csiborgtools/scripts/concentration_fit.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5a38ed25",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:26:19.645160Z",
     "start_time": "2022-10-30T17:26:16.063760Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "try:\n",
    "    import csiborgtools\n",
    "except ModuleNotFoundError:\n",
    "    import sys\n",
    "    sys.path.append(\"../\")\n",
    "    import csiborgtools\n",
    "import utils\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import joblib\n",
    "from os.path import join\n",
    "from glob import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "70c0f9a8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T19:56:47.381127Z",
     "start_time": "2022-10-30T19:56:46.989870Z"
    }
   },
   "outputs": [],
   "source": [
    "from astropy.cosmology import FlatLambdaCDM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3652ac34",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "09f794e5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "a117da19",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T19:56:48.741569Z",
     "start_time": "2022-10-30T19:56:48.716737Z"
    }
   },
   "outputs": [],
   "source": [
    "cosmo = FlatLambdaCDM(H0=70.5, Om0=0.307, Tcmb0=2.728)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a528cdc6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T19:59:17.762183Z",
     "start_time": "2022-10-30T19:59:17.429757Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "102.09716821960843"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = cosmo.Om0 - 1\n",
    "\n",
    "18*np.pi**2 + 82 * x - 39 * x**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a0e1606",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c167e66e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "267eb013",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:26:19.670054Z",
     "start_time": "2022-10-30T17:26:19.647215Z"
    }
   },
   "outputs": [],
   "source": [
    "Nsim = 9844\n",
    "simpath = csiborgtools.io.get_sim_path(Nsim)\n",
    "Nsnap = 1016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8b07450a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T18:25:45.214497Z",
     "start_time": "2022-10-30T18:25:44.696477Z"
    }
   },
   "outputs": [],
   "source": [
    "fname = join(utils.dumpdir, \"ramses_out_{}_{}.npy\".format(str(Nsim).zfill(5), str(Nsnap).zfill(5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "d31ed713",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T18:25:54.535804Z",
     "start_time": "2022-10-30T18:25:52.926227Z"
    }
   },
   "outputs": [],
   "source": [
    "data = np.load(fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b84497e3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T18:27:41.034366Z",
     "start_time": "2022-10-30T18:27:39.805147Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\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"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.scatter(data[\"logRs\"], data[\"rho0\"], s=2.5, rasterized=True)\n",
    "plt.yscale(\"log\")\n",
    "\n",
    "plt.ylabel(r\"$\\rho_0$\")\n",
    "plt.xlabel(r\"$\\log R_{\\rm s}$\")\n",
    "# plt.savefig(\"../plots/rho0.png\", dpi=450)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "b3c2f08b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T18:26:07.558919Z",
     "start_time": "2022-10-30T18:26:07.532857Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([287721.82008412, 249035.67807171,  69665.64384864, ...,\n",
       "         2582.73496889,             nan,             nan])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"rho0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80014969",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3be99383",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3b0c2257",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:39:51.221007Z",
     "start_time": "2022-10-30T17:39:17.363367Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████| 200/200 [00:24<00:00,  8.16it/s]\n"
     ]
    }
   ],
   "source": [
    "out = csiborgtools.io.combine_splits(utils.Nsplits, Nsim, Nsnap, utils.dumpdir, )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6adb8dec",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:40:10.433810Z",
     "start_time": "2022-10-30T17:40:10.403898Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('index',\n",
       " 'level',\n",
       " 'parent',\n",
       " 'ncell',\n",
       " 'peak_x',\n",
       " 'peak_y',\n",
       " 'peak_z',\n",
       " 'rho-',\n",
       " 'rho+',\n",
       " 'rho_av',\n",
       " 'mass_cl',\n",
       " 'relevance',\n",
       " 'npart',\n",
       " 'totpartmass',\n",
       " 'logRs')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.dtype.names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "134e7495",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:44:46.059808Z",
     "start_time": "2022-10-30T17:44:44.551875Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABQAAAAPACAYAAABq3NR5AAAAAXNSR0IArs4c6QAAAERlWElmTU0AKgAAAAgAAYdpAAQAAAABAAAAGgAAAAAAA6ABAAMAAAABAAEAAKACAAQAAAABAAAFAKADAAQAAAABAAADwAAAAADIn4SfAABAAElEQVR4AezdC/wcVX3//5OQQLgkIBAumnCTAGKQe2wbAljAVlsxVivYykUQy8NqQeu/tvVXlVb6qO0PBQu21V9AoD8Fbf2jVf8+FI0UqRokgCIQAggkcgvGQLgEwuW/78Hzzdn5nsvM7szu7OxrHg/Y3bmcy/PMTvZ8vufMTHmhsxgWBBBAAAEEEEAAAQQQQAABBBBAAAEEEGilwNRW1opKIYAAAggggAACCCCAAAIIIIAAAggggEAmQACQEwEBBBBAAAEEEEAAAQQQQAABBBBAAIEWCxAAbHHjUjUEEEAAAQQQQAABBBBAAAEEEEAAAQQIAHIOIIAAAggggAACCCCAAAIIIIAAAggg0GIBAoAtblyqhgACCCCAAAIIIIAAAggggAACCCCAAAFAzgEEEEAAAQQQQAABBBBAAAEEEEAAAQRaLEAAsMWNS9UQQAABBBBAAAEEEEAAAQQQQAABBBAgAMg5gAACCCCAAAIIIIAAAggggAACCCCAQIsFCAC2uHGpGgIIIIAAAggggAACCCCAAAIIIIAAAgQAOQcQQAABBBBAAAEEEEAAAQQQQAABBBBosQABwBY3LlVDAAEEEEAAAQQQQAABBBBAAAEEEECAACDnAAIIIIAAAggggAACCCCAAAIIIIAAAi0WIADY4salaggggAACCCCAAAIIIIAAAggggAACCBAA5BxAAAEEEEAAAQQQQAABBBBAAAEEEECgxQIEAFvcuFQNAQQQQAABBBBAAAEEEEAAAQQQQAABAoCcAwgggAACCCCAAAIIIIAAAggggAACCLRYgABgixuXqiGAAAIIIIAAAggggAACCCCAAAIIIEAAkHMAAQQQQAABBBBAAAEEEEAAAQQQQACBFgsQAGxx41I1BBBAAAEEEEAAAQQQQAABBBBAAAEECAByDiCAAAIIIIAAAggggAACCCCAAAIIINBiAQKALW5cqoYAAggggAACCCCAAAIIIIAAAggggAABQM4BBBBAAAEEEEAAAQQQQAABBBBAAAEEWixAALDFjUvVEEAAAQQQQAABBBBAAAEEEEAAAQQQIADIOYAAAggggAACCCCAAAIIIIAAAggggECLBQgAtrhxqRoCCCCAAAIIIIAAAggggAACCCCAAAIEADkHEEAAAQQQQAABBBBAAAEEEEAAAQQQaLEAAcAWNy5VQwABBBBAAAEEEEAAAQQQQAABBBBAgAAg5wACCCCAAAIIIIAAAggggAACCCCAAAItFiAA2OLGpWoIIIAAAggggAACCCCAAAIIIIAAAggQAOQcQAABBBBAAAEEEEAAAQQQQAABBBBAoMUCBABb3LhUDQEEEEAAAQQQQAABBBBAAAEEEEAAAQKAnAMIIIAAAggggAACCCCAAAIIIIAAAgi0WIAAYIsbl6ohgAACCCCAAAIIIIAAAggggAACCCBAAJBzAAEEEEAAAQQQQAABBBBAAAEEEEAAgRYLEABsceNSNQQQQAABBBBAAAEEEEAAAQQQQAABBAgAcg4ggAACCCCAAAIIIIAAAggggAACCCDQYgECgC1uXKqGAAIIIIAAAggggAACCCCAAAIIIIAAAUDOAQQQQAABBBBAAAEEEEAAAQQQQAABBFosQACwxY1L1RBAAAEEEEAAAQQQQAABBBBAAAEEECAAyDmAAAIIIIAAAggggAACCCCAAAIIIIBAiwUIALa4cakaAggggAACCCCAAAIIIIAAAggggAACBAA5BxBAAAEEEEAAAQQQQAABBBBAAAEEEGixAAHAFjcuVUMAAQQQQAABBBBAAAEEEEAAAQQQQIAAIOcAAggggAACCCCAAAIIIIAAAggggAACLRYgANjixqVqCCCAAAIIIIAAAggggAACCCCAAAIIEADkHEAAAQQQQAABBBBAAAEEEEAAAQQQQKDFAgQAW9y4VA0BBBBAAAEEEEAAAQQQQAABBBBAAAECgJwDCCCAAAIIIIAAAggggAACCCCAAAIItFiAAGCLG5eqIYAAAggggAACCCCAAAIIIIAAAgggQACQcwABBBBAAAEEEEAAAQQQQAABBBBAAIEWCxAAbHHjUjUEEEAAAQQQQAABBBBAAAEEEEAAAQQIAHIOIIAAAggggAACCCCAAAIIIIAAAggg0GIBAoAtblyqhgACCCCAAAIIIIAAAggggAACCCCAAAFAzgEEEEAAAQQQQAABBBBAAAEEEEAAAQRaLEAAsMWNS9UQQAABBBBAAAEEEEAAAQQQQAABBBAgAMg5gAACCCCAAAIIIIAAAggggAACCCCAQIsFCAC2uHGpGgIIIIAAAggggAACCCCAAAIIIIAAAgQAOQcQQAABBBBAAAEEEEAAAQQQQAABBBBosQABwBY3LlVDAAEEEEAAAQQQQAABBBBAAAEEEECAACDnAAIIIIAAAggggAACCCCAAAIIIIAAAi0WIADY4salaggggAACCCCAAAIIIIAAAggggAACCBAA5BxAAAEEEEAAAQQQQAABBBBAAAEEEECgxQIEAFvcuFQNAQQQQAABBBBAAAEEEEAAAQQQQAABAoCcAwgggAACCCCAAAIIIIAAAggggAACCLRYgABgixuXqiGAAAIIIIAAAggggAACCCCAAAIIIEAAkHMAAQQQQAABBBBAAAEEEEAAAQQQQACBFgsQAGxx41I1BBBAAAEEEEAAAQQQQAABBBBAAAEECAByDiCAAAIIIIAAAggggAACCCCAAAIIINBiAQKALW5cqoYAAggggAACCCCAAAIIIIAAAggggAABQM4BBBBAAAEEEEAAAQQQQAABBBBAAAEEWixAALDFjUvVEEAAAQQQQAABBBBAAAEEEEAAAQQQIADIOYAAAggggAACCCCAAAIIIIAAAggggECLBQgAtrhxqRoCCCCAAAIIIIAAAggggAACCCCAAAIEADkHEEAAAQQQQAABBBBAAAEEEEAAAQQQaLEAAcAWNy5VQwABBBBAAAEEEEAAAQQQQAABBBBAgAAg5wACCCCAAAIIIIAAAggggAACCCCAAAItFiAA2OLGpWoIIIAAAggggAACCCCAAAIIIIAAAggQAOQcQAABBBBAAAEEEEAAAQQQQAABBBBAoMUCBABb3LhUDQEEEEAAAQQQQAABBBBAAAEEEEAAAQKAnAMIIIAAAggggAACCCCAAAIIIIAAAgi0WIAAYIsbl6ohgAACCCCAAAIIIIAAAggggAACCCBAAJBzAAEEEEAAAQQQQAABBBBAAAEEEEAAgRYLEABsceNSNQQQQAABBBBAAAEEEEAAAQQQQAABBAgAcg4ggAACCCCAAAIIIIAAAggggAACCCDQYgECgC1uXKqGAAIIIIAAAggggAACCCCAAAIIIIAAAUDOAQQQQAABBBBAAAEEEEAAAQQQQAABBFosQACwxY1L1RBAAAEEEEAAAQQQQAABBBBAAAEEECAAyDmAAAIIIIAAAggggAACCCCAAAIIIIBAiwUIALa4cakaAggggAACCCCAAAIIIIAAAggggAACBAA5BxBAAAEEEEAAAQQQQAABBBBAAAEEEGixAAHAFjcuVUMAAQQQQAABBBBAAAEEEEAAAQQQQIAAIOcAAggggAACCCCAAAIIIIAAAggggAACLRYgANjixqVqCCCAAAIIIIAAAggggAACCCCAAAIIEADkHEAAAQQQQAABBBBAAAEEEEAAAQQQQKDFAgQAW9y4VA0BBBBAAAEEEEAAAQQQQAABBBBAAAECgJwDCCCAAAIIIIAAAggggAACCCCAAAIItFiAAGCLG5eqIYAAAggggAACCCCAAAIIIIAAAgggQACQcwABBBBAAAEEEEAAAQQQQAABBBBAAIEWCxAAbHHjUjUEEEAAAQQQQAABBBBAAAEEEEAAAQQIAHIOIIAAAggggAACCCCAAAIIIIAAAggg0GIBAoAtblyqhgACCCCAAAIIIIAAAggggAACCCCAAAFAzgEEEEAAAQQQQAABBBBAAAEEEEAAAQRaLEAAsMWNS9UQQAABBBBAAAEEEEAAAQQQQAABBBAgAMg5gAACCCCAAAIIIIAAAggggAACCCCAQIsFCAC2uHGpGgIIIIAAAggggAACCCCAAAIIIIAAAgQAOQcQQAABBBBAAAEEEEAAAQQQQAABBBBosQABwBY3LlVDAAEEEEAAAQQQQAABBBBAAAEEEECAACDnAAIIIIAAAggggAACCCCAAAIIIIAAAi0WIADY4salaggggAACCCCAAAIIIIAAAggggAACCBAA5BxAAAEEEEAAAQQQQAABBBBAAAEEEECgxQIEAFvcuFQNAQQQQAABBBBAAAEEEEAAAQQQQAABAoCcAwgggAACCCCAAAIIIIAAAggggAACCLRYYFqL60bVGiywYcMG89Of/jQr4ezZs820aZyKDW4uioYAAggggAACCCCAAAIIIDCiAs8++6xZs2ZNVvoDDjjAzJgxY0RrQrH7ESDq0o8ex/YsoODfggULej6eAxFAAAEEEEAAAQQQQAABBBBAoJzAsmXLzOGHH17uIPZuhQBTgFvRjFQCAQQQQAABBBBAAAEEEEAAAQQQQAABvwAjAP0urK1ZQNN+7aK/QOy66672I68IIIAAAggggAACCCCAAAIIIFCRwAMPPDAxA8/ti1eUPMmMiAABwBFpqLYV073nn4J/c+bMaVsVqQ8CCCCAAAIIIIAAAggggAACjRJw++KNKhiFqV2AKcC1E5MBAggggAACCCCAAAIIIIAAAggggAACwxMgADg8e3JGAAEEEEAAAQQQQAABBBBAAAEEEECgdgECgLUTkwECCCCAAAIIIIAAAggggAACCCCAAALDEyAAODx7ckYAAQQQQAABBBBAAAEEEEAAAQQQQKB2AQKAtROTAQIIIIAAAggggAACCCCAAAIIIIAAAsMTIAA4PHtyRgABBBBAAAEEEEAAAQQQQAABBBBAoHYBAoC1E5MBAggggAACCCCAAAIIIIAAAggggAACwxMgADg8e3JGAAEEEEAAAQQQQAABBBBAAAEEEECgdgECgLUTkwECCCCAAAIIIIAAAggggAACCCCAAALDEyAAODx7ckYAAQQQQAABBBBAAAEEEEAAAQQQQKB2AQKAtROTAQIIIIAAAggggAACCCCAAAIIIIAAAsMTIAA4PHtyRgABBBBAAAEEEEAAAQQQQAABBBBAoHYBAoC1E5MBAggggAACCCCAAAIIIIAAAggggAACwxMgADg8e3JGAAEEEEAAAQQQQAABBBBAAAEEEECgdgECgLUTkwECCCCAAAIIIIAAAggggAACCCCAAALDEyAAODx7ckYAAQQQQAABBBBAAAEEEEAAAQQQQKB2AQKAtRM3M4Ojjz7aTJkypdB/zawBpUIAAQQQQAABBBBAAAEEEEAAAQQQKCJAALCIEvsggAACCCCAAAIIIIAAAggggAACCCAwogLTRrTcFLsigcMOO8xccsklFaVGMggggAACCCCAAAIIIIAAAggggAACTRMgANi0Fhlwebbeemszf/78AedKdggggAACCCCAAAIIIIAAAggggAACgxJgCvCgpMkHAQQQQAABBBBAAAEEEEAAAQQQQACBIQgQABwCOlkigAACCCCAAAIIIIAAAggggAACCCAwKAECgIOSJh8EEEAAAQQQQAABBBBAAAEEEEAAAQSGIEAAcAjoTcry9ttvN69+9avNdtttZ2bMmGHmzJlj3vjGN5rLLrvMbNy4sUlFpSwIIIAAAggggAACCCCAAAIIIIAAAj0I8BCQHtDadMhDDz1k9J9dfvGLXxj999WvftV8/OMfN//xH/9hXvGKV9jNhV9Xr14d3feBBx6IbmcjAggggAACCCCAAAIIIIAAAggggEA1AgQAq3EcuVSmTp1qjjnmGPP617/eHHjggWaHHXYw69evN8uXLzf/9m//Zm677TZz6623mte85jVm2bJlZrfdditVx7lz55ban50RQAABBBBAAAEEEEAAAQQQQAABBOoRmPJCZ6knaVJtssC6deuyab++Mmrq7xlnnGEuvfTSbPOb3vQm8+Uvf9m3a3DdlClTgtvyG1atWpVNPc6v5zMCCCCAAAIIIIAAAggggAACCPQnoBl6dpAO/e/+LEf5aAKADW69MkG0UDUuueQSc+qpp4Y2B9c/++yzZv78+WbFihXZPrpgvOxlLwvun99QZArwggULssO4AOX1+IwAAggggAACCCDQdAGNo7hrzRPmgUefMrtuu6V5+eytTRW/35teb8qHAAKjJ0AAcPTarI4SMwW4DtUWpDlt2jRz+umnm7/4i7/IanPNNdeYP/qjPypcMz1MhAUBBBBAAAEEEEAAgTYKPPrURnP2FTeapSvWTFTvNfvONuefeLDZdsvpE+t4gwACCCCAQFMECAA2pSU85dB9+Ppddt11156T2H///SeO1YNBWBBAAAEEEEAAAQQQGHcBjfzLB/9komCg1l/yjhdnuYy7E/VHAAEEEGiWAAHAZrVHV2n222+/rs+D/sAUhkGLkx8CCCCAAAIIIIBA0wU07dcd+eeWV+vvfPhxs/dO27ireY8AAggggMDQBaYOvQQUoLECegqwXV760pfat7wigAACCCCAAAIIIDC2ArrnX2xJbY8dyzYEEEAAAQTqEiAAWJfsiKerh4BcfPHFE7U48sgjJ97zBgEEEEAAAQQQQACBcRXQAz9iS2p77Fi2IYAAAgggUJcAAcC6ZBuc7tKlS826deuCJdy4caN55zvfaew9CN/whjdMPDI8eBAbEEAAAQQQQAABBBAYAwE97VcP/PAtWs/0X58M6xBAAAEEhi3APQCH3QJDyP/SSy81xx9/fPbf0Ucfbfbdd18za9Ys8/jjj5sbbrjBfOYznzF2+u9OO+1kLrjggiGUkiwRQAABBBBAAAEEEGiegO6Traf95h8EYp8C3LwSUyIEEEAAAQSMIQA4pmeBgn2f//zns/9CBAcccIC54oorzJ577hnahfUIIIAAAggggAACCIydwLZbTs+e9qsHfuief5r2y8i/sTsNqDACCCAwUgIEAEequaop7Ac/+EFz0EEHmR/84AfZSL81a9aYtWvXmi222MLsvPPO5rDDDjNvectbzJve9Caz2WabVZMpqSCAAAIIIIAAAggg0DIBBf0I/LWsUakOAggg0FIBAoAtbdhYtV7xilcY/Xf22WfHdmMbAggggAACCCCAAAIIIIAAAggggEALBHgISAsakSoggAACCCCAAAIIIIAAAggggAACCCAQEiAAGJJhPQIIIIAAAggggAACCCCAAAIIIIAAAi0QIADYgkakCggggAACCCCAAAIIIIAAAggggAACCIQECACGZFiPAAIIIIAAAggggAACCCCAAAIIIIBACwQIALagEakCAggggAACCCCAAAIIIIAAAggggAACIQECgCEZ1iOAAAIIIIAAAggggAACCCCAAAIIINACgWktqANVQAABBBBAAAEEBi7wwgsvmLvWPGEeePQps+u2W5qXz97aTJkyZeDlIEMEEEAAAQQQQAABBFICBABTQmxHAAEEEEAAAQRyAo8+tdGcfcWNZumKNRNbXrPvbHP+iQebbbecPrGONwj0K0CguV9BjkcAAQQQQAABCRAA5DxAAAEEEEAAAQRKCCggkw/+6XAFA7X+kncsKJEauyIQFiDQHLZhCwIIIIAAAgiUE+AegOW82BsBBBBAAAEExlxA037dkX8uh9bf+fDj7ireI9CTQCrQ3FOiHIQAAggggAACYytAAHBsm56KI4AAAggggEAvArrnX2xJbY8dyzYErACBZivBKwIIIIAAAghUIUAAsApF0kAAAQQQQACBsRHQAz9iS2p77Fi2IWAFUoHk1HabDq8IIIAAAggggIAECAByHiCAAAIIIIAAAiUE9LRfPfDDt2j93jtt49vEOgRKCaQCyantpTJjZwQQQAABBBBovQABwNY3MRVEAAEEEEAAgSoFpkyZkj3tNx8EtE8BrjIv0hpfAQLN49v21BwBBBBAAIE6BHgKcB2qpIkAAggggAACrRbYdsvp2dN+9cAPTcXUaCxG/rW6yQdeORtozj9xmkDzwJuCDBFAAAEEEGiFAAHAVjQjlUAAAQQQQACBYQgo6Efgbxjy45EngebxaGdqiQACCCCAwCAECAAOQpk8EEAAAQQQQAABBBDoUYBAc49wHIYAAggggAACEwIEACcoeIMAAggggAACCCCAAAIIlBN44YUXzF1rnpi4HYDu36gp3CwIIIAAAgg0SYAAYJNag7IggAACCCCAAAIIIIDAyAg8+tRGE7pPo6ZwsyCAAAIIINAUAZ4C3JSWoBwIIIAAAggggAACCCAwMgIa+ZcP/qnwS1esydaPTEUoKAIIIIDAWAgQAByLZqaSCCCAAAIIIIAAAgggUKWApv0q2OdbtF5PCWdBAAEEEECgKQIEAJvSEpQDAQQQQAABBBBosIBGOymgce3KFwMb+syCwDgLPPDoU9Hqp7ZHD2YjAggggAACFQtwD8CKQUkOAQQQQAABBBBomwD3OWtbi1KfKgR23XbLaDKp7dGD2YgAAggggEDFAowArBiU5BBAAAEEEEAAgTYJcJ+zNrUmdalSQE/7fc2+s71Jav3eO23j3cZKBBBAAAEEhiFAAHAY6uSJAAIIIIAAAgiMiAD3ORuRhqKYAxeYMmWKOf/EgycFARX803oWBBBAAAEEmiTAFOAmtQZlQQABBBBAAAEEGiaQuo+ZtjPSqWGNRnEGJrDtltPNJe9YkN0fU98FTfvl+zAwfjJCAAEEECghQACwBBa7IoAAAggggAAC4yaQuo9Zavu4eVHfagU0BV2jUG1wTdNuNfKuaYuCfgT+mtYqlAcBBBBAwBUgAOhq8B4BBBBAAAEEEECgS8De52zpijVd6/WB+5xNImFFhQI8fKZCTJJCAAEEEBh7Ae4BOPanAAAIIIAAAggggEBYgPuchW3YUp/AoB4+o3zufPhxc+3KNdmrPrMggAACCCDQRgFGALaxVakTAggggAACCCBQoQD3OasQk6QKCRR5+Ey/U24ZYVioKdgJAQQQQKAlAowAbElDUg0EEEAAAQQQQKBuAQVcFs2bzb3O6oYm/eyefzGG1MNpYsdq26BGGKbKwXYEEEAAAQQGJUAAcFDS5IMAAggggAACCCCAAAKFBFIPl0ltT2VSZIRhKg22I4AAAgggMEoCBABHqbUoKwIIIIAAAggggAACYyBgHz7jq2oVD59JjSBMbfeVi3UIIIAAAgg0WYAAYJNbh7IhgAACCCCAAAIIIDCGAnU/fCY1gnDjcy9k04THkJ4qI4AAAgi0VICHgLS0YakWAggggAACCCCAAAKjLFDnw2fsCMOlK9Z4iU773PVGIw3PP/Fgo3KwIIAAAgggMOoCjAAc9Rak/AgggAACCCCAAAIItFigjofPhEYYuowKDp59xY3uKt4jgAACCCAwsgIEAEe26Sg4AggggAACCCCAAAK9CegpuHc+/Li5duWa7FWfx22xIwwvPvXwYNUVBJQTCwIIIIAAAqMuwBTgUW9Byo8AAggggAACCCCAQAmBR5/amI1sc6e/jvN01+mbTYnq6YEgGoXIggACCCCAwCgLMAJwlFuPsiOAAAIIIIAAAgggUEJAI/00rdUN/unwYUx3bcooxNQDQVLbS/CzKwIIIIAAAkMTYATg0OjJGAEEEEAAAQQQQKDNAgpw3bXmCaMRZAoi6cETuvfcMBeVJx/8s+XRek13HcRotyaNQow9EEQjIwfhYduAVwQQQAABBOoSYARgXbKkiwACCCCAAAIIIDC2Agpw6Umyx37iGnPSkmXZqz5r/TAXBSNjS2p77Nii25o0ClFlDj0QxE6LLlov9kMAAQQQQKDJAowAbHLrUDYEEEAAAQQQQACBkRNIBbgueceCodUpNZ01tb2KgjdlFKJbF/tAEI2AtCM2GfnnCvEeAQQQQGDUBRgBOOotSPkRQAABBBBAAAEEGiVQJMBVpMB13CPPTnf15T+o6a6pUYap7b6yV7VOQb9F85j2W5Un6SCAAAIINEeAEYDNaQtKggACCCCAAAIIINACgVQAS9tTo8vqukeene6afxDIIKe7pkYZpra34BShCggggAACCAxcgADgwMnJEAEEEEAAAQQQGIxAEx9CMZiaDzeXVAArtb3uKcTDnu5qRyH6HkYyqFGIwz1DyB0BBBBAAIHBCxAAHLw5OSKAAAIIIIAAArUL1DWCrPaCtyCDfgNcRaYQp0YQFmFUGlWkUyQvd58mjEJ0y8N7BBBAAAEExkGAAOA4tDJ1RAABBBBAAIGxEqh7BNlYYfZQ2X4DXFVMIe6h2F2H1D16dNijELsqywcEEEAAAQTGQIAA4Bg0MlVEAAEEEEAAgfESGNQIsrpV6w5C1Vn+fgJcqSnCqe391muQo0c1AlEjJnXOXrtyjVHd9FlBVBYEEEAAAQQQqE6AAGB1lqSEAAIIIIAAAgg0QqAJI8j6hRhkEKrfssaO72Wabb9TiGPlSW0b9OjRtrRzypXtCCCAAAIIDFtg6rALQP4IIIAAAggggAAC1QqkRoiltldbmvKppYJQ5VMcrSPsFGI9EMNdBvGk3iKjR90y9fN+3Nu5HzuORQABBBBAoKwAIwDLirE/AggggAACCCDQcIFhjiCrgqZIEGoYD6+oom5F0+hnCnHRPHz7DXL0KO3sawHWIYAAAgggUI8AIwDrcSVVBBBAAAEEEEBgaALDHEFWRaWLBKGqyGcU0lCgc9G82QN7Wm9qdGhqexlT2rmMFvsigAACCCDQnwAjAPvz42gEEEAAAQQQQKCRAsMaQVYFRirIlNpeRRnGNY1Bjh5NtWNq+7i2EfVGAIHhCozyA6qGK0fuwxYgADjsFiB/BBBAAAEEEECgRoFeHkJRY3EKJT3IIFShAo3RTnb06NlX3GiWrlgzUfM67j/Y9Hamkz/R/LxBAIFfC/DgIk6FURaY0vmH7YVRrgBlH02B1atXm7lz52aFX7VqlZkzZ85oVoRSI4AAAggggEAtAuPUyWpqoOnOhx83mqarkXh13XOxqe3c1HLV8mUjUQQQKCSga/Vpn7u+648j9kD9keSSdyywHxv3Sv+7cU0ylAIRABwKO5lyAeIcQAABBBBAAIEiAoMIQhUpR137EGh6UbZJ7TzKnfy6zlPSRQABY3SdOvYT1wQprn7/UbX9sSSYacEN9L8LQrV8Nx4C0vIGpnoIIIAAAggggMAoCwz6IRiDtFKgKT/VVvlr6q3Wj9PSpHYu8nTicWob6ooAAi8K8OAizoRRFyAAOOotSPkRQAABBBBAAAEERlKAQFN1zaZgqkbnXLtyTfaqz70udPJ7leM4BNotkHowUWp7u3Wo3SgI8BCQUWglyogAAggggAACCCDQOoEigaa67r3XJsyqp1GnOvGp7W2ypS4IILBJoOkPLtpUUt4h4BdgBKDfhbUIIIAAAggggAACCNQqkAokpbb3W7gqR831W5Zej69jGrXt5PvKpBv9E5T1ybAOgfYL2Kek6zrgLnU8Jd1Nn/cIVCXACMCqJEkHAQQQQAABBBBAAIESAjbQpHv+5Ze6A01Vj5rLl39Qn4tMoy4bsLOd/Pz9GenkD6pVyQeB5gpsu+X07Gm/TXpwUXO1KFnTBAgANq1FKA8CCCCAAAIIIIDAWAgMK9CUGjV3yTsWjIx/XdOo6eSPzClAQREYioD+sFD2jwtDKSiZIuAIEAB0MHiLAAIIIIAAAggggMAgBYYRaKpj1FyVZgpQqowK7mkatEZKKljqW1LTpFPbfWm66+jkuxq8RwABBBAYZQECgKPcepQdAQQQQAABBBBAoFKBMsGnKjMeZKCprlFzVXiUnZo8zGnUVdSXNBBAAAEEEBiUAAHAQUmTDwIIIIAAAggggECjBcoGnxpdmVzh3MDmxudeyG3t/tjvqLnu1Ip/6mVq8rCmURevFXsigAACCCDQDAECgM1oB0qBAAIIIIAAAgggMESBXoJPQyxuqax9gc3tt97crH3imUnp1P3wkUkZOit6nZo8jGnUTrF5iwACCCCAwEgITB2JUlLIWgWeeOIJc9FFF5ljjjnGvOxlLzNbbLGF2Xnnnc0hhxxi3vve95pvfetbteZP4ggggAACCCCAwLAFigSfhl3GXvIPBTYV/FMQ0F2G/ZTbIlOT3fLm32sa9aJ5s7kxfx6GzwgggAACCHQEGAE45qfB0qVLzTve8Q5z7733dkk8/PDDRv/deOON5tprrzWvfe1ru7bzAQEEEEAAAQQQaJNAkeDTKD7xMRbYVBDw4lMPN9M3m5I9bGPY9UtNPU5tb9P5SF0QQAABBBCoWoAAYNWiI5Te1Vdfbd7whjeYDRs2mO22286ceeaZ5uijjzY77bSTefLJJ81tt91mvva1r5mHHnpohGpFURFAAAEEEEAAgfICqeBSanv5HAdzRCqwqeCfRs01YRnmAz3ceySqrWNPHm6CFWVAAAEEEECgrAABwLJiLdl/zZo15sQTT8yCfwcddJD55je/mU37dau3cOFC8853vtM888zk+8O4+/EeAQQQQAABBJovQIAj3kbDDD7FS9bf1lTgMrW9v9zLHT2sB3r47pFop0Pr/oIsCCCAAAIItEGAAGAbWrGHOvzVX/2V+eUvf2m22morc9VVV00K/rlJbr559/1h3G28RwABBBBAAIHmCxDgKNZGZx2zT/ZgjJtXPzpxgA0ETawYsTejFtgc9AM9QvdIXLpijTn7ihvNJe9YMGItTnERQAABBBDwC/AQEL9Lq9f+6le/Mp///OezOr797W83u+++e6vrS+UQQAABBBBou4CCGHc+/Li5duWa7FWf7ZIKcNj9xvlVAdLTPne9Wfzp64wN/h04Z1tz1Z8uzAJAozwKzI6qUyDTXZoe2BzUAz1i90hUEFDfKxYEEEAAAQTaIMAIwDa0Ysk66L5+Tz31VHbU8ccfP3G07vt3//33m2222SYbEagfjCwIIIAAAggg0GyB1Oi+IgGOYT/8YZjCoQCpAoEXXH3HyI0AU33U5rr3n72X3aBH1Q2zPcvmnbpHoraP8/ejrCf7I4AAAgg0V4ARgM1tm9pK9sMf/nAi7QMOOMBcf/312VN+Z86caebNm2d23XXXLAD4nve8hweATEjxBgEEEEAAgeYJhIJXdvqiSlwkwNG8mg2uREUCpIMrTX852ZGMx37iGnPSkmVGrxrZqPVaBjWqrr9aDPbo1D0QU9sHW1pyQwABBBBAoHcBAoC9243skbfeeutE2ZcuXWp+67d+y3z72982zz///MR6PSTkoosuMnpAyM033zyxvuib1atXm9h/DzzwQNGk2A8BBBBAAAEEAgJFglepAEZqeyDr1qxuS4C0SDDYNpr2DU0Zt/uMy6u9R6Kvvpomzeg/nwzrEEAAAQRGUYApwKPYan2Wee3atRMpnHnmmUZTfT/2sY+Zk08+ORv5d+edd5p/+qd/Mp/73OfMgw8+aBYvXpwFAWfNmjVxXOrN3LlzU7uwHQEEEEAAAQT6FCgSvDpi7x2NAhkaFZhfCHCYbJps3sX9PCoB0iLBYAWzUlPG3bqPw3t7j0Q98MP9jjT9Honj0DbUEQEEEECgWgFGAFbrORKpPfHEExPl3LBhg1myZIn50Ic+ZBS00xN/999/f3PJJZeYd73rXdl+99xzj/mXf/mXiWN4gwACCCCAAALNEEgFp7TdBjgU0HAXAhwvarRlBFiRYHCZUYLuudL29/YeiVe//yhz+ekLjF719N9RfvhL29uM+iGAAAIIlBeY0vkhsOkxceWP54gaBap4CIcCeaeeempXKefPn29+9rOfZete9apXBaf4/vKXvzQve9nLzNNPP20OPvhgs3z58q50Yh80/Te2aArwggULsl1WrVpl5syZE9udbQgggAACCCDgEdDPON3jzR25ZHdTgE9BDHfRtE8FihQYZGrjJpk2jIpT2+qef6FFQS0tqX2adl7oHM8/1KSK38ghJ9YjgAACbRRQ/9zO0qP/3cYWLlYnpgAXc2rVXnrYh11e+9rX2reTXnfYYQdz2GGHmeuuuy4LEj7zzDPZCMFJO3pWENDzoLAKAQQQaIkAHfLmNKQd3Vd0+qKCO00L8DRB044AG+UAqR3JGAoGq92vXTl5Grjrr+Bwk86PNgRmXV/eI4AAAgggMEwBAoDD1E/kfdtttyX2SG/WE33ziyL/9knA9q8A+X3sZ7tdDwjRvQN32WUXu4lXBBBAAIExFKBDXrzRBxUobUPwqrhqvXuOcoC0SDA4NWV8l1kzsoeD2FGiCiq6o+0GdU6rlZVXPrCt9Qpwan1+dKu2sSCAAAIIIIBAWIAAYNhm6Fv222+/Wsrwyle+0nzpS1/K0n7uueeiebjbp03jdIlisREBBBBouQAd8uINPIxAaZXBq0EGeoqrDmfPUbJIBYNjowSP2HsH8/ffuK1rOrm9T6TSHfQ5XfShJsM5K8gVAQQQQACB0RPgISCj12Z9l/jII4+cSOPuu++eeO97c9ddd2WrZ8yYYbbffnvfLqxDAAEEEBgTgSId8jGhiFYzFSiNHtyAjQr06L6CulfcSUuWZa/6rPXjtoyqhYLBi+bNnjSd144SzD8Q5uh9dsxG+uWnD9vRdsM4p4s81GTczkfqiwACCCCAQD8CBAD70RvRYxUAnD37xScB/td//ZdxR/m5Vfr5z39ubrrppmzVwoULzdSpnC6uD+8RQACBcROgQ16sxUc5UDqMQE8x1cHvVcRC++i+gbq3nl71uemLHSXoPvH2f/3+Kzt1eMRbdAUB7X++HbRNda96SU1XTm2vujykhwACCCCAwKgLENEZ9RbsofybbbaZ+cAHPpAdee+995q/+7u/m5TKs88+a9797ncb3ftPy5lnnjlpH1YggAACCIyXQKrDndputUYxaGLLXuR1UIHSOhxHOXhZpG3K7JOyuOm+dbWNlKyjbfN1d0cJps7Z2x98LH941+fU8V07F/xgpyv7dtcIRpWfBQEEEEAAAQSKC3BTt+JWrdrzz/7sz8yVV15pli9fbs455xyzYsUKc8opp5iddtrJaNrvJz/5SfODH/wgq/PrX/968+Y3v7lV9acyCCCAAALlBWyHXCN+8kvRDvmg7yOWL+cgPqcCoantRcpYl2MqkKPt4xJ4SVl85Ku3mJtXP9rVXPpu9PuAirratquguQ+pc3K/XWbljuj+mDq+e+9in+x05fyDQOx9CYulwl4IIIAAAgggYAUYAWglxuxV9/T72te+Zg499NCs5ldccYV53etel31+61vf2hX80zb3CXBjRkV1EUAAAQR+LWA75Pn7hxXtkGtUU74zr6Rt0KQt0DZQ6qtP0UCp71i7rk7HVCAntd2WcZReQ6PtUnXNB/9snfuZEltn29ry+V5T56zO2/z33qZTxTlt08q/+qYr6+m/Ws+CAAIIIIAAAuUECACW82rV3rvuuqv54Q9/aP71X//VHHXUUdl9AadPn2522WUXc/zxx5svf/nL5utf/7qZOXNmq+pNZRBAAAEEehfop0OemlJZx33Eeq9p70f2GyhN5VynYyoQVPfov1AwLmXS6/bYQz5iFgfO2TaaZWr0YOjgOts2lKfWp87Z1PZY2u62XtvXna7spsd7BBBAAAEEECguwBTg4lat3HPatGnmT/7kT7L/WllBKoUAAgggUIuAOuT5YJA69wpgKPih0VMKoChwYJdUUETb82naY0ft1QZKFdS0HlXVrU5HG+jJj9TUKK/zTzy41mYoMvU1dY6VKaDSytdTx9sRqRpppjqf9YXl5nt3bHpAhp6Ye/Zx+5rFF10XzC41ejB0YJ1tG8rTrk+ds6ntNp3Qa5H2DR3LegQQQKBqgSr/Pam6bKSHQF0CBADrkiVdBBBAAAEExkigSOc+FRRJbR9FTl+gtN96pJxS21P5lw309NOJssfev+5Jc+HSu8yyn6/tKp4bjCtyjnUdnPhQZLTd7JlbdAWxlaSCpHvssFU2JVblyy/9TIlNtV1qe74svXxOnbOp7b48iwRbfcexDgEEEKhDoOp/T+ooI2kiUIcAU4DrUCVNBBBAAAEExkgg1bm3FLEplf0ETWz64/Iqx0XzdvRWV+urGmmodBbNiz9tVZ2o0z53vTn2E9eYk5Ysy171WetTi3vsyRdfPyn4Z4/P7qn30ProaD27b5nX1Gg7BSVDIwRPuXiZOevYfYxGA7pLvyMl2/odKRJsdR15jwACCNQlUPQ3S135ky4CwxQgADhMffJGAAEEEGi0gH4kagrntSvXZK/6zDJZoGjn3k4vVZDEXfoNmrhpjcv70LkYWl+Hi/IKBci0PraEjg0dc8N9v8qm5vq2ZwHCzve07JIaTbfxuReCeeoBIJoCrHP6qncvNJefvsBc/f6jTL8PqKjqOyLfJl27UsHW1Paybcv+CCCAQEig6G+W0PGsR2CUBZgCPMqtR9kRQAABBGoTYHpIcdpU513b7ai0stNLi5difPZU5+X7d/7SW2GtV+DHent3qmhlkU5UqByxY3spnnuOFT3ejrbzTeNVGp/6zspkUvZYBf6qWvr9jjTx2pUKtqa2V2VLOggggECZ3yxoIdA2AUYAtq1FqQ8CCCCAQN8CodFJ6uynRjb1nfkIJpDqvPu2F5le2hQKRlP5W6JIJ8p/pMkejBLall+vEaKH7r59fnXXZ9851rWD54MdbZefxmt31Si/IkuvIxBTaffyHWnqtcsGW311VvuGAsW+/VmHAAII9COQ+vcitb2fvDkWgWELEAAcdguQPwIIIIBA4wRio5Pq6uw3DqFEgdrcuXfvU1f2HnclCEvtmuqcpLaXyiyycyofTaFVQMq3pI61x9jp4XWdYxpt979+/5U2u55fU8HQnhMueWCv1666g9w22Kr2dBfbvu463iOAAAJ1CtT170mdZSZtBKoSIABYlSTpIIAAAgi0RiDVmU9tbw1EwYq0tXPPaKr4CRDrROlIPQwk9ECQ2LEL9njJpHvq1XmOpb7PB87ZNg7R2Vo0oJlMqM8dUnW54d61k4Kygwpy26nNuldiVfdM7JOLwxFAYAwF6vz3ZAw5qfKICUzp/Lj1/2l2xCpCcUdLYPXq1Wbu3LlZoVetWmXmzJkzWhWgtAgg0GoB3UNNTzUNLerAMmXNryM7BSEUEBl1oyafB025z5uvHPkzQ6O8fPfI8x1rR4QpWJRf9JNVI9wUxNJyyG4vMfN2npnfrfTnIu2svD/wpZuNb1pwqH6lC1LBAam6KAvXWPVSkNbey9AtQpPq5ZaL9wgggEBVAm36zZIyof+dEhqP7TwEZDzamVoigAACCJQQsKOTQp3iUQ9slaAovats2uKTGk2l7YOuqw2CKe8P/d7+5q9f/4J58LENQwu42lFd37394SyQ5Dth7LT5vJU9Vh2w+9c9aZ593pjpm00xa9Y/bWbNmJY9YdemVzZYaI8r8lr0+37Z6a+e9NRjG0wrks8g9onVxeav9tC9TBWULTJlON9uNh1eEUAAgVEX0PWNa9yotyLlLyNAALCMFvsigAACCIyFgJ0eok6yGwRsWmd/LBrj15V0A18aXahAh9qpziU1rTO1veqy9RsEq9NQgbvYEguWzp65hTn367d6v2sKEqrc+e+i8nIDWbG8U9uKft/dgKXq08RRrqG65A1sUFb1iC2xdosdxzYEEEAAAQQQaJ4AAcDmtQklQgABBBBogMAodPYbwDSQIvQb+Oq1kLHRVAoGD3LUQL9BsLoNU8HQ0PYi9RrEKLUy3/emjxixdbny+vvMB//zp8HT3wYxgzt0NoTaLXYM2xBAAIEmCdT5x68m1ZOyIFBEgIeAFFFiHwQQQACBsRVQZ3/RvMEGe8YW21PxVIDIc0hlq+xoKgX73GUYI0GLBMHcMrrvY4ZnXHr9pIdCuMcWfW+Dpb79Y8HSIvUqMkrNl28v69zvu9w0PfnalWuyV30epeXQ3bePFldPad5rx62yewL6doy1m29/1iGAAAJNE9Afv3SfU93X+aQly7LX0MOpmlZ2yoNAHQKMAKxDlTQRQAABBBCoSEBBBwVJ7GidQUx9rajolSRTJEBU50g8O5pq2DcKLxIECznEDJfd8ytzwmd+aD578mFGde11scHS/FTdVLC0SL1So9BS21Wnst+jukdM9upc5jgblHVvY+Aer06w2udvF883H77qFu8UbHd/3iOAAAKDEih7zfaVS2nk/03SflXdPsKXJ+sQaLoAAcCmtxDlQwABBBAYW4E2BCH6bbwiAaJQ4KvfvN3jlccg8nHzdN+nglyx7SnDZT9fO/FQCDfPsu97CZbGyq38Z86Ynt3vUYEqXyCryCi1st+jMp3GKjqpZZ2L7h8KyrrHy1TBPz0QZNhBbrdcvEcAgfEVKHvNDknF/vila5+uecP8dz1UbtYjUKcAU4Dr1CVtBBBAAAEEehRIBSF6THbkDksFiFLbR67CgQLb0Vy+zakgWBEj2xnypV92nTpURafNx+qlfP/m//1pNnrv/BMPnjRVVfXW+tjSy/eoSKdReaqT2vSpZTYoe/GphweZbNuXabdgYmxAAAEE+hDo5Zodyi71x6/U9lC6rEdglAUIAI5y61F2BBBAAIHWChQNQrQW4NcViwWIUoGvNtnY0Vyqs7ukgmDqTHUiaObAOdu6h3nfhzpDSqPOe+G9+ZA53vJo5U/vf8wc/HdXm8c2bMxGqV39/qPM5acvMHrVqLXUtOVevkchB1tIba+yk2rTrfO1yFOa68yftBFAAIEiAr1cs0Pppv74ldoeSpf1CIyyAFOAR7n1KDsCCCCAQGsFigQhxmHqig185e/jkwp8tfHEsKO5FIy7f92T5tnnjVFgZ836p82sGdOMrNzFN43K3Z5/7+sM+dKw9qngWz59Bc3UudO5rbxmb7O5OfvKm7xTe91jVYY3XnidWf43x2XTgbXNfj8UIM7XW9ttXt+69UF9DC6+KWA+BzcBbS/SSW3S97NIndw68r75AvYct9+n0Heh+TWhhAhsErDX9k1rut9pe9Frq/0DokY55xf9O1Y0nfyxfEZglAUIAI5y61F2BBBAAIHWCtBh39S0buDLdnYH+cO9aR3t2TO3MOd+/dauwFk+KKcy54Omm0Qnv/N1hkJpqDOltDUCr+jiCyRuv/XmZu0TzxRKQvt97eb7zX8uXx2ttxLz5RXK5OLv321+d/4uXZuLdBr1ZODYUqaTGkunqm1F6lRVXqRTv4DvHM9fA+ovBTkgUL1Alb99+ANi9e1DiqMvwBTg0W9DaoAAAggg0EIB22H3Vc0XrPHt17Z1CvrF7i2ngFXVU1XV0a7zPm9lyxwLyp31heUTTR4boTax06/f2MBBfn0sDXvfuPwxvs+hMhcN/tk0P3H1HV3BP623wUi7Tygvuz3/qqcg65xxF9tplIu7uE5VdlLdPOp6X6ROdeVNutUKhM7x/Heh2lxJDYHBCFT928f+AbHs7SMGU1tyQWDwAowAHLw5OSKAAAIIIJAUsB32/CguNwiRTGRAO6hD6k7t1A94lX+QSx0jYlId7fwIuLIOvZQ5FpT73h2PmJvuW2cO2m27iSmyoTb4+JsP6EzDnRGdRlzVVKxYmUPl862/uzN92Lco8PHd2x/OHhLSS16+0Xq206jgoG/Uqe2kKu/8ou/oIEeo5vMPfU7VKXQc65slEDvHdT76prU3qwaUBoGwQF2/fXRNbuJ1OSzBFgTqESAAWI8rqSKAAAIIINC3wCh02Nc9+Yx512U/NhpJZRcbpFT5B7HEAnUnL/mROe+tB2X3jisblCzT0S4bzHv++efNGZde3+UmKzuKJx9ctI6poNxHvnqL+cp7jsjusWeP8b3uu8ssc0FuRF2+3aoa5ZYqs698+XUzO/c4XL/h2fzqic8apanyn3D43Il1Rd/E6hnqNNbRSS0bQC5av/x+qpMCmDq/NZVZ9R9G0D5fLj4XE0h9n7SdQEcxS/ZqpsAo/PZpphylQiAtQAAwbcQeCCCAAAIIZAKD6qDnuUNBiPx+g/78aCf499vnXTPpPm6pIFbV5YwF6m5e/ag59hPXZMGh8088OPnUWLdsRTvasQCkgnzvPWZeV5BFwcIzckFTN9/YKJ5YsEppqL4aAZQaoZYP/unYfLul0igaZEiVWXnHFt0r8FNvO8i8/f8si+2Wlf+JZ56L7pPf2M9ovTKd1NS1wxdAXrDHS8xpR+yVBXOqDNANMq+8N5/7F0h9n1Lb+y8BKSAwGIGm/vYZTO3JBYF6BAgA1uNKqggggAACLRPwdZrzI6ZaVuVodRTQOOPyGyYF/+xBsSCW3aeq11SgTvnkg1tF8p65RXwE466zZmTBthvuXZul70tTIyNPWvJi4ErnyydPOMi8r/Pk22U/X+vbfWKd6qSgj4Kbeq9OvT7rvwPnbJsF+iZ2zr3R/uo4/e3i+dnTc9177SmYdvqivTrBtB/ljnrxo9tuVY1yU5lVd6WdXxRE03crtJzbqcMf/8bu2VN9Q2m4x8pVgTN3RKrdricmb3zuBftxIig8saLgG18wLxYMTV07QgFk1WHZPTdkparqWjPIvApysltJgdj3SedJ7FwsmRW7I4AAAgi0TIAAYMsalOoggAACCFQvEOo09xJUqr50w0lRgakiQaxBdEaLjnhxg1spNbX5Bd+5I7jbonk7mnO/cZs3qBU6SPnnp0uH9lXwUdNa3aCZDQKd88b5ZvFF14UOzYKFKv+Hr7plUoBWwcB/+ubtwWO1wQYQ9b6KUW6xQOIJh+9mzvz3F4Ncyi+/7LbDVtmqUBr5/fX5tIV7mjs756cb+NR6Bf8UHLQjMns5N1PBPOXjLkWuHbERrDatqq41g8zLlp3XagVC3wV7fag2N1JDAAEEEGiTAAHANrUmdUEAAQQQqEUg1mkuE1SqpXBDSlRBotRSNDCXSie1PTYiJn+sG9zKb3M/x9pc+z3x9LNmeeeBG2UX38i0fBpH77NjFnx0g3/axwaBlpxymFmw5/beAKwdAaRpwPnjbT6aJhxbfO2mYJkbMFNgS0by1P6zt9ncnN0Z2ejmaQMSCiKGAokqZ2zZ5dejLJXPzBnTs5GAsf21bfPpm00K/tlj5K/yunWx21KvRYJ5+TRi55GsVP8i3yWla/fvpey2XIPMy+bJa/UCoe9T9Tn1n2L+WqHrtYKYLAgggAACgxcgADh4c3JEAAEEEBgxgVSnWdv76ZSPGEdWXF+QyK2HRloNyiQ0IsYtj32fKrfdL9XmvQT/bNqxV7mddew+5k2f/h/vbgoCnfiZH3qnuNqAmw5MlT80jdgGEL2Zd1aqM68A4ke+ckvXNGRNLc6PuFNZ8/dA1Dnhnhex4O0Re+9g/r7kKEuVX1N9Y0uv39ciwTy3bipDqh2+deuDZr/OA1mKLr2W3aZf9PzX/jYvAjhWr3mv+e9T00pYdsRs08pPeRBAAIG2CUxtW4WoDwIIIIAAAlULpDrNdrs6yhrRoydr6lWf27rYwI2vfgoGffaUw32baltnR8Rc/b4js3vk+TJKBbfcY2ybuuuqeq/Re75F6+X20a/+zLd5Yp1vFKECh3pysBy0pMp/zvHzs3vgTSTaeeMGEN319r0685qWrOnH+VGE+eCfPUZl1T0Q9SAWHas03EXBW90XUeV3F42C1DYFEYsutvypuqe2h/JLBfN821N5/eM3V2Qu+s4UWVLppdKIfW/zxyov2+Zqv1g75o/lMwL69+/sK26c9B3Wd1rrWRBAAAEEBi9AAHDw5uSIAAIIIDBiArFOsw0qjVtH2Y66U/3dRUGspR84eiIQ5W4bxPu9d55pLjv91aWDW/myxdr8VZ2HcMSWf/iD+dkUXd8+8vrsyYd5y/fZkw7NOsb54Jovnfw6BdrufGj9xOpY+VWG0N2rlgAAQABJREFUg3bbLgsYXv3+o8zlpy8wenUDiBMJ/fpNqDOf3y/22dfx1/cmeyhKp/x2ke/R++7UCaQ/YlclXz/+5gMmyh+ru0Y+agkF57U+FMRPBd90j8F88D9WFrdSCqCmgoD2WuMeV/Z96HubT0d5qewEcPIyfC4qUGTEbNG02A8BBBBAoBqBKZ0fOu0dnlCNEanUILB69Wozd+7cLOVVq1aZOXPm1JALSSKAAALVCShQke8Mq5N8/okHm1kzpk16YIPNWfsosNLmxd7HTAGS/BTIYda733L52tzWxzflVdtse/uO1Si3047YKzNScMW9h57cVF6NtOp1UXBLwU87CtBXBnvO2n2K5tVv2dx8FGxUffUTNP+gE3e/Mu9tmvYYX93tNr36HHzHuG22145bmdMv/fGkEU1KL38+uOn70tUxvuXiUw83zzz7nLn4unu67vHopuc7rpd1atM7H14/KS+dRxohuvUWm5njPvnfwaTz5sEdExt0HrjfBX03FKhkGW0BBcPtE9B9NdEfHhbN6/4Dkm+/Jq3jXB1Ma+BcjzP973pcRy1VAoCj1mItKS8XoJY0JNVAYAwFfEGlVHCkqo7yGHIPvcrqiJzwbz/w3nNPQTQFd+ziC9KEgiy+fVMd5v12mWluf3DTKD+br/uqdPMBZ9856x6j96kOV6ps+fRin23HP/W9iaXhblPA6ivvOcJdNfFeoyL//Es3T5qyrB1cK9U/FYzU/n+7eH72dGV3anI++Gczd9PXOtVX9/zTtN/QYm3s/ppWPIjA+k2r1k26r6NcY6NR//Xth5rfnb/LRFVS59DEjs4bX3BUbvrDStkgtZMsbxsgkPp+j9q/i5yrgzmpcK7Pmf53fbajlDJTgEeptSgrAggggMDQBTRySaMW3JFuvnt/uQVNbXf35X2zBDQyyXfPPZXSDf5p6rMvaKHRTFdev6prNJeO9U2HTU0x/ee3HTxp6rDSchelq463u/jOWXe76qHgV+w+b6myKb3UFFabp02rqu+FRqsFl85IslAQy7WKTVe0aWv/D191SxZgVfBCwTqN2Avd/9BNX2moHV67/6aAmU3XfXWnEevcyV9r3H2req/A3QVX3zHJKeRm8734+3fbtz3dK1D55kdVK0G5cY+4CdqRfaPzV8Fc36L17r+hvn2atI5zdTCtgfNgnMllvAUIAI53+1N7BBBAAIEKBGxAI5RUanvoONYPX6BokGrZz9d6gxaxwFI+QKQppvmHYVgBdZjnde5vqCCjRmbFllCZ1blScNC9T13RDlesM6+yqHy696MCY5eddnj0Hoi247/LrBmxahTapnx1P8PQErKw+9vt+aCp3Z5/tW1mg6pFnjjsphFzVABVgdhBP2wjdo66Zc+/z+472Tmfip5D+eNj+Vrn/DF8Hh2B0P0m9Z3VdWyUFs7VwbQWzoNxJpfxFiAAON7tT+0RQAABBCoQiHXq1dmxAY8KsiKJAQuUCd76ghY2wBQqtt2uUXi6v5xvtKHbYda0yPPeelAouWy9r8yhUX4a5aVy+xa3PqHOvIKRV7174cQDOHSuH7nPTsEHnbgd/zJ3efvoG145KTjquvjKr3U+C3dfbVcAyx3N5m73vbdtpm1F0nfTCDn6phHLfxAj4dz6uGUt8l7H9tppT+Wb2l6kfOwzXAFdr3RLAjtiVq+xhw0Nt7Th3FPnYmp7OGW2uAIpx9R2Ny3eI4CAX2CafzVrEUAAAQQQQKCogO3U56ezFQlQFM2D/YYjYIO7oSBZvlTqoLgB3yIBotAIKqWtqcX5e/rFyuQLOIfSV51C01dtvdz62M68Rstpvepm66o8FAiy61VGldu370Taj22wb6OvqtOpC/fI/oul50ukiJXS9AVefelpndumRdLPp5N31LRfjfzzLTYIa519+/S7btc+RmLq2BvuXRstgnsOuTu6ju56+z613e7Ha/oensM20vlb5zlcd/1S52Jqe93la0v6KcfU9rY4UA8E6hQgAFinLmkjgAACCAxVwBeUULCujiXfqdcP1VHu8NRhNIw0+z0HQsHdUF3uX/dUFvRSYEjHFgkQ6QEMoQCjphbrQRZ7d6b/2iVUJl/AWfVX2qH0U/d583W48p15jS4MBb/z+9o66NWXtrtd7/N1CqUXauciVgpQFV3yAdYi6YfStnXRlOzYEgqgxY4ps+2FxM4KQus8zC+L5u1ozv3GbcFzy+4fauci3w2bBq9hgdj3T/8usfQvwLnav2GRFHAuosQ+CPQnwFOA+/Pj6B4FeApRj3AchgAChQXoFBWmavSOocBOkUKXOQeK5KORYveve9JcuPQub0DELZMNXKkDHivHrBnTzOKLrpv0AAY3LU2zvez0V3ufihobEefL10039V75arqxOmUKdPkWuYWenqvA0Xt/e+8s0OdLI3aszVtBstTiq6frb48PWd103zqz+NPX2d2Cr6rPZ08+zNsOOiiUfjDBX2/QcXoAS2jRtMkiDqHjU+tTT3j+17cfkj3Ixg0iy3fjc8+b79/5y2jy2i8/gtU9oGjbucfwfpNA7DuUst+UCu+KCHCuFlHqfx+c+zcMpUD/OyQzXusJAI5XezemtlyAGtMUFASBVgq0vVOk+uWnW4YCNMNo4KrK109HoMw5UCYf7fun//eGZOBD7nt1Amf/6/f2N0fvs6OZOnWqN0CUCv7Y9ivbmY/V36ZZ9FV5+55wrOPLlN+XRhl7X3lj9SxiFjvezU8PZ/nimb/lrqrsfawMRerQb0FSbWgDkNrPTvFWnrGgpbbHzhttdxc37TqDnW6ebXhftO3aUNem1IFzdTAtgXP1zvS/qzcdxRSZAjyKrUaZEUAAAQSiAkVuSh/qZKoz3uTgWr8BkyhcBRurKp/aIT+tVMXTKKQzLr3evPeYecGRZdqv6DmgfN7z+eWdJ+M+osMmFuWj9Zd3Rt7ZxZYpNerJ7n935554Gh2nUYAfecP+5lVztjNH7L3jxGg6pZe6f5pNS+XRVOGD5oafeGv31Wus/u5+Rd4rb7VFfiRX2fL70igydV75hL6TsXqq3OpEhr7rRZ1sIKuIld0nVma7j33tZxqxTaOf16LT7uRoLVPTlj/+5gPMCYfvVrhYbtqFD2LHLCAbY6h7+ngs77Zu41wdTMvGnMtcXwdTWnJBYHQECACOTltRUgQQQACBggKpe3qFOkVVBa8KFrP0bvrRGwqK+YIrpTPo84AqyxcL7OiBDSctWZaV1gZn8ve6KnoO3NUJEOWDf5ZB690AUqxM9hjfq86r93/x5q7y6oOvLX3H23Uf+cot5qo/XRgMhtn99Jqqv7tvkff5YJrvu5JKJ5+Gu3+os+fLx23zVD1D33Wbd+r4f/iD+ebEBbvb3Qu9psrsS6RIINR3XBXreglAhu7rZ8tz6O7b27e81iiQaofU9hqLRtII1CLQy/W1loKQKAIjKjB1RMtNsRFAAAEEEAgKpDo9vu2p4FUwswFuiAWgbHBlgMWZlFWV5UsFZmzmqrcCaflll8STTe05cMN9v8of2vXZHaFXtExdCeQ+qLxndcpbNvinZPTAjhM+88Ns6qUCoJqCqRGG6hDll36e7JpPy3629Q99V+x+sVebRmwfuy2Uj9vmqXradrZp5l9T27984/1e33w69nORMtt9fa8KhC6aN3tipJ1vnzrW2QCkpvtefvoCo1eN+MwH1m3edtSg/ey+KkCrerDUL0A71G9MDs0RiF1fz/rC8uwPdhqdrD/caV8WBBCYLEAAcLIJaxBAAAEERlygl05RlcGruvhSwZPQdv0Q1g/iqn8Y59PVAzJiS6h8vmNSgRn3GAWErrz+vq4f/f5HVrhHlX9fpkyx1L/XKa/K3MuSfxqrDYbl2/f5Gjo/tv6x70qqThufe6FwxyyWj+qddfJSGSa2x64VOlTevgBzKNkiZQ4d24T1RQOQdtSggn3uYkdnuut4X58A7VCfLSk3TyB2ff3eHY8U+uNY82pFiRAYrABTgAfrTW4IIIAAAgMQsJ2i/CirWOc0FZzS9mGParEBmBChb3uR6TIK5OmHteqoNBQUkWFs8aWrp6TGFqVdNC8bmCkaKPvgf/40y9q28QOPbYgVJaur2vOQ3V4S3c+dyhgrk7SGNd5ARktXbHqKrAyO2menaL1CG1+y1XTzqycnjyhUmvb8T31XQmlrvUYsZm10wkFmzePPRM+5VD7fuvVBs8PWm8eym2jn0E72WqH7SmpquW+xwUZbf98+dl2qzNpeJB2b3qBeY9/L0DY7alCBWNVL3+8m1m1QhsPKh3YYljz5DlogdX11y6Prtn4D5u9d6+7DewTGUYAA4Di2OnVGAAEExkBg1oxp5kOdJ7D+7vy1WW0V6Jm388xgzX3BM3fn1HZ337rexwJQboDG5q+Oez4Iqm3uD2NfIC8L0Jx4cHD6XyhdjZbavhOQWfvEM7YIE69Kc/bMLbIAkPK3SygvG5jxld8e63u1dVPbxxbbngpYHLH3Dt6n+mq9DWjYIMhbD5trlnemDT/61LNdyVcZ/NMTZ0PBqK5MAx9kcP+6pwJbN63ed+dtzIqHHp9YceCcbc3/8zv7mSXfv7trhKJtI+0oB43i62dR+V5z3jVd54nNw51yatsolNc/fnNFaNPEejviMBbQVp56qIy9r+TEwc6booG7VJlT250ss7f2vLMBtiLB+Xwa7mdfeo9teHbSdcK2h47NfwftNttW+o7Y74mbF+8HK0A7DNab3AYr0Mu/Pfq3Rn+g4Po02LYit2YLEABsdvtQOgQQQACBHgR6CWqVDa6VLZav4x0LSih93zHndwJzoQ55vkyx6TL6YbzyofXm779xW1ewR2lom/II/eU8lq6Cf/kAVhYw6Iz4ypc7lZc7skXTiy9celc2JTNfz/xnlf+vX/9CNtJM7/OLymM7BGqDi/740Ells0EOHes7n/JpVvXZ5uuzKpOHG9gLHZffR/cYfPuSH2VuetjI+g0bu0Z1VemQDxL7zrnYdzJUp/x6jTjU+fiZkw8z220VHi2YCsylttt8d9xm82AQXAFWLfpep7772s/nbc8PG3zTfkWXUHobn3t+UgBc7aF7aqmc+e+Qr62KloH9EEAAgbICvmtX0TSK/vGmaHrsh8CoCxAAHPUWpPwIIIAAAl0C6lz7giepTqs6umWCa12ZJj74frymOvKxYxSYKzLtLjVdRiPZ8p17WxWtd/9y7gYj9eTc2KLRVLt0Rvt982cPmnWdB1Qs3Hu2ebgzJTeW102r1pmD5m7nTVbBOo0e3Hyz+LRk9+AHO/kVbU830GhHWtkAYeh8cvPq9f3hu29nrr933cThR++zY1ZmjV496Td2D3pNHFDTG7XTE08/a678k9+cCFTV6WCrkT/nQt9Ju3/RV42mXPSPSzsPt3i1sUG4/JT3WLBR31V7PsTylNH7rrypa2Sju78CrHpwS+q7r2NC3jKKBefd/Nz3sfTc/dz3uqdWaMm3VWg/1iOAAAL9CISuXUXTLPrHm6LpsR8Coy5AAHDUW5DyI4AAAgh0CcRGp6U6rbFAkDLRD9F84CA1kif049V25DVV1Qad7PS+1DEKACogkQpK9PvD1/7l3BeM7ELPfZDJCZ/90UQgZMn37zEzO0Gt2PKRr9xivvKeI7y7WI/v3/lL73bfymeefd6sWf+0Oe2IPc1Jv7mHmdZ57NlLt9sqauaa2rbWU4DVVlUvml48fbPuZ7HJ7bHOqDtfALvq/FPpKWimJw5/tjNyTt+L2PcqlVaZ7facs8e430nd8y827ffPX7uPOe9bd9hDu17Xd6a5Lr7oumy6t5yvXbkpuKWg4DnHzzfna5RqJ4DntrcN1nUlFvhQ1Mh+90MjbJV8LC0d7wbnA8XpWh1Lr2vHEh/ybVXiUHZFAAEECgmkrl1LTjnM/PsP7+26btuEi/7xxu7PKwLjIBD/NT4OAtQRAQQQQKBVAuqUxpYinVY3EGTT8gXBbHBAQYrQEvvxqo58/uENGrWmwJUbhHDTLtP5T41qch9w4eZh3yuAaINvofLYfe3r4XtsZ/7sCzdOBP/segVgYotGR3339oez0VH5oGrMMJTmp76z0ihNu9i2sp9jr762ju2f2qYAk1sWjfTTbfTypvr8xguvm2SXSt+3PT8N27dPap19Aq4CVanvVSqtottt0NoGYJWv1ulcfu3+u0QDgDt1RommFl8QWW2z+NPXTYzM0/fP5psKsrv5lTFKfY9TaWl7XWVz6xR7b9sqtk9om69989/70LGsRwCB8RFIXQs37/x1r+ho//FRo6YIhAUIAIZt2IIAAgggMIICqU6pu71oJzQUBFMnPjUdL/Xj1SVWerrv1usO2NVdPem97fw///zzRtP0bn/wMbPfLrOMAktTp24aVaYOdeyHsaaaLpq3Y9doKJuZ1ivAoJFGKlfRZcEeO5jr79k0rbXocdpv4gmxuQeQlDG0+bkBN60r0lbaL9TW2tbrct5bD8oOVT3s+aepoL4lf2883z6pdQp2frIzmu1dl/24r4eJKB+56Ryw5U7lXWR77EExOud8AVhbJ736zketTz3ROVU29xwpE1yz6ZY1st9je7z7mkortd1NS+/L7q9jdD3RNSTk3YuR0g21r65VsT+m6FgWBMZZoOhvljYZpa5d2u6OFLf/zvZ6fWqTHXVBwCdAANCnwjoEEEAAgZEVSI16sz8Ky3RCYyPQbIDEppuHS/14ze+vgF7s3lvaX2mu+tWTk0aLaZrtv7z9ULPw5TtM3Lst9sNYnQn951vs+rLBtw3PPudLrvA6NwhjDypraI/Lv6baSvvH2jqfXpHPCqLYc8O+XruyeEC1SB75fc46dp/sgRd68MVv5562m9+3yGedA0fsvWM2Qs4XDCqShvbJptq+cb7Zc8etJ01zVgBPASCdd74p0MpX99cLBbTPOmYfo+na/S5FzpFQHrFrj++Y2HkdS0tW9lzypetbF0vPt7/a6oK3HZJtyreHbSvfcal1sfZN/TEllTbbEWizQJnfLG1yiF278tdCXRfLXhvbZEVdECgisGmYQJG92QcBBBBAAIGGC9hRb/ph6C5upzXVCXWP0/tUECy23f54zafZ62fVY68dt5oU/FN6mmb79v/zo2wknToL7qIfxYvmbQocyEDBDt+USB2n9WVHfqlseuBHbJnXKUdqsUEYu18Zw9S9BmNtpfxS222ZNIrNXXRPv9/ca3t3VfZeU33zbREL/ExKoIcVup+iFj31dukHjjYL9pxcrjLJqryh71UsHQWRLj71cHPZaYebq99/VHaPRz3oxQalte7y0xdk2zTNWOtjAVidF5qeq33tsXpasRZN4f3LL79Y71iZimwreg7k07JGqndq0Xcl1lG1aWk/d9FnBUHLLqH0Qulo1KraI9ZWoWNj61Ptq2sOCwIIdAuU/c3SffRofwpdu3q9Fo62BqVHoH8BRgD2b0gKCCCAAAINE7CdVnUm1ZlXAMPtbBfphLr7pwI2se32x2t+FE0vZLqvm6Z2aoRgbKqoAiWx0TS+kQS+8siuzMivjc89bw6Zu60JTfGc3nmK78qCHfz71z2Z3fdNbaVyaFSbOkGp0ZGpew3G2koGqe3aR+3wxTN/KwuQ2vNLQUpNYc4vetjEGZdeb/RkZKWt/WxAU+1Ux6Lpzzr3dQ7ru/DFztN8//k7d5jzvr0ymN0enaDyPY88OWm7G6iy36srr7/PfPA/fzpp3/wKlcOd1p3frvK53zO1b2oUn7ztcda8asci50C+LvazjBQ8C03x1n46f4oE8ax36Dpm8yz66qan79eF373TO0XcbXObtjW3n3t9VfvFFtu+sX3YNr4CukbYfxPs9VT/xrZ9KfubpW0e7rXL/pvr/tvRtvpSHwTqFCAAWKcuaSOAAAIIDFUg1Gkt2wmNBWx8neV8pSf9eJ01w5z7jdu899bKH+t+1pNZNQ3ygDnbuau97xUUsUEgd4fQSAJ3H/teHazHOqMKFdgrsmjU4Pu+eHNnpNfCSSMUFfzbqOFwBZcLrl5pzv/2HWb5qu4HeVz17oXmf+5+JPowCI3Ayt8DUNnm28rXmYy1tS262mHlQ+snpllrvaxDgSjtf9KSZdnhKoOCP5qyGtrf5tPPaz6QckRnZGYsAHj+CQebC66+o6tMtqz5cqQeHpPfX/WMBaS1f9GgtBuci3WK82Uo+jl/jhQ9zt0vdg5pNKYCsmWW/HXMd96WCYLY9A6c+5JJ061DbV6mvLF93fbz7Zfa7juGdeMh4LtG2PNV/8a2eSn7m6WtFvbala9fv9fEfHp8RqDNAgQA29y61A0BBBBAwCuQ6mTmt4dG8dnOhzcTz0r3x6vvXmaeQyatUjDlkc40yCJLPgikY4oGTXTvus6QO3Pykh95g2mh/FW+pzc+b5b/zXHZU331gJJtZ0w3H7qq3PTMG+6b/CARGzD70O/tHw0A/vGrd+sU776ucufbKtaZVNuk6v2BL93clX6RaZ8ys8Gw047YM0SYrf+HP5hvXrrdlp1A8e1mxYPro/v6NrrnsDpHn/puePTf/JfOMttsMS2bruuOrtH56ltiAS7f/lqnevsC0tqm8hUZIas2dMuU6hQr7bKLRpr2u1R1vfCVI3belg2CTPrDRG6ktC//ftfFzp18+/abF8e3RyB0jdB1RddqjbrVuVUmEF5UpwnBJfd67it3arvvmLasq/Ka2BYT6oFATGBK56JW/M/xsZTYhkAJgdWrV5u5c+dmR6xatcrMmTOnxNHsigACCPQnoKfnHnbud7zTaDV9VcGr0FLVdDybvk1vl86owL8vMSpw6y02M088HX/ghu6T5gZMlKceQGFHo9ky5F91Pzt1pDR9tZdF93XT/QbtUiRPu2+R16vfd6T52NdvTU4HVloKzJ3TefCE7j1nF/300dRUG1C06/WqIITuMad2iU3jdI/p5b3ujeebMmzT0kixz3Ye4vHzR54wiy+6zq4u9GrrYHcuWhcdp+BnkUCSr9MVGnlpy2HPi3yHWp+P++R/2928r76yper1hlftYv7rJw960wuttGUMbS+73n6/1UHPfxfLplXkvC2b5jD29507vvYdRtnIs5kCqe+6Sl3HOdSUc7UN3/38db+KgG0bXAb5jaP/PUjt5ubFCMDmtg0lQwABBBCoSeDuzr3OQvfQ03p1NkKdda0PbeuluG56ZUYFpoJ/6gzpB7YbgNDn1EiBJaccZv79h/d6g2NF65fPY9dOcLPK5YHHNpizj9u3UABQU4E1tVVBPbvERkHakWqykqEvSGjT6ed1WucxbLH0l/18bTYqToHC2H75Mmjf8zv3iXTbXfd7K7KorqmpujYd3+gxbYsFTXVe+DrUqdGTH3/zAeaEwzWqs3tRG2mkaui+kA+tf6b7gAKf8udugUOiu7jfb+3o6wRrvTvyUvXyjWQqct5WeW1SuepYfOfOKJS7DgvSLCZQZLRvmetXkVz1XfWNTK46nyJl6WdUse+a47u+FClHr/v4rvvZv1UF/+AUyrct18RQ/ViPQB0CBADrUCVNBBBAAIFGC6Q6E76ps4OokNsx/v9uecCc9607espWo8fOeeMrJ41y0w9uPURk0bwdvaP7tH73HbbuK+ilPNzOvH74a7RelYvuJfjYU8WDO+qw2Xv2qW3vX5d+EIGCMJoOqoCwez/BfXfexqx4qP8nlb50u62y0XZ6QIjuEehbVG51cIoGhi/uBG+333oLc/LFy7rKfEBnim/RRXnGAuD5dNwAlzqaan+lkV+0Xqa+kZeub/44fQ7dc1Cd2FggWEHUeZ08V3YMiyz5c7fIMWX28XWC9Z2Tm/s0bpXDNxKzqdetMgbuvu65467nPQJ5gaKB+bLXr3w+7uemBZfc3we6FsjE/bfWLbt977vmhK4v9piqX+sMpLbtmli1Pekh4BPo/P2ZBQEEEEAAgfESSHUmfNv1I1aBEU1n1as+17XoR31qVFQsbwU+Fl/0P5MCMeoc6SEimgLtW1Sn1A9q97i9Ok+OdRfbsbDr7A//0Agtu1/ZVwWR9ATTMovu2afRaZr+nHqC7cwtpmeBKk29tcEp3SfvlZ3/qgj+2UCTOnR6OnBsUXvYjp9GwsWW8zsjHRd/elOZ7b4/vf8x+7bQa+ocCH0X7CgV1c9d7HkR61C7+7vvrZW7zn2/fsNG9+Ok93/8m3tMWudbYcvo21bFOvtdyAdHNc3eDf4pL+2jkUf5xXddcvdJbXf35T0CoySgPx7kryuh8qeuX6Hj8utT6aS259Or6rN+H+gWG6ngX+iaE7q+VFW+fDqx677Kot9TvS6pa15qe6/5chwCoyzACMBRbj3KjgACCCDQk4DtTOQ740rMF3AYxl/RNUKsnyU0xdlXZ5uPAhGnHbGX/Zh8/czJh2f7qCOkH9puh0SdD+UVyy+ZQWQHjZrT/RpD9cwfagN5+fX5zy/Zarq54DvdT8PVPreUDKLl03U/v/mQOVkAWQGzVAdFox0VdNZ+h+z2EjeZSe9/8otygb5JCfx6RaxMqe+CDVaqU5c/L36yevKDXdwy5O8hGArK6dxSp1Lpp54sfcTLdzAL9nhJcJSl8v/z4+aZ1x3wUjNrRn0/i2OdYNfAvtf3Robudyp23bJ/MJDNoKf32TLr1W0bnUcq8zDL45aN96MrYP+44JuSm69V7PqV3zf2OZVOanss7UFsi11zfNeXusqUCpRqu3udK1OO2DXR91uuTNrsi0BbBer7pdNWMeqFAAIIIDDyAqHOhC/goA6tr9OhH9Ba795brihMkU5y7Idt0Xx62W+zKS8YTSHWKMLYooCD/dFuX+3+viCR3Vblq4J/2245rXNfuWcrS/ZXT26sLWhpC/meL9xo/nP56myaZ6ydFeB0HxRydGdk3SFztzXLVz1qk6r8NdZpKvNd0DmRPy9SHWY9yVNLPnDoVtJ3boUCwVlddp5pPtN5mMpvn3dNMFh83rdXGv1nv/8KYvaz+L7fqU6wL78b7l3bFUALXbd0rALcGuFaVR185YmtU51v7pyXH/nqLROjZrX/sMoTK2u/23ztS5CzX9X08faPC7qdQ/4p7Pbo7DvfufZUscSuzVXmU0VZfWmkrjn9BN58+YXWpa77qe2hdLU+dE20153YsWxDYFwFeArwuLb8kOvNU4iG3ABkjwACEwK+kUoTGztvtD32YAPfk3bd4/PvFcA46wvLux5coAcZXPC2QyY9fdUX7MinV/XnQzujzG64z39POjevq/50YdeTde02TS8+8bM/SgYQ7f7j/KpOigLIvnYOBbV8Xnt2pmL/vPNgm34X22kKBcD6/S4ocOK7B6DKbS1idYgdn/fK10XGZ1z24+R5WaQcsTL62lJp6n6SZZ/mbF189wNMBUF6+cNErF6xbapz/prm7t+vqZvWsN+H2tfXRsMua5vzH1Q7DCqfKtoqH5juDMc1x0aerl72t0uvZYxdt6u8NqR+y/Va/jYdR/+7Ta3Ze10IAPZux5F9CHAB6gOPQxFAYKACmn6p+8aFlstPX5Ddjye03V2vH8InLfnRpHt+aZ8j9t7B/Ps7f8PdfeK9ftjqSa6f/PYd5sYaR3/N3GIzs/7p5ybyDb1RsGX53xw3abM6S7GHWkw6gBXm3MXzzdsWzDVTp07Ngs0alaFpre7Iv7qZNJrzf//hgdloCuWvERka/ZIf1VTFdyHUoT7rmH06597GYN4ySAUgZTl3+y2Nps/nRx9aQ6WhkXWx+0D22jGOdXQV5JdnL1PifZ3klMW333ekmdcZ/Vj3Equzm3evpm4aw34fq6uvjYZd3nHIX98De80KfeercBhUPr2W1Xdd1TWn80+J94Ffgz5ffeVTGQic99rivR1H/7s3t7YdxRTgtrUo9UEAAQQQqFQgNT0ltd0tjDoR+Rv+2+1ar+0KvNj7m9lAjO3YlA3+5UdFpUb3FQn+qbyaevvd2x/ORm3ZIJE6x5oSHXqira0nr90CH7rqls700zvMV96zMAtaqa0VaBvUok7Y33YCZx/ulMMNTvk6Z6lzPbVddbLT+GyHeuaMzj0Xf/3wEltnX97apo5+bJGlPTa0n3xT6Wi773toz3Vf2jr/5ecauvvpQThXvXthtsrdx/cUYPc4vdf+8rLXAa1L1UFTJC87/dWTRhXr2CqX2H3G3HxUXrf87rZReR+rq6+NRqVeo1xOnVODOK8GlU8vbWH/7XWvK0pH1xz9YVHXRHdb6hrZSxlSx+Sv+/q3YhDtlioX2xEYRwECgOPY6tQZAQQQQKCwQJX3AVqemFr7/U7g59yv39r1Y1334/vsSYcmO/z5CimwcOEfHWLWrH86O3bXWTPMud+4Lb9bz581Qs12JPTjPtY57jmTMTlQAdXf/9S15qYPvzYbJVYkkFaEZr+dtzEr1zxunvM/9DlL4q9f/4pJwT9tUIcxf4/LXr4L6pzmA9oKpKnzp/R8U4J9eatMRVxCx+p4u6TSUXn/+Tsru4LZ7rlu07GvvtEtdpv7qhGOmpprg59uJ/iKZfeav/zyLe7uXe/zAbRUHXRPQNt+XW3QuQ7o+eUPPrYhOtqyK/PIh1Qg0h6aKq/dr8mvqbrm2yhWl642CYy4jR3PNgSsQOzfXv1hUaNvP/R78Xur2rTqfm1yILXuupM+Ak0RIADYlJagHAgggAACjRRQsELTVNSZrvuv6F+4fpVZ8eD6Lgc9jOM1nQcYXHzKi0/c7doY+fBwp4Ov4J+CLPrRraCDW/7IoYU3ucGWVOe4cKIN2/H9x+5tPnH1nbWXSg8yOf7C6zrTwF+dtVmRB7GkCjWrE5iNBf90vILSofNC692RZ2W/C77AmBtIi3Vc83mrrLEApLbbxXes3abXVDof/erP3N2z90rTBtTcjaHRN+4+9r0Ngvk6wTvN2tLu5n3NP+04VQclojLfdN8671OtbSZue9h1ZV5tnWLHKA/VeZhLkYBbap9UXVPbbf1T3wu7X7+vqfr0mz7HN0Mg9W+vti+aN/zvYDO0KAUCCBAA5BxAAAEEEEAgIVDV9BVNwY0t+eCf3VcjxP7+G7ca3dNH03qKLCseevHhJbaDn+okFEnTt4+CDFdef5+ZPXOGb3Oj151+xB5mXicw8eUb7/c+HELTp75z++Cm4/70F5tGbZ22cA9vmcqAVjEdW+eNG7wp+l0IBcbcQFrqnMznHQpA+kzyx7r7lEnHPU5ldwOi2hYLYrrHpoJg06a6e09+P32zKV0rVQdN3X79Bdea9RvCT8H+yy//xNye+6OCm5DbHu76ou9TgUh7/SmaXh37FQm4FdknVtdU+9p6Ffle2H37eS1Sn37S59jmCKQCz6ntzakJJUEAgUEIJH5uDKII5IEAAggggMBoCCgQ0stf0tXpU+Dg/k4w5dDdtvNWdv5LZ3nX25UK5uhJotttNd2uKvRqO/h1dgL0QAVN5dQ9B0dpWfL9e7JplxplmS+7fWiDplIOctkUZKr/AQ4L9nhJ53yMB6W32WJadu7qvoQ6h3Uua0l9F2KBMVvH1Dnp224DkBefGh8R6x5rv39uHWw6mh738TcfULiJ80FLPZwntRQJgs2aEf/uuPVRfqqT7tsYC/5pv1jwT9u12PZ48VO5/9tgquroLnqwjJ4UrinPsh7WIqf86G2VxV4X9b7IPtovVNci7avjtRT5Xry4Z+//L1qf3nMY3SNlo+uYey0Y3dq8WHIbmPbVo2hg2ncs6xBAoJ0CjABsZ7tGa/XRj37UnHPOOdF98hs/8pGPGB3HggACCCBQTsA3EiOfgu7X9+fH7WsWf/q6/KauzysefMyse3Jj17oiH9TZ/evXv2AU8KliVFgoT41UzD94JLRvXesVIO3FSGWXz3uPmTdxr7ljP3FN4WJqtKCW0ENeCifU2fHOh9eb33nlLpNu3l4mjSJTiHUufKxzz8lFe+9orr3TP7L09Et/nD30xeZtgx2poE4+UGaPt6/afkQnX6Wn8zO/hDqu6sAriKIRc6E6KvikRfs+1hkdlw8AuXVQIDNVVrds+UDcs5H7K+o4PZn4j39jdzeJSe9Vzgu+c8ek9XaFzyIWSLLHlXmVgQIJSlfvVU99VtArtdhgqgIr9lh31Gjq+Dq3x5zcwKfvHFS57D62Pv3WNXWuabvNq1eXInXuN49eyzbM43z/FrvXgmGWrZ+8bWA6dJ3rJ22ORQCB9gkQAGxfm9ZSo3333beWdEkUAQQQaLOAOvb5H+W++k6bOsUcOHfbYEDDHvO5/7nXvi39qpv+n3bEXp0A4A2ljy1zgAJpS045zHyq8xCFQY+e0yzJXoJ/tn4KiOlea+qE3/XwE3Z19FXTiN+2YPfOFOgtzHs+vzy6b9GNn7325+Z35+/qvfdkkTQUjLyo8wCYs6+8yRtcc9PQlPJDAqNStZ/a010UENE5rZFdsSUfKMvvq+1lO67rnnzGvOuyH3cFsTU1Nn9/PJ13Ct4qQDi9Eyi87q61Xdnn65Aqqz3YF4hLTd3dbYet7OHB11jARgdp5G9+SQWS8vunPs/cYvqkB7KUDY4oqKT/dN1zg4FFA4mpMvayPeWkEZwPPLohmrQvKGfrGj3QszF1rqW2e5KctCpVZ199JiXSshWhf4vz14JRrXa/gem66y3/Xv64UHe5SB+BcRQgADiGrf7ud7/bvOUtb4nW/LnnnjNHHnmkeeyxx8ysWbPM4sWLo/uzEQEEEGiqwDB/eKY69tZMnRDtq6f96oEf+aCL3a/IdD67b/61io5lPs3Q50cef9pcetoC86f/94ZJwZfQMVWs78Tuksvcl2xpVv3qqeB+mspcZtln55nZSCkdd+1K/yi6Mulp3xvu/ZX57u0PZ6Pj7FNjFajQaLMHO68Xfu8uc/+6cNBi+mZTzbZbbV44gLi886CIMovOVwV4YqOI7LQ07Ztf3EBa0Y7ro53g3297vhv54J+bl6Z2hxa3DrGy2uNtMMx+tq8v3S4e4CvyvUsFbNZvmDzqt0i6toypV0131wjEfFvpc5Fgr5t+00ZZpZwu/O6dXQFlty72fSoNu1+R19i55n4viqQV2idV3tT2ULqjvD72b7F7LRjlOqrsvQam66x3064JddaVtBEYBQHuATgKrVRxGXfaaSczf/786H/3339/FvxT1n/4h39ottwy/nS6iotIcggggEAlAvrhqcCMRgOdtGRZ9qrPWm9HqdR5L6BUx96tpPZV0GbpB442ByTuB+geV+S97VjuuM3mnftx1f+3P90TUCO1nnrmuSLFG8g+e3WmM2qJBf96KYjuobe0E6zLB096Scs9RuepPVc1uvCS6+7JPv/1VT+LBv+Uhu3Q2uCa7nP3F78zeRSZm1/Z9/bed6HvkR3dp3PPXUKBNHVcQ/fXVB5nXH5DMDDupl/mvf1+qqyfPOGgSfeBtGlpJGHoXnY2oGP3dV/t985d53ufCsj4tsfy9eURWqcynt25/UDo/LXnUuh4d73ayTfiWWlo/TCWmJNuV5C6JULRNixat7Lfi6LpuvvF6lx1fdx8m/zeftdDZUxtDx3H+rhAE68J8RKzFYH2C9TfC2i/YStreNlll03U6+STT554zxsEEEBgVARiPzw1Mk2jpNxOrzpG5594cKU3rPd13EN+dl8Fbf7idftlAcvQvq962Szzk188FtrctV73Q1O95PG+zpTQR58KPzG068A+P6Q61n0mX/rwuzsjLKtefmOv7c1H/+tnldz3z1c2N3Dinqu+ffPrbrh37cQ93BRcu2/ti/fFy+9nP+thH48/Xfzc0MipPWdvkz2Iwi2b+z2yAUh3Omhs1KAtS/5Vo3dio/ny+xf9bL9z2v+Rx58JBhiVd2jEow3o5ANf1qFIWWzAxnW0x4UCNjZo6RsVaY91X/P3t1TAQ/VXe+iPILFF+8baTdcWtZHOOV8dlLbWhwxjefe7LdQ+oftHuvmVaUP3uNT7qr4XoXxCda6rPqFyNGm9+133lSu13XcM69IC4zLyMi3BHgg0R4AAYHPaojEl0bTfr3zlK1l59txzT7No0aLGlI2CIIAAAkUFYj88fQ9qUAe17HQ3tyy2E2w71urUxzr27rH5Tn6qMzJ92mbmqncvNOuf3pjd/0wjxUKL7h/2k9Xrsv1CnfPQsawPC6jNnnrm2U7wLzzNNHx08S29tplGYX7zlgcngtqpe9Up+Jd/gEv+s1tqBXh//1Pfz0bTuut93yMFj2IBJPd43/s6Rufkv3OpPGJBsH4DOgrY/G3nYSFvvPC6riCk/LU+tMSClu4xNvCjctrFbY/U9Sa23Te9z+aRf40Z5vet8rOvfVQWjQoPLXoy9AmH7xbaXMn6fr8XsUL46uy2eezYNm6L/VucvxaMQv19vzd0HWna0s91tWl1oTwItEWAAGBbWrLCenzpS18yTz314v2RTjrppEJPgKswe5JCAAEEKhFI/fD0ZaLgRS+jVHydYNvp1ui7/OggN2+7n7tOnRU9IfX7gSez6h5xumfXxacebm7u3L9t5oxpZn3naaf5RQGEWHAwv38bP2sEZJUPI1F65731oGxE5XGf/O9Gk7nBuNS96lQR3XtS55QerKGgj6Yen6GHbgTupafz3rcoX93D0Kaj87mfzmksAOXLP7VO37mzjtknG/mmtFW+VB6p7cqz14COOvMfvuqWruCf0lN7aH3ogStFr3Ef+r39oyObew2OqNyxa5vq4C4hw0EEM5SHu+wya4b7cdL7Q3ffftK6UVzR6zk5inWNlblNoyJjvzfcIH/MY1DbQt95m39qu92PVwQQqE6AAGB1lq1Jiem/rWlKKoLAWAv0+sNSneoyIyVCnWA3+JJ/kMOa9S8+wOGQzv3j5nUeIuFbntjQ/fTV/D5K/63/9j/m+nv8D3BQ8CX0MJF8Wm37rKfavu+4fbKgjka2Lb7oukqqqODfOcfPzwJGX/zxqkrSrDsRnScKaseCPG4ZNFJQ3x3d4+++tU+aozoPiAgFAN3j8u/dwLMNcvfaOY2V3fcU4HxZ1G4aCau6zdpyc3PB1XeYxZ/edE6ofLoHoF7llV+0vsw1IX986nNstLJtP1/+Ra9xqWtaryMQY+XO1zlkOIhgRigPPS3bNxo8VNZ8nfg8WgJtGBVZ5PdGk1plrx23mjSy3JZPf6D0Xdfsdl4RQKAeAQKA9biObKr33HOPufbaa7PyL1y40Lz85S/vqS6rV6+OHvfAAw9Et7MRAQQQ6FcgFjSIpV20U23TiHWC3c67RlOd+/VbuwIMNqB04Nxtu0ZI3bzqUXPj6vQ9/kLBP5Ut9nRUW/a2vuqptmpHnQPvuCQ8zS9V/3133sb8zRv2N//0zRXZKEKNJFTgSAGCo/bdKXV4Y7bbAJBGo8ZG9KnAFy69q6eAX6yy+h70M70+NHpH93HTk7Nv6LT37Q8+ZvSQm4997TbzWG40rNpNAUm128bnnp8U9FH5dH9M32hdHaP1dS6pkXy2/fJlKHqNS13TFFSocwRiyHAQwYxYHovm7Tgp6Bsqa96ez6MroKDTqAaeiv7eaErr3P3Ik8E/ROoPlL3MuGhK3SgHAqMqQABwVFuupnJffvnl2bQmJX/KKaf0nMvcuXN7PpYDEUAAgSoEQkGDw3ffzlx/r3/UXC/5Fum8q6PumyrnBpQUZNAIBXVYP/LVW3opylgcM2P6VLNh4/PJuuqBBFq+d8cjyX3/f/a+BNyK4ky7ZBe5cFFkUTaRLQqCIMQIRoPLONEoM/5RJ4lEcUzyRw1xSTJ/dKImMRMzwSVxmcSAW4zBROMSHeMSNYILCEFBZdOwiSiKyEWU1b/evn6XOnVq6z7d5/Q556vnube7a/nqq7eqq6ve81WVLcL1Xxolrnjo1aIlxCCMmjwWmjaZlfAnAgjta8bXDhWn/upZ4+mnsMhIYu0XUiaVDA+Jr8cxWe+AVDe9V3paeoYONoewdU1bouW2mJTivQZu5SAKqH5sutnCbX2cKgeElq8MSUkFm16UP/bRw1JaW/5J8yX5IVdXHk8vfUfghOyLjxeJ6ht9NeRTW0E/jzphxwhkhUDIeMP2vmWlk0tutenrKguHMQK1ggATgLVSkymV47e//W0kqUOHDuKUU05JSSqLYQQYAUagMgiYSAMMSF2bvyM8zgDat5cUJsmuSSiQAfkw5c554pITDoxO0kxzz7rKIJ9drjd8ebTo03V38fs5K8W0mcudGfkmH53at5Yn3+4wysDyQDmbL7DYVCO+sOJ9AQvOpHWFZcpony5SSs0v6T2s5EBMkANBcdNXxxQRZzglNuuTmx95Za1Uo2ekT1KiBO8m/kC+wKovTfzo3ac8CLM0rybSyGXJ5yPwqI+bv2qDuPS+hQXtMdSazfeeEC46Dj69fYdoJM1X18P1jKXsLgcdDh/kJ0l1GbZlxfRDjh6fnxmBNBDwke6+8DR0iCPDp48vPE5eHJcRYATCEGACMAynisRKOjhWlb355pvFGWecoXpZ75977jmxZMmSKPykk04SXbp0scb1BaxatcoZBUuAx44d64zDgYwAI8AIpIVAnAl9nAEpJoE/kRZiNkeT96eX2i2PKC0s1Z686il65KsFAVrKOWXCICcBGLKJP8i/xo5txYbNhYdZYGngddL6D6cnu9yOnR8nJgHbyT0aTUtOQ/a0c+mkh8GiD5ipxASRRqqlG4gQFzGuy03y/DO5lBp/RExBj6TOR6onkRvy7psIvNDxmos0MrUFwimkLCP7NIr7zh0fLalDXaIs6PdCnK/ctnCUuxS9bXJJZ184xXNdt3uMhZNslYA2YLI8BRldylJ3Vzk4jBEAAj7SPfSdLxea1aZvuXDhfBiBSiLABGAl0c9Z3mke/tG7d++clY7VYQQYAUagGYG0BqS2SSDhrE7e05jIkly+NltM4kxPEHVYxqe7Yft0jg6waL3bxwIWcK5lrSD/Ljx2sJAmZdGpt4f036uFOPHV28I1G8WFxwwqsLrSdbE9P/eP94xLTte+/5H4yrTnbckS+duIiTjEOGWs44llw3EPm4E+k2QZcZoy3sdQAo10wNVnPabGDbknst4V10Xg+chMW3+h1g0dFhSXwFN1TlKnpfSJJjI5lIQoJV+1zK57HPziciDc4zoX+Yz65H3N4iLK8UMRKJV0D80nrXjVpm9a5WY5jECeEWACMMe18+qrdquSULV79eoVFHXr1q1ixowZUdwePXqIf/qnfwpKx5EYAUaAEag2BNIakLomgcDk4uMPiJZ44h4TXRtZhfB6dNPPGCMw+V6z4UPxvbsXxIbgSTnR/u2/j5UnuxYv0wUxB6s3cg0d2sg9+7bTY9F16iPN1u8ggYb27CJJxXWiV+cOYsfOndFy41XvfViUhjymPrqUbmNfsU8hETZEmsQhtob0bBCL1zYF5esjJtBGfUuaEX7X1z9TYGVm2ocvhBTE0umjpcUrCMXJ4/pLHBpikYE+ctYGCt5Dvc2oZL0tXQiBZ0sLf1d/odYNtQeXrLTD0ugTk+idRr46FqgnYE0kqq+d+MJ1+Xj2vaMIp/fZlJ79GIFSECiFdC8l36Rpq03fpOXkdIxAtSDABGCOa2ro0KFl0+7Pf/6zWL++ecP0L3/5y6J169Zly5szYgQYAUag3AikMSCNMwnEpPSDLXYCqtzlz0N+fffsGE2SYS2T1OF03nvPGSeeWPS2+LE8YRknDpqci/xT44OIwV8lXSghQaSVaSmiTX/XHnwgYy4/cVh0yrEt/eUnHlhA/oE0RDqT5RrqFflhya/LwTqTLDSpTHg/fc5lPWZLi30OsbQb8tXlzyFkTSiBZ8s7Tn9hk5Glfxp9YhL90szXZqGJ/TxnLnu3SD20t5C61xP63lFfuC6PnxmBJAgkId2T5JNWmmrTN61ysxxGIG8IMAGYtxqpkD5pLv+tUBE4W0aAEWAEYiNQyoDUN8lraN9MYmBSevatc8S8le795GIrX+UJHnn5TblMt4toJXaKYb0axMI3wyzZ1GLDisx2oq0aL6/3Q3p2LlIthNhSiTIi33DYwar1H4qL77WfIO3bg29Eny7R/nwmErSr3Cvx548sLiBSQKj9etIhch/FdhGRopIpzfc9vQSgCgDyDd1DLbIeO3Wk+NzUp4KWIMPSENaL5OK++0kJPLJIg6Wry/n6E1faNMNMuFAZgAH0JOI363zjyIeOJjIcbQpWn3hn1HZN71CcPCiu6x1NSiqSbL4yAowAI8AIMAJZIsAEYJboVonsd999Vzz00EORtiNGjBD4Y8cIMAKMQK0jEDqptcXDJNBmWQLsrn18icAyV0xKsz5dtRrr6md/aV52W6ru1YzttY8tiaznVAxsyyJBtk0eP6CIaENaLMO9QlpAqgSHKlO/txFtG+Uy6a3bzacivyf3StStqID9BEnAPXHRkS3L3dW8XESJGk+9h26he6it27Q1iPyzkT22d5v0UcN9h0WYCDyTRRrJVq95Jo1MZSA8Qyw11XJmee+y0MQ+oY9dcITclqF5+S7qSiWr4+ple0cJl7jyOD4jwAgwAowAI1AuBJgALBfSOc7nzjvvFNu2NZ+AOGnSpBxryqoxAowAI5AOAqGTWlM87IN2+UnDxEH7dhabt5rJEmgJIoP+0tGapdQaAjrZpRJO2EPy+5//WKzd+JH1RNcovlxqe+EfXox9EAnynr9qg8DpsXCQBbJ61mvN24GEYo0DQM6+7YUC6zpKG9dKj9LB0sxH0EBf7KHocgMkSX/VF0eKkX2by6jGNb3bROCA2Nqweav4miyXSjDb9jYkAk+tv55yD0mcEA6cXY7ydMUpR5iqO1n5IV+bVR38YX2aFxdioXn4oGRLfk1lTHPpskk++zECjAAjwAgwAlkgwARgFqhWmUxa/tumTRuB/f/YMQKMACNQywgQ0aFPzPGsTmp3ygMgsHRXJQCAC5adTrx+VnR4gW9Z76K1G2sZSi5bCggQ2eUjpHSCZu9O7cS3Z8z3EkwuFX9w7wJx/3mHR1FcFlQuGQjDHn42q71QKz01D5M1nRpuwkoNp/tfn36IkUj09QHXyKXFsGzUTzfGs04CEoEXqhPpduXJw8Xofnsa9aM4aV31tqMv4TXpjnJNOWqwtX2hv7TVeVp6x5HjazO+8Dh5qXFNS6bVcL5nBBgBRoARYATyhAATgHmqjQrosmjRIjFnTvNJiccee6zACcDsGAFGgBGoZQRcRAdNarGkElZNOvmn4kIHF6h++v1Qwx5vehx+DkNAJ16wp1tIHbikpyHDJT8kDMSEl5A67eAiSyzsyYdluaW4l97YKP784hpx/EG9vCeb+vIhIlOP57PM0uOTNZ3uT882rCicri45vj7g9Omzi8g/kgsSkE6wRt2BAIJOOHVa/1GB0piu+zQmX4bqI/TU/Gzk3jWyTcGKzYYnyqIToKpc3NvqXI9XjmfXcnNXWyiHbrWeR5z2WOtYcPkYAUaAEcg7AkwA5r2GMtbv9ttvb8mBl/+2QME3jAAjUMMI+AgJHKaA/dTSIJcw8cRfHGKghqFPXDQQLhOGdi84uRUWcKEHQJgyRr3QARr3SxLsF48vNUXL1A+kJggkWFLZ2gj8TZaopZJ/VLBz7/y7uHveajFlwiDySnQlIhPkGt4xPIOUwTXUoU5ATLmci7yjdMDVJgdkhW/p8EvSytfl2rbeTR4ssXdLlBCdWiJ/chMHFzWtj9BT47rIPbJ2dukOa2eXS1oGl8ykYbwvX1LkSksXpz2WlhOnZgQYAUaAEUgDASYA00CximVcccUVAn/sGAFGgBGoFwR8k9btO5v37ysFDxAQN8nTUW2T0lJkVzrtz/7P8IjU6dS+jTh92myxacv2zFXaKisFZAY53E+Ry199FkoUX7cePFISTSeP6i1ueHKZGCwJuL+++hZFLesV+v910dvCt1TcZYmahsIgGV9c7T+lunOHNgIHhegOxB2sZnUruIjQk8tpjxi0l3hq6ZixdeEAAEAASURBVLt6sugZVpjnTRho3edQT+Qj8BEfuK5r2lJ0MImJrNDlhzzrfUiITqpc4OLb41CNT/chhB7FxdVF7qHOl73VJN6Ue0y6HPY8NRGBScvgyqvUMN6Xr1QE46WP2x7jSefYjAAjwAgwAlkgwARgFqiyTEaAEWAEGIHcIuBbKgbrnlIcTmu96atjisgHVWbPzu3l4Q5bVK+quZ8+c7n43ymHR+TmRccOEZc98HLmut/09GtixpyVVis5lwIgmD4/rKdo+mhbRFLt23V3MeX3L4onJQGSBwfSLA9u/Qfu5cQRmSet86Kl8XLPP3JE8tkOizjnd/PEh9skq25xsLTFCbtEoun70+nJdPJND6dnyFNJNhtZQfHpivfXRbgiXJWLdKE6IS7hiPu4zkvoSUtSVTfC1JYPDo/BgUYuh/BrHl0snlzyTku0Iwd3s1pYtkSq4A0wUHGooCo1nXXc9pg2GHinoQPaOd5BX9+Rdv4sjxFgBBiBakSACcBqrDXWmRFgBBgBRiAYAX2SMKBbRzHl6MGRlZBq2UITc1gOJXGmTf1tpEO1kn/AZdHaJnHiL2eK2//902L3dq2SQBU7zdwVfus0VeiFxwwSg7o3iJtmvh4t5VaXc4Pe3WVLqKbiexsCsALDOwMLwLu+/pmCpdggWlxLmGcuM1v+qXmpJCi9h7DmMjkXga/G10k5F1lB6ZD31dJi8XzL4SqRZa8k93Xn0glk2SUnHNhCUpRCTPkIPZ301DHQ9Ub/B3IP5TYtQYf/ft32iMh+NS0sm9kxAnHbY5qImax5fX1HmvmzLEaAEWAEqhWB8ozcqxUd1psRYAQYAUagqhHAJAHkwtFXPRUtV8X1kCsej07xJfIP5Ma93xwX7QcH0oEm83EL3mX35v3c1HQhpIMaPy/3vun9gjUbxRH//aTYvGVHXlQu0GPqo0vF9+9dKPd6KyYOmfwrgCroAe8KTr7Gu4R3CiQW9sAjMstHBARl8kkkEFGwJrQ5WlaPyb7NIYx0ozg+HUHgY0/Ixo7N+wcePqgbJW25HtCroeVevSGdxg/cS/WO7qVxY2R5On5gs7ynlzafnosfB/AH8lT1KxKgePgIPVhSQia5kL4Mln047VfHE88gQ22Wna46ovz5WtsI+NqjLzwpOrYf1nx9R9L8OJ0Zgbj9l1kK+zICjEC5EWALwHIjzvkxAowAI8AIlAUB2yRB3zcO5Ma1jy8RFx9/QIuVzjWY+GpWQL4TY6dLa7Pj5FJT1flIBzVunu53UQh2rUAEXf7nV+wRKhyi13OF1amJ7DHBxoEkM6QVoGoFlvZEH/lgb0SQUGo+BCLt9TZ/1QZx6X0LC/aoQxrTASA+HUf325PER5aObVoV0+CwZgTxBaJQd7CONKV5euk74pw75oq2rVsVWNmBLETZEE6OdE9q/QiCVpVBxOSkac8XYET50bVpy7aWA3HQZwErEKguy07UEcJVohV9bl6WZOZJF8I5z9ckeBHBjLagO7RDtW3o4aU8u35YM7XLUvKq9rRJ6jWkzGyBGYISx2EE8okAE4D5rBfWihFgBBgBRqBEBFyTBF00Jg1PLH6qxZsm0VgOTBNiTHZO/fVz1tOBsW+YPiH2kQ4tGfJN1SNwxmH9xC3PrAgqR/89O4rl6zcHxdUjnTW+v5gm92F0Od8+dq60vjC081N+9WxEmGNfRbRxLKvHO2MiAnzybOEqmQVyzUQsjezTKO47d3z03tF7aiMd4pAVrr7DRjC8uOr9gn3y1HKZlkGb/CAbBOt5Rw0y7mlGhJ7JKo/ygwyVpASZOPWUkZEVNMXRr9RPATsVP98PGAin+HkiBPKki451Hp+T4mVrj/T9zKqscdplVjqUKpeIuTUbNgscPNZGrsnbp7FjqvsYJq1XX9mgu6kP0vsenxwOZwQYgcogwARgZXDnXBkBRoARYAQyRsA3SXBlrw5kaYKL+JPH9bcSgAhXJ8R4BumApYSqlQ/82dUeAq1j7IuWlPwDaqeN6StekCQcLWE3ITl5/H7iG0cOjJbsmsJL9Zsj88eSYHKY8P9w4jBx4V0vOt8Pio9rgzxFuslzgjTew3PlISKwrMM9OSIYyFJOJ65oco33EeQW3sM4ZIWv79Dfc+R36f0LSb2SriBYcbo2nF5O+JH1IywkQZKaHLBSf4yIQ36q8ogYVP3U+56dO0SPeSIE8qSLilVe70vFi9oj2hu9b+o3M4ty+9qlLzwLneLINBFzlN70zlNYnGup9erKK8kPJC55HMYIMALlRYD3ACwv3pwbI8AI1AECGHhhMBy6r1M5IcmzbmnjUOokgCbRql4D5cESLmfKE5izcyPQT1rEVbubNmu5tQgd5WEpg6R1VakOk8NBPRrE5Se6T2694cnXIouS/aRlXhJ3hSTz4ji8Kz+Qey6eN2FgcDIf+UeCQJ6r5B/88QwLFJPD5BrEmLrvJyx3H174poBF7/QzxojHLjhC3H7W2OiK5bxEJJI803tMYbjq4ZgQuwhZNW2ce1c5faeVqyQmkZ9oP6ojskH1U++JOFT91PufPPRqtCckvnd6HVE8+CO8XC6EnCiXLtWQT1p4gfRT9wXNsuyudok2nTUBWUrZbMQcyXS98xQHV99YLq16VfOke7VvIT/16gtX4/I9I8AIlB8BtgAsP+acIyPACNQwAqZfdmmSpU8yyw1DnnXLAgssS8SpnaXsBYeBrDqZoImHabJrmnhgEG5a6pdFeatVZv+95HLYd5Mth62WMm/eulMsLZEEGdOvMTqUAWUe0aeLcC3zfUnuazlputk6LAQzuV1d7CW9eCdOP7RfiPhU4hCxpL6ftsk1ToGmk6CpP1bT6Qq5+g70KXraLCe8pnJCX52E1Mughyex1CLicMqd84zLm6EbLDQ3StLV5fR+1BW31DBfXZRTl1LLUo701YgXtUt9GSq92+XALWkeLmKOZNreeQoPGctlWa9630J60dUXTvH4yggwApVBgC0AK4M758oIMAI1iIBt8onBnM1apVww5Fm3rDB4/Z3NJZF/0EsfyNLEAxMN1dkmHtjfh50bgeOH93JHqNPQTu1bF5R8jjzRGGQLJn9oh5PHDygIT/OB2jlIxjjumseWxIleclx9khs6ufb1x66+Az8o6BZtej+hF2y0JG9LcXo5IYt+jDDJRX+kk5QUD/5xLLVAHF5ywoGUvOgKC02f9aMPHwj1WTQVZWzx8OWF8LTysqhQVd4heOWxQERo+6x586a76V026WiLFzqWy7Jek/Y9pnKyHyPACJQfASYAy48558gIVDUCPHC2V59r8km/6NpTZxuSZ930kqfVxmwDaD0/27NtEh1n4oHNvdnZEcD+iH2lBWCIa+zYNiSaNQ4st6rFDd+3i9i0ZUeRunQKLQJsBE9RogQeOBEX7Ryn/eL061D30hsbQ6OmEk+f5Ia+877+2CdHD/dNiKefMTayqFQLjVOA0f5DnF5OpCGSNvTHiJB8bHFK+SHD1o+qeYHU1pdt4xn+cZ2vLvZuaJ9aXnF1y2N8H15Z9jNp4BGX0E4jz1JkmN5lkzxbvNCxXJb1Ws6+x4QN+zECjEBpCPAS4NLw49SMQF0hELLsoK4A0QqrTwq14KIDIvTwLJ/zrJta7jTbmG0AreZnu8ek9ZrTDrYFR/6YePgmRzjZj50ZAcL47Y0fmSMoviCjHjhvvLhwxnyBQxLiuN5ddxfX/dsosZ88CMK0ZGyKPHH10vtf9loxxcmzlLgo64I33reKIPKKJnh4TtOBlKJ2jYneTaePFmffPrdlCW2peaHet+3YaVwa31WSvO9t3kX6HDm4mzwh82NjXBOxRIdShOiIPpHKqcf39R16OE2ITe0L/Qj9aADLQeSL9JQ3/ECwXffEa0aMTeUkfV1yKU6pV/TJ1/11WSIxI3p38fajPosm7NEYxznr4tSRRX0AZOMdQt3FzSuOXnmN68TL8w3Ma5nyrFdIv+1650PHclnXq6nvQdlAUL60ekPUx+EZerBjBBiBfCHABGC+6oO1YQRyi0Dag/TcFrQExfRJoS7KF67HT/PZl7cvPE1dbLLSbmOugTY20N+2o/hwDkxYp54ysmVybtM11H+fxjDrtlB5tRDvsi8cIMYP2rVEsXOHNmJU30Yxb+UGa/FAQoD8O0+SdXRCqjWyFvBPB/YQnWQeyAcTfBMJc9tZnzYSA5qosjyirD5H5BXIJZ108qV1hWPiqRLfESEP0lXuoUcOOG78aDs9Bl2vPHm42Kdx9xbiK5IrCReVvIRFHCaL6onZeP4vmRYHjKhxdT3Rd2DiOXfFLj19irn6PFffYZucmybERPKRLni2+Y3o07WoLvVykhz9apKrx9GfCTMiJE2TdeqT45LulBf6UuDicj6LJpx2jP4a9WXS0STbVhd499V2pKaFP/IC5vVGWtjwUvHh+3QQQNty9dumd159V03jFlUztV8rR71S34M+HVa76vtFZfH1Aar+fM8IMALZI8AEYPYYcw6MQE0g4BukY2CtT2xqouAxCpFk0hhDfElR86wbFSztNoaB9tXS4mPC1KeK9gLEIFo/IATk32VfkHtdSTIBJzjbJpzqYNwWh8qEwwR0qyYKq9fr7u1aR1ZQKD/weV0SNwfu09lJACIuSAjf5AfxdDdt5nKBP5qM0IRFjadPlNZs+FB87+4FapRc3dMkr0Xvt5rEnOXrxY8efFVs3lq8dDhEeez3RxZQURuXffqFf3ixyDIyLvmHvLGkWP0+tOgt8wABBcs9nCirTh6RDs8g/2zELeJg4mk7pALhJoe2oOqjx7FN0qkN6fHVZ1P7UsNt9zomqGOXjjY5If2TiYClskEPcq4+GXGwPLydJOdMBx35MKY8fBZNIBXImXSkMNNVr4uQvOLmYcq3HH4h9RxXDx2vuOk5fhgC+ruO7xqR3Po7b3pX9bEL5Wp757KuV7RF0w9R6L/r1bKW6oSvjEAeEWACMI+1wjoxAjlEwDdwRrg+cMlhMTJVqZRJY6aKSeF51o3KnkUbe2fT1iLyj/LDZv7XfelgcdPfXo9IDmxk/y83PkPB0VWfDJoG43ocVQAOE1CXNKphIfcd2uwmPtpebKkYkjavcVRiLS452nq3jyPSQbVICy1nyGSEJkr4QSOvDu0NhD5ZMjZ0aCuueXSx8ZTWOGUAwTpjzkoxpEdnce3jS4rIuDiy1LiYrGLfNZNrwVsSmDr5R/HhTz8w6d8YTDzPuWOukYCi9PoVRCd+GPA5fZKelJDz5aOHEya6f8hzSP8UZ7Lu65PPmzBQHNS7sWjyT31iiM5EZofEDXmHXXJC8io1D1f+aYWF1HNaeSWRkwU5mUSPvKfxveu2dxVjF50EDH3nsqgb1w8Fav+d9/pg/RiBekGACcB6qWkuJyNQIgK+gbMvvMTsqyZ5pSaNIQDlWTfo72tDvnATBr4JLJF/prTwUyeDtsG4GkeX48tfj68/1xr5p5cvLjl6PfZJi7kHoJpn6GQEBNuh+3UVz/0j3n6Dal5Z3GOZ7A9POlCc+uvnCpblppWXSs4mkYk+BuSE6jBZdVmBID4sDV0O75FO/iE+iEGT9ZlLFtrP+XJZM+3N54qLMN8k3Zc+abhpog5ZmGwDD/SHaKf4cQfO1T/BQvKWyZ+O4sWZrPv6XISX+l1xWadHCmv/Qt9hLVn0GJpXKXmY8k3Tz1XPrvcsTR1csvJOTrp0z1uY611Fvzr9jDFWy0FTWbKqG984x9Z/m3RkP0aAEcgeASYAs8eYc2AEagIB18AZvzyaJmc1UfCEhfBNGk2TO5rIJcwyOJlPt2BBKUfMoo35JrCw+vM5mgwiHu5NjuIAW7VukyxZNclnPxFNdEoh/wjDkMkI6nDxW/myApz+1UNEV2lN9/lfzBRNMffgo7JneYVlna1+1PdD1YHIDN97aHuP561MRtBCn1CyRH2foQf6qbh9dVwZpok6DmeBHJXwxBLcyeP6y+9vQxRm65+eXPKOmC/32Bwp99qMM1mP0ycn/a7YrNPVdqLfh7zDeho8x8kraR6mfNP0c5FCtvcszfxdsuh91tthnPfNJb/ewnzvKpYNHy730w1xWdaNrX8mvXzhFI+vjAAjUB4EmAAsD86cCyNQ9QjYBs6hyw6qHoAUC2Ca3BGOsKaoV5dFG3NNYLHnn494oLrwDcQRD3Gw1BHEgjoBai1PApaHnrIrEYG0yFQsmfW5hxasLWnptk9+kvBrH18a3F6TyI+TRj9EB8vRThvb10oAQraJUHGRGaSP7QcmTGjfbtpC0WJf8Y5iyTP2J7SRemn01SEyUBZgAYxs+yGqh6NQYbEUnpbDoz9zuUvvXyjuO3d8LEvrLPpkk45kRYj6CLFCLYVQoLxw4Ie6v6CuVyl56LLSfPZ9i0zvWZr5u2S53me8b7SU3yWDw3Yh4GuD6CtoKwjEtfVjkJhl3bjGWbb+e1cp+Y4RYATKjQATgOVGnPNjBKoYARo4qwMO/OrPLhyBLH+FDdcivzHTbmOuCeyUowaLiTfMCgLDNxCHEAzGdfIP/kz+AYXyOUw4tm7fIWa9Zj4R9icPvhKdJmybMOEdvUruqZc3F0pW63rre0Xp4XGfdfIP6bEc7Y7nVjpFmd4hH5kBUks9lZgyMJFqFBbnSmST6QcYX1+N5XdE2rnakqlPUC2i0iqLr30gHN/ukMm6SkiibHpZs/rug4z1ubQIBcjBn/pjDeWdVh4kL82r6T1S5fvC1bhp3/ve50qSk2mXtRzyXO8qtoPQD05Cu7VtbZBl3bjGWab+uxzYcR6MACNgR4AJQDs2HMIIMAIWBJIu9bGIqyvvLH+FrSUg02xjNlIRk9wjB3fzHp5Ak0HEd00YMQg2TSZrqV7yXpYrJg4TJ4zYR0ya9rxVVSxTPX3a7CjcNGHCO4rDW6rdgTybesrIyCr1K795Xix4w7/cPaTMNkvMuY7luFgeTBNQ1UrFR1ZM/eIIsU5a+b20ekPLnnd4D8++dY7T2jCkHGocvLdoM8CL9PP11fo+jLa2ZOsT4L9MHn5yheH0Y1W3NO+JgMGkXCcmSX8TIUlhWRF/VEYX4YE4pAfFL+VaraSFCyPgk3UduTD3vc++cJfsegyztVGMW+TBwUXjDfQpeK/pNHcVMx/2vnBVluneNs4yxWU/RoARqCwCu8mBVG0dL1hZPDn3QARWr14t+vTpE8VetWqV6N27d2BKjsYIVDcCTy9d10I+mEpy+1ljg/d0MaVnv3gIzF+1QUy83m4FeECvBvGtowZFe2xh4rVR7r1mmziDpCBiKZ4WHDsNBDq1by3+9M1x4gpp4Yc9z0IdJs3qhOlvS94Wk6bPCU2eebw4S9VJGaS57axPRwc0wG/nzp3i4B89Kg/o2E5RKnYlEgcTRgxBsQzTRJJhz7s2rQpJdVi9fLhtp5i7ItnefyGFJv2SvM96W/L191eePDxoyWuI3iFxHjv/s2Jgj4aWqLo1v6s+9LK1CEn5xkRAoj1ffuKwaA/DlLOLxOk4ZJFHmjJNGIEU+vYxQ+T+oNtayHIQSOV0eWg/5SxvOfNS2yjyPfqqp6zZP3bBEUVEMNeNFa66CuD5d11Vt7WwbAFohYYDGAFGoFoRwEDHtzSrUmXz/crqC6+U3rWaLyZLLvfKm03iG7+dF0UhYgBkkToYJ4sLrjsXktmHbdqyQxxz9d9iZwTyaam0xBr0CTGyPSf7Nfbfq6O4+tSRAnsWuiZ7pgLDkg0EG7lWrVqJP3/rcHHSdbOi5brkX4mraqVis3DBu7ZNrp1/YnEhkasegJGV7tAP1oBTjh4cOwukRd8Q2id8uHVH7Dx8CQ6SZNlLlsONYG2oLhGEnqQrvpvQH38mp5fNFCcNv0pYEqk4pFGGUmX4xjA6Rg3t24prH19S8GMWfa/UfqBUvXzpXe8zLwX1oecOV9soflhwObL0VeNw3aho8D0jUN8IsAVgfdd/xUrPv0BUDPqaz9j0y3glBsI2oPlXWBsylfHHZD0OuYK2pFqLqVq76jbtfdjUfPm+dAQii7nJY8W6TVvFIy+/KX72lyWlC01BAqx6rsVyzRnzrcSMno2rjSIuDj+4Sx628PDLb+lJg56lUZ7YmcLakUelNRompZisgjzH+7N240cth1TEeS+DFJeRhvZsEIvWNoVGF0neW9WK29UnoJ4+kAQgHeLhU8p0CrAtjUtvU/swfTdNstWymcJ1P5Q/rz/G6bomec6ifKa6QJ2pxK2qq6+N2b5Xqows7k0/kmWRTz3K9I1bTBaAKk5cNyoa9XXP8+/6qm9baZkAtCHD/pkiwB1QpvDWrfC8DoT1Cok7wNfT83N6CKDNYAmwbwN9NUfX4NpVt29LcuOcO+aKJW9/oIrjewcCg3t0EhccM1hs2LxN/Mc9CxwxSw9ykSalS08uActe/+vkg4qs9zq1bxPtV6e2XRdRoGoQetqqmibte31ps6q7b+lsKbrErWc9PvYzxD6SNqf3D7Y+wXcIEfL5yb8e1EKQkqUeJu/4mz7zdaceNv3gr+ro+m7qMtR0epj+bCu3jcjS0+f9OYvyuerCRNwCo1LJoLzjzPoVI5CknRRLYZ96RIDn3/VY68Vl5iXAxZiwDyPACFQpAr5N2zFQpklUJYuoL9+B9Use9Co3JhjEVto6BBZI2Fsq9DRgYGRaXkPY2eoWZZ274kMm/wiogCuw/MM3Doti4tCHrB1Oss2jw7JX7Dup67dpy/bIQg2kDFnRhfQjaIvdOrV3FrV9m93Elu0pmPk5clGJS0TDElPawD7Jcvox/RpFh3ZtxNNLC5cN6yoAx+H7dgk+FAXxcQouTj+GXtgL1LZvIUgavQ5sfYJvGd/k8QMiWbo8POPvuGE9I2tO6BLXqX2Y67upyjWVTQ1X79HG9L1SEa7WsRq/2u6zKp+rLmxLsFGXLkd1DZ0r/b116clhfgTUOsQPCHBoF+ToRxR65isjwAgwAiYEmAA0ocJ+jAAjkDsE1IEPTcJA3qgudCCspqnkPU3kKqlDpfLOwnrCV5aCNtS5gwC9gSWHPeU9Bs7qQNolSyUnIBPE8rxPTkAd3ber2P+TCTrqF+E4aOQH9y4QL72x0SWWwzQE0Eam3DkvWibqsrjSktXk49wVG4zlQpu9+HhRdHBQQVv/hLRCf2l670yCSyH/fjzxQDF91nLxujxNOa4jksN10qlJ5tj99hR3ff0zweXDicidO7SJDvUxydP9QP4dPmjvFm9YsekEl2/yrff3aj/SIli5QXyfg15JnJq377sJ+b6y6TokIbJ0GXl+zqp8vrogMk/FRq1L1Z/uEW5676lOQVCzyz8Ctjq895xxLQe/hPQZ+S8pa8gIMAJZI8AEYNYIs3xGgBEoGQHbwEdfShQyEC5ZGRZQMgIgJ/TJM4Ri8k8WQCVnoglAGwKZZDsddmjPTqLz7pIQ8JySikkTDbIh85u/fUHMem19QW7Yq+u6L42K/EzlLIjMD04EbPXlTFRngTopYO0v5YEi5975d6+FnA8+7EsIMtFEmGO57CX3vuwUMUTuw7fYsQ/fmg2bo3fMRLJhOTTyVq38iMhApmRth30OfZZxONE71OnfFsoH5D/wRzj1C6EyXSQn9TM2Ipfy0PUif9eVZFMcnwxYP04Y2p2iB12TEFlBgnMSKavy+erCFO5rRwO6dRSn3fR80V6TWX5vc1JNNaOGa8yEQlZqn8eaAZgLwgjUGQJMANZZhXNxGYFqQ8A18NHJIt9AOO4ErdqwqhZ9s7KesJUfbQh777lOEF20dpMteYu/SjRApon8Q2SQE2S5ZiJJWgTyDSOQAgIqKeDqL0+fNltaob5fUo4g+H70L8Ol9VzbIhJf3yvPltHkcf3F9+627+d43V+XiRF9uraQeSaSzeSn5od3FX9pvH86Yabmg29K0u8KiEwTyUn9jJXIldaHZLXl+uaN7tdVNLRvXfCjB/YVPHVM38hqGWmhg0sGdNHJP7Qx31JStU2qeNG9L5zi5fXq098XbiuXry5Mbc3Vjn44cZg47dfPWfeKxPuBd8kk16Yj+5cfgXKPmcpfQs6REWAEyokAE4DlRJvzYgQYgdgIxBn4uAbCmGixywcCWVlP2Eq37K0mJ/lnS0f+P/3XYaJ7592jPcDWNW2JJtWYOOmWfxQfV7ZcU9Hg+6wQ0MkpV39ZKvmHMmA/vP/80wJxy+RPR1YnRMRt2/Gx1+KOMBgll8lDbxs5h+Xe6o87JpLN5EfycbV9C9Q4IfdExoXETRLHZEkIEug1Scpc+IcXiw4nAmYqNq5yzl3xnsBBK9f928GidStpJfTMisgKbPbyuZGqVDbo4CIi1XKFkJKIn4TIUvPJ+31W5bPVJ9WVDRdbO4IVrG/7BHyPmQC0IZsP/3KPmfJRataCEWAEskKACcCskGW5jAAjkAoCcQc+poEwD25TqYrUhPisI3zhcRTBhBXLHktxd85eVTARD7V0KiVPTssI+BBAO9R/2PD1lz6ZIeEgt+ev3CBG9m2MiAP0r74DLUguiIxBPRoivc++7YWiZYkUz2WZVGCBpuzliX4DxAxIFDj6FoQsB6Z86frd44aIYw/oWTZihAhN9Fe2A0ZINx0blBPLdE/91bNFZA8OWkH/Z+qzVDKRsCJCF1jq302XdalKSkLPpEQWlTHv1yzLF1IXNnyoHSEcdYk69rk0v7e+vDg8GQK+OvKFJ8uVUzECjECtIsAEYK3WLJeLEagRBHwDG1u4OhCuEShqphhZWU/oANGEdfFb/uW9elr1WT+tVD+NVY3L94xAuRBAO4RFKggDcr0kIVYOd+n9C8V9545vycrWD7dE+ORm246d0YEE0Pm8CQMFliXbnMkyyWSBpqYnSykVE/jhL4QMIVkq+VdAOGokI8VP40r9VYie2CcRDhgBe6R1WXrZ+izkpS4BdX03XdaluhzoFkpklQtf6JSmCy1f0jxddREiM+THALwXyCdtV611mjYOackr15gpLX1ZDiPACOQbASYA810/rB0jUPcI8MCntCaQx4F4ltYThBbKjUlpyGSa0qR5HdO/UXRq37Zi+adZllqUddC+nStyKnO/PTvK02T3Er99flUqsKokGcixHz/4SipyfUJAisOyDgQC3mdXP63Kwj6cZC2G07ddTicV8U4jreudRhjJJ9m2/obC9atKipgIR4TD8lIlGXUZSZ5dBJsuD/skqoQflvomdWobcsnwEUo2OS4iq5z4uspWSpirfKXILTWt/v7o8nBytm5BrMdJ8lwLdZqk3FmmsfVh1BdlmTfLZgQYgdpDgAnA2qtTLhEjUFMIVPPAp9LkW54H4llaT5jKneSlwKRat/4LkdO1Y1vxm6+OjaJ+8cZZYsnbH4Qk4zhlQuDQ/bqKuXIJayXcivWbxYrnm6230sifJvlEjpVz70ksVaUJKN5nkAmuk7apvCDpYHXWvFCXfP3XUIKM5KuWTdTf+JYDD9+3i7hGnpYMR5jqhKOJZPRr3ywPZQBRhnoDaYrvGzkfwUbxsJxXJf/gn6SfInnUhujZdvXFwz6QWApuKpsuE9iiDVwUsM+hnrYSz5X+licps4uUx2Ewd339M0nEOtOk/c44M6uzQOrD8N5QH6L2cXUGBxeXEWAESkCACcASwOOkjAAjUB4EqnHgYyKh1Mly1shVy0A8besJW7nj4o09tfpKa62jr3oqVlJYVdw06RB5Smqb6KTMgXt3YgIwFoLZRt6jXSvxyptNAmRFtTv0JzQBDCXH0i6zToaphJYrrxCyC3GofJAVkoby1NOSf9vWuwg38lOvC+Qpyd+eMT8iM7G8Wif/KC781aWz5G+6ok96cdX7AsumVaJO/x40yJOVQ5xtOW9IWj2O2ob0MP3ZRSiBlAQhTE4vG/njavo2quG4j4OvnjbtZ5O+rvKlnX9SeZX48dTVD+WpTpNimod0aY+Z8lAm1oERYATKi4A8F4wdI8AIMALVgQAGPocP2jXpzavWNhIKA2AsTyuHCxmIl0OPcufhKreqS+9G9/JDEAU04VXT+e73aNdabPyoeSN/kIcPvfyWLwmHlxGBD7bulPWzvYw5ZpMVERAkPQ45RmnSuqJf+/3sFQKHeuA+xMFKzGdRhv0MQbLBqgxX35JhNV+bbJu/mpb6aR+m2IdP1Q/9vu5AHp1582wx8YZZBeQf4lE+uEfaax5djNuSnGspMEg61eltSA0z3ROhhHSqcx0wosbDve3bqMfDsw9/U5q0/Wz6qnWXdp5pyqMfTx+74Ahx+1ljBa43nzk29eXrpLOvznzhJIevjAAjwAgwAtkhwBaA2WHLkhkBRqBOEXCRUJg4hFqOlAKfb6CNcNW6ppS88pTWV27oignslKMGR5Nym+5rNnwYWfBhOSAsglBv5EwTXgpDvJOumyXStNIh2XytbwSuPHm42KexmTjT390QYispeg3SmrXJQ5r+xz0Lg8Xj/YP+IFdwr75bJGTYPp3F9/+0oGCpK8itUX26iHnSms7ljhzcLQo2LUclUt+UpyoT4ad/pr/qVXR/3ROvFZxijLLQ3oAo22uStLzQsMRVFYR88D2AS2P59tRTRopNW7aLS+8zWxvCqhF9JNqL3oZUvWz3RChBZ8iBJa1q+aemo7Kp+bi+jWpa3KttOsLTsXxaT5vWs0tfU/nSyjdtOagDtR7Slk/y1DojP/XqC1fj8j0jwAgwAoxANggwAZgNriyVEWAE6hgBHwmF8KwH476Bti+8WqvPV64Ljx0s/nlYLzGgW0cr+YCyf+/uBREENKnXJ86uvcSY/KvW1pNvvUf17Rr1GyAldHIL7RnLz2f/Y33qhfCRf3EypPcJaciizHSwx8I1G4vE0vLZLru3kctIzVac4wfuJbC6W126D+Lw8pOGCVxdeeoZtpFrZGwEJX4E0LEGIYSygAQ0lUmXT8++7wXFw3WM3Ltt6/adRdaECIOu9F3BCc1L32oS81a+hyAxut+e0bYEIPAoThSQ8B9k4A/t0OX0b11oWdWyVHIJrk9fvXwuLCisUmQm5Z/l1UWwq3WapQ4smxFgBBgBRsCNABOAbnw4lBFgBBiB2Aj4SChfeOwMDQnqdSDuKjdgmvrIkugPk5EfThwmfnDvQqMFEkFKk3osm1InziAH2DEC5UTgh39+JbKaw0m65NR2rBNSiIPwbTt2CjUNpS339af/OkycNrZfQbYtFmWSrPJZy1FClfwD6fn9f/6UaNqyLVoi/JOHXi16n0EcTrx+VoQFWehhj8/fPb9SXCzff5vbp7GjkczDAQr6IRwkA/3FV37zvMBegqEu9HsA0nHO8mZCT5eNekbZyIE007GgOMA8LefTXQ/Xn016kJ4IA1lmIlPVftkkIy0/n76+cF2PSpKZui6m51LJSRvBrtapKV/2YwQYAUaAESgfAkwAlg9rzokRKECg1IFWgTB+yBUCLhIKA2GVSMpK8XodiNvKreOMCSTIPxB7WM42d8X6Fqs/U1x12TYmcdf9dZkejZ8NCOBdgMVaqMPei7VwQEdoeePEe3rpO0XR0Y5tS85BVKF9o71ifz4TQVgkUPEY0rNBLF7bpPiUdnvLMyvE0J5dxAi5jBfvaYGTz2ThV+DveUCZrn18iQChByzwZ3MIC7XQU/tpYKha00G+jQBEWBzyj/LBeAD3Jv1hudhe/uJgyhNhWParflPKSZrF/da54pvKUukluC59qe5Q5yGunPUSoo8eJy1ysoXU/2SZOEhStX3q+Zbrmcfc5UKa82EEGIG8I7Cb7BCLdy3Ou9asX9UjsHr1atGnT5+oHKtWrRK9e/eu+jLFKUBaA604eXLc8iKQpzqm/ZryMhAvV034iD3oAeIApBP2/KNlvyb9sIE6DqDBJxN7Xpkm6pTOtUcgxeErI1AOBLDpPybfWKp5+rTZ5cjSmweIE1ir0UnZWEbpe/98QodKsnJRIFnpWyqN9/e+c8eJPl07RtmiL59y57xU9uhTy0E4kEWe7Zvh26+U6phko99Tl0CTP131+OQfcjWRKDhUR7fS08umyraVk6wz1bi+dkv9spom7fs4+rryzrJeXPmGhLm+a6hLkOBZOFN7KvpxIGHGqmycsI1DdtR9Nl1tNGGWnIwRyD0C9T7/zn0FlUlBtgAsE9CcDSNACGBQog+WEUbWCVkNtCh/vpYHgTz9Cg4CIA+/wJcH+V25oMy+PZxsG9jvktJ8B6s0TEZxdZF/IBemnjLCu7RYl8/PjEAWCNAeZXFO0M1CD1Um3p9z7pgrifdWzndJTeO7DyX/IMdnCYk9PMk6GN9r6JrmEmpYumFPwpF9GguKZftm+PbZw2nEav/u6/OoTRRkHvDgIsIwbgn9oclWTpMKviW2vnCTzLh+cfR1yc6qXlx5hoZVwtLS1Z6AeSnOJFuXx2NuHRF+ZgQYgXpBgAnAeqlpLmduEKjEQCs3ha9DReqVfMtLVacxQYRFUChReN6EgZHlEE2I/7JwjfjvR5bmBQ7Wo84QQPvHZBj7weXJpUmoZVEukAMgtEAApqWraYmrSXf9m+Hrw3Aa8Yg+XQWRJr74vnCTTiE/XOp6m+SofiHx01yCq+ad5D5EX5dcH+6+cJfsUsPKTU6GtKekZbLJNsmj9xx1y44RYAQYgXpBgLcxr5ea5nLmBoGQgRYGMJh84Jd/moTkpgCsCCNQRQjQBDKpyg0d2og4p/rSJA7vMNxO3mQjKfSJ04GwPXS/rt70u7fR9qHzpqi+CHEmw9VXuvgaN7QP/90b3146RTd+ToUpYBl82+TCg4RCv/O+PgwWjVhVQM4VH8sek5AdIT9cUv6h15Dy056u0Ft1tHxT9cv7fRb1klaZ6btlk+cLR7qQ+iT5WbSnENkUR736xuRq3Kzv42CYtS4snxFgBGoXgfCRUO1iwCVjBMqKgG8ghb1K9D3GaLBLv/CXVWHOjBGoYgRoAmladm8r1mVfOED86e9vRIcSNMn9rUIdTa5Dlh+FyuR4YQhccvynxFZ52u3Qnp3FhKHdxfubt4oz5V6N81ZuMAoYhYMoWrWSh7+YT1WlRFfIk6JdJ8VSvLxeH174ZmrLbKmMV548XOzTuLvo1bmDuMJw6i7Fy+O1act24TrFV9V5+szXxcmjk+9PDLIR+cFFJN2M+dHeh/iOm/oI23ee+rCzb51jPAgE8lVLJoqv71t45OBuBScFI12o85EkCI9DLMYpP/Aii2rkgzFUnLxCy5h1PKoX/VtE9Z51/i75RE6iHekOP6js3dBe9y54jlOfSJh2e1KV8clW4+LeNybX42f1HBfDrPRguYwAI1D7CLAFYO3XMZcwZwjQQMukFgaC1z62pGjChkGZ+gu/KS37MQKMgBkBmkBi83tsGo+DP1zu7nnN5J8rjh5Gkzj8gq9P8PS4/Jw+ArDU/OaRA5vJPxzaIC2ibOTfnnu0FXvIH1p85N+QHp0kCWwmENMvQTYSpz6a/vLz0f32jA7EGdijISKU0ParyU0ePyA6cdenM07d3UuSH0kdkX+Unr7jtj6Cwim+ekUfdt5Rg1SvonsQH2RB9Oxr74jN23YWxAEBldSB7HU5IlEof9fqhSTlR94g/XAQU17Jv5Cy698ifJNAbsK/ki4iJ08dKUD26Q4W8K7xZ5z6JIxw6I/LUXtyxSFZelsLSUty0XfloT3FwZB05ysjwAgwAkkRYAvApMhxOkYgIQKuX4Fdp/1hcoAlSXkYrCQsOidjBCqKAN4d/GGwffigbnKJ/TtF+nRq31oseOP9In+bR7Sh/4kHik6SUHpJkkW+Q0Jsctg/HQRoIqWe9qhLXv/BNmPd6/EWv7VJ4I/dLgT0CTMRGn9d9HbwPpmwRAM5i9NjK+HQB5BF2f0vviF+8fgyqxrvbNpiDUsSgO84/ZnSu77zPmLDtHpAzQOyQeSg7HEcLJN+/OAr1iTUJkItmEKWf1bbOCe07AQifYvoOQ/XdZu2Wre7cLXL0Po0YWQqN7UnUxj5mWQhHU6Sph/ZobPLUXxXnHKFhWJYLn04H0aAEahtBJgArO365dLlFAGaNIHQU5e0+E77Q9xqGxjntArqQi2QIRhYUhvDwLgUK5BaAg3YmNymLTtM3la/F1e/Lybf+oJ14mRNyAGpIgCrNDjXRCrVDCssrG3r3SKyuZxqgOzGBNvkoI/LtSwblss34Y6+6ilX9EzDVq7fHJEE+JaeOGJfJwGYRX+5aO1GZ/ls33kXsQEyw7R6QM/IReTocfHsI9SJRKF4OumCZ510RPlczlZ+V5qswkK+oXHKnpWeacj11QtOm4ZDPJDRNJ7wpUM44oZYxlN70stTUA/SGhWEtP4jj9rW0E/p+UE2fmRv2rKtIsvIC8qg4EeY6mVWn4Ehj/1VRPieEWAESkGACcBS0OO0jECJCOi/Avt+4feFl6gOJ68hBFy/kFd6uVGlYQZJlNbJnihLnENCKl32Wsx/3P7N5B9+QPEtLauF8mMi+53jhoiv/GZ2QdvDe33pFz4VEYPfu3uBs6id5ZLpuBZ4U08ZaV2q6Ps2gaClCazvhy6n4ikEYo9dIhp8pBoRyylk2yIC+1S6nA3LpKsH9LxA5FBd6GF4VokKn0XzxccfELUJ/Jipk38kG/7q6gVb+Si+L5zixb2q5UIeRGDZ5IR+Q10/Ouhlt+UVxz9uOUJl+3DHadPYy5IcvUO+dAh3YQR5+IFA7SMoD1xN9aCGq/cq3mTlS4Slq82rMrK4N5WB8EO/HYJhFnqxTEaAEahPBJgArM9651LnFAHfZKSSA5icQsZqGRDABEH/9RvRMDjWrTEMyWvey2exUPMA1FABxw/cK7JqjWNRBks2WG6Wyw3t2SAWrW1KJTvsX4lDTuDm/ecxAktvYVFGh5/AH2SLy2GZe1zyD6fYur4/cb5dvsmuSffd27YSH2p72pnihfqhLzz7thfEeRMGiilHD45IL9WiiCbnIEpxj/hpOMiiP5NMhLlwTrp6QNUdRM6IPl2NZK6JqFDT6vdkmeTrUyke0sdpK3p+pucQQsxULmANSzHTD2JxvqFxym7SP45f3HLEke2qF+wNqJJ/kEvjCfRJwNLVnn2kPw4VMrV7Wz24yvXIK2tlcM+onUGmSa4rfdphtjIQfiAqXdj7+oS09WV5jAAjUPsI8CEgtV/HXMIqQoB+4ccHX3U0UFX9+J4RsCHg+rUdg04fQWCTWyv+SQiI4ft2qZXi10Q5QOL96f8eJtq2bhW0nx8VGn3pd44dQo9luf5EniR8kNRXdSbSQQ033UN3Iv8oHM90+An5DejW0biZP8LbtNpNxF3mjnT7dOkQkY07dxYeLIEwON+3C5Ng9DsRESDvsQ9gHHf2Z8MO7ogjE4TG6dNmi4nXz4r0v/eb46JDgnAwA0iNdRs/Ene9sEocMXhvMbpvYxzRxrj0HfdhZUyseYLUUA/EiNOnodyTpj0f1QfqhZyNqKBw05XypaspDvzU8DTKT/mAEINFJ34AQF3iimf4k7OViwgYiqde43xD1bKpMujeF07xfNck5fDJVMNt9YJTs21W7sAQWIFIRftWHbV3+PkwsIW76kHNS73/2cOLje1AjVPOe1cZaDxmw17FsJw6c16MACNQ2wiwBWBt1y+XrgoRsP3CX4VFYZUrhEA5LRIqVMSSsnX92m4SDOunGV87NJpYYsDOLj0EOrZrLTZvjbfvInKHBd9/PbyoyCrFphlOCb7xK6PEuP27iVN//ZwtWur+jbu3EZOlpdmGzbsICfTxd37t0+Jn/7uoaB8rUgAWN+qkO85E8PV3NhekJZm4bt+5i/BR/X33985fI/AHve47d5zo07VjURLbt4tIGvXdOXTAnqKxY9sCXIoEKh4jpcXaBccMiUgrWPhgkp+mg24fyHaI9xzWkZOmz45FLNt0AXmCU4d1SyQbVjY5Pv+4fRreH5Bl1K6gj4uoMOWPtGRd5cpfjUdy0ii/jxCjw05c5SIChspB+sX5hrrKjvpHeBouSTlM+QI3yEIZQbxBPxBQcKZ6QTyQqzaHcOBnWnKLvED8Y9k5vqO6FSFkmtoH5eWrB4pnuqJu87DiwVcGws+Evd4uTeUM9XPVe6gMjscIMAK1gQATgLVRj1yKGkQAH/40P/41CBEXyYKA7dd0iu4Lp3i1eqVf26fcOc9KwFDZaYIcJw2l5asdASyLPXNcf7FH+zbi3N/93R7REWKaTNqiN0lS54cPvCIOH9jNOAm1pSvVf8OHxSfdghDD/n1YwjtfnoZ76f0LC5YkE2nUrk0rabEnre8aO0bfAppMY8KoT9xVPX0TTjVu3HuQkiddNyvS3ZZW/XZBZ9N2BM+9vmsvMZsc8gd5S5aPkP3xxz1SJwCRF9rTqb96VgD3NPYIxb5mp47pS8UwXokcojpTyRhTAtskPuqfTh0pzr59bqz2rZIkpIMpX92P+kXyp/5Rr2s9HsWnq9pWyC/0GkqI+cqFcH2s5ftG9pIHUZCzlR3hs5e/F/1wREuNbfVHslzXJOXQ5aHvsdURCChycepFxUpNZ8or7g8bqmzSLc7VRvDGkVFqXF8Z9HAVw1LzpvSmuqB3U613is9XRoARqG0EmACs7frl0jECjEAdIoBJJAZ3GPzqDv76ZEePUw/PGPTeMvnTTgJGH4gjzSUnHCierOAJprVQN5gEYk88OqgCe9IlWZYaF4slb20S+MuDA5GG/ftAbN137vjISmbZ201i+qzlEYEze/ncSE2apMWZwOkTyrTLq+ruk+0iaXxpKfybR+4fLR1GuSKCjAIyuIKwScv5DhAx1SmWtl9+0jCBK4gl1ZniU/tAvG/PmF9A/g3fp7NYsMZ94jDSEUniazdYFo3TnhHP9A1B/2iyAkMeWbhQQsxXLlO46xuKslzx0KsF+wei7MAH1sX6DxNEstpOpiVy0IeRSU81jS/cRsaTfmQxqcrEvQsL23jClhf6DvzAcd5Rg6ztSM3flzcOofFZBJsIXjWPrO99ZTC9S2nqZKsLX72nqQPLYgQYgXwhwHsA5qs+WBtGgBFgBEpGgCwSMDhXnTpZVP3r+X6k3NsLBAz2/br9rLHR9a5vHCaOG9bTOMn1TTorjeXuckltHt11/3awuG3ymGjyh0mg6koh/6p5b0Yc3kEOk8QZc1ZZyQNYq2LCpjqawKl+uKcJp+6f5rOqu0sulv6V6q6Uy33V/d2WyeWLeXc6MYJJOO2BiCv2UtQtsVAmLM3FnoSmfezO/Z25DZxzxzyjLJB/INtDHPo1V7tBeUBWq/sO2uSC0AiJZ0sf6u8jvCjcVy4TAWP7hpJupncPZLdO/qnxz751TvA7TOnUa5JyqOldZDzKg3ZpcjYsaDyht208u/ICyY66MeGu5+/LGzKOPaCnnqzgmdpBgWcZH3xlyFoVV1246j1rvVg+I8AIVA4BtgCsHPacMyPACDACmSFQbmuMzAqSsmCanGDCi4kBJlUYoGMiETIhqfRkwgfHhwn20/PJTCP87nmrBaw10rSwgl7nfG7/iDjDRKba3LqNW6JJN9qgb5JmKxvKvfStpqgNq23aZG1kk5HEH6cO+xws1q776zJftFjhKO8HW4qXVccSknFk7HUG/MmZLPds+6FRGpQTBCFZZb0WHaDyDgUXXGcuM/sjUmRxZdl7TRWCfo2ICp2YJKJHjZ+HeyLETO++SsAmLRe+oeiznlj8lLG4yBekGX03fD8O2fo+XQ4ys32nTO91aP349EM4lUUvsG08gbYNslqtA+jjW/ruyis0b4oX2g4ofiWuNvzKoUsp9V4O/TgPRoARKD8CTACWH3POkRFgBKoYAdvAPK9FCiW28qp/mnqZJuI0ecIAPcS5Jhsh6es1DiaIB/ddk3rxB3ZvaF52KEmwuSvfiybOd897Q8xJcSln6kp/IvDmZ5YL/IVMmF06XPSHF417CIK8+MqhH4izbn3BmvyiYwaJnz+61BpuCoBVGe3JZwqHH/pJEEk20sOWLsQfMn0EWoicLOJgeeNdX/9Mi2jCQSVIEGizFGtJKG+Q5o7nVoj3P9om3m7aogbFuj9vwkCBPesu1NoJCUH7I+KnkkQF6aNeXd/bUGIPMtZJ/CaP30+cfmg/ieVHEdmJJdqd5f6SLheHPCnlxyGVEPN9p5Ius/bp5wsHTup4wta20W59JL0vL6p3WBBvlweP016o4+Uerqh31YW2AzVNpe5V/Mqlgw9rX3i59OR8GAFGoHwIuL985dODc2IEGAFGIPcI+AbmuS9AhRSkwTwmORhsgkTTB/FZq+aarKiWNj49bJMNnPZqOvDBJ6+ewq+KSTT5sBkll2+jLW3YvFV8/08LSiKbsOcall9WwoVMmF166XqDIFP3EBw/cC/roRbPvv5utK/bth3FpwN3kW26datWBScKg/zDKcCqM73fsIzSSS81Tan3n5dL9ENItFLz0dN/77gh4uGFa41thX5MUNO4LDvVeLb7i+9daAsK9m9o31YM7NEgbjvr00VLhU06Q3AliAq9QCHfWx9haZKh5kPlt/0A5CNH1HDXj0M+wprkhH6nktSPSz+VBFbxcd272raLpPfl5aozW3352oGrHLUelna91zpeXD5GoB4Q2E1+bIpHffVQci5jRRFYvXq16NOnT6TDqlWrRO/evSuqD2fOCPgQQFepL3WhNBiU0lIt8uNrMwKmwbxtEJ8lZiAkjnYc3oE9ADGpiuMgE6RmQ7s24ky5v9N7m7fFSc5xU0AA5NbLcq+zUrFH/cPB4gQHhfz4wVdT0C6eCB9JEE/artij+3aNrCN3+YTfAZeV6zfLQ1s2Ciz7heUf+kJM/qO2L8mlax9fUkD2DZOHT3y0bYfIcq8+nLBLh8iEl6b0mLDwM1k1RpZ/cu9Q3T29dF20f6Hun/bzGKmXzepV/z5RvwXSKW6fl7beNnlpfG9dMtR8dXzUMJcMUzrr906e0IxDWkykOH58mHrKyOjHDLxXaX+n1PJY9ZNL1m0kqJpevfe17f/5yqii7Rl8334X3pS3CXcK46sZgTTr3ZwD+1YLAjz/rpaaylZPtgDMFl+WzggwAjWCgOvXbgzqManK62SqUlWAwby+nxR0AV5xrO7S0B9khcuB+Ilbf4iPX9dx8mOpBJRLNw6zIzBz2bv2wMAQTChRl5gkXfHgK8ZJeqCokqJNHtdf7CEPcVFJAljhvf9haXveYWl0Uof3BqQfLfk1TSR12QslIZulA9lWCeciaEEKmr4BZNll03dMv0YxZ8UGW3CQP0jwi/5paHR4iCmB/n1CW4/b15nkZumXxvfWJUPVXceHwvD9ggzsZ4clrSrxS0QWxaWryxLNtH8f0sGCF6QfZJ46pvmHcZKnX/E+llJ3Lv30vHzPvrbdsj3DJz+UhRDOIXVmqy+fvuUKp3aDukKZMUYo94oHvaxp1rsum58ZAUag+hBgArD66ow1ZgQYgQog4DvNstSBeQWKlHmWrsF8uQfxvskKDisY0adrbCsIlLESSxEzr7w6yYAm8jayOk0YhvZskJZ0TVaR+oQZy3JhdWxzOAF5wRvZLltWlwaXAyO9rG1b7yZUHbAEGUSMSsboaWzPB0lLq5cSLvNGOzli8N7Od33uivVFk33f8jtYjs9fuUFcev9C47JiW1nI/4hBe4nzjx0qnnnNfhAI4tL3KykpUW5Sg/SlcurXkO8t4oQ6XZ6J6AYBDJIe76mPhDORrETC4NAefd9O6Ilv4geeQ5x837HQ8pr0C01L8XxtmzCKk1donen1RTpV6krvx7K3m8T0WcsL+gn6xqD+KR70rwQ5GKcuKoUl58sIMALZI8AEYPYYcw6MACNQAwhgI2qXUyeprnj1FOYbzJdzEO+arKBOQCgksUr0lbGe6ruaytogN/+/Xe6JNrJPY6Q2rLcwAc/Kgbj69aTR4tL7Xjbmg0miPmHGEjuX++aRA8RdL6w2ytPTDZJWKEslWR3XYfN9WjKKPi5LjEy6IU8QL+cJ0cvSAABAAElEQVTK056ve+K1gom1Kb7L74cnDitaruzb+3H3tq3EnV/7jLj2sSXisgdecYmPliRjf0BYemGyD2fbM5RIAcQZKfeyvO/c8S04r3x3swjd+2/Bmiar5R9kk8MPHCppinJfftIwgavPOslEhpH+VE7KJ40r8kNdu1wIERYSh/JQ49qI7uiHHmkVeN5Rg6JkSS27gLe+byfpgTxsy8yPHNytpY+g+JW8hrTtuPqp9eBKGxrPJSOtMNP7ocpGn4mxhckCNMv3SNWB7xkBRoARUBFgAlBFg+8ZAUaAEbAggImwy8FShV0hAr5Bui+8UFppT5isXC33YTriv5+MlnqapGGgblrGZ4pLfr4yNLRvLZq27KDofHUgADIBk6msHQilmyYd0kLSYMIP660s3foPtkbkn2kSiAk/2qbufG1rUI/OxkmlLgeTzOG9G8XSx+Od9gs5pZJuui5JnkGKbD9i/5LIP+TbtGVb84nRypJE+Lv2XEM7AfkXSnzSZF/dExbtOuTkVrLO2bn/TvHzRxYHbSuAduVzZDWpxgMBNfH6WdGyU5WwVOPg3kaGmcqpp9WfQ6yfKD+XVTXaM5Hleh7qs+9HH4qry3P9GAAS9fRps6OkSckb349Gk8cPEO3aLC86uAfn9KB/zIJ0JSziXkPbdqjckDrT6ytUdkj7C5VF8ai9+voHhJ992wtFfZjrPcpCX9Kbr4wAI1DfCHimtPUNDpeeEWAEGAFCYJ/GjnRrvPom68ZENe5Jg3lTMZMO4k2yQv3e2bTVSzD5Jmd6Xq4yYnLE5J+OmP0Zk1vsiXZgrwZ7pBJDQLbddPposa5pi4CF3fxVG8SZN88uy4ESmOzd9sw/xJQJgyKrNioKSIXz5QEBOvnpalv0/tAEHId1YNN9kJuqI5JicI94B9xARkQcSfItDw6HkJTq1mz4MCL4gevhg5pJJB/GPeUeXr7Jva4X4oNE0h1IK8pXD1Of0WcMkcvF03BoDy6SkAgIW14h2zjY0qr+aNtYzg6yFQQarnjW27wrP8g7sJckvQ1kuZoX3ZOFGvZItDl6Pygc+mB5bojzYWeT4RsrDJTts23r4unZ00vfiSzJ0LbQd+EKkigPLrRt+3SlOkO9mJxeX6Y4Jr/Q9mdK6/LztVc1rY3UNvUXWemr6sP3jAAjUL8IsAVg/dY9lzwmAvX2a1y9ldfXHGiiiMGa7jAoDbFI0NPV+jMN5vWDQJIO4kvFK4Tca+jQvHQvNC9bGTHx/vywnt5lg6H51Eu8Ug9E8OEEsu1zU59ykiI+GaWET310qcCf7ohMUC3HbG3L9P6g/8HfccN6RcQA2jqIBvihL//DnJV6ls7nTtJy1UUcORNnENgl5ntpUoFODSb8QJ76MH5pdbIDOoB/nG8CfW+x952+XNdUFp/fd48bIo49oGd0UjNZrNnSEAFh0tfXZ4aUE2XTvwHQxdTmffm9/ObG6DRdl9WiWs7Ocqm/iUxDHPTR6vtGetqW56py6d6FHcXRr76xhGyUVtIZ+T2x+KkWkWpbbvGs8hv6UQMEJ9oDtgHACgvqz+IWj+oV2KnO1P7U8JB7X3sNkYE46nuUpb6h+nA8RoARqG0EmACs7frl0qWEAH6N0wewtTjwIrjqrbxUbtfVN1F0pa3nMH0wn3QQnwaGPssL5IHlfjQpxEAcv/BjcI60mLihHejOVsYZMUkXXS4/Z4NAnogttYSYkMIikfYlRJitbVE6UxsFkaOSOWjDTy2Nd1ryphwtW4clYuieeISL66pO/IEfrEEnj99PnP6Z/gJbPcDam/AL6TNMeanpTHWk9iOm761JZhw/kH9UhpB0KgGhxlfLofrTvS8cZQfe+DM5+IPoIV17de5gilbgp9ZfQYDhwWWhBYssNW9XXIPoFi8bdi0RtBvfWCIO6axi4WtnmhoVeYyjI9oEtYtSlHXVq97+4ubja/8kz7avI4WrcrLUl/LjKyPACNQ3AkwA1nf9c+kDEMCARSf/kEwdeAWIqZoo9VbeOBXjm4zHkVVvcdMazJeCm8vyguTShGDvhvZF772P9NfLOKpvVxLLV0YgCIFL71sYHQihR9bbFsJNxJHeRtGfZ72/oa5rms84rCULwhbvOchWfX8/wo/KENJnUFy6QgYRF746Qv2c+7t5ckmn+xRfkh1yVfMP1V8lINQ8XOnVfNQ0KBNIDJBr02e+XnD4iBqP7olAA1Y/ftB90AqloX6acCZ//QrZLkd5I44vrk0OLNSwJBcYAi+V3KU0hAnyoHi2fSFtdUGy9KuvLWPckgfnexey0tFXr2obiKuD6/0gWXhPsMcrtnlAXelOf4+y1FfPm58ZAUagPhEo3mSiPnHgUjMCVgRCfo2zJq7CgGoqLwbVmGSUez8cTDpC9nKqwuqvepVdbYIsL3DypcthGZ6L9HelVcPQTg4bwCSgignfuxHA8kP0aXCutowwXxvFhBv7rNHSV3fO+Qxt+mh7Zor94N4FRRNyTNCBKznqMzBJD3FYVorlqVHdvdUkJk173pjH2bfOib5bTyx6Oxb5B0si1XXtWEjujJHh6h55pD9OkLU5nYBQ41F6vfx4Rjl1hzaHPTWxx983fjvXS/4hPQgvas9PLgknQn1ECcnWdVSfVbJNvVfjuO5hnYp3zLWvIb2Hpv0PTWMJIpVc+eph+OFAJ5f0tqynKecz1W9aOkbvl2Xsp4f5rEqT1DthZ3s/8J7+z1dGC+zNCqK3sWO76H0JeY98+vjCSTe+MgKMACNgQ4AtAG3I1In/ww8/LG655RYxe/ZssXbtWrFz506x9957i1GjRokvfelL4otf/KJo1aq+eWLfILOUXw/z2MyqpbyV+jU5j3XGOjUjENImYA3x8y+OEMdc/TcrbKvWf1g0maLImMCAoMEkDWQ53hcMyE2WH5gc3Hj6GPG1W2eL55cn20uM8q2n67B9OouFa0o/9KFaMUObMlmggsT59jFDRNNH26J9sfTJNJU3aqOSfLrioVet7Zji1vP1pTfMbcz0jl98/AFyT713xP/708tWyIbIg1bu+vpnIstMkEK2+oEA9TRZq0AtAOSBajXW0L6t3E9ycQGBOEfucXmOtCi8/sujW06LRZ93y+RPi/krN4hL718o1D3ubESemnWo5TuIl3PumFt0eq0qS79H/iDB0Ke68NLT4TmECCEyzSSb8ibZrrg4SAR7CapyTNapCAeBrG4j4SLq1Xjq98RlMUb6qle1TlV/6ANsgTHqR83D9M1S06Z5H/LDMnQMca7vPNLreKPfPHxQt4L3hPLR2wD5x7mGvh+h8VztMA1945SN4zICjEBtIsAEYG3Wq7dUW7ZsEV/+8pfF3XffXRR39erVAn/333+/uP7666NrY2NjUbx68fANMn3h1YaTrzy+8HKUFwNZfZCHfPXBdzl04TzygUBom8Dk4SeSGHE5335jy96W5IpcqqZOBjEwN21Mj0H/r786Vpz2q2fFq2ubXNly2CcIfOPI/eWyyF1WWHGBaWjfRp6+nJ3lWFx94sbvKfdBM/VvsI4KtZCa+dq7Be0zrg7VHH+oPEF3UYnvGkgT/R2HdZ/L/fTkg8RSSbziFFkbIeNK7wqj/gVxQJSAJADJaFo6PHPZuwUkFMkd2bcxWl6OstEPF6GkC+Xrig+5yDvUqWXy/fCoywwlQshCS3+f1LxJti8u+nKVRLVZp6qkWwjxZSL7Sb+5K96L6pl0NF1BPC9+q/jUaYpr+0GB8kC5sna++kW4q22Rfr7vPOKp32U8o88EgYvyqmFUfsRJw0H/kDL44vnaYRq6sgxGgBGobwSYAKzT+v/Wt77VQv51795dfPe7342s/tq2bSsWLFggrrzySrFixQrx9NNPi9NOO03AUrBeXb39GlcN5Q0ZVIcMxOq1TddiuUPaBNq2PhFMgsX0WcsFNpBXHSYWkE0WHRRGExYm/wgR/1Ue+Fg0WfOn2hUD5N9AWdfLpIUmuQHd9hCvv7PrmfzzdsWkFBNAdaKaRMeb5d5rWbg0yLUs9FJlTh7XX/z04cUl7R34878sKmg/kI93Hks+TXsSgmD4xeNLS643tRy4v/Lk4WJ0vz2LiAVXf4d0aD9k+YVn1fkICDVunPt5K98Ljj79jDFiwtDuLfHj/LAYl7gJtbyCMq646MuvfXxJELlLhJaP+MJ2EzrRDD3oewKcdOIK4eTQHl3kH+LZflCgPPRvFslO6wrcsE+iy4XWv6vdu/pMENNYjnvx8c17PSK/PI8RXe3QhSOHMQKMACMQggATgCEo1Vict956S/zmN7+JStW1a1cxd+5c0bt375ZSjh8/PrIOHDFihFi+fLn4y1/+Il544QVxyCGHtMSpp5t6+zWuGsrrG1TT4Lue2mm9lzWkTWySxJBrkhCCYXSan0b+UTrI1ifdrgkLpeNrIQI3P7NCTD1lhDjxlzPFe5u3FQYGPqnkH5JUA/mHSd8PJw4Ty1MgKlfIZexZuFIt67LQSZcJgt5E0unxXM96+6G4kKtbXI3p37xCotS+hfKgK0jFU8f0pceCK6yQfa5c30EQPOjnlkjrxxAHQgvkH6WDniCpbEQX/LEEG/FKIW7iEJ+muHH6ciK06GrDZfvOYos1iov2hDxhWa7/cHXQvp3lkuTWYq6HdAV2rh8UTN8syp+uaj2hPPghDTJDnGm5rp4OOoaScb7vvC5bfUbaatu72dQO1TLxPSPACDACSRBgAjAJalWe5vnnn4/2+kMxzjzzzALyj4rWuXNncf7554spU6ZEXs8++2zdEoAAoN5+jct7eX2Dal84tXO+1g4CvjrfJmdaF8xIvqwUSIH8O3Pcfs6N7THJUCczpUxYaqd24pUEllZT7vx7YvIvXm7NsYfIZaOLlWWjo+UJzlu27yjrXoSYLP/g3oUR2ZGkDFmnweE5aS9tzULnrElK3eJqTgb7e4IUMR2yAbxAyIDk9Lk1Gz6MfpCIQ9j4ZOrhIQSPmobKZUoHwlPfq43iY0yi9quqTNO9TloN6NZR/giwuYVETIJJaF+uElrIB88mchj+bWHu7HDIE0uEddehbWvndwjxCbuXVrv3n9W/WWpepnoiuagTcjreKDecTlxSfLqSLHr2XX3feVf6UtK65HIYI8AIMALVhgATgNVWYynou3Xr1hYpAwYMaLnXb/bff/8WLzVNi2cd3tTbr3F5La9vUB1nolCHzbgmi+xqE9FJjbe+UHK5sXG/z+mTDP3Zl57DmxGYJw8sKKc787B+4pD+e0WEyXS5fDakrrPQD0TB9z//sZU0yCLPEJmYqE85erCYeP2skOgcx4AACNT2IG4sFsRqEli8qQSLGgarsBAZdPozkSw2eapsE5GjWnup4bDaw36qJnJLlYl7HOwDQhPfZsgwHZKCZZrQFUs1QUqh70zyLTeRVvrS7TiYUFlC+nKSS2l8KyrWNW2hqMYrTrA1kWi+/glLx8l61Ke3LRz1ZMob9Q1/Wjpswhs4oL9wtQ19GbgRAM3T9Z1HnnCmPBGWpC1p2fMjI8AIMAI1gUCrmigFFyIWAkOGDGmJ//rr9n2CXnvttZZ4apoWT75hBCqEAA2qacBHauDZZjVBcfhamwjY2sSee7QteTmgihgmXl077rJ8UMNgvaJPMmB5YouvpuX7yiJwz9/XiL07tRMz5qysGPlHCKzd+FHUj+n9G4WX+wrLV/SrILAqqRNOXU3THSTLUy6HA0RumzxW3DTpEOE7TAQ6uazNXGGm8hBhYwpT/UDkgJg7+qqnxOnTZkdXPMMfTg/HSeomskWViXu0mTvOPrSlb3QtpYU8EE9Jl2raSCt9SXgoJmpZiHxS/ege7waIS5BiOtGKZ/gj/Pazmq8UzyUzetcS7geKfSPJ+fLQv1mUzldP2O7ChjfwvfS+hSTKePVZP5oS2b7zwAp9FP70PorCTPLYjxFgBBiBekQg3dFUPSJYhWUePny4OOyww8QzzzwjbrnlFnHhhReKffbZp6AkTU1N4pprron8YCV47LHHFoTzAyNQaQRoUI1BaCnWApUuB+efLQLrPwjbQ04/NMKllW1fOkyGdPe6tNaxxdfj8nPlEIBF1dm3zw2yrMpaS2yYr/dvDe3bRgcQhBAuIfoNlxZZC9ZsDIkaEaJT7pwnLjnhwMiq6AO5l6bPAilIsIzUp3F3sUouVfU5msTDYgr9PciJy+5/2ZesIBwE/ZZtO1p0f2n1+xHORHAVRE75IWpft70gJo8fIK6Q+zxecNeLYsEb71tzsVllIYErzCYQ7Ubfn1SN6yJyYO0Fay2TNZgqQ7//7nFDxLEH9Gwh/ijcR2DiFOXbzvp0EZFG6V1XF2mlp/Nhoscn8knHgdqmTvwhPXCFTjRGGT+wW8H+eT6ZvuW7uo54hj4qqRflcerIov6N9DbJgJ+vnijc1if5tgtI0o6hl943Qo5aXpCrPC4EUuwYAUaAETAjwASgGZea97355pvFcccdJ/7xj39Ep//SKcBt2rQRCxcuFD/72c+isG7duok77rhDtGvXLhYmq1evdsZ/8803neEcyAiEIoCBnzr4C03H8WoLAdsENqSUmAhhyR0sX0pxWMKmT7J9m7Tb8tOXrNnisX96CIQsq0wvN7sksoxRCeVO0voNJAzIhDfe2yx+/pfFwQSeKafvSHLmZrmPnG3yrqd5csk74knl/YAVG5ZNt2/TWrz85kaxYfNWcdiAvQQocBBzqzd8pIswPoeQf2SBiIk//tDf+8iD6LAeZck+3vGtck9HnbgMIf/0Qz+MBQnwRN6zl8+NYmK/O1gGm34cALaw2lKdSiS5DsxQ0+j3IGxs30oXcYY2Qn+6TNfzXvKEWjjoDhKKnK/uQBypS0wpXciVSKmQuIjjwsQkw0c+qWnQtkLIQpdM1HUcZyL1Ij1mzC/4cUN9p2zyffWEcB/etn1DoaetLdr00f2R3ibDFabL4WdGgBFgBOoNASYA663GPynv4MGDxZw5c8SNN94orrzyysgKUIWibdu24qKLLooOAVFPCFbjuO779OnjCuYwRoARYARSRcA1gXVlhIkQ9krCJBWTklBCxCYz7oTSJgdL1kD4gAz6uzzp8apHl9qisn+NIYDDG+bLPRCvfXxJQXtE+8Qpwbc8s7wk8g9w7dPYMVoud84dcwWI67gOZOkSeWjKhk+WhyL9tJnL44oJig/iTCeEaFmj6X0FTroV0KaPtouJN8TfvxCyrpbWU+dLAsWUl1oAxMUPCS8sf1f8xz3u5Y/AXLdIJFnAFktvsZwR5JCJSAKBOLpfo5i7InyvTBeh4yNyFq0NsxalMuBq24PQVXeUHljrP6ZQmOvqKqMpXdz4JMNHMOF7opN/SIty6W3ZJXMXbUqxzFebtaVND9M7pUt21RPauo18U+VcfuIwYz+Gts2OEWAEGAFGoDII8B6AlcE9F7k+8MADkXXfpk2bivTZtm2buOuuu8Tvfve7aGJcFIE9GAFGgBHIEQK+CayuKjalh6UNJkLf+O1cgf2stu3YGU3K9bhxnvUJ5Sh5mmxSB/IPe2F17hDPAjtpfpwuHwiAOAFZpRNOeD7pumJ/VeuQffJAHmHy3tC+tbSK26kmj3Wvkn+xEiaITIQQJQWxcfKo3mKAZikHYoLIBZQR7w+IjEvvdxNyJJeu6p5ujR3bGfcWo7i4oi+5RhKFOLH1ztmr1CDr/dNL3xHfOGJ/AQtD3RFRtHPnTnH2rXOK2gIIxIb2bYL2E4RsH2Gj91u6PkN7dta9gp+pLJQA1oAgsn1tNW6fDvlEWlFerqsPE1daX5jrBym9LbtkvSn3Aw1xqrWlGj+pHni/kPbUMX2K2pj6jrnwRryRfRut+x+qevJ9s6UsSO+nlzaT36gDdowAI8AIZIEAWwBmgWpKMtUlE0lFYqnvGWecUZQc+/5dddVVkf/EiRPFd77zHTFixAjRunVr8eqrr4pf/vKXAmm/973vieeffz4iAxEW6latcg+AsQR47NixoeI4HiPACDACTgR8E1g1MSYmIPt0yyc8Iwybta/ZsFlaLiyTFjbFJ//alu4hrW4VgUNAWkkzjp0JxvLYCw4EwIMvvaGqX/f3Q3s0iEVvNaWOwx6SEPtgy47U5aYpUD/MQJfdJC3dfA5jC1iVnS33pAMBXi2OrGtXrv9AfOGXM2UZdpUVZNKNXxklxg9sPglULdMy2VZ8+5Gp8XGvx9eXaTZ0aCt+8uArLfjBau/b0koQ/YqeVpetPk92nE4OomjiDc8I7FVocliWfe83xxVZWOnbB6BfIlLUJAd+ROQgT92B3GwjzQWiH0xkOXUH+bB8nLtifYvVnx6HSC/0jyA2fnDvQuFrq6Y+nYgptAWEQ291rIx7lFW3vkuCiV6GOM8+8pLask+mCQNTGpu1ZRI9TBansJTH/pWoP/UbZ8Nbb3N6OlMZ6tnPhDlhiL6HHSPACDACaSLABGCaaFaJrAcffLCF/AM5CKJPdQcffLCYPn26wNLfH/3oR+Kee+4RN9xwgzjvvPPUaM77JMuGnQI5kBFgBBiBTxAwTQJdE1iaoNKkEWJs+/1honrx8c1LJE3kH9Ji3y7THmOmSfZTS99NRP4hHywDHNWni5i3ykwAIE49uizIP+CYd/IvrbqG5VlE/hnInLTyyEIODkLZ8MEWcdTUpyTRVsiog0z61p3zxbz/PKYg61Vyv8R//Z9nC/xCH0wkDYgM9DV4N3Xy1ESeheZli2cj/yh+05ZtRcudoWPcQxBsRA6IM5Cbkz5pKzqRBlIQVmJwvbq496sjPF1WaVQu9Nkq0QT/UJJEJ2tBokWYSCKY9mTFKbmdUz5VmnTH1Ufc+cJJFn5AirPUG21QXWLsy0cPx7cVB/6AXFYd2voe7VdG21KobQvvgg1vNT3f2xEA5jphjdh6XdolcAgjwAgwAvEQYAIwHl5ljQ1LvFJdr169ikT85je/ifww4Pvxj39cFE4e3//+98XVV18tsEQYhGAcApBk8JURYAQYgTQRcE0CTZYf6q/oNKHEEhuX81lNIO15Rw2KJnlEKpJsXW6SvbNUGfVG/g3uvodY8vYHKgR8nwECIHWqzV3z2GLxrjzVWyf/qBywjvzrorfFhKHdIy9Yz2LJtM/SjNLrV50cQTgm65iYZ0H26fmHPJOO6H/UPkh/DpGlEjmwgL7ur8uKSE5gPKZ/ozh++L5yqfOKiByktoQfRVyOdPX1r1h+rf+YEkKSIA7IReqTQU4RJvhuXPHQqwX1pn4bXHonCfP9IEV6uWTTty7OPo+Qh7ZJ+yfG1eNF+WOTTv6RjpB76q+fKzxMRBLAN50+WnSRy+STtDnINtUb/PW6xJylFp2LEFfrshbLzmViBBiByiDABGBlcA/KdejQoUHx4kYiYrF79+5i3333tSbv0KGDOPDAA6MlwIsWLbLG4wBGgBFgBMqBQMgkUN/83zTRoomoTWdfONIhjmvCQ5OaHUnW/toUqwP/f//sAPHdPy6og5JyEeMiYCMmVDkg3IkARHzfkmk1rXoPMgvvN73HIJVggagfzKKmKfe9yUouiQ4gSoEVsMNef0cO7haJ0S0cSfac5RsE/nSH+Ni31ETQQleQUSCmcMiNy009ZWRkVabG8ZEktkNzQCTC0q/cFlY2i0oiHdWyme5t3zpTXJMf2ivabxw9kKdvr0wieylPPH9OWuQ+cdGRRXVGcVxXIjlVQh2H40AXdYsOwq0Wl8P6CHGqSxeOHMYIMAKMQBwEmACMg1aNxG3Tprnat2/ftX+OrWg4DASO0tjisT8jwAgwAlkj4JsEktWDi5iDji6rCEz8EQ6HSYc6MYk8P/FHHjZnmtTY4rJ/IQK/fXaFFffCmPzECBQjoB5WUYr17aH7dxPzV20Q1zy62GoRVZx7ej76FgO65OHyECOcTlyqwxJpWEmqRCmW+V5yfLIfoE3kH+Th0A8smzb1p2oZ0Oea+lYfSQLiSt97EXmB+MP+hLZ84U/fDVWPNO5Vi0roTz8ahch2fetC0qs/YoXqgTx1DEPyQtvBQTV3feOwkOgtcWwkJ7Yo0B3VJX7gqzWn1pWpbL5wUxr2YwQYAUbAhQCfAuxCp0bD9ttvv6hk7777bnTgh62Y69evFwsXNp+cR2lscdmfEWAEGIGsEfBNAn3hpB9ZRZClC/njCisWTFQ3yj3FYD2CCanqyBJB9VPvbZMaNQ7f2xF46Y2N4lsTBhWdPGlPwSGMQDMCXXZv02L9Bx+VDIyL0S8eXyomXj+r7OQfnT78+68dKkCc2dyCNRvF+fLQkQ2bt0YEVpKTQ2mJtEr+IT88X/5A6VvQkO6Qd+FdL1pJOIrn6lt9JIiNuAJxNDPmlg/ow0EKJsGUyqJeQWjiNGoTsanGwz3lff+LyQ9+0klUkkkkJP3Apecd+v3U0+EZ301gFsfFJTmJrI2TRzXEpR8kTbrqdWmKw36MACPACMRFgC0A4yJWA/G/8IUviD//+c9RSb797W+LBx54QLRrVzjQxMDwW9/6lti6dWsU74QTTqiBknMRGAFGoJoR8E0CbeGYAGGyoU+AbHsKqdYGIUuKVUzjTmrUtHzfjMBlD7ycyBKlFvD76b8ME0JudTVt5nKx1DChHj9wL/Hhth3yxNXiJZi1UH5XGY4YhLLvLNqXDmmwO9idkjRTHQh+/dAKNbyS9zhxuk2rVtHBFqQHdL3uy6NEn64dIzJFJ+YoHl3RT02Qyy/VeESihSyVdC2RhhXzIGkJvVT2m2k4femoKvOn/zpMdO+8e7R8eF3TlmjJrt43E0mCMusOpKmNAETcO+es0pMUPKvfDZP1dhxMCwTHfDDl7RKBvqBt61YFxCrpSulMMimO3kZUHCh9nCu+ryEkJ8lMQjjGzYPyyvOVfpDUl6lTPeVZd9aNEWAEqhMBJgCrs95K0hon/15zzTWR9d8jjzwiDjnkkOiAjxEjRojWrVuLV155Rdx4443i2WebT87r0aOHuOCCC0rKkxMzAowAI1AqAq5JIAbLpsmHaQIEYgCHiJqWGpGOZG0AmfRHYa5rkkmNS149hrkm87WOx389vLiAFDKV9yNJANaKu/CYQWLqo0u9xQHZsVPSfLZ96XAm8GX3vdxyOA/6ilaSYLvv3HFFS1y9mZUhQvOJ04X1CCLvB/cujE71De1HVPIPaqPfwgnP500YGC05BQ46mUbF8y2RBvlXDgL1ztmrCgg8Ij5UgspFkkw5enBkrUnl0q+L1zYVndpOcUAewuFHIjidhIEfMIV/lstPkb8pb+RvcipGsLxDewGBp34DbTJt5XF9X/HN3Azy3XF4UFwCMW584JAkjQk/+Jl+GLS9KzYZafmHLtNOKz+WwwgwAvWNwG6yA2z+6tU3DnVX+hUrVoiTTjpJvPjii86yY+nvPffcI0aOLH2vGTWj1atXiz59+kReq1atEr1791aD+Z4RYARqDIG0BtsmQk+dDKmwwZL5NJxaKJcnJXG3nzU2WrqFtKH6YzJ29FVPJcmO0+QYgYGSSFmWkjVUjotZdtUeO/+zRaezmpQYK08bdZEPehq9T8DpwLOWrYssK/W4eXt+7IIjIpXS6Ed0HNSyAhNsd+Bzw/ftIha88b4vmjXct5+hKSH0thFuOuGFvhnLtV0/HPzPV0aLGXNWFljLqfkivylHSSLxhlmqd8E96kUl2AoCS3yI89247AsHiDPGNW/l48rWJ3P6GWOiLS5U0sv1fZUfwejAD510hg6u+rLpiHoL2ReS0ifJg9LqV1c5VeJZT8fPjEC1I8Dz72qvwXT0ZwvAdHCsOin9+vUTc+bMEb///e/FH//4RzFv3jyxbt26aJK75557ioMOOkhMnDhRTJo0SeyxR/OG+FVXSFaYEWAEcoFAmoPt0F/KkScsYZKSfwCONrSPo7/LiiIXlcFKJEKgjVxqxy4eAqP7dRVHfaq7+Jm0arS5/134phjeu1H8450PxPJ3N9uixSL/IARWTlPunCcuOeHAyDqq754dRZvBe6dOAOLE0vek5d5CuSdfWg7WXOP23ysV6zubtRd0hVUX+lP0by5XCvkHC7v/98+fEr/461Ir+WbKG3qDwDIRbrpFNgisy08c5iTvkAaE4tK3msRFf3ixiCxEfiZiS9UN9WLSR42T9D7U4hPyx8v9BEOcTybIN5Bq2OuWSC/f9xWn/eLAD/W7SjJCdFLj2Kw6XacAq+mT3oN4NFlbut6VpHlxOkaAEWAE8ogAWwDmsVbqQCf+BaIOKpmLWPcIYKCNSZxpwgVw0vxFXwU7rmWBmla9hwXg+IHdrFYKNv1NhKEql+8ZgXpAAMt2L5PETBqWbGngFdeK0JcnLKgmDO0e9XFpljFNC0Aqg8167Z55q8QFd71E0VK7NnRoI5rkQUrk0BZA+Li2XaC4dFUtsMnPdnX1+Wo/7bOKs8mHvw1DV5rQsFC91LL4ZGchk/KEbBCM+rJjCo97hbw1GzaL7TtFtBck5H4sLfjnyZO44Ub321O4lrPHyc+HS5b1HEdPjssIZIEAz7+zQLX6ZPJP2tVXZ6wxI8AIMAJBCBABl9ZphkGZfhIJJBgsDI65+m9F1hYkh6w86Dmta1oHcWAS4pJF+us4d5aTX1ibYCJx1vj+aRWL5TACZUOgdSscq1Gam7ns3WhVAUiLUhyWkKbhsITYdbJu3DzWNX0UlY+sfuOmN8UHUQYrM5/1limty88m76DeYdiCPDU5WGvp9QuMVfIP6dAW2sg2BdI01MXZ742syXRd8AwLN3I2HCic9gSkZ7pCTlbWf8gjpA3pZSHdbFfItNWbmoa+Y6qf7x5YuE421r+JeHa5vRvai5tnLY/GDKdPmx39aHDqTc+L7929IPoDwY7xhM9a1ZUHhfnagC+c5PCVEWAEGIFqRYCXAFdrzbHejAAjwAg4EDBZodEEgpb7OJKXFITBvmmJjUkoBttpT6zSGMDThA/kqcvBmuCKB18pWN5GOKNcg3s0uJJzGCOQSwR27HRP2EOVXrvxo4iACe0PdLltW+8mfj3pEHH+jPkF75geL/QZyzxH92tM5RRlkBMPL1wblQ8kU9IyqrqDyIKLQ36p6W33NnlEErn2VwSJdJOsA7181M/he0IWYdg2AUSNyYFoOm5YT1NQkR/1v0UBDg/b8lUio/BdoG0dbGL+5eB9Rfu2rQuWnFM5bWnS8CcCU8eYZIMEV5fqkr/rCpmTx/UvKIstfprf4bhjD9t4QV+SjfYDfGx7Q9rKpvvb3gWK5wuneHxlBBgBRqBaEWALwGqtOdabEWAEGAELArYBNQ2gLclS83ZZzemZZDHYLlUmLFjIasQna9rTrxUREyrOo/o06kXO5LmhPf+elwmwNSJ02D6dK1ISvD9EzMAiFss641jFgrCZt3KDuPykA6WcdNr4NrnOcNpXD0kFD3rX1TLeNnlMdOpskgywRBZk2t6d2sW2VhzSo5MxS+z1B2eyBAdJdNPpo615oS8E+aeWD3WIugQRA384sghrk8KsQifciMAz6R9lrv0jXXAlS3RYkMGyDOSkywr0sgdeiQgzEG44OEQvp5ZVqo/AEhaSJotX7Lk3adrzUdsAHqFuYPewH6B837nQ/JKMPeKMF/C+4f0oxbmsLZMQz6XowmkZAUaAEagEAil8qiuhNufJCDACjAAjYEPANaBOYwBty5f8Qy3wshpsuwb4pKPrCsuDdU1boig+WXNWNO9RpMtrwfkTix49PO3npi279ttKWzbLqwwCWEqehjvlkH1xjHUaomLJ0N9vImbGDYy3JHj+yvXylNdnJJmTTht/6Y2NYtV6+4EjsQopI7e86/IeZfzs4O6R1aKLaHLlgb3Qvi0tHnULKFcahF35f0YULccd1bdR7qv2cbSksmVp5a+eFRs2b42WL4NMeUme8AviaUz/wh8rQETh0Aci+ZAH1SGucCo5N18Stdc98Vrkb/s3qm/XIh0pLpbfqoQbZEMmTvglAg/XU+XJ7u9L/X3ORkYBV1/dgHDDqcFUTl9eaYXj260esKHKxSnHcZfChhDJ+nuq5hn3PsnYI3S8QLrEjU/p6ErWlii36vBMP/yp/nzPCDACjECtIZDO6LLWUOHyMAKMACNQxQj4BsgIz3JiE2JNkOVgmwb4+nIqTPpCJ9VzV6xv2XQckwKcKPrkknditQpfPcQSxpHrDoGNyiEKpRT+rhfeKCV5orS0ZNGUGBZpcd7FBxesDX5vkR9ZO7pO5v39nFUm1Vr8OkmL2k0xSHW9T31n09ZYOrdkLG9elAcfgFSM66Az+qro9HO53yEcrCd1B4Lpcz9/UhworUKxNx859Mn3fnOcaNqyLehwB9NST5JlukL+ILklAnTU+2b6HhDZCNm2PhfLlT839akiclLP00VG4TswfN8uwnXCMRG7WX4rdZ1DvhnQK2QpbESAeohkwl3XI+mzT3+E40c11A3uMVbo2blDrOxCxhc+gWhnsGClpeuQWc569unH4YwAI8AIZIkAE4BZosuyGQFGgBGoAAK+AbIvvFSVyWrONImFlcfUU0ZmPtg2DfCx0bg+8bSVVd3fC7IuOeFA8aS0PonjMLEBGckuHQSwBHTfxo7ilTc3piOQpTgR6NS+tSTBdjjj2ALPO2pQgeWYGq9JyhzcfQ/x3D/8VlxIB7IgjgPxN6pPF2eSRWubnAQQyL892rUWH2wNKz+WKoNwofe9lGWKUx9d6tTdFgjLQexH6trPj9K+t3lbAfkHf+qvbXusoXxE3KBv+8lDr7akIbm2q0oIm/pmlXwhyz3XDy4g8M6+dY646xuH2bL0HqTiIv9IKEgqVTfyT+uqYorvcq9AMiyEnHQRoNB/ulwGP+FTPVqsOImQw/eb2nHccvrGFg3t20bLsKmtQT5ISBx+o5LRtnwRN836gKw05dn0Zn9GgBFgBPKEABOAeaoN1oURYAQYgRQQcBFwaQ+gTeraLPDI2gATwHI5fYBPv/pjsozlaq7JMiYpZGmByVFcd/G9C8WZh/UTh/TtIl5Y+X7c5BxfQwBLQN//kMk/DZbMHnXyL47Vno0IIHLnuX+8l5neEDxvlf99AwHUsV0rsXnrTqMuoeQfEmNvOerfsHR7+szXjTKz9JRbGwYTcjY9bMRSXGs/Xb6JENb7ZkrjI64oHiwZQbQSgaOTaXEty0iuerW1YzVO0nsTprCOxcnK2AvS51QrdVNc3zfr2seXikE9G8QP5HdKJ+RgpZnkO+0ae6Bs1z6+pCAv6I286TRpVQ+9v6H3C2n0ui6FtIQ8dowAI8AI1BMCTADWU21zWRkBRiC3CKQ5oPURcOUAwWflUQ4dbHnQxHNEn65ei0CaECeZCIJcdBGMNv3YnxEIQUCfIIekccXpv9fuom3rVmLp22aLO1hd4VRe30mqmKhjQq4ur6MJeii549IzzTAb+ZckD/QV+MHg4uMPsO7jlkRuSBpgjrpJw+lWb0TaquRM3Hzi9J8+4krNm3Q1kWnAJNSyTJVJ90hP5CL5pXW1YQqrR+iMvH1461bqum4+zLGn4EnXzSpaqk7t2GYJquejPrvGHlOOHhzt56jGp3sQntj/8eLjRcvSYGCv9iFUF7a6Tkpakg58ZQQYAUagXhBgArBeaprLyQgwArlFIIsBbV4IOCLb8gg+MMJk/YnF7qW9mGSOH9jNOikbu9+eTPTlsYJrWKdLPv8p8e+fHSAef/UtcdatL6RS0uXv+q1cQ8i/H04cVrTMD+/I5HH9o1NZU1E2p0JAnhw3rHn/vXKpCLII5AcdXFRqvnodl0raxiXSfMSVWj7EtZFpqIvR8tARbDsBsiuOQxoQVpCddDmsKz8XplgKi0NZvv/PQ8VFf3zJqTvKiNOBsa0GkeyUL559RKJtT1zIVa0rSWbIFd9V6A8Zi9ZuFEN7do70mLnMbdWI7+zh/5+9N4HXqqr3/xfzYThMgiKDAsIRFRXFQxmYptg1/aeUJZZhqFmWGKXd22D3pv2v9fOWpjlclSuYWKb9LBs0b2kOQCl4UIYQAZXhyDwfgcM5gL/92bge1rOeNez9PPuZP+v1Ojx77zW/98Oz9vrs7/qu4emiq/784LrX0lo/ShuZhgRIgASqmQB3Aa7mu8++kwAJFJ2A74E21wbiAVp/qM61zErKj6XAviAnxJhkY0KlBpxD2GAggUISaDlwcNnqUb27FLJaa123XnxiaMGDib++pBCZYAl7zSPzBayWKj4UcMNl+MWE4ArRpU+3jt7dbaOw1y0J41jk6eXj9xG/m3GCFK58eVA2xjeXmNaweltKQIOod9OFJziL7dzh4LQIgiF2H8bSbrygSzr4mKLeH/15qbj7slMzxhy9LbbdgaU1HvqdTfC10VYmeKH9+PuvZ95MHdfWuF1/RBF+Xfdaipa2dvE6CZAACZDAQQK0AOQ3gQRIgASKSCDKAy0mOQzJEoDwuiDwE/ajp5d6C8ZERk5kpQ9BTI4wYcG9gaUEQ+EIHB2IXqu2+oXbwrWo8DWNCHZTxffur4EFYCmE/j0P/V/ARLyaw/+d795hOEk28IuJZZwN3x8vvunZ8TVqvXjhoVq+RRFmZNn4nYTlXFNztJ2EZT71UwpX1/6ywboxhPw9Rr6oQhWEsk7t3XYPe1rT/UHiu2yzLAMjjN9yLNAt8NQ+6cdRmKJuiOkYcx6bt9ornpvaCmEY1oHjY25ghfZGaaPeL9cLTcThvpl+H2AhLO+jylFn7HthhzL4vKTfFZ6TAAmQQDoBCoDpPHhGAiRAAgUlIB96bZXygdZGJvvrsFCY+uh84dplUi9dnVxhgqFOMqTFimlio5fD89wJQPyD5RPEj3wFWLJ1aCfE5BnzxP50TSBfVUYut33bNuK/X1gh5q3aHjlPvhNCNJq1fJNYu92/jDjfbSlm+d1r2ol5K833BTvhYuMKW/DF2/JhGecvX1llFFZseVzX1RceEJAO69ohtDD0WcLh/8zZIw53FR05DhupwB+lKUAsUv3TxRGqwD+uywb8rkNsx++8FPxgzXbHX99MG0OkKAlmvhB1zJB1jz66t6/IMF6mV8enoX26CNt3y+ZHFH1Ry4hUeZDI9UIT4+2TXxubaqcsE22AhfCkB+eGlyRHnEB8VcdV9MMV4nwXXOUwjgRIgAQqmYB5dK3kHrNvJEACJFBCBHwPrL74EupKWTRFWijEEf9kx+TkSp7LT2mxgokLQ2EIQPzDDq75CCcO6CGwY+X02StLTvxDf/cdeL8o4h8m6qbQOxCIIBphAl/JS3yjLKXc2bzfhCi89pXAZ2NtIGyZAgRt7JQLEe3hK+vFDecONyWzXsOO5nHDsUfYLcvxWwfxZcfuFnHO7S95l8Hity8p8Q/9cAlJEItUq+tQ4ApEwagBLhv032rfvV2xsSn8jsOSDt9zLA/WxxDJLEo74owZeAkoBcMoZasvFSHawkeoSXgGg99PGZvBAtfjLtuW7VLrltfUz6a9raF4iw0/8D2HoKf7IQRHvKDTxT+Ug37YfofQ7mxES7V9PCYBEiCBaiBgfhKphp6zjyRAAiRQAgTkgz0eevXAB1qdSO7nmDiaWEct2WaRCasPTN4vvneOmB8sLS6n0K1Te/He3vxZ0+WLRZI7uKptXPTuDnHptFe4scsHUCCOYBkhfMxdOWNuxvd7667kfaSp96NUjuE/7ufPLc/69+OqhxusXYGgrVpAnVkXz5Ju/Y5ma9m2CIhQd3/uFDHl0deMSfA7eVEgdOkCjZ5YCkb6ck2Mbagjm+ATkuTvMAQuCEVxdlsfdnhtKEJhLEA58iWba5ns9DkrI9UBZig3ihCFMQOWjH9bujEUF22c0D4pGJpEMT2f9FkrX3aZxjvVitLk1kIvM+q5ZGlLL+MlH5Mwiby6uKqWh++jbsUpv4NqOh6TAAmQAAmYCVAANHPhVRIgARIoCAHbgz0faJPHj8nit36zIKeCj+xeE07w5MRRneRi4ldu4h+sgN7cQB+G+pcijqCg5y2385MCgW+hZZdU+TsEMeHqX8wru+93kvfiO08sFLd+5mRxRrAj+A+feiPJotPKgmCzqwCC/NL1TeL2YBmrK6zc4va1ic1fJtYfFVoIwgpUFZvkdyfKkli9DVIo0q/Lc8S7BC7UaVqyjDZJ8Qmf8hhlIU5tv6wrXD4bWB1GDVKctKVHXXIpMfoBa2Nb3dIyEXmkYPjruavEd3672FZ8sHS6Tcjmb4F/UFN/kFFaUcr+qyysBWsRej8wFsZ5oQlO2Ybrzh4WCrdyHJb9yLY85iMBEiCBaiJAAbCa7jb7SgIkkDcCpofhqNYP8sFetUjgA22ytwr3B9YTcATvCza/SGcM7yNuefqNtEmVOsmdH+w4WW6B4l9p3rET+teKxm3NRhEj6RZD/IPIccXYIaJT4PhwU9NBa7JTj+olhgebjWAZ6Nm3vei1BEu6XaVWHv6vYOmnZx+JRJoNy6jRR/cSDavi/aYc269WvBkIe1HD25vdAp+vHPimk7+tutiEc/zmqv769PKQN3xx8sFv5+jgO3dMIMxFEZKQT69Tlg/xLxTuFJ+L+K3+2cRRxhc4thdxo4/uKTbsjGdd6RIvpcWi2m60Czs5m3bPljv8quPMaYMPk900ftZ26iA+N+1l8fLbbtHyL/9cF+Q/MmQd9VlFPudgSbRuFSnbiOXDuqWijFMb7OKkpjMdI28U0VK2VwqF6gs7U7m8RgIkQALVQKBN8OP4fjV0lH0sLQKNjY1i0KBBYaPWrFkjBg4cWFoNZGtIIAYB20M9HoSzsX6IUXXFJM33gzomi64lXhKkbTKG663BbhCzV2yRSVOfiMMkN8pOjalMPCCBhAl06dBW7NZ2MY1ThW41FU7aA8Hk6pkNkZY/xqmLaf0E7vvCqYEfyneM/ttsuZ/95kfFd3+7sCA+IiGwPX7NR0JBzfXbCn9vphdaGDdNO/3iRcvdnz817KJNSMJ3FZvOyGXTJh4zrxqTZiXWt7aTVZhSx2mMFSaBy1SHfk2OBfp1nGOM060kZTqZb8WGJnFDYKVuelEl07jKgTVhsF5YvBCIr1FD+P88wrOK6TlHr0O2EdfBUQpvpvvv6wdESVUolXWpdchrpk9Te6P21VQer5FAJRDg/LsS7mLufciPB+3c28USSIAESKAsCOAhVp+koOHS+qEsOlHkRuJBHRMj6WAdnzjH9aSCb7kRHMk/ee3YUMgb1KtL+ImJKyaR+LzxguON4h/ah3uNyQ6sVxiKQwC7r1Z7yEX8Azv9/xu+1xBYqmk5dCl9hzq2byemBEsdowaIG30DFwU1HfO/uAdW0tO+WB82zffbaorHuImNHkwvVGYt3xyOqRDl8GJF/R3GuRTrfBZk0kpsXLBkO1DfxOUPvpIhKJnGaViJPTZvTezvvRSXbPfLtbGJHEMg3pnEP5QZpgkEQmmtiPrUgPNvnHtsLPFPlotnGFewPefoeVL9CCIg+p0x/NCSaz2tqx93fu7UcCMSUx+jbFBia6/pfuvt4jkJkAAJVDqB/D8lVDpB9o8ESKCqCUR5qDe9/a5qaErnfQ/qruVjSjHeQ99k8YHL6zOsVHDf5L2DtYkrYJKLiSasVzCBZSgsAdfuq4VtSWXVtjDYEIWhOATwEgRWdlFCKD4F1poQcnL9/akL/IIuc/gFHXxYF/GdT4wIlorvFd2DXY19v62meIybro0epJAkf4Pl77DKIsoyYZMVmFoGjtW6MB7hHH9xgvSF6MpjEkLV9Ij3+X6EdeDDV30o5Q8QL57Wbt8d7AwuQt9/S9dl9/9VZaC2SR67nnNkGvmJfpjul4xXP6XIa7MWxPgv4/oF4jZEw4WN28PvnGs5r6u9vr6q7eMxCZAACVQiAQqAlXhX2ScSIIGCEYjyUB/1YbhgjS6higr1oB5lsojJH9qDe4pJqzrBME1iVYzYeXH2is3iho8fKwIf7M7JrZqPxySQTwKTxw4WDwU7mDKUJwH4ArT5JNV79E7gzy+ucKWXgXOIf7adweH/EBuDXPPI/DArhEf41cPSU5Ogh3jT+AfRyhdMQpL+G30HRM/HXk/rdyiGBktabS+XTPWiLtMSYVNa07W+tTXhkmR93FDT+sYQCFw3Pmnf3ANlwToQIq98MYY23/LUkrT+q3XGOdZ5q6zXbo++YYevn6Y24Tti+p4gLa6b7o28z9IiVC0XfXEFva+utIwjARIggUojQAGw0u4o+0MCJFBQAr6HXV98QRtbgpXl+0FdncRMPacuJKBOkuUkwmQpIuMwwcASYd2pvMSJCTqsdWRAvie/NlY07W0Vzy/dEDhLXyWj+EkCBSWwuwC7yRa0Q0plEJ0C3T1nizelyJI83LqrRYwZ0tu5JBW/aUiXVHjP8L3B7rJ40aEG1As/fm3bmj0KwW8qflt1kQYWa76gj52u32hYI2IsQR68uMGLnGcWr4ssjGF3d5MrD18bEW/6/Tf5//W9hIJ1W5Tl9mAOqziUl22bTf1SeZtYm/Lo18YNO8wq5Olpo57bhFxwUMVQtTy1L+p1eeyLl+n4SQIkQAKVSIACYCXeVfaJBEigYAR8D/W2t9oFa2CJV+R7EPfFu7pnmsSE4lzg66+puTWcLOL+YIIBAQ8TCjXICYbc1RDWOHqoDZbA6RNvWQ6sNFYH1jIMJFAsAo+/2lisqvNa74CeNeKqM4aGlmqLg2XK23Yn5y/U13BdCPPtvIvlodgtFwIVLKm+/cQiXxUZ8Xtb94tHvjRG/P9/XCJsO3fbfMdlFBZcODZY5msrx5T+qF6dxeptZquqOW/Zd5uFjz8p0uB3FsIVdkt/c/1OUzWpaycP7JEmJEURgfBbjt980295qmDDAcYE+N6Tv9uGJNZLJutMOW5IKz01M15CYbxQ7xXqx/W/LFmvJnUeyxdn2bTZVDDaIJ9VbKxN+fRrEDGTDlFXCaDdKQv+QNCNa5WadLtZHgmQAAmUKgEKgKV6Z9guEiCBsiAgHVnrb+LxQB3FWXVZdDKPjcyXgGqbxGDChAnYbZeMCi0o0DXfBGPi/f8QS9c3GSk0Ne8zXkc9mOwO7FVjjC+Fi/171Ii1O5pLoSlsAwnEIvDu9mbnDrCxCouZGFZw0yfXhz7X5AsK1y64EP8gruAPvwnZBAhG1/7ytYyNWrIpC3mwy+53frtINKzKfKlhKtMm/pnS6tfwW/j6mu3ip/+71Ljph54e5zdfODLtsu83OluLOFhWTqwfFHCwi5iyIRAl0a5uwUsfCHD4HqiW3zIdPuXvvxTVTC+jUN6/nneseHDWO2LCvXPU7N5jfO+kCOhN/EECk1iJKPmsIgU0sED7swnwP4l7IfudTRl6Hl8/EW9aIgx/vLBIVDeakX3V6+A5CZAACVQTAQqA1XS32VcSIIG8EPA5ss5LpRVSaL4EVNeEEZNpTNjlZMA3wbCJf75bgHL3v5+8RYStXtSUvkDPlvLgdYp/bj6MJQEbAfjCww6nCBBO8FtiEk1wXRVDXC88bHXJ6xCRkghymWbnDuZlu0nUoZfx779bKBatNb9E0dNCqBp1VM+0y77faFjPjejX3XgP0gr64GR4IMb26tIhXHIbZdktBN+zRxyeKgr39KVlG1PnpgO0Genw/cCOx7qPRIxDX3/09QwLclNZ6jV8p/A9Wr01unW5HOvkUmmIl7BkhZCINsaxnLxq3GDx4OyVapPSjiEgou8oG+2UVoFSYDTFpRWgnUiRXbucOu0X+EHUX8AiEmIk+o1dpGWd6v/FVAE8IAESIIEqI0ABsMpuOLtLAiSQPwJ4uOQDZny++RBQ8cDvC5iwY+Jw4wXH+5JmFY+JSxRn91kVbsgUR/wzZOclEiCBiATufv4tcfKgXqFvO9tLDFh4YWknhA8EuTzR5Is0YrWJJEN70RbVMiqRgh2FRBX/UAQstHUrMp8I9F/PvOmoPTOqU6Dgmlw6ZKY86ONPFf9kGp8fQ+kvccGaHRninyxDdx8hr9s+6MyhswAAQABJREFUIWjdfNEJAlbprvYjHcY1XfjCWKs/o+D7aRLQbG0YO6yvUwBUl7hL4RFl6XXION0/pF6vTzTHxik2Fhjjb7zgkFivl81zEiABEqhGAoV7/VeNdNlnEiABEqhSAphUYBI3a/nBpbByEuzCgYkJrGr0CYorjy3ON2GU+UKrnaCtmIwkGVAe+tG/Z5cki2VZJEACJUAAVmMQNGToHiwLheBy0ydPCP3r4TosvLC08/Lpc4Plyq+EVseTHpybWu5504UnyOwF/YRlVJQlrwVtlFaZ/gKnb7eO4WYbWrKsTxevdfsgVAuWgqR6DcewAnUFWNhh3PvBH9w7+7rKUOOwXBm7Hk+45+9WwQvppbAWdTx1Wcur9cuyUX7U8VK+ZNPFP5Ql4/Q69HMpsMNy1RRs4p9Mq3+X5HV+kgAJkEC1EqAFYLXeefabBEiABPJEwOTvSE5KfG/7k2qSz2pArWfdzubQX+PVv5jnnFipeVzHsq9Ig3b4NglwlcU4EiCB0iQAAQMvOUz+x9QWQ3DTA/LuMuy0q6eLct4/2BBlbeATsZKC+gIntFB7LP5SWRsPWGZCnI0TICLJF1Noz0FrTjdz9AHp4tZlaxdE50mBmOyyGtSXKtvKktfRl6hisBzXpCBnEvVkueonvuu2IP8PSba2dBDYW7QdqG1p9evqd0mP4zkJkAAJVCMBz/urakTCPpMACZAACWRLIJysBZYx+kM/zlWLmWzLj5pPTlKiWCpgggBh8rpzhkct3pgOE0v4G8LujyhPThQvPW2gMT0vkkC1E+jasV1ZI8AS/6hCiN5RWC7BqiuXgN+ZbMS/U4/qZbXiat82nt9SiDNJBuzeiiCtx98KRFZ9PMm2PowH+gYjUcrCcl605/XV28ONP+BDVl3qqpeBeiBq+azPsIt8nLDQI1zC6jBqkH7/XP1AWdjFWh3XcA3fO4xzT147VmDcyyX4GKFsCKlRfDXq7ZD3Qb9ejud4noi7qqIc+8k2kwAJ5J9AvJEn/+1hDSRAAiRAAmVMwLWcKOrb/qS6LycpKzY0iRt+s8BoiaFOEHK1FMDEUloymKwgk+oXyyGBSiGwq2V/WXcFfuByEaeu+MjRYl9QyPxgl9y4oVundlntCozfvOFH1IZWz7p4CUEyrtCy07ITetz+ID2WecLQS91V+aQB3bMpKi3P0MAS+/vBEm30HQGfUe8bNiWx7fabVskHJyj7jktPCc98Y8p/f+HUcBfgqG0x1adeQ33yxROENZyrG3HItLYXdTJefuL70L9n5/AUefBiTQac3/nsMuO4KtNE+fQxQhlRREL9u6vehyjtKMU08l6u2Ngkps9ZmfZ/U/YPzzkMJEACJBCHAAXAOLSYlgRIgARIwEnA96COeCmSOQtKMHJYMNl9+KoPZVjqyAdoWZVv2bBv6VjT3oO7dOKhfcqv5oe7EMqy+UkCJFB5BDY1uZeB+no87aW3A/Ev3nJUlNmjc/tA/NvnKz4jvmew860Up1IvSAILOykW4RN+CgsdYGUGq8QfPf1GhjC38N3o/vrQbljByQ04ZD/eDizIIOKNGdxLPHD5aUbxU6ZVPyH+uZbcqmnRh9FH904b31xjCgSrscf0CUTPvqFlV3gPuteIWwwMUA/a7vJ3h/vZKdjZGf1UBUU5zqlCketFnewT+h4uO/7g+6CXE6UMlIV8CGqbwgvBP4iL8jzgEwnB5vGvnH6IYyB8RilXtqMUP30vEcETAj4sMRlIgARIIA4BLgGOQ4tpSYAESIAEnAR8D+q+eGfhESIhvpmWycjJLpYyzbxqTMaSJhRtWzYM4e/Jr40Vt10yytmCfsHkDXU/Pm8NxT8nKUbmSqB31w7i9KG5LR/NtQ3ML8Qb6+KJUzqzOOIffIn+n0+PDJcNZyP+oe7tu1vFpqa9ac2AUCI3X6rtlD9rou6BaGkKEIEm1h8V/v6aRCJTHtc1iH/Tv3iacWkqBLSzb3sxzA5/eRDhTAG/+YiPKv6hjCN71GSITrYxBekhrkGsg9CTugfBy6qfBRt9QNBSAxhBuJRimhonj1HORXfPyRDapFAk0+ETYqMrHHtEt4y+6+VE2eEe7YXgjD+97TLO1Q4ZJ4VUea5+QvD96SUnp4l/SF/OAc8xunWuqT+4J3jmYCABEiCBOATMo3GcEpiWBEiABEiABD4gIB/UTRM5PPDn86286Y25nGRI6wfU72qDFArxUC2tYmR6PJSjPFPfsHTNZL3CLwYJJEUA/vIuOOnIQNjoKT43ZpBY2Lgz3GE0qU0GkmpnNZXz0N9XFay7b65vEt/5be47ymLTBymQwIpL/s4N7dNF3Pncsrz156ZPHi/+uGBd2u8nhLap59SFy1Z9olSchm16b691aSpEvasfflX86FMnpi2pVMvH/6m41p13/22FOHlQr9A/nloWjjF2mIIU1aQVF8awbwYbnqiWfhApIaBhbMIn2m5bpm0TLKVQJMcy34u4NzeYRSVZDja+ufPZFaYupa7pG5Kgj6lxNXhZFii+wW/Ydusy5VRBHxxMDXz0vrpqm2jSlpxD8MXOyGrf9XFfL6vUz6NaV6If+H8j72up94vtIwESKA0CFABL4z6wFSRAAiRQEQSkxYP+9lo+kOerk5hgTX10vnhhWfqOm/oEK2r94QQ5KBOTZfxheRoesjEB0/sGp/XwW4W6GEggXwTgL+/xVxvDv9v+uixtwtsxsILJdpfMfLW3msuFaPPhwELz58+5RZJiMMKmD48FVsotge/BxWsPWTD6lpjm2tYTB/QUnz51kHg98Hf4g98vDgU6CG0T7p0TvliZOr4u1yoi54eA5tv9dvWW3ZHLQ0KIdvqSTGnJpY9LasFSVMOYo48tYblBW2W5EAGvO3tYVsu0VaEIYi++oyYhcURgabo0EJttYd47m8X//nODaFi9zZYkvJ9njzg8Ix5jqGnXbPl8IF/UISPYQQiDaDh99ttpoqhesCr+IS7bcV8vt1jnccRwn5hbrD6wXhIggdIlQAGwdO8NW0YCJEACZUnAZUWXrw4tCPxo2SZZcoKFyYecVOABGw/OmHSpjs3RPlhhmHz4nXpUT/Hljw4VNwbO5G88/32xbmdzWAbyqE7rcc5AAvkkoE94kxb/RvbvLrp0am8UCPLZr0ooW1o+QbgoRQEQjOcHu9nqQbU60+Nw/m//UideCF5y+NKZ8uIaLKTvCJa3mjaOwG/0e82tVgtr+C7Ed3L2ii224lPXISbBF1+u4Z4X3opdhDrWIHNUSy6MRxibkN8U1HKzFXxkPmkpbxL/4PfPJf6hbd/93T9NTUy7ZhNzpSCq9xPnV/9inngs8OOH8Vi2UU+XVonnRGXmSVpy0fJe+RqG7zqt/3yUGE8CJKAToA9AnQjPSYAESIAEEiEAcQ0PspjcYDKMh/+kA8rELr/XP/6as2i0AZMK+FyCWAdH9/iUPphkZjlBmbU83ZIQ8Zg0X/PI/DAfHLWfFCzFxMM3duhjIIFKIgDLMJNAUEl9zFdf5qw46JcLVlaYoJsChJaxx+QuUpnKzte1j59wpJj2xfqMPqEvaugViHWmEIo8MxusIte8VdsDH4UtwpQfvgs7tGsb+mLFsmFXaN1/QPTp1jHDj56eZ3Rg1a372tPTZHOOsUYG9VheM33C9+K3gp3qXUGWhXHV9b0ylSGFIjm+mYS1mvZt06yKTeVEvdYUiLmm4BJEISxPfODl8DtgsoQ0lee7Jpn50pVavOsey7binmJFAgMJkAAJxCVAATAuMaYnARIgARLwEogitnkL8SRI1fGzl8Tbm93LtbBBh2lSgYkQrsvgmqDINPiU+TChmj5npRpVtOM2RauZFVcCATj+Z8idwIOzV4YvCa76xavihxNGZog1EJ2e/9ZZ4t4vnFY2IqAUkKR1NzZTevjKYBONoC+6Neq2QKyzBZ+o/FpgyW3Lj9/cxu3u33nUCytB+NHDphm6OCnbFfYn2HDjynFD5aXEPlXrLfXYVgFcSMD3os+Xp9zZWLrZQB/UgPPfTxmb8X3DdSkUuca35mBJeFLB1m+fIIfvx5cDH4cmgTKbttnakU1Zhcxju8f4/3bfF0YbNzFT2xe+GA1eus5afvBlBM4ZSIAESEAS4BJgSYKfJEACJEACiRCwWRlI0Uw6PM+lMlsdpjJhMYIHatukAtdhoQhrPt8ERS0f+fDnm9SqefJ5jEf8Ewf0EIve3ZHPalh2hRKwOf6v0O7mvVv4bfiPJxeLcPODwEpZ+kzD8tTuNe3FzmAzg47t26W1AwIbXmwUM+i+4aSAhN9cCEj4jYSwgr9slwNn278pvzr0ssZVBthvfq8lFFr1TTNkf5A/38snpSUX2mMKaAuWy064Z44pOu0adruVQQqxGLfk/ZB9SdtsI7hH8jryxhnfZF1xPyFSod+mEEWQi/udgsiri9CoG2zVvpvak69r+v8V8MAzSJzguseucvD7ob/slN95lMlAAiRAAhQA+R0gARIgARJIlIDLygATISm25VKpqw693JsvGumd+GBihMlClAmKWv7S9Yec6KvXi3XctKcl2LCkp9HHV7HaxHorkwB2JcbGJAx2Avi9w6YX8HunikCw+tp34P0Mn3aYvNcG4qC+06m9hmRjTgz87E352DFi35nHiGBFqOjfs0v4uyitrdU++JbiJtuy+KXJ3/THA79yJqEMJfoEuvi1pu/KKi25dEEG7DAujRrUM7TSilKPOjaZBCa1DIxlJvFLLUNNn+QxBDy41oDVoS44JckbDG+7ZJRzU5Ek+xW1rKQFONu9NLXH9mIU/2/xHUzi5aupXl4jARIoLwIUAMvrfrG1JEACJFDyBHxWBnJilktHfHXIsvHmG5MsTABdQU6M4k5QRvTr7iq24HErt+4R+GMggXwS6N45sGDbsy+fVVRM2XLHW7VDtg2LkKZY4h/qXhT4frx8+jwchhZUEHEOHDgQbtCgW2b5lqyGhRTxnx3KUmT8riPIcQPnEOekQPe1R14Vc97amkhra2vSrax8llxy7HFVrlqz5SIwxR3ffG363vnHiesefS1j4xCb4CR5Y8MP/fuk1qVboapxONYt2lxWj3refJ4XW4BzvRjFPfnb0o0hO9wHBhIggeolQB+A1Xvv2XMSIAESyAsB34RGj8dDMwS6OP5q9DJMHZGTBMTJiY8tnbSWkBOUM4b3MSVNu4by5V9axAcn/XvWmC7zGgmUJYEbzh0u/s+nRwpMzin+Rb+F+RLKBvbsHL0RWaSEYDB5+ivi0mmvOMWaLIouSJb7Xjy4i6+0XtQ3f8KGIxh3/rFis1i81r2RU/u20QWTb//fBWG5GNfUgDHmjOGZy1JdYxPyq+NYKMYafORJwU2tz3QsxzeUmUvA+AhxGOXZdg1Gm0wv3iCIYrdf/I6YAto2LfDfGLeNNr6mOvJ1zSfAmXgk2RYpcNvKhGWmvvGZLS2vkwAJVC4BWgBW7r1lz0iABEigKATkhAYTAD3goV6KbYjL1prBVYdcGqTWIyc++lIstEc6SJdtxQRl5lUfCicvDau2ij0tB8TTi9amTYJlPle58Mf387+tkMXykwTKn0CgaZSKz8tygInfonwJgI3b82/pi005ihlu+uQJ4omGNaFlYtx2YCfr597YIGb+Y6XQLS4xNp1924tG33F6PXd/7hTx2KtrghdUmTvD62lxDl+aEBvlGKEvg5V5IBBCMIJoM/WcuvCyOmaGy4QvDJYJBy4dEDBWuiznpOCmjnthRu2flEVi4Jfy+sdfFwvf9buxOHVQD3HhqIGic8e2Aj4sZR0LG7drpaefYvzEWI1xUg04h8hnG4/VNt4Q7I6s/x9CX0txSatPgEO8ZKfySOo4yovRUmWXFAOWQwIk4CfQJhiA0l9R+fMwBQnkTKCxsVEMGjQoLGfNmjVi4MCBOZfJAkiABEqHQBRhD8MP3karkx7ZA0yefP5qotQhy1M/8RYeD+J4WI7zMO7Lp8c/8vJK8f0n/6lWzWMSIIEKJdCrS4e0HWzxAuDiUwaIm/60pEJ7nP9uYWfqYm9Ok4uIaxvHbGMXNgRpam7NGJtcY6V6Fx4Odmb+aN3hAumluIhxziTCIR/ace0vGzJ8UaplymNTXzDmQex0BZ8Qqo+balm+8rEbdZwxXC07H8fFbm/U7wn6Xmrs8nE/WGYmAc6/M5lU4xVaAFbjXWefSYAESCDPBFJv8B1iW5TlMq6H+yh1mLqJMl3lqnn0idS4YX0yrBlkerVcTKwem7taRvGzjAlwZ+UyvnkFbPrIQPDb27o/ZSmM3biLuSN3KYhnueIvtviH9uvWZ3H6ZLLKw5iiW76hTPkizPTiyzVWqu25+/m3xJC+3cLdp2V5iJciHHaf1oXBR7704ZS1+9J1TWLG31eqRaaOTX1xWeLLjMhns9YDCzXgXLUWLLZFndq2KMcuHrgHUZ87otRlSmNbkWBKm29rRFOdvEYCJFAaBCgAlsZ9YCtIgARIoCIJqKKY3sEkHu5tEwhc1yc66sRCb4vp3GalYdrdUM2PujHhWeTxK6Xm4XHpEoCIgwVs6VPV0m1vNbVsRL9acdrgnuKRl9fkpdtx7nvUJaJ5aaihUFU8gw877DqsB7xEwe9cNiGXvNnUV4w8SYioutDiEvMglmGjhg7t2oRWgNJyzzdWSjZYnn/R3XMyljaj3Cm/mh/s7NwmJTQijxQG5TgNP7w2ARDpZwfxaItqVXjHxFHiY57l1CbxMMr46lvS6otHmwsZbAKc5FyItsgXo/geYYWFLZQaO1s7eZ0ESCB5AhQAk2fKEkmABEiABCIQ8D2A+uJtE4gfThhptYDAw7EvhOJhYLmYre8h1wTPVzfjS5NApnRSmu2stlbd/flTgw1JWvImAFbKfYf4pwt2sAbLVvzDBg4mH26V9P3r3bWjuPUzJ4sJ98zJqVv6OOYT81TRRgpHehmuBm3d1WKMNgnUunWer56b/nhoObts26b3WjIER1MDVCFUviRD/WrQ21Nsizq1bVGPpQDnWtoctaxc0uH+4E9njDJxPd/WiLm0nXlJgATyS4C7AOeXL0snARIgARKwEJAP96Zo3wOqawIBCwj9oVdOLEx1qdcwIcYEbPzPXrIu/UJZeLhXA9qzPHCq/ti81eLRuavUKB6TAAnki0Dw/+4/nzokSuSrmkooF79t0794mrjvslMFxL+dzfuy6taYwb3EA5NGh4Lig0F5NR3KbyrRvbPb/gEC5/PfOkvA/99Zdf4d4eOA9Ilsally3HKNlWr6bI5Rx68DdxUY04b26SJwf6ME2TafoCnLUvvtekmmjq/Sog7PA2rAub55lxpfCscQ2Ey7PheqbeXMrlCMWA8JVCsB9whYrVTYbxIggYoiEFp0fbDbHh5C5bKaiupkGXTGdB/wEK/7Q4rycO+aQNgsIDCxMC2vkuhsoqKMVz9VawZMrKM6UlfL4DEJkEBuBBpWbRPzVxd3p9rcelDY3Hc8u0y0b9c2lvj34SG9ROsBIcAaYe7KbeKbj70eCjC41ozIMgtHdOskTh3UM2134PpA+Lpq3JDAMqo2zTrqG+cem5YublfVsQJ5pZiH8ShKQDqMd6axMkr+KGm+89tFYTKMvZeOOSrlx9KXF22bdPpgX7IMizOfaKgyS1nUBS/YGlYf/A5iJ2KI2EkH0zNKXNchSbcpl/JS7By+mHMpn3lJgATKk0Dyv57lyYGtJgESqFACEGdsAhMejhgKQ8B1H+D0PO5yGd8EwtYr0/Iq+T1wiYp6edKaAROGqY/Oj7SLol4Gz0mg0AS6dWon3tu7v9DV5q2+jU3NeSu7Egte+O7O2N06EHjAbFi1NS0fhB+Mq/WBpVw5huWBoNYrEAHVoAo9+F2X59iVN5cgxwpZhrTM0p9LZLzpUwpiGCt9vt1M+aNew33d1RLv96F9YAAK4RB5TcH0Qq+2k/vZS2eG54dbnn4jrQ5Zrhy/TXXHueZ6RkmqjjjtSTKt9PGYZJksiwRIoHwJlJ/dfvmyZstJgAQKTMBm0SUnLwVuTtVWF+U+xF0u45tARIGtfw+iioqYeEj/ORANX1i2OUp1TEMCRScA8e+Gc4cXvR1JNAD/Dw/vXpNEUSzDQQAbS5gCfj971LiFHFO+Urmm9wvn1zwyX4y//cXQDQQEIQRdjIrTfnWsUPNBUIKY9+z1Z4qZV40R0yfXq9EZx2gDxlG8KHt9zUEruIxECV0Ah6jLgFFl/55dQutE9FUNWD795NfGhv1UBTT0487nlqlJ0451ZlGeH9IKyOKkEHVk0SxmIQESIIG8EKAFYF6wslASIIFSIOCy6MLkBQ/TUsgphfZWahuSvg94WL/DMYHo2aWD2L47mtUGvge/Dnz2nTb4MHFkBDEBkxPV99CKjU2VetvYrwolYNoNtty6elIgLkysHyTaY5tehqIRGNirs8BmGTa3C7k07KQB3UWbYNfaBWsKv8RbvhyCMIfxBmLWgsbMdpwxrI/457qdxv5D9MJ3FM8ZNrcjuI6wdvvuUHTD8mo9YMzpW9spFCXRrlxC1F2Nrxg7RHTt1D7N4s5UryrWRbXkdz0PoI6p4+vSqnKlT+o5rhB1pHWKJyRAAiRQRAIUAIsIn1WTAAnkl4DPoksuq8lvK1h61PuAiRYexJEeFg+2SRMmYi84JkJHH9ZFnDKoo3fyIu/Md367ODyEs/czhvcRpt0SMQG87ZJRaYIx2jt9zkpZDD9JoCwI3PW3FWXRTlcjFwa/AbDWYsgvgeHBRgbLAwHLFnp06Sh+P2WswMZLSYqAEM/u+cLowM9bhwwXHra2JH0d4tLE+/9h9YcH8WvqOXViwr1zjFXDglB+R+WLI9USzrTkVBdTw3wTRyXCIGxvIK5F2dV4xpx3xLQv1otNTXvD8RgW97DaUwVI2TbVfQfGbN9LVd/zgL7k2pce8b46jTdIuViIOpTqeEgCJEACRSVAAbCo+Fk5CZBAPgn4lu744vPZtmoq28cZ8abJkJw0wdm3FAb7BVZ6P/j9QcHOxhAWI1hadeMFIpy8tO5/P7SesKWX17GUd9ywwzL8GcmJzqb3WgJxcFNKnESb9GVksix+kkCpEjjwfqm2jO0qNQIQ/3p37RCIe2aL6juDTUVg+TX/388Vv3x5lbjxSfdvc9T+YTyAqIhyVcuyqL/lUevxpTNZ5KkvgzAeRAkQzuAr9qErPxQmx8sjkw9AiKgnDeghvvUvdeHSWghqyKsKb1Hq09PIMWxq4LcxSkC/0T6wl+Kaeh8wZsMqUe+DHLNVoVOvL8rzgJonbno1b9TjQtQRtS1MRwIkQAL5JkABMN+EWT4JkEDRCODhGQ+kpodnXJcPtkVrYJVU7LsPiMfmHPp9wvmUX80X7YNlYHqcDx3e6J8x/OA9xmTL9j3Qy5m9YkuaeOia6Ew8bZCeneckQAIVQuD6wFfi7X9dXlK9gfj008+eHApthXr5YBP/AAa/y9KVxlGB5XWSAWIYREWUi9/hccFy2x27W0S7YDzYX0QVW10K7BOOVB54wfSnBWvFBScdGb7Qso1pC9/dEVjbLQ9dTZjGRbXMKMdXfGSw+I9PHh/WGcdfrXpvZT14ZsIfxlRT25BHCocyj/7pex7Qn8viptfri3JeiDqitINpSIAESKAQBLgJSCEosw4SIIGiEJC77UH8UQPOVT9uahyPkyfguw8u/ztYjmubKLlaqk7MZP2YPEcJckkRBERMDHQrB5SBNt3zwltRimMaEiCBMiSAlwGlFiA+zV+9TXzv/OPECUfWJtY8jIl3fW5UVuW9u21XKAKu3b4nq/yuTLAonPTg3HBjjokPvCw+e98/iir+ybZK369SOJLXfZ9THn0tFM4gmrpCw6rtoQVkNmOfXu6Mv6+MVKeeD+e2pbGuMRttdvVPjsdRn8vipjf1w3etEHX42sB4EiABEigUAVoAFoo06yEBEigKASxF0Zeu6G+Yi9KwKqs04z5gw402bcTCxu2BA/RkJ46YWOj3GPXDcubcn73kJa+Kh66JzqLAUoOBBEigMgnAwg7Wx6W2acq3n1gUAncts4x7R7Dxgs+1gq3Mr/96QejCwRaf1PVCWTyivV07tRO7gh2zbeHB2e8EY0xtKJCBHSziolrXQSDbtXefrejU9SR9KqJOWE/GDepYqOa1CYMyTcOqrVYfvkiT8TwQWHiqYzZ4YuxFPWgDhNZ8P8f52iT7xk8SIAESKHcCFADL/Q6y/SRAApEI4OFSfcCMlImJEieAe2DyHZRURS7rzigbhuriocuSIak2sxwSIIHSJFBq4p9KCX7ykgqwcl65ZXdWxfnaAcvrQEcVrxVhN9+sOhRkcol/KHNe4CNv/O0vporHuPHk18aKnc0t4pan3hBvbnBb+MHH3oh+tWLp+ux3kR8zuJe4ctzQUBy7+Y//FD6L1fkx+etjYaqzwYFNGJRpIFI/s3h9uNLCJVSbnstc/oBN6WWdSX0Woo6k2spySIAESCAbAlwCnA015iEBEiABEsiKAN7sm5bUZlWYkgmTzCevHRtaCdgmHOt2Nis5Mg9Rhro0HG2dPvvtzIS8QgIkQAIVRMAn/mFzJAhOcUKXju3C5Fi2XE7iX5w+yrSwsMMuuR+tO1zc+pmT5WXnZy4+ZKdPrhePX/MRcd7IfmL4EbXinstGh35unRU6IkcfnX5vIf6pY6GeNcrSZzDBWB8n2J4PsikrTr1MSwIkQALVRIAWgNV0t9lXEiABEigyAdeSWr1pmIS07j9gtGxA3I0XHJ9aIoS39r5QW9PBmeS2S0aFS5NkIrTVtAukjD8pEAwXBpNbBhIgAT+B3l07iulfrBd/WbJO3PsChXU/sdJIgRcjEJjgrgH++KKG3S32JbRRyyindBCpYDEOXhifcO4Kf168zhVtXX6Oss8ecXhaXrl89W9LN4b+/tIiI5xMPWdYsNRdBBaJOwPLxO5h++EXzxWw9HlT016xeO1OazLJJMr4jEJczwdxy7I2ihEkQAIkUOUEKABW+ReA3ScBEiCBQhLw+Q669eITRf+encMlRpg0uJYDYdKjTixMfoPkJAZxd/z1TWtXMalSy0JC6ejdlumrZw4Vj7/a6J3o2fLzOglUEwH4NPvBHxaLr58zPOg2BcByufcQevBb26+2U0k3+cT+3cUihxhViMav3b47HEfumDhKfOy2F4RtB2WI4a6XS2irafk57sPE+kGh0AgrPDm+yb6NPqqnQNlx/Qfe/fxbQvWxiPEQFoCoTw/wJXj1zIa09Hoa9Rxjvj62qvHqse/5IE5Zark8JgESIAESOESAAuAhFjwiARIgARLIMwGf76DRR/dOmyxgAhLF+TeEwqmPzk9zxH5WXR9x5+dODScxsCxwOWmfek5dWs/D5b9zVqZd00+GH9E9nCRd/Yt53smcnpfnJFCNBLAc9KpfvFqNXS/bPndo10as2bZbTJz2ckn34dOnDBAtgcW4z/9ePjsBIe3kQb3EpvdarOIf6o8r0Mk2Y5y75pH54emYIb3FtEmjRY8uHcPzcPnsY68by+7dtYM4oX8PMWv5ZllU6jMUI4MNb9QAazss38XYq4btgfh39m0vGutQ06nHvjE/Tto4Zanl8pgESIAESOAQAfoAPMSCRyRAAiRAAhEJYLKB5U6zlh9c9oTzKMHlO8hkhSfLhAXBGcMzrfQQj7qv/WVDhsAHwQ/XEXyWBXDervYHx6pFRFiI8g/8YaFNECgf+8rpAsuBGUiABEig0gjMX7lF/H8/n+0UtEqhzzdH2Hwj3+3EmAHhzDfeJNEO1PWxQIyDKIjgWj4LS8QbPn5shp9AjGM2MVIuuZVtxTj75YdftaaX6dRP15iuppPH2T4fyPz8JAESIAES8BOgBaCfEVOQAAmQAAkoBHzLcpWkGYdYsoSlRfpGIHLJUUaGCBcg1tl2QMR1xPssB/QlUPDj5ArYfVEG9OnhK+rFmT89NBmTcfwkARKIT+Bz9QPF/NU7Amuu7HdJddU6sGeN+HHgbmDqrxfEEjRcZVZq3M+ee6tSu5aXfkE4m3T64LyUrRcK8Q4W6NgQxCc6NjW3ZljTI4/LryPi5fJdn09cvW0QF10biejpcZ6P5wNTPbxGAiRAAtVMgAJgNd999p0ESIAEYhKAFYAu3qEI25IhU/FRl/Wa8pquzV+9zXQ5da1h1Vbx2dEDrb6RsMRNt/bDUkVXkJMipIEg+s3HF6QsMVz5GEcCJOAn8Oi8Rn+iHFI0bm8Wt/75TYp/OTDMZ9aundqJXXsLv4kIltVec+YxWW2kofJoad1vHW/gmgJCF8bMJAJ8CUZ5ySVfgmHsUscvVxtkHqTxCYxqOeD4eGAZn01I+vkgmzYwDwmQAAlUMgEuAa7ku8u+kQAJkEDCBFzLjPQlQ76qMQmxLes15YX4iIlO3GXHKGvhuzutk/3W/dGWL8s2nTighxjap0t4ahNEETmiX63Mwk8SIIESI+DavbTEmlp1zSmG+AfI3/vEcQIvhHIN02a/bRxv4G8Pfmlvv+TkwH1EcjYYEOeyWT4bJ48qBrr4wJp/2uWnuZJEiov7fBCpUCYiARIgARIQyY0+hEkCJEACJFDxBHxWAOqSoSRhuJYdjz6ql7MqxN/wmwXONHEiF727Q5x2y3Pi91PGii2Bs3ebJcfS9flZvhinrUxLAiRAAqVEYPBhXcQ5Iw4Pra6LvWuvzqVpb6vXXYSex3TesGq76XIoCr4TbEj1o6eXBBbj+4xpTBe7dWov3ttrT39k95rw5diZdX3F2h3N4k1l7AndawS7EuPlGcZnCHkQ/mCFGGfJrRQLTeMdrPZuvfik0LIwqnWhqZ+8RgIkQAIkkH8CFADzz5g1kAAJkEDFEPBZAfjiswFhs7LDRATLkadPrg8sCfsYdzjE9WCWI3xLeuO2C76XLrp7jhjUq7Mza037tqJ53wFnGkaSAAmQQLUQWLllt3jwgx3WYRFn24SiGDxgDb52+24B/3VYWpuP8P0nF4m41qcQ/2CZaLJWxxh30x//meEHd2T/7uI/J5wohgRin+62Q/rchXAXdcmtTSwEq2lfrA/LyQcvlkkCJEACJJAsgTbBxCre2qdk62dpRSbwpz/9STz00EPi5ZdfFps2bRK1tbVi2LBh4jOf+Yz46le/Krp27ZqXFjY2NopBgwaFZa9Zs0YMHDgwL/WwUBIggWQJYMi48qF5Rqs3TCpmXDEm2QqD0mC5MP72F63lPnv9maJvbSfrJGdh43ano/N2bduI/Qc4FFoBM4IESIAE8kQAO6h/6+N1gfC2R3znt4vzVIu/WF1ggzAmd9j15y5MihMDUU+1msSY27Jvv5jz1lZjAyDOdenYTrywbHNGfC7jtWpNmITFH54r4F5Et1DMaDQvkAAJ5ESA8++c8FVMZloAVsytjNeRpqYmcdlll4k//vGPaRm3bNki8PfKK6+I+++/X/zhD38Qxx13XFoanpAACVQvAZsVgLQoyAeZqMuOIT6aJiY+q0SIf3Barm8Eko++sEwSIAESIIFDBBYGGy7d/bcV4uPH9zt0sQhHunUdxD+IZ/8aiJNPLVorXl3l3hiqEE3+t0+MCJfwSqEMdbpejrmsGKXPXpuA5xLlkMeWLy4Hl3sPiLAMJEACJEACyRKgAJgsz7IoDYP6JZdcIp555pmwvaNHjxbf/OY3xYgRIwSEwaeeekrcddddYsWKFeITn/iEePXVV0WfPsEyOgYSIAESCAhEXTKUFCyfgKfGmyYmfbt1FLU17UVTs92H0pVjB4s9wTIr1boiqfazHBIgARIgATsBCFUuscqeM78xu1v2i5v/9EboYuLDQ3qJl99JXxaM7UJMtuOBUbnIh1E5xjp1jMOGWLmEhlVbU/4A1XIKJcphPqIvT0Y7pHuPfKwoUPvJYxIgARKoRgLcBbgK7/oTTzyREv/OPfdc8fe//z20BoQQeNZZZ4mf/OQnAkuD27VrJ1atWiVuuummKqTELpMACfgIYCISZxdfX3m2eOl83BQPy0ME287A4QTjsded4h/yTw98UsUV/+C/StaPMhhIgARIgAQqj8Cs5ZtF547tBdxN3HrxieLWT58ovnHOcKP4h97nQ/wzUVVffpnifde+/cSi0KWHutTZJ8r5yowTj2W/pk1FUAau/23pRoH2MJQmAdwbrLqwPX+VZqvZKhIgAQqAVfgdgM8/Ge655x7RsWNHeZr6HD9+vLj00kvD8wceeEBs3Wr2L5LKwAMSIAESyBMBuexYF9vg/Lx1/4FwCdSkB+eGnxPv/4d4ZvH68KEUD6euCYZsbujw/R33b1x7mHQoAeLfk9d+REwdXyfqDs+Pr1SlOh6SAAmQAAkUkYAUqs4beaR45p/rxR3PLU+0Nd0DK3VfwAYlquAytE8XcVZdbit0pLWdrNs1ZiIt6k8q+Nx7wN8w/lSBMqm6WU5uBHBPcG+wBF0+f/Fe5caUuUmgUAT8o02hWsJ6CkYAS3oRsNnH8OHDrfWed9554pe//KVobW0NfQFOnjzZmpYRJEACJJBPAqllxxuaRMPqbaFVwG/nv5uxbOzgUrKGsCkQDCfWH+Vs1rH9asWHjzksoxw9077ApOOWCSPFjuZWMaJfdzH66F7GpUt6Pp6TAAmQQLkTqB/cU9S0by9mrcjcTKLc+xan/Q0rt4o/L15n3FQjTjmmtDsDFxW+jUfgK1FdKl0fbPLx9bOHicZtgTC4abep2EjXpLAHq36fKId4pEsiRLFglAIllwMnQTyZMnxWorxXyXBmKSSQLwIUAPNFtoTLxSYfCEcccYSzlWr8Sy+9JCgAOnExkgRIIM8E8Mb5lqffsC4Z0qvHxGFX4NfPFd5c3yTwFyUM6t1ZXFZ3dCg+4k03ymcgARIggUonMG/l9kCcquwpA6y88aLHFb7920Wu6JzjMMbZREBYnaviHyqbF/hOnDR9Xs71ogAp7PlEOV98nMZI9x6+sRTxsDxMSniM00amzSQQxUqU9yqTG6+QQKkQ4BLgUrkTBWxHt24H39zt2OHe0UyNX7JkSQFbyKpIgARIIJ2A7Y1zeqrMM0yYsMNvEuGWp94Qr6/ZHk5EfBOWJOpjGSRAAiRQKgR27HG/TCmVdmbbDoh/w0vAnQNEQH3MgsX51l0t2XYtUj4p7ElRzpQJVvVJCjs29x6mun2WiaY8vJYfAr574YvPT6tYKgmQQFQClf06LyqFKkt33HHHiX/84x/ijTfeEJs2bRJ9+x50oq9jgNWfDKtXr5aHkT4bGxud6datW+eMZyQJkAAJqARcb5zVdKZj7PDbtWO7nC323tzwnphwzxxx8sAepmp4jQRIgARIoIwJLN+4S8AXH5bjFjNcFyzrhSAHIeXI7jXiht8syGtzVGFPinL67rxIc8elpyTeDuneAxt+wLLeFsCBoTQISLHY1hpfvC0fr5MACRSGAAXAwnAuqVouvPDCUADcv3+/+P73vy/uv//+jPYtX75czJgxI3W9qSnaEjmZYdCgQfKQnyRAAiSQM4Fc3igPO7xWwCcNlhAtD3wIfiuYTO1q2Z91mxY0uq2nsy6YGUmABEiABIpKoNjiHzpfW9MhtLSDtR3GrXyOOSZhT4pyqDsUIQMxMknLP7lBlyxbWh2iLTbrerj/gACJtlVzMLGDaFvIIO+X6V6pYnIh28S6SIAEohPgEuDorCom5Ve/+lUxYMCAsD/Y4XfSpEli4cKFoqWlRcA/4MyZM8VHP/pRsWvXLtGhw8GBds+ePRXTf3aEBEigvAjggbd1v9s3k61H6sMoHlpnzHknJ/HPVg+vkwAJkAAJ5Eagf8/Ks/KqO6Kb+MpHh4iTNMtx+PSzhTufXZaKyvbll76MWBZ4cAf7sWLmVWPEs9efGb4cs4lqEP3OGJ7ssl/b7rEQXiHwYcw2BYhNsEqs5mBjh+uFDNJKVL9XOM+HlWgh+8a6SKAaCLQJJlbZzaqqgU6R+5jEGx1Y8Zk272hoaBDnn3++2Lhxo7WXP/7xj8Xtt98eLhPu2bOn2LZtmzWtHhFlCfCYMWPCbGvWrBEDBw7Ui+A5CZAACQg82OpLkaJiGRPskHjluKGh5QLEPywjHn/7i1Gze9MN79tFLM9h50VvBUxAAiQQicDdnz9FPNHQaLUeilQIExWdwNG9u4hVW7PfzbboHfA0oP7onuKCkwaIzh3bBm4p2ospj9oFLYhz0gIw7rgF8e+nnz1JnHPbi8aXZxBqirFTK6actg20ZJtgdejqr+TiQV1x0VHYFaPT+bISLUZfqqFOzM/lKj3Ov6vhjpv7yCXAZi4Vf3X06NHi9ddfFz/60Y/Eb37zG7Fhw4ZUn+vr68UPfvADccEFF4ibb745vN6rV69UfJQDCnpRKDENCZCAiwAeeLMR/75+zjDx8ttbxdx3gr+VDWEVmFxMrE/WNUGvrp3E0YGrqFXbKnfC6ro/jCOBUiEAv203XnC8OG/k1nCX7t/MWy0a1uwsleaxHREJQPzDbsOVuuHIvFXbBf6iBFj+QQB0Lbc0ldMuWA06bdJo8aVfzDOKf8gDazoIN1GW9WIcxsszdblutgYKLl++sk0+i0fJxdT3Sr4WhV2U+5k0I9RZjHqT7gfLI4FqIkABsITvNjbpyDUceeSR1iIQd9ddd4V/69evFzt37hRHHHGE6NHjoIN7vCVobm4O859wwgnWchhBAiRAAvkg4HrgddUnxT81DSYXufj9U8uSx9hhuGtgycFAAiRQXAJ3P/9WKPgXtxWsPQkCl9YfJX71ymrRtLe4G3Ek0ZdcylDdXkw9py7cBTiKL0B4y5i1fLNXaFSFtFDkCwTBhtUHV/qcelSvUNTBslz9JZxc5qkuG44qEkYR93wbSPjic2FeynmjsKMQV8p3kG0jgdIhQAGwdO5FRktGjBiRcS1fF/r16yfwpwYsE5ZBLteV5/wkARIggVwJmCYNKFNaG6zdnp3vUVj+mQKuY1kwhLukwq6WA0kVxXJIgASyJGD7P59lccxWRAL3v/R2EWsvnarbB++WTC4wThrQXYwZ2lv8z6yV1sbervgQtCXCrrqwAlyxsUlMe+mdlPgn0489prdo27ZtKCbKa/iUvvjkEmJTG00iIfL6xDvEuyweUW61ilxR2IExAwmQAAn4CFAA9BGq4ngsDZZh4sSJ8pCfJEACJBCLgEnoM1kWjA78I9UEs545b5kFvFiVWhIf269WiGDHPAoGFkC8TAIkQAIkUHQCd/9thegYjIezV2xJa8vCd3cK/LnC28GSXVcYHVj4YVddiHm24BqH5XJdiHW6hSDK00VCWUdUcQ8bSejlSlFRllVtn1HZVRsX9pcESCA+AQqA8ZlVRY4lS5aIxx57LOzr+PHjRV1dXVX0m50kARJIloDNOqB1/4GMiU1DRN9IubRw5surw+ynHtVTnD70MHHPC2/lUhzzkgAJkAAJkEDiBLK1VD852G3YtVS4tqZduAmJS/yL0hm5JNVWjhQJVYs9uXusT9zD8mJYGHKDiUN3Iiq7Qzl4RAIkQAJmAhQAzVwq/uq7774rBgwYYOwndgW66KKLxL59+0SnTp1CH4HGhLxIAiRAAg4CsPzTH/SR3DZhcBSVFnVWXR8h/RylRQQnZw4/TOzZ977Xwm/+6u2iXbDEqleXDmLb7la9GJ6TAAmQAAmQQFkR6N21o7j5opFiwj1zrO3+8adPElN+Zd992JpRi8CSVCkCalGpU8SrAiAi4oh7yKvnTxVehQdx2FUhHnaZBEggIgEKgBFBVVqya665RmzatElcfPHF4rTTThM9e/YMz5977jlx3333hRuCwPfHAw88IArpi7DSOLM/JFDNBLLdxMPE7NaLTxT9e3YOfQhhQmCyLIRV35ZdrWLxWvfyKFn+vJXbxdBgCdP+AwfEzub98jI/SYAESIAESKDsCGzd1SK6dmgrIATiWA+4rm7eocdHPY/qi8/lt47iXlTamenILpMJr5AACUQnQAEwOquKSgnLnFdeeSX8M3Wsd+/e4t577xX0/Weiw2skQAJRCPisA6KUIdN06dhOYFOQcGOQ4PcLwt2NFxwvzhu5Vexp2S+eXrQuq809fL6SZP38JAESIAESqF4Cgw/rItoE3X9ny+6ShtAQWLebxD80GtfV3YV9HRk37DDRITCVV632VV989EvnI8h4EiABEig9AhQAS++eFKRF3/3ud8Wxxx4rZs2aJbDkd8uWLaEV4DHHHBMu//3Sl74k+vTpU5C2sBISIIHKJOB6+x+3x9c9+npaFi7dTcPBExIgARIggTwSWFniwp/s+ow578hD4yd2F4aIp4p6poQQ/+65bHRoMWjzxUe/dCZyvEYCJEACpU2gTWAJ9n5pN5Gtq0QCjY2NYtCgQWHXIEAOHDiwErvJPpFAVRPA8HLlQ/OMEw1MLpasa7JaKlQ1OHaeBEiABEiABGISsC39VYt59vozRd/aThn+eccM7iXOP6m/qGnfRhzevXNg+dcmdLkBKz8Ifb5gEwl9+WzxeH6AGxGsJMDLxKjtsJXH6yRAAkJw/s1vAQjQApDfAxIgARIggbwQCK0DJo4SV89sSNuUQ11CdPXDr6bF5aUhLJQESIAESIAEKpjAmCG9vWOp6rvPtMuuybeuHK99vgOT9EuXSzsq+BazayRAAiSQCAFaACaCkYXEJcA3EHGJMT0JlB8B00M8rAymfbE+zRG5tByAbyJYDDKQAAmQAAmQQLURCIzuRG1Ne7F9z75YXZ8+uT602Jv04FxrvpMH9hAPX/WhtLFXTeyy2IcICMGwEKFU2lGIvrIOEig0Ac6/C028NOsLPEEwkAAJkAAJkECyBPAQP/XR+RnLf+eu3BYuPVJrg+XAGcP7hn6JMNFgIAESIAESIIFqIxC8AwuWutbG7vampmZxZPcaZ77bLhllFf+QEcttbX4BcR0v6goRSqUdhegr6yABEiCBYhCgAFgM6qyTBEiABCqcwII1O8QLyzYbeyknExAJMamYtfzQ5OKOS08JhUBjxhwuTj796BxyMysJkAAJkAAJ5J9Aw+ptsSv59hOLxH8+tSR4kWbevE9d+msrHL72XMEX78obJ85Xjy8+Tl1MSwIkQALVSIA+AKvxrrPPJEACJJBHAhD2fvCHxc4aIPzdEkxYVIsD6WsIy5lwfc6KTeLB2Sud5cjIkf27i8Vrd8rTjM+nFq3LuMYLJEACJEACJFAJBPDCDZtrYRw1jau+PmKjDVfwxbvyxonz1eOLj1MX05IACZBANRKgAFiNd519JgESIIE8EsASngWNO5w1TJ/9tsByYDVg0nLtLxsCX0Zt0yYwahrbcZdO7uFs03sttqy8TgIkQAIkQAIlTwAbccC3ri3MXrFFYJffGy8Qqd1z4WIjSsAuu7p4KPNFsSCUaXP9LJV25NoP5icBEiCBUiXAJcClemfYLhIgARIoUwK+JTrH9qvNEP9kVzGBUa0X5HXf59x3tgpsMMJAAiRAAiRAApVIAOLfsECocwWMv9KvblTxD+W1adNGmFxwSMt8V51JxpVKO5LsE8siARIggVIi4DaZKKWWsi0kQAIkQAJlQcC3ROdz9YPETX9cknhfrhw3VOzdt8JrfahW3L9nJ7F2+171Eo9JgARIgARIoCQJrAgs7F3BN/668sLCELv9wkUHhESUFUdEdJUdJ65U2hGnzUxLAiRAAuVCgBaA5XKn2E4SIAESKBMCQ/t0Eb27djS2FtfHBTv+5iNgooKdDqOEIUEbESj+RaHFNCRAAiRAAqVOYMyQ3okIdtlYEOaDTam0Ix99Y5kkQAIkUCwCFACLRZ71kgAJkECFEnh7826xdZfZ5154PdgkBMuKkgwnDugRWiyIoOyz6sw7Iar1vRO0MZfQtk0uuZmXBEiABEiABJIlcOXYwckWyNJIgARIgAQqjgAFwIq7pewQCZAACRSXgM8H4LqdzUZfQxDuPhxYMGQTFr27Q0x6cK4Y/7OXxP73RbgbYjblRM1zIKiDgQRIgARIgARKhcCww2tLpSlsBwmQAAmQQIkSoA/AEr0xbBYJkAAJlCsBnw8ixJt8/PTp1lF87Kcv5NztWcs3hxaGT147Vvzbb14Xyza6fSblXCELIAESIAESIIEiEijkTr1F7CarJgESIAESyJEALQBzBMjsJEACJCAJvB8sP4Xz7FnLN4WfOK/GcEywS6Ftia+8/tKyjeK5NzaIV1duCfzw7RHvHzggrv7FPLFtd2siyMKdhAP8nTvyPVciQFkICZAACZBASRLAuIodfBlIgARIgARIwEeAMyMfIcaTAAmQQAQCO/a0im/8+jURCk8fpJcP5bB2q6bQpk2bcDKi8zhjeB/Ruv+AGH/7iwXBcf3jrwn4I2QgARIgARIggUokMH1yvTh7xOGV2DX2iQRIgARIIA8EKADmASqLJAESqC4CsPTTxS4QgBiI6zOuGFNdQILeZizx7V4jbnn6jYDJ5oKxoPhXMNSsiARIgARIoMAE8JKR4l+BobM6EiABEihzAlwCXOY3kM0nARIoPoG3Nu1Ks/xTWwQREMuCqzUMO7ybOGN4sONvYBWoWkeWE4+OHCnL6XaxrSRAAiRQcQR6d+2Y1ie5wiDtIk9IgARIgARIwEOAFoAeQIwmARIgAR8B7663O/YICGHVGmAh2bBqa9l2v+VA2TadDScBEiABEihDAhD4brzgeIHnC2ychWcIvExUz8uwW2wyCZAACZBAkQlQACzyDWD1JEAC5U8gyq635d/L7Hpg8o0YpyQsJUYZMhx7RDfx5obqtaiUHPhJAiRAAiRQmQROHthDTB1fJ7ChlvryEMfqeWX2nr0iARIgARLIJwEKgPmky7JJgASqgoDc9da0xBVv8av1gd3mG9H1pRgzpLe4+NQBAnn71taIju3bBhuHvC/2tu4TM/6+Ssx9p3wtCV39ZhwJkAAJkEB1EziyR01g4dcsFjTuEBPumSPkMt9q20isur8F7D0JkAAJ5JcABcD88mXpJEACVUDAtuutfHgvNAKIZ/BLKJcKQaBEGwsdXL4RTW3p1aVDKPCZRD74P9q6q8WULXUN+UcO6CFmLS/cRiOpynlAAiRAAiRAAjkQgPinhmreSEzlwGMSIAESIIHkCFAATI4lSyIBEqhiAhm73n7gs6fQSExLbqUQmQ8rAik2rt2+W+wLfOUFBnuif88u4dIln2/EG84dLg4PdgcW7wvxxPxGMXflNisun/iHjNt2t4r3mltEbaf2omnvPmtZjCABEiABEiCBciAgNxKr1pUE5XCP2EYSIAESKCcCFADL6W6xrSRAAiVPoJg+emxLbvNlRWASG+UNgug49Zw6eWr8/MSJ/VOOzb/920XGNHEvvrZmZ9wsTE8CJEACJEACJUsAL9MoAJbs7WHDSIAESKCsCFAALKvbxcaSAAmQgJ2Aa8lt0lYENrFRtg71IUAIlMcyTl6XExqfpaCaj8ckQAIkQAIkUE0EfBuNVRML9pUESIAESCA3AsFiLQYSIAESIIFKIOAT0nzxcRi4xEZZDoQ/7GQIEVANckmyvMbJjSTBTxIgARIgARI4RADjpXxZduhq5hFeyq3Y+F7gA3dT+IlzBhIgARIgARLQCdACUCfCcxIgARIoUwI+Ic0XH6fbUcXEpuZWMeOKMeGEBHnQBn0y49pFWW1TlI1A1PQ8JgESIAESIIFyJaC/LLP1w+SOQ+bNh+9fWzt4nQRIgARIoPQJUAAs/XvEFpIACZBAJAIuIS2qFUGkioJEUcVEmQ6iny78ybpsuyjLeHzKycympr3iL0vWi/965k01msckQAIkQAIkUPYEpk+uFx3atTG+LDN1zuaOAxb43/j1a+ELOFM+XiMBEiABEqhOAhQAq/O+s9ckQAIVSMAmpEnxLMkuu8RGWU9U0RETGAh7V44bIiadPji1kzDK0a0GYc3w/vtHUACUkPlJAiRAAiRQEQQwZp6HFtMAAEAASURBVJ494vBYfXG544AIiGXBtpdvsSpiYhIgARIggYogQAGwIm4jO0ECJEACBwlAIPMtuU2ClU1slGVHFR19S5f0iQvS/+jpN2Q1/CQBEiABEiCBiiAAn7lxg88dB+L1cTRuHUxPAiRAAiRQOQQoAFbOvWRPSIAESCBFAA/8+X7o18XG1v3vJ7Z06fIHXxG3XTJKwNIQYiOCbalTqtM8IAESIAESIIEyJQCfuXGDdLNhy+eLt+XjdRIgARIggcokQAGwMu8re0UCJEACBSOQrdjoWrq0oHGHGH/7iynffxAbXekL1llWRAIkQAIkQAIeAicP7CEwjsUJ/brXpG2Ypb4As5XjcscR1Q2HrexiX8dLP4z70hVIFB7FbjPrJwESIIFSJ0ABsNTvENtHAiRAAhVKYO323d6eqY7MfUudvIUxAQmQAAmQAAkUgEC7tgct16NWNW7YYaF7C4x5MkhXGngBZgs2dxwyry1fqV/3uQcp9fazfSRAAiRQqgQoAJbqnWG7SIAESCACgXJ9Q46H+7uffytCD4WQjsy5lCkSLiYiARIgARIoMoH5q7eL3l07iq27WjJaol8/q66PCDxohGOdmlh9AaZe1491dxwYK/PtAkS2IR/PIDZ3H1F5yLbxkwRIgARIIJMABcBMJrxCAiRAAmVBoFzfkMuH+7nvbI3MGdZ/44b1EZgovbBsc+R8TEgCJEACJEACxSAA8W/MkN5CHeukZR52vpdLW9E2uLwwBfkCLIqgl607DlO9Ua7l6xnE5e4jDo8ofWAaEiABEqg2AhQAq+2Os78kQAIVQUCKaHgYVkM5vCF3PdyrfVGPYdGws3lfaCWhXsfxsGCjkBWBnyAGEiABEiABEiglAtedPUxg/JJinxTyYLUnj2ctTx/H9fYjr0yrxxXrPJ/PIOivK5QiD1d7GUcCJEACpUSAAmAp3Q22hQRIgAQiEnCJaKX+htz3cK8jgMUEnH9f+dA8MWt5pvVf544cynRmPCcBEiABEig+Abkc1yXgIY0rIB6CWyltiJHPZ5AoPFy8GEcCJEACJGAnwFmTnQ1jSIAESKBkCfhEtFJ+Q+57uFehy+VSrsnGonfj7bSols9jEiABEiABEsgHAYxfqvBnE/F8O/n2re0UvgBTLf7l2OjaICQffZJl5vMZxMdDZSrbw08SIAESIIFoBNpGS8ZUJEACJEACpUTAJ6L54pPqCyY0Kza+F1jmbQo/ce4L8uHelA7O0U3BN9kw5eE1EiABEiABEigGASnQybrhLw9W7PD1N+nBueEnznFd7uSLPGoIy5g4Snzj169ZNwhR0xfy2PeM4Yt3tdXJ49JTXFkZRwIkQAIk4CFAC0APIEaTAAmQQCkSkCKaahEg24lJQyHekGfrAFw+3OuTGn1nRPQH/bv8wVfE1PF1snv8JAESIAESIIGSJTBmcC9xRyBUSes8vBjTxzs0HuMbrs+4YkyYFp94oYYXXhDQMI7j3DTOy/yIL8R4r8NO4hnEZhGJuoq5s7HeV56TAAmQQCURaBP8+PrNNSqpx+xLSRBobGwUgwYNCtuyZs0aMXDgwJJoFxtBAuVEIFsBLok+YuiA9YJpYgIBEhOZKEFOdlr3HyzPlcckELrSM44ESIAESIAEikFAHQcxztl2+UXbnr3+TKuIB+t6WAzawsyrxogzhqdbDtrSJn09l2eQXPIm3Q+WRwLVQoDz72q50+5+0gLQzYexJEACJFCyBIr5htzlkw+iYFSrBFgu4M+3CyJuwtZdLYIiYMl+HdkwEiABEiCBDwio46DPhQXibVZ8vqW0vvh83pBsn0HwAtFnEZnPdrNsEiABEqhmAvQBWM13n30nARKoCAKYOMACwDaByEcno0xootaLyQAsAKMEiIB1R3SLkpRpSIAESIAESCBRAh8e0kvAui9KkOOkT6Rzxcultqb6CuXuw1S3ei3uM0iUF4hq+TwmARIgARJIjgAFwORYsiQSIAESqBoCrgkLIPjiJSgsA8JSYvxFDcs2vBc1KdORAAmQAAmQQCIEILjdf3l96OICy3ZvvfhEZ7lyHMxFxJM+c3XREefwM1iOQQqjtrb74m35eJ0ESIAESMBPgEuA/YyYggRIgARIQCMgJzQ2H4BRrBFty4C0qnhKAiRAAiRAAkUhAJGvf8/OqU05ZCMwxmEcfGbxeqsvXDkOShFPX/YaVcTLdqmtbGupfUph1NYuX7wtH6+TAAmQAAn4CVAA9DNiChIgARIgAY1AthMaiH5Y/oM3/Fj2axIQtap4SgIkQAIkQAJFITD66N6h0IdxC75qIU5B+MMYiL8fThgpLrp7TuijVjYQvmpxXQ1JiHgQFKWoqJZdbsdJvEAstz6zvSRAAiRQKgQoAJbKnWA7SIAESKDMCMSd0Jh2/SuzLrO5JEACJEACVUIAFnp9aztl7HgvLfe617QX//Hk4jTxD2jgqxbXZ1wxJoNUpYh4GR2LcSHbF4gxqmBSEiABEiABCwEKgBYwvEwCJEACJBCNQJQJDZf7RmPJVCRAAiRAAsUnAJFv6tnDxeUPviIWNO5IaxAs17Gc98YLjrdasau7AKdl5klIIO4LRGIjARIgARJIhgAFwGQ4shQSIAESKGsC6tJcdYlTUp1y7fqXVB0shwRIgARIgASyJSD9/dXWdBB3PrtMTPjvv1uLgsB33sit1nhEwNVFJSzZdXYyYqTtGSPKC8SIVTAZCZAACZBABAIUACNAYhISIAESqGQCpqW5cokT3tInEbirXxIUWQYJkAAJkEC+CIw+qpc4JvCzh13pk/BPW42bWZiEvp3N+0KLSZVp0s8Y+fpOsFwSIAESqDQCFAAr7Y6yPyRAAiQQg4BtaS4e1LHEyeTDKEbxqaRJTYROHtgjYzlWqhIekAAJkAAJkECWBL4X+O373vnHRRb/Tg0EQwhZqrAlq8b1arP+M71MPKuujwj2+wo2UNks0YSfST9jpBXOExIgARIgASuBttYYRpAACZAACVQ8AdfSXDygr9j4XiIM5K5/uRR2xvA+AoIlAwmQAAmQAAkkTWDuO1vFD36/OFKxEPiGH1Er7rj0lFAEVDNJ6zb1WpLHGAcxNmNXYnyWwrhoe5n4wrLNGeKfZJHkM4Ysk58kQAIkQAJuArQAdPNhLAmQAAlUNAHf0tykfBhh17+p59QZLSVcgEcf3VN8Y3ydOLJ7jfjPp5aIhe/udCVnHAmQAAmQAAlkTUDf8MNUEAS+n00cFYpvGCOxGciN578v1u1sFrB2l5Z/EMXwkg1pkvKta7Kyk4JjUi47TH32XXO9THTlTeoZw1UH40iABEiABA4RoAB4iAWPSIAESKDqCPiW5vri4wBr2tsaJ7nAct9/v+AEcfKgHuEkCpYEDCRAAiRAAiSQTwI2VxO4ftslo0Tf2k5en3b5EOpsVnalsJwWQl42IclnjGzqZx4SIAESqDYCXAJcbXec/SUBEiABhYBraS6sCqQlg5Il68O4D/qwxJhw75zQIfvyDU1Z18uMJEACJEAClU9gzJDe4tqPHZNzR68+Y6iA7zo1YDx8+KoPCYyZ8I8L0U0NUoTDNZ9Qp+aLc+yysvMtp0Wb8rlsOO74jn7n+oyR7z7FuTdMSwIkQALlQoAWgOVyp9hOEiABEsgDASzNhQ8jfUIjlxQlWaUUG/WJk68OpG/cutuXjPEkQAIkQAJVSuC8E44Q3/qXEWJony5idrDhRJSlvDZUUx59LbRAv/tzp4junduL/j27pF6GQUSzjWG4/relG8WmpmZnGpSRzcs1n5WdbTltPqwRdXau8X3csMNEh3Zt05jk+oxRiD7pfeQ5CZAACVQCgTbB2xN6VK+EO1lmfWhsbBSDBg0KW71mzRoxcODAMusBm0sClUcAkxJMIPAmP5vJSRQieGj/+q8axIvLt0RJzjQkQAIkQAIkEJkAhKWrAgu+L/zPK9Y8sBT8+tnDxU/+d6lXKJRClfSvh403Jj0411p2lIiZV40R44b1ie0fEGP0+NtftFbx7PVnZozdmOZd+dC8NPFNFoC+zbhijDzN+dMnyiX1jFHIPuUMhQWQQAkR4Py7hG5GEZtCC8AiwmfVJEACJFBKBCD6JSH84eHc5vgck6gvjh1KAbCUbjzbQgIkQAIVQkBa50Hcksdq18YM7iUe/8rp4aVxw8eFFnsQyGwBZcBCXgpl2Sx11cuuremQIcqpQqNtDHVZ2SG/afyOsmzYlE9vc5RzjO/gZBP6knrGKGSfovSbaUiABEignAhQACynu8W2kgAJkECJE/BZAKD5S9dzJ98Sv41sHgmQAAmULQGIdk9eOzZsvyoCYhOP751/fOijD+4vEDq0O/gZnlj+QRkQtSBguUQ4S/a0yxDq7nx2WYY4KYVGl0sOCGyu+LSKPjjxLRtuWLU1ZfmPvkkuprKiXktK6LPV5+uTbSm0rTxeJwESIIFqIkABsJruNvtKAiRAAnkkAKsF3ZcgqpMTG2lBMaJf9zy2gkWTAAmQAAlUO4Gm5tbQGu31NdvFD36/OFzqKzeWUq3tolr0SVFJ+s2d8qv5YlbgazBOQL1Tz6kLN7cy5cNYefXDr4q572xNi1bHUJ+VXVrG4MTXv28/sSiVReWSupjlgc2KMcvi0rL5+uSLTyuMJyRAAiRQZQS4C3CV3XB2lwRIgATyRSDKshzUjd0Ve3ftmK9msFwSIAESIIEqJwARCCIUrO30DUGkoAZE0qLPh0sVlbrXtBft2/otB2WZt158ooB/PrwEa9rbKi8bP3XxTyZCm2GFKAOs7M4Ybl72K9PgM2r/kFblgvNsA1YCYFk1/BXCXyI+cY7rSQRXnyBigg0DCZAACZCAmQAFQDMXXiUBEiABEohJwLcsB0uN4ED97c27g+VZH8kQASEKPnLVhwQcpD/4xdPCXRhjNoHJSYAESIAEqpyAFIGivJSSFn14MWULsjwZ7ypXppGfWHY8+ujeoRCHa6qQKNNE/fzLkvWhCAhhM2qQ/UMfogRdaIySR03jWwmgps322NYn9BFLpBlIgARIgATsBLgE2M6GMSRAAiRAAjEI+CY2+lKj5791lmhYtU0sXbdD9OjcURx1WBfRr0dNOFHCBEu32lCbcu1Zx4h7XnhLvcRjEiABEiCBKieAF0l3TBwVCmUQzFxBLuvFstqHrvyQeH11sFz4DweXC8t8JlHJ97JL5sUnxjFYwMlypPUahDY9nNi/u1i01u4j97+eeVPgT5aFdkcJ+rLhtdv3CHU81suQXPTrUc5d4qgUF5Ow0NP7hOePJMqN0kemIQESIIFyJkABsJzvHttOAiRAAiVEwDWx0Zsplxrhbf3Mf6xMc4iOyc3E+qP0LGnnHxraW7y0bJNzspSWgSckQAIkQAIVT2DrrpaDfvRWbvP2VX9pNeqonuL3U8aF4iFEMJuopOfzVhQkkGMelgGbNvJAGRD/IGCiD66gluVKp8dBIMOfupRYT4PzbPony/GJo7mIi7IO9VP2Sb3GYxIgARIgATsBLgG2s2EMCZAACZBADAK2ZTm2IjCJufoX89LEP6TF9emz37ZlC6/379lFfO1jw5xpGEkCJEACJFB9BOZGEP/woslmMYbrLv968mVXXLIY2yC+wXpt+uR6MWZI74wiIP5F8ZEry8ooIMIFV/vlUmi460Bb4yw3RtU+8dAVj7pQZ7Z1R+g6k5AACZBA1ROgBWDVfwUIgARIgASSI6Avy/EtNbJN1HAdkyOTQ3RchxVBpw7tkms4SyIBEiABEqgKAnIJra2zEKKwlFVaAUIwwwsuGeTLLtOu9zKN7XPt9t2h8IjyTeMb8vksAGXZ2VrT2do/bthhYn/gXhBLlmWQrDC2RwlSXIRAqQeX6IoNQnSecevW6+M5CZAACZBAJgEKgJlMeIUESIAESCBHAnJZjm+pkaua80f2E3tb96f5AoRlBCZN2FkQIcpyKVcdjCMBEiABEihNAiMDn3iLg2WxSYWvnzNMXHjygDTLP13s69uto/jGY6+nWaabhCj1ZRd8DcI3X5Rw9/NviZMH9QrFxSjpXWlc1nSufIhT2w8hsV/3GvGjp99I6zfSQciDMIely1GCTVyUDE1l4B7o4h/Sxa3bVDavkQAJkAAJpBOgAJjOg2ckQAIkQAIJEnBZA9gs/GT1N/1xiTwMdwRuFxhgzF+zI3UNB7CUqO3UTjTt3Z92nSckQAIkQALlTeA/J5wo7nxuWYYolW2vXn57q7j+3GNT2U1WZxDGcF0NLiHq4DLifpEFQLzAgth14wXHq1XEPnZZ08UpTH1ZZ7LaQ1m4jpd5B/vqL10XFyFUuvIWauMQf8uZggRIgAQqnwB9AJbZPX7vvffESy+9JH7605+KSy65RAwZMiRcloA3boMHD47dm8WLF4uvfOUr4phjjhGdO3cWffv2FWeccYa47777xL59+2KXxwwkQAIkoBKQ1gCYrKgB59MmjQ53M1Sv246xk6Iu/sm0FP8kCX6SAAmQQGUQwBgxJFh6m2SA+Cat0m1WZ7r4J+uXIhjy6X7q5Isumdb3GQptQTn6uCjzwbIdy3FtAfmwkUiSAVaAruCL1/OCkxr0czXOV7YvHmWZ7otaB49JgARIgAQOEqAFYJl9Ez75yU+KF154IZFWT5s2TUyZMkW0tBzabay5uVnMnj07/JsxY4Z46qmnRJ8+fRKpj4WQAAlUJwGXNYBtN8TqJMVekwAJkAAJQOD62cRRxmWhudKBmARrNJfVma2OFRubxC1PLUmzSBwzuJe4ctxQMfWcujCbzYpOL3Pdzuawj2ff9mKGzz9Ytm8L/lC26if35IE9xM0XjhTYrTjp4FtO7ItX22OyrJSiJZ4H9OAr2xcftz69fp6TAAmQQDURoAVgmd1t9Q1a7969xcc//nHRrVu32L14+umnxTXXXBOKf0cccYT4+c9/Ll555RXx5z//WXz6058Oy5s7d6741Kc+Jfbv59K62ICZgQRIIIMAJl36zopSHHz2+jPFzKvGiJsuPCEjHy+QAAmQAAlUBwGIXvA3t3LL7jShLaneQ/iDBR8244gbps9ZmdEmCHTXPNIgJtw7Jyzupk9GW9oLUWvzey0Z4p9s0z/XNYXiH1xl3PeFUwXGyN9PGZcX8Q91uqwYId65lvDKNuMT8xSXPz89rbwXuO+m4Ks7Tn2m8nmNBEiABKqNAC0Ay+yOf/7znw+X7NbX14thw4aFrcfSXywNjhpaW1vFddddJw4cOCC6d+8u5syZEy4BlvnPO+88ce2114p77703tAScOXOmmDx5sozmJwmQAAkkTgCTC0xA7npueeJls0ASIAESIIHyIABB7bG5q8X0Oe/kpcE3/eGfYbnH9quNVX6Pzu2tu/bKgmD9t6vF/9JcilqzlmfulCvLkp9Ytty1Y7vIm3DIfHE/pbsOXbyTlntRy3NZVspl1BjvTVZ7+qZeUeqOWl/U9jMdCZAACVQ6AQqAZXaHv/zlL+fc4t/97nfi7bffDsv57ne/myb+ycJ/8pOfiEcffVRs27ZN4JgCoCTDTxIggXwRwIO8utwpX/WwXBIgARIggdIl8O3fLsp7495c3xSrjh17ovnFhmB3arBEd/7q7cbyYdE3sX5QaIV4ZLDzbpSgCmdR0mebBhb50yfXh1aOS9fvFCP6dQ/9FEIcjBp8/voQj5d9utCI8rH0GXyuO3uYgIVkFKvDKPVFKSdq/5iOBEiABMqdAAXAcr+DWbT/ySefTOWyCXtdunQJNxm5//77xZIlS8SyZctEXd1B/yapzDwgARIggQQJ+B7kE6yKRZEACZAACZBAXgi07DtgLLd7zUErQoiECGfV9RHHBZaIb0QQIzE+5lvIMlnlSSs8k+8+Uyd9/voQ77LaA5uo4h/qj1KfqZ28RgIkQALVSoA+AKvwzmOTD4Rjjz1W9OvXz0rgzDPPTMVhmTADCZAACeSTgO9BPp91s2wSIAESIIHCEMBSzw8NTn4ji3y3HgJelLB47U5jsp3N6VaELyzbLN7d7t59VxaU7/ExKV96UXwJ+l72+eIlE3xGqU9Nz2MSIAESqHYCFACr7BsAX4Fr1qwJez1ixAhn79X4N954w5mWkSRAAiSQKwHXg3yuZTM/CZAACZBAaRDAUs9lG3eVRmNitEIX8ExZsVNvnBCnTHUjQL0OxK3Y0CQem7c6/FseHLvS6/ldVnlyCbKex3SO5cI/nDBSQORVA85xHcEnZvri1XKl70JYKqpBWi6q13hMAiRAAiQgRLRXWSRVMQQaGxtTfRk4cGDq2HQwaNCg1GUpGqYueA7UekxJ161bZ7rMayRAAgUkgMkBHvrxth0P3BDg4vj6Sbqp8kHe5Bso6bpYHgmQAAmQQPEIbNvdWrzK81QzxL+bLxyZ2hE4qWoWNO4Q429/MfTHd8elpwh9OS6W7k751Xwxa/nmtCrHDTtM3HPZ6Iz0aYk+OPFZ3SE+yhJkPFf8x5OLM3Y3huiL69jhWb7sg7CoBwh3UepR84EHysWOwvJ5Jm4Zank8JgESIIFKJkABsJLvrqFvTU2HnB5369bNkOLQpa5du6ZO4uwyjEyqeJgqhAckQAIlQyAJXz9xOhNVbNQf5Pe27hdferghTlVMSwIkQAIkQAIFJ3DbJaOc4lauDYJghhdkELtkwNiKa7r4h/jZK7ZkpJf59M/amg76pbTzqFZ5USwJIc5ByNRf9uVqtYdyKfyl3TaekAAJkEAGAQqAGUgq+0Jzc3Oqgx07ppvnpyI+OOjUqVPq0p490XyUpDLwgARIoGQJyAmD/vbdNLlIohM+sdEkDuIhvm9tJ3H5/7ycRBNYBgmQAAmQAAnkjQCWuGLMslmyIx5WcLkGjNOwdJNCl0twQ116elP9GIPv+OubpqjwWhyrvKiWhPrLPgiMsk/WhjCCBEiABEggZwIUAHNGmFlAEkvoZsyYIWw79GbWGP1KTU1NKnFLi/tBZO/evam0nTt3Th1HOfAtGcYS4DFjDr3BjFIm05BApREwCV9J/H74OLkmDFEmC77y1Xif2GizAvjZxFFi6qPzxYJ3zc7U1Tp4TAIkQAIkQAIuAmOG9BZy911XOl/cCUfWisbtzQIvttQAcU9a55nELYiDusWbml89xlJiLPu1BXU5rk9wQxlqelOZeCbAhiS2MPWcOltUxnWfpaAeD9GPwl8GRl4gARIggbwRoACYN7SlWXBtbW2qYb5lvbt2HXLQ7FsunCr0gwOff0E9Pc9JoNoI+Kzi8snDN2HwTRbitM0nNl79i3li7sptaUVChPzyw69mXE9LxBMSIAESIAESiEBALi2NKsDJIscM7pUxDv1z3SFXOjKd/NRfoMHXHYIcc6dPrhePv7pGfPuJRTJLxuetF58oRh/dO/T5lxH5wQVVRFOPo6Q3pZHtM8XhWtPedLFTTae/yBzap0voqxAs9BDHklDPy3MSIAESIIFkCFAATIZjWilJ7Jh75JFHppWZ1MmAAQNSRfk26lCt+OjTL4WNBySQMwGfVZzq3yfnygwF+CYMvnhDkdZLvomFLv7JgmzXZTw/SYAESIAESMBHAKITLMo3Ne0VV44bIiadPli0bytEy74DXv+y150zXPTrXiO+9ZsFTos8tQ3yBZrtJd/U8W5rOoh/cTbJcKVFu9B/pFE3yMC5utrAN+bb4m19xG6/2PBDFQGlCKuy4jEJkAAJkEDhCVAAzAPzESNG5KHUZIqEBSDEPIh7S5cudRaqxh933HHOtIwkARKITsBnFaf694leavSUrglD0m/obROH6K1lShIgARIggUomMCSwGntn8+7Euzj5I0eLDw89THx5ZkPa8l+Mc2fW9fXW9/qa7eKE/u7luHohGPPwkg8uLPRltRDEEIf6VXFMloGlwys2HrQwvCMQLb/x2Otp6UwimvQ5aNsFGGLclQ/NM5aD+hBgtWeydkSc7ZnA9SJT7vario7VtMwXbPCcBzEY3wddcAVXBhIgARIoFgEKgMUiX8R6x40bJx599FHx5ptvivXr14t+/foZW/Piiy+mro8dOzZ1zAMSIIHcCPis4qQFQW612HPLCYO+HMo0ubCXEi3GJTYm5ZMpWkuYigRIgARIoBQJtGvTJi/NeujvqwT+9ADxDeKUL9z2l2W+JGnxUix7ffX2DPFPJoQo+LuvfiS0KNQ3BYFF3TWPzA+TnlXXR9z5uVNDy0UpJNlENAh5M6/6UNinhlVbw/zSklAX/xCJ/kt/hdKKz2R173omiPoi09bmsJEV+I/kqQq8kqMUXCuw2+wSCZBAGREIjOAZqo3AhAkTUl1+6KGHUsfqwe7du8Xjjz8eXjr++ONFXZ17yYKal8ckQAJuAj6rOF+8u/RosXgQxVLjZ68/M5g4HPzEedIPqFJsxAOwGnA+bdLo0LpAvc5jEiABEiCB6iKwIrCWKnRYs21PolVKkQfWXz/4w2Jn2csCKz9d/NMzQCi89pcN4QYZZwzvG2mjDIhtE+uPCv9w7BXpNjRZNybBCzrXM0GUF5l6nyr93GUVCcGVgQRIgARKgQAtAEvhLhS4DZ/61KfE0KFDxdtvvy1+/OMfi89+9rPimGOOSWvFv/7rv4pt2w465scxAwmQQHIEXFZxmEQU8o056sp3fVJsNC0HwvKki+6ekzYZQnq8RWcgARIgARIgAUnghP7dRdeO7TI25pDxhf7EslnpJxAvuxY2bhet+9/3+gvc03ogUlNnr9gSWvVlO0b7RLqG1dvSlgarjcKOydIdiWlJq+9FpS9eratSjr2Ca2B1mu29rBRG7AcJkEDxCVAALP49iNWCFStWiNmzZ6flkbv54lO36DvvvPMylvh26NBB3HXXXeKTn/yk2Llzp8Dy3u9///tizJgxoeg3bdo08cQTT4R1YLnwpEmT0urjCQlUMwHTgzAe/OMEaRVXiCW4cdqV77S62AiW8BWkW0JA/KutaS+amvflu0ksnwRIgARIoEgERvSrFUvX23fV1Zt13dnDxL+c0E9MfODlNJ9+erpCnONl3dRz6sT6nXvEjcE4BsEsanh64dqoSQWW9GYrGvlEuI07m53tgIDYt7ZThpVgaO0Y+CjEp7rUVRZW6BeZst5if/oEV8Rney+L3TfWTwIkUDkEKACW2b2E+HfFFVcYW71ly5aMuOeffz5DAETm888/X9x3331iypQpYsOGDeK6667LKBOC4O9+9zvRrl27jDheIIFqJJCkbxeXVVy1sHW9Laf4Vy3fAvaTBEigGgmcelRP8V+fOVmMv/3FyN0fdnhtuHvttMtPE5c/+IrX0i5ywRETTp9cLzq0axO8oOog7nx2mZhw75yIOdOTwd9eIXzgulYb9O7aUdz21+XpDdPOsAOy/qISSUIfgsEGJXdcekpGfCgOBterMfgEV198NTJjn0mABApPgAJg4ZmXTI1XX321OP3008XPf/5z8dxzz4m1a9eKrl27Cuz4e9lll4kvfelLon17fkVK5oaxIUUl4PPtAl852QTdKi6bMso1j+9t+ckD4+2+WK4c2G4SIAESqDYCXTu1F0MO6xwKalg26wu6VVmn9oV1Y476zx5xeLiLr2ljDV/79fgrxw4OlzObLOjUtNjMI9tgW20A8U+3vNfrQH+R39Y+XN/UtDf0E2hy76GXVw3nLsFV//5WAw/2kQRIoDQJUN0pzftibdXkyZMF/pIKI0eOFA888EBSxbEcEqhYAi5rNTwIS185FQsgDx3zvQ2/+cKR4kdPLykZf095QMAiSYAESKAqCcxavlk8Om9N6DPPB+CM4X1Ca7PQBUfgR+2G3ywoqPUfrPUm1g8Kx3m0wSaK+fqhxsOaES8OV2AjjsCabvHanWp0eIx+x10yGjIKNlXBCzaMsRClwnoCbrgGsRUCpitArIJ1H3wauoJc0vr/2HsTsDmK89630I52fQgjsHYkgUGAWPTZGMmssTkmNkqcIIwPNogAOQYOGPuGc02usR3bj52ELRd84nAQW7yQPOTIzomvkwgQRnJiCcnsiyRAQjIIBNoltHPn36LGNT3VXT0zPfPN8qvnEd1dy1tv/Xq+Gfrfb1V18otMl0+S4Gp5unU5hwAEINBTBBAAe4o8/UIAAi1FIBStZv9HuKUG1cPOht6WTytMEXvwylObYr2nHkZF9xCAAAR6jMARw/ub1zftyr3/Ox5ZGbQp8e2Oi06K6uUReRfsMFZhaGE9Wq3vZ9f4U2R6rcmNBpt02BDzw8s/kstU2rRlSqxI9/iK9ZndD72kC5Vn7qiNKrK8SxvdTIYCgTYlgADYpjeWYUEAAvkSCP2Pbqg8X2/aw1qWt+Wqo/WeLr//ieIDWHuMnlFAAAIQaA0CvQ+qz3TbdVvCoqKEN61Dp1RJ5N3Qg/uYYwqbjPznqxtrgrwlthnVU2s312RvxqRDoug610hcNNLae/rtUwSe/t9CL8t0nZayLlOS5f9VxFnMteahxEofd1fETPOrU8us4Nqp42fcEIBA8xJAAGzee4NnEIBAExEIRatVOk2niYbWo67EH3zsw46mXLsPPz+5/MPmxL+YbxThQIIABCAAgcYRWLPx3WBnWdaVCxpJqOAToBKqFrO3vLvXHNyvj5l//emF6MUd5o5HX26Kl0h9e/cy+t1T8k3XTdp1VzsOb921J1EQzLpMycjB/UyWeyXmsslGH8WPFCcQgAAE2oIAAmBb3EYGAQEI1JtAlmi1evvQzvbt23IJfPFpXoo00MMP4l87fwIYGwQg0IoENCX25gummUMLwtKZNz8W3FyikWOUiHXjecZ8bMoHzAljRpRNs22kL7Yv+aQ1g31C3xlTRhrth6L1Ed2kNvpnk34TJcxZIVH5K9/aaou9Ry1ToheZXyqsNxjaAMQasEubuGsI6iUdLzwtofyPPlE4FP2ZvxdYhAAE2pkAAmA7313GBgEI5ErAF63G/wjnhzhtCtPrm8IRKPl5giUIQAACEAgRsEKU1smTQJVVWArZzbNc0X9KOl586njziWMPK1wdZP5p2doe22BKvnz7X54vEfXk44LlpcKf8nxJrDVF98bzjjmw2UdhyvDdC1/1VS3mSbhLixIsVnRO3OnC9iWdU8xpzgTS1nB0xd6cu8UcBCDQYQQQADvshjNcCECgdgL8j3DtDH0W0h5OXnpzm68JeRCAAAQg0EMEPnPSaPMfL79t5i5a1RTTa30Y/upfl5tnflu+bp/W4tO/hSvf8TWra97e/ZWtZ+hz5kBU4GO+orK87vEjoqi9SjYAYY2/Mox1zUh7ASqxV1GYJAhAAAJ5EEAAzIMiNiAAAQhAoGYCoZ2Wa+4AAxCAAAQgkBuBq398YHOO3AzWwZBP/FM3Ev4kjDU6SVjr2zt9Q4+8fZozY2Jk0o3oS+vDRnam1aEsXwJpL0Al9mraODNO8mWONQh0KgEEwE6984wbAhCAQJMRyPpw0mRu4w4EIAABCLQggcWratshuNIhW2HtrS07K21aU30rHKVtZtY9octcc9akaJMRW7+mTmlcEYHQC1C7HmNFRqkMAQhAwEMAAdADhSwIQAACEGg8gbSHk8Z7Q48QgAAEIACB6glI8Lv2nMLuvTsP7N4rYU3rvGn9v0Yl+WAFvaTNzLSRy1c/+SGjIxtONOrOlPYTegEaKi+1xhUEIACBZAIIgMlsKIEABCAAgQYS0IPHrbOnmY9+9xGzY/e+BvZMVxCAAAQgAIHaCEhsK27M4dktV+u8XfXDpQ1bd9BGHLqjspuZPfnaJnPTz541T63dHP2bdeciY+uz4YRLrDHnaS9AXRG3Md7QCwQg0M4EerXz4BgbBCAAAQi0FoG3t+0Oin/fnjW1tQaFtxCAAAQg0LIEjho1JOi7Fc8UbTdz8u+i7tyGWset3puOzL1kunngsm4z//rTo40jfGKehMjbH14eCX+uf3Z3YTeP88YQsNGZ+hy5yX6u3DzOIQABCNRCgAjAWujRFgIQgAAEciUQWgdn6hFDzdhDBubaJ8YgAAEIQAACSQQG9eudVFSWL3FNGzrot0zTNhXZZafVLnut/msO7t67z5x19OFlfrkZbDjh0miecxudKaHYfn7s9O3m8RJPIACBVieAANjqdxD/IQABCLQRgdA6N9+adZwZPICfrja65QwFAhCAQFMTWFaYLts1qJ/ZsH13op+Knvvi3z9h9uw3ZvGrG4r1tLnGnNPGF9bhG2IkDtY7zV20ypw7NV0ADL1oUznCU73vVLJ9sYd/Mh9KIACB2gjwFFUbP1pDAAIQgECOBELr4Ej8e33TDtM9foSpZQfHPr0OMh8ccbBZ/c6OHL3HFAQgAAEItCOBNPHPjnfRy78T/myexEArCEoMrHdSX4ogSxOQQi/afOVpkY31HhP2IQABCEAgPwIIgPmxxBIEIAABCNRIwK6Dc91PfmMUUWHTzMkjzZ59+805tzxms8zAvr3MDoVbVJH27n8P8a8KbjSBAAQg0K4EDu57kHl3T/2i9CTOjRjY12zcsaeuCEMRfKEXbXHxUDsXx3+T7dp0vjUG6zo4jEMAAhCAQE0E2ASkJnw0hgAEIACBvAnYdXC0iHm0mPmXPmYUsRdfPL1a8S9vf7EHAQhAAALNQ2Bw/+xr9snrE0YPM3d/4ZS6in+WjsS/k8cNt5d1Ofoi+NyO7Iu2LBtOKPIvLv7JFhuGuEQ5hwAEINA6BIgAbJ17hacQgAAEOoqAXQdH05ncaMCOgsBgIQABCECgIgLbdu0z2g23b++DzH++/La5c8Erie2POmywuW9Ot/nX59Yl1sm74E9mTDTf+8wQ8+PFq83dC1cFzSsCXkKc+xIsaU1CiXrxCD5fB/ZFW2jDCTYM8dEjDwIQgEDrEkAAbN17h+cQgAAEOoJAaMHyjoDAICEAAQhAIDMBiX8zJx8a7cSbJgC+9OY2c8UDS80njx2V2XatFf/HPz1jfvlnZ5rPdo9LFQC/95njCtGCXUVBzxXrDh3Svywyz07LrcQ/+6ItqU3o9zc03TjJbj3zWa+wnnSxDQEItDoBBMBWv4P4DwEIQKDNCYSmM7X58BkeBCAAAQhUSODlQuS4fjsmjhxoJIylRZFrbb4X39hSYQ/VV9eaepff/4R58IqPJPomn2dPH1vSSVysu+fS7mjDD4lwGmuWyL8SgxkuQr+/ofIMXeRahfUKc8WJMQhAoA0JsAZgG95UhgQBCECgnQhowXLt+kuCAAQgAAEIZCHw9X9+Pto06rL7njDfnDU1EtrS2m3ZudcMLewy70sfmdhlzpgysqSoa1DfkutKLyQ6anrtbReeWOZbJZF8Ev0U6VgP8U9jshuG+MYnP+vVr6+/UB7rFYYIUQ4BCEDAGARAPgUQgAAEINDUBLRg+ZzCmkmhdNKYYWUPUqE2lEMAAhCAQM8QGHZwb3PsEUPr2rki/67+4TJz43nHmKvOODK1L4mA3RO6SupI5PqrPz7B6HfITcccPrQgvJWKgm55lvOlqzdEoqPWK9S/Pzv3qOio82bZXbeSDUOyjLmedbKsV1jP/rENAQhAoBUI+F91tYLn+AgBCEAAAh1DIBRlEC1oPufD0UOT1knSg9UNDz3TMXwYKAQgAIFWI3DkoUPMstc21d3tp9ZujqIBB/YL7w58zVmToum0dlqtIuDm3LukbAqxNuSQOCixTuXVJP1G/Z+n3yjb4MNGADaLCJh1w5BqGOTZphXXK8xz/NiCAAQgkIUAEYBZKFEHAhCAAAQaTkDTeSTmPb5iffSApIciXxrUv3e0i6OdviWx8IjhB/uqkgcBCEAAAk1CoFLxb3qNS0Hs2L0vOHK7lp6dVhuKKhsz4uCaIs8fX/F2ye6+clBRi9f95DdBXyut4P6m6rdV15Uk/bZaLpW0a1Td0HqEofJG+Uk/EIAABHqSABGAPUmfviEAAQhAwEvAt5D3jEmHRFOu9MDkpu279plZdy6KHsK0npKiFfgffZcQ5xCAAASqI6CJr5XJRNX1k6WVpqPO/9LHzP/33Drz9NqN5t+fX5+lWeY6eskUjzYPRZWt27IzWsdPgp1vo5HhB/cxm97dm9kHW1G2JNLF/bHl9igRTyKlG7EYn66sur7f1DwiDbP2b/2t59GuV+i7D757W09fsA0BCECgWQkgADbrncEvCEAAAh1KQA8UvocpO+VKD4Bf/senjKZ1uUn/03/tj5eZewtTgScccrD50OFDzAtvbHWrcA4BCEAAAhUQaBbxTy5r44yv/u9nzOJVGysYQbaqJ40dHgl58dqhl0mvbzqwA6+mAlshbs++90yfwhyr2+avqGmKs0S9NAEwq6iX9Juq30z91mo34WpS1v6rsV1NG7teYfz/H6zQWY1N2kAAAhBoNwIIgO12RxkPBCAAgRYnEJpydfGp48vEPzvkBcvfNv/63BvR+n+bduyx2RwhAAEIQKANCNRD/FPU+D998TQvHUWVaQdg/bb4kl1r1opMVrBb8ebWmsQ/9ZUmPlYi6oV+U7NEGsbHXkn/8bb1vG6V9QrryQDbEIAABNIIIACm0aEMAhCAAAQaTiA05erFdVtSffpiYcfHfftTq1AIAQhAAAIQiAgokk0imMQ+G8Un8U3X2hm4ENAXTIqmu/z+J4zdREQbUdWSugvrHdrfQvkRn9YbEvUeefEt07f3QZGI+PqmHamuhCINfY1D/VcjKvr6qTZPQqwVY6u1QTsIQAAC7UgAAbAd7ypjggAEINDCBNKiHjSso0cNTR0d4l8qHgohAAEIQCBGQILVt//l+ZJ1/BT5J/Evvu5srGnxUlOUL757cXR91GGDi/lpJzMnjyzbBbhrUL9omrO1ZaMLFd1mkxUH7XX86O5M3D2hK15ccp30m6sov7ggaoXIUP/ViIolTnEBAQhAAAJ1IYAAWBesGIUABCAAgWoJKNpBDzxJC3mr7ITRwxKnAVfbL+0gAAEIQKAzCdz8ry+aFYXNNNyUNO3XrZN0/tKb25KKovzvfeY4c/K4rmKUmgRIRerd8ejL0VqHbmPfWn1Jop3bzp5LmJSouGH7bptVPCrSUL+5NlnRT/7MXfhKyXqLrhAZ6j9UbvvjCAEIQAACjSVQWKKWBAEIQAACEGgeAnYhbz1suMk+fKj8G+dPdYs4hwAEIAABCFRNIC7+VW0oQ0NF/c2ePjYS3iS0Pb7iwG7GRxSmHUus8yWJgKprk31RZq9DR4l/EvviSWsqKlpQ06D1T+fn3PKY+dO/X1oi/qmdFSJ1nta/fquZfitKJAhAAALNR4AIwOa7J3gEAQhAoOMJhBbyVgSgHjJ8UYIdDw8AEIAABCDQFATi0er2RZZvB13VTUvutFr7ouzy+5aUCXVJNq4+a1JihOG1P14WrTMY+k21QqQEvtsuPDHaRdhtY8eX5AP5EIAABCDQswQQAHuWP71DAAIQgEAKgaSFvO3Dz3U/+Q0iYAo/iiAAAQhAIH8CIwb2NRsz7DR/8wXTos4l3mlarH7TNM1WkXaucKZKT63dnOpofFqtXpRdc/bk4rqDqY0LhXsLm2MlRRhWMt3ZCpGhF3UhfyiHAAQgAIHGE0AAbDxzeoQABCAAgRwIDB3Qx9x43jHm3KkbzFtbd5mb/215DlYxAQEIQAACnUZA02M1HTaeZkw6pLCbbq8SsU55egkV2hzEnQrrTolN20E33r+9dm3ZPB3joqBb5p6rvXYFziPF+0x6UZdHX9iAAAQgAIF8CSAA5ssTaxCAAAQg0AACvulTSYucN8AduoAABCAAgRYlYKetxiPKbb4i3bT+niLfRg0dYL7z8xdKBEHfsG1bX5k2+0hLSdOGfW3sWnzxaEK3rvVlfeFFWa1Jtlwxs1Z7tIcABCAAgcYSQABsLG96gwAEIACBGglo+lT8QU0mtcg5ImCNcGkOAQhAoIMIWHEsNJ3VRrlJCEwT2777h1PNB4YeHEXbSXBTpLqiBd2kqbhp6dpzppixXQMjwfHwguBYMGCeXrspivaT4OfaS1oOQxGNc2ZMjMQ6K9jJF43X5/8ZU0ZGdn1l1lfLyl5zhAAEIACB1iOAANh69wyPIQABCHQ0gbTpUxIBrzrzSHPnoy93NCMGDwEIQAACyQSmHjHUfOsPjjPTxgwvqWSFvpJM50JRgGnpx4vXlKzlZ0UzCYw29ellz/xHTdWVH4cO6V/2sstnLyRe2l6SxEJrU/XiL9e6J3SZOaeNL/gzhMg/C5IjBCAAgRYmgADYwjcP1yEAAQh0IoHQA9jDL7zViVgYMwQgAAEIZCTw7OtbzO3zl5t7Lu3O2OJAtfj6d/HG8Y08FFEnUc32owj2UASg+ti/f7/x7fAbt+f2HxIvVTckFspPO91ZftjoQduP/NdLOP0OqzwekWjrcYQABCAAgeYkgADYnPcFryAAAQhAIIFA6AHsxXVbE1qSDQEIQAAC7UJg2MF9zOZ391Y9HIlpErskcllhS+vzSaBTlN4RwweWCVxZ1tyLO2T7GTm4n7ni/ie8m43YNorGU+TfhXf9OrGetRcX56wN92jHFRfs0sTCpDLf2rs2etCNcHT75xwCEIAABJqLAAJgc90PvIEABCAAgQABPYBpvaIFy98uq3nUYYPNS29uK8snAwIQgAAEeo7A9z5zXEHYGhCtjff6pnfNDQ89U7MztYh/tnMJY76ptrY8LnDZabRX/2hZcBdga0PHFW9uMRf84LlorVo33z2P+po9LYoYXPzqBreo7Fx+hwTAPAU7CYnx6cFyKi0iscxpMiAAAQhAoMcJBFah6HH/cAACEIAABCAQEdADiKI1/vW5dWbrzn1eKpWIf3/2iSlm+rjS9Z+8RsmEAAQgAIGqCSg6TP+0scWMSSPNyeO6qraVd0Pt6usTtmw/VuCy1zpqM40+vUo39nDLfeffX/Byqvg395Lp0TTh9dt2ezfpiNsMRcKHBLu4vdB12tq7NiIxZINyCEAAAhDoeQJEAPb8PcADCEAAAhAIEPBFMgSaBIv3vWfMktWbgvWoAAEIQAAC1RPQ9/ef/v2yyICi3G4tRLlpEw6tw9eTSb4ook8CVlqyApeNuEsTw5LsPPPb9LFq4w8lRfaFkvy2viTVTfMxPp4kG25+yK8sEYmuPc4hAAEIQKBnCBAB2DPc6RUCEIAABAIEbMTfL5e/FS2GHnpIC5grK77535aX5ZEBAQhAAAL1I6DvcUXc9e/Tu36dOJZnTh5p9C+eZkw6xNx24YmZBDe1dQUw9zxut9prG9Fnj0l2usePiPxOKrf5IR9D5daOPYb8CpVbOxwhAAEIQKBnCRAB2LP86R0CEIAABAoEJPa5OwseWlgs/boHnwxGZgAPAhCAAARai4Bv/VZ3BHmt5aqouu/84XFmzIiB0fIRS1cfWFdPU5BtBF0hADBTcgUu9zxT40AliXrWn7RNRrondJl/uPLUgLUDxSEfQ+XxTtL8yhKRGLfHNQQgAAEI9AwBIgB7hju9QgACEIDA+wQ0PWzOvUvMObc8Zi6+e3F0PO17jyL+8QmBAAQg0IEEPts9NpdR7yms8/DlwoskJQlss6ePjf5ZsW3//v3mmh/9JthXXOCyYpiv4Qmjh/myE/O6BvUzd31herHcbjKiPt2k67s+f4qblXqe5mN8PKmG3i9M80uRlCQIQAACEGgNAkQAtsZ9wksIQAACbUkgaaHybbv2tuV4GRQEIAABCKQTGFPYLCQtKUJw2MB+JrRTrmwsXrUxiv6zop9rV5GIG3fscbPKzhWdJ+FQG1BJVJMQZsWw+OYhqvt/f/JD5g++/6syO74MRfRJ1NMGKW7S9T2Xdkd9aqquovV8/rtt4udJPkr8q1awy8OvuJ9cQwACEIBAYwkgADaWN71BAAIQgIBDIG2hcqcapxCAAAQg0CYEhh/cxxw3erh5fMXbZSOSKGY3xCgrfD/jS783xZx65MjU3XvdthLRfALai+vSN+YYPeLgSEBcvGppZM6KZxLC9E9C2uX3P1EUIiU23j5/ebTmoG9san/jecdE6wlmEfXks89vd2xp5/US7JL8ii/lYQXTNB8pgwAEIACBxhJAAGwsb3qDAAQgAAGHQKULkTtNOYUABCAAgRYksOndvdG6rxLE4ps7Karv24VlIdLSpA8MiQQ4iWmPvvRYWtWoLL7enRWq9u0vbAWfktZuLN2R125goug8G70ej0JUVOFJY4aZ+Nhc8bAWUS/F3cSiJMEusUEVBVrKIx4R6Y65CpM0gQAEIACBOhBAAKwDVExCAAIQgEA2AvEHsyytLpsx3ty9cFWWqtSBAAQgAIEmJLBw5Tvm36+babbs3GOWrt5U4uFL67aWXLsXEpWsgJblBZJbX3Z8QpVrP3QuEVDTgZXi4qVtu2zNZqNIxnlXnWa2FsaXJdrPttXRCpQa36ihA4z2KXljy87ITjNG1VkxNM7DFUzd8XEOAQhAAAI9RwABsOfY0zMEIACBjidgFyqPPzgkgZkx6RDz2e5xCIBJgMiHAAQg0CIErvrRMrP8re2ZvbURZbbBkP6la+fZfHvUmnzXnj2lMNV4fSSeTRw5sCxKzdat5JhFeFRkoKYDK1qwkhQSKC0DTe9tlpS2lId+2yWYWtG2WXzGDwhAAAKdSgABsFPvPOOGAAQg0AQE7ELl1/54mdHUqbSk3RW/8vGjjR7i9BCUVTRMs0kZBCAAAQj0DIGs4t/3PnOcOXlcV7QJh8Smp9duiiLjbnt4eaLjJ48bYQb172NmfX9RsY4EQa3TV2vKGrleqfiVFEnn+iubmmpbqbDo2sj7PCSIqhwBMG/q2IMABCBQHQEEwOq40QoCEIAABHIioEiGe+d82Dz52iZz08+eNU+t3Vy0fNLY4Wb33v3m2de3RPl6mJP4981ZU83X5j2LCFgkxQkEIACB9iRw+LAB5tAh/c2ce5dk/s6XmBZ/SZSH+KffH4lZsp/lRVQl4ldaJJ17ZysVFt229TgPCaKh8nr4hE0IQAACEPATQAD0cyEXAhCAAAQaTGBaQez76dUzoulCemjS2kff+fkLZQ9xeviR+KcICE0tWrp6g7nhoWca7C3dQQACEIBAIwh86/88b4YM6GeWvpY9em9Z4YVSralrUD+zYfvuohkJftr5V8lGr19+35LUqMJKxK9QJF3RkcJJJcKi264e52lLeVjBtB79YhMCEIAABCongABYOTNaQAACEIBAHQkoukL/JO7FIzhst24EhB4+fvHsusS6tg1HCEAAAhBoPQIHpgpnXyuwmhEmiX3rt+6KxDYJefFprIpef/DKU83sv/tPE98NWD5UKn5VIhZWUrcaHpW0sWJo0i7AldiiLgQgAAEI1JcAAmB9+WIdAhCAAASqJBCKhrAREEkPH1V2SzMIQAACEGgQAW3s1Ld3r1xf4Aw7uE9ht9+9iSPQDr2uYGcj+3xi39ABBx6V7O9RfBde/f7c9flTyjYXsTYTnfAUpEXSudUrFRbdtvU6lxhqo/LFyieY1qtv7EIAAhCAQHYCCIDZWVETAhCAAAQaSCAU4aByrcOkdZP0wHHjeceYr37yPbOsME2MKcENvFF0BQEIQKAKAoq6u/NzJxuJR4r4/rfn15m//MVLVVgqbSLx76hRQ8xL67aWFhSurOBYVlDIsNHntsy3I68V9uSzTXmJX1leZtn+bd/NdowzbDb/8AcCEIBApxNAAOz0TwDjhwAEIJADAVeIkzAXj5Kopou0aAg9BPkWhVf+N84/1sSnc9n+Z04eaXYVNhVxoz9sGUcIQAACEGgcAa2vt37LzkgAPDC9dlQuAqBG4BP/jv/gUPPunn1m4cp3SgapJSXiO+vqNy0+pVWNfHWtsWrEL99vZzySTvaJqrOUOUIAAhCAQC0EEABroUdbCEAAAhAoTLXaU/agZKMU3CiJSlElRUNEtmdPK+tT9vVw9tSdvypZuN3227f3QeY7f3iceXX9NvP5VzfYbI4QgAAEINBDBL78j0+Z+y/7cCQCpr30qcUHVIh+AABAAElEQVS9IYVpvFt37jVP/3ZLohl3XVlVStuRN1430WigIO23My4mHhBIAwYphgAEIAABCAQI9AqUUwwBCEAAAhBIJBCKkkhsmLHATq2af/3p5oHLuo2Oio5Yv2134ppR7q6Nbjd79r1nLp37a/M3Dy93szmHAAQgAIEeIvDU2s3Ryxx1b1/66CVPnkniX5Zk1/lTXffc1zZU7rbR76SmOD++Yn101HU1v50+O24/nEMAAhCAAARCBIgADBGiHAIQgAAEEgk0IkpCncejISp5+HKdX7l+h3vJOQQgAAEI9DABN6LOvvR5srCW60X/69dmx+59DfPOXXfWPfc5ECq3bZKi/K49e0riSyyXR8jObReeGEVP2nocIQABCEAAAmkEiABMo0MZBCAAAQikEggJcaHyVOOFwqSIh6wPXyH7lEMAAhCAQM8TWLp6Q0mE3OABfRsq/inq0J1ma6cj+8jE6/rqKC8tyu+mnz2b1CzKd3870+xonUISBCAAAQhAICsBIgCzkqIeBCAAAQiUEQgJcaHyMoNORlLkhCIe7MOZIiVIEIAABCDQ2gTcndslsM2ePqZhA+oeP8LcWlhX1k12OnJ8IxD5pt+gLCktQl5Tn9OS+9uZZscXLZhmlzIIQAACEOhsAkQAdvb9Z/QQgAAEaiJghTifkaxREr62oYgH+3CmPtzUPaHLveQcAhCAAARajIBErbmLVqV63afXQanltlA7wvuSu0HV4lUbzZcefDLa0Mqta6cjx9egddu69ePnbhRfvEzXJ4we5ss28d/OkJ1QubcTMiEAAQhAoCMJEAHYkbedQUMAAhDIh4AV4mqJkvB5kjXiQRuCaHF1PQApYkKC5Jx7lySureTrizwIQAACEGguAosLO7UrMk/inC/t3f+eLzvKu+Sj48yHDh9qTh47whw6dIC5+kfLCtOL3y6prwhzN0l01O+YflPiKb4Gbbw86dqN4vPV+cb5U83t85eX/F75IgxDdkLlvr7JgwAEIACBziSAANiZ951RQwACEMiNgI2ScIU4dy2lajoKRTSo3PYRfzjT9Ky4IFmND7SBAAQgAIGeIzBnxkQzsN9qs2B5qXgX8ujeX62OqkhM09TerNGCeU+ntRHyshtP8m3amOGR4Bj67QzZsb+F8T64hgAEIAABCMQJMAU4ToRrCEAAAhCoioAeQmZOLl1IvSpDhUahiIa0citIatrWLRcczw6J1d4E2kEAAhDoQQL6Tfnz3z+2ag8kvF1x/xMlEXYhY6GXT6H2brmNkJfY56Z4lF/otzOrHbcPziEAAQhAAAI+AkQA+qg0cd62bdvMsmXLzOLFi6N/S5YsMatWrYo8HjduXPE8NIQ1a9YU28vW0qVLzZYtW6JmN910k/n6178eMkE5BCAAgboRyCPiQQ9V+jdr2gfNubc/bpa/ua1u/mIYAhCAAAT8BIYd3Kewvt5eb6HW6NuwfXdZmUQyfX8/vqI8eq6sckpG0hTipCZpL5dsG61Rq2Uq3KUnJNL5kn0hFYry87V18/Ky49rkHAIQgAAEOo8AAmCL3fNPfepTZsGCBTV5vXr1ajN+/PiabNAYAhCAQD0J2IiH+FReLZp+7dlTjB7Akh64XL+0ztPl9y1B/HOhcA4BCECggQSSxD+58DefnWbufvzVkig9N0IuiyCX11Cs6JhmL213eol0Scm+kEoqz5qfl52s/VEPAhCAAATaiwBTgFvsfuqh16auri7z8Y9/3AwePNhmZTq6NvQAPWnSJPOxj30sU1sqQQACEGgUARvxMO+q04q7JT61drOZ9f1F0UYf8UXc9d2mKAtFjOi4f//+aC3ASiNAGjU++oEABCDQaAKTDh2YS5cnjxueix39b6023kjaaddGg9fSWZbd4V3RMakv/cbEX0qprt1AJKkd+RCAAAQgAIFmIUAEYLPciYx+XHTRRebKK68006dPj4Q7NVM0n6YGZ01Dhgwx3/rWt0x3d7c55ZRTzIgRI6KowjPPPDOrCepBAAIQaAgBPXBpl0QJf26yD1x2x0ZfVIYe+rSTJAkCEIAABA4QWLl+R80oJJbNvWR6JHwtWrneDC9Evn1o1BDzJw8sq9i2jfBLimxLigbP2pEV9uLCnfKvPWeK2bpzT7TmrPoPpay704fsNEO5fluzTmNuBn/xAQIQgAAE8iGAAJgPx4ZZueKKK2ru65BDDjE33nhjzXYwAAEIQKDeBLI8cClCJP5wJ78Q/+p9d7APAQh0GgEJZ9+cNTWKwnZ3t9U6f3knV6S68bxjzI2ffM8sfW2jueGhZzJ1ZcU/G01e6zp8oQ1C3N3p4w66Y5Hoqd+tLMtYxO3kce17YeayyqMPbEAAAhCAQHMSyP/XujnHiVcQgAAEINCCBLI8cGlY7oNoCw4TlyEAAQg0LYHB/fuYv/6j482kw4ZEwtWce5eUfeemrfOXNrAk0SxJpJo9fWyaOfP1Tx8b+SiRLR7VlxRlmGrQKbTRik5WyWlSedJYbrvwxIbvUi8h0vfCLB5VXzIwLiAAAQhAoG0IsAZg29xKBgIBCECg/QgkPVDZkao8JBLauhwhAAEIQKByAtt27TVfnfesOXRI/2jaaJ4vXHzf8Wki1dyFr6QOYMakkWbm5AM7CKdWrKIwbT1CRdDFBUd1kTYWCXGNTlmi6hvtE/1BAAIQgEDjCCAANo41PUEAAhCAQIUEsjxw+R4g3W66x49wL82MSYcUHhBHluRxAQEIQAACyQQ2bN8d7ahezQuXrkH9vIaTRLM0kUqbOiVt6pFkz9t5FZl2PUL14yZdK5rPl9LGIiFV05IbmUL3L1TeSF/pCwIQgAAE8ifAFOD8mWKxQGDt2rWpHN54443UcgohAAEIiIB94IpPWXIfuKxI6ItKUT1tFBJf+0lRGY+8+Jb51ctvmwF9epn5L7xlXnqzsQ9i3GEIQAACrURA4tuefYVteytIJ40dbm7/7Inma4UIQvc72v0Oj5sLiVBzThtvBvXrXWLvhNHDok099N1ez7X1Kl1PMDQWlfsiB+NM8roOvTALleflB3YgAAEIQKBnCCAA9gz3tu91zJgxbT9GBggBCDQHgSwiobv2k9ZjuuqHS83Cle80xwDwAgIQgECLECi8LzES71wxL811CWZjRgws7hr84rot5uhRQyMbSUJdSIQ68tDB0YudJ1/bZG762bPRLvHaKX7WnYsiu41YW8/9TUkbf2gsofI029WUhV6YNVKMrMZ/2kAAAhCAQG0EmAJcGz9aQwACEIBAHQlkXT/JRmXMv/5088Bl3UZHRf4p302yd+2PlyH+uVA4hwAEIJCRwN79xtw6e5pRxF2WJKFQQp02DtG/v/zFS8VzvYzxJStS+cqU952fv2A27dhtbn94eST+ufXUX0+sref64J6njUVCaqMFN/vCTH27KS0i063HOQQgAAEItDYBIgDrcP+S3mhW0tU999xjLrnkkkqaNFXdNWvWpPqjKcDd3d2pdSiEAAQgkGX9JPcBKhSVIXsLlr8NWAhAAAIQ8BA4uTBld+X6bSZpV1+JeBKLLp850Vz942ybWNzw0FNlSyxYoU4vauLJilR6WeP7vlbbK+5/wmhKsi+pXEs89O19kFGEnUS4PP7f3NdXKM+OJW0Zi5CNvMvtC7P40hh594M9CEAAAhBoPgIIgM13T9rCo9GjR7fFOBgEBCDQswTyXj8pZK9nR0vvEIAABHqWwNJCtJ42Sdq+c49Ztmaz1xkJbO9s2+Ut82Umra8qOxKh3Jc4tr1Eqj///WPNglses1klxyTxz1aSUGmTjW6LR4Tbch0VHa4XRPqNyFs0bFbBLfTCzOXDOQQgAAEItAcBBMA63McXXnihZquHH354zTYwAAEIQKDVCYTWRwqVx8dfaf14e64hAAEItDuBx1e8HUX5zb1kejRd1zfep3+7xZddcV7aJhh5vbCR0KgIPF+0oRzWVOSkCL000bDSwSK4VUqM+hCAAAQgkDcBBMC8iRbsHX300XWwikkIQAACnUfArp+kB7h4UlSHL3IkXs+9njhyoJk+frhZsmqTm805BCAAAQg4BPSde/pRH3Byyk+POmxw2dTe8lrpOfGXMm4kXmjH4e4JXWbxqxvSO3i/NCnaMLTObJJomKlTKkEAAhCAAASajACbgDTZDcEdCEAAAhD4HQG7fpLEPjd1jx8RLUTv5oXOFeVx2X1PIP6FQFEOAQi0JAFN3f3IhBG5+f7jX69OtfXdzxxvugb1S62TVhh/iaPvaE3dPacw7ffiuxdH50n21fauz58SRSqm9eGW+SIKs6wz69rgHAIQgAAEINDKBBAAW/nu4TsEIACBDiCgKVi3XXiiUbSHTVr/6UsPPhlN3bJ5SUdFeKx8c6v5/N2/Nr5IwqR25EMAAhBoZgL6Tpz33z5a3Pn8/jndhY0veufmctLafepAfZ84doR59CtnmKNGDam4Twl4+l63KSkSb8P23WUio21r19azu79rynJaikcbqq5PFHRthMrdupxDAAIQgAAEmp0AU4Cb/Q7hHwQgAIEOJ2AfDONTvSTmpa3rJGy+tZ06HCfDhwAE2oSAvhNvf2RFJKQNHdDHPFrY+fbxlY3Z5XzOaeMjihLh7rzopChqLytWRXDHp9amReJJBJz7hVPM+vc3Hjl5XJfReG2ya+vpt0LioO9Fj/J9S0b4REFrV8dQuVuXcwhAAAIQgECzE/jdr2eze4p/EYGVK1eahQsXltDYtm1bdK3jvffeW1J27rnnmlGjRpXk6eIXv/iFWbduXTH/xRdfLJ4/+eSTJXYGDx5s/uiP/qhYzgkEIACBRhJIezBMWtdJ/lnh0Pcw2Ej/6QsCEIBAvQjo++2Lf/+E6dent1f4qle/kz7wu6i/tLVaff0rgju++28o0u72h1eYp9b+bldiNwrQ9mGXjEja0MPWc49pvieJhm57ziEAAQhAAAKtRAABsJXuVsFXiX+XXnqp1+t33nmnrOzRRx/1CoDf/e53zWOPPea189Of/tTon03jxo1DALQwOEIAAg0nEHowVLkvsiNNOGz4IOgQAhCAQJ0ILHo520YYeXUfF8YkvH1z1lRz/h2LjKL1sqT493Yo0s4V/2RfwqcvAtxOC5bAqD5k1/f7YH2sRjS0bTlCAAIQgAAEWo0AAmCr3TH8hQAEINDmBBS5J/HOPryNGjogdcRJD45qnyXlsZNlln6oAwEIQKDVCdjIO3cc+s7+2rxnM4t/ahv/3k6LxHP7cs/TIsDttGC3ftJ5mmgY/z2SnxINSRCAAAQgAIFWJIAA2GJ37ZJLLjH6V2tasGBBrSZoDwEIQCB3Ar41+/TAOWPSIWbhynfK+otHorgV4g+Ybpk9V/v/ftZk8wf/81c2iyMEIACBjiIwsSBqvVJ46ZKUtLlG394HJUbTVRptre/zeFReUiTeCaOHlUz9jfu4dPWG4suiWsW5uGiY9HukzUskGpIgAAEIQAACrUYAAbDV7hj+QgACEGhTAklr9inKY+bkkWWLu/siUVw0aREleqi8+YJp5tAh/aNpZG47ziEAAQh0EoE08U/fs2cd/YFUHFmjra2Rffvfs6clR18kniqcc4t/yRqV3fDQMzpEyf4m5CHOpf0e+aYeWx84QgACEIAABJqZQK9mdg7fIAABCECgcwikRZE8vuJtc+N5x5j5159uHrisOzpqF8m0Bz0bUaKHQjdJ/PvGp6eaiSMHRuKfBEYSBCAAgXYjoMi+WtO150wJmsgSbe0a+Y9XNpgVb251s0rOFYk3c/KBXXvti5ySCgkXdl3AhOKKstN+j+zU44oMUhkCEIAABCDQBAQQAJvgJuACBCAAAQiYaBpXGgdFmbgPhm5dRWto0ffHV6yPjrpWshEl8646zUj4U9Ji8rO+v8hceNevG7prZtQ5/4EABCDQAAJ68XHLH0+ruaetO/cEbVQi0lljV/9omdEU21BKepGT1C4vcS4U1RgqT/KPfAhAAAIQgEBPEmAKcE/Sp28IQAACECgSCEWRJJWH1mmSGHj7/OVl60gtfrWxO2cWB8oJBCAAgToROLhvL3Pn506OlkxQFxICa4lyTvredd23Ip2mxmbt66U3t5nL73/CXHPWpGhtwbT1++yLHLuz7+ub3i2Z+uv6onP7siieX8l1aNyh8kr6oi4EIAABCECgUQSIAGwUafqBAAQgAIFUAmlRJHqIjS8aL2OhdZpUJ20ql8qT0nEfPBAxmFROPgQgAIFGETj+/QjmUH/v7tlv5ty7xMy6c1H00uPW2dOKYmCobbw86Xs3Xk/XVqSzyzTc/YVTfNVK8vQS5uK7F0dr/MnnUESgjQA/eVxXiZ34RR7iXDW/R3E/uIYABCAAAQg0GwEEwGa7I/gDAQhAoEMJ2CgSPXS6SdfaddGX0sQ9OxWs2qlaV515pDn+g0N93ZIHAQhAoKEE/tvpEysS8qKlDgoi4JcefDL6/pQw97f/9WTTPX5EJr/TvnfTDFiRThuHaPOmrEnf14ogzJIaIc5V83uUxXfqQAACEIAABHqSwEGF6An/Vlw96RV9tz2BtWvXmjFjxkTjXLNmjRk9enTbj5kBQgAC2QnYqV6K5PBF/llLWvNPESRJSRuGyEbaLpJJbfXArFRN2ySb5EMAAhCohoC+j7Rr+efv/nXZcgYhexLiHrjsw8Vq+n5d+dZWM3fRKuMuhdA9ocvMOW184Tt3SOr3btFQ4EQRfZrm6/YRaBJt8JT2nW/bh5Z+sPWqOerRSC+X9PJIvx+6XrdlZ3Sexbdq+qQNBCAAgXoT4Pm73oRbwz5rALbGfcJLCEAAAh1FQA9ZWR60QlO9VG6jRXxrU3UN6mc2bN9dxtZOfdODn859bcsakQEBCECgDgT0PWW/D2++YFrFLyW0i7pEP2vDfr+eO/XwKN8KXbY8ryFoWvCDV3zEzP7Bf5jFqzZmMpt1/T475Tjry6JMnRcq1VNYzOoD9SAAAQhAAAL1IsAU4HqRxS4EIAABCNSdgBX3fB1ZES9tKtdPrz6tbFqddgu+9pwpUdSHbXvakelrTvn6Jw8CEIBAVgL9eh+UWFUvKSR0KaV95yUaKBQsXe3f9Eii38zJ/jVW0+xlLdN36F1fmF72PZvUPvRSJ94uT//1wse3kUkl05Pj/nENAQhAAAIQaCYCRAA2093AFwhAAAIQqJiAxDo9IGvNK5vi61elRYvcc2m3efK1Teamnz0b2bBrZ1kbQwf0MXv2sVqGZcsRAhDIn8BfzJqaaWdb+1LCJ1Tl71U+Ft3v39c37TB3PLLSGxFoX9rk02vlVrKsKZt3lGTlXtICAhCAAAQgUD0BBMDq2dESAhCAAAR6kIBvqpai977x6alm2tjhXs/08BZ/gFPUx+0PLy8RENXYRn189ZMf8j6sejsgEwIQgECFBPS9lXVnW31frd+6y8yZMcGcMHq4ue3hFZl6O2nsCLPyza1m6WsHpuLqWt+FEhQblez37wljRpRF2tkXLo3yxddPaMOorNOTfbbJgwAEIAABCDQDAQTAZrgL+AABCEAAAhURSJqqpeg9iXmK6suaQlEfq97ZntUU9SAAAQiUEPjeZ44rbN4xwMy5d0lJvnuhlxYTRw402oTDt2GGjYzzvfRw7SSdHz1qsPnm/3neaC1AN82YdIi583MnG0XoNTK5EYH1Wn+wmvGEph+HyqvpkzYQgAAEIACBRhJgDcBG0qYvCEAAAhAIEpC4p/WutMOvjrqOp5BoZ9fLirfzXYeiPl59e4evGXkQgAAEUgmcOrHLzJ4+Nlr/TiKeLyl/wqGDzGX3+XfLtZFxSS89fDbjeQP79SkT/1Rn4cp3oki8eP1GXSsisJ7rD1Y6jrT1Fa0IW6lN6kMAAhCAAASaiQARgM10N/AFAhCAQIcT8EW42AdgN0olJNqpXA9zEgpthImufdPdiOro8A8dw4dAjQR6F16n79tfbmTD9l3RSwxF9yWtVXrr7Gll02Gtpe7xI4rRzHqpUc1u5Md9cJhZVljjNCnJpmzHl0ZIqt/O+UnrK9rfoHYeO2ODAAQgAIHOIIAA2Bn3mVFCAAIQaHoCSREudi0+d1pvSLQbMqBvNOXOfWC2D3GukCgoNurDrdv0sHAQAhBoGgI+8U/OvfTmdnPOLY+ZQf17m+279hX9ddcqTRP2Fq/aWBTnQi89isadk65B/cxVZx5p/vTvlzm55aeyjQB4gEuzTk8uv2vkQAACEIAABConwBTgypnRAgIQgAAE6kCgkmm9VrTzuSGh7/b5y8uiZayQGG9joz7UjgQBCEAgbwKu+Cfbdq1SnYeEPVseeulx3BFDZa6YtJ7go185oyDsDSnmJZ2EbCe1a+f8Zpue3M6sGRsEIAABCDSOAAJg41jTEwQgAAEIpBCwD7pJVdzyJNFOIt61Z08pE/+sTYmAvvUBbdTH3Eum26ocIQABCNSNgP0uOnzogNQ+Xt/0bnEacdJLCol9P736NKPvrz8796jo+OAVH4k290h7WaKOZbMVov+yrA2bCpJCCEAAAhCAAAQMU4D5EEAAAhCAQFMQCEWhxMutaLfiza2FNa42RmM4eVyXeX1T+qYdEhKTHnj1MJy0E2dTQMIJCECgbQjoZcRPFq9OHc8NDz0Tleu76ZuzppqvzXu27AWHdg4+5dsPmw3bdxdtqf5tF54YiYA6Xv2jZWUbgWgXYJVJXEtaLzWtrNhZHU/U/1NrNpubfvZsFDlpu3LHZ/M4QgACEIAABCCQTgABMJ0PpRCAAAQg0CACNlLFtxafHvZ8op02DfnOz18oeSCWgJeW4kKiW1eRhRdOH230QE2CAAQgUE8Ccxe+YrTOX5ak70WJf4rym/2D/yhr54p/sqf61/3kN9EmInpZ8sBlH44iCZeuPvDdppcl+k7Vd+ice5eUfIdacU12ZMP9TrZlsllvcVC+XfvjZWbB8rflSklyx1dSwAUEIAABCEAAAokEEAAT0VAAAQhAAAKNJGCn9SY9cMZ92b9/v7n8/ifKxDqJd1r8Pv5ArPZJQqK1rQfanyxZay85QgACEKgLgWoijSV66V8loqG7w68EP/dFir7v4t+3GqwV1+y5C8CWKXIw3tYVB9021Zxb33zin7UnX9zx2XyOEIAABCAAAQj4CSAA+rmQCwEIQAACPUDATuvVQ52m6ipaz31gtS4pMuTy+5YkPghL/OseP6Kk3D6cWhu+o6bBEf3nI0MeBCCQFwF9F82ePqaq75oX122pyI20JQ9CGy8ldSThzffyxYqD7o7tSTZC+Wm+uW3TxufW4xwCEIAABCAAAcMagHwIIAABCECg+QjEI1VcD21kSCgK5pqzJ0cCYpqQ6NrVueqSIAABCNSDwOQPDDJ/+UcnmBPHjvBuRpSlz6NHle72G2qTtuRBLd93SS9K8orKy+pb2vhCbCiHAAQgAAEIdBoBdgHutDvOeCEAAQi0OIGskSE2enDmZP/6gT4MPEz6qJAHAQhUQ+COz55ojh41pNh0xVvbzd88vCJad09rnp4welixLMuJIgf1L2s71fVFUNu+6vV9l1W8s374jll8C43PZ5c8CEAAAhCAQCcTQADs5LvP2CEAAQi0IIEsD5eVPBgqolBTjh9fsT5a1F5tSRCAAARqJXDX46+YF9dtLTFjp8kq8/KPTSwpS7vQkgazp4+Nduv9xqePTasalel7TOv0pSW78ZKvjtonfRfKl7Tkinfu96u+Z3WdJaX5pvZZxpelH+pAAAIQgAAEOokAawB20t1mrBCAAATagID7cOkbjhbXDz342nZaSzC+kP2pE7vM8MIOl5sKZSQIQAAC1RJ4au1mb1OJgBf84FdmyapN3nJlSuC68bxjCi8ntpq5i1ZF6wUuXrU0qn/GlJFm5uSRhZcW5bvjKjrw5gumGQloipZ+eu2maCkEXWujJTdl2Xgp/v0ov26dPc186cEnS3YHtnZVbqMOfd+vVrjTeq9pKck3je8b508108YMT2tOGQQgAAEIQAACHgIHFd7EZXsV52lMFgSqJbB27VozZsyYqPmaNWvM6NGjqzVFOwhAoMMI6Gdrzr1LvA+fikz5hz/9aCYiaXYyGaASBCAAgQQCEqqSBMCEJsVsfY/94OKTzTvbdpsv/+NTXjszJh1i+vbuVfI9aMU1GfIJd3ox4hPe9F0oUVIbjGiNQdlxxULfpkwhcS/t+1X2K9koxNd/ERYnEIAABCCQiQDP35kwtX0lBMC2v8XNOUC+gJrzvuAVBFqFQOjhM8s49FB5zi2PZalKHQhAAAIVEdD6f1f/+DcVtXErdw3qZ7SbeVqae8l0M3bEweaNLTuLO6ZXKrzV+l2aJM6Fvl/nX396MVIwbYyUQQACEIBAPgR4/s6HY6tbYQpwq99B/IcABCDQgQQUxaIIkqSHzyxIsqwlmMUOdSAAAQjECWzbtSfarKPaKMCQ+Kf+FAlto/5sZF/aJknxHXolFsYjBWXXrlOYJUovacf20Peryu1UYfVJggAEIAABCECg/gTYBKT+jOkBAhCAAATqREAPkJXs8uu6EVpL0K3LOQQgAIFKCPyPf3rWO3V3wshBlZgJ1rVina2YRXizdbOIhbZupcfQ92uovNL+qA8BCEAAAhCAQJgAAmCYETUgAAEIQKAFCSi6RRGC2t1XR127KbTLpFuXcwhAoDMIjD9kYF0H+urb23O3byP7ZDgkrLnllYiFlTqd9v2qqEWi/yolSn0IQAACEIBA7QQQAGtniAUIQAACEGgiAhL6nlyzycy6c1G0xt/Fdy+Ojpoup/WubLK7TGrXYBIEIAABEVj1zo6WBGHFvEqEN1cM9A06VO5rY/Ps96vEPjfZKctuHucQgAAEIAABCDSGAGsANoYzvUAAAhCAQAMI+Ba0t93aqXLuulZaN+snl3/YnPgX80vEQduGIwQgAIFWIGDFOiu8xdf28wlvVizUd2M85RGll8darXG/uIYABCAAAQhAoHoCCIDVs6MlBCAAAQg0EYGkBe1dF+1UOXf62Stv70D8cyFxDoEOJDCoX2+zffe+ho78e585zhwx/GAzpH9fc/vDy6PNN6wD8V2AJcjt2bffLFz5jq1SPMbFuqzCWyViYbGz90/0fas1BBV5KPFRYqLs+ZK+b93vXF8d8iAAAQhAAAIQqD8BBMD6M6YHCEAAAhBoAIG0Be3d7vXA6j6M2qlzbh3OIQCBziLQaPFPdE8e11X8LvLtah7f5dwX4eyL7LN3LovwllUstDZ1TPND9qpJlQiK1dinDQQgAAEIQAACxiAA8imAAAQgAIG2IJBVyLNT5eyg49c2nyMEIACBehGIR+2pn7hgF7+uRqzL6n+8r6R2SZHWviUWkmzE8+shKNo+EBYtCY4QgAAEIAABBEA+AxCAAAQg0CYEsgh5vofutHWw2gQNw4AABKokMH3ccLNk9aYqWyc3u/acKcmFgZKsYl3ATFXFaZHWviUWQp3UQ1C0fdZTWLR9cIQABCAAAQi0EgF2AW6lu4WvEIAABCCQSMAKeUkVkqbK2XWwVO6msV0D3UvOIQCBDiHw5Y9PMffPmW7mX3+6uebsycFR9+3tX/sureHWnb/bkTytXrOVhSKtQ+Xx8WQRFONtslyHhMUsNqgDAQhAAAIQaDcCCIDtdkcZDwQgAIEOJZAk5J0wepiZ98XTjNbYSlqfyk6t0wP/A5d1m3lXnWZGDe3foSQZNgQ6m8DN/7bc3LNolenft5e549GXgzD27HvPHF/4npFoqI09sqQsEcvWjsQsrQf4+Ir10VHXPZVCfofK436HBMNQedyeva6XsGjtc4QABCAAAQi0IgHWAGzFu4bPEIAABCDgJWCFvPji+d7KnkxNrVMk4Zx7l5jFqzZ6apAFAQh0AgFNZz3/joVmw/ZskXpPr91s7nhkpfnqJ48J4vEtRZDUqNmmsdpIa/GJp0rGZduGBMNQubUTP4aEQ5Xr+54EAQhAAAIQ6CQCRAB20t1mrBCAAAQ6hIAe7GZOPrSqB7y0yJEOwccwIdAWBE4eN6KmcWQV/2wnemnw/8x7xkwcmbx8wMzJI81tF55oskT19fQ0Vp+PSZHWSUssWDZJRyso+sqrERStnZBwGCq3djhCAAIQgAAE2okAEYDtdDcZCwQgAAEI1EwgFDlScwcYgAAEGkLgunMmm9c3vWtueOiZhvSnTp55fYu3r6NGDSlMDz7eTBsz3CiqT1HGbhRd94QuM+e08YWXFkOiKGQJbWkvI6rZcMPrWEJmKPJQSypUG2ntdmkFxet+8psSHtUKita2FRZdxrasFmHR2uAIAQhAAAIQaEUCCICteNfwGQIQgAAE6kbg8KED6mYbwxCAQOMIKMqrpyO9hgzoY/53YQ1SO900Kapv8asbjP4pWfEr9DKiXtNYk3yUmCahTuKfksZkxxVlVPmfWpdu8HVbL2HR1xd5EIAABCAAgVYhgADYKncKPyEAAQhAoO4EFPXyrX95vu790AEEIFBfAjbKS2KWzn2RYNV6IMFK3xVZ0tade82L67YUhbK0qD5rzwptN56Xvp5gteKmmMgPCYiyoWg5CWY2pfko3xT5l4fwZ/uzx7wERWuvHsKitc0RAhCAAAQg0IoEWAOwFe8aPkMAAhCAQFUE9OCbtJumjXpZsPztqmzTCAIQ6BkCXYP6lXRsI+iUaSPBlJdHkp1f/l9nmJPGDs9s7pZ/e6lYNxTVZytKaLPipc1zj/KjGhHOTj8+55bHzMV3LzY6ajqyK2iGfAyVu342w7k4VbsmbDP4jw8QgAAEIACBvAgQAZgXSexAAAIQgEBTE9ADbtI6U4oUSYt6aeqB4RwEOpjA3EumFyP8FGl39Kih0bUb0RaPBBvcr4+57P4nCjv87s5M7oTRw8w3zp8areEnYW5Q/+z/C/3K2zuKUXOVRO2t27Iz2jAk6Xsrs/PvV7QvOeLRkDbi0E7tDfkYKq/UL+pDAAIQgAAEINAYAtn/76Ux/tALBCAAAQhAIHcCWR58f7txe+79YhACEKgvgU3bd5VtqGEjACX8uUmRYJruqog3n/jXt/dBZs++99wmxfOn1m42t89fHq1/p5cFj6+oLFJYUXO2f/kXF+GKHTknEtri4qXyqon8k9m0lxzyx07tZQMN5yZwCgEIQAACEGgjAkwBbqObyVAgAAEIQMBPIMuD79qNO/2NY7n//axJsRwuIQCBniLwZ4UdfuNimo1o8/mU9l0g8e/bs6b6mkV5ViSrZgqsjZrLOiU5PsU3j2msIb9teZKPVlhNBEQBBCAAAQhAAAJNTYAIwKa+PTgHAQhAAAJ5ELAPtkm2VL753WzTAf/mkZVmSGH639Zde5PMkQ8BCDSIwN79/og9K9bFo+VC3wWbd6Zv7qH2VszLOsS4mOdG9Snqbu7CV8ziVRuL5ioR2hTdLFHT+hXf0KNotHAS8tstd320tuMsXducQwACEIAABCDQ/AQQAJv/HuEhBCAAAQjUSMB9sPWZUnnS1D9ffcQ/HxXyINBcBCRcxUWr0HeB1hBMS2qfNkU23jZNzJNv+nfu1FHR9NtKhbbQuqZxX9L8jouUtq310V5zhAAEIAABCECgdQkwBbh17x2eQwACEIBARgL2wddX3T74njFlpInvJuqrTx4EINAaBHxiX9p3gTb6GDviYHP65EO8A7TfFXaKbPf4Ed56NvOOz54YrRkYX4vQlrtHCW2V7FQbWtfUtW3Prd8ah5t0fduFJ7pZnEMAAhCAAAQg0IYEEADb8KYyJAhAAAIQKCWQ5cG3V69eZt5VHy0suk9wfCk9riDQswQkUB1fEOcqSVasi7fRd8Gts6cZn3injT7OufWXZulrm+PNzIxJh5SIZBL1HrzyVDM9RQR8aNnaMjt5ZaStZWinP/v6slN7519/unngsm6jo3b/zSJS+uyRBwEIQAACEIBA6xDgKad17hWeQgACEIBADQTsg6/W3PJNtdN0upt++lxhLUDW9qsBM03bjECvg4xJWGavISMtRqcV1ro78+bHvLv3SrR3/25tG9/6eFt27jVfevDJkjX34gPZ5lnfs2/vXl6R7AunjjdLnPX7XFtWiFN0X95J32FpyTf92a3P1F6XBucQgAAEIACBziCAANgZ95lRQgACEIDA+wR8D75J0+mABoFOJ9CT4t9xRwyNotPsPXj0K2eYy+9bUibeSfxTRN+cGROjNfX0N755x24z++/+0yx+dYNtbiQM7tm33yxc+U4xL+tJXMzzrb/nsxUS4nxtsuT5pje77ULlbl3OIQABCEAAAhDoDAJMAe6M+8woIQABCHQ0AQl8ivx7fMX66KhrN6VNp3PrcQ4BCDSOwDOvb4n+Xm2Pdtpt94Qum1U8ahfdB5e8FgmAmwrin6IFXfFPFSXiVSP+2U5s1F0lLwwq2VzI9pPlmLaWYdL05yx2qQMBCEAAAhCAQPsSIAKwfe8tI4MABCAAgQIBX6SOnSJo172yD/YAgwAEmotAPIJOYn1c2LMeS+B75IU3zfd+8aJ3qrCtV+3RRtVV8sKgb+/CHOo6JLuu6XU/+U0kbNou7HebveYIAQhAAAIQgAAELAEEQEuCIwQgAAEItB2BpEgdCQV6cNbi90r2wb7tADAgCLQ4gfjfZkisn3PfE3UZsRtVF/LBdSDuv1tW63loXdNa7dMeAhCAAAQgAIH2IsAU4Pa6n4wGAhCAAAQcAmmROnZNL1VPm07nmOMUAhBoIIHjPjgsmtLrdllPQc3txz2PR9Vl9cEVDV17eZ9rzcOZkw8tY5V3P9iDAAQgAAEIQKC1CSAAtvb9w3sIQAACEEghEIrUWbp6Q7QuoITCW2dPizYJSDFHEQQg0EACfzFrallvIwf3M12D+pXl15IxY9Ih5oQxw8tMHHvEEDPvqtOiSGG7XIAqZXlhEBcNy4yTAQEIQAACEIAABBpMgCnADQZOdxCAAAQg0DgCoUidGx56puiMfWBfunqjmXPvkmI+JxCAQM8Q2LpzT0nHmtL/pQefzH19v91795un1mwq6UsXHxgywEzzCINJ6+/FdyIuM0gGBCAAAQhAAAIQ6EECCIA9CJ+uIQABCECgvgRspI6m+4aSXRdwzowJoaqUQwACDSAQ30E3bUp/Le5oB2FfsssEaIptPLH+XpwI1xCAAAQgAAEINDsBpgA3+x3CPwhAAAIQqJqAjdRRdF+WpAd+7RpMgkCnEThh9NCKhnzC6GHm7i+cUlGbSivHd9ANTen32Zefcy+Z7ivKlBfqk/X3MmGkEgQgAAEIQAACTUAAAbAJbgIuQAACEIBA/QjYSJ2sIsDfPfZy/ZzBMgSalMCrb283X//UsdE/TWVNS1oz7/7LPmz69an8fyOvOuPIaF092Qil+BT++HW8/fEFsc9NEv7lp45JLwG6J3S5TcrOQ32WNSADAhCAAAQgAAEINCkBpgA36Y3BLQhAAAIQyJdAPJooyfrTv92SVEQ+BNqWwJad+8zX//m5aHyKmrvjohPN0AF9zBHDB0Z52jBH6eRxXcXdZqsRx55/Y4v5yieOMn17p4uHZ0wZGfX3+Ir1Rv1oOn/alH5tDPL02s1RG/1HIuZtF55o7OYdOr/uJ78x7nIAEgVvK2z+c11hXUE33xpRuW/6ry3nCAEIQAACEIAABFqJwEGFBZXfayWH8bU9CKxdu9aMGTMmGsyaNWvM6NGj22NgjAICEGhaAivf2mbOueWxVP+OHjXEvLhua2odCiHQKQQkgF179hSzddeeoginafU27d+/31x416/N4lcPiIM2P3T8dmF33xvnPZtY7aSxw82g/n0KO3S/XawTiXUFEU8pLuRJ/NuwfXexrj1Rm3su7baX0VHfA5rWK1HRinua9h+3afuzAmKJES4gAAEIQAACLUaA5+8Wu2F1chcBsE5gMZtOgC+gdD6UQgAC+RHQey5tHvD6ph3m/314hVmyuny3T/WWJCLk5wmWINDaBBSVd93vHWW0O++QAX3Nbf/+klmw/HcinR2dIgifcqLxbH7WY1J7V9CzQp42CknbtXv+9adHkYP6DrDCnyIJXSHT+mVtuuKgLeMIAQhAAAIQaGUCPH+38t3Lz3emAOfHEksQgAAEINBkBHyRPXEXjz18iBnQr7dZmiAM2vojBvY1G3ewQYjlwbHzCEjs8wl+LglNvf3OHx4fjLZ128TPk8RDd1deRe/pn6YIp6WVb2013/6X50um+CZF91mbafayltkXDyHRMas96kEAAhCAAAQgAIFaCaQvwFKrddrnTmDbtm3ml7/8pfnrv/5rc8EFF5gJEyZEb7H1Jnv8+PGZ+tOUHdn46le/as444wwzatQo069fPzN06FAzdepU88UvftE8/fTTmWxRCQIQgECzEtADeHxan8/XQYVIppD450Ye+WyQBwEIHCCweNVGo789/c1UkxT9l5YkqMm+ovUk/ikCMC3NXbSqRPxTXQmJ+m6oV9KLB0UlasmBi+9eHB11zQ7j9SKOXQhAAAIQgAAEshAgAjALpSaq86lPfcosWLCgJo8kFGrdvXjas2ePee6556J/P/jBD8xXvvIV893vftc7TSbelmsIQAACzUZAU/58C/vH/QytX/a9zxxnZk8fG4w0itvlGgKdSmDdlp3mm4V1/s6/Y5F3bb4kLhINtebgrO8vSqoSTT2WmOb+bSdN31c0YtLftxtNmNhZFQVJLx6s6Bhfk7CKLmgCAQhAAAIQgAAEqiJABGBV2Hqukf7H0qauri7z8Y9/3AwePNhmZTq+/vrrUb1JkyaZG264wfzsZz8zTzzxhHn88cfNN7/5TTNixAijKMG//Mu/NDfeeGMmm1SCAAQg0GwEFCmUR9Kup0rV7HiaR//YgECrERg1pL/5WmGTD9/GHEljOe6IodGGHSeMGWZmTj6wA3C87oxJI83t85eXiH+qo34kArpJYuKcGRPdrLJzrQtqIwl1dP8fq6xyxoy0Fw9WdMxoimoQgAAEIAABCEAgVwJEAOaKs/7GLrroInPllVea6dOnGwl4Soro09TgrKm7u9vcdNNNkXgYXwR7xowZRn2ceuqpZv369eav/uqvzJ/8yZ+YiRPT/yc6a9/UgwAE2p+AHqKzLLhvSVRa37YLHSsR7KJIocLUxXiSiGB3CtXGAbp2I4/i9TvteuiAPmbLzr2dNmzGGyCgHX41FbiS9MzrW8wjL75ltNFIkhC3o7Ab8bI1m71mJQLOvWS66dv7oOIOvxL10tIdj6ws8VN/37cVdhquZeff0IsHldvvlDTfKIMABCAAAQhAAAJ5E0AAzJtone1dccUVNffwq1/9KtXGkUceab72ta+Za665xuzdu9fMmzfPXH/99altKIQABCAgAr5NN9IeqiutXwnlrIKd9S++XqDNt33qhYnEgXg9W96JR8S/+t31Pr0OMnv3/y7qv3495W+5UvHPeqCpvd0TuhKn7SaJf7a9xL+Zk3+39mDad4AiBuN+5jFNN/TiIVRux8IRAhCAAAQgAAEI5E2AKcB5E20Te2eeeWZxJC+//HLxnBMIQAACSQQUteMTx+xDdbxdpfXj7UPXVrCTkJeUrMiniB+tzTX/+tPNA5cdOOo6Hgnk1rt/znTzvz5/shnQh5/SJL7kV09A4p+mxR51WGXLfFTfY3O0TFqzL4t3cXEt6TtAImPS9ORap+la0dHnr75viP7zkSEPAhCAAAQgAIFGECACsBGUW7CPXbt2Fb3u3bt38ZwTCEAAAkkEsqx95T78Vlo/qd+kfAmM67fuKqwDNsFcfOp4I53uiOEDo+qahiexwPVHBbqO5/nsH1pY4+zb//I804F9cMjLjYCmxf7vL37UfO5//drs2L0vN7txQ4P79zHbdrXGVO6kCMEkcc2K9poObP/uddTuvEmplmm6VnSMvwyxLxuS+iQfAhCAAAQgAAEI1JsAAmC9Cbeo/ccee6zo+Yc+9KHiOScQgAAEkgjooTktxR+qK62fZjteFppanEXki9u010mRi7acIwTyJLB15x5z8x8fb/7bD3+Tp9kSW4o0fKkgkCVFxZVU7sELK6JVI65lFfc1vHgkYaVD9omOtXznVNo/9SEAAQhAAAIQgICPAAKgj0qH5+3YscPcdtttEYX+/fub888/v2Iia9euTW3zxhtvpJZTCAEItB6B0ENzvDx+HR9xqDxe314nCXR2KrKm9taS0iIXa7FLWwj4CNzx6Mvmq5+s74u4/3h1g5l31WnmO4Wo1vi6eD6fGpEX35jHin95iGt2mq6+E+IpKZIwXi/LdSWiYxZ71IEABCAAAQhAAAK1EEAArIVem7a94YYbzGuvvRaN7qqrrjJHHHFExSMdM2ZMxW1oAAEItDaBSh+qK62flU6aQGfX96olGicUuZjVT+pBIAsBrYl327+/VPcdqBVp+OCVp5rZf/efiZtwZPE3VEcC27XnTDFb3t1t4rvw2rbaoOOuL0yPpvDr700vA+J/syFxTS8C9F1g2+v7RtNzlXpqmm6aT3bsHCEAAQhAAAIQgEC9CCAA1otsi9r94Q9/aO64447Ie039/da3vtWiI8FtCECg0QQqfaiutH7W8YQEOpXHxYSstlWv2sjESvpo97rHFqacnn30oWbIgL7mbx5ZabbubI315+p1X0YM7Gs27tiTaH7B8rfNvC+eFpW7UWtDBvQusMtnbcA9+wqCWWEacGgTDgl4N553TCSs6f7dPn955rUw514y3Zx19AeicUgMU/vPz11cdv81FVnTfBWta/9WKxHPQksAyIE8IgmjgWT8TxafMpqiGgQgAAEIQAACEKiKAAJgVdjSG9k3zOm10kvvuecec8kll6RXyrl0wYIF5rLLLousdnV1mYceesgcfPDBVfWyZs2a1HaaAtzdXds0vNQOKIQABHqEQKUP1ZXWzzKokEAXKg/1oUiiE0YPM0+t3Ryq2pHl5x57mPnFc2+mjv25wuYWb2ze2fRrzqUOIqdCRbtlWXtv3ZadZT1OOWyIWbp6U1l+NRlz7l1ijho1JLWpPve3XXhiJJ5ZYU4ind1g4/VN75obHnom0Ubf3gci8HxiWLyRG63rq+9OCXbbSiiMrxGoctmzoqJbPxRJ6Nat9rxSn6rth3YQgAAEIAABCEAgjQACYBqdDip74oknzKc//Wmj3X8HDx5sfv7zn5taNv8YPXp0B9FjqBCAQJxApQ/VldaP9+de12tqse1DL3m+cf5UM+vORTaLo0PgmEJ0X0gAVPUsopdjtulPTx43oiDGbQz66UbQKepOwluWNHfhK2Xr80n8k4gugSyU+vQ6yOzd/15qtZfWbU0t1+de/cWT/fuVEJiWJL4niWG+dorW1d9zJYJevZcA8PkZymtGn0I+Uw4BCEAAAhCAQPsRQACswz194YUXarZ6+OGH12wjq4HnnnvOnHvuuWbr1q1Gm37MmzfPfPjDH87anHoQgAAEmopAvaYW20FKwBjcrzdRgBaIcxxemMq6cMXbTk5nnErUu/WCE8wp355fENmSx+xGrUk0e3xF+SYUvtbdE7oSp+ZmEf9kMyT++fqN52m6b9omOlnEd4mE7jTmeB/utQTDSsWzei8BYP3T90DSGoO2jj02yifbH0cIQAACEIAABCDgI4AA6KNSY97RRx9do4XGNX/55ZfN7/3e75l33nnH9OnTxzz44IPm7LPPbpwD9AQBCECgDgTqMbVYbvqmItbB/aY2qd1ZPz3tCPNX/7q8JPJM69hpCul/vrKhqf3P2zkr6in6L038+/PCTr5/8rGJUQScnTKrCMBQkv0LThmdKACG2udZ7k7L9dnNIr6HxDBrV+POIpLKnurZFJriHyq3dtKOvu8B+znwRUiG+gyVp/lCGQQgAAEIQAACEMhKAAEwK6k2rLd27VpzzjnnGK3H16tXL3PfffeZ888/vw1HypAgAIFOJWCnJuYx/kqmLubRX7PYOHVil/mLWccVd1O1Yst//ch488iLb5kX120xR48aasZ2DTTn3PJYs7jdED/cTS3EIS3t3r/fKyAnrQGo9fZuvmCaOXRIf3P5fenThI86bLB56c306bdpvlVSFhfcfJFw7rqAErfsZ0b9ZBG7rJiWpX7cXigKUTYVeal2qlvpus1J3wNJawyqv5BPLh/VJ0EAAhCAAAQgAIF6EEAArAfVFrD51ltvReLfqlWrIm//9m//1lx00UUt4DkuQgACEOgZAmlTEXvGo8b0+mJhXbgkIVU7utpdXbNOZ22M1/XvRSKVHbt6kwialo4qbNjhW8tOayHGRUArgA0d0CdaI3DxquS1BVX32nOmNGxNSldwS4uES/rMpIlhVvR0BbG0+hq7W1f8k6IQZ04eafbs218iUlvOvqi9pHuZ9j2QFCGZ5JPtP6kv8iEAAQhAAAIQgECeBBAA86TZIrY2bdpkPvGJT5iXXnop8vjWW281l19+eYt4j5sQgAAEeoZA1qmLPeNd/XrduGNPFOnnil2+3lxhyFeuaLn1W3em7hLra9eMeTMmHRLthuv6dsaUkWVCni0fdnAfM64QIZm09p1EQPHRLrniaEWt0Hp5WhtQu/JKKJSYlGRfZRK/Fq58x7pU1VF2rG9ZIuF80YEhMSwuxoXq+wZStgTA0AHm2z9/ocCndH3KtKg9n13lhb4H4hGS1k6ZT859tnU4QgACEIAABCAAgXoSQACsJ9062F65cqVZuHBhieVt2w5M+9Hx3nvvLSnT5h6jRo0q5mmX3/POO888+eSTUd7nPve5KBLw2WefLdaJnwwaNMhMmDAhns01BCAAgY4iEBK42hnGk2s2lkS7+cYaitSSgNjMUYIS9bRRRnwNQ+V/5RNHmxff2BIJmB8oiEknj+uKRDeXg5bS+OnVp5nz71hUtsPx5nf3mi//41Nu9bJziX8zJo2MNpawU1Rf37SjrJ6bcc1Zk4q78koIjEcYKqLuG5+eak4YM8w8tXaz2brz2ehobUjQU/Tgus07TXyXYV9U4q2zpxl3/cIkwVH5T67ZZLRpiFtH/cnPSsWwSuvb8Ums1L80IVX+qdwKm7Zt0jH0PRAqtz4l2ScfAhCAAAQgAAEI1IvAQYW3s+EVqOvVO3YrJiCB79JLL83c7tFHHzVnnHFGsb6m/FYq5p1++ulmwYIFRRt5nGj9wTFjxkSm1qxZY0aPHp2HWWxAAAIQqBsB/VzOuXdJiaBRt86azPBxHxxm/vmaGUGv0qaESsSR0NLIdQK/+4dTzY9+/Zp5+rfJ6/Md/8Gh5oqPHWmGFTYxkXij+7zstQNTbiX0SbAJjcsFo/afLoiAz/x2s5sdPJ931Wllgtn0woYrS1Km/86//vQy4coKdBpLku8SBi+fObE4Zom3irSLt3WvtRZhXGBMG5T6kOgYTxIB03YSjtfP41qC6sV3L0409cBl3Wbm5EMTy92CtO+Bnhib6xvnEIAABCAAgSQCPH8nkemsfCIAO+t+M1oIQAACEKiSQNJUxCrNtVQziVkSg0JRUqFIrbQowXoAOWX8Iea/HHeEueqHS8umv049Yqj5H//lQ+buha+Yq3/8m2L3bpSaMiX4+IQvRY4pX2KW6mhtOE3/1M6+lYp/ZxREse/8y/MmvtZfmvgXOVzoN57cCLMk3yXM+cbstpVde50mesX7t9c+8U9llUbcWXu1HENReaFyt++k7wH7uXHrcg4BCEAAAhCAAASaiQARgM10NzrIF95AdNDNZqgQaDMCigbTrqxxsUbD7NProGgaaZsNORpOJVFSaeP3RdONKETfaa3BSpLWv1v86obEJvFoLAmYS1cfqK/IPomRn5+7uDAtuXRdOBnUhhEPXPbhyLbapUUtzvtiIXLv4dKprolOeQrU1/ZdewtRh5s8pelZirK7v+CnhNd4kmgnsU1Rq1lSnJfbJsTAravzpOg/Wy+vz5K1FzqmCZhp4w7ZFReJvjbaMlSfcghAAAIQgEBPEeD5u6fIor+uFgAAP9lJREFUN1e/RAA21/3AGwhAAAIQaGICNqLKJ/5pmmylkV+NHmpBnzSFZe6qSopsyyMlRQk+WRDAbvpZ6Rp1Sf11F6bG/sOVp0ZRiSvf2mrmLlpVIgb6orFsNJu1ufLNrV7xT+USBR9c8lq01l9oHb6sPtt+48dde/ZVJf7JjqLsbBSia9cnsrrlvvO0yLzQxheuPbG/9uzCrsTfX+Rml5xXEnFX0jDjhf5ObUSm+pLY61sj0fc5ydhFVC3+maqkLXUhAAEIQAACEIBAowkgADaaOP1BAAIQgEDLEpCoIKHEl5pd/JPP1Yp/aqtNKvJMcfFk2tjhhU00ZkSinkS3Ox5Z6Y2y1OYUd31heuSKtXHu1MPL1q8L+br0/XX+kurd8NAzUZHExrSUNNU1rY1b5hOT3fLQeVy4syJ10uc0zV7SDrYhwS6+g7F8kLjm80H5um/1Sj7x0wp9mq5N1F69yGMXAhCAAAQgAIFmJ9Cr2R3EPwhAAAIQgEBPEZCQIcFAmwjoGIoG6yk/G9FvSATKyweJQx+b8oFI5JNw4yZN+330K2d4p7yqnTZyyFtckkAn0dGXNNW13imL7OpG6KWJ1CFfk+6xXbvR1173SDs8u+ztOnnx+2eFOJ+dPPKSxE8JkYqUVKrX5yQP/7EBAQhAAAIQgAAE6kmACMB60sU2BCAAAQi0LAFfJJEEqHZNxxw+xBwyuL93WqyEm7yFtRDHpKnCoXZZy08amx7Z59rZsH23ia85KCafOWl0yWYabhudH1fYaOSZ15N3II7X911nmXjtCneuGOizl5SXdo+toBffDCVN0Kv3/fONI038jEdK+tqTBwEIQAACEIAABNqZAAJgO99dxgYBCEAAAlURSIok0qYTigaTINSKKc3359/YamZM6lcmdEn4mj19TBQBqUgwiUGNTBIe6yE+yuaMSYeU7Q6cNLZrzpoUbfYggW3IgL7m9vnLU8W/SBybPc1c/sDSkvUJk+xXmx8X7lwx0GfzjotONA8tXVsyPTdNyLM2qhX06nX/rF/uMSR+qrwenyXXB84hAAEIQAACEIBAsxJAAGzWO4NfEIAABCDgJSBxLr7Af96iVFokURQNVlgXrta127yDyylTO8tqR2J3DTaJPN+cNdV8+cEnE31fuPKdEg8k+kj0tLvtWqFI+fVKjbi/8n3Lzr0VDUHCmsQjiaDaWddlGzdkWV8n1s5OxYoIvOqsyWbzu7uNXWMw3raSa9nT5hZustN1ff7Jr98//ojoX7Vr4TVS0HPHleU8JH6GyrP0QR0IQAACEIAABCDQqgQQAFv1zuE3BCAAgQ4k4JuWWw9RKhRJdM3Zk6NosKWrN+Qi5OR5K10ePpFHvl989+JMXYq3myQq+XaddevUct6o+2sjPOOCZ5LvYmojx8TUJ67ZttoQQ/UvvWexWbD8bZsdHTUdWLsL33jeMSX5aReKt/RNA5YI+8//fWZZ06zTdZtZyCsbVMaMiSMHGm3a4hPn3XuY0RzVIAABCEAAAhCAQFsRQABsq9vJYCAAAQi0LwEr2sTFl3qIUqFIITca7BfPrksVhBpxR9xdWBUBpgjGp9duikTKGZNGlkzbDY0t5K94SwSzglioftbyRt7ftAjPuL+aAn1bYSqvkgTKr/zjU/EqJdfaLfmpNZvLxD9bSfy++sn3jDYQybKDsMQ/iX2uGKup3D+9+jRrsuyo+j25422jojjdgVvxOEn8i0dKum05hwAEIAABCEAAAp1AAAGwE+4yY4QABCDQBgTSRJu8RanQNEorftloq2sLO4wuKAg7PZEU2aRdWJUkgsSnp6pc4oedtps2tqz+27XU8hB6rA1FU+o++lLe9zcU4XnUYYPNS29ui1zRFF5N5b21IAJ+qXAMiXaHDx1gvhwQCddt2Wm+cf5UM+vORb7hluVp3b49+94zL67bYo4eNbR4v8sqxjJ6IsrPCnHuvYx/BmNullzaz4PukcRqfV5DU/zVJr5BiTUqAVdiKAkCEIAABCAAAQh0OgEEwE7/BDB+CEAAAi1CICTaWFEqj+FYYS8uKlghw/Yh4eHVt7ebNzbvtFkNPWoTCxvZlCSCSIhxp+0mja0SxyXM1Cr0qD+fjSQ/8ry/oShIK/5ZX8Twivuf8E4ttXV01OejoFaFRcL3hS3Vd4Uy15Z7Ln8l5lmh1y1rpvOsn8Ekn32fB/s3ZwVsX9u0lwMScOsRserzgzwIQAACEIAABCDQzAQQAJv57uAbBCAAAQgUCYREm1B50VDGk9A0Sp9YkdF0LtWO++Awc+XpR5r1W3eZoQP6RNN+k8Qk5a98c2skTtnIKk0blnASXRei1r798xcyiVESZBSVFY801KDUjys2pg00SSxKapPn/a0mCtI3tdT1VVN6JcZq6nVaUj0bQar6l0tYdDYKibcddnCfYv14WbNdpwlx0WcwZep40uchy2dKn+G0lKd4nNYPZRCAAAQgAAEIQKCZCfRqZufwDQIQgAAEIGAJWNHGXrtHiVJWVHHz8ziX3ZmTS+0niRV59JfVxjO/3Rxt5nHOLY9FYpyinNKSpqWqrjYA0VHTT7cVdsLVGoGTDhsSiVfi6CatNecmG42VRehx2/nO02zE6+d9f20UZHy8EueqTTdfMC2aZh0SKjX11yaJzA9e8REjMTcpbX53bxTBllTeTPlZhLgkf9M+D1Y8TGobYh4qT7JLPgQgAAEIQAACEGgnAkQAttPdZCwQgAAE2piAFW1C03IbgSBNrGhE//E+JJBs37U3nl1yHV+7Ttezvr8omrZq1wj0bRwhYTGKEnx/GqqMhqLcVF+CrTjZtrrWPbQpJBbZejru2bc/mi6cNg3UrZ/l3BfhqXYSR5OS1pPzReu5AqUVqnVP4kn1po0ZXpItJledeaT5079fVpLvXohVvQRut5/4uYTutHsYrx8S2tLKQ5+HNAYh5j3BLs6GawhAAAIQgAAEINDTBBAAe/oO0D8EIAABCGQm4BNteuLhPiRWZB5QjhU1RTVJoErrJj7FUjytePf4ivVV7SQ8pH/fsinCEr+s0Ch/0sSguL8LV76TeWpxvG3oWuO1nyEJXvIzSbyT/yEBuhqhetIHhqS6WQmrVEMVFPqmuMfvYdxcLUJcaIxp5dUwj/vONQQgAAEIQAACEGh3AgcV/mf3vXYfJONrPgJr1641Y8aMiRxbs2aNGT16dPM5iUcQgAAEEggoKi4tUiyhWd2z//a/nmQeXLKmRMDStNZ49J/PkfnXnx4JYVmEH/2vg28NQNk9Y8rIKNIvSUSzO7Km2fD5pzz5aMVJibAShXTtRhYmtc2an2X8vqhIa1/jslFz2rm3T2GxlSOGDyyKjLaee0xjIdHNMnPb1PO8Fn+y8PP5Xkufrr20e+PW4xwCEIAABCDQSQR4/u6ku508VgTAZDaU1JEAX0B1hItpCECg7gTSxIq6d57SgRXxXBFE1bOIlQ9c1h2tB5gk7MWFqCSh59pzpkTrCya5aX1Uuc9GUjvl+wTOUFRamr20MpehjRBMq68y33iy+ldL25Bf+rxaUTKLaKqxp31m3HuY1Hej+SX5QT4EIAABCEAAAsbw/M2nQASYAsznAAIQgAAEIFAhgaQphxWaiaqfNHa4WfZa+s6xWexKaLJCVdZpra5dCUMSiXyRe6qnfIk6to+k6diaNpyW3LXc4jYUMScBMinNXbSqbA0++ZV15+Eku758l6GvPJ4nkS0+PVh1svoXZ6H7YVnH+6rkuhphMTTF3b2HSb5Uyk92amVQqdCZ5Dv5EIAABCAAAQhAoB0JsAtwO95VxgQBCEAAAnUnYMUKRUP9z8+dWBAvqnundsXHJkbrzrkOh3ajHdy/t1u9uJFHSeb7F1aslECYlKx4mEX4iduQ0OPukizhKi35yq0N+ZHkZ/f4EWXin+3HipP2uieOWcTTLH5ZFjrWmkKiZJJ93z1y64bK3brVnFfDQEKnxGNFLtqdrnWtfBIEIAABCEAAAhCAgDEIgHwKIAABCEAAAjUQkFjxX447wvzyz84yEqkqTdoAQmu8SUjUNFwdb75gWqqZow4bauZ98bSo/r9/6WPmxvOOiXbmVYSeRJ94smLlvKtOM3FxUYKbNrdQCgk7oXLZsBtB6DyerNAYz7fXSWKl2s2ZMdFW8x5D4qW3UY6Zof5D5Tm6UjRVrShZyz0sdt7Ak2qFzga6SFcQgAAEIAABCECgxwlUF67Q427jAAQgAAEIQKBxBLJMLZTI9g9/+tFomqzEHk1n7dv7ILN7735z2X1PBJ2VkGijvtSfRC9FtvnS0tc2mtsfXh4Jd/Fpp1bQkz/xNG3McPPTq2cUfZSgZ/tUXSv8+PoNiXe2LyviJfll6yUdrVgZX0NO12kpiziZ1r7WslD/ofJa+/e1D4mOKnfvv7WRdA+1wYvWeLS7Q+e9AYvtv9JjFqHTN85K+6E+BCAAAQhAAAIQaGUCCICtfPfwHQIQgAAE6k6g0jXUJDS4YkMla+LZwVgB5vL7lpjFqzba7JKjRDpfufJDa+LFfbSGbb/VinfWTpKIZ8uzHOM+5iFOZum32jrN6F9IdEwrj9/DIf37RqLzrDsXFRGlic3FSg04qVbobIBrdAEBCEAAAhCAAASahgBTgJvmVuAIBCAAAQiECCgyTpFgEtWSpruGbFRSnsfUwjSRRb6MGjrA65IEmGvOnuwts5lp4mAoYs7aiB+t8ONOSdYUZeVXmiTiuesDVtrerW/FSYlObrIilJuXdF7Pz08e/iX5XW2+FSV97bNGdOoezpg0MhL/4pGhVmz22W9kXuhvLFTeSF/pCwIQgAAEIAABCPQUASIAe4o8/UIAAhCAQEUEKo3Eq8h4QuU8phZaESYuntguv/PzF6KpvD6BrRbhIml6p+03dIxH4IXqN6LcipMSNzU+8ZGfWVIjPj+1+JdlDJXWsaJkrRGdefwdVOp7JfXT/sayCp2V9EddCEAAAhCAAAQg0IoEiABsxbuGzxCAAAQ6jEAekXjVIMsytTBk14owWj/Nl9KiqKyw4Wt39KghvuxiXi3iYdFIk55UGlnY6M9Ppf7VE7MVJWuJ6Mzj76CeY7R/Y7VEh9bTP2xDAAIQgAAEIACBZiBABGAz3AV8gAAEIACBVAI9FYEUEtGSyiU4yWcbpSYh789//1iz4JbHvOOUCKiotng0mxU24hFcMvLiuq1eW8ok6qkUTU99fkq96Nkrfbbin6+sHiV9zm37ULmtV8+jFTqriQ6tp1/YhgAEIAABCEAAAs1CAAGwWe4EfkAAAhCAQCKBLBFI1YobiZ0WCmwEnm/6bpLIljTVdPb0sWldRWKhbwxFYePNrebL//iUeWrt5lQ78uu2C09MrdNphT31+WkXztX8HfTU2GsROnvKZ/qFAAQgAAEIQAACjSCAANgIyvQBAQhAAAI1EQhFGIXKq+08KQIvSWRLm2q6fdfeVDeCYzjooFTx73ufOc6cPK6r6iivVOdavDDENlTe4sOv2f1K/w5q7hADEIAABCAAAQhAAAK5E0AAzB0pBiEAAQhAIG8CPRmBVIzAy7DxRNpUU+3Y2z2hyyx+dUMZnqRoQrdiKIrtiOHZN8Rw7XbCeU9+ftqFbyV/B+0yZsYBAQhAAAIQgAAE2okAm4C0091kLBCAAATalICNQJJQ5qakSDy3Tl7nmlo4c/KhqRF2IZHuwumjTdegfiUuSVj51AmHR2sAKoIwKYWi1ELlSXY7Ib8ZPj/twjnL30G7jJVxQAACEIAABCAAgXYiQARgO91NxgIBCECgjQm0QgRSSIT7yZK1ZsP23SV3SWsGXv8PT0d5VtDUWOOJKLY4kcquW+HzU9mIqA0BCEAAAhCAAAQgAIHsBIgAzM6KmhCAAAQg0AQEmjkCyYp0Pkzd40d4p/+6dbXZiHb89SWi2HxUKs9r5s9P5aOhBQQgAAEIQAACEIAABLIRIAIwGydqQQACEIAABFIJaPqu1gCcPX2M2b57X4nYp8g+7QK8eNXSVBsqlAi4srDeoISqeCKKLU6EawhAAAIQgAAEIAABCEAgCwEEwCyUqAMBCEAAAhBIIaBpvIrck3hnkyL+5syYGAl5EvMk6mVNWkvQJwDa9ipLK7f1OEIAAhCAAAQgAAEIQAACEBABpgDzOYAABCAAAQjUQECRf3HxT+a06++DS14rCnVp04Pj3YfWEozX5xoCEIAABCAAAQhAAAIQgEAaAQTANDqUQQACEIAABAIENO3Xjfxzq9vpvMqza/gpMjAtqZzovjRClEEAAhCAAAQgAAEIQAAClRJAAKyUGPUhAAEIQAACDgFN101LbrnW8HvwylNN94Qub5OuQf3MXV+Y7i0jEwIQgAAEIAABCEAAAhCAQLUEEACrJUc7CEAAAhCAQIFAaLpuvFyRgHd9/hSjjUHcJFHw0a+cYSQSkiAAAQhAAAIQgAAEIAABCORJgE1A8qSJLQhAAAIQ6DgCdm0/3zRgiXy+6bx57OZrdx1WhKFERvkhcZEEAQhAAAIQgAAEIAABCEAgTgABME6EawhAAAIQgEAFBOzafvGNQCT+3XbhiamWqt3N17frsO2PCMJU5BRCAAIQgAAEIAABCECgIwkgAHbkbWfQEIAABCCQJ4E8Ivqy+pO067AiECVC3nNpd1ZT1IMABCAAAQhAAAIQgAAEOoQAAmCH3GiGCQEIQAAC9SdQbURfJZ5l2XXYN+24kj6oCwEIQAACEIAABCAAAQi0FwE2AWmv+8loIAABCECgzQm4uwr7hhoq97UhDwIQgAAEIAABCEAAAhBobwJEALb3/WV0EIAABCDQZgTiuwrHhxcqj9dv92s2S2n3O8z4IAABCEAAAhCAAASyEEAAzEKJOhCAAAQgAIEmIVDNrsNN4nrD3WCzlIYjp0MIQAACEIAABCAAgSYlwBTgJr0xuAUBCEAAAhDwEbC7DmvXXzfZXYDdvE4+D22W0slsGDsEIAABCEAAAhCAQOcRIAKw8+45I4YABCAAgRYn0Mhdh1sVVSdulsJ051b9tOI3BCAAAQhAAAIQqD8BBMD6M6YHCEAAAhCAQJBANeJNI3YdDjrepBVCm6GovJ12S2a6c5N+EHELAhCAAAQgAAEINAkBBMAmuRG4AQEIQAACnUsA8Sb/ex/aDCVUnr9H9bMYmu58z6Xd9escyxCAAAQgAAEIQAACLUGANQBb4jbhJAQgAAEItCuBkHjTruOu97jsZim+frReYjtF/2WZ7uzjQB4EIAABCEAAAhCAQOcQQADsnHvNSCHw/7d3L3A2l/kDx78TIrfcc5lpxl1KF1EUopYkwu5atBKhC71esrFtrS12177WSoiNSC7ZzSpEWUpIJHddtIRyz31Zcr/M/3yf3d/5n5k5Z+bcZuZ3fs/neb1Oc87v93ue3+95P09m5jvPBQEEEHChAMGb3GkUmzZLCWe6c+4oUyoCCCCAAAIIIIBAoggwBThRWornRAABBBDwpEA4wRsvjVbLy0a0ZbOUnKYz53Q+L9uEeyGAAAIIIIAAAgjkjwAjAPPHnbsigAACCCBgBHIKzuR0HsacBTSA2rSmt6b9BtbapunOgfXmPQIIIIAAAggggED4AgQAw7fiSgQQQAABBOIuQPAm7qTWFWjTdGfrGpcKI4AAAggggAACcRJgCnCcICkGAQQQQACBaASc4M0zMzfJsm+P+IvQjSpGd7nN/5k3CGQnYMt05+wMOIcAAggggAACCCAQWoAAYGgbziCAAAIIIJAnAgRv8oTZipvodGfWjLSiqakkAggggAACCCAQkQABwIi4uBgBBBBAAIHcEyB4k3u2lIwAAggggAACCCCAgM0CrAFoc+tTdwQQQAABBBBAAAEEEEAAAQQQQAABzwsQAPR8E1NBBBBAAAEEEEAAAQQQQAABBBBAAAGbBQgA2tz61B0BBBBAAAEEEEAAAQQQQAABBBBAwPMCBAA938RUEAEEEEAAAQQQQAABBBBAAAEEEEDAZgECgDa3PnVHAAEEEEAAAQQQQAABBBBAAAEEEPC8AAFAzzcxFUQAAQQQQAABBBBAAAEEEEAAAQQQsFmAAKDNrU/dEUAAAQQQQAABBBBAAAEEEEAAAQQ8L0AA0PNNTAURQAABBBBAAAEEEEAAAQQQQAABBGwWIABoc+tTdwQQQAABBBBAAAEEEEAAAQQQQAABzwsQAPR8E1NBBBBAAAEEEEAAAQQQQAABBBBAAAGbBQraXPlErPuPP/4oGzdulLVr15rXunXrZNeuXaYqqamp/vfZ1e3w4cOycOFC0bxa1oEDB+To0aNy4cIFKVOmjNx8883SoUMH6d69uxQrViy7ojiHAAIIIIAAAggggAACCCCAAAIIIOByAQKALm+gzI/Xrl07+eSTTzIfjujz/PnzpU+fPkHzHDx4UPT10UcfyfDhw2X27Nly++23B72WgwgggAACCCCAAAIIIIAAAggggAAC7hcgAOj+NsrwhOnp6f7POlqvQYMGsmrVKtGRgeGmpKQkqVmzpjRv3lxuu+02qVKlilSqVEnOnTsnu3fvlhkzZsiHH35o3rds2VI2b94slStXDrd4rkMAAQQQQAABBBBAAAEEEEAAAQQQcJFAki+g9P8RJRc9GI8SXGDixIlSokQJadiwodSoUcNclJaWZoJ14U4BvnTpkhQsmH3sd/To0TJgwABTvn595ZVXgj9QlEf37dsnKSkpJvfevXslOTk5ypLIhgACCCCAAAIIIIAAAggggAACoQT4/TuUjF3H2QQkwdr78ccfl65du/qDf9E8fk7BPy3z6aefluLFi5viV6xYEc1tyIMAAggggAACCCCAAAIIIIAAAggg4AIBAoAuaAQ3PoIGCYsUKWIeTacGkxBAAAEEEEAAAQQQQAABBBBAAAEEElOAAGBitluuP/WSJUvMzsB6ozp16uT6/bgBAggggAACCCCAAAIIIIAAAggggEDuCGS/EFzu3JNSXSpw6tQp0fX4Zs2alWHNv/79+7v0iXksBBBAAAEEEEAAAQQQQAABBBBAAIGcBAgA5iTk8fNDhgyRoUOHBq1lgQIFZMyYMdKkSZOg57M7qIuMZpcOHDiQ3WnOIYAAAggggAACCCCAAAIIIIAAAgjESYAAYJwgvVbMfffdJ+PGjYt6+q+zw6/XXKgPAggggAACCCCAAAIIIIAAAgggkGgCrAGYaC0W5+ft27evfP311+a1evVqmTJlirRo0UJ0DcDOnTvLmjVr4nxHikMAAQQQQAABBBBAAAEEEEAAAQQQyEsBRgDmgnZSUlLMpWogrkePHjGXk1MBFSpUEH056c477zT3HTZsmAwePFiaN28u8+bNk1atWjmXhPVV1xLMLukU4DvuuCO7SziHAAIIIIAAAggggAACCCCAAAIIIBAHAQKAcUD0YhG//e1vZf78+bJ27Vrp06ePfPfdd1KwYPjdJTk52Yss1AkBBBBAAAEEEEAAAQQQQAABBBBIOIHwIzoJV7X8e+AtW7bEfPNKlSrFXEasBbRv394EAPfs2WO+3nXXXbEWSX4EEEAAAQQQQAABBBBAAAEEEEAAgTwWIACYC+B16tTJhVLzvsjy5cv7b7p7924hAOjn4A0CCCCAAAIIIIAAAggggAACCCCQMAIEABOmqfL+Qffv3++/afHixf3v4/Hm0qVL/mJ0PUASAggggAACCCCAAAIIIIAAAgjEXyDwd+7A38XjfydKdLMAAUA3t04+PtuVK1dk9uzZ/ieoV6+e/3083hw5csRfDJuB+Cl4gwACCCCAAAIIIIAAAggggECuCejv4mlpablWPgW7V+Aq9z4aT5ZbApMmTZLLly+HLF6Df88++6xs3rzZXNO0aVP+gQipxQkEEEAAAQQQQAABBBBAAAEEEEDA3QJJ6b7k7kfk6QIFduzYIStXrgw8JAMHDpRjx45J2bJl5eWXX85wrnXr1lKxYsUMx5KSkqRKlSry85//XBo1aiSpqalStGhROX78uGzatEmmTp0qX331lclTsmRJc794jwA8d+6cfP311+YeutZgJDsMZ6hMHD/ce++9prSlS5fGsdTQRcX7frGUF03ecPPE67pQ5ehwdmcUqe5a7YYNdEK3evAzoeoW/OrYj8bzfrGWFWn+SK4P59qcrsnufKL3vezqFnsvy1pCvO8Xa3mR5o/k+nCuzemaUOcTvd9pzwhVt6y9Jj5H4n2/WMqLJm8kecK5NqdrQp2n70XeH0NZRl7Sf3PEUl40ecPNE851sVxD34u8x4TjHW6psZYVaf5Irg/n2pyuye58ove9wLrptF9nFp7+bl+kSJFwuwDXeUiAKcAJ1pga/OvZs2fQp9YgYOZzy5YtyxIA1My6vt+YMWPMK2hhvoM33HCDzJgxQ+Id/NP76T84DRs2DHXrfDleqFAhc9/k5OQ8uX+87xdLedHkDTdPvK4LpxwN/uVV+8Wzk4RTN7feL9ZnjzR/JNeHc21O1+R03mmXROx74dbNqWOsX+N9v1jLizR/JNeHc21O1+R0XtsjEfudPnc4ddPr4pXifb9YyosmbyR5wrk2p2tyOq/tQt8Lr3eGYxleSf+9Kpbyoskbbp5wrovXNfS98HpMON7hlRT7v9mRPksk14dzbU7X5HTecUrEvpe5bkz7dVrT3q8EAC1s+w0bNsjChQtl9erVsnPnTjl06JCcOHHCjAKsXLmy1K9fXzp27Cjt27f3/5BuIRNVRgABBBBAAAEEEEAAAQQQQAABBDwhQAAwwZqxR48eoq9Ykgb49EVCAAEEEEAAAQQQQAABBBBAAAEEEPC+AJuAeL+NqSECCCCAAAIIIIAAAggggAACCCCAgMUCbAJiceNTdQS8ILBv3z5JSUkxVdm7d29CrgHohXawsQ70PRtbPf/rTL/L/zaw9Qnoe7a2fP7Xm76X/21g6xPQ92xtee/WmxGA3m1baoYAAggggAACCCCAAAIIIIAAAggggIAQAKQTIIAAAggggAACCCCAAAIIIIAAAggg4GEBAoAeblyqhgACCCCAAAIIIIAAAggggAACCCCAAGsA0gcQQAABBBBAAAEEEEAAAQQQQAABBBDwsAAjAD3cuFQNAQQQQAABBBBAAAEEEEAAAQQQQAABAoD0AQQQQAABBBBAAAEEEEAAAQQQQAABBDwsQADQw41L1RBAAAEEEEAAAQQQQAABBBBAAAEEECAASB9AAAEEEEAAAQQQQAABBBBAAAEEEEDAwwIEAD3cuFQNAQQQQAABBBBAAAEEEEAAAQQQQAABAoD0AQQQQAABBBBAAAEEEEAAAQQQQAABBDwsQADQw41L1RBAAAEEEEAAAQQQQAABBBBAAAEEECAASB9AAAEEQghcuXJFxo0bJ/Xr15eiRYtKyZIlpVmzZjJ//vwQOTiMQHwE0tPTZc6cOdKiRQupVKmS6X+1a9eWJ554Qr7//vv43IRSEMgkMHXqVElKSsr2dd9992XKxUcE4iswd+5cadmypZQtW1aKFCkiVatWla5du8revXvjeyNKQ+B/AmlpaSH/3WvevDlOCOSJwPDhw/39cPXq1XlyT25in0BB+6pMjRFAAIGcBTQA84tf/EJmz54t1atXl169esn58+dl3rx50r59exk7dqw8/fTTORfEFQhEITBw4EB55ZVXTPCvQ4cOJvj85ZdfyqRJk+Ttt9+WVatWyU033RRFyWRBILTArbfeKi+99FLQC95991355ptv5P777w96noMIxCqg33effPJJmThxovm+26VLFylRooT88MMPsnz5ctm9e7ekpKTEehvyIxBU4Nprr5VnnnkmyzkNDpIQyG2BzZs3m++/xYoVk9OnT+f27SjfYoEk3zfbdIvrT9URQACBoAL6y26nTp3k7rvvlsWLF8s111xjrjt69Kg0aNBADh48KFu3bhV+MAzKx8EYBLRvValSxfyiq0E//aXESaNGjZJf/epX0rNnT3nzzTedw3xFIFcFLly4IJUrV5b//Oc/sm/fPrnuuuty9X4UbqfAmDFjTACmb9++8uqrr0qBAgUyQFy6dEkKFmTsQgYUPsRFwPlZbteuXXEpj0IQiETg4sWL0qhRIylUqJDUrFlTZsyYIZ9//rk5Fkk5XItAOAJMAQ5HiWsQQMA6AR3pp+mFF17wB//0c7ly5WTAgAFmNOCUKVP0EAmBuAroLyA6/VyDz4HBP71J27Ztzb2OHDkS13tSGALZCbz33nty7Ngx0/8I/mUnxbloBc6ePStDhw6VatWqiQYCMwf/tFyCf9Hqkg8BBNwsMGzYMDPCXv+wG+zfPjc/O8+WeAIEABOvzXhiBFwvcPjwYfnggw/kxRdflAceeMAEzZx1pXr06BHR8+uUn2effVbq1KkjOiy+TJky0rBhQxkxYoScOXMmorIiuVhHYWnStYcyJ+fY0qVLM5/icz4LeKHv6V9/r776avnss8/k5MmTGUT1/ytNrMOWgcUVH7zQ90JBvvHGG+ZU7969Q13C8XwU8ELf++ijj+T48eOiSx5cvnzZrIH65z//WSZMmCA7duzIR11unZ2AF/qeUz9d5kXXQf3Tn/5k1n9es2aNc4qvLhPwUr/buHGjaABQl9+oW7euy6R5HE8K6BRgEgIIIBBPAd8/lrq0QNDXo48+GvatfJttpPs23ghajpZfq1at9O3bt4ddXiQX+tYeMvddsGBBlmyjR4825ypUqJDlHAfyVyBUv9PjidL3VNC3/l+6L2ie7tsAJN23Jlb6r3/963Tf2mvpvukh6b7pcem+6SL5C83dswh4pe9lrphvRGr6VVddlZ6cnJzum4KZ+TSfXSDghb73u9/9znxfHTRokPneHlgn7X++PwS6QJpHyCwQ2E6Z3yfS99zU1NSgP2v6/uCc7gtAZ642n/NZIHNfC/ycSP3u3Llz6TfeeGO6b2kh//dXfX6tj28KcD4rc3uvCjAC0Pd/GAkBBHJP4Prrr5dWrVpFfINNmzZJ586dzQio4sWLm7+O6cYHS5YskT59+pjytm3bJg8++KCcOnUq4vJzyqAjFzXpCATfN2j/5ToNzhcANJ9PnDjhP84b9wkkat9TSZ1mPnPmTPnxxx/NCJi//OUv8uGHH8qdd94pDz/8MFPh3NfdMjxRIve9DBXxfdClDnRKuo7eZmpSZh33fU7UvqcjejTp5ke69MHatWvN9/ZPP/1UfH/sk5EjR8r48ePdB84T+QUSte9pBXRdXf358tChQ2YDBv0Z9JFHHpF169aZEfe58XOmH443MQkkcr/TmVK+gQzm+yzfX2PqBmSOQICVdCPA4lIEEAhPQL+h6TRdfel6UbqmmTNtNrwSRPr37y+6JpCu+aNTgxo3buzPeu+995pFcn2jokSDgPqLwZAhQ/znnTc6dVindISb9J46/VKTBll0KsiyZcukXr160rp1a9FFenUtLGcNLN+ohHCL5ro8EvBC31Oq3//+9/LHP/7RfO3WrZuUKlVKvvjiCxMYbN68udmd+qGHHsojVW4TjoBX+l5gXTXwpwFAXcLhscceCzzFexcJeKHvaV/TpMsf6PdZ3XRGU9OmTeWdd96RW265xXyvf+qpp8xx/uMOAS/0PZXMvPu57og+ffp0g/zWW2/JpEmTzAZc7lDnKbzQ73STj5dfftn8/nLTTTfRqAjknYBXhzZSLwQQcI/Azp07/VMrwhma71t3xX/9E088EbQivjWC0m+44QZznS84ku7bpTLLdb41A/3l+P5VzfG9L9iXoQwdmu8LLJrpSL5fStLLly+f/vjjj6f7go6mLN9fHTNczwf3CSRi3/PtOm36l28UYBbQAwcOpPt2pE6vUaNGlnMccJdAIva9zIK+UaemL/rWnMx8is8uFkjEvjdw4EDT13wBv6Cy+m+efh/3rRMY9DwH3SGQiH0vO7mVK1eafvfTn/40u8s4l88CidbvdBkX34CDdF+gOcvvL0wBzufOZMHtGb6Sd7FW7oQAAmEK6F//naTTMoIlHX3XvXt3c0qn4upIvcxJp0/6/h0P+6UjqwJT4cKFzV+Fv/32WzOSUKcovf7667J//35zmW/NjsDLee8BATf0vYULFxrJFi1aZBGtWLGi2RBHF8XX/k3yjoAb+l5mTTb/yCzizc9u6Hu1a9c2uDraOVhyjuvMAJJ3BNzQ97LTLFeunDl9+vTp7C7jXIIJ5He/05/fdOqvzuzQUc/ORon6ddq0aUZTZz7p58BnTTBmHtelAkwBdmnD8FgI2Czg+4urqb7u+nv77beHpLjnnnv853TH1GjWGvQXEMGbv/3tb+Zq30YhEeTi0kQQcEPf841mNVRHjhwJSqbHNQDu2xAk6HkOJqaAG/peoJyudzpv3jyz83rHjh0DT/HeYwJu6HvOHzy2bNmSRVeX39A/eujPBL6R+FnOcyBxBdzQ97LTc3YCTktLy+4yziWYQH73Ox1g0KtXr6Bquu6pBgd1mRf9946+F5SJgzEIEACMAY+sCCCQOwLOLwC+KT/ZbnZQp04d/wM4efwH4vDm5MmT4tuFOENJ7777rrz55ptmfUPflJAM5/iQ+AJOP8rPvnf33XfLuHHjzGL4P/vZz8yC+I7shAkTZN++faLX6A+QJO8IuKHvBWrqulcajNY1KOlrgTLee++Gvle9enXzRzxd81dHnvbu3dsPrZtx6Uh/7Yu6LjDJOwJu6Htbt24V3UiiaNGiGWD1+HPPPWeO6brQJO8I5He/8y3lYv6dCyaqG25pAPD555+XRo0aBbuEYwjEJMB30Zj4yIwAAvEW0B13jx49aopNTk7OtvjSpUubEQE6NWPv3r3ZXhvNSd1xNSUlRXxrDUqRIkXMroSffPKJVKtWzSxKzo5d0ai6N49b+l6nTp3MbpfO7pf6V2Cd/rZx40ZZunSp6A+OulMmyTsCbul7gaKTJ082HwMDMYHnee8NATf1vddee03uuusu6dOnj5n2pn/k091Y9d+91NRUGTFihDfQqYURcEvfmzlzpvme2qxZM9PPdKSpbjD3z3/+02z+poEYPUfyhoBb+p03NKlFIgoQAEzEVuOZEfCwwKlTp/y1K168uP99qDf6g5oGAHNjPbTOnTvLnDlzZPXq1eaHQN3JePDgwTJo0KAsIwNDPR/HE0fALX1PA8s6CmbUqFEya9Ys+fvf/25GYunu0zoC5oUXXjBB6cSR5UlzEnBL33Oec+3atbJ582a54447zC7oznG+ek/ATX1PRwGuX79edIfPRYsWmX8Hdd3Tfv36mWMVKlTwXgNYXCO39D2dfq4jwjTYvGLFCjlz5ozo2n9t2rSRvn375tnyMhZ3hTytulv6XZ5WmpshECBAADAAg7cIIJD/AvqXOSfpwrg5JWdqWm4sDO7bAVj0RbJDwE19T/v1b37zG/OyQ9/uWrqp72lLaOBPN1AieV/AbX1PR91PmTLF+/DUUNzS93Q96cA1pWkabwu4pd+FUp46daroi4RAbgmwC3BuyVIuAghEJaBTbZ3kbIbgfA729fz58+awToskIRCLAH0vFj3yxiJA34tFj7yxCND3YtEjbywC9L1Y9MgbrQD9Llo58nlFgACgV1qSeiDgEYESJUr4axLOtF6d/qspnOnC/oJ5g0AQAfpeEBQO5YkAfS9PmLlJEAH6XhAUDuWJAH0vT5i5SSYB+l0mED5aJ0AA0Lomp8IIuFtA/zJXtmxZ85C622l26fjx42b9P71Gpw2REIhFgL4Xix55YxGg78WiR95YBOh7seiRNxYB+l4seuSNVoB+F60c+bwiQADQKy1JPRDwkEDdunVNbXbs2CGXLl0KWbOtW7f6z+lOvSQEYhWg78UqSP5oBeh70cqRL1YB+l6sguSPVoC+F60c+WIRoN/FokfeRBcgAJjoLcjzI+BBgSZNmpha6fTeDRs2hKzh8uXL/efuvvtu/3veIBCtAH0vWjnyxSpA34tVkPzRCtD3opUjX6wC9L1YBckfjQD9Lho18nhFgACgV1qSeiDgIYEOHTr4axNqN8ArV67I9OnTzXWlSpWSFi1a+PPwBoFoBeh70cqRL1YB+l6sguSPVoC+F60c+WIVoO/FKkj+aATod9GokccrAgQAvdKS1AMBDwnccccd0rRpU1OjyZMny+eff56ldiNHjpQtW7aY4/3795dChQpluYYDCEQqQN+LVIzr4yVA34uXJOVEKkDfi1SM6+MlQN+LlyTlRCJAv4tEi2u9JpCU7kteqxT1QQCB/BVYuXKl6Pp9Tjp69KgMGjTIfNSpur1793ZOma89evTI8Fk/bNq0SfTas2fPmh1+X3jhBTPKTz/PnDlTJk6caPLUqlVL1q9fL4G7emUpjAPWCND3rGlq11WUvue6JrHmgeh71jS16ypK33Ndk1jxQPQ7K5qZSuaSAAHAXIKlWARsFtCA3rRp08ImCPV3iPfff1+6desmJ0+eDFqWBv8WLFggNWrUCHqeg/YJ0Pfsa3O31Ji+55aWsO856Hv2tblbakzfc0tL2PUc9Du72pvaxleAKcDx9aQ0BBCIo0C7du3kq6++kgEDBogG+4oWLSq63l+DBg1k+PDhZpQgwb84glOUX4C+56fgTR4L0PfyGJzb+QXoe34K3uSxAH0vj8G5nRGg39ERbBRgBKCNrU6dEUAAAQQQQAABBBBAAAEEEEAAAQSsEWAEoDVNTUURQAABBBBAAAEEEEAAAQQQQAABBGwUIABoY6tTZwQQQAABBBBAAAEEEEAAAQQQQAABawQIAFrT1FQUAQQQQAABBBBAAAEEEEAAAQQQQMBGAQKANrY6dUYAAQQQQAABBBBAAAEEEEAAAQQQsEaAAKA1TU1FEUAAAQQQQAABBBBAAAEEEEAAAQRsFCAAaGOrU2cEEEAAAQQQQAABBBBAAAEEEEAAAWsECABa09RUFAEEEEAAAQQQQAABBBBAAAEEEEDARgECgDa2OnVGAAEEEEAAAQQQQAABBBBAAAEEELBGgACgNU1NRRFAAAEEEEAAAQQQQAABBBBAAAEEbBQgAGhjq1NnBBBAAAEEEEAAAQQQQAABBBBAAAFrBAgAWtPUVBQBBBBAAAEEEEAAAQQQQAABBBBAwEYBAoA2tjp1RgABBBBAAAEEEEAAAQQQQAABBBCwRoAAoDVNTUURQAABBBBAAAEEEEAAAQQQQAABBGwUIABoY6tTZwQQQAABBBBAAAEEEEAAAQQQQAABawQIAFrT1FQUAQQQQAABBBBAAAEEEEAAAQQQQMBGAQKANrY6dUYAAQQQQAABBBBAAAEEEEAAAQQQsEaAAKA1TU1FEUAAAQQQQAABBBBAAAEEEEAAAQRsFCAAaGOrU2cEEEAAAQQQQMBygV27dklSUpJ5TZ061XINqo8AAggggAACXhcgAOj1FqZ+CCCAAAIIIIAAAggggAACCCCAAAJWCxAAtLr5qTwCCCCAAAIIIIAAAggggAACCCCAgNcFCAB6vYWpHwIIIIAAAggggAACCCCAAAIIIICA1QIEAK1ufiqPAAIIIIAAAggggAACCCCAAAIIIOB1AQKAXm9h6ocAAggggAACCCCAAAIIIIAAAgggYLUAAUCrm5/KI4AAAggggEBeCAwZMsS/46ze7+TJk6LH6tWrJ8WLF5cKFSpImzZtZNWqVRke5/DhwzJ48GC58cYbpVixYlK2bFlp3769bNq0KcN1gR++//57GTlypLRr107S0tLkmmuuMa/U1FTp3LmzLFq0KPDyoO9PnDghw4YNk8aNG0vp0qWlUKFCUr58ealbt6507NhRxo8fL4cOHQqad+nSpdK1a1epWrWquW/RokVF792oUSMZOHCg6PncSJ999pn07t1bateuLSVLlpSrr75akpOTpW3btvLXv/5VtE4kBBBAAAEEEEDAVoGkdF+ytfLUGwEEEEAAAQQQyAsBDfYNHTrU3GrPnj3yk5/8RLZt25bl1gUKFJC3335bOnXqJF999ZUJCu7fvz/LdYULF5aFCxdKixYtMpzbuXOnVKtWLcOxYB+6desmU6ZMkYIFC2Y5vWXLFvN8P/zwQ5ZzgQfGjh0rTz/9dOAhGTBggIwePTrDscwfNIh59OjRzIej/nz27Fnp1auXccuukJdeeskEXZ1rdu3aZYKU+lktevTo4ZziKwIIIIAAAggg4DmBrD/1ea6KVAgBBBBAAAEEEHCPgAb39u3bJ88//7y0bt1adITcypUrRQNUOjJQg1kNGjQwI9c0uKUj8e655x4zCk9H7+nn8+fPm4DV9u3bzUg3p3aXL182n++//35p2bKlGbFXpkwZ+fe//20CjjoS7ptvvpEZM2aYQKETlHTy69dHHnlENPino/769OkjDzzwgFSsWFGuXLlinnv16tUyd+7cwCzm/QcffOAP/t18883y1FNPyQ033CDXXnutGX2n9/34449l7dq1WfJGe0CfSUdELl682BRRs2ZN6du3r/FT1wMHDphRlbNmzYr2FuRDAAEEEEAAAQQ8IcAIQE80I5VAAAEEEEAAATcLBI4A1NF7y5cvlzvvvDPDIy9YsMAE/fSgTrfVSRoabKtevXqG61577TXp16+fOTZnzhwzJde54PTp0yaIWKlSJedQhq9a5mOPPSZTp041U4p1dKEG6Jyk04ed+wUb4edcp+XolFqdHuyk7t27y1tvvWWm+27evNlMbXbOBX7VYKQGJeORXn31Venfv78pSqcm6+hJ9c2cNFCowcAqVar4TzEC0E/BGwQQQAABBBCwQIA1AC1oZKqIAAIIIIAAAu4ReOaZZ7IE//TpHnzwQRM80/dHjhyRP/zhD/5gnB5zUs+ePaVIkSLm44oVK5zD5quuExgq+KcXJCUlmfUBdaqxBgt1RF5gOnjwoP9js2bN/O8zv9FyAoN/et7JW79+/ZDBP70uXsE/DeqNGDFCizRr/U2fPj1o8E/PX3XVVRmCf3qMhAACCCCAAAII2CRAANCm1qauCCCAAAIIIJDvAl26dAn5DDp1VpMG2HTDjmBJN/XQqa6adMRedunixYtm2q6u66ej8vSl03t1HT5NX375ZYbsgcFDHSUYSXLyfvrpp/Ldd99FkjWqa7/44gtTN82sU5V1MxUSAggggAACCCCAQHABAoDBXTiKAAIIIIAAAgjkikCtWrVClluqVClzrly5cllG2AVmcq47depU4GHzXoN+utaf7rqrQbGUlBSzFqDuOOy8dHdhTZk349Cde5s2bWrOjRo1yuw+/OKLL5qde8+cOWOOh/qPTgHWdOzYMbnppptEA526ucaOHTtCZYnpeOBOyM4zx1QgmRFAAAEEEEAAAQ8LEAD0cONSNQQQQAABBBBwn4BuThEq6VRVTdldo+ed63TTj8Ck6+s1btzY7M67Zs0auXDhQuDpLO91k5HMSdfR0zI0/etf/zJTke+77z7RoKNOC54wYYKcO3cuczbRa8aNGyc6QlHP/+Mf/zDrDepoxeTkZHnyySezjDjMUkgEBwKDl87owwiycykCCCCAAAIIIGCVAAFAq5qbyiKAAAIIIICAlwV0Q4wNGzaYKnbo0EHmz58vutmFjt7TNfN08w596ahATfo+c9KNMlatWmXWB9QddW+88UYzJVlHFuqag7q7r47w27ZtW+asZnMSvZ+OHmzTpo1/gxHdbOT111+X2267TQYPHpwlHwcQQAABBBBAAAEEcleAAGDu+lI6AggggAACCCCQJwInT540o+70Zr/85S9l7ty50q5dO7OxiI7K03UFnXT8+HHnbcivOqJPpxLruoG6KcnMmTPl3nvvNdfrGn+h1iisUKGC6EYnuquxjkjUgKQG/XQEoQYchw0bJvPmzQt533BP6DRpJ+kOvyQEEEAAAQQQQACB0AIEAEPbcAYBBBBAAAEEEEgYge3bt4uO0tMUKjin57Zu3So//vijvg076aYhWuaSJUvkoYceMvl0Ew69Z3ZJpyrrrsC6o7HmddKsWbOct1F/1XKdpBuPkBBAAAEEEEAAAQRCCxAADG3DGQQQQAABBBBAIGEELl265H/W06dP+99nfqNr+MWSdGSgkwLX4XOOhfqqAbvSpUub05HkC1XeLbfc4p/K/MYbb0Qc1AxVLscRQAABBBBAAAEvChAA9GKrUicEEEAAAQQQsE6gRo0a/mm+06ZNC7q+3/vvv2826giFo6P69BUq6RTejz/+2JzWKcVpaWn+S3XTj2CbijgXrF+/Xpypx7rbcKxJRxcOGjTIFLNv3z7RXYhDbXqi6x/+8MMPsd6S/AgggAACCCCAQMIKFEzYJ+fBEUAAAQQQQAABBPwCOk1XN97QtfcWLVokrVq1Mht2pKamyuHDh2X27NkydepUqVatmpw4ccKs6+fP/L83Gvzr2bOnNGzY0KwfqKP2KlasaKYW79y5U6ZMmSKLFy82V+tU4MDdd5977jmz02/79u3NbsG1atWSYsWKybFjx2TlypUyduxYk69AgQLSu3fvzLeO6nO/fv1Eg5r6TLrmYb169UQ3LmnQoIHZSfngwYOyevVq0Z2NH374YRkyZEhU9yETAggggAACCCCQ6AIEABO9BXl+BBBAAAEEEEDgfwLjx4+XJk2ayJ49e8xIPWe0ngN0/fXXy3vvvWcChc6xYF/XrVsn+gqV7rrrLpk8eXKW0xpY1NGH+gqWChcuLDoFWQN08Ug6ClDr8+ijj8q7775rdibWDUhICCCAAAIIIIAAAhkFCABm9OATAggggAACCCCQsAIpKSmyceNGGT58uNlpd/fu3VKkSBEzVbdDhw7Sv39//zp8wSrZtWtXue6668yIOg0A7t+/Xw4dOiS6vqDu7qsjAnUzkC5duogG3wLTsmXLzGg83ZBj27ZtoqPvdMpv0aJFpXr16qJrBz711FNmBGJgvljfa/nvvPOO6P11hKKONtR7X7582dTl1ltvlbZt24rWjYQAAggggAACCNgqkORbyyXd1spTbwQQQAABBBBAAAEEEEAAAQQQQAABBLwukPFPt16vLfVDAAEEEEAAAQQQQAABBBBAAAEEEEDAMgECgJY1ONVFAAEEEEAAAQQQQAABBBBAAAEEELBLgACgXe1NbRFAAAEEEEAAAQQQQAABBBBAAAEELBNgExDLGpzqIoAAAggggAACbhC4ePGifPvtt1E9StWqVaVYsWJR5SUTAggggAACCCBgowCbgNjY6tQZAQQQQAABBBDIZ4Fdu3aJBvKiSbrjb/PmzaPJSh4EEEAAAQQQQMBKAaYAW9nsVBoBBBBAAAEEEEAAAQQQQAABBBBAwBYBRgDa0tLUEwEEEEAAAQQQQAABBBBAAAEEEEDASgFGAFrZ7FQaAQQQQAABBBBAAAEEEEAAAQQQQMAWAQKAtrQ09UQAAQQQQAABBBBAAAEEEEAAAQQQsFKAAKCVzU6lEUAAAQQQQAABBBBAAAEEEEAAAQRsESAAaEtLU08EEEAAAQQQQAABBBBAAAEEEEAAASsFCABa2exUGgEEEEAAAQQQQAABBBBAAAEEEEDAFgECgLa0NPVEAAEEEEAAAQQQQAABBBBAAAEEELBSgACglc1OpRFAAAEEEEAAAQQQQAABBBBAAAEEbBEgAGhLS1NPBBBAAAEEEEAAAQQQQAABBBBAAAErBQgAWtnsVBoBBBBAAAEEEEAAAQQQQAABBBBAwBYBAoC2tDT1RAABBBBAAAEEEEAAAQQQQAABBBCwUoAAoJXNTqURQAABBBBAAAEEEEAAAQQQQAABBGwRIABoS0tTTwQQQAABBBBAAAEEEEAAAQQQQAABKwUIAFrZ7FQaAQQQQAABBBBAAAEEEEAAAQQQQMAWAQKAtrQ09UQAAQQQQAABBBBAAAEEEEAAAQQQsFKAAKCVzU6lEUAAAQQQQAABBBBAAAEEEEAAAQRsEfg/xv2pubA2/28AAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "plt.scatter(out[\"mass_cl\"], out[\"logRs\"], s=3, rasterized=True)\n",
    "# t = np.logspace(-8, -4, 1000)\n",
    "# plt.plot(t, t, c=\"red\", ls=\"--\")\n",
    "\n",
    "\n",
    "# plt.yscale(\"log\")\n",
    "plt.xscale(\"log\")\n",
    "plt.xlabel(\"mass_cl\")\n",
    "# plt.ylabel(\"summed mass of all particles\")\n",
    "\n",
    "plt.savefig(\"../plots/mass.png\", dpi=400)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31897bb1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3ba9b194",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:36:29.023226Z",
     "start_time": "2022-10-30T17:36:28.965291Z"
    }
   },
   "outputs": [],
   "source": [
    "mask = np.isin(out[\"index\"], arr[\"index\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0838d466",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:36:30.294366Z",
     "start_time": "2022-10-30T17:36:30.269872Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True, ..., False, False, False])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae65a0fb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7723d433",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.where()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7aecdd0a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d5e27dec",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-10-30T17:34:30.777941Z",
     "start_time": "2022-10-30T17:34:30.751670Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([       1,        2,        3, ..., 21795024, 21796985, 21797711])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c70b85f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "570c36e1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2ceefa8",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2022-10-30T17:26:08.181Z"
    }
   },
   "outputs": [],
   "source": [
    "# clump_ids = csiborgtools.io.read_clumpid(Nsnap, simpath)\n",
    "# clumps = csiborgtools.io.read_clumps(Nsnap, simpath, )\n",
    "\n",
    "# particles = csiborgtools.io.read_particle([\"x\", \"y\", \"z\", \"M\", \"level\"], Nsnap, simpath)\n",
    "# clump_ids, particles = csiborgtools.io.drop_zero_indx(clump_ids, particles)\n",
    "\n",
    "# with_particles = csiborgtools.fits.clump_with_particles(clump_ids, clumps)\n",
    "# clumps = clumps[with_particles]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45d91357",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2022-10-30T17:26:08.182Z"
    }
   },
   "outputs": [],
   "source": [
    "f = join(utils.dumpdir, \"ramses_out_09844_01016_123.npy\")\n",
    "f = np.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "507f8233",
   "metadata": {
    "ExecuteTime": {
     "start_time": "2022-10-30T17:26:08.183Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.figure()\n",
    "plt.hist(f[\"logRs\"], bins=\"auto\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c202dd8b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv_galomatch",
   "language": "python",
   "name": "venv_galomatch"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  },
  "vscode": {
   "interpreter": {
    "hash": "f29d02a8350410abc2a9fb79641689d10bf7ab64afc03ec87ca3cf6ed2daa499"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}