HtGnTAgbO27F3714IIfD0008D4BgAhrmcYAMNzvNZAAAFwUlEQVSAYRQrV64MqGJCy96Xm4rJ+XLmzBlMnjwZLpcLL7/8cp/rnTp1CkFBQViwYIHe9vd///cB1U8ee+wx29nzy5n6+npERkaiu7sbX3zxhaMK0Ny5c/W2K+Weqaurw6BBg/DVV1/1af/Dhw9DCIHOzk69rb/1hdPANzY21laxx7zKcT7PQV/b/LHpzQB45ZVXEB0dDa/Xq115+sp9990HIYTlfVNUVBRQBai6ujrgagrDMBcHNgAYRvHKK6/46ZifPXsWWVlZmDBhwiU8s+/Pt99+i+nTpyM0NBR79+4NuM+ZM2cCzr7R7PhTTz2lt3300Ue2+udJSUmXbR6AQFlX33rrLYSFhWH69Ol6W11dHRISEiz98dBDD0EIgd///vd625Vwz3z66acIDQ3FnDlz/Mq+/PJLP9eU7777Dj/96U8hhMChQ4f09v7WF04D30WLFiEqKspitNBKxgMPPKC3nc9z0Nc2f2yc+uHtt99GTEwMcnJy8L//+7+2bQR6rk6dOgWPx4ORI0dacpBs27YNQgiL8taxY8cQEhKC1atXf7+LYRimz7ABwDAmGhsb9ezvzp074fV6ERoain//93+/1Kf2vVi6dCmEELj++uv9MnU++uijAGR20GHDhqGlpQU7duzAjh07cN1110EIgbq6OnR3d1vaJMNgwYIF6Orq0hlQe0r/XU6Ul5fjuuuu05lNly1bBpfLhaFDh+Ltt9/W+x06dAgRERGWTMCRkZEWyVSiv98zNEv7hz/8wa9s//79cLvdWL58Oe6//3788pe/RFlZmf5/70l/6Iv77rsPPp8PLS0tEEJg5syZ8Pl88Pl8+OKLLwDIYNWYmBh4PB7ce++96OzsxPDhw5GXl+dnEPX1OTifNn8MeuuHU6dOISUlBcHBwdi2bZvfO8M8q79p0ybk5+ejtbUVu3btQltbG9LS0hAUFIRf//rXluOSYRAXF4df/OIXuOeee5CSkoLExMSAhgTDMBcHNgAYxsSZM2ewcuVKuN1uREREoLi4OODAqL8xZcoUCCFsPwDw+eefY/bs2cjKyoLL5UJERARycnLQ2dnpp/kOSH/ezs5OpKWlITw8HDk5OX4/9pcbO3bsQElJCUaMGIHQ0FAkJCRg9uzZePfdd/32femll+D1ehEZGYnY2FgsWbIk4ApJf79nJk6ciLi4uICrNh988AEaGxuRnp6OyMhIuFwuXH311XjwwQf9/N6B/tEXaWlpts+BOQHakSNHUFNTA5fLhWHDhmHWrFn45JNP/No7n+egr23+GPTWD8ePH3d8ZzQ1Nem2nn/+eVRXV8PtdiMsLAzDhg1DTU0N9u3bF/DYH330ERoaGjBkyBAMGjQI06ZNC/gMMgxz8WADgGEYhmEYhmEGEGwAMAzDMAzDMMwAgg0AhmEYhmEYhhlAsAHAMAzDMAzDMAMINgAYhmEYhmEYZgDBBgDDMAzDMAzDDCDYAGAYhmEYhmGYAQQbAAzDMAzDMAwzgGADgGEYhmEYhmEGEGwAMAzDMAzDMMwAgg0AhmEYhmEYhhlAsAHAMAzDMAzDMAMINgAYhmEYhmEYZgDBBgDDMAzDMAzDDCDYAGAYhmEYhmGYAQQbAAzDMAzDMAwzgGADgGEYhmEYhmEGEGwAMAzDMAzDMMwAgg0AhmEYhmEYhhlAsAHAMAzDMAzDMAMINgAYhmEYhmEYZgDBBgDDMAzDMAzDDCDYAGAYhmEYhmGYAQQbAAzDMAzDMAwzgGADgGEYhmEYhmEGEGwAMAzDMAzDMMwAgg0AhmEYhmEYhhlAsAHAMAzDMAzDMAMINgAYhmEYhmEYZgDBBgDDMAzDMAzDDCDYAGAYhmEYhmGYAQQbAAzDMAzDMAwzgGADgGEYhmEYhmEGEGwAMAzDMAzDMMwAgg0AhmEYhmEYhhlAsAHAMAzDMAzDMAMINgAYhmEYhmEYZgDBBgDDMAzDMAzDDCD+P1VyQOHFwIRvAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Refined peak coordinate:\n",
      "[(918.3804241418839, 279.5866185426712), (918.55060338974, 338.37308943271637), (918.7212917506695, 397.05022401735187), (918.8901954367757, 455.8412373960018), (919.2437788248062, 515.3245315551758), (919.2116163223982, 544.6306998133659), (919.2832362055779, 574.1425551921129), (919.0927048921585, 603.6582366526127), (771.483876645565, 191.8469839990139), (771.4615589380264, 221.4316090941429)]\n"
     ]
    }
   ],
   "source": [
    "# Finally the peak positions are interpolated using a second order taylor expansion \n",
    "# in thevinicy of the maximum value of the signal:\n",
    "\n",
    "#Create bilinear interpolator\n",
    "bl = Bilinear(my_smooth)\n",
    "\n",
    "#Overlay raw peak coordinate and refined peak positions\n",
    "\n",
    "ref_peaks = [bl.local_maxi(p) for p in peaks]\n",
    "fig, ax = subplots()\n",
    "ax.imshow(img.clip(0,1000), interpolation=\"nearest\")\n",
    "peaks_ref = numpy.array(ref_peaks)\n",
    "ax.plot(peaks_raw[:,1], peaks_raw[:, 0], \".r\")\n",
    "ax.plot(peaks_ref[:,1],peaks_ref[:, 0], \".b\")\n",
    "ax.set_title(\"Extracted peak position (red: raw, blue: refined)\")\n",
    "print(\"Refined peak coordinate:\")\n",
    "print(ref_peaks[:10])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this stage we have about 2000 peaks (with sub-pixel precision) which are visually distributed on all modules.\n",
    "Some modules have their peaks located along sub-module boundaries which are masked out, hence they have fewer ontrol point for the calculation.\n",
    "Let's assign each peak to a module identifier. This allows to print out the number of peaks per module:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of keypoint per module:\n",
      "Module id: 1 cp: 48\n",
      "Module id: 2 cp: 30\n",
      "Module id: 3 cp: 48\n",
      "Module id: 4 cp: 46\n",
      "Module id: 5 cp: 42\n",
      "Module id: 6 cp: 47\n",
      "Module id: 7 cp: 47\n",
      "Module id: 8 cp: 30\n",
      "Module id: 9 cp: 48\n",
      "Module id: 10 cp: 48\n",
      "Module id: 11 cp: 41\n",
      "Module id: 12 cp: 39\n",
      "Module id: 13 cp: 48\n",
      "Module id: 14 cp: 30\n",
      "Module id: 15 cp: 47\n",
      "Module id: 16 cp: 48\n",
      "Module id: 17 cp: 42\n",
      "Module id: 18 cp: 48\n",
      "Module id: 19 cp: 47\n",
      "Module id: 20 cp: 30\n",
      "Module id: 21 cp: 48\n",
      "Module id: 22 cp: 47\n",
      "Module id: 23 cp: 42\n",
      "Module id: 24 cp: 47\n",
      "Module id: 25 cp: 48\n",
      "Module id: 26 cp: 30\n",
      "Module id: 27 cp: 48\n",
      "Module id: 28 cp: 47\n",
      "Module id: 29 cp: 41\n",
      "Module id: 30 cp: 50\n",
      "Module id: 31 cp: 46\n",
      "Module id: 32 cp: 30\n",
      "Module id: 33 cp: 48\n",
      "Module id: 34 cp: 42\n",
      "Module id: 35 cp: 47\n",
      "Module id: 36 cp: 48\n",
      "Module id: 37 cp: 48\n",
      "Module id: 38 cp: 28\n",
      "Module id: 39 cp: 48\n",
      "Module id: 40 cp: 42\n",
      "Module id: 41 cp: 44\n",
      "Module id: 42 cp: 48\n",
      "Module id: 43 cp: 47\n",
      "Module id: 44 cp: 26\n",
      "Module id: 45 cp: 46\n",
      "Module id: 46 cp: 42\n",
      "Module id: 47 cp: 45\n",
      "Module id: 48 cp: 48\n"
     ]
    }
   ],
   "source": [
    "dt = numpy.dtype([('y', numpy.float64),\n",
    "                  ('x', numpy.float64),\n",
    "                  ('i', numpy.int64),\n",
    "                 ])\n",
    "yxi = numpy.array([i+(mid[round(i[0]),round(i[1])],) \n",
    "                   for i in ref_peaks], dtype=dt)\n",
    "print(\"Number of keypoint per module:\")\n",
    "for i in range(1,mid.max()+1):\n",
    "    print(\"Module id:\",i, \"cp:\", (yxi[:][\"i\"] == i).sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grid assignment\n",
    "\n",
    "The calibration is performed using a regular grid, the idea is to assign to each peak of coordinates (x,y) the integer value (X, Y) which correspond to the grid corrdinate system. \n",
    "\n",
    "The first step is to measure the grid pitch which correspond to the distance (in pixels) from one peak to the next. This is easily obtained from a pair-wise distribution function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Pair-wise distribution function')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pairwise distance calculation using scipy.spatial.distance_matrix\n",
    "\n",
    "dist = distance_matrix(peaks_ref, peaks_ref)\n",
    "\n",
    "fig, ax = subplots()\n",
    "ax.hist(dist.ravel(), 100, range=(0,100))\n",
    "ax.set_title(\"Pair-wise distribution function\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The histogram of the pair-distribution function has a first peak at 0 and the second peak between 29 and 30. \n",
    "Let's start the fit with this value\n",
    "\n",
    "Two other parameters correspond to the offset, in pixel for the grid index (X,Y) = (0,0). \n",
    "The easiest is to measure the smallest *x* and *y* for the first module."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "offset for the first peak:  16.269793540239334 7.186804354190826\n"
     ]
    }
   ],
   "source": [
    "#from pair-wise distribution histogram\n",
    "step = 29 \n",
    "#work with the first module and fit the peak positions\n",
    "first = yxi[yxi[:][\"i\"] == 1]\n",
    "y_min = first[:][\"y\"].min()\n",
    "x_min = first[:][\"x\"].min()\n",
    "print(\"offset for the first peak: \", x_min, y_min)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The grid looks very well aligned with the axes which makes this step easier but nothing garanties it is perfect, so the rotation of the grid has to be measured as well.\n",
    "\n",
    "The default rotation will be zero and will be fitted later on.\n",
    "\n",
    "Once the indexes *X,Y* determined for eack peak, one can fit the parameter to properly align the grid with the first module. Those 4 parameters are *step-size, x_min, y_min* and *angle*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peak id: 0 (65.94893547, 16.45467511, 1) Y:2 (Δ=0.026) X:0 (Δ=0.006)\n",
      "peak id: 1 (65.94483702, 45.61336857, 1) Y:2 (Δ=0.026) X:1 (Δ=0.012)\n",
      "peak id: 2 (66.03506869, 75.15414216, 1) Y:2 (Δ=0.029) X:2 (Δ=0.030)\n",
      "peak id: 3 (65.89957739, 104.38019937, 1) Y:2 (Δ=0.025) X:3 (Δ=0.038)\n",
      "peak id: 4 (66.12287057, 133.89461011, 1) Y:2 (Δ=0.032) X:4 (Δ=0.056)\n",
      "peak id: 5 (66.1012452, 163.39174998, 1) Y:2 (Δ=0.032) X:5 (Δ=0.073)\n",
      "peak id: 6 (66.10113759, 192.66102123, 1) Y:2 (Δ=0.032) X:6 (Δ=0.082)\n",
      "peak id: 7 (66.11095764, 222.20659751, 1) Y:2 (Δ=0.032) X:7 (Δ=0.101)\n",
      "peak id: 8 (36.49696946, 16.50531429, 1) Y:1 (Δ=0.011) X:0 (Δ=0.008)\n",
      "peak id: 9 (36.54493174, 45.66864574, 1) Y:1 (Δ=0.012) X:1 (Δ=0.014)\n",
      "peak id: 10 (36.57917181, 75.22501931, 1) Y:1 (Δ=0.014) X:2 (Δ=0.033)\n",
      "peak id: 11 (36.48521471, 104.38776881, 1) Y:1 (Δ=0.010) X:3 (Δ=0.039)\n",
      "peak id: 12 (36.5958997, 133.89308376, 1) Y:1 (Δ=0.014) X:4 (Δ=0.056)\n",
      "peak id: 13 (36.56109262, 163.54238695, 1) Y:1 (Δ=0.013) X:5 (Δ=0.078)\n",
      "peak id: 14 (36.62988734, 192.63348889, 1) Y:1 (Δ=0.015) X:6 (Δ=0.082)\n",
      "peak id: 15 (36.66130301, 222.22433692, 1) Y:1 (Δ=0.016) X:7 (Δ=0.102)\n",
      "peak id: 16 (7.18680435, 16.41273034, 1) Y:0 (Δ=0.000) X:0 (Δ=0.005)\n",
      "peak id: 17 (7.23123039, 45.74501115, 1) Y:0 (Δ=0.002) X:1 (Δ=0.016)\n",
      "peak id: 18 (7.29059145, 75.19019249, 1) Y:0 (Δ=0.004) X:2 (Δ=0.032)\n",
      "peak id: 19 (7.19876912, 104.56766725, 1) Y:0 (Δ=0.000) X:3 (Δ=0.045)\n",
      "peak id: 20 (7.28363913, 134.01557775, 1) Y:0 (Δ=0.003) X:4 (Δ=0.060)\n",
      "peak id: 21 (7.25490889, 163.38282073, 1) Y:0 (Δ=0.002) X:5 (Δ=0.073)\n",
      "peak id: 22 (7.36717248, 192.76562056, 1) Y:0 (Δ=0.006) X:6 (Δ=0.086)\n",
      "peak id: 23 (7.37469381, 222.16684446, 1) Y:0 (Δ=0.006) X:7 (Δ=0.100)\n",
      "peak id: 24 (183.49989897, 16.39247844, 1) Y:6 (Δ=0.080) X:0 (Δ=0.004)\n",
      "peak id: 25 (183.50560439, 45.46551961, 1) Y:6 (Δ=0.080) X:1 (Δ=0.007)\n",
      "peak id: 26 (183.60742423, 75.08415242, 1) Y:6 (Δ=0.083) X:2 (Δ=0.028)\n",
      "peak id: 27 (183.51583004, 104.62201929, 1) Y:6 (Δ=0.080) X:3 (Δ=0.047)\n",
      "peak id: 28 (183.66220078, 133.73585817, 1) Y:6 (Δ=0.085) X:4 (Δ=0.051)\n",
      "peak id: 29 (183.65553248, 163.30831155, 1) Y:6 (Δ=0.085) X:5 (Δ=0.070)\n",
      "peak id: 30 (183.60811904, 192.46339762, 1) Y:6 (Δ=0.083) X:6 (Δ=0.076)\n",
      "peak id: 31 (183.75545964, 222.06266521, 1) Y:6 (Δ=0.089) X:7 (Δ=0.096)\n",
      "peak id: 32 (154.25518942, 16.26979354, 1) Y:5 (Δ=0.071) X:0 (Δ=0.000)\n",
      "peak id: 33 (154.21079713, 45.57556251, 1) Y:5 (Δ=0.070) X:1 (Δ=0.011)\n",
      "peak id: 34 (154.28871083, 75.04928852, 1) Y:5 (Δ=0.072) X:2 (Δ=0.027)\n",
      "peak id: 35 (154.21604921, 104.4366582, 1) Y:5 (Δ=0.070) X:3 (Δ=0.040)\n",
      "peak id: 36 (154.37423909, 133.8660319, 1) Y:5 (Δ=0.075) X:4 (Δ=0.055)\n",
      "peak id: 37 (154.35255641, 163.24378996, 1) Y:5 (Δ=0.075) X:5 (Δ=0.068)\n",
      "peak id: 38 (154.32582822, 192.64246738, 1) Y:5 (Δ=0.074) X:6 (Δ=0.082)\n",
      "peak id: 39 (154.46003968, 222.04596291, 1) Y:5 (Δ=0.078) X:7 (Δ=0.096)\n",
      "peak id: 40 (124.69245848, 16.47663069, 1) Y:4 (Δ=0.052) X:0 (Δ=0.007)\n",
      "peak id: 41 (124.74490786, 45.56257215, 1) Y:4 (Δ=0.054) X:1 (Δ=0.010)\n",
      "peak id: 42 (124.81674041, 75.13362026, 1) Y:4 (Δ=0.056) X:2 (Δ=0.030)\n",
      "peak id: 43 (124.75223885, 104.64793801, 1) Y:4 (Δ=0.054) X:3 (Δ=0.048)\n",
      "peak id: 44 (124.84565204, 133.79748473, 1) Y:4 (Δ=0.057) X:4 (Δ=0.053)\n",
      "peak id: 45 (124.85729225, 163.3060154, 1) Y:4 (Δ=0.058) X:5 (Δ=0.070)\n",
      "peak id: 46 (124.89991033, 192.57832247, 1) Y:4 (Δ=0.059) X:6 (Δ=0.080)\n",
      "peak id: 47 (124.96431521, 222.11254385, 1) Y:4 (Δ=0.061) X:7 (Δ=0.098)\n"
     ]
    }
   ],
   "source": [
    "#Assign each peak to an index\n",
    "dl = numpy.dtype([('y', numpy.float64),\n",
    "                  ('x', numpy.float64),\n",
    "                  ('i', numpy.int64),\n",
    "                  ('Y', numpy.int64),\n",
    "                  ('X', numpy.int64),\n",
    "                 ])\n",
    "indexed1 = numpy.zeros(len(first), dtype=dl)\n",
    "\n",
    "for i,v in enumerate(first):\n",
    "    Y = int(round((v[\"y\"]-y_min)/step))\n",
    "    X = int(round((v[\"x\"]-x_min)/step))\n",
    "    indexed1[i][\"y\"] = v[\"y\"]\n",
    "    indexed1[i][\"x\"] = v[\"x\"]\n",
    "    indexed1[i][\"i\"] = v[\"i\"]\n",
    "    indexed1[i][\"Y\"] = Y\n",
    "    indexed1[i][\"X\"] = X\n",
    "    print(\"peak id: %s %20s Y:%d (Δ=%.3f) X:%s (Δ=%.3f)\"%\n",
    "          (i,v, Y, (v[\"y\"]-Y*step-y_min)/step, X, (v[\"x\"]-X*step-x_min)/step))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The error in positionning each of the pixel is less than 0.1 pixel which is already excellent and will allow a straight forward fit.\n",
    "\n",
    "The cost function for the first module is calculated as the sum of distances squared in pixel space.\n",
    "It uses 4 parameters which are step-size, x_min, y_min and angle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "guess1 = [step, y_min, x_min, 0]\n",
    "\n",
    "def cost1(param):\n",
    "    \"\"\"contains: step, y_min, x_min, angle for the first module\n",
    "    returns the sum of distance squared in pixel space\n",
    "    \"\"\"\n",
    "    step = param[0]\n",
    "    y_min = param[1]\n",
    "    x_min = param[2]\n",
    "    angle = param[3]\n",
    "    XY = numpy.vstack((indexed1[\"X\"], indexed1[\"Y\"]))\n",
    "    rot = [[cos(angle),-sin(angle)],\n",
    "           [sin(angle), cos(angle)]]\n",
    "    xy_min = [[x_min], [y_min]]\n",
    "    xy_guess = numpy.dot(rot, step*XY+xy_min)\n",
    "    delta = xy_guess - numpy.vstack((indexed1[\"x\"], indexed1[\"y\"]))\n",
    "    return (delta*delta).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before optimization [29, 7.186804354190826, 16.269793540239334, 0] cost= 250.36710826038234\n",
      "     fun: 0.6337542147785734\n",
      "     jac: array([ 2.15254724e-04, -1.18207186e-03,  1.05350465e-03, -3.25701334e-01])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 51\n",
      "     nit: 6\n",
      "    njev: 6\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([2.93980817e+01, 7.13605736e+00, 1.63978976e+01, 8.76803451e-04])\n",
      "After optimization [2.93980817e+01 7.13605736e+00 1.63978976e+01 8.76803451e-04] cost= 0.6337542147785734\n",
      "Average displacement (pixels):  0.11490523403173132\n"
     ]
    }
   ],
   "source": [
    "print(\"Before optimization\", guess1, \"cost=\", cost1(guess1))\n",
    "res1 = minimize(cost1, guess1, method = \"slsqp\")\n",
    "print(res1)\n",
    "print(\"After optimization\", res1.x, \"cost=\", cost1(res1.x))\n",
    "print(\"Average displacement (pixels): \",sqrt(cost1(res1.x)/len(indexed1)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this step, the grid is perfectly aligned with the first module. \n",
    "This module is used as the reference one and all other are aligned along it, using this first fit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cost1:  0.6337542147785734 for: 29.39808169136302 7.136057363507019 16.3978976414565 0.0008768034506612712\n",
      "6\n",
      "[(1654.4202804 , 954.44135761, 46, 56, 32)\n",
      " (1624.68617365, 807.47743243, 46, 55, 27)\n",
      " (1595.5792897 , 954.49445057, 46, 54, 32)\n",
      " (1448.30209509, 748.8784325 , 40, 49, 25)\n",
      " (1448.66381988, 895.86545633, 40, 49, 30)\n",
      " (1448.84506877, 954.56920397, 40, 49, 32)]\n"
     ]
    }
   ],
   "source": [
    "#retrieve the result of the first module fit:\n",
    "step, y_min, x_min, angle = res1.x\n",
    "indexed = numpy.zeros(yxi.shape, dtype=dl)\n",
    "\n",
    "rot =  [[cos(angle),-sin(angle)],\n",
    "        [sin(angle), cos(angle)]]\n",
    "irot =  [[cos(angle), sin(angle)],\n",
    "         [-sin(angle), cos(angle)]]\n",
    "\n",
    "print(\"cost1: \",cost1([step, y_min, x_min, angle]), \"for:\", step, y_min, x_min, angle)\n",
    "\n",
    "xy_min = numpy.array([[x_min], [y_min]])\n",
    "xy = numpy.vstack((yxi[\"x\"], yxi[\"y\"]))\n",
    "indexed[\"y\"] = yxi[\"y\"]\n",
    "indexed[\"x\"] = yxi[\"x\"]\n",
    "indexed[\"i\"] = yxi[\"i\"]\n",
    "XY_app = (numpy.dot(irot, xy)-xy_min) / step\n",
    "XY_int = numpy.round((XY_app)).astype(\"int\")\n",
    "indexed[\"X\"] = XY_int[0]\n",
    "indexed[\"Y\"] = XY_int[1]\n",
    "xy_guess = numpy.dot(rot, step * XY_int + xy_min)\n",
    "\n",
    "thres = 1.2\n",
    "delta = abs(xy_guess - xy)\n",
    "print((delta>thres).sum())\n",
    "suspicious = indexed[numpy.where(abs(delta>thres))[1]]\n",
    "print(suspicious)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7ff811de84a8>]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,ax = subplots()\n",
    "ax.imshow(img.clip(0,1000))\n",
    "ax.plot(indexed[\"x\"], indexed[\"y\"],\".g\")\n",
    "ax.plot(suspicious[\"x\"], suspicious[\"y\"],\".r\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Only 6 peaks have an initial displacement of more than 1.2 pixel, all located in modules 40 and 46. \n",
    "The visual inspection confirms their localization is valid.\n",
    "\n",
    "There are 48 (half-)modules which have each of them 2 translations and one rotation. \n",
    "In addition to the step size, this represents 145 degrees of freedom for the fit.\n",
    "The first module is used to align the grid, all other modules are then aligned along this grid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost for module # 1 0.6337542147785734\n",
      "Cost for module # 2 1.8137335142043005\n",
      "Cost for module # 3 1.8517810791354326\n",
      "Cost for module # 4 4.9127875221043515\n",
      "Cost for module # 5 1.773711051583296\n",
      "Cost for module # 6 7.48693792691493\n",
      "Cost for module # 7 14.439344856965251\n",
      "Cost for module # 8 5.219239827628602\n",
      "Cost for module # 9 23.403682459536583\n",
      "Cost for module # 10 5.689200096256752\n",
      "Cost for module # 11 4.128382716158292\n",
      "Cost for module # 12 8.41469167554883\n",
      "Cost for module # 13 29.862717021161917\n",
      "Cost for module # 14 12.629471494880102\n",
      "Cost for module # 15 3.1375750005201866\n",
      "Cost for module # 16 5.280069866042303\n",
      "Cost for module # 17 8.497446247607941\n",
      "Cost for module # 18 4.655804873784172\n",
      "Cost for module # 19 6.008515385043476\n",
      "Cost for module # 20 4.982313469667585\n",
      "Cost for module # 21 5.13721994073221\n",
      "Cost for module # 22 5.050522255483948\n",
      "Cost for module # 23 1.437001287138772\n",
      "Cost for module # 24 6.050459713222455\n",
      "Cost for module # 25 38.26262874059206\n",
      "Cost for module # 26 19.514969043053544\n",
      "Cost for module # 27 2.4311336259686778\n",
      "Cost for module # 28 5.491303543176383\n",
      "Cost for module # 29 10.770599187417773\n",
      "Cost for module # 30 14.051565356868426\n",
      "Cost for module # 31 22.948589256445068\n",
      "Cost for module # 32 18.498872034582465\n",
      "Cost for module # 33 12.94939072065644\n",
      "Cost for module # 34 15.380312194242064\n",
      "Cost for module # 35 39.681054141224514\n",
      "Cost for module # 36 37.298625739026946\n",
      "Cost for module # 37 63.71626527040634\n",
      "Cost for module # 38 23.55576001555159\n",
      "Cost for module # 39 34.01669588160015\n",
      "Cost for module # 40 43.81908020764373\n",
      "Cost for module # 41 15.51614503136555\n",
      "Cost for module # 42 8.057425004151995\n",
      "Cost for module # 43 22.74618763379752\n",
      "Cost for module # 44 10.802033729233333\n",
      "Cost for module # 45 41.03620867139952\n",
      "Cost for module # 46 46.276855734650006\n",
      "Cost for module # 47 24.5621299905672\n",
      "Cost for module # 48 34.78883325879872\n"
     ]
    }
   ],
   "source": [
    "def submodule_cost(param, module=1):\n",
    "    \"\"\"contains: step, y_min_1, x_min_1, angle_1, y_min_2, x_min_2, angle_2, ...\n",
    "    returns the sum of distance squared in pixel space\n",
    "    \"\"\"\n",
    "    \n",
    "    step = param[0]\n",
    "    y_min1 = param[1]\n",
    "    x_min1 = param[2]\n",
    "    angle1 = param[3]\n",
    "    \n",
    "    mask = indexed[\"i\"] == module\n",
    "    substack = indexed[mask]\n",
    "    \n",
    "    XY = numpy.vstack((substack[\"X\"], substack[\"Y\"]))\n",
    "    rot1 = [[cos(angle1), -sin(angle1)],\n",
    "            [sin(angle1), cos(angle1)]]\n",
    "    xy_min1 = numpy.array([[x_min1], [y_min1]])\n",
    "    xy_guess1 = numpy.dot(rot1, step * XY + xy_min1)\n",
    "    #This is guessed spot position for module #1\n",
    "    if module == 1:\n",
    "        \"Not much to do for module 1\"\n",
    "        delta = xy_guess1 - numpy.vstack((substack[\"x\"], substack[\"y\"]))\n",
    "    else:\n",
    "        \"perform the correction for given module\"\n",
    "        y_min = param[(module-1)*3+1]\n",
    "        x_min = param[(module-1)*3+2]\n",
    "        angle = param[(module-1)*3+3]     \n",
    "\n",
    "        rot = numpy.array([[cos(angle),-sin(angle)],\n",
    "                           [sin(angle), cos(angle)]])\n",
    "        xy_min = numpy.array([[x_min], [y_min]])\n",
    "        xy_guess = numpy.dot(rot, xy_guess1+xy_min)\n",
    "        delta = xy_guess - numpy.vstack((substack[\"x\"], substack[\"y\"]))\n",
    "\n",
    "    return (delta*delta).sum()\n",
    "\n",
    "guess145 = numpy.zeros(48*3+1)\n",
    "guess145[:4] = res1.x\n",
    "for i in range(1, 49):\n",
    "    print(\"Cost for module #\",i, submodule_cost(guess145, i))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On retrieves that the modules 40 and 46 have large errors. Module 37 as well.\n",
    "\n",
    "The total cost funtion is hence the sum of all cost function for all modules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "778.6690275085203"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def total_cost(param):\n",
    "    \"\"\"contains: step, y_min_1, x_min_1, angle_1, ...\n",
    "    returns the sum of distance squared in pixel space\n",
    "    \"\"\"\n",
    "    return sum(submodule_cost(param, module=i) for i in range(1,49))\n",
    "total_cost(guess145)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before optimization [2.93980817e+01 7.13605736e+00 1.63978976e+01 8.76803451e-04\n",
      " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      " 0.00000000e+00 0.00000000e+00] cost= 778.6690275085203\n",
      "     fun: 27.18365832628731\n",
      "     jac: array([ 3.36764812e-01,  2.41279602e-04,  1.03421211e-02, -8.09069777e+00,\n",
      "       -2.82526016e-04, -8.50439072e-04, -1.01323128e-02, -8.08238983e-05,\n",
      "       -3.63349915e-04, -1.85797215e-02, -1.40905380e-04, -9.55820084e-04,\n",
      "       -8.91995430e-03,  1.38282776e-05,  8.19206238e-04, -1.05245113e-01,\n",
      "       -2.09569931e-04,  1.52707100e-03, -1.26422167e-01,  2.03394890e-03,\n",
      "        8.81671906e-04, -3.47824097e-02,  1.43098831e-03,  1.91617012e-03,\n",
      "       -2.55455971e-02, -3.88145447e-04, -1.01804733e-04, -1.31155491e-01,\n",
      "       -3.17335129e-04,  2.88486481e-04, -1.11642122e-01,  1.31368637e-04,\n",
      "       -3.75986099e-04,  8.54325294e-03, -1.75714493e-04, -1.26838684e-04,\n",
      "       -1.08163357e-01,  3.51667404e-04,  3.56912613e-04, -9.72857475e-02,\n",
      "       -7.34567642e-04, -7.43865967e-04, -3.60100269e-02, -1.92165375e-04,\n",
      "       -1.22308731e-04, -6.77630901e-02,  2.69412994e-05,  3.32355499e-04,\n",
      "       -1.52028084e-01, -7.98940659e-04, -1.35207176e-03, -3.32699060e-01,\n",
      "        4.24385071e-04,  4.83512878e-04, -2.34975100e-01, -1.58643723e-03,\n",
      "       -1.14440918e-05, -9.22925472e-02, -1.26242638e-03, -5.36918640e-04,\n",
      "       -4.03177738e-02,  2.01225281e-04,  2.02655792e-04, -1.15622759e-01,\n",
      "       -3.58581543e-04, -3.13043594e-04, -1.85351372e-01,  3.60727310e-04,\n",
      "        2.01702118e-04, -1.06734037e-01,  4.86373901e-04,  7.61508942e-04,\n",
      "       -8.16304684e-02,  8.49723816e-04,  2.74896622e-04, -1.41849279e-01,\n",
      "        8.97884369e-04,  3.00168991e-04, -8.56087208e-02,  7.53402710e-04,\n",
      "        3.68595123e-04,  1.32328033e-01, -1.43051147e-05, -1.49726868e-04,\n",
      "        5.17210960e-02, -1.03306770e-03, -8.61167908e-04, -1.73690319e-01,\n",
      "        9.89198685e-04,  4.65631485e-04, -9.13746357e-02,  4.30822372e-04,\n",
      "        2.80380249e-04, -1.09273434e-01,  2.12192535e-04,  2.64644623e-04,\n",
      "       -1.86563969e-01,  5.52654266e-04,  1.77383423e-04, -2.00356483e-01,\n",
      "       -7.89165497e-05, -2.15530396e-04, -1.59254074e-01, -1.34491920e-03,\n",
      "       -7.27415085e-04, -3.59580994e-01, -3.62873077e-04,  6.33001328e-04,\n",
      "       -4.18133974e-01,  7.90119171e-04,  4.77075577e-04, -3.38363886e-01,\n",
      "       -5.48362732e-06,  1.46865845e-04, -1.75536156e-01,  3.64065170e-04,\n",
      "        8.61644745e-04, -2.99779892e-01,  6.23703003e-04,  2.30121613e-03,\n",
      "       -2.43101120e-01,  7.79151917e-04,  9.93490219e-04, -3.10999632e-01,\n",
      "        4.47273254e-04,  1.13582611e-03, -3.22041512e-01, -1.87778473e-03,\n",
      "        2.86579132e-04, -3.00019503e-01,  2.96115875e-04, -5.55753708e-04,\n",
      "       -3.44004393e-01, -1.32369995e-03, -2.36272812e-04, -3.29681873e-01,\n",
      "       -1.74283981e-04,  6.97374344e-04, -3.31437826e-01, -5.36918640e-04,\n",
      "        5.60283661e-05, -2.70724535e-01,  1.46508217e-03,  2.64167786e-04,\n",
      "       -1.53188705e-01])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 14738\n",
      "     nit: 97\n",
      "    njev: 97\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 2.94082848e+01,  7.10550236e+00,  1.63621431e+01,  8.76343987e-04,\n",
      "       -2.61142002e-01, -1.72404666e-01,  2.75358939e-04, -4.65371706e-01,\n",
      "       -1.49368876e-01,  9.23377934e-04, -1.40925206e+00, -3.92431812e-02,\n",
      "        1.93786320e-03, -4.71619538e-01, -4.34506153e-01,  3.15955995e-04,\n",
      "       -2.55783527e+00, -4.42186027e-01,  2.08129218e-03, -7.62295275e-01,\n",
      "        5.00535589e-01,  1.34360338e-03, -8.36248315e-01,  2.10686060e-01,\n",
      "        1.08362469e-03, -1.27272229e+00, -1.27829390e-01,  8.94580313e-04,\n",
      "       -2.05296929e+00,  2.04524448e-01,  2.10557127e-03, -3.29262534e-01,\n",
      "       -1.11556153e-01,  4.68865734e-04, -5.88218340e-01,  3.71081910e-02,\n",
      "        6.46130657e-04, -8.24199310e-01,  4.59685359e-02,  1.14564520e-03,\n",
      "       -9.99768822e-01,  1.20247034e-01,  1.31121860e-03, -9.06361732e-01,\n",
      "        1.88553858e-01,  9.65779253e-04, -1.14461914e+00,  1.26388275e-01,\n",
      "        1.27134440e-03, -8.21266979e-01, -5.18563664e-01,  4.32107560e-04,\n",
      "       -2.16110379e+00,  1.33708683e-01,  1.53367349e-03, -5.67627925e-01,\n",
      "        3.19370766e-01,  7.07441671e-04, -4.90631071e-01,  6.01221530e-02,\n",
      "        7.15756603e-04, -2.58645439e-01, -6.04060774e-01, -3.01162879e-04,\n",
      "       -1.66726458e+00,  6.64322082e-01,  1.62371556e-03, -1.58599237e+00,\n",
      "        6.43415301e-01,  1.23645918e-03, -2.16623943e+00,  8.25942522e-01,\n",
      "        1.65256754e-03, -8.55872469e-01,  1.36470630e-01,  9.44940792e-04,\n",
      "       -1.04916637e+00,  8.15407272e-01,  1.75160691e-03,  2.14373439e-01,\n",
      "       -6.90411962e-01, -5.25494569e-04, -4.87271205e-01,  3.35472535e-01,\n",
      "        5.93598781e-04, -7.51957868e-01, -2.87512355e-01,  5.55801951e-04,\n",
      "       -3.03293420e+00,  1.59247632e+00,  2.32811165e-03, -4.66935314e-01,\n",
      "       -1.52659742e+00, -7.47172216e-04, -1.21117247e+00,  8.98551575e-01,\n",
      "        1.43614378e-03,  2.05750982e-01, -1.38157673e+00, -6.38868427e-04,\n",
      "       -1.40203507e+00,  1.03337865e+00,  1.55563831e-03, -9.47399558e-01,\n",
      "       -5.13283043e-01,  6.36750009e-04, -8.52438513e-01, -6.12855414e-01,\n",
      "        5.58099763e-04, -1.02281342e+00, -1.03557970e+00, -3.49555463e-05,\n",
      "       -9.28000183e-01, -8.97165498e-01, -4.07212989e-05, -6.65844032e-01,\n",
      "       -8.46731364e-01,  1.07502923e-04, -2.37944396e+00,  2.10370247e+00,\n",
      "        2.43396212e-03, -5.84541323e-01, -4.18588167e-01,  3.37284557e-04,\n",
      "       -1.08753981e+00,  6.65981023e-02,  6.11100460e-04, -9.52909811e-01,\n",
      "        9.59526263e-01,  9.85626571e-04, -8.37807529e-01,  1.62657619e-01,\n",
      "        5.46469118e-04, -3.42723669e-01, -1.67395622e+00, -3.58118168e-04,\n",
      "       -1.50828980e+00,  7.38683145e-01,  1.28170883e-03, -1.40264511e+00,\n",
      "        8.68409721e-01,  1.15128804e-03, -2.28992308e+00,  2.04723385e+00,\n",
      "        1.83647125e-03])\n",
      "After optimization [ 2.94082848e+01  7.10550236e+00  1.63621431e+01  8.76343987e-04\n",
      " -2.61142002e-01 -1.72404666e-01  2.75358939e-04 -4.65371706e-01\n",
      " -1.49368876e-01  9.23377934e-04] cost= 27.18365832628731\n",
      "CPU times: user 25.7 s, sys: 44.7 ms, total: 25.8 s\n",
      "Wall time: 25.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "print(\"Before optimization\", guess145[:10], \"cost=\", total_cost(guess145))\n",
    "res_all = minimize(total_cost, guess145, method = \"slsqp\")\n",
    "print(res_all)\n",
    "print(\"After optimization\", res_all.x[:10], \"cost=\", total_cost(res_all.x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Module id: 1 cost: 0.683 Δx: 7.106, Δy: 16.362 rot: 0.050°\n",
      "Module id: 2 cost: 0.473 Δx: -0.261, Δy: -0.172 rot: 0.016°\n",
      "Module id: 3 cost: 0.650 Δx: -0.465, Δy: -0.149 rot: 0.053°\n",
      "Module id: 4 cost: 0.613 Δx: -1.409, Δy: -0.039 rot: 0.111°\n",
      "Module id: 5 cost: 0.566 Δx: -0.472, Δy: -0.435 rot: 0.018°\n",
      "Module id: 6 cost: 0.666 Δx: -2.558, Δy: -0.442 rot: 0.119°\n",
      "Module id: 7 cost: 0.696 Δx: -0.762, Δy: 0.501 rot: 0.077°\n",
      "Module id: 8 cost: 0.341 Δx: -0.836, Δy: 0.211 rot: 0.062°\n",
      "Module id: 9 cost: 0.566 Δx: -1.273, Δy: -0.128 rot: 0.051°\n",
      "Module id: 10 cost: 0.661 Δx: -2.053, Δy: 0.205 rot: 0.121°\n",
      "Module id: 11 cost: 0.616 Δx: -0.329, Δy: -0.112 rot: 0.027°\n",
      "Module id: 12 cost: 0.495 Δx: -0.588, Δy: 0.037 rot: 0.037°\n",
      "Module id: 13 cost: 0.763 Δx: -0.824, Δy: 0.046 rot: 0.066°\n",
      "Module id: 14 cost: 0.353 Δx: -1.000, Δy: 0.120 rot: 0.075°\n",
      "Module id: 15 cost: 0.645 Δx: -0.906, Δy: 0.189 rot: 0.055°\n",
      "Module id: 16 cost: 0.492 Δx: -1.145, Δy: 0.126 rot: 0.073°\n",
      "Module id: 17 cost: 0.440 Δx: -0.821, Δy: -0.519 rot: 0.025°\n",
      "Module id: 18 cost: 0.779 Δx: -2.161, Δy: 0.134 rot: 0.088°\n",
      "Module id: 19 cost: 0.748 Δx: -0.568, Δy: 0.319 rot: 0.041°\n",
      "Module id: 20 cost: 0.423 Δx: -0.491, Δy: 0.060 rot: 0.041°\n",
      "Module id: 21 cost: 0.520 Δx: -0.259, Δy: -0.604 rot: -0.017°\n",
      "Module id: 22 cost: 0.676 Δx: -1.667, Δy: 0.664 rot: 0.093°\n",
      "Module id: 23 cost: 0.503 Δx: -1.586, Δy: 0.643 rot: 0.071°\n",
      "Module id: 24 cost: 0.822 Δx: -2.166, Δy: 0.826 rot: 0.095°\n",
      "Module id: 25 cost: 0.575 Δx: -0.856, Δy: 0.136 rot: 0.054°\n",
      "Module id: 26 cost: 0.320 Δx: -1.049, Δy: 0.815 rot: 0.100°\n",
      "Module id: 27 cost: 0.642 Δx: 0.214, Δy: -0.690 rot: -0.030°\n",
      "Module id: 28 cost: 0.599 Δx: -0.487, Δy: 0.335 rot: 0.034°\n",
      "Module id: 29 cost: 0.498 Δx: -0.752, Δy: -0.288 rot: 0.032°\n",
      "Module id: 30 cost: 0.830 Δx: -3.033, Δy: 1.592 rot: 0.133°\n",
      "Module id: 31 cost: 0.687 Δx: -0.467, Δy: -1.527 rot: -0.043°\n",
      "Module id: 32 cost: 0.422 Δx: -1.211, Δy: 0.899 rot: 0.082°\n",
      "Module id: 33 cost: 0.616 Δx: 0.206, Δy: -1.382 rot: -0.037°\n",
      "Module id: 34 cost: 0.393 Δx: -1.402, Δy: 1.033 rot: 0.089°\n",
      "Module id: 35 cost: 0.447 Δx: -0.947, Δy: -0.513 rot: 0.036°\n",
      "Module id: 36 cost: 0.587 Δx: -0.852, Δy: -0.613 rot: 0.032°\n",
      "Module id: 37 cost: 0.603 Δx: -1.023, Δy: -1.036 rot: -0.002°\n",
      "Module id: 38 cost: 0.295 Δx: -0.928, Δy: -0.897 rot: -0.002°\n",
      "Module id: 39 cost: 0.558 Δx: -0.666, Δy: -0.847 rot: 0.006°\n",
      "Module id: 40 cost: 0.498 Δx: -2.379, Δy: 2.104 rot: 0.139°\n",
      "Module id: 41 cost: 0.468 Δx: -0.585, Δy: -0.419 rot: 0.019°\n",
      "Module id: 42 cost: 0.569 Δx: -1.088, Δy: 0.067 rot: 0.035°\n",
      "Module id: 43 cost: 0.633 Δx: -0.953, Δy: 0.960 rot: 0.056°\n",
      "Module id: 44 cost: 0.413 Δx: -0.838, Δy: 0.163 rot: 0.031°\n",
      "Module id: 45 cost: 0.671 Δx: -0.343, Δy: -1.674 rot: -0.021°\n",
      "Module id: 46 cost: 0.542 Δx: -1.508, Δy: 0.739 rot: 0.073°\n",
      "Module id: 47 cost: 0.537 Δx: -1.403, Δy: 0.868 rot: 0.066°\n",
      "Module id: 48 cost: 0.593 Δx: -2.290, Δy: 2.047 rot: 0.105°\n"
     ]
    }
   ],
   "source": [
    "for i in range(1,49):\n",
    "    print(\"Module id: %d cost: %.3f Δx: %.3f, Δy: %.3f rot: %.3f°\"%\n",
    "          (i, submodule_cost(res_all.x, i), res_all.x[-2+i*3], res_all.x[-1+i*3], numpy.rad2deg(res_all.x[i*3])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysis:\n",
    "Modules 40, 46 and 48 show large displacement but the fitting precedure allowed to reduce the residual cost to the same value as other  modules.\n",
    "\n",
    "## Reconstruction of the pixel position\n",
    "\n",
    "The pixel position can be obtained from the *standard* Pilatus detector. \n",
    "Each module is then displaced according to the fitted values, except the first one which is left where it is."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "pixel_coord = pyFAI.detector_factory(\"Pilatus2MCdTe\").get_pixel_corners()\n",
    "pixel_coord_raw = pixel_coord.copy()\n",
    "for i in range(2, 49):\n",
    "    # Extract the pixel corners for one module\n",
    "    module_idx = numpy.where(mid == i)\n",
    "    one_module = pixel_coord_raw[module_idx]\n",
    "    #retrieve the fitted values\n",
    "    dy = res_all.x[1+(i-1)*3]\n",
    "    dx = res_all.x[2+(i-1)*3]\n",
    "    angle = res_all.x[3+(i-1)*3]\n",
    "    \n",
    "    z = one_module[...,0]\n",
    "    y = one_module[...,1]\n",
    "    x = one_module[...,2]\n",
    "    \n",
    "    #apply the correction the other way around\n",
    "    irot = [[cos(angle), sin(angle)],\n",
    "           [-sin(angle), cos(angle)]]\n",
    "    trans = [[dx * pilatus.pixel2],\n",
    "              [dy * pilatus.pixel1]]\n",
    "    xy_guess = numpy.vstack((x.ravel(), y.ravel()))\n",
    "    xy_cor = numpy.dot(irot, xy_guess) - trans\n",
    "    xy_cor.shape = ((2,)+x.shape)\n",
    "    one_module[...,1] = xy_cor[1, ...] #y\n",
    "    one_module[...,2] = xy_cor[0, ...] #x\n",
    "    #Update the array\n",
    "    pixel_coord_raw[module_idx] = one_module\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Update the detector and save it in HDF5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/kieffer/.jupy37/lib/python3.7/site-packages/pyFAI/io/__init__.py:999: H5pyDeprecationWarning: The default file mode will change to 'r' (read-only) in h5py 3.0. To suppress this warning, pass the mode you need to h5py.File(), or set the global default h5.get_config().default_file_mode, or set the environment variable H5PY_DEFAULT_READONLY=1. Available modes are: 'r', 'r+', 'w', 'w-'/'x', 'a'. See the docs for details.\n",
      "  self.h5 = h5py.File(self.filename)\n"
     ]
    }
   ],
   "source": [
    "pilatus.set_pixel_corners(pixel_coord_raw)\n",
    "pilatus.mask = all_masks\n",
    "pilatus.save(\"Pilatus_ID15_raw.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Error in pixel size (172µm)')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "displ = numpy.sqrt(((pixel_coord - pixel_coord_raw)**2).sum(axis=-1))\n",
    "displ /= pilatus.pixel1 #convert in pixel units\n",
    "fig, ax = subplots()\n",
    "ax.hist(displ.ravel(), 100)\n",
    "ax.set_title(\"Displacement of pixels versus the reference representation\")\n",
    "ax.set_xlabel(\"Error in pixel size (172µm)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.16861754193929496"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unmasked = numpy.logical_not(all_masks)\n",
    "misaligned = numpy.vstack((pixel_coord_raw[unmasked][..., 2].ravel(), #x\n",
    "                           pixel_coord_raw[unmasked][..., 1].ravel())) #y\n",
    "\n",
    "reference = numpy.vstack((pixel_coord[unmasked][..., 2].ravel(), #x\n",
    "                          pixel_coord[unmasked][..., 1].ravel())) #y\n",
    "\n",
    "def global_displacement(param):\n",
    "    \"\"\"correct all pixel position with dy. dx, angle\"\"\"\n",
    "    dy, dx, angle = param\n",
    "    rot = [[cos(angle), -sin(angle)],\n",
    "           [sin(angle), cos(angle)]]\n",
    "    trans = [[dx],\n",
    "              [dy]]\n",
    "    xy_corr = numpy.dot(rot, misaligned) + trans\n",
    "    delta = xy_corr - reference\n",
    "    return (delta*delta).sum()\n",
    "global_displacement([0,0,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before optimization [0, 0, 0] cost= 0.16861754193929496\n",
      "     fun: 0.02783531839357946\n",
      "     jac: array([ 0.24096283, -0.02946085, -0.02225318])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 45\n",
      "     nit: 5\n",
      "    njev: 5\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([-1.16044090e-04, -2.56376016e-05,  5.33220510e-04])\n",
      "After optimization [-1.16044090e-04 -2.56376016e-05  5.33220510e-04] cost= 0.02783531839357946\n",
      "CPU times: user 25.2 s, sys: 43.6 s, total: 1min 8s\n",
      "Wall time: 10.7 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "guess_global = [0,0,0]\n",
    "print(\"Before optimization\", guess_global, \"cost=\", global_displacement(guess_global))\n",
    "res_global = minimize(global_displacement, guess_global, method = \"slsqp\")\n",
    "print(res_global)\n",
    "print(\"After optimization\", res_global.x, \"cost=\", global_displacement(res_global.x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "dy, dx, angle  = res_global.x\n",
    "rot = [[cos(angle), -sin(angle)],\n",
    "       [sin(angle), cos(angle)]]\n",
    "trans = [[dx],\n",
    "          [dy]]\n",
    "\n",
    "raw = numpy.vstack((pixel_coord_raw[..., 2].ravel(), #x\n",
    "                    pixel_coord_raw[..., 1].ravel())) #y\n",
    "aligned = numpy.dot(rot, raw) + trans\n",
    "\n",
    "pixel_coord_ref = pixel_coord.copy()\n",
    "pixel_coord_ref[...,1] = aligned[1,:].reshape(pixel_coord_ref.shape[:-1])\n",
    "pixel_coord_ref[...,2] = aligned[0,:].reshape(pixel_coord_ref.shape[:-1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Pixel size (172µm)')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "displ = numpy.sqrt(((pixel_coord-pixel_coord_ref)**2).sum(axis=-1))\n",
    "displ /= pilatus.pixel1 #convert in pixel units\n",
    "fig, ax = subplots()\n",
    "ax.hist(displ.ravel(), 100)\n",
    "ax.set_title(\"Displacement of pixels versus the reference representation\")\n",
    "ax.set_xlabel(\"Pixel size (172µm)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "pilatus.set_pixel_corners(pixel_coord_ref)\n",
    "pilatus.mask = all_masks\n",
    "pilatus.save(\"Pilatus_ID15_ref.h5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This tutorial presents the way to calibrate a module based detector using the Pilatus2M CdTe from ESRF-ID15.\n",
    "The HDF5 file generated is directly useable by any parts of pyFAI, the reader is invited in calibrating the rings images with the default definition and with this optimized definition and check the residual error is almost divided by a factor two.\n",
    "\n",
    "To come back on the precision of the localization of the pixel: not all the pixel are within the specifications provided by Dectris which claims the misaliment of the modules is within one pixel.\n",
    "\n",
    "### Final comments:\n",
    "Using Kabsch's algorithm would have been faster then performing the fit ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total execution time:  74.55711460113525\n"
     ]
    }
   ],
   "source": [
    "print(\"Total execution time: \", time.time()-start_time)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7 local venv",
   "language": "python",
   "name": "python3.7"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}