Fit energy on multiple distance calibration images

LaB6_20keV.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "authorized-thunder",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib nbagg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "limited-yesterday",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import os\n",
    "import json\n",
    "import numpy\n",
    "from matplotlib.pyplot import subplots\n",
    "from matplotlib.lines import Line2D\n",
    "import pyFAI.goniometer\n",
    "import hdf5plugin\n",
    "import h5py\n",
    "import time\n",
    "import fabio\n",
    "from pyFAI.gui import jupyter\n",
    "from pyFAI.goniometer import GeometryTransformation, GoniometerRefinement, Goniometer, ExtendedTransformation\n",
    "from pyFAI.calibrant import get_calibrant\n",
    "from pyFAI.ext.bilinear import Bilinear\n",
    "from scipy import ndimage\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy.optimize import bisect\n",
    "import scipy.signal\n",
    "from math import pi\n",
    "\n",
    "start_time = time.perf_counter()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "horizontal-initial",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['lab6_500mu_20keV_CRL0_174mm.npt', 'lab6_500mu_20keV_CRL0_274mm.npt', 'lab6_500mu_20keV_CRL0_374mm.npt', 'lab6_500mu_20keV_CRL0_474mm.npt', 'lab6_500mu_20keV_CRL0_574mm.npt', 'lab6_500mu_20keV_CRL0_674mm.npt']\n"
     ]
    }
   ],
   "source": [
    "pts = glob.glob(\"*.npt\")\n",
    "pts.sort()\n",
    "print(pts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "running-australia",
   "metadata": {},
   "outputs": [],
   "source": [
    "images = []\n",
    "geometries = []\n",
    "for fn in pts:\n",
    "    base = os.path.splitext(fn)[0]\n",
    "    with h5py.File(base+\".h5\", \"r\") as h:\n",
    "        images.append(h[\"entry/instrument/pilatus/data\"][()])\n",
    "    geometries.append(pyFAI.load(base+\".poni\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "raising-ticket",
   "metadata": {},
   "outputs": [
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       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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ALxZn6AArVAA+GG5EWcLcoPATwTAqUBQBD/6nIHUwDgSz5nhjDK+CSELB4AEgfS9ROsz+NgDL+4HLS/gjapkDBnL+WZGBMCDSX5cLDKjJ7laEwBp7KoncfKO71aBwSmbHXvjG0JO2mR74hvRm1o84wBIRtBzOK0SO9euCwmAnbHN2K+rw0hmKYMQwZAWAA4aKzCe45wWAO7X1eFIugdHs0qCALAroUETAMNB3lTwR146us5snQShN1ZvxLY1G7D92fXYEdPCEL9LgEAtEAzlARRXLrQAULSDSX6MmYsjAsBOwXqSqzFqcmPrqk287W8KHsDXBQCkfbA1DABuXbUJ/SleCYAakgB4B6ILUW9qMfoMPhxIrOWf6rvB8Rwnn7S07Nit92PQWMEX8/EcJ8Pg6Xwbw8cZex4GUgMQczSrBMMZZehP8So8BEPGcpwvtLBH5Ui6B9c86YqJ9YIzhyfX4YwynHNYUblICYBXSzNwtTRDAYC8/FufoPDehQNAgjzymBBIakGfaCIAHjcX4WNvCiYshbzsRjB4ymbHRxVpDICH0ypxJN2DyyUmBQCezrcpvKwXnDk4nFbJsHLGnqeAHDpetK8PJNZiT3wjTlgdfLE5mVvAE+2YuZi9K72GqiAA3BPfiDFzcdDFbldcEw4k1k5OStUzCoDHsl3sud6vqws5EZEHUD0p9ad4cb7QwvuUYPJAYi3v71AAqLX8S57em/UJCqAKBYA3qpJxwuoICYDTgT967yFjOQ4m+bFPV8/fi845cZk6HASKACgavbbP4EPpgjZ+PxEARQgcSPXiw3IjRk1uBkDRC3swKXBceg1VQVDSGduM4+YivpaIRiEnas/NCauDl4/DQeDuuCb8Iq1oxsbu365qUAAgQSAtC6rhTwRA8vLTdxNBaFdcEzoFAKSwEy3oU4f6iHYs28WrCFoAuCe+kR+LBASngr9dcU3YEdOCV1duRsfjHfAv7kDDkg60P96BF5a34vVJb1qnBgRGshQs/o8AUO1VFG2frh4TlkJNABQ9f+LKSOdkaMFxc5HCA/hmiCXgroQGdOv9YT2Ar63ahMNplQoAfGXFZvxQAqAEwDsRXYh+kVaEXkMVu/3VJ/yBxFpMWAoVAEgTqgiA5CUkAKS7dtGLRR6+/hQvewFpciUP35CxHCOZpbhamsGTykhmKc4XWhQAeLHIzBMQAeB1nwHnCy1BAHi2IDdo+TcUABL8ncwtwHBGGQaNFRg1uXmZmeICJyyFmgBIEDie48Q1TzovJYuT9HFzET71JykAcNBYgSvuTPbc9Bl8OGF1YDijjCdNipGkfU7LYOoLbE9yNY5lu3AgsZYnRVq+OZlbwL+PmYt56YWWIwgAaWltzFzMXgUCwJ1r1+Fgkh87YlqwPcY/owA4Zi7m5UMCYK2JifaXOAEdTPLjcFolztjzQnoACcjF8Xok3aMYn2oAPJpVgpu1OgVghQLAT/1JIZd/w4GgOq7vWLaLQyYO6Wvw0jOtaP36rQl0T3wjepKrMZDqvWMIJACsXNQeFCMoAuBAamC/XS4x4bi5iD3ZovfvQGItTtnsOJxWGeQBpJiqg0n+oAn+WLYLR9I9iiXg3XFN7DGcygO4O64J/UbnjI3dV1c2MhyQbX92PQaNFYHzSvAK7lAtAfckV7OnUISh3ZPn6Y6YFgafY9kuDGeUacKfCIBqCBzPcfJ8IJ5XWgCotnDQp7Xsu3sSWl9ZsRl1SzqQEb0OKdENMEY3wRTdAt+idnz/6S14ffVGvCV4AsXlYDUIhosDjAQA6cZ5tzCGxLGktfzbObk8f8LqiCgGcE98I/oMPoUHUA2BBICvrdqkAEDpAZQAeEeiC1G/MeC5IwBUn6wHk/wMgLQETL9T8D15AOn3UzY7A6AYx3bcXIRBYwVPqGSH0ypxwZnDE8ioyY3LJSaeVEZNbo7HoonrkisbrvlbFAB4s1aH0/m2oCXgi0Vm3KhK5qXdcEbwN2Yuxp74Rjy3tB3fW9aGXXFNHFNFEKiGPxECJyyFuOTKxuUSUxAAHst24WatDgOpwQB4OK0SfQYf+gw+HDcXYdTkViytj5rcPIESuKgvtof0NRgzF/NESNC3X1fHMEiTAx2n2wXAbWvqZhwAydslTmLqCUcMahf/T+EHNHZFD6C4JC+C4JF0D664M9kbqAbAMXMxPqnRB8EVQaAaAEUPsdrCAaHoVR41uXEk3YNeQxVeeqYVRfO3IH/uZjjmtcI1fwu+u6wN+3T16DVUBXkCCQSn4wXsM/jgX9yBo1klIWMA6fy+4MzBCasjCAAJAk9YHZyoRMdxb3wDA+AhfU0QANL2qQGQVit2hZi4RWiaaQAU4Y9s0FiBt2JaGAi1ILDXUIWBVK/iuxDMdE56D2k/jZmLMWisiAgAxfNnwlLIy/Ki7Y2/BYChzjU16KmNPp/g753YZmxbswFbvt4BU3QLUqIbkBLdgNToRhijm5ARvQ7Nj3Tg5RWbOWaSrkMEgqEgUL38G0kMoOhNFgFQy/unBsC98cEAGMoDuCuuCQOp3ikBcCDVqwBAuQQckATAO5AWAA6kTg2Aoya3wntCwKEGQLqIn3NYGWDGzMU4nFYZEgBp8qA4OZpUjmaV4Iw9TwGAl0tMKFIDYH0CZ+OKSSCXS0z4qCKNl4NDGS3xHjcXYSDViw2PdqB0QRsqF7Vj/aMd2Kerx3BGGX9eOC/ghKUQ5xxWXPOkB3lqtADwcFolLpeYFABIz6f9d8Lq4AnxkL4Gp/NtQctp5J1VAyBB0gmrAweT/HcMgLQE/Ncrmu4JAFR7j7SyGskzLT5+JN2jiKWkc0ENgJSYQ8HhdKy0IHDMXIzrPkNQrB0B4HBGGYrmb8FIZilnANO4EH8PZ2L2Li379qcEsvkblnQgf+5mBkDHvFb4FrXjzTUbOESAsnfVnkDRtMCPrNdQhYYlHYq4Xa3l34HUQDLTKZtdEQMoJglMWAoxnFGmOIZdCbcAsCe5Omhyp32qBsDj5qIpAZA8SPuTPDM2dv9mZSO2hQBA0TOohkACwD6DL8j7RzD1VkwL7y9KulPDnugd0zpvTlgdOKSvCTqXCAApDlgL7kItN6uzeHeuXYfO2Ga8uWYDXnqmFZ6FbTBGNwUBoDG6CUWTNzGvrNjMYEUe0aniAsUEolAAqJVwcjK3QDOjPBwAkucwEg/grrgmThgJlQms9gC+PGnfWbZeAuBMb8CXWdMFQPp91OTmyXMg9VapEVoCPqSv4UQDNQBS3A5NpuKymhhvNWpyBwHgKZs9IgAU4/NEAPyw3KiI5VPH9YnLtyOZpdgb34DKRe0oXdCG8oXt8C1qx7Y1GxhQxeXgE1YHL82J73O2IJcBUF1+42atDofTKhUAeMmVzaV1+gw+XjIUM61FADxjzwsJgBQ7JQIg3dkTDNIy8d74QBkYNQDuCgOA3fp70wMYyqPRrfdrAuCgsYKTlmj8agGgeMNyJN2DS65szXJGR9I9HI5AIHUk3RMSAG9UJU8b+tSlhYaM5RhIDWTgd8Y2w7eonQHQPgmB7gVteG3VJuzT1QctBUcKgVMBoOgBFPfX2YJcBQCqS8FQpYBwAKj2AFJsWyQAqGW74prwy/TCGRu7f72iSQEG28IAIEEgeQEJALWWQmkJWPQAHk6rDAI+9RKp+pw5mVvAntc7BUAt+Ns9eWzeimnBG6s34oXlAU+1MboJqdGNDIAEgflzN+O5pe0MgG8JS+KiFzBUZvBUAKjlATxlsysyyqfKAN4R08LgGKkHUA2A6hjAV1du5ufIJWClJADegUIBoFZMmdoDqAZAggmCj6k8gKEAkCYPAkCaVI9mleBsQe5d8QBOWAoVHkD3pAew8eGAB/BoVgkmLIWKJWZ1ORjyBJ4vtOCaJz3iJWDyKpHHSe0BnLAUKrKw1WVNCN7JAzgdAPz/yxJwqOWtg0naAEixlmJdOlq6CgeAdKy0AHDMXIwbVckhl4AJACNZAg5nYkkXSq46kFiL9sc7ggCwZnE7dq5dxzUlqZSSGJsYyruoBYJ9Bh/qlnRwskC4GMDzhRYuDRUKANVxaiIAEoiI3h3ap1MBYCgIvBcAUCwLQoBwOK1SMzZQ9AJSUg9lxk4XALVMDYAnrI6wS8ChADCcicdW9ALuiGnBa6s2ofHhW/F/FANIAFi6oA0vPtOKbWs2YEdMSxD0hVrS1ooDnCoLmBJryAMojplQACiWyCIPoFYWsFgGZjpLwBIAgyUB8A4kAiAFvlNMn9qbJNabE0sDDKR6OfOSYm8IAMUkEBEAKQZQCwCHjOVcPPZyiYknk0hjAD/1J+GMPS8oBvCCMyeiGEBxGZhiAL/9jXZ864l2dMY2Y9TkxoSlkJNLwr3+hNWByyUmzRjAMXNx2BhAAkCqI6cVA0gAKE6k6hhAEQDpAizGANIy8Z0A4N8/Wztjk+iehFtJIGJguVaWYygApCQQ8v5pAaAIf+Q5o2OlBYDHsl341J8UcQyg6CGOJPYvVALIkXQPBlK96Ixthn9xB8OfZ2Fg8qT6keQ9o7Go/jwtwFTDYJ/Bh5rF7fy5lAiitQx8yZWNCUthSA/gydwCDBnLwyaBiN6dPfGNnNyglQRC4z7cMvDuexgAKQZQywPYGduMQ/oaTgJRL30SUNG+ohqkkYCf6DEfz3FyeTDRIkkCmcrEOEDa5rdiWvCDp7fAOa9VAYDG6CZkRa9H++Md2LpqE1ch2BPfyNuv3kat+EMRBjtjmzkJhPabVhKIegk4Ei+gOgnkTZWXVwTASJNA1DGAEgADkgB4BxKzgKn+H5UYUddRo3iQbr2fK53T82kJmGIAu/V+Bg4CQCoAS94CLQ8gZfmSd+JqaQZPqlQwN1QWMGXWTjcLWMwEJoCjnxSYfjitkjsqnLA6guBPXRxahMCPvSnc0USEwPEcJxfHJQAkqAiXBUxe0HAAeCCxNigLWEwCEY+NmAXcZ/ApAJAuhFoASF1CdsS04O0ZzAJ+V+dVFClXTzCiHUisxRl7XtAkQR4qAkARJikLWA2AVAhaDX8EgKMmN27W6qYsA3Mk3YNPavRBWb2RloJR1/8jGCPv0Pef3oLvP72FO0xowV8kCSZaENif4kX5wnbF0nCoWMBrnnQcy3aFBEAqFRWqDAzFrIrLh8fNRRgylgdN3tMpAzOTSSDhAHCHCgDVMYAHkwIVGLRiAEUA7EpoYE9vpJ4/MrpZj6QMzHRKwYTKAt65dh3eXLMB31vWhqL5W5ARvQ6m6Bbkz92M1q934NWVm7k4tBr+pgOd+3SB+pLkxdSKEaT3pySQ6dQCJHjW8gC+sXojtq7apCgD05NcPa0YQFkG5pbuOQAcGRlBcXExnnjiCURFRaG7u1vx/4aGhqBmzkajUfGcP/zhD2hra8PDDz+MuXPnwuVyBTV8/t3vfofa2losXLgQCxcuRG1tLf7jP/5jWtsq1gGk7F+KIxLjoQ7paziD75C+hpdk1GVgJiyFiuQEumjTxZ0KZFL8kBoCzxbkYiSzlCdVAkAKVFfXATxbkAvfImUnkCvuTFzzpIesA3jOYQ1ZBkYEQPIc0pKY+F6RlJCh19+s1fGysgiAVJhaLANDXk0RAE/n27i9Xq+hKqgOIJWB0SpuLNYBJAA8kKisA0httvbGN+DlNVboFyzFQ/dFIyoqCn+2LBd74htxNKsEO9eug2nR6qCx+8yDj+JHa2/VAbzbY7dLV8lgEa7NFE1QVAZG9G73p3hxscisGPPk6Qi1BDxorMA1T3pQkWgCQKoDGEkh6I+9KThls99WDUCt0AKKOaTzmOr/EZhqgV8k76uGwIFUL1yTEKuGQDUAXvcZ2GuoBYAXnDnsbVID4HiOk4+HGNN1MreAu2Z8d3khkuYv47H7raesfNOyc+06ZD20Kmjsrox+RFEH8G6PXUoCUccADqR68U5sc1CBaBECKRlNXQZG7QHsSmjAoLGCz/NwAKj2og1nlIUtBE0AGCn4hYJAscsLJYS8sLwVf/FkO76ztB0vLG/FG6s38o0nfS81/E0HOpr6ie8AACAASURBVHeuXcffIVScIMW1h4oRDAWA1KZTDYBvangAabu1PICvrLhVCHog1RtUB1B6AO9BAPzFL36B7373u3j//fdDAqDD4cBvfvMbtt/+9reK52zatAlPPvkkBgcH8etf/xpWqxWJiYn4n//5H36Ow+FAfHw8PvjgA3zwwQeIj49HcXHxtLZV7ARCyR9UsFmcDCn2TPTi0eNanUAoC/iQvoY7gVDMEC2HUZKDCIGnbHbuYHA4rZLrrNHEqu4EMmEp1OwE8qk/SbMTyMfeFFxxZ4YEQHouASBlAx83F4V8TTgAFLuSqCfVK+5M9i4RAI6Zi4PKjqg7gVwuMXEnkP4Ub8hOIAOpgQ4QFN9HtdFouY0u+iIA/mCVGe5HdfjmMgsDIC0hEQDGz1uKV1dX4401PrwdW4Gtq2uxJ8HLF6K7PXa7dJU8ZtTtxdSlRsRC0PR3t97P+5WeTwBI3mtqYaYuB0NlYMSuNmJpFYrtmwoAL5eYcLHIfNsAOJ7j5Pemz6MbKQqnoM/XWmKeCixpm9XJJ4PGCrgnPfBaACguj39So+fkJjUAduv9vP/VAEidQMS4MTJKgNoT34j/56l8lDyiw58tsyIqKgrfnARAsqyHViFh/pPYuqaKbUdslaITyN0eu+pOIGTUllOrTzB1xNgT34hRkzsoA1bMAqb91Guowgmrg/dfJN4/8oyP5zhDAuDe+Mg6gUwFZeIxJWh/cxKUxHIvYqxfpPAn/k9cEhYBUD2uCARpvooUAMloNUcEQLUXkIzapYbzAL6xeqMEwBC65wBQVCgAdLvdIV/z2WefYc6cOXjvvff4sU8//RRf/epXMTAwAAC4cOECoqKicPz4cX7O2NgYoqKi8C//8i8Rbx9diLoNtzoHkOdJDYDjOU72RFFWHvX2JTgZz3Gyp++E1YE+gw/7dPUYz3HiWLaLy2ccNxcpAFAseTJhKWQvyyVXNk80Q8ZynC3I5QB6ylj0LFQuAU9YCvF/m+IUCSAEgOcLLWF7ARP4iY/RBDlVz2AtAPzYm4KLRWZFYWiaVD/1J3GhVQJA8gKJHqdwvYCHjOVhewGLyzdU7oU8tbQkeizbxRdV6gTSldDAALhfF2g5RQCon/8U17rqSggEU1MpjevXr9/1sfteYgXXoaMbEQJB8Xd13UTRu91rqMLV0gwFnNBEdzK3gDuxiNZn8OFikRnDGWUhAZCyzqcCQLo5uRMAPG4u4nOAxhgtx4aLK4zEsxjKCzie42QPfKhlYPI83qhKZpBWA+AhfQ0uubI5SUmEwF2TMX1ak/T5Qgt7uGmC3ht/a+yKk7Vp0SroFzylWLrbr6tDj6Fkxsbu360O9NJWA15PcjW6EhoUWb9kVPqEsvMJOsRagJ2T3kNaKqXQB60iyaEAkK4V1NFJtH067V7At2vkBRQhXyypogV+BH9TAWYoL+CuuKawAEhZ5v0pXs0EkXCxgBSzHcoDSO3gXl+9keM4wwEg3RRIAAzWlxIAFy1ahEcffRSrV69GS0sL/u3f/o3/PzQ0hKioKPzud79TvE6n0+H5558HAPzoRz/CokWLgj5v0aJFeOedd0Juzx/+8Ad8/vnnbDdu3EBUVBQO6ANAdTDJz54OcYIkr9+gsQIHkwJJIASDVHtM7PIhFnzep6vnxAlaOjthdSg8KQSANBkSAJ7Ot2HCUsgTK2XX0gQ7ZCznXqS0rDWe48QnNXrOOlQvA3/qT8IlV7YmBIrxgmRU1mW6AEgxh5QMIi4BT1gKcbNWh6NZJYpewJdLTBy/RbBM/U5pX58vtPDkSYH/WgBIXlbKCKYAewLtfbpAi7BRkxt74xu4NAhNGDSJ0msJAKO/ej8WfO1BPHH/AlgXr8arq/w8ifb09Nz1sfvTpHKOSSMA1DKK66MldXFs9xqqOPaS9jWFL4yZixXvLQLg6XwbZ4trAeA5hxWXS0xTAiAlL2nFAUYCf+M5ToY08T1oO27n/cItAxMEXnJl8w1YOAA8bi7Ch+VGPtfVANhn8DHMqQFwb3ygVqV6ku5KaMDFIjMvH4rtu7QAMOuhVTx2v37/QpgfWoMfx5fj/eSyGRu7b6yp4+xR0eh8png/Aj8RMnauXYfj5qIg+KDl3zfX3MpwpVCG6XgACbAoOep2AVAdS64VpqH+fFqi3TV5PMX/R7Lcq/UZoQBQvT/EMUbJcuokkakAkGJQwwEgeQCHM8rwVkxLWACkZWUJgMH60gHge++9h97eXvzzP/8zenp6kJiYiLi4OPzhD38AALz77ru4//77g94rPz8fGzZsAAC88MILWL16ddBzVq9ejRdffDHk9vzv//2/g+JgaBIdNblxMMnP9cHUADiSWcpLNGIZCLrI9xl8vPQk/r5PV48hYzlO59vYq3Uyt4Dj3EQApEQQAsBj2S6cL7TwxCpmAlOLttIFbRjJLFXENZ0vtPDSq9oLeMGZE7InMAEjxflNFwDFJJAbVcm45MoOgr8xczEul5jYu9ln8ME5rzWoDVx/ipdLvogeVjHO8pTNzsdKfdEbMxdzNist3e/X1fFkvU9Xz5C5N76BQXFPfCMO6WsQFRWFjmW5fEOwc+06bHrSij9bmo8fPFOG7yy34KkHl+Ab9y/GodQCREVFobOzc0bGLnmARQ+dGgDJ40P15tT/p/hSgjuamMjTpQWAx7JdHN8aqhbgJzX6IAAUs4CpZMyH5Uacc1i/kCVgeh15yqcLfZEAIMXbUhmmcDGAF5w5fP5rAeBwRpkiSUk96Q8Zy4O6OuzX1eGCM0eRFLI7ronHrhoAW5fm4JvL8vH/rijDny2zYdkDS/DUg4uwO6FsxsYuAaBo70wmEfQZfPzYK5PdL9SgN2Yu5iVf0SiDWIwLpA44ag9guBjAA4m1fON+OwCoBX+hALAroUHxuXQ81Qke0wHOOwHAfbp6nLLZFXGBkQDgzrXrcMaeh11xTQyAb64JTgQhO5pVgm1rNmgCIEEg3djIXsDB+tIBoFo3b97EnDlz8P777wMIDYA2mw0bN24EELgQrVmzJug5q1atwl/91V+F/KxQd6L5c1vgWdgGx7xWOCfbRlH3AOekuRe0wb2gjX8vXRDI1HLN3wL35O+lC9rgWRj43T1ZPNk+dzNc87egZnE7P9+3qB2u+VtQpGH+xR1wCe9bt6SDf3cvaIN/caAzR+nk38vm56N8YTs8CwOfV76wHZWL2rHh0Q74FrUrrOqhgK1/tAN1Szr4bzJ6Ts3iW1a5KGDiY2pTv0/NYuXn03vQ9jU/0sEFpovmb8E35lngWdjG3532RdVD7bzPnfNaUfVQ4DX0d83idjgnj5PaKhe18+/uBYFja5+7GZ6FbXBNtgij/Zw3dxM/N2/uJjjntSIqKgq6+wvgmh8oy2CN3ghr9EZYojfAEr0BjnmtyHywFl+J+ipSHswPO4n+Kceufd56Hmta44nMPncziuZv4WPgFMY27Usau0WT498+dzNKF7Sh6iHt9y4Vxqc4Run88Cxsw4ZHO+BZ2Kaw8oWB4/iNeRbedv/iDjQ+3MFjZbpG4140Ok9u9z3FMUtG34HG+dL5efx9xfNStMaHO1C+UHnO036nsVq+sJ33uWiOebda2olGxyxv7iaFFc3fwmNX/T8ya/RGHru6+/NmbOxmP9ikOKfI6Nykv7Oi18MSvYHPQTLPwjbkz90c9Lg5egPM0RsU39m3KDDm1ftRrBWpZXRMxeORP3czHpuXobhu3ImJtSppDNB2q8fCnRq9lzV6I74+zxRyf9C4DDeGQlnN4nZYozfCFN2CrOj1fDyyotcrzBQdmHdN0S1sGdHrgix/cn+Ijxmjm2B48O5XX7jX9KUHQCBwAXnppZcA/GmXgNWiWJQH5ixD9P3P4MH7n8aD9z+t+F187HaMXjv3gZW39Xqt14mPzbnv8ZDvPe+BNZqvJZv3wBrF31qm9bpwJr5npNsU7jtofW/xeKiPk9b/xN/nPrBS83H171FRUZhz36MhP4PsK1H34b6vPvQnX0YLNXYfnDP98RXqudN9XBwX4f4Xapzdf9+TtzUm7wWjcSx+h1D7QGvMT3VO3MmxioqKwv33PRbyWkT2la/MmdGx+8CcZSHPq6nOu+k+T33uT8e0Xjfnvsdv673uJQv3HW53X4ljLdzxFZ//wJxlYU18P9Huv+9JCYAzvQHhFAkA/vu//zseeOAB7Nq1C8CtJJB9+/bxc27evKkZjDw+Ps7POX78+G0HI7+8IuBipswraswtlibY/ux6HNLXcFmC/bo6DlzeHdfE8SuH9DUc2Hwwyc+ZXN16P3bHNWH7s+uxc+067NPVa5Y52B3XhJ7kakW9q15DFbvX98Y3oD/Fy9liWdHrOXlFnR02YSnkeEb1kjYVpaaA3VBG7xXuOWKMnlguh5YhxOULig+hJYXtz65H/tzN6E/xKuKBKAaN9gslaVAsCcVHqZcU3li9kZclXp/c910JDXh15Wa8vnojDulreLlhv66OlxneimnhpYXdcYHevvVfD2zryys248VnWvHC8lu2bc0G/OWyZtz3la+h8YkMRSD93Ry7f7uqgceXOqCegupFeyumBQOpXsVjb67ZgM7YZgwZy/mx11dvxGurNnFQPgXWq9+rz+DjwrLqgPzdcU28HK8uN7E7LrAEJcY50ZgM10lhOsV2afnvdor0hureQGVFqNi02E1BKzuyz+DDQKqXj406Hmr7s+txOK0Sr0/WRyN7bfInjT91a6xD+hpeHn1ZsG59wCtS95gDLz3TGmQvTtr3nlqHOV/5Kkofzpmxsfv80y28PXR+0e+745rwkuqcI6PnUCFh8fUvLG/FD57eguefasNLz7Tyfnl9MuNUvR/F5catGvb66o04mORHZ2wzJy68tmoTUqMb8crk+6qvP1+E0bXoi3xP2v6tqzbhpWda+TuoCy9vXbUJPcnViiVXcYypx5K4//fGN2D7s+vxw+Vb8NzSdnxvWRu+P3k8nn+qDd9bFrDvLmvD65O1H59b2o7nlgZK3mhZZ2wznlvajr94sh1/LljHExslAM70Bqj1+9//HqdOncKpU6cQFRWF1157DadOncK//uu/4ve//z2+/e1v44MPPsBHH32E4eFhZGRk4Mknn8R//ud/8nts2rQJS5cuxa9+9Sv8+te/Rm5urmY5Ap1Oh7GxMYyNjSEhIeG2yxHsSfByPFq3PlDcWZ1NSZm9FChPwe/9KV7OhOxP8eKE1cGJIRS/Rj1tqUwMPU+MpyIbSPVyrTtquaVVD5Cygx3zWjFkLMdHFWkcp0TJIGcLcvGbhnjNjGCK87vuM+BGVTLXB1TH9VEs1FRxfx9VpOFmrQ7nHFaczrfx51Ff4AlLIa77DLjkyubkDSrwXLmonfch2TmHlWMrKUh+JLOU46fO2PMUcCvGvVA83MEkP8dKUjmI8RwnZwCPmYt5Ug/EHPnx4koXdugCpTQqHzNiW1w+Xltdie0xdShYEo/nni7G36yuwP9ZacPK6Mew5L652JOoLKVxN8fuT5MCRcUnLIWK/RXOqPyOGC9IiSAE71QGRrxREGMAxThAKhUjJoKIBaF/0xDPx1zdCo5iACl277rPwNnn003cEMfaeI6Tk2PEx8X/U8tDrYQS+qmOAaQkq2PZLi5iLsYAqgtB36hKxqjJHTL+bySzVBH/J0InxR5TIoOYxHCxyIyDSX6ht2stXljpwnvpRkRFRaH80XT85VMevLa6Em/F1MLxcBy+90wRXllVif/1dCFWRT+KR+9/EH+72jdjY/fvn60N2aeY4h7V8X2i7Ylv1EwE0YoBpJacNK4jLQVzIDHQKWc8x8k3s3caAxiJ0Y1SuOdofQbFModKCKHvJMYAqtvFUa93dW3AqUrB7Fy7Dqfzbdxqbqo6gIfTKrE7rinoxueF5a344fIteG0SwKkItIwBDNY9B4DDw8OaAb8NDQ34r//6L9jtdjz66KOYM2cOnnrqKTQ0NOD69euK9/jv//5vtLW1YcmSJYiOjkZxcXHQc37729/C7/djwYIFWLBgAfx+/20XJN2T4OULNxWOpVpzao8ZBcpT6Y3+FC9f8PtTvBwoTsVn6TmDxgqcL7TwJEAlY9QASLXtjmaV8CRyucTEWchU+uR0vo0BkDo5nHNYFckg4zlOfFhuxMfelLAQeMWdiZv1CbjmSVdAXagyMOL/L5eYcLNWhw/LjZwAIhaCpiSQS65sbvklAuCQsRzuBW2KQsNHs0q4yC0lx1xxZ/K+I0AUIV30co7nOBUttij4mybpfbp6zrqm4Oue5Go8t7xAc+yaFq3C2zH1iJv3JBZ87UF87StfxSNz5iFj4Wp0xrnRpavkC9HdHrsEgGPmYi40PJWdzrfxOBYTRqgV4SF9DXtYqeXWKZtdEwCpXmWolnDDGWW44s7ExSKzIhkkFACezC3AzVodw9ntZu9qASBB33Qyi9V9hz+qSMPZglyMmtxTAuCxbBduVCUrWhuqAZBudLQ8j3TDowbAA4m1igzgPfGNIcdu1kOrsCO2DvHzvhEYu1FfxcNz5sH80Eq8p3co2hje7bEbDgCpFqtWqzExYUTdpUcLAAkCx3MCpbymC4AHk/xcc/FeAsCp4PB2AfCUza7YhkiTQKg2JfViplZwWgC4bc0GjJrc2P7segX8qTuAbH92vcJzKwFQqXsOAL9MEgGQMnepMK5YWJcgkCYrWu4UQY96kNIyqNpTSJCmzhjWAsCRzFKcsefxhHrcXIRLrmzFxHqxyIwhYzkD4NGsEnxUkcaARRPqhKUQn/qTcMWdGRYCzxbk4sNyI27W6vCxNwWXXNk457AGeQDPOay4WGRmjx+1ntOCPyoBQ57IE1aHomXXqMmN84UWuOZv4f14OK0S5xxWBmdqByd6TMdznFyLUV3rju5e6eJ3zmHl+mgTlkL0JFdjn66e931XQgPfOVPx057kauyOa+Jjpc5026+r46r9h9Mq0RlbfdcvRCIA9hqqMJxRxh1BprJj2S72RosQSK3+CAApI7onuRrnHFbNWoDURYRKI2kB4Ji5WNEVRARArTp9NL7Eki53AoB3mgFMdr7Qgg/Ljfw9pgJA6sgjwp8IgFSAm8afGgBP5hbwxCsCIAG5unMDrTpoeWrUPYF7kqvRZ/DNaB/r7TH+kAC4T1ePw2mVQeCnLhkzZCzHgcRaRQhCKADsM/hwMrcg4lZwYlgAjWPK2r2TMjB3CwC1soanAkDqvy62HYwUAAdSA3NXZwQA+FZMC0ZNbkXog1YWMNUplACoLQmAdyARAA/pazBmLmYvktjijSbB/pRACRdaxhWLFlNrKKrfR8vI1K9zINXLAESwQ5OwVleQ84UWDBnLeVK95knHSGYpT7ATlkKcsDoYAGkp6WppRtBS8AmrAzfrE3DJlR0SAsUWbzQBf1KjxxV3Jq6WZuCTGj3bx94UXC4xKer+acHfydwCnC3I5cLU6p6t5wstGM9x8ncYNFZgzFyMUza7ohj01dIM9Kd4edKiJUyxjAkdJ1qa69b7ueYixZmdstn54n7cXMQFWCmObU98I3sId8c14WhWCdfkEj0M3frAxNUZ24zhjLIZnUQJAAdSvdytRhxLYpkhskFjhaLANtmgsQKXXNlcMocAkFohUns1dRvDMXMxLjhzeGxqQeCH5UZudUjeXwJAGquifVhuxCVX9h1BIBVLvx3wE43K3XxSo8dxc1FEAHg0qwSf+pMU3T9E+KOxSrXW1ADYrffjdL4N78Q2KwCQ+rMOGiuCerdS6EMkAEh1MWdy7HbGVocEwN1xTdzq7R0NAKQi0QcSazForFB4BUUAFJeBuxICxbPpvJ+qFIy6/MrpfBvfQEbqAbxdCCQv5e2An+j1C1UMWgsA9+nqcTK3AIf0NYpYXdp/4QBw59p1fH2l4/SaCgDFGoC0CjMVAPYkV+OtmBYJgCEkAfAORBeid3VeRe04ggc1APYaqhRLk1pxgDQRD2eUsdfwuLmIe92Krc6oxpR6gia4JE8ixaCINQGPpHtwtiAXrvlbGABHMktxsciMcw4rF9yliZMg8GppRhAEhgLBM/Y8fr34mFjvLxT8nbA6cMGZg//bFMfvQ5MpLfES2DkmO4FQfCMBM+2j0/k2nkBHTW6GcHUtu15DFdcJ7Nb7OR5zV1wTe75ocj2aVaK46xWr39OESn0w1XWuKAB/59p1GM4ow9+trp9xACTvBo1Ndds2tV1w5ijGHr3H1dIMrntGS8DUdeVkbkFQLUC6mbnmSceRdE/EXsAj6Z6wADie48SNqmRccObMOABST+sTVoeiFqAWABIEflSRxvU+xX0sAuDFIjMXK1dD4HBGGbc6EwFwn64eF5w5DOiinc63oSuhISwAkpGncCYB8L3ECk2QIBvOKOM6f6E8gFQP8J0pAJCAigrr344XcMhYjvEcZ1gADFWr724CYCTFoNUASB5XsTWm1vJvKACknvfvCMeIAFAr/m/QGDj24QBw66pNOJxWia3CsrAEQKUkAN6B6EK0P8mDg0l+Dtbu1vu504c6DpA8epTYQZ0r6M6fYGw851bx3LMFuby8SYBD0Ki1bEeTKnlVyDt2tTQDoyY3f9ZwRhlKF7RxsshIZimOZpXgmicdp2z2oHjAE1YHPqnR47rPoPDShQLB0/k2fr36cTX0ie93MrcA1zzpuFmfwO3dxGD68RwnJ630GXwMgKfzbRynQ9/5middkdxAMVNq+Dukr+GkAzpe5wstOKSvwe64Jv4sKqx7OK0SXQmBCzjd8R5MCoA/Za+OZJbyhY4AkP7XGduMfbp6DKR67xkAHM9xssdpKgA8nW8L6kndZ/AxrKsBkJaB1V5D+iwaO2IsoJgMMpxRhqulGVwAXARAullRLwVPWAoZAgnM7gYAihB4Ot+Gm7U6Hsc0hgkAxULQBIHjOU7u/Us3MmoPIHW1ESdlAsADibUcc0nJDuSl6TVU4ZzDGrQ8dyCxVrFkHA4AqY/uzrXrZhQAe1OLwwJgf0rgRkQrDlCEwKNZJRyS8c5ktvo2jSQQ2n9n7HlBcW+RAODBJD93JiJ4iqQ4890EQDUIRgqA1CWIqi9MJwGEYH3IWM7H5q0wAPjmmg2KAtDqJBCyN9dsQH+KVxEXKAFQKQmAdyC6EPUYAjFjA6kBKNOKAyTQoAmLlsyoxy+9ljx25LU6mOTH2YJc9o4QiNFETD2DtZbu6Ln0ntRFQ4RN94I2HMt2KfoDU7A6eSxECJywFOKKOxO/aYjHBWeOAtpEmKMJnSbkUNCnhr9zDitu1urwUUVaUAcQ8khSfBclLTjmteJoVoli2ftwWiV3JyGv1qjJzRdgrXZntAR6SF/Dwf90MZ2wFPIF8Li5iC90vYYqXvI9nFaJbn2gXA/1v1UDoNirk7w39woAUnxdOACk8IVRk5szqdXtCKkvrQiAlFyjLhskLitf86Rz9wut1nBHs0rwm4Z4jOc4NQEwFAR+7E3B1dKMaS8H36kH8HyhBZ/6kxThCyIAHk6r5EQW8fy7Watjr78IgKL3j7z5WmVoeg1VvJwmAuA+XT13chFjtHbHNbH3UctTQ2OYeujSDe5MA+CQKT8kpFLnGtpO8ixpJYNQeA79TQAoliMSIfBsQS73G54uBNIqUN7cTdMCwOlC4J16AMOZFgCSY0PdESQSANwd14SzBbkM4VMB4N74QCklKqkTCgBpH7y6MlB+5pUVEgDVkgB4B6IL0S/TC9kTFCoOkCCDltpo4hvPcWrGAVJZDlpaPmF1cFbwxSIzZwZSX9RwXkARii44c3gZYyA1sHxK3gmagEYySxm01BBIkye1a/vUn6ToG6wGQXptOOijWL8bVclcCiYc/J2wOjCSWcoA6Jq/BecLLVyyZdBYgaNZJZxdSvuXkmhEb0q3PtC+jwCZjtfZglxFT2cKFqdsbrrQ96d4Fcu/dNEbMxdjb3xDUAKIOv5vV1zTPQOAFFc6lQeQbiguFpmDWhL2pwRiLilBRgTAgVQvzhbkhkwGOZ1vU9ywaHkBT9nsuFGVjOGMMm4BKAKgFgSO5zhxxZ2J6z4Dw5gaArWg8HYAkKDzmicd130GzkZWZwMfy3YpAJDG8+USE9+khQLAQWMFL+NqASD1EVcD4IHEWlwuMQV5afbGBzI3qSxMOAik+L8DibUzDoDDWYGSIaEgcHdcE0ZN7qCbMLU3cFdck2IZWA2AagikGOpQ8BeqLRz9HDRWwDV/S0RJILcLgX9qAKQ6nFTXcsJSyF5RcVyFAkAKgdm5dh3HAYvLvwSAr08CoBj/R/Gr6tqXagDsM/iw/dn1QZ4/sheekQAoAfAOJAIgnTxj5mIGi0FjhWY9QAIwiisTS72QZ+5IugfHsl28rEh3/OQdHDMX80QZzgtIAegEgEfSPfiw3MiwScunl1zZnF1JEEjB9KfzbYqJVfQGMrjVJ+ByiYlr+JGNZJby8pLaztjzcLU0AzdrdfjUn8RLdaIXhSbME1YHZ0XS9g1nlKE/xQvPwkA/Y8qeHDKW45onnQPtyRtKcKPV73Y8x8nev0FjBTdx79YHlvZpcqX9tk9Xz3C4J74RB5P8OJLu4eW0Y9muoDpXu+KaOP5v12SQemds8z0DgHRzIkJdKAAkmBNr1JHRTUNXQkPQ+D+db8OQsVzTC0ixgOG8gCOZpfiw3IjzhRYUzd/CADgVBB43F+FsQS4+9SfhcolJcYMxnuPkPsAizA0Zy7FPVz8t+COv38Uis2Ic0/uHA0AqYUPLYeISsBgDSBn84oRM0NGt93Pf2n26egUA0rgWJ2oau1R/LVzMljr+b6YB8BdpRehJrg4bq0hJWepzUb0cPGpyc0FyAg56vjobmJJBCKSn6wXcp6uHc14r+lO80wZALRCk9xcfo/p4kYJfOE/kfl1d0GO74wJt+A7pa3DGnoeDSX7FsnikHsBdcU04ZbPzvhcLnmsB4PZn1+NYtouXf7UgkLKHxfp/WkvAL61YJwFwpjfgVX4aDwAAIABJREFUyyxxCZhOZvJCdev9PGGqAZCC2mnpizJ7Kf6PJtjxHCeXJjmZW4AxczEng5AXkO6e1F5AcbI+W5DLS04UqHvFnYmBVC/sczcziFKtNRECj2W7cLU0AxecOYrJVfSiTFgKccpmx+USE3vxblQlc82z0/k2XC4x4Yo7Ex+WG/k5n/qTcLU0A6fzbYoJWb1cdsaehw/LjRjPcSrgbySzFCesDrgXtCmSB845rDhls/N+HDKWK5IW1OVLaJ8QrBCk0FIXLZkdTPJjwlLIF/H+FC9nBJK3d098I9d0VE86VDOwc9IT2Guowo6YFvw4rmrGJtH3k8sUIEae4EgAcNTkZk+p6AUk7yDVRxS9gIPGCkVSjtoLeMLqwBl7Xlgv4NGsElz3GVC5qF0BgJFA4ISlEJdLTPikRo+LReawdf3EmLyp7JzDihtVyfiw3IgTVociCUTL+6deAh4zF3PBa4I/Or9FCDyW7cI5h1XRKUeMzaIVAQIPAsD9ujqcc1gxkOoNghY6n0KV7RAn7n26evZczzQAdukqFWVr1EbL1QOpynNRDYGUDXwk3cMeQLEjkNoLuCe+EUPGck54iAQARQjsSmhA3txNoHjl24XAcB5BOpZfpOdPtD3xjbDP3cwhNWImcKQQSHGax81FimNBAEjdl8SuWvt1degz+II6k6iNYq3DAeBP4r0SAGd6A77MErPRRjJLcTApMKkfy3bx0mKoZeBTNrtiGVjMBqYLv7h0eyTdg3MOK08MZwtyuWTJoLEiKGNQXJKjZWPRs0JZuI55regz+HgS0oJAKrlyzZOOCUthkDdQXD6j8jKn820MYmfsebhcYsIlVzbOF1p4qU+cfLXAj0CVun/Q9pBRRxPyYlKRaxGOqS6gGpBF+KBsaoLBswW5ikxgumgPGit4cj2QWIv+lFvt88iDsDe+gTuEqGNduvV+LjpLnQp2xLSgx1AyY5Nov9GpgDDKVJwqCURcBibgFSGQSvGoY9eoCwvFSKq9gAOpXlxxZyriYUUvIEHgqMmNykXtPD6nA4EEgpdc2QxtZwtyg2CQ4vK0gI+yy6+WZuBGVTKuedIVy8tq8BPhTw2AoyY3btbqcDK3gLOAtQCQShodTqtUFC+nSZlCF8hrI3oAe5KrccmVHVTCZJ+unj2GagBUQyDFuZLXbaYB8O3YQHkhre0UPXajJjeDRygvoFgUWmzpGc4LeM5hRbc+2As4VVmYroQGWKIDMEM3O3cCgVogOFUdwDv9vK6EBrgXtHEcswi+oQBQDYEU+yd6/wgA31yzQRMAR01uRVs9dRYw/d6f4uVlZHX7vlcmWyP+KrNAAuBMb8CXWWIdQIK+br2fvUndej+GjOU8AYrlRiiQvc/gY6ChuD1qcUYwSdBGMXWiF5AmCppY1EH59PeYuVixFDxorMDZglx4FrbxxC9CICWGiBA4nuPENU86LhaZFQWj1ZNrpHFUWpMlvScVzT2ZW8BFr8VtoVjGXkMVA+BxcxGulmbwMjrVThQTQdQASEvtdGzO2PO4m8VAaqBuI5XRoBIx+3V13GmAEkGoQ0C33s9eCa3iubQUPJJZypNQb2rxjE2ix3JzgrxwtL8i8QKesDqCgFGseSkuXYoxbGfseZoASMkol0tMIbuDHEn3YNBYAc/CNlz3GUDJJZFAoNZYJZC77jPgY28KrnnSccmVzTcp5xxWnC+04JIrG1dLM/CxNwXXfQZ8WG7keNVIwU8sA3M4rRKu+Vu4GDp5HOn7ijGA/SlehlStDjYUfkIhF2oPIIVjqLNXaclea7JWT9p74hu5xReN7e0x/pkDwBg/X3dDAeBuIWYxHAB2xjbzak0oAFR7Aen6ECkAEgQSAO6Jb+Ss4i8CAkUQpOMpPv5FvP/BJD9Xs3DMa+XYUvp+6v0QrhzMkXQPjmaVBHn/QnkA6TWi90/LA/jmmg1c/kWMCRQhcNuaDTic4ZAAONMb8GUWXYh+Eu/lhISDSX4uuKxeBhZjzqjIMHk9tJJBqDQJQZ/aC3jGnsfLCIPGCpyy2TmeUGvCpt66NLEOpHpRuqBNURqGTkqKYRIhkODrlM3OIDie4wzrbSGPjbo2mtYkSTFU5JGhmm/i54+Zi3HJlc3vTQB4NKsEH5YbFR5UygzWqpVI2ax0DKjm4hl7Hk+uJ3MLuN9kryHQvo/u4ikOkLqCUI9QKiOjBkCaDCgRhLIO9+nqsT/JM2OT6D/lm9hTR/tmzFw85TIwjSnyLquTQWgpnTqmqGMuT9nsihsd8fMpIURdFkaEwEFjBZzzWrk+4HQhUA2ComfwlM2Ocw4rTuYW4HS+DZdc2bhYZFZ4r9U3MFpjWsvrR0a9uP2LO9hDLRaDVgPg0awSXHJl81hVQ2CfwYezBbkczyUCICV/kKdGXRS611ClGbivhkCKgRXH9kwC4PaYwIoLbVMoO5jk53qe4SCQkkHeimlhAAznBaTkGa1l9XCxgCIAUmIZhZ18UZCmBsAvyqjU0yF9DazRGxkAacxN5QWk/UchCXviGyMGQMpSf10FgGoIpG3Qqg1ILeL26+oULThnqyQA3oFEAKQLES0Di9nA5FFSewHp4kGxPVQTcNBYgSPpHr64ixOhGAt4JN2DS65sLhEznFHGWZTiErC4ZHe+0MJA2WfwwTmvFecLLVz0mCbYkcxSnvDUS6800Z7MLeBOH+QJESe9MXOxwrOoNTGO5zi5n/DV0gycsedxr1/1557MLeC2YeQJ6jVUoXRBG9c4pP0kekjV3j816BCAUJYwealO5hawd4G8hOT9o4r+h/Q1HD+1X1eH8RwnV8AXA57FZTN6fudk+6O3Y2tmbBL9R0tuUEtByuqL1AtIsC5C4CF9DfpTvLhcYlIkMdC+o37MWnUBxaVgMXZVjAc8nFbJHWBO5hZwq8BwEDgdEAx386JlkXr9yMhbXb6wPagTiNoDKJbIUXtTyejm72CSXzEh71y7jpNQ1PBH1xZ15mYoCKTrmDi2ZzJ+dXtMAHSmWgambOA98Y1hYwE7Y5u5tE4oAFRD4MEk/5TdQdQQqAbAA4m1fMN5NKvkC/HWEaB+kfA3ZCzHGXse+gw+TgJRewAJAtUAqB5TtMqg1alFBMCtqzZxQs6oyc2ZwKHg7/XJLGFKEtHqDrJ11SaMZJZi6wwk391rkgB4BxIB8GDSreUIWgamZUK6cKsBkMqtUOC82gtIzcNpuZXi3MR6dwRQNFnQxV4NgDRhUwkJKuJrn7uZJ2q6CxUD7k/mFnA3BS0QHDW5uc7f5RITrpZm4Io7ExecOThbkMsTItUFPFuQiwvOHMVzzxbk4ri5iN9P/TnHsl244MzBGXteUMeE4YwylC9sZ68QgfHFIrOmF4sAg4L7CTzI+0PH53S+jRN7KECcLtaH0yr5QjecUcZ33HRMaDKiCYPq4e1cuw574ht5+Xfn2nWBJY01dTM2if48xYWzBblBcEzez0ggcDijjD2tBIGH9DU4kFjL2eVasZcET6G8gEfSPSE7hFAGO8XNjuc4cbM+gWFUbZGAoJb3mjrxROLtixT+Tlgd+E1DPI6bi7gTiLoPsBjDernExG3atADwSLoHp2x2BgcRACljVYzTosmZag2Gm6jJ9sY34Fi2Kwi0hkz5MwqAu+MCWckEpqGMxpVWEWKxNAzB4rY1GxT9gcMtBQ9nlAWVhQlXGmZvfDAAUhYuVTzoSa6+ZwCwW3+rFBmd11MBoLokjDiWaPVrd5zSGxsqCeTNSe/f3viGoOQP9e87165Dr6EqbHu47c+ux6jJjRdlFrAEwDuRmI1GrX4oloPghLI9KRlEXAbrM/hwOt/GXkDymJEXkFpqUekXmhjGc5w8QVOJGCp5QnFZ5OHTmrAJkIaM5bDP3cwFqi84c3C+0MKTEU2AR7NKcM5hxTmHVTMZg8CNvC9j5mJeSiOwOuewckYw9TSmpTAt8KOuHGfsebjgzMGYuZi3h+yMPQ9nC3K5pIIIf2IJGPG70/PoDpSOzQVnDi9djprcOG4uYg/ucEYZL9/QBLxfV8cFo6kYKk0C6mBnihWkrLdD+hq8E9vM8TQzWQZmf5KHM6RFAKNjORUA0n4957AqxiBNFCOZpdweTgRw+qyzBblBCSFiPOKxbBeuuDN57BMEqgGQuuJc9xlwzZOuCV7TBcFQ3uupoE/thRTtgjMHN+sT2MNKtQy1vH/ksRdjKdUA2GfwsSdVKyuYjol6YqZyMVrePy0I7DVUYchYroCqvfENGLdlzSgA0vl1LNsVFgApPEMdmqEFgT3J1eyhj8QL2JXQwKs0VH8vnBcwFAASBNL1nuaPuwmA4naI20KrW/R/AkCqbBAKANUQSB5TrdI86kQQAsDdkzHTYis4NQCS9ad4sSOmZcr+wAcSa2UdQEgAvCOJpTTIjX80K9AVhDofiL1QtXrP0qSk5QUcNFbgYJKf49koW5gyWylTkqCHPDZUG1CrnhtN0GIvYMp+pThCWnoTIZAmwvOFFpxzWDngXMtEqKPtFR8LBX2ix4/Aj/oii16/kcxSXC4x4XyhBb2GKvZi0rKvCCLq707wRwk4fQYfe1QPJvk52J6SeCh7mMrAkPdvv64OI5mlOKSv4QxhqgOoDpynjiDkrdgdF8gEPpLuuScKQVM8m3oJNpJkEDK1F5AAcCDVyyEGoheWYIaSkUItBfeneDljV4TA/hSvIoOdIHDU5MbFIjNn1YYCMTUIagFhOAAM9fpQ4Dme4+SM46NZJTyunEIGuxr+ztjzuPd3qPqVlNxBNQDFyZzCGCg8QYSR8Rwn97SdCgD3xjfgaFYJ9uvqFFDVn+KdkUxKNQDujmvim69wEEjhHaHakYkgQufmOxF6AQ8k1kZcG5AAkGLhtIp5E9Sestlvq1TMnXoA+ww+TFgKOdFOhL9wABguG3ifrp4LwYtZ2eoOLepOIATuagBU246YFgykehkOteDv9dUbuY6gBEAJgHckuhD9zODmE4TavFEBYfL8EZipl4G1vIAUC0jPoUn1lM2OI+keXnajHsH9KbeyfAl6qJVZOAikVnC0dEkTENX+o88TjTwttJRLmcmhYJA+J9T/ySimkLyQVI9O/fnUZYGKaR/S18A+dzNDsPiZWt+bklbUWawEfBRLRZ5bii/qSmhg7x3Vt6Osyv26OkxYCvniLgLgwaRASQ4qAn04rZKbnw8aK9AZ2zyjS8A/TQp4rckDKlokNQHFfSvGAooAOGQsx4flRvZuqzODj2W7eKLRygruT/Hy2CBA6k8J1LAkz5Q4PinrnICLwiKmA4LHsl283BzuOVOB35g50H7xZq2OPSkEq2IGuxr+TufbFLUr1YBMN48ncwt4X4sA2K33c+KHGgCpeK9W5wYtADyY5OcYOhGoTuYWYE/C3a+lpgbAXZNwR324Q1lXQrAXUAsE34pp4Z7fUwGgCIHk0dYqtSOaGgBDQeDBJD+HSpzMLeDr0p8SAAdSvVzKi1aztLaNWsGJAKgFfzS+qIqCOomIuiKFAsCuhEBojdgKLhQE9hl82Ll2XVjv3574Ri4QLQFQAuAdiS5E3oc2ouqhdvgWtaNuSQcalnTAt6gd/sUdaH6kA1UPtaPqoXY0Phz4vWax0jY82oF1j3TAvzjw2vWPBn6n96hbEvh73SMd2PRY4O+6JR3Y8vVbr6tb0oFvPtGBxodv/b3psVv/V1vdkg7ULG7HinnF6Hg88Dp634Ylgb//4sl2tH498Dc9JlrzIx1ofzzwvPbHA5+lNvosrf+RtX498B4djwe+u/pz6PM3PNqB55a2o/mRW49VPdSO5fOd+OYTge2h76D1nRuWBD5L/J7feiKwj2sWt/M+pePV/Ejg80sXtKF8YTsalnSgclE7KhcFjmXN4naULwwcw+ZHOlC+sB2ehW0Kq1kceKx0QRsaHw4cU/eCwONVDwV+dy3YMGOTaOVDG1GzOLDvG1T7rfHhwD7X2pfiOCJbNzke6iaPS+Xk+VC3JPB469dvvU59DnQ8fmtM1ixu1/ycbz0ROFfo+C6f70TN4vagsUnjqvmRDvz5k+34/tNbsP7RwN/TMRpj032daM8tbcd3l7Vh/aO3tou2s2ZxYOzSWGwQ9uN3lrYHHQ9xv/kXB853/+Jb41W0xocD/6exS+O2clE7b0vlosD4DWeehW28HeK4Ll8YOOdncuwWzd+A0gWBc6tyUWBs0LlGpj4f6XuLz1Fb0fwtKJq/BZseC+w/t2Dq56r3CV1ztfYl7X/PwjYsnZ8Hz8I2xXHxhTG6vm96rIPnmnBG2zTV80Rb90gHvv2Ndr5OhTLaf8vm5weNrVBjqmZxO775xK1rpLgPxf3rmr+FzT53M9Y9EjimRfO3wDmvlc2hMue8VjQ+3KH4n33u5iBrWBJ4P/vczciNlgAoAfAORBeiOV97Avff9+SX0u772mMRP/eBOcvu+vZF8pnT+Q5/Sptz3+MKEx8TnxP0/K89MWOTqDh2Q+3r6R73cM+f6r0i+awH5izDA3OWKfZlJM8ne/D+p4Me07JQrw9nWu891ZhRf06k3+dPsf+ne4xncuze97XHgs43rfNQ67yM5HnTfa76NeGOOW37F3EsvsixE6nRd5jua6a7H7/I56q3476vPSYBcKY34MssuhB976lbFcdffKYVWyczjV56phWvrNiMd2Kb8fKKzXh5RaAApbop9asrN+ONyWBXclXvXLsOr67cjBeWt3JxS/rfrrgm7pVIdY/E3ogHk/x4SwiE3RHTonCNk8v81ZWbkRLdgJdX3Eq379b7sXPtOoVr/Y3JWkz7dPXoM/iwJ75R0Z/xTeGn2mi/aP1Py+h9KHOvW+/nwqyi7YhpQbfej62rNiE1ulFRBV5t9P3pOW+u2YBD+hq8MRkr8sbqjTiQWMv7ZOvk/qdj9uIzrXhp0l5esRmdsc14YXkrXljeis7YZryyYjN+8PQW/ODpLfj+pP3g6S14bdUmPP9UG55/qg07Ylrwg6e34LvL2vD66o14YXkrnlvajh8u34LvPdUyY5PoD5c38xikcUTFUml/ieNyKtu6ahMOJNZi66pNeGF5K78P/exJrg55DlB9rjcmj4O4HaK9uWYDepKrkRW9Hq+s2Mxj9A1hrG7TGJPbn12Ptybbfo1kluJwWiX26erRGdvM9cdEe331Rry2apPm/8g6Y5uxN76Bwy6ovd/2Z9dj+7PrFeNabGj/+uqNeGXFZhijA/t225oN6DVU8Xmqrl0m7iNxrIr28uS+PKSv4WvR95a14ftPb8ELywPjd7+uDi8+04ofLt+CHy6/NVZD2VsxLXjpmVZ8/+kteP6pwHu9+Ewr9sY34Pmn2vC/ls6cB/AvntyA7y1rY/vB01uwO66JtzWU0TgN9f/vLG3Ht78R8NxS0eDvLmtTmPi59Drx3H9zTSDJ44fLA3/T/qZ9rptbg+efauPriJa9+Exk9vKKzfx5tOxKS6q0pE9L0XvjG/BWTEugF26E76/erh8u34LvLWtD0tzaoO9G35ce3/7seuyOa+JrI+0r2ne0P59b2o7vLG3HXzwZ+Pny5Hj/1hPt+PMnb9m3v3HLvvVEwJ5/qo2f+80nOtg6Hlfa9mfX47mlgdWG9sc7sPGxjRIAZ3oDvsyiC9GuOB8HXVPsxpi5mOv4UcyZGAuoTgah0htU246SHaj3IRU4pmQRyjqjAHwqEE3xgReLzBwvSOVhKPCb4ox6DVXIn7uZu15QvBa1caOC1mL5DcrMvVqagYtFZq69Jgbii9af4kW33q/ocqD1vFGTGxOWQlxw5uBqaQbXKxTLY1Bm9dmCXI5/pBhA2q9i+yxKnqGsaCqDQ6VJKCmEYtcolo0CrykOkOL+KCmkP8XL9QDHc5x8YRVjpyhWZ/dkliL1T6UyMBRw3muomtF2Wu8lVijKElGdL9HErjVTxQJSBvHJ3AIeu2Lc2qjJjSvuTC5orI5rGzKWc8/aUPGAlCDlWdjGJWLUZWLEckbqsSnGnF5xZ+K6z8C9qy+XmHDOYcXpfBvH8FIw/ISlEGcLcnHJlc09rakN3Ol8myIWlj5LjF8VaxhSxrljXiuGM8pwtTRDkQCm1bWGivBSnLFoVFXgnMOK8Rwnx2rtXLuOYwDHzMUYNblDxmmpjWKaxbjWPfGNHB95LxSCVsfyjZrcnGQQLiOYvpf4OL3HjslWZBT3dyzbxT28I40H7Epo4GoI6n29J74R5ugN3FtZq2OIVmxgqFhBMWuX4j+pW8shfQ3HIWtl+0Zi6iSPPfGN2Ll2HSzRGzi5Q/0duxIauFLDfl2dIjkuXEFuulk/bi7iG3+1g0C8kdq2ZgPHUoslYdQ3pTtiWjBqcmOr0BFExgBKALwjiXUA9+vqGEgOJNZyVihV6T9uLlLU7RKD4OkiTmBHE8CRdA9f2MnDQP+jGn0EOpQ5S1A4klmqgEBqlXbC6mAIpDqAIgCKWbtUCHo4oyyoE8NwRhnGzMU4W5CLK+5Mrv13Ot/GiRYEWZQEQpm/VAD6lM2OC84cXHFnclYvdR/RSj45nW/jNnSUNRkKAOn7UucTgj8CSzGxhrKrKSmE6tZRqzgKdCagpAsj1Q1UlzqgFlt0wRs1uTkRRCwDQ+U4ZjIJRATAPoMPF5w5GDKWKwBELJtDY3EqGDxuLlJAnGgncws0M3/pnKCON+EgsCe5Go55rXyzIvbNDgeCIgyqk5CoLRzVqaQWcNc86bjmSccVdyYuFplxxp7HPbEJ9kToCwV+4s0UXSs8C9s4eUkNfmr4o4QrrX1KWZsXi8ychHYwyc91KAdSvTwZq5MSQkHgqMmNbr1fkRCyX1eHswW5DE8zCYB//2xtEABSOSYq+hwKAqkbkxYAvhXTgm2TAPjOpBftuLloyqxgdWZwV0ID1/UTE0N2xzUFAWA4EIwEANUmZidPBXeRwp8IgQSAotdRtFGTG6fzbQx/WvtZXX6HbNQUSKqkLGDypG/TsK6EBvQkVwfVB1QblTB6TQLg/8femwZXdZ15v2oP6TDbmEnMCCQ0cSQhgQChowHNMwgNaJ7QdHR0/dqvuS5TENN+cePmxW2HhgajEKkhEFoyNFxoaAhw4aIABQRMbNx2kq7qpJJvnZ4+dLqqK8/9sM//0bPXWXufI4n4QL9nV62yOTrD3nutvdZvPcP/MR1BABzHgYloKGEjW4hgBYR4JrJLb60vYWC5kFhlkoWREzmkKOD+hNQLFmKZlQmQArwAqiR0QRBZZvgiowwAiMoMMkMYi+lwajF9kZ/OlgcdmMGCd8dZSA+zcrhu6tclKazVB0j8uiSFvipOZbhECS+rxRMWxy8LnXQvPd9rQQUIoIIFAOB+Rh4L3cqSZbedRXyN99LzvSBaWmGg64hMSNR4Hoqr42uW1j+084nVPPFBYxGWB1j/IFg6ENNMBwIIgGcSy0xjEPdblxEM8XDVGqezWp1NqGHLqw5WIPGjg0CA9+d5GbxRUSHwbEINW6/vphXQ1yUpXCFHQqA/IKgDQn8y2HWWbB346SResECWTekx3Usr+HuUnUW3nUUMyer9knqLsK5CHBllty4kVnkt5nANqhAIPUw1IxjyUFjMPwkwAKoABivghcQqWysgtOUgaSKhRJaCQ2YqVB0ktMjMYStL4InYRrq+diN9lrOBJWIkAPqqGmJlDfTVcA6j+Ywd9KkbBwDgMXENsAbeTSug+xl5bO1UdVF1+n+4p3h2jwgZGAmAEgQPLd9K19ZsokPLt9oCIKqIqDWBg0LQQQAc1yGrKeDBgXsXAs5SDFoWcockhgqB2OlDA/BsQg1XCwE4ynq/sERYQc2NdWXs8sQCdGNdGT3KzqJrazYxAKruU7mQQgsNumRw++oWQJ0LWIr16hZM3UIMd/CTgjR2QcoFFQ0ACAvf9bUb2VKCa0DJPHmfYO2R9wn3DfAHt+fJFY0cMwaL7oPMXDodX+u1eMI1LKsnYNLH5/s81j9YAgPpAv5/U7O8QhGgiyhhBNZSKUuiaxjHkLDQlXuDtNHPStexBqYVBOrORQIg6ipDyPxJQRr3lSqvIi3YVhAoxyA2RHbApwM/K/jDs/R5XgZ9XZJCl1aNSNnorH8Aw8e5mZaWP2gpQmZH7YsTsY28yfLl2pMWnNvOIpaQkda/h1k5JtdpIMsYAgAlgEFiCfJNKhxKAISWp1qRAkDRJwDwqKdM3JXkzV7agf5AIMTSAabOCe18rjqpGAmC+PtogNAXAMrvsAI+HfipACgtgKfjjdKCt9aX+AV/UgLmaFQrnU2ooeHUYra0IrZXxtJKELyQWMXVQazKw30c3kE31pXRQEwzx9EGAXDkCALgOA5ZTeFiUiWdcjR4WQExcQ/F1XGN3bMJNbzA6cSh4Qo+k2AABlxUmNhh0cMC9SAz16sSCCqFAPi+Kk6lO85C00J0N62Aiie7eBHB+9W6q6pFDppscPkOpxZzfN5YABDiz3AJf1nopIdZORxbaLWwqgCI70C85OXVFXRrfYkp5g+QrMZQyn9j0ZeadbKeMyozYPKUi+fFpEqe/ADUxzyuHsQB9ke30IXEKp7oAlGUHGN3ODON41MBFIgpxXjD2ETZP1/wBwCU1gCdFRA1bpE8of79YlIlQyCEk1UAhHg33o/+hlC6zi2sjids1EY7dmUJN7sxio0JYmcRlnAmodYEgKoVUFb5sYK/y6sr+B7qLKXY7CAWTBf/pS70EKaWYQ0ASVnq8FkBQFjj8GwNxDRzv+rctLLhPknLngqA0uKHvhiLJRDVV66t2UTpAgBlkoYdCOrATOrwqQB4LKbZtq/lf/0FP/zm0ahWEwBeTKpkIXi5aVDhTxf7dzSqlU45GuiOs5COxzbxPQX8oTSchEBAtS9x6BOxRiziR0pSVdAFbBxBABzHIZNArq3ZxJMrYpegqC6rg8Dthbg7NSFEBuSjgPuFxBGBaBkPKIHlYVaOyW0FyJH1cb/IT2ehYwBk4WQXV/WQ1god/KmWEwjYPgInAAAgAElEQVTufpazgb7IT6cvC53sLn6YlUP3M/J4sUQSyv2MPHqYlWP6DOoG30vPZ8ui1e/qALBwsovupefT3bQCUy3Vu2kF9FVxqgkE7mfkMewhYUaFPyz+iMNELOf5xGq+V+hrORHDugtL4HBqMVtLrq3ZRIOOeuqPbuGA7KNRrTQQ00yfrtwY0FrADzJzvcDicW6mCSoAFoghtQI/CYCIhVQTF+RnriaX0y82rWFhZAl/aEjUkZZwCYCqSxqbga+KU+lJQRpvUKxcwVaWQHznaCx/6hi9tb6EvshPp5+XraX7GXmmWEUJgKob+GZKKT0pSDNVrNHB38/L1pruLWKGsVFE/dbzidV+QSBCHdTQhnMrt9BnORu8Eicur80L2Nj9JLJWC19ItrqfkcfJELqGz1xfu5GhRgKgLj7tWEwz3XYW8fM7WgjEhr54ssurbJwdBFrBoBXA4fd9WfdGA35yowsAhLX4UXYWC1CPFv6wuTgR22h6fX94Bx32VAk5IiAQlVqOeGI1rQSiD0S003BqMZeGCwKg9xEEwHEcmIi+HzPi1sIkitJiUNG/tMrIhkVGLurMwm2jg0DEsmByRxavtFLBZXl5dQVbzQCWd9MK6HFupqnSB2L0ADk5E7sYIAFsvuDPLoZK1gJ+kJlLw6nFdMdZSI+ys+hRdhY9yMzlWsBWrjW731StLtfXbqSyKT0MebBuPs7NNCUHXEnezL+vwp/uniLm8l56Pltzb6wr4wVVAuDJFY0M/tjRI4D+WIyRiYesSSSCwPp3NqGGvhe9JaBJILgHMhThSvJm+rLQ6eWaRFasFfipFkD8G2NO97lrazYxBOpiC9E3gHdYLFUAVCEQFmAkGlnFsVqNaysAxCbD6vM31pVxScWvilN5YyIt7BIA8Tty84YayVZxgYA/K9fw5dUV9GWhk84k1HLYAgBRVzMYDS55tYrDo2wjVEAu7IOOerrh3BCwsTuUsNHSDTsQ00znE6u59CJeU2ENAAI3oQqAKFOGzx2NaqXjsU10x1lIg456v5JCJATCLZ09sYsrY+gyaH2BoJ3lzg4AVauhvxY/tfVHt1CBJwkLiXJjgb/jsU2cta7C9oGIdjrsyQqWWcKXV1fQyRWNXjGBKgjiWVArgwQBcOQIAuA4DmkBHHTUs6VoKK6OJ1xY/oZTi9mFiEBqO1ewTB65mlzOgAn3Edw7Ogi8tb7EK4lDSrrcdhaxWzRvUjdbYoZTizkxQxfQ7o/VxF832rU11pIwviDw2ppNdMdZyO6UPFFPFZYfwLKMu4ILC9YRgI+8l/LeotzcKUcDXUwysigRt4lFFBMnagSfiG3k78euH8H0AzGGJAwWDpSPCmQSyEnHCBxLKxKSOFAmT0IIypyNBgABlFeSN1vG+/1i0xqW47FqsKhdTS73CwBhDYY17KviVPpZ6ToeDzfWlVmOMemG1rmNJfDdcRZystPXJSlc9k2NAZShFhIAsSHBeclShvL6kL36i01raDi1WJsQgtJ+gAsAoA4CISGCDQykp+TCfzW5nC00Ug7mjrOQfhi3OWBj9+/W5LMkiQp1gA7Mu2rsmQobZxJq2WV8aPlWUxaw7v3IDMazLOHPyhKI+9Yf3UJOTwLFrfUlXMJTB1tSZsVf+PMFgPBQjMXyh2d6OLWYiie7eM5TS2Dq4K8vytuaesdZ6GVN1QEgGuYiXVygbP3RLXTbWUQHI9otawMHYwCDADiuQ9ZTHXTUs6UHu2lAHjQCb6wrozMJtXRu5RYvVzAsMLJhcoa8i7TAwEqlg8AHmbmcAYsYQNTXxSKEZIlNU3s4SxaQB7jCDhWwNhrw8zeOajTutetrN9K99Hz6LGcDJ4acTzTqqV5NLqfHuZksqYHrhAVIhWKd5U+FP1hnh+Lq2PUpAQmwDyg85Wigobg6dqEdj23ifoUcB+KN+qNb6GKSkWEcSBmYkw4jBOFBZq5XLN7FpEottElXsL8ACHf6k4I0r8xgwAkg8I6z0NIKiGflXno+lU7p4ax6aUVT4/7k+EasKoANQAgZos9yNtCDzFy22mFTcdtZxDVZkQz1dUmK6bN4XqwSQHQyMIhfvZ+Rxxs1XKcuLvDGujL6h/JkL++A7DNIHV1IrGIAVF3vcgyfjjfmpLtpBaZNzSlHA52Or6XP8zJM0iKQUbmbVhDQLOAfOIx+tUvKOOVo4IQQK/hDu7TKeI4hAyPjC3XvBwRCbkdn7dJZA/ujW2j9hK38HafjazkpDeLkUjNwNOA3XhewHQReSDQSFCHvgixgVQPVDgKl1dUO/qQLGJ+D+kJ/dAvXC1ZBEILv0HncrySFSAAciKkKAmCgT+B5PuROFA8QFvyhuDoGQohzDqcW08UksysYEzFgRAXAU44GFmcG9GFHLqVbbqaUmjTwIFyLxeZqcjl9lrOBTfZYGIsnu3jRk9B1fe1Gju1AVq0O0MYLgP58B0R7AX7yPM8nVlPZlB56UpDGMVaIYXyQmeuVDHA3rcCU7SvvndSwkxYguNWxcKLPAB+w/g066ulmSinHAULGB5MhstYQB3hu5RbPTjfwAHgxqVKbsQurlPo6ko/sYgABgNKCdWNdGT0pSOP7qVruriaX09clKaY+UgEQny2c7KIHmbkmaR9VAkYnBSPHCMbfrfUlDHiPczPpi/x0TqZ6UpBGX+Sn0xf56fQ4N5O1I2+tL+GxqMtQt4I/tLMJNVQ6pYfjX1URcxWAbzuL6B/Kk3nc6+Dvs5wNLBdzPrGatSatQB3j+G5aAZ1PrPYCAjxTcoE/EdtIDzJzaSiuLuA6gLByWkFgf3QLb/Ds4A9WQ1juAYB20Ngf3cIgc27lFi/gkXGGEgKPRrXS+glbqc/jBcA9RT9gjsb8r4KfPyB4bIwAqIIg1CywDiDZ8WhUK1sxRwOARz0KCDq3r5p0IwFQelKkSxgQeEDAH6S3DkaYK+9ICDwY0U7nVxUFATDQJ/A8H1JLTcb/qQkhFxKrWBYD8X/QlUJWMARwZTzgUFwdnVxh6MpBpkQmJ0gIhLYYtOsur66g284iTvrAwnjHWUif52WwJApElB9m5dBXxakcBygtb6imAVCEAO5oAdBf6+G1NZtYQBVxe3KxRcNkWTalx7TwQsRail5fTS7nhVuCMuAQEALAxL/vZ+TRpVWV3H8SAOG6hCUQ5wVXCZJ4jsU0cyhAf3QLS8Ig5mgoIXBJICcdFTz+oIOoQsLDrByGCrwXcHjHWWgLgDpARP/g2dBZ+iDCrIMiACAkjO6l57OF2wq8dIBmlxQCyMKzZhcTqwNLXwB4a30J3UvPp7IpPaa4QHmtsj3KzqKfla4zJeCo8lGf5WzgRBmMVV8AiDg5NbFp0FHPz4xMCDke28TP8bMgBI2kCtXFq1oCkbihuiHVBqv9EcX1aAWAsOzfdhZxbK8Kf+q5SABUk0RgEYRrGN4ef+RarADQX8sh3jcUV0fnE6tZ6B9hILBMIlnDCgCtYgAHPPPg3bQCU9JNn/Jf/D8A8JgHzAcd9V59grhAlF48FtNMd9MKuJqLmiUMCLyQWBWQsfusHUEAHMchYwCR6TvoqGerEFy419Zs8nIFAwgAJBIoMHlLAMTCeT8jzwSB0nKgQqBMdIAOINy/sDoUeESU4Rp7lJ1FXxWnclax6oJVwexuWgGXmNIldKiB9Pge/BeJIEgceZSdZQJNFfoAwl8Vp9Lj3Ey6tKqSYwCvrdnESS4o44X7jQQAKQx9M6XUBB53nIVe8DecWsyuMIAfIBCxm9Kii5gY9KOUSYD7B5YW1Or8f5KKAw6AGH+f5WzwCke4kFjFrmD5XiwSOpkS1QWsNlgCYfnWQeDdtAL6Wek6k8QR2rmVW7iKDfoe1jq47wFjOgj0J9tdAqAKerrX7Bp+646zkF3NF5OMsYsNnA4AYRFFZRTpDpYWVBX+pAVQbl50sZfQJ8VGBtbpL/LT6UxCrSke7XR8LT3IzH0mKoEciDCAACEFdrCGTFNY4KyADpB2IbHK1m2syzrGfCk/p3MJH4lso/UTttIRD9yoECh1/7Ap/SxnA93PyOO1BKCmgqEqA+ML+vB+eKGQOPggM5e9V1ZZwP4AICDwWEwzz7Eq/FlBOWq+I6FSB/d475HINjoS2Ua3nUV0IrbRq3qIhEAk4u0JxgAGAXA8h8wCPrdyCwdQy/i/obg6NknDFQw4kQLRiAdE0Pn5xGovAMRuXYVAWLqkqDEsW1hEkOUrF78b68po09Qe1tuTLrEHmbn0ZaGTHudm0m1nkTY2D+AGaRdk+j7MyqGHWTkcV4Y6v/cz8vi9kIIB7N1Lz2eY0FkFh1OL6XFupinAHvepYFI33XYW0ed5GabFHxMaXCpSGFqNm7yXns/whxg3WL2wiErrH+IDVZFv7J6l2wzagIhJknGAV5PLqS8qcFnAQwkbGeqQYPA4N9Nk7QTsPilI8wIM3CskKvkLgHAHo1yhVdIHKlygPjM2OhcSq0wi5jLhB/F0yIq3gjFf1kDArwqI8t/+WBeRFfykII11KgHTAEAZu4j/v+MspH8oT+ayerqYwMurK+iL/HTWZ1TvswRAtSFp7GLSSHiDjDu+mlxuWvgRT4ds4IFnBACRTAENOauGMBwroEM7HNnG7mBs2nSQqBOZvrTKcNVD/N1K/DhlQpsXAKqyMNL9i8TCmymlPHdik4y5SMZ0qkLQyPpG2MqV5M08LyM0CONMjQPVZQNLAMS5WwEg4PhmSqll0o5VEgjGpq4P1AbruBobKCHwYEQ7XVtjVA8JJoEEAXBchwTAU44GBohBRz3Hf0lXMB4uWd0DSSD30vN5EobLEgCoysMgJg6LwtXkcl6E8TvX1mxi0JTJD7CEwfKSN6mbhlOL2XKiWvwAVl8Vp3J8kWqVg/UQDXIwUn8NgfSoEaxaDHXuYVQfgZ6bjP+Ti3X5VDfvjiXcIqNZ3gMApgp/mERh+ZNlt07ENjLIA5Ig6wNtx4tJI25iFI+HfhpKckEcGosKJuPvhjcEbBG9vj6LARANCQ9qUhJi5HSxZ5DXkdnvVgAo4/6ur91oqoWrswQCSmENtANAadnDpgEwiIx62fCs6QAQ5wuw1FkKraAP1vov8tPp87wMjivVJYFICyDO50lBGn1VnErX1mzSxgNeTDLuCxKcrLQCrQAQYR8ykQdjFTW0ZQzayRWNHA4iMz4DDYCAAoRg+IrzwwbADiiQBALvjc6Na9fOJNSy29QqG1YCoAp//si/SKsdwgkeZObyJvyOs5BDgAB42JxjfsMYV13/Vgkh0hJsZQFUy+0hKe7SqkrLUnBWQA75LV/ADq/KcGoxWwPhElYhEN6Xj8M7ggBIQQAc1yG11BAwO5xabHIFIysY2oB44C4kVpmSQK55sm8lZECPS1cu7tb6EraKSJCRWYSYHFTr14PMXJ78IUR7fe1GXrBguVNdr3fTCujzvAwWb4aFRVbs8DcJRH2vrhqIzKxUwRRxX8OpxVQgSsHh+h5lZ5mSP64mlzMASPe4rFcLkIG2mhR2xoSL75OwJK27d5yFdDahhrMvL62q5InxYpIRy4OgZmS0BTIL+EfrctmtJC2BsACpmw9V1FlCEmJU7QBQTfoAyCCGzyrp49IqQwLm52VruUawWsbQKt4OzxaydxH+gLEnE0J0LmD8Tf2vbLCmADgh53J97YiupioDowIg7uE/lCebYlV1AHgzpZRFzuV9lfcaMYAqAMJqKyEX77++diN9kZ/O1kCAwLmVW+hRdhbHA2JMB7KKjQTAo1GtfE/V2DIVHCANY2VJklnAZxIMCMSmzRf8wRJ4ckUjx1aqYtR9FkkgOr09K/kXSLlIIJQN3ytlftCfujKA/krBAPb6fLiAT8Q2ctIdXNJWGcG6PsBceVjoMFoBIJKV4N6XcYESABHfCVdw0AUcBMBxHZiI/iaxlHfLiG+SrmC4czGZwFQPqxwW3psppXRrfYkp9gqyMWr8DlxoiNnCgomdn3QlwfyOxQfm//sZeVQ82cWLHBY2wNXj3EwGSHXRw+c/y9lAXxY66aviVPqy0Emf52VwfCDgDfB4N63AtFP9PC+DLR0o3yVj/9SsZFgwZcYvSsFJ4evh1GLTtcrrx4KKhAcpp/MoO4vj2QB/mEwHHfX8fVLPEYLPMstb9j3kYKDFhgnw2ppNdMrRQH1RrQG1ovwwbjNn80oIvLTKqEErk5KQLfykIM3L5Yt4svsZeZz0pAKgDv4k7MFKgU2NCoASkr4uSaGyKT0Mn1ZSK2qsH8YD4k2R3auOWySUSOu1rGaD8Suzg+9n5JmeF53rGe3SqkqTDMzdtAL6xaY1LF6uSwTBPcFGTSaEyIb7jfg9CYAXEqu4NrDOJfxloZPPDTGBqPF6PrHatNifcjTQ9fVZzwwADsQ0s5vRCgCR6HEvPd8rqUAHgIBAZAf7C4Cw7OF+n0+s5teRBILYRB386SyCMjbQV2LHWLOA/RGDPh7b5AWAEv5QTebamk2myjG6e6VL2IGnDDqAdjGbJ2KNus/ITJbwLyHwSGQb3VhXRkci2xgAPwhrDgJgoE/geT4wER1fUcn6TaccDey2QVbw9bUbOTYD8WGAhutrN7J0CDIxb6wrM0nJWOmmIQbws5wNJmsbrBFYSGD5QyYtFqGLSUYpOICZ6lodTi2me+n59HlehkkKRsYKymSOmyml/BlAHhZNxPvJRfa2s4h3yboYQ7iBH2Vncbm44dRi03meT6ym0ik9nOErF1pcMyygUkMOsAb4hai0hB3A0PHYJgYN9CMsluhH6L9hp433okrI1eRyXkDQd5jEAlkK7geOkaoxqisYCTeqK/hK8mYGBRUiAFeoY60bs1bxfrCKPylIYze9DgLRl2VTejjbW5d1K12rdgkhsHBDCgbyLwA/uM5QxeZuWoEpE95XMogVoJ5buYVKp/Tw5glalFbZwFeTy9mdLa2CdhCoAiBCMHQuYcRjov8xtiGYLbOBT8QaFq6/ji8P2NjdH1HPSQRoJ1c0+iX5csrRQPfS81lWRDbIisjX8MwjltdK7kV1gcIaiPkCHgBfACgtawA/O4ugCoSj0QH05XLWwanOAoiMbOj72UnC6ABwIKaZQ3H6o1u8AFCty4yMX1hz1T4GBB6JbKMryZu5eggSQoIAGATAcR2YiL4XvYUnXbiCb60v4Wytswk1HA+I4vUABCSFXF+7kSEQ2aiIAcQioltMEQj+KDuLpV1kXKAUQIY1EFB0MamSKxEg3g7uX7mAwfoGiwksdSjnZifpggXfykWsQuRtZxHr9z0pSPOKO5SB9fcz8uiOs5CKJ7sY7rC4wzqnxv89yMw1JR1AbuHy6got/MEKCGssrLi3nUUMgwAIwB+AXW4IBh317JJBXNHRKKMU3PdjqgMKgLBeQpJINsCy6gqGuDhcvioE3lpfQoOOelvrnxUQIuFEp42HvkQM4MUkw1L5i01reCOkgy1fiRpq/J90j+L508GeP9+tc0ljjJdPdXMsop0cjKzeowNnKwgEAOIZ15WOu5BYxdJQ6tjHcwaLLhZ7JJt9ElXzTAFgX1QrnVu5hS6tqrQFQFj27qYVcGIC/qYDwAFPPNvNlFI65WiwtfypTVrGEDKSMaHDBID+uoCtAFBtOCe79/n6biv4kwA44AFcJNxdTKq0jAe0gkBkUV9fu5HOrdzC99zOAjgQ08ybeDvYl+NBlYUJAmAQAMd1YCKqm95BrTN66fXQXmqdYbTu2b305lw3bZ3ZS1tn9lLvnF5yzTb+v32m8d7u2cb/d87qpXfmu6l7tvH/3bN7afuCHuqc1Ustnu96I9RN7jnG/6vNNbuX3HN66d1FLnpzrptc4rXtC3rorXnGZ9FeD+2lbZ7XIiaVUfds4/xeD+2lt+e7affibnp7vpteD+3VtrfmuWnHgh7avbibPgjrovcWu2jbPDe9EerdcC6vh/Z6/Q2vvTXPTbsWueiDsC56f0k37VxonLPV72+b56b3Frvobc89Wz5pE7nnjFzDNs9n5TW/Odc4Z/SDy3NPdy1y8X3tnOXdcI9bZxh91T27l3Z4+qZ1xkjftXv6uXOWcR4YB/itlhm91PSacR6tM3qpfnovNU43zq3ylY6ALaJNr3V4XZd6/bsWucilGXc7FvRwH6gN4xDjczQNffneYhftWNBj6kc0l6ffMXbfCDXG7UfLOmnbPDf1er6jV4yL0TZcy1g+K39Xnsebc920b2kX7VnSTe45xjW4PNegu073HGM871nSzWPan3uojtvXQ425AK/L/n1rnpveXeTyegbQ95ints4cGdfbF/RQ64xeqnk1cGO38pUOqn2116vVTzeuqek182u6hv6Sr9W86qaqaW7+d6NoW2ca/dH0mvl1XWt6zbu1zDD6MGrSZv63XWsdY8M5jPXzaFbnVftqL4VNKqKm14yxsG2eMa/prtnXfWqc3strRaPoh6ppbqp51e3VZ7WvGmNz2zzvv6mtcfrI+6pfMfoVrWzqNz92n7UjCIDjODARvfjCDHrpxVnPafP/3F9+ac43fn7+/ebzfP9n0YsvzAjYIop7/Dy25/nc/7tcw0svzgrY2P0/Zd59dtvzfQ2BmHefteOZA8AbN25QUVERhYaGGlU2zpwx/f33v/89fec736HQ0FD69re/TWlpafT555+b3vO73/2Oenp66LXXXqOJEydScXEx/epXvzK957e//S3V1dXR1KlTaerUqVRXV0f//M//PKpzxUT0f4V20LZ5bto2z03bF/TQ+0sMC9rb8w1L1QdhXfTOfDe9M99N7y/ppvcWu2j7gh5+765Fxr93LOihfUsNK9iOBT30jufzHy3rpHcXuejdRS7atchFe8O6aJfn3/J12T4O76BDy7fS7sXG77232EXvL+mmgxHt9OGyTtq92Pjd+Il1tHNhD30Q1kUfLetkK5za9izp5gLphz2BtLBk2LV3F7lo50LDWujrvXuWdNO+pV2sAA8tqD2a83l/iWF93LOkm1ZOqKddi1y0e3E3tw+XddKh5Vtpz5KR69+9uJvdAO8tdpnu4c6FPbRzodEHuB/495tz3bQ3rIs+COviftuzpJv2in7dtchFbXPKaOm3F9PkFyZRSEgIVc/M53GxN6yLdixw0drJq2nSC5PopT96keZ/ax7Vz6iljlkjO9Fveuxum9fOY2/Hgh56b7GLDkS0m+7FzoU9tGuRi/qiWum9xSP3Cm3f0i46EtnG9/Fdz3iGNRnjUB2juoa+Utv7S7oN3bnlW/mZwdiV/Y4mx8m+pV2cNdkf3UL7wztor2fs6MYVmhy7du/D87E3zBi7yEw85Wigj5Z1mt4nz3HHgh6Kn1jnNXb3h3fQ8dgm2uuxruua1f1T54S9YV2m8Y327iIXHVq+lT4O76CdC3uocdZGCv/2Ypr84kQKCQkh1/wNtGuRYYHdvqCH3pnvotSpq2jqixPppT96kRZ8ax61zKqh3tDAjd2OWR1ell7Z3gh104fLOm29CWjvzHfTx+Ed9ObcEU+LzqMh2/YFPfShx+L85lz79ta8kfZGqJuiJm1mbwo8GoeWb6W9njkG84auYW2xa/Cw+Pv+t+db/x7WtQ/CuuhwZBtbo6Mmbfa6NjR/7gfWMav72zlrxGMFb9FHyzpp1yKXz/58c67x3jfnmr0BsKB3z+6llhlBC+AzB4B/+7d/S9u3b6dPP/1UC4B79uyhKVOm0Keffko//elPqaqqikJDQ+nf/u3f+D2dnZ00b948unLlCv3kJz+hjIwMiouLo//6r//i9+Tl5VFsbCz9+Mc/ph//+McUGxtLRUVFozpXTER9UVs4huNEbCPH5SAeEBUnkFEH6QZIhyD5ABm/d5yFdCV5Mw066unkikav2B3E3yD+So39QbYgsmZlJYUryZtZvPnamk0spYFYJiRySHFoNUbqZkop3U0rMIk5P8rO4gB5JHfI30WSCDKdbzuLTBmV8nvupedbZlPi93GOqAiBgH9kouIe4vdvppSyqLWuooKMb0P8F2L+EJeGmD9kb0PuB0Lf7yzJoI2zVtDbS9ZTSEgI/c9F6VwF5NqaTVQ9eyV9+4WX6Z2wFPoospCSpy6hV16aQPuWjcQAftNjdyhhI49DWbMaiUlSGgaVYuT9QkOShKoDiEQlVBbQjVWrpsbBXUneTPcz8ujLQicNpxZT3qRuv2RgMLaRoPJFfjr9rHQd/bxsLX1dksKJFUjuQGKSlDBCNjvGHsb/53kZ9HVJCv28bC39vGwtZ6hDgNouQ1mVgbmZUkpfFjo5IckqE9gqgUaOZehZoi/U/oIAMGL+doalU8XsGB67/2v5ah4Tp+NrqS40nia++BLtjkqiDyOKaO20xfTKSxPoLyI2B2zsfje8geP+jkS2ecUCHo1qpUFHPZeK08WH4X2QHhlOLaa+qFY6GNFuWc9XxvwhOQTiy1bxf7INxDR7JYFgg4ISnredRXQleaQSx2hjA3HO/sT5WX0/5jpkwEPSTE0CwTXprlV3T9AnyIy2SgpBDCCuBfHmvhJ8+qNbOJlJjgckhEAoet/SpiAABvoE7A4VAH//+9/TnDlzaM+ePfza7373O5o2bRodOnSIiIj+5V/+hV5++WX64Q9/yO/59a9/TS+88AJdunSJiIiePHlCISEhdOfOHX7P7du3KSQkhP7+7//e7/PTASAeHsiFIBMYAdaQg0GmL4ShAYWAQNSWhA4goEuWgILOnV2WJWQz1GoYkIIpndJjqZ0GMWdkD9sFziPLDSKyVpmUAAVIbchsSqvvv752o+lcpKAuFlFUL4F8h9Q9xO9eTS73WjSlBhoEtAHjUrAbMH8lebMW/iADBE3HkJAQemNhBvfdidgGmvbSBKqfG89yMEciG2nCC9+i6lnJFBISQr/85S+/8bH7N4mlPA4BvEj+uJpc7gWBECFXIfB8YjXrS0IGBlqY0MNEAo6/EGiVBXw12SipVj7VzdqOdvBnlQyCzQQErhX3npMAACAASURBVB/nZrIs0dclKfRZzgYWoP5Z6Tr6uiSFRcmRGX/HWajdLPlzLmcTaqjAI8QO8JMVfMYKgJdXVzBwSw1L9KEKf7Ldz8ijkJAQenuJkwHw07gamv7yt6knLIL79URsDU184WVqmpsYsLErAVDXAASo3OMPOKDaxhFPNRCrBkhBFizmJMie6GDIFwDKZBAkk2FOxWb6TIK+SoeaJTxaAATwQUUCcmKAUKskEF/XKiEQsjiQSdMlhagAiH7Ac+6rD6EHeTGp0gT5EgABgX++rDEIgIE+AbtDBcBf/OIXFBISQj/5yU9M7yspKaGGhgYiIrp69SqFhITQb3/7W9N7HA4H7dy5k4iIvve979G0adO8fm/atGl09OhRv89PBUAJgYOOehYIRmWQ284izipFhp0KgVL7D5YoWY7rfkaeSX4DgGS3qEL0GFY6ABIyKWGhUasVSBiE5QPWITUr16rJ8/Q3CxPSOPL3dOeFcyid0sMThBR+hk6hLPumWzDl+WFRvJBYxRAEKQdAsRX8QdZn0FHPi+it9SV0ytFAH0YYchl/EZ3NE19/dAslTF5IyVPDKCQkhM6dO/eNj90fOCoZRiQEAuigCScBAhZkHQTCoovNjxyT0LBDJuto4U9C4IXEKsqb1E231pcwPMn6z6OFQV1W72jH7mhA9GZKKd12FlHFNDdLMNllAfsCQNxPSPdcWlWprWIDSMc4l9B/N62A7jgLeezC+tcXa7z258vzTBmkSVPnU/r0BQEbu98Nb9Ba/nT1ZaGW4AsA4b6HTqeVFVAn+4LN3pmE2nEBoK4kHCAWUkUom4lNLdYRiDzjPNW6v7AGQykC4xCbcWyA4X3SZQCPFgChfoB5GFDoC66RiQ1dW3/gD5tNX/B3OLKNPgpABaZn7XiuAHB4eJhCQkLo17/+tel9W7dupZycHCIi+sEPfkDf+ta3vL4rOzub2tvbiYho9+7dFB4e7vWe8PBwev/99y3P53e/+x3967/+K7df/epXXApO9+Ci+ocssA75EH8g8JSjgSsgYLHF7l7KVEDeBaLGVpYVuEJRWFxWU7iSPCKQez8jjycD3aIJQINVzq68m9QrVKVg4FKT3yMBExZMFUaHU4vZinhpVaXJBQzwg4i1btFUoQT3DosiXI0XkyrZtYPrln2pgz9I94SEhNCfRiWxkPSfLDUsKweWV5gmurRXIihqohHv2tfX942P3eMrKrn/AQPS9a0TiUaYgixfCAAEON/PyGP5HHVM3nYWcd+NBwDl2B1OLWbpIEgZjQcEsRkYDQDK79SNXVSeQZWbq8nl2lJwdtdud7+guSnFuwGA5xOreQMIC7eEP3z2TIIhSv5/L3YyLBxNXE0hISH0SfQmE1DkzwyjFZNnB2zs+gJAFQRx/3wB4OHINhaLHoqr80v0WWr+YSML6aexAKCVLIwUg0bteIQ3ILQGZd6ur91Id5yFDIwIJcKGGnMe5jCpQWgHfzodQCvwg0SMtPr5koSRFVMQ+uQP/CF8R4W/IABaH88lAP7mN78xva+trY1yc3OJyBoAs7KyqKOjg4iMiSgiIsLrPcuWLaM//dM/tTyf73znOxQSEuLV/jq+3PSQyAf1TIIZAiHGCgg8t3KLFwRCpw66W3iQMbFfTKrkeCVYsRCrhM/aQSBA8H5GHpVO6THpq8myafcz8rhuJFzAVguoKggNsIO7+db6Em74O2ARlkQ1RkoCJ9x0sCDB2ncmoZZyJnbR1eRyepCZy6XKsJBawR/i8gDcWDBvrS/hOp7oDwAH+hC7TFhCVPgbiqvjRRST4EfR6R7tsirTLtf5SgRFT7IHwD/k2D2+opJ14nA/ZcOG43xitRcEQkAcECh15VBRxiru7/rajfQwK8ekyThWAJRj99qaTXQ3rYC+yE/ncoVWmxlfMGgFgL6+Q45dlGyUpQ1h7dPVAra7bisIvJpczmUZ1ZjWE7GNdDahhj7Py2APhNrHgHm4fDF24RL+MDLTAMCocoa/C4lVlP3aUoqdNCdgY9dfAJQQKN2DOvjrj26hI5FtdDCinU45Ghio/QVAWMQQG3h5dQVXzxgtANpBoB0cwgXcH93iM9bPrgKJDvz8BUDEwiNOWxcPaAd/mFMh1G0Vvym1H6+t2cS1lq3gLwiA5uO5AsBAu4CtdqIDMVU82erM97BSSIDQQaBMDMEChAn8SvJmLl2GhQkQJ+MAsduSC6/VAns+sZoKJnWzCDRESlUYRCk3ABjcD/4sqjhXf60xMi4LcYQoXaU7t6vJ5bRpag/dz8gz1UG2i5NCwP2V5M1eQfMQQ0bptjvOQlPtTSzWdvA3nFpMISEh9PrCDN4B/8XyMgoJCaE/CSsxAWDClAXkfHXRH9yNZmcBhGsI900FBFhEdRAIMJfudIzjC4lV9GWh0zJE4fLqCk7YUftsrACoVv6Q5QO/yE/n6jRS7BzvVUFQAqAKhzpoRBUECKbDNQ2LjAREAKC0Xo/WAohELzXBRgLg6fhaepybaRrXqtsXlj+4fOEChhD3gchSCgkJoT8LL+RN7IXEKkqaOp/WTVscsLE7GgCUIAgItKpFe9gDgP3RLXQ8tonjjnXQ4kv8GW7hS6sqGagGYprJOaHdLwAcCwSeXNHI1zWWz/qCP7tawCdiGzmO8mLS6EWhj8U0c2WivqhWr0ogugajiVr9Q9cOBwHQdDxXAIgkkA8++IBf+8///E9tEsipU6f4Pb/5zW+0wch3797l99y5c2fMwcifRNWwtUgHgCiJBauRCoH47I11ZRxAjzgsueDC8gfFdLh/kXUorYFIzIBbGJAj2/nEasqe2MVWrjvOQvosZwNbTVTgwmIHQEPJt/sZeaakDukOlhYfndtXTRoBEMgsShX6UJUE2ZJ5k7rZnWsHf3D3wr0sK1cgthKLJBINoEx/ckUjLxzoU+w6ES8D+IMb7X8szKDLqytoKK6O/iq6iaa9NIEqZycxAPZFNdLEF1+m2jmrTIH03+TY/avYEQCExU9WPQEoIP5UTRxAWMPDrBzTPUX24pXkzfSkII3uOAstLdOwkqH8mwRAfKcKQhIAVQu2VVawDB+AuxgJHaiCgyz24dRi/h5YrpHQhM3QZzkbvL7nYVYOW8x1lkHZYL3GpsRfCyCSlVCNB/dJhXBsEDGPqH2KzRzmIFSyCQkJoT+LWcmei79eUUevvDSB6uas5DrRP4itpYkvvEz1oYEbu2MBQEAg7qNVLeCDohIIoOSOs9CrCogVAKKhXi364/LqCjoR28gACGh63gHw5IoRix9g1y4TWAeBJ2IbOSnwWEyzthScleXvqA/wCwKg/njmAPDf//3f6eHDh/Tw4UMKCQmhDz/8kB4+fEj/+I//SESGDMy0adPo9OnT9NOf/pS2bNmilYGZP38+/ehHP6Kf/OQnlJmZqZUjcDgcdPv2bbp9+zatWLFizHIEn0QZ9WIxyVpBICZ6nSUQCzDgBDGAkI3Bwgs35W1nkSkjeDi1mO5n5JksARJ4dGB0buUWyp7YRWcSar0WF9TvhcUEC5qVpUXWUwXYAVZhQUSToIgMYKtFEhZNWU/4bloBu9FOxxuLKMDXCvxwHjJOEpYtxJnIeswI5h6Kq6NjMc1seZV9eTW5nN0qp+Nr6cq6fNoXkU+7lxoWwI6FcbQvIp/+PNyI+6uclUgTX/gWuedn0v8K20ipryyiVzUyMN/k2P1h3Ga2/GAMwjKqg0C4fCUEnk+splvrS+hRdhZblgGA6Bf0nbz/sp+uJBs1muE29gVA5xOrbS2AdiCoi2lFcL2sY43geLWONTYpGL/+uoWfBgDCOvIgM5cTAHSxrYBcbDhlX55buYUeZWdxQtPp+Fo6FltFeyMK6MPl+RQSEkJdCx20N6KADkYaG5zaOQk08cWXaceydbQvoohSXvHIwCzfHLCx6ysL2BcEYtxBIkYCoK4U3JmEWrqXnk8XEqt8gp8uOUJ6c/Imdftl/QsUAPo6JwAgNnkwQKjubl8AiIYNCdztaik4XR9iDrey+h320YJZwM8gAF6/fl0b79HY2EhEI0LQc+bMoT/+4z8mp9NJP/3pT03f8R//8R/U09ND06dPpwkTJlBRURH98pe/NL3nn/7pn6i2tpamTJlCU6ZModra2jELkn4/ppofcLhd7CAQ7mAEZ992FpmkOABEpxwNdDy2ic4nVjMYSgsVFkuZDIJdvery1IGgBECd201a3KD5B50+GVdlt/gCqtT4KKuFGnWHkcH7ODfTyyIpz9EOAAF+2HmriQgPMnP5HDExwx0JiwjcaTKOBvcG8AftvD9ZmqUdu+tfWeaZ1JqoZEYCTXtxAr38Ry9Q9KRZ9CdLNtKBiHqeiL7psfujdbkm958agmBlCZTADGv09bUb6fO8DLqSvNkEgNik3HYW0Rf56TyWdQ2xgcj88wWAsF6PFQB9hS/IsTvWZnVeKgD6gj9ANqwsug0dLK530wrofGI1hy6gDy8kVtHj3Ey6tmaTyer3rsXYTXs1jE45GujTuBqqnRtNr7xkjN3ISbPpz8JLTHWsv+mxO1YAVGVfrq/dyNY6FQDxPkDJidhGVig4uaJx1BCIGMCMCR3sKr20qpL19Z4WBI4VAP0BUkibFUzqpqvJ5ez58lcHUFr/TsQ2cg14NevaCgDhxr+0qpLh77AP6EN95yAAmo9nDgCfpwMTEZJAAIHnE6s5JswfCEQslXT/wgpyPLaJd+2wwgFYsKjKZBC4NB9k5nrFXsGaBhBUAdBXDBaC7IdTi+leer6XgDMyc3FOSMZAzJ3O9QtriyoEjaQTu4XxYpIBatkKAErwkxZRTLgyYB7wAvceQBwxcVeTy1nkdCiujq0u6FNYDJHtO+BxFyF7WCdvgAkUC0xf1JZvfCLC2P105UaTJQgNshNWEIi4P1Vg+EryZvo8L4MBWQIgkkOeFKTZZgEDdh5m5ZgSesYKgGMFwbEAIMIEfG2MVADUPWv4f4zZO85C/n5p9cP/300roK+KU9ljgBhiAOCV5M30ODeTxyfmH2iTQvdNZvpKQWA1W/SUo4H+bk1+wMbu/oj6cQNgf3QLnU2ooZsppXQ8tsnWAijb+cRqtgaqoDPgAwD7o1s4CeTkikbePMFDgbXjmwbAE7GNppg++dtDcXV0MamSBdGH4uoo3Q8ZGDsAhEX1SvJm01ypCkFLAOyPbmHNXGnpU+HOVzu0fGsQACkIgOM6MBF9L9qACEDgyRVGIKyqpSStSAgux0R8NqGGrR5yEQbYYfG9vLqCHwBYYGANlNIwF5NGAsRVEIRF8GpyOeVYAKC/wfjSDQxXGlxn99LzGfwQJwgXMKqFyOxif2Og5PlJAATgIvtOXjOEomEdxX2S2aqwhCGuBJm/qChwfe1GOptQw/2JxRmW2pMrGhnsreAPiSOAv+OxTXTSURGwRfSvYiv5vo0GAq8kG8LOsDzJBhgBfOuEyu+l59OTgjRba+Dl1RUcX6iC4HgA0F8YVK3XY7X0jRUAAX64l1b3CVD9KDuLxzbOHRuXW+tL6LOcDeyel/AH99ulVZUm8FPhT53Lrq/dSEMJGwM2dg9F1ppiAEcjCaNmAA866unW+hIadNT7BED8W1qv8Mz7YwGUAChBC+sCwmmgRanT5PtDWgBPrmjkZB/EfGMNQUIcXMBWFUDsAPCUo4HXCTWm0g4Aj8c20c2UUhqKq/PbzXto+VbLFgTAIACO6+AYwMgRd5fcNfmCQIAGJuQzCbWccSbV16UKPJJDADnSBQcJk8urK0xl4+DuRHkrmS2YN6mboVK1LvgLgnZNgqu/cU7+gB8aqikgyUSNMYM1FK5d6S6/m1bAGotwrV9aVcllhBCrecrRwGCOPoSmIaAfsTA6hXsr+EPsy18urwsoAA7F1bEkjj8QCAv05dUV9DArxzQOZfYpxMdln8gGcMF3WI07CYKwUkkAlJuRsTYJcPh/HQDahTA8DQC8vLqCrZ8AP6vxf3m1EfLxVXEqJ1zJyjYIXcBmDGLfEgAh+I25yh/4O7mikWNwA2m9HkrYyLItso0WANEAdENxdaYkECsrICx9kNK5sa5M6xa2A0AZH6ha3VCZA9ZBWfnJqkTcaAEQ/YxYWnhOMJeeSajVuoZ1AKher3ofTsQ2srFCVwbODgBPx9d6Kio12sKfHfCpLZgEEgTAcR1qEgh2TXJH5wsC4VIDcJyOr+WKE4AJxAXifdIKo+rYXVpVyRY2CTyXVo1YBCGQfDahhrIndvFELx/+pwWDgIanBXyXVlXydUNqAMkAMvkFi6juPiBBBW5wWFohjooFEkLeUPZHOTjcP8S9oETcKUeDJfydXGEEgAP+BjzwNxDTTPtFDOA3PXZlFjA0Ga0gUCaGyMx0CJNLAIS78Ma6Mvo8L0MrBQNIv+MspC8LnaaMVt1YAxzBklswqZsB8GlAoNoAgE/7e3UAiMQrxLuqGyX1ngynFtNXxalelYEkAF5NLmevAvpNwh8AEpUfdPCnsz5B9sYAgcAB4CdRxvhTM0DHAn8y1g/jXMYFWgHggICeC4kj1YOwMfRlAbQCQB0QQvwZoSmyRrXUU8XYlRtveGmkXiuaFIVGf/s6nyORbT4tgLgvJ2INbwmSFOFqtquyIkvBYVM+ENP81ODvcGQbDcZvCgJgoE/geT7kThSD3goC5S5aAiDiweC+xeR8aZVhvcJkDDctoAeLMOJHsEDLuCWIRcsFAt+BOr15k7pZs03qswGwMEFgQRotEOLcxwN8l1dXsD6gCqhDcXWU7QHAq8nlnCGJcmOqJRTuXmk5xWQqyynBynpu5Ra21iFh52xCjSmr7/LqCq9JTU5mAH0d/PVFtZqSQL7psQsABASiv31BoJoFjMQgjEGMd9x7VKGQFmh1zD3MyqEnBWleSQ66sXJ5dQUVT3ZxhQMZL/o0AXA0LmZ/G87xfGI1FU92sQyS1LHUPReYE54UpNHj3Ex2C8t7CXc7suZhxZaJPijLBf0/Ff7wvOrgDyABSPgkqiZgY/e74Q2sO6eTARktAAICD0e2cbKHFFX2BYGwcl1eXcHzjA4EAYB9AgD9BUGr5BBsTjHf4jWMYQn/sl9H+3s4T38AEOCHmG5pHbUTgZaC3FeTy7l/oQuoA0B/we+gx6p4PrE6IGP3WTuCADiOAxPRmURDxBkDHwAxGghEgsGlVSML8qCjnidcGZ+G3Z7UZMPicHl1hUkyBlAES4AMyr+0qpKKJ7u4BJtcUOSiA5FbCWCI27ODN8ToyRhDXxB5JXkzx8DIiiG4N+rnzq3cwosodt/SFXZ5dQWDnw6S4RaXUjzYSaPmb390C11aVcnxJ5h4ca+w29VNZFh8Vfg75oG/o1GtdCaxLGCL6A/jRpKR7CAQ0If7q0IgkmEQGC8BUEoV+bIGXk0up89yNtAX+enaGs4YJ1IGBjGmcPVjg/AsAiCq2iARqXCyyxJy5TUjw1pmUevu4dXkcq76gRhACYAo+3YzpdQL/AAMdvCHsAfAQKAB8EhkG4fbSAgcC/xJADwQ0U4nVzSya90OWCQEDmhAUC0LZweAY4FAXZNu7afV5DnaASDGCsAPnhF/4A8N3qzjsU2mJBD0L6x4vmBPbYeWb+XkqH1Lm4IAGOgTeJ4P6YpAXJIKgTKwFgunFQQOOuoZuCAlcyymmaVRZBwWgASuXBmvJGvbykoccH3KRXzDxE46k1DLdYDhXlM1xlSLnKwJLJt0SciFXlcHWEKeCpew8Ol+//rajewuu7GujAomdXslGsClhjgqCX6XV49UApECubinMh4KCyLiqWS8H6x4OrfvQEwzA5Ua8yfh79KqyoAmgdxwbuDwA38gUGaoSwBEu7ZmEz3MymFNMFkiDkCOjHFdbKBMbHicm0lf5Kd71XQGAGaLGECMS4zjh1k5pprWY3XRjhcAkTV/PyOPHmblcGLU5dUjGpYyBlAd6zfWldEX+ekMxFbgBxcbsnyxCcSCDCs/3HBw0asxyReTKrWxZdLtK2FgIKYq4ACog8CxwB+aTAIZiGnmWGJdwoKVJVBaBC8kVrFuJOYMOwAEBI4HBvueMgCq56cC4InYRo7Tk9ZPf6p/yHYitpHXAICczrrrCwCt4A9JfAcj2oMASEEAHNchs9GOxzaxhUl1B0sIRMKBOvlKCISVD4XIMXnfcRZytqqU5AC0SBCE1Q6LgYwRhKXm+tqNlDOxi4bi6kwLsKy9C0kXKwucFSBKKQ24WaVgLlxhvr4T8R9IZIGVBzVkBx317AJG7B8WfoACzgGAh6QGKaeDSQfiz4jru+0sohOxjTw5ydgoGeisTmT4HhX+4PYF/J1buSWgMYCD8Yakiw4CAes6CIS1VgeBF5Mqve6/BEHI8Xyel0HDqcWWbmGA4KPsLNa2w7ixEjHXxQxiY4NKH8OpxVqZofEAIJ43PFsPMnMZ+FC7WhceAQ1L+SzAao3qIthIWd2nmyml9EV+OstBybGNDQs2TTK5CdY/iNJjrlIzQqH3qcLAUFwd/X/pmc8EAB6JbGNPi13ZsNECoEzgAoD7AhmrbOAzCbWsIZg3qZsBUQeAEqx8gdkfGgB15wcAhKUTXiZ4vnSyOFbuXvwdiYzYNB/wQJuq9XfExvWrAz/V8ncwop0ORLTT/w4CYBAAx3NICyAech0EXkisolOOBp5QsRjaQSAywNTFF7IDMiAf8WpSHgaxWViYVCsY5GAKJ7vYcqezyMAKgdg6aP1hEYU1SF24pQsY12LX5CIKl60EPjXDF+1MQi0VemLBUCEEi5m0fgL81PsDS6Qa/wcr6KDD0Bo75rEEXEis0k5wcvI/m1DDrmMEeqvwB/d1X1QrfTcA2WgYuwMxVZzIoYNAbDBkDBnGHVy2ank4fM/l1RWcpKBCIOJR76YVcK1aK7fwxSQDNu9n5NGXhU56lJ1lkjDyJ75Uhheg6ocsP4gmpYpgtYasESzosnThw6wc/g5klQOYfJ2PCoAQwf6qOJUeZuWYrPC6ewO3sJoIIvsDkhsIX5DQh9ATWHNV+AM4Xl5dYQKBYx7r9v2MPPqBo/KZAUBpCTRKLY4NBHUAiJJw2Lycjq8dFQBKEDwW00zZE7t4ow2LrB1wWYGe1d/GC4B2vw/pIIQPQf1Al/nrCwDhKYFVXCbeSACUsX9WAGgFf4cj2zgc4oAH/oIAaBxBABzHgYnozbkd5J7TS+45vdQ7p5d2L+6mt+a5qdfz7zfnuumd+W56PbSXX3t7vpve9rz2emgvvRHq9mq9c3pp2zw3vbvIRW/OddObc9301jw37VjQQ/uWdtE7841/vzXPTds8r+9Z0k3bF/TQNs9r2+YZv7NrkYve9/wNv/3WPDfFTKykbfPc9P6SbvpoWSd9ENZF2xf00Dvz3dq2fUEPvev5rn1Lu+ijZZ20P7yD9od38Od3L+6mdxe5aOfCHj6/7Qt6aMeCHtq5sId2LXLR7sXdtDesiz4O76ADEe38+b3i8/I83gg1nwfuwZ4l3RQ/sY7e8VyTbNsX9ND7S7pp1yIXvT3fbbon2z33aseCkXN8c67xOu7tG6FG/3TP7qUdnnNB/7lFc80eaW97Ptc92/ica3YvvTPfTS7Pv7s979mxoIc6Z/VS56xeapnREbBF1DW7g96c66adC3tob1gXjzM53t5b7KL3Frv4Hskx945nbMl7u83zvtdDe+ndRS76OLzDNO7Q0Jc7F/bQgYh22hvWZTnm0DDGD0a0U/KEZu5nX22Hj7ZzoTGudy0yrnX34m5+7f0l3fT+km7avbib3ltsvAfj29f3bveML905vTXPTSsmVtP2BT20P7yD+qJaaW9YF38OTXdPPgjrokPLt9KuRS5+Td5b9A3mA/Qd2huhbu73t+aNzEOyveu5TjlvoeEZ6ZgVuLHb9FoHtc/spfaZvfwsdc7q5bmie7b59c5ZI8+gXWuf2UutM3pNz7Bsr4f28n2Vz797jn/NNbuXIiaVUfdsY214b7HxjOwN6zKtG+NpuNan8T1yHdsb1kX7wztox4Ieipq02e9r1s2VrtnG+oZ5R/1b6wzvvu2c1ct93j6zl7b60bbNM8Z764xeU6uf/s2P3WftCALgOA5MRC++MINeenHWc9qe53P/73ENL74wI2CL6LM0dl9+ac4z9T3f5DWO9pyflWsMjt2xtuf53P97XEMgxu6zdgQBcBwHJqJGz070rXlu3kG2zzR2TdLSg92UtBB1zx6x/snXXGInih0Rvu/NuW7TruqNUDftXtxNb8/33j2+Pd+wIKq7fFixYiZWsgUBlgGdRRLWsT1LummPxxqyc6FhndgmLGj4DjTsjHUWTmllgiXnXY918IOwLnp/SbfpvGTDObrn9NKKidVsodNZMrbNG7FSucW9eT20l7Yv6KHdi7vp9VDzDvUtjwXFNbuXWmYYO0l194mG69zq6a+tntc6Z43sNjtnGX23dabxfS2efu2c1Us1rwbOitI2s8O063bP6aX3lxgWbHX33jvHsApts7BS4H7ifnTO8u6LnQuNMfTWPO8+lW37gh76aFkn7Vrk8rJe4buiJm1my4QcR/uWdrFF8V2P9RdWy9E0XNdYPouG529vWJcn8LyLz8c9x7gG+SzomrSi2t2zt+YZFr+dC3v4GW+facwn6MPXQ405wT1Hb/2CdVy1uHTOGnmO8Frj9F5qfC1wY7dlRgc1vdbLDc+VbLAs6f7WoliE0Jpe66X66fq/6SxM7TNH5lnMA/JvqsWqdUYvhU0qopYZ+vlEZ9V0e+b+vWFd7GXZudCwquOZwPzVPXvkXFUrJsbAm3ONsblzYQ/Pt3vDumjnQsOqaWVxQ2t6rZeWTSrRXqOVZa57tvH8b1/QY2u9G7HQ6ftV9nnTa55xqDRYghunG9+jtqppbqoKwLz7rB1BABzHgYnoQEQ9i/1eTKrk7CeIg0rphBOxjZyoIbOBEZcnZRkQDyHjdc4k1HJChVT2hxwG6oVKwWjECyHzjTjkAgAAIABJREFUFfGDQ3F1tGFiJyc8ICsXwqCquCwC+BGThaB3VBpQ2920Ak4kQEYuYqjU9yFLDnGFiHuSv41rQWKIFILGPUX8E+If8Z2qiDF0Em+sKzPFviGxRkphHIlso/7oFlMMFJJCUKoJAc2IAYQaP+p9QgcLAc2IBQ2UIj3Gbl/UFh6DMgkJWbpqTODZhBrOrJXSOTIeVRaIV6VikOAEGRTdGMM4g4zG49xMTgDBmJAi5rrEIYggP8rOoi/y01k7735Gnt9xev6KmCPpCdn6yMZ9UpDGJdpkIgjOcyiujqVs1Dg/BNYjxk9KOOnu1a31JfQoO4v1LPH8H4tpppMrGjm2FdnHmGNUmRdku6rxXxeTDD03KXbeF9VKhyJrAzZ2/3Z1oUkcWKcB2B/dwvOqv7GAh5ZvpQMR7aZ6wVZNxv0hRvtqcrnpPqnxcEejWmn9hK10JLLN7/JxMg4P6gSYh1GCE/XMEb+KGEM0WaMdceEXkyo5ZtkuIUU9x8ORbbR+wlae8+waxtat9SV0buUWbd1fXdsf3sExgDIRxEr/DzF/J2KNuRWxnGpDuFEgku+etSMIgOM4MBH95fI6U31ISCngYT6bUEM31pXxQ4ZsUrVKyOn4Wg4O1wEgIHAoro4XUlnD9nS8sQADBFWZE8jEYAI4n1hNGyZ28qIvs2UBWFIIWgUyq8VIBu+ri6ga1O7r++QkB6kYCainHA20YWKnqZzRzZRSurW+hLOQ1ezou2kFdDOl1JT4IcH6TMJImaUTsXoAlFqPmMgAddCuOrR8Kw3F1dH1tYZQOCYyTOCY0AJRkxJj9/sx1dokpDMJtXQ/I4+urdnkBYFnEmp50ZHjSwK21KLUQSAy/h5m5TCg242B4dRi+ixnAz3KzmJwlACoS0BSM9NlNjkkZgBpn+dl8PcjqQMbIiR9IPHjUXYWPc7NpM/zMvjzAExkzuOZsUt8kgCIjc3NlFJ6lJ3FGdJIfLK6NzfWlXH1EJkAgjnhWEwzDTrq+flVdf8AhwjCBwQgcx2JbciGV4P5A1nG8JOoGrqZUspZqVYQeDSqlcefmiH8tABQgiCe+etrN3IVIQlEvgDQXxi0a7g+u6QSX83uvPwBQCgJoM64VZUkXTsa1aoFQBUC1SxgrJ0HNeAnW390C/3dmvwgAAb6BJ7nQwVATAjYMaOUGyQTMCEAAgcd9ZwpK62BmPAxEUsAVEEQ1j3IVmCBPrdyC91YV8YZtDL7FZa0y6srqGBSNy+QMktYBUIrMWjIaFgBHc7XDhixSPsSgdad36CjnvImdXN2J7KA1UoVN1NK2SIJPUVAMwAT3yctIyoAYncJ6womM1jHsMPvj27hDGSZkYjfPCImsGcJANVMdFhmVQjEZuWOs9BLSBsAfcrRwH2nZgnLbHRAmS8QhNAxdP7KpvSYxp+vTHN/dC1vrCtjawqygHXWE1l2yx95JLVBLDtnYhdrJ8Lap4qZ69r1tRvpfkYe3XYWsfSLhG30A1QIYOVRARAC3pDIUDNLcb2wBKkLeCAB8KNwY5N8M6WULfU6AMT/Y76F9VICYJ8FAPoDgVYVQlBDHHqt2NSPBgDHCoS45qcBe6MBQHjBoLoA74g6bnzdVwDgYaUfrWRg+qJaWcZIB3/7PcmGByLa6XhsE91YVxa0AFIQAMd16ABQQiBkSvCQwRV4MamSJ1tZLQHggXJMMJfLRVkHgbCCQPdPLsao3nDHWcgWBSnVAesZAAoWNsiU6BqsMurCqYo6Y+LDJGjVIGEjBaB1sCeBFBaoy6srKG9St9bSBB0/1RoqS5tBY01KZEjrHyQV+qNb2Gor3TvHY5sYHKXm35XkzSZNsqNRrfw+dQILJAB+L3qLJQBijEEGSLrKZeiBdAlLAIT1GxZlFcxlv15MqmQQhK6lHQieTaihvEnddDOllB7nZtKj7CxbAfOxNH8ljEbb8DzedhZR+VQ3yxf5soxDggQ1ruUzqgI2XPGoyKLT/ruaXM4VQVQJkEFHPbvddRIemOsCDYBHIttoIKaZbqwro6G4Oq0lUMLg8dgmQ3xdhGjYWQD9BUA7EMRzgHnyTEItOSe0jwkA/W247j/U90sAxKYYklowXljp/vlquO+QcLGzAB6ObOO1tj+6hd3AVpY/SBsdiWyjPwtrDgJgoE/geT7UGEBdXAigRe6q4Y6CNiBcwnALwfokdQTlBK6DQBUEATyqbhs00OAC3TCx01QzEnFCACxZe1daGuyaagGEu1Q2f79HxhveWl/CMX3Qlju5opEhFrBxa30Ju3kB4dINDiujel/VuCj0zdGoVv683C3Lus+qYOzp+FqeuAZimvl9OvdFoAFQrUqjg8DLqyvoQWYu3zMJgSifJ/UpAYBq+IGqxaiCIOLZADlWsahnEmopW4iYX0neTMOpxeyexecRLhAoAAT83nEWsmv3UXYWDacW09mEGo5ftbP2XVplwDFcvepzqAM/bAQHYpq9ABBxnAAhtSbsuZVb6H5GHletsVvAAw2A0IU7GtXKVnzVWqRWBoF1/mxCjQk4rABwtCDoq9LFmYRayvN4XuSG8nkCwP7oFsqe2MWbiItJxliyum5/752831YWQMyfRyLbeBN6JLLNJ/whzOfQ8q20P7yDPggCYBAAx3NwLEpkrW1wMBYRWRj8bEINC+xi4oX799zKLVx2CPAB4NFBIBZp/BeWKtQMxoIpY7RQNqt4sstUXUFnSZAxgYAwgCEC6WG9UAEPMGEFiXDdqeXl8DtwAcPaoZ7fKUcD5U3qZiuVtHLKa76YVMlxOecTqzn2zw4AEdMn4zmPeSZxxA9KNXvEZaoxOKglahW78iwCoM7qjOQQlIiTEIj4U0CXCoBqkogan6mCINyciMeTAt8qAMrYU4ynq8nlNJxazPF+gEJsDOzKDcoYPX8AUMYYYvPxMCuHf/dBZq5XrW3E42VbACCSxxB3iHFrBX4qYMPSDejAWEdilCxJKb0RKKGI8JVjPhbxAwGsYgMAPCwgD3OZWj5MlwAClzBCbSQA7g/vsK0XrELLaECwz+MCRmwi5laIquPZGa+F7mkB4PHYJg4XAPBdSKyiDRM7TUlx4wE/HYjbxQAOxDQzPKsi0Cr4HYxo52f1oMcd/HEQAIkoCIDjOjARnUk0YmTsJoBTjgbOLAUESqV9WXoJwAI3hYzXAdzoIBA7fWmhwUML97AaH7RhYifDKMr5wE2tAy5pqdHF7QHc0FD6DfFTapOJJrKqiO63pYUSiS7X126kgknd7BZUrX2wHkqLqIRlK/hDlt3p+Fo67LEwHI9tYtCRu90TsY3swpMTGZJ1sBhZBS5/P6Y6YIvoX8WOWIH8gcDT8bU0nFpscgmr1WowHpBMoksSAeCgVCEysHUbBZRGe5iVY3LnI4NdBSeriiJYvFDV5rOcDQxpSACRlT3g0kK2uqz+8Sg7y+vzKDWHxVzCnmzSOi4BEJbMO85CvlZdbK4O/ADIuMfoD4xPxFqijKFa9WMoro6fJ1npxm4xPxrV+swAoCwTho2YzBC2qghyzAMSZxJq/QZAFQQRI+wvBAIA4b6GoQDeHjw/sF5Li/ofGgCxLsHogA05QmWwMYAL+KjHw+Ev+FkBtK7pALDPM6/C5aurAiLh70hkG29YUbDg4yAA8hEEwHEcUkoDxa+tHn5Yji4mVZriAvEa3IZyMUZGkwQUTBKYGOTijL9LCJSZm9IKBomPjAkdDJ3ShYRFHu5ixLRZgZmVJcfKAmi1oMkgdsSGScsKym1BzuZEbCODAD4D6yYmLSyI6n3RASAmPki5HI9tosOeiRSWQ7kwQvphKK6OJy64fIfi6rxKF0kAPOxxYfx1fHnAFtFPV240jTtf7uBTjgaWDXqYlcNZ62qD2xihBjoIBGRjocNYsAsJQBb33bQCKp7s8plNbgWEKhzKZBBIaOB1gCAs6mryh/p9OFdf5zboqKeciV10eXUFQ9+99Hy22ts9K0gwwsZD3fygH5DFC2+Dzsp9MamS7mfkcaiKdPPpFnS5SA/EVD0zAChBcNBR75UcctgCBLFZgzVwtADYp4EaOxDsi2qllAkjlixdOxbTbDIGAArlZhmbdFXWB3HLiHmUFl48zzAOIMQG8YlIfML6Akkz9fwOLd+qBcDRWPzs4E8HgMdijHKciKPWScDIpI9jMc2cwCTBLwiAI0cQAMdxyBjAYzHNdHl1BQ3FeSeEyIf6WEwzL3zSJYxg+8urK/hBxmfwoMtFGROWBMGTKxq1AKjGbMEFfCV5MydQqG5iCYQAKmj+wVIodftk8obqAob1Ul3MVfev+htw6cqYP3WhOxHbSNkTu3ihxnth7bMCPzWmEvGDSMaRkyZiNKVl5OSKRgaBYzHNJs2/i0mVnD1sBX9HItsYKAOdBQyA8BcCMcbOJtRwH0noAFAei2nmTOFrazZZSsYA+iDD40+sKZJApJsYG4OxAqH6d5lpP5rmK5MZUkw3U0qpbEoPDacW+33dyIRWk2pU+IMlFjJRVvIv0I6Tnglfrl/Az+n42oDWAt4fUa8FQGn9gs6ndCGqFiUZq4t+P6iJAbRqdhZAXfMHAK2gEMmEeP6kJwYhNNj4yg2/3LxITwus+FiL7Ny5dgD4NMFPBcD+6Ba+1v7oFq+5VFf/FxI0fZ7vUeEvCIDGEQTAcRxyIsKDgMXUFwTCJYxdOh7si0lGCj0kRfo8UAFAkRp1sBICBFXXsC8QPOVooIwJHRyHIt0OOquN1HiDjAw+d2t9CWfcSoDTCUHDsohMSLwHQGW1sKlQCtjLm9TNQd0yNs3q+qULGBZDWGSkK15OOsjuPR7bROcTq7kgvOxj3BtM8rqF6dByY9KELIRRHeKbL0quCkEDXuTY8gcCh+LqWMYEIsMSACWMwH1rNa5UyxbGoa6djq9lDUvEqUKzD0CI7GRfWnpWgCgTmKxAT8bvqQCIxRkJMvcz8tjKB4tc9sQutlzbWUDxPQBFu+cDbuSryeXsAlYB8NKqShb7ltIvEv6sFm7Euw466gPqAj6XWEJHLZ4zmRyCDSaeS7uG5xxzhAolVtqBo0kSGSsAjqbhHqgwL/9fWu90Ln9/AFBaP/29B/6C9f7wDjoR28hzpRSD1ln/DnpcvnjeEe9nBYCB2Hg/a0cQAMdxSCuKnAQwYatuFPVhA0xIayAma8BNf3SLV8UQxKapu3lAGWKq7CBwKK6OTjkaKH1CO1u4pAsVLgFZmUNngZOLt67hvO3eg++wAgIsftIFAuA9HttEGRM62K3hD/ghSUaCn3SLwe0COAe0wUp7aVWlKeYT4I4FQw1YhrsXkgWwGmLSCqQFsC9qiwl4ZQWU0UDguZVbGOzPrdzC1lJpFTybYAiiIxYNwK4bRxJ6ZPiBDgB11mUVvACFCCHQJTCpkGiVwa6CICwwsGAjxvBhVg5r9cFVKy3kpxwNXgBoZe3TJWlZgR/0RuGNgJoAQhyw8RqKq9PCn531D3MW4pMDCYCfRBkbV8SkWUHgkcg2GoozxK4BEnYNrkQ1FttfGPQFQEci2xgA7VzFTwMA7d4z1t9D7J0KgOMFPtmwDmJOVTUArSqAoI8PRLTTxx740wHg0ahWOpdYEgTAQJ/A83xIAJQxYIAFGRdo9dAh+BeyDVKOAVlq2AEBUGD1QDyh6hqGhexCYpUtEJ1c0WgCQLXJgH0ZJyLjoaQ7Qbp+JQACLnRxgtJSoiaUqFVIsOjJc5QAqLPwyQbAASSrVhG45s8m1JgWxj6Pxe762o2cnd0fbQig4hpgrdUJlgIA0Z9YZA5GtFNfVCv9VWzg3GgAQEDg6fhaDmWwSw7RScVgzD/IzGXI1Y0rHQjabSgw/iQM2gGgDgjxvMiSbXechQyHsqHqB3Qq8W+r995LzzeVMlTDIazi+XQAKC3ruFbdhkkHfjfWlTEcoz8AbUNxdewuv5BYZcr+tYI/CYAIbzifWG0KeQiEmC7G7p8vM+ZWCA7bQSBgCK5zAJwVAO4P72C3MPoFc4E/1kA7EAQAwr1p1cYDgJhzfIGcP7+jOzcrAFSve7TgB02/84nVJpFnKwFoXCeSZ/qiWjkGEO2jZZ0m+Du5wpBiC4Tn5Vk7ggA4jkO6gAFRMK1jFwOXl+7BkpMu6soC9qAt1xfVyvp90kUnQVC6f+XCjIQGWLpUGAQAYoFQMzqtoFC6YnXB84BEWMtkIL1salA9Fk25yPk6n2MxzZQxoYPhVwVAae0DMOvkTWTihwQifA5SMOi7QUc9W8vkYqLqjyGDGMkohyNH9KrwPYG0AP7AUWnadGBc4X74A38qBJ5JqGWLmHQLq+MI2ZqIEVTDDnTWYsAgBMAhLeMLAq2gUGfdkzqAsAKh+YrzG805AACR3ALow/fYgd+5lVtYskWCn2oF7482auFCSkaGOfiy/skNK8Bdzm99zwAAAhDgodAJBUtLYF+UIch+Y10Z1+a2A0CZgIA+VmVjRguB/gKgDgb9BUN/ANDKIujP+RyMaLcFwLGCnwTtjz0xgLoKIIBAVPU4k1DL+o0qAAL8DkS0s/Fhf3gHvR/WEgTAQJ/A83xgIvpueANPEsjwxcAeiGnmRUUXY6Gm4SM+B1alIx634aCjnq4kb+Y6qCoIAmKQfSoXaWkVhCsJcVoqAOpiBUfb1CQNiJ+qbazfL89RB4AS+nC9atIH3iNBBwsj+uDW+hI6n1jN2YMDMSOljs6t3OK1GCLuT05Yx2Ob2BIsd63ou4MR7QFRpMfY/dE6wyKkQiCsPXBt+wuC6AN8zx1nId1LzzcJK+uszKiOAY0xGRqga0NxdZTtqaOLzEWEKowFCHVwiOsbK+BZfTcskRcSq6hgUjeDpT9hElLM/WpyudYqjj6QSQAydtjK+qeDArh8AZPqwj0YvyngAAjYwcbDKi5QPpfHYppNYTYqAH4c3uGVJAJQwUYBIvGjhcGxAKAdGOr+jXsiX7Oz6I22jQUAda9DokjeT9zvj8M7OK5PBUBA/7U1m6g/usWr7JsKgIcj2zjB8mOPVTAIgEEAHNchARCTRX90C8fnyYE/FFdnWRtRp8UEy4ZM44dbGLIOEgSlGxNxTTpr1+n4WpOLeMPETi/9wKcJgzj/sX7eV1wfAPB0fC1nFKtxkLpsX+k+lyAN8EMm7zHPbro/uoUXb1hnVfhTMw3xW5iQsZuFlhZijQIJgN+PqaZb60voanK5l/UT8ZCw4vlrCRx0GBbxgZhmBpF76fl0N62A3bdWm4ZLqyo5M1UnFi0BUFaxUd2nOsvyaGHNHwkjf2BPWshlSMMpR4Opio1VO7dypKwhhM51Gyk8p7jf99LzObZYB3++3L+QnFLHOza219dupL9JLH0mABDAA01OteqODgL7ogyR/ZsppTQUV+cFgL4SRc6t3MLeAX+tXk8bAK0a7skf6vsPRrRTyoQ2EwBaXbPqKu+PNiom4bmUwvmy6QBQxnOejq/lGEA7ADwW00xXk8vpaFQrfbSskz5a1kkfBgGQiIIAOK5DB4AY7MjQlbsiJABcSKzymmx1ENgf3cJuyNPx3vGBkJPQWWmQFAKr4Ol4bxhEGTUs8ngvAsifBhDCxfS0gA+/DXfgmYRayvG40QAG6nXCjQdXOCyk8l6hQoJMyEE/YNc/6KjXTnYq/EES6HR8rUmvCq40GWgeaAD8JMqId8T1A94kBAKMseHwBwRRC1T22aVVlZyIobMI6lyciK0D1FsBoA6apLVNAhikMFQtP9XSpwNAnbsYYRCIU7QDUDVBygoAz600krEQq6i6yHXPDO7vvfR8zmKG1Upmt+vcvwMCAAE3cPmqY/7kikYuZRdIF/C+pU1eoupI2MJ40bmEVaAY8Dyv19ZsouOxTT4BUM7zAx6vDzaUMj7Sqv13BEB/4Bf3Cl4XGTftCwCRQIcY26NRrT7h76DH5YsKIIC/IACOHEEAHMehAqDqMkDJN5kxiodAZw1UIRCuDMh0qCCIxfny6gq24qiWGglAKgyeiDVcwNC1Ox1fy65kWNKweGHR8QWGEg6H4up8AqA/3wXYQ6IIzuvcyi10PLaJ0ie0872Q0Cdj/3QWLCQjwNUrF8YTsUbiyuXVFTxRqa4O1fp3aPlW/oyamQgrLWIA5YQVaADE9Z5PrKY7zkJOgpG6gEjk8dcaiDGv609poULykx0MXkisohvrykwweDq+lgHQlwVNB4ZSgxKAKCERyQIILlcb3i/Ho0yE8udcVACEpQ/Qh3rVUttPvVdwewL8UMIOG0KEplhZ/wCAeB8SlWDVUtu5lVtoOLWY4+cCDYAHI9q1EChdwgMx+ixhFQRPrmjkesJI0PK3waol5ZSswEgCIKRqnlcAxPnbNaxfMFT0R5td7rpKLUci2+ijZZ0cKw0tWlh2ZQbwR8s6vSDwaFQrXUneTKccDZwIIuEvCIDGEQTAcRxSkd6u8DhARz5AsAZCfV4HgYgpk6XjJAjKXf0pRwPr091YV2aSN5ELNHZE2IVlTOjgGENdPBdc0RIKYTlRFzzdQo4FxspqqGoLqhYVFUJVC99ATDOlT2g3ZfGqCR9Wbt7razdqEz9gfQG8YxdqB38nYhtNVj8sMkejWul0fC27knU71mcBAAGBQ3F1XLdWBUB5/2BhsoJAAKAaG6jGad5xFnJ94bMJNbYgCBhEearCyS5OzvAXukbTrDLYn+b350zsoqvJ5ayhKavXWLl4AYw31pVxyTiZ8Y97jjAUFQDR3xIAj8c2sZVTpwN4LKaZ4VdabgIJgJ9E1WjhT0Ig3H/qc2kFgXiWAfQqrPiyCOJ+Y9N9buUWVoLA3w8LAPQ3bnAsgAYx6/HCnu687ACwP7qF66VjHka89GigGkkbcNH7qv6Bur9DcUYVIlgRPw4CoOURBMBxHJiIXLM76I1QN70517u9Nc9oOxf20O7F3bRtnpvb2/Pd9N5iF30c3kHbF/TQ2/PdpvbWPDe9Eeqmd+ab286FPbQ3rIv2Le2iHQt6aLtoOxb08Hcejmyj95d00w7P63jvzoVGe3eRi1ZOqKc9S7ppb1gX7Vrk4r/p2ruLXPTuIhftWuSi9xa7aPfibtqzpJs+8JzLvqVd/HB96HnY9iwx3vOh8vCh7VvaRXvDuuiDsC7as6Sbdi/upvcWu/i3ZNOd044FPZQ0oZG/473F1tewb2kXHY5sow+XddK7i1ym+7Z9QQ/tWuQygoOXdJv6o3dOL705d6Tf3lLarkUu+nBZJ70z3+jzN0KNtm2em3Yv7qa35rnp9dBe6p1jbm5P65jVEbBF9H/Oa+dxJccQgqfl2JHt/SXdtG9pl+W9fme+cf3q2FHbrkUuen9JNx1avpWOxTTTvqXGONS1nQt7eOy9u8hF8RPraI/ns3Cr71lijJ/xtN2LjXG4QzxPuveM9fs/COvijMW1E1pob1gXva+ct+76cb8+XNbJMaS7F3fz33TPylueeUbOE+hr2e97w7ro3UUuHvPqPHUwop32hnV5jf+eOYEbu7sWt9I7841ny6phXsb8IJ9P2eScjecT/bR9gXEf7eZ3q7ZjQY9pft3mmdOjJm2m10N7Te/d9hQbrv9pfudb4r+9c3opatJm0z3YNs9N73rG5wdhxtqE9+N96r2zen37gh76cFknz5/oJ7V/5Xz6emgvryOYX12zR1q30v7H3G9+7D5rRxAAx3FgInrxhRn00ouzLNvLL80ZUxvv562+0+7fz2P7Q1+DVT/o7qWu3+3GxksvzqIXX5gRsEXU7t5966V532g/fuuleaP6TfXcR/v5QDV5nmMZu4G4Tqvfe+nFWQEfu76eL1/PqT+fG81nfM3bT2Nt8OfZ+Ca+39/fGOu9G8vnRvP+IAAGjzEfmIhKpnRQ/fReqprmpvKpI61imr5VTXNTy4xeavR8Bq36FTc1Tjd2LvXTe6l8qps2Te2h6lfcXq3mVe/WON3Y6WydaXy+9lXvhve8OddNnbN6afHkAqqa5ja9p366d2uc3kutM0Z2T52zjN9pndFLLTN6qek14z2Nyudwvlbf2Tjd+GzLDOP72mca3+/y/EbLDP354Pqqprlp0eRcqn3VeK97jrGr7p5tfLfuHtRPN37HNdv4f3kP1ftcNc1NZVN6qHzqSD+1zjA+W/3KSJ+iv1tmGN+HvpOtbIp3q3nVTWVTA2dFqXjFGLtvhLq97kXNq8a4aHrNGC9Nr+nvJ+595yzjnte8OnKvrPrOaiw0KuOifWYvW2DaZ46Ms/rpxtjFuG96zb/WMmNk/MPSBQvD66EjVlk8R1tnjox512zjb7A2vBE6Yvl4e77xHd2zR54HX63mVTctnlzgdf24bliQ5HXrmt3zUeGZV9BPNa8afSL7Sje/tMww7hGeMXUOa5xu3IdNARy7hZPb+dnaOtO4HvWZUxueU9ds457K+RrPbOkUo+nm8vaZRt/XT++1nN99tfKpblowOZvKpvRQ1bSRebtz1si4wPMj14zRNFzvaD9n1fCM4zmoedW4Brt1zt9W+6pxTztn9ZruUfFkF8+9uvl009QeanrNOJ/yqW6eU0uVVjzZRcWTXVQ6pYefr+LJLsqbtDUIgIE+gef5kDGAfZ5gV2j3WcUE9ok4CcTYHYsxq7Ijw/dMQi0HZ+uyhNUGDTvUU0XygxrHhZJQ0CFD2SzEEVnpviEGDOetBtRD9FnGCiLeSb6mxhLKAHrEEuqyeeV5obLHmYRaKpjUzVUbUF9Zxv3JcnSILURsjhoTpSuFdcATA3jK0cBCvWoGGxJdjsc2WRYqR3YaYlUQ5xnQGMBIY/ydTaihW+tLWMdSjinE89xxFtLl1RXa2EB5fxFHhmx4O7kYXXygmkyEjGDU+R1OLWYJI1lv2K5hzEqRaZkpjAQjKWiO16GlJ4XLZRk5NQ7W33Yi1kgCwVi+vLqCbjuLuF4wMn/9SZrSPSNI1BiIafYq94cELXW8Q7dyOLXYlMgg5y4IKR+PbaLvhjcEbOz+b08SyMGIdjoc2cZZ0mqpvKFkAAAgAElEQVSlCF1s4NGoVu5fNUkESQPqPI65fNBRz2NBFYL3pyEGEGLTMm7udHwtj0loQ0KxAbHi/mTdyhhAf+Vp0P9IrEIMH8Y4EhAxJ8oYwNFcv1TKQOWn0/G1nCCDhuQO9ItM+OmPbuFY5MORbaYMYFn1A2FH+8M7+Bn6OLzDcC8vaQ0CYKBP4Hk+JAAioBiLZp8ymHXBwpBogKyFqsaOTFRIk0iZBl8giIB+yGDITFgs2sdjm8jpyQJGBuLNlFK6tb6EbqwrY9jB5+TiYregq0kayC4ca8MCicX41voSGk4tZoFbaBn6gj4kLugyIe0EcY9GtXIW8jEF/CDtMuio58ldB38yUBnj5NDyrbQ/vIM+eAYAEIkC6HeMDzmeMGHfdhaZkiR09xxZ1SqQjBYC1eQh9OeNdWVUOqXHBP46AAM0jQbMJKBBC/FpN2yMiie76G5aAT3MymHtQzUZxu7e2G2SAIBSsw6LuKr/h03AbWcRXUyq1IIGEkEurarkxTrQACiD/yGwfjGpkhMhfIEggPd8YjVLixzwZJaqAsTqfI5EPiTdqXODLwBEprEv6RRs2GWinG7TLJOA1HlXPku6zTu+DxB9ytHAiVw6XT8A4OFIbwOHXYYvKqrcTCmlK8mbtWulDgBlWTgYOKSWqhUAQs7nQmIVDcQ0MxDuW9oVBEAKAuC4DkxEf7m8zrSD7I9u4cwvOXlYZY3h/edWbjFJwyDr6XS8IRtzadUICPqCQLlwQ+IFMIjF8kRsIzkntPPvYwEfdIxUyoDo9K31JQyGWAQw+chFSgeAAzYAqE5Ksl4rQA+/KwWeUS6vL6qVq5nAMogJAtA3FFdngj6rTEgVAKEPKKsgSMFvnHt/dItXiSJdlhokDQZimnnC+jjQWcACADGWLiRW0a31JZy9rIqRn0moZQCHdUJtqGqjq7s8FmugCoSnHA2UMaGD++i2s4hr8952FrEFT2rnBQoAIa10Y10Z3U0roAeZuXQvPZ+uJG/mcna6DPrRgp8KgHhG8JxajflBRz2rB2Dekhmg/dEtdCbBEEzGRgeL9LMCgAfEZgsL/qCj3tYaKDOBBx31XFnl0PKtlhZAnUUQ9wdWQWS92gHg2gktJqmZo5r/+mOxw/Mp5+5BRz2/ro4XbAyk/qO/On4S6vaHd/gFgLg/p+NruUzo2YQazq62u7eqBfBsQg1dW7OJTjkavBQVrEq/wXhwMKLdlHgYBEDjCALgOA5MRCcdFazxJicVLJi6nZDOGgjZDIjQHvGYvfGgI739SvJmLxeOFQSqizesMthN5niK0UMyRWfRkQu31Aq8mlzOkhwAxOHUYm7QbINgtdV7JFjCWgmw1Lmj4brFBJY9sYthVQKHqnumAz91MYRF9tqaTVz1A5OQznWvq0+pWv8gIwP3sJysDke20UlHRUBrAetCDAYd9QzdWDDUcnGQcYHelhw3sJwOOuq58szTBEEAoFplBpZi6Abez8hjMPz/2Tvz4KiuO9/rxWbploEEJ8GsklrqVgttSAIENsYQ25jYrALEon1XayGe8YvjmAJDETGSZclS9CQLSyYQCJgBm5jxQpkAweUtNXnOvDhxzT9OJabsVKUyGZxJVUhV4t/7o+/36Nenz7n3dregBbqn6leC7tvd95577u98zm872GoOiykr160dAOQljBBKga3afr5yNf3igVUhUIoSL+ijla4G8VzZqYtpZS3nxavfXLxF7MiiGv8nsisEPANacN94uSo8l6pJO55lYGQA1FkDsTeuGQRCZ2OhDGvekF9fMkYFg7BwXb57gyg/I8OgCgCt3KWRCvohms/K0CfDHwplmwEgPCMXlxTRW/esF+XOrKCPG0x60hppML2OzuQFv+flBaF7qZvB3+H51WLDhR4D+hwADG8OAMbQuAv4VE6wxh7qPPG9GKHs7TzgWNlB4cMNwOsEwrKCFStgKFIQPJpZRctd9WI/Rl57D3X3rKDQrCDw6dxS7UpUBXa6uEM57o8X8eUFgVXAZwV+fDLE3qnYkByTYJ+xLyh+n0O9DH4yAKK8CdwVPA4QsNkTRyvKiZwtIdve8TADbg3EdctyMqdc7OOLAsIcAPn9A5TIxYrthADIciK7QtSw1NWY5O5fLFowIWGPYgAi5OcrV4uiypfv3kBv3bNeFK1WHY/P/PuKb9J7y9cIwOTWR34+/JoBgBjb0UIfBPCC2NsT2RVipwu5yPm5RcWifqAc8woddDZ/e9g2aXwCP5pZRafzNsZ1KzgZ/niMLQALFlC5jpwOBgeMZ/NC4SY6kxcem2YHBOEifrVgm7AMIiwChaCtAFBnNLADhtEAoBWIov+G/LVhAIhwprP524WlD3rlUEbouLEj+D5se4jflsNq5G3fUIwfVj9d6TEHAIPNAcAYmrwn5RFj9Xc8qyLMxQBrgu5BU5n4oWRhEZRBEO4duGRP5ZRZgg4HwSMGAB7KqAnbXYQXVYY7FUG33O2rAznAIiYUO7CHyf5M3kggNECXgylcW9htA3GMkYIf3JkI/IebjE+EmBzhRpYVmRkAol+H/LUhExRWtSdzyqnfVx/XGMBBf/A8kBigijM9mVMuJjH0vWwNPJ1bSpeWbqT3lq8RUAEAlBcNZ/JKRMIQgtztxoLqAFAXN2gGh3KxaXnHEPwm3x6OF5zWuW7NYJT3xaGMGlMAtNsvAGtMlvz54wCIRQ6sttyKzuVkTrmw/soLV0AJkhX641kI2l8iYEcFgNwaeCyrUsRSW0EgkkBwnRcKN9HZ/O1CJ0cDg3wHqAuFm2iVOyAs69EkUchzh/xaPwNgO8fbET6n9XobaLkr6GJF7Dh0KI+FjLS/MIdeXFIkFs1mxZ/5gprHf/Lizyr4605rjMvCe6w1BwBjaKpNyeFG4NZADG6AEEzhVhCI7CYACOLfZKWNSRB7kb5asC0kiF8nKgBUCSYtFZwBDgFpADW+BRvccjxLmH+OfxaZlch+lC2QmLQAd0MKAJRdu/J1n84tFQkl5xYFrVaqPgUUYPWpgz8ZAAH8R6Qg5X7fSMLNcEaNcFnEGwABfAgK59ZA3n/IFEYsqg4EL9+9gS7fvSFsMSCD4OncUmF55hnoduREdoWI/bQTN2gHBGVYw5iKBCatXLnoIzMLoOzONbP28ThXVX9jEQnwu7ikKCyOWM4Axr1TWYaOZlaJ+Lohf21crdfPpFaK5BT5OeNWQJ4pjDGHnXlU0mdkifIFPCoAnFtULPROtDCIRSviDuEuRr9i8RQtqCFGr9+mi9kKLrEQPplTTm8sHKkYgfhVbuXjnpFI+gZWaWyROuSvFdm7Vkl1R4zxjQW1bucPwB9cxF2plQ4AxvsEomlPPfUUJSQkhMiMGTPE+1988QU99dRTNHPmTJo8eTLdd9999Ktf/SrkO65du0YtLS105513ktvtprVr19KVK1ciOg8oomPZxSHuBWxBBBCTgQEPk84tjIcfGWncLQNXGh48lVXwbP52AVawmKkA8PD8alrmqhPmdjMIVE32Otcwn6hkF7DKaqj6LjuuXKw0l7vqxQSmEw595ws3i5ItfBIECMPKg9U5lBAHQHlLKX7fEevHFdWQP7g36Zav54SN3am3TRaK6EaP3efSS0PG0KmcshBroAwKUNRvL1tHZ/O3a8cGwgpk17AqhAAWZywOXi3YZmkBO54VOQBGAoY8fEH1nt2YPdW4x18AIIdCKxfvawVbBYggRANWWTkTHp95e9k6Yb1VJTxBV8HVj2fhkKSTimdkh43dKXEcu097qsSzCV2giglUJYkgCxZ6VgWAqhhBWBKhQyJ1D2OeWOqqFoAGiD2dWyoACzHR/HmAvtdtR2nXAqiaawB5SBjEOIM7F3PJqZyykDIwcAFHA8SHMmroTF5JyJaoXLfqABD381DGiHsfVkl56zfZ/YtY7p60Rtqf7LiAb1oAzMzMpN///vdC/vCHP4j329vbacqUKfTSSy/Rhx9+SFu3bqWZM2fSn//8Z3FMY2MjzZ49m86fP08ffPABrVy5knJzc+nvf/+77fPgVhTUPuMQOOSvFS4aXmsKD8CxrEolCMoAyIOyIcezKkJcVSrXHTKL4eJE7BVACgA4bACgnbjBSAARK0MrC2MkwrPXkCmtAkBYbt5cvEVAH6BZBhu4guG2lVfgvd4GkcihA8AjRn8PZ9SErFQRjA6r3zenF9DMiV+h/Sll9C+eUnohs4h6fCNxVPEYu1hccEuQmTUQCxjE06FfuSBh4HRuKV1cUiTcjtxSpQsDgEsTk5/KMggA1JUYsoqrsyOqxUssgvPiiTIAQF0yB5+MVYk0kG4ja/VkTrnIuPzZfQ8Ll5wq4QmlX2DVPZqpzgg9nhV0rW35eg7NmvRleiZtBz1tyPdSiuM2dgGAsHbh2QXEqQCQu4WPGNZMeGugu3sZAEKXyzB4KGPEPQyLuF0Q4gAoWwfxHdD50GNIpEKNyst3bxBhGRgbvKYqxhHCF3i5F4TV8O/SASdP/JFrJWI/Y/n6zKx/wxk1IuQEMZYHjK1C5QU1B8ABDcDDk9KngD8OgH2G1W8wvU5sP+oA4E0MgLm5ucr3vvjiC7rrrruovb1dvHbt2jWaNm0aDQ4OEhHR1atXacKECfTiiy+KYz799FP60pe+ROfOnbN9HlBEXalBiw+sAnjIeVkYuDRlJcED5fnG41BIfd4GZVYWj1GDexiB36qsTkCODEQrDBewlQWNB5DbgTT8ezQBUD6nowwA5RU03Luoe6YqnQPY4DGW8gSoAkAV+EG5cEWFQPoT2RUiAeSb0wto9sQ76Ygx+Q5n1FC7sSn51atXb/jYPVOwQSh6VSwY4vRkcOCWVUwg6Gs+cXBr1BsLi0WixCt5OyxjQjGuYRlEdjgmJwCgWX1BOwklKvfraAOgyoWtAsDTuSM1Lzn0WYHzyZxgAfh37l1LP7vvYRHagNATGf5Q1uVC4SZxv+Sxj/H7asE2Ojy/mtbemUdzJk0PGf/DGdvjNnY5APIkAFjuzayAfIEGq96ZvBLxvHMAxEJchkBuFUQVAiyaZG+BDgB1sCQDoc41C73NQzCQZX4ypzwkXhVjCLqU6zsrl7IMeGYAqLoWLCJgiJCtfapQGhkAhzNqRGw6L6WlKv7MBc9Ar7dBuIEdAAy2mxYA3W43zZw5k5KTk2nr1q308ccfExHRxx9/TAkJCfTBBx+EfGbdunVUXl5OREQXLlyghIQE+tOf/hRyTE5ODu3Zs0f7u9euXaPPP/9cyJUrVwQA8lXl2fztwg3IFcWJ7ArhFpYfLF6LD5OnCgBV1kAoAkAeMnh1MAjL48sLSmiVO0BvLCwWyuvlBSXCeqeLpZPf04EaFGE0AGgFo4C3M3kltDqxScQRAoJVri4OfVjlykkfKveKygII8INll8PfsOHaQNkCrqjW3JlHk750G33ldhfdefsUyrsjlb49dzMlJCTQf/zHf9zwsTucEbS28TIgclgBkjZgaVZlnL+8oCQEBBEwL4cMAFTeXraO3lu+ht5cvMUW3JzKKaMzeSUhMYMPGoH0Vu5Tq0xjlYuWu8CtgM6O+1YlAEAez4eYPu7eNcu8hxXqZ/c9LNzy+MzxrAqxAMV9AvjBJawa+yh1hKQJ6Kq1d+bRxP91O0273U1fnXAH3fuVedSX8VDcxm6HAgB57Bt0sBUEchCE9Yy7Hs1Kx6hKfwEGEfogu4kHfPVhFkCdyIDI5w0dqMEqFmkMYCTu2z5vAy11VWsB8JBh6eN9cTyrQgl9ukS6rtSAmP9QaonHe5rBX3dao1iEAyY5/DkAGGw3JQC+/vrrdPr0afrlL39J58+fp/vuu49mzJhBf/zjH+mdd96hhIQE+vTTT0M+U1dXR6tWrSIioh/96Ec0ceLEsO998MEHqb6+Xvu7qtjDhIQE6vOVKYONeSLIyIp5pDaaHEw8bChfKHc8aLq0fRUIAgZRvwwxEqr4H+4CxmoRpTIuLd0YUs7idG5pSGyeDsxkMMB1mVkUdd8FywgmfsSk4NxQrgUuYJ3lE5YkuBMBffLkp4ut4QAI9+dRBn48+QO/hTgZnpl4PKuC9nhWUOOs++k78zZT0+xHKHXyTLrjNhclJCTQm2++ecPHLmIAYWlDnJEsmNheK9gasrCQ79uZvBKxm4hqccDjPE/nBhOX3l/+CL29bJ2YfO1kjJ/IDm6jBqs2XGBY/MhQpoNA/rp8DMZUNHCni+FDGSOUalnlDgjrvSo+VmcZPbcoaE3F9nx4PuUYWlipz+ZvF7GAuDbV+EcmJeLbOBzsnPMQNc66nzq866g9fTlluGeIGMB4jF0OgL0KEOSF11VuYR0IQh8idMdO6RidZRA7LOF+A0qXukbKS0UKgfLrwxk1YcfgWiOBukikVwJA6PhX8naI5D4+x5lBnwr+EEMN3S8n1Klq/wEA4e7l1lzAnwOAoe2mBEC5/eUvf6EZM2ZQV1eXAMDPPvss5Jja2lp66KGHiEiviB544AFqaGjQ/o5uJfrDrODEKdd/Ozy/WpS5kB8CBMDK5QWgcAFyckyaXQjkLj0eRwJXNCyNy1x1wqKlsxLK8Sc89gSlYXhBXT758uQCbjGRtyRSxaYA9M4tCoVQDrIH/bW0zFUn3OE4b2xHhs8B+mQXul0ABJjD7cyV1pC/NgTq5Sy1Q4br4nhWhchSg/wfXwVNuz10Er2RY/e59NKQuFK+l6/KGohMQJQ7OqIAQcDHawVb6a171gurtwoCuavq0tKNolizFQwey6qkFQb483g57CbDa1rifPn4NLPa4fsiBUB5XKM4tHwueAaPZFbRCqMOpx3oeyVvB711z3r62X0Pi20QVUlU6GdcB54jjF9+T/m9x3OsKv0CLwWOGc6ooe/7KsIA8EaO3UF/idICKFsDDxowdiijJgwiVCAIaEDoDty6KlCxAsGDrO8QBvHGwmJhvcZ5jTag4fqvB/whznm5q17EWUNPn84tFfMZ7wPZha7rxyF/rViEnMge6XNZp6rgD3srwz2sKv/CAdCpA3iLACBRUIk0NjZeVxew3HgMINxgUDIDbMAfz6rQuoVR4kWunzTMlBUsYVAW0YLgEQZIqGF2v7tRTBaAJJ3bWGWdg1UDECeXeQHgqcrEcHhUxajoAtf5OR3KCG4Fdzp3pF4bd3/ziQ7u2mFNf8nwB4sIL2Qq3z+4OVBfTM78RVwogsu5ssKE7XXNuu5uNN3Y7feVhY2VM3kldL5wcwjAyyB4KqdMxFjKIQJ8UjuVEyx18c69a+nNxVvoVE6Z1iKogsF37l0rfscMAFWuUkCZCsj4GOXjEYH0SJhCEgbGN8a42fdw4JQTWPj5HZ5fHbKNoSy4D4jr4+VeVJnz3LKKPn95QehWfzL8Hc+qEEkCuG8q9yAmeoAQxOeaGbexO5wRXNzh2bICQVipoFux1ZgMgdg5glsE4RKHjo8GBCEDRgYtSurwxQESqnjyRawAaJaUYQf24FGChwh1ER90B8QikFslVRY+bM2m6zcYRPCsD2fUiJItutp/XJcO+WtFApCu9h+Hv35fPf0wq9gBwHifwGi0a9eu0ezZs2nfvn0iCaSjo0O8/7e//U0ZjHzy5ElxzGeffRZ1MDK2JDpoTHgnc8pN3YM8I5iDIBISuJLCZtYo1cIDyGMBQXx+mStYQgHWE24lxGStAzCVC1AGNu4esBKz3wCkApYBeydzykVBYJXVigc627H6weKK+3h4fnXYnpRw479WsFXca66kBtPrBMigjAxXWIeMCWXIX0tPp9bR1NvcIYH0N3Ls/iBzW1j8F2LGADs6tzDGDayGHNwR+oD/Y1WPbf8Qq6kDQcAcIAjuzst3bxD9DgCUwc8sZk7l6oVFkBeF1gXS88LPKjdzJAIAxNhGLCCsfO8tXyPKjVhBH+KLsbUiLLTwNsgACIsfLC26siInsivEjjt8ERR0qVbTtDiO3Q5PUL8gftXKGsizhaFjVS5hDoDyYv5Y1kiGPEp8qSDQDAYRA4itIKFToHfgceG1URG+whfqsos+EgsgTyaRDQMIUUApMXhgEDMKrwi2s7OK6dNZ/fgCGgsQbvHr9IwAoMr1y8EPbmmznT9QABqeDCTfOQB4k7XHHnuMfvrTn9JvfvMbev/992nNmjU0ZcoU+u1vf0tEwTIw06ZNo5dffpk+/PBD2r59u7IcwZw5c+gnP/kJffDBB/SNb3wj6nIEfE9KxJ1gr1jdSgcbYnMIBAgCcA7PrxZmbS7c7YXVYiQgCBnOqBG1nPikzickQCFEzihTJYxwSyKuSwV1HO64ywpWRfw2LDCIk4LrBCCNWoYq8DMTOeMRVk1kL+PcAYAANw5+stsfJV+OZlaFKazB9Dpa+9X5tDvlIXoqeTs9OmcjzXcn0aT/NSGklMaNHLv/tnCtyKpT9dHJnHJRGoLHTupAEO5eGQC59Rh7e75z71pRGsYKbnBvsLXWW/esp7V3NAuLHU+aiFUAfjwberQF17w6sUmUbHl/+SN0aelGUW/NDvTxvrxQuCmkzNOxrEqhc/DcncgOBT/5OYCOOZpZJUqKwKW3ano2PTbvEWrzbKUnktbRgjvmkutLt8dt7HZ4qoQFCB4YDj9mEDjgqxcLHRkEVQCoihOESxeLdh0MykDYrwBA2SAgW+AQy4wYUmSJ64rwY9EiW6lxDP8/3+GJzylyJjMXOwCogz5YnWFlR8KjXEUBAKja6QVzChJeVKVfOACizAwWMp2eAO1zYgBvTgBEfakJEybQrFmzqKioiH7961+L91GQ9K677qJJkybR8uXL6cMPPwz5jr/+9a/U0tJC06dPJ5fLRWvWrKFPPvkkovPgWxLxVQqHAZXLAMAFmOIxgDzehlstVKtzuHAwWRzLqgxT6CroMQNAGaCggABrmBzhWuOgxmtOAdpgYVG9j2NgdeQuM7iCVa4rLoPpdSEAaAd8ZegDzCLWUl5VD/jqhcWPx6VAYQ2m1wk3//GskZIvPBgdCnzhFA9Nvc1NtyV8iabe5qacxBR6Yt66sGK6N2rsPpcetEpfvnuDiN9RWY5fXlAisqx18YHImEWRYlhazJJ8Xi3YRm/ds57eXrZOmcwgx7bh33ABw8X89rJ19P7yR0SZGZwDH0+RSqwAyF3QKIGB80TyxurEppBztAPCyPx95961dPnuDaLUkGohBgCEy56Dn2rheCQzWBQall+ukxZO8dC024Njd/oEF907fRbt9TwSt7Hb7qkOCasYTK8Tz7L8DNoFQVgAOz16AOQgiFhvWG+hA5CYobII9vvqqdAVhFcdNOnAyo5FD2FIODcV4Ku+w477OlIAhHUTzzpcvIfnV4fMiar+7fQEQtz0shsfXhUz+EMpGTxbvd4G4QZ2APAmBcCx0qCI+nxlwh2gqjoPV5G8QjzoH9nrVwWC+C5YnRA4LoMgLxoKd5QdGBzy1woANHMVq8BQnvx1sYMqC6B8rNXvmQkAUBfXJ4Mvhz65n+Q+hbVEVuj8/mE1ezKnnAbT68L2p4R17PD88P0p8X4891Pt95UJCxFcPugTWY4aixa4JeV7J997wCCvqaeDQbiCAIOoU6mDoKOZVSL7m7uMEWbx5uItdPnuDfTOvWsFcAGYUPAWEzbf21pOYJKTQPAbfAEEaway1FHihv8u6lLCysJdwFhYmckreTvo4pIiAbh8T2xdzCwWUDyRQV4kcfCDxehkTrkWEk7mlAvoHPLX0rNpFXEbu+2eavEscRCEl+Vopn23MIrAww3ZlRoIKx5tBwa5lwCJTPD04BgrADSzpkUCaLKFMZLPW0lPWqMpAB6eXy0W/rD02YE+3t8dnoCoxyhba3V1/zj49XobhP4dTK8LiQF0ADDYHACMoUERfWtmAz05p5UOpDTRgZQmenJOa5jsT26mXm8DtSUH3398dis9MaeVds1tod1zW6gtuUlkLu2ZF3ztiTmt9O3ZrbRnXgvtTWqm9pQm8YDsT26mPfNaxHtc9icHj0Xcw/7k0Pf3GbJnXgvluHfQrrkt4jWd7E+OTnB90X4eojuvXXOD17Bnnvk1tCWP9MeBlCbaJ/UZl05PQCi5fUnN9Nis4P3aNbdFyP7kZhrw1VNXaoB2z22hJ+cE7ydk19wW6klrpA5PQNxHLrvntlCHJ0BPzmml5hkNcZtEvzOnXoyhfUnN1J3WSMeyKqkrNaDsRxyH+Jv2lCbl/dozL9hP7SlNwmXTlRqgtuSmEMEzw6XDsL7AZTnkr6UOT4DaU5qEtCU3Ub6rjPYZz4VKOjwBIZ3GZMJL+gBqYVnkljszAOSuYkAWFlSI28Vkg99Xnd/epGbKd5VRW7L6/Ds9AQElyGzs8ASUfXYgJbRfe9IaaTijhjo8gZDnV76Xe5OaqcMToOGMGupOa6S9SSN6BbJ7bvAvrGV4rnfNbaHHZsVv7Lbc1RD2XH179ohubU9pol5vg9C3357dSo/NCj1GlieNZxfPhEqXmwnXEehbQFKvt4H2JjXTE3NaKdu9LUynqGQ3+xuJ4Br5a3a/h/+u/G/It2cHr4Ff896k4ByH56DTEwj7rJ0+xH14dOZO2m3oEPTb47NHRL7vj80akSfntFKvt4H2Jwf19z/PDMqjM3cKCcRB74615gBgDA2KaMJtM2ni7bNp4u2zadKEueLfskyaMNfy/ckTk2I+Rv491bF47fbbvh527GiK6lxG+/vla4ikH6LtXzv30up9/HvCbTPjNomq7s3kiUmiD8zE7nGRHit/zjUxRfnZCbffdd3GFf89nHs0528lZtdgdu3xuDeqYybePjtuY5fr3WifQ6vPRvM5O3oFOutmFvka5GscrX6L9nNWn42H3h1rzQHAGBoU0UpXDd3vbgyRB90BWntHM62f0kIPugNhssodoPVTWmjLtFZandhEq6T3VrFjtk5rpUfuaKZV7gCtTmwKk4cTm2jT1FYq+cpOKpraQg8rjpGPfzixidbe0Uxz7rif1k9pofVTWuiRO0z00TsAACAASURBVJrFe6MluB67x8vnaHYc/s5KXEFFU1uoaGroNZj1wdo7mmnbl1tp25dbaa3xGbzH+391YhM9ckdzyD1Q3U/cy1XuQNhYuN/dSKsTm2iDMRZWuhpopauBVrjqaYWrnpZNrozbJLrlyw30yB3NpmOk8s6dtGVaq+U92TqtlXZ8Jdif6MdH7mjWyqaprVQ2fSdtmhr8DH9vrYU8YozdrdNaqf5rO6n6qztpx1daadPUVjGerb7DSngfjIasn9JCG6YEx2nJV3ZSxfSdlJa4jrZOa7V9vnIfbZ0W7MMNxvMry4PGGMa1rJ/SQmXTR/SE7jl5OLGJSr4S7FP5meDy8B31cRu7RVMbaMOUFvE86YTrZDzH/Nnkx+D/y131Yc/ww8YzvNrQa9HK/e5GmpF4D610NYTpeoyLbV9upaKpLSHPUiSCa7d7vDz3QEcWTW2hbV9upYrpO6nkKztpraEDV7oaaEbiPTH1Af8/71v093JXfci94fdTvsdr72imLdNaxXvQrWaydsqNH7tjrTkAGEODIhr0B7f80lWiP5FdIQKMVdsPoSSGqnhmr1EvDlmwvOaSHASM70JsE+KM5ABhCGIAEaSLoHU5CcNucoVKeKB0tMJrGPLzPJ0b3MViuateG9TOBTtV8A3T5ZhK9CcC57H9kJz4AUHG96mcspAxgPgUxPkdy6pUFift9TZQXxxjAIczgoWT5UQj3m/HsypEgW6MKdU9Opo5UkMQ+6qaxX6i9ATKXqDOHY9p47GDvH4gv++INTpfuJneumc9vXPvWlFuBlurIYPcbqIFMpkPz6+2fTzPVkbGJrZZxHkhDvF84WY6mTNSwsjulojI/EUdQsQC6sooIQ75ZE65+Azi0lSlXw5l1Iht/V4r2CqyueWsTpRfeTF3c9zGbldqpUikQ/KGLDxWDDF3uD8oHSLr7W4jdIPvHMKLSkMXIblPFyeoix3s8zZQoauKeqT9htGviOdGFQY5aY4nyyEhStbT+C05/ptXesBYlWu5Qj+iHBiygnkMO2IAUfbKKkZSJbwvUdGBJ3wgBlC36wdKpKE8Dtevqtp/vAbg2fztTh1AcgAwpsY3JUcSAmKAeIAxQA+QpwLBowwkoHSR3g7li2xM7GMrp+oDBAE7KGKLBBI5MeSgAYAIXuaKgpeDUe2DiomUT9SqZBEOgLoSIrwcDGKxOOSpoBTX0e8LFlUFtHHhdbVQS0uGYlXiBzKTcb+wJ6UM7tiJIVgTLVRJ9RtwiB1iVBlqyJCLRz0qjN3ve8tF0Dw2aVctFpCVfnFJkdhVQpc4hPv58oLQPYR1iUKYBHgNNGTx8jEmlxla7qoXgCoXl0YZI76LDRJMAIhv3bNeJIVcKNwkfpcXguYB/XgdZTQuFG6iS0s30uW7N4jvhWC/Xb6LjVw2aTijhpa76sWzJu+jjb+ncspEYgtqLppBn1yjExO6WdkXJC9cvnsDnVtULBaaqiQCJEcFY0XjZ70+YCSBHMqoEUkuckkQFQRyEERZEB0AyskiPMlviAEMEj3sgA8HQDmJxEygL1T6GTUqUZUBOhS1ZflOTXLRfehTVaKbSgYM0Cp0VYXoRbvQh4QOJAnyChocuNtTmpQA2Gck+gD8AP8q+OMA2JPWKBacg+l1ThIIOQAYU5PrUfUbQdIAE1lxIGsUpUR6JagYTK8TFiUoJg6APK0eZUdQaoXDoKpczMmccrFNFjabP5pZRctcdSEAaCZ8BakCNhnaePan/LqccSkH1fPVrO58kBEGKyZ+B8DHwVcugcAnPvQljsdqF8oQAIgsSGzrJmf99jHwAzyqipNiZd5vJJHEY09KDoC8BiXgF5ZR1RhAcWBYBPm9AgTCWoAsaVjikMFrBS7oZ1itcG8AhIfnVwsANLOgqYSPWdWWhNjpQ66lxuEQpYv41od8DFsJJj9kMnPg49eOOm18dxurounIvkZGt1wBQL6fsPi9uXhLSOa+rHeOZlYJyzlg55k4AyDP+DyRHSw2LmfccwjklneUjsFiAYk2XakBJQDKECjDIPof418HQb0KAFQZBeyCoUpw3dF+Xi5zJVs2u1IDtgBwML1OlBKT+0bVl7yvZQsgvCnYLQU1G812/uDFnzE2kJzlAKADgDE1GQCxETVAjhcl5YMcFj9MsqpVIJ/Y4EJW1YQ6ZLh3MHGr3JqylQu1zU7nltKD7gCdySsRleYxyVi5U+3AIiyiZi7gaL6XF0Y9kV1BD7oD4vqx76/s2lJZ+gDEgGG+0wGXAV89ncwpFzsOAPy40pLd/fIExItJD6bXhSiqsQCAGE9YXGDbK5XFCMfDInhp6UbhjucAiD7BouF0bqmwngGi7cAgt4IBCM/mb6f73Y1a69loCHeBXw8ZzghuY4jFGQc+buWz2innqPE8v1awlS4UbqI3FhaLupY84xnPD3TA2fztomYiH//yM3B4frVwPcqhLGMBADHJ4xmD65Q/h3whhgLDXAZ89cKqf3h+dZjlyQ4IAgZlK5dsHQQAdpsAoB2RIZH/u9sCAFXfE4mYWQCH2PVz66iuz3S7fAAAYXWGnubgZwZ/3UYmPAr3o74jMvP3JtU6ABjvE7iZG59EZYUCixEmQ9WA5xZBHk+ChxTfdTyrQlgFVa4ZDoMAG1j5MJGpQIi7gDGJYCsgbumAa5pb5+wCG5RCpODIXRw8FgZWGLjVhjOC29mpLJ/y7imwDsKaJE96vF8B1mfztwtXtmrVKrv3VcVJAX7YVUReocbbBayLKUXcmAoE+b06kV1B5ws3iy3euGtHVTcSsarYlSASGOSAt9LVQGfySkL24EXcEq+Rp4qrswtoowWAiLfCYgsWxlXugLAkysBnB/qwzza2a5N3a+ETMiblc4uCW/K9VrBVLBZVRYEPz68WllEsfGRL0FgAQJUc9NcKCy68LXYEehkLFngZIgVBDoTcAgbX/1JXdYgHyK7YqUkIQDOzMMYqsACiODO/Pisrnxn0yf0K/X8oY6Tws53iz0P+WmHU6PM2hIAfyjI5AOgAYEyNB9KfyK4QqztZoeABMQNBuL24ooXLglsFT+WUiWKy3FWpSwoB0OFh4NaxwfQ6UcxTV1watdj4HryAQx4wzHfz4HumQilg/1S43OSt3vBdADwEIXP4lMGTu4DhGudWTliNALKIW9NV0wdA4xp4UVh5T0oO7xz8uHJCrAosEaoV6uH51fTC/O1xm0R7NADI40l5QWczEES82Vv3rBcWGLMi3oB8wOD5ws1iVwsrGDw8v1oUAOeuU8T9wVLIXbdYzMg7b5gBICyikbiU+XMCi6cKUBEDyCdPKwDG9mOAPoxTVQwuABDF6BEHCSuXKvkJsIgtx45mjiRAqWDkaU9V3MZuW0qNFgABQACBSEAQLmBueTqeVaFM9IsEBjm88bAVQBOPwYsV0Hi4yWgIYhChWxG+gGffLvCZgV+/rz4kzIbHZqrATwV//H4DVGX4AwDucQDQAcBYGq9Ij6BimKi5JRCDmz88KsUA1zEsAchq4lZBZIodzawSkw2HQZ3AUgMgRCzPcle9gB8zC5oqHsxOXKBcTFcuoitnsB1S/JbZOfX76mmZq070ByZeuINVVj4d9AE+AMdQxAgghisb9wcTggr6ce4IKufwB0WF3WHaUuLnAu7xlisXEBwCEUeKpA6VRVBOCIFL8uKSIuG6sdrVBZZuxK/BDa2yDnIAlC2EqsxZFZxxSOSgpttPVT6WH88hE1macqKULHwS1QEfxuabi7eIPkGYg1WfAoqxwwsWQPIzxWNAsWDC+Na5DaG34mkBbEupCVtQqSAQRbHtgmBXakAUkebP8+ncUuE5kBO/IgHBnrRGWuSqFLsBDRgLSswPsgUY94zHJVtBYiQAyJNMhth5yM8UFuAH/bXCBSzv1RsN9GExjXhaxEdjMwPdrh897B7z+4u4bZ75K8OfYwEMNgcAY2jylkTYhgiWEp61xEvDHDImLRkE+UPJ43UQQ6HKCuMwCLeoFfRwCx/2UwUUolyGbHGLBg7xIFu5gK2+m58vrCAAWcQxIh5Q59KSYRirTMRaQbGp+rnX2yCgBlYVVVmCAV9oEpCcmQZrLr4H2YbxCEa2C4Cya52DIGIidbGfA77gHsjnFgWtgucLN4tFgZVlkGcFA7YAhMhmlQFQ5S6OVOzGAOo+b/bb8jnKAMiTXwB8iHfkVlGzvoN7/dLSjfTWPevF2NaVfUH/AYpV4KeDvz5vw5gHQA6BKBuCrFhY5mUBJKjCegZ89aIaA4dBM8CxAkAzayEW/KrFtpkMsbnBzjPBF+HQn7qwl37fiAvYLgCaQR9Cm2S9agWAvd4GOjy/WsxbAD8z+HMAMLQ5ABhDkwGQu/7ggoQVSKUYoHwRWC2DIL4PFjS4pXQlArCKh7sWmYM66+CAr17UcgJk8VhAuGe5i1euP3UkM9R6pwNAMwuiXJ8KCSqq2lQyoHIXsJmVD25ouJXRl3IspWxlPZVTFnZ/5HsJy6AK/PhKHJbDXm9DiHIaCwDIY0ntgCDCEZCwgNACCCZFfn9P55aKmnjnFo0kKljBoAyEcKeuMsCfZwePJgzyUIpIBb9rlthyeH413e9upLP520VZGV2ZFyvoe3lBCV1cUkRvL1sn9vPF8wHrEgdAWL7xfON6VYsglesXz0G8XcCqjE8zCIQc9NeKReTRzKqQxVynBgB1MIgyLMezRvaDN4NBACD2G45VVNY8XRaw6j5GI1YAKF835gDMLUga0y2mzQCw31hYYkEIi2ck8HfAAUAicgAwpibXo5JXJ/2+YGYZzNqqekYcBJFsgAcGCQN4sKG0T+WUiWBiGQK54HiUuQAQ8uxjAKDVZC/HAyKOT47hkwUTtO59uawGd59xtwNWpbJ1r8/bQEtd1QLaAHzHs0YKqcIyqkug4fADcIelajC9TriAuWJDn6Ev+7zqwOQBX70oEAzFKSunsQSAdtzB/N8YY3KtOWT9ye5hjCNupZJrBdqxEKIMzPGsIMTAYoYsWsS8IhnEjkVOBjdct+5z8vEqKyB3P/PzvLikiF7J20EPugNhRdf5OZlB35m8IPS9c+9aulC4SYxx3tcyAB6eXy1iOs/mb1c+E2bQIIPDWLIAWkGgCgYHfPV0OrdUZE4jbswKAOUQH1j/4Z2AJwbPAdf9HADtxg5GA2hWFka7ojrHTk9AlLIxi+fD4gShSlgky8er+lYGwIP+WuF9OJlTrgyvkYs+q+AP4sQAOgAYU1Nlo6lqT8kgqHoAoKih4If8tSJtXRWzgZg+DoNywVZ5Uj88P7TC/OncUlphuKDsuE51gGjmDuYu7UjdvnbOYcBXT8td9SFxfFA2PLDaDPp4jCIsIXyy6zCUSS+z9uEeqbJ+eyTww6SiW53GEwBfmL9dC8WR3H9Yj1G/DgWydXGCHAbP5JUIy+CFwk0iK9gMAg9ljGR/yxCnSgZBHBxPyEDMEE8M4XGqPMsZca28SDmvIYgMdV4kGr/Hkz+4pfKgv1bUMrRjCUVcJQpPY1cP7r6TBXACNy9P5sG9jBb++n319H1vedzG7v5kNQBGA4J93gbRR6dzS4WOtps9LOtznknMgXDIH4w/5ABo5jKOFhDRB9cDLpFVCwDkFr7jWRUhEIxFtB3gk+VAShN1egLCzftqwTZR41FX+sWO9c8BwJHmAGAMTQZA1VZEHAQHGAjCPaN6+AEZSHIwC/iVYZBbYHSWQS7LXCPFp3nFeMTUHWUWuEgAkVvodBZGu5CJoGSuXJBBfCK7glYYmZSHLGCPW0bhUsQEymNeMNHhL7YPwiQLhSbHpWCViuB/u66JeLgiMHaf95eITFIVCEazCECsJnbR4MkHunqQPFno3KJiunz3BlGcmCeCqACQQ5JsQVO5XuWkEAAcLwKNGEe5EDREznxX7fRhltELAEQcowr4UNIJrl1szwYrvg76uMUeUP5qwbaQklD8PkYDgBjnRzK3xhUAOz16AIwUArnn5mhmaNFruyCoAkK+uMcCYqWrQdwfVYiJ7G24ngAYKXzCS4WFN+IheRULlVXQTr8BxuEVQxUIxGKb1f2LxPrnAGCwOQAYQzOrR2W2HREUDLL5eByEHCvS6x1RFIitMsvkOsRWYbBo6cCo3xd0AWPFikmdxwLySZIDIi+locrmlZMBVJmiuC4+KXP3MiBPVQ4Glr1eb4MoZaODXliJEFsIRWUV6wS4wPuyVQA7EPR5R5J/jmcFXb12lFN7SlPcAfDZtGDcEi+0GgkI6iAQkwCSEuByxALFSnhs25uLt9DluzeIRJJX8nbQsazKMADUxQ9GK3zs2BG7v4nzgwUQwIy6fpeWbhTAh32azax8cr/Bxcu3dJMXcQiZ0MGfSsdg8od+Gc6oiWsMoB0AVIGgCgy5ru70BOhASpOI5cYC4XhWRUh91mgsg3ABo4gyoBDWZB7+AistdI8O3HQu2kgsgPw7ePIJvEZ81xxYkLGLVL8vvOpFJNZTfA6VNGAxhx6VQ2tw/3RbvsmWPxkADzgAKJoDgDE0s3pUVtZAgCBiclBPjj+U3YYy4iZ2vmq0gkE8wIArABQUCwAQliszNymf8PkEDdcYd4kB4F7J2yHex/+5y+3lBaHbaAHueKkKnaUCAgDEKhuTHSZUAB/vM7OK+AAKKODB9LqQLYn4/eMWXQSSW8WkdCqUUrwBEMCMIG1dwfFIrIFY1PAYUuyzHA0M4p4gXuvNxVvo4cQm4XKF646XjIkVAlUAaAaXqvg9lRUSsP3yghJandgk6vNdKNwk6lXaBT5Y+ni/AJARdzyYXqe04OsSoHj2J382AOSILYx3EkiHp0o8Y3Yh0Moq2JMWzMw/kNIUorOR0Y4dhwCDkYIOFo46FzAWngAvea9flc6UF9+q6gvyeIE1nIc04Dd0IIoxARcwMpl5H0TqNh9i0PdqwTY6mjlSRg0uYDu7fphZ/1QAeMABQCJyADCmxndTUGV+WgGg/CDgYUd2FAdA2QR/iMEgz7pUgaAMhFjRwX0KFysmCDtuVDtQgNUyrs9KIvldAAtiAHFN3HUNK6Eqa5r3EcAaSSdc2fX76sP2pAQoIaZTdk1Eopg6PIG4BtIDALnVdDijRqz4OQhGC4BybKgMg3Dl2wUejNVlrjpheUW5GFgK37pnPV1cUqRNCLGCN4RRRGIB5IDHSxWdL9wsEl7eXraOLi3dKDJ1Eb7AXbp2+gFJIIg75NDHM311AGgGf/z5OOivFXHDRw29xK1P8QTA73vLxfOH5ytSa6BKZACU9TcWfkiAQ1Fvu/ADAERcscpKaJZFzBds3N0PqOPjQFW+COMb4+SgpO/snEuHAYB8TtPNbyqjBxIDz+ZvD4E+3tcyAI4G/EGC51LmAGC8T+BmblBEz6SO7HcoD1Q7lkAOglAumHx7veYxIBwGZbeBGQwCGJe6qoWSB9TAagZrCuIRo4E0bt6PVGSXtOocAQJQirprRX/gOFgJAX2yEuSKEBvD476cyK4Q16YCf53ljyunTuM7hzNq4gqAPd5yZUkhGQThGrYLgSoA5BDIJy/sBoJiyiipYQZCuO+IrZJdv7AAA8LeXLyFLi4pCgHEt+5ZT5fv3kCXlm6ki0uKQpJEEAMIyOIJHucLN4s9kPn3vb1snfjOi0uK6M3FW0L22JbLJg346oUb206MJFzEOD/cF7Pamr0MACOJ+9OBnwwI8XYB96Q1iuvtYc9eLBDY4QlQW3KTLR2O2GCMM4C4mXVQBkArl3GkwoF4NL5P9f3tKU3Cimk1px3014oFH55vWJFl6OOw15bcJBbfKh0bTeJHT1qjgN54JN+NteYAYAxNdgEjIQN1mKKFQKz2YMLHlmqI21OJyoUJeJOBEIq+z9sgajnJAABXL4LRuasALgh5Oy3uioDgO3WTNCwmqt/A7/DJ81BGaEX8nrRG4QJWXSMHvqOsX1TxlOh3/OXnDde5rLTsKqZOBfgNGLE68XQBH8sOL/6rsrQCpniRWTMQHDD6yW62OORoZpWo92cGhEP+WgGAOpexVVYtTwpRZffiPdk1pnPByWNfFn5u0BNIAgEAcosOr3vIC0LjOVABHwfxIWORAr1gBwDhieDFeXWxZwf9tfSDzG1xjwEESMkgGK01UAZAOwt6JC8AdhA3iIz2If9IxQAzALSKJVTF2akgLRoAlH9P/l0usAB2p4WHNUFfAPjO5m8Pi5+UYa9H6t9oAFDlXQEEdhvgN+SvFTGejgvYAcCYmqoeVXdao5iUOAhGAoF48LpSgwMYZnNYY+zAIK8dyGEL1pODhkJCKr/OaqazDnHrHE/qwO9gYsQxOleELuZPZ52QpVsCQJwbd4vgumHlMyttAegDCBzLqhT3Vae8dJMLt/ZBGQM8O9nqNB6KiFsAuaXHCgQBRNgyTweBAECzRBEzEOQgBBcvLHEAoeWueiUAqoAwUkBECSOVhdFKdL8rCwAQLvEzeSUiju/comJ6JW+HSFjigBhJSSW4LK3gD7HIPMavX/F84BmBmzveZWDkRRaesVhAsD2lSQuAVhDIdTpCX2DhRub4iewKWuaqC1lw2gVBK4sh9BNfbOpAMhZBGRhYimEBfWNhcNxCl/Bz0omun3UAaBVfDb3aYbiPoae6UgNODKDUHACMoUERPTargZ6c00q75rYI2T23hQ4YhSz3JTXTbuM1neyZFy5Pzmmlx2e30t6kZiH7k5uFtfGgMaj3JTVbyv7kZmpLbhLFNaEcF7oqxHv7k5ttS1tyk6nsT26mJ+e00hNzWmnPvBbL462+i/+by+65LZTvKgtZTfM4Hn6sWf90eALCAtLrDQYg75kXvDePz26lJ43rkO/bLkmenNMaIk/MaaXdc1vEqnOX8X1cds5siNskumteHe1PbhZZjwf9tcICohO4UpBIxJUqZF9SM+2Z1yIy7uwIz4zWCQLn4T6FKx8uVcTN6qyvdqTDExDn35bcZPtzdqXHWCQe9AezgLlFEFmoZn1g5uI6kCIFus9rEfeXC+5lpycgPAQdnoDl84JzD2avN9N35tTHbez+06wGesJ4xrg8OSeoMzHhq55LLvIz/PjsVnpsVvjrsn6PRKDT9yc3U3tKExW6qkR9RsQr9xjQs9cYe9HI7rkt9G3j/KF7YxXMPdAR8MIgfAFx0vvYeeOaI+kjWYc+NiuoH1X9r9KzXHYZOrfDEwjRud9mEg+9O9aaA4AxNCiiyROSyDUxRSvuSamm75vJ5In673ZPSqXESb6ov9s1MYUm3j6b3JNSYzrHeMtoXEPiJJ+yLydPTDK9B3YF54bv4zJpwty4TaI4Nwj6gb9mJlMm+7Xvyd892oL7njjJR1Mnz6cpk/0RnXu8hJ8vH7ujLXzsmZ1LJH2GY8XzMSEpbmPXSu/y5y5SnTsaz7yZTLj9rpBznDLZL56leOtTMx3Jz5Nfw2iKrB+vh86Nl94da80BwBgaFFH+5B20zFVHD7qDZvGFrgqlLHJVUqGrila4gskXi1yV4nWV5LvKKN9Vpn2fS6GrigpdVbTUVU1LXdW00tVAqxObaKWrge5x1Yr3uSxyVdKd7oW00FWhfJ9/H5d7XMHV3wpXPa10NdD97ka6391IK10NQla46mmFK2ilwbFccJz82eWu4N6+qt9Vnd9CVwVNd+eLPuB9wa9hhaueVic20Sp3gJa56sT38c/pJNNdTL7EDeJ+mQnuL84N91CWRa5KetA4l7zJ2+M2iS6aXKrsa8gKVz096A5o74ksy1x1tDqxiVa46mmRqzJs3OBvrLLUVU1fTVxMha4q25/BWJRluSuYSc7H84PugPj3KneAVrkD9KA7IMbqCuMzy9kYh+C3rM6n0FVFd7oXRt03do5f4C6ljMTNtMxVJ65BdS9Vz9ZyVz2tMo7X6Yf8yTviNnaXTNY/XypZ6Kqge1xBq6v83OL9ha4KWuAupRz3DtNjYpF8VxlNd+eHfJ8dHW+l+2Xdzp8/s2MiFfTRl125UfeJnc9lJG6mtMR12s9zXYo5VXXfF7hLlZI7+cYXMR9rzQHAGBqPRelOaxQlKZC9qws07veNFEYe8NVrYyMQJ2Y3/kOVQIL4LpTBQDYnAnILXVXUndYYtgOGlfA4MTkLlMdw8d1K5DgmOeZPV5/PTLpSA6KoKs4dcWGoUo8i0sj2tVvuAP0Md5hZzAoSO1B6QxeY3JUaEONkOKOGOjyBuMYAHsncahpredBfG5L9bCcTHGVKsNsKkjbMyslYxQnKctAfBBxe68wsntBMzGL0rGIM8flofrffF1zsHIzi+s3iL+VknEMZNSFxm2ZlX3A8kryGjfPUPS/xjAH8YVZwy0Ge9WolXakBoY+G/LXKOEGEjkRbRsYqbrDTEwy9QYyaVZy4nZhxVZJGh0WSifx9dn4f0p7SRAtdFSKcKJo+sUrugCtcdx+QZIaYVVWNVVX9v/aUpmC1jexiBwDjfQI3c1NVpOcgeNQAQd1gR5Awaq31SQ9hpACIhxgwJCeGoN4dapShDhkmTl2SRCwCxWZ2jF3olAEUMLfMNVKkFpmaKDKMcje6Cvp2MuJ09agQD4XJRJ6IeExbd1qjqH91KKNGxAQeSGmi3fPiB4AncoL75J7MKbcEwaOZVWIHGCTV4DMyBCJbGkkcHMJ18GIFQhwURxMAdcITqcwSMKL9fgDgkD90p45YQBAxkdjBB8+1Ve0/fn9P5pSL2C55pwj8Hc6oodcKttKZgg1xTQIZTK8T59znjQwE+aINugpxgzoA1EFLpyJZQT6mO00PgLGICt54EkSkcGcXAOUyMKMJf12pAREvyV+DzoUegc61s/MHwA/j5YCn2gHAeJ/Azdx02Wh42IcNEDyWVSl29tCtDrmVDNY5QILVys8O0Oi2/1nqCsLLieyKkGrwfFcFAA4mDZRM4X/NAJBbGCMFPExqKEcDeAXoHckMuqoABaqsRbvQp8uQkwEQ0IF7ZZaZ1uttEDtYDBvgJydNxBMAu1KD5i52SQAAIABJREFUmdpn87crQVAuqQMg4hnpfGxwAESiCMANMIi9c48qYDAaC6AqoxjjRgVseE93DAdADpijLbFaACE8i/iVvB0hVteetKDHQZdZj5IdvLqA7hni4He+cDMdzayKax3Afck1IrlHBYJ2En+gq6F/hzOCFR3akpu0licVEEZiGQQAojyJKitWB17c4mYFaKMFmFYAGCv0qeCPAyC8Znx+lJO9VADI/w6m1wmjR09ao5MFbDQHAGNofBKVJ3+uIIb8taJuGAavzkXArYLI8o22JIAVCPakNYpaTqp6gnDlAbz4Vm+qrdzkeoC67bR4qRi+BzD/fg6ifJu44YyR+n39vhEXcK9XD7nRQJ8MgD1pQcsuzqHPsOyqwK8rNVi6B1B90F8bUvZFdkfEcxLtSq0UoMNB8HRuqQgV0AlKXKisgrBm87JBHPKOGJZo7CsNiy0HQjPoGUyvUwKgLLKlTn7dCtBGAwB15xYtAGJBhP6De5e72iEAQLnAOqyE2NdVdgPL3oPD86vp3KJiAX54tjrGAADyckuD6XWihihCROxaBKFr0Qew6tuBwFgA0Gw+kGHPCvw4oCFbP1bpZn8hBwwXsJXl0661T9WnADd4yPi9MIM/Ph6G/LVh4OeUgRlpDgDG0Ph2Woh3w+Ds8ISvMgcMKDiVU0aHMmqEe5i7B+TVXq+3IaQuWSQgaAWFAEAAix1RWegwKanqAeI9Xv9PVwOQWxhVE5FKOj3hADga0IeJ4JABG7CMmCkwbvU9mVNOA76RuBQV+KGkQjx3AuEACDloKM3zhZvpTF6JAC6VW5jHycE6eyK7QvSVancXWTA+4LaENQpAaAaAsEpFKjKYqdy5KgC0gsdIzsEuAAL4UIwbFlQ8X2ZxgNwCiFp/KHItF4hXybGsSlGImoPfSKzZ2AFAbvHp8zaIRStqwNkpDQTr3/7kZuEiBljLiz4VBNqJE7QDgJFINAAoQ6Xq+8x+MxYANIM+xMfLcfQc0lX3kUt3WiMdyawSu7J0G/0hl0GKh+dlrDUHAGNoXBHx4GJ55ckHbndao4A6WD4GDGuc/ADyPSn5g4EVux2IsQuAdlzG0Qh/sK+HcACMxc2Lz+MeHmX93G64gHVKrN9XH1JMGfdOFYyMwt4A+vYx4AJWxWLCwnc6t5QuFG6iVwu2Cau0VYFwbNuHv4B7MwiUrYNI4IGFCwlMgCwOgNEkkdgFNCsLYyzS521QAiC2x4O7HMB3PKtCuK7tyoAxNrlr2CzhCtbCUzlldKFwE72xsFgE2auen7ECgHL9SDkE45W8HXTEeDatrIFyEkh3WmMIDGJsWFmyZDcnpMMAwAOjBIA6QBstwBwNANT1EQ+p4bHwuhhAs/vW622gE9nBsX54fjUhnlNVp9QBwGBzADCGplJEcENA0WLFB4iQBz/cw0gOwCpTBkAILF2YKPHQIOg+Egg0A0AzILQCRP4+hySz463AU2fRBADCfR4p9AEgYLmExY8HTh9ICa9I32tY7+Bu4lYGFfh1egJC0fUb4IdivPFOAsGiRRXPiSQabglCNrAMERwG0ec8C50DjBUIciBEKAIsjIAZJDBxKzIsYjrosoJF/j6Pe4tFdAkuA75gGRkeGwngPZVTJsajrm/kPsT/uXtdtY+3KgMYsZ1n87fTxSVF9ErejpBEENVzNOCrj+tWcO2eai0AQvize3h+tVhMqLw1+AsAlPU1dxPz7PCDhntSZQVUWQQ5AMrvmVkPrSyL/P3RAkCdRVMHgHYso1zn8v7TxQCagV93WtDrgrAkFDTXZQA7LuDQ5gBgDM3MFdGVGhCxM8MZNWLlqVspwh2IeLrhjBolAMow2MeUEU/YkF01KiDsjgAAdUBoBm4ANDMAlL9LB4Y66fQE96Q0A0B+3bBwoL9kgFb1M3ZM6PU2CGA/kxdMQME56GJRug3IB9y3p4TuxNCW3ES75tXFbRL9vrdcwAf2fjVLzDk8v5peLdhGF5cU0dn87WFb7AEq0Hd8GzmeqY0tziKxZnEoHPKP7KIBSyHgCS547B8tA2IkFjq7AKgCS1g1eAITP9fjWRW00tUQsj+1lUtXBXxy5i+yrVUxgDL0Ye/a84WbRRKQnDkvP0+D6XUCMJ9LL41rCaPjWRUhFncz6WR6mT/DgDI8x9gJhXtwdLobFiy+EMECSAdEZhbAaGIKY7UARvNbbcnhAKi6VjkEQRdDLUunJ7iziA4A+331Ys/l41kVhjVanQEsS3tKE/X76ulIplMH0AHAGBrfC1incDo9I/tTwvpj5TKA2+ZE9ojFxCqVn6/KuUULDxwsPL0MigCAOEcr61mkkCgDYDSft5IOBQBy4Btgyodvu8T7A6Lr1560RjqWVSni23jmryoWBbCICR0xOfI2XJC9cawD+ExqpVDQAMGjmVXa2DCeAHIqp4zOF26m84WbRekQbgHsTguPAeRuYkzCsnXQjgym14k9oDkYArqOZ1XQyZxykVwE6AIk4ndR744nMSFWFd+JuFU5eelkTnlYAhP/HR2QYlz0eYMuYPRnJAB8hMUEykkgvK9hcZHvwZHMKnq1YBtdWrqRXivYKqzAZtb5g2yMIIa5PQ6lNPjCGzAnQ4AVCHZ6gvAGq+CpnDIaMvqLWwDtQKAOCI+wBTnit1UWQJWVTfd6JAB4vV3MKgtgr7FA4B4qWNMR124l6PN9xvZz3PKK2D4e22m1NSIHPyQJHcuqpLaUGgcA430CN3PjSSAAOyuFgwfjoD+0CKmcOQxF0Z3WKEo8IHmkzwQGdS5ODkCwSvZ5G4QFMFrAsxI8wLHApNnxAEAOv7hWTLhQQDoXucqqCmssJjsosO40deYv7h8vMosYFNUerNjovM/bENckEAAg5KC/lk7mlIuVtao2pKosDFyHbywspuNZFaK/rIpGw4LFk0AQ7yZnBcuxbTIAWkETt8zJCUsy1KEIMkr4INv9RHaFEJ7xrrM0mp1TJAB4eH51WBIIFjNm/csBELBzcUlRSMkfXcIVLKCHDBfbK3k7aNgAPzw38QTAvUm1IXG1APl+X71tEMTfPm+DiJVE4gBf5MnPvB2Q4d6dg8Y4hz66x1UrdI2ccBEL+EEAT9F8rx0rZIcnIPYzPsRgT7aAqjKtZdjT6VNAOMbf2fztorauzuui22N8yF8rYrS7UgNODKDRHACMoXFFBMsdsh91EMjdEJgwoLBkxYE4MZjSB9NHCh5jMMvxavK/Ve7fATZpLnMFV2scDHktsFgBkFtBIxUOZBBkqcLlctAfdAVy94LdBBk54xeFcF/J20EnsisEpAPWVKtUwC2gAokpZi4IuDD6vEGXcDxdwE97qpSu+cH0OjqeFXSxoIahCgRhSeW7hrxWsJXeWFhMp3LKQuoE2oFBwA6SILiljsfERQqAkVrYuAuYvyb/28xCafU7KgBUJYHwmEA5nk+uvyhLv6+eTuaU04XCTXRxSRGdySsRca7y/eT3HxnAuP/wQsiLprEAgHyi7zVA7lROmSi/ZAaBeB7584yF+it5OwQkY7EeiTXQzMIFrwUWQNBfvCICni2rrFw+Z+BvLBZA9IFK3wL08PxBz5q5c60sfTIg9nobxCIe1ro+b4PW46KDv+60RhEicnh+tYjvjGfs9VhrDgDG0FSKCHCHOCgdBGLAI65MFRvBAZAL4ip46Q1k+MHVYGYV7GUPLVzAUPpQSDx+CcIV1BCbfFQTiOwC5hAnw4aqrAwCrHntQH4OgABYALvZdZpdMwc+WPkAGUcNxSYr3P3JzWEAyO8bYq2s4k+wSAD4Idbou3PjC4C6+4J7A7eLzj2sygpG7NwbC4uFZZBvRWZXMB5QBoVv7beCgb88LkcDBDkAXg/p8wb3vob1k9e+lOsi6vpHhj+MyVfydog4TVX2rw7+hvxB1/7Z/O0i3MEsVCIeuylg7O6RAFA1+WNrTjtxgjwLeF9Ss9DlsAyezi0Vru9o4Q9eIjMXsAxehyT44tsQyolGEOhAVZb+EPte+btVpbl4fDTmpn1JzWI3E5U1zy4A4rr7jQU41zPQp/K8qbp3fBHQ520IqcEK0Ofel/3JzXFZeI+15gBgDE23EsWghSUFCSAqCOQwCHcLoAKmarPVGh50WF/4BGlVLqYrNSAA0CqDmIPakEYxHZVEjqOS3z+qUTpQZrIVUnV+KgDUWT0BzLCqoBaa1SobAMihD674ToUS4vCHzwHMAfWAv3gpIrsA2Mvu/bABzIAKQLgKArHAwHiBZfDikiJ6c/EWsYtLJNZB/u/B9Dpa5grdlUSO7TuRXREWdxdJkgX6JVKo5M8GSuFweMX4O5YV3MQe418+N7uQPJxRQyeyK+iNhcV0aelGulC4SVg9ABSqzF9+7/jke0RR74/DX/dNAIB4BjsN9x/GA6/NqZO25CAAqvQzvATQH3Iojx1pT2mifFdZGADadSlzvd8rPbvcCwWvkQr0+7yhMC9bE60ESSDywtiu9HobQvQJCpJjXuIxgHYAsCs1QMMZNWLxhEW2HH6zP7nZAUDWHACMoZkBIF+RIBYKD6YOAvmKCCtATKCwDFrBIAdCvg8rag7C/QOTuhUAxio8xiZSt6zd7+cACNhTFRdWAZ+VewXHwirJ76GZ+wETBo7nK9D9yc20L6lZ/B0rAKiy0vZ6G8IsghwY5FhBFQDKVogjmVWi0DSsgydzypVJDDrhLigVfB0xFiA8EYQnaeh2tEEcGc4H26whPpDHCMrgyb8b3wvwOKqAvF5vuAvYLvChtt2Fwk10aelGpYUVyUoyAPKM7pcXlNCrBdtC9v+V42/HKgDuT64JCfA/oABAXh6m1zuyLaOZVRAAaLZgh05HfDaA3g4QthsJFNEAYCSAZvb9ZtY6O5a8SAEQwHcypzxkAY4xqupjFQDKFtsBX72oGcpr/+nirvnC23EBOwBI/f39lJycTJMmTaL8/Hx66623bH+WT6Jy3JcKBDnYqWIaZBDEAIb1Ss6osgODcu1AHlvFa6lFGzunE/wuz4o1Oy4S4fGA/b564UbDJMy3FlO5xK22YAJAYtLuSh1ZZeqUEY9BggtUjjmRFRAsi9EW0x2tsauLwVSV5pEtDUPGJHg2fzudySsR2/+pAFBVPBpjElvQAQgxSeugiAOgmaXQzEpnZsXWZQFzy7XsirNrIcT5cQA0s3weYn2EZBszKyrv467UQAgAwmL6asE2OpNXEpL9q0vA4s+qLNEC4GiM3X5fMFGHT/pmFkE8o12pATpoWAV59q8KAM0gUBXKw4HwZE65iPHm1rVYLIBWgvOJBQCtvr/TYw6AsDzCBQ/dAOMDj6c0k70GAMrQ1+ttEJbYE9kVIoberOizLL3ehriUMBprbVwD4IsvvkgTJkygoaEh+uijj+hb3/oWJSYm0u9+9ztbn+flCDBR4gFXKR4+iDFxcRexvNpRVaQHyGESAkyaAaFZeZOlrmqxkgUY8sBzWC+Q3WXHLcsnDL76tgt2AIyDxuSHOmr8/AB6hzJqaJlrJO5MNVF1p+ktfQh2hmsX18qV9v5k85UooBH30qzkC1wQGAPdaY1RrURHa+yaAaAO/mQIRFwjd+mgnpwMJGa7iMjWLVgIzxduFlYqXtbILgDaAUIVpGFM6r5H/t1IBQCIsQ7YQ8mhc4uC8ZMcilVWUrO+7TYsVYA+ZLkitktX8kX1LKueq2gAcLTG7h4j+Q6xbHj27Aqe3SF/rSjVc9Af9OZwADSL49YBIXQCinJzKBzOqKGlrmBSQjTJE3YgDfrGLjBGKm3JTSGJLLCsQjejYgXXo3b6TgWAgD5YrAHtWJibxV1z3Yv6fwiNcgpBj3MAXLx4MTU2Noa85vf76YknnrD1ea6IeLwXLHRycKpKuFVQdhHLAKgyq8OVA2uVGRBy5Y3fwCpOZTGUAYy7vORaZypXGuIQUcKCu9i4W07nQkM8hwygPH6lPaVJlLLRlcaxAj6zav46AOT3jYO/mQJCIgisv7A0RJMEMlpjt8MCAK0gUAZB7gY+kllFZ/O3C+gYsoAVlSVsyD9SAuXVgm10vnAznVtUTOcWFdOD7oCo3wcw1FnbdECogjduoeuVAFDO7o0GABFOMOSvpZWuBgG7l5ZupItLiujcomLhUlQlzdjpQ2Q/4rkD9Omyfs0sf6MNgKM1dnfPqxXPWVdqQIyVPsPzYBcC+SIVNSSRaKYK94gUZLhlDOMJXgu+2EbpI+gUuexUpIAmA6AMe2bwB33Z6w2tLQt364nsCrrf3SjOO1bYU0l7ShMNZ9SIueBQRk2IpVZ1j1W6t9MTtPiiSgPmVScGcBwD4N/+9je67bbb6OWXXw55fefOnbR8+XJb36FSRLwCOxRrp2KgqlaWMJ1DUXd4AqZbEskPbK83dFcQbi1Rxe/oAFBnNVRlFnOLnZzNi3g7OZOST2I6i6LV7+McZQBUub95YVYkBfC4Squ+xZZEWNUPMVi343rA5IKxgNg/SKQAOJpj9/mMHUrrT6QQKMMg3DxwO6K2oC4rNVIoPGhMoseyKunVgm305uItwlp2oXATnVtUTK8WbBOTFUA/EnetbAHUAaPsVubJH0g6emNhsbBo4hzP5JXQ/e5GOp41ArA6V7Cub3i2KIDitYKtwh3PJ/Fo4c/sefy+tzxuY1fWu7zYL8aXSvdawSCsRYfnV4sFLbJ/Oz3hEBgpFMouYCxKAe4qbwwvKI59tjGeuU7FvYXukp9Lrp95rKxugY/fBZwiTAiFoFWhMXZF7reu1IAoP4SYPlixzTJ/dfq3x7AOH55fHQxXSIl/8t1Ya+MWAD/99FNKSEigd955J+T1trY28vl8ys9cu3aNPv/8cyGffPIJJSQk0HfmltOepNow2ZtUS20pNfRMaiV1pVbSAU817Uuuob1JtbQvuUYr+5NrqMNTJeTZtAo64Kmm/cZ7+5NrqC3FXA54qqnDU0VdqZXU5yujQX8JPZ+xg57PCG7f1JUarISeN3k77U2qpQOe6jBpHwXBterej/W3ds+rpdzJW6ktJfgbXamV1O8rE9f6vL+E+n1l9GxaBXV4qkKuz6oPgzu8VInvfTatgtqN+4D7yEW+/wc81fRMaiV1eKpob1It7ZpXJ+S7c0ek5mvBGMCrV6/e8LE76C+il/I30g8yt9EzqZX0tKdKK8+kVtqSrtRKajf6t8v4P6THW07P+0voWHYx/euCTfSvCzbRDzK30fe95fRsWoVteSa1khZNLqWnPVXU4y0X8n1vefD++0voB5nb6Ec5wd95KX8j/bhgPf3bwrX06qI1Svm3hWvp3xaupbMF6+hswTp6MXczvZi7mX5csJ5+XLCezhasE8fw419f/Ai9vvgR8T1nC9bRjwvW0+m8jfRi7mb6YVYxvTB/Ow36S6jPV0bfN871gKeaCiaXiH7pMfqA/9tMBv0l9GLuZjq1oIhezN1MP8jcJsY6+hu6hN8D+X7xe9yhENVz91x6Kb2Uv5G604rjNnYfn1NOu+eFP3fQvR2eKnouvZSeSy8VusiO7JpXR0/MrRP6uN1TTX2+MvpB5jY6ll1MP8jcJvoWwnW3lexNCuqs3fNqtcfIurzdU01PG/exxxjjz6WX0vP+EhrO2E4vzN9OP8jcRj/I3EZHMrcG9b2/hI5kbhWC91+Yv52e95fQoL+EnksvpT5fGfV4y6nLGAvtGv3Iz++7c+so21VMe5P012BH2lJqqN9XRseyi+lHOcU0nLGdnk2roLaUGnpibh3tnjcyV2Iu0d033Pdn0yroeX8Jfd9bTvuTa2j3vFraPS9U/+6aF7nevRXbuAfAd999N+T1733ve5Senq78zFNPPUUJCQmOOHJd5MqVK87YdeSmFGfsOnKzit2xeyu2cQuA0bgi5JXo7373O0pISKBPPvkk5PWbTa5cuSIehHify3i8hqtXr9KVK1foH//4hzN2x9F9vxWuwRm74/O+3wrXEOnYvRXbuAVAomAwciAQCHktIyMj4mDkzz+/uWMIboXruBWuIZLmjN1guxWu41a4hkiaM3aD7Va4jlvhGsZzG9cAiHIEL7zwAn300Uf06KOPUmJiIv32t7+19flbZfDfCtdxK1xDJM0Zu8F2K1zHrXANkTRn7AbbrXAdt8I1jOc2rgGQKFiQNCkpiSZOnEj5+fl0+fJl25+9VQb/rXAdt8I1RNqcsXtrXMetcA2RNmfs3hrXcStcw3hu4x4AY2nXrl2jp556iq5duxbvU4mp3QrXcStcw41st0p/3QrXcStcw41st0p/3QrXcStcw3huDgA6zWlOc5rTnOY0p42z5gCg05zmNKc5zWlOc9o4aw4AOs1pTnOa05zmNKeNs+YAoNOc5jSnOc1pTnPaOGsOAEbZ+vv7KTk5mSZNmkT5+fn01ltvxfuURFNVzp8xY4Z4/4svvqCnnnqKZs6cSZMnT6b77ruPfvWrX4V8x7Vr16ilpYXuvPNOcrvdtHbt2uteMf3y5cu0Zs0amjlzJiUkJNCZM2dC3h+t8/7Tn/5EpaWlNHXqVJo6dSqVlpbSf//3f1/XaxtrbayOX2fsOmPXqjljd3SbM3bHb3MAMIqGOlZDQ0P00Ucf0be+9S1KTEyk3/3ud/E+NSIKKqLMzEz6/e9/L+QPf/iDeL+9vZ2mTJlCL730En344Ye0detWmjlzJv35z38WxzQ2NtLs2bPp/Pnz9MEHH9DKlSspNzeX/v73v1+383799ddp165d9NJLLykV0Wid9+rVqykrK4veffddevfddykrK4vWrFlz3a5rrLWxPH6dseuMXbPmjN3Rb87YHb/NAcAo2uLFi6mxsTHkNb/fb7uS/fVuTz31FOXm5irf++KLL+iuu+6i9vZ28dq1a9do2rRpNDg4SEREV69epQkTJtCLL74ojvn000/pS1/6Ep07d+76nrzRZEU0Wuf90UcfUUJCAr3//vvimPfee48SEhLoP//zP6/3ZY2JNpbHrzN2nbFr1pyxe32bM3bHV3MAMMIWzV6WN7o99dRT5Ha7aebMmZScnExbt26ljz/+mIiIPv74Y0pISKAPPvgg5DPr1q2j8vJyIiK6cOECJSQk0J/+9KeQY3JycmjPnj035BpkRTRa5/3CCy/QtGnTwn5v2rRpdOjQodG+jDHXxvr4dcauM3Z1zRm71785Y3d8NQcAI2yffvopJSQk0DvvvBPyeltbG/l8vjidVWh7/fXX6fTp0/TLX/6Szp8/T/fddx/NmDGD/vjHP9I777xDCQkJ9Omnn4Z8pq6ujlatWkVERD/60Y9o4sSJYd/74IMPUn19/Q25BlkRjdZ5t7W1kdfrDTvG6/XSgQMHRvMSxmQb6+PXGbuhzRm7I80Zu9e/OWN3fDUHACNsUELvvvtuyOvf+973KD09PU5nZd7+8pe/0IwZM6irq0s80J999lnIMbW1tfTQQw8Rkf6BfuCBB6ihoeGGnLNOEcV63rrJIi0tjf7lX/5lNC9hTLabbfw6Y9cZu2jO2L3+zRm746s5ABhhG+tuCF174IEHqLGx0XFFjHNXxM04fp2x64xdImfs3ojmjN3x1RwAjKItXryYAoFAyGsZGRljIhBZ1a5du0azZ8+mffv2iaDejo4O8f7f/vY3ZVDvyZMnxTGfffbZmAhGjvW8EYz8s5/9TBzz/vvvj6tg5Jtp/Dpj1xm7vDlj9/o2Z+yOr+YAYBQNpQheeOEF+uijj+jRRx+lxMRE+u1vfxvvUyMioscee4x++tOf0m9+8xt6//33ac2aNTRlyhRxfu3t7TRt2jR6+eWX6cMPP6Tt27cr0/rnzJlDP/nJT+iDDz6gb3zjG9e9HMH//M//0C9+8Qv6xS9+QQkJCdTd3U2/+MUvRImH0Trv1atXU05ODr333nv03nvvUXZ29rgqRzCWx68zdp2xa9acsTv6zRm747c5ABhl6+/vp6SkJJo4cSLl5+fT5cuX431KoqFO04QJE2jWrFlUVFREv/71r8X7KOx511130aRJk2j58uX04YcfhnzHX//6V2ppaaHp06eTy+WiNWvW0CeffHJdz/vSpUthhVQTEhKooqJiVM/7v/7rv6ikpISmTJlCU6ZMoZKSknFXkHSsjl9n7Dpj16o5Y3d0mzN2x29zANBpTnOa05zmNKc5bZw1BwCd5jSnOc1pTnOa08ZZcwDQaU5zmtOc5jSnOW2cNQcAneY0pznNaU5zmtPGWXMA0GlOc5rTnOY0pzltnDUHAJ3mNKc5zWlOc5rTxllzANBpTnOa05zmNKc5bZw1BwCd5jSnOc1pTnOa08ZZcwDQaU5zmtOc5jSnOW2cNQcAneY0pznNaU5zmtPGWXMA0GlOc5rTnOY0pzltnDUHAJ3mNKc5zWlOc5rTxllzANBpTnOa05zmNKc5bZw1BwCd5jSnOc1pTnOa08ZZcwAwhvaPf/yDrly5QlevXqXPP//cEUeikqtXr9KVK1foH//4hzN2HbmpxBm7jtysEo+xO9aaA4AxtCtXrlBCQoIjjoyKXLlyxRm7jtyU4oxdR25WuZFjd6w1BwBjaFevXqWEhATq9W2h03kb6ZnUSnomtZK6DHk2rYJ6vOX0fUP6fGXU7yuj59JLadBfQj8uWE+vL36EnveXKKXPV0bPplXQ8/4SGjSRn9z9EP0wq1j8X/d9sjyXXkpLJldQn6+Mns/YERR/yci/rYR916Dxff2+MnGtfb4yetpTRU97qkL6QRbVe/i8lTztqaLCyeWir3u8wX/Lwu9JF7tHXamV1OMtp5/c/ZD4rPz+/uQaavdUi2t52lNFHewv5PmMHfRG4cPU7qmmA4a0pdTQ/uQa2sdkb1It7U2qpT2GdKcVU0JCAl29evWGj922lB3U4y2ny8vvp+fSS8P6vz8C4felK7WSfphVTP+6YJP2vqvE7n3v8ZZT4eRy6kqtDHtPPhdZ+LjDPX8mtZKe9lRRu6da3D/cn7aUmjA5wO5xu6dajAcu0Ac6aUupoYLJJWFiteMrAAAgAElEQVTHyuNMJThPK9mTVEvPplXQq4vWiM8dUAiuiV/j/mS17EsOvn9p2QO0L7kkbmN3X3KJrb6W70ufr4x+XLBe9C+/5wc81bQvuYZ2z6sNu8fRiOretaXUUP7kHbQ/uSbkfprdX36fuE7Zm1RLu+fV0nfn1tF35tTT47Pr6X/PrqfmGQ3UPKOB/mlWA31rZvDvP81qoMdmNdDjs+vpO3OC8sTcOto1Lyi75wW/C+N+ryRch313bh3lTt5Ke6TXZeGf36MQ/KZK/vfskfPDa6p/P+8voeGM7eI1Lt+dO/JXln+aXXHDx+5Yaw4AxtA+//xzSkhIoCOZW+mVvB3U76sXMuCrp8H0Ojror6WD/loa8tfScEYNHcqoocPzq+lIZhW9vWwdnVtUTEczq5QynFFDg+l1dDSzio5o5GhmFf37im/SsaxK5Xtmcnh+NS1z1dFwRg0dy6qkY1mVdDSzSvzbTPj3HDG+65BxfUPGNQ/46qk7rZG6UgMhfYP+QR+hn4YUMpxRYyp93ga6x1Ub0tcQfLcdeXvZOjpk9PcAO78BXz11egLUk9ZI/b566vM2hEmvIcMZNfT+8keo19tA3WmN4tq7UgPU4RmR9pQmOsCkw1NFCQkJ9Pnnn9/wsduVWklD/lr6xQOraNi4d7zfD0Ug/L4M+OrptYKtdCqnTHlfzQTnYXbfD/pr6R5XcIxZjREu+A0+PgaM+4r71ukJ0IGUJtozr4V2z22hfUnNtC+pmfYnN1NbMu5ZgDo9wXvbndZIPWmNYhzwsSGPey5dqQEqdFUpj9ONMVl6jN/WyYGUJur1NtA7964Neb2b/eXjVJZOT6hgDHd6AvTe8jX0bFpF3MZuh6fKVj/LfXksq5JeK9ga1n/oiw5PgNqSm8T/u1l/RSv8fnWlBmiRq5I6PQFb91G+R52SHtmX1Ex75rXQk3Na6duzW2nnXTup5qs7qfLOnVT3taA0zdhJO+/aSY/NaqXHZ7fSk3NaadfcFtozr0WMbT6+D6Q0Ubsk+M0OT4D2JTVTvqtMPAs6kb9D1n1tyXrZNbeF9iYFzwnnppKD/lo6k1cijuOCZ5fLXkOemFt3w8fuWGsOAMbQoIh+lFNMJ3PKqSetUSgjOwD4s/seplfydlgCoAr88B3Hsirp31d8UwmJVgB4KKMmDACtIFD+Dg5/mGAH0+uo31dPPWmN4qHkE0dXasCyr1QQOJheZwqAmNijAcBLSzfS8ayKECjgANhtACCffOWJeTC9jn6+crVQ6FDafPJUKcF9yTVxB8B/X/FNLXhHC4DnCzfTsazKiAHQziJgML1OCYBm4MjhD+NjwICEXm8DdaUG78++pGZ6ck4rNc0ITqT1X9tJzTOCk+eTc1pprzFhHkhpsoRAQAgWENECoA4C7QBgV2qA3rl3bcjCRCVW8NfOJvtOT4Au372B+nxlcQVA9IEOAlX9eCqnjM7klYT0H+8HHQCOFgwCADuMhWUs8Lc/OQh/T8xppUdn7qTqr+6k9VNa6B5XLeW7ymiRq5KWuerokTuaqWz6Tmr8ehAEv21A4G4bELg/uTkM4swAsF16zQwAAYEqGASgtiU3hZ0fB8JebwO9VrBVCYCAwL0S/DkAGGwOAMbQoIj+dcEmOp5VEaL0VdYtGQB/vnI1nc4tjQkAT2RX0PvLH9FaCI8wUDMDQPk9K/Dj8Hd4fnUI/PV5G8QqsXnGTqqYHlRMzTN20pNzWgUQdhsTZiQQaAWAMgTahcE3FhbTmbySiCyA8mTc76un//uNh6hPsgBaAeDepNq4AuChjBr6+crVou+igUD5vgz46unikiI6PL867F6MBgTqAFAHfgf95vDXndZI7YbVr3nGTtowpYWWuqppgbuUFroqaKmrmtbe0Uz1XwtOnnvmtYiJUQWBMnRYWQAx1q4XAL69bB0NGCCKcWlm/ZPhr1Oa5Ds9AbpQuIme95fEHQB1lldVH/Z5G+hMXgmdzCnXAmC7ASNmABgLDHalBmihq8IUAGUwl3UIgGmvsVh5dOZO2vGVVip0VVGmu5jSE4soPbGIMhI3U3piEWW6i2mpq5q2TGul+q/tpEdn7hSWwN2GpU0HgSproF0LoAyAMvyZWQFlC6BOulID9ObiLaYAKFv/HAAMNgcAY2hQRKfzNtKRzCpbAMgh8P9+4yE6kV2htdrpABDQdXh+NZ3OLaW3l60zBUCdZRAAOOSvtbQWquCPW/8wufZ5G6jTE6An5rTShikttNBVQQvcpZTvKqNCVxWtvaOZdt61k/YmjUCgHUugbnLv99XTPa7Q4yOBP/zmmbwSeq1ga4h7GhOymQtYtvr8fOVqYfFRKW+VGzjeAHjECCNAX+lgTe57Dn/8/SF/EMwuLd0o3LVWEikQDqbX0VJXNfVrAFD1GRX84R7yBctKVwMtcJdSpruYMt3FlO3eRtnubZTj3kErXQ1U89Xg5InJKVp3sAyAZtYrO/CnghFYKS8t3UgH/bVhVqVYAPCNhcX0g8xtcRu77Z5qratVBeGQVwu20bGsyhBLPe+TSAFQB4W6f3d69ACos8qq4G9fUjPtnttCj81qpYrpO6nQVUUZiZsF9AEAuRS6qmjbl4PW7cdmtdITzBWsgkAdCO6NwgVsBn0qFy/Oywz+YEw4X7jZcQFH0RwAjKFBEb2Uv5EOz68OUTIyAMoQeHh+Nf3Hgw/QsazKkPg5WPaOZFaJic4MAM/kldDluzdEBIAQDoBWbmPdOXALC2L+9sxrobV3BBVEjnsH5bh3CAhc4C6lhxOb6NuzW6ktuUnAVbQQGI0LWLbwDfjq6WROOZ0v3Bz2OgCQu4B1k3Kft4H+fcU3aTC9Trt6V1kB4wmAz6QGrbvvL39E9I1dUFMBF7cEX1q6UWuRjURUMDfgq6elruAzZwZ7qvHAY/5gkWlLbqLHZ7fSw4lNlOPeIaCPAyAgcHViE7XetZN2GfGB0cYE6lzAZuAXqbUJgHpxSRENZ9SYQkYkANjhCQRBKrs4bmP3gKfa0hqnekbfWFhMh+dXC8uvfO0cAPFaLDAoS4cBgO0p4ZCpug+yzgD8wfXbPGMn3e9upEx3sYA/X+KGEAugL3ED+RI3UEbiZrrf3UjVXx1xBQMCdytAkAMZh0ArAFSBn87Vq5L9yUHLph0AbE9poguFm4RL3Az+HAAMbQ4AxtCgiM4UbBAw0usNtwLKExkA8P+tul9Y4rgAruwA4Nn87XRxSVHY6xD5M/x7hjNqhPVM52ZWCbf8YGKF1as9pYnqv7aTFroqKN9VJibOBe5SIYtclVQxfSftntsiLBRQ3mbwLEPGkGFxVCWBWFn9ZDmeVUEXlxSFvQ53th0XMADwoL82TKGrlCMU4544A+CxrEp6b/makD6K1WI3mF5HF5cUjQoAqqTfAMBeb4OlxVcGem754Qkfdca4BejBAohFDMAw31VGZdODFhRAICYiMxCUYwM7PUEARPjAaFj8ZEsSFlnnCzfT4fnhwGQn+aNDA4Cv5O2gH+XEHwBlC5tO0I9vLt5ChwwY7lH0A+LedH0Tq7SnNNFCV4Vwz1sBtwx+e1nSxz/PDFr/FrhLQ6x+MgByyXeVCVfwzrt20j/PDE8M2cuASWURBAC2JYe7h81i/aygj8NbJAB4cUmRJQDKcYDfmVPvAGC8T+BmbhwAh/y1YQrezA0MC+BRCbQ4BMKqZgZkrxZsE8rdSjhcAjABgDrIU8V48UkekAQ32u65LVQ0tYXyXWXCAohJExbABe5SeuSOZnp05k7aMy8UAu0ANJdebwMtdVWHWK6s4v1kIBhMr6NjWZW2ANCOBZC72uSVvGo1//jsG6+IOAAez6rQAqCZRc0MBFUAaAcsdSLfw35fvYAnK7jnljVu9ekw4G9vUjN9e3YrbZnWSgvcpSHWP1gAuVUwx72D1t7RTI1fD1pQdrNYpUisgQBALHxGEwDxPgDwzcVb6EhmlRIAdZYnKwB8eUGw/EY8ATBSiygAcFgCQN4How2AqmQawJPOuirrCJ7MsHtuEP4emxV05RZNbRHWP50LmANgpruYHk5sogojKeTRmersYDOX8J55LaYAqIr14xCoy+rVASA/D1kOaADQygX8rZkNDgDG+wRu5qYCQA4wZtnAMgBy8JMBUGXJiwYAh20CoFWQP5/keRD9gZQmenJOK62f0iJcvpg4uQVwgbuUVrkDYQDYlRqwnRTCAdDMAsgh3AwUjmVV0qWlG0OgwU4MoAoAhwwAVLlyxloMoA4AzfpeBWfycdFYAM0AsV+6j9wCqLunqpg6bvlDtueeeS30zzODMavc2ie7f7k8nNhETTOCsYAAQLOkEFVMGrcAjlbSh+zi5QB4VAGAZq5HMwjs9AToTF4JvZi7eUxYACMRDoCqPoALeDQtfqMFgChN9IQBgI1fD2b9cvcvLIBw+fLXIasNAOTlYZ6YYy8z2I4F8IBNEDSzAtqNAQQAAtx1rl8ZAh0XsAOAMTUZAKHsdQCocgEjBpC/DujCxGcGdWfzt9OFwk22AFAFhDoLoJnrVy75AksZJpyK6TtDLICIAeSyYUpwFQs3CHf/yn2lykS1EwNo5g6UX4cLGHBhJwkkWgvgWANAuIBVrncrdy+HM378aAOgmQvYjrVXBYGwAiLeCK40KxdwjnsHFU0NQqMqDpCDny4BZMAkBpCPMxX8mYFgt/Rv7gJWWQAjiQOUk0BeydtBJ3K2xB0AZdC2AsBzi4oFAHJYNwNAM3d5LC5gK9evDIFw/+6a20KPGzX/tn25VbiAAXjcBSxbBLPd22j9lGDIgyoOUI4BVGUCW2UB27EImsEfAHCvieXPygVsZQV0ANABwJgaTwIZzqgJswAOWAAgTwJRiR0AfCVvB11aujGqJJBhRRKIHeFAKMcBdnoC9PjsVlrhqhcxgBwAc9w7aKGrgmq++v/Ze/PgqK4z4bsDxnaLRWFHrEJoa9RqqdWSWqAFsAEL0ALapZbU2lek8difPR47cezhhUAIBIZXjDRS9KFXimQVsvSiEUEDERQUWFBeyJSnUvlnaipOxVNTNXG2qomnKpXn++P2c3T69Dn3ntvdUot8faueAvVy+957nnvO7z5rJ5wKb4eLHPCjYU8LSq9Gz2UBs9mfWjBIy6ilGmbshVxLEp2oIpsEIgOAZxcJANJJIFrWPy0YRMEs4PmKAaSTQPS4j3lxgAiBnZs6IcvY5JEEQv8dH1IGyUYn1KydK2mEFh42hIGdA1i5FNlCMpl5oQnexAWygpAxYy8UJoF4C4CLIQlElOyhdm1uJZdAv6leeA1YAGTf57nPRa513rXFJBA6BlB07XlxgAiC72w7CW9sUWL50o0NHgCIFkA2BjAxpBIqVndAB1MPEMGPhT523M+77hfMZNZKGPI2NlAGANECyUsCCQKg9hYEQB82nIiuJxaQrDI9MYBPDx6GkXin0NpGu4BF4k0ZGFEWsLclYOjSH7jotGzohAxjIwFAhMBko5NY/85HtMIVlwUHAY6GPplz6I5pJLUMacugbEYoyoTVAdMpJaoAyC7KvAD/T196xaPemtqEvhgAcCBOKUruKwDS11pvGRi9v9cdM1cGRs9x0RBIxwSe2aksOFVrlEQQS0gFmJYXecQAWkIq4HBIK3RuUsIXzlIWbDZ8QSuhBsMX8OFHzXIpA4M86EHIQBi/xAEUbyAQy8AMxJUuijIwstfjUmQLTNnKYCCuVtMF7M/MX1qwDAwvC5h3PLxMYITAt7cqVsDCVR1EZ+ksYFoQDrOMTVC/Tkn+wDg7GvzYgt9oJaXldLhixeS9J5rztGCQzRKm6wCy8YF0DOE51wNOEAD1b4sOAO/fvw85OTkQFhamuFcnJtzedzqdHs2c7Xa722e+/vprOHnyJKxduxZCQkIgNzfXo+HzV199BZWVlbBq1SpYtWoVVFZWwm9+8xtdx4oT0QcJRTAY59mWiLUAshauTw5kw6il2g146P/3xqpbAAfi5ApBi0q8+LMOINYsxGzgU+Ht0LGpE7KXt4HdWAt2Yy0cMDaDY7VSPuNchBLvh4sfWyRbqywNSk9sgxsAsi5iLRBEuWlT2vnx4slYABQtxq9uzYXMteshdGkIGAwGqN30CnniPx/RCrYVMR66u+2FjW4AuNC6+32qEDQNId4CIEpXtFIIul8FAL3dN+oaDYBa3T9oHWAhEF2Bp8Lb4a2tHVD2zQ5IMdZ4JIFgHcCWDYoOs+ELvNhVtfMUhS+IkpVERaJF8HM5qtmtEDRaHXmxgu1b8mB3yA5Y5dLdmk3Zmrobu3wN/KOpImC6KwOAPAicsDpg2OwUWkN9BUAtq+yFXeqFoHkgyD48IhC9u33OCnh0eZtbLCAPAJONTigNVUrHYPwqD/5YsGOP6czONtLOTgtevbEK4gMZDYAiubBLiXGlLaQIyGoQGATARQiAP/7xj+Gdd96BDz/8UAiA2dnZ8B//8R9Efv3rX7t9pqWlBbZs2QJ37tyBzz77DA4cOAAJCQnwpz/9iXwmOzsbzGYzfPTRR/DRRx+B2WyGnJwcXcfKtoITxfrw3MC9sQ3wOOsYjCc6PCxesi7ggTj1VnBaACVqBaenDRwNgfTCemFXK0kKwSyzd7adJBPrFQ344/2WGgDSlkM1CBTB4N20ArhuqeJaYWQB8OSWbKjfEQH1YYfcABAnQtuKGIg2boNvbXfCO9tq4J1tNfCt7XVwimoFt9C6+70I5Rp++tIrbnDEg0C65qPatUUAxMSDXmY/euGPB3bdMfKdQHgPAiwEYnD+qfB2eHNLB9St64TDIUqM3h5jHew3NkFxaAex/OmpYcleQ1H8KquXahAoC4JnXFamR5m5bq5vFjYaw47CwdVJ4Nz4ihsAnqcAMMa4Db693Unkn1KOwj/EVAZMd9kkEBr4RCB4MbIFrluqYCyhUghcmBzkD9gTAaBMKzgZCHx/h/LQ8lqYAoHZrjqWbC3AuJASsBtroTRUyRzmZa/Lwh9allOMNeQBiHfcIkuyCAJZEKTja9UA8HKUUttRFEsogsAgAC5CAKQ3EQDm5+cLv/Pb3/4Wli1bBh988AF57Ve/+hUsWbIEpqenAQDgZz/7GRgMBnj8+DH5zOzsLBgMBvj5z38ufXw4EQ3ElcKE1cFt9yQCwJ7YBri/9zhM2cqEiRbdMUpbNTZ7l5bBOKWLw5C5hgt+ahB4bXedLgDkgSANgbgwowuwK7qJlNrAiYS2+tHWUDX447WoEwGgKHtZCwIfZebCgGt/LASej5jLTmYXYNr922eqhyf7jsLlqGYhAO4OCfdw55yLqAWDwQBffPHFguvu9yIUN/rTg4fJuGlZsWhgUQPAm7ZSGIl3Cq+7FvT5EwDp/fHcwZddEIh1Ad/b0Q6vhSmWEsySfGfbXPs3LcsfC39qRcx510LGEsiDQBYEz+5UFshHmbluxa8vMQs6vcDTAEjrblxIuJtLcDYrBy5FVQdMd0UAqGYJvLCrFQbjamHKVqYJgCz8sNdMr9DHgNYzrThOkTsY51W0Ar61tQPe2KLoa8XqDjhgbIYUYw3pBZy7oh3q1s21gNMLf+xxnVUBQLVj18p6pudF1jrJA8EzO9ugJ7YBblgrVBNKggDI355JAAwNDYX169dDVFQUNDQ0wH/+53+S92dmZsBgMMBXX33l9j2LxQLvvvsuAAD88Ic/hNDQUI/fCw0Nhf7+funjw4noH00VcCu5xA34eBmV6CLFSX46pQTu2Iu4i4MWANKw9zjrGFy3VHGhTw2q/AGA9G/gIktbinAyYCFYFO8nAj6R9MY2QJaxySNhRA8EIrjRCS304nthlxgAaRky18DDjDxVAHxxyfOwfMmLsO65UEhZYYK3t9dAV3QVGAwGmJycXHDd/f6uGrgarfQwRrASZdN2Rat3CaGlK7oJxhIqYcLq8MrFqwWAPbENugFQDQLphRhdn5hxiYsKL9lDFOah5pZG6Yp2T2ASHZ8WBKqB4NmdbdAd0wgP0vNV4+JkAJDo7rJQsK80wT/vfQm+53p4CYTunt5ZzwUU9jxxPPGzvbENcDu1WAoAvQE9HvTRIMoCoFbMolpM4Jmdc11BsDwMWgPr1nVC03ql1l8nlfAhivmj4U/LyokAqAbDWi5hLbcwloARlZJBGYyrhVFLNbfOoBoE/m0QAJ89APzggw9gamoKPv/8c5icnISEhASIi4uDr7/+GgAAfvSjH8Hzzz/vsa9Dhw5BU1MTAACcPn0aoqKiPD4TFRUFZ86cER7P119/Db/73e+I/PKXvwSDwQD/EFMJM/ZCIfih4NM4/j2e6ICHGXnCBQOBkdclhAbAu2kFcNNWSgBKNqHDWwAUWQJpAKQXOTZOyx/gxwNANkNZrYYhLQNxtTCblcNNEkEAZF3AvEV3wuqA26nFQgB0bDgENZuOwl9vLYHqjUch7Pm1sGHZGvjh7kIwGAzQ19e34Lp7YVcNdMc0kjACHnBcjW6CMzvb3ECeFR4ADsbVwoy9ULfbVwbkaABkx9gbCKQXalzAcIFhLSGiJC/2HP0JgN5YAq+4AHAgrhamU0p8AkDHhkNQt+kovL61BGo3HoHNz6+FiOUr4O92OgOmu6d31nNdlKxgxyH8G+NTefCHAEh/3heLn14AFI2RGgRivNt7FAi+vlkBwbe2epZ4obNneYkeMuctA4AyEKhmCZQFwPFEB/Sb6qVKywQB0H175gCQ3b788ktYtmwZfPjhhwAgBsCDBw9Cc3MzACgTUXR0tMdnIiMj4bvf/a7wt77zne94BEIbDAbIeLEGjq88CVnGJq7sd0mGsZH8f7+xCQ6FtEJxaIfba7Rkub5zwNgslJdDWuDYinbIX3kSXg5p0SUHjM2wbnkq7Dc26f4uT/YbmzyOL8PYCFmc1/HY/fGbG5enq14j0fWlx6Fg1UlyzVnZY6yDdKPiauYJvpe7oh2OLm+DdKOS1BH7/EHYY6xzE0yIsRtrwfpiKXzDsAQSXjiouojOp+7ufbEGsoxNULiqAw6FtLqdN55fllEBFZF+q+k6Xld/S5axCdYtT9W8P2TGnz1X/D+OU7qxwWP8eeesVzKMjbBh+R7NYxOJSB9psRtr4XBIKxxd3kZ0lRbUbVoMBgPEPP+yh+7SkvJiBSwxLIFdy7ICprspL1aqHiM5VmON29/pxgY4vvKkx3mj2I21kGKsEb7vq+wx1sHakGQ33dLzXXY+QVdvirEGko1OSDY6SdktrMeKr+Pn6HmI3afMcdiNtbBuear050VjQx8HK0nGKo9jpc8V3zu2oh2yjE0e7/EEr0Oy0QnWFxe+i81i2555AARQJpCzZ88CwPy6gEVPoi8s2wbG53fCi8/v0C0hL+zy6nv+2s+y5zb55fcDKb6eg9bYvbBsm+4xMBgMsOy59fDCsm2q8g3Dc/Dckm/OuxtNTXfxGnirw/Ohl0Hd9Z/oHVfUXa3PfcPwHCxdEhow3X3+uS2a9xdPRNeE97n5kBeWbYNlz23y6Te8OW+ta+LNOQTymFGMz+/06nvPP7clCICBPgC1TQYA/+u//gteeOEFGBgYAIC5JJDR0VHymS+//JIbjPzkyRPymcePH3sdjPy325ResqfD24gp/j0m4FSUmTSe6CAlKNgCl9j3kW3Dw1ZlP7uzDa5bqohpHoVXoZ2WMzuVlkSnwtu5xT61RGv/5yJayfnLfPYcs2+Z3z4VPleRXlRbSis7bCyhksTSsP0i39vRTnpkvrv9JHGxoLzjkne3n4Qb1grSpN1gMEDB2qPw5halx+YbLnl985y0bmyApYalUBuW5hZIv5C6+9a2RnhvRztcjmqGYbPT7bzRpcQT9nOsvmO/0mGzEy7s8tRvb4Qey/d3tENiSKVbjJ6syGYJvu1qjcU7P7V7mj1WkXx7m9IyEeOx2FpnPF1kx4HWRVawUPCw2Um6R7zjGhdW3qLEYDDAiTVzukvrL8qpnTXw3DeWwqHQAwHT3b8Ka+Ye35sCoc8Ri9a/xZw7tlh7NayT/M27Xt4KdvCICymBN7Z0kDERjYvaWInG5/XNSpHnDlfyEi3sNeKdv8wxvL65A+JDyqQ+zztenk6xx4oJWK+FdQjlra0dcG13HbwWpowZTzo3uQtem+YNwV7Aiw4A//CHP8DTp0/h6dOnYDAY4OLFi/D06VP4xS9+AX/4wx/g9ddfh48++gj+/d//He7duwd79uyBLVu2wO9//3uyj5aWFti6dSv85Cc/gc8++wxeeuklbjkCi8UCs7OzMDs7C/Hx8V6XI7gUVQ137EUwbHbqLqZ7f+9xmEwqF2Y6YgygWhLIQFwt3LEXkbIbsuJrDKBMfCCep1qMHy/mD1/TigfEGEBeGR1eSRg2FgzboPFKcKBgEohaTbY+Uz08yDwIf7O9EP6fbUp/1KOr06EtrAS+tb0S/ld4A2SFJkDb5hPwN9sc0LgpH7a/sBFCly6HUesRt1IaC6m7P4hUdHYwrtajFqAoHlAr/g9jALE8w01bqc8xf1oxgLIiExuIgokeWokqvP2wCV08wRjA3tgGbrKSSB9leh7TcjetQFgqBmO1zkXUw+vbiuB1l+4eoXT3zM4G2BeaAO2bT8DfbnNA6+Y8MC1fC2uWhcDb26sCprsYA6glvDi/wbhamEwqJ3FqdNwaPhx7G/OnJRcjWzRjAPXEBfJKruBDCPvgTF8T/Jfdp8w5nYtoJTGAMserVRqGZ1DAGEBeuRiU7phGuGkr9SgfgyXHeA99wRjAuW3RAeC9e/e48R5OpxP++7//Gw4fPgzr16+HZcuWwfbt28HpdMIXX3zhto8//vGPcPLkSVizZg0YjUbIycnx+Myvf/1rcDgcsHLlSli5ciU4HA6vC5JeiqqGG9YKmEwq5xbTVSsKe8NaAQ/S830GwOuWKniy7+iiAUAa0HzZv1ZSiCwAihb/6ZQ5QGHHSg8AXrdUwaW4dK7uJq+MgTPhjRBt3AbLl7wISw1L4JtLV0DSijsmr6AAACAASURBVBg4E1EO1xMLyES00LqLANhnqoefHjpI4MpfADhsdsLDjDxhAs5CAyDqgQwM4tjqOVbe/rUAsIcBQD3JIKKsYJR+Uz2MJVRqAmD75lyh7p7dqejuCpfurn5uBRzZsA2+F1kK71M1LBdad7EMjDcQeJVKBGHBxxsA1ANy3gKgTAIPXg/0GmnV81PLXJ4PAJSpD6gHAEct1TBsdnp4fVgrfBAA+duiA8BnaaMBcNjshBl7IdeCgoskb7EcjKslJTjUAJCFQF7B54/3H3ErB/OXAIBaVkBfLID9JqX8C3ZdEVldZADwbloBjCc63CY+XuYbm+02bHbCD3cvfDAy6i5mAffENsAnB7LdMoHZlmRqfW1FANjnusbXdtf5DQCxu4i3AChjDcQs3S6JMjMyv6HHAuhPAMTuNloAqLVQ0zp8KbIFPjmQDZejmt0AcKF11xcAvBzVDPf2nCCdi54FC6AWCNLjhyExeqBP9BveAiDugweoMgCIdQrVAHA6RSm/ptVfmBfuEQTAIAD6tNEA2Geqh4cZedwK/mq9QftM9fD04GEYjKvlAuCVqGYuAPJapk2nlMDdtAK/AKCeUixqgufi635ExyMLgDzQGLVUu5Xh8dYF3BXdBJ8cyCZuQz0AeNNWCj+IdAYUAFE/76YVEGBg9VdWn2kAvBSp1Fy7t+cEjCVULpgFkAUuWUjTC4AyFkbUPS0A5Fkgezm6qAcCe2IbYMZeCJejxN1CtCxJ7GJ9YVcrXI1ugo/3H4ELu1oDCoC0C5jn5lRzAV+KbIFbySUwGFfrEwDiNZSFNn8BoBoEXoqciwX3Fli1zk0WAHnXXvRgwUKgFgBe2KX0uMbi7SL4E8X9BgEwCIA+bTQA9sQ2wIP0fFLAWXbh7HV9b8pW5hMADsTVwrDZCZ++9Iqb6/QvBQDnwwL4ID3fDUxkAJAXZ9VnUnrp0q22RLWvaAA8F9EKd9MK4PTOwC2i399VQ6x7YwmVcH/vcS5YeOMCRgC8bqmC+3uPu4HNfFoAWUDTAkARxOF5y1j6vBFZAJSJy+QB4HVLFdywVsDFyBY3AKQXdW8AcCRe8Xacj3h2AfBiZAsMmWvcOoJ4awHUC27+AkA1EMT5xRv3rozosQDKuoBFAMh2TsL/98QqPdx5vYSDFkC5LQiAPmwsAN5OLYZRSzW3aKtah5DxRAc8zjqm6gIW9QJmrYD39x4nT7Z6ANBfwKcFgMNmJ/dzote9AUCZgtBD5hp4su8osdDoBUBaJpPK4Y69iOv24AEg/XQ+Yy+E93Y0BGwR/V5ELbFi9pnq4dOXXiF6x2tpqMcFjACIrnaeG9gb6x9rAZwPOENA88XFrAWfelzA3riB7+89Dt0xjR4A6K0FEGXGXggj8U4ly38RAKAo0UELAvEasddhMccA6gG0cxFzrebUrHnPEgDSMmF1wLXddUEA9GELAqAPGwuA1y1VMJ1SoulC62IgsN+kBOBjP13aynE1uokLNjwAHIhTWuJ8ciBbygroLwCk4Y0FOTwffH3Y7PQa9nyxALIL7N20AphMKneDEW8B8HHWMRiIq/WY8HjwRz/BDsTVwniiA95dBACIbc0+fekVAic8ALwS1awbAHtjG+COvYhku///AQBljkmPBVAvAPaZ6mE2K4e0rlMDwIucRZq3UGM7NbR2BxoAT4XXc0tEiQAQrwXtBr5jL4Le2Ia/aACcr/37AwDVIJAGQBYCz7u8Jxd2tXIBkG0LxyvbFATAIAD6tLEA2G9yjwMUTdasFbA3tgEeZebCDWuF28LBA0AacHgAqMcKOF9JIDTs0RY3hD81ANQLh1oWQJ4beNjsJNa/7phGnwAQrWa0+1cNAOlJ7KatFHpiGxYNAGKLrBvWClULoCgGkAY7vB7495BZKbfDcwP7CoDzAX/9pnpyrvO1f18BkO5FzI7XTVsp3LBWEGjzVwxgd0wjif97VgCQPh8WAEfinXDDWrEgAKg3BpA3XnoAbb4B0xcAPBfBhz9ZAOyOaYTplBJu7VcZC2AQAJUtCIA+bCwAYhzgQFytZvA2u3iOJVSSBZJ1AYusWyI38Ei8Ez45kA3DZueCAiD+Pg1xPbFKD2Se9Y8HhGqWyAHOe3oAEOVhRh5MWB0eMMJmbONYqQHgDWsFTKeUuMVXycT/nY+YC2AOJABiDCAC4KilGh5l5kq7gHs4IMcDwD7XdR+1VC9KAMSELPq1K1HNcCq83S9WP14iiD8tgDh+mPyBva3VAJC2/sm6gMcTHTCdUkL0OZDhC3otgLxEkK7oJri354Tb9XgWsoDZ/bG/f2ZnG7y1tUN6H+z3r6i85w0AqlkB2aL/IgCkY6cnrEr/X1kA5EFgEACDAOjThhPR37sAsDe2AaZsZXDDWiGsKSdynfWZFDcwnQ2sFQOoBoF37EWaGcELZQFEC5A3Fj49FsBBCfhD0O5nFlpvLIBXo5Xs32u76zwWVS0AvBrdBNMpJXBmZxt8e3vgAZCGh6cHDxM3rhoA0pY/FmCuMgCIySC8moCL1QWM4z3fFsCeWM/C0jydpPVSLbxkwuqA26nFxE1LAyC7sMss0DREPcrMhX5T/aIAwPcFAMhCoFoZlMtRzXA7tRiu7a4jr533EgBlIXChLIDeuIB5esJ7eOABIO/8efrlrQsYBbN/0f0btAB6vwUB0IeNBkCcsAfjauFBer7m5M1bRGfshXA7tdhtEaWzgEUgyHMFD5lr4OP9R2AsoXLRJIGoxQr6CwB51wev3UCcUitxJN7pASEiAOyiLICsVQyvMev+xUVHrfzLeKIDBuNqAw6AWAaGBj201ImsgGruXzUAxLi0kXinJgBqgeFfkgsYAZC1oqrNIWqhJZhQdsW1UKtZANkFmnWZ0tIVrcSIops00AAoYwGkwU8EPQNxtXA7tdhnAGSvq7cASI8VO2YiVz4PAGUtjGznGFZ4x8ECoOh8ZR4weAB4dmebEAAH42rhhrXCzSWM0BcEQH1bEAB92HgA2Geqh0eZuaS4sNrTO7uIDsbVwk8PHSQuKQRA1sIhA4CDrgSDJ/uOEtdqoAFwPoRnAeRZAa/troMZeyFMp5R4LLJarjYRAD7MyIPxRIcu9y9OzHfTCuBiZMuiAUBaxhIq4UF6PtfiKQOBCM4sAPa6Qh1oK6A31r+/VADUo5ciAKStfzwLoBYAqlkAr1uqSPmXxQCA74fXc3uG8+BPDciuRClFodHa76sLWMsSKGMBVIM8GspEn8PrwntfzcLH+z8PBEUuYPbcZcIL9FgAz0coWehd0U1C618QAOW3IAD6sOFEdCW6ym3SvpVcQjJM1cCCt4DOZuXADWsF9KoAoB4InLEXwr09J6QAcD4gcKEBUASBWGqHzrQWLbbsOGH3AxqG+k1KAW+0dMkCIAYw304tJpNXIGMAeQAo4wYWQSBePzYLmH1Aum6pcrv+i9UFHOgkED1xgL2xDcT6528AvBjZQkInFgsAntIAQB4EiuBs1FINk0nlXscAylj+9AAgC2BaFkIW2s5TAKgGdWoWP97rIgugSLyxAJ5XAcCe2AaYTinxSAoJxgB6twUB0IdNBIBD5hrSYUIrhocNph+Jd5JSHP4AwCFzDTzOOgZTtjIPAOw31T/TADjosrKyADjIXIeReCd8vP8IDJud5PrJBtyLAHDGXghTtjI36x8LgKL6VpNJ5TAQV7toAfBqtFIfbcLq0JUNTIMgAiCbHYw6/jjrGPQzAKgHBFkAnA8IDJQF0FsX8HRKCUzZytwstzQAyi7OPADsiVVaBWI5lTk33eJzAeuJAUTBmoB4v3sLgDIuV29jAGXgjQVAGbgUgZ4I/vwNgCIrIAuA5yNaYTqlBHpjGzxqAqoBIM/6F6wDqGxBAPRhEwFgn0npMoEWKj3JIL2xDfBk31GYsDrcAFALAnkAyGYFs/GAPAD0NwgGCgDp88DrKeoMomVtYV3AfSbF+tcd08id5NTcv3QA85lFDIB43dTcwDwARF2+4rouvBIxfaZ6mLEXwk1bqdeuYB4A+hsC5wsA8ThlAFDWAjgQV0syf7t0AKBMDcCLkUrbtClbmYc1+1kAQFEmMAtxYwmVMGF1+JQE4k8LoJYbVs1ix7MA+sPyF0gA7I5phDv2IjgfMVf7z1sXcBAAlS0IgD5sIgDsjVW6e9xOLdZ8iueV1Bi1VJOODJdVAFANAum/B+NqYSyhEj45kA2jlmopAPQXCHoLgDK/rwWAQ2al9tx0Sgm3O4isFZDOAr7qsv7dtJWqWv9EADgQVwuTSeVuE1cgAfAHkU5hMsEnB7JhIK7WKysgC4AsBF7bXUfiU2kIlHUJiwDQnyDoLQBqHQO+rwaAWjpJQ2BPrFJHdNjs9BgrEQDSOqsFgJejmuHTl14h1jEaAAOpuyIXsFY9QFFJmCtRzXB/73G4FNmyaABQBIRakMgCIA8Y1SyOajGI8w2AvBjA8xGtZD1l28J54/4NuoCVLQiAPmw0ALJP7f2mehIzw4NA3mTOxgKOJVS6WQBlXcE8IMTMKcyClQVAXyEQF3N/W/5QemMbIMPY6AGAQ2bFDT9jL/QoD8NbjDHmkrfg0gB4bXcdsf7xAFAr+YMOYF7MAHg1WqlxeG/PCd1WQBkApBNC2HF41gFQFhC1AJAHgbwHxylbGdxKLvEYJ29dwOziPBLvhPt7jxO9puOvAg2AeiyAMhA4aqmG8USHTwCoBYEXdrV6BYBasYA8AORZDNUAUvZYZAGQ94DM6hjWRVWzAPaZ6uF2arGH/gUB0LctCIA+bCwAshA4nVJCEjpkIJBeKIfMSokR3gInA4E8V/BgXC1M2coIBMoCoC8Q6A8ApH+fPa4eDgAOmWvgQXo+SX5R6xFMX9fumEZVAOyOaYRHmbkwYXW4TZY86x+9WNIBzHfsRWQCW+wA2BurJIMgrIgAkAeBV1yWDjUA7DMpLfluJZd4QI8WAHbHNKoCoD9A0FcA7GP+z4oMAGpB4JBZifFFa6A3AMiDIdThS5EtpGsOr5zRYgBAkRVQLwQiuN1OLVaNF/QVAH2xAKpZBWlhy8CIIFDkXvYXAMo8ZIjG770d7XBmZxtc2KVUTbjq0md/wF/QBaxsQQD0YcOJ6OiKJshfeZJI7op2yF3RDoWrOqBuXSf5W02OuYR+rW5dp9t+RXJcUgpWKVKzthPq13XC8ZUnYeuKlyF3RTt5z9+Su6Id8lfOz75x/1tXvOx2fo7VndC2sZP8zbsWvOsoGpfDIa2QvbwN8leehI5NyngeXd4G2ZQcDml1k0McKQ3tgMJVHfBySIub7DPWBWwRPby8kegeT+rXdUJpaAccc50zitp3jq1oJ9dES++PrzwJbRs7hWMiktwV7bB5+X445tKv+RA8l/na/9HlbbB5+X5yj2idL0/o8aEFx+mQSx/x72yBsPqLcmxFO7Rt7IRs175QFoPuHjDWc+8zWkTnJZLs5W1EF0XXylc5HNIKG5enwyHX782H4PmL3lfTBdn9hy3PItdM9rxFwhu7/cYmOGBshtwV7VCzttNN70RywNisKfuNTbDf2AQZL9YEATDQB/AsbzgRPbd0Ayx7bhNXnn9uCzz/3Bbh+1qi9n18zxfBY/fHvnjiz2MV7f+5pRukP6t2jN6Og6/ff27phoAtosuWhj2T4466O5/7XwiZ73PgjYMenX1h2TbVzwRSd9XmXX+IL/e7lsz3sS+ELMQ5+Drvah1/EACDm9cbTkSvb26Gt7d2cOXb205Cn6ke3tl2Et7e2gFvacibW+b+//pmZR9D5hryfVre2XaSK98WyLvb3eWdbSchxVgDF3Yp5nb2fTV5b0c7+Q79Lyt4Trz3ZEV0DN/edhLe2toBlhClKvyw2Qmnw9uEn6WvDX296GuKx0tL56ZOuBrdBBcjW+CNLR3wxhZlbF4LU6RzU6ebdLikfeOcXI5qhre2dkDLBsU62bJhTurWNQdsEf2rsGaP833TdY4oFyOVMhl43q9vdn+fFvw+Xhf8W03n396q6MdgXC18m6PnPHlzSwfEhZTAG1u0Pysj7D309ta5MaZ1hHe/efN7eH/Hh5SRa6D2WfYzGJpA6ys7Pq9v7oD2jYpO4uuos7TuvhrW6aHDnZs64b0d7dAb2wCdLl1uo2Qx6G7zhmbuvYbSsUksvPNFwXPtjmmEN7d0wKthnX6Vjk2dELO8ANo3Kn+/FtZB/vWX4Dn4c594nK+GKdcoZnkB0R81YT/Dmys7qOuO49e4fm7eZPWPnUNpaVrvKY0cca5deN1dbFsQAH3YeDGAPJmxF8KE1SEs88AKxgNiN4UH6fluLeJkYwG1ysP0m+ohy9gEd+xF8DAjjySH+CpsDGBXdJNb8WlRQgcvxk8kA67j741tgKPL22A2KweuW6q4dQB5MYC8OEC29AaOQ5+pHp7sO0oSRTC+io6dEWUBn4tohavRTXA3rYCUl2BjVwIdAyjKSkfpN9WTDjVXVeIA6XhAjHXixb3ydL7PVA+TSeUeSSG+xgCK4gL7TJ6xeWz8HtYyxL97XMldvO/w9qcW04dxkjIxgKzctJXCg/R8ckzYNYguDYM6StewFAX782K0LkUqhZ8H4mpVA+8Dqbund9arFhPWGwuIr2Eh6GGzE26nFnvEsvkaD+htEoiemMDzEa1wOrzNbW7yx74vua6TTAyg2jVh66WyiXPnXfMmluVB/WP1UBQHeCq83S3+7/0dc/+iBGMAgwDo0yYLgFiOhLdAqIEgLkDXdtfBTw8dJN0TtCCQhUERDNFJIDdtpfDx/iMwmVSuC8REAEeXacGkFn/AJS1jCZVwN60ADoe0uiW6yMCfWjYwDYH9JqWm47XddR6B9iwAijKBbyWXwLXddW6T17MEgN0xjTCdUkLaZWnBnxYAqkHgTVsp3N97XBOmEAC7vABAWUHQ5UGfv/bPAqBaAkxvbANMJpXDo8xcj+oCouLQ3gLgsNkJjzJzPQo/s/obyDaGsgAoWxcQBQHwclQz3EougVFLtU/wx0LgfAMgJmnI7F+mbI1sEsilSM9+yFoAKOoKcjW6CW7aSt2gUA8AqtX/CwLg3BYEQB82WQDsMykp7FO2Mk3LAD2p0+20rluq4OnBwzAQVysFgTKWQATA3tgG0jHjYUYeadXlD0jDc/In+I3EO+HenhPwOOsYDJlrIMuoLNIi+ONdDx4A0tcf//8oM5f0+8UF9kpUs9uCKnqyvbCrFXpjG2DGXkiemnkTViCL6V6KqpaqUdlnUopfD8bVSkEgAiDbJk4GAqdTSjQhkAZA2dIx3gLgfAJmurGBXF8eALIW0tmsHLi2u06YGUxbAHkAiBaiK8yiTevwlahm+ORANvSZ6j2y2VndDeTDy5mIOqm2Yt4CIF63e3tOQJ+p3mcrIP5LA6BM1vB8AqAv+8fwIRb6ZABQVDkBx+VuWgFciWqGM64SMTQA0vOoHgik4e/9He3wzvYgAAYB0IdNDQDZiXwgrhYeZx2DQQ7A8eCPraWGZWV4lkReCQoZCKQBkAasCavSN/f+3uNuhaPZkjILCYBD5hoYNjvhjr0IPt5/BG4ll8CQucatDIys5Y+Fv36TZyFivN6Ps46RRZF1r7HWFF5JjbtpBdAb2+A2cZ0OX7wASLu+WXhDvcD3ZAFQBIEiyzdCIFpeRQC4x1gnbQH0BhLnGwBZFzDv+PC1KVuZB/yxISO8LiE0AKpZAWlAmUwqhxl7oZuLTvTw8qwAoB4IPOdynyKo9JnqSZs4X1zA+DcC4DlJQPMGEhcKANECqAf8RJZAlClbGVy3VMGp8HY3AGRF1hKIAPheEAA9tiAA+rDxCkGrPcnfsFbAjL1Q1RXMAiC60XB/WNyY/b43ENhncrcAsj2Ep2xlBATHEiqFblyELG8AcID5lwd+o5ZqmLEXwsf7j8Dt1GIYNs/FKiIA9rsgW6/lTzQW44kO+Omhg3Btd50uAKQntWGzE24ll3hYUdhJK5CLKAIgDWkssNF1AZ/sOwrjiQ6hyxGFBUBvIPCmrRQeZeZyrd6sC9hbCyDecyIAVANMX62ONADS503/v9+keA8QhnnXih0rWQDkQSDWfsSkJ5Hu4gIbSBfwWQoARSBIF2GXjQVEAKRrAeLDJ2vx90ZYAPTWCohzjTcAKHJPewOAvl4P+tqPWqrhVnIJXIxsgfd3zAEgDwJZAGQhUMsNHHQBBwHQp02PC7g3Vokne5iRB6OWalXwo7sp0HFUuI9PDmRz3cl6IVAEgAMMgN2wVsDDjDyYzcqBW8klMBLvlI7p89YCOGx2wpStDB5l5sLjrGNwK7nEDfx4AEifmyz88QBwyFwD/3L4ZRg2O6E3toEsoLjAiiwp9ITWFd0ED9Lz3fpyLmYAVBMa4IbMNfD04GHod0GYHgD0BgInrA54su8oDJudHgCoxwLojWgBoK/CAiALf9d218G9PSfgbloBsVKrwZ+vAHglqpmEPKAeszC1mGIAz0XUqsaTsRZBOuFAFgBpwJmwOmDKVuaVpUsNAH0REcAtpAXQVwBEuba7Du6mFcDlKMVNfiq83aNLiK9WwCAAum9BAPRh0wOAKCPxSnC1Gvzxuilgz0+EqZ8eOgjjie6ZxaKOBCIYQgDsUQFAWkYt1XA7tRhms3LgUWYu3E4thvFEBxfMtACQtRoOmWvguqUKbiWXENi8m1bgYXmkLYYDOgFQFv5+euggjCVUkmPHBbSXWmTpmCreZIagLGoLR09Yi80FrCWYqEFbB3kAeGGX0sC9i0oO0RMPiCA0Eu+Ex1nH3DLpAwmAalZDfF/mdR4AogybnTCblQM3baVuc4UWALJuYBYA1dzAYwmVMJuVQ+YdXkY77Qo+HR7Yh5d/iKkUuhJFICiyBooAEN9D0LqVXALjiQ6fIJAGQG8tcDKAxgNANauhGlCyr5/d2eZXAOw3zbnZ8brzAFD0IO1NLGDQBRwEQJ82GgB5Ll86todeMKZTSuCmrZQbxK3WToue+IfNTunMYBEE9pnqyQKkVi6G56IdtVQTEEAgvLfnBEynlMBkUjmMJzpg1FJNfmsk3gkj8U4YtVTDWEIlTFgdMJlUDnfTCoiV72FGHkynlKgmoLDH1x3T6OYCpmFPBH+8seozKUkkTw8edmvfxwJgLzVeWKaHdWcMxNXCjL2QTPaiJ1ictBYjANJt8Vj3cG9sA3y8/wiMJVRKASDbKs4bCByIq4UH6fkwYy8kGdmyAOitq1YNAOnEDX9YAOnX0eqJ9zYv3o83NloASIcwsO2/emMb4NOXXiH6zgNAnhUwkAD4z2lHuElYtEuYhj3ZsjCsBZCGnCtRSqu465YqryFQDwB6C4jeAqCsiABQDQjZa4n/7zMplRZ6YhvcrjkCoGgOpbOCEfhEbmCeKzgIgEEA9GnDiag71uERw6P21N5nUlzBw2anEP4QAC8JALA3tgFG4p3wL4df9hoCZQCQThjRyswdT3TATVsp3LEXwb09J0j9whl7ITzKzIWHGXnwID0f7u89DjP2QriVXAITVoeUS1l0XDQA+uL2RfibspV5WFZoFzC72LIQiK5fLNQriklajADYK/iXBxhohaZrA9KQgQudqFewXgjE+wbjUofNTukyMGrWOm8A0F/CAuBgXC3c33sc7u89DgOU9VzL6qcGgJilydZupCGwK7oJZrNy3CxbMgAY6F7AP049BiPxTu5DmFqJES0AxEQtXoICQuAde5HXEMgCoBrkeQtrOMfMh3Xxkusa+cMCiPDXZ6r3GDsRAGq5gmXLwrwfXh8EwEAfwLO84UT0YdIJVeDjTdxD5hp4mJEHfaZ64eKIAMjbBw2B6LLUC4G9sQ1kAVLLopW1CuqNAVRzN7OuXi0A7OMAoMglTo8VDX+0VZYeB4zpEy24WBrmclQzcf2KFlDeBLZYAJAFMTWw6I5pJGVJeLGAWgDoTUwgjtewWSkDdDik1Wu4k7EKLlQSSG+sUt/vcdYxuGGt0JxLRNeNHR81AKRBEAtL0zCjBoD0ghtIAOyKroLHWceIxVkLAmWLQ2sBIA2BYwmVuiGQB4A8EJR1x+oFQC3oFB0P/Z63AEhfRx780SBOA6DWHEqXhFGzAiIEntnZBhO240EADPQBPMsbTkT/15ZPEgb0BGrfsFbAHXuRxwKLn6PrAKpZTBAC2W4jajDIA0CtwtFaQMgTPEYZYKTj97R+EwFPBIBq8Mez/E0mlXPHqzumURUA6c+NJVSSzgGyMUnnI1rh9M6FfxKVjQFkwY+29HXHNMKD9HyYTinxgEB0AXsDgGpASMPpyyEtcG/PCZhMKvdbcWYRAMrCHv05te/0uu7vl0NaiGsbE7P0zCNqHgR0ASMA0hCInxmJd8LTg4ehJ7bBw/q32AHwexG1MJ1SQhIz1AAW63Cek4BANQBkIXA6RfFiyEAgflcNALXgzBsAlHUj05+jj4N9HSHZWwvg5ahm6DMpMX8YcsDTu9PhbUILoFY8oJoV8HR4G/TENsA/px0JAmCgD+BZ3nAi+sdYBynNojZps6UzemKVIsHjiQ7uwocAqLU49pmU5IVPX3oFbiWXeHS2EFkDe1wA2B3TKHSfiqBMy4LHA0DWoieyJMqCJ8aCsQAoC39YXHvC6lCFbARANWgZMtfAo8xc6KEmNHZS47mkLuxqhQ8SihYdAPJggi6CTZeG+fSlV+C6pcrN+sQCoAgC9QIgytXoJthjrIOe2AaSmHTDWuFm4aXvARbGeK/xLHS0BZC1RHprBex36d7t1GLIXt4GgxrgJ9JNvH68OEs1AMT3r+2uI9nuOLZa7tPF5AI+F6F4AJ7sOwp9pnoPAGSP398AiDAzZSuDW8klbvGIvM+inI/QBkAeNNH/akEdawHkwaWsxZEHgd4C4OWoZhiJd8LdtALycC2SU+HtcC7Cfa4UQaBWYWgaAs9FtMLDjDz4QaQzCICBPoBnecOJ6O+jqmEyqZyAhFrsFCt9Jvd4QD0AyC4+g3G18GTfUbi3gvHX+wAAIABJREFU5wS3gK43AKhmFZQp58ICoF5XsGwMIJ6fjBWw36TEkv3L4ZdJSR61hZa1ALLg0m+qh9msHBgy1xD44VkEeJNcn6l+UQEgD/q0BOMBB13jIQJAb0FQDQAR0AbjauGOvQhms3JgylZGLNw8y5sI2tj3WADkQR/vPlQDv/FEBzzMyIP7e4/Dtd115P4TnadWzJ9obqHLwFyOava4/r2xDfDJgWyYTCp3+47IeiZacAMNgFdcQIEll2SOX8sVrAWAPAgcS6iEGXshdMc0akLQhV2tkGx0SgGgmmVRza2LCRJqkHeR8zsyFkIaAOksaS25EtVMvF64tqnNjQhramNIv3dGAgLP7GyD8USlnE8gShgtti0IgD5sNAD2meqJG0cG/GgZjKuFR5m5cG13ndt32SQQeqFkLXu4yGDtsCf7jsKQuUYaANWSKNQsdmw5F1EMoCwwaonIAiiCPxYEB+KUQPtPDmTDkLlGarG96Jq8eOOArgzaisvGBYpAEDMKvxdRG1AAFMEDHSfGS/SggWIsodKtPiANgCL3oy8QSAMgDW4DcbWkgPSMvRBGLdUeFnGeS1kEgDjuImufyLpI33PDZiexUt6xFxG9wxhABDJWB7XgT831qwaAPbENpKA8D/qvUIAgAkCEwEAD4GXXGN1NK3CrXygLgDwIRAAUlYkRgeBgXC15+FYDNxkXsAwA8sCLtgCe3dnmAXlqsX4ygIlCA6DMcV2NboI79iKYTCrnhsiILIBqMYDs2IlqVdJy1ZXwdGFXazALGIIA6NPGWlGGzDVwx15EJm4Z+MOFb9RSDQ/S8wmY8QCQZ/njuTf7TUrfUIwL5L3PA0CeFY1nnaP/RvjD14bMNW6Cixq+p/av6DfUYgVpAKRf58lIvBM+OZBNsixFYMAusiwA0uNwx14EN22l3IUZ4Uc0iU5YHTBkrgloDODfuwBQlCDAE541rye2AaZsZW7uOJEF0BsI1AJA+jOox9hB5lFmLsnapMccLfAiqyBaAGlAVANB+u+ReKULzKPMXHiQng8TVgexyuPxigBQr9WPvp7s+LEA2B3TCDP2QniYkcedo+jvykBgIDIp2ULQlyJbiCu4N7ZBEwBFrl8aAE+Ft2vCHw8Ce2LnwnpEXUNYAPQmjg7BSwSBOD48yBPNR3ogVA0A2e/iQ/eQuUbT6kePHQuAPAjkjR9rpUY573L99pnq4XR4WxAAIQiAPm08N9oNa4VbqywZ+KO/i71jcYG4yACgTOwSyrDZCR/vP0KAh30fAfBqdJNHljANUzyrHwtuLPjRANhnqhe+zxNZS6AIAFkQHIirhVvJJfAvh1+GyaRyYhUUWXNogO+KbiIAyI7ZTVspzNgLudDYw+yD7RhybXcd3LSVwqXIFjgTURewRfSDhCKh1U8L/liQ64lV4vEeZeZCV3STLhewXksgAiDWsBO5TntjG0jM3R17ESlDRNebFCWQyJSBQb2j62JiTcwb1gqP+44+tssaFkBfLH8IcDQAdsc0wq3kEgJKsvu4RC3KLAQGEgDPRtS5AcWw2QkPM/LIw4e3wgKgFgTyXJ0TVgcxBrAAJeMCvsj8K/q/yAXMA0Ae0OkBQfq3ZQCwK7oJJpPKSaKjDPihnp2L0AZA3tjR4M/GBmInF4wHDAJgEAB92nAi+kGkk0ygaBWi46FkF7leF1TgxCEqBC0Df7RL+HZqMTw9eBjGE92tgSwA0sCEoEWDlQwAsjDoDQDqgcCeWHEvYFyYP95/hNSOo13CWgDIcwHjInnDWgH39pyQXrDpBRXdIRhzFUgA/Oe0IzAQV6sKfTLwR+v13bQCUgibhgot8OMBpUhkABDdnazVfDCuFiasDridWgz39x4n9SnvphXAHXsR3EpWMkuxePmE1UEKl9+0lcLt1GK4m1YAD9LziYVvxl4Ik0nlRMe07ks1F7AWCGpdQ54LuDtGKduDFlr6eqvFd+LDiwgCA2m9xl7ANIhhIXrWAigS3ufO6ARAEQz2m+qJa5q2BsoA4PmIVo996rEU0jGA8yFqAIhWv3t7TnDL5MhcR9YCiA8csqV8aF09F9EKfaZ6eJSZq+isqxRMEACDAOjTxgPA7hgloQItQ95YOaZTSmA6pYRYn3iLmJZVggWckXgnPNl3FB5l5sKw2SlMApGJ1eOBnowFUPQdtX15C4BD5hq4m1YAPz10EKZsZW4WQVFmsGgBpi2APbENMJ7oIPWr6PFUG1d6ob1pK4XBuNq5gOoAAuA/xjrg/t7jxFIpC4BaDzcIUfQ9IAsxMveKDACq3S9sSaSBOKX/9HVLFbEUjCVUkuLmU7YymLKVwQ1rBYwlVMJIvJM8IGllm4tECwBlLIJaIHhhVytciWqGyaRy+ORAthv86REEGHaxvZ5YEDDdPcMAIN6njzJzYSCuVhUC1d7jAaAsBPKsgeOJDribVgADrnteBgD9AWg8FzObKe1vAEQr8+3UYjernyz40eOiFQOoBYAoV6ObSL1IOhs4CIBBAPRpw4moMLQZyr7Z4SYtGzqhaX2n22sVq+XEsboT3tzSATVrO6FwlfvrWlK1Zk54770W1gGnwtuhbl0nVKzugB0rXoGK1R3gXNNJpGat/wR/25/7rFk7d6wVqzsgfMVRqGKO/+2tHfDu9pNQt055rUogvGvIjkfhqg4oDVX+X7VG2XfVmk4oDdU3rhWrlTHt2KR8t9gleSubA7aIFoY2w6thnVC/TtHV0lBPYXVbRkpDO+DNLcp9oHY9RN/Xuo5l31R0F8dFdI+Ixl1G8Fh82YearpWGzt1/Wve1rH6x17FwlXL8p8LbwUmdkzdjizpbuEqRsm92wF+FBU5381Y2Q8Gqk0TwuJxrlPmTPlae0N+lJX/lSchd0e6xb/o39EhxqDIGb23tgPp1ypy+dcXLcHzlSTIH4Of8JcdXnoTjK0/6fb94TsdXnoRtKw5Bwaq5c6hY3QFvbe2ApvWdmtdeZlxyV7RD/krP8TnOeU00NsWhHdCxqRPaN3a6jW3uinbIXh4EwCAA+rDhRLR0yTp4bumGZ1aWPbcp4Mfgm6x7ps9j6ZJ1AVtEad2dr+u37LlNz+zYPOsy39d9sejusyfP8rH/ZZxDIHR3sW1BAPRhw4mocX0ztG/s5Mqp8HZ4a2sH+btjUyd5ItGSlg2d8MaWDrgY2QKvhnVC5yZ1eTVMXl4L64BXwzohPqSMuHje2XYS3tjSAa9vdpc3tngvna7z9XU/KOxxvRbWASnGGug31cOp8Hby3mthnsK7DqJr2UFJ0/pOeH9HO5wOb5MeO1rw/M/u9Px+y4ZOqFkbOCtK3bpmaNmgHAvqWdtGseBxa32maX0nNK5XruU7205Cb2wDvLGlw+266rkX2OvZtrETopcfh5YNyt/e3gdqgufjz32y+49ZXgAdm9R1UU03RdK5qROuRDXDezvayfjKjJ2MdGzqhEuRLdCxqROcAdTdqjXNUL+ukyuN6xWL24VdrUQXaWE/X+eSespjgPtR+w1vpH5dJ0Quz4O3typzO1rKm9b7T+rWKZ6QRj/uEwX1KdnohLM728j9Tos314QV9ByJrr/aeDSt74T3digt39jjqXddm/LVC6+7i21bdAB4//59yMnJgbCwMDAYDDAxMeH2/p///Gf4zne+A2FhYfDiiy/Cvn374F//9V/dPvP111/DyZMnYe3atRASEgK5ubnwy1/+0u0zX331FVRWVsKqVatg1apVUFlZCb/5zW90HStORBd21Qjjo/pNSn1AtsafWikHfB+TBm4ll8C9PSegnxOnxsY5qRU/ZjN9+031kGFsJIkin770CjzZdxSmbGUwbHbqTtzgCR6XP/aFMmx2wg1rBcxm5cBsVg5kL2+DYbOTlKXhZQKLikOLEkHomMvrliq4lVxCEmdEsVevb8uB+OXbIXRpCBgMBmjZfAh6XPuYsRfC/9ldAzlrrRC6NASWfWMpRBnD4Fs7iuD7u2rIRLTQuvv9XTUkxm/IXAP39pzwiAfUShLgxQeyfawnk8rh6cHDpGWi1r2gFWfYxcQAyui/VrFzVvAY9H5Pqwg5Sld0E+kFjLolShjREyPYb6qHx1nH4P7e46ROnihJBOWvt+aCmdLdps2H3RODohrh6JokCF0aAs9/YymYV2yAd3YUwTmqhuVC6+7pnfVu8WFsHNhlV33AG9YKjxg00fcwC5guBC2TRKInNvB8hBIDeD6iFXpjlfJJM/ZCGEuohO6YuULyvggmTPhjX7QOYWmlG9YKyDDOHaveeEKt+D9RGRitsUAZiFOaIlx1xdGzv3E+QBnsi21bdAD44x//GN555x348MMPuQB49uxZWLlyJXz44Yfw+eefQ2lpKYSFhcHvf/978pmWlhbYsmUL3LlzBz777DM4cOAAJCQkwJ/+9CfymezsbDCbzfDRRx/BRx99BGazGXJycnQdKw8AeYvVYFwtaRWnFbxNT+QIgH2merhhrYCHGXluxZXpxUEWAOlkDwRAuk4fgtXTg4fhYUYe3LBWwEi89zDoLwAcNivZmA/S8+HpwcMEVPtM9ZBlbHIrV6MHANUgkM7ik8liPbklG46sSYTmzQcJAPbGKqVRRi3VcGJdCry4ZBk0bz4I3w4vhOSVERC6NARO73SQiWihdfd7EbVusDeZVA7TKSW6kwRY/WcBsDe2Aa5bqkhtSl8gkE4CwTIt/gQ/FDqpyxcRFSWnAVA2eUQLBofNTtISEmviXWEKQfOkfUs2ZK+xQmPYIQKAtF7kr0uFF5csgzfDM+GHlpeJ7v5deGXAdJcGQFECQFd0EzzKzIVRS7UQAtnvn3N1ldD6PA861YCQBUA6CaQruglG4pWC4bdTi+G6pYpkisvKZer/mCih5/s86Y5R+kVPp5TAjL0QJqxKwXtsZ4egrdY9xFsYRACUqd1IX/M+U71HTUh+lnEQABcdANIbC4B//vOfYdOmTXD27Fny2tdffw2hoaHQ3d0NAAC//e1vYdmyZfDBBx+Qz/zqV7+CJUuWwPT0NAAA/OxnPwODwQCPHz8mn5mdnQWDwQA///nPpY+PBUA1qMObu5ez2PEAsJcCQAS8UUs1mczoBcEb+OMBIJ3lOxLvhJu2UnicdQyeHjwMj7OOwXRKCYwlVMKw2UmEB2r0/3kAKPou+xm0vCGQfrz/CIEpzBDGLGBRuzq9FkC6VMjDjDyYTConE7SeLFaDwQCtWw7CTVspTFgd8A/RDbBqqRFOrEuhIKkOjEueh+L1aWAwGOCLL75YcN39nqudFm3Ju2MvItDrDQD2xIqLmA/G1cInB7I9emfLXlu8N7pjGj1qWPoL/PwNgKh3rA5eZQBQNotY5AW4Ya2Afzn8MowlVJJrSmewy2T/dkU3eQDg/45qhFVLjVC60UYKSF+KrAfjkuehcN2egOmuDABiZupsVg4MxtW6AQfvO5cYAJS1HMpmuF4UACBtaeuNbYCxhEq4Yy8i5YWGzDXEKICledQEj08P7GG/8wFXmST8feyxTf/uORcA0sfubxBkW8HJwF93jFIQHLPA1QAwECWMFtv2TAHgv/3bv4HBYIDPPvvM7XN5eXlQXV0NAAAzMzNgMBjgq6++cvuMxWKBd999FwAAfvjDH0JoaKjH74WGhkJ/f7/weL7++mv43e9+R+SXv/ylNAD2uG7qW8klwkWOrQlIAyAKDSa8xUJmIUQ46hMAIFvbbyRecbliCzV0Fd/bcwJu2kphPNEBo5ZqNzBEwWPivYcyEu+EsYRKmLKVwd20AgKds1k58CA9n9Rk45WGUasDKOOa4y2w1y1VMJuVA6OWauh1lTJgAVALVAwGA7wdkQmTSeXQE9sAp3aWKq/tOOH2OcuKHZC8chcYDAaYnJxccN1lARDP8/7e4zAS7/TK+qcGgAg79/ceJ+0KZSCQ/j5+lu5i40/w8wcA9sY2aAKhCAD1lJLpc50v296QV8JICwBx/FkA/LvwMjAYDHAtKZOAQFd0E8Qv3wG2FYHTXRkARKjriW2Ax1nH4Npuz9IxrIVODQDVXMLeAiANfzwgGzLXkILKM/ZCuJVcAuOJShchLOfl5q6PbiLHJCrn1B3TSB50xxIqSVF7tPKNxDvJGiQCTLuxlpS6kXUl64FABEBZVzyWexk2OzXhLwiAyvZMAeCjR4/AYDDAr371K7fPNTY2wuHDhwEA4Ec/+hE8//zzHvs6dOgQNDU1AQDA6dOnISoqyuMzUVFRcObMGeHxfOc73wGDweAhWgBIL2JYV4xd5NhFUgSAuFjcsReR2lJ64E8PAPJgEIEQC+k+SM+HJ/uOwqcvvQKfvvQKfHIgG57sOwqzWTnwMCOP1DS8v/c4PEjPh4cZeTCblQNP9h0lMPnpS6/Ax/uPkJZdN6wVXAsh77j8CYD9pnqYTimBB+n5bq52EQCqQaDBYIBv7Uonn3lje55SvHZXhdvnMkJjIdq4GQwGA/T19S247rIuYLr7xcOMPNUi0SL40wJA2mL100MHYTKpXGgN5H0PQyl4AOgP8EP94QEg6pVay0HZ47ga3UTuP5nQBJ6MWqrh6cHDMGMvhH5Tvcf1YwFQBIH0uLIA+Dfbc8FgMMCVmBK3z6UHWHdZANQCrz6TEhvZb6oXwh92T6EBUAQosvFoagDIAz8WAmlBfceH8lvJJQQMZ+yFcMdeBLdTi0nxcpx/b6cWe3wOi2aPWqrJAw/7e2oWRhoAWTe0P2CQBUA1uRrdRB7aZeAvCIDK9kwC4Jdffun2uYaGBnjllVcAQAyABw8ehObmZgBQJqLo6GiPz0RGRsJ3v/td4fGInkR/EOmUAkBcIG9YK2DKVkbggF3oaAsgG0dFL4QTVgc8yswlPU71uMFYANQqAK3lrkVL3nVLFYwnOsg5YjHdW8klpKAutsu7bqmCkXixO1mmGLQIANUWZ55gG6nplBKykMoAIA/kxxMdxAWMryMAntvl3iYwPTQGYkPUF9H51F2eBRDh7truOniYkUesVVoASOuzCABZmBsy18DjrGPwKDPXDbpFOo/jxQKgrzDGwh8CYI/r3lBrM+gtaGoBoBoEXtutFJt/evAwjCVUCgHaVwDsiW2ArvhMV+HlSrfP7V0VCzEaADifuqsXAC9GtpAEmX5TvRts0EDCWgD9CYGXIud6AbMxeghcNHxpFWfv4tyDGDuID3KoG3h/8sZcr4gAUBSb6A0IygLg1egmsg7yXPwiCQLgMwaAgXYBsxvGonRFV0kDIA8C2YWRtgCqASAuoPf3Hoc79iIS18cT1iXFAiC+5i0EzlcSiJZlUg8AigB5ylYGs1k5cN1SxY2z0gJAGnzwqRuTQHDMA+0CFunu93fVqC40GHLQpwKBtF7TAHhRAwBpqJuylcHTg4fhpq3UA8DRXcXqMwIgApE/rH6yAChjCfQHANIgiP8fT3TA04OH4d6eE3Btd52HvmoBIA8CeQDYHdMI9/acgKsm5eHlre0Fbp9bKBewSHfVAFANCNESiJ05WBBRswDqhUAaYBA0L0a2kC4alyUhT6/g+c/HvmkA1LJg+gKBp8OVBBC1RBGM77xuqZIGvyAAzm3PFABiEsi5c+fIa//zP//DTQIZHR0ln/nyyy+5wchPnjwhn3n8+LHXwcj/nHaELFR6IHDCOucOpidvPQCIC8NkUjk8yswl/X5l3MAIgOwiJ9OHVxbgaEuPP8HPHwA4Eq9Y/e7Yi8hCqgaAIvckCrpkemIbPABwLgkklUDT/47mJ4EspO7SZWBEMmx2ktZ3CAs89y8NgbIASOvyYFwtPEjPh08OZBOrtii8gQZAf4OfLADKWJxlAFAmgQut1LNZOfDJgWyPRDA9AChjAWzZfAjuphXAhNVBkkCOr0slDwuXo/hJIAupu7wYQJEljgXC3tgG0hYTrdUIIjwA5EGKFgTy3Mu4HwRAf4MZjicdF3eV876vFsALu+YAsCtaOynFGxA8s3MOANnrTsd1jsQ7yeuy8BcEQGVbdAD4hz/8AZ4+fQpPnz4Fg8EAFy9ehKdPn8IvfvELAFDKwISGhsL4+Dh8/vnnUF5ezi0Ds3XrVvjJT34Cn332Gbz00kvccgQWiwVmZ2dhdnYW4uPjvS5HMGJRmsNrJQaIYgJ5bkcWAFlI5LmFhsxKHbf7e4+Tfr9qLjARAKqBIA/O/AWAstBHl3vpjmn0AEAt9+9gXC3csRfBw4w8t4UUY8vYcbjkmkjV4tOmbGUwllgA3wo/Ae/sUPqjFq1Pg3d2FMCZiHLojmmEE+tSwLjkeWgIOwzfDi+ElJW7IHRpCAwnHnMrpbGQuisDgF3RSokKGgLVyrTQAMjGBnbHePa95SXhfLz/CInp4cG7NwDIs9z5CwC9AUFZAMT7+qeHlKxy+mGFtZSyuilrAbwQWQtvbS+At7Yrutu6Ix5+EHMETu2sgK5opQyMccnzULfpFXhnRxEku3T3fzEljBZSd2UBkIU/BIleF0CMJVQSOOEBIA0nLKSouSZ5Gb5XKADUY6GjoU0mIYsFQBnxBQBZ0QuBFznXWgSAlyJb4NruOpJEJuP2PR/R6lFTMAiAixAA7927xw34dTqdADBXCHrTpk3wwgsvQFZWFnz++edu+/jjH/8IJ0+ehDVr1oDRaIScnBz44osv3D7z61//GhwOB6xcuRJWrlwJDofD64KkP4h0kmBbPRCI8IAp/zQE9khYAHmWwH5TPYwlVJJ4tkGVRanPVA/pxgafAVANBLUAULQvBDUR+IkAUAsA0N07ZSsjYKFVZoMGQBYCe2Mb4FayEkz92rajXN1NWxWtBFi7iumuWmqE576xFKKMm+CK6Qj8OHUOABdad2UBkIZAjAlU020tCyAvsYNn1f70pVfgYUYejMQ73UDeHwCoJXoBkL6v9AIgnhf975C5BmbshfDTQwdhxl5I7gutkjDeAOBfbc3h6q59VTR0RSulYGjdjTSGwd9uL4bvUYWgF1p39QAga5FD0OiJbSBVFRBOEABl3ZW8RAMR/OGcbjfWegWAskLHx+mRy1HuNSPnAwBlrYE8ALwc1QzDZic82XcUru2uI9cfXe1BC6C+bdEB4LO00XUAe2Ib4G5aAUzZyqThj14ER+KdMGMvhIG4uUD4rmh+FjA9+YtKwFzbXUfcwreS+SCoBYB6XMIiwWP2ZR+yAKi28N+wVsCjzFy4nVpMFlK1IHsaUlgAxPf6TUo29lhCJRf81Sba7phGGE90wMOMPLgUVb3gE5E3AHg1uokky+C1n08ARKifspXBpy+9QmJ9ru2u8xoAZVy/vlgA9VgBWQBEGTY7icWPBj+ZhxU62F8PAKJ+3997HCasDo/FX7SI0wC40LrriwWQBo2r0U0kM/ZqdBOxFqkBoFYWKw/8ULQAUC+0+RMARb+vFwB9cQvj9TvjstjR1xIbFeC8rJblGwRA7S0IgD5sNADihIsTqB4AxH8H45SOIXQNJjUAVFs46QX0pq0UHmXmwnRKCQyZa55JAFRbpEUAOBhXSyD4jr2I1M0SZVmycC2yAOL53E0rgGGzUxf4oWBR797YBriwq+aZAEBcHIbMNfAoMxeGzDVC/Ua3jiheUkanWT2+Ya2Aj/cfgY/3H4EJq4OEL+hxu+oBOW8BUBYCaQAciFPqsT3KzIVPX3pF14OKNxZAVk/7TPXwID0fxhIqhZafvwQAFLl1r0Q1w2RSOTzMyIOr0U2qAKhlEWThjwXAy1HNixYAZSERAZDNWub97a0l8CwFgAjp9/acgKvRTaoueFmdCHYCCQKgTxuvFVxvbAM8SM+H8UQxBKolEvSb6kkdJzTJ6wFAUTwRWlIeZuTBjL2QxL7JAKAvQEjDrb/hjwZA2ooyZK6B6ZQSYvHjgZ+aNUULAK9bqoi1Vg/44eQ+Eq8E8/eZlKK6318EACiqO8ZbnLpjlG4BGEPpjQVQVqd5CU3XLVVwN60A8leehOmUErhuqZKGroUEQLVjwv3vNzbBreQSUlx9MqkcBuI8s/m14I99oNQDgANxtfAoM5cU/tZj0QkkAJ4Kl08CuRgpttax7sUH6fkkk10WAmkRgZ8IANUsb74A4KV5AsCr0XIWQFkQ1ALAflM9zGblEDe9lvs9CIDyWxAAfdh4AIhP0w8z8khzb1n4oyfxyaRyovB6Fky1gHJceMYTHXB/73G4m1YAL4coMYZ6F7j5BEC9izS2ghtPdMC9PSfgUWYuTNnKiNtbrbSGmrAA2Geqh5u2UphOKXFztanBH8+FOpuVA/2muY4KgQZArQWLtUzgOfeblI4eN6wVHnquZgH0VZ/RBZxlbIIJq4MUFb+bVgDXLVVcHdILf74CoJqMWqrhjr0IHqTnQ/7Kk3A7tZjEOOrRVS3rn1YWcHeM0ucVazCqwZ9oMQ80AMr0iZUFQITArugmmE4pgVvJSk9sPdAicx+JLIDPIgDKPDR6Yw28EqW0m8N4vyFzjVuyiK8AeD4iCIAAQQD0aRMBIMICawmUgT96kRyIqyVdMfRa/9QWT9pFeiikFWbshXA3rQDGEx26AYwGQh4YygKgt785GFcL2cvb4EF6PgEA2vKill0pC4CXo5qh31RP2iTRC60W9NGClj+Ev8WwiGIhaBYC2YmdhT/a4n07tZhAsbcuYNnYVjYLGAFt2KwkYmFXmocZeaSFoLf65S8AHDY7YTKpHB6k55NuOVh6iE0C0aOn3gIgnteEVXkQxKSeZxUAUXyFPwRA3N+t5BJSCF0WYLwBwPkAtIUEQBm90QOBqK/Yj7jHNQfT7vaLAgDUygSmJQiAQQD0aVMDQFwcH6Tnww1rhS74wwUSJ4fbqcXC3r96LIAsBOIiim5NLI1yb88JmEwqh2Gz0+fFD8+HBkRfF9Mb1gpi6btpK4UDxmaum80X+KNBZCCuFm4ll5CG7LTIwh/G/PVxFpPFCIB6LBPdMY2kV/S13XWaLmARAMrEArIAyCaBDMQp2ehs72oMBxhPdMCwWQ4K9QLgoEs/xxLh5k8UAAAgAElEQVQqYTpFgQf8fQRSvKdEWcDzAYCXXQsq/XA6Yy8kVQtk9Fe0UC8mAORBoB74owHw7M42uBLVTDrV3LBWCK2BeuCPBcD5ArTFCIAyENgV3USsftjTVybzOgiA3m1BAPRh0wLA7phGkll301bKnaC1APByVDP0mZS2bzP2QrfuGr5AoGgRRRcV9u+9t+cEzNgL4Ya1witrCp6PtxY+7Hk5Yy+Ehxl58DAjD26nFhNXHy8GULSY8iykIqsTgh/+FsIAa82lF1bRpIdleXpjG7iT3rkALqIyLmCZBaE7ppFkCI9aqv0KgDx97hEAIJvljkA4nqhYEx5l5sInB7LhkwPZpP/03bQCmE4pgSlbGUxYHTCWUEmyja/troOReKXN4ailGsYSKmHC6oDJpHKYTimBu2kF8DAjz60f9uOsY+SeoYFPLQlEC/7Ya8NCn5YFEMdpIE6J3cRENS3401qwFzMAiqx/WlZBOgsYrVG3U4tJ9rvadZGBIBkApMdsMQLgxcgWaQDkXRfa5Yvv98Y2kHm+31RPYgDVxiwIgL5tQQD0YdMCQBoCZ+yFcDu1WBcE4mRBZ57esRfBlK1M04rlLQCy1pTBuFpi0bi/9zg8zMiDB+n5MGMvhJu2UhhPdMCopVrozhUBIP35IXMNjMQ7YTxR6YwyYy+EB+n58CgzFx6k5xPLzZC5xmMxZa0oWpYUGQtgvwu476YVwEi8k8QFIfCx/4oW0KvRTTCZVA739x4nQeUodLZgIAHw/40rc5uQvYE/1HOMC7ybVgCTSeWkzpo3bmAtnaYBkBfeoJUAgg8X44kKzN1OLSb6PZuVA0/2HSVF1Z/sO0oE+xbf33scZuyFcCu5BCasyj2A+kmLTBZwbyy/FZwey5+MC3g80QEP0vOJddNb+KPjtAKdBaxl/ZMp1KwGgHRc35C5BmazcojlVNbqNZ8WQPYexXFdaAugGgSqgTF+fzxRieWdsDrI62d3ureCu8QZN1kARB05FwRAty0IgD5sOBFVrWmG+nWdRBrXu0vT+k5o2dAJp8Pb4O2tHeQ1Lalf1wk1a5XvorRt7IS3t3bA+zvaoW2j53t6pGVDJ0QvPw6N6zuhfaOcdGzqhFfDOuHNLR3w7vaTpFgn3nznI1rhdHgbvLv9JLy9tQNeDZv7/JtbOuDtrcr3sM8jfdOe2dkG7+1oh7e2dsBrYR3QsWnud0XH2LheOQdvz5+Vto2d8O1tJ+G9He3Q7vpMzVplLHhjRI8zrQP16zrh9c0dcHZnGzSt74S6dWKpXNMcsEX0rW2N0LbR89h5uizSb56+v721A97a2gEtG7T1nDcOWnrdtH5Od9n3ZHVZTcc7Ns0dH/6Nond/rO7iccrorta1QRFdW+caZcze3toBZ3a2kd9lhTf2ajqLUhVA3a1a0wxVazo9xElJzVpFnGs8Bd9jpWpNJzhWe54rzgHv7WiHcxGt0LJBfN+oSd26TohYnkPmFdn7So/g+fljPzxdca5RzqHOi/Nnz/m9He1wPqKVzEN4vStWd0CVyjipjS0tPB2pWtMJpasXXncX2xYEQB82nIiWLlkHzy3d8IzKs3zsfxnnsHTJuoAtos+27gYl0BLUXW/lWT72v4xzCITuLrYtCIA+bDgRla5u5j59ip4269Z1wvs72qFzk/qTTdUa5SkIvyOSV8MUq5WeJ9I6l3UxYnkOsRJoWYAC+SRKHw99fHqfRNnPobXqzS0dQquH2pMoO85tGzvhVHi7myWBJxWrO6BidQcUh3ZA8TcDZ0VB3W3fqFgstZ6mZQXPEcf+VLii76h3rMhYm1DwO1q666tO+6K7MsdRpaG7vPPmXQeetG1UPA74OzLWEtZCItJdx+pO6Nyk/EZJAHW3MLQZXgvrgPaNnVD2zQ4iFavn/kURvc6T0lDlvhSdO2tt7NzUCeciWqFzk7rFib6m4SuOQsVq/91vrOC5zNf+y77ZAeErjpLroWVtc6xW3m/Z0AlndrbBW1s73D7Pu87Focp4sXOmmtB6oCY1azvhrzcHLYBBAPRhw4moK7qKG4uhJhiMPZlULowL7IoW9wJm46VGLdUkLo/uIMCLf8O/ZQLpvRU2k1KrMK6MsIkeGEeFmcxaMY90LNlAnNIl5G5aAYwlVHoE3LOFoDFImU7+YGU80QGPMnNhIK7WI15K1Dngwq5WOBtRF7BF9FzEXBzPZFI5KUDOizWSzQimy8DQmbR30wpI+RM2eUFPWRj8brpRyWCViXf1Rt/wXLzVVzbelj2mLkZ3tTLS1eL+8N9+Uz0pXzIS71StAyiKAVTT3ctRzTBqqYabtlK4FNkSUN19P7weLkW2kA5HWjF/3sYA8go80zGzV6ObYDCulsSQYnF0UVzcs5YFzEtI0RMDeDVaST7Cyg3XLVXk82oxpnQnEFECj94kkAu7WqHPpDRbCET91cW2BQHQhw0non9KVhZ9WfhD6TMpvWTvphWQwHY9AMirl4ZdKrBsiQgARYH03i6W87WIaokeAETwm7KVkbqHooxgenFFAGTHB8+tN7aBjCNmb1+JaiaTl6hlFJEA9gLGMjA4Ud+wVsBkUjl3AeMFnYseelgAREjBjOgpW5km2Kglh+gFQG/0G89JD/Cx4KcmNAB6A37s9ZmwKg8g+FDZHdMorAOoBYCs7iIAjSVUunVkCCQAYhbwpcgWuGkrhVFLtbA4sB4I1AOALAjig86jzFyYsDq4ZXbmCwDpccVzY8dapmORjPAAkHc8o5ZqUr2B7TSjBn80AKqV7eGNKX6PTQC5sKsVBlyJlFeimuH9YBJIEAB92XAiuhJdRUq08G44tvo+ryDrbFYOjMQ7fQJAGgRHLdVwO7UYbqcWw6ilWjML+FkDQDxWWQDEQsEz9kI3i59aeQ3WAsiz0mJfXOyGQU9uMvDXb6qHf0rOXRQAiIvYdUsV3Ep2z3SkFzmRdFE6TgMgWwS9z1RP2hJOWB2aoMPTcRoA9WS+s3qupveyAKj3d1kA7BGcoxYE4sPHdUsVKY90bXed2wOKLACyCzMPfiaTymE80eGmz2cWAQAirGIZHwQDrYxgFiRoADwj6AUsU/4FH0puJZfAbFYO3E4tdsu8RgCc7zItuH9/QZ8sAPablI5Js1k5cDetwKPLzBXBtWSv9RmOBVBvHUAa/kbilTUAxzgIgEEA9Gmjy8D0mepJj101CORZArFQ8oP0fJhOKSELnAwAqlkP+k31MGSugVvJJaQu2QDlHhZZAP0Jg/MBgPTxqQHgQJzS9g5L8IzEO4WuNrXrS5eBoSEGJzleGy0ZAMSn0QsBbAXHAiAuYMNmJ9xOLYY+U73He1pWCB4A8kDw2u46mE4pIR1z1MaBHa/umEafAVBLaAAUQaMvogWAWvf9qKWalKPBrjusdfqSpAuYZ5lB3b0arfQrxpJItA4HGgDpxf5SZAuMJVTClK0MLrusmFolYUQWQL0AKCqh1OMC9Afp+W4hPwsJgOz96W8AxAeRsYRKeJCeT/r29rnuIdnyQuyceS6iVdUCKAuAFyNbSLknrFRxLgiAABAEQJ82upju1ei5tljY/k20OIoWxd7YBrhpK4WHGXkwbHb6DIBszBu21sHixn2m+nkHQHoR9Tf88QDw2u46Ush6xl4Ik0nlJCZSr5UFx4S2APa6rH5ocemlXDxqMVTs5IVPo13RTQFdRL8XUSuM3bm2uw7u2IsI4MqKCABFtQBpEJywOoh1Wk3XEQC7KAD0NwjSFg1/Ch6nGgCqnT8utOh16OVcV7zmsjGAPP29EtVM4qWu7a7jLr6LCQAR9IbMNXA7tRi6XCCkNxZQ5AL2BgJZq+CUrQzu7TkBR5e3wailmjwkLxQA+ksuRbZAhrERrluq4P7e48TSOUhZOkV1/7TAD2uknqHqAHoLgJejmuGmrRTGEirhwi4F/M4FAZBsQQD0YeMVgu5xQdyUrUwXBNILJAIGxtrIxgFpwSAuQEPmGpiylcF0SgkcCmklxZt5gLVYAFBkfbkarRTTHYl3EksnWivYBdfbOCsEQNrqh+56eoxlAPByVDOMJzqIlSLQi+j3d9UIFy1MfJlOKSGB2zLwp2YBFIEgWgRv2krhQXo+3LSVwkBcrSoA7jHWcQHQX0DoTwDkHZceALy2uw5uWCvgYUYegXIe+LEJShd2tXrlAsbCx7dTi0kcLG/hDaTunt7pCYAofSYlvrrPVO8VAIosgDwIZP9Wu5+uuq5vurGBwBO2KRy1VBPd9hUK/QmAdKwzPrjesRfBsRXtcNNW6hH6JDp3Wcsf7QIWAaCMC/hqdBO5V85HuMPf2Z1t8N6OhiAABvoAnuVN1AmkO0bJCGUtRLIAiAvCWEIl3E4thrGESin4645p1FwM6QWxN7YBsoxNpA/wHXsRTCaVw0i8kwuEgQJA9rcHXF0cJpPK4Ya1ArKXt5HjZo/ZW+hjAZDuAoAuenai1gLArugm0j1lsVhRtACwK3qu1++UrcwjqF20YMi4gNl4V7QI9puUhAa0cuHCyOq6LAB6C4G+AqDWMSEIsABIgy664h9m5MFNWylc210nvIYyAKg2bjSkTFiVhxT0QogW3sUKgAgAGPqhBg0iAKQf2tQgEK2sshDIxgD2meZitjFh4o69CMYTHQT01dYN3rjyAFArFImW3lglcx/XoIcZefAoM5fEUHdFN8EeYx2JAdSaQ0SwrJZt7i0AXoxUwmtm7IXQE9vAhb8gACpbEAB92FgXMCvDZifM2Au5Zn4ZCMTF925aAdzfe5y4e0SCC6jsgshmUmLbN7SkYdu565YqGDLXeAVr3gIgHuO13XUwZK6B65YqmLKVwR17EbHyjSVUknNgYwBlroEM/A26ysWw7jYR/LGT3UXXAtITq2QKD5lrPCaw0zsX3hXBAqCM5QITaXBc/QmA+B5r7RuJd8IdexGxCmIvbL0AyOo+C4Y8UKRdd3qgT/YeFAEglih6kJ4P9/acgLGESrJfPfAnsgCqAWCfqZ5YoxB+RIvuhV2tAdVdnguYlctRzeThBXVSCwL1AqBaiRg1AORlAeND/Ei8E27aSknplIcZeXBvzwm4lVwC44kOGDY7yTzJG3c8drU1ps81vw6b59pw3rEXEdi7v/c43EpWrP/9rnsOj5OOAZSFP1nLny8AiB6Wm7ZSuBLV7NYCjoa/IAAqWxAAfdhEVhT6hr62u84tOURG8Aa94pp8MeAbnwx5rjF8SpRdfHDiUCulMRhXC9ctVaRXKkLhreQSmEwqh7GEShiJd3J79OoBwAGqHzCWmbiVXEJg73ZqMQHRQcYyiW40BEA9IKAGfhiXRid58BZakfWPntyGzDUwYy+EPlO9x+QV6EUUk0BkFi+0VkynKPAtgglvXMDs9WVh8NruOpiwOkh/3hvWCsgyzh2Tv8QbAPT2t2gAxAeN+3uPw4P0fJiylXHvc18AUMtyi7B9bXedm/7yFl0ErEDqLvYCZrM9RXGBai5hGi7OUQCoBij09dETE0gDIG/N4BkK+kxzD+jYLx3rDiIgYp92TCbE/u2oU5iI8igzlwha2REs8QGLDW9hBQHwsuAcZeBPDQAvRbboBsDumEYS3446SgMgDX9nd7bBu0EADAKgLxsPAK9ybuje2Aa4lVxCXGiyEIgASD+x3bBWwKPMXOIO4sVIyUKgFgDy4gHR/YpZVQhqCGv4fyxBM2F1wA1rBUynlJDXbqcWu30HY0qmU0pIKQeRG5oVGgBpsPMW/vpNSqD246xjcNNWCv0uaEMXpR4A7IpWXGk3baVwNbppUS6iegCQdglPWB3EHS4CwAu7WqUs3SIRjRG6prKXtxF9um6pIhYRfwmer9Y9xMKjzL7x4edwSCvcTSsgFs7BuFqhfuqFP1kA7I11j1u+EuUOfuyiS8NVoC2AuMDTIoJAGhBYa6AsAPJe04Ic9n66FNniAYBaICgCQ/pewvkLPU49rnsF51B67qM9TDLWYdbLwQNA9jy9tfxpASAP3ofMNaSeLg1+ahbAIAAGAdCnTS2OinfDjiVUwoy9kNSE0guA9E0+mVQOjzJz4VZyiZvrSTYhhAVAngXk/2vv3IPiOq6Ez2dbjwFLiu3EEkIS7+E1DAwgyYoU24ptxZVIfujBa4Dh/YZ4rYpWsUoPSpEWVh8sfHywsGAWFiLMguGTSrJUUmzHLsv2/uNsxYlr/3EqsctOVSqbtbOpilKV9fn+uHOanqb73r73zmhG0KfqlMQ87tzbfW6f3z19+rRZpSN6E1lVJH9lNENbeDLpfw3fp6eNrSoCIC+R3gz4jWdWw5X8Ynjv0f1wraCQwPVwei0ZqGUAkIaGmzsPE2cTqVEUEQAarWgcdGpFb9Gh0m1hFAGkbdwIBvXyXXc5NEeHq74x2oERSpnV33YBUEbp9Ao8z7d3PwuXPKWw19EgvH9loM8MAGIf0f9OZ2tpKlh1gE1hEDneSLBdMwCIENiX2kD6YTi9llyXCAD1poHp14MFgGZBUKTYT0ZAJ3s89vyMIoBWI39mIoB0XvWV/GKSj8nWAOQB4HkFgACgANCWGCXS824knBLGKTSzADhMOQaMVr2z5xm4vr2QRA9Y2BE5pqG0pbXURA7MquJ1y0yjyeZYsU7aKJFeBH+jGVq+FRZsZcEP1SwA4rZ8Yxk1AU6UrUeGA9XZMJQjsAOAtH0Pp9eSCC/mCZkFQJmIINt3g856kgPI9icWsn5z1/Mkj+769kJuZDlYAIj2iRFyjJDiOdBgOuG/T3EKGFM32Fxeu/CnFwEczdAKFV/NLyLtqQeAopWW4bRdEQDqRQFR8QFtxl2xBHR5AEjnQ4qigbIQ2JvSCNsdlboAaBcEZQFQ7zf0zksUAZRRI/BDNSoDg6k1k1lVxEZ5RaA7E5uXRP8UAGqiANCGWAFAdJqYV0c7TVbxicbIKY5laKsm39nzDLzxyEGYzvYJIYgFQCuJ9GYjdLJTzFbyq+g8Kh4AiqKiuEDnvUf3w5X8YhijPsu2M67yEzlaHCxH0rWSKZfzSmDQWa+bQxUpTtQqALI2PZFVRSBrOL1WCgBlp4J5EIgA2J/KL5PERt/oXFbMI3zrm8/Bm7ueJ3mmV/OLyMpyzIeaclXCXE4ZzOd6YT7XSxYUXM0vInmxCHkIm/TiKTYKSZ+jHgAGA/54EcDhdK1gLy5IYp09z1FHqu2aBUAWAjEaiAXPjQBQdlGIkSIAdic3GQIg776TAUMZADQDfLIAaNQOMpE/IwAcSqsjKVUDznquXbL5fwoA+aIA0IbIlNIQ3WxDaXUw6V+qjqtZRQCo5yhZpzfjroA3dz0P7+x5Bi55SnXzoqwCoBlIFAEgC5JWf0cEgLxIIA3K7+x5ZsnuE6I2RgDUc7Sz7nJ445GDMJFVtWSgM8qjCqcT/d/JlZYBkLVvbAfc+godUCgg0AgAZdIhMGI35aqEGXcFzOWUwYJHy229kl9MwA8jZVfyi+FyXgkseLwwl1MGM+4KuOhajCiK7E+kfQIAlIVAo3ZlARAXQoj2qBU56+WQAyiCQJxhub69EC55SmHAWU8AkFciRmZRiBEE2QFAWT+D18lG+oL1exeSAgFQJuqnB4A80GYBsN8P7LhQSWSTCgDlRQGgDZGtpab31IXRQFzdayYCqDdFNumf2rz1rQPwxiMHyVL+OwWAqNgGoTq+EQCOZdSQPCcsuMqW02GdqhkAHM+sJhEf7DMRAIqeVMMJgP8v/9mA8zYzBSyy7ZF0rcgtTncGEwBRzQKg2fxYtC2ztmvmHEQAqAd7VgBwJF1bhIb5wnrRH7P22xkBewHbhUCMBiIgT2RVQadOBFAWBGUA0My9ZjZCJzPFHAwAtJvvZwSAfakNpK7fXE4ZmV0QjaciAFQ5gEtFAaANMVNMVw8Ch9LqyL6wV/KLCZzxptHMwuBoRg3JSbv1rQMk7wWnnpcjACL03dhxBG5968CSWmpmptl4eVTosLE+IJaJ0YueRCoA/otL24JtzN+WVkCQZ9N9qYt7yOKKdRlguVMAKKN47ez9pPe3HQAM5tTvUJq2veNFlw+u5BcbbudnFgAxuvTaju9FJAAaQaCoFMyAs57UxZvIqhLCiZ1IIA8Agw2CeJ2hgL/+1AYCgBiZCxUADqXVBaTV6KUjKAA0LwoAbYjMfqpmIJCeSsRq67w8KrPTZahjGTUw6y4PiIbtdTQQ53M3A+BYRg3M53rJtb2563mYz/UuWdSh52hFERYaAIfTa0kf0Xs+Y1/JTP9GEgD+fZK2MvudPc/AdLYvAAKs5AKi4qIXTHXAEj8yIGgWAPE7oQDAUAJmX2oDWcksA3t64EePIaMZNSTfEa/DCP4wWiT7ADPht5mhdG/EAaBR9E8EgKhdSdr7l/NKyOImHqRYBcAeCgBFABVpAIjnhOcnC4BWwK8vVcu3xt2eRtJrueCH2pnYrADQoigAtCFsIr1dCGSjS7hCjzfom40W8KbAJrOq4KnoJlL9nd5+KJiAhk40WMfExH5Myv/e/S3w1jefIzsY0As66Igf3XZGbcjLo8JVZ/TKSV4OlUz0JFIAsMtvuyPptfDmrudJzUKzDkIPAFGnXJVwfXthwJZmVm2aBkCRjQcDAPtCBIDDFABiKoiMLfLsmI74XckvJtufoe1iNJa2VbaP9Rw3bcN9qQ2w4PHCW998DobS6iIyB1AWAkUgSC8CGUnXaiTi9DkLLVYigTQAGkXP7ADghaQmS8dgf5t3XkYAyAM8+m/R+yPptcSGB5z1JAdQBH96fatyAI1FAaANwYGo4eEGaNvUDm2b2qHdgr4Qy9cXY9vgvH8J+4uxbeQ1O/pCbDsc3dwGRzdr/8+IOQztm9rh+JY26IhvIYPeSLq2h+LxLW3wg7hFxe/KKraL2e/Rir99fEsbXEhqItNufakNcHJrK2RFF8KLsfzv8q4f/6XbWU+bN7bD2YQW6EttgONbtO9iv2EftjHasnFRmxltfDhQKx9qCJsTrfvGou2+ENtOnKIVO6ZtucV/nTybPrG1lUzxmLHd9k3tAf9PizkIbZv4/WfH3oJpu7QdsvbYslG7/2Tvaz3bPZvQAv2pDXAmviXgM40Pa32Bf/P6rG0T345pG0bt8jvktk3asau/Hj7brXyoAeq/0Q7131h6T8koe1+i1n+jHWq+vvh3y8Z2OBbXBr3+aJOobXiKbdnM/N8Z8xw0Prx03DCjevchXqOMT7Ly2/Xf0K6Bvka9MZAdC3nt1BGv2fCJra3QslHrg/pvLB07ReMoq2gb9d9ohzqOlj9452030kQBoA3Bgejee74O9937MKy6b1PEK3ueeue9+r64sJ+vzDlFetvfd+/DunrvPV8PmxON9LYzatdwn8NKv4b77n04bLaL426oNdj9HOxji37vThzfym/Ifi/U/RqOcTfSRAGgDcGB6Hv318Nz61pN68H1i/+y+ty6VjhwfwscuL8l4PXir2lP99Vfb4dD69vg0Po2OLi+lfzfjB5c3wpb7n8Cnl0n//0jG5Zq0YY2KP5aG5Q/qD1ZYcTh6OY2EhU6FtcGx+IWI48tG/EprB2Kv6Ydg3dso/N5dp12DXbagNZD69vA96AWWfE+oLXx9+5vgWd1+onVZxnFfqT1e5Tui6kLmxP97v315DzZ6/A+oPVh0YY2U7aMtvs9xnb19ND6Nqh8SItI+B5sN+x7K7ZrVrFNQnl8s7brfWAxAsOzX1bN2i5rw4fWaxHG8gfbl9hyuG3X91ADPLuuNeBe0lPefci7L5+OaYanY5qFn6Hvl7pvaP1R/LU27r3P0wP3t8DmmMfhuzHNws+wfWHWt+A1W/FLMnbxPf810O0hq0c2tJEo4MH14nHy6Zhm+K5OPxiNq6jf9R+H1aei1RSwAkAbEozdFGQS6dmFIrhtGS6LHxHkCBrlVQ3486iwFpZeziAezyi3ibcIhK0DyH7GbO4UvZBDNo/KaOXkSHotWSBzraAwoHwJm0dF9xmdJ8PWutKrn0bnqYQ7B1CUqzTg1HY1eWfPMzDjrjCVG9jD2K5o0RNrsxNZVWQBwyVPKUxkVenarmyZJCt5s9ge9D1h9hhGx5ex3fHMapjP9cKNHUfgWkEhTLkqubbMa2cso8HaqyjJn875mnJVwq1vHYC5nDKuHYfbdgec5aR2nygP0EpJmM7EZjiX0MxdJcxqf6pWouRqfhFc314I09k+sgpepJgD2JnYbLhoBMcRo1xBXo6eTI6hWcXz7EpqIruZyORADjjrSWkyzFEd8Ps4VrG9zyU0kwU5aHeigs96OYCY90fnAfakNMJUdqECwHCfwN0sMgBoFQTx5uA5UXq134JHW/l6Jb+YOEvZxHp0orST03Og4VxJKTonK4n0dNuMZ1bD5bwSeOORg3A5ryRgZxZsbxoAef3EJkrrLQCJdADkOaGR9Fq4ufMwvL7zUMDKbj3l2S7vYUcPyC+6fGTHjUueUrK3NG27fQa2a3XRFAKa0fGt6lBaHfSmNAptdyKrChY8i9A3466A0Qz+rkF6i8poAJSFd+zvNx45SFZgRiIAnk3QbPGSpxTGMmoCnL7ZxSAIF93JTUIAFEEgLmDAKg64qwzutCICQOwb0f1nFf4QAHERSLDhTxYAB/wP/ljn9pKnlORu69VY5AGgCP6MFoCwq4C7kppgOF3bvvJ/J1cqAAz3CdzNIguAeFObhUARALKOc9jvLK9vL4SbOw/DrLscRjNquODDA8BgOTk6QkeXuuAB4HC6PtzJOtEeHSfKgz/83Rl3BdzceZjURaQ/p+dEsR9Fqyj1VgCLBqlIA0DWCeE1T2f74J09z8CCRyt/YwSAF5LEEUBZEKRhEFcHXskvhilXJex21Eo9vFjVUALgoLM+wHZH/TX7MPppB/pY28X6dkZj0KCzHuZzvXDrWwdg1l0O/QY2HG7bxVXAPSmNMJ3tI5FK2vFbWRGsB4B6EEivbh1JryVR26v5RXDRpa3K7pcAQKMHsjsFgOw4QDihZfAAACAASURBVI9rnYnNXAAcdGqRviv5xXBz52G4nFcC45nVAUArA38sAGI/W4FABL/u5CaYzvbBrLscupOb1CpgUABoS2S20zIbBaQhUCaKwjoG3O7s5s7DZEqCnsINJQCKnGiwnTReKw6mPABkp8ERIq4VFMLrOw+RgUnPoWJbs9NovGiKKPrHOk/aId0NAMja71BaHVzNL4K3dz9LIhyyAKiX7iALg8PpWnRsxl0BT0U3wSVPKVzOK4HpbB+M+R96IhkA6WsZzaiBp6KbyPQhHeXUawMZAKRtFwFQTyezquDt3c/CjR1HSGQd7ThS0xfYMjAj6bUkykTfX8EAQHaq2AhkEAbx4XfWXQ7XtxfC9e2FMOsuh92OxR2GZCCQd3/qwaEVAGSPzVO8rzsTm8lOIKP++rLXt2vTuwseLyksbxb66LZmp4DNlH5hAXDAWQ+X80pgNKNGlYGhRAGgDcGB6MfuQhhOr11yM1kFQCtRFL18KoRBjCiYBcBIm0ajHRwLgPS5jvp3BEHowx0R6M9h28lEUUSw088ZOEUAyBus/j6pKqIAkHZeIjsey6iBNx45CK/vPES2F+PZrii6bQcCMfqIu9hgTUgEqWsFhbDg8RIotBplDobtjqRraQbT2T5Y8GjniDqZVQWPOhYfXIyu2UzkD9vcCABHM2rgxo4j8PbuZ2EiqyrAnmkA5EX/wg2AHZw6gD0pjTDrLodZdzl5gDY7DWwUATQDgWytwEH/vbPX0QCX80rgWkEh2XUEH2r7mfuQB35GkUFsD73PiiJ8RrMB45nVMJFVBfuim+BagVbg/aLLR3ygDPTpAaBRDqBM/h++h9Hh+VwviVwqAFwUBYA2BAei3tQKWPBoBZT1ANAsDFqZRtODQYwM0k9psgBoNdoRbADEQRKdXHdyUwAATvhh4MaOIyTSx0KfnWk0EQCKpn+NFoGMZ1aHJRlZBgCNooEDTm3brLd3PwvXCgphxP9QMeAHczsAaASD/akNJALB2vpYRg1MuSphPtcLV/KLSeTlWoG2pdR8rgaHU65KGM+s5m4RaGS7+PmxjBoYz6yGyawq4mjQsd/YcYQUvp7P9ZLFG2i7F5KaCMTaBT5RZFpku8PpWoHjW986QBb4iOw4kgEQp/foaE93slYr9JKnFEb9uYGhAEAzEEjDYHdyEykEPZSm7ZSz4PESm0F7wWgw3Te8aB2v37ooANQDPJGvGnRquaB4H9EPLnM5ZTCUVkcWEPLGD7vwJwJAMzqSXktmeujFIOcVABJRAGhDaCeKOVK4PVgwpoTpKEownCY99TTjroBLnlLY559GQ4AN5krHobQ6MkDYhUn6++jA8FyfiG6Eq/lF8PrOQ2SKBacDeW1hti31AFA0ABsBYH9qA8zllMFkVlVYd1MQTQHLTAmjDQ8662Eupwze2fMMXMkvJgsHWAAUpTpYsWsEwN6UpVsl8h6AMCI84Qe1uZwyuOQphSv5xXCtoJBAIg2L87leWPB4A17jfe5KfjFc8pTCXE4ZTGf7YMK/kw7voQNhb9C5+PDCAiANc3bgjweAw+naNOmtbx2AS55Sck48OzbK/4tEAKS1N6URZtwVMJ/rJQ+LMmoGAK1AIAJgFycHEPtoIqsK5nLKyAMMPkxcyS+GBY8XZt3lMOWqJLaGaQP0g3FPSuCsBd4/eC+MZ1bDlKsSZtxaAIP3WzhG0RFxNgcQx3h2zDMCPyMAPJvQYgkA+/xj61xOGYFhtRMIX+5KADx9+jRERUUF6MaNG8n7X331FZw+fRpiY2Nh7dq18Nhjj8EvfvGLgGPcvn0bWltb4aGHHoLo6Gg4cOAAfPrpp6bOg3WimO+BuTxGYXcjCLQ7jWYEgziNNpRWBzPuCpK4e3PnYfKkN+WqtDyNxgNAKyCIkZYpVyUZFHGQmnWXw+OOeqHDNQN+NNDQA6cdAGRzV/Y9kL/Edu+/x0EGonDZrozSU8M8EBxKq4MFjxfe2fMMmXIRgYndqKAZAJRV1u7oe5qNDhrZmpH9YZSUBkCrbTHorCfnKgJAGvyu5BfDsD9aK4os8Wx43wMFEWW7RgCI04NDaXUkAiszLWwWAM2CIA2AvGli0cMXRuXGM6vhoktbzLDg0SLO+CCDuuDRtsnEcRIfVq4VaBHpy3klBCQvurSHFjbaqPdAywKgnagf9pNdAOxJaYRJf9oTnQfK2wdYAaAmdy0AZmVlwW9/+1uiv/vd78j7nZ2dsG7dOnj11Vfhww8/hKKiIoiNjYU//vGP5DONjY0QFxcHN2/ehA8++AD27t0LOTk58Ne//lX6PEROVC8ayAu7mwFAu46TF0Whp9EQuDDRHjdEx6ljnEbDaMdkVhWMZ1YH7L/LOlE702hYfuTGjiNwOa8EZtwVZPHGoL+N9KIoZvTUtlaSMCwzjWZm+rfH//0jG7Nhy5qvwZmECji5zQcnt/ng+NZSMhDdadsdzSgxBD7ZqCC2yVBaHUxn+8j05ygnR9CuPdMAyHvI0XvwkVXsw2ABJtsGCIDo3M0qfayTW5faLt4fCx6vIfiJon8sAG5a9QCx23Dbrh4Asq9hugWmvugBhcwiEDsQ2J3cBAUOXwAA8qaKzSovB1AE92aUN5YhAHYnL70Gmegfrce3aFsZ8gCwM7FZCvxG/eVmplyVpL9EewEjAJ7cpgDwrgXAnJwc7ntfffUVbNq0CTo7O8lrt2/fhg0bNsDQ0BAAAHzxxRewatUqeOWVV8hnPvvsM7jnnnvg+vXr0udhVEttJL0WFjxeuOjy6Q66ooggL4+qj/qMXQiknSgLUKLoCD59IqRhnbbXdx4i0cMbO47AjR1HSO0nLG2B7/MUc18wR+uiywfjmdUBK5h5EUw2imInkiKCEzsAiIM55tJ898E82Lz6oQDn1OGfRvviiy/uuO2+kqNFezGKZMbZ6EUDcRCfz/WS1aVjVGFwsxDIvs/arpGtsw8/RlG6YAMg73qsAqAeSGNbjGXUBKw6RfCTgT/R9O++BwoCbLcvtQFeyTkcNtulAdAoEogQ2JvSSBbkDKfXckGQB4CiKJUMCLJ/0wBoBEt0X8iCGj3taQf49ABODwCNgE9WZQBw0FkPCx4vzOWUQX9qQwD4GQGgigDexQAYHR0NsbGxkJCQAEVFRfDxxx8DAMDHH38MUVFR8MEHHwR855lnnoGKigoAAHj99dchKioK/vCHPwR8xu12w6lTp6TPQ7aUxpSrkhQrlYFA2oka5VEFaxpN5BxpB2oUZWGnyLAQ9ICzXreosx3HKutEZQBDpF0cAJRxnr0pjeQhYCKrikRRVv2v+2D9vdHwwH3rICcmBb4fdwSioqLg3//938NiuxNZVXBz52GYclUGBQD7UxsCbHfQqS0WeeORg/Dmrudhxl1BAF6v7fX6r4+xXTN9zwIZG6HD19A5GwEd7z6Ruf96Uhphp6NKynYHOH+zbTWUVgcXXT54c9fz8PbuZ0m9s94U42LCPAhgHfK+Bwpgtd92v77qfnjswa3QkfBc2GyXB4BGEIgg15/aALPucjJLwwNAOsJkVXkAeCHJOAIoG00TQSO2BQ2RMnAnqzIAaKfdjABwwKnlHS94vDDoXMzv5PU3DYDnVQQwQO5KAHzttddgbm4Ofv7zn8PNmzfhscceg40bN8Lvf/97uHXrFkRFRcFnn30W8J26ujrYt28fAAD8+Mc/htWrVy857lNPPQX19fXC3719+zZ8+eWXRD/99NMlAMg+qdH5G/SAE0wAtAqELACKnCLvdREIsp/Rc6J2oin4bzCn0YIJgIP+AWrGXUGAqDu5CWo3fRfKH94HL24phLpNByBp7WaSR3Xjxo07brudSdXk2rBMyVBanRD8eJEInv12J2uDLhvZHsuogWsFhfD27mfhan4RjGdWG/YHr9/MAKAZW2ABDW03WL8hC4BG9zcb7buSXwzv7HkGbu48DBNZVeQzGGWSBT/RlF9PSiPUxX4XamOfhP+b+TR0JH8bktfGhtV2aQDErb5kAJAuHYL3KY7LGN0KFgDyIoJmAFAPAnt0PoPtESzgkwXAYLQVjpU8AETwu+QpheH0WiH0KQCUk7sSAFn505/+BBs3boTu7m4CgJ9//nnAZ2pra+E73/kOAIgHoieffBIaGhqEv8NbfGJ2JSVGhOjSCyInahUAZUHQzDQaDV1mIM0uABoBqWwUhQYHs+2ITlQ0fUb38YCzfskUEw5ovKfUswm1S5zonbRdBEAEu/HMarix4wgBV5npIh4IsgDIpjcMpWnbZr2563l4c9fzMJ/rJUnoetDDAiD2i51IuB6gBRMwWe1Oblpiu3p2SN+nw+m1MJdTRqJ987le7jQv7nsqC39slIgGmIsuH5nKjwTbFUUAZUEQS8awINif2hAAgMEEQRzTCxw+0jdWonwygHanAFDmmrGtjaCPVgTAnpTFB2os9I2fl4U/lQPIl2UBgADaINLY2BjSKWCZCKAMBPb7He0lTylcdPl0AZC3KCFYAMiLophxpCJIo1/Xc6Lsd606aVzIIvoM3SY9fmAJNgAOOOsDpvrZp2EWAOmBKWnt5pBPoxlFAGntT9XKKFzfXghjGTW69oxlF1gb5wEgDwYHnfUkgfutbz4HbzxyEOZyyggMsjaJ/6cBkO7jYAMgffxQAaCMPQ76be+iywev7zwE7+x5JiCCKopM8wDQbP7XSHotXN9eSFZ2X4gQ2zUCQCMI7ExsDogGIghOuSphylUJo4LFIqEAQFG00A6gdSY260YQ7eh5PwBeSJJrD2xrWfjrTm6CcwnNMOCsJ+WYMOKnN91rBIAIf+cSFAACLBMAvH37NsTFxUFHRwdZBNLV1UXe/8tf/sJNRp6ZmSGf+fzzzy0nIw84y3WnyEQgOODUdjG45Ckl22rxAJB2mGwkxQ4UslEU2tEFy+GFOopiFAE0024snODfetNoNPhNZFUJ86d4A1dXUhOcS6yH9fdGByTS30nbPU8BIO0o+lIbSLHgy3klutPCVgCQFxUcdNbDeGY1gcE3dz0PCx5vwKpvke2affgxUnxY6AmB7eL50QDIvoc6mlEDczll8MYjB0nBbXqKF1X0EImQIdt3tJMfdNaT1fh0nhza7o8SGmBdGG1XNAVsJgrITgljDmBXkrZvLJb06kttWHIfhwoAeSAoC3E0cCEAyn5P73isygKg2agfTiljjUL0i2bAjy0MzgLguQRNT2yrUwAY7hOwIkePHoWf/vSn8Ktf/Qref/992L9/P6xbtw5+/etfA4BWBmbDhg0wPz8PH374IZSUlHDLEWzZsgV+8pOfwAcffADf/va3LZcjeDVPc1Q4EJtRPRCkAVDPcVoFQR4ABtvJ6TnRYPwmbxqNPraZNsF2pf8VAeCgU1vYgH3Wnyou/0IPXo9tyIHG2Gfhh1u90Lb5IGRFx8Pae+4LKKVxJ233fFK1rnPpS22AiawquLHjCMzllEnbODpSEZgY2TPCz3yuF9545CC89c3nArYz7NexXREMytqbrO2Kjsf7Td458Wx3JL2WlNB5e/ez8NY3nyO7GbDHYaN6IgDkRWn1AHDAqeUrYz5hr9+Gadtt2XwQMqLjYfX/WhU225WJAJqFwe7kJjif2AxnE1oIjEz4x+ZZdzlJa5GBG7sAiPelCAh59y0LgDLnwzum0XfOJzZDgcMnHQE0Aj+8z7D02JSrklyDmYgfC32iItBqCliTuxIAsb7UqlWrYPPmzXDw4EH45S9/Sd7HgqSbNm2CNWvWwKOPPgoffvhhwDH+/Oc/Q2trKzz44IPgcDhg//798Mknn5g6D3ol5Yy7Al7feYhEgcxOCbMgOJ2tTQ3zAJAXrTILOejI9QAQHYsdQAtVFEUPAO3CMdveNAAOpdWRyMCUqzIAiGQAMPf+FFh/bzTcG3UPfO2+aNjzQBycSdy/pJjunbJdBEBR5IGeFp7O1nLAprN9hlOJNADybN0sDA6n18JkVhVcyS+GN3c9D6/vPAT7optgMqsKxjJqlkQIebZrNkJIOyY90NODPL3f6k1phD2OxZqJb33zOXh797NwfXshTGf7AnL6RLYpUmxzMwCIU8w3dx6GGXfFkqgXbbvr740BV3QiNMceCpvthgIALyQFAiANKJi3Shf6593jRpEwIwBE2JGFN969awYArahZAGTbB//tS11Mh5rP9QZMu3fELy4Cke07BYDm5K4EwEgRHIgwj2rQWU/2S6SLIFsBwfHMalL0GPdYNeM0ZVRvClgmQmIVAIMZbZTNozIzBcwDQIyK4FQvfl40fSZ60sU8Iyyo3ZfaQOoAhmM7LQRA1nGJooHYDjd2HIGLLjEI8gDQLAjqAeGAsx72ODSH/PrOQyR/8FpBIdm+it4eS8b2WDjEtuDZihkbHUqrgxE/wGJu5Zu7nofr2wvh6ZhmkgssWgRjpq3Ytj7vz70yGnumXJVwc+dhMpPBs2Gekz0ThlpqaLvnEmt0p3+twiACIEYE2SlihJb5XC/M52opCiws68FQl4kIoAgiZQCNPX4wF7LIAiANfPj/3pRGktpAwzRtZwiAaL9WoI8Hf6oOYKAoALQhOBC1bmqAo5vb4AdxbXAsrg3OJzbDeGY1nE1ogWP+12g9urkNXozV/uW9T3/u+JY2Mric2NoKx7e0BU1/ENcGWdGF5HdeCoEe3axpKI790hatHbOiC+FYnP61Gr0v+s5LW9rIisCO+BbyOq0/YBSvGfXF2MX+PpvQAuOZ1dAR3wIvxrbBC7Ht0LSxIWxOFG1XpLxrezFWa5/+VG1V+8mtrUva5MXYNmjf1K5r3yI1a7svbWmDE1tb4Ux8C4F13DoQt7kadNZDZ2IznNrWCie2ahps28XjntrWCp2JzTDo1CL6F10+Uth8wFnvB6cWOLq5DbKjiw2v+QcW2hC1bVM7vBgbaKv0vye3thLwPLG1dYkNo+2ivhDbTrR9Uzs0PBw+2/2HFB8c3dxGzgWVPkda2zYtqugz+Lnmje1Lrp1VHDc7E7XFCj0p2q4WevcTnm9GzGFo39Ru+FmritcZyuNnxByGF2LFv4H2Qvu6C0naA/CFpCY4sbVVaGMvxrZB48PtxH71+ktPabto3xRoA+Gw3UgTBYA2BAeiVffGwur74gJ0zaqtsGbV1iWvW9W1q+ODejzU++59OOjHvNMaymu4E/246t7YsDlRnu2aaRe8HlbZzwVb6X43+qxjdSI4VicKz1XvN6xew9rV8eR39Y6/6r5NIWknPCbvGkR9aMUOwmm7wb43Q3Fvh2PMulNq9hrs2lqwNRy2G2miANCG4ED0rbVVsNfRwNUnohthX3QT+B5sh+fWtcIT0Y1Cpb/zRHQjPO6oh0cd9dzP7otugqINbXBofRvsi27SPa7e7z0cswseZ37jqeimoOnjjnrY62iQ/rzsOdBttDFmt6XrxzZ4IroRno5phkPr26D4a0vb81FHfUAbsf0k6vu9jgZ4bl0r+B5sJ22B+iil31xbGTYnumdtpe75m9EnohvhyIY28D7QDvuim4S2GwwV2a6R3inblbE5tF3alqzYrp7Stvt0TDOUPtAGRRvapGyXttdItN1vrq0k13dkg3Zdex0NAednRvH69jjqYLejVnj9ZnSvowEO3N8C3gfa4dD6Nng6phked9TDwzG7An5T9lh0v+j10x5HHexx1Okeg9fXMv2Px8f7Dz+PY2i539cZ2ZDR9e521AZcg9V+pfv30Po2KH2gDR531MMja30KAMN9AneziBLpeblTI+m1cK2gEK4VFMIop7Yar3wMbyUlnbczlFZH9pidyylbUh7CaMFIb0ojKeZpd+GESDHvI5THl62lxuZLDaXVwWRWFakzNeWq5O7SYpRIz8uXw/7GnTVEOVSRkEdlNjdIr4TEgFNbHX05rwQuunxkxa7Ixo1y00R5gz2U7VrNJZSxLTP3huj3ROdzIamJ1OE0k9dnRjsTm2EorY7sxz2d7SP3vlHZD9Hqy0ix3TPxtST/rydF23f6+vZCGE6vNcwL08sLPJfQDB3xLcLSIjKlZOhcNhz/xjOrYdZdDrPuctjraICxjBqyXabZXECjexbz3IzyCHk5erzPsu93JTXBbkctTPjHz0ue0gAfJMp/NlPOBXMAzfYjT+m8a6xjqBaBKAC0JSIApJNdWRDETdqv5hfBiMFCETaRvj+V7wxpGFzwaInJk1lVZL9VkWO6UwAYquPTTlQEgOx1D6fXknZa8HjhoktbbannfM9LAiAN+te3FwasaNNLWI4kADRyLDI1ydB2B5z1cCW/GK4VFMJFlwYeovaThUE7AKgHhrzX0IHzPsP7Ww/2eHbVpQOALACb1QGnVp8SFy6NZ2rbJRrVf2Mdvp7tdiY2RwQA0jrgrCe1K/tTG0yDAg2A9GtWawrytCupCbY7Kkkf4Z6287lemM72kbqX2F9WF2nguGV1IQja5VBaHYxnVsN0ti/gYflRRz0ZO4MBfKydnTEAQJnFP32pDXDJUwo3dhyBobS6gFqACgAVANoSvVIaRhHBUf/+nVfziwKiJEYrKWWcCxvZmnFXwFhGzZIVhnc7APZJAOCgU1sQMOOuIKUGJvxwrOec6f6QKaUx6t/jFnfP6E0JdKSRDoA8x6BX0uJCkv42U7iasi91cR/s69u1J/Axgb3LQCALgBeS7AOgXoQuGIDJ015/FIUHgHptoAfL/anaA+blvBK4ufMwzOWUkb6VKQLMizKJbBeBK5y2e4oDgAgFI+m1cGPHEbJ7CZ43On89aOABoBUVgVCnfwUtAhpdEoWGLQRDhMMZdwVZ1DSaUQPD/sU7/Yx9sGVgWN+DtoIr1EczamAiqwqmXJUw464gfoP+3YmsKgJ73claG+F+xsGCPh4AGvWVSHtTGmEup4yUZqP7XhWCXhQFgDaEXo0mcpi8aCA9wGJE8Pr2QvKUrgeAZmFw0KkV1MX9afEpc4wqpmsF0OioR7gAEKM0NAAOpdUR4MNBjAbgfom2402j8QCwP3WxSDILfrLw15XUFNYyMAiAoiksEfzhtJsRANKOhwYU3FoMp8DMwiALgLL3g1kADCVg8gDQ6LpZAOxP1aLO87leuLHjCFzJLw4YR7CMhhEAiqYZ9Ww3EgAQI128Uh8XkppgIqsKbu48DLPuchIZswKAdkCQvbd4AKinCIdYD3M8sxoms6pgOttHppSxJA09s3HR5SN/00CHKUOz7nKYzvbBlKuSlBvDMZL1U6waAaCdtlp8MDYPgD0pjTCdrW2XeNHlI+1NbwGnAHBRFADaEByIZnMPwqy7nDgms1NnGEG6ml9E6qshPCEA8gZ+MyBIA+GYHwhn3BWw19EQsPclThvfDQCI5/qoo55E+BY8i4CLg5mM6jldFgAHnPVkkMGpfCv5Uzhg/XNWcdgBUOR4zEwX0YpP3Kzd022IhZ0RBkWRcCMANHsfyH42FABIXwNOBVrJjcRdUm7sOAJX84sCipLT/WAFAGWnfyMJAFmlo4HdyU2kzuGMuyIgIigCQCwpxE4z2gEb1M7EZshzlEsDINsfMp/j5QDiPW32N40AMBhtwusHMwBIg9+MuwJ6/H3cydiFAsBAUQBoQ+hC0JNZVWSfTqO8Db3cqaG0OljweOHmzsMwna1FFmWdolln1JuyuI/uhP+JEp8iMfQ/5aqEMWq64U5PAeNTL9Z1w6ddhL3xzGrY46gj52bXKesB4Eh6LVzylMLrOw/BfK6X7I+rN30mcqLdyVp04mp+EQw4yyMSAM1CIG3bNADq2TsNgxgZxGLb7PSWEQCyD0Z27g07AMj7Pd45IQD2pBgD4KCzHib8bYSRvkl/QXI6OsgqDwCN+tAMAIajmK4RAIqmhREEb+w4Qh7YefBBA6Ce2gXAcwmBRY6DAWY0oFkBTFkAPZvQEhQA1GtfHgCyQN6b0kh24WLBjy38TMPf2YQWBYCgANCWsE60L7UBZt3lcCW/GEaZ6UBZCETHOOCsJ9Xmr+YXLRnsgwGBdA4g/TpG10bSawkYzuWULckNmXWXk7yUyawqmPBvyzXq1xFqccVIei3R0YwaGMuogfHMapjIqiLFcmfcFQTw6GmLuZwymM5ezH2hF7dcSJJbSWkF/PqotsC8KnYxA8+pGk2FjKTXwtX8IphxV0B3cuTkAAYDBFkANLJ1Xm7SmD+6dX17IdnZYyyjhvS5HgDq3Re8v3m2gH/zAJC9x8xE7mQBEO/BMf9uCZhbuuDxknYQAR+r6EBlwG85AyALgpP+1A3c+YS+PlkAtAqCIgBEuOJ9xwoAYgF7M3BHn4PoXC4kLQJgp+ROHTLAx+qpba3cCCDekwseL5nq5YGfAkBjUQBoQ0SJ9IPOerjkKYVLntKAzcPNQGAvZdAYebq58zBc8pRKT5UZARA6URYA9ZSefh32wxzmpODOCzi9POsuJ4CHuSoIjdPZPpJ/MplVBeOZ1QGJzQOSET0zACjrmBFCLueVkAFmUCfSIhv9Q5Bc8HgJAIR7Gi3YAIja6R9wZQFQNA2Ku2lc8pQSIJzP1UBol6OaPHiFQtHZhPL4aLtDaXWkpMa1gkK4seMIXM4rIaWJ6O/JticNgMGEP3pqLRIBUDYieCFJy8HGck0j6bUkumUGAM3CoB4AGinbL2xkjgeALNTpgZ2s3gkAZCOA9MPzjR1HYCJLy183Aj8FgGJRAGhDcCA6m7DUifakNMJwei1x+HogKHKSGEWho1E41XxjxxGYyylbkkSvBzrBAEAr02ihPr4RAMq2y2hGDXmqvFZQSKKuRnlUegDYndxEHggu55XAoLM+YMAKtxPl2W4wQJCOAJqBQD0YRCDEqPRT0U1wyVMKV/OLYD7XS/JY6dzPSABA2hYHnfUw4i9FNOWqhKeim+BqfhEBW3qFuhXguxMAGCm2awcAWRDEe/TGjiMwnllNwMYM+MkCoR0ANANooT6+HgB2cf5vFqaxDExvSiOZur+SXxxQ51Gvb/XgTwGgJgoAbYiMetAOUgAAIABJREFUE+1JaSQLPBY83oAimUYQiE6U5xgH/QsRrm8vJOUORqnpIRmHRE+j3Q0AyIPYC0mL02g8hy+CgP5UDahp6MNCuYNMG1oFQHQqV/OLlhSnpQeqSAFANoogsmcZEMSpNLNRb1kg7E5uIg8vGD2byymDK/nFZFX21fwiuOQphVl3OUz60xPoCLNRlJiebuLZE/tdNmcVI9+XPKXkvNCJzed6YTi9FnY5qsn18a7VSlvR7W0VAEWRG9bJhtN2T26TA0DZiCBOlU9kVcGCxwuX80pIVNBqNJAHgectAKDZqF0wAZB3DSwA8q7ZSpuh4hgzn6uNzZizKbJDUdRPAaC+KAC0IbQTZW9WEQheyS8mEUG9vBwRAPKcxKBT233hWkEh3Nx5GC7nlQQk0YsgiM2jMgtfsgAYasCUTaTHCMyUqxKu5BeTSB87xcs6Xrqoqp6zRR32T9lfzivh7krADljhBkAj2zUTDcTXRQBoBwJpRQBE2+X1NdY4QxBb8HhJYWosvYS781zJL4bLeSVkcRFGFHGnHTovFfuWPRYejwZPXETFRvXQmSHE8uzKLPSJABAfYOzCX6Q9vJzcVhvg2O0AIA2CCAh4H+NsyyCTK2hVzQCg7LRyKAFQdHxcycxCL7tQwwwwDzi1mqG4CFIG+vTAj4U/BYCBogDQhph1ojjQjvinhi95SrklRNhpNDPREVw8ggMXltjglUVhI4B608V3CgDN/A7tRFkAxM8M+ttjwaOVzMA8yvHM6iXRUpFDPZewtKgqD2oQ8BH80JmKnGekAaAZ+DOaEqZzAPXULgBi1EYUKTSKgtNRO3aBEua5TvgXOI1nVpNFTiPptUuiiWamhXv9bYQAaBeMeRBOAyDbV/TfvH4VAWCkRQDNgJ8sCLI5gD0pjTCeWQ1X84vg+vZCmHFXLFk4YgUAzyYYF5u2A4BnE1qkPmt0DrzPd8QvAqBV4MPf7E9tgOlsHylpNOmvpHEmvoVsB8eOmbLwpweAP9yqAFABoA0RAaCRM8WBF0u+XM0vgomsKhKVMwuAIgeIUZApVyUpH4GrCTG/jZcDKJpCDQcA9nFe50VRelMWty3CRQMIfHQyPc9RG7UpPkmjk6YdZ3+qVkfxWkEhmeLngZ8o+hdJAGgVBO0AoFUgFAGg0T1hRrHPzECdGduiAbBX0Aaiv2XbkzcFjPYpgj/Z/L9IAUBWgwWAoiniSX/5puvbC2HWXR6w17cVAGS/F6wInSwAikCTPR/6HDviF6eAabuQAT5Mj5l1lxOfdNGlRfvwdzoTm+HUtlY4m9CyZMzEB3IR/LE2wMJfR7wCQBQFgDYEB6KhdC/0pDQKby4jxzng1AoZXyvQni4Hndo2bV1JgdNoVqaGeECIqw2v5BfDvuimgOrxbBJ9MKZoWQDUA0pZ6MQdTkYzauCJ6Ea4kl8MN3ceJhFPXjK91Zwq2onia0NpdaRUyYy7AvpTG0xHT3CACvdOIGZsVhYGrQKgLAiaAUCZe0QEaCwA8r5j1a5YAOQpG3U2A38sABpF/Vj7jfSHl86k6gAHz3P+VmDwbEILnNrWqjtNjHY3nllNHq5xZqGPGvdkI4BG0MSCmOg1/D8NgDzI5B3fjNIRQJnz70ttIDNTN3ceDoj00dAXEF3mACD98GEU9RPl/qkp4EVRAGhDcCD6xzRtz8bRjJolACDrTHEKc8K/OwJOI3YmNnMHfV7EwMhxstEJnALG36WT6PHJ7HJeSUAuk1ESPa14c5uJALLTclgAei6njBQKvrnzcMB0ARaC7k+1FonRc77oRPEasHjz1fwiMtizDlXGgaIjGcuogWn3kbA50X9xFQZMV4tg0AwUWgFAXiRRr28uJAUPAEV9j30UiuOLAFB03WYBGtsTIcMI+qxM/3YmNkN3cmXYbHcqu5DU0uRN9VmBwc5EbRs4PQBk72GtHZpgOL0WZt3lJC8UF+axQGgWAM0qQizv+FZgTw8A2agfXmdvSiPZrQbzY7FqBc5u6T0Y8wDQCtiLpn8vJDXBaEaJAsBwn8DdLPQ0Wk+KtlR9weMlK8esRFbo6WHc+WIupwyG/bmCIhi0ohhFwSc0NpcQ99W96NJ2CLmcV0JK0CCEYeL7lfzigAT6uZwyson4RFYVzLgrSG1Auqj05bwSUgYDj0sfG1dMXnT5SDI9XQhXJooiC8i89sXXMEI76y4nK7l50RS9J3/aaYyk15KdTMIZATyfVE3sjJ6+thsRtBsBNIoMXkhqIjsRhBLQQgmY5xO17bRwOpb3cGdVsR/QgZrpO5n0BZy1+Kd0b1jLwAw662HBoy3YuZDUtMTxW4EGMwDIm/qkAYgu5H3JUwqTWdrOSwUOH3mwDAUEigAwWEpHALuTm0iJMl7uOd6veg8SPAhEALQCfCIA7EpqIuf5Dyk+BYDhPoG7WXAg6kioCbjxcUs1vciKDATizTKWUUPKiUxn+8gKYhZYrAIg7eTsJNCPZdSQws9YFBoT6rHw80XXYvFneucQqwn1vDwqO04ZFZ/mr+YXwUWXj7tq20z0BO1j2A9+U65KErmIhBzAvtQGshsLJrjbAUEEQD37tqN3OwDi8Xk5gHaAj53mNQOAohwwWvtTG8juPz0pjRGRA3g+sZms2J3MqgoAQTsAKJMvKAuE+FCPD9NYw/JyXglMZ/tIcX+0baN+kAE0uwDInkdPipZnjQulnohuJEWZL3lK4aLLB8P+CJ9M9JgX2aNfO7m1lSwCCQb44VaKI+ma3agcQAWAtoQFQPqm6UttMARBGSd6NqGFDOo4BYlRsxl3xRIYNAuAsk6UlwMlu9KxKyk4uyng7+o5UR7UybRFX2pDwBQOltLpS21Ykkdl5DjpnBa0iREG/OiB7+S28DlR1nZxRd50tk8XBI3sl7bdUAJgZ2JglDFYcIZwjikYodDziYGrgHlQZwUAaTUCQLYfRdCB4Ded7SP3XbgfXthFIJ2JzTDqf1hmQdBMNLAjvgVObm3lvmcWBFkY7EpanALuTGwmhc0x/QanS7Fu7HS2D8Yzq2HYX/C/l+pv0X2J09iyi0DQznr9PmY4vZY8tONWpFhvFouuj/hrWIoixmbaR9QPRgAogj4sgXM+UYuwos8cy6iB84mLC0EUACoAtCU4EH0/tgGOxbXB8S1L9Ux8Cwz4q/93xLfAS1vapPVYXBu8GNsGJ7a2LtEz8S3Qk9JICs72pzbAGf/AJasvbWmD7OhiOBbXZup7tJ7apinvvR/4z/9YXBv5DH6eVqu/fXJrKxyL067hhMXvd8S3kOn2sQxtKv/UNq2NsR/wGrDt9fqM7f+zCS3k6f6E/3x/wGjrpoawOdG/2dzAtdsOv932pzYQW7Fiuy9t4duvXT0usF2RHdDfNbKJE1tb4ejmNnghtt3WvWGkP/Db7ktb2paco1VlbRFt10zf0XZwcmsr2ZbxTHwLHItrC7DhcNpuy8YGOLq5bYkei2uDC0lafu2FpKYl9xx+jr0PUV+IbYe2Te3C91k9ZlKPbm6DrOhC0jd0e+P9gquQe1MayYK3CWpmBZW3lWaPH9BxanaQs3UnfSx6dgYLpmNgAWESxwA8zxdi2yErutDS9fPGQF7/tG1qhxdi5fuB7deupCYYz9QgFccj1Bdi26Fp45233UgTBYA2BAeitaviwbE6UVdj1jghek2y4edYXbva+NjRa5Jh3dp0S8dfdd8m09+JNLVzDUZtt3Z1vFQfWOl3PPaaVVvD5kSNbNeq3UZ6v0eKRvo1RK9Jhpg1TuH7a1fFh81216zaSu4hVnnnjq+zn9M7Rih07ep4WHXfJlu/Eb0mmVzfurXpsH5tJmxwZBNdvzaTKP06vrdubTrErHHa8kt2r4F3TL2+0Huf1294baLPhWPcjTRRAGhDcCDKWVsEeY5yaS1w+GC3oxa+G9MMux21UODwBSh+Jje6DNzRpcL3jXS7oxJ2O2rhwP0tcOD+FtjraIBdjmrY7qgkx3kwOk/6eFY0N7os5Mf/miNnyW9sd1TCLkc17HU0kOvf7agl126mLTNiDkNKzDOGn9vjqIPv3d8CuxzVS/o8N7pMqNmOwrA5UTO2W+DwweOOengqumlJO/L6xY7tGulytl0zbRAs2y1w+GCnowr2RTfB4456cnyeRortZjmO6N5XrBY4fPDdmGZ43FGve0+6o0shO7rY1LFlFX/3a44ccEeXmvIbZtQdXRrS42dHF8MGR3ZI2gg1LeYgJMXsl2rTxx318L37W2C7o1LYp6xmOe589YVIEwWANgQHojPxtbo5H7zE2u5kbUHAXE4ZWeXLJgBjvgKbq6OXf8VbNYl5Jlj7D1fWjmdWkzwONmfOaBWmmUR3ozwqveP2CD6Df2MeVW+KtnADV2JjqRasCYi1FWXyplg9408K5+XP9KQ0kv2E53LKYCitLiAHUJTnQucuRUoOoIzdYtoB7q9L13rk2S4vx0y23fXsu4uTAxiMXDpaMecrGDmLouMXOBZXAbPnaaedUDHNQi//C4uZz+WUkTQIUT4Xa8PhtN0T2+qW1HajlVcSpjelES66fLDg8ZIpYvZ+PCPIAbRTY5DOHzyb0AK50WXQER9Y4sRKfqFIcReNYB6TPT5uZ8e71mAoTjmz/YPv4zT/JU8pzLgroC+1YclnaXvoiF/UM/EtcFzlACoAtCN0MV0Z+BOtsOpPbYBJ/wbkU65KUlSYBkBZpZN6RdpHJfrudTTAXE4ZXM0vCqj5hwWhjWroGUGhXQCklS4AjQ5rxl1BVtRh+40wCdNmE+dlEukHnPUwne2DS55SmHJVBlSxpx2naFCkB6lwFCQ1C4CszXYnN8FQWh1MZ2srh7G+F9qgCAD17LbL4MGG/j8PAEMBaEbHtwqXPADk2aZdEEQIYBcN9KRoW1LOusvJYjL6M/QiJj07jmQA5EEgKsLDfK6XFHLH6xMBoN5iBLpcCQvLMgAYbO2QAEA70EkDoNFiDqvKWwTSmdhMFiThQj0exLPgxwPAv91SrwAw3CdwNwsORL2pFSTyQ4OgTFSQdaoYFcTVw+cTzdXwEkVMeEqvpOxN0XYkoeEKS88gHC54vDDrLiflXTBZmC0MLbudFl1OBpOUsZTMdLaPnMOV/OKA85jLKSOQ2p3cpLuSMhgRFQRALJiN0T7e6m7ZyAntiMJZTLcjoUbXPnnvsVEkrPKPDw8Dznri6IIRxeKpEQCK7AH7SwbesL/uVAQwWFE/EQDig8tFl3Zv4Sp3vbIjPGhYDgBIrxzGle8LHm22oCupaUkZmGAotp8RAOqBGZ6zEbzdyQhgKOCPBcDuZG017yVPKcy6y8kYo9e3rC2oCOBSUQBoQ+gp4J4UbQqSB4JWai5hlG4yqwpm3eUw6i+oGQyngM5GJoqCJVJwGzl6Ndqsuxzmc72knhUNaqgIs+zrqDglfclTCvO5GmBOZ/tgIqsKRv2ASe/wYSWKYkfx2mfcFaRwc28Kf9s/Gfijpy8QnsNZCBoB0Iytimy2O1nb4xNXJ2IEOZQAyD4gyUTmZB4WQgmAeK7nEhZtN1SgfDZBqxaApUawjiiCsBk7jjQA/OFWYwBECDQCwvOJiwXacTUsPmAGG2wQAM9woltGMGj0dygAkPebCIBmCzWbUazQgJsGjAqm7I3AjwXAMwoAiSgAtCF0RXq8ORAEcVcFnnOVjQieS9BuApwixh02cHsho8HfyLHQTjQYjk00BdyVpF9nMJhRlGBB33hmNRl40GFimxk5TT3H2Z2sgd9QWh10+fs4nFPAZzlTwPSAbxUGzydqUeXpbB/MusvJtnmyfWDGdvU+R9sED/5YcAwmAPLOgVYEQL2pb7PtROf1jWdWw3hmNUmLkIU+MwAYzjqAP9xaR6b3eFEeo6igCAjP+L+LU8Q45srCoFGuoAgA9aKGPNDTA0eEHLvAJzqvU9tauTmAdrU7uYlsIYd225PSaAh8MuCnAHCpKAC0ITwAxJsHQZCuyyTrUFkAZBO2cUEHLnAY8G9NZtZ5yDpRkYMMRxRF5ETtRFF6UrSFMriABNsVczFxGkLGYfKcJvtggOAXCTmAc57nSTK8yD7t2m5PipZvhlsBos3agXQztqsHhnowSDsl0WfZ98ycQzAAkP593I4Lc2NH/YVvWduVtWOjSHZXUhP8Y1pZ2AHQCPh47xkB4MmtrQRuupMX8wVxbKCLYQcrAmhGeb9Nv4aQY/Qdq4oAaDcC2JmoPSiOZ1bDgsdLpuF7UhrJFLDRNL5MFFgBIF8UANoQGgBZo0btTl6c6utNaTQcbOl/WQBkp9t6U7QVqLPucljweMmgLxtpsetEaUfKc4IiAGS/p3dMWnmQZ9WJ9qc2wFhGDcy4K0heCT3NTrc1C4Bm4K8vtQFG0mthgAN+OHiFEwA7k6rJfqUIgqKIoKzt8h5e6MUHw/5pNswnxX2urQDguQTz+9zKvs8CoB0Npu2i9vrBGnP6prN9S6oJ8B5ezEb9WL2QpOVj3dhxBCayiiICAM8IAPCMARyindJASAMgb+UpLp7BnTpwhkAWsKwCoFG0jX6fB4BWlfe7p7a1Qm50mWkARPsZpBbRsRFW8mDsL4htFfpUBNBYFADaEBkApKMnuCMIbrFlNPWGBiuadmQd6yAVAcDVbfQek6wD6Uxstg2ARko/RYfq+EZOFKMjWL4EBx06EqUXIcGBVAQ9rHYnawMcrkZGxyAayMIJgGfia6ErSYOJWXc5XN9eCJNZVQSy9K5TL0qIA6+e7XYna/fEeGY1iQ5OZlWRXQj0+n05264IUulSR3M5ZUuiqbw27qBsVzbqJwLB7uQmmHJVwo0dR2DGXQHdyU0RMQXMRgBF/zcCBPwbd2XRyxfENqXTcxY8XrJvuB4QBiMCaKSntrWG/PgyAEgHQbD8zoLHC5N+u0W/x2tnHgCaAT+96J9aBayJAkAbIgJAIxDEBR4Y+RBBBT6NiqbZZIBwwr+IBFeuTmZVwXB6LVn9J+tErU6x3mkn2pOyuJ/llKuSDMzoLAep6XKjNsT2xkHIyGFitI+e9mefpHmDWbgBkLZPzNu7vr2Q7PtqBhho22UB0Mh2aZtFIKTL+tAPMTIAiDZ7t9gubZNoxyNUtJQGZDrKp6cdkrarp/hwcGPHEbjo8kF38qLTDvciEDa6IzMlbKS4FaTR1CMPCHEaHscdelYG0yxkABCPazXHLlwAiOPgqH92BYEPF4VdSArcn1lPaQC02pc0AJ5RALhEFADaEBkAFIEgPhnRkSJ0bEYAaBYG0bn0UQ4Fk5v3OhaTxYfS6qBPEC20qjgI2YFJ3ufRQfamNMIeRx2BPVxNfNHlgxE/6HYnm2svto31ALAnpZGsjsYBjpczpTeNEU4APMUAIG2bk/5pvvlcrzBqTYOfCADN2isNQXSEEHPbEIJ2OqrIuYZCO0JkuywAdic3EdijV9fPuCtgPLOajA1m2s7swwuvn4bS6uByXgnc2HEEJql6a7Q9RzIAWs0PNAuAPBikYWiMStNBGNrtqCUpMXjvBBPQEJ54UCmros93Jmr3doHDRxbMYSoNzq6g3XYmBraNmbbEawgG/KkIIF8UANoQeiWlURhcTzECgFFB3F0Bc1hkB2wzilCEu2iMZdSQXCJcCIF5RZNUSZYBf2kP2aR3s1EUXE2MtQIRriap2oA4kGLuyG6HNq3Oy98zC3s8ZZ1od/LidD4dxeWtphNBID1IhRsA9ez0QpKW84Qlfsb8uTp0+/AAQwSAVmyVtlnc2WYkvRYeddSTMkkz7gqYclXCmB/E8eHAboTObI4hahd1zvQDy1BaHYz5a21iIfbpbB+prTlo0o7N2q6R9qRoJWOuby+Eq/lFMJxeuwRQaDsONwCekQRAHgh2xGuwJwJAOk+QzhE0A4M8KOxOboJdjuqA/G2cpaCL8GO5KXpsuRMRwHMJi/c+Wx8Wz/eiywd7Hdr0Nz5odyU1LTmOkbJtin+fTWixBIB6fU/D36ltrQoAQQGgLcGBaDSjBMYztS3VrEIg7XAxGoBPULKgYta5diY2k6X8bLSwO1l7ekVnO5FVRaaiMMcQBy5cHYfTVDPuCpjO9sF09mLB6Isuzcnh6zjFh8dij4fRnosurSbgiH8FLR2hxCkurGVoFihk2xTLKWC/jFCQLupHPfijB7ru5CYYSvdGBADq2WqX3y4xT3DWXU7agNdmMtFrOzZM2y4LhmhvaGNok1jfbTyzmsA7XcSc3vUGFzB1JgYuYOpNCayNOeCsh0FnPQyn18JoRg2MZ1bDpP9eYX+ffpgacNbD+cTFKWArQMy2l1UAvJCkzUTM53rhxo4jMJdTBv1+h24UzQ7nw8txfwTQLAQaTQ+zAEirlaggqx3xS6eAEb77/dOnk/40CPqBlx0X0ZZHM2pIDVq0ZxzDB/x/o51iwX2erfLGdUw7QCjF1JaTWwOngK20Aw/+Ah6MgwiA7PTvqW2tcCxOAaACQBtCO9H+1AYCK/TqV/qJiudkRU4Xn6YwAkNHBoPlUM9zAFA2EkNHNnoEThEHjF7/NOkg9TrrdHkRRZlzOZsgD4Bm2w0HUIQLI+gTASBv8OtNaYQpVyVMZlXBucTwFYIWpS+wtstGq8czq0nxb7T5OwmAsrZLR5X7qQca3HEGHSD7YII5o3SEkYY5BDosej2RVQVjGTXkQYXeilBky2Zs16oNiwAQoztTrkoS7aOju3q2HBClCTMAnqEAkAXBU9tapUCQBcJT21rhpS1tuqARLADUixay/gLvPYzKDaXVwQgFc2ivGEXEByF8bTKrCiYoaBzxQyM9q4Pjm2gsQKVzAK22gxHMvbSljRuhNRP1YyEQI6MqAqiJAkAbggPRyW2LTrTPvyoM9/TtZG5s2UggJgtj9Akjg8P+CBTW/rPiYFGtAqAZxQFCz6HZPb7IiVoBDzqShItlMJHeTN+JQAp3ysCq9uF2ojIAKHpAwajgdLYPrhUUwiVPKSnnYAcAZaAwVLZL5+2ho+Ll8gXr3jACQLvtRgPghSQNhscyauBKfjHc2HEEprN9AVs2ytgx7fQjBQBpNQOAvIigDACyMGgGDBEAT22zlmdIQ6PVKWDesfT+ZhUjgDg2Won82QVAMxFfOvKHqgBQAaAtoQGQvSkxSoJlAXBwZZ/q9KAQByPeNDFG1ejoIJubJQuAZxPMrdaUjVSEEgDxGs4maFsS0VBipB1+qO5KWlxogGCNJUhoZ4iDkFUAvJCkVbefztbAD88b9YdhqEclAkCRY9GzVezDobQ6mMspg+vbC2HGXUFy2YIFgbSt0AAYDHu1Yrt2f4MGQNnrRzs0A4BdfvvDBR3zuV6yYEkEfkaRbDJNF4EAKIoIyoLgya3mANBshPBMkABQTxFyQnFsbCMZAKRhDws7y7YhDwDN9qco/08BoCYrHgAHBgYgISEB1qxZA3l5efD2229Lf5cHgCwIdiVpU7jT2T4Yz6wOKA/COlUWMkQAyJuSo6ODskDIAiDraEX/N+Pk8IY3crbsv7LRkI54YwCkIYUGPsydoafWeW0sA4A8OMJo8HS2DwapzcvZgc4qAAbDdo0igLIPK+cSAmEQ66Nd365FBscyasgUUzBAUPTwEswHDFkAtPobVgBQFpJ7/Ys5prN9cCW/GOZzvWSfciPok5kCRDu2CoDBsF09AORFBEXKRgoRANnooBl44cEgfZxQA+DJraEDQDw+C4CykT2zAGgV+ni5fwoAA2VFA+Arr7wCq1atgpGREfjoo4/g+9//PsTExMBvfvMbqe/LACDtQNEpXnT5yJZgImfbmdhMBiczkScaCDFCSC+gQCjE3xIBoBlnQztAXsSiI74l4H2MYrJwaUURABG26fNiF7JghI8tDWPUpmYAsDu5iWx7hltGiaIn2DZWADBYtvsPKT6hw9eDQSM9m6ANthgZnHWXw7WCQriSXwxTrkrdsjIy8Gf08BIMxT7Sgz0rD0X0vYG1DO0CX3fy4u4K1woKyUIdXJgmY+dmAVCLZplfBRws2/3bLfVSAGgGBnkAKJoqtqJ4HgiALDQFE9Do3Ux4x7fzmzQA0scJFvx1xIcGANUUcKCsaADcsWMHNDY2BryWnp4Ox48fl/o+DkQnttUJQ988GLyQ1ETq8U1kVUEftVuEXQBkYZCOCNBTnbiSdbujkoALDUTBikbgABHMCAd9juhEccEGDb3DVK4k63zNtKMRAHYlNZG9hHE7LgQV0bSIXQAMlu3+U0YpXM4rgTH/1LTeNLAZCGSj12iHGBW9nFcC1woKYcHjhfHMalIo1wwE3gkAlIkAWokuou3yHl5koQ/3Bcep3Sv5xTDpH0/wd6ykL/AAkLXhC0nadnD/mnsobLbLA0DMfbMDgnoASIOgVSA8E98C7uhSOClYaWwHBPG7vAigHqSJfJfoezwAtAJ5+C9PX9rSRqaN7Ub9VASQLysWAP/yl7/AvffeC/Pz8wGvt7e3w6OPPsr9zu3bt+HLL78k+sknn0BUVBQc21IBJ7fVCvVUPF/PxNdCZ1I1/GNaGfxzVjEMpXvhbEINef+HW+v8g1ytbe1IqAnQs/5/89aWQmdSNfSmVsD/YbQ7uRLOJ1WTz1rRH26tgxPb6oTvi86Pd76dSdXQnVwJ/ye1Avqd5dDvLIfOpGrIX+uFv0+qgq6kqiXnG4y2+9st9XBiWx3pM9TOpGoYzSiBf84qhgFnOZxPqoYzTB+ztnBiW12A/nBrHdR8owqioqLgiy++CIvtnk2ogaF0L/xr7iEYzSiBDsoGRXZ7hvo/2y5nDGwX++ZcYg38Q4oPXs4sgX/NPQSv5j0Ps7kHYSjda2h3p+JrIWdtEde2zgZJsY9E79v9veNb6yDbUWjK/v8poxTmPM/DQv5zMJt7EF7OLIHu5Eo4l8i3ebRdM/au1/dnE2rgX1yF8K+5h2DAWQ6NG8Nnu38T54PjW+ss6Q+pf1k9FlcPRzc3cN/TU/beFunxrXWQ5TgCx+Lqpb8jUtGXiPQ7AAAIrUlEQVS4ciyu3vD49DnzjqGnRzc3QKbjEBw3cd3sbxvp32xugGNx9VKfle33v91ST7Tq6+ZsdznKigXAzz77DKKiouDWrVsBr587dw6cTif3O6dPn4aoqCilSkOin376qbJdpXelKttVereqrO0uR1nxAPjuu+8GvP6jH/0I0tLSuN9hn0R/85vfQFRUFHzyyScBr99t+umnn5IbIdznshKv4YsvvoBPP/0U/ud//kfZ7grq9+VwDcp2V2a/L4drMGu7y1FWLABamYpg5csvtVyUL7+8u3MIlsN1LIdrkBVlu4uyHK5jOVyDrCjbXZTlcB3L4RpWsqxYAATQkpGbmpoCXsvIyDCdjHy3G/9yuI7lcA1mRNmuJsvhOpbDNZgRZbuaLIfrWA7XsJJlRQMgliN4+eWX4aOPPoIXXngBYmJi4Ne//rXU95eL8S+H61gO12BGlO1qshyuYzlcgxlRtqvJcriO5XANK1lWNAACaAVJ4+PjYfXq1ZCXlwdvvfWW9Hdv374Np0+fhtu3b4fwDEMvy+E6lsM1mBVlu8vjOpbDNZgVZbvL4zqWwzWsZFnxAKhEiRIlSpQoUbLSRAGgEiVKlChRokTJChMFgEqUKFGiRIkSJStMFAAqUaJEiRIlSpSsMFEAqESJEiVKlChRssJEAaBFGRgYgISEBFizZg3k5eXB22+/He5TIsLbOmnjxo3k/a+++gpOnz4NsbGxsHbtWnjsscfgF7/4RcAxbt++Da2trfDQQw9BdHQ0HDhwIORb5rz11luwf/9+iI2NhaioKFhYWAh4P1jn/Yc//AHKyspg/fr1sH79eigrK4P/+q//Cum1RZpEqv0q21W2ayTKdoMrynZXrigAtCBYx2pkZAQ++ugj+P73vw8xMTHwm9/8JtynBgDaQJSVlQW//e1vif7ud78j73d2dsK6devg1VdfhQ8//BCKioogNjYW/vjHP5LPNDY2QlxcHNy8eRM++OAD2Lt3L+Tk5MBf//rXkJ33a6+9BidOnIBXX32VOxAF67yffvppcLlc8O6778K7774LLpcL9u/fH7LrijSJZPtVtqtsV0+U7QZflO2uXFEAaEF27NgBjY2NAa+lp6dLV7IPtZw+fRpycnK473311VewadMm6OzsJK/dvn0bNmzYAENDQwAA8MUXX8CqVavglVdeIZ/57LPP4J577oHr16+H9uT9wg5EwTrvjz76CKKiouD9998nn3nvvfcgKioK/uM//iPUlxUREsn2q2xX2a6eKNsNrSjbXVmiANCkBGMvy1DL6dOnITo6GmJjYyEhIQGKiorg448/BgCAjz/+GKKiouCDDz4I+M4zzzwDFRUVAADw+uuvQ1RUFPzhD38I+Izb7YZTp07dkWtgB6JgnffLL78MGzZsWPJ7GzZsgLGxsWBfRsRJpNuvsl1luyJRtht6Uba7skQBoEn57LPPICoqCm7duhXw+rlz58DpdIbprALltddeg7m5Ofj5z38ON2/ehMceeww2btwIv//97+HWrVsQFRUFn332WcB36urqYN++fQAA8OMf/xhWr1695LhPPfUU1NfX35FrYAeiYJ33uXPnIDU1dclnUlNT4fz588G8hIiUSLdfZbuBomx3UZTthl6U7a4sUQBoUnAQevfddwNe/9GPfgRpaWlhOit9+dOf/gQbN26E7u5uckN//vnnAZ+pra2F73znOwAgvqGffPJJaGhouCPnLBqI7J63yFmkpKTA3/3d3wXzEiJS7jb7VbarbBdF2W7oRdnuyhIFgCYl0qchRPLkk09CY2OjmopY4VMRd6P9KttVtgugbPdOiLLdlSUKAC3Ijh07oKmpKeC1jIyMiEhE5snt27chLi4OOjo6SFJvV1cXef8vf/kLN6l3ZmaGfObzzz+PiGRku+eNycj/9m//Rj7z/vvvr6hk5LvJfpXtKtulRdluaEXZ7soSBYAWBEsRvPzyy/DRRx/BCy+8ADExMfDrX/863KcGAABHjx6Fn/70p/CrX/0K3n//fdi/fz+sW7eOnF9nZyds2LAB5ufn4cMPP4SSkhLusv4tW7bAT37yE/jggw/g29/+dsjLEfz3f/83/OxnP4Of/exnEBUVBT09PfCzn/2MlHgI1nk//fTT4Ha74b333oP33nsPsrOzV1Q5gki2X2W7ynb1RNlu8EXZ7soVBYAWZWBgAOLj42H16tWQl5cHb731VrhPiQjWaVq1ahVs3rwZDh48CL/85S/J+1jYc9OmTbBmzRp49NFH4cMPPww4xp///GdobW2FBx98EBwOB+zfvx8++eSTkJ73m2++uaSQalRUFPh8vqCe93/+53+C1+uFdevWwbp168Dr9a64gqSRar/KdpXtGomy3eCKst2VKwoAlShRokSJEiVKVpgoAFSiRIkSJUqUKFlhogBQiRIlSpQoUaJkhYkCQCVKlChRokSJkhUmCgCVKFGiRIkSJUpWmCgAVKJEiRIlSpQoWWGiAFCJEiVKlChRomSFiQJAJUqUKFGiRImSFSYKAJUoUaJEiRIlSlaYKABUokSJEiVKlChZYaIAUIkSJUqUKFGiZIWJAkAlSpQoUaJEiZIVJgoAlShRokSJEiVKVpgoAFSiRIkSJUqUKFlhogBQiRIlSpQoUaJkhYkCQCVKlChRokSJkhUmCgCVKFGiRIkSJUpWmCgAVKJEiRIlSpQoWWGiAFCJEiVKlChRomSFiQJAJUqUKFGiRImSFSYKAJUoUaJEiRIlSlaYKABUokSJEiVKlChZYaIAUIkSJUqUKFGiZIWJAkAlSpQoUaJEiZIVJgoAlShRokSJEiVKVpgoAFSiRIkSJUqUKFlhogBQiRIlSpQoUaJkhYkCQCVKlChRokSJkhUmCgCVKFGiRIkSJUpWmCgAVKJEiRIlSpQoWWGiAFCJEiVKlChRomSFiQJAJUqUKFGiRImSFSYKAJUoUaJEiRIlSlaY/H+pIpNEvG7vCQAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = subplots(2,3)\n",
    "for a,i in zip(ax.ravel(), images):\n",
    "    jupyter.display(i, ax=a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "intelligent-carter",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = numpy.min(images, axis=0)<0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "nuclear-fluid",
   "metadata": {},
   "outputs": [],
   "source": [
    "for ai in geometries:\n",
    "    ai.detector.mask = mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "secure-patio",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LaB6 Calibrant with 151 reflections at wavelength 6.199209921660013e-11 20.0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "6.199209921660013e-11"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wavelength = geometries[0].wavelength\n",
    "LaB6 = get_calibrant(\"LaB6\")\n",
    "LaB6.wavelength = wavelength\n",
    "energy = pyFAI.units.hc/wavelength*1e-10\n",
    "print(LaB6, energy)\n",
    "pyFAI.units.hc/energy*1e-10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "hollow-accuracy",
   "metadata": {},
   "outputs": [],
   "source": [
    "goniotrans = ExtendedTransformation(param_names = [\"dist0\", \"scale0\", \n",
    "                                                   \"poni1\", \"scale1\",\n",
    "                                                   \"poni2\", \"scale2\",\n",
    "                                                   \"rot1\", \"rot2\", \n",
    "                                                   \"energy\"],\n",
    "                                    dist_expr=\"dist0  + pos*scale0\",\n",
    "                                    poni1_expr=\"poni1 + pos*scale1\",\n",
    "                                    poni2_expr=\"poni2 + pos*scale2\",\n",
    "                                    rot1_expr=\"rot1\",\n",
    "                                    rot2_expr=\"rot2\",\n",
    "                                    rot3_expr=\"0\",\n",
    "                                    wavelength_expr=\"hc/energy*1e-10\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "medieval-japan",
   "metadata": {},
   "outputs": [],
   "source": [
    "param = {\"dist0\":   0.0,\n",
    "         \"poni1\":  0.27,\n",
    "         \"poni2\":  0.13,\n",
    "         \"rot1\":   0.0,\n",
    "         \"rot2\":   0.0,\n",
    "         \"scale0\": 0.001,\n",
    "         \"scale1\": 0.0,\n",
    "         \"scale2\": 0.0,\n",
    "         \"energy\": energy,\n",
    "        }\n",
    "#Defines the bounds for some variables\n",
    "bounds = {\"dist0\":  ( -0.1, 0.1),\n",
    "          \"poni1\":  ( 0.0, 0.4),\n",
    "          \"poni2\":  ( 0.0, 0.3),\n",
    "          \"rot1\":   (-1.0, 1.0),\n",
    "          \"rot2\":   (-1.0, 1.0),\n",
    "          \"scale0\": (-1.1, 1.1),\n",
    "          \"scale1\": (-1.1, 1.1),\n",
    "          \"scale2\": (-1.1, 1.1),\n",
    "          \"energy\": (energy-1,energy+1)\n",
    "         }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "adolescent-fields",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "174.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def distance(filename):\n",
    "    base = os.path.splitext(os.path.basename(filename))[0]\n",
    "    return float(base.split(\"_\")[-1][:-2])\n",
    "distance(pts[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "german-pastor",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty refinement object: GoniometerRefinement with 0 geometries labeled: .\n",
      "lab6_500mu_20keV_CRL0_174mm.npt 174.0\n",
      "lab6_500mu_20keV_CRL0_274mm.npt 274.0\n",
      "lab6_500mu_20keV_CRL0_374mm.npt 374.0\n",
      "lab6_500mu_20keV_CRL0_474mm.npt 474.0\n",
      "lab6_500mu_20keV_CRL0_574mm.npt 574.0\n",
      "lab6_500mu_20keV_CRL0_674mm.npt 674.0\n",
      "Populated refinement object: GoniometerRefinement with 6 geometries labeled: lab6_500mu_20keV_CRL0_174mm.npt, lab6_500mu_20keV_CRL0_274mm.npt, lab6_500mu_20keV_CRL0_374mm.npt, lab6_500mu_20keV_CRL0_474mm.npt, lab6_500mu_20keV_CRL0_574mm.npt, lab6_500mu_20keV_CRL0_674mm.npt.\n"
     ]
    }
   ],
   "source": [
    "gonioref = GoniometerRefinement(param, #initial guess\n",
    "                                bounds=bounds,\n",
    "                                pos_function=distance,\n",
    "                                trans_function=goniotrans,\n",
    "                                detector=geometries[0].detector, \n",
    "                                wavelength=None)\n",
    "print(\"Empty refinement object:\", gonioref)\n",
    "for i,f in zip(images, pts):\n",
    "    sg = gonioref.new_geometry(f, image=i, metadata=f, control_points=f, calibrant=LaB6)\n",
    "    print(f, sg.get_position())\n",
    "print(\"Populated refinement object:\", gonioref)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "drawn-dollar",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 1.4385584060425726e-05\n",
      "[0.0e+00 1.0e-03 2.7e-01 0.0e+00 1.3e-01 0.0e+00 0.0e+00 0.0e+00 2.0e+01]\n",
      "     fun: 6.051269858900252e-08\n",
      "     jac: array([ 2.49951010e-07, -7.20807123e-05,  7.86336214e-08,  6.89405358e-05,\n",
      "       -9.38068436e-07, -6.56028473e-05,  4.19462335e-07, -7.18186071e-08,\n",
      "        1.45283814e-07])\n",
      " message: 'Optimization terminated successfully'\n",
      "    nfev: 260\n",
      "     nit: 22\n",
      "    njev: 22\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([-3.61862566e-04,  1.00200701e-03,  2.70539710e-01, -1.36405226e-06,\n",
      "        1.28784525e-01,  2.37496904e-06,  2.21087894e-03,  2.92650014e-03,\n",
      "        2.00000886e+01])\n",
      "Cost function after refinement: 6.051269858900252e-08\n",
      "GonioParam(dist0=-0.0003618625661814575, scale0=0.0010020070132358355, poni1=0.2705397104585412, scale1=-1.3640522556111816e-06, poni2=0.1287845246256937, scale2=2.374969044353745e-06, rot1=0.0022108789354605015, rot2=0.002926500137512136, energy=20.000088570908787)\n",
      "maxdelta on: rot2 (7) 0.0 --> 0.002926500137512136\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-3.61862566e-04,  1.00200701e-03,  2.70539710e-01, -1.36405226e-06,\n",
       "        1.28784525e-01,  2.37496904e-06,  2.21087894e-03,  2.92650014e-03,\n",
       "        2.00000886e+01])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gonioref.refine2()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "welsh-alabama",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 6.051269858900252e-08\n",
      "[-3.61862566e-04  1.00200701e-03  2.70539710e-01 -1.36405226e-06\n",
      "  1.28784525e-01  2.37496904e-06  2.21087894e-03  2.92650014e-03\n",
      "  2.00000886e+01]\n",
      " final_simplex: (array([[-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01],\n",
      "       [-4.07046434e-04,  1.00343416e-03,  2.70523135e-01,\n",
      "        -2.16450380e-07,  1.28785994e-01,  2.67270526e-06,\n",
      "         2.46401138e-03,  1.98549771e-03,  2.00226614e+01]]), array([5.69967265e-08, 5.69967265e-08, 5.69967265e-08, 5.69967265e-08,\n",
      "       5.69967265e-08, 5.69967265e-08, 5.69967265e-08, 5.69967265e-08,\n",
      "       5.69967265e-08, 5.69967265e-08]))\n",
      "           fun: 5.699672646712962e-08\n",
      "       message: 'Optimization terminated successfully.'\n",
      "          nfev: 1652\n",
      "           nit: 1027\n",
      "        status: 0\n",
      "       success: True\n",
      "             x: array([-4.07046434e-04,  1.00343416e-03,  2.70523135e-01, -2.16450380e-07,\n",
      "        1.28785994e-01,  2.67270526e-06,  2.46401138e-03,  1.98549771e-03,\n",
      "        2.00226614e+01])\n",
      "Cost function after refinement: 5.699672646712962e-08\n",
      "GonioParam(dist0=-0.0004070464344764765, scale0=0.0010034341583563145, poni1=0.2705231348153043, scale1=-2.164503804312851e-07, poni2=0.1287859938925323, scale2=2.6727052589120153e-06, rot1=0.0024640113833614245, rot2=0.0019854977134011365, energy=20.022661370176756)\n",
      "maxdelta on: energy (8) 20.000088570908787 --> 20.022661370176756\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-4.07046434e-04,  1.00343416e-03,  2.70523135e-01, -2.16450380e-07,\n",
       "        1.28785994e-01,  2.67270526e-06,  2.46401138e-03,  1.98549771e-03,\n",
       "        2.00226614e+01])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gonioref.refine2(method=\"simplex\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "superior-bennett",
   "metadata": {},
   "outputs": [],
   "source": [
    "gonioref.save(\"table.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "swiss-triple",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"content\": \"Goniometer calibration v2\",\n",
      "  \"detector\": \"Pilatus CdTe 2M\",\n",
      "  \"detector_config\": {},\n",
      "  \"wavelength\": 6.192193741930409e-11,\n",
      "  \"param\": [\n",
      "    -0.0004070464344764765,\n",
      "    0.0010034341583563145,\n",
      "    0.2705231348153043,\n",
      "    -2.164503804312851e-07,\n",
      "    0.1287859938925323,\n",
      "    2.6727052589120153e-06,\n",
      "    0.0024640113833614245,\n",
      "    0.0019854977134011365,\n",
      "    20.022661370176756\n",
      "  ],\n",
      "  \"param_names\": [\n",
      "    \"dist0\",\n",
      "    \"scale0\",\n",
      "    \"poni1\",\n",
      "    \"scale1\",\n",
      "    \"poni2\",\n",
      "    \"scale2\",\n",
      "    \"rot1\",\n",
      "    \"rot2\",\n",
      "    \"energy\"\n",
      "  ],\n",
      "  \"pos_names\": [\n",
      "    \"pos\"\n",
      "  ],\n",
      "  \"trans_function\": {\n",
      "    \"content\": \"ExtendedTransformation\",\n",
      "    \"param_names\": [\n",
      "      \"dist0\",\n",
      "      \"scale0\",\n",
      "      \"poni1\",\n",
      "      \"scale1\",\n",
      "      \"poni2\",\n",
      "      \"scale2\",\n",
      "      \"rot1\",\n",
      "      \"rot2\",\n",
      "      \"energy\"\n",
      "    ],\n",
      "    \"pos_names\": [\n",
      "      \"pos\"\n",
      "    ],\n",
      "    \"dist_expr\": \"dist0  + pos*scale0\",\n",
      "    \"poni1_expr\": \"poni1 + pos*scale1\",\n",
      "    \"poni2_expr\": \"poni2 + pos*scale2\",\n",
      "    \"rot1_expr\": \"rot1\",\n",
      "    \"rot2_expr\": \"rot2\",\n",
      "    \"rot3_expr\": \"0\",\n",
      "    \"wavelength_expr\": \"hc/energy*1e-10\",\n",
      "    \"constants\": {\n",
      "      \"pi\": 3.141592653589793,\n",
      "      \"hc\": 12.398419843320026,\n",
      "      \"q\": 1.602176634e-19\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "print(open(\"table.json\").read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "seventh-cancellation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6.192193741930409e-11, None)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gonioref.wavelength, gonioref._wavelength"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "contrary-biology",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total execution time: 7.503s\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total execution time: {time.perf_counter()-start_time:.3f}s\")"
   ]
  }
 ],
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