ExamplesNotebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import AmorphSim\n",
    "from AmorphSim.clusters.clusters import Icosahedron\n",
    "import matplotlib.pyplot as plt\n",
    "import diffsims as ds\n",
    "from diffsims.utils.fourier_transform import get_recip_points\n",
    "from diffsims.utils.probe_utils import BesselProbe\n",
    "import time\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1, 2, 9], [1, 2, 10], [1, 5, 6], [1, 5, 9], [1, 5, 6], [1, 6, 10], [1, 2, 9], [1, 5, 9], [1, 2, 10], [1, 6, 10], [1, 2, 9], [1, 2, 10], [2, 7, 8], [2, 7, 9], [2, 7, 8], [2, 8, 10], [1, 2, 9], [2, 7, 9], [1, 2, 10], [2, 8, 10], [3, 4, 11], [3, 4, 12], [3, 5, 6], [3, 5, 11], [3, 5, 6], [3, 6, 12], [3, 4, 11], [3, 5, 11], [3, 4, 12], [3, 6, 12], [3, 4, 11], [3, 4, 12], [4, 7, 8], [4, 7, 11], [4, 7, 8], [4, 8, 12], [3, 4, 11], [4, 7, 11], [3, 4, 12], [4, 8, 12], [1, 5, 6], [1, 5, 9], [3, 5, 6], [3, 5, 11], [1, 5, 6], [3, 5, 6], [1, 5, 9], [5, 9, 11], [3, 5, 11], [5, 9, 11], [1, 5, 6], [1, 6, 10], [3, 5, 6], [3, 6, 12], [1, 5, 6], [3, 5, 6], [1, 6, 10], [6, 10, 12], [3, 6, 12], [6, 10, 12], [2, 7, 8], [2, 7, 9], [4, 7, 8], [4, 7, 11], [2, 7, 8], [4, 7, 8], [2, 7, 9], [7, 9, 11], [4, 7, 11], [7, 9, 11], [2, 7, 8], [2, 8, 10], [4, 7, 8], [4, 8, 12], [2, 7, 8], [4, 7, 8], [2, 8, 10], [8, 10, 12], [4, 8, 12], [8, 10, 12], [1, 2, 9], [1, 5, 9], [1, 2, 9], [2, 7, 9], [1, 5, 9], [5, 9, 11], [2, 7, 9], [7, 9, 11], [5, 9, 11], [7, 9, 11], [1, 2, 10], [1, 6, 10], [1, 2, 10], [2, 8, 10], [1, 6, 10], [6, 10, 12], [2, 8, 10], [8, 10, 12], [6, 10, 12], [8, 10, 12], [3, 4, 11], [3, 5, 11], [3, 4, 11], [4, 7, 11], [3, 5, 11], [5, 9, 11], [4, 7, 11], [7, 9, 11], [5, 9, 11], [7, 9, 11], [3, 4, 12], [3, 6, 12], [3, 4, 12], [4, 8, 12], [3, 6, 12], [6, 10, 12], [4, 8, 12], [8, 10, 12], [6, 10, 12], [8, 10, 12]]\n",
      "Numshells 2\n",
      "Total Atoms :  55\n"
     ]
    }
   ],
   "source": [
    "ico = Icosahedron(num_shells=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "ico.get_5_fold_axis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "ico.add_disorder(.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "real_grid, recip_grid =get_recip_points(2, dX=.2, rX=40)\n",
    "probe = BesselProbe(50)\n",
    "c = ico.xyz_cartn.reshape(-1,3).max(0)/2 # Centre of crystal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "ediff=ds.generators.diffraction_generator.AtomicDiffractionGenerator(500, real_grid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Standard diffraction pattern: 4.08s'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tic = time.time()\n",
    "diff_plain = ediff.calculate_ed_data(ico, probe, slice_thickness=1, probe_centre=c[:2])\n",
    "'Standard diffraction pattern: %.2fs'%(time.time()-tic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = ico.xyz_cartn.reshape(-1,3).max(0)/2 # Centre of crystal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "centers = [[c[:2]+[x,y] for x in np.arange(-1,1,.1)] for y in np.arange(-1,1,.1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tic = time.time()\n",
    "stem = [[ediff.calculate_ed_data(ico, probe, slice_thickness=1, probe_centre=c) for c in cen] for cen in centers]\n",
    "'Standard diffraction pattern: %.2fs'%(time.time()-tic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_plain = ediff.calculate_ed_data(ico, probe, slice_thickness=1, probe_centre=c2[:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
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       "};\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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* 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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.imshow(diff_plain)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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 (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",
       "    // 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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* 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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.imshow(diff_plain)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "spot_indices, cartesian_coordinates, spot_distances = get_points_in_sphere(ico.lattice.reciprocal(), 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "max() arg is an empty sequence",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mValueError\u001B[0m                                Traceback (most recent call last)",
      "\u001B[0;32m<ipython-input-25-39a6b803689d>\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[0;32m----> 1\u001B[0;31m \u001B[0mgenerator\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mcalculate_profile_data\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mico\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m",
      "\u001B[0;32m~/AmorphSimDevelop/lib/python3.7/site-packages/diffsims/generators/diffraction_generator.py\u001B[0m in \u001B[0;36mcalculate_profile_data\u001B[0;34m(self, structure, reciprocal_radius, minimum_intensity)\u001B[0m\n\u001B[1;32m    266\u001B[0m                 \u001B[0mhkls\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mappend\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mk\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    267\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m--> 268\u001B[0;31m         \u001B[0my\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mnp\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0masarray\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0my\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;34m/\u001B[0m \u001B[0mmax\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0my\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;34m*\u001B[0m \u001B[0;36m100\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m    269\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m    270\u001B[0m         \u001B[0;32mreturn\u001B[0m \u001B[0mProfileSimulation\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mx\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0my\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mhkls\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;31mValueError\u001B[0m: max() arg is an empty sequence"
     ]
    }
   ],
   "source": [
    "generator.calculate_profile_data(ico)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "    // 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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* 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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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.one(\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",
       "\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",
       "    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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f8d3a4dc950>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.imshow(sim.get_diffraction_pattern())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'cube' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mNameError\u001B[0m                                 Traceback (most recent call last)",
      "\u001B[0;32m<ipython-input-13-d1b02fe8b848>\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[0;32m----> 1\u001B[0;31m \u001B[0mcube\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0madd_random_clusters\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mnum_clusters\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0;36m1000\u001B[0m\u001B[0;34m)\u001B[0m \u001B[0;31m# adding 1000 randomly oriented clusters\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m      2\u001B[0m \u001B[0mprint\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mcube\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;31mNameError\u001B[0m: name 'cube' is not defined"
     ]
    }
   ],
   "source": [
    "cube.add_random_clusters(num_clusters=1000) # adding 1000 randomly oriented clusters\n",
    "print(cube)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cube.plot_symmetries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e88004e8da77494ca00c1a210b385d76",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=16384.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dbd7f4db0517429eb34f6ba809974a66",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=16384.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7e4e815854d84affb0fb3f75b564fbb3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=16384.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3f2f73b80679427e91f2a036eddad171",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=16384.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "no_noise = cube.get_4d_stem(convolve=True)\n",
    "small_noise = cube.get_4d_stem(noise=100, convolve=True)\n",
    "med_noise = cube.get_4d_stem(noise=200, convolve=True)\n",
    "large_noise = cube.get_4d_stem(noise=500, convolve=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import hyperspy.api as hs\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:hyperspy.drawing.utils:Axes labels were requested, but one or both of the axes units and/or name are undefined. Axes decorations have been set to 'ticks' instead.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f = plt.figure(figsize=(20,10))\n",
    "hs.plot.plot_images([no_noise.inav[10,10],\n",
    "                      small_noise.inav[10,10],\n",
    "                      med_noise.inav[10,10],\n",
    "                      large_noise.inav[10,10]],per_row=4, fig=f, colorbar=None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_noise.set_signal_type(\"DiffractionSignal\")\n",
    "small_noise.set_signal_type(\"DiffractionSignal\")\n",
    "med_noise.set_signal_type(\"DiffractionSignal\")\n",
    "large_noise.set_signal_type(\"DiffractionSignal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "no_noise.metadata.Signal.Ellipticity.center= [64,64]\n",
    "no_noise.metadata.Signal.Ellipticity.angle = None\n",
    "no_noise.metadata.Signal.Ellipticity.lengths = None\n",
    "no_noise.metadata.Signal.Ellipticity.calibrated = True\n",
    "no_noise_polar = no_noise.calculate_polar_spectrum(phase_width=180)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "39520522451446d6b0931ac70153fe74",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=2500.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = no_noise_polar.autocorrelation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:hyperspy.signal:The function you applied does not take into account the difference of units and of scales in-between axes.\n"
     ]
    }
   ],
   "source": [
    "p = corr.get_power_spectrum().isig[0:12,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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jjvKfmy8L/+cC5oBrj7rZpttVgxWqm+ofrZ2FP7Sl74UnnrqqVzUScsfe+yx8JnPfCZsvfXWRZ7LLbdc2GijjcLb3/728Mtf/nLS6RIRAhAYYgKtJyMECEBgFgm0BtUmWj90Jlpuoudf60dih6WtmSZlvNaPpI77VcE///M/l/o6d6Gqc8stt0y0BiLLeFVbWz8OJ374wx+WSbV2WptorXeV1W8Nxk1cccUVpb47aQ2MlfFvu+22idaiyhPLLLNMKava0PqhOvHwww+XSX3yk5+caD19zeq3BjInWp2pUj930hr4nDj44IMnWjN5smnJFtVh68drLplS3no6PNF67a9rWq1dOidar6xMVOuhTIQTCECgUQTe8573lD5h9913n1LZUt9Z9ZPV62pG8k+tNQl7+rvWw5SJ1vqF1eht1/o+ivnpe6pbaD1Emmj96Cz1Y7z02NpVeeL3v//9RFo+fTcQIAABCDgCd95558Tyyy9f+JXWA9aJ1rqrhVpreYbS18ifDCKkvqrbucuv9cB8Yt999y1tysVvPSieuOCCC7qam5btzW9+c1fd1qZTE60HO9l81YduTU4o0kht6pooNyEAgaEn8KzWB5oAAQjMEoHzzjsvtAaXytw1S007QeqJ37Oe9aygJ3M33nhjuOaaa0Lrh0+pN5Mnjz/+eNhtt90KO2SfXm1bc801i9mIP/7xj4vZapq5odfYfvOb3wS9/vC3f/u3QfG026VmNWomY6sjFn7yk58U93Vv7733LhZK1ky+XuHCCy8snopq0fznP//5xSw8PRn99a9/Ha666qoi+tVXXx1e97rXhX//938vnmZ+9KMfLeQvfOELi1mC4tkamAya2aKg2ZKtH93hq1/9anHt/ulp68te9rLy6bF0NCNlyy23LJ6UtgYci3ua/bdo0aJiMX+VTTMFc0EzJs8666zytmYl7rLLLiUj2aUZla1BgLDXXnuVepxAAALNJSDfGcO6664bTyd1bP3oK2foabZzDJp93S3Iv77qVa8K3/ve90q1VVZZpZj1p6Nmqmsmnr6LtIuxXnHW8V3velepP5kTzZJ56UtfGu69994yumbAvOhFLypmz2gjE30Hyle3HgKVOpxAAAIQ6EbgH/7hH8ITTzxRvLGhN1g0C2+6QvSvyu/0008vsmkNPnbsAKz+cBq0acj/+T//p23XeM221hshmo2nN18uu+yy4q0V+Uj1C9WHfPWrX50m0/e5Zvepb6+3dWLYaqutijdm5OM1G7H18D+0HkQX/d2owxECEGgAgaEfosRACDSYwF//9V+XT95a0/6zM9JaHYqJb33rWxOtxeQ7aEz3DEDN7mu5uonW6wATrcGttvxbPwgnNt5447IMetrYGhybaHWyJlqvEU+0Bgbb9Fs/4iZag4elfnyy2Kb054t0lods0FPcb3/72x2qZ599dttslWOOOaa41lPN1mBah/7RRx9d5q+nm91mkLQG60rduXPnTrgZlq01tiZar+1ORE6aKfizn/2sI18JWp3CMj0xVZ23On9tuq3BxIlWZ7DQa71mXOprNiABAhBoHoHWAFibD3N+brKllp+Jf73SaL3aW+oqzj/90z91+PDWD9CJXXfdtdRrPViZaP1QtEnXnQHYGvwr02s9EJr4/ve/35GeZr201u8q9BZffPFSv5v/7kgEAQQgMDYEWoNkpZ9oPRBuK3c6S87NyGtT7vNCPin63Dpp//3f/32pr/7jscceO9FaoqYt19ZEgKJvHdPVWzQ535eWLTcDUH3zTTbZpMy39dDJ9ltPO+20om+b9kVlAwECEBhtAnyKR7v+sH6ECWhQL36Z68s3vprQb5GmewBQNu63335Zs1pPJstyxPJ0G6xq7XhZ6qsDkgvpAKAGFH/0ox/lVCdaCzyXacoGvY6rV8pyoTVDsdTXj14XLrnkklKnNetv4sEHH3RqpSztdLXWaynl8UQdOtVzZNSaPRNvdRw1KNiauVjqKk43ph0JIIAABEaGQGvWXflZX2+99Sa07MCgQvQ3OnYLrdnmE63ZJqUd73vf+7Lqsq+1XlSp25rBbHXrDAC2djwu05Gfb80St2lJKJ8snbRMuR/B2US4AQEINJ7AQw89NNFaR7TwFXp4W/WpaX+tziBdP8D6GQBsze5rW6qmtc5fNistcdNaP7D0fwcccIDVTcuWGwCcN29emU7rbZqJ1hrXNi0J0z579L1ZZW5AAAIjQYBNQFrejACB2SCgV0Vj0CsBrR828XKojtrs4qijjsrapMXrWz9ay/vaIKPbK7CvfOUri9cxFKG1zl3xekYZOXOiVx70WnEuvP71r2+7pdeqW4OLbbL0ItXXa8EupDvFtWYNFq8zO70o0+twrdmQxaVeQ64uki+ZXqFT0OL23Zj2ul8kwj8IQGDkCbRmWITvfOc7ZTm0GHtrNnF5PVMnZ555ZvkqmHz4Jz7xiWzWsk8L0sfQGugrlnOI1/0cTzrppFJdr7RpOYRc0Ctxqe/O6SGHAATGm8Bhhx0WWg9tCwhaOmA2fGqdGjjxxBODll5QaL0RFPTKci5oB2NtwBSDfLaWCZpMSP1ua83Xsu/q0nrjG98Y/uZv/sbdQgYBCIwoAQYAR7TiMHv0CWh9PK1jp6D1jeIuZcNWMv3o0g/CbmHzzTcvb++5557lAF8pTE40uKV19BRaj0nC7bffXpx3+9drrRPt8puGXvqpva2ntWnU4rz1Wm9ozTgszrXu4R577NGh4wTxx6vKVa1P/UiOQev7VdeBiffiUQOerY1U4iVHCECgYQTmz58fWhtblKXS4JZ2vJ2NoPVZY5Ad8tPdwjbbbFOsFRV1Uv8WZXWOaTytj9oraH1DAgQgAIEcgdas4tDaNK64LX8R+2U5/dmUp35XD5F7TQTQWttaj1VBa2+3NtPr23ytUajvnhjwu5EERwiMDwE2ARmfuqakQ0ZAM+u0EUZrDbugASctAtzaBaxY2FcbZ2hziGEI6WBZzh49mYxBi7f3CrEDI710JmQuXi8b0vyVRi8beuWvzUW0AYhCa72p2ovcxw1JFC/O9tO5gjYpiUEbvfQK6ghuu+224d/+7d96qXIfAhAYMQJ68KCHJa1X0wrLtVlRtw2Jprt4qX+qO9tDs7/j5iXaqKPfcPfdd5ezdBR3u+2265mEdOQb9ZCFAAEIQCAloH5b3FhPD1m7vWmRxpuNc/mwX/3qV2XWdfyu+qN6+PLDH/6wiCe/21pypkyjzon6t3HWoTYp6dVfVpp1+qx18kYHAhAYDgIMAA5HPWDFmBJobVgRtBPXTTfdVOysqKeW+mttTlF8KWv23d/93d8VO3XN1isMdXbp1Q67MfSrr12De4Veaab5K61+9F3+2tU3Br3Km+6kGeW9jo888kibSnwdRcL0lek2pcpFXb1KNC4hAIEhJqCdHOXX77vvvsLK5z3vecUPOs02zoXWhkG5W4Vcu6NPZTfe1D+11sTqmle82VqPKp6G1ppb5XndkzRP7e6rWfG9ghjJv2v3YQIEIACBlMDhhx9evlVSZ+mWNG71vLXmXjjiiCOq4rZrPZBorZHdJqt7odd30/7nbPhd7Tjfa9ahykNftG6togeB0SDwl1/to2EvVkKgUQRaO+IWU/GPPPLIoLVA7r///qJ8ejqnmRX6a+0wGzTD7QMf+EB4//vfH1q7hM0ogzqdg9SgfvXTuLnzftPsV7+a72TXVUnT0azONDz55JPlpX7s1gnLLrtsHTV0IACBESGgBwoa/LvlllsKi9daa63wn//5n0HHbqHXQ4jWZlBTGgBM/VNdv5Pq6bWyfkOaZ12fqDyULwOA/dJGHwLNJqDZcMcdd1xRSL32O9XlAvR2Si+/Kx822QHA1P/J6NSfdqupVG+m/G6aZzfbuAcBCIwGAQYAR6OesLLBBDSj4ZOf/GT42Mc+VgwGXnrppcX6ca3ddctZFZpN9qEPfSj8/Oc/D+eee26tJ3Y5ZHHqf+4+8vaOmF7N+3//7/9NGUtrh80yjdYuv+V5t5P4GnI3He5BAAKjQUA/KF/2speFa6+9tjBYM940+Lf++uvPegHkn+KDj7p+J9XTq2T9hsn4ROWR5ttvnuhDAALNJJC+2nrnnXd2XVIgnX2sGdnp8gMf/ehHw//9v/932iGl/k+Zya/VGWhL/d9M+d00z2kHQwYQgMC0E2AAcNoRkwEE6hHQzD6t+aa/973vfcUaHT/72c+CZgd+73vfKxL57ne/W+wYmW5yoTVBYqjOOovy9Bh/5KUyztsJpJuexNf02jX6v5ozZ04ZSZ3TOqG6jmCdOOhAAALDR0A/oLT5j5Z8UNBrrFrHadNNN61l7HSveSf/FL8b5J+0zlSvkG7gVOf13Wp6qU/UQxHNjuy1OZJmvEQ7q+lxDQEIQEAENMM6zrLuReT3v/99+MUvflGqxcFBLXEwnX5X3wHqv8fXgOV3V1999dKO3Mkg/e6CBQuKMvZ6a4a+aK42kENgNAmwC/Bo1htWjwEBrQP44he/OJx33nnFK2OxyHEwMF6n60bpB1SvEBdt76U3zvf/+q//OsQ1Fx944IFw8803TxnHFltsUaahmZy9gjqeaae0lz73IQCB4SSgjT722muvcmdwve56/vnnhy233HJoDE79kx481Qmp3ote9KI6Udp0tMt5OghYxy9KZzp/lLcZyAUEIACBaSKgQTf1NWNI/WmUVY96yJ9uNjcZv6u3WvT7QkGz0q+77rpqNh3Xk9ltuCMRBBCAwNAQYABwaKoCQyDgCaiToN0iY4jrBMbrdCH2dEexeD89anMLvVpM6E5g6aWXLnZljlpah3GqQWvSxHDBBRcELTDdLfzkJz8JejpLgAAERpeAZne86lWvCvo8K+jBgmZyawfdYQrahT4G7UwfdyeOsupx/vz5Qa/cxZD6tyirc0zjaQOsXuH000/vpcJ9CEBgDAm85S1vKR4O6AFBr79TTjmlJKTNN1J9pTNTIfW7p512Ws+HG5oQEB/0L7XUUpPanVevDW+11VZlEfG7JQpOIDA2BBgAHJuqpqDDRkCvMunVgzohnX5ffUVArwzHcNZZZ4Xf/e538bLjeNhhh5WvG3TcRNBG4IMf/GB5rYWltVZX3eBeG951112DdlxT0Otu2tQlF/Tj+73vfW/uNnIIQGAECPzhD38Ib3jDG4IG/BW0W/m3vvWt8Ld/+7dDZ73sjGtSaU2sj3/841kb9b116KGHlvc1iLfRRhuV1/2cHHjggaW62FxyySXldfXk8ssvD2eeeWZVzDUEIACBkSTw9re/vZyNp01M5s2bly2HNj5K+42vf/3ri6UkshG63Ej97he/+MVw4403ZrX1QIiJA1k83IDASBJgAHAkqw2jm0BAa0Fp9p42/8hNwdcPyG9+85vlzmYq92677dZW/D322CPEhYDvuOOOoC/2RYsWtelottn+++9f/PiMr7a2KXDRQUC7asZd5PTahRaF/sxnPhOqO7fFiBq009PZV7ziFcXrflEej1rjUZu9xHDyySeHd7/73R0zbTR4qBmf2nhkiSWWiOocIQCBESKgGSVve9vbwjnnnFNYrVeuNNNCrwIPY9BSElr8PobPfvazxXX1IZVmoMvHxdd1NagpvzjZoB2R4yxAMdt7773LAdM0zf/4j/8o2GkTq3Td21SHcwhAAAKjRGCDDTYIBx98cGnyO9/5zmLn4epmfVqGRg+Rb7vttkJX/vqII44o4/V7ot8D8aGNfi/ID7slZ77xjW+EAw44gL5ov4DRh8CQE3jWkNuHeRBoNIE400KzLdZcc81iPRAd9aNKP7Q0SKjXdmPYcccdw+te97p4WRy1npR+uMUng1//+teDfizpR5U6CZo9qFkVmnW2+eabF7tQHn300W1pcOEJnHDCCUF1JJ76IfzhD384fOpTnyo2allvvfWK1/n0VFaLTV9zzTXl7Mvc2l4aUNRsIM10UfjCF74Q9Eqb6kqL36uuLrrooiId7QyqH9rHHnusNw4pBCAwtASOP/74oFe6YtAPPc2iqDuT4ktf+lKMOmNHbT4l+77//e8XecrXqRzyTyuvvHKbf4pGaZOqdBZ6lPdz1MOQ7bffvvjO0473etii7yqtb6UlMK6++urydeP3vOc9xUZYethFgAAEIDDqBI466qigJRW0tp8eNmsQUA9gtAa4ZmWrf6k+vCYEKOj3gXymJhBMNmgigB5Iybdrg6q4a7I2f5LvVX9XD3ni+teaJfiP//iPk82OeBCAwJARYABwyCoEc8aHgNaZ0xd53LlXM7+0K2QuaOffr33ta+XrAqmeXhfVFP6TTjqpEGvjCs0cTMN2221XzEY58cQTUzHnXQiok6QBOw3QatBUg6j60yBdLmh2iljnggZoVfdxcEA/eP/t3/6tTX3jjTcO5557btCrFwQIQGD0CMgHp+Gmm24K+qsbZmMAULMU5Yu0VIQG/vSDU+tNxVmMqe3awVIPJwaxXpYedvz4xz8O++yzT8lID1T0lwa9Lqcfxt/5zndSMecQgAAERpaAHuJrjVjNGI8Ph7X+s+v/rbXWWsXgX/VNoMkUfuutty76t/vuu2+Iy9ZceeWVQX8x6DtBEwy05AMDgJEKRwiMPgEGAEe/DinBiBLQrAn9SNTacpp1oVkOetKnH1z64aXZe5o1osGk/fbbL+jJXC7oS1oDe/oBpTVENJVf6WhW2SabbFLEf9Ob3sSrUzmAXeR6dfcTn/hE0QHSbD3Vl17Zfuihh4r1FFVPWkT6BS94QfE0dffdd2/b2bKatAYITz311OKVbNWV1rVSO9AMmw033DC89rWvDW9961vL9biq8bmGAAQgMF0E9FBKa54ecsghxQMnDcxpZrLWrF1llVXC3Llzg3ycBuP0/TKosNlmmxWz/OQT9fDqhhtuKB626AevfqhqaQu9pkaAAAQg0DQCmuknv6dlYTQz76c//Wnx9o9ez11ttdWKWXla7kd9w2WXXXZgxX/JS14Srr/++uK1Yz380W8QbVz17Gc/O+ieXk/u9ttjYIaQEAQgMKMEntFac2ViRnMkMwhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQGDGCLAJyIyhJiMIQAACEIAABCAAAQhAAAIQgAAEIAABCMw8AQYAZ545OUIAAhCAAAQgAAEIQAACEIAABCAAAQhAYMYIMAA4Y6jJCAIQgAAEIAABCEAAAhCAAAQgAAEIQAACM0+AAcCZZ06OEIAABCAAAQhAAAIQgAAEIAABCEAAAhCYMQIMAM4YajKCAAQgAAEIQAACEIAABCAAAQhAAAIQgMDME2AAcOaZD12Od9xxR3jve98bNt5442J7+VVWWSVsvfXW4cgjjwxPP/300NmLQRCAAARGnQB+d9RrEPshAIFRI4DfHbUaw14IQAACEBg0gWdMtMKgEyW90SHw/e9/P+y3337h8ccft0bPnTs3nH/++WHDDTe09xFCAAIQgEB/BPC7/fFCGwIQgMBUCeB3p0qQ+BCAAAQg0AQCDAA2oRYnWYarr7467LDDDmHRokVhueWWCx/60IfCLrvsUlyfffbZ4cQTTyxS1iDg/Pnzw/LLLz/JnIgGAQhAAAIigN+lHUAAAhCYWQL43ZnlTW4QgAAEIDC8BJ75sVYYXvOwbDoJ7LvvvuGWW24Jz3rWs8JPfvKT8IY3vCGsu+66Yf311w977rln8Trwj370o7Bw4cKwxBJLhJ133nk6zSFtCEAAAo0ngN9tfBVTQAhAYMgI4HeHrEIwBwIQgAAEZo0AMwBnDf3sZnzllVeGbbfdtjDi4IMPDl/96lc7DPrjH/8YNt9883D99deHlVZaKTzwwANh8cUX79BDAAEIQAACvQngd3szQgMCEIDAIAngdwdJk7QgAAEIQGDUCbAJyKjX4CTtP++888qYBxxwQHmeniy22GJh//33L0SPPvpouOiii9LbnEMAAhCAQB8E8Lt9wEIVAhCAwAAI4HcHAJEkIAABCECgMQQYAGxMVfZXkMsuu6yIsOyyy4Ytt9wyG3mnnXYq711++eXlOScQgAAEINAfAfxuf7zQhgAEIDBVAvjdqRIkPgQgAAEINIkAA4BNqs0+yqLXehW0u6/WAMyFjTfeuLwV45QCTiAAAQhAoDaB6EPxu7WRoQgBCEBgSgTwu1PCR2QIQAACEGgYgfzIT8MKSnH+QuC3v/1teOihhwrBOuus85cb5mzllVcuNgN56qmnwl133WU0vGjBggX+xp+lsuGGG24Ia6yxRpgzZ07XQciuCXETAhBoPIH//d//DQ8++GBRzhe84AVhqaWWsmWW3n333Wfv1RWuueaa0+KP8Lt1awA9CEBgGAjgd+vVAv3depzQggAE6hGYKd87Xf3deqVEazYJMAA4m/RnKe8nnniizHm55ZYrz3Mnek1YA4BPPvlkTqVDrt2ECRCAAAQGTUALum+99dY2WQ3+TdX36EFHrwcjNvMeQvxuD0DchgAEhpYAfjdfNVP9zsmnzB0IQGDcCUyn752u/u6419kolJ9XgEehlgZso2aixLDEEkvE0+xxySWXLO4tWrQoq8MNCEAAAhDIE8Dv5tlwBwIQgMB0EMDvTgdV0oQABCAAgVEmwAzAUa69Sdqevj73+9//vmcqv/vd7wqdpZdeuqduVOj1urDu/83f/E2hro1GUpseeOCBmEzb0a1V6GRtkZKLOJCZiNryTeXpbJ0oj68gxmsd//CHP6SX5bmzK8faDaymndYy0czJM5/5zI47iy++eIfM2SQlZ5eTSXdiYkKHtuBmkTqZIjlb3SD0M57xjLY84kVsi/FaRyeT3NnquLj8Fd/Z6upKuo899pgObUE7Z1fDdNRrNY94nWubf/zjH6NKeXSsyps1Tlx9OX5KyrVDF1+6US6bn376aYmKJQOKkx7/rrjiitoz+fQK1/bbb98jxandTn1c7vOV5hDb9XT53Ze//OUhTfvXv/51mn157tqR86VlhMqJXmWpG2KZU333mcv5lxVWWCGNWpw7+3XDfWYffvjhjvg5+53fSOu4I6GK4PHHH69IQvif//mfDpkELt3NNtusQ/eFL3xhh0wCV19p3cdIzjfo3p133hlVymPutUfHdbHF6j9rdm8auHYhQ1zbcJ+tHNep+r0SxhicaKmWOgG/20kp7e++5z3vCSuuuGKp5Pokuul8mWvb0nV9U/dZzn0O77jjDiXTFm699da2a13kfKErQ87WuPxQmng/fteVwfmy1VZbLc2iPHffB86PKILLS29EVYPzr9Jxcidz+Si+4+J+m0hXb2lVgyvrSiutVFUrrp0853dde3O25vyuNWBIhbEPmprnZLk6dP3dnG6arj6/sV0O2vfORH835cX5cBJgAHA462VarVp++eXL9F1nu7z555P4xZL70VXV13U/r9Dpx036Be6+IJWmc6Su4yFdF9yPKCdTXPfF5fLKOXJna+7Hhuso5QZPXLmcrpM5m5Se6yTkyuXK4NJ1rJSX03X1nX4RKl4MLn/X0ZW+03V2uR/yiu8Y5jrATjdXBqVdJ7j4/dSLi698c/I6NuV0XJpOpviuDDldJ3dtyNm19tprB/3VCa6t1InXj86w+V353GWWWaYsgvts6Karg5xumVhy4uInt9tOnS9yn61cG3CfZZemMnVp9NM2na6zta2AyUU/XJyu85tpG0uysj9E3Q/ZHKu0ncR0Xf6659pGP1xcveT8rqsDx8rJZOtMfO6VzyCCK8N02R/zStN39eLKhd91VP4i0+BfOtjifJa0U50YOzcg4/qr7rPsPi9K2/XtXd/Y5aP4rgyxDel+Glw7cnY5mdJxcudfnE2K73xJrlwuL5eukykv5yMdV2e/4rt0nX+Vbi4N3UtDLr6zNf38p2m4vHL1ncYbxXNXrroylde1ISeTrktXcveZkbwa6vreXL1W0+O62QTqP5ZtNoexKp2+gFZdddWizLmn+BHII488Uj5ZYp2TSIUjBCAw7ATUyennb7rLg9+dbsKkDwEIzDaBfnzuTPwQxe/OdosgfwhAYCYI9ON7Z8Ie8hhuAgwADnf9TJt1m266aZH2zTffbJ+IxYy1U28Mm2yySTzlCAEIQGCoCfTTGZqJH6KChd8d6iaDcRCAwBQJ4HenCJDoEIAABCZBoB/fO4nkidIwArwC3LAKrVucF7/4xeHSSy8tZvf98pe/DNtuu62NevHFF5fyHXbYoTwf5Mm9997bNtXdrZ2m/Nx0eCeTrpvS76ZRu2nviu9ey3VrG8U1GhSnV+jn9Q03FdzZrzzdlH5XfjdtX/Hd4EfutVrpV4PLK67XVtV1r6X0U1Y3dd7VlfJ15arao+sc1/S19Bivn7xcuWI61aPTdW3b6SktV1bHqppvvHb1Eu9Vj84Gl5eTKS1XLieTbmyzsq/OcgWKE0PsDMXrbkfHr5v+ZO8Nk9+96aab2urCrc2UK2e6hlWq49qRk+X8i2sz7pWthQsXptmW585HO/+kCM5HObtiGywz6XLi0sy1Lccll7Qrg1uXLxff5eW+N3KvELv4uc+jW+fUMXSvwsl+J3dtQLrOFzl/7uxXfFc3TibdqQZnq0szl39O7tKYqmwqeSlu3fh19aZanmHyu3qonr5+73yeyrvKKqt0FDvXh7zvvvs6dN1nJvc969aVc98Hub65+3w5PyAjc2WoFiDHxbUZ53fdOnXKI9fnr+ava+cj3efYsVZ8t85rzm9KvxpcueKSTFVdx9uxcnpKy/nNah7x2pXXfXdG/VE+Oob9lMdxzbXBtL3pM5Wr61z+srWOvXV0cnkgbw4BZgA2py77Ksnee+9d6p9yyinleXoih3766acXIq1Hsssuu6S3OYcABCAwtARiZ6jucSYKgt+dCcrkAQEIzBaBuv426s2EnfjdmaBMHhCAwGwSiD61znE27STv4SDAAOBw1MOMW7HNNtuEHXfcscj35JNPDtq5rRqOPvrocP311xfid73rXfZpWDUO1xCAAASGgUCdTlCqMxM243dngjJ5QAACs0Ug9al1zmfCTvzuTFAmDwhAYDYJ1PG3UWc27STv4SDAK8DDUQ+zYsUXvvCFoNd69RrrrrvuGj784Q8Xs/x0ffbZZ4d58+YVds2dOze8973vnRUbyRQCEIDAZAj009GR7kwF/O5MkSYfCEBgpgngd2eaOPlBAAIQ+NOSFnX6snV04Nl8AgwANr+OsyXcYostwje/+c2w3377FWtVaACwGjT4d/7554fc2kBVfa4hAAEIDAOBYf0hit8dhtaBDRCAwHQQwO9OB1XShAAEINCdQF3fywBgd47jcpdXgMelpjPl3HPPPcOvf/3rcNhhhwUN9i2zzDJB6/1ttdVW4XOf+1y4+uqrw4YbbpiJjRgCEIDAcBKInaG6x5ksBX53JmmTFwQgMFME6vrbqDdTdikf/O5M0iYvCEBgJglEn1rnOJN2kddwEmAG4HDWy4xa9ZznPCd8/vOfL/5mNOM/Z6ZdwdIdpHK7VLndw+ToXHC7krkd0NwOTUrPxXc7MjmbnD2SuZ2zJHdlcHY5PcV3O0RKXg25/FP21TjVa7ebo2OQ2y03J6/mk7t2O8O5XdkUP91RK6bnuObK73jldnBzbdbVl+Mn21y5nMy1y1i26jHHJSevxs9dO7vqypSmy9/t/Cnd+Jmt28YVJw2uDtL7s3k+2363ytS1d/Fxbc7ttitdx9u1Daen+C44/1K1PcZzn29nv/Rzn/uYVjy69qp7uXRjvHjsp6wxTvXobHW+6J577qlGLa6d33X1kvNPzpe6elFmjks/O6q7sjr7c3k53rlyubp19jubCrDmn+MqNWeDS9flb7IZapGrg2ExeLb9rj6j6feda4Ni5T7LuV14nS+I350p9zTfVO4+y24HW7dbsNJx3x25z6xr8+4z4z4vqc3puWPoyqQ4rm06/5amn567755cXk7u8nf8lKfLqx/dfri4HYcffvjhtOjluWtv/fgtZ5fjUmY4ZCfOfifLmZ3bBTj9fObqOZdmlI8Sx2gzx9khwADg7HAnVwhAAAIQmEYC6gjV7QzV1ZtGc0kaAhCAwMgTwO+OfBVSAAhAYAQJ1PW99HdHsHKnwWQGAKcBKklCAAIQgMDsEqjbGZKVdIhmt67IHQIQaAYB/G4z6pFSQAACo0Wgru+lvzta9Tpd1jIAOF1kSRcCEIAABGaNQN3OkAykQzRr1UTGEIBAgwjgdxtUmRQFAhAYGQJ1fS/93ZGp0mk1lAHAacVL4hCAAAQgMBsE6naGZBsdotmoIfKEAASaRgC/27QapTwQgMAoEKjre+nvjkJtTr+NDABOP2Ny6JNAbvFgtyhqzpG5BVndIrW5hYZdXk7mFjRWcZ1dTiZdtwCyW8w+F9/JnawfWx0/2eqC4+Lyd3H7lTm7nCyXbt1FmRXfLYrsFsaWrtsEpB8urm6czLVh5e+Ca1dOr1+Z4+3q28mUlytXzob4OcillYsnueLUjVdXr1t+o3ZPC1GnC8W7elWZXDvO1aFrc042XX43Z5erG2eXk8U2WE3DlcHln/s+c7ydTPm69unSzW0S4OyqlkfX/ZTVLVCvNJytTiZdF5yPc75YcZ0/d/Fz+efkzq66MteGFNfJna118xlWPTGty7Wu3rCWdTJ2LVy4sM3v5tq2+3y79p6zId1QIOo4me65z7KTue8CxXe29tO2XTvI+SznI/uJ7+zK+T2nu2jRIhW5LeS45MrQFrl1kYvv8ncypecYOFa5vNyGH7nNvlx9V8uka5d/N3k1DVemqk6va2dDP+m6+HVlss3llavD9DvC5dGrrMrL5VeNV0enGofr5hFgALB5dUqJIAABCIw9gbqdIYGiQzT2zQUAEIDAAAjgdwcAkSQgAAEI9Emgru+lv9sn2IaqL9bQclEsCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAoEWAGYA0AwhAAAIQaByBuk9DVXCeiDau+ikQBCAwCwTwu7MAnSwhAIGxJ1DX99LfHfumUgBgAJB2AAEIQAACjSNQtzOkgtMhalz1UyAIQGAWCOB3ZwE6WUIAAmNPoK7vpb879k2lAMAAIO0AAhCAAAQaSYCOTiOrlUJBAAJDTAC/O8SVg2kQgEBjCeB7G1u1Ay8YA4ADR0qC/RJ44okn2nYfdDuqKk23o5bbiVG66W5KulZwu1+5NKXrbHC7ouV2c3I7ODmblNfiiy+uQ1twspytzi6n62RtmSYXzn7ddmk4Wa6srr5yeSXmdD3NxXdfhG4XPaenDB3Xp556ytri2oFjkMvLJep0HWsXd9RkjtVUyyB+jqFLt66eizuqMu36l+5+6D4bKptrc/3wcp9Pl6bycp8599lyaSq+C87nSE+7IFdDyiPey7VNx8B9xzg9pZ2Tx3zTo9N1OzHmuNbl5VjLDsfQlVW6Tu7SdWnm4ruy5nQdK+nOVMjVgct/tm11NkkW28tk7FOcuvHq6uXsHEX5ggUL2vqnrq+pcjk2uc+M6y+6z5xLU3m5nYidzPlnxXdtPrYh3U+D86dO18mUjiuD03XlV3zHSnIXnC9z+efSdN8xjpXLR/Y4ea5czkc6XcdfeT355JM6tIVc22xT+vPFEkss0SF2rKTk5I6Lk+XiuzYg3Zxc9+oEF98xdDKl78rq6kq66Q7Tru6l0y0oL5dfNU4dnWocrptHgAHA5tUpJYIABCAw9gTqdoYEig7R2DcXAEAAAgMggN8dAESSgAAEINAngbq+l/5un2Abqs4AYEMrlmJBAAIQGGcCdTtDYkSHaJxbCmWHAAQGRQC/OyiSpAMBCECgPoG6vpf+bn2mTdZkALDJtUvZIAABCIwpgbqdIeGhQzSmjYRiQwACAyWA3x0oThKDAAQgUItAXd9Lf7cWzsYrMQDY+CqmgBCAAATGj0DdzpDI0CEav/ZBiSEAgcETwO8OnikpQgACEOhFoK7vpb/bi+R43GcAcDzqeahLqU1A0gVUcwu/usVYnUyFdQuougWMc47QLZ7rdHP5p+WJ8PtZKNgtqBvTqR6dXU7myqS0nG6uXHV1+1ms2rHKxXd2uXpVuVw7cu3ClUnx3aYILr50nV25Mki/GpytTlaNF69dGfqJH9Opc3TtyNWhs0npO7sca+lGrjnu0skF5Z+zoRqnrl413ihfP/jggyVflSPHONZBWlZX37k0cumm6cVz1zZc/rnPlpPnfOkyyywTsy2PbtH28mblJF2wO96qa7/0nW4/7dB9DnPxHcNoc3p0m6DkbM3Vq7PLldXVVS4vl6Z0c+XVvdkKOZscA2djrq6cvG6aysfFdzLpxs+3ypJjLz0XFCfHoKpfV68ab5SvH3vsMVsX1TLlPotVPV27OnLfqc5nKb7blMClmasv91mObUjpp8HJc+0wjRfPnV3xXnrM6eX6i2nceO7ScP14V/6YRvXoyp/73nHyXB04W52Pdnqy0W0CkvMvrm0utdRS1aLaTb2k5OzKlasj0ZbAtRcnU9yc3KXrZK6+nMzFlcwxzG2uknJx8XJ5RLkY1uFYRyemybG5BBgAbG7dUjIIQAACY0ugbmdIgOgQjW0zoeAQgMAACeB3BwiTpCAAAQjUJFDX99LfrQm04WoMADa8gikeBCAAgXEkULczJDZ0iMaxhVBmCEBg0ATwu4MmSnoQgAAEehOo63vp7/ZmOQ4aDACOQy1TRghAAAJjSICOzhhWOkWGAARmlQB+d1bxkzkEIDCmBPC9Y1rxkyj2YpOIQxQIQAACEIDAUBNQR6ifv6EuDMZBAAIQGAEC/fhcfqyOQIViIgQgMBIE+vG901mgBx54IPzgBz8IRxxxRNhtt93CaqutVqzFqPUY3/KWt/Sd9YUXXhj22WefsM466wSti6mjriWvG7S+4le/+tWw4447hjlz5oSll146bLDBBuHggw8O1157bd1kwkMPPVSU64UvfGFYYYUVij+dq6wLFy6snc4111xT5C0bZItskm2yMV0LsleCU2HDDMBedLk/7QS0KG3aEUzP08z7WXjVLfzqFlV1MuWZk6f26NzlU9Xpde3K5RbZzS007Bb1dQydnmzLyZ3dLl1nl1sQWOnJ0VWDi++YKJ6rl5z9Tread7drZ1euvp3csXJ6ORuc/S5Nxc/JXdqObT92uTSdrU5PMldfbsFy6cZyuTi63y0obozfTU/36ur1SmeU7ot5Wu+uXeTKk+OVphfjOl2nJ333mXN2OT3Fdxt+uM0+pLvsssvq0BZc/Fzbc500t5h+rqyOS5sxPS5c/Nzn0NngZC5NmeHkOS5O18lyxXPffbly5dIYtNyxGkQeLl0ny+XlPhv96DrWih83OhD3p556Kpeklauu69Z3XT2b0YgKq3xyvszJc23DfT7c59P5LGF0uq5unE2K7+S5tlW3zboyKS9nl+TVkNNzm4A4+5We03X2u+8NxXe6zi7HPxffpSnd3Pec7qXBlSm9n56777P0fnruypWz1emmafU6d5+DXF5O3k/+Lr7LP2eza8dOpvjp57MfG2PeilMnXh2dmOZkjmusscZkonXEEaeDDjoonHzyyW337r777qC/8847Lxx44IHhhBNOsJ+1GEmDdrvvvnu46qqroqg43nrrrWHevHnhtNNOC1/60peKtNoUKhe/+MUvwt577x3uu+++tju/+c1vgv5OOumkwqZtttmm7X714sQTTwzvfOc72zZf0sYwl112WfF3yimnhPPPP78YOK3GjdeDYMMMwEiTIwQgAAEINIZA7AzVPTam4BQEAhCAwCwRqOtvo94smUm2EIAABBpFIPrUOseZKvh6660Xdt1110lld/jhh5eDf1tssUU466yzwpVXXlkcda2gQbePfOQj2fQ1uK7ZgnHw75WvfGUxc1CDeV/84hfD6quvHvQwXDMBu80ovOuuu8Kee+5ZDP7p4cYHPvCBcMkllxR/Opfs3nvvLXQWLFiQteeCCy4IhxxySDH4p4FS2SBblLdsU1AZZXPuwYB0BsGGGYAiSYAABCAAgUYRiJ2gOoWSLgECEIAABKZGAL87NX7EhgAEIDAZAnV973T3d/U67NZbb138aZDr9ttvD+uvv35fRbrxxhvDUUcdVcTZaqutioG2+AaZ0t5rr73CTjvtFObPnx+OPPLI8Na3vjVsuOGGHXlodp9m1in8wz/8Q/jyl79c6mimnl5R3nLLLcPjjz8e/vEf/zFcf/31xWBeqfTnEw24Pfjgg8XVmWeeGV7zmteUKnp1V2nsu+++Qa8/a0Dy1FNPLe/HE82+PfTQQ4s32fT68OWXX168hhzvv/zlLw/veMc7wle+8pXC5jPOOMO+Mj0oNswAjOQ5QgACEIBAYwjEzlDdY2MKTkEgAAEIzBKBuv426s2SmWQLAQhAoFEEok+tc5zOgn/84x8Pe+yxR5jKq8DHHnts+Ur0cccd17F8lF55l1xBr04fc8wxtkhxEHGVVVYpBgqrSho0/NCHPlSIb7755nDuuedWVYpZf9/4xjcK+cte9rK2wb+o/NrXvjbonoIG7qqvCUuutPXasYLy1Pp/1aDBzJVXXrkQ69yFQbFhANDRRQYBCEAAAiNNoE4nKNUZ6cJiPAQgAIEhIJD61DrnQ2AyJkAAAhAYeQJ1/G3UGebCysbvfve7hYkbb7xx2G677ay5km+00UbFPekrXho0U04z+hQ0QJdbJzPdmMQNAH7ve98r158/4IAD0izazmM6Wp9PcapBaxbGEHXjdTzKRtmqcN111wWVIQ2DYqM0GQBMyXIOAQhAAAKNIBA7OnWPjSg0hYAABCAwiwTq+tuoN4umkjUEIACBxhCIPrXOcZgLfdttt4V77rmnMFGv+XYL8b42BdGrxmmIr/5KFvXS+/F8zTXXDHPnzi0u9VpuNdRNJ82jWzoatFSeudAtnUGxUd6sAZirAeQzRiA6q5hhbuHLdIekqJs71t2lSXlPJeTyycldXnV35crtVObK4GQu75ysH/vdbm+5XdG0hXs1uPhVnXitnZKqIdde3E5brlw5rnG9iTS/uDtiKtN5XbvcjmKK7+rL2S/duiGXlyuv4+JkubydrU6m+K69u/JLN37mc2lJJxeUZi7dapy6etV4TbrOMXbtIMfLtTknwMK4zwAAQABJREFUc2mKpdN1/sF9NhXf7T7ej65jkNuh2vmd2F5lSwxOL96bzaOrAyeTjVMtg0vX1avycnXo2oV0n376aR3agmubLn9FysnbEuyi109e1TRz1zmbnNy1V6envJzfd9/H0o11oHpnF2ARmb6Q+2w5v5OrWyd3bdPJVLKcfCqlzqXp2qzTzXGpW1aXT648Of/i0nCyXLpOt5/vCFfWnN90ebn+qvMDst/ZtWjRIls05xNcv85GbgldfTtZLr6T5+rQ8eonrxyvqg25NB3XXNtO08yll+pUzxWnTrw6OtW0Z/JaM99i0AzAbiG9r9l+6VqD/aaj2Xba7EPte9llly2zjemsuOKKXQfu1lprraC1/bSeYJx5GBN58skni7R1ndoc76fH9H41nWjLZNJJ2Sg+A4Apdc4hAAEIQAACEIAABCAAAQhAAAIQgEBDCWjn2l5hnXXW6aUy0PvpLrq98l533XXLvDV4l4bJpKPBUcWLrxYrvZhOL1ukK3uuvfbacrBPMoWYhs57pTPoMinPKhvJGAAUBQIEIAABCDSOwLA/6WwccAoEAQiMPQH87tg3AQBAAAKzQKBf36udcHuFftPslV6v+0888USpstxyy5Xn7iSdqadZdmkYdDq9bFHe0Z7ptkV59bIn2iLdqj2SMQAoCgQIQAACEGgUAXVa6nZc6uo1ChCFgQAEIDBgAvjdAQMlOQhAAAI1CNT1vcPe302XVMotJxVxpMtYVF9ZH3Q6vWyRTdGe6bZFefWyJ9oi3ao9kjEAKAoECEAAAhBoFIG6nSEVetg7RI2qGAoDAQg0lgB+t7FVS8EgAIEhJlDX96b93SuvvDJo7bphCnENWtn0+9//vqtp6Vqp1fWeq+mk19VEe6Wj9YZ72aI0Yzq9bKnmn17HNCSbrnSUNgOAokCYVQJavDZ1SG4xWxmY6kSDnSzeG/TRLQbrZMrXyd2CvtJ1ZXCOJhdfaVSDW2Q2Fz99ShDTcfbrnkvX6boyKb5bENfp5mxNHaPSU3Bp5uRuoeCqgy0Sbf3Tgq/V4MoqnYULF1ZVa31ZxEhuAWUnc6xiGtVjjqFj4MrlZMrDyV27cHWl+E6312e+n3IrDwXFqRuvrt6fUh7s/w9+8IPhX//1X8tEL7roorDzzjuX1+7kwgsvDPPmzQtXXXVVePDBB8OcOXPC1ltvHQ466KCw2267uSgdMrWDtI3kGOTkHQm2BK4eXfw03zQd1zadf8p15Jxu7impy8t95nL+xfloJ3NMVGbHwNkkXcdQ8mpwaUrHpetkuXxyZajmr2vnH1wdLL/88i66fa3F1Ysi33fffR1pOP/ibFJEx8AxzJXf5ZVj6NLtML4lqKuXs9+lmdPNcYmfr1zbz+UhucqfY1CNV1evGm/Ur9M6zjFwcicTizS9bmxy8Z3cpelkufxcmjnd3OfL6bt0Xfycra6/l74ql+bpZs2k9+N5rq/jbI1x0mNdPcXJfSbdd4/zu7nXBt13Z85HpzOrYjmcXc6/St+V18li2nWOufp2Nji/52TK1zF07c0xUXz33ZWzNZWLh8tHaeaC4tThmOpo8K/XmnS5/KZLnrY79+pqmm+6IU21bVfTid9rafx43isdDQD2skVpxXR62RLzdceYhu5NVzpKmwFAUSBAAAIQgECjCNTtDKnQaYdoJiH86le/Cp///OdrZ6kOoQb5Tj755LY4d999d9DfeeedFw488MBwwgkn2MGNtkhcQAACEBgwgVHwuwMuMslBAAIQmHUCdX3vbPV36wJKByTTzTNc/HRzi3TzDOlW01lttdVcEoUspqNB2DReTOf+++9v28gjl1BMp2rL2muvXUYZZJnKRM1JtEW3qvZItpj+ESAAAQhAAAJNIhA7Q3WPM132OJinJ+err756rewPP/zwcvBviy22CGeddVbQKxw66lrhpJNOCh/5yEdqpYcSBCAAgUESqOtvo94g8yYtCEAAAuNKIPrUOsdhZrTpppuW5t1www3luTtJ72+yySZtKpNJRwNl1RnBMZ3HHnvMvnUQM9WOyo8//nhxWbVFsxHjIFxqc4ybHtP71XSiLdJP9dL48Ty9X01HOgwARlIcIQABCECgMQTqdIJSnZku+Be/+MXiFd6NN944vO1tb+uZ/Y033hiOOuqoQm+rrbYKl19+eXjd615XvPqr42WXXRYkVzjyyCPDzTffXJzzDwIQgMBMEUh9ap3zmbKLfCAAAQg0mUAdfxt1hpnD+uuvH5797GcXJl588cVdTb3kkkuK+5ph99znPrdN98UvfnF53S0dLSWi/rXCDjvsUMaJJ3XTSfPols5///d/dx1I7JbOoNiobAwAxhrmCAEIQAACjSEQOzp1jzNZ8DvvvDN89KMfLbL86le/ateZqdpz7LHHluv/HHfccR2LAy+zzDJBcgXNKjzmmGOqSXANAQhAYFoJ1PW3UW9ajSFxCEAAAmNCIPrUOsdhRqLXcF/xilcUJmoW289//nNrruRxlpv00zUUFWHu3Lkhznz71re+FbSOnwunnnpqKd5nn33K83iy1157lUvqnHLKKVHccYzpaN1JxamGvffeuxRF3VLw5xPZKFsVNNtPZUjDoNgoTdYATMlyPisE1KDThVoXX3xxa4ecWjW4hWel43Tdgt1VhxHTT+2JMmeX08vlH9OpHp0NztbcgrBu8Vonc4vZypZ+yuUWGnYMcvXiyuXqyjGRrW6hXbfIrnRduq6sK6ywgtQ7glsvoroga0ekRPDEE08kV386dfx0x/Fy9jtZRyaTELg6fNaz/NdDTl7NNleHLi8nU3qxHefSquaZXotVXV519dL0p3L+jne8o1hQ+M1vfnPYaaedgjb+6BZk33e/+91CRTMGt9tuO6su+UYbbRT0hFH6X/rSl9o6RbfeemsZT/6gDlf3mXUyJew4OlkuX6cb20BpeJcT5yPdZ0tJOBucL3EyxXdyl3+ubTt5zkc7Lq4OXP6ytW58p6f4Ll3HT7rOP7iF96vr7CiuQrpw958k+Z0AXYe+7sL9StsxdPWa4+IYuHpVXk7XyXJ5KY1q6EfX5eVkyiO+AuVYVG2oXsumunbV1avmMcrX+nyk3HPtpR82Ttd9Zp1ejmVqY04nyl1e8V716Py5syuXptN1tua4Ov9UtTFe19V1NikN9/lx5XIyxc+lq3vV4Bi4/mZuIwS3Ccgqq6xSzaa4dpshOJnzr0qgn3JZA4ywnzTd96weoLrg2kA/ZXXt0MmUd1qHKk+u7+LslExx6nCoo5PLY6bk7373u4uN7tSGDj300KCZfmk/Qt/zkiuojqTvwvve977iDZuHH344fOADHyj6xKneLbfcEj7zmc8Uog033DC4AcA111wzvPGNbwxnnHFG+Pd///dwzjnnhFe/+tVpMuHb3/52cU/CN73pTUFxqkFpP+95zwvqhyvP17zmNWGDDTZoU3v/+98fHnnkkUKmcxcGxcb/wnM5IoMABCAAAQiMEIFh7Ojo6d4PfvCDoM51fKW3F9Lbbrst3HPPPYWaBgy7Bd3XAKA2Bbn99tuDXhmIQesFEiAAAQhMJ4Fh9LvTWV7ShgAEIDAMBIbB92o5mnQJmoceeqhEI3l19ttb3vKW8n480cw3DYB99rOfDfPnzy9ezf3gBz9YDJhp0O5zn/tcuPrqqwt16T3/+c+PUduOesj+ta99rVgy58tf/nLx6u3b3/72sPLKKxfrZ3/yk58s1u3ToKyW5XEDvkrwX/7lX8IPf/jD8OCDD4bXv/71hU177LFHkZf680cffXRxPmfOnPCpT32qOK/+0wQUvaWz5557FnnqNWGt173NNtsUg34nnnhi+M53vlNE02vHGkh0YVBsGAB0dJFBAAIQgMBIE1BHqG5nqK7eVIE8+uij4V3veleRjDowbpapy+O6664rxZoB2C2k96+//vq2AcCbbrqpW1TuQQACEJgSgWH0u1MqEJEhAAEIjACBur53uvu72ojutNNOs8S0drX+0uAGAHVfg24PPPBAMYCnwT6tdV0NWj87N+AmXc04Pu+888Luu+9erLmtAbY4yBbT0uxXvS2z2267RVHHURt4fP/73w96jVdrBqr/rr80aNaf8sq93SBd2aFlf975zncG7SwcZzGm6WhA8Nxzzy3fgErvxfNBsGENwEiTIwQgAAEINIZA7AzVPcaCayevBQsWdP2Luv0e9QqCOg968ldn44+YvuyJoVvnQjpxpzGd33XXXTqUQWUjQAACEJguAnX9bdSbLjuU7s4771y8VqdX6+r+/fSnP20zSbNV6satzmxpS4gLCEAAAtNIIPrUOsdpNGNgSWtW3sknnxzOP//8Yk1AbQyi17d11Jp/F1xwQdBgY+6V6miIHrT/7Gc/C1/5yleCZtatuuqqQa/C63VczQb85S9/GQ488MConj1uu+224Te/+U0xa2/zzTcPWhJKfy94wQsK2TXXXBOk0yvEPHWUDbJFNsm2448/vhgg7TU5YBBsmAHYq6a4DwEIQAACI0cgdoLqGC7dGPT0rVdI9XvpxvuXXnpp0VnRKwZ6Apiu9xJ1csd0Pcle61DG9buUVnWtmup1Lj/kEIAABCZDYLJ+dzJ5DTqOflTlXiUbdF6kBwEIQGCQBOr63sn0X/uxUw9CBvkwRLPm9DeVoH733//93xd/U0lHA3N6bVh/UwkaQJw3b95UkijiToUNA4BTxk8CEIAABCAwbATqdoZk93R3iLQY90EHHVTkc9hhhwV9+fcT0s1v3ALWaVrpYt7VDRF+97vfpaqcQwACEBgogWHyu9qx8amnnupaPi2vsO+++xY6L33pS8Paa6+d1dcC8Jp9kgu9Zmfn4iGHAAQgMFUCdX3vdPd3p1oO4s8MAQYAZ4YzuXQhoIUx0ym8uV2q3I5SuV2ScvIuZrTdcrNznF2p3WkCztZ+dvrqJ76zwe20lg4MpLa6nXFdfMVxuq5cbvcxxXe7orm6yn1BOS5Oprxced2uZquvvrrUO8JKK63UIXOspZTuTtURKRG48uu2K6/j4lgnybedujYsBZeGy6stseSibvxcvTi7XJrKMnKJx8SMnqeKUzdeqqeNMtZaa62e6fej8OlPfzrccMMNYb311gv//M//3E/UQjf1PbnPVkw0HeSrtsv0M1H1uzF+9ejqJle3rh05WTWPeO3ahvM5Tk9pOFtzvJyuGyxwO80qr3RQVtcKaTv6k+QvO1nH63hM6yLK0tmbUaaj03Vc05miafzqQLDuuTp09kvXyXO+0H13uJ19c2V1djnWssst2F1t8zk9yV19O66u/IqfY6B7dUKuHdeJKx0XP2er083lEz8b8ZjTc3Lln7Ohql9Xrxqv7nW6AVIujnZ2jGH//fePp/aoxdef+9zn2nt1hXqAk7Yb116VlvNbrm1K13F0n6NcfTrdftqLbKiGXF5VPV27/J1Muq6sTpaz39mV4+r8blp3skfBpZmT91OvLt1cuZwvdDvb5t4gcPFzbww43u572rESF8fbyVz5Fd8FZ5P0HG8XP8fVlcH1CZz9Lh/JcramNuR0cmnGdOvEq6PTLR/uNYMAA4DNqEdKAQEIQAACCQF1cup2dFI9Df4NciaHBv4+85nPFJZpB7DcwEdiesdpOoCS65THSOmgRrWzX72OcThCAAIQGASByfrdQeTdbxoaYPjGN75RRJNvfOUrX9lvErX0cw/+akVGCQIQgEANAnV9b9rfrZEsKg0lwABgQyuWYkEAAhAYZwJ1O0NiNJ0domOOOaZ4Cq3FfvXk+Oyzz+6oFi0eHMNPfvKTYqMQXe+5557FgGE6IJluCBLjpMd04490QxDpDHpmY5ov5xCAAASGxe/WqYkf//jH4e677y5UX/3qVwc3Y6pOOr10tAA9AQIQgMB0Eqjre6ezvzud5SPtwRJgAHCwPEkNAhCAAASGgEDdzpBMnc4OUXwl99Zbbw2vf/3re5JJFxe+7bbbigHATTfdtIynGYXdQnp/k002aVNlgfs2HFxAAAIDJjAsfrdOsU4//fRSrdfrv6XiJE6uuuqqScQiCgQgAIH6BOr63uns79a3Fs3ZJrDYbBtA/hCAAAQgAIHpIBA7RL2O05H3INPUWlZx8fmLL764a9KXXHJJcV+L2VfXq6qzw3HXxLkJAQhAoAeBXv423u+RzLTe1lIK5557bpHHc57znLDzzjv3zO+AAw4o/LDW8dNukNttt134yEc+Us4izCVw44035m4hhwAEIDAwAtG3djsOLDMSGmkCzAAc6eprhvHqTKULh7uFd1VSt5B5umhqSiNNL8pziwrH++nRLfzq7HIypRNn/aRpOvt1360P42RpWum5K6uT5RapdQvtuvIrT8fQxXf5K75L15XVpan4rr5zi2i7zT30GmY1aGMGF9yiyPF1oaq+03WbiDj7lZbb2dXVVy6+vuyrIcfQ6bo6cHWtPFwdurycrGpjr+u4gPNk0oodoF556L5jUideHZ1TTz016K9b+NjHPhY+/vGPFyoXXXRRx49R1fsrXvGKcPzxxxebifz85z8vfnxW05Q8zgCUfrW9pO1fn9H0c5pj4OTVdKMdaXpR5tpRLr77HK244ooxqfLo8tFN52OdTLqPP/64Dm3Bra/oPhuK5Li4hdDTDVzSzNxakCussEKqUp67NNxC5DkuTu7K73yOjHCfeWeTdN1GS25nVeefFd9tZHLffffpVkdw9jq7XBtSYu77++GHH+7IJ9eGXBvoiPxngfNhTpaL7z4zU80/17Zj23J8c/ZFuWyqa1eqd++998Ykssd0KYSsUs0b3/nOd8pNYPbbb78OX+mS+elPf1qKFy5cGPT3i1/8Ihx99NHh2GOPDQcffHB5Pz1Jy6b+Svp57Oe141x7cT42zT+ep/lGmY6ubTmZ82+K7/LPtR0nd+VK24byiMHZVVcW06genU3ScTY4hk6Wix/7NKkNTpaLn6sD990xZ86cNJviPPcZcnX40EMPdcSXwNnr7HI22QRbwnTt4qjjbNI9116cTdJ1det+n7k0Fd/VrcsrF19pVINrV5PRcXGmK+1qXlyPPgEGAEe/DikBBCAAAQhUCKgjVKczpGh19SpZzOjlu9/97jBv3rzix9ahhx4aNNMvHfzWIIXkChpIkz4BAhCAwEwSmKzfrTM7eZB+up/Xf/XgRBuEbL/99iGuq6olHTSIeM455xQ7gh9yyCHFQNpBBx3UgdsNbnQoIYAABCAwBQJ1fe8g/egUzCXqLBPgFeBZrgCyhwAEIAABCPQiMHfu3PD+97+/UJs/f37YYYcdwje/+c2gcx11rXMF6bHeX4GCfxCAAATaCGgjpTibT6/xyrfmwj777BNuvvnmcOSRRxaDgFtvvXXQ37777hu+9a1vhe9973shzn467LDDyg2c0vTcjKP0PucQgAAEIACBmSTADMCZpE1eEIAABCAwIwTqPg2VMaPyRPRf/uVfwgMPPBC+9rWvhauvvjq87nWv62D5tre9LXzqU5/qkCOAAAQgMN0EJut3r7zyyhnbpfzrX/96+Rrhm9/85q5Icq+Px0h77LFHOOKII8JHP/rRYpf3k08+ORx++OHxdnF0r5q3KXABAQhAYIoE6vreUenvThEH0XsQYAZgD0DchgAEIACB0SMQO0N1j6NQQq3Fph+Y559/frEmoDYG0fqROmrNvwsuuCCcdNJJds22USgfNkIAAqNNoK6/jXqxtGuttVbQ+mTd/qLuVI9nnHFGkYQG5jSTb6pBr/3GdejcJk1uvc+p5kl8CEAAAimB6FPrHNN4nI8nAWYAjme9U2oIQAACjSYQO0F1Cind2QzaBER/dcPuu+8e9EeAAAQgMEwEht3vapmE6667rkCm2Xsrr7zylPFpQ5tVV101aNMEt1GYBjd/9atfTTkfEoAABCCQI1DX9852fzdnP/KZJcAA4MzyJjdDoLrTk9thSdGc03KynK7byTA+ta2a5eRul6eq7TEdl5fb4VL6bic+l5dLM+ZXPTouufjOrpxuNR9dO/tzdeh25HLxHX/l5Trra665pm51BCd3u1E+5znP6YgrgdvF13GVrts91HF1O4rl4sd1hXS/V3DtJdc269ZBrg5zZaja6GySTo5hNb6uow39xInpKE7deHX1YtpNOOoznn7Oc+2ln7K6Ondsc59vl5f7bOXaoFtrK+5oWk3byZ0vqsaL1+7z2c9nPmUf08xxcVydrJ/4rr6dTbLNvQbpdvuV7vLLL69DW3C7QTpfrkgaLKkGV1bpuM0VXNtwsmoe8dq1Ieczo/6gj7k6dPk4Xfd5U1xX39G/VtOODHJpVfXTa8WpG6+uXpr+VM/TzT96vf7bT16uLmJ8rTF44YUXFpfVeqhexzjus5hrxy5vFz/H28WPdqTH3OfAlcHJlFbus5zmo/OcTU7u/G5u1qXbddntHC4bHG/3mXE7lyu+80/xs6X7vUJdX6p0XH/V+Vinp/iOwV133aVbHcG1LcfKsVZi7rvT5Z9rK65t/fa3v+2wUwJXX65Pkfvud/FtRhmhK0Odz2FOJ5NNIVacOvHq6HTLh3vNIMAAYDPqkVJAAAIQgEBCoG5nSFHoECXgOIUABCAwSQLD7Hf1I//ss88uSjZnzpyw2267TbKU7dEefPDBYvafpFqOoRq0aQgBAhCAwHQSqOt76e9OZy2MTtoMAI5OXWEpBCAAAQjUJFC3M6Tk6BDVhIoaBCAAgS4EhtnvahaeBusU3vCGNwQ3c6xL0bK35s2bV36H7LTTTh1622+/fYcMAQQgAIFBEqjre+nvDpL66KbFAODo1h2WQwACEIBAFwJ0dLrA4RYEIACBaSAwrH43ff13//3371ny22+/PTzyyCNhiy22yOr+4Ac/CJ/4xCeK+0svvXQ44IADOnS1URMBAhCAwHQTGFbfO93lJv3+CTAA2D8zYkAAAhCAwJATUEeobmeort6QFxnzIAABCMwqgWH1uxrI02Cdwuabbx5e9KIX9eSkAcBddtklaAbfnnvuGf7qr/4qaMMPhVtvvTWcc845xV/8/jjqqKOCW2e4Z0YoQAACEJgigbq+N/qrKWZH9BEnwADgiFdgE8zXgq6pQ8otNOzK6hZYdXo5mVtMVrpuoeHcIrMubbcgrls4V3HdgrhuQdpcWVN20Rb3aoueTrvgFt915Vdct4Cx082xcvGd/UsuuaQzNbiNPdZff32r6566u3SdTAnGjn6auFuUWfddGo8++mgatTh3Gw/oxuOPP96h6+ow14Zc23BclYn7fLk67GfxYxc/Z6vTdZ8X2RrlKp+zWzq5oPLnGFTj1NWrxhvl62qbyfGt6qnMOb/pdPth5PzDvffe25FErm11KHax1ZWhn7bpdF3+dfUUN9cOXd04+933htJ19eLyct8Fiu/WNdMaai44G1z+OS7Pe97zOpKNr21Wb7jvtEWLFlXVgmtDUnJ+17XBjgSnUeDqRdk5Xjnduubl4sc6zN3vlr7i1I1XV69bfnXvffOb3yz7L3Vm/6XpXnHFFUF/uaDNDo455phw0EEH5VRKub5XU/+VYxC/+8qIrRPXV0zvp+fOZ+Tatvt8Ov/i9JRnrgypPfHcteOUR9TL5RXvp0fnB9ZYY41UpTx3mxe5+Irg6sAxzPmnW265pcw3njhWrv8ofedj3cYeMe3q0THM9c3dpimu/MrD9U1dXm6zDcV3vHPfPdKvBtc2XZrVePHalVUPCFxwvFxZncylJ1mOaypXO+mnD650Fce1L91LQx2dVJ/zZhJgALCZ9UqpIAABCIw1gbqdIUGiQzTWTYXCQwACAyIwrH73jDPOKEqoH9lvfOMba5V2yy23DF//+teLwb/58+cXA8kPPfRQ8TBKAzGbbbZZeOlLXxoOPPBA+8CwViYoQQACEBgAgbq+l/7uAGA3IAkGABtQiRQBAhCAAATaCdTtDCkWHaJ2dlxBAAIQmAyBYfW7l19+ed/F0Yx/DRbWHTDsOwMiQAACEBgQgbq+l/7ugICPeDIMAI54BWI+BCAAAQh0EqjbGVJMOkSd/JBAAAIQ6JcAfrdfYuhDAAIQmDqBur6X/u7UWTchBQYAm1CLlAECEIAABNoI1O0MKRIdojZ0XEAAAhCYFAH87qSwEQkCEIDAlAjU9b30d6eEuTGRGQBsTFWObkG0Jku6CHBcgLpaIrfIqpMpXl0Hl9NL7Yl2uMWL473q0enmFnB2eTkGbvFh5esWxHVpuk0xFN8tvuviS9ct/psuXCsdhVx8t6its9/lo3RXXHFFHdrCqquu2nYdL1wduPi5xYPvuuuumFR5vPvuu8vz9MQtIOwWns9tAuLaoauXXB26z4GTyWYnd7ydTWmZe53n2oDLK1euKNeC5jl2OTtkf90y1NXL5TWKcvmTtI5cu1C5nNzJcgzSPKKOk+me8wVOFtOpHt1nPpeXkztf5tJUvnXjuzQV36Xr/KN0Xft0i5M7meLXZZj7jnILz7sF6pWXW/h9hRVW0K224Bbjl8L999/fpqcL50sld3k99thjutUW3IYIUsjJ2yK3LlxdScfJXV1JNyfXvTS4dqX7OXkaV+fOJsldfOeLpRvbgT7nbqMU6eSCylm3rHX1cnmNorzKJ9cGHRtXh2Lg/LHzJf3k5fxWrr24enDxpefkzj899dRTLlnbB3X+ZZ111rHx3YZGrq+Vs9X52OWWW87m5TYHcbIcV7fpXM5vut8Mjkv8bFcNvuOOO6qi4GyVkmPg2mCuvbm26dqANtdxwfFyMsWt+zlyNim+K5djLV0X3Gc29mur+mkZlG/Opmq8eF31LVFePTomVR2um0+AAcDm1zElhAAEIDB2BOp2hgSGDtHYNQ8KDAEITAMB/O40QCVJCEAAAj0I1PW99Hd7gByT2wwAjklFU0wIQAAC40aAjs641TjlhQAEZpsAfne2a4D8IQCBcSSA7x3HWp9cmRkAnBw3YkEAAhCAwBATUEeobmeort4QFxfTIAABCMw6AfzurFcBBkAAAmNIoK7vpb87ho3DFJkBQAMFEQQgAAEIjDaBup0hlZIO0WjXNdZDAALDQQC/Oxz1gBUQgMB4Eajre+nvjle7yJWWAcAcGeQQgAAEIDCyBOp2hlRAOkQjW80YDgEIDBEB/O4QVQamQAACY0Ogru+lvzs2TaJrQRkA7IqHmzNBQDtwpTuDuV2TZEc/OyK5HaVcWXJ51XWQud2c3E5bud353E5ZbpetXPldui7/JZdc0iEIuTI4Zaeb1l2Mk+Pn4rtyOSZK29Wr26FSum63tNVWW023aoVrrrmmQ++ee+7pkEnw6KOPdsidLLeTs+PSTx26duy4ykjH0Onm6iDdqSwW2tnqZNJ3O+7ldmKOu+vJvvvuuy9mV+tYtzOkxHLttVZGI6qk+nW+o1ocxyYXz7UN1zbdznrK130++snf2eXyV15O7nyZS1PxXVldO87tZOg+B0rXBbfrYM4uF98xdOV3+bj0JMv50rXWWqsjivPFOS5XXXVVR/wFCxZ0yCRwO9S6705XfsV3DJ3MsVJ8J3fxpev8rrMrF19pVIPTde1S8dz3/7LLLltNsriO7Vg+wjG2kf4sVJlcuVycunou7qjKVA+pn+mHQc5vus+t+07P5eXakeuTrL766hb7iiuu2CF3aUrJ7dK9cOHCjvi5XYBdv8L5l9wu5auuumpHXi5NKbnPh2PdkeCfBa5v+tBDD3Wo95Oms18Juu8TtwvwokWLOvKX4M477+yQP/zwwx0yCdz3tPNvuXK5dpx+JmKmrky65+or17bd94HbPT7n51y6Ln/3eZGtzh/nyhX9ruLJ97rPiu7lgmx19lb16+hU43DdPAIMADavTikRBCAAgbEnULczJFB0iMa+uQAAAhAYAAH87gAgkgQEIACBPgnU9b30d/sE21D1xRpaLooFAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEItAgwA5BmAAEIQAACjSNQ92moCs4T0cZVPwWCAARmgQB+dxagkyUEIDD2BOr6Xvq7Y99UCgAMANIOIAABCECgcQTqdoZUcDpEjat+CgQBCMwCAfzuLEAnSwhAYOwJ1PW99HfHvqkUABgApB3MOgEtipwulJpbPDjViUbnNipwcuf0nJ7SdovXuoVrnSzaVj3myuXkbpFZt+C48nCLz7oF1nMLzzqubkFe5ZWT614ann766fSy67mrF7fIsBJxi8E/8sgjNv3NNtusQ7722mt3yK688soOmQQ33nhjh/zee+/tkEngNvxwbcPVteI7uePiFlpW/Lr1Il3X5l17l64LrlxO5uJK5tpxrm3GRbhdG82lH+Xi5xjG++mxrl4ap2nnuTbk2mZO12004HRz/mGq9dCPra4dOlmunpdffvmOW2ussUaHzJVfSq6sbuF+6bpyuc+ckym+86eurM43KL5bIH7dddfVrY6w1VZbdcjWX3/9Dlk/fvfBBx/siC+BK5dj5WSKn5PrXhocK91339NOJl3nu53fzdWhay91Zcrf+dDoX3U/DenmS6m8zrlscna5uHX1XNxRlem7LvUJufp25ct9Pl3bcvFzebnPgdPN5e/y6qduUx4xrdxnzvVt3SYgsQ3H9OLRfT7TzReino7Ox7tNJRwrxc+VQffS4PyA7ruNz5wvle4mm2yiQ1twG6FcdNFFbTrxwvVtcxux1G0HuXbpyuu++xxr2et8WU7X9c3d5ia59uo+G669ur5PzlbXBqWbtkPHSDrdgsqQK0car45Oqs95MwkwANjMeqVUEIAABMaeAB2dsW8CAIAABGaYAH53hoGTHQQgAIEWAXwvzaAuAQYA65JCDwIQgAAERoaAOkJ1O0N19Uam8BgKAQhAYBYI4HdnATpZQgACY0+gru+lvzv2TaUAwAAg7QACEIAABBpHoG5nSAWnQ9S46qdAEIDALBDA784CdLKEAATGnkBd30t/d+ybSgGAAUDaAQQgAAEINI5A3c6QCk6HqHHVT4EgAIFZIIDfnQXoZAkBCIw9gbq+l/7u2DeVAgADgLSDWSegxVNzi6KmxrkFdd0CrYrjHFxuQdo0j3ju4ruFb90i5ErDLQrs7Jeuk7tyOZniuwVx3SK1/cTPLWjryuVkjpVsdXVQt/yKv3DhQh3awmWXXdZ2HS+c7uqrrx5vl8ebb765PE9P7r777vSyOO9nUWTHxZW1I5M/Cxyr3MLAbgFlJ1PSzi5X3+4zkLPVyZ390su1DZdGbLPx6HRyMtlftwx19XJ5jaJcC06n7THH2LHpR9e1N5dmPwz7iZ+z1flIl66TyVb3neU2s8m1d/dZdqyUl5M7v+82hFJ8tyC+s9WVSfGffPJJHdrCFVdc0XYdL9zC9WuuuWa8XR5vueWW8jw9cX530aJFqUrX81x9u0hp+4/3XXzXVqTv6sDJpOvYOt1+/GZOV/lVg2vH6aLzqX6UOz6pnjtXPi6vnK6TN1kmpml7Ss/Tcjv2TqY4zsc43am2lyeeeCI1sTx3/eBcG3C+zNlfJl45cZ9P50sr0cpLt4nISiutVN5PTxxDx8BtKqF0nN90n3lXJsV3G1jMnz9ftzqCs2G11Vbr0Lvmmms6ZBK4crm6spH7FLp2mNvEwyXtuOT65i4v95nLtVfXNuvKZLtj6NqgdNO24eJJp1uo63tzZe2WNveaR4ABwObVKSWCAAQgMPYE6naGBIoO0dg3FwBAAAIDIIDfHQBEkoAABCDQJ4G6vpf+bp9gG6rOAGBDK5ZiQQACEBhnAnU7Q2JEh2icWwplhwAEBkUAvzsokqQDAQhAoD6Bur6X/m59pk3WZACwybVL2SAAAQiMKYG6nSHhoUM0po2EYkMAAgMlgN8dKE4SgwAEIFCLQF3fS3+3Fs7GKzEA2PgqpoAQgAAExo9A3c6QyNAhGr/2QYkhAIHBE8DvDp4pKUIAAhDoRaCu76W/24vkeNxnAHA86plSQgACEBgrAnU7Q4JCh2ismgaFhQAEpokAfneawJIsBCAAgS4E6vpe+rtdII7RLQYAx6iyh7Wo2gEr3QWrH+fkdulSOdPdlGK53W5Qubyc3O00ltt5yu0ylbM1LXu0tZ8doJyu25Ut7uwX84jHuvGl//TTT8do5fHxxx8vz+NJjosrq9u50vFX2i6+2zVSug888IAObcHl5Xb0UiRng8tfuq5tOZlrF7m8XP5OpviuDp1Muu6z4XYBzrVXx8uVNcfKlcHJZOtUw3SlO1W7hiG+Pgtpe3T+TXa6esy1jTS9WEbXXuK96tHlVdXpdu3aofOFSiNX3mr6rkzScek+8sgj1eiWn5Rc/s5+6bp27D7HbmdfxXe7XLpdwnN15fyDK6vyuv/++3VoC6695PJyclf+tgx6XOTalUvX1beTKUtXBzldtwuw+052Nikv993r2qB0XXD5u3pV3LhLpas3l3ZVlitDVW8cr9W+Uz65tunaVk7Xtbl+6i61J9aJ25V1ELtxuzI4Wa7/4vqWbldY93lR2dzOvK6s0n3wwQd1aAsLFixou9bFHXfc0SGTwOXl6jVXVlcvzr8qr4ULF+rQFlx/N+cz3PdBzi5XX20Z//kip+fK5fx+rg7dd2fOVuf3VlhhhQ5zXZpScu3N5ZX77na8XXzllfPHulc3OLZ146I3XgQYAByv+qa0EIAABMaCgDpCdTtDdfXGAhyFhAAEIDBJAvjdSYIjGgQgAIEpEKjre+nvTgFyg6IyANigyqQoEIAABCDwJwJ1O0PSpkNEq4EABCAwdQL43akzJAUIQAAC/RKo63vp7/ZLtpn6izWzWM0t1fz588MnPvGJsOuuu4Z11lmnmDK83HLLhblz54YDDjggXHbZZX0V/sILLwz77LNPmZbS1LXkBAhAAAKjSiB2huoeu5UTv9uNDvcgAAEI/IlAXX8b9bpxw+92o8M9CEAAAn8hEH1qneNfYnE2rgSYAThCNf+Sl7wkXHrppR0Wa+2Gm266qfg79dRTw/777x9OPPHE4NZ/iJG1BsFBBx0UTj755CgqjlpPTX/nnXdeOPDAA8MJJ5wQ+llLpC0xLiAAAQjMEoHYCaqTvXRzAb+bI4McAhCAQDsB/G47D64gAAEIzASBur63W393Juwkj+EgwADgcNRDLSvuueeeQu/Zz352eM1rXhN23HHHsN566xUbEFxxxRXh6KOPLgbvTj/99GKB8TPPPDOb7uGHH14O/m2xxRbhAx/4QNhggw3CLbfcEv71X/81XH311eGkk04Kc+bMCZ/+9Kez6QzihhZJTRdQzS007BaJzS2mmqYXbXSLvDqZ9HPpxrR6HftxsE7XyXJ5usV73cKzuYWOXVkda+XvFuV1eTn+iu8WQHayXHxnV07X2eUWJXYLaMtWtyBvbjDcMVQa1eDyl46T15Xl4udsrdqka1dWzSx2wbUBt1By7rPlyuXqSnnHMsSjsycn02eo7ueom15T/W6Vj/ts5djm6sN9Dly6ubbh4udsqCvP1W3dvFx7Vd5u4XmX1/LLL1/X1NrtVQm6xc2XXXZZm5fTdXXgFq1Xgo6VS1O6zj+4vHJcc/5YaVeD4+1k1Xjx2tng2naurO4ha85+l4b77ou2VY+OoftsOfuVVtzYI013xRVXTC/L87XWWqs4d369VMqciH/dOuim11S/q/5aWkeuDQqtq9sMcqvrPrO5+N3qIY1TV09xcrquvDndNO947n4fuA0w9FvGhbvuuqtD7HyWlNwGd85H5uK7vqnzA7m6dnKXpmx1/sH1+R1/xU/bpK4VnOxPdzr/u/aWy8vJXXwnU86uvbg0pevK4DZfyvV3XbquDbi6Uv4uvrNJuqkN/Xw3KK6CuDg2f7r7l/91dP6izVlTCTAAOEI1u/HGGxeDca961avadm9UEbbbbrvwpje9Keywww7hxhtvDGeddVY45JBDgmavVIPuH3XUUYV4q622CpdcckmIDnHrrbcOe+21V9hpp52CXr848sgjw1vf+taw4YYbVpPhGgIQgMDQEqjbGVIBunWI8LtDW8UYBgEIDBkB/O6QVQjmQAACY0Ggru/t1t8dC1AUsiDAGoAj1BB+8IMfhNe+9rUdg3+xCKuttloxCzBen3POOfG07XjssceWTwyPO+64cvAvKulJseQKeqpxzDHHxFscIQABCIwEgdgZqnvMFQq/myODHAIQgEA7gbr+Nuq1x/7LFX73Lyw4gwAEINCLQPSpdY690uJ+8wkwANiwOt5ll13KErkp8HIM3/3udwsdzWzRzEEXJN9oo42KW9JXPAIEIAABCHQSwO92MkECAQhAYDoJ4Henky5pQwACEIBAUwkwANiwmk3X0nJr0dx2220hrq2i13y7hXhfm4Lcfvvt3VS5BwEIQGCoCNR5CprqTMV4/O5U6BEXAhBoCoHUp9Y5n0q58btToUdcCECgSQTq+Nuo06RyU5bJEWAAcHLchjbWxRdfXNq2ySablOfx5LrrrounQTMAu4X0/vXXX99NlXsQgAAEho5A7Oz0Ok7VcPzuVAkSHwIQaAqBXv423p9qefG7UyVIfAhAoEkEom/tdmxSeSnL5AmwCcjk2Q1dTO2Y9NnPfra0S+sFVsOCBQtK0TrrrFOeu5N11123FLuds8qb5iTNx9wO9957bynWTnPpbEW3c5WU3e5XTiZdOb9qcLq5nZuqcXWd2hjv53ZzysljvPTodrpy9juZ0nG7f7nd+9xuVIrvdjLsx363q5nSdaFuWV1cyVxZXZq5+E7u6lV6jkFON1c31fxcmtJxO345rrn4Lv9cfTu5yz+Xl2PgdF2aKqsr11JLLaVbHSHuaurS71CuCMTEcamoFZd19VzcUfW71d0onX9UeV17cRwkc59F52OdTPHr1kPOJte2cm3HyV26rkyy1e1GKXk15D4Hrs27/JWe03U7uObiO7/pWOdsdd8nLr5sdTY4n5HLy9VhLi/XjpxMdrng7HLfh3GTtGoaTu7SVDzX3qrp6TrX/3Ht0KXp2orSXWmllXRoC7k+4KabblrouZ2u2xIwF6qrXH1V1evqVePpelT9rurX1Vu1jHV0YhzH0cncZ1NpOLlrx05P8Z2tLn/punbsZLnvI5fu/fffr6TbwiOPPNJ2HS+crblyxTjp0cVP76fnzlbH1cmUjr6jq8GxqurEa1cu51+l7/yxiy9dZ4Pzu05P8V26Tub49RNfus6fp7vtSkfB2S+5qxvHSrouOH/sfLHirr766mUSuZ2lSwVzIl45Zql6HZ1Un/NmEmAAsEH1qs06rrzyyqJEr3zlK8OWW27ZUbonnniilDknWN5sncQf35K5bc9T3ep5OnhYvcc1BCAAgekmULczJDum0iHC7053TZI+BCAwKgTwu6NSU9gJAQg0iUBd3zuV/m6TeI17WRgAbEgL0KsQ//RP/1SURk8Rjj/+eFuy9OmyezKSRlpyySXLy7qzHcoInEAAAhCYRQJ1O0MycbIdIvzuLFYwWUMAAkNHAL87dFWCQRCAwBgQqOt7J9vfHQOEY1VEBgAbUN3XXntt2GeffYopzJpu/O1vf7ttKnFaxHQ6sptenuqmCyy7V11S3ep5r1eG9QrwNtv8f/bOBPqOosr/pTMjhBCWJISQBBK2sIjM4UAQjMJBWQYQwnJEOB5hEAQBA3hmWDww4xwEBEFhjAxbgqgzgoIKijCCsq8hA56RfUnCkgAJISEx4Db//PNtrGe97u99r/q9fr/Xr/tb54Tuvn3r1q1PVd9X1K+7aud0Nl2LgAiIQCEEYgdDKKyTAZHibiHNJCMiIAIVIqC4m21MjXezTCQRAREolkBs7O1kvFusp7JWBgKaACxDK3ThA3b13XvvvR3Wu8BaBddff73bbbfdTIsjRoxo3Gv3WW+47k+7z4UbRv9yYq0tk9bTtQiIgAj0gkDsYAhl5x0QKe72osVkUwREYNAJKO4OegvKfxEQgUEkEBt78453B5GFfG5PQBOA7RmVVmPhwoVuzz33dDhiAdVrrrnGTZs2raW/4cRcu406wrf4ermmHz4vDhfWtRZjZQvK5lkomOVnC88CIJPHypCfLbRrLRzL/GL1st7YZHL2yXbIGD76xH4MLF/ZgrjsU3JWJ5TH2paVb+Vnur4e6SOrL5Ol8/lrxtXfSx+ZX6wspgdbTJdxZfyQn8kthqxtmSxcAgBl+BQuI+BlrF+wOkGf2Q3fTPY2cVxnnXWSS+ZfqMfOwdrindaP1UO+qsRdbAzBYlqaDdOxeDE565tML11uq2urb7E31dlzBNvMBuvH4ZvwoU/sOWALd1t1ZX4xn1Cm9XyE/uDcys/8Ys+U5StrwzzxhdWVsUYd2G+fVRb004nVK63jrxlX9sdOFrNgg8nZbz90rfriXpgYa9xnbctkrE7I72Mpzn0aNWqUP206brjhhsm1VZcm5dQF+pDVj1Kq0XrIp7jL+wDYsOeD9aPYdoFNllh/hx57ZtZaay1mgspYLLVeUGCxjNWf2UTh7Jmxnk32LLFYZpXF/GK/p0yPgmohZHZZXZkezOaJu8xfVhaToSwWo5ku27wK+Vk/turF+mxs+SiLxcBYGfKzZ8PaBGTs2LHIkqRwvX4va3eMjb2MXzvbul89ApoAHNA2ffPNN91ee+3l5s6dm9RgxowZ7sgjj2xbG7+7GxSfeeaZlvrh/W222aalrm6KgAiIQJkIxA6G4HPsgEhxt0wtLF9EQATKRkBxt2wtIn9EQATqQCA29saOd+vArM51fH+dKz+odX/77bfdPvvs45566qmkChdccIE76aSToqqz6aabunHjxiW6WMC+Vbr33nuT2+PHj3eTJk1qpap7IiACIlAqAn4wFHts57zibjtCui8CIlB3ArHx1uu146W4246Q7ouACIjAe3/I9nG13VG8REATgAPWB/D6+/777+8ee+yxxPOzzjrLnXHGGdG1wGvS/jNhvOH38MMP07yQ+zcAoW+9Xk0zSygCIiACJSDQbhDk77dzVXG3HSHdFwEREIH3CPi42u7YjpfibjtCui8CIiACfyXQLubivpIIgIAmAAeoH2BNMuz2+8ADDyRen3LKKe7cc8/NXYNTTz21sR7N9OnTXXq9OFxDjoS1EqCvJAIiIAKDRCBmIBTqWHVT3LXISC4CIiACzQTCmBpz3pz7r1eKu39loTMREAERaEcgJt56nXa2dL/6BLQG4AC18RFHHOFuv/32xOOPf/zj7phjjnFPPPGEWQMsVjt58uTMfchOO+00h0+H58yZ46ZOnZq8Rbj55pu7F1980V144YXu8ccfT/JBb8stt8zYKFKABXTDNwzD807LYTbYwq1s4dlOywzzsUVyw/vhOVtUOE9+tnhvaN+fMya4xxhYiyIzXbZZhrV4L6sX85/pWb6yhZp9ndNHZhc/iCxZcqbLZHnqxRa2ZlxZOZAxX632Zm3L2tXKzxgymZWfLcDMFkpGvUaOHImDY89IcqPFf/IMdBg/b7qqcRf9M2wj1i/AgPUN1obQtWzgXpjybKzBniPmE+xb8rBsfx7W3cuY/1Z8YYuLs3qxZxvlWXLvS3hkvJcuXRqqJOfMf9xgvrLfQ1YO8rMNBVh+6Fq8cC9M1m8Ea2/r+bTkYTmtzlmMXb58eSbL8OHDMzIIGC+LS6wu60Moi/nF6s/KsXy1dH0/yvM8oQwk+MT8eu9u839b6dUl7rI4BEq+DUJiFi/2zIT5OjlnZbHfedhm5Vu/2WwzGvYcWn2T1YU9M1Z+NtYYMWIEM+vYplJsc5L0SxTeGOPFWDHWsMH6hvVMsvqy/N639JH5ymTIx/xlulYsZH2D+cpYoXxWFssPXSZn+ZkM+VldWRsw/sjPfjusTUBGjx6NLEmy2Pn77Ahfmb9p3RiddB5dV4+AJgAHqE1/8pOfNLy988473fbbb9+4ZicTJ0508+fPZ7fceeed5xYtWpTsHIzJvsMPPzyjhwnGTt4wzBiSQAREQASGmEDsYAhutRoQKe4OccOpOBEQgYEloLg7sE0nx0VABAaYQGzsbTXeHeDqy/WcBPQJcE5gVVHHXzBmzZrlfvGLXyRrAmJjEPxVBkes+Xfrrbe6mTNn5nqjoipsVA8REIHBJ+AHQ7HHoaix4u5QUFYZIiAC/SIQG2+9Xi/9xNs/+Ie36a655hqzqO22267tePe2225LluCZMGFC8kYtjliSB3IlERABEeg3AR9TY4799lXl95+A3gDsfxtEe4CHuui03377OfxTEgEREIEqEfCDoJg6tYqtre7F2GY6iruMimQiIAKDTqDMcddiO2rUKOtW8rnhcccdl/zBPFRasGCBw7+bbrrJHXvsse7KK6/UH8xDQDoXAREYUgKxsbcXY9ohragKK4SAJgALwSgjIiACIiACZSIQOxiCzxoQlanl5IsIiMCgEihj3D3hhBPciSeeaCJl63R55bPOOqsx+bfDDju4008/3fn1sr/+9a8n62Xja5kNNtjAnX/++T5b09Fay6xJSRciIAIi0AWB2Nir8W4XkCuUVROAFWpMVUUEREAEROA9ArGDIWhrQKReIwIiIALdEyhj3B0zZozDZ75503PPPecuvvjiJNtOO+3k7r333sbGEFOmTHEHHnig23333ZPN9C666CL3uc99zm2xxRaZYm644YaMTAIREAERKJJAbOzVeLdI6oNrSxOAg9t2lfEcuy+FOzWxnbdQWbbzkvWX1dCeBxW78xT0rR0KvS1/zLNzlKXL6sV0mR78YH+9ZjLrM5e11lrLV6dxtH4gsGNzOq1cuTItcmxXNyix9mIy1n7Iz+pl7TrJdmZju8Wx8lEWSxYXpmvVgemytmX5Wb+APSZnNqHL6stYWW24YsUKmGlKjCvbxRCZ2I6kTcaCC7/7qD8Gt9qexg6GYChPu7YteEAU0D5hH2PPFqrC4oO14x3buY7psj6EspYtW4ZDU2J9K/Q7VGbPgdW27DlguqxOKHP8+PFh0ck5e2bYrpFQZr8xzH/oWnLcC5P1nLC6st9DJoN99syuu+66YdGNc8YwDxfWX5hNFMi4MFme/sLaxdqxmdllrOEr++1kutazwX5nWX72DKF8bPqWTviElaX1118/EVu2WB4vQ1tZ7eV1/DFWz+sP9fHSSy9t7IA9Y8aMxuSf9wOxEfJdd9010bvkkkvcZZdd5m83jvg82EpWfGHPAeubsGv91qfLZM8GdJictQ3TQ37WDy1dNl5jcYvVH2WxuMN2VfV9GHnCxH7nLH7smWXPvPXMsthvcQl99OdsDGX9/5HPEx7ztGGYr905qwNjaPVt9nvC8rP6wzcWj1ldoct+e5YsWYJbTcnKz+Iu669WfiZnfQjOhHbD8yZHW1ygLFZeOkuMTjqPrqtHQJuAVK9NVSMREAEREIHVBPyAqN1RsERABERABIoh0C7e+vvFlNYbK/Dx5ptvToxvvfXWbpdddqEFQb7VVlsl96CPfGHCW4QvvPBCKNK5CIiACPSEgI+trY49KVhGB46AJgAHrsnksAiIgAiIgAiIgAiIgAiIQC8IzJs3zy1cuDAxjc98WyV/H29Uzp8/v0n1/vvvb7rWhQiIgAiIgAj0m4AmAPvdAipfBERABESgcAKt/gLK7hXugAyKgAiIQM0IsNjaSjYUeLAG37bbbpssZzBixAi35ZZbuqOOOsrdddddZvFPPfVU4x7eAGyVwvtPP/10k2pop+mGLkRABESgQAKt4mz6XoHFytSAEtAagAPacHJbBERABETAJuAHPLbGX+9AV0kEREAERKA7Ap3G3ddee61twRMmTGirwxTSk3D4JBf/vve977mDDjrIXXvttZm15V599dWGqXblbrzxxg3dV155pXGOk9BO0w1diIAIiECBBGJjr8a7BUIfYFOaABzgxquq69bCr2zhVGtRZLaAMFvgnC08C64sQLKFjq38zC+2cK5VFivfKmudddbJdAW2491mm22W0YMgdlFm6C5fvhyHpsQWF3/55Xcel8cAAEAASURBVJebdPzF3Llz/WnjyFgxn5CBLR7MFoCGLltEl20oAF2WGG/WLsjL2pb1V9YvkZ/1TVZXq3y2WDWrP8pi9WK+MpvIzxiyhZatujLdt956C6Yz6dlnn01krMyMckoAVhavlGq0XjrfIF+n2bD4hvqx9rJ0Wd9ae+21M5hYf4MS63NWWRmjqwWsz1v5LR/Sdq34wiYFWIy1FkJnG+9Y/Zy1AdO1JlGeeeaZdLUoa9Z+yIi3ptJp3LhxaVFyzZ5ltmg7i/swENsu0E33YUsGOUssbjM9qw+xdmE+wSbrB6y/MlbIz9qb+f/2229DPZNYWWyBe2T0b7Gx+mUMpwSov8Ugpdqkt/POO6dvZ65j7fqM2KQDO/V+4hOfcHhLD7Fo8eLF7p577nFXXHGFw2YAN910k5s2bZq74447mtoo3NiBxTBfBo7hxhLpjR9CO2GeTs5Ze8MO48KeI+s3mfVvVhaToXzWT6x+yHxgcZ/1V5TFYtE222yDW01po402arr2F9bY0t8Pj2y8yzbFYvWHnXRfgIzVy/p/HjYuZON92GUMmV+sryA/i/2WLutbTMZsoizWB1hdrbZi+a24yfo2++1h7QJfmS6zabUha4M33ngDpjPp8ccfb8jY+KBx0zhBe1ltFmaJ0Qn1dV5NApoArGa7qlYiIAIiUGsCsYMhQNKAqNZdRZUXAREoiECZ4i7W5GMT+HvttZebPn2623fffR3+pxsTgpdffrk7+eSTGxTCCRU2OdFQXH0S/rEu/T/uoZ0wj85FQAREoEgCsbFX490iqQ+uLU0ADm7byXMREAEREAGDQOxgCNk1IDIgSiwCIiACOQh0Gndnz57trLe2chTfpMom/7zChhtu6G688cbkzUC85TNjxoymCcDw7SP2Fo+3g2P4duawYcPCW/QLiyYFXYiACIhAAQRiY6/GuwXAroAJTQBWoBFVBREQAREQgWYCsYMh5NKAqJmdrkRABESgEwKdxl1M/rHP6jvxITYPPtnH24C33nprsiYgdv31n7aHn5qyTznDMsJPqdOfC4d2wjw6FwEREIEiCcTGXo13i6Q+uLa0C/Dgtp08FwEREAERMAj4wVDs0TAjsQiIgAiIQCSB2Hjr9SLN9kwNuwP7hE+GfQonI9tt5BFu/BFuCAJboR1vW0cREAERKJqAj6kxx6LLlr3BI6A3AAevzSrnMdZPCReLZQu8WpVGoGOJLdLKFnm11nZhPrDFYJlN+MN08/jK6hSuMxPeZ76yhYLDgW6YH4tjp5PFhS3w/j//8z/p7M5akBc776UTYxh+UhPqs4XUrYWp2aK8YT/zdq38bFFjqw2ZnMlY+fCD8Q4XFve+WvlZH7DagPnF+mt6LSPvA9NlrNOfQvn8rK7WJ1ZYpB2JlentWUfUk9WV6cfqsbyDKkOMDPu4xZixsfohYxF+Sufvs/6CeyzGsTW0WMxAfia3nm/oxyS26Dvysecj/fYP9PbYYw8cMmmHHXbIyKxPFpctW5bRfeSRRzIyfNLIUnoXVOiw9g77Q2iHPbMWVxaLWLswGcpkv91MZumy/mrVi/VD1reZHspnZVlxl/VtFvcsLow3K9/Kz95iY88W6uU3k2Fl4n6rBJ+YXyxPrB7LW5TM6hvheIltohOWH95Pb0gR2kEe9KWwzPA8tMnYW7yYLuvHVn7Wv5mu9Ryy8Zqly+Ssz7KxHviwGMv8HzNmTIizcZ6eoMUNFt8gZ88MG9ew+Iz84cQwrpFi6w9d1q7WG6WxcZe1K8piciaz/GL9zerbzFdWL9auKJ+NKaz+wmIcs8v0rLoy/61xAivL2iAn/O1gvw3wp1VCe1ltFuaL0Qn1dV5NAnoDsJrtqlqJgAiIQO0J+AFRu2PtQQmACIiACBREoF289fcLKq4rM+HkuP/8FwY33XTTxufA2CSkVbr33nuT2+PHj3eTJk1qUv3oRz/adK0LERABEegVAR9bWx17VbbsDhYBTQAOVnvJWxEQAREQgQgCrQZA7F6ESamIgAiIgAi0IMBiaytZC1M9vzVv3jx3xx13JOVsvvnmDhN4PuHtpWnTpiWXeMPv4Ycf9reajpD7NwChn37rafLkyW6LLbZoyqMLERABESiaQKs4m75XdNmyN3gENAE4eG0mj0VABERABNoQSA942l23MafbIiACIiACbQi0i7Pp+23MdXz75z//OV0SwBt844033KGHHur8p3Ynnniiv9U4nnrqqcknuxBMnz4989k/lgGAHAmfBUKfpeOPP56JJRMBERCBwgikY2ur68IKlaGBJaAJwIFtOjkuAiIgAiJgEWg1+GH3LDuSi4AIiIAIxBFgsbWVLM5qfi1MzE2cONGdfPLJ7rrrrnMPPfSQ+81vfuN+9atfubPPPtttt9127vHHH08M4zPdk046KVMI3t477bTTEvmcOXPc1KlT3Q9/+EOHcxxxjXMk6G255ZbJefo/n/rUp9IiXYuACIhAoQRaxdn0vUILlrGBJKBNQAay2eS0CIiACIhAKwJ+wNNKx9+DrpIIiIAIiEB3BMoUdxcuXOhmzJiR/LNqhbcAZ86cSTcgQp7zzjvPLVq0yF1zzTXJhOHhhx+eMXXMMce4c889NyP3ArYRgL+nowiIgAgUQSA29mq8WwTtwbehCcDBb8OBrwF2dAoHSNZuTmz3LLbzFICw3bPYTmNsN6c8QPMEUsvXsO6+bGaXybx++sh2tLJ2KsMgOZ022GCDtCi5ZjsZMv/T6+B4Y2wHN7ajV552serFdrlkbZCnrDxtwBgwGdgwhswvpof8TJf1d+iy54g9L4wf8jOGrA2ZDPktOe6lk6+DP6bvt7pGW8W2V6xeq/IG7R7aMeyPFmPWN/LUlcUMqw+wvsVkVnuxvs1kefxfvnw5VWc7or/55psZ3cWLF2dkELAdIvM83yzGr1y5kpbFdrlkZbE4AoNsl8/58+fTstgumUwxTxtafdOywcpjMpafyaxngPWtcCfHsEy2oygri8lCO+F5+Px6uZWf+cpk3g6Olq1QJ32OPLH5YvXSZcRcf/e733XYvANv/s2dO9fh2cSzjDEIdoL9yEc+4o466ii36667tjSH+DNr1qzkc+GrrrrKPfroo4mt0aNHuylTpjh83rvvvvu2tBHeRDwMY5rFgMlZe4e2w3Orz4Y6/pzZZTLmE2ywfmTprlixwhfbOLL87HcDGVjcYzGayZB/yZIlODQla/f1sJ18BhYLrbjL4imTMdYoj+00z35joMt4sTZgMuRn/YXJoMtsMJmVHzbSif1usDql8/lrqw3Ybx8bf7C2hm3WX1m9WHxHftZfWR+AbtgP2DMBnVYJbcDaIZ0nRiedR9fVI6AJwOq1qWokAiIgArUnEDsYAigNiGrfXQRABESgAAJlibu77767w7+i0n777efwT0kEREAEykggNvZqvFvG1ht6nzQBOPTMVaIIiIAIiECPCcQOhuCGBkQ9bgyZFwERqAUBxd1aNLMqKQIiUDICsbFX492SNVyf3NEEYJ/Aq1gREAEREIHeEYgdDMEDDYh61w6yLAIiUB8Cirv1aWvVVAREoDwEYmOvxrvlabN+eqIJwH7SV9kiIAIiIAI9I6CBTs/QyrAIiIAIUAKKuxSLhCIgAiLQUwKKvT3FWynjmgCsVHMOZmWw0Gu4IDlbZBc1Y3K2GCt02aLhbEFda6MDa5FW2I5JbCMTa0FbtiBtyMOXZ/nKAv7SpUt9tsbx5ZdfbpyHJ3/84x/Dy+T87bffzsggYHVgm3Awn5B/7NixODSlcOFbf4O1H+6xhXZZu0KX1Yst9Gu1NeNt1YvZjZXBV2aX+Q9dlpiuxZDxZr6yfomyGS+mO3z4cOaqY4s9M5vI7LmwZ58aD4TI6/MHYnoaq0czD6gQMSpsd4sxW4ya9SFgYAtes8XYrWeWxXPWNkxmNYPla6wNiwvb7OH111/PuPHMM89kZBCw59OKu2whcxbPWdxHWWzzJcjTyWLCGFhlsfZmz7fVLqwPMFna91bXVllMzhiwZwDl5dFt5V94j/mE+5Y8zJtHL52PXaN+edkjD+Ni2WfyKstGjBjRNN5lcQT1Z89ct1ysdgl/B3wZTJanL1i6ltyX649sTIN77DeGbbT00ksveVNNRzaGtDYBYb4uWLCgyR4u2BgYcjZeZmMlNt5Hfhb3mf/QZVxYG1p9gNWVyVAWS8yulZ+NrVm9rD7Ang1Ll8VN9tvLxqWsnpCx32mrfNYult2QF+Np5fNy5InJF6PjbXZ6ZNyZLazTevfdd7NbDdltt93m/AZMeNaxSSU2YDruuOOiN2BCm2O39//6r/9yGJOhv40bN87tueee7uSTT3Yf/OAHG+W1OsEmPN/61rfcTTfd5PxGaJMmTXIHHXSQO+WUU9yoUaNaZW/ce+KJJ5Ld6X/1q185bMSJMdrWW2/tPvOZz7hjjz2W/n9WI3NBJ5oALAikzIiACIiACJSHQOxgCB4PxYCoPGTkiQiIgAj0hoDibm+4yqoIiIAItCIQG3sHZbyLCVFM8mEX9jBhEh7/MAmHybIrr7yy6Y/ZoS7OMWmHDZywg3uYsDs8JhaxY/y3v/3txFZ4P33+yCOPJBN96T/0/va3v3X4hwlG+LTzzjunszZdX3311e6LX/xi00sqmCi+//77k3/f+c533C9+8QuHneZ7md7fS+OyLQIiIAIiIAL9IOAHQ7HHfvioMkVABESgSgRi463Xq1LdVRcREAER6BcBH1NjjkPl4wknnJBMjvlJsvQRk11WOuussxqTfzvssIO77rrr3OzZs5MjrpEw6Xb22WdbJhze3j/44IMbk3+HHHKIwxuFmMzDm3xjxoxJ3rY+/vjjE7ll6JVXXnEHHHCAw+Qfvmg4/fTT3b333pv8wzlkr732WqLz6quvWmbcrbfe6r7whS8kk38bbrhh4gN8gU/wDQl1hM/Wlwem8Zw39AZgTmBSFwEREAEREAEREAEREAEREAEREAEREAERyBLABNt2222XvdFG8txzz7mLL7440dppp52SiTb/mTY+/z3wwAMdPh+eM2eOu+iii9znPvc5t8UWW2Ss4u0+vFmHdOKJJ7rLLrusoYM39fbdd1+34447Oixdgk+Bn376afr5LSYj/VIDP/jBD9ynPvWphp2PfexjiY1Pf/rTbtGiRcmE5LXXXtu470/w6fv06dOTZTXWWWcd98ADD7jNN9/c33b/8A//4E466ST3H//xH4nP3//+990//uM/Nu4XfaI3AIsmKnsiIAIiIAJ9JxDzV9BQp+8OywEREAERGHACYUyNOR/w6sp9ERABESgFgZh463VK4XALJy699NLGOskzZszIrB2+1lprJWvowQTW97vkkkuoNT+JOHLkyGSiMK2EScMvf/nLifiFF15wP/3pT9MqyVt/WDsQaZ999mma/PPKhx12WHIP15i4S38mDDls47NjJJQZTv4lwtX/wWTm+uuvn1zivJdJE4C9pCvbIiACIiACfSHgBzqxx744qUJFQAREoEIEYuOt16tQ1VUVERABEegbAR9TY459czKiYPh/8803J5rYGGOXXXahuSDfaqutknvQR74w4S1CvNGHhAk6TBqyFL5lxyYAf/aznzU2wzr66KOZiUTm7WDtQuRJJ6wP6JPX9df+CB/hK9JTTz3lUIdeJX0C3CuyshtNwAcrn4Ht8IR7TG59I58OBMgf7rCEayS2GxXkbAcjtlMX290Q+dlOX9ZOjP61ZuTziZVv7SbF6uBfVfb2cLR8xboF6cR8Suv4a7ajp9Uu2L0pnRhX1tbIx3bvYuWny2h1zVhb+qwPQZfZYPViu7IhP+PF6sVsIj/bgYyxgi7rm2y3OctX1jdYfrYDnlW+9cPsn2Or78OeldJxxdKD3JfTSqdq99K7ALM4gjqzfmTxYrqsH69cuZLiZPmtsqiBHgitZ37FihWZ0t54442MzBrAYWHqdHrsscfSouSa9X8W49kOvDCAz01ikhV3WRtauowXiw9WLIvxs5UOi1tMBhssbjOZ9dvJ6mr1V+YDK4vJLF9ZWUyG/EzerizkYXWEPSshDyuL6cfqsbyDKkNfsvpTWCc2JsjDi+kyWVhmu/Nu87ezH963+h2Lu9hFM51YzIQOG4ezMQ10WRuwHWCZHvKzuMvGX0yG/ExucWG7Sef5PWVty2Twi6U8uswvtgvw8OHDWVF0x2NrTMF+ZxhDa7zK+gv77WN1gvOsb1isQnl4TiEQIfLE5IvRIeaHTDRv3rxkZ1wUiM98WyXcf/bZZ5NNQbAr76abbtpQ95/+QtDKztixY93kyZOTyTZ8lptOsXbCMmAHG5iEydvBpCXKtBLsYGMTJNiBb71IegOwF1RlUwREQAREoK8E/GAo9thLZ7FOyTnnnOP23ntvN2HCBIfBJgaW+GHHXxT9wCDWBywYjEWCvS0ccQ25kgiIgAj0i0BsvPV6/fJT5YqACIhAlQj4mBpzHKp633DDDW7bbbdN3r4bMWKE23LLLd1RRx3l7rrrLtMFvPnmE94AbJXC+/5tP6/fiR1s9pGeTPZ21l133ZYTdxtttFFj0j/tCya4YRsp9Nn7Gh7D+2k7oV6353oDsFuCyi8CIiACIlA6An4QFOMYdHuVdtttN3ffffdlzOOtzeeffz75hwWDjzzySHf11Vc79raUz4y/XOOvirNmzfKi5LhgwYLkL6D4xODYY49N/nrI3jhqyqQLERABESiYQFnibsHVkjkREAERKDWB2NgbjnfZF2DpSuIPzJ0mP3nm82OdPfz73ve+5w466CCHsS8m1sIU7qLbruyNN964kdVPsHlBJ3bABvn8p8Ww5e208wW68OfJJ59sTPZBhuRt4LydnVZ1Qv6ikiYAiyIpOyIgAiIgAqUiEA50+uWY/zxp3LhxyeLB2DFsk002ST4Neeihh9w3vvGNZPIOAyJ8hosdxqyEncj85N8OO+zgTj/99GQh4RdffNF9/etfd48//ribOXOmw6f2559/vmVGchEQARHoGYEyxN2eVU6GRUAERKCkBPLGXuyE2y7ltQl7WNYHO/V+4hOfSN54wxcvWLbknnvucVdccYVbsmSJwx+sp02b5u644w6HJWl8Cj/zZ59gez0cw8/E05+RF22nnS+hP73yJax7t+eaAOyWoPKLgAiIgAiUjgAGLbEDl1i9TiqJ1/kxGXfooYe69Ho0WMT4s5/9rJs6dWqy/sh1113nvvCFLzi8NZhOWEvO72i20047uXvvvbexM9qUKVOSwRbWDsHnxtg97HOf+5zDDmdKIiACIjBUBMoSd4eqvipHBERABMpAIDb29nK86zngq5T11lvPXzaOe+21l5s+fbrbd999kz9YY0Lw8ssvdyeffHJDJ1y/s9UXMcgQrt2YXqu4aDvtfAn96ZUvDUgFnGgCsACIMtEdgfQiqUUspso8yhP0mC77pC79P/S+3DAoeZkVPJgNVhZbEBi22cLvbIH59F8kvF+srmyRXOizevkty709HLHWA0tMl9U1HTy9LVYvlt/rp49sowMrP+OStuevGS9WltW3vZ3wyBZot3xNP0Owk8d/5pfVX9kC5kyX+R/WLzxnz0Ce+6GuP0f9YxnE6nnbeY633HJLS/XRo0cnbwEecMABid6NN95IJwAvvfTSxoYcM2bMaEz+eeP4iyvku+66a6J3ySWXuMsuu8zfzhzTfKz2svpcxuBqAbPB+iZ7NmCPPUe9bBtWh1gZi1HscxoWn1EGqxerP3TDv47jGon9HjA96I4cORKHpsSe+fAv5qEy84vlRx7W3kzXWnif9aHQl3bnebiyspiM1Ql+sH7MyocuY8ierXaxELZ8ssry98MjqxcrH3m8bh77vizkic0Xq+dtV+GIfhD2BatvMTZMVgST0J9W9ny/aKXT7l5sHSw9FnfZJmhssw74xmKk9cwxORsDM5soi20CwvJbm6Cx55PVH2UxBizuWlyZnMlQVmw/sPo2i5uwm07hBE54jzFgMuRhbcP6u+Ury89+u9jGICif2WUy6Ka5WvyhyxL0Y/KEOrNnz3ZYu67oxCb/fBkbbrihwzgXfxxHX8C4NZwADMc2rF97OziG3NPtkrYTXoc2Yuxgk512voR22vmSLj+8blWnUK/bc20C0i1B5RcBERABESgdAT8Yij32swJ77LFHo3h8zptOqMPNN9+ciDFowpuDLEHu1y6BfjjQg/7cuXNZNslEQAREoBACsfHW6xVSqIyIgAiIQM0J+Jgac/SoMPmHNela/fO6RR4322wzh7cBkbAmoF8qB9fhCyTWiyvQQwo37Eh/olu0nXa+hP70ypek0gX9RxOABYGUGREQAREQgfIQiBkEhTr99Dz8ix9762DevHmNARI+822V/H18gjF//vwmVfy1V0kEREAEekUgjKkx573yQ3ZFQAREoE4EYuKt1ykDF+wO7BPGqz6Fm2SEm2f4++Ex3Pgj3DwDOp3YwVuYYb7QTjtfoOv9Sfsyfvx43E5SOzveBpTTdt6zUMx/NQFYDEdZEQEREAERKBEBP9CJPfbTdayD4tM222zjTxvHcCc1vAHYKoX3n3766SZV7DqsJAIiIAK9IhAbb71er/yQXREQARGoEwEfU2OOZeCS/uTZ+xRODD7zzDNeTI/h/fTYuRM7mHALNxZBod4OlhV4/fXXqR8QYgkYv+RL2he8jegn80KfmbHwftoO0+9UpgnATskpnwiIgAiIQGkJxAyCQh1fEfyI4y90rf553SKOWI/mggsuaJg67LDDGuf+JPyLYfqvk17HH/0gA9fhXxJxzdaog1xJBERABIogEMbUmPMiypQNERABEag7gZh463XKwCr8w/a4ceMaLm266abOX4d/HG8oBCfYDA8Jb9hNmjQpOff/+ehHP+pPk92HGxepE0zqYZM9JGzIl06xdkJfW9l59tlnW04ktrOT9q/Ta20C0ik55SuMABbWDBe7tRZIZQVaf0HoVjf0x9timx+wz/Wgz/Ij8LLEFqRlMragL+wxXbZYKZPlyQ9dtiAuq1eeRY3ZBhKWr4yr1QcYl9jFh1FXlphNpgcZ68eMlZWf6Vp1ZXLGFWWxPsv6llVXtog1K4u1lVVXS+5t+KOlx+Tgxxhaul6+8847+1PzGGvXNBDcwGYd/tPcQw45xO24447B3fdOw80Z0muLpJXDv16m1ywJr7uJu+ky/TXrh4wVk3kb6SOzmdbx13ns+jydHtnz7f/6G9oM2y6UM1+turJnji0wv8EGG4RFNM7Z4tfsmc/jK/MfBbJn1dJtOBicMF0mQxYmZ7LAfNMp483a1frdyFMW02VlMT04zbgy/5kM+Zmc/RaEZVm/AdCxEvy36pDOE6uXzjfI11juIXz2wvN29WJtaOVhuhZvJmf5mcwqfyjlrJ9azywbW1r1YmN+9hyGv7lhvdm4iMVy6zed1YHFcpQZ6ytr69DnTs/ztAHTZZt4sPgI/yw58z1W1+oD7Plk/x/E+MMfyy7ztVsZ2jamfWN0uvWlXX4sa3PHHXckaptvvnkygefzgNm0adOS3YHxNtzDDz9M172G3L8tB/0068mTJzu8QYcvYX70ox8lm+2x/ze99tprfdHu4IMPbpz7kwMPPNCdcMIJyf9rf+c733Gf/vSn/a2mo7eDGIE86XTQQQe56667LhFD98wzz0yrOGw2Al+R8OYh6tCrpDcAe0VWdkVABERABPpGwA+GYo/9cBR/6fODgDFjxiQDHuZHuBse+5+KME/4PxjpQXW41mCYR+ciIAIiUASB2Hjr9YooUzZEQAREoO4EfEyNOfaS1c9//vOmP3Kky3rjjTfcoYce2thV98QTT0yruFNPPbXxssL06dNdeiyLa8iRMPkKfZb++Z//ORG/9dZb7vTTT8+oYNO9r33ta4l8iy22oBOAY8eOdZ/5zGcSnV/+8pfJDsZpQzfccIPDPaTPfvazDnnSCZOL2PwECWWyDf9OO+00t3Tp0kQH571MegOwl3RlWwREQAREoG8EMBDKm/A2HnZG63V68sknk8EG/sKMv+pjAIFJQJbCv/qzNxjCPOEk37Bhw8JbLpwcbLqhCxEQAREoiEAncbegomVGBERABGpLoAyxFxNzeHsVk3y77rpr8mkuxqJvvvmmu/vuu92VV16ZnKOR8HntSSedlGkvvPmGCTAsjzNnzpzk09wzzjjD4W1BTJxdeOGF7vHHH0/yQW/LLbfM2IDgqKOOctdcc4174IEH3GWXXZZ8evv5z3/erb/++smXN1/96leTdfvw1t63vvUt+iYt7Jx33nnuv//7v93ixYvdEUcckfj0yU9+ErfcLbfckrxdiHN8hXHuuefiNJPw5uiMGTPcAQcckJSJz4TPPvtsh6+OMOl39dVXux//+MdJPnDBRGIvkyYAe0lXtkVABERABPpCwP8VNKbwcNCEyb926+zF2Gylg88f9t577+RHH5/hXX/99W633XYzs2ABYZ/Cz3i9LDyuXLmycZn+tCh93VDUiQiIgAgUQKDTuFtA0TIhAiIgArUlEBt7w/Fur2AtXLgwmezChJeVMEE4c+ZM8w/TmHRbtGhRMoGHyb7DDz88Y+qYY44xJ9ygjPH1TTfd5Pbbbz/36KOPJhNsfpLNG8Mfxr/97W+7fffd14syR6ytjTcb8Rkv1gzEBCT+hQlv/aGsVv//AD+uuOIK98UvftHhTUj/FmNoBxOCP/3pTxtvQIb3ijzXBGCRNGVLBERABESgFARiB0NwdigGRB4KBkZ77rmnwxFrluCvk1i/pFUKBxThhiAsT7jxR7ghCHSH4s1G5pNkIiAC9SBQ1rhbD/qqpQiIQF0JxMbeXo93v/vd7yabbjz00ENu7ty5ydt+WB8Zf4DGmPQjH/lI8mYe3g5slfBW3qxZs5I3Ca+66qpkAg9vEY4ePdpNmTLFHX/88S0n7bxt6D/44IPJG3Y/+MEPkjUB8YdybDTyiU98wp1yyinugx/8oFc3jx/+8Ifdb3/7W/fv//7vyUTf/PnzE11sWoIxPD5DHjVqlJnf38AbiKg73jj89a9/nfy/ANYRxXqF+NT42GOPNd9E9DaKOGoCsAiKsiECIiACIlAqArGDITjd6wGRB4PBy1577ZUMiiDDX0ePPPJIf9s8YjFgn/yix/46fQzvY0ARJusziVBH5yIgAiLQKYEyxt1O66J8IiACIjAoBGJjb6/Hu7vvvrvDv6IS3prDv24S1gnERh74103CZCI+G8a/btJ2223nMKnZz6QJwH7SV9kJAawVEO6sxXaIgiILWuldfzxSJg/L8HpMhnssP5Mxn5Cf7TzFdvSCLttlitm18jM585XJUD5jwHyCLiuL7XyJBVdZYjswsd0src8cw/XNvH3mE+6xNmBcmQz5mZzZhC5jy3YFs3ZdZHLWLigrNln5ma9MZnENPzH1vrTbmMLr4cjshptchLrersU91E2fo/1YG6b1cB2rx/LGyt5++223zz77uKeeeirJgrVN2NonzB7+woi/VuKtQWwc0irde++9ye3x48cna6+EuuEOx3jGw3a3nvkwvz8P83lZnqPVN5kNVhaTIS/rW0PRtt5v9ttVRPmsvulFseGD9RwxOYtPLL7CLqsD8wm6LLH4xmTI28mzHpbJ+harK/IwH1hdLZ/yPDOhj63OWR+y9FldWZ2QP4+ut5HHF+8j+DGG/n54jNUL8wz6OWJU2J/C87BujH2veMU+y7F6qEevfGU7sLK1bf3YIWSKc8absYZunmcG+unE7DK/8sQRZhPlsraJlVn5rbLS9cQ1Y2XFXSZnZeXpQ5YukzMZY8XqCRnz38dMK89QyFEvVrd02TE66Ty6rh4B7QJcvTZVjURABESg9gT8YCj22Etg77zzjtt///3dY489lhRz1llnOSxoHJswOPWfCeMNv4cffphmhdy/AQj99KDW70BGM0soAiIgAl0SiI23Xq/L4pRdBERABERgNQEfU2OOAiYCmgBUHxABERABEagcgZhBUKjTKwDYtffggw9OdiFDGVhvxNolrJUPWF/E/5UZCwen3wDDtV9QGH+hhr6SCIiACAwlgTCmxpwPpW8qSwREQASqSiAm3nqdqjJQveIJ6BPgeFbSFAEREAEREIFcBI444gh3++23J3k+/vGPO+xa9sQTT5g28InQ5MmTM/chO+200xw+HZ4zZ46bOnVq8hbh5ptv7l588cVkRzLslIYEPa33l0EogQiIgAiIgAiIgAiIgAjUmoAmAGvd/Kq8CIiACFSTQJ6/dEK3V+knP/lJw/Sdd97ptt9++8Y1O5k4caLzu4ul75933nlu0aJFyc7BmOw7/PDD0yrJBGMnbxhmDEkgAiIgAjkJlCXu5nRb6iIgAiIw0ARiY28vx7sDDbBmzmsCsGYNXsbqxgat9HpWreoSuyCt/6QubYsFSLZILVtQGLbYout5FvpN+4NrKz/zi9WLMYFdpssWVYYuW2SfyZYsWQL1TGJcR4wYkdHDmmksrVixIiNmrKFk8UobsPoV85Wxhj22MDXb3GSDDTZIF59cY2epdGLlsw1XkI9xsRiyPssYsPJRFrPL+tawYcOgnkmsv1ibD6y55ppJfut+xngggP9WHQK15DRWL51vqK/BedasWe7QQw9NdhB79NFHHXYWRv+ZMmWKO/74492+++4b5RY+Ew7bjfULGMrDhumy+BKWGzrL+qGlG+bz56wOTOb1+3lkdbX8YXEHn5anEzaaYYnlZwuZsw1+YI/lt9qFyYcPH55xy6o/K8vSZX1r7bXXzpTF4iuUmJz9nuAZY2nZsmUZMYuPUGL1ymRuIWDPFlO3WDE5k8Ema0NWFpPBz1hfY/VYOYMqQzwK6231i1DH15XJ/L300WrbtF4Zrlm9rD7I4hYba7AxGerK7DIZdFlZTAZdllgsYGVZbcU2w2M2UXbseJeVz3yHjLUL5LFxl42BkZ9tBsh+z1j9kZ/FaGuMyLgw3kyGsphfrCzmE/JbzzfuFZ3QXlabhWXF6IT6Oq8mAU0AVrNdVSsREAERqD2BMgx0euHDfvvt5/BPSQREQATKRqAXMa9sdZQ/IiACIlA2Aoq9ZWuR8vqjCcDyto08EwEREAER6JAABkKxg6FYvQ5dUTYREAERqAUBxd1aNLMqKQIiUDICsbFX492SNVyf3NEEYJ/Aq1gREAEREIHeEYgdDMEDDYh61w6yLAIiUB8Cirv1aWvVVAREoDwEYmOvxrvlabN+eqIJwH7SV9kiIAIiIAI9IRA7GELhGhD1pAlkVAREoGYEFHdr1uCqrgiIQCkIxMZejXdL0Vx9d0ITgH1vAjkgAiIgAiJQNIHYwRDK1YCoaPqyJwIiUEcCirt1bHXVWQREoN8EYmOvxrv9bqlylK8JwHK0Q629wO5L4Q5M1i5VeXZTYjbCMooCbu0wyeRs5yj4ERuMLT1WV1Y/q/5sRy9rBzVml+2y9e677zJVx3ZNZDt9WazYLpVsly5a+GphLCvkZ7ys/GxXs3HjxmXcWH/99TMyCFjfZn3I74pLjaSEFhcmjy0fRbD2ZvlZOcjP+tYHPvAB3Mokvxs12zk4o5wSxA6GkM16tlImK3UJ5mF/ttqLtW0eEIxtWG5oi+2wyPoGswk7zFcrljDd0Jd25yw+tMsT3u82P3sOrZ0IWdxgXJgMPjNfrTZk7eWf47D+Fn+W3/o9WW+99UKTyfnEiRMzMhZzoMR+e9iO6iwWIz+za3Gx6gs7MYn1+ViZZZ+1K3S93B+t/EwOn5hfli6TV1mGfhDyCc/DelvyUKfVebf5mW2rD7N+0m35zCbzCTLmF4uP0GXxhcmgy+ImK8san7DfVLajuBW3mZzJ4KvlA+6FyYpPjLfFkP0/w5gxY8JikvOxY8dmZBCw33nGisVn5Ge73TOu0GVcmMzqr0yX/R4w/1G+ZRf3ik4oK6a8GJ2ifZO98hHQBGD52kQeiYAIiIAIdEkgdjCEYjQg6hK2souACIjAagKKu+oGIiACIjD0BGJjr8a7Q982ZSxRE4BlbBX5JAIiIAIi0BWB2MEQCtGAqCvUyiwCIiACCQHFXXUEERABERh6ArGxV+PdoW+bMpaoCcAytop8EgEREAER6IpA7GAIhWhA1BVqZRYBERCBhIDirjqCCIiACAw9gdjYq/Hu0LdNGUvUBGAZW0U+iYAIiIAIdEUgdjCEQjQg6gq1MouACIhAQkBxVx1BBERABIaeQGzs1Xh36NumjCVqArCMrVIznxCMwoV12WK0QGItXtsNrrDcdnaYX0wGO2yRWCaDLgvGTGaVxeSsXkxm+coWN4cuW7yX1csqiy3mbumivHRifYD5lM7nr/Nw9XnCI2ON+0zOFmteunRpaK7lOasrk1lGWF2hyxZ2Zm1o5Wd1ZW3I6o/y2WLJ1uYDXs78g612yapDu3x1uA82IR/Wrnk5hPZ8XiazymL9my04zmQoj5XF+rul630Oj8wn3LfqEObFOXs20jr+2rLJfLB0va3wyHxgXIYNGxZma5wzufVMMl9Zu7CNQVAga1sfBxoO/eWE1euVV15JqzkrP1vgnfnK6pQppI2AtRcryzLD8jNdxoTpQWbZ9PI8tsIy8tQrzFeHc/Q5zxf17ZRxlViFPHy98jxz7DlmNi3eVllMzsYvbHM6lMXGuyy/9bywGMvq6pmlj4yBVRaTMxnKYHbZONzaXGX48OFpV2ncHzVqVEYPAraZoBXjWdswrlZdY9vLys8qYOmGXC0dZi+UdZovtKHzehDQBGA92lm1FAEREIFaEcBAKHYwFKtXK4CqrAiIgAjkJKC4mxOY1EVABESgAAKxsVfj3QJgV8CEJgAr0IiqggiIgAiIQDOB2MEQcmlA1MxOVyIgAiLQCQHF3U6oKY8IiIAIdEcgNvZqvNsd56rk1gRgVVpS9RABERABEWgQiB0MIYMGRA1sOhEBERCBjgko7naMThlFQAREoGMCsbFX492OEVcqoyYAK9WcqowIiIAIiAAIxA6GvK6oiYAIiIAIdEdAcbc7fsotAiIgAp0QiI29mgDshG718mgCsHptOpA1Chc/Dc87rQyzwYIek1llsgWBmQz5WflskVyrLOYXkyE/k7OFpdnCt8jPFl2HPDaxulo2Yxnkyc8W6YXvTM4WUGb+Iz9rW4shK2vFihUw05RYu0DBWiy5KfPqC4sLW9DfKov1FyZLl+2vma+MoVU+kzN+KM/r+qP3IeaIOsXWK1YvptxB0UkzZf0ddUnrQWbxYvJYmWWXlW/FEfZ8sA0srLIgTyfrmWfPnKWbtolr9sxYbcDqxTZqYouro6x11lkHh6bEbFpcmV8svqEAtvA9y7/22ms3+dPqwtpQiC3w3ot2aeVb+h7rr2mdTq5j4y573qzyeuEryo/1IVbP8r8KchYHUK88bJgNlp/JUBbLz2TsObbyW32L2WCxiOmhLGbX2gAC+unEfg/Ys4V8LJawWNRu/BL6kKeuYT5/ztoF95ivjJW3082R+cDKYnool/1Osd8zxgr52QZSixcvxq1MWrRoUUbGfqetZ4P5kCd/pvDVAqtvh3L4w8ph9rwMeax6eB0cY3RCfZ1Xk8D7q1kt1UoEREAERKDOBPxgKPZYZ1aquwiIgAgUQSA23nq9Isq0bMyZM8edc845bu+993YTJkxIJg4w8Tx58mR39NFHu/vvv9/K2pBfe+21yQQZJjPa/YOukgiIgAj0g4CPqTHHfvinMstFQG8Alqs95I0IiIAIiEABBPwgKMYUdJVEQAREQAS6I1CWuLvbbru5++67L1MZvK31/PPPJ/8wYXfkkUe6q6++Ovot/IxBCURABESgBARiY6/GuyVorBK4oAnAEjSCXBABERABERABERABERABEeiewMKFCxMj48aNc5/61Kfcxz72MbfJJpskn9U99NBD7hvf+IZbsGCB+973vuewNMgPfvCDtoX+8pe/dLBnJbxlqCQCIiACIiACZSegCcCyt5D8EwEREAERyE0g9q+hMKy/iObGqwwiIAIikCFQlri79dZbu/PPP98deuihmbVzd9llF/fZz37WTZ061T333HPuuuuuc1/4whcc3hpslfDp8KRJk1qp6J4IiIAI9IVAbOzVeLcvzVO6QrUGYOmaRA6JgAiIgAgUQcAPiNodiyhLNkRABERABN77g0q7mNvr/wm95ZZb3GGHHZaZ/PPtM3r06OQtQH994403+tPCj2zzscILkUEREIHaE+h33K19AwwQAL0BOECNVVVXsfNgevcjVlc2YGQ7T7G8kHWbn9m1yg/r4/OxXa5wz9p50efzR7bLF+6xwSXzy9pRismZTe9H+sh2ybJ2VWO7dzFd5j/KZQwsfswGy2/tVMb6C5NZfrHd4li/QH7mK+NitQvbBY/JUBazwepl9Ve2gxvrA++88w6KyyTW31j9kdHrWvczxgMB6sTqFag0TmP1GhkqcJLmY/VNJrfag3FkMt+uMRhZfmvXRWaP9U3osf7N6sWeY1YOZFYsYfqMq+UriwXsORw5ciQryo0fPz4jX3fddTMyK2YsX748o8tYQYnFY9bea665ZsYmBCxGsz5g6bKyaEGrhay9mMzKz/xi7WrlZ74yfsjP2pv1Yau/srIsvzwDf7T0mBxMGBdLl8mHSrbHHns0inrxxRcb50WfPPjggw2TeJbDPmI9R0zOZDDMeFu6DUfanIQ+tlGlt61Yxvos07X6a+z4xeq7LMb97ne/o3VgDBnrtdZai+ZncZvZtH7PWF0tLswvJrO4sApYukzO6pAnFrH4xmzCT7b7u1UWqxfr26xfIi9rW9YG1niXtTfjh7LC2I+2Y+VAz0rIw9o8rR+jk86j6+oR0ARg9dpUNRIBERCB2hOIHQwBlAZEte8uAiACIlAAgUGKu+FkEJuEKgBHYuLRRx8typTsiIAIiAAlEBt7Nd6l+Gon1CfAtWtyVVgEREAEqk/AD4Zij9UnohqKgAiIQG8JxMZbr9dbb1pbv+eeexoK22yzTePcOjn66KOTTUDwZhc+IcZagmeffXaymYiVB3KsM6gkAiIgAr0k4GNqzLGXfsj2YBDQG4CD0U7yUgREQAREIAcBPwiKyQJdJREQAREQge4IdBp3X3vttbYFF7nLLj7Nu+CCCxplYr3Adunuu+9uqCxZssTh3yOPPJKsJXjppZe6448/vnE/PImpW6ivcxEQARHISyA29mq8m5dsNfU1AVjNdlWtREAERKDWBGIHQ4CkAVGtu4oqLwIiUBCBTuPuzjvv3NaDIuP0JZdc4mbPnp2Uecghh7gdd9zRLH+zzTZz0Nl1113dxhtvnOjNnTvX/fjHP3bYPATrj2EXYaztddxxx2XssDXLMkoSiIAIiEAXBGJjb5FxtAt3lbXPBDQB2OcGUPHOYTHwmPVX2OLgbJFcMGUBjuVnelab5FmQlS3yyhaetcpiC8cymZWfya265qkXs8vqxRY/Rl62SD3TZW2F/MuWLcOhKVmL/7K+kaeuFq+mwltcsAWMWb+ACeYreyYsn8K1jLxLTIZ7rB8xu6x85GftzXRZu1rls/pD1/tlcYOOlZDX57d0vDxWz+tX4QimIddwAeqwfqy/MFmYJzxnbJkMeZhdq2+EZfjzPP3Q5wmP7JlhzzHyMF9DW/6c+YR7jDd7tqDLniW2ODk+S2Rp0qRJGTHTtRYyf+aZZzL533rrrYwMAragPovnVtxmfcNqA8aW5be4hv3fVyZW5vXTR9ZW0GEM3n333XR2ujkNlFhdWVms/sjP5MynsKw8v5fIh4RyWFnv3W3+b6xec67ur/Dp75lnnpkYGjNmjLv88stNowcffLA76qijmmIllKdMmeI+/elPO+w2jMlBxKkvfelL7sADD3Rjx45tshfGFWy+w579pgyrL8I8/h7rL7jH2pG1HdND/tg+n6e9rDqysphfzH/4yuIu84vZRH4WS6zfGGaX1Wu99daD6UxiMZbV32rXt99+O2PT4sLkTMbKRyGsrpYu65vs94DFLJTF8rNNqVhbIf/ixYtxaEqsfCiw/sLqZW0CYtWhqfDVF7F66XzhNfMrvN/uHG3I2jGdL0YnnUfX1SOgNQCr16aqkQiIgAjUnoAfDMUeaw9MAERABESgSwKx8dbr+eLwNt4rr7zS8p/X7eb45JNPOkzqYYIIf3y+4YYbHCYBrYSJiVb/Y/7JT37S/eu//muSHRPos2bNyphaY401MjIJREAERKBIAj6mxhyLLFe2BpOAJgAHs93ktQiIgAiIQAsCMYOgUKeFKd0SAREQARGIIBDG1Jhzb3KjjTZyWOOv1T+v2+lx3rx5bu+993ZLly5N3ti5/vrr3W677dapuUY+fPbrJwnDjUW8wvDhw/2pjiIgAiLQEwIx8dbr9MQBGR0oApoAHKjmkrMiIAIiIAKxBPxgp90x1p70REAEREAEWhNoF2/9/dZWir27cOFCt+eeezocMVl3zTXXuGnTphVSCN4gHDVqVGJrwYIFGZuY3FQSAREQgV4T8LG11bHXPsj+YBDQBOBgtJO8FAEREAERyEGg1QCI3cthWqoiIAIiIAKEAIutrWTEROGiN9980+21114OG3cgzZgxwx155JGFluPfAGRGJ0+ezMSSiYAIiEBhBFrF2fS9wgqVoYEloE1ABrbpquM4FtUNF9a1BlKhjq+9tXArW/iVLTxrLUTO8jO/mMz7FntkZTGZZS/WB0uPLZCOHwuW2KLCrA2YDPbYouXDhg3LFGUtyow1e9Jp+fLlaVFyzRYQZgtDW3VlcqtdGFumy3yCs8wvZpM9A7Tyq4WsXaHL6hUrQ35WB9YvmAz52WLJTAZdz8CyBR0roU6sXkw/Vo/lHVQZnjHPF3Ww+kuo4+tq6cZyZDZhmz0zTNcqP48ue+by9LPYsljMQ13XXnttHJoSqz8U2PPByrfiLoubTGZxZbp5Fq5n9WJ1Ql1Zu1hlMQZscxTmP8pi9WV+WZ9wsrZlm6CgLLZwPSvLivHMV9hNJ8YEOqysdF5/7desY23hdaxj2eIuNlLYZ5993FNPPZW4fMEFF7iTTjrJcr8jOdoWk4xI48aNy9jAhiE+YSM01m/8fX9k7K1Netguw0zGnkOUx/oM6y9Wfu9zeLT6K/uNYHaZnuVrWK4/t/KzWMLKhx1mg8VYK76wsRKLT1Z/YHat/2dhbcj8ZzKrrpYu+51k43BrHI9P8NOJMbD6EGtDiwurA2OV9sdfM7usXux5hY08ZYX9kPntfbKOyBOTL0bHKkPy6hDQBGB12lI1EQEREAER+AuB2MEQ1DUgUrcRAREQge4JlCnuYsJs//33d4899lhSsbPOOsudccYZ3VcyZeGqq65q/IbsvvvuqbvO7brrrhmZBCIgAiJQJIHY2KvxbpHUB9eWJgAHt+3kuQiIgAiIgEEgdjCE7BoQGRAlFgEREIEcBMoSd/H2FXb7feCBBxLvTznlFHfuuefmqIlz8+fPTzYM2WGHHcx8t9xyizvnnHOS+/ia4eijj87osrebMkoSiIAIiEAXBGJjr8a7XUCuUFZNAFaoMVUVERABERCB9wjEDoagrQGReo0IiIAIdE+gLHH3iCOOcLfffntSoY9//OPumGOOcU888YRZQUzSpdfqwwTgHnvskbzBd8ABB7i///u/d9jwAwnrCd54443JP//7cfHFF7vx48ebZeiGCIiACPSKQGzs9fGqV37I7mAQ0ATgYLSTvBQBERABEchBIHYwBJMaEOUAK1UREAERMAiUJe7+5Cc/aXh45513uu23375xzU4mTpyYvPHH7j300EMO/6yEdd0uueQSd9xxx1kqkouACIhATwnExl6Nd3vaDANjXLsAD0xTtXcUa5tgwVH/7+67726b6bbbbks+k5gwYYLDws844rMJyJVEQAREYFAJ+MFQ7LHTeirudkpO+URABKpGIDbeer1O699J3M1b1o477uj+8z//M9k05MMf/rDbZJNNHCb78Lbghhtu6PBm4XnnnefmzZunyb+8cKUvAiJQKAEfU2OOhRYsYwNJQG8ADmSzZZ3+zW9+4775zW9mbxgS7DaEv1bOmjWrSWPBggUO/2666SZ37LHHuiuvvJLulNeUqcsLDKbCne/CnZBC02xXMrYjF/IgAMYktksX8rEdnVj51g5PrHxmE2VZO13hXpisslh+i2Foz58zXeY/9NnuX2x9Gyu/tUOi98Ufw/7gZTiyXdFY/aHL6sX8hy5LVh2YLmsbVj7Tgz0mZ/ViNpGf1cvShX46sbpazwbz1WqvdDm4ZmVZvvrdKFmZzHYoQzmsrFDHn8fqeX1/HOS4i/YNubL+hnoyOZNBNzZGWrGQ7a4XaxPls35k9ePYZ8aqa8gOZSMxmfUbxZ4Zqx8yLkzGdleEXy+88AIOTYntpMhieVOm4MLiynZNZO3CWME8Y8DaKnCl6ZTVi/UhZFp33XWb8uKC7dJptSGrq7VTK6sD61uWrz4Whg6z/BZXVj6Twb73gbVFWD47R57YfLF66XJi4m5oG/2PjXdDu3vttVcSP0KmI0aMcJ/5zGeSf6FuN+foc+E4hj3Hln3WN6GLtQdjklWW1Q9ibEKHPd9WjGf9M2yrdmWG7eN1WX7fh72OPzJd5j/0WR2YrvXM+52hfdk4jho1KrxMzq34wp55q61Y21q6GQdWC7ptF1aWxYX9drD2YjL4ztqQlW/psvx/+MMfoJ5JTJf1AaYHY4wrk1m6GYdaCOCD5UeYLUYn1Nd5NQnoDcAKtCuCEQY3+LHy65O0qxZ2Q/OTf1jg+LrrrnOzZ89Ojn7B45kzZ7qzzz67nSndFwEREIFSEvADonbHTpxX3O2EmvKIgAhUnUC7eOvvd8JBcbcTasojAiJQBwI+trY61oGD6tiegCYA2zMqvca3vvUt9+ijj7qtt946Wei4ncPPPfecw2LFSDvttFOyS9rhhx/upkyZ4nC8//77EznuX3TRRfTtAdxTEgEREIGyEmg1AGL38tZDcTcvMemLgAhUnQCLra1keXko7uYlJn0REIE6EGgVZ9P36sBDdWxNQBOArfmU/u7LL7/s/uVf/iXx84orrkjWJmnn9KWXXtp4tX3GjBmZzwfwmQHkSHirEIsbK4mACIiACLxHQHFXPUEEREAEhpaA4u7Q8lZpIiACIiAC1SSgCcABb9eTTjrJYV21o446yu2+++5ta4O/Atx8882JHt4Y3GWXXWgeyLfaaqvkHvSRT0kEREAEBoVA+i+e7a7z1EtxNw8t6YqACNSFQLs4m76fh4vibh5a0hUBEagTgXRsbXVdJy6qKyegTUA4l4GQ/uhHP3K33HKLGzlyZOOT3naOY7eyhQsXJmrtJgxx/9lnn002BZk/f77bdNNN25nv6D4WwA0XwWULa8MwW3iVyaCLwJdOTGYtxmrZTdu0rpldtqAw8rPF4JndPD6xuloL6jJfWfmQsQWYWX6rrqxtWf2HDx9OXQgXz/YKVr0YL8bF24k5srpa+Zgu8wn5mdxiyMpj+a26Mr+YjNm0fGW6rK8gP/OLlQ9db4PZx/1WCeWwslieWD3krUrcBfOQu8WYsQnzhTx9e4Uy9nxaC3YzH1hZTIYyWX6rLGaD1TWsS3jO8jMZq39oJzy3dNli6la9Qnv+nG2+9Pbbb/vbjeMGG2zQOA9P8iwwz+IWaxerrnnagOmy8ln9UT9WL7bwPvuNsvKztrJ0GQMmQ/5wjIRrK7E+CF3WX5gMun5BfOs+dKyENmHtwvRj9ZC3KnF37bXXbvrqhj2HqK9vA5z7xPq2v5c+sn7E4jPysU0Z2DObp71YfpRl+YB7MYnlZ30+j6+WLpMzGWsr1IU9s2wMbNU7T71YLGNtwGxa5eeRMy5W/IjVZW0Nn1gdmAy6rA0gTyfGCjpMzmRW+ayulm74zLIy0j6nr1EWK4/ppWW6rh8BvQE4oG2+bNkyd8odyJivAABAAElEQVQppyTeX3jhhW706NFRNXnqqacaengDsFUK7z/99NOtVHVPBERABEpFwA+GYo8xzivuxlCSjgiIQF0JxMZbrxfDSXE3hpJ0REAE6kzAx9SYY505qe7vEdAbgAPaE04//XT3+uuvu6lTp0Zt/OGr+eqrr/pTN2HChMY5O9l4440b4ldeeaVxHnMSlsP0X3vtNSaWTAREQAQKIeAHQTHGoBuTFHdjKElHBESgrgQUd7Mtr/FulokkIiACxRKIjb2x491ivZO1shHQBGDZWiTCn/vuu8/NnDkz+XQUG39YrxMzUytWrGiI8SlCqxR+hml9QmPlDycPLR3JRUAERKBXBGIHQyg/ZkCkuNurlpJdERCBqhBQ3K1KS6oeIiACg0QgNvbGjHcHqd7ytTMCmgDsjFvfcmGtjuOOOy75H9YvfelLbrvttsvlS7j+xAc+8IGWecO1cN59992WuropAiIgAmUiEDsYgs/tBkSKu2VqWfkiAiJQVgKKu2VtGfklAiJQZQKxsbfdeLfKjFS3vxLQBOBfWQzE2fnnn++eeeYZt8kmm7ivfOUruX0ON1FgC/+GBsOFbYcNGxbeanve7pNhfBKx8847t7UjBREQARHohEDsYAi22w2IFHc7aQHlEQERqBsBxd1si2u8m2UiiQiIQLEEYmNvu/FusV7JWlkJaAKwrC1D/MLE39e+9rXkzowZM1z4iS5Rp6IRI0Y05O0+6125cmVDt93nwg3Fv5y0W18w1Ec54e5HbDcr6LNdkfIEMraDGrOJsthn1awsJrN8tcpifsWWb/nKds9iMuS35LiXTlZ903rWNdtNMWx7n896O5X5ymx6O90cWRtY9hgXJrNsMl22g5rVh5hfFhfGm+VnrKHH5Mx/ZhMyVr7lq/+DBXtGLPuhPI9fYb7wvKpxN6wjzvOwYn0TNpi82/4Cu+lk+crKt/qO9Symy2L9FTqszzKZVQ57li1d9sc6lt+qK3uD39JN19+qK/MJuqwNLIasLMbAys8YMJvMJ+iFX0T4fGz8YZXPdK2yvP3wyOrK+hDyMB9YWex5Q35WFpNB13P1R8jyJOv5zGOjqnH3jTfecOH4hvVBcMrTt5guez7z9I1O2963sdUHmF3WD5kMtlkdmC6TIT8r3/IV+jGJ2UQ+JmfPLJNZ+Vm7QteygXthylNXi2EeG2HZ/pxxYTaZDDZYjAy/WPPl4Mh2AWb1sn4P2fNptUFYrj9n/ZX5BP211lrLZ0vak/1uNxSME4uZoS5xjQloAnCAGv+SSy5xCDybbbaZe+edd9z111+f8f6JJ55oyO68885koxAIDjjggGTCMJyYa7dRR/gWn9b0a2DViQiIwAAQwEAodjDUSk9xdwAaWy6KgAiUgoDibimaQU6IgAjUjEBs7G013q0ZslpXVxOAA9T8/pPcuXPnuiOOOKKt51/96lcbOvPmzUsmALfddtuGDH9hbZXC+9tss00rVd0TAREQgVIRiB0MwelWAyLF3VI1q5wRAREoMQHF3RI3jlwTARGoLIHY2NtqvFtZOKpYhsD7MxIJKk1g0003dePGjUvqeM8997Ss67333pvcHz9+vJs0aVJLXd0UAREQgTIR8IOh2GMvfVfc7SVd2RYBESgLgdh46/V66bfibi/pyrYIiECZCPiYGnMsk9/ypT8ENAHYH+4dlXrttdcmb6q0erjDjUHuuuuuhr6fwMPaB9OmTUvKxxt+Dz/8MPUFcv8GIPTZmgk0o4QiIAIiUAICreIku2e5rLhrkZFcBERABJoJsNjaStac+69Xirt/ZaEzERABEWhHoFWcTd9rZ0v3q09AnwBXv40zNTz11FPdVVddlSwyOn36dIc3/cJdfrHwKORIWGwV+r1MS5cubZpgRKCKTdbEJFtklsmsciy7aX3LV0uezo9rpssWjrV8itVl5TB/WsksH9J5umVtLWi8fPnydFEu3KwmvMl8YP4zGewwucWQyVn5oX/tzhkDyyZbFJn5b5XJdNmi88jPyrL8YuWxBZCZTeT1XP2R2bNkyBObL1bPKitGXra4i7gRtrvVhkxu8fKfS4c82AL1zCbyxMay0H67c8tXlo+Vz/or8oYL+XtbLD97jqHPGLD80GU2mMxayJwtWs6e72XLlqG4TGJ2rU3Ewj6VMdShwOLC5Iwrk8EVJmf9hdUf+Zkuk0GX+Qp5OrFF59M6/prZZP0C+swvJoOu7y+MD+63SrBp2U3ni9VL58tzXba4+/zzzzf1BYsxe45Ye4MFa3OrzzJ2ll2mGyvrtm1ZfELZbKzAGDIZ8jM5k0GXJVYvKz9rQ5af/UaibBZjsf47S6wsJmN588pi7bK6WmUxXSZDftZfWb+wdFn+cAOO0MdRo0aFl8k525zDituMFZNlCulAAF4Ws9BcjE6or/NqEtAbgNVs15a1mjx5sjvttNMSnTlz5ripU6e6H/7whw7nOOIa50jQ23LLLZNz/UcEREAEBoWAHwzFHntdL8XdXhOWfREQgX4TiI23Xq/X/iru9pqw7IuACJSBgI+pMccy+Csf+ktAbwD2l3/fSj/vvPPcokWL3DXXXOMef/xxd/jhh2d8OeaYY9y5556bkUsgAiIgAmUn4AdBMX5CdyiS4u5QUFYZIiAC/SKguNsv8ipXBESgzgRiY+9QjXfr3BaDUHe9ATgIrdQDH/EK9KxZs9wvfvGLZE1AbAyCT5pwxJp/t956q5s5cyZ91boH7sikCIiACBRKwA+GYo+FFm4YU9w1wEgsAiJQCQKx8dbrDUWlFXeHgrLKEAER6CcBH1Njjv30U2WXg4DeACxHOxTmxb/92785/ItN++23n8M/JREQARGoGgEMhIYiKe4OBWWVIQIiMAgEFHcHoZXkowiIQNUIDFXsrRq3OtZHE4B1bPWS1RkbkIQL/rIFjeEyW9TYWnyXVZEtvGqVxfLnkbFFZln5sJlHl/lg2U3rWqzYD4Zlk8mZXWtBXL+4eOgb29gj7A+hLlt8ly2UjDyMa2jLn7M64R6Ts7pClzFkukzPys90mQz5WbJ0mZzVlclQTrhhkC+XtZe1KDPbPIH1C9j2cvbs+7KtI+rJ6sr0Y/VY3kGVoX+GbZyHgaXL5GEZnhXrL7jHdNlznCduM5tWWcwvVj7ys7oyv5gM+Vl8gJwlVhbLz2Swx54fJrM2VGJ1sGI848XagNUJvlpy3EsnZjdWBlusLIthumxcs7JYH7J0mU0f89L3mK8sljL+aVv+2tL17Z2HhbcJP5mv/n54jNUL8wz6OZ6bsN/0ikFYhmfGZLjH5Kxv5PE1jy4ri/kEX1mfZDLfh5EnTEw3vN/unNXLKott2MHirlVXFo9ZfvjMxluMK5MhP6uXxSpWl+lZZTFdJkN+VgdLl9WB5R8xYgRMZ9LEiRMzMsaabYCGjOz/WRYvXpyxCcGSJUsacqs+DQVygjwx+WJ0iHmJKkZAE4AVa1BVRwREQARE4L0BbexAJ1ZPXEVABERABGwCiKWx8TRWzy5Nd0RABERABEAgNvYq7qq/gIAmANUPREAEREAEKkcgdjCEimtAVLnmV4VEQAT6QEBxtw/QVaQIiEDtCcTGXo13a99VEgCaAFQ/EAEREAERqByB2MEQKq4BUeWaXxUSARHoAwHF3T5AV5EiIAK1JxAbezXerX1XSQBoF2D1AxEQAREQAREQAREQAREQAREQAREQAREQARGoMAG9AVjhxlXVREAERKCuBGL/Ggo++otoXXuJ6i0CIlAkAcXdImnKlgiIgAjEEYiNvRrvxvGsupYmAKvewgNQv+HDhzftYGXtqMXk1u5ZbJcmtruetYOstcNhGifbTQo6bCdAJoMuqwML0ExmlcV2vrLyM655fGX5rZ3KmA8sP9NDXfMkxpXJrLqysixdxpvVKw8XVj7zH3qsfJYfMsaW9WPLJtNda621MsVZu6qNHTs2o2vVy++Whh3WFi5cmMnXSoB6srqyPLF6LG8dZSy+ggNr87/7u7/LILLiK5OzZ4Y9WyiEtaPVt5ic5beeg9j8zH/4yuTs2YIukzOZ5SurFyuf7TqJ8lli9YceK8vyi9ll+ZleHlm3NhlrlM+eA7Yzr+Ur88viynxgv0drrrkmLW7ttdfOyNmzCSX/HP7pT39y1hgpY+wvAtSJ1Yvpx+qxvFWR5WHA+gA4rLHGGhkcTGbFTTY2Zrp5nuOMQ38RsP7NGDAZTLD8VllMzhhaNpkPli4rC89POrG4y1gjH+Ntlc98ZfGJxQGrLOYrdJm/TJfVH/mZLqsXkyE/42KVxXxlzwazibJYPB85ciRuNaVhw4Y1XfuLDTbYwJ82jitWrGichydPPvlk4xK7B999992N65gT9AHWD9J5Y3TSeXRdPQKaAKxem6pGIiACIlB7ArGDIYDSgKj23UUAREAECiCguFsARJkQAREQgZwEYmOvxrs5wVZUXROAFW1YVUsEREAE6kwgdjAERhoQ1bmnqO4iIAJFEVDcLYqk7IiACIhAPIHY2KvxbjzTKmtqArDKrau6iYAIiECNCWigU+PGV9VFQAT6QkBxty/YVagIiEDNCSj21rwD5Ki+JgBzwJKqCIiACIjAYBDAQCh2MBSrNxg1l5ciIAIi0B8Cirv94a5SRUAE6k0gNvZqvFvvfuJrrwlAT0LHvhHAgqzhYtRY8J8ltuA1W3QeeddZZ52MieXLl2dkloAFSLaYLFtQGDaZr5YuW+iWySxfmV22yC5b6Bk2WV2tsthCuSw/04NNxpDpsjohP+MKOUvML2aXLfLL7EGWp11Yvay+zXSZjPHL6ytjyGRsoWSUxRY7Zs8bW/wY+TfeeGMcmpK1MPX666+f6GFzgjlz5jTlaXeB9md9gOWL1WN5B1UWW2f2fFht69srZMLiLha4Zon5xJ4Dpgd7lpyVFSuznnm2wDp7PlksRtmsXswmdJmcxTLLV1ZWHlbMLosZ8DWWQZ7yYbcXidWr23JYu8Am2yiJlc9kyM+eQxY3R40aBfVMGjduXEbG8kPpnXfeSXRxfPHFFzP5WgnQrrFtG6vXqryq3mPPF/udRf3ZpgTYXC+d2LMJnbfeeiutSjd/8ZvDpJVZjLPalvVvVlcmQ7lMzspiMQ/5WSwN//8DOj7F1ovVydtIH1kbMBnysXoxGXSZDyxmsN9o5GdcmU3oMi5MZm12wX7/Wd+y6gofYhOLx6y92bgWZbBNldizZf2/KOO93nrrUfdDLnk3X4JB8IphFqNDHZSwUgQ0AVip5lRlREAEREAEQCB2MOR1RU0EREAERKA7Aoq73fFTbhEQARHohEBs7NUEYCd0q5dHE4DVa1PVSAREQARqTyB2MARQGhDVvrsIgAiIQAEEFHcLgCgTIiACIpCTQGzs1Xg3J9iKqmsCsKINq2qJgAiIQJ0JxA6GwEgDojr3FNVdBESgKAKKu0WRlB0REAERiCcQG3s13o1nWmVNTQBWuXVVNxEQARGoKYHYwRDwaEBU006iaouACBRKQHG3UJwyJgIiIAJRBGJjr8a7UTgrr6QJwMo3cfkriIVmw8Vm2WK0qAVbeHXs2LG0gn4Ra3ozELIFXnGbBUi2yK210DDLn0eXLd5rbcrAygqq2Dhli+ziZsjeKzMZ7rE6xJaP/Mwuk0GXpW51Wd9ii0KjbLZQsKXLFhpm/jN+0GP5wwWBvS1shsGSZZfpsr7FFqi3FjUePXp0xizbFIJt9oGMW2+9dSa/tSjySy+9lOi+/fbbmTztBOiXsX0zVq9dmYN0P82HPRuoD9tUYNKkSbSqixcvzsiXLVuWkVmxiPVjJrPaK098yDi1WsAYsGcDeZmc1Yv5j/xMbtWL+cXqymRWWax86LLEYiGLWcjLNjpiZVkL37Pyu5VZcduSp8uzuDIuTAZ7bMMNJmNtjfxskXr2bG622WZQz6Rtt902I2O/BVBasGBBoqu4m0HWtSAdd62+xTb8YBu5wKF111034xfrW9Z4l21U8Prrr2dsss1CoMQ2e2DjZeiyGMeeQ2u8CxsxyeLKGDAZymCxjPlvxUIW99i4jumhfFYW5CyxuMF+o1i/gj023rO4sPqyTQatjSzYOJb1Ldav4KvFC/fSKZYLqz9sMV5Ml8Vi5N9www1xaEqsv0Mh/P/WXsbePP2qyXFdVIqAJgAr1ZyqjAiIgAiIAAhgkBM70InVE1kREAEREAGbgOKuzUZ3REAERKBXBGJjr8a7vWqBwbKrCcDBai95KwIiIAIiEElAA51IUFITAREQgYIIKO4WBFJmREAERCAHAcXeHLBqrqoJwJp3AFVfBERABKpIAAOh2MFQrF4VOalOIiACIlAUAcXdokjKjgiIgAjEE4iNvRrvxjOtsqYmAKvcuqqbCIiACNSUQOxgCHg0IKppJ1G1RUAECiWguFsoThkTAREQgSgCsbFX490onJVX0gRg5ZtYFRQBERCB+hGIHQyBjAZE9esfqrEIiEDxBBR3i2cqiyIgAiLQjkBs7NV4tx3JetzXBGA92nmgasl2+0UF2C5LbPcy6LIdqdiuYtZOZWznKLYjmLUbFbPLfIKvbLcytpOgtXMUKwt204nt3AUdVldWftqev2blWz8wTM52g2RMUJ7FwPvS7sjqZdlkOyRau6KxvsXKsvxjXNjuqRYXlp9xRfmsviNHjsy4tummm2ZkELBdzVhdrR26N99884zdjTbaKCODwMeCN998k95vJQQTxoXlidVjeasiYzsGom5jxozJVJHtggelefPmZXT/9Kc/ZWTd8raeA0uecWC1gMW9bp/jPOUzBtbvCXu+WNxlzzbqzspiMst/FvdYu6IsVodYmeUr5LGJMWD+wx7rA4wL+y1Afh+fcO4Ts4l7zAe2U7q10yvLz3y1dgH+4Ac/6F1sHNlOsbjpd2VX3G2g6tkJ290ZhbHxLovFlq5vw9Bx1odwn+la48XQnj9nYw220yv0WZ9lZVnPEYt7LD+LmSif7erK6g9dNuZncY/VH/mZr0xm5WdyVleUxfoR2x2axSzkZwwYK+gyG6xe1k62bGzL6sVkKJ/9nrDyoct+01hdN9lkE6hnEovH7PeAsYYxlt/iGv529TL2smcwU3EJKk9AE4CVb2JVUAREQATqRwCDnNiBTqxe/SiqxiIgAiIQT0BxN56VNEVABESgKAKxsVfj3aKID7YdTQAOdvvJexEQAREQAUIgdjCErBoQEYASiYAIiEBOAoq7OYFJXQREQAQKIBAbezXeLQB2BUxoArACjagqiIAIiIAINBOIHQwhlwZEzex0JQIiIAKdEFDc7YSa8oiACIhAdwRiY6/Gu91xrkru91elIqqHCIiACIiACIiACIiACIiACIiACIiACIiACIhAloDeAMwykWSICWCh23ChVrbALFxiC7eyhW+hyxY7tjbhgH46sYV+wwVa0/rpa7Z4b55FkVm9rAVxWVnsLzzWosps4XtrcXDG4J133klX3zF+UGIL9bJ6MRnys8V3w74DHZ+YnMksLqyujBXKY7xYG1oLU//+97/3bjeOjCHzHxlYHRhr6LKNc9jC8dtuuy3UM4ktdsxYjR8/PpMXgq233jojtzaVsJ6ZjAEiiP1rKLKy54WYrLTIeuZY3+4VCNYOTGY9B5ac+cueRfbbw35LYI8tRM4WjWf+M38gs3SZD+z5Zj7BLpOzslh8RX62QQyLWdBliZXP/Ede5hezaclYHVi7WvlZH2L1R34WS1kshC7bPOlDH/oQbjUltkkSFNjvCXtm2cYiyL/VVlvhEJX8Iv3sN6idAbRfbBvG6rUrc5Dvs/6G+rBnno2Bocv6Fuub1nPAdNkzy54tlM/6/GuvvYZbmcT6FKsrG9PAGOszLJZY+dn4ZeLEiRk/IWDP19KlSzO6v/vd7zIyCNgmGCxuMtbIz8b2jDV02cYSTGaNYVl8YflR1ujRo3FoSqxdmM2mTMHFu+++G1y9d8rqjzvsmWF9ALps/MI2uNt+++2hnkkbbLBBRsYElt6kSZMy6tZzGP4/qtV/M8YCAdqAtUOgkpzG6KTz6Lp6BDQBWL02VY1EQAREQARWE9BAR91ABERABIaWgOLu0PJWaSIgAiIAAoq96gexBDQBGEtKeiIgAiIgAgNDIM9AKI/uwACQoyIgAiIwxATyxNI8ukNcDRUnAiIgAgNFIDaexuoNVOXlbG4CmgDMjUwZREAEREAEyk4gzyAnj27Z6y3/REAERKBfBPLE0jy6/aqPyhUBERCBQSAQG09j9QahzvKxcwKaAOycnXKKgAiIgAiUlECeQU4e3ZJWV26JgAiIQN8J5ImleXT7XjE5IAIiIAIlJhAbT2P1SlxVuVYAAU0AFgBRJkRABERABMpFIM8gJ49uuWopb0RABESgPATyxNI8uuWpoTwRAREQgfIRiI2nsXrlq6E8KpKAJgCLpClbHRFYvnx50y6mVnBiO5VZu5KxXcXYLlFWfrYjFds1kskAge0eZu0Uxvxiuw4yPZTFdotiDK2dxtiubFZZbAcxiyF8Sye2exeTWTudsbJYXVEuqwNjYOVnXFn9URbzi+30Ze3ix3aGY36xfoHyWX9nuzNDd6ONNsKhKbFdgJkMmVhdWRtauwBvsskmTWXjgtUVcr8LnVUX6FjJssn08+iy/FWQsR1sUS8mt+Ie6xssFlq8WDuwvmXZtOSsPLZDIdvdkNUJ9lh8Yc8xiyPIH1tX6DIfWBuEuwgin08s7jGuLGbBBosv3nb6yLjkaZe0vVbXrA6MCxs7tLKbvmfFbRbjrDZgumxHdGu3XsaQ/Xaz+I76jBw5Ml0t2oeh5H9n2DOSMZISsH6dUmlc5tFtZKrYCWtDVJHJWRyALtuBlPUD/3uKPGFiu9WytmE7qsIOk1sx48033wyLTs5ZvVh/hzLjwuKutYOs3+E6dAL/D8IS4+WfjVDfKmvlypWhWnLO6spiJpTZOJjlhy6Ts7hv+cp4s/qjLEuOe2Gy+kCo489ZG7L4Dn1WVyvujhkzxhfROLKdea3d09mu0ezZYDtxo8AJEyY0ym13MmrUqIaKVZ+GAjlhfhE1OvZgepJVm4AmAKvdvqqdCIiACNSSQOxgCHDy6NYSpiotAiIgAhEE8sTSPLoRRUtFBERABGpLIDaexurVFmRNKq4JwJo0tKopAiIgAnUikGeQk0e3TgxVVxEQARHIQyBPLM2jm8cH6YqACIhA3QjExtNYvbrxq1t9NQFYtxYvSX3DV97Tr6mH90J32Svi1qeB7PVplt8qi332xl6dT/vu/WWv0zOfoM/sMl3LV/ZJBLNp+crkLD98ZWUxv6z8TM5e82cylM/Ksn7MWFmsrlZ+VlfWLvCLfebHPkVjMuRn/Y31V6aH/CxZvrLP29knMG+99RYz61gdWHtZn4+9+uqrGbtWG7z++uuJ7uLFixt5WB9o3AxOYNOyG6jV6rQVO4sV60esbwIks5/nmbN8SDeSpWfJ0/lxzeIDqyvLCxmrK7Np+cTkTGaVxXSZT8jPdNkzy2Ie8rPfM6ssxiBPH0B5sYnVi5Vl1Su2HCvusvGHVRZbAoTF2DfeeIO6lacNmAH2G2W1ofch/FzT0k2XhTZh7ZLWq9N1K3YWK9aPWH8DR/YJL/v8ktlE/hUrVuDQlNiYgPVhZGJjCiuWMhasbzMZymL5WcxhMiu/9XvGxjqMoRUfmC7zi8Us+Mr6Bstv1Yu1gVVX9rky6wMoi32aDHk6WVxYf2N9yPKV8WJ1hT/smWH1WrJkSdr95JrZZe1CM68WsvGupfvaa681bi1atKhxzvp842ZwAr/y+BZk1WkNCWgCsIaNXoYqh/9Dn16Tgw2K4fNLL71UBtdr4YM10KtF5WtYydtvv31gao3YwdZwGZgK9NHRMO6m3bAG6//7v/+bVu37NfsfADhlyZnD6d8d6DAZy9srGfsfRpSl37544ux/Lpks3mLvNL///e/3znjBlhV3OwfaKu5az/zcuXMzBTJZRkmClgSWLl2aub9w4cKMbNAE7P+bXn755UGrhvwlBBR7CRSJuibw/q4tyIAIdEDA/4W5g6zKIgIiIAIi0AEBxd0OoCmLCIiACHRBQHG3C3jKKgIiIAIiUDgBvQFYOFIZjCEQ7n734IMPOmsHphhb0hk6AnhFfeedd04KnD17Nt1Rdui8UUkxBKrQZvgEwr9F8aEPfcis9tixY90rr7xi3o+5ARtVTYq7g9myVXiGB5N8515Xoc0Udztv/zCn4m5IY3DOq/AMDw7tYjytSpsNVeyt8ni3mB5VXSuaAKxu25a6ZuH6JJj8y7NVeqkrViPnNtpoI7XbgLX3ILdZzGe/WJtGscTulIq7NptBuTPIz/CgMC7az0FuM8Xd7nuD4m73DPttYZCf4X6z61f5g95mir396jn1KFefANejnVVLERABERABERABERABERABERABERABERCBmhLQBGBNG17VFgEREAEREAEREAEREAEREAEREAEREAERqAcBTQDWo51VSxEQAREQAREQAREQAREQAREQAREQAREQgZoS0ARgTRte1RYBERABERABERABERABERABERABERABEagHAU0A1qOdVUsREAEREAEREAEREAEREAEREAEREAEREIGaEtAEYE0bXtUWAREQAREQAREQAREQAREQAREQAREQARGoBwFNANajnVVLERABERABERABERABERABERABERABERCBmhJ436rVqaZ1V7VFQAREQAREQAREQAREQAREQAREQAREQAREoPIE9AZg5ZtYFRQBERABERABERABERABERABERABERABEagzAU0A1rn1VXcREAEREAEREAEREAEREAEREAEREAEREIHKE9AEYOWbWBUUAREQAREQAREQAREQAREQAREQAREQARGoMwFNANa59VV3ERABERABERABERABERABERABERABERCByhPQBGDlm1gVFAEREAEREAEREAEREAEREAEREAEREAERqDMBTQDWufVVdxEQAREQAREQAREQAREQAREQAREQAREQgcoT0ARg5ZtYFRQBERABERABERABERABERABERABERABEagzAU0A1rn1VXcREAEREAEREAEREAEREAEREAEREAEREIHKE9AEYOWbWBUUAREQAREQAREQAREQAREQAREQAREQARGoMwFNANa59ftU95deesn90z/9k9t6663d8OHD3ciRI92UKVPcRRdd5N55550+eVW/YufMmePOOecct/fee7sJEya4NdZYw6299tpu8uTJ7uijj3b3339/Lii33XabO/jggxu2YBPXkCv1nsAZZ5zh3ve+9zX+3X333W0LVZu1RVQZBcXdcjSl4m452qEoLxR3iyJZTTuKu+VoV8XdcrRDUV4o7hZFUnZqS2CVkggMIYGf/exnq9ZZZ51Vqx84+m/15NOq559/fgg9qmdRH/vYxyj/dLsceeSRq/7whz+0hPR///d/q4455piW9o499thV0FPqDYHHH3981d/+7d82tcFdd91lFqY2M9FU8obibjmaVXG3HO1QlBeKu0WRrKYdxd1ytKvibjnaoSgvFHeLIik7dSbg6lx51X1oCTz22GOrhg0blkxSrH7TbNV555236sEHH1z161//etXnP//5xuQFJgGXL18+tM7VrLTNN9884T1u3LhVp5xyyqobb7xx1ezZs1c99NBDq775zW+uGj9+fKM9jjjiiJZ0zjzzzIbuDjvssOq6665LbOGIaz+p+OUvf7mlHd3sjAAm81a/QZtwHjNmTIN3qwlAtVlnrAcxl+JueVpNcbc8bdGtJ4q73RKsdn7F3fK0r+JuedqiW08Ud7slqPwi8B4BTQCqJwwZAf9XOLyphIm/dPr617/emLz4yle+kr6t6wIJ7L///qt++MMfrvrzn/9MrS5evHgVJmL95N0999xD9Z599tnGm2c77bTTqtWfcDfprVy5chXksIN219udTXgKubjkkksSvqs/qV+FSVbfZtYEoNqsEOwDY0RxtzxNpbhbnrbo1hPF3W4JVju/4m552ldxtzxt0a0nirvdElR+EXiPgCYA1ROGhMAjjzzSmJg4/vjjaZn4y84222yT6K233nqr/vjHP1I9CYeGwM9//vNGm02fPp0WesIJJzR08PYgS5D7SakTTzyRqUjWIYHV6wutwtu04Lt6zb9VmDj3rK0JQLVZh7AHMJvi7uA1muJu+dtMcbf8bdRPDxV3+0m/s7IVdzvjNpS5FHeHkrbKqjoBbQKy+v+WlXpP4KabbmoUgg0mWHr/+9/vVq85l9xatmyZWz2BwdQkGyICe+yxR6OkF198sXHuT1YHR3fzzTcnl9jQZZdddvG3mo6Qb7XVVokM+sinVAyBk046yf3ud79zRx11lNt9993bGlWbtUVUKQXF3cFrTsXd8reZ4m7526ifHiru9pN+Z2Ur7nbGbShzKe4OJW2VVXUCmgCseguXpH5+R1ns+rvjjjuaXoWTGA888ICppxu9J7B6849GIX/zN3/TOPcn8+bNcwsXLkwuw3bz98Ojv79gwQI3f/788JbOOyTwox/9yN1yyy3JLtoXX3xxlBW1WRSmyigp7g5eUyrulrvNFHfL3T5l8E5xtwytkM8Hxd18vIZaW3F3qImrvKoT0ARg1Vu4JPV7+umnE0+22GILt3otONMrvEnmk8/jr3UcWgKr1/1rFLj60+zGuT956qmn/KkL260hDE7C+2rXAEyHp3hDdvXmLUnuCy+80I0ePTrKktosClNllPyzprg7OE2quFvetlLcLW/blMkzxd0ytUacL4q7cZz6oaW42w/qKrPqBDQBWPUWLkH9fv/737s333wz8WTChAktPVp//fUd3hJEeuWVV1rq6mbvCPy///f/3AUXXNAo4LDDDmuc+5NXX33Vn7p27brxxhs3dNWuDRQdn5x++unu9ddfd1OnTnXHHHNMtB21WTSqgVdU3B28JlTcLXebKe6Wu33K4J3ibhlaIZ8Pirv5eA21tuLuUBNXeXUgoAnAOrRyn+u4YsWKhgerNyxonFsnfgIQa5sp9YfA6p223OzZs5PCDznkEPrZdp529W0Kg2rX7tr0vvvuczNnzkzepL3iiivc+973vmiDarNoVAOvmKetUVn/jOr57F/TK+72j327khV32xHSfRBQ3B28fqC4W942U9wtb9vIs8EmoAnAwW6/gfAefxH16QMf+IA/NY9rrLFGcu/dd981dXSjdwTwKcSZZ56ZFDBmzBh3+eWX08LytKtvUxhSu1KcUcLVO2O74447LtlI5Utf+pLbbrvtovJ5JbWZJ1H9Y562Bg3/jOr57E/fUNztD/eYUhV3YyhJBwQUdwerHyjulre9FHfL2zbybPAJaAJw8Nuw9DVYc801Gz4ioLdLfjHeYcOGtVPV/YIJPPnkk+7ggw92f/7znx3a7YYbbnCYBGQpT7v6NoUdtSujGSc7//zz3TPPPOM22WQT95WvfCUuU6ClNgtgVPw0T1sDhX9G9XwOfcdQ3B165nlKVNzNQ6veuoq7g9P+irvlbivF3XK3j7wbbAKaABzs9hsI70eMGNHwM+bzspUrVyb6MZ8LNwzrpGsC2CF27733dkuXLnXY9ff66693u+22m2k3T7v6NoUxtauJtOUNTPx97WtfS3RmzJjR+GSzZabUTbVZCkiFL/O0NTD4Z1TP59B2CsXdoeWdtzTF3bzE6q2vuDsY7a+4W+52Utwtd/vIu8EnYG/HOvh1Uw1KQgB/ER01apRbsmSJCzchYO5h8sn/j2i4cQTTlaw4AgsXLnR77rmnwxFryl1zzTVu2rRpLQsIN/5o167hxh9q15ZYzZtYpwZv0G622WbunXfeSSZo08pPPPFEQ3TnnXcmG4VAcMABByQThmqzBp7Knyjulr+JFXfL30aKu+VvozJ5qLhbptbgvijuci5lkirulqk15EsVCWgCsIqtWsI6bbvttg6Lub7wwgvJ56V/+7e86/1/9s4D7IrifPsTE2M0IkhRQBFQwG5EBQvWGHs39oYoYm9JlCh8mkSNPfbEAkLEXmKJNTZELBTFqKCgAhZUmqJG0eSv77f3xtnM2XPPOXPqe8o91/W+Ozv7zDPP/Gb3OXPmzM7gVx8b1lxzTRvVsYIEsEPzdtttZ2bOnBmXgtllhx12WN4S0aY2uO1m09yje13t6pIJj9tXNNFOBx54YN6M55xzTiKDX7uxyYPaLEHSFBH53dptZvnd2m0b1zL5XZeG4iEE5HdDKLWOjPxu63AvtFT53UKJSV4ECiOgV4AL4yXpIglsvvnmcU7M7nvppZe8WrAgrw0DBgywUR0rROCzzz4zO+ywg5k2bVpcwgUXXGCOP/74oNJ69uxpunbtGsu67cYyjxs3Lk5eaaWVTI8ePZiI0qpAQG1WBcg1VIT8bg01hmOK/K4Dowmi8rtN0MhOFeV3HRg1FJXfraHGqIIp8rtVgKwi6paABgDrtunqy/A999wzMXjUqFFJ3I1899135qabboqT2rVrZ7bZZhv3suJlJoDXSHfZZRfz8ssvx5qHDRtmhg4dGlwKXhW2rwljht+LL75I8yLdzgCEPPIpFE5g9OjR8e6/LS0t3qO7McjTTz+dyNlBV7VZ4dzrOYf8bu21nvxu7bVJLovkd3PR0TVGQH6XUWndNPnd1uVfaOnyu4USk7wIFEgg+jKpIAJVIbDFFlu0RLdnS/T6b8vzzz+fVeZFF10UX4dMNJCRdV0J5SMQTa9viTb8SHiffPLJRSmfPn16S7RhSKxno402aok6WRl6cI502+4zZszIuK6T8hLAcwPW+IsGAKlytRnF0rCJ8ru107Tyu7XTFuW0RH63nDQbQ5f8bu20o/xu7bRFOS2R3y0nTelqNgI//F0Uoi+LCiJQcQLrr79+PMMPGxnccccd8UywJZdc0rz11lsGr57iD6FPnz4Gv/4stdRSFbepWQvYb7/9zIMPPhhX/+c//7k588wzzfz58828efPo36JFi+KNXNK8sLnL4sWLzfjx4+MNRB5++GGD2Ztff/11vObjEUcckcwwxOxClKtQOQJjx4419nXsww8/3NiZf26JajOXRuPH5Xdrp43ld2unLcppifxuOWk2hi753dppR/nd2mmLcloiv1tOmtLVdASabcRT9W1dAg888EDLcsstl8xSih64jHg0+NcSDQi2rpFNUHqae77z7t27e6l8++23LdFAX0Y7pvUdeeSRLZBTqCyBkF9EYYHarLLtUGva5Xdro0XSfjHfufxubbRbPivkd/MRas7r8ru10e75/Gz6uvxubbRbPivkd/MR0nUR8BPQGoCR51eoHoHddtvNvPrqq+bUU0+NZ/ots8wy8Yyx6DVRc+GFF5opU6aYXr16Vc8glVQygSWWWMKMHDnSPPTQQ/GagNgY5Mc//nG8QQjW/MOswBEjRhjIKdQGAbVZbbRDtayQ360W6eqVo2e4eqzLVZLarFwk60OP/G59tFMhVuoZLoRWbciqzWqjHWRFbRH4AcYGa8skWSMCIiACIiACIiACIiACIiACIiACIiACIiACIlAuApqSUy6S0iMCIiACIiACIiACIiACIiACIiACIiACIiACNUhAA4A12CgySQREQAREQAREQAREQAREQAREQAREQAREQATKRUADgOUiKT0iIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIiUIMENABYg40ik0RABERABERABERABERABERABERABERABESgXAQ0AFguktIjAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAjVIQAOANdgoMkkEGpXA//3f/5kbbrjBbLfddmbFFVc0P/7xj80PfvCD+O/www+vWLVHjx5dkXKs7TgqiIAIiEAtEvjqq6/Mn/70J7Pllluajh07mh/96EeJP/zd735XMZOh2/rIcpUze/bsRGePHj0qZrsUi4AIiEC1CDz++ONmv/32M927dzdLL710VXxcpXzp1ltvndg/duzYaiFUOSIgAgUQ+FEBshIVARFoIAIvv/yyufPOO80TTzxh5syZYz755BPToUMH07lzZ7P++uubbbbZJh6ow3k5wjfffGN23HFHow5BOWhKhwiIQD0ReOGFF8yYMWPMiy++aPDF64svvoi/6OGHkL59+5o999zT/PKXvzRLLbVUWasFv46Bv6lTp5ZVr5SJgAiIQDUJfPvtt7EfmzRpkpk8ebLB8dVXXzX/+c9/YjO22mqrovuXTz75pPnrX/8a+2f0h+GHV155ZbPDDjuYI4880qyxxhoVq+oZZ5xhLrjggorpl2IREAERSBPQAGCaiM5FoMEJzJs3z/zqV78yt9xyS1ZNP/roI4O/KVOmmFGjRpnjjz/eXH311VlyxSRccsklGZ0zdNZ69eplfvKTn8TqNtlkk2LUKo8IiIAI1CyBhQsXxl8g77///iwbMQiIv7ffftvcdddd5qyzzoq/hA4YMCBLttiEoUOHJoN/mPm37bbbxrNMllxyyVhl//79i1WtfCIgAiJQFQL33XefOfjggw1mM5czfP7552bIkCHmjjvuyFCLcj799FPz2muvmSuuuML8/ve/NxioK3d47rnnMgb/1l577fgHobZt28ZF4Ud5BREQAREoNwENAJabqPSJQA0TeO+99wym58+aNSuxcvXVVzfrrrtuPPsPnZ533nnHvPLKK2XvaGH2iw34pfWwww6zpzqKgAiIQMMRWLx4sfnFL34R+1NbuU6dOsVf8DC7ZP78+fHg3MyZM+PL8L3bb7+9eeqpp8zGG29ssxR9xJILt912W5Ifs1wwG1BBBERABOqJwKJFi8reJ8XMwb322iv2t5bFOuusYzbYYAPz9ddfm2effTb+QRxyZ555ZjzTED/SlDO4/WLMNMQSOVpSppyEpUsERIAR0AAgo6I0EWhAAp999ln8Wq8d/MMrvpdffrlZb731smr773//O+4UYXZKOQIGFqdPnx6rwrp/hxxySDnUSocIiIAI1CyBCy+8MBn8w5e6c845J559jTWebGhpaYlnnxxzzDEGPhq+8qijjopfbbMyxR5nzJhhvvzyyzg7Zltr8K9YksonAiJQCwSwZEK/fv2Sv8ceeyyeoVeMbfDH+LEFAW+i4K2XAw44IFGFfvDw4cPNxRdfHKdhHVO8uYK/cgUsxWPDoEGDNPhnYegoAiJQUQIaAKwoXikXgdoh8Jvf/MbYmSb7779//ArwD3/4Q2ogBumwXl+5Al6lsAEduCWW0P5DloeOIiACjUkAmw/ZcNJJJ5lhw4bZ0+SIgUF86cTrufvuu2+cjtfO8IeZ2aUE1+926dKlFFXKKwIiIAKtRgD90XfffdesssoqGTZMmDAh4zz0BEvhYGMkG/BjuDv4h3T0gy+66CKDN2fwijB+rMFrwM8//7zNVvJRPrpkhFIgAiJQBAF9Cy8CmrKIQL0RwCu9I0aMiM3u1q1b/JqBb/CvEnWzizRDtwb/KkFYOkVABGqJANaWwhdWGw488EAbpUdsArLMMssk1zB7r9Qgv1sqQeUXARGoBQLYjC49+FeKXViGxs6O7tOnT7wOoE8fBgFtvxWbOWGN7HIF+ehykZQeERCBQghoALAQWpIVgTolcO211yaWY2OPNm3aJOeVjGB2C/569uyZFIMvxTbdHnv06JFcT0ewa+YJJ5xgsDjy8ssvH7+qgfWz8IswNiixnbh0vlLO8Sre+eefH79mgjKXXXZZg7US8WreSy+9VIpq5RUBEWgCAv/6178yagk/kitgBuByyy2XiHz33XdJvJAIdhi2fhXLPNjwzDPPJOn2OtaD9QW8WnfEEUcYfDmGXXhtuXv37vGaWZjZ6H5x9ekoNB0bUGGWJJalQJn4g98/9dRTkyUkCtUpeREQARFIE8CmIjYcfvjhsW+05+kjBh5//vOfJ8n33ntvEi8mAr9rfbD7IxH6yTbdHuHPWUA+rEeIzfPwVg1mK+KI87PPPtu8//77LFtJafhMwsDpdtttZzAgi9em0XffY489jMuzpEKUWQREoDoEoinNCiIgAg1MIFoIviX6ItUSeZT476233qpabW2Z+Y7RF8ssm6Iv0C3Rq8qJ3T4d0attLQ8//HBWfjchWtsl0TNw4ED3UlY8Wvi5pWvXrol8utzol+CWaEe4OJ97LUuREkRABJqWQLR+VEv0BSnxI3/7299ysoheSWuBb7E+JVozNae872K0xmuiw+ryHaO1rLLUzJ07tyXaKTivjt69e7dMmjQpK7+bEH0RTfQgniuAT7t27RL5tM1LLbVUS7RAfotbP/a5kasMXRMBEWgsAq6PYf6M1TbanCnD10av9DKxjLTzzjsv8U3RLu0Z1wo9gZ1p/+Y7h79Lh3PPPTfjs4XlxWfPBRdckM6acV6IL41+nGmJNqbKaXe0oUpLNPO9xa3f008/nVGmTkRABGqDgNYAjDynggg0MoHXX3/d4HU0hLZt25rVVlvNYHdI7D528803x7tQYh2Sjh07xjMvdt9993jmR/SFq2QsmG2IgM1EbrrppjiO2YfpHYA7dOgQX7P/sBA+fnGdOHGiTTLRoJzZYost4tl4b7/9thk/frz59ttv413aYDN2u9xnn30S+WIimN230047GXf2zkYbbRSvxYUFoTEbETt14hfWfDN6iilfeURABBqDwJJLLhn7EjtbJPrSZnbYYYeM13zdmg4dOtTYWX/RAFw88869HhrHrDnrd+fMmZPMzID/xI6XbogG8dxTEw3+mejLbezj7AV8XmBHYnweTJs2zdg1t6IfkuJNpR599NE4j5Uv5vjQQw+Z/fbbL/5cQn68bgc7MPsQvnjcuHGxn8cM7CuvvLKYIpRHBERABGIC2JDO+lrMtOvbt29eMtgZ2IY33njDRos6wg9jt2EE9IvtZnvoF6ffzoE/dwPehrnmmmuSJLydgpnemJH38ccfm2jALfaZ2MX4t7/9bZx22WWXJfLFRLADM/rjbr0xW3HTTTeNPxemTp0a99XxWWdflS6mHOURARGoIoHaGIeUFSIgApUigFkTkUuJ/6JOR0u0oHFL//79kzR7zT1Grzy0RINvZTOpkF8aUeixxx6b2BetVdgSLdDcEg32ZdgTrZHVsuGGGyZymOXIfi1FppAZgN98803LmmuumeiL1kpsYb8MR69AtGA2SvTKRSILdgoiIAIi4BKIvjC1RF/QEj8RDaa1RK/PtmAWNmahwBc/+OCDLZtvvnkis9Zaa8Xprp5i45h9Yf06ZmXkC9GPH4n8T3/605boR5WsLJj1t+qqqyZy8JPRD0hZckhwZ+cgzsKCBQtaVlhhhURftPFJSzTQmCEK3x/tqNwSfVnP8LuaAZiBSSci0HQEXB8T4uMAKNrQI/E30WuzQcyiQa4kD3wqZmyXI8CHWR/t67/acly7kSd6dbklWq7GXo6POD/kkEMSnZC75557MmTsSWi/PFoKItGHfu/IkSOtiuQY/TDUYuvi9o3xGaQgAiJQewSWiJyDggiIQAMTSK8FghludmbdGmusYQ499FCDNVDcXzix6xnWKWmN9e4ww+66665LWuSKK64wJ598ctYvi5i98vjjj8drkEAYsxz/8Ic/JPkKjWBtE/sLJ9Y2+cc//hH/wpnWg19pow6QwYxABREQARHwEYB/fe6555LF6+Hb4Gvhu7CmHtaW2nXXXePZzNHrr+bEE0+MZxljo6Zqh+iLmnnkkUeSYrHrZXpXTFzEjOgnn3wynk2Oc3y+lDIrDztxYkdOBKxh9cQTT5joh5j43P7DrJLTTz/dnHPOOfK7FoqOIiACRRFYuHBhkg8+JyRghp0bPvnkE/e04nHMWMSMPhuwY/yNN96YsW4srmHGIGYVYl0+G+A77YxHmxZ6xGZU0Q/oifj1118fvyGUJHwfiSYVxH1mbGSlvnGajs5FoPYIaACw9tpEFolAWQlg+r4NeB0Y0/XxIX3nnXfGA17oLOADHoN9Tz31VPwqMOTxGm60Bl/VP8yjGYtJZ2X99dc3xx13nDU/64jXcKOZIUn6rbfearCBRzHB7pKMvPgiji/vvnDwwQebzTbbzHdZ6SIgAiIQE8CGFvgShQ2Loll1Xip4PRg7BadfAfNmKPMF90cXLKmwyy67eEvAwu9nnnlmch2bTEW/byfnoRHkwZdYG7CofTQb0J5mHfFFNpplkpWuBBEQAREIJeAu8YIfYkJCWs7VEZK/VBn8IB3N2IvVYMMP/OiC15dZQDpeE8YyFAj44Qk/lhcT8GO39e0Y5IvW0PaqwZINp5xyive6LoiACNQOAQ0A1k5byBIRqAgBtksu1v7DL4jpgLVEHnjggWS2HToOt9xyS1qsoucYhLQBs2V8nRwrg/VU2rdvH59Gr/GaF154wV4KPmINlsmTJyfy6TUKkwtOJFdHyBFTVAREoIkJRK+4mmhJg3gnW/hizCTZe++9zZAhQ+J17+yAFmbc4UeFo48+Ol7btNrIMAPQBuz+my8MGjQo+ZzA7r1YV6vQgBnXWLcKAbsgH3TQQTlV4AttPpmcCnRRBESg6QlgfTwbMJgWEtJrYkdLOIRkK5uM2y/eeeed48+RXMpXWmkls+OOOyYirn9PEgMibj68LZQvqF+cj5Cui0BtENAAYG20g6wQgYoRwOusbsDCvenF4NPX8QXVBnwxrVbAL42vvPJKUlzILDt8KcQvkza8/PLLNhp8fPXVV5NZh5iBs/baa+fNC44KIiACIuAjgI0ysMA8ZljjNVbMAsQrs9GaTPEyB/CtmNWBmct2sXe8YoUZyNUM2CzEvoaLckP8bqdOnTI2KinG706ZMiWpJmZc4zXofEF+Nx8hXRcBEchFwO0Th76uih+X3ZCeEeheq0Tc9ZUh/hk2YCMlG4rxz+iP//Of/7Qq6JI4ycXvI5gFaH+QT1/TuQiIQO0Q0C7AtdMWskQEKkIAu4S5Idfgn5WDzN133x2fRhth2GSDdU/wmlausMkmm5hoEeJcIt5reH33P//5T3Ldzo5JEjwRvJJmA2bcFBrmz5+fZMH6W/lmHUIY63cpiIAIiAAjgJ3W8UPKBx98EF/Ga7KY0ZwO8DV49Re7sG+//fbx5b/85S+xrP1hAwOJWAs1V8CsEPwVE1z/hy+2GNwLCfC7b775Zixaqt8N9aehciH2S0YERKD5CLh94tCZfGk5VwcIRpuRGHdtwTTVDh06mN///vfp5OBz10dXq1+M/rg7QBrqeyFX7TUSg0FKUAREICagAUDdCCLQ4ATQ8XBDtMuke0rj7iLseD0Wf5gZh402sLZIroC1UYodAEyvq5JrzSzXBlcOthYa3HKxPmJIcMsMkZeMCIhA8xDALD+suYqw+uqr51w7CTLbbbed+cUvfhFvgoFzzBq0A4CYoZfP72IAsdgBQNf/FeLXXFn5XbSaggiIQK0TcPvEc+fODTLXLlVghdOz3LCJ3LvvvmsvZx0xaFfKAGAxPrqc/hkVUt84q1mVIAJ1S0CvANdt08lwEQgjkN7MIv3LJdOSXoi+mC93TG++tLRtbP1CpsOVS9vO5NNpbrnY/CQkuGWGyEtGBESgeQg8+uijSWWxtmrIrOKf//znSR53TdIksUIR1/8V4tdcWfndCjWO1IqACJSVAH6QsQFLH7hrAtr09PG9995LkjD4FzpLOslUYqQYH11O/wzz1TcusRGVXQRqiIBmANZQY8gUEagEgXXWWSdDrftLYsYF5yQ94Ne2bdv4Kl75sjuCOeJli6IcrOlnXwNGpyvXrpC24NmzZ9tosotxkhAQcTtzeGUPdcz3hR1reSmIgAiIACOAWXs2uDNObBo7YhafDe5u5ltvvXVF/a7r//CqG17ndW2xNqWP5fS77hfsdDnuufyuS0NxERCBQglgABBrsn733XexX8W601i6Jldw19Bz35CxeVxfaNPKeXR9dKivdG0K8edpe9EfbYykogAAQABJREFUxyYp9jVglOvakZa35/LRloSOIlC7BDQDsHbbRpaJQFkI9OzZ0+DPhmnTptmo94jdGW3Ar53uqwQ2vRJHDLqtv/76iWp3/cEkMRXBWluTJk1KUjfYYIMkHhpZb731kh0t8ZpzCKNidhsOtUdyIiAC9U3AXSQ+dD0kdw2pkA0xykUIO0a6P7SE+F0MEs6YMSMxoRi/iw1SbMBagu6gp01PH+V300R0LgIiUAgBbALiDviNHTs2b/ZnnnkmkXFnaieJFY64vjLEP8McV64Y/4z++M9+9rOkZi+++GIS90WwXq37OeaTU7oIiEDrEtAAYOvyV+kiUBUC7q6+9913X94yXZktt9wyr3w5BdzOFdZVyTfjELbaDgc6dsXsEonX1zbaaKOkGmPGjEnivshNN93ku6R0ERCBJifgLpj+9NNPB9F46qmnErlevXol8WpE8JqyDaNHj7ZR7xEymEGD0LVr13idQ6+w5wKWp+jcuXN8FT/k3HbbbR7J/yaHyORUoIsiIAIiEBHYc889Ew75/B1mtD355JOJvJs3SaxwxO0XP/zwwxm7trOiP/zwQ/PII48kl9z8SWJAxP1cuPnmm/PmUL84LyIJiEBNENAAYE00g4wQgcoSOPbYY+NXa1EKfhV84IEHvAVOnDjR/O1vf0uus50rk4sViBx11FHJbDy8dnH99dd7S1m0aJE5/fTTk+vYTdO+rpwkBkYGDx6cSF555ZUZs1uSC99Hbr/9djN+/Ph0ss5FQAREICaADT1swOy2fD8qYPDv8ccft1nMDjvskMSrETn66KOTYu69917z2GOPJefpCBa7P++885Jk5M23ZEIi7ETwGt4RRxyRpGCRfHe3y+TC95FLLrnEzJo1K52scxEQAREoiMDAgQOTN1umT59uRowY4c0/dOhQ8+2338bX8QNzMbPpvMoDL2CHePsmzzfffGNOOeUUb078aH7iiScmS+msttpq8QZT3gw5Lhx55JHJVcwAzDUI+Pbbb5vLLrsskVdEBESgdgloALB220aWiUDZCKADcNxxxyX6DjrooIxBPnsBrznsuuuuSWcHr0nsvvvu9nJVjrDV/TJ6wgknxDtg2tkm1gh0NtApsl8Il1tuOXPWWWfZywUfDzvssGQWC9bBwq6cEyZMyNJzyy23mEGDBsVro2RdVIIIiIAIRAR22WUX06dPn4TFkCFDzLXXXpv4VnsBX9buvPNO487S7tatmznggAOsSFWOmOmx0047JWXts88+5q677krObeSll16Kv0zixxcE2HrSSSfZywUfTz311GS9Qey0Cb+LAVM3wPdfeumlZtiwYfK7LhjFRUAEiiKAJQ9+9atfJXnhw+CH3YC1qH/7299mzEw+//zzXZGqxfFjyQUXXJCUh9nS+LE8vaY31u9G/9T9Ef+iiy5KflRPFARG8BnmTgLAD+V4MycdsGkVfDc2HsG6gQoiIAK1TeAHUeezpbZNlHUiIALlIIBfDfEB/eyzzybqsJhxv379zA9/+EPz6quvGny5s6FLly7xABi+4JUasBix/fWye/fuxl2cmOnGbmNbb711xtp+K6+8stl8880NdkN75513zLhx45Iv0z/60Y/iThq+tLKAVzzQKULAL7++Vz6wliC+CLu7p/Xv399gIxUshIxfQDHwiIBZgu4XX7nSGIv+iYAIfE8APyDg1St390T41c022ywe9MKad/Aprj9caqmlzBNPPBH7ulJBYm0r+wrXVlttZfKtdTV37lwzYMCA2L/asnv37m023njj+Esd1kZFnayvw9qwmCmIPCz87ne/M5jVh3D22WcbnLOAGekYALWzbPBlF74eXz7xBRe+Hq+0IVxxxRXm5JNPjuMhnyWxoP6JgAjUPYGdd9458QO2MvjRAH4LAf6ILZ2AV2axTEE6YIBvxx13NO7SC+uuu248ww87A8PvfPTRR0k2+LJSfmROFDkRbKyHGdUI+DEb57mC/UHcymD5Gvj4FVdcMX4tGK8qu4OCmCnom5WHz52Qfvmnn34aL62DmZI2rLrqqnEaPq+mTp1q8OYQPhfgx7Ekj10zEctfoC+vIAIiUGMEogdWQQREoEkIRLM2WqLXZDHon/Mv+sLXEu34VTYqUccmKS/60hakN/ols2W//fZL8vlsjr5Qt0QdvJw6R40aleiJBgBzykYdl5ZoXapEPl1u9OW0JfoyG+twr+VUqosiIAJNSSAaMGuJBrK8/sT1IdGXsZZoaYGycYq+fCXlRgOAQXqjL9Qt0aBlks+1z41HX7Rboi99OXXCT9o81mf6MkSzDVui5RsSeZvPHqMvmi3XXXddSzGfJb4ylS4CIlA/BNB3tP6gkCN8hi+gT5yvn7nkkku2REse+FSUlO7WKZedbiHnnHNOC/xhLgbRetgtf/zjH91sWfFCfGm0q31LtE52zjKjt4Vaok30WvBZY23DZ5CCCIhA7RH4UfSQKoiACDQJAayPd+utt5pjjjnGYLFerGMXfbDHMy/wCyJe+Y06Q/ECycWs6VROjJjpd8cdd8RrnWD9LMxewSwQvJ7bsWPHeFYeXlfGGlLl3KUYm55gF+Rrrrkmfo0Csw3xSzF+QcY1vJ6MWYEKIiACIpCPAHwFZkhglhs2LMKrUvBjmKUBvwW/u+GGG8ZLLWAGc/RlM5/Kil6HPZhF8uijj8b+F58RmGUDH4jX5rAbJRbBP+SQQ8pqK+qOmZFXXXWV+fvf/x7PisFnEGZ+Yz1FrGOLGeuYtaIgAiIgAuUggD4x+pl4nRavtmKXccz6gx/G2y9YixXr4MH31EoYPny4OfTQQ+N1CzEDOxrIM1iSATvHY2YebMaruu5GVKXajv4vZqvjewOWwcEbQ5jBjs8L7BSMN2t++ctfFrUWbKm2Kb8IiEDhBPQKcOHMlEMEREAEREAEREAEREAEREAEREAEREAEREAE6oaANgGpm6aSoSIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiJQOAENABbOTDlEQAREQAREQAREQAREQAREQAREQAREQAREoG4IaACwbppKhoqACIiACIiACIiACIiACIiACIiACIiACIhA4QQ0AFg4M+UQAREQAREQAREQAREQAREQAREQAREQAREQgbohoAHAumkqGSoCIiACIiACIiACIiACIiACIiACIiACIiAChRPQAGDhzJRDBERABERABERABERABERABERABERABERABOqGgAYA66apKmfou+++a37961+bNdZYw/z0pz817du3N/369TMXX3yx+eqrrypXsDSLgAiIQJMSkN9t0oZXtUVABFqNgPxuq6FXwSIgAiIgAjVC4ActUagRW2RGKxD4+9//bg455BDz+eef09L79OljHnroIdOrVy96XYkiIAIiIAKFEZDfLYyXpEVABESgVALyu6USVH4REAEREIFGIKABwEZoxSLrMGXKFDNgwACzePFis+yyy5ozzjjDbLPNNvH57bffbm644YZYMwYBJ0+ebNq0aVNkScomAiIgAiIAAvK7ug9EQAREoLoE5Hery1uliYAIiIAI1C6BH/4uCrVrniyrJIH999/fvPPOO+ZHP/qReeqpp8xBBx1kunXrZnr27Gl22223+HXgxx9/3CxcuND8+Mc/NltvvXUlzZFuERABEWh4AvK7Dd/EqqAIiECNEZDfrbEGkTkiIAIiIAKtRkAzAFsNfesWPHHiRLPxxhvHRhx99NHm2muvzTLou+++M+uss4554403TLt27cy8efPMkksumSWnBBEQAREQgfwE5HfzM5KECIiACJSTgPxuOWlKlwiIgAiIQL0T0CYg9d6CRdp/3333JTkHDRqUxN3IEkssYQ477LA4adGiRebpp592LysuAiIgAiJQAAH53QJgSVQEREAEykBAfrcMEKVCBERABIog8N5775mzzz7bbLTRRqZTp07mJz/5Sfy24RZbbGHOOuss8/rrr+fU+sgjj5i99trLrLzyymappZaKjzhHemj4v//7v3iiE8qEDUsvvbRZbbXVDCZATZ06NVSNWbBgQWzzeuutZ5Zbbrn4D3HUA29LhgbUGWXDBtgCm2AbJmPB1qoEbAKi0HwEohsNm7+0RLv+tvznP//xAnj++edjOchGN7hXThdEQAREQARyE5Dfzc1HV0VABESg3ATkd8tNVPpEQAREID+BK6+8Mh5nwBiC7+/kk0+mir799tuWI4880psP+gYPHtwCuVxh/vz5Lf369fPqiQYVW6I9D3KpiK+9+OKLLZ07d/bq6dKlS8uECRPy6rn++utbomXVvHr69+/fApsrHTQDMLqDmjHgtV4E7O6LNQB9YY011kgu2TxJgiIiIAIiIALBBKwPld8NRiZBERABESiJgPxuSfiUWQREQAQKJnDuueeak046yXz55ZcGm4lefPHFZuzYsfFGeE888UR8vtlmmxm8bcjCsGHDzMiRI+NLffv2NbfddpvBcg444hxhxIgRZvjw4XGc/YsGB+PZg5MmTYov77333vHMwWigzkSDk2aFFVYw33zzTTwbL9eMwvfffz/eG+Hjjz+Ox0xOP/10M27cuPgPcYyjfPTRR7HMBx98wEyJ0x5++GFzzDHHmH//+99mxRVXjG2ALSgbtiGgjpjhCNsrGbQGYCXp1qjur7/+Op5yCvN22WUX8+CDD+a0FDsE4wHeZJNNzAsvvJBT1l7M9QBABja8+eab8QOAqa+5BiGtTh1FQASakwCmxEe/iMWVX3fddeNXCBgJyOEDupQQ/cJXEX8kv1tKqyivCIhAtQnI76q/W+17TuWJgAiY+DXQavR5K9XfffLJJ80vfvGLuCmxlBgG6nx7CGAwDBuNumHGjBlm7bXXjjng1WEMtuFVWRu++uors9VWW5nJkyfH/XX8yIMf1tPhxhtvNNEswjj5uOOOM9dcc02GyNtvv2023HBD8/nnn8f5oYeNR6AOY8aMifPeeeedZt99983QgzRsNIUwcOBAM3r06Dju/ovetjSYVDVz5sz41eGXX345fgXYlTn++OPNn//85zhp1KhR5vDDD3cvlzde6SmG0l97BKLNPJKpp9ENm9fAaIQ8lo82BMkrawWiuzQpQ3Gx0D2ge6Bc90D065h1M1nH6Fe6kv0OdFQiyO/qGSjXMyA9upeqfQ/I7/o/FardFipPz7/ugea5ByrpeyvR38Urub1794774j/72c9yLjPm86rHHnts0pePJh5RMaTb5yAa3KMya665ZizTvn37lmgiE5U5//zzEz3RQF6WTDSzryWapRjL7LDDDlnXbQKuwR7IIk863HHHHUk5KJMF2Lj88svHcmuttRYTKVsan3cZ1UChcQlgJooN6VF3m+4esegmwuLFi91kxUVABERABAIJyO8GgpKYCIiACJSJgPxumUBKjQiIgAgEEPjHP/5h3nrrrVhy6NChdEZdLjXRCJe5//77YxHMmMPbhywgffXVV48vQR753IBZhHb5h/32288ss8wy7uUk7s6yu/fee5N0G3nggQfMd999F5/6Nk3FRasHssiTDu5mVFY2LQMbYSvCtGnTDOpQqeBf/K1SJUpvqxPADjw2YOptvoD34xHc6bf58uB9+VwB1/HuPwJ29nGn3Pp20mHrBLh1ccvzTTV2ZRBnOpHOuPzrX//CpYzg263nBz/4QYYcTtw6uhftAKubFv0C4J7Gcew4FBownTkdWBpkbPu68m6n2U1PO1hcY6xZGmStE0XcBsbKXksfGW+WhnzMVtYG7dq1SxcTn3fo0CErnemEEKajp8Nnn32WTjLYTZsFXx2YbL2k+dqVPXMsDfW06eBun0ksGRASog2MYt8SIoslC6w/CpEvRsb1VbYuufTY57JSfjf6dTHjtYtPPvmEmvPDH/4wK933wxGWi0gH7HKWDr42ZM8R+yzBkhQsML/l83uffvpplgpWvu+Zt/emq4T5ct9zwMrCKyIssLLc+8nm8XVwmT9mtvraleX31SvUl/m4smeDsUKdv/jiC1v15MjuAZ9NrA5Ylycdunfvnk6Kz9mPoswmCDO7WHv7uDAGrF7sXkH57LM33xpDsMXa43tmodsN8rsujf/G3f4uvrS6z94///nP7AxRiuXuXmzTpo17msRZf9Etwwqy+x3XmI+cM2eOzZYc2f2Oi8xvMP8EWZbOnnn2bPjKYvem75ll9zwrH2Wx5URYH873eeSrA3S7gflXXGd90K5du7pZkzh2Ik2HlVZaKZ1k2OcehKI3FLJkWR8WQrNnz86SZWnsO1NWxhpPYPcr+y7GnkFUjd2bvs9p13fj8wLr5fl0xBdS/0J9b6X7u3fddVdsGfzNrrvumliJPia+3+O+jmbkJenpyKxZs8yHH34YJ+M131wB16dPn27gr3AP9uzZMxEfP358Es+lB69BY41CDLY999xzSR4bCdXjlgE9Q4YMsSrio9WDQUuU6QvQc91118WXoQe2VSJoALASVGtcp9uJCHHQ9sONfbnzVRWDeqEBgzLuwIzrBF0dLJ19OUUeV5+rIx1nOiHDOstMlqUhP+to+WRZHViHgHXoUBYLLD8rB3mZXSwNsqFcfGVBRzowViwN+Vj5Ptl0OThn9fLdK6xTyzrl0Ms6eoxBIbZCby2G0Dr45Fg6S0PdWbqvvdKs0PllHeC0HM597cpki02rNb+L+9v1KT6uLJ35F3Bx9VlO0U7zNpocWQcaF9nzyQZA2Zc45Gft6LOVPZ+sfOZzfLay/CwN+dm9zdJ8skwvqxPyh7Yh83nIzxj6bGV2QUc6sLaCDEtn9kOWleWzC/LpwGQZQ3ZfQxe7DxkryLLBOnZvsfojf2hdWZ2Qn6WzNMi6wdrjawNXFnH53TSRzHPcS+6gAmtX5LDc3dy+NmDPLbtnfe3N7llmly8/k2XPEerC6sCeI5aG/Ewvqz/73EB+ppfZD1nGhZXvy+/jBd1u8OVnrNx7x9Xh9i9sOhuUYvWHPPuBgfVrIct4szr46s/ubeitxcDqxe4Bdq+gPqy9fPcmKws62H2A9HQI9b2V5h/tlhub1qNHD4P78tZbbzXRK6/m9ddfT0zGoNZRRx1lTjzxxKx+I2a+2eBuRGrT3KN7HbP9ejoDgIXqwQAgfqzBmIfbb7V62rZtm3PgLtoFOF7bDz+o2JmH1laMtdgfs12b7XX36F5P63HlSo1rALBUgnWYHw4JI/AYic+3WQd+LbIDgN26davD2spkERCBZiSATk5oRydUrhSO8rul0FNeERCBeiAgv1sPrSQbRUAEGo1AqO91+7vYuTZfKGRCD37UwgafCB07djQnn3xyvNNtugwMtp122mkGr9w+9NBDxn0Tyx2XyFe2Oy5hB9hsWcXoARvks68WQ5fVk88WyMKeqVOnJoN9SEOwOhDPpydXnZC/XEEDgOUiWWd68PrXs88+a7ADDn6Z9v3CYB9kVC9aTLMitcQrM+4vKuxXcRTMfk1yHZlrHHvdxifr5ssVZ7/g+35NY7/k2Ff60mWw1w/Yqxa+V6PdXyqsbjaz0w7kWplcR18bMIYszceF/aLI8rM02MvSfbaydJaf3Ssoi+VnaZBlbcjuF19+6KiXwBgWYjt7jn2/nlq/BG6+58dXNuwMtTVUzldWaHqt+V333mczAFAv1l62XdL1dvXZa8wX+l43ZvndjpPVyfwbrjG/46sX80XMVt+9ye4ZptP3zPvSbR3dI7OLpflsZW3IWDN+sIPNYnA/s11bmQ42G8lnK3vTwHe/MR/LymdpsJmVhVkL6cBYQ4Yx8M3uYDYwn8buIZTF2pDpZEyQn92vSM8Vis0Tmi9ULpeNIddqye/C97kzqHx+gLUte2ZR/wULFmRhYPchu1+Rkd0zzC5mE/KzvqXP7zIbmH9gciiLBfYcsVd1kZc9y8x+yDLeLD9LQ34W2D3PWCMvaxefrXbHWLdM9pqhe++5sszH+9qbta2vDm4ZNs58GeNi5atxZPcgymVvK7DXeqPNMqmZ6667bla6O8DjXnQ/EzH55tFHH3Uv542DYQhHV6Z///5BevMKfS+A18btvfDaa6+ZSZMmGcyMu/jii83OO+8c9yWQhrUBMVMQry0fccQR5m9/+1tShLuMBvuMTgSjiPv9N90vLLeefLbALmtPpWxx615qXJuAlEqwTvNvvvnmseX4MHnppZe8tXjmmWeSawMGDEjiioiACIhALROwnaHQYzXqIr9bDcoqQwREoLUIhPpbK1cNO+V3q0FZZYiACLQmAetTQ46VstMdoMYAOtY7fPrpp83BBx9s8Eo6fpjYcsstzVNPPWWiHYJjMzALcMKECYlJ7sC7b8DaCrsDt+mJM+XWk88W2GTtqZQttt7lOGoAsBwU61DHnnvumVg9atSoJO5GMIp/0003xUmYnrvNNtu4lxUXAREQgZolENIJcmWqURH53WpQVhkiIAKtRcD1qSHxatgpv1sNyipDBESgNQmE+FsrY+2cOHFi/LoqXp/1/VnZkGN6JungwYMzXqe1OjAQeN5559lTc8cddyRxVwd7uyoRjCLu7N/0rOdy68lnC+yy9lTKFrfupcY1AFgqwTrNj2m/W2yxRWz9yJEjzQsvvJBVk0svvTRZyBLv8bvTk7OElSACIiACNUTAdnRCj9UwXX63GpRVhgiIQGsRCPW3Vq4adsrvVoOyyhABEWhNAtanhhytnXg9F2vS5fqzsiHH9GY022+/vTfbtttumyw/hteCbXB1pF+ltTL26M44TL+iW249+WyBTdaeStli612OowYAy0GxTnVcccUV8XRcrDOBhxS79OCdfEzXPfroo83pp58e1wy79fz617+u01rKbBEQARGoHQLyu7XTFrJEBESgOQjI7zZHO6uWIiACrUcAr8C6ayT61juEhZihh41CENw1LN1NMtga0HGG7/+5G3+kyypGD9andPOhGHuezxbIWnvStmCHZhvy6bE6IJ/WY3WU46hNQMpBsU519O3bN552e8ghhxhsW33mmWdm1QSDf9ihxx1JzxJSggiIgAjUGAH7K2iIWZCtVpDfrRZplSMCIlBtAvK71Sau8kRABETgvxs9hfRlQ2RK4bn22mubsWPHxip8G8lY/fa6u9EXNm2ywd2I1Ka5R/d6eqPStJ7111/fzZoRt3ow4GY38rAC0IO9ErDByccff2zY5jqQxY7KGEtBSNuCMRToxuCeLSsWJP/c62k9RLzoJA0AFo2uMTLutttu5tVXXzX4dRQDfRiZxkKXvXr1Mvvuu6854YQT4kU8K1lb7Pbl7vjl21GLpVvnkbbP7kLkpjOnx+SQh6WzsphOt0w3znS61904k/WtP8B25GJ2+XYXZGW5trhxtnsX26mMpUEPS2e2sjTXDjfObHKv54v76s94u4vKunqt03fTmKyvXqwOPlm3jFqJM/tZGuxl6b7lBewaHnj23B29QuoNfqEMQ+VCyg2RqQW/m34W2f3uq4vPl7D0efPmZanxvUrBnhm2myOTQyGsHdP1tMbYxZrtOY7shy7m9yGbXuQZaXb9F8Rt8OVnfod9xkEPe2aYXt/uyswuVj4rB+Wz59M+m7juBiz6nQ5Y/Dsd3A6/e81ngytj426/waaxhbpZXSHP6sXy29d6bBn26NNrr7tHVi+W3/ccsns7NA12MFnXvnLFUU5oWaFy5bKtFvxuur/L7mHUl90bzL9Clvk4lt9XFvMlhbQNu7dhFwtMlqWxZxP6WB3YM+POKHLtYJ8dzD8iD+PNyvLlD+XqY836lexzC7YuXLgQh4zAbGWskYl99mDAgwX22cfaxWcrk2X3MOMPe3y8mK0sjdU1/cqmzde+fXsbTY7s84z1HZCB7SLMdgaGrPuZyvpNkMkVwCWETYhMrnLyXcMmH3YAcObMmQY/erOA+9vuYO7OkOvZs6fp2rWr+fDDD427ESnTMW7cuDgZ+Xv06JEhYjd/QiL0HHDAARnX7QkG9WbMmBGfss1OoWfMmDHxdejZf//9bdaMo2urT89tt91mpk+fnnMgMZ+ejEJLONErwCXAa5Ss3bt3N3/605/imxIdXWw/jvfx8Qow68w3Sr1VDxEQgcYmYDtE+Y6tQUF+tzWoq0wREIFKE8jnb+31StvB9MvvMipKEwERaAQC1rfmOla6nr/85S+TIrDDry/gGuxEsHsSII5B6j322APReLYcliZjAel2thzk04PbeIPRzqC78847DZssA72jR49O1O+1115J3EZ23333ZIDct2kqZK0eDDAjTzq4m1FZ2bQMbIStCJh5iDpUKmgAsFJkpVcEREAERKDVCOTqALFrrWaoChYBERCBBiHAfGuutAaptqohAiIgAq1KIJefTV+rpKHrrbee2WmnneIiMOPtySefzCoOs+6GDx8ep2PW/aBBgzJkTjnllGS274knnpj1xgVmoSIdAW8TQJ6F3/zmN3Ey3o6w+xq4cu+88068/wHS8OYjGwDEK78HH3xwnO2xxx4zd999t6sijt91110G1xAOPfRQ+powdK+66qqxDPZcQNnpcNppp8WTsJCOeCWDBgArSVe6RUAEREAEWoVAusOT77xVjFShIiACItBABPL52fT1Bqq6qiICIiACrUYg7VtznVfayMsvv9y0a9cuXspg1113NWeccYZ59tlnzeTJk82f//xn069fv3jJMdhxzjnnGPcVYKRh5psdAEMevFJ7xx13xPlxxDnSESDXu3fvOJ7+N3DgwFgW6ddcc43ZZ5994oG6iRMnmquvvtpsttlm8bp9mLV35ZVXJrsSp/Wcd955yeYmBx54oPntb39rxo8fH/8hftBBB8VZsAHKueeem84en2NZg6uuuiqeTYjXn1EH2ABbMHgI28AGAa8dYyCxkkFrAFaSrnSLgAiIgAi0CgHb+QkpHLIKIiACIiACpRGQ3y2Nn3KLgAiIQDEEQn1vNfq7GMD7+9//Hg9qzZ0711xwwQXxn1svvLI7bNgwOjMPchh0w1qIN954o5kyZQpdw+/II4/0DrhBB9abvO+++8zOO+8cL212zz33GPy5AWtVYiDOzlp0r9k4NvBAffAaL2YvXnjhhfGfvY4jZgqiLLtrsHvNxmHHtddeG++vAC52FqO9jmP//v0NXo9ma2W6cqXGNQBYKkHlL5kA1hl0FwT3LajLFm71Fc5k2SKzbJFe6GSybFHl9JoD1p5CHCyTDU1DeawOzC5mvy+/rUf6GKqX2Q9dvvR0OYWcM5uQn90DTNbHhS2A7Ls32cLS7B4qpF6lyrK6+nRWs11YWb42sHWwR5/9LB3lsLJ8siy9kdPA1OXqawOW7uZzGTFZtpC5b1MF9sywhcyZHOxg5TM/AFm2yDxbyJttQoL87N5iXJhNvvw+W1k6W4idfRagLBaYTiaHNKbXt0A7S2cb+Pg2gmGdXqYTdjEGzEf78rN0tk6Q7x5g7Q27WGD3AePK5KCPtRcr35ef2eRLs3rZPe7LY9Pldy0JfsRmA+5i/27czcHY23Zx5RBnsuze9uVnPjZdBs7Zs8nkkOYri22ywxj4NpBgzwHzA+xzB3ax5xvpoYFxZc+xTx+z3yfLPud89jMfyzYG8fkH7GCaDhjoYIH5WPc7nM3j48LuN1ZXdl9b3emjjyvTwWxl9yXKYP0EVn9fn4alt23bNm1+fN6lS5ck3Xf/JwIkgrqy+qZFQ2TSeYo5xyy2qVOnxrPeMDA2a9Ysg7ZHPbfeeut48Mu3QQjKQ5uOHDnSYE3B66+/Ph7Aw6YhHTt2jGcQHn300TkH7azNkH/++efNDTfcYG699VbzxhtvGLQLNhrZdtttzcknn2ywc3G+sPHGG5vXXnst3jQV9Zk9e3acBZuWYA1CvIbcoUOHfGrMUUcdZTbddNN4xiFej8ZmJ9h5GOsV4lXjwYMHZ4yJ5FVYpIAGAIsEp2wiIAIiIAK1SyC0M4QaVKtDVLu0ZJkIiIAIlE5Afrd0htIgAiIgAoUSCPW91ezvYkDsd7/7XfxXaH2sPGbN4a+UgEHfY489Nv4rRQ8GE/HKMv5KCeuss048qFmKjlLzagCwVILKLwIiIAIiUHMEQjtDMLyaHaKaAyWDREAERKBMBOR3ywRSakRABESgAAKhvlf93QKgNrCoBgAbuHFVNREQARFoVgKhnSHwUYeoWe8S1VsERKCcBOR3y0lTukRABEQgjECo71V/N4xno0tpALDRW1j1EwEREIEmJBDaGQIadYia8AZRlUVABMpOQH637EilUAREQATyEgj1verv5kXZFAIaAGyKZlYlRUAERKD5CKij03xtrhqLgAi0LgH53dblr9JFQASak4B8b3O2ezG11gBgMdSUp6wEsFuYu4MT26HJVyDboQmybAcytvuVz1myHalYfp9dPr0++XQ6y8/SkM+XntZZyLlPJ0tnrAspqxBZVr4vP2svtisZ29UNOtnuXT5Zdr8wu9z73L3ObHWv23gh9S9E1uoPObL2ZmkhuqyMr/62DvZo5UOOyBOaL1QupFwmM2/ePDNx4sT4b9KkSfFuZnaHvoEDB5rRo0ezbN60Rx55JNkVbf78+aZTp07xrmhDhgwJ2hUNinF/u7s6smcDcqxtfO3NOLI033PAdnNkzxbTCVuZXb7PCLfuyIvA0ny78TH/UAgrxsD32cfqxRgwnagX08vSfPkZF5YfZTEdbJd0xgr5Wb18fpftxsjuF19ZLJ21K0vz2erbTdL3fEFPSGC2huTLJcPuq1zyIdfQfqwNWd5QOZa3XtOw+7V7P/v8E2Pjay92b7D8LA0c2a6sTCd7tpGfpfv8JnZBTgfsgJkOTCdk2O6+Lk+rx7dbLvMZvrKsLvdYyHPM2is0DWWyNmB1hSzzUXPmzMGljMB2XIbA+++/nyGHE7azMNKZ72d6ffc2axv2GeGrK7uPGSvYygLL7yuLfZ6w58WXn5WPjSRYQD/OBnaf2mu+I+rF6paWD5FJ59F54xHQAGDjtalqJAIiIAJNTyC0MwRQle4QrbjiimVpD3RyMcg3cuTIDH3o6OPvvvvuM4MHDzbXXXcd/VKWkUknIiACIlBmArXkd8tcNakTAREQgZolEOp7K93frVlAMiyDwBIZZzoRAREQAREQgQYgYDtDocdqVXmVVVYx22+/fVHFDRs2LBn869u3r7ntttviWYU44hxhxIgRZvjw4UXpVyYREAERKIVAqL+1cqWUpbwiIAIiIAL/JWB9ashRzERAMwB1D4iACIiACDQcAdsJCqkYZCsZzjrrrPgV3X79+hnMBpw9e7bp2bNnQUXOmDHDXHLJJXGejTbayIwbN84svfTS8Tn07r777marrbYykydPNhdffLE54ogjTK9evQoqQ8IiIAIiUAqBWvK7pdRDeUVABESgngiE+t5K93friVkz26oZgM3c+qq7CIiACDQoAdsZCj1WEsPvf/97s+uuu8aDf8WWc/nllxu7Hs1VV12VDP5Zfcsss4xBOgLkLrvsMntJRxEQARGoCoFQf2vlqmKUChEBERCBBidgfWrIscFRqHoBBDQDMACSRCpLAIunwmHZwBbJxTW28KxvkVm2mDxL8y20GrqgrM9Wtz62XoUsNGzzhBxZWSxfqBzLmyuN6fVxyaWn2GusfOhi6SyNLeiL/GxR39D7AvlZ8HFh90YhZbF6sfILSfPZ6ksP1c1stQNbaR32+SyEhdWBclhZ9rp7DJVz81QzDvvuv//+uMg11ljDbLLJJrR4pK+++upm+vTpsfzVV1+dsTHGzJkzk3xg6953PgaFsGcLpLPny6fTdx8kRn8fce12r7F03/3KbGXPfJs2bdwikjiTxQL/6eDjmpbDOdtsA+msLPZ5yBbTR3626DgGjNOBpUGGMZw7d246e3z+6aefZqUz+xl/ZGRlWT+QVsx0sPzpfPac2fXJJ5/Yy8mRyeEia9vQezhRnor47gFWV1Z+Sl1Rpy7DQsuAfGieULmiKlGjmbBpk/vs+trbt5kMqxa755gv8m3qwPKzcph/hRyz1ec327dvn6WabQzCPjeQkdWL2c/SkJ999rj3O2RscNvJphWSn+llDH33AJNl5cM2xgVvGqTD8ssvn06KzxcsWEDTWSJrL7YJyKJFi1h2+nnG6sXSoJC1rc+XsDZg+X3PBtPbrl27rHqx+kOIfe986623svIjwa3vRx99RGVyJcJWZm86T4hMOo/OG4+AZgA2XpuqRiIgAiLQ9ARsZyj0WMvAZs2aZT788MPYRLzmmyvY69gUJP0FADsRK4iACIhApQiE+lsrVyk7pFcEREAEmomA9akhx2biorpyAhoA5FyUKgIiIAIiUMcEQjpBrkwtV3XatGmJeZgBmCu41994440MUd8vzxlCOhEBERCBIgm4PjUkXmQxyiYCIiACIuAQCPG3VsbJpmiTEtArwE3a8Kq2CIiACDQ6AXR2Cg0hr16svPLKhaotSf6DDz5I8ucru1u3bons+++/n8QRCalbRgadiIAIiECBBIrxuwUWIXEREAEREIEUAfneFBCdegloANCLRhdEQAREQASajUD//v3zVrnanSx3fRq2/o5rsLsOXHpdoPS5m09xERABERABERABERABERCBxiagAcDGbt+6qB0WwHUXwWUL76IibDFX3xdxdzFVC4Etom2vhRxZWSzNp8sn69bd5mV1tddCjqwslgZdvvSQciDDFir22c/KYmmhZRcqx8piCwJDL7sPffViDNg9yNoaZTG7WFmF3MNMJ8piepGeDj45ls7KYmnpMuw5Y4VrdvF/33Wbnx1RfqgNoXKsnGqkff3110kxbMH15GIUWWqppZLT9ALUlicEcC+59XbjiYIoEtreyMN0sHu2mPZ0bfLFmV7fBg5skXmWn22ggfKZf2Bt89lnn1FzWfm+Ta2Y7HLLLZeld9VVV81KQ8K6666blb7iiitmpTE/BiE2cPzUU09l5UcCNjlIB/e+S19LnzOGrF2Qj91vaX04Z/cw0pnvZwvX+/JDRzow+yHDFolnvFka8rP7mD1brE7Iz4KvXvZzCnxZuUyXTUOe0HYJlbO6G+EIX275oj6+Nlh66aWzqsvuIQi5+mymtO9Huvs5YuVwZG1cSNsUcs+5P1BZGzp06GCjydH3HDC/W4itSQEBEWZDIeWztmU6WRrMY/VibQVZtvkS+9yALAusLN/nEfNx7B5g/gllMy6sLKYT+dnnAbMfsqHBZ+uXX36ZpcLXBlmCUcK7776blTxhwoSsNCS4sqw9aSYnEQxCOITIOGoVbVACGgBs0IZVtURABESgmQmEdobAyO0QYaOMLl261BQ694tfvk69O9iS/hLpDg7WVAVljAiIQEMQKNbvNkTlVQkREAERaCUCob7X7e+2kqkqtgYIaACwBhpBJoiACIiACJSXQGhnCKW6HSIM/uVbZ6+8lubX1qZNm0SIzcZKLkYR9xfr9OvC6XM3n+IiIAIiUCqBYv1uqeUqvwiIgAg0M4FQ3+v2d5uZV7PXXQOAzX4HqP4iIAIi0IAEQjtDqHqtd4jcAUl3QxDWbO7GH+6GIJCttZmNzH6liYAI1C+BRvK79dsKslwERKDZCIT63lrv7zZbu7VWfTUA2FrkVa4IiIAIiEDFCIR2hmBArXeI1lprrYTTm2++mcRZxL2+5pprZoj07t0741wnIiACIlBOAo3kd8vJRbpEQAREoJIEQn1vrfd3K8lIuv9HYIn/RRUTAREQAREQgcYgYDtDocdarnXPnj1N165dYxOfeeaZnKaOGzcuvr7SSiuZHj16ZMiG7HCckUEnIiACIlAAgVB/a+UKUC1RERABERABDwHrU0OOHhVKbiICmgHYRI1dq1XFDmbuzlpwXiy4i9vb675donzpNp89st2ocI3ZwNKsnvSR6fXlZztasfzpMnKd+8rKlSfkGrOL7WDGdqWDflZXllaI/YXIsjqyOkGO7Va3zDLLMBW0XmzHPVZXKGR1yLfZg2uIbwczV8bGffW11+3RJ8fSWRqrk9WdPvq4WAaF6LK6kSc0X6ic1V3tI/juscce5i9/+YvBDL8XX3zRbLLJJllmIN3OAIR8ul3cXWJxz7jc07JZyp0En2wox1A5p8iMqGu3e4HZ5ZNlnydsfUXfbnyhnzE+X8j8JrMf9WO7Li6//PJu1eO4HSROX1httdXSSQYDxKHhjTfeyBL1+RzGm6VlKfw+gfFi9Yc4a0PG0O1fuOWyNmQ6WVtBD0v3bbTD0pldTCfKsr4QcRvY/equAWrlcPS1lytj47YN8JwWsuMl8iNP6PMdKmftaoQj+gVuG7N2RT3Z7uFsp1TIsr4Kew7ccpHPBiZbSNsw2a+++sqqzzjOmTMn4xwnTJbVKSvj9wnMfl9d7b3t6mL5cZ3Vi+n15WfpoWkonz2zbHdnyDK/xe4tZj/ys76tu/kYZGxgelkbMvuhgzFg7eKzleW3toUcC8nP6sD69vPnz6dFM//50UcfUdkVVlghSfe1cyJAIrhf2T2bFg2RSefReeMR0AzAxmtT1UgEREAEmp6A7QyFHmsd2CmnnGJsJ/nEE0806Q4izpGOgIEFyCuIgAiIQDUJhPpbK1dN21SWCIiACDQqAetTQ46NykD1CiegGYDhrCQpAiIgAiJQRwTQEaqFMH78ePP2228npixYsCCJI3306NHJOSKHH354xjlO+vTpY0477TRzwQUXmMmTJ5sBAwaYoUOHGszueuedd8yFF15opkyZEueDnNb7y0KoBBEQgSoQqBW/W4WqqggREAERqBkC8r010xQ1b4gGAGu+iWSgCIiACIhAoQTsr6Ah+SrdaRoxYoT561//Sk157rnnDP7cwAYAcf28884z8+bNMzfeeGM82HfAAQe42eL4kUceac4999ysdCWIgAiIQKUJ1JLfrXRdpV8EREAEaoVAqO+tdH+3VnjIjtwE9Apwbj66KgIiIAIiUIcEbGco9FgPVcSaOCNHjjQPPfRQvCYg1nzD+mg4Ys2/hx9+2GCw0bd2Tj3UUTaKgAjUL4FQf2vlKlnTrbfeOl5vDGt+hf6NHTs2wyTMzg7Nm57JnaFIJyIgAiJQQQLWp4YcK2iGVNcJAc0ArJOGamQzsWi1XdsK9WQLWyOdLdjNFmiFLBxgOrC0QhYnZwvHsjSUy76AszTIMh3MVsiGBqbTl5eV5cvP6uC2nS2Dydlr6SMrn6Wl8xVzzurVtm1bqqpXr15Z6R07dsxKQ8KiRYuy0lkaWzwZGdkCzuw58N2vjBdLyzLy+wTGxdeGLJ3l99nK0n222nR79NnP0pEnNF+oHCsnJA1fDMv55XDnnXc2+Ctn8C0wz9qb+WLYwu6D0DTkZ+3A8jM5X36ks8DqwBbeZ4t4Qx/jxZ5vX35WL+ZLURZbEH/ZZZfFpYzANpWAwOeff54hhxPWrr5F3z/++OOs/GwhdAixz2T2zLPykZ+ls7pClullXH2biDBZ1oasTiif5WdpkGWBbQyy9NJLM1HDZL/44ossWd8C8+zzJCvz9wm2DRhfXx6bjmfT93xaGXsMlbPylT6i3pVeOgH+wL1HfPcWq6tPlvky5gvccl39zO+wtHK0F+vruEtiWLt8fpP5QpbGNrWAbuYLfL6MPV+MtX1erO32yHgzhoW0q++ZZGVZO9wj26wD1xlDlgZZHy9cc4PPl7kyNs7a21cnX7rVVc4jay/WBj4m7N72bdTkpjMe+eoFW5m96XwhMuk8Om88AhoAbLw2VY1EQAREoOkJhHaGAEodoqa/XQRABESgDARqye+OGjXKuF+qWfWmTZtm9t9///jStttum3N37Mceeyyebc30IG3llVf2XVK6CIiACFSUQKjvVX+3os1QN8o1AFg3TSVDRUAEREAEQgmEdoagTx2iUKqSEwEREAE/gVryuz179vQb+v2VMWPGJDKHHXZYEmcRbMTUo0cPdklpIiACItCqBEJ9r/q7rdpMNVO4BgBrpilkiAiIgAiIQLkIhHaGUJ46ROWiLj0iIALNTKCe/C5e5bvlllvi5sJr5nvvvXdFmq6Y1/kqYoiUioAINCyBUN+r/m7D3gIFVUwDgAXhkrAIiIAIiEA9EAjtDKEu6hDVQ4vKRhEQgVonUE9+98knnzRz5syJke6zzz7Gt25cqcyff/75UlUovwiIgAjkJBDqe9XfzYmxaS5qALBpmrp2K4pFad1FdH0L4rKFV32yoQ4uVA702KLIrt0uYbZILcuPPExHIXVlZbF6sTSUz+xiNvlsZYsqQ5YFtsA6s4ulQZ8vnZXFuLRr1y5LdK211spKQ8K6666blb7SSitlpSHhww8/zEq3XyzcCywN1+fOneuKxXHGyne/Z2WOElj9mRzSSpVlC46zexhlsXRfvZgsdIQE3Cuh90uoXEi59SKDTQXc57x9+/bUdLbZxeLFi6ksm+nCZAvh7dpoC2Xl4Bp7ZnxlsXue5feVFer3WDmwlfld33PANoBgtvo2gGBtwNrVtwnIrFmzYHJGYAvkQ4DVgbUBa1fkZ1yZ3/aVxcqHLAul+BemD2msrkhnmwcwWeZLkZ8tyM/uTV9+dr/52sDes8XwQZ1YvVCHdAiVS+cr1/lNN92UqMr3+m8iWERk0qRJSS60g8vd116Mve/eZukszS03MSiKMP/CnkPmc6CH3Ye+trX3lls+k2U6kadNmzZu1jjO1l70fZ6x52jhwoVZOpHwyiuvZKUXslFUVuYogdWfySGN3QOMFWSZXibLNmFBfna/sPsCsswupKeD7/OE2co+o3y2smeG+VfYwxik7SxEzifL+EGWfc76+Ll18OmDTl9AXUPqGyLjK0PpjUNgicapimoiAiIgAiIgAv8jYDtE+Y7/y6GYCIiACIhAKQTy+Vt7vZQySs2LXZHvvffeWE337t3N1ltvnVfloEGD4k1AMDjWsWNHs8kmm5jhw4cnswh9CmbMmOG7pHQREAERKBsB61tzHctWmBTVNQHNAKzr5pPxIiACIiACjIDtALFr6TTIKoiACIiACJRGoFi/65u96lrDZnq51wuJ33PPPckOwYcccgidQZXWN3bs2CQJs8bwN2HCBHPppZeayy+/3Bx99NHJdTcSUjdXXnEREAERKJRAqO9Vf7dQso0prwHAxmxX1UoEREAEmppAaGcIkNQhaupbRZUXAREoE4Fi/W7//v3zWlBOP13I67+rrrpqvEHIpptuarp16xbbOXPmTINBxLvvvtt8/fXX5phjjokHEYcMGZJVjy+//DIrTQkiIAIiUE4Cob63nH60nPZLV3UJaACwurxVmgiIgAiIQBUIhHaGYIo6RFVoEBUhAiLQ8ATqwe9+8MEHxs7mw2u8ffr08bbLXnvtZQYOHJg1Q7Bfv35m//33Nw8++GA8OIg160499VSz++67m86dO2fo861lliGkExEQAREogUCo71V/twTIDZRVawA2UGOqKiIgAiIgAiIgAiIgAiJQTwQmTpxo3n///Zx/5arPzTffnGxkgMG9XKFt27ZZg3+u/K677mrOOuusOAkb2o0cOdK9HMd9mylkCSpBBERABERABKpAQDMAqwBZReQmgJ2P3N3JCvl1gu0m5SutEL2uPVYf2xWN7fAEeWaXr3yW7tslytriHpks08nqBD1sRy2fLNtJkO305dvByt3lytaB2crSrHz6yFhDZvnll0+Lmo022igrbYMNNshKQwJe+0kH326UbGe6pZdeOp2d7rQGIbazHGPA2jqrkDwJTC9jyNoaqtm9we4h1tbIz8pnaa6s7zpkfAF5QvOFyvnKqsf0ZZddNuPZT89asXViz/IyyyxjL2cc8SpcOrB7Ky1jz9k9w/yuTyd71Y7ZhPJYvVia795gzwd7DnyfESw/S4OtzMeyen388ccQzwoLFizISmNlsTRk/Pzzz7Py+2Y1sfqyARCWhkJYe2cV/n0C483q4LtfSvWnrHyWBnOZ32S7qjLWyM/aGxtZpAMGoVhg9zZLQ17LsBg+xfrdLl26mHKu8ccY2LQxY8bEUdyDmMVXasBrvxgERN2feeYZM2zYsAyV7s6zuL/de6GQe9Pni5jf9D2fGYZ9f+LaY6+z/hMrB/JsR3B2v1rd6SMr3+cHOnTokM5uevfunZXWq1evrDQkML3z58+nsp9++mlW+pw5c7LSFi1alJWGBPZ8s2eK1R/5WbrvHmD3EfPF+NxngaUzW5HX52PSelm/GDLu82DzzJs3z0aTo/VDScL3EcaF1R/ijBerly+/Lz1tEysHMszHsvLT+oo5hw0+O1x9ITKuvOKNSUAzABuzXVUrERABEWhqArYzFHpsaliqvAiIgAiUgUCov7VyZSiyIBWTJ08206ZNi/Ng9h4b6CpIYSS8wgorGDswxQaIMLipIAIiIAKVJGB9asixknZId30Q0ABgfbSTrBQBERABESiAQEgnyJUpQLVERUAEREAECAHXp4bEiYqKJrmbf+R7/bcQQ3LNFMq1xmAhZUhWBERABHwEQvytlfHpUHrzENArwM3T1qqpCIiACDQNgUI6OpBVEAEREAERKI1ALftdbNRx++23xxXs1KmT2WmnnUqr7Pe58Qqpfc2+a9euWTqxYYiCCIiACFSSQKjvVX+3kq1QP7o1AFg/bSVLRUAEREAEAgmEdoagTh2iQKgSEwEREIEcBGrZ7z7yyCPGrvd20EEHZayBmqNKeS9df/31yWfIVlttlSW/6aabZqUpQQREQATKSSDU96q/W07q9atLA4D123ZNZ3khTostElvIwqts8Vm2EDtLQ8Pgl+Z08C3KzBZWZvnZYrIog716wurPFgRGfpbuK2vx4sXIkhHYQsdsoWVkYraW2q527Z0Mo6KTtdZaK51kWOd8/fXXz5JDAlsbiNUfsuw+YAsgs7ZGfrYAsm9Bf8inA2PI0tL57DmTZW0FeV+61ZXvWMhzmE9XvuusXvnyNMv15ZZbLmNBdJyzwDYl8N0DzJewNFYO0lh7sbLY84b8zO/5NmVgi9SzTUR89yvzkUzW5zOYLKsr6sX8KfuMYhsPIT9jwHyRr3zoSAffJh5soyTWXmzR+XQZ9pwtxo9rzN5CymKfyawsdl/5yvfJsnub3YNsYw+Uxe4XZr9vgX6WP5+tzGbYki8Umy+f3lKvu6//HnbYYXnVzZ492+B+6Nu3r1f2wQcfNH/4wx/i63j+Bg0alCXrPr94Ft1nl7ULFLB0lpZV2PcJ7Nnwybr2WBn2eeDb/OmTTz6x2ZKjnRGZJHwfYf1FZqvPl7F09hxMnz49XXR8zjZc8/loO1jsKmL2M1bIw3ws2zDF97yw55O1Fcpi/pj52G7dukE8K3Tv3j0rbe7cuVlpSGAM2b3B2gr5mY9mG6kwfsjv44Vr6RAq65NjbeCTTZeNc1YHX37X97P+BdOfTvPpTsvpXAQ0AKh7QAREQAREoOEIoCMU2hkKlWs4SKqQCIiACJSRQK36XQzkYbAOYZ111jEbbLBB3lpjAHCbbbYxmMG32267mZ/97Gfxhh/IOHPmTHP33XfHf/bz45JLLjErrbRSXr0SEAEREIFyEwj1vdZflbt86asvAhoArK/2krUiIAIiIAIBBEI7Q1ClDlEAUImIgAiIQB4Ctep377jjDmNnioXM/nOr+cILLxj8+QJmP1122WVmyJAhPhGli4AIiEBFCYT6XvV3K9oMdaNcA4B101QyVAREQAREIJRAaGcI+tQhCqUqOREQARHwE6hVvztmzJjYaLxCefDBB/sr4FzZcMMNzc033xwP/k2ePNl89NFH8WYfeK0PS4SsvfbaZttttzWDBw9OZgY62RUVAREQgaoRCPW96u9WrUlquiANANZ088g4ERABERCBYgiEdoagWx2iYggrjwiIgAhkEqhVv/vcc89lGhpwhnV8MVgYOmAYoFIiIiACIlARAqG+V/3diuCvO6UaAKy7JpPBIiACIiAC+QiEdoagRx2ifDR1XQREQATyE+P5RNEAAEAASURBVJDfzc9IEiIgAiJQbgKhvlf93XKTr099GgCsz3ZrKKuxA5i7C5hvp7NCnBaTdcuwAH07arF0ppPt4gfdbOcntrMvZFk6y8/sR362yybbkeunP/0pxLMCq6tdKyctzOxisqxO0MXqwLgyOeRnO/6y3X4hy9L79OmDSxlh3XXXzTi3J127drXR5Pjuu+8mcTfCdux1d/6zsniFiIVQruV4Nlj5LI21C+R8bZPW4cvP0llaWl+h59AZqjdUrlAbalkei+K7u8O6cdduthsdu1/dPG6c7U7o4838Biuf7cyHMtu2besWHcd9fo/txsh2UPU9c4wBs8tX1yxDowSfLOPC/C7bxRjlsM8IVr4vje2IvsIKK1BxtvMkuwfYbsFQyHaIfO+992hZzB+z/Mx+KGS8S2Xl6xOw+4i1F0uDrSw/S2PPC/Izv83SIFtKAFPGlekMlWN56zUNPsL1E772Ym3L0sDBpyPNyC3XvcbS2edBp06d3GxJvH379kncRnw747Kdddkz49tBlvlttlM9260XtjEf75NlO4Kz59PnMxhDxtr3HLLPM+ZfUS9WFvvs8+0CvMoqq0BNRmC7/UKA1YHdm4wV8rPPs4ULF+JSRmCfcRBgfoOlZSjLc8LqhCzs+5GvvfIUkVz2leXWwY0nGfNEkCckX4hMnqJ0uQEIaACwARpRVRABERABEcgkENoZQi51iDLZ6UwEREAEiiEgv1sMNeURAREQgdIIhPpe9XdL49wouTUA2CgtqXqIgAiIgAgkBEI7Q8igDlGCTREREAERKJqA/G7R6JRRBERABIomEOp71d8tGnFDZdQAYEM1pyojAiIgAiJgCaijY0noKAIiIALVISC/Wx3OKkUEREAEXALyvS4NxXMR0ABgLjq6JgIiIAIiUJcE0BEK7QyFytUlCBktAiIgAlUiIL9bJdAqRgREQAQcAqG+V/1dB1oTRzUA2MSNXytVxwLh7kKrixcvpqaxhY4LcWSFLNzKFrRliwczORjP7GJpkPXpwLWQwBZYZ4ue+xZlZptVsLrCFrZ4L0vz1cmXnq4nqxNkVlxxxbSo6d69e1aaT5YtquxbjN69J20BvsWiP/nkEyuSHGfPnp3EbeTll1+20YzjnDlzMs5xwrj67qGszBVMYAsYs2eL8YNZTNZ3X9j64jpbKDxXNZHX5s8lh2uhcvn01NN1LJzutqVvwW3mH9iC46g7WwydbZbha0uWzu4j30LorHyfray+hdwHTJbZ6jJ27w/2HDCdbh43zp4Z5jOQh9WVle9beJ9tvtSlSxfXnCTO2pu1AdusA0qYj583b16i340wve51G2c24Rr7PGBpvvwsnbFGWWxBffY5y3QiP+v/ID0dWLtChqWzNMjae5bdY7ieK+AeDr2PQ+VylVdv18Dc5V4IA197sHvDLcMy8j0v7Llnz3znzp2tqowj22yCbQyCTEzv22+/naEPJ77vAWzDNVZ/ny9knzEsP2zwPcu45gZfG7JnmbWBr7/L+ra+fjzzJezzkG0QiLr06tXLrVIc98kytq+99lpW/rlz52alIYFx/de//pUl6+PqS89SECWwz2SWZn1eWgeTZc8WYw1d7HOOfT+DrPvMgNGCBQuQHBzAJYRNiExwoRKsWwIaAKzbppPhIiACIiACPgKhnSHkV4fIR1HpIiACIhBOQH43nJUkRUAERKBcBEJ9r/q75SJe33o0AFjf7SfrRUAEREAECIHQzhCyqkNEACpJBERABAokIL9bIDCJi4AIiEAZCIT6XvV3ywC7AVRoALABGlFVEAEREAERyCQQ2hlCLnWIMtnpTAREQASKISC/Www15REBERCB0giE+l71d0vj3Ci5l2iUiqgeIiACIiACIiACIiACIiACIiACIiACIiACIiAC2QQ0AzCbiVKqTAALn7oLqC5atIha8OWXX2als8VkIcQW32WLvPp+CWGLLbOFgn35swyNEtjCsZBji8wWUhazlaUxJszOXGlsQwC37WxetkiwvZY+srqyhZKRjy3+zxaVhuwKK6yAQ0ZgCyj77qEZM2Zk5MWJbxMPtoj11KlTs/K//vrrWWlIYJuIMC40cxkS2b3J0lBU6D3P7gvkZ/c7ezYhawNYsMW77XV2hJ2htobKsXLqNQ3PqNvGPv9QSHuFyvr8A7vn2QL1hTD31Ytt6MP8pq8sds+wNMYEOpmP8z0HTAcry+fL2Gcn4+LeD2692SL/vgXi2XPKPjdYGspki/z7FpNn9WLl+9qVtUHPnj3dqsdxtjEILrCNPQrpvzC7WFqWQTkSfG3I7i1Wf6i2mxLAFsYzR/Gxz2X3JssTKsfy1msamLvcmR9C3dh94OPF2twtw7Ky7WrP7ZHd32xzNOYHoKNNmzZWVXL0+W22yQ97jt55551ElxvxPV+uDOLMvyGdffawzx3IsnT2HDH+yM94F9IurG/L0lAWNvVKB9bf7d27d1osPu/Ro0dWOssPIXYfsvb69NNPs3QigW1YwljTzJ5EZhNEWXuxdvHVlX1OsTb03e/s2WLfTWCrm45NUSZMmIDk4AAGPg6ukhAZV17xxiSgAcDGbFfVSgREQASamkBoZwiQ1CFq6ltFlRcBESgTAfndMoGUGhEQAREogECo71V/twCoDSyqAcAGblxVTQREQASalUBoZwh81CFq1rtE9RYBESgnAfndctKULhEQAREIIxDqe9XfDePZ6FIaAGz0Flb9REAERKBJCaij06QNr2qLgAi0GgH53VZDr4JFQASamIB8bxM3foFV1wBggcAkLgIiIAIiUPsE0BEK7QyFytV+rWWhCIiACLQeAfnd1mOvkkVABJqXQKjvVX+3ee8Rt+YaAHRpKC4CIiACItAQBEI7Q6isOkQN0eSqhAiIQCsTkN9t5QZQ8SIgAk1JINT3qr/blLdHVqU1AJiFRAnVJrDyyiubn/zkJ0mxbIcmXFy4cGEiYyNffPGFjWYc2e6AbFe1jEzOSaiD9O3+xXaeYjs5okgmy/Sy3cuQn+12xtJ8u/kxu1j5KIvt7MrSSmXtqytsSAe2qxxk+vTpkxalu9Wx3cuQ8emnn87K/+qrr2alIWHWrFlZ6WwXYbbbHTKWugNaVuEVTGC2snuIpcEstlua75m3OnA/zJs3r6BahXaGoDT0eS/IgBoXxjPqPudu3DWd+RL3uhtnu+OxNF9Zri4bZ/cb20UQ8sxWny9hnxG2zJAjqwPz5cw/Qj/jYu/3dPnu56O9xsry7QLMuDCuPlYsndkE29huimzHYN8z99Zbb9kqJsf58+cncTeCnRLTgbWL7/OI7XSa1odzZj/SmV5fn4R9/vraC7rTgdWLpbH7ArrYfch8MWTtbq+4b3yfWZBjQX6XUflfGpi7beF7Dv6X438xX9uy+4C1rVvu/7SGf/75ngNWB5+tTAfb2fbdd991TUzi7PlizyGzCUp86UkBToRxZflZ+VDDeLP6M1+M/Mzv+vq7bHdfJrvKKqtAdVbo3LlzVlr79u2z0pDA6rXqqqtmyU6ePDkrDQns84hxpZk9ib78jCFrL9bWKKpjx45ZJbKdfdk97Mvv7vbrKnd3YvbtoOzKp+Ng4OPgyobIuPKKNyYBDQA2ZruqViIgAiLQ1ARCO0OApA5RU98qqrwIiECZCMjvlgmk1IiACIhAAQRCfa/6uwVAbWDRJRq4bqqaCIiACIhAkxKwnaHQY5NiUrVFQAREoGwEQv2tlStbwVIkAiIgAk1MwPrUkGNrYRo6dGj85glmXOJv7NixeU155JFHzF577WXwtiDeFsIR50gPDZh1eu2115otttjCdOrUKX4TabXVVjNHH320mTp1aqgas2DBAnPWWWeZ9dZbL37bAW88II409paiT/Hrr78elw0bMFsbNsE22MhmyPr0lJKuGYCl0FNeERABERCBmiRgO0EhxkFWQQREQAREoDQC8rul8VNuERABESiGQKjvba3+7iuvvGL+9Kc/BVcNr2oPGTLEjBw5MiPPnDlzDP7uu+8+M3jwYHPdddfRpbRsJgza7bzzzmbSpEk2KT7OnDnTXH/99eavf/2rufrqq2NdGQKpkwkTJpg999zTfPzxxxlXXnvtNYO/ESNGxDb1798/43r65IYbbjAnnHCC+fe//51cwhIh48ePj/9GjRplHnroIfr6eZKhDBHNACwDRKkQAREQARGoLQK2MxR6rC3rZY0IiIAI1B+BUH9r5eqvhrJYBERABGqPgPWpIcdqW28H8zC7zbcGYtqmYcOGJYN/ffv2NbfddpuZOHFifMQ5Agbdhg8fns6anGN9TcwWtIN/e++9dzxzEIN5V155ZWwL1uLFTMBcMwrff/99s9tuu8WDf1i/+fTTTzfjxo2L/xBH2kcffRTLfPDBB0n56cjDDz9sjjnmmHjwD2t0wgbYgrJhGwLqCJt9a4OmdRZ7rhmAxZJTvrIRwCKrdtFpKHVHxd1C2MPgW7iVTaEtZMFtt9xccV/5bAFktnAudLOF31l+Vifkh7NPB7bIbVrGnvvqYK+7R7Zw/Y9//GNXJI77bPWlpxWwhXshg19y0sG3mH/oItj//Oc/0yrj8+eeey4rHdO2WWCL1LONClhbMX3lSCukXVl5Plt9bcN0sDT2HPg2FGD3FtPJ0mwniF1Lp/nqmpZrpHP4GPceYc826sv8k5vPZcLaluX3+SfWDqwsJgc7mH/xfZ6wdFYW88Uoi/Fi9zFb9B35GRff/d6mTRtkyQiMwSeffJIhY09YWfaae2RMcP3DDz90xeI4XllhYa211spKZovRv/zyy1lySEBHOx0WLVqUTorPmS9iDFkaFLD2YveAjwu7B3z3C+u/MFmmE7ayZ4bZ6svP0n2bL9nPTsYXtuQKuC/ZvcnyhMqxvPWaBh/p3o8+BuyZZfcAODC/y9qW9UmQnz1fzJewexj5WR3cOkLGBuYP2UYL9h60+ezx888/t9HkyOxizwYyMFt9sqwNkkKdiK9d2CZF7HuIz7+88cYbTin/jbLNNnBlwIABwbJZglEC++xktiIv64ezzwN2DyI/67P7GEI+HVgbsjTkY+msLFZ/5GeyzG/77nd2D7nfd1GGDe5z4LsnrSw7oq6svmnZEJl0nlLPMdCFQbg11lgjHtw6//zzc6rEJoqXXHJJLLPRRhvFA23WJ/Tr18/svvvuZquttjLYaObiiy82RxxxhOnVq1eWTszuw8w6hOOOO85cc801iQxm6u20005mww03NPArJ510ksEzxz4rMRhpv+fdeuutZt9990304NVd6Nh///3jzQoxIDl69Ojkuo3g8/TEE0+M7ym8OozvmHgF2IYdd9zRHH/88ebPf/5zbPOYMWPM4Ycfbi+X/agZgGVHKoUiIAIiIAK1QMB2iPIda8FW2SACIiACjUAgn7+11xuhrqqDCIiACNQKAetbcx2rbet7771n/t//+39xsVjjzjdY6tp1+eWXJ4PSV111VbxOnnsdPyQgHQGDt5dddpl7OYnbQUTsaI2BwnTAoOEZZ5wRJ7/99tvm3nvvTYvEs/5uueWWOH2HHXbIGPyzwvvtt5/BNQQM3KVfE0Y6dOO1YwSU6Q7+xYnRP9i4/PLLx6fMXitXjqMGAMtBUTpEQAREQARqikCuDhC7VlPGyxgREAERqEMCzLfmSqvDKspkERABEag5Arn8bPpaNY3HrDbMhh04cGA8ay9f2bD1/vvvj8UwY3CTTTahWZC++uqrx9cgj3xuwCxCO4sWA3Rs9jHk3Vl2bADwgQceSGaCDho0yC0iI271YNYo8qQD1iy0wcrac3uEjbAVYdq0aQZ1qFTQAGClyEqvCIiACIhAqxFId3jynbeaoSpYBERABBqEQD4/m77eINVWNURABESgVQmkfWuu82oZeuedd5oHH3zQYAaenY2Xr+xZs2Yly47gNd9cwV7HpiCzZ8/OELWv/iLRymUIfH/SuXNn06dPn/iMLf0UqsctI5ceDFqiTF/Ip8eXr9B0DQAWSkzyIiACIiACNU8gV+eHXav5CslAERABEahxAsy35kqr8erIPBEQARGoCwK5/Gz6WjUqhLVFTz755LioCy+8MHhXW8x8swEzAHMF97qd7Wfli9GDNYjTa1RaPW3bts05cNelSxeDtf0Q0rZgBqRd39i12drqHt3raT2uXKlxbQJSKkHlL5kAFop1F+P2rQ/gythCfYsas0VaC1lUFc4yJPjkWLqvfLbgKLO/kLoy25lNTC5XGqsDs5+lQW/oYs1s4V3kZ+sqPPXUU7iUFbCtejp06NAhnRQvxJqVGCW8+eabWclsYWwIsUWcGatytEGWUVECK4ulsbxIY7IsDbKsbdhi8UwO+VlYdtllWbKxz4E9UiFPIliH8g6V8xRVl8nwsy5X3zPL7gOWBgiuPguFpfnyswWzmaxvwW6Wzp5N2MbuT2ar795gC5yzxb3ZBh4on33O5XsOkM+Gzz77zEaTY7rjai+wzw5WL8YaOhYuXGhVJccpU6YkcTcyd+5c9zSO2zVt3At2LRw3DXG70LabzvwLrrP2KoQr2zyBlcU+S1D+4sWLccgIbOH/DAHnhPVpWJ2Qhd3bofcw8rP2ZnV1y2Kf17ieK6AcVhbLEyrH8tZrGvyB6zvYPYS6hfpCyLLnthC2X3zxBdRkBMyoSQd8wWUBX4zTgd3bkGH3bDovztlzjHSXHc4R2LPhqz9j5XvmWDrT66sT++xhzxzTiXoxX/rMM8/gUlZgbdizZ88sOdYHhhD7nPK1AXY7TQe2URSrfzqfPWftwtKsfProawOmg92bduAmrdduPOGmszQfK/Ych/S1mN2uDSyO+8h3L7nyrgxrS1cW8ZVXXjmdFHSO3XHxnQ0b1Bx55JFBeSDk7qKbr+xu3boleu0Am00oRg/YIJ99tdi1J58tkIU9U6dOTQb7SrEFedN1svrKcdQAYDkoSocIiIAIiEBNEQjtDMFot0NUU5WQMSIgAiJQRwTkd+uosWSqCIhAwxAI9b1ufxc74eYLrnw+WXv92WefNSNGjIh31MXGH4UMaLqD2b4fRW057o+u6R/fyq0nny2wydpTKVtsvctx1ABgOShKhwiIgAiIQE0RCO0MwehiOjg1VVkZIwIiIAI1QEB+twYaQSaIgAg0HYFQ31vp/i5mfg4ZMiTuV5966qlmnXXWKagt3Bn3vpmVVqE7Izg9m7rcevLZApusPZWyxda7HEcNAJaDonSIgAiIgAjUFIHQzhCMrnSHqKbAyBgREAERqBAB+d0KgZVaERABEchBINT3uv3diRMnGt+r/TmKynnpj3/8Y7yE0iqrrGLOPvvsnLLsovuKdr7XyL/55ptERfrV7LQe9zzJ9H0knx4so5LPFqiyevLZki7fPbc6kJbW48qVGtcAYKkElV8EREAERKDmCIR2hmC42yGquYrIIBEQARGoEwLyu3XSUDJTBESgoQiE+l63v4vBv5C17UJBYe30888/Pxa/6qqrkldiQ/NDzl2PMv0qbVqPu+5x+hXdtJ5cA4D59GAAMJ8tsM3qyWdLuh7uudWBtLQeV67UuAYASyWo/CIgAiIgAiIgAiIgAiIgAiIgAiIgAiLQhAQuu+yyeKbcqquuajBodvvtt2dReP3115M0bOJoN3fcbbfd4gFDd0DS3cgjyeRE3E0y3A1BIJLW07FjRydnZtTqwVqFbj6rBxvy5LMFslZP2paVVlopKTCfHqsDGdJ6EiVliGgAsAwQpaI0Ati9yd1tzo27mtlOX76dn9juXWwRUveXELcsls7S3DxunNnlmz7M6svKYnVCmaxeoWmuzW7cVxazi6Wx+rv63Tiz1Vc+Y/jaa6+56pI428WO/QI0b968JI8bcX+FsensHrTX0kdWr7RMoec+nb50pp/tSsbWtvDtVMbam93DrGykMVkfV2tDIfeTLRd2MlvtdfcYKufmqfc4dkB1nzMfA1fG1pndQ7hm28vK4cjaju2ECFlmAyufyfnKYvcbZH3puOYGVj6us1cz2HPE0pC/kJ0zP/30U2TJCGwX4M8//zxDxp6w54vVy+dHGG+2MzDKYzuls/vFx5/dLz672C6+jDfz+7CV1Yul+cpndXBf30EZucIyyyyTddkuIp6+wPSm1xlCHtbWSGdcWX5XluXB9VwB/BhDlidUjuWt1zTci+79yPo0qBu7j9kzC1nmd1n/xed3mQ3vvvsuVGcEX3t17tw5Qw4n7N5GOqsX26XcV1f2LLI0lMUCky2kLMbA95ywslga82Owndn13nvvsWrR3dPbtWuXJesbUFhttdWyZNu3b5+VhgRmw/Tp07Nk2T0IIcaLcWH3NfIzWabTJ8t2/O3UqRPEswL7nGY7KTM5KGMzuNg9BFn3uwj7zIdMrgC9Pt1uvhAZV76QuP2cmjlzpjnwwAPzZj3nnHMSmVmzZsUDgGuttVaShhmFuYJ7fc0118wQTetZf/31M667J1YPno/0ZzD0vPTSSwZ9LgxWMn8HXdhR2fbB0rZgNiJ0Y3DPluWW78bd62k9rlyp8SVKVaD8IiACIiACIlCLBGyHKN+xFm2XTSIgAiJQjwTy+Vt7vR7rJptFQAREoFYJWN+a61irtlu7evbsabp27RqfPvPMMzaZHseNGxenY4Zdjx49MmQ233zz5DyXHgzqzZgxI5YdMGBAksdGQvW4ZeTSg8FyO+vRluEe8+lxZUuJawCwFHrKKwIiIAIiUJMEcnWA2LWarISMEgEREIE6IsB8a660OqqaTBUBERCBmiWQy8+mr1WqEqNHj45nIabLc8/djUGefvrpRN4O4GGG5x577BGbiNlwL774IjUX6Xa2HOTTM0P79Olj7Ay6O++8M34lmSmCzTbstddeNpocd99992Q27qhRo5L0dMTqwcxd5EmHPffcM0mysknC9xHMhoatCJh5iDpUKmgAsFJkK6R38uTJ5g9/+IPZfvvt4/fUseU0phjjJhk0aJAZP358QSU/8sgjBjc83nmHLhxxjnQFERABEahXAm6HIySeq57yu7no6JoIiIAI/JdAiK91ZXJxk9/NRUfXREAEROB/BFy/mi/+v1y1GTvllFOMXTrkxBNPNOnlKnCOdAS8Kg55Fn7zm9/EyVia5PTTT88Seeedd5JNS3r16hWPf6SF8MrvwQcfHCc/9thj5u67706LmLvuusvgGsKhhx5KXxPG2ArWRkTARikoOx1OO+00Y1//RrySQWsAVpJumXVvueWW5tlnn83SivU73nrrrfgPo8qHHXaYueGGG+haGzYz1ksYMmSIGTlypE2Kj1g3DX/33XefGTx4sLnuuuuSke8MQZ2IgAiIQA0TsB2gEBMh6wvyuz4yShcBERCBTALyu5k8dCYCIiAC1SAQ6ntz9XerYWdIGZjUhAGwCy64wOCHILxSO3ToUIO1KjFwduGFF5opU6bEqiDXu3dvqnbgwIHmxhtvNM8995y55ppr4ldvjzrqKLP88subiRMnGqxBiHX7MGvvyiuvpOupQvF5551nHn300XitTaxtCJt23XXXuMwHH3zQXHrppXEca0mee+65cTz9D2t9YmdkbHaCMlGn4cOHm/79+8eDfhi3ueeee+JseO0YA4mVDBoArCTdMuv+8MMPY414N37fffc1W2yxhVlllVXixcxfeOGF+AbE4N1NN91ksNjvrbfe6rVg2LBhyeBf375945Fx+2BddNFF8YM1YsQIg5v5j3/8o1dPOS5gYc3/z967R91RVOn/9fUfZ4CEALlfSAIkJDHiMJAQjBKRm0EhXAaF5RLEMKDEAK41gLNgHMcBREHDGJSLCSI6BoVRGG4z4qAgCCZRWAMEEkISyI3cEwLozPzx++XppA51up99TvU5fd73nD5PrfW+3b17165dn6reXW+/3VXh5MTWUtvp/wCgbDZ5MeShPRwjsUlimw2E6VeOd5eUb5LanvKLTSjs/U1v2eTm0GETjMfK0mX4Y/9fHn9ca8tYsX4BG/56Ce2x9rLKZxMzW7qMF+tbTAb/WL2Yr0yG/JYc59KJ6bIFDQYNGpTOmhyzuvqJb8MMfjLgUIZ9xsC6jv2E4SxP2m76GHli89XS8/2obHEX120YE1i7ginrL9bk3KwfM7bWNZtuQxyHPvrzVvlMnqdezFdfZsyWxQffh9P58cZ9OlnXAZOzerHyUQa7vlm7svsm8se2K3SZX+wewcpHflYH1q7QDRdTwDES42rlZ2WxPmDFsj//+c+7Cw1+W7qMIWPAJqiHeRZjWflWG7J2Cdyu2vV+MZ+rFMkB+DGGRLWmXlnjLsa7YfzbvHkzQ+NYP7K4sv7N2o71IRTO+gwrn72xgvzbt2/HpiqxmFOlEBywGM/8RxYm9/01MEnvG+H5cJ/lD8+H+6wNmP/Iw2I/ayumh/ws7rN2ge7OnTuxqUrMVysOsFjI2hUFsAU/2OJPzH/kZ7wYg/RiDMhrJdaHocsYsPZm433kZ7psASzrOmb5sSAES+FKsdbfwSyfl6GurL7+vN/G6Hjd3tzioRsWRsEDPDzsO/vsszPuzJw503zgBmX0a7zQdPLJJ7tFixYlD9j8QzZvDGOGm2++2U2fPt2LMlss4PHAAw84fMaL+fvwABI/YcKbgigrvYpwqAM/br31VvfFL37RYWVh/xZjqIMHgr/4xS/oWCjUa3ZfDwCbJdiD+ceNG5c8jDvzzDMzHWPKlCnJ02I8UcZklgsWLHCf//znHd5eSSecv/HGGxPxkUce6TCJpr9ZT5o0Kfl2fdq0ackT7htuuMF97nOfc3g1VkkEREAEOoVA7GAI9ak1IFLc7ZQWl58iIAK9TUBxt7dbQOWLgAh0I4HY2FtrvNtO3PCgGF8p4pnH7bffnjzAw4PW/v37OzyruOiii2o+tPN1gf7vfve75MtIvBj10ksvOaxQjX/qH3fcce7SSy9173vf+7y6uT3qqKPc888/7/7lX/4ledC3atWqRHf0rkVLMAchPkNmK0SnDeINxKOPPjp54/C//uu/kpdV8LAb8xXiU2N8fcn+UZC20+yxHgA2S7AH8+M101oJnRyvoeL1UiR8p84eAN50002VN7nwOqp/+Odt77XXXslrquig+M/9nDlzkldn/XltRUAERKDdCcQOhlCPWgMixd12b2n5JwIi0C4EFHfbpSXkhwiIQDcRiI29tca7PcHrq1/9qsNPbMJbc/hpJuGB2he+8IXkpxk7eM6Cz4bx00yaOHFi8lCzGRvN5tUiIM0SbLP8xx57bMUj9ro+Lvz7778/0cGbLXhzkCXIDz300OQU9Hs7YDAfJRMBERABi4AfDMVuLTsxcsXdGErSEQERKDuB2Hjr9ZrhobjbDD3lFQERKBMBH1NjtmWqt+rSGAE9AGyMW9vmCueHYHM6rFy5sjI3Gj7zrZX8ecwr6F91raWvcyIgAiLQLgRiBkGhTjN+K+42Q095RUAEykIgjKkx+83UW3G3GXrKKwIiUCYCMfHW65Sp3qpLYwT0ALAxbm2b6/HHH6/4hu/J02nJkiUVEd4ArJXC8/hmXkkEREAEOomAH+zU2zZbJ8XdZgkqvwiIQFkI1Iu3/nyz9VXcbZag8ouACJSJgI+ttbZlqq/q0jgBzQHYOLu2y4nVsbBktk+f/OQn/W5lu2bNmsp+rZVqoIRVb3xavXq1343ahuWwDOvXr6+IsXpVuIITW80KymxVJEs3/M+wL4itHubPxWzZak7sLUvYYroIyCwxeawM9li9mIytvMX8gcxaKYz5xWyw+kOP5We6RfjK/GITq7KVJJGX6TKbkLFVLpnMWhUt7P++jFhW0GcMvZ30lumyFdAw1wVLzFeml6eubAU42PR+Wf2Rletl4McY+vPhNlYvzOP3OzXuIkayvuDr5bdMh8UX6DM5k1l9w4qn3he/teIDk1t9i/UpJmP+w49wJU/vF1uB1qqrzxNurdUBWYxi8claNZH5wFYEZfdY+MdiWTPXDGyyfgU5S1ZZTM76EOsXKCc9/zFkrL+w1Xahy1Z+tFbOfOedd5ClKrH+wlgjE4u7rL9WFRAcMAaMFbLss88+SU7YZ34HZjO7aBPWLhnFXYJYPZYX12Unjncx9g25W3xZ21qxiPFhbFkcQN5Yu1Z+tioqu45QFuuHLBb4ez/yhInFXcaKlQM7LG6G7RGWxWwwVsx/qyxWL1YO8rO+YbUBa28W4xkrlPXaa69hU5UYayiw9rYYVBncc8B4+5gT6lsrooc6ft+K0Sxusja04jZjwPxnNuGb5Zf3O9y+/vrrlUOrnSsKZAd9gPWDtGqMTjqPjstHQA8AS9SmWKxj4cKFSY3OOOMMd8QRR2RqFz4wYwE3zBD+MWH9YRDqh/vhw8NQrn0REAER6AkCsYMh+NLMgEhxtydaU2WIgAh0AgHF3U5oJfkoAiJQNgKxsbeZ8W7ZmHVzffQAsCStj08hvvzlLye1GThwoLvllltozcL/Rlj/ofMZw/9Os/+CeD1tRUAERKDdCMQOhuB3owMixd12a3X5IwIi0JsEFHd7k77KFgER6FYCsbG30fFut3Ita731ALAELfviiy+6008/PflMB58K3XPPPQ4PAVkKPyWq94px+Bkt+1SG2feyep8M4zOIyZMne3VtRUAERKBQArGDIRTayIBIcbfQ5pIxERCBEhBQ3M02osa7WSaSiIAIFEsgNvY2Mt4t1lNZawcCegDYDq3QhA9Y1ffEE09027ZtS+YVufvuu90xxxxjWgznGKr3We/bb79dsVPvc+GK4p6devMLpvV1LAIiIAJFEogdDKHMvAMixd0iW0q2REAEykJAcbcsLal6iIAIdBKB2Nibd7zbSQzkazwBPQCMZ9V2muvWrXPHH3+8wxYTsN5xxx1uxowZNf0MH8zVW6gjfIuvlXP6bdq0qTLZP5y3HkyGbyT6SlpvMVoTsvp8fssm5MU59nk0s2lNqMsCLJOhLEuOczGJTXLLGOZ5izNPvfJM/ttsXdnku0wGbmxiZearNek662+sD1hlscmmrf7G/GJtYJXfLFfW3/fff3/a/djE0uGbxT4T4+/PpbdWG3q536bz1ToGk1gusXooryxxF/2L9bs0U6Zj9UMmZ/mt9mS6aX9wzK4NyFl+1rehy9qcxQIWB5CfTdDObOaJu+G0GyjDp3A+Xi9jE6SzaxP64aJbPj+7d7I6ef30lrGGDpMzmRUfmJzJUBa794X/uIQO0tatW3fvpH7vtddeKYlzLJaxSe+RMRwjeUNWWazPsuuAsYJtdm0xmxYrVhbrVyhr2LBh2Dj0EYzP8iRcA+w6YDZi9ZC3LHEXY7OwjVjMQX1Z27I+AN1YjrF6sJknMb9YfLFshjy8jsWFXfNMN891ZMVddu9gDFn5qAfjwvJbrFhdmQxlMbusfGs6J3aPsO4nzAaLL0wGX9nYePDgwThVlazxMvv7htUfxljbML+YHvIzXyFPJ6tdmF1LN/TL0kmXGx6DgcUhrRcea787CbynO6vd+bXG6nMnnHCCW7FiRVKZuXPnunPPPbduxSZMmFDRefnllyv7bCc8P378eKYimQiIgAi0JQE/GIrdxlRCcTeGknREQAS6lUBsvPV6MZwajbunnHJKxfyXvvSl5OE0Hgylfz7ykY+4euPdRx55JJlqB/9ExwMjbDH1DuRKIiACItDbBHxMjdn2tq8qv/cJ6A3A3m+D3B7s2LHDnXTSSW7JkiVJ3uuvv97NmjUrys7o0aPd0KFDk/+mYgL7WumJJ55ITuO/waNGjaqlqnMiIAIi0FYE/CAoxino1kuKu/UI6bwIiEC3E2inuJunLazxLt6iuvDCC938+fOrzK1du9bh57777nMXXHCBu+2226re7KtS1oEIiIAItJhAbOyNGe+22FWZbwMCegOwDRohjwv4ROfjH/+4++Mf/5hku+qqq9yVV14ZbQL/+fSfCeM/ns888wzNC7n/jyj0rdfpaWYJRUAERKANCPgBUb1tPVcVd+sR0nkREAER2E2gXrz15+vxajbupu3/+Mc/ds8//3zm55JLLjHHuxhj+4d/hx9+uFuwYIFbuHBhssUx0rx589zVV1+dLq5yzD7nrZzUjgiIgAgURMDH1lrbgoqSmQ4noAeAHdSAmCcCnxw89dRTideXXnqpu+aaa3LX4LLLLksWDEHG2bNnu/R8DjiGHAnzH0BfSQREQAQ6iUCtARA7Z9VNcdciI7kIiIAIVBNgsbWWrDr3u0dFxV1Y9P/Avummm9zBBx/sJk6cWPnB8de//vWk4PR4d9myZe7GG29Mzh155JHJ2Pvss892kyZNctg++eSTDnKkG264wS1fvjzZT/+655570iIdi4AIiEChBGrF2fS5QguWsY4koE+AO6jZzjnnHPfLX/4y8fijH/2omzlzpnvhhRfMGmAC27Fjx2bOQ3b55Zc7fDq8ePFiN3Xq1OQtQgyEXn31VfeNb3zDPfvss0k+6I0ZMyZjo0jBG2+8UfXpRDgRalgOm4zd+s+qH/CF+dmEstbqxmxycDaZK5uMFmUyXxGAWbLkaV1Lj9WV+comR0cZzK41AS2bVJi1AbOZro8/ZrqsTtBnk5ZbEziziZUZA6uurF7e5/SW+cvyMz3YYlyZjNlEfsaQTawNXeYDW6iATYCN/Kxvs/7G+CM/q5d1zTO/YKMnU1njLtoh7AtWf8nDOrTn87FJtK2yWH4Wt1l/R3msz1nxgS32wK4v1l9RlhU3cC5Mffr0CQ8r+2yRHau/s7jF/GJ1QoHsPrdt27aKL36HtRXOsTawdFnbMF+ta571DUvX+x1uWbts2LAhVKnss8U92L2f9QsYwbQA6cTKhw6rg2U3bRPHzC7jyq4h5Gf3zpEjR+JUJh1xxBGJDOMbvDHXG6mouAvfP/jBDyYP7/KOd/HA0N/bMM92+vpEX4H86KOPTvTmzJnjvvvd72Zw4fNgn9COVht5nbxbds2wMti1ibJYP8rrQ1rfKiuth2NWvnVtsOuAlWXFJya37hFsDOT7Q1gP5lOeerH7FvJbdsOy/X5se1tcWR+yymcMrTp4/8It0/Xz2Yd67L6F88xXNi6FLiuLtSuzifysb7I+wGTIz3iz/grdML6w+wV0lESgKAJ6AFgUyR6w8/Of/7xSymOPPeYOO+ywyjHbweBu1apV7JS79tpr3caNG5OVg/GwD//NTCc8YGzkDcO0HR2LgAiIQE8TwCDLGmilfamlp7ibpqVjERABEeAE2jHuHnfcce7QQw/NNd5FPe6///6kkuPGjXNTpkyhFYYctpcuXZro33zzzVUP+PAWofVmIDUooQiIgAg0QCA29tYa7zZQrLJ0KAF9AtyhDdes2/hvB+Y1eeihh5I5AbEwCP4rgi3m/Hv44YeTeU2s/4o0W77yi4AIiEArCfjBUOy2lb5424q7noS2IiACZSQQG2+9Xk8wwNtRece7K1euTBbLg3/Tpk2r6aY/j0VB0v90x2fCSiIgAiLQagI+psZsW+2L7Lc/Ab0B2P5tVPEQF3XR6eSTT3b4URIBERCBMhHwg6CYOtWKrbXOxdhmOoq7jIpkIiACnU6gHeMu5uD72c9+ljycw6d1gwcPTr56+exnP+uOPfZYinzJkiUVOd4ArJXC8y+99JIbPXp0RT20UxFqRwREQAQKJhAbe1sxpi24KjLXAwT0ALAHIKsIERABERCBniUQOxiCVxoQ9WzbqDQREIFyEmg07q5fv74ukOHDh9fVYQrph3D4JBc/d911lzvttNPcnXfe6fbdd9+qrGvWrKkc1yt3xIgRFd3Vq1dX9rET2qk6oQMREAERKJBAbOzVeLdA6B1sSg8AO7jx5LoIiIAIiAAnEDsYQm4NiDhDSUVABEQgD4FG4+7kyZPrFpM3TmORjlNPPdVhDkC8pYdFBTZt2uQef/xxd+uttzosAnPfffcl0948+uijVYvd7Ny5s+KPtRiBVwgXWEkvDBfa8fraioAIiEDRBGJjb944WrSfstceBPQAsD3aoau9wAApXMHKGmyxlQitlZdCex4usxuuuuT1sGX52cpRbIUo5GerZ1m+Qj8mWfMxMi7hgNTbZvXHOWbX8pWttMVW2fJlprcsPyuf+Q9b+HQnnVi7QIet/Bi7mma6jEaO2U2W9SvYZgxYmcwm9Fg/tFYRY/2FrYK3detW5oLbvn17Rs5kVr9gfrHyUYi3wa6njBMpQexgCNksrimTpTpEO4T90WoDtood628WHHZ9MpmVn/UX5hPys35i6TIfGAOrruya7devX6YabLVfKLEYF7ZHaIjV689//nOokuxbvrL8TJet7gjDBxxwQKYs5j+U2Mq6/joOjbB2xXlLHub1++y6Zfcudt/xNtLbP/3pT2mR6VMs14zBPQJWFhZnY4ndu1jfZv0a9lh7DRs2jBVVWTWa8aUZAmE7xV3MyceuyRNOOMHNnj3bTZ8+3WERPDwQvOWWW9wll1xSqUl4fVlMvXIYN9JtGtrx+uHWGoOyfsyu2dBWuF/P51CXXR+sb1nxKbTl9/P0HabLyodt5gPr2+PHj/euVG2teFyltOeAcWHjIjxUZonlZ7GQyZg9yFhdIWcMWXxi/JCfxf6wX0PHJ+bDoEGD/OnK9p133qnshzvML9ZfrYfn7Dqw7ht/8Rd/ERad7LN7N2srKMe2DeOP/EzOWEPX4o1zMQllsfLSeWN00nl0XD4CegBYvjZVjURABESg6wnEDoYASgOiru8uAiACIlAAgUbj7sKFC92QIUMK8OBdE+zhnz+LBxb33ntv8mYgHkjMnTu36gFg+OCg3kOA8OFB+oFeaMeXra0IiIAIFE0gNvZqvFs0+c60pweAndlu8loEREAERKAOAQ106gDSaREQAREomEAjcRcP/+rNtVewm+6ggw5yeBvw4YcfTuYEXLdunRs6dGhSTJ8+fSrFpT/rrZzYsxO+nZn+0iK0k86nYxEQAREokkAjsbfI8mWrcwi8p3NclaciIAIiIAIiEEcAA6E8P3FWpSUCIiACImARyBNz2+GP1QkTJlSqgk+GfQofRtZbyCNc+CNcEAS2QjvetrYiIAIiUDSBPLG36LJlr/MI6A3AzmszeSwCIiACIlCHgB8M1VFLTrfDH6IxfkpHBERABNqZQKfFXWtOtPDB4Msvv1wTeXg+PfdcaKemEZ0UAREQgSYIxMZejXebgFyirHoAWKLG7NSqYPLXcBBmzdvCglY490pYfzbJanpuFuizBREgZxMws0mJ2WSyyM8S85/pQRby8DqsTjjHPjFhg84DDzzQm6rasjpYXNmkvGzS982bN1eV4Q/Wr1/vdytbVles3scSm0+H+Y+8bKJgJrPaxZIzv5guq5flK5MzmTXRMSvf6i9sAuf0Z0uoI2tryNnnUEzXmjeJ1Ss9cTrKQfJlsWtvt4b9G0wYF5YjVo/l7VQZmIZ9lE3MjboxNuw6sjiEZXidPP3Y5wm3Vn7W5+pNwh/aZb6yycmRh907sNJoOh111FFpUXLMFtZg/kN527ZtGRts4vnwDaYwA4vH/toK9di1ifMsHjP/oct8ZdevxZWVxe7HKItNMs/6MSsf+Vl7Q55OVn9jYwrmE+wxH5ivVn9lDBhDa/w0cuTIdLXcqFGjMjII/GT01jiAZtoj7LS4u2TJkkp1/Oe/EIwePTr5HBifBWORkFrpiSeeSE5jUZU00w996ENVWXGNhf2OtSEyhDreAOsDOMeuW9Y3rTGBtx9uWduzewHyMDmThfbr7Vv5WR3e9773Zcx97GMfy8ggsOIWU2aLmy1fvjyj+uKLL2ZkEDBdds2z2ID87B7DFtuALhtDsXGZde9mfYj1QcsvxjX9NizyIjHdQw45ZPfJ4Pdrr70WHL27+9///d/vHuzZY/cznGIM2d8R1rXF7mesLKsNGW/Wh+FreE+3/IGelXDNWNdNmCdGJ9TXfjkJ6BPgcraraiUCIiACXU3AD4Zit10NS5UXAREQgQIIxMZbr1dAkQ2bWLlypXv00UeT/AcffLALV0XGw48ZM2Yk5/CG3zPPPEPLgdy/AQj99EOTsWPHOvZwgxqTUAREQAQaJOBjasy2wSKUrUQE9ACwRI2pqoiACIiACOwmEDMICnXETQREQAREoDkCYUyN2W+uNDv3Aw88QL/k8Dk2bNjgzjzzTOffur344ov9qcr2sssuc/7tz9mzZ2fessJbV5Aj4a0e6LN00UUXMbFkIiACIlAYgZh463UKK1SGOpaAHgB2bNPJcREQAREQAYuAH+jEbi07kouACIiACMQRiI23Xi/Oan4tPJjDZ8+XXHKJW7BggXv66afdc8895371q1+5q6++2k2cONE9++yziWF8pjtr1qxMIXh77/LLL0/kixcvdlOnTnU//elPHfaxxTH2kaA3ZsyYZD/966yzzkqLdCwCIiAChRLwMTVmW2jBMtaRBDQHYEc2m5wWAREQARGoRcAPgmrp+HPQVRIBERABEWiOQDvFXczfN3fu3OTHqhXeApw3b15l3sO03rXXXus2btzo7rjjjuSB4dlnn51WcTNnznTXXHNNRu4F/i1Cf6ytCIiACBRNIDb2arxbNPnOtKcHgJ3ZbqXyevDgwcnnE75S/fv397tVWzZ57o4dO6p0/AGbeJVN0somSvY20ls2uTeTIR8rK20v73F6bhmfn9Vhv/3286crW+u/08OHD6/o+B02ITDOMd5+/hufF1trUmQ2oS5rV9Z+sMsmxrUm0YZ+Oln1SutZx9aNk8lZe1n9gvnFJgpmNuFrbH7oMhtsUmPW1sjPJsZmE4aztkJ+lvxnWOlz/vpifNO66WPkic0Xq5cuo5OP0WdYX0jXielYvFj/Zm1r/UHM+jzLz8qB36wfsvgCXbbYAvPLii9ssYV9990XpqsSi69QOOyww6r0cGBxXbNmTUb3D3/4Q0bGJp2HUji5uM/09ttv+93KltUfJy0GlYzBDusvrF3ZYh8wwxYk8nEgKCbZZXGLxR2LK/OVTRrvF8VIl8+OWR+EHrunMRnzH/kZQ7YgwF/91V9BPZPwxls6DRw4MC1Kjj2XPO3uDYG1xdvr+G2sntfPs/3hD3+YLN6BN/9WrFjhsBDOm2++mfQvLE7wwQ9+0J133nnu6KOPrmkWcXL+/PnJ58K33367W7RoUWIL49RJkyY5fN47ffr0mjbCk7jG2P061MG+b4NQzmQ4z+wxGetDyM/GkCxuWnGX+WXFErYAA+sHLO7DV7aIGeZvTCcWX6HzgQ98IK1KYw6U2OJJv/nNbzL58YCYpWXLlmXE7PpmcQAZmS5jBV0WT1l7sfse8rP2Yn0IuqwfsXbF33YsHXrooRkxW8glnJMzzMDqsHTp0lClss/qwBiyewmMsMVVWIy3+isri7FGWeE1Z/UJ6FkJZbHy0voxOuk8Oi4fAT0ALF+bqkYiIAIiIAK7CGigo24gAiIgAj1LoB3i7rRp0xx+ikonn3yyw4+SCIiACLQrgXaIve3KRn5VE9ADwGoeOhIBERABESgBAQyEYgdDsXolwKIqiIAIiEDLCCjutgytDIuACIiASSA29mq8ayLsqhN6ANhVza3KioAIiEB3EIgdDIGGBkTd0SdUSxEQgdYSUNxtLV9ZFwEREAFGIDb2arzL6HWfTA8Au6/NVWMREAERKD2B2MEQQGhAVPruoAqKgAj0AAHF3R6ArCJEQAREIEUgNvZqvJsC16WHegDYpQ2vaouACIhAmQnEDobAQAOiMvcE1U0ERKCnCCju9hRplSMCIiAC7xKIjb0a777LrJv39ACwm1u/TeqOFWvDVfYOOOAA6hlb+YmtfIXMbIXDcIUlXwBbZcufS2/ZilrWyk9Mt9mga60KxVZgY6tUMSaoI1vtla1mCd2+fftiU5UGDBhQdYyD/fffPyODgOkyRVYO9NgKcKyu0GVtw9oFuiyx9mIy5LXkabtWGzK/2OplTIYy2Kpili67DtgqoxZX5itbOZPJ0jz8MevDOOd5Ycv89vnbfWvVL+03Jq1nqwyGeo888ojzq1FidVdcU1iN8sILL8y1GiVibthHLB9Z386jy/oLk6GOzC67jn2/CLlgn9llMkuX9VnmE/KzFVJZH127di3UM4nVq0+fPhk9CNgqnWy1XOveyVZ7xYqo6WTdD1kfYCu6wx5jyFaIZD4hf9gncVwrsTqw/Mx/2GW6rL1ZfEV+Ztfqm9BPJ7aaplUWW3V6zJgxaZN0dWkoHXnkkRldqyy/8iXr4xkjEuQigD4X9jurvzC5FcuYLotFrL/BedYPwjG5ryDr7zjHdK2x3oEHHujNVbZsbLp169bK+XCH+RDy9LosNuDcli1bvEpla8VdJmfjIisWMr9YLGd6cI7VgY3VoMvG3Oz6ZfyQP0/cY3aZzPo7gq1ezlizfgFf2f2EsYIuu6cxBjt37oR6JrG/O9l1yGQwxq5N5hN0wzEB8xE6SiJQFAE9ACyKpOyIgAiIgAi0DQEMoGIHUbF6vVk5DCTxkG/+/PlVbuABE37uu+8+d8EFF7jbbrut6g/MKmUdiIAIiEALCZQt7rYQlUyLgAiIQGEEYmNvJ4x3C4MiQyYBPQA00eiECIiACIhApxKIHQyhfj01IPrCF77gLr74YhMpe8PVK1911VWVh3+HH364u+KKK9zBBx/sXn31VffNb37TPfvss27evHnJG4HXXXedz1a1tf5LXaWkAxEQARFokEA7xt0Gq6JsIiACItAxBGJjb0+NdzsGXJc6qgeAXdrwqrYIiIAIlJlA7GAIDHpqQITPHidOnJgb+7Jly9yNN96Y5MOnfE888UTls1B8/nvqqac6fD68ePFid8MNN7jPfe5z7pBDDsmUc88992RkEoiACIhAUQTaMe4WVTfZEQEREIF2JRAbe3tqvNuunOTXbgLvEQgREAEREAERKBsBPxiK3bZz/W+66abKXDZz586tPPzzPmMuVMiRML/MnDlz/KmqLT4PVhIBERCBVhGIjbder1V+yK4IiIAIdBMBH1Njtt3ERXXlBPQGIOciaQ8SwATC4aSubFEKuLN9+/aMVwh0LLEJkJmMTegLe6E/3n6eyVwtv7yteluW3/p8L5w41ttlE+Ju3LjRn67asgmIWV2RiU08z/IzfsjPJoBmkyKz+iM/m6jX6i+svRlDq66WHH4UnVh9ma9MD74wecxEw74erCwmgz5beIct2mJ9zsr6hjU5uZ+YGtcpPnHNmxiXvDZ6Wx91uP/++xM3xo0b56ZMmUJdgvzQQw91S5cuTfRvvvnmqom98Rbh8uXLK3nTi4D4if8rCnt22HVkXRuMN+uHVt9iC0gw3Tzls8nJUbUhQ4akq0rfmty8eXNGDwLfN8OTLBavX78+VKnsb9iwobLvd7AgFksHHXRQRszqNWLEiIweBOyaY/cDa+J9Nhk7WzgAZbHJ6FmMtxYsYf2Q9UGUxRYfYG3A+iXyW3XAuZjE+qFlk8XI0aNHZ4ph/R1K/fv3z+h+4AMfyMisN4xZWaytYNCPi6y+myk0JbB4p9S68hBxI4wd77zzDuXA+hZV3CUM7XkdZpddW9BncZfdv9n4D/nZuG7y5Mk4lUksRrGFLV577bVMXgiYnC3CgfsgS+z6YvmR96233sqYeOWVVzIyNt6GElsEg8VCNoZGfuYra1fosjpY1zf004ndp1ksRT7W31h8Ywt7ID+Lkew+y/oF8r/xxhvYVCWLC7uOWL3YYh8ogHFh8Y3JqhyMOAhthPsRWSsqjearGNBO1xDQG4Bd09SqqAiIgAh0DwEMhPL8tCuZlStXunXr1iXu4TPfWsmfx6Igq1atqlJ98sknq451IAIiIAJFE8gTc/XHatH0ZU8ERKBbCeSJvd3KSPV+l4AeAL7LQnsiIAIiIAIlIZBnMNRTf4hiDr4JEyYkb1Hiv+Njxoxx5513nvv1r39tUl+yZEnlHN4ArJXC8y+99FKVamjFztvAAABAAElEQVSn6oQOREAERKAgAu0YdwuqmsyIgAiIQNsSyBN727YScqzHCOgT4B5DrYJEQAREQAR6ioAfDMWUFz4AjPnsbfjw4TFmMzrph3D4JBc/d911lzvttNPcnXfemflsKPwMpl654edVq1evrio/tFN1QgciIAIiUBCBRuNuQcXLjAiIgAh0JYHY2BuOd7sSlCqdENADQHUEERABERCB0hGIHQyh4uGAyJq7KAQU6odyax/zJmKl3uOOO87hLT3MpbRp0yb3+OOPu1tvvdVt2bLF3XfffW7GjBnu0UcfrZqTKZz30pqDyZcbztuUnr8otOP1tRUBERCBIgk0GneL9EG2REAERKDbCMTG3rzj127j2C311QPAbmlp1VMEREAEuohA7GAISFo9IMKcfP369cvQP+GEE9zs2bPd9OnTk0VO8EDwlltucZdccklFN5ycmi38UFHctRMuipCe8D20E+bRvgiIgAgURaCd4m5RdZIdERABEWh3ArGxt9Xj3XbnJP92E9ADQPWEXieA1ZvClZbYalBwkr3BYv1Ry1YNjF0NCmVZK0rhXJjYKl0434oAy/xHWYwLHjikk+WrX2Ag1LdWD2MPMdgKZpavAwcODItJ9tlbTdbKvmzlSmsFttg2iNWDs3l02UppTJYBskfAymKsrfxspTPosn7AZFZZ4UMmXzZrQ9ZXoM9W/7T6m7+OsQpp3lWAwY8x9D6H21Bv4cKFdIXYUD/vvsUCdgYNGuTuvffe5M1A1Hfu3LlVDwDDFVytNvX++NU7cZxebTC0g/PpazSMwTjvkyX35+ttQ7ZeN/TTy7D17R3K2L51HTE562+wifkX0wmrKKeTFYvSi6wgH7sfWfez9BuayG+ths1WDGYrLLLVFWGXrXic7h/Qs1YhZuWzusIGiw9s5fDwbVXk8yndLyFn7Qo5s8timZWfyRnD9LWDspFYf2XtAt1DDjkEm6oUztnpTzCfcI6tAszyW23I+pZ1bXgf2LXr/bS2yBObL1bPKqsT5Yin4b3Viq95roPQnmfC2LJrA/qsH7MVbNlq5Mh//PHHY1OV8M8tlnzfCs+l56vFObYyMeQsHrMxcHoKDORFYryXLVu2+2TqN5s2g42XWRyCKTauYXGX+YT8bPV1awzA7qmMCysfZbE+YPUXdu9i/5y04ia7n+AriHSyVnJmKzFv3749nT05Zv2NKVp1ZdcRuzaZTchiy0/rotw85SA/8jB/cS5MMTqhvvbLSUAPAMvZrqqVCIiACHQ1gdjBECCFAyI8LKk3117RYPGHFf5gevjhh5M5AfFHxtChQ5NiwgcKbOAd+hL+wZB+KBvaCfNoXwREQASKItBo3C2qfNkRAREQgW4kEBt7w/FuN3JSnXcT0CrA6gkiIAIiIAKlI+AHQ7Hb3gaA1YF9Ct/gDR9GsjcSfB5sw7cewgVBcC60g2MlERABESiaQGy89XpFly97IiACItCNBHxMjdl2Ix/VuZqA3gCs5qEjERABERCBkhDAQKhTkvWpSPhg8OWXX65ZnfD8+PHjq3RDO1UndCACIiACBRLopLhbYLVlSgREQAR6lYBib6/i76jC9QZgRzWXnBUBERABEYghEPNf0FAnxmYrdZYsWVIx7z//hWD06NGVz4GxSEit9MQTTySnhw0b5kaNGlWl+qEPfajqWAciIAIiUDSBMKbG7BddvuyJgAiIQDcSiIm3Xqcb+ajO1QT0BmA1Dx31AgFMJh5OwMom+YVb6VUtIQvz4dgnBLl0ipUhX+zkq8xmutyijq2y2IIl69evzxS7bdu2jAwCNjk4m8gdumwicjxsSCdrvjE2KTKbQNmaYJ71ATZ5MfxhkxKzt6zY5MnIzyZbtvqF1TawEyYrf6hTa98qx2LAbMVOGM70YI/1F8bamtiatSGzibL8ROCNcAMrixdshylWL8xT5P7KlSvdo48+mpg8+OCDXXhNoc/OmDEjWR0Yb/g988wzbsqUKZniIfdvAEI/3dfHjh2bLESwfPnyJG8s07QdZLZ4Md2Mo7sEVt9iCzCwvmHFfdYPWcyBT2wydBb32MJFyM8mMmcLErHJzZGfTSbPrg3ovv7669hUpfQDXpxki31AzuI248Lqj/zsnmzFTXY/CuemhD2krVu37t5J/WZtyPoAsqXnuUyZqhxasYjVwbr3VIwFOz4+BSJnTXzPFgJi/ZgtvgD7bHEPxorJkJ+1LfMfuv76tGxBx0qdFHetOrRSjrgbxs9wv165lm5sLLfsx8ZdFnNg88gjj8yYHjBgQEYGARtXsRhrLZ7EFq5hsZQtFIHymV1rbl2my2IRFvJiiTFgrBkT2GPjeOuaZTZYLGbloywWi6z7UTjVCPIisXt/+E/N3Vq7f7OymK/svgMLbMGPPHHbx7fQJ+Y/zlvXXJgX+1Z+JmeytA2Um/e6Rp4Yf2N00vXTcfkI6A3A8rWpaiQCIiACXU/AD4Zit60C9sADD9CVB315eJB05plnVv4wuvjii/2pyvayyy5zfuA+e/bszD9DMFCHHAl/oECfpYsuuoiJJRMBERCBQgjExluvV0ihMiICIiACXU7Ax9SYbZejUvV3EdADQHUDERABERCB0hGIGQSFOq0CgAdzI0eOdJdccolbsGCBe/rpp91zzz3nfvWrX7mrr77aTZw40T377LNJ8fhMd9asWRlX8Pbe5ZdfnsgXL17spk6d6n7605867GOLY+wjQW/MmDHJfvrXWWedlRbpWAREQAQKIxDG1Jj9wgqWIREQARHoYgIx8dbrdDEmVX0PAX0CrK4gAiIgAiJQOgJ5BjrQbWXCJ0pz585Nfqxy8BbgvHnz6Kd6yHPttde6jRs3ujvuuCN5YHj22WdnTM2cOdNdc801GbkX+LcI/bG2IiACIlAkgXaKu0XWS7ZEQAREoJ0JxMbeVo9325mRfHuXgB4AvstCeyIgAiIgAiUhEDsYQnVbOSD64Q9/6LB4B978W7FiRTIHEeaKw/xlI0aMcB/84Afdeeed544++uia5DFvzfz585PPhW+//Xa3aNGixBbmd5s0aZLD573Tp0+vaUMnRUAERKCVBNol7rayjrItAiIgAu1GIDb2tnK8225M5I9NQA8AbTY600MEMHlrOEm3taBBnglR2SSrbOJXy2YnBUhWBza5OZskGE3MuDAZdNlEu6x86xNENhE5m1SZ+Y/y2eTB1qTIrXjbyWLIGLA+xGSoF5MzmVU+Y2BN4M7alrUr/GKJtQHTY/5Dj12bLD9knqtly8rXTvJp06Y5/BSVTj75ZIefZhNibtgWFmPWXyzd0J73j/VNtvAP9NkCCswmW2zDyu/9SG/ZtcQmF7fq6vtmaJf5yvSQh3Fli2VAl8VDVpYV8xjXvffeG6arkuUrY2VNnM8YMv8trqxvWLGM3TtYHRgrVJy1QTgW8XBY/XGO8bYW8WCLzjCGO3fu9MVWbVkbsgURLF/ZuMrSZWVVOaODhgng/hn2R9ZfGzYeZAzL8GImwzl2HTGZdR2y64j1N5TFYhyTWQtQsD7LYg67jq3yrfsJ84stcDd06FCYziTGK1YGYywWMtbQZXLGwIovsJFOVoxmvJYuXZrOTvsVlFg/ZGVZY01WrzzXEdNlPsFXxpXpMplVV2YzXRZ8tK4h6CqJQLME9ACwWYLKLwIiIAIi0HYEMKBkg0rmaKweyyuZCIiACIjAbgKKu+oJIiACItDzBGJjr8a7Pd827ViiHgC2Y6vIJxEQAREQgaYIxA6GUIgGRE2hVmYREAERSAgo7qojiIAIiEDPE4iNvRrv9nzbtGOJegDYjq0in0RABERABJomoIFO0whlQAREQARyEVDczYVLyiIgAiJQCAHF3kIwdoURPQDsimZWJUVABESguwhgIBQ7GIrV6y6Cqq0IiIAI5COguJuPl7RFQAREoAgCsbFX490iaHe+DT0A7Pw2VA1EQAREQARSBGIHQ8imAVEKng5FQAREoAECirsNQFMWERABEWiSQGzs1Xi3SdAlya4HgCVpyE6uBlYgDVfTyxOc8qy8xBhZ+dkqUXn8yqPL/Mojs+qQtmHpMV+t1bfYqoWbNm1KF0VXL4MSW12QrUb5xhtvZGxC8M4772TkrK2gxOSsrhmDewRs9dI8q3Ix3mxlPRTH5Kx8y1cmt1YaY6tRMl1rFT62oieTsdXurLqyfgVdv9oba3dW51CGto5t71i90H6n74Nt2EctBqxvhPlCDqzPsv5mrZTK4gNboZr1N/jB/LL6zvr160PXk322QiJbdRLKLBaw+rM6IX///v2xqUqWrzt27KjSw8HGjRszsvA+Gp5kXPbff/9QJdnfsmVLRgYBkzMZdBlDxorFZys/u0dAl62SyXhb/Y31I9bf99tvPxSXSWxF0H79+mX0LAHrW5s3b6bqsb6ytoZBxpvVFbqDBw/Ghq7Ympyo8UtxtwacXafQDmEbWXGXWQnzsfOhLI8u64dspde1a9eGRVT2V65cWdn3OywW4ty2bdu8SmW7YcOGyr7fsa4DJmd9m8Uc2GbjGivuMjm7Dq34xOLOkCFDfBUrW3aPw0k2LszTXyoFBDuMVXC64V1ml/mPAljcZrGIrcKM/JYc5xpNebgyX5kMvrDr0LpPh3LwtPqFVcfY2JunrlZZknc+AT0A7Pw2VA1EQAREQARSBGIHQ8imAVEKng5FQAREoAECirsNQFMWERABEWiSQGzs1Xi3SdAlya4HgCVpSFVDBERABETgXQKxgyHk0IDoXW7aEwEREIFGCSjuNkpO+URABESgcQKxsVfj3cYZlymnHgCWqTVVFxEQAREQgYRA7GAIyhoQqdOIgAiIQPMEFHebZygLIiACIpCXQGzs1Xg3L9ly6r+nnNVSrURABERABLqZgB8MxW67mZXqLgIiIAJFEIiNt16viDJlQwREQAS6nYCPqTHbVrJavHix+9rXvuZOPPFEN3z4cPfe977X7bPPPm7s2LHu/PPPd08++WSu4h955BF3+umnV2zBJo4hj02Y8/rWW291H/7wh92AAQMc5qY++OCD3UUXXeRefPHFWDMOc5B+5StfcYcddpjr27dv8oN9yKx5kZnxF154ISkbPsAX+ATf4KOf+5zlK1KmNwCLpClbDRHwwcpnDidC9TJs2cIUbOJZ6LKJV9kkrVZZ7AJkZcF3liw5021W1mxdGQNWV/jJ2oBNFv3666/TarFJbdliEdu3b6f5WVmWr8wAaxcmY3khs3SZnNXLmiCeTTLP+iubgBp+sUU0WFtBlyW2UAO7BpCXTa7N2oX1S+RnE0Mz/6Hr62DVGzpWQpuwdmH6sXosb6fKcN2EbRTuh3Vi/ZDFDORh/Yj1eQycWGJ9zveBUN/ylcUC1jdhi00Gj4FqOrEJ8qHDuLC+zSY8R34WH1j50GV22QT1a9asgXomseuHLZZhXYcsHlu6jBe7vpgs4/gegaXL+ptfwCK0xRY8wXnWD1l/ZayQn/VXtggKdNkfB2wye8Ya+dniB6xfsGsA+ZnddevW4VQmjRw5MpGxBb4yyikB2spqr5RqtF46XycfI3ZZ8avRejF7sTKUyXRZfFm2bBl18Ve/+lVGbi0YwsYPLJasXr06YxMCtogIW3CEyZCfyVldocuuJea/tWgdWwSELf5k3U9Z+SzmwFd2n4S8FYnFHRY3DznkEFo8k7P79NKlS2l+FrdYH0Lm2FhECzKE7Hqx2pCNE5gMRYVcG2nP2NjbCiYe1THHHON++9vf+sPKFuOCV155Jfm588473bnnnuu+//3v03GQz4T+f+GFF7r58+d7UbJFbMHPfffd5y644AJ322230fGYz4R758knn+wWLVrkRcl2xYoV7vbbb3c//OEP3c0335zYqlJIHfz+9793p512mktf788//7zDz7x58xKfJk+enMpZfYh6f/GLX3ThWAl/G+PBKH5+8IMfuIceeoguFFdtqbkjvQHYHD/lFgEREAERaFMCfkBUb9um7sstERABEeg4AvXirT/fcRWTwyIgAiLQxgR8bK21baX7/uHs0KFD3aWXXuruvfdet3DhQvf000+7b3/7227YsGFJ8XfddZf77Gc/W9OVq666qvLw7/DDD3cLFixIbGGLYyQ8dLv66qtNO3iQircF/cO/M844I3lzEA/zvvOd77iBAwc6/IMUbwLWeqMQ/5A45ZRTkod/eFB7xRVXuCeeeCL5wT5k69evT3Ssf8TCyYcffth9/vOfTx7+DRo0KPEBvqBs+IYEXvC5kYfAiYHIX3oDMBKU1ERABERABDqHgB8AxXgMXSUREAEREIHmCCjuNsdPuUVABESgEQKxsbeV491x48a56667zp155pku/VbklClT3Gc+8xk3depUh7eJ8SAPD8Pw1mA64fyNN96YiI888sjkQZt/43/SpEnu1FNPddOmTXP43PiGG25wn/vc5xx7sxRv9/lPji+++GL33e9+t1IU3tSbPn26O+KIIxzeQL3kkkvcSy+9VPUmplfGw0j/RvxPfvITd9ZZZ/lTyae7sPGpT33Kbdy4MXkgibcc0wlvD8+ePTt5sxhfHzz11FPJZ8he72Mf+5ibNWuW+973vpf4/KMf/ajuQ1Kft5Gt3gBshJryiIAIiIAItDUBPxiK3bZ1ZeScCIiACHQAgdh46/U6oEpyUQREQATanoCPqTHbVlXmwQcfdJ/85CczD/98efgE/lvf+pY/TN4QrBwEOzfddFNlio25c+dmppfB1CqQI+Gz+Dlz5gS53931DxExDQgeFKYTHhr+/d//fSJevny5+8UvfpFWSd76+9d//ddEftJJJ1U9/PPKqDPOIeHBXfozYchhG58dI6FMzP+XTvDRTwnF/E3rN3OsB4DN0FNeERABERCBtiQQMwgKddqyEnJKBERABDqIQBhTY/Y7qGpyVQREQATalkBMvPU6vVmJY489tlL8q6++Wtn3O/Dx/vvvTw7xRiHeHGQJ8kMPPTQ5BX3kCxPeIsQbfUh4QGfNxxx+isweAP77v/97ZT5QLGJiJW8HcxciTzphzkKfvK4/9lv4CF+RlixZkrwp6c8VvdUDwKKJyp4IiIAIiECvE/ADndhtrzssB0RABESgwwnExluv1+HVlfsiIAIi0BYEfEyN2famw+GiZOnPhOHXypUrnZ9LEJ/51kr+PBYFWbVqVZWq//QXQq9XpbDnAAuHYYViJHyWm06xdsIyatnBQ0u2WJkvt54dr9fsVnMANktQ+QsnwFZHRCEIaulkrYjFVmliKy8xPausdNk4Zqt0Qc6CGvMfuizl0WX5rXrF6lr5mZy1AVvRC2Uz3VibyM8mRWX5ocvaG/J0svIzX612YWWxlSOt/Gxlu3BFMO+znwPDH/vt3nvv7XcrW+Y/TjIbbGU8xhr52WqSzH+2yirys9UsIWfJ87J8YXm8DHl9fi+ztrF6Vv4yy9n1wfomGLBVbJluOAAM2TE560dW32b9hMlQJrPLfGWrPiI/u+ZZfmuFSRYfmE2UxewyVtYKtKwOrF2ZHspncqsNYq8lVj7KYsniwmKZn2Q8tIMJyVlicY/du1lbwR5b1d7PE5Quz/9BE8pZLGQrAyMP441VFdOJ9QvosD84mAy6O3bswIbG+uREjV+KuzXgtOgUu+aYzCqeXYtsbGut7Mti3Msvv0yLY2Wx+MJswiC7Dtj1uc8++9DymZyNn5CZ+cBWm7WuWabLPg1k9Uf5W7duxaYqWbqx7W3FUiZnsRDODBgwoMonHLC4y1ZBhi5jwFhZ5bM3uVgsRlmsv8SyQn6WGCsmQ17W35kMuqGNRnxEnph8MTrwp1Xp8ccfr5geP358Zd/v4M03n/AGYK0UnsfbfqNHj66o57WDNwax2Aeu5zAmeDvoz9Y9E4UOGTLEYW4//P3r3zz0zqB/+5XNQ5/9+XAbnk/bCfWa3dcDwGYJKr8IiIAIiEDbEYgdDMHx3h4QtR08OSQCIiACDRBQ3G0AmrKIgAiIQJMEYmNvON7FyrX10vDhw+upRJ/HPxauv/76ir7/3LUi2LUTrqJbr+wRI0ZUsvoHbF7QiB2wQT7/aTFseTv1fIEu/HnxxRcrD/sgQ/I2sF/PTq06IX9RSQ8AiyIpOyIgAiIgAm1DIHYwBIfDAVHbVECOiIAIiECHEVDc7bAGk7siIAKlIBAbe8PxLlbCrZdC/Xq69c5jsY6FCxcmameccUayAm86T/glA3tjN9QP39RLv0VatJ16vsAv70+rfAnr3uy+HgA2S1D5RUAEREAE2o5A7GAIjhc5wGk7EHJIBERABHqIgOJuD4FWMSIgAiIQEIiNvb013sWnv1/+8pcTjwcOHOhuueWWwPt3d8PPua0pwbx2OO1MelqXou3U8wU+eX9a5YuvdxFbPQAsgqJsiIAIiIAItBWB2MEQnO6tAVFbAZMzIiACItAkAcXdJgEquwiIgAg0QCA29objXbyNh7nrWp3wWezpp5+ezMmIOTvvueceh4eALIVzev7v//4vU6nIwjlv03MCp+2ExxUDe3bq2cF8oPV8gSlvp54v6fLDY28DsrSdUK/ZfT0AbJag8jdNAHMChJOiWk/Z2YSw1oS4oT3vIJOxCWKhzyaOZ5MiM598eeltOMFr+lz6mPnFyke+PHbT5eCY1ZXpQRZblqXH6sXaxcrPJsNn+S3/WflW/S05s838ZX2TyWAvvCF7+/4/Sf4YW1Z/yP1r59j3ifmEc+wmyPqWdR2yifPD/7T58q2JsVldfZ701rdtnjxpGzrmBBC7PF9osD4AObsOmAy64cAFx0isH4bl7tba/Zv5wMqy+gPLbw3amN3QF79v+crqxWwyn2Cbya3BHrvmLL+83+GWMWDlh3nCfXafY/VHHtY2rCymF5YZ7ltlsRjFdFnct3xN/+ceeqxdIU9/5gPZ8uXLsckkrGyYTqwsVifkYzE+bQ/HbIJ9yNnCXFu2bMGpTPJyK4ZnMkjQIwTyXDPsmmPXBhxnsYTJrPELW/iGLWCBsiwfcC5MrHycZwtAsGuDxSzkZ3atT/v2228/ZKlK7B7HbCITu+aeffbZKns4sJiw+GKVZdlIF2bpsbGl1d/Y/YQtaOTjSNoHFo+ZX1Zdma9MhnJZWcwukyE/60dsbM70kJ/Zte4noZxdv7BXdMLDv3pz0jVbJu59J554osNigeB09913u2OOOcY026dPn8o5dg1UTu7aCe9R6es4bYf97eNt1bODB4D1fIEtb6eeL75ctvU2cC5th+k3KntPoxmVTwREQAREQATamQAGsDE/7VwH+SYCIiACnUQgJuZaDxc6qZ7yVQREQATaiUBM7O1Jf9etW+eOP/54hy0eht5xxx1uxowZNV0IH0iGi2ewTOHCH+HiGdBtxA58DPOFdur5Al3vT9qXcJXsena8DdhL24GsqKQHgEWRlB0REAEREIG2IRAzEAp12sZxOSICIiACHUogjKkx+x1aTbktAiIgAm1FICbeep2ecBxvhZ5wwgluxYoVSXFz58515557bt2iJ0yYUNF5+eWXK/tsJzw/fvz4KpVG7OCBW/qNYm9nx44d5hv2KBgrKvu3ftO+4G1E/zAv9LnK4T0H4fm0HabfqEwPABslp3wiIAIiIAJtS8APdGK3bVsROSYCIiACHUIgNt56vQ6pltwUAREQgbYm4GNqzLbVFcHDspNOOsktWbIkKer66693s2bNiip29OjRbujQoYkuFg6plZ544onkNN6wGzVqVJXqhz70ocpxLTuYNmPZsmWJ7tSpUyt5/E6snbCMWnaWLl1a80FiPTver2a3egDYLEHlFwEREAERaDsCMYOgUKftKiCHREAERKDDCIQxNWa/ldVbvHix+9rXvpbMP4XPujB3F+ZUGjt2rDv//PPdk08+Wbf4O++8M/l0DZ+G1fuBrpIIiIAI9AaBmHjrdVrpH+bL+/jHP+7++Mc/JsVcddVV7sorr4wuEnHWfyaMt+GeeeYZmhdy/7Yc9JEvTIjz/g26n/3sZw5+sRTGbSxUkk6nnnpqZZ7OH/zgB+nTlWNvB/NZIk86nXbaaRWR160I9uzAR/iKhDcPUYdWJS0C0iqyshtNIJz4FJmsyVzZ5NhscnTLRroc6IWTbeLYJwTJmJQOOD4PmxCW+Q99pssm2WWT2SI/myyW+c9kVn7IWWL1Ze1l1ZXpssl/mR78YXJWf+iyCavZYhVMD/mZXVZ/6DK2VntBPyaxPmDdwJhf1uSxjDfzldU/xm+vkyc/4wc73lfrvC+LbZEnNl+sHiunU2W4ljxf1IH1AchZ3GR9E7qMI8tvxW3Wj0MfUQZSnvhilcXqy3xlMvjA6spsQpclFsus/EzOyre4MK558oeTafu6WFzYwhYsbln5mV9WLNm5c6d3p7K1Fh+oKAQ7rA3YJP/WPYKVhc+AWMIbEenE7v3MJ+Tbd99909npggjsHoeM27dvz+T3nyulT/gJ/RmLtG76GO3H2jCth+NYPZa3ngyTzP/2t7/NqCF2vfLKK8kP/gjDJ2nf//73zZiSMdCkANdoGNOs9mJsmAzuWPImXc1kZ/01o7RHYOkyecjD22MxC+dYflZ/q+8yu9Y1169fP+9OZcvufVZZrG0t3UoBwQ7jwhagQBZWB8aF8UN+JmexHLosljFd5j/yW3KcCxNrK5xn90PrfhLaq7XP+EGfLRzBxtZWndi9i/mPsljfgjw2ob1Zm6fzx+ik88Qeow54iPbUU08lWS699FJ3zTXXxGav6F122WXu9ttvT8afs2fPdnjTL1wkDf0NciS0HfRZ+ru/+zs3c+ZMh3v1FVdc4W6++eYqtVdffdV9/etfT2SHHHJI4nuVwq6DwYMHu09/+tPuRz/6kfvP//xPd++997q/+Zu/qVLDqsY4h/SZz3wmyVOlsOsAXA466KDkk2iUedZZZ7mDDz64Su3yyy9PFkuBEPutTHoA2Eq6si0CIiACItArBGIHQ3CulQOiXqm8ChUBERCBXiDQLnEXk84j4VMy/KH14Q9/2B144IHJH5RPP/20+9a3vuXWrl3r7rrrruSfhT/5yU/q0sIfeP7TNKacnjye6UgmAiIgAq0gEBt7WznePeecc9wvf/nLpHof/ehHk4dvL7zwglld/EOEveUGGR6A4dNhvMmNT2rxFiEemOGh3Te+8Q3nV9SG3pgxY2gZ5513XrLwCB5Ifve7300+vf3bv/1bhxW+Fy5c6P75n/85mbcPD3C/853v0AfpMHzttde6//iP/3BY8Rx1hE+f+MQnkjIffPDB5H6CgwEDBpgPPPHPaMyDeMoppyRlok5XX321mzx5cvLQD/+I+rd/+7fEJj47xoPEViY9AGwlXdkWAREQARHoFQKxgyE418oBUa9UXoWKgAiIQC8QaJe4O27cOHfddde5M888M/N205QpU5I/rvAHGOZ+WrBggfv85z/v8NZgrYQ/Skel5pmqpa9zIiACItBTBGJjbyvHuz//+c8r1X3sscfcYYcdVjlmOyNHjnSrVq1ip5KHbhs3bkwe4OFh39lnn53Rw9t9td4wxJut9913nzv55JPdokWLkgds/iGbN4a3avFm4PTp070os8UCHg888IDDZ7yYMxAPIPETJrwpiLJq/SMIftx6663ui1/8otuwYUPlLcbQDh4I/uIXv8jct0KdIvY1B2ARFGVDBERABESgrQj4wVDstq2clzMiIAIi0IEEYuOt12tVFfFWxic/+Unzj6j+/ftX3tqAD/isq1XJ+oS8VeXJrgiIQPcR8DE1ZtsJdPBW3vz5891DDz2UzAmIt6/xxiC2mPPv4YcfdvPmzav7STli/e9+9zv3ve99z+HNugMOOCD5tBuf4+JtwD/84Q/uggsuqIvkqKOOcs8//3zy1t7EiROT+WTxOfj73//+RIY3HaFTL/kysYUP+MwcPsG3W265Jfl8Gj63OukNwFYTln0REAEREIEeJ+AHQTEFQ1dJBERABESgOQKdFHePPfbYSmXxWVmrEv74VBIBERCBVhKIjb2tHO+2wjbemsNPMwnzBH7hC19Ifpqxgwdz+GwYP80kPEDEHIe9mfQAsDfpq2wREAEREIGWEWjFYKRlzsqwCIiACJSAQKfE3XBBBrYIQlFNgU/PlERABESg1QQ6Jfa2moPs1yegB4D1GUmjxQQQsMKVkqwAxgZo1spLbOVHtiKXVZYlT6OI1UM+y1cmZ6s5stWoYJetKMVWk7I+Q8mzehZrAyZj/OErW8GM1cta/SscsMMeUth3dkt2/47lwvRgwfIhLMPvs37AuLK2tspi9WL1t/Jb9WIrZzJdqyxWh7322sujqGytFbZZvSqZCtxBm7B2YUXE6rG8ZZGxdkXdGBurDVmfYX2LxQGUZcUNnAsT8wnnWX4WX6DL6sviJlvBFvnZ/YRxYfVHflaWpctiicUAttOJxTK26iGL5bDF6sX4QZe1AeTpZPnP5Kz+sMfawK9gG5bHVqjEeVYHVlfWr5E/djVM6Ma2wd577w31TGKfBDGbrF/BGKuXxcXfI6z+mHEuEKD9WBsGKpXdWL1KhoJ3Hn/88YrF8ePHV/atnfPPP98tXbrUoY/17dvXYdXI448/PnmrZNiwYVa2ZJ5Bf3LQoEFVE81bKzGzvm31Q+v68GX6Lesv/lx6y/qL1V7sOmLxBWWwsQLTtcpK+4njPL6y/BYXdp9i8Y21Fcphbct8ZT5BxuIxYwVd9jcDu35ZWyF/nsTsMpnFlTFkdbVYsbKYzKoTY8D4IX+fPn0yZvC5ZjpZdWV+WTH6rbfeqpiNvaYrGXbt4JqJuW5idEK72i8nAT0ALGe7qlYiIAIi0NUEYgdDgKQBUVd3FVVeBESgIAKNxt3169fX9aDW5Op1M6cU8HABK0z6hPkC66Xf/OY3FZUtW7Y4/Pz+979P5hK86aab3EUXXVQ5H+7E1C3U174IiIAI5CUQG3s13s1Ltpz6egBYznZVrURABESgqwnEDoYASQOiru4qqrwIiEBBBBqNu1j5sF4qMk7PmTPHLVy4MCnyjDPOcEcccYRZPCZqh87RRx/tsBok0ooVK5IVJbF4CN4AwyrCeAvowgsvzNix3obPKEogAiIgAg0SiI29RcbRBl1VtjYgoAeAbdAIckEEREAERKBYArGDIZSqAVGx7GVNBESgOwl0QtzFp79f/vKXkwYaOHBgsvKi1Vqnn366O++88zKfcE+aNMl96lOfclhtGA8HMcXKl770JXfqqae6wYMHV5mzPt2tUtKBCIiACDRBIDb2arzbBOQSZX1PieqiqoiACIiACIhAQsAPhmK3wiYCIiACItAcgdh46/V8aXgbb/Xq1TV/vG4z2xdffNHhoR7m5sL8oPfcc4/DQ0Ar7bvvvpmHf6HuJz7xCfeVr3wlEWG+0Pnz54enk302l1xGSQIREAERaIKAj6kx2yaKUdaSENAbgCVpyE6uBiZkZRPAputkTQib1sOxNSEr021GhkDLEpMzGfKySWIZD2vyXzahLSurkUllWd3Ssjztss8++6Szu7/8y7/MyPK0nzWhLvuvO2PAWGUcakDA7FqsWH1ZfquuzC7rV6gGs2vpsmqzfsgmUGYy2GOL0bB2ga731W8hi03IE5svVi+27E7UY30Q9YiNL1adGVurvzFdJmN90PLV0mX+suuoXt8M7bD8zH/kYdeBpRuW4fdZu7D7BvTZQigsv9UHWNyxfGVty3QZK1+39Jb5Ch3WtuxzSyZDfrYIBvOV1Qn52eT/zCZ0WWLtxe6HyMt0mU0r7jLerF1h0/dNq++zcr0M/BhDfz7chnpDhgxxRc7xF5bj91euXOlOPPFEt23btoTn3Xff7Y455hh/uuEtPvvFQ0DUB28XXnXVVVW2woVd8AlxeD1a/QU+ptP27dvTouTYL9oSnmRta7Un6xuhrXr7LG5Y/ZXpMpnlK4sF7PpksQH1YLphe4R1Dfunl+fhyq5FZtOqKxvDMv/hW+xD5mbb2nNIb1m9mAz5GMO0vVrHzC6TWTZYf7P6K5OzRUys/sbahbUrfA37C2Lwhg0brCpQORjEcIjRoQVIWCoCegOwVM2pyoiACIiACICAHwzFbkVNBERABESgOQKx8dbrNVdafO5169YlK/ZiiwcAd9xxh5sxY0a8gRqaeIPQrwy6du3ajCYebiqJgAiIQCsJ+Jgas22lH7LdGQT0ALAz2kleioAIiIAI5CAQMwgKdXKYlqoIiIAIiAAhEMbUmH1ionDR5s2b3QknnJAs3AHjc+fOdeeee26h5bC3inwBY8eO9bvaioAIiEBLCMTEW6/TEgdktKMI6BPgjmouOSsCIiACIhBLAIMdJREQAREQgZ4j0E5xd8eOHe6kk05yS5YsSQBcf/31btasWYXC2LRpk8NDRqShQ4dmbGPBECUREAERaDWBdoq9ra6r7DdHQA8Am+On3CIgAiIgAm1IIM9/OjVoasMGlEsiIAIdR6Cd4i4W5fj4xz/u/vjHPyYcMTfflVdeWTjT22+/vTL31rRp0zL2jz766IxMAhEQAREokkBs7NV4t0jqnWtLDwA7t+1K4zmCUTgxrTVBbKjjKx9Omupl1pZN3MomeLXy5wmazFc/sXbaPvOB+cpksMU+PWGTCjM95GflW3VlclZXqyw2gTObPNfKzybUZRNgo17MV1Y+89/KDzlLjCGTMZ9gz5Kny2L+Q4fxYn0AuqwfMl2rLDYJNZvI3OLK7DL/4WszCUxjucbqNeNPu+XFdRe2hdVerB+zaxb1YzYYW6aH/Ew39BE6SEX0F+YDuw6YHnxgcuY/dFli+ZkeZIxBuLCAz9e/f3+/W7Vl9w52n2UyGGKTlrNr3tJlXC1WTM76IMpi/YAtzMFkyM/qwOIb8wn5WRsyn6Br1QHnwsTiM85v3bo1VEv2mV9WG7I+xGQw7PuLVZeMI4EAPjG/ApXKbqxeJUOOHXDAar9PPfVUkuvSSy9111xzTQ4Lzq1atSpZMOTwww838z344IPua1/7WnIeC7icf/75Gd1wnIoFJ8KFXjzrdKa99torLXL7779/RgYBWxxk48aNGV2mByXWjzOZawhYO7JrHibY9cXuJ9Z1wPKzfsxkKL9v377YRKUtW7Zk9FgstBYRYW3LWDMZCmZ1sBY0YrwZV+uaZrwtv1h7W3YzAHcJWH6mZ9lksdTSteqQLs/Kz9qQtXd4TYe22cKH+McES6EN657F8nkZuMawjdHxNrUtLwE9ACxv26pmIiACIiACIiACIiACItBVBM455xz3y1/+MqnzRz/6UTdz5kz3wgsvmAzwkC49Vx8eAB577LEOb/Cdcsop7gMf+IDDgh9IK1ascPfee2/y4/+gvvHGG92wYcPMMnRCBERABERABNqBgB4AtkMryAcREAEREIFCCcT+NxSF+j/gCnVAxkRABESgywi0S9z9+c9/XiH/2GOPucMOO6xyzHZGjhyZvPHHzj399NMOP1bC23pz5sxxF154oaUiuQiIgAi0lEBs7NV4t6XN0DHG9QCwY5pKjoqACIiACMQSiB0MwZ4GRLFUpScCIiACNoEyxd0jjjjC/fjHP04e/i1evNitX78+WewDn6Hut99+7n3ve5877rjj3AUXXFB5M9AmozMiIAIi0DoCsbFX493WtUEnWdYDwE5qLfkqAiIgAiIQRSB2MARjGhBFIZWSCIiACNQk0C5xt4iY3qdPH/fpT386+alZaZ0UAREQgV4mEBt7i4iNvVxVFV8AAT0ALACiTIiACIiACLQXgdjBELzWgKi92k7eiIAIdCYBxd3ObDd5LQIi0NkEYmOvxrud3c5Fea8HgEWRbAM7V155pfvmN79Z8eTXv/61+8hHPlI5ZjuPPPKIu/32292iRYvcpk2b3IABA9ykSZOSuUymT5/OsrREFq7AxFZ4QqFMzmTQZSs/saAXlot8PjFdfy5my8pnq3TBFlupi63+xfSQn61SxVYCZHrIz8pi/kOXrcAGeTpZ+d966620Kq2/tVIbWwXYWlGLrdbG/Gf1zzi5R2D1F8Y2XPnP27PKYryYzOqXTNfqb0zOZIyVr0d6a/mV1sMxY8hk0LX6PM7VS/Ap1q9YPVZmp8ZdrDgXxk/rOmJsrHZh/Zv1LXZtgi1biZBd86HfYZuw8pkMeZgNtvImi6XIz+SsH7NykN/yC+fSifmFe3U6WasAsxUFWbum7dU6Zjahz+IGi0+MFfIzucWK6bI+ZPnK2pD5ymTwlSWrvRlv5itbvRXl7NixI1Mcuw5ZOZmMewRWvfxqlIyvZcvLUX6sD7F63na47dS4izYL2y3cD+vH9lkshB7j+Oabb2ZMWO3JYnQm8y6BdR2yfmzdT5hu7HUIn1ifZf5b5bOVfVldIWMr7rL2sq555itrA6tdWVmMFXxl91TWL1j5yM8YsvzQjU1WWawfxcpQNuNiMWR1YO3KykdZeAs4nfr165cWUT0oMb/YKsLQDX2w+i/0rIS6svqm9WN00nl0XD4CegBYkjZ97rnn3Le//e3o2uDGhAmL58+fX5Vn7dq1Dj/33XdfMq/JbbfdVhWUqpR1IAIiIAJtSiB2MAT3Gx0QKe62aePLLREQgV4hoLjbK9hVqAiIQJcTiI29jY53uxxv6ar/ntLVqAsr5B/m4T/vAwcOjCJw1VVXVR7+HX744W7BggVu4cKFyRbHSPPmzXNXX311lD0piYAIiEC7EfADonrbRvxW3G2EmvKIgAiUnUC9eOvPN8JBcbcRasojAiLQDQR8bK217QYOqmN9AnoAWJ9R22t85zvfST7hHTdunJs5c2Zdf5ctW+ZuvPHGRO/II490Tz31lDv77LOTT3+xffLJJx3kSDfccINbvnx5sq9fIiACItApBGoNgNi5vPVS3M1LTPoiIAJlJ8Biay1ZXh6Ku3mJSV8ERKAbCNSKs+lz3cBDdaxNQA8Aa/Np+7Ovv/66+4d/+IfEz1tvvdWxecfSlbjpppsq8/TMnTvX+flevB7mG4IcCW8Vzpkzx5/SVgREQAQ6gkB6wFPvOE+lFHfz0JKuCIhAtxCoF2fT5/NwUdzNQ0u6IiAC3UQgHVtrHXcTF9WVE9AcgJxLx0hnzZrlsLDCeeed56ZNm+aw8EethIBw//33Jyp4Y3DKlClUHfJDDz3ULV26NNG/+eab6eTcNHNOIRZQCCfRhY8ssUlqrcm92UTDzCY+J4lNTNea5JbZZJOjQy+su8/HymL19/rpLdO1Hg7Hlo8ydu7cmS6K9gtWPjKyCYxZWzGfkH+fffbBpipt37696tgfMF9Z37LaMJyQ19u0/GKLgDCZVRbjwny1+hDjzfKjHqxvMZmvc8yWlWXVldmzdD1D+McmuWa2vAw+Mb/8+XAbq+fzlCHuYiLqcDJtK5ayvuk5pLfsmmGydD5/zPpxnr7p+4u3h6014TbTZZODW32T1YvJQsahX5bdUMfvs7jHZFZdmV9MZrU1s/unP/3Ju1e1ZdcSk1n1Z7pVBQQHrG+wGM3aGmZYf4uVIT8rH3KWWL1YPLfagF2frK5MBn8YbyYLdRkLVrdQhnqyuoY6fj9Wz+uXIe7iurPayNcTW9YPWHyCLpOz/NBlKbYfW/2F5bfiA/OL9W2rbzA566eWryw/YwIZi5FsUQdrbM10mV9MD+WzerFxLXTZOJqVlaf+sNuKxPxirK24zRbFSr/IUstvxsC6T8f6tf/++9MimV1WPjKH/cBqZ1rIHiHsWrbDfDE6ob72y0lAbwB2cLv+7Gc/cw8++KBD4PGf9NarzsqVK926desSNTwwrJX8eSwKsmrVqlqqOicCIiACbUXAD4Zit7HOK+7GkpKeCIhAtxGIjbdeL5aP4m4sKemJgAh0IwEfU2O23chHda4moAeA1Tw65ghvPV166aWJv9/4xjdc//79o3xfsmRJRQ9vANZK4fmXXnqplqrOiYAIiEBbEYgZBIU6Mc4r7sZQko4IiEC3Eghjasx+DCfF3RhK0hEBEehmAjHx1ut0MyfVfTcBfQLcoT3hiiuucG+88YabOnVq1MIfvppr1qzxu2748OGVfbYzYsSIinj16tWV/ZidsBymv379eiaWTAREQAQKIZBnoAPdmKS4G0NJOiIgAt1KQHE32/Ia72aZSCICIlAsgdjYGzveLdY7WWs3AnoA2G4tEuHPb3/7Wzdv3rxk/iYs/MHmU7DMhPMKsDmEwnx777135RDzDOZJ4cPDPPmkKwIiIAJFEIgdDKGsmAGR4m4RrSIbIiACZSaguFvm1lXdREAE2pVAbOyNGe+2ax3lV3EE9ACwOJY9YgkT6F544YXJH6xf+tKX3MSJE3OVG062a01c6w2GE5JaE/p6XW1FQAREoJ0IxA6G4HO9AZHibju1rHwRARFoVwKKu+3aMvJLBESgzARiY2+98W6ZGalu7xLQA8B3WXTE3nXXXedefvlld+CBB7p//Md/zO1zuJofW40rNBiuuplnhSXYqPfJMD6JmDx5clIcHkqGKy1ZwYm96chkMMrkzC5bhQ/5mS7ksYnlZyulwV7I2dtnuu+8844/XbUN2fkTLH/Y9l4PW7ZKFeMHXeYD02U+IT9b/Y7lt1b/YnVgNlFW+LAbx0hsVTXLVyZn7Qq7jDeTMZvIzxiw/FZ/ZfViNq2yLIbQj0nMVysfKyv8Z0OYz7+FjPqxlQ5DXbZvtRfTrSUrY9wF07CPhPu1WOCc1Q/r5fPn8/QXpsv6O2zHXvPQZdciqxcrH/lZYjatWJaHN7PLZFZZLG6yfwBaXNk9ylp9nXFhDPPU3/KL/WOS1dXiwnxg9zgrjjA5swkmLO4xXWYT+RlDJoMuS+w+z2TI6/sGux6Y7bTMqkNar95xGePuihUrKnxRf6sNWNta7cG+0GHjexYzLB9Y37Tai7U3kyE/k7Prm+lZ5bPrm8mQn3G1ymLjkn333TfjxoABAzIyCPr165eRs9Vi+/btm9GDgMVdf22mM/jFHUN5+MWXl7N7pD+X3lp9wOKVzm8ds/ysLKu/svxWWUzO+gaLz8jLeG3bti1jduDAgRkZBAcccEBGzu5RUAr9sto5YywlaJZNypwOS0xADwA7qHHx4O/rX/964vHcuXOd/+M4TxX69OlTUWeDhsrJXTvhH9z1PhcO82G/3vyCaX0di4AIiECRBDAQih0M1dJT3C2yVWRLBESgzAQUd8vcuqqbCIhAuxKIjb21xrvtWjf5VTwBPQAsnmnLLM6ZM8fhv3oHHXRQ8ibW3XffnSnrhRdeqMgee+yxZKEQCE455ZTkgWH4YK7eQh3hW3ya06+CVTsiIAIdQCB2MISq1BoQKe52QGPLRREQgbYgoLjbFs0gJ0RABLqMQGzsrTXe7TJkXV1dPQDsoOb3r4PjE4Jzzjmnruf//M//XNFZuXJl8gBwwoQJFRnebKmVwvPjx4+vpapzIiACItBWBGIHQ3C61oBIcbetmlXOiIAItDEBxd02bhy5JgIiUFoCsbG31ni3tHBUsQyB92QkEpSawOjRo93QoUOTOj7++OM16/rEE08k54cNG+ZGjRpVU1cnRUAERKCdCPjBUOy2lb4r7raSrmyLgAi0C4HYeOv1Wum34m4r6cq2CIhAOxHwMTVm205+y5feIaA3AHuHe0Ol3nnnnQ4/tdJXv/pV90//9E+Jyq9//Wv3kY98pEodE63OmDHD3XLLLcliIs8884ybMmVKlQ4OIPdvAEKfTdCaydSgID0pr1UWkyPQscQmS2YTDbO8kLGymK5VPtO1bDK/0kyYvVoya/JclieceNaftyagZXLmv7cTs2WT71o22eS7O3bsoMWwSbBZG7D6wyDzi/Ur6LL2YnWw+guTM5tW+axeTGbVK09/Yb4ymVU+60PWpMjeL2YfdamVkCc2Xy29ssbdLVu2VMW5//u//6M4WT+02pbZYGyZTVr4LiHTZdc28rNrjl3H0LXkONdoYuUzJrDPrgPLp1gGFhd2fVlxj9WdLYzBZCwvZFa9LP20nNUfOmyC9nReHFvls77J2pDpwS5bwMHiyq4ZJsuTn/nFFi6Ar3kWcvNx17rfwJ6V4BPzi+nX0itr3H3ttdeqFiBifQismJz1F+iy68CKBdBPJ9/eobxW24R62Gf5mQy67FpkukyG/Oz6YHOUM37Iz1hZsWyvvfZClqrEFuxgC4MgU//+/avy4oAtFmFds1gsMZ2sdmX3GSZL2/PHrG9ZfSCPrrcfbpldFuOZHuwwuVVX1t5s8Sirv7H8GzduDKuT7DMZToRf3flMgwYN8rtV23Bef7aAS5UyOQAXxiatGqOTzqPj8hHQG4Dla9O6NbrssssqN+HZs2e7dDDEMeRIuIlCX0kEREAERKBxAoq7jbNTThEQARFohIDibiPUlEcEREAERKDMBPQAsMyta9Rt7Nix7vLLL0/OLl682E2dOtX99Kc/ddjHFsfYR4LemDFjkn39EgEREIFOIeD/Gxq7bXW9FHdbTVj2RUAEeptAbLz1eq32V3G31YRlXwREoB0I+Jgas20Hf+VD7xLQJ8C9y7/XSr/22msdXlm+44473LPPPuvOPvvsjC8zZ85011xzTUYugQiIgAi0OwE/CIrxE7o9kRR3e4KyyhABEegtAoq7vUVe5YqACHQzgdjY21Pj3W5ui06ou94A7IRWaoGPmO9g/vz57qGHHkrmBMTCIJiTCFvM+ffwww+7efPm0bk9WuCOTIqACIhAoQT8YCh2W2jhhjHFXQOMxCIgAqUgEBtvvV5PVFpxtycoqwwREIHeJOBjasy2N/1U2e1B4P/t6ig98+pDe9RXXrQJgTVr1rgRI0Yk3pxwwglVE1T/z//8D/WSLfZgTd771ltvZWywSVXT8x/6TGyiXTYhNpsMFzaYnMl8eekt02WT5CKfJU/bZJMvQ4dNdGxNGM64sMl3mf8oi8lZWeFkuMjnE2sD1i+gz/xirKwJmNkk/WyCeJTF/GJ1tcIts8tYs3JQPpvAmJUPXSZnMmbTys/6ljUJN9Nl7YKyvBzbN998EyK3evVqN3z48GQ//SuMK1i53PIhnQ9cV61alYhr2U/n67TjkA/aN2x3zzqmTmG+UJ+1LetHVj8Obfl9VpbVrkyX+QTbTM7ysziC/Ow+xa5jVg7ys4U5rLjHdPv06QMzVYnpQYHxZpObW/dDFmMtXdaPWCy1YiHz1WqDqsrvOWD9zWoDlp/5b/nKeLPyUQ7rW6x8637E+garV79+/ZhZuvgA66/I7MdV6OOLFi1K7NWKi2FcUdzN4g/5pONuVnu3xOpzln5azvobkyEfK4v1Y7YAB/KzMSTrr9BlNtg1z8Y/yM/Gi6zPMz3k37RpEzZVCQtiscRs7L///hlVpgcldi0zrkyG/Nu3b8emKq1du7bq2B+8/fbbfreyZTHeuuZZH6gYitjJk5/1Q3ZPZ30FrjBdy0XGgN1PrDZgZTEZuwbgE1vwgy1aA91QDr+ffPJJiAsf8+J664bxbgJPv0wC+gTYRKMTIiACIiACnUoAA9LYQWmsXqeykN8iIAIi0BMEFHd7grLKEAEREIFqArGxV+Pdam7deqQHgN3a8qq3CIiACJSYQOxgCAg0ICpxR1DVREAEeoyA4m6PoVZBIiACIlAhEBt7Nd6tIOvqHT0A7OrmV+VFQAREoJwEYgdDqL0GROXsA6qVCIhAzxJQ3O1Z3ipNBERABEAgNvZqvKv+AgJ6AKh+IAIiIAIiUDoCsYMhVFwDotI1vyokAiLQCwQUd3sBuooUARHoegKxsVfj3a7vKgkAPQBUPxABERABESgdgdjBECquAVHpml8VEgER6AUCiru9AF1FioAIdD2B2Nir8W7Xd5UEgB4Aqh/0OoG//uu/dvvuu2/FD2v1L7YSoV+trpJ5zw7TfeWVV9Jq7rXXXsvIIGArR7GgyWTIz1a5Yiv2QZetKMXsWqtUwUY6sVXVrNW/2GqOli6rFyuLyeAjy89Y2EHlvQAAKIlJREFUs1WckZ+xYjYtXbZyJysf+Rlva7U3Vl/Wj9lKbSiLrTwJeWxi/cXiwto2T37WBqxvsxUyUZ++fftmqsVsQsn3TfD1qwBnMhsC1InVi6nH6rG8nSqLrTPrR1bbhqvY1eJiXQdsdT5WPpNZ5Vn1ZHIms+yyPs/yMxlssjqw1XKhy1ZDZKysWMbukyzGsviI8vPEJ3YtsxUSmR7KYn2DxWLosrjLeDNWyM8Sa1fWVsjLeOVhlacstqoqux+xVUrh64QJE7CpSqx8KGDFXyTWb5ITNX6BP2sDliVWj+Uti4zdj626WdcMi8esz7LrBWUxObPJVjRF/sGDB2NTlax7Abs+2DXPxvAogDFg1wFbJR35N2/ejE1VYqygwOIp82vnzp1V9vwBi1vMpnUdMFasrVAe0/V+hFurrFCn1fvMB3YdMD34xuK5VX8mZ3aZDGWxGMn6G4vPyM9WqGb3Q+iG9WI8oFMroQ5WPcJ8MTqhvvbLSUAPAMvZrqqVCIiACHQ1gdjBECBpQNTVXUWVFwERKIiA4m5BIGVGBERABHIQiI29Gu/mgFpiVT0ALHHjqmoiIAIi0K0EYgdD4KMBUbf2EtVbBESgSAKKu0XSlC0REAERiCMQG3s13o3jWXYtPQAsewurfiIgAiLQpQQ00OnShle1RUAEeo2A4m6voVfBIiACXUxAsbeLGz9n1fUAMCcwqYuACIiACLQ/AQyEYgdDsXrtX2t5KAIiIAK9R0Bxt/fYq2QREIHuJRAbezXe7d4+EtZcDwBDGtrvFQIjR450BxxwQKXsN954o7If7rDJb9lExcjDJsJmE/WuWbMmLKKyHxsgLT0mZzIUyCYgZpPBswmFkZ9NiswWoLAm9A4nnoU9JGsCWuYrqxebeHe35exvVi826T1yssl3sxZ3S/wCEuF55itjhTysv1kM2UTBjAGzibIYV8YFuiyx/EyGvMzXWJvQe+9735tRZ9ehNSnyfvvtl8lvtavnjcn2X3/99Uy+WgK0NWtvlidWj+Utu4y17cCBA2m12cTvsdchDLJYxAqy2otdc1YsY3LrmmE+sLjL9Fg50MtTFotRjIHFj02yzyajZ/xYnWrJWL1YPLcmQme6ll+MAZMxflYdWIxm/JCf6Vp2mZz5yvQsGWPIrkHkZzE2HHeFZXjebMwU6rF91Cm2XrF6rJyyy1h8GTBgAK12uIieV2DXt9WP2fXB+osV9zGGTyerb7Gy2MIamzZtSptMjtn9hF2HzCYMWDGSFcbsssXI/PXCbKRl7H5gjfVYLGX5UQbzgV1fTJb2sdXHrF5MZvnB6mDlZ/cTxpv9zYXy2XiVLTBjLZAzevToTDXY36dQCheVQux9+umnM3lrCcCFsUnnidFJ59Fx+QjoAWD52lQ1EgEREIGuJxA7GAIoDYi6vrsIgAiIQAEEFHcLgCgTIiACIpCTQGzs1Xg3J9iSqusBYEkbVtUSAREQgW4mEDsYAiMNiLq5p6juIiACRRFQ3C2KpOyIgAiIQDyB2Nir8W480zJr6gFgmVtXdRMBERCBLiUQOxgCHg2IurSTqNoiIAKFElDcLRSnjImACIhAFIHY2KvxbhTO0ivpAWDpm1gVFAEREIHuIxA7GAIZDYi6r3+oxiIgAsUTUNwtnqksioAIiEA9ArGxV+PdeiS747weAHZHO7d1LbGoQDjRPJugFRVgE16zCV6hu2HDBmyqEpsU2ZpQ15pQtspgzgMr6LKJhtmEtGxSZrjAdNkE0qz+yM/Kz8PFqhdspxPjyhalYAtNwBaTs8mPoRtOqItjK1n+5+Fi2U7LWV2hw9qQXQdWXdPl1DpmPrDriMlgly3uwSaetyYsHz58eMY9dm1Dadu2bYkuFgN57rnnMvlqCdCuVtum88XqpfN18nGaD4sZqF/fvn0z1ezfv39GBgGboJ1Nus76O/Jb/QDnwmTFJzbB/FtvvRVmrewzv1ifZzIYiY1lzKeKE6kdS5fFItZnLS6sriyWMJspF+seMruWX8wY62/h+CDMw/oLu0dYfZvFstWrV4dFJPvLli3LyCDIsyAA6y9MxuI+ymIMmP9sgnrkZ/LBgwfjVCb5NrTGHJkMgSAdV4JTmd0i+lvGaJsLPFvvptXebBENttgG7LDrm8UM6zpgYwJ2T2fXG8pn/Zj5BF3mA1sUgfV35F+1ahU2VWn9+vVVxzjwC4ilT7BxMJMhH2PIYlm6TX2Zsf3b6gOsXRhrlGf54H0pcst8YDKrXuyeynSZzKqHxZrdD9iiOey+g7LYWKdfv34ZN6xrc/z48RldZhNK4QKYfuybyVxDEBt7LVY1TOtUCQm8p4R1UpVEQAREQAREQAREQAREQAREQAREQAREQAREQAT2ENAbgOoKIiACIiACpSMQ+99QVFz/ES1d86tCIiACvUBAcbcXoKtIERCBricQG3s13u36rpIA0ANA9QMREAEREIFSEtBAp5TNqkqJgAi0MQHF3TZuHLkmAiJQWgKKvaVt2sIrpgeAhSOVQREQAREQgd4mgIFQ7GAoVq+366TyRUAERKCdCSjutnPryDcREIGyEoiNvRrvlrUH5KuXHgDm4yVtERABERCBDiAQOxhCVTQg6oAGlYsiIAJtT0Bxt+2bSA6KgAiUkEBs7NV4t4SN30CV9ACwAWjKUiwBrAgVrgplrZDEVrxjK0/BO7aSH1sVlq3ohfzMLpNBNzZZQZfZZTK2IphVNls9i8ms/JbcqkNan/kPHVYHttobW7kL+dkKcpZPbKVRa2U42I5JVlksL/OV+YS8Yf/3thhDJoM+42qtwsfKYquaDR061LtStWW6rG9Z1/GYMWOq7OFgv/32y8ggWLduXSLfsWMHPV9LiLaKba9YvVrldfo565pjq+Oxaxb1Zyvu5rkOLB/SbK24zfq8tcIjs8GuL9a34Q/TZXVl1ybysxVWLa5sdWV2P7NWgmS+snpZ+eFvbGJlMRljhTLY6qNWfGAxhslYH0ZZLB6zlT83b94M9UxifchayTmTeZeAtTdb/RV5Bw0alDHBVvZl/QoZ2cqX1krtvqDY69HrY6u4G9Kov8/6O3INGTIkk3ngwIEZGQRbt27NyFnfZH0bGdn9j634y2TIz8YUVtxjuuw6sPIzX9mKqW+//TZcyyR2j2CskJHFLabLfEJ+Jmc2ocsSi9GMH/IyXuzeZ/UBVn4eGYvnVvxg9WJlWXVl/YW1K2yyvxsPOuigTHHjxo3LyCBgK1SzsqxYOnbs2Ixda2wd3uc2btyYyVdPgP7G+lw6X4xOOo+Oy0dADwDL16aqkQiIgAh0PYHYwRBAaUDU9d1FAERABAogoLhbAESZEAEREIGcBGJjr8a7OcGWVF0PAEvasKqWCIiACHQzgdjBEBhpQNTNPUV1FwERKIqA4m5RJGVHBERABOIJxMZejXfjmZZZUw8Ay9y6qpsIiIAIdCmB2MEQ8GhA1KWdRNUWAREolIDibqE4ZUwEREAEogjExl6Nd6Nwll5JDwBL38SqoAiIgAh0H4HYwRDIaEDUff1DNRYBESiegOJu8UxlUQREQATqEYiNvRrv1iPZHef1ALA72rmta/nmm29WTSLMJqtGBdgk2NbiAGySVrYAhDXpeexEvbF6tRogz+S5teyE51iAtybeZXVg+WGf6Ybl+n02ITHOsUnX2aTlTIb8bMJsqw3ZZOyx/qOsZhNjwCYvRjmsbZiM9RXkZ1zZBNDQZQxHjhyJU1VpwoQJVcf+gE2KzPyyJrMfNWqUN1XZWu3iFzpgLCqZjZ3YwRCyW/3dMF1KsdUG7FrMMzk36xusvwIq02XXtzW5OKsDuxegLNx30omVz65j5GN9ksksVuw6YgvsoCx2LW/YsAGnqtLOnTurjv0Bm/idsWL+wwbT9baL3rK+wWIWyh02bFim+AMPPDAjsxZPYIurLF++PJOfLSwCJbYgALvvQJctRMLsjhgxAuqZxPo865vMJowNHjw4Y9Maa/mxEuOTMZISKO6mgDR4yMYKLBbDPGtHdi1bsZDFF3YdhosUhNVifYv1V+Rhdpkui/vIz+rA/GfXJvJbcpxLJ+arH5OEupZNFjdZuzAZ7LP2ZvcN6LJ7F1tIgvmP/M2OgRgrtkgRymJty2TMJvKz+wHrF9AdPnw4NlXp8MMPrzrGwVFHHZWRQcD6JmPI4jvyjx8/HpuqZC2mEy6ixvp0lRFyEBt7m21rUrREHUhADwA7sNHksgiIgAiIQH0CGujUZyQNERABESiSgOJukTRlSwREQATiCCj2xnGS1q5/GgiCCIiACIiACJSNQJ6BUB7dsnFSfURABESgKAJ5Ymke3aL8kx0REAERKCOB2Hgaq1dGRqrTuwT0APBdFtoTAREQAREoCYE8g5w8uiXBo2qIgAiIQOEE8sTSPLqFOyqDIiACIlAiArHxNFavRGhUFUJADwAJFIlEQAREQAQ6m0CeQU4e3c6mIu9FQAREoHUE8sTSPLqt81iWRUAERKDzCcTG01i9zieiGtQioAeAtejonAiIgAiIQEcSyDPIyaPbkTDktAiIgAj0AIE8sTSPbg+4riJEQAREoGMJxMbTWL2OBSHHowjoAWAUJim1ksBTTz3l9t5770oRY8aMqeyHO2xVUbaSI/Js3749zJrsv/322xlZHgFb0YvJ8tiELlvpiq1yxVb8Q362+hfT9Sv7IU+Y2IpW4fl6+2wFM7ZyFuyw1erYqmas/sjP6mWtllVE26DMmMTKYu1irYrG8jOurK/Av/D68f5aK4KyFfvYyplsZWDYttrWl+u31mqUbOVOq296XtYKb74sts0zyMmjy8oqg8xavZRdX9aqh6wfMl22uiEYsuubraLLYoaV32qbdevWZU6x65DJkJFd3xmDuwQWV7bCKuMHmywWMFaWr7H9m9lkdYKMtSvkbDVHdv2ylYmRn9XBuh+wlRfZSqVDhw6F6UxiPrBYaI0zWN9kYw8UPGjQoEz5zC9WPjIyX1kbWCses9WFrfuJj/HW+UxFAkFsX0OWPLpBEaXaZfEVFWTxgbU3dFmfZ21n5X/jjTdgpm6yrsNDDjkkk9fqh+yaYfFh27ZtGZsQMF22YrLVt1h8ogXtEjJfY69DyyaL5db9kI3VrJXiwxVkfdmx9yivH7tlMZqxssaArA0YV8t/xsAaQw4ZMiRTLdZfrb872TXD7gfWmIQxsPpm2I99DM44X0Ng2U1nidVL59NxuQjoAWC52lO1EQEREAER2EUgzyAnj67gioAIiIAIcAJ5YmkeXV6apCIgAiIgAiAQG09j9US13AT0ALDc7avaiYAIiEBXEsgzyMmj25UwVWkREAERiCCQJ5bm0Y0oWioiIAIi0LUEYuNprF7XguySiusBYJc0dLtVM3zdO/3qtvUJDXvtnL32jrqmbULGPh1gr6JDlwVIJoNus4n5EPLx9q3ymZzlZ+XANsvvy0xvmS6TWWWx1+lZu1ifJbNP1KxP7BgD5mu6jo0cM7uMAfMJ5bG+zT4VYXrIzxgwrtBlbNnn8dZ1yD4tgt10sj7f2LBhQ1qVfu4Epa1btya6oS8Ww7RRtAlrl7ReNx3XYmexYv2I9SFwZNc3k1n9mF3fzGcW31E+u2YsX5ld5heToSyLF86FiZWD88yu5Wtoz+8zuyzmQJ/5Givz5aW3LL9VFusDzH/kZwxYfILujh07sKlKW7ZsqTrGgfWJHfOBfd5l9TfmK7te4AP71JPVi5WP/MxX1t5hrEQ+n1jcZZ/tQX/Tpk1JtpAlK9/bDrfoF1bfCPW6ab8WO4sVu6db/ZBdX+wTYtZf0Q7MP1a+Nd729+mwTVksxnk2LmDlW9cB84vVn10bKN/ijXPpxGyw/EyWtuWPmS4rB/osllhtyHQZF1a+9y12y2ywOrC2QhksP+sDTA/5GQOrLHbNsM/LWXxEWYwhm17HKp99nm/VK/wUf+PGjSg+SYyNPxduYdeyHeppXwRA4P/t6iz/n1CIQE8TWLRokZs8eXJPF6vyREAEOpzAwoUL3aRJk2gt1qxZ49hcV1TZEK5evdoNHz7cONvZYsXdzm4/eS8CvUVAcbdx8oq7jbNTThHodgKtjL1lHu92e7+pV//31FPQeRFoBQHrvy2tKEs2RUAEREAEnFPcVS8QAREQgZ4loLjbs7xVmgiIgAiIQG0C+gS4Nh+dbRGBcePGVSz/7ne/a/qtnYox7bSUwPr16ytvbuK/UmyFrZY6IOO5CZShzfAJhP8s7f3vf7/JAKvm4T+azSS28l4z9topr+JuO7VGvC9luIbja1sOzTK0meJuMX1RcbcYjj1tpQzXcE8z6+3yytJmPRV7yzze7e2+2O7l6wFgu7dQSf0LlzvHJ3tl/eSupM2XVAsP/9RundXCndxmo0aNqgsb8wupT9qYFHdtNp1yppOv4U5hXLSfndxmirvN9wbF3eYZ9raFTr6Ge5tdb5Xf6W2m2NtbPac7ytUnwN3RzqqlCIiACIiACIiACIiACIjA/9/evcRIUbV/AD6ggngheAkLwOtHUIwLjZiYIBqM4oIQxQUJG7zgJUoMISaCuuAfjQpodOFCF3iJG0VdKKKuFFREJQqJURTxGpUY0YgXLhqg/336S3Wa+XpmumfO9JzufiohU91VferU85t+o+9UdxEgQIAAAQJdKqAB2KXBO20CBAgQIECAAAECBAgQIECAAIHuENAA7I6cnSUBAgQIECBAgAABAgQIECBAgECXCmgAdmnwTpsAAQIECBAgQIAAAQIECBAgQKA7BDQAuyNnZ0mAAAECBAgQIECAAAECBAgQINClAhqAXRq80yZAgAABAgQIECBAgAABAgQIEOgOAQ3A7sjZWRIgQIAAAQIECBAgQIAAAQIECHSpwIhSeenSc3faBAgQIECAAAECBAgQIECAAAECBDpewBWAHR+xEyRAgAABAgQIECBAgAABAgQIEOhmAQ3Abk7fuRMgQIAAAQIECBAgQIAAAQIECHS8gAZgx0fsBAkQIECAAAECBAgQIECAAAECBLpZQAOwm9N37gQIECBAgAABAgQIECBAgAABAh0voAHY8RE7QQIECBAgQIAAAQIECBAgQIAAgW4W0ADs5vSdOwECBAgQIECAAAECBAgQIECAQMcLaAB2fMROkAABAgQIECBAgAABAgQIECBAoJsFNAC7OX3nToAAAQIECBAgQIAAAQIECBAg0PECGoAdH7ETJECAAAECBAgQIECAAAECBAgQ6GYBDcBuTn+Yzv37778Pd9xxRzj77LPDscceG0488cRw4YUXhoceeijs3bt3mGbVfYf96KOPwr333htmzZoVJk2aFEaPHh2OO+64MGXKlHD99deHjRs3NoXyxhtvhLlz51bHimPGx/F5y9ALLF26NIwYMaL6b8OGDf0eVGb9EnXMDupuHlGqu3nkkGoW6m4qyc4cR93NI1d1N48cUs1C3U0laZyuFShZCLRQYO3ataWxY8eWym+4uv/KzafSjh07Wjij7jzUjBkz6vr3zGXBggWlf/75p0+kgwcPlhYuXNjneDfeeGMp7mcZGoGtW7eWjjzyyMMyWL9+fa8Hk1mvNB25Qd3NI1Z1N48cUs1C3U0l2ZnjqLt55Kru5pFDqlmou6kkjdPNAqGbT965t1Zgy5YtpTFjxlSaFOUrzUr3339/adOmTaU333yzdNNNN1WbF7EJ+Oeff7Z2cl12tP/85z8V7wkTJpQWL15ceumll0qbN28uvf/++6VHHnmkNHHixGoe8+fP71Nn2bJl1X3PP//80nPPPVcZK/6Mj4um4l133dXnODYOTCA288pX0Facx48fX/XuqwEos4FZt+Or1N18UlN388lisDNRdwcr2NmvV3fzyVfdzSeLwc5E3R2soNcT+K+ABqDfhJYJFH+Fi1cqxcZfz2XVqlXV5sXy5ct7bvY4ocDs2bNLa9asKR04cKDuqLt27SrFRmzRvHv77bfr7rd9+/bqlWfTpk0rlT/Cfdh+e/bsKcXn4zgxd1d3HsaT5MGjjz5a8S1/pL4Um6xFZr01AGWWhL1tBlF384lK3c0ni8HORN0drGBnv17dzSdfdTefLAY7E3V3sIJeT+C/AhqAfhNaIvDhhx9WGxO33HJL3WPGv+xMnTq1st+4ceNK//77b939PNkagVdffbWa2e233173oLfeemt1n3j1YL0lPl80pW677bZ6u3hugALl7xcqxatpo2/5O/9KsXFeWPfWAJTZALHb8GXqbvuFpu7mn5m6m39GwzlDdXc49Qd2bHV3YG6tfJW620ptx+p0ATcBKf/fsmXoBV5++eXqQeINJuotI0eODOXvnKts2r17dyg3MOrt5rkWCcycObN6pK+//rq6XqyUi2N45ZVXKg/jDV0uuuiiYtNhP+PzZ511VuW5uH98nSWNwKJFi8Lff/8drr322nDppZf2O6jM+iXqqB3U3faLU93NPzN1N/+MhnOG6u5w6g/s2OruwNxa+Sp1t5XajtXpAhqAnZ5wJudX3FE23vX3ggsu6HVWtU2M9957r9f9bBh6gfLNP6oHOeKII6rrxcq3334bdu7cWXlYm1uxvfZnsf2nn34K3333Xe0m6wMUeOGFF8K6desqd9F++OGHGxpFZg0xdcxO6m77Ranu5p2Zupt3PjnMTt3NIYXm5qDuNufV6r3V3VaLO16nC2gAdnrCmZzf559/XpnJ5MmTQ/m74HqdVbySrFiK1xSP/WytQPl7/6oHLH80u7perGzbtq1YDbW5VZ+sWandLtcamAGuxitkyzdvqbx65cqV4eSTT25oJJk1xNQxOxXvNXW3fSJVd/PNSt3NN5ucZqbu5pRGY3NRdxtzGo691N3hUHfMThfQAOz0hDM4v/3794dff/21MpNJkyb1OaMTTjghxKsE4/LDDz/0ua+NQydw6NChsGLFiuoB5s2bV10vVn788cdiNfSX6ymnnFLdV65VigGv3HnnneHnn38O06dPDwsXLmx4HJk1TNX2O6q77Rehupt3Zupu3vnkMDt1N4cUmpuDutucV6v3VndbLe543SCgAdgNKQ/zOf7111/VGZRvWFBd722laADG7zazDI9A+U5bYfPmzZWDX3PNNXU/tt1MrkWmcUC5Di7Td999N6xevbpyJe0TTzwRRowY0fCAMmuYqu13bCbreLLFe9T7c/iiV3eHz76/I6u7/QnZHgXU3fb7PVB3881M3c03GzNrbwENwPbOry1mH/8iWiyjRo0qVnv9OXr06Mq2ffv29bqPDUMnED8KsWzZssoBxo8fHx5//PG6B2sm1yLTOJBc63I29GT5ztjh5ptvrtxIZcmSJeHcc89t6HXFTjIrJDr/ZzNZR43iPer9OTy/G+ru8Lg3clR1txEl+0QBdbe9fg/U3XzzUnfzzcbM2l9AA7D9M8z+DI4++ujqHGNB728pvox3zJgx/e1qe2KBzz77LMydOzccOHAgxNxefPHFEJuA9ZZmci0yjePItZ5mY8898MAD4YsvvginnnpqWL58eWMvqtlLZjUYHb7aTNaRoniPen+2/hdD3W29eTNHVHeb0erufdXd9slf3c07K3U373zMrr0FNADbO7+2mP3xxx9fnWcjHy/bs2dPZf9GPi5cHdjKoAXiHWJnzZoVfv/99xDv+vv888+HSy65pNdxm8m1yDQOJtdeSfvcEBt/Dz74YGWfxx57rPqRzT5f1GOjzHqAdPDDZrKODMV71Puztb8U6m5rvZs9mrrbrFh376/utkf+6m7eOam7eedjdu0v0PvtWNv/3JxBJgLxL6InnXRS+O2330LtTQjqTS82n4r/Ea29cUS9fT2XTmDnzp3h8ssvD/Fn/E65p556Klx11VV9HqD2xh/95Vp74w+59sna68b4PTXxCtozzzwz7N27t9Kg7bnzp59+Wn3qrbfeqtwoJD4xZ86cSsNQZlWejl9Rd/OPWN3NPyN1N/+McpqhuptTGvXnou7Wd8npWXU3pzTMpRMFNAA7MdUMz+mcc84J8ctcv/rqq8rHS488sv6vXvyrT7FMnTq1WPVzCAXiHZqvuOKK8M0331SOEq8uW7BgQb9HjJkWS21uxXO1P2u3y7VWpvH14iOaMaf58+f3+8L77ruvuk/8a3e8yYPMqiRdsaLu5huzuptvNrUzU3drNaw3IqDuNqI0PPuou8Pj3uxR1d1mxexPoDkBHwFuzsveAxS4+OKLK6+MV/d9/PHHvY4Sv5C3WKZPn16s+jlEAn/88Ue48sorw7Zt2ypHWLFiRVi0aFFDRzvjjDPChAkTKvvW5lbvxe+8807l6YkTJ4bTTz+93i6ea4GAzFqAnNEh1N2MwqiZirpbg9EFq+puF4Rcc4rqbg1GRqvqbkZhtGAq6m4LkB2ibQU0ANs2uvaa+NVXX12d8NNPP11dr105dOhQePbZZytPjRs3LsycObN2s/XEAvFjpLNnzw5btmypjHzPPfeEpUuXNnyU+FHh4mPC8Qq/Dz74oO5r4/PFFYBx//g6S/MCzzzzTOXuv6VSqdeftTcGWb9+fXW/oukqs+bd2/kV6m5+6am7+WXS14zU3b50bKsnoO7WUxne59Td4fVv9ujqbrNi9ifQpED5fyYtBFoiMGPGjFL517NU/vhvadOmTf9zzFWrVlW2x33KjYz/2e6JdALly+tL5Rt+VL0XL148oMG3b99eKt8wpDLOtGnTSuX/yDpsnPg4Pl/k/uWXXx623YO0AvF9E63jv3IDsO7gMqvL0rFPqrv5RKvu5pNFypmouyk1O2MsdTefHNXdfLJIORN1N6WmsbpN4Ij/Ky/l/1m0EBhygfPOO69yhV+8kcGaNWsqV4IdddRRYceOHSF+9DT+i8uUKVNC/OvP6NGjh3xO3XqAefPmhXXr1lVO/7LLLgt333132LVrV/jll1/q/tu9e3flRi49veLNXfbt2xc2btxYuYHI66+/HuLVm/v376985+MNN9xQvcIwXl0Yj2sZOoENGzaE4uPY1113XSiu/Ks9osxqNTp/Xd3NJ2N1N58sUs5E3U2p2Rljqbv55Kju5pNFypmouyk1jdV1At3W8XS+wyuwdu3a0tixY6tXKZXfcIetl5t/pXJDcHgn2QVH7+ne3+PTTjutV5WDBw+Wyo2+w3LsOd7ChQtLcT/L0Ao08hfROAOZDW0OuY2u7uaRSM+62N9jdTeP3Pqbhbrbn1B3bld388i9vzrbc7u6m0du/c1C3e1PyHYCvQv4DsBy5be0TmDOnDnhk08+CUuWLKlc6XfMMcdUrhgrf0w0rFy5MmzdujVMnjy5dRNypEELjBw5Mjz55JPhtddeq3wnYLwxyKhRoyo3CInf+RevCly9enWI+1nyEJBZHjm0ahbqbqukW3cc7+HWWac6ksxSSbbHOOpue+TUzCy9h5vRymNfmeWRg1nkJTAi9gbzmpLZECBAgAABAgQIECBAgAABAgQIECCQSsAlOakkjUOAAAECBAgQIECAAAECBAgQIEAgQwENwAxDMSUCBAgQIECAAAECBAgQIECAAAECqQQ0AFNJGocAAQIECBAgQIAAAQIECBAgQIBAhgIagBmGYkoECBAgQIAAAQIECBAgQIAAAQIEUgloAKaSNA4BAgQIECBAgAABAgQIECBAgACBDAU0ADMMxZQIECBAgAABAgQIECBAgAABAgQIpBLQAEwlaRwCBAgQIECAAAECBAgQIECAAAECGQpoAGYYiikRIECAAAECBAgQIECAAAECBAgQSCWgAZhK0jgECBAgQIAAAQIECBAgQIAAAQIEMhTQAMwwFFMiQIAAAQIECBAgQIAAAQIECBAgkEpAAzCVpHEIECBAgAABAgQIECBAgAABAgQIZCigAZhhKKZEgAABAgQIECBAgAABAgQIECBAIJWABmAqSeMQIECAAAECBAgQIECAAAECBAgQyFBAAzDDUEyJAAECBAgQIECAAAECBAgQIECAQCoBDcBUksYhQIAAAQIECBAgQIAAAQIECBAgkKGABmCGoZgSAQIECBAgQIAAAQIECBAgQIAAgVQCGoCpJI1DgAABAgQIECBAgAABAgQIECBAIEMBDcAMQzElAgQIECBAgAABAgQIECBAgAABAqkENABTSRqHAAECBAgQIECAAAECBAgQIECAQIYCGoAZhmJKBAgQIECAAAECBAgQIECAAAECBFIJaACmkjQOAQIECBAgQIAAAQIECBAgQIAAgQwFNAAzDMWUCBAgQIAAAQIECBAgQIAAAQIECKQS0ABMJWkcAgQIECBAgAABAgQIECBAgAABAhkKaABmGIopESBAgAABAgQIECBAgAABAgQIEEgloAGYStI4BAgQIECAAAECBAgQIECAAAECBDIU0ADMMBRTIkCAAAECBAgQIECAAAECBAgQIJBKQAMwlaRxCBAgQIAAAQIECBAgQIAAAQIECGQooAGYYSimRIAAAQIECBAgQIAAAQIECBAgQCCVgAZgKknjECBAgAABAgQIECBAgAABAgQIEMhQQAMww1BMiQABAgQIECBAgAABAgQIECBAgEAqAQ3AVJLGIUCAAAECBAgQIECAAAECBAgQIJChgAZghqGYEgECBAgQIECAAAECBAgQIECAAIFUAhqAqSSNQ4AAAQIECBAgQIAAAQIECBAgQCBDAQ3ADEMxJQIECBAgQIAAAQIECBAgQIAAAQKpBDQAU0kahwABAgQIECBAgAABAgQIECBAgECGAhqAGYZiSgQIECBAgAABAgQIECBAgAABAgRSCWgAppI0DgECBAgQIECAAAECBAgQIECAAIEMBTQAMwzFlAgQIECAAAECBAgQIECAAAECBAikEtAATCVpHAIECBAgQIAAAQIECBAgQIAAAQIZCmgAZhiKKREgQIAAAQIECBAgQIAAAQIECBBIJaABmErSOAQIECBAgAABAgQIECBAgAABAgQyFNAAzDAUUyJAgAABAgQIECBAgAABAgQIECCQSkADMJWkcQgQIECAAAECBAgQIECAAAECBAhkKKABmGEopkSAAAECBAgQIECAAAECBAgQIEAglYAGYCpJ4xAgQIAAAQIECBAgQIAAAQIECBDIUEADMMNQTIkAAQIECBAgQIAAAQIECBAgQIBAKgENwFSSxiFAgAABAgQIECBAgAABAgQIECCQoYAGYIahmBIBAgQIECBAgAABAgQIECBAgACBVAIagKkkjUOAAAECBAgQIECAAAECBAgQIEAgQwENwAxDMSUCBAgQIECAAAECBAgQIECAAAECqQQ0AFNJGocAAQIECBAgQIAAAQIECBAgQIBAhgIagBmGYkoECBAgQIAAAQIECBAgQIAAAQIEUgloAKaSNA4BAgQIECBAgAABAgQIECBAgACBDAU0ADMMxZQIECBAgAABAgQIECBAgAABAgQIpBLQAEwlaRwCBAgQIECAAAECBAgQIECAAAECGQpoAGYYiikRIECAAAECBAgQIECAAAECBAgQSCWgAZhK0jgECBAgQIAAAQIECBAgQIAAAQIEMhTQAMwwFFMiQIAAAQIECBAgQIAAAQIECBAgkEpAAzCVpHEIECBAgAABAgQIECBAgAABAgQIZCigAZhhKKZEgAABAgQIECBAgAABAgQIECBAIJWABmAqSeMQIECAAAECBAgQIECAAAECBAgQyFBAAzDDUEyJAAECBAgQIECAAAECBAgQIECAQCoBDcBUksYhQIAAAQIECBAgQIAAAQIECBAgkKGABmCGoZgSAQIECBAgQIAAAQIECBAgQIAAgVQCGoCpJI1DgAABAgQIECBAgAABAgQIECBAIEMBDcAMQzElAgQIECBAgAABAgQIECBAgAABAqkENABTSRqHAAECBAgQIECAAAECBAgQIECAQIYC/w/fxKpkpQJiPgAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:hyperspy.drawing.utils:Axes labels were requested, but one or both of the axes units and/or name are undefined. Axes decorations have been set to 'ticks' instead.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "p.plot_symmetries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "small_noise.metadata.Signal.Ellipticity.center= [64,64]\n",
    "small_noise.metadata.Signal.Ellipticity.angle = None\n",
    "small_noise.metadata.Signal.Ellipticity.lengths = None\n",
    "small_noise.metadata.Signal.Ellipticity.calibrated = True\n",
    "small_noise_polar = no_noise.calculate_polar_spectrum(phase_width=180)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "70273b86fcf34f48a45179d6e5675fa2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=2500.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = small_noise_polar.autocorrelation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:hyperspy.signal:The function you applied does not take into account the difference of units and of scales in-between axes.\n"
     ]
    }
   ],
   "source": [
    "p = corr.get_power_spectrum().isig[0:12,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:hyperspy.drawing.utils:Axes labels were requested, but one or both of the axes units and/or name are undefined. Axes decorations have been set to 'ticks' instead.\n"
     ]
    }
   ],
   "source": [
    "p.plot_symmetries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}