{
“cells”: [
{

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“# vector_plotn”, “n”, “In this example, we will plot the vector field from three point charges. Since the vector field is 3D, we will plot a 2D cross-section, and rotate it.n”, “n”, “An electric charge distribution of the form:n”, “n”, “$\rho = q_0(\delta^3(r’-a\hat{z})-\delta^3(r’-a\hat{x})-\delta^3(r’+a\hat{x}))$n”, “n”, “Gives and electric field:n”, “n”, “$\vec{E}(\vec{r}) = \frac{q_0}{4\pi\epsilon_0 a^2}(\frac{\frac{\vec{r}}{a}-\hat{z}}{|\\frac{\\vec{r}}{a}-\\hat{z}|^3}-\\frac{\\frac{\\vec{r}}{a}-\\hat{x}}{|\frac{\vec{r}}{a}-\hat{x}|^3}-\frac{\frac{\vec{r}}{a}+\hat{x}}{|\frac{\vec{r}}{a}+\hat{x}|^3})$”

]

}, {

“cell_type”: “code”, “execution_count”: 1, “metadata”: {}, “outputs”: [], “source”: [

“%matplotlib notebookn”, “import numpy as npn”, “import matplotlib as mpln”, “import matplotlib.pyplot as pltn”, “import animatplot as amp”

]

}, {

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“Here we compute the $s$ and $z$ components of the electric field at angles ranging from $0$ to $2\pi$.”

]

}, {

“cell_type”: “code”, “execution_count”: 2, “metadata”: {}, “outputs”: [], “source”: [

“def norm(x, y, z):n”, “ return (x**2 + y**2 + z**2) ** 0.5n”, “n”, “n”, “def electric_field(s, z, theta=0):n”, “ """The E_s and E_z components of the field at any point in spacen”, “n”, “ Computes the x, y, and z components then projects it onto the sz-plane.n”, “ """n”, “ x = s * np.cos(theta)n”, “ y = s * np.sin(theta)n”, “n”, “ Ex = (n”, “ x / norm(x, y, z - 1) ** 3n”, “ - (x - 1) / norm(x - 1, y, z) ** 3n”, “ - (x + 1) / norm(x + 1, y, z) ** 3n”, “ )n”, “ Ey = (n”, “ y / norm(x, y, z - 1) ** 3n”, “ - y / norm(x - 1, y, z) ** 3n”, “ - y / norm(x + 1, y, z) ** 3n”, “ )n”, “ Ez = (n”, “ (z - 1) / norm(x, y, z - 1) ** 3n”, “ - z / norm(x - 1, y, z) ** 3n”, “ - z / norm(x + 1, y, z) ** 3n”, “ )n”, “n”, “ Es = Ex * np.cos(theta) + Ey * np.sin(theta)n”, “ return Es, Ezn”, “n”, “n”, “def space(n):n”, “ d = 0.333n”, “ b = 2n”, “ s = np.linspace(-b, b, n)n”, “ z = np.linspace(-b + d, b + d, n)n”, “ angles = np.linspace(0, 2 * np.pi, 50)n”, “ s, z, theta = np.meshgrid(s, z, angles)n”, “ return s, z, theta, angles * 180 / np.pin”, “n”, “n”, “s, z, theta, angles = space(101)n”, “Es, Ez = electric_field(s, z, theta)”

]

}, {

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“These are just some arguments to pass to matplotlib’s pcolormesh and quiver to make things look nice.”

]

}, {

“cell_type”: “code”, “execution_count”: 3, “metadata”: {}, “outputs”: [], “source”: [

“pargs = {n”, “ "norm": mpl.colors.LogNorm(),n”, “ "vmax": 1000,n”, “ "vmin": 0.1,n”, “ "cmap": "pink",n”, “}n”, “qargs = {"color": "xkcd:butter"}”

]

}, {

“cell_type”: “markdown”, “metadata”: {}, “source”: [

“Now for the actual animating.”

]

}, {

“cell_type”: “code”, “execution_count”: 4, “metadata”: {

“scrolled”: false

}, “outputs”: [

{
“data”: {
“application/javascript”: [

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" +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 imagesn”, “ // almost always do), so we need to clear the canvas so thatn”, “ // 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%; 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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 bandn”, “ // 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 updatedn”, “ // 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-buttonsn”, “ $( ".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. 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But how to set the MIME type? It doesn’t seemn”, “ * 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 takesn”, “ // 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-canvasn”, “mpl.findpos = function(e) {n”, “ //this section is from http://www.quirksmode.org/js/events_properties.htmln”, “ 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 bugn”, “ targ = targ.parentNode;n”, “n”, “ // jQuery normalizes the pageX and pageYn”, “ // pageX,Y are the mouse positions relative to the documentn”, “ // offset() returns the position of the element relative to the documentn”, “ 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 keysn”, “ * we need this to avoid circular referencesn”, “ * http://stackoverflow.com/a/24161582/3208463n”, “ /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 ton”, “ * the text insertion cursor when the button is pressed. We wantn”, “ * to control all of the cursor setting manually through then”, “ * ‘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 eventn”, “}n”, “n”, “mpl.figure.prototype.key_event = function(event, name) {n”, “n”, “ // Prevent repeat eventsn”, “ if (name == ‘key_press’)n”, “ {n”, “ if (event.which === this._key)n”, “ return;n”, “ elsen”, “ 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 commn”, “ // object with the appropriate methods. Currently this is a non binaryn”, “ // 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 processn”, “ // 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 Commn”, “ // 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 realn”, “ // 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.ration”, “ 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.ration”, “ 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 son”, “ // 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 = thisn”, “ 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 ‘focusablen”, “ el.attr(‘tabindex’, 0)n”, “ // reach out to IPython and tell the keyboard manager to turn it’s selfn”, “ // off when our div gets focusn”, “n”, “ // location in version 3n”, “ if (IPython.notebook.keyboard_manager) {n”, “ IPython.notebook.keyboard_manager.register_events(el);n”, “ }n”, “ else {n”, “ // location in version 2n”, “ 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+entern”, “ if (event.shiftKey && event.which == 13) {n”, “ this.canvas_div.blur();n”, “ event.shiftKey = false;n”, “ // Send a "J" for go to next celln”, “ 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 forn”, “ // 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 outputn”, “ 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”

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WV45qE1mrUbN6kbXlkyDcWFlViz4hDefWkjSourVfszu+SIcxIRmxCMyM4BiOociHWrk7FhTarm87pqaDKZGn/tGxDQ+G+T4i9ng8HQ+JmZ62NUWAVMRmNjOwP3GW894NuwxnrO6irqozwP34cfW/Z7hTVX1I63HKhZOfix1SzFfDtPFocfm71cvD0aBGPwY4vasHMzC7n9UM6H78e3k/1ecX5RuzruPHwbdu56/jNuvNq6usa5qfXh2/HnqamtlcnL0nvYj9pqx3eyUgEXLP+bu0f33uG44a4ROJlVduqnBJvWHkVNteOcrsY0m/SYedNQ3HDX2fDxNeGDV//ER2/+pfn0M64/C7NvGYq5l3wKk1GP/LwKzX3ZymcCYAEPwcHBmvu505BZ0NjY6enHJYuauwfrHx+fAAapfH9PLYB2AGT1spllz34sXLgQS5culWqK03F6FCAAPD26n9FntT+A2N+3WgHwrsfG4+Kr+uHQnpO497pl0l+BWo4x53XDh9/PhsViwrofk3HL5V+gutrxEtMyRnO2MZnNjcP5BQY2/lsNAH14AOTAkHUWASAPdh4BoOI8Bg7uTgcAqkGe1wDIgbOVAx9P110Ed2qQxp+rJQGwnvve1HHw5QkA8pCohEYZAHLnqdYIgBWlpTL5a71wV3q6jo+/fCFufsBmkZp/9w9Y7AYE3vrgGEy/fhCOHs7HP674UvMUGABmAGB/JHsCZ1pOZH/+FhcXeXQOW/+QZgNALS5gLddFbZpfAQLA5te0w4/oLgD6B5jxR9p9CAnzwytPrMV/nlmvSUNmtbv5/lE4sDsH2/9Mx7GUAk39mruRDPQ4AOShj4c8dn6RBZAHO6kdBy8iGDQpYE4EcHw7pWVOZOkTjcXmJrL0qVoNOdDUqeyBEkGftzDoydqrWvNE1kAFaIrgUDm2CA5FlkF2PcKxuTnUcpDm1EfQTgmAPPTxn/H/VrMA8nDIWwPZfHgAVMKhJ2umtU90TCCGjIzD4JHxWPnFHuzdnqWp6/mX9cY7X8+EyWTAhQPfxsE9OZr6tSYAFhUVegyAISGhTtfjqQuYDcSCQIYOHSpFAduPvn37YurUqS6DQDSJSY28VoAA0GsJaQClAu4C4G3/HIu5d4/Asw+twYrP9rQ7QQkAIdvQTgAIKC2NBIBAWwRAbx42I8Z3wYL/TMGRQ3m4Y+ZXmoZqXQAs8AIAw9yyALL9gikpKZIGLInzq6++iokTJyIsLExK82JPA/Puu+9KbuD33nsP//d//4d9+/ahS5cumrSjRs2vAAFg82va4Ud0BwDZX9Bz7jwbn//fNpSXeR61djpFJwAkAFTefwSANkX4PYBnGgCy6zMY9Jg5bwh+WXkQJ7PlQROunkmtC4D5XgBguFtu6nXr1knApzzmzJmDxYsXS79m1r8XX3xRSgTNSr299tprGD9+/Ol8dHf4cxMAdvhboPkFcAcAm//srT8iASABIAGgTYH25gJu7adFawJgYWGexwAYGhrhFgC2to50vuZRgACweXSkUTgFzkQA5IM7lAEd/GcWP79GJfhIWx9ubyBrwO+t4/f5mbmoX2U7fg8f38eosgeQD+7g2yn30onmo7YHUOTq5ff2aQ3ucBUF7BtgQGVZvSyqmf+iad0PGBHrg7wT6lHhyi+wq31/Fn8DqivqUd/gOkBJcxQwt2/QE0uhakCHILqXDwiRLHPcHPjx+HZOewAFQSU1XOSwsg8/djUX6MFHDrP5VFU4Imn5/YD8XsHTESjS3A/29gSAnkYBN7dmNF7LKUAA2HLadtiRCQBtS98RAVCnB2K7B+BEqu2F7g0AzrgrEd+8ecxrALzuiR747LlU1Ndpiyxn83YFgJfcHI81S0+gqtJ1mhGtABgQagR0QEl+rUd7BQkA2++jtXUBMNcLC2Ckk8hag0Da7+p0vJkTAHa8NW/xKyYAbH8AyPYydUrwQ1ZahSzy2BML4J0v98e376UhI6XcKwB8dPEg/LA4A7vXu47u1mIB9As04F9LBmHJU8lI3SVPPaL2RVACYKdEX9z5Wl88P3cXSgpd56zTAoCBoSbc/EwfvHHfXtRWN3gFgCERZlRXNaCsxLF3VpgTUBEFTBbAFn8MujxB6wLgSS8AMMqtIJDToyad1VsFCAC9VZD6OylwpgCgyO3L7/ljF8+ndBFZ/ZRpV3hXr9acfnwaGB5+1NLA8PNRgzl2DbPu6YGa6gas/vg4qk9ZudQiekWu3lkPdEfS8BC89+hBZB+rlN0fauPxDZlL+LHPBqG2qgFv3rkf1ZWO5MlavnJ2l/KgCaGYdncXbP4+Fz9+eMKpq9Z8k3Of6YHEfoF447Z9yMtyuJNF/Z3Su1it8A824pZn+0g5Ll+7Y680F1ft7JPk3cOydjorxl8egwGjwvHmQ3tkY/BBF2qpY0RJovl0Mcq5yZJEC5JHK13AvHtY5A5m18vPh78GPiWMWuoYLfdEW2jTmgBYUJDjMQCGhUXTHsC2cMO08BwIAFtY4I44PAGgbdX5fX8tCYDDxnVC0pAwbFufg5S9RdAxP+ypwx0AjIrzxeMfDEVJfg2+eecIdm3Ml1nwlBY3EQCOn9oJl97SBWkHSvHRU8moKne4TN0BwEc/HSj1/X5RBlK2l7j1VbID4JhpURg3PRr7NhXiu3dZCl75oQUAI+MtEkSyvYQfPpaMzCOO/WpaAdCqs+KKu7ti6HkR2LY2D/979YhHAJjQOwBX3d0dcT0C8NHCg9ixPs9jAIxJ9MfQc6JQUVaLn786Ls2HANCt28ztxu0JAGkPoNvL2+46EAC2uyVr+xMmAGxdAGQWwJse7Y9xF8eiKK8aH79yADs25kqTcAcAWfub5ydh0NgIfPXfVPy+MssjAOzWPxDDJ0XCEmDAJ8/KS+tpBUC9QYfQaB/MW9gTr8zb5/ZNzweV3PN2EhY9dFgGovYBtQAga3vN492w+btcZKZWoLzUUWlGKwAya9q5Mzujc1c/HNxShK2/5HkEgN36B+GOF/qhMLcGz8zdChbzwVvqtFgAY7sF4OYn+yG2awCO7C/Gs3f8jdoam4WVANDtW82tDq0LgNleWAA7OV0X7QF0a6nbRWMCwHaxTO1rku0ZALW4fXmXL1sZUSk3UeUO1od9xopiXDyrO664sRdqqhpQWVGHT988gN1/2eCNHbzlkI/iVUb3Gs16/PPNoYjrFoBNP2Th63eTpTH5Pmo1eu2g2KV3AILCzJh+Rze8/+QBZKdVNc5FWT9YNh5fSk6nAzNC3vlGX6x4Mw0ZyQ6LmWjfnjIK2N7u5pd6YvnrxxujeNVqBou+JXe+1RvvP5ziEgA1fbN0Vtz/fl+8fusB1NfKA0l4+FKDSZ8APe58PQlv338QZUWOPYSqLmC+rFtDA/yDjLjjxX74+bN0Cdj2/GHbG8mPIXLt2ufG1uXcGXGYcm0XaYyFt25B/knHGsuigBVVTvjPomJ9cceCsxAUYobFz4iNa07gkzf3obJSXoZRVD2E/z27Bn5sPl+gyB0swSpXW7i9RAi3LgBmeQGAnWkPoKaHQ/tuRADYvtevTc6+IwGg2ceAgYOj0X9IFArzq/DLt8ca16QpALQ3TBoUjgeeG47QSAty0svx++oMbPzpBHKzKjUDIBsrJMIH0XF+OGtMBAaOisBHz+/H8YPljfPRAoASdOp06Dk4GFfd0x1vP7wfRXm2IAN3AJC17zsyBCMujsTiJ20VAuxju7ppRQB4wQ0xyM+sxrY1+VK30wGAnbtZMOn6GHw8X27NVMKXGgCef30M6mob8OtnWbI611oBUGcC/rEwSXLLr1+WKZNQKwCGd7Lg+n/2QUVpHVZ8kCKBW+reYjlAcsEifKCIHdICgkwYeV5njJ0ci25JwdI1vfPMTgkA2aG1fBwDwMEjozFweDT2bc/Fnu05KC+zgTEBoHePdfvzNz8/02MADA+PoT2A3i1Du+hNANgulql9TbI5ALBbr3AcOWx76XtyjJqQiM3r02QvW7VxeiZFIjO9GCxVWWyXYAwbHY9D+wqQesg2Bz7ww24BHD42Bg88NQrdetrqZuZklSM3sxylJTUoLa7B/h35+OErGzQoa/wq4dA/0IRzpsRj/9Z86eXKfvJzqvD8vX9LgRnsULMA8tfGAK7XoBDMeTgJy95je/ls7kZ3AJC1H3peJIZPisKixw7Yzq+o3atmAbTP59YX+2DFf9NwMt1mZXLXAthrWBC6nRWIH9+3AYYnAHjTCz2w9KkjqK5wL5DEfg2Dzg1FUJgJG75yrveqxQJoMuvwj1f7YNHDhyQrpFq0sGi8yTfEgbnFV/5fmmrksMgCyPZ33vPyIKz84Ag2r8mRWdxkAKkCgPMe6YezRkViy7ocbFidjqgYPyTvLURGmiO6Wg0AB4+OwjkXJSAwyAz/IBNCwy1I6BYsyVyQV4lFL23H6m9SUFXjsJDyFkCDvgZTZvTB9j9PIOVgHmqqqjFoeAx2bcmU1RJW+56z8m1bNh5HgyCXY1PPmoRuocg8Xoy6Os/uJaOPAUeq61sUrhwAeMILAIxt0Tk2pTN93joKEAC2js4d6izeAuA1tw7DFTechemjP9AMcKykXG1tPeK6hGD+GxchslMAbrzkUxTkOdyPrhYhIjoI9zw5HrNuGoKfvz2EwSPjUFFei+1/ZmD558k4vM8GgLzbl3f5ss+GjOiMyTO6I2V/AXb9nYvAYLP0U1lWh73bbPDFA58SCPkoXjvkMY9qYq8gpCU7ykvx7XiQckoEfcoda/EzQK83uIzodYI5Du74sf38jY0RuE7Jozm3rwgGjSa9LP8eP4aoj3KdtLZrqS+Z0kqnZd+fso3OgEYd1ABQ9JnRR2dLG2N1trLJoJFLBC2DQatVgtiSAhtcifYK8q5YV6lwMtPKpesQJY/m9xBK5+HmE5Poh9jEQOmPo+LCKkR08sMlV/XAmuVHsHFtumRNZIfIHRwSZsb1t5+Fs4Z3Que4AOzemoUBQzth51+ZePbhNTh+pEjqL3IHs/vozc+vQGKPMDx22/fYteUE7M8NrffOM29dDINRj0du/U5rF1m7q28dihcWbWtRuCIA9GhpOmQnAsAOuewte9HeAODEi3piwX8uwhVjP0RuTtO1NdmVGI16vPXllZIl4Po7huONf6/HF+9vbxIeL5vVHwvemILwKH9JkA9e34z3X9+GogJb6hJXVj/2eyUA8gAmcvu6C4D2FeL3ALoLgEpwlUGj0ponAEDecukJAIpcu2xuWsFOa7uWuqubAwBFlj21sWVpXLj9eE7VNgSVRZQAyOvjCQDKAkR40OSshmoAKNoPKEEbV01Ey35Ai68REy6IxcK3J0uXVV1Vh/8u/B3/9+pmVFY49jS6uifOubCH9IzZ9OtRhIb7SjBo/843dQ8xYFz603VY92MK3n1xY1PNnT63+JtwuLy2lQAwwwsLYBztAXR7ddtfBwLA9rdmbX7GngBgz76RmDC5J268dySun7wUyfsdgRBNXfBLH0zFVTcOQcqBXFx1zkfIz3Xse2uqLwv68A8wIyjEBzq9Drk5jhxvBIBy1zUBoO1u8sQCSAAohzw1V7EWAJT+QPOth9liRGlxNYryShvduloCQnx8jHjrf1fi/MuYSzkdsyctQWWF6wTfymdIUIgF32ych8/e24aTWaVY9ZX2KPXWDALJy0v3GAAjIuKdHp0UBdzU26T9fU4A2P7WrM3P2BMAfPH9qZg5bwgWv/kX/n3fj6iv17bH5qFnzsM1/xiGP9YexaZfj+C7L/aipFjdAsALyEf9st/zdX4JAAkA2T1BFkDbN6YtWQDZfERJorUAIKt8c8lV/TB2UjeMPq8bDu3Jwc2Xf6H5uTPzxiF48YOp2LcjC1OGvKv5mdy6AHjcCwBMIAug5lVtvw0JANvv2rXZmbsLgJHRAdiUdh+yM0rw6D++w8ZfbElymzqY5Y7t59m/K6dJd68I+pRVPXgAFO37U+650+L2dQoCMRgap8SPp0wYLdsfyLtpuX8rx5aljhG5dhQ1W8QAACAASURBVLnzs4nw1j2R21fpztXSzil5tCJdjF0EteAOrYEjTd0v7nyuFtHrqk6w0jKo1bWrPI8spx/nZlXbN8hb07TkBGRzFQWLyMbizq/sowUGldDIj61MAyP6TGQNZGPzbmw+JYwMDFlUl4ajS/cwyY2cfUJbwnHmsXj+vcswbEwCrj53Mf747aiGswCtC4BpXgBglxZ1U2sSixq1uAIEgC0uccc7gbsAePcT58DXzyTt3auq1OaG8UZV3upHAGhTkgBQfkcRAEIW6HGmA6AnzxP2RwsLWDt7XALuvuYbTUMQAGqSiRq1kgIEgK0k9Ok6zXPPPYdly5bh4MGD8PX1xejRo/HCCy+gd+/eqlP65ptv8MQTTyA1NRXdu3fHwoULMW3aNE2X4S4Ado4LQlaGtr+8NU2giUYEgPKoZgJA5xuGAJAAUOuzJqpTAPJzKzS5j1sTAHNzj3lsAYyMTCQLoNYboB23IwBsx4unZeqTJ0/GrFmzMHz4cNTV1eGxxx7Dnj17sH//fvj726Jflceff/6JcePG4emnn5agb/ny5XjyySexceNGjBgxosnTuguATQ7YDA1E0Me7fNlptLh9VSN6jcbG2fIuUt6VyxqI3L5O7TgXrqiqhygNjPJ6+NQvSper6DO1KGBRdC7fR2sUsHKJReli+HZacwKaLDrUVskreDR1S6kBoJo71j6ummuX/0w1opeL7hW5htn5+PF4167o96yPlihg5TXw7lj+PCJ3MDsP34dv507CaLum/Fjsd6KE0SJ3MOujZX9gU/eGN5+3LgAe9QIAu9IeQG8Wup30JQBsJwvVXNPMzc1FVFQU1q9fj/Hjx7scdubMmWAQt3r16sbPGUiGhobi888/b3IqBIA2iToiALJSY3roG+8RTwHQ19+A+L5+SNlaJkz+rBUAx84Kx8Yv3Esq7goAQzub4BtgwInDtjRB7NCyH1DZjo3NdLI2NJHTjwBQmB6GAFD8GLY/f3NzjyAoKLDJ57WyQUlJKSIjuzn1oyhgt6Vs8x0IANv8EjXvBFNSUtCzZ0/JCti/f3+XgyckJOC+++6TfuzHa6+9htdffx1paWlNTogAsOMCYOIAf/j4GJCy3ZbD0VMAZHVvr3u2CxY/fExovdMCgAajDre+3Q1fPJWOghPaAgLYvF0B4BWPxWHLygIc2+1IM+QJAEbEmRHT0w+71hY6lU7Tki5GaT0jC6C2gBC2rh3LAugdAKany9PI+Pj4gP3QceYoQAB45qxlk1fCXhRTp05FYWEhfv/9d2F7s9mMxYsXY/bs2Y1tPvvsM8ydOxfVXAF2+4fsd/zvGQDGx8cjjgUXNDmrlmugxe3Lu3zZTPgkz1oSPLM+wihgQaSv1If7TBS1y9ppcfsqq3rw16QluIOdp3OiHwJDTUjdVSqzXKolYXbl6vXx0+PORb2w5v1s7NtQrBkAlTAXGGrEvP90xa6fi7DhE9fWOy0AGN/PF1Mf6ow/vsrH9lXFmm82JQAmjQvEpJui8N2rWTi60zUA8n1ELuCYXr6Y/mAclr+agYwDFaopZkTRvfaxoxIsCAgxInmnY/+sMCJYEdErihbmXbtKl6sMNLnkz6KIYgm4+HZeJoxWRg5ryRfIu4PZfDyJENZ802ho2Jou4JMnUz22AEZFdac9gBrWs703IQBs7yvoxvzvuOMOrFq1StrLFxfH8Mz1wQBwyZIluPrqqxsbfPrpp5g3bx6qqpxz7C1YsABPPfWU02AEgK5TvTQnALKsKgbmT+QOTwDQaNDjlpd6o7qiHms/zcaJZFsJPXcBkPWZ82xXdOrmi3Wf5mDrqkLZ3ER7+5QwFxxhwtzXEqX5fPtSFnKOOBJ02wfUAoBjZ4VhwKRgnDhYiZUvZ2v+tvCw4xtowJXzYxEcacKq/2QjdaujQo3IYucKALsN9sel98RKc3hz3mFbSTXOzct+L9ofyLcLiTLhnJmd0GNIIP5750GUl3C1cznQU9s3qARAu0uaAFDzLeJRw9YFwBQvALAHAaBHK9y+OhEAtq/18ni2d911F1asWIENGzaga9euquO46wImC2DTgR9OuQOb0QI4dV4iouJ9cXRfKY7sLUHW0So01NuCHrRaAJk1r+uAANzw755STdYvnj2KI7vl+++U+fhEwR4Tr4nGwIkh2PhVLnb+UgRw8RdaAZBZAPudE4ROPSz47lXX4KYFAM1+esxcEIsVL2ahNK9O8/dHCXAjZ4SBWTcPbipFdqrjjyB3ADCujy8ufyAO2amV+Oq5dGku7gJgeIwPrp3fFUHhZvy8JBN/rsyVuZG1WADZHw0RcRZ07Rco/bAF+t/rqaipbpDlByQLoObbRXPD1gXAZC8AsCcBoOZVbb8NCQDb79ppmjl7kTH4Y5G869atk/b/NXWwIJDS0lL88MMPjU0vuugihISEtOkgEKecfmZz4/y1JHhmjbW4fT2p6+sqwTOzuph9DPAxG2Ay6WE061FbaUVFmQNUeMjh58a7fY0mA655uAcGjQtHVUU93nn4AHLSbIEKIgB0Sh59KkHz1Y8yuDAheVsp1n+RI7MAivqw8/CfhUSZ4R9qwKR50fj0seNoqHfccVoBkLXTG4A5ryVg6YMZqK91juLVAoDszLOfj8HX/85GTYW26jJKSxz77yue7Iy1H+Sh4EStzErnDgBOuasTThyolFzIxbk2q50SNJsCuKRRQZhwdTSqKhqw5PFUSZem+rDz8G1YIMttLychIsaCzNRyvPPIAVSV2xaJjw7mrYHsMx4IjWYdgkLN0h8L1dV1qK1pkH5qarnF1lg9hI0tihBuzvrB0nm4LSz8fkDeNdzU89Gbz1sTAHNyDnsMgNHRvQgAvVnodtKXALCdLJSn07z99tvB9u99++23stx/wcHBUl5Adlx//fWIjY0FyxnIjj/++EOKEGa5/9ieQdb38ccfb/NpYE43ALKAA73V4Y5tqsIHA76LZyfi4uu6wmTWo76uAe88vhf7txTA7hnUAoDM5cvOPefxXmBZYyLjfPHT0gzsWl/gNgD6hxjRUAPMfCQRGYfLse6zk423nlYAtM/5wlujkX+iFts4N7A7AMhOfNHdUdi3thTp+5y3HrQWAPoG6jHjyRh88lCGE7RpBcDYvhaMmxWBz+enN1pn3QXAvmOCMX5mFD57+ijqaqwoL7L9oeAOACb2C8AlNyegJL8GYZ19sOhfB1FS6AiO0QqA0Qm+uO+VsxAUZvsja9PqTHz9TgqKCuWuerWKIQaDDvWnLNUEgJ4+4Z372YPwCACbT9MzdSQCwDN1ZU9dl+gl+dFHH+GGG26QWk2YMAGJiYlS4If9+PrrryXoO3LkSGMi6OnTp2tS63RFAfMAyCxq0Dlcs+5aABmQWSxmVFXYXrKylC5crr+oGD+MmhiDsyd0xqE9BdiyNkeyXOn1OlSVNyDruC1gQK3EW2yXAFx7f2+ERllQVlyLiE4WHN5VhANbC7Hl15PSXjF2iCyA9j1/Jh+9BJIh4T645KZ4sP/+9u005By3wRN/DU3BnMlHh6v+lYjsI5VY+0mOU3/pmriybq7cwX5BBsx+JgFfLshAWaFNR3cBsN/EQIR0MuGPL+R7CdlYrQWAPUf6I7aPBesW24JRRHkARUEg7H64+pl4/PLBSWQlV8n6a7UA9hkTiLEzovD508dQnCePZtYCgL5Begn8ouItWPVBuhQ4wiy9Jfm1cheyILiDXXfS2SHoPzIMSUNCJXdxTXU9fHwN+OSVg9L9yg6l1ZAHu5BwM8KiLGhosKK2th4JPQNx0cxu2Lo+G3+uPYFjybZgFlFZOCus8PU3orzUZj3lrYNaAkKktWuolayWUn+uTNyZaQE85IUFsDflAdT0tmvfjQgA2/f6tcnZewuA8YkheHnxNKnGJntZaD3sADh8TBye/u+FmDd1GU5m2wBMDQAZx1w1ty9+W52GQcOiMe6CeAw6OxpvLNgqvZiU8GR3AQ8eFYUr5/VG0lnhMBj1OJ5SguLCaim/G5v34d2FWPFRqg18uITO0nz4COFTnyX2CUJGcrn0kus1OAQ9BwZj2btHGq2BTQGgXSc7jLEXdtHJmkZ3sDsAyMZibr7E/gFI3WELemgKGu3n58GMRb3mplVLFitJBw4a+XaidDGWAD18A40oynYuEagVACMTzchPr5G5opu6p3gw8ws2SFqU5Nog1l0AhA6I6W1BxgGbW14tWlgEc526+0iwVlpQ57bbWFpLiw6Dxodh65pcsDgRUYCImgXwvKtiUJRfg4PbClGUV4247gHIPl6OqirHlgU1ABxxbjTGXxwn5UBkPyxdUK+BYZImRw8VY/X/juCXFWmoq3e46nnI6xTvj5c/PhdHDxVh0y8ZWL8mDVOu6I5vlhxEWZkDikUJopnF8eNV0/Dpezvx7ecHPALAlz68HN9+tltzvXLlfTbtukF4Y+muFnWvOiyAB70AwD5OXxHKA9jUU6P9fU4A2P7WrM3P2BsANJkM+Hrjjfjojc1Y8dkel9fKp3exg11CtxAUFdTg5vuGY9JlPfD47T/jwF6H1UhU4SOuSxD+9fxoCfgKciux7Y9sbPwlHVs3ZqGhVtd4flGqF9YgONgHA0dESnugdv2R19iHhz5PKnxIL24XoCjBGPd7JZhpqeqh7COq+KFW1UP0mSeVQJwAkFt5EehpBUC+nVqFD/5m01wJhOukJQ2MEgDVcvrxn2mtHsL3Ef1bOQce2mR9OGsg6yOKEBalh1H2UbqDu/YOQpdeQdi1ORe52baoc3aouYP1Bh0GDI3E6PNiMWJiDMIjfZF9ohzP/3MT9u2wffdE1kD2WWQnXzzz5rnIO1mBBff+gshofxw5XCCDQWXqGN5S2O+sTnhvxdWYNup9nMwqdftZ3H9oDH7YltkqAJidfcBjAOzUKYksgG6vbvvrQADY/taszc/YUwAMi/DDXY+fA4uvEY/c+p3wOpUAyNp//stsWPxM2PV3Fp5/ZAPKy2pUrX5s8MEjO+G2h4dKgRhsL9KmX9Pxydv7Gs9r5ly9agAos+YJonsJAG2yarYAEgDKXKFnIgDyX3AtJeOUeQBHTYrBrJv7gln2mGH5q48O4MdlR1QBkFk42faMuXedhcuu6g2TjwFzpnyFtFRHrkk1AGRzvubWYbh0Vn/cMu0LVFXUoqZGHvii9oBuzSAQbwGwuLjYo1Jybf4FRRNsVIAAkG6GZlfAEwBM6BaKj76/RoooZH9dV3NuJeUElQD43LsX4fLZ/VBcWIW5l36NlIMFUhct+/6c6uhyrloCQLnbV2lxIwsgwMcVkwVQbn2TrHFcXkJvawYrAbCmzuF6buDOo2YBtLu4Q0ItePd/F6Nn3wjs25mD2ed/Ju1plCyQimT3rqqH/OezK8CsgS8//itWLzug+RnaugC43wsLYN8WtVJqFowatqgCBIAtKm/HHNwTALx3/gTct2Ai9u/KxvUXLkVujiPZLg98SrCbeeNgXHxlb/y0IhnrfjqOwnxHtCjvJuXdoj5cehjl3jwe+kSBH0prnqySB2cBdLXPz35H8H348yiBlJ+3yO3rVAmEg1ge2tT2AIo+4y12Sq1En6n2EVj2lHApSkCt5vZ1OOw9+96JdpuKqnqws4igz6kPNyUeVpR5AEWfqfXR4vbV6moWuYPZ9EX7A3ngUp5HBmYCGJRAkXM38314aFQCIH8uEQxWc4EeSiA1++gwblIXXHBZd2QeL8YLj22wAaCijzJ1jI+PEf/5/ApMnpaEn1cexE1Tm66Pbl/+1gTArKx9HgNg5879CAA9e4y0q14EgO1qudrHZN0FQPZS35ByN/bvysHD875FcaFts7z9UAPAiOggyfKnBEP23wSA8khZAkD17w8BoNxip4S5Mw0A+esxm6yS16GujuUzlEdZu8odyPYqP7TwPMy9ZwRGxr2K/FxHeUC1u6x1AXCPFwA4gACwfbxuvZolAaBX8lFnVwq4C4CDhsfirLNjseStv10KqgaArgJC7IMQABIAuvMNJQDsuAAoShAtWQQFyaPZZxMm90BwqC++/dx1wJry/mtdANztBQAOJAB05+HRTtsSALbThWvL03YXANmmbGW6FzWwE33GAx/TR4vbl3f5SlZDzn3KB37wbk1lJRBZ9RA+CIRLeaJ07Yrcvk7uXEG0r8w1rEgxI7L0idzByuvW0l/Zh3cP85WJlW5jra5d3p2rtU9zfidEqV7YOWRuX+6kWvvI3LmKSfOfaY0C1uICVss3KOqvTOkiihBWqx/M95G5eRU1kHlXrywghN/np+zDfabFHcyk5l3CMnc354JW2wPoCgZdPb9E9yIBYHN+S2ksbxUgAPRWQervpIC7AOhKQgJAmypa9v2ppXTREqjRFgEwKMKA0jzbpnxvAbDLUB+kbZNXqGjqayuCuQA2r1P5ACUYJABUrR/cEQCwqXuJ/7w1ATAzc5fHFsCYmEFkAXRnYdtpWwLAdrpwbXnaBIC21eGthh3CAqgDWPWPqmJHWgxPLYB9zvFDTbkVR7dWeg2Aly0Ix08vF6C6THtScVcAGBJrRO/xftj8WXHj189TAGSJpVmFkKpK+ZzIAigPCOEDP5QBM6I6waKAkJayALrzLG5dANzpBQCeRXkA3VnYdtqWALCdLlxbnjYBYAcFQACTbo3AwfVlyDxoC8zxFAB7jvbD8CuCsPLpXFQUOZKtiPIIir4PITFGXPxYOP74uBhH/3KuJyzqpwRAvRG4+F8ROJlSg82feweAgZF6jLs+HKtezYEi1zIIAAkAvX2225+/mZk7vADAwU7ToEog3q5M2+tPANj21qTdz8hTABS5fdWCQESBHkxEUboX3i2q3AMoqt4h2g/IziNKBM1b/ZyqdWio8MHGlu0V5Pb6eRLRK+yjAwZfEIqMAxXIS6+RnVOUrkaam4uybn3GB2DMtaHYtqIEu38qhYHV/OIO0d4+pT5dz7Zg9Jxg5CTX4Lc3ixvL4YnGUn5p7KCYdL4vBlzqj/Sd1fjzQ+fKDUqrkn0cpa1w8HR/9Jnoh4NrK7B9mSNFkShBs3LPnX28LoMtGHN9CI5sqcCmT4pkwMfOLRuP2/MmKxF3Kp1KQJgRPUcEYNevhaitsp1BNB+niF4uJYuWPYRsbC0VQ5T7BkUpYvjfS2Pze/D4lDCcBso0MKK8grwFUC0tjZb9gGxuoiAQLfkClfdla1oAT5zY7jEAxsYOIQtgu38TN30BBIBNa0Qt3FSAANAmWLsBQACde/hi5pPxyD5ShX3rSpD8V5lUv9ddAPQJ0OPaV2JRX2vFr4vykX1AXsNXKwAmDLZg4MX+OJlai93flaOmwtl9q5b3zw6AUb1MOPvaAOxaUY707fL0HmyNtAAgY9jeE3zRc5wvjmyuwt4fHSk/3AHA4E5GnH9XGALCjfjhlVxkHap2GwAZcycMsKD/xGB0GeSH3xbnYvfaosZvKAEgQABYguDgYHgLgFQJxM0XXztsTgDYDhetrU+ZALD1ADAkyozJc2NRV2tFcW4Nik7WYO+GYgnAlBZENashC7QYNSMcI6eFI/d4Nb5+OgO11e4DIDvnqJmhiO7pgz1rSnF8uzz4QisAGkw6hCeYMPBSf6z9j8Pl6q4FkLWf8mQofn6pCLWK/XZaAZC1GzzNH+UFDUjZVNmorZrFzZUFkLmjJ90ZhswD1dj4caFk1eRdvposgDrgglsj0WtkII7uKMd3r2VpKhmntIT1GhGIyHgfBEWa4R9kwO9f5yD9UIVsLGUfsgDKk0S3DwtggNuvi5KSMjALIAGg29K1uw4EgO1uydr+hN0BQC1uX76kmwQ1Gt2nZpOpUSyR21e5R41354pStTjV9dWQ+kU1RY3FiPDOFkTEWHB0TylqKh173kTQxv8+LNoHs/6ViKguvsg+Wokf3snEyTTbfjdhhQ8XqWNYUMLEuZEwmfSwBBqw5p2TqOVycvMuXza2uMqIDgGRBlx4bwTWvJovgZP9kEX08hVLFLe1ZMHTAZcsCMWvrxajqsQGtHx/rZU/Jj8ejF9fKXEJgKJvkyy4A1ZMeSIEa98oQVVxg8zNylsQ+T5KsNMbrZj8cDh2fluG9D2VjS5tpQVSmPrFapWCRsZcHYaIBBMKTtRi8zeFqCypF0KbaD9hYJgRE+dEo/fZQSgvrsP/XjyGjEMVkhQid7DyswZrA5LODkFRXg1yMipRXWkL/OGTK7P/FqVaUbqAeR1E7mBlH36uWtzBymuoqXVYp0VJrpXX5Gm+QPt91rou4K0ICvIUAIcRALb9V63XMyQA9FpCGkCpQEcEQMYrQWFmlBY4XioyFzAHiUwvlscvIMSEy29JxJCJkVKB+vLiWqz9XybyTlQh90QVCnOqoYNjD50aDJp99ZhxfwLS9pVj4DmhqCipx9Yf8iUrkX0bFd9fCb72z5i7Uw89Bl0YhP4Tg7DmnVzkp9uuSSsA2t2v3Uf5otcYf/z8WkHjHNwCQGZ5m+GP0pP1SN1osySeDgAM7WLAoKl++O2NEmkOohQxagA49Erbi3jr/0plkKUVAH2C9LjgtggUZtVi/dI8WBsg/ahBmxIAY3r6YuhFYWD/v/PXAiT2D8Cqd04gL9sRHKMGgAz6gsJN0h8qYTE+GDklCp0T/aQ5pO4pwTdvHUXmUcf+yKYA0D/IiJoqVnmjQeaKJwD07p1if/5mZGzxGADj4oYTAHq3DO2iNwFgu1im9jVJbwGQwdTN94/Ex2/vQH29Fe5aABlMzb1nEFZ9mYqCXGdLGB/4wYMQO69Rb0B0rB8unt0d+7bkYeuGHEl8UbJns8WAcy6Jw6Qr4nFoRyFKCmsRwax5nXyRdawcn7+ebIMnFwBoX9UeA0Jw7lUx8A82IXlbMSJiLYiMtSA4wozn5+5GQ702dy6DN51eB4NVj8SB/hg+JRx7fitG8hZb8IMWAOTbxfW1oNsQf2z8rNAjAGSdhk0PwqF1FY2RvO4CYGi8AUGdjDi+1bZ/zxMA7HOBBcm/VaFevh1R9UvFw1xYVwMsAXqc2G2bg7sAyCx3Q68IxLZvSqQ5yAI6FMmNRRbAvucFSK7n/evLnNzGImjjAZDlL7z07lhs/7EAB/8sQW1tA4wmnbR1gLeeqQHg3Kd7wj/YKP2BcjKjUrpHQ6J88OuXJ7DnzwIJSNUsgOMu64QR50cjL6sKeVkVEvxNnB6HdSsysHZ5BkoKbfqKAJCB58x/9Mb3nx5B6v4iSUf2nWUSarEAGk16zLm7Pz59Zx/Ky2rhiQVw2uxe+HH5YZQUVWsqGae8yYaOScDyTcdbFK4IANvX+/J0zpYA8HSqf4aeWw0AtZR1m3F9P0yY3B33z/2pSXjiwYq5fM0+Bjz28mjpBffyI39J/6+EHz6il0ERe4nMvj0JGUdLMercWHTtE4yfvjqK31ZmoKKsTgiAvQaFYPbdvdGlV5DU5tDOQuzamIf87Crpp/BkbaNrTK3Ch/0zBnxlBbbz2Q8tLmC1RNC8u1o1oINzx8racZG+IqshmyufnkUNNHm3rShJtQR6nAbK89o/4mFQmoOX3yeHo1oOecphebAS5QFU7p8TWQedolSbiPxlc6lXQKPI1esqcth+LVqgr6nIYWYNLMmvlQGtU/UQPs+NwYqwaAvCO1kQGmVGz0HBGH5utDSl/OxKLP+/VPz1S47MbczP06prwOjzY3DJNd1QWV6H7z5NxfBzOuH95/egvMIR4CNzDXPVQth5Zt2ShLEXxOGxW9cjN8fm9maHCAbZZ/w1zbvnLIRH+eG5f/0uiw5m7fgawiJX8aybh+LF/9vWSgD4txcWwLNbdI5eflWpezMpQADYTELSMA4FvAHAkDAL/vfb1bh5xnfITD9luVKxntkBMKqzH7r3Dsf1dwzAwd35ePeF7dBzKUhEJd4sFiPuWjAE4ybHIedEOb545xA2/5IpWR558BBZANlV+/ub0LmLP/wCjDi8wxGwoJaiRriPUWNZN61pYAgAtX8zCQC17wHUXD6OA0DlfsDEPoEwmfXIPFaB4kKHG5pvJyoR139YOK66tRd6DQxD8t5CLLx3M4oLbNsE1ACQfTZ5ejfMuqUvFj64CRZfI3b+laMZAI0m4POfr8Djd67Frr8zZDeXFgCMSQzB5mNFLQpXDgvgX14A4IgWnaP2byW1bEkFCABbUt0OOranADj2vG6YPL2XBH6L39rdqJ6a+9T+2TNvT8CYc+Ox5L978NmifVJfESTZLYCBIWY8+NxwhEf6IvtEOU4cK8OyD5IbrXZaAZC37on2/WmxACrnrHYNBIBydzDTiiyAYoBTBqU0hwXQ/gWVlXvj8gtKMKYCgPzjkXf7agFAZpiecnVX9OwfgqgYP6kk3+uPb5Os+E0BIDvvyAkxeOzV0cjNrsBNl/2A8nJHtHpTgSzsOXPrA8PwxtObsHl9euNlaAHA1gwCSU/f7DEAxsePJADsAO9vAsAOsMitfYl2AOxqMslcg2weyv18vEt41ZY5iOrsjwfmrcHfv2c2TlsVngwGjJwQi+fem4iigip8/OZefP9liiYAZHuCGurk+eV497AM5jhXqLKsmyjfH/97tWsQJXtmFyEaWysAaukvwROfZFpwrbybVwmnfH+RO5j1EdX1Vbp5eZiT7ftzkXzafqNojQoWfR9E7lynlC6cC5a3GvKQpQzuEOXnU7YTuXNFUbISZPHz0ZDgmfURJWjWGgUsAjYnt7EAANUiemVjc/2Vrm/ZXsG6OsmaqAwoUSaPts9vyOho3PboYMQlBmHJm3uw+M1djbeF09wU19C9dyhe/egCRHbyx6SBS1BabHM/a0kYHRhiwc6TJS0KV/bnb3r6n14A4KgWnWNrv5PofK4VIACkO6PZFfAEADvHBeKnnXNxLKUQd8z+AbnZjvwjavDk72/Gs4sm4vc1x/HLt2mornLUoW3KAiiBDwcUEqAajQ7w5FzPfAQsAaBNItFePwJA5wTTBIDyvXQtCVriGAAAIABJREFUAYD2Ly4PyyIAZG2tsGLMpFhcfl1vPP/PTcg8botgbgoAff2MeP7d8zBqQjwenPcTfvvxmGYADAq1YEcOAWCzv3RoQI8UIAD0SDbqpKaAJwA49eokXHnDQNw7ZzWKC6uFuf4k8ODALDjYgsrKOilSloc3JaCI9gASANpWkiyADAgcBw9sZAG06SJz9YpcuxpdwG0BAPnr8Q3Qo6TIOQpZum4X12ow6vD4S+Mk699LT2zSDIAMTo/W1raodc1hAdzkhQVwTIvOkd6gbUMBAsC2sQ5n1Cw8AcDJ03pi02+ZqKq0RcFqDqDgYJAA0NkyRy5g7V8tAkDtQSBt0QXsrgVQtFewKQtg43ka6nHJlb3x3f8OtUkAPH58o8cAmJAwlgBQ+6Oj3bYkAGy3S9d2J24HwJ4BAU7Jg9XSwGit8MFDDW+54vP7KS2AfDs+MlYJjbxFkG8n28+niEqWuTw1VimRjc3vv9MYBaxWZ1hUwUQ1D6CGfX9O6WYELnLRfkA1S6NTShfBXj+1PIDKMezfkIBoHcpynGsJK79BMqufwBrIfi3MA8incFFJ1cK7KJXBGfw+N97ypJY7ULafT8N+QHYNWvYAqlnptEYBy4JNBFZDpZVNtN9ROR9Z7j/uunm3L9+GnUe0x5KvH6xcE5lWGq9BtB+QrW9yWVmLwpX9+Xv8+O9eAOA4pKenIyjIluKKHT4+PtIPHWeOAgSAZ85atpkrIQC0LQW/d1EZyUwAKK8swsObyReI7GlE9h7bfk5hEIjijhcB4NAbzdi+pAZWx/ZQl98VLQAY2EkHvQkoOm4L/5CVgiMAlOXMY/oQAMrzA7YuAG7wAgDHO31H5s+fjwULFrSZ9wxNxHsFCAC915BGUChAANgxAdASpEdVSYNsP6Fyj6Vor6ES3i5YEIAtH1SiOINVe3DE97prATQHAOc8YsH2xTXIT+Zjdp2/tk0BIBtr9J2++Pv9SpTn2iyK3gCg2V+H6vL6xpJubDyyAMo1FUUEK+FSFPjRsS2A3gEgWQDP/Fc7AeCZv8atfoV2AOwbGiqLFGUTcbesm2RJU7pcBS5TpQtY5PYVuUjZuUR9RLn+WB8trmunSGbBNSjdrLylUBTVrNRH5OoVpbVRaiyK4lVaMfnIaHbOpAstMPnqcWhNNWqrTpWvU0RZi9zDyjQw4+63wGDR4a+3qlBT6jkAdh6iR9J0IzI21yN5VYPMfav8YqgBoN4IDL3JjJAEPX59srKxrJzInauW3qVBb0X3sT4IiTfg74/ltXNlrlXeosinQ1EEWohcpjxMKt2nIleoyDUswSl3Xi15BJV9lImgef1Fn4n2GjoBIDc3tWvQUjLOqTqLaGy+yomiYgjvvufdwWzs/YWFreICTktb57EFsEuXCS06x1Z/KdEJXSpAAEg3RrMrQABok1Q1kKUNAWB4vAm1FWis1+spAJr8dLjoyRApt+L+1VU4trkGBllRNzlg8+dRAuDweT4I72nA4R9rkbbB4bt11wIYP1qPxIkG5Oxq8AoAo/rr0Xe6SbLWrXvaUbXCXQCM6mNEv6kWBEYZsO71UuQfkxcodhcAzX46qVbyyVTnCFYCQDm0qkEjvwfwzAHA37wAwIkEgM3+Zmx7AxIAtr01afczIgBsXwDoH2rApf+01WRlIHFsayUy9tgqI8isjgpLrNICyNr3vcgXSRf64viWGmz/sgJ6qzw9s1YLYFSSAXHDjcjaUYeT+xwBHO4CIJvTqPtN2PpOHeqq1Gv8qlkA/cJ1GDzXhMOr6nByvwNI3QXAbuPN6D/VF9n7a/Hn++WyoASlxUzkDg6JM6DnWD9EdTfDP8yANf/JR+4RAkD7g5MsgCUIDg7GsWNrPQbAxMRzCQDb/Zu46QsgAGxaI2rhpgJKAOTdvlrKurHTiSJ9naCEs6SppYER1cR1cp8KomHVom5FFT/4a1W6doXl41SigF25gxP6+SEw3ASjWQ+jWYfCrBpk7HWUtRJVGVFa3EKjTJj8YAT8QgzY+2MZdv9QhoY6uRWTBz7lOtjHY1bAhMFmdB1rRsraGmTukEdeiKyLyvkwbAztqkO3SUbs+IBL7q1SCURhbGy8a4fdo8fORQ0SAKoeXKCwLHGz1YoeU/SoLgbSNzXIoI2PLRa5Vdk5GSiGxOsx5DoLDv5YjbKcehSlNzgFTYjG4GEwYZgJo64NlqyRa98qROZB13V0+bF4FyubT1i8EbFJvqirsaKmql4qf3h0Rznqah37JJWWMC1uX6WrWeba5auUqLhPRQDnNLagSgjfTmsJPD5y2KmaCTdvmaaKa9BS9o6NvSs7u0Xhyv78JQB088XVAZsTAJ7hi75hwwa89NJL2LZtG7KysrB8+XJcfvnlwqtet24dJk6c6PT5gQMH0KdPH01qEQA6WwCbAkCLnwHxSf44skO+J0yWwJpPu3IKFH0DDRg/Owr9xtvSNaRuK0PK3+XI2F+JytIGmQWPh04lcLHPgjsb0WOUHywBekT1MGP78lJk7bXlZZSAT7GfT7jXUK+HJViH0bf548CqauTscwCcOwDIzjniLhMOLKtHWZbzHJyifgW14LwFQJitGHGPEX//x2ZF5CFAKwD6R+swfK4FOz6rQv5Rh6ZKMFMDwLAEI4bMCEBddQNykmtQeKIOJ/ZUyxM0i2Dl1O9NFh0697IgfoAFA88LlkQ9vq8Cvy05icKsWmGaFNZOCYAJff1RmF2Nojyb9ZEdBICndBDAbusC4K9eWADPa1FI1fQioUYtrgABYItLfHpPsHr1amzatAlDhgzBjBkzNAPgoUOHZDmgIiMjZXva1K6qOQAwPjEYWek2GFLCipYSb/HdA5F9vEKqEMIOdy2AnRP8AasOuZm2knRaLICBoSZUFtfDYNKhe/8g+PqbsPfPQhs8KSx7DLgCw0zoNzoEfc8ORZd+ASjOrUHKjlJInKWT/oc1H2Y3Si0KCGH6xPSyYMJ1kdjxUxHYizk2yYKaygb8/kkBspNtFsGmAFBqpGOgp5csRMOuDEJxdj22fmlbB3cAkLVnbtORt/jjz7cqUV1mWwd3ATBmGINJPY79ZrNM8XPQCoADb9Rj36cNqHcYRl3fvgILYGhvILSHDsnfn0r9wr3cNQGgDhh9twUHvq9Bfkq9DLK0AmDX0T7oPdEXO1eU4/iuStvNcerksgodAgA0B+lwwW2RCI4yITu5SoK+niMCsG9dCfZvKmnUQ82KOeySUARFmMBiUxoarOjc3Rfxvf2RmVKBQ1uKsX9zMbKOlcu05a8vvrcfAsPMSN5RjPLSGvgGGFBb3YC6WqvMEiqyABrMQJdegTi8q8gJNkX7HZUWwJhu/khLtl2vKBG0mgUwKsYX2Rm2a9SaMJq3DPoGGLHp8PEWhSuHBfAXBAX5u/0CKikpR2LipBado9uTog4togABYIvI2jYHZS9MrRbAwsJChISEeHQh9gfQoE6dJPBxt6pHaIQF7y2fgmvPXykVd3dKQCwIoLC7gGMTA7Dg7dFYcNsfyDpue1jz7mFRsmedHjAaDbjo6kRMmBqLJS8cwIFtNoCTAaBiL1ynOD/MvLcHSgpqYPEzIqF3ANIPl2Hnunzs2lBgAxcFADKY0xuAhKQA9BkWjJ7DglBfZ8XmlXnSi90WAGrFoT8dFsGmEjyz8STIgu0fwdFG1FZYUV12Cp5cWBDtCyzKWejPUruUnoroVbqnBYmgZVZLH31jxKxSB34dlFHSjdCvsOrpDHrHPcn9k/1SBoR6gTlQeUc3OBBOVvKNyxhjrW+QARdfM07kZlVGAcPQ4Igc5q1DytJpgshfg8UquWuZW56HHQlkNJRla7DWIzzejPzjNdK9xcZgWwbYmFpdrgkDfGEJMEg6N1gb0HdUMDp180XythIc3laCo3vKUFXhsG6yufFWw/gkP4y8KAo9BgXhZEYVThwpR5+hIfjqP0eQfArqJLASWM/COplxx8KBSN1XjK/fSUFpWU1jCh1+HUQJos0+ejz38Th8/PpebP09R5bCR6sL+OUl52LJf/dg5185Tvs3tSSMvv2RYZh7+/IWhSv78/fo0Z89BsCuXc9v0Tl69GKhTs2uAAFgs0vadgd0BwATExNRVVWFvn374vHHH3fpFhZdqbcAOOeugTCZ9Pjw9d0u4UnNAhgYbMLzi8/BR6/txfbfcxqn2BQADh4biW59g3HWmCikJ5fi8/8eRnWZw3XpCgD1Bh3OvSIWU65LgNnHIFkLl711DEf2lkhWDRlUuQBA++Ts1xMSZUZpnvwFKrI8arFISsDFuW217kmUteP7ewCAatZbTQAokZ3jTjttAMjf7JzZTysAyip5eACAouhgrQDIQ6LUhwNNrQCorAUcHGlCcV4t6hkgnzq07Btkf2h17u6Hi66PR6/BNjf0pu+z8N0HaaiqqBcCIJun0aTDlGsTMXpyZ/z8dTp8fA1YufiIDMZEAMjOExVnwZNvjcaz92zG0eTixnlrBcDRk2JxweVd8cTtGzwCwEtm9sT8l9e2KFw5AHCNFwB4QYvOse2+JTvWzAgAO9B6awFA5vpl+waHDh2K6upqLF26FO+++y7Y3sDx452zwzP5WDv2Yz/YAyg+Ph6eWAAZ+H3661TcedUa5J20uV+1WgCnz+mNERM64+/12Vj5SYrM3agGgIm9g/DoW8Nh8jHgnfm7sXXdSem8wkCNU5avkEgzOiX4wWTQQ2fQQa/XIXlniWRVUfb3JL+fNIbAakcAKJk6ZUeLWgAJAOV7DQV5CbUAIJOSWfl6Dw2GwaAD4+G62noU5VUj53ilKgDalyG+RwAefH0I/AJNWPTUHvyxJtMBc9zclJZYBnoDz47ErY8Nwk9fH8WPXx+TrJZaAdCqs2LJj5fin/PWIuOYw3UuXROvicAqO3B4FD5Ytq1F4YoAsAO91L28VAJALwVsT921AKCr67n00kslt8/KlStdXi4rD/TUU085feYuAA4YHIVp1/WR9sA99/CfjeNpAcA+g8Lx8tKJyEwrw5P/2IT8nEpNABjd2R9P/t8I1FQ1YNefudj8czaOHrA92JsCQPsERe5Tdy2ArmCXAJAsgOy+aIsWQPv9L6oLzD4XRQ4r9z5qiaDlASuiswWjJnfGwFERiE30xwv3bkXybtveQDULIAM9X38j7n92GIaMjcZ7L+zC6i+PagZAdq1Xzu0DBnK//ZCGX1YebXxOaQHA4HAzftmZ2koA+JMXFsALW3SO7em9eSbPlQDwTF5dxbV5CoALFy7EJ598AhYJ7OoQWQCHJ8YD9eo1cXnAOe+Srnj81THSX9YPXr8WBXm29BZqAGh3MT70wtkYdV4Mln+UjK8/OCylsxDtmePdkv2HRtgsDxkVTtAnK1vGuT+VqWNEACiK4FVek9Z2WmCQjc3PWwSxyhJtwlQ23HW7ihy23w8it7wy7Y/I7aszys15zKJqP3i3r+z3iqhkWRoYD/YA8nv7ZDkBTwUS2ecj7Qk8dVi5z6x1jt87BXdorOqhJaBDaWXjzyVLgSJw87Kp831EqU2cziOw+okgTwmuqu0EFjO1nH72eQeFmRHfKwC7/8yT9jeKqn1I133qPBMujcec+/qhuKAad8/4FTV1XG5H5b5M7r/ZPtun3hqHYWM748v39+O9l3c23gtCHblru+XhIZh7R2vtAVyNwED3g0BKS8vRtetFBIAdgA0IADvAIje+SDUEgbiS44orrkBBQQHWrl2rSS27C2JIbKwEYSJAYoPx4DH7ln6Yc/dAPHTDWhzYmd94rqYAMCLaF/96ZQQWLdyFY4cdbhktAMhH1krzEQCPWvk4AkBFwmg+SEdZxo/Ps8i1IwC03e4EgHI41QKASqDVAoCsDwPHWx8diDXfHMNfG07lGWI5G1UAkK0Pe968+eUF2L31JJ65f5NbANh3SAQ+WN5aLuAfvADAKQSAmt527bsRAWD7Xr8mZ19WVoaUlBSp3eDBg/Hqq69KAR1hYWFISEjAI488ghMnTuDjjz+W2rz++utgASD9+vVDTU2NZPl7/vnn8c0332D69OlNno818BQA751/NvbvzMMv3x2TV6BQSY7MrFIRnXxRmFcFvVVuRSIAFLuxyQJ46lbmooDJAqjYx6YAIRGMnW4LoKcAaIft6Fg/ZBwvdQlySii39+nZLxQ3PTAID97g+KNYiwWQWV63pKe3KFw59gCu8gIAL27ROWp6kVCjFleAALDFJT69JxAldp4zZw4WL16MG264AceOHZOCPNjx4osv4r333pOg0NfXVwJBBolTpkzRfCH2B9Dw+HjJoiZLA6O0CHFwN2BoFPbvyJPOI3Ipss9ErlmlNU/mChWkLHFy53LtZDnruN8rU5aI0tyI8vapXZ9TZRKB61mrRVJWUUVQ5UQ5H6GrWQXERSXj1BJg81Y/nUnFBcy5h2UuYIWbV8f/Nx+9bLaivkaQFoZzk1r5lDD8v5UuYM7VK3MBc1U0eHewElBke+aU1SQEEcKiihrS2ALXrMgdrOwjciFrdQGrWelE+wN5aHTSR5TWRqEVH+DBz0E2H259ldctSh2jVguY/6z3oLDG55USFEUwyLTefOxYi8IVAaDmV1WHb0gA2OFvgeYXwFMAFO4jU4AHAaAckNX2JLY/AGQR1Dopqtp+yECR/71GAEwYU4vjm4zyaBL74B4DoG2eBIDqVsMzGQA9KRnXmgB45Mh3HlsAu3W7tEUhtfnfOjSiJwoQAHqiGvVRVYAA0CYPWQBdV0BxCXanLICBsVboDEDpCYdF0BsA1BmsGDK3GvuXmVFZoMgbwybiAQD6BNTDPwrIP0wAqGaBVFrFZJU3VGoBa4kIZmOfbgtg2wfAlV4A4GUEgB3gPU8A2AEWubUv0Q6AIxMTJRewzAql1Y2oEn0qq0HLufr4XH/smkUVP0RRsqwPP1c+r5woSpb1ESVY1gqAau20RP4Kq2gorkc1GEdQXUWtT1OVSSQ9FevNw5ze7Ax5eqMVQ//RgLTfDcjdb/tcz0cIc1Y/WVJoZo/jLYKnhg6KrUOvC6pxYpsJWbvNzl8FvuKHzO3LfcD9PjCmAT0urMWBFUZU5OpgFbh9G2q4/owzBRHCWt2sIihSQpaoioYyKlnmHubcziJ3sNN5NEQEuwOAIre42nz4SG2ZC1hQDo/NR5Qihs8DqMwdqDmJt8B9r3QHbzxypEXhyv78PXLkWy8AcGqLzlH5RUxPT8d1112HkydPwmg04oknnsCVV17Z2q+uDnc+AsAOt+Qtf8EEgO5ZANs7ADKLXcwAEwqPNqCmTOGedhMAmXJ9Lq9HaHcgc5sex//QQ8/vG3UTAOOGVyMqqQ6l2QYkr7F4BYARfeqReE4d6iqB7R/aXMreACCrbRvSHZJutbYsRML9fASAzrV3CQBdP8vbIwBmZWUhJycHZ511lgSBrHY9K0rg7+9+GpuWf8OdOWcgADxz1rLNXAkBYMcCQHa1nfubMOBqI0oyrMg/ZEXWNhvUuGsBZGNFD2xAlwlWyQKYtlEPHSNM++EmADKLYr/LK3FwtQW15S5cwJotgFZE9m1Awpg65B3S4ehaBoBwGwDZpUQOAiKSdAjtpsOx9fU4staRg04UUEEASACo9QFvf/6mpi732ALYvfu0VrUAKq9t4MCBWLVqlVRRio6WU4AAsOW07bAj2x9AY7t1k1yqoqANJpAo8EOtjyw6VyVBs2wMQQSsMoBCS+SvMrmxqOKHVhew5rJugmtVQpY7bmO/MD0iuplY2AVYGhQWCZt7qAH1tbbbV62aifI8Xc7Ro/v5RlQWWLHrgwbUlgHK/H4yt6/ZAXa8m9fkb4U5UIdeF9Vg/wof1FU52sn2AyqDQLgAEamczKmj72WlOPRjAOpr9bI9fzaCcxT2lQV08O7gugawvYR9L6/C8T/NqCm1orLQBpO8BbCBjw6ucUAda2d3CeuNQNJVQGh3HfL2WbH7i1pJd/uhrLfr8vcNDYhOMsJg1oHV1bVaG1CaU4+ijHphHkEeLNmYovN46wJWO4/aHkBR/kNV8BWUfBNFBEvXza231gTYvEtY5A5WaioKfmFz25CS0qJw5QDAZV4A4HS35sjKh7700kvYtm0bmDVv+fLluPzyy2XvwLfffltqwz5n2SVYyrFx48Y5vSe3bt0qZafYu3dvh32HttaFEwC2ltId6DwEgLbFblUA1AGhnU2oLre5Ye2HaJ8eD3aJI3wweLo/TL56lOXVY9c3VchLrYNVWcVF4c51BZp9phlQmatD3CgdjvzErIHy9CtaAJDNnaWFiexTh7DuDUj+yacxgvd0AWDssBoYfIDjm8yQgR63B7ApAAyMBXpeBhSlWsFAMHW1FdVVclBsEgB1QECMDv0utiCypxEN9VYc+qUKB9ZUSuslAiklmMFgRVicEXlptait5SyQ/H5AlRQ1WlLPqEGRMg0MAWDzvSDsz9+UlG88BsAePWa4BYCrV6/Gpk2bJNftjBkznADwyy+/lPb4MQgcM2YMFi1ahPfffx/79++X8tHaj/z8fAkK2WejR49uPlFoJJcKEADSjdHsCpwJAMgMSEajQSpUzw5PAigCAk2orrANoFbNxA5SgeFGVBTa2jPLTmgnM0pyHC9nJcwZjDr0GRuA+P6+6NzTB5ZAA7Z9W4TqMqCuugG1VVbkp9WhqsQ2plogS0CYEUNn+aOypAGWAD1C4g3ITa5D5rY65B62zcEppx+fW9EOhzrApDfANxzodbkeNeXA4W+BhlMWRXcAkJnGel9Si4JUI/KTbS7X0wGAvsF16H5eNfYtt6ChVucBAFoRP9aKiCQg5XsGgA1s+6Bk+VMFIQ7A/DsBCSNMkuWvoqgBBcfqpX9v/6IS+cdqGr/DIpCy6uvRuY8PTBYdjD56GH2AAZMDYTACOanVyDpUjQMbylBeUtc4lhIaAyIMKCusQ32tVdqrGBhmRGlBndCaqARAdk5Wc1tZrk3ZTi2QRW/QSdAr9SELoMtntwMAv0ZgoJ/bz/fS0gr06HEFWGBGUFBQY38fHx+wn6YOVyVHR4wYIcHhO++809g9KSlJshI+99xz0u9YSdHzzz8fN998swSLdLS8AgSALa9xhztDcwDgU2+PxcuPbEF5aa0TeGhxAd/x1CCs+fo4UvcV2+DFDRewXq/DtQ/2RkZqOdavyLTBk0p5M/tnRhNLC6JDXC9/TJodg6qyenzzWppLeOJhKiLGgvGzohAcaUbm4Up06m5BWIwZhVk1+ObZE2g4xYCurHkM1nqeHYAeI/wQ2dUHO74vhsnHIL3oTT46HN5Qifw0G32pRjKfuj6zvw71VTZAiOpthNGoR+ZOGxRoAkDe8qkDogbpkct5ctwDQMAcwNLC6Br373kCgJaQBlSVMF8pc3Nz/lZ2URpcwDpdPXwCrY1pZDyxAIZ2b0Bhig2E+YhgrQAYnKhDQIQeOQfqUF5cL60Puy8a6uQgJAJAg6UBw64IQl21VfrDgIFY73F+0r+T/ypH6l/lKM2rl9UIVgLgeTdFInGQH8oK6pB1pAr+QQbpj451n+bgxOFK6R5RcwGPuDQCg84Jw29fZGHPnwVg35e62lMwJ4hE5iEvISkAU29OxLuP7UNleb3bAOgfaMK9Lw7Gwjv/Rn2dVVbyTbXkHHePPPHmKLzw8F+oLK9rsmSc/cHPr8ns2/ripntbpxZwSop3AKh8cc2fPx8LFixo8n2mBEBWUcrPzw9fffUVpk2b1tj/nnvuwc6dO7F+/XqwgJ7Zs2ejd+/ems7R5CSogSYFCAA1yUSN3FHADoDje/SQQYcriHC1BzAs0oIXl0zELZf8JJ1WWeFDlgaGTxdzCvKShoTh+vv6Yv6Nf8J6yoInSv3ilETZpMfcx5JQX9uAT19OabQ2NJUOJWl4MAaMC4NfgBEhkT5Y+0UmkreUNvKFKwugxV+Pc2ZF46zzwsCseeylvP7Tk8hOrUJ+RrX0gpdBG1+lhN8PeOrfzEJTU9GAhmpHsINo3k7VTLjxRK5rtSolfB+9iduzp6jwoef+W8/tAVRWAuHH4PvouLH1RkV1D762sGJ/oOj+5at/NJp72Z69Om5vIOciZeM08G5f7jPZfkDlHkA+XYygPxtbVFZNDVCEffi0JMq8e9YGhMYYUXiiTgZtvPVNWRNXmoMOCIk2IaKLCaNmREhWanawe33dJznIzaqSSa3cCxff2w8TZ3WGj78eaQfKUFZYiw3f5MjAUy0lzPmz4nDWuAi88+heFBVUN55LS0Qwa3zTo32RllyKn75ME6aEUasFfP/zw/DryjRs/T3bIwC859/DMHXmp265V9159rK2DgvgV15YAK9sNgtgZmYmYmNjJRcx79Z99tlnsWTJEinad+PGjRg/fjxY8If9WLp0KQYMGODu5VN7NxQgAHRDLGqqTQFvAXDClHgMPDsa//33drcBkLlOn10yFktf24/kXTbrHzuaAkDWb+q8bojrHoDC3Gp8/vphGLjoUzUAPGt8OGY90A0Gox4r3z2OLT/mSuCnFtxhB0IGfsGhZviFGOEfbMTJo9WoLHG4fd0BQPu1iix9opJ1SjAnAOwAACjY69ckAJ66yRpQj8SB/qgsrUdpYe3/s3ce0FFUfRt/tmeTTe9AElooIfReBRXECq9YUYoNsVfE3ivyguVVUdEPQQF7B0QURHrvEAglpEBCek+2fefOZHbvzOZOZjeFJMycw2Gze++dO3dmZ377/BvKi22wEnVRYWm7hGR/3PJMZxhNWqz9+gz++DLD9V2tKyfgyGtiMfLqWOzbnIs132SgtMjKKUjCxsoJSD4PDjPghYVD8Nz0zcjP41VLstGBHnIAeOmkBMS2C8Dn8/b7BID3P98f196ytEkA8Nixb3wGwMTEG3yeo1QBFABw06ZNGDp0qGvNX3vtNRDIO3LkiLIHi9qqwVdABcAGX1J1wPoAoNlfj7ue6I19289h/Ur+oaBUAewzJBKDLo6BJciId57hZG9pAAAgAElEQVTaJepXFwAOvzIWtz7WFenHSjD/sb2oLLMzTaY0SPUbE4GLb2iD7NMVOHuyHMf3liDzGJ/UTQkASo9PzszKSqgtFwWsKoDy38cLVgGsJwCyFEmlABgUqUP3wSGI6eCPmAQzUnYVYdUX/Pe9LgAkP5pundUF/cdEYv0vWVj+7jHFAEjg7uqpHRGfGIgDO3Kx5ofTXgFgVJwZs94chKduX4+yUrfvpce8GUmh732mL66butxnuFLydBHuv8eOfu07AHa5scEUQCUmYCXHpbZp+BVQAbDh1/SCH1G4AT3/4CXY8EcGM9ULWSipOffOWb1w8dXxWLH8BJZ/fIRT0mifPw6Y9HxAANnoz268pysmTOuEPZty8N4ze+C0uU2EdDtpfVy/AB1eXjwYdrsTq5enY9OKs5xvkhJ40hs1ov3Qx9PQUcAsZY+GWw48GeliWHPjzgNlXmb1lzMB63VuszNt2qVfc+fLVLt5mH6fa6enUsTQ6WIoE7KH2ZiaA+h8gZT/J60U1Tz5XdeSw+5OCigy51ImW9LYQZl3HTa3Wuuocr+m+3N9qM9E/SWmYhs1B2aqFoVl1FimYTIfJZUz5KqHNHQUMLROLgUR4aa6IoLJ6ew5PBzjb41DTLw/3rxnF9JTS9znkaEGcufB6cQN9ybi8pvbY9+Wc5jz6E7+MqCrh0j8ROkqIcPGtcH9z/fF3m3n8OpDm0X3enqM2tLA9BkSjRvu7IqBwz9uEQAofZD56gNIxiFBIP379+eigIUtKSkJEyZMcAWBXPAPzvOwACoAnodFb+27FABw9oyLsP2fs14B4O2P9cTEKYn45M29WPnNSQ/IkwPA5z4agqg2Zrz58A6cSSsTK4CMIBAChhdf1w4kB9y/v52B0+GGRiUAKIVYFQABFQDF+QFVAOTveErzANYFgML90+50cP6AHZOD8M37xxQDIPHTfXRuX7Rpb8GMy9ZwfsJKATCxZyjeXDSKUw+fvnO9VwAY3SYAH/wwFsHBb7QIAPQmCri0tBSpqancevTt2xfz5s3DmDFjEBYWxqV5EdLALFiwgDMDf/LJJ/j0009x8OBBJCQktPZHYrM9PhUAm+2pabkTEwBwbM+usFezkz1L4YkoWbfcl4QBI2LwxJR1Lp98JQqg3qDFa18Mx38f34Xcs7xvjygwQQYASdSvoybxL0sJU+o/pwKgCoDk2lMVQE/oa2gAFBRK8tUm0cKCcEf780mjkoXP/Mw63P9Gb3z13hGcPlaiGABJ//tf6IuQcBNeun+TVwBIGr+16CL0G7ygSQDwaMpyn03AXbre5NUc161bxwGfdJs2bRoWLVrEvU3Uvzlz5nCJoJOTkzF//nwu8EPdzt8KqAB4/ta+1e5ZAMAxXbpwfnCsah9kAaQVP66dnogDO3OReqDQtT5yfnFC/+AwI4gZsjDXHRkoNfUKA9LvE4dlelMSQOExHzpFDOO14ghamWTLzLlJ+ogglDKXy1b1YFUZqS3XX82CsSJ/tX6U+ZaK2uXON2UCllUKKbOvjtVHMrYoRQxlDtZoSIAAf549ssDQZl+qkoeDiu6lTbZkDLsCc660j8gETI8tSQRN71dJRDCZD8ucy1LSSB/arMmsWkGZRT32Q+fgo9opTWtD75NbU1YaGLlIZoYfIysghOyHhkNS3SWyjRlZp8qYFUKkx03mGRRqxOR7u+PDV/eI7h2sKiH0+xOmdsY9s3/2Cq68fVAI99+jR+oBgN1u8tkH0Nv5qu3P3wqoAHj+1r7V7rk+ABga4YeC3EqRb58SACSLSef6I3+rACj2l7xQATAouhQlORYVAKk7jgqAYnBmlYirDQDJe+Q+lXfOHUUshViWP2BUOzMW/7GjSQAw5fAynxXArt1v9ng+KfUBbLUPtlZ4YCoAtsKTer4PqT4AKMydlezZA+xoxU1GzWMFgagKIL/iSgI/pCDeMhRAJzoOysLpPTGwW3WqAljzBVMBsH4AKFUTlQIgUWvXHDnSIgDQGx/A8/3MUffv2wqoAOjbuqm9ZFZAAMBLu3XzMAFLI1ZFUcAUwLGSPZPd0jAnghCJKVQu8leYPu3bJwUhpj+gjMmVZe6WS2Ujly5GSeSvRzLreppzmfWDKXMwD+KMyF/aZEu95s6diYrgZph5pe10fow+VH+uDx0trOfnZjRXoV1SBs6lRaEkL8jDBkxX9aDNtnY60lcSqWuvdJdLc1S5X7NMwxwsUO1E5mDKnMy1o/ZFRwSLzLwyufbqazam9+ORCJphcmVFK0uhSC4qmWWGljNj01VCWOXjaJMvmY/o+Ch/APpYpWZsVo5AqRmbbscyB5OxVx861DQAeKgeCmDSzY06R/UB2jxWQAXA5nEeWtUsVADkT6ds2hUFqVp4yHL709EqnSivoRTMWhwAOsH7+VFpeyhQrA8AhsTkI6xtAcoKA5B9IraRAJD3MVQBUL4UnAqAfKWXJgPAg0t9NwH3mKwCYKt6Ktd+MCoAXgAnuakPUQVAFQCFa84jv1+tCqATsb1t8Au2o+SsASVn9XCALzHGgXQ9FEBTQAWiO+YgNz0C5UWWBgFAp60alggrLFFWkj8EmbvNXPogFQBVABSu2eagAB454DsAdkuerAaBNPWD8zzsTwXA87DorX2XKgCqAOgdABLI06L9sHKExFnhsAHH14egoog3/dYHAEn/uOQ0ZB6Jg8OuqzcA6ox2dBicB5PFgYoiHY6tscBh5ZVLFQBVAGxWALj/K58VwG49b/F4TKlBIK3vya0CYOs7p+f9iAQAHJeUxOXik6Z6oSfICvag+0jzAIrGY+T3I/tQEvgh5z+noU2pjPQuZD+sih9y6W9Yfn8e86HTsNA+kgzTMJkPPQZzbhKzsZL6vwap76NRD70fENkTMAZquNc6I5C+WQ9rOQ9FHgog7fdHp4vxM0CjdaLTqGLojA4uYCNrfyCqSvXQiczBBtfloze7fQM9QJFKERPb4Riy0zvB6dBx1SbojU67Qvv22Soo375KKw+iRjuiE4thCqyGTufEiU2hqHRnK4Kjph0Hg9L0LpRvn9NqQ8IoB0j9aWupA7ZKID8VqCzQwFHtrkZir3bPwcrwv+P2xUjDQvvISf3VaHMsM42M1NeQVW+XaifdD6tiiFwaGKYfoyQtjZOROobep7TyC8sHUDRPSa4gVpJouZrBLH9AcmyrDhxoVPOqcP89Uk8AVINAzvujtNEnoAJgoy/xhbcDFQA9FUC5VDasoAspzNFpbuQSU3sNgBogqqMBUd31KMqw49xBNySJxqoFAMkcA2KAjuM0CE4Ap96VZGm4f6VnNSjL08NeTfn2yQAgD1kEjJwIjHUgplspCjP9kJ8e7KrQovM7HwBYjZA25YjoWIL8dAtyj5lgtNhRVaIXgZ4cAJKFCYh0whLtQECUHUHtnNCbgPI84NTfQOEJcvTKATAwVoO4wXqcO2xHzjEbt+5kE8GTDJipACjOCagCoPs5VVJSDqIAFhUVISgo6MJ7gF1AR6wC4AV0spvqUBsCAMdcHY9dG7JRUmT1qAWsRAHsNSQchbnVyDheyh02K/kzSwFslxiAyLb+2LM+j+/vpQIY3taEfpeE4+8vz/LqkUyC59oAMKGXP3pdGoQ1H+fCWskDmRwAWiJ06HNVIA78UYqIeBPC2xsQ0cGAw3+U48zBGgWLPoYaBTAmSY+eE80ICOejZm1VTjjcJW2Rc8CBIz/zdFGbAihcU1qjBqGdgcA2QOFpHQJjnbDEOuEfAez/2gg4axTBOgBQGE/np4NW70B01zKU5ZtRlu/Hr4EPABgYlofSojDAqfVJAdQ4KxDdtRg5R4NgrdTDTkf+UkqfHAB2uqSCU/xKz2pRkuGEX6gTcAJndzpE5QdZCmD0QKDTpbziyYWcaACDmV9Ta7kTKX9UIW2LDVaqNjGtABqDgFEzg5CXZkP+KSuyT1QjcZQZJ7ZUIPu4O3k6K5qW7Gf0neHIOFyJY5tLUS2KVnZfMHIKYJ+xISg4W40Te0tFqiUZm6liUipfbCczwmJM2PtvPr8OXiqAJIFz90Eh2LjiDNefVTGEzgnItaP2Q2oI/76UL1HpiwI46OJoPDd/daPClXD/PbzvS59NwN173dqoc2yqZ5G6H/kVUAFQvUIafAWEG9AVvZOhcWh8MgG/vfQi/HfWDuSerRT1l4KQKBqWApzZH/THtx+k4tQRvki8yNQsYz4l7fQGDR55vzd+/TQNx/YU8+DBMAdLPyPt2idbMOGBOPzx2Rmk7uT3LwVAKfQZTBoMmhCG3DQr+l8VAmuVAzt/LUTmIaqySS3RvUZ/DfpcGYRuowOg02tQeMaK3BM25J2ycmOVZztdue9YEcUaHRCdaERkdx0KTjlw7oDbDMlSE7k1rbVCh1OU6oU230r70L599GuuHRX4oTdTqp8/9TrAHShC+hiov/Vm92cajbuP08nDsLDZKqpdr61l7tc2+nW5tI/7bweVEoY2IdOvOVig0r3wAMlHDtPvc+3o9DNUH6liRxTAhBEGXgFMscJWc5mwzLnkfQL5YQl67scB93+CHhqtBqd2VGDXzyUozbWLK3JITMDBbfXod2UwojoYsXtVEUz+WqRsKkVBDgWQMilqwtoacN2sBGz59Ry2r8oVnQcl1UgCw/W4b24P/O+xgyjKrebKvwmbCOYY1UNMZh1eXjIYT920CTarUwRwNPh6gB1lEv5oxcW458q/4LA7RSllyDxEgR9UH/r9Vz8bjt4DPmxUuHIB4N56AGDvW9UgkAZ/Mja/AVUAbH7npMXPSLgB3Xb5IORkVPgEgB/+eilmT/4XFeU2rwEwJMKE2f/rj2cmb3GtpTcAeOVt8fAP1OOHD9Jc/ZUA4KDLI2C3AiOvi8I3c04hL90NCnIAGBhixITH2iCmkx8yDldg648FOHO0UhY8OTDTAAl9/BASY4DJooWfRYu0XZU4e8jtO8ZM8OylIskBlsRvkFnWjQJDFQD5S8gTAD3f9wYA6ZsEKw8fDTXSmrgB0Rr0GBeAqlIHykvsqCiy4+T2ClRXueFf2kcYLyRGj75XBqPb8ECUFtjw45xM5GXw8CztIwW7gGA9rp8dj7RDpSjMsfIg6BTDk1xZuCHjo5A8LBQLn0/xGgDJ/O5+pQf+/e0MDmzJ8wkA5349Ei/cuYmzTMgda20+gES1/fCXsWgXP7dFAKD0QaQGgbT4R7PHAagA2PrO6Xk/IgEAn777YuzddM4nAPy/v8bjrnF/csfikTyaCoaQKoDEzDZ6Qjuuxud3Hx33CgAj2/qh17BwDLsyBnPv2+tSVcggdQFg20R/3PlmF5QV2bDwiWMoybeKzM4sAAyK0OO6J+Nh8NOgIMuKU3vKsW8NrzrK7deX5NEsBZDsR0lQigqA/DmxVTSEAnh+AZAFh3JJnek+cb38kDw6ECGxRk4J/PWdLGQdrawTALlrzajB5Ofao13XAPy2IB27/swXqWd11QWe8Vo3nNhfjPTUUhzaWsADNh2gIlM/eOClUejaNxRL5h6Bnar9rFQBfGnhEHzwwh6cTS/3GgDDo8x4fM4AJPf9X9MA4J4lvpuA+0xRFcDz/iRt/AmoANj4a3zB7UEAwJ++ugV//ZSO9FTeDMrBnKRcW20VP/oMjcR9L/XBq/duRfrxEg8AFFX/oGFQo8H4mxMwdHws1nx3GltX5cBRE/VJl3xj1Qgec10bTLirAw5uycdXb6fC7rZsiQBQCnNGow4z3u6CiDYmHNhYiPXf5KAwp1pRImhi1iJRoIKfnxR2WdAmB3NKKpgorUzivQlYYhqmTLkc0IqqhLijeHX+4ohePe3rxzD7GgJNou+WKYiv90s2k6mN67VeH+x6bbMVifpUVWW5/q4q5v1FyWYtocyalDmYfGajTMI2OvK3vPYKIaSPKEWMqJII5XDphQmYPghWpK1c4mWWr5+casj6TKNzwhKqQ1GOTRaKhPmYzFoM/U8E+o0N5w5jwSMpnL+usMlVBSFf9/HT4zB6Uix2r8vFl3NSuW5Mc7DEJN0hKRAzX0nG9r9ysOy9FNc+RdU+JFHAwrxjEwJw+6wk7Pw3B3/+kIYqaaQ3DZ7UazJ2YLABE6clIqKtGReNW9gkAHhot+8AmNR3SqPOUfQlVP84byugAuB5W/rWu2MBAIuKnsIzt29Axgn3g1UJAD42pz8GXhSD7xce4/5JoUgOAG+4LxFjb4jH+t8ysWzeMdciKwHAB+Ymo22nACx5MxVHdhQyAz+kADh4fCQCwwycOaui2G1C86USiAqA/ClTAVBsNmZF7XJAyoj2bSoApH3m5Myi0vkY/LToPToUwZFGrP4iUxEAkkbRCWZMey4R/hY9Xpi8E3abUzEAjrw6Fjc/3AVH9xbi7Qd3egWA/UZG4dG3+iH3bAUenLhWpDqSgeh1kPoDEo+LZRuvRmWVFcHBbzQqXAn330O7FvusACb1m9qoc2y9T7+WdWQqALas89UiZksD4O1jV3F+ccKmBACvurUjbn2gOx6etA45meVeAeDkh7sieXA4Xrp9K+xuUQF1AWBAkB4PzeuFRa8eRXZ6BQ8hjMhfKQAa9FpSEILb6lsLWAVAFQCF7wrtN9gaAdD964yHJ0F4U1IX2D9Ij1ue7Iw1yzJwbG+xYgAkeQHvf6MnzBY93rh3h1cASIKs3v95NA5sz8P/nt/jFQCSHb37zcXITC/BsIs/aVS4Eu6/BwkAWvy9fmaUlJajhwqAXq9bS+ygAmBLPGtezHn9+vV4++23sXPnTpw5cwY//vgjJk6cKDvCP//8g0cffRQHDx5EmzZt8MQTT2DmzJmK9+pKRHrgQcy65R8RFCkBwC69QnHzvd3wyj18EIc3CuCtj3bF5tVncfxAkaLUL8J8otqZUVpkRVU5lQNPIQCyoE9VAMXRvBwgqyZg0JHDvkYB01/GlqoA0segBPqkKWacWidiO/gj41iZVwAYHG7E1NndMP+x3V4BIGl8y4NdkZ1ZjtXfpnkNgLPnDsLPy1Lx5sK/VABU/DRRGzbmCqgA2Jir2wzGXrlyJTZu3Ih+/fph0qRJdQLgyZMnkZycjLvuugt333031/fee+/FsmXLuP5KNgEAX33kMuxYlyNOwSKJPq2t4ofBqMWQS2Kx8Q8+Xxed/04KhLRKR8Zq2zEAmSfKeHBkVM4QVQiRJjemK29Qn7EqlkhVPyVVQUgfJUEXXDt6DrWkgZG24eZDHQOzwodMFLDIv5BOmaPjcwUKm5bK6SeKCKajgCU+gFpRVQ+daywdleqFOwZG6heDxZ3exRjE5wYUNr/AKNfrwMAertcGg9sH0GoV+wCWlBx0tassyXG9ri7mo7DJZi2lpGSJD6CdCggRvZb6h4lyB9K+ghIfQCr1C50SxmaXic6lTMDMqh6SKhqshNFyPoAiUy+jMomvlUBY5mpWahVyXkTQSK+BxP+OvkYEX0Fyn0ivyRFKPmcdm/SzdokWaKDBqaPFHnkARX6EtfgDDh/XFutWnsave/c2DQDu/MJ3BbD/NDUIRHR3aZ1/qADYOs9rrUdFzKB1KYCzZ8/GL7/8gsOHD7vGIOrf3r17sXnzZkWrJQDglb168aXgaBBTAIAcAOi0LpOQNwBIT1AFQHaZOhosyZqxoc8NaXoVALnLiw4CUQGQ7YPIrRXDP1GuNB1LDaQBq74AyIEdFeyhFABJkmhyOyNdpfkC6wJA7seE3d50ALijHgA4YJrHvV5NA6Po8deiGqkA2KJOV/0mqwQAR40ahb59++Ldd9917YxA4w033IDy8nIYDO6kukKDqqoqkH/CRgAwLi4O9QFAVrUPsg9W8mepqVgFQBUAyfWiKoBitUwAEeH7SkfQXigKYH0AUFi35g6AB3Ys8lkBTB4wXVUA6/e4bRG9VQBsEaepYSapBAC7dOmC6dOn4+mnn3btdNOmTRg+fDiysrIQGxvrMZkXX3wRL730ksf7V/fuzSmAtaV6ERrTkMaCPjmwE5lzJYmK6wr84JVGt8LFwSVDrZQrBafEB1Baco5V/9ejZFwt5ds4xY5hDuaOifGZLz6JYmVQYgKmzLtag/sz2hzsUeFDqQmYrgTi7zb7GgLZJmCThU8rQraAgETXaz+/GNfrykq+NJ+wlZW5I8WrSvmyf2QTmYBLpCZgKmUJXQmENgf7agK2uk29tK+gUhOwkpJq5PhYyhzLhEz6sEBRLncg6zOpAqjEB5CGU24+DFMvKyWM9LhJQIiw0cctVRqZyp4kXQwNhKw+RAH8affuJjEBH9heDwAcOL1R5+jxsFDfOC8roALgeVn287NTpQB422234amnnnJNkvgBjhgxggsiiYlxP0yFBiwFUAVANxSpAMhfLYp9AFUAFAWLqAAIqACo7LkhuOCoAKhsvS7kVioAXkBnXwkA+mICli6hcANSAVAFQFUB5L8dDqVBIKoCqKgqiKoAsh9cLgDc9n++m4AH3aYqgBcAG6gAeAGcZOEQlQAgCQL59ddfcejQIdfK3HPPPdizZ4/XQSANBYBS9YxlNvZIMUOZd1mRvxppNKyC1C9ydX2VmIPJwiqNAqYDYFgVPpSqi/UtBecRBKLABEwrfuS46TQwOrO7+odWEi1MJ4IWRQQHuH1QDRZxJRAjVRnEaIpwXb86nbtCiN3uTkpOGlRX5braVVPVP6yldCUQKpElMT1Spl66EghtsrVXuCN9OViho3spGPRIA+MDAPpSC7i+JmASDFGb+dTXKGAlJmA5szGtDjrpCGVJ9LOoRi8VoMIy2XLwzjrWZm4C3r/VdwDsOVgFwAsBDVQAbOVnubS0FKmpfLkkEtwxb948jBkzBmFhYYiPj+dMvZmZmVi8eDHXRkgDQ1LAkFQwJPKXRAH7kgZGBUC3Aujh28dIN+MBc4xUNr74AKoASPzYVAAk33MVANnl4+SCO0Tr1twBcMvnPiuAPYfcriqArZwNyOGpANjKT/K6des44JNu06ZNw6JFi7iAj1OnToG0EzaSCPqRRx5xJYImqqAviaDrA4CR0WaUlVhRVWEXqWVkjkoUQEuwAVqNFmUlvBLjrQJoMGkRFGJE4Tne4Z+l7Ml9FtvRHzmn+HxyvgBgm65+yDlW5U6HQ+fkUxAEEtFBD2u5BmW5fGCBtwAYHKeBOUiH3CO82qNEATRanLBZ9eTOAku0E0FxGpzdR5Q+Db8OdI7AWhXAmn35GaHRORAUVYmqSn9YK3nlT++DAqjXk7QdAdwcfAFAe3k1gmNLUHIuAHarrkYBJPPUQKkCGJpQhepyDUrOaGEvt8MQ4IS1jJiG3UEfnNrEUAD9Y50wBAD5x5ywWsW5A5UogE6dHTHdDcjcy6uZvgBgdKIBWUf469kXBTC0jQEFZ6v50m0SZU6JAmj014BU4ygt5L/TouOmxmMpgEY/LfwsOtd3mhUsIgeAEW1NOHu63GMNuHPHCEqh3w+LNeHjXzc2KlwJJuD99QTA9PR0BAUFuZ4LJpMJ5J+6tZ4VUAGw9ZzLZnMkwg3o9nFDUZJvFaVtkZppWZG/973cGxtWZmH/1jwRvHnAHAVFdNTv+FviYbc68dd3fI1RUUJlhqpGg1rfMeHo3DsI3797yicA7DYkCEOujsCS508BTnE6Fu4YGKZmAdJ6jQtC91EW/P52DipLeEhgpb8R+mi0gN6ogV+ADr0nBCCkjR47lpahIJ0HhroAMLqnDsYADQwmDdr018FWAWRsduDcQQYAUomg9RYtEkY6ERDjRFWRFkFxDlQWalCUocfZ/YTAeACkk0eLYNBPD63egbZ9SlFw2g+hCdUIiKhGaa4RBRkhsFbwAEibjfX+4pREeipaWEdFG0fGHEJ+Xjc4nXo4bGLgslPmWFu5O7qXzvXntFYjPKEIgVEVqCo1cPOzRFbh3PEAVBW4v3Z2OiKYMvmSFqHxVQjtaIclyo7SsySRHM/EJ/7UoLqEXxsOIhiJoP3bOJEwSgtLrAZn9thRlO6AJUqDk//YYWckiabNonqLAwMnW6DTA3t+LEduWjV3rqvLxDDGigIm19bY+8NRXmjHv0vyYaVAlQWTUigaMz0SlWUOrF+e4xMADroiAqHRJqz4LJ1fK0qBYyWFptsk9g7G8GtisPAlPscpDWasiGB6P4EhBjz1wUA8OXmjR3/yBg3FtcEgWcM3vhyODp3nNwkA7tvsuwLYa+jtHs8TNQ9gs3nENthEVABssKVUBxJWQADAj17/D/7+Id0nALzu7kQU5VXjL9KfAjYOIqi/aaihAfD6+zohI7UMW//kqzt4C4DTn0/E5t9zcGxXMQ8eDGCr7bOAYB1ue6Mzvn49DflZPFTQFTm4Y6hlPAJv/hYDel8WhJjOJqx4Nwd2viwxt8kBIFmSYdODuSS1kR0NOLymHKkbKqHT0ImcqdfU/smDqcdVfmg/0gBbpRMZ2+zI2mVHWY5TkiC69kogIR2BzlcApiDA6QBO/KVDwQkt7NUaSH37WAAYEA3EDyyGyeJAeYEe+ekBKMk2wWHXQuwP6PYbbCoAdPnzaZwICK1EUEwJgqKqYLdqkL7TgpKzvCoiB4BCVQ+NzglLuBWdxtpg8AdsVcDp9Rpk7yMQqGECoBAFbAwEonoBcUP08AvR4NxhO/Z+U8XBOtlYACe8H5tsQK8J/sg9YUVwrA5r3y9CZblbUZRLAwONA6OmhcNk0WL1ghxOTSvJtTHVRClkaQxOTH+rI359PxMZR/lqPcKmRAH0D9bhnrnd8fZd+7jrzFsAjG3vj0n3d8Q7j+7jdustAHZKDsbV0zpg3uN8CTmpUlgXAHbvG4bLbkzA0Is/bhoA3PSZzybgXsPuUPMAiq7Q1vmHCoCt87ye16MSAHDnxpl486EdPgHgqKvaIa6TBcveP+oTAN72dDds//scDm3jJRpvANA/UIeH30/GnDv3w2Hn1S+lAEhqk468LhLpKeXYucItDykBwGHXh6HTQAsKs6z48+NzsFU72aXgJFX1z+YAACAASURBVCbgwZMD0Xk4MZU68Od/C1F8thbVrxYTst4P6DHBD0HRWlSXA9WlTqT+YUN1jaucbB5Aow5aPRDYjih7Wg4+iapVWaxzqVpKADAgwoaYnlVwOjQcVFUU6VGQSQI3eGWs2QBgzbfKHFyCwMgq6PQOaHUOFKSZUJhhgp3K/UcHfXCwUO2GLI3DCkusk1MBOZOvEyg7B9gq6gZAbiyNHZ3H6eEfroEhQANrhROHfq5GRb6zTgAk/Q1mDcY8EoigKD3OHbfir/fzYa+Jc5EDQAF4Bk4KRvt+/hz8/fbfbMUASHLgxffwx9jbYvHL/9KRk1YJR82yKAFA0uaOV7rg76/P4OSBEq8BMDDUgPvmJOPVO3b6BIBDx8WgQ/cgfPlOik8AeNusHkg5kI+HXvq5aQBwYz0AcPgdjTrH8/qAUnfuWgEVANWLocFXQADAY4cfwtY12fh1yQnXPpSagLv2CcMVt7THkv8eQeE5d0QmGaguBTAgSI/bn03Cb4vScDqlhPOhUwqA8V0s6DcmgvM1+mXBade8lQCg2aLDAx92Q3mxHV88exxVpe5IyboAkPhH3fxKHLffDUvzsH9NiSe40tBHve4/MQhRnY3IOW7FuePVyD9ph7VSMNvWrQBykKUgKEVxKTi6RrC0FjD1mdQETF+INDjWDwAdiIw5goL8rnA4DD6ZgKURvUy/PxkTMA2AdLQw/T4Hdz7UAlbiA0iDHYH24HZaRHYyIKKTAdYKBzYtLoLDxlYQacWrTXcTLnswCnqDBqs/ykHKFv5aJZvUt49WyQgAEveCax5qh4QeAfjmzTSkHeSVQKUAOGBcBBL7BGH3ujwc2lpY635Zvn06gwYvfTUQr9y2g/MN9kYBDI00YfSEdigurMaf3/L3BW8UwJGXt8VN93bFY5PX4Yu/tjQqXAn3370bFvqsAPYecWejzrHBHzrqgD6tgAqAPi2b2kluBYQb0JmsWYiJtWDKiJWc4zcHb5K0K3SaE+EzYpJ8/L/90KVPKFYtTcPPn7kBUjpGbeXerpgSj0tvbIf0Y6V477H9HAAqKQtHxu41LAxTnknEucxKfPZ0isvhnAZA2tRM+gif9booFBMeiMOZ4xX4Ye5plBe6/c2kQSAic65Oh4mzY2GrcmD3ymKcPeYGXla0r3A8RHUzGHXcw1vYWJVA5HwAFfWRqwVMgZ3GSFUFod7n1opOHUODIuWzx7dzgyvtz8d6zV0XdIBJzdghUdkIDC1EZbk/zmXGE7uh6NK1U8ocDV+0byD9moMVUU4/t7JH5/qTgh1tHqY/c1ZLgkDo+VCvfUkELVfWTVz5wgHiKSAFQGlFDLqPJUqLPuOD0ba7H5Y9l+H6wUG3kUISgTwCgONntgHxkd2xIg9rvuArsxA4FDYaBmnfPGidmPJcZ3TuE4S1X5/BH19m1NqHlerl+gc6YsjlMdi3IRf/91qKWEFkpIQRjqHvyEjMeCEZedmVePO+HSguqBb19zhWSZ3ht74aidj4ACyafwB3zf6+UeFKBUD1+ax0BVQAVLpSajvFKyDcgP74YTrG/acD7rh4NSrKa6JxFQAg2dEl/4nDrY92w6evHMC2NdmifdPwVBvY9RgUinteS8aKL9Kw6iveYVwpAPYfE4GbHu+EpXOO49BGt8KgBACvn5XABZ6sXJAFm9UpazamjyE43Mj5U+VlVHtGCzOifeVK4CmCOel5YOynLhOwcGJo377mBIB+llJExWWgMDcCxXmRKgDWnDAlUcByACjAZUCIjvNlzMvwjC6uDQCF62XwxDD0GhOKBQ/wpfiUACABw+gEM2bO7YatK87ht8/cCr2SsnBJg0Ix45Uk/P5FGv74Kt0rAIxNCMDLi4fg398zseitmiASmTQwUn/Aed9ehOoqO2ZPXY/lm7c3DQD+Ww8FcKSqACp+4LXghioAtuCT11ynLgDgrRcNwvzlF+PZ2zZyv5g5EFMIgH5+Osz5dgTeeWIPZ8alt7oAkKSAef3rwXhx6nZXygelADhkfBTaJwXi23dOiszGdQEgMd32GxuGPatrh8a6FEDh+ORqAdMwpgIgSSnjDgjhrq1aFECNxoG2XY4h+3QCrFVmFQAbGADJcHK1gGkzqdTM22VgIM6lV3GpYZQCINnfkKsiEdnOjB8/5CP0pXNgKYDk1vP84gFYOu8Yjuws9AoAibn7/VWj8eJtW3AmjU8D41EzmEoDUxsAzn9yF06kFOC7nTubBAD3rP/UZxNwn1F3Neocm+uz60KblwqAF9oZb4LjFQDw2v790XtQFLLTy1BQ48enFAAJ4JCIO+JvQyIlRQBIRQHT5lh67Ovu7YifFrgfEDQw0dU/aBMr2QdRCU4eLEF1hUOsGnoRBVwbzMnlAWSlhCHj1GUC5tpQ/nvkb5YCSL8v9Un0pQ9L6dMa3OZbGso4SKPNvozX3DFQMMfuIwFAA2V6pszVEe1zkZsWzgeViC3AcFApVEQ5+KrdNnUPPz3KNCuq8MEw33KwwDA1OyQ5/VjmYRYgkbFZap4vfcSmYfFisQJEROqbJL8fa26+5AGk+ySPCMW+f/NrBUBWVRDS+LIpcVj3QyYqSu2i2sIsf0Aa9CbN7ISvPzjq2qc3ADh8fBtsXJUFq83WdAD4Tz0A8CIVAJvgUXned6EC4Hk/Ba1vAjQAEtBgJW7mHvQUzEmVPZNZV2ciaBYAmgN0XHSksCkFQBqERKqhCoAeqWxaCgBq9XY47DVQqgIg95VoKBOwh/rWRAAoVeCUJIUmfUz+WlSU8f6GNCgqAUCTnw5lZe5ckd4AoHAfalIAXPeJ7wrg6BmqAtj6Hs0eR6QC4AVwkpv6EBsKAIV5y9UCZgGgVD1TAVCsDF5ICmBNNhn+clIB8IIGQFFdX7pyB11JROrbx6gF3NoBUK0E0tRPzqbfnwqATb/mrX6PAgBe178/DHq9OOmxNKkzpayJlEKGMkgWT6k/H2s8HWUylaalYaV7YamBnIrJUAflUseI/Pnkyroxkl774gMoMvNKfDFZaWDkzMYiUy8V+auhTbuUWZY7dwzzMG3m5dtR5ly6Dx1trJckpqb+ps38cgBIlw2jq4Q4qYohHiZgymwrNhvTEcHicm20qZfu46RMw5yqRUUF033kzLlK0sBITa71VQBZpeCkqVEa0gQsBS5W6hiWD6BUNaTbKe7DKPfmMTbDH5AogN9sb5ogkN1rfVcA+46Z4fGcUiuBtL5HtwqAre+cnvcjUgGQPwUqAIpBTgVA/rpQAdAzX6CSPIAqACq7tQv3391/EwA0K+tEtSoprUDfi2eolUC8XrmW10EFwJZ3zpr9jFUAVAFQuEhpJU8FQBUAhevClyAQFQCV3fpdAPhXPQDwEtUHUNlqt+xWKgC27PPXLGffEADISnlCDpjl9yc159IRtLRJUM6cqyTwwyOlC2WmVRJNK1UHpUmh6ZNKB8nUNw2MnAmYpVbKJY8WmXMp8ysrJ6AHAFJmXg1l5uXb0SZg92uN3h1hrNHzpeJcsEknqtaKP2N+UajE0HREsLMmcTnp57RJzbnu5M0iNY9hGuZVP/cYdPJnD/MybXqm+sgldWapZ3Sf82UCZs6NSrxM1oeZx482pUoCTJT0kUIjbfIXBYFIEjfT1wudjFrkQyg5BpFJuTmYgFUAbJbPx+Y0KRUAm9PZaCVzUQGQP5EsvzoVAPn1oSFPBUB+TWg/RBoaVQCUNxuLfPhk/PQuJADc9dfHCAzwwQRcVoF+l9ytRgG3kuex3GGoAHgBnOSmPkQVABsIADWAjopg8FYBJCX1dFqdK/LVFwXQaHKXmZPmTFSiAGrNGjjtbjVO1EeJAqhxQsupi/wY508BJOHD/BxEgR9WtxrolFEAnQ6bax18UQAdWoer3J+03JpSBZCUe3PWCJE+BYE47K5rSWkQiKoAAvRaWe02fLOtaYJAdq2pBwBeqgJgUz83z8f+VAA8H6veyvcpAOC9E0ah4GyVT1HAE2/vhLOny7FjbY4o6peDAJncgcLSdh8Yik49grBqMV8KzlsTcHCEAVfdFY/lb53k+ssFdNRqNtYA017tiOWvnObKw0nNxqJ8g4wo4CsejsL2HwqRn86X2fIWAAfcaEFJtgPH/+UzaXsLgPHD9YjorMO+L/mkyN4CoH+kE10nOHDgGz1slTw8eQuAMT0r4bBpkZvq5zMAJgzIR/qeEG4cj02BCdg/pBKRXatwamMAB4HeA6ATSddWI3O7FgUntPAFAOPHaGAK0uDIzzZYJcmjlQBgSIIWPa8yY/1HJR41f1lRxLSqpjdpcPnjEfj1rWzYqpwiqBElj5Yx0054rA1Wf3YWpfk2UR5Cck6UmHMvujEap4+UIXV3MXcalfShj6HPqHCERBiw9rssrr+3JuDoODMmzuiIj549wPf30gRsNGnxyNw+6DXgg0ZV14T7764/F8DigwJYShTAsTMbdY6t/BHYYg5PBcAWc6pazkSFG9Da3+/EwlcPMpM9c0BAwxz1OnlwBC69rh3em71PFgBZUBSXaME1d7bHR08e9ABAkW+gJC2N8Fl0gh+uvjsenz3D1yqVA8DaPovt5IeLp8Rg+ct8vVJvAbB9XzN6jwvCb3NyXCfeGwDsdqkZsd2N2LCgBES4qRMAa1LjENVQCy0SxxkQnqjF3sU2WPnKV7J1ikVJoQ0aBLYBulwDpK7Wojid8uejU7XQfn6SlC7EJGwOs6PT6AqkrLTAbq1FAdSJ/fw0lN8f/brr2HwcWxcCh9UTAJ0UAIpe290JA502GzpfWo784wbknzTCQfsH0qof5b/npJRBsnbGADu6X2tHxlYtcvY4AY0TcGpEJl/SjoZDEaBoHOgxSQ+tAdiztApOB7h/UhCyU1Ai9QHsOykARosGWxeXwk5VQFECgGQ/A68PgrXSgR0/FfkEgKNujUB+ZjX2/lUogjePY2D4/Y27rQ3OnCjHnrV8BRDaN09U/YPO20eNdfUd8TiXWYHNK/ja4qw0MFKwE/Yz4Y4OqKywY+VXaXx/CeyyxhPaXTOtIwz+GkyYsqRR4coFgKvrAYDjVABsOU9c32eqAqDva6f2ZKyAcAM6sOsB/PjpcRzb666PKy0Fx8zVp9fi9aVD8db9O1GcxytgwkYrgCwoIr+2n13UHy9O3sF1Y5V/o8ci7QQAjOsWgDE3xGLJK8c94EcO5oTPRt4QySkl237lH1aKAVCvA2GxG15ug9ULzqEw3V2STAkARiUa4B+sR/J4f6yZXwhHlRuSZBXAGgBMvtYErVYDc4gGu7+sgkaooKEQAEM7AaGdNAjvCqT8BJTlScq1KQBAjc7JmXq7XVmOzF0mlGYb3OeeDgJpMgC0w2hxIHFsGVJWBsBWSXz1+HUVmX1lAJD49hkDnOg+yY78FMBuBTK3KAdADtI0QJcrdLDEaFBR4MSB76s5CBQpgDIASPoPvyMQxdl2ZB2sQk4q/71SCoBakwOTXozFb3OyUZhrc5mDlSqA7ZL80P/yMPzwdoZPADj6pmiUFtqwdcU5nwDwrpe7YfVX6Th1mK8t7g0Akh9Gr3w1BG8/sMtV1tIbAAwOM+Klz4di9i3/4tM/N6gAqD49m8UKqADYLE5D65qEAIAvzLwMUx/sgd3/5uCXL05wB6kUAEm7/9zVEZXlduzfnIesk2VeASBp/Oz/9cP7jx1AaRF50LnVHyUKYOc+geg/NhLfzK3bBCxVAC2helz3RBxWfHgGeZl86SilANh1cCDa9/PnlJb1i/NF6mldAEjc/Sa8FAFirvtzXiFKsu1M5VJqziXJscM66jB0ppkrobd1QSVKs52ygSyidTRqQR6SfWcA/uEanFoLZG0DNEbvATCkvQ0xvWyoLNYibaMZWiraV+QD2IQASM4hMQOHtreiOFOPrD0mrwGQdAhOcKD7RN6fb/dCoLJAXJqEpQAKkGbwB/rdYUBgjBaHf6tG2gabcgAkP3BMGox9Ihh+QVqsfC0fZfkOxQBIQK/7RRYQdTrjcCX2rOJNsUoB0Klx4O7/dcayl9KQlyUu8K0kD+CwCZHcNbb+e17B80YB1Oo0eOb/+mDOjD3cPcUbAAyNMqF9t0CMuDIW78za67oPKQXA0de0RdKAMJw8UowfFx3D8m3bmgYA//jIdxPwZfc06hxb1xOv5R6NCoAt99w125kLAPj+8xMx87neHIA9MnE9D4DSSiAMfz6jUYtbHu2KQZdGY8WSNO6fsElrBrvep8bq2i8Ek+7rCIfDiXn373c5v0vnUFtKFwJw1z/SAWaLHn8uycKJvSUiv8O6FMCbn09AbGczVn96Foc38g9JpQA4emoEki8OwokdZfjzk3PQOijzKe0rWEv1kQ6D/DB8egiKs23YurQEuSdsIr89WQVQr8XIR/xh8NPg5D9WpG+3wWGVj2QWAaBei7ZDgA6XanDukAYZG4GKPEAjUwmETuOioZTBDmOqEdnVgcLTWhz/ywSQ6IWaTUOletFIABDU+RdeRiRWISa5kjPdZu31J9Qg+t6I/qT+cNImYM5c6kTb/tWI6WlFeb4Gh37goytZ1UPoNDJcuxpTscHfiTb9nYjpB+QfBY784A4i4aCGUhFrTeOiASKSgE5jDPAP02L93AqUF1EVSCizZG39A8K1GHCzBUQpPrK2HLt/KANtNmbV1OWOweFAv2uC0f+aYJxNrcSPr5/l1kDkiyfjA9i2ux/G3RUDs0WHd25PEZ2HugAwPNaEy+9sCz+LDqu/yELawVKvfABvfbIzug0IwfcfnMTOv3P5eVNqKUsNJO16DA7F3S/1wPGDRVj48iEU5/M/6uRKwdGfPfhWb/QeGok/vknD4vmHsHTLlkaFK+H+u3OV7wDYf7wKgM32AduAE1MBsAEXUx2KXwHhBjR56GDc92IfDBvXBo9f9y/ysisVAyABxQEXR+GOZ5Pw9/cZ+O5D3hTLAZyC8nHB4UbOBFxebMPLU3cxfQ1ZOf0eX9gTQeEGzLvrIEryrV4B4LTXOyAizoQlT5/yWgG8+ZV2HO/8NjcbZYV2EcCJ8gXWAoDjnwhD1qFqHP6zwhUxSkOaHADGJhtgCtQiY4cVGielllJl86RrRY9tCNQi4SINsrY7UVVE5e3zFgA1TvSdWoWyHB1OrDPCYdWAhkNvATCsYxXiB1UgN9WIjJ0B9QBA4kdQA4HJVuxb7ofqUq3XAMhBntUBouS1GQTk7HegjBe0uK1OAKQUt6juOviFaHByIw8kHJTUAYBCu/hBRiRf7o+VbxagstTtZlAXAOqMGlx6TwQIzH1+/2nYqp2KAVBnAqa/1QFBEQa8ddMh0e2yLgAkyt/DC5IQHGHEW9P2c99rb4JAbnu+C5IGh+LjZw7j6O4ibt9KAXDgJZGY9mQ3/Pl1On742H0fUgqA7/46CjmZFZj3+C4UFFQ2HQCu/NBnBbD/5fc2KqSqz8rmsQIqADaP89CqZiEA4E2DBsFk1OOOp5JxYFsetv2V7RUAkkW56aFEGP10WDLHrRgoAUDSd9K9HUGCQd5//KDXADjp4fbcw+aL51O5c0P7CtalABIATNlajO2/FrjOqxIF0OSvxYRZsfj9nWxUlvDKEA1ZcgBITHqmAC2KzthA1zpWCoD02EqTWUsVQOFg+bQt/OatAmiJcSAkwY6sXUYuSIIbgx7PSwVQ7+dA8sRiHF9vQckZQ/0AsOaYwjpUg/gp5h4x+AyALmCjFD/ynjcAKIzBUuBkE0E7HPAL1MBk0SI/ww2QdQEg2SdxNbjoznAcXFuCrCOVigGQjN2+VwCuezLOawAk+x07NRaJ/YLwwUNHeIBj5Pur7f2JMxPQtlMAdy9wrZtCBXDUhFj0uygS7zy2F3Y6UbdETabhW4DD6Hb+uO2pJMyftRsVZTZU22wqALaqp13LPhgVAFv2+WuWs6cB0KjXQ6fTIj4xEGlHS7wGQL1Bi3E3x2MlwwQsAiSJeTk40oTLp8bh6/knRPsVpWCR9BE+63dpOOc1uOsvzyAOaeCI1Afwsrti8efnZ0RKmhIADAjVwVENVFe4zZQsAFQS0EEuDrqSiGielLLnAZqMyiY0WHJjM0zSImCTKoA0zIle87CnMzphr9ZApPTR7ehIXwUmYDJm4rhypK4xw+nwrA6iyARMRQoLkCbM00lF04qrh4hNuyJTMZ07UAKALGhjmWnJfETVKegIWgpwPEqvUQcuFzlM32BowLE7HQiONqDwrNUrACTjXTYjBisW8KlYaoNYeq60n19kggn9x4bj908yuG5Kkj8LY110bSyyTpQhpUb9484jAyDpc0DaDb8ymvNDLsytFvkdKlEAo+P8kX+uElUVvJm+KQFwxwrfFcABV9yr1gJulk/Xhp2UCoANu57qaJQJmCiABABZih1ZLFEUMMO0SyDQTqXeYClhUv9CEvlLfIfyzlR5DYAhUUZUlztQWcbfuGnYqQsAiRJXVeZQnDqGpb55gFktZl9pG26utNlWIcyxQFoOGhsDAIUvUEMCIEknU5Hv9iOkv6S+AqAwxoUKgCxQlQZG1GbaJd+P8hK32ZmsJcsETAMgaRPT3oyzpyq8BkDhPkBDm1IA1GidrvsPqywcB6QMoKT32aQA+PsHPpuAB1x5n8ez7IUXXsCLL76oPuNa0QqoANiKTmZzORSpAlhfAJQClzcAKKwJq8avFBpZ6qA3ACjsU2nuQBUAiZlXktOPNvXWUwGU+16oACj2hZMzGyvxL1QCgFLg8wYA6XPpjQIo9PMFAOljalEA+Fs9APCq+1QFsLk8UBtxHioANuLiXqhDu4JAhgzhFUBGsmdOAWSofqxqHx6qoczYSnL/+QKAUnMuyz+wIQBQZMJlBGR4VOhgmGbrC5qyvo/0eaDhTWICppU9ka+gNBE0Zd4VRfvSJmCJ+R6iz5R9+0QASCeFpj+QmoBFEcJ0wmi32Zc2+ZKZiJRCygTsoEzIHAjRpllGQmSpOdcXMBMlmVYYOCIyQzPm2RAAKFX9hDPpcdysOdDR3BI/PVHCaAWKHafsUWOwYFCunVQB/HLz5kYNsBDuv9t//Z/PCuDAq+9v1Dkq+3aqrRp7BVQAbOwVvgDHVwGQP+kqAHoGgagAyEcBuxQpFQC5pWD5/bFMw1LgYgWE0DBJ+qgAWPcDiZSCUwGw7nVqDS1UAGwNZ7GZHYMKgCoACpekNApYBUAVAKXApwJgw97AXQrgL+/7rgBe84CqADbsaWmWo6kA2CxPS8uelAqAKgCqAChJ8ExHC6sKoGwpONUEXL/7v3D/3faz7wA4aIIKgPU7Cy2jtwqALeM8tahZni8AlKYpYfkeimoJU/5yZJFZ/nysIBK5Pg1tAhYFv1D+gHJ+jKw5yCV1ZvkKeuyH4ZNI+y3SKWG4tRL59lH5AqVl3ejAD7rCB91OktVFQ/kA0lVBZL88tL8Y7etHFQyhq4KQsWhAofP2eVYPce9Z9BmV+oX2+ZMqYaxExb74AHqkgWH4F4pSylBpZDiTK93nPPgAStOusMzGIjOvNFcf7c/HSIXjkd6lhfoAbvvpPZ8VwEETH1QVwBb11PVtsioA+rZuLa7Xhx9+iLfffhtnzpxBjx498M4772DkyJG1HseiRYtw2223eXxWUVEBPz+/Oo9dBcDGUQBVABQDJFQA5C40JUEgKgDy30lWyTcWbHv0oSBY6l/IChY5X0Eg236sBwD+RwXAOh90raCBCoCt4CTWdQhff/01pkyZAgKBw4cPx8cff4yFCxfi0KFDiI+P9+hOAPChhx5CSoq4XmdMTExdu+I+FwDw/mtGozTf5lMUcK9hEVzW/UPbC0SRwmR8lrJHK4DhMSZ07RuCLatyuDnRfZQogFy1g0mxWP8dX6fLFwWw39gwHN1WgooSu+JawLQyl9DbjMoiB3LT+EoN3gJgSBs9wtoakLaziusvp0jWlnBaqwe6jjXh6B9WjzXgxlOgALYdqkXeUaCKr77ltQLoH+GEOQzIP8arhaKIYIUAGNPbhuwDOjjtnomg6drAToYCGBBlh94EFJ7i5+CtAkjWsd0wIG0tLyvSqqFSBTBuqA45h+2oKBCXXuMARUEUb2iCFkZ/LbIO8tcSK7iCpQD6B2vRrqcfjqwv5fv7oAAOvCYUW37K89i/dD4sE3DfS8NwbFcxivP469FbBbDbgGBUVthx4kAJ11+URoZRFYRuF9HGD8lDwvD3d3wiam8B0GjS4vKpCZgwdXGjqmsuE7AKgPxNR92YK6AC4AVwcQwePBj9+vXDRx995Dra7t27Y+LEiXjjjTc8VoAA4MMPP4zCwkKfVke4AR3c/QDen70P1RVufyipGZFlboxLDMSMF5Pw5sxdqCoX+1MxTbuUOdcvQIcnFvTGvPv2c0lnWfn9PJJHU+bGRz7qgf97LpWrBewLAE5+oT3+WpSN3PQqDwBUkjrmsvuikLK+FBkHK7nzoNQ0q68Bs0E3B6Iw047UDXx/VlUQ6dgCDHYcZURQrA77vvUESK4PI8m0ME+/UKDv7XrseN8OB//MlpR1cwMZHRzCtav5KGG0E9ZyDc7srDEX0wxHm3wl5nuujEvN1meaFfuX62GvqgUAqUtL9ECnYDCorRPthjpw6Fs+mbQopYvIVOweTGo27jlFg4xNDuSnOEXwJJc2hQaUdkN0CI3XYs/yKhHwkfmwUrrQgBQSr0P/6y1YPZf/TougkQE/dH8/ixbXPB2N5U9mcv2ZFUsoGOXWigLFmQs64YMZx7j+cookCwAf/qQ7PnokBRWlfHJ2FgDWpvKR6+mh93tg+bzjyEwt59dAZP6nIrNrMRuT/g+83RMbV57F9jX8j0rZcydJMUP6z3ypJ06fKMakO75sEgDc+sO7PpuAB1/7UKPO0acHi9oJzz33HGbOnIm2bds2yGqoANggy9h8B6muroa/vz++/fZb/Oc//3FNlCh8e/bswT///OMxeQKAd955J3eREdNInz598Morr6Bv3761HmhVVRXIoTKIqAAAIABJREFUP2EjABgXF4elH96MpD7h+Oi5/dDqNFw5JKUASCDiymkJCA43Yvl8vh6vsCkBQNL26tvjUVXpwJplmT4B4MT7EpB2sBT71hf4BIA3PBWPjd/l4uzxSp8A8Ja32uHn18+66gJ7A4B6Pw2ueSEcv71SAFslTyneAKDeDxj9uAWbPqhAZVFNf4m/ZF0A2H2SDqUZTmRtc1OSuK5vXQDoRN8ZwKFvtagurml7HgAQcKL/DAf2LtbCVqHxCQADYx3ofLUOuz6yw07BpVIAdGgcGPWoP3Z/VYnCDHEVDSUASBS78U+EYOuyUhSk27wGQHL93PRWLL574QxXIcdbACSK+l3vdcSH9/DfZW8BMKKdCRMfjMcns4667gPeAGC3gcEYfk00PnmGryPsLQCOvDoW3QeGYsFz7lrCSgGQ/Bi97KYEtOtkwbzZO7FkY9PkAdz6fT0AcJIKgI31VCfP3NmzZ0Ov16N///549913mbsi1rslS5a4Pk9PT8f111+PZ599tkGmpwJggyxj8x0kKyuLA7mNGzdi2LBhrom+/vrr+OKLLzzMvKTBli1bkJqaip49e3LmXHKBrlixAnv37kViYqLHwZLyQC+99JLH+5OHDMGDr/ZFVBszNq46g7U/ZngFgDq9Bk980Be7/zmHlN2FSDvCm5+UAmBIuBEPzE/GJ08fRkF2NZw1P/LlElPTylzvUWHo2CsQv3yY7hMAXvtYHHatKkD64XKvAdDkr8WNr7TF0lm84sIdN6MUnBSq/S16JPT3Q2icHju+LnP1VwqAkR0MiO6h51S4lJU10p3EhCw9D7TCag7VwhyqQbf/6Dj1z8kLNtymGAC1TvhHAp3HA/u/osq4nQ8AdAIdxzpQcgY4d1ADUc1fhQogMfv2uEWL3INOFJ1xoOxsDYRIFDNWPjvyfmwvPeIG6XFkVRUKT7sXVSkAdh7OXxN7fi5DVU2JQzILmwIFkLS79N5wHFhTgqwjlV4DoNGsxZTXE/DJQ8e5A/cWAAeMD0dwpBF/LnbXEFYKgCGRRtz4WEf8tTwLKbvcVg0lCqDJrAOpIzzs8hj898G9KMh1/9BVAoAdewTh5ge7cj+A37x/B0pKqtBUiaC3fPeOzwrgkOseVhXARnqsZ2ZmIiIiAiaTCZMnT8asWbOY4op0Cp988gnnn28wGBpkdioANsgyNt9BBADctGkThg4d6proa6+9xv2yOHLE/YuYdRTkRkdMyKNGjcJ7773n0YylAE4ZNhS3Ptgd425MwNnTZXh+6hZoNJRtTsY3j8COwajFrbO6oP/oSKxelo7f/i/NKwCMijXjplmdEB3nh3cfOshBoBxAks9okEnsF4Rr7o3Djj/ysOF73uwjbcNBTS2mUKJYjLklGmdSK7B7dQGqyylSkIE5sn9SK3XYDWEIitTjny/yUXyOV3xogJOr6jHw2iB0HGzGoT/LcPSfSpebGw2KgplYOCb6sxH3BCKikw67v67Amd1u0JCtmkLBaWwfHZIm6XHukANHf3HAxlugPY6BjtqVmoBDOgMJo8GBUtp6Dae88WtNXX5yJuCaZoFtnUi80oFTf2uRn1qLCZgajmUChtaJNgOAqGQgex+QuYU6l7QJmU71IqkeYocTHS7RIn6EFumb7Uhdya+rR8SpTHRuaHsdBt1uhsPmxMoXeT82bgxGRQsp2MV0M2LEHUE4m1KN9Z+4QUhJXV9zkBZ9rwkGMQXvXVXMqdrCJpusuWZu3UcEYeikcPz2fhbX1xsA7HNxGPpfFo4DGwqwfWUubNYaX0oFlUDI+s5e2AsGkxafv3gUmanuH0RKkkL3GhGO25/rhrQjJfj0xcMozGMDYG1l4u58LgkDL47Gga15+Oj5fSgtrcbiTZsaFa4EFxwVAKkvdzN9OXXqVA4AidhyPjYVAM/HqjfhPn0xAdc2vbvuugsZGRlYuXJlnbMXbkC3Dh0KP5MB429MwDW3dcCHz+3ngjrojRWcIQBOh6RAzHgpCSUFVrx5926uq1IF0GzWY8Zr3RDfzYLPnk/Bsd3Fsv3JhzQAXjw5FhddH4N9/+Tjp/fSXdNWUgourrs/iA9gebGNM3tpJSGrLIAjYxPIufvT9tz/3750BvkZvAqnFAAvuj0UHQaZsfvnEhz+s8I1b0UAqAGufi0EJCBi44Iyl1IlXXfpWtHH0+UKPRJG6HFyrQ2n/haDryhFDF26jSofR8YO6wYkXa9BabYT+77QwOnwDQDbDnEgfoQT+ceAlJ8pJbGWq5gFgIQzEq9ycgCYvhFIW+cDADqdiOyhQdL1OhSlObHrM/6cegOARosGQ+82IzBGhz9fL0FZHk+fSgGwTZIRF80MRnG2Hb++kutaASUAaPDT4MY32sAcqMO3L2bhXJobhJQA4KQn2yGhZwDWLsnGzpUFXgHg4KsicNltbXF0ZxGWvnbSNW+WryC9pn6BOjz/VV8U51Xjw1mHUZDjnrcSAJz8WGf0Gx2JZfOPYftf55hl4cikpAAYGmnCa0uHYMPvWfhuQSoqy+2ottmaFgD9zXXer6UNSssrcCEogJs3b+aCIl9++eUGM6l6s9i7du3ifPp+//13VzdiTSOb8P+pU6fQoUMHBAQEiIZetWoV1qxZI2rrzb6FtioA+rJqLawPCQIhvgYkCljYkpKSMGHChFqDQKSHR25sgwYN4n6lfP7553UePQ2AQi3g6Dh/DBgdhZVfnRb1rwsASePwaD/MeDkJn75wCPnZVYoBkAQzBATpcc/bSdj4Sza2rPCMCJZTtUjU3n3vdUfqnmKs+NhtilUCgATe7v0wEZkpFfj1vSzFpm9h7Kn/jUNWSiX+XshHTZJNKQBe9nA4pzj+u7CQWWuZpQBaIrW46KFAbPyoDMVnHBBFB0tq74oCaygFcMCdRhSlO3B8td0jglspAIYnAV0nAHs+ByryqXyBXiqA/pFO9J7mwPFVGuQcEKvPtV3nrvdEdYEBncmJvncQEzDEUKtUAaxRq6J6atDlKh3Wv15NXAu9AkAyN2OABkPuNiPlrypk7q6BSIUKIOmfNM4f3S/xx7ez3Iq2EgAkfXuMtWDYjWFY9HA6yovcfohKAHDg1WEYeVMkPr6fBFXZvAJAEk0//va2+OChIy4VXwpcLNN5uy7+uP3lrvh49mGcOVUhgrS6AJAYK574qA+Wv5OKk4c8I4elJmApABKzcW5WJY7sznddVk0KgN/Oh8VXALz+kUZVKet8iDRyA3LuiEWMWG+uuuqqJgfAs2fP4rrrrsP333+P6OhoJgD+/PPPePrpp3HwoNv3VGgshUVflkwFQF9WrYX1EdLALFiwgLvoiR/Bp59+yl1UCQkJIDI08RMUIoKJP9+QIUM4fz8Cc8TsS8zFxI+QgGBdW20AKPShlSLynhIAJG2IL05opBFnT1d4BYBkH2HRJvQaFYZ/vuMdr+R8AGmoITeHrgOD0D7Zgj8XnXGDmMLk0WOnxyA3oxr7/i70GgCvfSYWaz49h9JcN2EoBcDRd4Riy9Ji2KqcXgNgVFc9qkvBwR/ZvAZADdBxtB6n1vEmTun5VgqAEcmAKRDI3EpSv/gOgISy+t7lwIGvtFw0sdwmpwCSfsEJToR2BE6u8U0BFPYd1RMoPO1AZYH3AMitqdmJmCQ9Tm/3HgBJ/xG3B2HDokI4ahhOKQBCD9z4ShssfSoTDsrcrQQAozuYcNGUKCx/if8B6I0JuOeoEITFmrB2eY3jZM1CKlEAk0eEoqzIiuP7eICj+9QFgJYQA+eGkpftNnezcv1Jx2a1a0oA3PzNPJ8BcOgNj7ZqACQZMY4dO4b8/Hx07tyZA8CysjJERUVxAY1Cvtvy8nKYzWbO+kUCIklw5Pr162Gz2TBu3Dh89913zFsKCdiYMWMGduzYAavVihtuuAHkGUyscldccQXmzp3LuVbRmxTqiDpJfO8JKEo3FQDrIhH1c9cKEPVvzpw5XCLo5ORkzJ8/n/PpI9vo0aPRvn17kOhfsj3yyCP44YcfQH6lBAcHcw6q5GKjfQjllrYxAJDeHw0lGgrGPCKMKcXK6KeDtYqHGrmULrUBaVy3AGQdrd2USsZjpXQh/YhSUpgtTiMjBaPa8vPF9zLj9L4K8di0ryEjBx8Z2z9I54ocZql09BpK10Rknmbs06OP0E5D1tcNbHJR37QeJwVFcyRQQcRPpxgA6fQu9Lp7XI+UeTky2YlzBxjwJ/HVE8YRw6B7dHMEUJ5Ny37uz0SmWMmEPMy0ZDpEAZQEgShJVCzNHcg0AdPKIPVab9LAZrPDXhPfI8qHR/sgSiqBkP3G9zTj9H6xkqYEAMnl0WVoIA5v5N0wlAIgmVtMBzNyMytRVUlFE9VichWWnB5bZ9S4vveykMZICUP6iIJsGFVBmiUAfl0PALyx9QJgXl4eZ/rdunUrl+9WAEByDv/3v/9xQseyZcs4ULNYLMjJyUFISAimTZuGwMBAzJs3j7svnzhxAl27dmU+Ckme3dzcXO65SXzxR4wYwVnQSIAlEVm6devG9X311Ve5z8gmhbpJkyZx7YjPvnRTAVCOQtTPztsKNEcApGHBWwAkC8nKIygHgHJ95HwA6RMngkuFAFhXehYyfqMBoET18xUAaZdJUYAIRY1KAZAjLWnZEGGRvQRA7kFPqV/c0DWbVwBYSx/yVlMAoBTAvAFA4VgV1+tlmKe9AcDawE4OuFjmYBUAlT0SiA/g0FYMgESVGzBgAKfOTZ8+XQSAJMceSWH2zDPPYN++fZxSR9Q/shE/+F69euGBBx4QLeQTTzwB4k9IQJIUWJCWJBUak/Qt5B9RAlmbFOrImES0oaN+iXhDIoFVAFR2PautmngFVADkF1wFQLHaStaEBl85BbBhAVDmC6ACoLgiRh0KoAqAbuKvywewth8GTWkC3rT8vz6bgIfd9FirNAHv3LkTd999N7Zt28bdi6QASJQ4AnTXXHMNvvzyS8716Y8//uBOJVH+CBgSwCN5dS+//HLOPEuAjFjPiKpHrGWkL9mWLl3KpVA7fvw4ZzIuLS3F9u3bZVO+0FBH2gcFBXGp2ljp18h+hD6+POZVH0BfVk3tI7sCAgBOHTYMXBCIjJlWpMwx2smZdpWagFnl36QqEssn0RcFUFZpZB2rxL9QZB6mFEC5NDBKFEDZlC4spVESBMI6ryIfSxl/SdZac/BM7Ut0juTc+CRpYbz+mjJgkFb5pCoSbY6tLQ1IbcDEMtmStizfMVHpNYlplqXgyfmryeUbrA1cyHtKyr95E9VMnx8lOf2kqiFrvVl+ftJzx1JbnQrN8nLHypobAcBFGzY0KlwJ999NS+sBgJObHgBJoYJ169bhkksukfWt8/p7TXV45513uKAKUhyBbASyCNARU+vixYsRGhoKAokdO3bkkjUT3z0CfsTXj5hqf/nlF1H5VOJLSNykSD4/kj/3p59+wptvvonVq1dz5mXif9+jRw/O15BE85L/jUYj8xBoACSp28aPH89dK7VZO1QFsD5Xgtq30VZABUB+aVUA9AwCYZnipTc4FQDF/oEqAHr6DaoAWPst3AWAX831XQG85fFGhdTaZr527VoOyEiBArngivo8uMj4dInTRx99lPN/J7BXWVnJ+fSVlJRwwEVKpV522WW45557uFQxRDUkQEfg8ejRoxzQkUAOYhYmkcQkpy6BRRJk+fbbb+Pvv//mjoNAHwkeIaZcYlaW22ioI3BJfBFJ0EltmwqA9bkS1L6NtgIqAKoAKFxc0uAOFQDZeftUBZC/alhgpyqAym7Zwv1345e+A+DwW5seAMnREQWQBGI0FgBKV5A2ARPVjkQDE9Aj23333ccpeRs2bOCUQOJ3J5iOSXlUAngE0kiACFEASVAJCZ586623uKAPApAk0wbJnEHak4AQuqxbXVBH/BE/++wzrmKIsJFsHcQkTDYVAJV9H857KyIxkxDyC2VrLgDIMtvKmR6bygTMihz2UMJoUzFdCo5hDibXGOu4WRHBXB/GeHLmXFYfUao+mfrBLBgk86E/E7WT+RLJBoUo+PKJIn+p9lTMrwegKFGh5MBOnCabrfrJmo1pvz1GlKoUnphmY8ZY3DEwqpSwAkKkMCcXnNFYJmAPM62C6iGtxQTclABIVCqiehHzKVG6fvzxRw6A6I1koiBtyOfELErMsSNHjhS1aWoAVHBbkG2yZ88eLk0aie4lKiFRA6XH7c0+vIE6b9qy5qD6AHpzdhht9+/fL1vKhaggJKT833//5fILkSTMxG+gtW4qAPJnVs4ErAKgGPKkPokqAIp97lQA9M0EfEED4JK3fTYBD58yyysTMKkQRdKnkLx2xJ9OCoBCLloCgSQFy8cff8xFzJJUKfHx8a5HYUsDQDLxxx9/nFP/iN8gUez0er3Pj3ZvoM6btioA+nxK6u5ITjjJnUd+3QgbiRwi/gMcCGi1XGRQeHg45yRKInvIDZ1U1vjtt9/q3kELayEA4N1jR8FeJYn8lAQSsIJASPUPP38dzpwq90yiTAcIsIIpdBp06B6IU4dKPWBMqQIY1zUAGUfLuf6+BIGERRtRWWZHZZlD1J+MpwQASd1Vk58OpfmeSZVZ6hs9V50BCAzXc6W/PI5BGmzCUABD2+pRdMbOZVKRS+pMf0YrgJZIHapLnbDVVOBiJv5mXBc6E1/9giRN5r5LMt8FlgLoHwWUk8pnUilPMhZLAdRb+Cwy1TXld+l2ShRAjQ4wh4Mra0c2GuaUKoCWaA1Ksu1wOupIHs1QAE3BgL3aiaqymjmwlDCGAkjqU+sMTte1yFLsmGZaDRARb0T2ST6pshTMlCiAsZ39kHms3FXbWsna0/uJ7WhG/tkqVJTx3weWIslSAAOC9QiLMSHtCH9P8TYIRKvVoHO/IDw+92ev4Mrb279w/92w2HcAHDF1FkgiY/KsEjZiiqTNkUyo0Gg8AJBUoyJwSEymwta9e3dOLRMKEJD3WyIAent+5Np7A3XetGWeKyfrrteQR9XKxyKh38QJlNj9yS8AspGLndT64x5aWi0HeyRknPgCENmYhIcXFBTUK4S7uS6rcANK2f8QvpxzFNnpypIoi+rJ9grGlCe74rOXDyPjqLuAO7eejChV+n1ys75vbhJ+/CANqXuL2dVDpJGt1N+3vZKIXX/m4cCGQhGwyalVolrCt0ajvNiObb/meURxSSuOCOeSfr/rMAtiE834ZzFft1VJRDBpJ4BQWDsDhtwYgj/m8+XklAalCHCp1QFXvxqG354r5MDDl5x+g+4w4+Q/VuQd5x+6Sn0AhXaRSVpEJelw6Hu+bIVcEDALAIc+asD2D62wuQs61PrVYd0K2w3VwRAAnFjDHwMLAFlAYjADIx4x4+/X+B8TctG5NKPSoDjqAQt2f1+Ooky7R/JoOkCEZabtd20gCs9YkbqJ/y4ygYsBgN1HWRASo8eG5XxZM5bZV7qGwn4Skv0xaEI4vnmVrwTiLQBGJfjhxtntseDRFFRX8KvEBDgagmteh0YbcedrXfHlG6nITOXPA9PXsJYo6+BwI2a+0QPrf8rCxt/5iiTeAKAl2IC7nu+BzLQSXHrtZ00DgF/M8VkBHDHtCY/vyAsvvKDoeUW+h7QC6E09+gsdAMnxk40UZ6hr86YtayzVBFzXKiv4XIA9EgFEEkKS/D/E8XP37t38g1erBfkFRD4j7xOnUhIKPmbMGJDIp9a2CQD41kNX4c6ne+Lr94/BZnPiwJY8D4iQSwPTISkQ05/phiVvHuVqahbnV/PrqQAASbs2Hfwx7fku+Oz5FORluovAK1UAo9qZcevzHfHJ40c5FU/YlAJgeKwJk56Iw8LHjkMjQRclABiZYMTIyRH48U2+DJ23ABiTaETPcYH4+yNePvMWAEPj9egzMQD//I+XvrwFQFIQ5NLnLFj7epmr7Ji3ANjxYh0cVg3SNtQApMyXpbEAMKSjBnFDddj3FQ+h3gIg6TPsAT/sXV6J0hynTwCYPMGMkhw7Tm6q8gkAe14RAGuFE4f+5n9MeQuAw24KRV5GNQ6t9yypxhqL3s/VD7VBypZipGzxrKkrOx+nE+Q6mv5qJ2z8MQcp2/hKItI+NIxJwc4vQIe73+qGv5ZlYd8Gd11eJQAYFGaAVq/BzNd7YM3XGdjyR7Zr/0oAMHlwGApyq3D3i8lY+2MGVn59qsnSwGyoJwA2lAJIhBESvEBMxMOGDXOt3+uvv85F/ApBDcRiRkQTUpItLCyMg8iBAwe2tsdjszoeFQAb4HSQkmpCqDZJCLl8+XKcOnWKCwvnHpxaLRf9QxJHkhBxkhiSfBGI0+jJkycbYAbNawjaBzCufSDufa03Itv44cNnD+DIjhpbXs2U68oDGJcYgDtfSEJVhR2fvXQY5zIrFQMgGbvrgGBcdWc8jmwrxOolmbDbnMz6w7VB0sjrohASZcLmn88hL4uHSKUASNrd8Gw8tv6Ui9MH3SqoFOZY5mC9UYNp/03A5w+mcfv1FgDjevqh00B//Luo0GPe9FjCNSpcRYIC2HmkHwLCdNj/Kz93bwEwtL0OXccZse1Tt/TmLQD2vNmAM7scyDvKA/j5UAD1AcDAu43YNI//AeILAHa53IDKQifSNll9AsA2fQyI7mbAzmVlPgFgt4v9YTBpsHcFb770FgCvejQaW3/Mx9nj/HfAGwXQP1iHKa+2xycPpcJREwunVAEMjTWiQy8LOvS04Js5p0Q3OiUK4MU3xyKumwUn95dg3bdnRGtfFwAaTVo8+E5PkDKSv31+CnvW5zErtZCJiUz7TifCY/zw7MIBnMn5/944hJTdhWjKPIAbFr3luwI4fbbPKqVUARQAkOS1o8uJkvJm5LkoPCeb11PswpiNCoCNcJ7JL5c77riDy/8jPFzpmwOBRBIePmXKFC5qqLVtNAAGh/jh9qeS0GdEJArOVeHVO7ejvKSmCr3UJFiLPx/xA7z71SR0Sg7Ggc35WPjiYa8A0BKi51RAApLfzDuBPevyvQLAoHAD7ngrkTOBvn/fETgkAMlBCa1ISo6h65BA9Lk0FEc2l2Df3zyIKQVA0m7q2/H4+/NzyDxS6RUAGswaJPQxI6qDCdu/K+IUOG8UQKL+dR1jRsbeamTt44vGegOAwe20aNfPwPn/HV9bU3TWSxNwQLQGvW42YPciK6qK+HXzFgB1RmDQ/Qbs+sw9Buv7xjIBE6+5kU8asfdLK4oznD4BYHiiFu2HG3DyXyvOHXNf/x61gKnJ0Z/5hWow/C4Ldn5djtwTPIgKW10mYGLK7zDYjOAYPfavKuH8AL0BwNA2BhAAXPpsBqrLeRBXCoBxyWb0GhPM1cP+Z1mOa85KAXDKyx0RFe+HZa+fRPoRsStIXQBI+j34fg+UFlrx2XNHkZ1W4RUAXnZrHMi/gpwqfDD7AGeFYCWPlgIgNE48Mq8PEnuFIC2lGAtfOYSczIomBcB/P/cdAEfePrvBfAC9MQE39rOwvpkCGnt+9R3fW48+FQDru+Jqf48VEABw+oj/Z+884KMo9jj+y+Vqeu8NEnrvvSNIUYoFARELYkWfgvhQUbCg2ODZQIqCNBGwgIIiCEgXpJeEEEhI772395k5Nre3d7s3dwkhCbufTz6E3MzstN353r/212cCsbODd6AOA8b6Q6lSYMuXMTV1WLJJODgqMXC8PwZNDMDa96IQffamNb4ASsQkc50HeeCemSHISS/Dly8ZA6TwhSCEJM9ADaa83gzuvhqsfTMGNy4VSquxeTCotFdg3EtBaNHDGWf3ZuPP1Qb1kVh4Ff7fOw5zRd8HPVFWUoU1L90wtmPkg6ZgBcicOrgq8OB7/qisAPZ9nYnkqDJJ8BWGiGk7wgGd7nFE+tVyHPgyl0puTGL68e5rlJnEzg6BXVXoNtWBOi4c/qIQ5TcFoGLOIsJ1IP/vNFkN/05KJJyowMVteuiReoGb+6zlaCWCe9sj61oVBUmpS+zlGdrfHhF3qVCcU43Dn5YYJQYRlQbyb2QHdHtEA792KsQcKMXF7QaJKB/ehBDBdxDpfL8OEf11SDhTioOrDWpQYR1zYKd1VuDe+d5QaRXYtyILCedLjO3n+Pl6zQDo6Bd9EdJRhwt/5eHv9Xp7UjGvZCHQth/iihEz/JARX4qNC2NRetOUQiosDTenWkcFXlrdFuWlVdj6SRxizhiee9IHSwA4/vlQdB7sgb++T8bfP6agqtJY/S4mASSQ5+alxpyvOuL0gUzs2RSPnAz9/pMEQJ7tYf+xfght5YyDO5Jw/bJhvYgE8JuDB22WrrEcN9z79+BqAoBalipGZQqKSjDgiVdN6tlqA0gaIiZQ3bp1A/EC5i4SDWPcuHFGTiBWd7aBVCCp3t588018++23NLMICTD95ZdfUm1fQ75kAGzIq9NI+2YOALmhqNQKVFZWU4kauVgAkIMiYsvTsosbzh8xqJGNQErCw9jZTYWxTwbj+K50CnHcZQkASTniUPLQvGa4fr4A+zamMAMggSqdsz2mvReGtLhS/PJpYs19WQBQpbXDY5+GITu5HNveS7IKAMmNHnjPTw/c81Ko56Rk6jVBvMHwvlr0nOyMI9/kIeHMTdtLYVo33v4UAqB/ByV6POqIs1uKceO4AbysAcCWd6vQfLAKx74oQW7CTRWwYI2NOMvMZ54tFej6qBpXd5fj+n7pWJyiXsDaagx8VYec+Cr8u7rUegAE4BwIDJjliOi/yhC5y3oAdPSyw8h5brh+rAT/fK9X43IXS3y+oc95IKidBhtnJ6OsyFgCaARzZtrtP9UDHYe7YtMb8chM0K8lKwD2Gu+Bnvd6YuOCOKTF8sYtkW6NW4fWvV1w16P+2LQoFmlxJUZSR9IHKQB0cFFi0pxm2P71DaQnGO4rZStYM5/V1WjZxRXpicXITisD3yuYFQCJBz4BV3Lx91V9AuDfq2wHwIEzrJMAkgwbV69epeMlTpHEHp7YuBNbPhLmhQsDs3z5cqoGJqaDyN7HAAAgAElEQVRQK1eupJqw0NDQRnrSGbr9yiuv0LEQACQw2Lt3bzoPJHVcQ75kAGzIq9NI+yYFgCbAxZD/10Syx1CHTJ05ezNHFyWK8w0gwAKApC2VRoHe93jj0LY0qwCQ1PUJ02DwVF9sWRRvFQCSwj3GecAjQIU/v063GgAHTHdHWWE1Tv6ol0BYA4BBndRoM8wBfy25qXsVwDqdXwkA9G6lRKuRGhz+ooiGkOEuawAwuLcSPq3tcWqNwYHHWgmgQgkMel2DE1+XoSBFGHTF+AETVQFXVyNihAoaZzsqieS3wiQBvAlMHSZqUZJbhSt7DONhlQAS4Or6gCOFt7O/GqtCWQAwtJsWHe52wvZ30+mgjeDJggSw00gX+EVosesLngMEv45I6BlynyHTfZAYVURNIKQCRpsDs24jPRD5Ty7ys0ydbywBIPniRUIwkS+b/IsVAPl1bAFAoT0g115jAkCSg5YfBkbqOCIeqQT4hNf06dNBTJ7IRaR/H374IQ0E3b59eyxZsgTEfr6xXykpKWjdujWio6Ph7e1NhzN16lQKviTEzdy5c6kDaEREBI19SCSEDeWSAbChrEQT6kdDBkCrQIgfb5D8TohHIEmjIMSPoSesc3NdQ9o4IjHKfDgcsaDHpKrOUYl2g51xepdxQnAxL2JSh3PiaNnPEZlx5chK1EttrIll6B2uomPNjOXBsmCPirVHxuPZzB4VZUB+svEBzI/jJzVu8hmBPwKwufEGD2xrAZB0ufVYFSJ/lVb/knJSAKhyAAK7qBB7uJwNAHlQRNomIyDhYHzbqHDjpAEAhfcUy9BBZlHrbIeAdhpcPaIPY8JdLDH0oKxGl9EuOPmzHuiNYIzXV3OQ1rybA/LSK5AexwNXHgCKQTC5j39Lbc2+l/IWNgtmdkTSaNg/zHNlJgwMN1d3FACu/MBmFfDAJ/9rsw1gEzrKmIayfv16Kvnbu3dvTfm7774bDz/8MA3/RkCXQPDChQupVJDEBG4olwyADWUlmlA/miwA3lwjKS9gMSmbidetCCgKAYfUs1fZobK8mil4NB8AiQqZC8BsLQCS0Bs09h9P2ip0wJACwBpYFqaC4+1zSwBIpHfEeYV/X1sAUKmB0TyIPWpSAEjqcP1hkgCaAUB6XwI1lQagZYaam50m61JZYRzRmgUASRmyH8pL9L23BgC5/cfi+ME8HuH8iECoGLBRqBYJZi1m2yesI2UDyN8jjVYCuOJ92wFw5jyTx4TVBrAJHWVMQyEp7Y4dO0ajf5ArMzOTqrVJ5i/yd5L1i+QKJr+TRBAffPABU7v1UUgGwPqY5TvsHjIA6hdczDuYwoQVAMhtH7H2TKBRpG1rJIDcPW0GQA6WawGANeMWgUbhY1VbDz9LAMjdr1YAaCZcCH8cUhJArpzQ0YIVAI2ghg9PFiSANeNmAC4ZAPWz1RBUwAe+fh9OOhucQIpLMOipebIEkPHc3rlzJ2bMmIGTJ09S9e7jjz+O33//ncYzJLaQJNIHSRRBwt2Q/xP7x4ZyyQDYUFaiCfWjMQGgUDLHos61RQLIWkfoacsCipJj4O0rI5gTOEyIwaGYs4oJ4IpAp9S4pSSArKpisceGFQZZwiYIyxhJjngdkFKFikmbhG3zbQKN6ojY3FHYYAAzqXAzLJI9ch9RiZlE31jHzaKalYJLsTFI5QJu6hLAA8sX2Q6AT792Sz2Vm9BxR2GfQN+2bdvQrFkzTJo0iQa4vnLlCrV7dHNzoxJAki/4xx9/xOLFixvM8GUAbDBL0XQ6IgOgfi3FYFLqMxkA9XMnA6AAuGQANLHRFINGMe9gISzLAGj+zCkgEsCnX5MlgDYeySTf8e7du2kmE5L29bPPPsM333xDEz8QaSDJf9xQLhkAG8pKNKF+yAAoAyC3nWUJoH4mWCVhsgSQfa5kADR/aHDv3/3LbJcADn7mNZPGZRtAtkP6xRdfhLOzM959911aYc6cOVT617x5c6xevRpKpZKtoXooJQNgPUzynXaLhgiASr4zg4jXrpRkzhZpXm3rsPZHKpSNUZxF3ka0JRyPOQcVrkkxdS7nkWypnNDBREo9bK6tun7GpFTDYqpeMdtAIQCKQZ5JORFPWym1ppjtmbHbiHgcPyk1thhwSTldsIJvXaqApRxHKhjmVDi/jdUJZP9X79msAh787OuyBNDGlwrxACbhbyZPnmxjC/VXTQbA+pvrO+ZOMgDaLgEUQhaLTaIMgHX/aMkAaBoWRwZA9kwgDcEJZN+X79oMgEOee0O2Aaz710qDa1EGwAa3JI2/QxwAPjagP1T2+lRwYlIbsUwgGq097O3tUFJUaRp4mTEQtKOrCkV5+iCytkgAdY72KL2Z+9QWaZ69Uj9umkZNIkuJZIBmpR2tTy4WhxBhOVkCaNvzJAOgMQCSfMIVFeZj8rFKAEle5vJS0zA09BlhCAOj1tnVPI+sdfh9I8GhC/LKaVYcobRVKsMHJwFU2NtBrVPU5DK3RRKrdVVg6c97bylcce9fGQBte/bvpFoyAN5Jq11PY+VeQJdOv4C9mxNx8XgWSAq48rIqk1yuYgDYpps7HnopAjvXxuHfvRlGPbdjAECNToH/fNEBR3ak4vD2VNiTAGo3L1aYmzQ3DNmpZdi7PhmoNkAsK8x1HeGBkLYO2P5ZIuyMotmxBY/2DFLjrid88cM7CZKp3MQkgCRu3QNvBWLb28l6COXNIqsKePhznji+OReFmZUmaycWjJrfdoe7HZCfVon406a5fI3UvIK9yX3mHmyP5v01OPW9IYi22JcJse094HlHHF1ViApDRjCLTwIfHMIHalBRUo24f/RjsFYF7OJnjzYjdTi2Rp/L1hYV8NjXvbDjZhYPW8Bj5AveOLY1B9lJ0qncxMY25FFvGtA58oh+DGLlTNSnN2mr1zhPuPqo8PuKZJP6LDDXaag7zcSzYnZUzRciFmjk+tm6pyvGzgzBd+9GI+maPpC2NU4g4R1dMPGZZji+Ow37f0yi9VnWgbz3ykorEdLCCeNmNEdRcRl6DFpWPwD4eS0kgLNkCaDFl0QTKCADYBNYxIY2BA4A3545GpOfa0VoB5nJxbh4Ihun9hvDnFguX/J37yAtJjzTDEQaePyPdJrW6dS+DOOUaBLSRRd3FcY/GwqtoxI/fhYLn2Atrvybx+ydS+477vlgmgbux6U3oFTZoSjPjERSNBMIcO8LQSgrqao5+Li1EpPmCeHynv8EIDGyGKf/yGHKOELa54PVPS/74ewfuUi4VGL0dxMAFIHD0bN9cPLHXGTElZtIMVnG0GeaKxLPlyL+rD6LhFhcQeG4ue4EdFCDpKU7sUGf/kwyELTIg3D3G67Y+0keyostpIITqR8+QAO1ox0u7dJDqJh00AhIeG05eijQ/0kX7Ho/SxI8xKCEfHd56CM/bHhZD0/CkC6WwtLonBW4f0EA1s2Or5F+WaPODWylxbDHfLH+jTgakFwKnsyFaukywh0dh7hh09uxRhI8/nSb64+Diz0K8yswfJo/Qto6YvMHscjPMmR0sQSAfmE6GjS7/wRf+IbqsG1pLFJuGL5IWKof3NIRzdo6I6iFI/zCHPDjV9cRc86QGlESAKurEdLSCXdPDUF5WSUCmzvh1zWxOP5XMlYd+Lt+APCzd2xXAb8wX7YBbGgH6y3ojwyAt2BS7/QmOQB8fMAAqJVK9LrLF4/Oa4Oqymqs+ygKJ/bq85FSIBCBJ/7fO/TzxOTZERTEvn07ClEneflppdTLNz/rOtQTI6YFQutojxWvRiE1ziAKsijNswMG3u+Ldv3cqARz3YJrVBrEv6QkikRtdN8rwchMLENGQinO788xGbdUfSd3JSa/HYLNC+NRnF9VcwBLqY357bUb6Ayf5hocWJtpEwAOe9oLVw4VIvFSqU0AOPhpd1zaU4j0GP3BbS0ANu+jgbOPEue266U2twMAgzqr4B2hwqktegi1FgCJ6nPsGx746Q39lx9WlSkHGBpHBcb+1xtb3kixCQDbDnKCZ7Aaf6/LrNm2LABod9NZceo7Idj7bSoSIg3wxOLc0ba/Cwi89rrXCxsXxqIwV2+OYe4y158p85uBqJ4Lciqw/ct4lJcau7JIARxR9z7zcWv6zB/7LQ37f0hBZUW1kdROqj75svjs4rYgZiQ7VsXh719S6PtLzCGEjInfXnArJzz3fns4OCnx5+Z4/LL6Oq1PcgGv/rt+APCv/9kOgENfnG+yTLIXcNM72WUAbHprettHJATAoHAntO3hQdUgQRFO+GNjPP7Zk8YMgD7BDhj2YCDCO7nAyUWJlW9EIvZygSRI8eHS2UOFh+eFg7yUs1NLsWxOJIrz9YZ1FgEQgJObEtPfiYBngAan/szErhV6FRB3SQEcKePsocT098Ph4GyPVbNjkJ1SJmrPZ64/HYe6ot0gV8RdKMLRrfpDnBUAdU72eOidQGz/OAU5yYYDmFUC2H+aB5KjSnH9ZLFNADhyjgeOrc9DXurN+RZJLScmAWwzQkdVflf+0kP77QBArwh7RAzQ4ug3+j1nLQCSOhMXe2LrK/ovPtYCoIuPPQY+7oHt7+ufGWskgG5+Kgx42AMnd+QgKdLwxYcFAMN7OKLLSDf65WXvN2lMal9ubERa/uT/IkBAbNM7sVR9LGVXKexP17s8MGpmIEqLK/HdW9eQcs20vqi3r101Hnkrgr4vctJKsXHxNSRd1X+BELP14/fN2VOF5z9uS81WYs7n4/BvKbh6Nk+/dgzxGMPaOGPK7BZITyxGfHQBos/lIOq0/otfvQLgkrdtlgAOfelNWQJ420/SW98BGQBv/RzfcXcQAqARICkU0DrYU+cOIciISQP5Nn/uPhoEhTvi0j/Z+ly1DBJA7j5Epdy2txs0DvbYsyHJpL4QMPhtE/jrNtITnYd4YNuncbh2Vg8DUjDG1SdSvMFTfNF+oBvOH8jBzmVJkv3mbxjSRv9JXuh5ryfS40qx/vU4k/0k5QUc3t0JxH6LSB/WvHRDdC+ay/jh01yNfg95UCnOgW8zkZNkLMERDf1yE/I6jnZC26GOiDlWjJNb9Qcoi1czVy6gvRqd73VCcW4Vjm/MQ1G2qQ0pf0DCUDLks1ZDdGh3twNiT5Ti1FbDmpmbCHMKYjL2nlOc4NtSjci9RYjab2yLyGIL12qgA7pOcKYQfXR9Lvj34QctFsIhaZvYcY560QdOnvb4Z1sOrp0sAmtIF9LePbP9ENRGh8PfZ+LsnwbJOYsEb8RMX7Qb6Iprpwrw6+fJqCgz3Fmo/uTmk2u360h3DHvUD3EXC7F3bQrSb5Qyg6+zlxIzPmyBmNP5OLErE4nRpjZ7Qpjjj6f73Z5w89Hg0tFsJFwprFF7swJg847OyM8pR9oNAp0CBxUGACTvt6JCw7PCB/bGBIC5ublwcXG5486vO2nAMgDeSatdT2O1BIBCwDEHUkZgJ8wnK2pzZ4wAokBZiziAKq0CIW0c6eHECoA1QBOhw5Bpvvjtq0TkpYlL44TzQ7o7cKo3uo3ywIrnY1CYc9Mt+GZBKQAkKrDJ7wZBQ9TfT8daBYBKtR0e+TSIAuCa5+ONHGGEMMfvA+cc0nqQA3pPdsP5P/Jx6if9fFkDgI6eCoxb6IXsxIoa+zlrJYDNemvRa6ozrvxdjFNbrAdA0ueeU50Q3luHg6tyEX9Gb8soBB4hvPEBKaybFgNnuCP6cCGOrLMOAEm79/7XF74RGmx9KwlZCeVWAeCEef7wba7BDwsSkZmgd2KR6isfpGZ+0RxpcaX47fMklJdUSwIcv117lR0mvR6CkzuzEHlcD/5S9xR+Fthah6ykMhOVsTn7QkttS9WxZAPItW1UjgEAST0jSSOvTn0C4N5PF9osARz28lu31E5R9EUkf1CvMyADYL1O9+27GclJ+NFHHyE5ORnt2rXD0qVLMWDAANEOkbyG8+fPR0xMDMLDw/Hee+9hwoQJTANoygBobgJYnCFqwMVOr1Iu4kGcFNTw2+48wh1lxZW4fMgAn6Q/UgBIPgtsrcW4OQFY9uR10fUTy/k7aLoH9d789aNUk/tYkgB6hqhwz2ve+Omt1BoVsDUASDo78QMvXNhZSAHO3Fj5AzInAdQ422H8u544sCwXKZEGBwJzEyHmIuIZZo8Rsz3w8/wMKoXkXywSQCLFu/99X5z6OQ/Rh4qskgCSe/V60A3+LTX46Z2bNoCCzvMlTELJ3P3zAxB9vBBn/tCrIFmByStEjY5D3bDvuzQqKbcEcPx2idq3vKQKFeXGNnfWqr6FayQDINPrF9z7d+8ntQDA2TIAss124y4lA2DjXj+m3m/evBnTpk2jian79euHr7/+GqtWrcKlS5cQEhJi0sbRo0cpHL7zzjsU+khOwzfffBOHDh1Cr169LN6zKQKgEWgIYvpZBYBmZk9Kjc0vTsppnRQoKTCGEEmp2M2+9n/IC4c2Z4CjDynbR/49/VtoEdbJAce2ZUvaSxpJAG/ekxjwj3zBB78vNTj9MAPgzU4MfsodR9bloKxIj2essMwfw7BZ7ti3LBtV4j4ItLiUWnPEfzyxe6nBiaIGeBigSg9xrtSZJiuRxKEzoCY/JIwQsrhyzbs5QOdqj/N7b9qh8epLQRIZj3DdzQEgvw3unub2mSW1r9QcWgJIFpW0cKwsErw7WgL48QLbJYBzFsg2gBZPusZfQAbAxr+GFkdAoK1r164gSaq5q02bNjQp9fvvv29Sf9KkSfRb5K5du2o+I+lt3N3dsWnTJov3kwFQP0XWgB03qbYADgsAkqDUJIyOtQBI2nb3VyE72TQMjKgEkAfI7gEqUecTSUeWmxPi6qdEbgq7utzc5nT1VyKX5wAjtoGlAEfYD2sBkDhyELU/YTdrAVDnYk/DmZQU6sFfyplCCFJEHcuFbjEHelIAKQVcYm2JzaEMgPoZq1cVcC0BULj+shewxaOv0RWQAbDRLZl1HS4rK4ODgwO2bNlipMIlCavPnDmDAwcOmDRIpIIvvfQS/eGuJUuWULVxXJypE4KwARkAGx4ACteIVQIo5eHMAoBCOLVWAijsty2AzPrEsEi4TICJ9wdWFae1AEhuIerxKuiQVB9kAGTzApaK78fiBSxcr9vlBLL3w7fgqNOybv+acoXFJRg2d6EsAbR65hpfBRkAG9+aWdXjpKQkBAYG4vDhw+jbt29N3UWLFmHt2rWIiooyaU+tVmPNmjWYMmVKzWcbN27EY489htJSYyN4UoD8jf93AoDBwcHg4gAKvYD5N2SJA8j3AiZ1WZw7WMuxghCrt7GlkDDc2MVARiwcCqknBT9ic8q6WcTaZgUuMRiUml+juRJ0VKw9fjHW+WCdAxZAImVE7f5EYFBYRwrmWACOVQLIOm4pqR3LnLBK/fhtCeuwqIBZ7yM1vyxhYJoMAC6uBQC+ulB2AmF9gBpxORkAG/HisXSdA8AjR46gT58+NVWIU8e6desQGRlpFgAJHE6ePLnmsw0bNuCJJ55ASYlpPq0FCxZg4cKFJu3IAGjOLUE/TTIACjyCZQCkMyADIFteYOHLhgUgSZ07CQD3LH4TjlobJIAlJRj+6tsyALIcsI28jAyAjXwBLXW/PlTAsgTQAHqyBFA81IsQfGUJoKk9nwyAMgBaeqdb+pwzwdnzfi0AcJ4MgJbmuSl8LgNgU1hFC2MgTiDdunWjXsDc1bZtW4wbN07UCSQ/Px87d+6sKT9q1Ci4ubndUU4g/GmVVcCmm0xsTmyxG1TIEkBZAnhzD7B498oSQPGXvgyAd8ChXkdDlAGwjiayITfDhYFZvnw5VQOvWLECK1euxMWLFxEaGopHHnmE2glyHsFEXTxw4EAa+49A4i+//II33njjjgsDU1sAFKsv3CusdnYNbY+xSDttdgKRCNbNzcPtsgFkSaMmZeNmTUq0hrbmXH9scZiprQ1fbeuTvt9JKuA/F823WQV812vvyCrghvrw1WG/ZACsw8lsyE0R6d+HH35IA0G3b98exKuXQB65Bg8ejLCwMOr4wV1bt26l0Hft2rWaQNATJ05kGmJT8QKWAVB6uWUAlHAIEcTqE3McEc4wq7cv04N4CwvJAGgaN1IMLm+XF/Cf775hOwC+8a7sBXwLn5+G0rQMgA1lJZpQPzgAPPLnU7h6Og/nj2bB1VNNE7tnpRrSUZEhi3n0tunujlGPBOPM35k4dzgLuZnlCGnliNhLBUxewCTu3awlbRF5Mhdn9mUiI6EU3sFapMeXiKYjI/3hQ83Yp4KgsLfDyT8ykHKtBA4uShTlVVjMvMEtZcsezug42B1Hf05H8lVyXwIMpgstJsnSOCow4eVgHNqcjqRo4xy0rNtlxAw/nNmTjbRYU+9tljY6DHFD+o0SpMSYOv+wAGBQGweo1HaIPafP58ocBuamBNDRzR7h3Rxx4S/j7CfCtqTG0u0eV5z9Iw8VZWK5Pkxr84EtrIsDinMrkXpNP4fWSgA9AtXwDlUj8rB+DNZKAElmje5jPHDwe0NAbZa148o4utpj6KN+2LUsyao54OqTTDAkheGxnzNq9gELAHL73d1PjZ73eCI/qxyHtpofgznbRwcXe5oOzs1Xja7DPRDU0hFr3rxqdujm6pPc32nxxXD2UKHTIA90HuyBTR9eQ3qCfi9bUjV7+GloDu2S4kq07+OOzgM8ceV0DvZtTTKpL2yPtK1zUtK85dcv56JtDw907u8FO1U1eg5edkula9z79893agGA8981mWc5DqA1T13jKCsDYONYp0bVS+4FtPiFe9B7WAA69PFEWUkl3Lw0+GnFdRz6NblmPFJhYAIjHOlLt9NALxTmliOguSN9+e79Pom+mIUAKQQpd281Og3yRJchnjSRvVpnj2tn8/D7t4k0TZWwvnCSNTp7dBjoju4jPCm45aaXoay4CjtXJhodpGKhWwg8tu7lgj7jvFFeWoULB3PhE6rFnm+TzYKgOahp1skRwx7xowC4f1MqfEK0iD1fyLwfgtvqMPbZIOxcnmhUjzX0R0RXJ/QZ743v5l9jvid/Hdr1c0Voeyf8vkJ/aPIvFltB71ANhk7zxZb34iXrS3Xu8U+bYeP8GygtqpKEL34bfKAYOMUbWYlluHAglwkcSCF+/c7D3SnE7N+QKllfbAwjHvdHcV4lDm5No0VYVd9kX3r4q/HAf0NwfEcm/SLAXZba8GuuRUF2BToPcwf5EnBkWzrO7csxu2/NAW2Xu9yhc1bCO0QD/3AdTvyWiTN/ZaG8VP/cWYLgfhO90byTMw1iTcZwem8WTu3NpH3iLrE2yN7uc48PBt7ni5TYYngFanH+YBbO7M9Ecqzhi5QUAHYb6oXxz4Qh9UYx3LzVuHQ8G2cPZuLq2RxwqX2lwsW06uaGqbNb0PeMWqvAlTM5OHsoA6cOp+GrP/bVCwDufvt1myWAI958T5YAMr/xGm9BGQAb79o12J4LVcBqrT3mftEFgc2daJ8v/5uNDZ9cQU56mag0z8jBQKHA/bOaoc8oX1o/LrIAmz6+iszkUslsG/w2ugz2xAMvN6P1k68XYfNH15GZZFxfClBCWzti8uvNoXW0R3JMEX74KA55GfrcsmIAyD9km3dyAjnIPfw1iPonDzs+S6iBUDEo4v5OpJndR3ug290e9P4/L0nAtTMFTOtPDknvYA3umxuCQ1vSoNIqcHp3tmjaM2GjpP6UN5vh1O5MRB7TpyKzdPHH7RemxV2P+2PDW7Em1e4UABw+3Q+pcSU4v1+fj9caNa9ngAYPvR6GFS9fqYEnS/BG7tGiuzOUSgWGPuKLP79JwdV/pfNH8xeHANfUhWE0BzDZqwc3p9VkITG39kIQGzDJBwTgSooq6ZedS4dzUVXJNm4CS2OfDUSbPm70Vj9/fgPn/86mfZGyq+T6pXOyx/hZIWjdU1//0E8p+OO7xJp8xpZsAHWO9hj/XBg6D/TUv2su5+PLVy+hsuImuHL0ZyZ1IGmbfGkc92QY+o/1p/UL88rxwTOnkJmilzrWZyaQ2gJgbm4uXFxcLD3u8ueNeAZkAGzEi9dQuy5lA2ivVECh0IdNIS9V1kDQGp0CSpUCKrUCao09qquqkZnCDoDObio4uakoQJEfct+of3NhV80Wq4/UD2rlAEdXJW3HTmGHY9vTUVZSxQSAWp09eoz1hGeghko0CnMqsOPzRJQUVhoto9jhrtLYYfxLwWje2YlKE79/N45JLcwdzm6+Kjy6KBxKjR2+eSUGGUlsKmFS3zdMi4mzQ7BnbTKiT5qqYoX7kD8GtVqBZ75sic9nmgYcv1MAcNJroTi4Ja1mvVgBkHxp6H63Jy4fy8X5A3p4JJclAFRpFJi5JIKqPn94Pw6x50wlxmJtOHsoKfy5equRmViKzYvikJ8pnUSZ22Mk9/PwR/0R3MYB2cllyEopw+ndWchN139RsjRuOwXQbaQniOq3IKeCPiMpsUXIStabjbAAYGg7J2gcFBQ+SwsrUZRfQb9ocpclAHTxVNEvSeQZqyivotBdUqxP4UcuS5lAFApQs5HyiioDdPKgsV4BcMFrtksAFyy6pVLKhnp23Wn9kgHwTlvxehhvY3YC4U8Pq70av441+X9pft6bkgXWZXH1VtEDlqiSj/6cgeJ8Y4AUtsMdeJ4BavR/wAdt+rgi7mIh1i8UV+kK7an8wnR48JUwKr386LHz9HA2dyCbG4N/Mx2mvh6OU3sy8df3yUywTNoh86hQ2qHnKC+0H+CG3d8mIT6ySLS+GBiFtXfE2OeC8Nf6FCqJkrrMqRSJCrPfRB/kZ5fj2PYMasfGGnSY3Kv7SE8MnuSPHz+Lo/aw1lyvrG4PrZMSmxdfQwxP4mspe82waf7oO84bsRcKKHjeuFQoabfK9YmAS98JXijKq6R1MhJLa3JHs/SbACCR1PHtXFlsBaX2Emt6PX7/5EwgeXB1dcUfb9kOgCMXygDIsucbexkZABv7CjbA/ssAqF+UhhDeRXgYEk3tNr8AACAASURBVFu03vd44dq5fEQeNw8kwkOXgOrE/4SiXV83bPrgGiKPm9rCiW3DDgPc8eDsZki4Uoiv50ZZBYCkzScWt0BghAN+WnoDFw7lWA2AfSd4Y/BkX0Qey8WPn5raEfL7bQ4AiQr26f+1pJLejx+7SG3SrAHAsU8Ho8dILxz6ORV/rElkflqJBG7OyvZIvlaE7xZcRXFBVU1dKQAk6v4B9/vi2I50I8cd4V6USjnI3EmGgjIAArfLC/iP+fNslgCOfOd9WQLIsL8bexEZABv7CjbA/ssA2HABkNsudvZ6Fby5yxzgENXWuOdDUJBTjt1rzXtBmmuLqPVe+LwtBZkfPom1GgAHPuAL8vPJE5dQUlBpNQASIHrykxbY8WWCkRrV0rj5nz/9WUtkJJTgh8Vx9M/WAGC/8T4YMtkfnz51wciBwdJjS8C5z1gfrH8nhpoJsKjLSZt8qTJr8HJLfanN5zIAygBYm/0j1721MyAD4K2d3zuy9cYEgMIFEjs0rVHtmgUhXmBjqXvasmHqOkBuJc9miQ87lagCcaY59VemJAgZSR2rqtDjLh94B2qxc80N0eHZEcLkXdx8B4Y74N4nQ/H1PNOc1awS1tlft8fyuZE0pIjwYgGUsTNCqDfoid36ECaidmS8eePu07G/J8I7uOCnZddrbs0fq1ASx/2/Qz93RJ/OQ2mxXvKn5M2PcNz2vM9Y9i9pT2zuaisZZN2LtqyDlA0gyzpKrh1Pby3l3WvJBpAbl9EeuU02gL+/8V+bJYB3v/uBLAG05WXcyOrIANjIFqwxdFcGQNNVYoUVW9aX9dBltY0SA8AKAeCIScKEAEhsyyI6uuDKaXEbPDEAJPPRZZAnzv6dZTI1rHPacYA7zh00hEDhN8QCDs07ONPYccQO0FoA9A9zQHGhsSMCCwAKIU0GQGknEJZ1vOMA8LVaAOAiGQBteRc3tjoyADa2FWsE/ZUBUAZAbgb4EhOprSsFgCxhdoRts0qyWMFBDBqFsMvyeMoAaDpLLOsgSwBZdhfAvX93zSMAqGGrxCtVWFKKUe9/IMcBtHrmGl8FGQAb35o1+B7LACgDoAyA4o+pDIAyAN7KGHs1APjfV+GosQEAS0sx6oPFJoskZwJp8Eev1R2UAdDqKZMrWJqBhg6A/P5LeUeypDoTqupskVbx+yMluZJS9fLbYHFSELbFovbllyH3K68w2NTx1cOVlYbQNBW830kdMfs5qT0lFivSROonsCO0tE+Fn/O9NcUkfsIxiN1DzLaPlFfa29dUs+f9Tj/jjUGlVBrK8f7OLyPcfyz2gKQOq00ry960ZV+azD3PBk8qw4e1+1zqPmImEU3FBnBXLQEwPj7eKBC0RqMB+ZGvpjMDMgA2nbVsMCORAdB0KSwF7+VqyABoOncyAAJ8sJMBUL9HWL7o3NEA+GotJICLF8tOIA3mRL11HZEB8NbN7R3bsgyAMgByMyBLAPUzwYdYWQJo+nxIOShxpVltAC3lGTbXnlTAaTE7TylJYUPwAt45d67NKuDRH34oA+AdcILLAHgHLHJ9D7EhAqCYKquuVcAsKjNShlUiyLJ2rAee1CHHV++K/c5X+ZJ+lfHUu/zPSLor7iot13vOcldxmSEtVwnvd34dUlZMHSs1H4pbpAJmvaeap7LVqtVG1XS8/2tUqprP+HXIH/lqXzVPPSymDiZ1+NJBW1TA/I7W5b4k7bKqc/l9YK3DIgGUUk83dRXwb6+8YjMAjvnoIxkAWV6+jbyMDICNfAEbYvfNASAJg0fMfISHNGsuYBJQmKSZIpdYHUvZDrgguawBcoU2gGqdAmU347KxHJpCdS7JMUrmgbRh60FLUrplJhkgSuqQpSAlsK1y91PTdGZlpYbMEqQcKwDyAw3LAGi8n+sSAJUqOyiqDLERrQFA8qx4BWiQmWjYJ5aeDW4/c+VIxpi8jHJUVZoPFm7pvUNC/5CcvEV55vMIs4QuEj5v1koAyV4tLzfe5/x+swAg+U5RwZsDa+MAkue9stLQh/rMBbyjFgB4jwyAlrZ4k/hcBsAmsYwNaxAcAG7/bjqKciqRnlQCdy81WnRyw94tiUi8ZkhOLwZzQeGOGDDOH5kppchOLUVORhnGPBaCY7+n4cz+zJosFlIw98CLzVCYR2KwldKE8N2GeVH4OfZbmj7PqRlJHL+93mO84R2spXUKsitA4KlZR2ec/D0DFw/noKJMfziKwVxQSwd0v9uT5lYtyq2gCeoHT/bDlX9ycWZvNhKjiy0u3MSXg1FSVEWzQZBMGG36uNBk8+f25+DCwRwU5pBE9eKHdO9xXnQMtH5hBdx9NWjRzQUXD2fjzP5sxEfq10IMAEPaOKLrUE86fxkpxSguqMDo6SE4tCMFR/9MoSnSyCUmAaxEJe6Z1hwHfk1AVloJrJUAKhR26NDNG2dPpFmcKzEJYKv2HrgamW0x77KY1LFNR09cj85BSbFp3mX+Pc0BoIOTCkPvDcH5IxlIS9Kvt5gEkIy120AfDJ4QiNMHM1CSXwl3Hw3cvTVIiC7Cqb8yaH2+lI//f+8gLboM8USnwe7ISi6juYC1jvbQOtnTFHY7VxhS0ZmzNVVrFWjT1xUdB7nDK0iDYzsyaH3dzTb2bUxFTqrxlw/honj4q9FpqDtt49SfWSgrqYSDixIOrkpcP5uPi4ek0wgSeA3v7ITud3uhtKgSV0/nw9ldBWcPFSorqvDHGn0WGuEXHz7MObjYo+fd3mjZzQV7NiXBzVsNNy81SHq93d8lIi/LNJ4j/xmqRjVadXPFwAn+OP57Giorq+Hhp4GHrwZXTuXg/BF9TEopFbCLlwpDJgaivLQKkaey4R2ghXegDvn5pbh/5vpbKl3j3r8yAFp8ZdzxBWQAvOO3QN1PAPcCWr7wfoQ0d6EvvuAIJ/gGO9CbXf43G7s3xSP6bK6oNM/ZTYWIjq70pevpr4OnnwaturnR+vnZZfj7pxQc/CUF1bwzWQhiLbu6wM1bQw8AcpC26OICJze9+u3CkWzsWh2PvExjCQX/YPQN1cEnWEsPH/IT3MoRwa0daf2MxBL8vjoR184WiAKgk6sSAREOcHRVghxKLl5qCoTkykopxbl9OTi+I0McTOyAsHaONYc4OYy7jvCAq5cK6fGluHG5EMd+yUBuhvih7BWsgau3irahcbCnh2vL7q4Uqkn9M/uycP18gSgAOrjZI6yNE9x8NHDxVMI7QIc2Pd3pGArzyvH7+ngc3J6E4lKDqpevzq2yr8SYKc0oBF27nIufN0ShYw8fbFsThZQ0Q2DojHR9lg3uKsrPp7/a2yuw9/LzePq+zYg8n2rTZj0Y8yLGdPsaeTklVtd3dFLT+4/rtRKpSfo+8S8HZ+ea/3p5e4NA3NNzu+LI7mSMfjAcvQb748ieROzaGIfMNP39+epgDho79fPCA89G0PklV+zlPCTGFNEvL9lppUi5XkKDUdM5Eai6yf/JPu012huhbZ3o7ymxxTi3P5t+6SDwT76EJEQV1fRVCIBE2tZrrBead3KGX3MtldYf3pZOgZ988SgprEJidJFZCTjXaLv+ruh9rxe8Q7R0Hkj+5ZTrxVQKSO6fdqME2Sn6vWpOAkjS9t09IxBh7ZxoGfKMxZzJp8BGvoTlpJXRPctdQhWwRqfA0Mn+6DnKG0qVAhXlVbh0LId+eeG+BF49l2d2DFxbnQd5YuikAPiG6NfhRlQBUuKKkJlaiqzkEroumcn6L4/mANAv1AF3TQpC18FesFcqkJtZhuuX85CRVIz0pGJcj8rF68t/rRcA3D5njs0q4Hs//viW9tHqB1GucEtmQAbAWzKtd3aj5lTAvUb4ws1Lg7SEYppWKyO5GBXl1aIAaCTZUyjgF6ZD+z4etG56fDEykkqpeoo1nIVKpaC5VQl4pcWVUAAihxyrDSBZ0ZbdXejCpl4voQcSd7Gm1SISRPKTfLWYHqjWXkQ6EtrOkdbnUoSRNqyxAQwI19GMFrmZxrZ5rCrgoBaOCGvjjOTYIsTHFKAoXw/QfFs/PgByEj97ezt0H+SLkQ+Gom0XL8RdzcXcJ/ci6YYeqsQAkHz2wKOdMWR0Szz74A/WThktXxsAfObV/vALdMFbL+w0e28+AIY2C8CCzwai96AgJMTmY/uGaOzbcQPFRRVw0umBglzmAJD8XaO1R2gLFwSEOSI/pxyR/+TU1LFGBUxg3zdUi/jLBuCzRgVsr7KDf3MdMpNKUZxvKvW0tAgqjR38muno85101dAHfj0pFbDWUUHrO3uq6BcUsUvMBtDJXQm/UB18w3Q4vS+zJoMLacdSwGmisnXxVlMA9A3WUfi7fNKwDpZUwOQZ9fTVgkhjyRdepVqB3zfoc0iTqz5VwL/Mnm0zAI775BMZAC1t9CbwuQyATWARG9oQGooTCH9ebLEbZAU71nL8/thqA2hura0BQK6+VBxAVicQfuw/SwDI3bfP3b4YPCYEnj46qNR2WDT3ME4dTZEEQKVSgT2XnsfMCd8j/no2iouM4dXS/rcFADVaJdRqe/x58TmM770KKYl5kgAYGu6GLzZOBFH5pqcUIfJMFtZ/cZF+ySAXCwBSCOQ5iLDEBCR1mrITCIutoBDsWD16+QvKWscSAJp7vvimBfUJgD/XAgDHywBo6bXSJD6XAbBJLGPDGoQMgPr1kIrpd6cCYEGxwe4xt7AQOgcllZBJSQCJOnH6870wZWY3bFr5L7753zHmDe/iqsVvp57ClGFrER9rkORYaqDngFC8+9UYnD2RhNee2oHycvOSME4C6OCogqOjWw3wuTrqTQW4SwZA4xm3BeyEa2aLF7AlCaAQJk3gkpcPu6GHgZEB0NJTLn8uA6C8B+p8Bm4XAAoHIpbJg9ULmN9eXWYFkeqnLYtR1xJAfntGGT54hx/pp5jjh9jfSR2+E0g+Dwb5YEjKJSck1ExFZUU5vvj+AYx5oB2+X/UvXn1yO/M0zf9kJKbP6oVj+2Px8IjvmOtNe6YH3v1qLC6dTcGkwd8a2Q+qeCFd/IOCzEKeM0/lSwqIqX35ql1Sju9IUl+ZQMT2OfNk8QpK7UV+e1IevWLl6mKf2xJvsLHGAfzp5ZdtVgFP+PRTWQVsywPQyOrIANjIFqwxdFcGQP0qSUkA6+vQZQl1QfpS21RwfLu/ugbA8rIyqo5dtX0KnF01mNBnFfNjMOCucKzf/Qg++O+fWLb4EHO9d78cg/53heP+/quRkWZwPCANyAAoPo0yAOrnpiEEgv7xpZdsBsCJS5bIAMj8tmi8BWUAbLxr12B7LgOgDIDc5hQGeLZFAkgAkErRHFRYvm0SHh29QdLxhf9gEHA8nfEqxvdeiehLxp7GUg/Q/9bfhw9f24PEGwZPZa68DIAyAAohzwT6eKGZbpcN4Lb//MdmALxv6VIZABvsCVt3HZMBsO7mUm7p5gzcagDkT7RUnlhbVMBibduiAhZrS2qj2GIbWBeqMTF7KjGHEDIGI/UwLysI/+8m2UNEsoQIM4bw/8+HRrUWKCurQllppZHnMelPSZHB45SDRvL3+R8Pwztz9pqddj7MaR30YYrI5e/vjKwMfdgVNc8xg4KoSFYPvgMH/3faBi9LCF+1K8zra8/L/sH/TMzRg7QtZtJQW1MH1hearVI/fvss2T+EZWptz8eHNJHfhXPQmJxAttYCAO9fuhTx8fFwcdFHPiCXRqOhP/LVdGZABsCms5YNZiQyAJouxa1UB98pANi5lw/i43KRHF9AJ1gIjWIA+NGqMZj75G81Dhr81REDQAJwo++PwM6tV2UAtPBmkQFQP0FGat8GIAGsLQAKl/2tt97CggULGsw5I3ek9jMgA2Dt51BuQTADMgDKAMjNgDkJoIcPCTRcjZQkPciZgzmhBNDVXYMVP4/CE/fuqJHMsQAgCcty9PpzeGT0Zpw9kWyyMFIAuHnfRMyftR+xUcYBoKUkgCQAcXC4M5JijOPfyRJA8Rh8ZFFkCWDdHSPc+3friy/CwQaJXVFpKe7/3/9kCWDdLUmDbUkGwAa7NI23Y3UNgMKZsONlQqitCtikbRIJ9ubFGmSapVxDkADyxyqlTmNRBwslHkaqYhF1MKlD0vHd9WAwFs08ifIKQzDsCl4dUo7//8rqasz5uCs69/XB9EG/o7REH5JFmLqN3wdurL2G+GPuxz2xdVUUNi2LlHyo+GpWkuLtk82DQAJYz3/sCIqLDGFg7Hl7RMlX2d78/em329NA2TvXxdXk0jUqx9u/fJUv6ZxRH3j3Efs7qSNmniBlTiC2H+vaBIE/4bUN/cK6Z6XuyeIUZeKhLPB+59pv6GFgtrzwgs0A+MBnn8k2gI33CGbuuQyAzFMlF2SdARkATWeqKQFgSGtHdOzvgX/3ZSDxZqYHSwBIUvBNejECnfp5YseaWOxaF2fkeSwFgJ36e+OpNzpA56jElD6GjBwsAPjwrLYYNakZzh1Px+LZ/1gFgO+t6Uczc2xdEY1f11+vqWsJANv39sSs9zvixpV8rPkgkmaTYAFAkvP2rilBiDqZg+jTeUZpDmUANJUS1jqkC6MNIN/ujxUuG4IX8A+1AMAHZQBkPe4adTkZABv18jXMzssA2HABkKT58vBVw81PDZI79cKhHFRXGavnxCSAnYe60zyp7r4a7N+SjN+/48Xq40lJKs1IAElO55eWdoSTqwpvTD1O8xfzoVEKAGEP/O/HQdi2+ir+/NGQVosFAImw7YufhuPV6X8jP0c8Z7KJ9E2hQK+hfpj0dCt88soppCYYVLqWAJCkA3tvYx+4uKvx+dxzuHo+lwkASR869ffEw/MiUJhXgX9+T8eejYl0fVgAsEU3F5pOLiu5lKY8LC+5mYbEzGtClgAaA6WY/R6ZusYKgJtnzbJZAjjp889lCWDDPF7rtFcyANbpdMqNkRmwFQD5syep2q2lCljsPlLqNH4da/Kq8uuptQqUl1XRA90WiaBPqBZh7R1BAMNOYYfSwkqc3ZeDSp4qVWoHBrTU4ZGF4bBX2iEzsRQb37uGnDR9WjVLWRVInbumB6DXKG/EXizA2gXRqKw0AAbf89dcIOnxT4VC66jExaOZOHdYn9+Vf+jy69PPeEDZvrcH+o32x/L5F0RzuQrr8Odh0aa+ePfJf1BUoM9bLHYRta/wGvtIGJ3r39bG1nxkpHLl1eF77RJJp7uPBu37emD5vEuorjaYFvDLCfcS+WzU40E0b/XVM3nYtjQWRfmVkjmvub2k1inwwCthCO/kTPv624oEnNqtn2uW/da6twvc/TR0f5I1JDmzY88bx0DkJoHF8YP0p4SnOufPrS2OS8K1YVHn2lJHSgUsBYr8ezUECaAMgJKPu/whMR+pZnmS5alqtDOQnZ2NF154Adu367Mn3Hvvvfj888/h5uYmOqbBgwfjwIEDRp9PmjQJ33//PdM8mANAkli9ILccxQUGuy+pg0kIgK6eavg3c8D1S/ko40k2WG0AiS3XgPF+yEwuQfyVQuRl6sFHeDBKhXvpN94HvqE6ZCSWIiOxhB6QmcmlooerUVtKO/Qc7YnhD/vTA70wtwInd2Xg9N5sQFxQU2PfReCvTR8X9JvoQ/t95WQedq1IQmFOhcWYeAQ8Ow/3QI9RnrRufnY5Nn8Qi+J8g12bFAB6BWlw/0thiI8qRMy5fMRdKqD9F8sYIvx7j+He6DvWF1/OvYjym/Z7pB+sAPj4621w+mA6Th1Ir3cA9A7QYdYHHbFgukF9zAKA3L6aPDsCxYUV+GXFjZpnxxIAKuyBDv094OSuQu8x3vj5ixuIPW9wmJH6AmKvUmDs04EUAomG8/zf2Tj+WwaKcsynsuM/0Eq1HYZM8UPPMV70z+f/zsHZv7IRH1lIodASwDXv5ISBk3zh4qmCg4uSSpd3rUxAeanpBjd37Dh7KOEXpoNHoAZegVpqP/nbiniz3tvC/cNvT+OoQFALR/pzbFea0T5ngUZShnzhCWnlRAE2KcYw99YAoEqjgG+QDjeiDU5E9ZkL+Pvnn7dZAvjQF1/IEkCm065xF5IBsHGvn8Xejxo1CgkJCVixYgUtO3PmTISFhWHHjh2SANiyZUu8/fbbNWV0Oh1cXV0t3o8U4ABw5aIH4eykpob0geFO6HWXL+Ki8nH5RDYunshGXGS+KDx5+GjQoY8nVVNqdEroHO3RZ4wfvX/C1UJcPJqFAz8no0rPcWZhjkAHsatydFXC2U2FkNZOILZo5Lp0PBu/rYpH7k0JGNcG/3Bt3cMVzdo7w8NfTSUjrl5qaB3sUVpUiZO7M3H8t3QKkmLSFe8gLbqN9ERAuA4e/hqkJ5QgqIUDbkQWYd+GFCTHGPLimptYciAPneqHFt1dUJRXgeiT+Qhs6YBLR3Jx4W9DXlup73C97vFCr7FeiPonD8d2pMPBVYnU2GJUlBkfymIA2LK7M8bMDMbOVQm4dMw4ly4LAHoEqvHkO23w5ZyLyMkoM1KnsQAggdeF63ph/pRjVHoq5UggVAlzc1obCSBp479fdcP3S6/gRrQeBKwBQJVagec/bo+/tiTVSD4tASB/L/o31+GBl5rhzP4sHPox1eT+5A/mnJBC2zki7UYJuo/0RNe7PBBzugA7VyRKftngxhbSxgFDpvrhwsEctOzhAu9gDa6dK8DBH9KQm24qMebvXVdvFQY95Iv2/d2QcKUI7n5q+mUh6WoxLhzMRuwFvUTR3J7VOCjQdbgn3a8unmqUl1YhL7MMWSnkp5Tu23//zKy5nRDmtI72GDZFL6VW2NvR+jHn8lCQW4HCnHL677970+kXMGEfSFvE56b7cG90GeyJsDbOIAB3an8GslNLUFpcidLiKsRcyKXvH3KZ24vegVoQiXXr7u6I6OBKy184nkVhlkjq01KK8J/FP91SuOLev5uee85mAJz85Ze3tI9MB4lc6JbPgAyAt3yKb98NLl++jLZt2+LYsWPo1asX7Qj5vU+fPoiMjESrVq3Mdo5IADt37oylS5fa1PmaMAQrH4ZWrQLR5nn5a9FzuC+unsvF2cMZOHc4kwKBGDyRb87dh/nQF29ZSRUqyqowbmYYos/k4tSBTAqRBGKkJIBDHgxASSGRtpWjKK8SfcZ4oyCnAid2pyP5uh6+pCSAbXu5UXgkUr7slFJ4B2upBJAcQqVFBpGI2Bg8/TUIbuuI5KvFFP6IVCG0nRNiTouDr3DCOw1xx7WzBSjI1qsvCRRKwZuwfkhbR2QklNDx2+KFSaQy5CKgK5W/VUwFXFldBWL/l5lSqj90eapdFgAkdZzclFRqKXbocmMWA0AHZyWKC4jEUno7m1MBkxqu7mrk5xi+aVgDgKS+s4eKSq3JPqZryFMbm1MBc73kPiMg4uWvQWqcPjC1lATQnBcv2TPNOzjj6injcDbmZoOrz99nBMzCuzjj+tkCFBeYwpO5dnzDtBSYCLi5+agREKGjaxh/WW9LKfWlxc4eFCBJSJ3Lx3Pg4aehX6BUajv6xatmvXkLym/PxUuFbsO90KKrC3Z9k0CfYSdXJRzdVDi6M41+mRL2gduLxLwirJ0zug72RMd+nti3NQlF+eXQ6OzpT/S5XFw9q88OY+55Il9U2/XyoHXbdHfHtUt5uHouhwKpvVKBlMQCPDZ38y2FK+79u6EWADhVBkDpl0UT+VQGwCaykOaG8c033+Dll19GTo6x5Iaof5csWYLHHnvM7OgJAF68eJG+pH19fUGkiCQIqLOz3rbI0mVOBewTpENhXjk1budf/ENXDObI39UaBRRKOwp0rGFg+PchBxt5CZNv4qxqY6N+8kJysIbXYC1naT6FQCAsb4sVhy0wyBqGQ9KgntHzkj9GqewL/HJSY2KZYzGQN/mSYMZWkLTPuq9sKSdlmiC2z1js/oTzIrVn63Kf1UVWD6M9YmZfkWWqrKo2An+WeIPcPiJf2IjEv4DnPCS1t4V2f5wKOCHGYEdZnypgGQBZnvo7u4wMgE14/RctWoQ1a9bgypUrRqMk6l0Cf/PmzTM7+pUrV6JZs2bw8/PDhQsXaLmIiAj8+eefZsuXlpaC/HAXAcDg4GA8PmAATYElCUIMDh1SB7DUYSoEQO7/rAewDIDi3sFkbljtqSwd1MK2TABXRGooLCcDoPGM3OkAaG5fWQOA3GyKfQGRjAMoEjuwPgFw/bPP2qwCfvirr26plLIJH7uNamgyADaq5dJ3lqTjWbhwoWTPT5w4gd27d2Pt2rWIiooyKtuiRQs88cQT+O9//8s0+n///Rfdu3cH+bdr164mdcT6IwOgwfNTOGl1eTjXpWSG9NOSRzA3FhkAxYGL1bmItZwsAWTPJMIqgeavHmsYGGskgOZervUJgOueecZmAJy2bJkMgEynY+MuJANgI1y/jIwMkB+pizh6bNy40SYVsIkEprqaJgFft24diDew8BKTAD7avz+VAJozUufaYFUB8+8ppgKWgiyxA1QKxOorw4ItMFjX21ZMeiYGg+b2iCUwFNZh9ahkkdrU9Xyw7gv+fWsrjSZtsahz69q0oC7njtW0QGov8D+T2n8s+0LKblWsryZ1RCTQrBJAfj8JAH5z8OAthSvOBOe7p5+2GQAfWb78lvaxLvec3JbtMyADoO1z1+Brck4gx48fR8+ePWl/ye+9e/eWdAIRDoyogTt06EBDwwwcONDiuLkXkAyAhqlqyIc26aUMgMbbWgZAi4+52QIyAOqnhe+QdLsAcG0tAHC6DIC2PQCNrJYMgI1swaztLnHgSEpKwtdff02rkjAwoaGhNWFgEhMTMWzYMHz33XcUEmNiYrBhwwaMHj0aXl5euHTpEmbPng0SBoaolYW5S831RwZA01mRAdB0TmQJoLQXuph0sSHvJRkAZQC09oySy9++GZAB8PbNfb3cOSsryyQQ9BdffFETCDo2NpY6fOzbtw/E+zc+Ph4PP/wwdf4oKCigzhxjxoyhXsAeHh5Mfb7VAMjvhJQ6WEz1LCXdKTEhagAAIABJREFUsaVObdV2Ygc902TfgkIs0kDhbeuyDmmbRb3HOnTO+5u1vLBcbaWBwvZsAThb6tg6XmvrsTrf2GJOwO9LnahzGbzQxVK/UcmeSH2Tz3hq49slAVzz1FM2q4Af/fprWQVs7YPQCMvLANgIF62hd1kGQP0KSdk+iq1hY7EHtBUASbBeEspHeGAK2xMCYGALBxTnVyAj2eBtzvoc9LvXF4e364MoW3t1HOBOM1qIXWJg5uCkrBmnDID6GZABEKhPG8BvCQCq1dZueRSVleExGQCtnrfGWEEGwMa4ag28zzIANm0AdHCxp4Gl+ReLBDC4tSNCWjvi8M9pVgPgE++1xB9rE3EjypCWi+UxIIF9563phK9mX0ZOehlLlZoyJA7c3NUdseSZCygrFuRCu1lKDABJFhmSdebUHkPgYq5hS9I8c/NrqY5VA6vjwrIEUD+hwjiA3DTfLgng6pkzbQbAJ1askCWAdfycNMTmZABsiKvSyPtUFwDInwKhVMxIsiYSR5DUF5OmSYXUsKUOiwrYGimQ1NjramuYyyhirm3h4d5hoBv8muvw55pko+KWVLZegRo8sagFfluRgAuHTSVqUqFsWvVwwZTXwrHhvRhEntBnYWC9gls5YubiVvh1RTyO70xnrUbLkQwec7/pgP2bk7Hv+xSLdfn7gGSBee6z1vh+8XWat5l1TUkbXUd4UHg8uDXVJAev1L4mn7Guq8XBWChgC/Txm2S1FRQLNSTsnphqVmpfidYRxPBjtVWVAbB2u+rXX3+l9ubEgebVV1/FjBkzategXNviDMgAaHGK5ALWzoAMgPoZs8V2TDjXkvaK9kCVsSDO4lJ5BWlortWEqCKc3ZdtsTx3qBHV7eiZgWjXzw3fvHYViVf0Kb24SwoACUjNeL8FXL3V+HpOFJKvmeZAFqtP+P7Z/7UByav80+dxOLXXVKImNYjhDwdg0P1+iD6dh+8WXrU4Xn4BvzAdnlvahqYj/Py5S8i/mY5PrBGjLxb2wBvfd0JlRTXWvnWV5sXlLkv7gsz1f1a0QWpcMX7+LB7ZKcaSS6n6JFd0n3FeOLEzE3EXDRkoWAZOpKXUxM1CyjzSlgyApjPa0ABwVS0kgDPqWQJYUVFB05YSW3QXFxcab5ZErGC1O2fZ33IZ0xmQAVDeFXU+AzIAWgZAkiaKqBj5OYXNLQT/sHd0UyKsvROadXCESqvAr18loLyU4bQG4O6nxsgnAhDe2RnxkYX47s1rVh30ve/1wl2PBCA9vgTLXzLOLEP6bQkAp77eHES1+cWsyJqcuCwASSRaXYZ4IqKrM/7ZmYHoM8bSNEubl0geH3kzAls+jUV8lHVA5BuqRc9R3lQK99eGZJQUSdO2UBL82LsR8AnW4tv5V5F2Q5/Hl1yWAJCUGTcrGB0HuePcgWzsWJaAqgrDOluyEyXr3P1uT6RcL8aetclWgeCwaX5w9VEj9lwBrp8vMIFPbgzmAJCslXBPW5IMm1s/1kDk/LqyBNAwG9z7d+WTT9qsAn5y5cp6VQEfOXIEH330EX766Sc6kBdffJGGK5s8ebKlR1z+vBYzIANgLSZPrmp+BpoiAJKcoP7hDjQnsVprDwJwMafzUJBTwRS8lxyOw6cFwDdMC3dfDQWCbZ/GidqWCWFBrVPgkbebwzdMh8ykUqx9IwbF+eziP48ANR5+qzl0zvZY9cpVZCayOVNwB+sDr4SiuKASqbHFOLHLVAonddD7N9dhwgshWPPmVRPbQW6cUqq60U8GIflaEU7vzWKWPPF35kvL22HZ7EhRpwyp55hIAe95Ohir50VbfNyFAOjgbI+7Hw9E7MUCnNqTZRUAhrR1RPv+biB2k0TiWl5isEG0BIBkrzz1aQvoXJTY+mEcrp1lt5tU2AMPzA2jwF1cUIFv58WYhUBzAEgkiCMeDaD9zk4tQ1ZyKfasS0Z+VrnJ3Jmrr1LboU1vN1RUVKG8VP+TFl+C/Gx9fZvUuTyvXWEnmroKeMWMGTYD4MxVq6wCwL///psCHMkWlZycTEFu/PjxRlP+1Vdf0TLk83bt2mHp0qUYMGAALbN161bs378fJEIFuUg58jzNmTPH4nMnF7B9BmQAtH3u5JoiM2AOAHsM84HOUYmMpBJkJBcjM7UUVZXG0iuprCAtOrui72g/5GeXoSCnnLZz9hABEYXoOvAPSr9gHWa+35qWLS+rRuQ/Ofh9XQIqSsQlaPz6/s0cMG1+OFw81SjKr8AvX93ApaN6WzZL3r5KlR06DfbAgPt94eatxum9mfjt64Qa9a0lA39nTxVGPOYPF08VHF2VWLfgGnLTTA9VsYkgMDFuVhB+X50ElVqBS0ess6MjKsXQdk7Y/EGs/iC+ySIsakByaN83OxTRJ/OoNIv14rf95Ict8fNncUhPYINW4T1e/KoNvn7lik0ASFTQc75pj09mXKTqXOFlCcZ8QrS4f04olv0nqmbepNab375CYYfBk33h7qvGT0viWaeOlgvv4kxV1/c+F4Sjv6Tj9B72uSfS5YffakbHSyR6u1YmIuWaQYJJ2pdy+iEmBiOmB1BJ75Gf03Dyj0z65YHF7i8gwgH3vxQKzwAtKsqrsGnxNUT/m0dV00IAFLZHALTvPb7oNcqbflEjX9K2/O86Lh41jN2SPV+Lzi4IbO4AZ3c1nN1ViDmfhyM7DfafkmFgqqpgZwe4eWngFaCFl78OOkd7/LUtQa9aR/16Aa944gnobPACLi4rw8zVq60CwF27duHw4cNUdXvfffeZAODmzZsxbdo0EAjs168fjUu7atUqGmc2JCQEW7ZsoYkG+ABIzgNiEyhft24GZAC8dXN7x7bMAeC7T49BWAtX+Ic6okVHVwS3cKZzEnU6GzvXxSH6rDGI8AFQo7VHcAsnhLQkP870X58gHSorqnDkt1T8uSmBgiA/DiB/wsmLmNQnL3QCjwTg9OBSjV9Xx+PsAb1ERuoA9/LXouNAd3QY4EFVcNlpZdA52WPr0ljkZRgATAwASdked3uh2whPxJ4vwMXDOSDSsIPb9F6w3CXqRGIP9B7rjR6jvXDkxzQqRSJ2dDmp7N6sHQa5YeCDvtj2cRxSrhsf4iwbNKy9I0bNDMS3r8WgpIDN85ffrrufClPnN8eXsyKtslfkDloCzy+taIePH79Qc4iy9JtfpjYASNp59J0I7F6TiKQYU9tFSwBI6j80rxnO7svC5WP6/c4MgHZ2IFDz0OthiDldgH9+lU7/aG5enNyUeODVUKoG/mtDCpPan7RD1PUVZdUgXx7ueswfMafzceD71BqTBUte3617u0KjU1DbzQ4D3XH5eC6Obk+jkkFzFx/ulBo7jJ4RRCGQPHce/hpcPJKNcwezkBhtsKUU60NwG0dMeDYUbt4alBVXIiejDFfP5uHqmVxcu5hfA/JmpZAaBQbc64uhDwRC56REbkYp4qIKEB9dgPgrBYiNyqdfAMklrE+cF/xCHDDq4RB0G+wDEn8yM6UEF//JQmp8EVJuFCH2ai4+/XGPVXBl7X7n3r+1BUASE5bY43EXSQdKfixdZH8LJYC9evWicLhs2bKa6m3atKFSwvfffx/mVMCkzpQpUyzdTv68FjMgA2AtJk+uan4GuBfQoT+eQkFWBVJvFMHJVYUWHd3w+8YbuH7JvB0XHwAj2rtixJQg3LhSgIToQiRdK8Rdk4OwZ3MislMMkiBRAFQAT7zVGvFRBYg+k4uE6CK06+1Gbcj4dndSB/iwhwLoAM8fykJmUhmVwBF1FCcB40YvBoDN2jtRSQyxXSPzIHaJAYFaq8DQqX44/GM6CnPE60vtQyK9u3AwB/kS95eqH97Ziaq5U2NN4ZFFAujmo6IHeMyZfKseF65tMgcturrg4hHxWHyWGiYqSQJf5iR4luqSz5t3dEJmcily002lriwASNT+RBpFHG+sBUBSnqjtW/dysUqKxx+XSmOHPuO9cXhbuk1zQMwX+k30wcVDOci4KYW1BID8+xOVdNfhHigtrsK/f5p34jFn9+fqpUJuRjmc3JVo39cdfs101BGIu8T6QP5O4KvzIA+c+isDvqE6+iUwvJMLfloWi+xU/ftDdAxVVXBwVmLYpECcO5QJlU6B4AgnBLd0wuUT2Tj6uz6mpDkA5PrmHajDiIeCqRr72sVc+IY4UDjMzSnFsAnWqVdZ9ii/DPf+Xf744zZLAJ/+5huT25JkAAsWLLDYHSEAlpWVwcHBgUr5JkyYUFOf2PmdOXOGSv6IEwgBQqIG5pxAjh07Bk9PT4v3kwvYPgMyANo+d3JNkRkQqoBJMSLJqSivNpG4GXlOioR0Yc7cwatP7smvxxLepS7q8KfEkmrX3PTZUqehbUQWMLTUZyl7L0t16/NzVmmeWJ9YALI+xyN1L2ugzxKksdrzsZbj982mOrzQL1L715IKmBs31wfy3isrM9hvkkDQaw4dqhcJ4LLHHrMZAJ/59luaFaouJIAkFWlgYCBVEfft27dmiy1atAhr165FVFQU/dv27dupzR+RpM6dO5emLZWvWzsDMgDe2vm9I1s3B4DcRAgPPBkAjbeIDID6+ZABsOG9OmQAtJAKTiT9G3/e6hMAv6oFAD777bc2Q6pQAsgBIFHz9unTp2Zjv/fee1i3bh0iIyMb3ma/Q3okA+AdstD1OUwZAPWzbQvM2VKnPteW5V6yBJBllvRlZAmg6VzVWppXS8/fupQAktHdLgD88tFHbZYAPrdmTZ1JAFlUwOxPjFyyLmdABsC6nE25LToDHAA+0rcv1EolxLx7hZDEL8efSqlMIGJZQaQOVymvXbED2ZKnrzkJZ13AnC1ZRhrLNqwLUGyoY21MYCc2hyxeu5bmn1VqyFKOFcxYcw4bgaaECtiS5zA3B0R1yV1ifahPCWBtAVC4trbaAJJ2iENHt27dqBcwd5HAz+PGjaNOIPJ1e2ZABsDbM+9N+q4yAOqXVwZA6W0uA2DDfg3IAKhfn8YKgJ9Pn26zBHDW2rVWSQALCgpw9ao+006XLl3w6aefYsiQITSTBwnzwoWBWb58OVUDr1ixAitXrsTFixcRGhrasB+EJtw7GQCb8OLerqHJACgDIMvekwGQZZZuXxkZABs3AH72yCM2A+AL331nlQ0g8d4lwCe8pk+fjjVr1tA/E+nfhx9+SANBt2/fHkuWLMHAgQNv3waX7wwZAOVNUOczYCsA8jsipTZm8e6lEjgbvIqNnFJIMMGbF0v6LlKU1dvYaKy8+wgXwxYv06agfhTblLcDGpvyfAolXKwvg9qmeBPeh8XuzyTsCs/Wj7U/Ympffn+k7mMkDeSpfIXjaQgq4P9Nm2YzAL64bp1VEkDWfSOXa1gzIANgw1qPJtEbGQBNl9FWdXBTAkASD66s2GAnZc1m92umpYGsbQHA0HaOVuXD5feLxJ5LMxMDkaXvtRkvS/t1VcaWOWUFLn4fWcOzsLZda2gUATgZAMtAAFB4sdoA1tW+lNu59TMgA+Ctn+M77g4yADZdAAyI0CHpqmlGDIub3A4YPTMQO79OtFhUWIDkp33knXCseS3GJgCcsTgC3y24ZhN8PvhqKP5YnYz8TPbUe1z/h0/3x8EthuwZ1gzc5nm25iY3y8oAaDxpTQUAlz78sM0SwP+sXy9LAG14lhpbFRkAG9uKNYL+ygDYcAGQSKVadHOhWR2svVr1dEGnoe744QNDNgbWNvpN9Eabvq5YNUdvKG7NRe459pkgLJ56AWWl1kkQSSaSWV+1wZaPYhF53HwGGqm+PL2kJZUe/rE6yZou07JjnwuCRqvAtk9uWF13yFQ/msaMZIGx9iLZZ9LjS4zSFUq1IQNg0wTAT2sBgC+vX2+VDaC1e1Qu3zBmQAbAhrEOTaoXUgAoHKhYeBUpG0B+G1L2gGI2gGL1yd9Zwq7U1h6Q3EehsDOb29aSvRnJL9xtpCcij+UhM8mQEk9sA/Hbi+jqjFFPBmD3t8mI+sc6GOo0xB2jnw7EwR/ScEiQy9jS5iX5ZKe+1QwJkUVY99Y1S8WNPifSv2c+awU3HzWWvRiFrCT2PMikoe6jPDHy8QCc3Z+NX79MsOrepPAr69qB9OGrWVeslgLe9ag/eo7xovB48nfzKdDEOkQg7qHXwnD81wzs+S6ZOYcvac/NV40nPozAgU2pOPlHptm6YtCncVCgz73eOLsvG1m8lIusAEnMWflh+FjVuSzlWJ1SmMPFiIR+Ya3PD/tC5ocl/Ex9hoH5ZOpUmyWAszdskAHQ6rdF46sgA2DjW7MG3+OmDoBqjQLuvhoqZRFeYk4kpJzW0Z5K31r3cMWlozm4dDTXpL4YAHr4q9FrrDc6D/HA+b+z8RujKpW0Z6cAhSACjjlpZfhqVpRJPmOpTUXuPWleGM3p+92bMYi/rM9py3p1HuqOEU8EIOZ0PrZ9bJ00jEjwhk7zh7OHCvs2pODGpULW29Jy7fq7Yfh0P/zzawaO/pJhVV0C2/e9EgKVWkEhzlrV98AHfdBzrBeFqb3rUlBVUc18fyKpnb2mLUqLKvHTknhcP1fAXJcUvP+VELTq6Yrr5wuw7eM4o/zX5HMpyOk2wgN3PxGIyH9ycWx7OhKuSK83vy1iMzn4QT/EnM1D1Ik85GaYB3bh/Tl48vBToyi/EiWFlXS8rCFYWOBL2F51EwfAj6dMsRkA52zcKKuArXriGmdhGQAb57o16F7fSgAkMKPR2tNk70X5FZL5fvkSQG9/LTz9tXD1UsPNS420hGKcPZglmZuYP8kRnVzQZYgnAsId4Oqpxvp3r+JGpCmMiAFgRBdnTJ7XHEqVAke3p+GPNeZVimIA2HGwO8bPCkFBdjm+ejHK5EAX2xBce8QercNANxz+KZ3CkDWXztkeMz5qgYuHc3Dg+1RUlrODDAdh4V2csG9jqtVSNFL/3llBVOJ55YR1UktujM9+0QrfvBqNkkLr1MekvouXikriVrwcbc2U0bLOniq06eMKF08V9qxNtrp+3wneIOv+y2fxSI6xzu6SSF3vmx2C1LgSfP/edVTpearmklT72gGPvhOO4NaOOPZrOnaTvSqx5MK2Og5yx8QX9bHddq9NxOGf00zGLgaArl4qPP5uS1o+KaYIl//JwZn9WSYwKGyQA8DQ1k5o2d2Vgif5yckoQ/J1A8BaCv6sdbBHNapRWlKFqkrTQUt5AbNAaH1KAGsLgMI5lp1ArH6EG3wFGQAb/BI1vg5yAPhwnz40E4hSqcBDs1rCw1dDD6Kykkrs2hCH5LgiIwATVb8qFJj4VDMMuDeASmNS44uwdlEUEmIKJQGQP3PDHgrCmEdD6J8O70jB9pU36AueRZ2r0igwaIIfhk8NRElhBb5dEI34KAP8WcoSQg618c+FwidUh9TYYmx8LwZ8B0RLHsLkIJ74nxAqNUyMLsalI8b2e5Y8hbuO8KCSw5+W3qDQXFpUZVUKMqI2LsiuwMGtpgc5y+586PUwHN+RYbUUi2ubqDOJHV1OqnXq37oAQNLGS6vb4LOnIlFphQSPu7ejmxKPfxCBL56NtErqytUnavv+9/tgzesxVqmBSX2PADX6jvdGZWU1flvO5nzDQYx3sAY9R3ujeScn/L0llUoxWQCSq3/XtAB0GuyBooIK/Pz5DSRdLZKUOvLhyclDiRnvtoJXoBan92Vi17fxKMipMKkvpjbuNdob454Kg729HU7vz8CmT2Nq1o4v9TM3HvLlbsorLdCqixsqyqsQfTYXy964WAODQrUvvw3SH2c3FcZMD4OLh5qaeZSXV2H9J5dRmFdBixIA/O7IkVuqXuXevx9OnmyzBHDupk2yBJDl5dbIy8gA2MgXsCF2n3sBPTNqELr280XH3l5o18MDji4qXDmbg/WfRCI1Xi/RkIInB2clugzwQvehvvAO1MLNU4Ojf6Tgp+XXUVail+ZI2QCqtQp0H+6D/vf40Rewo4sSh3ak4vguA8j8v73zgI6q6OL4n/ReIUAoSSCV0IugSFMUCwoIioh06SJgoymCSA0IKL0ICCICAqKA8im9Se8lQIA0WkgIhBYCfOe+uMlms+/tvJdsskvunJNzlJ36n3lvf3vvzFwlACRrXZ2Xi6NR69KIPpAquaZO7klBwrmcLjGlMdR6yRdN2pbG1uVXEHvqDm4nP8T9uznNMUoAV7m+N5p2LI2VURdx+cI9oxChVJ6+wF/tXgYLvziPOzczv4QMdVNaQ3T9SquPy2PuJ2eRka7O8kf1uvvYodPoipjeV53bWdcnsvgOmBeByd1OqQag/ALAjqMq4M+5ibgWm9vlL/L8tR0SgP1/JksucC2Jyp/afQtHt+SEMFN1kbXKxq4Y2n8ZhLMHbmHPWtOWX32oIu3dvOzx7pAgRO9PxdZfrmY1KWdB1JWnsmQtd3SxxRu9yuH4jhRsWnZZFqINrWfk8m/cphTSUjPwzCslcPDvJGxdfSXLNUwdUdo3GFLdA2/3r4DY6DSUD3XD3o3XsHvDNdy6YXzfbA7LIJ7gxbfL4PXOAUhNTpfeHQc2X5f+blyVt8Tq+kPvudZ9KuLZl0sh/cEjnDmUguP/3sCxf28g4dLtAgPA8e++qxkABy1bZlZINbV2+fOCUYABsGB0LlKt6ADwwtmPEXsqTXr5kRWCfl3vWn8lxyZxOXgKre6FzkPCcWz3DRzckoQLp26hcj1fHN6eJAt9+nXZ2RfDoLk1cPZQKnasvYzLl+7Dq4QDbl5PF7Yatv2kgnQo5O+lCUi5kg7DDe7GYEofxqo29EaNF3yxZnosbifJXyMiB3Bu3nZ4b0gFrJh4EanX1Zen/r07JBCbfrqSC15MHTbRjY0sSEkJDzS7X+kOPrrSRO3+O137Lh62aNyulKbrY3R10GncjfMTs340qH0Yn21RHJdO3kHiWXVuWF07oXU84OZlh4P/y3Rlqk3epRzQ4G0/rP1e3SEWHdTQXsa3Pw/AL+Mumtw6YAyq6IdUm08CsOu3a7h4PNPybQoA9cfo6GyDlzuT9fwR/lpk3BJpzH2qe95oCwL9CKtYzR3TBp7Men+YOjhCz3vytQfSlo9nXyuJOk1LYNbQE7gam3seje01LB/mhru3MmDnWAy1m/ihZuPi2LwqQfozlgzHEFHbG8VLO+Nq3B1UruuLKnV9EXfhFuq9ONuscKV7/45v2xZODg5qlxvup6dj0C+/mLWPqjvFBcyiAAOgWWQt2pUauoBzWOn0onMYqpQT4GykF73kpjUoIwcvhv/u4GCDjP/2q+nvB9Rv17CM/v/b2hXLslgoHe6Qq4/2KT6R2XYmGjFEHzpFoc2US9jY6hStu2ivbMsffX5e6ZJjtMWAx4+NW4BFL3imx1i39cGwjFy/9f+dTmPLueFFDovQj8KHD7Kt7yJlDGHX1h54+N9VRMJj0NvvYePwBHP+3m5WuNK9f8e+845mAByyfLlZ+2j5T1LR6CEDYNGY5wIdZX4AYA7g0giAOayLMuCpBID6omkBQFN7+4xNipYyhvUwABbocreoxswGgCqtfjpRRC2FIgAoCpqK18Xk48lfLQBYkHsA8wqAcXFx8PDwyFrfjo6OoD9OT48CDIBPz1xazEgYADOnQgvMaSnDAGgxS7/QO8IAqHzFTX5e/WLpADiGLID29qrX5P2HDzF0+fJc5fgUsGopLb4AA6DFT5H1dVAJAA1HI3fhsyII6VnzlA6B6LclZw1Ucn2aOt2rq1+kD1rBTsSaJ+q+FalLabWJtmN9K9bye6wF7PRHpWQ9088n2o6p/XfGFM2rBU8YuPRuojY89StiaTTMI3fyV6k/cmUK0gI4+u23NQPgsBUr+BSw5b8W8txDBsA8S8gVGCrAAJh7TTAA8nOSFwVEwUyuDQbATGWKEgCOatNGMwB+uXIl7wHMywNrJWUZAK1koqypmwyADIDWtF6toa8MgLmvfRGBuaJsAWQAtIYnu3D7yABYuPqbvfXRo0dj3bp1OHz4MBwcHHDzZs5LhOVcNSNHjsScOXOQkpKCunXrYvr06YiMjBTqLwMgA6DQQuFMwgowADIAii4W3fv369atNVsAh//6K1sARQW34nwMgFY8eSJdp427Xl5eiI+Px/z584UAcPz48SBwXLhwIUJDQ/HNN99g27ZtOHPmDNzd3U02q3sBvVevnhQJRGmPnOEVL7rKlfbfiZSheoT25mk4YSzqzhWJMmIopug+O9E+mJys/zLkdX+gfjuyV9zYQFM0DKqb7oK7d9sgnpng4Ogy6tvJ2ZdgCxaTsuWlXboMWe4aIF0f8gp2hmMRdfXqlxM9qSunm+KpW739eEptivRBqR25EG+GfZa7+kWxbr2TwyLh3qhN/T2A+nXTHsAlu3ebFa50798Rb72lGQBHrFrFewDVvCisNC8DoJVOnNpuE8wNGDDAJADSC87f31/KO2jQIKmZBw8eoGTJkiAw7Nmzp8mmGQAzJXraAJDuRfQp5YDr8cajKRiDd92/ObrYoPLzXjiwUf1lyBTNolnX0tgwx3j8ZFMLskX/clj7fZxJGDNWT4M2fjiyJQW3FC7ylms/pJY7bl5Lx/U4eb3kwIMuASd20o/eYmqc9DkDIEG3fMznogSAX7VqpRkAR65enWu58SlgkSfQuvIwAFrXfGnurSgAxsTEoGLFijh48CBq1KiR1V6LFi0kS+KiRYtM9oEB0LwA6ORqqxjRQRY8iwH1W/ph/19JucqbsgCSNav1wPLYu/6GFNJOKRlrv3mfMpIVbuuy7HBiJhfSfxmqNvZG/bdKYOZH0aJFsvI5ONvg4x8isGTEBcSfyRnCT6SylgPKSdEgNv5wWSR7jjxhz3igfms/LBx6ToqBbSzJASBF3+g0qiJ+/Oq8yegd+vXqAJDAdffa60Lh+wz7QOuLonaIwiRbAHPPrCVYAL9s2VIzAI5as4YtgKqfeOsrwABofXOmqceiALhr1y7Ur18fCQkJkiVQl3r06IFLly7hr7/+ytU+WQjpT5cBXCNHAAAgAElEQVQIAMuVKwcRF7B+Zfl5JYxhJ+XcwXIRQqi8iAuZ8snBk1z5oCpuiDt9JztKCYX7kEn6dRAUNG5bCsmXH2D/xhtZJUzBG2Wksm/1D4CdQzEs/eaC8BrS1d28V1nUaOqDiZ1P4F6aOlcsWcIonuy25Vexdbk6ACTw7DU5FN4lHTGu/THgsbxWxgYVXs8DrSmM2Zpr2PyTurapvq7jg1G8jCO+630Kd2+pG3dobQ+0HRyILcuuYPvK7PjTouL3mxkuWR5/GhWTA+REwOyF90qhYg0PLJ9wQQojKOpqprrLhbmi3hsl8NeCBNy6YTwEoZLLtkJVd1w6mZYraodo5A3RK2Zk+yBz2TPpLnJwRO4KFyqv5AKWK1dYLuC8AmBqamqOi6BF1y3nsx4FGACtZ66yejpixAjQIQ2ltG/fPtSuXTsri1oATExMROnSpbPKd+/eXfpF+Oeff+ZqVq4/lgqAjk62sHewwd3bGVADgLRdMDDSHeG1vbB9zRXcTsn8chQBQHt7G1Rr5IPn3iyJM/tv4n+Ls92ZIvv5Kj/vjWZdykjxiKf0OpEDCEwBoE9pB7QbXAElyjnh95lxOPS3uBuW6q75kg9e6VYG99IyMPmDU6qeGHIbUxxZioerBYTKhrngzb7l4Opph3mDziL1qnxMZGMda9yuJOq85ovzh9OwalKsqr5T5g9nhoHG8M/iyzi61fQBKv0Ggmu6o93QIFy9eA9LR19AWoq6fYjthgUiuIYH9q5Pwl8/ZK8XEQAsXcEZ3aNCJevlykmXEHPsttDYdXV3/joYZUJcsHXFVexee00R5vQrpvKRz3nhtW7lsGfdNez7K0myJhrClxyIUbi2F9r6I/7cHUQfTM0Ku2YM3ozV4eBoA1tb4G5apta57vQT2JP4tADgFy1aaLYAfvPbb2bdpyi0GDmT2RVgADS7xPnfQFJSEuhPKQUGBsLJyUk1AGpxAauxADo62sLTxwG3Ux/iwb2cFhUlC6Czmx1Kl3dByfIu8C3lhG1rE3ErOT1HnGA51yd9gVeu64MKlT0QVMkDGQ8fY97wU0i//1gIAAn8XulYDnVeKgE3L3ssnXAOR7ZlQ5QpAKT23/k4CFWe90FS4n1M639SGOBoTI7ONnjnsyAJBjYuSsDONTmtSaYAkL5Ue04Mg4uHLWYOOKPKkkV1+/o7gmDkxM5UbF56RfWCrvOqL3xKO+LYthQknrunuvxbA8tLZS+dvIOM+8bj0SpV2mdaGH4YfA73VVouyfro5eeAtkMDMaPfGdX9Jt0q1nBHyQAn/D4jXnX5em8WR2gtD+z/6wZO7krNKi8CgJS515QwuHrYYe5n0biZlC7Uvq5uslJ3/joEyVceYMEXZ3NZAk0d2mg/tCIi6nohMeYuFg6Pxt3bj3LAmJJFslSgM/pERUj9Pb47Bb/NuiRBpAjM0Q+kNv2CEBDujosnb+H88Vs48W9yltXalAWQfhg2fstf+rFzJfau9EfvGV0yZQGk+N8lSjvh5o30rPdbYVkAh775pmYAHLN2LQOg0BNj3ZkYAK17/oR7L2oB1B0CGThwID7//HOp/vT0dPj5+Wk+BOLp64APv6kG/wBXuLjbY+3CGKxdECNtcs/hJpWJ1+vsbIfPZ9SEf6Cr9GKeNfw4zh7J/EKUOxEsffafa5Ve6j1GVUJYDS/EnU3DjEHHce8/q4QhNBqzCLp726P9Z8GoWNVDsvyt/yFOVndjMOZfwQXvDw3Go4eP8dvM2FzWGFOHRSKf9ULT9/1xfGcKtq+6KoGrmtPCjd4pCd/SjtjyyxUkXzEOAkr1tfyoHOJO38UBPbezoQBKEPr+V0GS6zfulPo9eNRO96gQrIi6JB2o0JI+nB6GeZ+fy7JEqa3jkx8qYXKPU3icoR4+aT9drymhmNrzlNAhFEO48w92liygsz6OBgSa14cNOrATVscTAZFuWDYup9tfBCIbtS2F8uGuiDtzB5t+zrkH0pSb1sPXHt1GhcHesRjWzYvDid03Fd3QhvVVb+SLtp9UQFLCfSwZdxaXL95TLq9/UrfYE3QcHIYajYrjxpX7mDrwKG4lZ1qORdzQPiUd8OH4qvAr4yxZEsf1OoDriZk/XEROC9dtWhIdP4+Q5jsl6T7mfH0cF07fynyXZmRg6Z49ZoUr3R7sIW+8oRkAx/7+u1n7qPYZ5PzmUYAB0Dy6WkytsbGxSE5Oxtq1axEVFYXt27dLfQsODoabm5v03+Hh4Rg7dixatWol/T+d9qX/X7BgAUJCQjBmzBhs2bJF9TUwHeo/i2calUbjFmVRsbInaPfW/DEncHDb9Sx9lACQLDA1G5bAq+0DkZH+GD6lnDBt0FEkxGQfQjAFgDUaFscbXQNw5lAqivs74cexZ3AnNdsVZwoAq9T3QcseAdi88rLUh/1/XweeyO9DMwSh8DqeaNk7ECunXMCNyw+QasQSowRftJ+qVb8ALBh+Fil68CYKgOTGe/vjQMz+NBr378rvYZOrz7uUAzp8VRHT+53O5QbUX+RyAOjkZivt4RMFoFwPTjHg0x8qYVK3k0IAZezByysAdh0bjLXT4pCUoHz6We6hbz88SNoDGHtS+fAMlTcGVu99EYSDfyfj9J5sK6BcW4aAQr+BOo6oiKNbU3BoU7bVWgQAqS7aO9plVAgOb0nGv+uyn1tTAEj98yzuAFv7Yuj0ZTD2bUzCttXy1mNj9T3TrIRkSXurTyB2/XEVm1clyq4Bwxi/ZHXvOjwcly/cRe2mJbBlVSK2/3YZDx9mnxCWtQY+fgz60ffh2CogrnTztMc/K+KwY/1lPLgv/wzpu47Lhrjhw9HV4Opuh6vxd7F5TTz2/H0Ft28/KDAAHNy8ORw1xAJ+8PAhxv3xBwOgxXyLm68jDIDm09Yiau7cubPRk7ubN29G48aNpT7SlzfBHuXVfQnRHsPZs2fnuAi6cuXKQmPS/QK9cHYgki+nSy+/h+mPkZaajssXc1qB5AAwIMwdXYdG4FrCPfz5UywSL9yRXsrkQtWHDTkApC+uvmMq49GjJ1g1MwZXLt6DvaNNjj1FNBglAHyzewAqVHbH0qhzOb78TVnsdCJVfs4br3Qqi0WjzuKGAjzI1edVwgHdx4VhyejzuHIhp+tUBADpy7/XpHD8tTABF46lKc6dXH2vflBGssLs25B96MRYRXIAGFnfCxWquWlygVI77j72aP9lEGYNVH8CWNfPvAJgi37lcGpPKqL3ZVpx1Kbar/jCs4SDtI/QVDIGQrQP8uXO/vhhyDlTxY1aqDxL2KPr6BDM+vhMlitUFACpQRcPO3wwOhTr5sfh/OHMvYQiAKjrLN2lSBbwmGO38L+fjF/lo1QfubFb9wuCs6stZg87JUGZYTIEQPqctj48yngCd28HNO9SHoERHpg9/ASuJ9yXiisBIH3u5GILVw97ad9ts3blEVHHG7/OOo/9m40f6DE8+evuZY+w6t64lngPTVqWRdVni+OfNZfQ5oOfzApXuvdvXgGQ9nx7eHhkSe3o6Aj64/T0KMAA+PTMpcWMRPcC6tO8Ee7eNNjnZ3DiVQ4A6eXp6euI+PNpuSFNrw4lC2DFSA9cOJn5hSUHOEoAWCrAGdfi7+PxoyeaTgS7uNuimE0xyeKoBGxKn9HpV2OuTxEApHF7+NjjtsDhA7n6CKQJoh89VPY/yrqAi2WeQE6/J383m6mFS27Ehw8E/J8yFdHJ54z0wi1P0CLiQpYDIdELqeWgxt3bLsc6UAOAJCv9+KJDUwRUagGQ8pNFjmA++apxK6oIUJYOckZCjPFtBMYA0HA5lAtxQ8KFtKzT96YAUFde1zfvEo6ga4UuXzLeB7mrX3Tt0D5m2t/41awNBQKAg15/XbMFcPy6dbmeJr4H0NSbyvo+ZwC0vjmz+B7rAPDdZ57JjASit7dPFIREy4hYAw0BUPh6F5k9iYZjkBuTyOlew8kUtS7qlxOFQVOHRYwtLNG687ootfQtr23md3kRqMqPNkWvdNFvS7Rv+XGnn367pg6LGNNDZJ+eBKEyFz4rlReBPiWtctRt0L6pAybU54LcA/jZa69pBsCo9ev5HsD8eFgtvA4GQAufIGvsHgNg5qwxAIqvXgZAca0YADO1YgA0vmZ0799PX31VMwBO3GBeK6X4auec5lSAAdCc6hbRuhkAGQDVLn0GQHHFGAAZAJVWCwOg+LNU1HMyABb1FWCG8SsBoGFzIu5Yw31++mUUrWwCrmdhd66MO5jGIzIGLdZAw7r1tRMFJi0uXNG65ZaOljbNsAytokotMGc4MFH3rn45kXZFXaGi9YrWJ+s21hDj11ArJReuLq9hP0XKUFkR13VBuoA/fuUVzRbAb//806z7FK3i4SwCnWQALAKTXNBDZADMrTgDYEGvQutoTwTETI2EAVAMvnJBmgxQPi0AOKBZM80AOOWvvxgATT14T8HnDIBPwSRa2hAYABkALW1NWmp/GAAzZ0bEeia350+0fFEDwP4vv6wZAKdu3MgAaKkvjXzsFwNgPorJVWUqoAPAd+rUgb2dHWwVrm0RuZ7F1GXPOt3z6g6meoTcuXl0B1M7psLHmVpLWk4L69epxU2bV9ewqTEp9Y8uBafIClqSjV0xoStYjNVtqt38ADiRMZnLykdti1zBotTH/Dg5bC63r2G9cnF+lUK86Y9d7qoXQ33k3MbkAl62d69Z4Ur3/u330kuaAfD7//3PrH0UWfOcx/wKMACaX+Mi1wIDYOaUa4E0UTDTUndeAdDbzxE3r2sLx0b30NE9cInnxWIB59jnaQPUetkX+/9Uvoxa7kGr38oPO1cbv7zX1MMZXs8TCdF3cfu/UGJKX/SGnzm62Ej3vlEMYy2JLgLX6c0AmFtBEashA6C96qVHkUAYAFXLZpUFGACtctosu9MMgOYDQIotSzGUHypcrCxnqaPLfENreeDA3zeEYwnrVpqjsw3aDqqAxSPPa1p873wWiIN/38C5Q5kXc5tK+gBY6TkvVG3kjWVjc8azNVUHfU4WvE9+iMS8QWdx86p6eG3UtiTs7G3wzxLjUTyUrF+unnboMioYMz8+oxhGT24crT4qj20rrkohBNUCYEhND9y++RCJ503HXzZWt2dxe6QIwj5bAE3Aqd5ew4K0APZt2lSzBXD633/zPYAiLxgrz8MAaOUTaIndVwJAw/6KXPic66SuwOle6ctfIGKI8MXUenVJkS3uZ/sjiwleGE19KhfqCkdnW8QcNQ5CSm7WoErueLlDGcwbdkaCQF0SsRr6lHJE55Eh+HNBPE79azqmrH7dBFHvDakAF087zP1cXUg2Gk9obQ+8N7QCfh4bgzMawqn1mBAKAt/v+p5SvdzLR7hKYdA2zI/Hv+uSVJd/+5MAVKzugck9TuCBymgmHr72+HhuJDb/fBlbV1zNalsU5pr3Koegym6YOyga9+9kR9QRcTt7+Tngw6kR+Gn0eVw4niYMkLq63x4YhLOHUqUYwLokeqlz8TJOKFneGSd2p8iHW9NfwAazYu+AHM+XXPsiFy8bTri+C1fU9Z1Xt69+HwoSAPu8+CIc7exUr/kHGRmY8c8/ucpxJBDVUlp8AQZAi58i6+uguQHQzo6sYE8kCBJ1hepAk9yYgeHuOLQtEwbUAGDpQBc0bFUaCefvYMfa7MD2IgBI7rxXO5VDaA1PjPvgMB7eNx6azBgAEl++0NZf+tu8/DL++TlnPFVTAEhuyE4jQqRwXmM7HMHd2/IB7XMBerFieLmTP+q3LImTe27il/HqrHAEu32mhIOAZHnUBZzcLQ6f1JeASq7oNDJY6taY945mhfESfSpe6lAa9VuVxPnDt7D46xjRYln5ek8OQ4myTti4KBF7/riuqrx3SQf0n1kJGemPJSvgjcTMMGiiANiwTUm82N5f6vuSUeezYuCKACC18/GcSGnOl0+8IM2dSNLVHVHXCx2GBePQlhtYO/OSBL+iAEjt9ImKkKyea+ddQsK53FZIpTFUrOKGhq38sW11Is4dyY6/nMudKwORYbU8cSv5IRJicrveRQAQNpDCP2aBp54FT6nfItfFFCQA9nrhBc0AOGvTJrYAijwwVp6HAdDKJ9ASu28MAMmA5lfGBQGh7rCzs8GujZkuNRELoK1NMZSp4Ibwmt7S36UzaVj340WTAKeDKfoSrPNCSdRqXAJlg90weeARxEanmSyvAyuCxncHBiOsphfiotMwdcDRHAHpTQFgcX9H9BgdAarnj/mXsHXVFVnwNAaAZUNc0fmrELh52iOq+1GkGLgyTQFgYKQbOg4PllyJMwaeVrVkSPvI+l544T1/nNyVgr9lXKFyldo72uC5Fn7wK++EA3/dkKxRapKzmy3e7FNO2kd3dGuyKnildgg8O42oiOUTL+JyjNj+Q/3+hdf1RLPO/pjzWTTupYmDs67t51v5wdndDr9Ni82yaokCYLUmPnjuTT+c2ZuKbb9eyYpnLAqAb30UgMrPe0tW33/Xi8Grrm4b22IYvKAqXNztsGxiDI7vlLfmGRtPxaru6DEmAg8fPMaCr8/g7OFskCNtFN3Gjx+j7cCKqNusJBIv3MHK72Jw8dTtXGXk6iDX+6CZNXD/7iMc3Hod+/+5jmsJmXMvAoDVGxZH4xZlcObwTZw+mIKYkzezXPgiAFiptg88fR0QG30LiRfvSLG0dcmaADA1NRUeHh5qHlfOa2UKMABa2YRZQ3cNAbBSdR/0H18Dru72iD17GxMG7JP2J4kCYPlgdwyaVgtOLnbYs/EyFo47neUCFbEAUhD3QTNrwsPbAT9POYud67KtdyIWQL+yzug1ppJUfkr/o0i8kNOiYQoAK1b1QNuBFXAvLQPTPj0pfSmqiR9c5+XiqPVicZw/cjuX9U/SUM89bWx9NOtUBpTlyLYUXLmgDoKo7jYfB+LswVs4sTNFtQWOgLbjiIqSGzTujOn9aMb633NiKJZHXcwFvqLPQv8ZEZj9WU43qmhZyvf5osqY2PU4HqvjP6kJ2jvZb1oEJnU/kXWKWRQA7eyLwae0I975LAjTPzqVteZFAZAsvwTeNV/0xYLhZ4WGrF/38y1Lwq+ckwQ/v82MVWUBpMY++CYMHj4O2PXHVexal+0CFwFAAv9Bc2rAwckWC0adltzRohZAykfbJQZMqiqN+bvPj+H8sUwAFQFAKv/SO+XQpnem5Xn2iGPYvznzEJEIANraFUOvEVVQu1FJPEx/jKVTT2PTmjipfEECYM8mTaRY7GoT9XH25s18ClitcFaYnwHQCifN0rusD4DV6/rh7Z6hKFnOBUmX7yFq4AHcuZUJfxK8mNg/F1HLB+0HhOFWSrrkSvt+yJEcG+pNWRDJYvj+p2HYteEyfEs5YcnEaNk2pf4YwFRwVU90GBSKX6fHgKwiR3coH6AwhMHASm7oMCgEC76Oxu2Uh9KfYVICuDLBrug4LBgzPj0lubWydDMBfbp8fmWd0HlkKL7vp7yHTengSM+oMEzudULxIIPcGMgCOGB2JUwigNJ4jcugH6sgqsuxXAAmei2NFgDUh7SeE8OwYuIFJF9Rf4iE5qHLNyHYuCgBCWdNA7AxwOjydQi2rbqC84dNH6AxBpcfjAnFrt+v4eTubDewCERSHglmJkRg59qrOLwl+xS2yP45srw/fvwEvcZGYNvqK/h3o/xJbGN3/FV6xhu3bqaj45Aw/P1LPHatz/7hZvgMGRtPo5b+8PC2xzNN/bB+8SXsXH9F6MobHSQSAIZU8YJXCUf8viAGOzdcxqPHeq5hhX2MxYo9QY/hVVDlmeK4nZqONQvOY+fGRKSnZ2D5vn1mhSvd+7d748aaAXDuli1m7aOlf4cVlf4xABaVmS7AcepeQHu29ETxEi5YMfssMh4+Ruy523igt5ldCQB9Sjih7YchKFXOFUsnn8HV+LvSr+kH93KaYeQAkKwnb3YNQuV6vlg45hTizt2RAI729ojeK1j3ZT+88n55zP/6VI7TlIpWRz2gJddtly9CsXB0tOKXv1x9zq62+HByJFZPv4jzBodGTFn9dNPdeUQIjm1LxqHN2Zv5jS0FOZh64d3S0knaf5YaPwVrCkjpNGrNl3xV7x3U1evibovuE8IwtffJXN0uKACkE8wHNt6QLLBaEu3lI17XPwgiV48xkImo64maTYtLBzpMJWNgVirIGe8Nrij9CHiYngkwogBIeb39HNBzXAQWjIjG1dhMC7IIAOr66uFjj55jI7Bxaby0p9BYkrvkmfpJ5T8YEYHoI6n4ff7FHAegdHXJjqfYEwkCOw0Ox707j7Bk4pkcP0CNldcBIM2Zt58TbG2L4d2PQiV3+JJvTyPuXOY2BkVr4OPH0nNTtW5xXLtyD216hKBUWRf8NP0UBn+7zqxwpXv/dmvYUDMAzt+2zax9NLWO+fOCUYABsGB0LlKt6F5AYwa8hhP/puQYu/6l0EoAGBTugeDKXti8Jh5QsBzJAaC9gw1eblce//slc++VyIlgqT96lrXnm5fC8T3JuJmULnRBNJXXtwCS9Y/avXDitvBhE32xXD3sEFLDE0e25YY3EQCkoZDr+NCmG0a/NPXbkoOpClXdcT3uvlHLpX55uf74lHKAk5sdEo0cBBB5KMiFWj7CTXJBGyZRAAx/xlMqT65M0aQPOGXDXHD7xkOkJuW23orUR4dBXL3sEC/gAjcGFfSbgvbyHd2W81kyClIyVikqf/ZAatZJZjUASO3Qnj7atnEt9r5qAKQCdAgqoJKbJgCk8g6ONni+RWlsWhFv1JIseyL4P7MzwdgLrcvi4NZrSL6aeRhHP4kc4Kj+fHHY2ttg36ZMd7YpANTV/+i/OalYyRPhtb3wXu9lZoUr3fu3a4MGmgHwh+3bzdpHkeeG85hfAQZA82tc5FrQvYDa1KolRQJRsrjJRQkR2ZtnKKxhOyL77EStgUqwI9uOYMQQEZBSAz8icCiSR02bWha5lj5oaacwyogAlpp+ie4blIMapbbUnO41Vo/IvjjDcvkd1i3HuPX2GijpJgJ9SqCXa0+iXrs66DMc98OMgnMBMwCqecKKZl4GwKI572YdNQNgprxyh0PoMzn4EYUixbB3AvsDRdvRXyiiFjfRxaWlD6J1F3Y+BsDMGZCFS4UNoTnATGGfnSmrH7VflAGw8/PPa7YALtyxgy2Ahf0SKYD2GQALQOSi1gQDIAOgyJpnABRRKTMPWwBza8UAaHz96N6/HZ97TjMA/rhrFwOg+ONptTkZAK126iy344YAqN9TQ5er4Z5AXV5Tp3uz8glE+1CyuBlatUydSjamuhZrnqmrY9S0Y5hXzlKnBbi0lDGn1dByV714z7TAnH7tWqyLSmVE+yMLXApWOqXDHXKKaWlH5HoXJYtkfkb7oHb0XcD6dZMLeOWBA2aFK9379/1nn9UMgEt27zZrH8WfFs5pTgUYAM2pbhGtmwEwc+JFTwvnAGQF960ojDEAWvaDJwpcagFJadQMgJnqiFgNRfc06oOdofaWAIDv1aunGQCX7tnDAGjZr5F86R0DYL7IyJXoK8AAyACoWw/5vW/waXjSGADFLlQ2nGvRU7ei+/5yWFXzMdybpVgAGQCfhreFecfAAGhefYtk7ToAfItOAdva5rxCReFkrIg7WMmyZmgh0+LOFbkuRtMJZQXLnpbDIqJWQ/18ojAmamnU0gdzPhCi45PrQ17BLD/Glt/uXV2fRMcm2n5eD3eIwl1eoU+0fH5b/eTgsiBdwO8+84xmC+CyvXs5FnB+PNAWXgcDoIVPkDV2jwEw96xpcQcrwa4W+BIFJLm+0p18D+4Zv5TRFDTSZcJ0j1zGfxcRq1nXxM50F+Clk8pxhOXGF1zdHec0RtEoUc4Jd1IzcPdWhpouZ+UtUdYJ1+Mz784TSfogoqR3DsBQ2IPHACh/96M59/1ZAgC+U6eOdA2X2qS7qsaw3FdffYURI0aorY7zW7ACDIAWPDnW2jUGQPMBoGdxB6Qm5QxJZgq+dL0JiHCX4hGbAhJj9bl52aF+i5L4a1GC0WVpqg/vDamA32bESjClNoXW8kBwdQ+snx+vWFQOAPtOicC8oWfw4K5yLDpjVrLqTXzgVdwBW1bIhyFT6lTXb0KxaMRZ4Uuo9QGw7qslkHDuLuLP3lEctzHrFYVwq9rAB4c2Z0beUGsBNLbORKBT9H4/wwGZ6+BHUbYA6u5hVfu86ayUcXFx8PDwyCru6OgI+uP09CjAAPj0zKXFjORpBkAKMefqbi8bGUPpRLCtfTE0bFEa23+7jIyH2ZYJURdw/TdKwtHZFpuWJ+aYa1PwRZkpLF3XkWEY2/lwjraNLZrcrnSgy9ehuHLxHtbNywxqb5iU+kAWOIpH/G3PY5ri6VI4O4rksGD4WdUA6FPKEQNnReKXqBgc35kdC9dYRcYgqVmnMqje2BcTux8Thjj9ur9YWh3bfr2Mbb9mRo8wlfSBpUYTXzRt749pA0/i3u2cIRBFYOyjKZWwdfUVHNmarBoAI+p4gf7WzL4khU8UBTYdADZsWRr7/7mOu7ezgV/UzergZAM7exuprCjAqQlNpxvL024BzCsApqam5gBAU2uXP7c+BRgArW/OLL7HhgCo32HRfXpyEULsHGzg7euI65czY5KK7sej/YD2jjao93IpJJxPQ8zJzNBiiq5ZvX17tnY2qPOCHyjA/PefH8P9u9lfyCLXwJQNdsV7n4bg3JFUrJp5QbFdfb0IDsma06p3IJ59tSQmfXgUiTF3hctT30oHuaDHmHCk3kjHlA+PG10/Su7hZh3KoMk7/vjfTwn4Z1k2fIqAJ/X9o+8qoURZZ3zf/wQuX8icN1NJV7dfOSd8NC1SAu7xnY+aKpbr8+fe9MNr3crh8OYbWDnlouryHb4MRlhtT6z49oIEUqIgpMv3zepaUgzryX2O49YNdaHkQmt7oPPwUJzefxOLvj5rMpwftakPQu8MrCDB688TzuHYzpxh5FxyZNMAACAASURBVEzt9bNzKIYRP9dC3Jk0/Dj2LO4YuMCVLH3UjzovlcDrXQKw4rvzOLZbnW7Ut96jI3H+WCo2r07EwweZllvDU7dy0Ofh64B6L5fEzvWXpW0H+kkE+tx97KU276bltlbrl5eL9mHYV32tHz56hFUFdA2Mbg+22kVfEH1U2yfObx4FGADNo2uRrtUYADq72iGyli+q1SuB7esTcO5EpjVG7qCGPgDa2dsioqY36jYthdCq3pjQfz+Sr2XG8xQBQB8/R7zwVjk8/7o/Lp25jamfH8maHxEADK3uhbf7BqNMBVesmH4eW9eIWeB0dVdv6Iv3Pw+VrBpjuh3Etfh7wgBHAFi/eUm81SdIimE6usshk+PWX3y2NsXw8vtl8UJbfxzclIRfvo0xujblAJCg+c0e5VGlvjf+WpyA3euuCWmny0RxcF/rWg5kiVs7KxaXTinv49OV02lXNtQVr3cvh5vXHmDN9Esm3biGg4t8zgvNe5THtpVXsPuP7L6LPqAvve+P2s1KSAB47lDueMRKIEXxqHtOCJeaWvX9RSSevyvarJSvbJgruo4IQWz0Han8zes5Xf/GKtOHoudblMQb3QNwfFeyNO8UE1uXTAEg5es4LARVnvPBnj+vYuW0C3ii50E3BYBkKR++pDbcPO3x109x2PBjbE4QMxHho2JlDwycXA2pNx7g9wWXsOevq8IASGNr1b0CXmxTFnv/uYZNv8Yh/nymG10EAG3si2HQ1Fq4nZKOPX9fweGd15FuBELlANDHzwktOlVA9LEUHPs3CclJ2XtACwKudO/fljVqSIfw1Cbq45pDh/gaGLXCWWF+BkArnDRL77IhAL72bhDa9wsHWdF+nn4avy/OhhARAGzUvCy6DonE48dPMPmzQzi+N3NfEyURAKz6rC/6jqmG9AeP8HWXfbhxNfuFLAKAFSI90H8ifRml45tu+3O5UE1ZACPr+aB17yBcjb+H2cNOmuy3/vwSADZsWQrhtbxw6XQa/vopcx+ciPVNl6/5B+Uli0bMsVs4ezg3xFA+JQtgu88q4OS/N3Hh+G3cSs62qIj2oduoUMl6GB99BwoRwHIsa/26+0yOwLLx5zW5j6nSj2dXxoyPT+H+HXk3qtIzNXRxNYzrfASPjRRXAilyWzs42uCT2VUwttMRIQuefj8cXW3gVcIB7w0KxqRex4Qee30A9K/ggnKhrqjeyBezh5wWBjBdxpov+CKijjcyMh7j54nnc5Q3BYCU+fUu5VGjcXEJIDcuzbl/U8Qd3PPrSois64Pl35/Hjj8uqwJAgu8v5tZBqfIu+G1+DNYvuSQMgNS3Ev7OGDGvLlzc7fHPr7FYMuVMrvJKFsAqdX3xaVQt6Z236bdYzBt/XHKlFyQAvlGtmmYA/P3IEQZAoSfOujMxAFr3/Flk7/V/gYZX8UXPYVVRvKQzdv9zGQsmnJDtszEYrFjJE72/qoq0Ww9x/N8krJ5/XtZqaAxIAsM90HtkFezfcg3JV+9j8+p42fLGwKpssBt6j6qMJZOiQV8qx3Znw2cWhMpcbSO5XwNd0Gt0JKYPPo6H9x8j5bqy5dJwDMX9ndB7fCSmfHQUd24/ymGFkRNSvw5PXwd8+G0kJvY6igf3TLutDet0drXFxzOrYHy3I3ik/vyG5L4esrAaxnam8k+EwVW/H8OWEIAd1bQHj+r5dE4VaR+dVgDs910lLP7mHG5eM22BMzYnvaLCsWraRWkPpZbUa3w4NiyMw0UTp6AN69ZB1oeTIrFxSTyiD6UabV4Oxghg6YdB/8mVsfGneBw3svapQrnyHj72Ejz2i6qC9T/G4siO7GdHZG9f6QAXeJd0wjsfBmPt/As4sEXegmusvoqVPfFMUz8QjK2cdQ77N1+TvwjaiEWyRoMSaNm1Ilzd7bBs2hns3XQ1R4SPXHob/Lpp0qIc3v8oAmmp6Vj83Sns3XylQAHw9apVNQPguqNHGQC1PKxWVoYB0MomTE13R48ejXXr1uHw4cNwcHDAzZvKm+Cp7s6dO2PRokU5mqlbty727Nkj3LQOAFfOb4f6L5XDD1HHpS/vU4eTAYWDmPoASNvvmr8fBHqJzh9zHJdj7+BWSroEQKL3+9Vq5Ie2H4Zi7qjjiDmRCjyhPVLy5Q0BUAd/C8eewrljxi1nUhkZAPTwssfAKdWwYtp5nD6QU3tTVkOql76A+0ZVxs7fr+DQliQoHRbRnxz9ult/GIikxAfYuupyjvkTtd7Ve80PJcs747dZlxSthHKLI6CSG5q288f8L6OlLKLt6upzcLbBwOmVMb6r+v1/ujryCoAdhgVjx5oruHBCzH1tqAUdJCHr8a7f1bugqa7aLxVHQLgbVn53QfgZ1Aez4GoeeK1zOXw30PiPL1PuYPoR0/WrMHzb94jxfXEm3Ln0I4YgcO7wk9muWKUyBiDlU9IRH0VVw2/zYnBw63VVEItiT+BTwhEfjq2GfZuv4vdFxjWU08C7hCNoP2TvEVURe/Y2fpx8Cg/uG7ckG4sMUuWZ4pILuPuQKriV8gCzxxzBvL/MG2dX9/5lAFT1uBTJzAyAT/G0071NXl5eiI+Px/z584UB8OrVq1iwYEGWMgSPPj4+wkrpXkBLZ7bFuiUXc7hMFV22eiBVu6Efnn+tDOaNOY57eicJlYBLv2761f7R+OqY980JXE/MuedODtgMAaXrFxHYvjYRZ4+mKsKPXH31Xy0FByfbXHsGlUBIfwx+ZZ3RuLU/lk/NdL+pBUACyPaDgqX9X7qN9LpJFAWxJu+UxpkDqdL+NdF7BPUXSkgND9CVIvv/l6QJAOn6mQatSmHDAuUrYJQWZ4ve5aXy+nvghBczgHqvlZAO3sSeVr6ORa7OwEg3+JV3wp71xuHFVF8Iglv0DMDyycb3b8qV14eat/sH4a8l8UYPopgCQKq/SZvSuBp7Fyf25DxMog+axvqhqzukuieqPueLX2dkjkHEAqhfH0Fgh8/CMG3wMWQ8zP0rUvYamf9gkizZ3YdXxm8LYnDhlLq9nAR2ZMl+u2cI7t9/hF/nnTMOoTL7G6hv9IO26VsBqPacL+o0mGVW65ru/ftK5cqaLYB/Hj9u1j6aWvP8ecEowABYMDoXaisLFy7EgAEDhAGQLIVr1qzR3GelTciGsCRrCdODQbkIIUowKApZojCoL4YSCIlaJ/XrE4UxuXxqwVDNxIr2Ta5OLdCopn/WmFf0Tj4RsBMdvwjkUV1a7/HT9UNkb59RUJSBp4IK66bfJy0xfg3HpK+Dfn0Zjx9h9UHzHrDQvX9frlRJMwBuPHmSAVD04bLifAyAVjx5ol1XC4AEf2T1I+tho0aNQK5kPz8/2eYePHgA+tMlegGVK1cOxk6hMQDmllEUshgARVe8ZedjAMw9P3LQ9bQBYEGcsNUBYNPwcNhpOAWc8egR/j59mgHQsl8j+dI7BsB8kdGyK1EDgL/88gvc3NwQEBCACxcu4Msvv0RGRgYOHDggews8hQcaOXJkLhEYALMlETmtbGoVMQCaUsg6PmcAZAA05yXLOgBsEhqqGQA3R0czAFrH6yRPvWQAzJN8BV9YDrb0e7Jv3z7Url0765/UAKDhiC5fvizB4LJly/DWW28ZHbCcBVB3DYGtnjtXi8vVsIycS1hT3XqXPdPgtLhw5dycSv3RFzKvcKh4lY3MARWllStqkRQdg7meEnO6l/MKaVrHLOqq1a9fSxk5V69oXbJ77gTiElPfldysBRXVI4eGCvcT6V/3otRvU/sQqb2CtAAyAGp9CotOOQZAK5vrpKQk0J9SCgwMhJOTU74AIFUSEhKCDz74AIMGDRJSS/cLlAHQRkgvBkAhmXJlYgDMlEQU2vQFZADMuZzye9+fHFwWJAA2DA7WbAHcdu4cWwC1vZasqhQDoFVNl7bO5sUCeOPGDZQpUwZz5sxBx44dhTrAAJgpE1sAhZaL5kwMgAyAusUjEuFDCZafRgB8vkIFzQC4IyaGAVDzm8l6CjIAWs9cqe5pbGwskpOTsXbtWkRFRWH79u1SHcHBwdI+P0rh4eEYO3YsWrVqhbS0NJCLuXXr1ihdujQuXryIoUOHguo5deoU3N3dhfrAAMgAKLRQ8piJAZABkAEw90Oke//WCwyEnYYtIBmPH2PPxYsMgHl8P1lDcQZAa5gljX00dqkzVbV582Y0btxYqpW+ROnOP8p77949tGzZEocOHZKujCEIbNKkCUaNGiWd6hVNhgCoX05/P6CSlUz0vkAtV8Rocblq2V+Y39fF6Osouk9PNJ/IVTJ0r6B+PFjRuqnfTi62uH9XPBSbYd0evvZG77ATWZPefg5I0RjFg+7go77I9d2U+1XtuPXH86TYE6HILznKCMbaM9VvJWuZoeZq7/Sj8nk93SvaBy19MwzxJmcdFK37kd6ckAvY3GHWGABF3gqcR/r+f1JYu51Z/6dWAQbAzKk1BwC6uNvh7u0M4Yga+iBFl/GePWw8HJgpAKSYtIER7ji8TSwOs+HibtUnEKtnXBRe8/r9DohwQ5lgV+z6/apwef2M7w8JxtLx54TjEOuXDazkBv8Krtj1h/G2TYEUXeD8x/xYTWHs/Cu6wMnVFueOyEehMRREf2+f0nyb6rejsy0ePnyUK+61sQkQBaEcoGoieojRdhTgVsuhFDmwe1oAsE65cpotgPvi4tgCqOltY12FGACta76sordPMwBSkHiKLCJijTMEQA8fB4TX9MLev6+pPm1M1rc2fSti5x+XkXjhrmoADK7qgZfeK4eZg42HA1MCQGq797hK2PvXNez/J/sAkqgFMCjSHT3HhGNwi33C61e/7vc+ryhF8VAbCk2yPLraYvhPNTB32BlcOHFbuH1dxmdf90P9N0piUu9jUhhBUcuTLl+/byOlMH471qqHV4oe0n1UOCb1PSZBv0jSB8BWvYNwPeEedqy9orrftvbF0OWLcPw47oxJy60x+KJ1fjv1IeLOGtfclAXQ2HOm6QSuipBzOpGeFgCsWaYMDD0uImuILJYHExIYAEXEsvI8DIBWPoGW2H3DWJT6X+b0QrKxLYbHj3J/m4pcwRIU5oEr8Xdx707mF6J+GVPuYL8yzmj0ZlmsmX8eD9Mzw0mJuoMdHG3wescgyZX5y/fGQ0Ep1Rde0xtdhkXgh29OIfqwfExmYxrY2RdDh8/DJHgc+va/RkFECUgplutH31bB0Z038POkzL6LwhvlbfpuGbzWOQCLxkTj6I5kVUuObtn5aHJllA91w7A2+3LAhEgfPHzsMXRBdQl6vxtgHF6VOlStoQ/eHxSCLb8mYt0Pcar6Tplb9wtCvVf8MPfL04g+aNx6aqxSHRQNmVcdZLUd0+0Q7qWJu8CpTp9Sjhj2Qw1p3haOOqO67/XfKAWCwIWjz+DojmzLrSjE9h1XGc5utpj1xUmk3Xwoe9rYGJi5edrj6yXP4NdZMdi5LjMOtSno0+9Xg+alEVrdG8u+j8btlHSjY1ey+r3RKQinDiTj3PGccyZi9XuCxwir6o0zR1JyPWsi1k76waSLO04dLywXcLVSpTQD4JErVywOAGmf+pYtW/Diiy9i5cqVqp8HLpBbAQZAXhX5roAxAPTxc0KDV8qiYoQXZn1zBA/u5f4ylANAezsb1G5cEq+0DcS1hHuYOfJIVp9FAJDabtGlIhq85o9FUaewfX1idnmDewCNgVRkHR+8NzAMxUs7Y3iH3biemB31xFA8Q6ih6l99PwCvdwrEreR0DGu3R3FfV65IKTZAx8FhqN3ED0d2JGH+16dNzpd+HwhcP/g6AqHVvfDHgkv4e1lmTF0R+KJ8BGBUvmywG+Z9dRqn9snDq7GOlQ9zQ7uPK8LbzxETeh1B8tVs7UT6UL2RL17vWh4Z6Y8R1fOIajfuy+3LoEHL0ji1NwVLozJjKqtJHYeFILy2F/63NAGbV2SvG1N16EBh+I81YWML/DbnEg5tlYcwY/W5e9tjxE+1kHLtARaPjcbFU+osmKG1PNFrdKRksSbLr772+u3JQc3L75VD884BiI2+jRlDTiDt1kPjICbjmu0zujIq1/PF3r+vYunkaKPPvK5Cwz7YO9hgzLJnpRi8v846hx3rEoVhjOoKCHXH8Ll1cXRPElbNPYe4c2lSUyIASHlefTcQL7Yqj40rLmHb+visHy4iAEjtdPkkUoobvOPPBFw8mw2hBbkHsJK3t2YAPJmSYnEASHvX6aDiokWLGABNvYAEP2cAFBSKs4kroA+Azo526DW0Opq8WV6yug3tvB1x541/kRkDQPo1/cHnVaSXcWryA3z27rYcX0QiAPhOn1C83j4IseduY0S3nAAmYgF8pV0AWvcKxqHt1zDji2OK17sYq6/BG/5o1b0Cdq6/jFWzYxSFNKZB07ZlUbNhccl1vG1NpjVFKRn24a3eQXBwssWR7Uk4tT8T4ETgS9dGhyGhuHDiFqIP3cL1hPumms/1ec/REdi0IgFxZ+/g/p1s8BftQ/+plbF0wjncuHxfNQBSZwbPr4ap/Y+rtsBRWbK+frm4Jka+d0BV2zpQKFHGCX0nVMLI9w+atNwaCkfwXqmuN17pUBZjux1Srbt3SQc0estfgvfvPj4mW14OaipEeoDWTlLifSwcc0aVBZAaq/2CH9r1D8GBrdex9NtoVRZAKv9ahwC06FoBuzdexo9Rp6UfASLgqhvPB8MiUf8VfxzedR0zvjwqvX9EAZDeOyNmP4uQKt44dfAGoj7dL0GgKAC6uttj/JKG8PN3wfH9SZg0aB9u3UyXLoIuqEMgTxsA0tyTBXDatGkMgKrfBsYLMADmk5BcTbYC+gBYIcQLn4ytjZJlXTFvwjFsXhubQyq5PSo6ECob5IZPomrjUcZjLJ8djb2br8jCi7GIIf6Brvh4Yi2cPZqCHRsScWLfDVUAV7KcCz75tibWzDsv7ac6fyK3G1DphLBvKSd8OrUGpg0+ioz0J7n2D5IYSodFyHr56ffVMb73ITy4/0jaC2eYlEDK1cMOg2fXwOhuB5F+L3dZU+vWydkWwxbUxDedD+LhA/Xl6Yt05NI6GNlhPx49fAJTh02M9WfET9T+IaEDCcbKD51fHZP7H9MEgFTfZzOrYs4Xp5F6w7gr0pSGA6ZWxk/jz+JafM69o6bK6T4fMLUKVn4fg/hzd6R/MnWAw7DeT6ZVw68zYhBzwvRhEv26yfpmY1MMn3xXDatmxSBa7wCRSOxeBycb0Prv/lUkVkw/hxP7xLYP6OqmtVurUUk0e7c8fv4uWrLmySVjmvj4OaJt31BUqOSJRRNP4ujunOVNRfigd8cnE2qDQHzu2GM4vPt6TgBVih7y+DGCI73w9Zz6uJWSjpmjD+PQrmsSAK47etSs1jXd+zfEzQ1K22LktCRdzqalqerjtm3bpKvGKGQoRY9avXq1dKOEfpoxY4aUhz6PjIzElClT0KBBA9HHQMrHAKhKLpOZGQBNSsQZ1CqgewFNHPo6OvWrjNnjjiLj4WMc3n0tF7wpAWC1eiXQY2gV6eUbfyENSVcyv0DlgMcQxAKD3TFgQk0sijqJkwduZAGE6JUuHt4OGDy9Nn6ZHo1ju+Tdd7J7F22L4fPva2LTqnjs/+earIxKANjti0q4cOoWtqyWdz8qAeCrHcpLVqzff7ikyuqn62zNxsURWdcHP004q3YZSPn9g1zQul8FfP/xcen/1QIg9f2LhTUwov1BTe1TobwCYPevw7FxaTwunc50I6pNrXoHIi46Dfv+J78GlOokKx65g/+Yf0nKphYAqzf0Re0X/TBn+EmTXTdWd8UqHnj3o2CM7XUoa++uCADqGitb0Q29vqmMcb0PSDBkKhnWXTrAFQMmVsf3Q49I7mhjSU4TG9snKOHvgk8m1sTS787g4PbsOTAFgNRO8VJOsHeyxadRtbFxxUVs+CX7JLvi5dH/wWH1Z0sgOemB9CN479bLWPT9caw9eEQVXJnSy/Bz3fs3yN5e0zNPWl54+FBVHzds2ICdO3eiZs2a0j2yhgBIMeY7dOgAgsD69etj9uzZmDdvHk6ePIny5ctLQ6hVqxYorKhh2rhxI/z9/aV/ZgBUuxqU8zMA5q+eXBsgvTi8vLzwz/ouWDjpOJKvy+/7kgPAGs/64d2+4fh++CEkXsy0fOiSXIA1fRCjTehfzqiLRZNO4vShlJzlFS5H1YepD0dXxdE9N7Dt9wTlwyIy9TVpVQb05bV0SrRieTkAJHhq/3EYJg9U3vsmB4BkfRs0swamDz6G2ykZipZGuYXbbmCwdAhB7d4/XX21XywOv7IuWL8o0/Kr9vJm2jvY7tOKmPG5aXiRG8On06ti+qATmi2A5AY9cygVJ/aIWbAM+1GtgQ9oL+TauZkApzZ5+tqjy5fhmDIg042rFgBpHXw8tSrmjTyFm9eVAUyu7nYDQ3DuaCr2/fdDRg0AUp+fb14aAeEeWBxleg+rsbqDq3jivQFhGNN7H9KNWKJlD4T8B2IEgf3HVscP408g5mSmFV+/jOIJYwD0Puk3sjqO7r2BdUszt3GIAKCuHScnW3QcGAk3D3u8+PoC6Z5VT09PtUtBKL8OAAmZxIJR5qyW7Pz0czMuLg4eHh5ZHzo6OoL+TCV6xg0BsG7duhIczpw5M6t4RESEZCWkQASiiQFQVCmxfAyAYjpxLhUKxMTEoGLFiipKcFZWgBVgBYqOAufPn0eFChXMMuD79+8jKCgIV67kvv5HtEGKFEUHLvTTV199JUWKMpUMATA9PR0uLi5YsWKFFHFKl/r374/Dhw9j69atpqrM+pwBUFgqoYwMgEIycSY1CtCvW29vbymEnLl+5arpj7XmpV/yFIHF8Je4tY6nsPrNOuZdedYw7xpSDeQdIZdnSkqK5CUxVyIIJPDSmujKHkNrvVYLYGJiohRPnlzEzz33XFaXxowZI53oPXNG7IqjZs2a4eDBg7hz5w58fHwkK2OdOnW0DpHLcSQQXgPmUEDngqCXnb4LwRxtPc11so75M7usY951ZA3zriHVUBR0NLQA6gBw165dePbZZ7OEHD16NBYvXozTp01vC8gf9bkWQwXYAshrIt8VKAovuXwXzUiFrGP+qMw65l1H1jDvGhZVAMxPF3D+zALXolOAAZDXQr4rwF8W+SMp68g65o8Cea+F12LeNSyqAEjjpkMgdMqXTgHrUqVKldCiRQtVh0DyZxa4FgZAXgNmU4CO8tPJriFDhgidGjNbR6y8YtYxfyaQdcy7jqxh3jWkGp5WHenAyLlzmWEma9SogW+//RZNmjSR9urRnkfdNTCzZs2S3MBz5szB3LlzceLECQQEBOSPuFyLagXYAqhaMi7ACrACrAArwAqwAjoF6HQuAZ9h6tSpExYuXCj9M1n/JkyYIF0EXblyZUyePBkNGzZkEQtRAQbAQhSfm2YFWAFWgBVgBVgBVqAwFGAALAzVuU1WgBVgBVgBVoAVYAUKUQEGwEIUn5tmBVgBVoAVYAVYAVagMBRgACwM1blNVoAVYAVYAVaAFWAFClEBBsBCFL8oNH3x4kWMGjUKmzZtkkITUVDv999/H8OGDYODg0NRkCBfxkiXpq5bt04KnUS6UbQVTqYVoI3nUVFR0sbzyMhITJkyBQ0aNDBdkHNICmzbtk3S78CBA5KGhjFeWSbTCtCNCKtWrZIuPHZ2dpaiYYwfPx5hYWGmC3MOVsCMCjAAmlFcrhr4888/pSsA2rVrh+DgYBw/fhzdu3dHhw4dMHHiRJZIUAGKw0mho+Lj4zF//nwGQAHddFdPEATWr18fs2fPxrx583Dy5EnpagpOphXYsGGDFMKrZs2aaN26NQOgacly5XjllVfw7rvvSmHLMjIypB+/x44dk9ahq6urhhq5CCuQPwowAOaPjlyLCgXIojBz5kzExMSoKMVZSQG6UmHAgAEMgALLgS6fJXChtaZLERERaNmyJV8+K6CfYRbDEF8aquAiAK5fvw4/Pz9s3bqVr0HhFVGoCjAAFqr8RbPxL774QrIM7t+/v2gKkIdRMwCKicfhp8R0UpOLAVCNWvJ56cLkkJAQyQpI9+FxYgUKSwEGwMJSvoi2e/78eckqM2nSJHzwwQdFVAXtw2YAFNNOF4Ce3Je050qXxowZg0WLFuHMmTNiFXGuLAUYAPO+GJ48eSKFP0tJScH27dvzXiHXwArkQQEGwDyIV5SLjhgxAiNHjlSUYN++fahdu3ZWHvpSbtSokfRHe7GKetKiIQOg2KrRAeCuXbuk0FO6RIdpFi9eLG3I56ROAQZAdXoZy923b1/pMNeOHTtQtmzZvFfINbACeVCAATAP4hXloklJSaA/pRQYGAgnJycpC30hU6gg2pdFEGNjY1OU5ZPGrlZDKsMAKLZs2AUsppOaXAyAatTKnbdfv35Ys2aNdLI6KCgob5VxaVYgHxRgAMwHEbkKZQUSEhIk+KtVqxaWLFkCW1tblkyjAgyA4sLRjw1ac3QKWJcqVaokueDoag5O6hRgAFSnly43uX0J/ugKHYqZS/v/OLEClqAAA6AlzMJT3Aed25eu3fjxxx9zwF+pUqWe4pHn79BiY2ORnJyMtWvXSvey6fYP0dU6bm5u+dvYU1Kb7hqYWbNmSW7gOXPmYO7cuThx4gQCAgKeklGadxhpaWmgQwuUatSogW+//Vb6Mefj48NX6QhK36dPHyxduhS//fZbjrv/PD09pXsBObEChaUAA2BhKV9E2iWLVZcuXYyOln4ZcxJToHPnztLhBcO0efNmNG7cWKySIpiLrH8TJkyQLjGmE5eTJ0/mqzdUrAOyWBHwGaZOnTpJ2xE4mVaALKfG0oIFC0DPNSdWoLAUYAAsLOW5XVaAFWAFWAFWgBVgBQpJAQbAQhKem2UFWAFWgBVgBVgBVqCwFGAALCzluV1WgBVgBVgBVoAVYAUKSQEGwEISnptlBVgBVoAVYAVYAVagsBRgACws5bldVoAVYAVYAVaADioLXwAADvxJREFUFWAFCkkBBsBCEp6bZQVYAVaAFWAFWAFWoLAUYAAsLOW5XVaAFWAFWAFWgBVgBQpJAQbAQhKem2UFWAFWgBVgBVgBVqCwFGAALCzluV1WgBVgBVgBVoAVYAUKSQEGwEISnptlBVgBVoAVYAVYAVagsBRgACws5bldVoAVMLsCs2fPBv2lp6ejatWqUkxWTqwAK8AKsAIAAyCvAlaAFXgqFUhJSUHTpk2xd+9e2Nra4ubNm/Dy8noqx8qDYgVYAVZArQIMgGoV4/ysACtgFQrcvn0bVapUQZs2bdClSxdERkZaRb+5k6wAK8AKFIQCDIAFoTK3wQqwAoWiAEHgmjVrMGbMGERFRaF58+aF0g9ulBVgBVgBS1OAAdDSZoT7wwqwAvmiwNmzZxESEiLV1aNHDzRr1gytW7fOl7q5ElaAFWAFrF0BBkBrn0HuPyvAChhVoGPHjvj333/h4uKCBg0aYMqUKbCxsWG1WAFWgBVgBcCHQHgRsAKsACvACrACrAArUOQUYAtgkZtyHjArwAqwAqwAK8AKFHUFGACL+grg8bMCT6kCxYoVkx3ZkydPntJR87BYAVaAFRBTgAFQTCfOxQqwAlaowOLFizFt2jTcvXsXQUFBWLlyJRwcHKxwJNxlVoAVYAXyVwEGwPzVk2tjBVgBC1Lgxo0b8PX1lXrUtWtXtG/fHi+++KIF9ZC7wgqwAqxA4SjAAFg4unOrrAArYGYFyM07btw4rFq1SgoFFxsbiz/++AP169c3c8tcPSvACrAClq8AA6DlzxH3kBVgBTQosGDBAuzYsUNyATs7OyMgIACHDx+Gt7e3htq4CCvACrACT5cCDIBP13zyaFgBVuA/BT799FNERESgW7dumDp1KiZOnIi4uDjWhxVgBVgBVoDvAeQ1wAqwAk+rAkeOHEGLFi0ky1+jRo2wf/9+rF+//mkdLo+LFWAFWAFVCrAFUJVcnJkVYAVYAVaAFWAFWAHrV4AB0PrnkEfACrACrAArUIQVePz4MRITE+Hu7g6l+y+fVonowNft27fh7+/P4R5VTDIDoAqxOCsrwAqwAqwAK2BpCsTHx6NcuXKW1q0C7w/t8S1btmyBt2utDTIAWuvMcb9ZAVaAFWAFWAEAqamp8PLywtatW+Hm5lbkNElLS5P2+d68eROenp5FbvxaB8wAqFU5LscKsAKsACvACliAArdu3ZLA58CBA0UWAGvVqiWBsIeHhwXMiHV0gQHQOuaJe8kKsAKsACvAChhVgAEwDQyA6h8OBkD1mnEJVoAVYAVYAVbAYhRgAGQA1LIYGQC1qMZlWAFWgBVgBVgBC1GAAZABUMtSZADUohqXYQVYAVaAFWAFLEQBBkAGQC1LkQFQi2pchhVgBVgBVoAVsBAFGAAZALUsRQZALapxGVaAFWAFWAFWwEIUYABkANSyFBkAtahmgWWK+k3wFjgl3CVWgBUoIAWKeiQIBkAGQC2PGgOgFtUAXLx4EUFBQTh06BCqV6+usZb8K8Y3weefllwTK8AKWKcClhIJ4tixY+jRo4cUniwsLAw///wzHBwczCZqQQLgv//+i44dO2Lfvn0Wc+ceXQTN18CoX14MgEY0MxVLsVOnThgxYkS+AGBgYCAGDBgg/eUl6W6Cb9JmBM6VrZSXqrisGRU4PrKZGWvnqlmBoqkAARCFQjMVCWLbtm2IioqSLky+fPkyVq9ejZYtW2aJZupzypiRkSG9/3/66SdcuXIFpUuXRufOnfHFF19IcWjv37+P2rVrY9WqVQgNDUXPnj1Rv359CZrMlfIbAAcPHixpQ8nOzg6lSpXCyy+/jH79+oHglgHQXDNZsPUyABrRmx5qXfrll18wfPhwnDlzJuvfnJ2dkZKSYlEAqHsBvNRuHKLLVy7YVcStCStwcdzrwnk5IyvACogpoHv/mYoEsWHDBuzcuRM1a9ZE69atcwGgqc+pN6NHj8bkyZOxaNEiREZGYv/+/ejSpQu++eYb9O/fH8uWLZP+beLEiVLnKS9t0fnkk0/EBqMhlzkAMCkpCWPHjpWAl8ZDgEuw/NprrzEAapgjSyzCAGhiVhYuXChZ5+iXpX7SuYB//fVXfP/99yCzeEhICGbNmoVnn302K+uuXbtAv6bIXF68eHG0atVKeqhcXV3RuHFjKXajfqK9LDdu3MCHH36I7du3Izk5GRUrVsTQoUPRrl072d4yAFri45W7TwyA1jFP3EvrUkAUAPVHRZ4eQwugyOfNmzdHyZIlMX/+/KzsBJMuLi5YvHgxvvrqK5QvXx7dunWTPv/ggw8k2Hz11VfNJqo5AJDqnDFjRlafCQC3bNmCSZMm5QBAMoaMGjVKgkQCcBo7WT1JJ0pr1qyRvvPo+0zfDU7WRDKmTJgwIc+6sAtYm4QMgHkEwPDwcOmXHsHfsGHDJNA7d+6cZDYnU/lzzz0nPRyvv/46rl+/LoFdtWrVsGDBAgnu6L9pr0j37t2lnpCpPSEhQdoz0rRpU2mPxbp16zBw4EDpl2vdunWN9pgBUNsDUNClGAALWnFurygoUJAAOG7cOOmH/saNGyUX75EjRyT36JQpU6Qf6fTZ+fPnJVfzwYMHJfcw7RW3tbU121QUBACShfP333/Hd999lwMAr169ij/++EP6rnNzc5MgkYCPvsPo+41c4s8//7z0PaiDYPrua9iwIebNm4d69erlWRcGQG0SMgDmEQBpAet+6Z08eVJyCZw6dQoEhrRPgn7hzJ49O6uVHTt2oFGjRrhz5w6cnJwgugeQADIiIiLLrWDYbQZAbQ9AQZdiACxoxbm9oqBAQQIgeWnIIzN+/HgJ6h49eiS5hYcMGSJJTe/2d955B7GxsfD29sacOXOk7wNzJnMD4NGjRyUjBXm3CHJN7QEkowZ5rgYNGiQNm/ZMkmFj7ty50v+T+5yspf/73/9gas+9iG4MgCIq5c7DAJhHANy7dy/q1Kkj1UKmcB8fH8mtS79uCAbJGmhvb5/VCr087t69C4JFAjpjAEgvFPqVSfsP6aF58OCB9Efu4+XLl7MFUNtat4hSDIAWMQ3ciadMgYIEQNrj99lnn0kWPnrHHz58WNom9O2334IOCBZGMgcArl27Fo6OjtIeQPp78cUXMXLkSOk7TR8A6fuKIHf9+vW4du0a0tPTpT/yYE2dOlWSg77v2rRpg82bN0vu8xYtWkhW0759++aLXAyA2mRkAMwjAOpfA0P7BOkXHy1y2t9HgPfSSy/ho48+ytUK7ZOg/RDGAJD2RNAfuRSqVKki7RekFwy5lWk/hbHEFkBtD0BBl2IALGjFub2ioEBBAiCdNqZ93frwQu7RJUuW4PTp04UitzkAkFy7ZLmj7x0/P78sQ4bhNTBk1SNPGFlF6cob8nqNGTNGso7q7yF866230KxZM8kdTDC4adMm6QR1fiQGQG0qMgCaEQDbt28vXRPwzz//yLaiuyZA/4TYG2+8IT1wuk3GdIKMYJL+GAC1LXRLKcUAaCkzwf14mhQoSAD09fWVTvz27t07S0La80b7uqOjowtFVnMAoOEhEN3ADAGwV69ekueLoI8SfV/RXj9yAesD4NKlSyXXL12Jc+nSpRyHaPIqGgOgNgUZAM0IgLRvgja40hUBtH+CLHm0P5D2PdDJYUpkBqdfTPSgkLmdTgrTgQ86XUyuBrIokmuBXL9NmjRhANS2zi2mFAOgxUwFd+QpUkAUAAkUyIVJqUaNGtK7ld6rBDDklTH1OZWjQx1///23tLebXMDkBaI9b127dpX2BRZGKkwAJPCjAzGkpaenpwTCdJ0OHVjUB0DSlqx/5E4mDxddJ5NfiQFQm5IMgGYEQKqaTgXT6eDdu3eD9v/Rr6K2bdtK5nJKe/bskY7M0z2DtM+P8tAJKXqZkOWQrhaglwttKKYj9mwB1LbQLaUUA6ClzAT342lSQBQA6YQqAZ9hor17dOWXqc+pHEX3+PLLL6UrZGjPm7+/v3Qwgu6LNWe0D6X5KkwApK1P9H1G33FkzKADMHTJNumkD4DU/88//1zaI294JUxe1yIDoDYFGQC16WZxpXgPoMVNidEOMQBaxzxxL61LAVEAtK5Rifc2vwFQvGV1OckbRkYQulMwPxMDoDY1GQC16WZxpRgALW5KGACtY0q4l0+BAgyAtyT3K4W4o7v4LC2RlZDusf3000+le20rVKiQr11kANQmJwOgNt0srhTHAra4KTHaIY4FbB3zxL20LgVEYwFb16jEe2vpFsAXXnhB2sLUp0+frHtzxUdnOicDoGmNjOVgANSmm8WVio+Pl4Khc2IFWAFWoKgqEBcXh7Jlyxa54Vs6AJp7QhgAtSnMAKhNN4srRUfvExMT4e7uni83q1vcALlDrAArwArIKECH5+jQAR3IsLGxKXI6MQCmoVatWpKVkcKnchJTgAFQTCfOxQqwAqwAK8AKWKQCDIAMgFoWJgOgFtW4DCvACrACrAArYCEKMAAyAGpZigyAWlTjMqwAK8AKsAKsgIUowADIAKhlKTIAalGNy7ACrAArwAqwAhaiAAMgA6CWpcgAqEU1LsMKsAKsACvACliIAgyADIBaliIDoBbVuAwrwAqwAqwAK2AhCjAAMgBqWYoMgFpU4zKsACvACrACrICFKMAAyACoZSkyAGpRjcuwAqwAK8AKsAIWooAuEtTWrVstMhScuWWii6AbNWoECjlHIfE4iSnAACimE+diBVgBVoAVYAUsUgGOBJU5LUU1EozWRckAqFU5LscKsAKsACvACliAAkU9ElRRjwSjdQkyAGpVjsuxAqwAK8AKsAKsACtgpQowAFrpxHG3WQFWgBVgBVgBVoAV0KoAA6BW5bgcK8AKsAKsACvACrACVqoAA6CVThx3mxVgBVgBVoAVYAVYAa0KMABqVY7LsQKsACvACrACrAArYKUKMABa6cRxt1kBVoAVYAVYAVaAFdCqAAOgVuW4HCvACrACrAArwAqwAlaqAAOglU4cd5sVYAVYAVaAFWAFWAGtCjAAalWOy7ECrAArwAqwAqwAK2ClCjAAWunEcbdZAVaAFWAFWAFWgBXQqgADoFbluBwrwAqwAqwAK8AKsAJWqgADoJVOHHebFWAFWAFWgBVgBVgBrQr8H/V/AEPr7so9AAAAAElFTkSuQmCC" width="640">”

], “text/plain”: [

“<IPython.core.display.HTML object>”

]

}, “metadata”: {}, “output_type”: “display_data”

}, {

“name”: “stdout”, “output_type”: “stream”, “text”: [

“Wall time: 3.95 sn”

]

}

], “source”: [

“%%timen”, “# The convenience functionn”, “timeline = amp.Timeline(angles, units="$^o$")n”, “blocks = amp.blocks.vector_comp(n”, “ s[:, :, 0], z[:, :, 0], Es, Ez, t_axis=2, pcolor_kw=pargs, quiver_kw=qargsn”, “)n”, “anim = amp.Animation(blocks, timeline)n”, “n”, “# standard matplotlib thingsn”, “cbar = plt.colorbar(blocks[0].quad)n”, “cbar.set_label(r"$\frac{4\pi\epsilon_0 a^2 |\\vec{E}|}{q_0}$", rotation=0, size="large")n”, “cbar.ax.yaxis.set_label_coords(6, 0.55)n”, “n”, “plt.gca().set_aspect("equal")n”, “plt.title(r"$\vec{E}$-Field in the sz-plane")n”, “plt.xlabel(r"$\frac{s}{a}$")n”, “plt.ylabel(r"$\frac{z}{a}$")n”, “n”, “# create the controls and show the animationn”, “anim.timeline_slider(text="Theta", valfmt="%1.0f")n”, “anim.toggle()n”, “anim.save("efield.gif", writer="pillow", fps=10, dpi=200) # save animation for the docsn”, “plt.show()”

]

}, {

“cell_type”: “raw”, “metadata”: {

“raw_mimetype”: “text/restructuredtext”

}, “source”: [

“.. image:: efield.gif”

]

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