non_ideal_gas_models.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Non-ideal gas models in Cantera\n",
    "\n",
    "In this example, we will demonstrate Cantera's ability to handle non-ideal gas equations of state.  This particular example will use a multi-component Redlich-Kwong Equation of state:\n",
    "$$p = \\frac{RT}{v - b} - \\frac{a}{v\\sqrt{T}\\left(v+b\\right)}$$\n",
    "and will compare results to an ideal gas approximation:\n",
    "$$pv = RT$$\n",
    "We will compare various properties of a mixture CO$_2$, H$_2$O, H$_2$, and CO.\n",
    "\n",
    "First, import the necessary python modules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cantera as ct\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['axes.labelsize'] = 16\n",
    "plt.rcParams['xtick.labelsize'] = 12\n",
    "plt.rcParams['ytick.labelsize'] = 12\n",
    "plt.rcParams['figure.autolayout'] = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Constructing a phase diagram\n",
    "For the first example, we will construct the phase diagram in the saturated liquid-vapor region for a mixture that is 99% CO$_2$, 1% H$_2$ (by mole).\n",
    "\n",
    "First identify the range of temperature and pressure values.  Store the number of pressures and temperatures, and initialize the matrix of specific volume (m$^3$/kg) values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Temps = np.array(range(282,380,2));\n",
    "P_crit = 7.38937e6\n",
    "press = P_crit*np.array([0.5,0.75,0.9,1.0,1.1,1.25,1.54,1.75,2,5,10]);\n",
    "npress = press.size\n",
    "ntemp = Temps.size\n",
    "v_spec = np.zeros((npress,ntemp))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First, construct the \"phase diagram\" using an ideal gas object.  \n",
    "\n",
    "Start by loading the gas object from the input file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "Ideal_gas = ct.Solution('input-files/non-ideal-models/co2_RK_example.cti','carbondioxide_ideal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now loop over the temperatures and pressures, and store the specific volume at each set of conditions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i, P in enumerate(press):\n",
    "    for j, T in enumerate(Temps):\n",
    "        Ideal_gas.TP = T, P\n",
    "        v_spec[i,j] = 1/Ideal_gas.density"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "We plot the results, seeing that (as expected) the ideal gas model is incapable of predicting phase change."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "\n",
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       "                evt.data);\n",
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       "            fig.waiting = false;\n",
       "            return;\n",
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       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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i++hR6pNknZSyktg75+viCd7AcZNpF1J51EERInA926+8InKQOcGRjgw2oF3G4XOfb7kIGWB4H3r/1+B0EFAbn3aLrslObkZ3wptrGvy6r3Fw0AUlZXhUGNL9DTQ41VXVRXu+6QH8vJeo06dubCynMbKTdLoxcPDg2kLThrBcDFyvRPx7tobKOmqwmQxP3WubO28tmUtIvy8Ub9Ne/SayU3i/zWbMhPzcHrlE2ba9z+3QnUTza8tqfDnyatWI+vkSag72MPyxIkKr5d1wY5nO/Bb8G+w0bfBpb6XZBVTedb5/QbcmAeo6gILowFF9m9OKo/z1NKqhkBS9kc4r7/PvAmWx10ggp/QuQ9NgEUQxUIHQV5BMRr9LLlIdWaiE5zq8FeWUFxaBnOPQEbXqaZ10LGGfOouRbDNnJrg+cgRRUWZqF9/LcxMh7CSfe3aNaYBTL169TBs2DBWssoXv7sRjVzPt6hWWweGU5pxIpNrIeUUaK0Hfg/nQfKhQHvzLBW33EIY5oeJO9tDSYn7hhGxI0biQ0AA9IcNg/FPy7mG7YvyJt+djMeJj/G/uv/D6rar5aZXMEUXxgIhFwGbrsDw84KZQRVTBLhAYL/HG6y7+QpaqsoIWNYZair8P9AJnfvQBJiLyGEpQ+ggyP5QhGYr7zBeXJjcGg6W1Vl69OXlucUlsH4UzEy4ZGcNZ30t3nRVVcGlpcV48LA+gDI0beoGg5qdWLlK2niT1t+kAUbfvn1ZySpfnHH6FT4GpkG9mQFqfE9sFdcQigLN/49o+P0eDX1jDQxb4cQ5KMSv106tUZqdDeMVK6A/lN3DkbQGEr3tz7ZHVkEWFrdcjGENuHmQkla/3OeRY7KtDYGcRKDTz4DLXLmbQBVSBLhEoPt2T7xKzmH6AJB+APIYQuc+NAGWxy5/RYfQQZCRWwD71e6MlVemtYGdBX9lCWmFRWjy+CWj64a9DVrocP8KWARbyqsJBQVp8HosSZ4cHC5BV4fdj9W+ffuQnJwMV1dX5h8uRureQBTGvodWe3Po9eD+ohdbG4WiQLtzIAQRAamo29wA3SdxXzNalJyMSFcJn7HlmdNQt7NjC5VU65Nyk9D1Yldm7vEex2FnKB+9UhnHx6SsGODXP793Y28Dtbh/mOHDbCqTIvA5BF4lv0f37Y+Yj+RRBllug9C5D02ARfB9EDoIUt7no9XaewwS12e0RWMz/iirCP0ZoUEj44GjLRpoqYtgByqXCTk5YfDz780Y7dzaE+rq7BqXbNq0CXl5eejTpw/s7e05ASNp3ROUZBdC7391odWaX15pWQwWigLtzGo/ZLzNhUNPS7Tqy33ThFwPD8RPktRx1wsIgJKWfB4w78Xew+yHs6GooMhcgFNXruLf6xengSuTAdLpbnE8oFzFO97J8iWjayoNAutvvsI+jzcw0lGF96JOUOKhOc/nwBA696EJsAhCVOggSHj3EW3W32eQuD27HWyNtXlDJSIvHy5+rxj5vk4NYKlO/3BUFOyMjEd4ETiGWebaPhRKLNrNlpSUMF3gyCD1v6QOmO0oKylDwjIvUqGBGqMaQr0hfzXlstoqBAUaYX4gDBCECaLLuIao58g933a6229I27oVKhYWsL4rKWuSx9j5fCfcgtxgrWeNy/+7LA+Vwuq4NgN4dgyo3Qb4QcKgQwdFoDIiQH6X2m64j8TsfExwscLSXg3l5obQuQ9NgOW21V9WJHQQxGbkof2mh4yB7nPbw9qQv7rc4JwP6BLwmtH1wrkRjFVVRLADlcuEpKTLCA2bByUlLbi2l1wolHVkZ2dj2zYJBdikSZNgwgFnbPG7fCSv92dkGs5sjmqm/MWTrH5/okCzrofha7bKKqZC696lfsDJnyTNQYYsc0RNc+4fNBPmzcf769eh1bkTLHbtqpB9bCZPcZ8CrwQv9K3bF2varmEjqnKs3ekAZEQALvOATvK7aFg5wKFWViYEfKMyMNRN8rvE9xvgf+IidO7zpX2iNGhyjGChgyAyNRedt3owHnvMd0XtGvy9NvV7l4u+zyMZXa/aNoaeirIcka4aqmLjfkNk5Hqoq1vCubWkdEXWQWLvwIEDzPJ58+ZBS4t9sloQk420fUGMTJPlTlDSFN9DjhAUaNFB6bixJ4jhRp70a3soV+P+lnVUn74oiIhAzalTYTBzhqxhUaF15AKc6zlXZOZnYlHLRRjeQD6MGhUyksvJuWnAZmuJxBEXAevOXEqnsigCckVg0cUgnPGPh42hFu7MaSc33nDipNC5D02A5Rpqn1cmdBCEJ+eg23ZPxjivhR1grq/BGyqemTkYHPiGkR/TrinUeKCB4s14kQiOiFyPuLjfoKvrAAf7s6ysCg0Nxblz56CoqIhly5Yx/8t2fHiRiswz4VBQUYTpSme5/qBKa7sQFGjPbsfC5/Ib6BioY+Sq1tKaKvW80sJChLewB4qLYbZ9O3S6d5N6LZuJyXnJ6HKhCyPiWI9jaG7YnI048a8NvQacGwkoKAILYwE1SuUo/k2jFn4OgfyiEqb1cU5+MeZ3s8W0Dn8+2MkJLqFzH5oAy2mj/0uN0EEQkpCN3ju9GBOfLOkEIx3+OjjdSc/GqOBocgiGRNdmokyORBAS/2nCy9B5SE6+DAOD7mjaZDcrc588eYKbN29CR0cHc+dyQ+X0/mE83t+KgbKBOox/5L+bUEUBEIoCzf1IKMJ9k2HZpAZ6TWPH3PHZP2avXiG633fMR3Vu3oCqlXzYN+7H3cesB7OYC3A+3/tAQ4W/B+iK7jUv828tBnz3ACbNgEmSgwM6KAKVEYFbIUmYfOIZYzrfh1+fw0fo3IcmwCKIWqGDIDD+Hf63+zGDBCHArqnF38W0q6lZmPQyFuqKCohuz30SIILt5N2E5y/GIDPzEczMhqO+7UpW+tzd3eHl5QUzMzNMmDCBlazyxVlXIpHnmwRVGz0YjOOe6outkUJRoJ1f54/U2Bw071ILzgO4P2nJvnoViQsXQUFNDbZPA6CgxH2Jxeew3/V8F/YH7Udd3bq40u8K2+0R//r97YGkF0CrKUCP9eK3l1pIEfgCApOPP8Wtl8loaVkd5yZz/1bqa8ALnfvQBPhrOySHz4UOgqexmRiw14fxNPCnrtDV4K9m82xSJma9ioO+shLCXMSXHMlhu1mreOLXB7m5obCymoU6VjNZybt8+TICAwNRv359DB06lJWs8sXpR14i/1UmNByMUH0ge1YJToz6i5C/UaAdPA11Le4vo/3TZnLq7DbbE8UFJeg0ugHqtzbh2i2kbNqEzIOHoNakCazOn+Nc/pcETnWfikcJj9CnTh+sdVkrN72CKCrIAdbXAspKgcHHgIb/E8QMqpQiwBYB0gCLlD8UlpRizXeNMbxVbbYiK7xe6NyHJsAV3jLuFwgdBH+9Bfryl27QVOXvYtqRhHQsev0WpqoqeObciHswvwGJj7xao7AwFba2q2Buxq7j1rFjxxAVFQVHR0f06tWLE/RStj9DUXIedDrXgk5n+f+ofs2JoHu3cddtJ9Q0tTDt0JmvTefk85zMfBxb4s3IGrjQAUZW3NeNxo2fgDwvL+gO6A/TNfJjYuhwrgPSP6ZjgeMCjGw4khO8RCsk8h5wor/EvHkRgJahaE2lhlEE/guBM35xWHQpGCpKCvBf2hl6GtXkDpjQuQ9NgOW+5f9WKHQQPI5Mx/ADTxjDXq3qzmsP8H1xqVjxJhF11FXh7dRABOhXLhPKykqZNshlZSVo0mQPDA3YXXTavXs30tLS0LFjR7Rr144TMBJ+8UHZx2LoD7SBpgP3XLdsjRSCAi3uZQZ+3ymhrJuwvR2qqXH/kBnh0g7FaWkwWrIY1UeNYguTVOtTP6Si03lJK+4j3Y/A3oibRipSKRdi0v3VgOcmoIY1MOOpEBZQnRQBThAYst8HT6Iz0aWhEX4bJcxdDaFzH5oAcxJK7IQIHQQPw1Mx5rCEt/XN2p68doHZHpOM9dHJaKiphvst67MD7htcXViYiUdejozn9vbnoKfLLuFYv3498vPz0a9fP9hx0Da3tKAYiT9Lymlqjm8MNWt90e2SEBRoL9zj8PhCJLT0VTF6XRvOMSnOykJEa2dGbq0jR6Dp1IpzHZ8T+DD+IWbcnwEFKDAd4Kr8BbjDvYBYL6D5SOB/8uNZlstmUiXfDAKJ7z7C+c/mV7uHtUCvptyXZEkDptC5D02ApdklnucIHQT3wlIw7mgA42X0up68MjOsj0rC9tgUtNDRwA178dWH8rzVrMXn5r7GE78ejJzWTvegoWEps8yioiKs+fNV+ciRI1G3bl2ZZZUvLErJQ8o2ya1io3kOUKkpvpa4R+dPR3pcDFoP/B7Og+TDWfvgxCuEeiXComF19J1pxxrnfwrI832CuDGS7oA2Pt5Q1pfPg8eeF3uwN3AvrHStcK3fNc79EpXA4gJJ/W9xPtBvL2DHrvxIVL5RY74pBPY+fIMNt15BW1UZ/ss68/rW97+AFTr3oQmwCMJe6CC4FZKMySeeMrVAEWt68orIz5EJ2B+fBmc9LVxqzv1NeF6NF4HwzCwfPH8+grGkfbtAKCvL3rgiMzMTO3bsYGRNnToVhobs6xnzwzORfvglI9NslTMUVOTDRCDt1jAUaKMGoriwAD2n/4gGLh2kXcpq3qVNT5H0JhvNOlqg7WAbVrI+tzjz2DGkrF0HZQMD2DySHzXX9HvT4fHWA73q9MJ6lyrOiBD3BDjUVQL/zBdAdfnQzHEeLFTgN49A9+2eeJWcg0H25tg0SDg2JqFzH5oAi+CrIHQQXA9KxPRTz6GmoohXqySni3yNBeHxOJaYgU7VdXCyWR2+1FRZuckpv+Ply9lQVFSDa/sQVqf1sbGxOHz4MIPVwoULoa7O/rQ21y8J7y5FQlFTBabLnUS3DzmZ6XCbIjkpHbZ6C0xsbHm3kSTdB398hIIPxXAdbotGLmac60xcuhTZFy9Bs21b1DrwG+fyvySw47mOSPuYhnkO8zC60Wi56RVEkdc2wH0FoG0CzA0DFAibOR0UgcqFQFjSe/T49RFj9KnxreBsXVMwB4TOfWgCLNjW/79ioYPg6osEzDrzAlqqygj5hd2lqq/BOTMsFueSs9DLQBcHG9MTlK/h9c/P4+IPIyJiNdTUzNHGWdK+WtYREhKCCxcuQFlZGUuXLmWVTJfbkH0nBjn346FipgWjGeLrCCYEBdqH94U4vEDSaOa7H1vA1EZP1i374rrogYOQHxKC6mPHwmjBfM7lf05g2oc0dDzfkfnoULdDcDSW1KZX2XFyMBBxG2jUHxgkeXCkgyJQ2RBYdzMM+z2iYKSjCu9FnXi98/M1bITOfb5kn0IZObagQy4ICB0EF56+xbzzgdDTUMGLn/58xceT5xNfxuBa6jsMNNLHrobio8jiyW3OxEa+2YzY2L3Q0bGDo8NFVnJ9fHxw+/Zt6OvrY9asWaxklS/OPBeOD89SodaoBmqObMiJTC6FfKJA09LGtIOnuRT9RVlvw7Nwddtz5vNxm12gpsUtz3ZZSQnTArmsoACmGzdAt29fufjlEe+B6fenM7pIBzitarKX48jFYDZKSkuBjZZAfjbQczPQkpumMWxMomspAhVFoLS0DG023EdSdj4muFhhaS9hf6OFzn1oAlzRCOJhvtBBcNY/DgsvBjMd4EgnOD7HqKAo3Ml4jxEmNbC5vgWfqqqk7NCwRUhKOo+aNTuhWVM3Vj7euXMH3t7eqFWrFsaOHctKVvniNLcgFERlQ8vZFHp92V+q48SovwjxPHkY/tcuwti6Hoav2cq1+M/KC374Fp5nXkNdWwVjN7lwrrMgOhpRPSS1+1ZXr0DNlv+yDqJr74u92BO4B5Y6lvj9u98590tUApNDgH1/sndMfgwYNxaVedQYioA0CPi8ycD3v/kyU/+Y2RaNTHWlWcbbHKFzH5oA87a10gsWOghO+MZi2ZUQGOuowXeJhNOTrzH4RSQ8s3Ix3rwmVtuY86Wmysp9ETgeGRkPYGoyGA0arGPl57/RnJ4AACAASURBVMWLFxEcHIxGjRph0KBBrGSVL07a5I+SjHzo9rSCdjvx7W85BVqDtq7oOWMeJz5/TYjn6XAEeyTArJ4e+s1t8bXpFf78/a3bSJg9G1BWRv1nT6FQTT6E9oT+jNCg9bDqgY3tNlbY7kq1wO834MY8QE0XWBADKCpWKvOpsRQBgsDCC0E4GxCPekZauD27HSdlb2yQFTr3oQkwm93jaK3QQXDkcTRW/B4Kc311eC2U1PTxNfo+i4Bfdh5m1DLE0rqmfKmpsnL9/PshJycYlrWnom7dH1n5eeTIEcTExMDJyQndu3dnJYssListQ8Lyx0BJGaoPqw+NpgasZXItQAgKtCvbniMhPAuN25uh/ffcn86m7diB9D17oWpjgzq/y4+KjDTAII0wvokLcOd/AF5eAmy6AcPl12aa6/in8r5dBPKLSpjWxzn5xZjfzRbTOgjPwiR07kMTYBF8H4QOggOPorD6jzBY1dTEg3muvCLS1T8cQbkfMd/SGD9aia9LGK/OcyDc63FbFBQkoZ7NT7CwYHfrfufOncjIyECXLl3Qpg375gwlOYVIWiPpKGgwtRlUa3Hf7pcNhGWlpdgxepDcKdDIBThyEc5lSD007cD9qXj8tOnIvXcPOr17w2zzJjYQSb2WtD4mLZDJqPIX4Mh1mK0NgJwkoPMKoO0cqXGiEykCYkHgZnASppyUcLR7LewAc30NwU0TOvehCbDgIQAIHQT7PN5g/c1XsDbUgvvc9rwi4vIkDBEfCrC8rimm1WLPO8ursSITTu6lPnjYEGVlhWjcaAeMjHrJbCGRtXbtWpBmGP3790fTpk1lllW+sDA+B6m7XzD/arKkJZR0VFnL5FLA3yjQ1myBiTX3p7H/tDc/r4ihQCPjf7PtYF6/OpcuMbIiu3RFUXw8DH6ci5oT5HM5y/OtJ6bdm8bo9/7eG9rVtDn3SzQCM6OBHX82Lxl3F7BoKRrTqCEUAWkRmHQ8ALdfpqClZXWcm9xa2mW8zhM696EJMK/bK51woYNg1/0IbL7zGvWNtXFrdjvpjJZxloPPS7zNL8IaGzOMMxffK3IZ3ZLLsuLiHHh4Sv4Qt2h+Cvr6sre7Je2PSRtkMkaPHg0rK/aUdB+C05F5MgxQUoDZqjZQUBQXT2r8yyCcW7mE8XnqwdNQ1+I/aSPNL0gTDDLGbGgDTV1uHwpKcvPw2sGBkW/hth9a7fj9/pYH+r7Afdj9YjdqadfCH/3/kEv8C6bkxSngyhRAWR1YFAcoy6fGWjB/qeIqh0D2hyKm/KGwpBRrv2uCYa1qicJHoXMfmgCLIAyEDoLt7q+x3T0Cjc10cH0G97fU/wpxY68QpBcVY6utBYaZ1hAB+pXHhA8fouHjK2HpcGp1B5qasrMspKWlYffu3Yys6dOno2ZN9mToOY8SkP1HFJT0VWGyUHynZJ8o0DS1MO3QGblsfOjjRDw4/gqqGsoYt8WF80snH54/R+z3kpa81g8fQMVYPmVFM+/PxIP4B+hu2R2b2sun7EIuG/Y5JVenA8+PA5YuwJjrgplBFVMEZEXgtF8cFl8KZrq9+i/tDD0NcTzECZ370ARY1ojicJ3QQbD5djh2PYiEnYUerkxjXwv6X9BYewYht6QUexrWRn8jfQ5RrPqist7549mzoYyj7VyeQUVFdgqbqKgoHDt2jJG1ePFiqKqyP5l89/sb5D5ORDUrXRhOYl9SwfWOCkGB5nUhAoHu8TCuo4sBC+y5dglZZ84iecUKKOnqwsbXh/ME+0sGd7nQBcl5yZhrPxc/NP6Bc79EJXCnPZARCbRbAHRcKirTqDEUAWkQGLzfB37Rmeja0AhuoyRvjMQwhM59aAIsgigQOghI/S+pA3a01Mf5yc68ImL+8AWKy4BDjS3R04D7jli8Gi+w8JTUmwgJmQ4FBRV0cA1jlewEBgbi8uXLTOJLEmAuRsaJUHwMyYBGc0NUH8J/fW1Fbb66eQ0i/X0gTwq033e+QNzLTDRsY4IOIxtU1OSvzk9euQpZp05Bw9ERtY9LHmj4Hpn5mWh/VnJX4EDXA2hlInspDt+2spafmwpstpGIGXkZqMsvSw5re6kAisA/EEh49xFt1t9n/uue4S3Qs4mJaDASOvehCbAIQkHoIFjzRyh+exQNpzrVcWYif8XxxaVlMPcIZBA/1bQOOtYQF0uACELhP02If3scr1+vgKqqMdq2eczKXC8vL7i7uzOlD6QEgouRsus5it7mQruDBXS7WXIhklMZQlCgHVvijZzMfLQZaA27ztzX3cWMGIGPAU+hP2IEjJfJ53TSK8ELU9ynMHvz+PvH0KlWhb/HoVeBc6MABUVJ/a8q/3XjnAY9FfbNI7DnYSQ23gqHtqoy/Jd1hpqKkmgwETr3oQmwCEJB6CBYce0ljnjHwMWmJo6P4+80J7e4BNaPghnEL9lZw1m/CrdO5SGu3kRtQ0zMLmhrN0JLR3Z8rzdv3sSTJ0+Yy2/kEhwXI3G1L0pzi6D3nTW0WonnlIH4JgQFWmF+MX6b7clA23tGM9RuxG3NO2HyeN2yFUpzcmC8aiX0OWpm8rVYcAtyw87nO2GhbYEb/W98bXrl/vzmQuDJPsDEDpjkUbl9odZ/cwiQ34hu2z3xOiUXQxwssGGguErThM59aAIsgq+E0EGw/EoIjvvGwtXWAEd+4O/yUlphEZo8fskgfsPeBi10NEWAfuUxIezVUiQmnkGNGu1h1+wQK8PPnTuH0NBQhv6M0KCxHWXFpUhYJjmVrjGmEdR5oPtiY6MQFGipse9xfl0AY/bINa2hU0OdjQv/WluUmIjIjpLOjZZnz0C9WTNO5X9J2JwHc+Ae545ult2wuf1muegUTMk+FyA5CHCaCnRn13lRMB+o4m8WgdDE9+i5Q0LDeGpCKzjXZX/ZmUswhc59aALM5W7KKEvoIFh8KQin/eLRuYERDozmr0A+Pr8Qjj6hDEoPHG3RQIvbhEBG+CvNssCgSUhPd4eJ8QA0bMiu9ezBgwcRHx/PNMAgjTDYjuKMj0jeJEn2jGa3gIqxuB5uhKBAC/dNgvuRMCirKmHitnac08LlPHiAt1OmAgoKsA3wh6KmfDDvdqEbEvMSMbvFbIxrMo5t6Ih3ff57YENt8voAGHwcaNhXvLZSyygCn0Fg3Y0w7PeMgomuGh4v7AhFkVFTCp370ARYBF8boYNg/vlAnH/6Fj0aG2PvCO5vqpdDHJGXDxe/V8y/+jo1gKU6e+YBEWyf3EzwDxiI9++fo3atSbC2XsBK77Zt25Cdnc20QCatkNmO/DfvkP6bpLzFdEVrKKopsxXJ6fpPFGha2ph28DSnsr8kzOfyGzy7HQuDWtoYvMSRc53p+92Qtm0bVGrXgvXt25zL/5zAd/nv4HJWQpXo1sUNrU35uzMgF4f+S0mEO3BygGTGvEhAi/KWC74n1ACpESgpLWMuvyW/z8ekdnWwuCf3l3ClNuYLE4XOfWgCzHYHOVgvdBDMOfsCl58noHdTE+wa1oIDjz4vIjjnA7oEvGY+fOHcCMaqKrzpqoqCvb074GN+HGysl6JWrbEyu0jqwlavXo2SkhIMGjQIjRo1kllW+cK8pynIOv8aCqpKMPuFXyYRWYwVggLtjz1BiAlKR71WRujyA3uM/+l3wtwf8f7GDWh36QzznTtlgaXCa7wTvDHJfRKzzmuoF3RVZafiq7ByeS+4txJ4tAWoYQPMkLzdoIMiUFkQ8H6TjmG/SVrT35jpgoam4rusKnTuQxNgEUSz0EEw/dQzXA9KwnfNzbBtyJ8tP3nAxe9dLvo+j2Qkv2rbGHoq4jol5MFlTkU+9GiCkpIPaNRwG4yNZX8dm5eXh02bJM0Lxo4di1q12LMTvL8Xh/d3Y6FspAHjOfy9RZAVUCEo0E785IPs1I9w6lcH9t25Z8V407s3CiPfoOa0aTCYwQ2Tx9fwPRB8AL8++xVmWma4NeDW16ZX7s8P9QDivIEWo4C+8nnAqNyAUevFhMCCC4E4F/AWtkbauD1HPh0iK+q/0LkPTYArumM8zBc6CKaceIqbIckYaG+OzYP4u0jjmZmDwYFvGARj2jWFmpIiD2hWTZEk8SUJMBnN7Y6henXZG5YkJydj3759jKxZs2ZBX599Q5KsSxHI80uGmq0+av7QWHSb8P8UaMPgPEjSOY3PUVxUAreZHigrA3pMboI6dty+Pi8tLER48xZASQnMdvwKna5d+XTnk+y5D+fibuxddKndBVtdt8pFpyBKiguAdRZASQHQbx9g970gZlClFAFZEMgvKoHjanfkFBRjQXdbTHW1lkUM72uEzn1oAsz7Fn9dgdBBMP5oANzDUvB9Swus688fTcqd9GyMCo6GAoBE12asGjl8HdWqNePjxzh4+3RgnGrV8ga0tGRvNBEREYGTJ08yspYtWwZlZfYn8WmHQlDwOguarYyh/92fjQNEsgVCUKBlJOTizCo/BoHhvzhBz0iDUzTyw8IQ/Z2EvaPu7VuoVrs2p/K/JKz7xe5IyE3ArBazML7JeLnoFERJrA9wuLtE9axAQJ/7E3xB/KJKvwkEbgQnYerJZ4yvjxd1hJmeOC+cC5370ARYBF8HoYPgh8N+eBCehpFOtbGqH3+nd1dTszDpZSzUFRUR3Z6/RFsEW8q5CdnZzxDwdBAj16XtE1SrJjudzbNnz3Dt2jWoq6tj4cKFnNiavDUAxakfodPNEjodLDiRyZUQISjQIgJScOfASygqK2DSr+2hyPHbjndXriBp0WIoqKvD9mkAFBT5f5uSXZCNtmfaMtuyv8t+OJuKr9abq5hhan9JDbC2KTA3lGHaoIMiUFkQmHAsAHdDU9DKqjrOThLvRVWhcx+aAIsgooUOgpEHn+BRRDrGOFtiRV/uL+uUQ3w2KROzXsWhuooSQttKXufTIR0CaWl3EBRMum8pomOHV1BQkL2bj4eHBx48eABDQ0NMnTpVOgP+Yxa5VJf4sw/KCkugP8QWms0NWcvkUsBfKdCmHTwDNS3+G7A8+T0KAX/EoIaZJoYu5765TMqGjcg8fBhqTZvC6txZLuH6oiyfRB9MvDuR+fzRkEfQU6vCrcxPDgIi7gCNBwAD2XFuy2VzqBKKwJ8IvPtQCMc17igqKcO6/k3wfUv2dzz4Alfo3IcmwHztbAXkCh0EQ9184BuViQkuVljaq2EFLK/Y1CMJ6Vj0+i1MVVXwzJm/RLtiVlWO2W8TTiE8fDlz8ktOgNmM69evIyAgAHXr1sXIkSPZiGLWln4oQuJKX+b/N5jYFKp1xMUM8IkCTVsH0w6cYu2vNAJuuYXgzbNUWDsYott47t+qxI0bj7zHj6E3aCBMVq2SxiTWcw4GH8T2Z9thqmmK2wPlQ7vG2mhZBJSWABusgIJsoNcWwLEKl3rIgg9dI2oETj6JxdLLIaimpAj/pZ2hqyFetiWhcx+aAIsglIUOgkH7vOEfk4XJ7etiUY/6vCGyLy4VK94koo66KrydxMdJyJvjHAiOit6J6Ojt0NKqj1Yt/2Al8fTp0wgPD4ednR369evHShZZXJiYi9Qdzxk5xgscoVxdjbVMLgWUU6CZWNti2JotXIr+oqzTK58gMzEPjr2t0LK3Fec6X7u4oCQtHUZLl6L6yBGcy/+cwB8f/og7sXfQuVZnbOuwTS46BVGSHAzsk5R6YIoPYMTfoYAg/lGlVRqBwft84BeTiW6NjLB/JH+NrbgAUejchybAXOwiSxlCB0G/3Y/xIv4dpnewxrxusl+u+hoM22OSsT46GQ011XC/JX+J9tfsqIyfvwr/GQkJJ1Bdvy2aNz/KygU3NzckJibCxcUFnTpJWumyGR9DM5BxjNRJAmar2kBBmf961IrY+4kCzaUDek7/sSJLZZpbWlKK/TM9UFpShq7jG8HGwUgmOV9aVJyZiQhnCQtIraNHodmKv/blf7Whx8UeeJv7FjObz8SEphM49UlUwp64ATfnA6TEY0E0IIf6alH5T42ptAjEZ36Ay8YHjP37RrRA98YmovZF6NyHJsAiCA+hg6DPTi8EJ2RjdmcbzO5cjzdE1kclYXtsClroaOCGPX96eHNAQMHBwdORmnYTxkb90KgRu1PMLVu2ICcnB7169YKjI/sOZbk+iXh39Q0UdarBdAn39a5sYS+nQHMeNBytB/JPZ5WVnIdTKyRlKkN/aokaptzWHOf5+iJuzA+MfBsfbyhzQGP3NYz/egFuX+d9aGMmOw3f13QJ/vn5McDLy0C9HsCwM4KbQw2gCEiLwO4Hkdh0OxzaaspM+YOaiux3RaTVyWae0LkPTYDZ7B5Ha4UOgu7bPfEqOQfzu9liWgf++AJ/jkzA/vg0tNHTwsXm/OnhaFtEJebp06F4l+2PWhbjYGOzRGbbSktLsWrVKpCLa0OHDkX9+uxP4rNvRiPH4y2q1dKG4VT+GqnI4vTfKNBmzEODtq6yiKnQmqjnabi5PxgKigqYtKM9lDg+Ec88ehQp69ZD2cgINh4PK2SbrJOfJD3B+DuSWljPIZ7QV2PPHS2rLbyuI8TNW+oDuclAl5VAm1m8qqPCKQJcIUB+07ts80Rkai6GOFhgw0DxMy0JnfvQBJir6GMhR+gg6LzVg/nSkPpfUgfM11gQHo9jiRnoVF0HJ5vV4UtNlZTr49sZHz5Ew7ruQtSuLbmJL8sgJ7/kBJiMCRMmwMzMTBYxf1uTcfoVPgamQb1pTdQYJq7a7pyMdLhNHcPYO3zNVhhb8//mIeBmDJ5cjWK4fwkHMNcjcclSZF+6BM12Lqjl5sa1+M/KOxxyGFufboWJpgnuDLwjF52CKMmMAnY0l6ge5w5YsH9DIogfVOk3h0BIQjZ67/Ri/D4z0QlOdWqIHgOhc58vAaRQRh4n6JALAkIHQYfNDxGdnodlvRpgvAt/ienMsFicS85CLwNdHGzM/cUguWyWQEo8PO1QXJyDhg02wsRkgMxWkNpfUgNMxty5c6Gjw74/fOq+QBTGvIeWixn0evEXP7I4LQQF2t1DL/HaLwVWzWqi5xTuT2GiBwxE/suXqDF+HAznzZMFlgqvme8xH7dibqGjRUf82vHXCq+vNAuenwSuTgWU1YFFcYBytUpjOjX020ZgzR+h+O1RNEx11eC1sCMUFcXPXS107kMTYBF8Z4QOgrYb7uNt1kes6NMQY9rwl5hOfBmDa6nvMNBIH7sayqdzlQi2l7UJJSUFeOghuYlu1+wQatRoL7NMwv5AWCAUFBSYLnBKSuxrxJLW+6HkXQF0+9SBdhv2J8oyO/eZhUH3buGu2y6oyZEC7ewaP6TH58K+e2049eP2jUpZSQnCW9ijrKAApps2QrdPHy7h+qKsXpd6IS4nDtPtpmNSs0ly0SmIkqvTgOcnAEsXYMx1QUygSikCFUWgpLQMrdfdQ2pOAe9sThW17b/mC5370ASYy92UUZbQQUC+OEnZ+VjdrzFGOPGXmI4KisKdjPcYYVIDm+uLq1uYjFsnl2X5+Yl47O3C6GrpeA3a2rJzKBP+X8IDrKWlhXkcnB6WlZQhYbkXUArUGNkA6o1k71DHB5geJw4h4PdLkBcFWllpGdxmeaC4qBSdf2gI21bGnLpVEBWNqJ49GZlWV69CzZb/ko6cwhw4n5Z0fdvTaQ9czCWxWCXHjhZA5hug3QKg49Iq6SJ1quoh8DgyHcMPSC7e3p7dDrbG2pXCSaFzH5oAiyBMhA4Ch9XuSM8twPr+TTCUx64xg19EwjMrF+PNa2K1jbkIkK8cJrx/HwT/gO8YY9u28Yaqquy0Wvfv34enpydMTEwwaRL7k7zidwVIXu/H2GY43Q7VzMX1wytvCrT36R9xfJkPg8fgJY4wqMUtHu9v3ULC7DmAigrqkxbI1fh/Re+X5Idxd8YxPj0c/BA11MVfWyjTNzsnBdjy5wPFyMtA3Y4yiaGLKALyRmDe+UBcePoW9Y21cWt2O3mrl1mf0LkPTYBl3jruFgodBHYr7+DdhyJsGtgUgxz4O5nt8zQC/u/zML2WIZbVNeUOwCouKT39PgKDJLyrHVxfQVFR9s4+V69exfPnz1GvXj0MGzaMNXIFse+RtjeQkWOyrBWUtPhPyCpi9NF505AeH4vWA4fBeRB7f7+mOyY4HX/sDmKmTfy1PVRU2ZeY/FVn6q+/ImPvPqja2qLO1StfM4eTz4++PIrNAZthpGEE90HunMgUpRBCfUYo0EibcVL/q8otfZ0ofaZGVXoE8otKQA6xcguKsbhHfUzi8SI712AJnfvQBJjrHZVBntBB0OTn28gpKMb2IXbo15y/Gs4u/uEIzv2IeZbGmGfF7athGWCvNEsSE88j7NUiqKjoo51LACu7T5w4gcjISDg4OKB3796sZJHFHwJTkXk6HFBWhNkqZ6a2WCyDoUAbNRDFRYXoKScKtOd34uB9KRLa1dUwaq2kbIDLET9tOnLv3YNOnz4w27SRS9FflLXAcwFuRt9EB4sO2NFxh1x0CqLkxgLAbz9g2hyYKB96OUH8pEqrFALXgxIx/dRzkJ9e70UdYaKrXmn8Ezr3oQmwCEJF6CCov/wm8otKsWtYc/Ruyt/JrMuTMER8KMCyOiaYXlv21/gi2DK5mhATsxdvojZDU9MGTq1usdK9d+9epKSkoEOHDmjfXvbLdOVG5HjEI/tmDJRrqsN4nrjabgpBgXbvWBheeSehVqMa6DOjGau9+tziyM5dUPT2LQzn/Yga4yW8vHyPPpf7IOZ9DKbZTcPkZpP5ViecfNL+mLRBdpoGdF8rnB1UM0WgAgiMPxoA97AUtK5TA6cnck+7WAFTKjxV6NyHJsAV3jLuFwgdBDZLb6CopAz7Rtije2P+TmYdfF7ibX4R1tiYYZy5AfdAVlGJr1+vQvzbI9DXc0KLFidZeblx40Z8+PABffv2RYsWLVjJIouzrkYizycJqtZ6MBjfhLU8LgXEhQTh/CpJ05BpB89ATYv/V9oXNgQgJfo97DpboM1AGy7dQUluLl47SHhpLX5zg5YL/5fRcgtz0fp0a0bn7k670c688tQXVgj8/GxgPbkAXAYMOQE0kA+7RoVspJMpAv9AICuvEI5r3FFcWoYNA5pgiGOtSoWR0LkPTYBFEC5CBgGhe7ZafINB4cAoB3RuyN/JbGOvEKQXFWOrrQWGmVbRizQ8xFNIyCykpF6HkWFvNG4sOwdrcXExVq9ezVg4fPhw2NiwT9DSj75EflgmNOyNUH0Q/4wEFYFX3hRo5Lt0YI4nCvNL0GFkfTRsw+3blA/PniP2z7ptaw8PqBgZVgQOmeb6J/tj7O2xzNoHgx+gprq4WD5kcupziyLuAicHSj6Z/wbQrKJ+cgYYFSQGBE74xmLZlRBUU1ZkWh/rqst+P0QIf4TMff7LX9oIQ47RIGQQFJeUwnrpTcbbIz84wtWWvz+q1p5ByC0pxZ6GtdHfqIq2UuUhbp49G46sd74wNx8N23o/yazh3bt32L59O7N+8uTJMDZmf9qf8uszFCXlQbtTLeh24Y9CTxanP1Gg2dhi2GpJ9zs+R967AhxZ9JhRMWCBPYzr6HKqLuvMWSSvWAElPT3Y+HjLpd66/AKcoboh7g2+x6k/ohLm/gvgtRWoWQ+Y7i8q06gxFIEvITBwrzcCYrPQo7Ex9o6wr3RACZn70ARYJOEiZBCQG6T1l0vqSk+Ma4W2NvydfJg/fIHiMuBQY0v0NNATCfriN8P3SXfk5UWgbp0fYWk5VWaD4+PjcfDgQWb9/PnzoampKbOs8oWJK31Q+qEY+gNsoOnIPqFmbdBfBFzdvBqR/r5o6NIBPab/yKXoz8qKD8vEtV9fMJ+N3+oCVQ1uT2OSV65E1qnT0GjZErWPHeXdH6JgoedC3Ii+AVdzV+zstFMuOgVRcqg7EOcD2I8B+sj+lkUQ26nSbxKB+MwPcNn4gPF9/0h7dGskrt9faTZFyNyHJsDS7JAc5ggZBIQ6pfHPtxkv+ewfTmqUzD0kdFmnmtZBxxrsW/DKYWtEocLzkQOKirLQoP46mJoOltmm0NBQnDt3DoqKikwXOPK/bEZpYQkSf/JmRNQc1xhqNuI61S+nQHMeNBytB37PxlWp1gY9iMejsxHQ0K2GHza0lWpNRSbFDB+Bj0+fQn/kSBgvldQ28z3KL8BNaTYFU+1kf/ji205W8ovygfUWQEkh8J0b0GwIK3F0MUVAHgjsuh+BzXdeQ0dNGf7LOkNVmVvKRXn4IGTuQxNgeeywFDqEDILsD0VotvIOY+WFya3hYFldCosrPiW3uATWj4KZhZfsrOGsz/+FpIpbKb4VpaXFePDQljGsWdPfULOm7OT8T548wc2bN6Grq4s5c+awdrYo9QNStj5l5BjNtYeKoQZrmVwJYCjQRg9CcWEBes6cjwZt2DNefM22h6fC8dIzAWa2+ug3p/nXplfoc1Jf/LplK5Tm5MB41UroDxpUofWyTM4rykPrU61RhjLs7LgTrhausogR/5pYb+BwD4mds4MBvcp1kUj8AFMLuUaA/B503uqBN2l5+L5lLazrL64LyNL6K2TuQxNgaXeJ53lCBgHpAEdItMm4Mq0N7Cz4KU1IKyxCk8cvGT037euhuY54kiWet5eV+IKCFHg9lvDJOjpcho5OU5nlubu7w8vLC+bm5hjPAYVW/usspB8KYewxXekMxWriOYH4GwXa2m0wrsv+wt/XgL+85RkSI96hias52g3l9kJgUUICIjt1ZkywPH8O6k34/4P3NOUpxtwaw+i8N+geDDX4ux/wNWx5/dxzM3B/FaBjDsyV/EbRQREQMwIhCdnovdOLMfHsRCe0qlM5L5ULmfvQBFgkES5kECRn58NpneRyy/UZbdHYjNuLO+UQx30sQEvfMOZfHzjaooFW5SHrFjJMcnJC4ecvoWRq4/wIamqyMwtcvnwZgYGBaNCgAYYMYf+aN88vGVmXIqCoqQzT5RKqLLGMv1GgHToDjXXBdAAAIABJREFUNU3+3zgcmv8IH3OK0P77emjcnttW3zkPHuDtlKkgbPe2z55CUZ3/78/x0OPY6L+RYX4gDBBVdpwYAES6A00GAQMOVFk3qWNVB4HV10NxwCsaZnrqeLSgAxQVxdOAqCIoC5n7VOkEOD09HQsWLMDTp09BQM7Ly4OpqSlatWqFRYsWoVmzf5PUP3v2DOvWrcOjR4+QlZWFmjVrwt7eHjt27IClpeXf8AoKCsLSpUuZE7XCwkI0adKE0de/f/+K7D8zV8ggeJv1AW03SP643ZrtgvrG/NTmvs7LRzu/V4weX6cGsFRXrTBO3+KCjAxPvAj8gXHdtX0olJRkx+3YsWOIiopCy5Yt0bNnT9ZwZt+NRc69OKiYasJoJntOYdYG/UVAOQWaurYOph44xaXoz8r6mFuIQ/MkJzL95jaHWT1u66HT9+1H2vbtqFa7NureZtcMRVowFj9ajOtR1xnuX8IBXCVHaQmwwRIoeA/02go4jquSblKnqg4CJaVlzKFVWk4BprjWxcLu9Sutc0LmPlU6ASbtXkeNGoXWrVujdu3azI33mJgYHDlyhOmE9ccff6BLly6fMDh9+jQznyTGgwYNgoGBAVJTU+Hv788kun9tGkBO0dq2bQtVVVXMnj2bmUtazJJk+MCBAxg3rmI/okIGQUx6Hlw3S9p+us9tD2tDfk7KgnI+oGvAa0bPC+dGMFbl9oZ8pf0F+IrhSUmXEBo2H8rK2mjfTsIwIOvYtWsXyINhp06d4MJBE4XM86/x4WkK1BrWQM1RDWU1i5d18qZAI6UPpASCjLGb2kJduxqnfiXMnYv3N25Cu2tXmO+QD0vB/678D1HZUZjUdBKmN5/OqT+iEZYUCOz/s7nHVF/AsIFoTKOGUAQ+h8CjiDSMPOjHfHRnTjvUM9KutEAJmftU6QT4S84lJiaiVq1aaNeuHe7fv89Me/369afElyTIX7sdT9aSZNfPzw8ODpL2r6TJgLOzM8LDwxEbGws9PelraYUMgsjUXKaYngyP+a6oXYM9NdbnsPd7l4u+zyOZj161bQw9FeVK+6WVp+GxsW6IfLMBGhpWaO0kqdWWdZC3GwUFBejXrx/s7OxkFfNpXdpvQSh4kw0tZ1Po9a3LWh6XAuRNgRbimQCPU+FQ01TBuC3cd2h706s3Ct+8Qc0Z02EwbRqXUH1W1oeiD3A65cRcgPu1w6/oWEv2y5e8G8tGge8+4NZCQF0fmB8FsGRGYWMKXUsRkAaBH88F4uKzt2hgooObs7j/rZHGBq7mCJn7/JcPVbYRRklJCfT19WFtbQ1S8kDGhAkTmJPhpKQkpuyBtIpVVlZGtWr/PsUhp8hWVlZwdXXFgwd/r4sjp8AjR47E4cOHMWaM5PKINEPIIHiV/B7dtz9izPRa2AHm+vxcTvPMzMHgwDeMnph2TaGmxI6CSxpcq8KciIi1iIs/CF1dBzjYn5XZJVKms3btWmY9idG6ddknrMmb/FGckQ/dHlbQ5rjmVWZH/1z4iQJt8HC0HsA/Bdqjs68R9OAtTKx10X8et4T0pQUFCG/eAigthfmundDuLLkMx+d4lvIMo2+NZlTcHXgXxpqVj2NUKnzOjQJCrwK2PYHvT0u1hE6iCAiFwMfCEjisvou8whIs6VkfE9ux/x0XyheiV8jc57/8rjIJcFFREbKzs5kT2ri4OGzZsoXhQl2+fDlWrlzJYEBqg2vUqMHU/5I63rCwMOYUmNQLr1+/njktLh9nz57F0KFDsWTJEqxZs+ZvGJL6SpJYTJkyBXv27JE6roQMgr/eJn2ypBOMdNSktrsiE2+nZ2N0cDRIqX6iazO5dLGqiH1infvy5Y9ITrkCA4PuaNpE9jrMjIwM7NwpaWQwdepUGBqyu9FPaHgSlj8G6WxS/fv60GhmIBoIGQq0UQNRXFQoNwq0a78+R3xYFhq5mMJ1OLc1eR9fvkTMAEmb3rp3bqNaLf5puk6EnsAG/w2orlYdDwc/rJrf17IyYHM9IC8V6LIKaDNTNDFMDaEIfA6B3wMTMeP0c3IXFj6LOsFYl5+/1/JCX8jc55tIgB8+fIgOHTp88pVwoJI2sKtXr2ZOeUlyTMoVqlevjpycHOYzMp/UEJMEl5wG37t371PNJEmg582bxyS4JNH96yCnbKQuuE+fPrh27doX8X3//j3IP+WDnDyTi0mkUxehqJLneBH/Dv12S9q3BizrjJpasl+y+i+7r6RkYXJoLNQVFRDd/t8XEOXpc2XS9fz5aGRmecHMbATq2/4is+nl9e9EwMKFC6HOkkWgJLcQSaufMPYYTGkG1dr8XJ6UxeG/UaCt2Qpja24pyT5nE2mBTFohtx1kg2adLGQx+4tr3l26jKQlS6CgoQHbAH8oyOE1/ZJHS/B71O9oa9YWezvv5dQf0QjLeAPs/PPy5vh7gLmknI0OioBYERh/1B/uYalwrlsDpyY4idVMqe2iCbDUUMk2kbA5ECYIUvtIan2PHz/OXIzbuHEjczGufAOIdHLZjSTG5YOUOHTs2JGp7X38WJIkrlq1Cj/99BPTUnbs2LH/MoqcHJM1hHP1S2PFihX45Zd/JzNCJMABMZkYuM+HMTXwp67Q5bh9azkGZ5IyMPtVPKqrKCG0Lf8cprJFi/hWPfHrjdzcMFhZzUYdqxkyGxgcHIyLFy9CRUWFeXuhQI4QWIzCtzlI3SW5lGeyuCWUdPl5cJLFRHlToBV8LMaBOZ6MqX1n2sGiIbfNZFLWb0DmkSNQa9YUVmdlL4OpCJbfXf0Oke8iMbHpRMxoLnvcVUSn3Oc+Ow5cmw6oaACL4gAlejFX7ntAFUqNQGZeIVqucQfpqrpxQFMMduT2QVtqQzicSBNgDsGURhRJiAnTQ6NGjZiuWOTVMKn7JSMiIoKpDf7rIAwSZJPI6bCGhgZTQlGVToB9ozIw1M2XcfnlL92gqcrP5bQjCelY9PotTFVV8My5kTRbRecAeOTlhMLCNNjaroK52TCZMfH29sadO3eYNx0zZ7J/1fsxJB0ZJ8IARQWYrW4DBRHxUAa538Ld33ZBXhRoydHZuLhB0hFv9DpnaOlz+1oybuxY5Hn7QG/wYJislP0tgLTBQy7AtT7dGqVlpdjeYTs61eok7dLKNe/KVODFScCqHTD698plO7X2m0PguG8sll8JQTVlReZtrY5a5X9gowmwAGE8ffp07N69G9HR0QxFmra2NsMTTJJcLa2/04A5OTmBtJBNSEhgaoWrWg2wV0Q6RhyUvMp+tao71FT46ea1Ly4VK94koo66KrydKNWQNGFfVlaKBw/ro6ysBE2b7IWBQVdpln12zu3bt+Hj48PE+w8/SHiF2YwcrwRkX4+Ckp4qTBa1ZCOK87XypkAL807E/WOvoKKmhAnb2rE+Xf8nIK/btEVJRgaMli9D9eHDOcfrnwJfpL7AyJsjmf9cpS/A/WoHZEUD7RcBHRbzjitVQBFgg8CAvd54GpuFXk1MsHu4uHjXZfWLJsCyIsdiHeHpPXToEMMC0bx5c6ZkgZQ7hIaGMl2y/jrMzMwYPmCSHKupqTFJc506dZg64XIatfL5lZEF4mF4KsYc9mdceLO2J5R4OsnbHpOM9dHJaKiphvstub0kxCIURL20sDADj7wkyaWD/Xno6sr+o3fhwgWEhISgcePGGDhQcqGKzXh3PQq5XgmoZqkDw8niqumWNwWa98VIPL8bByMrHQxcyG0daXF6OiLaSqiOah8/Bg1HRzbbJtXak2Ensd5vPfRV9eExxIPzhF4qI/ielJMMbLGVaBl1FajjyrdGKp8iIDMCcRkf0G6ThHXKbaQ9ujaqGqwsNAGWOST+eyFpdmFkZPSvSeQyEOnuRujQkpOTmaT26NGjDG3ZtGnTQJoFlA/SOpZ0duvevTtTLlE+SBMM8kqZNMkgssgo5wF+9eoVwwNMqNakHUIGgXtoCsYfC2BMjV7Xk7c/duujkrA9NgUtdDRww57/S0nSYi/mebm54XjiJ+nY5tz6AdTVZb/9T6j5SFyS+vdu3bqxdjvjZBg+BqdDw84A1YeK64HmyI9TkfE2Ds6DhqP1QP4p0K7vDkRscAbqtzZGp9HcNgTJ8/ZG3FhJY516T3yhpMtPq/K/BsRSr6W49uYa2pi2wb4u+1jHiigFhFwCLvwAKCpL6n+r8cN/LkrfqVGVDoGd9yKw5e5r6GmowG9JZ6YMoioMIXOf/8Kv0tOgkQ5td+/eZVq+kjbG5NIPoTcj7WBzc3OZpHfEiBEMBqWlpUySS+YPHjyY4fh98+YNkwyTBJkkuw0b/v8fNnJyTKjRyGdz5sxhaohPnjzJtFDev38/Jk6cWKHYFDIIboUkY/KJp1BRUkDEGvbtcb/k+M+RCdgfn4Y2elq42PzvddYVAusbmpyZ6Y3nLySvol3bB0NJSXaOZtLOOzMzE127dmUudbIdqbtfoDA+B9qu5tDtbsVWHGfrhaBAO77MG+/T89G6f1206FqbM1+IoIzDR5C6YQOUTUxg80DSuIfvUX4BbkKTCZjZgn29ON/2yiT/xnzAzw0wswcmyAdXmeyki755BAjlZKetHohKy8OwVrWw9ruqc4lcyNynSifAhIWBJKMBAQFMCQM5oTUxMUGbNm0wa9YshnbsryM/Px8bNmxgWhqTkzIdHR107tyZ4QquV+/fJ5akHTJhjSAd4Qj9WZMmTTB//nyZXi8LGQR/BCVh2qlnUFdRQtiq7rz92CwIj8exxAx0qq6Dk83q8KanKglOTr6Gl6FzoKiojg6uITK7Rn5ASRMMwok9YMAAJlbZjsQ1T1CaUwi9fnWh5WTKVhxn69+np+G3aZIa5+Frt8G4rg1nsj8nqLiwBPtneQBlQK+pTWHZVHKhlquRuHgJsi9fhlb79rDYz/9p7Mfij0wHOHIBbpvrNnSuzX/TDa6wqpCcvW2BlGCg9XSg29/53Cskh06mCPCMQPDbbPTZ5cVoOT+5NRwtuWWZ4dn8/xQvZO5TpRNgITe1orqFDIKrLxIw68wLaKsqI/gX9q/Gv+T7zLBYnEvOQi8DXRxsLJ4Tw4rulTznx8UfRkTEaqipWaCN80OZVX/8+JF5uCNj9OjRTCdDNqOsuFTSBKMMqDGmEdTri+cHOS4kEOdXLWXcm3boDNQ0/36plY3fn1ubFp+Dc2skNfQjVjlB10D2U/rPyY/uPwD5oaGoMWECDH+cy7X5/5IXmBaIETckb8ZuD7gNUy3xPNxw5vzHd8AGSzABPPQUUL8XZ6KpIIoA1wis/D0Uhx5Hw0xPHY8WdIAiT/d0uLZbGnlC5j40AZZmh+QwR8gguPD0LeadD4S+hgqe/yQ7y8DXYJr4MgbXUt9hoJE+djXk9jXx13RX1s8j32xCbOw+6Og0h6PDBZndIG9AyjsTzpgxg+l6yGYUZ3xE8iZJ3bjhrBaoZiKe+kl5U6C99kvG3UOhUFJRxMRf23P6x6msuBjhLexRVlgI002boNunN5ttk2rt6VensfbJWuip6sFziCdvdwKkMoavSa/vAKcGSaQviAY0xPMAx5fLVG7lRKC4pBSt199HWk4BpnWoi/ndxHXfgi2qQuY+NAFmu3scrRcyCM76x2HhxWCmAxzhFuRrjAqKwp2M9xhhUgOb61d+Am++cPqr3NCwhUhKuoCaNTujWdP9Mqsk9eykAQwZpAlGtWrVZJZFFhZEvUOaWzAjw/Tn1lBU54c7WhYj5U2B5nv1DZ7ejEVNCy0MWcotHVxBVBSiekpOJ+v8fg2qNvyWcxA9yx8vx5XIK3A2dcb+LrLHnCx7J7c17isAr22AQX1gmoQCkg6KgBgR8HydhlGH/BjT7s5pBxsjbTGaKbNNQuY+NAGWedu4XShkEJzwjcWyKyEw0VWDz2L+CO8Hv4iEZ1YuJpjXxCob+bZ75na35Cftxf+xdxVQVWVd+KOlQVIQRRBRwEZJxRy7u9uxW8fuHB1jrHFsHbsDO0BFkZIQpbuku+Nf5z6Z35lBH9x377uPx9trzZqF95599v7OebDfOXt/228a0tJcYGAwGi2a089T9PX1xe3bt6k23atWCc53mufzBRlXQyClIAODjXYidUp4e/dWhHu5w6JTV/SZt5T1xXp4LAARH1Jg1kEPP01jtsFL9sOHiF+8BFJycjD38ab+z7YMuzsMIRkhmN5yOha2W8j2dNzoP9kLiHUH2k8BBuznxgbJrBIEqoHAkqu+uOkTD0sDNTgv4NEhipNwGftIAmAR2UlcboKzb6Ow4W4gjOqT/KJurCEy0CcUHll5mN9IF2tMxTCvkAXkPDwHIycnAMbG82Bqspj2DISd5Pnz5xRbCWkCI6hkv4xB9uNoyOopQX8xjwZQVORvCrSR42A3jH0KtIsb3ZGRlA+bgU1g3Vew3Op/Y5i8fz/S/jgGhebNYXL7FusQF5UVweaCDcoqyrC3y170bNyT9TmFPkFJIbDTCCgrBoYeB1qNFLoJkgklCFQHgYLiMlhvfYq84jKs6dsCMzqLX/E4l7GPJACuzi4UwjtcboITryOw1fkzmmgr4+Uy9sjge3oGIyC3AMuN9bG0iXiQeLO9Nd64OaKoKBHNmm2EUUMeHRodefDgATw8PKjiN1IEJ6hk3ApF3vskKDTThM5UK0HVMTZe2BRoZaXlOLbAFRXlFej9sxVM2+oy5gtRFDt7DnJfvoT6oIEw+FrEyOgE/1IWkBKAsQ947bYfDn2IhqpieFMT5Qac+Ur3uDgQUBdDH9ncJBLdQkPgrl8CFlz6ACkpwH1Vd+ipMdtiXWiO/GAiLmMfSQAsCjsAAJeb4A/XcOx8GAQzXRU8XeLEGiKd3n9GaH4R1pkaYG4jZgMF1ozmUDGhLnvpYoGKimJYWR2Cnm4f2taQ9t2EA7tVq1ZUYxdBJfX0RxQGZ0C5oz40h7Kfl1pde7NTk3F87lTqdWFQoKUn5OHSZl4O6diNNtDUZ7YYMKxbd5QkJEB3+XJoTeP5xaZcCbqCre+3Qk1eDW9GvxGp1BbG/H61G3ixFVBvBCzm5bFLRIKAKCIw9YwnXgQlw6GpFi5MtxVFEwW2icvYRxIAC7x8zCjgchMcfhmG3Y+D0VxfFY8WdWbGoSq0WL8LRFxhCbaZGWJaQx3W5hEXxSUl2Xj1ui3lTrt2l6GpQb8F7okTJ6gvWYQDu2dPwa+1k/Z5o/RLPtR+agy1bvS70zG9VsKmQAvzTsbj4x8p5oeZB50gI8Ncd6aynByEdOAV1RmdOAEVRwem4fqPvg1vN+Bm6E3YNrDF8Z+Osz4fJxOcHwqEPwdajQKG/smJCZJJJQjwQyAttwgdtz9HWXkFdg9vhRHW4lk4zmXsIwmA+e1CIT3nchPsfxaC/c9C0dJQHffmO7LmsdWbj0gtKcVecyOMNRCMhos1I0VIcV5eBNzf84JVO9tnUFKin1+6b98+ZGVlUd0ObW0FP0mI3/AWFUVl0BzRDMrt/9tunCsY/Z4+xLMTh6GoqoY5Jy6yboancyQ87kVCU18JYzcKjuu3Buf7+CB67Djqn5q+coWcLvu3JiPujUBQehCmWk3F4vb0c85ZB57uBOVlwM7GQHEO0H8/YM1rmCIRCQKihsC5d1FYfycQCrLSFDuTaj32C2C5wIDL2EcSAHOx4lXMyeUm+O1JMA6+CEPbRhq4NYe9U6amr/yRW1aOoxaNMURPU0SQF10zMjI84POBV8Tl1NkXsrL06G9Im++tW7dS7b5HjBgBS0vBmArKC0uRsPEdZZf2jJaoZ6ohMiAKmwLtyYmPCPVKhmk7HfSeKXh3vW+BzLh0CUmbNkNGUxNmb91YT0coLiumCuBKK0qxx2kPehmz1xSHsw2T4Av8+TXNa64HoGPOmSmSiSUI/AiBoUfc4BOTiX6tGuDw2HZiCxaXsY8kABaRbcXlJiD5vyQPuIOxJq7NsmcNEUMXX5RVAKetjNFHR3SCJtYcFlDxl+QH+PhxPqSl5dHF6RPtACgvLw+7d++mrJk2bRqMjAS7SitJysOX/T6UPv3l1pDVUhTQU+aGC5sC7fIWD6TF58K6rzFsBjJboZ24cSMyL1+Bkq0tGp85zRxI39EUmBqI0c6jqacPhj6Akapg+4R1g+lM4H4UeLQSUNICloeDqi6SiAQBEUMgOi0PTrt5nT9PTLRGDwvRuWVjGiouYx9JAMz0atLUx+Um2Hr/E068iYSdiRYuzWT2GrcSjpLyChi5+lE/Xmplgq5aajSRqjvDYuPOISRkExQUGsDRgdcHno4kJSXhjz/+oIYuWrQIGhqCffkoCEpH2plAQAow3OIAKVnm8l7p+PftGGFSoJWXV+DPBa4gTBCE/5fwADMpUWPGouDDB9SfNBF6DHA387PtavBVbHHfAlV5VbiNZv/EmZ89rDy/MgH4fBdo3h8YfYGVKSRKJQgIisDvz0Ox92kINJTk4LG6B+RF6HesoL79ezyXsY8kAGZ6NWnq43ITbLwbiDNvo9DJTBvnp9nQ9ODHw3JKy2D2mldxfattU9hpqLAyjzgpDY/Yi6iow1BVbYmOHW7Tdi00NBQXLvD+2K9duxaysoJ1bct1T0Tm7TBIq8rBYA07X5joOEso0A5MHIaykhL0W7AczR3YYzQh9mUm5+PCenfK1FFrO0C7Ib0Ulap8JQwgIdYdUJ6XhwbbtkJj2DA6kNRozMa3G3Ej9AZs9G1woteJGo2tFS9XVAB7zIC8FOCnbYC94HzYtcJviZG1CgHy2e/+mysiUvMwzqYRtg1hNrVK1MDgMvaRBMAishu43ARrbwfgL/cYdDXXwekpzLZyrYQ3pbgELd0CqR8ftm+GtmpKIoK86JrxOWgNEhIuQ0urK9q0ph+Q+Pj44O7du1BSUsKKFSsEdjjrcRRyXsZCzkgVenPbCKyPKQXCpkCL9EvBg6MB1C36zANOkJWXYcoVFMfFI7wHry258bVrUGzJPtfyyHsj8Tn9M6ZYTsES6yWM+SIyilLDgENfm7bMeAEYilYDF5HBSWIIpwj4x2Vi4CE3yobrs+xgbVyfU3vYnpzL2EcSALO9utXUz+UmWHXTH5c8YtGjhR5OTLKupsU1ey2moAgd3T9Tg152MEcLFdHJG62ZJ8J728//Z6SmPkODBiNg0WIn7YldXV3x8uVL6OnpYfbs2bT1VA5MvxKM/A/JUGypDa1xLQTWx5SC6ABfXN+6llI37/QVKCgxy8n7bzt9Hkfj3a1wqOkoYsIWO6bcoPTkvHiBuDlzAWlpmHt7QVqR3c8LVQB30Qal5aXY3Xk3ejfpzag/IqHM5xxwdz4gpwysjAFkBLsJEQmfJEaIHQKb7gXitFsUGmqSzqxdadd+1BZguIx9OAmAP336hFevXsHd3R2JiYlISUlBQUEB1aaV/NeiRQt06tSJ4ixVU6sbuaJcboJl1/xw3TsOvS318ccEdk5FgvMK4eQRRO03d9sWMFZUqC2fT87s9PQajuzsD2jceDaami6jbcf9+/fh5eWFpk2bYvz48bT1VA5MPuaH4shsqDgaQqM/s4Vfghj3NwWamjrmHGc/v/PZmU8Idk+CcStt9JvTShDT/zM29ehRpBz4HfJNmsD04QNGdVelLDAtEKPv8wrgnIc4o5Ga6HA7M+b8rVmA3yXApAsw8Q5jaiWKJAgwhUBpWTlsd7xAam4R5nVtimW9xJ+lhMvYR2gBcHR0NE6dOoXTp08jPj6empfkulQlUl8rc2VkZCje0unTp6Nfv34gP4urcLkJFl3+gNu+CazSrfjl5KOXVwi1fL72ltBXEE9OQyb3p9vbLigsjIWZ2Vo0MqLPV3rx4kWEhISgbdu2GDRokMAmJv7qibL0Qqj3N4Gqo6HA+phS4HL+JLzv30KDZs0xdsseptR+V8+1HZ5Ijs5B258awX5oU0bni1u8GDkPH0G1Vy80PLCfUd1VKbsWcg2b322Gqpwq3MaIaQHc/lZAZjTQZTXQ5RfWMZVMIEGgpgi4hqRg0ikPatizJZ3RVJe5uoKa2iKs97mMfVgPgEkBzurVq3Hr1i0q4CX/SUtLw8LCAm3atKFOfOvXr4969eohPT0dGRkZiIyMpE6syM9ESEBsYGCA9evXUzROZLy4CZebYN5FH9z3T8TgNgbYP5rXeYxpeZ+Zi0Efwii1QY5W0JCTXD/yw/ilixXKywtgabEP+voD+b3+3efHjh2jblo6d+6Mbt260dZDBlaUVyB+nRsIn53W+BZQtNIWSB+Tg/+mQOvcDX3mspvDSn6PHV/0CiVFZeg+qQWa2zVg0hWE9+2H4ogIaM+fB525cxnVXZUyEvySILijfkec7HWS9fmEPkF2ArD3a7rOpHtAE/Y6XgrdN8mEYoPAkiu+uPkhHpYGanBe0Els/PqRI1zGPqwGwHPmzMHJkydRUlICdXV1DB06FKNHj4a9vT2Ulfnn54WHh1PFO5cuXaICYhIIm5ubUzrt7JjNueN6p3G5CWad98ajwCQMb98Qe0a0ZgUK1/QcjPILp3RHO7WCghh+iWESuNLSPLi+4l2rt21zHvXr0+dn3rNnD3Jzc9G/f39YWwuW412WXYTE7bwTCt15bSDPIPOBoPhVUqA5jBwP22G863y2JCe9EOdWv6XUD19pDT1j5lK1ygsLEdyuPVBejoaHD0G1e3e23PhbL0l/IGkQky0nY6n1UtbnE/oEH28A16cC0nK8/F95SRGu0NdAMuEPEcgvLoX11mfILy7D2n4tML2T6KSXsbl0XMY+rAbA5KSWBKzkBHjUqFGQl5enjSM5Sd61axfOnz+PNWvWUKfB4iRcboLpZ73w7PMXjOlohB1Dmc1lrFyjx6lZmBQQSahjkdCltdgn9gu6N/Pzo/HOnXdaa9PxIVRUmtFSWVZWRnWBIyeWY8aMoT6PgkhRTDZSjvD4nBustYGMCv3PtCB2/HussCnQYgLTcO8gD4cZ+ztDvh5zNxoFHwMRNXw4pdv02VPIN2zIJFQCKaNsAAAgAElEQVT/0VVSVkIVwJWUl2BXp13oa9KX1fk4Ue68DPA8DjTsAEx/xokJkkklCPwIgTu+8Vh42RfSUsC7Vd2hp1avTgDGZezDagBMTm7JiW9lTi8TqxkTE4PY2FiqQE6chMtNMPm0B1yCUzDethG2DmaHc/D2lwzM+hQNRWlpRDqxE2SL037IzPKGt/dIyqVOjp6Ql6dHhZOdnY29e/dSembOnEmlEgki+f4pSL8YBMhK8ZpgiEgnrW8p0Mbv2A89E2Zzcv+Nme+zGLhdD4OKpgIm7WD2d1HmzVtIXL0a0srKaObpASmWb0s+p33GyPu8vXZv8D0YqxsLskVEc+xRB+DLR8B+AfDTFtG0UWJVnUZgymkPvAxOgWNTbfw1nR0+flEEmMvYh9UAWBTBFlWbuNwE40+8x5uwVEy2N8bGgZasQHQ5MQ2LgmJRX04GnxzZCbJZMZwjpckpjxEQMAdSUjLo2iUIUlL08t5Jwenx48cpL5YuXQpVVcGKKnJexSHrQSRktepBf3kHjtD577QxH/1wbcsa6oEwKNBe/hWET28S0MiiPgYsYJYL+cuOnUg/exaKbdvC+NJF1jG+EXIDG99thLKcMt6OeQtpmnuNdUPpTlCQCewiQX0FMOYyYN6HribJOAkCrCCQlluEjtufo6y8gkpDJOmIdUW4jH1YD4CLioqgoCAY5dWhQ4cwb554d+3hchOM/vMd3CPSMd2xCdb2t2Dlc3cmPhUrQ+JgoCAHH3t2gmxWDOdIaVz8RQQHr4O8vC46Ob6jbUVQUBAuX75MndSuW7dO4ALSzLvhyH2bAAVTdejMEJ2TfGFToN3c7Y3E8Cy07mYEx5FmtNenqoHRU6Yg/507NEaNQoNNGxnVXZWyLe+24GrIVVjrWeN079Oszyf0CUIeAxd5J9xYEQko0btNEbrdkgnrDAJn30Zhw91A1JOThueaHlCtV3dYkriMfVgPgAl92Z07d2i3Xz1w4ACWLFkCkssozsLlJhh+9C28ojMwy8kUK/s0ZwXmP2KSsTE8AaaKCnCzFZ3mCaw4y4DSiMiDiIzcDxUVC9h0vEdbo6enJ5ydnamTX3ICLKiknvuEwk9pUGqvh/oj6OUlC2pDVeNd/zoFr3s3YdCsBcZs2c3GFH/rJPnUJ5e+RlF+KbqMM4dlJ+ao4IjuUHsHlGVkQG/9OtQfO5ZVX4jyMffH4GPaR0y0mIjlHZazPp/QJ3i6AXDbD+haAHPof5kUut2SCesMAkOOuOFDTCb6t2qAQ2Pb1Rm/iaNcxj6sB8CkEG748OG4cuVKjfMF9+3bR/3RJqdXkgCYvc/E4MNu8I3NZJV4e19UEnZFJsFSpR6ed2AnyGYPIeFrDgregPj4v1C/fie0bXOGtgEvXrygms40aNAAP//8M209lQO/HPyAkvhcqHYzgvpPopMrKkwKtPzsYpxe8YaCZMiydjBoqiEwrpUKSlNSENqJR9HV+MJfUGrPTmOayvlI4ZvtBVsUlxdjZ6ed6GfSjzFfREbRyZ+A2PeA9TSgPy8fXiISBEQFgajUPHTZ40KZc3KSNbq30BMV04Rih1gHwHJycigvL8ekSZOoRhjVld27d2PlypVU9XqfPn2oUyxxFi43Qf+Dr/ExPhuLephhUQ92TvV2RCTiQPQXtFdTgnN7duYQp/3hHzAXKSmPoK8/GJYWv9F27fbt2/D19aXYHwgLhKCSsMUd5Xkl0BxqBuWO+oKqY2y8MCnQ4oIzcGffB8r2ab91Qj1l5q4rc93cEDttOqW7mcd7yLDcCTM4PRjD7/EYJ+4MvgMTdTGjXiopAHYYAeUlwLCTQEuerxKRICAqCOx/FoL9z0KhqSSH96t7QF6WXr2HqPhTUzu4jH1+ZKtUxfdatdXAwwsXLlDBL1E1d+5c/P7773xH79y5k6I6I2MId+n169cFolDjO6EIvMDlJui9/xWCknKwvJc55nZlp3p+Q2g8jsWlwEFDBTfasjOHCCwjYyZ4eY9CVpYXGjWaDrOmq2jrJbSBhE+b8P+Sz5IgUlFShvh1PO5b7alWqNdMUxB1jI39BwXawhVobs9uk4MAlzi8uhwCRTV5TP3VkTE/iKK0U6eR/OuvkDMwQNMXzxnVXZWyW6G3sP7teijJKuHd2HfiVwAX9QY48/VUe/EnQJ25dBXWF0cygdgjQGKcrntcEJWWjwm2jbFlsJXY+/xvB7mMfVgPgMkEpAqdXL+SVAZyqrtt27bvzkueEY5fsjEGDhyIa9eugZwii7twuQl67HVFWHIulf9L8oDZkBXBsTiXkIbu9dVwobWYnTKxANjbd91RUBCFpk1XonGjGbRnOHLkCJKTk9G1a1c4OTnR1kMGlqQW4MseL0qH3pL2kNMVjWYCwqZAe3UpGAGu8TBspoHBS5jN10v4ZSWy7tyBSpcuMPrjqEDrVZ3BW9234krwFbTTbYezfc5WZ0jtesd1N/ByK6DRCFgUULtsl1gr9giQ1EOSgkjkxmw7tG9c9wo0uYx9hBIAk0m+zeclxPyrVv33VGvTpk3YvHkzFfwOGTKEql6vC8EvwYfLTdBl90vqGyib3WcWfI7G1aQM9NNRx0mrJmL/i01QB11cW6OsLBcWLfagQYMhtNWR5jEFBQXUl8l27QQL1grDMpB64iNli8Eme0gryNC2i8mB0QG+uL51LaVSGBRot/f5ID44E1ZOhnAaI1hjkX/jEDFkKIo+f4bWzz9Dd/EiJmGqUtc453HwT/XH+Bbj8UvHX1ifT+gTnB8ChL8AWo0Ghh4T+vSSCSUI/AiBjXcDceZtFIzqK+LV8q41rpMSB3S5jH2EFgCTibZs2YINGzZQi0zYHb6lNiOnvuT0lwS/w4YNo9ofy8oy111J1DcKl5vAcdcLxGUUYNNAS0yyZ6ewaWZgFO4mZ2K4niYOWTQW9eXg1L6ysiK4uPLo6Nq0PgMtLXo94UtLS6kucETGjRsHMzPB6LryvJKQcT0UUoqyMNwgOq3IhU2BRgrgSCFcp1HN0Korc3ydFaWlCG7bDhUlJTDc+xvU+rLbka20vBS2F21RVFaE7Y7bMcB0AKf7nvHJy0qBXY2B4lxgwAGg/WTGp5AolCBAF4GSsnLYbn+OtLxiLOjWFEt+YvbLNF27hD2Oy9hHqAEwmWzFihXYs2cPxUd64sQJTJ48mWqVTE6qSPA7cuRIkLxhGRnROF0S1mbgchOQD2FSdiG2DrbCeFt2gtMJ/hF4mpaN8Q20sKe5kbBgrZXzFBYmwO0tL+jt2OE+VFXp0cZlZGRQXzSJzJo1C/r6ghWtZT+LRvazGMg1UIbeQsFOk5lcGJfzJ+F9/5ZQKNAK80ooCjQigxa1QcPmzF1ZFoWFIaI/Lwg1cb4PBVN20pEqsf+2AO72oNsw1WB3PibXvFq64n2A4115r871AHTqZoBRLawkLwkdgZfByZhy2pOa9/lSJ5jqqAjdBlGYkMvYR+gBMJlwzpw5+OOPP6ggt2/fvrh3j8dzStomk6Kduhb8Et+53ATWW58iNbcYu4a1xKgOjVj5TIzwDcPrjFxMb6iNrWbMnZqxYizHSrOz/eHpxUt7cHRwh4KCDi2LSNvwSuaV5cuXQ1lZmZaeykHp10OQ7/UF9ZrXh/Zk0Wlmcnv3FoR7vYelU3f0nrNYIB/5DSbNL0gTDCKTdzlAWV2wJj/fzpfl7IyEpcsgJS8Pcx9vSLF8A1ZZAKcoq4h3Y95BRlrMDh3eHQYerwaUtIDl4YCItO3mt8ckz+sGAosuf8Bt3wS0aqiOu/OYLaatTQhyGftwEgCTSQkzBAl2SToEOfklV7Tnzp2rkzkwXAfAbTY/QWZ+CastGAd4h8IzOw/zGuliralBbfp8Ct3W1NQX8PMnhW9SVBtkaWl6qUCBgYFUESm5bSFd4MhnTRBJORmAotBMKNs2gOZg0WHyECYFGml/TNogKyjJUhRogmL67Xok792HtD//hIJFC5jcvCnIUlVr7Pb323Ep6BLa6rbFuT7nqjWmVr10eRwQdB9o3h8YfaFWmS4xVrwRyCsqhfXWZygoKcO6/haY5lh362LEOgD29/evcieT/MQZM2bgw4cPsLOzw+HDh3/YprVVK9Fpu8rGR5PLTWC14TFyi0pxYHQbDGrDDk1QT89gBOQWYLmxPpY2Eewqng38RUlnQsJVfA5aBTm5+ujciXdFRkfc3d3x6NEjqKurY/FiwU9Gk37zQmlKAdR6G0Oti2iksfyDAm3BcjR3EIzpgh/Ob66Hwu9ZLPRN1DBshTW/12v0PPbnWch1dYX6oEEw2LWzRmPpvDz+wXj4pfhhXItxWNlxJR0VojumogLY3RTITwV+2gbYzxNdWyWW1TkEbn+Ix6IrvpCWAtxXd4euar06h0Glw1zGPj8CnREeYHL6JOgpCRlPAmZxFi43QfN1D1FYUo7DY9uhX6sGrMDc6f1nhOYXYZ2pAeY20mVlDnFRGhV1BOERv0FZ2Qy2No9ou/X06VO4ubmhYcOGmD6d11yBrpBbmoT1b1FRUo76o82h1EY01jA7JRnH502l3Bq/Yz/0TNg9mb530Bcxgelo4dAA3SbQy83+3hqEduuG0oRE6K5YAa2pU+guVbXGkQI4u4t2KCwrxDbHbRhoOrBa42rNSykhwOEOPHNnvAQMRSdnvdZgKDGUNQQmnfKAa0gKOplp4/w0G9bmqQ2KuYx9hBIAC7oIklbIgiL44/FNVz9AaXkF/hjfHr2t2DmdtX4XiLjCEmwzM8S0hvRyWtlFQXS0B4dsRlzcWWhq2qFd279oG3bz5k2QGxgLCwuquFQQKcsrQeIWd0qFzqxWUDBWF0QdY2P/SYF2FQpK7HITn13thtz0IjgMb4o2PZjLly/LzkZIR94fQqOTJ6Di4MAYRlUpCs0IxdC7Q6lHNwfehJmmYAwhrBpLR7n3GeDeQkBeBfglGpChl0ZEZ2rJGAkCP0IgJacItjueo6y8AntHtsbQdnW7JkasA2A/Pz9GPg2tW7dmRI+oKuFqE5CTvSarHlCwsNmH3OrNR6SWlGKvuRHGGmiJ6jKIhF0BHxcgOdkZenoDYGW5n7ZNZ8+eRWRkJGxsbKh24oJIcXwukg/y2v/qr+wAWQ3RuLLze/oAz04cgZK6Bmb/Sf/LQnWwKS4sxfFFr6hX+89vjcaWzO3jfC8vRI+fQOk2e/Mastra1TGJ9jt3wu5grdta1JOpR3WAk6WZZ07bALYH3vwZ8L8MmHQFJt5mezaJfgkC1UbgtFskNt37hHpy0vBa2xMqCnX7yxlXsQ+/BWMkBYLfJJLnPAS42gSlZeVouuYhZcPZqR3h1Iyd01nTV/7IKyvHUYvGGKInGi10RXXvefuMRWbmexgZTUEzM16DBzpy6NAhpKamokePHnB0FKzKuCAwDWnnP5G6PBhudYSUjGAFdXT8qWqMy7kT8Ha+LRQKtOTobFzbweuEN2GbHdS0FJlyA+kXLuDLlq2QqV8fzd7yOkOxKTve78DFoItordMaf/Vl94sDm358V/f+lkBmDNB1DeC0ghMTJJNKEKgKgUGH3eAXm4mBrQ3w+5i2dR4krmIffsBLAmB+CDH4nKtNUFhShubreHmmF6bbwKEpOydPhi6+KKsATlsZo4+OBoPIiZ+qd+69kJ8fBlOT5TA2nkXbwR07dqCoqIjqqijoDUquWzwy70VARl0eDVaJTs6aMCnQgtwT8fzMZ8gqyGDmvs6QIhUsDEniho3IvHIFSna2aHz6NENav69mwoMJ8E3xxZjmY7DaZjXr8wl1gqx4YB+vkQwm3Qea0GskI1SbJZPVCQQiUnLR7TdXytdTk63RrblenfD7R05yFfvwA14SAPNDiMHnXG0Cwv5AWCCIXJlpCxsT5q51K+EpKa+AkSsvFeZSKxN01VJjEDnxU/XqtTVKSjLQovkuGBgMp+UgCXxJAExk4sSJMDExoaWnclDmg0jkvoqDfGM16M4WnXSk00tmIz0+Fg4jx8N22GiBfOQ3+N2tcPg8joZuY1WMWPW1wIrfoGo+jxo9BgW+vqg/aRL0VrHLyFBWXga7S3YoKC3AFoctGNx0cDWtrCWvBVwHbkwDpOWAVbGAHHMn9bUEAYmZIorA3qch+P15KOory+P96u6Qk5EWUUuFZxZXsQ8/DwUOgJ88eYKffvqJ3zw1ep6eno6oqCi0aydeVb1cbYKs/BK03vyEWoMbs+3QvjFzna0qFzantAxmrwOoH2+1bQo7jbrZ8aY6G728vAQvXZpTr7ZudQLa2l87WVVn8DfvpKWl4eDBg9S/zJ07Fzo6gqW2pF38jAL/VCi21oHWGJ59XMs/KNAWrkBz+86smuR8xB9R/qkwt9FHjylfTxgZmJH4EWLdAeX5+WiwbRs0hvGK09iS8MxwDL7DC3pvDLyBZprN2JqKG733lwBeJ4GGHYHpT7mxQTKrBIF/IUDqbbrscUF0Wj4m2TXGpkFWEow4TP/kB77AATChQCMFOISEn3R8E0S+fPmCvXv34ujRo1i2bBnWr18viDqRG8tVAJyaW0QRchO5M9cBrY2YT09IKS5BS7dAao6H7ZuhrRq7lfoit7g1MKio6AveuNlTIzpY34aaWssajP7/q6T4jRTBEVm5ciXq1ROsaC35iC+KY3Kg0rkhNPqKBmm7sCnQ/lr3DlkpBbAdbIL2vY1prUtVg4pjYxHek3dQYHztGhRbsvuH8V74Pax+sxoKMgpwH+sufgVwR+yA5E+Aw0Kg52bG1kmiSIKAIAj4xGRg6JG3lIqbc+zRrpGkFoZgwVXsw28tBQ6Ax44diytXrlDzGBgYYMyYMRg1ahR1elsdbmBy2nv//n1cunQJz58/p7iAjYyMqI5xTk7sEt7zA4fp51xtgi/ZhbDZ/pxyx3mBIywNmKe3iikoQkf3z9QcLh3N0VxZciX5vf2TkxMID08eJ6uD/RvUq0ePl5nQnxEaNDk5Oaxevbpan7cf7enEHe9RllUMjYGmULEXjU5+0f6+uL6NVyQ47zS7FGilJWX4c4ErSH+FvrNboklrwU7Uv8U659kzxM2bD0hLUy2QpQX8ssLvd9Muj1346/NfaKXTChf6ilmHtPx04NevX9DGXAHMe/ODQ/JcgoBQENhw5yPOvotGYy0luCzrIvDvZKEYLYRJuIp9+LkmcABMJvD29saKFSvw8uXLvxdcWVmZCoJJYQ65mq1fvz4UFBSQkZFB/UdOrzw8PKj/EyFXB5qamli1ahXmz59PvStuwtUmiMvIh+OulxScjxd1hrm+KuPQhuQVorNHEKX3vW0LNFYUv/VjCrS0NFf4+vEaO3Tt8gnS0vSwIg0wSCMM8tlasGCBQOZVlJUjfq0bUAFoTbSAogXzeeJ0DBQmBVpqXC6ubPWgzBy3yRYaeszdYqQcOYLU3w9C3sQEpg+c6UBRozGTHk6CT7IPRpmPwlpb+iwjNZpUWC8HPwQukVxwKeCXSEBRcsomLOgl83wfgZKycuqgKT2vGAu6m2FJTzFLOxJg8bmKffiZzEgAXDmJr68v/vzzT+o0Nysri/rn750Ck4C3Uuzt7amWyYTIX1FRfE8OudoEUal5VF4SkedLnWCqw3x+rl9OPnp5hVBz+NlbQk9Bjt/eq7PPExNv4NPnFZCVVYNTZx7vLh0hLZBJK+TGjRtjyhTBuoqVZhQiaRevJbPugraQN2B+j9DxUZgUaKFeX/DkRCBkZKUx80BnSDNYvBK3cBFyHj+Gau/eaLh/Hx0oqj2mvKIcthdtqQK4zfabMcRsSLXH1ooXn6wD3v4O6FoCc3jXzRKRIMA1Ai+DkjHlDO936IulTjBh4e8s1z7SnZ+r2IefvYwGwJWTkep08of59evX1ClvQkICxVVaWFgILS0taGtro0WLFujUqROV5kDauNYF4WoThCXnosdeHi2L6/IuaKylzDjc7zNzMehDGKU32NEK6nJ1m/j7RwBHRx9DWPivUFIygZ0t/QKea9euITAwEFZWVhg+nB6TxN+f2cgspBzzp35ssM4WMsqi8QVGmBRo7+9FwMs5ClqGyhi9jlkauPDefVAcFQWdhQugPXs245+/bxVGZEVg0O1B1D9dH3Ad5vXNWZ1P6MpP9ADiPIEO04F+vwl9esmEEgSqQmDBpQ+465eA1g3VcWeeYJzs4oYwV7EPPxxZCYD5TVpXn3O1CYKSstF7/2sKdreV3WCowfwpu2t6Dkb5hVNzRDu1goK0hPrle/s8NHQ7YmJPQkOjI9q3u0T743Dq1CnExMSA3KAIysSS75uM9MvBkJKThsFme5HJXRMmBdqjPz8i3CcZTa110Ws6c0Vq5QUFCG7XnuR5oeGRw1Dt1o32mldn4P2I+1j1ehXkpeXhPs4dcoQqTFykOB/YaQSUlwLDTgItBfviJy6wSPzgFgFCNWq99SkKS8qxYYAFpjiIRhExt6j8f3auYh9+/ksCYH4IMficq03wMT4L/Q++oTzxWN0dumqCsQVUBcnj1CxMCogECXvju7QWmQCKweVjTFVg4BIkfbkDXd2+aGnFozGjIwcOHKDy6Xv16gU7Ozs6Kv4ek+0Si+xHUZDVUYT+UmuBdDE1uLy8DL9PGIay0lL0EwIF2qXN75GekIcO/ZugY3/m/oAVBHxE1IgRFCymz55BvqEhUxBVqedXz19x/tN5tNRuiYv9LrI6l9CVR74Czg7gTbvkM6AmGsWaQsdBMqFIIXDTJw5LrvpBRloK7qu6Q0eVXl2HSDnFoDFcxT78XJAEwPwQYvA5V5vANzYTgw/zWq96r+0BLRXmP5y3v2Rg1qdoKMlII6JzKwZREz9VHz5MQnrGGzRsOAHmzTbScpDk0G/bto1iTSHpDyQNQhDJuB2GPPdEKJhpQGcaPVo2QeavaqwwKdDKy8pxbIEryssq0GuGFZq212XMncwbN5C4Zi2klZXRzMuT9S+HUx5NgdcXL/EsgHPZBbhsBzQaA4t4KTsSkSDANQITT3ngVUgKnJrp4OzUjlybI3LzcxX78ANCEgDzQ4jB51xtAq+odAz/4x3lid+Gn6CuyPyV6OXENCwKikV9ORl8chSNAIrBpWNU1XuPfsjNDYJJk8Vo0mQeLd0FBQXYtWsXNXby5MkwNhaMszb1TCAKg9KhZK2H+sNFo3o5OsAX17dWUqBdgYIS87nrleBnJOXh4sb31I+j13WEliFzRYBJ27cj49x5KLZpA+PL9FNeqrNRSAGc/SV75JXkYZP9Jgw1Y7fhRnVsYvSdc4OACBeg9RhgyB+MqpYokyBAB4HknELYbn+O8gpg36jWGNK2btQ01QQrrmIffjZKAmB+CDH4nKtN4B6RhtF/ulOeBG7qBWUF5gvUTsenYlVIHAwV5OBtb8kgauKn6vUbGxQXp6K5+TYYGtJr7ZucnIwjR45Q4BAKNEKFJoh82e+DkqQ8qPVoBLUejQVRxdhYYVKgRXxIwcNjAZCSlsLPB5wgI8dcDnv0pMnIf/8eGqNHocFGeif+1QU1KisKA27zUgSuDbiG5vVFo6Nfde3/4XtlpcDORkBJHjDgd6D9JEbUSpRIEBAEgVNvIrH5/icoysnAa20PVv6+CmKfKIzlKvbh57skAOaHEIPPudoEb0JTMf4k73QreGtvKMjKMOgVT9XRmGRsCk+AqaIC3GxbMK5fXBRWVJThxUsSlJSjVctj0NHpQcu18PBwnD9/nhq7Zs0aqhmGIBK/8R0qCkuhObwZlK31BFHF2FhhUqB5PYzC+zsRFPcv4QBmSkiqSqidPcoyM6G/YT00x4xhSnWVeh5EPMAvr3+hCt/ej3svXgVw8d7A8a8FhPO8AG0zVrGUKJcgUB0EBh56A/+4LAxqY4ADo9tWZ0ide4er2Icf0JIAmB9CDD7nahO4BCdj8mkeP2H49r5Uoj7Tsi8qCbsik2CpUg/PO4jRqRPDQJGTX3ICTMS6/XWoq9P7hUk4t2/fvk21PyZtkAWR8qJSJGzgpchoT2+Jek2Zb5VNxz5hUqA9PRWIEI8vaNJaG31nM5fDXpKcjLDOvI6WjS9egFK7dnSgqPaYPZ57cPbTWVhqWeJy/8vVHlcrXnx7CHiyBlDWAZaFEpL5WmG2xEjxRSA8JRfdf+NRjJ6e0gFdzZmrHRAn1LiKffhhKAmA+SHE4HOuNsGzT18w/ZwX9fcickc/Bj36v6odEYk4EP0F7dWU4NxeNHJIWXFUQKW5ucF479GX0mJv5wJFRSNaGl+9eoUXL15QXRbnzp1LS0floJIvefiyz4f6UW+ZNeS0mafJo2OgMCnQrmzzQGpsLtr3bgzbwaZ0zK1yTO7rN4idMYN61szTAzKqzHdh/HbiqY+nwjPJEyOajcB6u/WM+SESii6PA4LuAy0GAKP+EgmTJEbUbQT2PgnG7y/CoKUsj/eru0OWweY54oQsV7EPPwwlATA/hBh8ztUmePQxEbP+8oGcjBRCt/GCL6ZlQ2g8jsWlwEFDBTfaNmVavdjoS093wwffiZQ/XZw+QkaGXrDp7OwMT09PmJiYYOJEnj66UhicjtTTgdRwwy32kJJjPkWmprYJkwKtorwCfy50RWlJOXpMsYC5jX5Nzf3u+2knTyJ59x7IGRig6YvnjOmtShEpgHO45IDcklxssNuA4c3EiCOXdA7dbQrkpwG9dgB2c1jFUqJcggA/BEh6k9NuF8Sk52OyvTE2DpTUvnwPM65iH35rKAmA+SHE4HOuNsF9/wTMu/iBStL/vKU3gx79X9WK4FicS0hD9/pquNDahJU5xEFpUtIdBH5aAhkZZXRxok/jdPnyZQQFBaF169YYMkSwVre57xOReSsM0ipyMFjLXP6rIOslTAq07NQCnF/LSwEZuboDdBoxd0obv2IFsu/eg0rXrjA6yitaZEuis6PR/1Z/Sv2V/ldgoWXB1lTC15sSDBz+Si810wUwoJc6JHzDJTOKKwLe0RkYdpTXivvWHHu0baQprq4K7AOwlFoAACAASURBVBdXsQ8/wyUBMD+EGHzO1Sa4/SEei674QlVBFgGbejHo0f9VLfgcjatJGeino46TVsw1EWDFWA6VxsScRGjYdigqNoK93Uvalhw/fhzx8fFwdHREjx70CukqJ896HIWcl7GQM1SB3nzRCCyi/X1xfVslBdpVKCgp0caK38CogFQ4H/YHpICZB5wgJ8/cCXjE4CEoCgqC1qyfobtoET9TBHr+KPIRlr9aziuAG/secjKCFUYKZAzTg71OAfcXA/IqwC/RgAzzTDZMmyzRJ94IrL/zEefeRcNYSwkvl3Vhnd+7NqPJVezDDzNWA+DU1FQcOnQIT58+RXR0NAh3aVpa2t82ZWZm4uLFi9TGmTVrlthvIK42wXXvOCy75gdNJTl8WP8Tvz1B6/nMwCjcTc7EcD1NHLIQDRotWo6wPCgs7FdExxyDuno7WLe/Rnu2vXv3Ijs7G3369IGNDa+ojq6kXw1Gvk8y6lloQXuiaJwaVlKgKaqpY87xC3Rdq9a4D09i8PZmGFS16mHiNvtqjanOSxUlJQgiLZBLSmC49zeo9WUn/ajSlr1ee3E68DR18ktOgMVKbswAAq4Cpt2ACbfEyjWJM7UPgZKycthsf470vGIs7G6GxT0ldS8/WkWuYh9+O4u1ANjV1ZXqUJWeng6SK0OEBLplZWX/sKl9+/YgFe0vX75E586d+dlbq59ztQkue8Rg5c0AaKsoUDyFbMhE/wg8ScvGBAMt7DanV9jFhl2ipvPTpxVITLoBHZ2f0KrlUVrmlZeXY+vWrSD/HzlyJCwsBAtaU/70R1FEFlQcDKAxgLkCMFrOfR0kTAq05+c+I+htIhpbaaH/vNaCmP2PsYUhIYgcOIj6NxPn+1AwZRfb6Y+n433Seyr3l+QAi5XsswKyYoGuawGn5WLlmsSZ2ofAi6AvmHrGizKcnP420WavSU/tQ+e/FnMV+/DDjpUAmDjbsmVLZGVlwd7eHqNHj8b69eupn/8dAB89epSqYidk/vv37+dnb61+ztUmOO8ejXW3P6KBej28W9WdFQxH+IbhdUYuZjTUxhYzSSec74Hs6zcVaWmuMDQci+bmW2itRW5uLvbs2UONnTZtGoyMBPvCkfirJ8rSC6HerwlUO4nG2t36dTMivD1g6dQdvecspoVTdQdd3+WFL5HZaNOzERyGMVfAmXXvPhKWL4eUvDzMfbwhJcvetT05ZHC47ICc4hyss12HkeYjq+u+6L+XGQvs/9rqe7IzYOwo+jZLLBRrBOZf+oB7fglobaSBO3MdxNpXJpzjKvbhZzsrAfCiRYvw+++/U8U5169fp05+GzRoANK96t8BcFRUFFXJ3rZtW3h7e/Ozt1Y/52oTnHGLxMZ7n9BQUxFvfvlKJM8wkgO8Q+GZnYf5jXSxxtSAYe3io87DcyBycgLRxHgBTEwW0nIsMTERx44do8YuXrwY6urqtPSQQYQBIX6dG1BWgfpjm0OplQ5tXUwO/JsCbdQE2A4dxaTqf+gigeOJxa9QXFiGrhOaw8KBub2b/NtepB0/jnoWFmhy8wZrPhDFsdmx6HuLl2Jxud9lWGqLUUW6/1Xg5gxAWg5YFQvI0WNOYXUBJMrrDAK5RaWw3voUhSXl2DjAApMdJDUv/Bafq9iHn12sBMDNmzdHaGgoPn/+jGbNeLkx3wuAyTNFRUWK0D8jI4OfvbX6OVeb4MTrCGx1/kxd05DrGjakp2cwAnILsNxYH0ubMEcjxYatXOp84+aAoqIkmDfbhIYNx9MyJSQkhMqdJ7Ju3TrIyNAv2irLKUbiNl6XQJ05raHQSI2WTUwOEiYFWm5GEc6ucqPMH7aiPfRN6H+Z+DcGMT//jDzXV1AfMgQGO7YzCdF/dD2KeoTlrsshKy1LFcDJy8izOp9Qld9bBHifBoxsgGlPhDq1ZDIJAv9G4IZ3HJZe86MaShHuX5JaKJEfI8BV7MNvXVgJgJWUlCAtLQ1yVVspPwqACZk/SY8oLi7mZ2+tfs7VJvjDNRw7HwbBTFcFT5fwulIxLZ3ef0ZofhHWmxpgTiNJN5yq8CWnjS9dWqCiogQtrQ5DV5ceJR25Kbl37x6UlZWxfLlg+ZDFsTlIPuxLmdtgtQ1k1LgPnLKSv+DE/GmUTeN37IeeCXNpCf9el9jP6bh7gOf/9H2doaDIXJpCaJeuKE1Kgu4vv0BrymSmP3L/0LfXey9OfzyNFvVb4OqAq6zOJXTlh22AlCDAYRHQc5PQp5dMKEHgWwQmnHyP16Gp6GKugzNTvlLzSSD6IQJcxT78loWVAFhNTQ0lJSUU6wO/AJgEvSoqKiBjCGuEOAtXm+DQi1DseRKC5vqqeLSInUJD63eBiCsswXYzQ0xtKBrX6KK2l0pKMvHqdXvKrPbtrkBDw5qWiS4uLiD/6evrU+wpgkh+QArSLwQBMlIw3OIAKRbaZNfUPmFSoPm9iMWbq6FQVpfH5F3M5ZaWZWUhxIbHqdzo1Eko2zPHLlEVntOfTMf7xPcYZjYMG+031hRy0X0/Px349esV89irQDN2aBxFFwCJZaKEQHJOIWy3P0d5BXBgdBsMamMoSuaJrC1cxT78AGElAG7VqhUCAwOpNAiS30vkeyfAd+/exeDBg6liuTdv3vCzt1Y/52oT7HsaggPPQ9HSUB335jP3R/7bxbB88xFpJaXY29wIYxto1ep1Ysv4vLwwuL/n/QG3s30GJSV6uWPk9JecApuZmWHcuHECmZvzOh5ZzhGQqV8PDVZ0EEgXU4N9nzzA85NHoKSugdl/stvy1uViMAJfxaNhc00MWsQcB3K+pyeiJ/A69Jm5vYGsFnufCXKz4HjZEdnF2eJXABfkDFweSziEgF+iAEUNpraZRI8EgRojcPJNJLbc/wQleRmKUUlJnrkboxobU4sGcBX78IOIlQD4l19+oarU582bhwMHDnw3ACY8wLa2tlSgvH37dpBx4ixcbYI9j4Nx6GUY2hhp4DZLFaumr/yRV1aOoxaNMURP0hGnqn2ckeEOnw+8gNWpsy9kZel1HCP5vyQPmBSODhrEo9miK5n3wpHrlgD5JmrQ/Zk5CjC69pBxLueOw9v5DgzMLTBm86+CqOI79tZvPkgIzUTLrg3ReRRzXJ7pf13Al61bIaOlhWZu7H6xj8uJQ5+bfShfL/a9iJY6Lfn6XWteeLwGeHcI0LMCZvNytSUiQYArBAYcfIOA+CwMaWuIfaPacGVGrZuXq9iHH1CsBMBfvnyhTqfy8vKwceNGEFYIUgxXyQJBUiPu3LmDNWvWIDIyEiQHmATBJA1CnIWrTbDj4Wccc41AB2NNXJvFzlWsoYsvIRLAaStj9NGRnNJUtY+/fHHGx8AFkJZWQBenQNqNXwgDBGGCcHJyQteuXQX6yKSd/4SCwDQotdVF/VHmAuliavD/KdB6oPccdrunnVr+GgU5JXAaaw6rzsxdZyauW4/Ma9egbG+HRqdOMQVNlXqeRD3BUtelkJWShfs4dyjIiFFRzvFuQLw30GEG0I9H/ScRCQJcIBCWnIsee12pqc9M6YAu5pJal+quA1exDz/7WAmAyaSPHj3C0KFDUVRUBDk5OYq0n1CgkcCYUJ+RHGFydUcK5h48eEC7CQbJG16xYgV1JUxAJkG3gYEB1R1r5cqVaN36+6dapAFHhw4dUFpaivPnz2P8+P9W5fv7+1OBOknPIPnKhN+YzEd8q6lwtQm23v+EE28iYWeihUszeXmJTEpJeQWMXP0olZdamaCrlnh/kaGLXWzsWYSEbka9eoZwsH9FVw12795N7fP+/fvD2ppeHnHl5F8OfUBJXC5UuxpBvZcxbZuYHHh68SykJ8TBgWUKtIKcYpxazjudHbykLQybMXdzETlqFAr9/FF/8mTorWT3Zmu/936c/HgS5prmuD7wOpNLwa2u4jxgZyOgvBQYfgqwGsatPZLZ6zQCvz0JxsEXYdBWkYf7qu6QlZGu03jUxHmuYh9+NrIWAJOJSfBITn9JwU5V0qlTJxw8eBAkZ5iuhIWFYeLEibCzs0Pjxo2pyngSYJ85cwbkJNrZ2Rk9e/b8j3oS9JIgmVwlE7aKqgJgPz8/ODo6QkFBgfKDnFT/9ddfVDB84sQJqglBTYSrTbDxbiDOvI1CJzNtnJ8mWNvcqvzNKS2D2esA6tGttk1hp6FSE1jqzLvh4b8hKvoI1NRao4P1TVp+ky+RW7bwGmiMGTMG5uaCndombHVHeW4JNIY0hYpNA1o2MTnoWwq0/ot+gbldJybV/0NXQmgGbv32gfq3qbsdoajKDANGRXk5gq07oCI/Hw127IDGkMGs+UAUz3wyE+8S32FI0yHY7LCZ1bmEqjzCBTj3NcVnSRCgxv3+FKr/kslEBgFyWNd590vEphdgsr0xNg4UI55tIaDMVezDzzVWA+DKyUlA6ubmRl3bkj/genp6cHBwoE6D2ZKEhAQ0atSIOll+8eLFf6bZuXMnlXdMTnMJl2pVATAZS4JdDw+Pv0/aSOBMCvaCg4MRHR0NDY3qX/dztQnW3ArAhfcx6Gqug9Ms0LYkF5Wg1dtACuOH7ZuhrZoSW8taq/V+/rwKCYlXoa3dHa1b/UnLF0IXuG/fPmrszJkzqdsOulJRUs5rggFAa4olFM3r01XF2DhhUqB9fBUP14vBqKcih2l7mAu0i2NiEP4Tr9iRNMAgjTDYEvKHudOVTsgqysIamzUY3Xw0W1MJX+/LHYDrTkDTGFjIu2GSiAQBLhDwjk7HsKPvqKlJHQ2pp5FI9RHgKvbhZyErAXBMTAw1r66uLtXgggshgbampiaaNm0KHx+ff5hATn1JasSvv/4KVVVVTJky5T8BMAnamzRpgi5duuDly5f/GE9OgSdMmIDTp09j8uTq83tytQlW3vDHZc9Y9GihhxOTBLsyr2otowuKYOP+mXrk0tEczZUlnZqqwsnPfyZSU5/DoMFItGixg9bHguwhcvtAZOnSpdT+pSulqQVI2sPrZ6+3uB3k9LjvZ/8tBdr8M1chr8jel6nXV0Lg/zIODZqqY+gyHj0dE5L99Cni5y8AZGSoFsjSCuzl5MbnxqP3DR6f9F99/0JrHdEoZGQCR5wdAES+AlqPBYYcZUSlRIkEAToIrLv9Eefdo6lmUi+WOtGu36AztziM4Sr24YcdKwEwaYJB/iNOE65SYQjJKSanY+SElgTgv/32G65evUqd7m7e/P9rQXJiQoqHSD7v27dvce7cuSoD4CtXrmD06NFYvXo1tm3b9g8XIiIiYGpqitmzZ+PIkSPVdo+rTbD0qh9u+MShj5U+jo5n7g99pePBeYVw8giifnxv2wKNFdn7g19tsEXwRU+vocjO9oNx49kwNV1Gy0LSXZHsTdJenOxt8jmjK4XhmUg9zktdMdhoB+l63FP6CJMC7c7+D4gLyoBlJwN0GdecLoz/GZdy6DBSDx2CvKkpTJ3vM6a3KkVPo59iicsSyEjJwH2sO+rJcnPgwLiTZSW8/N+SfGDgQaAdj1JOIhIEhI1ASVk5Om57hoz8Eizu0QwLe7B3cy1s34Q1H1exDz//WAmA1dXVISsri7S0NH7zM/ac5Bl/WxFPbCBNArZu3UrZUimHDx/G4sWLqaI5UtBGcoWrOgEmAfSyZcuoAJcEut8KCZ5JXvCAAQNAeIy/J9nZ2SD/VQpJAenYsSNiY2PRsGFDxnznp2jR5Q+47ZuAAa0NcHAMc1ynlfP65eSjl1cI9aOfvSX0FOT4mVQnn7u97YzCwng0M1sHI6Pq3xx8CxZJxyFFo+Tkl5wACyJ53l+QcS0EUvVkYLiRHXaQmtonTAq0M7+8QV5WMRxHmqF1N6Oamvrd9+PmL0DO06dQ69sHhnv3Mqa3KkW/+/yO4wHHYaZphpsD6eWVs2ogXeVxXsCJ7rzR87wBbfa6AdI1UTKubiDw7NMXTD/HuylzWdYFxtrc35TVNuTrVADcvn17fPz4ETk5OZCXZ6awhN+CZ2RkUEEtYZ0gKQ4kp5cUxpE0B1IYR4ScDFtZWVH8xCT/l8j3AmBSaLR+/XqcPHkSU6dO/c/05OStW7duePbs2XdNIxRwmzb9t3WnsAPguRd94OyfyBp34fvMXAz6EEbhEOxoBXU57k8S+e0XYT8nNw8urpYoLy+CleUB6On1p2XC8+fP8fr1ayr3l+QACyLZz2OQ/TQasnpK0F/M/M0AHdv+T4HWHb3nLKajolpjigpKcWIxj4lj4II2MLJgLv85vFdvFEdHQ2fRQmgL2KmPnzOzns6CW4IbBpoOxDbHf95U8Rsr0s/dfgeergOUdYBloYCUlEibKzFOfBGYd9EH9/0T0baRBm7NcRBfR1n0rE4FwKQJBikuO3v2LJUry4WQgJjk+VpaWuLhw4eUCX369AFhjQgICPg7N7kunADPOu+NR4FJGNG+IXaPYD5H0CU9G6P9IiiMo51aQUGAa3ku9oow5iwtzYHrKx5xeru2F6CpSY+O7vbt2yD0fYT9gbBACCIZN0KR55mEes3rQ3uyaFQ1C4sCLSkiCzd+9abgm7TDASqazKTtlOfnI7i9NVBRgYZHj0BVQJ7mH60vlc51xQkZRRlY2XElxrUQrCugIHuJ8bGXxgLBzkCLgcCo84yrlyiUIFAdBHIKS2C99RmKSsuxaaAlJtmLBlVkdWwXpXfqVABMCtB69epFsSeQQrFhw7jhbyQnvSTlgTTb+PDhA8XdS5oIkJPbSrl58ybVgY4E7aSrlqGhIRQVFak8S3HJAZ5+1hPPPidjTEcj7BhKn3Luex+oRylZmPwxkjQrRUKX1pICgSqAys+Pwjt33pWurc1jKCvTu9IlNxvh4eEUf3W/fv0E+h2XcuojikIyoGyjD80h3Oe1CZMC7fPbBLw4FwS5ejKYsa8zY3u2wN8fUSNHUevS9PkzyBky11zj34udmJuIn278RP3z+T7n0UZXTDpTlZcDu02BgnSg907A9p8paAJteslgCQI1QOC6dxyWXfODjLQUPFZ3h5YKM1+Ua2CCWLxapwLgJUuWUMVo5HSVEPYTfl7S8pjw6MrIyFS5oKSoh+TdMimEp/fUqVMUC4SrqyuV+8tPnj59ih49elBBs4mJCZVX/G8atdrGAjH5tAdcglMwwbYxtgy24gdBjZ/f/pKBWZ+ioSgtjUgn5gPsGhskggMyM73g7cMLjDp38oacHD0aHZKTTjoqki9xhKZPEEna64XS5AKo9TKGWlfmcmDp2vQPCrSdB6DXxJSuKr7j3G6EwfdpDPSaqGH4L8wxo2Rev47EtesgraKCZp4ejAXWVTn0PPo5FrksgrSUNFUApygrJuwryUHAka985TNdAQMxCez57krJC6KGwPgT7/EmLBXdmuvi1OQOomZerbGnTgXAJD+WBLTkiq5SyM/fE/IeeU5OjmsqpNkF4RX+txAaM5KLTHQmJSVRjBTk6vjfQornyCnxggULQBpzkKCC0LcRIU0wCFOEp6cnpYtIJQ9wUFAQxQNMqNaqK1xtgsoP8RQHY2wYwPxV96XENCwOikV9ORl8cmxZXTjq1HvJyY8R8HEOpKRk0bVLEO3AaNeuXSCtxMltRdu29AsayWcuYcNbVBSXUy2QSStkrkWYFGj3D/shOiANze300X0Sczy9Sdu2I+P8eSi2bw/jC3+xCmllAVxTjaa4NegWq3MJVbnXKeD+YkBeFVgZDUhXfWgiVJskk9U5BL5kF8Jux3OUVwAHRrfBoDbs3eaIO7hcxT78cGWFBWLw4MG0/sDfulXzX+KkQxs5te3bty+MjY2peQlVFKE3Ix3eSB5yVS2OK4H5Xg4weU5OjklATLiMyemxtrY2Lly4QBUhkVSKmhYhcbUJRv/5Du4R6ZjRqQnW9GPuj30lhqfjU7EqJA6GCnLwtmc+wOa3iWvD87i4CwgOWQ8FeT04Or6lZTKh+quk5CN7mnBc05Xy/BIkbHanhuv83AoKTdTpqmJsnDAp0M6vfYvs1ELYDTVFu58aM+ZD9MRJyPfwgObYMdBfv54xvVUpmvVsFtzixbAA7sYMIOAqYNodmCBGzBas7gaJcqYROPE6AludP0NJXgZea3tASV5S3E0XY65iH372shIA85uUyeeEhYEEo15eXtTVMDmhbdCgAdVpbuHChRTt2I/kRwEwGUfaIa9Zs4bqCEfozwh12vLlyzF8+PAau8HVJhh+9C28ojMwu4spfunNHN9pJQBHY5KxKTwBpooKcLNtUWNc6sKAiIgDiIz6HaoqlujY8fvUeT/CghR2HjhwgHqFUPNVdfNRXSyLE3KR/DuvDbD+ig6Qrc89f2wlBZphcwuM3vRrdV2p8XslxWX4c6ErUAH0m9sKxi21a6yjqgHkVD3Uzh5lmZnQ37gBmqPZ68pG5upytQvSC9PFrwBunxWQFQt0Wwt0Xs7I2kiUSBCoKQL9D77Gx/hsDG1riL2jJGk4NcXv2/e5in342VzrA2B+DorSc642weDDbvCNzcT8bk2x9CdzxiHZF5WEXZFJsFSph+cdmA+wGTeYA4VBwesQH38RWvU7o02b07QsIDR+JKedCGFZUVKi3yWt4FMa0s59AqlcNNzqACkZ+g01aDlTxaC/KdC69EDv2YuYUvsfPSkxObi63ZP69/Fb7KCuw0zubMmXZIQ5OVF6G1+8CKV29FNU+DmflJeEntd7Uq+d63MObXXZm4ufLYw+z4wF9n+tU5jyEGgsGvzUjPooUSbyCIQl56DHXh5N4rmpHdG5mY7I2yzKBnIV+/DDRBIA80OIwedcbYLKb7JsdbHZEZGIA9Ff0F5NCc7tmzGImPio8g+YjZSUJ2igPxQWFrtpORYYGIhr165RhaRr166llWZUOXHuuwRk3gmHtJo8DFZ/LTiiZRVzgyop0BxHT4TNkJHMKf6XphCPJDw99QkyctKYecAJ0tLMcMzmvn6N2Bk8buZmXp6QUVFhzYcXMS+w8OVCSEGKKoBTkqP/ZYg1I+ko9r8K3JwByMgDK2MBOe5vJui4IRlTuxHY8zgYh16GQVtFAe6rukFWBA4IajOiXMU+/DCTBMD8EGLwOVeboPf+VwhKysHyXuaY25V+3uj3oNgQGo9jcSlw0FDBjbbM62dwCThT5eU9AllZPmjcaCaaNv2Flh3v3r3D48ePoaGhAZL7LohkPoxErmsc5BupQncO99d7/6RAWwlzO0dB3PvhWPc74fB+GA1tIxWMWvPjFKmaGJF24gSS9/wGuYYN0fTZ05oMrfG7hz4cwjH/YzBRN8GdwXdqPF5kB9xbBHifBhrZAVMfiayZEsPEFwGSXtTp15eIyyjAVIcmWD+A+boZ8UWvas+4in344cxKANyuXTt+8/7nOSleI53cxFm42gQ99roiLDkXq/o0x89OzFNLrQiOxbmENPTQUsNfrUzEeQlp+/b2XTcUFETDrOlqNGo0jZaeJ0+eUKwkRkZGIBR/gkjapSAU+KVAsZU2tMZyn7ctTAq0h38EIMI3BWYd9PDTNOaKNuOXr0D2vXtQ6dYNRkcOC7I8fMfOfT4Xr+Jeob9Jf+zotIPv+7XmhcM2QEoQ4LgE6LGh1pgtMVR8EPCKSsfwP95RDt2d54BWDelRVooPIoJ7wlXsw89yVgJgQoNWHfmWKo0uDVp15hGVd7jaBF12v0RUWj7W9bfANMcmjMMx/3M0riVloL+OOk5YMa+fcYM5UOji2hplZbmwtNgLff1BtCy4ceMG1cWQdDccMWIELR2Vg5KP+qE4OhsqnQ2h0Zf7Ly1R/h9wY9s6yrz5Z65CXpG9K/2LG92RkZQPm4EmsO7LXGeniIGDUBQSAq3Zs6C7cKFA68NvcNerXZFakIoVHVZgggU33Tb52Vjj5/npwK9ff3+Muw6Y8XKcJSJBQJgIrLkVgAvvY2Cio4znS5wESjUTpt2iPBdXsQ8/TFgJgCsr1b83eVZWFsWt++jRI6irq1MFPQoKChRrgzgLV5vAcdcL6jqHrVaOMz5G4V5KJobraeKQBXOUUuKyF8rKCuHiyjtpbNvmHOrXp9dPnjCWEH5r0lSmd+/eAsGTuMMDZVlF0BhgAhUH7vktfR874/mpo1DW0MSsY+y1vi0rLcexBa6oKK9A75+tYMoQ/3FFcTGCSAvkkhIY7t8HNQHX50eLm5yfjO7XeF0Fz/Q+g/Z6PI7yWi9BzsDlsaAqMwn/bz3uqflqPaYSB2qEQHFpOTpuf4bM/BIs6dkMC7pz3yGzRg6I6MtcxT784GAlAOY3aeVzQjFG+HvNzc0pLt/vdYmrrj5Rf4+rTWC7/TmSsguxbYgVxtkwH6BO8I/A07RsTDDQwm5z7juKido+KCiIw9t3PHYAm44PoKJCj4nj4MGDSEtLQ8+ePSmaP7pSUVaB+HVvgHJAa0ILKFoyQwNG1x4yTlgUaGkJubi82YMydexGG2jqKwti9t9jC4NDEDmId7Jv8uABFEzYuwlxiXXB/Bfzxa8A7vEa4N0hQL8lMOsNI+siUSJBoCYIPP30BTPOeVFDXi3vikZa7N1E1cSu2v4uV7EPP9w4DYCJcffu3aO6WpEOV4RfV5yFq01gvfUZUnOL8OuwVhjZgfkAdYRvGF5n5GJGQ21sMWsozktIy7esLF94eQ+jxjo6voeCPL2Ac/v27RQX9dChQ9GqFf2W06WZRUjayQsCdee3hbwhe2wF1QXs1q5NiPDxhCXLFGhh3sl4fPwjpGWkMPN3J8gwVN2dde8eEpavgJSCAsx9vCH1nZbv1cXjR+8d8T2Co35H0US9Ce4OpscpzYQdjOv4syuQ4AN0/Bnoyx4PNON2SxSKDQJzL/jAOSAR7Rpp4OYc+ocMYgMIQ45wFfvwM5/zAJi0KlZRUaG6WpH8RnEWrjZBm81PqCud30a0xrD2zAeo/b1D4JWdj/mNdLHG1ECcl5CWbykpz+Af8DMAaXTrStog17y1a1FREXbs4BU7TZo0CU2a0D9h0eza3wAAIABJREFULIrKQsof/pSuButsIaMsR8svJgedWjwLGQlxYJsCzdM5Eh73IqHZQBljNzBH/5a8Zw/STpxEPUtLNLlxnUlo/qNr/vP5cIlzQT+TftjZaSercwlNeVEusLMRUFEGjDgDWA4R2tSSiSQIEASyC0vQYeszFJWWY8sgS0ywY64+oK4jzFXsww93zgNgYqCqqirKy8uRl5fHz95a/ZyrTWC14TFyi0pZ62fewzMYH3MLsNxYH0ub6NfqNWLD+Pj4ywgKXgM5OS107sQ7ea2ppKam4tChQ9SwuXPnQkeHPjF7vm8y0i8HA7LSMNxiz3mRB6FAOzB+GMrLStF/0S8wt+tUU3iq/f7jEx8R5pUM07Y66P1zy2qP4/dizIyZyHv9GupDh8Jg+zZ+rwv0vPvV7kguSMYy62WYZDlJIF0iMzj8JXB+MM+cpSGAqp7ImCYxpG4gcNUrFiuu+0NWWgoea3qgvrJ83XBcCF5yFfvwc43zAJhQn3Xo0AGamppUfqM4C1eboPm6hygsKcfhse3Qr1UDxiF2fP8ZYflFWGdqgLmNdBnXX9sVRkYeQkTkPqgom8PG5gEtdyIjI3H27Flq7KpVq6iiUbqS4xqLrIdRkNVWhP4ya7pqGBuXlZyEE/P/x951QEWRNOGPnEFRBAmKChgxIYJiFrOe4Tyzd+acc845hztzzjmfOYsK5oAoSQQkS0Yk87+adb2VH2F2mN2BZeu9e3fHdldX1zTsN9VVXw1h9PVbsRGmFfin6hMbe2zxE0SHJKFeB2s4deKP/cK3aTNkRESgzIzpKDVgAG++yamImB+IAYJkT5s9cDRzlNlaclV8ZxlwbyVgXBEYJ2rRrRSlB+Tpgb673PHQLxotqpTBngEK8nslTwfmsZZQ2Ce/7QsKgO/cuYMRI0bAz8+PKYajfGBFFqEOgc2sy8jIysb2/g5oU53/CK3Do3cISU3HMlsLDLLkHplU1Gfv7bMAnz8fhHFJF9Spc4DTNqlg9OzZs9DU1MSsWbM46RBPij3vh6+Pw6BlUwImQ/iLgnI1Sl4UaFlZ2dgx7h6ICYL4f4kHmA/JiI2FbwNRy95y+/ZCz9mZD7W56iDuX+IAJnnc+zH0NYXP3+Zls/s6Ap8eALX7AV1ky6HMi71KJQrlgfD4FDRYcQvZ2cDm3nXQqZYylY/PBywU9slvDzIBwPk1wkhJSUFISAiSkpJAXVcomnX//n0mEqzIIsQhIP9WmCmKOu7+qx5aVuXnS1/yOVV380R0egbWVbFCn7KlFPkRctrbW8+xiIy8DDPTzqhefR0nHW5ubrh58yZKlSqFsWPHctIhnvRl/zukvI+Bbj1TGHcXvnW1vCjQ4iKTcXieO+OGnnPqo7QlP+Dxq8cTBP0lSkWwffQQ6sbGBXo+eU2m4jcqgrM2tMbFrgoSMMhIE+X/ZnwDOv8D1OknM/8pFSs9kJsHdt7/iKWX30NPUw3P5rSCjqb0dRpKz/7aA0JgHzbPQyYAmG0jDDKwatWq2LJlC5o2FdFEKbIIcQgyMrNgM/sK49b9g+qjqR3/EdpK99/ga2YWtlYrj66mJRX5EXLa2/MXfRAX54FyVoNha8stenvlyhV4eHjA2toaAwp4xR6x8QXSw77CoGU5GLXinxZPWifd2b8TLy6fh0WVaui1UHbV/wGvo3B561uoqIBhgFDX4OdLLubgIUQsXQo1k9Kwe/BA2u1LNZ7oz4gGrV2FdljVRHa+ksqogg4OfgrsdhVpGfsCKCW7FJiCmqqcr5geaL/xAbzCEvB7XUus7VFLMTcp4K6EwD5stisTAJxfIwx1dXUm59fe3p75p7iIEIcgJT0TVeZeZVx8eIgTXGy4UXDl9Yws7r5CZjawt4Y12pko20bm9NVj99ZITvaHTaVpKF+e2CCklxMnTsDLy4v5ffn9dxGlGlcJXfQYWckZKPm7LfQc+U+JkdYueVGgPb/6Ce7nPsLIRAf9FjeQ1sxfjg+bOxdxJ09Bz8UF5Xbv4k1vboqoAQY1wlCoAriHG4Eb8wB9U2CyN5g3FKUoPSAnD/hEJKL1+vvMagcH10djW/6DRHLaSqFdRgjsw8YZMgHAbBYujmOEOATE/kAsECTHhznDqSK/KQrpWdmwuvea0X+0ZkU0L2VYHB9tnnu+d78uMjLiUa3qKpQtyw287t69G8HBwWjYsCFat27N2cdZqZkInf+ImV96cA1o2wofsZcXBdrNfV7wdg+Hdc3S6DCKO49yTucH9OiJlDdvYDxoEEynyY7LXGEL4I70AnyuANW6AD1EhZ5KUXpAXh5YdfUDttz1h4mBFtxntoSaqvIFjG/fC4F92OxBCYDZeImnMUIcgrjkNNRedIPZwemRDeBQnt/8xMSMTNg+EPE3n6tjA+cS/ORV8uRywdVkZaXhzt2qjB21au1G6VLNONm0YcMGxMXFoU2bNmjQgHv0Mj0yGRHrnjM2mE52gIaJsJ2OfqZAm4HKDRpx8g+bSSeXP0VkYCLqtimHBl1t2EzJd0x2Vha8Heoh+9s3mK9cAaPv3eDynchhwIPPDzDq1ihm5qPej2CgacBBSyGbkpUFrKoApMQB7VYBTtxuSArZrpTmFBEPUGFs41V3EBL3DYMbVcDcjtWKiOVFy0whsA8bD8kEAFMRHPGUXrsmijzmJx06dEB4eDiIEk2RRYhDQB3gqBMcybnRLqhtxW+KQlRaOuwfvmP0X3WwQ21DYQFVYTs/KSlhePhIBOocHc/D0KCG1CZSIeOSJUtATWO6d++OGjWk1yFeNMUnFl/2eDL/a76oIVQFLvaQFwUa+XDHhPvISM1Ey7+qokoDfugA0wID4d+mLePPCmfPQLuq6GVHFrL99Xb8/epvlDMoh3+7/SuLJeSvM8IL2Pr9hW74A6Asf5F5+W9GuWJR88CTgBj02P6YMfvS2EaoYWFU1LZQJOwVAvuwcYxMADAVwZmZmSE0NJSNDUxXq6CgIOYLXpFFiENA9C7Oy2/J7Bc88FsqnNzfM/rv1q+MKno6ivwIpd5bQsJbPH0mIvh3cXkIbS3pc26Tk5OxapWo4GngwIEoX5574drXJ+GIPeMLVT11mM/lHkmW2hG/mPDp9QucXjaP+XTsvhPQ1JHNC1RiTAoOzBKlfnSfUQ+m1vyk6iRcv46QceMBNTVUfvkCqpqyI88ff3s8bgffRlvrtljddDVfj0BYPU93Af9OBrQMgemfAFV+ChOF3ZRy9aLigZln3uLokyBUMtHDzUlNBW8KVFT8Jq2dQmAfNjYWCgBsZWWFsLAwZGRksLG5yI4R4hAExyQzVzwk1yY0QWUzfq9Nvb+moOmTD4x+D+eqKK/DvUFDkX2weRj+5csdvH4javLQvNkHqKpK33Y4IiICW7duZXSMGzcOxgWg2Yq//gmJt4OhYaEP07F1BHe5vCjQgt5F4+JmUa760A1NoKmtzsveozb/jS///AMtWxtUlDGPeatTrRD+NRyTHCZhYI2BvNgvuJJTgwHPU4BNK6CfbFtIC75XpQGFygOpGZmov/QW4r+lY0prO4xpYVuo7FMkY4TAPmz8JzgApvbH9IWup6eHmJgYNjYX2TFCHIJPX76i2Zq7jM/oDdemDL85uq8Tk9HmmQ+j/3XD6jDVkh7gFdkHysLw0NBTeP9hOtTVS6BpE24pPtQo5tChQ8xqs2dTS2XuPo456YPk5xHQrlYKpf8UPt9NXhRor24G4eEpP+gba+GvZS4snhy7IZ/HjkPijRsw7NABFmvXsJvEYVRMSgyaHhdRRe5qvQtOZZ04aClkU6jrwPrqQEII0HIe0HhyITNQaY4ie+Dau3AMPyj6m/xgWnNYGcvm9kmRfch2b0JgHza28QKAfXx88OGDKApI0qVLF4bmbO/evb+0gXLyqKjn5MmTuHz5Mpo0aYK7d0VATVFFiEPgF5kI13Uiipd7U5uhfCk9Xt3rEZeEzi/9GJ0+je1hqK68wpR08KfA7fD3XwVdXRs0cGaXE5/zAb18+RLnz5+Hjo4Opk+fXqDnF7XzDVL946Hf0BwlfhOeb1VeFGh3Dr6H18MwlKtmjE7jahfIh5KT/dq0QXpgEEwmTkTp4cN405tTkVuIG0beHMn8+GHvhzDU5CeFQ2YGs1EcGwhs/J7zO/AqUF74lBw2ZivHKIYHRh1+jstvw1GvfEmcGinq5KgU2XhACOzDZie8AOCFCxdi0aJFP9YjcKvCksuRxpIQzykV+CiyCHEIPoQnoO0GETn/wxktYFGC3xzdezGJ6Pnan9Ef1LQmNFVVFfkRSr03H9+lCA7egxIlnOBQ94jU82kCdUm8ffs2ypQpg1GjRCwAXCV89VNkRKfAqH0FGDSx5KqGt3nyokA7veo5wj/Go1ZLKzT6g5+rzqyvX+FdzxHUP9Vy21YYNOPG8MHGmTve7MDml5thZWCFy91EnR2LvLw+BpwdDqhpATODAXVl+lSRf6ZFZAMJKelMcXhaRhaWdKmBfs7c6yqKyJYFNVMI7MNmw7wA4JUrV2LFihU/1ktISGAAsIHBr/NNqVDO0NCQqWgfOnQofvvtNzb2FukxQhwCz5B4dNzsxvjNY1ZLmBpq8+rDq1HxGOAZAIK9Ic1qsX7x4dWIQqzM891ERERcQJkyHWBfYxMnS//99188ffoUlSpVQv/+/TnpoEn0shky9yGQkQ3j3lWgW0tYwveszExs7P87sjIz0HGC7CjQaN+7Jz9AanIGmvergmqNzDn7UHLit9ev8alnL+ZHNnduQ6MsP8wSuRk34c4E3Aq6hTbWbbCmqexSLXhxDFslF8YBL/YD5RoCg0TdKpWi9IA8PHDiaTCmnX4DdVUVPJ3tipJ6sitelcd+CvsaQmAfNj7hBQDnXEhaFgg2hirCGCEOwcugWHTdIqp+fz7HFaX0+Y2ynIuIxQivQOiqqeJjEyWFUc5z+uJlf8TGPoKl5V+obCdiO5BWjh07xqQY1a5dm0kv4iqZSWkIW+LBTDcZWQta5YW9RpekQOu/chPKWFfkurU8532NT8W+6Q+ZMd2m1EVZG36oAGNPnkT43HlQNTSEnYe7TF/+Wp9qjbCvYZhQdwIG2w+WiZ/krvRvR+CLjyj3l3KAlaL0gJw80HuHOx5/jIZrVVPs+quenFYtvssIgX3YeFsmAHjChAkwMjICpUYo5T8PCHEInn2KQfdtIp7D1/Naw0iXewFVbs/yaFg0Jn4IhrGGGrwaFZ+21mzPtbtHO3z96oOKFSehgvVottN+Grdz506EhISgUaNGcHV15aSDJqV9TkTk36+Y+WYz60PdiN+XIWkNkxcF2ucPMTi/QbTvwWsbQ1uPn9+B8CVLEXvoEHTqOcD6e5GitD5gMz42JRZNjjdhhu5otQMNzBUgV/brF2D19xz0vqcBW+7nmo0PlWOUHhB7ICz+GxquuE2ZS/i7Tx10rMnPjZDSw7/2gBDYh83zkAkAZrNwcRwjxCF47B+N3jvdGXe/W9gGelr80D+Jn9/ekC+Y6fMZFloaeN6wenF8rHnu+f4DR6Snx6BKlWWwMO/JyT/r1q0DpRW1b98e9evX56SDJn3z/ILoQ+8BVRVYLHGBisAtP+VFgfb27mfcP+YDHUNNDFrFX6e5wP5/IvnpU5Ts0wdm8+Zyfi75TXwU8gjDb4o6pLn1coORlgKQ9b+/CBzvB6ioAtMDAW1hbyPyewbKzxXHA9vv+WP5lQ/Q11LHszmu0NZQFm7L+ukKgX3Y7EkJgNl4iacxQhwCN98v6LdbdO3tvaQttHhmadgaFImF/qGopKOFh86y64LF0yOQq5qsrAzcuVuFsm9Rs+YOmJRuKfX6WVlZWLx4MZO/27NnT1QtQKexRLcQxF/6CLUSWig7gzuQlnoTv5jwHwVadfRauJIvtf+n595Rb3jeC4FF5RLoMrEuL+vQ8/BxboCs+HiYLVyIkj178KI3NyW73u7CxhcbYaFvgau/X5XZOnJVfHUW4P4PYFYTGCEq0lWK0gPy8EDbDffxITwR3R0sseaPWvJYstivIQT2YeN0mQNgT09PuLm5MV3hiPNXzPqQ0zgqmlu7di0bm4vsGCEOwR3vSAzc+5Txmf+y9lDjOeq37lM4VgWEo4a+Dm46Vi6yz0YWhqemRsHtoTOjul69MzAylP6PbWJi4o/fiyFDhsDSkjtzQ9ylj0hyC4GmtSHKjJDeFr59JC8KtHPrXyDEOw41mlqgaW9+zmh6RAT8mopYH6yPHYVObf6o1XL6edLdSbgReAOtyrfCumbr+H4Mwujb0QwIfQk4jQDaye7lR5jNKVctrB6QZEU6PMQJLjalC6upCmWXENiHjQNlBoADAgIwYMAABvzmJ2LaNGUr5Pw8Jf3nN7wiMPTAMxArXcDyDtIryGfGMv9QbAqKRD1DXVxysONdf1FWmJj4Hk+edmS20LDBfejoWEi9HXpx3LFjBzNv4sSJTG49V4k+/B7f3n6Bbm0TGPeiyLSwIi8KtD3T3PAtIQ1NetnBvhn3FwhJbyXdv4/gYaK0hMrPn0FVj19+bcm12p5ui5CkEIyvOx5D7EVdBYu0pCYBK8oB2ZnAH/uB6twLO4u0H5TGy90DK658wLZ7/ihjoIXHM1vyHhCS+4aKyILFCgDHxsaiTp06CAoKgr6+PurWrctwmWprazNFPNTa9fXr10hLS0OpUqWY4h6Ss2fPFpHHyc1MIQ7BVc8wjDj0AhpqKvBd2p6b4XnMmucbgh2fo9CohD5O1bHhXX9RVhgd44ZXr/5ittCsqRfUiO9USvH29sbRo0eZWXPnzoWaGvd8tch/XiEtOBEGzSxh1LaClJbwO1xeFGgpX9MZCjSSzhPrwLJySV428mXnTkStXQcNKyvY3LjOi87clMSlxKHx8cbMR9tbbUdDcwUg7Pe/DRzsKtruFF9Av4zM/KdUrPSA2ANZWdlotPI2QuNTMKRRBczpKHwnzOLydITAPmx8K5MI8Pz585m8xZo1a+LatWswNTVFTmq06Oho5gt927ZtmDJlClatWsXG3iI9RohDcPF1KMYefQkdDTW8X9yWd/9N8w7GgdBouJYyxKGasqGx4t1oOSkMCz8HL6/JUFPTR7Omrzmt+uzZM1y6dIlpFT516lROOsSTQpd6ICsxDSW6VIK+s7CVz/KiQAvzi8OZNS8YFwxY6QI9npgvQqZMRcKlS9B3bQmrv/8u0HPJa/Kj0EcYfkMUaX7Q8wFKaPND4SYzg9kovr0EuL8aMK4EjBM9G6UoPSBrD7h/jEavHaKC8EtjG6GGBffbNFnbqmj6hcA+bHwoEwBMEV+K8F69ehWtWrVi7PgVNzB1ttq+fTvOnDmDzp07s7G5yI4R4hCcexmCCcdfwUBbHW8XtOHdd2PfB+JkeCw6mhhhVw1ho4q8b66ACgODdsHPbzl0dKzRsMEtTtru3LmDe/fuoWzZshg+XASEuEh2RpaoCUY2UGpAdehUMeaihrc58qJA83ILxZ1DH6Clq85QoLHtUJnfRj92+g2pvr4oPWoUTMaNzW8458/FBXDmeua41p1bK23Oi8tq4t4OQKAbUKcf0PkfWa2i1Kv0wE8emHnmDY4+CYZNGX3cmNiEt78FSjfn7wEhsE/+VgEyAcCUp0gFb9++fYOGhohzkwCwsbExvnz58pNd4eHhsLCwYFIjKFqsyCLEITj5LBhTT71BSV0NvJzXmnf3DvEMwKWoeHQ3LYm/qynbSUo62NdvBYKCdsLIyAH1HE5w8v2FCxfw4sUL2Nraom/fvpx00KSMmBSErxIVQ5YZXxeaZWWXs8rGyJfXLuH2nm3QK1ESI7YfZDOF0xi3k754fSsYZhWN8Ps0B046ck7KTkvDh7oOQEYGLDZsgGFb/l8sxWtOvjsZ1wOvw7WcK9Y3X8+L/YIqyUgV5f9mpACdtwB1uJ9pQfehXLxIeSA1IxOOS24iISUDU9tUxujmynQ9eT5AIbAPm/3JBADTdS3l+1Kag1joZxkZGUhNTf0/uwgYE1Cm3GBFFiEOwbEnQZhx5i1MDLSYlo98S783H3EzOgH9zUthdWUrvtUXaX3vvKYgPPwsTEzaoKb9Fk57OXz4MHx9feHg4IBOnTpx0kGTUj/GIWrHW2a++fwGUNXhlw9aWsPkRYF2cdMrBHnFoJpLWTTvzw9NX4q3NwI6iwq3Kl65DK0Ksrv5aHe6HT4nfca4OuMwtOZQad1c+MYHeQB7vr+Ij3sJGCvTpgrfQ1I8i656hmPEoefMxh5Maw4rY13F22Qh3pEQ2IeNO2QCgO3s7PDx40ekpKRAXV30RWtjYwNihqCiHvpvsVAhnK6uLjOOxiuyCHEIDroHYu45T5Q10maqXvmW7i/94BaXhKGWpbHYlp8Ke75tFErfy1cDEBPzABYWfVGl8iJOZlCOPN2SNGvWjPmHq3x9EYHYEz5Q0VKD+YIGgl//yYsCbf+sh0iKSYVLdxvUdi3H1X0/zYu/cAGh06ZDRVubYYBQKUBhYl4GxafGo9ExUYHwNtdtcLFw4cV+QZW4bQBuzgf0zYDJH8DQ0yhF6QEZe2DEwee4+i4c9cqXxKmRClBIKmN/8a1eCOzDZg8yAcDUsYrSGfz8/FDhe3Skd+/eOHHiBGbMmIGlS5f+sO3vv//GuHHjmHH+/v5sbC6yY4Q4BPseBmDBRS9YGevgwbQWvPuu43MfPEtIxrhyZTCrkrCFVbxvroAKPZ50QlKSFypUGI+KFcZx0rZ69WomnYiivxQF5ioJd4KQcC0Q6qa6MJvIXQ/X9XPOkwcFWlpKBnZOuM8s3XFsLZSvXooX8yNWr0bM7j3QtrdHhZPcUlvYGOIe5o6h10VR33s978FYW9i8bTY25zvmSE/A5ypQvSvwx758hysHKD1QUA/Ef0tn0h/SMrOwpEsN9HNWpuoV1KfSzhcC+7CxUSYAeOPGjQxn6aZNmzBmzBjGDgLE7dq1Y3KBqaNV7dq18fbtWxw5coRpjkFMECtXKjYhuhCHYNeDj1jy73tULK2H21O4RxB/dZhcn3rDM+kbplUwwyRrMzZnrtiMeeDWAGlpkahceTEsLfpIvW/ixSY2FZI+ffqAbla4SuxZX3z1CId25ZIoPbAGVzW8zJOkQOs0cQbsnPlrTyxpYMSnBJxa8Yz5Uf+lDWBYSocX+4OGDsPXBw9g1P13mC9ZwovO3JTs8dyD9c/Xw0zPDDe635DZOnJTnJUFrKoApMQB7VYDTsPktrRyoeLrAXEaIFGBPpnlipJ6msXXGQLtXAjsw2arMgHAlOrQrVs3JmK1a9euH3YMHToUu3fv/un6lcAvgWHiCSbOYEUWIQ4BkX4T+bctVb5Oasq7ext5vIdfcirmVTLHqHJKPk+xg7Ozs5g2yNnZmbC334IyJtIXSsXFxWHDhg2MSmKAICYIrvJlrydSvGOh52SGkl1tuarhZV5cRDh2jxM1dOi/chPKWMsmD/SDexhu7XsPdS01DFvfBCo8dUH0bdIUGZGRMJ01C8Z/9ufFJ7kpmXJvCq59uoYWVi2wscVGma0jN8UR74Ct36+fR7gBZvZyW1q5UPH1QM/tj+EREAPXqqbY9Ve94usIAXcuBPZhs12ZAOC8FqY0CPonODiY6WrVpk0bjBw5kskDVnQR4hD8fdsXa677oGpZQ1wZLyLU51McHr1DSGo6ltlaYJClCZ+qi7Su9PRY3H8g+mPr4HACJYykTzug3xF6YSShG5KCvCCGr3+OjIhkGLYuD8MW/OTCcn1AP1Gg7T8JTW1+IrM57Xl81g8vrgXBpJwBesxy5GruT/MyYmPh20AE4srt2wc9Zyde9OampMOZDghKDMKY2mMwvBZ3CjyZGSit4ic7gctTAC0jYHoAoMq9qYu0SyvHF08PhMR9g8uK28zm/+lTFx1qcg8iFE8P8rNrIbAPG8vlDoDZGKWoY4Q4BBtu+mDDTV/YWxjh4lj+r5qru3kiOj0D66pYoU9ZfnIsFeH5J331hYeHqPFIA+fb0NWVPu/My8uLeVmktKE5c+Yw/+YqIfMfITs1EyV72EGvrilXNbzMkxcF2r9b3uDTmy+o7GQG14H8dH366u6BoAEDGD/YPn4E9ZL8dJbL6djEtEQ0PCoC2ltabkFjS/5fXnl5mNIoOTUI8DwN2LYG+p6UZqZyrNIDnDyw9a4/Vl79AH0tdTyb4wptDeVLFydHFnCSENiHjckyAcCDBg1i1p43bx6sra3Z2FEsxghxCNZc88bfd/xQp1wJnB3FfxV5pftv8DUzC1urlUdXU9mAgaJ4OGJiH+Ply36M6U2bvIa6uvTpPR4eHrhy5QoMDQ0xadIkzm7ISslA6ILHzPzSQ+2hXUnYbmLyokA7NPcx4qO+wblLRTi05efvUMyBA4hYthzqJiawfSAqsJOFPAl7gsHXBzOq7/S4g9I6pWWxjPx0ZmcD66oBiaFAy/lAY+7nWX5GK1cq6h5ou+E+PoQn4g8HS6z+o1ZR306RtV8I7MPGWTIBwMTpS7Rm1AhDKf95QIhDQPm/lAdc39oYJ0Y04PVxUP625b3XyMwG9tWogLYmytaSYgeHR1zEu3cToKqqjWZNPTnRjt28eRNubm5MoxjKn+cq6eFfEbFB1HLWbGo9qPNUDMbVHjEFWo3mrdBmxHiuavKcl5GeiR3j7oFwV7sR9qhYm5/0nNA5cxB/6jT0GjdGuZ07ZGI7Kd3nuQ9rn69FGd0yuPUHty6CMjOOi+LYT8DG7wBk0DWgnDMXLco5Sg+w9sD7sAS02/iAGX94iBNcbIr4SyTrnRe+gUJgHzZekAkAtrS0ZKibYmNj2dhQbMYIcQiWXPLCLrcANKhYCkeH8fulk5aVhXL33jDP71itimhmbFhsnmV+Gw0K3gtf3yXQ1raES8N7+Q3P9fOzZ88yLcWrVKmCXr16cdJBk759iEH0vneACmCx2AUq6txTKTgbITFxz4ThiA0LQaNef8Kpaw8+VP6fji95NEYOAAAgAElEQVSfk3B8yRPm530XOqOEKT81BgF/9EDK27cwHjwIplOnysR2Ujrt3jRc+XQFzayaYXOLzTJbR26KXx0Fzo0A1LSAmcGAupbcllYuVDw9sPzKe2y/9xGmhlp4NKMl1Hgqgi2e3izYroXAPmwslgkAFnP++vj4oFKlSmzsKBZjhDgECy68w75Hn9DYtjQODua3YCchIxN2D0Tdxc7VsYFzCemv+RX1wfv5r0Fg4FYYGtaGY73TnLZ54MABpqGMo6MjOnTowEkHTUpyD0PcOT+oGmjCfDa/Z0Bao+RFgeb7NALXd7+Dmroqhm1sAlW1goP+7MxMeDvUQ3ZKCsxXrYTRb79Ju33W4zue7YjAhECMqj0KI2uNZD2v0A68MBZ4cQAo7wIMvFxozVQaphgeyMrKhsvK2wiLT8HQxhUwuwM/NQCK4R3570II7MNmlzIBwK9evUKDBg3g6uqKc+fOQU1GnZLYbLAwjRHiEMw59xaH3IPQvLIJ9g6sz6s7IlPTUfPRO0bnVQc71DbkJ8rGq5ECKfN6PwNhYSdRurQratXczsmKf/75B1FRUWjRogWaNGnCSQdNir/6CYl3g6FhZQDT0bU56+Fjorwo0DwufsSzfz+hlIUees3lB/SnBgTgY7v2jBsqnD8H7cqV+XDJ/+mQLID7p+U/aGLJ/dnLxEAuSjfXA6J9gcZTgJZzuWhQzlF6gLUHHvtHo/dOd2b8v+Maobq5Mj2PtfNkMFAI7MNmGzIBwAkJCbh8+TKGDRvGtD0eP348A4hNTEzyBMNU7KPIIsQhmHH6DY49DUaraqbY+Se/HIiB31Lh5P6eeWR361dGFT3Z0FkVxTPx6vUQREffgbl5T1StsozTFlasWMG0B+/SpQvDlc1VYo59QPKrKOjYl0apvlW5quFlnrwo0K7ueAv/F1GwqVcGbYbw0/gj4dp1hIwfD6iro8qL51DRlA2h/tPwpxh0TVRIrBAFcElRwBob0fnpdxqwceXlLCmVKD3wKw+Iv/fsTPVxbUITTjUYSu/y5wEhsA8b62UCgLlEfFVUVJCRkcHG5iI7RohDMOXka5x6/hnt7c2wpa/0XLR5Odv7awqaPvnADPFwroryOsq8PrG/njztgsTEt7C2Ho1KFaWveE9LS8OyZSLg3L9//wKlEkVuf420gAToN7JAiY6yaTrB9pfyBwVaSWOM2HaA7TSpxx1d5IGY0K+o36kCHDtUkHp+bhOiNm3Gly1boGVnh4oXzvOiMzcl+9/tx5pna1BGpwxu9VCAAjivC8CJ/oCKKjA9ENBW7ECHzA6GUjErD6SkZ8Jx6U0kpmRgapvKGN38+8sXq9nKQbLwgBDYh80+ZAKAufCVEgCm1q+KLEIcggnHXuLcq1B0qmWOzb3r8OreVwnJaPvch9H5umF1mGpp8Kq/KCt7+LAxUlJDYWc3H1aWf0q9lZiYGKaVOMmoUaNQpgz3LnthK58gMzYVRh0rwqCRhdS25JxA+cjPnj3DnTt3UK2adLl1d/btwIsrF2BZtQZ6LlhRYFtyU5CVmYXt4+4hKzMbbYbWgI0Dd99J6g8eMwZJN2/BsGNHWKxZLRPbSen0+9NxOeAymlk2w+aWClAAd3Um4L4FKFsLGC476jiZPRCl4iLlgaueYRhxSMR64za9OSxLKlPzhH6AQmAfNnuWCQCmynUuUquWYvP0CXEIRh95gX/fhKFrHQus78n9Gj235+kel4QuL/2Yj7wb1YCRhjqXx16o5hw9ehTz58+Hr6/vD7vo5YyKOZcuXYoePfJnLSB6uLv3qiErKw01amyGaRlR3qg0EhgYiL179zJTpk2bxrlTYnZWNkLmPASysmHctyp07QtOBVSjRg18+PCBoWhzdpaOWYRvCrR169Zh8+bN+PTp00/uVVVRhbamHspZW6Jxk0YYM2YMatasKc0j+L+xfq1aIz04GCaTJqH0MO60dPkZ0elsJ3xK+MQUv1ERXJGX7U2BsFeA00ignWxeeoq8j5Qb4M0DIw4+x9V34ahfwRgnhvNL/cmbkcVMkRDYh42LZQKA2SxcHMcIcQjEfwxkQQR+NyYBvV5/ZB5lUNOa0CxAp7LCdh527dr1g3t327ZtGD6cfSvajIxE3LsvetmoW+coSpaUvvjQ09MTp06dYvi0Z8+ezTmHLTMhFWHLRHRgZUbXhqaVQYFdTXnJiYmJTE6/tPKDAq33X3Dq8oe00385fsaMGVi5ciVTYzBz4kKEvkpD7NdIvI+9y4B1eon5+++/mWg6F8lM+gqfeqIceqsd26FfgKLEvNb/mv4VDY40QDayGfozokEr0pKaCKwoB2RnAT0OANU6F+ntKI0v3B6IT05n0h/SMrOwrKs9+jgJ2/a9cHtLftYJgX3Y7E4JgNl4iacxQhyCIfuf4ub7SPSuXw7Lu9nztBORmqtR8RjgGQAimAppVoszSOPVKJ6UEYVf5e9V/kRFVqEC+zzS5OQAPHYXFfo4O12Hnp70VICPHz/GtWvXULJkSaaIlKukBiUgaovoRqbsbCeoGcimcIuNfSIKtG6gf3eaNBN2Tvx1JiRftW3bFlpaWnA78wEeFz4y3L/dZtRiWDTc3d2Z8/n06VM4OEifC//t1St86tWb2abNvbvQMJVNO+nnEc8x4Kqo1TI1wKBGGEVa/G4Bh7qJtjDFD9CX/qWpSO9fabxcPXD0SRBmnnkLTTVVPJ3tCiNdZVqeXB/ALxYTAvuw2bdcADBdJ9OVbnJyMn6TIXcmmw0LOUaIQzBg7xPc9Y5Cf+fyWNyFn2p4sQ/PRcRihFcgdNVU8bFJwa6XhXwuua1NV+pi0BsWFgYzMzPWJsbGPcWLF6LGFU0av4CGhvQUPNevX8ejR49Qrlw5iFuLszZAYmDymyjEHPkAqKvAYpELVAQkg5clBdrdu3fRvHlzBgBf3PIcPk8imO5v1AXu9u3baNmyJeMViuRTRF9aiT1+AuHz50PVyAh27o9l9rJ30OsgVj1dxbQ+JgaIIi+3lwD3VwOlbIGxz4r8dpQbKNwe6Ln9MTwCYtC6mil28Mx6VLh3XritEwL7sPGITAHwnj17sHjxYgQFBTG25GR6oE5xVFCTlZXFRLuMjKQHCmw2WVjGCHEI+u3ygJvfFwx0scb8TtV5dcXRsGhM/BAMYw01eDXiN7rMq6EclBUEAEdEXoGn5xioqGiieTMvTmCJ0h8oDaJ69er44w/uqQKJ9z8j/nIA1Eppo+xURw6e4G/Kp1fPcXr5fEbhuP2noKGtzZtySQC8f+59fAlOgkPb8nDuUonpSqmvL2rS0qZNG1y9elXqdcMXLUbskSPQdXRE+YOyY6+Y+WAmLn28xHD/EgdwkZe9HYBAN6Dun8BvClDQV+QfiOJuICTuG1xW3GY2uLVvXbSzL6u4my1iOxMC+7BxkcwA8KRJk7Bx40ZQQRABX7HkZHro27cvjh07hv3796Nfv35sbC6yY4Q4BOI3Yll0w9kb8gUzfT7DQksDzxvyC66Ffsi/AsDR0dG4dOkSqE0xRWnpVoMijIsWLWKu1y0sLDBjZkeUL38eWlpmaOTy8MdWvLy8mEI6uhEhlgcdHR2MGDECI0eOhJg5hX5ODTBWr17NRH6NjY1B+cgE4G7cuMHoJ7l37x5T/EXR6ffv38PKygqjR49muLclxf3vq1i+ZQ1CU78gUSMFxNFNKQHEMUwtyyXlxIkT2LBhA8M9TCkgBBzppTQuLu6nPezbtw+HDh3CkSNH0KxZM4a+8MGDB4xPqPEN+aJ9+/aYO3cuzpw5g/T0dPz111/o17o57h/YBT0JCrSkpCQsXLgQFy9eZP5O0Lr0QkxCKSgGBgZMbi/ZnJdIAuCNQ68iIz0LrgOrobKTGYKDg5lIOgn5dPfu3cx/03NbtWoVypYty/icPiP+8pkzZzL/kFCuM61/d/duhMbEIF5dHW06d8aSJUtQseJ/lHI0jvZLUXt6sae0GdoHpa+QT8Xy4sULUL5yfHw8M+bLly/MRy9fvmSeoXUtaySFJgHZQNOmTUH7IqGo9Zw5c0Dnj4QYOMj3JOIzQ+fhyZMnoHNG54rrmeHtdy8jVZT/m5ECdNkG1BalkChF6QFZeGDrXX+svPoBBtrqTPqDtoaaLJZR6uTgASGwDxszZQKACRhQPp6uri6oSptaI9vZ2SEyMvL/qM6uXLnCRIG7devGFP0osghxCLpvfYRngbEY2awSpretwqt7twZFYqF/KGx0teDmJGyDBV43BjCsArmlQDx8+JABsAMHDmSWJKBKYKZz585MsdXQocQOkIn9B8rC2ro26juK+GIJ4A0ZMgQEMgnYEDiiBhf0cwKt27dvZ4AugUcCbCQ9e/ZkQC8BHBL6fPDgwQwYohxhAjzUPIbW//PPP3HhwgVMnDiR+Z0jITaWhvUboLWNC3bO3YTSvaoyYIzGUB4sUZmJ5d9//2XAGgE4olwjQEd20e+nGADfunWLWYPWpRdbMQgjfxAwo5dZAnVjx45lbOrTpw8DYCdMmMC8HIzu3QMVMr/+oEAj8Nu4cWMGxFOOrrW1NfNv8g/xIBMbx4IFC1g9WkkAvHaAqNVuj1mOMClngDVr1mDq1KnMz27evMmwQdDzo73RcyBwnpqayoBfekGgFwN6BuR3StmiWyzz6TOQlZCAt9264q/166Gnp8eATTEIpii9ubk51q9fz7zMkO/p71r37t1/AOCQkBCmoQm9QDk5OTE+pPGTJ09mALBddTs4H3FG1NUohB8L/wkAk+3kE2Ijob8jYt/nPDP0EkLgNyIigtOZYeVstoOCPIA9rUWjx78GSlqznakcp/SA1B5os/4+vCMS0bOeFVZ2V6yUPKmdUcgmCIF92LhAJgBY/MVOXzz0ZUtCUZbcADB94ZQoUYL5IvHzE1FqKaoIcQg6//MQr4PjMLaFDSa35rd16/pP4VgZEI4a+jq46civbqHPQF4pEN++fftBS0aAuGHDhj/MJSBEL3KTp5RGv36/oXat3UwKEPHlUgSPon9ioUgqATECUwQGSQh4Ur4xRZarVq0KSiOinxFQpkhpeLgIGBGY0tD4r8CDABeBK4qi+vv7M+CdgCgxH6xrPxODxg+DUWtrJlpLL6YUlSWAR0V2JL169WLWISAsFrKJqAlJn6QQgHz79u1PUUj6nAA7AXx6CdixY8ePKaSzY8eOqGpdDoPr26NG89ZoM2IcEw0nn8yaNYv5b7FQni7Nd3FxYajW2IgYAGtqamFl/3PQ0NDEgNUNcPTYYYwbNw70zMj3y5cv/6GOIrYUySXgTf8mG+lvFtG80V4I0NepUwfj+/aFX3NRBNr6xHH0mT+fiXQPGDCAoaqjSDm9iNBNlmS6ClHqeXh4/ADA9OJCNlDUl9g9xEJpGRRlzjbPxp9X/kTS+yR8Wvnp/wAwjaeoL0X/JSPAkmeGAgl0m0YvSFzODBtfsx7jth64uQAwMAcmeVEOHOupyoFKD0jjgfdhCWi38QEz5chQJzSsVHC6R2nWV47N2wNCYB82z0QmAFgMdilyRBEgkl8BYPqMADB9IdMXiSKLEIegw6YHeBeagAmutpjgasere5f5h2JTUCTqGerikgO/unk1lIOyvAAwRQ3F3Q4piicpYjquQYNKYvKUoahWdSUTfSRgRRFiMbMEzSEwevDgQSbi2KpVqx9q6P8J4NKVPAFESQYKiqYSKM7ZgIJSiyiSSkJAi8AcgdFZo6diZ+clcBzmCv36opw4sX4qTBWnBhDgI+BOEWJKpRCnZEyfPp0BZ5JCUVsCppIgjD6nKDTth0AhgUOx0L4JzJuWMMTU1o3R6DsFWrt27Zh83Jw0c6SDdNGtkbe3N6unJwbAaqpqcLBpgdTMJKSoxzD7IMBOvmzd+ns08rtGSoWgqDz9nGoQJIUi2qampowNehR9DQhgPtaxt0dsfDzzt4o+ozQKelGgVBEC0qdPn/7RtpoithQ9pn9Itm7dytCwUcSZmpyIW78TUCb/vNN6hxVPVkDVXxVvFr9hDYBJN6VP0N8XiuBT23lJkebMsHI220GHewC+14AavwPd97CdpRyn9IDUHlh++T223/8IM0NtPJrRAqoCFvtKbXwxmCAE9mHjVpkAYKrEpigT5cKJJS8ATFEoyjukKI0iixCHoO2G+/gQniiTlpDzfEOw43MUGpXQx6k6itVuMr8iOHFee04ATFf2FKnt/2cJzJs3CzaVpjLNIigSSFFdyvvNTwiU0hU8pSQQAC5d+r9oBumiNUlffpKdnomQuY+YYRp/lMO5Z1eZa35Kq6DftYCAAAa0kRBwojxbSgWoUqUKpkyZwuTk0+9yTsktCkljCPRS9DEnABb7sqSeDmZ3aPGDAo30Hz58mPHXvHnzfixDoJjAMbE6EMBkI2IATJHf9YOuoLx9KXQcnXdjHXEEngAp/bekiG0gfzkGBSNq/XpolC8HmxxAWTyHosyUGkLngqKw5L+cTULo7yFF6elGoFSpUkxzDnrZEPMpz3abjQv+F1DhSwVcnHJRKgBMz5FeaCSfqdg2ac4MG1+zGkN53KusgZR4oP0aoL7sGoewskc5SGE9kJWVjYYrbiM8IQXDm1TEzPaKlY6nCA9OCOzDxm8yAcCUQ0jXq/SFr6kp4h39FQCmK13KnaOolJgtgo3hRXGMEIeg5dq78I/6ipntqmB4U+n5aPPy8zTvYBwIjYZrKUMcqvlfQVBRfDY5beYDAC9Zsg7lrAbC1taWSe+hVALJwqlf+UkcoSUATNFXSRBKughIiYun8vJ1elQyPiy5gw0P9+JN5ieMnzyBuaKnKHRuYInSKChaKC68IiBOxWEUTZYUzgBYVwezO7ZA/5WbUMa6IgNuXV1dGaBH0WSxiCOl9G/KZ2UjPwCwuibWD76C2q3KweX3vF/K8gLABMwJoBOo7foxAAmXL8OgVStYbha1p84p9FKyc+dOJmdZHImnHGD6Gf3tE0tUVBSTBnHgwAHmBoDSX+glhyLt3S50g1+cH5qnNcfmYZt5A8DSnBk2vmY1JtwT2Pad53nkI8BUsYpkWflAOUguHnjk/wV9dooCApfHNUY1c0O5rKtchL0HhMA+bKyTCQCm61z6cqNiODH/5q8AMOXeUfTn999/x8mTJ9nYXGTHCHEImq2+g0/RyZjbsRoGN2LfzIGNk8e+D8TJ8Fh0MimBnTUUq8CFDwC8auV+mJn9BkdHR6bgjKKjdLWfU+hlkSKvYqBEL4QEoih1glgKJIVyUl+9esWkIFCObE6h4jMCx1Qs9fSiGzr27gwnq9o48eQStA1E0ee8ooX0OeU1U/c5yjWlFAIqFpNMHygoAJakQKNoMUVPqXCP0hEo8k1/Myjtg9YVp5rkdx7FAFhdTQMbhlxFiz+roGpD8zyn5QWAz58/zxQpEkDfrq2NVF8/lB4zBiZjRv/QSYwOdevW/WkNusmi1ApKe6BCNAKfb968gXYOyjeK1NLfPrKBUmqmz5yOK1WuICs7CwO0B2BKrym8AWBpzkx+fmb9uccO4MpUQLsEMC0AUKAukax9oBwoFw9MP/UGx58Fo7KpAa5OaMyJdlIuhhbjRYTAPmzcLRMATH/UKeeufv36TGSHrn1zA8D0JdOjRw8mEkLVy4reJEOIQ0C8iMSPuPC36virIb8gdajnJ1yMisMfZiWxuWp5NuetyIzhCoDnzZuNxYuXMSkQG9ZfgrGxC0NzRnmulLdLUVbJAihyCF2XU0GWmAebflfoZoSiicSEICkEEglgEYsAAdScKQqkh373CEDa21WHp68XXk65hNqrO/xQkxsApmJVYiSQFALBy5YtY670KbdVLAUBwMv6d8eIbf/x6NJLLzFf0J4JMNLfiq5duzKR6NzSL351gHIC4N+nOcCsYt684nkBYPHvKq23ydIKrnp6sNi0EYbf84jpJYMK98hn9N/E4kH+Egu91JCfqFiQmDM6derEgHyKwFO+rlgI5NNn+ob6sFov+vlyq+Xo1LIT7O3tGfAsKY0aNWJeUIjNQhxcoM/zeqmR5szw9gt6cgDw7ixg1xboc5w3tUpFSg9IeiAlPROOS24iMTUD09pWxqhmipWKpyhPWwjsw8Z3MgHAFNGgP9REaUQFKAQA6MuBrm4p15AI/umLj3IR6eqQoktcyOnZbLAwjRHiEDgtu4mIhFQs7VoDfZ34Ban93nzEzegE/GleCqsq//elXph8ztUW4lKlJhQklJojCVqouEkMzqj4TFwwRmNnz56IZcs2oG+/Eti21R36+pVBkUKKAtPvBRWbbdmyheH3pRQhYiWggjcqbBMLpRDRVTmlP0ybNu2nLRCdmJhCq0mTJkyKArEWUOSRUgaIqoxotkj0dHSRnPINz+f/i7oL2jM/IxtoL6GhoT/YIihvldIcKB+Vcm/FQgwtBMrJZmI4EIu4CI7WkuTnJdozKugigC7ZvU78MmGko43t08aj54IVjCqKYhNIJDqxnJFUaZ+bOGdXVUUVG4dex9ANTaGl8x/TQm76KPpMdhLbA/Ea5xQCpuRLLRUVTDEpg6n378GocmXm7xeBSgK/VHBGAJieCYFVSmkQCxW6URoLgVyihaRCSPFzlVyL9v4x6COs1lrBWNsY++rvY1JlKPpNYJd0U1EevSgcP36ceVEglgwR5Z5Iypcvz5xToqSzsfkZBEhzZqT1e67jqTB0bRUgKRxwXQg0msCLWqUSpQdyeuDy2zCMOvyC+fHDGS1gUSL/GgulF+XvASGwD5tdygQA08L0B5siOfQlJ9kIQ2yUuHiI8v+IUkjRu8DRvoU4BPWW3MCXpDSs/N0ePR1FzQD4ku4v/eAWl4RhliZYZCtq0KAoQiCVACFJTkBHBWjiAifib6XCJrF0794Wp09fQ4MGurh7NwiamqWYj6jxhLi5AtGXUZoDgVC6IqcXRTFbCkV+KZpHKRHE+Us8rzlFUhd9RmwCxEpAhVUEtsXNMprVdMG9t4/QtLozVu7ewKQXEMMCRY4pVYLyU+lMUqSZADDtiz4nsEZCAJEoySidiV5oSYjxgAAWgTBijCCAR0IvAuQHAoc5mz8QwwLpVFNVwcFli9B7+hxmDqU+UaoAFcySPwjw0csE+Yf+HhC9HL0A0MtCfiJm2qBx03ttwoqjY/ObAmrWQyCW0kWeP3/+f3+DKA2lYZ06+PSdU5ci9xShJtoxeqGnFAYSAsBUyEZ0ZnRWyP/0QkIpFPQ8CeBTLQQBYNrP2rVrmbQP2i/5i86SU38nRDpHwsXCBdtctzGBA4oekz8oJ5woJOl50E2COPJP/Op0PghU0x7ohYpylqm4juuZyddpbAbEfAQ21RGNHHwDsKrPZpZyjNIDUntg2IFnuO4VgfoVjHFi+M/sJ1IrU06QmQeEwD5sNiMzAEyLU7SJIiv0pUBfAvSlTkJfJBQRoy94qsBmm+fHZkOFeYwQh6DWwuuI/5aOtX/Uwu8OP3f+KqivOj73wbOEZIwrVwazKuWdb1nQteQ1nyKYlHZAkTRJIcorAmsElIhbl8AGCYE3cdU/NT2Q5LKmKB7lwRM4IaE0AgKvBGyI+o/Gk04xFy8BKor6ijmBaQ6tS+PFxaRim4jjlcYS4KXP6BaF/l+SMu3FymuYsG0OXoR7wdzKgkk3ogIsAm8EfgmUUgSZ0g8IAIs5gImHmEAXgTpiaKDfVRLq/EagUdxkgX5vKUpKoI6u9imSLRaym4AvcRHTTY/4d99ATw8LFy9m+MEJSNK6NI8AOf0/RdclmTUoCk8vGZKcx5LPhdIKKNJKRX1iUVNVR5WqlZm90Qt2TqGXc4qqSvIbE+CmCCsBU0l5P38Blm7ahFupKYjOyGDAP42RLM4TA2CaRz6hlxoCypSiQL6mZ00i2ZCDXlpIF90k0AvDcZ3j8I31xVD7oRhXdxxz/ig6TbnjxMpBNwX0vEgnsYKQXgLJfJ8ZXn7PXh4Gzo8C1HWAGUGAuqgQWilKD/DpgbjkNDguvYn0zGws72aP3vX5DfDwaWtx1yUE9mHjc5kCYEkDCAxTXhxFiihSlTMPko2xRX2MEIegxvxrSErNwMZetdG5Nr9RWten3vBM+oZpFcwwydqsqD8eXuwPCTmKD95zoKlpgsaN3DnppMgqcWgT4MlJpSWNwvC1z5AR9Q2Gba1h2Ey4FJWszExs7N8N9O9OE2fAzlkUTaYUCnqZoPx/SSEATC8BdHVPUU5Kb6BCrvzk7NoXCPWNg31zSzTpyQ8vddDgIfj68CFK/NEdZb/z+eZnh7Sfp2SkMB3gMrMzsb7ZeriWd5VWReEaf3408PIQYN0YGCBKx1GK0gN8e+CwRyBmn/WEppoq0/rYSPe/xkB8r6XUVzAPCIF92FgsNwDMxhhFHyPEIag85wpSM7LwT5+66FDzPzomPnzdyOM9/JJTMb+SOUaWK8OHyiKvIyBgMz4GbIC+flU41Zf+y5/AH0X16EWRoqriPGRpHUN6Quc9QnZ6Fox7VYZubeGeT1x4GHaPF+WriinQKF+VusxRJFucXpHbHilqTSkDkjnYv/LF7ikPkJKUjqZ9KqNGE35e9nwaN0Zm1BeYzp4N4/79pH0MrMa/jnqNfpdFuq/9fg3m+kX8NmVTXSDGH2gyDWjxX2EgK2coByk9wNIDPbY9xpNPMWhT3RTb+9djOUs5TAgPCIF92OxTbgCYIlqUq0ZCV6via0E2RuY1hq4f6QqWrqbJyZQLSfmEdMVJ1730JSsW+rIl5glqE0pfwERNRNeQVExC9FS5RaWpsIWuGymXma5nqTKb1qNrb2lFiENQadZlZGZlY3t/B7Spzm+U1uHRO4SkpmO5nSUGWhSe1pN0BiivlorDqJuXPMXbewE+hxyEcclGqFNnv9RLk+2rV69m5tEVuLhTm7SKMr+mI2yxKAJtMqImtKzzZkSQVr804z+9eo7Ty0VsFmIKNPodon3SFb+Dg0Ou6qholq7+c1LB5Tb4W2Ia9kwVtfDqdFQAACAASURBVE3uOrkOzG1FLZ4LIhnR0fB1EUWryx3YD736ssllPfrhKJZ5LEMJrRK43/N+0aZxSowA1n6Pvvc/C1QStZBWitIDfHrgc2wyGq0UcYdv7VsX7ez5De7waatSlzD1T2z8LlMATOCUojfUkpUqwSWFCn2oupzojqjqnatQziWBV6rGpkpoqsKmtYjiiHIVKa9R3GaWchspN69z585MZI2q3Km6nb6EibSeALJkwR5RVlF0ivL0yE4C7pTTTGCYik8oh1kakTcApihghZmXGRN3/1UPLavyCwaru3kiOj0D66tYoXdZUbGXkELgkYqECDBR0RDlStKLDpvua3zZ/fbtGERGXYGZaRdUr75WarVUNEV7IKHcUHF+sLSK0kKSELn5JTPNbIYj1EtoS6uCt/Evr17E7b3boV/SGMO/U6A9ePCASfGggjEq3CK+XclaAMr7pTFUhMeGDi3UNxZn14r2O2h1I+gYFDzv9Cu9KA8cxOi0c38Mte+5vLw55ruiuQ/n4pzfOTQ0b4jtrbbzrV6++t6dA07+BaioifJ/tfTlu75ytWLhgX/u+GH1NW8YaKsz6Q/aGmrFYt9FdZPyxj5s/SQzAEz8v3R9SXm/OdvFio0jsElf8ETtI8lpydb4vMZRhT1Fz4gqStxOVcydKQly6aqZqJgI1BJYbt9eRBdFQnPp51TAV6+e6IqFOIupOt3b25spvJEmki3vQ5CemQXb2VcYu/cPqo+mdiZ8uPaHjor33yA5MwvbqpVHF9OCR9y4GpcT+ErqoUgw3QbIS54/74W4+KcoZzUYtrazpF6Wip+oCxkJdQjjmiv/7V00og96ASqAxZJGUFFTkdoWvibc2bcDL65cgGXVGj8o0Eg3vahu3LiRKRSkFxb6fSVATMWDxAkuSbGWny2e90Nw74g3tPU1MHhN4/yGs/o8Zv9+RCxfAXVTU9jeu8tqDpdB3S90h3esN4bYD8H4uiJWjSIrV6YDHtsA8zrAMNn5rMj6R2l4gT3AUKeuvw/fyCT0crTCit9rFlinUoFsPSBv7MN2NzIBwAQOqWiFqIAoCkcV082bN2e+3JjcxNBQpkEGkcdTWgSlIlA1O1U78yUEbAlcU4oD6c5LxHyddN1KaRPiL2eqqCdwLNmmlT6jKHD//v0ZWqIBAwawNlneh4BIwqvMvcrYd2SIExra8JemQM/R4u5rZAHYV6MC2prI/4o9L+ArfiiU7lKQQjLWD/f7wMfurkhODoBNpekoX36YtNOZs0qNEyhqTe1xuUrSwxDEXfwINSMtlJ0pm6t7tradWbEAAS+foUbz1mgz4meWBbY68hv34LgP3tz5DHPbEug6+efubPnN/dXnobNmI/7MGeg1aYxyO3ZwVZPnvNTMVDgfdkZGdgbWNl2L1tatZbKO3JRuawyEvwGcRwNtl8ltWeVCxccD70Lj0WGTKN3p6FBnNKgk/O1j8fE+t53KG/uwtVImAJgqtymqS7l9VMFNrA+5CUWHiTuT8nd79erF0CxxlfT0dIZKiSK0dO0tTr2gzlhEb5SXENCga3NJvleyn2yaNWsW0/FJUj5+/MhQW1GDD+KLZSvyPgSJKemwX3CdMe/4MGc4VeTvD0VaVhbK3RN1qTpWqyKaGcuv/zoxBNDzJQYBSrPJSy5fvvwjes/2ORVk3KPHzZGRkYTKdvNhatpRalXUKIZuHSjdZuDAgVLPF0+Iv/kJXx+HQ8NSHyYDa3DWw8fEI7MnIS4iHM6/90Lddr/xofL/dFzZ/pZhgKjibAaX7ra8rBE4cBBSP3xAyX59YfKdE5oXxRJKvL54YcTNEaLfo47HinYBXEoisLkOkJ0FdNkK2LXh210F0kd80sWFcrNAjirkk5f+64WdDwJQ1kgbD6e3gKqqcLdbhdxVhcY8eWMfthuXCQCmwiMCJpTHR1yVeQnl2VK0mL7wxfyibI2XHCduhSr+GfF6UuSZKurzukamB0PFUkQ4T/nEYtJ9AljUopYALgFdSRF3AiMOVIrW/Uoox5j+EQsR61N7aGpIQDyrspbYr2mos/gGs8zpkQ3hUJ6/NIWEjEzYPXjL6D5XxwbOJeST6/fhwwfmTNELj1KUHlB6QOkBth6g7yX6nuDzppHt2spx/HiACrobLL+FyMRUDG9aETPbVeVHsVKLTD1QrAAwNQegwhWq4mYjlEdLoFLcXIDNnJxjaC2KJBPhvo+PD9PRigrjKLIr2Z5Uch5FEokon4A6NSmgznVioQYF1KkqZxcw8ecEmClHkfKKfyXUYYsaCeQUeQHgqMRUhiic5PxoF9SyEhHy8yGRqemo+egdo+qqgx1qG+ryoTZfHcTIsWyZ8mo1X0cpByg9oPTA/3mAmEcosKGUoumBh35f0HeXh+h7Z0JjVDGT381j0fRY4bC6WAFgesOmNAQCmAQU8xJqkKGvr88UwFB0jy8hQEwUaMT2cOWKqBBMUsg2Knij62a6Sh81atRPnytCBDgs/hsaLL/N7OvfcY1Q3Zy/PN3Ab6lwcn/P6L5bvzKq6MmnBzuxJND5onQXNkLR//zOIBs97MZkIztbFJlWUeHGQkC/D5RfTTbn1kKcnR3UmzhbNJSuB4W8IczOZjiNSdTU1VmbL+3ArAzRflXVedosPYfvdqtoyI5gPyMrA9nIhqqKKtSIOaEoS1Y6kJ0NqKjSgyh0O6HvAmL6EbcKL3QGKg3K1wNTTr7GqeefUcXMAFcnNMl3vHJA4fBAsQLAVL1OBWWUR0vtXvOSU6dOMWwRFNmjqCufMmbMGKYdakBAAIh2TSzUcrVdu3agfEtKcZBsayoeowg5wMExyWi8SsSVeH1iE9iZGvDmXu+vKWj6RPTC4uFcFeV1tHjTnZ8iAol0bii67uXlledweRbBfflyB6/fDGHsad7sA1RVpQdO9OJF55No+cQtiPPzR87PszOzEDLnIZANlPqzGnSq8Zf7La0tuVGgSasjv/HvH4Xi9oEP0NRWw5D1TQr24vB9sciNGxG9dRu07OxQ8cL5/Ezg9LlkAdzqpqvR1rotJz2FYlJGKrDcCshMBbpuB2r1KhRmKY1QHA9QUXe9JTeZzqbT21bByGaiFvNKKfweKFYAmFIZiCqMosBE6URgMze5du0a0+qU+HsJjPLN10o8vXv27GEq68WtVClySPyjRG22c+dOptlAbkKgmeiYiL1CTKMmHldUWCACvnxF8zUiKqJbk5uikgl/ebqvE5PR5pkPo/tNw+oooyU92Cvory0bICxPABwaehLvP8yAhkZJNGn8TOrt0X7oJZAiwFSAyTVXMSM2BeErnzLrlxlXB5rm/D13aTd1e992vLxyEZbVaqDn/BXSTmc1/uFpP7y6EQTTCoboPp2fjlDBo0Yj6fZtGHbqBIvVq1jZIe0gzy+e6P1vb2ba5a6XYWUoXLtqaW3/v/GBj4G93wH8+DdAyfIFVqlUoPSApAcuvQnFmCMvoaICpvjNvIR8bh2VT6HgHihWAJhoxSiKtWbNGqYIjIqWiE5MfPVENGj37t3Dq1evQMVqlJNFaRC5ybhxedMmUeFcbt2+iGOUWCjo+pWuzYlqjcBv69atmVxhojAjKrO8hJpgEDB/+vTpj25VYh5gStcgHmBpGhXI+xD4RSbCdd19Zov3pzZHuVL85em6xyWhy0s/RrdPY3sYqgt3fZsXEKYXHa6RVGl/7T992gr/j2ugp2cLZycR/Zw0Qr8r69atY6ZQd0KuV7WpAfGI2i5i6DCf5wxVXfm/nIj3fWb5fAS8ei5TCrRL/7xG4NtoVGlYFi3/5Kcoxs+1FdI/f0aZKZNRaogoqs+3nPA+gcXui2GgaYCHvR7yErnm20bW+h6sBW4tAgwtgInvKAeI9VTlQKUH2HhgyP5nuPk+As4VjXFsWAM2U5RjCokH5I192G5bJiwQkvmL4iYYOfMZf/XznIaL8wd/tSHq0Hbjxg0mn5fSHGid9+/f48CBA0wO8v79+9GvXz9mOgEh6vpGneByS80goC7JWkGRY2qGQeB54sSJDKcxRbSpQxVxGA8bJh3Pq7wPwYfwBLTd8IDZ+8MZLWDB4xvz3ZgE9Hr9kdEd1LQmNPPJ9WZ7IAsyLicQJqo6SpHQ1OSWjyutLT4+ixH8eR9KlHCCQ13pKf1CQkKYWwmSSZMmwdCQW4FH8stIxBz3hoqmKswXNhQUWO2ZMAyxYaFo3GcA6nfOOx1KWn+Lxx+c8wgJX1LQsJsN6rQux1XNj3mZSUnwqefI/L/Vju3QbyKbXMMFjxbgtO9pOJk5YVebXQW2W1AFh7oDfjeAGt2B7rsFNUW5uOJ5gBiNqKA7IysbK3+3R0/Hgv+eK56XCu+O5I192HpCJgC4du3avH3pEkNDXkIsDARGCdhSNymK0JYtWxYuLi5MK1miHRNLfkVF8+fPBzE3SArRtFF+MhXLEVOFvb09pk6dmm9uc242y/sQeIbEo+NmEWH4k1ktUcaQv3a4V6PiMcAzAFTiGNKsFm/Pm+3BzWscAWHqqEZUc79iAOFjnZw6PD3HIyLyEsqU6QD7GpukXoJuFag1N51TyqPnylmacCcYCdc+Qd1EB2aT+UkJkHozALIyM7Gxfzfm379NmgVbp4Zc1OQ5Jz0tEzvG32PynTuMrglr+4I3e0l+8RKBffow69rcuwsNU35biIs31ONiD7yPeY+B1QdiUr1JvPtGbgqzMoGV1kBqAtBhLeAom4i53PajXKjQeeCQeyDmnPOEppoqns5xhZGOcLdahc45RcAgeWMfti6RCQBmu3hxGyfvQ/AqOA5d/nnIuPnF3FYw1uMvEnouIhYjvAKhp6YK/ybKVpSMj1/0RWycOywt/0Jlu3lSH29KtaF23JQOVBCqpthzfvjqHgYt2xIwGWwvtR18TYgND8We8aJbkj9XbYZJ+Qp8qf6hJyooESeWifKd+y9pAMPSBc8LjD12DOELFkLNyAi27o9l8nKXlpkGpyNOIBaI1U1Wo22FIlwAF/YG2P69/fTIx4BpNd6fs1Jh8fZA962P8CwwFu1qmGFrP4fi7YwiuHt5Yx+2LlICYLae4mGcvA/Bs08x6L7tMWP56/mteX1rPhoWjYkfglFKQx3vGgnbaYyHR8OLCnePtvj61ReVKk6GtfXPtHpsFqBiy/v37zM3GMOHD2czJdcxX/a9Q8qHGOjWM4VxdzvOego6kXJ/KQeYZNz+U9DQ5u8GQmybt0c4bu71grqGKoZtbAoVHrpChS9ahNgjR6Hr6IjyBw8U1A25zn8X/Q69LomYEv7t+i/KGRbhK12P7cCVaYB2CWBaAFAI0qFk8tCUSgXxgCSb0fb+DmhT3UwQO5SLcveAvLEPW0uVAJitp3gYJ+9D8Ng/Gr13ujOWey1qA11N/rg593yOwizfEFhoaeB5w+o8eKfoq7j/oB7S02NRtcpymJv3kHpD58+fZ5qy2NnZoc/3K3iplQCI2PAc6eHJMGxVHoYthQNWL65cxJ1926Ff0hjDt8kGSLqf88fzq4EobaWPnrP/S3fi4jfxnE99++Hb8+co2b8/zGbPKoiqX8496XMSix4vgoGGAR72LuIFcCf+ArzOAXbtgD7HZOIvpdLi64G/b/tizXUfGGqrM+kPWgIWXBffp1Cwncsb+7C1VgmA2XqKh3HyPgRuvl/Qb7eoa473kra8/uHYEhSJRf6hsNHVgpsTP5X3PLhYMBVZWRm4c7cys36tmjtRunQLqW0hej1qx03sJdRmm6uELHiM7JQMlOxuB716sslfZWObPCjQrmx7i4+vomDraIrWgwv+IkbFuT6O9ZGVlASzxYtQ8o8/2GxV6jELHy/EKZ9TqG9WH7vbFOGiMWp8sbYykBQBtFoEuIyX2hfKCUoP/MoD9Pvouu4e/KO+ond9Kyzvpky3K4qnRd7Yh62PZAqAiYLq5MmTePv2LdMWOT1d1CUrN6HCH6InU2SR9yG44x2JgXtF+ZEfl7WHKg/Xw+Lns+5TOFYFhKOGvg5uOoqAX3GW1NRIuD0UUfM41jsLQ0Pp/1Bv3boVROtHlIH0DxfJSslA6AJR2kvpIfbQtuGv/bW09siDAu3wfHfERSTD6beKqNf+v2Y30toqHp8eEgK/lq7M/1qfOA6dmtI/RzZr97zUE17RXhhQfQAm15vMZkrhHBPtD2yuK7Jt8E3ASsSeoRSlB/jwgGQh9/FhznCqKFxTHz72U1x1yBv7sPWzTAAwMTEQRRhRkJGIKc/yMooAcH6UZ2w3VVjHyfsQ3PSKwJADz5huuB+Xd+DVLcv8Q7EpKBL1DHVxyUG4PFNeN1UAZYmJXnjyVBS1dWn4ANra5lJrW7VqFaiJDEV/KQrMRdIjviJi/QtmqtmUelDnoSiMix00R9YUaJkZWdg+7h6ys7LRdngNVKpThqupP+Yl3r6Dz9QWXUUFlZ8/g6ouf9zZ4kXSM9OZArj0rHSsarIK7Srk3iiowJuRh4KXh4DzowF1HWBGEKDOX6GtPMxXrlG4PbDkkhd2uQUwFJ4PpjXnNYhTuHeuWNbJG/uw9Z5MAPDSpUsxd+5cxoa6deuiZcuWTLOK/GidiLZMkUXeh+CqZxhGHHrBUMf4LOX3S3aebwh2fI5CoxL6OFXHRpEfG6u9RUffx6vXA5mxzZp6QU1NutbQ9NK4ZMkSZj7l/1IeMBf55h2D6L3vmKkWi12gokFEdfIXeVCgRYcm4diiJyKfLXBCSTO9Am/0y7btiNqwAZrly6PSNembmbAx4H30e/S4JMoRv9jlIqyNCh65ZrOuTMacGwW8OgxYNwYGXJLJEkqlxdMDmVnZaLD8FiITU5m2x9T+WClF0wPyxj5svSQTAGxjYwNqJTxt2jQsX76crS0KP07eh+Di61CMPfoSuppq8FrEL83SVO9gHAyNhmspQxyqWVHhn11+GwwLOwOv91OhpqaPZk1f5zf8/z6Pi4vDhg0bmJ+PGDECZmbcKp2TPMIQd9YPqvoaMJ/jLLUdfE2QBwWa3/NIXNvpCVU1FQzb1BRqagUH+yGTJiHh8hUYtGoFy83Sczmz8d9pn9NY8HgB9DT08Kj3I6iqFNxuNuvKZMzG2kBsANB0OtBcNgWDMrFbqbTQe0CyhuX6xCawMzUo9DYrDczdA/LGPmyfg0wAsI6ODtOQgloP68rgCpHt5grbOHkfgnMvQzDh+CsYaKvj7YI2vLpjjFcgTkXEoqOJEXbV4J/flVdj5aAsMHAH/PxXQkfHGg0b3JJ6xeDgYOzeLSqGokYrXBt4xF/7hMQ7wdCw1IfpmDpS28HXBHlQoD39NwBPLgagZFk99JnvxIvp/h06Is3fH6XHjIHJmNG86MypZPHjxTjhcwL1TOthb9u9MllDLkoTw0UFcCT9zwGVmstlWeUixcMDk0+8xukXn1G1rCGujP/OM108tq5wu5Q39mHrQJkAYGpJnJCQgJiYGLZ2FItx8j4EJ58FY+qpN0wDDGqEwacM8QzApah4dDctib+rledTdZHU5eu7DEHBu2FkVA/1HI5LvQdq2XzixAlQG3HqAkf/5iLUAplaIWtXL4XS/YVrSCAPCrTruzzh+ywSleqaoO2wgjf8yEpNhXddByAzExabNsKwdWsujyDfOb0v9YZntCf+rPYnpjpOzXd8oR3geQY4NRBQURPl/2rpF1pTlYYVLQ98S8tkWh8npWZgVvsqGNakUtHagNLanzwgb+zD1v0yAcAjR47Ejh07QK1dbW1t2dqi8OPkfQiOPQnCjDNvUcZAC09miyrb+ZJ+bz7iZnQC/jQvhVWVrfhSW2T1vHs3GeER52Bi0hY17f+Reh8eHh64cuUKjIyMMHHiRKnniydEbn+DtIB46LuYo0Qn4b405EGBdmzxE0SHJDHsD8QCUVBJ8fJCQLffGTWVrl+DZjn+OZSp8M35sDPSstKwvPFydKzYsaBmCzf/8lTgyQ7AvC4w7I5wdihXVjgPiNP3VFSAxzNawsyI/yY6Cue0QrwheWMftq6QCQCm69z69evD3t4eFy9ehJaWdAVBbI0vauPkfQgOugdi7jlPmBtp49HMlry6q/tLP7jFJWGYpQkW2VrwqrsoKnv58i/ExLrBwqIfqlReKPUWbt68CTc3N1haWmLIkCFSzxdPCFv1FJkxKTDqUAEGjS056ynoRDEFmn2L1mg9fFxB1f3f/KysbOwYdw/EBNFqcDXYOXLLmZZUHHf2HMJmzoSKri4qP3sKFY5R+Lw26x3jje4XuzNDznc5j4pGBQfuvDuXrcKtjYCIt0CDMUCbpWxnKccpPZCvB4bsf4qb7yPRsFIpHBkqXC1DvoYqB7DygLyxDyujAMgEANPixP3bu3dvJg+Y2B0IDFNhD9Gd/Upqyohzk60zZD1O3odg78MALLzoBStjopCRvjFDXv7o+NwHzxKSMa5cGcyqJD3ll6x9LW/9Hk86IinpPSpUmICKFcZKvfzZs2fx+vVrVK1aFT179pR6Pk0gOrCQuQ+BzGwY960CXXsTTnr4mCRrCrS4yGQcnvc/9q4CqqqsC3+0lCAdEtIGooIiooDd3d01to6dY47d3Tq2jt2ioICkiIo00t2dj3/d+3R+xzHeffe+Cw/uWWvWzPD23mfv7xx4+567z7f5XQ6Hr2oNjYb0L8ik/rkVWWfOoJ5NczS6Qr2MRRDcbkbcxBqvNVCQVsDrUa/F9wJcSS7wJ1H6VAWMuAhYMUuzKAiWnEztRCCrsAxtNj1DBa8K2wY3x7DW3BtGcV9ptnMfQfESWQKcnJyM5cuX49y5cz9Ner84SiTGxMW52jzY3gQnXkVj4/0QmGgo4vnvwjVW+NF6dPELw4eCYixppIOFxvRP38R93V95tEVZWTosLTegof4oyuEQvyfR0dHkm5NevXpR1icUKvPKkLyZ3/lPa1YLyBrQTwqFcYQNCrRPQel4cPg9QdeLaXudIS0rJYyr/9KJmzQJhV6voTp0KHQ3rKdt73sGNnpvxJWwK2il1Qpne/J50sVyRDwFLvBPsrHkE6CgJpZhcE7XPAS+vLmUlZaE/6ouqF9PpuY5yXlECQG2cx9BnRNJAhwXF4cOHTqACFqQJhhfnOXxeIL6LZZybG+Cw25R2PooFOZaSni60JlRzBy9QxBVXIq1pnqYaUi/AQGjzrFsrKqKhxduVqiqqkRz68PQ1KR+eerAgQPIyMggObOJ3x1hRll8PtIOviVVdVfYQ6p+9TQl+BcF2vYD0DRknuc24FEMvG9FQ0VTHmM28Dvw0R3hju1RmZkJ7VWroDZmNF1z39UffX803mW8w5jGY7C0zVKRzMGK0Wd/AB67AE0rYBb/oYsbHAJMIDD4sBcCYrPRy1oHh0YL1xCICT84G8whwHbuI6jnIkmAx44diwsXLkBNTQ3r1q1Dly5doKWl9ctGGMQFoNo82N4EB55HYMeTcJHQyNh6BSOxtBxbLBpior5GbV62X8ZWVpaJVx5tSDlb26tQVaH+R5vgyy4tLcWAAQPQokWLX875PYGi9+nIuhAKSEnwm2Aw2PqaikP/okA7dx0ycsxfYHl25iPCvFNg3FwDvX+j3664IiMDEe35Dx5G589BoTXzLX0reBVoe7EtSitLsbn9ZvQ15XcOFMtxqgcQ9xqwnQj05fNXc4NDgC4C8VlF6LCNf6Hy2FhbdGvKvV2ki2lN0Gc79xE0ZpEkwHp6ekhNTcXjx4/J5JcbfATY3gS7n4Zjr2sErPVVcHdOe0aXoYnHe2SVV2K3lQFG6tbt/uwFBWHw8eWXLTi0fQ4FBWq0cGVlZdi8eTOpTzw8mpoKx96Q/yoBufc/QUqtHnSXMJ/ACbqB/qFAU1PH9MOiec1/bYsf0mLz0aq7IRwG0u9EWOjlhbhJk8kQLXy8ISWCh/Hw7HAMvsNnmbjd/zZMVMX0Alx5CfCnAVBZBgw6DjTnd7XjBocAXQT2u0Zg59NwqMjLwG9lFxBlENwQfwTYzn0ERUwkCbCSEp8PsqCgQFA/6oQc25tg++NQHHwRhRYGqrg1y5FRjE1evkNRJQ9HmhhhgHYDRm2Lm7GsLE8Evh1Huu3s9A7S0tRa8mZmZmL//v2k/m+//Ua+LRFm5NyNQoFnEmQbqUBrOv1TUWF8IHRETYFGlFUdm/8SFaWV6Dy+MawcdIV19R+9zNNnkLZ1K6S1tWHu7kbb3vcM3Iq8hdWeqyEvLY/XI19DSpJ+3bJIHP2V0Vgv4PTn1urzPwCq3CWlX0HGff5rBIjf6y673BGVXohR9obYPJA+t/evZ+Uk2ECA7dxH0JhEkgATr3DDw8PJBFhYQn9BAxAnObY3wZaHITjqHo3Wxg1wbUY7xqAi/lDpuwWBqNg+06wRemjW7tKVXwGXknIHwR8XQFJSHh1dPvxK/D+fx8TE4MyZM+TPly1bhnr1hCsZyDz/EcXBmVBoqQW14Z87dFH2hr6CqCnQ8rNKcG6FF+nokGV20DauT9vppGXLkXvrFhSdnWB49Chte98zsNlnMy6FXkJLrZY41/OcSOZgxejLHcDzDYCKAbCA+n5nxUduErFD4H1CLvoe8CD9vjrdAW0acRcrxW4Rf+Aw27mPoLiJJAHeu3cvSeZ/48YNDBw4UFBfar0c25tgw72POOnxCQ4m6rg0jTkuxTIeD4bu78j1umJjCme16mEbqCkbJi7uFCIiN6FePQM4tqN+ekhQBhK/KzIyMlixYoVArCnfiz31QCDKEwqg3NEAKt2Zv3gmKN4n501FTkoyOoyagDb9PzMFCKosgFxscCbu7Q8iJafucYJsPWkBtH4uQjTAIBphqE+dCq1FC2nb+56BMQ/GICg9CKMbj8ayNstEMgcrRv8aDEQ+A6yHAYOPszIlN0ntR+DL95W+KkHb2RGS1XSHofYjzX6EbOc+gkYokgSYOCEkEl+C2P/kyZPo37+/oP7Uajm2N8G6O8E44xWDDuYaOD/ZnjFs8yoqYfHqPWnvdksz2KvW7RaovTfVbQAAIABJREFUkVHbERt7BPXrt0Rru+uUcfby8sKTJ0/IS6Nz5wrfNCJpozd4BeVQHWgGJXv6ZQGUAyGo2CoqsHfsIFTxeOi3aAXM2zD35uGLP2+fxcHzeiSU1OQwfjP90p6qigqyBXJVWRn0duyASh/mOW2JC3AOFx1QUlmCTe03oZ9pP2HgrX4dXiWw1RgozQP67AbsJlW/T5wHYo9AJa8Kbbe4Ij2/FL+5mGJJDyuxj4kL4P8IsJ37CIq9SBLghQsXgqA0I7hNiUYYVlZWIJpc/KwRBsEDvHPnTkH9Fks5tjfBypvvccEnDh0tNXF6Ip+lgImRWloOG69g0tRjOwvYKCswYVZsbXwMWYrk5OvQ0OgCm+bUX58Tl0Vfv34NIyMjTJw4USgcqsp5/CYYANQnNoW8ZfW8PmSDAu3F+RB89EyGYRM19J0rHGPG1yCXRkUhuje/JXGjO7dRz8JCqDX4mVJEdgQG3RlEitzsdxNmDehf3GPcSUEMJgcBR534kr/5AFpcoiIIbJzMzxF4FZGOsSd9SaEnC5xgoV233yrWtv3Cdu4jKH4iSYCJul8iof2WA/hHXeAIOeKzyspKQf0WSzm2N8HS6+9wxT8eXZto4/g4O8Ywiy0uhb13CGnPvY0VLBWFq1llzKFqNvQ2aDIyM92gpzcCja2ot4S9fv06Pnz4gGbNmmHIEOFKBioyipGyw59EQntBK8hoU7uIxxSEnwL98fef60hzc0VEgXZjWwBSonNh09kA7Yea03Y978EDJC5cBMjIwOpNACRkmCfevx15G6s8V6GeVD2yA5y0JP2yDdqBC2PA+zDwaBkgrwYsiQbZiYQbHAI0EVh49S3+fpOIJrr18WCecDzoNF3g1EWIANu5j6ChiCQBJrhMf9by+EfOEe1ga/NgexMsuhqEG28S0LOZDg6Poc5N+6O1CC0shotvGPmxT9vGMJKXq83L9svYfP36Iz//A4yNZ8PUZMEv5b8VOH36NGJjY+Hg4IDu3btT1icUSiJzkHGCX5ait84BkgzUxQrjyJuHd/DizDEoiYgCjXhYPrnoFUqLKuAy2hJNO+gL4+a/dNJ270Hm0aOQs7KCyS3R/A3a4rMFF0MvwkbTBn/1+ou2z9Vm4MpYIOQOYNkLGHmp2tzgJq49CBSXVcJu41MUllViRS8rTHMSjgay9iBS+yJhO/cRFEGRJMCCTl7X5NjeBPMuB+L22yT0tdHD/pEtGYP7bV4RegSEk/beOzaFpizzJ2aMOcuCIQ9PR5SWpsDCYi0MGvLp0KgM4tJodnY2unXrhnbthKuZLfRPRfb1cEjUk4b+OmY6o1GJ4Yvs89NHEfjoLgyaWGPY2i3CmPipTmFuKc4s5Zd6DPq9FXTNVGnPET/zNxS8eAGV/v2gt3UrbXvfMzD2wVi8TX+LkVYjscJ+hUjmELnRqipghzlQmA503QA4Cl+vLnJfuQnEBoE7QUmYeymQfJnwelln6KjU7TeKYrNwFBxlO/cR1DUuARYUKQbk2N4Esy6+wf13yRjYUh+7h9OvlfwCgXdOAQYERpL/G9HBGsrSYspnysCaEieSL9yaoKqqDM2a7Ye2Fr8hhqCD0N+0aRMqKiowePBgWFsLx32Z5xqHvKexkNFRgPZ85k77BY3ji9yNLWsR8zYA1p26odt05hOkhNAs3N7Db/c8eWcH1FOk//AV2akzypOSoLX4d6hP5jfDYHJU8irhcMkBxRXF2OC4AQPMBjBpnj1bGZHAgc97a4or0JC5sir2guBmqmkITD7jB9fQNDiaqePCFObYimpanHXZH7ZzH0Gx5hJgQZFiQI7tTTD9vD8eB6diqG1DbB9qw0AEfBNuWXkYERRN/ne8sw1k6jBdTXl5Ll6+akVi0arlJTRoQO2yYXFxMbZ+PnWcMGECjI2Foy/LvhGBQr8U1LNSg8aEpoytNVVDoqZAe++WgJeXwyFfXxaTttHvbliZn4/w1vw1Mzh+HEod6Nv8FrOonCgMuM1Pem/0uwGLBsxfsqO6TkLJvzkH3JkDyCgAy+IAKfoPH0L5wSnVGgQyC0phv9kVFbwqbBvSHMPsuKYqtWZxvwqE7dxHUAxFmgCXl5fjwoULePr0KVnjSHzZBwQE/ONbfn4+Xr16RdYL9+z5ubOQoJ6LoRzbm2DKWT88C0nDyDaG2DJIuJPF78H8MD0HEz/EQEoCSHRh7mRZDJcUhYVR8PbpRrre1v4pFBWptbdNS0vDoUOHSP05c+ZAXV24ttLpJ9+jNCIHim110WBA9TAMsEGB5n4pDB/cE6FvoYoBC/kPHnRGUUAAYkePIU2YvXSHjJBd+H7mw92ou1jhsQJyUnLwHuUtvhfgbs4Egi4CjZyB8XfowM7pcgiQCJx7HYM1t4MhJy0Jv1VdUL8e91BVG7cG27mPoBiKLAH++PEjiMtwUVFR/7BBfMv0QFClERRphIyPjw/s7Gr3KzW2N8H4U75wD0/H2LZG2DCgmaB74pdyN1OzMfNjLBSlJBHlVH0td3/pKAsC2dk+eBM4ipzJqUMgZGSodSUj9v758+dJfaIJhqysrFBep+z0R0V6Mep3N0b9jtVzipKdnIhT86eT/o/bfgCahsKdZv8MgFu73yAxLAfWzvpwGkm/2132pUtI+WM9pBo0gLmXp1CXd3+1YFt9t+KvkL/QXKM5LvS+8Cvxmvv5XhsgOwZwWQ64iHEjj5qLcJ3zbNAhT7yJy0Fva10cHE3/gbbOASgmAbOd+wgKi0gS4KysLNjY2CAxMRGmpqZkI4zjx4+TrZG/pTrbsWMHlixZQraA3bx5s6B+i6Uc25tgzAkfeERmYKKjMdb2Ze61+MXkTCwMjYe6jDSC2zOXWIvjoqamPcCHD3MgISGLji4fKSdQb9++xa1btyAnJ4fly5cLBQFRR5y01gtVZTyyBTLRCrk6BhsUaKeWeKA4rwxOIyxg7dKQdpjJ69Yh5/IVKLRtC6Mzp2nb+56B8Q/H403aGwy3HI5VbVeJZA6RG81LBnZ95vwddwcwcRb5lNwEtRuB2MxCOG/nd84kaDoJuk5u1E4E2M59BEVRJAnw6tWryYs9Tk5OePDgARQUFKCrqwvide+3CXBYWBgaN26MNm3awNvbW1C/xVKO7U0w/Ohr+HzKwjQnE6zo1ZgxzE4lpGNFRCL05WQQ0I65xJoxB1k0FJ9wDuHhf0BOThftHfl97KkMogTI1dUVGhoamD17NhXVf2R5ReVIWs//3dGc3hxyjVSEskNXSdQUaCWF5SQFGjH6L2iJhpYN6LqMmJGjUBwYiAbjxkJnBfPsDLwqHtkBrqiiCOvbrcdAczFtDf/hb+D6RIDgL14WD8jW7eY3tDceZwD7XCOw62k4VBVk4LuiC2SlJTlUaikCbOc+gsIokgSYOP0liP39/PzQqhX/tcaPEmDis3r16kFJSQkZGRmC+i2WcmxvgiGHveAfm42ZLqZYymBryUNxaVgflQQzBTl42DOXWIvjokZF70JMzEEoK1ujTetblEMgHhB9fX3RqFEjjB8/nrI+oVCWVIC0fYGkrs7S1pBuUD00QqKmQEuOzMHfO96QcU7Y6ghFFXr800S7ZuICHK+wELqbNkJ18GCh8P+ZUnRuNPrf4reCv973OizV6JdtMO6kIAYfLAZ8jwH6dsBUV0E0OBkOgR8iQLy16rzTHdEZhRhlb4jNA5m7o8LBXvMQYDv3ERQBkSTAysrKJK1TUVHRP6+Ef5YAa2pqki2Ty8rKBPVbLOXY3gT9D3oiKD4HczuZYWE35r54d8WkYNunFDRTksez1szZFcdFDQldgaSkK1BX74gWNicoh3DlyhWEhISQJUMDBwp3Olj8MROZ5z4CEoD+RkdISFXPSYqoKdCCXyXC7UIY5BSkSQo0YZrtfL1AZQkJiOrSlfyR8bVrkLdmvpznXvQ9LH+1HLKSsvAe7Q0ZSTG95HO4PZD6Hmg3B+i2kfI+5xQ4BL5G4F1CDvod4PN5X5vhgNbG1dO6nVsVdhBgO/cRNCqRJMCKiorklxNR8/tl/CgBJkoiiBIJQoeoHa7Ng+1N0Gf/K3xIzMOCLhaY14V+y9gva7M5Kgn74tJgV18B92zFlNKJoY0W9G46MjKeQVd3CJo0pt5E4cSJEyD2haOjI7p25SdjVEfB6yTk3I6CZH1Z6K2wp6rOmLyoKdA8rkUgyDUeOiYqGLyEPtdx/vPnSPhtFtnO1/JNACTl5RnD4ouhbX7bcP7jeVhrWONi74uM22fFYHEOsJW40FgFjLgEWFHjumbFR24SsULgj7vBOO0Zg4YN5PFycUdI1mEqTbFaOCGdZTv3EdRNkSTABLNDREQE4uPjoaenR/ryowT4xYsX6Ny5M2xtbcmSido82N4EPfa8RGhKPhZ3t8SsjsxRY62JSMSxhHR0aKCEay2YsyuOa+/nPxh5eW9hZDQDZqaLKYewe/du8u0HQQNoby9c8prz8BMK3BMga6gMrd+qh5aODQq0u/veIu5jFpo46qLjWPqlNxmHDyN97z7IGhvD9NFDymsniMKERxMQkBqAYRbDsNphtSAqNU8m/AlwcSjfryWfAAXutK7mLZL4eFRRyUPbLc+RUVCK2R3N8Hv3uv0WUXxWTnhP2c59BPVUJAnwrFmzcOTIERCX4datW/fDBJgoeejQoQP8/f3JG/AbN9buV2tsb4Iuu9wRmVbAeH/1JWHxOJeUia7q9XG+OTXeW0E3prjIeXo5o6QkAebmq2BoMJGS2wQNILHniX8PGzYMTZo0oaT/RTjzUiiKg9Ih31wD6qPoJ4bCOMEGBdrZFZ4oyCqF4xAztOhiKIyb/9JJmL8A+Y8eQbl7dzTcu4e2vW8NEBfg2l1qh8LyQqxzWIfBFszXGDPu9PcMPl0LeO4BNBsDs2r3RWVW8KzjkxDUnARFJzGeLXSCmZZyHUek9ofPdu4jKKIiSYCjo6NJZgdJSUkcO3YMY8eO/c8JMMH4sGDBApL/lyh/IE6MdXR0BPVbLOXY3gQu218gJrMIq/s0weT2jRjDbPbHWFxPzUZfTVUcb8Y81ytjjorYEHGRw829GXi8EjRtshs6Ov0ozVhYWIjt27eTOpMnT4aBgXD8vWmHg1AWmwclJ32o9qqeBxJRU6CVlVTg+PyXJFZ959jAsKlwDUO+XqConr1Q9ukTNObOgeZvv1FaO0GEP+V+Qr9b/D1xtc9VNFavnocTQXz9qczJbkC8D2A3Ceizm7Y5zkDdRmDhlbf4OzARzfTr496cDnUbjDoSPdu5j6CwiiQBJiY/c+YM+aVODG1tbWRnZ5OX3Ig6x+DgYCQlJZENMogk+fLlyxgyZIigPoutHNubwPHP50jMKcb6/k0xzoG5RHXKh0+4l56LoToNsL+xkdiuB13HKyoK4P6S32K6ZYvzUFNrR8lkSkoK+aaEGPPnz4eqqiol/S/CyVt8UZlbCtW+JlBy1BfKBl2lfyjQ1DUw/dAZuub+o58ak4frf/qTPx+3uR2U1egxXfBKShDWyhbg8dDw4AEod+7MuM8Poh9g6aul5MU3n1E+kBHH1sHlxcAWA4BXDgw6ATT/XArBOFqcwbqAQFFZBew2PkNRWSVW9W6MKR2q54G9LmBdk2JkO/cRNHaRJcCEA48fPya5TYluV98bBPXT4cOH0a0bv5VsbR9sb4K2m12RkleCTQObYbQ9c4nqmHfReJaZh3F66thmKdypZW1Y66KiWLz27kSGYt/mIZSUqF0IJN56EK3CibFq1SpIS0tThqWqsgqJqz0AHqA+tgnkGTgZpewEAFFToIV6J8P1TAhk5KQwdY8TbQaI4g/BiPn80G369AlkhTx9/xlWO/x24OzHs2iq3hSX+1wWBtbq14nxAM705vuxIBhQod98pPqD4jyoLgRuv03EvMtvQdx5e728M7Tr03uQra44uHmpIcB27iOodyJNgAkniFNed3d3eHp6Ijk5mWyEQZwIE7feO3XqBCkpKUF9FXs5tjeB3canyCgow7bBzTGsNXOJ6pDASHjkFGB6Q038YV49J441YTPk5AYgIGAY6UqH9n6QlaV2OSggIAB3794lWVCIbojCjIqcUqT8ya+n05rTErL6SsKYoa3zDwVa5+7oNm0ObXvfGnh9MxJvHsdBy0gZQ5e3pm0/58bfSF65EpIKCrDw94OEJPPUcZMeT4Jfih+GWgzFGoc1tH2uFgPu24EXGwEVQ2DB+2pxgZu09iAw8bQvXoSlo4O5Bs5PFu7Sb+1Bo+5EwnbuIyiyjCTAcXFxZCKrr193kyFBAGd7E7RY/wQ5ReXYNcwGg1oxd3LTJyAc/nlFmGekjeUmuoKEXitl0tIf4/373yAhIYWOLqGQkKCWRLm5uYH4h3ggnDlzplAYlcbkIv3IO1JXd3VbSClWD8/sFwo0p9ET0bof85e97h96h5h3GbBsq4MuE4S7LPg1wKlbtiDr7DnIt2gB48uXhML+Z0rEBTjHS44oKC/AWoe1GGIhpiVe5wcCUc+B5sOBQccYx4kzWHcQyCwoRZvNrqjkVWHHUBsMsWXuO6nuoCiekbKd+wiKEiMJMFHHS9CcJSYmCjpvnZRjexM0W/sYBaUV2DuiBfq3YO7hpLNfKIILSrC0kQ4WGNfui4s/26gJiRcRFrYasrKa6NCe+u144vSXOAU2MzPDmDFjhPqdKApKQ9alMEjISEJvfTvapQHCOMEGBdpfq18jN70YDgNN0ao7/XKe2AkTUeTtDdVhw6C7/g9hwv6pTmxeLPrc7EPKXOlzBU3U6SftjDv5K4OVFcBWI6CsAOizB7CjxnLyK/Pc53ULgbNeMVh7Jxj1ZCTht7ILlOtVz8N63UK9ZkTLdu4jaNSMJcAEgwNxsY0bP0aA7U1gueohSit4ODS6FXpZM3dS6+gdgqjiUqw11cNMQ606u+TRn/bh06e9UFJqDPs29yjjcPHiRYSHh6Nly5bo35/fLpfqyHePR+7DGEhrykNnkR1VdUbkv6ZAG7/9ADQMmbtwSThYUV6JY3PdUVUF9JppjUY2mrT8JsqyIto5ojI7G9qrV0Ft9Gha9r6n/PDTQyx5uUS8L8AlBQLHXPjhzfIFNDm+VsY3Sh0yOPCQJwLjctCnuS4OjGpVhyLnQmU79xEUcS4BFhQpBuTY3gRmKx6ggleFo2Nt0b0pcye1tl7BSCwtxxaLhpior8EAMuJpIjRsDRITL0BNrQNatqDOfHD06FGyLt7JyYmshxdmZN+OROHrZMiZqUJzirUwJmjr/IsC7fwNyMjK0bb5tYGMhAJc2civcx69vi1UtRRo2a9IT0dEByfShtFf56Fgx/yDw07/nTgTfIY8+SVOgMVyvD4EPF4OKKgDi6PIjnnc4BAQBoGYjEK47HAjVU+Ot0PnxtrCmOF0xBQBtnMfQWHiEmBBkWJAjs1NQJxyNVr+gPT61AQ7dLJi7g9OE4/3yCqvxG4rA4zUpc/HygC01WLi3ftZSE9/BB2dAWjaZCdlH3bs2EG2C+/duzdatxbuYlfG2WCUhGRBwU4bakOosVBQdvgHCqKmQIvwS8WTk8GQkpbEtH3OtNumFnh6In7yFDIaC18fSNWvzxQU/9iZ8ngKfFJ8yNpfogZYLMeVMUDIXcCqDzCCz1bCDQ4BYRDY+ywCu5+Fo4GCDHxXdoGMFLX7EsLMyenUHATYzH2oRM0lwFTQoinL5iYg2k2areS3dz07qQ2cLei9Nv46dJOX71BUycORJkYYoN2AJiriq+4fMBy5uf4wNJwCc7PllAIh2FCILnDEg8qIESNAtA8XZqTufYPy5ELU72KI+l3o18YK44PrqSN4+/geDJo2x7A1m4Ux8VMdnzvR8H8QA3V9JYxY3Ya2/cxTp5G2bRuk9XRh/vw5bXvfGiDW1PGyI/LL8kn2B4IFQuwGUW+y3QwoygC6bQLazRa7EDiHawYCxO9Dp53u+JRRiLFtjbBhQLOa4RjnBWsIsJn7UAmKS4CpoEVTls1NUFJeCavVj0iPL06xRzszZkoViD9mem5BqCKanTRrhB6aKjRREV91r9edUVwcAzOzZTAynEopkLy8POzatYvUmTZtGvT09CjpfxFOWv8avKIKNBhiDkU75spcqDhzY/MaxAS9gbWIKNAeHXuPqDfpMLPTQvcp9L88k5YuQ+7t21BycYHBkcNUQhVINj4vHr1u9iJlL/e+jKYaTQXSq1FCGRHAgc+lIVOfA/q2Nco9zhnxQSAoPgf9D3qSDt+Y6QBbI2p0keITKefpjxBgM/ehsgqMJcCysrJo145aJ6yvHZWQkICrqysV38VOls1NkF9SDut1T0iMrkxrC3sTZkoVSnk8GLnzabcu25jARY3518fisrBu7jaorCxAk8Y7oKs7kJLbBGPK8ePHSZ1FixZBWVmZkj4hzCurRNIaL1JPY3Iz1DOvntP4k3OnIic1GaKiQLv4hw+ykwvRpm8jtO5Nv6V39KBBKP0YAvVp06C1cAFl3H+l8CjmERa7L4a0pDTZAU5WSvZXKjXv84CzwN25gIwisCwOkKLepKXmBcV5VB0IrLsTjDNeMTBQk8fLxR2rhammOuLm5vw/AmzmPlRwZywBJhJY4nRQ2EHoE6+Fa/NgcxPkFJWhxfqnJJw3ZraDrREzyVFueQUsPT6Qdm+3NIO9avU0XqjufVJZWQo3dz61VQubM1BXp9bTPjQ0lGwBTuz71atXky3BqY7ytCKk7gog1bQX2UJGk97lMKrzE/KipkCrrOTh2Bx38HhV6D61Gcxs6bGOVFVUIKxlK1SVl0Nv5w6o9P7c5UyY4H+gsytgF05/OI3Gao1xte9VBi2zaOrv6cC7y4CJCzDuNosTc1PVJgSIUry2W1zJhkxzOplhUTeOSaQ2ra+gsbCZ+wjqEyHHWAIsLy+PYcP4XbGEHadPnxZWVSz02NwE6fmlaL3pGT9RneUIGwNVRjBKLS2HjVcwaeuxnQVslNlPuhgJhKaR4uJEeL3mMwm0aX0PysqNKVn08/PD/fv3yZNf4gRYmFESno2MU/yHEYIDWFKW/a6KoqZAy04pxMV1PmSMI9a0gboevQeu0shIRPfpS9ozuXsHcubmwkD/U52pT6bCO9kbg80HY127dYzbZ8XgHmsgJw5wWQG4LGVlSm6S2oeAW1gaJpz2IwN7ttAZZlr0fn9rH0J1IyI2cx8qiDKWAHM8wL+Gnc1NkJJbQj55E+P+3PZoqsdMrW5scSnsvUNIu+5trGCpWDd7uefmBcHffxCJQ3tHb8jJUbtk+Pz5c7x8+ZKs/SVqgIUZhb4pyP47ApKKMtBb3VYYE7R1ogP9cPNPfiOJuSKgQIsKTMOjox8gISmB6fucSSYIOiPvwQMkLlwECRkZWAa+gYQ0s6/2ibdg7S+3R15ZHla3XY1hlvQOBejEKrRubiKw+3PjjvF3gUb8Bz1ucAhQRWD+5UDcepsEa30V3J3Tnqo6J19LEGAz96ECGZcAU0GLpiybmyA+qwgdtr0gPX483wmWOtRrTL8XbmhhMVx8w8iPfNo2hpE8s5yvNCFmTT0j4zmC3hEX3yTINsiSktQSqdu3byMwMBCWlpYYOXKkUH7nPo1FvmscZPSVoD2npVA26Cq9eXAbL84eh5K6BqYfos6F/Kv5CfYHggVCVVsBo/+gn+Sn7d6DzKNHIde4MUxu/v2r6Sl/npCfgJ5/9yT1LvW+hGYa9C/tUXaCrsL768CNyYCkDL/+V7ZuvuWhC2Nd1y8srYDdxmcoLq/E6j5NMLk9/fr9uo6puMbPZu5DBSMuAaaCFk1ZNjcBQTnT8TPxuOsiZ5hqMvPqKTCvCD0Dwkkk3rVrCi25utnOMinpKkJCl0NGRg1OHfiv+KiM8+fPIyoqCnZ2dujTh98yl+rIuhaOooBU1GuiDo1x1dNqV9QUaAT/L8EDbNJCEz1n0G/0ET9jJgrc3KDSvz/0tv5JFfJfyj+JeYJF7osgLSEN79HekJMSwwfE+4sAvxNAw9bAFH4ZFTc4BKgicCswEfOvvIWkBOC9ojO0lOvm20KquNVGeTZzHyr4cQkwFbRoyrK5CSLT8tFl10vSY/fFLjBSV6TpPV/9dU4BBgZGkv8d3sEa9aXZrztlJBCaRmJiDiEqeicUFS3Q1p7Pt0xlHDp0CGlpaejYsSOcnZ2pqP4jm378HUqjcqHUTg+q/UyFskFXSdQUaFc2+SIjvgC2PYzQdgD9GCM6dUJFUjK0liyB+qSJdMP/j/6egD04+eEkLBtY4nq/64zbZ8XgoXZAWjDgOA/oup6VKblJah8C40/5wj08HR3MNXB+sn3tC5CLSGAE2Mx9BHaKyUtwXA3wr2FncxOEJOeh595XpFOeyzpBX1X+1w4KIPEiMw8j30WTkvHONpAhHu/r4AgLX4+EhLNo0KAdWrU8TxmBrVu3ori4GP369UOrVq0o6xMKKdv9UJFZApVejaDs1FAoG3SVREmBVsWrwrF57qgo56HLxCawtKfHc1yZn4/w1vxGGgYnT0DJ0ZFu+P/Rn/50OrySvDDQbCDWO4ph8licDWwlXlVXASOvAJY9GMeIM1j7ESAuYRN3UCp5Vdg51AaDbavn71PtR1o8ImQz96GCCHcCTAUtmrJsboIPibnos9+D9NiXeP1Un5nXTw/TczDxQwykJIBElxY0ERFf9fcf5iIt7T60tfuhWdPdlAKpqKggu8ARY/To0TAXgomAuGyVuNoTqKiC2igrKDSndgmPksM/EBY1BVpeRjHOr3pNzj5sRWtoGtKrYy8KCEDs6DGkPXOPV5DWYKY5zBd4iDVxuuKEnNIcrLRfiRFWI5iAmV0bYY+AS8PJ2nYs/QTIM0OfyG4Q3GzVjcBpz0/44+5H1JORhP+qrlCSo3ZHorr95+ZnFgE2cx8qnjOSAFOZsC7LsrkJAuOyMfAQv0lCwKouUFdiphbxZmo2Zn6MhaKUJKKcmtfZ5Qx4Mwo5OT4wMJjvEIj8AAAgAElEQVQIC/NVlHDIzs7G3r17SZ0ZM2aAeHtCdVQWlCF5I58eTPM3G8gZst+QRNQUaDHvM3D/4DsyF5u21xkyNGnesi5eROr6DZBSU4OFF78zFZMjqSAJ3W90J01e6HUBzTXF8Pfj6RrAcy+g1RT4jf/3gxscAlQRIDq/ER3g+troYf/I6rmgS9VnTl50CLCZ+1CJgkuAqaBFU5bNTeAXk4WhR/inZ0FrukFFgZnLaheTM7EwNB7qMtIIbi+GN9xpruEX9dfe3VFUFAlTk8UwNp5ByWpcXBxOnTpF6ixevBiKitTrs8sS8pF24C1pQ3d5G0ipMPOAQyUQUVOgBT6Jg9ffkVBWr4dxm4TvMvklpuS165Bz5QoU2raF0RnmOcefxT7DArcFkJKQgvcob9STZuatC5U1oS17oiuQ4Au0ngL03knbHGeg7iHw9QXsUxPs0MlKu+6BwEX8LwTYzH2oQM8lwFTQoinL5iZ4HZWJkce9SY+D/+gORYZeQZ1KSMeKiEToy8kgoF1TmoiIr7r7S1tUVOSgsdVW6OkNoRRIcHAwrl27BikpKaxatUqo1qDFHzKQ+VcIiCvW+hsdSZ5ctoeoKdBcz4Ug1CsZRs3U0We2De3wYkaMRPHbt1AbPx7ay5fRtvetgX1v9uH4++Mwb2COv/sxT7HGuMPfGiwvBrYYALxyYPBJwJravha5f9wEYoHA7qfh2OsaATVFWfis6AwZKXrc3WIRNOfkTxFgM/ehshRcAkwFLZqybG6CVxHpGHvSl/Q4bGMPyDHE1nAoLg3ro5JgpiAHD3tq3c9owldj1Hm8crxwsyL9sWl+AhoaHSn55u3tjUePHkFVVRXz58+npPtFON8jEbn3oiHVQA66S/kXu9geoqZAu77VH6mf8tCiqyEcB5vRCq+KxyMvwPEKC6G7eTNUBw2kZe97yjOezoBnkif6m/bHxvb8Gm+xGp9eAWc/U/ItDAHq64mV+5yz1Y8AUQdP0G/GZBZhnIMR1vevu28Jq381ao4HbOY+VKLmEmAqaNGUZXMTvAhLw8TPLSijN/eCJEMnhLtiUrDtUwqsleTxtHXd7OteUpoCT08+g0Bru1uoX58aP+3Tp0/h6ekJAwMDTJ48WahdlXMvGgUeiZA1rg+tGfRPR4Vx4gsFWvPOPdB12mxhTPxQh/giPbHgJcpKKtFpnBUat6OXjJUlJCCqS1dyPuPr1yHfjNm3F4S/zleckV2ajeVtlmNU41GM4sGKMfdtwItNgKoRMP8dK1Nyk9QuBL6+e3JjZjvYGnGXKGvXCgsXDZu5DxUPuQSYClo0ZdncBE8/pmLqOX9ISACftvSm6fn/1TdFJWF/XBpa11fEXVtzxuyKk6G8/A/w8+tPuuzYzgP16ulScv/vv//Gu3fv0KRJEwwbJlyr3MwLISh+nwGFFppQG8E/jWZ7iJICrSC7FGeX8y+qDV5iCx0Teq28811dkTBrNiApCcs3AZCsx2x9bkphCrpe5yfY53ueRwstMWRIOdcfiHYDbEYCA4+wvZ24+WoBAmtvf8DZ17EwVFMg+ecliC8gbtR5BNjMfaiAzSXAVNCiKcvmJnj4PhkzL7yBrJQkwjfxW7MyMVZHJOB4QgY6NFDCtRb0Xksz4U912MjIdENQEP/ktqPLR0hKUruAdvbsWXz69An29vbo2VO4tUk7+BZl8flQdjGASg9j1mH4FwXa7yth3tqBUR/iQ7JwZy//kt+U3U6Qk6dHo5R+6BAy9u2HrIkJTB/cZ9RXwphrnCvmv5gPSQlJ8gKcvDQzvNuMO/ojg5UVwJ+GQHkh0HcfYDuetam5iWoHAuWVPLTd7IrMwjLM7WSGhd3q5hvC2rGazEbBZu5DxXMuAaaCFk1ZNjfB3aAkzLkUCAVZKXxczxyZ/eKweJxPykRX9fo439yEJiLiqZ6UfB0hIUshLV0fzk6BlIM4cOAAMjIy0KVLF7Rv356yPqGQtMkHvPwyqA4whVJbeuUBwjjwLwq0HQehYWAkjJkf6gQ9j4fH1QgoqshiwlbhMPraeML8Bch/9AjKPXug4W5qvM2CBLY/cD+OvTsGM1Uz3Ox/UxCVmiWTGAAc78T3abY/oFE33+7UrEURL29ehKZh4hl+W/jni5xhoqkkXgFw3ooMATZzHypBcAkwFbRoyrK5CW4GJmDBlSAo15PG+3V8blImxuyPsbiemo2+mqo43oz9k0cmYqBrIzb2KCKjtkFBwQQObZ9SNrd582aUlZVh4MCBsLGhXr9bVcFD4ip+eYD6hKaQt1Kj7ANdBVFToLldCEXwqyQ0tGqA/vPp84hG9eyFsk+foDl/HjRmUKOtEwSrmc9mwiPRA/1M+2FT+02CqNQsGa8DwJOVgIIGsDgSZO0UNzgEKCAw73Igbr9Ngk1DFdyeTf+hlcLUnGgNR4DN3IcKFFwCTAUtmrJsboJr/vFYfP0dGijIIHBNN5qe/199yodPuJeei6E6DbC/MbOnfow5KWJDERGbERd/EqqqbWDb6hKl2UpLS7FlyxZSZ9y4cTAxoX6KXpFZjJTt/qQNrXmtIKtLnUeYktPfEf5Cgaasrolph5jn1L258w2SInLQvGNDdBhuQctdXkkJwlrZAjweGh46COVOn086aVn9vzJxAc7lqguySrKwrM0yjG48miHLLJq5PBoIvQdY9QFGXGBxYm6q2oBAYWkF7DY+Q3F5Jdb0aYJJ7Yl22tzgEOAjwGbuQwVzLgGmghZNWTY3wSXfOCz/+z00leXgt7ILTc//rz46KBquWXkYp6eObZYGjNkVJ0PBwQuRknobWlq9YN1sPyXXidIHogSCGLNmzYKmJvUWxqXROUg/9p60obfWAZI062MpBfBZ+AsFmmGz5hi6erMwJn6qc/L3VygpKIfzKEs0c9KnZb/4/QfEDB1K2jB99hSyDRvSsvet8tcX4M71PIeWWvRPrBl18FfGqqqA7aZAUSbQfTPgMOtXGtznHAL/QuDLG0cpSQl4L+9Mfu9wg0PgCwJs5j5UUOcSYCpo0ZRlcxOc947F6lsfoKdSD17LO9P0/P/qgwMj4ZlTgGkNNbHenF5iwphTLBsKDByHrGxPNGw4FpYW6yjNTlx+Iy7BEWPZsmWoJwQbQeGbVGRfDYeEnBT01jlUy01rUVKgFeeX4dRiDxKjgYtaQs+cHpVSzo0bSF65CpKKirDw92Mcr+dxzzHvxTzyAtzrka+hIKNAaU9Uu3B6GHDwM5f0NDdAT8wS+GoHkHNg3ClfvAxPh5OFJs5Nqh5ecm4Vai4CbOY+VFAQ+wSYOFFbsmQJAgICyGP2wsJC6OnpkTfsiQTj2xrLoqIirF+/HpcvX0ZycjJ0dXUxYsQIrFmzBgoK//3iIuiqVq5cCQ8PD7Ju09rampxv0KBBVHAmZdncBKc9P+GPux9JOpqXS6g1avhZYL0DwhGQV4R5RtpYbkKN/osyYDVUwcenFwoKw2DSaD4aNZpDyUtiPxE0aDIyMlixYoVQyVje8zjkPYmFtLYCdBbYUpqfKeETc6cgNzUFTmMmoXVf6r8LP/MjKSIbN3fyLxdO2tEe8kqytNxO3bIFWWfPQb5VKxhfZP71/oHAAzj67ihMVUxxa8AtWr5Wi7L/aeDefEBWCVgaC0jRY9yolhi4SasNgfT8UrTd4opKXhV2D7fBwJbMvmGptsC4iRlDgM3ch4rTYp8AR0ZGkrWUDg4OMDIygqKiImJiYnDmzBmkpqbi/v376NqVz89ZWVmJzp07w93dHWPHjoWTkxPev3+PgwcPokOHDnj27BnZnvbLCAoKIm/py8nJkR27iNfVf/31F5kMnzhxgnITAzY3wYlX0dh4PwQmGop4/rsLlT3xU9nOfqEILijB0kY6WGCsw5hdcTL0ysMeZWUZsLLcCH39kZRcJxpgEI0w1NTUMHfuXEq6X4Szb0ag0CcFchYNoDmJ/U5LlRXl2DtmMKqqeOgnAgq0Dy8T4X4xDPWUZDB5RwehMPpaKXbCRBR5e0N1xHDorqN2Yi/I5L89+w2vEl+hr0lfbO7AfDmIID7Qkvl7GvDuCmDaCRgrhgwWtILnlOkicMrjE9bf+wh5GSn4r+oCRTnuAYouprVNn83chwp2Yp8A/yjYpKQkGBoakknu8+fPSbFTp06RSeucOXOwb9++f1T37t1LJrgnT57EpEmT/vk5oUsku76+vrCzsyN/XlFRgXbt2iEsLAyxsbFkO1tBB5ub4LBbFLY+CoWFthKeLHAW1MVfyjl6hyCquBRrTfUw01Drl/K1TaCqqhLPXxCNJ3hobn0Empr8hytBB9ECmWiFTDysTZw4UVC1f8llnP6AkrBsKLbRQYNB7NNVZSUl4vSC6aRP40VAgfbqSjjevUiAnrkqBi5qJRRGX5SIC2oRDu1QmZMDnbVr0GAktQcWQSbveLUjMoozsLT1UoxpMkYQlZols8cayIkDOq4CnBfXLN84b2o8Av0PeCAoIRf9W+hh7wiufKbGL1g1OMhm7kMlvFqbABOnvQ0aNICZmRnevHlDYuLi4kKe/hInxEQC8mWUlJRAQ0ODTHLd3NzIHxMyjRo1InVevHjxL0yJU2DiBPn06dOYMGGCwHizuQkOPI/AjifhaKxbHw/n0T9F+xKkrVcwEkvLscWiISbqawgce20RJE5+iRNgYtjZXoeKCrU/+NeuXUNwcDCaNWuGIUOGCAVLyu4AVKQWoX43I9TvZCiUDTpK0W/8cHPrHyRV1rxzNyAtS69E4Vtfbu8JREJoNpo66cNlFD0y/fK0NEQ68R8AjS5egEIregn1t76mFaWh8zV+jf2ZHmdgq109JSlCr2duIrC7CV99wn3AmKOvEhrLOqgYnV6ATjvdychPT2yNjpZ171CkDi475ZDZzH2oOFdrEuDy8nLk5uaSJ7RxcXHYuXMnrl69itWrV5M1v8RJkLKyMlRUVJCYmPgfjIjTXiJRzs/PJ+syr1y5QtYGE3Wamzb9m9czOjoapqammDlzJg4dOiQw3mxugt1Pw7HXNQLNG6rgDoOcjE083iOrvBK7rQwwUldd4Nhri2BBQRh8fHuR4bRzcIO8PDUmDOItBLE/iZKd7t2F42dOXOuFqtJKNBhmAcVW2qxDG3D/NtzOHYeoKNDOLPVAYW4Z2g8zh00navh+C0aBhyfip0whf2zh5wspZWVG8XKLd8Oc53MgAQmyA5zYXYB7fx24MRmQlAGWxwMyYtbBjtHV5IxRRWDX03Dsc42AuqIsfFZ0hrSUJFUTnHwdQIDN3IcKnLUmASZObjt2/P9lLyLRnTFjBjZu3AhpaWlkZmaSp7xt2rSBj4/PfzAaNWoULl26RMoR9ZlEAv3777+TCS6R6H49iMtwRF1w3759cefOnR/inZeXB+KfL4O4dEfMHx8fj4YMUzF968SOx2E48CISLQ1VcfM3Ryp74qeyJi/foaiShyNNjDBAm97tfMacYtFQVpYnAt+OI2d0cf4AKSlqCQNRbpOdnY1u3bqRpTRUB6+kAknrXpNqGlOtUc9U8BIcqnP9SN711GG8fXwfoqBAKy2uwIkFL8mp+81rAYPG9Jp8ZJ48hbTt2yGjrw8z12dMQfCPnUNvD+Fw0GE0UmmEOwN+/LeA8YmZMnhvIeB/EjCwByY/YcoqZ6cOIEDyX+9wQ2xmESa0M8a6fk3rQNRciMIgwCXAwqBGQYdIKggmCKLRQHh4OM6fP0+esm3bto28GEcknURNMHHZ7eVL/hfs14Oo/SVKGr4kpxs2bCCZIb6tC/6iIykpiU6dOpEX53401q1bhz/++OM/H7ORAG95GIKj7tFoY6yGqzMcKCD5Y1HiD56+WxB4AM5aN0J3DRVG7IqTkZSUOwj+uABSUopwcX5HyXUCP+JtAvGWgih/IMogqI7ylEKk7uGX9OgstoO0OrUEnOp835O/vmk1Yt8FonnnHug6bTYTJv+xkRKdixvbAsj/H7/FEUoN6PGJJi1ditzbd6DUsSMMDgv+tkbQoGa7zoZ7gjt6m/TGnx3+FFSt5sgdcgDSPgKO84Gu//1bVXMc5TypaQi8icvGoENepFs3f2uHloZ170Ckpq1JTfWHS4BZXhkiISYo0Jo2bYqHDx/WuRPgDfc+4qTHJ7QzVcfFqW0ZQb+Ux4OROz/pu2JjCmc1Zl8nM+KkiI3ExZ1CROQmyMsbop3Dv2vDfzV1cXExtm7dSooRF+C+rkP/le6Xz4tDs5B5JhiQAPQ3OEJCmv1XjqKkQAvxSsLzc6GQrSeFKbudhKKJ+xrL6AEDURoaCvUZ06E1f76gMAss1+lqJ6QXp2Ox3WKMa8p/MyA2oygL2Pa5Y9eoq4CFcCU5YhMv5yijCKy5/QHnXsfCWF0BL353of27yqhznLEahQCXAFfDcsyePZukOCOaDxDJhpKSEsnaUBdqgNfdCcYZrxh0MNfA+cn8S1t0R255BSw9PpBmbrc0g72qEl2TYqcfGbkNsXFHoaLSCna21yj5n5aW9k/NOEGBRpTaUB0F3knIuRUFSWUZ6K1k5sGGig+ipkDzvBGJt0/joN2oPoYs5TOvCDuqyssRSrRALi+H/u5dqN+zp7CmvquXXpSOTtf4bZVPdz8NOx16/jLqnCDGwh4Cl0aAfJpaGgPIs19OI4ibnEzNQ6C8kgf7za7IKizDvM7mWNCVXrvymhch5xGTCHAJMJNoCmiLoDwjLh0Rl9tatmwJZ2dnsvzhWxYIomxCXV39XywQRNJsYmJC1hV/oVH7Mq04sECsvPkeF3zi0MlKC6cmtBYQsZ+LpZaWw8YrmBR6bGcBG2Ux63jFAAofPy5BcsoNaGp0RfPmRyhZjIqKIktziEE0VyGaYVAduY9ikO8WDxkDZWjPakFVnba8qCnQ7h0IQuyHTFi100XncY1p+VsaEYHovv1IGyYP7kPOxISWvW+V3ePdMfs5vwSEuACnKKPIqH2RG3uyGvDaB2g3A2Z6inw6boLag8Dz0FRMOuNPBkSc/jbSELO9X3uWQiwi4RJgES0T0exCW/u/N+GJJNfW1pZsfpGSkkK2nCWaV0ydOvU/PMAEJ/C8efP+09yCaILh5eUFPz8/0hYxvvAAh4aGkjzABNWaoIPNTbDsxjtc9otHtybaODaOmZOp2OJS2HuHkOG+bGMFC8V6goZea+TeBk1CZqY79PVGwspqI6W43r59i1u3bpF7kehSKMzIuhyKorfpkLfWgPpoegmiMPOLmgLt/Cov5GWUoN0gM7TsRo/iLffefST9/jskZGVh+SYAEtLMEvQTl9+IS3DG9Y1xd+BdYeCsXp3jnYFEf6D1VKD3jur1hZtdrBCYeykQd4KSYGOgituzmLtkLVYgcM4KjACbuY/AThHvvqqImzliPIgGFkRnrV69esHY2JisQwoJCcG5c+dQUFCAs2fPYswYPjk9kQwTJ7qvXr0iu8cR1GdEa1qiTIK4kU/w/X7dCY44OSZkiIRlwYIFJIvEhQsXSP2jR49i2rRplJBjcxMsuhqEG28S0MtaB4dGM8NNGlpYDBffMDJm37aNYShP74ISJfBqiLCvXz/k5wejkfEcmJhQqykl9o2rqyvZUXDWrFlCRZR2JAhlMXlQaq8P1T7MnmgK4pAoKdDKyypxbJ47UAX0ntUcxtb0eKbTdu5C5vHjqNekCRr9fUOQ8CjJEPRnBA1az0Y9sc1pGyXdahcuKwT+NAR4FcCQU0CzwdXuEueAeCBQUFoBu41PUVLOw7q+TTDB8XMduXi4z3lZDQiwmftQCU/sE2CChYFIRv39/UHUWBIntLq6unB0dCRPdQnasa8HkRQTvMAEzy9BS0bIDh8+nGR8IGqEvx1EO2TidTXREY6gP7O2tsbixYuFamLA5iaYdzkQt98moZ+NHvaNpNas4UcbKDCvCD0DwsmP3zs2haYs9Vf4VDZnTZT18HREaWkKLC3+QMOG1Lp+PXjwgOwqSJTWEA9gwozkrb6ozC6FSh8TKLfXF8YELR1RUqClx+Xj6mY/0r+xGx1QX4Mew0Xc9OkodH8JlYEDobeF+RbFRAMMohHG73a/Y3zT8bRwZV052h04xy8PwcIQoL4e6y5wE4onAn+/ScDCq0GQkpQguX81lOreQYh4rlz1ec1m7kMlSrFPgKkEW92ybG6CWRff4P67ZAxqqY9dw5mpFX2dU4CBgZEkjBEdrKEsLVXdkLI6P/Gy5IVbY1RVlcO62UFoafWgNP/ly5dBlM4Q7CQDBw6kpEsIV/GqkLjKE+BVQX1MY8g3o3dCStkBAKKkQAvzScGz0x8hLSOJaXudISEpIYyL/+hEdOyEiuRkaC1bCnUKHRsFmZRofUy0QCbGqe6n0FqHmTp7QeZmRMbtT8BtC6BqBMynRufHyPycEbFFYOxJH7yKyICLpSbOTPz3AZPYBsU5LlIE2Mx9qATCJcBU0KIpy+YmmH7eH4+DUzHMriG2DbGh6Tlf/UVmHka+iyb/O97ZBjI0ExRGnGLRSHl5Ll6+4rfStW11Baqq1Gqrjx8/TjKQELXlXbp0oex5ZW4pkrf4knpas1pA1oB9GroTcyYjNy0VTmMmoXXfQZRj+JmC960oBDyKhYaBEoavpPfFWpmbi3B7PkuG4amTUBSi6cjPfH2Z8BKzXPllLF4jvaAsy/5a0AL/bD/gkztgMxIYSO0yJ615OWWxRiAtvwRtN7sSz+DYM7wFBrRk/y2UWANYR51nM/ehAjGXAFNBi6Ysm5tgylk/PAtJw8g2htgyyJqm53z1h+k5mPghBlISQKILM6fKjDjGkpHCwih4+3QjZ3No+wwKCtRq33bt2kV2BiTq1b8tzREkhNLYPKQfDiJFdVfaQ0pZVhA1xmS+pkDr//sqmLVmlobt4ZH3iH6bDos22ug6iV5XqSI/P8SO5ZeZmHt6QFqd2bbdR4KO4ODbgzCqb4R7A+8xhjErhirL+fW/5UVAv/1AK+HKcVjxlZukRiFAcMsTHPMKslLwX9UFCrLMXiytUcFyzjCGAJu5DxWnuQSYClo0ZdncBONP+cI9PB3jHIywvj/1jmPfC/VmajZmfoyFopQkopya00RD/NSzs33wJnAU6biz01tISwt+6sfj8ci23MS/iZrzxo2pMzgUvUtH1sVQQFoC+usdaZcIUF2BrKQEnF4wg1Qbv+MgNAyMqJr4qfyFtd7ISS2CfX8T2PU0pmU7668LSN24EVIaGrDweEXL1veU5z6fixfxL9DDuAe2O29n3L5IDSYEACf4/MWYHQBomIl0Os547UGg734PvE/MxYAWetgzgpm7JbUHHS6SHyHAZu5DZRW4BJgKWjRl2dwEo094wzMyExMdjbG2L73TtC9hX0zKxMKweGjISONDe2aSapqQsqqemnofH4LnQlJSDi7OwZQ6HxGXL3fs4FNNTZkyBQ0bNqTse/7LBOQ++ARp9XrQWcx+zWlUgC9ubVsPSEhg3rkbkJZl7gS6soKHo3PdyTrnntOtYdJSkzI+Xyskr1mLnKtXydIHogSC6dH1elekFKZgoe1CTGw2kWnzorXntR94sgpQ1AR+jyDXkxscAr9CIDKtAF12uZNiZya2houl1q9UuM85BEgE2Mx9qEDOJcBU0KIpy+YmGH70NXw+ZWGakwlW9KJ+2vi9UE8mpGNlRCIa1pOBvwMzSTVNSFlVj48/i/CI9agnpwdHR2qnigTjCMFWQgyCUk9FRYWy7zl3olDglQQ5UxVoTmX/BP4fCjQNTUw7eJqy/z9TyEwqwOX1/PrmUevs0UCHHrF+zPARKA4KgtrEidBeuoRRX7NKsuB8xZm0eaLbCdjrMtNpkVEnf2bs0igg7D7QuB8wnN+YhRscAr9CYOeTMOx/HgkNJVl4L+8MaSn227D/ykfu85qJAJu5DxUEuASYClo0ZdncBIMPeyEgNhszXUyxtIcVTc/56gfj0rAhKgnmCnJ4Zc9MUs2IYywZiYraiZjYQ6iv3BytW9+kNGt4eDguXrxI6qxevfpffNOCGso49xElHzOh0EoLasMsBVVjTO7ZycMIenIfhs2aY+hqZmnFIgPS8Pj4B0hKSWD6PmdI0vhyreLxEGbXGlVFRdDdsgWqAwcwhgFhyCPRAzOfzSRteo70RH3Z+ozaF6kxHg/YbgoUZwE9/gTa8uPgBofAzxAgGHCctr9AfFYxJrQzxrp+de8AhNshwiPAZu5DxUsuAaaCFk1ZNjdB/4OeCIrPwdxOZljYjZlkaeenFGyPSYG1kjyetmbGJk1IWVUPCVmOpOSr0FDvBBub45TmDggIwN27d6GoqEjySAszUvcHojyxAMqdDKDSjV6NrDDz/0OB1qUHuk7ltwBmavjd/wTfu5+gpqeIkWvonaiWxcUhqlt30jWiAQbRCIPJcezdMewP3A8DZQM8GPSASdOit5UeBhz8zLAxzR3Qq3uXWUUPcu2bISA2C4MPvyYDIzq/ER3guMEhICgCbOY+gvpEyHEJMBW0aMqyuQl673uF4KQ8LOhigXldzGl6zlffFJWE/XFpaF1fEXdtmbHJiGMsGQl6Nw0ZGa7Q0x2Gxo23UJqV6DLo7u4OHR0dzJjBv0hGdSRteA1eYQUaDDKHYhsdquq05b9QoDmPmQQ7hinQHp/4gEj/NJi20kKPafTqy/OePkXinLmAlBTZAllSjlmi/vkv5sM1zhXdjLphp8tO2riyasD/NHBvPkDQti2LBSTrFpc3q1jXoslW3/qA896xaKShiOeLnCndf6hFMHChCIkAm7kPFRe5BJgKWjRl2dwE3Xe/RFhqPhZ3t8Ssjszc8l4VkYATCRno0EAJ11owY5MmpKyq+/kPQl5eEIyNZsLU9HdKc9+5cwdEa21zc3OMHj2aki4hzCurRNIaL1JPY1Iz1LNoQNkGHQVRU6Bd3uCDzMRC2PU2hn1fei2e0w8eRMb+A5A1NYXpfeYpyrpd74bkwmTMbzUfk60n04GVfd2/pwHvrkj/DGIAACAASURBVACmnYGxf7M/Pzej2CFQVsGD/eZnyC4qZ/RAReyA4BwWGgE2cx8qTnIJMBW0aMqyuQk673RDVHohlve0wnRnU5qe89V/D43HX8mZ6KpeH+eb00tSGHGIZSOeXk4oKUmEhflqGBhMoDT7hQsXEBERgVatWqFfv88taClYKE8vQurOAFJDe6EtZLQUKGjTF/2aAm3CzkNQb2hI3+hnC7xKHo7NewmCCaLblKYwt9OmZTth7jzkP3mC+r16Qn/XLlq2vlXOLsmG0xUn8sfHuh6Dg54Do/ZFbmx3MyA3Hui0CnASrhRH5D5yE9QoBJ59TMWUc/6kT26/u8BYg94F1RoVHOcMKwiwmftQCYhLgKmgRVOWzU3gvP0FYjOLsLpPE0xuT61hw4/CnP0xFtdTs9FXUxXHm7Ffg0oTflrqxCUQN/dm4PFK0KzpXmhr96Fk78iRI0hJSYGzszM6duS30KUySiKykXHyA6mi90c7SMqx++palBRoBPcvwQFMjOGr2kCjoRIVaP4jG9W9B8piY6E5fz40ZkynZetbZa9EL0x/xrfpMcIDKnLU2TwYdYiKsZx4YM/n8pIJDwBjRyranGwdRWD2xTe49y4ZLQ1VcfM3bs/U0W1AK2w2cx8qjnIJMBW0aMqyuQkc/3yOxJxirO/fFOMcmElWJ3/4hPvpuRim0wD7GjPbBIEmtCJXr6gogPtLfkvpli3/gloDaid/27dvR2FhIfr06QM7O2otlIk5C/1SkH0jApIK0tBbQ21uJsAJuH8LbudOQFkEFGifgtLx4PB7ko522j5nSMsIn9zziooQZmsHVFWh4eFDUBbiYeNneJ14fwJ73+yFvpI+Hg1+xAS07Nl4dxX4eyogJQssiwdk6rE3NzeTWCKQX1IOu43PUFrBwx/9mmJ8O2a+S8QSDM5poRFgM/eh4iSXAFNBi6Ysm5uAqNlKzSvFpoHNMNqemWR1dFA0XLPyME5PHdssDWiiIV7qRUUxeO3dmXTa3v4RlBQFvwRYWVmJDRs2kLojR46EpSV1Bo3cp7HId42DjK4itOe1Yh28/1Og2WDo6k2Mzh/wKAbet6KhoimPMRvoJffF798jZugw0j+z566Q0dNj1NeFbgvxNPYpuhp1xS4XZssrGHX0e8buzgcCTgMGbYHJj0U+HTeB+CNwPSABv18LgpSkBHxWdIaGErMXSsUfIS4CQRBgM/cRxJ8vMlwCTAUtmrJsbgLbDU+RWViGbYObY1hrZpLVwYGR8MwpwPSGmvjDXJ8mGuKlnpPjj4A3w0mnnTr4Q0ZG8Etoubm52L17N6k7bdo06AmRlGVdD0eRfyrqNVaDxnj2OThFSYH27PRHhPmkwLi5Bnr/Rq/BR87160hetRqSysqw8PVh/LZ6jxs9kFiQiHmt5mGK9RTx2sQH7YH0UKD9AqDLOvHynfO2WhAYc8IHHpEZ6GipidMTP9PnVYsn3KTijACbuQ8VnLgEmApaNGXZ3AQ2fzxBbnE5dg61wWBb6m13vxdq74BwBOQVYZ6RNpab6NJEQ7zU09Ie4/2H3yAhIY2OLiGQkBC8CxKx7idOnCADXrRoEZSVlSkHn37iPUojc6DooIsG/dln4BAlBdq1LX5Ii81Hq+6GcBhIL7aUTZuRff485G1tYXzhL8o4/0whtzQX7S+3J0WOdjmKdvrtGLUvUmNFWcC2z3cBRl0DLLqJdDrOuPgjkJpXAoctruBVAXtHtED/FnXr0EP8V7DmRMBm7kMlai4BpoIWTVk2N0HTNY9QWFbJ6B+uzn6hCC4owdJGOlhgzD4PLU34aaknJFxAWPgayMlqo317Ph2ZoCMkJARXrlwhTyOJLnCSkoInz1/mSNnhj4qMYqj0NIayMzMn+oL6L0oKtCpeFY4teImK0kp0ntAYVm3pPVjFjhuPIl9fNBg1Ejpr1ggaokByr5NeY9rTaaTsq+GvoFpPjJoBhN4HLo8iqN+BpTGAvBj5LtDqcEJMI3DiVTQ23g+BgqwU/Fd1gYKsNNNTcPbqCAJs5j5UIOUSYCpo0ZRlcxNYrnpIXlw4NLoVelnTSyq+hO3oHYKo4lKsNdXDTEMtmmiIl3p09F58itkHZaWmaNPmDiXnfX198eDBA/LklzgBpjoIBorE1V5ABQ9qIyyh0IJd7L+mQBu/4yA0DJipKSdwyM8qwbkV/AeKocvtoGUkfFthAqeItg6ozM2Fzrq1aDBiBFWofyp/8v1J7HmzB3qKeng8RMxqaB+vBF4fALStgZkejOLCGaudCPTZ/wofEvMwqKU+dg3nOgbWzlVmJyo2cx8qEXEJMBW0aMqyuQlMVzxAJa8KR8faontTZk5rbb2CkVhajj8tGmKCvgZNNMRLPTRsNRITL0JdzQktWpym5LyrqytevXoFfX19TJ06lZIuIVxZWI7kDXyaMM0ZzSFnzC71ligp0GKDM3FvfxAZ29Q9TpCtJ/wpU3lqGiKdnUlbRhcvQqFVS8pY/0xhkdsiPIl9gi6GXbC7I7+mW2zG8U5AYgDQZhrQa7vYuM05Wj0IRKblo8uul+TkZye1gbOFZvU4ws1aKxBgM/ehAhiXAFNBi6YsW5uAOAlrtPwB6e2pCXboZEWvscCXsJt4vEdWeSX2WBlghK46TTTES/3d+5lIT38CHZ2BaNpkByXnb926hbdv38LKygojhDiVLEssQNr+QHJOnWVtIK3K7k3sgPu34XbuuEgo0N4+i4Pn9Ugoqclh/GZ6HKMFr14hfiq/RMHC3w9SSvT4hL9d5J43eiKhIAFzW87F1ObUH2QobRomhcsKgT8NAV4FMOQ00GwQk9Y5W7UQgR2Pw3DgRSTJ+uC9vBOkpaiXbdVCWLiQhESArdyHqntcAkwVMRrybG2C8koezFc+ZPzpvZH7OxTzeDjSxAgDtAVnQaABWY1R9Q8YitzcNzA0nApzs2WU/Dp//jyioqLQunVr9O7dm5IuIVwcnIHM8yGAJKC/oT0kpCQo26CjIEoKtBfnQ/DRMxmGTdTQdy6916yZJ04g7X/tnQd4FMX7x79A6L2F3nvvvTcRFUEQRCkiKEUFRQSk2WgKgnSUpiDlJ1XpvYQOoYXeIdTQCSUh9f9891z+x3FJdm/vNne5d56Hx3g3Mzvzmbnd777zzju/jEXS3LlReNNGI11+paz1BrjfGv+GWrmMiXWnNi6uyi5uA+a2sOTqewZI65wVobguK997JgEaUOqM3oprD0LwUa38+K65+VFnPJOctDomAmZpH70jIAJYLzED+c2aBCFhkSjxrSVI/4KPq6FmYePuCrwp5tx2FNFcEitTAE2zmLsMbwC7U4ru3tMAISGBKFx4IPLl1Rf+aurUqbh9+zYaNmyIunUtx+jqSY93XcejlReRJH1y5BhofigiV4ZAWzr6IG5dfIRyjfKgdhvtsZXt8bverz+CV65EmoYNkWfqFD2I48y79+ZefLLBYvXd/t52ZEqRKc4ybpNh6yhg+09AxgLAF0fcplnSEPck4H/5Pt79bY/SuH8/q4VyeWTDpHuOlOe0yizto5eICGC9xAzkN2sS8PSeMt9vUFq6qHsNVC1g/GH9PCoK+bYHKHX+Xa4Q6mXSH8rLALp4L7ptezlERj5ByZJjkSN7S13t+fnnnxESEoIWLVqgQgX9fqkP11zEE7/rSJYvHXx7Wk6jMzO5KgQaX6pm9d2B588i0KBDcZSsbezQiostWuL5mTPI3LMHfL/4wqmIZh+fjV8P/orsqbNj47vOtS47taH2KpvTHLjkB5RvD7Sc6vLLyQU8m8Dg5ccwf18gCmZJjc196zk9lrZn05HWO0LALO2jt20igPUSM5DfrEnw4GkYKgyzPKSX9qyJSvmMuys8Co9AsZ3HlTr/rVAY1TI417/SAFaXF42MDMW27ZZlwPLl5yBzJkssWC0pPDwcI0ZYTk7r0KEDChfWH+f23oJTCAm4i5TlsiLz+8W1XNZpeVwZAu3po+f4c8Aupa2tvq6IHIUdtzRFh4XhNI9ADg9HrvG/It3rrzuNASvqt70f1l1eh4Z5GmJCwwlOrdullUWEWfx/I0KAtycDFTu69HJSuWcTCIuIQtWRm/DwWTi+alIUvRsZW5XxbBrSemcRMEv76G2vCGC9xAzkN2sS3H4ciqojNistXfF5LZTN7biwULt763k4yu8+ofzv+spFUS5tKgMkPKtoSMg17N5jiS5QtepqpE2jXYTev38fEydOVMr27NkT2bLp35B4e+oRhAU+Rtp6uZG+2X+HGZiE0DoEWuexU5E5d16nXfna6fv4d7xlSb7r2DpIkTqpw3WHnjmLSy0sfq4F16xG8oIFHa7LXsE3l72JwMeB+Lz85+herrtT63ZpZVcPALMaWy7R6xCQuZBLLyeVezaBjSeD8Mlcf6UT2/vVR77MqT27Q9J6tyBglvbR21kRwHqJGchv1iS4+SgENUZtUVq6undtlMpp3F/3cshzVN97ynJjrFocxVKnMEDCs4o+enQE/gdbK42uXXsfkifT7lN95coV/PGHJWxa//79kSqV/heHmyP3ITI4DBlaFEKaGsbcBPSSd2UItGPbrsHvf2eRMl0ydBmt3apurw+PVq7EjX79kSh5chQ76I9EPo6HU7Ot/3HYY9RcaDn1bWqjqaiTu45ejPGXf9cEYOO3QGpf4OuzQCJzN1DGX8flyo4Q+GzBIawOuImKeTNg2acetNHTkc5KGdMImKV99HZIBLBeYgbymzUJrt5/puziZdrQpy6KZjPur3vqSQgaHDij1Lm/egnkTWluKC4D2A0XvXNnEwKO0eqXGA0bnEaiREk013n8+HEsWbIESZIkwZAhQ3T700VHRuH6kF3g7sPMnUoiZUlzw88dXP0Pts2d6ZIQaNsXnsHx7deRq1gGtOxTUTNTexlvjx2LezNmIkWpUiiwdImhumwL77+5H103dFU+3tp2K7Kk1P4C5NSGOFLZgnbA2bVAyRZA27mO1CBlvIQA945UHr5JOUDpxxal0KlGfi/puXTT1QTM0j56+yECWC8xA/nNmgSX7j5Fg1+2KS3d0rceCmY17q97OPgZmh08q9R5rFYpZE3m+HK1AYTxUvT69f/h9JnBSJo0M+rW2a+rDXv27MH69euRIUMGfPnll7rKMnPE/VDcGn1AKefbuwKS5TQ+lnoa4coQaP+MO4TrZx+iTL1cqPt+MT3NeiVvYLdueOq3A+lbtULOkRafa2elP4//ibEHx8I3lS82t7G4FnlEiooCRhcAQh8CzUYD1TzIdcMjACesRi72v4p+SwLgkzgR9g1qhMxpvMfIkbBG0v16Y5b20dtzEcB6iRnIb9YksD7Fx69fA+TNrH/Z3babex4+wTuHzysfn6tTBml9tFtBDSBzi6KXLk3GxUu/InXqoqhezRJfWWvasGEDdu/ejTx58qBrV4sVUU96fvER7ky3RN/I+W11JE5l7ouHGgKtXJNmaPzxZ3qaHmfe2f13IiQ4DHXbFUWZ+rnjzB9bhnP16iMiKAi+3wxA5s6dDdVlW7j/9v5Ye3kt6uepj0kNJzm1bpdWdvsUMLW65RLddwA5yrr0clK5ZxNoP3Mvdp2/h4bFfTG7cxXP7oy03q0ImKV99HZaBLBeYgbymzUJTt0MRrMJO5SW7v6mIXJmSGmg1ZaiW+8F4/2Ai8rfV+uVQ9LE3uNLeObsD7h2bS4yZqyJihX+0sVy6dKlOHbsGEqWLIm2bdvqKsvMzw7fxv2/zyBRssTI+UNN3S4Uui9oU2DG510RfCcI9Tp0QeXmzjtBLPRJOGZ9bZmjLfpUQO5ijkcqiXjwAOdqWHx08/4xG6lr1DDa7ZfKN1/eHJeDL+PT8p+iZ7meTq3bpZUdmAWs/gpIng4YcBlI7D0vrS7lmgArDwoORfVRmxEdDUx8vwLeLmfuXoMEiFS6ZEXALO2jF7oIYL3EDOQ3axIcv/4Ib03aqbR0/6BG8E1nfMPa2jsP8dHxy+AhZNfrGzuxywDCeCl67Hgv3L69BtmyvY3SpX7V1YY///wTly9fRvXq1fG6A6G5grdeRfD6y/DxTYnsX1XWdW2jmSPCwzGxY2tER0ehRb+hKFy5mtEqX5S/cf4hlv9ySPn/j0bXRqp0yRyu++m+/Qj88EOlfJHdu+CTyXjca7UxT8KeoMZCi6Ce0mgK6ubWf5CJwx0zWnDpx8CxxUDhJkAH5/pFG22alHcvAjP8LmLEmlNInSwJ/Ic0Qcpk8rLkXiPk2a0xS/vopSQCWC8xA/nNmgSHAx/gnam7lZYeGtoEmVI7Li7U7i4PeoCeJ68gTZLEOF/Xu5ZSDx76AA8f7kOePF1QtMhgXTNg0qRJuHfvHpo0aYJatfTvqn6w/Bye7ruF5EUzImuX0rqubTTzvetX8edXFotn57HTkDl3HqNVvih/Ysd1bJt/BslT+Sgh0BIZiE5w/695CBoxAkmyZkHRHRarsrPSgVsH0GV9F6U6j9sAN64UEHwNaPQtUKevs5BIPQmQwJsTd+DEjWC0qpgL49p6l4EjAQ6n23XJLO2jt+MigPUSM5DfrElgfZRlwPevIV0K436jC27ew1enryJLUh8cr22uEDOA3ClF9+x9Dc+eXUChQv2RP5++jUQjR45EWFgYWrVqhbJl9b843P3zBEJP30fqKtmRsbW5QekvHNyHf0YPU0JnfTF3KXySGX+RUgdk56JzOLrlKnIUSo9W/SoZGqebQ4fi4eIlSF2zJvLOnmWoLtvCc07MwS/+v8A3pS82t/WgDXAPA4HxZSzd+WgdkM+5biFOhSyVxSsB6z0jf3WtijpFssZre+TiCY+AWdpHLzkRwHqJGchv1iTYc+Ee3p+xV2npyR+bIlUy4zFRZ1+7g0HnriN3iqTwr2E5Fc1b0na/ioiIeIQSJX5Gzhzvau728+fPMWrUKCX/hx9+iAIF9B9iETT+IMJvPUO6xnmRrnE+zdd2RkY1BFq6rL74ZPJsZ1T5oo6VE48g8OR95fhjHoNsJF1q+x5CAwKQqXNnZPtmgJGqXik7wG8A1lxag/q562NSIw/aAHf0b2B5NyBJcuCbQCCpcTcop4KVytyGwJj1pzFl6wVkTZscewc2QhIv2t/hNoOQwBtilvbRi1EEsF5iBvKbNQl2nLuDjrMs4brODm+GZD6JDbTaUnRK4G0Mu3ADRVIlx45qJQzX5ykVREWFYes2S3/LlZuFLJnra2763bt3MXnyZCX/559/jixZ9MePvf79bkSHRiJjm6JIXUn/KXKaG2sn46aZU3F04xrkLVMebYYMN1LVK2XnDNyFJw+eo9a7hVG+seOny0VHReFMpcqIDglBjp9GIUPLlk5t54sNcOU+Rc/yHrQBbuUXwME/gbw1gS76Ipc4FaBU5tYEoqKilZjx1x+GoGvtAhj6Vkm3bq80zjMJmKV99NIRAayXmIH8Zk2CrWdu46M/LLFjL458A4md8EY/9tItjLl8C2XSpMTGKsZithpAaHrR0NCb2LXbckpZlSr/Il1a7e4fly5dwpw5c5SyAwcORPLk+uJqRoVG4Mb3e5TyWT4pgxSFjB9prQfg4uFDEHjsCJwdAi0sNAIzvvRTmvJWr3LIV8rxwz3CrlzBhaavK3UVWL4MKUo47+XsafhT1FhQA9GIxuSGk1Evj+U4bI9Ik6sCd89YfH/pAyxJCNghcODyfbT5zXKPWfl5bZTJbfzUUAEtBGwJmKV99JIXAayXmIH8Zk0C9Tx36t6Lo9400OL/Lzriwg1MCryNqulTY0VFc31RndIBBysJfnwcBw60UErXqrULKZJn11xTQEAAli1bhmTJkmHQoEGay6kZw4OeIuhXS6SE7F9Xhk8W4+Hs9DTiRQi0jl1R+a139BSNNW/Q5WAs+clfydNpZE2kzeT48nzwhg243vsLIEkSFDt8CImd6Kd8MOggOq+zxBTe0mYLsqbyEN/Ip3eBMYUsY9B+KVCksdPGTipKWAQGLT+GBfsCUShramz6qp6hzagJi4z0xpkEzNI+etssAlgvMQP5zZoE647fRI95hxTXB7pAOCMNPXcNM67dRd2MabCofGFnVOkRddy9tw1Hj1oOsGhQ/zQSJ9a+oXDXrl3YuHEjMmfOjF69eunub8iZ+7j3xwmlXK5htZAoqXFXFq2NcGUItNN7bmLznFNImjwJPhlf19BD986kybg7ZQqSFS6EQqtWae2epnx/nfwLow+MVo4+ZgQIj0mnVgJ/dwASJQYGXAFSpPOYpktDzSMQFhGFKiM24VFIOPo2KYpejbzHsGEeZbkSCZilffTSFgGsl5iB/GZNgpVHb6DXwsNIlSwJTv5oWR42mr4+fRXzbt7Da5nTYW7Zgkar85jyN24uwalTA+DjkwH16h7U1e5169Zh7969yJ8/Pzo7cDrZk3038XD5eSROkxQ5h/x3opeuFjie2ZUh0PYsP49D6wPhmy8t2gw0duLUtV698HjjJqR74w3kGjfW8Q7bKTlwx0CsurhKif3LGMAek9YNAvZOAbKXBXo4NyycxzCQhsZJYMOJW+j2l+We5qwTQ+O8qGTwSgJmaR+9cEUA6yVmIL9Zk2D54Wvo8/dRpEvhg4Dvmxpo8f8X/fzkFSwJeoC3fTNgeqn8TqnTEyq5fOV3XLgwGqlSFUaN6ut1NXnx4sU4ceIEypQpg9atW+sqy8yP1l/G461XkTR3GmT7vILu8kYKuDIE2uqpAbgccBfFqmdH487GNt2cb9oU4VcCkbVPH2Tp3s1Il18p2+KfFrj46CJ6lOuBz8o79xhopzbUtrLp9YEbh4Gq3YE3Rrv0UlK55xL4bP4hrD52E5XyZcTSnpaTFCUJAVcQMEv76G27CGC9xAzkN2sSLPa/in5LApQDMHgQhjNS1+OXsPrOI7TNnhETS5gbjssZ7Xe0jrPnRuDq1dnIkKEaKlVcoKua2bNnIzAwEDVr1sRrr72mqywz8whkHoWcslRmZO5oTCjqvbgrQ6DNG7oHj+6EoMY7hVCxqeNzKerZMyUCBM9vzf3bNKStrz1CR1w8noU/Q/UF1ZUNcBMbTESDvA3iKuIe3z9/AvyUF4iOBNr8CZRynu+2e3RQWuEMAsGh4ag8fBPoBjGsZWl0rO7479AZ7ZE6EjYBs7SPXooigPUSM5DfrEmwcH8gBi47Bt+0ybF/sHM2wLQ/ehGb7wejU87MGF3MeSeCGcBpStHjJ/ogKGgFfH3fQJnS+uLAjh8/Hg8fPkTTpk1Ro4b+gwhu/x6AsEuPkKZWTmRo/t+mJlN6DbwIgVa6HNoMHeG0q0aERWL6F9upWfFGzzIoUM7xjWUhR4/i8nvtlLYV3rIZSXPmdFo7DwUdwofrLMcrb3p3E7KlNjcEncMdubAF+Os/0dv3LJDWQ9rtcIeloCMEFvlfRf8lAfBJnEh5RjjjtFBH2iFlvIOAWdpHL00RwHqJGchv1iT4a+8VDP3nOHJlSIld3zQ00OL/L9r68HnsevgE3fNkxQ+FczmlTk+o5NDhjnjwYDdy5+6EYkW/09zk6OhoDB8+HJGRkWjTpg1KldJ/eMjN0QcQeT8U6d8siLR1zGXuqhBod689xt/DLSH62v9YHRl8U2lmapvxwaJFuPXtd0icNi2K7t9naDOdbd3zTs7Dzwd+RuYUmZUNcEaOana4g44U3DIC8BsNZCoI9D7sSA1SxgsIfDBjL3ZfuIfGJXwx80NjfvhegEu6aJCAWdpHbzNFAOslZiC/WZPgj12X8MPKk8ibKRX8+jtn6fbNg2dxMPgZvsyXDd8UzGGAgmcV3buvGZ4+PYuCBb9Cgfza/UCfPXuG0aMt/pddunRB3rz6DnuIjorG9aG7gMhoZGpfHKnKOG4pdYS4q0KgnTsQhA2zTiCJT2J0m1jPUIzqW8OG48H8+UhZuRLyz5vnSDdjLDN452CsuLACtXPVxrTG05xat0sr+/Mt4PIOoHwHoKUHbdxzKRSp3JrArUehqPHTZmUVZvIHFfBWWeetnAhpIWCPgFnaRy99EcB6iRnIb9YkmOF3ESPWnELBLKmx5Wvn+EU2OnAaJ56E4psC2fFlfu2xcA3gcouifjuqIDz8PooXH4lcOd/T3KagoCBMm2YRTl988QUyZsyouSwzRgaH4ebIfUoZ38/KI1metLrKG8nsyhBo+1ZchP+ay8icKw3aDa1qpJm40rETnh04gIwffIDs3w41VJdt4Xf+fQfnH55Ht7Ld0KuC/hB2Tm2M1soiwiz+vxEhQIupQIX2WktKPi8iMN3vAkauOY00yX3gP6QxUiRN4kW9l67GBwGztI/evokA1kvMQH6zJsG0bRfw87rTKJotDTb0cc7pVbX2nsKFkOf4vlBO9Mjra4CC5xSNjo7Elq089S4aZctOR9YsjTQ3/vz585j3n1Vy8ODBSJpUe/xgXuR5YDDuTD2qXC/H4GpIkjaZ5msbzejKEGjrph/DhUN3ULiyL5p+rP1UPds+0cXkbPUaiHr0CNl/+AEZ32trtNsvynMDXI2FNRAVHYXxDcajUV7t4+60RjhS0dUDwKz/fP7p/kA3CElCwIZAswk7cOpmMN6tlBu/tCknfISAywmYpX30dkQEsF5iBvKbNQkmbT6HsRvPokSOdFj7RR0DLf7/ohV3n8CN5+H4qWhudM6VxSl1unslz8PuYufOakozK1dehvTptD8sDh8+jH///RcpU6bEgAEDdHf1WcAd3F9wGkiSyHIIhhOOs9baCFeGQFvwwz48uPkUVZsXQJU3C2ht0iv5wm/dwvn6FveefAsXIFUF54WJO3L7CDqu7ajUvfHdjcie2kNWPHZNADZ+C6TJDvQ9DSRK5DBfKZgwCZy59RhNx1uOIZ/XtRpqF/GOe3nCHE3P6ZVZ2kcvERHAeokZyG/WJPh141lM2HwOZXOnx4rPaxto8f8XLbnzGO6HR2J88TxolyOzU+p090oePzmN/fstR0nXrOGHlCm1GNjukAAAIABJREFUb0Tz8/PDli1b4Ovri08//VR3Vx/vuIZHqy8hSaYUyNHf3E0qrgqBFhkZhem9tiMqKhpNPymNwpUcX0l4sn07rnbvoXAt6u+PJGlS62YcU4H5p+bjp/0/IVOKTNjWdpvnbIBb0A44u9YS+owh0CQJARsCXBnkCiEjBO0Z2AhJTHyxlsHwXgJmaR+9hEUA6yVmIL9Zk2DM+tOYsvUCKuTNgOWf1jLQ4v8vWmB7AEKiovBbyXxomU2fP6tTGhAPldy7vxNHjlhCYdWvdwJJkqTQ3IrVq1fjwIEDKFSoEDp2tFgT9aSHKy/gya4bSF4wPbJ2K6unqOG8L0KglSmPNkOGG65PreDBradY8L3Fr7ndt1WROWcah+u+O2MG7owdh6R58qDwxg0O12OvoLoBrlbOWvityW9OrdtllUVFAaMLAKEPgWZjgGrOPRTEZe2Wik0jwBfPOqO34vrDEHxcuwCGvGVubHHTOioXcjsCZmkfvR0XAayXmIH8Zk2CUWtO4Xe/i6iSPyMW9zB+wg/9LXNtO4ooAHPKFEDTLOkNUPCcojdv/YOTJ/siSZI0qF/P4o+rNS1cuBBnzpxBuXLl8M47+g8juPvXSYSeuIdUFXyR6T36IZuXXBUC7cLh21j3+3HFnaP7xHpKJAhH0/Wv+yF41SqkadQIeaZMdrQau+XUDXCflPkEvSv2dmrdLqss6CQw7b9Y0z12AtnLuOxSUrFnEth38R7em75XafyqXrVROpd33Mc9c7QSVqvN0j56qYkA1kvMQH6zJsGwVScxa+cl1CiYGQu7VTfQYkvR51FRyLc9QPn773KFUC+TeREJDDfeQAVXAmfi/PlRSJkyH2rW2KKrpunTp+PGjRuoU6cOGjXSv4kqaPJhhF97grQN8iB9U3OPnnZVCDRGf2AUiAzZUqH9D8bm5cXmb+P5uXPI8mlPZO3tPJEaEhGinADHDXC/1v8VjfM55yAZXZPHkcwHZgKr+wLJ0wMDLgGJZWe/IxgTchkejsRDkgr7psHGPnU9x7UnIQ+Kl/TNLO2jF6cIYL3EDOQ3axJ89+9xzNlzBXWKZMFfXS2buIykR+ERKLbzuFLFigqFUTWD40vXRtphdtlz539CYOAMpE9fCZUrLdJ1+bFjx+Lx48d44403ULWq/nBfN4bvRdSTcGR4pzDSVDMv7rJ1CLSW/YeiUCXj80cFx/i/jANcsHxWNOvhuIUyKiwMZypWAiIikGv8eKR7vamusYkt89E7R9FhTQcly/rW65EzjYfESF3SFTi+BCjyGtB+sdN4SEUJg8DziEhUGb4JwaER6Ne0GD5rUDhhdEx64REEzNI+emGIANZLzEB+sybB4OXHMH9fIBoW98XszsY3UAU9D0e53SeUnm+oXBRl0zp+epcBfKYXPXHya9y6tRxZszZF2TJTNV8/KioKw4YNA11H3nvvPZQoUUJzWWaMDo+yHIIBIMtHpZCiWCZd5Y1kvnftKv7s21OpovPYacic23nHXv89Yj/uXn2CSs3yoXoLx492Dj19GpdaWtxKCq5dg+QFHI8mYctq4emFGLlvJDIkzwC/9/w8w0rGEw3GlQQe3wAafQfU+crIFJCyCZDA+hO30P2vg0rPdvRvgDyZvOMengCH0iO7ZJb20QtHBLBeYgbymzUJBiwJwN/+V9GkZDbM6FTZQIstRS+HPEf1vaeUv/2qFkfR1No3gxm+eDxWcOTIR7h33w+5crVH8WI/am4JLb+0ADN9/PHHyJ07t+ayzBhxNwS3fvFXymTrUxFJszkvwkFcDTnvvw//jhmGRIkSo/dfS+GjM35xTPVzA870L7YjMjwKjT8qiWLVHA8t9mjFCtzoPwCJUqRAsYP+SJTEecv9Q3cNxT/n/0HNnDXxe5Pf48LlHt8/uAxM+C9EX5f1QF5j7iXu0SlphTMJ9Jx3EGuP33LavhBntk3qSvgEzNI+ekmKANZLzEB+sybBV4uOYNmh63ijTHZMbV/JQIstRU89CUGDA2eUv/dXL4G8KZMbrtMTKti//208fnICBQp8gYIFtPuZ0veXPsBMffr0Qfr0+jabhJ5/iLszjynlc/5QA4mT+5iGy3/Vcmz/axbSZc2GTybPctp1H90Jwbyhe5T62g6qgqx5HfcjDxozBvdnzUaK0qVRYIlzl/tbr2iNsw/Oomvprviy0pdO679LKzqyEPinB5AkOTDwKuDjHb9PlzJNQJU/CglX3B/CIqMwvGVpdKieLwH1TrriCQTM0j56WYgA1kvMQH6zJsEX/zuMf4/cQPNyOTHpfeMHBBwOfoZmB88qPT9WqxSyJtN3qpkBZPFadOfOmngeFoRixYYhd64PNLeF0R8YBYJp6NChSKLTQvn0YBAeLD6LRCl8kOv7/3b2a766sYybZk7B0Y1rkdfJIdAuB9zF6qkBQCKg24R6SJrMcatt4Mef4OnOnUjfuhVyjhhhrMNWpUMjQpUNcJHRkRhbbyxey/+a0+p2aUUregGH5gL5agEfrXHppaRyzyPw94FADFh6DEmTJML+QY2RMbV5p0p6Hi1psSsImKV99LZdBLBeYgbymzUJPpt/CKuP3USrCrkw7r3yBlpsKbrn4RO8c/i88vf5OmWQxsdx8WK4MSZVEB0dha3bSiA6OgJlykyFb1btG638/f2xatUqpE6dGv369dPd4uDNgQjeeAVJs6dGti8r6i5vpMDiYYMRePwoyjV5A40/1n+AR0zXPrThCvYsu4B0WVKg43BjofnO1amLiDt3kG3QQGTq1MlId18qG3AnAO3XtFc+W9tqLXKn1ee64rSG6K1oUmXg3jmgztdAo6F6S0v+BE6g3fQ92HvxPhqXyIaZHxp3iUvguKR7LiBglvbR23QRwHqJGchv1iTo/pc/1p8IQptKuTHGCWe9b70XjPcDLio9v1avHHy84PSg8PAH8NtheVhUqvg3MmTQ/uDYunUrtm/fjuzZs6NHD8tpZXrSg6Xn8PTALaQonglZOpfSU9Rw3hmfd0Hwnduo17ErKr+lP35xTA3YPOckTu+5hXylM+Otz7UfKW1bX8SDBzhXwyKg8/75B1JXd56/6/9O/w8j9o1AumTpsLPdTs/YAPfkDvDLfzv6OywFCntI2DbDM1Uq0ELgxsMQ1Pp5C7hPcvIHFfBWWQ+JaqKlc5LHYwiYpX30AhEBrJeYgfxmTYKufx7A5tO38X7VvBjVyvFwU2pX19x5iC7HL8MnEXCtvnGLsgGEphV98vQc9u17XblejeqbkSqV9li8K1aswKFDh1CkSBG0b2+xKOpJd2Yfx/OzD5C6eg5kbGleuKKIsDBM6NQafFo6OwTakp/9EXQpGOWb5EWt1o736enefQjs3FnBWWTPbvhkdN6phN/t/g7Lzi1D9RzVMeO1GXqGLP7ynlwBLOoIJEoMDLgCpEgXf22RK7sdgd+2X8BPa08jTXIf+A9pjBRJE/7qndsNgjQIZmkfvahFAOslZiC/WZOg0+z98Dt7B51q5MOPLUobaLGl6LKgB/j05BWkSZIY5+uaeyyv4cY7WMH9B3tw+LAlHmy9ukfh46M99vH8+fNx7tw5VKpUCc2bN9fdglvj/BFxOwTpXs+PdPWdF4Ysroa8FAJt3DRkzuWcazMc3Iw+fggPjUTDTsVRoqbjVqj7c+ciaOQo+GTNiiI7/OLqkq7v26xsg9P3T6NL6S7oU6mPrrLxlnndQGDvVCBHOaC7c3nEW5/kwk4j8Pp4P5y+9dhpq4FOa5hU5FUEzNI+eqGKANZLzEB+syZB+5l7sev8PXxUKz++a258CX3BjXv46sxVZEnqg+O1jQtqAwhNK3oraCVOnPgSiROnQP16x3Uth//222+4desW6tevr/zTkygWb3y3G9FhUcoRyDwK2azkqhBoTx6EYs7A3Uo3Wg+ohOwF9EXFsO7/jcGD8WjpMqSuXRt5ZzrPSvs88jmqz6+OiOgI/FLvFzTNr93n26zxsXud3+sBN48A1XoCzX6K16bIxd2LwKmbwWg2YYfSqPkfV0Otwlncq4HSGq8hYJb20QtUBLBeYgbymzUJ2v6+B/sv3Ue3ugUx6A19hzDY696sa3cw+Nx15E6RFP41jAtqAwhNKxp49Q+cOzccKVLkRq2a23Vdd8yYMXj69Kli/aUVWE+KehaOGz/uVYpk7V4WyQ2IRT3XZV5XhUC7evI+Vkw8ojTn41/rInlKx8O6XWrTFqHHjiFT1y7I5sAGw5iYHL97HO+vfl/5es07a5AnnXOs33rHQFf+54+Bn/IC0VFA27lAyRa6ikvmhE1g1NpT+H37RWRLlxy7v2mEJF6wdyNhj6jn9s4s7aOXkAhgvcQM5DdrErSethsHrzzAp/ULof/rxQ202FJ0SuBtDLtwA0VSJceOasYFteEGmVDBhQu/4PKVaUiXrjyqVF6q+YqRkZHKKXBMH3zwAYoWLaq5LDOG3XiC2xMPK2WyD6gCn4zmHTqihkDLV7YC3h1s6YMz0tHNV7Fz8TmkzpAcnX+q5XCV0ZGROFOpMqJDQ5Fz9M9I//bbDtdlW3DRmUUYtncY0iZLi13tdumy+DutEXorOr8ZmNfKUurrc0Aa81YL9DZV8ptLgAfPcPPbzUeh+KROAQx+s6S5DZCrCQErAmZpH73QRQDrJWYgv1mToMXknTh67RF6NyyMr14rZqDFlqJjL93CmMu3UDZNSmyoYrw+ww0yoYJTpwbixs1FyJKlMcqV1X4i2KNHj/Drr78qLezevTty5Mihq7UhJ+/h3tyTSrzcXMNrIVGSxLrKG8m8ePgQBB474vQQaFvnn8bJHTeQp0RGvP2F43Gpn1+6hIvN3lC6WODff5CimPPm4ve7v8fSc0tRLXs1zGw60whG88puGQ74jQEyFwZ6WY65lSQESGDPhXt4f4ZlJWl179ooldNxtyMhKgSMEjBL++htpwhgvcQM5DdrErw5cQdO3AjGV02KonejIgZabCk64sINTAq8jarpU2NFReP1GW6QCRUcPfoJ7t7bgpw530OJ4iM1X/Hq1auYNctygtrXX3+NNGm0b55jmSd7buDhvxeQJF0y5BhUTfN1nZFRDYFWv9PHqPRmS2dUqdSx7JeDuHn+Eco2yI067+mziFs3Inj9Blz/4gvAxwfFDx1EomTOC+jfdmVbnLp/Ch+V+ghfVf7KaX13aUV/vAlc2QlU6Ai0mOzSS0nlnkXgm6UB+N+BqyjimwYb+tT1jBUNz0IsrdVBwCzto6NJSlYRwHqJGchv1iRo+qsfzgQ9Rr+mxfBZA8dDTqldHXLuGmZeu4u6GdNgUXnj9RlAaFrRAwfeQfDjAOTP/xkKFdQuiE6ePIlFixYhceLEGDJkiPJfPenh2kt4sv0akuVNC99PzQs5FxEejgkdW/0XAu1bFKpUVU+zY807q+8OhD4NR70PiqF03VwO13tn4iTcnToVyYsUQcGVKxyux7ZgWGQYqi2ohoioCIypOwavF7CEv3PrFPEcGJUHiHwOtJwGlNd+UqFb90saZ5hAeGQUKg/fBB6B7KxngOFGSQVeTcAs7aMXsghgvcQM5DdrEmw/ewcPn4WhRI50KJotrYEWW4oef/wM5589R6akPqibyXh9hhtkQgUPH/ojJPQa0qQugrRptW/8e/z4sRLzMDQ0FBUq6F/uD7/zDOE3nyKRT2KkLJnZhJ5aLhEZEYHrp0/gwc0bKFylOlJncE58XUa1uHUxGA9uPkXOohmQwTeVw30Kv3ULIUcDFJGe7nXnRWmg8OUmuJP3TqJxvsbwTeUBvrRRUcCtACBwj2XzWzrHQ8s5PCBS0G0JXH8YghVHbuDt8jmRK0NKt22nNMw7CJilffTS9HgBzHirjLu6ceNGXLhwARQg+fLlQ+PGjTFw4MBXfDADAgIwcuRI7N27VwlV5evrq+zU55G1NWu+ekQr8w8ePBg7d+5EWFgYypQpg/79+6NVq/82n+gg7q6TQEcXJKsQEAJCQAgIASEgBDQTcFft4/EC+JtvvsHEiRPx5ptvolatWkiVKpUibufOnYv06dNj165dKF7cEglh//79qFu3LjJmzIhu3bohb968uHz5MqZPn467d+9i7dq1eO21114M6tGjR1G7dm0kT54cX375JbJmzYp58+YpYnjmzJno2rWr5gnAjO46CXR1QjILASEgBISAEBACQkAjAXfVPh4vgP39/VGoUCFF1Fonilruwm/Tpo3ik8nUoUMHxVpMqy4tuWo6ePAgKleujHfffReLFy9+8TnFMsUuhTO/Z4qIiFAsxWfOnMGVK1eQIUMGjVNABLBmUJJRCAgBISAEhIAQSBAERACbPIzBwcGKBbhYsWI4ffq0cnUeTLBq1Srcu3cPmTJletGioKAgZM+eHZ06dcKcOXOUz2kZLlCggHKS19atW19qPa3AHTt2xB9//IHOnTtr7pm7TgLNHZCMQkAICAEhIASEgBDQQcBdtY/HW4BjGoNTp06hZMmSqFOnDvz8/JRskyZNQu/evdG0aVP88MMPyJMnj2LFHTp0KA4dOoTt27e/sAz//fffaNeuHQYNGoQRI0a8dJmLFy8qVueePXti6tSpmqeBu04CzR2QjEJACAgBISAEhIAQ0EHAXbVPghXArVu3xrJly16y0vKULm6Mo2jlUbVqKlWqlJLX+tSusWPHKnFcmZdC1zpxMxz9gmlRXrEi5nBMtELzn5pu3ryJqlWrgrFic+fOrWP6SFYhIASEgBAQAkJACHgeARHAJo4ZozwwckPLli0VYZsoUaIXV58yZQoWLlyofEfBe/78eYwZMwYpU6bE5s2bFbcHJh5n++233yqHGnTp0uWV1jO+a8OGDbFp06YYe/b9998rlmbbJALYxMkglxICQkAICAEhIATijYAIYJPQT5gwQYnYQN/d1atXK1Eh1MSIEbTsHj58GKVLl37xOQ8vKF++PN566y1FMDOJBdikAZPLCAEhIASEgBAQAgmWgAhgE4Z23Lhx6Nu3Lxo1aqS4JliL3/DwcOVYWlp9jx079kpreGgB/YHv37+vfCc+wCYMmFxCCAgBISAEhIAQSNAERAC7eHhHjx6NAQMG4PXXX8fy5cuRIkWKl65I/9ucOXOiRIkSoMXXNtEiTAHMgzSYLl26hIIFC6JBgwbYsmXLS9klCoSLB1OqFwJCQAgIASEgBBIEARHALhzGUaNGKdEa6MKwZMkSZYOabYqKikK2bNkUCy8Px6hevfqLLDw4g4doUOxa+/TyEIzdu3fjwIEDymlxTGocYIZWo2C2jT8cWzfddRK4cGikaiEgBISAEBACQsCLCbir9vH4KBCM0vDZZ58p4pZCOGnSpC9NM7o9cMMbk5qXn/Xo0QNFihQBj1KeNm2aImwZ77dGjRovyjM0Gg/DoDW5T58+yJIli3KQxo4dO/D7778rp8npSe46CfT0QfIKASEgBISAEBACQkArAXfVPh4vgHkQhXp4hb3ByJcvn3KohZr++ecfJR4wxS3dHXggBmMFDxkyBPQDtk08DpkRJXgiHMOf8QS5fv36KafG6U3uOgn09kPyCwEhIASEgBAQAkJACwF31T4eL4C1wHeXPO46CdyFj7RDCAgBISAEhIAQSFgE3FX7iAA2cZ656yQwEYFcSggIASEgBISAEPAiAu6qfUQAmzgJ3XUSmIhALiUEhIAQEAJCQAh4EQF31T4igE2chPRF5klz+/fvR44cOUy8slxKCAgBISAEhIAQEALmE2AY2qpVqyrhZfPnz29+A2K4oghgE4eC4dQ4CSQJASEgBISAEBACQsCbCND4V6VKFbfpsghgE4ciNDRUOYUua9as8PHxeXFl9e1ILMMvD4ZweXVyChP7P1jhInNF661c5or8hmSuaCXgnLnCMLN37txRomjZHlJmrCXGSosANsbPKaXd1T/GKZ0zUIlweRWeMLE/oYSLzBWttxqZK/IbkrmilUDCnisigI3NA6eUlhtywv6ROWWS/FeJzBWZK1rnk8wVmSta5wrzyXyRl0it8yWhzBURwFpH3IX5EspkcjYi4SI3ZK1zSuaKzBWZK1oJyIuBVlJyX0nYc0UEsNZfggvzBQcHY9y4cfjqq6+QLl06F17Js6oWLq+OlzCxP4eFi8wVrXc3mSvyG5K5opVAwp4rIoCNzQMpLQSEgBAQAkJACAgBIeBhBEQAe9iASXOFgBAQAkJACAgBISAEjBEQAWyMn5QWAkJACAgBISAEhIAQ8DACIoA9bMCkuUJACAgBISAEhIAQEALGCIgANsZPSgsBISAEhIAQEAJCQAh4GAERwB42YNJcISAEhIAQEAJCQAgIAWMERADb4bds2TKMHj1aObY4WbJkqF27NkaMGIGyZctqon3v3j0MGTIE//77L/h3/vz50aVLF/Tt2/elI5DVyvz8/PD999/D398f0dHRylnZ/P+6deu+cj0eKTh27FjMnj0bly9fRubMmdGiRQsMHz5c+ds2XblyBQMHDsTGjRvx5MkTFC1aFJ9//jk++eQTTX2xzuSuXLZv344lS5aAHNnfRIkSoWDBgmjfvj169uyJlClTvtTXzp07Y86cOXb7P2nSJIWPnuSuXLZt24YGDRrY7UqlSpWU+eaq+eKuTOrXrw/Ol5hS4cKFce7cuRdfe/JcmT59Onbs2IFDhw7hzJkziIyMxNWrV5E7d2673Y+ve4uZc0UPE2+6r+jh4i33FT1MvOW+cv36dcybNw/r169X7in3799Hnjx5UKtWLQwePBi8f9qm+LqvaHmGiwC2oTRr1ix8/PHHKF26NLp3747nz59j8uTJuHv3Lnbu3Ily5crFyvXx48eoXr26Mjk+/fRTRTTzITR37lx06NABf/3110vlOZHeeust5MqVSxFePCebP7xTp05h1apVaNq06Uv5O3bsqExAlnn77bcVETx+/HhFZO/duxdp06Z9kZ9BvCmmHz16hC+//BIFChTAypUrlX8U6MOGDdMyR5Q87syFvMmhZcuWKF++PMLDw5WXj82bN6NixYrYtWvXS+ePq6LGdizYz6pVqyovCVqTO3NRH1TdunVDnTp1XuoSX5aaNWv20mfOmi/uzIQvgkFBQa8M77p16zB//nwlFjdfMNXkyXOF9wTet/ibuHXrFi5cuBCrAI6Pe4vZc0UPE2+6r+jh4i33FT1MvOW+8ttvv6FXr1547bXXUK9ePWTKlAkBAQGYMWOGcsuknrE13MXHfUXr81sEsBWpBw8eKEKSh1GcOHHixaEUFAYlS5ZUHiS0MsaWvv32W0VY8iHKh6ma+vTpowhVirKGDRsqH9MiwzemO3fu4OTJk8ibN6/yOUU0BXjixIlx/vx5JEmSRPl8y5YtaNSokSJ8KfDUxL8p/oYOHYoff/zxxeedOnVSBPfSpUvRqlWrF5/z7xUrVigiu0iRInHOFXfnsnXrVsVKnzRp0pf68sEHH2DhwoWYMmWK8jJiK2pobTeS3J2L+qD6448/QCEXV3LGfHF3JjEx4AsCX3D5myhevLjHzxV24NKlS8iXL59yH1GFfEwW4Pi4t5g9V/Qy8Zb7il4u3nBf0cvEW+4r1EUZMmRQDHbWacOGDYqxjga3/fv3v/gqPu4rcT3nrL8XAWxF488//8RHH32kuB989913L3GkVZjWCj5UKJJjSvzu9u3biuuD9dK7eqTihx9+CF6HSb2R8OFEkWKd6NJAQcubMJdXmNSHGMvx7cs6UcjS8klLKNOzZ8+QJUsWZM+eHRcvXnwpLx/0fOCzj+xrXMnducTUfop8uofQks83VzWpHKOiopSXjdSpU794yYiLhfX37s7F+kHVtm1bRQhxhcFectZ8cXcm9vp++vRplChRQvlN2L7geupcse1nXAI4Pu4tZs8VvUy85b6il4s33Ff0MvHW+4p1v2kN5nMkNDT0lWet2ZpF63NcBLAVKfqLUijxbaZJkyYvMaTPbdeuXfH333+DYsJe4tIqBWfNmjWVZXfbRAtvmjRpFGsv088//4xvvvlGcXmw9clV35yYp3///kp+PqTPnj2rTLLkyZO/VL1qvWMbfH19sW/fPsUVg1ZQLu1aJwplinMuY6xZsybOueLuXGLqwLRp0xTLr61lXH3Y09LPY1F9fHyUMaP1nhZ2rcnduagPKrWf7Bdf0DiPBwwY8JLF3Fnzxd2Z2Bvbr7/+WlmxoZsSl+usk6fOFb0P8Pi4t5g9V/Qy8Zb7il4u3nBf0cvEW+8rar/pZpk1a1ZF/wQGBr7AER/3Fa3Pb+YTAWxFq3nz5orfLQUqB846qSZ+W9cG6zwHDx5E5cqVFYFMoWybKLKOHz+uiC4m+tLQv5gi1NYfk0K3WLFiSp6JEycq+enfmypVKrs+jIMGDcKoUaPANtDvlW4P7777riKeKaJtU86cORULMf134kruzsVe+2nZpf81nfbJ3Nqvl+KPb6lcriFTfk/3FFrt6V/NlwYtyd258CXsp59+whtvvKFsfLp586bSP/qk8zP6gtMqzOSs+eLuTGzHNSwsTGHDl0LysbWQe+pc0fsAj497i9lzRS8Tb7mv6OXiDfcVvUy89b6i9psb/MeNG/fKqnJ83Fe0PLvVPCKArWjR+kfLKzeLMIqAdeLSKN0O6N/LDWT2EoUFHcBpRaI1yTbR95f1cFckEy1xtCxb+wWrZfgWRf895pk5c6byMX2B6Xtj/Yal5qfvL10a2Ab6w9L3l1ZhW+unmp/9U32M45ow7s7Ftv3kSz/ptWvX4tdff1U2AMaVKJTLlCmjRJCgu4pt5Ah75T2NC/tAv+d27dph0aJFL61mOGu+eBoTcnjvvfdeetFMCHNF7wM8Pu4tZs8VvUy85b5ilEtCvK8YZeIt9xVy4gozN/hzAzn1jfXqdHzcV+K6f1t/LwLYiobZFgmxAFvgG7WMW09oil9acBcvXhyj9TumH0i/fv3wyy+/KC9BMYUPsy7r7vMlpn5yIwPTbK4KAAAbAElEQVQ3WfIFSQ0H560WYLoBcQc3V0L4AqQ1uftc0fsAjw9Ljdm/H71MvOW+YoSLddmEdF8xysRb7it8btCgwo3DfG7SDcI6xcd9Res9nPlEAFvRMtsnTXyALfCN+karQ8hl7Pfff19Zzmfs45EjR+r5LSjRIhiKLjY/b+sK3X2+xNT5p0+fKr7odLtRfcC90QeYG0a5ElKtWjXs2bMnQc0VvQ/w+PDVM/v3o5eJt9xXHOViWy4h3VeMMPGW+wqt3Iy1zwhZmzZtekX8kmF83Ff03MhFAFvRYiQGHljxww8/KBuirJMaBYIRFRhPN6ZEtwXG3uS/uKJAMMID3SIYeYKuENbJXhQIRpCgawUDtNvG2nNlFAh350Ju9OWk7zVDwmmNbmE7hnSVmDBhgl2+9sbbE7jYa/eRI0dQoUKFl+ads6JAeBITujLxgBtGd+HvXk9y97mi9wEeH/cWs+eKXibecl9xhEtCv68YYeIN95UFCxYoK4g8F4EraIwAYS/Fx31Fz31cBLAVLcalpIBNnz693TjAHGz62DJx1yM3zXAjGf+pSZ38tpvlGBOY/qh8U1IjDTAOcKFChRSxzPijPFGFSY0DTH9U+iOrcYBZltEpbOMAq+G+bA+3oF8O/XNiigPMJStutIsruTsXit/WrVsrGxgpaLghMKZEKwV52m524qZDno7GTYb0sbaNsmGvPnfnwk19tqcD0kWEoeFo+V2+fLkSP1pNzpgv7s5E7St/e/yt87d248YNJRSebfLkuaL3AR4f9xaz54peJt5yX9HLxRvuK3qZeNN9hRupGR2Hz0sefMG4wDGl+LivxKVnrL8XAWxDiyHJGDdWPQmON0Eej8vDKih+aTljUmNY2lobGeGBzuA8wIIhuFTRTF9LLs/zzck6UYhQ0HIneu/evZWjl9kGRqKgsOVufeukHu7Ak+AoZLjcQmFNNwIuYzPklZoo5NgWPuTVk+BYJ3f/63URcGcubdq0UY5C5nGMPXr0eGX+8yWjRo0ayue0fnLpn+xoNVfD0tEKyFP/WA+/05rcmQujXOTIkUO5UXHzJE8D+9///qe83NFazr/5kuXs+eLOTNS+8jfA3x3nC8Pl2UuePlfYx6NHjypd43HDhw8fBn2X1XsE9yDwZV9N8XFvMXuu6GHiTfcVPVy85b6ih4m33FfIhEYTGorowmmtN1QGNKS4g2bR8gwXAWyHEkXQmDFjcOzYMUWQMqoCLYvWxyDHJIBZHcUyrbEUmzwrm5Ymujkw3qjtaWXMT1cIRnE4cOCA0hreYOiCYW8jFv1cuVGLy4dXrlxRlh74IKfLhK0DOuviwR20iHKZ4smTJ0o4sM8++ww8Htda/GiZLO7KhbFtySKmZH34CEUgRYC/v79i+ePSP+Mm06WEnzOEnN7krlx4g+IcPHfuHGht402LG7349s7oIvbG31nzxV2ZqGPL3wxv5mrYQHtj7ulzRY1hHNN8tj3UJ77uLWbOFT1MvOm+ooeLt9xX9DDxlvsKD86ii2hsyfaE1fi6r2h5josA1kJJ8ggBISAEhIAQEAJCQAgkGAIigBPMUEpHhIAQEAJCQAgIASEgBLQQEAGshZLkEQJCQAgIASEgBISAEEgwBEQAJ5ihlI4IASEgBISAEBACQkAIaCEgAlgLJckjBISAEBACQkAICAEhkGAIiABOMEMpHRECQkAICAEhIASEgBDQQkAEsBZKkkcICAEhIASEgBAQAkIgwRAQAZxghlI6IgSEgBAQAkJACAgBIaCFgAhgLZQkjxAQAkJACAgBISAEhECCISACOMEMpXRECAgBISAEhIAQEAJCQAsBEcBaKEkeISAEhIAQEAI6CBw6dAgjRozA4cOHwWO1U6RIoRxF//nnn6N9+/a6j6LXcWnJKgSEgAYCIoA1QJIsQkAICAEhIAT0EFiyZAlmz56NatWqIWfOnAgNDcW6deuwZs0a9O3bF7/88oue6iSvEBACTiYgAtjJQKU6ISAEhIAQEAIxEXjrrbewceNGPHz4EClTphRQQkAIxBMBEcDxBF4uKwSEgBAQAt5H4LPPPsPUqVNx9+5dZM6c2fsASI+FgJsQEAHsJgMhzRACQuD/CdSvXx/bt2/Hd999h++///4VNE+ePMGPP/6I5cuX4+rVq3j+/LmSJzo6GnGVTWicva2/esfv008/xbRp07Bw4UK0a9dOb3HD+Z8+fYqQkBAEBwdj06ZN+PLLL1G8eHHQR1hPiq9xpguHv78/AgICUKpUKT1NlrxCwK0JiAB26+GRxgmBlwlERkZi/vz5+Pvvv5XNNffu3VM21/j6+iJPnjyoW7euIgDr1avn0Zts4nrYN23aFBs2bFDgpE6dGmnSpFH+5majuMo6a0517twZc+bMQd68eXH58mVNvI8fP44yZcooTaCPaOvWrQ03x6z+Gm5oPFRw9uxZRbQVKlQIJ0+eROLEiU1vRY8ePfD7778r102UKBEaNmyImTNnIn/+/DG2JSIiQvlNP3r0CDdv3lT+jq9xXrVqFZo3bw66bqxcudJ0fnJBIeAqAiKAXUVW6hUCTiZAsfvmm29i3759L2pOnjy54kfIByWtn2p68OABMmTI4OQWmFddp06dsH//fmXHPP9ZpxMnTqB06dLKR0uXLkWrVq1e+j62ss7sAS3UFCVMtOw1atQozuq//vprjB07Vln6vnHjBpIlSxZnmbgyxJcwiqtd7vA9XzCWLVuGuXPnomPHjvHSpNOnT+PatWu4ffu2sgHu+vXrmDRp0os5bK9R27ZtQ4MGDVC9enXs2bNHyRKf41ypUiXFYu3n54c6derEC0e5qBBwNgERwM4mKvUJARcReP3117F+/XrF4jlkyBBQ6HF3OdOzZ8+UZcoVK1bgr7/+wpkzZzxaAMeGcNGiRXjvvfcUEUk/yvhKfOEoXLgwLl68qIgriqzYEq33uXPnVqzUvXr1wsSJE53S9PgURk7pgIsq4bhwfNKnT68w58uiOyRGgPjzzz9B63RMPsBfffUVfv31VyWM2qBBg+JdAP/222/o2bMnWrZsqbgdSRICCYGACOCEMIrShwRPgFakEiVKKP2kAGzTpk2MfQ4LC4OPj0+8LPeaMRB0O6D7Qb58+RTXg/hMw4YNw7fffotUqVIpIitt2rQxNmf16tXKMjLTwYMHUbFiRac0XQSwfYwUjqNGjUKXLl0wa9Ysp7B2RiUc+8qVK2P69On45JNP7FZZpEgRnD9/HseOHXthKY7PcebqU44cOZRVJlqzs2XL5gwUUocQiFcCIoDjFb9cXAhoI7B48WK0bdtWyUxrr97wSdYPz4EDB2L06NHKpiAKSIo3+g5TyJUvXz7WBtGPcvz48diyZYuyhJ8kSRLFykY3hN69eyvWtpjShQsXMGHCBMVdgBvX+DCl33LVqlXxwQcfgH69arL3sOdmuB9++CHG+v/44w9FGGsRCnraEhuQwMBAFChQAFFRUUrM148++ijG7Bw/jmPZsmVx9OhRu/m4RE5rG90/7t+/j0yZMilxZGl94wqAvRRbf+lneuXKFahs7JWPKY91vYMHD8a4ceOU1QVaVjNmzIhmzZqBLwAURkwUbCNHjlRCfN25c0d5QaHAozUzNt9bI3MqJtgcj1y5cikvJfQVb9KkSZzsXNlH64vv2rULtWvXxs8//4z+/fu/0q5Tp06hZMmSyrwi69h+E9aFuSmUm0aTJk2qjBNXSawTmXBu0f+YK0TcO0DXhn79+il84porb7zxBtauXavcO1hGkhDwdAIigD19BKX9XkGAG6ZUq++5c+cU0aknqWLmm2++UaIr0K+Q/qeq/zDr4oOT1mUuc9pL9Fvs06cPuJTPROEcHh6u/GMqWLCgIja44cg2zZgxAwz/pOblw5fXZixUCmEKZ/4d28OeBwfwn7qjnqIqa9asL8pQXPOhH5cA1tuWuDhTPFDU8yWCbO0l+mRTKDJaBYUkOVonMqDIVTdLsW/p0qVTIgdQuDCRH8eAG6msk6sFMC2pnC9bt25VRBMTD3Vg4jzcu3evIn4piNlPjiXbrfqkf/HFF8pLk7PnVGzjcuTIEVSoUEF5QaN/PN2G7CWVnSv6SJ9fbl6zTXSXmTdvnsJT9SG3zkOBOWDAAOWFknM6tt8EvyNnMubcYD/pF2/9Msk8/N3x/vHvv/8q1ZEL55f6m5s8ebIibGN7WaI1nZzo6875LkkIeDoBEcCePoLSfq8gQEstBSYfdo0bN1YsPNmzZ9fcd/VBT3HCh+GUKVMUqytFMC1OtNTRMsUHKDeZ0XpnnVS/W4peWpA//vhj5frcrU5rJR/A9EGmdZPRKawtfv/88w/eeecdpTpakYYPH66IEyYKJVo9//e//4H54nrY83v6T9LSGpMLRGyC0JG2xAV5wYIFL462pWWZljvbxDBcDMfFlwwuIdsKI4pi+oYycaMcGdP6SyswhYd6ahgFEYWRdXK1AOZmSvrP0nJIkcvEyAAUco8fP1aEO8eQ0S3YPs5TjitFHC2OFOycU6oLj9p2I3MqrjGhGCQntonhu2JKKjtX9JGb2Cg0ae2l7zf91SlA+cJAMcr+20vMz98iLen8rcf2m+BvmasenIOcL3Sz4cY526S66nAs6FfMjaV01wkKCgJfilmeblNcXYpptWDz5s1Ke3gPoHDmXJYkBDyZgAhgTx49abtXEejatauyzM7Eh1WNGjWUhx39CWvWrKk8ZON60PN7Wp/at2//UlYKGYaLomtCt27dXlgimYlWSy6PcjmZG2DsWYgp1BiZgSGbrCMzUCDTIkxXgRYtWig78rWEoopN1DkqgB1tS1yTjBZpWndpaYwpbjHdGPiiQAbWQp91U3RwuZ6igmKShyTYpu7duys+oxQ5FNDWLjCuFsBsC8UPw3dZJ1VU8TP6rNKVgfNSTbRcFytWTLEOc3l+6NChL74zMqfiGg9+r1pZO3TooLwsavldOLuPFJIMWcjQd/ShpXDkb4Rt4wsnxbFtokimfy3D+vFva5FpO86cN++++67ilsDNsFx9sRenlzGz+T1/47TgUgBbJ75U88WGG2yZYhLA7EOWLFmUPM70YdcynpJHCLiCgAhgV1CVOoWACwjQ2kOBxeVkii7bRGsXl8kplK2FCPOpD09aTS9dumQ3Zi3Dc9H6SP9OPuzUpXaKXvr4Fi1aVPEdjCmpAp1xT2nxZOJDlb6rrItCiNZBLckVAtjRtmhprypQaf2lFdjaTcF6AyPFL0WwdVKt0hREfAFRfWqt8zB0FuMNU1TSivj222+/+NrVAtg6FJd1m+gWwRcvJrpu8MXJNvEzupzYWjyNzCkt48Flevqp09WE1vWYksrOFX3U0k7bPOoGT/qLM9a3dbIeZ664cEPl7t27FTcUWotjiivMl06Gg+M9gRZfvkTZJuuQfjEJYApl1sE5yBUAhmSUJAQ8mYAIYE8ePWm7VxKgtZWiibFC6XZAUar6iRIIH5RcCqXFSU3qw5Oh0/iQtZcY55ObYpi4+UZdyldj13IZPLbYwrQ08dQrWpO4JM6kblzj8jcthFqTKwSwo23R0mYua9Miz8Rx4UEkauISMzc80V+ZQtZ26ZiWUbqFxLVcT+shXQm4WdF6M6CrBbDtioDaLwp91RedQkztvzUvtW9cOqdIU5OROaVlPMqVK6e4PtBKzZCBMSWVnSv6qKWdtnlo0eUKir1VGuu28uWDESK4aXXdunWxRmVQx4BM6BttLzFyDK3OfMmObcMkw7bx/hNbHkf6LWWEQHwQEAEcH9TlmkLAiQTob0nrJnfgqw84HrfKOKJqUh+e9C1lPnuJ1iHVr5iCjsv2THSXoI+g1kTxRxHIxCV9+oHSCsylWq3JFQLY0bZobTN37tOfmv7JqqsKX0xouaXwtR0TtV71pLC4GKlxoK0t7KzD1QLYVnCr7aZfuvqSZP3CZM1LfemwnhNG55SW8aDrBePsxhWxQGXnij5qaad1HopQuhjQtYEb6GwttWpb1TL04eVLiPVGUHvXVOeX9YupvXxceaCbU2zilq46jP5CNx3+niQJAU8mIALYk0dP2i4ErAjQLYL+wLS00lJLNwbV31aLAObDT11+txbA7dq1U5ZjY9u4E9NAOCo6PVEAq7v3aUkjS24oVN0uyIehz7hJ0DZpFSiqALb1E3a1AI7Jr9laANOtxt4SfEwC2Mic0vKjp2sGraSxvfDF9fLA7430UUs7rfOoc8X2ZUHNo44zXQ927NihbDSkOw1D68W2IU11z3GGAKbvOSOAxBWLXG/fJb8QiA8CIoDjg7pcUwi4iIAaqojVU4SpAevVh+eHH36oRFGwl2JygaC/IU8to4WTS/B6EpfqKYLcwQXC0bZo7S83ADKuMcPEqUfvMtIG4y0z6gX52kuudIGgiwKthPTJptC2l+jzzQ14tpa/uMLJGRGHRuaUlvGgj/TKlSuVPqv+6PbKubKPWtppnYf++7SsMuKHGhHE+nvrtvJl6LXXXlM2tjHCCgWprd+/WladX3SXYIQWe0mLCwSFr7r5kv7VjHIhSQh4MgERwJ48etJ2IWBDgEKV4oKJvnoUN0zqw5NWOlrr7CU1FJftJjg1XBXLUABTCGtN3JnOmKTusAnO0bZo7SvzcWMS/a8ZMYGbj2hRp2We48Ljj+0lbmpjZA1ugmOEB3vh7SiuGeVD7ya4KlWqKH7iPOSBfsa2iRsTGcGByUwBbGROaRkPhmCjRZ5zjz6yMSV3EsDcoMpoKXTdUMckJgHMl0r6XVMIUwRzkxtDCdoTweomOFqJ6eak3hOs69ayCU49oIPl6AZhb7OmlrGRPELAXQiIAHaXkZB2CIFYCFC00rIY2wEY/L5OnTrK0q+t0LX2H6Q/7/vvv//S1biBjZusGAjfdkMQfRIZvYEPT+6up6CIydrETTQMcUU3ACZHQ4+5wgXC0bbomZjcwMSNTBT8asgpxlqmYOAGInuJfClueYgERTLFsm1SXUn0hkHjMcAUtjFtsGM8Z/WYYDMFsJE5pWU8GKWgefPmih8tXYHcXQDTPYYWWvouM2qIvWTvN8F4wRTB/P3SRUmN52tdnt9RrPK/3BDIjYG2iW4V6sbVmHyA1QgVvAfxMB5JQsDTCYgA9vQRlPZ7BQE+0GklpIWR/pMUutyQwsSlST4IaeFTN59xAxw3XalJfXjyIAwKQS61UgTTKsQHLkUv/QoZOYJxS20Pc7A+ipknnjGWKP0s6WNMqyT9jlesWKHEquUOdgbzV5Ma8or/zwct26keucxYp2wzH9y0VNm2157/qaNxgFm3I23RM8G4lMyYq6r/NdnQOseT/GJLHC8eGczEqBE8IpeWOorin376SbFmMtmzJMf2smDtg8yDIegGQv9wbrLiODB8WUwHILjaOmpkTsU1JnTp4AsH+cd2cqKr+xhXO9Xv1ZjKjI4xZswYzQKYGXfu3KlEXqHAZfg0/pZsYwyrvtj8vXITLN0t+JLKl1q+qPE3G9dBGDw8gwfoMNwhD0WRJAQ8nYAIYE8fQWm/VxCwFjJqh3ksLf9ZHyHM72hF5Ilc1rFo1Qe97VHI6qlOLMcHIJdRKdjsJVoK+eCkhZeJlk3uROdmHPWIY/WBXKtWrZeqoOCmAFOPUaYvIR/SfGgzaTkKWa3QiABmHXrboneCqf6tajn6ovLFJbZk7yhkMuHhGmqIO54kxyNr9RyFzGvyeGjrU8cogFkvxRCtffQRtXcErhni0MicimtcVKum7cugdTkz+hhXO/l91apVceDAAfj5+Skvt/ZSbG3lyytFMMMQ8gWZgtZaBPP3yVjefJFmsj0KmcKWL1p0waDPOuuwTpyfXAWi3zddiXj8tyQh4OkERAB7+ghK+72GAC1ZfIDxYUcrLZfVaf1ltAG6PNAiyxBcfJjaJuuHJ3fG06LIBx1dKyiCadWlEKpYsWKsPCmUKML4EOTDkA9cCjUeksFYr3zIqscc21ZESzMP8eCJW/R1pYCmFZuHEHCzWFzHvjpLALMePW3RO8EYik5lwE2I7GtMLiO2ddN/mGHj9u3bp1h/aQUmH7pAqMcQxza2tPTZJoofikAuYXNDHC1/rJOWP84Zzp34EsBsq5E5FdvYqAeM8PdAnnpFJfMb2eindd7Qv5u/A7pr0CJr74Q41hWXWKd45lHj/E3y98SNmNZ18eWTGwL50sHY4Xx5ZtSYfv36KYJWfTFiuEK6VVgn+hvzpZZzhSHvbF/CtPZV8gkBdyIgAtidRkPaIgRcRCCuh6eLLivVCoF4I0BXHwo2xmCm4ONLmjsmnpRHFyQekUzRGh/JejMkX0gYu9o6qREq6DbDDZWShEBCICACOCGMovRBCMRBQASwTBFvJKCKS27249/umLhZjys78RlbV90MWbx4ceUwF+tEf3HuCeBKE1cQ6PYkSQgkBAIigBPCKEofhIAIYJkDQuAVAlz2Z3QTCjdaOW0tm+6AjO5IjIrB2L+uFJeMTsI44NygqoZCIxNeX305oHsEI4dYJ27I5MY87iugH78kIZBQCIgATigjKf0QArEQEAuwTA9vJcCwgNxESh9z6+gk3saDfujqJlQKbW5sUzehkoVt+EOVz9ixYxWBztjK9NuXJAQSCgERwAllJKUfQkAEsMwBISAEYiDA0GWM4R0QEKBstuMBLVmzZlU2zTK0WVyRSgSsEEhoBEQAJ7QRlf4IASEgBISAEBACQkAIxEpABLBMECEgBISAEBACQkAICAGvIiAC2KuGWzorBISAEBACQkAICAEhIAJY5oAQEAJCQAgIASEgBISAVxEQAexVwy2dFQJCQAgIASEgBISAEBABLHNACAgBISAEhIAQEAJCwKsIiAD2quGWzgoBISAEhIAQEAJCQAiIAJY5IASEgBAQAkJACAgBIeBVBEQAe9VwS2eFgBAQAkJACAgBISAERADLHBACQkAICAEhIASEgBDwKgIigL1quKWzQkAICAEhIASEgBAQAiKAZQ4IASEgBISAEBACQkAIeBUBEcBeNdzSWSEgBISAEBACQkAICAERwDIHhIAQEAJCQAgIASEgBLyKgAhgrxpu6awQEAJCQAgIASEgBISACGCZA0JACAgBISAEhIAQEAJeRUAEsFcNt3RWCAgBISAEhIAQEAJCQASwzAEhIASEgBAQAkJACAgBryIgAtirhls6KwSEgBAQAkJACAgBISACWOaAEBACQkAICAEhIASEgFcREAHsVcMtnRUCQkAICAEhIASEgBD4P/7J7T7LcwowAAAAAElFTkSuQmCC\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(np.transpose(v_spec),Temps)#,'D')\n",
    "plt.xlabel('Specific Volume (m$^3$/kg)')\n",
    "plt.ylabel('Temperature (K)')\n",
    "ax = plt.gca()\n",
    "ax.annotate(\"\",xy=(0.0025,320), xytext=(0.0125,320),arrowprops=dict(arrowstyle=\"-|>\",color='k',linewidth=2.0),fontsize=14,)\n",
    "plt.annotate('Increasing Pressure', xy=(0.0025,320), xytext=(0.0035, 322), family='Times New Roman',fontsize=16);\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Repeat the process for a non-ideal Redlich-Kwong equation of state:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "RK_gas = ct.Solution('input-files/non-ideal-models/co2_RK_example.cti','carbondioxide')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i, P in enumerate(press):\n",
    "    for j, T in enumerate(Temps):\n",
    "        RK_gas.TP = T, P\n",
    "        v_spec[i,j] = 1/RK_gas.density"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(np.transpose(v_spec),Temps)#,'D')\n",
    "plt.xlabel('Specific Volume (m$^3$/kg)')\n",
    "plt.ylabel('Temperature (K)')\n",
    "ax = plt.gca()\n",
    "ax.annotate(\"\",xy=(0.0025,320), xytext=(0.0125,320),arrowprops=dict(arrowstyle=\"-|>\",color='k',linewidth=2.0),fontsize=14,)\n",
    "plt.annotate('Increasing Pressure', xy=(0.0025,320), xytext=(0.0035, 322), family='Times New Roman',fontsize=16);\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now we see the expected behavior, with phase change below the critical point, and a continuous change of properties for the supercritical fluid.\n",
    "\n",
    "## Calculating chemical reaction rates.\n",
    "\n",
    "In this example, we will compare chemical rates for the ideal and real gas models.  One wonderful thing about Cantera, as seen above, is that once the phase is created, the procedure for these calculations is independent of the EoS.\n",
    "\n",
    "### Application 1: Water-gas shift reaction\n",
    "For the second example, we will compare reaction rates of progress for the water-gas shift reaction:\n",
    "\n",
    "$${\\rm H}_2{\\rm O} + {\\rm CO} \\leftrightarrow {\\rm CO}_2 + {\\rm H}_2$$\n",
    "\n",
    "These will be calculated for a zero-D reactor.  Simulations will have an initial condition of $T =$ 800 K, and a composition of 50% CO$_2$, 50% H$_2$.  Start at low pressure (1 atmosphere).  Load the initial conditions to each gas object, and create the reactor and reactor network for each.  Initialize lists to store the H$_2$ mole fraction and the simulation time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "RK_gas.TPX = 800, 101325, {'CO2':0.5, 'H2':0.5}\n",
    "Ideal_gas.TPX = 800, 101325, {'CO2':0.5, 'H2':0.5}\n",
    "\n",
    "r_RK = ct.Reactor(contents=RK_gas,name='RK reactor')\n",
    "reactorNetwork_RK = ct.ReactorNet([r_RK])\n",
    "\n",
    "r_IG = ct.IdealGasReactor(contents=Ideal_gas,name='IG reactor')\n",
    "reactorNetwork_IG = ct.ReactorNet([r_IG])\n",
    "\n",
    "X_RK = list()\n",
    "X_IG = list()\n",
    "\n",
    "times_RK = list()\n",
    "times_IG = list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Integrate the reactors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_RK = 0\n",
    "t_IG = 0\n",
    "\n",
    "while(t_RK < 100):\n",
    "    t_RK = reactorNetwork_RK.step()   \n",
    "    times_RK.append(t_RK)\n",
    "    X_RK.append(RK_gas.X[2])\n",
    "while(t_IG < 100):\n",
    "    t_IG = reactorNetwork_IG.step() \n",
    "    times_IG.append(t_IG)\n",
    "    X_IG.append(Ideal_gas.X[2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting the results, we see that the two equations of state agree exactly at low pressure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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wN4IYMlxXr58ucrtFTG6aNGixHQD8U3SN/r166dSFeT0V/TMoUOHVJ6zfLItl+0kXcNIFZHTajkBTn55P6UTYHcCmCfA3vwk+aCvkatjvAQnyd7yrxsJuohfEbLSUspDkRwiCZgkdUsVCTmml3wcOfKXj0BkHvkBStqkAoR8XCIfIUgSu/xgiQ1SiSL5RzCeuKfjXzZJ131p+SEs3nscYYjDPseLyGO7mvjt4wn5USdmCrKHh2HvKw8zD9iTgLEPCZAACfgZAV8KYHHdamXQxCY5+Vy2bJk6jSxYsKASeZKTKyehcl8otSZCUnJgfZUDLJfapKJESs0XJ8DGJT+53CcXzeQynyH6ZU1JRxA9I0UA5ARYTnClGoakdEhVBsnPlcNAo0kOsFzCk8M74w2E3bt3Q06Ak+cAuxPAKeUAG5/UMwVC0x8asuklt+Xw4cNKkMrHGvJxRNJnkFMSwPJssghcSYCXRHHjJqkEXtIf5COGlJp8nPDaa6+pHxppcutRjv1T65+W27oFcNI/qCbaZ+GpUPPLeE2cY/C9qwR0X1zQFHpOSwIkQAIk4IaArwVwVj+EkdIpqgg7eQF20KBBqjSXNLm4LpfL5GtSBULSE0QYy9/hK1euVH2MygVSBUJKk8mnvjJ/eqpAyHjJk5XSq5I/K2kZcuoqwteoAuGLE2Aj3Ma9JElfkDRMo0n5MqkR/NZbbyWWfJODO0mZEJEq7yMYzagC8eCDDyZWgZBLfFIxInkVCHcCOGkVCDmNl31nVIEQG5Onqho2uNufOnSS39cBDoQ/9XQENikX+YOq6usbcT02AQ1C9mNu+CQTthlxT2Bi3DO8CBcIm4k+kAAJkEAKBNwJjPRAy8qnkFN7TlhOgUXkSZkwSY2Uk0+p6CQX4kT4yottkvogIjBpLeCktWvl02QZIwI2PXWARfCJCBbmcuoqJ7HyKbE8tuXLE2AjZlLVQg4Ak4pdqdYgB4Nyslu5cmXVVewSf+QEOfkn25JPnVIdYDlJl+ZpDrD0XbFihZpLKlYIS7lPJXWAZX0ps5ZSc7c/degkCuD0/NT7eIyOwCY38fl5e/Dlz2fhQAz2O7ojp+3f5yul/ZZQCA1iJqL2XfmZB+zj2HI6EiABErACAXcCI702rj/870fpj1X49+IZGwkkJyDVKqQmspRik38MUABzjyQSyAwBnDQNYrp9GpqG7jJFoKFzPI7aiuLbEY8wD5h7kwRIgAQCjIAuARxgmOiODwhIGoicnsvptxQnkLJvd9xxhzqNNmoDJ1/G3f7UoZN4AuyDYGd0Ch2BTW7Tv2kQm3A9Nh6PhezCzHDzU82TYp/C9PgWeLjM7ZjzXNWMusTxJEACJEACFiLgTmBYyFSa4ucE2rZtq057pVqWpKFIzeWkzyrzBNjPA+xL8zNDAIu9Xd7bi00/nEF23MABRzdks/1Xq/BIwp14LGYssoeHshqEL4PLuUiABEjAAgQogC0QBJqQKgF3+1OHTuIJsAU2pI7ApuSWnAJXGrUBcQkuvGN/C41C95m6PeicjGOuAqwGYYE9QRNIgARIwJcE3AkMX67FuUjAWwLu9qcOnUQB7G2UNPTXEdjUzGw/dxd2/HIezUN2YEr4TFO3sbFt8E58U1aD0BBjTkkCJEACWUnAncDIStu4Ngm42586dBIFsAX2nY7ApuaW8ShGBK5in6M7wm3xiV2/SSiF5jGjUe+e/FjQsZoFyNAEEiABEiABXxBwJzB8sQbnIIH0EnC3P3XoJArg9EbLh+N0BDY185JWg5hvfxP1Q781da1xYzou2fNj37CGrAbhwxhzKhIgARLISgLuBEZW2sa1ScDd/tShkyiALbDvdAQ2NbckD7jamE24FhOPp0O/wHj7u6auo2Kfxfz4xswDtsC+oAkkQAIk4CsC7gSGr9bhPCSQHgLu9qcOnUQBnJ5I+XiMjsCmZaJRDeJWRGOvowfCbAmJ3Xcn3ItnYoazHJqPY8zpSIAESCArCbgTGFlpG9cmAXf7U4dOogC2wL7TEdi03Er6NPJC+xjUCv0+sXuCy4bqzv8hJKIAtkTVYxqEBfYHTSABEiCBjBJwJzAyOn9mjk/tOeHkNvTq1Qtr165Vz/j6ui1YsAAdO3bE2bNnkS9fvjSnl2eZ33zzTXz22Wc4ceIE7HY77r77brRu3RpdunTBrbfe6mvz/G4+d/tTh06iALbANtERWHduPT9/D7786SyeDd2A0fYFpu6vxHbCwviHmQbhDiK/TwIkQAJ+QsCdwPATN5SZ/iSAd+/ejcaNG+O2225Dnz59UKFCBcTGxmLnzp2YNWsW6tSpg6VLl/oTfi22utufOnQSBbCWUHo3qY7AurPAuAx3Oy5iT7aepu7b48vj2dihTINwB5HfJwESIAE/IeBOYPiJG34lgG/cuKFOevPkyYMdO3YgIiLChPmff/7BqlWr0L59e3/Cr8VWd/tTh06iANYSSu8m1RFYdxZIGsRDE7/EmX+cWBY+ElVCfk4cEucKQRXn23BE5GMahDuQ/D4JkAAJ+AEBdwLDD1xINDGlE+CTJ0+ie/fu2LRpk0op6NevH/7888+bUiDk79shQ4aodISrV6+iatWqmDx5MipXrpw4//vvv4/Zs2fjyJEjcLlcuO+++zB+/HhUq/ZfeVBPUiA++OADdOjQAevWrcNjjz3mFvGpU6fwyiuvqGeE5f+LFCmCVq1aYcSIEXA4HInj582bh0mTJuH3339H9uzZUaZMGeWD+OKvzd3+1KGTKIAtsFt0BNYTt4zLcJ1D1+FV+0LTkEGxXbE0vh7TIDwByT4kQAIkYHEC7gSGxc03mZeSABbxJ3+Xjhs3Tp24jh07Vv0+LCwsMQf44sWLuP/++5EzZ04lNHPnzo3p06erdIRffvkFt99+u1rntddeQ8GCBVGqVCnExMRg0aJFKk3h0KFD6kRXmicCuHPnzhAxLSe92bJlc4v48OHDeO+991C7dm0l4n/++WeV7tGoUSOI6JW2bds21K1bFwMHDlSi+tq1a9izZ48a07BhQ7drWLWDu/2pQydRAFtgN+gIrCduGWkQRWxnscPR1zRkc/z96Bw7iGkQnoBkHxIgARKwOIFUBcYn3YGzP2a99fnvBZ6c5ZEdyQWwnOZKnu3mzZvx0EMPqTlE7BYtWlRdUDN8l5PUqVOnKmFpiF2n04nSpUujTZs26pQ3eUtISID8Kl++PFq0aIE33njDYwEsNn3zzTfqNDdpi4+PVyfL0mw2G0JDQ1P0Oy4uDkuWLMFzzz2Hy5cvq9PeiRMnKnF//vx5j1j5SycKYH+JlI/tzCoBnDQNYnX4K6gYcjTRM6crDFWcs5A94lamQfg43pyOBEiABDKbQKoCY3Y94OTBzDbn5vXuuB/o+qVHdiQXwKNGjVIpAJcuXTKNb9asmTq1NXyvUaOGOtlNfulM0hREpH7xxRdq/A8//IChQ4eqk+EzZ84kztmyZUssW7bMYwH86KOPqvUlPSNpkxNoSb+QliNHDly5ckX9v4hiEeiSfnH06FFIDrHR5HRYRPiWLVvQoEEDJYrbtWuHWrVqKWHs740C2N8jmE77s0oAi7lGGkSP0FUYbF9s8qB/zIv4JKEO0yDSGVcOIwESIAGrEAhkASy5v3L6K2kMSdsLL7yAjRs3Jgrgu+66C7/++muKIZF0B/mepCuULVsW+fPnR1RUFO68806VviDlyiQnV8qqSfMmBUIEbtIc3oMHD0JOgUXoSnqFIYBFxEtqw+DBg1G/fn2VBrF371707NlT/bdKlSpq7Q8//FAJ5f379yvbnnrqKUyZMkVVmvDXRgHsr5HLoN1ZKYCNNIg7bX9jq2OAyZON8Q/ghdiBTIPIYHw5nARIgASymkAgC2BPT4CrV6+uROLo0aNvCocIVClRtmHDBpVzK6kLcvnNaCVKlEC5cuW8EsDGJbhPP/0UchqcvCU/ya5ZsyYKFCiATz75JLGr5AQ///zzJgFsfPPcuXOqikT//v3VZbm5c+dm9TZL9/oUwOlG598Ds1IAJ02DWBs+FOVD/isYbqRB5Mx9GzYNqMtHMfx7m9F6EiCBICYQyDnAIjDlQpi7HGC5+Canp1LdQVIPUmoiKJs3b676SHUFaZIKIakGTZo08UoAG2XQ8ubNqy6v5cqVy7RkcgEsF/Tkkt3ixf99GvvII4+oU+ykJ8DJ7ZbUDEnhEDv9tVEA+2vkMmh3VgpgMZ1pEBkMIIeTAAmQgMUJuBMYFjc/TeEoubOSHiC5tvLimlSBkMtqyatAyMUxKXcmF+P69u2LYsWKqZfc5LGKO+64Q52knj59Wl2Kk6oSUi5NXm4ToSopC5UqVfJKAIvRMrec/sqa8hCG5PHKXJKuMW3aNJW3bFySk9QHSW2QEmcihBcuXIjt27erfGBDAMtFPvGjXr166iKf5AbLuAEDBqR4su0vcXW3P3XoJFaBsMDu0BFYb9zyJA2ifWQxvN68gjfTsi8JkAAJkIBFCLgTGBYx0yMzUiqDJn+PGrnAkjsrYlO+lvwp5L///hvDhg3D+vXrlZAUERkZGanEr6QgSJOqEpKL+9tvvykhKqXVRFjL5TVvcoANZ+QpZJkj+VPIjz/+OOS5ZqMiheQC9+7dW6U1SJPcXrnI17Rp00QBLOtLvq9crouOjlZ5yfKQhvgkJd/8tbnbnzp0EgWwBXaLjsB645akQTw8aSv+jr6BlNIgqsXMwsaXm+L2CPd1DL1Zl31JgARIgAQyh4A7gZE5VnAVEkiZgLv9qUMnUQBbYDfqCKy3bu389RzaztmNlKpB9IvpgZzV2vIE2Fuo7E8CJEACFiHgTmBYxEyaEaQE3O1PHTqJAtgCm01HYNPjlqRCbN+9J9VqEIu6VEfN0vnSMzXHkAAJkAAJZCEBdwIjC03j0iSQWKquePHiKdLQoZMogC2w8XQENj1unY6+gRpjN2O1/eZqEFWdsyDVIDayGkR60HIMCZAACWQpAQrgLMXPxd0QcLc/degkCmALbEsdgU2PW8ZluNTSIFYm1OajGOkByzEkQAIkkMUE3AmMLDaPywc5AXf7U4dOogC2wKbTEdj0uJV2NYjKeCE2Cs9ULYI3W/5XHDw963AMCZAACZBA5hJwJzAy1xquRgJmAu72pw6dRAFsgV2oI7DpcUuqQTR8ayskFWKN/WWUC/kzcRrjUYzHqt6DN1tWTM/0HEMCJEACJJBFBKQUV2xsLEqWLAmbzZZFVnBZEkiZgJScCw8PR9GiRVPsoEMnUQBbYDfqCGx63XJXDULSIHgZLr10OY4ESIAEsobAhQsX1CMP8iqZPMoQEhKSNYZwVRJIRkDqMZ85c0bty/z581MAB9MOsZIAFu4vLf8Wu/btS6EaRGV0i4tCwYhsvAwXTBuUvpIACfg9gYSEBPVS2j///KPEr91upwj2+6j6vwPyKl5MTIx6Jrpw4cKpfjqhQyfxBNgC+0dHYDPi1kvLD2Hx3uNYF35zGkRl5yxcQXZehssIYI4lARIggSwicPXqVfWCmKRDiChmI4GsJBAaGops2bKp09+0UnN06CQK4KyM/P+vrSOwGXGL1SAyQo9jSYAESIAESIAEfElAh06iAPZlhNI5l47AptMUNcy4DOeI/gNfOgaYptoYXxl9bYOx95WHkcPhv++OZ4QPx5IACZAACZAACWQeAR06iQI48+KX6ko6AptRt4zLcDenQdhR2fk2Znepz1fhMgqZ40mABEiABEiABNwS0KGTKIDdYtffQUdgM2q1nAJXG7MJz8evwGD7YtN0/WJ6YE+uh3kRLqOQOZ4ESIAESIAESMAtAR06iQLYLXb9HXQENqNWe/IoRvvIYni9eYWMLsXxJEACJEACJEACJJAqAR06iQLYAhtOR2Az6pYhgGWe1NIgmlS9m6/CZRQ0x5MACZAACZAACaRJQIdOogC2wKbTEdiMupX0VbjuIatSTINwVG7DV+EyCprjSYAESIAESIAEKICDcQ9YUQBLHIyLcHfa/r7pUYxN8fejS+wgvgoXjAxuTzIAACAASURBVBuWPpMACZAACZBAJhLQoZN4ApyJAUxtKR2B9ZVb8irc4r1/YU34UFQI+SNx2hhXKKrHvI1bIvLxMpyvYHMeEiABEiABEiCBmwjo0EkUwBbYaDoC6yu3jFfhuoauwVD7R6ZpB8e+gCXx9fkqnK9gcx4SIAESIAESIAEK4GDZA1YWwMZluMI4i6+y9TWFZFt8BXSIfZkCOFg2Kv0kARIgARIggSwgoEMn8QQ4CwKZfEkdgfWVW8ZluL8v38Cy8BGoHPJL4tTxLhuaOeZiSdQTfBXOV8A5DwmQAAmQAAmQgImADp1EAWyBTaYjsL50y7gM93zoZxhpf9809eaSg9Ggwyu+XI5zkQAJkAAJkAAJkEAiAR06iQLYAhtMR2B97ZakQny+61vsdvRCiM2VOP3uhHsR32Edn0X2NXDORwIkQAIkQAIkoAjo0EkUwBbYXDoC62u3jFSISdeHoWbIEdP0T4TPxqKolkyD8DV0zkcCJEACJEACJEABHKh7wB8EsLCXVIg189/AWPtcUyhGx7aDs+qLfBY5UDco/SIBEiABEiCBLCSgQyfxBDgLA2osrSOwutx6e/0edNn9KOy2+MQlvkkoieYxr/NRDF3QOS8JkAAJkAAJBDEBHTqJAtgCG0pHYHW4ZaRBjL02CvVCvzUtUdc5GbERd/JRDB3gOScJkAAJkAAJBDEBHTqJAtgCG0pHYHW4ZdQEbhmyDZPCZ5mWGB/7DGbGP8GawDrAc04SIAESIAESCGICOnQSBbAFNpSOwOpwyxDAuXAN+xzd4bDFJS7zQ0IxNI4ZRwGsAzznJAESIAESIIEgJqBDJ1EAW2BD6QisDreMFIjT0TfwdthbaBS6z7RMW/tUvDuwPatB6IDPOUmABEiABEggSAno0EkUwBbYTDoCq8st41GMx0O+xozw6aZldhXtgsjOk3QtzXlJgARIgARIgASCkIAOnUQBbIGNpCOwOt2SVIjlu37GfseLyG5zJi71W0IhnH52O2relV/n8pybBEiABEiABEggiAjo0EkUwBbYQDoCq9MtIxVi6LUJaBr6tWmp5+0T8b+BHZkGoTMAnJsESIAESIAEgoiADp1EAWyBDaQjsLrdklSIBfNmYHb4ZNNSb8c1xYkqL/FRDN0B4PwkQAIkQAIkECQEdOgkCmALbB4dgc0Mt6Z9fhjP72yICNv1xOX+cuVDbedULOoSiZql82WGGVyDBEiABEiABEgggAno0EkBI4BXrFiB8ePH4/DhwwgPD0ft2rUxZswYVKxY0estsW7dOjz++ONq3Pbt29VcSZvT6cTs2bOxYMEC/P7770hISMCdd96JNm3aoHfv3siZM6dXa+oIrFcGpKOzkQYRdW0KngrdZpqhRcwo/J2rAh/FSAdXDiEBEiABEiABEjAT0KGTAkIAz507F126dEH58uXRrVs3iECdMWMGzp07hx07duC+++7zeC9FR0ejXLlyuHTpEq5cuZKiAH7yySexcuVKNG/eHA0bNoTL5cJnn32GtWvXKrEsotmbpiOw3qyfnr5GTeC6Id/ivfA3TVPMi3sUr8V1YE3g9IDlGBIgARIgARIgARMBHTrJ7wXwxYsXUbx4cUREROD7779X/5UmsMqWLYtKlSph2zbzCWVa+6p79+5Yv349nn76aUyaNOkmAfzrr7/irrvuQosWLbB8+XLTVE2bNlUi+LvvvlMi2tOmI7Cerp3efoYADkMc9jh64DbblcSpTrvyoIZzBtpGFmcucHoBcxwJkAAJkAAJkECipitatCiOHz+OIkWK+ISK3wtgSUPo2LEjRo4ciREjRpigyKmwnA4fPXpUiWR3bevWrahfvz5WrVqF/fv3Y9SoUTcJYPl6lSpVVKrDtGnTTFO++OKLmDVrlkqLKFGihLvlEr/vjwI46aMYo0Pnol3YZpO/bWNewZQhfXB7RDaPObAjCZAACZAACZAACSQnoEMn+b0ANkTnhg0bVDpC0jZv3jx07twZixcvVie6abXr16+rfGE5MV66dKkS1CkJ4Bs3bqBUqVKQk2cRwA0aNFApEJ9//jn69++P9u3bY86cOV7tXh2B9cqAdHY2HsWIDDmCj8NfN83yUVx9fF9lNE+A08mWw0iABEiABEiABP4loEMn+b0ANtIOjhw5gjJlypj2iojiRo0aqVSGAQMGpLmPBg0apISrzFOoUKFUBbBMcuDAAXTq1Anffvtt4pwhISFKMA8bNsztfpU8Y/lltFOnTqFatWo+Pdp3a4SPOkgqxKJdf2CnozcK2i4mznrZlR1VnW9jQZfarAbhI9achgRIgARIgASCkQAFcApRlxPYLVu24LfffkPJkiVNPST3t27duhg9enSawnTfvn2IjIzEzJkz0bVrVzVHaifA8j1Za+jQoRDR26xZM9hsNkgVCjk5ljQMGZtWM+ZO3seXuS2Z9QNyOvoGaozdjJdDP8QLYetNy3aL7Y/DOeuwGkRmBYPrkAAJkAAJkEAAEqAATiGoGT0Bjo2NReXKlZE7d251WU7EbFoC+OTJk6hQoYJKt/j4449NFkn6w6JFi3Dw4ME0K08E2gnwh7uOoZztKNY5XjHxWBdfDT1j+7EaRAD+YUSXSIAESIAESCCzCFAAp0A6oznAkydPRlRUlLr4ljSFQvJ7p0+frkSuCGSp82u32/Haa6+pU95ly5ahZcuWJotkDimNNmXKFPTt29fjfaEjsB4vnsGORjUIwIVN4YNQOuRk4oxOlx1VnG/jich7mQucQc4cTgIkQAIkQALBSkCHTvL7HOD58+erfFzJvx0+fLhpbxhVINKqytCvXz9MnTrV7Z765ZdfULp0aVVnWB7BSOlinYjiVq1aYeLEiUpUe9p0BNbTtTPaL2k1iB4hn2CgfalpykGxXfFo+4FoUKZARpfieBIgARIgARIggSAkoEMn+b0AlmoMcjorKQwp1QGWRzCMhykuX74MuXCWL18+9UuaXGQTcZu8LVmyROX0Sv7wvffei8aNGyNHjhyq8oOc7j722GOQF+OStiZNmqgawim9HpfWftUR2Mz8+TCqQRSzncY2R3/T0jviy2Nw9teYB5yZAeFaJEACJEACJBBABHToJL8XwBJfOZGVk1njJbiYmBiVvnD27FklRu+//361DYyawd5cVEsuZiV/94EHHlAX4erUqaPSIKQMmlyCk75yKU5SIbxpOgLrzfq+6GukQqwIH44HQn5NnDLeZUOkcwYaRd7HNAhfgOYcJEACJEACJBBkBHTopIAQwLIPJP1gwoQJOHz4MMLDw9WTxGPGjDFdRvOFAJa15Inl119/Xb36JpUbpBqEvA7Xrl07VW5NcoW9aToC6836vuhrpEI8cmUVRtnfM005OrY95sY/hkVdqrMkmi9gcw4SIAESIAESCCICOnRSwAhgf94HOgKbFTw2HzmNwe9vxm5HT4TZEhJNOJRQAs1jx6BgRDamQmRFYLgmCZAACZAACfgxAR06iQLYAhtCR2Czwi0jDWKB/U3UC/3vkRCx5SHnRPzuuoMl0bIiMFyTBEiABEiABPyYgA6dRAFsgQ2hI7BZ4ZYhgJuH7MCU8JkmE6bGtcDkuKcogLMiMFyTBEiABEiABPyYgA6dRAFsgQ2hI7BZ4ZaRB/xP9CXsDe+OW2wxiWb84SqAto6Z2BhVDzkcYVlhHtckARIgARIgARLwQwI6dBIFsAU2go7AZpVbRkm0afbpaBb6tcmMjyrOQ5sW5sdDsspOrksCJEACJEACJOAfBHToJApgC8ReR2Cz0i1JhTi5ZyXmhU80mTE/rhHueX4mK0FkZXC4NgmQAAmQAAn4GQEdOokC2AKbQEdgs9ItSYV4dNJmrHZ2wm22K4mmnHNF4EnHXHwW9RDTILIyQFybBEiABEiABPyIgA6dRAFsgQ2gI7BZ7ZakQvy+oCvah202mdIh5iUUq9aUj2JkdYC4PgmQAAmQAAn4CQEdOokC2ALB1xFYC7iFxcuX4JnDL5hMWR5fG1GxPfgohhUCRBtIgARIgARIwA8I6NBJFMAWCLyOwGa1W5IG8cikL7DE2R1FbOcSzbniyoZqMW8jT0RuPoqR1UHi+iRAAiRAAiTgBwR06CTtAvjEiRPqeeKLFy8iNjY2TcwdOnTwgzD43kQdgfW9ld7NaNQEHhT2MXqGrTYN7hXTG2sTarAmsHdI2ZsESIAESIAEgpKADp2kTQAfOHAAvXv3xq5duzwKls1mQ1xcnEd9A62TjsBmNSNDAN9tO44NjpdM5myMfwAvxA6kAM7qIHF9EiABEiABEvADAjp0khYBfOjQIdSsWRPXr1+Hy+WCw+FAvnz5EBaW9gMIR48e9YMw+N5EHYH1vZXezWg8inE6+gbW2YegTMixxAliXaFo6piH5VGPsxqEd1jZmwRIgARIgASCjoAOnaRFAD/55JNYtWoVihYtitmzZ+Phhx9GaGho0AXMU4d1BNbTtXX2Mx7F6Ba6Bi/bPzIttbnkYDTo8IrO5Tk3CZAACZAACZBAABDQoZO0COD8+fPjwoUL2LZtG2rVqhUA6PW6oCOwei32fHZJhdi86yC+cvRBiM2VOHB/wl1wdviMj2J4jpI9SYAESIAESCAoCejQSVoEcPbs2RESEoIrV/57BCEoI+ah0zoC6+HS2rsZqRCTrg9DzZAjpvWets/A/IFtmAahPQpcgARIgARIgAT8l4AOnaRFAJcrVw6Sz3v16lXI5Ta2tAnoCKyVmEsqxIr54zHR/o7JrKlxT+JslSg+imGlYNEWEiABEiABErAYAR06SYsAfv311zFixAh8/vnnKv+XLbgFsHg/49OD6LzrEdxii0mEcTwhPx6MmYyFXWowFYI/JCRAAiRAAiRAAikS8BsBHBMTo3J/JQ9406ZNKFGiBEOaBgEdgbUScCMNYsi1iXgidKfJtGdihuN4rkp8FMNKAaMtJEACJEACJGAhAjp0kpYT4Pfffx/R0dHqFNjpdKJly5aoWrUqIiIi0sTJhzCOo0iRIhbacr4xxagJ/GDIt3g//E3TpB/F1cfLcS+wJrBvUHMWEiABEiABEgg4An4jgOUCnJH7K3WAPckD5kMYRXH8eGAL4FDEY6ejNwrYLiX+cEa7bkFV59toFVmaucAB90cWHSIBEiABEiCBjBPwGwFcvHhxj0RvciR8CCMwBXDSRzFeCl2IbmHrTKEfFhaFlwcNZTWIjP8ZwRlIgARIgARIIOAI+I0ADjjymh3SEVjNJns9vfEoxr22Y/jMMcQ0/kLh+rjthZVez8kBJEACJEACJEACgU9Ah07SkgMc+KHwrYc6AutbC30zm5ELvD78ZZQN+TNx0gRbKLY8thUPV63gm4U4CwmQAAmQAAmQQMAQ0KGTKIAtsD10BNYCbt1kgpEK8fjV5XglbKHp+6/FPouHO45kOTQrBo42kQAJkAAJkEAWEtChkzJFAH/33XfYv38/zpw5o3KD5ankypUro3z58lmI0zpL6wisdbwzWyKpEH3nfI5djp4ITfI08ncJxdH1lrdYDs2qgaNdJEACJEACJJBFBHToJK0CeO3atRgyZAh++OGHFJHJi3Fjx45FkyZNsgipNZbVEVhreJayFesPn0KVHS/g9tPbTR0ecb6JatVrsRqElYNH20iABEiABEggkwno0EnaBPCECROU+JUyaNJy5cqFO+64Q/3/yZMn8c8//6j/lxPhN998EwMHDsxknNZZTkdgreNdypb8vHEe7v6qv+mbs+KaYlxcGyzqUp2pEFYPIO0jARIgARIggUwioEMnaRHAe/bsQY0aNZT4bdSoEUaOHInq1aubMEmfUaNG4dNPP1Ui+Ouvv0a1atUyCaW1ltERWGt5aLZGcoEfn7QBa5ydkMt2PfGbf7tuRe2Y6bg9IjtTIawcQNpGAiRAAiRAAplIQIdO0iKA27Rpg8WLF+PZZ5/Fe++9lyai5557Dh988AFat26NRYsWZSJO6yylI7DW8e5mS4xqEG+GzcYzYV+aOrSPeRk7EirwZTgrB5C2kQAJkAAJkEAmEtChk7QI4KJFi6o0hxMnTqBgwYJpIvr7779RuHBhFCpUCOJgMDYdgbUyR0MAR4Ycwcfhr5tMXR5fG1GxPSiArRxA2kYCJEACJEACmUhAh07SIoCzZcuGHDly4Pz58x7hyZs3L65evYobN2541D/QOukIrJUZGeXQzkRfw9bwfihiO5do7jWXA00d87A66lG+DGflINI2EiABEiABEsgkAjp0khYBLGXOLl++rH7dcsstaeK5du0a8uTJg9y5c+Ps2bOZhNJay+gIrLU8vNka42W4qLAl6B1mfgXu87uGo1G7KKu7QPtIgARIgARIgAQygYAOnaRFAD/yyCPYvHkzJk6ciP79zTf9k3OaMmUKBgwYgAYNGmDjxo2ZgNF6S+gIrPW8vNkiSYXYuXsXtjjMFUC+ji8L13NrWAnCH4JIG0mABEiABEhAMwEdOkmLAF64cKG6ABcWFqbq/Pbp0wd2u92EJy4uDjNmzMDgwYMRHx+vLsK1bdtWM0JrTq8jsNb01GyVkQox8/pg3B/yq+mbT4XPxHtRzzANwh8CSRtJgARIgARIQCMBHTpJiwAWBk888QTWrFmjSpzdeuutqF27trrsJr8XR3bs2IGLFy+qUmnNmjXDypXmj8E1crTc1DoCazknUzFIUiHWzn8Db9jnmnpMjWuBs1UG8FEMfwkk7SQBEiABEiABTQR06CRtAtjpdGLQoEF4++231QmvNBG/0ozHMUJDQ9GzZ0/1EIbD4dCEzfrT6gis9b3+z8L/fXoAnXc9gmy22MQv/uXKhzrOKVjYpQZTIfwpmLSVBEiABEiABHxMQIdO0iaADd/F6OXLl2P//v2Jl9zkklyVKlXQokULFClSxMeY/G86HYH1FwpGGsSQaxPxROhOk9ntY4bi91xV+CiGvwSTdpIACZAACZCABgI6dJJ2AayBQ8BNqSOw/gLJqAlcK+QwFoaPNZn9SXwt9I/tyZrA/hJM2kkCJEACJEACGgjo0EkUwBoC5e2UOgLrrQ1Z1d8QwDYkYLvDXBP4hsuOqs638UTkvcwFzqoAcV0SIAESIAESyGICOnQSBXAWB1WW1xFYC7jlkQlGCsTp6BvoG7oUfcM+MY0bbeuKck37osUDTJXxCCg7kQAJkAAJkECAEdChkzIsgDt16qQwy1PGY8aMUf9vfM0b/nJBbu5ccyUAb8b7c18dgfUnHsajGEVtp7HdYa4bfSChNFrEvIZFXarzMpw/BZW2kgAJkAAJkICPCOjQSRkWwCEhIaq6wz333IMjR44oV42vGdUe0vJfxko/+a9RLcJHvPxmGh2B9Rvn/99QIxXi4/DRiAz5wWR+w5gJuJqrFC/D+VtQaS8JkAAJkAAJ+ICADp2UYQH8/PPPK/EqJ8BvvPGGctP4mrc+z58/39shAdFfR2D9DYyRClHrygZMtM8ymT8rrinGxbXhZTh/CyrtJQESIAESIAEfENChkzIsgH3gV9BPoSOw/ghVUiE6z9mKvY4eyGm7kejCaVce1HRORzxCmQrhj4GlzSRAAiRAAiSQAQI6dBIFcAYC4quhOgLrK9sye54VB/5CyOpeaI4vTEs/HzMI21z3o2BENqZCZHZQuB4JkAAJkAAJZCEBHTpJiwB+7bXXkDNnTgwYMMAjXNOmTcOlS5cwfPhwj/oHWicdgfVXRpIL/OPuDVjmeM3kwrr4augZ2099rX1kMZZF89cA024SIAESIAES8JKADp2kRQDLJbiCBQvi5MmTHrlYokQJHDt2jJfgjh8P+pfx/r0M9ye+CB+AEiGnE/eP0xWG6s7/4RJyUQB79FPFTiRAAiRAAiQQGAQogAMjjjd5oSOw/orKuAzX8urHGBi2xOTGyNjnsCHnE0yB8Nfg0m4SIAESIAESSAcBHTrJEifAuXLlQkJCAq5evZoOLP4/REdg/ZmKXIaLmrMeXzn6IMTmSnTlu4Ti2FhnCfo3vMef3aPtJEACJEACJEACXhDQoZOyVABfvnwZUvpMcoXLlSuHw4cPe4EjcLrqCKy/05FUiEf2v4gHQ817orFzLF7t/DQfxfD3ANN+EiABEiABEvCQgA6d5BMBPGrUKMjFN6MZD1t46Jfq9uqrr2LkyJHeDAmYvjoC6+9wJBXizQljMDruLZMr8+Ma4d0c3ZgG4e8Bpv0kQAIkQAIk4CEBHTrJZwJYRLDRjNfdPPHLbrejXbt2mDVrFsLDwz0ZEnB9dAQ2ECB9/dMJlF1UBblt1xLduejKiUjnDLSKLM1KEIEQZPpAAiRAAiRAAm4I6NBJPhHAf/75J/744w9lvpz+PvTQQ7jtttuwfPnyVF2SShERERG4++67ccsttwR18HUENlCAfjOrCyr9vdTkTp+YXlidUJOPYgRKkOkHCZAACZAACaRBQIdO8okATm5z8eLFUaBAAezevZsB9YCAjsB6sKzlu0gaRI+JC/B+bJTJ1q/iy+HZuFf4KIblI0gDSYAESIAESCDjBHToJC0COOOuBtcMOgIbCAT/rQl8DKvCh+G+kN9NLj3onIxjrgKsCRwIgaYPJEACJEACJBAIJ8CMoncEKIBT5mUI4Lahm/GGfa6p0//immFCXGsKYO+2GnuTAAmQAAmQgN8R0KGTtJwAb9iwAa1bt0a9evWwYsWKNEG3bNkSX3zxBZYtW6Zyh4Ox6QhsIHA0HsW4Gn0Bu8J7IrvNmejWGVcetHS8i8+iHkIOR1gguEsfSIAESIAESIAEUiCgQydpEcDPP/88PvjgA3z00Ud4+umn0wymCF/p07lzZ7z77rtBGXgdgQ0UkPIoRts5uzE+7B08HbbV5NaqeyfiidYvBIqr9IMESIAESIAESMCfBXDZsmXx888/49KlS8iZM2eawTx//jzy588PGfPdd9+lO/By0jx+/Hj1mIaUU6tduzbGjBmDihUrej3nunXr8Pjjj6tx27dvV3Mlb06nE9OmTcPChQvxyy+/ICwsDCVKlMBzzz2H/v37e7UmBXDauCQV4sjuTVjhMNeJ3hR/P7I/t4yPYni129iZBEiABEiABPyLgA6dpOUEWJ42djgcOHfunEeEpRxaaGgoLl686FH/5J3mzp2LLl26oHz58ujWrRtEnM6YMUOtv2PHDtx3330ezxsdHa1epRPxfuXKlRQFsPRp1KgRvv32W3To0AGVK1dGTEwMfv/9d8TGxiph7E3TEVhv1rd6X5UKMelLvHejD+4OOZFobrzLhicds/FRVAumQVg9iLSPBEiABEiABNJJQIdO0iKARdDGx8fj6tWrHrmaI0cO1c/T/kknFdEsZddkze+//179V5rAklPlSpUqYdu2bR7ZIZ26d++O9evXq7SMSZMmpSiAJV1j8eLFSlzL/BltOgKbUZusNl5SITbPH4FX7R+aTJsY2wqXqvbloxhWCxjtIQESIAESIAEfEdChk7QIYDlB/fHHH3Hw4EG3KQhyinr//ffjrrvuwk8//eQ1qgULFqBjx47qGeURI0aYxsupsJwOHz16VIlkd23r1q2oX78+Vq1ahf3790Net0ueAnHs2DGULFkSvXr1wpQpU5CQkKCEu5x6p7fpCGx6bbHyuLfX70Gn3Y3hsMUlmnk8IT8ejJmMhV1qMBXCysGjbSRAAiRAAiSQTgI6dJIWAdynTx+VgiB5tKtXr07VXXk1rlmzZurEVVIXZs6c6TWaF198UT2jLJUnGjZsaBo/b948dblOTmvdXca7fv26Eutyort06VIlqFMSwLNnz1a2irD+6quv1EU/GZs3b16V/yt5x9myZfPKDx2B9coAP+hsVIQYem08mobuMln8bMzL+C1XVWwcUJepEH4QS5pIAiRAAiRAAt4Q0KGTtAhgyYUtU6YM4uLi0Lx5c5VKkPwEVp5OHjBgAFauXKkukMkFOHkW2dvWtGlTrF27FkeOHFFrJm0iiiVXV9aXtdJqgwYNwpw5c9Q8hQoVSlUAywU3OfmVi3vy3LOMk4t+UvVCLs89+uij+PTTT9NcS3KI5ZfRTp06hWrVquH48eMoUqSItwiCor9RE7hWyGEsDB9r8nltfCR6xfZhTeCg2Al0kgRIgARIINgI+I0AlsBISTM5KbXZbOrXvffeizvvvFPF7M8//1QpEnICLL/k5Fdyb9PTGjRogC1btuC3335TqQlJm+T+1q1bF6NHj8awYcNSnX7fvn2IjIxUdnTt2lX1S+0E2EirkFxjEfpy8ms0qXssaRQpnUYnXdyYO7lBFMCp7wBDANuQgK3h/VEs5Gxi5xhXKKo7/4cmkeWZC5yeHyKOIQESIAESIAELE/ArASwc5XS3b9++6mQzpVasWDF1miqnxOltGT0BlqoNUsUhd+7c6rKciPW0BHDv3r1Veke7du3w4YfmC1nz589Hp06d8NJLL2HcuHGpusQTYO+jbaRAnI6+gRdDVmKQfYlpkom251Cy6WC0eIAn6N7T5QgSIAESIAESsC4BvxPAglKqQWzevBlff/01Tp8+regWLFgQNWrUUC+/SfmzjLSM5gBPnjwZUVFR6uJb0hQKKWU2ffp0fPzxx0ogy+m13W5XtYZF4MqYiRMnmkz/7LPP0LhxY7zwwguQXGFPm47Aerq2P/UzHsUogAvY6eiNUJsr0fxfEgqjYcx4LOoSyctw/hRU2koCJEACJEACbgjo0ElacoAzM5LGqatcWBs+fLhpaSNdQVIV5JGKlFq/fv0wdepUtybLYxelS5dWp8SSViGX6uRyXdJmXJCTdAtJu/C06Qisp2v7Wz8jFeJd+0Q0DD1gMv+pmJE4masiL8P5W1BpLwmQAAmQAAmkQUCHTvJ7ASx1gOV0VlIYUqoDLI9gSCkzaZcvX4ZcOMuXL5/6JU3KsIm4Td6WLFmiqkGIkJX8ZTnZlXrFUvZMLuudPHlSlW0rWrSoGioX/iSPWMqnyWm3/L+nTUdgPV3bS+NKfwAAIABJREFU3/oZqRDlr3yFd+2TTOYvjXsQg+K68zKcvwWV9pIACZAACZAABbD3e8A4eTVegpNX2SR94ezZs0r8Sp1haUbNYKkXLBfR0mqpXYKTMZLS8dhjjykR3aNHD1UFQsqh7d692+v0B5mPAti7mEsqxLNzdqo0iAK2S4mDr7vCUd05A9HIiUVdqjMVwjus7E0CJEACJEACliSgQydpPQG+ceMGli1bpl5MkxNTeTBCqj6k1OTymQjL9DZZZ8KECTh8+DDCw8NRu3ZtVZM36TPIvhLAYqOIXRHJctordYDvueceVUGiZ8+eiRfpPPVFR2A9Xdtf+6048BfOr34VL2CFyYWRsR3wfsKjKBiRjakQ/hpc2k0CJEACJEACSQjo0EnaBLCUA2vTpo26+Cai16iuYAhg4/fin/F9uTAXjE1HYAOdo+QCf7FrP7Y7+iEkhctwgI2pEIG+CegfCZAACZBAUBDQoZO0CGB5elhOXq9cuaIqK8gLbVJVQVIF5NKZiGKjdq+kEUi9YHkMI/lTxkERVaZApCvMxmW4ufYJaBB60DTHM85XsdtVhgI4XWQ5iARIgARIgASsRcBvBHCvXr3UoxLyKpqUF5PyYSEhIar8maRCGE1yd6WvCGR5RS1Ym47ABjpL4zJcuSs7McduLke3Jr4GxmYfxBSIQN8E9I8ESIAESCAoCOjQSVpOgKVqglRW2Lt3Lx544AEVnJQEsHxd8naHDBmiHpeQmr7B2HQENhg4ymW49nO+xjZHPxSxnUt0WV6Gm1dtHbo3qREMGOgjCZAACZAACQQ0AR06SYsAllQHqcTgdDoTc3/lwYs8efLg/PnzpiD9888/uO2221ClShV1oSwYm47ABgtHSYXIvXfaTS/DjYttjQc7jmEliGDZCPSTBEiABEggYAno0ElaBLDU5BXBe+HChcRgREREqGoJUhki+etvefPmVRfhkvYP2Cim4JiOwAYLP0mFaD3pE3zi7Aa77b9LlMdc+dHG8TY2RNVHDkdYsOCgnyRAAiRAAiQQcAR06CQtAljq8f7www+q7Fm2bNlUIMqVK4cff/wR+/btS6zLK1+XxyluvfVWOBwOJZCDsekIbDBxlFSIi++1QZPQPSa3n4t5CUWrNcXrzSsEEw76SgIkQAIkQAIBRUCHTtIigFu1aoUVK1bg0KFDSvhKkxq5c+fORevWrbFw4cLEwPTp00fl/4polv7B2HQENtg4Llv6IZ76vqfJ7Q3xldE1NoqPYgTbZqC/JEACJEACAUVAh07SIoDnz5+Pzp07q4cihg8froJw8OBBVK1aVaU6lC1bFhUrVsR3332nfkmbOHEi+vfvH1AB89QZHYH1dO1A6KcqQkz6Egtv9ELJkFOJLsW7bKgTMw2IKMyKEIEQaPpAAiRAAiQQlAR06CQtAlieIB48eDBKliyJV199NTFYUgs4KioKyR+8ePrpp9VTwkkfxwimCOsIbDDxM2oCdw5dh1ft/326IAymxrXA5LinWBM4mDYEfSUBEiABEggoAjp0khYBnBZ1yQOWZ4uPHz8OuSzXqFEjNGjQIKAC5a0zOgLrrQ3+3N8QwHnwD3Y7esFhi01057QrD2o5p6F1ZEnmAvtzkGk7CZAACZBA0BLQoZMyXQAHbfTScFxHYIOJs/EoxunoG5gQNhMtQ3eY3B9gG4jRQ15mNYhg2hT0lQRIgARIIGAI6NBJWgSwPH4h6QxLly5VaRBsaRPQEdhgYy6VINrO2Y0HbD9jhWOkyf1t8RUQ9txK1gQOtk1Bf0mABEiABAKCgA6dpEUAS+mz8PBwREdHBwR43U7oCKxum604/7+pEH/i0/CXUSbkmMnEVuH/w4Ko1jwFtmLgaBMJkAAJkAAJpEFAh07SIoBLlSqFM2fOQF55Y3NPQEdg3a8aeD2MVIiHr6zBaPt8k4Oz4h7HX1WGMA848MJOj0iABEiABAKcgA6dpEUA9+jRA++88w527tyJ6tWrB3hYMu6ejsBm3Cr/nEFSIbrO+QK7HT2Rw+ZMdOKCKydqOGdgfpc6TIXwz9DSahIgARIggSAloEMnaRHAJ0+eRKVKlVC4cGFs3LgR+fLlC9KQeea2jsB6tnLg9ZJT4DpvbsHAmFloF7bZ5OCg2G74Kmcj1gQOvLDTIxIgARIggQAmoEMnaRHA27Ztw08//aRq/trtdnTo0AE1atRA/vz5ERoammqIHnzwwQAOX+qu6QhsUIIEYJREu9d2DJ85hpgwHE4ojqYxY9A+8k6mQgTrBqHfJEACJEACfkdAh07SIoBDQkK8ftRCqkbExcX5XVB8YbCOwPrCLn+cwxDAYvvi8NdQPeRHkxstnCNRtvrDFMD+GFzaTAIkQAIkEJQEdOgkbQI4PRFKSEhIzzC/H6MjsH4PJZ0OJK0J/KhtF2aGTzPN9Clq4Xqz2WjxQJF0rsBhJEACJEACJEACmUlAh07SIoAzE0ogrKUjsIHAJb0+GDWBwxCH7Y5+KGS7kDhVrCsUNZ3TMLXLo7wMl17AHEcCJEACJEACmUhAh07KsACWfF+p+RsZGZmJKAJrKR2BDSxC3ntjpEL0Cv0EA+1LTRNMiWuJJTna8TKc91g5ggRIgARIgAQynYAOnZRhASz5voUKFcKJEycSgXTq1Al58uTBW2+9lemQ/HFBHYH1Rw6+tNlIhYiLPo0d4b3hsP2XX37GlQe1nNPwTGRJ5gL7EjrnIgESIAESIAENBHToJJ8I4IIFC0JKnxlNRHHyr2ngETBT6ghswMDJgCNGKsRb9ploEbrDNFPvmF5Yk1ATi7pUZypEBhhzKAmQAAmQAAnoJqBDJ2VYAOfMmVNVb7h27RpE+EqjAPZuK+gIrHcWBG7vFQf+woo1q/Cha6jJyX0Jd+Pp2JEoGJGNqRCBG356RgIkQAIkEAAEdOikDAvgqlWr4sCBAxgwYAA6duwIEcTFixdXNX/37dsHl8vlMfpixYp53DeQOuoIbCDxyYgvRi7wyvBhqBTyu2mqJs4x+N5VAu0jizEVIiOQOZYESIAESIAENBLQoZMyLIBnzZoFefpY6vgaTURv0t97woR1gIvi+PHjKFKE5bk82S+e9jEE8JMh2zE5/G3TsCVxdTE4rhsFsKcw2Y8ESIAESIAEsoCAJQWwcBg7diymTJmCs2fPZggL6wBTAGdoA6Uw2LgMdzH6H3UZLp8tOrGX02VHdecMTHquPhqUKeDrpTkfCZAACZAACZCADwhYVgAbvokAllzgEiVKqBSIPXv2eOX2nXfe6VX/QOmsI7CBwsYXfhiX4aLClqB32ErTlONiW2N1zqeZB+wL0JyDBEiABEiABDQQ0KGTMpwCkZKfvATnXfR1BNY7CwK/t6RCbNp1EDscfRFm++/Fwb9c+fCgcwraRhZnHnDgbwN6SAIkQAIk4IcEdOgkLQJ469at6nGMGjVq+CHmzDdZR2Az3wtrr2ikQrx6bRweCzV/MtE1pj82JFRlSTRrh5DWkQAJkAAJBCkBHTpJiwAO0vik220dgU23MQE8cPOR05j9wQdY7Bht8vKr+HJ4Nu4VlkQL4NjTNRIgARIgAf8loEMnUQBbYD/oCKwF3LKcCf9WhPgTn4YPQZmQ4yb7GjnH4SdXMVaEsFzUaBAJkAAJkECwE9ChkyiALbCrdATWAm5ZzgSjJFrr0C0YZ59jsm9xXD28FNeVAthyUaNBJEACJEACwU5Ah06iALbArtIRWAu4ZTkTjDzgy9GX8VV4b9xqu5Joo5REaxzyNtYMeRI5HGGWs50GkQAJkAAJkECwEtChkyiALbCbdATWAm5Z0gSjJNrAsMXoFbbKZOPk2Jao3nE8apbOZ0nbaRQJkAAJkAAJBCMBHTqJAtgCO0lHYC3glmVNkFSIDbu+xQ5HH4Tb4hPtPOeKwFOO2VgX1ZCnwJaNHg0jARIgARIINgI6dBIFsAV2kY7AWsAty5pgpEIMuvYWWoTuMNk5KLYrHFU7sCawZaNHw0iABEiABIKNgA6dRAFsgV2kI7AWcMvSJkgqxJi5i7HOMdRk508JRdAo5k0s6hLJVAhLR5DGkQAJkAAJBAsBHTopUwTwmTNncOzYMfVM8oMPPhgs8fLYTx2B9XjxIO0op8B13tyCmbEjUCP0iIlCh5iX8WuuqnweOUj3Bt0mARIgARKwFgEdOkmrAF6xYgVee+01HD58WJG02WyIi4tLpHrx4kW0adNG/X7ZsmXImTOntYhnkjU6AptJpvvtMkZJtIdD9mNO+CSTH1/E34eOsS+xJJrfRpeGkwAJkAAJBBIBHTpJmwAeNWqUEr8ulysxBiKA4+P/u3Qk32jVqhVEKC9atAjPPPNMIMXLY190BNbjxYO0oyGAbUjAlvAolAg5bSLRwDkBNarXYC5wkO4Puk0CJEACJGAdAjp0khYBvG3bNtSrVw92ux2jR49G27ZtUbVqVUgqRHIBvHr1ajRv3lyJ348++sg6tDPREh2BzUTz/XIp4yLc6egbaBeyAaPtC0x+LMPDCGk2FS0eKOKX/tFoEiABEiABEggUAjp0khYBbJzqivgdOvTfS0aFChVKUQBfunQJt912G0qXLo2ff/45UGLllR86AuuVAUHa2agJnB038LWjF3LbriWSuOGyo4ZzOv7XpSEvwwXp/qDbJEACJEAC1iCgQydpEcCFCxfG33//jfPnzyNPnjxpCmD5Zu7cudXJ8JUr/73MZQ3kmWOFjsBmjuX+v4qRCjEk7CN0D1tjcmhSXCssz9GGl+H8P8z0gARIgARIwI8J6NBJWgSww+FA9uzZIZfcjJbaCbB8X06ApULEjRs3/Dg86TddR2DTb01wjTRSIWzRJ7A1vB/sSR7GOOPKg9rOqXg6shRzgYNrW9BbEiABEiABCxHQoZO0COD8+fMr8Xv9+nWVBywtNQF87tw53H777bjjjjsgDgZj0xHYYOSYXp+NVIip9hl4InSnaZoBMd2xIuFBLOpSnakQ6QXMcSRAAiRAAiSQAQI6dJIWAfzQQw9h69at+PLLL1GnTp00BfDEiRMxePBgNGvWDCtXrswAHv8dqiOw/ksjayxfceAvLF+zGgtdL5sMOJJwJx6PfQMFI25hKkTWhIarkgAJkAAJBDkBHTpJiwCeNWsWevTooR692LRpE8LCwlI8Ad6yZQuaNm2qUh8+/vhjVRItGJuOwAYjx4z4bOQCLwkfhWohP5mmahszFDsTyrMucEYAcywJkAAJkAAJpJOADp2kRQDLYxdS9uzQoUOIjIxEnz590KtXL1y4cAFHjhzBd999h6VLl2L58uXq8lvt2rUhpdOCtekIbLCyTK/fhgBuFLIH74RPMU2zLb4COsS+TAGcXrgcRwIkQAIkQAIZIKBDJ2kRwOLjqVOn0KRJE3zzzTfqBbiUmjySUblyZaxfvx6SNxysTUdgg5Vlev02LsOdjb6GjfabH8Zo4hyDAR1aoUGZAuldguNIgARIgARIgATSQUCHTtImgMW/mJgYSDrE3Llz1alv0lfhypQpg86dO6Nnz56QqhHB3HQENph5ptd34zJc29DNeMM+1zTN6vgaGJd9EPOA0wuX40iABEiABEggnQR06CStAjipn1LjV2oDS8pDgQIFEusDp5NFQA3TEdiAApSJzkgqxNJdv2KHow/y26ITV4532VAv5i3UrV6VJdEyMR5cigRIgARIgAR06KRME8AMX+oEdASWvNNHwEiFaHHlYwyyLzFN8n5cQwyP68iSaOlDy1EkQAIkQAIkkC4COnQSBXC6QuHbQToC61sLg2u2zUdOo//7X2Know9y2v57nEWeR64dMx3hEbczFSK4tgS9JQESIAESyEICOnRShgWwL6s3SNm0YGw6AhuMHH3ls1ERYmjYQnQNW2eadmrck5gc14oVIXwFm/OQAAmQAAmQgBsCOnRShgVwSEhIqlUevImoVIqQ8mnB2HQENhg5+spnQwAXwAVsd/RFeJLnkS+5cqCmczpaRN7NXGBfAec8JEACJEACJJAGAR06yScC2FdRS0hI8NVUfjWPjsD6FQCLGWvkAZ+OvoFxoe/g6bCtJgtfi30Wtdq/ypJoFosbzSEBEiABEghMAjp0UoYFcGCizlyvdAQ2cz0IvNWMkmilbCew2THI5OAJV160dryNz6IaIIcjLPCcp0ckQAIkQAIkYCECOnRSwAjgFStWYPz48Th8+DDCw8PV63JjxoxBxYoVvQ7hunXr8Pjjj6tx27dvV3Ol1Z566in1ql2pUqXw66+/er2ejsB6bQQH3ETASIV41z4JDUP3m77fP+ZF5KjWjmkQ3DckQAIkQAIkoJmADp0UEAJYHtro0qULypcvj27dusHpdGLGjBk4d+4cduzYgfvuu8/j0ERHR6NcuXK4dOkSpHaxOwH8ySefoFWrVkp033HHHRTAHpO2fkcjFeKO6ENY7hhpMvjHhKJ4NGYcFnWJRM3S+azvDC0kARIgARIgAT8l4LcCWETlwYMHcebMGXVhTp49vv/++xEREZHhUFy8eBHFixdXc33//feJcwqssmXLolKlSvCmUkX37t3V08xPP/00Jk2alKYAFpEsazzzzDMQIRwWFkYBnOGIWmsCKYnW+f19WBI+CtVCfjIZ1zl2EH7IWYMl0awVMlpDAiRAAiQQYAT8TgCL6B02bBg+//xz0zPIEhcRwo0bN8bo0aOVSE1vW7BgATp27IiRI0dixIgRpmnkVFhOh48ePapEsru2detW1K9fH6tWrcL+/fsxatSoNAVwp06dsHnzZhw5ckSdGlMAuyPsf9830iAeCjmAeeETTQ7sTrgXz8QMZ0k0/wsrLSYBEiABEvAjAn4lgD/66CMlTGNjYxPFr8PhULglRcFokjogIrZ169bpCsWLL76IWbNmYcOGDWjYsKFpjnnz5qFz585YvHixOtFNq12/fl3lC4sYX7p0qRLUaQngjRs34pFHHsHatWvRpEkTJbApgNMVQksPMgSwDQn4PPwl3B1ywmRvC+dI5ChdEx90rm5pP2gcCZAACZAACfgrAb8RwD/99JMSkyJ+K1SogKFDh+Lhhx9G3rx5Ffvz589j06ZNGDduHL799lvY7XYcOnQI99xzj9exadq0qRKhcgpbpkwZ03gRxY0aNVKpDAMGDEhz7kGDBmHOnDlqnkKFCqUpgK9evaryjatXr46PP/5YzeuNAJaUEPlltFOnTqFatWo4fvw4ihQp4jUDDtBHIGlJtCdt2zApfJZpsS3xldApdjCfR9YXAs5MAiRAAiQQ5AT8RgBL6oGcvor4lHQCOeVNqYlAbtasmUqRkJPad9991+sQN2jQAFu2bMFvv/2GkiVLmsZL7m/dunVVmoWkYqTW9u3bh8jISMycORNdu3ZV3dI6Ae7bty8++OAD/PDDDyhQoIDXAtiYO7k9FMBehz9TBhgl0eyIw5eO/ihsO29at1nM6ziXqyxzgTMlGlyEBEiABEgg2Aj4jQAWIfrnn3/il19+uUmUJg+aCNe77roLd955p8rV9bZl9ARYRHjlypWRO3dudVlOcpPTEsBff/21Kov2zjvvqMoTRuMJsLeR86/+RirEs6EbMNq+wGT85/FV0C12AHOB/SuktJYESIAESMBPCPiNAL7lllsgvy5cuOAR2ttuuw2Sgyu/vG0ZzQGePHkyoqKi1El10hSKadOmYfr06SrFQQSyCHRJ1ZCSavJindQdNsSy2FyvXj2EhoaqS3Hie+HChT12RUdgPV6cHT0iYKRCXIyOxrbwfrjddsk0rpFzHH5yFWMqhEc02YkESIAESIAEPCegQydpqQMsgvbatWuqjq5cDEuryQlsrly5kD17do8Fc9L55s+fD6nGIBfWhg8fblrKqALx+++/o0SJEima0a9fP0ydOtVtFOQ0u3Tp0siTJw8uX76cZv9atWqp+sOeNh2B9XRt9vOcgJEK0Tl0HV61LzQNXBMfib5xfVAwIhtTITxHyp4kQAIkQAIk4JaADp2kRQDXqVMHO3fuhIjTDh06pOmY5NI+99xzENEoj05426QOsJzOSgpDSnWA5cTWmFeEq1w4y5cvn/olTS7hibhN3pYsWaKqQUj+8L333qtKtuXIkQOrV69GTEzMTf179OihToDl1FjmlhNhT5uOwHq6Nvt5R+DZubux75e/sMPRF3lt/yQOTnDZ0DBmPH5zFWYqhHdI2ZsESIAESIAE0iSgQydpEcBymaxXr15KMEqJs5YtW6bo2MqVK5VAlqoK8nKbpDOkp82ePVu9AGe8BCcCVYTo2bNnlfiVRzekGTWDpV6wXERLq7krg5Z8rDc5wMnH6ghsejhyjHsCRi7wi6Gr8ZL93wogRlseXxtRsT0ogN1jZA8SIAESIAES8JiADp2kRQDHxcVBToF3796t8mTltTSp1iB5sfJ7cUQqN8iJrcvlUhUYRKjKCWp627JlyzBhwgQcPnxYVZ2Qi2pjxowxPYNMAZxeuhxnEDByga9EX8T28D7IY7uaCCfOFYKHYiZhRIcmaFDm3+ogbCRAAiRAAiRAAhkj4DcCWNyU1ARJbZAavdKSXhiT34vwlSZl0CRV4tZbb80YHT8erSOwfozD8qYbucB9QldggH2Zyd7FcfUwNUcf5gFbPoo0kARIgARIwF8I6NBJWk6AkwKVsmGSTytPC0tKgrT8+fOjSpUq6nU2Of0N9qYjsMHOVLf/kgqxetcP2OHogwjbf9VLYl2hqOd8C/UjK+P15hV0m8H5SYAESIAESCDgCejQSdoFcMBHxQcO6gisD8ziFGkQMFIh2l99Dz3DVpl6vh/XEMPjOrIkGncQCZAACZAACfiAgA6dRAHsg8BkdAodgc2oTRzvnsDmI6cx8P0tqiJEDpszcYDTZUfdmCkIiSjEVAj3GNmDBEiABEiABNIkoEMnUQBbYNPpCKwF3Ap4E4yKEC+HLUS3sHUmf+fGNcbouGdZESLgdwEdJAESIAES0E1Ah07SKoAvXbqEdevWqcoMcilOHr1Ircklublz5+pmaMn5dQTWko4GmFGGAM6PS9ju6Itstv/293VXOGo7p6JxZAXmAgdY3OkOCZAACZBA5hLQoZO0CWB5Snjo0KGm542Nyg9JsYnwla/Lf+Pj4zOXqEVW0xFYi7gW0GYYecCno2/g1dD30DHsc5O/i0Kb4YnB85HDkfZriAENic6RAAmQAAmQQAYJ6NBJWgTwe++9h44dOyp35ZljqfRQoEABt3V+pRxaMDYdgQ1Gjlnhs1ESrSDOY6ujPxy2uEQz4kMdCO13CMhVMCtM45okQAIkQAIkEBAEdOgkLQK4UqVKKu3hiSeewIcffojs2bMHRAB0OaEjsLps5bw3EzBSIUaHzcOzYZvMHap1Ax4bT2wkQAIkQAIkQALpJKBDJ2kRwLfccgvkOeIzZ84gb9686XQ3eIbpCGzw0Mt6T41UCESfxJfhcgqcJNc9NBzofQDIUzTrDaUFJEACJEACJOCHBHToJC0C+I477sCNGzdw4cIFP8Sc+SbrCGzmexHcKxqpEMPCPkCXsE/NMCo/DzSdGtyA6D0JkAAJkAAJpJOADp2kRQC3atUKn3zyCU6ePInbb789ne4GzzAdgQ0eetbxdP3hUwi/cR4Pb2gIxF77z7CQMHzR8FNcz1kUj1UoZB2DaQkJkAAJkAAJ+AEBHTpJiwA+cOAAatWqhWeffRazZ8/2A7RZa6KOwGatR0G++qaRwI7JJgjL4h/EwNjufB0uyLcG3ScBEiABEvCegA6dpEUAi2urV6/Gc889hypVquCll15ChQoVVCUItpsJ6AgsOWchgWsXgCkVgZh/Eo2Id9nQKHY8ruUqxdfhsjA0XJoESIAESMD/COjQSdoEsDx6MXLkSIwdO1bV+HXXpE9c3H8lpNz1D6Tv6whsIPHxS1++GAtsHWcyfU18JHrH9uHrcH4ZUBpNAiRAAiSQVQR06CQtAjg6OhqNGzfGrl271CMXnjQ+hFEUx48fR5EiRTzBxT5WJ3DjMmLfqgB7zGWTpY86x+FHVzGmQlg9frSPBEiABEjAMgT8RgAPHDgQb731FsLCwtChQwc8/PDD6jJcaGhomjDr1q1rGdiZaYiOwGam/VzrZgJSGu2D8X3wYvxC0zc/j6+CF+MGoGBENqZCcOOQAAmQAAmQgAcEdOgkLSfAJUqUwLFjx/Duu++iU6dOHrgW3F10BDa4iWa99/I4xopdP2Obox/y2aJNBj3ufB3fuUoyFSLrw0QLSIAESIAE/ICADp2kRQDLy28JCQm4cuWKOgVmS5uAjsCSedYSMF6H6xy6Dq/azafAX8Tfh46xL1EAZ22IuDoJkAAJkICfENChk7QI4Lvvvht///03JBeYzT0BHYF1vyp76CRgvA53KToaX4b3QwHbJdNyHW2voWnTlmjxAHO+dcaBc5MACZAACfg/AR06SYsAfvnllzF+/Hhs374dNWvW9H/ymj3QEVjNJnN6DwgYr8O1D92I1+3zTSP2JtyNVjEjsKhLJGqWzufBbOxCAiRAAiRAAsFJQIdO0iKAr169iurVqyM+Ph5r165FqVKlgjNiHnqtI7AeLs1umglIKsSSXb9hiyMKRWznTKt1iY3CkZy1eBlOcww4PQmQAAmQgH8T0KGTtAjg999/H5cuXVJ1gEUMP/XUU6hYsSIKFiyYZk1gqRgRjE1HYIORoxV9NlIhal7ZgEn2WSYTf0oogsYx49A2sjheb17BiubTJhIgARIgARLIcgI6dJIWARwSEpIodKUOMB/CSHvv6Ahslu9WGpBIQFIh2s/5GuvCX0aZkOMmMgNju2FZfF3WBeZ+IQESIAESIIFUCOjQSVoEcPHixT0Svcn9PHr0aFAGX0dggxKkhZ1eceAvfLHmA0x3mV+HO+HKiwYxk3BbRARTISwcP5pGAiRAAiSQdQR06CQtAjjrEPnnyjoC658kAtfqf8ui/YnF4aNRPeRHk6Ovx7bDnPgmLIv2mDXcAAAgAElEQVQWuOGnZyRAAiRAAhkgoEMnUQBnICC+GqojsL6yjfP4hoBRF/h+2y/4xDHCNOklVw486JyCZpFlmAvsG9ychQRIgARIIIAI6NBJFMAW2CA6AmsBt2hCEgLGZbjT0TcwM2wyHg3da+IzH08gd7M3WBeYu4YESIAESIAEkhHQoZMogC2wzXQE1gJu0YRkBIy6wKVsJ7AhfDBCba7EHk6XHQ85J2JCl8dZF5g7hwRIgARIgASSENChkyiALbDFdATWAm7RhBQIGKkQb4S9i7ZhX5h6rIqviTezD+RlOO4cEiABEiABEqAADvw9QAEc+DE2PDRSIRKiT2FL+ADksDlNzjdzjkbF6vWZCxw8W4KekgAJkAAJuCGgQyfxBNgC205HYC3gFk1IhYCRCtEndAUG2JeZeu1OuBfPxLzKJ5K5e0iABEiABEjg/wno0EkUwBbYXjoCawG3aEIaBKQu8IQ1B/BJQh8UtF009ewW2x+Hc9ZhKgR3EAmQAAmQAAkA0KGTKIAtsLV0BNYCbtGENAgYucCtQr/EBPtsU8/fEwrikZjxaP1/7Z0HmFNF98bfJLvZhaVJR+mINCkWEAHpqCD6YfmrFBUFUbAhCqIiiIAKFj7EggoiKvYGKipVBBsgn4ggRUBBpSudbcn9P2eWuyTZZDfZZHZvct95nn12N5k795zfmey+mZw507ouUyE4i0iABEiABGxPQIdOogC2wLTSEVgLuEUTwhDATnjxmfsBNHJu9+s9JusGbK3bF71b1USPptXIkgRIgARIgARsS0CHTqIAtsB00hFYC7hFE/Ih4FsXuI1jLd5wP+bX+yDS0CH9aRxAabw58DyWRuNsIgESIAESsC0BHTpJmwBesWIFlixZgvXr12P//v0qaOXLl0fjxo3RqVMnnHfeebYNZKDjOgJLuNYnYG6GE0tnJk9EJ9caP6NneS7E2Oz+qFomlfnA1g8nLSQBEiABEtBEQIdOirkAXrhwIUaMGIE1a/z/mQcyad68OSZOnIhu3bppwhU/w+oIbPx4b29LzVzg0x1/4gv3SCQ5vLlAsg0numc+js1GdfRrXZP5wPaeKvSeBEiABGxLQIdOiqkAHj9+PB5++GEYhqG+nE4n6tSpg4oVK6rfZSV469at6mdp8vzo0aPVl52bjsDamWc8+e6bCvGQaxZuTPrSz/yvPU1xfdZIAA6mQsRTYGkrCZAACZBAzAjo0EkxE8DTpk3DkCFDlLNNmjTBfffdh169eqFUqVJ+AA4fPoyPPvoITzzxBNatWweHw4GpU6fmXhszWnE0kI7AxpH7tjfVTIUoiyNYmjoM5XDEj8nAzHuw2DiHqRC2nykEQAIkQAL2JKBDJ8VEAO/evRv169fH0aNHcdNNN+H5559HcnJyvlHKysrC4MGD8corryAtLQ2//fYbqlSpYsvI6gisLUHGsdPz1u7EWyu2o9bWtzA+eaafJ9u8VXBR5iRkIpmpEHEcY5pOAiRAAiRQOAI6dFJMBPC4ceMwZswYtG/fHl999VVE3nXo0AHLly9XqRMPPfRQRNcmSmcdgU0UNnbyQ/KB3/p+myqL1tC5w8/1x7J640XPpRTAdpoQ9JUESIAESEAR0KGTYiKA27Zti++//x6yAU4qPETSFi9ejK5du+L888/HN998E8mlCdNXR2ATBo6NHDHzgesdXoU33I/6eX7ESMUVzim49dJ2uOLs6jaiQldJgARIgATsTkCHToqJAK5atara4JaRkaE2tkXSPB4PUlNTVYk0SaWwY9MRWDtyTASfzXzgF5OfxkWuVX4uzfG0wV1Zt3MzXCIEmj6QAAmQAAmETUCHToqJAE5JSUHp0qWxb9++sJ3x7ShVIo4cOYL09PRCXR/vF+kIbLwzsbP9kgqx9IeVWOgegRRHlh+K3pmj8Efps1kX2M4ThL6TAAmQgM0I6NBJMRHA5gqwCFiXyxVRWGQFWAS0iOBdu3ZFdG2idNYR2ERhY0c/zFSIa4++gbuSPvRDsMl7GnpkPoZrW9dlXWA7Tg76TAIkQAI2JKBDJ8VEALdr1w7fffcdFixYgM6dO0cUmkWLFqnDMNq0aaM2w9mx6QisHTkmks+SCnHj9GVY4B6Oms69fq6Ny+qLGZ5LmAqRSAGnLyRAAiRAAiEJ6NBJMRHAsagCMXbsWIwaNcqW4dcRWFuCTDCnP1z9J77+ZBb+a0zy8+ywUQJdM5+Eq0w1pkIkWMzpDgmQAAmQQF4COnRSTATwnj17cPrpp6s6wAMGDMALL7xQYCqEpD5IHeDp06erwzKkDnDlypVtGXcdgbUlyARzOueY5D8wI/lJdHH9z8+7jz1tMDTrdpZFS7CY0x0SIAESIIE4EsBiqoje2267TZ3sduaZZ+L+++/HpZdeqg658G0ikufMmYOJEyfil19+UU/xJLg/UaNGDezYsQPVq7PEFV/8OQRyBPB21HTsxoIgG+L6ZD4AV72OeH3AeURGAiRAAiRAAglLQMdCYUxWgE3ijzzyCCSVwWxSEq1evXqoUKGCekhKpW3ZsgVerxeGYSixLIdfyCEYdm46Amtnnoniu7kZbvehdNzleg93JX3k59pWb1V0z3wcMwdegDanV0wUt+kHCZAACZAACfgR0KGTYiqAxdr58+djxIgR+Pnnn/MNX7NmzfD444/j4osvtn2YdQTW9lATBIBZFzgFmZjvHoFazj1+nj2TfQXeTuvHXOAEiTfdIAESIAESyEtAh06KuQA2zZaT4ZYsWYL169erlV9pshLcqFEjdVqcnPzGlkNAR2DJNnEImKkQ7Z1r8Jp7op9jGUaSWgVuc15rlkVLnJDTExIgARIgAR8COnSSNgHMyIVPQEdgw787e1qdgG8qxH+TpuIy13d+Jn/naYzeWQ/iri71cXe3BlZ3h/aRAAmQAAmQQEQEdOgkCuCIQqCns47A6rGUoxYXATMVohIOYFHKvSjjOOZnyj2Zt+IDb3vMuOFcdGlUpbjM5H1JgARIgARIIOYEdOgkCuCYhynyAXUENnIreIXVCVw34wcs27wPfV0LMSH5FT9z/zFKoUvGk8hwn4KVD3ZFWkqS1d2hfSRAAiRAAiQQFgEdOinmAlhKea1evRpS57dp06aoX79+gc49/fTTOHLkCEaPHl1g30TsoCOwicjJ7j6ZucAOePGB+2Gc7fzND8lHnra4O+s21ga2+0Sh/yRAAiSQYAR06KSYCeBjx45h4MCBeOedd/ywyzHJU6ZMQYsWLUKGo1q1apDDNEQ027HpCKwdOSa6z765wGdgOz51P4Akh9fP7Rszh2OJ9ywek5zok4H+kQAJkICNCOjQSTETwN26dcPixYtVfd/A5na78dRTT6mDMoI1CmAehGGj13FUrpq5wDLI8KS3cVvSXL/x/jbK4+LMSXCVKIuHejbGFWfzYJWogPNiEiABEiCBYidgWQEsq769e/dGUlIS5DAMOQ65ZMmSqgyapDX89NNP6tALOfBCDr4IbLEQwB9++CEmTZqEtWvXQgS3rDxPmDABUm840vbZZ5+hZ8+e6rJly5apscz2119/4Y033sCXX36JjRs34p9//lGnuLVt2xYPPvigOhI60qYjsJHawP7xQ8BMhZDawPPc96Oec6ef8a9nd8VD2Tepx94ceB4PyYif0NJSEiABEiCBIAR06KSYrABfcskl+OKLLzBy5EglOn2bnPp2zz33qDQIEcHB+kQrgGfMmKHSL+QI5ltuuQUZGRl49tlnsW/fPixfvhzNmzcPe0IdOnQITZo0wYEDB1RecqAAnjZtGu644w5ceOGF6NChA8qXL68O/Xj55ZfVPUQYt2/fPuz7SUcdgY3IAHaOKwKSCtFqwkIcy/TgXMcGvJ/ySB77r854CCuMRji1bCoPyYir6NJYEiABEiCBQAI6dFJMBPCpp56K3bt3q6+KFYMfyfr8888r4Sjt7rvvxpNPPpnrXzQC+N9//0Xt2rVRpkwZrFu3Tn03RWXjxo1V7vHXX38d9my69dZbMW/ePFx99dUqbSNQAMs9ypUrh9NOO81vTDkB76KLLkLLli2xYsWKsO9HARwRKnY+QWDR+t0Y8Noq9dvYpJm4IWmBHxvzmOQMuLkpjrOGBEiABEggrglYVgCnpKSolAcRo/m1V199Va3USp7wkCFDMHXqVNU9GgEsY954440qvWLMmDF+t5d7yerwtm3blEguqC1dulSdUjdnzhz8+OOPGDt2bB4BnN8YshosmwHT09MLupXf8zoCG5EB7ByXBCYv2IQpizYjDccxP2UETnPknLhotpeze2BCdj/1K1Mh4jLENJoESIAESEDTJ+UxWQEuW7asSjsIR/hJ/qwIVkmNGDRoEF544YWoBPDgwYMhaQmyAisb8XzbK6+8ovKRJUdZVnTza8ePH1f5wrJi/N577ylBHYkAPnjwICpVqoSqVati+/btEU1YCuCIcLGzDwEzH7ij8ye86p7kx8ZrOHBN5kNYZTREuZLJWH5fZ9YH5uwhARIgARKIOwI6dFJMBPDZZ5+NNWvWqC/Jwy2ovfnmm7jhhhuUCO7fvz8+/fRTla9bmDJol156qbp+/fr1aNSokd+tzbQESWUYNmxYvmYNHz4c06dPV+PIinSkAljynKWesaxCy7X5Nckzli+z7dy5E61atYLUUK5enbv2C5o/fP4kAbM02s6D6Xgq+QVc6Vrmh+cPb2V0z3wcx5CKro0qY/oNLYmPBEiABEiABOKKgGUFsKzCvvTSS2oDnGxyC6e9/fbbuO6665QIlpQI2SBXGAHcpUsXVX5ty5YtqFu3rt+tJfdXNqqNGzcOo0aNCmnWqlWr0Lp1a0iesqxKS4tEAM+ePRv9+vVTIlbuKSkh+TVz7MA+FMDhzBz2CSRglkYrg6P4MuU+VHP849fltexuGJ19I0q6XTwljtOHBEiABEgg7ghYVgDPnTsXvXr1UgJ006ZNcDqdYcGVVIO+ffsiOzu70AI42hXgrKwsnHPOOZA0DhGvIsQjEcAffPABrr32WjRs2FAJcUmDKKhxBbggQnw+UgIfrv4T4z5dj+bpq/Cqe2Key/tkPoBvvWdyQ1ykYNmfBEiABEig2AlYVgBL/q/UzRUhK6vAbdq0CRvWxx9/nJuesHXr1rCvMztGmwM8efJkVaZNNr75plA888wzapOerFSLQK5VqxaSk5P97Hv33XeVgJdqEwsXLgxL/AZzUEdgIwbJC+KegLkS/GjSy+iTtMTPnz+Nirg443EcQUnc1eV03N2tQdz7SwdIgARIgATsQUCHTopJDnBx4p85cyZuuukmtWFNDt3wbWYVCBHWderUCWrm0KFDVY3igtrmzZv9DrmQPObrr79e1RhesGCBqgdc2KYjsIW1hdfFNwHZFPfR9xtVKkR1xz4/Z973tMe9Wbeqx2bccC66NKoS387SehIgARIgAVsQ0KGT4l4AS+k1WZ2VFIZgdYBFoEotX2lSqUE2nEmtYrNesWzcE3Eb2GR1V1I0JH9Y0hu6d++OtLQ01U0qWcjmPVkZloMvpC5wNE1HYKOxh9fGLwHzkIzm2T/jLbf/oTTi1ZDMOzHP25r5wPEbYlpOAiRAArYjoEMnxb0AllkgG/DkBDjzJLjMzEyVvrB3714lfs866yw1WcyaweFUagi1Ce6TTz5R+c5S93jixIm5B2/4zkbZEBdJ0xHYSO7PvolFYOCslVj46x6MSZqFG5O+9HPugJGmUiF2oQLzgRMr7PSGBEiABBKWgA6dlBACWCL+/vvv44knnsDatWvhdrvRrl07lY/sewxyLARwqAoOvrNOqlpE0nQENpL7s29iEZBV4AsmLsbxY0cx1/0gznD+5efgN54m6Jd1Pww4eUBGYoWe3pAACZBAQhLQoZNiIoBdLlfUwKX6gmyis2PTEVg7cqTPJwmYG+IaO37Hx+6H4HZ4/PBMyOqD6Z6ePCCDk4YESIAESMDyBHTopJgI4HDLnuVHuLB1gC0ftTAM1BHYMG7LLglOwDwlbpDrEzyQ/Jaft5mGC70yx2G9UZsHZCT4PKB7JEACJBDvBHTopJgI4FmzZoVke9ddd+Hw4cOQY4kLanI6nB2bjsDakSN99idgbog7npmF2cmPoo1rvV+HLd5quDRzAuBO4wEZnDwkQAIkQAKWJaBDJ8VEAOdHTI4V3rNnT6FOebNsJGJsmI7AxthEDhenBBat340Br61CNezHFyn3oazjmJ8nZmm0fq1rYnyvpnHqJc0mARIgARJIZAI6dBIFsAVmjI7AWsAtmmARApMXbMKURZvRw/k9nnc/k8equzMH4yPvBTwgwyLxohkkQAIkQAL+BHToJApgC8wyHYG1gFs0wUIEzHzgR5Omo0/SYj/LjhopKhViq3EqD8iwUMxoCgmQAAmQQA4BHTqJAtgCs0tHYC3gFk2wEAEzH9iTeRxz3A+hoXOHn3XrvbVweeZYuNwlmA9sobjRFBIgARIgAQrghJ0DFMAJG1pLOWYekHG640984h6FEo5MP/tez+6Kh7Jv4gEZlooajSEBEiABEtChk7gCbIF5pSOwFnCLJliMgHlAxoFjWbjK9RWeSH4pj4VDM4fgY2875gNbLHY0hwRIgATsTECHTqIAtsCM0hFYC7hFEyxIwDwgAzDw3+Tn0Mv1rZ+Vxw03emU+go1GTeYDWzB+NIkESIAE7EhAh06iALbATNIRWAu4RRMsSsDcEJeG45jrHoV6zp1+lm71VsVlmePhdZdmPrBFY0izSIAESMBOBHTopJgI4M6dO4eMwzfffKOOOO7QoUO+sZKT4BYtWmSneOb6qiOwtgRJp8MiYG6IO5bpgeQDy6a4NEeG37Wfe1picNZQ9Gtdi/WBw6LKTiRAAiRAAroI6NBJMRHAchSyCFjDMArtO49CroEdO3agevXqhWbIC0kgXALmARnS/zLnt3jG/WyeSydk9cHLnp4qH7hB1TLo0bRauMOzHwmQAAmQAAnEjIBlBXD//v2VAI62zZw5M9oh4vJ6HYGNSxA0ukgJmAdkyE3HJM3CjUlf+t3fYzjQP2sklnlzToh7c+B5aHN6xSK1kTcjARIgARIgAR06KSYrwAxNdAR0BDY6i3i1XQiY+cDJyMbb7nE4x7nZz/UDRprKB95uVMGpZVOxYFgHpKUk2QUP/SQBEiABErAAAR06iQI4QQNrAbdoQhwQ8M0Hror9+CTlQVRyHPKzfKO3Oq7IHIujKMEawXEQU5pIAiRAAolGgAI40SJ6wh8dgU1QVHRLAwHffOBzHRvwpnsC3A6P352+9JyLW7OGwoCTNYI1xIBDkgAJkAAJhCagQydxBdgCM05HYC3gFk2IIwK++cC9XYvwWPKMPNZPyb4Ck7OvUo/PuOFcdGlUJY48pKkkQAIkQALxSkCHTqIAtsBs0BFYC7hFE+KMgJkPLGaPT5qBfkl5yxLemXk75nrboKTbxRrBcRZfmksCJEAC8UpAh06iALbAbNARWAu4RRPijIDkA3d7eil2HkyHbIp7w/0oznNu8PMiw0hG78wHsdo4AxfUr4jerWqyPFqcxZnmkgAJkEC8EdChkyiALTALdATWAm7RhDgkcPKoZKCi4yA+dj+E6o59fp7sN0qr45J3GDkpECyPFoeBpskkQAIkEEcEdOgkCmALTAAdgbWAWzQhTgnMW7sTG3cdxpRFm9HQsR3vuceitOO4nze/eU/FFZkP4xBKoVrZVCxkebQ4jTbNJgESIAHrE9ChkyiALRB3HYG1gFs0Ic4JmDnBHZ0/YUbyE3A5/E96/MbTBP2z7kMWklgeLc5jTfNJgARIwMoEdOgkCmALRFxHYC3gFk2IcwK+NYKvc83HuORX83j0kacthmUNZnm0OI81zScBEiABKxPQoZMogC0QcR2BtYBbNCEBCPjWCA52XLK4OC27Jx7P7qO8ZXm0BAg6XSABEiABixHQoZMogC0QZB2BtYBbNCFBCJg1gp3w4qXkp9DV9b88no3L6ocZnh4sj5YgMacbJEACJGAlAjp0EgWwBSKsI7AWcIsmJBABMx+4BNLxlnsCWji35PHujszb8Ym3DcujJVDc6QoJkAAJWIGADp1EAWyByOoIrAXcogkJREDygbs89RV2H8rAKTiE991jUc+508/DTMOFAVnDsczbTD3O8mgJNAHoCgmQAAkUIwEdOokCuBgDat5aR2At4BZNSDACvjWCqzv24EP3w6jsOODn5XHDjesyR2KV0ZDl0RIs/nSHBEiABIqLgA6dRAFcXNH0ua+OwFrALZqQgASkRvBbK7Zj2eZ9aOz4He+4x+WpEXzIKIE+mQ/iF6Mu0yEScA7QJRIgARIoagI6dBIFcFFHMcj9dATWAm7RhAQl4Fse7XznOryaPAkpjiw/b/8xSuHqzNH4zaiuHmc6RIJOBrpFAiRAAkVAQIdOogAugsAVdAsdgS3onnyeBKIh4FserYvzR7yYPBlJDq/fkLuNckoE/2FUZTpENLB5LQmQAAnYnIAOnUQBbIFJpSOwFnCLJiQ4AbM8mrh5mfNb/Df5OTgDTov72yiPazMfwnajCtMhEnw+0D0SIAES0EVAh06iANYVrQjG1RHYCG7PriRQaAJmeTQZ4FrXYjyePD3PWL4iWJ5kOkShcfNCEiABErAlAR06iQLYAlNJR2At4BZNsAEB3/Jo4u4A12d4KHl2Hs//Mirg2sxR2GFUYTqEDeYFXSQBEiCBWBLQoZMogGMZoUKOpSOwhTSFl5FAxAR8y6PJxYNdc3Ff8tv5iuB+rWuiTb2Kqk+PptUivicvIAESIAESsA8BHTqJAtgC80dHYC3gFk2wEQHf8mj5ieBdxinom/kAthin5dJhSoSNJgpdJQESIIFCENChkyiACxGIWF+iI7CxtpHjkUBBBALTIYa45mBE8jt5LttvlMb1mfdjnVEbTgdQtUwqFgzrgLSUpIJuwedJgARIgARsSECHTqIAtsBE0hFYC7hFE2xIIDAdIpQIPmSURP/MEVhtnKEoXVC/Inq3qsl0CBvOGbpMAiRAAgUR0KGTKIALol4Ez+sIbBGYzVuQQFACgekQA12fYVSQjXHHjBQMyhqG5d6mueMwHYKTigRIgARIIJCADp1EAWyBeaYjsBZwiybYmEBgOkRv1yJMSHolT53gTMOFe7MGY663jaJVrWwqFjIdwsYzh66TAAmQQF4COnQSBbAFZpqOwFrALZpgcwKB6RD/cS7HU8nT8pwYJ5jGZfXFDM8lihjTIWw+ceg+CZAACQQQ0KGTKIAtMM10BNYCbtEEEkBgOsSFzpWYmjwVKY7sPHRezu6BR7P7wIBTPcd0CE4gEiABEiABIaBDJ1EAW2Bu6QisBdyiCSSgCEg6RLenl2LXwXQYAM53rsNLyU+jtON4HkJzPedjeNYtyIBbpUMMv6gBUpNd3BzHuUQCJEACNiagQydRAFtgQukIrAXcogkkkEsgMB2iseN3vOqehMqOA3ko/eitj0GZw7AfZXOf42owJxMJkAAJ2JeADp1EAWyB+aQjsBZwiyaQgB8BSYeQ9u2WfXjj++2o7tiLWcmPo54z53HftsNbCQOy7sUmowYcJzbHsVYwJxQJkAAJ2JOADp1EAWyBuaQjsBZwiyaQQFACvhUiTsEhzHA/ibOdv+Xpe9gogduz7sRSb3P1HDfHcUKRAAmQgD0J6NBJFMAWmEs6AmsBt2gCCYQk4JsSkYJMPJk8DZe6vs/T32M4MCn7Wrzo6QmotWBujuO0IgESIAG7EdChkyiALTCLdATWAm7RBBLIl4BvhQgHvBia9AHuSvoo6DWfelpjRNYgHEMqawVzXpEACZCAzQjo0EkUwBaYRDoCawG3aAIJFEgg8MAMqRU8KfmloGXSNnhr4Jasu/GHURX9WtfE+F4nT5Ar8EbsQAIkQAIkELcEdOgkCmALTAcdgbWAWzSBBMIiEFgh4mzHJrzonoxKjoN5rj9olFRl0uZ7W7JOcFh02YkESIAE4p+ADp1EAWyBeaEjsBZwiyaQQNgEAg/MqIJ/8IL7v0E3x8mgM7K7Y1bJ/vj8nq5IS0kK+z7sSAIkQAIkEH8EdOgkCmALzAMdgbWAWzSBBCIiEHhghhtZGJv0KnonLQk6zk/eeljY5HHce82Fuc+bpdZ6NK0W0b3ZmQRIgARIwLoEdOgkCmALxFtHYC3gFk0ggYgJBKZDyAB9XIswJmlW0Lzg465SKNFrCtD0Kvhey4MzIkbPC0iABEjAsgR06CQKYAuEW0dgLeAWTSCBQhGQVdz0LA8mfrEBuw9lqDGaOrbiueQpqOncG3TMrEaXo+eWXth8OFk9X7VMKnhwRqHw8yISIAESsBwBHTqJAtgCYdYRWAu4RRNIICoCgavBZXAUjye/jB6uFUHH3WWcokqlfX3i4AypFNGmXkXVlykRUYWCF5MACZBAsRLQoZMogIs1pDk31xFYC7hFE0ggagKBm+MAA9e75mO0ezaSjOyg47+W3Q2PZffGcaTmPs+UiKhDwQFIgARIoNgI6NBJFMDFFs6TN9YRWAu4RRNIICYEzM1xuw+lq/EkvWFR3woo8ekQYM+6oPfY6q2Ke7IG439GfTgdTImISSA4CAmQAAkUEwEdOokCuJiC6XtbHYG1gFs0gQRiRiDoBrfsDCx7aSja7n4LToeR515yjPIMTw9Mzr5SrQabh2ewUkTMwsKBSIAESKBICOjQSRTARRK6/G+iI7AWcIsmkEBMCQQTrqM+XouNP8zH08kvoEaIDXI7vJUwKvsmLPU2x4M9GmLCvA3KLqZFxDQ8HIwESIAEtBHQoZMSRgB/+OGHmDRpEtauXQu324127dphwoQJaNasWcQB+eyzz9CzZ0913bJly9RYge3rr7/Gww8/jFWrVsEwDLRs2VL93r59+4jvpyOwERvBC0ggDgmY6RFHDv2LB12v49qkr0J68bGnDR7Nvg77UFb18a0UwVXhOAw+TSYBEsNybyAAACAASURBVLANAR06KSEE8IwZMzBw4ECceeaZuOWWW5CRkYFnn30W+/btw/Lly9G8efOwJ8mhQ4fQpEkTHDhwAEeOHAkqgL/88kslkE877TTcfvvtSE1NxUsvvYRff/0Vn376KS666KKw7ycddQQ2IgPYmQTimIBvekRX5494LPllVHIcCurRIaMEJmdfhdc93ZCNJJUW0ePMaugz/QfVn6vCcTwRaDoJkEDCEtChk+JeAP/777+oXbs2ypQpg3Xr1qnvpqhs3LgxWrRoAVmtDbfdeuutmDdvHq6++mo89dRTeQSwx+PB6aefjr1792L9+vWoWbOmGvrw4cNKgDudTvz2229wuVzh3pICOGxS7EgCwQlIKsQb329XT5bDYTyQ9CauTloaEtdGb3U8nH0DvvM2Qfk0Nw4cy1R9WT+YM4wESIAErEeAAjhITF599VXceOONKv1gzJgxfj1kVVhWh7dt26ZEckFt6dKl6NSpE+bMmYMff/wRY8eOzSOAv/rqK9Wnf//+mDlzpt+Q48ePx0MPPYQlS5agY8eOBd0u93kdgQ375uxIAglAIPAYZXHpfOc6PJo0HXWcu0N6+KnnPEzMvhY7jCq5fVg/OAEmBF0gARJIKAI6dFLcrwAPHjwY06ZNw/z589GtWze/gL/yyisYMGAA3nnnHbWim187fvy4yheWFeP33ntPCepgAnjixIkYOXKkSnm4+eab/YZcvHgxunTpAukzYsSIsCefjsCGfXN2JIEEIRDsGOUUZOL2pI9xi+sTuB2eoJ5mGi685rkQU7Mvx0GU8uvDlIgEmRx0gwRIIK4J6NBJcS+AL730UpV3K+kIjRo18guwiGLJx5VUhmHDhuUb/OHDh2P69OlqnGrVqoUUwHfccYfKL5Y0ie7du/uNuWnTJjRo0ADS55lnngl5P8kzli+z7dy5E61atcKOHTtQvXr1uJ6kNJ4EipOAuZnt2y37clMixJ46jp0YnfQaOrnWhDTvoFFSiWDJD86AO0/9YG6UK87I8t4kQAJ2JkABHCT6suIqK69btmxB3bp1/XpI7m+HDh0wbtw4jBo1KuTckUoOrVu3xvPPP49BgwapfqFWgGVFWVaWFy1ahM6dO/uNuX37dtSqVUutOouYDtXMsQOfpwC288ubvseSgO/hGYYBOBwyuoFOjtUYnfQ6ajn3hLzdTqM8nsv+D97xdEIWN8rFMiwciwRIgAQKRYACOAi2aFeAs7KycM4556Bs2bJqs5wj5z8lV4ALNUV5EQlYh4BvSoRv/V9Jixjg+hyDk+aitON4SIOlfvAznsvxoecClE0rEXSjHFeFrRNvWkICJJC4BCiAg8Q22hzgyZMn45577lEb33xTKCSFYerUqXj77beVQJaV3eTkZJXfyxzgxH2R0bPEIuArUH0rRYiX5XEIdyV9gL6uRUhyeEM6/oe3MqZ5LsUHnvbIRLLqx/JpiTVP6A0JkIC1CVAAB4mPVGK46aab1Ia10aNH+/Uwq0Bs3boVderUCRrdoUOHYsqUKQVGfvPmzar8mVR4kNQHqTwhqRC+jVUgCsTIDiRQbAR80yLEiFNKJmP/0SzUdfyNEUnv4GLXynxtk9SIl7MvwVueTupo5WDl05Zu2qvG6NG0WrH5yRuTAAmQQKIRoAAOElGpAyyrs5LCEKwOsByCIae5STt48CBkw1nFihXVl7Q1a9ZAxG1ge/fdd1U1CMkfbtiwodrwlpaWBqkDXK9ePXXIhhx8UaNGDXWpWQdYUigkH5l1gBPt5Ud/EoGAb1qEVHiY98vO3M1yzRxbMCzpfXTMZ6OcMPjXKIU3PF3xWvaF2ItyuVi6NqqMhb/m5BazekQizBb6QAIkYBUCFMAhIiElyeQEOPMkuMzMTJW+IIdViPg966yz1JVmzWCpFywb0fJroTbByTVSAeKyyy5TFRvuvPNOdfSy2CAVJObOnYsePXpENGd0BDYiA9iZBGxEwDctIlj94HMdG3Bv8nto7fw1XyoZRhLmeNpihqc7Nho5B+LIFgLZRcBjlm00oegqCZCAdgI6dFLcl0Ezqb///vt44oknsHbtWiVI27VrhwkTJvgdgxwrASz3lFSIRx55BCtX5nxs2rJlS5WCIYdkRNp0BDZSG9ifBOxKIFj9YGHRyvGrqiHc3rW2QDQ/eBuqFeEvveeqI5al5ZcnzM1zBSJlBxIgARLIJaBDJyWMAI7neaIjsPHMg7aTQFETCFU/WOxo7vgNtyfNQTfXjwWatdsoh7c9nfGepwP+NCoFzRNes+MA+kz/QY3FVIkCkbIDCZAACUCHTqIAtsDE0hFYC7hFE0gg7giE2ignjtR3/ImBrnno5VqOFEd2gb5962msKkd87m2FY0hV/a9pWR1fb9qH3YfS1e9MlSgQIzuQAAmQAAVwos4BCuBEjSz9ikcC+W2UE38q4QCuS5qPfq6FKO84UqCLR40UzPOch/c9HbDCaAADTr9rQqVKME2iQLTsQAIkYBMCOnQSV4AtMHl0BNYCbtEEEohbAsE2ypmrtmb5NDlQ4zLXt7jOtQDNnNvC8nW7txI+9F6Ajzzt8IdRNfeawJJq43qdiQGzVqnnmSYRFlp2IgESSGACOnQSBbAFJoyOwFrALZpAAglDIP9VYQMtHFvUqnBP5w9IcWSF5fev3pr43NMKX3hbYpNRXWpI5F5X0u1CepZH/c40ibBwshMJkEACE9ChkyiALTBhdATWAm7RBBJIKAKhVoUNAzBOeFoGR9HT9T2uci3F2c7fwvZ/i7eaEsJfeFphrSGH9pwUwzIIK0qEjZIdSYAEEpCADp1EAWyBiaIjsBZwiyaQQEIT8F0V9j0Ew3RaTpi70vU1rnAtRzXHP2Gz+NOoiC89LbHE2wIrvQ2QAbe6NtjJc8EqSjB3OGzU7EgCJBAnBHToJApgCwRfR2At4BZNIIGEJ2CKzfZnVEK3p5fmVncw84QFgBNetHX+osTwxc6VSA0zRUKuPW648YO3EZZ6m+FrbzNsMU7NXR0OVlEiVO4wRXHCT0U6SAIJTUCHTqIAtsCU0RFYC7hFE0jAVgQKqh4hMErjGDo7V+Ni10p0dK5BCUdmRIxkdfhrT1N87W2Ob72NcQil/K4Pljscqu4wRXFE6NmZBEigGAno0EkUwMUYUPPWOgJrAbdoAgnYjkB+1SNkM9sFZ1TCOyt3KC4lkI4Ozp/R3bUCnZ3/Q2nH8Yh4eQ0HNho1sMLbACu9DbHC2xB7cIrfGKHqDjN1IiLU7EwCJFDMBHToJArgYg6q3F5HYC3gFk0gAdsTCFwVblajXNBUCTeyVJpEd+cKdeLcKWHUFw4GV8qsrTRyxLDkD281quXZUBdt6gRXjm0/rQmABIqcgA6dRAFc5GHMe0MdgbWAWzSBBEgAQKBgLChVQnKGmzm2or3zZ7R3/YyzHJvhcph1JiJDetAoiZ+9dbHWqIs18t1bF3+jQh5RHG7qRKDtbU6vmMe/yCxkbxIgARIomIAOnUQBXDB37T10BFa70bwBCZBAoQnklyqRmuzCscycGsDSpLRaG+c6tHeuQXvXWlR37Cv0feXCfUYZrPXWwc9GXfzirYMNRg38aVTyO6Eu2Crxx7e1xX+e+8bvGOdINt1x5TiqsPFiErA1AR06iQLYAlNKR2At4BZNIAESCJOA78rqjOvPxag5vwStKCEVh+s5/laCuJVzg/qq4jgQ5l1Cd5Pjmjcb1bHBWwObjBpKFG/y1sA+lM296IwqpbBpt//Rz9GsHMvAgaKYIjnqUHIAEkhIAjp0EgWwBaaKjsBawC2aQAIkEAEBX/FXUJrEyWEN1HTsUUK4pWMjWjo3oK5zVwR3zb+rrBZL6bWt3mrYZlTFNqOayiveblRBFpLyXBzuyvGCYR0QuBFPBusz/Qc1ZkHHP4cSyhTQMQs9ByIBSxHQoZMogC0QYh2BtYBbNIEESCAKApFUlPC9TSUcwLnOjWju3ILmjq0407kt4goTBZntMRzYYVRWovh3o6r6eYdRSaVSyPcjKJnvynGgUK5cOkXlJe85nK6u8z3+OdCWYHnI0ifU4+b1+YljCueCIs7nSaB4CejQSRTAxRtTdXcdgbWAWzSBBEgghgQKqigRmDts3toBL+o4dqGpYyuaO7eiqXMrznT8HnEN4khcOWCk5QpiEcV/GRWxyyh/4usU7EU5eODKd0g5/nl8r6Z+fY5kZPtV0TCFsmwR9D2IJFBA5yeO83uusKKZK9SRzBb2JYGCCejQSRTABXPX3kNHYLUbzRuQAAkUOYH8KkoE5g4H1h32NdYFj8olbujYgQbO7TjD8af6uYZzb5H4JCvIIoL9RLFRDvtRBvuNnC/JP550fWe0blgLcDiUXaM+Xos3vt/uZ6MIZWnBHhcBHUo0p6Uk5ftcYUVzUa5QF6VAL8y9uLJeJC8nW9xEh06iALbA1NERWAu4RRNIgASKgEB+ucOBdYfzE8ViahqOKzHcwLkDDRw7UN/xJ+o4d+E0x/4i8CT4LYykVDjSKuGIqxxW7HXlCGSUVdUscn4ug3+N0jiINBw00nAYJeGFUw0mucTzftkZUhyHEtQjuzcKuaJcGEGtY4W6KAV6Ye6lIyWlMCJc5kFhVuQLc6/CXJOo9sX6D4YOnUQBHOsoFWI8HYEthBm8hARIIAEIFFR3OFAUh0qd8EWRigzUduxGHcdO9SUb7dR3x85CH9qhE/Uho6QSxEcdafjHk/OziGPz+yGkoXPz0zH7p39wDKk4YpTAUaTiqJGqvp/fsCYWbPAvN2emZIQSzbLaXFQr1PkJ6lgL9FiPJ3GPtaDmeBVzX06F+QQi1vx0vLZ16CQKYB2RinBMHYGN0AR2JwESSGACsUidCFYGTZCVxjFUd+xFDcceVaM45+e96rt8RXrEs1XCcMxI8RPFR1AC1SpVwM97PLlC+TjcSDfcOI4UdGxSA3PW/aN+T5fH4cZxn5/l9wzVN+e5bCQVeoVaGIVK+Yi1QI/1eLEW1BwvFVJVJb+UnqJ8w6Tr9atDJ1EA64pWBOPqCGwEt2dXEiABGxKINHUi8CCMcFaOpW5xWRxFNcc/qHriS36ugn/UY1Uc/6KaYz/KOo7ZLgLZhhMZDjcyjSRkIkmVlcv5ORlZcKFyudLYdiBbPaaeO9FHfs448VjO49I/59oLGp2KL379R/2eDcn0diLbyPn+n7Nr4t3VO0887kI2nGojotihvpv9T3yXa27teAamLPn9ZF/zGrgw/OJGGP/Fb3lOFcwvkIVNSYlnwR/rNxBWH0/XC1mHTqIA1hWtCMbVEdgIbs+uJEACJFDgkc1y7HF+B3aEyi8OtXLsi1xSLCrgECo4cr4qOg6q369vloZTk48g+/AebP39d5T1/ovyOIxkx8mT8hi64iUgGxpFLBuQQ7yl5oh8mT+ffEyel82M2UbO84b6frJ/+VIp2Hsk68S1vmM58oxtyHWGA7UqlsKWfcehfg+47xlVy2D9riPquZwm48hbMvnu/7M8K881Pa0cfv7rEAzjZD/zuRY1TsHqHXLojP/1Oc8HG8+BlnXKY8W2f4Pe9/y6FfDd1n98nstrm5/dhgMXnFEJSzfty/XJvK/069igMr7amLOJ9aTPOX6ZzXzcfKxLw8pYuOHkxlff67o2qoIFv+72e4NjPj/X08bvkBxz/ILqd0czU3XoJArgaCISo2t1BDZGpnEYEiABGxMItqkn2pXjgjbimbgDy6CZ4lukThkcyxXJIpjLOY6oleYyjmPqe1nHUXWEdHnXcZTyHkYZ9fsxJDm8No4mXSeB2BC4NGM81hp1/QZzOvKv3x3tnXXoJArgaKMSg+t1BDYGZnEIEiABEiiQQEGb7gJXjmWVKHAjXrgHYUS6yazHmdVyT5eTtbA0pOcK5CHnV8IH329EGjKQ5jiOUkhHSaSjlCNd/a5+9n0Mx5HmyFCVMmQcrkIXODXYIUEJBBPAod64xgqBDp1EARyr6EQxjo7ARmEOLyUBEiCBqAgUtHIsgwfuPJfHCjoKuTAHYUSaM9m1UWUs/HVPUP8f7NEQE+ZtUB8ypyALKchEKrKQ6sjEnReciteXbcz9PVU9l4FURxZyfs75KuHIPHFdJsomZ8PIlize7NwvtyNbbZGTx8zvyeqxrBO/e9TPXM2Oaory4igI9MwYj18CVoApgKMAaudLKYDtHH36TgL2JRAolMM5OCHSMk+FqRLw2Oe/FkmVBf8Vav95cFJsB58fkiXrJ5KRjbs71cTLX21EstrW5kGS+u5V32847zS8teKPE4/Jc94TfU58d5zsa15zYcMKWLphV04/R05mrznm+bXLYPXv+3LHkUxbl8PMxJWMXzMr2PzZQIoL8Hg8KmNW7pGT6XvieUdgf5Up7NM3J9M3Z9ycvup5uc7wwunw75vzfE7Ki9hmZu7mZAT7ZwbnPBfYx+zn/5w5ntzPri2YAGYKhF1nQ5R+UwBHCZCXkwAJ2IpApAcbRFrntDCiubBlqCJdoS7o5DsrjxeN4A82wfN7k1DQG4jYjWduq8sZ0Vdoj7z4DEz6Qj4xyPvciAvr48n5G/0EuinMT26z8xXvwNAu9TBl0eaAa3LueWfn0/HM4t9yt/yZtvjeWz1m7gkEcHvHunj2qy25dp/sCwzpUBcvLM15LnCsnUYFZMCdByE3wdnqz3BsnKUAjg1HjkICJEACoQhEekpXpKLZvG9RrFAXZV3XwrwZyM8+Kwv0/A4zKexBJ3bzV9dfIB06iTnAuqIVwbg6AhvB7dmVBEiABEggCIFIRbM5hO4VarlPUQn0wt4rlH2xFtQcjwdhFPaPFwVwYcnF8DoK4BjC5FAkQAIkEIcECiO2C3ONoIlUoOd3TWHGK4x4L8w1+Yl3jlfw8cmF5afj5adDJ1EA64hUhGPqCGyEJrA7CZAACZAACRQZgcKI98JcUxiBHmvBb8fxYj2RdOgkCuBYR6kQ4+kIbCHM4CUkQAIkQAIkQAIkYDkCOnQSBbAFwqwjsBZwiyaQAAmQAAmQAAmQQNQEdOgkCuCowxL9ADoCG71VHIEESIAESIAESIAEip+ADp1EAVz8cYWOwFrALZpAAiRAAiRAAiRAAlET0KGTKICjDkv0A+gIbPRWcQQSIAESIAESIAESKH4COnQSBXDxx5UrwBaIAU0gARIgARIgARKwJgEKYGvGJWqrdAQ2aqM4AAmQAAmQAAmQAAlYgIAOncQV4AQNrAXcogkkQAIkQAIkQAIkEDUBCuCoEVpzAB2BtaantIoESIAESIAESIAEIiOgQydxBTiyGGjprSOwWgzloCRAAiRAAiRAAiRQxAR06CQK4CIOYrDb6QisBdyiCSRAAiRAAiRAAiQQNQEdOokCOOqwRD+AjsBGbxVHIAESIAESIAESIIHiJ6BDJ1EAF39cWQbNAjGgCSRAAiRAAiRAAtYkQAFszbhEbZWOwEZtFAcgARIgARIgARIgAQsQ0KGTuAJsgcD+/vvvqFOnDlasWIFq1apZwCKaQAIkQAIkQAIkQALWILBz5060atUK27ZtQ+3atWNiFAVwTDBGN8jKlStVYNlIgARIgARIgARIgASCE5CFwpYtW8YEDwVwTDBGN0h6ejrWrl2LSpUqISkpKbrBCrjafBfF1WatmKManDGKCl+RXMwYFQnmqG7CGEWFr8guZpyKDHWhb2SFGGVnZ2Pv3r1o2rQpUlNTC+2L74UUwDHBGD+D6MijiR/v48NSxsj6cWKMGCPrE4gPC/lasn6cEjVGFMDWn3sxtTBRJ3JMIRXzYIxRMQcgjNszRmFAKuYujFExByDM2zNOYYIqxm6JGiMK4GKcVMVx60SdyMXBUtc9GSNdZGM3LmMUO5a6RmKMdJGN7biMU2x56hgtUWNEAaxjtlh4zEOHDuHpp5/GsGHDUKZMGQtbal/TGCPrx54xYoysTyA+LORryfpxStQYUQBbf+7RQhIgARIgARIgARIggRgSoACOIUwORQIkQAIkQAIkQAIkYH0CFMDWjxEtJAESIAESIAESIAESiCEBCuAYwuRQJEACJEACJEACJEAC1idAAWz9GNFCEiABEiABEiABEiCBGBKgAI4hTCsP9eGHH2LSpEnqxDm324127dphwoQJaNasmZXNTjjbNm/ejNmzZ2PBggXYsmULDh8+jFq1aqFr1664//77Ua1aNT+fjx07hkceeQRvv/025DQeef7aa6/F6NGjUbJkyYTjY1WHvF4v2rRpgx9++AFdunTBwoULGScLBEt2p8vftQ8++AC///47SpQogfr16+OOO+5Av379ci3k66h4giXxmTJlCt59910VH/nfU7duXfTv3x+DBg1CcnIyY1SEoXn88cfxv//9D6tXr1b/f5xOJ+SEtVAt0tfNzz//jAcffBDLly9HZmamOrVtxIgRuOKKK4rQy/BvRQEcPqu47TljxgwMHDgQZ555Jm655RZkZGTg2Wefxb59+9REbd68edz6Fm+Gjxw5Es888wwuueQStG3bVonY77//Hq+99hrKli2Lb775Bg0bNlRueTweJbaWLl2K6667Du3bt1dvYJ577jlccMEFSoS5XK54QxCX9krpwDFjxuDIkSN5BDDjVDwh/euvv9CpUyf1d0wEVZMmTXD06FFs2rRJvVGUf8R8HRVPbOSuIqzOP/98Jbbk75f8nJ6ejvfee0/9nevbty/eeOMNxqgIQ+RwOFCuXDmcddZZ+PXXX9XRwqEEcKR/19asWaMW1lJSUjB06FBUqlRJxVc0xvTp0zFgwIAi9DS8W1EAh8cpbnv9+++/qF27tqr5u27dutzav1LYunHjxmjRogW+/vrruPUv3gxftWoV6tWrh1NOOcXP9Jdeekm9Ofm///s/tVoi7ZVXXlF/NGQ1S0Sz2WRFRf7AyBubm266Kd4QxJ29W7duVSsZjz76qOIeuALMOBVPSCUO69evx4oVK1CjRo2QRjA+xRMfeYPerVs3VXP+qaeeyjVChNU555yj3szL/yf538QYFU2MZNVX/v9I69ixoxKnoQRwpDGRBRoZT16P5557rrqHjC2fnG3cuBF//PGHEt9WahTAVoqGBlteffVV3HjjjXj44YfVCpZvk1VhEVHbtm1TIpmt+AjIR4WyAtygQQNs2LAh9w+UrP7KR4eSJmE2WUWpWLGi+iPz1VdfFZ/RNrmzCC1JVZGVellxDxTA8o+EcSraySAriLLaNHnyZPWmRETV8ePHUapUqTyGMD5FGxvzbpKWctVVVynxKyLYt3Xv3h2LFi1SrytZMWSMij5GBQngSGIi/6Pq1Kmj4rhkyRI/Z2QVWD4BmDlzpvqkxkqNAthK0dBgy+DBgzFt2jTMnz9fvRv3beY7vHfeeQdXX321hrtzyHAJyMdRsiIvqQ2yIm8YBkqXLq1EsXzUG9jk3bZ8tCj/QORjLTY9BF5++WUMGTIEsnIvqULC2lcAM056uBc06gMPPIDHHnsMc+fOhbzJ/+STT5CVlYVTTz0Vt912GyTVSPIbGZ+CSOp7fteuXWq1MS0tTaXctW7dWqVAyCdcsodB9jaMGjWKMdIXgnxHzk8AR/q6EQ0he1PkdSl7i3ybfIIm80C0yPPPP19M3ga/LQWwpcIRe2MuvfRSfPrpp+qjwkaNGvndQETxRRddFPQdeuwt4Yj5EbjyyishGxXNd8n79+9Xq7ytWrVSG68CW58+ffDWW29B+pUvX55wNRD4+++/1ZuSW2+9FbJ5RFqgAGacNIAPY8jLL78cH3/8scozNP+5Smzkzf63336r0onkZ8YnDJgau8j/GHkDKR+9my01NVXtYzDTtxgjjQHIZ+j8BHCkMZFV/nvvvVcJXBG6vk02w8kqv2gRecNqpUYBbKVoaLBFVqsWL16s/gDJ7lvfJiuNHTp0wLhx49Q7cbbiISC5pbJhp1evXkoEyz/yHTt2oGbNmrkrwoGWyT8PEcvSr3r16sVjeILfVeIheYq//PKLqi4QTAAzTsUzCaRqinyELn/T5NMTqS4gTVaB5U2L/L2Tx2WTKV9HxRMjuat8cjJ27Fi1KfHCCy9UaSqy4Vc+Jpd9D/J3jK+h4olPfgI40piIhpBV/VD7UuTTmM6dO+epnlM8np+8KwVwcUdA8/25AqwZcJTDmxva5I/RZ599llvaLNJ34FGawcsDCEjZud69e6tydSK2zMYVYGtMFfPvmrxxHD9+vJ9RstdBPl5/4YUX1KZSfpJSPDGTqgDnnXeeytE2P0ERS+TjdUnh+vHHH9X+k6SkJMaoGELEFWCAArgYJl5R3pI5wEVJO7J7SWmte+65R+WUykdDvnV95Z+EbOiRXbPMAY6Ma7S9pUygVBWQUkHyUa1vkxqzsqt51qxZKke7cuXKjFO0wAtxvXysLgJ36tSpuP322/1GkNQH+bsnuYhSW5uvo0IAjsEl5qdUsgosVR98m/nGX9JYLrvsMsYoBrwjHaKgHOBIXjfMAY6UPvsXCQH5mFz+EMnHUPIRhW8zq0BIkrrs4GQrOgJSvP++++7DxRdfjI8++giSFxfYJD1F0lQCq0CIQKtQoQKrQGgK14EDB/KUqQt2K7OOKeOkKRD5DCsfo99www2qyP7EiRP9epob5Mzao4xP0cdH7ij7SyQHWPYwyF4G3/bkk09i+PDheP/99yH7Hxijoo9RQVUgIomJrORLOpLU5ZaUS9/GKhBFH1ve8QQBqbMoJbSkmkCwOsCys33ZsmXkVYQEZPe6/JPu2bOn+gcgGwSCNfkHfvPNN+epAyw1ge+66y7LFhcvQpRabiV5pHPmzAk6tnykLjWB5c2kvK5atmyp4sA4aQlFyEEPHjyoSjdKbrbUGJXVeGlyUIkcJLNnzx6VBywr+YxP0cbGvJuUPpMydYG7/+X1Ja8bya8X4SQ52oxR0ceoIAEcaUykLKFsQF25cmXuir9ZB1hKe0od4MD690Xvtf8dmQJR3BEogvubhyyYJ8HJrkz5Xx46fwAADJhJREFU6FBOgRHxKx/1shUNAdklK2WaqlSposo4+R4FKhbIx06y+Uqa1DaVd9QSo+uvv17lzclRk/KxvHwMLxtJeBJc0cTNvEtgDjDjVLT8fe9mrgJL7Wz5NEualHaUzW+S/iBvMhmf4ovP9u3blRCSk/okZ1tWhOVoXVkRlL9jd955pzommTEquhi9/vrrSohKkw1rEiP5dNhsvpvhI/3/I2U55X+UfJp59913q7zu2bNnq/9fL774ojr62mqNAthqEdFkj6w0PvHEE+pdt+yYlndr8k+CxyBrAh5iWCkELvmjoZqsKkrKg9lkRUs29EiO1c6dO9Vu6muuuUatQAYr+l+03tjvbsEEsFBgnIpnLnz++edqg5VsqPJ6vWp1Xv75Sk1S38b4FE985G+ZVAiQzaTy90v+98iR1fKJibxp8a1hzhjpj5F5uEWoO8nek2heN7LxUTamyolwstAmr0dJdZEDUazYKICtGBXaRAIkQAIkQAIkQAIkoI0ABbA2tByYBEiABEiABEiABEjAigQogK0YFdpEAiRAAiRAAiRAAiSgjQAFsDa0HJgESIAESIAESIAESMCKBCiArRgV2kQCJEACJEACJEACJKCNAAWwNrQcmARIgARIgARIgARIwIoEKICtGBXaRAIkQAIkQAIkQAIkoI0ABbA2tByYBEiABEiABEiABEjAigQogK0YFdpEAiRAAiRAAiRAAiSgjQAFsDa0HJgESIAESIAESIAESMCKBCiArRgV2kQCJEACJEACJEACJKCNAAWwNrQcmARIgAQKR6B///6YNWsWbrjhBrz66quFG8TCV23fvh0NGjRAnTp18Msvv8DpdBba2szMTNSrVw8HDx7Eli1bUKlSpUKPxQtJgATsQ4AC2D6xpqckQAJFQMDhcBT6Ltu2bUPt2rWR6AL4+uuvx+uvv4433ngDffv2LTQv88Jnn30Wd9xxB26//XZMnTo16vE4AAmQQOIToABO/BjTQxIggSIkULVq1aB3kxXK9PR0JCcno3z58kH7rFy5EjVq1MD999+Pjz76CJdffjkee+yxIrRe/61+/vlnnHXWWWrV9tdff4XL5Yr6phkZGWo1ed++fdiwYQPq1q0b9ZgcgARIILEJUAAndnzpHQmQgEUImKu6HTp0wFdffWURq4reDEnreO211/D444/jvvvui5kBI0eOxMSJEzF06FBMnjw5ZuNyIBIggcQkQAGcmHGlVyRAAhYjQAEMladbrVo1tRL++++/o2bNmjGLkqwsN2/eHBUqVMDff/8Nt9sds7E5EAmQQOIRoABOvJjSIxIgAQsSiEQA55cDLDnCf/zxB2bOnImrrroKEyZMwPvvv48///wTVapUwZVXXonRo0ejbNmyisLq1atVGsXy5cvx77//qs1nd999t8ozzq99/vnnmD59Or777juVWlCqVCm0aNECkr973XXXFSp14YUXXsCQIUPQpk0bfPPNN0FvbxiGyg2WTYBr1qzBgQMHUKZMGbW57dxzz8V//vMf/N///V/Qa5s0aYL169fj3XffDdnHglODJpEACRQDAQrgYoDOW5IACdiPQKwF8H//+1+8/PLLWLduHdLS0iDVELKyshTY1q1bqzSLL7/8EldffbV6TkSkrMCaTdIEJF0gsEnfm266CbNnz859Sq49fPgwRJxKu+iii/Dxxx8jNTU1okD26tULc+bMUakPkgIRrJkb5Mzn5N6S4ytf0k477TQl9oO1W265BS+99BIGDBigxDsbCZAACYQiQAHMuUECJEACRUAg1gK4XLlyqFy5shJ6F1xwgRK5kls7ePBgZGdnq410zz//vFoRllVi2Zy3d+9e3HzzzUqElihRQgnJwA15skIrK7W1atXC+PHj1Ypr6dKlcezYMcydO1etHu/atQu33XYbpPpCJE1WcWU1+YMPPsAVV1yR59Jly5ahffv2qizaE088oYSsrGSL8N6zZ48S9QsXLlTCP1ibMWMGBg4ciPr162PTpk2RmMa+JEACNiNAAWyzgNNdEiCB4iEQawGclJSkVn/POOMMP4dENL7yyivqsU6dOmHx4sV+zx89elTl4cqKrghmSWcwm5lHe8opp2DVqlVBqylISkTbtm0h99+xY4dKuwinSY3e008/XXX97bffVBWIwDZp0iS1OiwrzF988UU4w/r1+fHHH1WahLT9+/eHrLYR8cC8gARIIOEIUAAnXEjpEAmQgBUJxFoAX3vttXjrrbfyuCqP9enTRz0uKRAXXnhhnj7y2IIFCzB8+HCI6DTbXXfdhWeeeQaDBg3Ciy++GBKjiNetW7fi7bffxjXXXBMWbnN1VzpLKoakNgS2adOmqRXsc845BytWrIj4gAzJjZYcaWlywIbkBLORAAmQQDACFMCcFyRAAiRQBARiLYAfffRRleYQ2BYtWoSuXbuqh6Uagqz2BjZZ9ZWNZpIu4JtOIKunsooqKQ8lS5YMSeWff/5R+cZSdmzEiBFh0ZO6xpL2ICvHZq5y4IWyMiyiVdI5pFyc2NexY0dUr149rHvIqrYprJcsWaKuZSMBEiABCmDOARIgARIoJgKxFsCS5nDjjTfm8UbyZCX1QZrX60Wwk+lCVZmQDWYimsNtY8aMwcMPPxxWd3NlWoS1pGGEalLdQk50k5xjs4kAllVrSe+QChKhmghrs/zZvHnz0L1797BsYycSIAH7EeAKsP1iTo9JgASKgUCsBbAIxWClzHwFsFm1IdDdUAJYNsrt3r0bzz33nCpXFss2f/58ldsrTSo65FenVza8SSkzWcWV8m3yu9nyO+5YbDdP4pMUipYtW8bSBY5FAiSQQAQogBMomHSFBEjAugTiQQDLQRKyEU7Er4jgWDapRyy5vdKkikS4m+ek/08//YQnn3wytzRbqNVdOQa5UaNG6h6SoyzHI7ORAAmQQDACFMCcFyRAAiRQBATiQQCbJdAkFWLbtm1ITk6OGZkjR45ASrd5PB51uIbUKo6kyWp2s2bN1Oa2wM175jhyeEePHj1UXWQ5QEPyjdlIgARIgAKYc4AESIAEiolAPAhg3zJicprc2LFjQ9KSjXCBNYQLQmtuspsyZQruvPPOPN1l81t+qRGtWrXCypUr1bUyRmATeyUnWTYBSpULNhIgARIIRYArwJwbJEACJFAEBOJBAAsGybE10x/k0Ix77703t9Zwenq6qg8s+blSRUJEcCTtnnvuwdNPP42+ffuq6wOb3E9Winv37o127drlCmw5PENOrpPKF9Jkpffiiy/Oc33Pnj3x2WefYdy4cRg1alQkprEvCZCAzQhQANss4HSXBEigeAjEiwCWU+TuuOMOSE1es0lKgazMSv1eqSwhLb9yZqEIy+qtrOJWrFgRO3fuzJOiYDIyrzdLmh06dCh3yFAn0EllCTkZT6pHbNy4Mc8BIcUTdd6VBEjAqgQogK0aGdpFAiSQUATiRQCb0L///nslguUACxGrkrsrwvXMM8/EJZdcomr6hluf1zeQLVq0wJo1axBsI5ucFvfpp5+q0+tkQ5vcV1adRdied955qi5wqNJmb775plpZlqOUly5dmlBzh86QAAnEngAFcOyZckQSIAESIIEQBMzT3uS0utmzZ8eMk4hyEdWSWiFCmI0ESIAE8iNAAcz5QQIkQAIkUGQEZKNbw4YN8eeff2LTpk25RxdHY8DatWshJdykBJqUcXO5XNEMx2tJgARsQIAC2AZBposkQAIkYCUCsvLbr18/DBo0CC+++GLUpl199dV47733MGfOHFx22WVRj8cBSIAEEp8ABXDix5gekgAJkIClCEhN30mTJqkNdffddx+cTmeh7ZMV5YkTJ6rav8OGDSv0OLyQBEjAXgQogO0Vb3pLAiRAAiRAAiRAArYnQAFs+ylAACRAAiRAAiRAAiRgLwIUwPaKN70lARIgARIgARIgAdsToAC2/RQgABIgARIgARIgARKwFwEKYHvFm96SAAmQAAmQAAmQgO0JUADbfgoQAAmQAAmQAAmQAAnYiwAFsL3iTW9JgARIgARIgARIwPYEKIBtPwUIgARIgARIgARIgATsRYAC2F7xprckQAIkQAIkQAIkYHsCFMC2nwIEQAIkQAIkQAIkQAL2IkABbK9401sSIAESIAESIAESsD0BCmDbTwECIAESIAESIAESIAF7EaAAtle86S0JkAAJkAAJkAAJ2J4ABbDtpwABkAAJkAAJkAAJkIC9CFAA2yve9JYESIAESIAESIAEbE+AAtj2U4AASIAESIAESIAESMBeBCiA7RVveksCJEACJEACJEACtifw/xQkEJ7lQWW0AAAAAElFTkSuQmCC\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(times_RK,X_RK,'d')\n",
    "plt.plot(times_IG,X_IG,linewidth=3.0)\n",
    "plt.xlabel('Time (s)')\n",
    "plt.ylabel('H2O mole fraction')\n",
    "plt.legend(['Redlich Kwong', 'Ideal Gas'])\n",
    "plt.ylim((0.385,0.505))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Now repeat the process at a very high pressure (100 atmospheres)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "RK_gas.TPX = 800, 100*101325, {'CO2':0.5, 'H2':0.5}\n",
    "Ideal_gas.TPX = 800, 100*101325, {'CO2':0.5, 'H2':0.5}\n",
    "\n",
    "r_RK = ct.Reactor(contents=RK_gas,name='RK reactor')\n",
    "reactorNetwork_RK = ct.ReactorNet([r_RK])\n",
    "\n",
    "r_IG = ct.IdealGasReactor(contents=Ideal_gas,name='IG reactor')\n",
    "reactorNetwork_IG = ct.ReactorNet([r_IG])\n",
    "\n",
    "\n",
    "X_RK = list()\n",
    "X_IG = list()\n",
    "\n",
    "times_RK = list()\n",
    "times_IG = list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_RK = 0\n",
    "t_IG = 0\n",
    "while(t_RK < 50):\n",
    "    t_RK = reactorNetwork_RK.step()   \n",
    "    times_RK.append(t_RK)\n",
    "    X_RK.append(RK_gas.X[2])\n",
    "while(t_IG < 50):\n",
    "    t_IG = reactorNetwork_IG.step() \n",
    "    times_IG.append(t_IG)\n",
    "    X_IG.append(Ideal_gas.X[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(times_RK,X_RK)\n",
    "plt.plot(times_IG,X_IG)\n",
    "plt.xlabel('Time (s)')\n",
    "plt.ylabel('H2O mole fraction')\n",
    "plt.legend(['Redlich Kwong', 'Ideal Gas'])\n",
    "plt.ylim((0.385,0.505))\n",
    "plt.xlim((0,50))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While the difference between the two models is rather small, there are a number of other situations where non-idealities will have a more significant impact."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Non-Ideal Shock Tube Example\n",
    "## Ignition delay time computations in a high-pressure reflected shock tube reactor\n",
    " \n",
    "In this example we will illustrate how to setup and use a constant volume, adiabatic reactor to simulate reflected shock tube experiments. This reactor will then be used to compute the ignition delay of a gas at any temperature and pressure.  The example very explicitly follows the form set in batch_reactor_ignition_delay_NTC.pynb, which does very similar calculations, but with an IdealGasReactor.  All credit is due to the developer of that example.  This example generalizes that work to use a Reactor with no pre-assumed EoS.  One can also run ideal gas phases through this simulation, simply by specifying a cti file with that thermodynamic EoS.\n",
    "\n",
    "Other than the typical Cantera dependencies, plotting functions require that you have matplotlib installed, and data storing and analysis requires pandas. See https://matplotlib.org/ and http://pandas.pydata.org/index.html, respectively, for additional info.\n",
    " \n",
    "The example here demonstrates the calculations carried out by G. Kogekar, et al., \"Impact of non-ideal behavior on ignition delay and chemical kinetics in high-pressure shock tube reactors,\" Combust. Flame., 2017.\n",
    "\n",
    "The reflected shock tube reactor is modeled as a constant-volume, adiabatic reactor.  The heat transfer and the work rates are therefore both zero.  With no mass inlets or exits, the 1st law energy balance reduces to:\n",
    "\n",
    "\\begin{equation*}\n",
    "\\frac{dU}{dt} = \\dot{Q} - \\dot{W} = 0.\n",
    "\\end{equation*}\n",
    " \n",
    "Because of the constant-mass and constant-volume assumptions, the density is also therefore constant:\n",
    "\n",
    "\\begin{equation*}\n",
    "\\frac{d\\rho}{dt} = 0.\n",
    "\\end{equation*}\n",
    "\n",
    "Along with the evolving gas composition, then, the thermodynamic state of the gas is defined by the initial total internal energy $U = mu = m\\sum_k\\left(Y_ku_k\\right)$, where $u_k$ and $Y_k$ are the specific internal energy (kJ/kg) and mass fraction of species $k$, respectively. \n",
    "\n",
    "The species mass fractions evolve according to the nety chemical production rates due to homogeneous gas-phase reactions:\n",
    "\n",
    "\\begin{equation*}\n",
    "\\frac{dY_k}{dt} = \\frac{W_k}{\\rho}\\dot{\\omega}_k,\n",
    "\\end{equation*}\n",
    "\n",
    "where $W_k$ is the molecular weight of species $k$ $\\left({\\rm kg}\\,{\\rm kmol}^{-3}\\right)$, $\\rho$ is the (constant) gas-phase density $\\left({\\rm kg}\\,{\\rm m^{-3}}\\right)$, and $\\dot{\\omega}_k$ is the net production rate of species $k$ $\\left({\\rm kmol}\\,{\\rm m^{-3}}\\,{\\rm s^{-1}}\\right)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Runnning Cantera version: 2.4.0\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import time\n",
    "\n",
    "print('Runnning Cantera version: ' + ct.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the gas\n",
    "\n",
    "In this example we will choose a stoichiometric mixture of n-dodecane and air as the gas. For a representative kinetic model, we use that developed by Wang, Ra, Jia, and Reitz (https://www.erc.wisc.edu/chem_mech/nC12-PAH_mech.zip) by [H.Wang, Y.Ra, M.Jia, R.Reitz, Development of a reduced n-dodecane-PAH mechanism and its application for n-dodecane soot predictions, $Fuel$ 136 (2014) 25–36].\n",
    "\n",
    "To fun a different model or use a different EoS, simply replace this cti file with a different mechanism file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = ct.Solution('input-files/non-ideal-models/WangMechanismRK.cti')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define reactor conditions : temperature, pressure, fuel, stoichiometry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the reactor temperature and pressure:\n",
    "reactorTemperature = 1000 #Kelvin\n",
    "reactorPressure = 40.0*101325.0 #Pascals\n",
    "\n",
    "# Set the state of the gas object:\n",
    "gas.TP = reactorTemperature, reactorPressure\n",
    "\n",
    "# Define the fuel, oxidizer and set the stoichiometry:\n",
    "gas.set_equivalence_ratio(phi=1.0, fuel='c12h26', oxidizer={'o2':1.0, 'n2':3.76})\n",
    "\n",
    "# Create a reactor object and add it to a reactor network\n",
    "# In this example, this will be the only reactor in the network\n",
    "r = ct.Reactor(contents=gas)\n",
    "reactorNetwork = ct.ReactorNet([r])\n",
    "\n",
    "# Now compile a list of all variables for which we will store data\n",
    "stateVariableNames = [r.component_name(item) for item in range(r.n_vars)]\n",
    "\n",
    "# Use the above list to create a DataFrame\n",
    "timeHistory = pd.DataFrame(columns=stateVariableNames)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define useful functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ignitionDelay(df, species):\n",
    "    \"\"\"\n",
    "    This function computes the ignition delay from the occurence of the\n",
    "    peak in species' concentration.\n",
    "    \"\"\"\n",
    "    return df[species].idxmax()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate the IDT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computed Ignition Delay: 4.093e-04 seconds. Took 3.85s to compute\n"
     ]
    }
   ],
   "source": [
    "# Tic\n",
    "t0 = time.time()\n",
    "\n",
    "# This is a starting estimate. If you do not get an ignition within this time, increase it\n",
    "estimatedIgnitionDelayTime = 0.005\n",
    "t = 0\n",
    "\n",
    "counter = 1;\n",
    "while(t < estimatedIgnitionDelayTime):\n",
    "    t = reactorNetwork.step()\n",
    "    if (counter%20 == 0):\n",
    "        # We will save only every 20th value. Otherwise, this takes too long\n",
    "        # Note that the species concentrations are mass fractions\n",
    "        timeHistory.loc[t] = reactorNetwork.get_state()\n",
    "    counter+=1\n",
    "\n",
    "# We will use the 'oh' species to compute the ignition delay\n",
    "tau = ignitionDelay(timeHistory, 'oh')\n",
    "\n",
    "# Toc\n",
    "t1 = time.time()\n",
    "\n",
    "print('Computed Ignition Delay: {:.3e} seconds. Took {:3.2f}s to compute'.format(tau, t1-t0))\n",
    "\n",
    "# If you want to save all the data - molefractions, temperature, pressure, etc\n",
    "# uncomment the next line\n",
    "# timeHistory.to_csv(\"time_history.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure illustrating the definition of ignition delay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(timeHistory.index, timeHistory['oh'],'-o',color='b',markersize=4)\n",
    "plt.xlabel('Time (s)',fontname='Times New Roman')\n",
    "plt.ylabel('$\\mathdefault{OH\\, mass\\, fraction,}\\,  Y_{OH}}$',fontname='Times New Roman')\n",
    "\n",
    "# Figure formatting:\n",
    "plt.xlim([0,0.00075])\n",
    "ax = plt.gca()\n",
    "font = plt.matplotlib.font_manager.FontProperties(family='Times New Roman',size=14)\n",
    "ax.annotate(\"\",xy=(tau,0.005), xytext=(0,0.005),arrowprops=dict(arrowstyle=\"<|-|>\",color='r',linewidth=2.0),fontsize=14,)\n",
    "plt.annotate('Ignition Delay Time (IDT)', xy=(0,0), xytext=(0.00004, 0.00525), family='Times New Roman',fontsize=16);\n",
    "\n",
    "for tick in ax.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Illustration : NTC behavior\n",
    "In the paper by Kogekar, et al., the reactor model is used to demonstrate the impacts of non-ideal behavior on IDTs in the **N**egative **T**emperature **C**oefficient region, where observed IDTs, counter to intuition, increase with increasing temperature.\n",
    "\n",
    "### Define the temperatures for which we will run the simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a list of all the temperatures we would like to run simulations at\n",
    "T = [1800, 1600, 1400, 1200, 1100, 1075, 1050, 1025, 1000, 975, 950, 925, 900, 850, 825, 800,\n",
    "     750, 700]\n",
    "\n",
    "estimatedIgnitionDelayTimes = np.ones(len(T))\n",
    "\n",
    "# Set the initial guesses to a common value.  We could probably speed up simulations \n",
    "# by tuning this guess, but as seen in the figure above, the 'extra' time after igntion \n",
    "# does not add many data points or simulation steps.  The time savings would be small.\n",
    "estimatedIgnitionDelayTimes[:] = 0.005\n",
    "\n",
    "# Now create a dataFrame out of these\n",
    "ignitionDelays = pd.DataFrame(data={'T':T})\n",
    "ignitionDelays['ignDelay'] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the code above for each temperature, and save the IDT for each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computed Ignition Delay: 6.364e-07 seconds for T=1800K. Took 2.31s to compute\n",
      "Computed Ignition Delay: 1.583e-06 seconds for T=1600K. Took 2.71s to compute\n",
      "Computed Ignition Delay: 5.787e-06 seconds for T=1400K. Took 2.82s to compute\n",
      "Computed Ignition Delay: 3.911e-05 seconds for T=1200K. Took 3.09s to compute\n",
      "Computed Ignition Delay: 1.326e-04 seconds for T=1100K. Took 3.42s to compute\n",
      "Computed Ignition Delay: 1.839e-04 seconds for T=1075K. Took 3.63s to compute\n",
      "Computed Ignition Delay: 2.533e-04 seconds for T=1050K. Took 3.30s to compute\n",
      "Computed Ignition Delay: 3.365e-04 seconds for T=1025K. Took 3.50s to compute\n",
      "Computed Ignition Delay: 4.093e-04 seconds for T=1000K. Took 3.88s to compute\n",
      "Computed Ignition Delay: 4.289e-04 seconds for T=975K. Took 3.75s to compute\n",
      "Computed Ignition Delay: 3.911e-04 seconds for T=950K. Took 3.91s to compute\n",
      "Computed Ignition Delay: 3.407e-04 seconds for T=925K. Took 4.33s to compute\n",
      "Computed Ignition Delay: 3.145e-04 seconds for T=900K. Took 4.27s to compute\n",
      "Computed Ignition Delay: 3.233e-04 seconds for T=850K. Took 4.03s to compute\n",
      "Computed Ignition Delay: 3.439e-04 seconds for T=825K. Took 4.52s to compute\n",
      "Computed Ignition Delay: 3.852e-04 seconds for T=800K. Took 4.56s to compute\n",
      "Computed Ignition Delay: 6.824e-04 seconds for T=750K. Took 4.67s to compute\n",
      "Computed Ignition Delay: 2.057e-03 seconds for T=700K. Took 5.28s to compute\n"
     ]
    }
   ],
   "source": [
    "for i, temperature in enumerate(T):\n",
    "    # Set up the gas and reactor\n",
    "    reactorTemperature = temperature\n",
    "    reactorPressure = 40.0*101325.0\n",
    "    gas.TP = reactorTemperature, reactorPressure\n",
    "    gas.set_equivalence_ratio(phi=1.0, fuel='c12h26', oxidizer={'o2':1.0, 'n2':3.76})\n",
    "    r = ct.Reactor(contents=gas)\n",
    "    reactorNetwork = ct.ReactorNet([r])\n",
    "\n",
    "    # Create an empty data frame\n",
    "    timeHistory = pd.DataFrame(columns=timeHistory.columns)\n",
    "\n",
    "    t0 = time.time()\n",
    "\n",
    "    t = 0\n",
    "    counter = 0\n",
    "    while t < estimatedIgnitionDelayTimes[i]:\n",
    "        t = reactorNetwork.step()\n",
    "        if not counter % 20:\n",
    "            timeHistory.loc[t] = r.get_state()\n",
    "        counter += 1\n",
    "\n",
    "    tau = ignitionDelay(timeHistory, 'oh')\n",
    "    t1 = time.time()\n",
    "\n",
    "    print('Computed Ignition Delay: {:.3e} seconds for T={}K. Took {:3.2f}s to compute'.format(tau, temperature, t1-t0))\n",
    "\n",
    "    ignitionDelays.at[i, 'ignDelay'] = tau"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure: ignition delay ($\\tau$) vs. the inverse of temperature ($\\frac{1000}{T}$). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.semilogy(1000/ignitionDelays['T'], ignitionDelays['ignDelay'],'o-',color='b')\n",
    "ax.set_ylabel('Ignition Delay (s)',fontname='Times New Roman',fontsize=16)\n",
    "ax.set_xlabel(r'$\\mathdefault{1000/T\\, (K^{-1})}$', fontsize=16,fontname='Times New Roman')\n",
    "\n",
    "# Add a second axis on top to plot the temperature for better readability\n",
    "ax2 = ax.twiny()\n",
    "ticks = ax.get_xticks()\n",
    "ax2.set_xticks(ticks)\n",
    "ax2.set_xticklabels((1000/ticks).round(1))\n",
    "ax2.set_xlim(ax.get_xlim())\n",
    "ax2.set_xlabel('Temperature (K)',fontname='Times New Roman',fontsize=16);\n",
    "\n",
    "for tick in ax.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax2.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extension - looking at non-ideal impacts on NTC.\n",
    "\n",
    "Using Cantera's object-oriented nature, and branching functions in Git, it is possible to explore the impacts of non-ideal effects on NTC behavior.  \n",
    "\n",
    "As published in _Combust. Flame_ in 2017 (see above for reference), we created three different thermodynamic models to explore NTC of n-dodecane:\n",
    "\n",
    "- 'Ideal gas': An ideal gas model.\n",
    "- 'R-K $\\left(\\left[X_k\\right]\\right)$': A model which (incorrectly) used used the Redlich-Kwong model for the equation of state (EoS - phase density and species concentrations) but uses the ideal gas model for chemical kinetics (i.e. activity coefficients \n",
    "$\\gamma_k = 1$ and $\\dot{q} = k_{\\rm fwd}\\prod\\left[X_k\\right]^{\\nu^\\prime_k} - k_{\\rm rev}\\prod\\left[X_k\\right]^{\\nu^{\\prime\\prime}_k}$).\n",
    "- 'R-K $\\left(\\gamma_k\\right)$':A model which (correctly) used the Redlich-Kwong model for both EoS and activity coefficient calculations, such that $\\dot{q} = k_{\\rm fwd}\\prod\\left(\\gamma_k\\left[X_k\\right]\\right)^{\\nu^\\prime_k} - k_{\\rm rev}\\prod\\left(\\gamma_k\\left[X_k\\right]\\right)^{\\nu^{\\prime\\prime}_k}$\n",
    "\n",
    "### \"Low\" pressure (40 atm)\n",
    "<img src=\"images/IDT_40atm.png\"  width=\"500\">\n",
    "\n",
    "### Intermediate pressure (60 atm)\n",
    "<img src=\"images/IDT_60atm_zoomed.png\"  width=\"500\">\n",
    "\n",
    "### High pressure (80 atm)\n",
    "<img src=\"images/IDT_80atm_zoomed.png\"  width=\"500\">\n",
    "\n"
   ]
  }
 ],
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