09_MnTe_corefinement_solution.ipynb

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   "source": [
    "# Module 9: Unguided corefinement for MnTe"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "MnTe is an antiferromagnet with a Neel temperature of 307 K. A file containing neutron PDF data collected on the NOMAD instrument at 320 K is found in the files directory (NOM_MnTe_320K.gr), along with a CIF file for the atomic structure of MnTe. Your task is to perform a corefinement (either simultaneous or iterative) of the atomic and magnetic structure of MnTe at 320 K (MnTe_hex.cif). You may want to start by looking up MnTe on MAGNDATA to help you think about how to define the magnetic structure. Keep in mind that this measurement was done in the paramagnetic state, so the magnetic correlation length will be finite."
   ]
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import least_squares\n",
    "\n",
    "from diffpy.mpdf import *\n",
    "from diffpy.structure.parsers import getParser\n",
    "from diffpy.srfit.pdf import PDFGenerator, PDFParser\n",
    "from diffpy.srfit.fitbase import FitRecipe, FitResults\n",
    "from diffpy.srfit.fitbase import Profile, FitContribution\n",
    "from diffpy.structure import loadStructure\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lattice=Lattice(a=4.193, b=4.193, c=6.752, alpha=90, beta=90, gamma=120)\n",
      "Te   0.333333 0.666667 0.250000 1.0000\n",
      "Te   0.666667 0.333333 0.750000 1.0000\n",
      "Mn   0.000000 0.000000 0.000000 1.0000\n",
      "Mn   0.000000 0.000000 0.500000 1.0000\n"
     ]
    }
   ],
   "source": [
    "struc = loadStructure('files/MnTe_hex.cif')\n",
    "print(struc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
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   "source": [
    "def combined_fit(dataFile, structureFile, rmin=1.5, rmax=20.0, method='corefinement'):\n",
    "    \"\"\"\n",
    "    method = 'corefinement': true simultaneous corefinement of atomic and magnetic parameters\n",
    "    method = 'toggle': iterative fit that toggles between atomic and magnetic parameters\n",
    "    \"\"\"\n",
    "    # load in the starting structure\n",
    "    pcif = getParser('cif')\n",
    "    struc = pcif.parseFile(structureFile)\n",
    "\n",
    "    # prepare profile object with experimental data\n",
    "    profile = Profile()\n",
    "    parser = PDFParser()\n",
    "    parser.parseFile(dataFile)\n",
    "    profile.loadParsedData(parser)\n",
    "    \n",
    "    # define qdamp and qbroad (determined previously from calibration fits)\n",
    "    qdamp = 0.025\n",
    "    qbroad = 0.025\n",
    "\n",
    "    # set up calculation range for the PDF simulation\n",
    "    rstep = 0.01\n",
    "    profile.setCalculationRange(xmin=rmin, xmax=rmax, dx=rstep)\n",
    "\n",
    "    # prepare the function that calculates the atomic PDF\n",
    "    nucpdf = PDFGenerator(\"nucpdf\") # this will calculate the atomic PDF\n",
    "    nucpdf.setStructure(struc)\n",
    "    nucpdf.setProfile(profile)\n",
    "\n",
    "    # prepare a FitContribution object that will include the atomic and magnetic PDF\n",
    "    totpdf = FitContribution('totpdf')\n",
    "    totpdf.addProfileGenerator(nucpdf) # we'll add the mPDF later\n",
    "    totpdf.setProfile(profile)\n",
    "\n",
    "    # set up the MagSpecies\n",
    "    mspec = MagSpecies(struc=struc,rmaxAtoms=rmax,ffparamkey='Mn2')\n",
    "    mspec.strucIdxs = [2, 3] # determined from previous inspection of the unit cell\n",
    "    mspec.basisvecs = np.array([1, -1, 0]) # any vector perpendicular to the c axis will be fine\n",
    "    mspec.kvecs = np.array([0, 0, 1]) # this gives the desired AF structure for this choice of unit cell\n",
    "\n",
    "    # set up the MagStructure\n",
    "    mstruc = MagStructure(rmaxAtoms=rmax)\n",
    "    mstruc.loadSpecies(mspec)\n",
    "    mstruc.makeAll() ### populates the spin and atom arrays\n",
    "\n",
    "    # create the MPDFcalculator for MnO\n",
    "    mc = MPDFcalculator(magstruc=mstruc,qdamp=qdamp,rmax=rmax,rmin=rmin)\n",
    "\n",
    "    # Define an mPDF function that will be added to the total PDF calculator\n",
    "    def mpdf(ordscale, parascale, xi):\n",
    "        \"\"\"\n",
    "        ordscale = ordered scale factor (mc.ordScale)\n",
    "        parascale = paramagnetic scale factor (mc.paraScale)\n",
    "        xi = correlation length (mstruc.corrLength)\n",
    "        \"\"\"\n",
    "        mc.ordScale = ordscale\n",
    "        mc.paraScale = parascale\n",
    "        mstruc.corrLength = xi\n",
    "        mstruc.makeAll() # regenerate the spins in each function call to use the latest structural parameters\n",
    "        # return the \"unnormalized\" mPDF\n",
    "        rcalc, fcalc, dcalc = mc.calc(both=True)\n",
    "        return dcalc\n",
    "\n",
    "    # add mPDF to the FitContribution\n",
    "    totpdf.registerFunction(mpdf)\n",
    "    totpdf.setEquation(\"nucscale * nucpdf + mpdf(ordscale,parascale,xi)\")\n",
    "\n",
    "    # Make magnetic PDF depend on any changes to the atomic structure.\n",
    "    # A structure change will now trigger reevaluation of the mPDF.\n",
    "    nucpdf.phase.addObserver(totpdf.ordscale.notify)\n",
    "\n",
    "    # set up the FitRecipe\n",
    "    fit = FitRecipe()\n",
    "    fit.addContribution(totpdf)\n",
    "\n",
    "    # fix qdamp and qbroad based on prior information\n",
    "    fit.addVar(nucpdf.qdamp, qdamp, fixed=True, name='qdamp')\n",
    "    fit.addVar(nucpdf.qbroad, qbroad, fixed=True, name='qbroad')\n",
    "\n",
    "    # Configure the fit variables and give them to the recipe.\n",
    "    from diffpy.srfit.structure import constrainAsSpaceGroup\n",
    "    sgpars = constrainAsSpaceGroup(nucpdf.phase, pcif.spacegroup.short_name) # this loads in the space group symmetry constraints\n",
    "\n",
    "    for par in sgpars.latpars:\n",
    "        fit.addVar(par,tag='LatPars') # we will use these tags later\n",
    "    for par in sgpars.adppars:\n",
    "        fit.addVar(par, value=0.003, tag='ADPs')\n",
    "\n",
    "    # note that there are no positional degrees of freedom (i.e. xyz parameters) for this structure\n",
    "        \n",
    "    fit.addVar(totpdf.nucscale, 0.05, name='nucscale')\n",
    "    fit.addVar(nucpdf.delta1, value=1.0, name='delta1')\n",
    "\n",
    "    # mPDF parameters\n",
    "    fit.addVar(totpdf.parascale, 0, tag='Mag')\n",
    "    rstPs = fit.restrain(totpdf.parascale,lb=0,ub=10.0,sig=0.0001) # set reasonable bounds\n",
    "    fit.addVar(totpdf.ordscale, 0.0, tag='Mag')\n",
    "    rstOs = fit.restrain(totpdf.ordscale,lb=0,ub=10.0,sig=0.0001)\n",
    "    fit.addVar(totpdf.xi, 10, tag='Mag')\n",
    "    rstXi = fit.restrain(totpdf.xi,lb=0.5,ub=1000.0,sig=0.0001)\n",
    "\n",
    "    # Turn off printout of iteration number.\n",
    "    fit.clearFitHooks()\n",
    "    fit.fix('all')\n",
    "\n",
    "    # Now we set up either an iterative fit or a true corefinement\n",
    "    if method == 'corefinement':\n",
    "        # Our approach will be to introduce the parameters one group at a time.\n",
    "        # We begin with the structural parameters and then add the magnetic parameters.\n",
    "        # start with scale factor and lattice parameters\n",
    "        fit.free('nucscale')\n",
    "        fit.free('LatPars') # we use the tag LatPars to free all the lattice parameters\n",
    "        print(fit.names)\n",
    "        least_squares(fit.residual,fit.values)\n",
    "\n",
    "        # skipping xyz parameters because there are none in this symmetry\n",
    "\n",
    "        # add the ADps\n",
    "        fit.free('ADPs')\n",
    "        print(fit.names)\n",
    "        least_squares(fit.residual,fit.values)\n",
    "\n",
    "        # add delta1\n",
    "        fit.free('delta1')\n",
    "        print(fit.names)\n",
    "        least_squares(fit.residual,fit.values)\n",
    "\n",
    "        # add the magnetic parameters\n",
    "        fit.free('Mag')\n",
    "        print(fit.names)\n",
    "        least_squares(fit.residual,fit.values) # this is now refining all variables jointly\n",
    "\n",
    "    if method == 'toggle':\n",
    "        # In this approach, we toggle between just structural parameters and just magnetic parameters.\n",
    "        # We iterate back and forth three times (usually sufficient to ensure complete convergence).\n",
    "        numIterations = 3 # number of times to toggle between atomic and magnetic parameters\n",
    "        for i in range(numIterations):\n",
    "            # start with scale factor and lattice parameters\n",
    "            fit.free('nucscale')\n",
    "            fit.free('LatPars') # we use the tag LatPars to free all the lattice parameters\n",
    "            print(fit.names)\n",
    "            least_squares(fit.residual,fit.values)\n",
    "\n",
    "            # skipping xyz parameters because there are none in this symmetry\n",
    "\n",
    "            # add the ADps\n",
    "            fit.free('ADPs')\n",
    "            print(fit.names)\n",
    "            least_squares(fit.residual,fit.values)\n",
    "\n",
    "            # add delta1\n",
    "            fit.free('delta1')\n",
    "            print(fit.names)\n",
    "            least_squares(fit.residual,fit.values)\n",
    "\n",
    "            # now fix all the atomic parameters and free the magnetic parameters\n",
    "            fit.fix('all')\n",
    "\n",
    "            fit.free('Mag')\n",
    "            print(fit.names)\n",
    "            magOpt = least_squares(fit.residual,fit.values)\n",
    "            \n",
    "            if i < (numIterations - 1):\n",
    "                fit.fix('all') # fix all the parameters and start the loop again\n",
    "\n",
    "    # Display results and plot the fit\n",
    "    r = fit.totpdf.profile.x\n",
    "    gobs = fit.totpdf.profile.y\n",
    "\n",
    "    # Get the calculated PDF and compute the difference between the calculated and\n",
    "    # measured PDF\n",
    "    totcalc = fit.totpdf.evaluate() # calculated combined atomic and magnetic PDF\n",
    "    magcalc = mpdf(fit.ordscale.value,fit.parascale.value,fit.xi.value) # just mPDF\n",
    "    nuccalc = totcalc - magcalc # just atomic PDF\n",
    "    baseline = 1.2 * gobs.min()\n",
    "    nucdiff = gobs - nuccalc\n",
    "    totdiff = gobs - totcalc # total fit residual\n",
    "    results = FitResults(fit)\n",
    "    print('Rw = '+str(results.rw))\n",
    "\n",
    "    # Plot the structural refinement\n",
    "    ax=plt.figure().add_subplot(111)\n",
    "    ax.plot(r, gobs, 'bo', label=\"G(r) data\",markerfacecolor='none', markeredgecolor='b')\n",
    "    ax.plot(r, totcalc, 'r-', lw=1.5, label=\"Total fit\")\n",
    "    ax.plot(r, nucdiff + baseline, marker='o',mec='Gray',mfc='None')\n",
    "    ax.plot(r, magcalc + baseline, marker='None',color='Blue',lw=2, label='mPDF fit')\n",
    "    ax.plot(r, totdiff+1.4*baseline, 'g-')\n",
    "    ax.plot(r, np.zeros_like(r) + 1.4*baseline, 'k:')\n",
    "\n",
    "\n",
    "    ax.set_xlabel(r\"r ($\\mathdefault{\\AA}$)\")\n",
    "    ax.set_ylabel(r\"G ($\\mathdefault{\\AA^{-2}}$)\")\n",
    "    plt.legend()\n",
    "\n",
    "    plt.show()\n",
    "    \n",
    "    return fit"
   ]
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     "text": [
      "['a', 'c', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale', 'delta1']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale', 'delta1', 'parascale', 'ordscale', 'xi']\n",
      "Rw = 0.1017892836401424\n"
     ]
    },
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       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-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 = 'mpl-button-group';\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 = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 https://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",
       " * https://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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\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\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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",
       "    // 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"
    },
    {
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\" 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      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('a', 4.1522535258245545)\n",
      "('c', 6.724216477396914)\n",
      "('U11_0', 0.010079087261906526)\n",
      "('U33_0', 0.013586729589012534)\n",
      "('U11_2', 0.01709439420426118)\n",
      "('U33_2', 0.01632871258716953)\n",
      "('nucscale', 0.027942949079042007)\n",
      "('delta1', 1.5006177053984817)\n",
      "('parascale', 0.1160405001586272)\n",
      "('ordscale', 0.008048471829160918)\n",
      "('xi', 8.260279906748961)\n"
     ]
    }
   ],
   "source": [
    "dataFile = 'files/NOM_MnTe_320K.gr'\n",
    "structureFile = 'files/MnTe_hex.cif'\n",
    "\n",
    "fit = combined_fit(dataFile, structureFile, rmin=0.5, rmax=20, method='corefinement')\n",
    "\n",
    "# print out the refined parameter values\n",
    "for item in zip(fit.names, fit.values):\n",
    "    print(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['a', 'c', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale', 'delta1']\n",
      "['parascale', 'ordscale', 'xi']\n",
      "['a', 'c', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale', 'delta1']\n",
      "['parascale', 'ordscale', 'xi']\n",
      "['a', 'c', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale']\n",
      "['a', 'c', 'U11_0', 'U33_0', 'U11_2', 'U33_2', 'nucscale', 'delta1']\n",
      "['parascale', 'ordscale', 'xi']\n",
      "Rw = 0.10178935097282174\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-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 = 'mpl-button-group';\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 = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "                img\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 https://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",
       " * https://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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\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\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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",
       "    // 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": {
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       "<img 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OjU6duyIuHHjKmVJxrpv375gCsjPP/+MP//8EzI2USiuX7+OKVOmqHHs2bNHndhIkVObL774Am+99Zat/4QJEyozs1u3biFPnjxKQZL/Y8SIoU6G5MTm22+/VcpMWMWIzHC/ZljEwqxIBcR1hqa1QIE2DaVPNiT2xEWKBA39PSzDMtSzXaiL5ViJusHmJvfQJ8Qnl5uDJgESsICAkc2k0WHo39Fy8rFyZdh31amjnYRY+f0sjtiiDOzXnQZfD+/p06fq6b99SZkype1P2eCLD8W6detCVUBixYqlnNPDyiQvpxOyyZ8zZ064GEuXLo3Dhw/j+PHjEL8NKQ8fPlRmY6Ls2EfBkvHqZl56o6JQiOLRoEEDTJgwwdZXWD4gEqnrxYsXIZSxNm3aqJOb27dvq5OV0IoRmeF+zeinJux6VEBcZ2haCxRo01D6ZEOffgrYfa+iO0ZgBHra5jIkza/od+3zYHOTe8RRnYUESIAESCAkASObSaPcBg4EBg0Cli4F6gU9Gwpxu7zfoAEg9QcMMNq6a/XEB+Odd96Bn4NjipwmfPXVV8EaDwgIsPlsSEQscVyXTbl90U9AJHKWRNQKq4gjeuHChdXpQlhFzLvklKJdu3aYNGlSsGriwN6nT58ww/CKz4koUeJ/IpGurly5Atkr6cWIE7ooIqLsiFKyZs0afPTRRzhw4IBSfqiAuCZ3rtxNBcQVeibfSwXEZKA+1lzp0sC//wYN+if0RE+MsF34GT0wNNnPuHs3qI6Yw+7Y4WMT5XBJgARIwCICZiog4vowenTEJxsHDwKFCwNduwKjRlkz0bBOQC5cuICTJ0+qQYgfxz///ANnFJDu3btD/EvCKmJSVbRo0XAVkB07dijlSJQhewd4aVOc4sVkyv4EREIJi1/KggULlNmVfRG/lLNnzxpSQMRES8YuPiWifNgXiQpWXuzpQilGZIb7NdflmgqI6wxNa4ECbRpKn2yoYEHg8OGgoa9562PUuB6UFGoGPkZrzAg2N7lHfuxYSIAESIAEQhIwspk0ys2bT0CM+IDICcKMGTOCKSARmWCJb0d4yQaNmGBt374dZcqUUcqAKDT2RU5XxKzKXgGpU6eOMgn78ssvUaxYMRVKOHr06Bg2bBjOnDmjTLb0EtYJiCgvkiixVq1aaNy4sQoZLGOVfZY4woeX+NCIzHC/ZvRTE3Y9KiCuMzStBQq0aSh9siFxKt+zRxt6smTAwkc1UTkg6Fj7Qbk66JV/hXJ+1EuBAsChQz45XQ6aBEiABNxOwMhm0uggvNkHRI+CJQrGxx9/HOqUQlNAxNFb/DLsN/Vys30UrLAUEDldEQUmIid0cSIXBcCICZY40ctpTv/+/TFQND67IqcoV69eDTbWjBkzInv27CHygIhSI2ZWsv6ivOhF/Ec+/fRTKiBGhd6N9aiAuBGus01TAXGWWNSqL46N9nmgdqM4iiPI1hWlSmF86x0qwopeJGrijRtRiwNnQwIkQAJmETBTAZExeWsULPFxEF8MMV8SMys5OXAsEvZ25syZwU5AjIThDUsB0U8ZjIThlfC5R44cidAJXeYhJx4SqWqQONy8LtJH5cqVlaO9vbIkEa4kkpYoG/ZFTj1kTyWZ2iUClhTxJZH8KOJUzxMQsz5hkW+HCkjk2Zl+JxUQ05H6VIMVKwKbNgUN+QIyIiMu2S6cRnbkxOkQc7Iy0opPAeVgSYAE3ngCZisgkoSwTJmgPCDt2wPZsgHiliD+1Z7KAyILLRt8cSgXR209E3rixIlVjg9xTpecGOnTp1cbeP1UQE9EOGvWLLRs2dImL0ZOQD755BOsWrXKUCLCLVu2KAVCnNHlBEKUhrDC8FatWhVbt25Fly5dkDNnTuXDIXWzZMminMntFRAZ89y5czFgwAAVIljC8L733nsqRK84m9eoUUOZeN25cwfTp09X78teiwqI578aqIB4fg1sI6AC4kWL4YGhvP8+sHy53nEgniEu4sDfNpK7SIrksPNAf/2OlZFWPICFXZIACZBApAmYrYDIQLwxE7oOSE5Axo4diyVLlqj8HhJFSkya5HSkYcOGyjxLIl/ZF3HGlrC3oqDoJSIFRBL9iVmVJPaTSFZGyvr169G7d29bIkIxCQstEaEoTOKsLpG1JCSvjP27776DKElyEmKvgEguEskrIgqOKCd6IkIZz6+//qr+iamY5DCRELzii1KtWjUqIEYWzM11qIC4GbAzzVMBcYZW1KubOTNw4YI2r0R4gAdIEmKSMRGAl4iprotZ66tX1kZaiXrUOSMSIIGoTMAdCojOSwKALFkCFZlQ/PYk9K4v5mUSxaNu3brKNCl37tyGxEFOEzp37qxMnNKlS2foHl+pZERmuF9zfTWpgLjO0LQWKNCmofS5huyTEIpike7VRVxEphDzSI3ruInUwa7zBMTnlpsDJgESsIiAkc2kRUPx6m6qVKmiTgnEdCmiIiFt8+bNqxIQig9JVCtGZIb7NddXnQqI6wxNa4ECbRpKn2tID++YI4d2vJ8fh3EYBdU8LiE9MuCyep0Hx3ACeZA2LfDihWaHvGAB0Lixz02ZAyYBEiABtxMwspl0+yDYgU8RMCIz3K+5vqRUQFxnaFoLFGjTUPpcQ3qCq8SJgQcPgHewDdvwrprHDpRCaWgZCktiJ3ajJBIlAh4+1KbJExCfW24OmARIwCICRjaTFg2F3fgIASMyw/2a64tJBcR1hqa1QIE2DaXPNaSfgMjAJSN6kh1rsAa11DwWoSEaYbF6XQVrsR5V1Oto0YDAQPqA+Nxic8AkQAKWETCymbRsMOzIJwgYkRnu11xfSiogrjM0rQUKtGkofa6h+fOBDz4AJK9Hp07A0UHzMR8fqHmMxhfoijHqdQMsxlI0QJo0wLVr2jR5AuJzy80BkwAJWETAyGbSoqGwGx8hYERmuF9zfTGpgLjO0LQWKNCmofS5huxPQCSufOCkSZiEDmoei0sPR8MdX6vXH2MGZuFjpXSMHUsfEJ9baA6YBEjAUgJGNpOWDoideT0BIzLD/Zrry0gFxHWGprVAgTYNpc81pPuAJEkC3L8PdMcIjEBPNY9mmIs/0Fy9/irur/j52eeoVAnYsEGbJk9AfG65OWASIAGLCBjZTFo0FHbjIwSMyAz3a64vJhUQ1xma1gIF2jSUPteQfgKSMCHw6BEwEAMwAIPVPMpjEzajgnrdN9pQDA3so15L3HmJP9+1KzBqlM9NmQMmARIgAbcTMLKZdPsg2IFPETAiM9yvub6kVEBcZ2haCxRo01D6XEP2eUDq1AGqrPwSX0LTKrLhDM4iu3o9DL3xDYZBFJWePbXTD56A+Nxyc8AkQAIWETCymbRoKOzGRwgYkRnu11xfTCogrjM0rQUKtGkofa4hewWkXz8g6/dt0RbT8ArRUP3dJ1i7NZ6a01h0wucYq17Hjg34+wNyry9m3/W5ReKASYAEfI6Akc2kz02KA3YrASMyw/2a60tABcR1hqa1QIE2DaXPNaSbYOk+IPPQFE2xAI+iJcTkkQ/RuXtsxAoMwB+xPkLzgJkoUAA4fBiQvCHiM8JCAiRAAiQQkoCRzSS5kYA9ASMyw/2a6zJDBcR1hqa1QIE2DaXPNaQ7oefLBxw9CixHXdTFSlzDW0iLa7iJlEiJ2ziaqx7yn1zKExCfW2EOmARIwBMEjGwmPTGuqN7nwIEDMWjQIARKsqoIyo0bN/DFF19g/fr1uHnzJrp27Ypu3boha9asmDZtGlq3bh1RE6a+b0RmuF9zHTkVENcZmtYCBdo0lD7XUJcuwG+/acPOkQMYf7oKqmA9zkfPiqyvzuIcsiAL/sM6VEZVrEOmTEDv3lrOEPqA+Nxyc8AkQAIWETCymbRoKG7rJppkpTVQKlSogI0bN0ZYc+TIkUiePLlLG39nFJCWLVti4cKF+Pbbb5E5c2bkzZsXKVKkCKGAyB5p2bJlalxZsmSJcB6RrWBEZrhfiyzdoPuogLjO0LQWKNCmofS5hooVA/btgzKtqlIF+GD0O3gHO4D8+XFw7mEkeic/sj45ih0ojXewHQsWALlyAYULMwqWzy02B0wCJGAZASObScsG46aOZs+eHazlxYsXY8mSJfj555/x1ltv2d6T19WqVYtwFBkyZECOHDkMKSthNeaMApImTRqUKFECK1assDUnJyePHz9G3LhxETNmTHV98uTJaN++PTZs2ICKFStGOI/IVjAiM9yvRZYuFRDXybmhBQq0G6D6QJO6A7oeVleiYA1ZWRiFcRDPCpVE9SQ7McKvJEpiNw6gEIrggJqVbq7FExAfWGQOkQRIwCMEjGwmPTIwN3aqb/5PnTqlFAlni9UKSPTo0dG8eXM4KlKO46YC4uxKend9noB40fpQAfGixbBwKLoD+u+/A/37a9nNTyIncuI0tsSsgHIvNmJLrIp4N2ATTiM7utU5DTGrXbVKG+Ty5UDduhYOmF2RAAmQgI8QoAISpIDs3r0b/fv3x9atW+Hv748CBQqgZ8+e+OCDD2yrGZo5l5hFnT9/Xt0zdOhQrF69GsJVTiiyZcuGDh06KL8N+3uNnIDodRxF6dy5c+qSvQ9IWHXd4SNiRGa4X3P9C4AKiOsMTWuBAm0aSp9qSHdAl5OQ+PEB+S1Ytjc90uMKVqEW6mAVVqI2amM1riAthne9gjx5gM8+06ZZrhywebNPTZmDJQESIAFLCBjZTFoyEAs7Ce0EZPv27ahcuTKSJk2KTz/9FIkTJ8acOXOwZ88ejBkzBl3EERFQpxDiEC7mWn379lXXEiZMiPr16+PWrVvIkycPmjRpov6PESMG/v77b2U6Jf4bgwdryXOlGFFADh48CPn30UcfoUyZMvjs9Y9agwYNlDO6vQIi9WScU6ZMwTfffKP8RKTIfaIEmVmMyAz3a64TpwLiOkPTWqBAm4bSpxqyPwGZOxfw8wPuIBmS4R4WohGaYCFWJmiC2o8X4j4So2TO+zh1CkiVSjPD2rSJuUB8asE5WBIgAcsIGNlMWjYYizoKTQEpVaoUDh06hKNHj9ocuJ89e4Z33nkHJ0+exKVLl5BM7IABhGWC9fLlS7x48QJx4sQJNpM2bdooJ/Lbt28jtiSoMqiA6I3IyUmLFi2CmWDJiYtjFCyaYFkkQBZ1QwXEItBGuqECYoRS1Kuj+4DoiQVr1waWromDWK/8sSj+R2j8ZCamoTVaYwYCEBOxEaBOPaZO1XKBNGjASFhRTyo4IxIgATMIhKuAtGgBHD9uRjfmtSHH23PmuNSeowJy/fp1iKN327Zt1QmCfZk5cyZatWqFefPmoWnTpuEqIPb3iSLy8OFDiFKyZs0adYpx4MABFHqdFdfICQgVEJeW2edvpgLiRUtIBcSLFsPioUgCwgcPgObNgTkzXgCxYqkR3G7cEZe/HY+jlTrhwzu/q2uHdj9HweLaU6aDBxkJy+KlYnckQAI+RCBcBaR4cWDvXu+ajYRE3LPHpTE5KiA7duxQJx0SFatHjx7B2ha/kJIlS+KHH35Ar169IlRAxERrxIgR6jRFlA/7smnTJpQvX15dogLi0hK+ETdTAfGiZaYC4kWLYeFQHE9AGlV/iIX/JFYj2FKiG4al/gUVV32Fr/Czuta9zV207pYU8qBp6VKegFi4VOyKBEjAxwjwBCQHjCggP/74I77++utwFZAFCxaoU5JatWqhcePG6lRFTK5k7yLKi314XCogPvZB8cBwqYB4AHpYXVIB8aLFsHAojj4gJ/yu4zrSqBEMwTfohyEYiAEYAM3BLz0u4QrSKzOs6NHpA2LhUrErEiABHyNAH5AcCM8Ea9asWfj4448xf/585VwuJWPGjMiePXuIPCDiHC5mVsJUQufqZcKECcqx3d0KiJiPtWvXjnlAfOwzGNZwqYB40UJSAfGixbBwKPZRsORU49iqc8hbR4vq0RffYyj6Ykru4Wh7Qjse71jxBC7Fz2ULw1uiBLBrl4UDZlckQAIk4CMEqIBoYXhLly5tc0KXsLpSnj9/rqJIHT9+PJgTukS4EkdzUTbsi5yOWpzuAAAgAElEQVR6yD5F8otIBCwpT58+VUkExbnd3QrIn3/+iWbNmkESLYoy5K5iRGa4X3OdPhUQ1xma1gIF2jSUPtWQfgIi5lT16gHHFx9Fnkb51Ry+xEiMwpcYl+83fHZUC5PYq/o+HI5ZhAqIT60yB0sCJOAJAkY2k54Ylzv7DC8Mr0S6knC3iRIlUmF4xQfEPgyvjKtly5aYO3cuBgwYgFy5cqkwvO+9956KUiXO5jVq1FAKwJ07dzB9+nT1vuxf3K2AiOIj4xGfFZlDvHjxING9JFqWmcWIzHC/5jpxKiCuMzStBQq0aSh9qiHdB6RCBeDVK+CJ327sRkk1h44Yj4noiNaYhmloq669iy3YhndpguVTq8zBkgAJeIKAkc2kJ8blzj7DyoS+a9cuWyLCgIAA5M+fXyUi/PDDD4MN5+LFi+jYsSO2bNmiIl3piQil0q+//qr+XbhwAWnTpoWE4JVTlGrVqrldAZH+x44di5EjR+K///5TTvBMROhOSXJv21RA3MvXqdapgDiFK0pVLlkS2L1bm9JXpTdj+I4K6vX8ujMx49VHSLhqHuZB+5GY9dE/KNyzGp3Qo5QEcDIkQALuIPAmKiDu4PgmtWlEZrhfc10iqIC4ztC0FijQpqH0uYbsFZBvS67B4F211BxWtF6I3280QrRVK7AC72nzWrIEqF9fvWQYXp9bag6YBEjAQgJGNpMWDodd+QABIzLD/ZrrC0kFxHWGprVAgTYNpU815GiCldJvMRajkZpDLazCGtTCFwU3YPShyurahWFzkKl3c/WaYXh9aqk5WBIgAYsJGNlMWjwkduflBIzIDPdrri8iFRDXGdpaWL9+PapUqaL+FmepHDm06BNGCwXaKKmoVc/RCf3C0NnI1PcjNckW6Tei16oKiHfwX+T8qLS69lOuiaixoL0ywapTB8oZXZSY1wlooxYczoYESIAEXCBgZDPpQvO8NQoSMCIz3K+5vvBUQFxnqFrw9/dH4cKFIc5bjx8/pgJiEtc3oRnHMLyYOBHo2FFNvSR24l6Okohz+jAOo6C61hWjMAZdIfrt6dNQzuibN78JpDhHEiABEnCOgJHNpHMtsnZUJ2BEZqiAuC4FVEBcZ6haGDZsGEaNGoXmzZur/3kCYhLYN6AZxxOQy1+NQvqfv1Qzz4/DOIr8KJH8LHbdya6uTcw8BP2efIObN4Fo0YD//Q94ffD2BtDiFEmABEjAOAEjm0njrbHmm0DAiMxQAXFdEqiAuM5QhYPLly8ffvvtN/V60KBBVEBM4PqmNOHoA1LWb6hKPiglK87iPLIiNYKyo3+PvvgW3/ME5E0REM6TBEgg0gSMbCYj3ThvjJIEjMgMFRDXl54KiOsMUa9ePdy4cQPbtm1TygcVEBOgvmFN2EfB+iN7P3x4ZogiUKPQVcTMkAabVz3EQyRW13aU7ob4E36hD8gbJiOcLgmQgPMEjGwmnW+Vd0RlAkZkhgqI6xJABcRFhitWrFAKyM6dO1G8eHGElQDIsZurV69C/tmXY8eOqQyke/bsQbFixVwcGW/3JQL2CsjiLN3R4PwvavgDv7yPXScSY82ql3iJmNqU2reH8hNhFCxfWmKOlQRIwAMEjGwmPTAsdunFBIzIDBUQ1xeQCogLDJ8+faoyiUoG0AkTJmgbxoEDDZ2A6PVC654KiAuL4oO3OppgNfP7DJ9hvJpJLPjjBWIpR/O1W+IiduBz3K3TEslWzFLvMw+IDy44h0wCJGAZASObScsGw458goARmaEC4vpSUgFxgWG/fv0wbtw4nDx5EilTpnRKAeEJiAvgo9itjk7od95vheTLZ8IfsdDqQ3/06aOF2PVPmAyxH9/D0bwNke/oIkWBeUCimDBwOiRAAqYSMLKZNLVDNubzBIzIDBUQ15eZCkgkGV65cgXZsmVDt27d0K5dO1srY8aMwa+//op169YhS5Ysqo7RQoE2Sipq1QsRhrdJE2DhQtxDErSofQ8rV2rzfZo8PeLdvYItiWphbfdVaNgQSjlhHpCoJQ+cDQmQgHkEjGwmzeuNLUUFAkZkhvs111eaCkgkGe7fvx9FixYN9+4ECRLg0aNHhnugQBtGFaUq2p+AZMkCxGtSB7lOrcL1GGmR5uUVDB6shdqd4pcTOXEaG1EBlbDRxqBECWDXriiFhJMhARIgAVMIGNlMmtIRG4kyBIzIDPdrri83FZBIMrx//z7+J7tChzJ//nwsWLBAnYJkyJAB9evXN9wDBdowqihVUfcBSZYMuHsXWI9KSsE4jexK4dDLweiFUfDVQVxIUxIN0+/Enj3aO8mTA//+CxWWl4UESIAESCCIgJHNJHn5BoGXL1+if//+mD17Ni5duoSCBQtCHgaLtUnFihUxffp0UyZiRGa4X3MdNRUQ1xkGa8GoE3po3VKgTV4MH2nu1Ckgf34gIAAoUADY/LwUkp3aifuZCyLzvYO4f1+byHaURmn8i0MogEI4pBzTq1YFBgxgNnQfWWoO0wQCorB//z2wfTvw8iWQPj3QuzfQuLEJjbOJKEfAyGYyyk06khPauHEjKlWqZLs7WrRoSJo0KUqUKIFevXqhil3GW9nwb9q0yVZXLD7EF7Zw4cLqwWuzZs0QN27cYCMRBaFNmzahjk4C+hw+fDjckU+ePBnt27dX/8qWLav6q127dggF5M6dOxBzeBmj/HO2GJEZ7tecpRqyPhUQ1xlSATGZ4ZvWXPnygJ8fkCgR8PAhcC5hQWR5dBi3c5ZCylM7kDAhIJZ861AZlbEBd5Jlw6WNZ5RjupQ6degH8qbJzJs439OngQYNgLD2KPI5kaAMdnukNxET5+xAwMhmktA0AroC8sknn6iNu5w4CL/x48fj7t27WLNmDarKUy9AvX/w4EG10Zfy7NkzdSqxdu1abN26FXny5MGyZcuQM2dOG15dAendu7eKIGpfRNGpW7duuEvx4YcfYtWqVbh37x6iR49uq/vkyRPEiBEDceLEUddkzNLvgAEDVGRSZ4sRmaEC4ixVKiCuE3NjCxRoN8L10qZ186vatYHRo4G2bYFpftmRHWeVKVYVrFcjF/OsmXfroi5WAmnSAHY5ZBgJK/KLO38+MG4c1ClTkiTA55/zSXrkabrvTjkllNRIRlzq1q6lEuK+lfC9lo1sJn1vVu4Zsa6ATJo0KVhwnX379qncZDVr1sTq1attCoiwFaXDsYji0aRJE2TOnFmdasSOHVtV0RUQMV/XFRlnZlK5cmUVdTS0Pu3boQLiDFXP1eUJiOfYh+iZCogXLYZFQ3EMwSvdBqRKi1i3rmFz4jqo8GAFFiwAYsYEAho0QRMsBBIn1nbMrwtzgTi/WOvWAeKeFdqGVvAuXsxNrPNU3XeHfaJO6aVIzMPo/GIUVqIOlqJBsI7jxwceP3bfWNiybxF4UxQQfXMvCsK2bdswdepUdWohpkqiUGTKlEn5po4ePVpt4IsUKaKuix+FXsJSQOR9MXdKnjy5UgCkyAlIWAqIvD9o0CB1+iDj0M2uIquAOJqG6eOdNm0aWrduHcwEK6y6rVq1MuwjYkRmuF9z/XuACojrDE1rgQJtGkqfaShECF4ZuTyKf/AAR/I1RoGjC5RZSdaswL7CrdAKM4FYsQB/f9sceQLi3HKLn2IYZsjBGuKTdOe4uqu2fkqotx8bz3EG2ZEBl/EK0VAIB3EEBYJ1L1YhXbq4a0Rs15cIGNlM+tJ8whqrvrmX6JzieyHmSpIuYMSIEShUqBCaNm2KuXPnqg37gwcPMHz4cKRLlw7Hjx9X5ktSwlJAbt++jdSpU6NUqVJKuTGigFy4cEGdgEi/8+bNU/foY1y0aBHKi+2xXUmSJAliyW9bKOX69esq6M+QIUMgr3WzrzJlyqhUB/ZO6PK+OKn37NkTDRo0QEOJVw8ge/bseOeddwwttRGZ4X7NEMpwK1EBcZ2haS1QoE1D6TMNhXYCohSMFy9wp+7HSLFiBsQ8q3174GqDoAzpg/v5o36TWMoPhD4gxpdbTHly5TJWX3wKxCeHxbMEPv0UmDAhaAw1sAZrUMt2YVS8Pvjy6dBgg+QpiGfXzJt6D2szKYfIhw5500iDxiKHEvIcypmib+7FYXz79u2IKcfmAHr06IGRI0cia9asOHLkCOLFi6eui2Iim/R//vkH1apVU9d0BeSXX35By5Yt8erVK3XK0adPH2zevFlt/Lu81uwjOgGR9kSpkI2/7G2khOeEvnz58gh9QMLq0zEKFk2wnJEcz9WlAuI59iF6pgLiRYth0VDsfUAk4eCB3QEoXFKzl91V/FN8Gvg75LtbNlSDn/RAD4xU7yXGfTxEYhV6V5xzJSLW5s0WDdqHu8meHTh7NmgCCRMEou7jP3EDqbEeVULMTMzfGF3JswteurQWZlovg9Af/fGd7e+1qIJqWBtikPLZ0gM1eHYG7N2TBMJSQLZs0b43vbFIUJKyZZ0bmb65nzBhAjp06GC7eeHChcofQ8LXilmUXnbs2KFOBMaNG4fPPvtMXQ7LfEkiXEnS5e+++w4SGUuKEQVEUhGIwnNKnvzYKSBy+uKYR01MwsTMK7xCBcQ5mfD22lRAvGiFqIB40WJYOBQ9CpYoE9dPP8ADaI++RqA7emKEbSRDovXDN4FD1N9DPr+K0fPS4OZNQH4PJCUNo/+Ev2iOpjyi1HV+MhzD0Uvd6Nd3DeberoHx44PakbDI3vqU1EIR9WhX8jTYPvLVAjRGYyyyjelBzGRI8uI2AG1jpBc5Ofn9d48OnZ17AYE3TQGRSFU1atSwkZeoVHLCISFsJbqVXsT0Km/evPj+++/Rt29fdVlXQLp3745atWqpSFNyipEvXz7byYl+vxEFRO7NkSMH9rxOWhVZH5CI+uQJiBd80CIxBCogkYDmrluogLiLrHe3K74G1asDgYFA/hTXcPh2WjXg9WX6oeau71R+ECl9MBRDof1QZMVZnEdWnoA4sbT2pjyitAnvvSiKotivWpmHpvg60zxlAXfmjNawcv5/zd+JrljVRAIlSsCWdFOaPYz8yI+jwXr4sPR5zNuROdi1UqWAHTtMHAib8kkCb5oC4hhhSldAdIdtfRF1BURONfr166cuh+eE7rj4ESkg//33n/LN+OCDD/Dnn3+q26mA+ORHyG2DpgLiNrTON0wFxHlmUeEO+xOQl6fP4iyy2xSOH9BHmV89eQL8lGEUel76Ur03rtNhlO2Ynz4gTgiAoylPymQvcfFeQsQNfKZaOYNsyIHXmodduzTlcQKyG6pWqBBkXhgDL/AE8REbwbXCSliPjQhKoCbDkJMTiRDH8mYTeNN8QLxFAdGjYInSIRGorFRAzpw5o05emAfEuz/7VEC8aH28QQFhXgRrBcLRB+TEosPI3VgLi/hr9lH44kxXFQVr4kQg/aqJmIiO2gB37gQkNim05GuSoE0c2iUrOkvoBBwVkPyxTuJwQO5gld8t+gTb9mlOmnohV89K1OugcGoQGXEBF6CddPjFqIByL7VMzG0xBdPQNthA5eRk1y7Pjp29e56AkYhGnh+l6yMI63TBEycg4lDeuHFj5fguyQrNygNi1Afk2rVrSJs2Lb744gsVdtjZYkRmvGG/5uy8vK0+FRAvWhFPCjTzInhGEEJEwRLFQmxHAPxZZSKarWsPUVLEcXpRg1mYhY+1gW7cCMijYWhPeQsXBrp2BUaN8sw8fKHXJk2AhQuDRloPS0PkkMiJkziNoMy9UptcPbe6jn47pbADO6CF0hyCb9AXWvSr79AvmGO6XGvRApg923NjZ8/eQcDIZtI7RuraKDyhgNhnQn/+/DkuX76swuVu2bJF+ZdIQkI5idCLVSZY0l/GjBnh7++vnO9TpEihlCEJI2ykGJEZT+7XjMzBF+pQAfGiVfKUQDMvgueEIEQeEFEsKmmmJIsazEbjJS1seUAGFV6ERWisDVay0dasqV7yBMTY+jVrBrw2RVY3fIZxGIfOwW6ugrUhomHRmdkYX3fU0hV0ve0GWIzFaKT+FAVyIRojFl5gFlriY8wKNgRZ77lz3TEqtulLBIxsJn1pPmGN1RMKyKZN2gmklPjx46soVhLNqn79+mjWrJnKR2JfrFRAxJ9FwgxLJnZRjpiI0PuknAqIF62JJxQQ5kXwrAA4noCc/W0VsnWpowY1vvpifPZPA1sekAkNVmM1aqv35jVdhLx9G9IHxInlS58euHIl6AbHcK7yTmtMwwy0DtaqRKgcN86JjljVNAK6gq432Bm/4TdoGQaLYQ8WoRGy4jw2oTwqQtsM6QEG0qYNvt6mDYoN+RSBN0UB8alF8fLBGpEZT+zXvByb08OjAuI0Mvfd4AmBdsyLENHsmBchIkLOva+bmIg11atXQGq/hViIJqoRSbj2D7RwivIg6e1nm7AJFdXfLTELc9CSUbAM4nY05ZHbJqADOmBSsBb6YxC+Q/9g15o3B+bMMdgRq5lKQI9cpgdi+B59bWZXaXFFKSBlsB3HkRt5cTxE3wwgYOpy+GRjRjaTPjkxDtptBIzIjCf2a26bsIcapgLiIfChdWu1QDtuyiT8qIQcTZVK2/A+ewaVZ8K+MC+C+QIjvuS7d2vt/lxoJnoc1CKG+A3ZjB5Ly9kcad+JsRPbXmo2rItrTsCnezowD4jB5XA05ZHb/sL7eB/LcR+JkQQPVEsT0R4dMTFYq2+/HTwRnsEuWc0EAroCEiMG8PIlMBVt0AbT8RLRERv+SllvgCVqDZPifogeGUDAhEXw8SaMbCZ9fIocvskEjMiM1fs1k6foFc1RAfGKZdAGYbVAf97+OY5O3ooNqAz9Bz4iHKKk+PtHVIvvO0PAXgH5Nf94fH7kdVban3ah4dASuHtXay0/DuMwtAhZXTEKY9CVJyAGQTua8shtu6K/jRKvduEQCiA9LiM57mIJ6qMhliB2bCBNGuDCBU0hv3HDYEesZioB+3WTcNXfbK6BGvgHl5EOGXAZv6EzOkOzj4uPx0iWLj4SJABeJ15mAAFTV8M3GzOymfTNmXHU7iJgRGas3q+5a66ebJcKiCfpO/RtqUD/9x8O522M3E/3owI2YTvK2EaTKRNQrRpw4gSwZUtIQDRrME9oHE2wSviNxEj0UB3kwxEcQz4kSwbl63FhU1COkHVVhiLVyD70ATG4FPqT9Pz5gXPntLwq/yETMuEirhesgoAzF5HhyUlswbsohy2QekeOBDVOmTcI2uRq+rpJQsgXL4ADKIRCOIQ90YqjQ9HdaHDkO/R7rpnMSXLO5MWyYu9eKCXk8WOAAQRMXhAfbM7IZtIHp8Uhu5GAEZmxdL/mxrl6smkqIJ6k70kFRA+dBOAiMiA3TuAp4gcbUbp0QK5cWsRX+0KzBvOExtEJ/VqXIUjzm5aV9sNS5zDv3ywqypVk7f60wTVcg5YlHZK59rvv1EtGwYp4PfSNbPHiWq6U998HHiIhEuIx/sQHyIBLKIutOIFcyIMTqkHdmVleU+YjZuyOGo4+IDeREilxG8tRV5nPtcMkTEIH1XUZbFUPUuSUNnNm4PRpgAEE3LEqvtWmkc2kb82Io3U3ASMyQwXE9VWgAuI6Q9NasFqgJybpiQ4PRqjxf4XhGJ/wK6VwyBPE8Aqdck1bcoQIw9u3LzBUy23Qr/11DJmUWuUBkVKu8H3cR1Ltj+7dgRHa2jEPSMTrYW/KI2Hpz58OQABiqxvHoyPewnU0wFLcQTKkwB3oT9z1/5kLJGLG7qjRujUwY4bWcsH8r7D/SExERyCmoC3aYQrqYAVW4D31fkMswqo4DfH8edBIuG7uWBXfatPIZtK3ZsTRupuAEZmxer/m7jl7on0qIJ6gHkafVgv0Wwke4eCT7HgLN3ADqdRTYNmUiclPvXqaCdb27SEHW7EisGGDF4Hz4aGESET45Ze2bIJD+zxE32EJbScgTRoEbZrtH+3yBCRiAdA566ca6ePcwqXnqdSNo+L0QkL/O2gXqEXEigV/vEAsJEwIPHqktc0TkIgZu6OGnGSIH44ExYj37A7uIIXq5if0xNf4CaVj7sb2FyXVtU4Yi3nJO+HOnaCRcN3csSq+1ebZs2fx4sUL5JKnaywkYIDAyZMnETNmTGTLli3M2lbv1wwM2+eqUAHxoiWzUqB134M+GIqh6KsoyBPEJWgYIRFmGI4QkeEK+jrUrq0dfAS07YgSe7UoTAv+fIGmH8ZQeUCkrFoFvIoZC9HEGL5VK0AySAKoU0d7j34KYWO3j/gmJyCBp0/bMp73xjAkwsNg4V3F1K1ECS0DvWxoGX7asEibVtF+zSRMdZKbp/HXUS1LvazZj+iN9LiES8iortlnQ9dPrrhupi2HzzZ04cIFPH78WGXkjiX2eSwkEA6BgIAAyAlIggQJkEkcYsMoVu7XouqCUQHxopW1UqD1J8ISS/8iMiIGXtnsqiNCQsfOiAg59759FKyZ+AgfYTaeIQ7i4RkSJwYeaBFiUbQosO1oEsR9/gBH8jXByz/mY9s2zc69XDlg82bn+n2TattvZsePB+78sxt9FmtPzj/F70ib9BkG3PtS/V0QB5GsXEH4+QUR4pN066VF/44ShVH8OUpiJ3ZCC0PdAROU74ecVvkjjro2LWZ7PPh5IiZPBg4f1sbbpQswZoz1Y2eP3kPg3r17uHr1KhInToy0adMievTo3jM4jsSrCLx69UrJyoMHD5SsJE362uQ5lFFauV/zKkgmDoYKiIkwXW3KSoG2t4lfhVqohTV4jthIgdt4jIShTkU3X6Fjp6srHXS/hAstXVp7yi5lXdJGqHxvMZ7FT4Z389wJ4Y9zFWmQBtexAnXwHlaoe5In1/JUyEaNJXQC+mY2SRLg/n3ggxRr8eftaqryh/gDyeM/x7gnWgb0ctiM6znL2UK5yjX6ElgvWfp3lK6E18RqrIZ2HNg02gIsCGysXt9FUpUDZHOqhvix5CJ1GqgnLpRAGpcvWz929ug9BAIDA3H+/Hk8e/ZMKR8xJOY8CwmEQuDly5cQJSRu3LjIkiULosmmJ4xi5X4tqi4WFRAvWlkrBVqPLiPTl6eJE/CpItEIC7EYjcKlws2YeUIjuQ3kSfvgwcD//gf08dOUwUtIj4y4FKKjM8iGbDiHdaiMqlin3qcCEvF66JvZCROAr74Cqj5YhEXQNrCysY2D5/gL9dXf7+MvLMf76lRJFEMJx8tTv4gZm13DPnmkfD4kHf23J1qqbiphPTaiknp9CjmQA2ewCeVREZtQrBjQrh3QqZM2Ipommr0yvtee+IDcuXMHjx49UhtMFhIIjYAoqAkTJkTy5MmVD0h4xcr9WlRdLSogXrSyVgq0vQKSDpdxGRkUiRn4GK0xQyVik8+f5EtwLDRHMUdo7P0/Vq7U2nxUogIS7tmMG0lz4vduJ7FsWVBUMrFnL9+pAFLfPIKLGUrj7srtNMEyuBT6ZlZ/mt4t8RT88qCdurtW0u14fM8fm1FB/d0K0zETrZQCcvs2cPQow7kaxGxqtfnzgQ8+CEoEebnXGKQf3lX1URj7kaRcYdy6BUw7VgqlsBNHkA8FoCVvkUAaegJPfl+ZuixsjARIwAOJo6MidCogXrSqViogkgdh+XJt8ilSAKtvl0RJ7MYtpEBq3EAggtvJyg+6nEbSIdc8gQkRAUua1h1CChfGgRn7UaQIILkr9ux5HYlpRUlg924tM+Hr+Lx0Qo94TRx9QN6aMwL1/XqqG/PgGCqXDcC4LYXU35Jlfl+5rsF8QHjqFzFjs2vYn4CIeWGL0wMxEINUNxlxweZ8LuaIdbAKD+KlxoY/rqsUOeIDwhDKZq8I2yMBEtAJWLlfi6rUqYB40cpaKdBiCy/OzbpfxyD0R39oie3k6eJBFA6TDJ8omiM0IXKASLOSglseuZcujYE1tmPQIC0qr9RVm+B9FTRvc9mRiQMJExEaWgxHBSTPnG9Rwe97dW8aXEWNSgGYsUGLeDIQA7C+3EA6oRsi675K+udD/46aGO8LtH/6q+owPh7bEqdORyu0wky8QAzkzR6A02eiMYSy+5aFLZMACfAExBQZoAJiCkZzGrFKAbHfjMnIxdyqjP8GbEBlNZFu+AWj0S3MSdlFgDVn4m9oK6GegGTNCpw/D1SujG4F12H0aOCXXwBJD6IUvx21gDVrgPTpgUuajwgTEUYsQI5O6H+k7IIPb/2mbiya5ylOHX+BR0ik/h6NL9ANo5UJlvh/8NQvYr7uqOF4AjLwdAu0wNzXEeKeSq561e3P6IEeGKleJ8VdlayTIZTdsSJskwRIQCdg1X4tKhOnAuJFq2uVQNv/sOvTj4NnuIekiKuccd9HffwVjIyEwy5TBvjzT0Be//efF4Hz0aE4+oDI39nfTYOEj6/jRK66GFV5OSRkrG6CpZxpBzUCFi/WjNxfh85iIsKIBUB/mi5mhwMGAN32auGOJfKbyDwQCH/ERiy8UH5QPxeYoZJxDhmitc1Tv4gZm13D3gdEAjTEfK8W8l9cg2vR0yHtq6DQVt9EG4ohgVouo+l9T2HBvhwqEpZeuHZmrwzbIwHvIiC/jUuWAPfuARI5t2FDzUrZncWq/Zo75+DptqmAeHoF7Pq3SqAlkeDcuSEnvh6VUAkb8SB6EiR7dRuvEBSuUBygp03TEt5JYWQZcwRHj4Kl5zq4j8RIjIeYh6b4EPNsneh5Pu7WaYlkq+YgIEYcDOn3TH3R9unDRIQRrYaudOfLp1m4LcN7KozxdaRWYY0lMufVl6mQCrfUe/WwTDXpjB+BbJjHjdPC/IqJ4+efA421QFsskSDg+KBkBzRn80MogEI4ZGuxPSZiIjqqvzf9sB3DN5cOpoDQfycS8HkLCfgAAckP1LatFknSschv5tSp7gtPb9V+zQeWIdJDpAISaXTm32iVQFesCGzaFHL832IwBmOAeqM4dmMvioeolD07cOYMnwibtfpr1wLVqwOBgUCqlIG4ejsWYgS+xO6CrVH72jTcvKn11Lq1xg1KOGcAACAASURBVL2lXwd0wCR1LTpe2oIFiMnJrl1mjSrqtSPRxOREQ4pklh+xsxzy3NqCq4lyIv2jk4r/CeRCLpyCH8qiPPyCRVIKL6HdunVA/frAo0chuUnULTmwqlIl6jF194xE5mfMCOrlQpwcyPj8DPYlKo9iD4O+wBpgsS10eB2swCrUYQhldy8O2ycBDxMQF8h334X6jSxbVrNKlgdJL18CV65oSkmqVFCRIt2RI8uq/ZqHMbu1eyogbsXrXONWCXSF137MjqMrCz/4oby6/CVGYhS0zNAJEwZtrvREbnyq6NzahlXb/gTkv9NBWZ3HohM+x1hl7nbhQtDdc1J3Q/Mbo9WFskUeYev+BOo1c4GEvx46Z6klZm0f/1IU8U7sx74YxVHs5W7UqgUMWK09YT8eqwD8dx9SR/gFCmh+IJJbQiKROZbp04E2bULvW/8xFCdqMSGiEuLcZyZzZk32mzXT3J2W+iVHctzFYjRAIyy2NSaJIxlC2Tm2rE0Cvk7A0XrAcT66VYFuPWD2fK3ar5k9bm9qjwqIF62GFQItR5a5cwOh5WKKi6d4gMTKDj40E6CqVTX7eSm0q3ZdcBx9QA5vuYcC5ZKphreV6YmEv/+kNsFi0ypmPVKG4Bt8g2HqdSrcQN5yqaCvi7u+aF2fqWdb0DmL4i3mV/LE7FL8nEj/5DQ2ogJaZdqoFI0uq2qiJv7Grbjp8VuvS3jxQvMB0XNKOJodyhO4XLnCn5sewUlOQvQ19CwN3+jdPlCGnFitXPYSgbFiIVpgIJYk/wQN70y2TSQfjuAICqi/D7f+Gb1u9KAJlm8sM0dJApEioH8/SAAdf3/tVLtDB0BiuJw7B0ycqJkl6++7w2Tciv1apOD40E1UQLxosdwt0LJhElMdCb8bVvkXb+Nt7MJ/yIQs0DzN5UnCokWaU1fq1NoGTnxCaN/umvCEiIIl58Zyjiylf39IDF77jZgkj2x64jtU2tBfVTm2+jzy1sysXjMXSNhrYc9ZohyLzfCffumQDlexErVRF1oWyD/wofK7eYz4SIjH6lqsWEDfvprC7ah0izni2bNB/ebNqwVoePpUi5B89WrwMfEzY/zz4uizM6T7bXwzMqW2Thm+QvNLw22NpcZ1XEca9feJRn3Q/elQOqEbR82aJOBzBOz9wyTvj5w2Ozqgy0n3Z59pU3PHA1N379d8blEiMWAqIJGA5q5b3C3Qeo678MY/Cl3RFWNUFcmQfhXpbNX1I013faDdxdVb2w2RB0SOp3Lm1Ib7ww9Ar17qi1NygUhRZm8ZRwA9tQR6OHYMyJNHvWQkrLBX2ZGzKHW5SiZGvADN2b9ZtHnKB2QcPsNnGK8aio3nSJgstsqmrZ+A2JsdOoayzpgRuHgxfEkT36sNG7xVGr1rXPqaTZigOfNnDDiDM8ihBvkNhmAYvrHlMIqJAAQgtnpvItqjIyYqkzmJZs0Qyt61rhwNCZhBQA+kkygR8PBhyBZ1B3Qxj92yBZD6s2eb0XNQG+7er5k7Wu9sjQqIF62LOwXaccMk09bNQ+TH+to1zXHrQ/yBP9BcUWmIRViChuqJsYQvlZMP/R76gLguOI4nICcWHETuploCyFU1xyDDj11UFA/JBSJFPcVJ/TvQqZN2QZwSZPGYCyTcxdA5//67Fv3Nzy8QLxATMfAKU9EGn2AqRIEYEbsPmpz5QbV1ZMMN5K+YSvmLhPYUTU6jZHMcXtEVF72OmD4eP+663LwJLehrJqZrcmJbIdFebHyoBcXojN8wDp2DYbiDZEiGeyH8Q2yfm9emo28CO86RBKI6gbffDgq6Epb5lTigN2igmWO54+GPO/drUX399PlRAfGilXanQDtumHQHWftTDUGRGedxHlkVlZ/QE1/jJxshnoCYKyz2vgnik+PvtwM78I7q5BNMxlR8EswJXeon/WsGMvVvrepMbeOHEt3KKtM4noCEvTaO9sL1azzFkr/jqxvGoAu+ij1G2RH3ifEjhr7srTV08qTtNCo0s8PSpYF//w3qU3xIhn91E7lm9cOBK6nQ6/EAnP4vli2Mr9TMkkWzT2aJmIBj5vqOuTcClSqpG/tmmoWhF1ra7Lvl2n+xciBTwBlcylYO9ZNtDhYwgIlTI+bNGiTgSwT072TZkyxcCKz68wEe3fFHrDQp0LBRNBX5Sh4c6Q8wmjcH5swxd4bu3K+ZO1LvbY0KiBetjTsF2nHDlCaNFq5OD2Enr7dvB2LGCMTFl2lVbgQJR1otjp/KMyFPEugDYr6w2JvF9X57PYbt1OK17v5yDgacaG6zZZdIZEWLAmn85mM+PlB1quNv/A/VVcjR6NG10MrucLYzf9bWtyjR2+RJuvohGn1Li88IYBh6K6d+WYdiu8ZjPDSj4Yntd6H05yVsP2Ryzd6O2P7zJOw7dwZqTmqI2s+WqPvto8jps5VQkaHFq7eehvf36KiAVH/6F7J+WV8NvE/+ZfjhyHtqCfUw1dtRGqXxL44gHwrgiPpMiDsVE6d6/1pzhCTgDIHQrDk6YAIm4FPlv1cWW5CoXFFl1SG+eI7f3c70FV5dd+7XzBqjt7dDBcSLVsidAu2ogMi0Bw/WwoM6bookzGUDLMVTxEXOVPfRuHlsFYlJjwrkrg+0Fy2FZUOxV0AGFl+OAXveV33v6L0U3x2sF8yZVq4PKL4CA/e8p+r822cpBh8IqsNcIKEvm+MJSOuK5zFto3bK1xff48cYfZUy/gH+xJ9opq5Xxf+wDlXVa/0pmr3ZYZMm2pM3vcTDE9xHEhVBTsrh+G9jy4h/lbWc+JdIEbMB+1MTy4TMBzvSTbD0EOAfYSZmopWaSXlssoUL109yNyepi3L3V+JOzNTo2+66evqpJ+iUe6iY+6AQcMgkEAoBxwSlUmVKmm/Q9poWHbJGgcv453CQ76q7Pv/u3K+9KQtPBcSLVtqdAh2WzbrYT1arpmUMPfQ6ufDX+BE/QjNFKYFd2IMSNkrOZIb2IrReORRHE6x0fiE3wPIkd//+IEc7+1OSXd3nYuDxZjYlhQpI6Mvs6ANy2y8obGs3/ILR6Kb9cGEN1qCWet0YC7AIWhpzfRNsfwIiuSnk6bpeZFO8CRVtf4vynggP8RIxbdfkif2NG14pil43KN0JXVf+Psev+BVfqHEWwT4cQBH1Wv8+mobWaI0ZeIEYiA1/W4JOJk71uqXlgEjAJQL6d4PeiPjvDbvYAi0wF/6Ihbh4Zvv8S5106YDLl13qMtSb3blfM3+03tkiFRAvWhd3CnRox5ZhTb0CNmIjNHvrThiL36E5Pds71YaXGdqLkHr1UByd0C8OnIKMg9qpMU/5ZBtKfvGOenpeRNtrKX+QtBdC+onQBCv8ZXaMgnVq9r/I+VFpdVM7TMIUtFPO5jlvbUflfmXU9WXvT0aW7z4JZoJl/xRdzHskaINeeuEH/IA+wQYi+SmOIV+wa3wSb+wjaf+UU9am3qHvkWbst+rm0V3PYv25rJDs9nr5PUEPfPp4pPqzUuE72HhAy6fDxKnGeNvXmj8f6N1bS/4o3z9y+i1/9+jhfFu8gwTMJqA/TBX/j//+AwICgM0oh3LYgjPIhhw4A/voWO7w/5A5uXO/ZjYzb22PCogXrYy7BVpyIEgitohKAjxS5iQSJWhn3lZY/cF0mw9IRJmhI2qb7wcRCBGGd8wYLdaulNc7VccwvJ3ePYBcTTWNZHWtMUj/Qxc6oUcgVI6K3plJ65G9g+Zr0wxzldmVbHKz+x9D1S80hWFpuZ+xv3KPYGaHuvIQmjKvP4G3H4retv01d8Sjj4qfKdkEf/CB5qqjTo2+/hr46XVAjNu3MXBMclt4apl/bwxToXml5MRJJC6WE/Xq+X7iVOEwfLimDMhpT5kygOQ9EH88s8u6dUDdusCzZ6G3LBEQp08HPv7Y7J7ZHgkYJ6ArIPrppzwY3Xk3h1I8RBGpgM3BGpP6EgHR7OLu/ZrZ4/XG9qiAeNGquFugw8uC7ojhIAqiIA7jZso8GNLiWDAfkLAyQ3sRSp8Yiv3GWCIk3ezxA6qu056iH19+Cnnq5oD9cbPavDa3S7/944/axoxheMNdb0dTt6R+y7AM9dQ972EZVkDzqckY4wouvNQSQQ7GtxiAweq17megKw+h2SBvQnmUh1+wccimWDdl1Ntg+GpjH03HE5DG/+uIFIsmamvzbQDiJYqpi766JidZk9BBvS6N7fgXpZUj+pEjvpkLRJSB+vWBR49C51WwILB4sZYk1owivoDVqxtrSRSir74yVpe1SMBsAva/iep0Y3YgXsVPiOjPnmBfziZY1mI+duwA1qzRenbXd66792tmc/PG9qiAeNGqWCHQ8sNWo4YWASu8Mj1WO7QKmKKqJME9PEAS9Tq8zNBehNInhqJvjHWFTja93+J7Nfa0uIKc5dIq86tff9Wmo57Ap7gMZMigXRgwQAvNxESEEa63vbP/j0X+wNf7tVw3lbEON/JXVhtVcSR/ggTquoTnlYSc9maHejhXRxtkqX8RGZABl7E/bikUeabF5x2LTvgcY225c+QaT0AiXCpVQWesm1DpWeofIQESIeSuvEOqJZhws6G6d0ff5fhuX12fzYZuVBkQM5O9e81RQuLHB54+NbY2UkuiC5ml/BjvlTVJAHA8AWlU/SEW/pNYoTlT5wt8EThaffb1ExIJSDFunPnkrNivmT9q72qRCogXrYdVAi0nIWLeID9eoRV5Wtv25URMREf1th4RSN+MhZYZ2osw+sxQ5EdczOLEhlVM25Zk644cy35R429c7T4W/S8x4sXTNgbCXLI6H/a7iwLlk6s6W8t8hUS/D1fmGHXqQH3p0scg9OW3V0BGF5iELw5rT8vfxr84lvDt10+aA/EccRAbAThQ6CNEmzVTsdV/8MQHR2yO9b9l7S5cAPwfPsMzxFPtTUI7NMRipMAdLEddvI/leO89qCdyEjJ2wQKgsebbzhIOAccoWKtQC7WwBleQFulh53zzuo1mGfww91J59dfeLtPw7ZnWwRQQdz0Fdcci6iGjw2pb31jJ+2YEnhCTriFDnJuJPAO5eNG5e1ibBMwgYP/9GycO8HDvSZxEbtV0HwxVvnhy+im/l/JgiSZYZlB3TxtUQNzDNVKtWqWA6IM7eBBYsgS4e1fb4ErcbLGFl/Jb+wPoPEnzNfg9wxAcrPuNCm2pJ/iR63yaG6lltt1UvrwWAll3mFuVsSNqXdTMTJYufIFvB8bA4cNB2efliePF00Gb3d/QGV3wm3oSKUqlfOluDm7+6toAo8jdjiZYxf1+wS/ormanO4qL/IuysWBTKqTCLeD994G//lJ1dOVOXktb8jRNsqCL0nj7NpD46nEcR15VV8yuPsSfKIID2I/CKIr9tjC+/MwYFyjHPCAtfy+DBAe243qyPBjf9Zj6XNiHQc6DYzaH/574CSPQE8WKAc+fu3cTYnxGxmrqvi/Gamu1XH3oIHls9FDRer9ixtYTP+MUcmIgBuI54oYYkqv9SoNW+rg4w5R1vZeA4wm0fQTC1piGQ8VaB/P/ctfDB6v3a967IpEfGRWQyLMz/U5PC7T+45c8OVAo3wus2JIECfAEf+F91Ie2GfNlu2rTF8yFBvUNloRBHj0aaNsW6ODXEi0xB88QB/GgeYLqp03iACqbhFQpA3HtVgxERyB2FWqLOlenqCfr8r6YblTRfKtZ7Ag4OqFf+zwoolKBhOdx5FFm9ZRMTBPzN8iJnDiN0+nLY3a7TTYn9Lx5gWPHNKVbFHZZM73UwiqsQh31Z/MY8/Bx9FmoGbACt5EcKXFbXdfXz10/hlFtwUNkQv+1gKZJlCqljpMcw4qXyXkTW0+lVhh+QC/0wQ/qtR5C2V1mGGZzl1wxu3YFb1XCiErmZ3lAJP90WdJrufKENzSFJxVu4GyMnEj48oHqYhS64kuMCjFVV/q12sfF7HVie54jIBE4f/stqP/eWedh2LkP1YXPs6/G2DM1g3323fWg1NP7Nc+tgHk9UwExj6XLLXlaoB2daw8lK48Cd/0QkOItrJp8FRMnRfNZu2qXF8fkBhw3xdL8/SoNkWT9EjyOkww/97mjIo+dPatloZein3Q8REIkxGOIXXxz/METkAjWJkS0MYkpKg78ADp/cAvj5qVQryXnxNoHJVESu3EAhdQphhTxe5IfvI4dNYdGCUs6aFBQp59hHMahs7pQEjvRARPRHpO1e+GPRMliKaVFirt+DE0WT483p38+dB+QKzEzIu2LSziaoTr+6fG3UgDPnw8aZgy8gD9iK8X8ToNP4NdqsooWJSclUnT/HY9PLIIBOOuLIc291skiNTUx4dqzJ/itosD1wnDbRckunQGXcA9aaGO95MoFnDjhfLee8HFxfpS8w1sJyMnmvn1AzpxAmjRAMb9RGIUv1XALYz8OorB6recQMuOkLjQWnt6veev6ODMuKiDO0HJzXU8LtOPR5tz0PdHs8gg16851/8O6U5mC/eDUqqX5HbA4TyDEpliakEfw//yjOZm/NrAWn4GmTQGJknXuHCBmc9nfSYUET27heO734T//L/qARIDfMdrYs/ZdUGqX9gitS7un+G1yXFukq/+hKqpiHc4jM7LivO0ESv8xk7bkNER8qOSkUMLENj/RH/3xnWovPS6hM8biG2hZed/CNYxd8JbKiE4fEOOfE/3zkS+fFjr8PhIjMR5iPprgA8y3NSTmQ69eASlSAFeep0DsR3dw9e16aJdyqfpuihtXCyur++8YH4H1NR3DO4v/V+zYwP37QPHi2nhEWbD3AZFrkVUE5F45Yb13z36ugTiPLMiMC8EAfBJrJqYGfBTsmijm/v7OcxKT07Ciezm2ZoaPi/Mj5B3eSsAxcIs8ZCi7ohdq7NcU5q9bXUfL7qkh0bHkwFSUFUcF26y5eXq/ZtY8PNkOFZBI0t+9ezdmz56N9evX49y5c0iQIAHy58+PPn36oGrVqpFq1dMCrZs1yJOF69eB6g8WYAGaqrnYZ4a2n5xszCQcJE1/nFtyxxMQ+WJN9l5ZZLq4FbdS5MaV9ceVYvHhh8C8edr/f/zxuo/MmTXvZ5EzeZzIKFjhwnf80ZqKNmiD6SprdiwEiIGUul+yZv9wpjEaYxGexUmCkzvvqTUQvygx4ZEibYm86ycgsoH74W4HdMAk9b6ceHTBrxgJLWtbARxC8nIFlK+PFJ6AGPuc2JtZ1K31EstXaxnl/8n4CT6PO1lFYXIsx5EbuXESW/CuSkommw/Z7G7aFLR27sifYWxGEddyPIEW5UM2+JUra097xfRKThw2bAjelpiZPXwYcfuh1ZCAI6LA6aUQDtiyzE9BW7TBNHWqNB2t1GfGsTj7dDk0k6+8OIqaWIN5+ABXkD6EguVsH5Ejwbt8gYD+GZHv3++/1wK4iGy2wkz1fR4b/kiaLLrtxNmdCZM9vV/zhfWKaIxUQCIiFMb7jRs3xqZNm9CoUSMUK1YMjx49wrRp03D48GGMGzcOn+k7Fifa97RAO4a3a1zyPyzYlUXN4Cf0xNd4nQgslDmtXUslxImlVhtZCbFboYK2AZAN6l4UVU7Le1AMJbBH+duICdblyw7Rk+QR/PHjwLvvAlu2qG7lZKRwYffFPHdmbt5W1zHa2JrETZF+2wIExE+MysXu6wjVsJe/1Q51r0/RdnsvXgDRo4dQQKZO1XxAdFv8paiHeliGW0iBjHFvofGzWZgFLVtbRWzAJlS0baroA2JMOnQzC3H0P+R3T3tUL6V7d2DEiGBrIpflIzHp2Lt4F9sgikheHLd1JIrlmTPer/y1aAHMnWuMj6uKgNwfWkJNe3NCCVH9szjzY5/tRNCxX2f9QBxNvnInvY5/7+dGksD7OIUcyItjeAlN2dSLs31EjiDv8gUC+smofUTOP+9WR3X8D5eRToVCl6KfErrz+9bT+zVfWK+IxkgFJCJCYby/detWlChRAnEkDtzr8vTpUxQpUgQ3b97EjRs3EFM+BU4UTwu0Y4KfgQMCkSh3WqTBdUiitYp4/SgxlDm58hTOCURRqqp9aFhxRp+3PxcSXjmFW/nKoVWWzcHM25YuhYrsIeVJvuKIf2wvLqYqiimd9qJhwyBfET5hDykijtHGdqaqjZI3VyMgVTp8VPmyOmHSy6zUPdDyxkj1Z5sG93D6ZhKloNibYEkwAPsTkNV3S6EUduIw8qvknTWxGqtRW7UhJ4cr4za2ZZd25xO5qPLhcDyx+qnLBfT8NbOa3oaKg5BidH91MiW+OGKepJeNSeqhwv1leJogBcrluWUzvdD9SNy5GTGDfcWKQac1ju299Zb2tFdCi4ZWIvO5Dy2h5ixogTBeIjqS4D5+RC90hpZEIQVu4Q40fym9OOt/kjat5kivly4YgzHoavu7aZK/cSxjdZvvjrzhiomZGevCNryHgGOCUvHLe5qrEOKdOoSLqYthaqc96nOih5WOzOfC6Gw9vV8zOk5vrkcFxOTV6dGjB0aOHIkLFy4gY8aMTrXuaYF2PAGRJ7xLA99XuQzEEVF+kByfTtlPkDkOnFpuOCogC//NgHi3L+N60Rpom3ZNMAXEPlrWUL+yKIutwZ70Mjt96OxDizb2nV8FVMBmnEROZbIjRc+30g/f4Tv0V9cy4zwuILNSPn76KcgJvUwZzQdE/D/EAi5pkczKZn4dKmNw+XWolWo3ei8qqdqQJ8pVFnymTK/cbZPsnPR5b21HM4vcAYdwCIXUgLtilNqw2ieI1GcyGZ/gE0zFK0RTpnVFisUIFo7TnZsRM2i6cgISGeUqtP7OIBuy4Zw6jS2OvWiLKZiCdmp6ej4o+7lKRnY5fTVaxFdHV6LEh+SPgEZohMW22/tjkO3zp18UUzQJp+zOIt8TspkVfwFJ0ivPDsXvRsJte7PZnjuZeGPbugmffPfeuPF6hBIiThzs5Edy5Up1Ub/kzj2Jp/dr3rg+zo6JCoizxCKo36xZMyxcuBD37t1TfiHOFE8LtK6ASLQliTAjFijfYAiGoJ+ahtgH6xuB0OZFh0Hjqx2aCdYdJEMy3MMiNFR+CGKCJU62ug27ni9kT8rqKHbrf/BPkxGrx1+wRfuRH3Rx2GWG4qB1CC3amP0J0kf59iq+En3oyROgf7IxGHRXeyLbq+YBbH9cSJnHhXUC0q9vIPoOiYe4eI5FcZoj5845KJT4PJA1q2rjWwzGvjrfqt9FKonGPh+OZhY1E23B6ofl1M1tMBXT0Ua91h3Q5RBakkI23RsUvSklbuI2UvpU2HDH0MJGaMlPzOPHkUu25njiIicct5BKdTsWnfA5xqII9mEfiqlrX2E4fsZXNsd+uebsd74o+hIUQC/HkAd5EBRKa23cuqj2bHmIqbvLD0TyJ4krnSQYDaukTw9s3MjvVSPy6O46jicgpUu+RMESsRE98BX2FWmDGDOmWparzNP7NXeztqJ9KiAmUj527Jgywapbty4WLVoUbstXr16F/LMvcn/Lli2xZ88e5VdidXGMgiX9y1Ov/6G6Gkp7TMRktA9zWGISoYcbtXrsvtaf48ZYniLmLxobMV4Fz8ItplcShlffbIlN/D/x6yPtzr/wPHFKNCx7U52U6PkOmIwwuCSEGm0sTx7Nm7dsWRz4zU/54uhldvWZaPFPK+1P0UzKlw/TB0SekiZ4cc8WnnQkvkQPjESKOI9w63ki1cQYdEFXjFGnJWK2JdGwPPUkfvhwLYmibFhl4yrmYD00X/n/s/cd4FUU79eHHnqvUqSXH9KkI01RehEEAUWQIoKgSO8dpIoCgkCwIL33KjX0EnoPNUiHQIAQQiDfc2aYvbN7b5Kb5Ca5/L/M8/gY9m6ZmZ3dfct5z3GrZgezyL4OqFdP9PGPusvgW6axCWahOu9ZaDzanest/rl16ln8vL7QW0Ub7sgByYlr+AG/4jwKYia+MQgTOEZmqFnfQiM6MjonrD9TwqVcy5WCd2AHqpve9R54judIJrbNQnuDbEHNuRZ0DncNWWtOSJ38HEmRCMHGsTfwDnLght25ouOZYW0YMzjOZFfidJbCvb0xsoN6nytYZTo8EIEGNr1ONSZgl3EOSNRveZwDEvU5FGd4/PgxKlSoIJyK48ePIyd5H8NoQ4cOxTBdTEDbN7YcEEeY4NSwGViOPkD6EMmowqxJXAt/BuwMYwJXiTVg06ouVXE5N6sI+jy0FPofhMVRD4ROBwujCcOgMxJd0cLwR+V+ezhiG8tdOTtSPfkPF/PVwrHRGwTNsWrzm69Gi4Vvim2ohN6ggZ0DMmuWTQirTKrzOOhfSBzeG2MxHjSAQxCAZEJMcj5a4AvMF5HiIUOA+vVjnihgzhwpdEloibXRsf3zT+ArWTPvFs0OZsHKbOKF2DS2C6tmxuh8f6CfTzux25APvbAt6AMTwUBkYEoxOSHWAFASBOIk3hPCmGxdMAW/oYvDLkVmbDTS/KXWoGid8Ztx/grYi/2oILaTkpoQwz3xK6Np5l3Q42YUTjxwwLlZsn5f8lLwE/ntDqbTY1VeJ63qvHnOXcfZvQoWBC5IBKZTjc8K4xZxGWanpitadlJrSAXcCuA8zkO+f/tgDMahj/hb/R4djqsaWJwDEvVbHOeARH0OweLzmjVr4tChQ9i4cSOqMrQUTnPHDIgjVhQOQ6XJT+A9lIx/wkTbaB1mnPEb3p2Xv1sNYzL9vFdFMv3srdADKX6fILDHKgPC7fybyJ5Xbdqh5NE/xL4njr1GseKSRlbtG50vXedG5z57hQV1W4omaIqlorN0nmmgt8u3E54+1cS238rNwcJEreyK0OmXUAhLMDRN3QkQywKgXYK/8Mer1sJRPO6XQ0RyN+NjjKy82Q7GRWckJtpffwFfS8RSmI3ZkV69wtsrZn63ZkDqXp+O7KM7i4vP7HAI5buUNsEsqMfCwEdV/9VYDek8NsIKrEIjAZ0jHpxZAndnU2rRAli40DbHX+Fv/I02xgZZs3Qe8eLFA4kQ9BbR/OkjeQAAIABJREFUZ97Ru35xxs5oem+6OC0DT/5ILf7eBMkydBuZkRVaBTlkHZSBxQ9neVhrTmpjPdajrjiK35ZiOCn+LohzuICC4m/FNMdHzEo/HJXVuHq1jdQjIuehLg1rueJa7MyAvm5Jj/6Rxx7ka/OB6MzqBp54d0Q707shOu2ROAck6msgzgGJ4hwGBQWhQYMGQg9k+fLlAn4V2eYOC1oVb+ljUDzbr+PFx8iejzFkfIpQhxjRD2Fk5+ptP85qGPt43RQc+GzDMQhDMNyuBkS9TO+36IoMC6WQ3sgBz9GgmYdwVuKoeB2vCmux/5pNiRD/VTCuV2+Nqlf+MhS1GeEs+tqmg0CGnqnoaipCZySWAXmVjVr46SJ8vqK5uHBNbETZgTUxYgRwJmkpFAk8inNJS6BQwFG7LEpMFbZadR7Cem4ISXGH6K4VZsHM0lj0FV3PjwtG1Jw1T0wcKiO1U/G9mHa8kthvZplZmOvRXjh+ipIzMjClmHzPKIYo/p91LeOuNjUcZNWPkvDGMZQU/+R+hA+xqDuixbbWbAT5Uub6VkEVeMEX2ZETvsbQp6CLqAdho2MSnCy1qJdSzVkjT9WcKDgpIb0z0VGcZhK64Uf8Iv6mY7IRtU1TT+dl7lzX3Q17AUbnz+3seJ0/Y9yezs6A1QHpmGUV0KiRPPwNVaRVtym63rXuYK85O2/uul+cAxKFOxMcHAzqgaxZswbz5s1Dc6rFRaG5w4ImJvbUKfMgdG74qtiBXQg9wxMdqfIoTKlbH6obxu2rXsSsnQVEf09/NQa97/cx8Os0NAh7mD5dGr91vWzFtsTA+iGdcFYYQY3NGgN3nWx9nhvUCsKqjZI6+3Ktzqjp85uIjquma98sLjocU9MOMmUvmNxkaYgSwvr2pY1GtDiO4QSKC+dkid9H+Ajb8CDVu0j/+EqsOCC9e0v2Lmdb9uyAr83udPYwl+9nhVmMQn+TsvxdZBbXVA4I/xbvnSEXAOJqqOdS8Scc+bivgAdt3Ci7GBmYkssHF8oJrRmJeHiNB0gvSCn0ppxiblM4d/4d0cCPno1QDtxdZERG3MdG1ERtvJm0N9CvKfhedKN+5oNYe6eMkTGMyLX1a9IxHvhqKIZimDgv6aqXoqn4+ztMxTR8ZzDTcZsrs1ehZfoT4iUaYhWeICU2i7pHmVm2Nlf2JabW1/+V66h3g1r7Ouxy8Ie7seNlpRjLNruDvfa239c4BySSd/D169do2bIlFi1ahJkzZ6JDh9CLs529hDssaEcOyPs4jMOQtKI2nLt5VNGVKnd27t7G/XTDuMsHxzBlt4xsHu8wBf3/62I4IEz7k91KKSP/k38Yvrw4VOy7ydMXk5dnF/uq3+MidLbVYM00nfJ6aGgZjEVv9MVY09IhFK5o5Teid6zQnjDB5DzQiCIWXWVAJnr0R/fAn8Q5suAW7iCL+Hs5GuNTrMDTRGnw+cd+4v7oTFoxAcGigW6tycqWTUKSqMWg6zGoSXCHtWONcjbZ/h0yLJJaFCrjt3evTZ1ewedyp36Iy4+lTsUE9EAvTDDdW3c2HK0Zidy4jMvIK/r/C35AF0xFQrwyaorUwNR7N6LOlTUbkSXpY9x6nkacVhEnqGsws6cyEi0wHwvRQvykcPbOBp2sRfYz8I1R1J4D1+ELWTc5Gv0wAKNN986V2StHxf7x8QprUB91sEFcdyE+RwsscOiExOmSxN7XVmVHSY9MyGhH/3FG3YeC7llp03+RiTWXN3ew11w+qBg+YZwDEskJ7969OyZNmiTqPdq3lzzpevv444+RmepREWjusKDLl7cVFapUeSIEwR+pBNWojpt3NDRXp8ojMH1v1a5Ww/iV1x7sgcSyKqpRnYbX9LEvPg7oI4vtRFVkgQIiArxggTRydXG2t2pSoqGz1lqbs5t9UbimNHQoane/82BTEfrQwa8xZERCCJB9u3aAp6fJAaHxwhQ/G//f8UBbUcVN4bYm9YJw9EQCXL8OzEZbtIXcTk2KDyrHBzMSMVWEHlqUN7wpdgcjXe/7wIFA01VfotjJeQhOkBhnvF8IuKEOsyB8iM5U8MvXeIlESIDXIGz0a/xl0gtx1lAOb46i43e9AD1/fqDyveWY/aiJuFRTLEY//CQUyc+jgEFby3GrjFVUMiCk9877RKPbTTgJE4K7GcPUC32HJ/0JQ55LOJyHh6TUdbY+w1rjsgb1UA/rwMxLVtxCEBKLe/cn2ohnRwVUeK2IOlhh3SP9G6f2s9bbcHsb/GmqwVH7EtJH6F9ci/kZUO9zFcyZ905vtPxPpnk7fHof5+6lt6vZi65gjzvYazF/B1x7xTgHJJLzWa1aNexUAg0OzrF9+3Zwn4g0d1jQoXHR70UFVMB+O3wwx6eLgrmDAROROY+tfa2G8eXfNyNPp5qiO0s+W4SCg5rZFaGrD/K0IlPR6UxXse/2n49iwr8l4jIgodxIO7axs2cBppTYJk7EUP/uAk6l9BTefRc4dzs1kgT6Y0+WJmiTYqmAaKkP3mefAUuX2opv/SvXRard63EHmdC2zh1hCHt7AxPRHd0xSVwmFR6jROVUMQqRsz7HNJoYLQ/PcHKH6K56NlRmYzXqoz7WCkM1M+4a7xvdQOU801npPSETUgbew+409TCv+RpQ+E6pIjP7899/sfXEh31ddb+UHs1QDBF1YGysexmEEfgK/yAYCZAMAUiYNDH275caFtRgi2gNiL4+SNhY+voyLMNn4noNsApr0MDosE7F+zs6ohPeeOBv9nA26EQ9jZs35UF0enY8KSWcqmMojpI4hpvIKorcN6CWkYlQnXDld8VRlv8QSqM0jphuEkUZWfTvSHzXHTKF7rmSo7dXdjUgbwJAxsstQYIYg7u6g70WvbMd/WePc0Cif46dvoI7LOjQIqcsEuyGX8VYsuE/3EI2h+NyZarc6Yl7C3e0GsZXJq1E7u6fipHMb7EGRfvWMxWWc7uqAcnj9ZchxlYZu7AbleNqQEJZA3ZChIcPQ0jQs82YgW5nvsGvvwL9+wOj36A+FO3oFtQQ7D9sFLoj+025crYMIQu2F/q8LxSjj6MYSuC42JdGZM+AYRgGCZNrU/0a/t6eM0Yhco6ivPoUZcggi5hPSuIhoxG2FRQUuw9UmzbA33/LPjC4scJPKtdfRD4UwEWxnf2sWRNYu9bWV+67268IiuAs9qE8KmKf+FE5MvzbXQ1H5RCoviqq7RdIjE8qBeDDQ2MxJGiAGE8RnMZZvHGi3ww/ohkQq4M6NPl4DHkmNVQ+SHMKex79z7QI7sTLjEwhd3G7RC0cGLrBED/lTsxssDYtrKZ/VxR+3+pwHIHZIVEZFp7XldkrPreXLtl6mx2+BvyL2Ze7yIQ+GCd2qIUN2IRadkNzpUMUu0/b23V1OwdkXQNgzRqISMP9+2IwcUXob889jXNA3OheuYMDwunQaxPU9BD7Ox+Si19RXKrfVNSO/27dGiD1Z1wLewaUYaycihxe8zAPX4qDqmObEATTC8u5XRlPe3ssQ8WfZbSyT9F1KDOkDhiZj2PBsp9z9cFSgmk+njuQr4MUW1v26Vz8m/kL8cFSDga3n01cHIWCTuBqxtJYNeAQNm+W+ipsxYvL+6Cw9//Fz45sr//Dlvif4JPXmwR7EZmJKB73C97AWE6cQMuf3otRiFxoGgfdUv+Jqo9XYQq6Yhs+crhIY9tIz5ULAsamjLznhUog6fnj8M1UCn90PmKIEJKS+soVOQRluO+EZHJSzoqeneV+ETXUY+o9ZtUAURlnSb17QbxzV6Cx6E4TLMXuTE1M9LcRfe/q1xMimfc6GZmNZHhmiA+q8Z9OWQ5FnhyEb4pC+DDLWZEVVBBdOrIqsxHafOk1LjKbGCIgVxQhnINWaI05WIc6IvOh6H6JbPb0lGd0ZfaK2U6dxas9ZmGWEHmU37YTKGbU39AR/BL2AiTukCmMqbXpTtexFqEf8aiIUoH7cDtNQSwccg5btsh3dUzU27mLveZO9yeifYlzQCI6Y9G4v7ssaH5cSpYEnj61DTYPLuES8okNepEgtRDImqWiVUznX7sWjZP0f+TUyjBWMJLJRWei6ylJSblz3AGM21HWBKviduWseHhtxmZIuNbnWIjF+DwuAxLGuqhSBYIZhZHPgj5rsRb1xd4NsdLQjVCHi7qOeW8OIBj/jVIZ1zkzIFmy2Iq38+d9jdOXkpiMKJ6HDnnTAFuWqnf5XRi/v3KMZkBYM0TFc71VhK3OKABJkQ8+DjOZsRnd1SOchso2PY2rV4Hq1YFt28SQ6ta1OYVqjIRgNZ7XGCWvrIB/gjTo08HPBMHifq6sJXDlq8haH3E3fmZkfH0XW+LXxCevN+J/OIVTeE9csifGYyJ6imeesCZqh0T0vasyIIqieKfHJ6gSuAX3EmZB6Wy3hAOot0VohmZYAq6b5ODCMjNEhee0KodHXS93en9cfiB1Rphd7xl/Ema+bod2+AOvEQ+JESSgT67OXjnK8P+Br0W9EK+bBo/wBKnghQ/wAfYIsdcMuI9AJDXNhztkCl25/t6Wc6l1pIhZzqGgcNB3oxIqY7cYRkyJvrqLvfa23DtH/YxzQNzo7rnTgqYT8umnOiVvCO4hIzLgAbbiQ9TAVmPmSpWSmF5VEhPex8iNpjxWu6KUiAW8oNREoGdP2R9SXhUubBSWq/oE5ax0r7APE/dVFLse/W4WBl5pH1cDEsadpHj2J5/IuvL2KRdh1hNJl+3ZfAv6b60hMPRsrP8QEfUGb9L6b1TWVEpfj6bzp22L76No9Yzi2HHohXVVxgmnnTUgdG5WQkLq6mENbpWqB0Z0Y4ImOTQY5RJ8hs+wzJipH/ALJuMHu5kjzIz1BbHRVIRTGRh0KvpPSIekgX44W6gRXi5aIaCJyoBOmhR4/lz2lPdnjJ+NWYnkGcFIJOBazKq4sxihrgGSO9Mz7DkutZamoRO+wzSkhL8hDEiWqhlFJouMWr9+NkcsIu9da80JM0b5cAl7UFEY3tb2c4Je+PGVZBUrnO4Ozj3MZNolvMySngHhtyL9kyu4gjziHKxvGYmBGIGBGIhRYhthvoFps8HPz3aZ8K7hzHrV+6GymKxBKY4TQnCX8D020h2rZyM0GFZE5tuZvsXkPhQeJUX3o0cym0tCg7FjITLp7ty6dgWmSgksMECxdEd6JA14iP2ZG+KrVCtBLSOR0RsW/e9ad7LX3PmehdW3OAfEje6cOy5ownqIJ+dHfkP8Oqj1egP8kVJEikIQ3zR7efNKbK0rPhRudFuipSvWDMi8fEPQ0kcWnW70vIEpy98xORUmFqx+pwBWUrL9/DPw449xLFhh3CU9A1LFZzZmQ7LWlcc+HEB5I12vPmrj736FIof/wct4iVAkzwv4XIpn+qipSxGLfxpFxT97YAJ+Rg8RfWOhc4FbOwSMju1L/CPgdXTU6ZxEdxTeSunKPpBmlLoSafDYmKltqC60SqyNS4vPfWw0nWazSxcWzYcIZitS0DpitiIU5k2SSnR3JAYYFK66EevOYoRWh1HPdvTCOExAL0F56/s0jbh/K9EQn2KlcXsi897V62yK/y8YR84mRYLXwdj+zpdok+AfuwxIZ/yG39BFXLMMDgpadr1GI7w1vXgx8PnnAFXr89DvOHwIh1BWnO9bTMcMfCv0Pyj8yda53BGkq1HKIBDgtvCu4cx6taqxs8Ceuh9cX3PxBVpBqh3mhY8heGmlJVbXic1MoTNjdbTPnDkSJh1ao0PPkoqPHKMzI3tZlx3Hd+jRowAz0iePBkvueQeMhSpYFJ1Oojvaay6b6Bg6UZwDEkMT7cxl3HVBq4/VENiEo/7pexoPMhcR6rRH3pCHqOJCV3wonJmvt3kfvQZk1izgS+8fDSVgRjufIqVdDYjKgLSufg1/bX9XDP9s82Ho6T84LgMSymKw1oD812cy3hkno/7TO51ApW/fwx9/QBSiq0aDoytkmC0pAgT8Qk/rq/0+xFZsRQ3xzy8wF145vjBoUUsnOIpDr0qJ3050mIJ+mq4Lo3iTJ0ff6tXx/QqnT5FEpaCtrvwEKZAaj+0CCRzroUPR17+wzmyl2XwnzTPceCSzAbohqKA5OilA7dqMXE9B7Q1SNG9g7SNIWLaU24sRWh1GZswUCxXrPZZD0vGS6KAYTsIbJVEvq7cQJ2WLzHtX1dnQicgYeB3XkUuca937g3Dxy+EiGfvqle1ONU+xFgueSujiujZL0PfwZybB2vCMcesYB5XZiOGHpNo5aYaXx2+KRq9tTFx1sRbrUdfl2Sulf6KyH2VxQAQh2H7Ez/gFPxqDJuUxSQ/IhlUogQ+CX5lhZ7GZKYzM0zlmjMyYOdOYNXY3J0S9y5Vz8df4e2jd600mjrT0HCCkc0K4LJ0VZZs4M+aI7uOu9lpExxGb+8c5ILE5+5Zru+uCVh8PpqI3oI7otdKq4N/EIpMOUvFtx2VAwl9UykhUUXFP2PDPCRGMkqXiY9EiWSzJwmc2VQOii+mNR0/0xvi4GpBQptyOBYtUVwMkmxAuXwZy5xYZO6bsVZuabhC+ezhS/HPWsJtYeSCrqbCR24nZL+Q9H4PPS2KGGthiOCP8d9WcV7DjuoSYYORIcc2Y+jBa4TXsQgfMxEzIGiPCbCphr/ibFK+X4uUXEAyF+6fa+44d4a/h6NjDjuWm/k1Z6EDRzbIDsb/OCKMIndsULbLKcLROvhR/PZOK2nWwznhfqb6GZyhHx5jCO6fuMNIhaB84BUp5nCKw3nhfnELpZtxHeqFYHtn3rj7HLNYt4r8P+yAhnd9ghlGQrfd7fOtT6Pm3zLqOST8e/R70NIQIuS089kNrkf344nPR83grcT5FulEJuwWjHxs1OFanbSMgWK7MXlkzIHoBejVsx07YqPMpAPkDZKSAz4kP8ptuZWxmCsNbU9bfCU1ittDZxjo2aw2Zs8dG13560G7wYCD9vbMGG9zy8uNw/fNeRhE6+xDdgR53tdeia/6j47xxDkh0zGokz+muC1qlzwukf4DzDzKI0a3O2A6j83iKYnV+fIjLpsJyZDjpIzldb/VhVizrzEdN8c7epXiZNCUaVfcXBq+OZRUGyBqA2N19Xi/xEonF+BUvP42RmBS6e1sm304HhM6H4tu9c0csWt0g+/BDYGvtCVJml+1NPY5O7cjNxB/PLPwz3pnYQ+xWxuMkDgcWFYXu/NDvW29TXGc4+fe848VzEhPQACulK/un65IQ8vI7Ool+N8MiLEEz0+1kRJ3Y8NhoVgekaqazKNRYUs5u/ng8skzoCV0FXTkgnHeSX5R9aTNi22I2/kRbtxcjtFLikuSjH2Q0NzNu4y6koO1v6IzOmC7+/r7dM7T/Plmk3rtWnZXuOZZgoq9cA0PLrMP8R3UEll5v1hoUGubMoijCkfBoctUYyTZHGFZJr1/x6xuWuGI4jpMohg+znsXWW/Jej8kwHoHf9XR59kov9ifHRN+HvdD2gaxt0eea/2YWRhFWtIMn/kA7wxni71xz1nmKjWcmvGuy1oPfhog2Zmn5nXKXpt7l/A4yYORx2AteqCK6pwdEFaNhdCMx3NVec5f75Uw/4hwQZ2YphvZx1wWtR4jPJi6GQkEn4YO8yA8fY2b4MmaRp/iIDbVlQ2Jo6t66y5iwrNRiqFUL2LRJRntv3DC4zPXCZwW1oPG7eosHErx8Ad8qLfFtinkxRj34tk20NQNyr+UPyLhARjVH9X+G+p8nExDiEiXkyOrVA9Y09AQ6dJAb9u0TRVBW5W0qUI9Fb5F9YsuAe3gA6ZyzoPjurWBRAM22MUd71PadFWPFkXq0mfUvlD5ZGlAbtbERD5AOFbAPF1BQ9I2lv6Mw0O62Rid2Oqw1pO6Xqnkqh/3YjwriEGZxPCHvi/G7psvC7T939sGP02Skenr2UThRr7/bixFaHRBqUbTB30J0kGxQqtauD8ZgDCSGpiDOiXsYmfeuvj5YEN72yS8G9OjC4mM4k6g4mCnQqWoZEb8VmAapXj/GvykboeGrFabfw1NDV2NkFpDvtBpegzEYI8RY3sEN3MQ7yJLgHm69kpCaMehjOGFqvbgie6WK/RU0cUvyRqjxbBWexk+JzEkeI+C5DWaVBn6ibio+Qoz6I33tumOWwPpskfhi9mzzVmaa+mIM7iAz+mCs8d6yHstn7MmTsJ7WmP3NCs8cXmolBnlLoo/hZVZj7qP6wiGMCQpeXtNd7bWYvStRu1qcAxK1+XPp0e66oNUHi7jZX0K+x/eYIsa9bvp17L6WQ7zgmPlQuNrojjy4dNJj4WRWLKugfv27ojR2CxeWUXcNy1qoEHDunOyo2JdIGqZHKLxUvz6wenWMiS/FwnRF6ZJqrgkrev0a+MqrPdpjtqDcTACC3OMJClOddnRgoaUYcU7CeH6qsgHrX9fC7t2y3pEifer/LIqmfsHr+AnwYaUg7PQykzI8RiqkwhMsRlOMLbXYBKmLzmfEatByHJeRG7lxVcCvPsQ2PEdSYViRgpTUp4Rg0alSLbaCCOpdo4yIT7DJEILTszXqd70GhH3PnuYpfB+lFMNwVDPC7bHlXIW2kK2woE34RAhg3sA7yIEbxmEtYdMK0hncIvreVevj/fclhe/eSr3w1V2ZBdAdaXVh5eypGhQKBlpVw8NTQ7dCsNbm7Iy612U2J3eW57h2xwPxQ4KFNgjXJSGpHeDp0uyVI3a405DClY7GxL4phiw+P3lx2e4Wutta0jtITQyy/+mtEM7iKErCAy/EZurNVIYXXiOBw+XpTuOzg2cm0AJFTItWqBCj30F3tdei9MGM4YPjHJAYnvCwLueuC1rPgHTOshy/3ZZFka0wB3MhcbyRicS50dTHaFesWFY6b+cTF0WBoNO4kqkcVvXbb8KyNm8uDQU25YC8yJ4HSf67ggvZq2N+u20IDobBGONOH40YndhQLqYLa+7I2hxVby3Cq2QpsHb+E8ycaaMxpSNC6FFZ/y3YAvnlVjorNHiZTVDK28OHAzXG10SFJ5tBRed3cNPu6teRQxiQm/ExamJzjNXp6DATRpsD/QLwFCmEYTcbbYUDdg05kRO+2I5q+BDbRd+VIcu/w4PURNd91d81XOu1nixBrl4SHjT3iw0o1ruWCYJFY5r7sanCdBbXp8AzkHaY2hXuLkaoaoPUnJ7Ae3gPp3AIpVEWNjYAnfSAzsgCtIzUe9eajfjWqyVaYgECkQRJQU7jeCJr9OCB7BFpjF++BP71qIePAtfhYYIMaFnjnmA8VFnv8NTQrXVWO7N+jiq3FuMpkiMlbIJTrG9Jj4fYnb4hUm1babrXURUjtPaBzHDP4yVD4pAgbM3YHPWfLjAondW90AkpqJj+H7Kbln5sOerOPH+sndGJBHgMgyFNsdR0uHrHOTqnO43PzgHx06rqSYWXP3+cA+LMwnCjfeIcEDe6Ge7qgKgaECGLcOa+jL6LOpC2GJ1ntlEHwkL0uBqQ8BeUFctKiIwyCLeghoh+siksq4ryqqgvDartfpK7XjdSlAHmTh+N8Gcj+vfQHZD9meqj3N21eJk+M9Z53gYZyJTKuYJldChxCDOPSYpQz9K/Y07SjkLIUNGOkqqSTFFTvOQ90KOnuhF/M8N7yHr/FPzyl8GX+Q/GGFMZUXxKmZrGefV0x1GgmcSYKRG7HaiKqtiFq8glMiOq0FfNQXiQmui6a6Z3zV3Ad4gncgyXsCvPtntR9ocKdnUPzCap8VI3pOvk/Mjk74NjKT/AjC+83F6MkOspMFDOKJ/xy/7SCF+FBmiEVcZUl0hwEkdfFRP//iXnzzhf50dRVxTR9641G3EiXVW893AXGNTYOPWSySlXFyfcaHyArQbFqpYenhq6TsNLvZ1x3h8JCmi1/ngdvtf2PyqIAiEXcCx5JTTNuls4OOq9x32iElzRx836jwKJr2Lt6dxiiMMxCEMgadD1RoYuCr2y0VBfl/xzU3H2mwR0dD0OkT4vWf04Xr2lxUMBu6L6/AXkRy5cQxIEYSeqoBp2OrxWbAUiHHXGqoK+LHdPNL4yUey67p+HmLYgbYxCkd3VXov0oomFA+MckFiY9NAu6a4LWo8cMfLbckwx5A04KegJKV5lbXEGcNiLyoplZU3Hsu1p4fH8EfZmaYw2KZeZsKzKAZkxA5DaCDCUeqkEWxjnTFFe8rz/9ZcbLexY7IoVgjXMqzqqY4epholECuSWZ6MBO+IrjTKG1I59+pgia2o4DxNnRtqgu/CvXAfbe6wTjEzMRKl2LccHyOm7R1alnz8fI1otepRQ1Qx1yroS025JrHQjrMAmj0aYHijrDF4hPjwQaNSrqL6HB6mJrluqv2uYVW3gM1GofrNRd+UsithF/QlPVBlCGrGr/CoLVWSK65FGlc1dxQitsKDEeIEX8BB9VgQTaq4z4q5RkO6oRsLZ9641E3AtUV7kfHkZF7NWxrreu0zZV/0+98VP+An9xSbWoNxIVtBUBxKWc2C95mG8j/fhjaMogVI4asAaqWhNhjb1XuO11Drm386O0dH6tLLD6Rmlr/A3/sFXdocVSnYdZwMkRbFiHNR3crc6CdU39svKYsUx/o02Yhf+XRfr8DkWi387yu5we2xScltvhh64IxlLWy/7WqmYJGNxV3stut7N0XHeOAckOmY1kud01wVtxWX/ClsdyOzB1zB9XU4T33acARz2ArBLJX8TIrkmWaRA0ZU//zQZvApmoqtDf7WwNvL7bIR/ymy4uvs/kzo0oUSKnSaSS/H/zGHWIvSAomWR7PQh/JehGDy7HMenn0odK1MR+uy7QGbJPLSldD/sqTvaBHHj9gSw4dW3522HMXk9sXmzedoOZqqHMnfXITB1JjSpdCdGMiC6oacix9/DxjhUEt5CD2QQhmM4hogOU3TNo0he4dgqVp/wIDXRtUD0ejPelwnJBqNHgCxW/um7G5i0+B27ejNmD+icq6ZgJoRisQZHQbBcSefqqvEgN+zbAAAgAElEQVRb63Vy4SquQkblZ2Qdim9vyXvERsgQayQS4DVOl/0arV/9Ean3rspGyIxpiKgHYk3AAjQXUCw2ZjSUzgj/TWewXdJ56HvyS/H7Fxk3Y/69j01ihGE5B7rwIY+/niQfcry4BK8EVVHllY3zeRUaogFWC5jXPxPvwdMTQm9E3buo1E5Z2eFa4y/8ha/FeJZ22YGf9lYVQqHmFiKyBplwzwRX1PeJSlbGVevI2h/1PtO3s97ra8jIVDo8QDXsMDRmFMuXtT/uRDWsQ5fnzwd6edVHfazFXWREZtwVXacDwndX585Rc1aduS/uaq8503d32SfOAXGXO+HGrArqwVd1Hp9iufHiUpEjPviEfjASGWcAh72o7ByQL59JWh+2778Xqng66xINhmZvmFKZLVm3Dnj0STOk2bIEgYlTYkw/fzRuLEWmFJzI3T6KsfWY2dHw0os7exaoWBHYs0d0yxqdzZzmBW4/klHoaeiE7zDN1H3SiGYIuonzT6U+BdW3B0HqhhCmxUaj+B98iS8xDy+QWBh4MfFxVONVBhvrC/7O0AOldvws+pUe9/EQ6YU6u4r49nhvM1Y//1jAXRQEKzxITXTdT2sG5DufbugGqRKpBDqt9WbUilBCkhQj7OXbFdVPSSHJbu2eoO33KYRG2QJpW7tEUdtV4y9fHoJqVrXysGly6Kxf6vfbyCyMrXWog3pYJ9ZURN+7OgV4pUIPsPucZG9bkacH+iSYIJxQwsKesxwENtKFD2CjPVUUx3p2Iiy4jhI+pHF44waw3CsDMuCBHcxsbpK2+OLFnyIzVyRvEC5cSmDSG4lKBsTKDtfg+Aj0eDxYjDEPLuEK3uj2WG7uWtRFXayHP1IiDR7ZCXdGpU+uWkf6eazvM/UbM4JELLDGiNDR1HgkWL7o0M5DS/GusjZ3EltU301FAnImTQUUfrQfgXkKY9PPZwzooPo9ur+BcQ5I1FdvnAMS9Tl02RncdUHrBjMN4HG976NwtUyiqHVD+i+xuuk/AoscZwA7txSsWNaGZW9h5cFs4uDlRQbgl/QjRc2BTidItW4yNakPeBuvtmiLP01sTjw+b16I4lB3+yg6NzOu30vPgBB7/m6VnEjt7wufvJ8gYPkmkTlypBz+DMmQDM+xEJ+jBRaaIG6s8ygR4m0IxI3OOgUzE3exyzpNxXeG8+KB5yhb2SPatVp044MUq6TR9MryGT64vQwcUwpR8BsPVbEDO1BdTDgjwXPQ2m7yo/sD7uhuW2tAHjb8GulW/4XX8eJjxOBgfNo4nl0NCFWbmQFRNVD9McqgFmZ25zLyikup311B5+qqlVqwIMD6WdUIkVuBxuKf9bHa0KFQv6sC9TPJS2NKq0OReu+qGiHWdeQNOIETkEqnN3tNwsGK3TBokMw6qKac0qrvXsOOq++KzX/mHII+z4eKbFR4dUPW78foUSEo+n5iJHgdjBUpWqHx0znGvdGprZWzTBgQNUMfPgSWLJHik5Fp1mzTDHyDbzBLnCoJAhHfI4lRi6Off0T8IRj4WtaHKPpj/Xd3qpNgv6ysatyWFTcF1TEb30tdIR30AygriA5uIQuy4SaSJImHF5IgSzQ69CqoFZk5d/UxdHj9/d+QZBzML1kQ6IXv2iUuxXvBQAO/nY8fu/rq5vO5q70WvaN27dnjHBDXzmeUzubOC9oawZrgJV9c95ABmXHHiArFGcDhLwFl8NJoot5dFv/zOI9C4sDeGIvx6C1eoBSQIuUuYQdkZ/r7b9u552XqhpZ3ZWS4Sgl/eB2T1KMqIhkVqEL4I3h79rBSHiuWnWVojM+wTHy7CFeYIpmlRWMdSM/J0lG5nPsjPF35rzB6CUdQhlltrMd61BX7f4YlWAZpFanMA/9elK8/mvn8JLZ/8dFtzN+aOdo56nUDnsyUn38OTPeWz+oZFMb/ICmeqeystED+zD8aExL1U+zPxjzEhhOrO1C8Dy2XNkbhcyvw3CMNLh7wE/dBzw5yf0KFdAeEKtoUIBTPBnYaYmXKAQlPtdsVq5vrbuRIyaxNJiIa/X372hvPdAJUpoF1Km1e2hTrmQ05gPKm7pCkoga2ggxruXDd+M3Z967uDEyfDpyauAlTfWqJ8+hsSFbmMBZtJ034Et5nPUTEXNE3650LrW7ImkFPigAEILk4dAq6GLTu/HcvjMM49BG//d3vHBYfL2gygKOyJq3scPP8pDYOs0pZcdvu+VVjq4c1WIMG8jnGXMzHF6Z7wizjSWo5uUkjgcROS0257tg2xwIsQnPR25/QF30x1ngnUO1dp+SOrUyoo6m0ZkD8E6VDypd+eFy9EbZ/v8IgFInLgLjJQnSiG3EOiBOTFFO7uLMDYsXwEp/8za1hYmpaFzqAOecka1CcARz+arEWobcrfhiex8uIA2eXno6/PL4VuhN6BoR4eKq/qjYUQwzWlhy4jtyVcwg2nCFvIONR+VCHP4K3Zw/CScgmxvoGGgrHziVBguAg+FZrhW+TzRHGjQ43URA3UCSBgPDixYFjx8SASQOqcPGEoMxGe7G9e9ndWHmvEq5ckfOimLCWlx+LT/f3lRvPn8fv2wqIiDVbdGUXrBAmBggZ3cyCO9iImsLgYkuBJ3iCVOJvpZdBcUxmTFQdSGw4sVYImTK4yRL3Lq4ZmShlILOPbAqCRVai7Ge3YJqPpFF2ZDBG57g436wr0jMI+tNCpOXKlcBHH8k1oGP1iVt/d94o9HoshSH17I06x5JELfHZywUITpgE5Ys9xxFvKZzn7HtXXx+cw7p+NiheNWzHTlQD1wEF7Ngfa/NFdmTHf/gXH6FFhn9BB0pp6IRWN2StIcyCW7gFmfGdk2MAWvtK+CIbFa2pOM42+MPd2B5USbwLVYvKvdPZ4ejcdvrtf8jmdwbMJk396pBQaB81yn7MevZgErqhOyaZdmLQge8Xd2l8h23YYO4NBUdHQMLNqAWiAl4NsRIrIQkqWmA+FqKF3TCi610V0fnSa0D+mBmMg0el0OsstDcyWTEBc1X9dmd7LaJzG1v7xzkgsTXzDq7rzgvaiistiwNGdG4IhmJtqSFo2DDOAHZmOemGBz+E+a5vQ+s5H4lDr4+ei5z9vrDjMyfTD6PZZEAm5ORcp1/RbK/kWRzZ9DgaDCxmB02JLFTBmTG8LftQu4NwNsKRnj95iZdILLp+v1kn7G4xzQ5uouA5/pVqIdXeTXiUPBt+6fmfXRF6aDAfnlvpJsyr/Dtaer3xOA4exO9HykS7A2It4s6eIRC+95OKMc9O+A3aB9uqtZVQ4lI0MWkDKIcsNqBKen0CDeRNfmVQBocN3Lqa3wEDJMzQUQaEMJlzKCzGvLvuT+h2u6+pWDu6CuzpuNF4f2qTtQj1MeEzTDiRXjzPnWngqpqXVHiMgASpTFoOP+NH/IhfxHmJ4S9eOXWEAg9WB298lgnoebuXON/WKWfw84bCwimnY6Eroat53/GyIipin6BxLQgNO/amcF3RIesD178dZFE8v+oc5h6R94cZjwmQ12cj7Gw1Goq/aRzzbwZiMmWSaJvIrkn9nasyYWr9L8enaILldnox+hgoCkmtHy98gCrwsruva9YA9eq5x1tRz4CojOwiNBOaONR6IQzzFRKKzlKF/gZyiL8nojt6QtLaWu+fCmzF5gjV2uUz5uttzwjH7YsWyXXLuFFUnFVnxunO9poz/XeHfeIcEHe4C2/64M4L2srjfsz7FW4jCzLivsCRlscBAWc5fTrqWF03uiXR0hVr5LMJlmIppPJ2HazD08p1TEYF91++3JYBYRFuBZ85Bm6feP5dqBopUbJoGaCbnFTNMyOCjJB//9UjrN+XVvRuHHqhD8aJv61wE/57sp8sIA9CIiQRqsEy0qzajMRd8U2QxFEXz/sUV+8lF9hkvXXLsgCTbrcUm7oV3YJfT9WIdgiWNQPy2ucSLiGf6AOZr0ZikNHFsyiEQjiPm+9WQIP0ew0jPSahStalQiOClMgK1vIiVwEkuX4Rl7J9gLnfeIlIM6PU6p7xHk+bJg15ZTRTo+IZJKnDb+iMLvhNOAbMXvG/6IKV6Hozclwh6IgZKAVvjEZ/XIOsn2BjXwnp0wvQuX0uvsAXmP+GuIDiIOZ1N7/oaLQ4NUCcY3DzC/isX/4IBR6sNUIDn/RGb4wX5zu98z4uPkxv55Tr94hMWc2xCM/hgWQIgIdHPFPdhKNoubWuRwya1fcAhmWbgaE3vzFqQCpgL/aikvhtRhlPzPNoJwIIUWUwswbQcqZ5jGuP0ojrkNVROX1q7VvXpSpEf4TUSAs/u/vC9cgaFXdojjIghF+Srl3RHtv6GYJbyCoypEoPxB0yoY7mUQ9OdKxyFr/vKiJ2O9VmPPrc7SkcZwboiBSIY8Fyh5UYfh/iHJDw5yjG9nBnB8T6AudL7vdnrZBj51yExIuH0u/chveNTMZc8ftC/HNcs58B/UXKX0fmnIkB1zuKHVsX3I8558uJvwnXYDSVc6+YfhS854tUazDXX+KS/2m8Aj28GtnRk/4iA6Vu0WiEcBwKrsGaIn4oojNLoxegMzsn6HcIcAawodxQHKw9RMBlWODK/7MpA0SPNDMS/dIjlcnQUlSvZMZJDYvn8WbGrXUiW1J9ZqrriY77owcKCD175bUHe/CB6JGVanMrPhQq6EoMjoYHYWZK7T26I4jWhWmt12F2sM+kLEjx7A4u5K+DwKXrhLGtlMPZ3yNHzCQCrFVgtmuztxTzW436aIjVds+Aq2El1qACn9MvQmzwJilWedhkuPIZsNJlb8InQoiUEfccuGHqN8/ZIWQGZuBbsZ1Z6EMoG6HAg7VG6Gy5Nqj/8G8EIwESI8io5VNZPL0DZHgbFmhzWKhLch8ZDcgh93UE/dS/HazfqfF6M/J2rilOPTDfQozykUJ/bHpt0ppKY3CkRh/hr2yUyMFIR7Wt4ouTvzmFrjPfE+ecnHM8ztXtGSoEi/tQd0UFLELTzHD1morsi7tsWeDQIXk0Hd1XAYF4ihRIiFeYg1ZojTmmU69BPcGoRtrq1HhsrIHYzIQ6GrspODHNC2B6m+3PPwV9vaoN04MTfF9EV3Nney26xuzq88Y5IK6e0Sicz50XtPUF/sEHQNPgBfh+v4zwKlpG6/ApGMRC67hmmwGFRWaUhsWLFb3GYAz6GR9gFgKyKd0PGoJp0pgzIJl9dmM3Kov9iJsmn71ePOguNSBbt0poglJ6tq4DfiBXr5aYeFc3Owpe4tgKS+gHJkwAevQQf544IVP2qtHwrbZ3ND7aJiPN59b6YMT8vCD3vGp74n2AiiF7HEJR1D7dy+3BxAPS+B+b3xN9L7aL0QwIrzuq5FL0Pyqza4NKrsXIo7Jwns1ME2yLtscWW5QyVOmYsoCb2Y4AJEVSBGI+WojMgJ6toiM/ebI9jbK4Z0lLoODz47j7TgnUyXLUBMHi765+PqwMS7wGqXLrwAbGL45jBuMUf1fsUfq6P5OkJAq/OIaLyUugaqqjJi0O7tc21RLM9pec3H8224A+22tFKPBgzZBN9pGF2DeRVUCM2PT3iOqbCnx8h6mYiq5i8/s4jIsp3xd1Q6o5YoRSz6GqUyFpwxLIMdTCBmyCLIJnoz7FA0haYD1LqX6PLARL3R9mj+n0ffRyAzagjjitKr63ZkL1+8Jaorlo5bDPUe2bfh1X/E24GtnJ1HNcK8sxbLhdUpzas8A4dPuvl0mkcILHAPQIHC1+L53+Co48kJm62MyEWufBGpyY99kKQVDBNr/5ahTtV99hcMIV8xnaOdzZXovOcbvy3HEOiCtnM4rncucFrV7gjDDeuSOp8BgZvotMSIIgrEdtwZXuqMU5IbZZ0SOlLEYlNezd1r3w8fEJYqdeX99Hq27pTZTGNBpoN6saELIb9WtwGkvOFhXHdMdETEJ38beKXEaFrjKKy9g4nGrsX0udLyTHU0xEDyTFcwzGcBMchb8TE+9qJ8SaAbmw4AgKtCwt+rOm7u/INbqj+GjxPqgMCH9jJK3OjZnIMVJmpTzb7cPvx8qbjFgf5EVeXDYw4VmyALclkY5oNLYe7Tktw/VsEyfi92TdY6wGRPVjWpGp6HRGGozflT+CaftLGX10RHnKH2PL8FCGqjIEM6UJwp1HSUR/p+NbdMZ08bdVlM6afeA+zHxQpIysZ4SJRjesRGdIE88hguCHtEiOAGO+abxPw3e2RaL9xWDu1avAnuuyyHszPkZNmJUtWQvxvv82bIP01ltiHhagZYQyINYaoWMJ30fxYG88ylUcY1scw+zZ0nhVDoeeCaFjUsLXVqNBPShVwKyGwvqD7dvNQ1TPocroMhPniQ5iJ0Ku9qOCcQDFFl8ikaB4V0xbumMQWcpb9f1Sa6erxyxMDvxGXLci9mAfKpo6bYVi0XmkgCebtW5FHViggOCaiNXm6FnQNX+Yld2I2qY+svhcMXsRAqwcM7VTTGdCHU2gNTjx1Uv7NeQoOBGdN8Od7bXoHLcrzx3ngLhyNqN4Lnde0NYXOLnZDx+2feiJlScd7yNIjL21kcUprpmjteqF6Yl2aIc/hKZHIrxEpcoJDDVXzpm1BoQQkxRPbLzudzoMwP66IwV9rGLfUdHh2JpzFuTyg6wao5m9IJ2s/SiHCthv6hqNEz2S6op+q49x1apSZD6e107B8sPGj/I8fCnqlhiJVrSVykgKW4/BsXq03mdec1r/GyhSU0K+dlQZjH8rDzNYdnS4Bv9esUJSLTPTRVHJyEIH1HNK+FWSJEBj7wEYABndJJvPbWQVf9OYbes/yXBcW753EqkrFRVGcFThLpG9d1aoTscm9yWomw7q+32wp/4YowaE2/QsBus66ADy//yvnXdnw2FhTchzJBPniS5YSfbswH//2UZeCkdwBNLZVU1XGnc8R7Z1RWG49h7zTJlDTkW2ezZDuAum4Dd0iVDtnT7HdCj2+to7PLrQoxUm1rLwUcw7K53YgSl+wainkoZMOSwGi5w2QN0opnNf/8JEZPu5p9ij+XunseikxPKr9jhxBqQKeoBdaRpgQfNVSJ/exk5FiKA+z86uNT2Dz3n85t5Iox5KiRDqBiwdwjfSEuIS1AlRMKa/8RXaQONEf9MJOmtBQc72KHr2s0KleZVp6Qeh0wPJNFY24xUcumerReI23blaV3UchjztFSOkDRGZAWtwYmjSMRjy3B41YA1OROQaEd3Xne21iI4ltvaPc0Bia+YdXNedF7T+AifVJWn+goMBKqH/jTZiNEoV3dGUMhJOMb3/35sjperNyT9F1gMrEZQiLT6t8tDEQqM+uNbj3i/yHIfPSKNqXa7O6JboN8ESowpxI/uhdtX9oS4BayvYGNW8gewG1z63lcBRHEcJ0+WiI2ujFwYPKb0OQw9LqpoDfVdg+IlGhsYAYQt379roTHXVZwVxU50l9v0uMot/OoKJcDs/hB7BNqrbX/CDYC9SkVUaCtRNaNtWsnRZm2J0oTEYkaYcEOVIzYZNsJIYf7LfqD4wgk4njO1DbMV2fGi6VGThLhHpr76vXbEyFTXVBLDyvH9/sbuCmOjrRdd44D5Tsv2ELjfl/hXTncO+hwXF39GV3WEmU6/n+DLePPwTIudWtdMogqI4Her06NTIar1Yd25d/Tr+2p5LbD7XfCh6+A+JkE6GmmNpqIXgBZIgMV6K4vdWmCsyRWQSqlhRZkIUDFT1Q4dIOWJNcpQBsbL+1dg1GFV3jRCn7PvlDYydKwXyVDuHgoJhaw8q4gPsMd03/iMytRZWiJynRxe0C/xNnHtw96f4/Z/kYryqkS6bOil6U4Xc3iiJ8om8HVLvRqZvoS6ISPxghUrTyRzj2xItsUAQajAD/RoJTGemc/UMyYW+y59oIwRuY4K0ISLDswtOXOwpssps/Ts+QJKs6UINTkTkOhHZ153ttYiMIzb3jXNAYnP2Ldd25wWtXuDW1HQa+AkYViIEh1rwyWEyykxBrv/fm5WFhlH/A0mrouzzXbibKh/mD7soYBDWTIZ+nNIHIRONB14Y+HjOrR69jK2PoRUGUBqHRLGs3qhjMgxDTduYVVPFk65aJ7oDMrrkYvQ7Kgte9wzdgtEHaxjGG6PmSuODUdpqWc6hYCNZL7K83Fg0OdDb6JIe3R6WYQp+fdVFkATYtxAE0+B/82HvkfZPYz9CvghVYdYjtMZnbdOmiEHTdL0eor/+TVwHmb03IDBNZhRIeRu+vrar1cAWbIHUy1DiZK6Au0T23lmNjOqpvVGgxfvidOtqT0WOMd+B8EOlpaJnQKyGl47Z5zi3ooapW66GldDhe/bMdonhGIRBkFHnk8nK4b2AA4LZisxRVgMwZ06AmYYbXpcN1fYBGInRkDVIemv8yVMs2yxFRy/V/R7fh/xqckDCG5dOgFGh8CPsPSsz1j4NuuOH4IniXMp55Xb9fSL7ESIyAYSW/ZvmM3yVdImpToWZvx07zH1W91V9O+hc/YDJYic6XYqxTB21G5VQCXtBR4TMTdbajMjU7+gOCI3yib5NBfU0C69TQRax6GPl/nz2lLYPf1fEE6SyTY5ndveR+0Smb5F9XhwdZ611YR0VM87lcBDnUUCw3umwOt5rZqoXeBdAAVzEQZQR+1pbbH1LVD/sghOMaBLjS8OCg+T/QwlOuHJ+9XO5s70WXWN29XnjHBBXz2gUzufOC1q92Bzxw7P+g4WMjLBkxS08RHqHsxDbL7Eo3BqXHaqzFOXJI2FsJ1FUREYVnTEvplLJKsqrG/WqmPNO/KzI9Po2dqeohZGVNggDSBftiq2PoTXa2B6zMAsSb63aNlTHR9hm2kb4kWNDPnLTb4Vg5fOyiZwp7LkVgkV4BjMhp7z8ULRKOnHheZl+xJd3fzY6oYt3Ka0Caw8J4fjwQ6DXT2mR7MUjodabetsKoWNAylhHLEOORsnvKnHlzmZCaMiSaYyMRSz890lVEnn9j+F5weJolv+YwXDFaxXDcSML9XOuX3Gx9vcugbtE7m7Z2KzU+qYwnsrKKMgcz+1IdM8aIKmMXYKamm1JTU+Mvd8u2mAljnD3ylhlkGACehrOiCNxQfaR8MkUpw+gzwpJTzuv6gy8N/kbMKOgngk6Ktev27IWJBH4Cv+IaPWLF5ICPbyslSLA4Hs8e8B5Q5Du1g9jcKBaH4OCV71/uL8V8qQyAY6glKL2yeJU604xnYmf/doICBOZtwg5tVINb0vZANWfrIFfwgzo3/6eaU1ybsJzshytP2YbdRIJUs5Sz4O1XPnhI+ZQ17Hi/jTOdZ2WwRhmBE2oNXMBMqumt8jWqET2mbEeZ4VKc74v+GVABjwIs05ze+pGqPZ4FYISJ0fFok8MgUt1fld8S/jt+/FHGeghJJsOKQNEnOPwIKfW4ETz+fWRetdaPEmaERN73xWw1dCCE66aW+t53Nlei64xu/q8cQ6Iq2c0Cudz5wVtjTDqw9SL3LpissGSonDBat/wPo5RmLq35lArRpdsYisPZUP6F7ewK1kttMqwwaCq5aD0F7+u5EuDdJVPERTBWYc1FZH9ULtiIknBrOsbTEEXocXAxugmYRU0zFLiiSGIxd/4QSKsz1XNWoT+X5/JeGecxKxP73QClb59z2ERuoyE2iK9NCY/x2KjW1zjkyHPw2zIqUSl7OAYNEr5kc1V9V2keXwNV96tjiertpnIBcIapzIAuQ9hMDQuw2u6IcxINLNra72zCujbBtQyMTLxXLoi9UgMMIxkPcsZk0EDa7FyA6zCKjQSw+bfayBpp3V6aiWQZg2Q6AJro9AfAzEq2mAljnD3jCRTQJGwq1EYEGaRr3pP1sVarEV9MUYWeO9M+6nJIafYHce7zlsq25Nli/Sp+pwwO0RdFEdNXx+EFx2a5IXZFySVqQ4z1DMOLK4nU5/etieuiWpBm/EgSVZUyXsTZ86Yf7euGeUUq/f/4w8/RertK/HMIx0m9H0AGqb6OVh8/jX+wivEFw5KCP+fSGaJIitGqFPTsrdXkxRErhcXcDN3RdRPuwfe3nIMynGn40eabF2pXtdrCi3w4AiCFt5z68rf9e907dpA5WKP0W+s1DvZXKAL9rWcgs2bpbGuNz7/qlYsF64iQ6lc4v3BWj62yDh96vxkQmRfwlKLz50bol+hBVqsTGp7UUHUEVLLiN9A1RwFJ1w5v/q53Nlei64xu/q8cQ6Iq2c0Cudz5wXt6COrhpoUAbgTLwtShjwB8bHv483b3DIX5coB+821x1GYrbfzUHtHzlZ4qnDY+sj0F78V5340+Qco8WwPHmYsgE9ynrcTkosth69gQeCCJpK8A1VRFbuEtsEfiTthcNBAMcT/4RTO4H+mG+lKg9eOhnf0aIAS2mwsUOFXz0LDq4xBZkJOvyqIjA8vYH/8Cqjw2vbF1gvqlRaCPgieg44lazuOoTiK4wSkDsQRsZs1i+hMNsSZeVHPqIKSsPYmCIkFBEwxCun9TAibMvxMdEBHzHQJ3CWyT6a1WLn2/TnIObC1ON1fbXag1I9VTVFOfU7054pMfalSvMbuo8kERDG04m9n5tSZsTgKzpDWlo4fdT0GYQQOQmr7dMI0/I5OdqflmmgW8Cf+RFvxG2uQlH6L2pnkEzQKr6b4H3I9PYNnxcrj3+H7TOQTrVtLZIqjpr/D6WRU91uGZfhM7ErnZz3qCietfXsp5MbGdwghiXrjWukAT7GJ9QOZcyQxQfv0oIl+T1mgzkcwVaPqyH11B/zS5IbvzsuGkKS6hv58seYEadMJRywqYoSqbohZpAwZgK3eaZAGj6FU0NW1lXOrMhk0aJXAaFGcxElIYYk+GINx6GM3zY4gaM6sIVftY80+l4Q3vCFhjN0wCXPSdjM5tVx3hQoBRb1ttZwf4V+DaS2qpA06E2J4YyRpBqHHjpwQa3CCcDJCxqzK9I6CE+FdN7K/u7O9FtkxxfRxcQ5ITM94GNdz5wXtCGagD2UGvsE3mCU2OSow5nZG036OQdUAACAASURBVKi58P9zs0JFdNXmyehqYKMdFctaPy6KavQeMiAT7tnBCMKKhkbnPeBHS9f9uI4cQlSNwneT8KMR5SVOX9E/qv64ItWvn4uaEqTZJbziTvsByDxbMkKN73kHNVtlCiMDAvyLjwRMjP3PhevGlFnVoK0QErXj++8DKx9VRfZLu+CbJC9yvvARP1kzg9Z7kU4iv0zKys44k8oQVjVCeobjUI1++PbhaCPSq57H/T7pkez5Q5wr2BBBi1eaDHzuE5XIZ0TXmLVYucLhKaiz8XtxmguLjqJAsxKG2Bi36Q6EowDJZY/CyB14DrdzlkG9jAejTQvEmn2hY8fibkUlOwCjcAvZxDh+Ql/0x0+mqVGG9bR3x6HTVWnU9qhzFqsvFBIRf33NsK5n+6vKyHB2N55kK4DmJc6Lug0VuaeBbRU3VBezElkMzzodg25JT2Pn+IMYt72MHQEGz61nAbi2fvAfjuEYIo5TDFL6mtZhSFanmMfQGS+Fo4YqNwkzbkoJEjEOChDW2CoZjs6tOo9CDQqA51ywQO4T0TVp/XbRaQpEUnEuRe9spWlW7yEGzQ6+KYnwwHNRrK1TBKs+q/edIwhaRJ+DqOyvB6noZNbwW4zFkHVv9bFavHsZ8Eic2Fyz1DLXHsy7JjWLeqWegQmPJWQ2sqQNzGpRZonarxFpDB7owSt1rDU40a53OiT098OJvI2wotUKQaOuQ7BcFVwIq+/ubK9FZM5jc984ByQ2Z99ybXdf0NZCS7375bHP4FLXDWl9H348rel8N5r+GOmK1Ymgqq4vcoprszB7TamhJiyybnjqOGYWUg7xtdH3KoYjvZAyNvDI1o99YrzAcyQVH20yMo1MOAxXgiU1rSMGKVf22VoD0sTLVvyqqFkd1YDwQ0bNle+9WwvV4JdICA8EGkWn+1Ae5XEgTBFCtZhWoQEaYA3oJNYqdc90b9U+HDM1EhUMxNFCdCZ7qBvhw4cDV1ccxeyjkjJVh0aq8/Njv+9xYaS/ew5n01ZAg/R7hcHL7A8jxs7UFLjyobEWK/fHKIyCzJbR0H2UNo+I3ioHK7RIu+qTUnh+gHQCAx9dWiDWoIL+TI/AQEG3EAgPE9uUPm9Kvb25t42qOj3ui1o6HYqnoFEr0VCou+uBB2ZHFJV0aMaXlQCj6xPb/A5qeQnpy+RxSIChsgDKyWiNv4TwKRvrdPYkrCagk0pYUYchWZ1iHuObOC+yB13GjbxV0TD1Drt1/8t7nvjhpNQJ6VlpL1bdqSDWpZoLZ5xxfX6tzmkOXMd1SCaxuXmHYHTioThrQ/GI7WoOrbUjl5AHeXDFxNBlfQZiwvgN7bnTYbrMXDU48xOyTpZscL99dwa30hQ2qMD1c2TGbYOiW72XGQh5+FDu5azTR7gVM11RoSMm1JDitXrTvyuD+wdj2OhE4mfvku2Q8C9PEUhSSuj6/XPl+8l6Lne316Jz7K46d5wD4qqZdMF53H1BW6E15iGH4DT+J/CY/kiJHPCFP1KbdlEFvi6Yqrf2FA0aAHzBstEhm9rmMKr2LCP+Pe1/v+G7051NLDT8AM6dK/fnh10ZGfz3xGQD0T1glPitdrH/sMsnGwJsumdif6soWHRPnPVjz6Jbpew+ECMEHv4+MiA9Hgp4Si1sMnXJ1X3WWbA2ZW+HT278gZB48bB6+SvMnBXPIQuWgroszNsfn1+S0WpdQ4Piduw/Mfit0q4TGQ31oea+jC7y3tKhmINWgt6UBA1J8AKVK8cz0e7SkXzwAOK+0RD97jtJf0rWWT2q7IzImZUp5vLU9cjTVSqf98+3GI8+birOvXSpbcoVPE4V4/IXspGxP8Tlx2QWzVqs3NevN3pjvOisMsgZvZ06FejY0d4osmqBtPb+Ht9jijiebH2PIbHwUYWVWJ8hHYJF8oEXu/Yb4nrfYjpm4Fsow5XFz9Ww03QKdZ9JgaqKsxlQyJ4jvgnaxOg2CQm6eNtqJBKCRVPxxPlIfU3m4tCyiFYCjBaHu6M7JoljU+OR8b62EmDo7yxmWN5/vA3LH0sxREfU6/o7y+oUb9kCLPeSRdF0zhthlWkueA/L3VqBFZAq1/WwBusgrVEFXYzomrRC5HRWPkeQOJ3CXO8/79O6EEm4ogQu2S+VfVIDcWUWNyLva0dEJYtTtUdT/9lCY+q3cQHYuMPDxJqmzp8saQjuBaZEspBn2JKyMRq9Wmb6ljjj9EUEbhXWuOho6+9T7qsHJ9K+uod7yCROMQZ90A9jDOioo+BEROYwIvu6u70WkbHE1r5xDkhszbyD67r7grYWF1uH8A1miI8tWw9MwM/oYTfK2IwOucOtVtFEGqmMEnXIuhYzb8nC0zVfL0P/Q40FDtZRNFGPxtEQqH99qlHwz2Loo7CpXPN8uiEQU2O3Rgx1qlcFuSIU60Nsx21kFjh53dB2NYZad0B2ZG2OqrcW4VXylFgz1x+zZsFOB0QZX3Qgfik4DR8tk8rVZXAQh1EGug7CJHQzDDhH88tIIAvw86yXBfif1gzAyk0S+hFWowFESIf+EXZGqFE3lpgJq+xjY/1SNQWqSFNdf32Kpqj9dCmeJ0qJmeP9RSEoYTeqORv5DG9MzvxuLVZ+8FlHpF82Uxw6YlAQXrxOJByzwoUhItZWQ89aIzU++6/oeaObOL5G2iPY6iefj8jCSkIbgzWr2Ri22gplQCtH7wreFRF0a6PRtTddXRS6tB5PkmVC3uR3TIrk+v7zMnVDy7u/ik1VSvjD65ik5Q2vANcaHNjyThvU+O9vvIqXAI3qvMT5C/GMomOeT82vdXx6UIF0wSuLDBAFxqpgmfdBMU7Z0aeGhCAkcWLECw7GoUKtsL75HHHcvHlyhDTmywTaGMz+rvYnHjVqA09PGzV5WHUuju6RNUPFe6IIDQYWWYY//BqbqIT1LKw1ozslQTd0eSXnPgPu4QEy2F0yJp8Z/eL6/VWGONkGq2MHfJEdOSE5uK3UypJdzVavdhzFUALHTeMKz+mzCs8687yHtY/VTtCDE+VSncV+fyleqavShxWciGp/HB3v7vZadIzZ1eeMc0BcPaNROJ+7L2jrh8g6VBajX0dOEd0ibj4vLiEYiQxjWv+oRWGa3tpD9Y+ZKpbTKWoVNaxuJOofQ33+GaX/5MlSLEVTMR9Ta6/Dq5p1TB9q3RCIqUmzZmnawFZYS2rU3agMXQfAWsTtSgy1FYLV26ueYA26hSzIhltiSqwQLG5TH29iplejodiPRiWjsuVgi253xm+YjjfVug4mmA7I4KABKPevrDup+O5N7Lsqlcj1RmeUStpKuDG0exWe864ivcqhG5VsFPoHSAjT+I4+GL88r0lsjdvX5PwO9a5L2qTVCwMwY07SCAnbuWpdWYuV15HcSXkUTFm8Se3VrWtzkKzzYY1064ZmUyw2nhXVZ1cZilbc/Zd+NpY0FgEfQ0lTJixFgkC8fCV1C/Sm9BpO4X94D6ccaHDIvQnVHILh4m/CvTKXym6C9oUWgbfOj1e6Bvjg4Rr4J8mAbxrdE3UYuiimmh/rez9HxkBcvycd6dVZvkGPFDMEREoFTZjFUDUdVvrUCsUDUKxCcnHsgTJdkNRzitCXFPf7TWuQ7wxW+UhyitmFJ2DMyx7i/M7UuThaj3r/WVyfYqEnxj6UEK+K2GNAh9Wx1mi/yqzxd2a01DNfCbuxF5XsSCWcyRa46rnRz+NI5HbvjZxI+cgXJ9NVRZP0O4SzZyXBUBnf9UmboPbz5QiInxyNazzBpcvxjBokig+vXh16r3XhWX0vZh4/w1IBQVyMZghCEqeGbp1DPTjRo6wX8rWV7G0j8vyBWzW/BuFiYQUnnLpoBHdyd3stgsOJld3jHJBYmXbHF3X3BR1eITpHNQyDMRhS5bYDZsIT8kVvZRdxo2mPsa7YwZPyAoPjjcBXPoNFHz7Idhl7buY2pfR1Y8JqCLTKvRtzrlQWx/5abDamBrQN1RCIqUEyg7Frl+1qffETfoLEICsNhHbwNNbFh/G2Y3tINVP3wjO0nR2LlYb3aZlqSHF4J+6lzodpP14UhYvEDrNInX+rphzAmlmOY+NtqdauMnqtMAdzIJmZHAnccTuzJzSWqPHCCJ1iyymEs4bugrNj0PcLD9qhry9Cu3r62iBISvAtc2bgzh15VkY+21y3aRvkxDVRj8RaiatXZQYmOtTpHY1d9V0pb1MX46uFdZDfZwOepMiCK3tuiXulngFHxdbWSHdhnDFY1tZX+QmDn/WNFi0QK+6+6vo+KLR6nBhmJtwRcBFSAavic8L5gtJlNWW4GJXe4ZsH77y4ggvZqiFww3YxXsXexHPRyKLielXvn43ssmKSoyPNmp2w7pmaH16LWjfr/c2Cf7wGnW9ekwa/inrrjotyApi9zIy7DumdeR71DFvpU0OjflZrgs54mqA7uIMsYtNo9DPoYfXATETeEdasrF5bxHdScM68oGOrlM+tmWPdwfwy2zb8c1PCzwZlm40/0FY4WwrWx+3hZQvUWJkdGjdOFmoz80r1ea778DQxQnt3WGt8Xjyx1d/tKdQWhzrONtX48DzKaaRTMiTABnnkfeI9UMGMsAJDodkFKeEPb5RCPlwSXWbtXG1sMKCQYb0DdcIa/fzMFFbxW4mVkC9sVVhvDSRFZH1E5l3MY9zdXovsuGLyuDgHJCZnO5xrvQ0LWoe0OBoOsdqXkUeoyzLtmx8X8YKK3W+E0VyN8Xej2xduVxzRdU7Fd/gOMgLNDFL8ZElN2NvQqEY5n9kCL+ES8olj+VFVhr7ekZh4EevX02kruf1X2BvBehaBxdGrcnQNlcYz3EkNYwedhpeaHBnqlME7Nw/jVpYSuLfpqPGhJzNb8eJA8uQ2ZhgWNHptfIa5K1OIKyiaWl3hmnz5qphV78b//icNPNZbDMw0AyPuSljiwm770XtZOdNY5XEholC5JjZhDPoaWRfr0MKL2Cu4i4KRzUcLtMBCoblCBe5SpeKhUiVgiiyLEIX2xfdORz9fmcUhNv4ISpsuG57TE5X7ox+r7hVFybp0kZoBYSliO4LhWNmoyFr0HMlM94/OFYXQ+J8eqY/sOBzh7hW0iUJ7rOVIkDA+2gfbIudlcQCHUNbuko+RSrw3l+AzTKm8BDVqSN0Pa/vlvdn44WR7sXnXmD0Yu6uiU1krq0jdlaSF8e7zc7iQoQKG1NgrDGEKmVqLvR0xjB1NVAYlXh7GteRFUCfXaTstELVu1LEqAEUBv3MoLPquw2fUGHltBNvoob0Kd4B3x5lGZlfB5yKyLq0aIJ7Jvke7APkQlC74BEfOy2c8tG+U7sDQebyJd8T+Y9EbfTHW7v6ER6TBQu1GjYCnTx2vOhrfy5c7Lz6qzmKt8Xly2DbX+vdBJzbgscrJYMBwJjqK0zG7czJlJUH7rFpo35LQkBFkfLPOzx5UxCfYjADILFhojYGS27flr1ZyisHZPDHspgxs6us/shmyMDsSxo9vg70W2bHF1HFxDkhMzbQT13kbFjQjYyVLhv7y5DB1xVhyj6/M1c2ghoyNugQnpj5GdnH0ol6GxmiMFXiE1EgLs4Sw1UCyGgLJ8RRPIfHff6Xogl4eU3D/vnkoEflQR3USHEXCFsdrhqYhS/AEKYRxxcZo/BOkEn+TvvlbzDDVgYT3AXe2n9aoulJwpmFbmWCwysAff0hsOTMgzFzwbzbFOHQNOQV2mhh+YqmpG/ApViIASZECT4VIWmiNTkytx4uQq09zscs/X27CpNOf4OhR8xEUnVuOJmJjIJIgDy4btK3c5mzRdNeuskCbjWPZFr8GMp7YioAMOdC07HVhpFo1R/R6hZUd1mGkdx1TliCieHtn7411P3WvFPyN87/T7z0BRaKoXzlILtSwDFCrFgihJau938E7uCkooGtgq133ouqg68+kEn8c4i2Zz+4io8gSsOlwvkZYYQgsqg6l9niBR4Ee4p9LMnRCs/syKGGt2eG2kSWXYcBRqd+xd+B6jPKu7VTdjlWkbvGuzEjx7C4u5K+LwKVrhUPuiO7W0XO9FE3QBMvfPNf+wrl1JFxnpU/9MPkB5G8l1d7X1JuBXKO+saN+5to95JMGHoGPsTdLY7ROsUxkZJQTw2PDc8b1G62ySKrubiE+F8Kiz5AMKfDM2DW0LL2ClVKn4sWLEPgjFVLiKfZmaoiVrVdi2zaYnhk6PLoQq94XFuF/8oncEg+v8St+QDMsxnR0MlTW+RuDIceORcwJsX4fhpReh6GHZQH/2FILMfvJ56YaH71fzJjm891m6H+Q6UxletV+oX1L6DCp96balxpEN5Bd1PgxAHIJeVEUUk11Mz5GfawJE47Fe/XihTybvm75TOvsbYNbXES6svlMmZ2Yeme9Dfaa3QvPzTbEOSBudEPelgXNjwENNutLx/iYxvPHlXh5kPb1A/jFT4f8r88bxXo6tpPpZ6rNPnoko24scp8wIfIpaDe6lQ67oqfyVerbO2EZlAw+jHMJiqDwq9OmehlrDYcjQ4CMY/wYMmraDEvEdXVWloh8qKM6f44ipWT9qQIvXEQ+IRyl2mXkRm5cBRVtP/LYK4quHRXeR6VPxCxT/4ON9RhLD+RA0gc3cKdkTbTNulEYbWRmI+yH7GKffWZmiOJxW1BDGK6qYP4qcglNEMIJKmKfqXu6gjh/oBFd1m8jNqK22M9RHQK3b0c1EzOSlTLX2aJpBQVSGO9LKYsjz5MTCChcCptHH8GgQfbPLIvTvSDx1KzX+RtthGPGcy1cKGFaoelKROXeWI+1GqpkuQrKmhOJb/vifI4aWNhui8iKEOfN5shxcLT+DiarijIBu3A7SU6USnfNVGzM80TVQVfGEbNeSq2e4mgfYA/OoSAK45zo7/s4LEgM2BzVDunK7YSxDsUwsa9ituLfNMy5phJ7/Yt/8bH4vTkWYBGaC9gcDbawqJPNAZAQIVKZCMH4G18J9i3ldDsS/LMyjH3p/SN+xC+iD2nxEI+QVvxtdZbt7mvuzUDNmvImcoF9/rmJPlUa+QBZ2fLiMnTWMLKzPX8eMXpo6zuTc7jheTVkv7QTt5PlRpV3LgujXH92rWtCZUCUg3IIpYWoqK7CzWeGzwmLucNie+SzyTGwfY6FWIgWxqOgCwByY2iaGKE9d9YM+y+5f8UPVyQJQ/+PD2F3YGlTjY/1PHWLXsPaU++KzT8nG4geARJKrVpogaH06e1Zq1jPyPoYNq5nOlo7UA3FcFJsW4FGaI6FYToh6hlX65bPGNdXq8O2rDphXioIF1mWtNDmM7ztb4u9Ft44YvP3OAckNmffcu23bUETukJHRC+eVTCW7/ErfoV8+ekqzMTH0tH4+mvg9WvHk0/KURYlOlJEdaPbZXSFqe9p04DHj2XEkhASGrPWpuO51W+MkmbEfUHpygJpvTnKFilDQBnrVxLlx7svfeCTpRLW9d1tKkLnuWKyINKKteb1ryQugHeD7BVrlYgiHajUeIz48eMZ68FVWTJSoqqiWmYjOvZLByEk0aSJ8DR03ngaEDTifpUEN+Cxe/YA41/ZDK3iOIbjkDUhhM51xZt0w5ubxiiirySaMQwaXR+HhAN/J2wvNBNUI+zuEdIIjQjV6PR8gi3inyy+VA5AWM6kbmgRy06GrzXe2USx/UbUFNShbKrglH/TwFkz4TwKNiwkx5RjLE7X7S0w7P36hV7sHR3PoCMHRDxMlKF2cL8cOSCOHPRZaI/2mC26zLmmAJ0rHXQrxIjXueRRBHkCz5qcVL324ff0A9DpwUjTNNbMfAwb75QU2xZ/MBmFfutqugfcTmFL2uzD6h3CP+clhKsjfjdgM8pADq0GQQ+A5Ezjj2uPJE26zubGDBnXHINM+rvDyjA2MfskdL/RXRzfovAxLDxb3LTuVR/U/KhMzsBCSzDiXDOx709VNmBDSC3xjKrMnHqvHUtSDsVfHMTNtP/DkiGnDHa2iKqh606pcjJ8EhVG3pfncDlzeazuu8+uLsK6tvRz0IHZlfMLpF0/H8HxEqJqmecoViohaIQr55hjc7Q++W6hk6CaCs6ofy9CMzTHItO6cKSJEdrzZ63xGeFvM9SVk6jX+FizocxaULOJ76K5+ELQh+stNPg0z6O/03hMb4zFWPQVhxNyexDlQK2RXahiBKLIttUK/xjq8tZxqfVnhQ7uzPo5qtxajKCESdGk5jODvS2yOjGRfZ+9bfZaZMcZncfFOSDRObsRPPfbuKB1o1OPIiVAMA6jtEHnpxiQiLXnyzm8FpkUdHjndPXvYWF5+aInjvcjWa8oxqwrCnNbnszPcOmOxB97JumMDi8kXatqjl74uiHAj+HW+DWQ6cRWPEyaDe9n/k8UD0emINIVc2NlwKJBfsrXhmtXGRpei8Wl5G9nK5DkGi6+kGKMbK5wmtR8ExZDPYt790LwMl5iJAwJxsMGrbHr679MNLz80K9dC7AGQV/HjDAvQEvRr3loiS8wX/ytsgX6vBGKQE0PxQDE8afwtRVCO6KmppDbdnxomn46ZWnwyIB3qf6ENS+6kSQj2SFCjZvGxD/4El/hH+FgtW8PkAmIrTYTM35+WL9fSq9PQA/0wgSjL+HpSrhizahzWA3VypVeY8eehELAcnvuthiSfbYwVMPj+bc66KPSjEP/R1Jd/NuKJ7D17nsGs48r1pr+XFP8kRCbRV5ZBfREDyrQuGPGIQFemwIyavw6XTXX3M3KzY0slO408u8sTy7gAgqKQ291G4uD1XqL4mWVkQ4NgqIXy0/ochU9puYW55iRfTiO1x9kMAmpPukOrzW6rkP3GmIljuVsKArkFQGFOlav7enVC2jqbyOgUKx/vKfMbhDKxCYi7X51gA0bgCxZZMHOm+0RVUO3Zi94HgpTpoMfKOhIOCWbyrw4yl5Y391jPYagd6BkIcuNy7gKOY86nbijzBodXwUrohAqAw/MQKlGSFha+OElEhvbHGlihPbcWQ31vWnrooLfejxNnBYdGj+0q/Hhs/Jmao26H6VXwyweM9d6c0SRHloBuhJgJVSVASayYbJRBHInqorsN9sLJManWIENqGM3LNoKhKHpa49rY8b5akhxZCcepHoXU368gsaNgTFjgIiujdDm0dntb6O95uzYYmq/OAckpmbaieu8jQtaGZ0qcqVHF/XoLyE3JXDMwP47mg5rRIYfpUOHnJi4WNjFWdElQlholFLzgxASNoVF1ll6GDEaj96mkThKeVuzDL+jIzpCaiUodW/9JK6qp3Bmiglzos3ASCw/tIlePsMzSAeLehhKFI7/boH5mI8vxG91sRbrIQXz2JxlkQmrTzoDFlP3rZsGYM8xWfjIwvhukKkOxbrE/fkxpgOi01S+iyu4gjx2lyJkRhWjqh+pVp47t4xSq1Y133/Y4ZNd/HNSioHo/tQMa6BTMgG9xO/rURt1sEH8nQ8XDYIBZyBYVgrO8oUfY99ZKbzn0+BH/BD8s4CcWSk4WQBPg4eCdmdKt8JXIXMMPHt4uhLOrAln97EaqiH+/oYwnorQ01AdP96xCKG6ju6gc6wfB9gYc5pgqai1Ue8qV6w1a+amfLkQFHnfA4leBxmOn+rbDch6lJ0en6BaoFmAU38eOuXbgt99ahhT9//YuxJwH6r//dr3fZcte5bshFQUKSqJLIlEkUoLKbQnQkmWLFlTpB9Jdsl2EZG97Pu+Xq7tcrn+z3vO/cz3zPnOd7kX/dNzz/P05H5n5syZM2dmPsv7eV8J2sg6uL/kMSzeqlmitj3VA29e+lTd22BFuOY42U+5a386hAMCCRMIlpzYi4FPosz3pFyL369UUruyzk+y3XKsOMt2bc/gQl/glb1d1W5dH/kLq86VchW+ixE/J0dr1D8xQWUZWjW9gkOHk3gWyIdaX+76DSAlLitSFLbv07+I11OPcNXNBarfEOeNa6dl7ARMQGvVhzDhyXMl82NnK21D3XQ4+W0UbRgvWuBw65TsGp9v/yiJ7Ke24VDeyjg1Z7VfjQ+v6dAh9wyKbghr3ypn36feF4SVsXlpEXnBHrkvafjz4yCWohbuh0GLGCd6ORivOhkWBlzuwha/9ynXM+FqNrud1PKRtro6VjoXEM57MtR6ic/229Fei8/1/RP7Jjog/8Qsh3mO23FBmwaxGQGSSzZZkMjK8wyoOKWVe82iwkBTFO7LN8wpvim72aJLjJ7xZU4ng/UsgdhNzJNTbK5drpn4eJ0WIXw52w/4+lSzkJop9ge1K/o7jkuzUpsQEVnGhXMPVhB5UybD6MTOgJRMuRtbrhRRe1CwrDd6OnuXxUZshIZtvI3PMCj126oOhC0U53w445aPMTMbrDXaHnEUR6E1OD7Bu4oqmhmBjz7S56PBwCYQLN85ruMvlEYpbHF+8hLq4kZ+KMm2RSdGmkkUMAiv4jUMcg1f1K+vISkmN5iAlrO0U/Y0JuN/eNqlBREMgmVTcOY851Og/7lqb+xt0d0PaiIDEcNYoFqEo5kMTDdaJxHO/bIN1cZVDmDqap0Vm1L6A3yV5UNlgIbKgNgOuunkd0dvjMjSXaHwpN2og25DsBgEEKfbdHR5PhbTV8EabEIZBwsvRhPrfgZBL0JC/eTZkHVFuCAbnYSLkdEKSsYmUECuZWZHWMvEFgxGxO1Ppv8VP53X1dBSR8J/m9k/sw8T3kNIYLqYSERCZ87kOs1MjcyrH7Tu0PvAJ3FOOGm37rjDBYVkwIbv0A+jfNDHjDirAldeFMGh1pYt3hq7/4CimmYjo53oqYRaD507+9jjmt6xAj8e0vUN7+cYhvFpOioj3fye2c+MDWEz39svJR2BYbGafYq05QJdkjGFmxE2a3yYcbuItEiFK5iE5miJSX41PoRgingkz8UA4MiY51Q9EBncUiMa10BaMl+z15UX7NYkGRmGjuiEYZ63yaQoH43nHaikfT7Cm83MtGSwmGVphOnO7uFkikOtl/hsvx3ttfhc3z+xb6ID1ngLGAAAIABJREFU8k/McpjnuB0XtB0BMXHwvOxUiMYfqOp8cN/FJ/gUWhzNbv7R2ZsDxwlz+sPerWRJYNu2sHcPuKMZ/S6PddiRtnxACl7pxIYUkFGHAnlsJrtOMEjBjY/cuwf7Y2RmwExNGB7NSOQFpENyXHPwxuFwzoc7dtugbX/fdnyzVMNW/mrTD91OvKWixqZBS+eBDond6CB9hu7Oz/a1yAZ+nPv29alA8/fUqa7j3OUU6jql2NfsX4xSFuk/itnYgeJq83v4GL3wnmsowQwRm4Iz+ZrfHYE1c7wmBSfhJgsWAFnqVED+U+uxLW0FDGy9VmWgTA2Kf0ILxM9QrbkZIKaNbcAA4I03XIZqoMCE7QSXKnIZm3alUVCu2bna4rUMY1wQrBulBRdHV9YRhQHFwKVg4Ef40LmHhPw8gV8UBIhirWySZTLpnb948xDqtsmrnEBSOXP+u3TRkWgasnz3rFibShmXAq+TkwSCzdkQqh+enIxm0zQ7W+eS83G1dl0XBIsBEjM6bh/P9/zGA5mRGWfBei5el9nkeL/7+vdrwKA4J5y0WenTu+6r9PFNwV5ov0+v/9ca7sK6s4U9RRJDvQ9s5sHONdbgqxWaDGBYmaH48nInlxEeKPsqzxeN3KzXjuM4cqk++qMruqG/+jcz9qyH9NJiIaQ4TktT7TsObdAG34KBB8KuTiK7gkuSoYvU2WZjTWQ43xvTySmdfh82n9cF5RJw4b/NGh/WFP35p3sGTZFLL5px+x0kz5sZfCSdt9BMsxZ0MDp73iaygK1JUgUVr69VUKyC2Ofov8gBPB+/ZRIYeuzhK/hlnhYz/DnHC5jfZKQK/CRCsEI9Cf/O7YkOyL/ovtyODogXBtR2JCjA9juqq48VW1uMwTi0hamXEOg2ENay0pdl/X+/W4Ewr2WwCVlxGqtQzUnxhxosoz7PYyxikQTpcMGJavK4QNhfu6jyrmubnCK+KdU/x6FmXfwK0f+pLJINf6l9cSZmQmd4SDUr4lEyL1R8Lo2/sR7lUAHrXdN1o2P2M3wqrQEoYsOmKtI7+Bm0dEDsOh3uzqj2bDyqoATzUzRAi1Q/4fR5H06b+whcwDaAue1M0qzIFBuJeWmeQP1LGnOu23WcQwZFBUrjlHScLAJlnQANlLYY50QtuXewaL0dCPio0i94/09NAfZp5WkYf7aRJwUniR6G7HwYD2M+DiEv8kFjMvg7C5HZ/okMiN/9KrsCSrSEbdQooF27sBwQgQHSIaDhRjFIYVwT+mV2KdFS7m+qcId6Zu3t5rxzWdXOugHFn9ZEBW8m+wpfXuvsnOtrvISXoFMZ1CgRKBCNt6HXfds2rY7G8jWplCMo879nDzB+vO/sp5LnRNarJ7Cr9GNolvqXkLA5O4PRPuZrfI2XVYdk6FqLSkHXmhfUZmuaCihxaT1O5imD+nk3+RmzvKesg6NTL47W1AzPofG58biWJBkGfxGDXxckUYEAgaXKFQ4uPRyv/KUn4M17/8CMo1VcjmO4a9J2QF7IOwsjD2tq2pnPTcGw40+5KIwDOfnu67+Oc0kyIv3181hfqBGWvD7NKZKX8Zvj8/pm/ImKqIh1DlPaWlRQ70CTOU36YtBA4LvB1qdZ41MbPkpdqVezg4N8n0zUJW1OeyPTGAw420793TDDEsw6pxnypNnfY68MSGuMV2x6bHUx32Fs8xq7yQRmZ8m5P5/h2rV9WeW8OIRD0JBWcayCsbcFm68b3XY72ms3es03+/hEB+Rmz+gN9He7LmhbfM5rCvhCnIv6KspDg/slDHPYW0JNGV/AmTMD77yjI4H/n83+ECdXjCGtFK8822HkQTNMpspEyGGSyvUerFKUk9Wz71QsUIyesQWCTtkfsyqlLuCPv3WdxZwCHdA55XD1oQ5GKxlyYAncwS4A/qTYt3h3h1YNvw9LHLpX6V74+Bn9oqaGFCpye7gGRqCh+hm0RX/TuCI2fnVbtPA0aAmjuOCTBlAZEtaz8D9SPop+iX1eEgJs2qTpflkHY86/FHaSbrcOFjmHUiVbFJ8ZSV3dtD/6T70TBWP3gkWg7YtHoGlTH7uOHZU2x2BHqPsUHY13dmqxuvfrLMPimJp+FJwStfwx1bNoevk7xCZLgZ5dL2P0mCQq8i7bE0rlzDGNHq1x3JwPwoQIpfBSeraL0LuUmoPP/9aFqV/W+B+mJWsSVhG66QAKJGhx6odxf/R8nE6WAy0fOo5du3zO1Y1CFCUyLsXLO0ctRtEXaqtxv5V7Aj4/2kr9m9f/zrVeTlbLLF7mdtJoN8FUUIxQAjVmDQ7ff2Z2bjuKoRh2OjS1oWBzdoFyr9S90DNaZxjssfA32xD3MqJFw0hr/PhrgfCeEu7G6LXUWomOzmlkQTbolx0zByTrYPaQ0W4mvgqt+Z+CILLVxxzMQ331b8nghZuVsw1kBr/GQBvYpKBejntdTHOBGPjs52tbugoofmE99mcui24Pb1TZIkIEpZnPjL/z5tMSIR0tdaDGJmmL566PU9/GDDjnJ9QXKiBj3x8y7n2DF9VwulSNwJxz92KLD0Wqfue4CE81MzN18Bt+g35PPotv8R2edb3qTIVybjCDToR0McPy7N8+AUJmBMVhcHUU9wfJag4jL3LiBLygrbzfZJSUurpa6dZi6QVde/QKBmMoXlH/DsTe5nXOm/Xb7Wqv3azrvxn9JDogN2MWb1Ift+uCJjuGsJ8Emwri2r/HMwqOwtYLPRVIoVDhZMpIEUaOUNPJSGBrXQP4jzf7g/YZ3sbb6OcaBz/ItRDhULZ6DZKOy1lkQlpcgo1l5f7BIrO2sJaI5VFToyZWOKcLJKx1KybN/gAy2vbUgS/xJTRVJzNEf6GM69SMeAnMiFh9UUjmTjdaB2IbtN1LTkPvrRqq1rfWTMxCA0+DtkQJYPt29wyRNWrxYs2mFahJdsI0gMUJ2ZyiAkrHrMeGZBVQ/tpaJ9prKsJLIbDojtCRZcEyWyBcvjkWm4LzpSgfbKw4tilol4mhl2OZ6eiwsyu64gv1U1acUtj+G8mAsFC8m5tPwTVtLNSfP99Ns20XoT8S5dNIkChqOEXo9vPJbOxnF191KJNNzQoOKphmQzjPiWlccs7K7vSJSj6KWS52Hy/jV85BoUtm2OisFsUu9bM8vzzHXXdp5XqBzWWvXxl5j/yJo7nK4fj89Y5TJ+8G20C3C5Tfi3wT1Vd+qc7zwtNnka9URpVpnqvZmj2F/qRv1mlkzw60XNsFXTBA7Z8dJxytJ/O9kzWrTxyT77ThO+og/45FOJamEGrl26OycrwmJieZCWGj41jpnI8dbmydCYh6vJUrs0vRTUFyBbtPtgr6gBx98MaJHuqQmjm2Y8WJYurfgVTQpW95vmhkHzsGjI7SDqMWM6SkeRLX82U6cPaazIaTOIkcqusv8KZ69kzaeqGttZ9v0msHauY65LV8GO37LlG9XerfzOP5ziaDFB1yNhrxBUjpDj0nfdJ+gh4X33WcPv7GNW7WjdhBJ97jrw48iaKbfsbFZOlxZ9YoHD+haz7ZvOpETSIVeVeZ4+T6YECEjc6oMGaJrpKd2UlowCTYOvLadrvaa/G9zlu5f6IDcitnN559364L2gt2Yl46P0gsMCZXOCkbJ6OZwi+zzUF9vIBvgkZJvKaRBg4jZv90Y6RbBMcY3dmNwopK8WiKfJgdUw/PY4waEjH9ZP26CM28ZLeK8LHQsDjWrDHgvsGw6UyD/6GFoVWbnepJPHL5Z1xKkgYFM0fhRKQuHAz1Ub2Zc2dDw65d00We70HrHXh9BLkWBJZli/TRcDQzEfEdq23QNorywQIk8ull0FKjJpCKsbqOPNpAsp0Uydh4GcCzLmqhQdO4ZF8mxa9EeW1Ws9RZ0rqKpgNlhuwI96S8XdD8sDYO2zc+jW3Hs7hYhPi7GN8bW/XD3d9rqtrWVbbg8W4lVdQxkDEb7F6Q5pdZj1CNVNHUERKtH7tmp2/Rkei2Uxfmvlt3JZZcqhZWEboXVIiRUsGhV8UqbEpd1SE8YP+hosvBrkXWmRhWr6cfhS/Pv6DnstjvmLBDq36zPQyfKKWQDMg2gSMevKMaTs9e6VIHN6FM3J9Qr5ZjHkSGPxbidIaCGPTmXmVIrlihGeTY7HViQ5GkBoHFxikQgyxZkqh1Fkxnw37v9M0/BN0OvKqvteQfmLBVQxzN9w61kdat0yKKzBCqdAcLD5gG27DByUJKzZo4242LbsTUnZqkYuPzA9H96GsuFrdg2UDzftlO07NrX3cY8KS4nfuHCtbYz9d3+d7BMwf1B+ilJw7jr9N5VEDDa/7s76MpSimio/djMRZDZ86YvRgNnb2UFqoOxH7v/JKqCR67PBWXkqZF/ZrnceRoEuU4CAOcPPu2ijlrNoXggBo6L+Ib1zjM97JX0Ik6SAIv24iyKIeNLuY9ZvJIMiCN46kT+yt+hSZEeAMDMBBvuM5p/kGFdsK32bpWWYLZ5+/zzOx88EHALm7ahtvVXrtpE3ATOkp0QG5gEq9du4b+/ftj1KhROHDgAPLnz4/27dvjrbfeQjK+SePZbtcF7YUDlUun1gAjaybzDDVBpqCJSruyMWPwCd7D1+jkMMiEM3UjRwIv6G+9Z2N6mdFYvvBoIBArysaxEO+fEFiXWUzIgvpP8L7q86XsP2L4ySYYgQ7OS9umnjUHabLePJZuIWZe0B8facHw/vZ8m5mEu7HBT9iJS5GRfUI4vAQSw5nrUPvYEAXOda/ITg4DCj9sV6CLB6UVxi6HarYP3kEP9HFtJ1kO9Q0S0myD9svCg/H6bl0M+Xb9DVhx/m5Pg9Y21MI9txixXgawV/Ex++2BTx1ChhLYimtFSqDxrn7oB+0MPFl0E0o3K+MSOAsU3bO58r9P1hqYMEFbRKRnS5JE1ZAIV75cFx2AGjt9zhkNoaW4P0EZkHCpqeXcJs22H2QuykijEDtSsmRYNSC2UURj+L7oeQ6E5xl859A/yzhuBO5nZ0Ce3Om7f7ynotfBc5nMb0JdK9HdY8ip34cNGwIzZvhd65gxGsokxe4Cf4pEZqVpIU222+vEhMrw2Rwf+Rgew0xQCDUXjqvDQ8FY7PcOMzyzoOsp6FDtqvg0nngCEOOP0XBmNQSjr0qvPi+m8W/EjMWlzc2gDvvi/qkjDzu0rMJWZevYhHIcvWBjZGJkkfclpEZaXETFiknAWniJ6gdaC37PV+1Rvo8Pr6NWLdfzZc6/wDLlHjWBD17WEDPUHFKkT7IUZmG7HMN7w8c4ULOdHKkpESeAGTQGAOU6BXroFXA5kiQPcl8/ipUZ6qJx+vl+yASvd52ZpT2B7IpkYQYa4pkMM9T8SvMqfOe34TSyKjTATDRQ69Kr8VnuHO0TOLSfLzkm1LoI950ear/b1V4LdV3/5PZEB+QGZrtTp04YNmwY2rZtixo1amDFihUYO3Ys+PvQoW5RuXBOc7suaC+jK9T1MnswES1RCz7gLNlhhqMjRqOdp/aCV5/84DKgZqqmf/stQDGucBudExpPoWBd7g/adexEURTBbhxFLuTDQUVZyILl9Siv8NlsgYrw5qGeUrvmhzAbTuES0rqGG8woMo1kRqTuuejD7X5Z4Eu8deh1MAPh1bj/L7/4BBLDnaNQ+9lrgI7DE5OaofKuH3ExaTrcmf08jms7x2jXcRw5lRK8F188d0wo3M7PoD35qc+bYUVvoUKeBm0gkoFg18/iTzKKstnH88M85lprJQQo0WahoTZVulmUHJsiNR6PmYIpaKr6egy/qCL+UIYh97UjtIvTPor7L87B2bS5MfbTI0ogj8agyYIlUfunM83F5LNUJQQmPjEZr694Ot41IDY1NfsivrszBqEIduFzdHUE28y5FGPB734deNdX/EJlxzx5wnJA2LdEveU8rHHYDU0H/RHeR6/kHyljTK7/Rqh47RqQ4+26I+cYLbD5RPXj+OV3DbVhM6E3/fAW3knSTwVCkieNRXRsCkU+MD/vc+hVZKwfPFAY2iRSLwQWZFGihotNbW6/P8wCZT6bz31TE0WOrcDe1CXRr+2WoCKEMn7zvWOLbJIpjo6zCd0TY5PQofff1zCak8lyItu1E9hYsCEWvj7DWZfmmuD+40Zcxsr1Wq+Dxfsv42v1b1OrJJTj6PVdWp2+NiqfX4yoLAVR+869WLvW/WQHMl7t5+udaovQZ5UWEB1YbiyGXnhO+VVeatymg8WI/5uxPup0HzT1OiKRJSCrmLxbvOqnuM0Ng/avMZGrtMkXvAIuUpvoVRDPfmTevYJOlyN9NNRD0QmvYKjrncPn5Wld2uNqpAAnEcZ5pFOsYGY9oLnj8DRvoMOlgeqnBjUiseNEZs/Mjv8Zbv4vt6u9dvNnIuE9JjogCZy7TZs2oVy5cnj11VfxlSEe8Nprr2Hw4MHYsGEDygqNZJjnuF0XdCCjTdLqgS6fNHztMBq90UMZoWajQcqi9UWojQ0o52eg233SsObHiZhjlepPQGPGhGq9gZr5QTP1BQTHK8dR4TcCtZRBQWahu7ERp5HN6ZbFxweQXxXkk8KySYpf/FhOgkVx7I9GljTROHQpC9IgWkHaRMwu2BSQflVU2hMwVX6HiCHGwlkWNZK1ZT7qoi4WKFGqgohTs7KOlKJUOmJU/7azJDQSWZwf3+Zn0O7qptNhbFSGzJo1oEFLPDrZk8zGSLVASwSPLNtpfJsOMNegmfGjkJ4IH2bCGUdgbwEexINYCOpwULSLzawL6Yhh+DFLx5DQGB4na0IY6Lw0J5hxYK2VQAh5HMedfuc6rENFdX6BhMS3BoT0r6QgNRuNfeqtsBF+RrExU+WZvzMyT04Au2ZnfKbOaH12sDp2yGfnMWdpOj/a5EAwCxMqxHqFyxevYf/JNOp5E00Ec5w3QsVrvhOU0z27Ayqv1cKgUybFoGkLU0fBp07/HZ5xhNhYd3MK2dUxdExYU2bDA9u29TG0MZPQeNkbyPGdNsT6dI9Cg+YZ/GBbYqyaz4IYoCLmJnVjwUQIZa7s906B7Bex76SGmK4q3wGPHRruYPX5Gz9/fBdTi4fZVz5T0dD0web1kw2Ra5LZZcIuZQ2zhiDNtQs4U+9pLOk02VF7DyT25159bgVtbqPTNPdAKaXpswpVFQGI2YLBuuTaOVbCB4+u8dEts5ZRoKYydpPOV7LmAn8anqwTOlzTBR3UzBDdGArrVcMfIMFACViFaB7EAObYCQsV/akc8KYJ9lrzXt9uIQehijnZGZMnT6IcdmnisNsOHtflA7m2oMSTpdSuvz7UF0uqdXMyuHwWqSHD+RPNJ+nT1AQRiKx9P/n3ZDyNp/E/p/bmrrv02OzMjtexN/u329Veu9nzcCP9JTogCZy9nj17onfv3ti9ezfuZFVlXNuzZw8KFy6MHj164NNPP41X77fzgmaU1nxJxefCmTV4ESPxJgY4hph5PKN821Ec6xRRYXnsQDFlwPM/RtAl+hefcwba1zYmzf3MiM9L8NFY1sM8B8Mq+5Mi8F3o+08nozF+ckSd+MHqid5qmykCJsfSiDdxsvZY7cgTtzN13QCzVZSdM+NVdGj2c6M1FvaY7I8RDZoFkZpqch3Kq/97NVMLpU7qFVgUXd1vN7Kf9XGjs0LeatugnZixI1pEaYXAQZ9fwbyFKQIatIxk0niyP5JeJ/WqRbKx8ibUqgh2OtF4oYcl49V9iFC1JQ+XPoj/rcyvTjUix7s40ukTVZMSrDiY+z73nI+mlRHX5YcKIWPkPmzIVhtNsy5UH2hb+FNw4H8vOIxSde9Q5xyT912sfvwTVUtg6lCY0D06mxQHI76fa5WoIdtxZ0aH7DZZ4AN8N8ZUR7NG5lLoi2VNC1uSXaPAZ5wOFJ0OEY4cqO1vvyaQF1Px/C9ow5P49PrZ/1TMR6KBwOgxSQYS0mwF+h/RFE0xxWGzsotu9yUphALX94GMaI+mXqTWGKEkQsDQP3tf/FKymx88sFEjtwPyxLoPkXuEFq0Z8MYBPPRcvoAOiNez+VdkHuTBUczCo2iIWaqfUGQH5ntHoGNHkBu5cQzM6NbHPFeGgs8B167Awp54OBo/z9MCirMKdsIbKYeqdSnbCQuS2jau4WWHCiGTWsN10CTLbyrDEEzsz75/NvUwgyInkU2xb4l2iZd4otc6MK9dGfvnYnEpSVqkun4Zq4s2x4pXJrmK5JmBZ1bdy8DnnDNIRKiSwJB5TuoESaaU8DDbWbcZqGSc9jlqYpnDwtgBwz3ZJs2sn+m80El460Q3vHJJB2sYLDuhvrG+Jg67qT3EtcPAzPN552L0YZ1Nnf3sJAw91dwhFyBpAMkDbFFG7lsBaxUVNNsH+BAfw7uIYzlqoAZ+96Mrvlm02vF5B9zO9lp8rvNW7pvogCRwdh9++GGV5Th69KhfD7ly5UKFChUwV6yGMM9xOy9o1np4Xa4X60Wg6aB6az3MR1uMxcOYh0yICjlzpHAVZ+SgUjG4A/y//Me/jyEXriNpyL64A31JO5IrB5oRQInExCC5ShlLFEv2JcsVtU8qQys9kenqI3yAUvgbY/C8isYeQD4Uxm6VbjahMaEMItugoBHXINoH3fESezSNMRmjfBDCmpgQO9lOEY3ASb+LEVwHTbP+5qdDwbVR9fpKrIR2OhgF+xz+KShqBJAGNz7NNmi/R0ulBqxZazTPbjCDlsYODXBG7AK1QBkzGytPIcCR0AXVFGdchXsUPCkaqRUj3Ld4VomSsfH3y0ilsmdj0Bbt4kgNzDXoxYZDg5pCdZKluZAkHdJev4g1RZ7GslcmOyroppHJPj/+GFg4LwaLlmtdk5F4AR2gI/jSBHLx22/a+GcWJVQzBTJl31Fohxcwyu9QGlDffONmSxq0vxGKbJ6OqBRZUbnQKYctiZF0spIFg9/YeHhmpEafbqRUk6OQAZmUHpGPmSeUwx/sWmlQDRmi96DT/b9IndXai4K4E3v9Dt2cuSZKn1mBbSiOktBqpvVTL8acaF0DNq3ReDw5rbVfdk70NMQAZ7HuAGhO8lL4C1ugo84mc5ZkiOxnk5HqF15Pi6TRl/Bn8RaY2XKiylhKvCxQJsCGIdFxmBelqcS9ovZ0WqdM0VOg6j8aHQNy59Y/xEUV+LsUzvN5okMva3Q1Kqv3p0nPGkzsz55se7w5Msfg+JnA6zyY0Ke8c2VsdJAWnyiFbMe2YEemyng0x2rlIMnzJ9F+LxjYpmTlUebaBrBOoxJ8GDCSkfRGT3UZNisgf+M6ZvI20HXK7+b7hvWWXpTw5vNjs1iSkU/obavgD6xBFc/vk3ltvF6+f17ECIxARzUUIgHk3c6/5ZxeThnREKeQTQUsfkMdPITf/K6TWdZVh/Mj26WD+D3dg2iSaQGIzjTbjWQz/Wc2+C+3s70W32u9VfsnOiAJnFnCq1KmTIk/bSlRkO++ImJiYkCYVqB25MgR8D+zbdmyBa1atVJ9so/bqSUEOx/s+miIVcFqVMMqxSZVAeuU8U7Gqfg2Gp3LUROD0FnRr4bKmITCAfP8pEllBNGmvjXHRiXZZbjXEXezx20ql8fnJWrOtTh4KXBFOWIsKKWRVRJbcQR5g04VjRWzQDC+82rub0IUCL0jtprjyIDzYFSYOilMvdvGK8d9BplVASJxwA2TzfWsX4lvYaFpGNIZGrK3Ie78exZOp8qNewocCdugJVNThw76eggF4zWQ+OALzVrr2WyjwzTGpa7jTuxRDGpshCp9CJ8EO2F7eXHEM6rsVa9grgcahTFRFx32tSF42aGgFV0JGbREnvl3ZLJsyHztNHaVeRzNUk13icoxmssiVtqM4bbP4aNopbYFgwl7UAiFscevC64dRspdbEl16gCLFqlaHezZ4xjkAhUKth68SDFGZe2Gdqd1VLdcziPYeDzOEI4bTXzXl1wEX9PmuC+VrIA029bjQI4KGPPyWhUBnzbNd8mSIdHaGbo6t1PmiRh65hn17ykvzkeTEXUDFqHLPTR1HkzaVlM7RDJE5rPJOqzIEzFOdH1pqY5Y+8IwVy1GoJoYr4yCFHUzEJQGl5A5S1IHfsigFDVx2JQDUmeHVpZjY0rznXdc18n+uZ+0RWkb4IGLs3E2TS6M63M0qNif17q0qYcfLHkIXb7UInY/l3kXG5p8EpJ6WPq1n7GoKJ3ZZsG0qWliPmM8RsgDzPGxZpDvaTP7xO3MEE5FE7WrfBvMwFQgQUIGzfYavu5AvIbXoNXmWXdkwn/N6xGInu2wN4BPQJYF8zImOVYcdpsBjlmxMXl6ouFGnd0vmvogdkXf4aknxGux6xRlPgn9IhzXzgCZQRsRarVFj2+knstrDQX7LdEBie+M+e+f6IAkcA6LFCkCZjpYeG43FqQfP34cO0VK2OMcH374IT4ylaWMfW5HB4TD5wstofUX4dyGlLiscOQFsS8OgHUABVSFgc6B5MXhkA6KXa/hdd5A0VUxbMh5L2lpvuzfQAAsSJzIF4vtTbwxsyZd8IVDDWqPIZyXqCn+KDzoZvSJjtFDWBCydiZsw4uht3btAH55Ga5mOMpoYpxIBJaOhdRzkFr2m4rDFTEA2WHsRrYUwkBoxLAg384mcf9QBad2n6Zh+N13QObH70PB/RE4ma04Di/c5sBVwjFow1mb5j62M/5gyggsuKIVhakFQRrJB+DTORClYm5nJHHK/iqogjXYmaoUvmj7F7JlCx6dtqOzdYvvw/zthdT5vi/+IT66/oFyuCQ6K46HWechECXi0KtjpSIpYuEyBcBMHv5w54Lrj/2wvmUmGqIjNPzN1uHgb4wmb95ssSWNrKS9vnLlgPXr1bFSzMt76xH3cYbmFXVuh1EYBU2Z5yWKGd/1xX7kPssaYg1Il8GFkPnsPuy+80Gc/3mBowQugxuX+TW0OaONQ4r3nUMGvIkv8AW66mvEJhzOUkYZ8XKfODYpQuc+NNLrn/kBBd9poY759tlfUb7rQwFpeOXZ5PwLEw03AAAgAElEQVRxDexZ49OhoI5Rd+iieTHmAmUC7EwKr7fmrB6ov07jI7u3OoBkBfM5mRR5F4hR3q7cGozaoKl6R1f6GuPTvuQqthfIlszVvHztUO/gGFxPmhTTf7yCb8Ykc6mWh9J7sGtWTJgPqZknZnklrPoqGY+dZRyT+Q20PaPf/cM/PYWhk7KqdSxZEt43xhgpvimNRvQVpERSXMf4ZM/juWs+zmpmskQr6R30QV/4e/xe72sGocwmtXdkViM8zm42o5btsJNJcQPKq8Nm1B6Aj6LeCKpyz/3kXWKSI6TEFRQumsxRsDefMS/ERFf4ivPt7AnPkT/pIeyP1Q6kWXdjXl9CnmO/CQrzh0QHJMyJCrJbogOSwDlMzID4Txz9LRbwBqtfSOB0h3UY07g5cMIBYN2h1EUOohw2KEiXCCB61V2YJwjkAEikKBRnuz1Yjqs2FqEq/sB5pFcG2V746obs/cN5iXqJP/I8v+FB1IYGtBNn/hhmBKU2DudcqrPnnwfGjtVDZXSaeByj2TUI/bscRf22edQek4v0QPNdn/rVIMjhxCkPhxYwCJQVCscpk/7EMDSjketRTnHSr0ElZdzTwCZ6koZ5KIM2rMVn7WQWopsY/27oi/7oBjodY/G8OorOyBI84PRAdWTChc4gk1NDEQyfb+PTi59bo2ATbId6DMXqKp3w3nvayGcjjIqFwWzMDjEYneqR2ihxeDEOpboTvdruVrCY7t194nD2HEhRPnHfdq0M6z8oskmYISP+C1HHub9C82v2R9YqRuZNtqS9KYqiYMwubM9zH2Z3W+KK0IcSofPKxj6eaQmmn9Vz/Eb6bzDwvFtnIT7rS8Yujg7jSL16aeIFZnuY2ZCsn03EMaZEX7Tdpg1LroudSUugb6y/ECSNREK7mH2joV2jhk+IULHJzZqli2/YiM968kn1Ty/tFttxeP7+XRi9pKjaf3zJ3vj0WncXPDKQYe9VS/JUpE9xW+A+NsyPBjhrhCpH+dj6WuJ7TEJLV7G9OKL8P526+hE9HGru3DiCY8itnlXCMVm0HgwyxWuzqYerRfqL2IXDMCf3237HfVV8KOr8pJW4n8q3Cj8drOp6x3Ee+WyIA0LnL3P0EScz/Sl6OHWC7IMBtotIq+CXY/Ecnkfc+9Z4WOxrJv8N76/Z6PRTxHQhais4oH0/bCiXfV8zI1KJkbINwBtKbNIW++Mxpjgm1yTFL/N3fBT3nJ6D0ylyYeHEowH1hLyeUWr0EJ7K1iPpZ+gTq+nIpZnbpbZFgiqyT9gBNfeUJeivRAckQdPmOijRAUngHCbWgHhPHJ0Q2qoUZfo3tcpYjaW4TzFFkZGnBLY5ReH2OAPhSCVS9DKGYAi0AJdXpCac6/aqyYjPSzSQ+CMjzEtwP8pCW5sscH4Us3EeGTyHFY7htWFdLIpUz4H0l0+rPmKRBFuWnkTpWvojxWZHBzvU+hvDI0qrbZuf+xwt1nRRBrBXTRApmZnLYmMErT38lezig+2VD6pZsHokRX7kjjmIfSXqonG6+S76zVAGbTj3097HLEQvkvkUdp7RLEfC8W8yRBGqtx8FnS4ImxLa0XQ4j2QZ0rmgcrbTKJFe0p4yYzGw/lwM2aULQU3BO5kPOhe0X4nZppFGCuGXI5opmJxZI8PjxTmIzxyYRbDUu1iJexwsuLBsmf3JOUy2JNHFkGJh7i9sSaEi39zXzBDybxqwAkkUpilzDPFZX3KcGPaSATFrDEbgRSfrI/vzOusdn4AJaK1+qoPfsAh1FCPUM5ioGKJqVbqEh+snUVkEGniUQPHKgHS4a6nmXmWL46o26ynMNWIbmK/WXItBy3XB74YXh6LHwU6uzEKgoIQXm9aDWIAFqKv6ao3x+DlDaz9Yp2RyepT8CZ9ufUrt2+++mZgR28BVbC+0vbKOp9UehLcO6pRpeaxzovLmOiYZQqBmUw8XWzYWrRdrp/+LJ5YiskytsDR2pH+bac5U5W6GH/Ajmqm6MmGa4/5MGJPlTRqvw2acM8dPAdui2AVS4bLY2m5GQlBtYtbKhLWSZe8MtOCVCb80+7GL2W1nIGOG6zh0LoOqlZuCpxSpApv57uZ3g6rwAuKQDIiIEArxSDA2PZu4hnWThOOmw0U/eBrPb0LUCBObreDUvnaziVUCryy9JdEBCTVDobcnOiCh58hzD7Jc9enTJ5EFK8D80cgx8byym4k7T+DUJ/iwvuiGbtA4cFGe9uqMUWEaaHaTiNowdHSMC1NNN8EDS8BL1Ba3Ms9NiNgCPKQi/mxLcB8exG+eDlcww4vOJK85Zs16VYVjNmYqDlVupITtSJ1ZXmfslU3EWonrERGIgIYdCcTIpvo0++MHqzw2KGG0PDiCWLiFPEMV5pt9mRFfFllTA2NuRFpVZ+JFwxqOQRvfe2veH2amYqB1HiSyaTLepEa0696YxajFsQ07EIebjxuEPV4TYsM5zhcx0RHbo4G4EA/6RY5ptNBulTYpR2c0P6Fpb2uVP4dl69OrfwdzlAPNiUmpySJWstaJUSSQRdOYofPKYn95N3Dups9LheTXrmDRHc+gQ9rvXGxJ4WTt7AxhntzXseN4RqSLPY9ZKRqhYYwuzJBxBHrmg91307BXNQ5PHgdy5VKHLKj8DpY37IPp03WNCJut2fN6tglI+XwrNB5SG/dcWqwK1zs9slc5Aw0a+LJPZi2BPEOv1FyHwct1neCwMkMwIPplBXWR7eYaMdmK6MQli/DB/0SYkRlBZhVOn9aR7ECCpaZRz6h4igM+MdFg7EVqflKO1dEpNkao7r3XVQPCAM/33+vNZGaqf+5HZdSz7f56Djblre9Q8fI3YZryukdezhK1Sj5Dd7U7n6uTWYq76LJDrSu7qL1+wS2Ys08X/y9rqCP2ptYOv4GkHl692jfCllnm4PvIR9UPbdP9iHEXtOaPNIGjaoFJBnzc+KpgSuTsgwGxFaipumMx+TB08pser8yROOzyPAgkU+iKBZ4n7wN+N+gMMQMjxzAruvNSXmQ8fwTbCtdHrXNzguoJURx3u8U2LPAxZhJ5/eZ3wCReqJ1lPRZHlnO9n5g5u5UQcHsiEx0Qrycvfr8lOiDxmy9nbzJgkekqkA7I+vXrcXcg1aAA5/wvLeibXZSewNvkOswUJAuU4uYBgYzyPHk0bIcaJRRQDKZvEWq82bMrbTW/FyYjRsJpHqyPQBkQOYbaAr+irkN/68WMxX0DGV4cAyORLFI3a0ukf4nkMxpJjYLBgwGhUCU2PO/q6XhpXiO1+7D601Gz7+OKupVwBNY5EBZAPUBpNF6kENuLuSU+TEVmRoAGwMZVl3D3PVro8X+5XsaixkMUfIPjZpmBydkf6r6Fu92+PxLRF6VfOoWk3iUVL8UszcY6kTFop35qVyICY7bdq/4tUArbgLAhNl+XGoKX/tYZusUD1qL/ggp+2PnMmX3RS+5nUwVnrljEpWptXzeZyQIpM4vyO4tJyThFljeKjFKx28xoSJ9mpkoZqm2idbU/Gymvhg4NW4RQ+vR6Pgi/I+sQjasy+Mt1SQnJgNgihNi2TSm2qxZHkWbfmw73bcHwpdpoFTjeFpRUjFhCaGHW39hsSoSpjR4NRK7ZiZ0opvox6wUk4hwoA8LtpXf+jJ+hIVuixB2u7otNoVq1Ygx+X5caSa/H4ofUbdAiepxrrcokq/tKAbk33tA/xWFlzKyNFKHLOm9z51KM26OzPF+WG4evL7TxZJqy1yb/9oKLvR/p0+ORwFEo6mGzbz819FGXtFcJYHnZjvi18TA/ymxmPwhTlOfFhF56vef4Xu0KzXBBdfTjyOVioDKmztH+McdI7SBxOrzgjubx5nGPP+6DZXItTIp8GJVPzcfxZLlR5Y4jKltqPqd0FrmfmQHZvfOaqm8xAy3B1pWXCCK/U5/gfTU01uyYgS8KUr4EzVJg6qfIdSQkiOC1dsL97b9kr4V7zTd7v0QH5AZmtGPHjhgxYoRSQq9ZsyaWL1+ulNA7dOiA4V7h/xDn+q8t6BvRBrmB2xL0UEkRkwKXBexejFh8ubJw2WymQ0XHg8JxFJKj0N7NbIG43u1zeDH92PswE7IZZRTjCo1BUv4SR222QIaXGZ0iDtgutDcZXGjMsu6HzsUrr2gsvGlEE5KzJUtNJ9rIyCX3MaEJZbERG1FODY3neyfFgHiJM7o+wh31WARLvivikKoGYvsY7+EDfKxqQBjtDQdLnpD7a9+fzSiN0vhbCaDVSbsK2y4VQL7rBxyctnmORzELs6Dx/U9hCvZWfMrlDNgOk21sfZn1E7x+Wn/ER7+3Fz/9WdAPYiP4beLBSTRVYa2vSFtghZyj+EMpfer2dLIewBI1DqFU5TwIPNBrXpWh+vgRgFywbD17qgIL01ANB+ftlSGckqIFnor5AVeSpEThXBdx6KgvyxafDJuM286A1EnzO4q1qaE2T39sFO7s1Q49erizqWUKRGHT/kxqH8kGsdaHLGFT0RhNMNU1LbaeBMf5999AkhPHnGd5ToUe2N7mUxdLFOFsUiJisxW9kmE8Bp97Tp1nxDNL8d78WkEj1V7PlvkbMzcUGjXvt7ldarEGZv0Yr53W+g7mupTMl8mCxd9yR23DNmiHTpTW+W+bacorzudFPdzs5xbIPPcHXEmWGn3evYiYqxrqxhZMhFCuxc6AMNv0d6TWQSGD3yOY67p3Jg0xN/B9NLxgH1W4z1a34HYs2KedSGkmWUIgB0KcS68MAqm722KcgsnS+behtxwz33t2s50B0nGTMpv9MENLRirJVPJY7l+7tq8uiVnm7wccQ79v9fdlXoV3kGdcH0VM41WXxH3sICXfRdVjlmLmOe10voaBGAQfa4lTXJ8sD+7KeNiVveL+CQki+M9E+L/81+y18K/85u2Z6IDcwFxevXoV/fr1w6hRo3Dw4EHky5cP7du3R7du3ZCcPHPxbP+1Be31guSUMPpP0cL/j2J1smC9iS/VnTGx98JjLi9XW2tBjA3iVKnfEEinIT633KYQ5LGsHVi5MnQvXkw/Xke1gg9zTkVuuXbZ18vw+uUXKINX2mw8oj6uFPGiICSxyV6RezEk+JF7PvJzR9OjJLYoQ8JkhzFZffR5rmMniqpsgKZrZVbADT8IBZGQ8drGR5sKGzFunXZuxlcYiNHpX3MZ1rcCgmXfHxIC0BjntbH+iGuITDheWh+sV1qNqmq8AqMwI4l23Y5E4mV+TYcxA6KUEWLrJ7AexyTh+6jSL3j/T33TV70zDR9vbORyWsy1VQzb8Rb6K3pPstGYRk5R7HAgY73R3RHcFPpZXWNyHvnzJ8GBA+4VK4almSXY3KY/3j7RNWwVdOnRKwNi1t0wG2oSQcQnw2avMxm36Tg+iZ+cLIPsr5+P64r5ivh6zsnzGOPMnxdm31zz993ncwhHDbqIdp21CrlSdxs0yOWk0XlculRvNtci19EjOwc5hh0ZjzbhbofFSPYPpDJvOtby/lqe8gHUuLIEx1PnR+cn9ivGJJMAUjKjJjUzC53PIrOfFg8pi0XPJmX0WbUP229lX8fmdl86Yn/mu8RrrDb1MLMQK9LUQfVLi3AyQyF89/GesKiHzRXqRUPMWg0yHG5FCdyFrS4hRimqZx8yXpMFbWifKHw0IINLPd6sn+pXeDi+ON9BETSYTZ5/rwCfQKc2oQzuhr8MgOmYel2b/PZxio/xXox2Ft9uuhtjF9/pGieDIHQszHeIyZ5F52FdrdeUlpLcH6/3t13DkgrRisAiFa74OeR8dxbCPoVAuB9xi9u4iHDqGd0zeWN//dfstRubjYQdneiAJGzebslR/7UF7ZVivSUTF49OaRj8BF0ISTasn1I0Vw4R6RKFc90LkiMfXjotYrh8iA/wET6Mx9lD7xqK2UV6CBfiRnHHv1BaQTzIV8/6ilQZUjmFol6GFx0I0zlk0T71G6hCuxUllTgeI2PpcAHRiIPKxA1MRbA7AMfbdUfOMZres3/XYzibKqcTbeTY6YBI3Yhc07B0XdHxgoYfPFV4HX7aHVdYErdDuB8Y2/g3KW/pkH2PVq4bEa5jE/ru+faw788EtEIrfI8rSIHS+Msx0t/Dx+iF91xd58d+pyh9Qc0P0HL7h66Pvx3pMzVPaPRMTtMGpVZ/i6tJkqNUkSvYsTOJn4I0aV6J35b2Ro1VGLBCM9Cs7zgcPfd38HRAWBTPNUDJTzYydjXGT46z2AbjFM0wm8B7+G/Svb6Nfup3gZbYhAQ0johcion4Hb9DZxKodzEa7VXGiiJ1oVTQ5Xq8MoSsd/gOz6pdHsZczMfDrnkPJ7NiHmCTHZjOvs1sxuNoMDLzRxHC4tiBXblqYPojw/HmuLtVt6QhJR0v1zkjyjSazXoMzg+hMmyPPnIdM+alQNLYa9hX5zl0Sj1W3S/i8GnwL1nioJxgQsXY774XPsHjq3WG7N1We/H0WwWDRqrNaxbHTmoBaEAOueiLuku03L63zEj1Pd0eZVZqgomSRa9i285karymuCRhmVKbVKb0dazfkRbJrkTj4L3N0SHjJHWNJhQoUPDAph4mFNOmmuY4QlEPm9fuRUP8+A8tUGXnD7icJBXeePEismZP6rznRPfIHO8PMMkezvsFWajbcRI51GkDUbzzHlDjxX5/ElYWiSwqsOFF5sF7ZmtvyPXZKvcNTvhY+iQTY9Jxc975jTDryF4uOg9DdtZXXb5T6Af03avrd7y0aeS8XkFKgadqpXh6X0lAx4QMYYGujf3dive46wVh/fFfs9eCXeut2pbogNyqmU1Av/+1BR2ukRzuVJFKlMWJNEQS2kwHIhCXuNdHrWpVXUxI3O5S6BSxaDokdCxex8XHCCKumAZNqNYFvmwEIT3igMlx5jnte2Yqc1P86W+UQj9oekRTgVn6ogNyzz1AzPMdUHmtVtTe+GcMVvyR3FE8lvPZTEU1sBzLoesdWBMyOMsHrjR7uCl2MbhkTLzmKdDFnoxSz4EuApUWrOg21NwG225eHyk3e0DrJdBIHw8NgXkW3zpGsfTFj604diQ86IRhLhpMGyIohcFiTK3M+RiqHZ+Jq1lyYOaY4w4FrzjYJj2owNT2R/gc6/fxkcJhe5EGmBhzGa8JFRHoBreZImi2QvLGtNVx8aK7yJ1ZR8Ly0kX46FJlvdIBYf1BKBV0GZNXhpAF8X+gmtqFOhAjkr+iMrHmMYEi/1732XxWuO4b7v4Kd/TTnKjDOm5AzZfudmlz8Hcacd+fqKugm8eQS9VXTYeulSLLzzQ0ds27Vy2HZBQYUKBytDAVkaJ28mRNt0xWXjnWnguzzoCZiLtrZQ4ZqZbrNx07cTLoRH8MHS1nBux4hqIuJiynrq1pUy2Nzpd4VJSnuKTUiYnRzkwrFeWFUlausXlzrQUTrmYJHaApi7MhzcXTWJnrCbTO+HNY1MPmffeqK3krsrujo5IHh3EUefxob00q5j/S3o8qF5fiUOrCqJJllwp82Y1EHDlw0oF1pUuniT6c5+1+DTeyZcQewWyHGUpoas2+qQHJMiWvZsPLXivzGwZufkjt2jXXBPwvVSuVmZJ3CPenM2gy6d0ZMd55r5nvBEpG7drl7SDwW0ERUrN9gncdemL5xlAZ/m9oVkXWPI3O/o5yHnl+afH5dnrPQvx+/a/Za/G7+puzd6IDcnPm8ab08l9c0NQFYfTpRhuNbfK/S+vSBaqo2dYgCHUeMhIxxUuF7ohsjfBp5WkKCkJctTQvWlYxJs0opzAMhTpnuNsJkzEZU0IdJ8Js3M9RRI+LsprHkoL0IPIp2BgjcG1T/+CaN9PIsbNWd+AgDiK/6o4fBtaUTEZz9bfNJGaq9v4PTRSenWwmmXFW7S9GhZzPZCrite/fG4stJ7OrYmVClupgkTpO4AvhFhnahsILGImR6KD6omr01YrVFOZ75kw9S7cqcmZen6l18j1aKtpVGY8YxeY9IwsO582rLsA0ukwjmAY8NSIHra2JmljhwELYr+lM8HpFIE0oT9s0vYjl6zWkZyg64RUM9Vx+IjBobjTHKNH9v3GXqnmRVg/zMA86Okrl72FnWqg6c5NCVAp1+5abiG4btDL48o8WoPeqB5WxI9vDMTRsR5oQy5QXIrHjlKaOHoRXHbVoGWO4GTbZ3zwHiRcejPgQDyzRivZb5h/AXXXzuWBRso5NmmU62pJFrZZyHf64orN+8jybwRCJUjMTQkdp2toCKIADmId6qI956jivTJGpX8F9fsr+Ap48OUrtX6XCVaxZp2thgkWq5ZrtZ4tMWPcf8ME8H8Kv+A3acDWbyoxOradTO/nyQfB3trikCZ2i4T50rYY4meuJ10hdVL6zAxFI2ON8vP4VTJ+bSg1pT70X8UryEWFRD5vX4MWsZb5bGEDZnKGGHw0x+xA2vlEROvvFbPK9WO43T2rNJ62FGrHLFCsanS+78T6RJc2soeM+Q5O+gk6x+rktjF3Yg8KuQ4Nl181553N5ds12bEcJdTwJKvpA161IkIO+JAM3bHwv9+4N7O7QF0+u0ho3HzbfisbdS7i0hLyeWy+UROP08zH1vM5OMuAxAh1hIhfMIJo8J4FqWzwn+Cb9+F+0127S1ITdTaIDEvZU3fod/4sLmlhgGpdntQ2a4LZgAfDgg/6Hs3+mos0IUaCTiGgR1Z6rKXrQoupjwBZMmM788JhsQcTCCxNNgi8s7kBGuSj4zGhhuM2O9HsdJy9ofvBYu8G0di4cw3UkdXY3jRw7ImWLP23E3Q48htHbb/Ci53AZsaQgolkrIjUicj4vnL4wKF1CahTLFolk6VI7US5moexomdfJTUYXbv80Qx/0OKc/oPWL7MC8XXqSxWHyIh0I9x4E28+8PjM6yVqa7DilDiVvfxR0UbLZdiQtjqKxO7AxY03UT7fMFSk1DWXT0BIng8Ya8ejCqsSocfv2OnvAZtK68m8GpMl2dj55JqS7GoWzdZ7E4s4/KSgQsxTSyKx2HDmVI0sniqKf9fArriEpCmIfriOJU+xvOzGlsRmbUVZ1ReXvL/Gm63rFuVDXVvNr4OWX9XZGLypVUmMh5TPXULjvEjq8fC+YTEfCRsai4Sbp5rreG/Gl8ZS5l/6/Qmd0hqYyTosLSJ0lrcrg2Yxh1EKR4lrWEFAx3lwLLMaVQmGvDIg4CnvTl0bB83/jQrnqWPDRCowcqaPSpoI6HRXR6BHNl1cjmipthyhkUMXv0oJFqmUfr6z2MwWX4bt9tdQuXTONxBdnteK8NMkAbM1UDSXO/oHowqUw94u/lLPM8bJJ0MeGOa3I1QjVj03H1QyZMWtCpHON0ncgCJZNPbw7whdIYS0Q3b5wqYfNa7FpiEsemO9A+URc0XXxcX9IZrh4lYxIE3MOC7M8hSnNp4D3Wgrh5Tgzi8h1dAmaactsopni+81XQ8cgACG3dgvmuNtipjHnLjnnXVqqI9a9OMypv2G/pOBlf2Ztmll7xvdauVqZwPmiNpGwuXmNyYaSkeGKUDIKB09ECxWsMbMizLIdS18U54lgi2vhfhu87k1Cf/sv2msJnYuEHpfogCR05m7Bcf/VBS16EoEyIRQ0YkTWfKHI9PJjSqFfL+dD9mH/hByI0rN9a/gBZKSO+9HIWHJnG2Sd8S2uJU2OT3teQqMmyR2ohBhx5svaFJUbjg7oAA0touLzZaS+4ZXA1Dh1R+LjfMhJaTya8yY4c3tQrFch+xNbzdR/YkW01hBgMyNjNibXFH8ipn8dKjhGpq3ky74YCWZ0LGe9csh9bCMO56mEk3PXuKAoYlTZOH2O/ZWYARiALmpc92GJoyXCvwlfsQsyvSZfslViWJuQExrRovKbO7emVQ4X2hXfG21en2mASz+Hk+TFHdd1LYXdhOrZdJJlH5OxRwwHcaa4vlcfyIXUZ4/jaOUGaJdzpjLyJHIpx9rGM49bdLIMsh/9C9szVUGDHH+4Col5bmq/ECLERtE5ZhIFPkTY1i4UceprmuB/mIomzmVRIJNF62xLKndBl+ufKwiN2cRQH1e8N9ps76k2zR+2C1/NKBzvDAiPtdcyHZK553V2yHSMZe7iK2RmZhb43hgUqet8LiOlYg4idp1rmobuwoW+K2X9yVxooUhpR5ELeXBU/UnmK94zuwbEhnx1GBuHXzE8J5stzKy1kkh1iob1UOrgrziWMh8+andAPf+m6n2oDJMNncwLH8ucSTwg10bjkFC379a6HWNup3NMKmxxJOzMxYwCL6Phfq022LT+Oazfmd61LgNlL+3C+0w712ANqqh+vIgdws2C2jTE9Qtvx5zdOlPwWfpe6H5er1vT6ZV/05m4AK2vYxIO2PUydNBZC8QmVLS24rf7yQEqwXd9XrUjoRx3r/fBqj05kPbCSazO+ShaZpzlokCWd6up6zU3Sws8HPkDrqZIjWplLmLtOh+JSDDNFr7XT570XRFZFeedqYqqWA2quufHAczGo4oIhYxxWRDpVzsT3+ylPX8J+fu/aq8lZC4SekyiA5LQmbsFx/3XF/TGjQBhIiLMxY8PP35Co0h48NChuriNLyEGQQMJYnlNP/vv1QvK2GWxHTP9b7+t++jcWWtVsH1f9AO03KmN8efr7EXE/oLq5WoXRDJ6SD0MOgjSqGPwGGaqTEJOnAi4Cmh48KNRvTrQv7++xi++AAYM0NfHj5K5LaHL6bffoPDboZrJrsJi16/TdHXgLyaMQaLG0l9nfIWvoHHtVPHdmrwszl1NjRS4ChZWt8YE16kdZ4aTf+gQUK8eME/DQ2w6Ri+cvvkhpU7C0LTdXFH4UMaRHaG9917gvd1tUe+wpqYsnP8q9h1I6opK36qPl3l9KXAF55EeKeEr2iGtZPv88/3YoDhX05I1QaNrU3EheUZULX7WBRHkdpkH8xzaKLiOy0ilzrOy+LNY+dK3SjdCnHOJNJvzJEbEHNRXUJ4jyI288Aenk8L4PfRS95LZvz24E/tRQO27D+lRk3kAACAASURBVAWwFhXxJH5W88wsmxTT6gVyHZeQBqlxWWVPaKgzKGAyYQmErPnat/AWPldHicMY3xoQHuuFLxeaUmZtCmS7iOTpUiUYRy6ZBVnzUbUeRcZlc3A2bW4M7HZE1Wcxui001WJomqrs8vCYtNYmlNE0jP0ckCl1AaaGjfCy7YAweMNaATNSLRlgoUT20h0J9j6xRR5TpYjFmZi06t56CX1KUOcQ8qq1wnX2KOYo50Myc3KdZuaicGGg9pp+Ts0Z6wC24i41NJmjQPVbNvVwi4yzMDFKU1t/9+RUvLmscdjUw+Zc2JChlLjsBKG+QXu8iG9cdLXmsaYOVSBdJu7fMMU8zIjRcEURcQ31fpd1zf1Y6yTOlhwXKkPg9T4QyvqNKOuI2poUyNK3wMs+ivDPess+wRw826njMWbQiKKRK3GPHzTXnJNwHchQ8xif7f91ey0+c5HQfRMdkITO3C04LnFB34JJjetSPkgs4Kz6tz/DB3cjVIxOh8m0I3a0jMyhXUxWCrWy/OWK3JijD2Uo38wrpRNCzv9g9TA0gEn/SXrDyXgazTHZGYIY4F7win7wGYPUFTmF7Cp6TGyyF+8/IQU0cnt8mhYpr17CmfrNkXnOJBcWXj4W9vloJJUodBnTFqRXDs70tC3Q6OJEVzQx1IfGy6mZjsfxOGYoMTxCn0xjjJMQqs+E3iv7+kQIT/qTYm+v/glhYvE5GzNtpSumVjApEakMZLBtWXPeoXU1I6FeBpsY0BJdnZSuPZpfGK0ciNKFo7F1d0rX0MT5Pof0SmOAMD4SOfREb9d+v6EOHsJvrt/IwLMzVq8br/oe7kwNv61bAROCQhKE8hWTqeJqwsEI/QiXNtk2FhkU6BLTx8GzmwZtOIaS/XwLdEQyC1kbVkf+gytxPEcpHF3wlwo6mIrmPF4MOGGWkz5H5X4XLxz9xDmFSRhAxiNZp3QmxGFcnqsxahybhqsZs2Dm+NMOpMmEYAnbmRmp3pOqJApd3obDd9bAY1mWqwyEtGCRatnHCzpJGtoS2A46N49lX6lEKqN86C5VJzB9QVokv3IJB+9thg4Zf/DMatkO9aPnfsAPaKFOPfjROYitV98FBfKq1zPniv/m837fztGKTY2NwRiqhYcrvmjedztry+z98n13IMeVw1iT+SG0yP6rX+ZQjn8y1wr8dEyrlA8s/Q2mZmmPZcv8n/6c8Gm8ENb3Ogy6Oo+XBYM2q1BNQSOpt1MVfyQoQ2C/D35N1wgPXZiOiykz45t+kX4UyByKmZWOLnwXUu/Zij15quPbDisUKoHBMTuTZ1+CF2OdSWlNWG4jTFeHBXLc/snvrYw/0V7zWIzx/CnRAYnnhN3K3RMX9K2bXfmw0QCocHYRFqGOOtn42uNw5ok2joiX+fFu1Mif6lAMB9OIskdN4yEcdqqbfbXMIDHjs9strK1OwyjkkouVUfbyn9iTrAgKX9vpnF6iY17GOzG4LfADopEKaXBJfdhMTQvS89qNBrPglgk1eD/LEIWFl0ioaUBKVsTEya9HORVxMwtPpYA9VLbC62P2B6qgCtaAEd970m32qxe6lR8vk6vfhO9xzmpjIdZlqu1Z00DnRIqTTb0aex7se9am9n6MW1RQ3ZLvi3+Ej66/72L7MZ0tE0JE+FHXi75zFsIe7EMh162leCfpd5ehJmpBW05k/tmBYkgHX7FIM/yAH6EpOM0mdUiCUfdi2aKhOvJMU9yxYgpi0mZEowfOOvSyJl1rOGxVXg61CSl8Aj9jfuonXI57qPUl1yPzbhqxYoRH4F6lcm9mFuy5GI/WruyhSehgwijN+2UWoZOuuF1EG7TBt4hBcqTEFfVs2kXopuK9RKonR+RRcC/q+zRAXBFG3ADDccZtkUeO95cYnT1jjQ2F+czG7VeiDHX7uJSrV12PDSl8pvAKfLdbG+1Dyo7AV5deVAa+DSm059emHt77Ym888YeGR33Qcgeeerto2NTDZt+288U1PCNSw/p2ogiKwfdeleMEgmUWUgtFtanPI/szobXqYF7kjj0SUNxR9iVEay7qO9n4upiPBajr9+yFc1/N9wFRfdMLvIrCs4eovprUi8LU+RlcFMhyEqlvKVEtM1JfPostJZ9EzOSfPGG3fgOLExAkbbRrzeAKDuEOxQZmNq/sTkI0fLzGEd/fEu21+M6Y//63hQNy7do17N27FyfjgILZs2dHoUKFkIxP9n+oJS7oW3czTWPk+1570PLdOIYQ481swxeEEtIcFaO/FBGble5pvJBxsqpdsTG88S1mvdlXLUa4yT/Pc5gGMDH5l1JlUcxiEsUyCxGF519qEeh4FcUuNVQxnmj4pMJlV0E7t5uYcFEepxFCUWtOt/kxNOtreCw1WYZdaoMmF75Vxc0ZcE45MxKlD1WvIXTJ5pwSR3wHDoOQp4cx3zXdt/rjZeKb6yVdgHmx2jg4nPQOPFJ8NzZuTelcmzmw3gWGo/v+l9RPrUv+gQlbNX7dnge7aPeVe9dj8LIKat+N7Qeh++FXXWw/pvMnGQJZv8/DFyW+FxEOJbK6LziBE8ip+h2MV5xia/5NmMgotFcR2JlogMcwwy8Cy9qgJyc2QcXdU3EhaQZ0fTEK2bK5C3D5t3rF13VDi+S59KrPCvXsmDVSnLui0ZuU8B7bW+jniGVKP6HWl+wn825mFk4nz4EsV09iV5nH8XTK6a7MAo8z6wJMbRrC14phh1KbZpNnj/82nWNxeoSu+OmIVxy2MqlHs6FqonhvRqpj06RF0uhLWFu8OWa0nBR2pNqcI9tgJF10R4xQu1Ar5iLiRBLjDmpU7QimrdLq9tue6oE3L30aMgPCuU0f5asvMWvOTMfPK4BgO+YmQQCLnCvWSh829bC5xsT5ImkIszwMNJkaPwzSpMuQzI8Ji9+EQSW/Ru0pmlyhcf7VmHagsqdBz+2E5BGmRhZB1jyYpCEynnvwO+bhYWTEOfUTmd3eTDZIQV1tet9wgizyPpDvBqG6/aE570mHm6ZiKZWJFApk/i4ZPS/qcHN7sKylzKn5fPBYUziUf69DeVTEWiRJkkTBN4WC10tMN9R74WZsT7TXbnwW/7UOSFRUFL777jtMnToVq1atwiWTrxFAmjRpUK1aNTRp0gQtW7ZEJj4Jt3lLXNC37gaaDsg3g6PR/tU4AT2q5tHCoYE+XNM6yof/xRfdrEtpcNH5sHqpFsvob5WuRLizY3585aXOqFrr6JH45Limo22T91d8e9hXPML5EYfLVGhnETQdD4nq8lgWmnaHFhkknv0YcruG1qXuRnz+q1Yen1t/IJZVek1h4b0MSK+MBVV0B+INdTxpc48VrIZ9+/QpQjFW2QWyFGJkTQQZVeg4PYfxrrHe6o8XI5xmsTVrampjET5FTz+ctjkws+Cb0dJNBRoqOA+NT3MeTPpMwt+SRyzEQmi6OArvTcQzKiruRVtqQpToIORYNx+dZ2n6y/bpJmH0BU23zEZ61V9RT/2bjspYPO+aR2ZMyqbdjdkX70dskuRKaNJsvPcfRb6KV6EjqqLQbtY78HdF1/pN3KQRw8SFCU0e8ddfumjZLl53n8n9l12vYD7DgtnnEeKEJYTqmZmFBfNjsXBZCuWEUS+nLcb5Dcu+VmrA1MRy9MXbfpSpPNgkG+Df8g6TbOHkwt3x9G79HM4ZfxxDJufwM+qlBkTm9p5KMShXRTs6ayp1QMoxw8OOVMsFeT2zvTL0Rc9zmoK1RsbN+D1KazZIM3UcqEtEogmvuh7zPc1n+dzZa4iGrjmbkbkVhlaboDKYJnTJK7pvUw/Py9IM9SJ/REzKtLinzAXHOQyHeti8DjsDQkP4xQM+3QqKiAptuRwn79OJRd9Hi50aZjf3mwN466t8qjbLXhfc3jvpu+ge+6natyS2YBtKuuazLDZiKe5zKM4Jt3wTAzwdlXCDLDYFcrG1PvibZOjMdwkHJM6KKZ5qCvTa1Otez6o5p6bzTUeW0DLSeTPYVR9znXeb2U986euDvS/isy3RXovPbHnv+69zQCIjI9GrVy8MHz4c0dHRKFWqlHI0ChcujGzZsiE2NhbcZ9euXcox2bJlC1KnTo2XXnoJPXv2RBZ+6W7Tlrigb92NE6NcIpZRKbIiQ0wkztZ+Aos6/+yJnybP+vbtvjEVwD4HlhIIv2/rldy6Kwrcsw09kQ9gZazGalRVB9LIFypQ/s35EW0IMxJFpqOMiHLpUVDEbTA6q36IP16LSq7BvFRyEb7eqiFu+PZb4NlnAxqQNk6fmOrHUv+KLzZpY/etnOPx+fHWTv/BuOzt66bTleHCUWw+lUcd3wfvOGKA0mG4Ee+E3sdwqJJt5rJmzYCriyIw5fh96rQULvwWbVxDkHkwFZ/56ssZ4RNdJPUv2ZZoNJDWlQa8OX+mIcmIcoqdPrEvOztgRkMr4k+sg49FLdy5oYCY6AmwsPRkluIuoUnJ7uxNURQFY3Zhe577MLvbEiUdYdO1hntOr3oF6isUxH4XlCy+68GE+JCZbdOysyhbK7PqZlLuNxDx5AA114KBDzReZvx4f37/XTOymc0LDiYOttpWurdOK7JR6a1wYT+6YsnUiKFtKm33RTe8g77q8PgY4l5Qzab40YHdCbzIvBaTBEMEXAOp25tUt1yX83YWBqGeXjVnPIdXdN2mHu4VcZ+CxZmZXB4bDvWweR1ezlc7jMIoaOphCtUug6YklsZbNGcO0GHti6pInY3F68x4ecEQud2k7bbpzlnPR8KHMvhL9aWZx+is+FinTKcm3CCLnU3tUn0FPv9dw9/WdxqJnntfcGVT5foYNKiTYTWKPaO/LbMafI38vV9yObbBMjBecyp9M2BQBwuxDSUCUt6XLQuQgOafbon22o3P+L/OAaEDQYhVx44d0axZM+RjFXCQdvDgQUyaNAkjR45UEC06J7drS1zQt+7O2fjp4RGlUApbsApVldCV+njU0irrUoQ+apRbX8Q04EUgyR5xIL2SW3dl3j1LbYW5ldCDc8iofhqZrCM6XBvmRH5p0BCm8VVcvSPn4PiBy1i5XtMME771EnSmyMQyP4ZfMBOPuQbRLNkU/HBNK4///MIsfHPo0YAGpO2A8IOcMdKnyk3+9/fhK84NJDzGc3mJWpG5S4xlZh+Gp+jsqs8JF/N/I/fPpkoOpy9GPbeglNp16eOf481DXVyRfxm3bTQMKjMSr27WWa6l/Vai7+JqASFYtnF+Z7Yo7D6lM8l28SuZq1pikopE5k53HqcvaFG3cNsjjwDNosejzSKtAD/g8cV46JP7FWWzOPlcszTmyTBHsgAWn5JVi610ae1AhVuALuOy6xX4+7zkDVDv6mycT5oRxXOewZGjPsMtXGPNNMJpJMfs9K1ZKZS1yQ7MuSLzD1WpzQJwey6fflorm0uzMyDDSg1Gx791IGDhgPX4YkG5gBkQiURToG4XtA6OKTAXTqTaHof8TWO3/FVfcIM6J0PwqutymqaegR+jH1e/rXpnGj7e2MhTs4TbbVakNekfQKXzSxCVpSDqFN7rPAcSKLGDEmYgQggC7qhVGNnP7cHaDPdhVKsl8aYelovxcr7q4DdHfJH01JOSt1a0w9LEsRYyDOoAsbbB1ucxJyxHqigcuZzF0dwha5y0t/EZPkN39afO6jLb5lvD9joKN8hiX1vr2gcwflEB1d3Wpu+hy4WPPR0QZk/v2jUTLSfp78DeL6ag0JtP+SEKhO3SHp/XnNr7BPubMN6VWkrnH22J9tqNT/e/zgGZMGECnnnmGSRlLi4ejZmRiRMnolWrVvE46t+1a+KCvnX3w8ZPfxDxIB7EQkUfWgga32NCAvhRi0NmOYMymTlMNVbZgXhrU1H91l1N6J7N2gqTQ14KiVlI/lDSRYiN1X3xI0XdhBEjfFh1s5bDdAQIi1qJ6uo4L0eMETuq17JRyJBZl0AGpBn9kvQ7YVMXkVYxdlG5nUXw0ugY/fKL9/UzEmZrwdBB+gVPqANsbQr+Fk5xZujZDr5HuFTJZi85cBzHkUv9JJkbk7bW1vOQY8eU6Iu22zQU5teh2zFwVrGAis/m3DNbREw1efYpTvcTnsRT+MkZ0l/QDvsG3I3y0LCoYI1Zt9q1tb6NGIoskJ0PDfFqgYkOu5HZz6OPXMeMeSmQNPYafsvXBi+lGaeK6G1xvVDnl+1eGRATQmgW+Jt9csyMovft600FbtO81sm8Fr+d0ZnA6fWG4oV1nVw0r14wG/N8koEw97Mju/Y7rHDEOIxDW9WN1OzYsCaTSENFqjOvRbHmepyzHx2CfH1eDjtSbY6XNRCmSKWZWaEgXc/UA1zF/e1SjMeoGO18ggUk990X0EC1AwlSc3YVyVTNGVnRnnhCMxay2UEJf4KA6wrGxfeJUEDHl3pYrt0ry5rr/C78cVo7dYEy44QQLr1cFVl2rEZUgdJoUWazS5+HwR+yRZmNjFaV8SdIX5wPB5WTQSrfv1AaaRCtCv5LYivOIDjqI9wgiy3euCLiqoKvmrBCOk179/qEMuXZZlZrDNo5a/HvLPeq7GY4z60XWYQ5DyJkGeiZD5YVD/c9kZD9Eu21hMya+5h/nQNy45d0+/aQuKBv3b2zo4cL8z6D2ocnIjZFSsz4MRojv0niih56OSAsthXsu1eq/Z8wZsOdIa/IL4/9FQ8pilTRejCx7zRwTQfEzh4I7CofDuAAdGRMiszNcXVHb/SGhoY8WHAnFu4rEvBDJAaiWchPWMqKM6VQ7OoWbEhWEeWv+RTrGKklHa1Xo7DgMTcBD3qmG4heF3Q9CaFDG5JWdJwu/hZOcWa4cx5sPzohNAa9xDZ5nET/pY8sGa7i9LkU6k+zVsGEx3HspK0lZIv1H3TyGkS8jbfRTx1Ho5Dif4EUn01DjwYlsfWbUEZBO6gBQOOHjTAIUjiLIfJ8knF+NR6EHhJKVqiQduqovSP9y5hNMUapAzDn7L77gCUzz2mrhS0u3WHXZgWKpHrNvxe8ozkmYRJaqt294EJ2PzSA6EiZYqh2BqTgzgUO+5A4V2YGROaXfctapxN5551QejzMhNiK6YQiHaTdGdfE6ZE1u3fAVBTqosUev39mNsp2e0QxOxGOInTFbdv6mPxUfU3xRUCdOHjkhAlAq1ZhR6rNeSEFcVx5jvo5fbrrOHwhIzLgPKahERpjmmsazboubNqkinoC3VfznvGd9MIBn/6MOIzm3NoGtk0QYBIorKnTDR3O9I039bB5MaKVJOuakChq3PD5GIvn8DzGuq5dAiuHk+dHnqsHsfWOBzG36wI/fZ7x493UxQw8CESOBeesh5iDRxTbGFsw5XVzAOF+l8w1zbqmn38Gpq0tgAI4AC9qbeddlQXoEOmDV1IjaCeKqffBkCEAyyxDZS5th9brWQ702z/1DrfPn2ivxecuee+b6IDc+BzetB4SF/RNm0rPjlz46dxdtCogGyt0s2Z14af54RY4knxAiIvvh7fVISWwFduhFXCl/X+9CL0u1oz80rBj1IoRbjIYvYKh6pDMiMRZaNw696fRItdMyEz9pL6iZBptk6GLkpMjRkXGkuI6RuN5tMdo1xC+wJt4E1/q386cwfBJmVzF/aYBGQj/S/jNE/gFUcigNCdSpEjiQKcCzXOaNP5aKGSGkcLnTDiDKPjIKpgZsrgtbu0CBECqZEbVaVjSgKlZU8P4TcVqMWyoW5IVkU42wsaL02DgcaSnZSMU4uEpL+DeraPU3y93uIoOnZIFLDL2gqwtSN8ID56f7sw7o65mxut1fOkIU4Za+yY8jEZijw6nUPr+7OqwFTW6Iv2w/oo2eu5c3RPt4t/GHdDCemxxltONOCBe8A7TETJhSKFuPg3E1nHlSHYNyO9v/IjqAzX18Ftl56La+w8rJ0ygkJJhCnUOrmFZk4EyIDQMmQFQ3OEP64zSuEcmY2/Vp9G4sabhpgaDuT4kw/JSnp/x9ZEn1THT2/2CkUceCwiFCjZWr7XD7Njd2ATSaFdKut7l6JuMRt98cBA/r74j4HntrNXLGb7FkHO6BurlYvMx7lBdV/bFhhjZhvSWieswcauuWfKCh4VroMt8MFNs1gby9wNJCyBf7AEsS/EAasUscjGZcXsSxKosDAVCTQFXU5+HQrlLl/pmnRS7Ul83Cu2wAjWcLINm9KMjEhh6JT2F+13yYnZbn64myl1YgcjsRVG34A4/AgjJPpxo9TpyfK/xu5+9cwbnk2VSxCNEBWzZEjrTbDu0pjMuqus2SxbPpSieyUD9/9AS7bUbn/REB+TG5/Cm9ZC4oG/aVPp1ZGdAxhbvg+e291D7/fr1DgycWdSVAaHxQGPRYfnID7xyoBu6ob86RqLLkh7Okwc4fPjWjT++PQfKgLyMIQ4+m4blH6imuib2nUJwzIBIY4Tte2hI44NY4GIgYQaFfP+iamyOjyxA1CdQ9C5XrmD4iCQBHRDTWBBHj47BJ9Fd0RVfqG5z4agDR+LfXil3O40vfc1P2QB1r8zG6SRZke36Kdc0/n/TJdv31Cy+pTPx6qBiyBm1E+sy1MLIZ5b60dYyqshGp1EMmSl4SkGnCKXKQnBGFgTUYLHrR9gXC5NljVPj4yjyoAOGYzg0Pdz9WIyluN81dMKtmD2xmxipMrYGj8Ri+rxUSBZ7FQvveBYd0nzrJ9rWusImjF+naXLHVxiI0elfQ0REeFAOr2fECzITczEGe0+mU8agDfEL9ZwRDsbou50BqbPTBzsUrQIzSl+pkpu9i8KhTPTwncH7TvIFUU6XMQSqbeCzzXv+RZPfMWxDDbU7C6EFAmOyzY0Zo/elACvhoaxRGA8NhZIsrpcAa6h58ILNSNBA1p7ZhxkIYEYtGmk8hV95jA0NzL1/FVbhHtWdlwNhM+PZUKJMETMwA7r+hDow09BY1V8IlCi+rIX33ONmR2S/i3E/7sdSkOCAYpt2a3DPKcxcqZ3vaYW74O1kn/vp8yxapNFpvnYdf6ISKmKdq7sLSIty2ODU8gS7V8EyxvZx/tA1QHSgLiE10uIiatVKojRY5ukkjBKYZHbQid7xg0gPOkkSlwhnKCfIy6ENtQa5vXhxXUv1/9ES7bUbn/V/lQOyY8cOrFmzBqVLl8bdVp79s88+wzvvaGzzf7UlLuhbd2dt/PRdET6DQQxxEz8tBgMNA36oaByYCs3MAqTNkNyBA7FwkqxZ/5bmhX3n2Ex2FVMwjh8qGkU/xJVb0IhpHemjw70bGxz9BPYjqt4bUVaJBpptBhqiIWbhTKqceLzqsaAGZCDH4SV8ja+hOfNt8Slmatavd890oEJGit4Vxw5QjLCaUgj2tXCx0f/UPTWLbzn/syKrozpWugQZGfFjbQLF2PjRpnFPmAMbj5kaWRu1sVip1ReBVqQMpMHiNWemFog4G6Z+jJk1k3kJ5MiZtJ6M7K9ZA0gNkpcmC6Oe1a4sdRwcYf+iod6/f3hQDq97ZUNmuA81BVjLsgUlVW2L2WjkdkcfxbzzDL7HYdzhbCbUjQlTuwbkk3R98O4FHdDo32En+v9UxFUDwrVmvx/4jpGSRaKh7IJ0L6ON2Uw6ZIwKFzi3GZtRVp3z8FtfYnXN11UWjHVQvOd0OOh8yPqgsfhWqkF4YJr2XB8rsAEz99+tyCfiK/LI4+2M4zdpX0P7i4NU37lSRuL4FZ1dZfsOz+AZTMTlpKlRtsglZXwHOq8NDUx+4YxT5+BFf26/e+11PaT0MLz8Vyc1jiX9VqHf4qoB66LCeda9jGUJulC7KDWicRUaPintodyb8etRfa82P/c53j7exY8cgjUg9hoh/e0cPOrq6wWMdFi3Qo2XmTehMA+1r12836cPcLR1N9TboINub7U5jmffzIGnntLvH2lcc22/fxCF9yzEmUwFsH/pPgUFlHkKZwyh6kACjf3/q/6D40m010KtqNDb/zUOyM8//6wKyEuUKIGtW7eiefPmGDFiBJLzCwtGizKC2iD/5Za4oG/d3bXx0/u+mIKCXTVT0xslZiO69iNOlJ4GLlPCppFL425EZFM0xZQ4eIp7LYbCuN66K/Pu2QvaxCxN9cxbMHWLZlcim4pAyvi3WQhJ2EujNT2Ra1Rvte+9hQ9j+W5NZ8v2Cx7DY5iJU0myIft1t1rt77hHMYuxcJn1BKEMSC/8L7H5ErW0C/69oFNe10se+ShkVFCxMWiLdhjjmqz4Qi9u9T20DRuZ4+PIgVw47mQzJKPA4luyv6xbp3UyCK2/VKIc0mzfiP05K2FspzVOVN1Lg8Xro89i5gho+l8xdFgPwihsIKXnQI6cmWERGMXGVJVR9vKfOJi1LKa+v1HBNMzi27fv+gWfbdGkAZ/Xmo7p1x9Xmg/hFLMGuj9ekBlCWmQ9ZMUpRCKrOtwkLeDfXvUMvC5CmgT6xjqFVw+8hbfwuepD+jMzIFxrM2dqJyycFkjbgIYfsxkMiNQtvg/zt2u1+i0tPkbXs+8po1aytgyosObIXB/45BPg/ff1EPbuxfA5BdV7LyEij6LNItdDeN6XeFP9yfqxDSjvXCpV1x/BXCAuVRxMXNLLwJeMK2vY6uFX1xSaIovcYGf2fijSE8126ffY3NGHMHhq3oDMcOHcG6/n5gN8iA+hsZAsFN+X5E5XnZSpoyO1G7Y+D+F6sqbMcTAD+TH0PeP/h+KVcIap9rHriEIdaNMXl4sITrkumWapHZNAjwkXbdMGGOcvi+M3FDrNJnsYd2CdFOeFtX22uCK3h8qshLreG9meaK/dyOzpY/81Dkj58uXBLEf9+vUVnS6dESpe0jFJlSoVMmTIgHOBqk9vfB7+FT0kLuhbdxskKkb8NIt1hzReiIGb3IJtPLtAFQhJMtPhjB5+vbMuCm5fgONpCuDefPv8UujCynLrriL8ngNlBEwhNqoXd0Kcsp3RteDFf8j4IppFad76WtWuYNkqX1TPVD4WFWbpYjuKoRh2YkuOWnixxNKQBqRtyLAfQgzWnPBHBAAAIABJREFUxxkwXnUH9ofHK+PDws3foSEqpOCVInoZ5//nx8vrTpqGE2tweh9+DuU3jEdskmTYvPYK7i6f1EE68HiJqsvHnpHIroPyI1PUQewqXBcXps1XkchgIn6285cTxxxhyc/RBe/hE1WATiFHwjEYxbZbIEdO1qBgtzmO6bENUfjvWTiTMgeqFDjuiqTyOk4P/Bb/x95VQEdxtdEbgkshFLdixWmLOxQvbqVAixWX4sVLlWLFXQotLj/uXiB40eJOcXdJQkj+c9/jTd5ONmSTzW526X7ncNjszrx5NjOf3gtqLJRw0JJsvRuspcwwuqIQpEKgpIMFv0I+WIbXVFGtfj3O9cCBIalvyqAJghdi4ZVAaiKEbvHi0sBimg+dGjQsHj9+e895/9FQoQFjFqX8Crqrhw8EyABlGHoK8AEqtUy7okNEcaeo/SGK0M99C4yQqY0iNy9JkkiTPJrTPGthOZZD1peQSHNVjNpGHYhySoiH7xuourD2pbXUQKL2fYrtIoLGomhr86KSJsyEep0PyZRQhaIVBO8wyTlt3VN69Ice/poPZ2LcU5naRljev/Cm0P9Ng3rq26f4C0/zf2rBKs4+8x/3SGREJ/DTz48oR4aZwLF7lhUYcaG2aLJHlmUY+eazfg3urzMPkwto4dWoJhxTFHXf2+roYT3YMImfYZOQoeFq6K1g07lRcZBHX7N/Fl3GACGT+WPtyfz69Ws0bdoUN2/exKpVq5AqVSqPAWL/ev9nW1AvbhoWTE1Ic/cIjiCfmI/rvcfiQLFOmDo15KXNhyGLhRW6ENMe6N0phAMGFGlY6EKuMMlmL50O73kLKYVH3Vr9BvuuvM30/tbGCjxEElEMrcsA/IyfIXEw6fG7jEzGz6p4WsA+LVsWLsqOteiFD0KUKxa1q3oQdRFz2oWZ8Zpe4ObPQrx3pbFdePYVApFQdh+4wkqF9MFcMzEv7bdodF0qiy3rPMDZuz7CmFNrqdIE6TWlMkyv+FMkREI8N2obdE9kp07AWJkhY0ho4y8Y9/G+WG+mSf2AnwwjLiIF6LyAvgfVntIV9dgIwGvICLeSa73GIO2wrvLPNxaiPUXobMaaRz0LzhvEZkp516NuVHTTC+hToBtGYjQkkpoSXeHjHG5MUAep9y1HQEIf1Cn9wCISwXOUEsYIBvduWJEQGijz51s3PlQ7XG86UjKle4WPCr5hNS/YDrGnTxIGJ4W/sxCdMmmSDHrQEFqXvjU+uypBCpYvDsS0Gd5RRvJY1ucItj6Uz1TulbnJuuLem+Aoo2dMCTybugzW9tr2VnJJs/OEcz0+qL3BQ8Rngxl6Vn8eqPVWkSCF/HcF6QUBJes/aBw2bCjrciKTxkPjkNyPSlhPo2qj9Hoc9fvAhEPQ/5nk7mhT+jSm7chuRKr4nYqgW4sCWGy8CP4R0bGZ514vhKcTZ1f+ziDEO/cUhWm7q5YFIjh2bHqzsTdXC2z4YrpFPVNEHD00WhQ0fHhDVfVY4R3nqN89Boj9M+syBkjGjBnh6+uL9Ixnv5Hg4GC0bNlSpGQdOXIEL3TgcfvH7nIteDa0Y5dE5U/zKrMHXUXjfm/Qdhi6+PFHC0VZR62hAkRDpHjTrEjrdwFHEpfG+d+3i5cr0xcotnp5HDtCy9ZZD0iEELN3bC+KiHoIa/nvSrmlUrXheQmkubQb1xJkQ95YZwhoZYheK6A4CFic6P8iMCT/uVUrkGI+PAXSerQmGM+QEAnwAv/D5/gC/7MYnJlxXiGc6QcpA8ofsZE+wUPcfR7f+Llw4dCFpM5cG2vXUooTlRsS8rV/EkI4przwVOSZkkBFlt5Npl0pIyNlEn/ceiSJIyeiPTpiovis1tRamqA14289KqMyNopC9sExv8fQwB6ineLYZRgjqv/hIYmplA7FRTPRpz/aP5TpMNN+uoH+41NbpGCNeu8HdH3ys/i9Q42rOP4onV1F6GzHen55MG4gDVLjlkBtyofD2I/CwsFAT3keHBfRkPh4Cc6HSB+yItzzfC0dTfopPnqwHf7ps2Dd2PMYMEA6+sOae0LlUoljehSFSjHXPzyIYXMqKTix/v6ycnvOHKOHCopXjZ/9JFxz70NfiHtJosvJNFJem/UnEU0jNe8doswpw2A0uqAbRhv9UYbxQnyBhpDsimFxA+nrpRwGTAecCkmwaS3CoKMh6V58Psf2PMiOhDfO4kH2omiSZU8o4zCi42YfzJxD6XEFV/CB6J+ZPJXfjUEXdIa0/lfPfYy+g98T+8McJbAWDba68bQvOUeELjfziKi1D29P6e3rBfyE1P730D3cQ3JxyG/4VgBU5MsXsm/btAE6f3ELuSvI9Fzfkn2ReMKgSHHL8PxZWgD0beNmpKRnz/BmxrG/e/Q1++fXZQyQVq1aIUOGDPhe5adqYyMrOpnOSTb4LotnQzt2dVetAmpKMBTUqfQcSzcmFJ8vVOuEzsFjxYuJ+cRMw1LpVyodiccphmYy2jIyQFG/R+Yl5tjRSmJBM1wkr0nknwZYBIVsYoZyVPn6F2NlQ6ZX53A+VQk0zbQTe/aE9Lh6zPVYFVhFfKEXs+uY+yty9MaI5EPCVSDDKkA8iZzIidOgwcRibLMoz5q185Mm8MfF5ymEkrUVZQXppC6uVoDOvplTT4Z8+Dt6n2stuj2gwh5s9y8q5lIJPZH79sm/RHpNrVsyx54IrYX6Y0+1gRaeSGtGsjXjT4dMpdeYKS/cK0nxQKAX6RIe+IJZGRz74TiUXSbZu2ulP4SVV6XHXIkOE63QksKrIbLlPqIh8Pq15ZE6qMS3+A3DITUaVS+kG2I+IgIYGvKURsS0acAfhyQErQ52oEefospBoaeSEoo3MGlyxHx4D8cy18SSJisEDC8VTnMEhMXN3DtqTCqVSWfjjmgfrSHYMVqaBI8tWOzj4zmeQz5rZyf5Br8kHxcuuaRynqgVI4fPQRQUfxIOXa2VvqIsb2FqnG70+vsFwS9GfMQO8sejSl9gW/uFhnEY0RQh/VrmtD6Sp5ILhMhqq977CjWfhBiDPI+GFw0/IlglxDOxl/T9oZ5lygCwZU+Hd0xYdURvO8/8PCAx6Mot8eEd4IdrJRug7XsLQrGhE6BE1fvoUVIVgYrovqIR0qJF6PuV/aYz7Y8/QuCww5sDR/7u0dfsn12XMUACAgIQGBiI+HTVWJErV64IA+VdFs+GduzqqoerrPMIYcclQksTzDHyp+mZUukL6iEKBOMVYolceCKefA1ZVRfZh6xjRypbDwvaUCe4MkPc8sVP7x5TRB7AR0C5WivEzYt/8A8+FtfRU1TIj3IaOS0UBVsUSGupBxtQSRSc3kBqpEVojGOVXmB+aTKIWuDqMgG3SaFyOQLfWkx5RF+Kzlgv8zh+yb8M3x2SY9jTbxUGHqlu8fJXUNGqCPf00pPIUS+3OH5DxeFIPbyHUEYVF4U1uFFrxhshlzejosWQ16CqQDYzS3jpFWoPqkgB2ej/hy9EM0RkWw9pxKoo3dK4jVDHbwH8veOhef0Xgi/F3iJ0tv/++6FT7uhJ34IKFkNi9IPs0heQFQPRH/0hozWZcQGXkDnU+JUSqdC9uGdJFKcr9jwpvHmydX/pqaT0x/3pmxmZccnCyGZqKOdTOVEUpwJrNmafL4qkZ/dZsHGr3yPaR/PeYTBmj59EF5NRJVlLwxTNi8giPq8p9guq7f4u3Kio2XkSG/4iIhoLgZiPhvgS861O2cqVIU4mpmXGu38N647LrIpB6GuspzXl39Y14HHWnq3nkBVZcQG7UBwlscuiuR0ohVLYaQA5cH8QQpaog2aUKDqAwiIstbWPrO0iiIq1OqK3tWF2gnDPLDiSHYlunMX97MXQNMvuUAZIRWzERkg+GkXCyc8q7TKyzjmWKhHBjXPB9+w33wA9ZDDWJcSjr9m/DC5jgNg/FPdvwbOhHbuGevqCeDGWSINEz27iXNYqeLlkrZH+oKcv8Dh6l0t8/Ax5iiUSHdxbpAviTx0d6TCzY0cZ0rpZQVDpDL3em4yhT2TumM4Fover5mcBWLE+jvhqfYbWaPRkqkUKVvVi97Fqj8S1Z7Fyv1jDhbe9BHZiJ0qJ7ycXnoG5sb+2SYHUUw/oraZ3coK/RCpiYW8c+CPYO5aFF1thwOupIGqMTNv6HEvEuelxFU8TpbVgUI+osuWMNTPzFwT7hiBSNccfgr9B5y+oX18WN1OoaKQ8HzL3X2OGKLI2IzFZA0og/4uOpe+NQNxEalFUqkS1p89DliyWcJzW5shc19Io3Q7MuyZ5RDY2+gO/XG0u9oeSk+kqIue1zQCtSDJnvrn/VKpjZNfNnDIjrxeMvShqAc+spw6RM2IJJNN4fSzCYkjUPLNw7x4+Gx8xA17iWqmGaJtovlDSlNFFJJ/r16NuBxUqFFJDciHRx8j89B+8yF0Qm37926KOjR5wRkAJHmlE/MgMd/q0rI7ftcuCfDW84nhrI2DA7datkF9U2qPiAqFjocCrEDCIgRmmouaq1uE+O60p+IeQTxg1OsS0uU/KsFD73lptxtuUf1tXyZrhzpqpitiM60iDdLBccGWcXM9cEjWT+L6ViX3LFqCCpV1sa7fEcXwukpsjosYHz1Xzzj3NuWTUTNXQqKiZnp7MtObZlecgQ/8m4tozm25Bvh7lwiQ/jdBAXPxgj75m/wK5tAGSOXNmXCSt639EPBvasQttTl8w4F9MBQF6+oJSgNpW1RiardSMRFYxcuyIZQ66OfWkMtYbnmed4VzvS+NyNzB7q+Q/OFOvH6of/dUCsShO7GA8CoiHuPC3QEeqHWMFlgVJ1JTLY1YgY+ea4Xo7eay11APmUn+HX0VbaXAdN5HGYrpUHYhCwFJe9JTxnuDyyxSib1tQDhWwRZynjBOmzen1LI5eA1vb1yMgP/8MHJkfAplsLYqjUrDUuBq/txKzn0gI21l1l+Nb31oWXBRheSJZT0K+G11+xA/4AbIW4xIyIjvO4BVkwbMSW4pAzWzoc384K3MDAawqPhhr8vaxIL88HT8/sr84jJupPsHdDYeFUyC8GiJb5jesaGBWnMNy1EZunBSM840wHwGQhrdeqP49fsIvb6BQ9etxD3oF+Bmpadtzd8DhVhMwfboB9gRrxf+29DmsY3QD5LhPSeR+uAt+GbNj/ajTIh1MoV8pRD89ArJ4TxrEe3gTt/JXQctUay3IVyPzDNO5a6jwjvHqiqrnJCM2U/Yewgc6OlZNrDDgtd8WPbam4OtkhhnwL64i7IwI5X2n4f4HWoj+LOm4FYP2lH2r8h+RddEjFRz75KDWKH9RFvhbIgOG1LPpNTDqWtaisTRCmC4cVtkro02soSHLOB0/XOMSJSRfTkRqPszj1RHEWPdIA4QpiYz4k+OEjqCs2WMaDgs6Br6LNwJpRsoI84T2x1GqHXnc3h55jcg8u+qxHn3N/pVxaQMkRowY73zdh76Eng1t/4Z+WwvqpabYW58VKI2Eh3xxN3FWTOh6zsifrlYt5CWuajyqZTgmSLso22uPwrCAruLlbQ8/gWNHK1u3lnqSA6dwCpILxFo+NZ2ksU5Zz+vV+3wBMv1jO0oLiEx6fBu+mI7paCUOm9FiJ1pML2GzAkkDIjg45Ao6aztzwA8jf6gp45oSrUwReFEpqPV0NmajqTj2x7TTsDdPK4FYo8izatQAmKrhaqKUdbWnkuOOwQD/d/k+aP9osEDtUUK+Go6fQgWoxPkQaFnFcm1LBITnm4s/GQXpgjH4EOcwEt1xDtkspmvmTNvysM0RkAxJnuDfR4lFW+ZCZX5HJmkiFW1GeeFNVh5te++zsOqM5KCCkUQroFYD5Ry8QHyR16/SNM17hkpa7Ac3DeNYL0BWBegRZdp+2740p2D18a2Kqlhn4XU3p2CxTkXVgDxDAgHsoNKYdPLVyKQlmgvRuyCEvJQISkQabIPQpK8cY3gpOmbnSR0sxVLUE9OjSCrfNlc04lNPHIBWtwaKw6wZLZEZs7qmGXmvLwZhEPqLn5mKehbS0E6EJ3gCyz1vKxP74sUA/V0MBvLZyMJw9pnpl44QaylYIxL9gBwLpTOiedl/MfOvEMOP78d+j3uJ4nQKn1ksWrf1ueOIMTirTY++Zv9Mu7QB4u3tDcLx/lfEs6Edv9IKCYsPyGHn66AOloOwsclwX1xcPTiZNnHjRggviE7QptJhmOLAlwMV2sjmuTp6xNZST0jQ9wwynWxanG/QJ8G4UJC0eh3AV5iD0/m/Evn4RGeiCCjLGyWR9dYuML0gT+xzAnFLfwk3KngOT1JktdlQ4zySrE0JCQhV2ktVrAnFCMzj+DImQdWUKfIspgeMvVILtbASrxATKXHbIJlT7dJrN1ECRLmUqAiI2oNUgBWj8jS0QhtME3VKJBdj7jiNS7JyqxoQsmGnGS6J4CZ2OI6SbSPmiaT3tFev8KckIgg0OrIXGZlfvQrGcyQQ6FLWcvmtoSUxjYe54G3b2nef0ZiJaOSLSHE5cMaiuNw8Q+1KncAk3zzi699zjcCwV90dxhFkjuI+qtwASTYugl/sRBja74moXTMXoavIxuL5r/D5lzKKtTJ1WwSMnSwUWZVyGplnmIo+snaMYFyMcKyAjIDSYDiUoQ6aXQmB7C6a8hKmbsxoU4qOGRGKBI93kVwQi85CE8HtEZYo+PR2vl+KepEAxEI8vAQ5QGxV/sO7E8zcQ4wmz8eX4jRGmVVdRDacwRnkEN+faDoEve71touJPbx+2fN7qCL0qkDXhL+j4iIJhtEwrS8WXi9pcYkFcZqhgf8sBMXwxnc9A/D7jBg2RV7t6acrnOvR1+xfBY8BYv8cRlkLng0dZVMZZkObNwOVKklv0vw4zdHQfyaCvGOi/7cBmD7Dy3hwMvy9QgJdgRGTtmlWoebvEkKrferlmHyzllD8iMnfoYNrwvCyr+bUE76YKecfyALz5agljDBd6NXa3HI+Co6UL9P+hTZi0N8VDchIfkeFY6a/RNN6gXhIgOcC2UVPk6Ch8wIJBPmaLYaa2Uut15MQ9lelUuh9ZW47ox7KAPFCkOCx4Nj2xS+LFhm3kvDZIpUhotj4jt+V8gr6+LnnBg8GshROigT+D7HNpzYWNlgmYJ/79g2J0Km+Ef2nwvYBKOMrvb0nN99ArvKpLaJPtnh7mfpBQ/Dly9CjJvkakeTKS/5Om8TsUWU/u4zJhGRPL+Ngok/xafBfRsFtHISkMvl+1AFb604wULwYlWO6iS1jCKtjOgqeTZ0HQMS7mlglIInDQsJqlM4X865J9njWtYx53Nwupu239S0UDC+hrpnvRaGzjmFEhBgV/KwiICd87+M+ZN3WUPRCHwwVBi3TqCL7DFMREJVOpSMiKXCKhck64ot70uL/INlz/HtXAs28DRyBv1tLy/wbBVEQBwVABp0LykAPa85OJSyIHM8Owv+DbFg/5oxFjQzPsWc/maM/Jb33wPe1JD5th0mYgnbic1lsxVbIm+Zgl1n4/lwTh+0PW/d1WMfpdWiZM8tao7CKzNlGqlTAH7c+E8ALZKtPg5uiaU8ExN6V+G+c7zFAXGidPQaI4xdDj4B0Ot8ZnTFOXFRBfqoHJ1FEnj+XLNLkWsDs2SE5J9u2YfKpMkIZVCkikcmfdvxow+JAgECp+Rj/gIWdBXAoVFcm5RqLdie7iO//GnkYnWd8ogiMjWNJENgdo8TfSfAQz2MmwfxAWfxNnoEMiZ8I1ueIGGp6XrWeg98Pv2Iw+hnXVvUe9EIyFWmMTDtHHhzDMchUOcLJ/oifxGcaXop4MDKeXmesFa+hIESpFDLiNN1XssoTRacMdhjdYAG4IkJTqT7j0dHg/mAOenyfuILsWu3RiIybqR8TJsiIQZIkQMeOkUv7MHtU2Zc1D4sJWGUzDw3rfK4jnRwjiTSYQwNAT4m09z4LC5o6rPUl94EiwSRL/F2kCHWo7vVXNQ40upm/T9LTqIy4mSMgd5t0R/I58h4c1OcJqjdKFCoCompAWnx6EdO3STSqk1/9ip4P+9ldA6KvL+uIUsd/jO1Hk4hrEFKZz1cFCMHo1nt4KoATbOVQYlqnbgz3wWDjOaBHGaytH6FxiZwVD37YnaouxpZZIqLaOpR1RO4J8zXMe5uIgrcgYbCVgcfnVLOgGZiBluJ7lRpJw4/Ry6jeH/Y+p/QxKTj2cqlPYctNmbL7e7ah+O5xL9y+La9EMsffNn6EdA+O4Uz8fBjT7JDBZxOegWlvX6P7fI++Zv8KeAwQ++cwylrwbOgom0qrDZlrQG63+Q4pp8ki5+Hf3kKlJinFy5svBx36U3AsBE6QOIAUsnbly2fUsDOkr+fmO3YUEW+dnms/P8vzVqG6gFUlt0kK3LX4kUXNPwUPwABIb3paXMMNpBVRD6ZZUEqWBAbEG45KmyR3QtGEx/FZj9yoP6YEcj/ajbP4EBO7nAURliJiqDHyRE81RU8VY2SlyxsiL4UuxGPohaTjlylJFHoeJ6GD+Nwj70bMv1dRpGhRFO5/VCqEEV+Nt5+h82bwyKMJiuGj53txP2VOVE530thnOj8Nj6NiP+FhIzTCgjdcA4xIAUxf6t9fenrt8fZGdpx6VEfNP4u9GXUjZwQZ11URvQ7tvK7yaKQd1kXcjyqKZ4YrjUyfWAfEIm5bU7F0Ajwqj4cTlBKOCV0WVfkD9dfJQucv0+3A/GulhNFNBezEicgxbYc1NnMNSHnfELAAdZ/qNSAqMiFQsL49LHMnKcxp69jRbhQsa7U1d71SIFnwXWyOUREVgzaK9DUSPJ5ALuTBCWNotnAomRGhdKdEWHU56gJ66tMP+BE/4wfxk07mac+zwDz2rFmC8c/lRIj3+jmWoC4axlyCwEDgZ4Q8S0lYeA3pxTuGDpGo3h+RuSf0c1SETTk1+Kz1ehGSsksnRyeMt7iM4sfiO4XRQo6NKF4KcS86njv2zoMt53v0NVtm6e3HuLQB4ilCt3+BPS2EzEAoFCwms/fuLQ8gXuUbKCB6dRYulJ7X/fslw+yM7EPx9Zk+4tBN489g9NpsRhg9qlFuonrNPvkkpFhZtT0BHdABk8SfKvqjX3cy2qItpoqvmBqTJ38cEc1QXnd+/3Xc+ZjhJ9O0GKYnd8R5ZEEWXBSF6RPqbxdpFCqX2xZDzZwypmoCFqG+SPeiMErAegIKjydqGaFACQk62f9r1HwgEVtYWKxqXcQ440lvqqumYLGPZq/qStRADazGHSRHStwJ9XLnOSpK97R4ZSTasxGPEqbFmG+vGelL0R2lY80KPc8Uouv2vdoe7THZ2FsKdepT/IW/UE583xizMReNLcjamjUD/pT0O3YJjRASnemecNUgi3yZsqdE5wppglmYgyYWqYg8bmLm39D+oiyeObPsJP66lVMY3Urs8bJbG6iOgvV7juFoeVo6AbaMP4WRa3OEiYLVu8g2DNlXVhx7oMts/HCusd0RELalry///gufClCKa0iL9LiG20ghnBxmLhlbOZTKlQP++itkJnxRUvBssK4jA67gNlJZ3Q96DRkhlTclrAs+C+lcUgq2vc8C5eVXUaaDyI/8OGxhbLFehTxTrEmrVMoP8RN5u2wKlv78UY4BTi7rJOksYEriF7FXiHo/ip42eax4WzT3m2ygjNliYNp1I0fzyR4DxP4FcGkDpGLFiti0aZP9o3STFjwb2rELFSp/Wsf3ZLJrgQKiA40bA3PnSux81ng0aADUOvQ9vscv4ncFCUuFmsGQqFYwonoWrEGQ6qkM9BSaUY7WxKmLqv7L4B83MYrnemQBXUnFgZGQYq+2Yzs+Fd2VhfnNjAJjsq3TG68TftliqJn7et4rK7IEX8DJZKUwouYOER2hQahE58Lgd2RNL4L9ojA+G86Jw7hOT5/CKAx25fVSOdj0oLNe6Xn95ih2dqYwqDq1fYV2HWKIqABTyphepVIFWVvRbkYhpL1xALdT5MXtTf+I4yJi/EX1vlPt6VCt/G5K6h/R5qZMjdORiXSSws+wDhvwmTjGHsbqt42JxdfLlsl55D5VBdxqbnnuJwnO4fBziQDWHwMNlCO9XZ3YkyhAr32SizaVRLUHWDdAxuaZik7H24pLbRu2H79tK2QotzTIGf1TNSBJfZdjOeqIY2tgJVajht01IGxLX19GFwY/CXFupMYNAyFscowOaB80AbxnaVTYyu1ijjQ0wAIsQCMxDqaBqhQ581rrUNIf4izO40PxLCDAiAK7sPdZQChsOqmULI7zJer5y6L3+HiB14gp0idJQkjUwMpZLggUagWVzPOien/Ycx+b55rPFabLdZ/1MT588Q+uvv8JCsc6bHC/6CSTA/AzBmKAcXmVJupK47NnbsznevQ1+2fTpQ0Q+4fnXi14NrRj1ytUBITYlMzhoWzdCpSV3kE9AkISL3pKSbbXAyPF74nxCFnzJwbrPyNbvOnYkVq2bi1NgshW9OZSiHiliiTVmcrLyFSq7Dhrtbt1PzqPJf9IAgkqZ9Nif4M7ATL/exS6GvUhyttoy8teL1qmEr70rvR26v3QjRrFhSE7GIxHSILEeIKLuapjVZtVAl6WRqIurvxC1D2QrEdqez6kBsEHD/AIPhYFnqyB2bVLcgGo6NM2lEFZbIuw8eeoPWk2KttiMiZDhggKYx/+RmFUrw6kXR3y/YgG+/EsZyEjisNj7a3/sHV8ulKpe3inorURFdTbIkJZK0wXpJexESCUTmU0RXW/zSlYaX1DkJfUfWyG4VXztr/jTBSe2Fx0vfPH21H6u9J2o2CxLfP6foNxGIfO4joksFTgEQrym4YRz1EpOrasq55GGhOvcAo5Bes4Ff1cOCmY683CiAshigk9nBiPBQKWkqhKxzQXolMJV6leyui5gvQiEqRzErFGiBRnTMOKSphmW/f4245TUR2mPDLazPefisTew/sWBKU6OmRL/C5qXWjksX5k+3Z5FVvWNyr67ew2PPqa/TPu9gbIiROqFiHKAAAgAElEQVQnMGfOHAwmZIybi2dDO3YBzTUgl8auQqYuEtlqfoPlyN2vlkUNiFKciUg0IbAtMm6UKUk1PnuF1etjCvInhqLd4QGrF3fzxfLx4x1Y+VgyUltjuT7vnQ1ZXp/D0YQlMKXJTqEwFCtmiSblE+cFHvgnEG0wpWscOuE0coq/e2MIhqG3MNJ+l9xcNnn6zLwRy2N+jlqBsqidhoVZCDMsQAIAlMh0AzsvSfLEYeiJ3hhmdUO58nopA0ylP/ycYAgGPO8rxjG8zVkMW/ahRQRI1eXQKDv/UKZJsMaiHpaKcyJi/Dnq7tOVNKZg5b8a4olXRds0Nlvf/RW/4jvRjTGdL6Bsy8zhMmY7os9mpZLoPqlwG+tRGVWwPtQlNySog0rPl+Oxtw/6tnkgolO/ytIy4W2PShZ0sxPl0rjVyNS5hrjWggbLkKtf7VBF6CoC8onvWIyFBJb4GEfwDz6OkgiI7jTgPsz3cAu2QFJ5U3FlXQCFES7FLM+/bU3B4rHmKFptLMMy1BXtMt2zHLZaGBgsQH+ApOKZQSbvSrDMpIiqdEyz8dU51SKMudVA9ItRpl0JKuPe87gCOng6WqBH4ukilVWNnce5mkPEHNVhYsDY1x1Q/IhM2Y2P54S4EJ+/wEIsREPxec/36zDwwGciukOiRNYdRkXdliPu8aho06Ov2T+LbmmA3Lx5E/PmzROGxz+MowsEQvfnC/FsaPs3dHgt6ChYac6HpBCp/G6Dg8FbFjeL4s25Wl4WNT4/P7uLN8PrZ1T/bibNyohLuITM4jLWWJ4Jc0koW6XM6rCKPEd5ENVxhPMdgy5GDn9TzBRkgHy5Ek2JaVO2ePrMvBEjX32DbzBB9FPB+uoRENUvFksWfRGi+OhGFT1yTEXhP3pfVT1CVM9xVLRnjoB8en4apqGNaLoYdmMvillEQPi9AElo9RrBsWLBKzgYe3K3xMb6v1tED6JTyTHzJXyWZC/WPSomxsQi7+lerQUsto6qxiijIm+LiKIaFWugK5U0mP53Vab16ahdyrDj9VSKjYrS6fvTeH5ERccAhEoj3bED4M1NYbiviYxqKm4PflaOklkf/oIm574Xv2+ccgljVmSMkhoQsxKe0usObgWnDDViFRFQPyimdlsio6GjuMFYhyoC/pUyCH3RH4OMaxbE3yKyZu35phD0+Jst137b0pnH3qHkP5iw82NxSl+vIVgeXNMgff0Ov2Bbie+EAXL8uGs4B6yNzWyA8xg6lIZAOkJ0kkVCLY9ED/H9L/X/QaLieQUqNMdHiaq6rSi6faK0GY++Zv90uo0B8uzZMyxZskQYHdu2bRMGR7Zs2VC7dm3UqVMHRWi2u7l4NrTjF1DnASmb5DC2PpKoMCsqTUDrwx0svMvqxc0IyO/3aiP1/hUISJgUdUrfj5IXt+NHG3IFsxIYCwHwg/TM/Y6WaI03YQoiJyEAqjB43ydtUOP6FAtiKdUqUz0m+uYRyDZ/exXCpOB2BtxkGWzDDpSBjtZkixJs5o3YVGag4LegjO18Hp+2zGLhFVeeTBpEbV9PwARIpLKuRfYgTpmioo5CT8GiJ1Wxpjtz/m29ll4DQtLHy6OWIWN36entkW0VXpSrLnLniULGuhbm3FOhEbkcZCak9OwJEGDBBq4FW/tlz3G6QkOD8dX5y7iMTKJJPW98NhqjMeaKtJo4INyalzgmPMZse/pm7VyzUrkidn3UDFiMwDjxUSjHMxw5KvulhOhOuXAKe1AUxbHH4jd7i5zN/TNHQM4uPIxsDeUzbE2V8Ug/pKNFBERFyIQhlPpbYMQI2ST3i49PlDhSzAbb1avAGWQzarB4OUYwCQoRjBhIlgzInTskRceW5wLbMDOjE/b2KD4W4AwUnXuDBklfDBHfF8Fe7Id1/cDWa4e1x/S9TW//zSsBeIpEiIMALEY9LEBDg0yVURtF0hjR52JU7/G3taevp4pkfIm5AhSCUgGbjAiXnppMosiHkERTCqnQHpQxZ445Mtfy6GuRmTXLc1zGAHn48CHOnz+PPHnyIB61ijdRjfXr1wujY+XKlfDz80PSpEnx4MEDTJ48Ga1bS3bOd0U8G9rxK6lHQILOXzByh1mUPRR9LLzLKnWBObAbUREVsRn/IgMy4t8oSV1w/GhDrmDNq3UzRhqkCrqJfUkqoegj6UmksHCUsLuUX/CdKL43R0D4G5Wb5f6ShIooTdPQ2vBC5n7vKk4+kZwOKp3IFm+jGQVqTJ5p6HxcRgC2D96NYb7FLJjV9Tkcgt5G2lVYnA229MGZ62K+lj5+0mDcXuyL8f9IkjtZ6C9z+HVhBKR0mvPIWVPW42wuPxgpRvaxiW3aGWPVFRqOad3Sl9h9RKZwMHVPRbg2ozzKYyuuxUiPQW2viLS/3btDipXtVRZtHau5DqnX3ZA6nGS4a5D5qfbueafA+6/v4lDa6ljVehX27gXWv8nUiur9Zq4Bue4b+hlmrgFRjpR16Vvjs6vS0bB8cSCmzZBoTPamkurPFjo6tm2DcGq0xAxjys08Nsqo5AG2pkTSvlZcPqphkpVuQkXB9cEanJaYjvlohIvILEjxriIdPsC/wvCxJrZeO6y9Y2aC53E0RItiH1j7MTNGCwwIkoALWXEO1+JkFQAekRm/rfvX3uOsgZYQgpoOJYpOCksji+meL2PEx2clnuHmLS8B9hFVKGP2jsWR53v0Nftn1yUMkAULFghjInv27Hj69CkGDhyIHTt2YNGiRbh79y58fHxQr149fPXVV0iTJo04bvHixahbV3oG3xXxbGjHrqS5BuTEtrvIXVYSi/mW7IvEEwYJ72GmTBKKU6UMMZ3Bp1pxpL+2B3eT5cTNLSfFcSrNIaqVDEfMglmx5zUUYtRJ5ERunBQkykFBMj/8CPKJbnTCWIxHJ2FwEbPerACMRheDn4O51jTS/BBHIMDwpa+/aG1RIPVUC6ZoZDm5EitRS/SlFpaLz+YiRzVfBtylVyzkyuSH+w9jGGhEUVV06oi10dtUyq+at5w4iZPILQ7ZUXM4ul/vYcE5Q54PFqAXwn7Dy8si76mQyEiuAIWpFBq9MPtJjMRIFPREeInrY7Hoq4okcF+SqJB7bsYMoHhx21P4omJ9zHVIozOPRZeLsnaidIKD8H3+hktDxGiC8Aqx4I0g/IHm6OHzh9hzSgFzhAdYR8FqVP4O5m2R6U5nP++Hbi9+DRMF6xvfL/AF/gdFCMhz7GVCZxvWlHB6yTehkrEcysHDL3So44jUyLDeS6X26OvM58IS1BNrQKGT6ANcEZ+Z9qTqisx7g6l9jCLaI2YmeLY1BiEEt+RAKYy/8QLxkAhPkdjHG4MGhRjVERm/Pf2MyLnmKDTP/QAhUUud4JVEtvlEPVFeQWzL/cRnTlShjEWk384+1qOv2T/j0W6ABAcHi6hG37590atXL3BRCxYsKKIg1apVE0ZH1apVEYtvWpCH4AI+/PBDjwFi/9r/51oIhYJFVxRjzBRSPZOcS0PBIhrW/PnSQ5eq0kdIeecYrqcphPvr9lukOdiiWEf3ZJtzqKng/v6kvlD+iBLDl6NKeSGnx0ZUFl0+0GM+fjjV0AI2Uo2FmPqFj0zBFLSzGJ6eK88cYHpZba0BYUOKV4AIY8+27MXMM7JeoA2mGPUQ/FvlkPMzvbhrA6QHXUWp9E5FVdGpo9dR7VEVcSKs6x1IBZNwr/0w2ILETPWHrNDrUUX8WR+LjLQPZ9dPWJsfawrNaWQX6Go7UUJAlFJUPdHqWLUxqeIysW+io1hXGSBME+K+SXsgpGheT6Nhn5PgoZF2wnSUnhguyB+JHkS+kahOweI1dQOkduWXWLZBRpMuVv0GnTDOuFeJZsQ0Pt77rLGJVb0ycl3biDux0uLHVtcMxmp7HSnWlHAi0jEyUQFbxP2YD4eNedL5JSJSI2PNM6/2G6F5Z6EpYuOVsQUZgciLY0YtkV63w4OyZQPOnLHvjtYdO8rA1tOVVOtbUVY8myi6UyYi47evp7afbXZW0THlFRQoINaZWqYg1rnGj5FYsNuvi1MbPTIvw6lT8jru4vCxfVZCH+kxQOyZPXlutBsggYGBSJQoESZOnIivv/4aly9fRubMmUWko3HjxsIAyUvXxxvxGCD2L/p/tYVQBZycCOYREcqKxZss4oSMfHzxhVSEM2eWMIQK4pQkW+Xwl1AC+WAm1KC9YXxnrQc9U4QVVgqAXvSrIF7ZF/0FurjDFvxxuVwoA0S9YPTQvBrHMtRGXSwTf+ovfVsNtc6dgXHjZGs6zvzuKr+g853vjAiAMirUdc/Fyomsr07jaLyiqJ9uj0h1uHIl5GXI41w9WqUbiqw9GvxLID4qIJ0vK5K3wvp600QNCO1lEqpRiNXfOsE8ZOgrIaVnNd2MT3qUjxYEKWt72Vr0bVfMMigeuEPcVx/iPOLipYGsMxHtcbnnRKxbFz3FurrBRPS4LE8P4zBk1KNnrNEY/kpGQyhMq1EcOsuLDMaBCn0MBCxH7DdzCpavbzACEBuxEIg/0Qxf40+LZxP7oAx1lRqkGMlVhIlRBXKg2Hp/mtfY2vrymNjwRzHswRF8gseQ8NxmiYiBZg1OXG+PtR6/oae45gEUFOlYKnpo7dosG2W6nD1i7hOfiyle38A1pBP1dUrMHBnq+4iM355+RuRcfUy6sXgEH4soxzHkwUc4BqYj3oXMIDDzsbiLwyci82I+1mOA2DN78txoN0DYiSFDhoi0K0Y6jh8/jmbNmokULJIQstg8d+7cwhBp1KgRXr165YmA2L/u/8kWQkVAOAvE/yTTUq1aklKb+dHL5QtZCRXBJbtSIu7jO7hVsDpaplhlKOTEc//7b/eYzpo1IYj8KAz8tPMbhVHoLv5WsJz83BUh3+fBMZxAHnCcL14AJ0/K85UB8h4eC7hLlf7A3/R0C/4dUShY/QVIyMfnSCiuORadRLoXFacKFUJ4BPgbjcH7QUmQBI+xBHXxOZaIc1QxpFqhyCpZzlxhes9pOLFg/to1YIWvJSKZuS/k0JiUZzzSDekkfprc5hCKd8znMgaINcVxIWQ6kIy+PYOOyqYra9FRrKueE2qPl8hxHztPJxNza1a0qPQSmYxCRK8lPq0dSkJofoYxevFhkaSI5/cQp3LUwauFS0PB8LJvfIYt+CcnEl07jQfZi6FJlt3iGcbHHw0Uexwp4RkGb7t3IuoQSJfOFlhjKv4hQAHmyIfqT1Qp/4o3Qx8n01EZ/VGiP18554pMNaLjd9ZzSPnl9OvNQyNBLqtIFgvgIPahqDikAyZgEjqIz1GJMuas8UbmOh4DJDKzZnmOSxgg7BINj5MnTwo0qw/4BgZv0ruYP38+5s6di7///hsxYsQQRerHjh0D60bqk1L1HRLPhnbsYpprQHg1//RZEOfaRZxNVxbzWm4Fy4r69rVkquXLe8XWhIjp9xzXSjZA2/cWuKUBYk5hqIslBi5/dazCGlQXC6AjyBTNdBv7LqUQigpftKwDMctuFBM5+0rKYiu2QZI66mKr8q8rNPTufzckAeIEvsCmpA2w9IsFIgKgFyfzGrqhMg7foDPehFBMfXCHaFXz5sDMmSEd/zfOh8jgfx7XMpdCbZ8dFjUg6iidAI352lcgn6GukILFfiglTSn1U+J0Rht/uUYJ8RQFYx7FtsCS4u9WmIZFiVoZKF+M2lGctXb6/pPpMsEC2SghnlvUrLBP1bBaMIpT6mCpYBp3FAkhr2E1iqssVlrlmyTfhQ7Dy78FVPNPaSQWdZUq4gHH7xQbOY16IvpGVqwp4W9rS3nWI1ojw7S2DyXWgt0SVftJ581Qnn9CZm9BeVEcPxNN0RzaDe0GKUpkaz9r4p8l2axiOicULw2QeZBRV6aAqrRdfWFsfebbvZjR0IBHX7N/0l3GAAlvKOfOncPs2bMF/8fFixdFTUjp0qVFIXqtWrVEypa7i2dDO34FFQoW0Xj4rh7r+wk+wVEcQAEUwgGLDhBen0XZO32DEIiYBpkUWY/dMQXLbICUjL0fvgESnrI9Jhrs1Dqz8/FDr7B7n7ehqKgJ0kPz+ovpPpIiLa7DH29qa7QZtfWFr7y8Snm+iEzIhMtQ6W+qSd3TlgXncR5SM+mHXzEY/cRn8jgQFpRCb/qjR47fY/ZewZzSogw8BRbAvcfCcz19hMzzXTFGXDoRnuAZEonPzoawDWvsupJGBfLLa8Pw48ve4vDcOI6cOGXUrVCpv1OwGlq2jL5iXaXTKxjSc7FzIWvAKfyNgqKoWAn5bhQy2cha2/EgT2mHkRDymtaiuC8/zIt454/jcqoi+LPtXuFE2bIF6N5d1qIwckmP+0vvBIj7+gUefdYQ29rOx7RpIY4WRkYZSYusWCsQ158RYbUbmSjEb78BvXpFvKd6fxhJUc+FiLdkeQYdVEwX1J9HPCID/hUIXDtRMhQKl9pXkRm/vf215Xxr9TY0sJeinji9HhbjYxwVCIkUpiJaY6O39ZlvS59c7RiPvmb/iriNAaIPdc+ePcIY+d///of79++LyAhrSdxdPBva8StID1rhwjDSJA4nKIlPnu/CgxQ5UCn9KQvvMmF4+SA+tvc58haTaUD7inRGvKlj3K4InX3X4TLppU32+hZuIbUYlypw5ucVqCnYi+/hfSTHPdIFWKSV8Bj9ZUsP9v9QX3jE2mOSBduxWlFGUFgQa4soL69KvzHnrqs29NQKvRZFwdUmSAA8fx5yRRqUhAh1ddG5QMhj4lWjOvJeWYMHMVOgf6vbwhhcuhT4SaJ7ok0bYMiNpvBZPRuvY8TEwAEBqFPXK1ogbMOaW7OSRgVmMWQEm4zRGXEZ49BZ/J0fB0XNhSMJ/cLbA3oUKk8eYFPsqkh1aJ2Am84U/45Q6indMQIj8K34nAsncMsnl3GvOKLAWI/ijhkDtGgBDPEtLvhHlIHKvigFd/RooFo1oPXXgfhrp6wlmoy2aI/Jss+5ZFqlvZ7qsBCq1DzTP/j55xAkdfo9GdkUJJbrEeAiskKoWAI9RIWYOZYi0mZkxx+Ra0TmWGtpdZkRAvnM90UeHEcNrBaoaonxOJSRFRUoY5Hpu7PO8ehr9s+0Wxogatg0OtauXStStBYuXGj/bERzC54N7ZwF0FFk1kHyWBAvPgOuisiG8i4T7vXgQUjNOeUbZl/mZxFHUUtzcNWXiHk21YtSGQ8fZgnC8QtxBXLMHHyFJpgjTmE0qAAOGdCK/E5PKwlrlUgwxvnbswe4dcvyKBp9+/bZtr56BIBpIo3m18R721fhWbxkGNH7rqjPMadgEQVnARqJC1TCBgsIUHVVjv+vv2zrQ3QeZWZD73++uUjhCIQ3YgmUHy+xHW/flr2kkdxtS3VkO7cGzxKkwMXdt4WBTFGpMbaw0DtyzGYlrVDMw9gfKAu7WXPEqBkRpESfcdsoblV9cranWHmAVRSOhfFKaU+AZ3iBBCKi1udxH/TBUKv9dlSfVRSXBfKEkT2QrDIK3NuIgJTpsG7KVQFKoOBqjcjG/fsQDIAAthTohZ01hhp1bh9/bD84Q9Gilve3IkBktItoduXKARMnAlOmWO4yew0f8ioOHSojm69fy4h1eEKOTnJ1RpVY41hS0ZacOSXGyYUL1q9m7/ijagzW2jETPxL16g5SCKfUdpRGFlxAOlwXEZ5S8A3VBIkZ//3XkT2M3rY9+pr98+/WBoj9w3etFjwb2vHroXsQBw8GYjash1ynluJlXB+c2/dAKG66Akhv9I2dF9FlbBbRuZudfkXqsTK9RxWru/JLRJ9R/UWpUnMuIDMy4xJ0orCbSIVUuI21qIKZX6wVOde//ipb0mFRVdssliacpc44bl5JesDXrLFtfc1s4GjVSrpO+Vbn25xvxjcEh6rFbhiJkegh/lSF8/b0wbaeOuYoFQFSSszEeD3Q/uVIcbGfuj7EhLlJjCJW1YNdkF5wBYFsLtSP7j1qVtIIXqCQkVizQwOEyGmSo4JFH15QCjbH6GwjX4fipTJd4dBQQVRKITfLaeREvnxAz+PN0OjVLGEcdmkXgIuXYziMhFCtNaO4jFzQUcLozPpE9ZF2z2K8ip8YtT99JOrTFD8Mj2Pd1qnVF5CzhnT5by43CClG9Y3SKK45ZSdpUiBVqhDQirDulKhO0WFkhFEhGiNmoePljz+Apk2j9r4NCwXMlqtE9fhtuaatx3BvmWv+lqMWamGlRRPkPVHpn/oPRJEkiMa7Kh59zf6VdTkDhLUe5PmIjNhzbmSuF9XneDZ0VM9o6PZC5VDzbTR7tnxjU7l9U+xKjgslVGiPQbqUu2A0DpfqIgjSqBTxZe/KLxF9BvQXpUrR2BHjU5QK2o7LyIjMXpcQMzgAAYgjTpuK1miLqRapMKxfZb7z24TpFpxO3fsVEbQwcwSk7ZX+RtRpQKub8E6bCtevA79LUmchvyGErTop7hucA3o/3TUC8vn5wUZNi8q11pVzjvFSnBzI6H8GNzIVRw2fXYYx6ApEhOyfNSXtLpIhGe5jDaoiHa4JiM+j+EjUZJklosXK9j5JzNwlQz5ZgN5HZIStmtdarA2WnCsbUAmVsAnXkBbpIbUtR3MgKCeKSlGbjhZogT/wGjEQE4EoVcpLePiJekdhJDf40CEcQgHxt6r3iso6Nj1lx1wLodaCRolOZMrjrBkK9q4dz2dkhLROz55Jp8k33wA9pH8iysWcrmSQgxYCOGZyY5jhwNkJchcRKtxVRTmC9P6R5HQy2lt0uSrWYB2qhhoG0/IIhvCuikdfs39lXc4AYXH5l19+iU6dOglCQluECFljx44VaVgBb5RIW85ztWM8G9rxKxIKRYb5ASz2oHDvxIoF5gfTc8iyovffB5b23IPSfYqLQ8bknYaux1oZkQB70WMcP+KQK5hflISonfyiiUi9eoWYiAs/pMdVXEYmcdL3+Am/4HuLLtLTSeNL3WZK2SC7MQuNmefNugVzqkVEXkZqjZSC1SfeGAx+2VX04yMcNYxBvWNz8SW+xHzBwh4PL4UH3VwE64icfEesnzkCdKDtNBSc2kZcqkO+PSjXr6hQpqjUUJjmse1UCqTAXaxCdVG/oyRLFpn+Ed0REGs55ftQWBR0k5SQBghRppaiDuphaahpdVQ6U1jrZzaYuhXbi5F7JNxuO0wyyDfJiZAHJ0DG6yLYL35XBoij+qw7UTJlAl606Yqi+yQAwbE9z5C3aALxmTUOKvWnT+GtGLy/vPj+QLe5+OHMl1GO5EenhlKolRJOZwT7+PJl6Agp+8dn7bsgXPO3pX8pMAw1LxxzVBAhOnru9DXltUiMegNpEBMyxMSIZXLctQo64qj97+gx29q+R1+zdabCPs7lDBDyf5ARnUZF1qxZUblyZRQqVEiQE/pQIwELYh8KRnQes2HDBvG5cOHCGDZsGEpRI3SwvHjxArNmzcLKlSsFJDAL4TNmzIjq1aujX79+SJLEOulSeN3ybOjwZsj+30NFQOgqHC5zz0X1aJIkUDnW6mr9Cm/Gr/srij//7j4fLTY2FDnWfJmwgDOqihntH134LaRObVmf8Sv6CXZtShpcR2ZcxE7Ie6glfseihC2FB1VBdDLqwwiIDtHINonuaRa9SDwipF9qjVhkPXAgUO/VfMzHl6J5srRvhlwLXYiQ9Sm2g4hZWXDR6kREtxIe/urII8w1IHnPh6DPECFqLapZNNWubTDGT40F7+DXWJOsKdbUnynqQnQ4aVeI0tETrRcgK6NRH8ww9ERvDAs1VUzhmiNLlJwiygikB5tkpNcO3MRNSKRFHbCBQA3v4wH2JK+JBJtXYMgQYP582UVHpY2ZnSi32wxAymkDxTWH97iJSk1TifQqMrkr3p6B+Zei/yGJYLTnuzUYeKhqlBsgY8fKMdsq0V2XZGs/bTmOjio9usO5Z+mg4vuw1oY7KOhEUyO6sy46ga2OOGgeoys8c2xZu8ge49HXIjtzIee5nAGiurZ582ZMmzYNa9asARV+L7ozNQkODkb8+PGF0t+2bVuULRuad8D+6bHeAjlLPvroI2Hs0EBKkSIFDh48iN9//10YIvz8HpPsIyieDR3BCYvE4aG4QHRt7+pVHL2fDky/UmRRVL7THVqBFagtrkbEHuL+K++8uz1kWa+xYIGcOBYJ1rg+GeNfy5A6SdUy4ZJRzK1ju+tpJfT0mSMc+lKw1pXRFeWh528RedmGSjH5aitazJXe26V15+B1w68EU70uZ5AN2XAOO1ECpfCGIty0P9xlrcw1IDUS78DKx2XEaP5X7U80/6uZgcLE7wi7+wSJxe+E4+2OUQIMgDnYXGtXKQY1cwvoCFJqqQgmsAgNQt3Zzk6f0x8LTHd79jQILxAfceGP+Wgoom1x4Ac/xBN9JbJUP5/JwoehDG9HpY2pvjFwO28eUNR3GIZBQhpnwxnBzM76lMOHQ+7zclf+wB9oIb4ogZ3YzfuklESzs4eE0LxQ5MHw87P+YNZTs/h80I3RSDzKXeoUUpItXhx2l/i+oAqjGynu8jwywx57IQgVsBkBiI3t4HPJUjfjLDDyylqld1k8+pr9q+uyBogaGpGuqNCfOnVKEBNSkidPjpw5c6JAgQKI+aYg1f6psL2Fe/fu4caNG8II0WXGjBlo2bIlRowYge4EYY+geDZ0BCcskoerCAcRlmqcGY40oyQkyriOp3HydXZB0EVR6VVXBs9Fhn6NxXczm21Fvu5lcfGiZEt3F6+6mipzMTDzdxUBYX0sQgZcMWBFyc9wErnFqYpgi4YE/+k1MnpaQVhLEtGXLQ0/KlAshDw2/zjAHC7KyJFod6abyQAKIYpbhPpogEWhuuFOCo85AhLr/EljHXpguFFsrwZJ4kGVNrenys/45vYAC0AAwpX++Wckb5YoPM2MlFQcu7ALknxQSSZcNMaif+/s9DllBCpjgvtw9bls+MD/HMjLUirGbqQPCpl3la7Ie4HcG1S+ImJ0R2SalYHOGgKmQhnI4SUAACAASURBVI7LPRnfnJBOhG3DD+C3rQWM6Aa/4/HJZo9CmuHynTSxw3GUbJs7SovQVf+tecytjY1pmuWlT+GdkIiywStwAHcZfO/eANHDbJWohDm29ZrOPs6jr9k/4y5vgNg/ROe18OTJEyROnBgtWrTAdKL2RFA8GzqCExbJw6kcMCWI3ijmc09CB9GS4h/gZwawCMEr0qumTgXatpVXI5Zs4cIG07Cj0iwiObRwT1NwqKo+Qi+w7+U9AumDr6BTkMwnT4KHAqlIh+BV49WhjMO7aEQK0FVbnTsD496QmTcqfwfztkgY5MVZeuOrq0OMGhR+p0cARqMLBiUfLWBqFRQpj2Hkh95idxBzDcjJv24jV7lUout/pumL8akHWfDV1M14CEsuywLjjhiPiehoMUxXMZLNSElx8RL3kAwJIEk1bnunRqrX1xEjhleofHpnj0E3AhVi3EZUREVsxg2kRlrcANmuGUmgtMZUoFVrC2AERz4bCC5AhnhhmFWdCzSWDhJs3QqULQsVbSIXDguxb7X9Aamm/iwOGdHtGio2TysMEMWYHpV9pRFCMkTFYK9vRs4lOWzeJeNDjY/zeexY+E8YRoKIGuhOqbscla1GyMyZUY80Fv6sOv8Ij75m/5x7DBD759Bo4cyZM8iRIwf69OmDwcR4jaB4NnQEJyySh9M7Q28sDZAmmIVZkIxWpbEdvigtPjNfnR548ZIYOTIEQoVabe7cbgfBq6bqbXCo49FRpGBVw1o8gA/ex/1Q4XWlCNKIo2Hx+PHbF4GK0oEDEX/ZKg80PYWnT74W4X5vBGEGvkZLzLC4aHacFrColF4Yit8QmiY5ohGYSG6tKDlNV35//hnYuuEV/toVW7StkMn0C42uvhldVsu6mAFZ5uF+pUbC+87cbQaNXSXX3pqXWOfX+AnfY3r6n6wyVDt7/fS+KiQxzn1rSOg1pl9Vx2qDdJO1OVvjVrNIP3KU0WSOgPxUYCW+P1hL9Gtv3xX45WhNiwgIo4lNDnU1oFJJHPocCUWEl4Y5cTgc0VemJE2YIDk6WBbZsaMEqXhXhc9EOmY43rCEzpwNG9zXAKNxSWJLa+hdNHZXrHDfsUV0X3r0tYjOWOjjPQaI/XNotNC0aVPMmTMHhw8fxsdkd3qL3Lx5E/ynC9PMGjduLFLO8vOt4RGHzICeglX5+VJk7CGLM+d+tRaxa1Ux6gv4gqYX/n7XX1Bum0SDOrXuMnJ+9oF4CLsTBK+aSGtwqNeRBmlwE9tQRqBgsYibaSYlsDvU/OuKIF+4VGBoYFgTGigsyI2Mp0/1Uyl/d71TItnrOziWoRo+vroawcEhVyyLrdgKmc9Bg3IOmlh0h2k05ExwF1HGl/K8s9+PvX3w3utHOPdRXZS5u8Si6J+pc6puQtXtcM5VDrYjlMvIzqVObkZPcJygF+gXezieBMTFKHRDICRbty7RlT7HGpobN2RPeL9/smYgBmKA+Dtv7DOoELAGoyDTmj7BYRzFJxbRQkcZTeYakBi+27ANsgbyK8zBPHxlUQPC7zelbY4K12ci2NsbKxe/wtRpXuL5pdK4HNXXyO4Tdz2P9xx5SHxD8/IJMA/yJUfmeehq8/FfMy6tzb/HALF/V/7nDZBXr14JFC1bhEXvGVjRaUWmTp0qiuFZ+8EakPDkxx9/xE+E+bEi0WmAnDhxQqCL+fv7I06cOAJdLBfd0O+IhCpCpzvqs8/k6N64is0oWES9UWzHyXAXPlmTCeXOnSB41fJZ80IrNvjniC8gbGMgGH+gueAW0IXGgDXvHtM4WBCril75oqUH3lQiFaEdpPeTNTltx+cVOVUvchVEgpN/W7T1JeZiLmQKSnlsNowRdZA7wF3qA1IKpm5EnENWZMUFwUBMtC9d2ntNxsRgWQMwodl+/LS2kIh8qDS7qEyvidAiWjnYGrmZ+TA95Y+/RVf6nA7YQDLCmv4hhl4tLEclbERHTBTdZxpgtvyJjNobws+Sq8YRYkbBOrfgID5sJCHr11SbiPSD2ot7TxTPP4NIxzqds45kTiVc07174limb9FBQEM3vEimI8bxLrfJZ+KyZRJYkQXorBe053n4Ls+Vu47NY4DYv3L/eQPk8uXLyESgchukTJky2LZtW6gjly9fjs8//xxVq1bF0qVLbSqMd7UIyMWLF7FgwQLQIDMLDZEvvvhCQCG7u4SC4d25U1oSFNLkNm8ueCwqVYLwstP7ujnHNyh2aII4JH2yl7h2L65Q7jZtcs9wM0PlL2TavRBCn/bEGyjiN9/1xhADWUcdV6YMYGX7O2RLhDJA/lcB2LIF9xNmQLJn/1pc81v8ZqRdKZZq/QBHFQM7ZOAmIkzO+dOnwIRDRVEU+3ACuQTvhC59MQiD0F98lQXncRFZhJfVFSMg1sjNwpvH6PLOm2tWuLcUKEN/DEQp+OIzbMAdJEdK3AGNFJWa4siiefMz7NTKs8hZK7uYxk0VhiLliF7i2aUDRRxNWhYfPdgG/3SZsW7cBUybJiO4nghIeLvP87tnBqzPgMcAsX9n/OcNkJcvX2I7cQhtkKRJk4qIgC4bN25EzZo1Ubx4caxduxZxydwTSYmuDX3kyBGsYPJmONKkSRO3N0JCEREeOQKRr0AhdW7HjqF4QFh38DX+NJiGs2b1ctsICIepE5Tx7zoI4ZlQW0Cvh1HfRaaYPLw9FdbvSskyCoCTf4mKd+fjJeIivihaDoF+HIlu6IbRoqnEeGRA0qq2o0uBjezYeR6RlAhjrBjr9yWvjsJ31+DV+ynR7+tbBnUNj9VZ4H3wAJnz+4hUj+LFXasGRM2H8szbMj/O3HPm/uhs6FTUgwJe4TkSIDZeYR4aoRD+xoc4jz0oiuLYY3G6I41eZZzTOCUk9lnfW7iF1OL6v+A7fI9fBPSyTlQ591Q+5MMRHER+FMRBcayja0BsWV/PMZ4ZcNcZiC59zV3ny1q/3coACbJCNRqDicTRJDRcqlSpgrx582LLli1IyMplOyQ6NjRJFMdT8bZBYseOjb5kN3NjCRUBYUU6c3QoQ4fiaOVewnNYoIBEwaIi8c2O+sh9cjH84ryHs/sfi1C6u9aAcJhEtNURoqi0E41IsdtSyS+U9RFOnI9jsdIRYTO3d4so5Y98I+SK/OlJSBHte3iMpwjh2VmABgJ6lylkCfHMwjihAk8WZneT5s0BoslQmLa0MG4z5DowC6+9vJE04Ss8eRpigE1HC5EuF+zlhRqfBWLNuhgCRIHpNxRXqgFhf2yFaqWhcuhQ9OXMmyMg7PtRfISPcAxMiSNgA++Z2WiMppiNVKlCSD4dnfamo9DVqfQcSzfKd8+F6p3ROWiMUYSu4LMvIDMy4xK2oizKY6tRj8BIKMsVHd1fd7v/PP31zEB4MxAd+lp4fXK3313SAGFUggXdjCp069ZNzCkVZRL+mYU1GSzetifyEJlF27dvHypUqCDSt2iIKJb2yLSlzomODT127FjBLG+r1K9f361rQkLVgLDKlNWmlAED8GOMn8HSHGWACO95n6qS/puU32+qUplO7Y48IBymmY+B362PURWVg9aJaViMeqiP0KxaEWEzt3U/hXWcuQh9ygeD0OZfmWaUFedw2TsrXr+WZ+9AKUE+SKWQZIS6CB4RG6Ax7e1vVJ+vlF+mAFJJHI4e6IGR4jIKHlkRu61EDdTAajyNmwzTB98FEcBpYCoOC1dULmmE1K4dYiSZ54/GLuFao7NgVzdAlCJvjb29G0ZiNOR7SifsnCjLQxwiugFStUowVm+ICa+gIPxb7mt0iDvDAgWralVg2Y6kiP3sIW4UrYPWSZeK30m2ymedo1CwHDJwT6OeGXCRGYgOfc1Fhh5l3XBJA2Ty5Mno1KkTCGur6g5ogJCAsFKlSkhNRRAMPwdh7ty5mDRpElq3bh1lkxJeQ//++y/y5cuHp0+fYsiQIUhJ0gFN+HfFihIWMyLi7A1969YtTJo0FTFiSEghRpM4p36IiZjeMfFenBiChV4XrkEHvrHcWHQUrOJ5niBvSckivbtod0zMMgJz58rBGUXmzHXYsUNqQ4yYwDH4+c6aUmue3fS4guloiUDEREtMx02kCdUdR6aVmC8WqgYk5nSgVStxGAns9qC4ccp5ZBHIXdYKtB2Zi+/I9VJrpIyIEe8PQvf7lnUe6vpMAWJ9yEnkRG6cFF8r9DB+drUIiD5vRNMZOhS4dk0q7yVKAP37u0bBrhmymv2msTESPSyWvhR2YCdkHZlKmXPkvWJOwSLi0kMkQRI8NpwHrPNSTONHjwTjo/wxZb7W118DM2YIslUytbNAmv4nd0xTdOT952nbMwPhzYCz9bXw+uOOv7ukAcK0Jm9vb6xevdqYU2WAbN68GeXKlTO+r1GjhiicXr9+vdPmn4XoZctK2ENrElaxengddPaG7t37IP78Mx2aN/8TCRL4I1jHNg2jszRSBgyQUJTuKjoRYQy8xmvEFEOZgjZohyniswUPCMMhzAVhbtYbqCd3joBElLVXrbMzlRSzAVLJfxUydakpusKaleWo86ZbwXgh0Lv8sCRWQ3z+ar7FtnRl5ftt949efyCMqDIhZJhFsBf7UcQ4XRlgx5OWRt33twsbWYfwdea6ueszwVq/zaSdPEYvROffAYgFHzzECySwaMKRUSdzGikRlz4olR6Jn1zD+SyVcHjwBgElrtLw6n/2FIvWv0lZ5MYaNUr0VSGSEbWO6aYe8cyAZwZsnwFn62u298x9jnRJA4QRDsLZ9mTy9xsJywAZNmwYRo0aFYpTw32WIKSnztrQgYEASzmGvwE+ypLlPL76ap4RCXkWFAvXXydG1veC4P3yQaipbNeuXaiojzvNt05EyH6z5iEu/DEHX6EJ5oihxIoFnDwpvYhpy+dAsvtncCV9CTxavdPta0A4vty55fh0YUqG8uASxlUXIjGfsARfcuiSKyVLKVGFsQ/7UFRcsy0mYyokMz3TkR4iqfg8At3xLSwhsN1V+TZHQJokWIpZzyVfTVWswTpUNeb/Md7De3iKkznrIXDBYuzeLb3bFEfCwTp0A7hA49YiIEAwTiA3cuGU6OFS1EE9LA3VW0cavqGANAD4ZcmNuBdP4lLqYvg6224QV4WRpF9/BdLhKq5Cwsffav8j9lb6wUDB4nedOgFjx7rAhHu64JkBN5oBZ+lrbjQlEe6qSxoghH0lr0azZpKhmuLn54cJEyagQYMGSJcunfH9n3/+Kfg3yFvh7uKsDU3Md+YQv8kmkkpN1bUoXNiSXyHAKzY+zJAaTDnThRGeT+kedFPRU7CKFQOyFn0f8V8+wKkctfFq4TLUqychTJUyfhXpkA7XsR6VUQXrDYhTd+QBUUvG8ZEfwAquQ6hVZa3BmTPOzcdXSpZKJfoAl3EZEi57AH42COFy4QROII/4vgeGW6THaCU7brdTlQHCrD/efkVf7cAOlBHjaI4/MBPNxefY8Ic/JPLeJLRDB0wy0mr4nbumoLnCglkj7WRqU7l4ezD2XiM8hA/qYBn+RcZQ3XWk4atHQOhIIPHdMF+ZhnccuZEXx0V/iJp+8SJQNtkxbL33kfiuC0ZjLLqIz4x8MLDryGiNK6yjpw+eGXDEDDhLX3NE312lTZc0QFjQTZK+zp07hztPLKL+4YcfIlRIHW6j0XSAMzc0vdn58wcgICC2GG2CBM/QpesEPPGOgWQxLOs+zNNB1K+6detG0yzZd9lQRehsTmGeVqggyD3IA6JKeJgjff2FD+L5P8LxbHVR7uESg+TNXXlA1AyyELhyZRjF3NZmlnn55GosL4nGnSa68sd89eIfP0feYhLpZzw6omfc8fDzAypgEzahkvh+XLF5GHu3kcF/EV0EdlExSXoKFtsb1f4suk6SXA99MBjDvPoIroe0uIZrSC++/xkD8AN+tri8I2sRomKcrtxGWKmK330n+fxYZE4njpk40dHIa3oNCKOYjFYeer8i8t3fjIDUGdC09L8ChllJCew0alSU8UrjgyVVngJ0V96Bnr658gw4U19z5Xmwp28uaYAULVpUMI4vImtVOEKCvCtXrmDv3r3hHeryvzt7Q1epshnr11cw5qVatdUoVOgg/IK9cSUwMRJ7+SFlzNDGyAcffIDmxAl1QwkFw8sxML/o1CmA4ZDdu0PxgPgjtsD+n4UmaIZZ70QERC0dIyENGkhPqFmopFCRiQ4kIkVYx7SwO3dkz/xiJUTcwOdYhPoCdpfSFDONaEAZbDOiBPyNKTRzZEad24nZ+54hyRP8+0iCJYxGF4P35BMcxmHkF993wliMRyeLCIjHu23f0pNcMCAg7DbSpweuXpUpm4rDlWCNt2/bd93wzlZRXB5HA73tps+BJUsE+sDR7Y8sSAgbJFiNBc9riCb39VmGn/+p7SEhDG+CPb97ZiCcGXC2vvYuLohLGiCDBw8WUQ1C3RJtKiw5fPgwihQpgl9++QW9e/d2+/Vx5oYmAtb48dMxalRXvHghCyjTpLmONm1+D3ce3TkCYi1/WuSjHTggoHeOzjoqXt5MryK6TJMGAZi1UPJh/F2wPeJMn/hO1ICYF5mFrMuWSUQcRn0IMUy+k+gScwSkbVvgauwsSP/qIrahDMpim+BdaH5rMAajn+hmNpzBOWQzUueYJfjXX9E1Avuuq3vfpYc9WJDgxcdLkPekERaIC1TERmxEZfG5zwfzMeNFQ+ERV8JaEEfCwdo3Stc/m2lMly6F9JMpTzSIzTVS+kiY2nj6tGPHtmoVUFNiMoAwuxMCWiHj5uni7xpVArF6nbf4TGOowp25mIvG8uCtW4GyZUVq3vz5EqyAKbke8cyAZwYiNgPO1Nci1jP3OdolDRDC21LJff78OUaOHImGDRsiFl1Mb4SoVwsXLhSF6gkSJMCxY8fsJgF0hSVz5oYmkhf5SzZsqIg9e0IgTTt0mIgUKUwVyKbJKVCgAKpXr+4KUxbhPliNgBDRbNs2kTT9Y5MLAhu/Tx9gyBBgSO+H6D1UFjnj22+B334TH90ZBSvCkxYNJyhDUcGE8v81D4uhGPbiFHIYRcBj0QmdIIk0E+EJniGRgf7j7vUPpKd5QzsDetq3XZVkcsoA45i/whzMQRMx/vLYjK0oLzIKVdmWJwXLvs2rkLDCaoX70ssLeKBhdTjD8FXPMQZvmYY1DD3RExJVxAcP8Ag+RlSmAyZgAr4Rv/014hCGb8nniYDYty08Z3tmAM7U197V6XZJA4STffLkSaHksgCaJIPZs2dHokSJBPcG+UFYlJ4xY0asWrXKrYnx9I3lzA1N2GJGmO7cSY6JE0N4PcqV24LSpXe+db8XLFgQ1UgF7oZitQaExtSaNUDKlOja8BbGjAFKlgR27gRObriKnJUlgoxOqMCIgYdB2HEbQClYNAYHDpTpLctRC7WwEveRFMlwX1x8CeqiLpbhCRKhbP4nePo0BFzBkUhEjht5SMusYVkgAx1CdqE4imMPTiM7ckK62LtiFEahu/hcNN5R7Hv5kQULujunoTljjsO7hkoFDO84/ff//Q/4/POInBHxY5WBzkjIDz8Anx36Fb/iO9FQZlzAJWQWqZNMIat1IvRvjPByf3lqQCI+954zPDPAGXCmvvauzrjLGiCccEZASEq4YsUKnDhxAk+ePMF7772H3Llzo3bt2mjTps07EflQm8uZG5ocKwcPHhSFrOPGfYMHD94X3Uib9hpat5ah/LCEaW+fffaZ294TOgoWWcG9v2qAPCcWISBWAnRp+UzkVFP4kp7a/TRy1Mkp/t5Y8TekGv6tSE3yREAcu/zKUFQREK5FY982aINp4sKxEICPC8TC70cL4ZPAAzjplQu5gy1xgh2JROTY0cvWzYSRyth6hMTwwSNxzBD0Rm8ME59T4haexU8pmNMVS7ozvPHOmIvovAaR2J48sa0HzkppUga6QombkHsiOpzoKDrZtdRBjPGVdUFM3xv2uju6Q3J/JMYjPEFi8Wzr1QuoUcODgmXbynqO8syA5Qw4U197V+fepQ2Qd3XSwxqXMze0MkDYF3MaVvfuIxA/4XMEewGxvCRLui7uDsOrExFyXL+jJVpiBoLgBW+8BuAFMlCzFiT4wAEcQCEx/PaYiMloL17eVPCIte/uSq4r32MsgifvIwnTiMKVbMx3+A6/ii5nT3gdZ5+lwU2kQircNiCS1XjeBf4LnYeCRvPXf3dA85eTxBDj4QX8EA+z0RiNMVcQ4sWFH4IRQ6QEKU5Rd09Dc4X9SbQ4AuQpoVJPQ4NCw+Q1Hxl8angJED2nIMaZiTrbJponURcAzGyyGc1nlzdqof5EMwGeEeztjZWLX2HqNC+RgqXIKt09UugKe8TTh//eDDhTX3tXZ9djgLjQyjpzQ8+fPx9nz54Vo795MyumTJEvL0rNmiuRP/9hi5lhGpyXlxdevnyJ+vXru3Xam5mIcAw6ozPGifHGx3O8RHxj7L2KbMfQfZLz5GCXWfj+XBPx8qYULAj8bUmd4kK7yf27QhTucXJZEDs20DZgrMFhQPSnU8hpcGBMQyt8E3uagVj0Lije3F9kqFYGBflPfsYPYj4y4pLgn9iKsqIg/zI+QGavy4bhoVbfo1xGzX1AI4RF34wuWZP48YGVK51jfPD6oQyQDOtkNTqAy8MXI9O3krSSshI1UAOrAQ1SjlFeRVbpcaJEzR7xtPLfmgFn6mvv6sx6DBAXWllnbmgijQW8wZcMCvLC0KG94O8vCc3y5v0H9eotC3Nm3D0CYiYifNKxL0ruHCLGe+KvO6jaLDmuXJHD/77gWvx0QNa77Ou1BD8fr+sxQJx0z6g8d0ajAgOBL7AQC9FQXL0SNuA8suIissh1wk/4Bd8bPXsXiq/z5gWOH5fGF2/V1phqMMAXxy7sQXGcQTZkwzlRH1ISu4zUKzURHuUyajfr4sWy5oLPB0aZMmaUpWGOrvkwj0KlYKkoRtuP9mDyPxJMZFSuaeh+spX4TE6SLX6ydui2Tw5M6nwKpHDavdtjgETtzvC09l+bAWfqa+/q3HoMEBdaWWdtaELwTpkyxRi5t7c3Zs+uj7NnJdFZokRP0L27zBmm99UsH3/8sajBcUexWoTOKucBA8RwTq65hNzVMiJpUolsUx+LsAgNDKWXpHeeFCznrLwOxVu4MBB3/3Zsh4xGTSwwHXcSZsaP28uKv0mwtitrc4OE8F3gv2B90r59IXNNo2sDZO1VI8zDAjTEMyREAryw4EZRZyRMCFGU75F3bwaUcc7HeM+eQOonp3EaslbtW/yGEfjWGDRBC7LjrGGk6vvj2TMLbI13b6I8I/LMgINmwFn6moO67xLNegwQl1gG2QlnbWgFwasPfc+eotiwQfIJUDp1Gof33w/BlkycODHSpUsnwAD4uSvfgG4oVmF4R48GunUTo5nY/hg6TspjwPDO/PQPNN3WQvw2o8VOFOxSwlOE7qR1VwhENAYZBYh961+RdkQh6/c5fIjZaCr+VhC0ipX6XeC/MBehk+fkDHKI8fbDIExEewG3ShmFrkahsVqebNmAM2ectFieyzh1BsxF6LWK3MLyfalFHyYl7YcOD2StFOUOkiM57olULKLIKVHRk3fBWHfq5Hsu5pkBJ+pr7/JkewwQF1pdZxkgS5YswXHmdmhy82ZKTJnSzvimevVVKFgwhB6bdR9HjhzBORZQCISedkiZMqULzZ5tXbFKRDhtGtCmjVTkGuxF94VFQCjN+vWBxWXGod72zrLxI0ck9i4ADwyvbfNtz1FmNvAYeA0/xEUsBIria9aADEJ/cQlFQqgMkHchBUvP8+cY4+KlUZ80BW0wDp1wHHnF+HtgOEaih8V0FykC7N1rzwp4znXVGQhVA9LMD4gXT3R3f8EOKHJggvjshSC8Qix4Iwj7cjbH+gZ/CJJRPQXLUyfkqqvs6Zcrz4Cz9DVXngN7++YxQOydwSg831kb+s8//xT8KroEBZFjrydevpQF2HnyHMPnny8NNTofHx88fPgQ7loHYjUCMk9DkGm6Bc1nlTMiIJvKD0GFLX3lPND4Iri+h4gwCnd92E0pY1E/4jyyIAsuYidK4CyyoQX+EOhl8fECaTLFNVir3xWvLvlXWf+i5AZSIzVuYQMqYVrC7lj8TKZkNfaej7mvZX2MknfBCHPKRnPDi5gNEKbr5SoYD7EC/bAzfSOUujpP8MHEfPYQDyGJVHcX7Y6EU0aICC6FLOlkdHcGb4kbTrGny54ZeOsMOEtfe5eXwWOAuNDqOmtDWzNAOA0LFnyB06dlHjHrQHr0kHUgZKEn+zwlTpw48Pf3h7tygVirAbk0egUydZM1LRMqr8Q3G2oIwBi+nNfkH4CqhwaK305uvoFc5WWaA3kYiYblKfJ13A2kUpAIw3v9OvDwIbAJFVABWwT87iVkEsW1F0i6hguiI+9SChbHkz078AasTiqRkGzwLD4fie6YAhm1LIGd2I0SFovh2ZuO25vR3bJypNDIYB0H5TrSgMDUa1EF1SCh+khKeAHSadIPv2Iw+okaNsIKs5ie4omARPdqeq7vjjPgLH3NHefG1j57DBBbZ8oJxzljQz948ADjFLapaUy7dxfDxo2VjG+7dRuJxIllFWuGDBmQOXNmsH6E4q4REPZdoWD9/LPE7Y/luwVbIIH+ZXFvI2MORqIbumG0+DsRniBfqUTGy5sv8h07nLAx/qOXUAZI7tzAiTccg2PRCZ0w3mJG1qAqqmON+I5ZKC9fShK/SZIyw63FXAcyD43QCAvghziYhPbG3kyOO7iH5MZYiRz2xmfg1uP3dN76DKjooCIi5FHHkRu5cRJ7UUQYqZRC2I/9KCI+b60/CT0vtMOhN5m16tx3JVro2SueGXDmDDhDX3PmeKLjWh4DJDpmPYxrOnpD379/H1OnTjXgd83duHIlHWbMaGl8Xb/+IuTOfQoJEiVGk68aiZqP3377DS9evHBrLhASERJViR51SrPse/HnmWLi8//Zo743HgAAIABJREFUOw8wJ4r3j3+vc8DRO9KlSu8gXUVBEBBBaSoKqFQVC9h+dviDogiCFBvSpCjSRIpSRLpIF6T33jnu4Mr/+c6yuSSXu7RNsrl7hyfPhWR3duYzk933nbfM/4pMwvsntRSWLLNz98Fjl7Tdt+vUSMDmrWHqPQOjmaHojkeWiWZRxmmKIxesZzEZk9HbppNUEgdjlM1nGUWoso8D+Qhv4A0MU33djiqoih24hFzIAyaMSElZ16qVZqGTkjEJWMdHcU+PBg2ALA81RblTq3EQpVEGB1CpElBs9xIsQSsFgRn95qCTBUiZMsCBA2IByZgzRHrlawK+ltd83X4z1C8KiBlG4U4bfD2hqXycOnUqzR7fvh2GYcOGIilJE7IbNFiHBx9cajk+T548oAWFJZgtIEqZqANs3qx1rTJ2YAc0x+hB+Fxtdte8OfDHH8A0dEVXzEAsolW6U73IJoS+/+HYB6GrcbNa0dVb8ARmWPYH0T/LSG4lFBQPHtR6xr7OQFcb+NYr3voX4n7l+/kZyCvoGeLoKsqA8meeAQas6YROmIOriEFOXFXN64apmIoe6n0LrMAfaIGaNeliC6xapfVA5kogR1KuHawEfC2vBSsXd9otCog7tHx8rC8ntP3eH9ZdOZ8YjeiQBGQLvY1Jk57FiRN3qa+LFTuKZ5/9FnmKl0Pc+ePK8qGXYI0B0R+41atrGwcPGwb88fVBDPpC29COftLbWr+BRYu0OI8+i9up1JXXo/Ph09fPqQwyQ4dK/IePfwoWwYjjZF2iEIezKIAcSNngojBO4jS02By9ZCShiha7smW1npVHyn4Pel8n41n0xmRL3xkzs2OHP0ZIrhEoAtbKOZUJ7veysHhfPHxU8zvMGnITN5OzqOxon+BV9dnvY3bh018rKcsYNyiMi6NrLWCXjyRQXZLrCoGgIuBLeS2oQHjRWFFAvIBn9Km+nNALFy7Eli1bUprMHQaTk3ElKQo5Q+Mtn//660PYsEHzGQ4LS8DQocMQHp6k/q9nwOL7YLaApMqEdfYscCelMF1cKs/7CO3aAfPmAdk7aEHPKFECOHxYceDnVEQy0iq70XPZqPqyZtViOrT5CCQmAr8VegotT09Rn/2XvTrKXd9qc7mMuAHflCnAU08BTEV8GbkQgzuRxwCexPeW/VCyZdOyRYtroFEz0Jz16O6JjPVhljQqnROLvIsGS99TDS6GoziOYhiJV/AKPlWfvfL0edxVLS++/hrQs7BzTn33nTn7KK0SAmYm4Et5zcz9NrJtooAYSdPLunw5oSdPnowTTCV0p0RnzYaLN+KV5eN0YnaEJCehYHgsdu6sgjlzHrUc92yvSShZMR7Vy5VEnTp1MGXKlKCPAUm1F8iNG1A5KwGMxkA03zZaparkXh+x1eqjPjYAjIS+89SWPUC8nOhunJ43r7YjPQsDzJmWNt/VA1gV2RLRSdfxSMJP2JnjXsTHQ71YMuoGfCtWAI88AkyM7YZumG6hWAKHcRQlUKUK8NNPony4Mb2C9lBrC4i+oWBffIkv0V/1qSa2YCtqYgp6oAem4hYikAVxSEao+p6KPQ3aGWHDzqAdRGl4UBPwpbwW1GDcaLwoIG7A8vWhvpzQ9goI+3Ihx924fek0CoWlrKZeupQTo0en7HL+0ENLUL/+hlRdz1AWEG6CwuV1AHRnyT9vsrKAfPYZcP/LVVAFO3G8aF1cXLxBdkH39Y/Arn59rwL7y3KDNRZdoLL+PqNvwPf7R+vQ7K17EYpk/JblEXzzyC94801Y9nfw8xDJ5QJAwDo5gZ7N6oW8szDuwuOqNa3wK5bgISzFA3gAy3EMd6FR8WOIitK2M9ItJxklW1wAhkAumckJ+FJeyyxoRQEx0Uj7ckKncsG60+/YLPlxLTIPKkRcwKUL5+mVhU8+GYwbNzSLwN2V9uCx/rtRKuyCTQB7tWrV0L69tndGsBVHe4GAviuxsZiBJzCh6QxQJ1mzBjiIUiiFw1iBFsoVi6l3Q0O1AM6MFGdg1jHkqr7uLkLuHJeSJbX9MSh4cRV340aAXnR6yRRC1Z9/armJu3eHmrtSMh2BokWBkye1btPlruj+lViJ5ur/PTBFBZ8zUxoXUDahNupik7p/8XezcKF2XkbJFpfpBl86HHACvpTXAt45PzVAFBA/gXblMr6c0OkFodu3bcaMx7F3bwX1ca5cl/Dii1+o99wLJCYmBrt27ULOnDnxIn2ZgrToe4EwhSV3ES5zb0Fkv3EWS6Pa4sH4+ZZenQ8rgLyJ53CqTlv0yj/fktpUsmD5Z+Dt98HQXUfSu7oohv4ZG7lKYAl06cLNY1Pa0KnSLszaXVl9wODzURiMs8iP/DiPhXgYPXItxOXL2vEZbcPOwI6EXD0zEvClvJZZeIoCYqKR9vWEHjduHM5xe28nZc2ae7FihbYxH0vfIV+h1b13qRiQFStW4D/a8MHN3p5Xe4MEY2FmIbrq6PEF3E27NA7hdzTHffhddYnxBjdCsiHiViyONe6C52OmiwLi58G23wfD2eW594G+aaGzY+V7IRDMBOyV83w4h3MooLo0HK/jbXyAeEQpVz37TGkZbcPOYB5HaXtwEvC1vBacVNxrtSgg7vHy6dG+ntDp7YJu3bGDB0tiypSnLB916TId5ctrSgeLng0rmONAqEPR8qErILqrwgbU1YLO1bZuSUiCFhsyCb3QB5PEBcunvwDHlVvv2ZLe5bmq+++/EoQdgCGSSwaAQLduwPQ7uQiYVvdWXCJuIRJhSMI36Im38CFOoqhq2Yd4E2/jQ/Ved2Xke3HBCsDAySUzBAFfy2sZApKTTogCYqJR9seEPnjwIKZOnYpkBnukUeLiIjF8+BDLzsoVm27Di103WGJAoqKiEB8fj2DeC8TaBYu7COdpXR93ndiAnbgHKz7fqYI1X3nhOq4jRlFaX28Qsk78XILQA/B7sbdWOWoCg2qXLAHuuy8ADZRLCoEAEGjWTItFu5NRXbXgBIqgCE7hN7TEG/gYW1BbfT4AX2AsBqRqpaQSD8DAySUzBAF/yGsZAlQ6nRAFxEQj7K8JTUvInDlz0t0V/csvX8C5c5o5v0yZ/ejRY5qKASldujRWrlypPg9WC4jDIPT77wdWrMAhlMS1bYeUotH9/tOYuuLOBndMM/ShtoIoaXj9/6OhEsLdnpkYwL5wZ+cffxTLh/9HRa4YSALWFhC9HX+hARpgPfagAt7ER/gJHdVX7TAP89EuVXMlXiqQIyjXDmYC/pLXgpmRs7aLAuKMkB+/9/eEPnPmDPbs2YO4uDhkyZIFERERWL58ObJmzYq//+6PmTOjVe+jssRhxoylaNignor5GDlyZFDvBZJqI0L1hG4HzJ+Pc8iHv+adU//95s0DeObjuxWD5S0+RoHPhooFxI+/B0eXovL388/ApUt0BdQ2hKSyKEUIZDYC1nuB6H2ficfxOGYhFtGYXeUDPLXjFfVVVWzDDtj+UJjQgVsgSRECQsB9Av6W19xvofnPEAXERGMU6AlNy8Yq2vQB7N7dBLNmaSkdWfr3H4N8+S4iT548oAWFJVgtIKk2ImRnunYFZsxQD+7WTWNVutcra7ZhG6qrvuouDJKG10Q/GGmKEMjEBBwlaBiBV/EqPlFUqIw8gR/V+xhctbiT6sjy5AEuXMjEAKXrQsALAoGW17xoumlOFQXENEMBBHpCL1myBBs2aAHYp04VwoQJz1no9B30D0oWXaYsH3oJ1hgQewsIH+QJPXuj1tbJqmuhSFQb3PUs/xe+2Xuv+mxr/6/x1sFnJAuWiX4v0hQhkNkJMPECF0v00h9jMAYD1X/PoAAK4izOI69KxWtfChXifT6zE5T+CwHPCARaXvOs1eY6SxQQE41HoCe0tQUkR468eO2155CQEKEI1a27Ea1b/4qwsDAkJiaqzypWrIjOnTubiKBrTdFXDps21R7ejCsYhZfwEj5XFWTHNdxAdjwaswxzr7VUn20aPBPv7nlcFBDXEMtRQkAI+IEA3RD1vT14uQewFEvxoM2VN4XURZOoDYiLs22Q7GXkhwGSS2RYAoGW1zICWFFATDSKgZ7Q3GCQwemMBylQoAD+97/7cOxYcUWoaNHj6N3761S0mBGLSgiD04OpWKd2bd0aGJXtLZSf/ZHqQoVcp7H3ckG0x8/4GY+qzx7GQizGw5KGN5gGWdoqBDI4ASoRW7akdLIAzuAMCtn0ejyeR1+MT0Vi9mzgsccyOCDpnhDwEYFAy2s+6pZfqxUFxK+4079YoCe0tQWELV2z9jGsWHaPanRYWAKGDh2O8HDN+mFfevToEVRKiL0CMiLPMNwz9Q3VrXaV92P+zjLogSmYAm0/lG+fXoVaLzWRIHQT/V6kKUIgsxOYNQt4/HFbCqdRULle6aUXJuFr9LI5KDISiI/P7PSk/0LAcwKBltc8b7l5zhQFxDxjYaoYEGI5dqIJvp6UEojeq9ck3HXXSYfEIiMjMXToUBPRTLspjlywGGT+BQapk5gxJlfjquhwahxe2t9Pq4jLjMz3Kml4g2KMpZFCILMQ4CaE1srEPLRDO8y3dL8KtmMnqtjgWL5c9szJLPND+ukbAqKAeM9VFBDvGRpWQ6An9MKFC7Flyxbkz58f4eHh2L37JkaP1oRyllatfkW9ehvT7G+nTp1QqVIlw3j4qiL7IHSmdj309jdoN/9ZdckfB/2FCj0bYOeTI9Bt++vqs39/2YsKj5RT7+fN09K/yiZevhohqVcICAFXCaxYAXAbI710xBzMQSf1362ojpr427KpLD977TXg//7P1drlOCEgBBwRCLS8lhFGRRQQE41ioCe0tQJy7do13LwZh5EjX0FsbDZFqWrVbXj00XlpEitcuDD69OljIqKOm+IwDS93snviCXVCh+zLMO/6/XgP7+AdfKA+K4yTKNu4ML75Bhg0CCoYXTbxMv1QSwOFQKYgMHKkplhoJRkD8QWqYjs+wps4hJT4PFE+MsV0kE76gUCg5TU/dNHnlxAFxOeIXb9AoCe0dRpevdXTpnXBf/9pK/958lzAwIFj0+wQA9KHDBnieocDdKSjjQgPjlmI0gPbqhYx+HzX3e3xba6X0GizlhnrsZZXMXdpDLJnB65fhwpGX706QB2QywoBISAE7AjQEtK2LXDzZmo0UVHAokXidiWTRggYRSDQ8ppR/QhkPaKABJK+3bUDPaHtg9DZvJUrm2DlypQ4kNde+z9kzWqXz/FOP0JCQvDOO++YiKjjpugxIMx+NXo08MwzQNiaP/AHWqgTumEqpqMbJof0xrPJ2t4g8+Ym4u3/hWLnTiAighs1Andrm6RLEQJCQAiYhsCcOcCXX2rpeXPlAvr1k2xXphkcaUiGIRBoeS0jgBQFxESjGOgJffr0aUyYMMGGyP79ZTB1anfLZ127TUW5sgfSpPb888+jYMGCJqLquClNmmj7f8TEANeuAb2qbcKkbXXVwau6TkDreX0wObYLumAmriMbYnBdfce8+5cuifuV6QdYGigEhIAQEAJCwEcEAi2v+ahbfq1WFBC/4k7/YmaY0CNHjrTZ7Tw2NgtGjNACsVkqNNmEJ1osTrMjTZs2RbNmzUxE1XFT9u8HGC9/+zZQuTLQ8q7d+HSJlnJ4UsVR6LPnJSwObYNWSYtwNrQgxr9zWgWeHzwoAeimH1xpoBAQAkJACAgBHxIwg7zmw+75pWpRQPyC2bWLmGFCjxs3DufOnbNp8Bdf9MfFi3nVZ2XL7kO3bjPS7FCVKlXw6KPa5n1mLroblm7RKI4jOIKSqslv430sqvE2fjzbDGVPrMJ+lME/s/erTbuYMataNS0Q/XMtPESKEBACQkAICAEhkIkImEFeC3bcooCYaATNMKEdKSBz53bAjh1VFamsWW/g1Vc/QUiIY3AlSpTA008/bSKqjptiHYheqhTw9gvn8ctf+dXB3xV8HT3PDMcm1EZtbLmTynKrCjzv0gXo21dS8Jp+gKWBQkAICAEhIAR8RMAM8pqPuua3akUB8Rtq5xcyw4SePHkyTpw4YdPYDRvq4tdfW1k+GzRoNHLnvuywQ8FiAbFPxbt9Yxyq1otWfRqD/ljSegxmbquAmBN7sQaN8GTJNTh8GOAOwrduSQyI89ksRwgBISAEhIAQyJgEzCCvBTtZUUBMNIJmmND6XiDWWI4fL4rJk3tZPnrssTmoXHmX5f9ZsmRBXJyWGatWrVpo06aNiag6bop9Kt5t/ySjco1whCEJP+fqiTKrvkHVVkWBkyfxKx7Cxnd/xd69wIwZQI4cwJUrpu+iNFAICAEhIASEgBDwAQEzyGs+6JZfqxQFxK+407+YGSa0o0xYCQlh+PjjoUhKClMdqF9/HR56aKnDztSuXRsPP/ywiag6booeA9K0KZCUpGXEuoIcyIFr+BGd8QR+xNXQnIhJuopZ6ISxjWepY8QCYvqhlQYKASEgBISAEPApATPIaz7toB8qFwXEIMjM/rR69Wp069YNU6dO9ahWs0zoSZMm4eTJkzZ9mDixF06eLKo+K1bsKJ599lvL9+Hh4UhISFD/r1atGtq3b+9R//19Up06wObN2lW5p8eq/UVQBKewOnsrNL2+CAnQLCLfoCeexTcSA+LvAZLrCQEhIASEgBAwIQGzyGsmRONyk0QBcRlV2gdOmTIFffv2xY0bNzKEAnLx4kW1H8gtBjvcKYsXt8LGjdo+GeHhtzF06HCEhiWhYIECOHv2LMLCwpCYmIicOXPiRQZYBEGxVkBKlgQWH66IivgXFyo0RNuoZfhrWzbVi/ERA5B/+heSBSsIxlSaKASEgBAQAkLA1wREAfGesCggXjK8fPkyypcvj5deeglDhw7NEAoIkVAJmTlzpiUl77ZtVfHzzx0stJ57bgIKFz6t/l+oUCFERUXhyJEj6v/BsBmhIxes9aiHetiIHaiM+7ACZ6FtqPgR3sBb+EgsIF7+VuR0ISAEhIAQEAIZgYAoIN6PoiggXjLs168fli1bhp07dyohPCO4YFkjOXPmDJgZ6/TpHBg7doDlqzZtFqJ27S029HLnzo1Lly4hGDYjtA9CHzkSqPZaS7TEMhxFMfSrtBILdpdR/XsDH2FO2Tfw338SA+Llz0VOFwJCQAgIASEQ9AREAfF+CEUB8YLhli1bULduXTBzVKtWrRASEpLhFBDimTdvHrZu3YYRI15DXJyWqrZIlf9Qre1qtCueAAaus1ABi4+PR7169fDQQw95Qdb3p+ppeBcsAEaM0ILQGWzeCXNUMHozrMRW1FQN6YsvETmoL86elSxYvh8ZuYIQEAJCQAgIAXMTEAXE+/ERBcRDhklJSahfvz4KFy6MX375RdXijgJy6tQp8GVd9uzZg+7du4OKTc2amvBrhrJy5UqsWrUKU6d2xf79ZVWTcuW6hBdf/EK9L168OEqXLg0exxJMFpCcObWUuo0aAU/92Qu98DWSEIKO2Zfi5+sPqP50xTSsLd4VR4+KBcQM81HaIASEgBAQAkIgkAREAfGefqZXQG7fvo0DBw64RDJr1qxK2Gb56quvVNzH7t27UYpbabupgLz77rt47733HF7XbArIrl27MGfOHGzY0Ay//trU0uYeAyfgwUYFcH+ThihYsCBGjhyJ2NhYdOrUCZUqVXKJaaAO0mNAtLEEqAvGvDcYgzFKNaknvsG3eEa9b41F+BWt1f4fL7+s7YLO1//+F6jWy3WFgBAQAkJACAiBQBEQBcR78pleATl8+LBFgXCGkyv7XOU/d+6cCjzv378/3n//fctpGd0CcuxYUXz9dcqGhB06/Ixq1bar/ufJk0cFrrMEgwXEXgHZswfIOfo9vId3VR++KfY/PHNMUxAbYi3iazbE338DuXMDly4BgwYBn3/ubMbI90JACAgBISAEhEBGIyAKiPcjmukVkJs3byr3IlcKhWzGfAwYMADTp09Xykh0tBYTwVK2bFm0a9cOn3zyCfLly4dcuXK5Uq3lGLNO6CVLlmDDhg1ITAzF8OGv4/btSNXmQtX+w3uv78aV4/uU5UMvwRADogeh06px9Sr3NgEePfY5PsdLqhuLCzyN1me/U+8rYjeeeLciChYEXnhB66VYQNya2nKwEBACQkAICIEMQ8Cs8lowAc70Cogng8WN9vS4j7TOpzvSK6+84lb1Zp3QegwIOzNz5tP4998Sql958lzAwIFj1Xs9AxbfB4MFRA9CnzABePVVTQl5Gt9a3K7+QDM0hxbTUhgn8figwsriUaAAcO4cMHs21L4gUoSAEBACQkAICIHMRcCs8lowjYIoIB6M1rp163DixIlUZzL2oXHjxhg4cCCqVq2KcuXKuVW7WSe0HgPCGJjbt1/Fm2+mdOvVd75Fkzr5UadOHXBDxmCJAdEtIHoQOkN7ah79GT/jUdW5wyiBktD2NYlGLAoUj8azz6bEfYgFxK2pLQcLASEgBISAEMgwBMwqrwUTYFFADBwtd2JAHF3WrBPa2gKSN+8jGDCghqX5HTvORZUqO226EwwWEPsYkHXrgP3f/4k/0dimL/GIRBbEMcWA+lxXWCQGxMAfjlQlBISAEBACQiCICJhVXgsihBAFxMDRyqgKiB4DEhkZidjYBAwfPgQJCRGKXNV7D6Hfk8tsUgpXq1YNdFMzc7FXQD7+GMhydC/2ooJNs0+jIApD2+eEpUwZgEnTxAJi5tGVtgkBISAEhIAQ8B0BUUC8ZysKiPcMDavBrBNat4Doma6mTOmOgwe1XcJz5ryMF18cjcKFCyFv3rygu1bOnDnxIoMsTFzsg9DZ1Ny4iIvIa9PqXaiEytiF55+H2gdk8WLtayowVauauIPSNCEgBISAEBACQsAnBMwqr/mksz6qVBQQH4H1pFqzTmjudD6B0doASpQogUWLymPOnAaWLvbrNxb5819AlixZEBdHdyXg+eefV3uDmLVYB6Ezs1VSEp2sknALkQhHoqXZy3EfHsByFXzeogWD8LnxInBECw+RIgSEgBAQAkJACGQyAmaV14JpGEQBMdFomXlCf/bZZ7h69SrCw8Nx8mRujBvX10JuyJAzKFZsrtofhW5oycnJps+EpVtAuF/i7t1aVyIigKO3C6EQzlj69mv+Hmh9borNLHnqKeA7LUOvFCEgBISAEBACQiCTETCzvBYsQyEKiIlGyswTet68edhGvyMA+fMXwOtvPY3rl7Q9UKpWPYlHH52EiIgIcGd5FrPvBWIdA1KiRIpFYzuqoApSgur/D69hCP7PZpZI/IeJfjTSFCEgBISAEBACfiZgZnnNzyg8vpwoIB6jM/5EM0/ohQsXYsuWLRYlY/78tvj775oKQnj4bYwa9T26dXsUc+bMUQHptWrVQps2bYyHZGCNVDwY1xEeDiQkaH+X4X40S1hhucqL+AyjocWzcM/JmzdlDxADh0CqEgJCQAgIASEQdATMLK8FC0xRQEw0Umae0LoCkj9/fuWGtXx5Lsye3dlCr1u3aahV66yygHB3+UqVKoH7opi5PP008P33ti2ciN7ojcmWDx/HTMzC4zYHiQXEzKMqbRMCQkAICAEh4FsCZpbXfNtz42oXBcQ4ll7XZOYJrafitXQyuhTeHdIdSA5VH9WqtQVt2y60YVC8eHG0a9cOzJ5lxsLMVndi6y3NG4JhGIY3LP+vjU3Ygto2zZc9QMw4mtImISAEhIAQEAL+IWBmec0/BLy/iigg3jM0rAYzT2jrzQjZ4Wx5CuKzz1rh5KESqv/Zsl3H4MGjEBqabMODe4c899xzplRCHCkgD2ApluLBFD0LsYiDFusSFgYkJgLMmjVunGHDLhUJASEgBISAEBACQUTAzPJasGAUBcREI2XmCc39PRjfERUVpYjFx8dj06ZaWLQoJc7j6ae/RcmSR1MRNeu+IN26AdOn2zb3rnxx+Du+EvJfO4TFebqjw/UfcOuW7TFUXMaPN9HEkaYIASEgBISAEBACfiNgZnnNbxC8vJAoIF4CNPJ0M09oewtITM7cOHn8Nj799GVwBw2WevXWo1Wr3xwi6dKlC8qVK2ckLq/ratYMWLUqtXLRv8sF3Fi0EsO3tcLPv2VFaKi2T4hexAXLa/RSgRAQAkJACAiBoCVgZnktWKCKAmKikTLzhE4VA3KH29df98SxY8XV/3LkuIKXXvocIZo+YlO4SeHrr79uItqAIwuIfQMrVgROnACuXk35RoLQTTWM0hghIASEgBAQAn4lYGZ5za8gvLiYKCBewDP6VDNPaD0LVu7cuXH58mW12SDLunX18dtvKTETPXt+gxIljjlEY7bd0fXNCPXG1q4NnD2rpeZNr3APkapVjR59qU8ICAEhIASEgBAIBgJmlteCgR/bKAqIiUbKzBNaV0AYVH7LKijiypUYfPbZSxY3rBo1/ka7dgscUm3atCma0e/JJMV6M0K9SYzvuO8+YO5cYP164PDhlH1CeAz3Crmz16JJeiHNEAJCQAgIASEgBPxJwMzymj85eHMtUUC8oWfwuWae0Gm5YBHBDz90w4EDdysakZHxeOWVTxEZqe2Ibl2qVKmCRx991GBq3lWXPTtw40badRQqBJw+nfJ95crAjh3eXVPOFgJCQAgIASEgBIKXgJnltWChKgqIiUbKzBPaPgjdGtuOHZUxd25Hy0cdOvyMatW2pyJbokQJPM3d/0xUvvgCYFC5XiIjkSrrlXVzZ88GHnvMRB2QpggBISAEhIAQEAJ+JWBmec2vILy4mCggXsAz+lQzT+jTp09jgv2ufXcA3L4djk8+GYz4+CzqkxIlDqNnT7stxgFwY8KePXsajc3r+rJlA2JjnVdDa8m1a86PkyOEgBAQAkJACAiBjEvAzPJasFAXBcREI2X2Cf3RRx8hISHBIbEFCx7Gli0pO4Y///xXKFTojM2x3ENkyJAhJiKuNWXFCuCBB4A7cfUO28fMXsuWafEhUoSAEBACQkAICIHMS8Ds8lowjIwoICYD9W7nAAAgAElEQVQaJbNP6DFjxuDixYsOiZ05UwDjx79g+a569a1o335+qmPNlglLbyCVEIanWKfb1b/LkQP46SdRPkz0U5GmCAEhIASEgBAIGAGzy2sBA+PGhUUBcQOWrw81+4SePHkyTnBTjDTK99/3wKFDpdW3YWEJePHFzxETYxvhbbZMWPZdmTMH+PJL4PJlIFcuoF8/ifnw9byX+oWAEBACQkAIBBMBs8trwcBSFBATjZLZJ7SeijctZPv2lcX06V0tXzdqtAb33/+7zeH16tXDQw89ZCLq0hQhIASEgBAQAkJACLhOwOzymus9CdyRooAEjn2qK5t9QqcXiM7OJCXRetAPFy7kU32LiLiFl1/+EtHRKduI16pVC23atDERdWmKEBACQkAICAEhIARcJ2B2ec31ngTuSFFAAsc+6BQQNnjSpEk4efJkmtS2bauCn39O2eujXr31eOSR33H7zu59tWvXxsMPP2wi6tIUISAEhIAQEAJCQAi4TkAUENdZpXWkKCDeMzSshmCY0AxCZzpe693QrQEkJYVg/Pjnce5cAfUxY0GGDp2C8PBj6v/WmxHu2rULmzZtQnx8PJghq27duqhUqZJhPKUiISAEhIAQEAJCQAgYTSAY5DWj+2x0faKAGE3Ui/qCZUJTCZk5cybOnTvnsLe79pTH7B+fsHxXtuw+dO06A0xly80ImzRpglmzZinFw75ERETgiSeeQOnSWjC7Lwp3df/nn3+QmJiIsLAw1KhRAw8++KAvLiV1+pBAMCmwa9euVco2LYGc41S2GzZs6EM6UrUQEAJCQAj4ikCwyGu+6r8R9YoCYgRFg+oItgl95swZTJ8+HVfv5K4NDQ1FUlKS2k/j22+fxtGjJSxkOneehUqV9qBkyZI4fPiwU2Lt2rVD9erVnR7nzgF//vknVjDfbhrlvvvuQ6NGjdypUo4NAIGDBw8qBVh367Nugj8UWHe6TEV3/vz5SE5jkxlfzHN32ifHmp8AY+/+/fdfxMXFIUuWLKhYsSIKFixo/oZLC4VABiYQbPKaGYdCFBATjUowTmjrzFiRkZHKNetGciROn8mPaRN7IikpTBHOlu06XnjhK8TExKYpjNkPxYABA5AnTx5DRmjp0qVYt26d07oaNGiAli1bOj1ODggMAQr0v/zyi9OLm0Gw37p1q1I+nJXKlSvj2rVr4oroDFQm+56W5tmzZ4MKiH0pXrw4OMeNuj9mMrTSXSHgNYFglNe87rTBFYgCYjBQb6oLxgltn5qXK9D6yvSKFS2wZk1jC5LSpQ+ge/dpCA1NdglT7ty5MXDgQJeOTe+gCxcuYOzYsS7XY6/40H1m/fr1agWSVp677rpLKSmyCukyUo8PpJvVypUrceXKFaW4JiQkuFxXgQIFcP78eXVeeHg4mIHNn65277//vsvKtn2nzGbJcRm6HOgRAXsXvTJlyoDPg/QKF3yee+45UUI8Iu7ZSfIs8IxbRjwrGOU1s42DKCAmGpFgnNCMp9iwYYNDirdvh2PSpF44ezbFXaBx49W4774/XKZuxM7pI0eORGxsrMvXjImJwcsvv6ziRNJbbc+bNy+6du2apgDAlcvVq1fj+PHjyjUtR44cysVLD7S3jmEICQlRMSlUlviXig6Pf+CBBzJlYH56blYuD2QaB/rD1c6hxS08ConJIcgaGYL4mzdd6oYZLDnWDeWcZt+4ISnnNF2CaDVkPAvvBVu2bFFKIudz9uzZ1Z4/klgi7aF25qLnbJKQc3R0tMQVOQPl5ffePgu8vHxQnO7secdOZKR7RDDKa2abSKKAmGhEgnFCc3V61apVFopcabZepT53Li8mTuyD27cjLcc8/PBC1KmzBaFZc+LGjRuIDkl7VdvbfUPS2rskNikcsckRyBuVjJCEuFSzoGrVqti+fbvT2cGVaipJ1q4QzoL0yYjF1dV8BspT0bEPzM9IN3Nr0AcOHMDUqVOdsvfmAApuelwG+dapUwfVqlXDggULlMuLI6tJer741pYatstRfIqn7TWDRY5zetq0aeBfdwuV6W7duvk0sYS7bTLD8c5i0jxto9mUVk/74e55tE7wRUs1f99GLeC4Ok6OngXu9iEYj3fleUc3UypxaRVv7hG8L2/evNniqlioUCF1P/e1h0Iwymtmm1+igJhoRIJxQjvbnJB4t2+vjJ9+6mghHRKShLZtF6BmTdsbUlh4BBITbqcaEd7Yc+bMiebNm7u9mups93Yjhr9w4cLo06ePqooWDKYpNlIA1duoCxbOHohpKSxG9NUfdQwbNizNNM/212dsN7Or+brkypULly9fTnUZWstu3rzpkjJ5KzkUkSFJbjdVd0X0ZhXWkXDGh/T+/fsdWjOoUC1fvlwlmKAyllYQvTudyayCsSNG7rqF3g4JR1R0doTdvuHSvYXzkhYqCnbFihVTmQc5hulZZN0ZS18f644y4ex3wQWfLl26eKQAuztO1s8CXzMyQ/3k89VXX7l0/3Olve7cI6j4zJkzB6dOnXJYdZEiRdCxY0efuSgGo7zmyhj48xhRQPxJ28m1gnVCWwuM1ivL1t1ds6YRVqy4z4ZA8+a/o37jtYgKdV0oc/dhMmbMGKertiEhoQC8E7J0VzFnGzV6O92YGSy9lSTr+rnh4/Xr14Mqew4FXz5UUhWOUbLr88Rbzkafn4QQhCIZV5KikD0kHmFuKk1UKuma56zw9/HCCy9YHrrOhDNn9Rn9vZGJJYxum7v1eZOdatSoUSrxgBmKfk+lIEdrtr54olsG/Rk35Wy+UqGiQn7p0iWLUuyqcmxtnee+U1TK6DqouxUyO6OrdaU3bo7chq0Vep7L69Md1z4Vd3oujjzPmznni7k2fvx4nD171tCqXblHuLrQR85cHPRFsoZgldcMHSwvKxMFxEuARp4erBP6u+++w5EjR9JFwZXq3357EOvX17c5jnuEtGv3C8KyxiMiMhLhCcb6xn/wwQdqJdDXha5i3OWd1g+96MpYeGQWREaEI/bGdV83w2n9Zs+eM3HixDRXtJx2Tg5QBPiw5UPcmaUsELgYF1K/fn2sWbPGZh8ge4EwPVe4QLTb+ppceWVs2NGjR1M1hZbaJ598Ml2BxxWrcaD7aH99BrxzdZrxPGntv2PvhmhvtXa2b48Z56sn48D7Pq32TFZCXnSVTc/dllx5X3bm4pg1a1aHsYzO7um8PmULtoEKHF2U2rZtqxJ06Ak+2E93vQx8NY9dST7DpDJUQhwV+0VQX1mlglVe82RO++ocUUB8RdaDeoN1QjtTQJjzigu+VEJWrmyKVaua2dDJkuUmmjdfiVq1tiA83Pkqr36ys5USmvHpRmJd2Ba2IzQEiE8ORZQHLjGOhpYZl+jqwCBcsxdfZ8/xZpVu+PDhDjeodMY06c6YOjsukN/HJ4chKsT1+e1NW9u0aQO6H2a04o8EAukxo9BDK6ejTVStz3PUTj2DEuPejFhpD5axpSWFQqEjIVy3vlD4dSdTYbD03dV2puU54Or5vKdXqFABe/futWywyxgIR0qyszqpPDFmg4lAHG2cqt/faa1idkJflPSSz7CP3AcqvaLvSaYfY0QyG/vrBau85ovx8rROUUA8JeeD84J1Qs+dOxc7d+50SIRZf8JCbNPu/v13dSxe3BoJCRE258TEXEW9ehtRtep25MjhmnsCs0TZm7F54+QGia64rBg1jPS5ZjYao83RRrXPvh59ldzI+tNbGU4vY5i1v3dmEswcsQ8GRcrIOeNJXXRD5KqxP4q964w78TC6EuLMrUjvBxNjZA11Pc20P/rvr2voe0gZdT3avOlYK8VYArRg0q03rWLU/cs++Yx1+mNXk7dYK3XeJrNx1N9gldeMnRHe1SYKiHf8DD07WCe0fSYsV6CcOZMfc+d2tEnRm3JeMooXP4q77z6AEiUOo0iRk4iISH/lWA9ec/Vh70ob3TnG2xUsXouWGb6uXs2JS5dy4+bNaMTFZVGf0TIUFRWHnDmvIFeuy4iOjneneQ6PZWBmuXLlvK6HFbi6MmwdZOjqWHkavO1QwE+CYsrX7dsRSglmumj9b2JiGJKTaa9jlizWwL8p75lAISws0eErIiIBWbJwt+qbiIq65ZfgeEMGLwgr6dGjh8OgYgoq7sYxcEWXLl+MgaCCoccZMOmAPxcxgnAYMm2T/ZX8ItMCBtTvu0SJEvjjj7TT9vO3Gp6rEHafjVMxdllDbqNQWGoFqWjRoujVq5ehOINVXjMUgpeViQLiJUAjTw/WCZ2eL2h6N+rExBBs2lQHK1c2Q1xcdJooKfTlyXMR+fOfQ758F5Ajx1WbV9asNxBq0uWuC4lZ1KpmWqmG4+MjcPRoCRw8WBqHD5fAuXP5U1mGHIHJmfMy7rrrOEqUOILy5fchZ86r6U5Fe5M0D6bf/ZAhQwyZwun55NpfgEoIBT1Xdgl3p3EJCaG4eDEvLl3KhStXmLUqJ65cyYmrV3MgNjarUuj4Sk72/WThnKUyEh19U81VKo7a36vIleuSmsu08vkjg5c7DNM7lr/Xa9dy4Pr17HeUuCjEx2dBQoKWVlpT2IDQ0CSlgEVG8hWv3mfNGovs2a8jMjJ1ljtP2keF/5133rGcumjRIpWKM71i7xZFi92UKVN85kbiSb8CeQ7H79atSCQlhSqlOykpRG0ayzEMD/d9HF0g+y7XNpZAIBW0XLlz4/KlSzYdEgXE2PE1qjZRQIwiaUA9waqAsOveBHvHx0fi779rYv36ekpwdLdQ2MuW7QZiYq4pIScm5rr6mz37tTvvtc/5cmZJcffa7h6fmBiKEyeKKIWDr+PH70JSUpi71aQ6vlChU6hSZSeqVduG7NlvuFyfEb6xafnk0q2CgqIzf3lnjXX0MLt2Lbtid/p0IZw9m18pbhcu5PWLcuGsva5+T8GOighfBQqcQ8GCZ9TLnfFz9VruHBcbm0VZJk+fLogzZwoqrroi563yxj7zt8rfIhWy3LkvqVeePNpffkah11elYsWK6Ny5s7LYjRs3zi8JKtzti9HCG3NwxMZmA38z16/H4No1vvT32dX/qVTylZioKZP2JSwsAVFR8WrcNGX6mvqbN+8F5Mt3Ti0QBfre6oyzrmBdv55N9fXWrSgkJDC7HF/hd/5q92I+U6hIay9axZIQEXHrjmIdr5RrTcnm+9tBtZDgjFMwfx+VJQvi41Lv68UEMcwKaWQJZnnNSA7e1CUKiDf0DD43mCe0w52f3eTDB+WxY8Wwa1dl7N9fRq1mG13oHqMpKdeQO/dl5M17/s5D9IISgMLCjF3pY58ozB0+XBIHD5ZSf/ng81UJDU1EuXL7UK/eBpQsecTyYExEGMKQ2o3NCN/YESNGqL0wfFXIkIoG2VHp4Ituahm10KKnKyMFC55V76mk0MXLyEKBjNaiU6cK4/RpvjSFI5BsKehSqGWfCxRg38+iQIEzynJklLWIO7fv27cvzSw6RjL2RV20TNCFkNa82FjNqnfzZoqFTxewNUUjBjduZDNkkSO9vlBgp2tovnzn7V4XlPXLqLGzbwPnMBewqFDcuEElKluqv9p3mtJhH3dozPgkK+WMFk/Hf2kFpGtm2n+pyJjVim8MI+e18D7PDYtpheOY8jmpucemflFhtP087I7lLhR3330UZcvutrmgEQtt9j0IZnnN+Wj45whRQPzD2aWrBPuEfv/99w3N7sJVuqNHi+PMmQJqhZsvxkaktUrnEuR0DuJDlEqItqqnKSR8qNJlJleuK07dR3gDpfB29mwB1WYKykeOlEjXvUxvDq/NWBfGvvAhnjfvRWTLdl09tEJCktVKHYUMuhWdP59fWVGorPGhm1YpUuQE7r13LSpW/DfNVWVaKJilhi5aTBvZsmVLt3aQNTIVYwJjXe7sj8F+UgmllejQoVKq7+6W8PDbapWWL666Z816E9HRsXf+3lQrmhTqeRz/RkTcVrEd5M19YTShyfYvXVO0FdPUr1u3Iu64JlEgZJxJNG7cyKpcwHQLgqfWLt0N0V4xoSueM8GF85KuUxcu5FFK/fnzeZVCR8WDLlTBUCjAFSp0GoUKnVF/CxY8raxG7mTNM1s/deGZ1glrF8EUpUJXLqhopCgYVD60vILBUfib0+6p55WFS7dG6y55/P2FhyeoxR/+rjSrRLiK0SILre9MQcvfk65kaAoFFQvfKBX+ZqspMXxprovai/ck7T3vUfrntu+147Rj7N+Tq6+UP3V3VG57Eeo+Eh8fhbg4umVqrpm2/49SCoV2LP/qikbKe6MW5ho2/AstWy6zDCA3JOzdu7fhAxrs8prhQDyoUBQQD6D56pRgn9CuBhV7w483PD6IKNTpL819QHcr0FwJ+PJU2EurfbSeaEHG2koXC/2luRKjX9MdFxW6LpQufQilSx9UwfbuBpZTsDx5sij27i2P7durpOm+lifPBTRrtgqVK+90yb2FaRhZrDckYzCgtXKiZ64yyvLBcaUr1b//VsSePRXUirxrJdkSH0SBNH/+s0rYocLoy5VX19pmexTHi/OESoCuUJ87l08prOkpkuldi4IH+6nPSypPWtC8tkpO4Y0vT38LFB5piaAyriVA0GJZtN+CtqKrWWY0tykKOxQirVcxKXBQEdN/I/pfKmVcUPC0bbT2Uai1V0yyZfOdNS69sWCMjM5bVyrYb+0zrszr71P++moxxfn8TE7ltkqrMBV1cuU8ousRXUYpGGrCZBbluqUr07znSjE7gWSlxNi/qJjon/G99ttNcX3U7yOaQphibdASd2jKoaZoRJnO7bV+/fV46KHf7vQpBP3795eNCE06TUUBMdHABLsCQpT+UEJcGTIKe3RNsFVMUpQUKi8XL+bxWPBzpQ32xzDNcKlSmsJBxcPVVMOuXIv9paWAsTS7d1dy+FCgwsP9VipW3O101Tyta2bLRkHK9RgTZ22/ciUG27Zxd/dqLrnckSGD7++664T6W7jwKaeWKWdtMMP3FE5pNaMLFF9USvjy1+ouLSy6MJ9iZTmjYqh8uYJKd6KrV2OUInLpUh4Vb0IO7LunrmCcI7pSQmWUChM/49+oKNeC4NkuTYmKUgqEpjzoSkSKMsEVeL54THqJNPw1x6g8UCGlMmEdE6e912LidEXDW3fTW7fC1XidP59PWWVpWaNizfuqv+ZtWlzJgRYWPd5I+6vFHtGyzPdUomlB07La0QLDv3TBTba483CBiS8qYnQP0l2D9L/6HNFW/mn1TFHWdKWNf3muFN8QoAWNY6fH7NSs+Tfuu0/LnMUsj8z26IuSEeQ1X3Bxp05RQNyh5eNjM9KEnjx5Mk6cOOERMaODMNNrxM2bUeohqr3yKTcVPlD5EPX2oUH3GLpUMVMV4zEoDPlSmNP7Sb/+devqK2XEkSBA95VmzVaiQoW9PmtPevng6WJBq83WrdWxf//d6bqTcAVeV9hKlTqIPHkuezSngvEkCsGch/aKCQV1bwof2LRqUEinAscXYy2MjjHxpo08l79NTRHTlDI9RsWb3yUFTWsXF15Htxjxry5QenMNb/vN86kQMoMalQn+tX5proSaO6H+uf4Z++aPe0x6feRiCK0kmmLCeyr/5lVz2RvLNMeOioSuVFCJ0JUJ7a+mWPB9dHRcwDlYM6ICk+KSpCsqjv/SuqC7KDl6H+i56e78pjKou5ZZu5jZvtcD+m0D/TUrDd1kqSBqf61fVBjTm+9NmzZFs2a2Gx+72/60js9I8ppRTNytRxQQd4n58PiMNKGNjA3wIfI0q9ZcvRhzkUsF6l6+nFutgup7SPBhorkpaPtCpGT2uXYns9FZ5y5VIaFAsrFB79YdunEjGuvWNcCGDfUcKlOFC59E06arUa7cXo8tIu6MDQXIrVtrKHex9GI6aKmpUOFf9WJcjLMYB3fakBGO5eqrHmdEdy4tIFnzudYL5yYf8NmyMeaFK+JXVVwR3fG4Ah6sTHWljDEsnE/a30LK0mnWoisTWhySNh586WPDpAPaZymKBscu0IqEL3hSOaGlSI/fSHHpCVeueLo1gpYJCpp6zBb5UBjNiEzc5UyGXFhiPAUVFS1w2/F78rV9ae5T1q+UvY9SWqLthcT9p1IL/br7lhZwz5gV6wB8LY6Frpn6976OQ0mPny+Cz/XrZSR5zd05aNTxooAYRdKAejLahH7vvfdSUTFyUzkDkGe4KhxZj65fz4q1a+9Ve644sogwy1Djxn/innt2uRQj4g40xuvs2FEZ//xTHadOFUnzVArGTCFcqdIe5M9/3ukl6K1sVBgug/BlwzmnyB0ekCtXLly9elWls2UiAwZ8Muf+hg0bPKvQw7OY/UizkKQoJlx9dycmy9VLW6/Ea4qEpkDYKxT6/+nqE6wKn6tM5DghYOQ92QiaTAM/dOhQI6pyWEdGk9d8BiqdikUBCQT1NK6Z0Sb08OHDvd4DwkTD43VTXLlBZ8mSBffeey9WrFjh9fXsK2AA6Zo1jbBlSy2HmcSoBNSuvVkpAt4E8jIY98CBu1VcB12t0gq0ZQA1lZ4aNf5RrmpGrG6m5/plzyM8PFz5B3PHXb189NFHSEgwNt2t4QMZoAqZMY0bSHKONm7cGA0bNky3Jb/99hs2bdoUMOWOrn5MQ8sYE2YB419ai6zdW9gBPfiWf/X9HVIyEsUrNydNmaB7T6w6xoi5GqBhTHVZf7q8mqXP0o6MT8CX8R+kl9HktUDMCFFAAkE9kyggEydOxKlTp0xEOHVTkhGCkDsZfMzQ0AIFCuCFF15QTbEX4LhzebFixUD3NgaCUxj0pFy5kkMpInSHcqQccIW3fPm9Kn3v3XfvV/7UzgqDL7nPCRWO//4rqwJ20yrFih1VSgeVD27m5YtyMykcxQrmxvlz52yqp7WD6Ybr1q2LSpUqpbr0wYMH8cMPP/iiSYbUyd282e4xY8Z4XV+rVq0Uhz///DNdhZdWjh49ehiaSWb8+PE4e/as132QCoSAKwQSEIZwB/sgOTpXX5hYsmQJztndP1y5lhxjDgK+jP8QBcSYMRYFxBiOhtSS0TTqXbt2Yc6cOanYMJNSTEyMEqTdKdHR0WrPiuvXr7tzmmmP5YPOfrXd1Y0BV65ciVWrVjnsm6tWAFpE/vqrATZvrp1mwD3917kJHgOVuXGjlqZTy9fP8xkjQx98Zr9JzymKGXhoWaHiwT1WfFGojt1MikDW0LQzHbnC151MbiGhoUimU7YfSrt27VC9enV1JXfa6KhptGa88847Nl9R4d2yZYuyWPD7woULo02bNm7tC+MqhosXL4JKiFib0ieWPTtTigfufkcllW2gMH7t2jVXh9c0xyUhBKFuLDDZK9tnzpxRVjz9WZU7d27s3LnTNP0L1obQXZNum74svoz/EAXEmJETBcQYjobUktEUEEIZNmwYbt0yZpV7wIABahWWD4UFCxZ4lGWrZMmSOHz4sCHj5YtKXL1pGhnkzziNjRvrqKxZnqY+dcRCt6RUr/4PypQ5gLAwzyw2nnJ2pOC5ypcC8owZM3D+vPN4FE/bl9553IuFFi4q3fXr13fo7kRrzcyZMy37tbjTDlo0rF3P3DnXqGPJeMqUKbhy5YpRVQZdPfxFcJ4muuH2p28eys76UoGjkPj222+nYurMYmbkIOjWiLi4OGzcuFG59NISTEsxFQMjih675Kqy7c/+G9G/QNZRsGBBdQ+lssF7Ws2aNfHggw+Cv33eu3xlYfJ1/IcoIMbMKlFAvOTIH9HYsWOxfft2JTCUKVNGudA899xzbtecERUQo1xaGjRooDbCsy/urASzjpMnT+LIkSNuj40/TuCKc58+fVy+1IgRI2DURoC8KDMMcfdxumYxPa4n6R6Z4pVpc8uX36f2G8ma1bn7VlodTkwGwkLoo6/FHnhbKMy8+eabblVDZXfPnj2gAMQ2UAhyt8QnhiJK7S/gWsmfPz/69u3r2sEAdu/erdyo+DB3RSBN67fk8gUNPlBfUOBvUx/nrFm570as21cyaq64fWE/nqAvxPCSvP/Nnz/fkN+HfRfSU1Ldue9eTYpEljAgMjnthSgKp7Qu8H5GYTVnzpwqFs6Rm6R1O//66y/1m+SmqTzXnfuEu78z6+v6kjvncIsWLbBmzRqXFu/INwKJiA5N9OMsdH4puos2atQo3QP526cln/dYI4vuXmpknfZ1ZUR5zZe8HNUtCogXxF9++WWMHj0anTt3Bv0NefP777//VJDmxx9/7HbNGXVCO1updSY0OLuRsf7p06enG+yqu69MnToVBw4cUKsx+k7fbg+Uiye46grF6tgers7TwuNq2bt3r1pF8kVhAO/hwyVx5EhxnDpVWO3DwNSZ1lmFmN+du2PnyXMRRYtqGwNyv5PISNc2e/Om3Xnz5lWCyqVLl1yuxoiH0tKlS7Fu3TqXrhmfHIqoENcVD1bKlTsuXrgzD+wFo19++SXN9lm7cbnUiQAexH5Q0HOl0DWNfWMxatHDlevaH0Mhmqu8vkgiwWulNX7WgjjvJVwI27Fjh8f3OGf3XL3fvO7q1auVoOyO8K+ff8899+Cxxx7zBHWqc7iq7k5slLUi52kDrLm7ozBzjNq3b48//vhDZZEjO7p/cc8Ka6XL3cUFV/pBCxLvnXzu5siRwydWXnfvM0Y+y8j2jTfecAWFV8dkVHnNKyhuniwKiJvA9MMXLVqk/KMp+Bq102ZGn9C8maZ3w6UP+tatW5UiwViPGjVqKHOtq4X1L1u2TPkq69l6uIpmna3nu+++M8QCcjs5BBEh3q/Ks28Uprt27eqR0Enr24ULrsdUeJPxRs/hzxzxjANhrvdApBflg3rQoEFqWriatcoT60da884TF4yw8AgkJqSvmBUvXlwJmJ4qH9bttRdIGWzuLGuVq78zfx7nCmtHwo4r5/miH7pQa/QKOYWqJ554wm23OUf33IoVK6o0yXRnsi+OMsO5yskd5Vyv01WXSFfbQOWTi0zpKUMUvLt378Uu92QAACAASURBVO42S2dtcEfxddcF0pHLbZ68+XDm4hVEJLu24JPWHPLW3ZQubCx6BkdP7zPuPsvSGg932Tob17S+z+jymqdc3DlPFBB3aFkd26RJE+UisHnzZnWzY6AgA6u9KTKhvaHn2rlz5871OohQT6ebkAyEp7MZRVppd/kA5MOA2ZjoVkY/WU8LHx4TJkxwyVTv6TXMdp71yqWrD31fPJR0hZluT/b7iCRFxSA+7iaiQ9JO6cv7BVc7+eCmUOjNPDDbGBndHkcZ4XgPTk/YcXVuWLeVK//MMMf7uj6m/K26EsfmSBFy1zLBa9FFjm6ierxDWhnbvGVM5cQ6rsKI67z//vsuW0LcdTl1tb+8JzL5iaMMjIUKFUKnTp0MUfIdtceZtd9TRZLXcnWxxbpdjCFjvIwrY2vvbkqrRHrxWd4snDli521iCm+UZ1fnlvVxIq95Qs32HFFAPGBIZYM+qoz1yJcvH7744gvlCkLz+7PPPqvcr3ijcbfIhHaXmPvHp5c9yv3anJ/BjF8UaKyL0ekB03vgOm9hcB3hyDWED/1Zs2Y5XNGluwFdJH0dcO1o001rst5kPAuuETJfaylop5fFiWNTu3btdK2tnGNMSuAoxsYTodKZNdh8FF1rkauxIZ64nLrWgpSjrAVqfyv5vhjf9evXq9Ts7hRvLUxkyGseO3ZMuW3RM4Gp4L1dOEurD3yWTZs2TQWpOypcvONizaFDhyz3e8pi999/v9N4IXe4uXKsyGuuUEr/GFFAPGDImyzdg6h88EfJTCFczeYD6qeffkK3bt2UGTi9wtUZ+xUaBmLRNMxUmPQjlmI8AUembN1SEZsUjoTkUOQISztY0jp9YFxSKLKEuufjzx55+1BIi4p1yki+dyUg2b4uBmZSmfbkXONHy7ZGZ37FvljRdbVPI0eOtAmaZiyHo1Vz63gnX80DV9ssx7lPIJBzzP3WBuYMZ0qI0SvngellYK7KxU1XYxd9ZWHyR891xefEiRNKxkovG6A/2uPoGqKAeE8+0ysg/DEzKNmVwsws9NOmfzF3AmZhAJ7+nv/nCu3vv/8O7oGRXgaPd999F2mtmooC4spoeH7MBx984PMc5Gm1zjp+wfMeOD8zrT1YnJ1J94Rt27Zh3759zg5N93v7xAJcZaZQzpVP/oa4oqYHX3JVjZ/pWc644mbmB4+jjq9duxbLly9PkwnvHWTAPrPQ/YpJLKQIgYxKgO5nTNhAVzLeD4xwOc2orFztl6tuhd4ms3C1PZn5OFFAvB/9TK+AcE+IUqVKuUSSrjN04aGCQJM995SgKdC6MMi5Z8+eGDdunGVHa0eViwXEJeQ+OYiZyy5fvpyq7ptJYWozvejQBGVq5kPTkSWA5nwWpmZ1txiRecXVa7qraOl5/33hppYZVvvd8X/35zxwdb7IcUJACJifAJWQH3/8Mc24JMZ8PP744z6LczE/If+0UBQQ7zlnegWEucPT2lHaHi+z0zCYi248NG/Wq1cP9Mu0LvQ1ZrpPBoy5mwpOJrT3E9qVGozKhOXKtayPcTW1pbv1pnW8q6tl+vl6oLaRmxyybm/y7RvFwh/1OHM90dvg73ngj77LNYSAEPAvAT1FL7M+crGMsRlMzCDJLPwzDiKvec850ysgniLkj52FriTWZfLkyejduzcmTZqEXr16uVW9TGi3cHl8sL17kisWDR7jicVDb6Sz+AWPO+PkRFdTY9pvTucs44qjoGpHTclsrgDO0q8Gah74an5JvUJACAiBzEhA5DXvR10UEA8Zvv766+BO1AsWLFD7gbAwbSPTQtJFa//+/cpFy50iE9odWt4d6yyYzz6GgXu9zJs3z+nO44z7YfwCY4sY72CG/Recrcw7Eoo9ybhiPyJFihRBx44dM6UrQEbZh8O7X5mcLQSEgBDImAREXvN+XEUB8ZAhMwUxDoSxHNwUrWjRoioV6Jo1azBkyBAMGzbM7ZplQruNzOMT3HFP0l2ImBqQuzMfPXo01XWDIbOLu0Lxhx9+mO7u8vYQyICWIron8rchrgAeT085UQgIASEgBExMQOQ17wdHFBAvGFL5GDp0KBYvXqw27Ln77rvRv3//dIPP07ucTGgvBsODU51ZBlilIxeiQOaX96CbHp/ijpLG+CgGVksRAkJACAgBIZDRCYi85v0IiwLiPUPDapAJbRhKlyuiVYP7t5w/fz7VOUwNS/ckCteZtXiqpGVWXtJvISAEhIAQyPgERF7zfoxFAfGeoWE1yIQ2DKXbFWUWq4bbYAC1K60oaZ6Qk3OEgBAQAkIgIxIQec37URUFxHuGhtUgE9owlFKRDwiIkuYDqFKlEBACQkAIBB0Bkde8HzJRQLxnaFgNMqENQykVCQEhIASEgBAQAkLAJwREXvMeqygg3jM0rAaZ0IahlIqEgBAQAkJACAgBIeATAiKveY9VFBDvGRpWg0xow1BKRUJACAgBISAEhIAQ8AkBkde8xyoKiPcMDatBJrRhKKUiISAEhIAQEAJCQAj4hIDIa95jFQXEe4aG1SAT2jCUUpEQEAJCQAgIASEgBHxCQOQ177GKAuI9Q8NqkAltGEqpSAgIASEgBISAEBACPiEg8pr3WEUB8Z6hYTXIhDYMpVQkBISAEBACQkAICAGfEBB5zXusooB4z9CwGmRCG4ZSKhICQkAICAEhIASEgE8IiLzmPVZRQLxnaFgNMqENQykVCQEhIASEgBAQAkLAJwREXvMeqygg3jM0rAaZ0IahlIqEgBAQAkJACAgBIeATAiKveY9VFBDvGRpWg0xow1BKRUJACAgBISAEhIAQ8AkBkde8xyoKiPcMDatBJrRhKKUiISAEhIAQEAJCQAj4hIDIa95jFQXEe4aG1SAT2jCUUpEQEAJCQAgIASEgBHxCQOQ177GKAuI9Q8NqkAltGEqpSAgIASEgBISAEBACPiEg8pr3WEUB8Z6hYTXIhDYMpVQkBISAEBACQkAICAGfEBB5zXusooB4z9CwGmRCG4ZSKhICQkAICAEhIASEgE8IiLzmPVZRQLxnaFgNMqENQykVCQEhIASEgBAQAkLAJwREXvMeqygg3jM0rAaZ0IahlIqEgBAQAkJACAgBIeATAiKveY9VFBDvGRpWg0xow1BKRUJACAgBISAEhIAQ8AkBkde8xyoKiPcMDatBJrRhKKUiISAEhIAQEAJCQAj4hIDIa95jFQXEe4aG1SAT2jCUUpEQEAJCQAgIASEgBHxCQOQ177GKAuI9Q8NqMMOETk5ORr/F/bDm6BqMbTUWTUs2Nax/UpEQEAJCQAgIASEgBIKdgBnktWBnKAqIiUbQDBN66YGleHDqg4pK2Txlsbf/XoSEhJiIkjRFCAgBISAEhIAQEAKBI2AGeS1wvTfmyqKAGMPRkFrMMKEH/zYYo9aPsvTnwMADKJ27tCH9k0qEgBAQAkJACAgBIRDsBMwgrwU7Q1FATDSCZpjQtH7QCqKXhV0W4uFyD5uIkjRFCAgBISAEhIAQEAKBI2AGeS1wvTfmyqKAGMPRkFrMMKFLjy6NQ5cPWfrzyQOfYHDDwYb0TyoRAkJACAgBISAEhECwEzCDvBbsDEUBMdEIBnpC30q8heiPopGUnGSh0qtGL0x6ZJLl//zuctxl5M6SW2JDTDR3pClCQAgIASEgBISAfwgEWl7zTy99exVRQHzL163aAz2h957fiwpfVrBpc/OSzfH7U7+rz24n3kbjbxtjw4kNeLvJ23i/+ftu9U8OFgJCQAgIASEgBIRAsBMItLwW7PzYflFATDSKgZ7QKw6uwP0/3G9DpHze8vi3/7/qs0X7FqHNjDaW768OuYqYqBgTEZSmCAEhIASEgBAQAkLAtwQCLa/5tnf+qV0UEP9wdukqgZ7Q07ZPQ/efu6u25ozKiSvxV5A9MjuuDb2mPntt2WsY+ddIS1+W91iO+0rf51Lf5CAhIASEgBAQAkJACGQEAoGW1zICQ1FATDSKgZ7Qo9aNwuClWsB5i1It8PshzfXqypAryBGVAw9NfQi/HfjNQmxMqzHoX7e/iQi63pSEpAR1cHhouOsnyZFCQAgIASEgBIRApicQaHktIwyAKCAmGsVAT+jXl72OEX+NUEReafAKPln3iXq/u+9uVMxfERXGVsDeC3stxF6q/xJGPZiyZ4iJUKbblD3n9qD5981x7dY1LOiyQClbUoSAEBACZiSQnJyMf8//i7ty3CUur2YcIGlTpiQQaHktI0AXBcREoxjoCf3UvKcwZdsUhIWE4Zt234D/Z6GrFYX0rB9nRVxCnIXYI+UfwS9P/GIigq41pfPszpi9e7Y6uHaR2tjUe5PTE1cdXoWdZ3fi6epPI1tkNqfHywG+J8CMbJ+t+wwnrp3A/5r+Dzmz5PT9Rb24wt+n/saRy0fQtnxbsbx5wTGjnnrg4gGVWdB+41d9YahUrlL469m/UCh7oYyKQPolBIKGQKDltaABlU5DRQEx0SgGekLrLlaFsxfGtEenocUUzTLwffvv0bJMSxT+tLANrcoFKmPHCztMRNB5U5hqONfwXLiZcNNy8LlXzyFf1nxpnjx9x3R0+6mb+r5d+XaY98Q85xfK5EfsOrsLq46sQqdKnZA/W36vaOy/uB8/7flJ1VUqdylLXd9u/RbPzH9G/b9tubaY32W+V9fx5cmbT25Gvcn1VIrrl+u/jE8f/NSXl5O6g4zAgr0L0G5mO9Xqnx7/Ce0rtFfvL8ReQL6RKfcmKtrvNns3yHonzRUCGY9AoOW1jEBUFBATjWKgJ3T1r6pj25ltqF6oOn587EeUH1te0fm4xcdoVrIZGn7T0IZWtohsKkCdq3bBUjad2IS6k+vaNPf3J39H81LNHXaB7g9VxlfBrnO7LN8fGHgg1SplWv1PTErEH4f/QLm85VA8Z/FgweRVO7nKf8+4e3Dj9g1Uyl8JW5/bisiwSI/qvBp/FWXHlMXZG2fVyu/e/ntVPBJLi+9bKLZ64Vxk0gQzlsG/Dcao9Zq7Ii2MN9+8iYiwCPV/prdm7NWxq8fUb43ujs7KxZsXceraKcU3mH5/zvqVWb9v+HVDrDu+TnW/TpE62Nh7o3pPxeSRmY9YsDQs1hBrn1lr+T/vT/wXGhKaWdH5vd83bt3AhZsXMs393B3As3bNwtAVQ1EiZwlM7zg9lbXuWvw19FrQC2uPrlXxo0MaDXGnelMdG2h5zVQwPGyMKCAegvPFaYGe0LRwnL5+Gg/d/RBmd5qNmGFait1+dfrh3mL3outPXdX/K+ariD3n96j3l16/hFxZcnmM43zseXD/kfp31UdYaJjH9bh64hcbvsCgJYNsDh/90GgMrDfQYRUMxL9vim2mr2/bfatcsVwpvef3xuStk1VWse0vbM8UD603V7yJj//82ILn58d/tqzousLM+hi6BOqugPyc1rgnqz2pLAm0ZDGORy8rnlyRKp6HyQYo8AdaSKf1Y+MJTahk+ee5f1CtUDX1nm5kLy99Wb2novpvv3/Tbe+aI2vQenprXL91HR0qdMDcznNd6h+VYQqrknjB3VmY9vFUAOgCWCSmiMdKABXQbB9nw+2k2+pCVCYuv35ZxXt8vOZjvPn7m5YGcOx4z6WivfrIajw26zFER0Tjt+6/oUI+2z2cjOtlYGraemorft3/Kx4o/QDqFK3jUiP4/Dp06RDq3VXP4/FI70Lbz2xXCx9UQPrX6Y8xrce41K7McNDxq8fVomXs7VjV3c73dFYLmdbl6XlP4/tt31s+4ryld0UwlkDLa8HIzL7NooCYaBQDOaEpnER9GIXE5EQ8Ve0pfNf+O+T+v9xq13O6HdUrWg9v/P6GotW7Zm9M+lvbHZ0uWHTFYjlx9QR2nN2B+0rdZ1ndTQ8vV7W5Uk4lhAI9BXtfly5zu2Dmzpk2l2F/Jrad6PDS7We2xy97beNc+tTsgwltJzhtKh+G1m5rbzV+Cx+0+MDpeUYeQEE9hP/8aKWyT1bQo2oPTOkwxaNuDVg8AGM3jbWcq88T+svfPeZumzo/aP4B3mryluWzpQeWotPsTsq9bnHXxSifT7Po+bvQ7Y8Cpp55jdef3HYynq35rGpKnUl1QBctvax7dp1SyB0V1lF5XGWbZBB8yPNhn1755/Q/eGTGIzh57SQ+avERXm/0ulcYKHg7mlOcbzdv38wUcVLsa4cfO2D+3vlqgWZpj6XIGpHVba6MLaOV1broKc4d3a9WPb0KTUo0UffO3ed2q9PalGujEmpklMKg+5oTaipXWVpPGadXtWDVdLtHjg2+bqAU8+drPY/xbcYbjsM+E6T188/wixlcYVq/WaMu88GqD/DOyncs1fG5Q4t12bxl1WfnbpxD0VFFLYo2P2taoilWPr3S6yasO7ZOWcO7VumKkrlKel2fKxUEUl5zpX3BcIwoICYapUBOaCoDBT8pqGi8fu/rGH7/cPVQ5E29VuFa6jXxb01I/67dd3j6F80CQMGuVdlWynJCwZN7h3Sp3EWZX52VkWtH4rXlr1kOO/bSMZXpxZelxOclcPTKUdWfU9dPKYHs/tL3Y1mPZakue/DSQeX+Q0HjwTIPgv//7+J/qFm4Jrb02eK0mTRHPz7ncctxjYo3wpqeayz/pxD91h9vqZU6Cs8MPmWGrgOXDmhB/y4IM+M3jceU7VPwZNUn8UKdF2zaNHvXbDw570n14J73+DwUjrGN4XHaAScHcKWL1ivWr1uv7H3WWUXBbAVxavApj5QgezcrPlwODTqkYkI6zupo00I+fBi7xEKFutzYcmrMWDh+S7ov8bbLHp3PFdnSX5S2Obdv7b748uEvlftV9mHZQSVFL682fBUjHtCy0bHwwc25wOQHE7dMxHMLn7Opy9plx1EDKXhQydlyKmXOLuyyEA+XexiTtkzC+6vfBwOcf+jwA0rkKuG0j19t/gqvLH1FPejndJ5jWXnn3KVAzkx5vWr0Ukp6RnANYr9m7JyB1mVb2yiGVDz0uA1C+7Tlp3i5gWbJcqdYx5jp59EVb2jjoZZ7sHV9vM6jFR9FqdEp8VARoRHKMqInyKDrFq3UXFzJHZ3bneaY4lhadubumWtpy2OVHlNWeZY5u+fgrd/fUgsKXz/ytSV+r+vcrmqc9HJ40GGX5rOrHeYzjgI0nwd6ebvJ23i/+fsuVUG3yT8O/aGeH9axbPYn05LwyV+foEC2Amo+ZQnPYjmEbpecd3zmuurSy3a3ndEWfN6Mf3g8Hq+sPZO4UMAYOrbptXtf82juWre9/uT62HBig013hjYaio/v06zhn/71KV5Z9koqVt4+9/88+ieafNtEWXfzROfB0u5LUatILZfGxJuDAimvedNuM50rCoiJRiOQE3rHmR2o+pW2wjSq5Si81OAltJrWCkv2L1E3QsaFcEWZfvh0+bj3m3vVsRPbTETvWr3xf3/+H4asSPHnPPGy5paQXuGK7IJ9Kat2unuNr4aEFpq7PtMUnAF1ByiXGN4w6fbClRr7ortP8fNFXRcpq8+8f+cp9wfuAu/MqvDeyvfw7qqUgNHo8GhcHXpVucDwIcaYG1qMWHjj5GoQ6+eNlL79XAnX4x0cMeGDQ08UwO9XP70ajUs0VofGJ8SrvtK6pPf3i1ZfuIyWAvzyg8s1C1iFdjYPQVZy6eYlFVRNhazV3a0UH/JY/N9iPDz9YXUdKh5nbpxR7/VUzmk14Jut3yjh4blaz4HChl4KjCyAc7HnbE678NoFfL7+c3ywWrMmUcglT2tBnFnLmn3fzHIeV+OouOgCNi0Cv/73q1I+7d072HdaAt2NW6Eyu/LwSqU8WmcqoqtM0++a2vSBx9BlzNHqN5XjzX00i8iHqz/EO3+8g6jwKNCCNn7zeOXyExMZg6Ylm2LhvoXqOGuXLnvGbBPTTlsXKhy0hOhulfyOq/ire662KA10f5u2Yxpalm6phBOO738X/kOlcZUs1hwqn5t7b1bfcT5bx0qNuH8EXr33VZfnnP2BVGY5BnRF8nXhb+mFRS+ovjMDoG6BUnE24yqp3wF/t+yr7jpH5YPCoF7K5C6D/wb8l+Z9gYogx4/JGZjmXJ93Q5cPxfC1w226yEUcWqF1yxkVDl6LFrAnKj+BFiVboM/CPjbn6ItBv/z7C9r/qAWx857yx1N/WNrEe/jLv72sBLSvHv5KuW/5qzCDIt0NKYjz+ZLW84H3rCKfFrFZKacb5fGXj6umlvy8JOIT49V73bpKRT7/yPxqAUwv9vtUcdHi661fo03ZNqkWa1xhMHbjWAz4dYDNoZz/257f5vT0K3FXUHNiTbUgQoWCC1HMwGhfeFyNCTVw6PIh9dUz1Z/B1+2+Vu+5EEGrF++HfCbv6bdHPTf0wtiUCVsmqEU8JuzQn0/P/PIMvv1H8y7gQsbxl44rpfSj1R+pBTC9WFtzuCA5+e/JqFKgirKu2T/rOJbWipGK0fukkHp2ce6uPbZWLfRxjI+8eES5wVb4sgL2XdiH3Fly48vWX1ruPV889AUG1LPl6hSo1QFc5ONiHwvbRAVEfw66U4+7xwZSXnO3rWY9XhQQE41MICf0sgPL0HKq5os5/dHp6FKlC/os6GNxtWJQ2ZErR9SDmS4ftCSwvNPkHbzX/D2LsqLj1OtICy8fxnxg0JdWL1QK7IVkPlj44Hcm7LsyjFw5o0sOy4yOM9QqOtPxUjG48cYNm2swkJouPnzg1yhUQ1k8hiwfYtkn5eTLJ51aFHr83ANTt0+1aZouKNoHlzpqP4WUkS1Tdp63P4arzVRY9GL9sLIXerlaxhVBVzjy4cK6qXyyUFjmTd06RocrdK8uSxEudV/e91e9j/+t/J86j4qsHtvAB07fOn0dDtP64+uV6wQLH1T/9v8Xd+e5WwWe61Y5Kn10rWChe8oXG79QAhkTIdAdhb7ijEW6+NpF1Uf79vG8kQ+MxCsNXwHT4XK1jj73vB5jVJgal+WHbT+oGCEqIHQJpOBnXSjckQuVbq5k6oUPfwoH/I2w7XyY6w/oadunofvP3W3qKRpTVAlUnB+cJyx8MF+Ku6SEYCpZdK/RFX17cMyGRN9p/XtHvx39nL6L+irBl4Wr+FQS0yq0lFHhtG6XNTtanfi7sS4c26iwKBVcal2oPDNhQ1oZ5ihsUSCjQG9vKdEVLwpMMx+bqYQgVwrvKz9s/0EJJHmz5sUbjd5w6npHSx6FWl3RpWWHcThU+oatGWZxPeX19d8YlVRmp6JiYl3WP7texR9QsaTAyLmp/26sLaJ5o/MqNkwdTYWdY8I4MQqPVOLo1sp7lO6aRYvInD1z1NylolOjcA1lCbAuuuW68beNwVVhvVBposLB33Xxz4pb+qlbWazroILJRQXe562FW1fY8xhax95b9Z5SfLigRIZ6sXanpJK9odcGh3F/1nF6dP/VXWBp+aHy8tGajyx10vLDFXS6bFkvOPAA68x4HI9qX1WzWC+YPp5p5PVCK9SYjWNU1jEmh6DiybYzYx3vGbyncBGB91Xec3iubm05+8pZlemPiz5fbvpS1TG44WAbfvbWfiofG3ttTHU/tp9v/F1wLtKNyd6CYG9xe/LnJ9XcZ9GFej6/uIjD+4peGPPI+wWt+7S260W3yqpn3oQaag6z0OPhqepaSn4u9Dw7/1l898936l7CxUje56yteLRCU9HgPGDh4hSZ6ePzYr0X8dF9H6nnP397/I3QrdCTwt97kVFFlAcGiz9jSgIpr3nCyozniAJiolEJ5IS2Fjj0YF5rYVLHxNUN9WD5MEqtdvSs3lOtGBb7rBhoOtaL/jBMC6+1NUI/hg89rvqz8MZCVxNaHWh9octI0RxFvRotrvx9tv4zVQeFcT7o9MxE9ql4B/06SAm5LHoQ9dd/f20RslY+tVKtQLNQ+KRrDF0CeFO29MeBSVq38jy34DmLS9vj9zyOH3dpwXrFchRTK9y80XOVm65LjvYd4Wo7hQkKynqhwMB+8KFl/8DjMY6sEAz05Co6ha4OFTsogbzznM6WlXW97m8e+QY9a/S0XKvN9DZY9N8iy//1uBg9ZoaCI9ued0RepcRxRW5WJ22Vyr68tOQlfL7hc8vHHzb/EG82eRPWCQD4cBy3eZw6hivrjAvhCluDuxqo+CT9fH0cu//UXa3es1A45oopj+U+Cg/88ICy7uiFlpp9A/aB6X7rTqprYUoBmg9/3XXNuj38bl//fSiYXXNbtA+W54NZV16shQoqc6yHhVY0PqQ/Xael5H2/2fsWH2oKSBQm7IVMHsfFAK66sg1UeuhqQ+WLSrH9ijYFZbqN0BJFqxqFPrpKco7phUIW5zrHqW7Rump1lsIJ+eqFlggqGr0X9FYfcWWU33PFmWPNRQJmLKOiSMVZt/ylFahLAYaKEX38+fte0m2JhSVdRXh93l9Y8mfNrywLzvZ54fW52mvtukOhfn2v9ekGaFNopvXDutCy26tmr1QZ8Ng/zjEKvBTSWCjo6pZcCldUHnRljPOeCzYUYFv+0BLLDqa4ek5pPwU9qvVQv2NmQKOLJn//FGzJk+5FegIGxndw0UJ3g9XbSqsVhT0qTxTkqEBSMbJ2E9Jjo+wV4Xvy34OdfTUhk4WLGVyg4TygwMiNZp+r/Vwqt1jem6mEcvGIbo965jn7cfvswc/wYv0XVd2O0p/b31P0dpArLZS8/3H1nO6LVPSoeFEBsRameQ4Faj57Rv6lLdbwt8DjmU7+5OCT6jN7KxPnOX8LLJyLPX9JubfZTIQ79xsmvmA8H+ck79dUiPWFg1mPzUKnezqp+awr+vZuvZW+rGRJ3KLXT8Hc+nlBl6iSo0uqhRfrortk2seKcQGCAjeLvdWI7rz7B+zHX8f+QqNvG9nUx77TFavWRFs3JVpt6bnAhR0uQOmF941dfbUskJwj1t998sAnStmyfp6dHnxa/a51F8GOFTsqZY5KCgvrYp265YLWaV7XExdh3rN5r2BxtmBnP67e/j+Q8pq3bTfL+aKA7xreGQAAIABJREFUmGUkAARiQg8cOBCHDx/GlexXsLr8apsbRIPWDbD+wHqAXktNNFD06fyg2QfIVjWbWvGp0KACNk7YiBzDtdSouAHgF6gVoTGvj8Hjj6fEQOzduxevvqqtmjd5rAlePWTlnnEMCFsbptx53nnnHZzOcTol/eQ+IOfOnOoBPfrz0ShTpoxl1KZOnYpZszTB9vvvv0fu3Cn+zp+P/hyfTftMCV9PDX8KC/9bqGI+uPrc+1pvzF4+G7uu7QI6AH/3+VutKrL0G9gPE5ZNQGKuRFTsXlE9pCnUK6vCI02BOKBdi3aYN16zPqhV4d0/ATMApsns2qEr+vXrh3wj8qmH9D3Z7sGuSdoNvPWjrbFo2CLLrvKlk0rjnq33qNX91l1aY2D3gUqZUab+40D1fdVRLGcxvPXWW6hbNyV98FMjn8KUyVpgd5kuZXAgRFvJosD897K/MfjTwWoVD/TEuBMXO7XDVFxecxm//aY9tPqM7KNcNXQlJvLPSISdCsPNsJvAo5pbGB/4LIX+LIQ60XVQunRpjPpslFIsLKu/PwNRt6MwtPNQfJPzGyWY6spknup5lLtW9orZcfXnFLe1S5cu4amntFW1Tbk34XRpbQWLpWZUTRT9q6jKZrOz+E6gnOZeRnezhGMJyL85v1pdRmPg+fbPqxiUvov7AvuBRqcbKfeCPTX2YH/ofiUo8/tpM6YB26HGeGvdrYD1XpKbgBLnSijB5mr7q4BVRtPmR5sj+7nsyJEjB+IeibMRbpvubYoc13OgZMmSuNriqk12l0prK6FMljKoWbMmztY5axFMuOr8Ru83QNn65W4vY3up7UoZopVgeeflqN6yumJQ/8H62Jx/sxIGm5dsjjervIkn+zwJhADvDX4PvZ7QrA2j1o3C4O8GAyuh5kmeB/LgWsFroMJGt6lR00bhlQ80v+t+b/bD2CfHqtVxBjef3XgWZY6VURab6EejMeuI9jtiQPus72cB+6CU3xsdbgDWCerWAI1DG+MaruGfe/+xjBvfNNzTELlv5MZfV//CpRaXlELLeDIKVT8O+xGhN0IRdVcU9la1dXkssqgIahWqhRYtWuBQ+UMW5Z+/NfwE3FPgHrza61XLnOG1jhw5guf7Pa/mV4WWFbA6y2qL6wpOAbiToblSh0rYMWyHxcqyYsUKjB49WrX742Efo+MfHZUQrwp/ptuAHFlyYO6UuXhg3gMp/WMIzV4oC0en/3XCK39oXJnGu9OgTriw9wIQCUR0jrBxH+p4vCOun7yOpeeWIvlhTaliYQazmN9iMGXtFKAg8MLrLygFRE/2UXhxYZy6fAooCRz68ZCaJ0oBpPfRnfCI9h3aI6l6khIaackdUXcEBvT///bOBN6mqv3jP0IZkrGIXMJbRChJpYGIBpRUpsxlzJCilKhURMlMehtkTDS8JCUipKSM+csYhQrRZNb/81v7rnP3Pc6955x7zrlnuL/1+byfV/fsvfba3/3stZ9nrWdIdmfhBt2lwPWlrjeudQ1HNMTcCY7LHphRvTSMEc3V9YWfLcTtD93uxCIx6Z9jV5uWtCcJJbaXAHdtJkyYgImbJ5q4IbayO8qiwsEKJtHFFQ9dgadXOKvebBdtuAhVj1VF7ty50WNYj9SK8EIgz6E8aHVdK3Qa2MmMn7s/zLBYq0kt4E+g6uVV8d2s79B5bmfjWmQaRfQkcOvNt+KLi74w8ya/C78d+g2bJ2zGOTnPQa16tbCwgLPAQMX29OHTqHx7ZWe+4hSfnOV6Xed1OPTjIdRpWwcnT51Etmuz4ZrrrzHvHI2YJUuW4NjSY8Z4vO+h+zBjv5O8ZMbdM/DXur/Q8WnnHby///0Yee9IY6AY17BvORHDLFDNmzMP+0/sN4YF2yWbL8Hmbzeb9+naPtdiWbtlnl2Q+u3q45MVnwDnAi+88oL5DtAVi4bBjRtuxMwVMwGWVEoWSe48MFtam1ZtsHnvZqzJtQZw2RqLWizCg20exNYDW4FLgMq3Vva4/Da+sDE+GO4kV6nSoArWFnLcyLgA+Oy7z+Kj8cm7pNyYLpOSbKbe4HpY+Hby4k1tIOnSJGzvuR0VxlbAD8t/QL4N+UxK+zFjxqD95+3x2Y7PnOf2HYBNMHPzrmW7kC9fPsz+fjaazmoKrAAqHamE8kXLo+uwruCuFo1pch8wYADWrl2LPAXyYE/tPcbQpJcEDUB+Y1dsWIE1p9YYJt67Wh5BjNA/oqGvRehWotatDJCooT/zwtEQ6CpVqmDdunUodkkx7GvuKIH7H91v3BcKFCqAw78fNpMXmjvjZfaeNpe3Qc6cTg2DArUKYOHMhag+KdmflS64ziYDnnnmGTOB2PbVV1+hZk0nu0/rJ1tjcg5HgaaCtXj+YiA5Y9/cuXMx5tAYjwsQWKg8ebH9s+WfoVq1ap7ASvY/ePBg08/evXtRrFhKleCqt1XF2vnJ/rmu2l09r+6JLaO34KOPPjKTPfrArBzS9YTt4ooXY8emHUBxYOR7KSl6za7NhSWNkVWuZjls+XKL+agxW5hZrE3+9j744IMY8soQFHrR8c9td3E7vNHa8cG9+K6LsXzyck92rCb5m2DOw45LCz/unTp1MgoVt5WPbjxqjBq2pyc+jeknppvAQQYMDhw+EPvfceI7hs0ahkc3OsYc3YZ2vr8TTz/tDKb4U8WxNzu1MWeF6I/Zf+DVV51kAiVeKpFqJRxcoKIelhf4z5D/mBgFpgDl6j74/d8LVK1aFW99/JZxZ/A0LuD/CdSsXRMrb1xp/tyleheMu31ciotBNWDDxxuMIsm2b98+FC+eHBRP49apeWla9n3ZcXpCcqAnw0mugqk3Q9eSNUvXwIyT7T5g/CPjjQLNXQ1QQUwOKcr+QHacLnHa+IjTjaNp96YehRS9gWznZTO1FqiIb528FbBJqAYAzas0N8YmdwnOefccHN1wFIWLFMZfPf/y+J7z8nnfyou/d/yNyy+/HCc7nfRkJOJvZ488G8d+P4b69esjR+scZreIChzdExr8p4GRl+sbXY9NtTaZ1UuumE5rMA3nn3++c28M5UnO/kyF59JTlxr2bKNHj0b37t3Nv2mIFe9SHKfeTt4JYzKsik4XXJ2c9848LB7paOJT5k5By9udgppsfG/s+/npN5/ilrm3eHYdzPvG944ZlibfgbnbkxVXAKU+LoVdK3ehUKFCOHfAucbtjO2SwpfgvCnn4euvvkZS+ST82NL5u6dxXuD8wHj81jCKhk09C4bznAKatWyGuZfNNYol41T279+PPwc7qZb79u2LoUOHmn/z9/aT2mNWdycwGQ1otTn/rHJBFfQq2gvtmiavat8DvNk/xY2ECxVt2zpJNIZMHYLHtjixa1zxXzZtGVZNdm786hevxlf/JK+SM/FG57ZAcoxt47cb44NtH5gYFSqBV9a9EpuWbgLocfR46tvOPzU//tjyB8B6gs5jM407WPnG58OeXXuMkjdu5jhjRDJg2DROayeBHFVz4Pi3x02NJrPrwhqqDga07NQSlVpVMrUX2Cr8WwGbnnZSpCfdm4QfK/5oxnj4scNI6pGEX8cnr64zf0NlmDgQ7nL0fakvhj3i7CCU71Mex0oeS9kBY9mR5I2bd5a+g2aLm6XssNBL03nlcdmIy7DxcEq9JPDRbIRRNvt/1N9jWNE9a8mgJcCPwDkXnIMTXU+k2skFN54PAtVqVsO3X34Lt4sm6H11Arj7nruR876cKRkNaZS94Izj1vtvxfyy882/qZQWP1YcNao4izcFGhXAoSsct7k+1/TBnvV7MP0RZ5K9f9D9mDwwJVtfz2E9Mapvctwc10rKODEUXOF/dcyreOQRxwAt/URpPH7X4ynJIbi+42zk49ChQ5izfY6nYOoN39yApXOXAvx8PgHYnXS6IhWsUBDHtx1HtkLZ8PvPv5s4N7uTmHtCbhzZdwQoBdQdXNezg0s3rroV6+KPP/4AOLU6Hsam9arWC680dnaW816fF9MmTUtJmkDP5+QMwt37d8eYXE6mwR41emDSe5NwZFJyoV5uhFSBiRejK1qB+wvgyPTk3+g5WtZxZ+Y8au7ZWdvChg0bsO70upQYM8pPcvmagwcPmoVC3jPdw/6e+bdZHMqeMztOP+HM+9altG7duuCCQZ6iefBPNye9L+fRXb134aqqV+H7778HLgLQIUVvSSEQ2X9FQ1+L7B1lfu8yQDKfeZpXjIZA165d27zEOUrkwJ7Ge4xScPTJo2a1sNwl5bDt520As50m78hyhaR6serIVySf2QHJeUVOvD7mdc92dOnspbFz6E5zj4MHDMYT/VJy2K9evRq33ea4KNVoVwNzcztKDYMFHxr1EPA+jJvF1ClTcfc3dxtljzsKmxduxoEPk2NFWjurc/TB5Rb+pFGTMGKEY/GsX7/eo8DRv7xo3aI4scbJrY/kzRbeF+Mwhjw8BB9/8jEOnnUQ6OKMgYWR2EpWKYmft/1srrNzdUomFbo15CiWA//+/S+SrkjCzqU7nV0RBhjTABnuBET37tQb9/W+z1Pw8Nnqz+KZFs+YjEfn3nQuJg2ZhGazm5lrvXDZCxjRzRn/sGHD0Lo1bxDG9WLy7MnAezBBuEcbHsWJMsn3wgO48Pyp80Gc+9Fc1PnE0eAZxF10TVEMHuIYZR0mdsD7P79vdmKYHrnquqp4++23zbM7/NBhs6JONzrGMwzsMRCHNh7CeYXOw7b/22aMPM+W+2Tg3EPnmkm/yQtN0H2+w+qx6x7DkFZDgL+AElVL4Od6jmuPTU5QsIiTypnKTtOHmxrXFf73Y1UfwzPNnjEG1Z9X/GkUbmaqWrBtAfALUHBWQfx17C+cqHMCZWqXMatsHT7ogNdnv25WxE27E1j14irjomNWGNcCeRfnNdv9B5scBC50lPDO1TujyF1FcHQJl9MJCWh5XUtMaTIFJli95U3mXLYLB16I9d3Xm50F42v+HlDwp4LInT839rRx3Dk8bQpQ9I+iuPTSS7GszrIU5Z2xLBPPQuFThcH3a9NNm8D6AXQ1ojtfmYvKGHmpWLsivq/upFGlcdjvin64qNxFxlcfVzu7jrw3+rhv3bzV7A6wPf/88+jQwUnhy9ZieAtMH5RsqdKt3Z1tmDkOPobxtV+5aCWqV08JfH3llVfwwguO1rZq1Sr0Xtk7Jb5jIZB3Y17jirNy40rUm1bP+ItTTiosr4BPP/7UKBH/W/4/E/NDuR9cZzC6tugKvudkcsuzt2DA4gEeLtlezYZ/D/8LJAHVe1XHpIaTTLYys3jxMnWynKhRrwaWV3Y0lYl3TMSqravwWofXzH8/0OUBvDrsVXMO4yYWrFwAvJkMoTaQ95q8xvBlVqKvV3yNpvc0dZIwNASKXlHUBO1yYWX8m+PxVN+nzJiLdiiKjWdvNP9mTMbY0WMxfOhwp1MucBeEcU/c3mM7itxaBAeXHTTHFny8IA6cOGBW3+my1qptK0ybPQ3/5voX6AGTSIFuVCbl9zQg255s+Lfgv8j1YC5wAcS6CxWZWgT79+w3iuWyj5eZXQC7Wm4Wck4CF1x1AfYt3mdW5o0//6HfjfLIcQzoMwC129ZOiX/gmsQbzvO+q8tdeDePEydCd6/WI1ubHQSunB+/9ThOX3raU6uhTr86WDzWMVTfefcdNKrbyBjNdGeb9t9pgHXRp9ilxD0Di4Ac3+Uw8SsHHnR2gGwsExcD8u/Ij8LnFcZ/nvmPebfprsVd2lI1S+H0rtOGr+HsbpOAXH/mwm11bsN7771n3HGp4Bo31VeA/Nnzo/k9zVG/Z300eSc5RosGyCjH/apFuxYYl89x12TihgtPXIiudzvxZy26t8DXJb427pb81mXbnQ3Hpx03LKe9Pg333ZOyYz9nzhy0bN/SeR9p2CcBdLEb0WAExo8fjz79+5j5C+2BMmXLmN0KE/e1GDi68qh5Bgd/Oohun3UzMVXcJWr7U1t88P4HOHjyINALZqWfMW3MKjfq4VHAbqBkqZLY/f1uswPsyZ7HOPSDQK5SufDR3I9Q9+265n7G3DoGI1qMwK5fd+FE+RO4qBW1cRiXvrzIi7+H0SUB4GLcymkrcf7w842rJBgS8hrM+/38089j+Knh5hznZG7zwDyr07eexj//+cckqGDGrwZPNgDmOjJ09K6jZheNfbDoLBdxzltxnpl/uXuUVDbJuEcZd88lQM7VOY1s0BOiQAGndljLOS0xbcg0gNMgd1ldSeRYwHZw98FYunQpfsv5G+DKucCF0Ld6vYUVa1bgVLFTqNgrxU3MS5oi9p/R0NcidjNR6lgGSJTA+7psNAXa+ifb4FiOjx/684ac50wuyY2rfTQSen3cCyO/ctwY6OdtazXQX9V+XFe0X4FrLnKCi72bDWalAs2JxlZdZ3Atq67brD30I6Y7D9Ox0q/U3bjyzWA7ftiYzYqxAE/f9LQZH1ePei/obQ6nEkrlibUWWHCw1eVOQPAvf/2CYi85Oybu1KcM7KXvLAO36YPsbtaX12Zc8pUZhUGJdJewGYaYnYaByzamhMqJ9e1PK5idec29K897M+Rk/n23780WPSd6flTpbjToxkGeDzNX3JkBheOhSxV3t7i13ezdZuaDzo8iYzVsLIP3NWjI0d2Kblr0fWZAsD2XChbPLflyyVQ7A+yDefsZaOlZ5XLJEH+naw53IJhOkwHk/KDNbznf89wZ58EsVyw0aINJx3491mP4sA/GdtisYnmey2PGQPchZm2yPvi2noI7DoNKCt0vuNrMNnPDTAz+YrDJ2jXmtjEmXoCpV5n9iK1DtQ5m659yRqWFMmqzx7B/crABlvRbt8URbXrJQkMLGfcu3sf7zd43mY2o1Hg+3NyduGsKWl7eEqv3rE7ZTaSxkZyO1edLlPxHG3jNAGLG8ew+vNuTBcmeN+TmIX5rfzDonRW5GddBxZo7YDYTGI3nnYd2mvShwRQyZJA5WZIp/dKp/PA9JmubEME7mQLHzFVO8qNrVNWJzs6PjTfr/1l/vLDMMZw4B/S9tq+RNVaQd2fm4e9Dlg3x7A5wZ4Rjt+mI3TswnBOYhpjNu2gkV3/7X98f7mr2lusT1z9hDC82vrNDlw81MToMsiVP9uVulAG6sfp6tzm3clekwNACjpKY3LioMOGOCea/+L7YIGybZYwxaDzHXWeGTBiXwLgBtvKFypvgcjbu9jLrFncWmE1pV69dZh7kwoA7A5u9vneGQ/6dhh7nDhuXRTevL3Y5KcaZgMTOfTyOLjPcJeaulU2H7S6wyGfGOA66bnJOotskjU+68drGbxGzhzGug8+Zje9Q2VFljVstG79dnK8pV3znKMcsYkjZY4A5GzPhMRbGnf2Jf+f1HrwydVYx/p3PgfFuvDfGTjBWyaY19k6zzuMZE0PZtdej0ctvF1O+u9O3u2XeKPM0crgAcu6FJiOjjavxTkPOXZtBNw0y32UuiDE2hbFCLBpskodcepfpg8Hw7jbn3jlmbnDLMN8FuuDxne4xv4dnzDyPBhnlos8nfcwz4X8zloNJW9h4HmM4vttH3yqn8Rh+z9zfEi448V3lvMhxeyek4O+Xj788lcui7Y+pvCc1mgRmSGTgu7tRjpglztbZcr8jqQ6M4H9EU1+L4G1latcyQELAPXXqVOMOQYueSkC5cuVA95uOHTsie3aXI3mA14imQNOlhqu03h8g5te2HxZ3UJ87yxAneE4k9EH+sPmHjjsMYCbG9tXa+7x7ez0qzIy/YAwJlVVOoAzitClWbdYoKtfT1083yh2DeN01DdwX4IeQNT2YUpjKC5VNph30FcjNCdwqrkxtya1kd4VtX8W9bPA1PzL7++6HO1WvHQcV6VU/r/IEFDOAlivt3lmC0kr/y34oT1zlsgHL/BtX8/iBo7sFjUIaW9whYrMZUPgRYBEuqxgwEJH+09Yo5EeFHwhmIOHHlStby9qnZMzx9bColH7505fmw/rro7+ahAP86NtAzrqT66b4+ianQmRNAqsMMo2sfZ7u/qk0MtMKP5yM/aFynv+F/MaQ4G+2OJ/NJU+mNV5LiYNxj93WrGHGMv7dGsQ2KJ3KGXc1GLDd7apuPlNget87C6G5P7D8nTtvDBa3SjGfAY1omxGMCpcNRGVsAFOtUjlg43Vp4DBdLd1p3G1DlxT3tEGfDzJZvJjrn0qxt1IdyHTiTrhAxYyZxaxSk975dP+jsc7dmmAMjUDGlNYxnHdSufQBZrXV1ldgYoBVe1aZ+YWZzOzuG40YZqdLLzkFDScaAd7P0T0WzhGcZ2yKZu9sVWRHxck77TX7SG+Rhb/bd8dejztgt5e/3bhn2qxu/I2GFOcJNrsAYs+xxin/m4o4K0nTMORcYLOH0W3LpmTmcTZdsFX8bV80GjhvUb6sEUdDxtZjGlp3qHHx9G5uw4dzDrPi0ShnalV34zNh3AWNd86/DHSnW6h9b90G9bwf5plgc869ZQulxPUFI0vMHsbFLHJhkos7L3XSD9efUt+kjefODIOb+X2iAcxdLs5dXPCy/GmcMWudO2OXewyci2mcUU7cWQTdqWft8QwK5zOx30AWTmWQO5t7kYvGPGWDholtHCvPZ4yRbe7MjZwHGMDN+7DzHb+9THJg3x8ay5w7ef+28b3nQpHNJMjddb5znFft99mdYIPnUUbntphrsgKylpS78ftMXkypbLMcGuYZrLVEueX3ifFPzOzVYGoDIxdcMKO7G+MU+Zwp80wkQkOUcxPdB+031f2OBCM/oRwbTX0tlHHH0rkyQDL4NJ577jkTGEwf70aNGhmFcfbs2Vi8eDH69OmD4cOTt/GD6D+aAs10p5xQmZWD2Tlsc2cPsSuQ/I2uBcbv09WotHC1n/ELbGllpSArFl+jwcFMQcwYZJUMfoi5os9AWavweqfopPsQM5DY1RhvxG7llX7dL9d/Oc2nUG5UOaNwWWXWve3NFJ5cyXQ390oRVyyZupj1RNyNH3TW92AWI670H3niiJlQ3cozj/e3asMPJbeoubJNn1gqBmml0WVBQhOI7WpUmrgbw2dlVyQ/bPahUZjtFn4gtRoGLh7oCTplMTCbypirccNvGZ5qlZmXpzHxUcuUVK8MbKVSzRVhrjJyRcudqYjn2DS93gobf7MpnWkccqfHFhd8pf4r6Fmzp7njJjOb4L3/e8/sKlAOmYee7ixcRc9o81U4ix97rgRSgaQBxxVWrohSaeWKOo1Py5YfSLpY2J0UuwvhzlvPsfF50Ec/nAo/Da7RX402q8p0LcyogpdRdsGe585aRkWEipat//HWmrc8hU9tv2TF+hbcqfHXmKKT7xGVLCp5jPXi7iFlhP9PpdsmoLB98Xmu3bfW7EoxYw8bjRlmmLK7E1bZdqen9h4LlSsb00G5pGHA423qXXt8myptzIoum3fGJi4a2N26tO6VyrZVOqmkLW+/3GfmLe4SMyuYO+26u0/uEPiqJM05mwtRZMmYKquse2fDs/Ote2HGuGkm1zlh0PV1pZwaUuFqTHvL7FTu1XVfix4syvhqQyf+bcHWBSbzGd9d7hJTkc9Ic+9kcEGGaZj57nnXJGHfnBsalGOwktOYJIRZGWkc8fpcoPAuBEruzATJb0zLyi1NgDebcUdd87r5tzvdOXdomGmPRVhp5LDZhY/07o8G3A1v3mB2/rmzzLS4NIQYY0bdwGakYx829T6/31xM4c4aDVsu/N18cXLgWkZgJp/j3rVkhjF+67koxe8Kd7htxjLqBzaNf7iLTgYy/Gjqa4GMLx6OkQGSwafEYNGkpCR8/XVKLu/Tp0+brDfMKsXgs2BbtASaH1abVpfuJq81cnyu2ehDzUmWSuS797zr+RAu37X8jPR+XMmisshVN25/21UUrjzTB5ZpLVkLwmSietlJqWvT9Xb8sKMpEuVu1jjxxZETMz/u3AnhR5VGBwM03elFeR79jZkeN61GVy8WarPuVu4iXgz+tVVj7flu1y66GXGHiC4lnBypBNBVidviNBq4a8DUkVt7bDUfJWbFchfKstviwcqJr+OpLNlVefu75e92J+KKPV02XlzhVNp2r7ynNQ4agwwAZ6MyRkOCzQbub/x1IyqNr+Q53Qa2ptUfP7hMH2tThfKDx3SZXPFyr9zb87kyTMOU7YsfvzDVdBnwzBgCqwixRgvdX9zN1w5WMKzposdaMHallK41HAvrBNw29TbjOkaDh+Om/zR3D2m8W7c+Gmg0ULiix0ZFh6vWbvcT/p1JGBa1cVLzZtVGZYbzBBUeGpVc5bWNylHN/9b07Ijx7/5kzBdHXoOryKFUZ3fvBHgXukvr2dHw4TtDNy+uorN5G7c2Zoq/cbeXK9x2Z9BtzKcnH5y7eJ0uV3XxXMd7YcLuQJBFgSEFUrm+uFPTBiqH7npDdLOh+xB3HHytnHMH69Bjh4Iu8BnoWNzHuQui2r/bdLkZ6S+tc7hoR3dkzut0B7aGPhfnTPxPcqPBzAUrXzvxGRnPxG8movO8zuZUzoWbDzhZ5eyOL9Orc1eW8sZ50rqNpXctygSzkdFQdhtktV6vZYx1Nr47jIeyhhLvn+npuStm09Jn5H7c57gXAd1uquNuG2cMEBpE7vTznJd39nKMrcxs0dLXMvMeI30tGSAZJMzUgjfffDOYscnduCPCYOg9e7wCVgO4TrQEmj7jpV4pZUZoVzf8DZeF+jzBkskH2/oNLCpH/2IqEZz8bp6csirCrB2c6KzPPIPJOlzRwdTkYAE4dwv0A2/P4Yee7kB2tcb6kKZ3LybYe+1ks1Nx7MljRjl86vOnzCm+6ma4Cwhyu5tZotgYF0BfWVMfoFg1457A3Pxc8eLKF9u9s+717NrwY7zvkX3pVjr39wzcv1NJo+Fn4w/4m83Dz9/oBkRDiS5uXBmjSwp9heme5q84IQ1Ub5cRrnjxY8egXjYqZnTpoMLNzDNpuTPYMT/6yaMY/qWzS2hdrPhvb79qd3FS3AOqAAAgAElEQVTB9Hj48hN2u/EEw9J9LF0guAJHxZUGuF3h8+UXb1zfbh/n8eGnuxZ9/m3tDAYrc8WexeTcOfjDMc6M3l+8nMeFEMZ0cdWYCxlc7IhG48IHDU8qlJR1f+9OWmPkzhTdgGhkMO6DSp19l3gOXWSoRNKlyF/9k/Q4cLGBblKcj2goc06zPvpu91r2wYDmbjW6BY2V8W2ce2lcU3llM/FCI8uk6osr84wryozGXSrGB/Bbw8b3l/NVIG6I4Rift4cA5wLOi+FqlA1WVne3SCniNDIZI8pdCH8eBeG6P1874XYn0NvlN61aQ+EaS1r9REtfi/R9ZWb/MkAySPuOO+7A/PnzjatV48aNjQvWrFmz8MQTT5gc2F26pC5sFchloiXQ7jSHga4sundN7L3Zgn0sBsbAZyqpdHdwV+vmZMGPlPXd5FYv3VTcq+y2P8YvBOs6wl0I+uAzhScNBO/CbN7Pwb2iSXcdKjlUOvnBYupXb7cY92o/A9Hpm87G3YxpG6adUTjOPTkywJjuOfQntoGtgchFoMdYY8oe7979YeVvBurT8LHB/G63D3/XaPpO01RuU75iR+ga58/wsNfh+7J452IjI0w6YBU5unjYwEIeG+iH29cHme6AjKMItVHWOT63LHz101dmVd7d6J7FFbrqr1Y3O3NcRby34r0e9zXrJsB7p1sWjVW6bdGfOr1dulDHr/NjkwDdXRjXxh1TxgpFqnGxiNXE6V5rdxJ5LbdrG92X6H4VLgWdMp70SlJKZiVmDk4jviRS991lbhdMWO0E7zMWg7EomdVoAPH+ba0kugtyngtX45zEuEkbvM5+bRxjuK7h7oexYTRiK19QORLdn9HnG9+94UldzB+ZwXFha6f+iPeunrsocKYMLvki0dLXMvMeI30tGSAZJMw6Bvfffz8WLkypqHzOOedg0qRJaNXKybKUXmPNCv7P3TZt2mTOZRpLunJlVmNVWwbysbHiLl1XAmmlXyntqQHA462rjK8q3LY/BrKzNoN1AWLAIlfiuUrP4GYblMeMNWs6py5yFsiYgj3GvZXNgNK2H7Q1wZO+ssGwb66oMYuRd6OxRDczm7fd/u69i8Mta/6PgXzhbnTDYpwJ3eXop82gbtt8uTYFE7jHVc5bp6Yo8+74i3Dfh0nNmFw1l8Gu9cq6isGlcTFfO0AH+h4wq76RaFQA3H7eNKR+eeQXk7nHul8waJKZwxgLxN+5w0b3LTa6GdC3m9WMw6mYROJe1WdiEqCRwEyGjE+ju2C4lUt3nAIJcpeHGZcyq/157E+zQ83d7WfrPBs24yrQ8XM+plsx3/FAv6mB9s3jvJMVpJXJK5g+Y+VYfsOYPIKyyYUf7h4zGyYbUx83mtHIZHZ88IoHTYa4jO5EhnK/MkBCoeecm+UNkBMnTmDbNqeKtL+WJ08elCrluCqxknO/fv1w/PhxU9uC/UyePBmLFi3C9OnT0bRp03S7GzRokKdYnPeBmW2AMFi1x8c9zDDcFcH98XC7FDGYkwofJwJf/rfuqtpchaOfM4Nv/3r8L8/kYTNrUVljsPPdFR2jKJJt/pb5uG2aU5uEK2TcvaELlzvg3vv6XKHnSr1tXDVkEDF3eqwhZ39jBe/rk5z4icxo639ZbzJLMeWiO3uSO0iV4+DKO+MuvNMipjVGKisM/mMGHu5+MODQ3+5SRu+XHxgac9z9ottGoK3R9Eb43w9OJUIG4q7osCLQUzN0nDulpdvgcwfA0g2RQfM0smlsq4lAViHAODgqkUxB3bV6V4y9PXVq2KzCIVL36b2oxAxf7tipSF03s/ql+yB1CSaIcO/c8fr8HjE2zyaqyKwxua8jAyR06lneAGHAeJkyga3K3Hjjjfj8889x6tQp1KhRA2XLlsU777zjeQp8KWrVqmXS8u7evRuME0mrxdIOiDuAl6u4zA0fSGPAWuMZTvXwh2s+jJfqsyS2U6WYq8N2e5hBxnRPYTo9d6MrFmuA2EZ+TLHHTDXeWWkCGU9GjqGyzoBPNrrPMAaBzcZP+OqThQfpF2sbU/8ubbfUBJ4z+4i72bopGRlbOM/hsyg1opSJS2FrXqk5pt1tS4oHfiX64tOYDCWQN/CrBXck/eaZCYgfLu7khSsoMq1RkOngpYNNooZnaz/rqVtA44lxI+5mC9YFd0c6WgTimwCTCjAxCHe0o7FKHd/00h89d+rpWksDz13HJpHvOZbuTQZI6E8jyxsgR44cMVU7A2mFChUyhgdT7bIq8cyZM3HvvSyRmtJeeuklPPLII6aysLvqcCD9R0ugqSxRaXJXQQ9kvDQYGC9Bl6IHrnwgVXYTpmq1xfbo48xgdGaBcgdJ+0tDG8gYQj2Gvros6sTmzrjBYMm0Vt+902TaIGpTC2Z0OU+aWHdu/1DHGY7zmTWM2cboBsEdJqapTbTGOBRm14rU7kwgvHzFh6S3oxZInzpGBERABLwJ/PzHzyaWjG6c6aWDFrnwE4iWvhb+O4lej1neAMkIerpYtWjRAtOmTUPz5qlrYQwdOhSPPfYYvvzyS9SsmTpI1d+1oiXQzFLFLCa+Kn/7G3NavzNg7aH5D5kKqKxyyzSAd8640wRD2vZm4zfRpmqbjF4ibOcxHaU7PS47Zv0MdyVe98W8XcyYepUBnmzuoHZ3leSwDVYdxTyBg0cOmurx7haJpAMxD0IDFAEREIEEJRAtfS2RcMoAycDT/O6770yQeIMGDUwmLNtOnjxpdj3ogvXbb78hX758QfUeLYG2xfiYy5sFrCLV3FlX6MLzY68fY2IV3juYz18BO7reVBxbETsO7TB1Pr7v9r1n94e/sXAf26CbBkV1JT5Sz1H9+ifA3T5bJItHR6IGgf9R6AgREAEREIFIEIiWvhaJe4lWnzJAMkieaXjnzZsHxoU0adIEND6mTJkCGicDBw4Eg8yDbdEQaGbzyf1cbk8BvbfufCvYYQd8PK/VbHYzMPCbdTP61eoX8LmRPLD7R90xdlVKgOQ9Fe/BO/ekxPb4ujaLKS7esdjUhWDldjURcBNwF+/i3zd125ThassiKwIiIAIiEFsEoqGvxRaB0EcjAySDDI8dO4Zx48aZzFfbt2832bAqVqxo6n907NgxQ71GQ6AZyMaCWGwMpH3yhiczNPZgTmLK1FjyV2UlV1uXhPfx8i0vo/c1vYO5JR0rAqkIDFg0AIO/GGz+FmgxRSEUAREQARGIDwLR0Nfig0zgo5QBEjiriB8ZDYFmYHLD6Q3Nvc24ewbuq3RfxO8z1i7A6sosGnXi9AmTM57pDJMKJMXaMDWeOCLAGKirJl1l0jVHsmZKHCHRUEVABEQgYQhEQ19LGHjJNyIDJIaeaDQE+vkvnjfFmtiCqQESQ9jCMpRZG2eZqrkdq3VE88qpEwuE5QLqJMsROHz0sElJXSJ/iSx377phERABEUhkAtHQ1xKNpwyQGHqi0RDoK1+9Et/u/Ra5c+Q2xfRspeYYwqKhiIAIiIAIiIAIiEDMEIiGvhYzNx+mgcgACRPIcHSTmQLNAlG9FvTCtPVOMbobkm7AkraB1UMJx72qDxEQAREQAREQARGIRwKZqa/FI59AxiwDJBBKmXRMZgr0zA0zTUYq25656RkMuHFAJt2pLiMCIiACIiACIiAC8UkgM/W1+CTkf9QyQPwzyrQjMlOgWbWbwefztswzaWTXdFqDC/JdkGn3qguJgAiIgAiIgAiIQDwSyEx9LR75BDJmGSCBUMqkYzJboI+dPIYvf/oSFYtWxPl5z8+ku9RlREAEREAEREAERCB+CWS2vha/pNIeuQyQGHqqEugYehgaigiIgAiIgAiIgAj4ICB9LXSxkAESOsOw9SCBDhtKdSQCIiACIiACIiACESEgfS10rDJAQmcYth4k0GFDqY5EQAREQAREQAREICIEpK+FjlUGSOgMw9aDBDpsKNWRCIiACIiACIiACESEgPS10LHKAAmdYdh6kECHDaU6EgEREAEREAEREIGIEJC+FjpWGSChMwxbDxLosKFURyIgAiIgAiIgAiIQEQLS10LHKgMkdIZh60ECHTaU6kgEREAEREAEREAEIkJA+lroWGWAhM4wbD1IoMOGUh2JgAiIgAiIgAiIQEQISF8LHasMkNAZhq0HCXTYUKojERABERABERABEYgIAelroWOVARI6w7D1IIEOG0p1JAIiIAIiIAIiIAIRISB9LXSsMkBCZxi2HiTQYUOpjkRABERABERABEQgIgSkr4WOVQZI6AzD1oMEOmwo1ZEIiIAIiIAIiIAIRISA9LXQscoACZ1h2HqQQIcNpToSAREQAREQAREQgYgQkL4WOlYZIKEzDFsPEuiwoVRHIiACIiACIiACIhARAtLXQscqAyR0hmHrQQIdNpTqSAREQAREQAREQAQiQkD6WuhYZYCEzjBsPUigw4ZSHYmACIiACIiACIhARAhIXwsdqwyQ0BmGrQcJdNhQqiMREAEREAEREAERiAgB6WuhY5UBEjrDsPUggQ4bSnUkAiIgAiIgAiIgAhEhIH0tdKwyQEJnGLYeli9fjlq1amHKlCmoUKFC2PpVRyIgAiIgAiIgAiIgAuEhsGnTJrRq1QrLli3DddddF55Os1gvMkBi6IFPnTrVCLSaCIiACIiACIiACIhAbBPggnHLli1je5AxOjoZIDH0YPbv348FCxagdOnSyJ07d8Ajs5a4dk58IxOf9EVJfPy/amIkGfIvJWkfIfmR/IQiPzxXMhRbMnTkyBHs3LkT9evXR5EiRUJ9vFnyfBkgCfDY5YuY/kMUH/EJ9TWXDEmGQpEhyY/kJxT54bmSIclQqDIUa+fLAIm1J5KB8Whi0sSUAbHxnCL58U9PjPSO+ZeStI+Q/Eh+QpEfGSD+6ekd888o1o6QARJrTyQD49GLp49bBsRGBkgQ0PSO6R0LQlzOOFTyI/kJRX5kgPinp3fMP6NYO0IGSKw9kQyMRy+ePm4ZEBsZIEFA0zumdywIcZEBEiQsvV/+gYmR5iD/UhJfR8gAia/n5XO0e/fuxcSJE9GpUycUL148Ae4ovLcgPunzFB//8iZGkiH/UpL2EZIfyU8o8sNzJUOSoVBlKNbOlwESa09E4xEBERABERABERABERCBBCYgAySBH65uTQREQAREQAREQAREQARijYAMkFh7IhqPCIiACIiACIiACIiACCQwARkgCfxwdWsiIAIiIAIiIAIiIAIiEGsEZIDE2hPReERABERABERABERABEQggQnIAEngh6tbEwEREAEREAEREAEREIFYIyADJNaeSPJ4Tp06hWHDhuG1117D7t27cdFFF6Fjx4549NFHcdZZZ/kd9YYNG9C3b18sW7bMHFurVi28+OKLqFSpkt9zY/2Ab775BlOmTMGiRYuwY8cO5M2bF5dddhkef/xx1K1b1+/w27Zti7feesvncWRdsmRJv33E+gE7d+5EmTJlfA6zQ4cORq78tUSWofRkgFwGDx6MJ554Ik1EiSRDf/31F4YPH47Vq1eD79a+ffvQpk0bvPnmm2fcf6jzEjuMR7kKlFGocxP5xKNsBconHPNSPMpQoHxCnZfiVX6CeW+y6hzk73sdj7/LAInRp9a1a1eMHz8e7dq1w7XXXosVK1bgjTfeAP8+duzYdEe9ZcsWXHXVVShUqBAeeughc+yoUaNw6NAhfP311yhfvnyM3nVgw2ratCmWLFmCu+++G1dccQU4uZMNFZtx48ahS5cu6XZkJ3kaIdmzZ091bJMmTZAnT57ABhLDR9kPfePGjUFe7lauXDnUrFkzS8vQl19+iW3btp3BYOTIkUYJpzJO2UqrJZIMWVlhDaErr7wSc+fOTdMACWVeIst4nZsCZRTq3ORWIONpfgqUT6jzUrzKUKB8Qp2X4lV+gnlvsuocFMPqRoaHJgMkw+gid+L69etRpUoVYzxQIbKtZ8+eGD16NNauXYvKlSunOQC+zB9//DE2bdpkdk7YuLJfoUIF3HrrrZg1a1bkBp8JPS9fvhzVq1fH2Wef7bnakSNHULVqVfz222/49ddfkSNHDr/K44kTJ9I9LhNuJWKXsB88ruJzNT/Ylugy5IvHP//8g2LFiqF06dJYt25dQEZsIsjQsWPHsH//fpQoUQInT55Ezpw5fRogoc5LBBqvchUoo1DnJrcCGU+yFSifUOeleJWhQPmEOi/Fq/wE+t5k5Tko2G94PBwvAyQGnxKVxueffx7bt29P5UZDd6OLL74Y/fv3x3PPPedz5NwNKFy4MJo1a3aGmxHdKmbOnGmUjXz58sXgnYc2pD59+uDll1/Grl27PIaXrx7t6vXx48dBw4UsvHdCQhtJ9M92f+itK1Hu3LkDGlhWlaGpU6eiVatWxh2JspReS1QZSs8ACWVeIstEkav0GKUlM4HOTW4FMl7np/T4hDIvJYoMBSs/wcxLiSA/7nfI+73RHBTQJzxuDpIBEoOPqn79+maXg77Y3u2CCy5AtWrVzA6Hr8YtXLps0X2rc+fOqQ7h37h9yWP8ueDEIBa/Q2revDneffdd42rGuJC0mlUezz33XPz555+gYs6dIcbIlC1b1u914uEA+6GncUXFj42uV7169UK3bt3SvYWsKkO33HILFi9ejJ9++gl8zwIxQBJNhtJTjkKZl8gyUeQqWAWS9x7o3ORWIONVtgIxQDIyLyWKDAUrP8HMS4kgP+551/u90RwUD9pH4GOUARI4q0w7ku5VuXLlMn7o3o1+6dya51akrzZ79mzj5vDhhx+iYcOGqQ7h3xgTQCWd8ROJ1OhuRhesO+64A2SQXnvssccMQ/q7041r5cqVxrWNH3z6/yclJcU9Gu4CtW/fHnfeeae5nz179pjAc97fI488YhIcpNWyogz9/PPPKFWqlDFEGQPhryWqDKWnHIUyL5FnoshVsApkMHMTOcW7bKXHJ5R5KVFkKBj5CXZeSgT5sXOvr/dGc5C/L1N8/S4DJAafF1fhuQLLwHPvxt0Nxjhs3brV58jffvtttG7dGgsWLABXTtztk08+AVcQeAxdTRKlHT58GNdccw327t1rdo6oSAbbPv30U8Mrrew/wfYXi8cze0idOnVMZrQffvghzd2erChDQ4YMMVnUGB/lHbQf6LNMBBlKTzkKZV4iw0SRq2AUyHDMTWQXT7IVDB/eW6DzUqLIUDB8wjEvxZv8cLxpvTeagwL9GsXHcTJAYvA5hWLlJ8oqY6CPhTEcNKpWrVpl3NJuvPHGQE894zjuiNCI4W5Borb//e9/aNSoESZOnIgHH3zQ521mNRkihIoVKxqXRz5/d3KDYOUg3mVIOyD+n3igCmQ45yaOKl5kK1A+btKBzEs8PhHmpmD4hGteiif5Se+9CUU3ShT58T9Dxc8RMkBi8FmF4ueYKH7WgTwWBmlSmWY9kDlz5hj3q1AaU/DS/Yb9JmpjdidmWGMSAyYz8NWykgzx/mm81qhRI6AU1/7kIt5lSDEg/p4w0s0UZs8O99zEfuNFtoJRsC2vQOYlHpsIc1OgfMI5L8WL/Ph7b0LRjRJFfvzPUPFzhAyQGHxWVAxfeOGFiGTBmjFjBg4cOBD3WbA4idNVhitnzBLCrF+htssvvxy///67SVmcqI2GGuN/GA/CgoS+mr9sRYkiQ/beu3fvbmrrfPXVV8YQCaXFuwylpxyFMi+RaaLIlT8FMhJzE/nFi2z54+Pr/QpkXkoUGQqUTzjnpXiQn0DeG81BoXydYu9cGSCx90xMHAMzXaVVB2TNmjXmY8RAahZTO++888AiYrZRwWQMyP/93/95qnrbOiBcQfAXpB2DSFIN6fTp02jRooVJKfzqq6/igQce8DlkX3z+/vtvU/vD282GfdGI6dSpEyZMmBDrCPyO7+DBg6YQpbtxa/u6664zBRspN6wRk1VlyHLhituFF16I888/H99///0ZXLOaDKWnHAU6LxFiIstVeowCnZvSYpQI81N6fAKdlxJZhgIxQPzNS4kmP4G+N5qD/H764+oAGSAx+riYQpd++qyETqWRhXpY7dutINtUq96B05s3bzYruawH0qNHD3OHrITOnQ9WQr/kkkti9K4DG9bDDz+MESNGmHiPjh07nnFSvXr1TBC/Lz403m6//XaTHYoV4ZltjNv606ZNMwo5V8H9pWANbJTRPYruGiysx3TLJUuWNHEtrKzM2jLcXWOmHbasKkP26diVVwZ79uvX74yHllVkaMyYMSZ9NRWBgQMHmgUQyhAb3Ry54MEWyLyUqHIVCKNA56a0GMXz/BQIn0DnpUSUoUD4BDovJZr8BPPeZOU5KLpaRfivLgMk/EzD0iNXSViXgq4yrEtAJZLKdt++fT3Vu9NSHjkA+tTyWBoubLVq1cLQoUM9ikRYBhmlTm666SYsWbIkzauzlgOP8cWHgcYsbkT/WirlXKml4cGUxSxyVKRIkSjdVXgv+9///tcYHDRGuerIvPtM4dyzZ0+jUNqWVWXI3j/TUjPuhzuE3AnxbllFhlj9/ccff/QphFz4YO0ctkDmpfSUx3iemwJhFOjclBajeJ6fAuET6LyUiDIUCJ9A56VEk59g3pusPAeFV0uIfm8yQKL/DDQCERABERABERABERABEcgyBGSAZJlHrRsVAREQAREQAREQAREQgegTkAES/WegEYiACIiACIiACIiACIhAliEgAyTLPGrdqAiIgAiIgAiIgAiIgAhEn4AMkOg/A41ABERABERABERABERABLIMARkgWeZR60ZFQAREQAREQAREQAREIPoEZIBE/xloBCIgAiIgAiIgAiIgAiKQZQjIAMkyj1o3KgIiIAIiIAIiIAIiIALRJyADJPrPQCMQAREQAREQAREQAREQgSxDQAZIlnnUulEREAEREAEREAEREAERiD4BGSDRfwYagQiIgAiIgAiIgAiIgAhkGQIyQLLMo9aNioAIiIAIiIAIiIAIiED0CcgAif4z0AhEQAREQAREQAREQAREIMsQkAGSZR61blQEREAEYovAiRMncNZZZyF79uyxNTCNRgREQAREIKIEZIBEFK86FwEREAER8EVgyJAhGDRoEM4++2xMmDABzZs3FygREAEREIEsQkAGSBZ50LpNERABEYgVAuvXr0fNmjUxcuRI7N+/H88++yx27dqFwoULx8oQNQ4REAEREIEIEpABEkG46loEREAEROBMAjNnzsSsWbPw7rvvmh+vvPJKjBs3DldffbVwiYAIiIAIZAECMkCywEPWLYqACIhAZhNYunQp6tSpg40bN+KSSy5JdfmdO3eiQYMGmD9/Pn7//Xfcd999WLNmDfLmzZvquMmTJ6NHjx7Ytm2bdkcy+wHqeiIgAiIQQQIyQCIIV12LgAiIQFYlwN2M8uXLY8qUKT4RMAbk8ccfN7/NmDHDGCHe7dSpU8Z4adiwIUaMGJFVUeq+RUAERCDhCMgASbhHqhsSAREQgegSWLhwIerVq4eVK1em6VZ12223mV0P7oC0b98eY8eO9Tno4cOHY8CAAdi7dy8KFCgQ3RvT1UVABERABMJCQAZIWDCqExEQARHIOgSOHz9ubjZXrlw+b5q7Gd9++y22bNni8/dff/0VJUqUQO/evbFjxw58/vnn2LNnD3LmzHnG8bt370ZSUhJGjRqF7t27Zx3IulMREAERSGACMkAS+OHq1kRABEQgVAJvvvkm2rVrh3nz5mH58uVgXAaNhdWrV6Nq1apndM/aHtyp4DljxozxeXkaEz179jQ7IDRA7rrrLnz44YfG1cpXq1SpEooWLYrFixeHejs6XwREQAREIAYIyACJgYegIYiACIhArBKwBgiNAO5QtGzZEtmyZUPTpk1RqlSpM4ZNt6trrrkGPK9NmzY+b6tGjRr4559/sGHDBnA3pVixYsZli9mxfLUOHTpg+vTpOHz4sM9dklhlp3GJgAiIgAj4JiADRJIhAiIgAiKQJgFrgFSsWNHsepxzzjnp0nrjjTdMTAezYF1//fVnHPvDDz+YwPLnnnsO/fv3N78/8MADJlj9l19+Qf78+c84h8c++eST4LkMbFcTAREQARGIbwIyQOL7+Wn0IiACIhBRAtYAYRaqXr16+b3Wiy++iH79+oHFBrlr4t2eeuopDB48GNu3b0fp0qXNz4wBqV27Nl5//XXjuuXdWCm9S5cuWLFihdldURMBERABEYhvAjJA4vv5afQiIAIiEFEC1gBJL0bDPQB/BkjZsmVNvY85c+Z4Tvv333+NYVGlShV89tlnZ9wPixR269ZNBkhEn7Q6FwEREIHMIyADJPNY60oiIAIiEHcErAHy6aefom7dun7Hn54LFncwrrvuujT7yJ49O3bt2mUyZLmbXLD8YtcBIiACIhBXBGSAxNXj0mBFQAREIHMJBGuA2CB0GiJt27ZNNdiuXbti0qRJePvtt5EjR45Uvx04cACdO3cGd1AeffTRVL8xpoTFChWEnrnPXlcTAREQgUgRkAESKbLqVwREQAQSgECwBohNw0vjw11ckH8vXrx4mm5WRMXgdAa5r127NhW5yy67DOeff77S8CaAPOkWREAERIAEZIBIDkRABERABNIkEKwBwo5YiJAZs7Zu3erplzEkjRs3xujRo9MsKMjgde6ArFu3DpUrVzbnqhChhFMEREAEEo+ADJDEe6a6IxEQAREIG4GMGCCLFi3CzTffDLpjXX311WYs9957L2bNmmUMipIlS/ocn3Xf6tu3L4YOHWqOGTZsGJg5i8UPCxYsGLb7UkciIAIiIALRIyADJHrsdWUREAERSFgCNWvWRLly5Ux9j4y2U6dOGbcsVkhnGmA1ERABERCBxCAgAyQxnqPuQgREQARiigALEdapUwcbN240RkRGGoPVu3fvbmqGFC5cOCNd6BwREAEREIEYJCADJAYfioYkAiIgAiIgAiIgAiIgAolKQAZIoj5Z3ZcIiIAIiIAIiIAIiIAIxCABGe5FzNEAAAB5SURBVCAx+FA0JBEQAREQAREQAREQARFIVAIyQBL1yeq+REAEREAEREAEREAERCAGCcgAicGHoiGJgAiIgAiIgAiIgAiIQKISkAGSqE9W9yUCIiACIiACIiACIiACMUhABkgMPhQNSQREQAREQAREQAREQAQSlcD/Ay9H8HHg9o6bAAAAAElFTkSuQmCC\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('parascale', 0.11604224094470658)\n",
      "('ordscale', 0.008040296866293154)\n",
      "('xi', 8.263432400299152)\n"
     ]
    }
   ],
   "source": [
    "fit = combined_fit(dataFile, structureFile, rmin=0.5, rmax=20, method='toggle')\n",
    "\n",
    "# print out the refined parameter values\n",
    "# note we print out fit.fixednames and fit.fixedvalues because the toggling\n",
    "# routine ends up with all variabales fixed after completing the fit\n",
    "for item in zip(fit.names, fit.values):\n",
    "    print(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close('all')"
   ]
  }
 ],
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