Jupyter notebook running constrained HMC to sample from joint Student-t density conditioned on a fixed MLE of location parameter.

student-t-conditioned-on-loc-param-mle.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import autograd.numpy as np\n",
    "import logging\n",
    "from autograd import grad\n",
    "import scipy.linalg as la\n",
    "import hmc.constrained as chmc\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import animation\n",
    "plt.style.use('seaborn-colorblind')\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.INFO)\n",
    "logger.handlers = [logging.StreamHandler()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define energy function (negative log target density on configuration state $\\boldsymbol{x}$) and constraint function and associated derivatives"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def energy_func(x, mu):\n",
    "    return 3 * np.log((1. + (x - mu)**2 / 5.)).sum()\n",
    "\n",
    "def energy_grad(x, mu):\n",
    "    return -3. * ((2 * (mu - x)) / (5 + (mu - x)**2))\n",
    "\n",
    "def constr_func(x, mu):\n",
    "    return 3. * ((2 * (mu - x)) / (5 + (mu - x)**2)).sum()\n",
    "\n",
    "def constr_jacob(x, mu):\n",
    "    return  -6. * (5 - (mu - x)**2) / (5 + (mu - x)**2)**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specify fixed values for a 3 dimensional toy system with $\\mu = 1$ and fixed MLE $\\mu_0 = 2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mu = 1.\n",
    "mu_0 = 2.\n",
    "num_dim = 3\n",
    "seed = 1234\n",
    "rng = np.random.RandomState(seed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find some initial $\\boldsymbol{x}$ corresponding to a stationary point in the log-likelihood for the specified $\\mu_0$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.66533453694e-16\n"
     ]
    }
   ],
   "source": [
    "x_0 = rng.standard_t(5, size=(num_dim,)) + mu\n",
    "constr_solve_grad = grad(lambda x, mu: constr_func(x, mu_0)**2)\n",
    "for s in range(100):\n",
    "    x_0 -= 0.1 * constr_solve_grad(x_0, mu_0)\n",
    "print(constr_func(x_0, mu_0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check second order condition to ensure at maxima in log-likelihood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "constr_mu_grad = grad(constr_func, 1)\n",
    "assert constr_mu_grad(x_0, mu_0) > 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up constrained HMC sampler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sampler = chmc.GbabConstrainedIsotropicHmcSampler(\n",
    "    energy_func=lambda x, cache: energy_func(x, mu),\n",
    "    constr_func=lambda x: np.array([constr_func(x, mu_0)]),\n",
    "    energy_grad=lambda x, cache: energy_grad(x, mu),\n",
    "    constr_jacob=chmc.wrap_constr_jacob_func(lambda x: np.array([constr_jacob(x, mu_0)])),\n",
    "    prng=rng,\n",
    "    n_inner_update=5\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perform 1000 MCMC updates with timestep $\\delta t = 0.5$ and number of integrator steps $L = 5$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acceptance rate: 0.99\n"
     ]
    }
   ],
   "source": [
    "xs, ps, accept = sampler.get_samples(x_0, 0.5, 5, 1000)\n",
    "print('Acceptance rate: {0:.2f}'.format(accept))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot traces of configuration state elements $\\boldsymbol{x}$ over run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "            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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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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lMiXXZpUKJwq3wBZZz73HDnyZvoHRaXKC4bplLx8n09dIw/WvVDSAgBe3GuULNq8z1TYydl+oBkd1sB4t5QCNx1PSvtJCQC8sPtwWbPTAcCUzg0HAFMqweD3/55UCq6piIz0XBYSAD7TqKy8dX3aA0DC6s/Pky3d3Z/hPsm6XQel5KvD424d+2jiKnn013ky/4Ur5ZLz0zcZa5YX/pajx09kCHe0fo9VOw7IRT1GGgBILU4s1TdffkG4zxW33zmQM7/wt3RrUVFebn5mcGTv+W6WfD1jXUwHPQdorqyZZF+P1nGTsd0R/WfPfK4cfKNNqvSf0TudvHqn1Ht3vBzp1Uaafjw51YNA1KqF0pe/MwWkHAAMNkfIRrAuDfOkdh2yRLbuS5C+N6WMN5nR5rwDgKnzRe4RkTtEpFnS/6ICgE81LCNv33Bp6owsRK/XfDpFWlcuKo/VL53mz47mgfM27pEqvcfE3Tr23riV8uQf82X60w3TnZMF0AHwZKRqG0u37hMqlBzo2UYa9Z0gD9e9UO6sUSKaT5eiaw8dOSY52g+UV1pWlJeahQaA5HS8slyhDBNAE+zFn/x9vrw3fmVMXM+0AIB5smWOKi/mJ5NXm+jMN88ACsu0Nbuk9jvjjKLZ5rOpqQ4ANfn7lm7NpUiXoWcFACSh+z8dro56XyjebZhs2HNIFr94lflGu19L3dyt4ayd/D7s4brSNJWs8VELKMIbHACMUFBRXMaJOF5EGojIGsq6RmsBfKJBGXn3xrQHgC0+niwtKxWWZxqXi+J10/7S2et3S7W3xsbdOtZn9HJ5vv9CGf94falfJm2jW71SzPR8f0MCzwh8RB3b/I17DDdp12utpNlHk+T2asXl/jql0mwC7D10VPJ2GiSvtqwonX0A4Mx1u6TGfzkMWkq+ToPlh7uqy63ViqfZ+GJ5UOdBi+W14f/I+pebyQX5oku3wqGTM2sm2Z+KFsACObLIju6R89DUcp0arsto5bvr4JEU1aqesXaX4bpuf7WF/N8X01MdABbpMsRYmZgLUC3OBgtgrACwWNehsmnvYfn0X5cb2k5qz7dIAODpyE12ADDaXSX89VRZ/klEPhOR47EAwDuqFZcvb68qmTOlbfQnUWjNKxaWF6++KPxbpuMVujFv7NJMzo9jjrKeI/6RDgMXx12T+3Tyanll2FJZ8xIG4fCNdCvnPp9YPGZVpyZyYcG0LbcWbIQALBJAUyoPa3Gbi4vKo1eEtxZf+9lU+fqOaik6jBnT9v0Jct7LQ4KmSfrfpNXy8C9zZQEu/DdHyz01S8iXt1cLL/B0vEIB4KxnG0nV4tRjj7xxKOXIcq6xyKZGo/8iubPK5ihKI4Y7KFNjnH59bt132FjRAG8FY+QKq6IJILvj25mpDgC1+s/KTk2kzGsjzgoAWP68XLI0BgugguVPbqli6pJnBAAYiWcireZ/pM9xADBSSUV23WNJvD9NnBUVALQP/uevLJfmbhSIzk3KnxfWvRaZKFLvqimrd5o0JGtfaiol8scvWvfVYUvl5cFL5Lf7asq1FxeNGoCPWLpVfp+/6ZT8WlhWhy7dGvEmlXD0uGR7cYARIO6RSOve7j54RKgm8P3dNVJF+HCibvpiuqzv0kz+74tp0qhsIXm6UdmQzzp+/IRkeuFvGfxQnRRHDG/ac0iKdRsmr7WqJB2blj/luQoASVDd4n9T5OYqxeTne2umiizi1amW/4rFfZTaHD36vyBvdvO9I20ZBQDO3bBHLu8zJibLqr6rWpRXdGwi//5xdqoCQPZ+1smJE2LybFbsOSrDAUDqIb9w1UVSNE82M7aUfmvur1A4lyxpH70L+LyXBsv2A0fkw5suM7zttACAWTOdK4d7tZHHf5snd9coIXUuLBBYFrxLsH0p0rUT7XUk0n7qj/kpCtJyADBaqQe/npMQ128dEVmbdFlIANi2bVvJmjUxkrVFixbSpGkzydIu8eC/7pKi8uf9taMe3Za9h6VI0gKN9uYG742Xqy46L8NXWRi3YrtJRMzGXKZQ7NYxwEmvUcvMppbp3HPkpUGLpftwyjeL1CmVXyY/1TAqEQaLFGz5v8kyZEnkAHDf4aOSp+Mg8+xF7a6USkUjC0jBRXtZ7zFyvPc1cs4550Q19kguHrt8u9z7wyxZ2amp3P71DGOxCmctPpBwVHJ1GCQDH6wtrSoXjeQxQa9Zu/OglOo+PCwAVLfQ9ZcUlT9iWEMpGqTnZpSC7FkyBaUUsIG/O26l9H+gtlxzcXTySQsAeGGBHLKqMyyWyFpKQUFkTwl/1ahl2+TqDyelaI9QRXNhuysNyEjNSiAHjxwLRP7Oe76xWce01AA2sX4j7vvv9ZcElL5Y+9GvlxIAWLDzYNl58Ii8e8OlhredGnKyZ5ltDeff/3fZ+fLrfbXMJRqc1qN1JWnf5FTFNPxsje0KPCt/x5BBYMiQIcL/aAkJCdK3b1/+ifthT2wjif2u+J9SsY8lpXfeKyIfJwlR34saN7tF5EcRecR6gG8UsJLcuc6eYJEOTC1HsaYxqfvOOGlcrpC8cU3GzkE4bMlWaf6/yUZTrlA4d6TiOeU6BRRrOjeVkgVySPu/F8kbo5YFrot2UyEwYpxPwfhWn0yWwYsjB4CkuCn40hChAMic5xqHrLe7ee/hgEY+dc1OqfPOeEno1caU8Ip3G750q7T9bZ7R2O/7fpZJleMXjEGS1nduuNQAGhIdF+4yVAY8WNsEGPk1kt5yuDavGDqn4PJt+00UcrAoYLUAtr/6Iuk5cpm0qlREBj6EPhb/RtlA3gfFIVTzHpKs0dHLtwXe9dFf5spHk1bLr/fWlP+rUiyqgdJ3tsznyqEUROkePXbcWK1v8URzqzci2jxtKQUFXgH8Pm+j4d9Fuxa/n7neuG0Bb5UjVKC8zx6/Yrs07DtRcM8//ecCM0eJgA/3zaP6iEkXq8uaqO6xba8wXFZatO/t9+xf526Q72dtkF+SrOGRfKPRy7bJjV9Ml50W/5P7el1T2SjMtEj6Cbc2YrUA5u80SHYfOmoA6TN/LoiLnMKNVd3VvLetXKrCbssmWF8EFtUqFZ+k79ECQPbiWev3SLOKJ9NGOQtgLKvV/x4Y3N7IgXUicquIwOjdFQ4AKsmd6/51+QXy4z3RufIU0ERjNXp9+D8y/J+tMvLRK6Tmf8dKw7IF5b/Xp30ASjSfAa2HyQ/X6+IUpGsh7c2lb44WODelC+aU5/5aIG+NWRERAMzXaZD8fl8tubr8yUoYWFAnrNp5ymbU+pMpMmjxlog3Kay4RbsOldzZMsm4tvWTccM4EOteWCBQn5XNaOIT9U1JNrV67O/RSnJmjX8pu0GLNku7vxfJvBeulId/niOFc2eT7j41eRnTfbVKyue3VRWdk3/+u1aynIF7Dh0xaW7gZ/13zHJ59q+FYeWzePNeqdxrdNBScB9PWiWP/DJP4NCOWLbN1Bkd/ki9aKZWRNdiOc7S7m8z/8JZZ72HJKDi5q9mmOhu2gM/zpZ+U9fKd3dWl9urRxewQt/qlopo4D4X8U1bfzr1FNmrRapi4VyyOAoXXUpBgXeIHQYsMmA+WiCkc2rGMw1jrlcNCLrqw0ky+ckG0n7AIhm9fLsc7NnaWHRjaViKjp844auckWIJxQn3KvsKFJd4AUBSNk1dsysgw0i+0Yt/L5Reo5Ynkzv3vd66knRIsnJF0g/v0GvkMqlZMn+yvVIBZKwAMG/HQbL38FF585qL5YW/F6ZqyUw1rNQqmV+mPt3QAF+UW6z2NAXvva+9WJ67MngA5cY9h+SCbsPiRl0KlUOUPWr97kPGsKENpf3L6clTTjkAGMtKjvyeY9GkgVHLD91ziH17V/XInyQimrYgmjx2uToMlAMJx8xCJ8VH/dIFM3yuo1/mbJBbvpohP95dQ/5VNfI8dFg4/7q/dsBFjkuz8QcTA0Dyid/myfsTVkUEANkEOjctn8xdfsW742XS6lMBYJtPp8jARZEDwPW7D0qJV4ZL4dxZZeCDdczmqY3n6tzQ0mx//LuWXH/p+cYdADBGa8+fCsmj/5y/yQSzzHimkZC+BOuTX7oPGwAu2bJPKr0xSr6/q7rcZkXkUsydTP5waroPWyovDV4S9pDX9D9Y+Hq0ObVUogLAqy86T7bsOywFc2aRMW3rR7WGIrlY12kkgRveQ3Loki1y29czA5G1d383U76ZsV6+uK2q3FurZCSPN9eotyBLpnMkoVfsiZoVAHprTmvADSAawB9pixQURNqfHxCJ5F69b8Lj9eWKGCP61dMw+rF60nXIUgMA97zWSvJkj025uuObmTJkyRbZ7lPdA2WUnIPMWUoDavv2zmomsGnv66FzPRLxzJzwC4ojafvMdbujAoDqDbGBN9/WDnSI9FtznZ8iEezvkXzf3B0Gyv6EY4LblcA9OPNY4FKD+qJejKsuKmQMJYzb9i6s3nFASr82QsIBQF1rsXrovHIJVTsaRfP+H+ckC7DxyznqAGAksy3+1yRzAR85dlwoA/T7v2sFor/urVlCvogighHEf/NX0+X3eZskGq3XXsRYw+pdWEA++dflUb3xy4MXy+It++Tionnkobqloi6jxsbl1ao5KCsVyS2lCpzK8ftmxjq5+7tZZoxTnmogtUudJOPaA0fjppwSVhoNRpgLv6YY4hdR99LUpxoaszwBFB9PWh0WAKp7zEv6ZQMnUEI3TQAapO6bv5wuA6IAgCu3k3B5hLHy4bbB4mcDQKJbKcOGm9i8x3015YbLismPs9bLbd/MFPKIYZ2Ld/t5zgZjIZ30ZAMheIFaxX7pimwAqJGU8PIesFLG2POu25Al0nXo0rAAUKO/gwVI9R2/Uh7/fb5cXDS3saQcPHLcjDUlbRluZ09VGHVFYxmyieB+z/Eekn/M2yh3fz8rcKDf+tUM+WnOBvn45iryn3oXRjxU7TelAFBBDtUncliWLbXcXn5BXpn9XOOox4WrFItHSoO02vVfKG+OTm6JimQwD/44Rz6bukZGPFLPWIJZl5FUrUGxIc0Q1XcGLtosbT6dKgQV9RixzABAu044lAiC5vxABxbuvNmzJBtqKMAE3/CGz6cJeRf/2bY/cN+tVS+QH2dvCLs2Lu89RuZu3ON7nfc3v3GwP0Ib1nfxs7xy30vNyssrLSuZ8aUFAMTqX7FI7lNkrLXS+VYoj7RDb7SWbJljs84SqHdTlWLJ1iD7PFY0PBVEZTevUFiGPFzXvHeLioVl8H/qmucu2rxXLu41Oig3mX5QqD6evFo6D1oi9hkUyVwOdo0NALVMp3p/MAY89NMc2ZjkaaAP9TbYoN4BwJR8gdjvTQYAbcufdvlA7VLy6a3BgRjcobErtsuCdleZW1Zs3y/lXk/MN21rvarJB+OF2Yu48hujBDP3V3dElzojx4sD5NBR4l0kZJ1WDhW0Z9s6pW4Wr4uHcdUvXUDGP3HqAU5aFUL/aYMeqiMtg9Sj1coe9K08jWlPNwxY1LQfNPzG5c4LLBD9BsHcTmzu5Jl767qLk+VM9Lpa2Hj3Jxw1HCQWZKTBGSRcJtE1VVlIn9KwLFTSxIZc/l2rpOHelX09MVUEUcs3XlZM+k1ZIw/8NCcuuQMVMNuR1t/OWCf/m7zaWNU6DVwk29jUbjl1juoY+91WVSau3CH1359gAOtTVsSwzjsqTbxwVTl5ddg/YQ85rczwdKMyvjSFt8Ysl+f+WiiFcmYxCVkBb9OfaWRktP/wUcMfXNr+6qgsOIzTq2RMX7tLar09TnTehNoGvIfkdzPXyb9/mGMsn7QbP58mf8zfZMjsTzQsE/GOov2mtFQbCbObfDRJdrzaIllpxTkbdkvVPmNNRRw8CpE2HRfKUadBi8N+U/rFSjxh5Q7fnJIaJR2tC5ggpR9mbzDc0zdGLpOxPtxc7zvpXglohNrx1/xNcv3n04z1qlCurDJx1U7R1FNwJwnYU+XR7ktdhuPaXiENPGuX6/zehe+ApQ+rOtZAbbdcXkx+nrMxpBwVxAfr+5JeozsdgZYAACAASURBVGTh5n2nWAChCim4IqoWt6YaHToOXGRAr+5Zuh90aHKRvN460foeDQBEmV/0YuJZRdPACe/f+U2j/Xk26bDgx1YumjsZl1PzpJJ7r9vQpaZP8n9OX7tbGpUtaDI44HomSNDLb/Wby37WSDU0aFAOYB9KCdc2LX+eDEuil2i0+MvNKki3lhXNuwG+Prq5imTNfK4MXrxFWn0yRdrWLy19J6wKabSIdJ1xnQ0A1dOi8/On2RvMfNrQpZngbWHfgysJ39gBwGiknDrXJgOAyvmyH/VwvQvNBLIbB3y90gXMQlATuH7MhZv2mtxntJGP1jPRvDQNDAjmurAXcfkeI6VGiXzygyeNCIEGzT6eZAISbG0X7kPD9yfI5n0JgguCFioUnmfBMRxrueUUtLDYzaaSFL3KtVWK5ZU5z5+0PuDevOHS8wV+0hO/zzfXq/uT55NT7f3/O1mq57XhS43GZTaVrs3l/K5DhU054dgJwbJB1QLcBxqhqu44lXmwQwcLHeDrvRsvlccbnDy0a7091mxAep/Klo0VAOjHH3pn7ArjvoWDqI0DoO6746Ro7mwGrGJJYeMhsIM+sbI+3bBs4HtrAIFWMlFOY0qmrroY7aTY1EX9buZ6s/G9MnSprNxxwPD8vI0x3l+7pHx2a1XBStLs48mnzAuVDfd25FCxDptg41aXPVavec8nHl52g88K6KA9Xr+0jFmxXeY+nwhe4Fihxb9/46XS1vpm3mflbD9AvritmqEW6CGFBQgXIO4vgCXWadLM4NbGQgN4KVUgh6+12ntIqtKBm57wEQIVoAfgPsJySTLoyy8Inw9Q+yUgAWtbrG3M8m1y5QeTzEGBxVmbgp9o8rQpSKAPrNRfefhG3jFyPe3Diavk25nrZaKPtVZ5uV4Xdbj31cORtXHTl9PN5eFAJBHblHxTwE/wxM1fzjD34prdceCIaMCYciQVLNrj0X5IfVQkdzap/t+xBkgBZkrmz+6bD5SgIixZzInZG04GYxIM+Nu8TcnGrpxijRy315LfO1boMdJYFfnNTjXGmHXvoA8bjKHgsSbVqqZ0E8o/9kqq8pISAKjy8wOAqpRojj+oMCTI1nfTdcn4OzUtbxKp07SCitJNGF+keTK5ljW82op4V48CXgS8OwRIjn4s0QWs7mCeq8FCL151kfS8prLoeb60/VVSvnDugGdGrbmRKI7h5je/39Bvqvy5ILGOuCpsmjbsi6lr5bHf5sqSF682mRNWd24ivUevMFWHbEupswBGIun4X5MMAKq7xX4MeYamrNlptG+N6GTiod1ggcnWboAkHDtuCMq4oZT/Rx+2VUwDA1gchXJmTVYaC9dz1nYDjMVk26sthVqU1Yrnk9+Swtt1POrGU24Z2i/WH1wOHITn5cpq/psWKhKK8SvpF4tlmYI55Ytpaw1XAWDIgaAWP/taHYduOByWVOyg/XRPDaPhofHc+vUMs9Giqc9av1v2HDoaAATLO15tLKTkWwOQIF/chL1HL5df7q0hN1W5QG77eoZxt2jTDQfrEW66f9dOrHqhrkgIyM9fdZL0G4xro/3ZVhasDVgVFND9z7KkIW9SWDA+yh3xHlu7NZfzcmcz1z96xYVyT82SZlOyZaCJrO3o6Ks+mGjSNgAyo2lq5Rz1aD25MkmZgGP314LNMuDBOsaqMmfDHvnOh6dqA0AOtuv6TRPbcsA47EOLjZPo68NvtDEac7CmByu/t65cxIxDG5YiFBXq6tKIFP5+1vqA1UE1ZDu4qseIf6RBmYKnWFjvqlFcvr6jeoBnx3pCg/9P3VLG4vnDrPVy+zczzXO6Nq9g3NfVS+Qz3Ehv8x6S745bIU/9sUDyZc9s3IwVzsslw//ZZgAy4FXXYrhvFQsARD4oQba7VwGgV2lAmXh5yBLJnyOz9Gxd2UQoh4ssV08GAB1FLZzlivlLUETLikXkrwWbZJaPq/mZP+fL22NXJhtzONnwO5VqkOs3d1STu5LoIqxnUjLhgfAqudzDfOg4cLF8cNNl8mCdUvLr3I2B78w9KJnsI2UL5RJyblKv9+8HapuE6HbTfgAiADpoGRy62V8cKGUL5ZTlHZuc8gpELb8/YaVxNxKwoQ05YiFm7DyfoHO8DzTGCF0nHAAs+9oIo6zRh51pgj4+uvkyebheadMH3NkRjyYGTWmCct3z1YNiW9/1uYALsh/4lYVUwIkFb2GSt4r+VX5+ANC2aNqC0v1YU0vxm+4d/FvzJyo3nPFFWsuaaznHtr6iKXxFvp6+Vu75frYQwIYlmL0CiyzrV8Egz1WFUGWjFBHdh/VsYo+Ai+mXEgulP9r68+o94BvC4yeQTnnJgNcn/pifWEig+wgBjGL9g8JjU4TORADIqXCtiFQUERKo7RARToX+IpIYW5/+LRkAxFWF9c1uzSqcJ8OWbktmzWOS1i6VX6Y81VDUBM49LAxcqQApNuwuzSsGDnw9gOEvTFu7K1lZJw020FQPFNjGMva3dbDSv7rxNKWCJkzWhLscZoTk07yuPvudGL8elPwb/gYaMqZqbW+0qSztrr7IbEj0CyeGwwmTvm443VtVDFj2cJHeVaOE4Fq789tEXiBWCzReItbY0GnwIkmtgNaMJREgwOHzy9yN8tXtVeXumiXlpi+mGWuMurPheVBwHH5W60+nBOpN6oL3Zn6v1meM0d51o9J6vvpuVBSgsgKL8MUBiww/jUPwsStKJwu8Acxf22+qFM6V1bwHXDs22RL5cphksZQKJFE1qXBoVI0BEGoeQzsICJnZEWuRTn2NbLMTFAMKRvyz1eTWe3vsCiEfo+bC8n5ntQAqL/HJhmVMahiabSniv1FqcNHtfb2V5M4WnGCvrhTuaVO5SGCeeq0a/M4hDrjXw1Y1ZOW06SHidXEiLzb5n+6pKQqC9d2eaVRW3rr+EmOxeuzXeebPWBjgGkYKABUcaJ8oPhz4fGMakd9K+CfoBl6Yn1VH1wKA4FhvtrvwTekWNo9NrS18n/9ed0lAQcTyxqEOBwolhCAV9gnbpel9ooJs3qFx2UJhea/6Do/Uu9BEsPtFGz/9x3x5Z9zKU1zU+mwsSZnOOecUxUEDsjQnJNcjR30m+8wHE1cly3GoFA6uZe8okS+7AQB2o/YslmddHz/fU0Nu9qTQIWFyn6RsArqPa3k3O60OFnWUcriJWIYBzAeOHJPxKzmyEhvrvP/CzUb+7GWHjh4zlkiaKkHhAGCpV4fJ2l2HzPsr8NL+sYg/ckVpYa9CKVb6j7dEoYJ7LOvvJXlZ9LmsdSLZ/eaprjMvAFT5ef+ugV5+sxkFGmvq9KcbmYpAtOcalw3Ieji1eD+eHPAKMT5c6ni/MJawt1TpPVoeqVf6lHr3XOstq6gc8XduuMSAPrjY0FBogMFxjycGmMHrJWUOivkHN1UJGAhmPtNIqpXIZzxN//l5rpDih8AVb8on3WdUudB3p9oSRvJgqawUANqyIoUQlKE3Ry0zGRs4C+D2MxaU4/+OXSF2EMqZBgDbiwg+qUkiwpc6xJ4qIvhDyeo7RUS6h98qY7qiB+eSiMDk3iciZPJslwQ+vR0GAGC2nLkMJwhrhd3gv5FSBPfYaxbnQt2i3kU/YOFm6TBwkeTKmlk4qDQ6VrUY7dtepMpdwBK3olMTob7iZcXyyNCHk6fOUI0Mdwd8oStKFzBWNrWMsHDQQGheXhx/I2r3vh9mm8nPYY8ZXUud4faCn2I3e6Pm77hvqUmq1TGIvtWEzarBfjV9rdybtFnzDvM27g1EiNHH0P/UNYAJax9uHQAgFlasIm/fcInRggGG/A13g93Uaqg8Ss0x5rVqEUWNVQyrAMTzS3uPln2HE+VCY+FhdSWVCQ0ASeWRpxqWkbeTwBF/x6WINRKNVN1B8HUg1JMgmu9bv0yBgHtKZfDsnwvMAteNh76YJ9EkFSdSbcnW/eZQJcEq2ipzCovXs43LGvkAjgBBuF7QLO2UMwru4Ck+Vr+0zN+411RRgNP6QJ2ScsV7E4IuLgUmbKhfzVh3iiVa3ZJ0wMH41wO1DQgFqGA9UyuNmXP31jCcF6L2SGaM5k1qDSwCFI7XuQTP0iZKIy/N8aXRfzpgnomFhkjOJO+lyQmHS4rgKVyYgCAUOrUKeS2AdrJx+iXh+PLtBwIWdDuoQ8EiPDbAf5ULEoOX1B1nvu85IscjBIDKabLrS6syo/OT3I6abgdAMHjJFrMedD+CBqLjAHhjnWbONypXKOAK4x04IEct2x7S7aqygXyPcqruNyzuOIc5sAnKwG2FixorCdHdd1Sn3HpiIx8cBzNrCf6yUkh0LQJwCAyi2fsKVJcZVmSsHsLq6gVYoBygVNsNPtilxfLKht2HTL1eVR4h4XcZvMSAo3//MNt4NmjqvuQ6wKTtUtf3x4rM3IWysPvgURm5bFvgkYA8lFK/Vq14Xpn5bOOwFsALug2VjXsOm/dXK7D2Rx49KuaUfHW4iaTVqH6NolaXoro1bWqSjh9re5chS06x4BNUd0+NEoYD7AV6Kj/v33uPWm7Suvg1uO30pd4c1jKBUyRSp31+a1Wz19guYNIkocgPXLxF9r3eSnK0H5jMeqfP4V28a0mzTbDvobQzv5inNM7ACUn8dD0PAMKAS+Yp41AOqPedmJN4VdTiN2vdbgNsvenbvHuHVyZ+ABDF5tJieYxHEM8EFB7qt4957Ar5YfZ6+XDi6mRBomcaAGwrIiatdZD2pIi8G+L3lPz0GueOiGAagND1oYiQUdkvoiIAAGdsSTDuPm/DUsHGinb8YRIXkAmhLlQbAMIBwl3B4Y/G80DtksaiRYNjRhJTbTYA1Cg3LfdEfUUieQFodlNLxP9uqWI0GdwYK7YfMO7Xf301QyCiczDSsM51alohcDvWwiGLtxgwSyN8nsOZ6hA0no2FwW7qLtG/cehgOaMMGFoU9Wex7tDUDatJgPkbh+oUy43C39gUADHqEsLdwUaLhs6YnmlczriHsLjxbnb76/5axo0JEKVyCIACjRCrycN1LzS5CIk2hmsE8KRxKC3fvj8ZmGTh464ngIAG0IDDYfNq+LtacwvlymI4hTRy/ZUrlMvkB+R6Nk49nDQ7v0Yx20ELzBPcSESYh2saSWZfh7Y6e8NuE6SBVYTN7Zs7qwdy92nwAgoIWjYBOTnbD5SaJfOZsevmCf+leL7syfIseseDlQQOnHIxvbWebU6WgloluNOXWuP4Nxvev76eYQ48lKhxK3cI3M31ew6ZyGxtgJUDPVobQj+VZeB2aooHPaTCyY3fryxXSEY9doVoQJSXB6r/7c01ySFORQNS4mjTaz+bssYUuqehKGnAl1pPvNfb40S5q17iZPogQBUKCc/hAF2365C8PW6FAebXfDbV3KoBDawl1tc3d1YzexOKG5YrgGqf6y6WZxsn0h60ign/Zsy/zd0oj/46V7bsSzCeCjv3HBZYlKH6SSlZtGoN92IFJYvAgAfqSOmCOQyvGI8C4ySoB9cV36baW2PM320XNvNb9xCsU/M27TX7F7y37QcSjIsQa7uOUfdNPcxV1oyn3nvjpWzBXIbagjuvcpE8ybwT9MEh/1TDspI3e2bDKWV+Vy+ezwBWMhNAQcFqC1WCpoBSvw0A8Ns7q5v1q9V++I19ExlApSFpvF+Do7bGShGDpXV391bGK+A3F7Cmochd+eHEAIdOwb1ez/6JO7P2O+MC+9Bd3840Fmm8Ixqxqt4itexzv8pSy7EpgOFbw2Pldyz1ZEDw8uuUk+vNA2jztr0yUADIPK3//ngTtX5b1Qvkf5PXmEtVocbqe2f14gbssb6PHLMWvIc+Akee76cVuJgPKLGcZ7/M3RDwKtE/a5VEyjTOGKgARfNklUvPz2vWKem5Nu49ZOYoCqeWv/QqfYBS9kqdewo06ZezjrXOfqW4wGtZhROO0omCTtYPv9buqnImjyPGCNY3/8/3RDGB1gO3nPm34rm6Ura4ScB/RlQC6QL9x1ciIsSH8/vLQX6P958Jj4QoRHLoxFP8ZAsAwJlbEkyyUW/TDVf5SLrgWEhwEqq9NTZwCwcnVgmI1Cx4XFgP1k1MKYFWSu42bWhBWOyYpEwGyPxMRkj1cNjgZHjJ2OpexfWINq5WO5uLp/3bFku7pq3+jrZJoAZcJG8DTDzz1wKZ9lRDoxFpw3oHeCDIhbHfX6tkIF+fpiUg4ks3eg5jUjbYTS0B+v9sPGy2uEf5N6D16g8nys4DR5KRsOnjB3LYfTNT1MVAkmNkR3Qg1jI2SaJ22ZDV4sf3YxOxc3rRl4JJ/q2HJDIDOGHlxLqAxfXx3+eZJMnqcuB6+JWY9QGAJfJnNyBUG1YirMjklKPt6t7ScMzYhLWqDNbHUDwuDvCuQ5cEQCz9YLnYvDfBaOXIGuBAdC/XAni1KoceBnCGCnQebOYRB5rSA7CeYdH8PMky4rfYlId2/w+zzXUcLFiHNKWNzb0DABIJDSDHdeZts59rJFd9MMmAK7XCcOji0sRqZTcOLqyyuOJxCyoXSg8pv7F6/6ZpIbxau/e/tfKH3o8VADeuKg78nTV6+Nhx+WHWBlN5hWa7vL2UEfuAwJUIdxSFxeaC2m5JEljDN8MaAF8K7ixNk3U/9ivuqsyGY0YORxpjRMdTHiR/s5VQgA8plD6dssZY1nRt8HcOYCyurOF1LzczQVwoCdq4FmDO2oFcj+VQmyrC0E+e/mOBqalN08h3xmBbZviNtUD6FsDWjZedbw5Cmm0BVCVRZYcyDK8YBRPFBeUOfqZaD+3vzfzA6l4hqV4vv5HIm4AeaAwoktPW7jb7qu0d4bpiebMZa5z3PfEmsPds3Z9glHm/xlyxI4Shx+Dys88Cey4gGwBQ7qyZzTrgN4Ky8JSo0o1ShzUULjdgts91l0iejgMNP5s5qRxzXQsAKxRA+/sTDEdQHvskVSYKvTTE0HYAyPQD/xDAjOXdzO/DR00KLiyi6n3i72oJC7be2PdICQSwIg8s78b+TbARjeC4TyavMTQkgiWpiqTz1u7T5gEjIy9NgFq/ROvidsdzpQ3vG8oBTY0g/Ltnm8omUTh7Ffs1+wtJqjE2wItUK7b2A8+XOsYYFFir8Km5n9b3/y4zNCysdjQvxQOre95OgwxAR1FVRcN+P6gLcL55B/JIQo3CAAKXFI47gZOAXoJDxj1UVRpWNtz2MwIAkl6/j4gQFoStFtMSPFxqnxBS20lEfg42weL8d9y/lH+jRrC3BQDgrK0JJgrP23BNbdp72GxgGpTBZMUShoZtNzQiXHPDlm411g04I8on0MlsX0/yTDhXVKfQDYnf2VAAQ5o6Q+/RyEXdtFTjhvPAIWI3JcISyLB210FzENkNQEu4/KVvjpHHG5ROZhHCxXzXdzPllRYVjeatbjZ4fljdqP+Lyw0tlIVO0+dp3ir+psDKfq66KfRvgIJ82bOYcH60dNzsWB5wA+BStJu6FjCvAzLVeqibCxsKQSKq2YWaR7pJcY1+Y01lwLfd3K2FyT8G0AMQ2nwgNlE2F1zGgCnNf0VfbOS4J1Qj5GDALYlmC+iG28Ohq5xJvzG+P36lDF2y1Rz8kJ5pgLBzzznHfA+sRZkznROITse6S8oaAiYUDGxmU+s69BTLbstKhSV75kxmEwrVcLMT5QiBX5umorDd/ByG5N8i2h0LJwcb1lRtAAZyc9EAHgC/qhfkNUDDdvGzWV53yfkG+GnT9EO8W0XrkA81bgApFRzUGsOYeVfKmNH0He79flbgwOLvgBTmIpQKbbhP+e4K+Pk7ngCUjqEP15Xf5m00gRFe+fDfVPMB5HMQMV9RcthHJq7aIS83ryDQBAiawqpGY/1oX0olqP/eePO8BmUKBVINcS17BeMlCE3ToOgY+O7kOSNAiu+g+xR5yV7ov8jIVzlryinWe5nnew4fNVYNr5VLr4HcDpBTqgyWPQ5KQJdambzfB5CHdYZ8gBotrYnvlcaigIkAJ9YOBzffgpQdvKvtPdH+8RpQLQlulTb1MMDVBUzhqlauXsgJb/2I2/nYiRPJvq19r01x4O8oVVWL5zXWeW1eAMjfVTElkhqw1G/amsAeRxQtwAYlQHmgmdv9LaXy5zDKK9YilDnkAuBVZdLm8WIVxlLLGgDA4E5WrjXPV2OG5qhTBU/XJkoBTfOBhpMXoIbvwsF+ZbnzzN5LYy+39w329aoX5EvmUuc66CkosTT2LXtPZp3Wf2+CSeivUcg6Hj+6Er8xV1BYmW+28sJvnHW2AYa/6dqAXtOkfGFj7FBgjyxLF8gZiFxnz5//PPSf7IbeoNSGUDJinRJYxZj4HiiReO/IRAFgBJhiPUWB/+nWyvKvOqZ+8RkBAM18Z16ICEQRMugC2SnwCicvua8x3EyL/Xeqp/9OSd+kMnDenkJaANmU0aTVmgTw4vAlmg2QxmK0G5ww3L+3VysuR48fNxYRLdlz5zcz5TsPv5AFTx+Y/tGe1coAp6J84VwmdQabsda8VDeyHe3L8wksUY1cx6MWAgUEan3R33EFYp5u/vFkaWe5Z/h9+tMNzUaEq4mG2RrNEqCIGwquBweaHXSiLgnbssKGs2rnQfMO2gBNkMm18W5ovhy2BIOwoZPGpVie7AZA200XkebkAozalj1ABMEikTS1jNnXaiSpRgjicu82lAjMLKdsKNwH8EarRxvWhtWTA0c1VIAeByPJohk3WipR0Brg4DdWcn/RhwF9zye6ldiQeBYAkO8NAV6TP8N9eWfcCpn8VGJ5JJpaQ5XwzN+Ys7iE+R4oHqEawJUcWlhWtTFmNvLp604CXAXDHNIEZpCjkLxv2uAuaWCVbrgABtwnKFAKNLC8kO/MbqyPH+6uLsOXbjNuFppG6QYbO0pAv1svl9wdE6kNRG1TA1mbpl645cvpxhWjDWUKzuqQJSfdfqpIoBhAR8CSzGHnXcfah53CBRqHAlyUmeJ5sxtXKIEqWPge+22eAcPacL+qwsN6QJm84JVh5lqAM4e5NpRRuEVrX24mmhlAf2PtAlBZcVgetNlpWFRxUgs61zBG2yWv39UrZwKmSPOjaxMlhT2ShlUK74e3ATiRJUAcZY08dOQ6ZVtQTiM0A/ZCOF7IGQoINX9ZY8xbtR7afaPM9GhdOZnlTekxAFW4xhywtrs25KRP+hGwAGjxA51+96OY4jHRFFxcowBQraz0Bz+bwDZc53h81u0+GPAUcA+uS+YWQAalgTmsrmu1gimVg3cf9FDdZDxUDAoEGBBoMv2ZhkZpsnnafG9AGp4d6DJUZFKKjiq9WAQf+HGOsVSGa3iK3hy9zKxjDZ7iHu/cYc+Z8mRDIYE9HhxtGqzhDUbjd+YDVBqUGLxFg5dsNcCJplZte3zM32sqFzXnAe5fL3/czxsFTYtxYzXm38/1X2D2RuQHFSB/9izy7viVsnTr/oCBBjCKV8+2ugeTE5bRGy8tZmSu+xb7OEF0BJZq0A73v9WytDzb3KSbO60BIPXASACXGBqUvo2kXF+LyL14/IIMxQDAp3+cKpeXPt8QRu32GVUTkrg/+ncFHX6cBjRoFg4HJQ0AqJYxrRfoNw5I92wOmIK1Mckp/QTBmc3s2T8XmgMEl6oNqPz6Y2wAPKxtmpSaBdDv1qoBSwLWGkzlLw1eLF2aVTTvrpotQRLwZ+YnJUJlM8MdBQDpPWa53Hr5BeaQR6PlQGM8aKQP1b1QSALM5KYhD0Az+bO0YXlU96j+jc0MAIxLhnQKaPQcgupS0OvUEmOb/dWMH26qqXbMe+P6wLJDSTTcGZq3Ub8fvEEOuot7jTJjqlUyX+Cd7OfgbrQBg98YANmAkppvj0tMXdCwrHEr6AbuvQfXAuR1eC1YinSjQbkAdLPB40JtXamI9L7uEnM7kZuANcAWgNF7mOsz1NoSTlb8TmQ4wJZv7uWGBptzE59okOiysdzLWGJIf0BTSy1WQywzbNKaPwzAiWXZbnAJsSxgIddGcBNpFoI1Aib41kW6DDWbOq4z2zXHwULgErzTRVbQE/xZ3Fh+llEslnDmsMaMWr7NlxsGKMONVrlIblmz62AyaxBjxZIH4AM4kX8M3ijfE0sy75kzSybjjtJGDlG4R1j0aFhztTFnSQS+67VWYnNu+Z1qNN/P2mCiodWdxd8ZHymPWlQsYtxPKCjRKEz6bCxRWLo0QIJ1r3xdwyv2cZvyTVbvPOCrdCBbO98ez8EVCM0AK5LOGZSBrJnPCXBxuQ7FijWCi1Eb9AjGh2sa9yT7ik3fiGTus8+QbJhsBZE0oltxB9rN5jRe1nuM2QvVuqoUB6pMURPW25grKB1wrfWc0b2GajhQD1CiCP6DaqRzg/0ea/zPczeaeYDXx7bG8dzRy7dJxyblTR5N+IYKjtn7oY14qRGh3p8xko/Urpii1xN8p+eHZszwRj5zxpHSi2+Mp0UbygJWOcAwUc2coQA79aqoJdMeG3K6pGgeIXjKz3WvPG+9x+Ypo2iP+GebCQZh7+JZWLbxssBdxiKrfFj27f/UvTDgUQg3P2zFjmt5F6gZKHusSX2nZ+udL2/dYmoan9YA8FvSLSVZ/nT1vCgiqO8Dwgkrjr/fKSLvi8gtInISVZ36AAMA5fLWIpmSygWVriZSOpFbYeeu0o9nu3yCjZcIW8oPobFgDSRHG3ngvHw47mdj2NG9ZSBppfbJYQJH4PI+Y4SqGRqwYIMfrsWtaG+6aOFYabwRXAAviMZsKjS1xrDwWWxEhSp5F6tJm8+mBvJgsZmR2w6z9dS1u8yhRPg/9+4+dMRYDuwFb8sFiymuH20cEvaBzt/RfAGKHFzkv6IYO24Mr6yJjtOgE+0PMMRBjsscTc3blC+p0cekaiG6F8Iy4Iw+AQt2YyMgtQ51gLFwcHB7x8z1JJMFxGi6mnDzlwMLLZyDCWsTlAKi+oio8wYrhNI0Ad68l1YCwJWHxZbE3gRPeK3Tyv/RDPjhxsnvgAy0NeyvKAAAIABJREFUX+QKB4lgDkAFUb4EFbB5ew8vkvP2GPlPgI5ApCKHBIXX7Yb1FWUG2cGzw9VHxQfScQBaFAhh/aDZLjx1/wd7B74XVo8yr48wuTTZyJVbx6H5ZIMypyh12pe9IXv7Z64AAImKtvPD6XVYngBWHCQ0rPjn581mLAwoEawtDm6UGhS6O7+daYAi3gW1yGlfuLAAvvAD4bJhWdJyg1yDReSpPxfIkV5tTPQ66x+eJ41USUQZ3lOjpFHqADI6JlJRwCHTYBMsNew/akW3eXKaNoU+1XXPvwEdRJqqDNjr4JYRqMGB6Rcpy6EHpWHZtgOGj2c3v+Az5gQKqO1GBCwRjYyCoQoOewTztKGlOGiSX57B2CjhSPJwm1qgz/dSRTTLAJ4GIuftPHeh1gxrF97cwMWbA2mxdD0TlHX/j7OT0YUAMCScx3oJCPM2vgmWPptaYl+DYsPaYF7ZSijzfvO+wwZcoGwChPEW4WXJmy2ziSwmFQrBIDTblY2nYF+P1qYUKhQW+/sHe3dN8m7zZvVagkLUE8A3Id+jX5oov76hzPAedhAgfbCXUP2HvJh2sJauN6y9gDNymXrPA0AoSh5nI3PBpnApSCNS9/ZvZhgLIPs0ATcYAx6qc6Fc+Npwc87h1q1QOLdZ1/3vr5XMu6Dvguyh2WD54zn0Zze+LxSD8vuWyIzxifSFGhfkkhl/f8c/T2sA2IFUb0l5/k6G04lcn5QL8JtQCylOvz1OIFJSDsLguS4SH5YIANv+IJLt1Fq3Gl2r4yLKEwBiu278xszhWDxfDqMla5g6nCCQv7dpVJZXO2JjxH0M+ZUcV4AGmtfdaxNn+R0ODFYFO6cff+fwxwxN0lRv081KI9Pgf+EaBrBqzkGNkOLwJkIKMrltffOziPIcL2jz4wWykQCU4UKQCoR0CYTxc9DYTasa8DfdvJVErq4R77up6R0AQ24vDkR4iuQHA0xwn0aecS/WCqxs9I9LGgI/oMQvwAHNlQ3C5o2FmsO4uzjEONjUiqsuGi8ABLBC5A7matByRzwPvlerT6fI/bVKGaC6cPPeQDQ4v2sKC3WP2Zu7Wky84+bQfn/8KsOnIXJcs+nrdVqhwL4PCwKuLWgQBAC0rlzUWJ00V5hei7t416EjyaoK6G8kQdfN3Y/aoEqKXu8l92M9ARxzsDKnmJfKj4WUDnfNG5mufWm1B/67/dUXSc+RJ13SWFcAgN2HLw1QI7gO+sYv99QwAOzWr2cGrKWsa5QzwCtWBQA9FhHoD0TSUi+cCEUoAUQ1wlfThmuI33CF4gWwgQhKKdZIiP24szsMAJDvDET34wb8ZuZ6w1skAEPfQ1NraEJ6fZZtIdK8nfxmuw5VieLvKKVQFDRlFAoYHGNcXQBa3La2W5h7cKfx3rjPvbxpTd+j49Fa1U0/mhQArvzG2j905Lg5VDWyHcDO2OzsDZrkl3s0nVGwhMZwzlCWcDtjlS2VP6dRoHDp3lc7MXuDX3Uo/o7lcsWOAzLkP3UDNcLtVF9aMeWDCauk/8JNMnrZ9oCiyL5JqTcszpG4Er1BJwDyZhUKm3ml+yDfFzAMRYf9f8HmvWYO0ewIXzw5uh6UHsIaIjDt53tqmmwSgHS/tDekLUIp1sb6QqnRlCz2XqD7KPsndB5Kj9IieV/bS6R8dw3CVGVXqT7MR5QFGorxyEeuMGtfaULq1cHazTsVyJHVAES1pNpjZj3hMbPPdzwOD9a5MGDhBVAjT+YdoFQpOtqPXeGoxCvDDNXFYkAFHochBwDON+I7bOjQQPLlM5WHTmsA+ICIEDr2JzQIW7gi8hKeJc/fUuM/UTHxpRxO6px9h7EQ+uQFhAYA1ug5SGZsOZXzoJNLNykiMSnLo9o2/Xv5ePyNg2TDnsPG9UA6hZWdmibWAfSxUGkCXG9mePq9o3pxw7fTUHL6VqKs/j8g9eGf5wY4G3B90Jy8FkD6eLVlpUDeNVvwNmGZ3GYU8m71yWTj6jIZzAvmDESGsbCIWGTi21pUsMALO1k0z/Qz3wNmABxYOba/2kLImN+9VSXDO7QtPrb1UFMB6N/sjcB+N42M0yg6fgOkAC71sLE3JS8gwhqKy9DmLdr960YT60TWw1KDE7K2+9tUsrisWGKuuWAbpp3mh9QZWBEblikotUsVOAU4I9snG5Q1gSItP5kSSGrL3COiGqsw1hQoD8qXU2uhgjBviTKtDevdQJEta0RL13mTOHM9Fsl9CUd9AWCTDycF3IvKibKfwaHe4n+TA8qUBvDoNcgTyyMJwwliejQpUTRWaywEhbsMScZXsvuGEqHuIwXL+juR9iXz5zCKlc310qhjL9DVdDRaGxwyPiX0cKuTSBdwBsEd6ztR5uRG1KbRjFrmyuZIsVYVECILwBjBJRqFCAj4YvpaGfhgHZMe5qvbq5nay1qKa8rqncmepRGdPFuDXuD2Yi0i1RRNoyhJ6gyHt92ARQHXoR6wKHqAvxnrdpmE2MxbtajqGvTjbnnXjebz8wJA1hnWUhQcBScAbL43c1qb8pKVxsHftXqGl/fLHMeiQ5lKUjZhxcSVq9Z37vWrD8/f2afgiJ2LFpjU7Oh4lPZrLykqXQYvNV4SlD7mCPMe5W/Yw4l1jnV9a/SyncpL+9UKGCprAANzHOBqN74NgWLIhypL6j7HDT71adLvnqwsYt9np1XRv+My/fL2askMBhpYptcw91GqvcF6/K4Bed7UKaH2NO0Xl6vmFNQ9QANGUHZwbeOapWl9YP6tgTHwS1GAUEALvzzEnI0A5GcblTV7APu5rShwr54F5OBlPdFQ4ugfJUGBHpZXaGBa5EHrkevY7ff1nvnQGDKdKyaFDYYQwCHWQZTUbZ0bnREAkPotP1JjWkTIH4J9k6AP2NY9CfzxLvh0/m8DAFu/P0IGrjjpPlRNWBMsawAFVg1cLljy2Kiw8qEB4+JSAGQ4R8XzGZetBgKEIq5rElEvERb3DC4rFheTBY4QFjk2wvduvMxYp3guQQa4fTmQsWpx0KCVkXyXpuRhLCdo9V6NhWv8FmmbT6cYd46WPtODnI3q9urFzcZlRy7b/6b6A9opbiI7ASzP8kbQ8TetWnLR6yNMlQoiNiHyE2yjtYO5jkU7d8MeYxlRAjsbLcl+WYhwyLyWSI0cJh2J1nb975jlhkem9YupcoCbmgPGG3FGWTQ2IxtQQ17GxI+lyw5qCRadxqYB6GHeoDXzPfX7aOQkxPBsmc410ata5zTUZqk5B7mG3IfwjHg+/B61FuvaUmuhWn+UNgAABKiRLkZloQeSAlM4LygC3hrWdu45fQ4gls2VNaKJelWx0cOLa3Gd4za364pqH1jC0cBxsXwyZfUp0e3MVcjkWCrQwof/szUZl49+GDt/B0jz7QBsmuC7aJchp1ih9Nk2nUIpA/ob8mZfUPepfVBSkcX+VowLSyREe/L+QeYHaMONxfpAvlBqehOpCL2DQ9/mKeqatfNG2mlscKUxT8jHhkuUvUfT+nBQAgBR3EoVSPRqcK9STbwVHkjlgayJNlfAhoWDNdn608S8hKRMuvaS8016pntrlhRyKNp8Ra7hwGXNo3wefKONATkAENzLVDmBS+2XF5R77bRNpDC5tVpxsRUBriHSlnrXgDkCLuBOATLurlnC8JNtNxt7HcA2exYyjiU21jjf13YXs3ZxxbIWCZqCxsL+qDk1uW/voaMGFHoDznC/UxXJbnZ+TP6uex/KA3QggAXWUqx0cIwBqfpdtUaxX7oUvhEg11a4sSKzJ9l8NwL/sHABoOCOqxsUa6WW9+szenmgfKeOXTmJ9rsgq5/vrZlMAQX0klpGG5ZY5tWtVYsH8mTqb+qKDwYA1YqbTIBJ/2FbnzU6XhNf4+2gyogqYfSvNeE5M7RMqPbb4uPJgQBJrPg0lH8s9ygs2nTPtYO37KpJ5z7f37iAOb9QOqlK0rxikUCydu3Hfl+tSKW/8T2ILCZgk3OAgBulD+3u0viMAIBfich7gGe8IyJylYjAVCec9GERgSOYkZoBgPd/OUH6zTk5GZRXphU3dCGRBBh3IBGU+qFVQ9RoLUjvbLyAGY2iDfXCdukq29rDpg7pmehBIjHVkqZaDn2SgRzCOwEDGrrPZoGbkzxWlHcjVQWHpVYG8Vq72lQuapIie5sWOreTvZLiA74SWi/92CRyW7uGwP7RxNXGXePlUfrJQnOJPfHbPAPuSI2hOcQO9mxtEonSAOIAYQ4VDiii9DTJp+au8qavUPe5nd1dE/tqhnj61o1RQT9/0/qVduUL/s63h68GkR8LZZ8xyw2osKMq7feEkA1vhwMVTheWgNKvJQZGaLUU6kIC+qlTiqZdJE8283swC6BqrFyzZucBE2hBLiusBbY1id85gJ67spzhPhKAotGaAEAACGlpNPecPk+vUWsLoEWj0enTjyyOXDSX1tqXmpqKKVow3gZX0BuQh9ZFDbY+sG55I4N5hpaGQmaAfizyALYnfp8XiFq2Ezbb/Ws1BvtvGrVoW3O1dJNehxIHncObK1T5TVynZSF3v9bScIC1kfKFoJrXR/xjrKO8g64vgBqRolqVhnvU4gPvDVehPQ+8VAEst3CSoKYgU6w9BDj5JWle36WZUQ6JylavBoFD5L3DbaZeBSyBzBmdR+yDWKvYb+qXLiidBy8+xYqK0kcuyO37j8ie1xPzzGnTMoS4m0f5BLHZXgHdCwCbdioP7h32SGJlpDu+mWlc+bw7gBTeqSZq53cs2ffXSawX7m32eiLdC7LDqqsUB37XmuTcqwqMKoa6z/kBGy33qc9kzvMtVnVuIg/9NNcEwkADMFkCnm9srPw6Z+gPixAR1ShQdiPwhnlnK1Fcr4nIlROJ2xWPU4cm5c2aZm+pWSK/STYMp5Gm+5b2z/yDq8q+Q1PFD8vbt9RQTsoqwG/eYBeUWkDzx7dUOYXni+GA4JB6pUm/m7wB4uGlquvW+7tdOlT/raXvSG5N2U6CD2nIgfXDnEbhYw+0Gx4tkkMTeIgSx7WU8tPSfnqtVpcq9NLgAOdY8zFyjZYTZa/grP/ytmqm6s66XQcDEfreCiakcbLpQZxNlQrnNgDQNgqhEM9/qs4ZAQA7kgrN80FJb/0vESHhVWKOiozTDAB87uep0mfSyUhVPZS1fItqrpT2ggSPG0I3AHXHKB9ON38t/B3uVYMBQL1PTeBo+wAgXMMFcmY9pVsFMIAvcrJpg4SM1QJyOOV67AWtVh+/MaoLWF2T3mvox9aKbe0e7ZZktFgEFMiFkoOWTCOFCAcZUYGAbQJT4NJg7VCNTSNZ4eyQt1G5Zpv2HDKuTDuqkIOFZNetPplieFdlCiVaRLQouPIb+Ru593A5cx3AFaCvqRGwuMDVeOjnOWZTo0asJuXGAgsopjbogIVbAulK9H0BoCQDxVHEe7EZ224ldfmQsJV6pFgbtPA7fQQDgGop4Rq7rBSarB1Nzu/KaSJ1CAe9ph8AJJF4HPmqlUefp3w43Si9Bx6l1silZ/PpuKb7sKWGvG5bDOkTLhpWYpJms0lPeqKBiQT2Uz5UdnZScf0bz9Can+QzYz0y1w70bCN2qScsDNOebnTKtKPOtjdVkAYi2Ln4vOljSBLOd7QjTuncBmlZXvjbKDB6mHgfrtQD3kHLR/EOKA9w+mhYDqF+AGxtC4RtAbTnBdbk/7usmJmvvAfk+aK5swlgTxv3amojraqi846xEkRFsBkBM1go+fYkGSZzAa5LAAgls9hjiJIG1KAc2cFPACS+BYB/26stk726AiMsmiTK18NblWZNBcNNup69QXOaE5JrtMQboPCBOqVMUnyi5LGyEZikffjtOfZ6Yk6iBFE5RBUW1iZWHi1lpwqMlpDT0od+fds1svkdizFrDAsxNX2hYCA7gje0Dqy3Yg1ZFMjlZzetvGFzrhX4APQUzAM4KQ+onh673J32p2vHXk/8G8sX8wZ3PWBT5zXeAbW22co49+Bub16xsPzvlsuNF8FufgDZ/p2qVLbr3v5NlXv+plQMBWPQXar0GRNIWRTuOfShyddRDAg+I+LYSy/RfshAobkA7XKquraxVpOcvf/9taVWqfxGNvru3moqzT6alCyQifME7iGgUN+L8woeafYTh88IAPgfqqgk1foN7D+shSQQmFr1f/3WYyR/MwCw/a/TpeeEk7nLFERo9C1WkCznniPf311D7vlulom60wmjG4RuZkr+xS2HyV+TJtupW2wzf6QAEMsRAQTBmqaDUO6VXqduP5J2UrvT3gB1Y/frkyz6pDgJtsD0UNFILZu4i7uVQxmysW5eoT4GnChALfVk4XdxQGDdefavBSa5MU1rpSq3BM0VKxrfCFCl7fLeYwKud74briA2NJvDphs1z9DqFu+OW2HACQc/1VngTdkF4+kfsE8QI4RmDYpR6wi/AxSJvLODV/zkp3OGe3AnqEuoaO6shoOniVr53QsAVdsnN6PWubU3IVzWWl9XZaIl6dCeq/YZa3Kr8W3USsYziIAkNYQ+Ty1/mj7B7z0gZJNrjfGb9+9zrWi5JVtxoE8sYJ2bJaa14SDzggS/+UFS4Ed+SazAoc0GgF7lxC63iMLgLaVIH6W7Dz+lKowqMsxDwDQAESv647/ND0SPwnsFLNhJh+nPrsiRrd2AZKWlvO+EOxHX9I2XFZPbv55hUsIQeYnlBzqHWhO1PJtW17HngdcCCOjr1qKCPPTz3EAkvl2tRO/Vb61zBasDblP600Tbyj0kUv6emiUD1lvW8BVlCpoUI5rUm7Q9gEnyuvE9qVxBHlP4UnZNZ56PC5ja5bin8UiwvmgchliBGa9yGHUeXvnBxGQuOnufVOszoBDXIKlCKP+nSehnPNMwWfk9+zt4PSDw/khirVQX7zfTyFWtQqT1qf3m64ilW417kqYAGzoA+Tr5xuQ5JGAFioPuR1iCsQhhYad5S4byN/Y4qjkVyJklIH++m45N6Ues2UZlC8mLV19k1pm37Bt9wUNt/MHJdEs6n6BeACSh2MAnxhJISi57b8HtbQfM0R/0ElI5efeccMAMsE7Nd79m82+VwoNy0vOayiFdrr6diUjXIUuk29ClpmQqssflj6KFpwneL/NYq24R9EO6Hug4lMNUr4cCQAJm+LasCapF2YnYvevu+n5TzbxWGg1rA6sp1DDlfGo+2DOpFvBDIlIoifPHNyEZM3k2iHG+K9hHSqe/+wJA0gBgvULrwzVju13v+36W0TLtCc5iU26bd+Jjpv986tpAeTTe0w4c8QJALwdELV/hFpQWwtY6oipPAlEwmdsuPo2cDLVRNv94kuEshQKAdtQgFp9/fT3d8MVwpwAA4SR6XWmMC2skUWda3kkPcrvkl/dwZwMk3xWHCNw7LK1oYrZbkr7J3YdFg7Gx8bLocHvCX4FsT1NXqM3jUesRkWBEGxIt7QWA9hxVt/DiF68ySZm1kS6nw8DFgf8OJT8uIuXBqp0HzIaAyxRXhu1u9QJAtbwQ1YwLgmZHifK87C8OSOaiU+VBD3BNWK6ggEOBVAhYPfR5Gn2nvDC/98C9MmjRFrkxqcoG12jxeu/6UM6irhWsnOHal9PWJisBpTw2BSzeMfUdvzIwp4LlWfSjZug8BjxnzXyS16UuNtyb1L32K0ln1wj3WnNCvR/7yJgV202AmFqElXel9V4BZBzmtGAWQH7DbQpvVpPdYgF6tVWlwOO5V/cZLQsJZ+/O6iXMIbd6xwGjTKmXwB43lhqsPGoRg9NIhCnBRjougAeUATi70ELWvHTS+sg1ugcx776ZuS6QpBevARZ1LOiaykrndeO+E5LlDbRd+tv2HTaJtHFnt61fRn6cvV6GPlwvYH32BizZ72OvJzhhBKYAYkk9kyuIgs090DiY53ZFKO/3RYFF4YeuQ9lGLJNaI12v1SAD9RTxPdgL9dn2HNZ71F0cbB5oQmO+P25x6qkzZiztcKjt5uWAeteQBjVokmbuJTCNMoLKU8TqTE5Z3hcLLIDIyy0Pd16pAs35RtYCO3GzTRsi4wTWaay1PdpUNnxnLf2nNcvD7SPqSSC11z9b95s9QgMrsXg+3qBMuC4CMmD/Jap3QbsrjQKj3wTPFBk4lHfL31HySIXDfETBg5+OwYCoafYcglmIbifY5kwCgF5hsqPC/0PtSKyonnGaLwDUyav+fbtmIdUhyBWEy0kbi015RH4T35us1QZOJDzWkm8c5Cbti1VTlU0KMGW7dPzEpxqVHezAdWh0LCBI6E2SLDwKQNUN4defmq9DARib98d1Lw9ebCxguFNY1OTa+/K2qoGqDPocdTfCBflrwSZjmaSxEWZtl5gu0u+5uG4rFsllXLUcFHoo2eMHQHEw6P1EjeG2s61qcOau7zctQIzmfgVubHI0NjTM/bh7/ZpaEb3BEV63ZTD56WGBG4tqKbhDtTauFzzZz9d5ZoN3tShqvUrlsSifUftbvm2/sWxqahA/nhxueLhXHPIc3KGi+ez5r98Msj0R0953YCzUWcaCTtmsZxuXC7sLfDNjnXHPaQt3qNjrjACq2c9BQ07eKvUcmay6Cb9qmg2v0qHRo1qabceBhGQkeO61AaCWNws3TnPfL3MNrYDoTK0WoUEfCugjBYDKVTY58coWlCtKF5RCuU7SRNifNB2VWo3sg0/pExxgJEePprHvAOQIUINr7Kc0KejQvUwTixPBv2jLXqldskCgjJgGRzTqOyFZdKldq5bx4RHAYk8gB2P4+8E6gf3HL0DDO1f5b/hlHOKM28txtWXAt4LrS6ANY7YVPvs6Bbp4VpAHVicoIDdfTn2ExKbUoGA0gY8mrgpErus9tpLppwhoUmOA2T01SkjbBmUMANTkzvYYlS+sASXeuapeAuSqgVO2ZZt+7QhrP7kS7Trn+VPXnj0OrOHQDcj2QJqeflPXGGUEVy/Bgyg0uPKZy7hYmdu9rr04EPBBX6G+s/0sVe5xYZOHE84nHgmoKlgbKWAQrqkM9DpS4hAESkMmfsrTAz/ONtZp6sFf12+q4ZtiVaWpVVz3jzMZAIaTbWr93g1Oa1KuP5LotRWRxNDYk+0UAKi8Ly5R83corU8nABFIcHlUY7cfQj9vjlpmCOA0OxeeDQD5TQnOen8khwnXjlm+zXDibF4bf1fSt6ZBYbLq4rddoN6PoGkYQgFAOz8V13UZvMTUW7StbSofu3/bbep9rneDi3ZyqItPx61WnFAbPM+gni7ka72PfHS4CxJ6JQJCb8O1zqL2AkS+s53VPpj8FLThUiKnmp1NPxQA1Ih08muxoWhDblgCDr3RRh78cY78PHeDKfrOga9Aee3Og4YfqDWPbeuz/X7UnCa6FM4inEJSe9xwWWJ1G79mfzMsRnd/P0u2dCMhQGIDOKn1NZrvqVbtSNdCvylrkiV59pP9Jb1GBXLYab9QPvgGh3udVOr4Tb+RHhK2617vtQFg7g4DjTs8kjULUOabD3iwjmgGAOWXKUjTMpL2GtK+bUsWa5uADcrpaXJwW85ci5uOw1b7sg8s3efUSxDNN9JrlVuGUkipN7up4kF07VtjlwfyPMLDQtHgHpJo05QPrABQE8l7LbrjV2yXO7+bJQRyoLD8/u9avtZn77sQqQvFBMUC61yZQjnk5i9nRPTNwsmFCFUq/kDDoSY8XD6vh0BryAabI1rv3X6WzV/2A4Cazw/uOi5nAA3Xaeofuy9VNgj+IRjNy8FVLwFpfUgFRPMCQLwW6jLVvnVcuKNRtr0R0uFkZ/+u/ECAdL3SBUyAinIAFcByfTB+uvdZuGlJV0NglgbBKM+QiPt7ayXmfAzVvF4V+4xDASG3KunT7Pb4b/PMPuoH9hdu2msqUGmlMAcAw32B6H5/QURICE04GoVau5BLlJyYSRHJ2psBgJ3/mCHdx643Fp+VHZvIebkTI4nUIuX17XuHwgaKthWuYX0gfQK8ldeGJxYO9wJAb5H6SA4Ts3Gu22VKF3mtekr6xpQOQfjmL6ebQAm0H6/Lyx5/JAAQTY8yOoePHTeBJwoA7QhE+mRzwNXSolIRk5bDzsnnlZkutEjf23t/8W7DTDLeaO9X7preh4bKdy1ZIFHL8zbcdG+OWh7QkvV3DoFGH0yUj266zLio/69KaODkl+suFADUvHdeNxcyVoslgILEl173uAaLYInB8ghHCLezt301fa2p90r0eSRadkpBe7B1g2uy3nvjDWmeFu6baiJegBA5yhqXOxkMpc+o0nu0qWyirnRAM9ZCLNZ+1l7ezY649rrkbVdZ3o6DDM8r3DgZS/u/F5mADVKb6BrBlQog1P+2cz16ZZyv06CAxVhzoQUDgOxjlAzTnHVE21NCTfmvCgqUfxduH/P7XYPN/Kw/ynGEhI/Vh3yoWNLgIS7ass9kOtCqEVBGUCwpvUXABLJEgSB/G//Txn5H8my4YbjUfrynhqmLTITnwIcSZRiqIU8CySoVyWOiUbE8prSptwXOLZ4iFH6v4qncxmBzxBuly5hsV6e6Y21FAEoP0cpYSTs3rWCSWPN+3qjUSN5Pwbo9l+w9mX5DAUDGsr+Hv9ckkudzjXpHOCcwluCN0YAoPc8i2Q/8nqdeBQw2ZHHQtGbhxqb0Dr3O9igFu7dd/4Xy9rgVvkYEtfKj4Hx66+VntAs4nGxT43cyZL6VVA6O/tk5UDGf9aSiMQBww5btckHPCeJH8GXC2ykIUjJY+DPwB9DYAE3kcAKMQSbVhvXGLp0WyWHCvcqL0jQ02p/yi3RjNQvnxAlTkLpV5aJBX8ePy2VfjFw0h6H+XQGgVzPjWqLK4BLd+e2sQI44v4eTxJO0HpG+t7cPzeMU7f3kkiKdC1HDadWQC0EEuMrtFgoAahS01/VMX8qRCzZ+nQvkSXupGbqQf8Py1mHgIhMsEYmWnVoAUEcXaf9qMSQXJlUW/JoqWBq0hdUkX/YsBgBu90Svcj/P1lRD+t92vzYAzN88voAYAAAgAElEQVRpkAlwiGTuAW7ZA9SKy3NIuj3k4bqme6yZKA+qWHplAMinxB3cOSxEVLBQnlS081ctkF5rVTT9aJCWV6GlD80hCqe616jlJhUKQVwcjpSHo0wZdV/NPtb+KilfOLc0eG+8qW4STJYAlUpvjDL1znEja7BYNGOO97VaSQl6BkoLwSVY4e2mgQHB3gvl697vk9ektwNUFPjbABBlhgY9BK4tlJrf5m406UqI3o6mqYXNrjTkBYBKJ7D71fmpJeWieab3WrWkKveRvslV2Pemy5JlPIhknXn71mTdpPrB8kvhhFBKut6fs/2AQPQ6f9Ngz1DvSfDJ22NXmJrdfo33UuOSswCmZMYkvxc0tQt+vScamQyWhBQ+b11uAODu3bvlaObsp2iZuuFTU3JM2/rxG2GInrz51SKd5KplU+z+/LzZA09Q0reWRYr0JXB3oVWGIkbbBxb9KgD0jpmJDtmV9CO4qW2Xhnc8mn4m0veO9/2Ryice1yEXJSPbSV6DAUBSkeAuu+f72adYFujLpi/4jU+TEmtEbrB3gKBNRCe5JI/3vjbsq0YK0MJ2FOSCSPtXYnkoSxaBK1ih+d/wR+qZQxIgReCQN3qV4WA1tXOLeS2AejBxbcHOg03VgVjmLv0SDEEt7GCHBX+3+4abBj+YtU25Pc33GIucAWl27sJo+9BsA37WIY2UJJIWqxhRkFiwcY+heGGp+nZmIgDUykOaQy2YLJWPCTds2/4E6ZdkSY123PG8Xq1ndtCGt/+7v5tpctIFey9NL2XfZ+eVvLD7cFOFxQaAWLGxjjK3qfxicw6jfT/lg3ZtXkG6JCVOHr1sm8loAT+UeUqeyHGPJz8PdV2E4k1HOhZ1Q6s3i741EbRW3InFusnzNVm3JnoPpSza41V+r/4tkjUOHxwlZ0OX5IE42gfvpQqTA4CRzo7w1xFRgEmlsojYGTV/QBklc4PVRQAA5s170gpnP4KPBMl58lOJpXRSu+GeeX/CqsBjIploXIwbB/fnmpeahkwXE6/x4+6gJqVNNtcgED8ASJqYDleXN7wHItO8CTt1XHAWiSx9omH4yCy/d2ETTDh6IlB7Ml7vmxr9kB+NKDjemcAckjnTbPnd+tUMmbl+t7kG7Z6UGwBAPxnzPda9nDwC0x63UhrCAUAinInoJLdhMA6kd414xx1PeUGd4AAKpknrs3C74c4jRUnDsokR0n4NS2G3oUtkcfurzc+kPMIVubozCQtCNy8ApJyYWo0pOwUYiXTNemUYLHUN1/mBYA5DkgtXL5HfpMcgoCEl3Ktw7x7qdzh5VNkIpiyrJRV+LAAQ0Aq4pkzaBxNXGVBEUwWWsnOUygsmS+VjolgCfj66uUpKhh+Xe9V6Zied93aMpZTURis6NfF9pibNtn8keEGrmlBaEDdog6T5jVyJwmX/YI2khMfJMxVgwRPumgQAvfOUQKOxHoOIzk+skF6rZ7TCVd66ur7pW12lyleNFQBq9gZc/mTH0Jrr4cao/F69LpI1Tm5ZLIDLOvp/axTWykXzGMqDA4DhvkDkv8dkAQwFAL2uzsiHEv2VVA0gzUk0E02vRdNOrwOAMYQCgHDdPrv1cpODalzb+snSbUQvpTPzjmCWLhKTkn+O9ET31SphIsu8qQu4l3x2q0KAGA0usLllfpIctGizKQ0Gb4yyXuFapBa6cP0E+51oXEofhrNQKQ9N8x4G6w+LRtehSwN5Akl4DACEGB+u6bsS6V7y1eFiA0AtMxfJ4eB9TjDLil5X6+2xMmfDnogAebh3SI3ftcZwMLoM0fhUKSG5O9Gydl5Tm/es5PpwAJB3UM6lbYVNjXeLtE+1nqXEla5WbJ6p0b2h3I1YDKn4RJL6VTsOikbbRzpm73Va+i4UAPQD+bouSA4dTlELNzYNVlPXN31TZUlLAebpOCgmfiPPZW+jIpOmJ4MH6scV9o4xT8eBplRoNOcyNA4sgHOfvzLcKzsAGFZC0V3gxwGkHvEzfhzAtm3bStasiWkTWrRoYf6njckXrKxUdEOK7GqIoxSMj2aiRdZz6l9FDqm7vp0ZsKzoEwkoIJdipaJ5Un8Qp/ETggEp1YjtIvV+AAILUDgQwzMoQ9SxKbnZ/Rsl/ygmH6k7J7UBYKSfVHloGvAU7D6AMHU9NSiCwCjcTgvaJY9e9bsfEj6RjiRw5r1tAIhLlrRGwVw+od6DvvzSa+g9kMbJxZYvgmCzSOUVz+s0CI3gjlBBGJpf1A5A09yqjEeBITkXUXw02bnfWHXeeVOtxPO9oulLrWcpAYB2pQ5N1xWJQqHc6VAZFiJ5FzwoRN2GAoDBLNV8D7/UM5E813sNPMAaSQn+6Zcyd1/dUS2QMilWC6DubdCQLuoxwkRs+5Wr845HlY1ozmVKVmIBDEYfGzJkiPA/WkJCgvTt25d/5kvyVMYitpjvoVLVmdTg+REFjPkCMPhyUhJqqkFTl1hbRC7gUAmB4y00b/3TSBZ/vMfg+ksfCQQDUqoRa0m3YIehXwoO77U8w04v4teXVguIVJsnZyRuuL8eqJ0+gkt6qubWivYAJmErgUezfPIGel8Iri2tWN7s8sXUtdKqcpGgdIZohMF3wUJGXsDTsWmuv1CVMnivm76YJr/N25QsuOihn+aYGrjmIKTaRKaTybhDySKjKB46Rg2yinb+2e9o1xPWCjWRnAHV3xojs9bvCUt/CDe3NCAoFAAk4TSVV/z2lnCBaOGe7/c7VTiI2r27ZslAZo5YASDWfypDYcEniAi6CBSKcM2OuufaSL4JHjk4wRptH+oZzgUc7gtE/3vXpATUmJ2mh8oDSBBIKBcw6Qq82e2jH05kd2hJMr06kokWWc/uqowugWAHGuWJqIISDgAS0RrO3cAzerSuJO2bBLcATlq1w7jqCJDwi4zNqHJU4Epd5dIFE+s+R9JwQQIAp6QRz9dvTHyXtKSaRCKXaK7RCFitZhLsXr9KSljObvt6hqmbGknUufad0QAgQXM52g80/EabGx2NHNVFyT14nshPGckZoC5zb2nMaJ5ty9WOArb7QObBgpUoa4cVmxRDqdUUoKYUAMJDJwsHlJqcWYOXWNX30Ah//tublDwe7+oAYDykGH0fYS2AZCkvkT+7IWumRYPczGGkNUcjWfxpMS73jNSXQLADjTqdlKZDC/537VK+A+HeYImdvRu4XWHCrzMtBxUuqjj1JRLdEzR/mDcSPlwvWKBYc97IxnD3xfN3vl8kFRTi+cx49qURsHB9v70rsX63X9PkuN59TRXfaPY7ZEbpubUhAp/i+Y5p0ZfSGHiWlvaLRCZXfzjRJMROifVR3w+52nWovfsHdbKJoE+vxvi06lG0Y9CCCdGCdKqREIBCs/N1Rvv8YNc7ABgvSUbXT1gAGF138bs6o2m38Xsz11MwCWR6vr/JE+nd8NWyQCLd++v4A0AsK9ddcn7YnFYVeoyUX+6taZKCB2ua0LZY3mwx8dnS6wure2fHqy2kQFLd50jG8tivc01y4vQ+1NL7YI1EVsGu0QhY8n1+cXu1oF11GLBIeo5cdsocjwUA4nbG5eiXzDwl75Ke945YulWafjzZuCZJNN9/4eaILIAtPp4sQ5duFbtEWazvEQ4AxisvbkrGFysAVC8B5dmi4dNqiidybVL32s7dG+t72Pc5ABgPKUbfhwOA0cvM3ZFKErBLLtmPULdHKAAYzyFpHq7Tzbqih6e3Ek042VCWDQAYSQWJcH3F+jtF7iH9RwNcY31WatyneUj/XatkyJx8fUYvl+f7LzwF1Lw3bqU8+cf8iMBOaow/o/SpFirSlFAtijJjkVgAtXKTnTMw1ncKBwCDWQdjfV609zG+WF3A6iXY93qroDlu/caj9dUj+RbRvg/XOwAYi9RSfo8DgCmXoeshThLQZKN+mwybnl2SLE6P9O1Go45LF8whKzuFz42XmmOJpm91n0WSpd/ul8h7Kun8cX/6BrFE864Z7dpt+w5L4S5DTWnIR64oHXR4WLNHLtsmrT1ViLT+a2odsBlNXsHGo/kU4fJRSWLAoi0RAcDGfSfI2BU7TkkQH8t7s9d0blpeXk2qHW33QS5R8g5qffFY+k/pPSnxjql8D73R+pTavaHGdd5Lg00Z19Sanw4ApnRWxHa/A4Cxyc3dlQoSIOnz6OXbZHO3k2mI9DFseqHSwMRzOOrOS8vo93iMXy2A0W7SnQYukn+27Zef7qkZj2GclX2QPuSCbsNMGqKCUbjfbWHRR7bMJ+v9no2CJEciCYpnP9dIOgxYLIMWRwYAw1VOiUaWoQBgNP2k1rXxAIDeGs3hxpqSJO/h+uZ3BwAjkVL8r3EAMP4ydT3GKAFcvTTNT2d3w6b3/V3VTTmm1G7qzjvdACDygwfVslKRqETUbcgSAwC/uTN48EJUHbqLnQRilMC0Nbuk9jvjTKLi5/svkMGLt0ZkdarzzjiZumZXRNeGGxp7TahyiuHuT+3fUwIA1+06aBK4R6skxlpjPlJZOAAYqaRCX3d3UuoXysAdT6r921lEJga5zQHA+Mjd9ZLKEiAyt3rxfL7gMN6PVndeaqQ7iPdY49Efst2677C08rgl49G368NJIBoJaELtJe2vkpcHL5EfZ2+ICKxoHsBogU00Y8so16YEAMb6Dm+MXCYTVu5ItVynDgDG+mWS3/eoiCxLAnxkbCUZ9KsiUklENvg8wgHA+Mjd9XIGSWDPoSOSr9NgKVUgR0T1cc+gV3ev4iSQrhLQCPzlHRNd6Su3H5BqJSgOEbpV6T1a5m3cGxFYDNdXRv89PQBgasvEAcDUk/BOEblPRP50ADD1hOx6PnMkoOWgiufLLuvOoBxrZ84Xcm9ypkpg/sY9clnvMbKmc1MpWSBHxK+ppeCcBTBikWWoCx0ATJ3PUUdExokIqclXnU4AkDJT5+XOKtdcXDR1JON6dRIIIgFq5Z77/N9SOHdW2eITkOIE5yTgJJA6EtCSetEmMy/fY6QQvX82AMAcLw6QQ0ePn1Hv6gBg6PX0uYjcSwk+EfGrWzxaRK72dFFSRMaKyFci0iVI9xnWBZw624vr1UkgMgnEs7B7ZE90VzkJOAmoC3hrt+ZyXu5sEQtk4sodMn/TXvlPvQsjvud0vTC1c/Klh1wcAAwtdQp7Zg9xCTVa9lq/XyQiQ0XkRxHpEOI+AwDbtm0rWbNmNZe1aNHC/M81J4GzWQIAwJxZM8n+Hq3PZjG4d3cSSFMJzNmwW6r2GSvRVqpI00Gm88NKvjJM1u0+dNpbAIcMGSL8j5aQkCB9+/blnxA+96S1iP2samk9hng9r4qIDBaR90Xk9TCdOgtgvKT+/+ydB5QUxRaGLyhJCQooIiBBRRFQgqKgiCAKijmnZ86YsxgxYM5izjlnVAQEBUGQJIiIiCAgIEmSSNR3vtr9h9qmZ3Zmd3ZZsOqcdx7udFdX/91ddeve//439LNBIYABiODrynsO2qDuK9xMQKAkIzD694XW/P6vLdNKFSX5nrI9tj0eGmhDsyR5k+2xFbS/4AEsKHJ5z2tjZh+bWXczeziNLoMBmAZI4ZD/HgIbYqbdf+8phjte3xAYN2uxNblngGVaznB9u8/CjHf24uU2a/HylPXMC9P/ujg3GIDZQf1LM9vbzJZ6XEF4g3gC74y5RDAAs4N76GUDQyAYgBvYAw23s14gQALWgEnzrP121deL8YZBZgeBYABmB8dMewkGYKaIheP/EwgEA/A/8ZjDTQYEAgIlAIFgAK6bhxAMwHWDe7hqCUcgGIAl/AGF4QUEAgIbDALBAFw3jzIYgOsG93DVEo5AMABL+AMKwwsIBAQ2GASCAbhuHmUwANcN7uGqJRyBYACW8AcUhhcQCAhsMAgEA3DdPMpgAK4b3MNVSzgCwQAs4Q8oDC8gEBDYYBAIBuC6eZTBAFw3uIerlnAEggFYwh9QGF5AICCwwSAQDMDsP8qLzewBM7vNzG5M0n0wALOPe+hxA0AgGIAbwEMMtxAQCAisFwgEAzC7j2kHM/s0tzzcR8EAzC64obcNH4FgAG74zzjcYUAgIFAyEAgGYPaeQ2kzG5wr/nypmQ0MBmD2wA09/TcQuPLjH+3XeX/Zu6fu9t+44XCXAYGAQEBgHSEQDMDsAX+9meEB/J+Z9Q8GYPaADT0FBAICAYGAQEAgIJBdBIIBmBrP583sFDOjrFupmEMHmFkHM2tmZh/k/v+CYABm9yUNvQUEAgIBgYBAQCAgkF0EggGYGs9NzKx8ikNWmtnfZjbCzG7KNQI5PC0PYNeuXa1s2bKu+06dOrn/hRYQCAgEBAICAYGAQECgKBDo3bu38T/aihUrrGfPnvyzipktKorrpeozzqtW3GMo7PXqmtmvZjbP8xICJsYhf28ac4GQBVxY1MP5AYGAQEAgIBAQCAgUGIHgASwwdIkTMWJrRrp5x8yGmtmdZvZHMAALD3LoISAQEAgIBAQCAgGB7CEQDMDsYen39KWZDQpZwEUDbug1IBAQCAgEBAICAYHCIRAMwMLhV9CzQwi4oMiF8wICAYGAQEAgIBAQKDQCwQAsNIQF6iAYgAWCLZwUEAgIBAQCAgGBgEA2EAgGYDZQzLyPYABmjlk4IyAQEAgIBAQCAgGBLCEQDMAsAZlhN8EAzBCwcHhAICAQEAgIBAQCAtlDIBiA2cMyk56CAZgJWuHYgEBAICAQEAgIBASyikAwALMHZy0zu8vMOpsZ6s6/mdnxZvZDzCWCAZg93ENPAYGAQEAgIBAQCAhkiEAwADMELMnhm5vZSDN728x6mBnl4LY1s4VmNjcYgNkBOfQSEAgIBAQCAgGBgEB2EAgGYHZwvJVqbmbWKs3uggcwTaBK0mGUzwnl+krSE0lvLOG5pYdTSToqPLOS9DTSG0t4ZunhVJKOCgZgdp7GkNyQL6HfdmY228xezfUG/hM8gNkBeV33ctlll9n999+/rocRrp8hAuG5ZQhYCTg8PLMS8BAyHEJ4ZhkCVgIODwZg6ofwvJmdYmb/enV+/TMGmFkHM5toZvXN7H9m9paZNTazT8zsETO7JxiAJeBNz8IQwgSXBRDXQRfhua0D0At5yfDMCgngOjg9PLN1AHohLxkMwNQAbmJm5VMcstLMFpvZCDNbYWatvWOvMbNDI3/Tzy4EPG3aNKtcmX+Gtj4g0K1bN+vRA4pnaOsTAuG5rU9PK2es4ZmFZ7b+IbD+jRgDsE6dOgy8ipktKu47KFXcFyyi6z2d6/Vrk6YBSMbw9CIaS+g2IBAQCAgEBAICAYGAQLoI1Daz39M9OFvHbSgGYAszG2xmJ5vZO2bWyMx6mdmDuf+L4sV9b53rPcwWlqGfgEBAICAQEAgIBAQCApkgUMnMZuRS3TI5r9DHbigGIEB0MbM7crmAs8zsqST8v0KDFjoICAQEAgIBgYBAQCAgsD4jsCEZgOvzcwhjDwgEBAICAYGAQEAgIFBsCAQDsNigDhcKCAQEAgIBgYBAQCAgUDIQCAZgyXgOYRQBgYBAQCAgEBAICAQEig2BYAAWG9ThQgGBgEBAICAQEAgIBARKBgLBACwZzyGMIiAQEAgIBAQCAgGBgECxIRAMwGKDOlwoIBAQCAgEBAICAYGAQMlAIBiAJeM5hFEEBAICAYGAQEAgIBAQKDYEggFYbFCHCwUEAgIBgYBAQCAgEBAoGQgEA7BkPIcwioBAQCAgEBAICAQEAgLFhkAwAIsN6nChgEBAICAQEAgIBAQCAiUDgWAAloznEEYREAgIBAQCAgGBgEBAoNgQCAZgsUEdLhQQCAgEBAICAYGAQECgZCAQDMCS8RzCKAICAYGAQEAgIBAQCAgUGwLBACw2qMOFAgIBgYBAQCAgEBAICJQMBIIBWDKeQxhFQCAgEBAICAQEAgIBgWJDIBiAxQZ1uFBAICAQEAgIBAQCAgGBkoFAMABLxnMIowgIBAQCAgGBgEBAICBQbAgEA7DYoA4XCggEBAICAYGAQEAgIFAyEAgGYMl4DmEUAYGAQEAgIBAQCAgEBIoNgfXJADzWzLqa2S5mVtHMypjZPx5SO5vZI2bW0swWmNnTZta92JAMFwoIBAQCAgGBgEBAICCwniCwPhmA+5lZVTPbxMyeiRiAGIQ/m9lzZnaLmTU0s8/M7F4ze2g9eRZhmAGBgEBAICAQEAgIBASKBYH1yQAUIO3M7MuIAXiKmd1lZlt7XsGLzOxCM9u+WJAMFwkIBAQCAgGBgEBAICCwniCwoRiA95tZIzM7wMO9tZkNMrMqZrZkPXkeYZgBgYBAQCAgEBAICAQEihyBDcUAJCS8qZkd7yG2o5mNM7M6ZjYjgiT3jbdwcZEjHC4QEAgIBAQCAgGBgEBAIB6BSrk2yr/FDdCGYgBm6gGsZWbTixvscL2AQEAgIBAQCAgEBAICEQRqm9nvxY3KhmIAnmxmd0c4gBeb2QVJOICVzWzhtGnTrHJl/hna+oBAt27drEePHuvDUMMYPQTCc1v/XofwzMIzW/8QWP9GvGjRIqtThyClo6otKu47WJ8MwNK5iR8kgZDhi9t0tZmtyA3/TsjNAr491+jrZWb3JckCdgbgwoULgwFY3G9cIa532WWX2f334+wNbX1CIDy39elp5Yw1PLPwzNY/BNa/EWMAVqmC7RcMwPyeHpm+z5uZ4uQYr/y7vZl9bWZNzOyxXB3AhWb2uJndmqTTYADmh3YJ/D0sSiXwoaQxpPDc0gCphB0SnlkJeyBpDCc8szRAKmGHBANw3TyQYACuG9wLddXevXtbp06dCtVHOLn4EQjPrfgxL+wVwzMrLILFf354ZsWPeWGvGAzAwiJYsPODAVgw3MJZAYGAQEAgIBAQCAhkAYFgAGYBxAJ0EQzAAoAWTgkIBAQCAgGBgEBAIDsIBAMwOzhm2kswADNFLBwfEAgIBAQCAgGBgEDWEAgGYNagzKijYABmBFc4OCAQEAgIBAQCAgGBbCIQDMBsopl+X8EATB+rcGRAICAQEAgIBAQCAllGIBiA2QV0SzN70Mw6mFlZMxtvZtfmysT4VwoGYHZxD70FBAICAYGAQEAgIJABAsEAzACsNA5918yqm9nhZvanmV1qZjeb2TZmtsA7PxiAaYAZDgkIBAQCAgGBgEBAoGgQCAZgdnEdbWbPmtkjud1uamaLzWx3M/suGIDZBTv0FhAICAQEAgIBgYBAwRAIBmDBcEt21vFmdpaZnWBm86hoZGZnmFlTM1seDMDsgh16CwgEBAICAYGAQECgYAgEA7BguCU7i1DvE2bW2cxWmdn83HDwkMgJIQScXdxDbwGBgEBAICAQEAgIZIBAMAAzACufQ6kN/IuZDcj1/BH6PcjMXjKzvc1sTNQD2LVrVytbllwRcyXGQpmx7D2M0FNAICAQEAgIBAQCAnkRoGQf/6OtWLHCevbsyT+rmNmi4sYKo2lDaVXNbK6ZNTez772bGmFmb5jZPVEDcOHChVa5Ms7A0AICAYGAQEAgIBAQCAgUHwLBA5hdrH8ws8FmdrmZLTGzLmb2tpkdaGb9gwGYXbBDbwGBgEBAICAQEAgIFAyBYAAWDLdkZ21rZveaWRszK2dm03J1AckM9lvgAGYX99BbQCAgEBAICAQEAgIZIBAMwAzAyuKhwQDMIpihq4BAQCAgEBAICAQEMkMgGICZ4ZWto4MBmC0kQz8BgYBAQCAgEBAICGSMQDAAM4YsKycEAzArMIZOAgIBgYBAQCAgEBAoCALBACwIaoU/JxiAhccw9BAQCAgEBAICAYGAQAERCAZgAYEr5GnBACwkgOH0gEBAICAQEAgIBAQKjkAwAAuOXbIzW5vZbWa2m5mtNrNxZrZX5OBgAGYf99BjQCAgEBAICAQEAgJpIhAMwDSBSvMwjL9PzewCM3vHzFaaWUsz+y4YgGkiGA4LCAQEAgIBgYBAQKDIEQgGYHYh/trMhprZlfl0GzyA2cU99BYQCAgEBAICWUZg9uLlVuPmL2zZXQdauY03ynLvobt1jUAwALP3BCqYGfV/7zOzfcwMUejJZnaHmb0XPIDZAzr0FBAICAQEAgJFj8Co6QutxQNf2+IeB1jFchsX/QXDFYoVgWAAZg/uWrmVP/7ILQE32swOza0DvHeuZ1BXCx7A7OEeegoIBAQCAgGBIkBg2NQ/bfeHBtmC2zpblQpliuAKoct1iUAwALOHPkbdAjO708y6ed1+bmajzOxa72/BAMwe7qGngEBAICAQECgCBAb9Os/a9hxsc2/pZNU2LVsEVwhdrksEggGYXfQnmtnb6RqAXbt2tbJlcz6qTp06uf9tCK3JPQNsv4bV7YFDm2wItxPuISAQEAgI/CcR+HLiXNv3iSE26+b9rUYlyttnp5W6/GN7+LAmdmHb+tnpMPSSNgK9e/c2/kdbsWKF9ezZk39WMbNFaXeSpQNLZamfktLNRWZ2jZkdYGZjzOxgLwQ83BvkBu0B5OMuu1FpW353l3yfy2fj/7AmW1W2OptDoQwtIBAQWFcIVOr2qY2/qr3V3ix8i+vqGZS06/b+abZ1fnqoTb+xo9Wqkr33gjXiqJ1r2tun7FrSbvk/NZ7gAcz+477azLrmWtR4BG82s08il9ngDUDu99/7sH9TNyaCzjtuYZ+dtUd+h4bfSzgCk+cttRmLltme9auW8JGG4cUhwLfY68xWdmCjGgGggIBD4MMfZtlhz39nU67b1+pW3SRrqPCuHbPL1vbmyaikhbauEAgG4LpBPhiAubgzERy8Uw376IxW6+ZJhKtmDYHtevSzSfOWpmX4Z+2ioaOsILD6n39t4ys/sc/O2t0677hlVvosyk6Wrlhl5TfeyEqX3tCCSEWJWuZ9vzHqdzv+lZH2y7UdbNvqm2beQZIzmPePbba1vfG/YABmDdQCdBQMwAKAloVT/hMG4D/3HmSlSqWeoJkIjt6lpr118n8vFPDQ17/apR+Ns3/ujfeU3tFvorWuu7nts+ksrlcAACAASURBVF31LLxyRdPF3CXL7Zx3xti7p+5mdW7pY9MXLgsGYNFA7Xr96Y/FtsOWFfN8V2RqTpzzl53YsnaBr7xs5WqrcM2n1vvs3W3/HYrGAPxm8nzbo+7mtlEWjDbmjfsO2ckua4faVmhFhcBzQ6faGW99bxOuaW8Nt6iYtcvw/I5vXsteO6lF1voMHWWOQDAAM8csG2dssAbgv//+a6WvyIl4L7+ri5XduHRKvJgI/teytr10QvNs4Lpe9dHh8cHW/5d5SQ0msNm5ZmX7/op2Jfa+3h870454Ybitvucgq3NrXxcCTif0H3dDx7w03LasWM4ePaJpib3fdT0w3ol3T9nVjti5ZmIoDW7vZ5PnF87zuvDvlbbZ9Z9bn3P2sI4NtyiS22TsLxzXzE7ZrU6h+6evM1ptY88cu0uh+wodJEeg56DJdsH7P9i4K/exnbaqlDWoeH4ntqhlr5wYDMCsgVqAjoIBWADQsnDKBmsA/r1ytW1yDdXwzBbdfoBVKp9cPFTG4tl7bGNPHr1+T+S/zV9q85eutOa1SaZKr7V5eJAN+e3PlAZg05qVbMwV6IqXzNZnwhzb/6lvnU5Yo7v728xFywtsALIo0ApqQJZMhLI3Kn0vLx7fzE7edY0R1fKBr23k9IWFwm3OkuW25U1fWL9zW1uH7YvG48zzvf2AHa1bx+0LDQp9ndemrj125M6F7it0kByBe/r/Yld9Mt6+v7yd7bw1y1Z22vq48V+8bFXK9Sw7yBR9LytX/2MblSrl6BPBACx6vOOusMEagDMXLbOtu/dx9zyn+/5WvWJy6QCFnS7cq749fPj6LRlT97a+NvXPvzNahJvf95WNnrFovTYAv540z9o9NtgmX7evtX54kM1aHAzAoppS/lq+yip2+8xeP6mFHdcc3fmc1vGJIdZv4tyM3r3oGH9f+LfVvqWvfXlea2tfRJQDFv3L2zWwew9pXGiI6OuSvesHqalCI5m6g1u++Nlu6j3BRlza1lrU3ixrV+P5nbxrbXvx+PUn8sOYh1/S1lrWyR4OWQM0g464DzldggGYAXBZPHSDNQDhKDW//2tbtuqffKUD5HW4cp9t7e6Dd8oivMXfVfUbPrd5S1dmtAg3uqu//TR7yXptAPb7eY51fPJbt0Ac8PRQm71kRUYY+E8qeABTv7faXEVDwEe/ONzeGTPT/r7zQCtfpmD1Wn+d95dt2+NL63vOHrZvEYaAT92tjj1/XLOMPtCxMxfZ1pXLJ4SI//nnX9voyk/sqvbb2l0Hrd/zhoB4beR0O6TxViWu3No1n4y3u/r/YkMv3stabbN5Rs8t1cF86wV5F+hzwC9zbdqCv+1/uV7w76YusOqblrX61bKXpRw3dsb84Wm72SFNtsoaDuuiI+5ju+qb2sRrOwQPYBE+gPdzS8F1NLMvI9fZYA3A/r/MtVNeH+U8QWiKpcoc06JzTYft7I4ujYrwURR911ve1NvmZGj81Lutr/2WwmvIh9pkq0o29srshoDfHTPDOm6/RVZKO6HjeOAzwxx3jGzBuX8FA7Co3jY2V43uHmBvndzSjt5l68RlTntjtL3w3TT7tdu+BV4E1XemWcDvfD/D9muY/7uk8PUhjWvYh6dnlvHPd7Dv9tWt77mt3T0vWrbSqlz3uV3fcXu79YAdiwrupP2S+LTFTV/YqnsOykpCCxeqfUsfe/XE5tZu26IJv8fdDLSVMTMX2cGNkxs0F3/wgz08cLJ9c8Ge1iaL8k4809Nb1bFnj81sM8B9oFe5ZPnqxEaTvmpVKW/Tb9yvSN8FrvPeqbva4U3X8G+L9IJF1Dn3Ua9qBZt8XcdgABYRxieb2QlmxhvJ/2INwJe/mWAntWlYREMo3m7hFZTZqLTd8NlPjpD+4bhZNvSitimJw6N/X+i8hdkKCxXvHZsRksPjQlbjVjd/YX944U/wuLXPz9a90w5JM6Fr3NQ7pccsagCSNPLYEU1txxqFI2PTb7a8Jx+MnWmHvzDcGSXnvTMmpReU6z599M525h51Yx9V8ACmfoNVl/Wl45slvB+cccIrI+31Ub8XykszZsYi2+W+r+zjM1rZQTulrwPIM0tnAyeZmb3qV7WBF+yZ0afKNVrUrmIjLqWkutmMhcus1i197JbOO9gN+xX//Dly+gJr+cBAW9LjANu0XHKOcyY3yVzw8gnNiywDO24s+zw22L6alDwJjXPOeut7e2boVPvq/Da297bVMrmllMfyTM/cfRt7+pjMud+bXNPL/l75Tx4DsNomZWzurZ2zNr5oR/I6v3NKSzty5zWbryK7YBF2DPZ1NitvU2/YLxiARYAzWgyDzGwvM5sKRSeZAWhd37B/Hz22CIZQ/F3yUn13SVu74uMfXVbv1Z/8aH3OaZ0yKWLgr/Ns756DrTg4gN/+9qeToMhm454Vvq7VvU+eDFgtEsvuOtDKbRwflqty3We2aNmqlCHgxltVsh9yPYBcr8eBO9q1+xaORJ9NLtZbo2fYsS+PsCeOamrX9vrJ/vw7eRic66aSfggGYOq3Uwk3Tx29s53lGdFHvPCdvT92lg26YM8Ci3ATRmv10EB7/9Rd7bAMPBz+N5Bq9OL7FsSjHTUAJ8xeYjve1d9u3r+h3dRph2x+0mn1pW87P45zWp3lHlTths9dhnQqb1wm/aVz7N49v7GBv85PSdk48ZWR9tqo37OeHOTz0NIZq39M2as+sZWr/y1WA3DFqn+s3NW97M3/tbRjmq3/BmDNyuVsxk37BwMw05cvjeMpsveWmT1rZv+sSwNwKEbPw4MKzMlK414Th/BBw026re/PdtP+O9j57441dkut6yWvCqHw4bmt69rjRxVdNp8I7n/cvL9tmeV6lh22q279zmu9lgbe8GkLbLcHU3sJyl3Vy1asXrOTjeINplED8NbOO9j1hfR60O+lezew+w8tPBn/lRHT7X+vjXKG6d39J9mCYADm+9kM+nWe1axcPmNhXUL3R704wh45vIldsNeaGqoHPP2tff7THOt/XusCa0ai0bfXo9+sFV6O3kz7xwY7oeirO2znfkp3M7Fk+Sqr1O0za1Sjov14Vft8MfIPiBqA+rau3Xc763Fg8VNHZABOvb5j1kpYVu72mT177C55QvsZgVSAg9s++o0NmpzaADzomaHWa/zsrOpDyht8Tuu69kQB5v2NrvjY/vl3jVoA7wccwDm3dMoIBc5L9xlK3eK1E1vY8S3WJGBldMEScjD3vUXFsja7e6dgAGb5mZyfy/vTm7hODUCEhi/5cFweA3D5qtX2/YxFhSL0Qgy+sG29PLUhxY+4ttd4e+Twpnbuu2Ps2WN2SbkgffTDLDv0+e9SckFQosdI8mUvMn1mE+cssYZ39i+SguYyAKNZwArXIY9SpUKZ2CHn5/Hi951qVLRxuQsm/50Nrwf9FCSDcr8nhljL2pvZnQetWXQlFHvjfg3toYG/2sJ8PJrBA5hjNG1VqZzNvHn/jF5lYX3PQTvZFe3XCCArlFcYEWe4ux0eH2L5LXCMfZvNK9hv1xPYyLmXy9o1sPvyyexlY7D59Z9bwy02tQnXdMjovqMGoMa6rqgjRBPIeM+mODJhzaeO3sVOKoSYd0agEqJ6ZJB9MyW5DBUbldPe/N5+mfuXfXpmKzsgSyUC5Q0uqIxPdN70DZp0MVBI94uz97D9dshf9xIJmMrXfWavnNC8UILr6Y6vKI8Dr6qblLF5t3YOBmAWgW6QG/rd3cym5fa7Tg3A6z/7yW7vOzGPAUjWJsruU3In8ILcPy+Qz7/Rx0T46KIPfrDXT2ppZ739vT1wSGPrlKKs1HtjZtqRLw5PKQSdn5GUzvh/nLXYGt8zIN+s5HT6inom2m9Xzb48r43Vv72vTZm/RgZGi0SqMFHcvfE3FV7n3/KYiESPodW9c96wFx6J54ZNS1tAmX5rVynvuFj1MqjvyXkVy21ki3scmIDh8cFTnLcXHljPb6bY4uWrjAowhLajhi/nH9dsa3s9SfmnbDzrTJ/huji+oPf5IJVjPhxnUS/w7g8NtGFTF9gnZ7SyLhnw9/x7//yn2S6LO8ovjOLD2MUfkgGYjjdZGf/KPkwX93Pe/t6e+naqtaxdxYbncgC1cbxgz3r2SJqi4Xw/JChtkUKWKt0xkYXa/vEhNvryvW2XrdPX/UzVf5krP3HesDN238YdRl3tdLJaMUzKbVw6X8F9hL4rl984Dx95z0cG2eAUBqDeU8bz0em7ZS08LWOq65718sxZrAcdG1a3yuXjN8zCLxsGII6Q8ld/6kof7rNtNff9JOM4Ml7mNXinUQ3OdN+ZknQc+PEuLLz9gGAAZvHBnGJmT5KkxsY4t19YswvN7E0zO9e7lssCtl0OtEvaN3Qf5T77drT2++6fVaHJc98ZY08O+S2PAfjp+D/suJdH2qIeBxT41qMGoPgRH5y2m53x5mjH/Tv9zdF2c6cd7NAUKfPijxXUKCAb0H2YVSqkvBeFjAqTJVnz5i/cvfghC3Bg8uh/fhuL1sEdMmW+tXnkG5tx034u3BfXohOZjLzPz9rdGc6+AUhSSdmretl1Hbe32yKZjye9OtJeHfl72qF+XXe/htXti3NyMivTaXEGoLzMeGOeGPKb/bVitfMinfDqyLXGU5IMQLJe7+o/KWNJknRwyu+YghqAlAbs9ulPa70DO987wMbOXJwxf88fp4wqvPan5xohyd5ZP+OSe7m4bX178LDUOp6SsKlfdRP79bp984Mo8buw8g1A1afNRED+zVG/23Gv5H0n+d5caK9sZokcMpaHXLRXVnjF+u4fPbyJdd2rvs1evNxq3PyFze6+f74GK/gctXNNe/uU1KU0Oe7Jo3a2s1uvScBKR4heDyKb2a/zl66wajf0Xov7zRhv2G97u6Vz6szubBiAoiSwafrxj8VO7DqZAD1Zx5uVL+PKXLLpIPzc88j1t1pRqSO728bTRjv8V6xYYT179uQxs5PBdinWtiFV8maVjxLeppsZWR4oIy9YywDs+oYte/AolyQAH4OqEEgLZKsd9eJwe3fMzDxyBR/+MMsOe/47W3F3F5e1W5DGB+h7ISRQi0bSca+MsJGX7u1CB3gGRJj95Mc/rNnWla32ZmuMtVdHTLeTXhtlRzTdytWSTcdI8o+BjzQgnyw2jteO/aer27s6qgVp3LOIszqfv7XbtpoNOL+NNbzjS5s496/EJEL4pG3PwSk5JtGJTIZ0rzNb2YGNajgDcMctK9r4q9ubJixlXC5dsSqxcBXUAPSlNdLBJM4AVKUAJpNnh021pStW211dGtnVvdaeUDk/VQH4ghpG6Yw9esxlH46zB77+NW2juSDXSHZOQe9TorzR0Of2d3zpwnR3dmnkwrEF+a6Rczn6pRFrGQnRe2DsaPL9flOO5Ab/fVHb+vaQZwDCJ+zz8xy3AVSb9uffts1tfZ3neVoGch3Catc6Vey7S3KygF8ePs1Ofn20nbJrbXshHyHhx76ZYm9/P8M67bCFXfvpT3met/pJp2a5j4Pm0FSi2fP+WuE0PvdMQzplFQoKV/VK1DZGnqXe7f1s2g0d88yXyebHbattYr90S21Ug2M0VE8Ym0hFMsNH2ONhJEPZlx7y58Ap1+1rdTOIJKCWgGqCNg7cP0YVSRbp8DrjDMAtK5a1P7qnzwH8c+kKq3pDb8Npgc7kDZ9PyBcHH//1oVrRfQMmWattNrO2DfJmb4Mfz3TZXV2CBzCbE3tMX6tTycCQBTz/7sNt803KWjSzqbDjEueGfnyBWCbDY14aYYVJiOAFuu2AHey6jjkSDC8Nn2anvD7aiWTC6fvt+n3dBH1GqzoJuQrOOWDHLe3Ts4iQ57QXv5tmp74x2g7eqYZ9dEa8NliqxXLr7l+40mP5SVf0+vEPO+jZYTbminbWtGbByhkxjihvi7/t3aCqfdV1T9vxzi9twpy/XPgTj654SpO6dbAG1TZd63EqbM4Pmkxk5Cnc4huA0h4j6/iEFrWcfI7OU6ZeOpOSX6tZ/MV037U4A/C2Pj+7yRNCN+8B8gx4MqgfGhUmzoYBWFCvTfQeL3r/B3tk0OSsGoBscro02jKp7I/GECWxp4u/KB3R0BkacuhuQq6Powik0782Y/JC6ZzrPh1vv85bmgjb+xshkfmjodg4bpk0P0U+T2dMMjD5f7iwtNGXtzMSj05/8/uUGeXqX2LrbFiji/zzw6a6fsZe0c4lEWyVxFMfHau8idqo8U5GKQ/afKfzTYoTpzJ54iz/cm2HfBOFeB7bV9/Ufr62g9skVkwiS8Nx0VD9Hg8NtKFTF+Rr+LDxve/gxmslP+j5Z8o9nb7gb1c3XDzk/Z8cYqN+X+RC9Ehqjbps75TzdJwBWKNSOcfxTrfJy0qi4sQ5f7nNwfxbOzmjcHGPA2zj0qWsdKlSLrSu66VjAPIugGm2FSdEl0rnffKNcz+J0P8797fynoOCAZjuC5Pl43JCwF3fsGm3HeJ2eeWv7mXLV/2TMCAKe72Px82yQ577znXj1+RFcf7EV0fZ+Kv2KZCenAwITVbi9nAdUuSRBIH3xjWO3qVmQvONj+jARltarzPXGIDPDp1qZ771vXXecQv77Kw9Ym9ZHx8f97hZi/PUKZX4sm9ExXWiUHNcGR8WvhmLltmV7XOyGpM1xqFdJpINQy9ua3he2jaoal933dN2uru/jf9jiS2/q4ubNBQmSkYUl5itP3aFRiTF4RuAmjTxCOJZoEliRjpw6UwO8jZwvviL6b5rjGfTshvZkjvWcABv/Pwnu7XPRJfIQxiad5gwIjzTqAeD84/ZZWt78+SWKZ81P7IoN4kx1uGw3th7gn1zISpLBW9d3x1rjw2ekjUDUB6FdDZWem/1rqR7F0grkWl9Rqtt7Jlj1+inUYUGDwoSPGftsY1LJsi0yRh68NDGdvHe0JlzWtxiq42QMiOjBmmcvMjPc5bYDnf2T3CP0h2frl+p3MaO7jHv1k4uqnH222NSRg7Uv7yjGMa39Pk5z/N+Ydg0O+3N0U7K6Z4Bk/LMvRg3eMfiPHjauEoTTjxYvj/mRxLONq9Qxr6blty48u9fnDgZ79/PWGjN7vs66Tfgnws+O2yxqf10TQf3rJIJNvObH6rHAKJ2N/XL8/MAYkRc3X5bt7GhLNykXG8jUYhNr/0skSAyavpC27pKecMYS9XgNzbo0S/hOY4aWNF1ItpXNgxAKUOwZlHC88pPfrSfr2mfSBasc2sfVy2DjPV0DEDW2wvfh//ewlF/MvUqJ8OL9RXeKhuxHv1+Sfqsvpgw2zavUNZ22yanTF3fn+fYfk9+m+CQcw9a8338Qim4dGei7B6XMAB/urGLc8fWv71f4grpLOT5DQdvzKODprhJiEmz6iZl3Sma9PyJAhf4TjUqpaVqrzCl9Oj0IdE3BFk8gX/dcYDjGe6/wxYJuQpeOgRmCVOVLmXWqEYle3LIFDv3nbGWyhOll/XInWu6iZ/dWfmNS9vGG5U2DDEmMFoqzLS4Db5wz7VkadL1xjAOeS/4NyER5E8kbNvkngHOQF14e2dHYhanCg0/JtBoU0iMHa/C/rMWLbOa3fs4+RzERv3JfdLcv2y7O/LqiYsjlJ8BiLex1/g/HIlbizbjEX8xv3fJNwaiBqBKRZ3Uspa9NXqmy9h+/Mimdt67Yx0VoHntNST5TAzAZHp08L9YhDLNJI3eo5ILCvqtsSP/6td5idCnvoN0aAZ1bunj+EQ0Jfyk8wwUtj6xRS175cQWiVM2vfZT58FiISuouK6+xXsP3sku32dNhnHcYquNEIkFm13/uUWzOeMEhvk2+EYUekrnfuVh4ljeO/ilePGfGPybM96ZT/D+p2oNbu/nhOm7IRkTWUCfGDzFvadwkN8YPSMPLQZdxM5Pf+syJaNNWDEHkLUL75kkLN4lcXVlsKbzfmnjd3X77VyGvfjD6ZRf4/mQKPbDFfu48nhvn9zSjvKqxDB2OQN8vdXGd/e3H//I2UjmZwCyyT1ttzr23thZhpdbx2vcisAwFjxfcCNTNW0GtHGIM7BSJRbFvZNktbIW+GtdqjFMmb/UrbkkPVHCk+Qq5mreUXjbqmfPvaZjAJ76+ih7cfh0V0ubbPpMN3dxY1WU6Mer9rE3R8+w7l/8nNSw/N9rI612lQqJiloaM1n3467cx1EMfGqRnnswANOZibJ/TMIAHHlNZ2vxwNd5rpDOpOGfAN+ERfFRLyPu4YG/Wu8Jc+zT8bMT8idfTpxr+z4xxJ3qh015WdLJbiLE8OfSlY7Lc8eBO9o1+25vCu3Q52NHNnUZoavvOchxAXffZvPEYsI1KANFQkSFMqVdEfeegya7UKG8aHEw60WGJ8gERJNuoISUU01i/PbIwMkuO3nA+a3XKrUkz2t+mMsAxMNT+opPEgbgnvU2t0EX7mUi4uOpZAcsTlWyTEGM7p3v/coZw6vvPdjd19Q/l1rd2/q5XeRxzWvlMQC1gPoYKUR0/Msj3ALGPRB6QhX/Sc8LNHjyfNvz0W9s5d1dbOnK1a6MFk38xXRf7zgP4KUf/mAPfj3ZefbeGzvTVv3zr91/yE522Uc/GhILLE4YhYTBUxmAChtqLMlqbiKFcvMXE5yKfWGav2gXpB+F/PXewMHD2/TtRXvZ7vkIjsso4brDLm6b2LXnN44L3xvrEm3AGO4SSUl4nFj4G9eoZD/MWlxgA5D54uIPxiW+a40lbrHlN6Rg0B2kfnBUxzOOmyuvFuem6x3xveRlNyrt3iM2YZRcpO3fcAt77aQWiRrBcfhtc2sfm7Zgmat8g/eUuak0H52ZKasaCsrHP/7hNpc0+qfWbMcnh9jfd3Zxf2OjpqbEJwlyH/PScHv7+5nu+xONgyzLVCLvbs7691/nVVM4Uh461deOm6+i98jzQVz7mwv3dN81guwYnye0oB5BTtMz9EP16WyedR78STbgH4/7w+Gkd14VWZrXqmy9z97Dtrzpi0SJsVTvsuYyvTdxBlaqZKFk7yTXTEa58ccD7k9/O9XOeWeM8QyJWuC9w3CFFzn5un0TDpl0DcDT3xhtz383LWEAKuqmCln5fdtxv2uzzndGtvZ1n/3k3tG4MD/vIJvAx47M0dMVRngxKdCABBMJL3hXWb/c+3ffwSEEXJAHk4VzEgbgwMs6umSBPC/ofTkGQbpNIQnfiOnee4Lb+bIrUSgOrkWfn+e6bn2Dj5cFr825beqlvKSMHA7Ck4cYrG+YQP5ncV56ZxdjR9Joy0rWrWNO1QqucViTrZwHgN0aL6omUn/XiMv75zl/JUIvepHRj6PcFU0ZgXg+SDrQy5xs8Hf2m+g4HnGaTxWv/dR5FsDu0OeG2cVtG+QJM6tPjQPhUAxgeQDb1NvchSOb3jPALcAiRCvUzse3a50ct7zfSBJp99hgF7rToiQjguMIV+/64MCEbtqIaQvcf/tNHjbfAIxOjhyvhBQ4Llyv+o1olVsew7v3T7PdfadKIIgzAAmlPv/dVCcO/NG4PxwPDXoAkxW1Tbu+90NCHJrzoQW8dfLaGYvRRSAZr/PRQZPt5t4TCl32iXrVLw2fnrYx4uMOib3944NdyF/fHJ6Rg58d5mQlwCKu4SXsM2Gu9eg30SUM0ZRIIAMp1UZEXkvOU0k9yVnwHrJIFNQDeG//SS4MFpWYSbXY4j2B6xsV9KVkYf9f8pYY89/fZN4Rkh/2fmxwQmNQBkay7xoeE8ZwKsxUoYcEiPu/+tXRJvAUsRHVvEAyVL+Jc533iA0s3hbmiv2f+tZ57zcps5ENu6RtYhh3ffmLXdNrvD10WGO7qG0DkxA342AzzvdVBZmNFJqY/vOW91gGkTx2aO/Bizuk8VYptUR3rlnZeXfg1cHXgxctTHyu8flt6iWyV7e4sbfrO9XcWeHqXnZpuwZGmUC8rdBaPhy3xgD0N//a9KXDxVMJUNEV4gzAVHqRqd5JvGVEl6INqaxmW1dxxr88kBzDM2RzgSeYbxcpJGg70BWETdz4okmU2lDKA6joDOe+cVILO7Z55uLRopXAsYQjyTsHv36bzTdZ6/4OeXaYM/xfPSknMqAxN6i2iSvjx7sBt7zTDlu6ZBvd23/NA0hsY1KyCaUY/54wAB85rpXbffgNEqxP8k81LjxJhCvgXPk7azwzpayUPTxosnXv1NBGTl/o6s6i/E574NDGzmvw14pVrpbrc8fuYqe1ytGgStb8D0EGoEpIcQ7F2eHDUJPxzDe/t62rlEuk9HMuXjyMLbIInzuumbHoYCg0qVkpUecTIwxDQhOYrkkIgh0WjR3nyMvamSpp8De/sDgJGIQ32V3TqE98W9+JsTpp7IxUvYJr+YsZ/y0DTuMos1EpV4ZI4W52qhjaZOJNmrc0wbNIFXZmTCSmwD/C26DJRHqF/P7wYU2c11ITobx4/rORh+C4l0e4RcvfrfqLogxAjFMMcMLMNMLXkrUh9JGOBEg0BEyt0A9+mGW7b7OZffbTbGdgIlWD/mTPI5pa1/fG5plI0zUAk+mOkXV88xc/218eD7Eg360SZ/CKQifwGyUKMejuOmgnV88Zz4cMAIXpkUL5feEyh7lEv+nDF1JGtoXMdwnoyuhkV46xT1PITiLPqYwZeRk4TyWptAGDR0s1kCg/MBU2D3w1ydECGE+PvhPdt3jT/g3zZO+mWmxZwPGkRK/Z8YkhzqDy7wU+HX/n+xdNIjo2ec2hROBxUzJE3D3gkONdo/kGJV4TKCL69sW3JFP54YGTbSayTN37uA0W3izCaq0JW/72p/uNTGjmSDYgGPRq/r0oG1tzoPT0mH8xvtCLgwMIJzNObQEPFPJcGB2cQ+ierN9TmeOOa2ZKMqGyEjqpJNyd3mobFwb3NfJY9LkH5sNXTmjhtE4xwNigMC89fHgTa9egmhMwpvmh+mT8aV9dgOgIIferPv7ROjbcwj1TvnVh4c9XSvySvlyq905rhubsOAMrLnmB59G2m90CLQAAIABJREFUflWnMEBjHD5NgL+xdjarlVebUZ5essbfHTvTBpzXJrGZpmzp17/Os9/+/DshX0XUBg4mjecjj5l/T3/e1tk28wT+VTNZBqCcLtwb9eBv3D/zmtWaa5gLh09b6DisSIR1fnpogv9N/6zdb4yaYaxNn5y5u/Msa8x1N6/gzml09wBniDJvyeHEd/bXksVWpYrD6z8hA3MbdkpBFowsn5MwAK3c2ta8SPRxi1N0HLwAkIDJQPXrzp72xmg3CbAI4TFD8V08CfpAbwnyvlp+FQA4zv9QlQX89aQcTxaNSfb9sTNdeI4sS3botx+4o+HVI7SJXhWhlW2rbep2KuzA7/zyFxdOGnPFPq4PeSmjBiCT1+ODf3PH7LJ1ZZcNuPGVn7gJwJ+kxVH0JRrEnULLil0v4yDzmgaBHg4Ihd0rdvvMSZhc5ZW5kjBudJIidAARnXA2ma8yDEdc2tZa1N4swW/8umubtdLwuS7JJxilJHT8fuN+1u3T8XbJ3g2c4U9T/zIA/fC97peJoUujGnbUS8NdLdhkBiAE4U5PDXUhDrwZu9z3leuC8DXvhRoSDIc23ioRwsR7gLeTGrMIRsd5AE9+bZQNnDzPZSLKuyxvCwkFVKKh4a2E6pBMsyyKL9/Aaa3qrJVRi2e7e5+fnddUi3yybxOjY9faVdYy8DheRvPzxzazU1vVydOFX9UlWuNZBhdhdt4b+Jp4ofGE0TB6z98zx5POPUk0WcYNf2dSZsGhyfMuj7Efoozel3g+zw2bale13859a3p+yOuwCcjEAGR8cDdfPqGF3fT5BLfAwJW73SuvlswAZBPHvZHxqD403ug3zN/ZhByF+sDi5Un17VQaEu/JO2Nmukx6QqtxDUHyJctzvP8kT+D9uHyfBm7h82slV73+c2eI4f2CN/j95e3c+w/fjnZX/19cCFXee1QJkJaKNt8A5Fu9o98viao8ioxgiLIpIMFBHkC87ppr1Ocz3/5mZ709xv0nczYhaugDqpKjzaPma0T34b7C2Zt7S6dEyFvPhvmd946yn3ov6ZvkFt5F8cv9BCFkWHgWNN2bjCl4rMw7YInHCToHiSpf/Dwnz/EqiccfNV8xD664e42UGV6sV0b8bhe2XVO6UJvZk3etbS8e3zyWY6dNvv8cuF9tvPg748TjKUoLf4tSMPykNzYV3ONA5uRI1I1ztSYyZ1Ojnrb0zgNtk2s+Xet9YM4m4UVN3nkZaBOv7eAkjypc86lFK/fEvc/MKxh8+zbMqUqClBLOGeZtNntDp/7pPNj3HbKTXf7Rjy7RsnrFcg473hsSGd29XbBnHjz5Rt87dTdXlpSogd47rsG7VGb1sg3KAHzOzJLFMXEHoVaaf92X2Ckn3z/eYWYQRlDahF3LKnsVPO+YM1MagFjqiJamU6eQF0B8EyabTctu7IjIJ7460vbdfgu3q9+5ZqU8Cz3jgYBL5Qa1/NzUCEh3eWbNjliCncp2pR92sBCYyUiDYA0nbPU/Zl/+khN2hic2xiWcVHS6f0iIMClXLrexO4fmh1P4b01ykILRbaM1rVnJGYxRo4GJTDw6CZfiNWHXBx9HuPrl1DQRyusKh+ac1vVMoRNI8RhmGJt+04cYfbZ9ztnD7ZbFO+x3buvYkDL6ZCz6LOAItMJHgfS9+0ODXJcKr0niQYujfz3C0HirqJRAS2YAYigc8cJwV8VDiybHK2wYvQctCDLuuQd4mghRRz2AGFJMXvBPtHASyoKrdvdBjZzAqt/SNQA5J84IVCZsVGJG10CTEm84Gxq4cXC/dquz2VrEeMl0CDd/jPKOENZik4QBIUzAm8VBhj/nkRSBd52m7Hi9u9KOFGeQv2M8MWHTVFFHz0jcId5tP1OfjQ08H7JS4fYyJrz6aiymhLQzNQDxrOONF4+NZ0dfquGdzABEl2/h36tcKDvq1e381LdujH5EAmPujDe/d95yvCMYbGTLw7+C60dYS3MMGeBN783ZpCRr8nT5v2uTwXO7tF1OIot4wvJWykODwUw280MDJztDFiOMLFC8cni6kn0TeMO4N+YxJW1ok8B/l924lHtn8LRzbzS8+b4BJGOb3/AksfDjoZEeqrjRGgPvCGP6KtcwlfdJz4b3m/eOkLUMT52Ll4oIB81PHpKElv/+SzqMcHLH7bdwoUI4zRd/8IPbXKjpW/CjEs8cs4tTdPD749/3fzXJGSy+Af3VpLm2z2NDEuOJ8wASUfj24pywO7+TFEakShEX/s46csN+De34V0YmxhblTYqT6T9PNs5SyIh7v+DKIRtGg/ONKHe08a5sv0WONBGFBkj8IEsdbi46uySUVCy7kfPsiiqgPqDbkAQGJ16VafxIlO5Zx4MtUQbmeaRz4FyrqAHYHN50K4MuAb87ui5iMFO+jso1RP1IdnH9lzKbeE0H26Ls6g3KAGSbcSPJrjEPFgPwcjPLjGAX94bE/+12M3sHBQszw633OO8oEcuYw9PyALJTaVOvaoK0TD8HPj3Uac+RgCFvFyGPZav+cRmFELnJloXgjw4fHhheAioF+M3n1PF3QpontahtT337m21SdiNXexfNQLT7IJ1GP1ImT3YbhKAxLmgQhclWHXV5Oxv625/W5ZmhzkuiRrYdRgI7VlzVcLnQ9GLs1BZlh8Y5JK4wYfj8Fd8AZMfOpKeQsPrnHJVg06Trj1thW0KUcJ3IkD7yheHuY9QO9hE07PaqnydbljDe6Bl5RdIlK+FjyqT/4nHNHKn/tZG/O92xOI0sjJR7B0xyiwiJLTIm/Z2pxioDUAaCfz1+E5eMvyczAMGYjOVo4xmiHxdtWrhv7/uzXf/ZBOcVIoOQ0FnUADzihe9c2IuQHBw0GqEWuKcsSki2+F7aTAxA+vINKv5b+n1xnhV+V7Y0XiRI6f674d/nYc8Nc3wm4eb/VrnbZ24y95s8wdLL839Txid/uwJJkYP57HMWLhWp9zN//UQGvObnta5r/3t9lAvz4FnA84PnQNng0u6kT7yqGCCjZyx0uKsRynp5xBoDkHEuWbHKbWaSNX0bLIhsQODFkR3J/7OA6R58jHQOiRODp8x33zffIhgsW7Xa2AARtiQcjaFHdixebuYojv91PjSJ9i6jHZoGEQGoE4SFmbte+G6aC2mhz5eqwW1Cn1ANo3q76pvY17/Oz5PIIp6wDGQwPerFEU56apvNKri5cvnqf9zGiHu+/KNxDt9oi0Yk3LvYtr6jvfjvWdyYoxmtzHuEnmlknFKGDKNB8icSV1dfbFjZRHNvNOYU+IXoudLgUGO4471k7hYvOjoWDAW8QTQZrf6zlTIBBsPBjWs4zxrG5gXvjXUST2ryUvtRCVFW/P4Q4GfdgcqCJw2PIwYZcw4SJaoAFWcAQk/hnqb8udTNQRjXeGt9GSyeOVELn0IVnW99mTKN3zeE4p4X3GVkzGQk7XBX/zxzGOfomGiSiLjhUAzgmmKUSzHDYeOFZ/3NmgxAYetjwngJm7+Wy4GnHzzZJNixKeddnrVouc3/e6UzDH1nBRtQZKEIn7ORuPHzCe6WmYM+PXN3a1il9AZlAHJv55OQmmTyOM3Mnk85s2TvR8S42JpQHWTNVj2nf2cAVr/6XZu7cu26h6qkwIHKMkXWBWOMyUbF2FVeSUNmV8ILR01ajD48KKe8MdpNvgo5cSyGVsftq+eZ6KLhQGRiyBxViCruIyX0zA6Mah40XkSyhNm5qToIf5eEwwnNazmvIB93n3NbG8K2qOoTfqGsE+GKGz6bkMg0q3db3zzj1n2y8yPUwiToNwwXQqEsQKqW4I9bRGUWaXbb6DVpMUaKhklW3gMRcJO9DuIU+b/Xq1rBKpTZyCUHaKcarc8qFXzOU6gUjghZ3HjalKWNJxKJHPhZjJUMxvyaElR0HB4RPC4sMEyecY3wHSEav4mjxWJI2IEmqQyeJTUk8TKXL7OR89iuWv2v9fW8Jnh63/p+huOTEeKXJ4R+uBfwl4dJ1417v/iNd4UsOHh6XKtM6dLu/cBQYnKj+aHgH2Yuct4jZfSp/yi3ThsNfteky4aDTFMWPv6/IM2f1LknPDJMtHxLar5XBvzBR6FOwlqzlyx3XkbJNojrxfmE+npPmO14sn7Du8Mi3aJ2FZfAoEQf3TfE9y0rlkvwlvzNlbyZolkwPhZ+h+3lH7v/jxpAJJtQ+eXffy1Bf+C8+w7eyXnc2cTJ6OJ8PHZbbFrWfc8yrn0vmR+R8M9L9gx4H5kH9V2wGcK45N3Dowd/k6Ysf7yUYCxvO7y/7bfY1G1Uoc/QwBsPCUlo0RZnAMIXJkOWRRUjl4SUuIYXWuPhd2gM8FhpvrdJlXn83zmGuQxeIuF2d0+5G35di2fue4OTYQb1AEmQTcttbP6GJMrpYzOxcNlK947haaekKBs6NegyzNnfTJnvvHs0VCFItNO7IkNHm2f4kiQxCGeiSfIcx337hKDjngMJL2ycaWw6rmy/bcKo4W9R7rAiQj4mogMkw4k1D3UKIlN4jMkMxknhN/FGo32ICwltZq/cbx4j1YUft6rsah1rw8C78/nZOfq3MgD5tyTP1Dfrw4jpCxxVASkjGv2zNhDBwtnDnIEXEEcK0kxqfHdsGvGSKhOe38D30cOb2u41y21wBmCy51rcfyf8S/3fNaqqa0bgDMAmt/WyH+bn8Fj8Jjev/gYfwmUBddjOLagiyEY5cHDjvs/1VEn/Bz4KxGvp5dEnCyeaQXjAok2hFYULJdybbIH2eQV4JmlUxmACQHsI749C1JqEpZ1HOA+yPdwWRInJHJRXiwy4A72Qc3SckoXw/84uEzI9H++hjWs4vp/PcdMHwASAseqHAViMCIl23mFLxwGMGtfR68vL5f/dD6kKR8l1kDHHTpaQG0Y6jdAAXg8J0fr3rF0qySV/LGHnvNp52ZKsMbHvNgkGkNpTNTLECNfiUcJwpUnLzk860MQLTmfvUddV0UCGpum9A+z6jg0d1UCNjEGeK0bCM0NzwtPRFjXIkr1fMpbg1MCTUoiLa7PxKLtRKfe+qYlgrhC6/s75eDLw7kQ9n7w3eILivKQpwYv5EQOXzQEhLhoGM5xXLVr8zTd8+Cbw5Ck5Sx4EjnuL57fL1oawMslCGBl4qr+YMMdx5Pzme/TxJGGA0cBZlSbYgDnP1+YVrEWtzRLJARzHYooRxvxCQ8uTGrnJDEA8X3BY1fDqY8Bg3JHU0Gv87MS3zDF4phpW39R525V96p/LHMH3n26Tpp3/3uAJYwwshhLD1hzJYsuzxxtDPWU2kSzIhOKFfapr45EHP+Y0Gt83G3LmXJII+v48dy2vsfrjO+B6POe7D94pjwHoX5NNOJWSSKCK2/AhDwXvGM8uhreaOODpYEfY8cPTW5l4rpyDYQE+GJJ4vvzG5uist793nlw1+GfnvzfWzRcYgjT/feCdUwKDv9nR+VrHFPJO9u3H3Q/UAzzlNDx0l7RdQw3ib/pmdO6E2Utsx7tyMnrVqIEuvnLcNTBWSf7i28V7e8eXvzgKUToNbjzzvOqhcw7yO49+M8X1h+EmnjcGOcYdUTTmyahDQ9djA8D6j2FO4iCNjGXO3+nuAc4ewOuLt9R/LziOZKTam+VEAH0ePSH2y9pta50bVNwgDMCtoYbhHU/nIRXDMR3N7H0cHrl1gKOXdAbg0U99ZW//FHUO2loLlE7Wy89EB1EV92+yJr7Htj36uQnZ351iUGIQ+l5B9cNLRfIGYRleHoiuhEaSfaQ+0Z/xUTQb7x5N5e1kTGoSJmREViUeJsZB2Ie/YZD6/KhMnxOk1tv6/uwmdHaP/kfLAkT4EZ4UO6z221ZzhqIaE2OV8mVcGI3dLDp8Ik/HhYAxMBVCVAKIJhYM4eHTF7qPUlmekuph0vt8whz3m/gi+jDhLSqcroWK58HYmWx9Dp/PQUuGkyqzpMIREjrGNE2ZY+xiWUiRcBF/0+9D3kAWRULZkJzJTFNjsZu64O88fMPoGDA8WXzBmZbuIiCPbTTDGKkKjOUR0xe6pKSogZIKA8LJTe75KsHLy/S984/Hk0x2o7ziYAv/zOfb+sfz3rEBUlZw9NrwVm/tO9FqVCznngVJK9TZ9cNBnKMkEP6NR4BvgM0Xi/GVH//onpMa7+erJ7Zw0hBqeBOOb751IjFMHCffAPQzLuXp0Pm8L2ye+IYXLV/pQsBKYsDgZA7iG+eZ471XY6OKMUV1CIljM4/AQZMxGvc8FFb13xsMNIwYaCBggPEho56aqHjCWUxRRsAbitFKNISoQTpNNBHeF7J4x8xc7HTvmMPIjlVShfrie21bv5rji8LhkyyMsoiTXdOnFPjHkGBAqD46b5NsIOx0fLJQMJgwfhwDRIrya7w/Z7/9vcv2ViPScNJrIx1vkggDzafooDbA3+GdRRtrCmPgdxmj6X77cWPlOYsbSb9QePCGEu7es15VF35O9u0lu3coLzxf0ZegcUQ3LcnOJbrBtwZHnqRFNmZsltV8j29+2Ot3omMYgDgwtKHH0GWtxMvIO8w75vO74/r2oz1sBA9vUtOOa7z5BmEAvkqUiuIGZiaxtKvNjBU+uZWU7hPI7DhSoF6GCoVHOsmpzgBsdfCJNuz3HK+L1WtuVm+Nun/0PIwbhXV8HkSyobHLuqNLo0SNWt/rgYBqn4lz1tot0BfGzCm71nE7EgwfODrIuiT7SH1vJQs/2aIq9yYDUJOR3OZK4oBcXKZ0KafbdN67Y5y8iu8d0b1JYDp6r+xiFBbhNyamtj2/caTr098cnYd/iCFFWBYOIuMgqcHfZWOErVj1rwtr0SDgQ8ymRRNm+Js/8ShkJS+mvxhL1NnP/NPxCrPrvsQr4b+VkcZHziIDv87/gJW9etAzQ523Ja75YZe436OaWUiBkJTjL9D+eQpNoOfIgkcIm3HB01PoWsdHyejR6zP5E2Lys9nS+cwU/vLfE/Fw8GSQtIMx6j+D/PpF/qPlAwNjDUA/LK9+osk0fv9srs5tXc8t1DS8tnBKMZ7iFiI2RRhreOnVMNDE92IxeuG76dZh+2ouVM87ggfQD8lxnsLu/Jvve9CU+W6TATaIIe/doJoLEeNthobBd+onO+CV36/hFo6KQMPYwJiWZ5d+/Coy4tJpzLwb1EFmjP/av86bh4eGBY9kkRNeHem+u1/m/ZUQcuZcDMdRvy9MRCjo551TdnXUEHhxyZrCqv68BGcMI5MkoFSN70nGTyovtd8H8yLVkvDCEhZFWoTnRvkt6DYvjZi2lkHFxpnQHd6zf/791wb+Ot/x2thg4xHKtJHggE6hKnjofAxt3i88z1J2wNC9L5e+oeMwGsjaJ+Gty7PD8nAok42F5+4nTHEcOnnQEuCcSZQbI4XNM0kNXdvUc5n6cVxEbcz4hpCogQuenwHoq1fEjVObYTYT7ber7ow3aACUF0Xeym+qCJMKezx27/8wy20QmKOScaXj+lCyEe8xXlD+nyxqNZ//m+7zJ0qAkQt/k28CYxR6F3MgaxjJH9ENJM6OaJRAkRmbMtKqzx1nc5essLN329qeepJ0hfVbBuZaMyPWhfHnb2sOJbphZq+kC3YhjzvRzB41s6Mpx5eiL2cAdv9opN00YA23Qgsr5yllXX3wIaIQj5SCsrr4zSd2+tcT8VQCxQojc4y/WMSNUUK+8nKJgJsfNkyszWtVSRCNpdOncC0GIpMXHyoLNSFY+t6z/uYps7KYuER49scQTcSAr4EhsvSOA53kiEKanOOHDvjv6CKOwcVkRjg02iClw3WBo0h4huZ7BRnHzZ0auiw4JnsR8jlOyQMQu+Fv8Ozg4Tz6zWSHAbU01QgpscBQYumsPeq6nSQTRtUKZZym11aVyjsJCz+bT0kvcc+GiQNPTDShwX+nouf53Dh+k9iuDNmaN3/h/obHAU8XCyk6k1FZBenSJXtnFBZBc4vwcpzWls5NxgfS76jjV+qWg6OyBfEEQYxWtm10HHrH+TvK/3s+8k3ssVGSN2NlPNHJVf3zDSAmrmw7/s7iiBdB/B1/LCRCRGVH8MpSShEjm5DSbX0musWdyZ5vAQ+g75GhP9Er+DcJGvCz8ExJ4kRUDYwSwvbRUBEGOZV7MPhY8M7YfZvEu06f4OBX5vA5TvwO9/HQJjVc4hNSQ+jq0fgmMRzhfLHp4n1lo6cmfU9tDuUVist693GTXI1vPDCXtKxTJXau8N8hP5NUHptk76n+LsqHZH3I4oeXzbflBJYHT8kz33AeNAW+52s/He/4ZKKjiBKT7JoYlC8c18xeHD7Ncaq1wYPXeuH7YxMhUJ2PAcT7RVicrHtlnd43YJJd8fEa44NnSJk+5g/ErIny5Nc4Z5d7v8pDYeCbheIAT3bf7aq7JBRtFOC7IZHDHIGO4aGeEQ+3/dw2dR3HlneBkCic6WQeWL5RjL8TWtSyz8bPdsoYNM0dGrv4h2xiSDDZqJTZtIXLbMQlbRObeB2LtBpyNr6iBb8pLM2/MZTG/7HY1XvH6RIXxk6Gm9ZWnBxNt6psu9fdzNF8aHwzx78ywnlOacgGSZQ51XOAsoXRB/d6o1Kl7OiXhrvyqXgWUZyA8hDF0F+zmWN4p6ChKBlU5Tq/PrOZ7b2T0/9dr3UAzzAzCCQfMldFwLzBzG7N70XPwu8XYI/lZhmvYXzHd+wMwFs/HmU39F/DrRDPiVOibmdxppBTIOVcDb5WlOPAb3DIkC9pcf9Xzn2MgcOunF0r5GV2SXENb90DhzR2HgwmFN99nR9GyGGwA3vjfy3dob5QM/8tXhzeOAwhQiJk5LJgoWGVrEm6Ifq7nyzDbyRO3Nz7Z5t58/7W6sGBeTiOUW8hYRY8atIWZNL8Ze7S2PvFQIDATKkmEkdovhdBVSvIcIM7yEIt7pvEla/tNd7dM6RlyqKpRXe/eHfBR5mITD54kfBE4f3CKynBWPrwS2zF4SfRYV8/i+NUsSR6jvTx9HftvvX++SXbCGevWP2ve7ckX8N5JBiRvY6uXLLGPRD6Z6ODdhc6VTRfxwzv4BY3feGy3XxjPtqnQmbg89yxzZy3CQMfPinvflzzQ5h8QyyMyoiW0ct5cQYgnoFoBrqugecTjT6fEwlOu2xdJeFd88cTRybnmqrvLENVfFEMXBJuot5EnzjO7h/PrG/84rXCA4jRTmYs2pV+4z3BUOU9Z3GB+gFdgqZ61XMpTJ+bWY1xQyavFkfmCkLI+j7UN0YLWmxsEOgXPpL65RgShciIlUdYmbDKMIVugAc+usFg09W98w4uaxkeGlmObHqb1qycR8BZ4/D5uRJp5jclYPlY+PQC/R2PO/wrQskYBs8OnZqQPcEoVyKI3w+JSr/9udSF7TB2lNQQTeKIvp9kOE/qtm/izxIQx3MHHw8OnKRrdBCbawxRaC2qEoPcCN5wDADWAkoHSh8WZQBfQSAxH5UiU3UNT5V3cZNreuV5X/BEiuOKwdO63uaJDY9ElJnTHzqsSR5NRJWuJCEJjxbZ7am4eMhIXZmr1+iXb/MTThi3uM6EffHYsalg/vXHqfuLS+bhN/Gw/WeBUHKZqz6JjZT5x1HOsdVDOfMX3ncMTDbuYMNm6J4Bk5zxh4QTDf3Ebyb/6aSB8vN+yhHky+LwPvC9QiVg7sLgVuRK4/I9nUQNyHiHe853D+cZw3u3B7+2C3arYafutSOnrdcGYCfE8UnoMzOUdPH7IiQFU/pOMyP7t6gbMyqaJ9JmIPEHY5QCk1GD0BmAn46abAe+nFMpgYZr/aBnhlm3fbd3MX3tePhNL67K6Ogcv3C1f4PSENv9oYGO+8LH0LpuVbfjIGzLAuLvxHUuPComZYRteYnwiPkJJP415NHT31h0j2ha04l70qIGIC8zoFTbtGyCL4PEwSm71Unw7aIPCYkUwkQos8s40O5GWb0iQROShJD93SV7m+qRqjSSMuW06yKES/gNQjgNDxf8JWW9+uMQ9r6xxSJSqfzGbpcbLfVGeTRCqTSyDs9uXdcQCsWo90V2+T06AcCXwstEEgVNiR9I/JAtSu1VX9A1juTsj13CtywCGNJkiKWqURrl+/gVL+hXRc/5Nws698Tu2a9nzSKOYYM3SO81JZZ82Q4/RKGwCccSjiUDlsVJzwqjGG4P0hGpGu/H3QftlAgBKkyPB5pnTfawmk8rYGHFABVP1jcQePZ+ySueDf0m2xgR9nT0i9xsPRb7nbaq5BYDFibI935GYTSDU+XAkNdhV6+FSV5wQqp9J85xWmB+Y/GTFwAPDwYgPCuFyv2kG78MGH0QLoe+QMjuwYGTrU3dzZ0xLM8kfSy7q0uexCh5XeVNwwN4VYdtEyW0NDYMgtKlSrm61yyOn5zZyqiaoBC29OOUxMIxvc/ZI1G+UDqFqApQVUbnST+R6+CtgQyP4QaVg+QUyV3o/glPy5Pmc+ziFn7qUPueK66B155KG5Iu8aWVyDxFbst/vzmH0nJ8s9vc2jcPBzu/ZC7m4F88A5AsXDbsUDYwJtHdFGdaOGOYXrfv9m7cLPjUAlYFINGBOJZ60iz+H42blch+jn5TfA94mJnDeG/YvE6YsyTxfkmiivOgszBH6H1n00ZWPvcI9kQ4xFH0K8DAiWYjEMcx1njkxNB/63786/Mb1Uow/E96daTb5MBLR36KjHRf+Jg5afBFe7nuovOuFBmi875fM1m/aU3Rf/u1g/3z8Yby/j47dJrdeVCj2KkrOg4pZuhgEjx43r6UkKqOcAyY4vRAI9f3VPoGoCsFt1kFZ4zTpHrAJnP7yqXslkMd9Wy9NgBfMrNHqFEOPcvM2ptZY4S8zewcZHtSrhzF/6MzABcuXGhDZixzuzR4axfsVS8haSFPH7sLjMEmNTnFjHqZiEuq8QL4Suj83Rd1lscGLwuTBKE2PFlvjJ6xFmkZ71+LWlVcuImQK5Ms9XeTeV+YHPy6iix+LARPH4MCztoGIH+LJnn4FUWoKEEGld9IjGDRxduAhw+jFTWmAAAgAElEQVQy/MjfFzquC0YBGlAYgnjyMBSYeD44vZVJjFYLp0JA8ujAkeGjYOLGK0JJNBaNKPFcoU/GFC1NJY2+6OtDGT4t0Hiauu4FnsNdiO3yfXIEatWiEwBGTNsG1Vz4j8aHjDFEVhnZwLVv6ZunpFP0fVC/LHJ4qvqf38bxQzBqMLxr3NTbiRZHs3B1ni/9wt8UOtfxvkYZxgvPhjAaXBup4EMdwAOokk3owUEI93kqfojYz1rF6GvzyCDHP9OzwsBHKFzvMgtK7c0quHCi3/BAI0t02Ufj3OYGLwRGH5m1JCHIK4eXbsr1HZ30Ag2ZGcZH2T8MQd+7whj8mrSEdqBq8P6h24gUjryXfFcIC+PdhKeHBw4DCUkNxoUXRsLEeE3x5JAswwRPk/eLfysUj2H08Y+z7O2Td3V1StE5g7sXzRL1k5J4nynLR7b25e22dddgIVHTOyAKhcSnES9/e8wMx3Xr+/OcRIiQjd3iHgcm5h6MabIQmUuEFQYuRrV4yroWm9pyG5V2cxYUB7JcVQOcY7gfqh2Ii4ch+uV5bRLl9fzyZTKEOA8vEFqoNEl98JxPalnb3h0zw2n90cS58mkZCE1T9xh6RDSKwDnRMnAqu4dA82FNt7JaVSo475VoKczBJG9FBaSVSa1oRH6GnzDDu0M0SE2VjNB46/jkEGdoEkKFU6jGZoz7pwydcBg1faHbmPnC2BhzvI9EgwhPxzVl8UJzgL9KQ/ZJSYc+v5DNG1nukniJlvljfhPNwRcGx4B++tvfElzXuHFIk1W/6X5Up1l/V31cyo/iCSO5jmothHL978Sf86LzblR5g745HuWBKL8uysFPJhbt6//FAo1o8ec/uc2a3h08/mwwCfOSNc6cwG9oMx61C7muZq+P/N1FOWhgyrrFpoc1jnOQM6JAgygneF7xvJe/OqeiiXDg2lNmzrOXT3dG8XptAHYzsx4RkKnIfgw2E990sgewjv6eMACHzlzuXLNyy2o8qsIQV/GAguM1u3/hFjnc1BJ+1A7A10KSJwxP0M5bV3Y7H8I1eBEmzV2aR++M0AMGILs6+Hm44AlF6uWMTpZx7nTCNY8eQUJ2vAEoj4d2NqqnyfFwak7JLaklHJiM2e2idyRjjBR9Xnpp5bFTfH7YNFu+arXjRHB9VRRhcWMhxqjAk8mYKb5OFiDnEOpmQtnP6Xn9lKc8nv+x8O/pC/52mZO6Bzyg465ir5G3XfPJ+ITuHrvRi/du4OqgkqV4+u556y1HJyK8VXCppAvnT1oSNZWXiKv6uoL+KDDiCcFEm1/mLO7d9zXI8C6/N2amI3TP7o6T3Uzq/2wWMMZZ1Jk8G97ZP1HJBD4au22Rn0lgAn9f1wu+juQ3fG0vdqdPD/3NCWkj7wI+MrT3fXyI8xggssqkSYaf3zDsoBTgLYHfhCEGfxOPhCoScLwWRGGvTYJ0FH2+GPjDyax2Q47AAOPG+CAkiacEjh3SIBi06P3xbzLM2Wyxa8cjw1gxjs5rUy9RehCeH2EgQnryHIn/xnVUT5eFnYX6tZOau7Abxirfoy/BwvEydvm3Fij4fr7hJ6zgceLhUyhNtXcJpzIWdAbxKPCNkBAkXUAWwsZ3D7Dld1PwKK8XBWF1sMerwOZSnjcwxVOOsc299DuvtT015Df33WFMs7FBt1ELMIbN1133NEU6+PsDh+a8x5d88IMzsGl+eS2FpmWofTxuVoJTrCotvm6nvimeK3Moc4saG1iyfakio4YXkxC+3z76YZZ7tnh5ehzYyEntYMjvmktl4Fh5Wvhmun32k02c81damebRjaXmE0LKuz74tVvko9xRNgBsfHmn8ZAh5K/oAMbDiS1ru+FTfYnvkOSUaDIJIt4kB2GAxjX6jmYcw8d78LAm7n3FYxxdrzgH/uQLuVEh9esbMbEXy6X0+ELmMgB5r/3kDhmdirzwvK76eLxTT9BGmmukMgDj6E4cv8dDA/MkGtJPVIScNUb1lv17iRqwye6zz4Q5eaTBLmrbIGHkQe3g2+b/Kcig5mfnU+6VSBZzE40CDWjsiq8u2yIq6UTd5+VL/7Kqm2/Gaeu1AXg2dCgzW6NFYS7ayBYRI5AawCWpJQzA0XNWOtkKf3fEQKnyQfHyK9rn9RjpJiRwKi8Jux1Ct3gj+p6zR6KmoOpyshNvuEVFN0Hw0ZJ5h2dAhFT6xdCC0MsLh1EK74iUeoVdotm4cQag76rWGH3gMRjwTijhhUQIecXEWeF4aRriISCdnzq92tlCYGbHCb+O7LzDm9Z04UE8Qlpo5UHR4tborv5uIfUnAYVxVD5IhqU/Xv94GQLKCoZX9M2FOSEFv/mGpBaqlg987aRJGKvf4jggvqabf/2Ff690IVy4Wk8eneNl9Yn5fr9R8Vn9tsOdX7oFIJkH8IGvJiUMt7hC9hjZ7CTxyuFJJFkAPJDM4R3b4c7+jmSOASiZHbx6JK/4Hgc/icYPe0THBT7yiMioJxTGs6ZahPg/8PZ4F67psL0rjwdPTuF37h3SPiFEmur1Cnv+G6/hnO6d3ETuG6SMh4mSUBb3POD8Ns4wouoC75qq5EjEd7se/WzJitV20V71rVvH7RMZlOKCqvQgxgGJEnDXKOtGky4a/9akzljI8mMRhycLlwgDUNm6eq5+iFN/S8bzVBUIZYlHMScbHG8piw78Parg4DH9cdZi2/3hgc4bSIOmQOUVOMVsXEqXLpXASmMgJEgtXDapeo7KiCdECi8WWgPGIwsWnkAiCFyLkKvKrdEf3it56P3woLKTVf6RTdF+Tw5xhHcloPmamP79qvyZxqs5xv8upYvpf1+aq/xQNL/750VxTSZsHw37RQ1A1R4GL7BizLxvvsdRiWFsUqnkAt1GG1a/OgbZy9BkiOpEPYB+neG1JrXce4uGSmWgH/vSCCf+Hq1lTZ1kvFoHN94qT5dvjZ5hx74cr1Eqio++GZ2I44MNLPxI32jXNeUpRcScSAZzhIxcvPMYqmrReTdOHJrnF02K4/xoVjCJJdKH9G+SRB7oTfk1P7KkwgtsvClogNPg1ZPWVgcpc+UnjlbAGOVRZ/6AXoIKxw2f/eQ2iX6d7qgB6NaPRYs2CBkY7uUs6GW5nD/+Gy0+tnavmdlJ+T2EYv49YQBWrFjJGURddqqR0RBEzJUBiEFFCSpc1oMv3DNRaYHScfSvusK8BLzsyLvgGSPUpsYOHaXytvWrOg8HCyiZXiq1I5FadpsQWkXQ9T8mn28SZwCK/K8dvzxkjEG7fnhOjBmeIh4PJCzYkUv6RN4cZdj6E++C2zpblQplTPIomoSZPLgXJkc1fWTIsbSpX9Xu7DcxoWavY/xJXMaPMk39Bdt/eOyyxX9TqGqnu/vb/Yc0ts474phe08AOT4hfqk8yMVTyaF57jedBgr4+B1DlAKMvD5uBmzvtsNY7pYy+ZAbgk0OmuAok0WLn0Y7YWGBk3dCxofMYE6LnHEJQPGMMQLw82ow0vrt/Ho+DklP8fjHiVt6zppC8nqs4USrfBucGXisLiAjY7PbBhwQMMuYggYt0Tj/PD5uaKC+mhUXvLTxUZDngHzKRSzOO88BJ+nd+9nX0GSLdgsfy0OeGOSK6DBR5JeSFkRFAv9QQVfiY/vxSXfw3u/jnhk11BudLxzd3RjT1okmQUNUFnbds5T/um/FbsgW99i19nGdPWpPRd0G1aDHGeJaEm6gwAAe2/WNDbH5ulZBkExa8YxYnNo9UjaDyhL/4KIECbxFeed4ZPIh4SFUjGG8jc5mSPbgW9cWp1UvzvSuqOhGtAqFrskBTSYb/5j35644cA5bmS9vw3yq/589pvG94xvxGmTNoA/4GVu+rjkvHACREjRfSV3YQ5UH9yJsDltVu7O14hVExY4xwaCx+UzUjzW/8hvFNdAE5nihnkY0a9ZmTtT0fGWRPH72LM8zVVPoQeRlkYJLNK9E+/TB99DclaPnzu3+M75Hn77omG4THB0+xBbcfYNRbvuPLiQmee9zG0u8zmhipjYiSsfxjo6oEWoP1PelYbUiSApr7A+sKG2g8u8xnlBJVXWxxYKN9+LWDtaHCMQC/+/X/tUwYgL5jSZ5/H4sNyQCMYsSbDP9vcK53ML/nUJy/JwzAypVzuH2ZtkrdPnXCj74HkOwv6rXqJaJPceGojYpGExMbIUSI2XP+Wp4INXIs5zerlWNwsDCpPjAafRSilnAxC+ZNnnHhT5b+hB1nACrdXvVvxZHjmuJaYTR8+tNsl5ChyYtrEJpBHuXRQZOdUerz8677dLzj5iDVQlP5rFQTkqQm4H6RyOGHCfU8oucTbqKRDZns4xRPTqWK4H+xmD1xZNOEZ1b9c1++piB/h8OFnEw0hCdDRJOTm/y82pL+O+RzpPy/H//yCBeiS4aLwnPihSV7L2VgQwvACwj3C84TnjIM1DZ1q7qsSXhyezWo5kI24rrRp0+klu5d3JjABx7dr9fta/IywLkhYYeC7XgdT319tPNC4ZXDu11mo9J2/6FQgNc0P+QkkjzZeJDqD9wxJ0GAa3A9X4fP93KnMgBFMJe3Rt5Hea0kCC4+GP1SAYDkCLWoAYgn7uYvJtiutTezF45v5ryrbAqQgRG/kndsUY8DEvQFlTqjzzgPLn9HFxDPP7SQE18daWNz6/5qHC8Pn+aSwOB6UYkEftvvN+3n6pEe/Nwwm3Xz/vlOV0pikXcGbwyGOZEKqvWg1cfihPeT8Hr0fRWvz68F7SsgRMNraNUxf+Ft9L8t943cl1P+nWcLxxZdUzVf3Jq/qXSjP6dBhfA3jhw3ZMp8l/GsiEP0mv519VvUAwhl4cer2lvz+79y3nQ1Qvjjr15DLVFEAUMW3BA9R1EBeo5q8Kr0pf9gtDn0PcFvjPrdfSd+eUadk67x5mOjELiSx9LtQzqPRA+gjCirmLGI2uPP7/59RaMeuib0FfT7Rl/ezhm6fgJIMgMQhwFRFeYsmuSVdHw0KY6s9sY1KtmgyfMSlaq0BqsKiMZKSB1KUkEakm8dn/w2D9/b74cNLXPgY0fubK+NnO4quOBFJ0r0yBFNE/OBf99k/cI7/q8YgAXBPRvndDezM3Pr/eLj7koSWaTjQhuACiXp5YOYjYAqemh4CVpts7m75H5P5HhqyNpTuIqdAjw5ysb5Hgi9GKqnKk6NDC4MM15KFn3KpcVNekrq4Lc4A1AlzsS7UjiO40U0JszVa/wfLrNMxiyTDtlMe29bzeSl0m497qHJE5NqQvpq0lw38YgfCQk+yiuLO1+Lhh+K9ccglzzZcXCKkKtg8seLw/j9xn1JOoC/EzYgNAiPDSJ4lI/D8X69Wc6JCyP7nlX/eng80BZD5iOuQcym3FQ0lBM9Vgt8dCFmLEzqhMeZlPT8CAX5Xk4/E5Msvnv6T7KXTsjJHo/ig+TO5Os6OhFbvAwYp8OnL3BySCSYkBCChxcjFLI/iQnRbOv3x85MVFkhc/uInXNC8ZRZIzGJkNj3V7RzWPrPwzce/HBKdIwky5B9rslYoUSFcuWd8t9LP4GK/vDiv3/abomuCdehJ0i4D+/3Nrf1NRIYSGxR9roMQNUxJgwHj1bSRHHP2PdCxv0ufhsSKZDQCYP90b2TwUs++fVRLhycX5OxHvf9yBvLbwqv+5If9K1SYv5c45dnxPBBRiNVi4a8+G84bNNu3G+td0x/kMda3kIyowm9VvUMS45l84B4eDTMBwVA+nr5eQDhEo+4dO88dXnpO2oAipfr96fQpDKWo5ty3Q/fO1m/aoTtoR3Q2JwR6YHLzDHDL907v8fqfvfnG5KZbum8o8suxouergGocRCtYj6VzA8bOJwQaKpq0xQdlN4ZNmp8u3i8aPf2n+T0L/mGSIIgaUotmQGo9ZNN97PHNjO8nHifed9pPu+U//b78d8v/s33cnWHbe3VEb87Q53Ey93r5qzDmTZlPMvDmup8PIgvD59uxzar5QTHiYDhAUWGyx/vFR+Nc+LgwQDM9Gmkf/yV6FTmSr9Qe+kmMuWpvZybkayeCm0A8pKSFNC6XlX3QbJIkMxAqFSLIheTEaYFnWMVQsQj45Np9WIo/KI6tgrZYFii9xY1LvwJwSdnw7EjrOsr0rOrY9ePDAhFsSVaKmBYnMgmfXP0DFcwPY6ArQWEye+QJnm5Jern8Oe/cwTgVBOS6saqIoYfYko2cejv3DOTFbutaFM/6NexqEMSh3eFwcrz8hv9JBTacycYatYS/lbYPnp81PMYZwCyi/YJ1Om+wto55zeRSy8wytNhLIT3yQImS1ISDc3u+ypRpzo6llTXwvvRsvZmTsNM8gd4QkisgDurxXnxslWOvwd/lRDu9fvxya1p/oJAltyBjXIoF2yQqK/MJDrowr3ctyRNOn/C5++pDEA4q3geJBWk8I82T+JhIQeEN517Vga3qqaIyK9RyxvLeMAZrzObFSQ8RDGQAahzxK2iVCTZ5HGt/u19nYB3Mtzl3WJzhiEPwR+vGWE7OHgYuvk1SXLEXQNPP5V6Pj97D8NwZc4iIkBtUjWF+aJacMxX8LrSMQDZ4BElEb2GTQAE/mhCh//9SK8NPhnHEmlQGNu/Z82d0dqzyNU0uru/87DmZwAizj/ysnZuE+Jn9IrqouuJm+z3Jw+86odHQ9HJno9C1/wuiSi+mY/OaJXfI038TrIeWcToeGL03Lh/Q4szLlJ1qOgL8jqLlq+y1g8PcnIy02/cz14YNs1FD7T+RPuRZ9OnG3EMIW+ed53NK5icGPAp2VjCbY/Oo/q+ef7IERHJYB5AB5HsfhqRJV/APZUBqJC1HAvRSktpA2zmvO1oC0alcNLtI84AhM9LeTu8x2obcgg4XayyedyvJBnmVgOhX96iGWZ2WUSKptAGYPRlxqB6+5Rd17oXXgQy8iCk01iQ+ODrVt0kIWsCsbdM6dIJrSKRh5lcDmhUw14dMd3VNpUWVtS4qH7D54mya1GDLsqxwbjrtOOWiQL10YmLD7Dcxhsl+HhxH5GSNzS+uAd45Avf2XtjUxuAmiTEFYuGDdhdEvqKa0waybxsCnEh3skiDDdzy5t6uyzRqGYg/fiaeEww4o0RavM/VsbB8b4QtP4WHaMyATN9ucmQPu+dsfkuCPLGRcM0jI8EFAxAyhYp+UiC5HHjyc/Y1DkYxoRoyEIl0QO9QGUdalEgnE5ChPipOtdf+BDV7rB9dfcT3hAkYlh8kChh/H6lHN8DiHcxmZdSGeHwEBFa5lnznqsGtBKNbu49wQkf06+8XJJGihqA+u7QniMxAu/+iEvb2sfj/nCbI1rUAJT3Lm7jJCwa3N7PaQQmwx1aAUbWdtWZI/5y9UbhVeF5Z1NFia38mvQi03m2cd8Sourcr7+h5Jry/kTnmfzGk+p33wAE3xa1XVak8wRB3RCH0O9Dv8V5Whve8aWTboreuzLw1Y8MQPh/eLDh0Upn0L/W7X1/dvJYfn+iuEgSJd0Nn887VbnLZFzmVJgpyiGpE/EU03ne9CsDEH3TGQuXO2MHDVS4pprf/Y2aPxZFYHx6QHSsSphLti5iZJJcJcpQsnsV9vrdvz9+26x8GSfzxTNkI4fiANn0cPqQ7alfLS93NN33lDA/nN9kXtD8+vHnmVTHBgMwPyTT/x2jboGZtY5kI6MfAXP5Cq+rrBqAZMyxgOH6zaTpRY2GUiWrgNYXSQtvjvrdiVJLJiO6Q8WTcelH45xQaHQiYtfhZ0jJLS7uWjKumrJRfSK/7k1ejlQcC1LrkbJgUU/WyGBk0pWOlMKfOj5u4tdveDHIBiPzMdo0gRFKhDCMlxDSLkZAnPcBbhkCpjQmmPPeGeMEuMlmQ4LDbyxWUVmFOA+gwveZvA+ZHCvNragXlrGQ7cyOG46e+Ee7PvB1noQjroXxT+YusgfpNLwyJEVgjGiTIpKz3ie0DzHUkN7xm18yz1flhzs2eMp8a1u/mr15csuEgY13Q8+D/+e+khmALGbbVt/UZdnT8I7edsCOLnyv0DPcITAhjEm4G46iSPoSU/ZlYOhH5xKeeuroXVwmLbQAPDCq+SqNPt2rslNTLT5w/JDsIOSVX0NkGZrIkjsOTEiIxBnB0X7krU3HIABbnwtMXzLooxtE0USSbb7yu5+43/3vh00uwt00DA0M+Kh0E7+Jo+grLqjvbXv0cwkW6RqAOo9xoADwWiTrU9xkvz9FOKRhKV5rfvev7GqOUzUXhMBVvSm/8/W7EoXkoSWTFSOVbyid9s73Mxz/FmoSVAjC6aqAAk/x+FdGJuS5ov3pW8/PCwyeyOWghVrQ5qsi+PNBqv54b4hc4B0l+aggTfQQP6Ezk36CAZgJWtk5FqGlqWaG5LevZvwG2daUBPUuk1UDsKDDV9JF1NWu3bcMQImezocLc0Nvp911fItaeS6rFw7dtdNardG608eqkja+pIJ4E4QQok2yHTLO/N+1MMqrUtD7n/bn345XpVCruIXqL53FK+7awgtSLiWP0GWqeO2njg+nxcWf9P26tFxTYUIJyfrXSGaI8Hf4Wie1qO2yNqMZkQXFKNl55787xolvU12E8n/+/TDxYYhhAMqL6ZfmQzCcMAs6eko6Smd8JFRQH3XGTfFJCFSeqU8t3r0buIxSv42YtiCh0eZzcwhVwps7uWUde+bYXZzuIVp00BMY5z/3rkkgSGYApho7gspIFEUzujlH3izCVHiMoqE4lUNDo4xa0GzMqlcslycsFTUA5VnJT9IjHbw5hoWdRJW/7+piF3/wg6vxet8heRNs4vrKxCPEuystzsS3l5vcFDUANZ8UNDQWN1bfAJzUrUOeUo3JcJL+ZtwclIxjGfUAIoU06nLqFuS0ZAYgXmX0L0Vb4FhFOMTjS0WH8e/BF44nukIFlWTUhlTviObKgj4HecbZwFGjlkpPbJYnXNPBZBxi3O7jzS3+eJBBISnQX2ui4wVPdDqjSU7pvvscJxpGYdeETK7JsVHnRKbnx20a4voIHsBMkU1+/DrzABb0FiQsHDUW5LVTiFVyKcryjEu+EE8lbifKh6gC6EhtbJUrxSJv0a0HuFqEeZomGP94HdDrxz+cceHLGxQEA3k6JXkS5QAW1ACUxAFJKyz+qtYy7qp91krqYAzSSeMeuKa8J9Iw9O8NzOKyUcVdgzRPveDogloQfFKdI3K0Mqj9RQyvLpVrnMZdrhfTF1TFaIGrkylHhk0G3lW/TJY/RjLjq5QvYxDiz9yjbp7hi7TPH30DUMa2Lzisxdg3APHKwp1VeDBdPIdN/dPxZn3Pks5VKEvCzVED8Kc/FrtnGdV0vPqTHxMVDqIGoLIrk2UApztuHTd53lJreOeXTp4HSYyda1ZKVOBI1RdUjgmz/3Li8/m1aKKC/y5FuYF6NgU1POLGwrejdzKZdmL0POkH+t5kHVPnlj42fWH+HMA4KkecBzBuzFQWQs4FzzL8OZ/WkB/e8GXxIpM5T3QmmZpBqn5El0lX7DjalzyIzHei4ohG8cHYmXb4C8Pz1M+Nnl/h6l5OF1bVMZI9V6I01IYvaPNL/ml+LmhfmZwnDmx+0jzJ+sSDTsWsKPcxenwwADN5KvkfG8cBpB7xpXEcwK5du1rZsjmyBZ06dXL/K84mnoSkD/xrMykqxKoPEoOEYuLwb3y5Bc5TtmMcZ4G+JPvhK8Xz9yiRV2PQzisuA++LCbNd+Shf7qaguEHaV1jWFwsuzMeuELU8piwqlMJKtbjIC8GEePobo+3576bFcrQ4Lk4clL8joIqRQlhb8isFxSW/8676+EdX5Dwqkss4WLS3q7apq5Sg593m4UEuu5kGrxEPSqYcGd4xKoQk29HDRV39r7n3k0oIfktmAIq8rmxGncN9+AZgfngk+111auOoDJzDdVQWj2QgOGVqkruIGqdXfvyj3TuAHDNzhouEmflvbY4KunmJ3odCnfRHwsxxzWs5snxxNLCJM/T4u1/erLBjoT+McPQsqQ2cTthO3GaF9v0xJKu243sAMb4wnpAs8t+5dA1AJWGpfGFB50Lu3dcVTRdLJWpIuDjd83Qc0ZerPvnRZfDqG0H0nEx8ZQinyqIlooLqRVRX1R8HeqzQMo5pllNCrSDNVw/g/Gx9VwUZS7bO6d27t/E/2ooVK6xnz578c72uBJItbArbDzw/soCplYQxeGOuCDWKvNQlVisRIWBNYnHJFGRNwmGD4yZieaqXX9p3caEIJhn4UIhPU1Ten/B8pX8ffPHxJF/j/yZCf6YhxPwerjI2EXomCyzV5JKqL2nOUe4LIjt6fmi4pRJX9g3AVAT6ZGEiPInwBRH3rntbP1fXNppwkt/9Z/K7ylNFNdLwBJ/Xuq4r88YuXtnnquPLNVQ/Nk5fLdUYCGuQHT704raxh23d/Qubs2SFk9uJUhTY7ECq/u3PvxNhaToRdSGabJAtA1AGVByVgetzHdXkJXnlkzPXcFYV7ox6ikhAeGTQZFcpCGPa1+UjqxYpjGQZwJk8Y44VTYTn2PqRQa7uM9qAxdHAJo7rp02GnzVcmPHQX1R8Ob/+lL3sKy7oHJ4PXM/oM/ANwDgDNtm3HTcWCRQzBza//+uMven+HExhgJ5Hrq1mkAoDaUUqezY/vFL9rkoYSooRjcFPyImev9l1n7mKFxQkKMoG5xRZl4cH/Wq/zF3qNDc3pBY8gNl/mjfnClDDJB5eVDqA2Ri2Qr3KzE3W5+zFOfWKkblI1sQ5iOuLiQ0yLqr/7PDU2OlRdSQueUUhBowosoL99s3k+S4zMVmt04Ji8/DAX+3iD8YVepensAH8FjJCB1+4l5ukJcYdNz7fAEylqs9xvtZitC9ppUnbsKBY5HfepR/+YA/+n73zgLKyON/4IwICIogIShWpoiIKNlBQQMAWTdTEaCzJP3Y09oYFK/YWxV5ii7F3pDfpvXcEaVKl9/Y/v9l9l9mPe3fv7r1bmTknJ7j3+2bme6Y989ZBczPiS0afN7MBuzT4oeXsqoQAACAASURBVC7w9sPzNpZ0N6t2URt9PvE3l44tVrHwJjnxnHtuwBzd8f3UPZyXwBn/nh3pNoDZ4RHvd1Pl4O1IoPJo4SB/5g+NVfORPs572SeAPEs/ogGirQ5yo0L6c+tpmMg3ma0bqiicQR4/+wgXtig/Ct8ey5udvyca9iSRflJfNP1aIu/l9BkjgJhFVNiv5B4OZPTDD/KeVf0WZoe4kORSjhUyKpH+/fn90ercrkGmjEOJvGeX3ETTnWVV5y8rN7gUd6QiHXlLK1luXAshFetd4iBiAxhrTSXS/5w+g73ujp1yea2LUwkEsGBGs1BIAE3CkBP7kXhwWdDaWGJ7Nrac3jItlEqsgMQWI8lCjKRqCC20QbJifjNwpp6K9/3k4hqSNSCWV6/13SeAWcVQw36H3KGxvI+py+waU02OoxibE0g0h7U9h4qHvLHmsNHm1aHO85QSyxwgkTEkvtaA2SszZaHx37M8x4kaxPOumRpEbVdTRQBpAwlHg3QP4XjfSXs48SDV8At/t1AbiWCU6mcswDb2v1xiiA2Y2+wGOe0boTAw4o/O9bwggJZuMKd9zMnz8VTDVgcXW743kWgOlm7SQrlgbhI1y8lJ33L6rDm6WYrDnL7vP2+OKZZNxzK+8G1HHJLmkR1K3iAQCGDe4JpdrYWCANJJbBzOP+rQuIQiuw+x3y10SSyjVTbsW1vX3SM9V1Z1m41JLDJmOYNzakOW3bfYxpMsAWRDO+/dUU7aWfmBHvrs8uYug0qsgLLWJ58AmnonN/2wAztWAvvsvj8nv//z0/EuXV2ifWz32jDnyUghHRcBSeORx5z0w3/Wso1kFR8yWrdJMmLlkcVzHbvX/CjxCCCXNGKLFVQxO2Gyrxz97AB9fOlxLrVfQZaz3hquV/7UxIXeSUUBe0s3mIr64tWRHQHMSds4EOGIwv+w+U2V00+ifTAJfyrCTVlIp1PqVHLB2C3GZzy72UT7GJ7LHoFAALPHKC+eKDQEMFUfhwSQ0A/EC4sW4reRHiwnG7YvRYvWZ15jsexvUvU9qaqHlH3YyeARm5VHl08AzcA7UXLl99XsOvNaIpCVlDIWdpaSkN8sDVxuvi+rcbFYg7Fis8V77/spSxxZj4acYDzymwCedUTVLONWpmpO5qQeCwnFfDriqf5OQpmXtqU56VuqnmWsD6tUNqEUd8m0aTmYUznvUU3e2326Xvrj0cl0Lcfvml24n1Yxx5Wkv2BmK6cefpALmTV07u865ZUhWTrN5bat8F5mBAIBLJgZUewIYKphtFAqsTZLS8MUK1NGqvuRbH2EhCBu2sUfjslS4uUTQAvxkMqDItnviL5PAOUvJ/6WsASw4xvD1WvmclcNmWlIRp/q7zNPY8sZncg3m0PR6FtaqXmttAwQFDxtIQU3npp1vtlE2kjkGcYfb+BEsmwkUl+qniEGXdl7umv5wx1U74l+LvQSIX6KUwF7wmXg0ZuX5bWh84SW4bMr9szYlJft5kXd5m2eE3OLeP2wcGTE3xzU6RRZKsKsnOby4pv2xjoDASyYUQ8EMBvc8bIbMX/VHrlzec0IYE6dCApiqHFMeKhDI5fcnFhq8YpPAHNKrgriu5Bo4sSTKIlDbddjehoBtEDQib6b6PeZnWGs0Bzx6rAA0TPvaZOtnV6i/cjNc4WVAJqjGPE48S6PFcsyN99bmN4h1mHFsiV1ULm0kFyhZI+AZZzJiblFvFrNUcoIoDn5ZeU0l30PwxOJIBAIYCIopf6ZQACTwNTSGeW1mjOJLma8Sl7QW0+rq9u/m6KNT+4OgROt2yeAObWvS0U/c1rHpN/Wquf05bqjTb2EXsVrr/u0ZY4w+t+a0MsJPmRtRKV5Wb1uKZdiBRxPsNmUPAYmHRtVUY9rss+zm5IGE6zEHMUIYwMBLApmFwl+WngsCQT6zlzu7JpTEXDe7EzbNzxYva5tocG/rFSrbkOzdJpLouvhVQ+BQABTMx0uTw/9Qhq4nem5f++XNDRO9YEAJoG7ReGPFSImiWrz5NUjn+6vf55YW4/0nqk1j8ePIeWTIjx956zckKM0aXnS+RRW6ksM84oAmuQ0q/AR0U8izEm1h3s5B51ypQsuxAOYJBoEOIXDklBV+97xvctkQlaSVKWYS6jh8FChRcBMJ7JK15Zo583O1MIdmRNIVk5zidYdnssagUAAUzNDrie3djrh25weDPpRSeQ4WxyjiUAAU4N7oa+l6bMD9eem1YSTzIpHz4zb37wiRYUFoPPfHanvpqSpjPPqWy1+Yk7DR/jZYAoKLxybiI9YoUypgupC3HbJsTzkplNcHMBwKBe64SmQDpmULhUZh8xxzXJtGwHMbRq0AgGkiDYaCGDeDRx5r/4u6dtAAPMO5MJeM56pHRpV0XsjF2SZkzKvSFFhwedP743SN5OX5CkBvO6LiXpj2K8K4SNSO+rl7vlR3a86SW1eG6ZtT5+TUKq01PYg1FbYEDBHjZzY28b7BrJtlL7rR13X4jC9dtExGjRnpU57dWhGFqHC9u3FqT+BAObNaBLN9WdJDSXNCwQwb0AuCrWe/NLPzsPwq0m/af4D7fdaCeCF/xmlryblLQG07CS5zYpQFOZTQfSRtFvvX3KcULFn5chUEH0LbRYMAhaMPyf2tvF6amn1bj+trp497ygXzJ7sJr891KFgPm4vajUQwKwH+z1JV5IDGufFGI8OkNQ28ney0A+S9IGkLnGqDyrgvWSRtXpliBofUl59Z63QnM7t9loC+OqQeer01aQ8lQDe9f1UPTNgjgraoaO4TW1yLHc9q7Fu+maS1nXdM85ncfve8D3ZI0AawmYvDNL421urafWK2b+QzRNoQLp0aKiHOjZKuq5QQeIIBAKYNVblJJXJ4pFtktZ5v9eX1EvSp5LuzeK9QAATn6NF+klCk9SoWEajF6zW9Huid4Xdn8YGSHiUnUnmni0KYOWVurtz92l6ou/sHOcYLgqYFWQf63XtqxtPqaOufWdr+SMdC7Iroe1CggBp+po+NzBl+djZE54+t7HubMMRGkp+IRAIYOqQPkZSD0mvSOqaTbWOAHbq1EmlS6fFnurYsaP7XyjFC4EObwxzmS9mLt+gSXeeHvfjUpl7trAjmFcEsEuPGc7bmrRlxS1pe0GOaZNnBggPTexYFzwY34yhIPsY2s5fBCwUV6rysbMnvHphE13fsk7+fshe2FrPnj3F/yhbt25Vt27d+Cdi3LX5DUfBJblM7Ze2lPS9pIcl/TuBqoMEMAGQisMjZ781Qru0S8vWb9WYW1tnSQDzM/VYQWLLZl+9Qhkt6pJaMvFo75l6sMcMFYXwQAWJf07bPvHFn3Vi7QPVc8Zyzbo3vhQ7p/WG54suAjOWrXepAed0bqu6lZPPycye8P4lx+qK47GgCiW/EAgSwNQg3U8Sp/tGz1YQu0EkgU/GaCIQwNTgXuhrIfzJms3bRUqt4Te3itvfy/87Vg0OLq8HO+A3VLwLyd9JB1el/H4p/dAn+s5S5+7Tg/dgSlGVTn91qCPsBP/OSoqd4mZDdYUYgdkrNqjBE/1EgPDalbCUSq5UvO8njb/tNB1eOfm6kuvJ3vV2IIAFM96BABYM7vneKp6T81elER4SnYeSdwg823+O7vxhasLp6fKuJ8WrZtL4kbt587adGprH+XKLF3LF92t+WblB9br20+Iu7VWtQlZm8sUXg+LwZYEAFswoBgJYMLjne6t//XCMJixeq5oVy6j3dS3yvf29qUGCbd/67ZRAAFM86Bf8Z5SGzlultvUP1n8va5bi2kN1RRGBOSs2qP4T/bT0oQ6qekBqJflFEY+i2udAAAtm5AIBLBjc871VVLs9pi/XafUq64srj8/39vemBl8ZPFc3fT05EMAUD/plH4/Vx2MX6d529dX1bLJdhrK3I2Aq4OUPd9DBKTbl2Nuxzc/vDwQwP9He3VYggAWDe763+o//jdf7oxfoHyfU0jsXH5vv7e9NDb4zYr6u+mxCIIApHvSrP5ugt0fM15t/PkZXn3xYimsP1RVFBGYtX6+GT/ZXIIBFcfR29zkQwIIZv0AACwb3fG/1ms8n6K3h83VL68P1wvlH53v7e1ODW7bv0A9Tl+rCY6rvTZ+d59968zeT9e+f56rXNSerfaMqed5eaKDwI7Bj5y49N2CO7ji9nkqUKC7BPAo/7qnuYSCAqUY0sfoCAUwMpyL/VKcvJ+nVofNClPsiP5J77wfc88M0PdV/tgsBU//g5EN+7L1Ihi8PCBQuBAIBTP143CzpBUmPSXowTvWBAKYe90JZo0lPnj/vSN16Wr1C2cfQqYBAVgg80mumHuo1Q5ufPEelS5YIYAUEAgLFBIFAAFM7kCQy7J6eHu67QABTC25RrO2O76bouYG/6O2/NNU/T6pdFD8h9HkvR+CZ/rOdCjhkAdnLJ0L4/GKHQCCAqRtSrsZD04M/3yrp50AAUwduUa3J1GefX9FcFzUNtmlFdRz35n53GzxXn05YrEGdQhzLvXkehG8vfggEApi6Mb1fEhLAyyX1DwQwdcAW5Zoe+Gm6HuszSz2vOUkdGlUtyp8S+r6XIrBs3RYtWrNZx9UkXWgoAYGAQHFBIBDArEfyPUlXSiKtWyxXpwGSSI5JfI9v0v9/dSCAxWV5JP8dD/ecoYd6zdSIm0/VibUrJV9hqCEgEBAICAQEAgIpQCAQwKxBJDFhVnlutknaJGmMpC7pJJAaE5IAdurUSaVLl3Y96Nixo/tfKMULAQJBfzRmkTY+ebbKltq3eH1c+JqAQEAgIBAQKFII9OzZU/yPsnXrVnXr1o1/It5fm98fUhwCCBEZ9RdJKz0pIWBCDvl7kxigBi/g/J5pBdSeBdHd9dwfCqgHodmAQEAgIBAQCAjsiUCQACY/KyCx1SLVfCFphKQnJS0NBDB5kItqDVu379TWHTtVfr+SRfUTQr8DAgGBgEBAoBgiEAhg3gxqP0mDgxdw3oAbag0IBAQCAgGBgEBAIDkEAgFMDr/cvh1UwLlFLrwXEAgIBAQCAgGBgEDSCAQCmDSEuaogEMBcwRZeCggEBAICAYGAQEAgFQgEApgKFHNeRyCAOccsvBEQCAgEBAICAYGAQIoQCAQwRUDmsJpAAHMIWHg8IBAQCAgEBAICAYHUIRAIYOqwzElNgQDmBK3wbEAgIBAQCAgEBAICKUUgEMCUwplwZYEAJgxVeDAgEBAICAQEAgIBgVQjEAhg6hCtIekpSWdKIr3Hr5IukTQ5RhOBAKYO91BTQCAgEBAICAQEAgI5RCAQwBwCFudxkryOlfS5pK6SyAdcT9IaSSsCAUwNyAVdC+lzQrq+gh6FnLcfxi3nmBX0G2HMCnoEct5+GLOcY1bQbwQCmJoReJR0vpJOTLC6IAFMEKjC9Nhtt92m559/vjB1KfQlAQTCuCUAUiF7JIxZIRuQBLoTxiwBkArZI4EApmZAhqWrfFH9niZpmaSP06WBO4MEMDUgF3QtYYMr6BHIXfth3HKHW0G+FcasINHPXdthzHKHW0G+FQhg1ui/J+lKSbskkfM3WgZIaitplqTDJV0u6TNJR0n6QdLLkp6JRwAXLFigChUQBoZSFBDo3LmzunZFwx9KUUIgjFtRGq20voYxC2NW9BAoej2GANaqVYuOV5S0Nr+/IBapyu8+ZNVeOUllsnhgm6R1ksZI2iqphffsPZLOj/zNfsZhZGFh+tDQl4BAQCAgEBAICAQE9koEakpalN9fXtgJYKJ4vJUu9WuZIAHku6unk8dE2wjPBQQCAgGBgEBAICAQEEglAgdIWpyu6UxlvdnWVVwIYDNJQyVdIekLSY0l/SjpxfT/ZQtEeCAgEBAICAQEAgIBgYDA3oJAcSGAjNc5kp5ItwVcIunNOPZ/e8vYhu8MCAQEAgIBgYBAQCAgEBOB4kQAwxAHBAICAYGAQEAgIBAQCAgkgEAggAmAFB4JCAQEAgIBgYBAQCAgUJwQCASwOI1m+JaAQEAgIBAQCAgEBAICCSAQCGACIIVHAgIBgYBAQCAgEBAICBQnBAIBLE6jGb4lIBAQCAgEBAICAYGAQAIIBAKYAEjhkYBAQCAgEBAICAQEAgLFCYFAAIvTaIZvCQgEBAICAYGAQEAgIJAAAoEAJgBSeCQgEBAICAQEAgIBgYBAcUIgEMDiNJrhWwICAYGAQEAgIBAQCAgkgEAggAmAFB4JCAQEAgIBgYBAQCAgUJwQCASwOI1m+JaAQEAgIBAQCAgEBAICCSAQCGACIIVHAgIBgYBAQCAgEBAICBQnBAIBLE6jGb4lIBAQCAgEBAICAYGAQAIIBAKYAEjhkYBAQCAgEBAICAQEAgLFCYFAAIvTaIZvCQgEBAICAYGAQEAgIJAAAoEAJgBSeCQgEBAICAQEAgIBgYBAcUIgEMDiNJrhWwICAYGAQEAgIBAQCAgkgEAggAmAFB4JCAQEAgIBgYBAQCAgUJwQKEoE8GJJnSQ1lVReUilJO73BOEbSy5KaS1ot6S1JDxenwQrfEhAICAQEAgIBgYBAQCAVCBQlAthe0kGSykl6O0IAIYQzJb0r6RFJDSX9JOlZSS+lAqhQR0AgIBAQCAgEBAICAYHigkBRIoCG+WmS+kUI4JWSnpJU3ZMK/kvSTZIaFJfBCt8REAgIBAQCAgGBgEBAIBUIFBcC+LykxpLO8kBpIWmwpIqS1qcCrFBHQCAgEBAICAQEAgIBgeKAQHEhgKiE95d0iTcoR0iaIqmWpMXFYbDCNwQEAgIBgYBAQCAgEBBIBQLFhQDmVALId6MuXpcKEEMdAYGAQEAgIBAQCAgEBHKBwAHpQqpduXg3qVeKCwG8QtLTERvAmyXdGMcGsIakhUkhF14OCAQEAgIBgYBAQCAgkDwCNSUtSr6anNVQlAhgiXTHD5xA8PCFNe+QtDVd/Tsj3Qv48XTS96Ok5+J4AVeQtGbBggWqUIF/hlIUEOjcubO6du1aFLoa+ughEMat6E2HMGZhzIoeAkWvx2vXrlWtWlipOV+Ftfn9BUWJAOLp+54kE5PSd/7dRtIgSUdLejU9DuAaSa9JejQOoI4ArlmzJhDA/J5xSbR322236fnn0faHUpQQCONWlEYrra9hzMKYFT0Eil6PIYAVK8L9AgHMz9ELBDA/0U5RW+FQShGQ+VxNGLd8BjwFzYUxSwGI+VxFGLN8BjwFzQUCmAIQc1FFIIC5AK2gX+nZs6c6duxY0N0I7ecQgTBuOQSsEDwexqwQDEIOuxDGLIeAFYLHAwEsmEEIBLBgcA+tBgQCAgGBgEBAICCA0V9QARfIPAgEsEBgD40GBAICAYGAQEAgIAACgQAWzDwIBLBgcA+tBgQCAgGBgEBAICAQCGCBzYFAAAsM+tBwThDYsXOXNm/bof33K5mT18KzAYGAQEAgIFDIEQgSwNQOUFVJL0pqK6m0pGmS7k0PE+O3FAhganEPteURAnd+P1XPDpijXc/9IY9aCNUGBAICAYGAQEEgEAhgalH/UtLBkv4kaZWkWyU9JKm2pNVeU4EAphb3UFseIdDutWHqN3tFIIB5hG+oNiAQEAgIFBQCgQCmFvnxkt6R9HJ6tfun5/s9SdKoQABTC3aoLe8ROOP1Yeo7KxDAvEc6tBAQCAgEBPIXgUAAU4v3JZKulnSppJUEtJf0T0lNJG0JBDC1YIfa8h6BQADzHuPQQkAgIBAQKAgEAgFMLeqoel+XdKak7ZJ+T1cHD4s0E1TAqcU91JZHCAQCmEfAhmoDAgGBgEABIxAIYOoGgNzAsyUNSJf8rZN0rqQPJLWWNDEqAezUqZNKl8ZXRC7DRMgykbrBCDWlBoFAAFODY6glIBAQCAgUBgTI2ML/KFu3blW3bt34JwmB1+Z3/yBNxaUcJGmFpOMkTfA+aoyk/0l6JkoA16xZowoVEAaGEhAonAgEAlg4xyX0KiAQEAgIJItAkAAmi2Dm9ydLGirpdknrJZ0j6XNJZ0vqHwhgasEOteU9Au1fH6Y+wQkk74EOLQQEAgIBgXxGIBDA1AJeT9KzklpK2k/SgvS4gHgG+yXYAKYW91BbHiEQCGAeARuqDQgEBAICBYxAIIAFMwCBABYM7qHVHCIQVMA5BCw8HhAICAQEiggCgQAWzEAFAlgwuIdWc4hAIIA5BCw8HhAo5gis37JdD/aYoXvb1VeV8ii6QimqCAQCWDAjV6QIYL9ZK1TnoLKqW5m41qHsTQgEArg3jXb41oBA9giMW7hGzV4YpC4dGuqhjo2yfyE8UWgRCASwYIamSBHAfW7/XkcdeoAm33l6waAVWi0wBAIBLDDoQ8MBgUKJwNC5v+uUV4bo+paH6dULjymUfQydSgyBQAATwynVTwUCmGpEQ315gkBwAskTWEOlAYEii0CfmcvV/o3h+nPTavrsiuOL7HeEjkuBABbMLChyBLBJtQM08Y4gASyY6VJwrQYCWHDYh5YLJwKbt+3QviX2Ual9SxTODuZxr76bvETnvzdKbesfrL7Xt8jj1kL1eYlAIICpR5cV8ZikEyTtkDRF0qmRZhIigNt37FTNR/to5j1tVKFMqdT3NMEaUQE3rV5B428/LcE3wmPFBYFAAIvLSIbvmLFsvQ7ev7Qq75+WfSm3pdSdP+jsxlX17f+dmNsqivR7n45bpL9+NFbHVKugCXckdybc+NUkVSpbSo+edUSRxqSwd37swtWa9Ns6XXlCrUxdDQQwtSMH+esu6UZJX0jaJqm5pFG5IYB4Wx3Q+SeNv721mlYnU0vBFAjgcTUqaOxtyS32gul9aDUZBAIBTAa9gnl36/adKrGPVHIvlVDFQ5197MTaB2rEza2SGhjqOahcKa18lJTve195b+R83fj1ZEfcFj7YPikAwJLy2RXN9d2UJfrw0mZJ1Rdejo3A0c8M0JQl67TruT8EApiHk2SQpBGS7symjYQkgOs2b1eF+37SuNta69gaBUsAm9esqNG3ktI4lL0JgVQRwG07dmr5+q2qXrHM3gRfgXxr5Qd66KTaldT96pMKpP3C2ihk49AD9tNvD3VIqovUgyRx+SMdk6qnqL786pB5+vfPv2jeqk3a9OTZ2mef3Gd0NQL40h+P0g9Tl6rXtUGlnBfz4oQXB2n0gjWBAOYFuOl1lpW0TtJzkjCWIyvIXElPSPoq0m5CBHD1pm2qdH8Pjb21tY6rWbAE8IRaB2rkLcndnPMQ+1B1HiHQ4Y1h6j1zxR4bR06bu+O7KXpu4C9J15PTdvfG5zlUy5QsoU1PkYkyFEMAXA4sW0qrHktOckc9VcqX1rKH904C+Gz/Ofpp+jL1m71CG588W2VL7ZvrSWYE8KlzGqvHjGXqdz1JtEJJNQKtXhmiwXN/DwQw1cB69dVIT/22ND0H8HhJ50v6nyREZ0gGrSREAFdu2KqDH+ypMbe2UrOaB+Zh17OumkV6Uu0DNTxJ1UmBfUBoONcIpIoA/uGdke6GH1VB5Lpj4cW4CLBey5YqoY1PBgLog5QqYkw9VcuX1tK9lAA+0mumxi9eo68nLdGax89Myj7dCOAjZzZS75nLNajTKWFl5wEC8TQ5wQYwdWBD6lZLelJSZ6/aHpLGSbo3SgA7deqk0qXTDJI7duzo/ueXZeu26JCHemn0La3UvFbBEsAWh1XS0H9FfVlSB16oqXAikCoCeOabw9VzxvJAAPNhmDlU9y+9r9Y/cXY+tFZ0mgAXtJU7n81sB5XTL6CeQw7YT0uSVCXntN3C8vy9P07Tb2s36/3RC7Xy0Y46qFzunWqMAHZuV1/9Z68MZ0weDbJ/Ae/Zs6f4H2Xr1q3q1q0b/0TFuDaPmo9/Wc3vBvO4vVmSPk+UAK5Zs0YVKsAbYxcWWfWHe2vkza10Qu2CJYCn1KmkwTcFApjH86fQVW8EcMcz56oEngW5LG1fG+o2+CABzCWAOXiNQ/WA/UpqbdezcvBW8X/UyEayczBVtoT5gfhlH4/VsF9XaU7ndilr7uZvJmvnzl16Zcg8LX2og6oekPt0cDYmt59WVwN/WalRtxReO/P7uk/TWyPmF0nV/18+GK3PJ/wWVMApWwWxK/qXpHsksfNOlMRV01TAo71XElIBL1y9SbUe7aMRN5+qE2tXyuOux6+eRdq67kEaGMTzBTYGBdWwEcCtT5+TVNyzU18erCHzVmVJAHfs3KV/fjpeb/65qUqX3DtjrKVinFmvFcuU1OrHAwH08dwbCSAha7bv3JXSi9c1n09Qlf1Lq2vf2Vr0YPukHLtsTDqdUkdD5v6ucYU41NhRT/fX1KXrU4plKtZ7InVc+ck4fTB6oXY+e24mp52gAk4EvZw9c7ekTukiVSSCD0n6IVJFQgTw1983qs7jfTX0plPUos5BOetFCp9mkZ5er7L63xAMdFMIa5Goyggg3n5lkjD2PvHFnzVqweosN0+zeZ1xTxs1rFK+SOBTGDvJeiVEx+9JOjsUxm9Lpk+pJIDVKuynxV2S8yZO5lsSfTdV3+y3h1SR1KD3/TRd8+5rp9qVyiXanT2es/5ddVJtDf91lSYV4nSjRZkAXvv5BL05fP4eTjuBAOZ66ib1YkIE8JeVG1Svaz8NvKGlWternFSDybzMIk1l1HfC2xxQpmQyXQrv5hMCHd8Yrl4zl2t917O0/365H7NjnxuoCYvXZkkAV23cqoMe6KmJd5ymJtXim0bk06cX2WZYr5XLldKKvTROXbyBSxUZop7qFcpoUZfkYuDlxwRL1Tf7fb3gP6PUum5l3fXDVE2/u43qVt4/159i/buseQ0XpmTa3W1yXVdev1iUCSBq+3//PFfLHu6gKuV3q+wDAczrWRO7/oQI4Kzl69Xwyf7qe10LtW1wcIH0FFuPfe/8QWc0OFi9r0s+RhPx4Erf9aN+6dxOh1fO/c2xQMDYCxs1Apist9+RT/fXtGzUJyvWb1GVLr0K3Oa1qA8zh+reHKcuPwhgjYplkg6CnB/zLC8I5lxEUAAAIABJREFUINL8G0+to+u+mOiyQyUjrbf+kVd43KK1mnVv2/yAJVdtFGUCaGG45t7XTnUO2n3uBgKYq6mQ9EsJEcDpS9ep8dMD1POak9ShUdWkG81JBTUf6a1Rt7RyEe/L3N1dHRpWUc9rT85JFTGf3bh1u/a/9ycNufEUtTy84NTaSX/IXlKBEcBkvf3qd+2rOSs3ZikBXLpuiw59qJd+7tRSp9YtOIl3UR/avAxTwoXwx2lL9YejDi1yMKWKDFFPzYpltCDJLBj5AWCqvtn6OnflRjV6qp8WP9hedbv20/B/naojDz0g159i/fvDkYdo0pK1mnvfGbmuK69fLMoE8NZvJ+vFQXM16Y7TdLSnXQkEMK9nTRISwMm/rVWTZwfqh3+eqHOOPCTferpr1y6VuOMH1y6ifrKRnHlEFf10dfIEcO3mbap4Xw/1ufZktWtYJd++qbA2NHXJOnXuPk3fFNK8okYAo6qDnOJZ+9HeWrB6c5YEcPGazarxSG/1vvZknRHmRk4hzng+L71Uf/5lpVp3G7qHMXmuO5uPL6aKDFFPrQPLaP4De58KuOf0Zbrl2ylOVXvQ/T004IaWOqZ67sw1cPoqeWeaeTwChilL1xVqqWpRJoD/+nqyXh48V8P+dapOPmy3Q2kggPm4AXlNJSQBnLB4jY59bpC++ccJOv/o/Ltxb9+xU6Xu+lHf//NEEf+PYNQkP//xquRTS5mh/3f/d0KRlCKkerrc/9N0Pd5nVqH1LDMC+FuX9jq0Qu7TuCHZQ8KXVQiOBas2qfZjfdy8OzcfLzypHtOCri8vbdT6z16htq8NU7Je4QWBUSoJYO1KZfXr/YVXWmX4puqbrb5vJy/Rw71muLzwVbv0VI+rT8p1koINW7arfOefXNVEmZixfEOhjq1YlAngDV9O1GtDf1X/61vo9Pq7zckCAcy7nejr9Ewg7BL9Is0kRADHLlyt5i/8rM+vaK6LmlbPu55GajY1LSTt+FoHuliEHMgczMmWJWs3q9rDvfXp5c31l2Pz75voNwQEKdOxNSro11WbMtlCJPtduX3/wR7T9WjvwksALYDzwgfPUI2KZDvMXUFasGrTtiwJoHm9F8TcyN1XFc638lJFOWD2CrV5bZjWdT1L5ZNwCioI5IwMbX/mXO2bRExL6jmsUlnNywUB5AKMWU0y+XNzgl2qCeD/xi1yzgQkBaj+cC8nnMhtiDKz+eV7yDQ1e8WGQu24VJQJoHkBR83JAgHMyWpK/NkrJF0qCR0B/8sVARw1f7VOfOlnfXJZM/31ODLN5U+xHMQs7mOrV3ChaM5pXFU/pEACaLEN//PXY3XlCbXy54PSW7FQJNitXPLRWP1yX+qCo+b2Qx7qOUMP95pZ6CSABD2lELqFXMC/3p9cuIfy93bXhq07svxO83p/7+Jj9fcTczc3ug2eqwZV9s93m9ncjn9evMehn1cSqoFzVuj0V4clnQEiL747uzr3veN77dyllOSvrXNQ2VzZqzE2X155vC44plp23U3J76kmgP8ZuUAfjlmovte3EGYd/7usea5tuU3iz4ceU41L+cZCHbuyKBPAqz6doHdGzldU8xYIYEqWWaZKakoaLIm0GfMl5VoCSFykFv8erA8vPU6XNafa/ClmjP/134938Z7wRE6VDSBGxHW79tXLfzpaN556eP58UHorDZ/op1krNjgbs4s/HKOV+RwmA2KNuveZPxyZ8d3k1ezSc0ahI4B2cBD+h6TvyXptl77rB23bkXVAWvN6f+VPR6tTLudGXjpA5OtkTaKxZCRU2TVrBHBxl/aqloRJQHbt5MXv2Jthd5aIR3ujJ/upc7sGMS+p4JsMAXzm3CN1R5t6efGJe9SZagL4+tB5+n7qUmcOVPfxvuIin9sQZbbe6TR4Ll+/tVCnLyzKBPAf/xuv/4xaoC+ubK4Lj9mteQsEMPXLkCR7n0l6R9LOZAggkdFPfWWI3r24qf5xYu3U9zROjXYz46baqGp5Hf3MgJSFgbFF//hZR6jzGQ3y7ZtoyDxRf7zqRF34n9Ha9NQ5+dr+mAWr1frVodrg5Wh9rPdMPdBjRqGzqbKD47R6lTVwzkrNvKeNGiQRnDmRg8i83p8+t7HubFM/V2NDO0UlSG+uPjCbl8x+9/CDyuWJhNtsAAkAfJgXTiIvviXVddolZPnDHXSwFwstVjvMo7OOqKruV+9p98xvucWXd588p7Hubpu7+Z1TTBJZdzmp88VBvwhHoC//foK4UL9+0TG5DlGGk+Mxzw3Url3SgWVLadO2Hdqcz3ty9NvNATLW/C7KBPDy/47VR2MW6b9/a6ZLmu3WJgYCmJPZn/2zN6Tb/XVMfzQpAjhozkqd9upQvfnnY3T1yYdl33qKnpizYoPqP9HPTZYjqpZXsxcGpSwTCF6vRz0zQHe3qa8nz22coh5nXw22hzUf7eMkAF/9/Xhd8J/RSja/bfatZn5iKIS+2xDXrtkAde0zy0XURypRssQ+bjNMJuByTvsU73k7OE49/CANnvu7pt11uo44JPlwD1k5gUxZss5dNrp0aKhrTj5MfWYt1xXH50wVnJf2b6nC1q+H/k6963Q1TgJbvz4zrK9XuZxmpzD/q7WBF+iZb41QVtlaKnT+SWNubRXzwsAauPHrSc6JIL/Lfnf9qK07diaUvoxxITTJdxG7Z4uLWrdyOZdfl+einpVZfRfPJ3P5ZXxJ7VaxbKmE4Es1AXyi7yyxTj/6WzMR2/PF84/KZG6BU1u1A/ZLSIKPjTv2pGs3b5eZZO54luypiZdxC9c46WGlcqUTfymLJ037RfrVptUrqPS+JTL26qJMAC/9aKw+GbfISWx906tAAFMybVwlddNVv1wZF6SCANptu9sFTXTDKXXi9vT3jVtd8vdS+6Ymf6qRNCSPRx5ygE7+92BBBH6+8ZSk0Zq4eK2aPjdQN7Sso24XNkm6vkQrOKRLTy1bv9U9/j9sKj8am3R2i0TbtudsPP20ak/2naV7u0933m/tXh8mxrIwpJiygwMvcJLJT77zdGcOkNuSyEFkc+PO0+tp2foten/0whypxuf9vlGHP9431wb6uf223L5n0oZUOr1YNpUGB++vmdkE1cUhConO055JQnbf8v2UJTrv3VFZZmthrOOZrVg8sqwuAtn1Ibe/mwTQD4ZrkRai/eEb/tTkUH319xMyNbdl+w4XF9UINs8lqqEx6ezDHRvpwQ4Nc/UZJ7w4SGMXrlGiRCmRdZeTjnTpMUOL1mzW2xc31THPDtATZzfOFKIs0fZsrZNRZfHazRldyOmlvHW3Ifq/E2rn2mY4+u0j56/SSS8NdqQe86tn/3Ckbj89TV1f2Aggl7E29Q9OKG/6xR+M0WcTFu8hTAoEMCezP+tnr5T0hqS1kvZJf5RotmskfSrpOu915wXcqVMnlS6ddnPp2LGj+59fes9Yrg5vDtdLfzxK/2oFv4xdWHQ3nXq4/v2no1PyNeMXrdFxzw/Sqxc20ZGHlHdG38QOYlEkW1CDHv/izyL1z4eXNku2OnHg2e3vx6lLXQ7UWAGmbWOiwfcvOVZXfjJ+j7Q4SXcmmwp6TF+ms94aod8f7ZjRZ27UnbtPF4cS5IVSEIdjtOuG14m1D9TI+as17rbWwobRDyGQE7z8gwEV0v6l990jfAS3eaTNJIbHYQSblZxgYW3klfQr0e9lnAlrUa501qnzUHmVu6d7Sp0CzMu+UZX9Nf2erLMqPN1vtu7+cVomjF8bOk9/PbZ6XInKlxMX66L3x2j0La3UvNaBMSFhHD669Dj9LYbdcn4TQMxouMSs3LhVVbv0cv31pZcfj1moy/47TlHPYL7hL02r69Mrmmf6xvVbtuuAzj+pPgT7njYuXir7yRN9Z7s9OKuLuklnH2zfUA+f2SjR6ZTpuRJ3fO+0BPHWxafjFqnjEVWdSpXCd+DxzPelotz9w1S3Nl+5oImaPT9QXTo0yhSiLFEC+NyAObrj+6lOlQ6hRDJLyWl4oSbPDHC4X9MiNRqyzycs1l8+GOOyb3Eh/1uzGk7aSUmGABL/Fq1Tn1xm0+L98qVLqoTnvQ7Wb/+lqf55UvbmYRe9P1pfTvxNt7Q+XCMH9dNJu+al4b11q7p168Y/K6Zzl1RMk4TrMKKU8AuF+EGCpEVTWyyUdLGk3pJWe31PKAyMEQb/FhLr+5kI5x11iL5NUTBhuwW9cP5R7qbLjf/4WhU16pbWScNvji0XHlNNX1x5fNL18e2odP/UpFqWm51PAN9Cpf75RJfIPD/tmIih9cf3RmVSQT3cc4Ye6jXTqQGPfHqAw+OdvzTV5xMXq/tVJ7n8mCfUjn3Q5gY8JI7PDfxFyx/JfNmIRwCb16yoMQvX6J629fVkv9k5ImR+nf7BEO+QGL1gtU548Wf9I907/L0cEECTrtBmIuTH79uydVu0c9eupOIcRr/1qXMa66629WWHfiy7M9o95KFe+vYfJ+i8FMX5tFA6DavsrxnZEEA8pm/8erK7kJQsUULl99vXEZqsLpyfjF2kSz8eGzeTj0k1P/7bcbq02Z6Oa7khgNQ5Yv5qdxmtUCZ71ee0pevcWiJ2JSGnuLxwobXiS7Ptkr3owfaqXnF3nEvm6CXH1dB/L9t9SWWOkc+aCyz4krMaaSDf+rePx+mUOpXU85qTtUuKGSIH6X7lB3qqc7v6evzs3Jm/mCNLPAJIvzGheKhjI9lYlClZImX2zgQULr3vPnr2vKNEVIW729bL5FRA+3CU7CSUzw+co9u/m+pMjCCA67Zsd8Oz8cmzVbbUvglvbWSswlknK+KdcGWSjJjiLcu55wsqME9B/Z2TS6m1bfb8OQ1BhMSdNtESRdelEUBI6gejF2ZJgv/47kh9O2WpC+c2Yv4qLXs4bf8PEsCczI6cP7sjmTAwSLTOfWdktkbDTITLm9fUB5cel/Mexnhj8C8r1arbUD1x9hGqeWBZXf7fcS4czLjbc2a388LAOfpl5Ua9fMFuVa/VnarA0ny7OQ3w71L77qOtT+952/UJIF6mHHzJ2F5t3rZD05et17E1uDhlLmy8v63dkulA4YnPxi923sez722regenJVAnCwjSA2ymiPnoF7KlnPHG8FxtOPEmQvMX0lRI2W1ihhfjPn7xWl3f8jAXSDS793rNWCYcR/YrmXkTz4oA8hu2REiZMTdg08X25t2RsSWAOBIhhZpwx+75aGYLfDdEYcpdiSWVt0MyVRcc2ud7Hj2zke5v31BG8mI50ZitLd72f2ySmrAg5mSViJPC+6MW6O//G++mCup9gsQiJcNE4uI4YafsnWhAWZtvpiKNF7rqlm8m66Wf52Y7j/z5a85Bhml2m5xdtLCdvubziU5aCWmzMvbW1jquZtq67TtzuVtj2Hz58exi7anmsMV7XDLQiBz0QE8X05R1jZnMknVbxN4QK02cZbq5q009PXXu7kgA2X2P/3tW3vQ2l9m372nXwPWj7D3dHbGfemcbd6m87bTkvI+v+XyCDim/nx496wi1/Pdg3dzq8ExzBdywZd4WQ+K4aM2mjFiiRgCxs4MArtiQZp6z9vGzdECZrCXnPh6El8Km8ubW8TVkOcH3ru+n6pkBc1zoNUKFXXF8Tb1/Sdq5agQwHonj258778iYGGP7esorQ3JMcIm1yFlC8c2mbJ0hacf0i/lnezO/LVm7JZNw4w/vjNQPU5eqTf3K7jJljoiBAOZkdqTu2YQkgN9NXqLz3xulx85qpPvOiG0zYoseVR2Ttm7lNGKRTLFNkZtk1fL7OaPtow45QJPuPD1H1caS9JgdHOFFiCWVbKENM6rm3/Fuuz4BfJ5F+t3ULNVY2fXLiFssQmSG8tHfPhy9QFd8Mj5TPsbbv5ui5wf+osE3nuI8vv1C4G0WbiJ2MTi3cPPOLsAsKpPJS9Zlm8rL8GpS7QBN+m2d/u/EWo6Q7Xx2twNLLIx4L5bEOjsCeNEx1XRr67puk0T1hk0rcati4Yua8oYvJ2X6jc0NrCj0eeIdu+fqG8PmqWWdg9TEy4FpfZ+/aqMOe6yvzj/qkKTS8T3ae6YO3r+0rmtxmJOi2Zo1j/rpd7dxHvWoUE+odaBqVyonM7WIeuZlN/fi/W7zjt/JVdvv+hZZem5/MWGx/vzBmIzqiI8JAf/siub6c5zA828N/9WRKjJAoGqMlnWbt7vUkfHsGo0AZjeP/HotHiq2oYnYK5qa2qTW/trar2QJDbyhpU5KT4dlmPmx+WxPZc6/c/GxGV35+yfjnF0qBclVn+tOVs1H+rjQGlxIzGGK32PNWwuBBWl68Y+5M9cpc/eP2rJ9Z8z612zapgPv75EhKbKxqFCmpFNlJnKBy27uXfHfcWpUdX93HmF/d+3Jh2VS9bPOubxteTpzhAXLAIWt8yEH7CcjgGgYIDhmB5iTnOPbduxU6bt+jLnfZPcdaNfA0c+w9Wz/OXq49wyt37LDqVav+myCrjy+pv4TIYC+DbffDt9OSrue1+6ZMtUI4OrHzkzYgYe6D3+8j+b9vsk145t5LV+/xV3WmLd8B1J5m3P+JeubSb+5falr39n6afoymUmPnSmBAGY3U/Lm94QI4NeTfnN2AybSj9UVW+T8xsJigcUrqDBKJuAo8tO0pTr77ZHOU7di2ZJOLF6l/H4u/2NOSpQAWmYT6sAuh2jyyRbawKj6gfYN3MFbrvS+mcKsWP0+ASQMwz0/TtOgTi3Vqi5mmtkXu73bwfXPT8fHlVARLZ/bI8+u2bw9wx7n7eG/OtXzyJtbZah1b/xqkroNmediE7Z/Y3imjhCu5py3R2rDE2dla0/G93U9+wjd2y7r0DrEN5u5fINrJytpnuGFNG3q0vW6FHXYuEXa8tQ5exgdMwfrP9FXCx5or/3u/jHTRoVdH9IWq48QLXajtfb5DdJ346l1XJ5ZjO/ZtN4aPt95R3NoI1F8c9ivzi7wHyfWciTEJxE+mYlKq6n/9HqV1f+GlnsMtKkAIaCfeyYJt307xZk/JBqP0L4PFRZ2fZg49Jm5XCNubqUjnurv1JBIi3nOvEstr26iTgTWeSRiLwz6RW/8uWmm77nnh2l6qv9s9zf2Ajwa/bkW/XiTlNnfIaIcJNi0Rb2viUjA4fHOiPlOeh5PbW0HfTwSaYcTkp5Xh84T0rDsLi0WDeHGU+pk0ibEW7W2/nj+lSHzXN5xpHwUsnAQ4N7WvWlZ/v3Ho3VTq7S4pFu373TzmOKn4TQ7Kv6OCphc6cRI9SWAeMzHW1smybzqpNp66y+Zxy77HSjtibJ3/6jNEQKI81Odg8q5TBoNnugni6NpY4E94CXHVY9JAHOameQvH4zWSbUrOceIdq8NU7sGB7sYsc1qppmpxLuE20Vo/O2tnYqXCxsqYAjg7xu3ae7vG937Sx/qoKoH7JcQHEaCTOKZ0EvpD8USTvhnBPPhX99MduYo7/417RJgEsB4Ukrex/Z3YKc9nSWNAObk+2jziCf7uRR5FOz3Xjg/7eJg2gPMnzZu3eHsWDFtQPpHbFnUveyv9Ikz8dQ6B7moCkQbQKW8vutZLtpEIIA5mTWpezYhAmiH2n1nNNBjZx0Rs3XzfORHpCZru54Vt5dMhmgqmFgP28HAhCtTcl99Nek3Z3iM8XS8zZobFf/zb7a2oFj03H7/9J/RGc3lRqUcq6+0cf8ZDfREv9kuxAvqjnVdz3aPMtEPP6isI0/+4kasj82ESTF81UQ88Ex1bQTI4irFIlGGH7ZVqIhM/Wc2V0ggLHjq1Z9N0Nsj0iK0Y3Pil5+uPsk5jax4pKMq7591mAO+LxE1JsFbbbNNhACi6mIDgtBgRBxr8zP1K2pBwjqY8bxJ1wyHKLY+AcTx4NoWh7n3yTpTo2IZvTmcOOpybWMvauprCNP/fTohUzqyj8YsdKYKFA6V0bfutlcFmzMaHKzeMQywXx0yT52+mrRHrmveKVuqhDY+mVisSJtfbPDY9TEPkSSY/dmQG09xzkk898ejD9XX/zhB3actdQQ/Oy//KG6dvpzkyJM/fkituNQ83X+Oe9zajyep45mvJv6mC99PW5NIj188P+3Qe/2iJrq2RVrUAdYQIU8gtR9ccqxT1SE9j5ee0i5K0YCz9g1mA2ikLJHLDWYFHd8c4aTQvkQu3lo1SfvfT6jlLgwmSed5JKOEwmjXsIp73dbqxcdWF/ssUmIM7ive18P97l++z3pruHpMX+7+joodckhEAzyemXvZSQBN4hu1LYy7Ycf4Yf97u7sD38bevJiR6GBfjQSdtYMtYuVypZwNJKSXNfn6sD1NOJiPaERuTVA1jJSd+IjY3FmecLrpr+VY62bm8vVq9GR/hxv7D6pSCOBxNSpo07adzpyGErXFzAobM3dI1DTArys7AgipxO7On3NGALHnXbp+6x5REaiTSxKXvmgxG8AFD5zhzKqyK6xn5uaDPWc4DQzlttPq6rnzjnL/Noc5Lh+QPjRLVrhgEqzbCCDrF9yZH1XKl3YSRSOigQBmNxJ587sjgIuXrVS1KlG/kbQGT+s2RCs3bnMbMLdk1B/9Zq/cI3+uedXyjk9+rNvYgeAFhp1APPVc9BPNVg111j77SOMWrRULmJsahwP/TQBQCkTowDKlnKMA4UL8Q8knXb7kh/dQoeREoojkiht3NBgxbSCpNMkH6o41j6eRYPuNeIN+X+x7fecRJHBnpB8KsYbcFjD2RKSTem7gHH06fnFMKZo570B8j30uzfgcG78Bc1a6TQ9id2a6+gyVCqmVzDHFb5vDm5hriWwafB8hFcjZGyXpxIBqW7+yrjr5MNV6pLcWrkkLu2BjhaMCUgWfZBpeeDsiWcB4mFt7LGcG3/6Oeu0WbMb4ENiDHyQ+euZy9KEHqNe1J7tc00gY2WyR1KBGObxyOb0x7Ff3guVdxeuQuWde3Niz1KlUzt3QkUyhsqGQV3S4twnzLfEy2SCRAn8O/gGehNC+fxT2Y3G8Xf2v4XlI1CzsO7vuzvw49KZT1PLlIU7Cy/ziOZM2mqQqOyevKG4W1d9faxZOKPos5Iexs9Jv1gqnbiOzkHk88ht2W4T0uPOHqc4eE5sqCynz2oVNdP2Xk1xc0PmrNzmiGc/L1y6k2UkAjZQlohIzksYl4ZPLM3vlxlqr746Yr39+NiHj0gJZNVU34XGIlvDy4Lm6/bS0cENI662AqcWC42+YJTx/ftqhi8rz51/SJHy1Diyjz6443oUKwWmL9uIRQNKnHXJAaR1UrrRTsSfjsBdNqWhOdUjK+89e6ZzMKIz5qxc0Ue3H+mRLALEff+WCox3pzY6Qt399mHOO+b+Tauuct0eo+7RlGXuJebXH0sIYYTGczQwHQQD76bRl61ymoJyknDTTgFhe1RAoSiyBhcVy5Hdfi+CfEQgVHuszS/88sbYLeUMxAoimhcgNsUIHYdOI1J1z0w/LZhl05nRum5CZll2kkDSbxsY3gbD6uHxs37FL//h0NwHkAv3jtGUZBBBtW+mSJTR1aRqRJOOKZXYqjgQQwzJksNMl/ZA+4bjOopgnPl9mQ6tYO0je/80RwK4/jtO9Z++2MYkeKPbfMH9c7zkQmXSQQoy2OfRQldmij7XwKt3fQy3rVHLkCRVpvCCkSM/IxQrBMmkKN2jsLAj/0WPGcidh8zfKEb+uchsahUO718zlexBA+sSNNVpymkydxRlVlZmtzu3cjAb+ktHENSfXdgSV7+U3PNZiEUAOsUub1XDP2aEHGUIiZHYfVNr2taFO7YEXrBXUlF9PWhKTAJo9GhICGxuIMwSajcOIJ3VZfCbGGFtAv9ghmVXQXXvevu+Ni47J8AZD7cDCx7OW+YKKwI+HiLqSg7/ly4P3iC1m9dmNvX3Dg11OYAhmjYq7b7DHvzDIOW+gxrZiErhJRPp/dqAjsLUe7RNzVTEGqC+wUUIyi6QHdS0XBCQWFMtre9xzA51DSpQssyZMusrzzPchN+02L7BviZIhnr3s47FO+lBin3008pbdN3d/vmTn+OIOmnQHJAijkX7+buEkUJn+4ahD3FxD2vS/y5vL7OliSTCQQkG8G1UprzLpXpGE4EATgOOGXT4g2axLSBmbPgU7WAg9xZ9rbp2+McyNI5cL5iMqXwpqdg5SgpKbSu23tZsdOccOCts30jdCOD4euyhu7DuT9MTzAr7hy4lOFQlBJNwGRIqLLo4Z2EjGKoQ2IW5nosQJm8/rvpikjo2qqOeM5RkSOuom5+y97epnkD4kUFwqrDDWvlbFJwB2AeFZLrQfXdrMhQohXBY2qfEIoM0lnH3QgsSTRsf8+MgfCbKNx6zNSSNW4Ddm4WpnYkK5oMmhevrcI11A/4plSjrSxnpKC0Ivl37y/jMaOlU3uKLyJOc7DkCs53jREVq9MsQ5hOHhff67I/XdlKWuPYutyr99QcQDP013QgvOEMw7rOC4d9cP09x4MPdYgxBI9rpYduxcMmsdWNZJDwf9stI5RKDSZL9gPLtGvKoPfqCHC3hsEjNr1zdD4m9gwwWsY6OqjixTqpYvrb81q+nMLK4+ubbeTDe1sDAwdt7EIoBoTCCdaOP8/cRMTRINqG/aE19w4quA7YzhTITrcgGxgoQWez9C6mAjiX0za2zB6k1avmGrO4+5kB5Xo6JK7disihWdQ1SxCAPTSdId5LCXZPlOzpe0Ij1Q8yxJifuYJ7Iic/eMI4Av952sG9um3S6jxT+AMP5cs3mbU1sSeoBDdfNTZ7sQBKaa4/1Yonc7mNZ1Pcs9T5l0x2k62jOI57aBVAECx80ARw0mFDfu9Vt3uNh6SEn8YuJl+5v1wxYFhxIhC6KSP3vet1fENpFDARuwWDc2u1lGvRPNCBh8uNH7BUlVlS69MjyoYxFAvAQhuSwS7L3w6pu1fINTo/g3Yd7loFqwenfAUpOIxSIHplqDVN7y7RTXLf7NgftI75kubISFyDD3fKRZ3OD9YsblSBKbVt/T29gZ/eBbAAAgAElEQVR/1r4PaTGk4a/HVdf+9/6kQ7ELXbfFeeYi4Tro/h5atWmbe5UxOL5mxQziEEt6C/mav2qTs9lEwhu9wZrky7sbuAj6428/TRbWBQcI7OBiFTZf4oEhhcBOCdtTwmnwvag5KUYAj31uoAvDQTiEm79Jw5XCWENQqIcStcMxbGJ5J0LAiREH2fE9h3NDAFl/va9tkcmZh4sXnvw4aOH5jpQFaefHlzXLMISPFRYEG0QOIAoSbiSYqMfxXL/7h2mZVDw8wyaP3Q8FlR9zjRIlYjd9NcnZxeGEhS2lqc3p+11t6uvhXjMdESROndmUQaiHzlvlxmXIvFWuXqSC17VMUxNjj0QIFWy7jPSjZv1x2lK3vs5uvFsCadJLfjcPZBvHqDMMzmiYSnw8ZpGTcBhxggxwQSAmGpfA76csdeTa9g67DFi/zRuYdlDRoSIj/SIFNSmHoxXWgNnq8bc/N63mJH0U334WVdq7Fx/rHI/Mpjg7AmhtsCcihUG6iFMLDkRIY33HJX+tYJONjR3rlQs9ZIp+YlZzyiuDM2xq/Yswl4yHOjRU46cHuJibrC8IIPsakjacRSzyABcubBKxH7SCBAxP32ghEPW9bRvogmOq6cL/jNJXk5a4RyBhRDOg+FoYSBNEs1K5Us6cxQqXHsYAAsjzEMANW7e7faNhjJSTrEfOIzyEsQ0mhBferHi/mmSMcwKHCGwebf0iGYUgWeYU31nM/zaIPk5nFJzI2O8wQcEsxbRdNv5ZEUCykpjTBqS698zlLpuM2ZribY5DZbxsT8xnzCwg+WgSzJSDfvlk1OxRESzsu88+GcSf5+zigzQVBze+Dekf+76p2nkOc4gpt5xUrAjg+5KukZTmNy0hXrsL+8n04My/Ye6yx6xOzR+ekITBEBEpMWgYmN52ZuaU1pYjgB8OmaHLWsb27vUPIG5cbOjc+s2jDbsyDJB9AhjL+4p6uPE5O7IH0tRwbDzYcLAxkNDdpFD8hroY42lCNXAzZLNpVrOiXhyUmWBFCaBJCYxEmB2NSZCiEPubhN3KIKkEWcVeqkypEi4sCvWZODwqwdm4dbsjOYQNIc+hX5DEIPmyeGyxCCCkjCCatEnhgEYNhl2PxQg0KSMHjr94Ykk8qQNPPNQiSFbA2Q5xfmNjAk8/eKfZFXETZSz8Nkw6Fk01xSFwQ8vDMmKJ2behWkRGi60emwUbpalwGUvs6HgXaXKsEosAYk9EmAb7fgudg00kdpemAvLrszh8ZrwfK8RNtH0OKCQFHKh4yXJQm1QxSgDtwKUOiMu4205z34z0igKZ7nd9msOHHx+Q/2ZeIKE0snDBf0Y56R/Sk7n3nZHRrUQJINIipClczihmn2gVmWQENeEZDQ92G7IFl8VYm3d9NaO9569JvgdSzwGO4xIkre+sFRkqHt5B4mOHsTmA8HeIGtKNZwbM1qsXHiNsTiFpOCdBLE11xEHDRYpD3A5Uy9ZghBIVtxF9PyaZr9Y2kxST0qKO+uGq3fl0//rhGLePxSp+yA1+p16kjhB3VNAcypu373ASO+wRLz++Voa6dsLtp+mY6myrctlNbv12iiMXE39b66Rb2DZSIGnYRNl4sWdaEGJ+Zw346koO0x7XpHl1EnOOtWAFEt1v9ooM8mMEMBqKyp9LkAtsQ5FkQRaYc/W69nXhsmgbBxT2YP5nhfeN/NoFjmcJs4U9phXbg/lv9sQ7T6/v9jIkwkjD0CBxWeJST9B5VJUnvvSz298/vOQ4l6LTSmOcv2KEUkIN+sy5jXVW40MynRu+BoO9jLismGKgRoXsIRHzPc7NQxs8iDQxY9l6rd68TUNvOjXDW//BHtOd/Rv2smAAoefZbyYvEeONNPraLyZmOEec/dYIJ/ky7Qzfwv7F+FrcO4twEZ1/BJ+3/QbHlir7l9b/xi92TiAdGlXRX4+rIbOfNgIYDVpNH+3C7dfPWJlDp5EznDUxP4hGJjDv6FiXZrs4mkCENpjbSFDBwYppayz8Ed8wZSkq9p2ZpN08/0yHw3TnmU7FXSwkgLcTyzEyuET3vFsSp/ywPJQAPi7pCwRsksqx9xKSTFKs4HyOAD7fa6JW7yithzo23EPy5W8aHObcGJn4JlEwpwH/5u9LOLBjQT2MFI4y//4zMkTcdoBasFjfu82wY2Nko4SwEGjTNlD7PUoAbQFZIE/LSIBkbc7KNA8vv7BJzrynrbuFsMjJAAHpQg1B4QbLQYGNBl6obDy+5yGSM1K7IZXKSnqG2Pypc47M8Orz+4AtBzlnzT4NexTIGTHDOMAgh+COUX9UVWRtRkO0MG7YthFqxd+I/HY51G48Nc3jEPXykLmr3CYFgftiIneUtGK2V4TzIOWPFdpAGjM4Xc1pc4VNGJUMkhsKBwxSS1PdQ6w4ELklR4svkbVwEjzDhsblA1U+c8G8WZ/qN9upHWMVCBvqLotr+DPe1p76J9Y7HBbc6CmMA4cpkioK0tf5D7RX02cHuv4joUKSSkGawmGycPVmF7+L4qvYzI7Nb9O3X4NwovLBaJpDAjOIN4fNz7Ap5T0jxlw4kArc4sUcix7C0W9j/nF5Ysxb163sDmRzArFQQtjavpZuU4t9EqQQiTtSALBHQsMGTs5UpGTPDpiTYW+77x3fO1KGkT+pniisKbPz5ALEzd+CeGOzu3On3PcS6N3sJrmQXX1SbWdKYd62w+b97uwXbQx8CbjF3uQ3m39oJYgxyTs2d03dbbj4asMoVkjbPrmsud4bOd+tPdTlePejgSBjCfuZeZCbqYOpnP186c/0n+3Ui+xfECv/wsC6Zf4j0YxVtj19jst8gxaA4kcr8KXn/rsWI9MkpFys1z+R5ojm48O/meesJaT9fNfvj52ZQSxsT406u4AvEkfmJ6pNJJbmIOb3w1R//I1Dnz2ZvYxzAUkszmYQJxx/2CNwCESFyiURbYNvuhB1KIQ8QDyaPT/ISQvZj/720VgXGYDik0/rU6u6B7n5gJQf6bAv8bXnMU2pfWBZZ2Nu5wQ4+I44hgt7cLlS+zopNBehYfNWuXlh89W3b7bLtvXF1rBJ4qJj70tPUZev2rQ1w+HH9gCr35417QXEFMEM85UxNQ2L37bZ1aOdGPTL7xkXNsaj8v6lMsxqzntnpFubmOtw5vnFQlWZZJ7f6AMEH898K3YxscgSXAY4Q8uWLJEhwbdnr21WRW9c5sKxFQsC+BecYSU9lC6N202LpWslkfMk8SiTMbeIhP8IrcbABi8P0sH5xRHAS94epE+mrnZxqcwrlId8I1X+m8ULoeN2897Fx7pbu8Vn89UOfsofNg1fVebfKCzGERsqGSFw7f98QhrxMJGzL7mzm6L/AVECiOoRD0SzEeMgRYRtKsR4qHGDQSLDhuuHa7DwI6gs8GTj8PMNy2NJ9Pw2/Ft/vLZRc1zX8jAXy4uF9O7I+Xrrz00zNn+IApIvi/xvxrjUZ5t9NCaU368oabR++IfnKS8PdtIADjbigyF5tWIH1yNnNtJpdStnzBHaMHso/zbIgY7kwwqSJuy1/II0ON0+OtPfkZYQWDl6Q3aXiBL7ODUyhVhxxFCzWHyxsIVQYX9kG74dNImuHMYeh4l/p2NhBNBiGPrShqhkljbM4YPMC6TuQurmFz9W15lvDnf5rt8c/qs7tLEJjGJmh4c5mviG41nh4LeJXRVrgksLEgZSQpmal8OQUEaHVtjPqX+YjxTbyBkD/s7N/qJjCOcxz9lCQlYqPdDDSZQsTA/vGfHh33i2YvODJJrv4LIHvo/2nuXmvKnNOTAva1bDkW6IBAIo+myqUpMq2Dch1WFfwqPR5jzfwAGHqpo4iPf/NCPDiB7HjJL77uPUuZiaxCqYVbAmsSvGOQQ1JVJJSD7rgj3QCmsTifH4RWudFMt38jHJKqRp87adzrTE1JNIYLhw+vln/b4gmZn829qMsDFmO8sz5oEb7TuE4ZNxi9w+hjOcETt7zt8TwIffUddbxgyL9WZ7KmOx6rEzM5qx9/m9yoM93VywNv2+WPv8jbXPJRMnFYrND3Nu4G9IUc17FOkrzjZIhq2Ygw5SdLzVUeMS5ganmhZ1DtKVn4zLkKSaZMvvj+2R7EsIFLCttmLzibmIynfWig3Otp3Cd1a87ye359t/gwFSSS6z7MMIQCDxXGxMTYsK2y6/vh2s1YHXMOQem+No8fcU9mGki3Yh5VnWPOcQczBqc87vZm8Xa3/lXfYUzC0wj8GMxceLizn2gmibOGsgzbHiwtrFFgcQUply9oPJr6s2OW2PFS6MOBya9oHoEKwTLj/Y//rlrpbV9PRFLt91sSCAfAghwUk9gcHbbuOOtK/GOSS/nEBQPZP/N1aIckcA277QR/0WbNwjeGRUaoGad9XGbU7dgJrSV7v5ByCTb9TNrZy0gAniS0p8aRQTbtSC1e6goF7IJLcSB176rRkxPpsBEjykjtiS+AXJ177p0kX+fsfp9ZxkAhtFxNosZm4wVs8eKy79D5AhFgU3UcJh2CZhkkPfgYBNn40P258oAcS7j03ESiy7wFiLnlsyqnRuS6jHuN22fQ1BsZytELgRciRqK2QBNaNejH6/kKrYJua37SeDx4kCiQQSQ19SwfPYhhHA0wobo9k9csOHyLP463ZNIzhmM2ibq3naxcPe/zv4PfOHIx1J8dVKPANhQeVIsctKVpIvvhtVuo0ljgjEs0y00Be8pM2uE4kWmJmhs0kPkFJwwbCDw9R5pnZkLGJhYKo3922vDXP2kUjdOHRPf3Wo26D9Au6kZMLJAjWaHwrHyIb/fCwpgP+7hYq4/ouJTipjMdyQarGhm7E8HsVP95/tNndU3ewDrHfUlxyCxPKq90Q/dyhZaCPasewt/BtpEoci65s1e967I51N3h3fT9HVJx+WQbKZ39T/zsgFjvAzJ/3L5b9aHe4uSJBNCgQDPPBCxMscxysOZLQZrGUrtM+6JiMFRJbvM0/aWPPBDkbbr/guHMZQ8SPFsGK/97rmZGcHtn7rds24u63ztm3x7yFOUgxmxC89t/EhGfakrGkcQ3y1r98PwmpAsDlAKebtS4q9yz8Z5+zn0F7w/1ZM8uZ7bPoOK/6ewNpE2m4mK8ytOo/1cevYv1Tzb+wlmb+EkqLwN3PiimoL+J11smjtZnfBo328nM94Y5jrK/+NdsD2LZ5HOowEzQrfSvgYS0lpKfNY6zyH0wD2nti5EtvTYqHyvhEbq4s9ADUqUj32NS5iqIOtQKxZt8xn3mXvhvjYd0ZNMPhv1u3qTdsdUSIXMZEZMIswRx27IFob/pkAdtjw0S7Oe9HCfkrqSQqaITLeWPw9/gbBO/ShXk4i76uL+Y31wt6BKRGXDrRGfiG49TeTlrj9ywQiZp/Kc1y0kGhii27Fd6pBAECkDS4ZxM4lHeMrQ+Y6s5D3Ry/IMMuwd9nPBs5Z6ezOzQad32wO+H17vF0t3XeOU1IWaQJYPZ307RlrYo+hzpc/YEz0NaY56XmAo406Atj4kR9U6cCK7jbPwWrhJkx6Zi8xQfbdR3uIb/ndpAP2rNmm8d8YAZNnNl6xRcgE3p5u3OMvGpwPCLOB6s9Us1aX5dm0/7ZN0NJamYt+dmgj0TygzL4ukj6HDGpfbo5mz+Tbj2FHxSJlMwEzv5hXmf3NRO1ZtY/qjTaxFWTji2biQDVSp1JZTfht7R6L2iSwy3A2Kb87cGl2kkn6g+0VoWkoDZ/o50g3h5KFN7E+RzcaNjHzJuPGimGvxSXjHTYRyAMecve3b+D6jMoxq4JEYPTC1U4qgn2Tb8TMe2xoFzapluGRy4HbvlEVxQs7wjsckFw+THpktozZzQX7nQOfiw6OQRRfpcl/Q/AY//f/eqyu+3JSxq3f1D5IkpBSQDpiqaaQvGx68hzn/HH+u6McmfE3ymg/o7dxPywPJA412L9OPTzD3glV72mv7vZ4tPqwcUWCctt3U5x9FQc8sQCRClKYi81qVMyQnDLepuKEoBGcmZzF305Z4gzNsec68aU0CbK/bu2CF/0ODOIh4nwvHueMrTke8e9zGkMSlmQ4kJj9KPWwDvvMXJGJMPB31HwQOvavtq8Pc7j7ZB/bxJf+eLTzAoeQIW1FSpZo4dDioMPUw4Is8y7aDqRBtIfqn4MZtTPEj1BLViAXrFUjXL7NdKw+RKMWcIFFymmXDN7xpUuEXmK+0r8o8TfJsb8nQEDxZjUHJ6Rw9/eY4RytkBShRqTYBdtSkvE3VOx1HuvrpPGxDnMuQNiZIiBA2nNfuwa64P3R7hJqpMD/ZjNPwIMYExwu3XjPQ3QoFkPy5m8mO3XrknWbnfp5zC2tdMQhB+jazydkxOpE7e3bFtM+0jb+FrXRBtMdu3a5ywT2wqTgm7NyQ4ZaHsl2KY8MIZWlT3YJR9LJBQXcudicf/Qhale/SqZQKPTfJ8mYF3FRhsT688/mEWYZmFhRcKx4sMeMjHXJ31i7SF/xrrf4kvyddYcWBucVTIlwVMF20C+cTVxWsWM1oYC/pzGWZCrCpIazj1BL/zq1rgvJRCGaBHsWEnW0NGQsGbkgbb5ZrFS/PVuT0UuCmVX5z75yTl3d2M4Fly7SBPBjSX+VRP4nS/qI3R+K8d20OtFdJ7nnSET7IWYRkr6LU5UjgJXu/EJ/bFbPbWZMEIs35cf247ZYqsQ+Tj00ekH2G6epTmk3evhx+2ChTku/SUcPVt5hQRKigkmNmJ8Sy44q1nchgWx5WJptmjkAZAclGxyLGXUht3/a/ccJtTMWs2/rQriFW76ZknF796WL/kZJm2zMHDix7A+tT2Y4D/6oNiGCVnwVeCxpoh0CLE5uzkhlkJIhyaPQNgFOowWMqI9DkXLgfT+5kAMcCFFVKY4Rvve1LyGIqoupa8qdpztDbrOV9L0Z440DdWLs3+LlwU5V6KsPeQfp3/E1D8ywiTNHnId6znDOCPEKEiHbnLDPIkyGXTL8d1DrEw/PCH+s+swRxX5DisHmdmeb+pniGprHOeSRGGjRS4u9zyGPpNyM3n2PVHMe8vsRPTwZv+rYHrZroD+9N8odrtjg1Xikd4aNJO9HLwNgbXHbMMlA6oi00Rx/uLQgzTPJA88vXL3JkSfmMxcCSD9kA9u2eCUeAYS44oTR6ZTDNWTe75lC97DPtKt/sKvbAoWzJ2GHiArP7B75Jn+PsT7gZFa1S089f95uqQMHG1qEF847Sq26DXHrnLBEscJCxfsWMME8gUPRQo74z3JYIx3csTNNKolq1y4ePMfYVNivpLOrosQ6oLPao1ivfzp6t4MNz5pTDFIf8gNTt28eYvXFIoDMEy5ZmMvEupzYu+YQ52tFkMh1eGO4+8ZYKlfe7X7Vidq4bYdbm+TsnbRknZtT8cxReMfsw5HGYZNmWVDMWY38v5BIEgKwhokUgdTaQvqYs42Po5FL/hYlq76QAgLFGEEA7TISvQhHx8evL7pf+c/6GjD7e9RJAzMIiNQHYxY6RzAuFTjLEb7Ll/Jii4rZBGPPfmhmDAS/P/vtERpza2snOeUSh+lKVEUfdQikP5BO5hcSSS6vmGxxyYvuG5yBzOGLPhitxV066I7vpmjbzl3OVMzspP3v9qWLvrTal3La8x9d1EiXtWzEfxZpAngvl9R08peWOC+tEAIGm8CPslrkKfztb5JeIXqApNiBz9IacwRQTc9W8zoHq3zpktpaq6mu+ssfnYQLux2CbCKUYzMfu2iNDixTMlO4AipBgoUIPGp3wCF25/dTHVFCUtLtT00coeLmxK0eKRsqWzyOzKvPDEbZ3P1wGLQT9aSM4mVExZKho7oiGDLSFfrAzZSNmvRLfqgB6uEGzCFx09eT3cbI9+KYYWnRbDNAddK+YRV3S7I+cyiaLQ+3Y27+fjw6327JgrX6ffdtZtj4TFpGHwjga7dQs7v03+X2idqGYrdI/3eTQJotlP3GQsfYndhSltDbbLH8PsSakxb6B4kwaj6Lk2fPkqQcCU7axrKPU+f6QYntOcbHxoFDyjcq9r+L59nI8bwjfiEFiQuqOMISReMW8juSIKRfvhE2qoh7u0+LSYhpP5HLgj/H2fRva13XpWmDdJjKxQ4DDkfUJie9lGb/FHXGwSaGkCfEoaOQTxPDeD9dm4+/HRoY+xNGAqkGUinUMTimsF6xQSPEi5/qyd/IIbELH2zvNm3CwiBtIS4Xcx91Y6xwSWCDHSPe+8z1O9vUE+nj2A8s1ESseeKr+QgD87eP02ye8ODG/umBMxo4T1ALAcNvtH9KnYPcXGDPMFVVNEcyNpMQbAvDYxJjJFY1H+3tcgib7abNfTQNeLfiwYsjiQXHtr6jFrZLafR7kOCxHiEeZPWIFhyAIA/7ly7pJELMSz9igS/ZIcbc431mZditxcLO/uZ7PPvhb/gdJy/WKqYo5sjjO2BYHWTAQcqLvZ+li2PPxpYOm0RL9RirH6ZhMeJhz9hlyKQ8/J35CbnG+QBsIe2mhrfnfWc8015YnWgxyCtr3vs2b9EgdenYSASrr3lgmQw7Svp2aIUy7jJhZwnmP37xQ+9EnfRIhYfpA4XziPXKGCKdM1vNeGMDwWUMLRyRP9ej78Tat3mGiwKSPC4OEGwu8EjXfvl9g4b/q5WL5GBOQFYnZxxkinmIpNBMe6JB7k3rZk5QqPC5uHBO2SXBvPSZC8yb898blSms0iuD57rz0AokkxRuSEEx+0g7K8vF3YPjYZehUZo3VpqXtiec37iyvv34Xf5ZpAngPyVhtPEtphIRAB6Q9GhWiz1Fv90o6RFMxxKwM0wjgJ3+pycvaO4WHjc2pHNMbP6bj2DCmJTKpBBscmRPIEgA9kh47UXt7LBRem/UfLdJczvDLge1DKTksErlnFQpahuFiofgqQRG9r0cDZusVJsmjeJmhoRj6cMdnds7Im9un9HsHD7eELOl67dkEAw8uogvZh5Qz5x7pO7vMd3dwtnkPxq7MMOL1b6bW9nKR8+UZZ6w+n0niNn3tnVBUf3i22sQoNPsHC2OHFkiILIEGbWUWbwP4et73ck6/dU0W8FYqnYMk+9tW98FVMWrETtCCgcmRPnDS5uJFHQY/FumAm7iH49d6FIQxSoYPhNeBtueWNI3kzjYuyY9itZlkkTDzQL+8lzUvonxWbtlu3MuQSoKmYL4WbT5aN047RCax6+H4OMYa3MwxeoLpMi3ZYz17Ug12SgpSKYglWQj8I3FbY3gPMFt3gzafRLE+9iV8S2GIbiyEVue7HhzHVXUGa8Py5DyMr84RBZ3aa9K5Uo7Qk/O4uia4YCG/FloD2K+kX0CmzHWJ4colwIcsTio+T5IGONEJh9U2RBAiCaOYOMWrckUjiSKl38oRp212FtI10i9fmpGtAGEA0G9iOrOwnRY6IloG4YRZBrNBO0c+XT/TESOnLTmnYhUApUfKlqIqNmZUa+RJ19qbO1BEPCchcggNYuaEyBRY39hLvO7b/9IHf4lkD5a6kX/e2JJ6/1Yijg1mZqe98xhyq39dEk4F9zK5Uq7cTFzAgv8zHOWJpF4eezd2PZymJPe0Lc1s36ZF2jUkcu/9NqzEDouxaipeY94enb5sefteyDj429r7eLTEXOTwnlR4b6fnDpz5r1tXVxC9m0caMiC8ef3R6tFnUoZqnWze7a4nKiKz3p7hLM95AzD4x2McGigQOCx8cN+mcuTT2qZ7+cddaiTOrOm40ntqcdyVJvNJG2cdNiBmRwg/HEdcEOLjD3a/ztECNtUohSwv7EO2VeZ+9PuauPsSX2PaN7lIkSg8poVy2aKiIHaHts9026YI55dKrGR7TVjub6YuDjjAmxrBmcSTBLwmqevp9VLi/RgKe6sz4QBYw0wRuxbmOuAMXPNT04Qa9/0/+ZnzLK/D7rqWLU+sjb/WaQJYEdJn2I6gSmUJDwWMH7CtfVJvOKzAycFv6Pvw+nEXNVY5/A48pJFHU8yCODbl7dwkjk85xhkbMEo5uzBBoBa9NEzj3AqKwvd4m8+UVUukqBPxy9yN38mOipGItaz0XLTf3fkgowbqX23OW/EwyErAoiBPuosRMwYqm566hx9PGah20jY3HyvNquHmyoSuytPqOnsX8zZAe/C61vWyZQ6DM9k7NBQ55IAnIN09oqN2r5zpyqWSQulQDGJl212FgsPyQ195JZLYaPDM9APJkyAY5OWcbselJ7QG3KCarfDm2nJ5Cm+agf7ybG3tXbBuf0STfhu3qLcdsvvV9KpGYg3hpE2qhYIOhsxMZ1MBRNrLDjcL2hSLWYIligBXLZuiwthEyV1RgosHZ8f9sXaxOOsz6wVLlZYr5nL3A0Z7zJUcagfUQ1jz4V0hCwNVsx2yZc4QFz4fgtO7H+X3+d4c4wDZEi6ZKPlvwc7STgHKsHMCbqNDSOSA/KLrtmUpqoyVTyXEqRSvrQL43ecoCzkDlIF4ppZoR++Xaz9nTzQhO1BTWpSaIvpF2us7HsgiMR4tLJi/RYXpJxiKiMuPqhzIDpIlzjEa1cq5wzesQtj3bIHsK4hh1FDc7/9KAG0fLH2DNihJsSz0woSv8ZVyzvHJw7k7tOXugthdB77GPFvJJ/YoTKOpe/6IZPazE+FyDjgvYqjSNR+2OqIOiVQPzbOXMi4NHExRbLt255xmOIhj8rNCIcfecAPL0QfudT5nvbWBn3zS5T0+b9ZoHP+1rXPLBd/0nI9+zEE/Yw1FsCfCy0hRtjv6A/21cTmjBbTyET/HrX55nckkqxx4iPOva+dszHsM3O5SyPpS5a5RGEjSG50imUVYV6z50C20Q5Q3hz2q1tHSBW5ECApu/vHqY7Eo4ngolPm7h/dZdzfD2NdxtlnmG+dWtbR7HRJHyYhFAgTZBMCiFmM2R/GWk8Wd481j6PjA+0bZsoAxDvmtLNyw1bnXOJnIDL7TiJWINFr8uxAF1aJ+JF4kmOagJkE0sGopoq9jwsmNrp2EaU9vggZuhIAACAASURBVN3XQlgcULMbRvJLQHwLUcU7ZoeKivqiptXc2eFrDnA48okwNpo43TR+qn+GuQgXoRnL1zu1dFbFzmaeiWqj+NvYG49Xs7q4UBRtAviBpJdJGoDZB7FgJZFiA0MZwr9gI1iYSgYB/PzqVk61ScgDX1QOcUNSx8b2/iVpoQQ5ULjtWcR4i3fl2+RYOjhTq7EJIVpnc+S2zAJFdcghQN5VixGXXYqaWIezhRTgNoJY2jyBWah4USHmx5XeD4vghzQg5hFBNpF0mscnqgO8unwPY+ztLj++piNi3GjJaGEbnMXHAh9L4WSqQDtcWaQ+yeFQ49DB8cSK720cTSVmdlv2rL/hIa3BuJ6xwvPaCvY9fjo5y09qEfMxyGWMIaGQXoKkcpukmCE4/6av2FW9Pmyei22G2oCbqB/uBSPrW1rVVfNIzlo7XGIFu2UcLMuBeRZb37mJQ8IJjYIkE5UL0jIuJdxmue1CMs4+oqoe7NAwU3+NXPpqJuxfkGz6UpQolja/Y4VR8Ekit2PIFCTaivWfFGYcfkid+HZs9cj7ylz0Y5CRng1CaOYD0TzQYBOVJFlst3PfHqF5qza5bDo43OA5jUo+VqGeWPm5efbhnjOcg5blFWVecLggoT+h9oGZqqMepIi0Rfq4ib+tc98Xr/g2gLHs0JAorNu83V1qjOgimUa6cOXxtVzQYC5wqItZQ2av6rdn69hfY6QJ8x01WBcDZq90ByZznWC/aDgInYRU04oRQEup5reDKpZA1mT6YE5SjMQxrxmX20+vq/vOaChL1YWd6o1fTXJSZd+sAixiea+b2YPvABK1FfMvBNjTjb2NY0YZzlAWON6iH/AbY/tM/zmORNkFE4kTZAePWBub/45dmKGmt2/3nUP4G8QcW0M/M4Q9y/7PxREC6DulMUZ+UHCXDGD/0hnwVnuol5N6mfMJ++aczu3c7zgnsd+Y8wvEBrMiLl8WBgkvXObhOem5pmkPwomdmp9Oj0sNe/js9LoJIn/6a8Oc3TWOj0/0neUwgRxzDsYr0Qsuz0FU/SDIqNX9zDN4zFq6Q9MQoLFB00X0ByIUkOYT+10K+GH7Z/9tfWHMLz62hhPWmHmSxUo0iSTPmjbHzGzw5sUz23dMspBpOIegzUFoQn8sOL0lPrD5aMH3ySl987eTnfqZSytrib05q32ASBIm6Y8VGm3uHS10ePUqVFGkJYCdWW8RIKpKIi4groTfx0WpYH7IIIA/3djGhbxgMaIiM08qJAtIA1n4JLunsMC48Y66pbX771eHzHOhNvxbLjdXVLBIDljcGAL/gpfgE/1cxHrqx0aHQ4CQECZJyC5JtU8AUemRRgrnAW6ZpmLjAEZ9yS0VMT/eaHwD3lsrHk2T0vkEkJhkSJAQaaPWQrJhDgx+e0j8rm9xmCOUSNC++b8TnS0UBzCEcFGX9mmLN13iZd7NLBLUHGwcfrw8SBQSCVOB8C43MKRlFPAcfvPuvLBRkbx/qBrevGc3av4Ncf/vZc0yZhebHHZ0vl0KJJHcjHizXvPFRH31dxePKZMRsNVj/efWiEOQ3aB5Ho/gaM5L/m7vcDj4wZ/pPw4ieDcakfLx9uMtUg9BWfH0JAyIOWtgtwVZuLtt/Uz9NQIIQeTCQZw5VHs/TF0WM/ZaVAIYlbz55gNZLVX6z20XCbmpV2fckybNsMTp9j4SDKQu5qTjq194BtU5eJnJACSEebbgwfYu+C3SFp/cx+sXfcJMYfXjKAEyl5cG/eJUhSYx6ILHfkdnjL1HsYOcDRy7XaSbvsdl1MsyOwKIrSO2cpgw2CHDIU3YDsaTrAffTV7iiFusNHV00AJQE/gd0wtSlUUvElwEJ6cHeeewwxYKghhVS5tDQzxvcfa861rUccGh3XxPT5NnIbBQv17boo4sVy+E/rovJjqNAY4abV4dmqFStzSN/kXDLtDmZUq99AlJodmy+k5hluuavpCfGdUzUjQcXPy9gosPXttIwLloE0cOiRB20VxA/Llf4+HemdYHeOFYhvkFGhKTrMe6ILEWWTfso6iVLc0Y88Y3c4kGra/fta/DyMbDD4/E3t6625AMMwokZXilonaMRcRs37Ic75YIwO2LZUo6yXaszCL8Tv51nBpQxVu60ljrIFa7drG25xFsnO4FzfcdKu2yBbZcwIkPCmEkqHW59AsJWhjGLEpEIceYOuEAYvaBFtDfMoTQBzNVIfQLtrsQQC7MfuxBs49EqkpGrmgxDYGlH/XPZrssQJ4xJcEELFoshAySc2ydsTmm2Nljzl1I6A8vv0+xSAVH+jeMrHYHoJIztWiQTgIfy+rwKIDfMgjgoNvOcM4R2BYh4TLbG2ytWIRtGxyckYyaBe1ngLDbjQV+5Dv8W5x9F2pT1J9MPKRtGOwiVv7bf8dm2Oxgf1arUtm4UBhBWPRge5f3k0LAVMTolpXEDF+tEstOYAGnbZPg/1nMl3w4xkknUcdxkyefqwUapj3f+9KCb1qUfAszYxuOtYlkA7Uqags/YK/lJuY51G2I3s2Gj79xUJgqxgJzWp1RFalPAP32/VRReKl+fmVaDlEKhyShBVBHErfMCqqCUw5P87a2wreb7Q5Stx/TU2mRxeGhDo1cjCc/+Tdk+5Ez98zbad/M/EAaZnaMsTZSIyvYzVn4h+hkIN4bt1UKZge3n14vTS13++77lR0mlnsYZyakzoRr4CCLligBjJJVM0zPbo3SByTSqH2QpkbzAfsXANrE9srijpn6LtqGSX4hCFxCkLwjeWYDJRh2doU+mUos+qxJJc0RIF7uVVszXDRwHHq41wxNWbI+Uxw7wv7gRY5kgTHH1IPQNEgKbA4SxBp7VtTeSPtRx3OQRUOXYLtEnlfygRMPEw9pJILRAhHGGWXa3ShbdpfKD/TIUPWDM7aGeOXilNPxzeHuIhElgOYVanEs/fogNkjjHj/7COchSUG6h7OX5eNG6nJR0+ou6DFjRjgkbP0wP4HsI7Gxdo0QcGnCqQQczEPW1L6QWjI3IDVGLYp6mGwV2C9S/Ev4//1vvHPcs3nsq+8g5jgL3d++YUZmCwgC0kwu+xXKlMr41FNfHpwpzBfkEVMD1JK0S/2mco2OBYQVYogjjU/ymH/++EbX/THPDnCk0cbD38vM+cjawp6Ry5wRxlhzn/bMRMn2TCR/W3bsVJND0wLNZ1XM3IFnYqm6Y+1bH45ekBHMmvfItUtYGSvkjcZ0Cls89ixMrdBwcMlB3Wx7ne1hEHkufH4YGusPgg8utsc9PyiTZNyINM9Z1AqTcqP6RzCBts0KGghMsrjQ3dQqLSOUXww7xhUewOXQbIttXZIKlgsK6yAaJcFsbJGs39a6Xob5kkknjVhiF1+l9I5iQQDB72pye6fb/PHfxOJDpPNfUiNmOfPy/8cMAjjmno7u9kysJZPM4XZPwm3ydyKetjRRTFILekmXzd7EDwngGyjbZ+GBh40Hhw1ie+xPCBmC6NxUNubZFQ8K2maT2fksPi67C+mxSGWGOinqaWuBZH0pGdIYklefWrey8y5rVHV/1wcOAQIQM7EbVCmvl3+e62KMsdgopjrlkHvq3CMzyCe2ZqZasF7Z4R7dMGyRc5PDLhK7DyvmvMB/YwyPW78Vf2PiIMP2hEJ9PkHxjeCj3pNWVzQZuX2vjyn1mmcwGP58I/HLd5eoyohAq0huYhXqsswTvvQ1+iyXDYKK4uCBfaaFAPKf8wO/IhlB4ovDTiwCCAnpfvVJLkwKGyrhTmKF5IkSwGgcNj+vb1bL1DDjAoQ9JZePT69onukV//v9Axc7x6jalRfNOQbjaYjpw2fGltBltWZ8EwX/ObIuEGoC8gkRiydps3lGPR9ccpxu/26Kpi1bnymbi10a/RR3sfpkF0bUlUieCXsUVXVamB/slvgd5zD2p0TLglWbdOZbw52neHT9IVGKRQC51Pl2yX4oHlSYkJH3/3qcLmlWw3XDHDksPJOlSiSIN5cjSABOV6gvuQQiAUEbQX/sMoxDDzbEOGFZNADDgnfeH7XQRU5AvU8YLCTlFj/OAnnTF0vdZd/qO1RxAOOFjHTSpKPxLldGVAxnJP8rNmxx9miGGSGjuKD5YYt4nj0Im1QcLaLryVTGsSTRRpiNAFrGHer09zz+m367+JUxxtX6zPrCvg37ZjtzTL3uk+bs1jF7wIh/neqEC36JRQBtTltEDKRaTaujzUwrc1dudPH/ILDYtr4zcr7LsIMqnAs/obc6NKqasYeZ0MDf06gHc4O3/3KMu/g1erK/M3fCJMPh/2S/DA9fy5rlCx+iGiRz8MH0h8tBtFiO+1iXXzvziQGKtg2tGLiY+YWtXxsLhB2QXoo5JZnXPVm7DthnW7EhgFEcS6Tb/xGRNc0Fs/CUDAI4o8s5LhUONhOvD/3VqU5NhI/qAnUmUc8peI3iaVbm/9u7DnArqnO7HgY0FowlFuyiYoy9oBJLYruW2J+JJSYYa8KLUaJGeSpYULChicSWaJ6Jib0LogIKxooSFcWuKIKVpmLAwvvW3Pkv+86dmbNnzpxyz1n7+/i83rv3v/dee8o/f1l/19ZMQ7NqWFYRf5d0o9FUzjg6i+ei9s8vOiO/jMaHRKFKUx7MHcuvLDfY3lwqvHnmXbBXB/SpUFjAMrnJfrDWMkHgu9tsXsu0ZaD4KTut00ZdYokM7hirGZukAPLrmsknbqaXSz7qBnmbXK4jqozwd4wVm/i71i/brS8bH1ge2VzLnbu2aKm1aIIA+9IdNOLo3sH6mMDypwM3bofJbc9Paxe/6NYWjjs3UwBpOaE1wRJcon3PGPlyEJvE+DYmWETb8XdMaovVpEWM8aVH9F69bd+miBIXZq/f1neroGD8nHlfBg/iuGzH6AvL3BOcmx82V/73xgHlQanG+DIqf7Ry7XPt023xf3HXEufc9crHgyQXNguyjs5hVhCzipVaQxz2VCqmD9qtw1BzSxvROZW48/dqJQePk0OLCN2HR9787w4UMObaopvOlKQ4OWNe+ziwPFD5Iakvr69oBR17IVriiNX2zrJ3Kv18rkTvvx2H/yuwBEctgPz4YrgKFTaeHf9udXftZWVWPq7DSpBZ0oglsLVc9UTAz0YlgPG4vCaYkEZ3MBkTbD28FtdabnGYq83iPc2Swn7mWmQIDt2wVGhokWOjUsgQGjbS5jz29ow26ySTD6y2OJ/FPNcDNw6C7NH70vGBhciNw3NxtfuL9wCVUtLFfPX1giD2j2uymD3ul9RhVgGIVjfGrTGOLsmi7pa0szkZi8es8sF7fi9QgIyqyP7uKkEMk+AHOq3mcYoYxxjjA+v+UoFkHXrG+PGZ6NZUTruWzMv1SL8fBCVKGXJiCWVx89763LTA4m/1xiecsH27WGhTyKOKt707Lf6Xa6X13OZw925hKbwGefZMLHHJ/C05wz46GV5Domxr0dAIJuqsNXh0ogXQaNcsK9vFixZ1Ugv9/bDNg/uAJea4ZiankUfRtWiyshDP3QocmHvaqrbwnd/16/80rAKY5ZlV7b5tCuDUwfu0FYKOLmK/a58KaETigrDdm9RqhvJ3cRYxVy6JS+mSYdLDoFGvBl9EbG55qzgw/v7M1CAehm6XaDN3rFu+hn3oBuVDjDxy5+7R0UXJBzOVRJaU4tfQ3t9fKfblx1/aS87ISY1CJY630ILBow8M+8qmO/m0ndcNLIBGqOu+lJhV98LJ5BRf2PhAiFoG+Tv3wUY3L93ZfPlY3cbohh57a0Y7jqk03PklSOXZ6ElMVtSKyNiOvr07uunYn2tMWkt0bYMfejXI9p1y+s4dFHH2Pe2+ye1oB5IUDs5Jt+TwAzcC3dYMxqerjS/4aIxf9IXlUhpZbFeWm5PB68xujbOouR8xZrmh7CSF177EGeIQd22WWhfno9uJsYPRZgqWuWsY9H946OKM9qUc3id3/bJ3YDWMZqwaWXCaDMq0BAXGJ/FlTSoWWsNp3bJgcjeGipYLWuOzNibK8J6O3n//fm92wHkYFzbAOZhxz4xuuvDMlWwft1ZhiP2Mf85imiwsxc6ULm7GXPHeJkMAY8yYMRm1ZDJchNQalrBkrjGu+89PTMHRtzwfUAYxHjSIxX32Pdz83LRUZcZkcp204Pxx/42Cyjk+jUkWDM9hLN6ii3QJrE2sOsF4UcY9W81gS9iz65mKAt2sDLGI3k8WM2ihM0nroCxL4LA+XU++t43ehFZVJp4xiztJAYzKXvK0EYG1jQqshYSUwoHriIZv8PzoQegTCZWhrDtfmB4kORATJtTd1nfLdglilgjHOvM7r7fwHHitMdHQfh81cLgKoLnRWRKVCYIszedaAJPeN9H3B/+fcY4fDGppDStY5ttt1FBuX7O+ulnZcbgxhp40VDwP+/iJ7vOpd2a2UQKxihM9dRYjTLLxb+bNlQJY6qLM+PezmLwZkj0z2Ksfn70RGW0K4MwLDwgUq7hGDZ8WP6sQEteHDxxeBHRXsJUKmjcFkNlO/Co21nzGLJhlMeN+8cL0OUEqu3EfkQ7mLz/dpC2rKUneb25/AfxavO2F6YH72A3etTF2I5Lig5lUliRiX9pxZnIzyUcfVJYk4t687o1vP9PqEA1Y5t+iyjV/R2ti9Hz4+yQXsEsTwT2Sssf44Xxxt3Jw1p+WoZ9s2mpliDauhVxoDxy7bUnxVteW8ZBx16RdOyaIGXT7b7RyB7n8ICCGVCxo5eXDm1/XTPKhwjz6V9u2BV1HX1gu/1pSjEzaRka9/GGQmETKA2aGxj2EOSctk3yZs7EqBzOro81iKKM0MSWBDDsQ+2iMqo21WDFa4ml5oYvZsgDjzpAK4P3HbBO4eugWdJtZ3plQQotsUuOLhdQepBGicsQkl5N/2DOI+aM7kC3J/e+7Z/azl1GaokBrGD+W2OL6sewWX5JW1YAvX8s2/d8Rk4MwFvvgNFoS8tUxxpEWFiqJpCxiRmpSMzcllSxaWKngMTOc67HsUj4rGMLAsBM2s1Cx2lFcM3J3/o0v+BsO3SwId/Fpp947Oai4w5jEt2Z8gUM269HO+m8hJrxmei6/RJvbkooCYwVt7TaXq8TQ8shkw6TGvnS30zpsjclftBpTwaLVkVWYWI/eVwHkGTKGjbWsfT9C4zwtadjZx3DSR6udRzTRizJpUWWW+ApLLRrcV1RWLcyDHjnGzdIjYrRCVK62W3vZIFGFBPnD9m2t5mQ1iNNw4b4YDnDHEa2JfqVa3PsmOoZZwaTmYdLn3n95KiCpt1rt1pcfXQyjooGFyUhkmDBic3q95n7+mRTAUoeR4e8nM0Y55P4jNfpA8s6y5GtISWOi2hTA+ZcdhK6L0FvdsV0w5nUs1rULjt9+7dQl8EIwBZAd0y5EcvMxGYEUDXQj9Bo6NnBj5FFEbFFWr5TxB1TI+EIzrqm0hTObbwEWBGbsEUdt3VYL2R1jDzGWyeEXnr2szToTZ/EkhQXN4SQxdZspja4C2PefEwPXJF06NpfLtWjjyc5OczozxqyxJjEV2KgC9+zUWYHbctnFF1Iu2JhoeTbfh6m7j2jlDNc9FsWbe6IrlcpDqWYu4KRrIUqhEaVciJPPWrm0+jAWiYTBFtMY/eLmWP7ODVqn0t9/x56llt3u7+ZiJ9H5iZGx7py0TFp92LQMeI4xGoZMCwFARYVf2/vFKMl2LbI6BUNA0hrXQMV47K/6tFWr4f3wxJRZQVKOVZlgktfR26zhtcx3Zs4NsiBbXZQrt5VBZPyd1ST3EhTTaecrHvdSFOKuARO34sBRAW2QJYKZa5p/p4uMlh26ZsndafcQk8pYh5VhFazyQoXIaE3i9mKWFvKFMsHG+Nwo76rH3w54EOmeZrPnGdfs8oRG5Zplib+n0k7Sft8YSrOwM2SDCYH0VFy0D9nMWptlORvljOHHZyCTSohX9IOK4yxDudQ1Fhev+vDrHwcxZIxVHjrmjcBj5PvMYp1zWlBpZEgKiYl7XvkqixxrsbTRmuwm187YMMtyTVtFDmOVYLwuCbGpRJFM2kKzNrv4kbYs8yT5jD1dvOsibeFdpdbBs41L6Ewad8Bfnw5KykUT2szqb/c15VLRfeTNT4J3/pw5c6QAljqMDH9nTvYlYTk4DmOwHs0M/SNchG0K4ILLf5pBfHxXt9JEXKKGO8qsPPbVvP6QMYEC5HtTx63AXialvjKjY0mhQGJRVi2Z2H/HWCuMPeSMO4lfLXSJmnUmycISt05zB9DqcUEYwOv2cx+o0cSSsg8pFGDKspEz58E9SmuSFqPGPTEYfeTRpRVAs0AkrYkcdMfc8nwbFMxmY5Z6WmNyE+PBmNXMDE1mJI/9dZ92dEA2nmu1Yun8HZNMWG83S7MXFjPSmaASd77cn8WR8e9pGfC8zrJaaH3WyxcTK4CQjiLJ8mdy6NZeeSl+VC2C9YeODX5NihVyZ9Iqbpb3LC5zo+mgAnjwZj3a4mGZQUtWgnKam+yRJoc0FsSXGZnRZvFuVsnDEj3S5JkCSBf3gX+dgA8/m9ehrGV0PK85c48yKYDPCF4f5lqM3gs+Fqp7Xnw/iGXkdTPppB3bxYOlrd/KyllVmGh2/zaXjQ94Vc3lbc8rKgpcN8Ms4hRAn2cMZblsDbZOcyEyZIgfIdPmzAsyo30aPS50vZOuK8kjEnceTAgcdWzp5xXHWjx0qRAmn/VG+xhVkxGrW6wwsSI/KuOT2d74+PNgny7/YJ75os8ql5anlDzzaEQT2ux9Y3GyXDs9dNwTn49SAEsh6/93KnX0adDX5tLRjGKYEYCTHFGFKoAjJ38QcNqRfJIvlrS4HSOgtSylJHep/7YX8u9ldZWdPvLlINOSGYDMSFpl6Y40NPaQcwlnbW1mGWEZOJ9m8TmWSRz38OHvstx4PvO6fSzw3GgOfB7O0TlIRWJkpPybGx8VtyfLyC21VmaYMgs4aU2WfWxxRXEUNtE5GNfEDxTWsmS2d1pGMs+TdEC0BrOeMHn9SDSdpTGwffvhj7WVjYo+VPn/3B8Dqa22bFwiTpY5q9XXJdfl/Xv5o28HZanuPGKrwAW430YrBRZpn2YWSH4MkebFSi8mZUT7yLQ+VOz+NmEq7j6yd5Zh7foaL56VHGSQfylXqimA5MJjrCQJmCc42fxxi+E1Z6TtS5w2IsCR1wefo1Nn/acDNRaTjBgjTA7NpEbXKetCs2WxPPF5yFhMKhcMz4l+AFnmulm77NlIjsJP5s4PaH/KUQDjKIssZKVUkmASFka7Y6TzpS4I7sn3eUVZN018L6hEZIaBUvKz/N08HlbX3Y29dNk4ssj07Uscshg3zKMRTWizLGhjmzAF0LiFpQD6nkjpfqvSmACAqXyvON1vZI4FAHIVWitUAaRQKlJuuamk5Q4kJ9eDr7Y9KIpQAO2B58bplIartRrCc9PnBKZruqRdXiwbbw85fuExpofm+OjffJUocxu7GVzuOjlXQKia4avdZ59xfVY7+0FMTSFVTZNr2ZzWJ+2lneWBetLdLwbEokl4mrvFEjWiGXdxa6YbdNi4N4PsObrl7eue4Q3M/HTjJ7lW8oYxc5NxNaz96es+s7kff3tGUFszSmbNvzOIntmSrMvrUtqQUmH5JRfNe5RVG+dSjPCMrLygUT9kWYh9DNHNeAyrywwZG5BSp8UQZpFfbl+jdGEMGZ8Pxg+aJteSQ6gM7H3tU0G1k6RYPfcZQr4+1uZm/CjvSSOczrsHq9/M8UmuyTjZFoJhtD5087vhPxY3aWTP9mykC5/ZvKa8mmyyMzC8KKlSTfTZ55bstL+ZCzGvhY2Z2LRaJ9WUjuLA+/JnW6zaLtQm7RyYnBgl1c57btFxF419IyC/Npe863qna9sqdBU1X/Q8GHs45XSy2ZVuRo0UTWgjLdPq5z7U9iHCa4Zl8K4/tLW6mBTA0tj69shuAdxkT5y4Uyu3WEtLS/Cv0u3M+18O6gfaS55xGlH+qKxrsGDqrNmSrKPJouSMEUuKO+OXDYuSu6TK7sObP/sqgBYQnES5wZuDWc58oVa6laMAMs7oqiemBNVAorxX0XVzT77xN3Qj0UoXl+lNuWZ5tGxJn9g4CzkwV17a1z3XStf4/AtaS+LlaeayivsYYcwmG5NTyLXJ4HQ2K26fZ75qjnEpRnjNm0s+a+gF12xKCpOYWBebsXQ+Ft1q7ZcflYxr63/XS0Gyjg8foSmAxIZB8aT6eOi49OQnXnPRqj3l7tGNA2SmpVu2ME22PZuN8YA0S0c5MZ0WF2nPO66dIRWjjtkG65w/Gu/OSq7SUWpPlBXHFUhLKBNrSGCfp7GqDmlTXKUjj5ykMRb/7vsOyDI3P1J/f9/kNgWQCTJMlCFWvgptlvncvpwjiUEgTuYp97wU1BuOlnQ1BdDCXCh3/6WmY805Lwdi5s+fj+HDh/PHTl0KLi/ORY+LiwGcDuDESsYAZtmEfWUWqQBaoG2aKzJujaxlzEB8Fgj//Pw9s2wj6GtfwL43v/ErkVT6vD07cq5RHnm/ynFd+W6iHAWQc0Rv7KR5uadoVRLfNUb7mXXNSmf5uLeGjH4tICyl4kcrRRq+XCvjpvgxkLcxAWeLYeNRKmaMySmsic3GQH+fpKW8aypqHBXYpQaMDMTxmrfYX9I7+FKN2FoshpY0MKxHSitBEh9iUevPI8dcWxbDlCbDVQDJRcgSXKU+5njN+bons6zfnk1ZkuvMO2M1W1li89DN6VhqbdHnHf/f6l2TFovx1HHZ7D7rZvwvOVWT6KR8ZMT1IYk2aVMO3rQH/nl4e2L2vDLdcYxlZUnFGysg28p3Wia6PSeqpQBGeRnT8LLnrGWIW1/SPbHiiXk5SO1E7l1j/JAFsIircKEMxvkxC5isx1QGzwyrkNDMN9eZKnABf/TJTCy/rD/LfhFLtTgTU5pYI5hZwL5KVNIaeFMwFmnfDTty+SWNuXTcm0Ft0/lfL2hHP+C7T6OK8F27Kar1oAD69OdPZgAAGPRJREFUZkomYWEkxaXcl3QDbbDiUonks75Ys5/F85APkYSwrJ9MCoW0xvNlogJrL7MWbBoVQlaFPm5e49djVnea66vfbS8E5dPYmFCRlImfBZ9K93UJZXnNWxmsUspu2j1LBYL3Q4+zHgyqA23ghFhUej8+8s1VH7VsxI11FUBSwrDFeQ7csbzmjLTcZz2+ffJcy4NGvYKzHni1rT50lGZpqQEjAl5Qi3mmdY2Zu1YmzHdt1exn3iGrEFLNucudi0lrJFgmm4NbA5lxoJuvsnTJZ1858/P6ifIypskz2qK4j3K+35MSd6QAlnNK8WMHhRVIGKzGp1AiD+Ds2bPRvXvHigvFL2mhROPQKloBZHwYA7ajpMVpexn+6FuBiZ3VEvJk3TLDiYHapTJRow/8pLJbvOlKEaYWdTaMT6KLy+oq55FLl20Sh2QeeaXGGKeUZcX5uLeMSoEvWbL6p1kj87w0o2u2mCXye23cI/necquauGWbSmFQy7+75bl4/1oZrCj3l+8aiTfpLFjakFYCJpH5Znj6zlFuP7PURi0bpRRAJoRQqbdYpzQl2DdDNcte8lzLFi7B+FXS2ESrV9DaxRjlzhCvGn3mVsuzkuWMfPvmOUtf2WnXZVIVobgxrF3NGvOWIe47vxRAX6SK7RdYAGuhANIkT0uMFXgvygKYBx77anHLqeWRk2UMb2YSYsZVJqHywMwr35idLPM2Ql9LQjAiUR/3lp0xY2b+MfG9gPYkyV1TxIPWeBbjaiy7Z3DCnZOCYupsvhbkejhDFyNm21JRiHJ/+a6TslhqcNBuvbDioAcyvzx85ymnnynqPuEGrgWQrmNmRJPfL62ZEmycbuWsNar0ZL22jKOVbApkdSiCkqeo/ZQjhxj7cpGWM0+lxhbxXMq6Ns4ZJeZOk2FMID5eGVeOFMCsJ1NM/5opgNHlr3PeaLzxSfsaksVssbQUi2EycuDSI8rvwRvr9F3WxTkxpenKl94cEnx53oiGBWmTe4oWW1qbWhIqEhTxoDUFMIlWyE7IKG+yvqRrfcIuRnewqsdfJ3hlyMatm7KMz4zJMyzBVm/NFHUfy4arAJLmh5ySaWU0uVfG0tKNmrcKUhJeVkYty8eFcVhS8SN3nk+Wfb2dV9J1Fq2j3hnWbWsc+/rHAYkzS/NVq/HeXGHJbkGVD59m9FczzmnBMjEFCJJkSAH0Qbf4PlIAAVgKfxbep3KPgjdWlGC1XJnNNp5lwxgf4/NyM+7A47ZdA1eExKlJeG192figisztff3KJcXJsbKEpR6EVEa3HDY+cMP77KNezthVAI1wOG/1DsqyKhj1sr/oOk68axIuHfeWF52KkeHyPEmLQV47K+FW7f2Vk+RloRY+WfbV3lee+Xid0WtQipInj+xGHUPM4oi5k/Zrsc9ZGQ2kANbmCqobBbDneaODuqC1eAkaiWclsvCSjpU31pm7rtdW87E2x9+5Z91y2Dg8M3W21zVz63PTcND1z7SrnVnJ3U94d1ZQ1syntjUD1O968f3cFBeV3Efa9cu/8X41t8/E/jtg01XI4pCt8V6oNKFtthV17M1ykeSRTKpP7Y447tbnAwJlYsPqKSx1uUPP8qqa5F3/VpeOC0of5nmuMmifoTk+bu+866vmOF5nLIn41AnbV3PaTj0XMWMpwY89ixyQ1umwG57FzT/fMlPlIimAtblM6kYBXHvwaLw1ozYK4O3PT8eB/zehaokXPGreWAN3Ww+DWlr5F9WyI7DpxY/guWlzvF5ud096H/te9zSSyLezz54+gtxvv7l9Eq75ycYlS6wVPXc15HU56R4sWNCqAD74ykfY7eon4EORErc23gt9t1oN1x28aTWWnmsOUwCN/DhNCGlyqDzlUYZzLS5lEBVQVkPJQ31iZfqyxnMVvYei5PE6q2acd1HrrqUcYsa66DPO9atylXetUgDzIlfeOCmAAO596YOAsJVl3krF6pQH98LRUgDLR5Jlw5gw42PdIGXCHtc8Katr+bAHEqxEGrFnbNJOVzyOvK5C3guVrmhQ7rYtVnPe0L3Q7VtdyhXXKcbTMs2MzpsO36Ih9szrbMvVlsbTJ+zQKfCvh0USs7jKLEWvTQpgMYgeHlK/kF34m7D27+kAHksQLwUQgFVtSMrKLeZo2kvhjTVot/UwUBbA3PBmKR9oZesG77E+Buyybu45NbAVAde1SI5HJgu8cuqPsN53l8wMEe8FK4OWeXCVBlh5ws5C1VMlWDrVNE9OmYlVv7NYbK33TrWRKi6W9yaTmGYP3qOis0oBLAbeXwF4PVT4/hOSQZ8DYH0A02KmqBsFkPVR357xhZc1pxioFkqZTR670+8HC9JfsPcGRYuPlccb6+zdewXZqGr5EMgSN2rZaRfvswH679gz34Qa1YbAlBlzMfG92dhvo5WDRBwm5LwxYCesvdwSmVHivXDuHr3wv7vU771w8j0v4aKH36jJ8ykzoBogBApCgLHTPbovhj5rLVuQxHgxUgArB+9MAH0B3FXPCuBRNz2H655+B19ftHflkEiRzJdQ0bU40zbC+c7ZvRdOlwKY+7xXP+dB77qjZuW9fP8N0W+7tXLPqYEdEbCEl7zJAvwAW2rRb6FLl/+qW3ilANbt0WhhDYCAFMDKHOLWAMYD4Kd1a72p9q1uLIAsXP7NggWZKngUCdlyZ9wPugeP67NmkWITZVEBvPqgjXG0U2S9KhM30CSka3nqnVleVhmjtIgWtm8gOGq2Fat7XIrzsGYLLGBiK3LvE29awHQSIQSaCgEpgOnHfR2AX5B1gQmkMV0fBrBT5PerARgH4HoAAxPE140C2FRXOws0f/I51lxm8bq2etT7mbAO8ewvvsJayy1ecqkvvf8pvn/hw7j+kE1x+Ja8NdSKQmDi1NnYfNg4TB+4K1bqvlhRYutKzqn3TsbQsa97fWzU1cK1GCHQCRCQAph+SHzDpT1ZvwTwqSNiHQAPALgJwGkpogMFsF+/fujWrVvQraWlJfinJgQaCQHjNGN904M26dFIW6v5Xsy6+uFZu+G7Sy5a8/VUYgGn3TcZQ8ZIAawEtpLZnAiMGjUK/Mc2f/58DB8+nD+SSHROtRGp3+CT7EhsDOB+AJcDOK/EcFkAs+OrEZ0QgXdmzsUa547GXUdshX02XKkT7qB+l2wKYKmqJ/W7g9IrkwJYGiP1EAJ5EZAFMC9y7cf1AXAPgLMA/MFDpBRAD5DUpfMj8MGn87DSoAdwz5G98eMNVuz8G6qjHVj5p9mDd0f3xbrW0cqKW8qAEZNx/mhZAItDVJKEwEIEpAAWczWMAUCWy7lOrCDjBmkJHBIzhRTAYnCXlDpHYObc+Vj2jFG498je2EsKYKGn9fy0Odjk4kfgUyWj0ImrKOzpd2ah740T8eIpP6rirJpKCDQHAlIAa3POUgBrg7tmrTICn8/7CksOGIkRR/XGHt+TBbBI+F/96DP0GjIWc4fsiW93XaRI0ZIlBIRAEyAgBbA2hywFsDa4a9YqI/Dl19+g2yn3YeTRW2P39Veo8uyNPx0tZFut/p3G36h2KASEQOEISAEsHFIvgVIAvWBSp86OwIIFC9DlpHtx/9Fbo0UKYGc/Tq1fCAiBBkJACmBtDlMKYG1w16w1QIDk26+fthN6Lp+9XFkNlqsphYAQEAJNgYAUwNocsxTA2uCuWYWAEBACQkAICAES/82Zg6WXJgWgeACLuiB+C2AYgHMBnJkgVApgUWhLjhAQAkJACAgBIZAZASmAmSFLHdALwIiwOsjdUgCLBVfShIAQEAJCQAgIgWIQkAJYDI6U0gXAYyH334kAxksBLA5cSRICQkAICAEhIASKQ0AKYHFYng6AFsDDAYyVAlgcsJIkBISAEBACQkAIFIuAFMB0PK8D8AsArOoRV7f4YQA7AdgUwJ3hf2dJASz2IpU0ISAEhIAQEAJCoFgEpACm47k4gMVSunwJ4AsAzwAYGCqB7C4LYLHXqaQJASEgBISAEBACBSIgBbB8MNcA8CaATxwrIfOqqRzy9xvFTBFkAffr1w/dunUL/tzS0hL8UxMCQkAICAEhIASEQCUQGDVqFPiPbf78+Rg+fDh/pM4ypxLzpcmMc6tWew3lzsc9rBwRciuAJwEMAfBBkgI4e/ZsdO9OXVBNCAgBISAEhIAQEALVQ0AWwMpgPQbAo8oCrgy4kioEhIAQEAJCQAiUh4AUwPLwyztaRNB5kdM4ISAEhIAQEAJCoGwEpACWDWEuAVIAc8GmQUJACAgBISAEhEARCEgBLALF7DKkAGbHTCOEgBAQAkJACAiBghCQAlgQkBnFSAHMCJi6CwEhIASEgBAQAsUhIAWwOCyzSJICmAUt9RUCQkAICAEhIAQKRUAKYKFweguTAugNlToKASEgBISAEBACRSMgBbA4RFcBMBTA7gDI7jwFwCEAJsVMIQWwONwlSQgIASEgBISAEMiIgBTAjIAldF8GwLMAbgFwHgDWA+7Jah8APpYCWAzIkiIEhIAQEAJCQAgUg4AUwGJwPIfV3AD09hQnC6AnUPXUjeVzVK6vnk7Eby06Nz+c6qmXzqyeTsNvLTozP5zqqZcUwGJO4/HQ5UvX744APgRwQ2gN/EYWwGJArrWU/v3745JLLqn1MjR/RgR0bhkBq4PuOrM6OISMS9CZZQSsDrpLAUw/hOsA/ALAAgBxdYsfBrATgNcArAXgcAA3A/g+gHsB/BHAhVIA6+BKL2AJesAVAGINROjcagB6mVPqzMoEsAbDdWY1AL3MKaUApgO4OIDFUrp8CeBTAM8AmA9gW6fvqQD2jfzO/hy4gN999110784f1ToDAgMGDMB55zHEU60zIaBz60yn1bpWnZnOrPMh0PlWTAVwtdVW48KXBjCn2juIs6pVew1FzHdNaPXr46kAMmN4ahETS4YQEAJCQAgIASEgBMpAYFUA75UxPtfQRlEANwfwGICfA7gVwPcA3Afg0vBfFBzuu0doPcwFnAYJASEgBISAEBACQqBMBJYCMC0MdStTVLbhjaIActd7ATg/jAV8H8DVCfF/2RBSbyEgBISAEBACQkAINBgCjaQANtjRaDtCQAgIASEgBISAEKgMAlIAK4OrpAoBISAEhIAQEAJCoG4RaFYF8CwARwFgCjAziPsBeLFuT6mxF0a3Pd33awD4DMAjAE6JJOlsHFL6bBFWeWHSD8/QbTrT2l0nd4QZ97sAGBMuQ2dWu/NIm5lMCecC2ArA1+FzbzudWX0eFoAVwjh20p2R53YygNMAjNOZ1c2Z/TTUITYBsCSArgBc/uEinoU+MjID0owK4MkA/gfAHgDeADAwTB5ZD8DczAhqQLkIDA4Td14AQNqfKwBsAGCzUDBvqFcBXAvgbAA8p5EALgJwWdhHZ1ruKeQfz8SrQwHsGv6jAqgzy49nJUdS+RsRPv+YLEcaLX5UPa0zqyTsZcm+DcDyAPYHMBPAiQAGAVgdwFd6NpaFbVGD+exbNnx//TmiABbxLPSRkWsvzagAvgmA5SQuDxFbJMzA6R9WD8kFpAYVhgC/oljXmTcUazmTCHxomLVtX1XHA/gNgHXDWXWmhcGfSRCpCx4FQAvSOwDMAqgzywRj1TrTavQkAH4wRZvOrGrHkGmifwP4S+gB4cAlQvaKrUO2iwv0bMyEZyU7swoZP4BdC2AR95WPjFz7ajYFkC7fWSE5NB+E1kYBoAXqpFwoalCRCND9exyAtUOhVNZJ60OLrTVaMqh4kDyzi860SPgzyeJ9w8o7fEFROTcFUGeWCcaqdP52qDhcDOCHAHoCeCtkTrg9/CjWfVaVo8g0ySEAjg6t7J8AoKHilwDoEmT4jM4sE5wV7RynABbxLCwlg6FTuVqzKYC0WNBSwZvmFQexG0MW7mNyoahBRSFABYLxZAcAeDAUSpM6v3r5ILS2fhi7RAp1KoA606JOwF/Or8O4v5ZwiKsA6sz8caxWT5LfvwvggzDmlpYlVkris48vLsZE6z6r1mn4z0NX75UAdg9dvjNCd/DjAHSf+eNYjZ5xCmARZ1RKBjkEc7VmUwBlAcx1mVRl0I8B/C10+d7tzFjq60cWwKocT7tJaJ2lBZZuKCoVbLIAVv8cssxoz74hrPTmDLwfwEQAi8qalAXOqvTl+/l1AKx5T8sfy57yOXk9gB0A9NWZVeUcfCeRBdAXqRr2i4sXmx4G195Qw3U189SHhTGZBwF4KAIEkwyicS6/DQPZ02IAdaaVu6IYk3JVaDW3j8jlwpjNm8KqPBcCWNnJhtOZVe48fCW/BuCWBAWQ2aW6z3yRrE4/xkF/HCbEPedMSeYKWm5pzdWZVecsfGaJUwDLeX+dAOAfYZJqqXP2WV+HPs1mASQAjPNjFjCpR6gMngngZwB6KQs41zVU7iCeBbN79wbwrxhhzICiu55ZwMwYptLHMn+MZbIsYJ1puaeQbfxiYZKOO4q1tUmHQNc9sxN1ZtkwrUZvJk+dGsbTPh/ec1QkaE16WWdWjSPIPMek8IPqdyFNFt9bVOL3DLO3dZ9lhrTwAfRCMfGDCiAZKljajRRL88OwinLPyOcdmGtTzagAEiim0R8bHtQE8QDmunaKGkTXIeko5oUCeU0uCF9SphBuCOBPIWUFM4NJFXNOZAE606JOJJ8cPvBIh2A8gDqzfDhWetTvw+cdE6hoEeR9c284qc6s0uhnl89kHVJe9Qnd9Ay5YI17Jl6x6cyyY1r0CHpErnNq+do77EchX2MRZ+QjI/O+mlUBzAyUBggBISAEhIAQEAJCoFEQkALYKCepfQgBISAEhIAQEAJCwBMBKYCeQKmbEBACQkAICAEhIAQaBQEpgI1yktqHEBACQkAICAEhIAQ8EZAC6AmUugkBISAEhIAQEAJCoFEQkALYKCepfQgBISAEhIAQEAJCwBMBKYCeQKmbEBACQkAICAEhIAQaBQEpgI1yktqHEBACQkAICAEhIAQ8EZAC6AmUugkBISAEhIAQEAJCoFEQkALYKCepfQgBIVCPCHwalp0cV4+L05qEgBBoXgSkADbv2WvnQqARERgLYHxY4/utsGQg60hXurEc1LkAVqv0RJIvBISAECgCASmARaAoGUJACNQLAkUrgIsAYL1q1qdOa30BnA1g9XoBQusQAkJACKQhIAVQ14cQEAKNhIApgFsCaAEwD8DXAN4GsFG40Z8D6A9gTQDvhpa7m8K/7QiAMg5xFLo1AOwA4FQAawP4CsDjAH4byt0OwIMAugL4IlQWjwXwz1B53AXAmFD+XgDOArAOgPcBXAPgEkfBpLJ5PICDAWwC4E0Avwbwr0Y6JO1FCAiB2iMgBbD2Z6AVCAEhUBwCUQsgrXLXOeJpqRsEYH8AEwH0ATASwB4AHgNgCuAdAI4C8FmoQFKJmw7gBQDLhjK/G46neLqAz4mxAFKhMwVwKwCPAjgUAOVvCuAeAEMB/CFcI/s/B+AAAFMAXAxgPwBrFQeRJAkBISAEACmAugqEgBBoJARKuYCpXF0eWt5s31eHPxwTKoC01vUC8HoKMJsBmACgO4DPPRXAKwFQaTzQkXsCAM67gaMAHg7ghvD/+XsqnSsB+KiRDkp7EQJCoLYISAGsLf6aXQgIgWIRKKUAzg1duHTjsvEZyDi/RwDs7SiAi4b9bHW0DJ4RKmqLh+OWDF25TDbxsQDeB+BFAKc4W/4xgBsBUBabazHk/9P9TDfwuuF/i0VL0oSAEGhaBKQANu3Ra+NCoCERcBXANwAMBuBmAfN3AwH8PWH3VPRoAWQ8H5UxNv78Seg6phWPSiTdt884ihmtdpwrmgTiKnS+FkA3ZlAKYENeptqUEKg9AlIAa38GWoEQEALFIeAqgEycYMzd7x3xTLDoB+CwUIHrFiaHUFF71rEAugrgEgBmAjguVCZ7AKDbmHGDZpnbFcBdAFYFMMOZz1UAewMgHyATTNiXSR6MAbwQwGUpFkBaGJk0QkugmhAQAkKgEASkABYCo4QIASFQJwjQekel78wwC5iK1YphQgWtdmxUwH7nZPROCvtzXJwFkGOYOczs3eUA0Io4LEwEMQWQbmRaFakIdgkzd+naZQYyf2dZwHT5Uk5PAB+GiiQTPYxmJtpfFsA6ubC0DCHQaAhIAWy0E9V+hIAQEAJCQAgIASFQAgEpgLpEhIAQEAJCQAgIASHQZAhIAWyyA9d2hYAQEAJCQAgIASEgBVDXgBAQAkJACAgBISAEmgwBKYBNduDarhAQAkJACAgBISAEpADqGhACQkAICAEhIASEQJMhIAWwyQ5c2xUCQkAICAEhIASEgBRAXQNCQAgIASEgBISAEGgyBKQANtmBa7tCQAgIASEgBISAEJACqGtACAgBISAEhIAQEAJNhoAUwCY7cG1XCAgBISAEhIAQEAJSAHUNCAEhIASEgBAQAkKgyRCQAthkB67tCgEhIASEgBAQAkJACqCuASEgBISAEBACQkAINBkCUgCb7MC1XSEgBISAEBACQkAISAHUNSAEhIAQEAJCQAgIgSZDQApgkx24tisEhIAQEAJCQAgIgf8HoYiYESFPQ5oAAAAASUVORK5CYII=\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(num_dim, 1, sharex=True, sharey=True, figsize=(8, 6))\n",
    "for i in range(num_dim):\n",
    "    axes[i].plot(xs[:, i], '-', ms=3)\n",
    "    axes[i].set_ylabel('$x_{0}$'.format(i), fontsize=16)\n",
    "axes[-1].set_xlabel('Iteration')\n",
    "fig.tight_layout()\n",
    "fig.savefig('student-t-mle-constrained-traces.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot first and second derivatives with respect to $\\mu$ of negative log-likelihood across sampled configuration states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dls = np.array([constr_func(x, mu_0) for x in xs])\n",
    "d2ls = np.array([constr_mu_grad(x, mu_0) for x in xs])\n",
    "fig = plt.figure(figsize=(8, 4))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(dls, '-', label='$\\\\frac{\\\\partial \\\\mathcal{L}}{\\\\partial \\\\mu}$')\n",
    "ax.plot(d2ls, '-', label='$\\\\frac{\\\\partial^2 \\\\mathcal{L}}{\\\\partial \\\\mu^2}$')\n",
    "ax.set_ylim(-0.5, 5)\n",
    "ax.legend(loc='best', ncol=2, frameon=False, fontsize=18)\n",
    "ax.set_xlabel('Iteration')\n",
    "fig.tight_layout()\n",
    "fig.savefig('student-t-mle-constrained-neg-log-lik-derivs.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualise configuration states samples in 3D - confined to 2D manifold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(6, 6))\n",
    "ax = Axes3D(fig)\n",
    "points, = ax.plot(xs[:, 0], xs[:, 1], xs[:, 2], '.', ms=2)\n",
    "ax.axis('off')\n",
    "\n",
    "def init():\n",
    "    points, = ax.plot(xs[:, 0], xs[:, 1], xs[:, 2], '.', ms=2)\n",
    "    return points, ax\n",
    "\n",
    "def animate(i):\n",
    "    ax.view_init(elev=10., azim=4 * i)\n",
    "    return points, ax\n",
    "    \n",
    "anim = animation.FuncAnimation(fig, animate, frames=90, interval=20, blit=True)\n",
    "anim.save('student-t-mle-constrained-3d.gif', dpi=80, writer='imagemagick')"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:phd]",
   "language": "python",
   "name": "conda-env-phd-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}