diff --git a/examples/timoshenko/.ipynb_checkpoints/beam_buckling-checkpoint.ipynb b/examples/timoshenko/.ipynb_checkpoints/beam_buckling-checkpoint.ipynb
index 34a3cfad9aafdb26c3e1ee7ea87fd2244f4ccfc6..145f111f04dfafc62721bab8783e71d43a0ff510 100644
--- a/examples/timoshenko/.ipynb_checkpoints/beam_buckling-checkpoint.ipynb
+++ b/examples/timoshenko/.ipynb_checkpoints/beam_buckling-checkpoint.ipynb
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,17 +79,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n",
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/ffc/uflacs/analysis/dependencies.py:61: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  active[targets] = 1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/ffc/uflacs/analysis/dependencies.py:61: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  active[targets] = 1\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "(<dolfin.cpp.la.PETScMatrix at 0x7fabd944fba0>,\n",
-       " <dolfin.cpp.la.Vector at 0x7fabd944fb48>)"
+       "(<dolfin.cpp.la.PETScMatrix at 0x7fdbf38b0990>,\n",
+       " <dolfin.cpp.la.Vector at 0x7fdbf38b00f8>)"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -130,9 +161,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/ffc/uflacs/analysis/dependencies.py:61: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  active[targets] = 1\n"
+     ]
+    }
+   ],
    "source": [
     "N0 = Constant(1e-3)\n",
     "kg_form = N0*dot(grad(w_), grad(dw))*dx\n",
@@ -155,823 +202,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Computing 3 first eigenvalues...\n"
+      "Computing 3 first eigenvalues...\n",
+      "Critical buckling loads:\n",
+      "Exact:    0.31800  FE:    0.31805  Rel. gap 0.01%%\n",
+      "Exact:    0.93995  FE:    0.94033  Rel. gap 0.04%%\n",
+      "Exact:    1.87267  FE:    1.87415  Rel. gap 0.08%%\n"
      ]
     },
     {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        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"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/bleyerj/.local/lib/python3.6/site-packages/matplotlib/font_manager.py:1241: UserWarning: findfont: Font family ['serif'] not found. Falling back to DejaVu Sans.\n",
+      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
+     ]
     },
     {
      "data": {
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\" 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+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Critical buckling loads:\n",
-      "Exact:    0.31800  FE:    0.31805  Rel. gap 0.01%%\n",
-      "Exact:    0.93995  FE:    0.94033  Rel. gap 0.04%%\n",
-      "Exact:    1.87267  FE:    1.87415  Rel. gap 0.08%%\n"
-     ]
     }
    ],
    "source": [
     "eigensolver = SLEPcEigenSolver(K, KG)\n",
     "eigensolver.parameters['problem_type'] = 'gen_hermitian'\n",
-    "eigensolver.parameters[\"spectrum\"] = \"smallest real\"\n",
     "eigensolver.parameters['spectral_transform'] = 'shift-and-invert'\n",
     "eigensolver.parameters['spectral_shift'] = 1e-3\n",
     "eigensolver.parameters['tolerance'] = 1e-12\n",
diff --git a/examples/timoshenko/beam_buckling.ipynb b/examples/timoshenko/beam_buckling.ipynb
index 34a3cfad9aafdb26c3e1ee7ea87fd2244f4ccfc6..145f111f04dfafc62721bab8783e71d43a0ff510 100644
--- a/examples/timoshenko/beam_buckling.ipynb
+++ b/examples/timoshenko/beam_buckling.ipynb
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,17 +79,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n",
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/ffc/uflacs/analysis/dependencies.py:61: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  active[targets] = 1\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/ffc/uflacs/analysis/dependencies.py:61: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  active[targets] = 1\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "(<dolfin.cpp.la.PETScMatrix at 0x7fabd944fba0>,\n",
-       " <dolfin.cpp.la.Vector at 0x7fabd944fb48>)"
+       "(<dolfin.cpp.la.PETScMatrix at 0x7fdbf38b0990>,\n",
+       " <dolfin.cpp.la.Vector at 0x7fdbf38b00f8>)"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -130,9 +161,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/ffc/uflacs/analysis/dependencies.py:61: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
+      "  active[targets] = 1\n"
+     ]
+    }
+   ],
    "source": [
     "N0 = Constant(1e-3)\n",
     "kg_form = N0*dot(grad(w_), grad(dw))*dx\n",
@@ -155,823 +202,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Computing 3 first eigenvalues...\n"
+      "Computing 3 first eigenvalues...\n",
+      "Critical buckling loads:\n",
+      "Exact:    0.31800  FE:    0.31805  Rel. gap 0.01%%\n",
+      "Exact:    0.93995  FE:    0.94033  Rel. gap 0.04%%\n",
+      "Exact:    1.87267  FE:    1.87415  Rel. gap 0.08%%\n"
      ]
     },
     {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        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"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/bleyerj/.local/lib/python3.6/site-packages/matplotlib/font_manager.py:1241: UserWarning: findfont: Font family ['serif'] not found. Falling back to DejaVu Sans.\n",
+      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
+     ]
     },
     {
      "data": {
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B8aPH6/UdsrbGT9+PGbMmKEsyfvdvXs3xo8fj7q6OuUcyueouro65bPyuZ43b56mJnW0ay8QCOChhx5Sjknul+l2uwtWA3jq1CkKoNkFKAS59gHMlAXMJBDrEg4z81SD3wdseARw/0dmUXv8fKD+R8BbE4ADq4DjrUDwBBDNcg6H+oAT+4CDq4Edc4CV9wKzKzPvZ8YFQNOfgc5dgEUGIzYLJoGUN5liEQgEUF1drekzFwgE4PV6R+2HSFJhEoh+bCWAQOZxjIwMAyP/OiPmEYlE0NzcrNS62JJYDPjYAyz+KTDx3FQRe+wzwMIfA7tfBs4cin++kPR2AHuXIPbGvRiZmqGm8MXrgLY3C7/vMqFYM4FwZhYxyBQLeYiUdMgzoBB96L2H/H4/BdDsAhSCXAQwXWq9nLGUK8wiIkIQjQCti4A5Y1OFa/LngGW/BvYtj9fclbJMH20EGu4GpnwhtVzPXQG8/3r8c0SBWcD2xOfzoaqqKm0WrjwtHNEHs4D1UxYCmCmBQ/7llJj0kWkquHzmKJQvoEKMdUSMEYvFlM7GtiEWAw6sBJ65NFWwZn8b2DYLGCh994SUWAwF44L6wjWp5XzqIuCDBjYN/4ti1QAODw+zBlAARouFz+fTDAEj1wrm826yM3rvIblLGAXQggQCAdTW1iqdcRM7icrIU7wlZ/3KN5p8g+Uz3hLAPoAiYas+gJIUb+qd+91UoXr15ngTq4k1axljIUnxWsGXfpha7pdvBE5+YE6BBYJ9AMsbxqL4sA+gfiwrgCJAARQH2whgbwew2JVGoP4L6Ggxu3QAdMRCkoCjO4AFt2qPYVIF8OaDwKB9+9RSAMsbxqL4UAD1QwE0AAVQHMpeAKNhYMfTqf3p5n4X+PgtoZpQc4rFRxtS+y7O+Eq8f6BAx1QqKIDlDWNRfCiA+qEAGoBZwOIQiUTQ0tJSnlnAnbuAF67WStLMb8T7zgn4Isk5FpFhYPtsYOp52mNcdqftagOL1Qfw7Nmz7AMoAIxF8WEWsH4ogAZgFhEpKpERYOM/k4Z0ORdY+1A8saLcCJ4AGn6bKrqHm80uWclgFjAhxmAWsH4ogAaQL6De3l6zi2J7otEo2tvblVkWLM+Zj4F530tt7j22x+ySZcVwLA6sBKb/u/bY1z4EhEOFLaiAFKsGMBQKsdZJABiL4qP3Hurt7aUAml0AK8M+gOJQNn0AJQnYUw9M/WLCWH6fjff/s8iYeQWJRfB4apJI3Q+Avq5CFVNI2AewvGEsig/7AOqHAmgACqA4lIUAhgLA67/USs+zl8WnXbMQBYtFLAa8Ow+Y8nn1fDzx1XgGcZlCASxvGIviQwHUDwXQABRAcbC8AHa3pWbDrvkjMDJodslypuCxOLk/PmC0MqXdp4H3XizLLGEKYHnDWBQfCqB+KIAGYB9AcYhGo2htbbVmH8C2NcC0f9MOg9L2ptmlypuixGLQDyz4b60gN/5vPIO4jChWH8DBwUH2OxMAxqL4sA+gfiiABmAWETFELAZsnpaa6BH4xOySiUk0Amz8h/Z81d9SVhnRzAImVsPn88Hr9cLn85ldFADMAs4FCqABWAMoDparARzuB5b8TCszDXdbssk3maLHYt9y7YDYc78L9J8qzr5KjJ1rAAOBAFwuFyoqKuBwOFBdXY2amhplkf9frLnXPR4PXC4XqqurR5UZr9erfM7r9Wq+X1FRMep3rRILvcgxczgcmmlYC4HH40Ftba0Se71TtrIGUD8UQAOwD6A4WKoPYP9JYO412inQdswpmz5tJYlF5654U7l8Dp++GOg5XLz9lQj2AQTq6urgcDjSipQsiMWUQIfDoRG7dPh8PjgcDjQ0NGi+63Q6RxVAq8VCL1VVVQUVQK/Xq9leIBBARUUFampqsn6XfQD1QwE0AAVQHCwjgKc/BGZXquIy/XzgkMfsUhWUksXi9IfArG9pM4SP7y3uPosMBRBoaGjIKICBQAAOhwO1tbVF278eAQSAiooKjQDqwWqx0EuhBTCd6I32wyARCqB+KIAGoACKgyUEsOMd7QDHsyvjElNmlDQWfceA565Uz+m0fwOObi/+fosEBXB0AQSgNA8XCwpg7hRaACsqKlK25/V64XA4sjYFUwD1QwE0APsAioPwM4EcXA1M/lxCv7Vr4k3BZUjJYxHqBV66QT23U79o2bECORPI6AKYTgLkJITEZmEjiQn5CqDP54PH4xm1edpqsdBLoQXQ6XSm1PIWWgDZB5ACaAhmERFd7HlVO5/vglvLKnNVCMIhYNHtCRJ4HtDRYnapcoZZwJkF0Ofzwel0apoH5YSMxP54gUAANTU1cDgcaZsSvV4vampq4Ha74Xa7U4QiUQDlvmdyrWOi3CUKoM/nQ3V1taYcHo8HVVVVyvYaGhrQ0NCAmpqajE3YbrcbtbW1yr91dXWoq6uDy+Ua9ZyNti/5HHg8HtTV1cHtdsPlcqUVVa/Xq9lvOqnz+XzK+ZP3k0kAPR6Pco5rampyrjFNRL4ussk5s4D1QwE0gHwB+f1+s4tieyKRCFpaWhCJCDZd2s4XtJm+K+8FIiNml6qomBaL8BCw6CdJEvhOactgkKwvr3nfB2ZemNMizbwQsSf/E1KO38t7mfd9Q+dAftHL4lBXV4fa2lo4nc6MtT/JCRkAlKzhRLxeL5xOp0Z+ampqNNtNlgyXywWPJ7Wfbrom4HTlkPssBgIBSJKEs2fPpv1uXV2dpmk78f/p9p+OxH0lltPtdqccU/K58Xg8KU3rDQ0NGvlMd/7kmrlkAUwnrk6nM28JrK6u1tX0r1cA/X4/BdDsAlgZ9gEUByH7AG6bpZW/DY+UTabvaJgai2QJnPZvwCc7S1+OPMn68pp5ofaaEnGZeaGhczBaE3BtbS2qqqpS/pZOqNJJjtPpTBGV5NqrRAFMlqls+8y0Tq7xk/sAXn/99Sm1gFVVVZp1cqZxLhnPifuSqa6uRlVVlWad2+1OWVdRUZFVdNOdv0zr022vtrY2r/6bDQ0NKeKZCfYB1A8F0AAUQHEQSgAlKXWA5+aptpA/QIBYhIeAhT/WSmDXbnPKkiOsAcyeBOJ0OtPKSzYBlIUqW22aLIAul2vUfm25CKC8ThbA22+/PUVOM5U3VwHUI8LJAijX4qXbl8vlgsvlUsqTrgk2WaLl4XTkGtzEmtxcM7gDgUDW4XUSoQDqhwJoAAqgOJguHTKSBGz8p1b+ts00t0wlRohYhIeAhbclTK93AXD6I/PKoxNmAWcXQLl/X+Lf9YiPLCXZRMLhcMDlcinDjhSiBlCPAMrjCMrIgyDnQi4CmLiv0Y7V5XKhqqpq1POXLIDZzl0uZBuYOxkKoH4ogAaQBbBYg5IS/cRiMXR0dJj7kpOkeDNvovztfMG88piEELEA4okhr96sxmLWt+LDxghMsbKAh4eHLZN5mk0Aa2trU2qi0olPch/AXGsA5W1kSsDIRwDlWGTqg9fQ0KAkgeid+SLb/vUIoCx36d5l8jkY7fwlC6Bco6gnm3o0ampqUrZRqCQQeUxJCiDJC2YREQ2bJifI37nA7lfMLhEZCsanipPj8twVwKC4SVvMAs4ugHK2ayLpxCc5Y1helylbVSZx37Ik6E0C0bsuk5QZrUzIVwAzfVdeL8torn0A031W73AxdXV1Kefd5/NlTSJhFrB+KIAGYBawOEQiETQ3N5uXBbzlCW3Nn43lz/RYJHO2G3h6jBqb+dXCzrlcrBrAYDBomRrA0WZ8cLvdaTNtk/vryc2pVVVVGqmS5+tNHjMwWQATa5nkDORkOcuU8TvaOjkW6TKU5do/n8+HQCCQlwzqzYZOJ4DycC6JJGcmJzdTy+vSzc6S7lx7PB5dGc1yRrI8VI+8JM+/nA5mAeuHAmgA9gEUB1P7ne14Wit/7+bedFNOCNEHMBn/EeCJr6kxWuwCogKV71/YuQ9gIBBQ5vqVx92Tx7GrqalRhgFJJwA+n0+RQLnmSN5WsrAkJnjI49gBqnQ4HA5UVVUp6+UaR3kIk8SxB+WaL6/Xq3xXHq4m3ef8fj/uuusuOByOlLltE8cclBf5M9lkMN2+EsdDTNyXLLTyOImJop08RmK62jr5M/I4gbI4ppuhJfFcp6vRy0TyeUhcssE+gPqhABqAAigOpknHu/O08tfyTGn3LyBCCiAAnNgHPP5lNVZrHhAuM9vOAmgHMsUiEAikyG0gEFDEMttA0ESFAqgfCqABKIDiYIp0tC7Wyt/WJ0q3b4ERVgAB4Mg2YPJn1Zi987zZJdJAASxvMsVCHiIlHfIMKEQfFED9UAANwCxgcYjFYuju7i7dS659LTDpUwnj/E0pzX4tQMljkSvvv65N1vlwvdklUihWH8BwOGyZPoDlTKZY+Hy+lP6KMvK0cEQfzALWDwXQAMwisikdLcCUz6sSsfYh4ZoSSRaap2gHij653+wSAWAWsJ3x+XyaIWDkWkEj8+faEWYB64cCaAA2AYtDOBxGU1NT8ZsdT+4HHj9flYeGuwFRa7pMomSxMEIsBiy7U43j7G/Hs4VNhk3A5Q1jUXzYBKwfCqABKIDiUJJ+Z71HgSe/rkrDwh8DkZHi7c+iCN0HMJGRQaDuWjWeL46LDx5tIhTA8oaxKD4UQP1QAA1AARSHokvH2dPAnLFaWRgZKM6+LI5lBBAA+k8Cs76pxnXVH0xtzqcAljeMRfGhAOqHAmgACqA4FFU6RgaBF69TJeHZy4WeTcJsLCWAQHx4mKlfVOO76yXTikIBLG8Yi+JDAdQPBdAAsgD29fWZXRTbU7TZDmJR4LVfqHIw80Kgr6uw+ygzrDbzBADggwY1xo99BujcZUoxipUFHI1GrRWPMoWxKD5676G+vj4KoNkFsDIUQHEo2lAX6/6WkC36JWGyRUXGssOOrP97guh/w5SkkGIJYCwWs148yhDGovhQAPVDATQAm4DFoSjNju88rwrBpE8BhzYVbttljOWagGWiYeCVm9SYv3JTyaeLYxNwecNYFB82AeuHAmgACqA4FFw6Dq6ODxIsy4B3YWG2awMsK4BAvNZv5jfUuK//e0l3TwEsbxiL4kMB1A8F0AAUQHEoqHR07dEO9MxZPnLC0gIIxPv/PfYZNf4HVpZs1xTA8oaxKD4UQP1QAA1AARSHgklHX5d2rL83xnOWjxyxvAACwO6X1Wvg8S8Dfl9JdksBLG/KMRY+nw9erxc+X2nukWxQAPVDATQAk0DEoSCJByMDwNxr1Bf/yzcCkeHCFdImWDYJJBFJAlb8Tr0W5n2/JNeCnZNAAoEAXC4XKioq4HA4UF1djZqaGmWR/1+sudc9Hg9cLheqq6tHlRmv16t8zuv1ar5fUVEx6netEgu9yDFzOBxwu90F3bbH41GmxqupqdE9HzKTQPRDATQABVAcDA89Eotph3t5+mJggDW7+WDJYWDSMdwPzLlEvSbW/a3ou+QwMEBdXR0cDkdakZIFsZgS6HA4NGKXDp/PB4fDoZmn1+PxwOl0ZhVAK8VCL1VVVQUVQI/Hg7q6Os06p9MJl8uV9bsUQP1QAA3AJmBxMNzs6JmkbfLrbi9sAW1EWTQBy5zYB0z+nHpttL1Z1N2xCRhoaGjIKICBQAAOh0N3bVA+6BFAAKioqNAIoB6sFgu9FFoAa2pq4HQ6U9Y5HNmVhU3A+qEAGoACKA6GpGPv0oThXiqAjz2FL6CNKCsBBIBd89XrY/r5QOCTou2KAji6AAJQmoeLBQUwdwotgA0NDSm1fRTAwkMBNAAFUBzylo7O94DJn1Vf8DvnFqeANqLsBFCSgGW/Vq+R+dcXbXxACuDoAuj1euFwODTNg3ISQmKzsJHEhHwF0OfzwePxjNo8bbVY6KXQApiOQjcBUwApgIagAIpDOBxGU1NTbtLRdwx44mvqi/3NPzHjtwDkFQvRGeoDnrpIvVY2TS7ObiiAGQXQ5/PB6XSipqZGWScnZCT2xwsEAkptUeJnE79TU1MDt9sNt9ud0tcsUQADgYAmKSVR7hIF0Ofzobq6WlMOj8RfzXgAACAASURBVMeDqqoqZXsNDQ1YtmwZ7rrrLjz00ENpj93tdiuJD7W1tairq0NdXV1W8Um3r4aGBiWBRv5MXV0d3G43XC5XWlH1er2a/aaTOp/Pp5w/eT+ZBNDj8SjnuKamJucaU5m6ujo4nU5dfT8pgPqhABpAFkA7X0CWJRwC6n6gvtBfvbnksz4Qi3FsD/DYp9WuAh3vFHwXxRBAqyELoCwOdXV1qK2thdPpTJE1meSEDABK1nAiXq83RSRqamo0202uAXS5XPB4UruFpGsCTlcOuc9iJnmUqaur0zRtJ/4/3f7TkWlfbrc75ZiSz43H40lpWk9uik13/uRa2WQBTCeuTqczJwn0eDyoqalBVVWV7tpcvfcQ398UQEPIF1CxMtKIfmKxGLq7u/XVckhSfHw/Wf5mVzLjt4DkFAursW2m9roZKuwIANleXne8eQfGLR+X+7Isj+/kudzx5h2GzsFoTcC1tbVpZSCdUKWTHKfTmSIqybVXiQKYLFPZ9plpnZy0Ig+RVF1dnZLIUlVVpVknZxrn8n5J3JdMdXU1qqqqNOvcbnfKuoqKiqyim+78ZVqfbnu1tbV59d8MBAKj/gBIRK8AyglFFECSF2wCFoec+p21PKu+xKd+ETj5QfELaCPKrg9gIrGodr7gFb8r6OazvbzGLR+HyvpKoZdxy8cZOgfZkkCcTmdaeckmgLJQZatNkwXQ5XKN2q8tFwGU18nN8bfffnuKnGYqb64CqEeEkwVQrsVLty+XywWXy6WUJ13/yGSJlofTkWtwE2ty883glocHytY/k03A+qEAGoACKA66pePQpnjznQnTfNmFshZAIJ4F/Pj56jX0QX79mtJRrBrA616/rixqAAE1GzTx73rER5aSbE2JDocDLpdLEY5C1ADqEUB5HEGZ2tratH0YRyMXAUzc12jH6nK5UFVVNer5SxbAbOcuG8lJPfI6PUMAUQD1QwE0AAVQHHRJh98HTP93zvFbZMpeAAFg3/KEcSMLNzQMk0CyC2BtbW1KTVA68UnuA5hrDaC8jUwJGMUQwIaGBiUJRE9zp54y6RFAWe7SCZt8DkY7f8kCKMuanmzqZOSm2XT9NymAhYUCaABZAP1+v9lFsT2RSATNzc2IRCLpPzAyADx/lfrSXvKz+OwfpOBkjUW5sOIe9Xp65aZ487BBijUTiJVmZskmgHK2ayLpxCc5Y1helylbVSZx37KM6E0CybZOjkUmKTPanzxfAcz0XXm9LKO59gFM91k9w8U4nc4UeZSvi2wCr/ce8vv9FECzC2BlmEVkESQJaPit+rJ+5lJgiDEjBgkFgNnfVq+rlmcMb5JZwKNPBed2u9Nm2ib315ObU6uqqjRSJc/XmzxmYLIAJsqHnIGcLGeZMn71rEuXoSzX/vl8PgQCgbxkUO++0gmgPJxLIsmZycnN1PK6dDVz6c61x+PRldGcnLUMxMVfTwIJs4D1QwE0ALOAxSEWi6GjoyN9M1di0se0LwGnPyp9AW3EqLEoN47uACaeG7+2Jn/O8BSCxaoBHB4eFr4GMBAIKHP9yuPuyePY1dTUoLq6GtXV1WmbFX0+nyKBdXV18Hg8yraShSUxwUMexw5Qh0FxOByoqqpS1ss1jvIQJoljD8o1X16vV/munK2a7nO9vb2455574HA4UFFRoRGzxDEH5UX+TLZ3TLp9JY6HmLgvWWjlZtZE0U4eIzFdbZ38GXmcQFkc083Qkniu5bjoRR7HsLa2NmtCTiLMAtYPBdAA7AMoDhn7nR3ZCkz6VMnmciU26QOYyIZH1Our7gdANP+mb/YBLG8yxSIQCKTIbSAQUMRSzwwYJA77AOqHAmgACqA4pJWOQCfg/o+iz95AtNhOAMMh4NnL1OtsyxN5b4oCWN5kioU8REo65BlQiD4ogPqhABqAAigOKdIRHtLO9LHoJwXppE+yYzsBBICuPerwQo99BjixL6/NUADLm0yx8Pl8Kf0VZeRp4Yg+KID6oQAagFnA4hCJRNDS0qJmnq6+X5W/py8GQr3mFtBGpMTCLmyarF5zL1wNRIZz3kSx+gCePXtW+D6AdmC0WPh8Ps0QMHKtYL7z59oVZgHrhwJoAGYRCcqeevVFPOULwMn9ZpeI2IHISFz8lC4Hj+W8CWYBE2IMZgHrhwJoAPkC6u1l7ZLZRKNRtLe3I9q5O56NKb+E33/d7KLZDiUWURs2uZ/8IN4EPPGceJPwsT05fb1YNYChUIg1gALAWBQfvfdQb28vBdDsAlgZ9gEUh3A4jHUrFkGa9S1V/tb+1exi2RJb9gFMZMsT6jX4/HfiNYM6YR/A8oaxKD7sA6gfCqABKIDiEB4eQvfMhOa3+dU5vXhJ4bC9AEbDwNxr1Gtx8+O6v0oBLG8Yi+JDAdQPBdAAFEBxiL71mPrCfeKrQPC42UWyLbYXQCCeBfzYp/+VFfxp3f1Q5ZdXKBQqWFEoHeLAWBSfUChEAdQJBdAA7AMoCB+uV+RPmvQp4Mg2s0tka6LRKFpbW+3ZBzCRxKzged/XNUB0OBxGW1tbQV9KkiRhcHCQ/c4EgLEoPsFgEG1tbVl/gLIPIAXQEMwiEgD/EWD6+eqLdsccs0tESJzIMPDs5eq1uf0pXV/z+Xzo7OykJBCSI5IkobOzM+080snw/U0BNARrAE0mHALmfld5wQbm3YKo3caeExDWACbQuUs7V/CZj7N+Ra7B6OzsRDAYRCgUwtDQUN5LKBRCb2+v4e1wMb4wFsU7r8FgEJ2dnbpr0FkDWAYC6PP5lMmr5cEz9VBVVQWPx4NAIIBAIKBMbJ0L7ANoMo3/qzb9zhmLpjdes3e/M0FgH8AkEucKfukGQEf/r2AwCJ/Ph7a2NsPLwYMHsWfPHhw8eLAg2+PCWIi6+Hw+3ULHPoAWF8BAIACn06mZPqempkaXBDocDs1SXV2d8/4pgCbiXaC+VKd+EeFj+ygdgkABTGJkEHh6jHq97pqv+6vhcNhw7Uh/fz+amprQ399vek2N3RfGonhLrs8bCqDFBbC2thY1NTWadT6fDxUVFVm/K4ui2+2G1+vNa/8UQJM48b52sOd9yygdAsFYpOHIVvV6nfalkmapMx7iwFiIAwXQ4gLodDrT1vY5HI6sUpdrc2862AfQBEK9wFMXqS/Tpj8DsPnsE4LBWGSg8T71un3tFyXbLeMhDoyFOLAPoMUF0OFwwOPxpKyvqKjIKniFFEA7X0AlJRYDltyhvkRfvC6eaUmIFRj0x8eolK/ftjVml4gQ28L3t4UFMBAIZBRAp9OJ2traUb9fW1urJI643W5dQjg8PIxgMKgsXV1dcDgcOHXqFMLhMMLhsPLLLhqNKusS10ciEc16eUDQTOsT14XDYUiSBEmSdK8H4oOPJq6L/CtTNtP6TGU3+5iib7vVpI8ZFyB85ojyt6GhIbS0tGBkZMRSx1SOcQqFQti+fTsikUjZHFOh4hR5f5l6DT/5nwj39xT9mOR4yH8r52tP9GOSYyHPB1wOx2TVOHV3d1MAzS5Avvh8vlEFMLlvYDIul0vz/5qamqzSOHHixJTkEYfDgaVLl6KxsRGNjY1obW0FALS2tirrGhsb0d7eDgBoaWnRrO/o6AAANDc3a9Z3d3cDAJqamjTrg8EgwuGwZp3cpyQYDGrWNTU1AYhf6Inrm5ubAQAdHR2a9S0tLQCA9vZ2zXoRjmnHommQ5OE0Jp6LwO4Vms9u2rQJjY2N8Pl8ljmmcoxT8vpyOqaCxGnVKvS9cIMigUeeva1kxzQ4OGiLa4/HxGPSc0yrV6+mAJpdgHwxKoDJeDweOBwOTUZxMplqAE+ePMlfWMU8pp4OSG6n2nT29oyUsodCITQ2NmJ4eNgax1SOcfrX/wcHB5WHfrkcU0Hj5O8App6nXM8R3/aiHpMcj5GRkbK/9kQ/JjkW8mwg5XBMVo3TqVOnKIBmFyBfZAFsaGhI+VtFRUXW2rxk5CbldNvLBLOAS0BkBJhfrcrfop+kHUctHGZ2nSgwFjrY+YJ6TT97efw6LxKMhzgwFuLALGALC6AsbJmygEfr01dTU5NScyhvL5fkEFkAR6s1JAZZ9zf1RTn72/GO9GmIxWLo6OjgJOsCwFjoIBYF6q5Vr+2tTxRvV4yHMDAW4iC/8ymAFsXpdKYVtmzDwKQTx9GalDPBLKIis3+F+oKc/Fng2B6zS0RI4TixD5j0qfj1PeXzgD/7/KWEkMLA97fFBTDdQNBerxcOx+iHla55uK6uDhUVFTnV5skXkN+fvlaKGKC7XdNPCrteGvXjkUgEzc3NSj8RYh6MRQ4kThO38MeAJBV8F4yHODAW4uD3+ymAZhfACJmmgkvsx+fz+eB0OjU1ex6PR/MZeTu59P8D2AewaAz3A89epr4YV96b9cXIvjXiwFjkwPBZYNa31Gt9/4qC74LxEAfGQhzYB9DiAgjEBa+2thZ1dXXKv8l/r6ioSGna9Xg8Sg2iy+XKqelXhgJYBCQJWHan+kJ84er4XKpZ4INVHBiLHGlvUq/3J78ODPUVdPOMhzgwFuJAASwDATQTCmAReOd59WX4+PlAz2FdX+ODVRwYizxY+vOE6Q3/UtBNMx7iwFiIAwWQAmgIZgEXmI53gMc+rb4I25t0fzUWi6G7u5vZdQLAWORBoDOhz+u5QFfhEp4YD3FgLMSBWcAUQEMwi6iA9J8CnvxPVf48E80uESGlpeUZ9fqf+10gykQBQooF398UQEOwCbhARMPAyzeqL7/6W3J++YXDYTQ1NbFpRQAYizyJRoAXrlHvg3fnFWSzjIc4MBbiwCZgCqAhKIAFInGw51nfBM6eznkT7FsjDoyFATp3JfSB/TLQf9LwJhkPcWAsxIECSAE0BAWwAHzQoB3sOc++T3ywigNjYZDV96v3RMPdhjfHeIgDYyEOFEAKoCEogAY5dQCY+kX1Zbf75bw3xQerODAWBhn0AzMuUO8L39uGNsd4iANjIQ4UQAqgIWQB7Osr7LhdtiAUAOaMVV9yq+4zNAuCJEkIBoOQijCTAskNxqIAeBeo98YzlwKR4bw3xXiIA2MhDn19fRRAswtgZSiAeRKLAUt+pr7g5n0PCIcMbVKSJITDYT5YBYCxKACxGDC/Wr1Htj6Z96YYD3FgLMSBAkgBNASbgPPk7enqi23GV4DeDsObZNOKODAWBeLkB8Ckivh9MuXzQO/RvDbDeIgDYyEObAKmABqCApgH7WtV+ZtUARzaVJDN8sEqDoxFAVn/sHq/LLkjr00wHuLAWIgDBZACaAgKYI6c/giY9iX1hbb9qYJtmg9WcWAsCshQUDtA+ofrct4E4yEOjIU4UAApgIagAObAUBB49jL1Rbb8LkNJH8nwwSoOjEWBSRwq6amLcu4vy3iIA2MhDhRACqAhmASik1hMO9n981cBIwMF3QU7V4sDY1FgJAl49Wb1/tn8eI5fZzxEgbEQByaBUAANQQHUydsz1JfX9H8H/L6C74LDK4gDY1EEutuBxz79rwHTP5fTPcR4iANjIQ4UQAqgIdgErIO2Nar8TTwXOOQpym7YtCIOjEWR2PhP9V5a7NLdhYLxEAfGQhzYBEwBNAQFMAunDgBTz0tI+phdtF3xwSoOjEXh6Qn1oOPMQXz81IU4MO0z2Pv4Z7H7vWdx7OyxrLVJjIc4MBbiQAGkABqCAjgKAz3AU5Wq/K24p6BJH8nwwSoOjIUxJEnC0b6jWPHRCjyy/RH814r/QmV9ZcblqiVX4a71d2H6e9Ox8uOVODVwSrM9xkMcGAtxoABSAA1BAcxANAy88v9U+av7geGZPrIRDofR1NTEB6sAMBb54R/y44W9L2DcsnGjCl+25eIFF+N/N/0vNn+yGZFYhPEQCMZCHCiAFEBDyAJo5wsoLW8+qMrfk18HgsfNLhEhwtIR7MCUnVNw6aJL0wrdpYsuxW/W/wYPb3sYE1omYMrmv2DGMxfAPeffcd/cr2Hc6z/IKIPjlo3DHO+clFpBQuwO398UQEPIF1AgEDC7KOKwa74qf5M/B3TtLsluY7EYuru7EYvFSrI/khnGQh+dwU78afOfcFH9RRppG7NgDO59617M/2A+WrtbMRIdSf3yW49qEkJ6Q37sPLETz7Y+i+uXX58igpctugwv7nsx/bZIyeC9IQ6BQIACaHYBrAybgJM43AxM+pT6Ytq7tGS7Zt8acWAsRicmxbC4bTEuW3SZRtKuWHwF3LvcOH5WR4358Flg5oXqvda+VvlTNBbF1q6teKD5AYxZMEazj1tW3oIdx3YU8ejIaPDeEAc2AVMADUEBTOD0h8Dj56svpI3/KOnu+WAVB8YiM58EP8Gd6+7USNl1y67DSx+8hOBIji+i/SuyzhByevA0prwzJaWW8YHmB3Di7IkCHRXRC+8NcaAAUgANQQH8FwNn4i8g+WW09OdALFrSIvDBKg6MRSoxKYaFBxem1PpNe3caBsOD+W1UkoD6W9T77u3paT8WDocx9425+NXaX2n2ffXSq7H92HYDR0VyhfeGOFAAKYCGkAXQ7/ebXRTziAwDL92gvoTmXhNvnip1MSIRNDc3IxKJlHzfRAtjoWUoMoQH335QI183rrgRu07uMr7xxBlCpnwe6D2a8hE5HuFwGGsOr8G1y65VynFR/UWY9/48xCT2SSsFvDfEwe/3UwDNLoCVsX0WkSQBK36nyt/MbwB9x8wuFSHC4B/y45drf6mRv8fffTz/Wr90bHhEW/uehf6Rfvxf8/9pynR/8/3oH+kvXJkIERzbv79BATSE7bOAE+f4nfpF4HiraUWJxWLo6Ohgdp0AMBZxOoIduOmNmxTJunzx5djatbXwOxruB578T/Ve/Gij5s/p4hGTYnhx34uavoE3r7wZhwOHC18+osB7QxyYBUwBNISt+wC2LtbO8dv2pqnFYd8acWAsgNbuVnz3te9qxuNr62kr3g73LVfvx6fHAOEh5U+jxWPHsR245rVrNP0CD5w5ULxy2hzeG+LAPoAUQEPYVgAPedR+RxPPAXbMMbtEfLAKhN1jsa1rG6oWVilSdVvjbTg5cLK4O5Uk7ew7W59Q/pQtHl39XXCtcSnl/c6S72Bv997iltem2P3eEAkKIAXQELYUwON7gWn/pr5o1j5U1Dl+9cIHqzjYORa7T+7WzOgxfuP40vWtO3VQHYdzyheAwCcA9MVjIDyAu9bfpRmTcPfJ0gzibifsfG+IBgWQAmgI22UB93bEp3aT5e/1X5Z8uJdMRCIRtLS0MLtOAOwaiwM9B3DlkisVifrz239GOFbiF/36h7X3J/THIxQJ4Xcbf6eZPeSd4++UotS2wa73hogwC5gCaAhbZREN+oFnLlVfLi/dkHbgWULsyOHAYU2fv997fo9w1IRanqE+4ImvqffpoU05fX04Oow/eP6gHEfVwips69pWpMISYh62en9ngAJoAPkC6u3tNbsoxWVkAJhfrb5Unrk0LoQCEY1G0d7ejmhUjBpJO2O3WHT1d2HcsnGKNN257k6EIib+ONq7VHOvRkdCOcUjHA3jj5v/qKkJ3Hd6X5ELbQ/sdm+ITG9vLwXQ7AJYGVv0AYwMAwtvU18oT3493hQsGOxbIw52isWZ0BnNUC93vHkHzo6UfiB0DbEY8NIPlXs2umVmzvEIx8L489t/Vo7re699D58EPylioe2Bne4N0WEfQAqgIcpeAGNRYNmdqvw9fj5w8gOzS5UWPljFwS6xCEfDmnl9/3vVf6N3SJDWgBP7gEkVwMRzIE09DxuWv5JzPEaiI/jtht8qx3fTGzfBPyRWzb/VsMu9YQUogBRAQ5S1AEoSsPp+Vf6mfAH4ZKfZpcoIH6ziYJdYTNk5RR3nb/k4nBo4ZXaRtDT9Wbl/jz1VnVc8giNB3NZ4m3Kcv2j6hbnN2xbHLveGFaAAUgANUbZ9ACUJ2PhPVf4e+wzwscfsUo1KNBpFa2sr+9YIgB1isfLjlZpEif1n9ptdpFQG/YD7P9Sm4MNv57WZkwMnNX0c72++H1FBsv+thh3uDavAPoAUQEOUbRbR1ie1s3zsX2F2iQgRhn2n9+GShZcoQrTq0Cqzi5SZPfXqvfzs5UCemckf+j/UDHEz/b3pBS4oIaWlbN/fOUABNEBZ1gBun50gf+cAu18xu0S64C9rcSjnWJwJndHUhk17d5rZRRqdWAxS3bUFmbVn54mdGLtgrHLsb/rMnf7RipTzvWE1WANIATRE2fUB3DFHK387nja7RLph3xpxKNdYJCd93LnuztIP9JwHkY73IE08N35PT/s3IHgi7201fNSgHP/liy/Hx70fF7Ck5U+53htWhH0AKYCGKCsBfOc5rfxtm2V2iXKCD1ZxKNdYzN4zW5Gf65dfjzOhM2YXSRfhcBhHnrlVvbcb7s57W5Ik4Z87/qmch5tX3ly6qe7KgHK9N6wIBZACaIiyEcCdL2jlL2EieavAB6s4lGMsdp3chYvqL0JlfSXGLhyLD06LORxSOsLhMNauWARpxlfUe/xI/rN7DEWG8NM1P1Uk8I+b/whJgPnArUA53htWhQJIATREWfQBTJa/LW6zS5QXHGFfHMotFv0j/fhhww8V4Xl5/8tmFykn5HjEdr2s3ufPXZl3QggQn/3k6qVXW/acmEW53RtWhn0AKYCGsHQWkSQBb8/Qyt/bzOwjJJmHtz2siM5v1v/GukOgxGJAYkLIO88Z2tzWrq1KrejFCy7GeyfeK1BBCSk+ln5/FwgKoAHkC8jvt9jo+JIErP97WclfJBJBS0sLIpGI2UWxPeUUi3VH1inyd9WSq3DibP4JFGahicexPfGhnSaeA0z7kqGEEAB4bu9z6mDYy8YhMBQoUKnLk3K6N6yO3++nAJpdACtjyT6AsSjQeJ9W/gzWBIgA+9aIQ7nE4uTASVy19CrLD3uSEo81D6j3/op7DG07Goti/Mbxyjl68O0H2R9wFMrl3igH2AeQAmgIywlgZBhY9mv14T+pAvAuNLtUBYEPVnEoh1jEpBju3nC3IjYPbXnIsmKTEo9BPzDjgoSEkK2Gtt892I3vvvZdawyMbTLlcG+UCxRACqAhLCWAoV6g/hbt9G4HVppdqoLBB6s4lEMslrYv1Qz50jfcZ3aR8iZtPAo0Q4iMp8OjnK8rFl+Bzv5Og6UuT8rh3igXKIAUQEPIAhgICN7vpfco8Oxl6gN/yheEn9s3V2KxGDo6OhCLxcwuiu2xeixODpzUTHv27ol3zS6SIdLGIxYDXhxX0EHfH93xqHLOfrn2l4jE2M8tGavfG+VEIBCgAJpdACtjiSyizl2A26k+6N3/AXQyW4+QTDzQ/IAiMhNbJppdnOJxfK+aEDL1PKDvmKHNDYQHcOOKG5VzN/f9uQUqKCGFxxLv7yJDATSA8FnAB1YBUz6f0NRzGeA/YnapikIkEkFzczOz6wTAyrHY1LFJEZgfvP4DSzf9yowaj6Y/q8+HZXca3tfe7r0Ys2AMKusrMWbBGOw7vc/wNssJK98b5QazgCmAhhC2D2AsFh/QOTHT99Wb4/0AyxT2rREHq8bi7MhZjFs2ThHA9UfWm12kgjBqPEK92haCw82G9/f83ueVc3jLylswHB02vM1ywar3RjnCPoAUQEMIKYChXmDxT7Xyt/L3QGTE7JIVFT5YxcGqsZi6c6oiLn/w/MGyWb/JZI1H62L1WTHnkvhoAQaIxCL4+Zs/V87lHO8cQ9srJ6x6b5QjFEAKoCGEE8AT7wNPXZQgf+cCW5+MD/xc5vDBKg5WjMXe7r3KrBaXL74cx88eN7tIBSNrPGIx4KUbEqaDND4X+Me9H2PswrFKU3BbT5vhbZYDVrw3yhUKIAXQEEJlAbcu0vb3m3FBQZpzrEIsFkN3dzez6wTAarEIx8K4rfE2pcZqwYEFZhepoOiKx8n9wKRP/WuUgM8XpK/wC3tfUM6pa40L4Rilx2r3RjnDLGAKoCGEyCIKBYA3xmubfF+8DghwHC5C9FB/oF4RlTvevMO+w5dseER9hiy63XDLQTgaxo9X/1g5t/M/mF+gghJiHCHe3yZDATSA6U3AhzYBMy/Uyt+bDxruw2NFwuEwmpqa2LQiAFaKxZnQGXxnyXdQWV+Ji+ovwoGeA2YXqeDojsdwv/Z5crDR8L73n9mPixdcjMr6SlQtrIKvz2d4m1bGSvdGucMmYAqgIUwTwJEB7fANE88BHj8f2Le8tOUQCPatEQcrxWJCy4SyH/Mvp3gcbFSfKTMvjEuhQWbtnqWc41+t/RWisajhbVoVK90b5Q4FkAJoCFME0Pc2MGesVv4W3Gp4EFerwwerOFglFgd6DiiJH1ctuQo9IUGSuQpMTvGQJGDRT9Rny4ZHDO8/FAnh/73x/xQJXNy22PA2rYpV7g07QAGkABqipAIY6ASW/VorflO+ALz3oi2yfLPBB6s4WCEWkiTh1+t+XbaJH4nkHA+/T00om/SpeIKIQXaf3K2c6yuXXInuwW7D27QiVrg37AIFkAJoCFkA+/qKOFtAeCg+qPOUL2jlb3410HO4ePu1GJIkIRgMls3YbVbGCrFo8jVpBisOR8v3hZxXPBIHkn/ph/GhYgwysWWics7/suUvhrdnRaxwb9iFvr4+CqDZBbAyRRXAaATYuzRpXL9zgCe+Gh/yhcMIaJAkCeFwmA9WARA9FoPhQYxbrs74sf3YdrOLVFTyikdkGHimSn3u7H7FcDn6hvvwvde+p5z3lmMthrdpNUS/N+wEBZACaIiiNAFHRgDvAuDpi7XiN+lTwPqH48O+kBTYtCIOosfimdZnFAm5b9N9Zhen6OQdD98W9fkz/Xyg/5Thsqw6tEo59ze9cROGIkOGt2klRL837ASbgMtAAH0+H2pqauB2u1FXV4e6urqifi+Rggrg8Flg13xg9re14jfxHKD+R0A3R9IfDT5YxUHkWBw/exxVC6tQWV+JsQvH4mjfUbOLVHQMxWPlvepzqOFuw2WRnsrfIAAAIABJREFUJAl3rrtTkcDn9j5neJtWQuR7w25QAC0ugIFAAE6nUzMTR01NTVaZy/d7yRgWQEkCPnkXaLwPmHpeqvgtuBXosF8zST7wwSoOIsfi4W0PK/Lx5K4nzS5OSTAUj4EzwIyvqM+kQ5sMl+dQ7yGMXRCfJu6ShZfYQsJlRL437AYF0OICWFtbi5qaGs06n8+HioqKonwvmbwEUJLitXnbnwKevTxV+iaeAyx2AZ27ciqL3eGDVRxEjUW7v10Z9uWa165BcMQeD37D8WhdpD6bnr4YCIcMl2n2ntmKiP9u4+9s0ydO1HvDjlAALS6ATqczba2dw+GA1+st+PeS0Z0EMugHDqwCVt8PzPpmeumb9iVgzQPA8b26909U2LlaHESNxb1v3atIR/2BerOLUzIMx0OSgFduUp9Vmx4zXKbB8CBuaLhBice6I+sMb9MKiHpv2BEmgVhcAB0OBzweT8r6iooKuN3ugn8vGUUATxyJj5114n3gyDbAuzA+gOrC21KnakteXr4R2LskPrsHyRsOryAOIsZi54mdimzc0HADRqIjZhepZBQkHqc/Ah77TPyZ9dinC9InefMnm5WYjFs2DoPhQcPbFB0R7w27sujNWRRAswuQL4FAIKPIOZ1O1NbWFvR7ADA8PIxgMKgsXV1dcDgcuHHO13DP3K/hkWcvwJynz8ebT3wRfY+dm1b4oo99FmdfvBmDb89G+FQ7Yv8aziUSiSAcDiuLvD5xnfzLUf4VqWc9AMRiMc26SCQy6vpoNKpZH41GR12fqeylPKZQKITGxkYMDw+XzTFZNU6Dg4NKM5cIxzQ8Mow71tyhyMaqj1bZKk5yPEZGRgwdU9QzWXmOSfOrER4ZNnxM93nuU+Iya9essr+f5FgMDg6WzTFZMU67D7yNb79wIQXQ7ALki8/nG1Xkkvv4Gf0eAEycOBEOhyNl+ebcbyoPMXkZ++q38bu5X8UrMy/AhkmX4aV//Ax3/n0avvG3N/CVvzXhK39rwjf/8SZufmoz/rr8ffzlpQ2Y/MpqvPR6I1atakR3d3yk/KamJjQ2NipLMBhEOBzWrJNftsFgULOuqakJANDd3a1Z39zcDADo6OjQrG9piSectLe3a9a3trYCAFpbWzXr29vbAQAtLS2a9R0dHQCA5uZmzfpiHtOmTZvQ2NgIn89XNsdk5TjJ60U4psnLJyv35Q8X/RArV620ZZwGBwcNHdOalcsRcqtdWN6ff7/hY3p9w+sYUz8GlfWVGFM/Bq1HWnk/8ZiKekztH7bhr89ehG/O/SYF0OwC5IsZApipBnDM86kCmLxc+PyP4HxsjiJ/oy2VEzfgZ/PewZQ3D6Jh9yf4+GQAIyMjlvqFNdr6YvxqZA2gOMckUg3g4NAgblxxo3IfbunYYrs4FaoGMBwOI3JYHRtQmvZvCPccNXxMs3bNUsdl9NxX1vcTawDNPaaRkRGsne3Cpa98iwKIMhDAhoaGlL9VVFRkbMrN93vpkPsAnjlzBsGRIA71HsK2rm1w73JrOjgnLtVL/wd3L12Bn9W9g+88vkmXEH7lb024dIoHf1i8By9vP4L9x/oQjbEPSSLhcBhNTU3KQ4WYh0ixWNy2WLn37tl4jy37XhU8Hqv/T+3WsuQOw3ORD4YHMW6ZOjPL1q6thSmngIh0b9iR5iUzMefp81FZX0kBhIUFUO7LlymbN1MyR77fS4csgOkuIEmS0O5vx/N7n8ctK29JEcH7m+/HR70fYWA4gv3H+tC49xhmbfwQ99TvwpXTsovhxZM24r7FXry+6xOc6DM+LAMh5cZAeEAz9diBngNmF6k8CAWAJ7+uSuD+NwxvMnFu5ptX3myrJB1SGna9sxk9Ez+Lq17+Vvxam/ttCqDZBTCC0+lMK2x6hoHJ53vJyAKYOKB0OqKxKNYcXqNpiqqsr8TYBWPx4r4XEY1FU75zun8Yb3/YjWc2fYw7X34P356wYVQhrJ61BY+vbYP3k17EbFg7GIvF0N3drTRNEPMQJRZz35+r3GsPbXnI1LKYSVHicXC1dn7yQb+hzSXPEPLy/pcLVFCxEOXesBtHO7vQOfHrqJ/1JeUa++uGv1IAzS6AEdIN6Oz1euFwjH5Y+X4vmVwHgg7Hwlj24TLNRPSV9ZX4zfrf4OTAyVG/G41J2H+sD6/uOILfL9qDiyZmFsIrpnnwj1UfYPvHZxCO2uNBEw5zgFVRECEWfcN9uGrJVfHkggVj8EnwE9PKYjZFi8drv1AlcJXxOZXb/e24eMHFqKyvxBWLr0D3YHcBCikWItwbdqM/NIyWKdUYmXgOxr10ofLe3XNkDwXQ7AIYIdOUbon9+3w+H5xOpybpQ8/39JDvVHBDkSHM8c5RHnaV9ZW4eunV2Hh0o+5tRKIx7Onoxay3PsKtz+3AfzycXgYvmfwWHm3cjz0dvWXd/4kPVnEQIRbPtD6j3FsTWiaYVg4RKFo8gieAx7+sSuDhzYY3OWXnFCVuf9/29wIUUixEuDfsRCwmYeXTfwImnoOVT56nXFsPND/AmUBgcQEE4oJXW1uLuro65d/kv1dUVKRk/Wb7nh6MzgW8++RuVDdUa2oDJ7ZMRDia+8PBPzCCZbs7cferu/D1f6xLK4Pfc2/GzI0f4siZ8ht0mg9WcTA7Fr1Dvbhi8RXxbhYLx+L42eOmlEMUihqP3S+rAvjURcDwWUObCwwFcPXSq5Xn4f4z+wtUUDEw+96wGysaFiI64VzEJp6DW178hnJdvX/6fQogykAAzUQWQL8///4vfcN9+MuWv2gkcPzG8RgI5y9pZ4cjaNp3Avct8eI/M8jgHfPewarWYxgKp/Y/tCKRSATNzc3KUAHEPMyOxazd6rAiU3ZOMaUMIlHUeMRi2mni1v7V8CYTM7d/tfZXZdVyYfa9YSe27GpFz4QvARPPwSb3FzRdrgDA7/dTAM0ugJUZLQs4FyRJwqpDq3DpokuVi/SON+/AmdAZw2XsHwqjYU8XfvXSu2mbiS+etBETVx/Ax6f6De+LELM5EzqDyxZdhsr6SlQtrMKpgVNmF6n86TkMTPmCKoFHdxjaXDgWxo9W/Uh5Fq4/sr5ABSV24dDxM9g3oSo+XuXEc/CTl6qU62lb1zYAhXt/WxkKoAH0ZgHrpbW7VdP8cdMbN6Ez2FmQbQNAd3AIdVsP47qZb6etFfzF/J146+ApS44xGIvF0NHRwew6ATAzFtPfm67cPzPem1Hy/YtISeLxzvOqAD49BhgxNq/vtq5t6uwtDT/EUGSoQAU1Fz6nik9fKIzGKT9TrkfPE2rT709W/0SpUZaHhKMAkrww2gcwHYcDh3H98uuVC/b7r38fB3sOFmz7QLzG8b0jfjz4+t60TcTfdTdj/jYf+kLW6afCvjXiYFYsTg6cxCULL0FlfSUuX3x5QWrQy4GSxCMWBV76oSqB6x82vMl7Pfcqz8G6fbn30RYRPqeKSzQmoe6Zqcp1ODLxM7hn9c+V66jJ16R8ln0AKYCGKIYAAvEX2W2NtykX7ZVLrizaILZ9oTBe2n4E339ic4oIfnvCBkxb24aTfeL/+uaDVRzMisXkd9Q5f2ftmVXSfYtMyeJx5mNgyuf/9fI9F/hkp6HNHQ4cxpgFYxShL4dhYficKi6vrFiN0ITPKgL4jmea8ky4ccWNiMTUvpcUQAqgIYolgEA8OSRxYNTvvfY9+Pp8Bd+PTCwmobn9FH710rspIvi1R9bioYb3cajbWIZfMeGDVRzMiMWxs8cwduFYZQy53qHeku1bdEoajx1z1FrAZ6qAsLFZiqa9q77AH9n+SIEKaR58ThWPDbsP4pNHv6pcfycXjceDbz+oXD/LPlym+TwFkAJoiEJkAY9GKBLSSOD1y68vyZAWh7r78fAbH+Drj6Q2D9+7cA8OHhfvholEImhpaWF2nQCYEYvH3nlMuU+eaX2mZPu1AiWNRywKvDhOlcANxqQtMBTAVUuvUqfzO2Pt6fz4nCoOB7t6sXXC95Xr7vSs7+Boz4e4qP4iVNZX4gev/wDD0WHNd5gFTAE0RCmyiPpH+vHTNT/VzJNZqr5N3f1DcK9vR2WaWUdqFu7GgeN9JSkHIaNxcuCkUvt35ZIr0TfM69JUutuByZ9Vm4INZgUvOrhIef7due7OshoWhhjHPzCCVybfo8jf2cnnQwp8ggktE5Tr5qUPXkr5HrOAKYCGkC+g3t7iNjf1hHpwy8pblIvZtcaF4EjpLtr+oTDqth7GZVM9KSI4fsFutJ0w/waKRqNob29HNFoe4xpamVLHYurOqcq9Mcc7pyT7tBKm3Bs7nk4YILoSGM5/mKlwLKx5/nk6PNm/JCh8ThWWcDSGJ+Y8pVxr0YkVGPl4s+ZH4VVLrsLZkdTuS729vRRAswtgZYrZBzCZE2dPaGYNuXPdnRiJjhR9v4kMhaN4efsRXJ4kghc83IQHXmtFR495M4ywb404lDIWpwZOaTJ/2fcvFVPujVgUePm/VAlcfb+hzW3+ZLNmeKxSP/sKBZ9ThWXOsvUITlDHoAxumgkAeGLXE1l/FLIPIAXQEKUUQAA40ncE33vte8qF/c8d/zSlOWQoHMWrO1JF8Kt/X4t/rPoA3cHSZw3zwSoOpYzFjPdmMPM3C6bdG/4jwNTzVAn8MP8BnSVJwt0b7lZiXX+gvoAFLR18ThWON3Z+iA8f/ZZyfflf/TkgSQgMBXD54stRWV+JSxddip5Q+vczBZACaIhSCyAAHDhzQJnpoLK+EovbFpds38kMhaOYv82HSya/pRHBb/xzHZ7c8CHODpeuozMfrOJQqlicCZ1RZs+5bNFlGR/0dsfUe2PPq6oAPvE1YCD/GLX1tCmd+q9aehUCQ4UZgL+U8DlVGLwdfmx4tFq5tvqevESZh/qFvS8o78dp707LuA0KIAXQEKXqA5jMuiPrlAt8zIIxePfEuyXdfzL9Q2HMfusjfOvR9RoRvHSKB0ve/QSRaPFHvY9Go2htbWXfGgEoVSxm7p6p3AdP7HqiqPuyMqbeG5IELHapErjs1/F1efKP7f9QYj79vekFLGhp4HPKOKeCQ3jhsXuVa2rosfOAM4cAAIPhQVzz2jXKu/HY2WMZt8M+gBRAQ5iZRfTUnqeUB+E1r12Drv6ukpchmZ6zw3hszUF87ZG1GhG8YfZWbPnotNnFI2WEf8ivaeY5PcjrS1j6TwIzvqJK4L5lWb+SiVMDp5S4j10wFkf6jhSunER4hsJRTJ41C7EJ5wITz0Fs4rmItKtdC+oP1Cvvxb9v+/uo22IWMAXQEGbVAAJANBbFHzx/UC72H6/+MQbDxubfLBQdPQP4w+I9KRnDv3nlPRw5U5xEEf6yFodSxCLxB5AVa4JKiRD3xoGVqgA+/mWg92jem0ps4ru/2VhySakRIhYWRZIkTF+4RpP0MbDJrfx9ODqM65Zdp1wbhwOHR90eawApgIYwow9gIv0j/ZrhER58+0GhxsjaddSP/35uR8qsItPXtWOgwP0D2bdGHIodi8BQAFcsvgKV9ZW4ZOElODVwqij7KReEuTfeGK9K4PxqIJrfM2AwPIhxy8Ypz733TrxX4IIWD2FiYUEWvr0Phx/9htrvr/7nmu4Er7e/rlwTf9r8p6zbYx9ACqAhzBZAIJ4Z/J0l31Eu/CVtS0wrSzpiMQmNe4/hymmbNCJ4xTQPGvceK5iw8sEqDsWOxfN7n1eu9yk7pxRlH+WEMPfGUBB46iJVAjdn7qCfjVWHVinXwE/X/BQxqfj9jAuBMLGwGNs/6obn0WvV4V5mXaYkfQDxsSJvaLhBuSYO9hzMuk0KIAXQECIIIABs6dyiXPhVC6vwof9DU8uTjsGRCJ7Y0J4yvdzP6t7Boe78B4mV4YNVHIoZi4HwAK5eerXSB6wUUyNaHaHujc5dwKRPxV/kkyqAjpa8NhOTYpoZkhoPNRa4oMVBqFhYhKNnBvDSxDsV+QtN+XJ8iKEEEn8Q/N7ze13bpQBSAA1hZh/AZBLHQ/vRqh8J0x8wmY6eAdxTvyulWdi9vh2hkfz7xXCEfXEoZixe2f+Kcp0/st3YPLN2Qbh7Y+sTai3grG8Bofyen++deE+5FsYtGyfsMy8R4WIhOP1DYUyfPlEz00fs0GbNZ6KxqKYr1N7uvbq2zT6AFEBDiJRFNBId0fwintAywewijcrmD7vxPfdmjQheM6MZze3sz0XSMxwdxg9e/wEq6ytxUf1F8PX5zC4SyYdYFHjlJlUCl9+V99Aw9zffrzzzXnj/hcKWk5hKLCZh2rx6DE/4jDrky47UGK8/sl65Bn674be6ty/S+9ssKIAGkC8gv99vdlEAAEf7jipDJFTWV2L9kfxH3i8FQ+EoZm38MGXYmPsWe9Hdn9tsIpFIBC0tLYhESjf4NElPsWKR2Mn7wbcfLOi2yxkh742+LmD6+aoEehfktZkjfUcwdsFYZSrA7sHuAhe0sAgZC0GZu3oLTk9Qr5Hg8v9N+aEQk2L48eofK8+FnSd26t6+3++nAJpdACsjSh/ARBoPNSo3w3eWfEeI8QGzcfj0WfzPizs1EnjRxA1YtqtTd5II+9aIQzFiEY6F8V8r/iunTt4kjrD3xoFVqgBO+Txwcn9em5n27jTlunh0x6MFLmRhETYWgrF2zyHsf/Ri5foIvPBDIJp6zhLniP5F0y9ySipkH0AKoCFEFEBJklC7tVa9Kdb+ApGY+L82JUnCytaulGnl/ufFnTiqY+xAPljFoRixWH14tXJN3+u5t2DbtQNC3xtr/qhK4DNVwHDuCWG9Q724aslVSteAdn97EQpaGISOhSDs7+rF+gk/VGv+ZnwLGExtZZMkCf/T9D/Kc2FL55ac9kMBpAAaQkQBBICzI2dx44oblRtj/gfzzS6SbvwDI/jT63s1Evif/1iHF7f6EI1l/nXHB6s4FDoWMSmGH636kXI97zm1pyDbtQtC3xvhIWDuNaoENvw2r/6Ar+5/Vbk+7tlwj1DjoSYidCwEoLt/CPWTf5MwzdsXIZ1KX9vfcqxFifntq2/POeYUQAqgIWQBDATEm5R8b/deXLzgYmWw3EO9h8wuUk5s+eg0rp7erBHB257fgUPdZ9N+PhaLoaOjA7GYNcYDK2cKHQtPh0d50N+57s6CbNNOCH9v9ByOzw4iS+Cu3H+wjkRHNF0Ecq0NKhXCx8JEhsJRPDvzUU3Gb7htXdrPSpKEX679pRLvDUc35Ly/QCBAATS7AFZG9CyiWbtnKTfIz978mSWaghMZGI5g0poDuOBhVQK//o91qNt6eNTaQFI+SJKEO968Q7mOtx/bbnaRSDE42KgK4OTPAsf1DeWRyIajG5Tr5JaVtyAcYy2bVZAkCS+8PB/hCZ9SroP+rc9l/Hxi7d9tjbflNRC46O/vUkABNIBoWcDJDEeHNU1nL+570ewi5cWuo35c++TbKbWBh0+rtYGRSATNzc3MrhOAQsYi8UH/0zU/FbZpT2Qsc2+s+5sqgU9fDIRya1mRJAm/Xvdr5XpZ3La4SAXNH8vEosQsX7tRM8fvmYbMU7lJkoRfrf2VOtrF0fxGu2AWMAXQEKL2AUxk3+l9SlPw2IVj8XHvx2YXKS9CI1FMefOgpjbwG/9ch1d3HEEsJrFvjUAUMhZ3b7jbUDMPsVC/s8gI8OJ1qgQuuQPIsal0/5n9yvVy9dKr0TfcV6TC5odlYlFCtu89iK4JTiXup+bdGh8rMgMtx9UfhbeuujXvaQDZB5ACaAgrCCAAzN4zW7lh7njzDks3jezp8OO6pNrAX8zfiU/O9PPBKgiFesntO71PuW5vXnkzoqO8FEhmLCUdgU+AGV9RJbB5as6beHjbw8p1M+O9GYUvowEsFYsScPjYKeybUKXK3xNXaOb4TaZQtX8ABRCgABrCKgI4HB3GratuVW6aee/PM7tIhgiNRDFx9QGNBH57wgY8Mn81RkZGzC6e7SnUS+6Pm/+oXLMrPlpRoNLZD8tJx+Hm+DzBsgQeXJ3T108OnMRliy5T5os+2ne0OOXMA8vFooj0BgfwzmNqja9/ylcR6xt9bu9C1f4BFECAAmgIkbOAk/ng9AeapuBymEZrx6Ez+M7jmzQi+PtFe9A7QAk0k1gshu7ubkOZjr6AT3nQX7fsOoxEGdN8KUQ8Sk7LM6oATj0PyDAUSCae2/uccv3c33x/kQqZO5aMRREYCUexeYZLifHApC8i1PX+qN9Jqf0zONMVs4ApgIawWhZRYlPwXevvKosO9X2hMB5cph038IppHmz/+IzZRSMG+OeOfyrX6qv7XzW7OKTUSBKw4p6EpJAxQKhX99cHw4MYt2yccg29+//bO/e/pq587+cvOIfnPM95rue82jLT9swM3lDbqq296TidttbT0nGmdXqZduhlnE6dTvEu3ittrb14o7aVmyigGDUiGsAroFxVQFQIVxEQQhIgAXay9+f5gZMNmwRI2En2Svb3/Xrl1Ve3JPu789l7rU/W+n7XunvZj8ES3iAIAnJ3LRW1HYj9F3Rc14/7voKWAsnon9yUkGDrv/0BGUAZBMsUsBOb3SZZIDrzdqbSIfmME+XN+OVqncQIbjpRhT6O8sYCDcdx0Ol0E57mau1txdSkwf1dZ6XOQi83/k4wxOjI1UMxBqzAnseHTGDSf45ZHDCS4dtivnzsZSZySINWCx9SkLpV1JRf98+oO5c87ntGVnj7Yp97mgImAyiLYDOAgHRZjdmps9FpC57Yx4LjOCSma/HaiD2FF+w4j1tt3m8vRUwcuXlOcUVx4j36bdm3Po5OfQR13pmpCYgbqhDFqZUev5UXeMkakhm3MvwYqGcEtRY+oEKfCH7dP4t6XjvsWZHO8H7LF6N/ABlAgAygLILRAAKQ7BW84sIKpcPxCc6Gtb9/AD9crMODq7IkW8klFzaExJR3MCCnkzP1mTAzZSYiEiIwI3kGjH1srrEZTAS96ai/CGz4lyETeMXz9UxL2krEtm7uobnoHlD2x2DQayGDO8U6DKwb0rHw+488et/IxeB9MfoHkAEEyADKIlgNYIetA7NSZ4kPVEFLgdIhyWZkw1rdasGvvzovGQ2MTiqGyUrFBP5GTie3++pu8b7ccnmLH6JTHyFhOkoShgzg+jDgpucm4JNzn4j31OdFn/sxyPEJCS0mgLn6HGyx/ypqmP9lFHiHZ4Uww7eCfOXYK7Iqf4dDBpAMoCycBtBsZmuxUU84fOuw+FD99shv0WfvUzokWQiCAIvFIhnl6+McWKutkJjAx7bmoNAQXIY92HCnhSdYOSseP/g4IhIiMCVxCu703PFThOpionowhz5WWhns4XZxLT0tmJ48XVwWps5c59cwxyJktPCCgaYS9K7/30Pmb/MCWPs8628cvAMLjy4U+6rzzed9FpfZbCYDqHQAwUwwG0Be4PFG1hvig/VN6TdKhyQLQRjcDcRdw3q6shVTNpwWTeADK3TYob9F+wn7ibG0GIuUGyni/bj8wnI/Rac+JqoHc/A8kP7WkAn84iHA3OzRW3eV7xLvrff17/s50NEJGS08RGirQs/Gfxc1K1g/F62dnveXx2uPi7otObnEp98bGUAygLII1ilgJ7WmWrHacmqSsr+M5TLe1EqruQ+L4wsko4GL4wvQZgnukU8Wmcg0F8dzmJ8xX2zsb3Xd8mOE6iKkph25PuCH+UMmcNcsoG/8Dtxmt+HZ9Gf9MpLkDSGlxXh01qJ3ywOiVkXrHsH1+rsev51zcFhweIGoWVFrkW/DoylgMoByCHYDCADflH4jPmDRZ6KD9pepJw2rgxfwbc5tPDBsP+HIjWdw7ta9AEYa+kykkxv+S//DnA/9GJ36CDnT0ds5uC6g0wT+9FuAs437tqy6LPEeeyHzBXCOwH8fIafFaBjrYNv2sKjR1bVTcabUu33oD1UfEvX68+k/+zxEMoBkAGURCgbQZrdJRl5yGnKUDmlCeNOwXqkz4tEt0h1EPsuqBudhUjIxNt52coIgYJF2kXgPlrSV+DlCdRGSpqOjBth2/5AJPPA7YBxDJwiCJO0loTIhQMEOEZJajKSzFgOfD5m/6rW/wr7TxV59hM1uw9NpT4taVXRU+D5MMoBkAOUQCgYQkFZZzc+YD5t9/F/TrOFtw2rsHcDb+4skJvCV3fm4aw6+a2cNb7U433xevP9eP/l60I5Cs0rImo47JcCW/ztkAjP+NO5C0Tc6b2BSwiREJETgsQOPocMW2B2DQlYLJx01cHz+kKjJrbW/wNoDuV4/0/sr9ottwt/y/uaXUMkAkgGURTAXgQxHEAT8+fSfxQfuu7LvlA7JayaSXM3zAvZdMOBnK0+KJnDaxjM4e7Pdj5GGPt5qMXxUJq8xz8/RqY+QLjyouwBsHFpeBCc+HtxGbgxi82PF+23VxVUBCnSQkNbi3i3wXzwoanFj7a/wzq4s9Nu9W7S5e6Abcw7OQURCBCYlTEJNV41fwqUiEDKAsggVAwgAdeY6sSAkMikSTZYmpUPyCjnLK5Q2dmH2Z7miCbx/hQ5fZN+EnaaEJ4Q3WpS3l0tW+PfVGl/EECG/9MjNLGD9fxsygfrYMf+809YpWQe1tK00IGECIaxFezWEz38+zPxFYGGcFl293q+7uqNkR0A2KiADSAZQFqEyBexke8n2oE3Elzu1YrIO4E8jpoQXxxegvZuqhL3FGy2W5i4V77mjNUcDEJ36CPlpRwC4lg7EDm0xhrwtY44EHqw+KNkn2M7bAxJmSGpxpxRC3FC1b+XaSZi7/jAM93q8/qi7PXcRmRSJiIQITEua5te1QGkKmAygLELNAFo5K55Jf0ZsGM81nVM6JI/xRcPK8wL2nKtF+LAp4Rmb9bRwtJd4qkVNV414rz2b/qwiVZlqICRNhzuK9g0ZQOdI4Cgm0ME78OrxV8X7L+VGSkBCDDktavMkeZjX1k7B9FVpuDzBNnP5heWiJtuLt/s4WClkAMkAyiLUDCAAnKo7JT6E+iJGAAAgAElEQVSAvzn8Gww4gmPrNF82rEX10irh8JUnsedcbehN2/gJT7VYdXGVeK8lViYGKDr1EXKmYywKd0tN4KmVo5rAa/euifffYwcewz2r/5eDCiktKo4AG/67+F1fXvsIJi1Pw+ESzxbnHkllR6Wox5yDc2AZ8K8xIwNIBlAWoWgABUHA29lviw/iD9d/UDokj+A4DjqdzmcNa0dPP17bVyiZEn43sRhmWwg03H7GEy1ae1sxNXEw53R26mxYOWsAI1QXvn42mGfkSKDuk8FdRNwwvCDEn/lmTkJGiyvfS6bcT695Gg8tz8SXp29O6OMEQcBbp94K6IgsGUAygLJwGsBQu4FuGm9icuJkRCRE4JGURwLyy5hFHLyA7advSkzg3M/zUNUSWnorwbYr24K66pxgnNJEaU7gsaVul4jp6usSK04jEiJQ3OrdenWqg+eB3M0Sg31o9UKELz+Gvx0sm/AsSV5jnmRv+kCkg4Rq/+0NZABl4LyBTCaT0qH4nI0FG8UHcs2lNUqHMy48z6O9vR38KL/05ZB3s12yl/BDq7OQMcFpDjUwnhamPhNmpsxEREIEZiTPgLHPGOAI1YU/nw2muXoIWB82ZFYOve52x5D0W+liW7dIuwgc7z/zEdRaDFiBtDck5m/n6iW4b/kJ/G5vgdfLvTjheA4vZL4gaqBv0Ps4cPeYTCYygEoHEMyE4hSwE2OfEbMOzBLXYqrsqFQ6pDHxd25Nc5cVC7+7KBkNXJl5fcKNXigznha7y3eLjf3Wy1sDHJ36CKm8M2+pOCJdImbfs0CvdPFnB+/A70/8Xrwnf6z40W/hBK0WlhZg71zxe+Rj/xnrV/0F9y3X4Zkvz8Jsnfj1DK/I/mPWHwOWa01TwGQAZRHKBhAAkqqSFHkwJ0IgGtZ+uwMrM69LTODC7y7ijol2DxnOWFpYOas45TYlcQpaeloUiFBdBK3p8BU1eumOIV9PGdxKbhiVHZVi2sv05Ol+Wwc1KLW4UwJ8MbS7R9+G/4W3V27Efct1mL7pDJqME8/ftQxYMPfQXLGfuXbvmg8DHxsygGQAZRHqBnDk0HxWXZbSIY1KIBvWjJJmPLQ6SzSBUzecxsXbgd1SimXG0iK5KjmgSfdEkJoOX3P3GvDl0P602HY/0Fgo+ZPheanvnn7XLz94g06La+nApv8pfm+mrQ9j/oo9uG+5Dg+vyUJ5k7z0p62Xt4rf+SfnPvFR0J5BBpAMoCycBtBoDN0cpuH7tD6b/iyz+wTb7Xbk5ubCbg/Mgq6VLWY8Hje0e8gDK3TYfZaWigFG14LjOczLmCfeT7e6bikUoboI9LPBLOZmYNesIRO48V8Hi0X+CytnxfyM+eL9eaz2mM9DCBotOBtw/CNJvl/b109i2vJUcbek7MpWWacYXmw4I3kG7vbc9VHwnmE0GskAKh1AMKOWKqL39e+LjeLu8t1Kh8MMZiuHt0fsHvJ+cgl6+hlv3BXiWO0x8T76S85flA6HUCN9ZiBxoXSZmKMfisUhw3/wPn7wcXUWKHXcBnbPlnxHd/a/jYdXHBXbucSCelmnEARBsgf499e+903sXqCW/nssyADKIJSrgIdjMBvENdtmJM9Aa6+8X37+gOd5NDQ0BLy6jucF7NDfkpjAZ748i5p277dBChXcacELPF46+pLY4Je1lykYobpQ6tlgFvsAcGKZ1ATungN01gIAPj33qXifLr+w3KenZl6La2nA5v8z9L1s+l9o0O/Fw2uGdkfamnVD9mmO1x4Xv+PnM59XZMMBqgImAyiLUM8BHM7w/JhVF1cpHY4LSufW5NxoQ0RstthI/mpdNk5VsGeUA4E7LYav8/VG1hsKRqc+lH42mOVaGrD5fw+Zna3/Btw4gQ5bB2anzhbv10t3LvnslMxqYTUCme9JTfF3M3HnZimmbTwjtmt/TS0Dz8tLc+ke6MaTh54Uv9+Ldy766CK8g3IAyQDKQk0G0NxvljSKrC0Lw0LDWt/RiwU7zktGAz/ProZDZoMZbIzUQhAEvH7y9aDcYzoUYOHZYJb2G8C3012mhDMrU8T7dcHhBT7bqYZJLW4cB754cMR38AHuGY2Y+3me2JYtjp/4Wn/DGT6Y8FHuRz64gIlBBpAMoCzUZAABaQXnG1lvMFXwwErDah2wY2lqmcQE/vHHKzBZg2NPZV8wUoui1iLJQru8wOj0V4jCyrPBLP3dQPqbEgMkfPkw/pQ5lLKwuXCzT07FlBY991yuG1v/DShPRU+/Hc9/e0Fsw+Z/dc4n22De6rqFKYlTxOV27vTckX8dE4QMIBlAWaihCng4nIPD85nPB3zFdk+w2+3Iz89norpOEATsu2BA+MqhvJnH43JVs4XcSC2iz0SL98wJwwmFo1MfLD0bzCIIQMl+YMv/E81Q46Z/wYyEyeK9W9BSIPs0TGjBO4DSpMGlcIabvwO/AywtGLDzWPLDZbHtemxrDu6a5a/+IAgC3jz1pvh97rm6xwcXM3GoCpgMoCzUWEU0PJfrN4d/o0jybrCQX9shyZ95eE0WtOXK/eJVgsrOSslUmp0nE0IwjLkZSH5ZNEUHvvy/kmWwuge6lY5QHrV5gwUvw43ftvsH1/sTBPC8gI8ODs1gTF5/GrfbfHPNGbcyxO/yuSPPod/R75PPnShq7L9HQgZQBs4bqKurS+lQAoYgCPhT9p/EBzmhMkHpkAAADocD1dXVcDjY2prtjsmGF0dsIbdZVwW7I3SnQYdrsezsMvFeSbuZpnRoqoTVZ4NZBAEoSwG2/jv42H/CO3t+PlQAp3tz8N8niGJatFcDKVFS4xf7T4NTwD33xD/brKuS7HleXO+b2a3W3lY8euBRvxTWTJSuri4ygEoHEMyoLQfQSbWxGpMSJiEiIQKzDsxiYq0spnJrRtDHOfCP9KsSE/iH7wth7A3N0VOnFrc6bon3yVNpTyn+i1+tsPxsMI2lBUj7I+5u/G947KdfiuYl96engOaSCX1kwLVorQCOREv3Q479J2DvE0DdBcmffn/eIFnY/rTMhZ6dCIKAD/QfiN/fmktrfPK5cqEcQDKAslCrAQSAtZfWig/0psJNSofDfCcnCAKSCurxs2F5gbM/y0XFHbPSofkcpxYrL6wU75H9FfuVDku1sP5sME/jZRz9YWgFhLk//gLGDWHAT88NVtDyno/mBUQLQRic6k1a5Drit/0XwNVDwIh1CDNKmiU/UFOvNPosnOFr/j2d9jTM/Wy0eWQAyQDKQs0G8J71HmamzEREQgSmJE6BwWRQNJ5g6eSK6o2YvkkvmWY5WhZaeYEcx2F/5n5x8fDZqbPRy/UqHZZqCZZng2UEnsdSbZRoZJbtCofgNFU7JgEFu4C+8Y2EX7Xo7QSK9gF7Hnc1ftvuA85/Ie54Mhx9VZukYO1r/W2fhTRyTcW8xjyffbZcyAAGuQE0GAyIjo5GXFwc4uPjER8f79H7IiMjodfrYTKZYDKZEB8fj7i4OK/Pr8YcwOHsubqHma29HA4HysrKgiLPqdXch5d2XpL84t54InTyAh0OBz4+8bF4b+ws36l0SKommJ4NlumwdeDxg3PE+zrzi/8jNVkb/xVI/QNw9SBgc787lM+16O8eHNFLiQI2/Iur8dsxCbgcDwy4/wF22dCJh1Znie1Q7LFKny3vJQgC/pb3N/H7+vT8pz75XF9BOYBBbABNJhPCw8Ml27BFR0d7ZAI1Go3kNW/evAnFoPYqIpvdhmfSnxEf8MK7hUqHFDT02x1YfviaxAT+Pr4QnT3BnyfXaevE9OTpiEiIwMyUmTD1hfZWiYR6ONNwRmzvZiRNQ03ic66mK/afgA3/fbCa+PJeoLkY4Pp8EwBnG8zdO7sNSHgR2PQ/3Z8//kmg4gjgGL3qvrLFjIh1Q7sXfXRQ/i4fw8muzx6aNj80F119bA2UqL3/BoLYAMbExCA6OlpyzGAwICwsbNz3Oo1iXFwcSktLJxyD2kcAAeBY7THxIX/l2CtweJEP40uCcZRDEAQkFzbg56tCKy/wq+KvxHsirsj7kXXCtwTjs8EyGwo2iPf3wqMLYW0pA3SfuO6mMdIQ7p0L/vjHaM5YBf5aBlB/CeioGZw65myD/7Uage42wNQENF4eHN07uw04+gGwbx6w8X+Mfo7tvwTOrAVar49bqdzQ2StJRXnzpysYsPtuBuKe9R7mHporfk+n6k/57LN9BY0ABrEBDA8Pdzvap9FoxjV1E5nuBYD+/n5YLBbx1dzcDI1Gg9bWVnAcB47jxEbW4XCIx4Yft9vtkuPOTcFHOz78GMdxEAQBgiB4fBwY3IB8+DHnIqSjHR8tdnfHeYHHq8dfFR/0jOoMRa7JZrNBq9Wiv79f9jUFWqfCmnbM2CzNC8wobvSpToG6JmOvEY+mDC73MDVpKu723PXbvReKz5M/rslqtUKr1WJgYCBkrklJnXr7e/HysZfFNm/l+ZWDsds5oKEA/MkYCNt/MbpR8+FL2P4L4MTH4Osughvo9+iaWs19mLMtV2xv/nPXJfTYBnymk91hx9un3ha/n7/m/BU8zzN377W1tZEBVDqAiaLRaKDXu+5EERYWNq7Bm6gBjI2NdZk+1mg0SE1NhVarhVarRVlZGQCgrKxMPKbValFdXQ0AyM/PlxxvaGgAAOTm5kqOt7e3AwB0Op3kuMViAcdxkmPOpGKLxSI5ptPpAADt7e2S47m5uQCAhoYGyfH8/HwAQHV1teT4eNe0X79ffNhnJc7CTcPNgF9TTk4OtFotDAaDT64p0Dq1Wfrw/NdnJVPCf959CnYH7zOdAnFNHx36SLwX1l5c6/d7LxSfJ39dk9VqDblrUkqnOnMdpidOF+/1denrpNd09CjOpn6Nq/uWwpb6JvDdTAix/yzb8Nm/moSGb19E6Y//wOm0fV5f09mCYjzz5VA789j6E0g97Fud9pTvkfQHBzIPMPk8HTt2jAyg0gFMBJPJNKoBDA8PR0xMzJjvj4mJEQtH4uLiPDaENAI4+jUtzVk6lPRftjPg1xTMI4DOa7INcIjJKHfJC7xnsQXFNXVZu8SKv8kJk1HXVUcjSwxcE40A+ueajt8eWt5kRvIM3DbeHvuaeozoq9aj5KdPMXD2SwinVkI4/A74/c+D/+k58Akvgk96GULqYgiHlsBx4u9wXPwG9gotuOZyoL9b1jUZu6347ddD+/s+EZeLO8Yen+pU2lYq7vU7OXEyCpsLFdeJRgBHJygNoMFgGNMAjswNHElUVJTk/6Ojo8c1je6gHMAh6s314rIfM1Nmot3aHtDzh9JuBymXgzMvcN/1fUNV4bq/hIQWoUAoPRusEZsfK97zi7SLYOWsY/69UlrYBhyI2pMvtimPbslBk3HsWL3F3G/GvIx54vexq3yXTz/f11AOoEoN4Ej0ej00Go2kotgTqIpIymdXPhMf/tUXVysdTlBTXG90yQvMLGtWOqxRsXJWPHHwCUQkRGBSwiTUmeuUDokg/I7NbsMi7SKx3fso9yPwAlvLOfXbHfjjj1fEtmTaxjOoafftnsaCIOCj3KH0jzdPvcn8vt/Ufwe5AczIyHD5t7CwMK9H85xTyu4+byycN5DRqPxWaCxg6jNhVuos0QTc6LwRsHPb7Xbk5+eL0wShQJulD4t2SdcL3HC8ChyD6wUmVCaIjf8nZz8JOS2CmVB8NljCYDbgsQOPiff/jpIdo/5toLWwO3i8l1Qith8R67L9Mptw4MYB8fofP/g4Wnt9s42cPzEajWQAlTy5yWRCZGSkxy+nQXMattGqgMfK6YuOjnYZOXR+nrfFIWreCWQ0hhuBt7Pf9tmiouPBcaG520G/3YEVR6TrBS6OL0AHQ+sF9tn78FTaU6LuN+7dCEktgpVQfTZY4tKdS5icOFl8Bo7VHnP7d4HUwsEL+GtqmdhuPLwmC0X1vh+sKGotwtSkqeK1n2s65/Nz+APaCSRIRwCBwaled4ZtvGVg3BnHsaaUx4IMoCsDjgE8d+S5oY3TG3MDct5Q7+QOXG6U5AXO2pqDa81sLLA8/Nf/x3kfh7wWwQbpERhSbqSIz8G0pGkoay9z+ZtAacHzAv6RflVsLx5clYXzt+75/DwNlgbMGbY7SjCt+0kGMIgNoLuFoEtLS6HRjH1J7qaH4+PjERYWNuEcQDKAUvQNerFBeD7zeXAO/3c8aujkShqkeYEPrs5CenGTojENOAbwbPqzQ6N/nTdUoUUwQXoEBkEQsKlwk2T3izs90n2+A6GFIAhYffS62E78bOVJ6KvafH4ec78ZL2S+IF7ve/r3mM/7Gw4ZwCA2gKNtBTc8j89gMCA8PFwysqfX6yV/4/wcb/P/gCED6K1xDHUEQcCbp94UG4bkqmS/n5PnB9fLc5b4hyptlj7854i8wLXaCp+u4u8N6bfSXfaDVosWwQLpETg4nsM7p9+RVAab+4dy7vythSAI2HC8SmwbHlihw8nrd31+Ho7n8E629Dq7B3xbWOJvnKlfZACDFIPBgJiYGMTHx4v/HfnvYWFhLlO7er1eHEGMioryeurXCVURjU5lZ6XYOMxOnS1pBAl59NsdWJV5XWICX9mdj/ZuH+036iEcz2HB4QWiztfvXQ/o+QmCRUaOjP3+xO8DYo4EQcC2U9Vim3D/Ch2Olt0Z/40TOM/w5W/cjXQGA9R/B7kBVBqqAh6bVRdXiY3Etivb/Houu92O3NxcVVU6HipqxIOrssQGf+ZmPUoaArcmZcatDFHf6DND6Rhq1IJlSI/A02hpxJOHnhSfjyUnl8DKWf2mhSAI+Dy7WvKjMK3IP+khP1X8JF5XZFIkytvL/XIef0NVwGQAZUE5gGPT2tuKGckzBveFTZyKenO9386l1jyn8iYTHtuaIzb6P191EsmFDX6vvuYcHOZnzBc7gqv3rg79m0q1YBXSQxlqumrEtTGdqyJYbBafayEIAr7Ivikxf0mFDT77/OEML3SJSIiAzqDzy3kCAeUAkgGUBRnA8dlZvlNsLJbmLvXbedTcyXX09ON3ewskHcA/0q+ij/PfbgNpN9NEXd/Xvy/5NzVrwSKkh3JUG6vFtVEjEiLwbva7yDia4TMtBEHA9tMjzF9BvU8+eyRJVUkS87fn6h6/nCdQkAEkAygLMoDjY+WseDrtabHRKGgp8Mt51N7JcQ4eG09USTqC57+9gOYu3273BAD9jn5J5W9FR4U0FpVrwRqkh7JUdFTg0QOPis/Lyykvw2Lzjen46swtyTOf6CfzN3x914iECOws3xmwNV79BRlAMoCyoCpgz9DWaCXVYv5YKoDnebS3t6u+0lFbfgf/seaU2CFM3XAaF277dv2v4ev+Lc1xHdUlLdiC9FCesvYyzEyZKT43i08sRoetY8KfJwiCi/nbf8k/2y/ur9gvMX+7y3f75TyBhqqAyQDKgqqIPIMXeCw+sVhsQA5VH1I6pJCmutWCuZ/nSZaC2JlXA56X/4u9z94nGdEN5HZ/BBHMFLUWSUYC52fMx+2u215/jiAIiDslLfj4yQ/mTxAE7Lm6R2r+roaG+QOo/wbIAMqCpoA9p6y9TLJXpK+XheE4Djqdjqa5/guzjcPb+4skncQ7CcUw2+R9P8lVyaKOf8v7m9u/IS3YgvRgh6p7VZiTNLRzxmMHHkN+S77H7xcEAZtGpHr4w/z1cr1YdnaZxPztvbrX5+dREpoCJgMoCzKA3vHpuU/9tmUQ5Tm5wvMCvsm5jftXDHUWT36eh+rWiTV4NrtNsrTFTeNNt39HWrAF6cEOHMchOTMZrx5/VXyOpiROwcHqg+Pm1AmCgHXaCr9X+9ab6/HS0Zck5u/Hih99fh6lIQNIBlAWZAC9427PXcmyMHVm3/1ypU5udM7ebMfk9aclm8JPZIHY4Yngy84uG/XvSAu2ID3YwamFxWbBR7kfSUzWB/oP0Nbrfss2nhewctji7/ev0OFQUaPP4zvbdBaPHXhMMkJ5rumcz8/DAmQAyQDKggyg9wxfFubDnA999rnUyY1Nk9GK57+9IBk9WHO0Av12z5aK6RnoEdc0m5QwaczcJdKCLUgPdhiuhYN34IuiLyQmcNaBWdDWaCWjgXYHj7+nXZXk9B4pbfZpXD0DPfi86HNJLC8dfQkNFv+sJ8gCZADJAMrCaQDNZtrmzFOsnBXPpD8jNjKX7lzyyecKggCLxRL0SxP4kz7OgZiMaxITuPC7ix4tFbOrfJeo2afnPx3zb0kLtiA92MGdFmebzkoKq5w/jtt629Bvd+D95BLxeQ1feRLact9tu8YLPLQ1Wklqh3OE38r5fgkpljCbzWQAlQ4gmCEDODFOGE6IDc2LR18E55A/MiEIAjiOo07OA9KKmvDQ6qEt5KZsOI2zN9tH/ftOWyceSXlEnLpvtIw99URasAXpwQ6jaWHuN2PFhRUSEzY9eTqe+ukj3L8mSdzl51TFXZ/FUtFRgdd0r0nOGZkUif0V+1Vxr5ABJAMoC5oCnhiCIOD1k6+Ljc7+iv2yP5OmubyjssWMJ+LyJDlF20/fhMPNUjGfXflM1GpT4aZxP5u0YAvSgx3G0yKvMQ9PpT0lMWW/2j8Zv/z2DaSWX5F9/n5HP7Lrs/FhzoeSc0QkRODjvI/R3O3bqWWWoSlgMoCyIAM4cao6qzApYRIiEiLwSMojuGeVt1gxdXLeY7ZxeCehWDIl/IfvC3Gvu1/8m+buZkxNmoqIhAjMTJnp0eK1pAVbkB7s4IkWdcZ2zI7/G371U6SLSVtycgl2le9CaVspON4zPe28HdfuXcOmwk2YnTrb5TNfOvqS33ZoYhkygGQAZUEGUB4bCzaKjdCKCytkfRZ1chNDEATsOVeL8JUnRRM4Y7MeBbWD9/TwaalvSr/x6DNJC7YgPdhhPC3umGx4+suzg8/iynRM/voTPHZgjotpc/4ge1//PjYXbsY3pd/gh+s/4FD1IWTezsS3Zd9i2dllWKRdhGlJ09y+f17GPCRXJXtsJEMNMoBkAGVBBlAepj4T5hwcatxK2kom/FnUycnjSp0Rj2zRSyoNN2TrxVHaOQfnoHug26PPIi3YgvRgh7G0uNXWjUe35IjP4CNb9Ljd1g0rZ0VyVTJePPqiWyPnzWtmykysvLASl+9eBi+oe2tAMoBkAGVBRSDySbuZJjZOLx97ecL7BFOiu3w6evrx+r7LYgf0H99FidokVCZ4/DmkBVuQHuwwmhYlDUbJWp1Pf3EWTUbXKtzW3lYcrTmKFRdWuOQKuntNS5qGRdpF+PvZvyPzdiZ6ud5AXSrzUBEIGUBZkAGUj4N3SFbFT61OndDn0FIXvsHBC9ihv4XwDd+Jmkz64XFcqGnx+DNIC7YgPdjBnRa51W14eM1QVf6L311EZ0//GJ8y9FlN3U2o6KhA4d1C5DTkQFujxcHqg8hrzEODpWHCP6jVABlAMoCyoClg31DeXj60EGrqLBj7jF5/Bk1z+Q5BELDwyGJRk59tXY8HVujwTc5tt1XCIyEt2IL0YIeRWqQXN0nyb1/fdxk9/WTaAgFNAZMBlAUZQN+x6uIq0XCsvbTW6/dTJ+c7suqyhtYi2z8f9y0/JnZQr+0rRHt335jvJy3YgvRgB6cWAwMD+OrMLUkF/l8OlGLAru68vEBCBpAMoCzIAPqODluHZA9KbwtCqJPzDX32PszLmCfqcL7pAr7JuY0HVgx1VNM3nRlz4WjSgi1ID3bgOA5HMrVYdqhMYv5ij1WC92B0nfAdZADJAMqCDKBvOXDjgGRtKm92COE4Djqdjjo5mcRfixc1eE//nni80NApqRK+b7kOm3VVbkcsSAu2ID3Ywdhtw4LPhp6h+1fosO+CQemwVAkZQDKAsnAaQDXfQL7EwTuw+MRQ7tm+6/uUDklVtFvbMTNlJiISIjAlcQpqTbWSf+/s6cfb+4skJvCFby+iroMqCwliPO6abViw47z47Dy4Ogsnr/tuazfCO6j/JgMoC+cNZDKZlA4lZKjqrMLkxMniXphNliaP3sfzPNrb28HzlEMzUVZfXC2a7y2Xt7j9G0EQ8OPFOjy4aqhq8RdrTyGjpFmsbCQt2IL0UJ6rTSbM2Dw0gj5l/WkU13tf7Eb4DpPJRAZQ6QCCGZoC9g/brmwbmoY8855Hy1dQnpM8KjsrJZXYpr6xf9RU3DHj6S/OSkYDPzxQCrOVIy0Yg/RQlhPXWvDQ6qEfTJHrTuBmCw0aKA1NAZMBlAUZQP/Qy/Xi2fRnRUNyqu7UuO+hTm7iCIKAN7LeEL/v5Kpkj97X22/HP9KvSkzgY1tzcPFWG2nBEPRsKIMgCPgm57bk+Xhl9yWkZJAWLEAGkAygLMgA+o+chhzRkDyV9hQsA2M/pNTJTZzs+mzxu34h8wWv9wbVXbsr2cXg/hU6/Omb4+i1jb+YLeF/6NkIPH2cAx8dlFb6/j3tKnps/aQFI5ABJAMoC6cBNBopl8PXCIKApblLRWOyoWDDmH9vt9uRm5sLu50WUfUGK2fF/Iz54vd8runchD7nrtmG38cXSjq8574+j1ttnu0fTPgPejYCS4vJhhe/uyj5QbTnXC0EQSAtGMJoNJIBVDqAYIaqiPzL3Z67YlVqREIECu8WKh1SyLG9eLv4/UafiZa1XRjPC9h7rhY/X3VSUum474KB1jgjVMGVOiOmbzoztJ/2mlPIrmxVOizCDdR/kwGUBVUB+5/U6lTRoCw4vABWznWDdGCw0rGhoYEqHb3gpvEmpiROQURCBCKTItFoafTJ515v7sKT26RrBv5ubwGau9xrR/gXejb8jyAISCqox8+Gbev2eFwubtyVmgvSgh2oCpgMoCwoB9D/8AKPt069JZrAzYWb3f4d5Tl5By/weP3k6+L3uufqHp99NsdxyMjUYsOxCtw/bAeRX63LxqGiRlmjjIT30LPhX/o4B2Iyrkl+8Cz54TK6egdc/pa0YAfKASQDKAsygIGhydIkmQouai1y+RtqWL0j41aGpHi1gFgAABpuSURBVPBjwOHaWU2U4VoU1HZi9me5ks7xjR+v4K7Z5rPzEWNDz4b/aDJa8fy3FyT395aTN2B3uB/hIy3YgQwgGUBZkAEMHCk3UkTD8pvDv3GZCqaG1XM6bZ2YnTpb/D6v3L3i088fqYWlj8MnI5aLiYjNRlpxE40GBgB6NvzDmao2TIrNFu/ph1ZnQVt+Z8z3kBbsQAaQDKAsqAo4cPACL1mr7rMrn0n+3W63Iz8/n6rrPGDlhZXi97jywkqff/5oWuRWt2HmZmlu4Fs/0Wigv6Fnw7fYHTy2Zt2Q3MdPfp7nku/n9r2kBTNQFTAZQFlQFVFgabA0YEbyDNG8FLcWKx1S0HHl7hXJjh+dtsCOXputHJallUs6z1+ty0ZyYQNVChPM02ruw6t7CyT37/vJJbD00YhesEH9NxlAWThvoK6uLqVDUQ1JVUmigZmfMV9cINrhcKC6uhoOh0PhCNnFylnx3JHnxO8v/Va6X87jiRb6KtfRwFf3FsBwr8cvMakZejZ8w5mqNkzZMLTg+c9WnsQPF+u8SmMgLdihq6uLDKDSAQQzlAMYeBy8A2+eelM0MZ+c+wSCIFBujQdsKtwkfm9LTi4BL/hnKQpPtTBbOZfqyQdXZ2FnXg24UZLoCe+hZ0MefZwDa7UVLlseljR4n/pDWrAD5QCSAZQFGUBlaO1txazUWaKZybydSQ3rOOTfyRe/r5kpM9FgafDbubzV4lJNB56Iy5N0sAt2nJ9QB0u4Qs/GxLnd1o0FO85L7s3opGKYrBOrmict2IEMIBlAWZABVI7T9aclhqams4Ya1lGwDFjwTPoz4veVWp3q1/NNpJOzDTiwWVeFB4atG3jfch1WHLk+4c6WGIRMh/fwvID9l+rw8JosSZVvcmGDrMp10oIdyACSAZQF5QAqS2x+rGhqfnf8dygqKaLcGjcMr/p99/S7fpv6deJwOFBWVjYhLa41m1zWVYvceAaZZc20ZMwEkaOHGrljsuEP30v3tf71V+dxs1X+vtakBTtQDiAZQFlQFZGyWDkrXsh8QTQ324u3Kx0Sc+Q05AxV/R6YhdZe9vcltTt4/HixDr9ce8plO7nqVnrWCP8gCALSi5sQsS5bct+t01agjyPDFmpQ/00GUBY0Aqg8NzpvYGrSVNHkXGi6oHRIzNBp68TcQ3PF7+ZY7bGAnNdXoxyt5j68n1wi6YzDV55E7LFKmG00heYpNOo0Pm2WPrybWCy512ZtzcGlmg6fnoe0YAcaASQDKAvKAWSDhMoE0eTMSZ2D5u5mpUNSHF7g8WHOh+L38tfcvwZsCtXXeU551e2Y+3mey7RwWlETrR3oAZR3NjqCICD1SiMiYqWjfn9Pu+qXtf1IC3agHEAygLIgA8gGvMDjgzMfiGbn5WMvu2wVpzbir8WL38cTB59Ah823Ixlj4Y9Oro9zYGdejSQp/77lOjz/7QVcNtDzNxZkOtxT39GLxfEFLj8ssiv9lyZBWrADGUAygLIgA8gOxl4jnkp6SjQ9n577VLVFAwUtBZiUMAkRCRGYlDAJ+S35AT2/Pzu5OyYbPkwplXTa9y3X4b2kEjR09vr8fKEAmQ4pnIPHnnO1eGi19MfEsrRydPX6t+KctGAHMoBkAGVBOYDs4HA4oC/T45GUR0QTmFCZoHRYAae1txVPHHxC/A72Xt0b8BgCsdtBfk2Hy/psP191Ept1VbRszAho94kh8ms7MG/7Ocl9M2dbLs7fuheQ85MW7EA5gGQAZUFVROyR0zhU9To5cTIKWgqUDilgcA4Or518Tbz+D/Qf+H3JFyVx8AIOFTVi+ibplnKTYrOx62wNbAPUyRKDtFn68NfUMsl9cv8KHTYcr0Jvv13p8AgFoP6bDKAsnDeQ0Ug7FiiN3W5Hfn4+7HY7viv7bqgo5OAcNHU3KR1eQNh6eat43b/O+DXM/WZF4hiuRSDo6bfji+ybLlN6j2zR48DlRtVvKxdoPVhiwM7j+/MGlyWFFu68hGvNpoDHo2YtWMNoNJIBVDqAYIZyANlheG4NL/D4S85fRDP02yO/RacttDU6XntcvN5pSdNQ2VmpWCxK5Tm1mGz4NOOqy24iT31xFkfL7sCh0ophNeadCYKArOt3XarHp244jYNXGhWrHlejFqxCOYBkAGVBBpAdRjas3QPdWHh0oWiKXj3+KnoGehSO0j8UtBRI1kLMuJWhaDxKd3K327rx5xFrut23XIdnvjwLbbn6jKDSegSa8iYTovbku0z3rsy87vcij/FQmxYsQwaQDKAsyACyg7uGtbW3Fc+mPysao3ey38GAI7QKBG503pAUvqwvWK949TMrnVxJQxd+t7fAxQg+u/0cjl1tUY0RZEUPf2O414OlI/L87luuw+L4AlTcUSYdYiRq0SIYIANIBlAWTgNoMgU+l4SQwvM8GhoawPPSfC+DyYA5B+eIBmnZ2WVw8KFRHNDU3YQnDz0pXtvS3KWw88rnFo2mhRIIgoD82g68usfVCD75eR4OXG5Evz007ofRYEkPf9BktOKTdNep/6e/PAt9VZviP4iGE+paBBMmk4kMoNIBBDNURRQcXLt3DTNTZopGaWPBRqY6hYnQaevEb4/8VrymJSeXoM/ep3RYzCIIAi7VdOCV3fkuRnDmZj32nqtFtx92fiD8x12zDasyr+NnK09K9Jy28QwSC+pVX/xDjA3132QAZUFVwOxgt9uRm5s7anXdxTsXMTVxKE9u6+WtQbtEipWzYvGJxeK1LDy6ULGKX3eMp4WSOI3ga/sKXYxgRGw2Np2oQpMxtHaRYVmPiWC414OYjGv4+Sqp8ZsUm43vcm+jh+FlXUJNi2CGqoDJAMqCcgDZwZPcmhOGE6JpikiIwPILy8HxwTXqY+434/WTr4vX8Ez6M7jbc1fpsCQES57T1SYT3k8uwf0jpg4fWKFDdFIxCg2dQT9SDASPHuNxvdmMD1Jc9frl2lPYfvomzDb2ry9UtAgFKAeQDKAsyACyg6cNq7ZGiymJU0QD9WHOh7DZbQGKUh5tvW1YpF0kxj4rdRZud91WOiwXgq2Tq/2vEaUHR6wjeN9yHX7z9QUkFTbAEsTTw8Gmx3AcvIDTla3uR2zXZWPbqWoYFa7s9YZg1iLUIANIBlAWZADZwZuGNa8xD5FJkaKReiPrDVgG2G4E6s31+HXGr8WY5x6aixudN5QOyy3B2sl19vTju9zbmLlZ72I2/mPNKcRkXEN5kynoRgWDUQ+TdQB7z9VizrZcFy2mb9Jj99naoDTlwahFqEIGkAygLKgKmB14nkd7e7vH1XVFrUV49MCjoqF65dgrzE2lOqnsrMTcQ3PFWBccXoBGS6PSYY2Kt1qwxoCdh7b8DhbuvORiPu5brsOCHecRf74WbZbgKLoJFj0EQUBRvRH/SL+Kh9e4jsY++XkeUi43oI8L3qrtYNFCDVAVMBlAWVAVUXBT2VmJJw4+IRqr2amzkdeYp3RYEvIa8yRG9eVjL+OeNTAb1xNAZYsZq49ex6/WZbsYkgdW6LDkh8s4XNJM+8nK4K7Zhp15NXjqi7NuDfcbP15BXnW7Yrt3EKEJ9d9kAGVBU8DswHEcdDqd11MrdeY6LDi8QFIcsu3KNnAOZadobHYbNhVuksQVDFPVwMS1YBnrgB1pRU1YtMv9qOBDq7Pw58RiHCltZq4YgUU9jL0DSL3SiNf3XXZZv8+Z3xd7rBKGe6G1ew+LWqgVmgImAygLMoDsICe3xjJgwcd5H0vM1uITi9FkafJDpONz03hTso2dcwHrYClWCfU8J8O9Hmw/fROPx7nmp923XIefrzqJN368ggOXG9FiUl4zVvTo7OnHwSuNWPLDZYSPWLvP+frD94XILGuGbSB4p3nHghUtCDKAABlAWZABZAe5DasgCDhYfRDTkqaJpuvRA49i3/V9ATNeDt6BxMpESQwzkmcg7WZaUBUeqKWTEwQBxfVGrMq8jumbzrg1NPct12H+V+ew5eQNXKrpUGTXEaX04HkBV5tM+Fp/Gy/tvOSyfIvz9XhcLr46cyvk1l90h1qejWCADGCIGMDS0lLExMR4/PcGgwHR0dGIi4tDfHw84uPjJ3ReMoDs4KuG9UbnDTyf+bxk9O2Z9GeQeTvTb1vIOXgHsuqy8OLRFyXnjToeBYPJ4Jdz+hM1dnIOXsCVOiPWH6/ErK05o5rBh1Zn4ffxhdihv4X82o6AFDQESg9BEHC7rRvJhQ34a2rZmKZ4zrZcbM26gevN5qD6cSMXNT4brEIGMAQMYGlpKcLCwjw2gCaTCeHh4ZLK3ejo6AmZQKcBNJvZ2YVBrQiCAIvF4pPOpJfrxcaCjZicOFliyBZpFyGvMc9n++3yAo9T9afw0tGXJOeJSIjAl8VfYsARPOubDceXWgQjgjA48rVDf2vMkS/ndPFLOy9hrbYC6cVNuNnaDYePix38pYfJOoCLtzuw51wt3ksqwbSNoxs+Z/X0Z1nVuBqES+n4CrU/GyxhNpvJACodwEQxGAyIiopCTEwMwsPDPTaAMTExiI6OdvmssLAwr2MgA8gOgiCA4zifNqy1ploszV3qYs7mHpqLTYWbUNJW4vV2crzAo6KjArvKd7k1fm9kvYGSthKfXYMS+EOLYKardwDa8jtYllaO2Z+5zxscuebgwu8u4u9pV7H7bC3OVLWhrqN3wnvbytWju4/D1SYTMsua8eXpm3gvqcTt+nwjX79cewrvJhYzkwvJAvRssAMZwCA2gMOJjIz02ACGh4e7He3TaDQoLS316rw0BcwO/pxaKW4txh90f3Axa87p4dj8WPxw/Qecrj+Nqs4qdA90w8pZ0dLTgsrOSly6cwnaGi1WX1yNJw896fZzlpxcgoKWgpDoGGiaa2yau6w4UtqMmIxreHqUpU/cve5focOjW3Lwn7su4S8HSrH15A3En69FWnETzlS1objeiJr2HrSYbOjo6Ud3H4cBO4+BgQEcPaqFta8ffZwDPf12mKwDaDJaUdViQaGhE2eq2pBR0oydeTVYq63AnxOLsfC7i5i+yXVR7NFek2Kz8U5CEb4/b8DVJhPsEzSsoQw9G+xAU8AqNIAajQZ6vd7leFhYGOLi4sZ8b39/PywWi/hqbm6GRqNBa2srOI4Dx3FwOAZzehwOh3hs+HG73S457lwQdLTjw485fzk6f0V6chwYXHx0+DHnRuSjHR8tdpavyWazQavVor+/3y/X5HA4kNeYh4/zPsb05OluTdxEXq/rXse5hnMQBCFkdLJarWInFyrX5M/nqdNixfmbrdiVdxsfppTi8W25Y04bs/D6xdpTeHnXJaw9eh1pVxpQ1WICzwshrZMvrsn5bFit1pC5pmDVqa2tjQyg0gH4Ak8NoHPlb3cG0JNp5NjYWGg0GpdXamoqtFottFotysrKAABlZWXiMa1Wi+rqagBAfn6+5HhDQwMAIDc3V3K8vb0dAKDT6STHLRYLOI6THHN2thaLRXJMp9MBANrb2yXHc3NzAQANDQ2S4/n5+QCA6upqyfFguKacnBxotVoYDAa/X1Pa0TSsT1+PV1JewdTEqV4ZvhnJM/B+9vtYnbYaiZmJIauT83goXVMgdUo/osXOA1qs2XcMa9Ov4IOUEjy15SQi1pwImMm7f4UOkRuy8czmE/j99uP4aPcxfHvkLGrv9aCy6gbpRNcU1Nd07NgxMoBKB+ALPDWABoNhTAM4MjdwJDQCyO41+XsEcLRrsvRZUNFRgRM1J7CnfA/WXFyDt069hbdOvYVlZ5dh/aX1+Lr4ayRcT8D5xvPos/eFvE40Aujfa+qx9qGm1YyLt+/hxLUW7L9kwI4zN7FOex1/Sy3F+8kl+FNCEV77vhBRe/Lxwjfn8eSmE3hl9yUsji/AH74vwB9/KMQHycWIySjHlpM38G3OLfx4oRYnyptRZLiHps4e2B086eTja6IRQHauiUYAyQCKeGIAR0JFIOxAydXsQFqwBenBDqQFO1ARiEoNYEZGhsu/ebOUjBMygOxAyyuwA2nBFqQHO5AW7EAGUGEDaDKZEBkZ6fHLnXEDvM8BHK0KeLwikJFQFTA7cBxV17ECacEWpAc7kBbsQFXAKhsBBAanet0ZPVoGJrihhpUdSAu2ID3YgbRgBzKAKjSA7haCLi0thUbj/VdBBpAdqGFlB9KCLUgPdiAt2IEMYIgYwNEKOAwGA8LDwyVFH6NtBTfa9PJYkAFkB47joNPpqGFlANKCLUgPdiAt2IEMYBAbQJPJhJiYGERFRYnr8UVFRUmmd51bvI2s+jUYDIiJiUF8fLz434ngNIBqvoEIgiAIItig/juIDSALOG+g4aOJhDLwPI/29nZxjSdCOUgLtiA92IG0YAdnUSgZQGJC0BQwO1BuDTuQFmxBerADacEONAVMBlAWZADZgRpWdiAt2IL0YAfSgh3IAJIBlAUZQHaghpUdSAu2ID3YgbRgBzKAZABl4TSARqNR6VBUj91uR25urrhfJKEcpAVbkB7sQFqwg9FoJAOodADBDFUREQRBEETwQf03GUBZUBUwO/A8j4aGBqquYwDSgi1ID3YgLdiBqoDJAMqCcgDZgXJr2IG0YAvSgx1IC3agHEAygLIgA8gO1LCyA2nBFqQHO5AW7EAGkAygLMgAsgM1rOxAWrAF6cEOpAU7kAEkAygLqgJmB7vdjvz8fKquYwDSgi1ID3YgLdiBqoDJAMqCqogIgiAIIvig/psMoCycN1BXV5fSoageh8OB6upqOBwOpUNRPaQFW5Ae7EBasENXVxcZQKUDCGYoB5AdKLeGHUgLtiA92IG0YAfKASQDKAsygOxADSs7kBZsQXqwA2nBDmQAyQDKggwgO1DDyg6kBVuQHuxAWrADGUAygLKgHEB2cDgcKCsro9waBiAt2IL0YAfSgh0oB5AMoCyoioggCIIggg/qv8kAyoJGANmBflmzA2nBFqQHO5AW7EAjgGQAZUE5gOxAuTXsQFqwBenBDqQFO1AOIBlAWZABZAdqWNmBtGAL0oMdSAt2IANIBlAWZrMZGo0G9fX1sFgs9FLw1dnZidTUVHR2dioei9pfpAVbL9KDnRdpwc6rvr4eGo0GZrNZaSuhGGQAZWAwGKDRaOhFL3rRi170olcQvgwGg9JWQjHIAMrAZDJBo9GgqalJ8V8zan81NzdDo9GgublZ8VjU/iIt2HqRHuy8SAt2Xk1NTdBoNDCZTEpbCcUgAygDi4XKyFmBtGAH0oItSA92IC3YgbQgAygLuoHYgbRgB9KCLUgPdiAt2IG0IAMoC7qB2IG0YAfSgi1ID3YgLdiBtCADKIv+/n7Exsaiv79f6VBUD2nBDqQFW5Ae7EBasANpQQaQIAiCIAhCdZABJAiCIAiCUBlkAAmCIAiCIFQGGUCCIAiCIAiVQQaQIAi/MW/ePKVDIAhC5ZSWliImJsbtvxkMBkRHRyMuLg7x8fGIj48PcHTKQQZwAqj5hmENvV6PmJgYREdHY968eaQFQ8THx0OjoSZGSQwGA2JiYhAXF4eYmBhkZGQoHZIqGalDXFyc0iGphtLSUoSFhbk1gCaTCeHh4ZLdQKKjo1XTj1Dr7CVqv2FYorS0VNKQmkwmhIWFITo6WsGoCGBQi3nz5pEBVBC9Xo958+aJbZXBYHBpuwj/YzKZXMyHXq+ndsrPGAwGREVFISYmBuHh4W4NoHPwYOT7wsLCAhWmolDr7CVqv2FYwl0D6hx1UvMG3ywQFxeHjIwMMoAKEhYWhtLSUvH/9Xo9wsLCyAAGmJiYGLftUWRkpALRqJPIyEi3BjA8PNzt4I1Go5E8O6EKtc5eovYbhiXCwsJcplJKS0uh0WhoRFZBDAYDMjIyyAAqSFxcHBkMRoiKinLbHlF+bOAYzQBqNBro9XqX4+76llCEWmcvUfsNwxLuhvXJACqP8zkgA6gc4eHhiIqKUjoMAoPPg0ajkeRflpaWkj4BxJ0BNJlMo/bno00ZhxrUOnsB3TDs4zQdNBqrDHq9XpzuIgOoHBqNBjExMWKRWlxcHP1AVZDIyEhoNBpERUWJhWtE4HBnAA0Gw5j9uRpyNKl19gK6Ydhn3rx5NLWiIMNNBhlAZXD+UI2KipLknsXFxdGok4I4i6LoB2rgIQPoHmqdvYBuGLbJyMigKkcFiY+Pl3z3ZACVwdlOjTR7TmNI5iPwDB+NdZpASlMJHGMZQHdLI422bEyoQa2zF9ANwy7O5Xmo+lcZTCaTS4dGBlA5NBqN2ynf0Y4T/sNp/pwYDAZxSpjMeGAYKwdwtKJONTwn1Dp7Ad0w7DJv3jwyfwqSkZGB6Ohoycs55RUdHU0/jgLMWAaQZioCS3h4uNvjo1WmEr5nrGVgRntO1GDOyQB6idpvGBaJjo52+e5JC+WhnUCUY6xlL+iHauAwGAyj5iRnZGSQAQwQoz0P7tb1da4koQbUcZU+RO03DGvEx8e75GQ616EjlMW5/AUReOLj412MhzOFhUbKA8toI4Dx8fHUTgWI0XL0R9vZSy26UOvsJWq/YVjCudWVc4kL52vevHk0Aqggzr2yw8PDodFoaI9mhQgPD5c8B1FRUTT9qwDO/X+H49ymjPAfzi34oqKixMKbqKgolxFw5z7N8fHxLvmaoQ4ZwAmg5huGJcLCwsQHe+SLINSOyWQS8y+jo6Np6ldBnDmyMTExiImJIS0IJqCekiAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlUEGkCAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlUEGkCAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlUEGkCAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlUEGkCAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlUEGkCAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlUEGkCAIgiAIQmWQASQIgiAIglAZZAAJgiAIgiBUBhlAgiAIgiAIlfH/AcqAVvG9wygvAAAAAElFTkSuQmCC\" 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+      "image/png": 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\n",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "metadata": {},
+     "metadata": {
+      "needs_background": "light"
+     },
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Critical buckling loads:\n",
-      "Exact:    0.31800  FE:    0.31805  Rel. gap 0.01%%\n",
-      "Exact:    0.93995  FE:    0.94033  Rel. gap 0.04%%\n",
-      "Exact:    1.87267  FE:    1.87415  Rel. gap 0.08%%\n"
-     ]
     }
    ],
    "source": [
     "eigensolver = SLEPcEigenSolver(K, KG)\n",
     "eigensolver.parameters['problem_type'] = 'gen_hermitian'\n",
-    "eigensolver.parameters[\"spectrum\"] = \"smallest real\"\n",
     "eigensolver.parameters['spectral_transform'] = 'shift-and-invert'\n",
     "eigensolver.parameters['spectral_shift'] = 1e-3\n",
     "eigensolver.parameters['tolerance'] = 1e-12\n",